diff --git a/.github/workflows/hsp2-pip-install-test.yml b/.github/workflows/hsp2-pip-install-test.yml index 16f7db1c..92eda6d9 100644 --- a/.github/workflows/hsp2-pip-install-test.yml +++ b/.github/workflows/hsp2-pip-install-test.yml @@ -1,87 +1,94 @@ +--- name: Python application -on: - push: - branches: [ "master" ] - pull_request: - branches: [ "master", "develop", "develop-specact" ] +on: # yamllint disable-line rule:truthy + push: + branches: [master] + pull_request: + branches: [master, develop, develop-specact] permissions: - contents: read + contents: read jobs: - lint: - runs-on: ubuntu-latest - steps: - - uses: actions/checkout@v4 - - name: Set up Python - uses: actions/setup-python@v4 - with: - python-version: "3.11" - cache: "pip" - - name: Install dependencies - run: | - pip install flake8 - - name: Lint with flake8 - run: | - # stop the build if there are Python syntax errors or undefined names - flake8 . --count --select=E9,F63,F7,F82 --ignore=F821 --show-source --statistics --exclude=build/* - # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide - flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics - - test-pytest: - runs-on: ubuntu-latest - continue-on-error: true - strategy: - matrix: - python-version: ["3.9", "3.10", "3.11", "3.12"] - pandas-version: [""] - include: - - python-version: "3.11" - pandas-version: "pandas>2.0" - coverage: true - - python-version: "3.11" - pandas-version: "pandas>1.5,<2.0" - steps: - - uses: actions/checkout@v4 - - name: Set up Python - uses: actions/setup-python@v4 - with: - python-version: ${{ matrix.python-version }} - cache: "pip" - - name: Install hsp2 - run: | - # install the hsp2 executable - pip install .[dev] - - if: ${{ matrix.pandas-version }} - run: pip install "${{ matrix.pandas-version }}" - - if: ${{ matrix.coverage }} - run: | - # python coverage - NUMBA_DISABLE_JIT=1 pytest --cov --cov-branch --cov-report term-missing - - if: ${{ ! matrix.coverage }} - run: pytest - - test-cmd: - runs-on: ubuntu-latest - continue-on-error: true - strategy: - matrix: - python-version: ["3.9", "3.10", "3.11", "3.12"] - steps: - - uses: actions/checkout@v4 - - name: Set up Python - uses: actions/setup-python@v4 - with: - python-version: ${{ matrix.python-version }} - cache: "pip" - - name: Install hsp2 - run: | - # install the hsp2 executable - pip install . - - name: Run hsp2 - run: | - # TODO: find much shorter test case. - hsp2 import_uci ./tests/test10/HSP2results/test10.uci _temp_test10.h5 - hsp2 run _temp_test10.h5 - + lint: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + - name: Set up Python + uses: actions/setup-python@v4 + with: + python-version: '3.11' + cache: pip + - name: Install dependencies + run: | + pip install flake8 + - name: Lint with flake8 + run: | + # stop the build if there are Python syntax errors or + # undefined names + flake8 . --count --select=E9,F63,F7,F82 --ignore=F821 \ + --show-source --statistics --exclude=build/* + # exit-zero treats all errors as warnings. + # The GitHub editor is 127 chars wide + flake8 . --count --exit-zero --max-complexity=10 \ + --max-line-length=127 --statistics + + test-pytest: + runs-on: ubuntu-latest + continue-on-error: true + strategy: + matrix: + python-version: ['3.9', '3.10', '3.11', '3.12'] + pandas-version: [''] + include: + - python-version: '3.11' + pandas-version: pandas>2.0 + coverage: true + - python-version: '3.11' + pandas-version: pandas>1.5,<2.0 + steps: + - uses: actions/checkout@v4 + - name: Set up Python + uses: actions/setup-python@v4 + with: + python-version: ${{ matrix.python-version }} + cache: pip + - name: Install hsp2 + run: | + # install the hsp2 executable + pip install .[dev] + - if: ${{ matrix.pandas-version }} + run: pip install "${{ matrix.pandas-version }}" + - if: ${{ matrix.coverage }} + run: | + # python coverage + NUMBA_DISABLE_JIT=1 pytest --cov --cov-branch --cov-report \ + term-missing + - if: ${{ ! matrix.coverage }} + run: pytest + + test-cmd: + runs-on: ubuntu-latest + continue-on-error: true + strategy: + matrix: + python-version: ['3.9', '3.10', '3.11', '3.12'] + steps: + - uses: actions/checkout@v4 + - name: Set up Python + uses: actions/setup-python@v4 + with: + python-version: ${{ matrix.python-version }} + cache: pip + - name: Install hsp2 + run: | + # install the hsp2 executable + pip install . + - name: Run hsp2 + run: | + # TODO: find much shorter test case. + hsp2 import_uci \ + ./tests/test10/HSP2results/test10.uci \ + _temp_test10.h5 + hsp2 run _temp_test10.h5 diff --git a/.gitignore b/.gitignore index 8cad0c9b..7a22225a 100644 --- a/.gitignore +++ b/.gitignore @@ -68,7 +68,7 @@ tests/GLWACSO/HSP2results/hspp007.uci tests/test_report_conversion.html # Omit big files -tests/**/*.h5 +tests/**/**/*.h5 tests/testcbp/HSP2results/*.csv # R files diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 00000000..bdc42a59 --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,96 @@ +--- +# See https://pre-commit.com for more information +# See https://pre-commit.com/hooks.html for more hooks + +exclude: | + (?x)^( + .*\.hbn| + .*\.wdm| + .*\.hdf5| + .*\.h5 + )$ + +repos: + - repo: https://github.com/pre-commit/pre-commit-hooks + rev: v4.6.0 + hooks: + - id: check-case-conflict + - id: check-docstring-first + - id: check-executables-have-shebangs + - id: check-json + - id: check-merge-conflict + - id: check-shebang-scripts-are-executable + - id: check-toml + - id: check-xml + - id: end-of-file-fixer + exclude: notebooks/tstoolbox_plot_bash.sh + - id: fix-encoding-pragma + args: [--remove] + - id: mixed-line-ending + - id: trailing-whitespace + exclude: notebooks/tstoolbox_plot_bash.sh + + - repo: https://github.com/astral-sh/ruff-pre-commit + # Ruff version. + rev: v0.5.5 + hooks: + # Run the linter. + # Uncomment the following lines to enable the linter. + # Right now way to many things fail. + # - id: ruff + # types_or: [python, pyi, jupyter] + # args: [--fix] + + # Run the linter sort imports. + - id: ruff + types_or: [python, pyi, jupyter] + args: [--select, I, --fix] + + # Run the formatter. + - id: ruff-format + types_or: [python, pyi, jupyter] + + - repo: https://github.com/pappasam/toml-sort + rev: v0.23.1 + hooks: + - id: toml-sort-fix + args: [--in-place, --spaces-indent-inline-array, '4'] + + - repo: https://github.com/adrienverge/yamllint.git + rev: v1.35.1 + hooks: + - id: yamllint + args: [--format, parsable, --strict] + + - repo: https://github.com/jumanjihouse/pre-commit-hook-yamlfmt + rev: 0.2.3 + hooks: + - id: yamlfmt + + - repo: https://github.com/jumanjihouse/pre-commit-hooks + rev: 3.0.0 + hooks: + - id: shellcheck + args: [-s, bash] + + - repo: https://github.com/lovesegfault/beautysh + rev: v6.2.1 + hooks: + - id: beautysh + args: [--indent-size, '4'] + + - repo: https://github.com/asottile/blacken-docs + rev: 1.18.0 + hooks: + - id: blacken-docs + + - repo: https://github.com/asottile/pyupgrade + rev: v3.16.0 + hooks: + - id: pyupgrade + + - repo: https://github.com/commitizen-tools/commitizen + rev: v3.28.0 + hooks: + - id: commitizen + stages: [commit-msg] diff --git a/HSP2_Driver.py b/HSP2_Driver.py index c91b8963..262699e8 100644 --- a/HSP2_Driver.py +++ b/HSP2_Driver.py @@ -1,4 +1,5 @@ -import os, sys +import os +import sys # print('in HSP2_Driver') command_line = "" @@ -6,25 +7,29 @@ if len(sys.argv) >= 2: # see if anything on command line command_line = sys.argv[1] - print('command line' + command_line) + print("command line" + command_line) # if given UCI, import to h5 file # if given WDM, import to h5 file # if given h5, run HSP2 -from PyQt5.QtWidgets import QFileDialog, QApplication +from PyQt5.QtWidgets import QApplication, QFileDialog application = QApplication(sys.argv) -if command_line == '': - file_filter = "Run HDF5 (*.h5) Full Output;;" \ - "Run HDF5 (*.h5) Light Output;;" \ - "Import UCI to HDF5 (*.uci);;" \ - "Import WDM to HDF5 (*.wdm)" - filename, filetype = QFileDialog.getOpenFileName(None, 'HSP2 Open File...', '', file_filter) +if command_line == "": + file_filter = ( + "Run HDF5 (*.h5) Full Output;;" + "Run HDF5 (*.h5) Light Output;;" + "Import UCI to HDF5 (*.uci);;" + "Import WDM to HDF5 (*.wdm)" + ) + filename, filetype = QFileDialog.getOpenFileName( + None, "HSP2 Open File...", "", file_filter + ) else: filename = command_line - filetype = '' + filetype = "" file_ext = filename[-3:] dir_name = os.path.dirname(filename) @@ -33,12 +38,14 @@ if file_ext.upper() == "UCI": h5_name = filename[:-3] + "h5" from hsp2.hsp2tools.readUCI import readUCI + readUCI(filename, h5_name) # readUCI('HSPF.uci', 'test.h5') if file_ext.upper() == "WDM": h5_name = filename[:-3] + "h5" from hsp2.hsp2tools.readWDM import readWDM + readWDM(filename, h5_name) # readWDM('GRICM.wdm', 'test.h5') # readWDM('ZUMBROSCEN.WDM', 'test.h5') @@ -52,11 +59,7 @@ io_manager = IOManager(hdf5_instance) SaveLevel = True - if 'Light' in filetype: + if "Light" in filetype: SaveLevel = False main(io_manager, saveall=SaveLevel, jupyterlab=False) # main('test.h5', saveall=True) - - - - diff --git a/README.rst b/README.rst index 179d43a9..e4003f95 100644 --- a/README.rst +++ b/README.rst @@ -44,7 +44,7 @@ Source Code Directories future automation and model coupling. - NOTE: With v0.10 the I/O abstraction classes provide an alternate approach to running HSP2. Our plan is to migrate solely using the I/O abstracted methods, but we will maintain both approaches - for for several more releases for backward compatibility. + for for several more releases for backward compatibility. - **docs** contains relevant reference documentation. @@ -65,13 +65,13 @@ We recommend getting started by: HSP2 Installation ================= -We **recommend Python 3.10**. +We **recommend Python 3.10**. Install From Pre-built Packages ------------------------------- Python Package Index (PyPI) +++++++++++++++++++++++++++ -Starting with version 0.11.0a1 we provide a PyPI wheel package for HSP2 which +Starting with version 0.11.0a1 we provide `a PyPI wheel package for HSP2`_ which should work on any supported platform for Python 3.10, 3.11, and 3.12. .. code-block:: console @@ -113,13 +113,17 @@ Option 1: Install using "conda" ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Follow these steps to install using the conda_ package manager. -1. Install the Anaconda Python Distribution +1. Install Miniconda or Anaconda Python Distribution ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ -Install the `latest release`_ of the Anaconda Distribution, which includes the -conda package manager, a complete Python (and R) data science stack, and the -Anaconda Navigator GUI. Follow `Anaconda Installation`_ documentation. +We recommend installing the light-weight Miniconda_ that includes Python, the +conda_ environment and package management system, and their dependencies. + +NOTE: Follow conda defaults to install in your local user directory. DO NOT +install for all users, to avoid substantial headaches with permissions. + +If you have already installed the Anaconda Distribution, you can use it to +complete the next steps, but you may need to update to the `latest release`_. -A lighter-weight alternative is to install Miniconda_. 2. Create a Conda Environment for HSP2 Modeling (optional) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ @@ -131,7 +135,7 @@ Use the following `conda create`_ command in your terminal or console: .. code-block:: console - conda create -c conda-forge -n hsp2_310 python=3.10 + conda create -c conda-forge -n hsp2_310 python=3.10 Install the necessary and optional packages for HSP2 in the new environment: @@ -147,13 +151,21 @@ Install the necessary and optional packages for HSP2 in the new environment: cd /path/to/module/hsp2 pip install . # or "pip install -e ." to install in editable mode +**Alternately**, you can replace all of the create and install steps above by +creating the new environment from the included `environment.yml` file +from this single line of code: + +.. code-block:: console + + conda env create --file=environment.yml --solver=libmamba + You should now be able to run the Tutorials and create your own Jupyter Notebooks! Option 2: Install From Source Code Using `pip` ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Installing HSP2 using `pip`, the `Package Installer for Python`_ -is an alternative method to installing with `conda`. +is an alternative method to installing with `conda`. 1. Install Python ^^^^^^^^^^^^^^^^^ @@ -170,7 +182,7 @@ activate a new environment for running HSP2. python -m venv hsp2_env /path/to/python/virtual/environments/hsp2_env -3. PIP install HSP2 +3. PIP install HSP2 ^^^^^^^^^^^^^^^^^^^ Navigate to your copy of the HSPsquared folder (for these instructions /path/to/module/hsp2) on your computer in the command @@ -221,8 +233,9 @@ The HSP2 API is designed to be used in Python scripts and Jupyter notebooks. .. _`HSPF Conversion Project`: https://github.com/respec/HSPsquared/blob/archivePy2/Why%20HSP2%20(EAA).pdf .. _`Introduction to HSP2 by Jason Love (RESPEC)`: https://www.youtube.com/watch?v=aeLScKsP1Wk .. _`initial release`: https://github.com/respec/HSPsquared/releases/tag/0.7.7 -.. _`GNU Affero General Public License (AGPL), copyrighted 2017 by RESPEC`: https://github.com/respec/HSPsquared/blob/master/LICENSE +.. _`GNU Affero General Public License (AGPL), copyrighted 2017 by RESPEC`: https://github.com/respec/HSPsquared/blob/master/LICENSE .. _JupyterLab: https://jupyterlab.readthedocs.io/en/stable/ +.. _`a PyPI wheel package for HSP2`: https://pypi.org/project/hsp2/ .. _conda: https://docs.conda.io/en/latest/ .. _`latest release`: https://docs.anaconda.com/anaconda/reference/release-notes/ .. _`Anaconda Installation`: https://docs.anaconda.com/anaconda/install/ diff --git a/_version.py b/_version.py deleted file mode 100644 index 2fb6788e..00000000 --- a/_version.py +++ /dev/null @@ -1,4 +0,0 @@ -import os - -with open(os.path.join(os.path.dirname(__file__), "VERSION"), encoding="ascii") as version_file: - __version__ = version_file.read().strip() diff --git a/compare_case.json b/compare_case.json index 5cd4e8c3..cb746076 100644 --- a/compare_case.json +++ b/compare_case.json @@ -17,4 +17,3 @@ } } } - diff --git a/environment.yml b/environment.yml index 807dd2c7..026de50e 100644 --- a/environment.yml +++ b/environment.yml @@ -1,45 +1,49 @@ -name: hsp2_py38 +--- +name: hsp2 channels: - conda-forge + - nodefaults # Speeds solving env, by limiting the number of options dependencies: - # Aligned with Anaconda 2021.05 (May 13, 2021) - # package management - - conda - - conda-build - - pip + - python >=3.10 # Running HSP2 - - python =3.8* - - scipy # Scipy also installs numpy - - pandas ==1.2.* # Pandas installs most scientific Python modules, such as Numpy, etc. - - numba ==0.53.1 - - numpy ==1.20.* # for compatibility with numba version <0.53 - - hdf5 ==1.10.6 # latest compatible with both versions of PyTables & h5py below - doesn't work with setup.py - - pytables ==3.6.1 - - h5py >=3.1 + - scipy # Scipy also installs numpy + # Pandas installs most scientific Python modules, such as Numpy, etc. + - pandas <3.0.0 + - numba + - numpy + - hdf5 + - pytables + - h5py - hdf5plugin # HDF5 compression filters for h5py & jupyterlab_hdf - - mando # for Python CLI app in HSP2tools/HSP2_CLI.py; hasn't been updated since 2017 and doesn't support Python 3.9: https://github.com/rubik/mando + - cltoolbox - # Interactivity & Visualization via Jupyter Notebooks (optional, but required for tutorials) - - jupyterlab ==3.0.* # also installs classic Jupyter notbook - - ipympl # jupyter-matplotlib, https://github.com/matplotlib/ipympl - - nodejs # required for many JupyterLab extensions - - nb_conda # Conda environment & package access extension from within Jupyter - # HoloViz, https://holoviz.org + # Operational Model (om) + - pyparsing + + # Interactivity via Jupyter Notebooks (optional, but required for tutorials) + - jupyterlab # also installs classic Jupyter notbook + - nodejs # required for many JupyterLab extensions + + # Visualization (optional) - hvplot # hvPlot installs most HoloViz libs, including matplotlib + - ipympl # jupyter-matplotlib, https://github.com/matplotlib/ipympl - ipywidgets # Required for HoloViz interactivity in Jupyter notebooks + - ipywidgets_bokeh + - jupyter_bokeh # Renders Holviz / Bokeh objects in Jupyter + - pyviz_comms # bidirectional communication between Python & JavaScript for Jupyter # Dev tools (optional) - - python-language-server - - jupyter-lsp-python # Includes both the server extension (jupyter-lsp) and pyls third-party server (python-language-server) - - jupyterlab-lsp # Docs at https://github.com/krassowski/jupyterlab-lsp - + # Language Server Protocol (LSP) extension for Python (pylsp) + - python-lsp-server + - jupyterlab-lsp # Provides both server extension and lab extension + # Environment and package management + - conda + - conda-libmamba-solver + - pip # PIP install requirements only if it is not possible with conda # https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#using-pip-in-an-environment - pip: - # Optional, but recommended for tutorials - # - lckr-jupyterlab-variableinspector # https://github.com/lckr/jupyterlab-variableInspector - # - jupyterlab_hdf # Explore HDF5 files in JupyterLab. Requires an additional step to install. - # Installation instructions: https://github.com/jupyterlab/jupyterlab-hdf5#installation + - hsp2 diff --git a/environment_dev.yml b/environment_dev.yml index 2bf310a7..78bfc5a9 100644 --- a/environment_dev.yml +++ b/environment_dev.yml @@ -1,40 +1,45 @@ +--- name: hsp2_py311_dev channels: - conda-forge - - nodefaults # Speeds solving env, by limiting the number of options + - nodefaults # Speeds solving env, by limiting the number of options dependencies: - # Python 3.11 is supported by Anaconda since 2023.03-0 (Mar 20, 2023) - # https://docs.anaconda.com/free/anaconda/release-notes/#anaconda-2023-03-0-mar-20-2023 - # package management - - conda - - conda-build - - conda-libmamba-solver - - pip + # Python 3.11 was default for Anaconda 2023.07-0 (Jul 11, 2023) + # https://docs.anaconda.com/anaconda/release-notes/#anaconda-2023-07-0-jul-11-2023 + - python =3.11 # Running HSP2 - - python =3.11 - - scipy # Scipy also installs numpy - - pandas >=2.0 # Pandas installs most scientific Python modules, such as Numpy, etc. - - numba - - numpy + - scipy # Scipy also installs numpy + # Pandas installs most scientific Python modules, such as Numpy, etc. + - pandas >=2.0 + - numba + - numpy - hdf5 - - pytables - - h5py + - pytables + - h5py - hdf5plugin # HDF5 compression filters for h5py & jupyterlab_hdf # - dask # for future performance enhancements - - mando # for Python CLI app in HSP2tools/HSP2_CLI.py; hasn't been updated since 2017 and doesn't support Python 3.9: https://github.com/rubik/mando + - cltoolbox - # Interactivity & Visualization via Jupyter Notebooks (optional, but required for tutorials) - - jupyterlab # also installs classic Jupyter notbook - - ipympl # jupyter-matplotlib, https://github.com/matplotlib/ipympl - - nodejs # required for many JupyterLab extensions - # HoloViz, https://holoviz.org + # Operational Model (om) + - pyparsing + + # Interactivity via Jupyter Notebooks (optional, but required for tutorials) + - jupyterlab # also installs classic Jupyter notbook + - nodejs # required for many JupyterLab extensions + + # Visualization (optional) - hvplot # hvPlot installs most HoloViz libs, including matplotlib + - ipympl # jupyter-matplotlib, https://github.com/matplotlib/ipympl - ipywidgets # Required for HoloViz interactivity in Jupyter notebooks + - ipywidgets_bokeh + - jupyter_bokeh # Renders Holviz / Bokeh objects in Jupyter + - pyviz_comms # bidirectional communication between Python & JavaScript for Jupyter # Dev tools (optional) - - python-lsp-server # Language Server Protocol (LSP) extension for Python (pylsp) + # Language Server Protocol (LSP) extension for Python (pylsp) + - python-lsp-server # Rope for Completions and renaming # Pyflakes linter to detect various errors # McCabe linter for complexity checking @@ -46,7 +51,12 @@ dependencies: # pylint for code linting (disabled by default) - jupyterlab-lsp # Provides both server extension and lab extension - + # Environment and package management + - conda + - conda-build + - conda-libmamba-solver + - pip # PIP install requirements only if it is not possible with conda # https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#using-pip-in-an-environment - - pip: \ No newline at end of file + - pip: + # For developing HPS2, we recommend using the `conda build` command to "install" diff --git a/examples/1_Intro_to_HSP2.ipynb b/examples/1_Intro_to_HSP2.ipynb index 0e15e45b..1c3ee74c 100644 --- a/examples/1_Intro_to_HSP2.ipynb +++ b/examples/1_Intro_to_HSP2.ipynb @@ -34,56 +34,168 @@ "source": [ "# Installation and Setup\n", "\n", - "## Install HSP2\n", - "\n", - "Carefully follow our **[Installation Instructions](https://github.com/respec/HSPsquared#installation)**, especially including:\n", - "- Creating a virtual environment for HSP2 (step 3)\n", - "- Adding HSPsquared to your Python path (step 4)" + "This notebook is designed to be run from: \n", + "- a cloned or copied version of the [HSPsquared](https://github.com/respec/HSPsquared) respository and \n", + "- a custom virtual environment as described in our **[HSP2 Installation](https://github.com/respec/HSPsquared#hsp2-installation) Instructions**, especially including:\n", + " - Creating a virtual environment for HSP2 (step 3)\n", + " - Adding HSP2 to your Python path (step 4)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Python Imports" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### General Imports" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "from pathlib import Path\n", + "\n", + "import tables" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Import HSP2" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'hsp2_py38'" + "'default311'" ] }, - "execution_count": 1, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Confirm that your active environment for this notebook is the one you created for HSP2.\n", - "import os\n", - "\n", "os.environ[\"CONDA_DEFAULT_ENV\"]" ] }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# Install HSP2, HSP2 Tools, and HSP2 IO Utillties\n", + "from hsp2 import hsp2, hsp2tools, hsp2io" + ] + }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Import Python Dependencies\n", - "- Most dependancies get installed when you import the `HSP2` and `HSP2tools` modules. " + "### If you get `ModuleNotFoundError`\n", + "\n", + "If you get `ModuleNotFoundError`, you need to install hsp2 into your environment, either using \n", + "- `pip` (see [HSP2 Installation](https://github.com/respec/HSPsquared#hsp2-installation) Instructions) for normal use, or using\n", + "- [`conda develop`](https://docs.conda.io/projects/conda-build/en/latest/resources/commands/conda-develop.html) if you want to develop HSP2.\n", + "\n", + "If using the development environment, the following steps will install in develop mode:\n", + "1. Run the [`conda develop`](https://docs.conda.io/projects/conda-build/en/latest/resources/commands/conda-develop.html) command in your terminal with your local absolute path to the `src` directory of this repo.\n", + "2. Restart the kernel.\n", + "3. Rerun the import statements above." ] }, { "cell_type": "code", - "execution_count": 2, - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T17:40:19.613424Z", - "iopub.status.busy": "2024-05-21T17:40:19.613169Z", - "iopub.status.idle": "2024-05-21T17:40:19.737150Z", - "shell.execute_reply": "2024-05-21T17:40:19.736693Z", - "shell.execute_reply.started": "2024-05-21T17:40:19.613404Z" + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "PosixPath('/var/home/timcera/programming/HSP_old/HSPsquared')" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" } - }, + ], + "source": [ + "# Find project directory (i.e. the parent to `/examples` directory for this notebook)\n", + "project_path = Path.cwd().parent\n", + "project_path" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "PosixPath('/var/home/timcera/programming/HSP_old/HSPsquared/src')" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Your source directory should be: \n", + "src_path = project_path / 'src' \n", + "src_path" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### To install in developer mode:\n", + "- Copy from the output of `src_path` from the cell above, and \n", + "- Paste it after `!conda develop` in the cell below (replacing the previous user's path). \n", + " - NOTE 1: If your path has any blank spaces, you must enclose the path with quotes.\n", + " - NOTE 2: The Jupyter `!` magic command runs a the follwoing terminal command from this notebook." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + " # !conda develop '/Users/aaufdenkampe/Documents/Python/respec.HSPsquared/src'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You now need to **restart the Python kernel** for this notebook, if the path didn't already exist." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, "outputs": [ { "data": { @@ -116,11 +228,11 @@ " \n", " \n", " Python\n", - " 3.10.14 | packaged by conda-forge | (main, Mar...\n", + " 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11....\n", " \n", " \n", - " HSP2\n", - " n/a\n", + " hsp2\n", + " 0.11.0a1\n", " \n", " \n", " numpy\n", @@ -128,15 +240,15 @@ " \n", " \n", " numba\n", - " 0.59.1\n", + " 0.64.0\n", " \n", " \n", " pandas\n", - " 1.5.3\n", + " 2.3.3\n", " \n", " \n", " matplotlib\n", - " 3.8.4\n", + " 3.10.8\n", " \n", " \n", " tables\n", @@ -144,19 +256,19 @@ " \n", " \n", " h5py\n", - " 3.11.0\n", + " 3.12.1\n", " \n", " \n", " os\n", - " Linux-5.15.0-91-generic-x86_64-with-glibc2.35\n", + " Linux-6.19.12-200.fc43.x86_64-x86_64-with-glib...\n", " \n", " \n", " processor\n", - " x86_64\n", + " \n", " \n", " \n", " Date/Time\n", - " 2024-05-21T13:40:19.728733\n", + " 2026-05-09T12:07:57.013563\n", " \n", " \n", "\n", @@ -165,77 +277,89 @@ "text/plain": [ " version\n", "name \n", - "Python 3.10.14 | packaged by conda-forge | (main, Mar...\n", - "HSP2 n/a\n", + "Python 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11....\n", + "hsp2 0.11.0a1\n", "numpy 1.26.4\n", - "numba 0.59.1\n", - "pandas 1.5.3\n", - "matplotlib 3.8.4\n", + "numba 0.64.0\n", + "pandas 2.3.3\n", + "matplotlib 3.10.8\n", "tables 3.9.2\n", - "h5py 3.11.0\n", - "os Linux-5.15.0-91-generic-x86_64-with-glibc2.35\n", - "processor x86_64\n", - "Date/Time 2024-05-21T13:40:19.728733" + "h5py 3.12.1\n", + "os Linux-6.19.12-200.fc43.x86_64-x86_64-with-glib...\n", + "processor \n", + "Date/Time 2026-05-09T12:07:57.013563" ] }, - "execution_count": 2, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "import os\n", - "from pathlib import Path\n", - "\n", - "import tables\n", - "\n", - "from hsp2 import hsp2, hsp2tools\n", - "from hsp2.hsp2io import hdf, io\n", - "\n", "# Confirm installed versions of HSP2 and key dependencies\n", - "hsp2.versions([\"matplotlib\", \"tables\", \"h5py\"])" + "hsp2.versions([\"matplotlib\", \"tables\", \"h5py\"])\n", + "# TODO: need to fix hsp2 version links" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### If you get HSP2 `ModuleNotFoundError`:\n", - "\n", - "If you get this error:\n", - "```python\n", - "ModuleNotFoundError: No module named 'HSP2'\n", - "```\n", - "Then:\n", - "1. Run the following terminal command with your local absolute path to this repo.\n", - " - NOTE: Here we use Jupyter `!` magic command to run from the terminal via this notebook. \n", - "2. Restart the kernel.\n", - "3. Rerun the import statements above." + "Alternate ways to get the HSP2 version:" ] }, { "cell_type": "code", - "execution_count": 3, - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T17:40:25.655357Z", - "iopub.status.busy": "2024-05-21T17:40:25.654849Z", - "iopub.status.idle": "2024-05-21T17:40:25.768746Z", - "shell.execute_reply": "2024-05-21T17:40:25.768142Z", - "shell.execute_reply.started": "2024-05-21T17:40:25.655339Z" + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "# Built in approach, that will work with next release\n", + "# hsp2.__version__" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'0.11.0a1'" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" } - }, + ], + "source": [ + "# From PyPI Package\n", + "# NOTE: this won't work when in `conda develop` mode.\n", + "from importlib.metadata import version\n", + "version('hsp2')" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "/bin/bash: line 1: conda-develop: command not found\n" + "# packages in environment at /var/home/timcera/miniconda3/envs/default311:\n", + "#\n", + "# Name Version Build Channel\n", + "hsp2 0.11.0a1 pypi_0 pypi\n" ] } ], "source": [ - "!conda-develop /Users/aaufdenkampe/Documents/Python/respec.HSPsquared/" + "# From conda magic command\n", + "!conda list hsp2" ] }, { @@ -249,50 +373,23 @@ }, { "cell_type": "code", - "execution_count": 4, - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T17:40:35.309422Z", - "iopub.status.busy": "2024-05-21T17:40:35.309181Z", - "iopub.status.idle": "2024-05-21T17:40:35.312823Z", - "shell.execute_reply": "2024-05-21T17:40:35.312344Z", - "shell.execute_reply.started": "2024-05-21T17:40:35.309405Z" - } - }, + "execution_count": 11, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "PosixPath('/home/tim/programming/HSPsquared/examples')" + "PosixPath('/var/home/timcera/programming/HSP_old/HSPsquared')" ] }, - "execution_count": 4, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "# Get your current working directory, for reference\n", - "Path.cwd()" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T17:40:36.407261Z", - "iopub.status.busy": "2024-05-21T17:40:36.406989Z", - "iopub.status.idle": "2024-05-21T17:40:36.409351Z", - "shell.execute_reply": "2024-05-21T17:40:36.408997Z", - "shell.execute_reply.started": "2024-05-21T17:40:36.407244Z" - } - }, - "outputs": [], - "source": [ - "# Set your project directory to your local folder for your clone of the HSPsquared repository\n", - "\n", - "project_folder = Path(\"/Users/aaufdenkampe/Documents/Python/respec.HSPsquared/\")" + "# Project directory, found above, is local folder for your clone or copy of the HSPsquared repository\n", + "project_path" ] }, { @@ -308,32 +405,25 @@ }, { "cell_type": "code", - "execution_count": 13, - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T18:52:11.477985Z", - "iopub.status.busy": "2024-05-21T18:52:11.477555Z", - "iopub.status.idle": "2024-05-21T18:52:11.481211Z", - "shell.execute_reply": "2024-05-21T18:52:11.480827Z", - "shell.execute_reply.started": "2024-05-21T18:52:11.477968Z" - } - }, + "execution_count": 12, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "../tests/test10/HSP2results/test10.uci\n", + "/var/home/timcera/programming/HSP_old/HSPsquared/tests/test10/HSP2results/test10.uci\n", "File exists? True\n", - "../tests/test10/HSP2results/test10.wdm\n", + "/var/home/timcera/programming/HSP_old/HSPsquared/tests/test10/HSP2results/test10.wdm\n", "File exists? True\n" ] } ], "source": [ - "# Set input data paths, using our Test10 example\n", + "# Get input data paths for the Test10 example\n", + "# Using `pathlib` concatenation\n", + "inputs_path = project_path / 'tests' / 'test10' / 'HSP2results' \n", "\n", - "input_data_folder = Path(\"../tests/test10/HSP2results/\")\n", "\n", "input_files = [\n", " \"test10.uci\",\n", @@ -341,16 +431,16 @@ "]\n", "\n", "# HSPF User Control Inputs text file\n", - "input_uci_path = input_data_folder / input_files[0]\n", + "input_uci_filepath = inputs_path / input_files[0]\n", "\n", - "print(input_uci_path)\n", - "print(f\"File exists? {input_uci_path.exists()}\")\n", + "print(input_uci_filepath)\n", + "print(f\"File exists? {input_uci_filepath.exists()}\")\n", "\n", "# HSPF Watershed Data Management Fortran binary file for timeseries inputs\n", - "input_wdm_path = input_data_folder / input_files[1]\n", + "input_wdm_filepath = inputs_path / input_files[1]\n", "\n", - "print(input_wdm_path)\n", - "print(f\"File exists? {input_wdm_path.exists()}\")" + "print(input_wdm_filepath)\n", + "print(f\"File exists? {input_wdm_filepath.exists()}\")" ] }, { @@ -362,100 +452,46 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T17:40:42.208083Z", - "iopub.status.busy": "2024-05-21T17:40:42.207839Z", - "iopub.status.idle": "2024-05-21T17:40:42.437978Z", - "shell.execute_reply": "2024-05-21T17:40:42.437379Z", - "shell.execute_reply.started": "2024-05-21T17:40:42.208070Z" - } - }, + "execution_count": 13, + "metadata": {}, "outputs": [ { - "ename": "PermissionError", - "evalue": "[Errno 13] Permission denied: '/Users'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", - "File \u001b[0;32m~/anaconda3/envs/hsp2_310/lib/python3.10/pathlib.py:1175\u001b[0m, in \u001b[0;36mPath.mkdir\u001b[0;34m(self, mode, parents, exist_ok)\u001b[0m\n\u001b[1;32m 1174\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1175\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_accessor\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmkdir\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1176\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m:\n", - "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '/Users/aaufdenkampe/Documents/Python/respec.HSPsquared/examples/_TutorialData'", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", - "File \u001b[0;32m~/anaconda3/envs/hsp2_310/lib/python3.10/pathlib.py:1175\u001b[0m, in \u001b[0;36mPath.mkdir\u001b[0;34m(self, mode, parents, exist_ok)\u001b[0m\n\u001b[1;32m 1174\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1175\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_accessor\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmkdir\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1176\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m:\n", - "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '/Users/aaufdenkampe/Documents/Python/respec.HSPsquared/examples'", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", - "File \u001b[0;32m~/anaconda3/envs/hsp2_310/lib/python3.10/pathlib.py:1175\u001b[0m, in \u001b[0;36mPath.mkdir\u001b[0;34m(self, mode, parents, exist_ok)\u001b[0m\n\u001b[1;32m 1174\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1175\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_accessor\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmkdir\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1176\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m:\n", - "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '/Users/aaufdenkampe/Documents/Python/respec.HSPsquared'", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", - "File \u001b[0;32m~/anaconda3/envs/hsp2_310/lib/python3.10/pathlib.py:1175\u001b[0m, in \u001b[0;36mPath.mkdir\u001b[0;34m(self, mode, parents, exist_ok)\u001b[0m\n\u001b[1;32m 1174\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1175\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_accessor\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmkdir\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1176\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m:\n", - "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '/Users/aaufdenkampe/Documents/Python'", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", - "File \u001b[0;32m~/anaconda3/envs/hsp2_310/lib/python3.10/pathlib.py:1175\u001b[0m, in \u001b[0;36mPath.mkdir\u001b[0;34m(self, mode, parents, exist_ok)\u001b[0m\n\u001b[1;32m 1174\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1175\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_accessor\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmkdir\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1176\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m:\n", - "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '/Users/aaufdenkampe/Documents'", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", - "File \u001b[0;32m~/anaconda3/envs/hsp2_310/lib/python3.10/pathlib.py:1175\u001b[0m, in \u001b[0;36mPath.mkdir\u001b[0;34m(self, mode, parents, exist_ok)\u001b[0m\n\u001b[1;32m 1174\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1175\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_accessor\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmkdir\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1176\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m:\n", - "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '/Users/aaufdenkampe'", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[0;31mPermissionError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[7], line 7\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[38;5;66;03m# Create temporary directory, which we ignore in Git\u001b[39;00m\n\u001b[1;32m 6\u001b[0m tutoral_temp_path \u001b[38;5;241m=\u001b[39m project_folder \u001b[38;5;241m/\u001b[39m output_data_folder\n\u001b[0;32m----> 7\u001b[0m \u001b[43mtutoral_temp_path\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmkdir\u001b[49m\u001b[43m(\u001b[49m\u001b[43mparents\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mexist_ok\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m 9\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mFolder exists? \u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mstr\u001b[39m(tutoral_temp_path\u001b[38;5;241m.\u001b[39mexists()) )\n", - "File \u001b[0;32m~/anaconda3/envs/hsp2_310/lib/python3.10/pathlib.py:1179\u001b[0m, in \u001b[0;36mPath.mkdir\u001b[0;34m(self, mode, parents, exist_ok)\u001b[0m\n\u001b[1;32m 1177\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m parents \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mparent \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mself\u001b[39m:\n\u001b[1;32m 1178\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m\n\u001b[0;32m-> 1179\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparent\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmkdir\u001b[49m\u001b[43m(\u001b[49m\u001b[43mparents\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mexist_ok\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m 1180\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmkdir(mode, parents\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m, exist_ok\u001b[38;5;241m=\u001b[39mexist_ok)\n\u001b[1;32m 1181\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mOSError\u001b[39;00m:\n\u001b[1;32m 1182\u001b[0m \u001b[38;5;66;03m# Cannot rely on checking for EEXIST, since the operating system\u001b[39;00m\n\u001b[1;32m 1183\u001b[0m \u001b[38;5;66;03m# could give priority to other errors like EACCES or EROFS\u001b[39;00m\n", - "File \u001b[0;32m~/anaconda3/envs/hsp2_310/lib/python3.10/pathlib.py:1179\u001b[0m, in \u001b[0;36mPath.mkdir\u001b[0;34m(self, mode, parents, exist_ok)\u001b[0m\n\u001b[1;32m 1177\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m parents \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mparent \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mself\u001b[39m:\n\u001b[1;32m 1178\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m\n\u001b[0;32m-> 1179\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparent\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmkdir\u001b[49m\u001b[43m(\u001b[49m\u001b[43mparents\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mexist_ok\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m 1180\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmkdir(mode, parents\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m, exist_ok\u001b[38;5;241m=\u001b[39mexist_ok)\n\u001b[1;32m 1181\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mOSError\u001b[39;00m:\n\u001b[1;32m 1182\u001b[0m \u001b[38;5;66;03m# Cannot rely on checking for EEXIST, since the operating system\u001b[39;00m\n\u001b[1;32m 1183\u001b[0m \u001b[38;5;66;03m# could give priority to other errors like EACCES or EROFS\u001b[39;00m\n", - " \u001b[0;31m[... skipping similar frames: Path.mkdir at line 1179 (3 times)]\u001b[0m\n", - "File \u001b[0;32m~/anaconda3/envs/hsp2_310/lib/python3.10/pathlib.py:1179\u001b[0m, in \u001b[0;36mPath.mkdir\u001b[0;34m(self, mode, parents, exist_ok)\u001b[0m\n\u001b[1;32m 1177\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m parents \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mparent \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mself\u001b[39m:\n\u001b[1;32m 1178\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m\n\u001b[0;32m-> 1179\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparent\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmkdir\u001b[49m\u001b[43m(\u001b[49m\u001b[43mparents\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mexist_ok\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m 1180\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmkdir(mode, parents\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m, exist_ok\u001b[38;5;241m=\u001b[39mexist_ok)\n\u001b[1;32m 1181\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mOSError\u001b[39;00m:\n\u001b[1;32m 1182\u001b[0m \u001b[38;5;66;03m# Cannot rely on checking for EEXIST, since the operating system\u001b[39;00m\n\u001b[1;32m 1183\u001b[0m \u001b[38;5;66;03m# could give priority to other errors like EACCES or EROFS\u001b[39;00m\n", - "File \u001b[0;32m~/anaconda3/envs/hsp2_310/lib/python3.10/pathlib.py:1175\u001b[0m, in \u001b[0;36mPath.mkdir\u001b[0;34m(self, mode, parents, exist_ok)\u001b[0m\n\u001b[1;32m 1171\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 1172\u001b[0m \u001b[38;5;124;03mCreate a new directory at this given path.\u001b[39;00m\n\u001b[1;32m 1173\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 1174\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1175\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_accessor\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmkdir\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1176\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m:\n\u001b[1;32m 1177\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m parents \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mparent \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mself\u001b[39m:\n", - "\u001b[0;31mPermissionError\u001b[0m: [Errno 13] Permission denied: '/Users'" + "name": "stdout", + "output_type": "stream", + "text": [ + "Folder exists? True\n" ] } ], "source": [ "# Create temporary data output folder, where you want to store your outputs\n", - "\n", - "output_data_folder = Path(\"examples/_TutorialData\")\n", + "tutoral_temp_path = project_path / 'examples' / '_TutorialData'\n", "\n", "# Create temporary directory, which we ignore in Git\n", - "tutoral_temp_path = project_folder / output_data_folder\n", "tutoral_temp_path.mkdir(parents=True, exist_ok=True)\n", "\n", - "print(\"Folder exists? \" + str(tutoral_temp_path.exists()))" + "print('Folder exists? ', tutoral_temp_path.exists())" ] }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T17:40:43.187481Z", - "iopub.status.busy": "2024-05-21T17:40:43.187028Z", - "iopub.status.idle": "2024-05-21T17:40:43.190486Z", - "shell.execute_reply": "2024-05-21T17:40:43.190114Z", - "shell.execute_reply.started": "2024-05-21T17:40:43.187460Z" - } - }, + "execution_count": 14, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "/Users/aaufdenkampe/Documents/Python/respec.HSPsquared/examples/_TutorialData/test10.h5\n", - "File exists? False\n" + "/var/home/timcera/programming/HSP_old/HSPsquared/examples/_TutorialData/test10.h5\n", + "File exists? True\n" ] } ], "source": [ "# Create path for temporary data output file\n", - "\n", "output_file = \"test10.h5\" # HSP2 data HDF5 binary file, for all inputs and outputs\n", "\n", - "output_hdf5_path = (\n", - " project_folder / output_data_folder / output_file\n", - ") # pathlib concatenation\n", + "output_hdf5_path = tutoral_temp_path / output_file\n", "\n", "print(output_hdf5_path)\n", "print(\"File exists? \" + str(output_hdf5_path.exists()))\n", @@ -490,15 +526,65 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 15, "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + ":5: DeprecationWarning: Call to deprecated function readUCI (\n", + "\n", + "readUCI is deprecated and will be removed in a future release.\n", + "Use hsp2.hsp2io.control_file_readers.read_uci_parameters to read the parameters.\n", + "\n", + ").\n", + "/var/home/timcera/programming/HSP_old/HSPsquared/src/hsp2/hsp2io/control_file_readers/utils.py:181: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " nparms = nparms.fillna(\n", + "/var/home/timcera/programming/HSP_old/HSPsquared/src/hsp2/hsp2io/control_file_readers/utils.py:181: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " nparms = nparms.fillna(\n", + "/var/home/timcera/programming/HSP_old/HSPsquared/src/hsp2/hsp2io/control_file_readers/utils.py:181: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " nparms = nparms.fillna(\n", + "/var/home/timcera/programming/HSP_old/HSPsquared/src/hsp2/hsp2io/control_file_readers/utils.py:181: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " nparms = nparms.fillna(\n", + "/var/home/timcera/programming/HSP_old/HSPsquared/src/hsp2/hsp2io/control_file_readers/utils.py:181: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " nparms = nparms.fillna(\n", + "/var/home/timcera/programming/HSP_old/HSPsquared/src/hsp2/hsp2io/control_file_readers/utils.py:181: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " nparms = nparms.fillna(\n", + "/var/home/timcera/programming/HSP_old/HSPsquared/src/hsp2/hsp2io/control_file_readers/utils.py:181: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " nparms = nparms.fillna(\n", + "/var/home/timcera/programming/HSP_old/HSPsquared/src/hsp2/hsp2io/control_file_readers/utils.py:181: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " nparms = nparms.fillna(\n", + "/var/home/timcera/programming/HSP_old/HSPsquared/src/hsp2/hsp2io/control_file_readers/utils.py:181: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " nparms = nparms.fillna(\n", + "/var/home/timcera/programming/HSP_old/HSPsquared/src/hsp2/hsp2io/control_file_readers/utils.py:181: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " nparms = nparms.fillna(\n", + "/var/home/timcera/programming/HSP_old/HSPsquared/src/hsp2/hsp2io/control_file_readers/utils.py:181: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " nparms = nparms.fillna(\n", + "/var/home/timcera/programming/HSP_old/HSPsquared/src/hsp2/hsp2io/control_file_readers/utils.py:181: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " nparms = nparms.fillna(\n", + "/var/home/timcera/programming/HSP_old/HSPsquared/src/hsp2/hsp2io/control_file_readers/utils.py:181: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " nparms = nparms.fillna(\n", + "/var/home/timcera/programming/HSP_old/HSPsquared/src/hsp2/hsp2io/control_file_readers/utils.py:181: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " nparms = nparms.fillna(\n", + "/var/home/timcera/programming/HSP_old/HSPsquared/src/hsp2/hsp2io/control_file_readers/utils.py:181: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " nparms = nparms.fillna(\n", + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'CURV-DATA1'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though\n", + " check_attribute_name(name)\n", + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'CURV-DATA2'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though\n", + " check_attribute_name(name)\n", + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'CURV-DATA3'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though\n", + " check_attribute_name(name)\n", + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'CURV-DATA4'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though\n", + " check_attribute_name(name)\n" + ] + }, { "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 18.2 s, sys: 621 ms, total: 18.8 s\n", - "Wall time: 18.9 s\n" + "CPU times: user 5.92 s, sys: 125 ms, total: 6.05 s\n", + "Wall time: 6.08 s\n" ] } ], @@ -508,13 +594,13 @@ "# from the HSPF *.uci text file in Fortran punchard format\n", "# to the HDF5 file\n", "\n", - "HSP2tools.readUCI(input_uci_path, output_hdf5_path)\n", - "# NOTE that parsing this text file is not very efficient!" + "hsp2tools.readUCI(input_uci_filepath, output_hdf5_path)\n", + "# NOTE that parsing this text file is not very efficient, takign 8-20 seconds" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 16, "metadata": {}, "outputs": [ { @@ -532,9 +618,23 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 17, "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + ":5: DeprecationWarning: Call to deprecated function readWDM (\n", + "\n", + "readWDM is deprecated and will be removed in a future release.\n", + "Use hsp2.hsp2io.time_series_readers.read_wdm_ts.read_wdm_ts to read the time\n", + "series data from the WDM file, and then write the data to an HDF file using\n", + "pandas.\n", + "\n", + ").\n" + ] + }, { "name": "stdout", "output_type": "stream", @@ -558,302 +658,9 @@ "135 reading from wdm\n", "136 reading from wdm\n", "140 reading from wdm\n", - "CPU times: user 2.88 s, sys: 70.1 ms, total: 2.95 s\n", - "Wall time: 3.05 s\n" + "CPU times: user 1.73 s, sys: 160 ms, total: 1.89 s\n", + "Wall time: 1.91 s\n" ] - }, - { - "data": { - "text/html": [ - "
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StartStopFreqLengthTSTYPETFILLSTAIDSTNAM
TS0391976-01-01 00:00:001977-01-01 00:00:001H8784PREC-999.0HOURLY PRECPRECIP TRAER IOWA
TS0411976-01-01 00:00:001977-01-01 00:00:001D366EVAP-999.0DAILY EVAPFARMERS COOP WEATHER STN
TS0421976-01-01 00:00:001977-01-01 00:00:001D366WIND-999.0DAILY WINDFARMERS COOP WEATHER STN
TS0461976-01-01 00:00:001977-01-01 00:00:002H4392SOLR-999.02 HOUR RADFARMERS WEATHER STN
TS1131976-01-01 00:00:001977-01-01 00:00:001D366FLOW-999.0DAILY FLOWIOWA RIVER MARSHALLTOWN
TS1191976-01-01 00:00:001977-01-01 00:00:001D366FLOW-999.0DAILY FLOWIOWA RIVER MARENGO
TS1211976-01-01 00:00:001977-01-01 00:00:002H4392ATMP-999.02 HOUR AIR TEMPCEDAR RAPIDS IOWA
TS1221976-01-01 00:00:001977-01-01 00:00:002H4392ATMP-999.02 HOUR AIR TEMPIOWA FALLS IOWA
TS1231976-01-01 00:00:001977-01-01 00:00:002H4392ATMP-999.02 HOUR AIR TEMPMARSHALLTOWN IOWA
TS1241976-01-01 00:00:001977-01-01 00:00:001D366DEWP-999.0DAILY DEW PTCEDAR RAPIDS IOWA
TS1251976-01-01 00:00:001977-01-01 00:00:001D366DEWP-999.0DAILY DEW PTIOWA FALLS IOWA
TS1261976-01-01 00:00:001977-01-01 00:00:001D366DEWP-999.0DAILY DEW PTMARSHALLTOWN IOWA
TS1271976-01-01 00:00:001977-01-01 00:00:001D366SEDM-999.0SEDIMENT CONCIOWA RIVER MARENGO
TS1311976-01-01 00:00:001977-01-01 00:00:001H8784PREC-999.0HOURLY PRECPRECIP IOWA FALLS
TS1321976-01-01 00:00:001977-01-01 00:00:001H8784PREC-999.0HOURLY PRECPRECIP SHEFFIELD
TS1341976-01-01 00:00:001977-01-01 00:00:001D366WTMP-999.0WATER TEMPIOWA RIVER (ESTIMATED)
TS1351976-01-01 00:00:001977-01-01 00:00:001D366CLDC-999.0CLOUD COVERWATERLOO (TENTHS)
TS1361976-01-01 00:00:001977-01-01 00:00:001D366FLOW-999.0DAILY FLOWIOWA RIVER ROWAN
TS1401976-01-01 00:00:001977-01-01 00:00:001D366CLND-999.0COLINDCOLUMN INDICATOR MEIER POND SUMMER-WINTER OUTLET
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The second time will use the precompiled code, executing \n", + "# 80 times faster! Try it!" ] }, { @@ -887,16 +698,16 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 12, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } @@ -904,23 +715,22 @@ "source": [ "## Create instance of HSPFIO.HDF5 class, from the file created by reading HSPF inputs\n", "\n", - "hdf5_instance = HSP2IO.hdf.HDF5(output_hdf5_path)\n", - "\n", + "hdf5_instance = hsp2io.hdf.HDF5(output_hdf5_path)\n", "hdf5_instance" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "['/Users/aaufdenkampe/Documents/Python/respec.HSPsquared/examples/_TutorialData/test10.h5']" + "['/var/home/timcera/programming/HSP_old/HSPsquared/examples/_TutorialData/test10.h5']" ] }, - "execution_count": 13, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -935,16 +745,16 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 14, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -952,49 +762,54 @@ "source": [ "## Create an instance of the IOManager: Management class for IO operations needed to execute the HSP2 model\n", "\n", - "io_manager = HSP2IO.io.IOManager(hdf5_instance)\n", + "io_manager = hsp2io.io.IOManager(hdf5_instance)\n", "\n", "io_manager" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 21, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[0;31mType:\u001b[0m IOManager\n", - "\u001b[0;31mString form:\u001b[0m \n", - "\u001b[0;31mFile:\u001b[0m ~/Documents/Python/respec.HSPsquared/HSP2IO/io.py\n", - "\u001b[0;31mDocstring:\u001b[0m Management class for IO operations needed to execute the HSP2 model\n", - "\u001b[0;31mInit docstring:\u001b[0m\n", - "io_combined: SupportsReadUCI & SupportsReadTS & SupportsWriteTS & SupportsWriteLogging / None \n", - " Intended to allow users with a object that combines protocols for \n", - " UCI, Input, Output and Log a shortcut where only a \n", - " single argument needs to be provided. If UCI, Input, Output and/or \n", - " Log are not specified this argument will be used as the default. \n", - "uci: SupportsReadUCI/None (Default None)\n", - " A class instance implementing the SupportReadUCI protocol. \n", - " This class acts as the data source for UCI information. \n", - " The argument io_combined be used in place by default if this argument is not specified.\n", - "input: SupportsReadUCI/None (Default None)\n", - " A class instance implementing SupportReadTS protocol. \n", - " This class acts as the data source for any input timeseries. \n", - " The argument io_combined be used in place by default if this argument is not specified.\n", - "output: SupportsWriteTS & SupportsReadTS / None (Default None)\n", - " A class implementing SupportsWriteTS & SupportReadTS protocol\n", - " This class acts as the location for outputing result timeseries as \n", - " well as the data source should those result timeseries be needed for \n", - " inputs into a model modules. \n", - " The argument io_combined be used in place by default if this argument is not specified.\n", - "log: SupportsWriteLogging/None (Default None)\n", - " A class implementing SupportWriteLogging protocol. This class\n", - " This class acts as the location to output logging information.\n", - " The argument io_combined be used in place by default if this argument is not specified.\n" - ] + "data": { + "text/plain": [ + "\u001b[0;31mType:\u001b[0m IOManager\n", + "\u001b[0;31mString form:\u001b[0m \n", + "\u001b[0;31mFile:\u001b[0m ~/programming/HSP_old/HSPsquared/src/hsp2/hsp2io/io.py\n", + "\u001b[0;31mDocstring:\u001b[0m Management class for IO operations needed to execute the HSP2 model\n", + "\u001b[0;31mInit docstring:\u001b[0m\n", + "Initialize the IOManager for HSP2 model IO operations.\n", + "\n", + "Parameters\n", + "----------\n", + "io_combined : SupportsReadParameters or SupportsReadTS or SupportsWriteTS or None, optional\n", + " Object that combines protocols for Parameters, Input, Output, and\n", + " Log. If `parameters`, `input`, `output`, or `log` are not\n", + " specified, this argument will be used as the default for those.\n", + "parameters : SupportsReadParameters or None, optional\n", + " Instance implementing the SupportReadParameters protocol. Acts as\n", + " the data source for parameter information. If not specified,\n", + " `io_combined` will be used by default.\n", + "input : SupportsReadTS or None, optional\n", + " Instance implementing the SupportReadTS protocol. Acts as the data\n", + " source for any input timeseries. If not specified, `io_combined`\n", + " will be used by default.\n", + "output : SupportsWriteTS or SupportsReadTS or None, optional\n", + " Instance implementing the SupportsWriteTS and/or SupportReadTS\n", + " protocol. Acts as the location for outputting result timeseries and\n", + " as the data source for result timeseries needed as inputs to model\n", + " modules.\n", + " If not specified, `io_combined` will be used by default.\n", + "log : SupportsWriteLogging or None, optional\n", + " Instance implementing the SupportWriteLogging protocol. Acts as the\n", + " location to output logging information. If not specified,\n", + " `io_combined` will be used by default." + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ @@ -1020,100 +835,108 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 22, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "2022-06-23 10:03:45.64 Processing started for file ./; saveall=False\n", - "2022-06-23 10:03:51.39 Simulation Start: 1976-01-01 00:00:00, Stop: 1977-01-01 00:00:00\n", - "2022-06-23 10:03:51.39 PERLND P001 DELT(minutes): 60\n", - "2022-06-23 10:03:53.14 SNOW\n", - "2022-06-23 10:03:54.27 PWATER\n", - "2022-06-23 10:03:54.84 PSTEMP\n", - "2022-06-23 10:03:54.85 PWTGAS\n", - "2022-06-23 10:03:54.88 RCHRES R001 DELT(minutes): 60\n", - "2022-06-23 10:03:54.91 HYDR\n", - "2022-06-23 10:03:55.17 ADCALC\n", - "2022-06-23 10:03:55.20 CONS\n", - "2022-06-23 10:03:55.53 HTRCH\n", - "2022-06-23 10:03:55.56 SEDTRN\n", - "2022-06-23 10:03:55.62 RQUAL\n", - "2022-06-23 10:03:56.53 GQUAL\n", - "2022-06-23 10:03:57.72 GENER G001 DELT(minutes): 60\n", - "GENER 'G001' encountered unsupported feature during initialization and may not function correctly. Unsupported feature: 'Invalid SVOL. GENER module does not currently support reading TimeSeries for 'RCHRES''\n", - "2022-06-23 10:03:57.72 RCHRES R002 DELT(minutes): 60\n", - "2022-06-23 10:03:57.75 HYDR\n", - "2022-06-23 10:03:57.82 ADCALC\n", - "2022-06-23 10:03:57.83 CONS\n", - "2022-06-23 10:03:57.84 HTRCH\n", - "2022-06-23 10:03:57.84 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2022-06-23 10:03:57.85 SEDTRN\n", - "2022-06-23 10:03:57.86 Error count 3598: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", - "2022-06-23 10:03:57.88 RQUAL\n", - "2022-06-23 10:03:58.24 GQUAL\n", - "2022-06-23 10:03:58.98 RCHRES R003 DELT(minutes): 60\n", - "2022-06-23 10:03:59.01 HYDR\n", - "2022-06-23 10:03:59.04 ADCALC\n", - "2022-06-23 10:03:59.05 CONS\n", - "2022-06-23 10:03:59.06 HTRCH\n", - "2022-06-23 10:03:59.06 Error count 3: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2022-06-23 10:03:59.07 SEDTRN\n", - "2022-06-23 10:03:59.08 Error count 513: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", - "2022-06-23 10:03:59.10 RQUAL\n", - "2022-06-23 10:03:59.43 GQUAL\n", - "2022-06-23 10:04:00.02 RCHRES R004 DELT(minutes): 60\n", - "2022-06-23 10:04:00.09 HYDR\n", - "2022-06-23 10:04:00.16 ADCALC\n", - "2022-06-23 10:04:00.17 CONS\n", - "2022-06-23 10:04:00.18 HTRCH\n", - "2022-06-23 10:04:00.18 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2022-06-23 10:04:00.19 SEDTRN\n", - "2022-06-23 10:04:00.21 Error count 6720: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", - "2022-06-23 10:04:00.22 RQUAL\n", - "2022-06-23 10:04:00.59 GQUAL\n", - "2022-06-23 10:04:01.38 IMPLND I001 DELT(minutes): 60\n", - "2022-06-23 10:04:01.39 SNOW\n", - "2022-06-23 10:04:01.50 IWATER\n", - "2022-06-23 10:04:01.56 SOLIDS\n", - "2022-06-23 10:04:01.57 IWTGAS\n", - "2022-06-23 10:04:01.59 IQUAL\n", - "2022-06-23 10:04:01.61 RCHRES R005 DELT(minutes): 60\n", - "2022-06-23 10:04:01.64 HYDR\n", - "2022-06-23 10:04:01.68 ADCALC\n", - "2022-06-23 10:04:01.69 CONS\n", - "2022-06-23 10:04:01.70 HTRCH\n", - "2022-06-23 10:04:01.70 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2022-06-23 10:04:01.71 SEDTRN\n", - "2022-06-23 10:04:01.73 RQUAL\n", - "2022-06-23 10:04:02.10 GQUAL\n", - "2022-06-23 10:04:02.94 GENER G002 DELT(minutes): 60\n", - "GENER 'G002' encountered unsupported feature during initialization and may not function correctly. Unsupported feature: 'Invalid SVOL. GENER module does not currently support reading TimeSeries for 'RCHRES''\n", - "2022-06-23 10:04:02.94 Done; Run time is about 00:17.2 (mm:ss)\n", + "2026-05-09 12:08:07.01 Processing started for file /var/home/timcera/programming/HSP_old/HSPsquared/examples/_TutorialData/test10.h5; saveall=False\n", + "Skipping un-typed siminfo\n", + "op_tokens has 186 elements, with 1 executable elements\n", + "2026-05-09 12:08:12.05 Simulation Start: 1976-01-01 00:00:00, Stop: 1977-01-01 00:00:00\n", + "2026-05-09 12:08:12.05 PERLND P001 DELT(minutes): 60\n", + "2026-05-09 12:08:12.42 SNOW\n", + "2026-05-09 12:08:13.08 PWATER\n", + "2026-05-09 12:08:13.38 PSTEMP\n", + "2026-05-09 12:08:13.39 PWTGAS\n", + "2026-05-09 12:08:13.40 RCHRES R001 DELT(minutes): 60\n", + "2026-05-09 12:08:13.41 HYDR\n", + "2026-05-09 12:08:19.70 ADCALC\n", + "2026-05-09 12:08:19.71 CONS\n", + "2026-05-09 12:08:19.77 HTRCH\n", + "2026-05-09 12:08:19.79 SEDTRN\n", + "2026-05-09 12:08:19.82 RQUAL\n", + "2026-05-09 12:08:20.24 GQUAL\n", + "2026-05-09 12:08:20.86 DISPLY D005 DELT(minutes): 60\n", + "2026-05-09 12:08:20.86 DISPLY D001 DELT(minutes): 60\n", + "2026-05-09 12:08:20.86 GENER G001 DELT(minutes): 60\n", + "2026-05-09 12:08:20.86 DISPLY D002 DELT(minutes): 60\n", + "2026-05-09 12:08:20.86 RCHRES R002 DELT(minutes): 60\n", + "2026-05-09 12:08:20.87 HYDR\n", + "2026-05-09 12:08:24.08 ADCALC\n", + "2026-05-09 12:08:24.08 CONS\n", + "2026-05-09 12:08:24.08 HTRCH\n", + "2026-05-09 12:08:24.09 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-09 12:08:24.09 SEDTRN\n", + "2026-05-09 12:08:24.09 Error count 3598: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-09 12:08:24.10 RQUAL\n", + "2026-05-09 12:08:24.25 GQUAL\n", + "2026-05-09 12:08:24.62 RCHRES R003 DELT(minutes): 60\n", + "2026-05-09 12:08:24.63 HYDR\n", + "2026-05-09 12:08:24.65 ADCALC\n", + "2026-05-09 12:08:24.66 CONS\n", + "2026-05-09 12:08:24.66 HTRCH\n", + "2026-05-09 12:08:24.66 Error count 3: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-09 12:08:24.67 SEDTRN\n", + "2026-05-09 12:08:24.67 Error count 513: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-09 12:08:24.68 RQUAL\n", + "2026-05-09 12:08:24.82 GQUAL\n", + "2026-05-09 12:08:25.11 RCHRES R004 DELT(minutes): 60\n", + "2026-05-09 12:08:25.14 HYDR\n", + "2026-05-09 12:08:25.17 ADCALC\n", + "2026-05-09 12:08:25.17 CONS\n", + "2026-05-09 12:08:25.18 HTRCH\n", + "2026-05-09 12:08:25.18 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-09 12:08:25.18 SEDTRN\n", + "2026-05-09 12:08:25.19 Error count 6720: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-09 12:08:25.19 RQUAL\n", + "2026-05-09 12:08:25.36 GQUAL\n", + "2026-05-09 12:08:25.78 PLTGEN L002 DELT(minutes): 60\n", + "2026-05-09 12:08:25.78 IMPLND I001 DELT(minutes): 60\n", + "2026-05-09 12:08:25.78 SNOW\n", + "2026-05-09 12:08:25.84 IWATER\n", + "2026-05-09 12:08:25.86 SOLIDS\n", + "2026-05-09 12:08:25.87 IWTGAS\n", + "2026-05-09 12:08:25.88 IQUAL\n", + "2026-05-09 12:08:25.89 RCHRES R005 DELT(minutes): 60\n", + "2026-05-09 12:08:25.90 HYDR\n", + "2026-05-09 12:08:25.93 ADCALC\n", + "2026-05-09 12:08:25.93 CONS\n", + "2026-05-09 12:08:25.93 HTRCH\n", + "2026-05-09 12:08:25.94 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-09 12:08:25.94 SEDTRN\n", + "2026-05-09 12:08:25.95 RQUAL\n", + "2026-05-09 12:08:26.12 GQUAL\n", + "2026-05-09 12:08:26.54 DISPLY D003 DELT(minutes): 60\n", + "2026-05-09 12:08:26.54 GENER G002 DELT(minutes): 60\n", + "2026-05-09 12:08:26.54 DISPLY D004 DELT(minutes): 60\n", + "2026-05-09 12:08:26.54 PLTGEN L001 DELT(minutes): 60\n", + "2026-05-09 12:08:26.54 Done; Run time is about 00:19.5 (mm:ss)\n", "\n", "\n", " version\n", - "Python 3.8.12 | packaged by conda-forge | (default, O...\n", - "HSP2 0.10.1\n", - "numpy 1.20.3\n", - "numba 0.53.1\n", - "pandas 1.2.5\n", - "jupyterlab 3.2.8\n", - "notebook 6.4.7\n", - "os macOS-10.16-x86_64-i386-64bit\n", - "processor i386\n", - "Date/Time 2022-06-23 10:04:03\n", - "CPU times: user 16.8 s, sys: 610 ms, total: 17.4 s\n", - "Wall time: 17.4 s\n" + "name \n", + "Python 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11....\n", + "hsp2 0.11.0a1\n", + "numpy 1.26.4\n", + "numba 0.64.0\n", + "pandas 2.3.3\n", + "jupyterlab 4.5.6\n", + "notebook n/a\n", + "os Linux-6.19.12-200.fc43.x86_64-x86_64-with-glib...\n", + "processor \n", + "Date/Time 2026-05-09T12:08:26.919628\n", + "CPU times: user 19.2 s, sys: 691 ms, total: 19.9 s\n", + "Wall time: 19.9 s\n" ] } ], "source": [ "%%time\n", - "# This model should take 2-4 minutes to run the first time\n", - "HSP2.main(io_manager, saveall=False)" + "# This model should take 1-4 minutes to run the first time\n", + "hsp2.main(io_manager, saveall=False, jupyterlab=True)" ] }, { @@ -1133,7 +956,113 @@ "\n", "Note the total run time before and after you rerun the model. You'll notice the model runs much faster the second time.\n", "- During the first model run, numba compiles specified code blocks, then saves the complied code.\n", - "- During all subsequent model runs, numba-compiled code is used directly, avoiding the time to compile, saving 1-2 minutes of runtime." + "- During all subsequent model runs, numba-compiled code is used directly, avoiding the time to compile, executing **~11x faster**!" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2026-05-09 12:08:26.93 Processing started for file /var/home/timcera/programming/HSP_old/HSPsquared/examples/_TutorialData/test10.h5; saveall=False\n", + "Skipping un-typed siminfo\n", + "op_tokens has 186 elements, with 1 executable elements\n", + "2026-05-09 12:08:29.58 Simulation Start: 1976-01-01 00:00:00, Stop: 1977-01-01 00:00:00\n", + "2026-05-09 12:08:29.58 PERLND P001 DELT(minutes): 60\n", + "2026-05-09 12:08:29.59 SNOW\n", + "2026-05-09 12:08:29.64 PWATER\n", + "2026-05-09 12:08:29.71 PSTEMP\n", + "2026-05-09 12:08:29.71 PWTGAS\n", + "2026-05-09 12:08:29.71 RCHRES R001 DELT(minutes): 60\n", + "2026-05-09 12:08:29.72 HYDR\n", + "2026-05-09 12:08:29.76 ADCALC\n", + "2026-05-09 12:08:29.76 CONS\n", + "2026-05-09 12:08:29.76 HTRCH\n", + "2026-05-09 12:08:29.77 SEDTRN\n", + "2026-05-09 12:08:29.79 RQUAL\n", + "2026-05-09 12:08:30.16 GQUAL\n", + "2026-05-09 12:08:30.76 DISPLY D005 DELT(minutes): 60\n", + "2026-05-09 12:08:30.76 DISPLY D001 DELT(minutes): 60\n", + "2026-05-09 12:08:30.76 GENER G001 DELT(minutes): 60\n", + "2026-05-09 12:08:30.76 DISPLY D002 DELT(minutes): 60\n", + "2026-05-09 12:08:30.76 RCHRES R002 DELT(minutes): 60\n", + "2026-05-09 12:08:30.77 HYDR\n", + "2026-05-09 12:08:30.80 ADCALC\n", + "2026-05-09 12:08:30.80 CONS\n", + "2026-05-09 12:08:30.80 HTRCH\n", + "2026-05-09 12:08:30.80 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-09 12:08:30.80 SEDTRN\n", + "2026-05-09 12:08:30.81 Error count 3598: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-09 12:08:30.82 RQUAL\n", + "2026-05-09 12:08:30.98 GQUAL\n", + "2026-05-09 12:08:31.36 RCHRES R003 DELT(minutes): 60\n", + "2026-05-09 12:08:31.37 HYDR\n", + "2026-05-09 12:08:31.39 ADCALC\n", + "2026-05-09 12:08:31.40 CONS\n", + "2026-05-09 12:08:31.40 HTRCH\n", + "2026-05-09 12:08:31.40 Error count 3: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-09 12:08:31.40 SEDTRN\n", + "2026-05-09 12:08:31.41 Error count 513: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-09 12:08:31.41 RQUAL\n", + "2026-05-09 12:08:31.56 GQUAL\n", + "2026-05-09 12:08:31.88 RCHRES R004 DELT(minutes): 60\n", + "2026-05-09 12:08:31.89 HYDR\n", + "2026-05-09 12:08:31.92 ADCALC\n", + "2026-05-09 12:08:31.92 CONS\n", + "2026-05-09 12:08:31.93 HTRCH\n", + "2026-05-09 12:08:31.93 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-09 12:08:31.93 SEDTRN\n", + "2026-05-09 12:08:31.94 Error count 6720: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-09 12:08:31.94 RQUAL\n", + "2026-05-09 12:08:32.11 GQUAL\n", + "2026-05-09 12:08:32.52 PLTGEN L002 DELT(minutes): 60\n", + "2026-05-09 12:08:32.52 IMPLND I001 DELT(minutes): 60\n", + "2026-05-09 12:08:32.53 SNOW\n", + "2026-05-09 12:08:32.58 IWATER\n", + "2026-05-09 12:08:32.60 SOLIDS\n", + "2026-05-09 12:08:32.61 IWTGAS\n", + "2026-05-09 12:08:32.61 IQUAL\n", + "2026-05-09 12:08:32.61 RCHRES R005 DELT(minutes): 60\n", + "2026-05-09 12:08:32.62 HYDR\n", + "2026-05-09 12:08:32.65 ADCALC\n", + "2026-05-09 12:08:32.65 CONS\n", + "2026-05-09 12:08:32.66 HTRCH\n", + "2026-05-09 12:08:32.66 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-09 12:08:32.66 SEDTRN\n", + "2026-05-09 12:08:32.67 RQUAL\n", + "2026-05-09 12:08:32.84 GQUAL\n", + "2026-05-09 12:08:33.26 DISPLY D003 DELT(minutes): 60\n", + "2026-05-09 12:08:33.26 GENER G002 DELT(minutes): 60\n", + "2026-05-09 12:08:33.26 DISPLY D004 DELT(minutes): 60\n", + "2026-05-09 12:08:33.26 PLTGEN L001 DELT(minutes): 60\n", + "2026-05-09 12:08:33.26 Done; Run time is about 00:06.3 (mm:ss)\n", + "\n", + "\n", + " version\n", + "name \n", + "Python 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11....\n", + "hsp2 0.11.0a1\n", + "numpy 1.26.4\n", + "numba 0.64.0\n", + "pandas 2.3.3\n", + "jupyterlab 4.5.6\n", + "notebook n/a\n", + "os Linux-6.19.12-200.fc43.x86_64-x86_64-with-glib...\n", + "processor \n", + "Date/Time 2026-05-09T12:08:33.275713\n", + "CPU times: user 6.29 s, sys: 174 ms, total: 6.47 s\n", + "Wall time: 6.35 s\n" + ] + } + ], + "source": [ + "%%time\n", + "# This model should now take <1 minute to run, now that it has already compiled\n", + "hsp2.main(io_manager, saveall=False)" ] }, { @@ -1148,16 +1077,16 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "['/Users/aaufdenkampe/Documents/Python/respec.HSPsquared/examples/_TutorialData/test10.h5']" + "['/var/home/timcera/programming/HSP_old/HSPsquared/examples/_TutorialData/test10.h5']" ] }, - "execution_count": 17, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -1169,35 +1098,27 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "# Best practice is to delete the HSP2 IO Manager and HDF5 instances\n", - "del io_manager" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [], - "source": [ + "del io_manager\n", "del hdf5_instance" ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "['/Users/aaufdenkampe/Documents/Python/respec.HSPsquared/examples/_TutorialData/test10.h5']" + "['/var/home/timcera/programming/HSP_old/HSPsquared/examples/_TutorialData/test10.h5']" ] }, - "execution_count": 20, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } @@ -1209,14 +1130,15 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "Closing remaining open files:/Users/aaufdenkampe/Documents/Python/respec.HSPsquared/examples/_TutorialData/test10.h5...done\n" + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/file.py:113: UnclosedFileWarning: Closing remaining open file: /var/home/timcera/programming/HSP_old/HSPsquared/examples/_TutorialData/test10.h5\n", + " warnings.warn(UnclosedFileWarning(msg))\n" ] } ], @@ -1227,7 +1149,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 28, "metadata": {}, "outputs": [ { @@ -1236,7 +1158,7 @@ "[]" ] }, - "execution_count": 22, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" } @@ -1260,93 +1182,101 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 29, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "2022-06-23 10:04:03.69 Processing started for file ./; saveall=True\n", - "2022-06-23 10:04:10.12 Simulation Start: 1976-01-01 00:00:00, Stop: 1977-01-01 00:00:00\n", - "2022-06-23 10:04:10.12 PERLND P001 DELT(minutes): 60\n", - "2022-06-23 10:04:10.21 SNOW\n", - "2022-06-23 10:04:10.43 PWATER\n", - "2022-06-23 10:04:10.77 PSTEMP\n", - "2022-06-23 10:04:10.81 PWTGAS\n", - "2022-06-23 10:04:11.00 RCHRES R001 DELT(minutes): 60\n", - "2022-06-23 10:04:11.03 HYDR\n", - "2022-06-23 10:04:11.17 ADCALC\n", - "2022-06-23 10:04:11.18 CONS\n", - "2022-06-23 10:04:11.27 HTRCH\n", - "2022-06-23 10:04:11.40 SEDTRN\n", - "2022-06-23 10:04:11.74 RQUAL\n", - "2022-06-23 10:04:14.21 GQUAL\n", - "2022-06-23 10:04:16.23 GENER G001 DELT(minutes): 60\n", - "GENER 'G001' encountered unsupported feature during initialization and may not function correctly. Unsupported feature: 'Invalid SVOL. GENER module does not currently support reading TimeSeries for 'RCHRES''\n", - "2022-06-23 10:04:16.23 RCHRES R002 DELT(minutes): 60\n", - "2022-06-23 10:04:16.25 HYDR\n", - "2022-06-23 10:04:16.36 ADCALC\n", - "2022-06-23 10:04:16.37 CONS\n", - "2022-06-23 10:04:16.43 HTRCH\n", - "2022-06-23 10:04:16.44 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2022-06-23 10:04:16.55 SEDTRN\n", - "2022-06-23 10:04:16.56 Error count 3598: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", - "2022-06-23 10:04:16.79 RQUAL\n", - "2022-06-23 10:04:18.75 GQUAL\n", - "2022-06-23 10:04:20.10 RCHRES R003 DELT(minutes): 60\n", - "2022-06-23 10:04:20.13 HYDR\n", - "2022-06-23 10:04:20.23 ADCALC\n", - "2022-06-23 10:04:20.24 CONS\n", - "2022-06-23 10:04:20.32 HTRCH\n", - "2022-06-23 10:04:20.32 Error count 3: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2022-06-23 10:04:20.44 SEDTRN\n", - "2022-06-23 10:04:20.45 Error count 513: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", - "2022-06-23 10:04:20.73 RQUAL\n", - "2022-06-23 10:04:22.47 GQUAL\n", - "2022-06-23 10:04:23.67 RCHRES R004 DELT(minutes): 60\n", - "2022-06-23 10:04:23.74 HYDR\n", - "2022-06-23 10:04:23.85 ADCALC\n", - "2022-06-23 10:04:23.86 CONS\n", - "2022-06-23 10:04:23.92 HTRCH\n", - "2022-06-23 10:04:23.93 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2022-06-23 10:04:24.04 SEDTRN\n", - "2022-06-23 10:04:24.06 Error count 6720: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", - "2022-06-23 10:04:24.31 RQUAL\n", - "2022-06-23 10:04:26.15 GQUAL\n", - "2022-06-23 10:04:27.62 IMPLND I001 DELT(minutes): 60\n", - "2022-06-23 10:04:27.63 SNOW\n", - "2022-06-23 10:04:27.84 IWATER\n", - "2022-06-23 10:04:27.94 SOLIDS\n", - "2022-06-23 10:04:27.97 IWTGAS\n", - "2022-06-23 10:04:28.03 IQUAL\n", - "2022-06-23 10:04:28.14 RCHRES R005 DELT(minutes): 60\n", - "2022-06-23 10:04:28.17 HYDR\n", - "2022-06-23 10:04:28.28 ADCALC\n", - "2022-06-23 10:04:28.28 CONS\n", - "2022-06-23 10:04:28.35 HTRCH\n", - "2022-06-23 10:04:28.36 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2022-06-23 10:04:28.47 SEDTRN\n", - "2022-06-23 10:04:28.73 RQUAL\n", - "2022-06-23 10:04:30.57 GQUAL\n", - "2022-06-23 10:04:31.98 GENER G002 DELT(minutes): 60\n", - "GENER 'G002' encountered unsupported feature during initialization and may not function correctly. Unsupported feature: 'Invalid SVOL. GENER module does not currently support reading TimeSeries for 'RCHRES''\n", - "2022-06-23 10:04:31.98 Done; Run time is about 00:28.2 (mm:ss)\n", + "2026-05-09 12:08:33.33 Processing started for file /var/home/timcera/programming/HSP_old/HSPsquared/examples/_TutorialData/test10.h5; saveall=True\n", + "Skipping un-typed siminfo\n", + "op_tokens has 186 elements, with 1 executable elements\n", + "2026-05-09 12:08:35.99 Simulation Start: 1976-01-01 00:00:00, Stop: 1977-01-01 00:00:00\n", + "2026-05-09 12:08:35.99 PERLND P001 DELT(minutes): 60\n", + "2026-05-09 12:08:36.03 SNOW\n", + "2026-05-09 12:08:36.11 PWATER\n", + "2026-05-09 12:08:36.26 PSTEMP\n", + "2026-05-09 12:08:36.28 PWTGAS\n", + "2026-05-09 12:08:36.36 RCHRES R001 DELT(minutes): 60\n", + "2026-05-09 12:08:36.37 HYDR\n", + "2026-05-09 12:08:36.47 ADCALC\n", + "2026-05-09 12:08:36.47 CONS\n", + "2026-05-09 12:08:36.51 HTRCH\n", + "2026-05-09 12:08:36.57 SEDTRN\n", + "2026-05-09 12:08:36.71 RQUAL\n", + "2026-05-09 12:08:37.73 GQUAL\n", + "2026-05-09 12:08:38.57 DISPLY D005 DELT(minutes): 60\n", + "2026-05-09 12:08:38.57 DISPLY D001 DELT(minutes): 60\n", + "2026-05-09 12:08:38.57 GENER G001 DELT(minutes): 60\n", + "2026-05-09 12:08:38.57 DISPLY D002 DELT(minutes): 60\n", + "2026-05-09 12:08:38.57 RCHRES R002 DELT(minutes): 60\n", + "2026-05-09 12:08:38.59 HYDR\n", + "2026-05-09 12:08:38.65 ADCALC\n", + "2026-05-09 12:08:38.66 CONS\n", + "2026-05-09 12:08:38.69 HTRCH\n", + "2026-05-09 12:08:38.69 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-09 12:08:38.74 SEDTRN\n", + "2026-05-09 12:08:38.75 Error count 3598: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-09 12:08:38.85 RQUAL\n", + "2026-05-09 12:08:39.57 GQUAL\n", + "2026-05-09 12:08:40.17 RCHRES R003 DELT(minutes): 60\n", + "2026-05-09 12:08:40.18 HYDR\n", + "2026-05-09 12:08:40.25 ADCALC\n", + "2026-05-09 12:08:40.25 CONS\n", + "2026-05-09 12:08:40.27 HTRCH\n", + "2026-05-09 12:08:40.28 Error count 3: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-09 12:08:40.32 SEDTRN\n", + "2026-05-09 12:08:40.33 Error count 513: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-09 12:08:40.43 RQUAL\n", + "2026-05-09 12:08:41.10 GQUAL\n", + "2026-05-09 12:08:41.62 RCHRES R004 DELT(minutes): 60\n", + "2026-05-09 12:08:41.65 HYDR\n", + "2026-05-09 12:08:41.72 ADCALC\n", + "2026-05-09 12:08:41.72 CONS\n", + "2026-05-09 12:08:41.75 HTRCH\n", + "2026-05-09 12:08:41.75 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-09 12:08:41.80 SEDTRN\n", + "2026-05-09 12:08:41.81 Error count 6720: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-09 12:08:41.92 RQUAL\n", + "2026-05-09 12:08:42.78 GQUAL\n", + "2026-05-09 12:08:43.40 PLTGEN L002 DELT(minutes): 60\n", + "2026-05-09 12:08:43.40 IMPLND I001 DELT(minutes): 60\n", + "2026-05-09 12:08:43.41 SNOW\n", + "2026-05-09 12:08:43.49 IWATER\n", + "2026-05-09 12:08:43.53 SOLIDS\n", + "2026-05-09 12:08:43.54 IWTGAS\n", + "2026-05-09 12:08:43.57 IQUAL\n", + "2026-05-09 12:08:43.61 RCHRES R005 DELT(minutes): 60\n", + "2026-05-09 12:08:43.63 HYDR\n", + "2026-05-09 12:08:43.70 ADCALC\n", + "2026-05-09 12:08:43.70 CONS\n", + "2026-05-09 12:08:43.73 HTRCH\n", + "2026-05-09 12:08:43.73 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-09 12:08:43.79 SEDTRN\n", + "2026-05-09 12:08:43.91 RQUAL\n", + "2026-05-09 12:08:44.70 GQUAL\n", + "2026-05-09 12:08:45.36 DISPLY D003 DELT(minutes): 60\n", + "2026-05-09 12:08:45.36 GENER G002 DELT(minutes): 60\n", + "2026-05-09 12:08:45.36 DISPLY D004 DELT(minutes): 60\n", + "2026-05-09 12:08:45.36 PLTGEN L001 DELT(minutes): 60\n", + "2026-05-09 12:08:45.36 Done; Run time is about 00:12.0 (mm:ss)\n", "\n", "\n", " version\n", - "Python 3.8.12 | packaged by conda-forge | (default, O...\n", - "HSP2 0.10.1\n", - "numpy 1.20.3\n", - "numba 0.53.1\n", - "pandas 1.2.5\n", - "jupyterlab 3.2.8\n", - "notebook 6.4.7\n", - "os macOS-10.16-x86_64-i386-64bit\n", - "processor i386\n", - "Date/Time 2022-06-23 10:04:32\n", - "CPU times: user 26.5 s, sys: 1.7 s, total: 28.2 s\n", - "Wall time: 28.4 s\n" + "name \n", + "Python 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11....\n", + "hsp2 0.11.0a1\n", + "numpy 1.26.4\n", + "numba 0.64.0\n", + "pandas 2.3.3\n", + "jupyterlab 4.5.6\n", + "notebook n/a\n", + "os Linux-6.19.12-200.fc43.x86_64-x86_64-with-glib...\n", + "processor \n", + "Date/Time 2026-05-09T12:08:45.373019\n", + "CPU times: user 11.7 s, sys: 362 ms, total: 12.1 s\n", + "Wall time: 12.1 s\n" ] } ], @@ -1355,14 +1285,14 @@ "# Setup IO Manager and run the model, as recommended,\n", "# all within a Python `with` statement as a context manager\n", "\n", - "with HSP2IO.hdf.HDF5(output_hdf5_path) as hdf5_instance:\n", - " io_manager = HSP2IO.io.IOManager(hdf5_instance)\n", - " HSP2.main(io_manager, saveall=True)" + "with hsp2io.hdf.HDF5(output_hdf5_path) as hdf5_instance:\n", + " io_manager = hsp2io.io.IOManager(hdf5_instance)\n", + " hsp2.main(io_manager, saveall=True)" ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 30, "metadata": {}, "outputs": [ { @@ -1371,7 +1301,7 @@ "[]" ] }, - "execution_count": 24, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" } @@ -1394,9 +1324,6 @@ } ], "metadata": { - "interpreter": { - "hash": "776e005896af2bdd35b514f04d0649047a67df21e3539ef9c16d2c229e31ef47" - }, "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", @@ -1412,7 +1339,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.14" + "version": "3.11.11" }, "toc-autonumbering": true, "toc-showmarkdowntxt": false diff --git a/examples/2_ExploreResultsHDF5.ipynb b/examples/2_ExploreResultsHDF5.ipynb index 38d6885b..477bf7b4 100644 --- a/examples/2_ExploreResultsHDF5.ipynb +++ b/examples/2_ExploreResultsHDF5.ipynb @@ -59,7 +59,7 @@ { "data": { "text/plain": [ - "'hsp2_py38'" + "'default311'" ] }, "execution_count": 2, @@ -91,7 +91,7 @@ { "data": { "text/plain": [ - "PosixPath('/Users/aaufdenkampe/Documents/Python/respec.HSPsquared/examples')" + "PosixPath('/var/home/timcera/programming/HSP_old/HSPsquared/examples')" ] }, "execution_count": 3, @@ -109,10 +109,22 @@ "execution_count": 4, "id": "e9e4c731-7c85-4e30-99db-34ecf3d4bff9", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "PosixPath('/var/home/timcera/programming/HSP_old/HSPsquared')" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# Set your project directory to your local folder for your clone of the HSPsquared repository\n", - "project_folder = Path(\"/Users/aaufdenkampe/Documents/Python/respec.HSPsquared/\")" + "# Find project directory (i.e. the parent to `/examples` directory for this notebook)\n", + "project_path = Path.cwd().parent\n", + "project_path" ] }, { @@ -125,7 +137,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "/Users/aaufdenkampe/Documents/Python/respec.HSPsquared/examples/_TutorialData/test10.h5\n", + "/var/home/timcera/programming/HSP_old/HSPsquared/examples/_TutorialData/test10.h5\n", "File exists? True\n" ] } @@ -138,7 +150,7 @@ "output_file = \"test10.h5\" # HSP2 data HDF5 binary file, for all inputs and outputs\n", "\n", "output_hdf5_path = (\n", - " project_folder / output_data_folder / output_file\n", + " project_path / output_data_folder / output_file\n", ") # pathlib concatenation\n", "\n", "print(output_hdf5_path)\n", @@ -230,7 +242,7 @@ " TS039\n", " 1976-01-01 00:00:00\n", " 1977-01-01 00:00:00\n", - " 1H\n", + " 1h\n", " 8784\n", " PREC\n", " -999.0\n", @@ -263,7 +275,7 @@ " TS046\n", " 1976-01-01 00:00:00\n", " 1977-01-01 00:00:00\n", - " 2H\n", + " 2h\n", " 4392\n", " SOLR\n", " -999.0\n", @@ -296,7 +308,7 @@ " TS121\n", " 1976-01-01 00:00:00\n", " 1977-01-01 00:00:00\n", - " 2H\n", + " 2h\n", " 4392\n", " ATMP\n", " -999.0\n", @@ -307,7 +319,7 @@ " TS122\n", " 1976-01-01 00:00:00\n", " 1977-01-01 00:00:00\n", - " 2H\n", + " 2h\n", " 4392\n", " ATMP\n", " -999.0\n", @@ -318,7 +330,7 @@ " TS123\n", " 1976-01-01 00:00:00\n", " 1977-01-01 00:00:00\n", - " 2H\n", + " 2h\n", " 4392\n", " ATMP\n", " -999.0\n", @@ -373,7 +385,7 @@ " TS131\n", " 1976-01-01 00:00:00\n", " 1977-01-01 00:00:00\n", - " 1H\n", + " 1h\n", " 8784\n", " PREC\n", " -999.0\n", @@ -384,7 +396,7 @@ " TS132\n", " 1976-01-01 00:00:00\n", " 1977-01-01 00:00:00\n", - " 1H\n", + " 1h\n", " 8784\n", " PREC\n", " -999.0\n", @@ -441,21 +453,21 @@ ], "text/plain": [ " Start Stop Freq Length TSTYPE TFILL \\\n", - "TS039 1976-01-01 00:00:00 1977-01-01 00:00:00 1H 8784 PREC -999.0 \n", + "TS039 1976-01-01 00:00:00 1977-01-01 00:00:00 1h 8784 PREC -999.0 \n", "TS041 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 EVAP -999.0 \n", "TS042 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 WIND -999.0 \n", - "TS046 1976-01-01 00:00:00 1977-01-01 00:00:00 2H 4392 SOLR -999.0 \n", + "TS046 1976-01-01 00:00:00 1977-01-01 00:00:00 2h 4392 SOLR -999.0 \n", "TS113 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 FLOW -999.0 \n", "TS119 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 FLOW -999.0 \n", - "TS121 1976-01-01 00:00:00 1977-01-01 00:00:00 2H 4392 ATMP -999.0 \n", - "TS122 1976-01-01 00:00:00 1977-01-01 00:00:00 2H 4392 ATMP -999.0 \n", - "TS123 1976-01-01 00:00:00 1977-01-01 00:00:00 2H 4392 ATMP -999.0 \n", + "TS121 1976-01-01 00:00:00 1977-01-01 00:00:00 2h 4392 ATMP -999.0 \n", + "TS122 1976-01-01 00:00:00 1977-01-01 00:00:00 2h 4392 ATMP -999.0 \n", + "TS123 1976-01-01 00:00:00 1977-01-01 00:00:00 2h 4392 ATMP -999.0 \n", "TS124 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 DEWP -999.0 \n", "TS125 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 DEWP -999.0 \n", "TS126 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 DEWP -999.0 \n", "TS127 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 SEDM -999.0 \n", - "TS131 1976-01-01 00:00:00 1977-01-01 00:00:00 1H 8784 PREC -999.0 \n", - "TS132 1976-01-01 00:00:00 1977-01-01 00:00:00 1H 8784 PREC -999.0 \n", + "TS131 1976-01-01 00:00:00 1977-01-01 00:00:00 1h 8784 PREC -999.0 \n", + "TS132 1976-01-01 00:00:00 1977-01-01 00:00:00 1h 8784 PREC -999.0 \n", "TS134 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 WTMP -999.0 \n", "TS135 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 CLDC -999.0 \n", "TS136 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 FLOW -999.0 \n", @@ -598,13 +610,18 @@ " \n", " \n", " \n", + " AVDEP\n", + " AVVEL\n", " DEP\n", + " HRAD\n", " IVOL\n", + " POTEV\n", " PRSUPY\n", " RO\n", " ROVOL\n", " SAREA\n", " TAU\n", + " TWID\n", " USTAR\n", " VOL\n", " VOLEV\n", @@ -613,65 +630,90 @@ " \n", " \n", " 1976-01-01 01:00:00\n", + " 0.702923\n", + " 1.857768\n", " 0.822988\n", + " 0.562775\n", " 1.747608\n", + " 0.000583\n", " 0.0\n", " 7.371986\n", " 0.304628\n", " 2.052829\n", " 0.088680\n", + " 5.645279\n", " 0.213918\n", " 1.442980\n", " 0.000000\n", " \n", " \n", " 1976-01-01 02:00:00\n", + " 0.651220\n", + " 1.770455\n", " 0.754730\n", + " 0.526685\n", " 0.428585\n", + " 0.000583\n", " 0.0\n", " 6.350832\n", " 0.567059\n", " 2.003019\n", " 0.082993\n", + " 5.508303\n", " 0.206945\n", " 1.304407\n", " 0.000100\n", " \n", " \n", " 1976-01-01 03:00:00\n", + " 0.534142\n", + " 1.576605\n", " 0.604331\n", + " 0.443217\n", " 0.150780\n", + " 0.000583\n", " 0.0\n", " 4.385298\n", " 0.443642\n", " 1.893593\n", " 0.069840\n", + " 5.207382\n", " 0.189840\n", " 1.011448\n", " 0.000097\n", " \n", " \n", " 1976-01-01 04:00:00\n", + " 0.429286\n", + " 1.416886\n", " 0.474719\n", + " 0.365824\n", " 0.066827\n", + " 0.000583\n", " 0.0\n", " 3.010308\n", " 0.305604\n", " 1.799683\n", " 0.057645\n", + " 4.949128\n", " 0.172471\n", " 0.772579\n", " 0.000092\n", " \n", " \n", " 1976-01-01 05:00:00\n", + " 0.346840\n", + " 1.221629\n", " 0.376407\n", + " 0.302669\n", " 0.034621\n", + " 0.000583\n", " 0.0\n", " 2.013996\n", " 0.207616\n", " 1.728451\n", " 0.047693\n", + " 4.753240\n", " 0.156879\n", " 0.599497\n", " 0.000087\n", @@ -688,11 +730,20 @@ " ...\n", " ...\n", " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", " \n", " \n", " 1976-12-31 20:00:00\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000583\n", " 0.0\n", " 0.000000\n", " 0.000000\n", @@ -701,11 +752,16 @@ " 0.000000\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", " \n", " \n", " 1976-12-31 21:00:00\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000583\n", " 0.0\n", " 0.000000\n", " 0.000000\n", @@ -714,11 +770,16 @@ " 0.000000\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", " \n", " \n", " 1976-12-31 22:00:00\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000583\n", " 0.0\n", " 0.000000\n", " 0.000000\n", @@ -727,11 +788,16 @@ " 0.000000\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", " \n", " \n", " 1976-12-31 23:00:00\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000583\n", " 0.0\n", " 0.000000\n", " 0.000000\n", @@ -740,11 +806,16 @@ " 0.000000\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", " \n", " \n", " 1977-01-01 00:00:00\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000583\n", " 0.0\n", " 0.000000\n", " 0.000000\n", @@ -753,32 +824,46 @@ " 0.000000\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", " \n", " \n", "\n", - "

8784 rows × 10 columns

\n", + "

8784 rows × 15 columns

\n", "" ], "text/plain": [ - " DEP IVOL PRSUPY RO ROVOL SAREA \\\n", - "1976-01-01 01:00:00 0.822988 1.747608 0.0 7.371986 0.304628 2.052829 \n", - "1976-01-01 02:00:00 0.754730 0.428585 0.0 6.350832 0.567059 2.003019 \n", - "1976-01-01 03:00:00 0.604331 0.150780 0.0 4.385298 0.443642 1.893593 \n", - "1976-01-01 04:00:00 0.474719 0.066827 0.0 3.010308 0.305604 1.799683 \n", - "1976-01-01 05:00:00 0.376407 0.034621 0.0 2.013996 0.207616 1.728451 \n", - "... ... ... ... ... ... ... \n", - "1976-12-31 20:00:00 0.000000 0.000000 0.0 0.000000 0.000000 0.000000 \n", - "1976-12-31 21:00:00 0.000000 0.000000 0.0 0.000000 0.000000 0.000000 \n", - "1976-12-31 22:00:00 0.000000 0.000000 0.0 0.000000 0.000000 0.000000 \n", - "1976-12-31 23:00:00 0.000000 0.000000 0.0 0.000000 0.000000 0.000000 \n", - "1977-01-01 00:00:00 0.000000 0.000000 0.0 0.000000 0.000000 0.000000 \n", + " AVDEP AVVEL DEP HRAD IVOL \\\n", + "1976-01-01 01:00:00 0.702923 1.857768 0.822988 0.562775 1.747608 \n", + "1976-01-01 02:00:00 0.651220 1.770455 0.754730 0.526685 0.428585 \n", + "1976-01-01 03:00:00 0.534142 1.576605 0.604331 0.443217 0.150780 \n", + "1976-01-01 04:00:00 0.429286 1.416886 0.474719 0.365824 0.066827 \n", + "1976-01-01 05:00:00 0.346840 1.221629 0.376407 0.302669 0.034621 \n", + "... ... ... ... ... ... \n", + "1976-12-31 20:00:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "1976-12-31 21:00:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "1976-12-31 22:00:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "1976-12-31 23:00:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "1977-01-01 00:00:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "\n", - " TAU USTAR VOL VOLEV \n", - "1976-01-01 01:00:00 0.088680 0.213918 1.442980 0.000000 \n", - "1976-01-01 02:00:00 0.082993 0.206945 1.304407 0.000100 \n", - "1976-01-01 03:00:00 0.069840 0.189840 1.011448 0.000097 \n", - "1976-01-01 04:00:00 0.057645 0.172471 0.772579 0.000092 \n", - "1976-01-01 05:00:00 0.047693 0.156879 0.599497 0.000087 \n", + " POTEV PRSUPY RO ROVOL SAREA TAU \\\n", + "1976-01-01 01:00:00 0.000583 0.0 7.371986 0.304628 2.052829 0.088680 \n", + "1976-01-01 02:00:00 0.000583 0.0 6.350832 0.567059 2.003019 0.082993 \n", + "1976-01-01 03:00:00 0.000583 0.0 4.385298 0.443642 1.893593 0.069840 \n", + "1976-01-01 04:00:00 0.000583 0.0 3.010308 0.305604 1.799683 0.057645 \n", + "1976-01-01 05:00:00 0.000583 0.0 2.013996 0.207616 1.728451 0.047693 \n", + "... ... ... ... ... ... ... \n", + "1976-12-31 20:00:00 0.000583 0.0 0.000000 0.000000 0.000000 0.000000 \n", + "1976-12-31 21:00:00 0.000583 0.0 0.000000 0.000000 0.000000 0.000000 \n", + "1976-12-31 22:00:00 0.000583 0.0 0.000000 0.000000 0.000000 0.000000 \n", + "1976-12-31 23:00:00 0.000583 0.0 0.000000 0.000000 0.000000 0.000000 \n", + "1977-01-01 00:00:00 0.000583 0.0 0.000000 0.000000 0.000000 0.000000 \n", + "\n", + " TWID USTAR VOL VOLEV \n", + "1976-01-01 01:00:00 5.645279 0.213918 1.442980 0.000000 \n", + "1976-01-01 02:00:00 5.508303 0.206945 1.304407 0.000100 \n", + "1976-01-01 03:00:00 5.207382 0.189840 1.011448 0.000097 \n", + "1976-01-01 04:00:00 4.949128 0.172471 0.772579 0.000092 \n", + "1976-01-01 05:00:00 4.753240 0.156879 0.599497 0.000087 \n", "... ... ... ... ... \n", "1976-12-31 20:00:00 0.000000 0.000000 0.000000 0.000000 \n", "1976-12-31 21:00:00 0.000000 0.000000 0.000000 0.000000 \n", @@ -786,7 +871,7 @@ "1976-12-31 23:00:00 0.000000 0.000000 0.000000 0.000000 \n", "1977-01-01 00:00:00 0.000000 0.000000 0.000000 0.000000 \n", "\n", - "[8784 rows x 10 columns]" + "[8784 rows x 15 columns]" ] }, "execution_count": 9, @@ -825,13 +910,18 @@ " \n", " \n", " \n", + " AVDEP\n", + " AVVEL\n", " DEP\n", + " HRAD\n", " IVOL\n", + " POTEV\n", " PRSUPY\n", " RO\n", " ROVOL\n", " SAREA\n", " TAU\n", + " TWID\n", " USTAR\n", " VOL\n", " VOLEV\n", @@ -841,46 +931,65 @@ " \n", " count\n", " 8784.000000\n", + " 8784.000000\n", + " 8784.000000\n", + " 8784.000000\n", " 8.784000e+03\n", " 8784.000000\n", " 8784.000000\n", + " 8784.000000\n", " 8.784000e+03\n", " 8784.000000\n", " 8784.000000\n", " 8784.000000\n", " 8784.000000\n", " 8784.000000\n", + " 8784.000000\n", " \n", " \n", " mean\n", + " 0.416398\n", + " 1.182163\n", " 0.590523\n", + " 0.334599\n", " 9.918233e-01\n", + " 0.004514\n", " 0.004978\n", " 12.050080\n", " 9.958744e-01\n", " 1.920959\n", " 0.052725\n", + " 5.282637\n", " 0.128277\n", " 1.846853\n", " 0.000927\n", " \n", " \n", " std\n", - " 0.926055\n", - " 6.259102e+00\n", - " 0.078443\n", - " 51.651436\n", - " 4.111245e+00\n", - " 5.763461\n", - " 0.055300\n", - " 0.103699\n", - " 8.604043\n", - " 0.004121\n", + " 0.454871\n", + " 0.935351\n", + " 0.926041\n", + " 0.350934\n", + " 6.258680e+00\n", + " 0.003897\n", + " 0.078435\n", + " 51.653969\n", + " 4.110970e+00\n", + " 5.763384\n", + " 0.055298\n", + " 15.849998\n", + " 0.103701\n", + " 8.604532\n", + " 0.004122\n", " \n", " \n", " min\n", " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", " -1.664352e-07\n", + " 0.000292\n", " 0.000000\n", " 0.000000\n", " -9.247787e-07\n", @@ -889,11 +998,16 @@ " 0.000000\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", " \n", " \n", " 25%\n", " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", " 0.000000e+00\n", + " 0.000875\n", " 0.000000\n", " 0.000000\n", " 0.000000e+00\n", @@ -902,42 +1016,58 @@ " 0.000000\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", " \n", " \n", " 50%\n", + " 0.241527\n", + " 1.098524\n", " 0.259827\n", + " 0.213238\n", " 7.014202e-02\n", + " 0.003354\n", " 0.000000\n", " 0.966114\n", " 8.215849e-02\n", " 1.324102\n", " 0.033601\n", + " 3.641279\n", " 0.131678\n", " 0.319806\n", " 0.000133\n", " \n", " \n", " 75%\n", + " 0.719509\n", + " 1.882429\n", " 0.845124\n", + " 0.574267\n", " 5.902275e-01\n", + " 0.007875\n", " 0.000000\n", " 7.708535\n", " 6.481222e-01\n", " 2.068982\n", " 0.090491\n", + " 5.689701\n", " 0.216091\n", " 1.488651\n", " 0.000953\n", " \n", " \n", " max\n", + " 2.665695\n", + " 4.079803\n", " 7.691414\n", + " 2.023250\n", " 2.333915e+02\n", + " 0.015458\n", " 3.413368\n", " 987.538513\n", " 7.383160e+01\n", " 93.850304\n", " 0.318815\n", + " 258.088318\n", " 0.405607\n", " 192.907166\n", " 0.088074\n", @@ -947,25 +1077,35 @@ "" ], "text/plain": [ - " DEP IVOL PRSUPY RO ROVOL \\\n", - "count 8784.000000 8.784000e+03 8784.000000 8784.000000 8.784000e+03 \n", - "mean 0.590523 9.918233e-01 0.004978 12.050080 9.958744e-01 \n", - "std 0.926055 6.259102e+00 0.078443 51.651436 4.111245e+00 \n", - "min 0.000000 -1.664352e-07 0.000000 0.000000 -9.247787e-07 \n", - "25% 0.000000 0.000000e+00 0.000000 0.000000 0.000000e+00 \n", - "50% 0.259827 7.014202e-02 0.000000 0.966114 8.215849e-02 \n", - "75% 0.845124 5.902275e-01 0.000000 7.708535 6.481222e-01 \n", - "max 7.691414 2.333915e+02 3.413368 987.538513 7.383160e+01 \n", + " AVDEP AVVEL DEP HRAD IVOL \\\n", + "count 8784.000000 8784.000000 8784.000000 8784.000000 8.784000e+03 \n", + "mean 0.416398 1.182163 0.590523 0.334599 9.918233e-01 \n", + "std 0.454871 0.935351 0.926041 0.350934 6.258680e+00 \n", + "min 0.000000 0.000000 0.000000 0.000000 -1.664352e-07 \n", + "25% 0.000000 0.000000 0.000000 0.000000 0.000000e+00 \n", + "50% 0.241527 1.098524 0.259827 0.213238 7.014202e-02 \n", + "75% 0.719509 1.882429 0.845124 0.574267 5.902275e-01 \n", + "max 2.665695 4.079803 7.691414 2.023250 2.333915e+02 \n", "\n", - " SAREA TAU USTAR VOL VOLEV \n", + " POTEV PRSUPY RO ROVOL SAREA \\\n", + "count 8784.000000 8784.000000 8784.000000 8.784000e+03 8784.000000 \n", + "mean 0.004514 0.004978 12.050080 9.958744e-01 1.920959 \n", + "std 0.003897 0.078435 51.653969 4.110970e+00 5.763384 \n", + "min 0.000292 0.000000 0.000000 -9.247787e-07 0.000000 \n", + "25% 0.000875 0.000000 0.000000 0.000000e+00 0.000000 \n", + "50% 0.003354 0.000000 0.966114 8.215849e-02 1.324102 \n", + "75% 0.007875 0.000000 7.708535 6.481222e-01 2.068982 \n", + "max 0.015458 3.413368 987.538513 7.383160e+01 93.850304 \n", + "\n", + " TAU TWID USTAR VOL VOLEV \n", "count 8784.000000 8784.000000 8784.000000 8784.000000 8784.000000 \n", - "mean 1.920959 0.052725 0.128277 1.846853 0.000927 \n", - "std 5.763461 0.055300 0.103699 8.604043 0.004121 \n", + "mean 0.052725 5.282637 0.128277 1.846853 0.000927 \n", + "std 0.055298 15.849998 0.103701 8.604532 0.004122 \n", "min 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "25% 0.000000 0.000000 0.000000 0.000000 0.000000 \n", - "50% 1.324102 0.033601 0.131678 0.319806 0.000133 \n", - "75% 2.068982 0.090491 0.216091 1.488651 0.000953 \n", - "max 93.850304 0.318815 0.405607 192.907166 0.088074 " + "50% 0.033601 3.641279 0.131678 0.319806 0.000133 \n", + "75% 0.090491 5.689701 0.216091 1.488651 0.000953 \n", + "max 0.318815 258.088318 0.405607 192.907166 0.088074 " ] }, "execution_count": 10, @@ -1011,44 +1151,27 @@ "cell_type": "code", "execution_count": 12, "id": "wrong-syndrome", - "metadata": {}, + "metadata": { + "tags": [] + }, "outputs": [ { "data": { "text/plain": [ - "File(filename=/Users/aaufdenkampe/Documents/Python/respec.HSPsquared/examples/_TutorialData/test10.h5, title='', mode='r', root_uep='/', filters=Filters(complevel=0, shuffle=False, bitshuffle=False, fletcher32=False, least_significant_digit=None))\n", + "File(filename=/var/home/timcera/programming/HSP_old/HSPsquared/examples/_TutorialData/test10.h5, title='', mode='r', root_uep='/', filters=Filters(complevel=0, shuffle=False, bitshuffle=False, fletcher32=False, least_significant_digit=None))\n", "/ (RootGroup) ''\n", "/CONTROL (Group) ''\n", + "/DISPLY (Group) ''\n", + "/FILES (Group) ''\n", "/FTABLES (Group) ''\n", "/GENER (Group) ''\n", "/IMPLND (Group) ''\n", "/PERLND (Group) ''\n", + "/PLTGEN (Group) ''\n", "/RCHRES (Group) ''\n", "/RESULTS (Group) ''\n", "/RUN_INFO (Group) ''\n", "/TIMESERIES (Group) ''\n", - "/TIMESERIES/LAPSE_Table (Group) ''\n", - "/TIMESERIES/LAPSE_Table/table (Table(24,)) ''\n", - " description := {\n", - " \"index\": Int64Col(shape=(), dflt=0, pos=0),\n", - " \"values\": Float64Col(shape=(), dflt=0.0, pos=1)}\n", - " byteorder := 'little'\n", - " chunkshape := (4096,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", - "/TIMESERIES/SEASONS_Table (Group) ''\n", - "/TIMESERIES/SEASONS_Table/table (Table(12,)) ''\n", - " description := {\n", - " \"index\": Int64Col(shape=(), dflt=0, pos=0),\n", - " \"values\": BoolCol(shape=(), dflt=False, pos=1)}\n", - " byteorder := 'little'\n", - " chunkshape := (7281,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", "/TIMESERIES/SUMMARY (Group) ''\n", "/TIMESERIES/SUMMARY/table (Table(19,)) ''\n", " description := {\n", @@ -1065,26 +1188,15 @@ " chunkshape := (512,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Start\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Stop\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Freq\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Length\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSTYPE\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TFILL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"STAID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"STNAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", - "/TIMESERIES/Saturated_Vapor_Pressure_Table (Group) ''\n", - "/TIMESERIES/Saturated_Vapor_Pressure_Table/table (Table(40,)) ''\n", - " description := {\n", - " \"index\": Int64Col(shape=(), dflt=0, pos=0),\n", - " \"values\": Float64Col(shape=(), dflt=0.0, pos=1)}\n", - " byteorder := 'little'\n", - " chunkshape := (4096,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Start\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Stop\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Freq\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Length\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSTYPE\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TFILL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"STAID\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"STNAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/TIMESERIES/TS039 (Group) ''\n", "/TIMESERIES/TS039/table (Table(8784,)) ''\n", " description := {\n", @@ -1094,8 +1206,8 @@ " chunkshape := (4096,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"values\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/TIMESERIES/TS041 (Group) ''\n", "/TIMESERIES/TS041/table (Table(366,)) ''\n", " description := {\n", @@ -1105,8 +1217,8 @@ " chunkshape := (4096,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"values\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/TIMESERIES/TS042 (Group) ''\n", "/TIMESERIES/TS042/table (Table(366,)) ''\n", " description := {\n", @@ -1116,8 +1228,8 @@ " chunkshape := (4096,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"values\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/TIMESERIES/TS046 (Group) ''\n", "/TIMESERIES/TS046/table (Table(4392,)) ''\n", " description := {\n", @@ -1127,8 +1239,8 @@ " chunkshape := (4096,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"values\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/TIMESERIES/TS113 (Group) ''\n", "/TIMESERIES/TS113/table (Table(366,)) ''\n", " description := {\n", @@ -1138,8 +1250,8 @@ " chunkshape := (4096,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"values\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/TIMESERIES/TS119 (Group) ''\n", "/TIMESERIES/TS119/table (Table(366,)) ''\n", " description := {\n", @@ -1149,8 +1261,8 @@ " chunkshape := (4096,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"values\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/TIMESERIES/TS121 (Group) ''\n", "/TIMESERIES/TS121/table (Table(4392,)) ''\n", " description := {\n", @@ -1160,8 +1272,8 @@ " chunkshape := (4096,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"values\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/TIMESERIES/TS122 (Group) ''\n", "/TIMESERIES/TS122/table (Table(4392,)) ''\n", " description := {\n", @@ -1171,8 +1283,8 @@ " chunkshape := (4096,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"values\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/TIMESERIES/TS123 (Group) ''\n", "/TIMESERIES/TS123/table (Table(4392,)) ''\n", " description := {\n", @@ -1182,8 +1294,8 @@ " chunkshape := (4096,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"values\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/TIMESERIES/TS124 (Group) ''\n", "/TIMESERIES/TS124/table (Table(366,)) ''\n", " description := {\n", @@ -1193,8 +1305,8 @@ " chunkshape := (4096,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"values\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/TIMESERIES/TS125 (Group) ''\n", "/TIMESERIES/TS125/table (Table(366,)) ''\n", " description := {\n", @@ -1204,8 +1316,8 @@ " chunkshape := (4096,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"values\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/TIMESERIES/TS126 (Group) ''\n", "/TIMESERIES/TS126/table (Table(366,)) ''\n", " description := {\n", @@ -1215,8 +1327,8 @@ " chunkshape := (4096,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"values\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/TIMESERIES/TS127 (Group) ''\n", "/TIMESERIES/TS127/table (Table(366,)) ''\n", " description := {\n", @@ -1226,8 +1338,8 @@ " chunkshape := (4096,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"values\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/TIMESERIES/TS131 (Group) ''\n", "/TIMESERIES/TS131/table (Table(8784,)) ''\n", " description := {\n", @@ -1237,8 +1349,8 @@ " chunkshape := (4096,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"values\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/TIMESERIES/TS132 (Group) ''\n", "/TIMESERIES/TS132/table (Table(8784,)) ''\n", " description := {\n", @@ -1248,8 +1360,8 @@ " chunkshape := (4096,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"values\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/TIMESERIES/TS134 (Group) ''\n", "/TIMESERIES/TS134/table (Table(366,)) ''\n", " description := {\n", @@ -1259,8 +1371,8 @@ " chunkshape := (4096,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"values\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/TIMESERIES/TS135 (Group) ''\n", "/TIMESERIES/TS135/table (Table(366,)) ''\n", " description := {\n", @@ -1270,8 +1382,8 @@ " chunkshape := (4096,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"values\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/TIMESERIES/TS136 (Group) ''\n", "/TIMESERIES/TS136/table (Table(366,)) ''\n", " description := {\n", @@ -1281,8 +1393,8 @@ " chunkshape := (4096,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"values\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/TIMESERIES/TS140 (Group) ''\n", "/TIMESERIES/TS140/table (Table(366,)) ''\n", " description := {\n", @@ -1292,10 +1404,10 @@ " chunkshape := (4096,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"values\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"values\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RUN_INFO/LOGFILE (Group) ''\n", - "/RUN_INFO/LOGFILE/table (Table(63,)) ''\n", + "/RUN_INFO/LOGFILE/table (Table(70,)) ''\n", " description := {\n", " \"index\": Int64Col(shape=(), dflt=0, pos=0),\n", " \"logfile\": StringCol(itemsize=156, shape=(), dflt=b'', pos=1)}\n", @@ -1303,19 +1415,19 @@ " chunkshape := (399,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"logfile\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"logfile\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RUN_INFO/VERSIONS (Group) ''\n", "/RUN_INFO/VERSIONS/table (Table(10,)) ''\n", " description := {\n", " \"index\": StringCol(itemsize=10, shape=(), dflt=b'', pos=0),\n", - " \"version\": StringCol(itemsize=84, shape=(), dflt=b'', pos=1)}\n", + " \"version\": StringCol(itemsize=51, shape=(), dflt=b'', pos=1)}\n", " byteorder := 'irrelevant'\n", - " chunkshape := (697,)\n", + " chunkshape := (1074,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"version\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"version\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/IMPLND_I001 (Group) ''\n", "/RESULTS/PERLND_P001 (Group) ''\n", "/RESULTS/RCHRES_R001 (Group) ''\n", @@ -1337,13 +1449,13 @@ " chunkshape := (2048,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_COADDR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_COADEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_COADWT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_CON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_ICON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_ROCON\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_COADDR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_COADEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_COADWT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_CON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_ICON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_ROCON\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R005/GQUAL (Group) ''\n", "/RESULTS/RCHRES_R005/GQUAL/table (Table(8784,)) ''\n", " description := {\n", @@ -1414,69 +1526,69 @@ " chunkshape := (256,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DSQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DSQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DSQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DSQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_GQADDR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_GQADEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_GQADWT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_IDQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ISQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ISQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ISQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ISQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_PDQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RDQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RODQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ROSQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ROSQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ROSQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ROSQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RRQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL10\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL8\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL9\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_TIQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_TROQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DSQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DSQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DSQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DSQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_GQADDR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_GQADEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_GQADWT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_IDQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ISQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ISQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ISQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ISQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_PDQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RDQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RODQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ROSQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ROSQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ROSQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ROSQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RRQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_TIQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_TROQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R005/HTRCH (Group) ''\n", "/RESULTS/RCHRES_R005/HTRCH/table (Table(8784,)) ''\n", " description := {\n", @@ -1497,48 +1609,58 @@ " chunkshape := (1170,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AIRTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"HTEXCH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IHEAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QBED\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QCON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QEVAP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QLONGW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QPREC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QSOLAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QTOTAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROHEAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TW\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AIRTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HTEXCH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IHEAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QBED\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QCON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QEVAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QLONGW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QPREC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QSOLAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QTOTAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROHEAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TW\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R005/HYDR (Group) ''\n", "/RESULTS/RCHRES_R005/HYDR/table (Table(8784,)) ''\n", " description := {\n", " \"index\": Int64Col(shape=(), dflt=0, pos=0),\n", - " \"DEP\": Float32Col(shape=(), dflt=0.0, pos=1),\n", - " \"IVOL\": Float32Col(shape=(), dflt=0.0, pos=2),\n", - " \"PRSUPY\": Float32Col(shape=(), dflt=0.0, pos=3),\n", - " \"RO\": Float32Col(shape=(), dflt=0.0, pos=4),\n", - " \"ROVOL\": Float32Col(shape=(), dflt=0.0, pos=5),\n", - " \"SAREA\": Float32Col(shape=(), dflt=0.0, pos=6),\n", - " \"TAU\": Float32Col(shape=(), dflt=0.0, pos=7),\n", - " \"USTAR\": Float32Col(shape=(), dflt=0.0, pos=8),\n", - " \"VOL\": Float32Col(shape=(), dflt=0.0, pos=9),\n", - " \"VOLEV\": Float32Col(shape=(), dflt=0.0, pos=10)}\n", + " \"AVDEP\": Float32Col(shape=(), dflt=0.0, pos=1),\n", + " \"AVVEL\": Float32Col(shape=(), dflt=0.0, pos=2),\n", + " \"DEP\": Float32Col(shape=(), dflt=0.0, pos=3),\n", + " \"HRAD\": Float32Col(shape=(), dflt=0.0, pos=4),\n", + " \"IVOL\": Float32Col(shape=(), dflt=0.0, pos=5),\n", + " \"POTEV\": Float32Col(shape=(), dflt=0.0, pos=6),\n", + " \"PRSUPY\": Float32Col(shape=(), dflt=0.0, pos=7),\n", + " \"RO\": Float32Col(shape=(), dflt=0.0, pos=8),\n", + " \"ROVOL\": Float32Col(shape=(), dflt=0.0, pos=9),\n", + " \"SAREA\": Float32Col(shape=(), dflt=0.0, pos=10),\n", + " \"TAU\": Float32Col(shape=(), dflt=0.0, pos=11),\n", + " \"TWID\": Float32Col(shape=(), dflt=0.0, pos=12),\n", + " \"USTAR\": Float32Col(shape=(), dflt=0.0, pos=13),\n", + " \"VOL\": Float32Col(shape=(), dflt=0.0, pos=14),\n", + " \"VOLEV\": Float32Col(shape=(), dflt=0.0, pos=15)}\n", " byteorder := 'little'\n", - " chunkshape := (1365,)\n", + " chunkshape := (963,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PRSUPY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SAREA\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TAU\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"USTAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VOLEV\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AVDEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AVVEL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HRAD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"POTEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PRSUPY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SAREA\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TAU\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TWID\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"USTAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VOLEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R005/NUTRX (Group) ''\n", "/RESULTS/RCHRES_R005/NUTRX/table (Table(8784,)) ''\n", " description := {\n", @@ -1613,73 +1735,73 @@ " chunkshape := (240,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INH4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISNH41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISNH42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISNH43\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISPO41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISPO42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISPO43\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NH3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NH4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADDR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADDR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADDR3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADEP1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADEP2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADEP3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADWT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADWT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADWT3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_BALNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_BODNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_DENNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_NITNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_PHYNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_TOTNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_ZOONO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_BALTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_BNRTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_BODTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_NITTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_PHYTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_TOTTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_VOLNH3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_ZOOTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF6_NITNO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF6_TOTNO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_BALPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_BNRPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_BODPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_PHYPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_TOTPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_ZOOPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNH3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNH4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF4\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INH4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISNH41\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISNH42\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISNH43\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISPO41\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISPO42\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISPO43\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NH3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NH4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADDR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADDR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADDR3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADEP1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADEP2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADEP3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADWT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADWT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADWT3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_BALNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_BODNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_DENNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_NITNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_PHYNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_TOTNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_ZOONO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_BALTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_BNRTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_BODTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_NITTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_PHYTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_TOTTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_VOLNH3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_ZOOTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF6_NITNO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF6_TOTNO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_BALPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_BNRPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_BODPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_PHYPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_TOTPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_ZOOPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNH3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNH4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF4\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R005/OXRX (Group) ''\n", "/RESULTS/RCHRES_R005/OXRX/table (Table(8784,)) ''\n", " description := {\n", @@ -1710,29 +1832,29 @@ " chunkshape := (682,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IBOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IDOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_BALG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_BENDO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_DEC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_NITR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_PHYT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_REAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_TOTAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_BALG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_BENR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_DEC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_PHYT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_SNK\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_TOTAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SATDO\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IBOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IDOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_BALG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_BENDO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_DEC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_NITR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_PHYT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_REAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_TOTAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_BALG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_BENR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_DEC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_PHYT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_SNK\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_TOTAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SATDO\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R005/PHCARB (Group) ''\n", "/RESULTS/RCHRES_R005/PHCARB/table (Table(8784,)) ''\n", " description := {\n", @@ -1758,24 +1880,24 @@ " chunkshape := (862,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ICO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ITIC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OCO21\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OTIC1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_BGRCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_BRECO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_DECCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_INVCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_PHYCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_TOTCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_ZOOCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTIC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SATCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TIC\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ICO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ITIC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OCO21\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OTIC1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_BGRCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_BRECO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_DECCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_INVCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_PHYCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_TOTCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_ZOOCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTIC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SATCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TIC\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R005/PLANK (Group) ''\n", "/RESULTS/RCHRES_R005/PLANK/table (Table(8784,)) ''\n", " description := {\n", @@ -1854,77 +1976,77 @@ " chunkshape := (227,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BALCLA1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BENAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHYCLA\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHYTO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_DTBORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_DTPORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_DTZORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_SNKORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_TOTORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_DTHPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_GROPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_SNKPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_TOTPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_ZOOPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF6_DTHZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF6_GROZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF6_TOTZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF7_DTHBEN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF7_GROBEN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_DTBORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_DTPORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_DTZORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_SNKORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_TOTORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_DTBORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_DTPORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_DTZORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_SNKORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_TOTORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_PHYT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADDR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADDR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADDR3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADEP1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADEP2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADEP3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADWT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADWT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADWT3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"POTBOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TBENAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TBENAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BALCLA1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BENAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYCLA\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYTO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_DTBORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_DTPORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_DTZORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_SNKORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_TOTORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_DTHPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_GROPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_SNKPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_TOTPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_ZOOPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF6_DTHZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF6_GROZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF6_TOTZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF7_DTHBEN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF7_GROBEN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_DTBORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_DTPORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_DTZORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_SNKORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_TOTORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_DTBORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_DTPORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_DTZORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_SNKORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_TOTORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_PHYT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADDR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADDR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADDR3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADEP1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADEP2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADEP3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADWT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADWT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADWT3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"POTBOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TBENAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TBENAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R005/SEDTRN (Group) ''\n", "/RESULTS/RCHRES_R005/SEDTRN/table (Table(8784,)) ''\n", " description := {\n", @@ -1962,36 +2084,36 @@ " chunkshape := (528,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BEDDEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED10\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED8\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED9\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BEDDEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R004/CONS (Group) ''\n", "/RESULTS/RCHRES_R004/CONS/table (Table(8784,)) ''\n", " description := {\n", @@ -2006,13 +2128,13 @@ " chunkshape := (2048,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_COADDR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_COADEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_COADWT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_CON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_ICON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_ROCON\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_COADDR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_COADEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_COADWT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_CON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_ICON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_ROCON\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R004/GQUAL (Group) ''\n", "/RESULTS/RCHRES_R004/GQUAL/table (Table(8784,)) ''\n", " description := {\n", @@ -2083,69 +2205,69 @@ " chunkshape := (256,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DSQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DSQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DSQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DSQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_GQADDR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_GQADEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_GQADWT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_IDQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ISQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ISQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ISQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ISQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_PDQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RDQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RODQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ROSQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ROSQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ROSQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ROSQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RRQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL10\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL8\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL9\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_TIQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_TROQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DSQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DSQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DSQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DSQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_GQADDR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_GQADEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_GQADWT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_IDQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ISQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ISQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ISQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ISQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_PDQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RDQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RODQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ROSQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ROSQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ROSQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ROSQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RRQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_TIQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_TROQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R004/HTRCH (Group) ''\n", "/RESULTS/RCHRES_R004/HTRCH/table (Table(8784,)) ''\n", " description := {\n", @@ -2166,48 +2288,58 @@ " chunkshape := (1170,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AIRTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"HTEXCH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IHEAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QBED\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QCON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QEVAP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QLONGW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QPREC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QSOLAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QTOTAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROHEAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TW\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AIRTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HTEXCH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IHEAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QBED\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QCON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QEVAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QLONGW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QPREC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QSOLAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QTOTAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROHEAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TW\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R004/HYDR (Group) ''\n", "/RESULTS/RCHRES_R004/HYDR/table (Table(8784,)) ''\n", " description := {\n", " \"index\": Int64Col(shape=(), dflt=0, pos=0),\n", - " \"DEP\": Float32Col(shape=(), dflt=0.0, pos=1),\n", - " \"IVOL\": Float32Col(shape=(), dflt=0.0, pos=2),\n", - " \"PRSUPY\": Float32Col(shape=(), dflt=0.0, pos=3),\n", - " \"RO\": Float32Col(shape=(), dflt=0.0, pos=4),\n", - " \"ROVOL\": Float32Col(shape=(), dflt=0.0, pos=5),\n", - " \"SAREA\": Float32Col(shape=(), dflt=0.0, pos=6),\n", - " \"TAU\": Float32Col(shape=(), dflt=0.0, pos=7),\n", - " \"USTAR\": Float32Col(shape=(), dflt=0.0, pos=8),\n", - " \"VOL\": Float32Col(shape=(), dflt=0.0, pos=9),\n", - " \"VOLEV\": Float32Col(shape=(), dflt=0.0, pos=10)}\n", + " \"AVDEP\": Float32Col(shape=(), dflt=0.0, pos=1),\n", + " \"AVVEL\": Float32Col(shape=(), dflt=0.0, pos=2),\n", + " \"DEP\": Float32Col(shape=(), dflt=0.0, pos=3),\n", + " \"HRAD\": Float32Col(shape=(), dflt=0.0, pos=4),\n", + " \"IVOL\": Float32Col(shape=(), dflt=0.0, pos=5),\n", + " \"POTEV\": Float32Col(shape=(), dflt=0.0, pos=6),\n", + " \"PRSUPY\": Float32Col(shape=(), dflt=0.0, pos=7),\n", + " \"RO\": Float32Col(shape=(), dflt=0.0, pos=8),\n", + " \"ROVOL\": Float32Col(shape=(), dflt=0.0, pos=9),\n", + " \"SAREA\": Float32Col(shape=(), dflt=0.0, pos=10),\n", + " \"TAU\": Float32Col(shape=(), dflt=0.0, pos=11),\n", + " \"TWID\": Float32Col(shape=(), dflt=0.0, pos=12),\n", + " \"USTAR\": Float32Col(shape=(), dflt=0.0, pos=13),\n", + " \"VOL\": Float32Col(shape=(), dflt=0.0, pos=14),\n", + " \"VOLEV\": Float32Col(shape=(), dflt=0.0, pos=15)}\n", " byteorder := 'little'\n", - " chunkshape := (1365,)\n", + " chunkshape := (963,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PRSUPY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SAREA\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TAU\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"USTAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VOLEV\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AVDEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AVVEL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HRAD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"POTEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PRSUPY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SAREA\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TAU\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TWID\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"USTAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VOLEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R004/NUTRX (Group) ''\n", "/RESULTS/RCHRES_R004/NUTRX/table (Table(8784,)) ''\n", " description := {\n", @@ -2282,73 +2414,73 @@ " chunkshape := (240,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INH4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISNH41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISNH42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISNH43\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISPO41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISPO42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISPO43\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NH3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NH4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADDR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADDR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADDR3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADEP1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADEP2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADEP3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADWT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADWT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADWT3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_BALNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_BODNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_DENNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_NITNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_PHYNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_TOTNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_ZOONO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_BALTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_BNRTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_BODTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_NITTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_PHYTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_TOTTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_VOLNH3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_ZOOTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF6_NITNO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF6_TOTNO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_BALPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_BNRPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_BODPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_PHYPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_TOTPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_ZOOPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNH3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNH4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF4\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INH4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISNH41\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISNH42\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISNH43\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISPO41\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISPO42\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISPO43\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NH3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NH4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADDR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADDR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADDR3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADEP1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADEP2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADEP3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADWT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADWT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADWT3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_BALNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_BODNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_DENNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_NITNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_PHYNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_TOTNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_ZOONO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_BALTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_BNRTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_BODTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_NITTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_PHYTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_TOTTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_VOLNH3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_ZOOTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF6_NITNO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF6_TOTNO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_BALPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_BNRPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_BODPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_PHYPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_TOTPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_ZOOPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNH3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNH4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF4\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R004/OXRX (Group) ''\n", "/RESULTS/RCHRES_R004/OXRX/table (Table(8784,)) ''\n", " description := {\n", @@ -2379,29 +2511,29 @@ " chunkshape := (682,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IBOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IDOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_BALG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_BENDO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_DEC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_NITR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_PHYT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_REAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_TOTAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_BALG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_BENR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_DEC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_PHYT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_SNK\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_TOTAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SATDO\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IBOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IDOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_BALG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_BENDO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_DEC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_NITR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_PHYT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_REAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_TOTAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_BALG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_BENR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_DEC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_PHYT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_SNK\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_TOTAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SATDO\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R004/PHCARB (Group) ''\n", "/RESULTS/RCHRES_R004/PHCARB/table (Table(8784,)) ''\n", " description := {\n", @@ -2427,24 +2559,24 @@ " chunkshape := (862,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ICO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ITIC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OCO21\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OTIC1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_BGRCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_BRECO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_DECCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_INVCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_PHYCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_TOTCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_ZOOCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTIC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SATCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TIC\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ICO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ITIC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OCO21\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OTIC1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_BGRCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_BRECO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_DECCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_INVCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_PHYCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_TOTCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_ZOOCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTIC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SATCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TIC\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R004/PLANK (Group) ''\n", "/RESULTS/RCHRES_R004/PLANK/table (Table(8784,)) ''\n", " description := {\n", @@ -2523,77 +2655,77 @@ " chunkshape := (227,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BALCLA1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BENAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHYCLA\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHYTO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_DTBORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_DTPORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_DTZORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_SNKORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_TOTORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_DTHPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_GROPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_SNKPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_TOTPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_ZOOPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF6_DTHZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF6_GROZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF6_TOTZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF7_DTHBEN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF7_GROBEN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_DTBORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_DTPORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_DTZORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_SNKORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_TOTORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_DTBORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_DTPORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_DTZORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_SNKORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_TOTORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_PHYT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADDR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADDR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADDR3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADEP1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADEP2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADEP3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADWT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADWT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADWT3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"POTBOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TBENAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TBENAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BALCLA1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BENAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYCLA\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYTO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_DTBORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_DTPORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_DTZORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_SNKORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_TOTORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_DTHPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_GROPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_SNKPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_TOTPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_ZOOPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF6_DTHZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF6_GROZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF6_TOTZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF7_DTHBEN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF7_GROBEN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_DTBORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_DTPORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_DTZORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_SNKORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_TOTORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_DTBORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_DTPORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_DTZORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_SNKORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_TOTORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_PHYT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADDR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADDR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADDR3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADEP1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADEP2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADEP3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADWT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADWT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADWT3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"POTBOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TBENAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TBENAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R004/SEDTRN (Group) ''\n", "/RESULTS/RCHRES_R004/SEDTRN/table (Table(8784,)) ''\n", " description := {\n", @@ -2631,36 +2763,36 @@ " chunkshape := (528,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BEDDEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED10\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED8\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED9\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BEDDEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R003/CONS (Group) ''\n", "/RESULTS/RCHRES_R003/CONS/table (Table(8784,)) ''\n", " description := {\n", @@ -2675,13 +2807,13 @@ " chunkshape := (2048,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_COADDR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_COADEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_COADWT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_CON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_ICON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_ROCON\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_COADDR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_COADEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_COADWT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_CON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_ICON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_ROCON\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R003/GQUAL (Group) ''\n", "/RESULTS/RCHRES_R003/GQUAL/table (Table(8784,)) ''\n", " description := {\n", @@ -2752,69 +2884,69 @@ " chunkshape := (256,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DSQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DSQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DSQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DSQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_GQADDR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_GQADEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_GQADWT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_IDQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ISQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ISQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ISQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ISQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_PDQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RDQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RODQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ROSQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ROSQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ROSQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ROSQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RRQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL10\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL8\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL9\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_TIQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_TROQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DSQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DSQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DSQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DSQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_GQADDR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_GQADEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_GQADWT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_IDQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ISQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ISQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ISQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ISQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_PDQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RDQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RODQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ROSQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ROSQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ROSQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ROSQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RRQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_TIQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_TROQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R003/HTRCH (Group) ''\n", "/RESULTS/RCHRES_R003/HTRCH/table (Table(8784,)) ''\n", " description := {\n", @@ -2835,48 +2967,58 @@ " chunkshape := (1170,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AIRTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"HTEXCH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IHEAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QBED\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QCON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QEVAP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QLONGW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QPREC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QSOLAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QTOTAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROHEAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TW\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AIRTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HTEXCH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IHEAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QBED\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QCON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QEVAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QLONGW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QPREC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QSOLAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QTOTAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROHEAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TW\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R003/HYDR (Group) ''\n", "/RESULTS/RCHRES_R003/HYDR/table (Table(8784,)) ''\n", " description := {\n", " \"index\": Int64Col(shape=(), dflt=0, pos=0),\n", - " \"DEP\": Float32Col(shape=(), dflt=0.0, pos=1),\n", - " \"IVOL\": Float32Col(shape=(), dflt=0.0, pos=2),\n", - " \"PRSUPY\": Float32Col(shape=(), dflt=0.0, pos=3),\n", - " \"RO\": Float32Col(shape=(), dflt=0.0, pos=4),\n", - " \"ROVOL\": Float32Col(shape=(), dflt=0.0, pos=5),\n", - " \"SAREA\": Float32Col(shape=(), dflt=0.0, pos=6),\n", - " \"TAU\": Float32Col(shape=(), dflt=0.0, pos=7),\n", - " \"USTAR\": Float32Col(shape=(), dflt=0.0, pos=8),\n", - " \"VOL\": Float32Col(shape=(), dflt=0.0, pos=9),\n", - " \"VOLEV\": Float32Col(shape=(), dflt=0.0, pos=10)}\n", + " \"AVDEP\": Float32Col(shape=(), dflt=0.0, pos=1),\n", + " \"AVVEL\": Float32Col(shape=(), dflt=0.0, pos=2),\n", + " \"DEP\": Float32Col(shape=(), dflt=0.0, pos=3),\n", + " \"HRAD\": Float32Col(shape=(), dflt=0.0, pos=4),\n", + " \"IVOL\": Float32Col(shape=(), dflt=0.0, pos=5),\n", + " \"POTEV\": Float32Col(shape=(), dflt=0.0, pos=6),\n", + " \"PRSUPY\": Float32Col(shape=(), dflt=0.0, pos=7),\n", + " \"RO\": Float32Col(shape=(), dflt=0.0, pos=8),\n", + " \"ROVOL\": Float32Col(shape=(), dflt=0.0, pos=9),\n", + " \"SAREA\": Float32Col(shape=(), dflt=0.0, pos=10),\n", + " \"TAU\": Float32Col(shape=(), dflt=0.0, pos=11),\n", + " \"TWID\": Float32Col(shape=(), dflt=0.0, pos=12),\n", + " \"USTAR\": Float32Col(shape=(), dflt=0.0, pos=13),\n", + " \"VOL\": Float32Col(shape=(), dflt=0.0, pos=14),\n", + " \"VOLEV\": Float32Col(shape=(), dflt=0.0, pos=15)}\n", " byteorder := 'little'\n", - " chunkshape := (1365,)\n", + " chunkshape := (963,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PRSUPY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SAREA\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TAU\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"USTAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VOLEV\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AVDEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AVVEL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HRAD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"POTEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PRSUPY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SAREA\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TAU\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TWID\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"USTAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VOLEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R003/NUTRX (Group) ''\n", "/RESULTS/RCHRES_R003/NUTRX/table (Table(8784,)) ''\n", " description := {\n", @@ -2951,73 +3093,73 @@ " chunkshape := (240,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INH4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISNH41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISNH42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISNH43\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISPO41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISPO42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISPO43\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NH3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NH4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADDR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADDR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADDR3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADEP1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADEP2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADEP3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADWT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADWT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADWT3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_BALNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_BODNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_DENNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_NITNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_PHYNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_TOTNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_ZOONO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_BALTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_BNRTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_BODTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_NITTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_PHYTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_TOTTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_VOLNH3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_ZOOTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF6_NITNO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF6_TOTNO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_BALPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_BNRPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_BODPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_PHYPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_TOTPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_ZOOPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNH3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNH4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF4\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INH4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISNH41\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISNH42\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISNH43\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISPO41\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISPO42\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISPO43\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NH3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NH4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADDR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADDR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADDR3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADEP1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADEP2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADEP3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADWT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADWT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADWT3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_BALNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_BODNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_DENNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_NITNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_PHYNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_TOTNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_ZOONO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_BALTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_BNRTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_BODTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_NITTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_PHYTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_TOTTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_VOLNH3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_ZOOTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF6_NITNO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF6_TOTNO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_BALPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_BNRPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_BODPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_PHYPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_TOTPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_ZOOPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNH3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNH4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF4\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R003/OXRX (Group) ''\n", "/RESULTS/RCHRES_R003/OXRX/table (Table(8784,)) ''\n", " description := {\n", @@ -3048,29 +3190,29 @@ " chunkshape := (682,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IBOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IDOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_BALG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_BENDO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_DEC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_NITR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_PHYT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_REAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_TOTAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_BALG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_BENR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_DEC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_PHYT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_SNK\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_TOTAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SATDO\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IBOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IDOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_BALG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_BENDO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_DEC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_NITR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_PHYT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_REAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_TOTAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_BALG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_BENR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_DEC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_PHYT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_SNK\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_TOTAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SATDO\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R003/PHCARB (Group) ''\n", "/RESULTS/RCHRES_R003/PHCARB/table (Table(8784,)) ''\n", " description := {\n", @@ -3096,24 +3238,24 @@ " chunkshape := (862,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ICO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ITIC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OCO21\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OTIC1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_BGRCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_BRECO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_DECCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_INVCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_PHYCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_TOTCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_ZOOCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTIC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SATCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TIC\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ICO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ITIC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OCO21\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OTIC1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_BGRCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_BRECO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_DECCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_INVCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_PHYCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_TOTCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_ZOOCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTIC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SATCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TIC\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R003/PLANK (Group) ''\n", "/RESULTS/RCHRES_R003/PLANK/table (Table(8784,)) ''\n", " description := {\n", @@ -3192,77 +3334,77 @@ " chunkshape := (227,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BALCLA1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BENAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHYCLA\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHYTO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_DTBORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_DTPORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_DTZORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_SNKORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_TOTORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_DTHPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_GROPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_SNKPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_TOTPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_ZOOPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF6_DTHZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF6_GROZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF6_TOTZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF7_DTHBEN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF7_GROBEN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_DTBORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_DTPORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_DTZORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_SNKORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_TOTORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_DTBORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_DTPORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_DTZORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_SNKORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_TOTORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_PHYT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADDR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADDR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADDR3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADEP1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADEP2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADEP3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADWT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADWT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADWT3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"POTBOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TBENAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TBENAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BALCLA1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BENAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYCLA\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYTO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_DTBORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_DTPORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_DTZORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_SNKORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_TOTORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_DTHPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_GROPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_SNKPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_TOTPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_ZOOPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF6_DTHZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF6_GROZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF6_TOTZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF7_DTHBEN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF7_GROBEN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_DTBORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_DTPORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_DTZORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_SNKORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_TOTORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_DTBORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_DTPORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_DTZORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_SNKORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_TOTORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_PHYT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADDR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADDR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADDR3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADEP1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADEP2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADEP3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADWT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADWT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADWT3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"POTBOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TBENAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TBENAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R003/SEDTRN (Group) ''\n", "/RESULTS/RCHRES_R003/SEDTRN/table (Table(8784,)) ''\n", " description := {\n", @@ -3300,36 +3442,36 @@ " chunkshape := (528,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BEDDEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED10\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED8\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED9\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BEDDEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R002/CONS (Group) ''\n", "/RESULTS/RCHRES_R002/CONS/table (Table(8784,)) ''\n", " description := {\n", @@ -3344,13 +3486,13 @@ " chunkshape := (2048,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_COADDR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_COADEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_COADWT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_CON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_ICON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_ROCON\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_COADDR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_COADEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_COADWT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_CON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_ICON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_ROCON\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R002/GQUAL (Group) ''\n", "/RESULTS/RCHRES_R002/GQUAL/table (Table(8784,)) ''\n", " description := {\n", @@ -3421,69 +3563,69 @@ " chunkshape := (256,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DSQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DSQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DSQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DSQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_GQADDR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_GQADEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_GQADWT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_IDQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ISQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ISQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ISQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ISQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_PDQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RDQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RODQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ROSQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ROSQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ROSQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ROSQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RRQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL10\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL8\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL9\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_TIQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_TROQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DSQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DSQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DSQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DSQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_GQADDR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_GQADEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_GQADWT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_IDQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ISQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ISQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ISQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ISQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_PDQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RDQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RODQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ROSQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ROSQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ROSQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ROSQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RRQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_TIQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_TROQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R002/HTRCH (Group) ''\n", "/RESULTS/RCHRES_R002/HTRCH/table (Table(8784,)) ''\n", " description := {\n", @@ -3504,48 +3646,58 @@ " chunkshape := (1170,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AIRTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"HTEXCH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IHEAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QBED\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QCON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QEVAP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QLONGW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QPREC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QSOLAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QTOTAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROHEAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TW\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AIRTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HTEXCH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IHEAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QBED\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QCON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QEVAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QLONGW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QPREC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QSOLAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QTOTAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROHEAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TW\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R002/HYDR (Group) ''\n", "/RESULTS/RCHRES_R002/HYDR/table (Table(8784,)) ''\n", " description := {\n", " \"index\": Int64Col(shape=(), dflt=0, pos=0),\n", - " \"DEP\": Float32Col(shape=(), dflt=0.0, pos=1),\n", - " \"IVOL\": Float32Col(shape=(), dflt=0.0, pos=2),\n", - " \"PRSUPY\": Float32Col(shape=(), dflt=0.0, pos=3),\n", - " \"RO\": Float32Col(shape=(), dflt=0.0, pos=4),\n", - " \"ROVOL\": Float32Col(shape=(), dflt=0.0, pos=5),\n", - " \"SAREA\": Float32Col(shape=(), dflt=0.0, pos=6),\n", - " \"TAU\": Float32Col(shape=(), dflt=0.0, pos=7),\n", - " \"USTAR\": Float32Col(shape=(), dflt=0.0, pos=8),\n", - " \"VOL\": Float32Col(shape=(), dflt=0.0, pos=9),\n", - " \"VOLEV\": Float32Col(shape=(), dflt=0.0, pos=10)}\n", + " \"AVDEP\": Float32Col(shape=(), dflt=0.0, pos=1),\n", + " \"AVVEL\": Float32Col(shape=(), dflt=0.0, pos=2),\n", + " \"DEP\": Float32Col(shape=(), dflt=0.0, pos=3),\n", + " \"HRAD\": Float32Col(shape=(), dflt=0.0, pos=4),\n", + " \"IVOL\": Float32Col(shape=(), dflt=0.0, pos=5),\n", + " \"POTEV\": Float32Col(shape=(), dflt=0.0, pos=6),\n", + " \"PRSUPY\": Float32Col(shape=(), dflt=0.0, pos=7),\n", + " \"RO\": Float32Col(shape=(), dflt=0.0, pos=8),\n", + " \"ROVOL\": Float32Col(shape=(), dflt=0.0, pos=9),\n", + " \"SAREA\": Float32Col(shape=(), dflt=0.0, pos=10),\n", + " \"TAU\": Float32Col(shape=(), dflt=0.0, pos=11),\n", + " \"TWID\": Float32Col(shape=(), dflt=0.0, pos=12),\n", + " \"USTAR\": Float32Col(shape=(), dflt=0.0, pos=13),\n", + " \"VOL\": Float32Col(shape=(), dflt=0.0, pos=14),\n", + " \"VOLEV\": Float32Col(shape=(), dflt=0.0, pos=15)}\n", " byteorder := 'little'\n", - " chunkshape := (1365,)\n", + " chunkshape := (963,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PRSUPY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SAREA\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TAU\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"USTAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VOLEV\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AVDEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AVVEL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HRAD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"POTEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PRSUPY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SAREA\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TAU\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TWID\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"USTAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VOLEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R002/NUTRX (Group) ''\n", "/RESULTS/RCHRES_R002/NUTRX/table (Table(8784,)) ''\n", " description := {\n", @@ -3620,73 +3772,73 @@ " chunkshape := (240,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INH4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISNH41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISNH42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISNH43\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISPO41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISPO42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISPO43\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NH3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NH4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADDR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADDR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADDR3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADEP1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADEP2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADEP3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADWT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADWT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADWT3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_BALNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_BODNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_DENNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_NITNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_PHYNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_TOTNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_ZOONO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_BALTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_BNRTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_BODTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_NITTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_PHYTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_TOTTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_VOLNH3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_ZOOTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF6_NITNO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF6_TOTNO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_BALPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_BNRPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_BODPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_PHYPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_TOTPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_ZOOPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNH3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNH4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF4\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INH4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISNH41\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISNH42\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISNH43\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISPO41\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISPO42\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISPO43\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NH3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NH4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADDR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADDR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADDR3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADEP1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADEP2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADEP3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADWT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADWT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADWT3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_BALNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_BODNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_DENNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_NITNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_PHYNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_TOTNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_ZOONO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_BALTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_BNRTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_BODTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_NITTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_PHYTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_TOTTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_VOLNH3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_ZOOTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF6_NITNO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF6_TOTNO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_BALPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_BNRPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_BODPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_PHYPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_TOTPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_ZOOPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNH3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNH4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF4\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R002/OXRX (Group) ''\n", "/RESULTS/RCHRES_R002/OXRX/table (Table(8784,)) ''\n", " description := {\n", @@ -3717,29 +3869,29 @@ " chunkshape := (682,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IBOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IDOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_BALG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_BENDO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_DEC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_NITR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_PHYT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_REAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_TOTAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_BALG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_BENR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_DEC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_PHYT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_SNK\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_TOTAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SATDO\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IBOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IDOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_BALG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_BENDO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_DEC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_NITR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_PHYT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_REAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_TOTAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_BALG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_BENR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_DEC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_PHYT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_SNK\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_TOTAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SATDO\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R002/PHCARB (Group) ''\n", "/RESULTS/RCHRES_R002/PHCARB/table (Table(8784,)) ''\n", " description := {\n", @@ -3765,24 +3917,24 @@ " chunkshape := (862,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ICO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ITIC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OCO21\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OTIC1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_BGRCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_BRECO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_DECCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_INVCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_PHYCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_TOTCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_ZOOCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTIC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SATCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TIC\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ICO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ITIC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OCO21\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OTIC1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_BGRCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_BRECO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_DECCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_INVCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_PHYCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_TOTCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_ZOOCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTIC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SATCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TIC\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R002/PLANK (Group) ''\n", "/RESULTS/RCHRES_R002/PLANK/table (Table(8784,)) ''\n", " description := {\n", @@ -3861,77 +4013,77 @@ " chunkshape := (227,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BALCLA1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BENAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHYCLA\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHYTO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_DTBORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_DTPORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_DTZORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_SNKORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_TOTORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_DTHPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_GROPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_SNKPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_TOTPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_ZOOPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF6_DTHZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF6_GROZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF6_TOTZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF7_DTHBEN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF7_GROBEN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_DTBORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_DTPORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_DTZORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_SNKORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_TOTORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_DTBORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_DTPORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_DTZORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_SNKORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_TOTORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_PHYT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADDR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADDR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADDR3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADEP1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADEP2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADEP3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADWT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADWT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADWT3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"POTBOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TBENAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TBENAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BALCLA1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BENAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYCLA\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYTO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_DTBORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_DTPORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_DTZORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_SNKORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_TOTORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_DTHPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_GROPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_SNKPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_TOTPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_ZOOPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF6_DTHZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF6_GROZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF6_TOTZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF7_DTHBEN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF7_GROBEN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_DTBORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_DTPORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_DTZORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_SNKORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_TOTORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_DTBORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_DTPORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_DTZORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_SNKORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_TOTORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_PHYT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADDR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADDR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADDR3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADEP1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADEP2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADEP3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADWT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADWT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADWT3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"POTBOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TBENAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TBENAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R002/SEDTRN (Group) ''\n", "/RESULTS/RCHRES_R002/SEDTRN/table (Table(8784,)) ''\n", " description := {\n", @@ -3969,36 +4121,36 @@ " chunkshape := (528,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BEDDEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED10\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED8\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED9\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BEDDEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R001/CONS (Group) ''\n", "/RESULTS/RCHRES_R001/CONS/table (Table(8784,)) ''\n", " description := {\n", @@ -4015,15 +4167,15 @@ " chunkshape := (1638,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_COADDR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_COADEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_COADWT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_CON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_ICON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_OCON1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_OCON2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS1_ROCON\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_COADDR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_COADEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_COADWT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_CON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_ICON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_OCON1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_OCON2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS1_ROCON\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R001/GQUAL (Group) ''\n", "/RESULTS/RCHRES_R001/GQUAL/table (Table(8784,)) ''\n", " description := {\n", @@ -4104,79 +4256,79 @@ " chunkshape := (221,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ADQAL7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DDQAL7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DSQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DSQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DSQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_DSQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_GQADDR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_GQADEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_GQADWT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_IDQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ISQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ISQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ISQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ISQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ODQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ODQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_OSQAL11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_OSQAL12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_OSQAL21\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_OSQAL22\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_OSQAL31\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_OSQAL32\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_PDQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RDQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RODQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ROSQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ROSQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ROSQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_ROSQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RRQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL10\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL8\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_RSQAL9\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_SQDEC7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_TIQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_TOSQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_TOSQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL1_TROQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ADQAL7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DDQAL7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DSQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DSQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DSQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_DSQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_GQADDR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_GQADEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_GQADWT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_IDQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ISQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ISQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ISQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ISQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ODQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ODQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_OSQAL11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_OSQAL12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_OSQAL21\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_OSQAL22\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_OSQAL31\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_OSQAL32\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_PDQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RDQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RODQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ROSQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ROSQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ROSQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_ROSQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RRQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_RSQAL9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_SQDEC7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_TIQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_TOSQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_TOSQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL1_TROQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R001/HTRCH (Group) ''\n", "/RESULTS/RCHRES_R001/HTRCH/table (Table(8784,)) ''\n", " description := {\n", @@ -4199,58 +4351,68 @@ " chunkshape := (1024,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AIRTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"HTEXCH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IHEAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OHEAT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OHEAT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QBED\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QCON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QEVAP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QLONGW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QPREC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QSOLAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QTOTAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROHEAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TW\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AIRTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HTEXCH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IHEAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OHEAT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OHEAT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QBED\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QCON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QEVAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QLONGW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QPREC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QSOLAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QTOTAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROHEAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TW\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R001/HYDR (Group) ''\n", "/RESULTS/RCHRES_R001/HYDR/table (Table(8784,)) ''\n", " description := {\n", " \"index\": Int64Col(shape=(), dflt=0, pos=0),\n", - " \"DEP\": Float32Col(shape=(), dflt=0.0, pos=1),\n", - " \"IVOL\": Float32Col(shape=(), dflt=0.0, pos=2),\n", - " \"O1\": Float32Col(shape=(), dflt=0.0, pos=3),\n", - " \"O2\": Float32Col(shape=(), dflt=0.0, pos=4),\n", - " \"OVOL1\": Float32Col(shape=(), dflt=0.0, pos=5),\n", - " \"OVOL2\": Float32Col(shape=(), dflt=0.0, pos=6),\n", - " \"PRSUPY\": Float32Col(shape=(), dflt=0.0, pos=7),\n", - " \"RO\": Float32Col(shape=(), dflt=0.0, pos=8),\n", - " \"ROVOL\": Float32Col(shape=(), dflt=0.0, pos=9),\n", - " \"SAREA\": Float32Col(shape=(), dflt=0.0, pos=10),\n", - " \"TAU\": Float32Col(shape=(), dflt=0.0, pos=11),\n", - " \"USTAR\": Float32Col(shape=(), dflt=0.0, pos=12),\n", - " \"VOL\": Float32Col(shape=(), dflt=0.0, pos=13),\n", - " \"VOLEV\": Float32Col(shape=(), dflt=0.0, pos=14)}\n", + " \"AVDEP\": Float32Col(shape=(), dflt=0.0, pos=1),\n", + " \"AVVEL\": Float32Col(shape=(), dflt=0.0, pos=2),\n", + " \"DEP\": Float32Col(shape=(), dflt=0.0, pos=3),\n", + " \"HRAD\": Float32Col(shape=(), dflt=0.0, pos=4),\n", + " \"IVOL\": Float32Col(shape=(), dflt=0.0, pos=5),\n", + " \"O1\": Float32Col(shape=(), dflt=0.0, pos=6),\n", + " \"O2\": Float32Col(shape=(), dflt=0.0, pos=7),\n", + " \"OVOL1\": Float32Col(shape=(), dflt=0.0, pos=8),\n", + " \"OVOL2\": Float32Col(shape=(), dflt=0.0, pos=9),\n", + " \"POTEV\": Float32Col(shape=(), dflt=0.0, pos=10),\n", + " \"PRSUPY\": Float32Col(shape=(), dflt=0.0, pos=11),\n", + " \"RO\": Float32Col(shape=(), dflt=0.0, pos=12),\n", + " \"ROVOL\": Float32Col(shape=(), dflt=0.0, pos=13),\n", + " \"SAREA\": Float32Col(shape=(), dflt=0.0, pos=14),\n", + " \"TAU\": Float32Col(shape=(), dflt=0.0, pos=15),\n", + " \"TWID\": Float32Col(shape=(), dflt=0.0, pos=16),\n", + " \"USTAR\": Float32Col(shape=(), dflt=0.0, pos=17),\n", + " \"VOL\": Float32Col(shape=(), dflt=0.0, pos=18),\n", + " \"VOLEV\": Float32Col(shape=(), dflt=0.0, pos=19)}\n", " byteorder := 'little'\n", - " chunkshape := (1024,)\n", + " chunkshape := (780,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"O1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"O2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OVOL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OVOL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PRSUPY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SAREA\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TAU\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"USTAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VOLEV\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AVDEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AVVEL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HRAD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"O1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"O2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OVOL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OVOL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"POTEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PRSUPY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SAREA\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TAU\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TWID\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"USTAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VOLEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R001/NUTRX (Group) ''\n", "/RESULTS/RCHRES_R001/NUTRX/table (Table(8784,)) ''\n", " description := {\n", @@ -4333,81 +4495,81 @@ " chunkshape := (215,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INH4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISNH41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISNH42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISNH43\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISPO41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISPO42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISPO43\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NH3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NH4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADDR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADDR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADDR3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADEP1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADEP2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADEP3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADWT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADWT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADWT3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_BALNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_BODNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_DENNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_NITNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_PHYNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_TOTNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_ZOONO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_BALTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_BNRTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_BODTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_NITTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_PHYTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_TOTTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_VOLNH3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_ZOOTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF6_NITNO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF6_TOTNO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_BALPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_BNRPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_BODPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_PHYPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_TOTPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_ZOOPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF9_11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF9_12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF9_13\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF9_14\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF9_21\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF9_22\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF9_23\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF9_24\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNH3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNH4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF4\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INH4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISNH41\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISNH42\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISNH43\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISPO41\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISPO42\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISPO43\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NH3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NH4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADDR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADDR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADDR3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADEP1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADEP2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADEP3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADWT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADWT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADWT3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_BALNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_BODNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_DENNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_NITNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_PHYNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_TOTNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_ZOONO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_BALTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_BNRTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_BODTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_NITTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_PHYTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_TOTTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_VOLNH3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_ZOOTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF6_NITNO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF6_TOTNO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_BALPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_BNRPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_BODPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_PHYPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_TOTPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_ZOOPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF9_11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF9_12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF9_13\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF9_14\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF9_21\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF9_22\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF9_23\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF9_24\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNH3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNH4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF4\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R001/OXRX (Group) ''\n", "/RESULTS/RCHRES_R001/OXRX/table (Table(8784,)) ''\n", " description := {\n", @@ -4442,33 +4604,33 @@ " chunkshape := (585,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IBOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IDOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF2_11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF2_12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF2_21\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF2_22\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_BALG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_BENDO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_DEC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_NITR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_PHYT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_REAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_TOTAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_BALG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_BENR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_DEC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_PHYT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_SNK\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_TOTAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SATDO\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IBOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IDOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF2_11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF2_12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF2_21\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF2_22\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_BALG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_BENDO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_DEC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_NITR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_PHYT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_REAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_TOTAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_BALG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_BENR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_DEC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_PHYT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_SNK\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_TOTAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SATDO\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R001/PHCARB (Group) ''\n", "/RESULTS/RCHRES_R001/PHCARB/table (Table(8784,)) ''\n", " description := {\n", @@ -4496,26 +4658,26 @@ " chunkshape := (780,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ICO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ITIC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OCO21\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OCO22\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OTIC1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OTIC2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_BGRCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_BRECO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_DECCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_INVCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_PHYCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_TOTCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_ZOOCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTIC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SATCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TIC\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ICO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ITIC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OCO21\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OCO22\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OTIC1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OTIC2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_BGRCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_BRECO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_DECCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_INVCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_PHYCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_TOTCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_ZOOCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTIC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SATCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TIC\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R001/PLANK (Group) ''\n", "/RESULTS/RCHRES_R001/PLANK/table (Table(8784,)) ''\n", " description := {\n", @@ -4614,97 +4776,97 @@ " chunkshape := (178,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BALCLA1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BENAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHYCLA\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHYTO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_DTBORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_DTPORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_DTZORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_SNKORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_TOTORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF2_11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF2_12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF2_13\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF2_14\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF2_15\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF2_21\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF2_22\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF2_23\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF2_24\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF2_25\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_DTHPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_GROPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_SNKPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_TOTPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_ZOOPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF6_DTHZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF6_GROZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF6_TOTZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF7_DTHBEN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF7_GROBEN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_DTBORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_DTPORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_DTZORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_SNKORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_TOTORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_DTBORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_DTPORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_DTZORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_SNKORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_TOTORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_PHYT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADDR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADDR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADDR3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADEP1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADEP2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADEP3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADWT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADWT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADWT3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"POTBOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TBENAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TBENAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKCF2_11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKCF2_12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKCF2_13\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKCF2_14\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKCF2_15\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKCF2_21\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKCF2_22\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKCF2_23\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKCF2_24\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKCF2_25\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BALCLA1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BENAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYCLA\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYTO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_DTBORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_DTPORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_DTZORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_SNKORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_TOTORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF2_11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF2_12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF2_13\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF2_14\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF2_15\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF2_21\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF2_22\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF2_23\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF2_24\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF2_25\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_DTHPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_GROPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_SNKPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_TOTPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_ZOOPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF6_DTHZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF6_GROZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF6_TOTZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF7_DTHBEN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF7_GROBEN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_DTBORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_DTPORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_DTZORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_SNKORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_TOTORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_DTBORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_DTPORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_DTZORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_SNKORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_TOTORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_PHYT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADDR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADDR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADDR3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADEP1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADEP2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADEP3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADWT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADWT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADWT3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"POTBOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TBENAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TBENAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKCF2_11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKCF2_12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKCF2_13\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKCF2_14\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKCF2_15\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKCF2_21\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKCF2_22\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKCF2_23\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKCF2_24\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKCF2_25\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/RCHRES_R001/SEDTRN (Group) ''\n", "/RESULTS/RCHRES_R001/SEDTRN/table (Table(8784,)) ''\n", " description := {\n", @@ -4719,12 +4881,12 @@ " \"ISED3\": Float32Col(shape=(), dflt=0.0, pos=8),\n", " \"OSED11\": Float32Col(shape=(), dflt=0.0, pos=9),\n", " \"OSED12\": Float32Col(shape=(), dflt=0.0, pos=10),\n", - " \"OSED21\": Float32Col(shape=(), dflt=0.0, pos=11),\n", - " \"OSED22\": Float32Col(shape=(), dflt=0.0, pos=12),\n", - " \"OSED31\": Float32Col(shape=(), dflt=0.0, pos=13),\n", - " \"OSED32\": Float32Col(shape=(), dflt=0.0, pos=14),\n", - " \"OSED41\": Float32Col(shape=(), dflt=0.0, pos=15),\n", - " \"OSED42\": Float32Col(shape=(), dflt=0.0, pos=16),\n", + " \"OSED13\": Float32Col(shape=(), dflt=0.0, pos=11),\n", + " \"OSED14\": Float32Col(shape=(), dflt=0.0, pos=12),\n", + " \"OSED21\": Float32Col(shape=(), dflt=0.0, pos=13),\n", + " \"OSED22\": Float32Col(shape=(), dflt=0.0, pos=14),\n", + " \"OSED23\": Float32Col(shape=(), dflt=0.0, pos=15),\n", + " \"OSED24\": Float32Col(shape=(), dflt=0.0, pos=16),\n", " \"ROSED1\": Float32Col(shape=(), dflt=0.0, pos=17),\n", " \"ROSED2\": Float32Col(shape=(), dflt=0.0, pos=18),\n", " \"ROSED3\": Float32Col(shape=(), dflt=0.0, pos=19),\n", @@ -4750,44 +4912,44 @@ " chunkshape := (420,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BEDDEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSED11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSED12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSED21\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSED22\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSED31\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSED32\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSED41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSED42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED10\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED8\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED9\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BEDDEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSED11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSED12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSED13\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSED14\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSED21\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSED22\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSED23\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSED24\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/PERLND_P001/PSTEMP (Group) ''\n", "/RESULTS/PERLND_P001/PSTEMP/table (Table(8784,)) ''\n", " description := {\n", @@ -4800,11 +4962,11 @@ " chunkshape := (2730,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AIRTC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LGTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SLTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ULTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AIRTC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LGTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SLTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ULTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/PERLND_P001/PWATER (Group) ''\n", "/RESULTS/PERLND_P001/PWATER/table (Table(8784,)) ''\n", " description := {\n", @@ -4849,43 +5011,43 @@ " chunkshape := (431,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AGWET\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AGWI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AGWLI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AGWO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AGWS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BASET\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CEPE\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CEPS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GWVS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IFWI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IFWLI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IFWO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IFWS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IGWI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INFFAC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INFIL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LZET\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LZI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LZLI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LZS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PERC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PERO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PERS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PET\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PETADJ\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SUPY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SURI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SURLI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SURO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SURS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TAET\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TGWS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"UZET\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"UZI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"UZLI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"UZS\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AGWET\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AGWI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AGWLI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AGWO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AGWS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BASET\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CEPE\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CEPS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GWVS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IFWI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IFWLI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IFWO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IFWS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IGWI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INFFAC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INFIL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LZET\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LZI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LZLI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LZS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PERC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PERO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PERS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PET\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PETADJ\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SUPY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SURI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SURLI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SURO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SURS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TAET\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TGWS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZET\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZLI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZS\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/PERLND_P001/PWTGAS (Group) ''\n", "/RESULTS/PERLND_P001/PWTGAS/table (Table(8784,)) ''\n", " description := {\n", @@ -4915,28 +5077,28 @@ " chunkshape := (712,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AOCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AOCO2M\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AODOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AODOXM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AOHT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AOTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IOCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IOCO2M\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IODOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IODOXM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IOHT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IOTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"POCO2M\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PODOXM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"POHT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOCO2M\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SODOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SODOXM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOHT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AOCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AOCO2M\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AODOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AODOXM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AOHT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AOTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IOCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IOCO2M\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IODOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IODOXM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IOHT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IOTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"POCO2M\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PODOXM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"POHT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOCO2M\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SODOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SODOXM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOHT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/PERLND_P001/SNOW (Group) ''\n", "/RESULTS/PERLND_P001/SNOW/table (Table(8784,)) ''\n", " description := {\n", @@ -4967,29 +5129,29 @@ " chunkshape := (682,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALBEDO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COVINX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEWTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DULL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MELT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NEGHTS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACK\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACKF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACKI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACKW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PAKTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PDEPTH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PRAIN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RAINF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RDENPF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SKYCLR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOCOV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOWE\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOWF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"WYIELD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"XLNMLT\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALBEDO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COVINX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEWTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DULL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MELT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NEGHTS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACK\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACKF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACKI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACKW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PAKTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PDEPTH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PRAIN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RAINF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RDENPF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SKYCLR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOCOV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOWE\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOWF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"WYIELD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"XLNMLT\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/IMPLND_I001/IQUAL (Group) ''\n", "/RESULTS/IMPLND_I001/IQUAL/table (Table(8784,)) ''\n", " description := {\n", @@ -5008,17 +5170,17 @@ " chunkshape := (1365,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IQUAL1_IQADDR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IQUAL1_IQADEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IQUAL1_IQADWT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IQUAL1_SOQC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IQUAL1_SOQO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IQUAL1_SOQOC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IQUAL1_SOQS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IQUAL1_SOQSP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IQUAL1_SOQUAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IQUAL1_SQO\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IQUAL1_IQADDR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IQUAL1_IQADEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IQUAL1_IQADWT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IQUAL1_SOQC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IQUAL1_SOQO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IQUAL1_SOQOC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IQUAL1_SOQS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IQUAL1_SOQSP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IQUAL1_SOQUAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IQUAL1_SQO\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/IMPLND_I001/IWATER (Group) ''\n", "/RESULTS/IMPLND_I001/IWATER/table (Table(8784,)) ''\n", " description := {\n", @@ -5035,15 +5197,15 @@ " chunkshape := (1638,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IMPEV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PET\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PETADJ\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RETS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SUPY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SURI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SURO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SURS\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IMPEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PET\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PETADJ\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RETS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SUPY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SURI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SURO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SURS\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/IMPLND_I001/IWTGAS (Group) ''\n", "/RESULTS/IMPLND_I001/IWTGAS/table (Table(8784,)) ''\n", " description := {\n", @@ -5058,13 +5220,13 @@ " chunkshape := (2048,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOCO2M\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SODOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SODOXM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOHT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOCO2M\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SODOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SODOXM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOHT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/IMPLND_I001/SNOW (Group) ''\n", "/RESULTS/IMPLND_I001/SNOW/table (Table(8784,)) ''\n", " description := {\n", @@ -5095,29 +5257,29 @@ " chunkshape := (682,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALBEDO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COVINX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEWTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DULL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MELT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NEGHTS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACK\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACKF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACKI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACKW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PAKTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PDEPTH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PRAIN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RAINF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RDENPF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SKYCLR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOCOV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOWE\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOWF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"WYIELD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"XLNMLT\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALBEDO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COVINX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEWTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DULL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MELT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NEGHTS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACK\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACKF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACKI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACKW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PAKTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PDEPTH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PRAIN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RAINF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RDENPF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SKYCLR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOCOV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOWE\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOWF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"WYIELD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"XLNMLT\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RESULTS/IMPLND_I001/SOLIDS (Group) ''\n", "/RESULTS/IMPLND_I001/SOLIDS/table (Table(8784,)) ''\n", " description := {\n", @@ -5128,9 +5290,10 @@ " chunkshape := (4096,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SLDS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOSLD\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SLDS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOSLD\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/RCHRES/ACIDPH (Group) ''\n", "/RCHRES/CONS (Group) ''\n", "/RCHRES/GENERAL (Group) ''\n", "/RCHRES/GQUAL (Group) ''\n", @@ -5156,26 +5319,24 @@ " chunkshape := (1260,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"D\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"W\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RHO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TAUCD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TAUCS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"M\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"D\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"W\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RHO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TAUCD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TAUCS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"M\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/SEDTRN/FLAGS (Group) ''\n", "/RCHRES/SEDTRN/FLAGS/table (Table(5,)) ''\n", " description := {\n", " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", - " \"SANDFG\": Int64Col(shape=(), dflt=0, pos=1),\n", - " \"OPNID\": StringCol(itemsize=3, shape=(), dflt=b'', pos=2)}\n", + " \"SANDFG\": Int64Col(shape=(), dflt=0, pos=1)}\n", " byteorder := 'little'\n", - " chunkshape := (4369,)\n", + " chunkshape := (5461,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SANDFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SANDFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/SEDTRN/PARAMETERS (Group) ''\n", "/RCHRES/SEDTRN/PARAMETERS/table (Table(5,)) ''\n", " description := {\n", @@ -5188,27 +5349,25 @@ " \"RHO\": Float64Col(shape=(), dflt=0.0, pos=6),\n", " \"KSAND\": Float64Col(shape=(), dflt=0.0, pos=7),\n", " \"EXPSND\": Float64Col(shape=(), dflt=0.0, pos=8),\n", - " \"OPNID\": StringCol(itemsize=4, shape=(), dflt=b'', pos=9),\n", - " \"LEN\": Float64Col(shape=(), dflt=0.0, pos=10),\n", - " \"DELTH\": Float64Col(shape=(), dflt=0.0, pos=11),\n", - " \"DB50\": Float64Col(shape=(), dflt=0.0, pos=12)}\n", + " \"LEN\": Float64Col(shape=(), dflt=0.0, pos=9),\n", + " \"DELTH\": Float64Col(shape=(), dflt=0.0, pos=10),\n", + " \"DB50\": Float64Col(shape=(), dflt=0.0, pos=11)}\n", " byteorder := 'little'\n", - " chunkshape := (682,)\n", + " chunkshape := (712,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BEDWID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BEDWRN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"POR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"D\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"W\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RHO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KSAND\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"EXPSND\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LEN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DELTH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DB50\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BEDWID\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BEDWRN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"POR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"D\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"W\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RHO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KSAND\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"EXPSND\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LEN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DELTH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DB50\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/SEDTRN/SAVE (Group) ''\n", "/RCHRES/SEDTRN/SAVE/table (Table(5,)) ''\n", " description := {\n", @@ -5250,40 +5409,40 @@ " chunkshape := (244,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BEDDEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEPSCR4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSED4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSED4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED8\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED9\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSED10\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BEDDEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEPSCR4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSED4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSED4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSED10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/SEDTRN/SILT (Group) ''\n", "/RCHRES/SEDTRN/SILT/table (Table(5,)) ''\n", " description := {\n", @@ -5298,13 +5457,13 @@ " chunkshape := (1260,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"D\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"W\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RHO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TAUCD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TAUCS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"M\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"D\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"W\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RHO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TAUCD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TAUCS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"M\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/SEDTRN/STATES (Group) ''\n", "/RCHRES/SEDTRN/STATES/table (Table(5,)) ''\n", " description := {\n", @@ -5315,49 +5474,43 @@ " \"BEDDEP\": Float64Col(shape=(), dflt=0.0, pos=4),\n", " \"SANDFR\": Float64Col(shape=(), dflt=0.0, pos=5),\n", " \"SILTFR\": Float64Col(shape=(), dflt=0.0, pos=6),\n", - " \"CLAYFR\": Float64Col(shape=(), dflt=0.0, pos=7),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=8)}\n", + " \"CLAYFR\": Float64Col(shape=(), dflt=0.0, pos=7)}\n", " byteorder := 'little'\n", - " chunkshape := (1074,)\n", + " chunkshape := (1092,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSED3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BEDDEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SANDFR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SILTFR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CLAYFR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSED3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BEDDEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SANDFR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SILTFR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CLAYFR\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/RQUAL/FLAGS (Group) ''\n", "/RCHRES/RQUAL/FLAGS/table (Table(5,)) ''\n", " description := {\n", " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", - " \"BENRFG\": Float64Col(shape=(), dflt=0.0, pos=1),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=2)}\n", + " \"BENRFG\": Float64Col(shape=(), dflt=0.0, pos=1)}\n", " byteorder := 'little'\n", - " chunkshape := (5041,)\n", + " chunkshape := (5461,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BENRFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BENRFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/RQUAL/PARAMETERS (Group) ''\n", "/RCHRES/RQUAL/PARAMETERS/table (Table(5,)) ''\n", " description := {\n", " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", " \"SCRVEL\": Float64Col(shape=(), dflt=0.0, pos=1),\n", - " \"SCRMUL\": Float64Col(shape=(), dflt=0.0, pos=2),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=3)}\n", + " \"SCRMUL\": Float64Col(shape=(), dflt=0.0, pos=2)}\n", " byteorder := 'little'\n", - " chunkshape := (3120,)\n", + " chunkshape := (3276,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SCRVEL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SCRMUL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SCRVEL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SCRMUL\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/PLANK/FLAGS (Group) ''\n", "/RCHRES/PLANK/FLAGS/table (Table(5,)) ''\n", " description := {\n", @@ -5367,50 +5520,50 @@ " \"BALFG\": Int64Col(shape=(), dflt=0, pos=3),\n", " \"SDLTFG\": Int64Col(shape=(), dflt=0, pos=4),\n", " \"AMRFG\": Int64Col(shape=(), dflt=0, pos=5),\n", - " \"DECFG\": Int64Col(shape=(), dflt=0, pos=6),\n", + " \"DECFG\": Float64Col(shape=(), dflt=0.0, pos=6),\n", " \"NSFG\": Int64Col(shape=(), dflt=0, pos=7),\n", - " \"ZFOOD\": Int64Col(shape=(), dflt=0, pos=8),\n", - " \"BNPFG\": Int64Col(shape=(), dflt=0, pos=9),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=10),\n", - " \"PLADFG1\": Int64Col(shape=(), dflt=0, pos=11),\n", - " \"PLADFG2\": Int64Col(shape=(), dflt=0, pos=12),\n", - " \"PLADFG3\": Int64Col(shape=(), dflt=0, pos=13),\n", - " \"PLADFG4\": Int64Col(shape=(), dflt=0, pos=14),\n", - " \"PLADFG5\": Int64Col(shape=(), dflt=0, pos=15),\n", - " \"PLADFG6\": Int64Col(shape=(), dflt=0, pos=16),\n", - " \"NUMBAL\": Int64Col(shape=(), dflt=0, pos=17),\n", - " \"BINVFG\": Int64Col(shape=(), dflt=0, pos=18),\n", - " \"BFIXFG1\": Int64Col(shape=(), dflt=0, pos=19),\n", - " \"BFIXFG2\": Int64Col(shape=(), dflt=0, pos=20),\n", - " \"BFIXFG3\": Int64Col(shape=(), dflt=0, pos=21),\n", - " \"BFIXFG4\": Int64Col(shape=(), dflt=0, pos=22)}\n", - " byteorder := 'little'\n", - " chunkshape := (378,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHYFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ZOOFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BALFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SDLTFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AMRFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DECFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NSFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ZFOOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BNPFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADFG1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADFG2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADFG3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADFG4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADFG5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADFG6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUMBAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BINVFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BFIXFG1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BFIXFG2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BFIXFG3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BFIXFG4\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"ZFOOD\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"BNPFG\": Float64Col(shape=(), dflt=0.0, pos=9),\n", + " \"PHFXFG\": Float64Col(shape=(), dflt=0.0, pos=10),\n", + " \"NUMBAL\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"BINVFG\": Float64Col(shape=(), dflt=0.0, pos=12),\n", + " \"BFIXFG1\": Float64Col(shape=(), dflt=0.0, pos=13),\n", + " \"BFIXFG2\": Float64Col(shape=(), dflt=0.0, pos=14),\n", + " \"BFIXFG3\": Float64Col(shape=(), dflt=0.0, pos=15),\n", + " \"BFIXFG4\": Float64Col(shape=(), dflt=0.0, pos=16),\n", + " \"PLADFG1\": Float64Col(shape=(), dflt=0.0, pos=17),\n", + " \"PLADFG2\": Float64Col(shape=(), dflt=0.0, pos=18),\n", + " \"PLADFG3\": Float64Col(shape=(), dflt=0.0, pos=19),\n", + " \"PLADFG4\": Float64Col(shape=(), dflt=0.0, pos=20),\n", + " \"PLADFG5\": Float64Col(shape=(), dflt=0.0, pos=21),\n", + " \"PLADFG6\": Float64Col(shape=(), dflt=0.0, pos=22)}\n", + " byteorder := 'little'\n", + " chunkshape := (364,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ZOOFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BALFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDLTFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AMRFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DECFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NSFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ZFOOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BNPFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHFXFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUMBAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BINVFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BFIXFG1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BFIXFG2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BFIXFG3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BFIXFG4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADFG1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADFG2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADFG3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADFG4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADFG5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADFG6\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/PLANK/PARAMETERS (Group) ''\n", "/RCHRES/PLANK/PARAMETERS/table (Table(5,)) ''\n", " description := {\n", @@ -5433,157 +5586,159 @@ " \"ZRES20\": Float64Col(shape=(), dflt=0.0, pos=16),\n", " \"ZD\": Float64Col(shape=(), dflt=0.0, pos=17),\n", " \"OXZD\": Float64Col(shape=(), dflt=0.0, pos=18),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=19),\n", - " \"CFSAEX\": Float64Col(shape=(), dflt=0.0, pos=20),\n", - " \"CMMLT\": Float64Col(shape=(), dflt=0.0, pos=21),\n", - " \"CMMN\": Float64Col(shape=(), dflt=0.0, pos=22),\n", - " \"CMMNP\": Float64Col(shape=(), dflt=0.0, pos=23),\n", - " \"CMMP\": Float64Col(shape=(), dflt=0.0, pos=24),\n", - " \"TALGRH\": Float64Col(shape=(), dflt=0.0, pos=25),\n", - " \"TALGRL\": Float64Col(shape=(), dflt=0.0, pos=26),\n", - " \"TALGRM\": Float64Col(shape=(), dflt=0.0, pos=27),\n", - " \"ALR20\": Float64Col(shape=(), dflt=0.0, pos=28),\n", - " \"ALDH\": Float64Col(shape=(), dflt=0.0, pos=29),\n", - " \"ALDL\": Float64Col(shape=(), dflt=0.0, pos=30),\n", - " \"OXALD\": Float64Col(shape=(), dflt=0.0, pos=31),\n", - " \"NALDH\": Float64Col(shape=(), dflt=0.0, pos=32),\n", - " \"PALDH\": Float64Col(shape=(), dflt=0.0, pos=33),\n", - " \"TCZFIL\": Float64Col(shape=(), dflt=0.0, pos=34),\n", - " \"TCZRES\": Float64Col(shape=(), dflt=0.0, pos=35),\n", - " \"ZEXDEL\": Float64Col(shape=(), dflt=0.0, pos=36),\n", - " \"ZOMASS\": Float64Col(shape=(), dflt=0.0, pos=37),\n", - " \"MBAL\": Float64Col(shape=(), dflt=0.0, pos=38),\n", - " \"CFBALR\": Float64Col(shape=(), dflt=0.0, pos=39),\n", - " \"CFBALG\": Float64Col(shape=(), dflt=0.0, pos=40),\n", - " \"MINBAL\": Float64Col(shape=(), dflt=0.0, pos=41),\n", - " \"CAMPR\": Float64Col(shape=(), dflt=0.0, pos=42),\n", - " \"FRAVL\": Float64Col(shape=(), dflt=0.0, pos=43),\n", - " \"NMAXFX\": Float64Col(shape=(), dflt=0.0, pos=44),\n", - " \"MBALGR\": Float64Col(shape=(), dflt=0.0, pos=45),\n", - " \"TCBALG\": Float64Col(shape=(), dflt=0.0, pos=46),\n", - " \"CMMNB\": Float64Col(shape=(), dflt=0.0, pos=47),\n", - " \"CMMPB\": Float64Col(shape=(), dflt=0.0, pos=48),\n", - " \"CMMD1\": Float64Col(shape=(), dflt=0.0, pos=49),\n", - " \"CMMD2\": Float64Col(shape=(), dflt=0.0, pos=50),\n", - " \"CSLIT\": Float64Col(shape=(), dflt=0.0, pos=51),\n", - " \"BALR20\": Float64Col(shape=(), dflt=0.0, pos=52),\n", - " \"TCBALR\": Float64Col(shape=(), dflt=0.0, pos=53),\n", - " \"CSLOF1\": Float64Col(shape=(), dflt=0.0, pos=54),\n", - " \"CSLOF2\": Float64Col(shape=(), dflt=0.0, pos=55),\n", - " \"GRORES\": Float64Col(shape=(), dflt=0.0, pos=56),\n", - " \"CREMVL\": Float64Col(shape=(), dflt=0.0, pos=57),\n", - " \"CMMBI\": Float64Col(shape=(), dflt=0.0, pos=58),\n", - " \"BINV\": Float64Col(shape=(), dflt=0.0, pos=59),\n", - " \"TCGRAZ\": Float64Col(shape=(), dflt=0.0, pos=60),\n", - " \"CTRBQ1\": Float64Col(shape=(), dflt=0.0, pos=61),\n", - " \"CTRBQ2\": Float64Col(shape=(), dflt=0.0, pos=62),\n", - " \"CKTRB1\": Float64Col(shape=(), dflt=0.0, pos=63),\n", - " \"CKTRB2\": Float64Col(shape=(), dflt=0.0, pos=64),\n", - " \"FRRIF\": Float64Col(shape=(), dflt=0.0, pos=65),\n", - " \"CMMV\": Float64Col(shape=(), dflt=0.0, pos=66),\n", - " \"RIFCQ1\": Float64Col(shape=(), dflt=0.0, pos=67),\n", - " \"RIFCQ2\": Float64Col(shape=(), dflt=0.0, pos=68),\n", - " \"RIFCQ3\": Float64Col(shape=(), dflt=0.0, pos=69),\n", - " \"RIFVF1\": Float64Col(shape=(), dflt=0.0, pos=70),\n", - " \"RIFVF2\": Float64Col(shape=(), dflt=0.0, pos=71),\n", - " \"RIFVF3\": Float64Col(shape=(), dflt=0.0, pos=72),\n", - " \"RIFVF4\": Float64Col(shape=(), dflt=0.0, pos=73),\n", - " \"RIFDF1\": Float64Col(shape=(), dflt=0.0, pos=74),\n", - " \"RIFDF2\": Float64Col(shape=(), dflt=0.0, pos=75),\n", - " \"RIFDF3\": Float64Col(shape=(), dflt=0.0, pos=76),\n", - " \"RIFDF4\": Float64Col(shape=(), dflt=0.0, pos=77),\n", - " \"NMINGR\": Float64Col(shape=(), dflt=0.0, pos=78),\n", - " \"PMINGR\": Float64Col(shape=(), dflt=0.0, pos=79),\n", - " \"CMINGR\": Float64Col(shape=(), dflt=0.0, pos=80),\n", - " \"LMINGR\": Float64Col(shape=(), dflt=0.0, pos=81),\n", - " \"NMINC\": Float64Col(shape=(), dflt=0.0, pos=82)}\n", - " byteorder := 'little'\n", - " chunkshape := (100,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RATCLP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NONREF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LITSED\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALNPR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"EXTB\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MALGR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PARADF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SEED\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MXSTAY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OREF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CLALDH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHYSET\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"REFSET\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MZOEAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ZFIL20\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ZRES20\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ZD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXZD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CFSAEX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CMMLT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CMMN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CMMNP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CMMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TALGRH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TALGRL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TALGRM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALR20\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALDH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALDL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXALD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NALDH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PALDH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TCZFIL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TCZRES\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ZEXDEL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ZOMASS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MBAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CFBALR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CFBALG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MINBAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CAMPR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"FRAVL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NMAXFX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MBALGR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TCBALG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CMMNB\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CMMPB\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CMMD1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CMMD2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CSLIT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BALR20\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TCBALR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CSLOF1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CSLOF2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GRORES\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CREMVL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CMMBI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BINV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TCGRAZ\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CTRBQ1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CTRBQ2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CKTRB1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CKTRB2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"FRRIF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CMMV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RIFCQ1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RIFCQ2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RIFCQ3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RIFVF1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RIFVF2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RIFVF3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RIFVF4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RIFDF1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RIFDF2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RIFDF3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RIFDF4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NMINGR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PMINGR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CMINGR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LMINGR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NMINC\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"CREMVL\": Float64Col(shape=(), dflt=0.0, pos=19),\n", + " \"CMMBI\": Float64Col(shape=(), dflt=0.0, pos=20),\n", + " \"BINV\": Float64Col(shape=(), dflt=0.0, pos=21),\n", + " \"TCGRAZ\": Float64Col(shape=(), dflt=0.0, pos=22),\n", + " \"MBALGR\": Float64Col(shape=(), dflt=0.0, pos=23),\n", + " \"TCBALG\": Float64Col(shape=(), dflt=0.0, pos=24),\n", + " \"CMMNB\": Float64Col(shape=(), dflt=0.0, pos=25),\n", + " \"CMMPB\": Float64Col(shape=(), dflt=0.0, pos=26),\n", + " \"CMMD1\": Float64Col(shape=(), dflt=0.0, pos=27),\n", + " \"CMMD2\": Float64Col(shape=(), dflt=0.0, pos=28),\n", + " \"CSLIT\": Float64Col(shape=(), dflt=0.0, pos=29),\n", + " \"CTRBQ1\": Float64Col(shape=(), dflt=0.0, pos=30),\n", + " \"CTRBQ2\": Float64Col(shape=(), dflt=0.0, pos=31),\n", + " \"CKTRB1\": Float64Col(shape=(), dflt=0.0, pos=32),\n", + " \"CKTRB2\": Float64Col(shape=(), dflt=0.0, pos=33),\n", + " \"MBAL\": Float64Col(shape=(), dflt=0.0, pos=34),\n", + " \"CFBALR\": Float64Col(shape=(), dflt=0.0, pos=35),\n", + " \"CFBALG\": Float64Col(shape=(), dflt=0.0, pos=36),\n", + " \"MINBAL\": Float64Col(shape=(), dflt=0.0, pos=37),\n", + " \"CAMPR\": Float64Col(shape=(), dflt=0.0, pos=38),\n", + " \"FRAVL\": Float64Col(shape=(), dflt=0.0, pos=39),\n", + " \"NMAXFX\": Float64Col(shape=(), dflt=0.0, pos=40),\n", + " \"BALR20\": Float64Col(shape=(), dflt=0.0, pos=41),\n", + " \"TCBALR\": Float64Col(shape=(), dflt=0.0, pos=42),\n", + " \"CSLOF1\": Float64Col(shape=(), dflt=0.0, pos=43),\n", + " \"CSLOF2\": Float64Col(shape=(), dflt=0.0, pos=44),\n", + " \"GRORES\": Float64Col(shape=(), dflt=0.0, pos=45),\n", + " \"FRRIF\": Float64Col(shape=(), dflt=0.0, pos=46),\n", + " \"CMMV\": Float64Col(shape=(), dflt=0.0, pos=47),\n", + " \"RIFCQ1\": Float64Col(shape=(), dflt=0.0, pos=48),\n", + " \"RIFCQ2\": Float64Col(shape=(), dflt=0.0, pos=49),\n", + " \"RIFCQ3\": Float64Col(shape=(), dflt=0.0, pos=50),\n", + " \"RIFVF1\": Float64Col(shape=(), dflt=0.0, pos=51),\n", + " \"RIFVF2\": Float64Col(shape=(), dflt=0.0, pos=52),\n", + " \"RIFVF3\": Float64Col(shape=(), dflt=0.0, pos=53),\n", + " \"RIFVF4\": Float64Col(shape=(), dflt=0.0, pos=54),\n", + " \"RIFDF1\": Float64Col(shape=(), dflt=0.0, pos=55),\n", + " \"RIFDF2\": Float64Col(shape=(), dflt=0.0, pos=56),\n", + " \"RIFDF3\": Float64Col(shape=(), dflt=0.0, pos=57),\n", + " \"RIFDF4\": Float64Col(shape=(), dflt=0.0, pos=58),\n", + " \"CMMLT\": Float64Col(shape=(), dflt=0.0, pos=59),\n", + " \"CMMN\": Float64Col(shape=(), dflt=0.0, pos=60),\n", + " \"CMMNP\": Float64Col(shape=(), dflt=0.0, pos=61),\n", + " \"CMMP\": Float64Col(shape=(), dflt=0.0, pos=62),\n", + " \"TALGRH\": Float64Col(shape=(), dflt=0.0, pos=63),\n", + " \"TALGRL\": Float64Col(shape=(), dflt=0.0, pos=64),\n", + " \"TALGRM\": Float64Col(shape=(), dflt=0.0, pos=65),\n", + " \"ALR20\": Float64Col(shape=(), dflt=0.0, pos=66),\n", + " \"ALDH\": Float64Col(shape=(), dflt=0.0, pos=67),\n", + " \"ALDL\": Float64Col(shape=(), dflt=0.0, pos=68),\n", + " \"OXALD\": Float64Col(shape=(), dflt=0.0, pos=69),\n", + " \"NALDH\": Float64Col(shape=(), dflt=0.0, pos=70),\n", + " \"PALDH\": Float64Col(shape=(), dflt=0.0, pos=71),\n", + " \"NMINGR\": Float64Col(shape=(), dflt=0.0, pos=72),\n", + " \"PMINGR\": Float64Col(shape=(), dflt=0.0, pos=73),\n", + " \"CMINGR\": Float64Col(shape=(), dflt=0.0, pos=74),\n", + " \"LMINGR\": Float64Col(shape=(), dflt=0.0, pos=75),\n", + " \"NMINC\": Float64Col(shape=(), dflt=0.0, pos=76),\n", + " \"PHMXFX\": Float64Col(shape=(), dflt=0.0, pos=77),\n", + " \"PHFXAD\": Float64Col(shape=(), dflt=0.0, pos=78),\n", + " \"CFSAEX\": Float64Col(shape=(), dflt=0.0, pos=79),\n", + " \"TCZFIL\": Float64Col(shape=(), dflt=0.0, pos=80),\n", + " \"TCZRES\": Float64Col(shape=(), dflt=0.0, pos=81),\n", + " \"ZEXDEL\": Float64Col(shape=(), dflt=0.0, pos=82),\n", + " \"ZOMASS\": Float64Col(shape=(), dflt=0.0, pos=83)}\n", + " byteorder := 'little'\n", + " chunkshape := (98,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RATCLP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NONREF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LITSED\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALNPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"EXTB\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MALGR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PARADF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SEED\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MXSTAY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OREF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CLALDH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYSET\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"REFSET\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MZOEAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ZFIL20\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ZRES20\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ZD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXZD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CREMVL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CMMBI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BINV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TCGRAZ\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MBALGR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TCBALG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CMMNB\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CMMPB\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CMMD1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CMMD2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CSLIT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTRBQ1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTRBQ2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CKTRB1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CKTRB2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MBAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CFBALR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CFBALG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MINBAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CAMPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FRAVL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NMAXFX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BALR20\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TCBALR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CSLOF1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CSLOF2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GRORES\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FRRIF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CMMV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RIFCQ1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RIFCQ2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RIFCQ3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RIFVF1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RIFVF2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RIFVF3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RIFVF4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RIFDF1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RIFDF2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RIFDF3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RIFDF4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CMMLT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CMMN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CMMNP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CMMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TALGRH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TALGRL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TALGRM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALR20\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALDH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALDL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXALD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NALDH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PALDH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NMINGR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PMINGR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CMINGR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LMINGR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NMINC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHMXFX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHFXAD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CFSAEX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TCZFIL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TCZRES\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ZEXDEL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ZOMASS\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/PLANK/SAVE (Group) ''\n", "/RCHRES/PLANK/SAVE/table (Table(5,)) ''\n", " description := {\n", @@ -5679,94 +5834,94 @@ " chunkshape := (93,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHYTO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BALCLA1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BALCLA2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BALCLA3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BALCLA4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BENAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BENAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BENAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BENAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TBENAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TBENAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHYCLA\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BALCLA\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"POTBOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_PHYT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKIF_ORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKIF_5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF1_5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF2_11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF2_12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF2_13\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF2_14\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF2_15\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKCF2_11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKCF2_12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKCF2_13\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKCF2_14\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TPKCF2_15\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_SNKPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_ZOOPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_DTHPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_GROPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF5_TOTPHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF6_GROZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF6_DTHZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF6_TOTZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF7_GROBEN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF7_DTHBEN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_SNKORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_DTPORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_DTZORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_DTBORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF8_TOTORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_SNKORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_DTPORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_DTZORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_DTBORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF9_TOTORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_SNKORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_DTPORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_DTZORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_DTBORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKCF10_TOTORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADDR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADWT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADEP1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADDR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADWT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADEP2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADDR3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADWT3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLADEP3\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYTO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BALCLA1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BALCLA2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BALCLA3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BALCLA4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BENAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BENAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BENAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BENAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TBENAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TBENAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYCLA\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BALCLA\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"POTBOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_PHYT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKIF_ORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKIF_5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF1_5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF2_11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF2_12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF2_13\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF2_14\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF2_15\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKCF2_11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKCF2_12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKCF2_13\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKCF2_14\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TPKCF2_15\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_SNKPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_ZOOPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_DTHPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_GROPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF5_TOTPHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF6_GROZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF6_DTHZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF6_TOTZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF7_GROBEN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF7_DTHBEN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_SNKORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_DTPORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_DTZORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_DTBORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF8_TOTORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_SNKORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_DTPORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_DTZORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_DTBORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF9_TOTORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_SNKORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_DTPORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_DTZORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_DTBORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PKCF10_TOTORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADDR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADWT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADEP1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADDR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADWT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADEP2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADDR3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADWT3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLADEP3\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/PLANK/STATES (Group) ''\n", "/RCHRES/PLANK/STATES/table (Table(5,)) ''\n", " description := {\n", @@ -5777,48 +5932,44 @@ " \"ORN\": Float64Col(shape=(), dflt=0.0, pos=4),\n", " \"ORP\": Float64Col(shape=(), dflt=0.0, pos=5),\n", " \"ORC\": Float64Col(shape=(), dflt=0.0, pos=6),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=7),\n", - " \"BENAL1\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"BENAL1\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"BENAL4\": Float64Col(shape=(), dflt=0.0, pos=8),\n", " \"BENAL2\": Float64Col(shape=(), dflt=0.0, pos=9),\n", - " \"BENAL3\": Float64Col(shape=(), dflt=0.0, pos=10),\n", - " \"BENAL4\": Float64Col(shape=(), dflt=0.0, pos=11)}\n", - " byteorder := 'little'\n", - " chunkshape := (771,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHYTO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BENAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ORC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BENAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BENAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BENAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BENAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"BENAL3\": Float64Col(shape=(), dflt=0.0, pos=10)}\n", + " byteorder := 'little'\n", + " chunkshape := (780,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYTO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BENAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ORC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BENAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BENAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BENAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BENAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/PHCARB/PARAMETERS (Group) ''\n", "/RCHRES/PHCARB/PARAMETERS/table (Table(5,)) ''\n", " description := {\n", " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", " \"PHCNT\": Int64Col(shape=(), dflt=0, pos=1),\n", - " \"ALKCON\": Int64Col(shape=(), dflt=0, pos=2),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=3),\n", - " \"CFCINV\": Float64Col(shape=(), dflt=0.0, pos=4),\n", - " \"BRCO21\": Float64Col(shape=(), dflt=0.0, pos=5),\n", - " \"BRCO22\": Float64Col(shape=(), dflt=0.0, pos=6)}\n", - " byteorder := 'little'\n", - " chunkshape := (1456,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCNT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALKCON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CFCINV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BRCO21\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BRCO22\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"ALKCON\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"CFCINV\": Float64Col(shape=(), dflt=0.0, pos=3),\n", + " \"BRCO21\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"BRCO22\": Float64Col(shape=(), dflt=0.0, pos=5)}\n", + " byteorder := 'little'\n", + " chunkshape := (1489,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCNT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALKCON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CFCINV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BRCO21\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BRCO22\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/PHCARB/SAVE (Group) ''\n", "/RCHRES/PHCARB/SAVE/table (Table(5,)) ''\n", " description := {\n", @@ -5844,54 +5995,52 @@ " chunkshape := (468,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TIC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SATCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ITIC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ICO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROTIC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OTIC1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OCO21\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_DECCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_PHYCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_ZOOCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_BGRCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_BRECO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_INVCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCF3_TOTCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TIC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SATCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ITIC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ICO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROTIC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OTIC1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OCO21\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_DECCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_PHYCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_ZOOCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_BGRCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_BRECO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_INVCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCF3_TOTCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/PHCARB/STATES (Group) ''\n", "/RCHRES/PHCARB/STATES/table (Table(5,)) ''\n", " description := {\n", " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", " \"TIC\": Float64Col(shape=(), dflt=0.0, pos=1),\n", " \"CO2\": Float64Col(shape=(), dflt=0.0, pos=2),\n", - " \"PH\": Float64Col(shape=(), dflt=0.0, pos=3),\n", - " \"OPNID\": StringCol(itemsize=2, shape=(), dflt=b'', pos=4)}\n", + " \"PH\": Float64Col(shape=(), dflt=0.0, pos=3)}\n", " byteorder := 'little'\n", - " chunkshape := (2184,)\n", + " chunkshape := (2340,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TIC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TIC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PH\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/OXRX/FLAGS (Group) ''\n", "/RCHRES/OXRX/FLAGS/table (Table(5,)) ''\n", " description := {\n", " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", " \"REAMFG\": Float64Col(shape=(), dflt=0.0, pos=1),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=2)}\n", + " \"DOPFG\": Float64Col(shape=(), dflt=0.0, pos=2)}\n", " byteorder := 'little'\n", - " chunkshape := (5041,)\n", + " chunkshape := (3276,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"REAMFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"REAMFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DOPFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/OXRX/PARAMETERS (Group) ''\n", "/RCHRES/OXRX/PARAMETERS/table (Table(5,)) ''\n", " description := {\n", @@ -5911,36 +6060,34 @@ " \"REAK\": Float64Col(shape=(), dflt=0.0, pos=13),\n", " \"EXPRED\": Float64Col(shape=(), dflt=0.0, pos=14),\n", " \"EXPREV\": Float64Col(shape=(), dflt=0.0, pos=15),\n", - " \"OPNID\": StringCol(itemsize=5, shape=(), dflt=b'', pos=16),\n", - " \"ELEV\": Float64Col(shape=(), dflt=0.0, pos=17),\n", - " \"REAKT\": Float64Col(shape=(), dflt=0.0, pos=18),\n", - " \"LEN\": Float64Col(shape=(), dflt=0.0, pos=19),\n", - " \"DELTH\": Float64Col(shape=(), dflt=0.0, pos=20)}\n", - " byteorder := 'little'\n", - " chunkshape := (407,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KBOD20\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TCBOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KODSET\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SUPSAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BENOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TCBEN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"EXPOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BRBOD1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BRBOD2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"EXPREL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CFOREA\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TCGINV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"REAK\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"EXPRED\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"EXPREV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ELEV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"REAKT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LEN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DELTH\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"ELEV\": Float64Col(shape=(), dflt=0.0, pos=16),\n", + " \"LEN\": Float64Col(shape=(), dflt=0.0, pos=17),\n", + " \"DELTH\": Float64Col(shape=(), dflt=0.0, pos=18),\n", + " \"REAKT\": Float64Col(shape=(), dflt=0.0, pos=19)}\n", + " byteorder := 'little'\n", + " chunkshape := (420,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KBOD20\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TCBOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KODSET\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SUPSAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BENOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TCBEN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"EXPOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BRBOD1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BRBOD2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"EXPREL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CFOREA\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TCGINV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"REAK\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"EXPRED\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"EXPREV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ELEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LEN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DELTH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"REAKT\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/OXRX/SAVE (Group) ''\n", "/RCHRES/OXRX/SAVE/table (Table(5,)) ''\n", " description := {\n", @@ -5973,48 +6120,46 @@ " chunkshape := (334,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SATDO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IDOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IBOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF2_11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF2_12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_REAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_DEC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_BENDO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_NITR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_PHYT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_BALG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF3_TOTAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_DEC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_BENR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_SNK\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_PHYT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_ZOO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_BALG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXCF4_TOTAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SATDO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IDOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IBOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF2_11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF2_12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_REAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_DEC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_BENDO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_NITR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_PHYT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_BALG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF3_TOTAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_DEC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_BENR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_SNK\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_PHYT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_ZOO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_BALG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXCF4_TOTAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/OXRX/STATES (Group) ''\n", "/RCHRES/OXRX/STATES/table (Table(5,)) ''\n", " description := {\n", " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", " \"DOX\": Float64Col(shape=(), dflt=0.0, pos=1),\n", " \"BOD\": Float64Col(shape=(), dflt=0.0, pos=2),\n", - " \"SATDO\": Float64Col(shape=(), dflt=0.0, pos=3),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=4)}\n", + " \"SATDO\": Float64Col(shape=(), dflt=0.0, pos=3)}\n", " byteorder := 'little'\n", - " chunkshape := (2259,)\n", + " chunkshape := (2340,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BOD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SATDO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SATDO\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/NUTRX/FLAGS (Group) ''\n", "/RCHRES/NUTRX/FLAGS/table (Table(5,)) ''\n", " description := {\n", @@ -6026,34 +6171,33 @@ " \"DENFG\": Int64Col(shape=(), dflt=0, pos=5),\n", " \"ADNHFG\": Int64Col(shape=(), dflt=0, pos=6),\n", " \"ADPOFG\": Int64Col(shape=(), dflt=0, pos=7),\n", - " \"PHFLAG\": Int64Col(shape=(), dflt=0, pos=8),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=9),\n", - " \"NUADFG1\": Int64Col(shape=(), dflt=0, pos=10),\n", - " \"NUADFG2\": Int64Col(shape=(), dflt=0, pos=11),\n", - " \"NUADFG3\": Int64Col(shape=(), dflt=0, pos=12),\n", - " \"NUADFG4\": Int64Col(shape=(), dflt=0, pos=13),\n", - " \"NUADFG5\": Int64Col(shape=(), dflt=0, pos=14),\n", - " \"NUADFG6\": Int64Col(shape=(), dflt=0, pos=15)}\n", - " byteorder := 'little'\n", - " chunkshape := (560,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NH3FG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NO2FG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PO4FG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AMVFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DENFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADNHFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADPOFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHFLAG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADFG1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADFG2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADFG3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADFG4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADFG5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADFG6\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"PHFLAG\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"NUADFG1\": Float64Col(shape=(), dflt=0.0, pos=9),\n", + " \"NUADFG2\": Float64Col(shape=(), dflt=0.0, pos=10),\n", + " \"NUADFG3\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"NUADFG4\": Float64Col(shape=(), dflt=0.0, pos=12),\n", + " \"NUADFG5\": Float64Col(shape=(), dflt=0.0, pos=13),\n", + " \"NUADFG6\": Float64Col(shape=(), dflt=0.0, pos=14)}\n", + " byteorder := 'little'\n", + " chunkshape := (564,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NH3FG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NO2FG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PO4FG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AMVFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DENFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADNHFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPOFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHFLAG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADFG1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADFG2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADFG3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADFG4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADFG5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADFG6\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/RCHRES/NUTRX/MONTHLY (Group) ''\n", "/RCHRES/NUTRX/PARAMETERS (Group) ''\n", "/RCHRES/NUTRX/PARAMETERS/table (Table(5,)) ''\n", " description := {\n", @@ -6083,46 +6227,44 @@ " \"ADPOPM1\": Float64Col(shape=(), dflt=0.0, pos=23),\n", " \"ADPOPM2\": Float64Col(shape=(), dflt=0.0, pos=24),\n", " \"ADPOPM3\": Float64Col(shape=(), dflt=0.0, pos=25),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=26),\n", - " \"CVBO\": Float64Col(shape=(), dflt=0.0, pos=27),\n", - " \"CVBPC\": Float64Col(shape=(), dflt=0.0, pos=28),\n", - " \"CVBPN\": Float64Col(shape=(), dflt=0.0, pos=29),\n", - " \"BPCNTC\": Float64Col(shape=(), dflt=0.0, pos=30)}\n", - " byteorder := 'little'\n", - " chunkshape := (276,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BRNIT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BRNIT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BRPO41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BRPO42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ANAER\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KTAM20\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KNO220\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TCNIT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KNO320\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TCDEN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DENOXT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"EXPNVG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"EXPNVL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BNH41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BNH42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BNH43\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BPO41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BPO42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BPO43\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADNHPM1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADNHPM2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADNHPM3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADPOPM1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADPOPM2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADPOPM3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CVBO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CVBPC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CVBPN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BPCNTC\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"CVBO\": Float64Col(shape=(), dflt=0.0, pos=26),\n", + " \"CVBPC\": Float64Col(shape=(), dflt=0.0, pos=27),\n", + " \"CVBPN\": Float64Col(shape=(), dflt=0.0, pos=28),\n", + " \"BPCNTC\": Float64Col(shape=(), dflt=0.0, pos=29)}\n", + " byteorder := 'little'\n", + " chunkshape := (277,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BRNIT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BRNIT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BRPO41\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BRPO42\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ANAER\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KTAM20\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KNO220\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TCNIT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KNO320\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TCDEN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DENOXT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"EXPNVG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"EXPNVL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BNH41\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BNH42\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BNH43\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BPO41\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BPO42\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BPO43\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADNHPM1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADNHPM2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADNHPM3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPOPM1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPOPM2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPOPM3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CVBO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CVBPC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CVBPN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BPCNTC\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/NUTRX/SAVE (Group) ''\n", "/RCHRES/NUTRX/SAVE/table (Table(5,)) ''\n", " description := {\n", @@ -6221,97 +6363,97 @@ " chunkshape := (90,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NH4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NH3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNH41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNH42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNH43\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SPO41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SPO42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SPO43\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INH4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISNH41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISNH42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISNH43\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISPO41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISPO42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISPO43\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUIF4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF1_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF2_11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF2_21\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF2_31\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF2_12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF2_22\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF2_32\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TNUCF1_4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF9_11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF9_12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF9_13\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF9_14\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSNH4_11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSNH4_12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSNH4_13\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSNH4_14\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSPO4_11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSPO4_12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSPO4_13\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSPO4_14\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNH4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RNH3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_NITNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_DENNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_BODNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_TOTNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_PHYNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_ZOONO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF4_BALNO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_NITTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_VOLNH3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_BNRTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_BODTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_TOTTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_PHYTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_ZOOTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF5_BALTAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF6_NITNO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF6_TOTNO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_BNRPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_BODPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_TOTPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_PHYPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_ZOOPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUCF7_BALPO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADDR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADWT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADEP1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADDR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADWT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADEP2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADDR3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADWT3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUADEP3\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NH4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NH3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNH41\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNH42\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNH43\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SPO41\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SPO42\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SPO43\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INH4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISNH41\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISNH42\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISNH43\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISPO41\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISPO42\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISPO43\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUIF4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF1_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF2_11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF2_21\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF2_31\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF2_12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF2_22\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF2_32\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TNUCF1_4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF9_11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF9_12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF9_13\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF9_14\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSNH4_11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSNH4_12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSNH4_13\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSNH4_14\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSPO4_11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSPO4_12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSPO4_13\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSPO4_14\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNH4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RNH3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_NITNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_DENNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_BODNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_TOTNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_PHYNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_ZOONO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF4_BALNO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_NITTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_VOLNH3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_BNRTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_BODTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_TOTTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_PHYTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_ZOOTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF5_BALTAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF6_NITNO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF6_TOTNO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_BNRPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_BODPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_TOTPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_PHYPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_ZOOPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUCF7_BALPO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADDR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADWT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADEP1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADDR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADWT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADEP2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADDR3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADWT3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUADEP3\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/NUTRX/STATES (Group) ''\n", "/RCHRES/NUTRX/STATES/table (Table(5,)) ''\n", " description := {\n", @@ -6326,174 +6468,223 @@ " \"SNH43\": Float64Col(shape=(), dflt=0.0, pos=8),\n", " \"SPO41\": Float64Col(shape=(), dflt=0.0, pos=9),\n", " \"SPO42\": Float64Col(shape=(), dflt=0.0, pos=10),\n", - " \"SPO43\": Float64Col(shape=(), dflt=0.0, pos=11),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=12)}\n", - " byteorder := 'little'\n", - " chunkshape := (704,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NO3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TAM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PO4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHVAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNH41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNH42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNH43\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SPO41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SPO42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SPO43\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"SPO43\": Float64Col(shape=(), dflt=0.0, pos=11)}\n", + " byteorder := 'little'\n", + " chunkshape := (712,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NO3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TAM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PO4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHVAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNH41\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNH42\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNH43\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SPO41\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SPO42\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SPO43\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/RCHRES/NUTRX/MONTHLY/PHVA (Group) ''\n", + "/RCHRES/NUTRX/MONTHLY/PHVA/table (Table(5,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"PHVA1\": Float64Col(shape=(), dflt=0.0, pos=1),\n", + " \"PHVA2\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"PHVA3\": Float64Col(shape=(), dflt=0.0, pos=3),\n", + " \"PHVA4\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"PHVA5\": Float64Col(shape=(), dflt=0.0, pos=5),\n", + " \"PHVA6\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"PHVA7\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"PHVA8\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"PHVA9\": Float64Col(shape=(), dflt=0.0, pos=9),\n", + " \"PHVA10\": Float64Col(shape=(), dflt=0.0, pos=10),\n", + " \"PHVA11\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"PHVA12\": Float64Col(shape=(), dflt=0.0, pos=12)}\n", + " byteorder := 'little'\n", + " chunkshape := (655,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHVA1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHVA2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHVA3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHVA4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHVA5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHVA6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHVA7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHVA8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHVA9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHVA10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHVA11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHVA12\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/HYDR/PARAMETERS (Group) ''\n", "/RCHRES/HYDR/PARAMETERS/table (Table(5,)) ''\n", " description := {\n", " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", - " \"VCONFG\": Int64Col(shape=(), dflt=0, pos=1),\n", + " \"VCONFG\": Float64Col(shape=(), dflt=0.0, pos=1),\n", " \"AUX1FG\": Int64Col(shape=(), dflt=0, pos=2),\n", " \"AUX2FG\": Int64Col(shape=(), dflt=0, pos=3),\n", " \"AUX3FG\": Int64Col(shape=(), dflt=0, pos=4),\n", " \"ODFVF1\": Int64Col(shape=(), dflt=0, pos=5),\n", - " \"ODFVF2\": Int64Col(shape=(), dflt=0, pos=6),\n", - " \"ODFVF3\": Int64Col(shape=(), dflt=0, pos=7),\n", - " \"ODFVF4\": Int64Col(shape=(), dflt=0, pos=8),\n", - " \"ODFVF5\": Int64Col(shape=(), dflt=0, pos=9),\n", - " \"ODGTF1\": Int64Col(shape=(), dflt=0, pos=10),\n", - " \"ODGTF2\": Int64Col(shape=(), dflt=0, pos=11),\n", - " \"ODGTF3\": Int64Col(shape=(), dflt=0, pos=12),\n", - " \"ODGTF4\": Int64Col(shape=(), dflt=0, pos=13),\n", - " \"ODGTF5\": Int64Col(shape=(), dflt=0, pos=14),\n", - " \"FUNCT1\": Int64Col(shape=(), dflt=0, pos=15),\n", - " \"FUNCT2\": Int64Col(shape=(), dflt=0, pos=16),\n", - " \"FUNCT3\": Int64Col(shape=(), dflt=0, pos=17),\n", - " \"FUNCT4\": Int64Col(shape=(), dflt=0, pos=18),\n", - " \"FUNCT5\": Int64Col(shape=(), dflt=0, pos=19),\n", - " \"FTBW\": Float64Col(shape=(), dflt=0.0, pos=20),\n", + " \"ODFVF2\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"ODFVF3\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"ODFVF4\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"ODFVF5\": Float64Col(shape=(), dflt=0.0, pos=9),\n", + " \"ODGTF1\": Float64Col(shape=(), dflt=0.0, pos=10),\n", + " \"ODGTF2\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"ODGTF3\": Float64Col(shape=(), dflt=0.0, pos=12),\n", + " \"ODGTF4\": Float64Col(shape=(), dflt=0.0, pos=13),\n", + " \"ODGTF5\": Float64Col(shape=(), dflt=0.0, pos=14),\n", + " \"FUNCT1\": Float64Col(shape=(), dflt=0.0, pos=15),\n", + " \"FUNCT2\": Float64Col(shape=(), dflt=0.0, pos=16),\n", + " \"FUNCT3\": Float64Col(shape=(), dflt=0.0, pos=17),\n", + " \"FUNCT4\": Float64Col(shape=(), dflt=0.0, pos=18),\n", + " \"FUNCT5\": Float64Col(shape=(), dflt=0.0, pos=19),\n", + " \"FTBW\": Int64Col(shape=(), dflt=0, pos=20),\n", " \"FTBUCI\": StringCol(itemsize=5, shape=(), dflt=b'', pos=21),\n", " \"LEN\": Float64Col(shape=(), dflt=0.0, pos=22),\n", " \"DELTH\": Float64Col(shape=(), dflt=0.0, pos=23),\n", " \"STCOR\": Float64Col(shape=(), dflt=0.0, pos=24),\n", " \"KS\": Float64Col(shape=(), dflt=0.0, pos=25),\n", " \"DB50\": Float64Col(shape=(), dflt=0.0, pos=26),\n", - " \"NEXITS\": Int64Col(shape=(), dflt=0, pos=27),\n", - " \"LKFG\": Int64Col(shape=(), dflt=0, pos=28),\n", - " \"IREXIT\": Int64Col(shape=(), dflt=0, pos=29),\n", - " \"IRMINV\": Float64Col(shape=(), dflt=0.0, pos=30),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=31),\n", - " \"CPREC\": StringCol(itemsize=1, shape=(), dflt=b'', pos=32),\n", - " \"CEVAP\": StringCol(itemsize=1, shape=(), dflt=b'', pos=33),\n", - " \"CFVOL1\": Float64Col(shape=(), dflt=0.0, pos=34),\n", - " \"CFVOL2\": Float64Col(shape=(), dflt=0.0, pos=35),\n", - " \"CFVOL3\": Float64Col(shape=(), dflt=0.0, pos=36),\n", - " \"CFVOL4\": StringCol(itemsize=1, shape=(), dflt=b'', pos=37),\n", - " \"CFVOL5\": StringCol(itemsize=1, shape=(), dflt=b'', pos=38),\n", - " \"NOCGT\": Int64Col(shape=(), dflt=0, pos=39),\n", - " \"CTAG1\": StringCol(itemsize=1, shape=(), dflt=b'', pos=40),\n", - " \"CPREC1\": Float64Col(shape=(), dflt=0.0, pos=41),\n", - " \"CTAG2\": StringCol(itemsize=1, shape=(), dflt=b'', pos=42),\n", - " \"CPREC2\": Float64Col(shape=(), dflt=0.0, pos=43),\n", - " \"CTAG3\": StringCol(itemsize=1, shape=(), dflt=b'', pos=44),\n", - " \"CPREC3\": Float64Col(shape=(), dflt=0.0, pos=45),\n", - " \"CTAG4\": StringCol(itemsize=1, shape=(), dflt=b'', pos=46),\n", - " \"CPREC4\": Float64Col(shape=(), dflt=0.0, pos=47),\n", - " \"CTAG5\": StringCol(itemsize=1, shape=(), dflt=b'', pos=48),\n", - " \"CPREC5\": Float64Col(shape=(), dflt=0.0, pos=49),\n", - " \"CTAG6\": StringCol(itemsize=1, shape=(), dflt=b'', pos=50),\n", - " \"CPREC6\": Float64Col(shape=(), dflt=0.0, pos=51),\n", - " \"CTAG7\": StringCol(itemsize=1, shape=(), dflt=b'', pos=52),\n", - " \"CPREC7\": Float64Col(shape=(), dflt=0.0, pos=53),\n", - " \"CPRI1\": StringCol(itemsize=1, shape=(), dflt=b'', pos=54),\n", - " \"CEVAP1\": Float64Col(shape=(), dflt=0.0, pos=55),\n", - " \"CPRI2\": StringCol(itemsize=1, shape=(), dflt=b'', pos=56),\n", - " \"CEVAP2\": Float64Col(shape=(), dflt=0.0, pos=57),\n", - " \"CPRI3\": Float64Col(shape=(), dflt=0.0, pos=58),\n", - " \"CEVAP3\": Float64Col(shape=(), dflt=0.0, pos=59),\n", - " \"CPRI4\": Float64Col(shape=(), dflt=0.0, pos=60),\n", - " \"CEVAP4\": Float64Col(shape=(), dflt=0.0, pos=61),\n", - " \"CPRI5\": Float64Col(shape=(), dflt=0.0, pos=62),\n", - " \"CEVAP5\": Float64Col(shape=(), dflt=0.0, pos=63),\n", - " \"CEXIT1\": Float64Col(shape=(), dflt=0.0, pos=64),\n", - " \"CEXIT2\": Float64Col(shape=(), dflt=0.0, pos=65),\n", - " \"CEXIT3\": Float64Col(shape=(), dflt=0.0, pos=66),\n", - " \"CEXIT4\": Float64Col(shape=(), dflt=0.0, pos=67),\n", - " \"CFVOL\": Float64Col(shape=(), dflt=0.0, pos=68),\n", - " \"CDEM1\": Float64Col(shape=(), dflt=0.0, pos=69),\n", - " \"CDEM2\": Float64Col(shape=(), dflt=0.0, pos=70)}\n", - " byteorder := 'little'\n", - " chunkshape := (141,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VCONFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AUX1FG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AUX2FG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AUX3FG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ODFVF1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ODFVF2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ODFVF3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ODFVF4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ODFVF5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ODGTF1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ODGTF2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ODGTF3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ODGTF4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ODGTF5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"FUNCT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"FUNCT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"FUNCT3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"FUNCT4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"FUNCT5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"FTBW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"FTBUCI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LEN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DELTH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"STCOR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DB50\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NEXITS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LKFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IREXIT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRMINV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CPREC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CEVAP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CFVOL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CFVOL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CFVOL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CFVOL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CFVOL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NOCGT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CTAG1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CPREC1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CTAG2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CPREC2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CTAG3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CPREC3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CTAG4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CPREC4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CTAG5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CPREC5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CTAG6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CPREC6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CTAG7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CPREC7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CPRI1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CEVAP1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CPRI2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CEVAP2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CPRI3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CEVAP3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CPRI4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CEVAP4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CPRI5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CEVAP5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CEXIT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CEXIT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CEXIT3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CEXIT4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CFVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CDEM1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CDEM2\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"CPREC\": StringCol(itemsize=1, shape=(), dflt=b'', pos=27),\n", + " \"CEVAP\": StringCol(itemsize=1, shape=(), dflt=b'', pos=28),\n", + " \"CFVOL1\": Float64Col(shape=(), dflt=0.0, pos=29),\n", + " \"CFVOL2\": Float64Col(shape=(), dflt=0.0, pos=30),\n", + " \"CFVOL3\": Float64Col(shape=(), dflt=0.0, pos=31),\n", + " \"CFVOL4\": StringCol(itemsize=1, shape=(), dflt=b'', pos=32),\n", + " \"CFVOL5\": StringCol(itemsize=1, shape=(), dflt=b'', pos=33),\n", + " \"NOCGT\": Float64Col(shape=(), dflt=0.0, pos=34),\n", + " \"CTAG1_CDEMAND\": StringCol(itemsize=1, shape=(), dflt=b'', pos=35),\n", + " \"CEXIT1_CDEMAND\": Float64Col(shape=(), dflt=0.0, pos=36),\n", + " \"CPRI1YR\": Float64Col(shape=(), dflt=0.0, pos=37),\n", + " \"CPRI1MO\": Float64Col(shape=(), dflt=0.0, pos=38),\n", + " \"CPRI1DY\": Float64Col(shape=(), dflt=0.0, pos=39),\n", + " \"CDEM1\": Float64Col(shape=(), dflt=0.0, pos=40),\n", + " \"CTAG2_CDEMAND\": StringCol(itemsize=1, shape=(), dflt=b'', pos=41),\n", + " \"CEXIT2_CDEMAND\": Float64Col(shape=(), dflt=0.0, pos=42),\n", + " \"CPRI2YR\": Float64Col(shape=(), dflt=0.0, pos=43),\n", + " \"CPRI2MO\": Float64Col(shape=(), dflt=0.0, pos=44),\n", + " \"CPRI2DY\": Float64Col(shape=(), dflt=0.0, pos=45),\n", + " \"CDEM2\": Float64Col(shape=(), dflt=0.0, pos=46),\n", + " \"CTAG1_CEVAP\": StringCol(itemsize=1, shape=(), dflt=b'', pos=47),\n", + " \"CPRI1_CEVAP\": Float64Col(shape=(), dflt=0.0, pos=48),\n", + " \"CEVAP1\": Float64Col(shape=(), dflt=0.0, pos=49),\n", + " \"CTAG2_CEVAP\": StringCol(itemsize=1, shape=(), dflt=b'', pos=50),\n", + " \"CPRI2_CEVAP\": Float64Col(shape=(), dflt=0.0, pos=51),\n", + " \"CEVAP2\": Float64Col(shape=(), dflt=0.0, pos=52),\n", + " \"CTAG3_CEVAP\": StringCol(itemsize=1, shape=(), dflt=b'', pos=53),\n", + " \"CPRI3_CEVAP\": Float64Col(shape=(), dflt=0.0, pos=54),\n", + " \"CEVAP3\": Float64Col(shape=(), dflt=0.0, pos=55),\n", + " \"CTAG4_CEVAP\": StringCol(itemsize=1, shape=(), dflt=b'', pos=56),\n", + " \"CPRI4_CEVAP\": Float64Col(shape=(), dflt=0.0, pos=57),\n", + " \"CEVAP4\": Float64Col(shape=(), dflt=0.0, pos=58),\n", + " \"CTAG5_CEVAP\": StringCol(itemsize=1, shape=(), dflt=b'', pos=59),\n", + " \"CPRI5_CEVAP\": Float64Col(shape=(), dflt=0.0, pos=60),\n", + " \"CEVAP5\": Float64Col(shape=(), dflt=0.0, pos=61),\n", + " \"CTAG1_CPREC\": StringCol(itemsize=1, shape=(), dflt=b'', pos=62),\n", + " \"CPREC1\": Float64Col(shape=(), dflt=0.0, pos=63),\n", + " \"CTAG2_CPREC\": StringCol(itemsize=1, shape=(), dflt=b'', pos=64),\n", + " \"CPREC2\": Float64Col(shape=(), dflt=0.0, pos=65),\n", + " \"CTAG3_CPREC\": StringCol(itemsize=1, shape=(), dflt=b'', pos=66),\n", + " \"CPREC3\": Float64Col(shape=(), dflt=0.0, pos=67),\n", + " \"CTAG4_CPREC\": StringCol(itemsize=1, shape=(), dflt=b'', pos=68),\n", + " \"CPREC4\": Float64Col(shape=(), dflt=0.0, pos=69),\n", + " \"CTAG5_CPREC\": StringCol(itemsize=1, shape=(), dflt=b'', pos=70),\n", + " \"CPREC5\": Float64Col(shape=(), dflt=0.0, pos=71),\n", + " \"CTAG6_CPREC\": StringCol(itemsize=1, shape=(), dflt=b'', pos=72),\n", + " \"CPREC6\": Float64Col(shape=(), dflt=0.0, pos=73),\n", + " \"CTAG7_CPREC\": StringCol(itemsize=1, shape=(), dflt=b'', pos=74),\n", + " \"CPREC7\": Float64Col(shape=(), dflt=0.0, pos=75),\n", + " \"IREXIT\": Float64Col(shape=(), dflt=0.0, pos=76),\n", + " \"IRMINV\": Float64Col(shape=(), dflt=0.0, pos=77),\n", + " \"NEXITS\": Int64Col(shape=(), dflt=0, pos=78),\n", + " \"LKFG\": Float64Col(shape=(), dflt=0.0, pos=79)}\n", + " byteorder := 'little'\n", + " chunkshape := (129,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VCONFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AUX1FG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AUX2FG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AUX3FG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ODFVF1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ODFVF2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ODFVF3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ODFVF4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ODFVF5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ODGTF1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ODGTF2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ODGTF3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ODGTF4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ODGTF5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FUNCT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FUNCT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FUNCT3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FUNCT4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FUNCT5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FTBW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FTBUCI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LEN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DELTH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"STCOR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DB50\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CPREC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CEVAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CFVOL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CFVOL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CFVOL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CFVOL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CFVOL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NOCGT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG1_CDEMAND\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CEXIT1_CDEMAND\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CPRI1YR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CPRI1MO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CPRI1DY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CDEM1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG2_CDEMAND\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CEXIT2_CDEMAND\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CPRI2YR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CPRI2MO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CPRI2DY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CDEM2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG1_CEVAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CPRI1_CEVAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CEVAP1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG2_CEVAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CPRI2_CEVAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CEVAP2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG3_CEVAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CPRI3_CEVAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CEVAP3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG4_CEVAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CPRI4_CEVAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CEVAP4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG5_CEVAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CPRI5_CEVAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CEVAP5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG1_CPREC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CPREC1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG2_CPREC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CPREC2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG3_CPREC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CPREC3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG4_CPREC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CPREC4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG5_CPREC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CPREC5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG6_CPREC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CPREC6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG7_CPREC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CPREC7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IREXIT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRMINV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NEXITS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LKFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/HYDR/SAVE (Group) ''\n", "/RCHRES/HYDR/SAVE/table (Table(5,)) ''\n", " description := {\n", @@ -6518,33 +6709,47 @@ " \"TAU\": Int64Col(shape=(), dflt=0, pos=18),\n", " \"USTAR\": Int64Col(shape=(), dflt=0, pos=19),\n", " \"VOL\": Int64Col(shape=(), dflt=0, pos=20),\n", - " \"VOLEV\": Int64Col(shape=(), dflt=0, pos=21)}\n", - " byteorder := 'little'\n", - " chunkshape := (381,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CDFVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CIVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CRO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CROVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"O\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PRSUPY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RIRDEM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RIRSHT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SAREA\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TAU\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"USTAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VOLEV\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"VOLEV\": Int64Col(shape=(), dflt=0, pos=21),\n", + " \"STAGE\": Int64Col(shape=(), dflt=0, pos=22),\n", + " \"AVDEP\": Int64Col(shape=(), dflt=0, pos=23),\n", + " \"TWID\": Int64Col(shape=(), dflt=0, pos=24),\n", + " \"HRAD\": Int64Col(shape=(), dflt=0, pos=25),\n", + " \"AVVEL\": Int64Col(shape=(), dflt=0, pos=26),\n", + " \"AVSECT\": Int64Col(shape=(), dflt=0, pos=27),\n", + " \"POTEV\": Int64Col(shape=(), dflt=0, pos=28)}\n", + " byteorder := 'little'\n", + " chunkshape := (287,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CDFVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CIVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CRO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CROVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"O\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PRSUPY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RIRDEM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RIRSHT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SAREA\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TAU\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"USTAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VOLEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"STAGE\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AVDEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TWID\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HRAD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AVVEL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AVSECT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"POTEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/HYDR/STATES (Group) ''\n", "/RCHRES/HYDR/STATES/table (Table(5,)) ''\n", " description := {\n", @@ -6561,53 +6766,66 @@ " \"OUTDG3\": Float64Col(shape=(), dflt=0.0, pos=10),\n", " \"OUTDG4\": Float64Col(shape=(), dflt=0.0, pos=11),\n", " \"OUTDG5\": Float64Col(shape=(), dflt=0.0, pos=12),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=13),\n", - " \"CTAG1\": StringCol(itemsize=1, shape=(), dflt=b'', pos=14),\n", - " \"CFRAC1\": Float64Col(shape=(), dflt=0.0, pos=15),\n", - " \"CTAG2\": StringCol(itemsize=1, shape=(), dflt=b'', pos=16),\n", - " \"CFRAC2\": Float64Col(shape=(), dflt=0.0, pos=17),\n", - " \"CTAG3\": StringCol(itemsize=1, shape=(), dflt=b'', pos=18),\n", - " \"CFRAC3\": Float64Col(shape=(), dflt=0.0, pos=19),\n", - " \"CTAG4\": StringCol(itemsize=1, shape=(), dflt=b'', pos=20),\n", - " \"CFRAC4\": Float64Col(shape=(), dflt=0.0, pos=21),\n", - " \"CTAG5\": StringCol(itemsize=1, shape=(), dflt=b'', pos=22),\n", - " \"CFRAC5\": Float64Col(shape=(), dflt=0.0, pos=23),\n", - " \"CTAG6\": StringCol(itemsize=1, shape=(), dflt=b'', pos=24),\n", - " \"CFRAC6\": Float64Col(shape=(), dflt=0.0, pos=25),\n", - " \"CTAG7\": StringCol(itemsize=1, shape=(), dflt=b'', pos=26),\n", - " \"CFRAC7\": Float64Col(shape=(), dflt=0.0, pos=27)}\n", + " \"CTAG1_CINIT\": StringCol(itemsize=1, shape=(), dflt=b'', pos=13),\n", + " \"CFRAC1\": Float64Col(shape=(), dflt=0.0, pos=14),\n", + " \"CTAG2_CINIT\": StringCol(itemsize=1, shape=(), dflt=b'', pos=15),\n", + " \"CFRAC2\": Float64Col(shape=(), dflt=0.0, pos=16),\n", + " \"CTAG3_CINIT\": StringCol(itemsize=1, shape=(), dflt=b'', pos=17),\n", + " \"CFRAC3\": Float64Col(shape=(), dflt=0.0, pos=18),\n", + " \"CTAG4_CINIT\": StringCol(itemsize=1, shape=(), dflt=b'', pos=19),\n", + " \"CFRAC4\": Float64Col(shape=(), dflt=0.0, pos=20),\n", + " \"CTAG5_CINIT\": StringCol(itemsize=1, shape=(), dflt=b'', pos=21),\n", + " \"CFRAC5\": Float64Col(shape=(), dflt=0.0, pos=22),\n", + " \"CTAG6_CINIT\": StringCol(itemsize=1, shape=(), dflt=b'', pos=23),\n", + " \"CFRAC6\": Float64Col(shape=(), dflt=0.0, pos=24),\n", + " \"CTAG7_CINIT\": StringCol(itemsize=1, shape=(), dflt=b'', pos=25),\n", + " \"CFRAC7\": Float64Col(shape=(), dflt=0.0, pos=26)}\n", + " byteorder := 'little'\n", + " chunkshape := (402,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ICAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COLIN1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COLIN2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COLIN3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COLIN4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COLIN5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OUTDG1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OUTDG2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OUTDG3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OUTDG4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OUTDG5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG1_CINIT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CFRAC1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG2_CINIT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CFRAC2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG3_CINIT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CFRAC3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG4_CINIT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CFRAC4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG5_CINIT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CFRAC5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG6_CINIT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CFRAC6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CTAG7_CINIT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CFRAC7\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/RCHRES/HTRCH/FLAGS (Group) ''\n", + "/RCHRES/HTRCH/FLAGS/table (Table(5,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"BEDFLG\": Float64Col(shape=(), dflt=0.0, pos=1),\n", + " \"TGFLG\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"TSTOP\": Float64Col(shape=(), dflt=0.0, pos=3)}\n", " byteorder := 'little'\n", - " chunkshape := (399,)\n", + " chunkshape := (2340,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ICAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COLIN1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COLIN2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COLIN3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COLIN4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COLIN5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OUTDG1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OUTDG2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OUTDG3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OUTDG4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OUTDG5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CTAG1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CFRAC1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CTAG2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CFRAC2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CTAG3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CFRAC3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CTAG4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CFRAC4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CTAG5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CFRAC5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CTAG6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CFRAC6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CTAG7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CFRAC7\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BEDFLG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TGFLG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSTOP\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/HTRCH/PARAMETERS (Group) ''\n", "/RCHRES/HTRCH/PARAMETERS/table (Table(5,)) ''\n", " description := {\n", @@ -6622,37 +6840,35 @@ " \"TGRND\": Float64Col(shape=(), dflt=0.0, pos=8),\n", " \"KMUD\": Float64Col(shape=(), dflt=0.0, pos=9),\n", " \"KGRND\": Float64Col(shape=(), dflt=0.0, pos=10),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=11),\n", - " \"SHADFG\": Float64Col(shape=(), dflt=0.0, pos=12),\n", - " \"TOPFL\": Float64Col(shape=(), dflt=0.0, pos=13),\n", - " \"VEGFL\": Float64Col(shape=(), dflt=0.0, pos=14),\n", - " \"NSSP\": Float64Col(shape=(), dflt=0.0, pos=15),\n", - " \"LATDEG\": Float64Col(shape=(), dflt=0.0, pos=16),\n", - " \"LONDEG\": Float64Col(shape=(), dflt=0.0, pos=17),\n", - " \"LONSTD\": Float64Col(shape=(), dflt=0.0, pos=18)}\n", - " byteorder := 'little'\n", - " chunkshape := (464,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ELEV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ELDAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CFSAEX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KATRAD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KCOND\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KEVAP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MUDDEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TGRND\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KMUD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KGRND\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SHADFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TOPFL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VEGFL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NSSP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LATDEG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LONDEG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LONSTD\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"SHADFG\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"TOPFL\": Float64Col(shape=(), dflt=0.0, pos=12),\n", + " \"VEGFL\": Float64Col(shape=(), dflt=0.0, pos=13),\n", + " \"NSSP\": Float64Col(shape=(), dflt=0.0, pos=14),\n", + " \"LATDEG\": Float64Col(shape=(), dflt=0.0, pos=15),\n", + " \"LONDEG\": Float64Col(shape=(), dflt=0.0, pos=16),\n", + " \"LONSTD\": Float64Col(shape=(), dflt=0.0, pos=17)}\n", + " byteorder := 'little'\n", + " chunkshape := (468,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ELEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ELDAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CFSAEX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KATRAD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KCOND\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KEVAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MUDDEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TGRND\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KMUD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KGRND\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SHADFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TOPFL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VEGFL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NSSP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LATDEG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LONDEG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LONSTD\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/HTRCH/SAVE (Group) ''\n", "/RCHRES/HTRCH/SAVE/table (Table(5,)) ''\n", " description := {\n", @@ -6676,38 +6892,73 @@ " chunkshape := (528,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AIRTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"HTCF4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"HTEXCH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IHEAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OHEAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROHEAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SHDFAC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QTOTAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QSOLAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QLONGW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QCON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QEVAP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QPREC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QBED\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AIRTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HTCF4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HTEXCH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IHEAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OHEAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROHEAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SHDFAC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QTOTAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QSOLAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QLONGW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QCON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QEVAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QPREC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QBED\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/HTRCH/STATES (Group) ''\n", "/RCHRES/HTRCH/STATES/table (Table(5,)) ''\n", " description := {\n", " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", " \"TW\": Float64Col(shape=(), dflt=0.0, pos=1),\n", - " \"AIRTMP\": Float64Col(shape=(), dflt=0.0, pos=2),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=3)}\n", + " \"AIRTMP\": Float64Col(shape=(), dflt=0.0, pos=2)}\n", " byteorder := 'little'\n", - " chunkshape := (3120,)\n", + " chunkshape := (3276,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AIRTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AIRTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/GQUAL/EXTENDEDS (Group) ''\n", + "/RCHRES/GQUAL/FLAGS (Group) ''\n", + "/RCHRES/GQUAL/FLAGS/table (Table(5,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"GQADFG1\": Float64Col(shape=(), dflt=0.0, pos=1),\n", + " \"GQADFG2\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"GQADFG3\": Float64Col(shape=(), dflt=0.0, pos=3),\n", + " \"GQADFG4\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"GQADFG5\": Float64Col(shape=(), dflt=0.0, pos=5),\n", + " \"GQADFG6\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"GQADFG7\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"GQADFG8\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"GQADFG9\": Float64Col(shape=(), dflt=0.0, pos=9),\n", + " \"GQADFG10\": Float64Col(shape=(), dflt=0.0, pos=10),\n", + " \"GQADFG11\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"GQADFG12\": Float64Col(shape=(), dflt=0.0, pos=12),\n", + " \"GQADFG13\": Float64Col(shape=(), dflt=0.0, pos=13),\n", + " \"GQADFG14\": Float64Col(shape=(), dflt=0.0, pos=14)}\n", + " byteorder := 'little'\n", + " chunkshape := (564,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQADFG1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQADFG2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQADFG3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQADFG4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQADFG5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQADFG6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQADFG7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQADFG8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQADFG9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQADFG10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQADFG11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQADFG12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQADFG13\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQADFG14\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/GQUAL/GQUAL1 (Group) ''\n", "/RCHRES/GQUAL/GQUAL1/table (Table(5,)) ''\n", " description := {\n", @@ -6763,64 +7014,253 @@ " \"ROC\": Float64Col(shape=(), dflt=0.0, pos=49),\n", " \"CLD\": Float64Col(shape=(), dflt=0.0, pos=50),\n", " \"SDCNC\": Float64Col(shape=(), dflt=0.0, pos=51),\n", - " \"PHY\": Float64Col(shape=(), dflt=0.0, pos=52)}\n", - " byteorder := 'little'\n", - " chunkshape := (159,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONCID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QTYID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QALFG1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QALFG2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QALFG3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QALFG4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QALFG5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QALFG6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QALFG7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KA\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KB\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"THHYD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"THOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CFGAS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BIOCON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"THBIO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BIO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"FSTDEC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"THFST\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADDCP1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADDCP2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADDCP3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADDCP4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADPM11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADPM21\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADPM31\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADPM41\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADPM51\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADPM61\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADPM12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADPM22\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADPM32\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADPM42\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADPM52\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADPM62\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SQAL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SQAL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SQAL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SQAL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SQAL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SQAL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TWAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHVAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CLD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SDCNC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHY\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"PHY\": Float64Col(shape=(), dflt=0.0, pos=52),\n", + " \"ADPM13\": Float64Col(shape=(), dflt=0.0, pos=53),\n", + " \"ADPM23\": Float64Col(shape=(), dflt=0.0, pos=54),\n", + " \"ADPM33\": Float64Col(shape=(), dflt=0.0, pos=55),\n", + " \"ADPM43\": Float64Col(shape=(), dflt=0.0, pos=56),\n", + " \"ADPM53\": Float64Col(shape=(), dflt=0.0, pos=57),\n", + " \"ADPM63\": Float64Col(shape=(), dflt=0.0, pos=58),\n", + " \"GQPM21\": Float64Col(shape=(), dflt=0.0, pos=59),\n", + " \"GQPM22\": Float64Col(shape=(), dflt=0.0, pos=60),\n", + " \"GQPM23\": Float64Col(shape=(), dflt=0.0, pos=61),\n", + " \"GQPM24\": Float64Col(shape=(), dflt=0.0, pos=62),\n", + " \"GQPM25\": Float64Col(shape=(), dflt=0.0, pos=63),\n", + " \"GQPM26\": Float64Col(shape=(), dflt=0.0, pos=64),\n", + " \"GQPM27\": Float64Col(shape=(), dflt=0.0, pos=65)}\n", + " byteorder := 'little'\n", + " chunkshape := (127,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQID\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONCID\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QTYID\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KA\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KB\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"THHYD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"THOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CFGAS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BIOCON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"THBIO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BIO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FSTDEC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"THFST\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADDCP1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADDCP2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADDCP3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADDCP4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM21\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM31\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM41\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM51\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM61\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM22\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM32\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM42\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM52\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM62\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TWAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHVAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CLD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDCNC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM13\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM23\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM33\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM43\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM53\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM63\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM21\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM22\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM23\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM24\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM25\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM26\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM27\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/RCHRES/GQUAL/GQUAL2 (Group) ''\n", + "/RCHRES/GQUAL/GQUAL2/table (Table(5,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"TWAT\": Float64Col(shape=(), dflt=0.0, pos=1),\n", + " \"PHVAL\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"ROC\": Float64Col(shape=(), dflt=0.0, pos=3),\n", + " \"CLD\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"SDCNC\": Float64Col(shape=(), dflt=0.0, pos=5),\n", + " \"PHY\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"ADPM13\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"ADPM23\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"ADPM33\": Float64Col(shape=(), dflt=0.0, pos=9),\n", + " \"ADPM43\": Float64Col(shape=(), dflt=0.0, pos=10),\n", + " \"ADPM53\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"ADPM63\": Float64Col(shape=(), dflt=0.0, pos=12),\n", + " \"GQPM21\": Float64Col(shape=(), dflt=0.0, pos=13),\n", + " \"GQPM22\": Float64Col(shape=(), dflt=0.0, pos=14),\n", + " \"GQPM23\": Float64Col(shape=(), dflt=0.0, pos=15),\n", + " \"GQPM24\": Float64Col(shape=(), dflt=0.0, pos=16),\n", + " \"GQPM25\": Float64Col(shape=(), dflt=0.0, pos=17),\n", + " \"GQPM26\": Float64Col(shape=(), dflt=0.0, pos=18),\n", + " \"GQPM27\": Float64Col(shape=(), dflt=0.0, pos=19),\n", + " \"QALFG1\": Float64Col(shape=(), dflt=0.0, pos=20),\n", + " \"QALFG2\": Float64Col(shape=(), dflt=0.0, pos=21),\n", + " \"QALFG3\": Float64Col(shape=(), dflt=0.0, pos=22),\n", + " \"QALFG4\": Float64Col(shape=(), dflt=0.0, pos=23),\n", + " \"QALFG5\": Float64Col(shape=(), dflt=0.0, pos=24),\n", + " \"QALFG6\": Float64Col(shape=(), dflt=0.0, pos=25),\n", + " \"QALFG7\": Float64Col(shape=(), dflt=0.0, pos=26),\n", + " \"SQAL1\": Float64Col(shape=(), dflt=0.0, pos=27),\n", + " \"SQAL2\": Float64Col(shape=(), dflt=0.0, pos=28),\n", + " \"SQAL3\": Float64Col(shape=(), dflt=0.0, pos=29),\n", + " \"SQAL4\": Float64Col(shape=(), dflt=0.0, pos=30),\n", + " \"SQAL5\": Float64Col(shape=(), dflt=0.0, pos=31),\n", + " \"SQAL6\": Float64Col(shape=(), dflt=0.0, pos=32),\n", + " \"ADDCP1\": Float64Col(shape=(), dflt=0.0, pos=33),\n", + " \"ADDCP2\": Float64Col(shape=(), dflt=0.0, pos=34),\n", + " \"ADDCP3\": Float64Col(shape=(), dflt=0.0, pos=35),\n", + " \"ADDCP4\": Float64Col(shape=(), dflt=0.0, pos=36)}\n", + " byteorder := 'little'\n", + " chunkshape := (224,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TWAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHVAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CLD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDCNC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM13\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM23\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM33\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM43\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM53\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM63\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM21\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM22\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM23\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM24\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM25\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM26\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM27\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADDCP1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADDCP2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADDCP3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADDCP4\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/RCHRES/GQUAL/GQUAL3 (Group) ''\n", + "/RCHRES/GQUAL/GQUAL3/table (Table(5,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"TWAT\": Float64Col(shape=(), dflt=0.0, pos=1),\n", + " \"PHVAL\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"ROC\": Float64Col(shape=(), dflt=0.0, pos=3),\n", + " \"CLD\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"SDCNC\": Float64Col(shape=(), dflt=0.0, pos=5),\n", + " \"PHY\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"ADPM13\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"ADPM23\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"ADPM33\": Float64Col(shape=(), dflt=0.0, pos=9),\n", + " \"ADPM43\": Float64Col(shape=(), dflt=0.0, pos=10),\n", + " \"ADPM53\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"ADPM63\": Float64Col(shape=(), dflt=0.0, pos=12),\n", + " \"GQPM21\": Float64Col(shape=(), dflt=0.0, pos=13),\n", + " \"GQPM22\": Float64Col(shape=(), dflt=0.0, pos=14),\n", + " \"GQPM23\": Float64Col(shape=(), dflt=0.0, pos=15),\n", + " \"GQPM24\": Float64Col(shape=(), dflt=0.0, pos=16),\n", + " \"GQPM25\": Float64Col(shape=(), dflt=0.0, pos=17),\n", + " \"GQPM26\": Float64Col(shape=(), dflt=0.0, pos=18),\n", + " \"GQPM27\": Float64Col(shape=(), dflt=0.0, pos=19),\n", + " \"QALFG1\": Float64Col(shape=(), dflt=0.0, pos=20),\n", + " \"QALFG2\": Float64Col(shape=(), dflt=0.0, pos=21),\n", + " \"QALFG3\": Float64Col(shape=(), dflt=0.0, pos=22),\n", + " \"QALFG4\": Float64Col(shape=(), dflt=0.0, pos=23),\n", + " \"QALFG5\": Float64Col(shape=(), dflt=0.0, pos=24),\n", + " \"QALFG6\": Float64Col(shape=(), dflt=0.0, pos=25),\n", + " \"QALFG7\": Float64Col(shape=(), dflt=0.0, pos=26),\n", + " \"SQAL1\": Float64Col(shape=(), dflt=0.0, pos=27),\n", + " \"SQAL2\": Float64Col(shape=(), dflt=0.0, pos=28),\n", + " \"SQAL3\": Float64Col(shape=(), dflt=0.0, pos=29),\n", + " \"SQAL4\": Float64Col(shape=(), dflt=0.0, pos=30),\n", + " \"SQAL5\": Float64Col(shape=(), dflt=0.0, pos=31),\n", + " \"SQAL6\": Float64Col(shape=(), dflt=0.0, pos=32),\n", + " \"ADDCP1\": Float64Col(shape=(), dflt=0.0, pos=33),\n", + " \"ADDCP2\": Float64Col(shape=(), dflt=0.0, pos=34),\n", + " \"ADDCP3\": Float64Col(shape=(), dflt=0.0, pos=35),\n", + " \"ADDCP4\": Float64Col(shape=(), dflt=0.0, pos=36)}\n", + " byteorder := 'little'\n", + " chunkshape := (224,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TWAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHVAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CLD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDCNC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM13\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM23\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM33\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM43\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM53\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADPM63\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM21\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM22\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM23\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM24\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM25\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM26\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQPM27\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QALFG7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQAL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQAL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQAL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQAL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQAL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQAL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADDCP1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADDCP2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADDCP3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADDCP4\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/RCHRES/GQUAL/MONTHLY (Group) ''\n", "/RCHRES/GQUAL/PARAMETERS (Group) ''\n", "/RCHRES/GQUAL/PARAMETERS/table (Table(5,)) ''\n", " description := {\n", @@ -6832,22 +7272,20 @@ " \"CLDFG\": Int64Col(shape=(), dflt=0, pos=5),\n", " \"SDFG\": Int64Col(shape=(), dflt=0, pos=6),\n", " \"PHYTFG\": Int64Col(shape=(), dflt=0, pos=7),\n", - " \"LAT\": Int64Col(shape=(), dflt=0, pos=8),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=9)}\n", + " \"LAT\": Int64Col(shape=(), dflt=0, pos=8)}\n", " byteorder := 'little'\n", - " chunkshape := (949,)\n", + " chunkshape := (963,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NGQUAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TEMPFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHFLAG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROXFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CLDFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SDFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHYTFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NGQUAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TEMPFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHFLAG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROXFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CLDFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYTFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/GQUAL/SAVE (Group) ''\n", "/RCHRES/GQUAL/SAVE/table (Table(5,)) ''\n", " description := {\n", @@ -6878,29 +7316,194 @@ " chunkshape := (364,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DDQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DSQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQADDR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQADEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQADWT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IDQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ISQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ODQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OSQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PDQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RDQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RODQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROSQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RRQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RSQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SQDEC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TIQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TOSQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TROQAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DDQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DSQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQADDR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQADEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQADWT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IDQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ISQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ODQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OSQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PDQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RDQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RODQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROSQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RRQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RSQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQDEC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TIQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TOSQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TROQAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/RCHRES/GQUAL/MONTHLY/CLDM (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY/CLDM/table (Table(5,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"CLDM1\": Float64Col(shape=(), dflt=0.0, pos=1),\n", + " \"CLDM2\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"CLDM3\": Float64Col(shape=(), dflt=0.0, pos=3),\n", + " \"CLDM4\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"CLDM5\": Float64Col(shape=(), dflt=0.0, pos=5),\n", + " \"CLDM6\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"CLDM7\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"CLDM8\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"CLDM9\": Float64Col(shape=(), dflt=0.0, pos=9),\n", + " \"CLDM10\": Float64Col(shape=(), dflt=0.0, pos=10),\n", + " \"CLDM11\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"CLDM12\": Float64Col(shape=(), dflt=0.0, pos=12)}\n", + " byteorder := 'little'\n", + " chunkshape := (655,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CLDM1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CLDM2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CLDM3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CLDM4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CLDM5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CLDM6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CLDM7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CLDM8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CLDM9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CLDM10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CLDM11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CLDM12\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/RCHRES/GQUAL/MONTHLY/PHYM (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY/PHYM/table (Table(5,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"PHYM1\": Float64Col(shape=(), dflt=0.0, pos=1),\n", + " \"PHYM2\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"PHYM3\": Float64Col(shape=(), dflt=0.0, pos=3),\n", + " \"PHYM4\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"PHYM5\": Float64Col(shape=(), dflt=0.0, pos=5),\n", + " \"PHYM6\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"PHYM7\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"PHYM8\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"PHYM9\": Float64Col(shape=(), dflt=0.0, pos=9),\n", + " \"PHYM10\": Float64Col(shape=(), dflt=0.0, pos=10),\n", + " \"PHYM11\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"PHYM12\": Float64Col(shape=(), dflt=0.0, pos=12)}\n", + " byteorder := 'little'\n", + " chunkshape := (655,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYM1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYM2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYM3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYM4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYM5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYM6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYM7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYM8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYM9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYM10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYM11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHYM12\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/RCHRES/GQUAL/MONTHLY/ROCM (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY/ROCM/table (Table(5,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"ROCM1\": Float64Col(shape=(), dflt=0.0, pos=1),\n", + " \"ROCM2\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"ROCM3\": Float64Col(shape=(), dflt=0.0, pos=3),\n", + " \"ROCM4\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"ROCM5\": Float64Col(shape=(), dflt=0.0, pos=5),\n", + " \"ROCM6\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"ROCM7\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"ROCM8\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"ROCM9\": Float64Col(shape=(), dflt=0.0, pos=9),\n", + " \"ROCM10\": Float64Col(shape=(), dflt=0.0, pos=10),\n", + " \"ROCM11\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"ROCM12\": Float64Col(shape=(), dflt=0.0, pos=12)}\n", + " byteorder := 'little'\n", + " chunkshape := (655,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROCM1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROCM2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROCM3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROCM4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROCM5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROCM6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROCM7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROCM8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROCM9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROCM10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROCM11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROCM12\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/RCHRES/GQUAL/MONTHLY/SDCN (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY/SDCN/table (Table(5,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"SDCN1\": Float64Col(shape=(), dflt=0.0, pos=1),\n", + " \"SDCN2\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"SDCN3\": Float64Col(shape=(), dflt=0.0, pos=3),\n", + " \"SDCN4\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"SDCN5\": Float64Col(shape=(), dflt=0.0, pos=5),\n", + " \"SDCN6\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"SDCN7\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"SDCN8\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"SDCN9\": Float64Col(shape=(), dflt=0.0, pos=9),\n", + " \"SDCN10\": Float64Col(shape=(), dflt=0.0, pos=10),\n", + " \"SDCN11\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"SDCN12\": Float64Col(shape=(), dflt=0.0, pos=12)}\n", + " byteorder := 'little'\n", + " chunkshape := (655,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDCN1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDCN2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDCN3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDCN4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDCN5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDCN6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDCN7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDCN8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDCN9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDCN10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDCN11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDCN12\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/RCHRES/GQUAL/MONTHLY/TEMP (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY/TEMP/table (Table(5,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"TEMP1\": Float64Col(shape=(), dflt=0.0, pos=1),\n", + " \"TEMP2\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"TEMP3\": Float64Col(shape=(), dflt=0.0, pos=3),\n", + " \"TEMP4\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"TEMP5\": Float64Col(shape=(), dflt=0.0, pos=5),\n", + " \"TEMP6\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"TEMP7\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"TEMP8\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"TEMP9\": Float64Col(shape=(), dflt=0.0, pos=9),\n", + " \"TEMP10\": Float64Col(shape=(), dflt=0.0, pos=10),\n", + " \"TEMP11\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"TEMP12\": Float64Col(shape=(), dflt=0.0, pos=12)}\n", + " byteorder := 'little'\n", + " chunkshape := (655,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TEMP1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TEMP2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TEMP3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TEMP4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TEMP5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TEMP6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TEMP7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TEMP8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TEMP9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TEMP10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TEMP11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TEMP12\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/GQUAL/EXTENDEDS/ALPH (Group) ''\n", "/RCHRES/GQUAL/EXTENDEDS/ALPH/table (Table(5,)) ''\n", " description := {\n", @@ -6927,25 +7530,25 @@ " chunkshape := (442,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALPH0\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALPH1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALPH2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALPH3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALPH4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALPH5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALPH6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALPH7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALPH8\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALPH9\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALPH10\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALPH11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALPH12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALPH13\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALPH14\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALPH15\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALPH16\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALPH17\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALPH0\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALPH1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALPH2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALPH3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALPH4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALPH5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALPH6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALPH7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALPH8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALPH9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALPH10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALPH11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALPH12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALPH13\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALPH14\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALPH15\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALPH16\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALPH17\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/GQUAL/EXTENDEDS/DEL (Group) ''\n", "/RCHRES/GQUAL/EXTENDEDS/DEL/table (Table(5,)) ''\n", " description := {\n", @@ -6972,25 +7575,25 @@ " chunkshape := (442,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEL0\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEL1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEL2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEL3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEL4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEL5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEL6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEL7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEL8\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEL9\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEL10\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEL11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEL12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEL13\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEL14\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEL15\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEL16\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEL17\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEL0\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEL1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEL2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEL3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEL4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEL5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEL6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEL7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEL8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEL9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEL10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEL11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEL12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEL13\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEL14\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEL15\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEL16\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEL17\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/GQUAL/EXTENDEDS/GAMM (Group) ''\n", "/RCHRES/GQUAL/EXTENDEDS/GAMM/table (Table(5,)) ''\n", " description := {\n", @@ -7017,25 +7620,25 @@ " chunkshape := (442,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GAMM0\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GAMM1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GAMM2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GAMM3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GAMM4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GAMM5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GAMM6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GAMM7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GAMM8\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GAMM9\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GAMM10\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GAMM11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GAMM12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GAMM13\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GAMM14\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GAMM15\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GAMM16\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GAMM17\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GAMM0\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GAMM1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GAMM2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GAMM3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GAMM4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GAMM5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GAMM6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GAMM7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GAMM8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GAMM9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GAMM10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GAMM11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GAMM12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GAMM13\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GAMM14\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GAMM15\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GAMM16\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GAMM17\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/GQUAL/EXTENDEDS/KCLD (Group) ''\n", "/RCHRES/GQUAL/EXTENDEDS/KCLD/table (Table(5,)) ''\n", " description := {\n", @@ -7062,25 +7665,25 @@ " chunkshape := (442,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KCLD0\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KCLD1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KCLD2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KCLD3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KCLD4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KCLD5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KCLD6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KCLD7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KCLD8\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KCLD9\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KCLD10\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KCLD11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KCLD12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KCLD13\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KCLD14\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KCLD15\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KCLD16\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KCLD17\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KCLD0\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KCLD1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KCLD2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KCLD3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KCLD4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KCLD5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KCLD6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KCLD7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KCLD8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KCLD9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KCLD10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KCLD11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KCLD12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KCLD13\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KCLD14\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KCLD15\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KCLD16\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KCLD17\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/GQUAL/EXTENDEDS/PHOTPM (Group) ''\n", "/RCHRES/GQUAL/EXTENDEDS/PHOTPM/table (Table(5,)) ''\n", " description := {\n", @@ -7109,27 +7712,27 @@ " chunkshape := (399,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOTPM0\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOTPM1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOTPM2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOTPM3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOTPM4\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOTPM5\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOTPM6\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOTPM7\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOTPM8\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOTPM9\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOTPM10\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOTPM11\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOTPM12\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOTPM13\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOTPM14\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOTPM15\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOTPM16\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOTPM17\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOTPM18\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOTPM19\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOTPM0\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOTPM1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOTPM2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOTPM3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOTPM4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOTPM5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOTPM6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOTPM7\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOTPM8\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOTPM9\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOTPM10\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOTPM11\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOTPM12\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOTPM13\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOTPM14\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOTPM15\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOTPM16\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOTPM17\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOTPM18\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOTPM19\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/GENERAL/ACTIVITY (Group) ''\n", "/RCHRES/GENERAL/ACTIVITY/table (Table(5,)) ''\n", " description := {\n", @@ -7139,75 +7742,88 @@ " \"CONS\": Int64Col(shape=(), dflt=0, pos=3),\n", " \"HTRCH\": Int64Col(shape=(), dflt=0, pos=4),\n", " \"SEDTRN\": Int64Col(shape=(), dflt=0, pos=5),\n", - " \"GQUAL\": Int64Col(shape=(), dflt=0, pos=6),\n", - " \"OXRX\": Int64Col(shape=(), dflt=0, pos=7),\n", - " \"NUTRX\": Int64Col(shape=(), dflt=0, pos=8),\n", - " \"PLANK\": Int64Col(shape=(), dflt=0, pos=9),\n", - " \"PHCARB\": Int64Col(shape=(), dflt=0, pos=10),\n", - " \"HYDRFG\": Int64Col(shape=(), dflt=0, pos=11),\n", - " \"ADFG\": Int64Col(shape=(), dflt=0, pos=12),\n", - " \"CONSFG\": Int64Col(shape=(), dflt=0, pos=13),\n", - " \"HTFG\": Int64Col(shape=(), dflt=0, pos=14),\n", - " \"SEDFG\": Int64Col(shape=(), dflt=0, pos=15),\n", - " \"GQALFG\": Int64Col(shape=(), dflt=0, pos=16),\n", - " \"OXFG\": Int64Col(shape=(), dflt=0, pos=17),\n", - " \"NUTFG\": Int64Col(shape=(), dflt=0, pos=18),\n", - " \"PLKFG\": Int64Col(shape=(), dflt=0, pos=19),\n", - " \"PHFG\": Int64Col(shape=(), dflt=0, pos=20)}\n", + " \"SEDFG\": Int64Col(shape=(), dflt=0, pos=6),\n", + " \"GQUAL\": Int64Col(shape=(), dflt=0, pos=7),\n", + " \"OXRX\": Int64Col(shape=(), dflt=0, pos=8),\n", + " \"NUTRX\": Int64Col(shape=(), dflt=0, pos=9),\n", + " \"PLANK\": Int64Col(shape=(), dflt=0, pos=10),\n", + " \"PHCARB\": Int64Col(shape=(), dflt=0, pos=11)}\n", " byteorder := 'little'\n", - " chunkshape := (399,)\n", + " chunkshape := (712,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"HYDR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADCALC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"HTRCH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SEDTRN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQUAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXRX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUTRX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLANK\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHCARB\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"HYDRFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONSFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"HTFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SEDFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GQALFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OXFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NUTFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PLKFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HYDR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADCALC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HTRCH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SEDTRN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SEDFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQUAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXRX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUTRX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLANK\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCARB\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/GENERAL/INFO (Group) ''\n", "/RCHRES/GENERAL/INFO/table (Table(5,)) ''\n", " description := {\n", " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", " \"RCHID\": StringCol(itemsize=18, shape=(), dflt=b'', pos=1),\n", - " \"IUNITS\": Int64Col(shape=(), dflt=0, pos=2),\n", - " \"OUNITS\": Int64Col(shape=(), dflt=0, pos=3),\n", - " \"PUNITE\": Int64Col(shape=(), dflt=0, pos=4),\n", - " \"PUNITM\": Int64Col(shape=(), dflt=0, pos=5),\n", - " \"BUNITE\": Int64Col(shape=(), dflt=0, pos=6),\n", - " \"BUNITM\": Int64Col(shape=(), dflt=0, pos=7),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=8),\n", - " \"NEXITS\": Int64Col(shape=(), dflt=0, pos=9),\n", - " \"LKFG\": Int64Col(shape=(), dflt=0, pos=10)}\n", - " byteorder := 'little'\n", - " chunkshape := (753,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RCHID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IUNITS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OUNITS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PUNITE\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PUNITM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BUNITE\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BUNITM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NEXITS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LKFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"NEXITS\": Int64Col(shape=(), dflt=0, pos=2),\n", + " \"IUNITS\": Int64Col(shape=(), dflt=0, pos=3),\n", + " \"OUNITS\": Int64Col(shape=(), dflt=0, pos=4),\n", + " \"PUNITE\": Int64Col(shape=(), dflt=0, pos=5),\n", + " \"PUNITM\": Int64Col(shape=(), dflt=0, pos=6),\n", + " \"LKFG\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"BUNITE\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"BUNITM\": Float64Col(shape=(), dflt=0.0, pos=9)}\n", + " byteorder := 'little'\n", + " chunkshape := (762,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RCHID\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NEXITS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IUNITS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OUNITS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PUNITE\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PUNITM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LKFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BUNITE\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BUNITM\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/RCHRES/GENERAL/PRINT (Group) ''\n", + "/RCHRES/GENERAL/PRINT/table (Table(5,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"HYDRPR\": Int64Col(shape=(), dflt=0, pos=1),\n", + " \"ADCAPR\": Int64Col(shape=(), dflt=0, pos=2),\n", + " \"CONSPR\": Int64Col(shape=(), dflt=0, pos=3),\n", + " \"HEATPR\": Int64Col(shape=(), dflt=0, pos=4),\n", + " \"SEDPR\": Int64Col(shape=(), dflt=0, pos=5),\n", + " \"GQLPR\": Int64Col(shape=(), dflt=0, pos=6),\n", + " \"OXRXPR\": Int64Col(shape=(), dflt=0, pos=7),\n", + " \"NUTRPR\": Int64Col(shape=(), dflt=0, pos=8),\n", + " \"PLNKPR\": Int64Col(shape=(), dflt=0, pos=9),\n", + " \"PHCBPR\": Int64Col(shape=(), dflt=0, pos=10),\n", + " \"PIVLPR\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"PYREND\": Int64Col(shape=(), dflt=0, pos=12)}\n", + " byteorder := 'little'\n", + " chunkshape := (655,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HYDRPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADCAPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONSPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HEATPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SEDPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GQLPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OXRXPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NUTRPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLNKPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHCBPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PIVLPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PYREND\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/CONS/CONS1 (Group) ''\n", "/RCHRES/CONS/CONS1/table (Table(5,)) ''\n", " description := {\n", @@ -7221,12 +7837,12 @@ " chunkshape := (1820,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONCID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CONV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QTYID\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONID\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONCID\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CONV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QTYID\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/CONS/PARAMETERS (Group) ''\n", "/RCHRES/CONS/PARAMETERS/table (Table(5,)) ''\n", " description := {\n", @@ -7236,8 +7852,8 @@ " chunkshape := (5461,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NCONS\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NCONS\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/RCHRES/CONS/SAVE (Group) ''\n", "/RCHRES/CONS/SAVE/table (Table(5,)) ''\n", " description := {\n", @@ -7253,14 +7869,149 @@ " chunkshape := (1092,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COADDR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COADEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COADWT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ICON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OCON\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ROCON\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COADDR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COADEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COADWT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ICON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OCON\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ROCON\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/RCHRES/ACIDPH/STATES (Group) ''\n", + "/RCHRES/ACIDPH/STATES/table (Table(5,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"ACCONC1\": Float64Col(shape=(), dflt=0.0, pos=1),\n", + " \"ACCONC2\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"ACCONC3\": Float64Col(shape=(), dflt=0.0, pos=3),\n", + " \"ACCONC4\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"ACCONC5\": Float64Col(shape=(), dflt=0.0, pos=5),\n", + " \"ACCONC6\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"ACCONC7\": Float64Col(shape=(), dflt=0.0, pos=7)}\n", + " byteorder := 'little'\n", + " chunkshape := (1092,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ACCONC1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ACCONC2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ACCONC3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ACCONC4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ACCONC5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ACCONC6\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ACCONC7\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/PLTGEN/CURV-DATA1 (Group) ''\n", + "/PLTGEN/CURV-DATA1/table (Table(2,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"LABEL\": StringCol(itemsize=16, shape=(), dflt=b'', pos=1),\n", + " \"LINTYP\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"INTEQ\": Int64Col(shape=(), dflt=0, pos=3),\n", + " \"COLCOD\": Int64Col(shape=(), dflt=0, pos=4),\n", + " \"TRAN\": StringCol(itemsize=4, shape=(), dflt=b'', pos=5)}\n", + " byteorder := 'little'\n", + " chunkshape := (1365,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LABEL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LINTYP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INTEQ\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COLCOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TRAN\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/PLTGEN/CURV-DATA2 (Group) ''\n", + "/PLTGEN/CURV-DATA2/table (Table(2,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"LABEL\": StringCol(itemsize=15, shape=(), dflt=b'', pos=1),\n", + " \"LINTYP\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"INTEQ\": Int64Col(shape=(), dflt=0, pos=3),\n", + " \"COLCOD\": Int64Col(shape=(), dflt=0, pos=4),\n", + " \"TRAN\": StringCol(itemsize=4, shape=(), dflt=b'', pos=5)}\n", + " byteorder := 'little'\n", + " chunkshape := (1394,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LABEL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LINTYP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INTEQ\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COLCOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TRAN\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/PLTGEN/CURV-DATA3 (Group) ''\n", + "/PLTGEN/CURV-DATA3/table (Table(2,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"LABEL\": StringCol(itemsize=12, shape=(), dflt=b'', pos=1),\n", + " \"LINTYP\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"INTEQ\": Float64Col(shape=(), dflt=0.0, pos=3),\n", + " \"COLCOD\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"TRAN\": StringCol(itemsize=4, shape=(), dflt=b'', pos=5)}\n", + " byteorder := 'little'\n", + " chunkshape := (1489,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LABEL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LINTYP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INTEQ\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COLCOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TRAN\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/PLTGEN/CURV-DATA4 (Group) ''\n", + "/PLTGEN/CURV-DATA4/table (Table(2,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"LABEL\": StringCol(itemsize=16, shape=(), dflt=b'', pos=1),\n", + " \"LINTYP\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"INTEQ\": Float64Col(shape=(), dflt=0.0, pos=3),\n", + " \"COLCOD\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"TRAN\": StringCol(itemsize=3, shape=(), dflt=b'', pos=5)}\n", + " byteorder := 'little'\n", + " chunkshape := (1394,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LABEL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LINTYP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INTEQ\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COLCOD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TRAN\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/PLTGEN/PARAMETERS (Group) ''\n", + "/PLTGEN/PARAMETERS/table (Table(2,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"PLOTFL\": Int64Col(shape=(), dflt=0, pos=1),\n", + " \"NPT\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"NMN\": Int64Col(shape=(), dflt=0, pos=3),\n", + " \"LABLFG\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"PYREND\": Float64Col(shape=(), dflt=0.0, pos=5),\n", + " \"PIVL\": Int64Col(shape=(), dflt=0, pos=6),\n", + " \"TYPEFG\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"TITLE\": StringCol(itemsize=39, shape=(), dflt=b'', pos=8),\n", + " \"YLABL\": StringCol(itemsize=3, shape=(), dflt=b'', pos=9),\n", + " \"YMIN\": Float64Col(shape=(), dflt=0.0, pos=10),\n", + " \"YMAX\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"IVLIN\": Float64Col(shape=(), dflt=0.0, pos=12),\n", + " \"THRESH\": Float64Col(shape=(), dflt=0.0, pos=13)}\n", + " byteorder := 'little'\n", + " chunkshape := (489,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PLOTFL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NPT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NMN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LABLFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PYREND\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PIVL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TYPEFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TITLE\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"YLABL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"YMIN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"YMAX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IVLIN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"THRESH\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/PERLND/ATEMP (Group) ''\n", "/PERLND/GENERAL (Group) ''\n", "/PERLND/PSTEMP (Group) ''\n", "/PERLND/PWATER (Group) ''\n", @@ -7271,18 +8022,16 @@ " description := {\n", " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", " \"ICEFG\": Int64Col(shape=(), dflt=0, pos=1),\n", - " \"SNOPFG\": Int64Col(shape=(), dflt=0, pos=2),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=3),\n", - " \"VKMFG\": Int64Col(shape=(), dflt=0, pos=4)}\n", + " \"SNOPFG\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"VKMFG\": Float64Col(shape=(), dflt=0.0, pos=3)}\n", " byteorder := 'little'\n", - " chunkshape := (2259,)\n", + " chunkshape := (2340,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ICEFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOPFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VKMFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ICEFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOPFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VKMFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/PERLND/SNOW/PARAMETERS (Group) ''\n", "/PERLND/SNOW/PARAMETERS/table (Table(1,)) ''\n", " description := {\n", @@ -7299,27 +8048,25 @@ " \"SNOEVP\": Float64Col(shape=(), dflt=0.0, pos=10),\n", " \"CCFACT\": Float64Col(shape=(), dflt=0.0, pos=11),\n", " \"MWATER\": Float64Col(shape=(), dflt=0.0, pos=12),\n", - " \"MGMELT\": Float64Col(shape=(), dflt=0.0, pos=13),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=14)}\n", - " byteorder := 'little'\n", - " chunkshape := (601,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MELEV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SHADE\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOWCF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COVIND\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KMELT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TBASE\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RDCSN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSNOW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOEVP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CCFACT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MWATER\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MGMELT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"MGMELT\": Float64Col(shape=(), dflt=0.0, pos=13)}\n", + " byteorder := 'little'\n", + " chunkshape := (606,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MELEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SHADE\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOWCF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COVIND\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KMELT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TBASE\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RDCSN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSNOW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOEVP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CCFACT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MWATER\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MGMELT\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/PERLND/SNOW/SAVE (Group) ''\n", "/PERLND/SNOW/SAVE/table (Table(1,)) ''\n", " description := {\n", @@ -7350,29 +8097,29 @@ " chunkshape := (364,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALBEDO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COVINX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEWTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DULL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MELT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NEGHTS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACKF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACKI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACKW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACK\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PAKTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PDEPTH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PRAIN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RAINF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RDENPF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SKYCLR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOCOV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOWE\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOWF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"WYIELD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"XLNMLT\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALBEDO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COVINX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEWTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DULL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MELT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NEGHTS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACKF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACKI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACKW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACK\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PAKTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PDEPTH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PRAIN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RAINF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RDENPF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SKYCLR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOCOV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOWE\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOWF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"WYIELD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"XLNMLT\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/PERLND/SNOW/STATES (Group) ''\n", "/PERLND/SNOW/STATES/table (Table(1,)) ''\n", " description := {\n", @@ -7385,29 +8132,21 @@ " \"PAKTMP\": Float64Col(shape=(), dflt=0.0, pos=6),\n", " \"COVINX\": Float64Col(shape=(), dflt=0.0, pos=7),\n", " \"XLNMLT\": Float64Col(shape=(), dflt=0.0, pos=8),\n", - " \"SKYCLR\": Float64Col(shape=(), dflt=0.0, pos=9),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=10),\n", - " \"PKSNOW\": Float64Col(shape=(), dflt=0.0, pos=11),\n", - " \"PKICE\": Float64Col(shape=(), dflt=0.0, pos=12),\n", - " \"PKWATR\": Float64Col(shape=(), dflt=0.0, pos=13)}\n", - " byteorder := 'little'\n", - " chunkshape := (648,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACKF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACKI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACKW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RDENPF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DULL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PAKTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COVINX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"XLNMLT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SKYCLR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKSNOW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKICE\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKWATR\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"SKYCLR\": Float64Col(shape=(), dflt=0.0, pos=9)}\n", + " byteorder := 'little'\n", + " chunkshape := (862,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACKF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACKI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACKW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RDENPF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DULL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PAKTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COVINX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"XLNMLT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SKYCLR\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/PERLND/PWTGAS/PARAMETERS (Group) ''\n", "/PERLND/PWTGAS/PARAMETERS/table (Table(1,)) ''\n", " description := {\n", @@ -7421,48 +8160,46 @@ " \"SLIFAC\": Float64Col(shape=(), dflt=0.0, pos=7),\n", " \"ILIFAC\": Float64Col(shape=(), dflt=0.0, pos=8),\n", " \"ALIFAC\": Float64Col(shape=(), dflt=0.0, pos=9),\n", - " \"SOTMP\": Float64Col(shape=(), dflt=0.0, pos=10),\n", - " \"IOTMP\": Float64Col(shape=(), dflt=0.0, pos=11),\n", - " \"AOTMP\": Float64Col(shape=(), dflt=0.0, pos=12),\n", - " \"SODOX\": Float64Col(shape=(), dflt=0.0, pos=13),\n", - " \"SOCO2\": Float64Col(shape=(), dflt=0.0, pos=14),\n", - " \"IODOX\": Float64Col(shape=(), dflt=0.0, pos=15),\n", - " \"IOCO2\": Float64Col(shape=(), dflt=0.0, pos=16),\n", - " \"AODOX\": Float64Col(shape=(), dflt=0.0, pos=17),\n", - " \"AOCO2\": Float64Col(shape=(), dflt=0.0, pos=18),\n", - " \"OPNID\": StringCol(itemsize=2, shape=(), dflt=b'', pos=19),\n", - " \"IDVFG\": Int64Col(shape=(), dflt=0, pos=20),\n", - " \"ICVFG\": Int64Col(shape=(), dflt=0, pos=21),\n", - " \"GDVFG\": Int64Col(shape=(), dflt=0, pos=22),\n", - " \"GCVFG\": Int64Col(shape=(), dflt=0, pos=23)}\n", - " byteorder := 'little'\n", - " chunkshape := (360,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ELEV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IDOXP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ICO2P\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ADOXP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ACO2P\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SDLFAC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SLIFAC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ILIFAC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALIFAC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IOTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AOTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SODOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IODOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IOCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AODOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AOCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IDVFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ICVFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GDVFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GCVFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"SODOX\": Float64Col(shape=(), dflt=0.0, pos=10),\n", + " \"SOCO2\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"IODOX\": Float64Col(shape=(), dflt=0.0, pos=12),\n", + " \"IOCO2\": Float64Col(shape=(), dflt=0.0, pos=13),\n", + " \"AODOX\": Float64Col(shape=(), dflt=0.0, pos=14),\n", + " \"AOCO2\": Float64Col(shape=(), dflt=0.0, pos=15),\n", + " \"IDVFG\": Float64Col(shape=(), dflt=0.0, pos=16),\n", + " \"ICVFG\": Float64Col(shape=(), dflt=0.0, pos=17),\n", + " \"GDVFG\": Float64Col(shape=(), dflt=0.0, pos=18),\n", + " \"GCVFG\": Float64Col(shape=(), dflt=0.0, pos=19),\n", + " \"SOTMP\": Float64Col(shape=(), dflt=0.0, pos=20),\n", + " \"IOTMP\": Float64Col(shape=(), dflt=0.0, pos=21),\n", + " \"AOTMP\": Float64Col(shape=(), dflt=0.0, pos=22)}\n", + " byteorder := 'little'\n", + " chunkshape := (364,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ELEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IDOXP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ICO2P\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ADOXP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ACO2P\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDLFAC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SLIFAC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ILIFAC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALIFAC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SODOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IODOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IOCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AODOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AOCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IDVFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ICVFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GDVFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GCVFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IOTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AOTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/PERLND/PWTGAS/SAVE (Group) ''\n", "/PERLND/PWTGAS/SAVE/table (Table(1,)) ''\n", " description := {\n", @@ -7492,28 +8229,28 @@ " chunkshape := (381,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AOCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AOCO2M\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AODOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AODOXM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AOHT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AOTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IOCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IOCO2M\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IODOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IODOXM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IOHT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IOTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"POCO2M\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PODOXM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"POHT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOCO2M\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SODOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SODOXM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOHT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AOCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AOCO2M\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AODOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AODOXM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AOHT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AOTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IOCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IOCO2M\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IODOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IODOXM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IOHT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IOTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"POCO2M\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PODOXM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"POHT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOCO2M\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SODOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SODOXM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOHT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/PERLND/PWATER/MONTHLY (Group) ''\n", "/PERLND/PWATER/PARAMETERS (Group) ''\n", "/PERLND/PWATER/PARAMETERS/table (Table(1,)) ''\n", @@ -7528,220 +8265,220 @@ " \"VIFWFG\": Int64Col(shape=(), dflt=0, pos=7),\n", " \"VIRCFG\": Int64Col(shape=(), dflt=0, pos=8),\n", " \"VLEFG\": Int64Col(shape=(), dflt=0, pos=9),\n", - " \"IFFCFG\": Int64Col(shape=(), dflt=0, pos=10),\n", - " \"HWTFG\": Int64Col(shape=(), dflt=0, pos=11),\n", - " \"IRRGFG\": Int64Col(shape=(), dflt=0, pos=12),\n", - " \"IFRDFG\": Int64Col(shape=(), dflt=0, pos=13),\n", - " \"FOREST\": Float64Col(shape=(), dflt=0.0, pos=14),\n", - " \"LZSN\": Float64Col(shape=(), dflt=0.0, pos=15),\n", - " \"INFILT\": Float64Col(shape=(), dflt=0.0, pos=16),\n", - " \"LSUR\": Float64Col(shape=(), dflt=0.0, pos=17),\n", - " \"SLSUR\": Float64Col(shape=(), dflt=0.0, pos=18),\n", - " \"KVARY\": Float64Col(shape=(), dflt=0.0, pos=19),\n", - " \"AGWRC\": Float64Col(shape=(), dflt=0.0, pos=20),\n", - " \"PETMAX\": Float64Col(shape=(), dflt=0.0, pos=21),\n", - " \"PETMIN\": Float64Col(shape=(), dflt=0.0, pos=22),\n", - " \"INFEXP\": Float64Col(shape=(), dflt=0.0, pos=23),\n", - " \"INFILD\": Float64Col(shape=(), dflt=0.0, pos=24),\n", - " \"DEEPFR\": Float64Col(shape=(), dflt=0.0, pos=25),\n", - " \"BASETP\": Float64Col(shape=(), dflt=0.0, pos=26),\n", - " \"AGWETP\": Float64Col(shape=(), dflt=0.0, pos=27),\n", - " \"CEPSC\": Float64Col(shape=(), dflt=0.0, pos=28),\n", - " \"UZSN\": Float64Col(shape=(), dflt=0.0, pos=29),\n", - " \"NSUR\": Float64Col(shape=(), dflt=0.0, pos=30),\n", - " \"INTFW\": Float64Col(shape=(), dflt=0.0, pos=31),\n", - " \"IRC\": Float64Col(shape=(), dflt=0.0, pos=32),\n", - " \"LZETP\": Float64Col(shape=(), dflt=0.0, pos=33),\n", - " \"FZG\": Float64Col(shape=(), dflt=0.0, pos=34),\n", - " \"FZGL\": Float64Col(shape=(), dflt=0.0, pos=35),\n", - " \"OPNID\": StringCol(itemsize=3, shape=(), dflt=b'', pos=36),\n", - " \"MELEV\": Float64Col(shape=(), dflt=0.0, pos=37),\n", - " \"BELV\": Float64Col(shape=(), dflt=0.0, pos=38),\n", - " \"GWDATM\": Float64Col(shape=(), dflt=0.0, pos=39),\n", - " \"PCW\": Float64Col(shape=(), dflt=0.0, pos=40),\n", - " \"PGW\": Float64Col(shape=(), dflt=0.0, pos=41),\n", - " \"UPGW\": Float64Col(shape=(), dflt=0.0, pos=42),\n", - " \"STABNO\": Float64Col(shape=(), dflt=0.0, pos=43),\n", - " \"SRRC\": Float64Col(shape=(), dflt=0.0, pos=44),\n", - " \"SREXP\": Float64Col(shape=(), dflt=0.0, pos=45),\n", - " \"IFWSC\": Float64Col(shape=(), dflt=0.0, pos=46),\n", - " \"DELTA\": Float64Col(shape=(), dflt=0.0, pos=47),\n", - " \"UELFAC\": Float64Col(shape=(), dflt=0.0, pos=48),\n", - " \"LELFAC\": Float64Col(shape=(), dflt=0.0, pos=49),\n", - " \"SWILTP\": Float64Col(shape=(), dflt=0.0, pos=50),\n", - " \"UWILTP\": Float64Col(shape=(), dflt=0.0, pos=51),\n", - " \"LWILTP\": Float64Col(shape=(), dflt=0.0, pos=52),\n", - " \"AWILTP\": Float64Col(shape=(), dflt=0.0, pos=53),\n", - " \"SFDCAP\": Float64Col(shape=(), dflt=0.0, pos=54),\n", - " \"UFDCAP\": Float64Col(shape=(), dflt=0.0, pos=55),\n", - " \"LFDCAP\": Float64Col(shape=(), dflt=0.0, pos=56),\n", - " \"AFDCAP\": Float64Col(shape=(), dflt=0.0, pos=57),\n", - " \"NCRP\": Int64Col(shape=(), dflt=0, pos=58),\n", - " \"PMON1\": Int64Col(shape=(), dflt=0, pos=59),\n", - " \"PDAY1\": Int64Col(shape=(), dflt=0, pos=60),\n", - " \"HMON1\": Int64Col(shape=(), dflt=0, pos=61),\n", - " \"HDAY1\": Int64Col(shape=(), dflt=0, pos=62),\n", - " \"PMON2\": Int64Col(shape=(), dflt=0, pos=63),\n", - " \"PDAY2\": Int64Col(shape=(), dflt=0, pos=64),\n", - " \"HMON2\": Int64Col(shape=(), dflt=0, pos=65),\n", - " \"HDAY2\": Int64Col(shape=(), dflt=0, pos=66),\n", - " \"PMON3\": Int64Col(shape=(), dflt=0, pos=67),\n", - " \"PDAY3\": Int64Col(shape=(), dflt=0, pos=68),\n", - " \"HMON3\": Int64Col(shape=(), dflt=0, pos=69),\n", - " \"HDAY3\": Int64Col(shape=(), dflt=0, pos=70),\n", - " \"NSKED\": Int64Col(shape=(), dflt=0, pos=71),\n", - " \"SZONFG\": Int64Col(shape=(), dflt=0, pos=72),\n", - " \"VCRDFG\": Int64Col(shape=(), dflt=0, pos=73),\n", - " \"VAWDFG\": Int64Col(shape=(), dflt=0, pos=74),\n", - " \"IROPFG\": Int64Col(shape=(), dflt=0, pos=75),\n", - " \"IRAREA\": Float64Col(shape=(), dflt=0.0, pos=76),\n", - " \"IREFF\": Float64Col(shape=(), dflt=0.0, pos=77),\n", - " \"ARZI\": Float64Col(shape=(), dflt=0.0, pos=78),\n", - " \"WILTP\": Float64Col(shape=(), dflt=0.0, pos=79),\n", - " \"FLDCAP\": Float64Col(shape=(), dflt=0.0, pos=80),\n", - " \"CRDEP\": Float64Col(shape=(), dflt=0.0, pos=81),\n", - " \"IRAWD\": Float64Col(shape=(), dflt=0.0, pos=82),\n", - " \"CAPRIS\": Float64Col(shape=(), dflt=0.0, pos=83),\n", - " \"XPRIOR\": Float64Col(shape=(), dflt=0.0, pos=84),\n", - " \"XFRAC\": Float64Col(shape=(), dflt=0.0, pos=85),\n", - " \"GPRIOR\": Float64Col(shape=(), dflt=0.0, pos=86),\n", - " \"GFRAC\": Float64Col(shape=(), dflt=0.0, pos=87),\n", - " \"RPRIOR\": Float64Col(shape=(), dflt=0.0, pos=88),\n", - " \"RFRAC\": Float64Col(shape=(), dflt=0.0, pos=89),\n", - " \"IRCHNO\": Float64Col(shape=(), dflt=0.0, pos=90),\n", - " \"IRCPFR\": Float64Col(shape=(), dflt=0.0, pos=91),\n", - " \"IRSUFR\": Float64Col(shape=(), dflt=0.0, pos=92),\n", - " \"IRUPFR\": Float64Col(shape=(), dflt=0.0, pos=93),\n", - " \"IRLOFR\": Float64Col(shape=(), dflt=0.0, pos=94),\n", - " \"IRGWFR\": Float64Col(shape=(), dflt=0.0, pos=95),\n", - " \"IRYR1\": Float64Col(shape=(), dflt=0.0, pos=96),\n", - " \"IRMO1\": Float64Col(shape=(), dflt=0.0, pos=97),\n", - " \"IRDY1\": Float64Col(shape=(), dflt=0.0, pos=98),\n", - " \"IRHR1\": Float64Col(shape=(), dflt=0.0, pos=99),\n", - " \"IRMI1\": Float64Col(shape=(), dflt=0.0, pos=100),\n", - " \"IRDUR1\": Float64Col(shape=(), dflt=0.0, pos=101),\n", - " \"IRRAT1\": Float64Col(shape=(), dflt=0.0, pos=102),\n", - " \"IRYR2\": Float64Col(shape=(), dflt=0.0, pos=103),\n", - " \"IRMO2\": Float64Col(shape=(), dflt=0.0, pos=104),\n", - " \"IRDY2\": Float64Col(shape=(), dflt=0.0, pos=105),\n", - " \"IRHR2\": Float64Col(shape=(), dflt=0.0, pos=106),\n", - " \"IRMI2\": Float64Col(shape=(), dflt=0.0, pos=107),\n", - " \"IRDUR2\": Float64Col(shape=(), dflt=0.0, pos=108),\n", - " \"IRRAT2\": Float64Col(shape=(), dflt=0.0, pos=109)}\n", - " byteorder := 'little'\n", - " chunkshape := (75,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CSNOFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RTOPFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"UZFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VCSFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VUZFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VNNFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VIFWFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VIRCFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VLEFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IFFCFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"HWTFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRRGFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IFRDFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"FOREST\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LZSN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INFILT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LSUR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SLSUR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KVARY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AGWRC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PETMAX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PETMIN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INFEXP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INFILD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEEPFR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BASETP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AGWETP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CEPSC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"UZSN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NSUR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INTFW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LZETP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"FZG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"FZGL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MELEV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BELV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GWDATM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PCW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PGW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"UPGW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"STABNO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SRRC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SREXP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IFWSC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DELTA\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"UELFAC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LELFAC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SWILTP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"UWILTP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LWILTP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AWILTP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SFDCAP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"UFDCAP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LFDCAP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AFDCAP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NCRP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PMON1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PDAY1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"HMON1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"HDAY1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PMON2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PDAY2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"HMON2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"HDAY2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PMON3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PDAY3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"HMON3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"HDAY3\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NSKED\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SZONFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VCRDFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VAWDFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IROPFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRAREA\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IREFF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ARZI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"WILTP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"FLDCAP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CRDEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRAWD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CAPRIS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"XPRIOR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"XFRAC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GPRIOR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GFRAC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RPRIOR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RFRAC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRCHNO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRCPFR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRSUFR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRUPFR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRLOFR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRGWFR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRYR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRMO1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRDY1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRHR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRMI1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRDUR1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRRAT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRYR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRMO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRDY2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRHR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRMI2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRDUR2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRRAT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"IFFCFG\": Float64Col(shape=(), dflt=0.0, pos=10),\n", + " \"HWTFG\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"IRRGFG\": Float64Col(shape=(), dflt=0.0, pos=12),\n", + " \"IFRDFG\": Float64Col(shape=(), dflt=0.0, pos=13),\n", + " \"NCANPY\": Float64Col(shape=(), dflt=0.0, pos=14),\n", + " \"FOREST\": Float64Col(shape=(), dflt=0.0, pos=15),\n", + " \"LZSN\": Float64Col(shape=(), dflt=0.0, pos=16),\n", + " \"INFILT\": Float64Col(shape=(), dflt=0.0, pos=17),\n", + " \"LSUR\": Float64Col(shape=(), dflt=0.0, pos=18),\n", + " \"SLSUR\": Float64Col(shape=(), dflt=0.0, pos=19),\n", + " \"KVARY\": Float64Col(shape=(), dflt=0.0, pos=20),\n", + " \"AGWRC\": Float64Col(shape=(), dflt=0.0, pos=21),\n", + " \"PETMAX\": Float64Col(shape=(), dflt=0.0, pos=22),\n", + " \"PETMIN\": Float64Col(shape=(), dflt=0.0, pos=23),\n", + " \"INFEXP\": Float64Col(shape=(), dflt=0.0, pos=24),\n", + " \"INFILD\": Float64Col(shape=(), dflt=0.0, pos=25),\n", + " \"DEEPFR\": Float64Col(shape=(), dflt=0.0, pos=26),\n", + " \"BASETP\": Float64Col(shape=(), dflt=0.0, pos=27),\n", + " \"AGWETP\": Float64Col(shape=(), dflt=0.0, pos=28),\n", + " \"CEPSC\": Float64Col(shape=(), dflt=0.0, pos=29),\n", + " \"UZSN\": Float64Col(shape=(), dflt=0.0, pos=30),\n", + " \"NSUR\": Float64Col(shape=(), dflt=0.0, pos=31),\n", + " \"INTFW\": Float64Col(shape=(), dflt=0.0, pos=32),\n", + " \"IRC\": Float64Col(shape=(), dflt=0.0, pos=33),\n", + " \"LZETP\": Float64Col(shape=(), dflt=0.0, pos=34),\n", + " \"NCRP\": Float64Col(shape=(), dflt=0.0, pos=35),\n", + " \"PMON1\": Float64Col(shape=(), dflt=0.0, pos=36),\n", + " \"PDAY1\": Float64Col(shape=(), dflt=0.0, pos=37),\n", + " \"HMON1\": Float64Col(shape=(), dflt=0.0, pos=38),\n", + " \"HDAY1\": Float64Col(shape=(), dflt=0.0, pos=39),\n", + " \"PMON2\": Float64Col(shape=(), dflt=0.0, pos=40),\n", + " \"PDAY2\": Float64Col(shape=(), dflt=0.0, pos=41),\n", + " \"HMON2\": Float64Col(shape=(), dflt=0.0, pos=42),\n", + " \"HDAY2\": Float64Col(shape=(), dflt=0.0, pos=43),\n", + " \"PMON3\": Float64Col(shape=(), dflt=0.0, pos=44),\n", + " \"PDAY3\": Float64Col(shape=(), dflt=0.0, pos=45),\n", + " \"HMON3\": Float64Col(shape=(), dflt=0.0, pos=46),\n", + " \"HDAY3\": Float64Col(shape=(), dflt=0.0, pos=47),\n", + " \"NSKED\": Float64Col(shape=(), dflt=0.0, pos=48),\n", + " \"SZONFG\": Float64Col(shape=(), dflt=0.0, pos=49),\n", + " \"VCRDFG\": Float64Col(shape=(), dflt=0.0, pos=50),\n", + " \"VAWDFG\": Float64Col(shape=(), dflt=0.0, pos=51),\n", + " \"IROPFG\": Float64Col(shape=(), dflt=0.0, pos=52),\n", + " \"IRAREA\": Float64Col(shape=(), dflt=0.0, pos=53),\n", + " \"IREFF\": Float64Col(shape=(), dflt=0.0, pos=54),\n", + " \"ARZI\": Float64Col(shape=(), dflt=0.0, pos=55),\n", + " \"WILTP\": Float64Col(shape=(), dflt=0.0, pos=56),\n", + " \"FLDCAP\": Float64Col(shape=(), dflt=0.0, pos=57),\n", + " \"CRDEP\": Float64Col(shape=(), dflt=0.0, pos=58),\n", + " \"IRAWD\": Float64Col(shape=(), dflt=0.0, pos=59),\n", + " \"CAPRIS\": Float64Col(shape=(), dflt=0.0, pos=60),\n", + " \"IRYR1\": Float64Col(shape=(), dflt=0.0, pos=61),\n", + " \"IRMO1\": Float64Col(shape=(), dflt=0.0, pos=62),\n", + " \"IRDY1\": Float64Col(shape=(), dflt=0.0, pos=63),\n", + " \"IRHR1\": Float64Col(shape=(), dflt=0.0, pos=64),\n", + " \"IRMI1\": Float64Col(shape=(), dflt=0.0, pos=65),\n", + " \"IRDUR1\": Float64Col(shape=(), dflt=0.0, pos=66),\n", + " \"IRRAT1\": Float64Col(shape=(), dflt=0.0, pos=67),\n", + " \"IRYR2\": Float64Col(shape=(), dflt=0.0, pos=68),\n", + " \"IRMO2\": Float64Col(shape=(), dflt=0.0, pos=69),\n", + " \"IRDY2\": Float64Col(shape=(), dflt=0.0, pos=70),\n", + " \"IRHR2\": Float64Col(shape=(), dflt=0.0, pos=71),\n", + " \"IRMI2\": Float64Col(shape=(), dflt=0.0, pos=72),\n", + " \"IRDUR2\": Float64Col(shape=(), dflt=0.0, pos=73),\n", + " \"IRRAT2\": Float64Col(shape=(), dflt=0.0, pos=74),\n", + " \"XPRIOR\": Float64Col(shape=(), dflt=0.0, pos=75),\n", + " \"XFRAC\": Float64Col(shape=(), dflt=0.0, pos=76),\n", + " \"GPRIOR\": Float64Col(shape=(), dflt=0.0, pos=77),\n", + " \"GFRAC\": Float64Col(shape=(), dflt=0.0, pos=78),\n", + " \"RPRIOR\": Float64Col(shape=(), dflt=0.0, pos=79),\n", + " \"RFRAC\": Float64Col(shape=(), dflt=0.0, pos=80),\n", + " \"IRCHNO\": Float64Col(shape=(), dflt=0.0, pos=81),\n", + " \"IRCPFR\": Float64Col(shape=(), dflt=0.0, pos=82),\n", + " \"IRSUFR\": Float64Col(shape=(), dflt=0.0, pos=83),\n", + " \"IRUPFR\": Float64Col(shape=(), dflt=0.0, pos=84),\n", + " \"IRLOFR\": Float64Col(shape=(), dflt=0.0, pos=85),\n", + " \"IRGWFR\": Float64Col(shape=(), dflt=0.0, pos=86),\n", + " \"FZG\": Float64Col(shape=(), dflt=0.0, pos=87),\n", + " \"FZGL\": Float64Col(shape=(), dflt=0.0, pos=88),\n", + " \"MELEV\": Float64Col(shape=(), dflt=0.0, pos=89),\n", + " \"BELV\": Float64Col(shape=(), dflt=0.0, pos=90),\n", + " \"GWDATM\": Float64Col(shape=(), dflt=0.0, pos=91),\n", + " \"PCW\": Float64Col(shape=(), dflt=0.0, pos=92),\n", + " \"PGW\": Float64Col(shape=(), dflt=0.0, pos=93),\n", + " \"UPGW\": Float64Col(shape=(), dflt=0.0, pos=94),\n", + " \"STABNO\": Float64Col(shape=(), dflt=0.0, pos=95),\n", + " \"SRRC\": Float64Col(shape=(), dflt=0.0, pos=96),\n", + " \"SREXP\": Float64Col(shape=(), dflt=0.0, pos=97),\n", + " \"IFWSC\": Float64Col(shape=(), dflt=0.0, pos=98),\n", + " \"DELTA\": Float64Col(shape=(), dflt=0.0, pos=99),\n", + " \"UELFAC\": Float64Col(shape=(), dflt=0.0, pos=100),\n", + " \"LELFAC\": Float64Col(shape=(), dflt=0.0, pos=101),\n", + " \"SWILTP\": Float64Col(shape=(), dflt=0.0, pos=102),\n", + " \"UWILTP\": Float64Col(shape=(), dflt=0.0, pos=103),\n", + " \"LWILTP\": Float64Col(shape=(), dflt=0.0, pos=104),\n", + " \"AWILTP\": Float64Col(shape=(), dflt=0.0, pos=105),\n", + " \"SFDCAP\": Float64Col(shape=(), dflt=0.0, pos=106),\n", + " \"UFDCAP\": Float64Col(shape=(), dflt=0.0, pos=107),\n", + " \"LFDCAP\": Float64Col(shape=(), dflt=0.0, pos=108),\n", + " \"AFDCAP\": Float64Col(shape=(), dflt=0.0, pos=109)}\n", + " byteorder := 'little'\n", + " chunkshape := (74,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CSNOFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RTOPFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VCSFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VUZFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VNNFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VIFWFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VIRCFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VLEFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IFFCFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HWTFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRRGFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IFRDFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NCANPY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FOREST\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LZSN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INFILT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LSUR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SLSUR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KVARY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AGWRC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PETMAX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PETMIN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INFEXP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INFILD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEEPFR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BASETP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AGWETP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CEPSC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZSN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NSUR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INTFW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LZETP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NCRP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PMON1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PDAY1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HMON1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HDAY1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PMON2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PDAY2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HMON2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HDAY2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PMON3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PDAY3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HMON3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"HDAY3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NSKED\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SZONFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VCRDFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VAWDFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IROPFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRAREA\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IREFF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ARZI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"WILTP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FLDCAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CRDEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRAWD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CAPRIS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRYR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRMO1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRDY1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRHR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRMI1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRDUR1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRRAT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRYR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRMO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRDY2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRHR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRMI2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRDUR2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRRAT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"XPRIOR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"XFRAC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GPRIOR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GFRAC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RPRIOR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RFRAC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRCHNO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRCPFR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRSUFR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRUPFR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRLOFR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRGWFR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FZG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FZGL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MELEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BELV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GWDATM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PCW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PGW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UPGW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"STABNO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SRRC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SREXP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IFWSC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DELTA\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UELFAC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LELFAC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SWILTP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UWILTP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LWILTP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AWILTP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SFDCAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UFDCAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LFDCAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AFDCAP\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/PERLND/PWATER/SAVE (Group) ''\n", "/PERLND/PWATER/SAVE/table (Table(1,)) ''\n", " description := {\n", @@ -7793,50 +8530,50 @@ " chunkshape := (188,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AGWET\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AGWLI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AGWI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AGWO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AGWS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BASET\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CEPE\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CEPS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GWVS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IFWI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IFWLI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IFWO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IFWS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IGWI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INFIL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRDRAW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRRAPP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRRDEM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IRSHRT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LZET\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LZI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LZLI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LZS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RPARM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PERC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PERO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PERS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PET\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PETADJ\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RZWS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SUPY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SURET\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SURLI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SURI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SURO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SURS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TAET\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TGWS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"UZET\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"UZI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"UZLI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"UZS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INFFAC\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AGWET\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AGWLI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AGWI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AGWO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AGWS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BASET\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CEPE\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CEPS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GWVS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IFWI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IFWLI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IFWO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IFWS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IGWI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INFIL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRDRAW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRRAPP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRRDEM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IRSHRT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LZET\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LZI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LZLI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LZS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RPARM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PERC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PERO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PERS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PET\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PETADJ\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RZWS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SUPY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SURET\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SURLI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SURI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SURO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SURS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TAET\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TGWS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZET\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZLI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INFFAC\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/PERLND/PWATER/STATES (Group) ''\n", "/PERLND/PWATER/STATES/table (Table(1,)) ''\n", " description := {\n", @@ -7847,21 +8584,19 @@ " \"IFWS\": Float64Col(shape=(), dflt=0.0, pos=4),\n", " \"LZS\": Float64Col(shape=(), dflt=0.0, pos=5),\n", " \"AGWS\": Float64Col(shape=(), dflt=0.0, pos=6),\n", - " \"GWVS\": Float64Col(shape=(), dflt=0.0, pos=7),\n", - " \"OPNID\": StringCol(itemsize=3, shape=(), dflt=b'', pos=8)}\n", + " \"GWVS\": Float64Col(shape=(), dflt=0.0, pos=7)}\n", " byteorder := 'little'\n", - " chunkshape := (1040,)\n", + " chunkshape := (1092,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CEPS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SURS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"UZS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IFWS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LZS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AGWS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"GWVS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CEPS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SURS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IFWS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LZS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AGWS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GWVS\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/PERLND/PWATER/MONTHLY/CEPSC (Group) ''\n", "/PERLND/PWATER/MONTHLY/CEPSC/table (Table(1,)) ''\n", " description := {\n", @@ -7882,19 +8617,19 @@ " chunkshape := (655,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"JAN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"FEB\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"APR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MAY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"JUN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"JUL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AUG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OCT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NOV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEC\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"JAN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FEB\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"APR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MAY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"JUN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"JUL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AUG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OCT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NOV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEC\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/PERLND/PWATER/MONTHLY/LZETP (Group) ''\n", "/PERLND/PWATER/MONTHLY/LZETP/table (Table(1,)) ''\n", " description := {\n", @@ -7915,19 +8650,19 @@ " chunkshape := (655,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"JAN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"FEB\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"APR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MAY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"JUN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"JUL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AUG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OCT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NOV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEC\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"JAN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FEB\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"APR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MAY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"JUN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"JUL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AUG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OCT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NOV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEC\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/PERLND/PWATER/MONTHLY/NSUR (Group) ''\n", "/PERLND/PWATER/MONTHLY/NSUR/table (Table(1,)) ''\n", " description := {\n", @@ -7948,52 +8683,52 @@ " chunkshape := (655,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"JAN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"FEB\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"APR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MAY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"JUN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"JUL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AUG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OCT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NOV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEC\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"JAN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FEB\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"APR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MAY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"JUN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"JUL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AUG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OCT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NOV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEC\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/PERLND/PWATER/MONTHLY/UZSN (Group) ''\n", "/PERLND/PWATER/MONTHLY/UZSN/table (Table(1,)) ''\n", " description := {\n", " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", - " \"JAN\": Float64Col(shape=(), dflt=0.0, pos=1),\n", - " \"FEB\": Float64Col(shape=(), dflt=0.0, pos=2),\n", - " \"MAR\": Float64Col(shape=(), dflt=0.0, pos=3),\n", - " \"APR\": Float64Col(shape=(), dflt=0.0, pos=4),\n", - " \"MAY\": Float64Col(shape=(), dflt=0.0, pos=5),\n", - " \"JUN\": Float64Col(shape=(), dflt=0.0, pos=6),\n", - " \"JUL\": Float64Col(shape=(), dflt=0.0, pos=7),\n", - " \"AUG\": Float64Col(shape=(), dflt=0.0, pos=8),\n", - " \"SEP\": Float64Col(shape=(), dflt=0.0, pos=9),\n", - " \"OCT\": Float64Col(shape=(), dflt=0.0, pos=10),\n", - " \"NOV\": Float64Col(shape=(), dflt=0.0, pos=11),\n", - " \"DEC\": Float64Col(shape=(), dflt=0.0, pos=12)}\n", + " \"UZSJAN\": Float64Col(shape=(), dflt=0.0, pos=1),\n", + " \"UZSFEB\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"UZSMAR\": Float64Col(shape=(), dflt=0.0, pos=3),\n", + " \"UZSAPR\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"UZSMAY\": Float64Col(shape=(), dflt=0.0, pos=5),\n", + " \"UZSJUN\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"UZSJUL\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"UZSAUG\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"UZSSEP\": Float64Col(shape=(), dflt=0.0, pos=9),\n", + " \"UZSOCT\": Float64Col(shape=(), dflt=0.0, pos=10),\n", + " \"UZSNOV\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"UZSDEC\": Float64Col(shape=(), dflt=0.0, pos=12)}\n", " byteorder := 'little'\n", " chunkshape := (655,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"JAN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"FEB\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MAR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"APR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MAY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"JUN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"JUL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AUG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OCT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NOV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEC\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZSJAN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZSFEB\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZSMAR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZSAPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZSMAY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZSJUN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZSJUL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZSAUG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZSSEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZSOCT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZSNOV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"UZSDEC\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/PERLND/PSTEMP/PARAMETERS (Group) ''\n", "/PERLND/PSTEMP/PARAMETERS/table (Table(1,)) ''\n", " description := {\n", @@ -8004,35 +8739,33 @@ " \"ULTP2\": Float64Col(shape=(), dflt=0.0, pos=4),\n", " \"LGTP1\": Float64Col(shape=(), dflt=0.0, pos=5),\n", " \"LGTP2\": Float64Col(shape=(), dflt=0.0, pos=6),\n", - " \"OPNID\": StringCol(itemsize=4, shape=(), dflt=b'', pos=7),\n", - " \"SLTVFG\": Int64Col(shape=(), dflt=0, pos=8),\n", - " \"ULTVFG\": Int64Col(shape=(), dflt=0, pos=9),\n", - " \"LGTVFG\": Int64Col(shape=(), dflt=0, pos=10),\n", - " \"TSOPFG\": Int64Col(shape=(), dflt=0, pos=11),\n", - " \"AIRTC\": Float64Col(shape=(), dflt=0.0, pos=12),\n", - " \"SLTMP\": Float64Col(shape=(), dflt=0.0, pos=13),\n", - " \"ULTMP\": Float64Col(shape=(), dflt=0.0, pos=14),\n", - " \"LGTMP\": Float64Col(shape=(), dflt=0.0, pos=15)}\n", - " byteorder := 'little'\n", - " chunkshape := (546,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ASLT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BSLT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ULTP1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ULTP2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LGTP1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LGTP2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SLTVFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ULTVFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LGTVFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSOPFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AIRTC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SLTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ULTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LGTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"SLTVFG\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"ULTVFG\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"LGTVFG\": Float64Col(shape=(), dflt=0.0, pos=9),\n", + " \"TSOPFG\": Float64Col(shape=(), dflt=0.0, pos=10),\n", + " \"AIRTC\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"SLTMP\": Float64Col(shape=(), dflt=0.0, pos=12),\n", + " \"ULTMP\": Float64Col(shape=(), dflt=0.0, pos=13),\n", + " \"LGTMP\": Float64Col(shape=(), dflt=0.0, pos=14)}\n", + " byteorder := 'little'\n", + " chunkshape := (564,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ASLT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BSLT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ULTP1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ULTP2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LGTP1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LGTP2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SLTVFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ULTVFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LGTVFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSOPFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AIRTC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SLTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ULTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LGTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/PERLND/PSTEMP/SAVE (Group) ''\n", "/PERLND/PSTEMP/SAVE/table (Table(1,)) ''\n", " description := {\n", @@ -8045,68 +8778,44 @@ " chunkshape := (1820,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AIRTC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LGTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SLTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ULTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AIRTC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LGTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SLTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ULTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/PERLND/GENERAL/ACTIVITY (Group) ''\n", "/PERLND/GENERAL/ACTIVITY/table (Table(1,)) ''\n", " description := {\n", " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", - " \"ATEMP\": Int64Col(shape=(), dflt=0, pos=1),\n", + " \"ATEMP\": Float64Col(shape=(), dflt=0.0, pos=1),\n", " \"SNOW\": Int64Col(shape=(), dflt=0, pos=2),\n", " \"PWATER\": Int64Col(shape=(), dflt=0, pos=3),\n", - " \"SEDMNT\": Int64Col(shape=(), dflt=0, pos=4),\n", + " \"SEDMNT\": Float64Col(shape=(), dflt=0.0, pos=4),\n", " \"PSTEMP\": Int64Col(shape=(), dflt=0, pos=5),\n", " \"PWTGAS\": Int64Col(shape=(), dflt=0, pos=6),\n", - " \"PQUAL\": Int64Col(shape=(), dflt=0, pos=7),\n", - " \"MSTLAY\": Int64Col(shape=(), dflt=0, pos=8),\n", - " \"PEST\": Int64Col(shape=(), dflt=0, pos=9),\n", - " \"NITR\": Int64Col(shape=(), dflt=0, pos=10),\n", - " \"PHOS\": Int64Col(shape=(), dflt=0, pos=11),\n", - " \"TRACER\": Int64Col(shape=(), dflt=0, pos=12),\n", - " \"AIRTFG\": Int64Col(shape=(), dflt=0, pos=13),\n", - " \"SNOWFG\": Int64Col(shape=(), dflt=0, pos=14),\n", - " \"PWATFG\": Int64Col(shape=(), dflt=0, pos=15),\n", - " \"SEDFG\": Int64Col(shape=(), dflt=0, pos=16),\n", - " \"PSTFG\": Int64Col(shape=(), dflt=0, pos=17),\n", - " \"PWGFG\": Int64Col(shape=(), dflt=0, pos=18),\n", - " \"PQALFG\": Int64Col(shape=(), dflt=0, pos=19),\n", - " \"MSTLFG\": Int64Col(shape=(), dflt=0, pos=20),\n", - " \"PESTFG\": Int64Col(shape=(), dflt=0, pos=21),\n", - " \"NITRFG\": Int64Col(shape=(), dflt=0, pos=22),\n", - " \"PHOSFG\": Int64Col(shape=(), dflt=0, pos=23),\n", - " \"TRACFG\": Int64Col(shape=(), dflt=0, pos=24)}\n", + " \"PQUAL\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"MSTLAY\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"PEST\": Float64Col(shape=(), dflt=0.0, pos=9),\n", + " \"NITR\": Float64Col(shape=(), dflt=0.0, pos=10),\n", + " \"PHOS\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"TRACER\": Float64Col(shape=(), dflt=0.0, pos=12)}\n", " byteorder := 'little'\n", - " chunkshape := (334,)\n", + " chunkshape := (655,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ATEMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PWATER\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SEDMNT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PSTEMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PWTGAS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PQUAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MSTLAY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PEST\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NITR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TRACER\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AIRTFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOWFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PWATFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SEDFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PSTFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PWGFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PQALFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MSTLFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PESTFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NITRFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PHOSFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TRACFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ATEMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PWATER\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SEDMNT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PSTEMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PWTGAS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PQUAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MSTLAY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PEST\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NITR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TRACER\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/PERLND/GENERAL/INFO (Group) ''\n", "/PERLND/GENERAL/INFO/table (Table(1,)) ''\n", " description := {\n", @@ -8116,22 +8825,84 @@ " \"OUNITS\": Int64Col(shape=(), dflt=0, pos=3),\n", " \"PUNIT1\": Int64Col(shape=(), dflt=0, pos=4),\n", " \"PUNIT2\": Int64Col(shape=(), dflt=0, pos=5),\n", - " \"BUNIT1\": Int64Col(shape=(), dflt=0, pos=6),\n", - " \"BUNIT2\": Int64Col(shape=(), dflt=0, pos=7),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=8)}\n", - " byteorder := 'little'\n", - " chunkshape := (992,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LSID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IUNITS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OUNITS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PUNIT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PUNIT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BUNIT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BUNIT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"BUNIT1\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"BUNIT2\": Float64Col(shape=(), dflt=0.0, pos=7)}\n", + " byteorder := 'little'\n", + " chunkshape := (1008,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LSID\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IUNITS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OUNITS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PUNIT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PUNIT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BUNIT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BUNIT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/PERLND/GENERAL/PRINT (Group) ''\n", + "/PERLND/GENERAL/PRINT/table (Table(1,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"AIRTPR\": Float64Col(shape=(), dflt=0.0, pos=1),\n", + " \"SNOWPR\": Int64Col(shape=(), dflt=0, pos=2),\n", + " \"PWATPR\": Int64Col(shape=(), dflt=0, pos=3),\n", + " \"SEDPR\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"PSTPR\": Int64Col(shape=(), dflt=0, pos=5),\n", + " \"PWGPR\": Int64Col(shape=(), dflt=0, pos=6),\n", + " \"PQALPR\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"MSTLPR\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"PESTPR\": Float64Col(shape=(), dflt=0.0, pos=9),\n", + " \"NITRPR\": Float64Col(shape=(), dflt=0.0, pos=10),\n", + " \"PHOSPR\": Float64Col(shape=(), dflt=0.0, pos=11),\n", + " \"TRACPR\": Float64Col(shape=(), dflt=0.0, pos=12),\n", + " \"PIVL\": Float64Col(shape=(), dflt=0.0, pos=13),\n", + " \"PYREND\": Int64Col(shape=(), dflt=0, pos=14)}\n", + " byteorder := 'little'\n", + " chunkshape := (564,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AIRTPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOWPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PWATPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SEDPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PSTPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PWGPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PQALPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MSTLPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PESTPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NITRPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PHOSPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TRACPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PIVL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PYREND\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/PERLND/ATEMP/PARAMETERS (Group) ''\n", + "/PERLND/ATEMP/PARAMETERS/table (Table(1,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"ELDAT\": Float64Col(shape=(), dflt=0.0, pos=1),\n", + " \"AIRTMP\": Float64Col(shape=(), dflt=0.0, pos=2)}\n", + " byteorder := 'little'\n", + " chunkshape := (3276,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ELDAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AIRTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/PERLND/ATEMP/SAVE (Group) ''\n", + "/PERLND/ATEMP/SAVE/table (Table(1,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"GATMP\": Int64Col(shape=(), dflt=0, pos=1),\n", + " \"AIRTMP\": Int64Col(shape=(), dflt=0, pos=2)}\n", + " byteorder := 'little'\n", + " chunkshape := (3276,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GATMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AIRTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/IMPLND/ATEMP (Group) ''\n", "/IMPLND/GENERAL (Group) ''\n", "/IMPLND/IQUAL (Group) ''\n", "/IMPLND/IWATER (Group) ''\n", @@ -8147,24 +8918,22 @@ " \"ACCSDP\": Float64Col(shape=(), dflt=0.0, pos=3),\n", " \"REMSDP\": Float64Col(shape=(), dflt=0.0, pos=4),\n", " \"SLDS\": Float64Col(shape=(), dflt=0.0, pos=5),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=6),\n", - " \"VASDFG\": Int64Col(shape=(), dflt=0, pos=7),\n", - " \"VRSDFG\": Int64Col(shape=(), dflt=0, pos=8),\n", - " \"SDOPFG\": Int64Col(shape=(), dflt=0, pos=9)}\n", + " \"VASDFG\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"VRSDFG\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"SDOPFG\": Float64Col(shape=(), dflt=0.0, pos=8)}\n", " byteorder := 'little'\n", - " chunkshape := (949,)\n", + " chunkshape := (963,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KEIM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"JEIM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ACCSDP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"REMSDP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SLDS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VASDFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VRSDFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SDOPFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KEIM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"JEIM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ACCSDP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"REMSDP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SLDS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VASDFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VRSDFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDOPFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/IMPLND/SOLIDS/SAVE (Group) ''\n", "/IMPLND/SOLIDS/SAVE/table (Table(1,)) ''\n", " description := {\n", @@ -8175,26 +8944,24 @@ " chunkshape := (3276,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SLDS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOSLD\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SLDS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOSLD\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/IMPLND/SNOW/FLAGS (Group) ''\n", "/IMPLND/SNOW/FLAGS/table (Table(1,)) ''\n", " description := {\n", " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", " \"ICEFG\": Int64Col(shape=(), dflt=0, pos=1),\n", - " \"SNOPFG\": Int64Col(shape=(), dflt=0, pos=2),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=3),\n", - " \"VKMFG\": Int64Col(shape=(), dflt=0, pos=4)}\n", + " \"SNOPFG\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"VKMFG\": Float64Col(shape=(), dflt=0.0, pos=3)}\n", " byteorder := 'little'\n", - " chunkshape := (2259,)\n", + " chunkshape := (2340,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ICEFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOPFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VKMFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ICEFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOPFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VKMFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/IMPLND/SNOW/PARAMETERS (Group) ''\n", "/IMPLND/SNOW/PARAMETERS/table (Table(1,)) ''\n", " description := {\n", @@ -8211,27 +8978,25 @@ " \"SNOEVP\": Float64Col(shape=(), dflt=0.0, pos=10),\n", " \"CCFACT\": Float64Col(shape=(), dflt=0.0, pos=11),\n", " \"MWATER\": Float64Col(shape=(), dflt=0.0, pos=12),\n", - " \"MGMELT\": Float64Col(shape=(), dflt=0.0, pos=13),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=14)}\n", - " byteorder := 'little'\n", - " chunkshape := (601,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LAT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MELEV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SHADE\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOWCF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COVIND\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"KMELT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TBASE\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RDCSN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TSNOW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOEVP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CCFACT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MWATER\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MGMELT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"MGMELT\": Float64Col(shape=(), dflt=0.0, pos=13)}\n", + " byteorder := 'little'\n", + " chunkshape := (606,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MELEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SHADE\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOWCF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COVIND\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"KMELT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TBASE\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RDCSN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TSNOW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOEVP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CCFACT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MWATER\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MGMELT\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/IMPLND/SNOW/SAVE (Group) ''\n", "/IMPLND/SNOW/SAVE/table (Table(1,)) ''\n", " description := {\n", @@ -8262,29 +9027,29 @@ " chunkshape := (364,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ALBEDO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COVINX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DEWTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DULL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MELT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NEGHTS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACKF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACKI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACKW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACK\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PAKTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PDEPTH\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PRAIN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RAINF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RDENPF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SKYCLR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOCOV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOWE\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOWF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"WYIELD\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"XLNMLT\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ALBEDO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COVINX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DEWTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DULL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MELT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NEGHTS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACKF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACKI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACKW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACK\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PAKTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PDEPTH\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PRAIN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RAINF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RDENPF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SKYCLR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOCOV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOWE\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOWF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"WYIELD\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"XLNMLT\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/IMPLND/SNOW/STATES (Group) ''\n", "/IMPLND/SNOW/STATES/table (Table(1,)) ''\n", " description := {\n", @@ -8297,29 +9062,21 @@ " \"PAKTMP\": Float64Col(shape=(), dflt=0.0, pos=6),\n", " \"COVINX\": Float64Col(shape=(), dflt=0.0, pos=7),\n", " \"XLNMLT\": Float64Col(shape=(), dflt=0.0, pos=8),\n", - " \"SKYCLR\": Float64Col(shape=(), dflt=0.0, pos=9),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=10),\n", - " \"PKSNOW\": Float64Col(shape=(), dflt=0.0, pos=11),\n", - " \"PKICE\": Float64Col(shape=(), dflt=0.0, pos=12),\n", - " \"PKWATR\": Float64Col(shape=(), dflt=0.0, pos=13)}\n", - " byteorder := 'little'\n", - " chunkshape := (648,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACKF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACKI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PACKW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RDENPF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"DULL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PAKTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COVINX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"XLNMLT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SKYCLR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKSNOW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKICE\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PKWATR\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"SKYCLR\": Float64Col(shape=(), dflt=0.0, pos=9)}\n", + " byteorder := 'little'\n", + " chunkshape := (862,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACKF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACKI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PACKW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RDENPF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DULL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PAKTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"COVINX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"XLNMLT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SKYCLR\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/IMPLND/IWTGAS/PARAMETERS (Group) ''\n", "/IMPLND/IWTGAS/PARAMETERS/table (Table(1,)) ''\n", " description := {\n", @@ -8327,30 +9084,22 @@ " \"ELEV\": Float64Col(shape=(), dflt=0.0, pos=1),\n", " \"AWTF\": Float64Col(shape=(), dflt=0.0, pos=2),\n", " \"BWTF\": Float64Col(shape=(), dflt=0.0, pos=3),\n", - " \"SDLFAC\": Float64Col(shape=(), dflt=0.0, pos=4),\n", - " \"SLIFAC\": Float64Col(shape=(), dflt=0.0, pos=5),\n", - " \"SOTMP\": Float64Col(shape=(), dflt=0.0, pos=6),\n", - " \"SODOX\": Float64Col(shape=(), dflt=0.0, pos=7),\n", - " \"SOCO2\": Float64Col(shape=(), dflt=0.0, pos=8),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=9),\n", - " \"WTFVFG\": Int64Col(shape=(), dflt=0, pos=10),\n", - " \"CSNOFG\": Int64Col(shape=(), dflt=0, pos=11)}\n", - " byteorder := 'little'\n", - " chunkshape := (771,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ELEV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AWTF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BWTF\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SDLFAC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SLIFAC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SODOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"WTFVFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CSNOFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"WTFVFG\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"CSNOFG\": Float64Col(shape=(), dflt=0.0, pos=5),\n", + " \"SDLFAC\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"SLIFAC\": Float64Col(shape=(), dflt=0.0, pos=7)}\n", + " byteorder := 'little'\n", + " chunkshape := (1092,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ELEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AWTF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BWTF\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"WTFVFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CSNOFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDLFAC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SLIFAC\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/IMPLND/IWTGAS/SAVE (Group) ''\n", "/IMPLND/IWTGAS/SAVE/table (Table(1,)) ''\n", " description := {\n", @@ -8365,46 +9114,59 @@ " chunkshape := (1260,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOTMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SODOX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOCO2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOHT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SODOXM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOCO2M\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SODOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOHT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SODOXM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOCO2M\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/IMPLND/IWTGAS/STATES (Group) ''\n", + "/IMPLND/IWTGAS/STATES/table (Table(1,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"SOTMP\": Float64Col(shape=(), dflt=0.0, pos=1),\n", + " \"SODOX\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"SOCO2\": Float64Col(shape=(), dflt=0.0, pos=3)}\n", + " byteorder := 'little'\n", + " chunkshape := (2340,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SODOX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOCO2\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/IMPLND/IWATER/PARAMETERS (Group) ''\n", "/IMPLND/IWATER/PARAMETERS/table (Table(1,)) ''\n", " description := {\n", " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", " \"CSNOFG\": Int64Col(shape=(), dflt=0, pos=1),\n", - " \"RTOPFG\": Int64Col(shape=(), dflt=0, pos=2),\n", - " \"VRSFG\": Int64Col(shape=(), dflt=0, pos=3),\n", - " \"VNNFG\": Int64Col(shape=(), dflt=0, pos=4),\n", + " \"RTOPFG\": Float64Col(shape=(), dflt=0.0, pos=2),\n", + " \"VRSFG\": Float64Col(shape=(), dflt=0.0, pos=3),\n", + " \"VNNFG\": Float64Col(shape=(), dflt=0.0, pos=4),\n", " \"RTLIFG\": Int64Col(shape=(), dflt=0, pos=5),\n", " \"LSUR\": Float64Col(shape=(), dflt=0.0, pos=6),\n", " \"SLSUR\": Float64Col(shape=(), dflt=0.0, pos=7),\n", " \"NSUR\": Float64Col(shape=(), dflt=0.0, pos=8),\n", " \"RETSC\": Float64Col(shape=(), dflt=0.0, pos=9),\n", " \"PETMAX\": Float64Col(shape=(), dflt=0.0, pos=10),\n", - " \"PETMIN\": Float64Col(shape=(), dflt=0.0, pos=11),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=12)}\n", - " byteorder := 'little'\n", - " chunkshape := (704,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"CSNOFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RTOPFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VRSFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VNNFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RTLIFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LSUR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SLSUR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NSUR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RETSC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PETMAX\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PETMIN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"PETMIN\": Float64Col(shape=(), dflt=0.0, pos=11)}\n", + " byteorder := 'little'\n", + " chunkshape := (712,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"CSNOFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RTOPFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VRSFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VNNFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RTLIFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LSUR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SLSUR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NSUR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RETSC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PETMAX\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PETMIN\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/IMPLND/IWATER/SAVE (Group) ''\n", "/IMPLND/IWATER/SAVE/table (Table(1,)) ''\n", " description := {\n", @@ -8421,30 +9183,28 @@ " chunkshape := (963,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IMPEV\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PET\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PETADJ\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RETS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SUPY\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SURI\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SURO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SURS\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IMPEV\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PET\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PETADJ\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RETS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SUPY\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SURI\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SURO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SURS\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/IMPLND/IWATER/STATES (Group) ''\n", "/IMPLND/IWATER/STATES/table (Table(1,)) ''\n", " description := {\n", " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", " \"RETS\": Float64Col(shape=(), dflt=0.0, pos=1),\n", - " \"SURS\": Float64Col(shape=(), dflt=0.0, pos=2),\n", - " \"OPNID\": StringCol(itemsize=3, shape=(), dflt=b'', pos=3)}\n", + " \"SURS\": Float64Col(shape=(), dflt=0.0, pos=2)}\n", " byteorder := 'little'\n", - " chunkshape := (2849,)\n", + " chunkshape := (3276,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"RETS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SURS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"RETS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SURS\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/IMPLND/IQUAL/IQUAL1 (Group) ''\n", "/IMPLND/IQUAL/PARAMETERS (Group) ''\n", "/IMPLND/IQUAL/PARAMETERS/table (Table(1,)) ''\n", @@ -8457,10 +9217,10 @@ " chunkshape := (2340,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"NQUAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SDLFAC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SLIFAC\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"NQUAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SDLFAC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SLIFAC\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/IMPLND/IQUAL/SAVE (Group) ''\n", "/IMPLND/IQUAL/SAVE/table (Table(1,)) ''\n", " description := {\n", @@ -8479,17 +9239,17 @@ " chunkshape := (780,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SQO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOQSP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOQS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOQO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOQOC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOQUAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOQC\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IQADDR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IQADWT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IQADEP\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOQSP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOQS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOQO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOQOC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOQUAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOQC\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IQADDR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IQADWT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IQADEP\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/IMPLND/IQUAL/IQUAL1/FLAGS (Group) ''\n", "/IMPLND/IQUAL/IQUAL1/FLAGS/table (Table(1,)) ''\n", " description := {\n", @@ -8497,20 +9257,20 @@ " \"QUALID\": StringCol(itemsize=3, shape=(), dflt=b'', pos=1),\n", " \"QTYID\": StringCol(itemsize=2, shape=(), dflt=b'', pos=2),\n", " \"QSDFG\": Int64Col(shape=(), dflt=0, pos=3),\n", - " \"VPFWFG\": Int64Col(shape=(), dflt=0, pos=4),\n", + " \"VPFWFG\": Float64Col(shape=(), dflt=0.0, pos=4),\n", " \"QSOFG\": Int64Col(shape=(), dflt=0, pos=5),\n", - " \"VQOFG\": Int64Col(shape=(), dflt=0, pos=6)}\n", + " \"VQOFG\": Float64Col(shape=(), dflt=0.0, pos=6)}\n", " byteorder := 'little'\n", " chunkshape := (1598,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QUALID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QTYID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QSDFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VPFWFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"QSOFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"VQOFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QUALID\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QTYID\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QSDFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VPFWFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QSOFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"VQOFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/IMPLND/IQUAL/IQUAL1/PARAMETERS (Group) ''\n", "/IMPLND/IQUAL/IQUAL1/PARAMETERS/table (Table(1,)) ''\n", " description := {\n", @@ -8524,45 +9284,33 @@ " chunkshape := (1489,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SQO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"POTFW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ACQOP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SQOLIM\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"WSQOP\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"POTFW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ACQOP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SQOLIM\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"WSQOP\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/IMPLND/GENERAL/ACTIVITY (Group) ''\n", "/IMPLND/GENERAL/ACTIVITY/table (Table(1,)) ''\n", " description := {\n", " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", - " \"ATEMP\": Int64Col(shape=(), dflt=0, pos=1),\n", + " \"ATEMP\": Float64Col(shape=(), dflt=0.0, pos=1),\n", " \"SNOW\": Int64Col(shape=(), dflt=0, pos=2),\n", " \"IWATER\": Int64Col(shape=(), dflt=0, pos=3),\n", " \"SOLIDS\": Int64Col(shape=(), dflt=0, pos=4),\n", " \"IWTGAS\": Int64Col(shape=(), dflt=0, pos=5),\n", - " \"IQUAL\": Int64Col(shape=(), dflt=0, pos=6),\n", - " \"ATMPFG\": Int64Col(shape=(), dflt=0, pos=7),\n", - " \"SNOWFG\": Int64Col(shape=(), dflt=0, pos=8),\n", - " \"IWATFG\": Int64Col(shape=(), dflt=0, pos=9),\n", - " \"SLDFG\": Int64Col(shape=(), dflt=0, pos=10),\n", - " \"IWGFG\": Int64Col(shape=(), dflt=0, pos=11),\n", - " \"IQALFG\": Int64Col(shape=(), dflt=0, pos=12)}\n", + " \"IQUAL\": Int64Col(shape=(), dflt=0, pos=6)}\n", " byteorder := 'little'\n", - " chunkshape := (655,)\n", + " chunkshape := (1260,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ATEMP\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOW\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IWATER\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SOLIDS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IWTGAS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IQUAL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"ATMPFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SNOWFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IWATFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SLDFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IWGFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IQALFG\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ATEMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOW\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IWATER\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SOLIDS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IWTGAS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IQUAL\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/IMPLND/GENERAL/INFO (Group) ''\n", "/IMPLND/GENERAL/INFO/table (Table(1,)) ''\n", " description := {\n", @@ -8572,35 +9320,82 @@ " \"OUNITS\": Int64Col(shape=(), dflt=0, pos=3),\n", " \"PUNIT1\": Int64Col(shape=(), dflt=0, pos=4),\n", " \"PUNIT2\": Int64Col(shape=(), dflt=0, pos=5),\n", - " \"BUNIT1\": Int64Col(shape=(), dflt=0, pos=6),\n", - " \"BUNIT2\": Int64Col(shape=(), dflt=0, pos=7),\n", - " \"OPNID\": StringCol(itemsize=1, shape=(), dflt=b'', pos=8)}\n", - " byteorder := 'little'\n", - " chunkshape := (936,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"LSID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"IUNITS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OUNITS\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PUNIT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"PUNIT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BUNIT1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"BUNIT2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"BUNIT1\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"BUNIT2\": Float64Col(shape=(), dflt=0.0, pos=7)}\n", + " byteorder := 'little'\n", + " chunkshape := (949,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"LSID\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IUNITS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OUNITS\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PUNIT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PUNIT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BUNIT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"BUNIT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/IMPLND/GENERAL/PRINT (Group) ''\n", + "/IMPLND/GENERAL/PRINT/table (Table(1,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"ATMPPR\": Float64Col(shape=(), dflt=0.0, pos=1),\n", + " \"SNOWPR\": Int64Col(shape=(), dflt=0, pos=2),\n", + " \"IWATPR\": Int64Col(shape=(), dflt=0, pos=3),\n", + " \"SLDPR\": Int64Col(shape=(), dflt=0, pos=4),\n", + " \"IWGPR\": Int64Col(shape=(), dflt=0, pos=5),\n", + " \"IQALPR\": Int64Col(shape=(), dflt=0, pos=6),\n", + " \"PIVL\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"PYREND\": Int64Col(shape=(), dflt=0, pos=8)}\n", + " byteorder := 'little'\n", + " chunkshape := (963,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ATMPPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SNOWPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IWATPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SLDPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IWGPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"IQALPR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PIVL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PYREND\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/IMPLND/ATEMP/PARAMETERS (Group) ''\n", + "/IMPLND/ATEMP/PARAMETERS/table (Table(1,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"ELDAT\": Float64Col(shape=(), dflt=0.0, pos=1),\n", + " \"AIRTMP\": Float64Col(shape=(), dflt=0.0, pos=2)}\n", + " byteorder := 'little'\n", + " chunkshape := (3276,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"ELDAT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AIRTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/IMPLND/ATEMP/SAVE (Group) ''\n", + "/IMPLND/ATEMP/SAVE/table (Table(1,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"GATMP\": Int64Col(shape=(), dflt=0, pos=1),\n", + " \"AIRTMP\": Int64Col(shape=(), dflt=0, pos=2)}\n", + " byteorder := 'little'\n", + " chunkshape := (3276,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"GATMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AIRTMP\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/GENER/OPCODE (Group) ''\n", - "/GENER/OPCODE/table (Table(1,)) ''\n", + "/GENER/OPCODE/table (Table(2,)) ''\n", " description := {\n", - " \"index\": Int64Col(shape=(), dflt=0, pos=0),\n", - " \"OPNID\": StringCol(itemsize=6, shape=(), dflt=b'', pos=1),\n", - " \"OPCODE\": Int64Col(shape=(), dflt=0, pos=2)}\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"OPCODE\": Int64Col(shape=(), dflt=0, pos=1)}\n", " byteorder := 'little'\n", - " chunkshape := (2978,)\n", + " chunkshape := (5461,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPNID\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPCODE\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OPCODE\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/FTABLES/FT001 (Group) ''\n", "/FTABLES/FT001/table (Table(14,)) ''\n", " description := {\n", @@ -8610,18 +9405,26 @@ " \"Volume\": Float64Col(shape=(), dflt=0.0, pos=3),\n", " \"Disch1\": Float64Col(shape=(), dflt=0.0, pos=4),\n", " \"Disch2\": Float64Col(shape=(), dflt=0.0, pos=5),\n", - " \"Disch3\": Float64Col(shape=(), dflt=0.0, pos=6)}\n", - " byteorder := 'little'\n", - " chunkshape := (1170,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Depth\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Area\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Volume\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Disch1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Disch2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Disch3\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"Disch3\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"Disch4\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"Disch5\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"rows\": Int64Col(shape=(), dflt=0, pos=9),\n", + " \"cols\": Int64Col(shape=(), dflt=0, pos=10)}\n", + " byteorder := 'little'\n", + " chunkshape := (744,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Depth\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Area\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Volume\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"rows\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"cols\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/FTABLES/FT002 (Group) ''\n", "/FTABLES/FT002/table (Table(13,)) ''\n", " description := {\n", @@ -8629,16 +9432,28 @@ " \"Depth\": Float64Col(shape=(), dflt=0.0, pos=1),\n", " \"Area\": Float64Col(shape=(), dflt=0.0, pos=2),\n", " \"Volume\": Float64Col(shape=(), dflt=0.0, pos=3),\n", - " \"Disch1\": Float64Col(shape=(), dflt=0.0, pos=4)}\n", - " byteorder := 'little'\n", - " chunkshape := (1638,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Depth\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Area\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Volume\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Disch1\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"Disch1\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"Disch2\": Float64Col(shape=(), dflt=0.0, pos=5),\n", + " \"Disch3\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"Disch4\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"Disch5\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"rows\": Int64Col(shape=(), dflt=0, pos=9),\n", + " \"cols\": Int64Col(shape=(), dflt=0, pos=10)}\n", + " byteorder := 'little'\n", + " chunkshape := (744,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Depth\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Area\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Volume\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"rows\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"cols\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/FTABLES/FT003 (Group) ''\n", "/FTABLES/FT003/table (Table(13,)) ''\n", " description := {\n", @@ -8646,16 +9461,28 @@ " \"Depth\": Float64Col(shape=(), dflt=0.0, pos=1),\n", " \"Area\": Float64Col(shape=(), dflt=0.0, pos=2),\n", " \"Volume\": Float64Col(shape=(), dflt=0.0, pos=3),\n", - " \"Disch1\": Float64Col(shape=(), dflt=0.0, pos=4)}\n", - " byteorder := 'little'\n", - " chunkshape := (1638,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Depth\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Area\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Volume\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Disch1\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"Disch1\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"Disch2\": Float64Col(shape=(), dflt=0.0, pos=5),\n", + " \"Disch3\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"Disch4\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"Disch5\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"rows\": Int64Col(shape=(), dflt=0, pos=9),\n", + " \"cols\": Int64Col(shape=(), dflt=0, pos=10)}\n", + " byteorder := 'little'\n", + " chunkshape := (744,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Depth\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Area\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Volume\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"rows\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"cols\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/FTABLES/FT004 (Group) ''\n", "/FTABLES/FT004/table (Table(13,)) ''\n", " description := {\n", @@ -8663,16 +9490,28 @@ " \"Depth\": Float64Col(shape=(), dflt=0.0, pos=1),\n", " \"Area\": Float64Col(shape=(), dflt=0.0, pos=2),\n", " \"Volume\": Float64Col(shape=(), dflt=0.0, pos=3),\n", - " \"Disch1\": Float64Col(shape=(), dflt=0.0, pos=4)}\n", - " byteorder := 'little'\n", - " chunkshape := (1638,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Depth\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Area\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Volume\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Disch1\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"Disch1\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"Disch2\": Float64Col(shape=(), dflt=0.0, pos=5),\n", + " \"Disch3\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"Disch4\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"Disch5\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"rows\": Int64Col(shape=(), dflt=0, pos=9),\n", + " \"cols\": Int64Col(shape=(), dflt=0, pos=10)}\n", + " byteorder := 'little'\n", + " chunkshape := (744,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Depth\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Area\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Volume\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"rows\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"cols\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/FTABLES/FT005 (Group) ''\n", "/FTABLES/FT005/table (Table(13,)) ''\n", " description := {\n", @@ -8680,53 +9519,110 @@ " \"Depth\": Float64Col(shape=(), dflt=0.0, pos=1),\n", " \"Area\": Float64Col(shape=(), dflt=0.0, pos=2),\n", " \"Volume\": Float64Col(shape=(), dflt=0.0, pos=3),\n", - " \"Disch1\": Float64Col(shape=(), dflt=0.0, pos=4)}\n", + " \"Disch1\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"Disch2\": Float64Col(shape=(), dflt=0.0, pos=5),\n", + " \"Disch3\": Float64Col(shape=(), dflt=0.0, pos=6),\n", + " \"Disch4\": Float64Col(shape=(), dflt=0.0, pos=7),\n", + " \"Disch5\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"rows\": Int64Col(shape=(), dflt=0, pos=9),\n", + " \"cols\": Int64Col(shape=(), dflt=0, pos=10)}\n", + " byteorder := 'little'\n", + " chunkshape := (744,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Depth\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Area\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Volume\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch3\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch4\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Disch5\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"rows\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"cols\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/FILES/FILES (Group) ''\n", + "/FILES/FILES/table (Table(6,)) ''\n", + " description := {\n", + " \"index\": Int64Col(shape=(), dflt=0, pos=0),\n", + " \"FTYPE\": StringCol(itemsize=5, shape=(), dflt=b'', pos=1),\n", + " \"FUNIT\": Int64Col(shape=(), dflt=0, pos=2),\n", + " \"FNAME\": StringCol(itemsize=10, shape=(), dflt=b'', pos=3)}\n", " byteorder := 'little'\n", - " chunkshape := (1638,)\n", + " chunkshape := (2114,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FTYPE\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FUNIT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FNAME\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", + "/DISPLY/DISPLY (Group) ''\n", + "/DISPLY/DISPLY/INFO (Group) ''\n", + "/DISPLY/DISPLY/INFO/table (Table(5,)) ''\n", + " description := {\n", + " \"index\": StringCol(itemsize=4, shape=(), dflt=b'', pos=0),\n", + " \"TITLE\": StringCol(itemsize=28, shape=(), dflt=b'', pos=1),\n", + " \"TRAN\": StringCol(itemsize=4, shape=(), dflt=b'', pos=2),\n", + " \"PIVL\": Float64Col(shape=(), dflt=0.0, pos=3),\n", + " \"DIGIT1\": Float64Col(shape=(), dflt=0.0, pos=4),\n", + " \"FILE1\": Float64Col(shape=(), dflt=0.0, pos=5),\n", + " \"PYRFG\": Int64Col(shape=(), dflt=0, pos=6),\n", + " \"DIGIT2\": Int64Col(shape=(), dflt=0, pos=7),\n", + " \"FILE2\": Int64Col(shape=(), dflt=0, pos=8),\n", + " \"PYREND\": Int64Col(shape=(), dflt=0, pos=9)}\n", + " byteorder := 'little'\n", + " chunkshape := (712,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Depth\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Area\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Volume\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Disch1\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TITLE\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TRAN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PIVL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DIGIT1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FILE1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PYRFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"DIGIT2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"FILE2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"PYREND\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/CONTROL/EXT_SOURCES (Group) ''\n", "/CONTROL/EXT_SOURCES/table (Table(50,)) ''\n", " description := {\n", " \"index\": Int64Col(shape=(), dflt=0, pos=0),\n", - " \"SVOL\": StringCol(itemsize=1, shape=(), dflt=b'', pos=1),\n", - " \"SVOLNO\": StringCol(itemsize=5, shape=(), dflt=b'', pos=2),\n", - " \"SMEMN\": StringCol(itemsize=4, shape=(), dflt=b'', pos=3),\n", - " \"SMEMSB\": StringCol(itemsize=2, shape=(), dflt=b'', pos=4),\n", - " \"SSYST\": StringCol(itemsize=4, shape=(), dflt=b'', pos=5),\n", - " \"SGAPST\": StringCol(itemsize=4, shape=(), dflt=b'', pos=6),\n", - " \"MFACTOR\": Float64Col(shape=(), dflt=0.0, pos=7),\n", - " \"TRAN\": StringCol(itemsize=4, shape=(), dflt=b'', pos=8),\n", - " \"TVOL\": StringCol(itemsize=6, shape=(), dflt=b'', pos=9),\n", - " \"TGRPN\": StringCol(itemsize=5, shape=(), dflt=b'', pos=10),\n", - " \"TMEMN\": StringCol(itemsize=6, shape=(), dflt=b'', pos=11),\n", - " \"TMEMSB\": StringCol(itemsize=1, shape=(), dflt=b'', pos=12),\n", - " \"TVOLNO\": StringCol(itemsize=4, shape=(), dflt=b'', pos=13),\n", - " \"COMMENT\": StringCol(itemsize=1, shape=(), dflt=b'', pos=14)}\n", - " byteorder := 'little'\n", - " chunkshape := (1040,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SVOLNO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SMEMN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SMEMSB\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSYST\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SGAPST\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MFACTOR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TRAN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TGRPN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TMEMN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TMEMSB\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TVOLNO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COMMENT\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"TVOLNO\": StringCol(itemsize=4, shape=(), dflt=b'', pos=1),\n", + " \"SVOL\": StringCol(itemsize=3, shape=(), dflt=b'', pos=2),\n", + " \"SVOLNO\": StringCol(itemsize=5, shape=(), dflt=b'', pos=3),\n", + " \"SMEMN\": StringCol(itemsize=4, shape=(), dflt=b'', pos=4),\n", + " \"QLFG\": Float64Col(shape=(), dflt=0.0, pos=5),\n", + " \"SSYST\": StringCol(itemsize=4, shape=(), dflt=b'', pos=6),\n", + " \"SGAPST\": StringCol(itemsize=4, shape=(), dflt=b'', pos=7),\n", + " \"MFACTOR\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"TRAN\": StringCol(itemsize=4, shape=(), dflt=b'', pos=9),\n", + " \"TVOL\": StringCol(itemsize=6, shape=(), dflt=b'', pos=10),\n", + " \"TGRPN\": StringCol(itemsize=5, shape=(), dflt=b'', pos=11),\n", + " \"TMEMN\": StringCol(itemsize=6, shape=(), dflt=b'', pos=12),\n", + " \"TMEMSB1\": StringCol(itemsize=1, shape=(), dflt=b'', pos=13),\n", + " \"TMEMSB2\": StringCol(itemsize=1, shape=(), dflt=b'', pos=14),\n", + " \"TMEMSB\": StringCol(itemsize=1, shape=(), dflt=b'', pos=15)}\n", + " byteorder := 'little'\n", + " chunkshape := (910,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TVOLNO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SVOLNO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SMEMN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QLFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSYST\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SGAPST\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MFACTOR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TRAN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TGRPN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TMEMN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TMEMSB1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TMEMSB2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TMEMSB\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/CONTROL/GLOBAL (Group) ''\n", "/CONTROL/GLOBAL/table (Table(4,)) ''\n", " description := {\n", @@ -8736,94 +9632,84 @@ " chunkshape := (809,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"Info\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"Info\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/CONTROL/LINKS (Group) ''\n", - "/CONTROL/LINKS/table (Table(11,)) ''\n", + "/CONTROL/LINKS/table (Table(22,)) ''\n", " description := {\n", " \"index\": Int64Col(shape=(), dflt=0, pos=0),\n", " \"AFACTR\": Float64Col(shape=(), dflt=0.0, pos=1),\n", " \"MFACTOR\": Float64Col(shape=(), dflt=0.0, pos=2),\n", " \"MLNO\": StringCol(itemsize=5, shape=(), dflt=b'', pos=3),\n", " \"SGRPN\": StringCol(itemsize=6, shape=(), dflt=b'', pos=4),\n", - " \"SMEMN\": StringCol(itemsize=5, shape=(), dflt=b'', pos=5),\n", - " \"SMEMSB1\": StringCol(itemsize=3, shape=(), dflt=b'', pos=6),\n", - " \"SMEMSB2\": StringCol(itemsize=3, shape=(), dflt=b'', pos=7),\n", + " \"SMEMN\": StringCol(itemsize=6, shape=(), dflt=b'', pos=5),\n", + " \"SMEMSB1\": StringCol(itemsize=4, shape=(), dflt=b'', pos=6),\n", + " \"SMEMSB2\": StringCol(itemsize=1, shape=(), dflt=b'', pos=7),\n", " \"SVOL\": StringCol(itemsize=6, shape=(), dflt=b'', pos=8),\n", " \"SVOLNO\": StringCol(itemsize=4, shape=(), dflt=b'', pos=9),\n", " \"TGRPN\": StringCol(itemsize=5, shape=(), dflt=b'', pos=10),\n", - " \"TMEMN\": StringCol(itemsize=3, shape=(), dflt=b'', pos=11),\n", - " \"TMEMSB1\": StringCol(itemsize=1, shape=(), dflt=b'', pos=12),\n", + " \"TMEMN\": StringCol(itemsize=6, shape=(), dflt=b'', pos=11),\n", + " \"TMEMSB1\": StringCol(itemsize=3, shape=(), dflt=b'', pos=12),\n", " \"TMEMSB2\": StringCol(itemsize=1, shape=(), dflt=b'', pos=13),\n", - " \"TOPFST\": StringCol(itemsize=4, shape=(), dflt=b'', pos=14),\n", - " \"TOPLST\": StringCol(itemsize=3, shape=(), dflt=b'', pos=15),\n", - " \"TRAN\": StringCol(itemsize=3, shape=(), dflt=b'', pos=16),\n", - " \"TVOL\": StringCol(itemsize=6, shape=(), dflt=b'', pos=17),\n", - " \"TVOLNO\": StringCol(itemsize=4, shape=(), dflt=b'', pos=18),\n", - " \"SMEMSB\": StringCol(itemsize=1, shape=(), dflt=b'', pos=19),\n", - " \"TMEMSB\": StringCol(itemsize=1, shape=(), dflt=b'', pos=20),\n", - " \"COMMENTS\": StringCol(itemsize=1, shape=(), dflt=b'', pos=21)}\n", - " byteorder := 'little'\n", - " chunkshape := (736,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"AFACTR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MFACTOR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MLNO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SGRPN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SMEMN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SMEMSB1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SMEMSB2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SVOLNO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TGRPN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TMEMN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TMEMSB1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TMEMSB2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TOPFST\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TOPLST\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TRAN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TVOLNO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SMEMSB\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TMEMSB\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COMMENTS\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"TRAN\": StringCol(itemsize=1, shape=(), dflt=b'', pos=14),\n", + " \"TVOL\": StringCol(itemsize=6, shape=(), dflt=b'', pos=15),\n", + " \"TVOLNO\": StringCol(itemsize=4, shape=(), dflt=b'', pos=16)}\n", + " byteorder := 'little'\n", + " chunkshape := (799,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"AFACTR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MFACTOR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MLNO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SGRPN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SMEMN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SMEMSB1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SMEMSB2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SVOLNO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TGRPN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TMEMN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TMEMSB1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TMEMSB2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TRAN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TVOLNO\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/CONTROL/MASS_LINKS (Group) ''\n", "/CONTROL/MASS_LINKS/table (Table(15,)) ''\n", " description := {\n", " \"index\": Int64Col(shape=(), dflt=0, pos=0),\n", - " \"SVOL\": StringCol(itemsize=6, shape=(), dflt=b'', pos=1),\n", - " \"SGRPN\": StringCol(itemsize=6, shape=(), dflt=b'', pos=2),\n", - " \"SMEMN\": StringCol(itemsize=6, shape=(), dflt=b'', pos=3),\n", - " \"SMEMSB1\": StringCol(itemsize=1, shape=(), dflt=b'', pos=4),\n", - " \"SMEMSB2\": StringCol(itemsize=1, shape=(), dflt=b'', pos=5),\n", - " \"MFACTOR\": Float64Col(shape=(), dflt=0.0, pos=6),\n", - " \"TVOL\": StringCol(itemsize=6, shape=(), dflt=b'', pos=7),\n", - " \"TMEMN\": StringCol(itemsize=5, shape=(), dflt=b'', pos=8),\n", - " \"TMEMSB1\": StringCol(itemsize=1, shape=(), dflt=b'', pos=9),\n", - " \"TMEMSB2\": StringCol(itemsize=1, shape=(), dflt=b'', pos=10),\n", - " \"MLNO\": StringCol(itemsize=5, shape=(), dflt=b'', pos=11),\n", - " \"COMMENTS\": StringCol(itemsize=1, shape=(), dflt=b'', pos=12)}\n", - " byteorder := 'little'\n", - " chunkshape := (1191,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SGRPN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SMEMN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SMEMSB1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SMEMSB2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MFACTOR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TMEMN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TMEMSB1\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TMEMSB2\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MLNO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COMMENTS\": Index(6, medium, shuffle, zlib(1)).is_csi=False}\n", + " \"MFACTOR\": Float64Col(shape=(), dflt=0.0, pos=1),\n", + " \"MLNO\": StringCol(itemsize=5, shape=(), dflt=b'', pos=2),\n", + " \"SGRPN\": StringCol(itemsize=6, shape=(), dflt=b'', pos=3),\n", + " \"SMEMN\": StringCol(itemsize=6, shape=(), dflt=b'', pos=4),\n", + " \"SMEMSB1\": StringCol(itemsize=3, shape=(), dflt=b'', pos=5),\n", + " \"SMEMSB2\": StringCol(itemsize=1, shape=(), dflt=b'', pos=6),\n", + " \"SVOL\": StringCol(itemsize=6, shape=(), dflt=b'', pos=7),\n", + " \"TGRPN\": StringCol(itemsize=6, shape=(), dflt=b'', pos=8),\n", + " \"TMEMN\": StringCol(itemsize=5, shape=(), dflt=b'', pos=9),\n", + " \"TMEMSB1\": StringCol(itemsize=3, shape=(), dflt=b'', pos=10),\n", + " \"TMEMSB2\": StringCol(itemsize=1, shape=(), dflt=b'', pos=11),\n", + " \"TVOL\": StringCol(itemsize=6, shape=(), dflt=b'', pos=12)}\n", + " byteorder := 'little'\n", + " chunkshape := (1024,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MFACTOR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MLNO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SGRPN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SMEMN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SMEMSB1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SMEMSB2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TGRPN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TMEMN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TMEMSB1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TMEMSB2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False}\n", "/CONTROL/OP_SEQUENCE (Group) ''\n", - "/CONTROL/OP_SEQUENCE/table (Table(9,)) ''\n", + "/CONTROL/OP_SEQUENCE/table (Table(16,)) ''\n", " description := {\n", " \"index\": Int64Col(shape=(), dflt=0, pos=0),\n", " \"OPERATION\": StringCol(itemsize=6, shape=(), dflt=b'', pos=1),\n", @@ -8833,10 +9719,10 @@ " chunkshape := (2520,)\n", " autoindex := True\n", " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"OPERATION\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SEGMENT\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"INDELT_minutes\": Index(6, medium, shuffle, zlib(1)).is_csi=False}" + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"OPERATION\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SEGMENT\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"INDELT_minutes\": Index(6, mediumshuffle, zlib(1)).is_csi=False}" ] }, "execution_count": 12, @@ -8873,10 +9759,13 @@ "text": [ "/ (RootGroup) ''\n", "/CONTROL (Group) ''\n", + "/DISPLY (Group) ''\n", + "/FILES (Group) ''\n", "/FTABLES (Group) ''\n", "/GENER (Group) ''\n", "/IMPLND (Group) ''\n", "/PERLND (Group) ''\n", + "/PLTGEN (Group) ''\n", "/RCHRES (Group) ''\n", "/RESULTS (Group) ''\n", "/RUN_INFO (Group) ''\n", @@ -8886,23 +9775,33 @@ "/CONTROL/LINKS (Group) ''\n", "/CONTROL/MASS_LINKS (Group) ''\n", "/CONTROL/OP_SEQUENCE (Group) ''\n", + "/DISPLY/DISPLY (Group) ''\n", + "/FILES/FILES (Group) ''\n", "/FTABLES/FT001 (Group) ''\n", "/FTABLES/FT002 (Group) ''\n", "/FTABLES/FT003 (Group) ''\n", "/FTABLES/FT004 (Group) ''\n", "/FTABLES/FT005 (Group) ''\n", "/GENER/OPCODE (Group) ''\n", + "/IMPLND/ATEMP (Group) ''\n", "/IMPLND/GENERAL (Group) ''\n", "/IMPLND/IQUAL (Group) ''\n", "/IMPLND/IWATER (Group) ''\n", "/IMPLND/IWTGAS (Group) ''\n", "/IMPLND/SNOW (Group) ''\n", "/IMPLND/SOLIDS (Group) ''\n", + "/PERLND/ATEMP (Group) ''\n", "/PERLND/GENERAL (Group) ''\n", "/PERLND/PSTEMP (Group) ''\n", "/PERLND/PWATER (Group) ''\n", "/PERLND/PWTGAS (Group) ''\n", "/PERLND/SNOW (Group) ''\n", + "/PLTGEN/CURV-DATA1 (Group) ''\n", + "/PLTGEN/CURV-DATA2 (Group) ''\n", + "/PLTGEN/CURV-DATA3 (Group) ''\n", + "/PLTGEN/CURV-DATA4 (Group) ''\n", + "/PLTGEN/PARAMETERS (Group) ''\n", + "/RCHRES/ACIDPH (Group) ''\n", "/RCHRES/CONS (Group) ''\n", "/RCHRES/GENERAL (Group) ''\n", "/RCHRES/GQUAL (Group) ''\n", @@ -8923,10 +9822,7 @@ "/RESULTS/RCHRES_R005 (Group) ''\n", "/RUN_INFO/LOGFILE (Group) ''\n", "/RUN_INFO/VERSIONS (Group) ''\n", - "/TIMESERIES/LAPSE_Table (Group) ''\n", - "/TIMESERIES/SEASONS_Table (Group) ''\n", "/TIMESERIES/SUMMARY (Group) ''\n", - "/TIMESERIES/Saturated_Vapor_Pressure_Table (Group) ''\n", "/TIMESERIES/TS039 (Group) ''\n", "/TIMESERIES/TS041 (Group) ''\n", "/TIMESERIES/TS042 (Group) ''\n", @@ -8946,10 +9842,7 @@ "/TIMESERIES/TS135 (Group) ''\n", "/TIMESERIES/TS136 (Group) ''\n", "/TIMESERIES/TS140 (Group) ''\n", - "/TIMESERIES/LAPSE_Table/table (Table(24,)) ''\n", - "/TIMESERIES/SEASONS_Table/table (Table(12,)) ''\n", "/TIMESERIES/SUMMARY/table (Table(19,)) ''\n", - "/TIMESERIES/Saturated_Vapor_Pressure_Table/table (Table(40,)) ''\n", "/TIMESERIES/TS039/table (Table(8784,)) ''\n", "/TIMESERIES/TS041/table (Table(366,)) ''\n", "/TIMESERIES/TS042/table (Table(366,)) ''\n", @@ -8969,7 +9862,7 @@ "/TIMESERIES/TS135/table (Table(366,)) ''\n", "/TIMESERIES/TS136/table (Table(366,)) ''\n", "/TIMESERIES/TS140/table (Table(366,)) ''\n", - "/RUN_INFO/LOGFILE/table (Table(63,)) ''\n", + "/RUN_INFO/LOGFILE/table (Table(70,)) ''\n", "/RUN_INFO/VERSIONS/table (Table(10,)) ''\n", "/RESULTS/IMPLND_I001/IQUAL (Group) ''\n", "/RESULTS/IMPLND_I001/IWATER (Group) ''\n", @@ -9079,15 +9972,22 @@ "/RESULTS/IMPLND_I001/IWTGAS/table (Table(8784,)) ''\n", "/RESULTS/IMPLND_I001/SNOW/table (Table(8784,)) ''\n", "/RESULTS/IMPLND_I001/SOLIDS/table (Table(8784,)) ''\n", + "/RCHRES/ACIDPH/STATES (Group) ''\n", "/RCHRES/CONS/CONS1 (Group) ''\n", "/RCHRES/CONS/PARAMETERS (Group) ''\n", "/RCHRES/CONS/SAVE (Group) ''\n", "/RCHRES/GENERAL/ACTIVITY (Group) ''\n", "/RCHRES/GENERAL/INFO (Group) ''\n", + "/RCHRES/GENERAL/PRINT (Group) ''\n", "/RCHRES/GQUAL/EXTENDEDS (Group) ''\n", + "/RCHRES/GQUAL/FLAGS (Group) ''\n", "/RCHRES/GQUAL/GQUAL1 (Group) ''\n", + "/RCHRES/GQUAL/GQUAL2 (Group) ''\n", + "/RCHRES/GQUAL/GQUAL3 (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY (Group) ''\n", "/RCHRES/GQUAL/PARAMETERS (Group) ''\n", "/RCHRES/GQUAL/SAVE (Group) ''\n", + "/RCHRES/HTRCH/FLAGS (Group) ''\n", "/RCHRES/HTRCH/PARAMETERS (Group) ''\n", "/RCHRES/HTRCH/SAVE (Group) ''\n", "/RCHRES/HTRCH/STATES (Group) ''\n", @@ -9095,6 +9995,7 @@ "/RCHRES/HYDR/SAVE (Group) ''\n", "/RCHRES/HYDR/STATES (Group) ''\n", "/RCHRES/NUTRX/FLAGS (Group) ''\n", + "/RCHRES/NUTRX/MONTHLY (Group) ''\n", "/RCHRES/NUTRX/PARAMETERS (Group) ''\n", "/RCHRES/NUTRX/SAVE (Group) ''\n", "/RCHRES/NUTRX/STATES (Group) ''\n", @@ -9137,12 +10038,15 @@ "/RCHRES/OXRX/SAVE/table (Table(5,)) ''\n", "/RCHRES/OXRX/STATES/table (Table(5,)) ''\n", "/RCHRES/NUTRX/FLAGS/table (Table(5,)) ''\n", + "/RCHRES/NUTRX/MONTHLY/PHVA (Group) ''\n", "/RCHRES/NUTRX/PARAMETERS/table (Table(5,)) ''\n", "/RCHRES/NUTRX/SAVE/table (Table(5,)) ''\n", "/RCHRES/NUTRX/STATES/table (Table(5,)) ''\n", + "/RCHRES/NUTRX/MONTHLY/PHVA/table (Table(5,)) ''\n", "/RCHRES/HYDR/PARAMETERS/table (Table(5,)) ''\n", "/RCHRES/HYDR/SAVE/table (Table(5,)) ''\n", "/RCHRES/HYDR/STATES/table (Table(5,)) ''\n", + "/RCHRES/HTRCH/FLAGS/table (Table(5,)) ''\n", "/RCHRES/HTRCH/PARAMETERS/table (Table(5,)) ''\n", "/RCHRES/HTRCH/SAVE/table (Table(5,)) ''\n", "/RCHRES/HTRCH/STATES/table (Table(5,)) ''\n", @@ -9151,9 +10055,22 @@ "/RCHRES/GQUAL/EXTENDEDS/GAMM (Group) ''\n", "/RCHRES/GQUAL/EXTENDEDS/KCLD (Group) ''\n", "/RCHRES/GQUAL/EXTENDEDS/PHOTPM (Group) ''\n", + "/RCHRES/GQUAL/FLAGS/table (Table(5,)) ''\n", "/RCHRES/GQUAL/GQUAL1/table (Table(5,)) ''\n", + "/RCHRES/GQUAL/GQUAL2/table (Table(5,)) ''\n", + "/RCHRES/GQUAL/GQUAL3/table (Table(5,)) ''\n", + "/RCHRES/GQUAL/MONTHLY/CLDM (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY/PHYM (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY/ROCM (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY/SDCN (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY/TEMP (Group) ''\n", "/RCHRES/GQUAL/PARAMETERS/table (Table(5,)) ''\n", "/RCHRES/GQUAL/SAVE/table (Table(5,)) ''\n", + "/RCHRES/GQUAL/MONTHLY/CLDM/table (Table(5,)) ''\n", + "/RCHRES/GQUAL/MONTHLY/PHYM/table (Table(5,)) ''\n", + "/RCHRES/GQUAL/MONTHLY/ROCM/table (Table(5,)) ''\n", + "/RCHRES/GQUAL/MONTHLY/SDCN/table (Table(5,)) ''\n", + "/RCHRES/GQUAL/MONTHLY/TEMP/table (Table(5,)) ''\n", "/RCHRES/GQUAL/EXTENDEDS/ALPH/table (Table(5,)) ''\n", "/RCHRES/GQUAL/EXTENDEDS/DEL/table (Table(5,)) ''\n", "/RCHRES/GQUAL/EXTENDEDS/GAMM/table (Table(5,)) ''\n", @@ -9161,11 +10078,21 @@ "/RCHRES/GQUAL/EXTENDEDS/PHOTPM/table (Table(5,)) ''\n", "/RCHRES/GENERAL/ACTIVITY/table (Table(5,)) ''\n", "/RCHRES/GENERAL/INFO/table (Table(5,)) ''\n", + "/RCHRES/GENERAL/PRINT/table (Table(5,)) ''\n", "/RCHRES/CONS/CONS1/table (Table(5,)) ''\n", "/RCHRES/CONS/PARAMETERS/table (Table(5,)) ''\n", "/RCHRES/CONS/SAVE/table (Table(5,)) ''\n", + "/RCHRES/ACIDPH/STATES/table (Table(5,)) ''\n", + "/PLTGEN/CURV-DATA1/table (Table(2,)) ''\n", + "/PLTGEN/CURV-DATA2/table (Table(2,)) ''\n", + "/PLTGEN/CURV-DATA3/table (Table(2,)) ''\n", + "/PLTGEN/CURV-DATA4/table (Table(2,)) ''\n", + "/PLTGEN/PARAMETERS/table (Table(2,)) ''\n", + "/PERLND/ATEMP/PARAMETERS (Group) ''\n", + "/PERLND/ATEMP/SAVE (Group) ''\n", "/PERLND/GENERAL/ACTIVITY (Group) ''\n", "/PERLND/GENERAL/INFO (Group) ''\n", + "/PERLND/GENERAL/PRINT (Group) ''\n", "/PERLND/PSTEMP/PARAMETERS (Group) ''\n", "/PERLND/PSTEMP/SAVE (Group) ''\n", "/PERLND/PWATER/MONTHLY (Group) ''\n", @@ -9199,8 +10126,14 @@ "/PERLND/PSTEMP/SAVE/table (Table(1,)) ''\n", "/PERLND/GENERAL/ACTIVITY/table (Table(1,)) ''\n", "/PERLND/GENERAL/INFO/table (Table(1,)) ''\n", + "/PERLND/GENERAL/PRINT/table (Table(1,)) ''\n", + "/PERLND/ATEMP/PARAMETERS/table (Table(1,)) ''\n", + "/PERLND/ATEMP/SAVE/table (Table(1,)) ''\n", + "/IMPLND/ATEMP/PARAMETERS (Group) ''\n", + "/IMPLND/ATEMP/SAVE (Group) ''\n", "/IMPLND/GENERAL/ACTIVITY (Group) ''\n", "/IMPLND/GENERAL/INFO (Group) ''\n", + "/IMPLND/GENERAL/PRINT (Group) ''\n", "/IMPLND/IQUAL/IQUAL1 (Group) ''\n", "/IMPLND/IQUAL/PARAMETERS (Group) ''\n", "/IMPLND/IQUAL/SAVE (Group) ''\n", @@ -9209,6 +10142,7 @@ "/IMPLND/IWATER/STATES (Group) ''\n", "/IMPLND/IWTGAS/PARAMETERS (Group) ''\n", "/IMPLND/IWTGAS/SAVE (Group) ''\n", + "/IMPLND/IWTGAS/STATES (Group) ''\n", "/IMPLND/SNOW/FLAGS (Group) ''\n", "/IMPLND/SNOW/PARAMETERS (Group) ''\n", "/IMPLND/SNOW/SAVE (Group) ''\n", @@ -9223,6 +10157,7 @@ "/IMPLND/SNOW/STATES/table (Table(1,)) ''\n", "/IMPLND/IWTGAS/PARAMETERS/table (Table(1,)) ''\n", "/IMPLND/IWTGAS/SAVE/table (Table(1,)) ''\n", + "/IMPLND/IWTGAS/STATES/table (Table(1,)) ''\n", "/IMPLND/IWATER/PARAMETERS/table (Table(1,)) ''\n", "/IMPLND/IWATER/SAVE/table (Table(1,)) ''\n", "/IMPLND/IWATER/STATES/table (Table(1,)) ''\n", @@ -9234,17 +10169,23 @@ "/IMPLND/IQUAL/IQUAL1/PARAMETERS/table (Table(1,)) ''\n", "/IMPLND/GENERAL/ACTIVITY/table (Table(1,)) ''\n", "/IMPLND/GENERAL/INFO/table (Table(1,)) ''\n", - "/GENER/OPCODE/table (Table(1,)) ''\n", + "/IMPLND/GENERAL/PRINT/table (Table(1,)) ''\n", + "/IMPLND/ATEMP/PARAMETERS/table (Table(1,)) ''\n", + "/IMPLND/ATEMP/SAVE/table (Table(1,)) ''\n", + "/GENER/OPCODE/table (Table(2,)) ''\n", "/FTABLES/FT001/table (Table(14,)) ''\n", "/FTABLES/FT002/table (Table(13,)) ''\n", "/FTABLES/FT003/table (Table(13,)) ''\n", "/FTABLES/FT004/table (Table(13,)) ''\n", "/FTABLES/FT005/table (Table(13,)) ''\n", + "/FILES/FILES/table (Table(6,)) ''\n", + "/DISPLY/DISPLY/INFO (Group) ''\n", + "/DISPLY/DISPLY/INFO/table (Table(5,)) ''\n", "/CONTROL/EXT_SOURCES/table (Table(50,)) ''\n", "/CONTROL/GLOBAL/table (Table(4,)) ''\n", - "/CONTROL/LINKS/table (Table(11,)) ''\n", + "/CONTROL/LINKS/table (Table(22,)) ''\n", "/CONTROL/MASS_LINKS/table (Table(15,)) ''\n", - "/CONTROL/OP_SEQUENCE/table (Table(9,)) ''\n" + "/CONTROL/OP_SEQUENCE/table (Table(16,)) ''\n" ] } ], @@ -9267,18 +10208,18 @@ "text": [ "/ (RootGroup) ''\n", "/CONTROL (Group) ''\n", + "/DISPLY (Group) ''\n", + "/FILES (Group) ''\n", "/FTABLES (Group) ''\n", "/GENER (Group) ''\n", "/IMPLND (Group) ''\n", "/PERLND (Group) ''\n", + "/PLTGEN (Group) ''\n", "/RCHRES (Group) ''\n", "/RESULTS (Group) ''\n", "/RUN_INFO (Group) ''\n", "/TIMESERIES (Group) ''\n", - "/TIMESERIES/LAPSE_Table (Group) ''\n", - "/TIMESERIES/SEASONS_Table (Group) ''\n", "/TIMESERIES/SUMMARY (Group) ''\n", - "/TIMESERIES/Saturated_Vapor_Pressure_Table (Group) ''\n", "/TIMESERIES/TS039 (Group) ''\n", "/TIMESERIES/TS041 (Group) ''\n", "/TIMESERIES/TS042 (Group) ''\n", @@ -9361,6 +10302,7 @@ "/RESULTS/IMPLND_I001/IWTGAS (Group) ''\n", "/RESULTS/IMPLND_I001/SNOW (Group) ''\n", "/RESULTS/IMPLND_I001/SOLIDS (Group) ''\n", + "/RCHRES/ACIDPH (Group) ''\n", "/RCHRES/CONS (Group) ''\n", "/RCHRES/GENERAL (Group) ''\n", "/RCHRES/GQUAL (Group) ''\n", @@ -9392,19 +10334,31 @@ "/RCHRES/OXRX/SAVE (Group) ''\n", "/RCHRES/OXRX/STATES (Group) ''\n", "/RCHRES/NUTRX/FLAGS (Group) ''\n", + "/RCHRES/NUTRX/MONTHLY (Group) ''\n", "/RCHRES/NUTRX/PARAMETERS (Group) ''\n", "/RCHRES/NUTRX/SAVE (Group) ''\n", "/RCHRES/NUTRX/STATES (Group) ''\n", + "/RCHRES/NUTRX/MONTHLY/PHVA (Group) ''\n", "/RCHRES/HYDR/PARAMETERS (Group) ''\n", "/RCHRES/HYDR/SAVE (Group) ''\n", "/RCHRES/HYDR/STATES (Group) ''\n", + "/RCHRES/HTRCH/FLAGS (Group) ''\n", "/RCHRES/HTRCH/PARAMETERS (Group) ''\n", "/RCHRES/HTRCH/SAVE (Group) ''\n", "/RCHRES/HTRCH/STATES (Group) ''\n", "/RCHRES/GQUAL/EXTENDEDS (Group) ''\n", + "/RCHRES/GQUAL/FLAGS (Group) ''\n", "/RCHRES/GQUAL/GQUAL1 (Group) ''\n", + "/RCHRES/GQUAL/GQUAL2 (Group) ''\n", + "/RCHRES/GQUAL/GQUAL3 (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY (Group) ''\n", "/RCHRES/GQUAL/PARAMETERS (Group) ''\n", "/RCHRES/GQUAL/SAVE (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY/CLDM (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY/PHYM (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY/ROCM (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY/SDCN (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY/TEMP (Group) ''\n", "/RCHRES/GQUAL/EXTENDEDS/ALPH (Group) ''\n", "/RCHRES/GQUAL/EXTENDEDS/DEL (Group) ''\n", "/RCHRES/GQUAL/EXTENDEDS/GAMM (Group) ''\n", @@ -9412,9 +10366,17 @@ "/RCHRES/GQUAL/EXTENDEDS/PHOTPM (Group) ''\n", "/RCHRES/GENERAL/ACTIVITY (Group) ''\n", "/RCHRES/GENERAL/INFO (Group) ''\n", + "/RCHRES/GENERAL/PRINT (Group) ''\n", "/RCHRES/CONS/CONS1 (Group) ''\n", "/RCHRES/CONS/PARAMETERS (Group) ''\n", "/RCHRES/CONS/SAVE (Group) ''\n", + "/RCHRES/ACIDPH/STATES (Group) ''\n", + "/PLTGEN/CURV-DATA1 (Group) ''\n", + "/PLTGEN/CURV-DATA2 (Group) ''\n", + "/PLTGEN/CURV-DATA3 (Group) ''\n", + "/PLTGEN/CURV-DATA4 (Group) ''\n", + "/PLTGEN/PARAMETERS (Group) ''\n", + "/PERLND/ATEMP (Group) ''\n", "/PERLND/GENERAL (Group) ''\n", "/PERLND/PSTEMP (Group) ''\n", "/PERLND/PWATER (Group) ''\n", @@ -9438,6 +10400,10 @@ "/PERLND/PSTEMP/SAVE (Group) ''\n", "/PERLND/GENERAL/ACTIVITY (Group) ''\n", "/PERLND/GENERAL/INFO (Group) ''\n", + "/PERLND/GENERAL/PRINT (Group) ''\n", + "/PERLND/ATEMP/PARAMETERS (Group) ''\n", + "/PERLND/ATEMP/SAVE (Group) ''\n", + "/IMPLND/ATEMP (Group) ''\n", "/IMPLND/GENERAL (Group) ''\n", "/IMPLND/IQUAL (Group) ''\n", "/IMPLND/IWATER (Group) ''\n", @@ -9452,6 +10418,7 @@ "/IMPLND/SNOW/STATES (Group) ''\n", "/IMPLND/IWTGAS/PARAMETERS (Group) ''\n", "/IMPLND/IWTGAS/SAVE (Group) ''\n", + "/IMPLND/IWTGAS/STATES (Group) ''\n", "/IMPLND/IWATER/PARAMETERS (Group) ''\n", "/IMPLND/IWATER/SAVE (Group) ''\n", "/IMPLND/IWATER/STATES (Group) ''\n", @@ -9462,12 +10429,18 @@ "/IMPLND/IQUAL/IQUAL1/PARAMETERS (Group) ''\n", "/IMPLND/GENERAL/ACTIVITY (Group) ''\n", "/IMPLND/GENERAL/INFO (Group) ''\n", + "/IMPLND/GENERAL/PRINT (Group) ''\n", + "/IMPLND/ATEMP/PARAMETERS (Group) ''\n", + "/IMPLND/ATEMP/SAVE (Group) ''\n", "/GENER/OPCODE (Group) ''\n", "/FTABLES/FT001 (Group) ''\n", "/FTABLES/FT002 (Group) ''\n", "/FTABLES/FT003 (Group) ''\n", "/FTABLES/FT004 (Group) ''\n", "/FTABLES/FT005 (Group) ''\n", + "/FILES/FILES (Group) ''\n", + "/DISPLY/DISPLY (Group) ''\n", + "/DISPLY/DISPLY/INFO (Group) ''\n", "/CONTROL/EXT_SOURCES (Group) ''\n", "/CONTROL/GLOBAL (Group) ''\n", "/CONTROL/LINKS (Group) ''\n", @@ -9492,7 +10465,7 @@ "data": { "text/plain": [ "/ (RootGroup) ''\n", - " children := ['CONTROL' (Group), 'FTABLES' (Group), 'GENER' (Group), 'IMPLND' (Group), 'PERLND' (Group), 'RCHRES' (Group), 'RESULTS' (Group), 'RUN_INFO' (Group), 'TIMESERIES' (Group)]" + " children := ['CONTROL' (Group), 'DISPLY' (Group), 'FILES' (Group), 'FTABLES' (Group), 'GENER' (Group), 'IMPLND' (Group), 'PERLND' (Group), 'PLTGEN' (Group), 'RCHRES' (Group), 'RESULTS' (Group), 'RUN_INFO' (Group), 'TIMESERIES' (Group)]" ] }, "execution_count": 15, @@ -9562,39 +10535,41 @@ "/CONTROL/EXT_SOURCES/table (Table(50,)) ''\n", " description := {\n", " \"index\": Int64Col(shape=(), dflt=0, pos=0),\n", - " \"SVOL\": StringCol(itemsize=1, shape=(), dflt=b'', pos=1),\n", - " \"SVOLNO\": StringCol(itemsize=5, shape=(), dflt=b'', pos=2),\n", - " \"SMEMN\": StringCol(itemsize=4, shape=(), dflt=b'', pos=3),\n", - " \"SMEMSB\": StringCol(itemsize=2, shape=(), dflt=b'', pos=4),\n", - " \"SSYST\": StringCol(itemsize=4, shape=(), dflt=b'', pos=5),\n", - " \"SGAPST\": StringCol(itemsize=4, shape=(), dflt=b'', pos=6),\n", - " \"MFACTOR\": Float64Col(shape=(), dflt=0.0, pos=7),\n", - " \"TRAN\": StringCol(itemsize=4, shape=(), dflt=b'', pos=8),\n", - " \"TVOL\": StringCol(itemsize=6, shape=(), dflt=b'', pos=9),\n", - " \"TGRPN\": StringCol(itemsize=5, shape=(), dflt=b'', pos=10),\n", - " \"TMEMN\": StringCol(itemsize=6, shape=(), dflt=b'', pos=11),\n", - " \"TMEMSB\": StringCol(itemsize=1, shape=(), dflt=b'', pos=12),\n", - " \"TVOLNO\": StringCol(itemsize=4, shape=(), dflt=b'', pos=13),\n", - " \"COMMENT\": StringCol(itemsize=1, shape=(), dflt=b'', pos=14)}\n", - " byteorder := 'little'\n", - " chunkshape := (1040,)\n", - " autoindex := True\n", - " colindexes := {\n", - " \"index\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SVOLNO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SMEMN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SMEMSB\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SSYST\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"SGAPST\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"MFACTOR\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TRAN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TVOL\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TGRPN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TMEMN\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TMEMSB\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"TVOLNO\": Index(6, medium, shuffle, zlib(1)).is_csi=False,\n", - " \"COMMENT\": Index(6, medium, shuffle, zlib(1)).is_csi=False}" + " \"TVOLNO\": StringCol(itemsize=4, shape=(), dflt=b'', pos=1),\n", + " \"SVOL\": StringCol(itemsize=3, shape=(), dflt=b'', pos=2),\n", + " \"SVOLNO\": StringCol(itemsize=5, shape=(), dflt=b'', pos=3),\n", + " \"SMEMN\": StringCol(itemsize=4, shape=(), dflt=b'', pos=4),\n", + " \"QLFG\": Float64Col(shape=(), dflt=0.0, pos=5),\n", + " \"SSYST\": StringCol(itemsize=4, shape=(), dflt=b'', pos=6),\n", + " \"SGAPST\": StringCol(itemsize=4, shape=(), dflt=b'', pos=7),\n", + " \"MFACTOR\": Float64Col(shape=(), dflt=0.0, pos=8),\n", + " \"TRAN\": StringCol(itemsize=4, shape=(), dflt=b'', pos=9),\n", + " \"TVOL\": StringCol(itemsize=6, shape=(), dflt=b'', pos=10),\n", + " \"TGRPN\": StringCol(itemsize=5, shape=(), dflt=b'', pos=11),\n", + " \"TMEMN\": StringCol(itemsize=6, shape=(), dflt=b'', pos=12),\n", + " \"TMEMSB1\": StringCol(itemsize=1, shape=(), dflt=b'', pos=13),\n", + " \"TMEMSB2\": StringCol(itemsize=1, shape=(), dflt=b'', pos=14),\n", + " \"TMEMSB\": StringCol(itemsize=1, shape=(), dflt=b'', pos=15)}\n", + " byteorder := 'little'\n", + " chunkshape := (910,)\n", + " autoindex := True\n", + " colindexes := {\n", + " \"index\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TVOLNO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SVOLNO\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SMEMN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"QLFG\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SSYST\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"SGAPST\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"MFACTOR\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TRAN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TVOL\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TGRPN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TMEMN\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TMEMSB1\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TMEMSB2\": Index(6, mediumshuffle, zlib(1)).is_csi=False,\n", + " \"TMEMSB\": Index(6, mediumshuffle, zlib(1)).is_csi=False}" ] }, "execution_count": 18, @@ -9713,7 +10688,7 @@ { "data": { "text/plain": [ - "PosixPath('/Users/aaufdenkampe/Documents/Python/respec.HSPsquared/examples/_TutorialData/test10.h5')" + "PosixPath('/var/home/timcera/programming/HSP_old/HSPsquared/examples/_TutorialData/test10.h5')" ] }, "execution_count": 23, @@ -9738,22 +10713,19 @@ "text": [ "/ (RootGroup) ''\n", "/CONTROL (Group) ''\n", + "/DISPLY (Group) ''\n", + "/FILES (Group) ''\n", "/FTABLES (Group) ''\n", "/GENER (Group) ''\n", "/IMPLND (Group) ''\n", "/PERLND (Group) ''\n", + "/PLTGEN (Group) ''\n", "/RCHRES (Group) ''\n", "/RESULTS (Group) ''\n", "/RUN_INFO (Group) ''\n", "/TIMESERIES (Group) ''\n", - "/TIMESERIES/LAPSE_Table (Group) ''\n", - "/TIMESERIES/LAPSE_Table/table (Table(24,)) ''\n", - "/TIMESERIES/SEASONS_Table (Group) ''\n", - "/TIMESERIES/SEASONS_Table/table (Table(12,)) ''\n", "/TIMESERIES/SUMMARY (Group) ''\n", "/TIMESERIES/SUMMARY/table (Table(19,)) ''\n", - "/TIMESERIES/Saturated_Vapor_Pressure_Table (Group) ''\n", - "/TIMESERIES/Saturated_Vapor_Pressure_Table/table (Table(40,)) ''\n", "/TIMESERIES/TS039 (Group) ''\n", "/TIMESERIES/TS039/table (Table(8784,)) ''\n", "/TIMESERIES/TS041 (Group) ''\n", @@ -9793,7 +10765,7 @@ "/TIMESERIES/TS140 (Group) ''\n", "/TIMESERIES/TS140/table (Table(366,)) ''\n", "/RUN_INFO/LOGFILE (Group) ''\n", - "/RUN_INFO/LOGFILE/table (Table(63,)) ''\n", + "/RUN_INFO/LOGFILE/table (Table(70,)) ''\n", "/RUN_INFO/VERSIONS (Group) ''\n", "/RUN_INFO/VERSIONS/table (Table(10,)) ''\n", "/RESULTS/IMPLND_I001 (Group) ''\n", @@ -9911,6 +10883,7 @@ "/RESULTS/IMPLND_I001/SNOW/table (Table(8784,)) ''\n", "/RESULTS/IMPLND_I001/SOLIDS (Group) ''\n", "/RESULTS/IMPLND_I001/SOLIDS/table (Table(8784,)) ''\n", + "/RCHRES/ACIDPH (Group) ''\n", "/RCHRES/CONS (Group) ''\n", "/RCHRES/GENERAL (Group) ''\n", "/RCHRES/GQUAL (Group) ''\n", @@ -9962,18 +10935,23 @@ "/RCHRES/OXRX/STATES/table (Table(5,)) ''\n", "/RCHRES/NUTRX/FLAGS (Group) ''\n", "/RCHRES/NUTRX/FLAGS/table (Table(5,)) ''\n", + "/RCHRES/NUTRX/MONTHLY (Group) ''\n", "/RCHRES/NUTRX/PARAMETERS (Group) ''\n", "/RCHRES/NUTRX/PARAMETERS/table (Table(5,)) ''\n", "/RCHRES/NUTRX/SAVE (Group) ''\n", "/RCHRES/NUTRX/SAVE/table (Table(5,)) ''\n", "/RCHRES/NUTRX/STATES (Group) ''\n", "/RCHRES/NUTRX/STATES/table (Table(5,)) ''\n", + "/RCHRES/NUTRX/MONTHLY/PHVA (Group) ''\n", + "/RCHRES/NUTRX/MONTHLY/PHVA/table (Table(5,)) ''\n", "/RCHRES/HYDR/PARAMETERS (Group) ''\n", "/RCHRES/HYDR/PARAMETERS/table (Table(5,)) ''\n", "/RCHRES/HYDR/SAVE (Group) ''\n", "/RCHRES/HYDR/SAVE/table (Table(5,)) ''\n", "/RCHRES/HYDR/STATES (Group) ''\n", "/RCHRES/HYDR/STATES/table (Table(5,)) ''\n", + "/RCHRES/HTRCH/FLAGS (Group) ''\n", + "/RCHRES/HTRCH/FLAGS/table (Table(5,)) ''\n", "/RCHRES/HTRCH/PARAMETERS (Group) ''\n", "/RCHRES/HTRCH/PARAMETERS/table (Table(5,)) ''\n", "/RCHRES/HTRCH/SAVE (Group) ''\n", @@ -9981,12 +10959,29 @@ "/RCHRES/HTRCH/STATES (Group) ''\n", "/RCHRES/HTRCH/STATES/table (Table(5,)) ''\n", "/RCHRES/GQUAL/EXTENDEDS (Group) ''\n", + "/RCHRES/GQUAL/FLAGS (Group) ''\n", + "/RCHRES/GQUAL/FLAGS/table (Table(5,)) ''\n", "/RCHRES/GQUAL/GQUAL1 (Group) ''\n", "/RCHRES/GQUAL/GQUAL1/table (Table(5,)) ''\n", + "/RCHRES/GQUAL/GQUAL2 (Group) ''\n", + "/RCHRES/GQUAL/GQUAL2/table (Table(5,)) ''\n", + "/RCHRES/GQUAL/GQUAL3 (Group) ''\n", + "/RCHRES/GQUAL/GQUAL3/table (Table(5,)) ''\n", + "/RCHRES/GQUAL/MONTHLY (Group) ''\n", "/RCHRES/GQUAL/PARAMETERS (Group) ''\n", "/RCHRES/GQUAL/PARAMETERS/table (Table(5,)) ''\n", "/RCHRES/GQUAL/SAVE (Group) ''\n", "/RCHRES/GQUAL/SAVE/table (Table(5,)) ''\n", + "/RCHRES/GQUAL/MONTHLY/CLDM (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY/CLDM/table (Table(5,)) ''\n", + "/RCHRES/GQUAL/MONTHLY/PHYM (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY/PHYM/table (Table(5,)) ''\n", + "/RCHRES/GQUAL/MONTHLY/ROCM (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY/ROCM/table (Table(5,)) ''\n", + "/RCHRES/GQUAL/MONTHLY/SDCN (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY/SDCN/table (Table(5,)) ''\n", + "/RCHRES/GQUAL/MONTHLY/TEMP (Group) ''\n", + "/RCHRES/GQUAL/MONTHLY/TEMP/table (Table(5,)) ''\n", "/RCHRES/GQUAL/EXTENDEDS/ALPH (Group) ''\n", "/RCHRES/GQUAL/EXTENDEDS/ALPH/table (Table(5,)) ''\n", "/RCHRES/GQUAL/EXTENDEDS/DEL (Group) ''\n", @@ -10001,12 +10996,27 @@ "/RCHRES/GENERAL/ACTIVITY/table (Table(5,)) ''\n", "/RCHRES/GENERAL/INFO (Group) ''\n", "/RCHRES/GENERAL/INFO/table (Table(5,)) ''\n", + "/RCHRES/GENERAL/PRINT (Group) ''\n", + "/RCHRES/GENERAL/PRINT/table (Table(5,)) ''\n", "/RCHRES/CONS/CONS1 (Group) ''\n", "/RCHRES/CONS/CONS1/table (Table(5,)) ''\n", "/RCHRES/CONS/PARAMETERS (Group) ''\n", "/RCHRES/CONS/PARAMETERS/table (Table(5,)) ''\n", "/RCHRES/CONS/SAVE (Group) ''\n", "/RCHRES/CONS/SAVE/table (Table(5,)) ''\n", + "/RCHRES/ACIDPH/STATES (Group) ''\n", + "/RCHRES/ACIDPH/STATES/table (Table(5,)) ''\n", + "/PLTGEN/CURV-DATA1 (Group) ''\n", + "/PLTGEN/CURV-DATA1/table (Table(2,)) ''\n", + "/PLTGEN/CURV-DATA2 (Group) ''\n", + "/PLTGEN/CURV-DATA2/table (Table(2,)) ''\n", + "/PLTGEN/CURV-DATA3 (Group) ''\n", + "/PLTGEN/CURV-DATA3/table (Table(2,)) ''\n", + "/PLTGEN/CURV-DATA4 (Group) ''\n", + "/PLTGEN/CURV-DATA4/table (Table(2,)) ''\n", + "/PLTGEN/PARAMETERS (Group) ''\n", + "/PLTGEN/PARAMETERS/table (Table(2,)) ''\n", + "/PERLND/ATEMP (Group) ''\n", "/PERLND/GENERAL (Group) ''\n", "/PERLND/PSTEMP (Group) ''\n", "/PERLND/PWATER (Group) ''\n", @@ -10047,6 +11057,13 @@ "/PERLND/GENERAL/ACTIVITY/table (Table(1,)) ''\n", "/PERLND/GENERAL/INFO (Group) ''\n", "/PERLND/GENERAL/INFO/table (Table(1,)) ''\n", + "/PERLND/GENERAL/PRINT (Group) ''\n", + "/PERLND/GENERAL/PRINT/table (Table(1,)) ''\n", + "/PERLND/ATEMP/PARAMETERS (Group) ''\n", + "/PERLND/ATEMP/PARAMETERS/table (Table(1,)) ''\n", + "/PERLND/ATEMP/SAVE (Group) ''\n", + "/PERLND/ATEMP/SAVE/table (Table(1,)) ''\n", + "/IMPLND/ATEMP (Group) ''\n", "/IMPLND/GENERAL (Group) ''\n", "/IMPLND/IQUAL (Group) ''\n", "/IMPLND/IWATER (Group) ''\n", @@ -10069,6 +11086,8 @@ "/IMPLND/IWTGAS/PARAMETERS/table (Table(1,)) ''\n", "/IMPLND/IWTGAS/SAVE (Group) ''\n", "/IMPLND/IWTGAS/SAVE/table (Table(1,)) ''\n", + "/IMPLND/IWTGAS/STATES (Group) ''\n", + "/IMPLND/IWTGAS/STATES/table (Table(1,)) ''\n", "/IMPLND/IWATER/PARAMETERS (Group) ''\n", "/IMPLND/IWATER/PARAMETERS/table (Table(1,)) ''\n", "/IMPLND/IWATER/SAVE (Group) ''\n", @@ -10088,8 +11107,14 @@ "/IMPLND/GENERAL/ACTIVITY/table (Table(1,)) ''\n", "/IMPLND/GENERAL/INFO (Group) ''\n", "/IMPLND/GENERAL/INFO/table (Table(1,)) ''\n", + "/IMPLND/GENERAL/PRINT (Group) ''\n", + "/IMPLND/GENERAL/PRINT/table (Table(1,)) ''\n", + "/IMPLND/ATEMP/PARAMETERS (Group) ''\n", + "/IMPLND/ATEMP/PARAMETERS/table (Table(1,)) ''\n", + "/IMPLND/ATEMP/SAVE (Group) ''\n", + "/IMPLND/ATEMP/SAVE/table (Table(1,)) ''\n", "/GENER/OPCODE (Group) ''\n", - "/GENER/OPCODE/table (Table(1,)) ''\n", + "/GENER/OPCODE/table (Table(2,)) ''\n", "/FTABLES/FT001 (Group) ''\n", "/FTABLES/FT001/table (Table(14,)) ''\n", "/FTABLES/FT002 (Group) ''\n", @@ -10100,16 +11125,21 @@ "/FTABLES/FT004/table (Table(13,)) ''\n", "/FTABLES/FT005 (Group) ''\n", "/FTABLES/FT005/table (Table(13,)) ''\n", + "/FILES/FILES (Group) ''\n", + "/FILES/FILES/table (Table(6,)) ''\n", + "/DISPLY/DISPLY (Group) ''\n", + "/DISPLY/DISPLY/INFO (Group) ''\n", + "/DISPLY/DISPLY/INFO/table (Table(5,)) ''\n", "/CONTROL/EXT_SOURCES (Group) ''\n", "/CONTROL/EXT_SOURCES/table (Table(50,)) ''\n", "/CONTROL/GLOBAL (Group) ''\n", "/CONTROL/GLOBAL/table (Table(4,)) ''\n", "/CONTROL/LINKS (Group) ''\n", - "/CONTROL/LINKS/table (Table(11,)) ''\n", + "/CONTROL/LINKS/table (Table(22,)) ''\n", "/CONTROL/MASS_LINKS (Group) ''\n", "/CONTROL/MASS_LINKS/table (Table(15,)) ''\n", "/CONTROL/OP_SEQUENCE (Group) ''\n", - "/CONTROL/OP_SEQUENCE/table (Table(9,)) ''\n" + "/CONTROL/OP_SEQUENCE/table (Table(16,)) ''\n" ] } ], @@ -10118,7 +11148,7 @@ "\n", "# Paste your path from the block above into the statement below.\n", "\n", - "!ptdump '/Users/aaufdenkampe/Documents/Python/respec.HSPsquared/examples/_TutorialData/test10.h5'\n", + "!ptdump $output_hdf5_path\n", "\n", "# You can pass the -v or -d options to ptdump if you want more verbosity" ] @@ -10162,7 +11192,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 26, @@ -10185,10 +11215,13 @@ "output_type": "stream", "text": [ "CONTROL\n", + "DISPLY\n", + "FILES\n", "FTABLES\n", "GENER\n", "IMPLND\n", "PERLND\n", + "PLTGEN\n", "RCHRES\n", "RESULTS\n", "RUN_INFO\n", @@ -10253,10 +11286,13 @@ "data": { "text/plain": [ "['CONTROL',\n", + " 'DISPLY',\n", + " 'FILES',\n", " 'FTABLES',\n", " 'GENER',\n", " 'IMPLND',\n", " 'PERLND',\n", + " 'PLTGEN',\n", " 'RCHRES',\n", " 'RESULTS',\n", " 'RUN_INFO',\n", @@ -10288,23 +11324,33 @@ "CONTROL\\ LINKS\n", "CONTROL\\ MASS_LINKS\n", "CONTROL\\ OP_SEQUENCE\n", + "DISPLY\\ DISPLY\n", + "FILES\\ FILES\n", "FTABLES\\ FT001\n", "FTABLES\\ FT002\n", "FTABLES\\ FT003\n", "FTABLES\\ FT004\n", "FTABLES\\ FT005\n", "GENER\\ OPCODE\n", + "IMPLND\\ ATEMP\n", "IMPLND\\ GENERAL\n", "IMPLND\\ IQUAL\n", "IMPLND\\ IWATER\n", "IMPLND\\ IWTGAS\n", "IMPLND\\ SNOW\n", "IMPLND\\ SOLIDS\n", + "PERLND\\ ATEMP\n", "PERLND\\ GENERAL\n", "PERLND\\ PSTEMP\n", "PERLND\\ PWATER\n", "PERLND\\ PWTGAS\n", "PERLND\\ SNOW\n", + "PLTGEN\\ CURV-DATA1\n", + "PLTGEN\\ CURV-DATA2\n", + "PLTGEN\\ CURV-DATA3\n", + "PLTGEN\\ CURV-DATA4\n", + "PLTGEN\\ PARAMETERS\n", + "RCHRES\\ ACIDPH\n", "RCHRES\\ CONS\n", "RCHRES\\ GENERAL\n", "RCHRES\\ GQUAL\n", @@ -10325,10 +11371,7 @@ "RESULTS\\ RCHRES_R005\n", "RUN_INFO\\ LOGFILE\n", "RUN_INFO\\ VERSIONS\n", - "TIMESERIES\\ LAPSE_Table\n", - "TIMESERIES\\ SEASONS_Table\n", "TIMESERIES\\ SUMMARY\n", - "TIMESERIES\\ Saturated_Vapor_Pressure_Table\n", "TIMESERIES\\ TS039\n", "TIMESERIES\\ TS041\n", "TIMESERIES\\ TS042\n", @@ -10411,7 +11454,7 @@ { "data": { "text/plain": [ - "PosixPath('/Users/aaufdenkampe/Documents/Python/respec.HSPsquared/examples/_TutorialData/test10.h5')" + "PosixPath('/var/home/timcera/programming/HSP_old/HSPsquared/examples/_TutorialData/test10.h5')" ] }, "execution_count": 34, @@ -10431,18 +11474,10 @@ "source": [ "# This cell is disabled, to prevent accidently running this command\n", "\n", - "!h5dump '/Users/aaufdenkampe/Documents/Python/respec.HSPsquared/examples/_TutorialData/test10.h5'\n", + "!h5dump $output_hdf5_path\n", "\n", "# WARNING: This is extremely verbose and takes a very long time to complete!!!!" ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "sound-monroe", - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -10461,14 +11496,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.14" + "version": "3.11.11" }, - "toc-autonumbering": true, - "vscode": { - "interpreter": { - "hash": "776e005896af2bdd35b514f04d0649047a67df21e3539ef9c16d2c229e31ef47" - } - } + "toc-autonumbering": true }, "nbformat": 4, "nbformat_minor": 5 diff --git a/examples/3_DataVisualizationDemo.ipynb b/examples/3_DataVisualizationDemo.ipynb index 84083be3..b8d4a014 100644 --- a/examples/3_DataVisualizationDemo.ipynb +++ b/examples/3_DataVisualizationDemo.ipynb @@ -49,21 +49,45 @@ "outputs": [ { "data": { - "application/javascript": [ + "text/html": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ "(function(root) {\n", " function now() {\n", " return new Date();\n", " }\n", "\n", - " var force = true;\n", + " const force = true;\n", + " const version = '3.8.2'.replace('rc', '-rc.').replace('.dev', '-dev.');\n", + " const reloading = false;\n", + " const Bokeh = root.Bokeh;\n", + " const BK_RE = /^https:\\/\\/cdn\\.bokeh\\.org\\/bokeh\\/(release|dev)\\/bokeh-/;\n", + " const PN_RE = /^https:\\/\\/cdn\\.holoviz\\.org\\/panel\\/[^/]+\\/dist\\/panel/i;\n", "\n", - " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", - " root._bokeh_onload_callbacks = [];\n", - " root._bokeh_is_loading = undefined;\n", - " }\n", - "\n", - " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", + " // Set a timeout for this load but only if we are not already initializing\n", + " if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n", " root._bokeh_timeout = Date.now() + 5000;\n", " root._bokeh_failed_load = false;\n", " }\n", @@ -75,26 +99,28 @@ " callback();\n", " });\n", " } finally {\n", - " delete root._bokeh_onload_callbacks\n", + " delete root._bokeh_onload_callbacks;\n", " }\n", " console.debug(\"Bokeh: all callbacks have finished\");\n", " }\n", "\n", - " function load_libs(css_urls, js_urls, js_modules, callback) {\n", + " function load_libs(css_urls, js_urls, js_modules, js_exports, Bokeh, callback) {\n", " if (css_urls == null) css_urls = [];\n", " if (js_urls == null) js_urls = [];\n", " if (js_modules == null) js_modules = [];\n", + " if (js_exports == null) js_exports = {};\n", "\n", " root._bokeh_onload_callbacks.push(callback);\n", + "\n", " if (root._bokeh_is_loading > 0) {\n", + " // Don't load bokeh if it is still initializing\n", " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", " return null;\n", - " }\n", - " if (js_urls.length === 0 && js_modules.length === 0) {\n", + " } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n", + " // There is nothing to load\n", " run_callbacks();\n", " return null;\n", " }\n", - " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", "\n", " function on_load() {\n", " root._bokeh_is_loading--;\n", @@ -103,13 +129,36 @@ " run_callbacks()\n", " }\n", " }\n", + " window._bokeh_on_load = on_load\n", + "\n", + " function on_error(e) {\n", + " const src_el = e.srcElement\n", + " console.error(\"failed to load \" + (src_el.href || src_el.src));\n", + " }\n", "\n", - " function on_error() {\n", - " console.error(\"failed to load \" + url);\n", + " const skip = [];\n", + " if (window.requirejs) {\n", + " window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n", + " root._bokeh_is_loading = css_urls.length + 0;\n", + " } else {\n", + " root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n", " }\n", "\n", - " for (var i = 0; i < css_urls.length; i++) {\n", - " var url = css_urls[i];\n", + " const existing_stylesheets = []\n", + " const links = document.getElementsByTagName('link')\n", + " for (let i = 0; i < links.length; i++) {\n", + " const link = links[i]\n", + " if (link.href != null) {\n", + " existing_stylesheets.push(link.href)\n", + " }\n", + " }\n", + " for (let i = 0; i < css_urls.length; i++) {\n", + " const url = css_urls[i];\n", + " const escaped = encodeURI(url)\n", + " if (existing_stylesheets.indexOf(escaped) !== -1) {\n", + " on_load()\n", + " continue;\n", + " }\n", " const element = document.createElement(\"link\");\n", " element.onload = on_load;\n", " element.onerror = on_error;\n", @@ -118,25 +167,27 @@ " element.href = url;\n", " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", " document.body.appendChild(element);\n", + " } var existing_scripts = []\n", + " const scripts = document.getElementsByTagName('script')\n", + " for (let i = 0; i < scripts.length; i++) {\n", + " var script = scripts[i]\n", + " if (script.src != null) {\n", + " existing_scripts.push(script.src)\n", + " }\n", " }\n", - "\n", - " var skip = [];\n", - " if (window.requirejs) {\n", - " window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n", - " \n", - " root._bokeh_is_loading = css_urls.length + 0;\n", - " } else {\n", - " root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length;\n", - " }\n", - " for (var i = 0; i < js_urls.length; i++) {\n", - " var url = js_urls[i];\n", - " if (skip.indexOf(url) >= 0) {\n", - "\tif (!window.requirejs) {\n", - "\t on_load();\n", - "\t}\n", - "\tcontinue;\n", + " for (let i = 0; i < js_urls.length; i++) {\n", + " const url = js_urls[i];\n", + " const escaped = encodeURI(url)\n", + " const shouldSkip = skip.includes(escaped) || existing_scripts.includes(escaped)\n", + " const isBokehOrPanel = BK_RE.test(escaped) || PN_RE.test(escaped)\n", + " const missingOrBroken = Bokeh == null || Bokeh.Panel == null || (Bokeh.version != version && !Bokeh.versions?.has(version)) || Bokeh.versions?.get(version)?.Panel == null;\n", + " if (shouldSkip && !(isBokehOrPanel && missingOrBroken)) {\n", + " if (!window.requirejs) {\n", + " on_load();\n", + " }\n", + " continue;\n", " }\n", - " var element = document.createElement('script');\n", + " const element = document.createElement('script');\n", " element.onload = on_load;\n", " element.onerror = on_error;\n", " element.async = false;\n", @@ -144,13 +195,14 @@ " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", " document.head.appendChild(element);\n", " }\n", - " for (var i = 0; i < js_modules.length; i++) {\n", - " var url = js_modules[i];\n", - " if (skip.indexOf(url) >= 0) {\n", - "\tif (!window.requirejs) {\n", - "\t on_load();\n", - "\t}\n", - "\tcontinue;\n", + " for (let i = 0; i < js_modules.length; i++) {\n", + " const url = js_modules[i];\n", + " const escaped = encodeURI(url)\n", + " if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n", + " if (!window.requirejs) {\n", + " on_load();\n", + " }\n", + " continue;\n", " }\n", " var element = document.createElement('script');\n", " element.onload = on_load;\n", @@ -161,6 +213,27 @@ " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", " document.head.appendChild(element);\n", " }\n", + " for (const name in js_exports) {\n", + " const url = js_exports[name];\n", + " const escaped = encodeURI(url)\n", + " if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n", + " if (!window.requirejs) {\n", + " on_load();\n", + " }\n", + " continue;\n", + " }\n", + " var element = document.createElement('script');\n", + " element.onerror = on_error;\n", + " element.async = false;\n", + " element.type = \"module\";\n", + " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", + " element.textContent = `\n", + " import ${name} from \"${url}\"\n", + " window.${name} = ${name}\n", + " window._bokeh_on_load()\n", + " `\n", + " document.head.appendChild(element);\n", + " }\n", " if (!js_urls.length && !js_modules.length) {\n", " on_load()\n", " }\n", @@ -172,1525 +245,88 @@ " document.body.appendChild(element);\n", " }\n", "\n", - " var js_urls = [];\n", - " var js_modules = [];\n", - " var css_urls = [];\n", - " var inline_js = [\n", - " function(Bokeh) {\n", - " inject_raw_css(\".bk.alert {\\n padding: 0.75rem 1.25rem;\\n border: 1px solid transparent;\\n border-radius: 0.25rem;\\n /* Don't set margin because that will not render correctly! */\\n /* margin-bottom: 1rem; */\\n margin-top: 15px;\\n margin-bottom: 15px;\\n}\\n.bk.alert a {\\n color: rgb(11, 46, 19); /* #002752; */\\n font-weight: 700;\\n text-decoration: rgb(11, 46, 19);\\n text-decoration-color: rgb(11, 46, 19);\\n text-decoration-line: none;\\n text-decoration-style: solid;\\n text-decoration-thickness: auto;\\n }\\n.bk.alert a:hover {\\n color: rgb(11, 46, 19);\\n font-weight: 700;\\n text-decoration: underline;\\n}\\n\\n.bk.alert-primary {\\n color: #004085;\\n background-color: #cce5ff;\\n border-color: #b8daff;\\n}\\n.bk.alert-primary hr {\\n border-top-color: #9fcdff;\\n}\\n\\n.bk.alert-secondary {\\n color: #383d41;\\n background-color: #e2e3e5;\\n border-color: #d6d8db;\\n }\\n.bk.alert-secondary hr {\\n border-top-color: #c8cbcf;\\n}\\n\\n.bk.alert-success {\\n color: #155724;\\n background-color: #d4edda;\\n border-color: #c3e6cb;\\n }\\n\\n.bk.alert-success hr {\\n border-top-color: #b1dfbb;\\n}\\n\\n.bk.alert-info {\\n color: #0c5460;\\n background-color: #d1ecf1;\\n border-color: #bee5eb;\\n }\\n.bk.alert-info hr {\\n border-top-color: #abdde5;\\n}\\n\\n.bk.alert-warning {\\n color: #856404;\\n background-color: #fff3cd;\\n border-color: #ffeeba;\\n }\\n\\n.bk.alert-warning hr {\\n border-top-color: #ffe8a1;\\n}\\n\\n.bk.alert-danger {\\n color: #721c24;\\n background-color: #f8d7da;\\n border-color: #f5c6cb;\\n}\\n.bk.alert-danger hr {\\n border-top-color: #f1b0b7;\\n}\\n\\n.bk.alert-light {\\n color: #818182;\\n background-color: #fefefe;\\n border-color: #fdfdfe;\\n }\\n.bk.alert-light hr {\\n border-top-color: #ececf6;\\n}\\n\\n.bk.alert-dark {\\n color: #1b1e21;\\n background-color: #d6d8d9;\\n border-color: #c6c8ca;\\n }\\n.bk.alert-dark hr {\\n border-top-color: #b9bbbe;\\n}\\n\\n\\n/* adjf\\u00e6l */\\n\\n.bk.alert-primary a {\\n color: #002752;\\n}\\n\\n.bk.alert-secondary a {\\n color: #202326;\\n}\\n\\n\\n.bk.alert-success a {\\n color: #0b2e13;\\n}\\n\\n\\n.bk.alert-info a {\\n color: #062c33;\\n}\\n\\n\\n.bk.alert-warning a {\\n color: #533f03;\\n}\\n\\n\\n.bk.alert-danger a {\\n color: #491217;\\n}\\n\\n.bk.alert-light a {\\n color: #686868;\\n}\\n\\n.bk.alert-dark a {\\n color: #040505;\\n}\");\n", - " },\n", - " function(Bokeh) {\n", - " inject_raw_css(\".bk.card {\\n border: 1px solid rgba(0,0,0,.125);\\n border-radius: 0.25rem;\\n}\\n.bk.accordion {\\n border: 1px solid rgba(0,0,0,.125);\\n}\\n.bk.card-header {\\n align-items: center;\\n background-color: rgba(0, 0, 0, 0.03);\\n border-radius: 0.25rem;\\n display: inline-flex;\\n justify-content: start;\\n width: 100%;\\n}\\n.bk.accordion-header {\\n align-items: center;\\n background-color: rgba(0, 0, 0, 0.03);\\n border-radius: 0;\\n display: flex;\\n justify-content: start;\\n width: 100%;\\n}\\n.bk.card-button {\\n background-color: transparent;\\n margin-left: 0.5em;\\n}\\n.bk.card-header-row {\\n position: relative !important;\\n}\\n.bk.card-title {\\n align-items: center;\\n font-size: 1.4em;\\n font-weight: bold;\\n overflow-wrap: break-word;\\n}\\n.bk.card-header-row > .bk {\\n overflow-wrap: break-word;\\n text-align: center;\\n}\\n\");\n", - " },\n", - " function(Bokeh) {\n", - " inject_raw_css(\".bk.panel-widget-box {\\n min-height: 20px;\\n background-color: #f5f5f5;\\n border: 1px solid #e3e3e3;\\n border-radius: 4px;\\n -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.05);\\n box-shadow: inset 0 1px 1px rgba(0,0,0,.05);\\n overflow-x: hidden;\\n overflow-y: hidden;\\n}\\n\\n.scrollable {\\n overflow: scroll;\\n}\\n\\nprogress {\\n appearance: none;\\n -moz-appearance: none;\\n -webkit-appearance: none;\\n border: none;\\n height: 20px;\\n background-color: whiteSmoke;\\n border-radius: 3px;\\n box-shadow: 0 2px 3px rgba(0,0,0,.5) inset;\\n color: royalblue;\\n position: relative;\\n margin: 0 0 1.5em;\\n}\\n\\nprogress[value]::-webkit-progress-bar {\\n background-color: whiteSmoke;\\n border-radius: 3px;\\n box-shadow: 0 2px 3px rgba(0,0,0,.5) inset;\\n}\\n\\nprogress[value]::-webkit-progress-value {\\n position: relative;\\n background-size: 35px 20px, 100% 100%, 100% 100%;\\n border-radius:3px;\\n}\\n\\nprogress.active:not([value])::before {\\n background-position: 10%;\\n animation-name: stripes;\\n animation-duration: 3s;\\n animation-timing-function: linear;\\n animation-iteration-count: infinite;\\n}\\n\\nprogress[value]::-moz-progress-bar {\\n background-size: 35px 20px, 100% 100%, 100% 100%;\\n border-radius:3px;\\n}\\n\\nprogress:not([value])::-moz-progress-bar {\\n border-radius:3px;\\n background: linear-gradient(-45deg, transparent 33%, rgba(0, 0, 0, 0.2) 33%, rgba(0, 0, 0, 0.2) 66%, transparent 66%) left/2.5em 1.5em;\\n}\\n\\nprogress.active:not([value])::-moz-progress-bar {\\n background-position: 10%;\\n animation-name: stripes;\\n animation-duration: 3s;\\n animation-timing-function: linear;\\n animation-iteration-count: infinite;\\n}\\n\\nprogress.active:not([value])::-webkit-progress-bar {\\n background-position: 10%;\\n animation-name: stripes;\\n animation-duration: 3s;\\n animation-timing-function: linear;\\n animation-iteration-count: infinite;\\n}\\n\\nprogress.primary[value]::-webkit-progress-value { background-color: #007bff; }\\nprogress.primary:not([value])::before { background-color: #007bff; }\\nprogress.primary:not([value])::-webkit-progress-bar { background-color: #007bff; }\\nprogress.primary::-moz-progress-bar { background-color: #007bff; }\\n\\nprogress.secondary[value]::-webkit-progress-value { background-color: #6c757d; }\\nprogress.secondary:not([value])::before { background-color: #6c757d; }\\nprogress.secondary:not([value])::-webkit-progress-bar { background-color: #6c757d; }\\nprogress.secondary::-moz-progress-bar { background-color: #6c757d; }\\n\\nprogress.success[value]::-webkit-progress-value { background-color: #28a745; }\\nprogress.success:not([value])::before { background-color: #28a745; }\\nprogress.success:not([value])::-webkit-progress-bar { background-color: #28a745; }\\nprogress.success::-moz-progress-bar { background-color: #28a745; }\\n\\nprogress.danger[value]::-webkit-progress-value { background-color: #dc3545; }\\nprogress.danger:not([value])::before { background-color: #dc3545; }\\nprogress.danger:not([value])::-webkit-progress-bar { background-color: #dc3545; }\\nprogress.danger::-moz-progress-bar { background-color: #dc3545; }\\n\\nprogress.warning[value]::-webkit-progress-value { background-color: #ffc107; }\\nprogress.warning:not([value])::before { background-color: #ffc107; }\\nprogress.warning:not([value])::-webkit-progress-bar { background-color: #ffc107; }\\nprogress.warning::-moz-progress-bar { background-color: #ffc107; }\\n\\nprogress.info[value]::-webkit-progress-value { background-color: #17a2b8; }\\nprogress.info:not([value])::before { background-color: #17a2b8; }\\nprogress.info:not([value])::-webkit-progress-bar { background-color: #17a2b8; }\\nprogress.info::-moz-progress-bar { background-color: #17a2b8; }\\n\\nprogress.light[value]::-webkit-progress-value { background-color: #f8f9fa; }\\nprogress.light:not([value])::before { background-color: #f8f9fa; }\\nprogress.light:not([value])::-webkit-progress-bar { background-color: #f8f9fa; }\\nprogress.light::-moz-progress-bar { background-color: #f8f9fa; }\\n\\nprogress.dark[value]::-webkit-progress-value { background-color: #343a40; }\\nprogress.dark:not([value])::-webkit-progress-bar { background-color: #343a40; }\\nprogress.dark:not([value])::before { background-color: #343a40; }\\nprogress.dark::-moz-progress-bar { background-color: #343a40; }\\n\\nprogress:not([value])::-webkit-progress-bar {\\n border-radius: 3px;\\n background: linear-gradient(-45deg, transparent 33%, rgba(0, 0, 0, 0.2) 33%, rgba(0, 0, 0, 0.2) 66%, transparent 66%) left/2.5em 1.5em;\\n}\\nprogress:not([value])::before {\\n content:\\\" \\\";\\n position:absolute;\\n height: 20px;\\n top:0;\\n left:0;\\n right:0;\\n bottom:0;\\n border-radius: 3px;\\n background: linear-gradient(-45deg, transparent 33%, rgba(0, 0, 0, 0.2) 33%, rgba(0, 0, 0, 0.2) 66%, transparent 66%) left/2.5em 1.5em;\\n}\\n\\n@keyframes stripes {\\n from {background-position: 0%}\\n to {background-position: 100%}\\n}\\n\\n.bk-root .bk.loader {\\n overflow: hidden;\\n}\\n\\n.bk.loader::after {\\n content: \\\"\\\";\\n border-radius: 50%;\\n -webkit-mask-image: radial-gradient(transparent 50%, rgba(0, 0, 0, 1) 54%);\\n width: 100%;\\n height: 100%;\\n left: 0;\\n top: 0;\\n position: absolute;\\n}\\n\\n.bk-root .bk.loader.dark::after {\\n background: #0f0f0f;\\n}\\n\\n.bk-root .bk.loader.light::after {\\n background: #f0f0f0;\\n}\\n\\n.bk-root .bk.loader.spin::after {\\n animation: spin 2s linear infinite;\\n}\\n\\n.bk-root div.bk.loader.spin.primary-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #007bff 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.secondary-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #6c757d 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.success-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #28a745 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.danger-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #dc3545 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.warning-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #ffc107 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.info-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #17a2b8 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.light-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #f8f9fa 50%);\\n}\\n\\n.bk-root div.bk.loader.dark-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #343a40 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.primary-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #007bff 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.secondary-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #6c757d 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.success-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #28a745 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.danger-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #dc3545 50%)\\n}\\n\\n.bk-root div.bk.loader.spin.warning-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #ffc107 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.info-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #17a2b8 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.light-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #f8f9fa 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.dark-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #343a40 50%);\\n}\\n\\n/* Safari */\\n@-webkit-keyframes spin {\\n 0% { -webkit-transform: rotate(0deg); }\\n 100% { -webkit-transform: rotate(360deg); }\\n}\\n\\n@keyframes spin {\\n 0% { transform: rotate(0deg); }\\n 100% { transform: rotate(360deg); }\\n}\\n\\n.dot div {\\n height: 100%;\\n width: 100%;\\n border: 1px solid #000 !important;\\n background-color: #fff;\\n border-radius: 50%;\\n display: inline-block;\\n}\\n\\n.dot-filled div {\\n height: 100%;\\n width: 100%;\\n border: 1px solid #000 !important;\\n border-radius: 50%;\\n display: inline-block;\\n}\\n\\n.dot-filled.primary div {\\n background-color: #007bff;\\n}\\n\\n.dot-filled.secondary div {\\n background-color: #6c757d;\\n}\\n\\n.dot-filled.success div {\\n background-color: #28a745;\\n}\\n\\n.dot-filled.danger div {\\n background-color: #dc3545;\\n}\\n\\n.dot-filled.warning div {\\n background-color: #ffc107;\\n}\\n\\n.dot-filled.info div {\\n background-color: #17a2b8;\\n}\\n\\n.dot-filled.dark div {\\n background-color: #343a40;\\n}\\n\\n.dot-filled.light div {\\n background-color: #f8f9fa;\\n}\\n\\n/* Slider editor */\\n.slider-edit .bk-input-group .bk-input {\\n border: 0;\\n border-radius: 0;\\n min-height: 0;\\n padding-left: 0;\\n padding-right: 0;\\n font-weight: bold;\\n}\\n\\n.slider-edit .bk-input-group .bk-spin-wrapper {\\n display: contents;\\n}\\n\\n.slider-edit .bk-input-group .bk-spin-wrapper .bk.bk-spin-btn-up {\\n top: -6px;\\n}\\n\\n.slider-edit .bk-input-group .bk-spin-wrapper .bk.bk-spin-btn-down {\\n bottom: 3px;\\n}\\n\\n/* JSON Pane */\\n.bk-root .json-formatter-row .json-formatter-string, .bk-root .json-formatter-row .json-formatter-stringifiable {\\n white-space: pre-wrap;\\n}\\n\");\n", - " },\n", - " function(Bokeh) {\n", - " inject_raw_css(\".codehilite .hll { background-color: #ffffcc }\\n.codehilite { background: #f8f8f8; }\\n.codehilite .c { color: #408080; font-style: italic } /* Comment */\\n.codehilite .err { border: 1px solid #FF0000 } /* Error */\\n.codehilite .k { color: #008000; font-weight: bold } /* Keyword */\\n.codehilite .o { color: #666666 } /* Operator */\\n.codehilite .ch { color: #408080; font-style: italic } /* Comment.Hashbang */\\n.codehilite .cm { color: #408080; font-style: italic } /* Comment.Multiline */\\n.codehilite .cp { color: #BC7A00 } /* Comment.Preproc */\\n.codehilite .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */\\n.codehilite .c1 { color: #408080; font-style: italic } /* Comment.Single */\\n.codehilite .cs { color: #408080; font-style: italic } /* Comment.Special */\\n.codehilite .gd { color: #A00000 } /* Generic.Deleted */\\n.codehilite .ge { font-style: italic } /* Generic.Emph */\\n.codehilite .gr { color: #FF0000 } /* Generic.Error */\\n.codehilite .gh { color: #000080; font-weight: bold } /* Generic.Heading */\\n.codehilite .gi { color: #00A000 } /* Generic.Inserted */\\n.codehilite .go { color: #888888 } /* Generic.Output */\\n.codehilite .gp { color: #000080; font-weight: bold } /* Generic.Prompt */\\n.codehilite .gs { font-weight: bold } /* Generic.Strong */\\n.codehilite .gu { color: #800080; font-weight: bold } /* Generic.Subheading */\\n.codehilite .gt { color: #0044DD } /* Generic.Traceback */\\n.codehilite .kc { color: #008000; font-weight: bold } /* Keyword.Constant */\\n.codehilite .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */\\n.codehilite .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */\\n.codehilite .kp { color: #008000 } /* Keyword.Pseudo */\\n.codehilite .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */\\n.codehilite .kt { color: #B00040 } /* Keyword.Type */\\n.codehilite .m { color: #666666 } /* Literal.Number */\\n.codehilite .s { color: #BA2121 } /* Literal.String */\\n.codehilite .na { color: #7D9029 } /* Name.Attribute */\\n.codehilite .nb { color: #008000 } /* Name.Builtin */\\n.codehilite .nc { color: #0000FF; font-weight: bold } /* Name.Class */\\n.codehilite .no { color: #880000 } /* Name.Constant */\\n.codehilite .nd { color: #AA22FF } /* Name.Decorator */\\n.codehilite .ni { color: #999999; font-weight: bold } /* Name.Entity */\\n.codehilite .ne { color: #D2413A; font-weight: bold } /* Name.Exception */\\n.codehilite .nf { color: #0000FF } /* Name.Function */\\n.codehilite .nl { color: #A0A000 } /* Name.Label */\\n.codehilite .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */\\n.codehilite .nt { color: #008000; font-weight: bold } /* Name.Tag */\\n.codehilite .nv { color: #19177C } /* Name.Variable */\\n.codehilite .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */\\n.codehilite .w { color: #bbbbbb } /* Text.Whitespace */\\n.codehilite .mb { color: #666666 } /* Literal.Number.Bin */\\n.codehilite .mf { color: #666666 } /* Literal.Number.Float */\\n.codehilite .mh { color: #666666 } /* Literal.Number.Hex */\\n.codehilite .mi { color: #666666 } /* Literal.Number.Integer */\\n.codehilite .mo { color: #666666 } /* Literal.Number.Oct */\\n.codehilite .sa { color: #BA2121 } /* Literal.String.Affix */\\n.codehilite .sb { color: #BA2121 } /* Literal.String.Backtick */\\n.codehilite .sc { color: #BA2121 } /* Literal.String.Char */\\n.codehilite .dl { color: #BA2121 } /* Literal.String.Delimiter */\\n.codehilite .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */\\n.codehilite .s2 { color: #BA2121 } /* Literal.String.Double */\\n.codehilite .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */\\n.codehilite .sh { color: #BA2121 } /* Literal.String.Heredoc */\\n.codehilite .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */\\n.codehilite .sx { color: #008000 } /* Literal.String.Other */\\n.codehilite .sr { color: #BB6688 } /* Literal.String.Regex */\\n.codehilite .s1 { color: #BA2121 } /* Literal.String.Single */\\n.codehilite .ss { color: #19177C } /* Literal.String.Symbol */\\n.codehilite .bp { color: #008000 } /* Name.Builtin.Pseudo */\\n.codehilite .fm { color: #0000FF } /* Name.Function.Magic */\\n.codehilite .vc { color: #19177C } /* Name.Variable.Class */\\n.codehilite .vg { color: #19177C } /* Name.Variable.Global */\\n.codehilite .vi { color: #19177C } /* Name.Variable.Instance */\\n.codehilite .vm { color: #19177C } /* Name.Variable.Magic */\\n.codehilite .il { color: #666666 } /* Literal.Number.Integer.Long */\\n\\n.markdown h1 { margin-block-start: 0.34em }\\n.markdown h2 { margin-block-start: 0.42em }\\n.markdown h3 { margin-block-start: 0.5em }\\n.markdown h4 { margin-block-start: 0.67em }\\n.markdown h5 { margin-block-start: 0.84em }\\n.markdown h6 { margin-block-start: 1.17em }\\n.markdown ul { padding-inline-start: 2em }\\n.markdown ol { padding-inline-start: 2em }\\n.markdown strong { font-weight: 600 }\\n.markdown a { color: -webkit-link }\\n.markdown a { color: -moz-hyperlinkText }\\n\");\n", - " },\n", - " function(Bokeh) {\n", - " inject_raw_css(\".json-formatter-row {\\n font-family: monospace;\\n}\\n.json-formatter-row,\\n.json-formatter-row a,\\n.json-formatter-row a:hover {\\n color: black;\\n text-decoration: none;\\n}\\n.json-formatter-row .json-formatter-row {\\n margin-left: 1rem;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty {\\n opacity: 0.5;\\n margin-left: 1rem;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty:after {\\n display: none;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-object:after {\\n content: \\\"No properties\\\";\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-array:after {\\n content: \\\"[]\\\";\\n}\\n.json-formatter-row .json-formatter-string,\\n.json-formatter-row .json-formatter-stringifiable {\\n color: green;\\n white-space: pre;\\n word-wrap: break-word;\\n}\\n.json-formatter-row .json-formatter-number {\\n color: blue;\\n}\\n.json-formatter-row .json-formatter-boolean {\\n color: red;\\n}\\n.json-formatter-row .json-formatter-null {\\n color: #855A00;\\n}\\n.json-formatter-row .json-formatter-undefined {\\n color: #ca0b69;\\n}\\n.json-formatter-row .json-formatter-function {\\n color: #FF20ED;\\n}\\n.json-formatter-row .json-formatter-date {\\n background-color: rgba(0, 0, 0, 0.05);\\n}\\n.json-formatter-row .json-formatter-url {\\n text-decoration: underline;\\n color: blue;\\n cursor: pointer;\\n}\\n.json-formatter-row .json-formatter-bracket {\\n color: blue;\\n}\\n.json-formatter-row .json-formatter-key {\\n color: #00008B;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-row .json-formatter-toggler-link {\\n cursor: pointer;\\n}\\n.json-formatter-row .json-formatter-toggler {\\n line-height: 1.2rem;\\n font-size: 0.7rem;\\n vertical-align: middle;\\n opacity: 0.6;\\n cursor: pointer;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-row .json-formatter-toggler:after {\\n display: inline-block;\\n transition: transform 100ms ease-in;\\n content: \\\"\\\\25BA\\\";\\n}\\n.json-formatter-row > a > .json-formatter-preview-text {\\n opacity: 0;\\n transition: opacity 0.15s ease-in;\\n font-style: italic;\\n}\\n.json-formatter-row:hover > a > .json-formatter-preview-text {\\n opacity: 0.6;\\n}\\n.json-formatter-row.json-formatter-open > .json-formatter-toggler-link .json-formatter-toggler:after {\\n transform: rotate(90deg);\\n}\\n.json-formatter-row.json-formatter-open > .json-formatter-children:after {\\n display: inline-block;\\n}\\n.json-formatter-row.json-formatter-open > a > .json-formatter-preview-text {\\n display: none;\\n}\\n.json-formatter-row.json-formatter-open.json-formatter-empty:after {\\n display: block;\\n}\\n.json-formatter-dark.json-formatter-row {\\n font-family: monospace;\\n}\\n.json-formatter-dark.json-formatter-row,\\n.json-formatter-dark.json-formatter-row a,\\n.json-formatter-dark.json-formatter-row a:hover {\\n color: white;\\n text-decoration: none;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-row {\\n margin-left: 1rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty {\\n opacity: 0.5;\\n margin-left: 1rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty:after {\\n display: none;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-object:after {\\n content: \\\"No properties\\\";\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-array:after {\\n content: \\\"[]\\\";\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-string,\\n.json-formatter-dark.json-formatter-row .json-formatter-stringifiable {\\n color: #31F031;\\n white-space: pre;\\n word-wrap: break-word;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-number {\\n color: #66C2FF;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-boolean {\\n color: #EC4242;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-null {\\n color: #EEC97D;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-undefined {\\n color: #ef8fbe;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-function {\\n color: #FD48CB;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-date {\\n background-color: rgba(255, 255, 255, 0.05);\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-url {\\n text-decoration: underline;\\n color: #027BFF;\\n cursor: pointer;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-bracket {\\n color: #9494FF;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-key {\\n color: #23A0DB;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler-link {\\n cursor: pointer;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler {\\n line-height: 1.2rem;\\n font-size: 0.7rem;\\n vertical-align: middle;\\n opacity: 0.6;\\n cursor: pointer;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler:after {\\n display: inline-block;\\n transition: transform 100ms ease-in;\\n content: \\\"\\\\25BA\\\";\\n}\\n.json-formatter-dark.json-formatter-row > a > .json-formatter-preview-text {\\n opacity: 0;\\n transition: opacity 0.15s ease-in;\\n font-style: italic;\\n}\\n.json-formatter-dark.json-formatter-row:hover > a > .json-formatter-preview-text {\\n opacity: 0.6;\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open > .json-formatter-toggler-link .json-formatter-toggler:after {\\n transform: rotate(90deg);\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open > .json-formatter-children:after {\\n display: inline-block;\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open > a > .json-formatter-preview-text {\\n display: none;\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open.json-formatter-empty:after {\\n display: block;\\n}\\n\");\n", - " },\n", - " function(Bokeh) {\n", - " inject_raw_css(\".bk.pn-loading:before {\\n position: absolute;\\n height: 100%;\\n width: 100%;\\n content: '';\\n z-index: 1000;\\n background-color: rgb(255,255,255,0.50);\\n border-color: lightgray;\\n background-repeat: no-repeat;\\n background-position: center;\\n background-size: auto 50%;\\n border-width: 1px;\\n cursor: progress;\\n}\\n.bk.pn-loading.arcs:hover:before {\\n cursor: progress;\\n}\\n\");\n", - " },\n", - " function(Bokeh) {\n", - " inject_raw_css(\"table.panel-df {\\n margin-left: auto;\\n margin-right: auto;\\n border: none;\\n border-collapse: collapse;\\n border-spacing: 0;\\n color: black;\\n font-size: 12px;\\n table-layout: fixed;\\n width: 100%;\\n}\\n\\n.panel-df tr, .panel-df th, .panel-df td {\\n text-align: right;\\n vertical-align: middle;\\n padding: 0.5em 0.5em !important;\\n line-height: normal;\\n white-space: normal;\\n max-width: none;\\n border: none;\\n}\\n\\n.panel-df tbody {\\n display: table-row-group;\\n vertical-align: middle;\\n border-color: inherit;\\n}\\n\\n.panel-df tbody tr:nth-child(odd) {\\n background: #f5f5f5;\\n}\\n\\n.panel-df thead {\\n border-bottom: 1px solid black;\\n vertical-align: bottom;\\n}\\n\\n.panel-df tr:hover {\\n background: lightblue !important;\\n cursor: pointer;\\n}\\n\");\n", - " },\n", - " function(Bokeh) {\n", - " inject_raw_css(\"\\n .bk.pn-loading.arcs:before {\\n background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n max-height: 400px;\\n }\\n \");\n", - " },\n", - " function(Bokeh) {\n", - " /* BEGIN bokeh.min.js */\n", - " /*!\n", - " * Copyright (c) 2012 - 2021, Anaconda, Inc., and Bokeh Contributors\n", - " * All rights reserved.\n", - " * \n", - " * Redistribution and use in source and binary forms, with or without modification,\n", - " * are permitted provided that the following conditions are met:\n", - " * \n", - " * Redistributions of source code must retain the above copyright notice,\n", - " * this list of conditions and the following disclaimer.\n", - " * \n", - " * Redistributions in binary form must reproduce the above copyright notice,\n", - " * this list of conditions and the following disclaimer in the documentation\n", - " * and/or other materials provided with the distribution.\n", - " * \n", - " * Neither the name of Anaconda nor the names of any contributors\n", - " * may be used to endorse or promote products derived from this software\n", - " * without specific prior written permission.\n", - " * \n", - " * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\n", - " * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n", - " * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE\n", - " * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE\n", - " * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR\n", - " * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF\n", - " * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS\n", - " * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN\n", - " * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)\n", - " * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF\n", - " * THE POSSIBILITY OF SUCH DAMAGE.\n", - " */\n", - " (function(root, factory) {\n", - " const bokeh = factory();\n", - " bokeh.__bokeh__ = true;\n", - " if (typeof root.Bokeh === \"undefined\" || typeof root.Bokeh.__bokeh__ === \"undefined\") {\n", - " root.Bokeh = bokeh;\n", - " }\n", - " const Bokeh = root.Bokeh;\n", - " Bokeh[bokeh.version] = bokeh;\n", - " })(this, function() {\n", - " let define;\n", - " const parent_require = typeof require === \"function\" && require\n", - " return (function(modules, entry, aliases, externals) {\n", - " if (aliases === undefined) aliases = {};\n", - " if (externals === undefined) externals = {};\n", - "\n", - " const cache = {};\n", - "\n", - " const normalize = function(name) {\n", - " if (typeof name === \"number\")\n", - " return name;\n", - "\n", - " if (name === \"bokehjs\")\n", - " return entry;\n", - "\n", - " if (!externals[name]) {\n", - " const prefix = \"@bokehjs/\"\n", - " if (name.slice(0, prefix.length) === prefix)\n", - " name = name.slice(prefix.length)\n", - " }\n", - "\n", - " const alias = aliases[name]\n", - " if (alias != null)\n", - " return alias;\n", - "\n", - " const trailing = name.length > 0 && name[name.lenght-1] === \"/\";\n", - " const index = aliases[name + (trailing ? \"\" : \"/\") + \"index\"];\n", - " if (index != null)\n", - " return index;\n", - "\n", - " return name;\n", - " }\n", - "\n", - " const require = function(name) {\n", - " let mod = cache[name];\n", - " if (!mod) {\n", - " const id = normalize(name);\n", - "\n", - " mod = cache[id];\n", - " if (!mod) {\n", - " if (!modules[id]) {\n", - " if (externals[id] === false || (externals[id] == true && parent_require)) {\n", - " try {\n", - " mod = {exports: externals[id] ? parent_require(id) : {}};\n", - " cache[id] = cache[name] = mod;\n", - " return mod.exports;\n", - " } catch (e) {}\n", - " }\n", - "\n", - " const err = new Error(\"Cannot find module '\" + name + \"'\");\n", - " err.code = 'MODULE_NOT_FOUND';\n", - " throw err;\n", - " }\n", - "\n", - " mod = {exports: {}};\n", - " cache[id] = cache[name] = mod;\n", - "\n", - " function __esModule() {\n", - " Object.defineProperty(mod.exports, \"__esModule\", {value: true});\n", - " }\n", - "\n", - " function __esExport(name, value) {\n", - " Object.defineProperty(mod.exports, name, {\n", - " enumerable: true, get: function () { return value; }\n", - " });\n", - " }\n", - "\n", - " modules[id].call(mod.exports, require, mod, mod.exports, __esModule, __esExport);\n", - " } else {\n", - " cache[name] = mod;\n", - " }\n", - " }\n", - "\n", - " return mod.exports;\n", - " }\n", - " require.resolve = function(name) {\n", - " return \"\"\n", - " }\n", - "\n", - " const main = require(entry);\n", - " main.require = require;\n", - "\n", - " if (typeof Proxy !== \"undefined\") {\n", - " // allow Bokeh.loader[\"@bokehjs/module/name\"] syntax\n", - " main.loader = new Proxy({}, {\n", - " get: function(_obj, module) {\n", - " return require(module);\n", - " }\n", - " });\n", - " }\n", - "\n", - " main.register_plugin = function(plugin_modules, plugin_entry, plugin_aliases, plugin_externals) {\n", - " if (plugin_aliases === undefined) plugin_aliases = {};\n", - " if (plugin_externals === undefined) plugin_externals = {};\n", - "\n", - " for (let name in plugin_modules) {\n", - " modules[name] = plugin_modules[name];\n", - " }\n", - "\n", - " for (let name in plugin_aliases) {\n", - " aliases[name] = 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null==this._interactive_timestamp?-1:Date.now()-this._interactive_timestamp}destructively_move(e){if(e===this)throw new Error(\"Attempted to overwrite a document with itself\");e.clear();const t=(0,g.copy)(this._roots);this.clear();for(const e of t)if(null!=e.document)throw new Error(`Somehow we didn't detach ${e}`);if(0!=this._all_models.size)throw new Error(`this._all_models still had stuff in it: ${this._all_models}`);for(const s of t)e.add_root(s);e.set_title(this._title)}_push_all_models_freeze(){this._all_models_freeze_count+=1}_pop_all_models_freeze(){this._all_models_freeze_count-=1,0===this._all_models_freeze_count&&this._recompute_all_models()}_invalidate_all_models(){l.logger.debug(\"invalidating document models\"),0===this._all_models_freeze_count&&this._recompute_all_models()}_recompute_all_models(){let e=new Set;for(const t of this._roots)e=p.union(e,t.references());const t=new Set(this._all_models.values()),s=p.difference(t,e),o=p.difference(e,t),n=new Map;for(const t of e)n.set(t.id,t);for(const e of s)e.detach_document();for(const e of o)e.attach_document(this);this._all_models=n}roots(){return this._roots}add_root(e,t){if(l.logger.debug(`Adding root: ${e}`),!(0,g.includes)(this._roots,e)){this._push_all_models_freeze();try{this._roots.push(e)}finally{this._pop_all_models_freeze()}this._trigger_on_change(new S.RootAddedEvent(this,e,t))}}remove_root(e,t){const s=this._roots.indexOf(e);if(!(s<0)){this._push_all_models_freeze();try{this._roots.splice(s,1)}finally{this._pop_all_models_freeze()}this._trigger_on_change(new S.RootRemovedEvent(this,e,t))}}title(){return this._title}set_title(e,t){e!==this._title&&(this._title=e,this._trigger_on_change(new S.TitleChangedEvent(this,e,t)))}get_model_by_id(e){var t;return null!==(t=this._all_models.get(e))&&void 0!==t?t:null}get_model_by_name(e){const t=[];for(const s of this._all_models.values())s instanceof M.Model&&s.name==e&&t.push(s);switch(t.length){case 0:return null;case 1:return t[0];default:throw new Error(`Multiple models are named '${e}'`)}}on_message(e,t){const s=this._message_callbacks.get(e);null==s?this._message_callbacks.set(e,new Set([t])):s.add(t)}remove_on_message(e,t){var s;null===(s=this._message_callbacks.get(e))||void 0===s||s.delete(t)}_trigger_on_message(e,t){const s=this._message_callbacks.get(e);if(null!=s)for(const e of s)e(t)}on_change(e,t=!1){this._callbacks.has(e)||this._callbacks.set(e,t)}remove_on_change(e){this._callbacks.delete(e)}_trigger_on_change(e){for(const[t,s]of this._callbacks)if(!s&&e instanceof S.DocumentEventBatch)for(const s of e.events)t(s);else t(e)}_notify_change(e,t,s,o,n){this._trigger_on_change(new S.ModelChangedEvent(this,e,t,s,o,null==n?void 0:n.setter_id,null==n?void 0:n.hint))}static _instantiate_object(e,t,s,o){const n=Object.assign(Object.assign({},s),{id:e,__deferred__:!0});return new(o.get(t))(n)}static _instantiate_references_json(e,t,s){var o;const n=new Map;for(const i of e){const e=i.id,r=i.type,a=null!==(o=i.attributes)&&void 0!==o?o:{};let l=t.get(e);null==l&&(l=E._instantiate_object(e,r,a,s),null!=i.subtype&&l.set_subtype(i.subtype)),n.set(l.id,l)}return n}static _resolve_refs(e,t,s,o){function n(e){var i;if((0,f.is_ref)(e)){const o=null!==(i=t.get(e.id))&&void 0!==i?i:s.get(e.id);if(null!=o)return o;throw new Error(`reference ${JSON.stringify(e)} isn't known (not in Document?)`)}if((0,u.is_NDArray_ref)(e)){const{buffer:t,dtype:s,shape:n}=(0,u.decode_NDArray)(e,o);return(0,m.ndarray)(t,{dtype:s,shape:n})}return(0,b.isArray)(e)?function(e){const t=[];for(const s of e)t.push(n(s));return t}(e):(0,b.isPlainObject)(e)?function(e){const t={};for(const[s,o]of(0,v.entries)(e))t[s]=n(o);return t}(e):e}return n(e)}static _initialize_references_json(e,t,s,o){const n=new Map;for(const{id:i,attributes:r}of e){const e=!t.has(i),a=e?s.get(i):t.get(i),l=E._resolve_refs(r,t,s,o);a.setv(l,{silent:!0}),n.set(i,{instance:a,is_new:e})}const i=[],r=new Set;function a(e){if(e instanceof c.HasProps){if(n.has(e.id)&&!r.has(e.id)){r.add(e.id);const{instance:t,is_new:s}=n.get(e.id),{attributes:o}=t;for(const e of(0,v.values)(o))a(e);s&&(t.finalize(),i.push(t))}}else if((0,b.isArray)(e))for(const t of e)a(t);else if((0,b.isPlainObject)(e))for(const t of(0,v.values)(e))a(t)}for(const e of n.values())a(e.instance);for(const e of i)e.connect_signals()}static _event_for_attribute_change(e,t,s,o,n){if(o.get_model_by_id(e.id).property(t).syncable){const i={kind:\"ModelChanged\",model:{id:e.id},attr:t,new:s};return c.HasProps._json_record_references(o,s,n,{recursive:!0}),i}return null}static _events_to_sync_objects(e,t,s,o){const n=Object.keys(e.attributes),i=Object.keys(t.attributes),r=(0,g.difference)(n,i),a=(0,g.difference)(i,n),_=(0,g.intersection)(n,i),c=[];for(const e of r)l.logger.warn(`Server sent key ${e} but we don't seem to have it in our JSON`);for(const n of a){const i=t.attributes[n];c.push(E._event_for_attribute_change(e,n,i,s,o))}for(const n of _){const i=e.attributes[n],r=t.attributes[n];null==i&&null==r||(null==i||null==r?c.push(E._event_for_attribute_change(e,n,r,s,o)):\"data\"==n||(0,w.is_equal)(i,r)||c.push(E._event_for_attribute_change(e,n,r,s,o)))}return c.filter((e=>null!=e))}static _compute_patch_since_json(e,t){const s=t.to_json(!1);function o(e){const t=new Map;for(const s of e.roots.references)t.set(s.id,s);return t}const n=o(e),i=new Map,r=[];for(const t of e.roots.root_ids)i.set(t,n.get(t)),r.push(t);const a=o(s),l=new Map,_=[];for(const e of s.roots.root_ids)l.set(e,a.get(e)),_.push(e);if(r.sort(),_.sort(),(0,g.difference)(r,_).length>0||(0,g.difference)(_,r).length>0)throw new Error(\"Not implemented: computing add/remove of document roots\");const c=new Set;let h=[];for(const e of t._all_models.keys())if(n.has(e)){const s=E._events_to_sync_objects(n.get(e),a.get(e),t,c);h=h.concat(s)}const f=new d.Serializer({include_defaults:!1});return f.to_serializable([...c]),{references:[...f.definitions],events:h}}to_json_string(e=!0){return JSON.stringify(this.to_json(e))}to_json(e=!0){const t=new d.Serializer({include_defaults:e}),s=t.to_serializable(this._roots);return{version:a.version,title:this._title,roots:{root_ids:s.map((e=>e.id)),references:[...t.definitions]}}}static from_json_string(e){const t=JSON.parse(e);return E.from_json(t)}static from_json(e){l.logger.debug(\"Creating Document from JSON\");const t=e.version,s=-1!==t.indexOf(\"+\")||-1!==t.indexOf(\"-\"),o=`Library versions: JS (${a.version}) / Python (${t})`;s||a.version.replace(/-(dev|rc)\\./,\"$1\")==t?l.logger.debug(o):(l.logger.warn(\"JS/Python version mismatch\"),l.logger.warn(o));const n=new r.ModelResolver;null!=e.defs&&(0,j.resolve_defs)(e.defs,n);const i=e.roots,_=i.root_ids,c=i.references,d=E._instantiate_references_json(c,new Map,n);E._initialize_references_json(c,new Map,d,new Map);const h=new E({resolver:n});for(const e of _){const t=d.get(e);null!=t&&h.add_root(t)}return h.set_title(e.title),h}replace_with_json(e){E.from_json(e).destructively_move(this)}create_json_patch_string(e){return JSON.stringify(this.create_json_patch(e))}create_json_patch(e){for(const t of e)if(t.document!=this)throw new Error(\"Cannot create a patch using events from a different document\");const t=new d.Serializer,s=t.to_serializable(e);for(const e of this._all_models.values())t.remove_def(e);return{events:s,references:[...t.definitions]}}apply_json_patch(e,t=new Map,s){const o=e.references,n=e.events,i=E._instantiate_references_json(o,this._all_models,this._resolver);t instanceof Map||(t=new Map(t));for(const e of n)switch(e.kind){case\"RootAdded\":case\"RootRemoved\":case\"ModelChanged\":{const t=e.model.id,s=this._all_models.get(t);if(null!=s)i.set(t,s);else if(!i.has(t))throw l.logger.warn(`Got an event for unknown model ${e.model}\"`),new Error(\"event model wasn't known\");break}}const r=new Map(this._all_models),a=new Map;for(const[e,t]of i)r.has(e)||a.set(e,t);E._initialize_references_json(o,r,a,t);for(const e of n)switch(e.kind){case\"MessageSent\":{const{msg_type:s,msg_data:o}=e;let n;if(void 0===o){if(1!=t.size)throw new Error(\"expected exactly one buffer\");{const[[,e]]=t;n=e}}else n=E._resolve_refs(o,r,a,t);this._trigger_on_message(s,n);break}case\"ModelChanged\":{const o=e.model.id,n=this._all_models.get(o);if(null==n)throw new Error(`Cannot apply patch to ${o} which is not in the document`);const i=e.attr,l=E._resolve_refs(e.new,r,a,t);n.setv({[i]:l},{setter_id:s});break}case\"ColumnDataChanged\":{const o=e.column_source.id,n=this._all_models.get(o);if(null==n)throw new Error(`Cannot stream to ${o} which is not in the document`);const i=E._resolve_refs(e.new,new Map,new Map,t);if(null!=e.cols)for(const e in n.data)e in i||(i[e]=n.data[e]);n.setv({data:i},{setter_id:s,check_eq:!1});break}case\"ColumnsStreamed\":{const t=e.column_source.id,o=this._all_models.get(t);if(null==o)throw new 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extends((0,c.Signalable)()){constructor(e={}){var t,s;super(),this._subtype=void 0,this.document=null,this.destroyed=new c.Signal0(this,\"destroyed\"),this.change=new c.Signal0(this,\"change\"),this.transformchange=new c.Signal0(this,\"transformchange\"),this.exprchange=new c.Signal0(this,\"exprchange\"),this.properties={},this._watchers=new WeakMap,this._pending=!1,this._changing=!1;const n=e instanceof Map?e.get.bind(e):t=>e[t];this.id=null!==(t=n(\"id\"))&&void 0!==t?t:(0,u.uniqueId)();for(const[e,{type:t,default_value:s,options:r}]of(0,l.entries)(this._props)){let i;t instanceof _.PropertyAlias?Object.defineProperty(this.properties,e,{get:()=>this.properties[t.attr],configurable:!1,enumerable:!1}):(i=t instanceof h.Kind?new _.PrimitiveProperty(this,e,t,s,n(e),r):new t(this,e,h.Any,s,n(e),r),this.properties[e]=i)}null!==(s=n(\"__deferred__\"))&&void 0!==s&&s||(this.finalize(),this.connect_signals())}get is_syncable(){return!0}set type(e){console.warn(\"prototype.type = 'ModelName' 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r=Object.assign({},this.prototype._props);r[t]=Object.assign(Object.assign({},n),{default_value:e}),this.prototype._props=r}}toString(){return`${this.type}(${this.id})`}property(e){const t=this.properties[e];if(null!=t)return t;throw new Error(`unknown property ${this.type}.${e}`)}get attributes(){const e={};for(const t of this)e[t.attr]=t.get_value();return e}[m.clone](e){const t=new Map;for(const s of this)s.dirty&&t.set(s.attr,e.clone(s.get_value()));return new this.constructor(t)}[y.equals](e,t){for(const s of this){const n=e.property(s.attr);if(!t.eq(s.get_value(),n.get_value()))return!1}return!0}[v.pretty](e){const t=e.token,s=[];for(const n of this)if(n.dirty){const r=n.get_value();s.push(`${n.attr}${t(\":\")} ${e.to_string(r)}`)}return`${this.constructor.__qualified__}${t(\"(\")}${t(\"{\")}${s.join(`${t(\",\")} `)}${t(\"}\")}${t(\")\")}`}[d.serialize](e){const t=this.ref();e.add_ref(this,t);const s=this.struct();for(const t of 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n)e.change.emit();if(!r){if(!t.no_change)for(;this._pending;)this._pending=!1,this.change.emit();this._pending=!1,this._changing=!1}}setv(e,t={}){const s=(0,l.entries)(e);if(0==s.length)return;if(!0===t.silent){this._watchers=new WeakMap;for(const[e,t]of s)this.properties[e].set_value(t);return}const n=new Map,r=new Map;for(const[e,t]of s){const s=this.properties[e];n.set(s,t),r.set(s,s.get_value())}this._setv(n,t);const{document:i}=this;if(null!=i){const e=[];for(const[t,s]of r)e.push([t,s,t.get_value()]);for(const[,t,s]of e)if(this._needs_invalidate(t,s)){i._invalidate_all_models();break}this._push_changes(e,t)}}getv(e){return this.property(e).get_value()}ref(){return{id:this.id}}struct(){const e={type:this.type,id:this.id,attributes:{}};return null!=this._subtype&&(e.subtype=this._subtype),e}set_subtype(e){this._subtype=e}*[Symbol.iterator](){yield*(0,l.values)(this.properties)}*syncable_properties(){for(const e of this)e.syncable&&(yield e)}serializable_attributes(){const 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w._value_record_references(this,e,{recursive:!0}),e}_doc_attached(){}_doc_detached(){}attach_document(e){if(null!=this.document&&this.document!=e)throw new Error(\"models must be owned by only a single document\");this.document=e,this._doc_attached()}detach_document(){this._doc_detached(),this.document=null}_needs_invalidate(e,t){const s=new Set;w._value_record_references(t,s,{recursive:!1});const n=new Set;w._value_record_references(e,n,{recursive:!1});for(const e of s)if(!n.has(e))return!0;for(const e of n)if(!s.has(e))return!0;return!1}_push_changes(e,t={}){if(!this.is_syncable)return;const{document:s}=this;if(null==s)return;const{setter_id:n}=t,r=[];for(const[t,i,o]of e)t.syncable&&r.push(new g.ModelChangedEvent(s,this,t.attr,i,o,n));if(0!=r.length){let e;1==r.length?[e]=r:e=new g.DocumentEventBatch(s,r,n),s._trigger_on_change(e)}}on_change(e,t){for(const s of(0,f.isArray)(e)?e:[e])this.connect(s.change,t)}}s.HasProps=w,(o=w).prototype._props={},o.prototype._mixins=[]},\n", - " function _(n,t,e,l,s){l();const i=n(16),o=n(9);class c{constructor(n,t){this.sender=n,this.name=t}connect(n,t=null){u.has(this.sender)||u.set(this.sender,[]);const e=u.get(this.sender);if(null!=g(e,this,n,t))return!1;const l=null!=t?t:n;a.has(l)||a.set(l,[]);const s=a.get(l),i={signal:this,slot:n,context:t};return e.push(i),s.push(i),!0}disconnect(n,t=null){const e=u.get(this.sender);if(null==e||0===e.length)return!1;const l=g(e,this,n,t);if(null==l)return!1;const s=null!=t?t:n,i=a.get(s);return l.signal=null,d(e),d(i),!0}emit(n){var t;const e=null!==(t=u.get(this.sender))&&void 0!==t?t:[];for(const{signal:t,slot:l,context:s}of e)t===this&&l.call(s,n,this.sender)}}e.Signal=c,c.__name__=\"Signal\";class r extends c{emit(){super.emit(void 0)}}e.Signal0=r,r.__name__=\"Signal0\",function(n){function t(n,t){const e=u.get(n);if(null==e||0===e.length)return;const l=a.get(t);if(null!=l&&0!==l.length){for(const t of 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e in l.named_colors}},\n", - " function _(r,t,n,a,o){a(),n.GeneratorFunction=Object.getPrototypeOf((function*(){})).constructor,n.ColorArray=Uint32Array,n.RGBAArray=Uint8ClampedArray,n.infer_type=function(r,t){return r instanceof Float64Array||r instanceof Array||t instanceof Float64Array||t instanceof Array?Float64Array:Float32Array},n.ScreenArray=Float32Array,n.to_screen=function(r){return r instanceof Float32Array?r:Float32Array.from(r)},o(\"Indices\",r(25).BitSet)},\n", - " function _(t,s,r,e,i){var n;e();const o=t(26),a=t(11);class _{constructor(t,s=0){this.size=t,this[n]=\"BitSet\",this._count=null,this._nwords=Math.ceil(t/32),0==s||1==s?(this._array=new Uint32Array(this._nwords),1==s&&this._array.fill(4294967295)):((0,a.assert)(s.length==this._nwords,\"Initializer size mismatch\"),this._array=s)}clone(){return new _(this.size,new 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l.Renderer{constructor(t){super(t)}}i.Annotation=a,o=a,a.__name__=\"Annotation\",o.override({level:\"annotation\"})},\n", - " function _(e,i,t,n,s){n();const r=e(1);var o,a;const _=e(42),l=(0,r.__importStar)(e(45)),d=e(20),h=e(53),u=e(54);class c extends h.Model{constructor(e){super(e)}}t.RendererGroup=c,o=c,c.__name__=\"RendererGroup\",o.define((({Boolean:e})=>({visible:[e,!0]})));class p extends _.View{get coordinates(){const{_coordinates:e}=this;return null!=e?e:this._coordinates=this._initialize_coordinates()}initialize(){super.initialize(),this.visuals=new l.Visuals(this),this.needs_webgl_blit=!1}connect_signals(){super.connect_signals();const{x_range_name:e,y_range_name:i}=this.model.properties;this.on_change([e,i],(()=>this._initialize_coordinates()));const{group:t}=this.model;null!=t&&this.on_change(t.properties.visible,(()=>{this.model.visible=t.visible}))}_initialize_coordinates(){const{coordinates:e}=this.model,{frame:i}=this.plot_view;if(null!=e)return 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h.Model{constructor(e){super(e)}}t.Renderer=g,a=g,g.__name__=\"Renderer\",a.define((({Boolean:e,String:i,Ref:t,Nullable:n})=>({group:[n(t(c)),null],level:[d.RenderLevel,\"image\"],visible:[e,!0],x_range_name:[i,\"default\"],y_range_name:[i,\"default\"],coordinates:[n(t(u.CoordinateMapping)),null]})))},\n", - " function _(t,e,s,i,n){i();const o=t(1),h=t(15),r=t(43),l=t(8),_=(0,o.__importDefault)(t(44));class d{constructor(t){this.removed=new h.Signal0(this,\"removed\"),this._ready=Promise.resolve(void 0),this._slots=new WeakMap,this._idle_notified=!1;const{model:e,parent:s}=t;this.model=e,this.parent=s,this.root=null==s?this:s.root,this.removed.emit()}get ready(){return this._ready}connect(t,e){let s=this._slots.get(e);return null==s&&(s=(t,s)=>{const i=Promise.resolve(e.call(this,t,s));this._ready=this._ready.then((()=>i))},this._slots.set(e,s)),t.connect(s,this)}disconnect(t,e){return t.disconnect(e,this)}initialize(){this._has_finished=!1,this.is_root&&(this._stylesheet=r.stylesheet);for(const t of this.styles())this.stylesheet.append(t)}async lazy_initialize(){}remove(){this.disconnect_signals(),this.removed.emit()}toString(){return`${this.model.type}View(${this.model.id})`}serializable_state(){return{type:this.model.type}}get is_root(){return null==this.parent}has_finished(){return this._has_finished}get is_idle(){return this.has_finished()}connect_signals(){}disconnect_signals(){h.Signal.disconnect_receiver(this)}on_change(t,e){for(const s of(0,l.isArray)(t)?t:[t])this.connect(s.change,e)}cursor(t,e){return null}get stylesheet(){return this.is_root?this._stylesheet:this.root.stylesheet}styles(){return[_.default]}notify_finished(){this.is_root?!this._idle_notified&&this.has_finished()&&null!=this.model.document&&(this._idle_notified=!0,this.model.document.notify_idle(this.model)):this.root.notify_finished()}}s.View=d,d.__name__=\"View\"},\n", - " function _(t,e,n,i,o){i();const s=t(8),l=t(13),r=t=>(e={},...n)=>{const i=document.createElement(t);i.classList.add(\"bk\"),(0,s.isPlainObject)(e)||(n=[e,...n],e={});for(let[t,n]of(0,l.entries)(e))if(null!=n&&(!(0,s.isBoolean)(n)||n))if(\"class\"===t&&((0,s.isString)(n)&&(n=n.split(/\\s+/)),(0,s.isArray)(n)))for(const t of n)null!=t&&i.classList.add(t);else if(\"style\"===t&&(0,s.isPlainObject)(n))for(const[t,e]of(0,l.entries)(n))i.style[t]=e;else if(\"data\"===t&&(0,s.isPlainObject)(n))for(const[t,e]of(0,l.entries)(n))i.dataset[t]=e;else i.setAttribute(t,n);function o(t){if((0,s.isString)(t))i.appendChild(document.createTextNode(t));else if(t instanceof Node)i.appendChild(t);else if(t instanceof NodeList||t instanceof HTMLCollection)for(const e of t)i.appendChild(e);else if(null!=t&&!1!==t)throw new Error(`expected a DOM element, string, false or null, got ${JSON.stringify(t)}`)}for(const t of n)if((0,s.isArray)(t))for(const e of t)o(e);else o(t);return i};function a(t){const e=t.parentNode;null!=e&&e.removeChild(t)}function c(t,...e){const n=t.firstChild;for(const i of e)t.insertBefore(i,n)}function d(t,e){var n,i,o;const s=Element.prototype;return(null!==(o=null!==(i=null!==(n=s.matches)&&void 0!==n?n:s.webkitMatchesSelector)&&void 0!==i?i:s.mozMatchesSelector)&&void 0!==o?o:s.msMatchesSelector).call(t,e)}function h(t){return parseFloat(t)||0}function f(t){const e=getComputedStyle(t);return{border:{top:h(e.borderTopWidth),bottom:h(e.borderBottomWidth),left:h(e.borderLeftWidth),right:h(e.borderRightWidth)},margin:{top:h(e.marginTop),bottom:h(e.marginBottom),left:h(e.marginLeft),right:h(e.marginRight)},padding:{top:h(e.paddingTop),bottom:h(e.paddingBottom),left:h(e.paddingLeft),right:h(e.paddingRight)}}}function u(t){const e=t.getBoundingClientRect();return{width:Math.ceil(e.width),height:Math.ceil(e.height)}}n.createElement=function(t,e,...n){return r(t)(e,...n)},n.div=r(\"div\"),n.span=r(\"span\"),n.canvas=r(\"canvas\"),n.link=r(\"link\"),n.style=r(\"style\"),n.a=r(\"a\"),n.p=r(\"p\"),n.i=r(\"i\"),n.pre=r(\"pre\"),n.button=r(\"button\"),n.label=r(\"label\"),n.input=r(\"input\"),n.select=r(\"select\"),n.option=r(\"option\"),n.optgroup=r(\"optgroup\"),n.textarea=r(\"textarea\"),n.createSVGElement=function(t,e,...n){const i=document.createElementNS(\"http://www.w3.org/2000/svg\",t);for(const[t,n]of(0,l.entries)(null!=e?e:{}))null==n||(0,s.isBoolean)(n)&&!n||i.setAttribute(t,n);function o(t){if((0,s.isString)(t))i.appendChild(document.createTextNode(t));else if(t instanceof Node)i.appendChild(t);else if(t instanceof NodeList||t instanceof HTMLCollection)for(const e of t)i.appendChild(e);else if(null!=t&&!1!==t)throw new Error(`expected a DOM element, string, false or null, got ${JSON.stringify(t)}`)}for(const t of n)if((0,s.isArray)(t))for(const e of t)o(e);else o(t);return i},n.nbsp=function(){return document.createTextNode(\"\\xa0\")},n.append=function(t,...e){for(const n of e)t.appendChild(n)},n.remove=a,n.removeElement=a,n.replaceWith=function(t,e){const n=t.parentNode;null!=n&&n.replaceChild(e,t)},n.prepend=c,n.empty=function(t,e=!1){let n;for(;n=t.firstChild;)t.removeChild(n);if(e&&t instanceof Element)for(const e of t.attributes)t.removeAttributeNode(e)},n.display=function(t){t.style.display=\"\"},n.undisplay=function(t){t.style.display=\"none\"},n.show=function(t){t.style.visibility=\"\"},n.hide=function(t){t.style.visibility=\"hidden\"},n.offset=function(t){const e=t.getBoundingClientRect();return{top:e.top+window.pageYOffset-document.documentElement.clientTop,left:e.left+window.pageXOffset-document.documentElement.clientLeft}},n.matches=d,n.parent=function(t,e){let n=t;for(;n=n.parentElement;)if(d(n,e))return n;return null},n.extents=f,n.size=u,n.scroll_size=function(t){return{width:Math.ceil(t.scrollWidth),height:Math.ceil(t.scrollHeight)}},n.outer_size=function(t){const{margin:{left:e,right:n,top:i,bottom:o}}=f(t),{width:s,height:l}=u(t);return{width:Math.ceil(s+e+n),height:Math.ceil(l+i+o)}},n.content_size=function(t){const{left:e,top:n}=t.getBoundingClientRect(),{padding:i}=f(t);let o=0,s=0;for(const l of t.children){const t=l.getBoundingClientRect();o=Math.max(o,Math.ceil(t.left-e-i.left+t.width)),s=Math.max(s,Math.ceil(t.top-n-i.top+t.height))}return{width:o,height:s}},n.position=function(t,e,n){const{style:i}=t;if(i.left=`${e.x}px`,i.top=`${e.y}px`,i.width=`${e.width}px`,i.height=`${e.height}px`,null==n)i.margin=\"\";else{const{top:t,right:e,bottom:o,left:s}=n;i.margin=`${t}px ${e}px ${o}px ${s}px`}},n.children=function(t){return Array.from(t.children)};class p{constructor(t){this.el=t,this.classList=t.classList}get values(){const t=[];for(let e=0;e{document.addEventListener(\"DOMContentLoaded\",(()=>t()),{once:!0})}))}},\n", - " function _(o,i,t,e,r){e(),t.root=\"bk-root\",t.default=\".bk-root{position:relative;width:auto;height:auto;box-sizing:border-box;font-family:Helvetica, Arial, sans-serif;font-size:13px;}.bk-root .bk,.bk-root .bk:before,.bk-root .bk:after{box-sizing:inherit;margin:0;border:0;padding:0;background-image:none;font-family:inherit;font-size:100%;line-height:1.42857143;}.bk-root pre.bk{font-family:Courier, monospace;}\"},\n", - " function _(e,t,r,a,c){a();const n=e(1),l=e(46);c(\"Line\",l.Line),c(\"LineScalar\",l.LineScalar),c(\"LineVector\",l.LineVector);const i=e(49);c(\"Fill\",i.Fill),c(\"FillScalar\",i.FillScalar),c(\"FillVector\",i.FillVector);const s=e(50);c(\"Text\",s.Text),c(\"TextScalar\",s.TextScalar),c(\"TextVector\",s.TextVector);const o=e(51);c(\"Hatch\",o.Hatch),c(\"HatchScalar\",o.HatchScalar),c(\"HatchVector\",o.HatchVector);const u=(0,n.__importStar)(e(48)),V=e(47);c(\"VisualProperties\",V.VisualProperties),c(\"VisualUniforms\",V.VisualUniforms);class h{constructor(e){this._visuals=[];for(const[t,r]of e.model._mixins){const a=(()=>{switch(r){case u.Line:return new l.Line(e,t);case u.LineScalar:return new l.LineScalar(e,t);case u.LineVector:return new l.LineVector(e,t);case u.Fill:return new i.Fill(e,t);case u.FillScalar:return new i.FillScalar(e,t);case u.FillVector:return new i.FillVector(e,t);case u.Text:return new s.Text(e,t);case u.TextScalar:return new s.TextScalar(e,t);case u.TextVector:return new s.TextVector(e,t);case u.Hatch:return new o.Hatch(e,t);case u.HatchScalar:return new o.HatchScalar(e,t);case u.HatchVector:return new o.HatchVector(e,t);default:throw new Error(\"unknown visual\")}})();a instanceof V.VisualProperties&&a.update(),this._visuals.push(a),Object.defineProperty(this,t+a.type,{get:()=>a,configurable:!1,enumerable:!0})}}*[Symbol.iterator](){yield*this._visuals}}r.Visuals=h,h.__name__=\"Visuals\"},\n", - " function _(e,t,i,l,s){l();const a=e(1),n=e(47),h=(0,a.__importStar)(e(48)),o=e(22),_=e(8);function r(e){if((0,_.isArray)(e))return e;switch(e){case\"solid\":return[];case\"dashed\":return[6];case\"dotted\":return[2,4];case\"dotdash\":return[2,4,6,4];case\"dashdot\":return[6,4,2,4];default:return e.split(\" \").map(Number).filter(_.isInteger)}}i.resolve_line_dash=r;class u extends n.VisualProperties{get doit(){const e=this.line_color.get_value(),t=this.line_alpha.get_value(),i=this.line_width.get_value();return!(null==e||0==t||0==i)}apply(e){const{doit:t}=this;return t&&(this.set_value(e),e.stroke()),t}values(){return{color:this.line_color.get_value(),alpha:this.line_alpha.get_value(),width:this.line_width.get_value(),join:this.line_join.get_value(),cap:this.line_cap.get_value(),dash:this.line_dash.get_value(),offset:this.line_dash_offset.get_value()}}set_value(e){const t=this.line_color.get_value(),i=this.line_alpha.get_value();e.strokeStyle=(0,o.color2css)(t,i),e.lineWidth=this.line_width.get_value(),e.lineJoin=this.line_join.get_value(),e.lineCap=this.line_cap.get_value(),e.lineDash=r(this.line_dash.get_value()),e.lineDashOffset=this.line_dash_offset.get_value()}}i.Line=u,u.__name__=\"Line\";class c extends n.VisualUniforms{get doit(){const e=this.line_color.value,t=this.line_alpha.value,i=this.line_width.value;return!(0==e||0==t||0==i)}apply(e){const{doit:t}=this;return t&&(this.set_value(e),e.stroke()),t}values(){return{color:this.line_color.value,alpha:this.line_alpha.value,width:this.line_width.value,join:this.line_join.value,cap:this.line_cap.value,dash:this.line_dash.value,offset:this.line_dash_offset.value}}set_value(e){const t=this.line_color.value,i=this.line_alpha.value;e.strokeStyle=(0,o.color2css)(t,i),e.lineWidth=this.line_width.value,e.lineJoin=this.line_join.value,e.lineCap=this.line_cap.value,e.lineDash=r(this.line_dash.value),e.lineDashOffset=this.line_dash_offset.value}}i.LineScalar=c,c.__name__=\"LineScalar\";class d extends n.VisualUniforms{get doit(){const{line_color:e}=this;if(e.is_Scalar()&&0==e.value)return!1;const{line_alpha:t}=this;if(t.is_Scalar()&&0==t.value)return!1;const{line_width:i}=this;return!i.is_Scalar()||0!=i.value}apply(e,t){const{doit:i}=this;return i&&(this.set_vectorize(e,t),e.stroke()),i}values(e){return{color:this.line_color.get(e),alpha:this.line_alpha.get(e),width:this.line_width.get(e),join:this.line_join.get(e),cap:this.line_cap.get(e),dash:this.line_dash.get(e),offset:this.line_dash_offset.get(e)}}set_vectorize(e,t){const i=this.line_color.get(t),l=this.line_alpha.get(t),s=this.line_width.get(t),a=this.line_join.get(t),n=this.line_cap.get(t),h=this.line_dash.get(t),_=this.line_dash_offset.get(t);e.strokeStyle=(0,o.color2css)(i,l),e.lineWidth=s,e.lineJoin=a,e.lineCap=n,e.lineDash=r(h),e.lineDashOffset=_}}i.LineVector=d,d.__name__=\"LineVector\",u.prototype.type=\"line\",u.prototype.attrs=Object.keys(h.Line),c.prototype.type=\"line\",c.prototype.attrs=Object.keys(h.LineScalar),d.prototype.type=\"line\",d.prototype.attrs=Object.keys(h.LineVector)},\n", - " function _(t,s,o,i,r){i();class e{constructor(t,s=\"\"){this.obj=t,this.prefix=s;const o=this;this._props=[];for(const i of this.attrs){const r=t.model.properties[s+i];r.change.connect((()=>this.update())),o[i]=r,this._props.push(r)}}*[Symbol.iterator](){yield*this._props}update(){}}o.VisualProperties=e,e.__name__=\"VisualProperties\";class p{constructor(t,s=\"\"){this.obj=t,this.prefix=s;for(const o of this.attrs)Object.defineProperty(this,o,{get:()=>t[s+o]})}*[Symbol.iterator](){for(const t of this.attrs)yield this.obj.model.properties[this.prefix+t]}update(){}}o.VisualUniforms=p,p.__name__=\"VisualUniforms\"},\n", - " function _(e,l,t,a,c){a();const r=e(1),o=(0,r.__importStar)(e(18)),n=e(20),i=(0,r.__importStar)(e(21)),_=e(13);t.Line={line_color:[i.Nullable(i.Color),\"black\"],line_alpha:[i.Alpha,1],line_width:[i.Number,1],line_join:[n.LineJoin,\"bevel\"],line_cap:[n.LineCap,\"butt\"],line_dash:[i.Or(n.LineDash,i.Array(i.Number)),[]],line_dash_offset:[i.Number,0]},t.Fill={fill_color:[i.Nullable(i.Color),\"gray\"],fill_alpha:[i.Alpha,1]},t.Hatch={hatch_color:[i.Nullable(i.Color),\"black\"],hatch_alpha:[i.Alpha,1],hatch_scale:[i.Number,12],hatch_pattern:[i.Nullable(i.Or(n.HatchPatternType,i.String)),null],hatch_weight:[i.Number,1],hatch_extra:[i.Dict(i.AnyRef()),{}]},t.Text={text_color:[i.Nullable(i.Color),\"#444444\"],text_alpha:[i.Alpha,1],text_font:[o.Font,\"helvetica\"],text_font_size:[i.FontSize,\"16px\"],text_font_style:[n.FontStyle,\"normal\"],text_align:[n.TextAlign,\"left\"],text_baseline:[n.TextBaseline,\"bottom\"],text_line_height:[i.Number,1.2]},t.LineScalar={line_color:[o.ColorScalar,\"black\"],line_alpha:[o.NumberScalar,1],line_width:[o.NumberScalar,1],line_join:[o.LineJoinScalar,\"bevel\"],line_cap:[o.LineCapScalar,\"butt\"],line_dash:[o.LineDashScalar,[]],line_dash_offset:[o.NumberScalar,0]},t.FillScalar={fill_color:[o.ColorScalar,\"gray\"],fill_alpha:[o.NumberScalar,1]},t.HatchScalar={hatch_color:[o.ColorScalar,\"black\"],hatch_alpha:[o.NumberScalar,1],hatch_scale:[o.NumberScalar,12],hatch_pattern:[o.NullStringScalar,null],hatch_weight:[o.NumberScalar,1],hatch_extra:[o.AnyScalar,{}]},t.TextScalar={text_color:[o.ColorScalar,\"#444444\"],text_alpha:[o.NumberScalar,1],text_font:[o.FontScalar,\"helvetica\"],text_font_size:[o.FontSizeScalar,\"16px\"],text_font_style:[o.FontStyleScalar,\"normal\"],text_align:[o.TextAlignScalar,\"left\"],text_baseline:[o.TextBaselineScalar,\"bottom\"],text_line_height:[o.NumberScalar,1.2]},t.LineVector={line_color:[o.ColorSpec,\"black\"],line_alpha:[o.NumberSpec,1],line_width:[o.NumberSpec,1],line_join:[o.LineJoinSpec,\"bevel\"],line_cap:[o.LineCapSpec,\"butt\"],line_dash:[o.LineDashSpec,[]],line_dash_offset:[o.NumberSpec,0]},t.FillVector={fill_color:[o.ColorSpec,\"gray\"],fill_alpha:[o.NumberSpec,1]},t.HatchVector={hatch_color:[o.ColorSpec,\"black\"],hatch_alpha:[o.NumberSpec,1],hatch_scale:[o.NumberSpec,12],hatch_pattern:[o.NullStringSpec,null],hatch_weight:[o.NumberSpec,1],hatch_extra:[o.AnyScalar,{}]},t.TextVector={text_color:[o.ColorSpec,\"#444444\"],text_alpha:[o.NumberSpec,1],text_font:[o.FontSpec,\"helvetica\"],text_font_size:[o.FontSizeSpec,\"16px\"],text_font_style:[o.FontStyleSpec,\"normal\"],text_align:[o.TextAlignSpec,\"left\"],text_baseline:[o.TextBaselineSpec,\"bottom\"],text_line_height:[o.NumberSpec,1.2]},t.attrs_of=function(e,l,t,a=!1){const c={};for(const r of(0,_.keys)(t)){const t=`${l}${r}`,o=e[t];c[a?t:r]=o}return c}},\n", - " function _(l,t,e,i,s){i();const a=l(1),o=l(47),r=(0,a.__importStar)(l(48)),_=l(22);class c extends o.VisualProperties{get doit(){const l=this.fill_color.get_value(),t=this.fill_alpha.get_value();return!(null==l||0==t)}apply(l,t){const{doit:e}=this;return e&&(this.set_value(l),l.fill(t)),e}values(){return{color:this.fill_color.get_value(),alpha:this.fill_alpha.get_value()}}set_value(l){const t=this.fill_color.get_value(),e=this.fill_alpha.get_value();l.fillStyle=(0,_.color2css)(t,e)}}e.Fill=c,c.__name__=\"Fill\";class h extends o.VisualUniforms{get doit(){const l=this.fill_color.value,t=this.fill_alpha.value;return!(0==l||0==t)}apply(l,t){const{doit:e}=this;return e&&(this.set_value(l),l.fill(t)),e}values(){return{color:this.fill_color.value,alpha:this.fill_alpha.value}}set_value(l){const t=this.fill_color.value,e=this.fill_alpha.value;l.fillStyle=(0,_.color2css)(t,e)}}e.FillScalar=h,h.__name__=\"FillScalar\";class u extends o.VisualUniforms{get doit(){const{fill_color:l}=this;if(l.is_Scalar()&&0==l.value)return!1;const{fill_alpha:t}=this;return!t.is_Scalar()||0!=t.value}apply(l,t,e){const{doit:i}=this;return i&&(this.set_vectorize(l,t),l.fill(e)),i}values(l){return{color:this.fill_color.get(l),alpha:this.fill_alpha.get(l)}}set_vectorize(l,t){const e=this.fill_color.get(t),i=this.fill_alpha.get(t);l.fillStyle=(0,_.color2css)(e,i)}}e.FillVector=u,u.__name__=\"FillVector\",c.prototype.type=\"fill\",c.prototype.attrs=Object.keys(r.Fill),h.prototype.type=\"fill\",h.prototype.attrs=Object.keys(r.FillScalar),u.prototype.type=\"fill\",u.prototype.attrs=Object.keys(r.FillVector)},\n", - " function _(t,e,l,s,_){s();const i=t(1),a=t(47),o=(0,i.__importStar)(t(48)),n=t(22);class h extends a.VisualProperties{get doit(){const t=this.text_color.get_value(),e=this.text_alpha.get_value();return!(null==t||0==e)}values(){return{color:this.text_color.get_value(),alpha:this.text_alpha.get_value(),font:this.text_font.get_value(),font_size:this.text_font_size.get_value(),font_style:this.text_font_style.get_value(),align:this.text_align.get_value(),baseline:this.text_baseline.get_value(),line_height:this.text_line_height.get_value()}}set_value(t){const e=this.text_color.get_value(),l=this.text_alpha.get_value();t.fillStyle=(0,n.color2css)(e,l),t.font=this.font_value(),t.textAlign=this.text_align.get_value(),t.textBaseline=this.text_baseline.get_value()}font_value(){return`${this.text_font_style.get_value()} ${this.text_font_size.get_value()} ${this.text_font.get_value()}`}}l.Text=h,h.__name__=\"Text\";class x extends a.VisualUniforms{get doit(){const t=this.text_color.value,e=this.text_alpha.value;return!(0==t||0==e)}values(){return{color:this.text_color.value,alpha:this.text_alpha.value,font:this.text_font.value,font_size:this.text_font_size.value,font_style:this.text_font_style.value,align:this.text_align.value,baseline:this.text_baseline.value,line_height:this.text_line_height.value}}set_value(t){const e=this.text_color.value,l=this.text_alpha.value,s=this.font_value(),_=this.text_align.value,i=this.text_baseline.value;t.fillStyle=(0,n.color2css)(e,l),t.font=s,t.textAlign=_,t.textBaseline=i}font_value(){return`${this.text_font_style.value} ${this.text_font_size.value} ${this.text_font.value}`}}l.TextScalar=x,x.__name__=\"TextScalar\";class u extends a.VisualUniforms{values(t){return{color:this.text_color.get(t),alpha:this.text_alpha.get(t),font:this.text_font.get(t),font_size:this.text_font_size.get(t),font_style:this.text_font_style.get(t),align:this.text_align.get(t),baseline:this.text_baseline.get(t),line_height:this.text_line_height.get(t)}}get doit(){const{text_color:t}=this;if(t.is_Scalar()&&0==t.value)return!1;const{text_alpha:e}=this;return!e.is_Scalar()||0!=e.value}set_vectorize(t,e){const l=this.text_color.get(e),s=this.text_alpha.get(e),_=this.font_value(e),i=this.text_align.get(e),a=this.text_baseline.get(e);t.fillStyle=(0,n.color2css)(l,s),t.font=_,t.textAlign=i,t.textBaseline=a}font_value(t){return`${this.text_font_style.get(t)} ${this.text_font_size.get(t)} ${this.text_font.get(t)}`}}l.TextVector=u,u.__name__=\"TextVector\",h.prototype.type=\"text\",h.prototype.attrs=Object.keys(o.Text),x.prototype.type=\"text\",x.prototype.attrs=Object.keys(o.TextScalar),u.prototype.type=\"text\",u.prototype.attrs=Object.keys(o.TextVector)},\n", - " function _(t,e,a,r,i){r();const h=t(1),s=t(47),n=t(52),c=(0,h.__importStar)(t(18)),_=(0,h.__importStar)(t(48));class l extends s.VisualProperties{constructor(){super(...arguments),this._update_iteration=0}update(){if(this._update_iteration++,this._hatch_image=null,!this.doit)return;const t=this.hatch_color.get_value(),e=this.hatch_alpha.get_value(),a=this.hatch_scale.get_value(),r=this.hatch_pattern.get_value(),i=this.hatch_weight.get_value(),h=t=>{this._hatch_image=t},s=this.hatch_extra.get_value()[r];if(null!=s){const r=s.get_pattern(t,e,a,i);if(r instanceof Promise){const{_update_iteration:t}=this;r.then((e=>{this._update_iteration==t&&(h(e),this.obj.request_render())}))}else h(r)}else{const s=this.obj.canvas.create_layer(),c=(0,n.get_pattern)(s,r,t,e,a,i);h(c)}}get doit(){const t=this.hatch_color.get_value(),e=this.hatch_alpha.get_value(),a=this.hatch_pattern.get_value();return!(null==t||0==e||\" \"==a||\"blank\"==a||null==a)}apply(t,e){const{doit:a}=this;return a&&(this.set_value(t),t.layer.undo_transform((()=>t.fill(e)))),a}set_value(t){const e=this.pattern(t);t.fillStyle=null!=e?e:\"transparent\"}pattern(t){const e=this._hatch_image;return null==e?null:t.createPattern(e,this.repetition())}repetition(){const t=this.hatch_pattern.get_value(),e=this.hatch_extra.get_value()[t];if(null==e)return\"repeat\";switch(e.repetition){case\"repeat\":return\"repeat\";case\"repeat_x\":return\"repeat-x\";case\"repeat_y\":return\"repeat-y\";case\"no_repeat\":return\"no-repeat\"}}}a.Hatch=l,l.__name__=\"Hatch\";class o extends s.VisualUniforms{constructor(){super(...arguments),this._static_doit=!1,this._update_iteration=0}_compute_static_doit(){const t=this.hatch_color.value,e=this.hatch_alpha.value,a=this.hatch_pattern.value;return!(null==t||0==e||\" \"==a||\"blank\"==a||null==a)}update(){this._update_iteration++;const t=this.hatch_color.length;if(this._hatch_image=new c.UniformScalar(null,t),this._static_doit=this._compute_static_doit(),!this._static_doit)return;const e=this.hatch_color.value,a=this.hatch_alpha.value,r=this.hatch_scale.value,i=this.hatch_pattern.value,h=this.hatch_weight.value,s=e=>{this._hatch_image=new c.UniformScalar(e,t)},_=this.hatch_extra.value[i];if(null!=_){const t=_.get_pattern(e,a,r,h);if(t instanceof Promise){const{_update_iteration:e}=this;t.then((t=>{this._update_iteration==e&&(s(t),this.obj.request_render())}))}else s(t)}else{const t=this.obj.canvas.create_layer(),c=(0,n.get_pattern)(t,i,e,a,r,h);s(c)}}get doit(){return this._static_doit}apply(t,e){const{doit:a}=this;return a&&(this.set_value(t),t.layer.undo_transform((()=>t.fill(e)))),a}set_value(t){var e;t.fillStyle=null!==(e=this.pattern(t))&&void 0!==e?e:\"transparent\"}pattern(t){const e=this._hatch_image.value;return null==e?null:t.createPattern(e,this.repetition())}repetition(){const t=this.hatch_pattern.value,e=this.hatch_extra.value[t];if(null==e)return\"repeat\";switch(e.repetition){case\"repeat\":return\"repeat\";case\"repeat_x\":return\"repeat-x\";case\"repeat_y\":return\"repeat-y\";case\"no_repeat\":return\"no-repeat\"}}}a.HatchScalar=o,o.__name__=\"HatchScalar\";class u extends s.VisualUniforms{constructor(){super(...arguments),this._static_doit=!1,this._update_iteration=0}_compute_static_doit(){const{hatch_color:t}=this;if(t.is_Scalar()&&0==t.value)return!1;const{hatch_alpha:e}=this;if(e.is_Scalar()&&0==e.value)return!1;const{hatch_pattern:a}=this;if(a.is_Scalar()){const t=a.value;if(\" \"==t||\"blank\"==t||null==t)return!1}return!0}update(){this._update_iteration++;const t=this.hatch_color.length;if(this._hatch_image=new c.UniformScalar(null,t),this._static_doit=this._compute_static_doit(),!this._static_doit)return;const e=(t,e,a,r,i,h)=>{const s=this.hatch_extra.value[t];if(null!=s){const t=s.get_pattern(e,a,r,i);if(t instanceof Promise){const{_update_iteration:e}=this;t.then((t=>{this._update_iteration==e&&(h(t),this.obj.request_render())}))}else h(t)}else{const s=this.obj.canvas.create_layer(),c=(0,n.get_pattern)(s,t,e,a,r,i);h(c)}};if(this.hatch_color.is_Scalar()&&this.hatch_alpha.is_Scalar()&&this.hatch_scale.is_Scalar()&&this.hatch_pattern.is_Scalar()&&this.hatch_weight.is_Scalar()){const a=this.hatch_color.value,r=this.hatch_alpha.value,i=this.hatch_scale.value;e(this.hatch_pattern.value,a,r,i,this.hatch_weight.value,(e=>{this._hatch_image=new c.UniformScalar(e,t)}))}else{const a=new Array(t);a.fill(null),this._hatch_image=new c.UniformVector(a);for(let r=0;r{a[r]=t}))}}}get doit(){return this._static_doit}apply(t,e,a){const{doit:r}=this;return r&&(this.set_vectorize(t,e),t.layer.undo_transform((()=>t.fill(a)))),r}set_vectorize(t,e){var a;t.fillStyle=null!==(a=this.pattern(t,e))&&void 0!==a?a:\"transparent\"}pattern(t,e){const a=this._hatch_image.get(e);return null==a?null:t.createPattern(a,this.repetition(e))}repetition(t){const e=this.hatch_pattern.get(t),a=this.hatch_extra.value[e];if(null==a)return\"repeat\";switch(a.repetition){case\"repeat\":return\"repeat\";case\"repeat_x\":return\"repeat-x\";case\"repeat_y\":return\"repeat-y\";case\"no_repeat\":return\"no-repeat\"}}}a.HatchVector=u,u.__name__=\"HatchVector\",l.prototype.type=\"hatch\",l.prototype.attrs=Object.keys(_.Hatch),o.prototype.type=\"hatch\",o.prototype.attrs=Object.keys(_.HatchScalar),u.prototype.type=\"hatch\",u.prototype.attrs=Object.keys(_.HatchVector)},\n", - " function _(e,o,a,s,r){s();const i=e(22);function l(e,o,a){e.moveTo(0,a+.5),e.lineTo(o,a+.5),e.stroke()}function n(e,o,a){e.moveTo(a+.5,0),e.lineTo(a+.5,o),e.stroke()}function t(e,o){e.moveTo(0,o),e.lineTo(o,0),e.stroke(),e.moveTo(0,0),e.lineTo(o,o),e.stroke()}a.hatch_aliases={\" \":\"blank\",\".\":\"dot\",o:\"ring\",\"-\":\"horizontal_line\",\"|\":\"vertical_line\",\"+\":\"cross\",'\"':\"horizontal_dash\",\":\":\"vertical_dash\",\"@\":\"spiral\",\"/\":\"right_diagonal_line\",\"\\\\\":\"left_diagonal_line\",x:\"diagonal_cross\",\",\":\"right_diagonal_dash\",\"`\":\"left_diagonal_dash\",v:\"horizontal_wave\",\">\":\"vertical_wave\",\"*\":\"criss_cross\"},a.get_pattern=function(e,o,s,r,c,k){return e.resize(c,c),e.prepare(),function(e,o,s,r,c,k){var _;const T=c,v=T/2,h=v/2,d=(0,i.color2css)(s,r);switch(e.strokeStyle=d,e.fillStyle=d,e.lineCap=\"square\",e.lineWidth=k,null!==(_=a.hatch_aliases[o])&&void 0!==_?_:o){case\"blank\":break;case\"dot\":e.arc(v,v,v/2,0,2*Math.PI,!0),e.fill();break;case\"ring\":e.arc(v,v,v/2,0,2*Math.PI,!0),e.stroke();break;case\"horizontal_line\":l(e,T,v);break;case\"vertical_line\":n(e,T,v);break;case\"cross\":l(e,T,v),n(e,T,v);break;case\"horizontal_dash\":l(e,v,v);break;case\"vertical_dash\":n(e,v,v);break;case\"spiral\":{const o=T/30;e.moveTo(v,v);for(let a=0;a<360;a++){const s=.1*a,r=v+o*s*Math.cos(s),i=v+o*s*Math.sin(s);e.lineTo(r,i)}e.stroke();break}case\"right_diagonal_line\":e.moveTo(.5-h,T),e.lineTo(h+.5,0),e.stroke(),e.moveTo(h+.5,T),e.lineTo(3*h+.5,0),e.stroke(),e.moveTo(3*h+.5,T),e.lineTo(5*h+.5,0),e.stroke(),e.stroke();break;case\"left_diagonal_line\":e.moveTo(h+.5,T),e.lineTo(.5-h,0),e.stroke(),e.moveTo(3*h+.5,T),e.lineTo(h+.5,0),e.stroke(),e.moveTo(5*h+.5,T),e.lineTo(3*h+.5,0),e.stroke(),e.stroke();break;case\"diagonal_cross\":t(e,T);break;case\"right_diagonal_dash\":e.moveTo(h+.5,3*h+.5),e.lineTo(3*h+.5,h+.5),e.stroke();break;case\"left_diagonal_dash\":e.moveTo(h+.5,h+.5),e.lineTo(3*h+.5,3*h+.5),e.stroke();break;case\"horizontal_wave\":e.moveTo(0,h),e.lineTo(v,3*h),e.lineTo(T,h),e.stroke();break;case\"vertical_wave\":e.moveTo(h,0),e.lineTo(3*h,v),e.lineTo(h,T),e.stroke();break;case\"criss_cross\":t(e,T),l(e,T,v),n(e,T,v)}}(e.ctx,o,s,r,c,k),e.canvas}},\n", - " function _(e,t,s,n,c){var a;n();const i=e(14),r=e(8),l=e(13),o=e(26),_=e(19);class h extends i.HasProps{constructor(e){super(e)}get is_syncable(){return this.syncable}[o.equals](e,t){return t.eq(this.id,e.id)&&super[o.equals](e,t)}initialize(){super.initialize(),this._js_callbacks=new Map}connect_signals(){super.connect_signals(),this._update_property_callbacks(),this.connect(this.properties.js_property_callbacks.change,(()=>this._update_property_callbacks())),this.connect(this.properties.js_event_callbacks.change,(()=>this._update_event_callbacks())),this.connect(this.properties.subscribed_events.change,(()=>this._update_event_callbacks()))}_process_event(e){var t;for(const s of null!==(t=this.js_event_callbacks[e.event_name])&&void 0!==t?t:[])s.execute(e);null!=this.document&&this.subscribed_events.some((t=>t==e.event_name))&&this.document.event_manager.send_event(e)}trigger_event(e){null!=this.document&&(e.origin=this,this.document.event_manager.trigger(e))}_update_event_callbacks(){null!=this.document?this.document.event_manager.subscribed_models.add(this):_.logger.warn(\"WARNING: Document not defined for updating event callbacks\")}_update_property_callbacks(){const e=e=>{const[t,s=null]=e.split(\":\");return null!=s?this.properties[s][t]:this[t]};for(const[t,s]of this._js_callbacks){const n=e(t);for(const e of s)this.disconnect(n,e)}this._js_callbacks.clear();for(const[t,s]of(0,l.entries)(this.js_property_callbacks)){const n=s.map((e=>()=>e.execute(this)));this._js_callbacks.set(t,n);const c=e(t);for(const e of n)this.connect(c,e)}}_doc_attached(){(0,l.isEmpty)(this.js_event_callbacks)&&0==this.subscribed_events.length||this._update_event_callbacks()}_doc_detached(){this.document.event_manager.subscribed_models.delete(this)}select(e){if((0,r.isString)(e))return[...this.references()].filter((t=>t instanceof h&&t.name===e));if(e.prototype instanceof i.HasProps)return[...this.references()].filter((t=>t instanceof e));throw new Error(\"invalid selector\")}select_one(e){const t=this.select(e);switch(t.length){case 0:return null;case 1:return t[0];default:throw new Error(\"found more than one object matching given selector\")}}}s.Model=h,a=h,h.__name__=\"Model\",a.define((({Any:e,Unknown:t,Boolean:s,String:n,Array:c,Dict:a,Nullable:i})=>({tags:[c(t),[]],name:[i(n),null],js_property_callbacks:[a(c(e)),{}],js_event_callbacks:[a(c(e)),{}],subscribed_events:[c(n),[]],syncable:[s,!0]})))},\n", - " function _(e,t,s,a,r){var c,n;a();const _=e(12),o=e(53),i=e(55),l=e(59),u=e(61),g=e(62),h=e(57),p=e(63),m=e(67);class x{constructor(e,t){this.x_scale=e,this.y_scale=t,this.x_source=this.x_scale.source_range,this.y_source=this.y_scale.source_range,this.ranges=[this.x_source,this.y_source],this.scales=[this.x_scale,this.y_scale]}map_to_screen(e,t){return[this.x_scale.v_compute(e),this.y_scale.v_compute(t)]}map_from_screen(e,t){return[this.x_scale.v_invert(e),this.y_scale.v_invert(t)]}}s.CoordinateTransform=x,x.__name__=\"CoordinateTransform\";class y extends o.Model{constructor(e){super(e)}get x_ranges(){return new Map([[\"default\",this.x_source]])}get y_ranges(){return new Map([[\"default\",this.y_source]])}_get_scale(e,t,s){if(e instanceof m.FactorRange!=t instanceof g.CategoricalScale)throw new Error(`Range ${e.type} is incompatible is Scale ${t.type}`);t instanceof u.LogScale&&e instanceof p.DataRange1d&&(e.scale_hint=\"log\");const a=t.clone();return a.setv({source_range:e,target_range:s}),a}get_transform(e){const{x_source:t,x_scale:s,x_target:a}=this,r=this._get_scale(t,s,a),{y_source:c,y_scale:n,y_target:_}=this,o=this._get_scale(c,n,_),i=new v({source_scale:r,source_range:r.source_range,target_scale:e.x_scale,target_range:e.x_target}),l=new v({source_scale:o,source_range:o.source_range,target_scale:e.y_scale,target_range:e.y_target});return new x(i,l)}}s.CoordinateMapping=y,c=y,y.__name__=\"CoordinateMapping\",c.define((({Ref:e})=>({x_source:[e(h.Range),()=>new p.DataRange1d],y_source:[e(h.Range),()=>new p.DataRange1d],x_scale:[e(i.Scale),()=>new l.LinearScale],y_scale:[e(i.Scale),()=>new l.LinearScale],x_target:[e(h.Range)],y_target:[e(h.Range)]})));class v extends i.Scale{constructor(e){super(e)}get s_compute(){const e=this.source_scale.s_compute,t=this.target_scale.s_compute;return s=>t(e(s))}get s_invert(){const e=this.source_scale.s_invert,t=this.target_scale.s_invert;return s=>e(t(s))}compute(e){return this.s_compute(e)}v_compute(e){const{s_compute:t}=this;return(0,_.map)(e,t)}invert(e){return this.s_invert(e)}v_invert(e){const{s_invert:t}=this;return(0,_.map)(e,t)}}s.CompositeScale=v,n=v,v.__name__=\"CompositeScale\",n.internal((({Ref:e})=>({source_scale:[e(i.Scale)],target_scale:[e(i.Scale)]})))},\n", - " function _(e,t,r,n,s){var _;n();const a=e(56),c=e(57),o=e(58),i=e(24);class u extends a.Transform{constructor(e){super(e)}compute(e){return this.s_compute(e)}v_compute(e){const t=new i.ScreenArray(e.length),{s_compute:r}=this;for(let n=0;n({source_range:[e(c.Range)],target_range:[e(o.Range1d)]})))},\n", - " function _(n,s,o,r,c){r();const e=n(53);class t extends e.Model{constructor(n){super(n)}}o.Transform=t,t.__name__=\"Transform\"},\n", - " function _(e,t,n,i,s){var r;i();const a=e(53);class l extends a.Model{constructor(e){super(e),this.have_updated_interactively=!1}get is_reversed(){return this.start>this.end}get is_valid(){return isFinite(this.min)&&isFinite(this.max)}get span(){return Math.abs(this.end-this.start)}}n.Range=l,r=l,l.__name__=\"Range\",r.define((({Number:e,Tuple:t,Or:n,Auto:i,Nullable:s})=>({bounds:[s(n(t(s(e),s(e)),i)),null],min_interval:[s(e),null],max_interval:[s(e),null]}))),r.internal((({Array:e,AnyRef:t})=>({plots:[e(t()),[]]})))},\n", - " function _(t,e,s,n,r){var a;n();const i=t(57);class _ extends i.Range{constructor(t){super(t)}_set_auto_bounds(){if(\"auto\"==this.bounds){const t=Math.min(this._reset_start,this._reset_end),e=Math.max(this._reset_start,this._reset_end);this.setv({bounds:[t,e]},{silent:!0})}}initialize(){super.initialize(),this._set_auto_bounds()}get min(){return Math.min(this.start,this.end)}get max(){return Math.max(this.start,this.end)}reset(){this._set_auto_bounds();const{_reset_start:t,_reset_end:e}=this;this.start!=t||this.end!=e?this.setv({start:t,end:e}):this.change.emit()}map(t){return new _({start:t(this.start),end:t(this.end)})}widen(t){let{start:e,end:s}=this;return this.is_reversed?(e+=t,s-=t):(e-=t,s+=t),new _({start:e,end:s})}}s.Range1d=_,a=_,_.__name__=\"Range1d\",a.define((({Number:t,Nullable:e})=>({start:[t,0],end:[t,1],reset_start:[e(t),null,{on_update(t,e){e._reset_start=null!=t?t:e.start}}],reset_end:[e(t),null,{on_update(t,e){e._reset_end=null!=t?t:e.end}}]})))},\n", - " function _(t,e,n,r,s){r();const a=t(60);class _ extends a.ContinuousScale{constructor(t){super(t)}get s_compute(){const[t,e]=this._linear_compute_state();return n=>t*n+e}get s_invert(){const[t,e]=this._linear_compute_state();return n=>(n-e)/t}_linear_compute_state(){const t=this.source_range.start,e=this.source_range.end,n=this.target_range.start,r=(this.target_range.end-n)/(e-t);return[r,-r*t+n]}}n.LinearScale=_,_.__name__=\"LinearScale\"},\n", - " function _(n,c,o,s,e){s();const t=n(55);class u extends t.Scale{constructor(n){super(n)}}o.ContinuousScale=u,u.__name__=\"ContinuousScale\"},\n", - " function _(t,e,a,o,s){o();const r=t(60);class n extends r.ContinuousScale{constructor(t){super(t)}get s_compute(){const[t,e,a,o]=this._compute_state();return s=>{if(0==a)return 0;{const r=(Math.log(s)-o)/a;return isFinite(r)?r*t+e:NaN}}}get s_invert(){const[t,e,a,o]=this._compute_state();return s=>{const r=(s-e)/t;return Math.exp(a*r+o)}}_get_safe_factor(t,e){let a=t<0?0:t,o=e<0?0:e;if(a==o)if(0==a)[a,o]=[1,10];else{const t=Math.log(a)/Math.log(10);a=10**Math.floor(t),o=Math.ceil(t)!=Math.floor(t)?10**Math.ceil(t):10**(Math.ceil(t)+1)}return[a,o]}_compute_state(){const t=this.source_range.start,e=this.source_range.end,a=this.target_range.start,o=this.target_range.end-a,[s,r]=this._get_safe_factor(t,e);let n,c;0==s?(n=Math.log(r),c=0):(n=Math.log(r)-Math.log(s),c=Math.log(s));return[o,a,n,c]}}a.LogScale=n,n.__name__=\"LogScale\"},\n", - " function _(t,e,c,a,s){a();const n=t(55),r=t(59),{_linear_compute_state:o}=r.LinearScale.prototype;class l extends n.Scale{constructor(t){super(t)}get s_compute(){const[t,e]=o.call(this),c=this.source_range;return a=>t*c.synthetic(a)+e}get s_invert(){const[t,e]=o.call(this);return c=>(c-e)/t}}c.CategoricalScale=l,l.__name__=\"CategoricalScale\"},\n", - " function _(t,i,n,e,a){e();const s=t(1);var l;const _=t(64),o=t(20),r=t(9),h=t(19),d=(0,s.__importStar)(t(65)),u=t(66);class g extends _.DataRange{constructor(t){super(t),this.have_updated_interactively=!1}initialize(){super.initialize(),this._initial_start=this.start,this._initial_end=this.end,this._initial_range_padding=this.range_padding,this._initial_range_padding_units=this.range_padding_units,this._initial_follow=this.follow,this._initial_follow_interval=this.follow_interval,this._initial_default_span=this.default_span,this._plot_bounds=new Map}get min(){return Math.min(this.start,this.end)}get max(){return Math.max(this.start,this.end)}computed_renderers(){const{renderers:t,names:i}=this,n=(0,r.concat)(this.plots.map((t=>t.data_renderers)));return(0,u.compute_renderers)(0==t.length?\"auto\":t,n,i)}_compute_plot_bounds(t,i){let n=d.empty();for(const e of t){const t=i.get(e);null==t||!e.visible&&this.only_visible||(n=d.union(n,t))}return n}adjust_bounds_for_aspect(t,i){const n=d.empty();let e=t.x1-t.x0;e<=0&&(e=1);let a=t.y1-t.y0;a<=0&&(a=1);const s=.5*(t.x1+t.x0),l=.5*(t.y1+t.y0);return el&&(\"start\"==this.follow?a=e+s*l:\"end\"==this.follow&&(e=a-s*l)),[e,a]}update(t,i,n,e){if(this.have_updated_interactively)return;const a=this.computed_renderers();let s=this._compute_plot_bounds(a,t);null!=e&&(s=this.adjust_bounds_for_aspect(s,e)),this._plot_bounds.set(n,s);const[l,_]=this._compute_min_max(this._plot_bounds.entries(),i);let[o,r]=this._compute_range(l,_);null!=this._initial_start&&(\"log\"==this.scale_hint?this._initial_start>0&&(o=this._initial_start):o=this._initial_start),null!=this._initial_end&&(\"log\"==this.scale_hint?this._initial_end>0&&(r=this._initial_end):r=this._initial_end);let h=!1;\"auto\"==this.bounds&&(this.setv({bounds:[o,r]},{silent:!0}),h=!0);const[d,u]=[this.start,this.end];if(o!=d||r!=u){const t={};o!=d&&(t.start=o),r!=u&&(t.end=r),this.setv(t),h=!1}h&&this.change.emit()}reset(){this.have_updated_interactively=!1,this.setv({range_padding:this._initial_range_padding,range_padding_units:this._initial_range_padding_units,follow:this._initial_follow,follow_interval:this._initial_follow_interval,default_span:this._initial_default_span},{silent:!0}),this.change.emit()}}n.DataRange1d=g,l=g,g.__name__=\"DataRange1d\",l.define((({Boolean:t,Number:i,Nullable:n})=>({start:[i],end:[i],range_padding:[i,.1],range_padding_units:[o.PaddingUnits,\"percent\"],flipped:[t,!1],follow:[n(o.StartEnd),null],follow_interval:[n(i),null],default_span:[i,2],only_visible:[t,!1]}))),l.internal((({Enum:t})=>({scale_hint:[t(\"log\",\"auto\"),\"auto\"]})))},\n", - " function _(e,n,a,r,s){var t;r();const c=e(57);class _ extends c.Range{constructor(e){super(e)}}a.DataRange=_,t=_,_.__name__=\"DataRange\",t.define((({String:e,Array:n,AnyRef:a})=>({names:[n(e),[]],renderers:[n(a()),[]]})))},\n", - " function _(t,i,e,h,r){h();const s=t(24),n=t(26),{min:x,max:y}=Math;e.empty=function(){return{x0:1/0,y0:1/0,x1:-1/0,y1:-1/0}},e.positive_x=function(){return{x0:Number.MIN_VALUE,y0:-1/0,x1:1/0,y1:1/0}},e.positive_y=function(){return{x0:-1/0,y0:Number.MIN_VALUE,x1:1/0,y1:1/0}},e.union=function(t,i){return{x0:x(t.x0,i.x0),x1:y(t.x1,i.x1),y0:x(t.y0,i.y0),y1:y(t.y1,i.y1)}};class o{constructor(t){if(null==t)this.x0=0,this.y0=0,this.x1=0,this.y1=0;else if(\"x0\"in t){const{x0:i,y0:e,x1:h,y1:r}=t;if(!(i<=h&&e<=r))throw new Error(`invalid bbox {x0: ${i}, y0: ${e}, x1: ${h}, y1: ${r}}`);this.x0=i,this.y0=e,this.x1=h,this.y1=r}else if(\"x\"in t){const{x:i,y:e,width:h,height:r}=t;if(!(h>=0&&r>=0))throw new Error(`invalid bbox {x: ${i}, y: ${e}, width: ${h}, height: ${r}}`);this.x0=i,this.y0=e,this.x1=i+h,this.y1=e+r}else{let i,e,h,r;if(\"width\"in t)if(\"left\"in t)i=t.left,e=i+t.width;else if(\"right\"in t)e=t.right,i=e-t.width;else{const h=t.width/2;i=t.hcenter-h,e=t.hcenter+h}else i=t.left,e=t.right;if(\"height\"in t)if(\"top\"in t)h=t.top,r=h+t.height;else if(\"bottom\"in t)r=t.bottom,h=r-t.height;else{const i=t.height/2;h=t.vcenter-i,r=t.vcenter+i}else h=t.top,r=t.bottom;if(!(i<=e&&h<=r))throw new Error(`invalid bbox {left: ${i}, top: ${h}, right: ${e}, bottom: ${r}}`);this.x0=i,this.y0=h,this.x1=e,this.y1=r}}static from_rect({left:t,right:i,top:e,bottom:h}){return new o({x0:Math.min(t,i),y0:Math.min(e,h),x1:Math.max(t,i),y1:Math.max(e,h)})}equals(t){return this.x0==t.x0&&this.y0==t.y0&&this.x1==t.x1&&this.y1==t.y1}[n.equals](t,i){return i.eq(this.x0,t.x0)&&i.eq(this.y0,t.y0)&&i.eq(this.x1,t.x1)&&i.eq(this.y1,t.y1)}toString(){return`BBox({left: ${this.left}, top: ${this.top}, width: ${this.width}, height: ${this.height}})`}get left(){return this.x0}get top(){return this.y0}get right(){return this.x1}get bottom(){return this.y1}get p0(){return[this.x0,this.y0]}get p1(){return[this.x1,this.y1]}get x(){return this.x0}get y(){return this.y0}get width(){return this.x1-this.x0}get height(){return this.y1-this.y0}get size(){return{width:this.width,height:this.height}}get rect(){const{x0:t,y0:i,x1:e,y1:h}=this;return{p0:{x:t,y:i},p1:{x:e,y:i},p2:{x:e,y:h},p3:{x:t,y:h}}}get box(){const{x:t,y:i,width:e,height:h}=this;return{x:t,y:i,width:e,height:h}}get h_range(){return{start:this.x0,end:this.x1}}get v_range(){return{start:this.y0,end:this.y1}}get ranges(){return[this.h_range,this.v_range]}get aspect(){return this.width/this.height}get hcenter(){return(this.left+this.right)/2}get vcenter(){return(this.top+this.bottom)/2}get area(){return this.width*this.height}relative(){const{width:t,height:i}=this;return new o({x:0,y:0,width:t,height:i})}translate(t,i){const{x:e,y:h,width:r,height:s}=this;return new o({x:t+e,y:i+h,width:r,height:s})}relativize(t,i){return[t-this.x,i-this.y]}contains(t,i){return this.x0<=t&&t<=this.x1&&this.y0<=i&&i<=this.y1}clip(t,i){return tthis.x1&&(t=this.x1),ithis.y1&&(i=this.y1),[t,i]}grow_by(t){return new o({left:this.left-t,right:this.right+t,top:this.top-t,bottom:this.bottom+t})}shrink_by(t){return new o({left:this.left+t,right:this.right-t,top:this.top+t,bottom:this.bottom-t})}union(t){return new o({x0:x(this.x0,t.x0),y0:x(this.y0,t.y0),x1:y(this.x1,t.x1),y1:y(this.y1,t.y1)})}intersection(t){return this.intersects(t)?new o({x0:y(this.x0,t.x0),y0:y(this.y0,t.y0),x1:x(this.x1,t.x1),y1:x(this.y1,t.y1)}):null}intersects(t){return!(t.x1this.x1||t.y1this.y1)}get xview(){return{compute:t=>this.left+t,v_compute:t=>{const i=new s.ScreenArray(t.length),e=this.left;for(let h=0;hthis.bottom-t,v_compute:t=>{const i=new s.ScreenArray(t.length),e=this.bottom;for(let h=0;h0&&(r=r.filter((n=>(0,l.includes)(t,n.name)))),r}},\n", - " function _(t,n,e,i,s){var r;i();const a=t(57),o=t(20),g=t(21),p=t(24),c=t(9),l=t(8),u=t(11);function h(t,n,e=0){const i=new Map;for(let s=0;sa.get(t).value)));r.set(t,{value:l/s,mapping:a}),o+=s+n+p}return[r,(a.size-1)*n+g]}function _(t,n,e,i,s=0){var r;const a=new Map,o=new Map;for(const[n,e,i]of t){const t=null!==(r=o.get(n))&&void 0!==r?r:[];o.set(n,[...t,[e,i]])}let g=s,p=0;for(const[t,s]of o){const r=s.length,[o,l]=d(s,e,i,g);p+=l;const u=(0,c.sum)(s.map((([t])=>o.get(t).value)));a.set(t,{value:u/r,mapping:o}),g+=r+n+l}return[a,(o.size-1)*n+p]}e.Factor=(0,g.Or)(g.String,(0,g.Tuple)(g.String,g.String),(0,g.Tuple)(g.String,g.String,g.String)),e.FactorSeq=(0,g.Or)((0,g.Array)(g.String),(0,g.Array)((0,g.Tuple)(g.String,g.String)),(0,g.Array)((0,g.Tuple)(g.String,g.String,g.String))),e.map_one_level=h,e.map_two_levels=d,e.map_three_levels=_;class f extends a.Range{constructor(t){super(t)}get min(){return this.start}get max(){return this.end}initialize(){super.initialize(),this._init(!0)}connect_signals(){super.connect_signals(),this.connect(this.properties.factors.change,(()=>this.reset())),this.connect(this.properties.factor_padding.change,(()=>this.reset())),this.connect(this.properties.group_padding.change,(()=>this.reset())),this.connect(this.properties.subgroup_padding.change,(()=>this.reset())),this.connect(this.properties.range_padding.change,(()=>this.reset())),this.connect(this.properties.range_padding_units.change,(()=>this.reset()))}reset(){this._init(!1),this.change.emit()}_lookup(t){switch(t.length){case 1:{const[n]=t,e=this._mapping.get(n);return null!=e?e.value:NaN}case 2:{const[n,e]=t,i=this._mapping.get(n);if(null!=i){const t=i.mapping.get(e);if(null!=t)return t.value}return NaN}case 3:{const[n,e,i]=t,s=this._mapping.get(n);if(null!=s){const t=s.mapping.get(e);if(null!=t){const n=t.mapping.get(i);if(null!=n)return n.value}}return NaN}default:(0,u.unreachable)()}}synthetic(t){if((0,l.isNumber)(t))return t;if((0,l.isString)(t))return this._lookup([t]);let n=0;const e=t[t.length-1];return(0,l.isNumber)(e)&&(n=e,t=t.slice(0,-1)),this._lookup(t)+n}v_synthetic(t){const n=t.length,e=new p.ScreenArray(n);for(let i=0;i{if((0,c.every)(this.factors,l.isString)){const t=this.factors,[n,e]=h(t,this.factor_padding);return{levels:1,mapping:n,tops:null,mids:null,inside_padding:e}}if((0,c.every)(this.factors,(t=>(0,l.isArray)(t)&&2==t.length&&(0,l.isString)(t[0])&&(0,l.isString)(t[1])))){const t=this.factors,[n,e]=d(t,this.group_padding,this.factor_padding),i=[...n.keys()];return{levels:2,mapping:n,tops:i,mids:null,inside_padding:e}}if((0,c.every)(this.factors,(t=>(0,l.isArray)(t)&&3==t.length&&(0,l.isString)(t[0])&&(0,l.isString)(t[1])&&(0,l.isString)(t[2])))){const t=this.factors,[n,e]=_(t,this.group_padding,this.subgroup_padding,this.factor_padding),i=[...n.keys()],s=[];for(const[t,e]of n)for(const n of e.mapping.keys())s.push([t,n]);return{levels:3,mapping:n,tops:i,mids:s,inside_padding:e}}(0,u.unreachable)()})();this._mapping=e,this.tops=i,this.mids=s;let a=0,o=this.factors.length+r;if(\"percent\"==this.range_padding_units){const t=(o-a)*this.range_padding/2;a-=t,o+=t}else a-=this.range_padding,o+=this.range_padding;this.setv({start:a,end:o,levels:n},{silent:t}),\"auto\"==this.bounds&&this.setv({bounds:[a,o]},{silent:!0})}}e.FactorRange=f,r=f,f.__name__=\"FactorRange\",r.define((({Number:t})=>({factors:[e.FactorSeq,[]],factor_padding:[t,0],subgroup_padding:[t,.8],group_padding:[t,1.4],range_padding:[t,0],range_padding_units:[o.PaddingUnits,\"percent\"],start:[t],end:[t]}))),r.internal((({Number:t,String:n,Array:e,Tuple:i,Nullable:s})=>({levels:[t],mids:[s(e(i(n,n))),null],tops:[s(e(n)),null]})))},\n", - " function _(t,e,s,a,i){a();const n=t(1);var _;const r=t(69),o=t(112),l=t(48),d=t(20),h=t(24),c=t(113),u=(0,n.__importStar)(t(18)),v=t(10);class p extends r.DataAnnotationView{async lazy_initialize(){await super.lazy_initialize();const{start:t,end:e}=this.model;null!=t&&(this.start=await(0,c.build_view)(t,{parent:this})),null!=e&&(this.end=await(0,c.build_view)(e,{parent:this}))}set_data(t){var e,s;super.set_data(t),null===(e=this.start)||void 0===e||e.set_data(t),null===(s=this.end)||void 0===s||s.set_data(t)}remove(){var t,e;null===(t=this.start)||void 0===t||t.remove(),null===(e=this.end)||void 0===e||e.remove(),super.remove()}map_data(){const{frame:t}=this.plot_view;\"data\"==this.model.start_units?(this._sx_start=this.coordinates.x_scale.v_compute(this._x_start),this._sy_start=this.coordinates.y_scale.v_compute(this._y_start)):(this._sx_start=t.bbox.xview.v_compute(this._x_start),this._sy_start=t.bbox.yview.v_compute(this._y_start)),\"data\"==this.model.end_units?(this._sx_end=this.coordinates.x_scale.v_compute(this._x_end),this._sy_end=this.coordinates.y_scale.v_compute(this._y_end)):(this._sx_end=t.bbox.xview.v_compute(this._x_end),this._sy_end=t.bbox.yview.v_compute(this._y_end));const{_sx_start:e,_sy_start:s,_sx_end:a,_sy_end:i}=this,n=e.length,_=this._angles=new h.ScreenArray(n);for(let t=0;t({x_start:[u.XCoordinateSpec,{field:\"x_start\"}],y_start:[u.YCoordinateSpec,{field:\"y_start\"}],start_units:[d.SpatialUnits,\"data\"],start:[e(t(o.ArrowHead)),null],x_end:[u.XCoordinateSpec,{field:\"x_end\"}],y_end:[u.YCoordinateSpec,{field:\"y_end\"}],end_units:[d.SpatialUnits,\"data\"],end:[e(t(o.ArrowHead)),()=>new o.OpenHead]})))},\n", - " function _(t,e,n,s,a){s();const o=t(1);var i;const c=t(40),r=t(70),_=t(75),l=t(78),h=(0,o.__importStar)(t(18));class d extends c.AnnotationView{constructor(){super(...arguments),this._initial_set_data=!1}connect_signals(){super.connect_signals();const t=()=>{this.set_data(this.model.source),this._rerender()};this.connect(this.model.change,t),this.connect(this.model.source.streaming,t),this.connect(this.model.source.patching,t),this.connect(this.model.source.change,t)}_rerender(){this.request_render()}set_data(t){const e=this;for(const n of this.model)if(n instanceof h.VectorSpec||n instanceof h.ScalarSpec)if(n instanceof h.BaseCoordinateSpec){const s=n.array(t);e[`_${n.attr}`]=s}else{const s=n.uniform(t);e[`${n.attr}`]=s}this.plot_model.use_map&&(null!=e._x&&l.inplace.project_xy(e._x,e._y),null!=e._xs&&l.inplace.project_xsys(e._xs,e._ys));for(const t of this.visuals)t.update()}_render(){this._initial_set_data||(this.set_data(this.model.source),this._initial_set_data=!0),this.map_data(),this.paint(this.layer.ctx)}}n.DataAnnotationView=d,d.__name__=\"DataAnnotationView\";class u extends c.Annotation{constructor(t){super(t)}}n.DataAnnotation=u,i=u,u.__name__=\"DataAnnotation\",i.define((({Ref:t})=>({source:[t(r.ColumnarDataSource),()=>new _.ColumnDataSource]})))},\n", - " function _(t,e,n,s,a){var i;s();const r=t(71),l=t(15),c=t(19),o=t(73),h=t(8),u=t(9),g=t(13),d=t(72),_=t(74),m=t(29);class w extends r.DataSource{constructor(t){super(t),this.selection_manager=new o.SelectionManager(this)}get_array(t){let e=this.data[t];return null==e?this.data[t]=e=[]:(0,h.isArray)(e)||(this.data[t]=e=Array.from(e)),e}initialize(){super.initialize(),this._select=new l.Signal0(this,\"select\"),this.inspect=new l.Signal(this,\"inspect\"),this.streaming=new l.Signal0(this,\"streaming\"),this.patching=new l.Signal(this,\"patching\")}get_column(t){const e=this.data[t];return null!=e?e:null}columns(){return(0,g.keys)(this.data)}get_length(t=!0){const e=(0,u.uniq)((0,g.values)(this.data).map((t=>(0,m.is_NDArray)(t)?t.shape[0]:t.length)));switch(e.length){case 0:return null;case 1:return e[0];default:{const n=\"data source has columns of inconsistent lengths\";if(t)return c.logger.warn(n),e.sort()[0];throw new Error(n)}}}get length(){var t;return null!==(t=this.get_length())&&void 0!==t?t:0}clear(){const t={};for(const e of this.columns())t[e]=new this.data[e].constructor(0);this.data=t}}n.ColumnarDataSource=w,i=w,w.__name__=\"ColumnarDataSource\",i.define((({Ref:t})=>({selection_policy:[t(_.SelectionPolicy),()=>new _.UnionRenderers]}))),i.internal((({AnyRef:t})=>({inspected:[t(),()=>new d.Selection]})))},\n", - " function _(e,c,n,t,o){var a;t();const s=e(53),r=e(72);class l extends s.Model{constructor(e){super(e)}}n.DataSource=l,a=l,l.__name__=\"DataSource\",a.define((({Ref:e})=>({selected:[e(r.Selection),()=>new r.Selection]})))},\n", - " function _(i,e,s,t,n){var l;t();const c=i(53),d=i(9),h=i(13);class _ extends c.Model{constructor(i){super(i)}get_view(){return this.view}get selected_glyph(){return this.selected_glyphs.length>0?this.selected_glyphs[0]:null}add_to_selected_glyphs(i){this.selected_glyphs.push(i)}update(i,e=!0,s=\"replace\"){switch(s){case\"replace\":this.indices=i.indices,this.line_indices=i.line_indices,this.multiline_indices=i.multiline_indices,this.image_indices=i.image_indices,this.view=i.view,this.selected_glyphs=i.selected_glyphs;break;case\"append\":this.update_through_union(i);break;case\"intersect\":this.update_through_intersection(i);break;case\"subtract\":this.update_through_subtraction(i)}}clear(){this.indices=[],this.line_indices=[],this.multiline_indices={},this.image_indices=[],this.view=null,this.selected_glyphs=[]}map(i){return new _(Object.assign(Object.assign({},this.attributes),{indices:this.indices.map(i),multiline_indices:(0,h.to_object)((0,h.entries)(this.multiline_indices).map((([e,s])=>[i(Number(e)),s]))),image_indices:this.image_indices.map((e=>Object.assign(Object.assign({},e),{index:i(e.index)})))}))}is_empty(){return 0==this.indices.length&&0==this.line_indices.length&&0==this.image_indices.length}update_through_union(i){this.indices=(0,d.union)(this.indices,i.indices),this.selected_glyphs=(0,d.union)(i.selected_glyphs,this.selected_glyphs),this.line_indices=(0,d.union)(i.line_indices,this.line_indices),this.view=i.view,this.multiline_indices=(0,h.merge)(i.multiline_indices,this.multiline_indices)}update_through_intersection(i){this.indices=(0,d.intersection)(this.indices,i.indices),this.selected_glyphs=(0,d.union)(i.selected_glyphs,this.selected_glyphs),this.line_indices=(0,d.union)(i.line_indices,this.line_indices),this.view=i.view,this.multiline_indices=(0,h.merge)(i.multiline_indices,this.multiline_indices)}update_through_subtraction(i){this.indices=(0,d.difference)(this.indices,i.indices),this.selected_glyphs=(0,d.union)(i.selected_glyphs,this.selected_glyphs),this.line_indices=(0,d.union)(i.line_indices,this.line_indices),this.view=i.view,this.multiline_indices=(0,h.merge)(i.multiline_indices,this.multiline_indices)}}s.Selection=_,l=_,_.__name__=\"Selection\",l.define((({Int:i,Array:e,Dict:s})=>({indices:[e(i),[]],line_indices:[e(i),[]],multiline_indices:[s(e(i)),{}]}))),l.internal((({Int:i,Array:e,AnyRef:s,Struct:t,Nullable:n})=>({selected_glyphs:[e(s()),[]],view:[n(s()),null],image_indices:[e(t({index:i,dim1:i,dim2:i,flat_index:i})),[]]})))},\n", - " function _(e,t,o,s,c){s();const n=e(72);function i(e){return\"GlyphRenderer\"==e.model.type}function l(e){return\"GraphRenderer\"==e.model.type}class r{constructor(e){this.source=e,this.inspectors=new Map}select(e,t,o,s=\"replace\"){const c=[],n=[];for(const t of e)i(t)?c.push(t):l(t)&&n.push(t);let r=!1;for(const e of n){const c=e.model.selection_policy.hit_test(t,e);r=r||e.model.selection_policy.do_selection(c,e.model,o,s)}if(c.length>0){const e=this.source.selection_policy.hit_test(t,c);r=r||this.source.selection_policy.do_selection(e,this.source,o,s)}return r}inspect(e,t){let o=!1;if(i(e)){const s=e.hit_test(t);if(null!=s){o=!s.is_empty();const c=this.get_or_create_inspector(e.model);c.update(s,!0,\"replace\"),this.source.setv({inspected:c},{silent:!0}),this.source.inspect.emit([e.model,{geometry:t}])}}else if(l(e)){const s=e.model.inspection_policy.hit_test(t,e);o=o||e.model.inspection_policy.do_inspection(s,t,e,!1,\"replace\")}return o}clear(e){this.source.selected.clear(),null!=e&&this.get_or_create_inspector(e.model).clear()}get_or_create_inspector(e){let t=this.inspectors.get(e);return null==t&&(t=new n.Selection,this.inspectors.set(e,t)),t}}o.SelectionManager=r,r.__name__=\"SelectionManager\"},\n", - " function _(e,t,n,s,o){s();const r=e(53);class c extends r.Model{do_selection(e,t,n,s){return null!=e&&(t.selected.update(e,n,s),t._select.emit(),!t.selected.is_empty())}}n.SelectionPolicy=c,c.__name__=\"SelectionPolicy\";class l extends c{hit_test(e,t){const n=[];for(const s of t){const t=s.hit_test(e);null!=t&&n.push(t)}if(n.length>0){const e=n[0];for(const t of n)e.update_through_intersection(t);return e}return null}}n.IntersectRenderers=l,l.__name__=\"IntersectRenderers\";class _ extends c{hit_test(e,t){const n=[];for(const s of t){const t=s.hit_test(e);null!=t&&n.push(t)}if(n.length>0){const e=n[0];for(const t of n)e.update_through_union(t);return e}return null}}n.UnionRenderers=_,_.__name__=\"UnionRenderers\"},\n", - " function _(t,n,e,s,o){s();const r=t(1);var l;const c=t(70),i=t(8),a=t(13),u=(0,r.__importStar)(t(76)),h=t(77),d=t(35);function f(t,n,e){if((0,i.isArray)(t)){const s=t.concat(n);return null!=e&&s.length>e?s.slice(-e):s}if((0,i.isTypedArray)(t)){const s=t.length+n.length;if(null!=e&&s>e){const o=s-e,r=t.length;let l;t.length({data:[t(n),{}]})))},\n", - " function _(t,n,o,e,c){e(),o.concat=function(t,...n){let o=t.length;for(const t of n)o+=t.length;const e=new t.constructor(o);e.set(t,0);let c=t.length;for(const t of n)e.set(t,c),c+=t.length;return e}},\n", - " function _(n,o,t,e,f){function c(...n){const o=new Set;for(const t of n)for(const n of t)o.add(n);return o}e(),t.union=c,t.intersection=function(n,...o){const t=new Set;n:for(const e of n){for(const n of o)if(!n.has(e))continue n;t.add(e)}return t},t.difference=function(n,...o){const t=new Set(n);for(const n of c(...o))t.delete(n);return t}},\n", - " function _(n,t,e,o,r){o();const c=n(1),l=(0,c.__importDefault)(n(79)),i=(0,c.__importDefault)(n(80)),u=n(24),a=new i.default(\"GOOGLE\"),s=new i.default(\"WGS84\"),f=(0,l.default)(s,a);e.wgs84_mercator={compute:(n,t)=>isFinite(n)&&isFinite(t)?f.forward([n,t]):[NaN,NaN],invert:(n,t)=>isFinite(n)&&isFinite(t)?f.inverse([n,t]):[NaN,NaN]};const _={lon:[-20026376.39,20026376.39],lat:[-20048966.1,20048966.1]},p={lon:[-180,180],lat:[-85.06,85.06]},{min:g,max:h}=Math;function m(n,t){const o=g(n.length,t.length),r=(0,u.infer_type)(n,t),c=new r(o),l=new r(o);return e.inplace.project_xy(n,t,c,l),[c,l]}e.clip_mercator=function(n,t,e){const[o,r]=_[e];return[h(n,o),g(t,r)]},e.in_bounds=function(n,t){const[e,o]=p[t];return e2?void 0!==e.name&&\"geocent\"===e.name||void 0!==n.name&&\"geocent\"===n.name?\"number\"==typeof o.z?[o.x,o.y,o.z].concat(t.splice(3)):[o.x,o.y,t[2]].concat(t.splice(3)):[o.x,o.y].concat(t.splice(2)):[o.x,o.y]):(a=(0,c.default)(e,n,t,r),2===(i=Object.keys(t)).length||i.forEach((function(r){if(void 0!==e.name&&\"geocent\"===e.name||void 0!==n.name&&\"geocent\"===n.name){if(\"x\"===r||\"y\"===r||\"z\"===r)return}else if(\"x\"===r||\"y\"===r)return;a[r]=t[r]})),a)}function l(e){return e instanceof i.default?e:e.oProj?e.oProj:(0,i.default)(e)}t.default=function(e,n,t){e=l(e);var r,o=!1;return void 0===n?(n=e,e=u,o=!0):(void 0!==n.x||Array.isArray(n))&&(t=n,n=e,e=u,o=!0),n=l(n),t?f(e,n,t):(r={forward:function(t,r){return f(e,n,t,r)},inverse:function(t,r){return f(n,e,t,r)}},o&&(r.oProj=n),r)}},\n", - " function _(t,e,a,s,i){s();const l=t(1),u=(0,l.__importDefault)(t(81)),r=(0,l.__importDefault)(t(92)),d=(0,l.__importDefault)(t(93)),o=t(101),f=(0,l.__importDefault)(t(103)),p=(0,l.__importDefault)(t(104)),m=(0,l.__importDefault)(t(88)),n=t(105);function h(t,e){if(!(this instanceof h))return new h(t);e=e||function(t){if(t)throw t};var a=(0,u.default)(t);if(\"object\"==typeof a){var s=h.projections.get(a.projName);if(s){if(a.datumCode&&\"none\"!==a.datumCode){var i=(0,m.default)(f.default,a.datumCode);i&&(a.datum_params=a.datum_params||(i.towgs84?i.towgs84.split(\",\"):null),a.ellps=i.ellipse,a.datumName=i.datumName?i.datumName:a.datumCode)}a.k0=a.k0||1,a.axis=a.axis||\"enu\",a.ellps=a.ellps||\"wgs84\",a.lat1=a.lat1||a.lat0;var l=(0,o.sphere)(a.a,a.b,a.rf,a.ellps,a.sphere),d=(0,o.eccentricity)(l.a,l.b,l.rf,a.R_A),_=(0,n.getNadgrids)(a.nadgrids),c=a.datum||(0,p.default)(a.datumCode,a.datum_params,l.a,l.b,d.es,d.ep2,_);(0,r.default)(this,a),(0,r.default)(this,s),this.a=l.a,this.b=l.b,this.rf=l.rf,this.sphere=l.sphere,this.es=d.es,this.e=d.e,this.ep2=d.ep2,this.datum=c,this.init(),e(null,this)}else e(t)}else e(t)}h.projections=d.default,h.projections.start(),a.default=h},\n", - " function _(t,r,n,u,e){u();const f=t(1),i=(0,f.__importDefault)(t(82)),a=(0,f.__importDefault)(t(89)),o=(0,f.__importDefault)(t(84)),l=(0,f.__importDefault)(t(88));var C=[\"PROJECTEDCRS\",\"PROJCRS\",\"GEOGCS\",\"GEOCCS\",\"PROJCS\",\"LOCAL_CS\",\"GEODCRS\",\"GEODETICCRS\",\"GEODETICDATUM\",\"ENGCRS\",\"ENGINEERINGCRS\"];var d=[\"3857\",\"900913\",\"3785\",\"102113\"];n.default=function(t){if(!function(t){return\"string\"==typeof t}(t))return t;if(function(t){return t in i.default}(t))return i.default[t];if(function(t){return C.some((function(r){return t.indexOf(r)>-1}))}(t)){var r=(0,a.default)(t);if(function(t){var r=(0,l.default)(t,\"authority\");if(r){var n=(0,l.default)(r,\"epsg\");return n&&d.indexOf(n)>-1}}(r))return i.default[\"EPSG:3857\"];var n=function(t){var r=(0,l.default)(t,\"extension\");if(r)return(0,l.default)(r,\"proj4\")}(r);return n?(0,o.default)(n):r}return function(t){return\"+\"===t[0]}(t)?(0,o.default)(t):void 0}},\n", - " function _(t,r,i,e,n){e();const f=t(1),a=(0,f.__importDefault)(t(83)),l=(0,f.__importDefault)(t(84)),u=(0,f.__importDefault)(t(89));function o(t){var r=this;if(2===arguments.length){var i=arguments[1];\"string\"==typeof i?\"+\"===i.charAt(0)?o[t]=(0,l.default)(arguments[1]):o[t]=(0,u.default)(arguments[1]):o[t]=i}else if(1===arguments.length){if(Array.isArray(t))return t.map((function(t){Array.isArray(t)?o.apply(r,t):o(t)}));if(\"string\"==typeof t){if(t in o)return o[t]}else\"EPSG\"in t?o[\"EPSG:\"+t.EPSG]=t:\"ESRI\"in t?o[\"ESRI:\"+t.ESRI]=t:\"IAU2000\"in t?o[\"IAU2000:\"+t.IAU2000]=t:console.log(t);return}}(0,a.default)(o),i.default=o},\n", - " function _(t,l,G,S,e){S(),G.default=function(t){t(\"EPSG:4326\",\"+title=WGS 84 (long/lat) +proj=longlat +ellps=WGS84 +datum=WGS84 +units=degrees\"),t(\"EPSG:4269\",\"+title=NAD83 (long/lat) +proj=longlat +a=6378137.0 +b=6356752.31414036 +ellps=GRS80 +datum=NAD83 +units=degrees\"),t(\"EPSG:3857\",\"+title=WGS 84 / Pseudo-Mercator +proj=merc +a=6378137 +b=6378137 +lat_ts=0.0 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o.push(!0),t[o[0].toLowerCase()]=o[1],t}),{}),c={proj:\"projName\",datum:\"datumCode\",rf:function(t){u.rf=parseFloat(t)},lat_0:function(t){u.lat0=t*r.D2R},lat_1:function(t){u.lat1=t*r.D2R},lat_2:function(t){u.lat2=t*r.D2R},lat_ts:function(t){u.lat_ts=t*r.D2R},lon_0:function(t){u.long0=t*r.D2R},lon_1:function(t){u.long1=t*r.D2R},lon_2:function(t){u.long2=t*r.D2R},alpha:function(t){u.alpha=parseFloat(t)*r.D2R},gamma:function(t){u.rectified_grid_angle=parseFloat(t)},lonc:function(t){u.longc=t*r.D2R},x_0:function(t){u.x0=parseFloat(t)},y_0:function(t){u.y0=parseFloat(t)},k_0:function(t){u.k0=parseFloat(t)},k:function(t){u.k0=parseFloat(t)},a:function(t){u.a=parseFloat(t)},b:function(t){u.b=parseFloat(t)},r_a:function(){u.R_A=!0},zone:function(t){u.zone=parseInt(t,10)},south:function(){u.utmSouth=!0},towgs84:function(t){u.datum_params=t.split(\",\").map((function(t){return parseFloat(t)}))},to_meter:function(t){u.to_meter=parseFloat(t)},units:function(t){u.units=t;var n=(0,l.default)(f.default,t);n&&(u.to_meter=n.to_meter)},from_greenwich:function(t){u.from_greenwich=t*r.D2R},pm:function(t){var n=(0,l.default)(i.default,t);u.from_greenwich=(n||parseFloat(t))*r.D2R},nadgrids:function(t){\"@null\"===t?u.datumCode=\"none\":u.nadgrids=t},axis:function(t){var n=\"ewnsud\";3===t.length&&-1!==n.indexOf(t.substr(0,1))&&-1!==n.indexOf(t.substr(1,1))&&-1!==n.indexOf(t.substr(2,1))&&(u.axis=t)},approx:function(){u.approx=!0}};for(n in e)o=e[n],n in c?\"function\"==typeof(a=c[n])?a(o):u[a]=o:u[n]=o;return\"string\"==typeof u.datumCode&&\"WGS84\"!==u.datumCode&&(u.datumCode=u.datumCode.toLowerCase()),u}},\n", - " function _(S,_,P,R,I){R(),P.PJD_3PARAM=1,P.PJD_7PARAM=2,P.PJD_GRIDSHIFT=3,P.PJD_WGS84=4,P.PJD_NODATUM=5,P.SRS_WGS84_SEMIMAJOR=6378137,P.SRS_WGS84_SEMIMINOR=6356752.314,P.SRS_WGS84_ESQUARED=.0066943799901413165,P.SEC_TO_RAD=484813681109536e-20,P.HALF_PI=Math.PI/2,P.SIXTH=.16666666666666666,P.RA4=.04722222222222222,P.RA6=.022156084656084655,P.EPSLN=1e-10,P.D2R=.017453292519943295,P.R2D=57.29577951308232,P.FORTPI=Math.PI/4,P.TWO_PI=2*Math.PI,P.SPI=3.14159265359},\n", - " function _(o,r,a,e,s){e();var n={};a.default=n,n.greenwich=0,n.lisbon=-9.131906111111,n.paris=2.337229166667,n.bogota=-74.080916666667,n.madrid=-3.687938888889,n.rome=12.452333333333,n.bern=7.439583333333,n.jakarta=106.807719444444,n.ferro=-17.666666666667,n.brussels=4.367975,n.stockholm=18.058277777778,n.athens=23.7163375,n.oslo=10.722916666667},\n", - " function _(t,e,f,o,u){o(),f.default={ft:{to_meter:.3048},\"us-ft\":{to_meter:1200/3937}}},\n", - " function _(e,r,t,a,n){a();var o=/[\\s_\\-\\/\\(\\)]/g;t.default=function(e,r){if(e[r])return e[r];for(var t,a=Object.keys(e),n=r.toLowerCase().replace(o,\"\"),f=-1;++f0?90:-90),e.lat_ts=e.lat1)}(n),n}},\n", - " function _(t,e,r,i,s){i(),r.default=function(t){return new d(t).output()};var h=/\\s/,o=/[A-Za-z]/,n=/[A-Za-z84]/,a=/[,\\]]/,u=/[\\d\\.E\\-\\+]/;function d(t){if(\"string\"!=typeof t)throw new Error(\"not a string\");this.text=t.trim(),this.level=0,this.place=0,this.root=null,this.stack=[],this.currentObject=null,this.state=1}d.prototype.readCharicter=function(){var t=this.text[this.place++];if(4!==this.state)for(;h.test(t);){if(this.place>=this.text.length)return;t=this.text[this.place++]}switch(this.state){case 1:return this.neutral(t);case 2:return this.keyword(t);case 4:return this.quoted(t);case 5:return this.afterquote(t);case 3:return this.number(t);case-1:return}},d.prototype.afterquote=function(t){if('\"'===t)return this.word+='\"',void(this.state=4);if(a.test(t))return this.word=this.word.trim(),void this.afterItem(t);throw new Error(\"havn't handled \\\"\"+t+'\" in afterquote yet, index '+this.place)},d.prototype.afterItem=function(t){return\",\"===t?(null!==this.word&&this.currentObject.push(this.word),this.word=null,void(this.state=1)):\"]\"===t?(this.level--,null!==this.word&&(this.currentObject.push(this.word),this.word=null),this.state=1,this.currentObject=this.stack.pop(),void(this.currentObject||(this.state=-1))):void 0},d.prototype.number=function(t){if(!u.test(t)){if(a.test(t))return this.word=parseFloat(this.word),void this.afterItem(t);throw new Error(\"havn't handled \\\"\"+t+'\" in number yet, index '+this.place)}this.word+=t},d.prototype.quoted=function(t){'\"'!==t?this.word+=t:this.state=5},d.prototype.keyword=function(t){if(n.test(t))this.word+=t;else{if(\"[\"===t){var e=[];return e.push(this.word),this.level++,null===this.root?this.root=e:this.currentObject.push(e),this.stack.push(this.currentObject),this.currentObject=e,void(this.state=1)}if(!a.test(t))throw new Error(\"havn't handled \\\"\"+t+'\" in keyword yet, index '+this.place);this.afterItem(t)}},d.prototype.neutral=function(t){if(o.test(t))return this.word=t,void(this.state=2);if('\"'===t)return this.word=\"\",void(this.state=4);if(u.test(t))return this.word=t,void(this.state=3);if(!a.test(t))throw new Error(\"havn't handled \\\"\"+t+'\" in neutral yet, index '+this.place);this.afterItem(t)},d.prototype.output=function(){for(;this.place90&&a*o.R2D<-90&&h*o.R2D>180&&h*o.R2D<-180)return null;if(Math.abs(Math.abs(a)-o.HALF_PI)<=o.EPSLN)return null;if(this.sphere)i=this.x0+this.a*this.k0*(0,n.default)(h-this.long0),s=this.y0+this.a*this.k0*Math.log(Math.tan(o.FORTPI+.5*a));else{var e=Math.sin(a),r=(0,l.default)(this.e,a,e);i=this.x0+this.a*this.k0*(0,n.default)(h-this.long0),s=this.y0-this.a*this.k0*Math.log(r)}return t.x=i,t.y=s,t}function M(t){var i,s,h=t.x-this.x0,a=t.y-this.y0;if(this.sphere)s=o.HALF_PI-2*Math.atan(Math.exp(-a/(this.a*this.k0)));else{var e=Math.exp(-a/(this.a*this.k0));if(-9999===(s=(0,u.default)(this.e,e)))return null}return i=(0,n.default)(this.long0+h/(this.a*this.k0)),t.x=i,t.y=s,t}s.init=f,s.forward=_,s.inverse=M,s.names=[\"Mercator\",\"Popular Visualisation Pseudo Mercator\",\"Mercator_1SP\",\"Mercator_Auxiliary_Sphere\",\"merc\"],s.default={init:f,forward:_,inverse:M,names:s.names}},\n", - " function _(t,n,r,u,a){u(),r.default=function(t,n,r){var u=t*n;return r/Math.sqrt(1-u*u)}},\n", - " function _(t,n,u,a,f){a();const e=t(1),o=t(85),_=(0,e.__importDefault)(t(97));u.default=function(t){return Math.abs(t)<=o.SPI?t:t-(0,_.default)(t)*o.TWO_PI}},\n", - " function _(n,t,u,f,c){f(),u.default=function(n){return n<0?-1:1}},\n", - " function _(t,n,a,o,u){o();const c=t(85);a.default=function(t,n,a){var o=t*a,u=.5*t;return o=Math.pow((1-o)/(1+o),u),Math.tan(.5*(c.HALF_PI-n))/o}},\n", - " function _(t,a,n,r,f){r();const h=t(85);n.default=function(t,a){for(var n,r,f=.5*t,o=h.HALF_PI-2*Math.atan(a),u=0;u<=15;u++)if(n=t*Math.sin(o),o+=r=h.HALF_PI-2*Math.atan(a*Math.pow((1-n)/(1+n),f))-o,Math.abs(r)<=1e-10)return o;return-9999}},\n", - " function _(n,i,e,t,r){function a(){}function f(n){return n}t(),e.init=a,e.forward=f,e.inverse=f,e.names=[\"longlat\",\"identity\"],e.default={init:a,forward:f,inverse:f,names:e.names}},\n", - " function _(t,r,e,a,n){a();const f=t(1),i=t(85),u=(0,f.__importStar)(t(102)),c=(0,f.__importDefault)(t(88));e.eccentricity=function(t,r,e,a){var n=t*t,f=r*r,u=(n-f)/n,c=0;return a?(n=(t*=1-u*(i.SIXTH+u*(i.RA4+u*i.RA6)))*t,u=0):c=Math.sqrt(u),{es:u,e:c,ep2:(n-f)/f}},e.sphere=function(t,r,e,a,n){if(!t){var f=(0,c.default)(u.default,a);f||(f=u.WGS84),t=f.a,r=f.b,e=f.rf}return e&&!r&&(r=(1-1/e)*t),(0===e||Math.abs(t-r)3&&(0===s.datum_params[3]&&0===s.datum_params[4]&&0===s.datum_params[5]&&0===s.datum_params[6]||(s.datum_type=d.PJD_7PARAM,s.datum_params[3]*=d.SEC_TO_RAD,s.datum_params[4]*=d.SEC_TO_RAD,s.datum_params[5]*=d.SEC_TO_RAD,s.datum_params[6]=s.datum_params[6]/1e6+1))),r&&(s.datum_type=d.PJD_GRIDSHIFT,s.grids=r),s.a=_,s.b=t,s.es=u,s.ep2=p,s}},\n", - " function _(t,e,n,r,i){r();var u={};function l(t){if(0===t.length)return null;var e=\"@\"===t[0];return e&&(t=t.slice(1)),\"null\"===t?{name:\"null\",mandatory:!e,grid:null,isNull:!0}:{name:t,mandatory:!e,grid:u[t]||null,isNull:!1}}function o(t){return t/3600*Math.PI/180}function a(t,e,n){return String.fromCharCode.apply(null,new Uint8Array(t.buffer.slice(e,n)))}function d(t){return t.map((function(t){return[o(t.longitudeShift),o(t.latitudeShift)]}))}function g(t,e,n){return{name:a(t,e+8,e+16).trim(),parent:a(t,e+24,e+24+8).trim(),lowerLatitude:t.getFloat64(e+72,n),upperLatitude:t.getFloat64(e+88,n),lowerLongitude:t.getFloat64(e+104,n),upperLongitude:t.getFloat64(e+120,n),latitudeInterval:t.getFloat64(e+136,n),longitudeInterval:t.getFloat64(e+152,n),gridNodeCount:t.getInt32(e+168,n)}}function s(t,e,n,r){for(var i=e+176,u=[],l=0;l1&&console.log(\"Only single NTv2 subgrids are currently supported, subsequent sub grids are ignored\");var l=function(t,e,n){for(var r=176,i=[],u=0;ua.y||f>a.x||N1e-12&&Math.abs(n.y)>1e-12);if(d<0)return console.log(\"Inverse grid shift iterator failed to converge.\"),a;a.x=(0,u.default)(l.x+t.ll[0]),a.y=l.y+t.ll[1]}else isNaN(l.x)||(a.x=r.x+l.x,a.y=r.y+l.y);return a}function f(r,e){var t,a={x:r.x/e.del[0],y:r.y/e.del[1]},i=Math.floor(a.x),l=Math.floor(a.y),n=a.x-1*i,o=a.y-1*l,u={x:Number.NaN,y:Number.NaN};if(i<0||i>=e.lim[0])return u;if(l<0||l>=e.lim[1])return u;t=l*e.lim[0]+i;var d=e.cvs[t][0],s=e.cvs[t][1];t++;var y=e.cvs[t][0],f=e.cvs[t][1];t+=e.lim[0];var x=e.cvs[t][0],m=e.cvs[t][1];t--;var N=e.cvs[t][0],c=e.cvs[t][1],_=n*o,g=n*(1-o),v=(1-n)*(1-o),S=(1-n)*o;return u.x=v*d+g*y+S*N+_*x,u.y=v*s+g*f+S*c+_*m,u}t.default=function(r,e,t){if((0,o.compareDatums)(r,e))return t;if(r.datum_type===n.PJD_NODATUM||e.datum_type===n.PJD_NODATUM)return t;var a=r.a,i=r.es;if(r.datum_type===n.PJD_GRIDSHIFT){if(0!==s(r,!1,t))return;a=n.SRS_WGS84_SEMIMAJOR,i=n.SRS_WGS84_ESQUARED}var l=e.a,u=e.b,y=e.es;if(e.datum_type===n.PJD_GRIDSHIFT&&(l=n.SRS_WGS84_SEMIMAJOR,u=n.SRS_WGS84_SEMIMINOR,y=n.SRS_WGS84_ESQUARED),i===y&&a===l&&!d(r.datum_type)&&!d(e.datum_type))return t;if(t=(0,o.geodeticToGeocentric)(t,i,a),d(r.datum_type)&&(t=(0,o.geocentricToWgs84)(t,r.datum_type,r.datum_params)),d(e.datum_type)&&(t=(0,o.geocentricFromWgs84)(t,e.datum_type,e.datum_params)),t=(0,o.geocentricToGeodetic)(t,y,l,u),e.datum_type===n.PJD_GRIDSHIFT&&0!==s(e,!0,t))return;return t},t.applyGridShift=s},\n", - " function _(a,t,r,m,s){m();const u=a(85);r.compareDatums=function(a,t){return a.datum_type===t.datum_type&&(!(a.a!==t.a||Math.abs(a.es-t.es)>5e-11)&&(a.datum_type===u.PJD_3PARAM?a.datum_params[0]===t.datum_params[0]&&a.datum_params[1]===t.datum_params[1]&&a.datum_params[2]===t.datum_params[2]:a.datum_type!==u.PJD_7PARAM||a.datum_params[0]===t.datum_params[0]&&a.datum_params[1]===t.datum_params[1]&&a.datum_params[2]===t.datum_params[2]&&a.datum_params[3]===t.datum_params[3]&&a.datum_params[4]===t.datum_params[4]&&a.datum_params[5]===t.datum_params[5]&&a.datum_params[6]===t.datum_params[6]))},r.geodeticToGeocentric=function(a,t,r){var m,s,_,e,n=a.x,d=a.y,i=a.z?a.z:0;if(d<-u.HALF_PI&&d>-1.001*u.HALF_PI)d=-u.HALF_PI;else if(d>u.HALF_PI&&d<1.001*u.HALF_PI)d=u.HALF_PI;else{if(d<-u.HALF_PI)return{x:-1/0,y:-1/0,z:a.z};if(d>u.HALF_PI)return{x:1/0,y:1/0,z:a.z}}return n>Math.PI&&(n-=2*Math.PI),s=Math.sin(d),e=Math.cos(d),_=s*s,{x:((m=r/Math.sqrt(1-t*_))+i)*e*Math.cos(n),y:(m+i)*e*Math.sin(n),z:(m*(1-t)+i)*s}},r.geocentricToGeodetic=function(a,t,r,m){var s,_,e,n,d,i,p,P,y,z,M,o,A,c,x,h=1e-12,f=a.x,I=a.y,F=a.z?a.z:0;if(s=Math.sqrt(f*f+I*I),_=Math.sqrt(f*f+I*I+F*F),s/r1e-24&&A<30);return{x:c,y:Math.atan(M/Math.abs(z)),z:x}},r.geocentricToWgs84=function(a,t,r){if(t===u.PJD_3PARAM)return{x:a.x+r[0],y:a.y+r[1],z:a.z+r[2]};if(t===u.PJD_7PARAM){var m=r[0],s=r[1],_=r[2],e=r[3],n=r[4],d=r[5],i=r[6];return{x:i*(a.x-d*a.y+n*a.z)+m,y:i*(d*a.x+a.y-e*a.z)+s,z:i*(-n*a.x+e*a.y+a.z)+_}}},r.geocentricFromWgs84=function(a,t,r){if(t===u.PJD_3PARAM)return{x:a.x-r[0],y:a.y-r[1],z:a.z-r[2]};if(t===u.PJD_7PARAM){var m=r[0],s=r[1],_=r[2],e=r[3],n=r[4],d=r[5],i=r[6],p=(a.x-m)/i,P=(a.y-s)/i,y=(a.z-_)/i;return{x:p+d*P-n*y,y:-d*p+P+e*y,z:n*p-e*P+y}}}},\n", - " function _(e,a,i,r,s){r(),i.default=function(e,a,i){var r,s,n,c=i.x,d=i.y,f=i.z||0,u={};for(n=0;n<3;n++)if(!a||2!==n||void 0!==i.z)switch(0===n?(r=c,s=-1!==\"ew\".indexOf(e.axis[n])?\"x\":\"y\"):1===n?(r=d,s=-1!==\"ns\".indexOf(e.axis[n])?\"y\":\"x\"):(r=f,s=\"z\"),e.axis[n]){case\"e\":u[s]=r;break;case\"w\":u[s]=-r;break;case\"n\":u[s]=r;break;case\"s\":u[s]=-r;break;case\"u\":void 0!==i[s]&&(u.z=r);break;case\"d\":void 0!==i[s]&&(u.z=-r);break;default:return null}return u}},\n", - " function _(n,t,e,u,f){u(),e.default=function(n){var t={x:n[0],y:n[1]};return n.length>2&&(t.z=n[2]),n.length>3&&(t.m=n[3]),t}},\n", - " function _(e,i,n,t,r){function o(e){if(\"function\"==typeof Number.isFinite){if(Number.isFinite(e))return;throw new TypeError(\"coordinates must be finite numbers\")}if(\"number\"!=typeof e||e!=e||!isFinite(e))throw new TypeError(\"coordinates must be finite numbers\")}t(),n.default=function(e){o(e.x),o(e.y)}},\n", - " function _(e,i,s,t,o){t();const n=e(1);var l,a,r,_,c;const d=e(53),v=e(42),u=(0,n.__importStar)(e(45)),h=e(48),m=(0,n.__importStar)(e(18));class T extends v.View{initialize(){super.initialize(),this.visuals=new u.Visuals(this)}request_render(){this.parent.request_render()}get canvas(){return this.parent.canvas}set_data(e){const i=this;for(const s of this.model){if(!(s instanceof m.VectorSpec||s instanceof m.ScalarSpec))continue;const t=s.uniform(e);i[`${s.attr}`]=t}}}s.ArrowHeadView=T,T.__name__=\"ArrowHeadView\";class p extends d.Model{constructor(e){super(e)}}s.ArrowHead=p,l=p,p.__name__=\"ArrowHead\",l.define((()=>({size:[m.NumberSpec,25]})));class V extends T{clip(e,i){this.visuals.line.set_vectorize(e,i);const s=this.size.get(i);e.moveTo(.5*s,s),e.lineTo(.5*s,-2),e.lineTo(-.5*s,-2),e.lineTo(-.5*s,s),e.lineTo(0,0),e.lineTo(.5*s,s)}render(e,i){if(this.visuals.line.doit){this.visuals.line.set_vectorize(e,i);const s=this.size.get(i);e.beginPath(),e.moveTo(.5*s,s),e.lineTo(0,0),e.lineTo(-.5*s,s),e.stroke()}}}s.OpenHeadView=V,V.__name__=\"OpenHeadView\";class f extends p{constructor(e){super(e)}}s.OpenHead=f,a=f,f.__name__=\"OpenHead\",a.prototype.default_view=V,a.mixins(h.LineVector);class w extends T{clip(e,i){this.visuals.line.set_vectorize(e,i);const s=this.size.get(i);e.moveTo(.5*s,s),e.lineTo(.5*s,-2),e.lineTo(-.5*s,-2),e.lineTo(-.5*s,s),e.lineTo(.5*s,s)}render(e,i){this.visuals.fill.doit&&(this.visuals.fill.set_vectorize(e,i),this._normal(e,i),e.fill()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(e,i),this._normal(e,i),e.stroke())}_normal(e,i){const s=this.size.get(i);e.beginPath(),e.moveTo(.5*s,s),e.lineTo(0,0),e.lineTo(-.5*s,s),e.closePath()}}s.NormalHeadView=w,w.__name__=\"NormalHeadView\";class H extends p{constructor(e){super(e)}}s.NormalHead=H,r=H,H.__name__=\"NormalHead\",r.prototype.default_view=w,r.mixins([h.LineVector,h.FillVector]),r.override({fill_color:\"black\"});class z extends T{clip(e,i){this.visuals.line.set_vectorize(e,i);const s=this.size.get(i);e.moveTo(.5*s,s),e.lineTo(.5*s,-2),e.lineTo(-.5*s,-2),e.lineTo(-.5*s,s),e.lineTo(0,.5*s),e.lineTo(.5*s,s)}render(e,i){this.visuals.fill.doit&&(this.visuals.fill.set_vectorize(e,i),this._vee(e,i),e.fill()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(e,i),this._vee(e,i),e.stroke())}_vee(e,i){const s=this.size.get(i);e.beginPath(),e.moveTo(.5*s,s),e.lineTo(0,0),e.lineTo(-.5*s,s),e.lineTo(0,.5*s),e.closePath()}}s.VeeHeadView=z,z.__name__=\"VeeHeadView\";class x extends p{constructor(e){super(e)}}s.VeeHead=x,_=x,x.__name__=\"VeeHead\",_.prototype.default_view=z,_.mixins([h.LineVector,h.FillVector]),_.override({fill_color:\"black\"});class g extends T{render(e,i){if(this.visuals.line.doit){this.visuals.line.set_vectorize(e,i);const s=this.size.get(i);e.beginPath(),e.moveTo(.5*s,0),e.lineTo(-.5*s,0),e.stroke()}}clip(e,i){}}s.TeeHeadView=g,g.__name__=\"TeeHeadView\";class b extends p{constructor(e){super(e)}}s.TeeHead=b,c=b,b.__name__=\"TeeHead\",c.prototype.default_view=g,c.mixins(h.LineVector)},\n", - " function _(n,e,t,i,o){i();const s=n(9);async function c(n,e,t){const i=new n(Object.assign(Object.assign({},t),{model:e}));return i.initialize(),await i.lazy_initialize(),i}t.build_view=async function(n,e={parent:null},t=(n=>n.default_view)){const i=await c(t(n),n,e);return i.connect_signals(),i},t.build_views=async function(n,e,t={parent:null},i=(n=>n.default_view)){const o=(0,s.difference)([...n.keys()],e);for(const e of o)n.get(e).remove(),n.delete(e);const a=[],f=e.filter((e=>!n.has(e)));for(const e of f){const o=await c(i(e),e,t);n.set(e,o),a.push(o)}for(const n of a)n.connect_signals();return a},t.remove_views=function(n){for(const[e,t]of n)t.remove(),n.delete(e)}},\n", - " function _(e,s,_,i,l){i();const t=e(1);var o;const r=e(115),p=(0,t.__importStar)(e(48));class h extends r.UpperLowerView{paint(e){e.beginPath(),e.moveTo(this._lower_sx[0],this._lower_sy[0]);for(let s=0,_=this._lower_sx.length;s<_;s++)e.lineTo(this._lower_sx[s],this._lower_sy[s]);for(let s=this._upper_sx.length-1;s>=0;s--)e.lineTo(this._upper_sx[s],this._upper_sy[s]);e.closePath(),this.visuals.fill.apply(e),e.beginPath(),e.moveTo(this._lower_sx[0],this._lower_sy[0]);for(let s=0,_=this._lower_sx.length;s<_;s++)e.lineTo(this._lower_sx[s],this._lower_sy[s]);this.visuals.line.apply(e),e.beginPath(),e.moveTo(this._upper_sx[0],this._upper_sy[0]);for(let s=0,_=this._upper_sx.length;s<_;s++)e.lineTo(this._upper_sx[s],this._upper_sy[s]);this.visuals.line.apply(e)}}_.BandView=h,h.__name__=\"BandView\";class n extends r.UpperLower{constructor(e){super(e)}}_.Band=n,o=n,n.__name__=\"Band\",o.prototype.default_view=h,o.mixins([p.Line,p.Fill]),o.override({fill_color:\"#fff9ba\",fill_alpha:.4,line_color:\"#cccccc\",line_alpha:.3})},\n", - " function _(e,t,i,s,o){s();const r=e(1);var n;const p=e(69),a=e(20),_=(0,r.__importStar)(e(18));class h extends p.DataAnnotationView{map_data(){const{frame:e}=this.plot_view,t=this.model.dimension,i=this.coordinates.x_scale,s=this.coordinates.y_scale,o=\"height\"==t?s:i,r=\"height\"==t?i:s,n=\"height\"==t?e.bbox.yview:e.bbox.xview,p=\"height\"==t?e.bbox.xview:e.bbox.yview;let a,_,h;a=\"data\"==this.model.properties.lower.units?o.v_compute(this._lower):n.v_compute(this._lower),_=\"data\"==this.model.properties.upper.units?o.v_compute(this._upper):n.v_compute(this._upper),h=\"data\"==this.model.properties.base.units?r.v_compute(this._base):p.v_compute(this._base);const[d,c]=\"height\"==t?[1,0]:[0,1],u=[a,h],l=[_,h];this._lower_sx=u[d],this._lower_sy=u[c],this._upper_sx=l[d],this._upper_sy=l[c]}}i.UpperLowerView=h,h.__name__=\"UpperLowerView\";class d extends _.CoordinateSpec{get dimension(){return\"width\"==this.obj.dimension?\"x\":\"y\"}get units(){var e;return null!==(e=this.spec.units)&&void 0!==e?e:\"data\"}}i.XOrYCoordinateSpec=d,d.__name__=\"XOrYCoordinateSpec\";class c extends p.DataAnnotation{constructor(e){super(e)}}i.UpperLower=c,n=c,c.__name__=\"UpperLower\",n.define((()=>({dimension:[a.Dimension,\"height\"],lower:[d,{field:\"lower\"}],upper:[d,{field:\"upper\"}],base:[d,{field:\"base\"}]})))},\n", - " function _(t,o,i,n,e){n();const s=t(1);var l;const r=t(40),a=(0,s.__importStar)(t(48)),c=t(20),h=t(65);i.EDGE_TOLERANCE=2.5;class b extends r.AnnotationView{constructor(){super(...arguments),this.bbox=new h.BBox}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render()))}_render(){const{left:t,right:o,top:i,bottom:n}=this.model;if(null==t&&null==o&&null==i&&null==n)return;const{frame:e}=this.plot_view,s=this.coordinates.x_scale,l=this.coordinates.y_scale,r=(t,o,i,n,e)=>{let s;return s=null!=t?this.model.screen?t:\"data\"==o?i.compute(t):n.compute(t):e,s};this.bbox=h.BBox.from_rect({left:r(t,this.model.left_units,s,e.bbox.xview,e.bbox.left),right:r(o,this.model.right_units,s,e.bbox.xview,e.bbox.right),top:r(i,this.model.top_units,l,e.bbox.yview,e.bbox.top),bottom:r(n,this.model.bottom_units,l,e.bbox.yview,e.bbox.bottom)}),this._paint_box()}_paint_box(){const{ctx:t}=this.layer;t.save();const{left:o,top:i,width:n,height:e}=this.bbox;t.beginPath(),t.rect(o,i,n,e),this.visuals.fill.apply(t),this.visuals.hatch.apply(t),this.visuals.line.apply(t),t.restore()}interactive_bbox(){const t=this.model.line_width+i.EDGE_TOLERANCE;return this.bbox.grow_by(t)}interactive_hit(t,o){if(null==this.model.in_cursor)return!1;return this.interactive_bbox().contains(t,o)}cursor(t,o){const{left:i,right:n,bottom:e,top:s}=this.bbox;return Math.abs(t-i)<3||Math.abs(t-n)<3?this.model.ew_cursor:Math.abs(o-e)<3||Math.abs(o-s)<3?this.model.ns_cursor:this.bbox.contains(t,o)?this.model.in_cursor:null}}i.BoxAnnotationView=b,b.__name__=\"BoxAnnotationView\";class u extends r.Annotation{constructor(t){super(t)}update({left:t,right:o,top:i,bottom:n}){this.setv({left:t,right:o,top:i,bottom:n,screen:!0})}}i.BoxAnnotation=u,l=u,u.__name__=\"BoxAnnotation\",l.prototype.default_view=b,l.mixins([a.Line,a.Fill,a.Hatch]),l.define((({Number:t,Nullable:o})=>({top:[o(t),null],top_units:[c.SpatialUnits,\"data\"],bottom:[o(t),null],bottom_units:[c.SpatialUnits,\"data\"],left:[o(t),null],left_units:[c.SpatialUnits,\"data\"],right:[o(t),null],right_units:[c.SpatialUnits,\"data\"],render_mode:[c.RenderMode,\"canvas\"]}))),l.internal((({Boolean:t,String:o,Nullable:i})=>({screen:[t,!1],ew_cursor:[i(o),null],ns_cursor:[i(o),null],in_cursor:[i(o),null]}))),l.override({fill_color:\"#fff9ba\",fill_alpha:.4,line_color:\"#cccccc\",line_alpha:.3})},\n", - " function _(t,e,i,o,n){o();const a=t(1);var r;const s=t(40),l=t(118),_=t(126),c=t(127),h=t(130),u=t(168),p=t(131),m=t(192),g=t(132),d=t(173),f=t(172),w=t(196),b=t(204),v=t(206),x=t(133),y=t(20),k=(0,a.__importStar)(t(48)),z=t(9),j=t(207),C=t(208),L=t(211),B=t(123),S=t(11),M=t(113),T=t(65),A=t(8);class O extends s.AnnotationView{get orientation(){return this._orientation}initialize(){super.initialize();const{ticker:t,formatter:e,color_mapper:i}=this.model;this._ticker=\"auto\"!=t?t:(()=>{switch(!0){case i instanceof w.LogColorMapper:return new u.LogTicker;case i instanceof w.ScanningColorMapper:return new u.BinnedTicker({mapper:i});case i instanceof w.CategoricalColorMapper:return new u.CategoricalTicker;default:return new u.BasicTicker}})(),this._formatter=\"auto\"!=e?e:(()=>{switch(!0){case this._ticker instanceof u.LogTicker:return new m.LogTickFormatter;case i instanceof w.CategoricalColorMapper:return new m.CategoricalTickFormatter;default:return new m.BasicTickFormatter}})(),this._major_range=(()=>{if(i instanceof w.CategoricalColorMapper){const{factors:t}=i;return new v.FactorRange({factors:t})}if(i instanceof f.ContinuousColorMapper){const{min:t,max:e}=i.metrics;return new v.Range1d({start:t,end:e})}(0,S.unreachable)()})(),this._major_scale=(()=>{if(i instanceof w.LinearColorMapper)return new b.LinearScale;if(i instanceof w.LogColorMapper)return new b.LogScale;if(i instanceof w.ScanningColorMapper){const{binning:t}=i.metrics;return new b.LinearInterpolationScale({binning:t})}if(i instanceof w.CategoricalColorMapper)return new b.CategoricalScale;(0,S.unreachable)()})(),this._minor_range=new v.Range1d({start:0,end:1}),this._minor_scale=new b.LinearScale;const o=k.attrs_of(this.model,\"major_label_\",k.Text,!0),n=k.attrs_of(this.model,\"major_tick_\",k.Line,!0),a=k.attrs_of(this.model,\"minor_tick_\",k.Line,!0),r=k.attrs_of(this.model,\"title_\",k.Text),s=i instanceof w.CategoricalColorMapper?c.CategoricalAxis:i instanceof w.LogColorMapper?c.LogAxis:c.LinearAxis;this._axis=new s(Object.assign(Object.assign(Object.assign({ticker:this._ticker,formatter:this._formatter,major_tick_in:this.model.major_tick_in,major_tick_out:this.model.major_tick_out,minor_tick_in:this.model.minor_tick_in,minor_tick_out:this.model.minor_tick_out,major_label_standoff:this.model.label_standoff,major_label_overrides:this.model.major_label_overrides,major_label_policy:this.model.major_label_policy,axis_line_color:null},o),n),a));const{title:_}=this.model;_&&(this._title=new l.Title(Object.assign({text:_,standoff:this.model.title_standoff},r)))}async lazy_initialize(){await super.lazy_initialize();const t=this,e={get parent(){return t.parent},get root(){return t.root},get frame(){return t._frame},get canvas_view(){return t.parent.canvas_view},request_layout(){t.parent.request_layout()}};this._axis_view=await(0,M.build_view)(this._axis,{parent:e}),null!=this._title&&(this._title_view=await(0,M.build_view)(this._title,{parent:e}))}remove(){var t;null===(t=this._title_view)||void 0===t||t.remove(),this._axis_view.remove(),super.remove()}connect_signals(){super.connect_signals(),this.connect(this._ticker.change,(()=>this.request_render())),this.connect(this._formatter.change,(()=>this.request_render())),this.connect(this.model.color_mapper.metrics_change,(()=>{const t=this._major_range,e=this._major_scale,{color_mapper:i}=this.model;if(i instanceof f.ContinuousColorMapper&&t instanceof v.Range1d){const{min:e,max:o}=i.metrics;t.setv({start:e,end:o})}if(i instanceof w.ScanningColorMapper&&e instanceof b.LinearInterpolationScale){const{binning:t}=i.metrics;e.binning=t}this._set_canvas_image(),this.plot_view.request_layout()}))}_set_canvas_image(){const{orientation:t}=this,e=(()=>{const{palette:e}=this.model.color_mapper;return\"vertical\"==t?(0,z.reversed)(e):e})(),[i,o]=\"vertical\"==t?[1,e.length]:[e.length,1],n=this._image=document.createElement(\"canvas\");n.width=i,n.height=o;const a=n.getContext(\"2d\"),r=a.getImageData(0,0,i,o),s=new w.LinearColorMapper({palette:e}).rgba_mapper.v_compute((0,z.range)(0,e.length));r.data.set(s),a.putImageData(r,0,0)}update_layout(){const{location:t,width:e,height:i,padding:o,margin:n}=this.model,[a,r]=(()=>{if(!(0,A.isString)(t))return[\"end\",\"start\"];switch(t){case\"top_left\":return[\"start\",\"start\"];case\"top\":case\"top_center\":return[\"start\",\"center\"];case\"top_right\":return[\"start\",\"end\"];case\"bottom_left\":return[\"end\",\"start\"];case\"bottom\":case\"bottom_center\":return[\"end\",\"center\"];case\"bottom_right\":return[\"end\",\"end\"];case\"left\":case\"center_left\":return[\"center\",\"start\"];case\"center\":case\"center_center\":return[\"center\",\"center\"];case\"right\":case\"center_right\":return[\"center\",\"end\"]}})(),s=this._orientation=(()=>{const{orientation:t}=this.model;return\"auto\"==t?null!=this.panel?this.panel.is_horizontal?\"horizontal\":\"vertical\":\"start\"==r||\"end\"==r||\"center\"==r&&\"center\"==a?\"vertical\":\"horizontal\":t})(),l=new C.NodeLayout,c=new C.VStack,h=new C.VStack,u=new C.HStack,p=new C.HStack;l.absolute=!0,c.absolute=!0,h.absolute=!0,u.absolute=!0,p.absolute=!0;const[m,g,d,f]=(()=>\"horizontal\"==s?[this._major_scale,this._minor_scale,this._major_range,this._minor_range]:[this._minor_scale,this._major_scale,this._minor_range,this._major_range])();this._frame=new _.CartesianFrame(m,g,d,f),l.on_resize((t=>this._frame.set_geometry(t)));const w=new L.BorderLayout;this._inner_layout=w,w.absolute=!0,w.center_panel=l,w.top_panel=c,w.bottom_panel=h,w.left_panel=u,w.right_panel=p;const b={left:o,right:o,top:o,bottom:o},v=(()=>{if(null==this.panel){if((0,A.isString)(t))return{left:n,right:n,top:n,bottom:n};{const[e,i]=t;return{left:e,right:n,top:n,bottom:i}}}if(!(0,A.isString)(t)){const[e,i]=t;return w.fixup_geometry=(t,o)=>{const n=t,a=this.layout.bbox,{width:r,height:s}=t;if(t=new T.BBox({left:a.left+e,bottom:a.bottom-i,width:r,height:s}),null!=o){const e=t.left-n.left,i=t.top-n.top,{left:a,top:r,width:s,height:l}=o;o=new T.BBox({left:a+e,top:r+i,width:s,height:l})}return[t,o]},{left:e,right:0,top:0,bottom:i}}w.fixup_geometry=(t,e)=>{const i=t;if(\"horizontal\"==s){const{top:e,width:i,height:o}=t;if(\"end\"==r){const{right:n}=this.layout.bbox;t=new T.BBox({right:n,top:e,width:i,height:o})}else if(\"center\"==r){const{hcenter:n}=this.layout.bbox;t=new T.BBox({hcenter:Math.round(n),top:e,width:i,height:o})}}else{const{left:e,width:i,height:o}=t;if(\"end\"==a){const{bottom:n}=this.layout.bbox;t=new T.BBox({left:e,bottom:n,width:i,height:o})}else if(\"center\"==a){const{vcenter:n}=this.layout.bbox;t=new T.BBox({left:e,vcenter:Math.round(n),width:i,height:o})}}if(null!=e){const o=t.left-i.left,n=t.top-i.top,{left:a,top:r,width:s,height:l}=e;e=new T.BBox({left:a+o,top:r+n,width:s,height:l})}return[t,e]}})();let x,y,k,z;if(w.padding=b,null!=this.panel?(x=\"max\",y=void 0,k=void 0,z=void 0):\"auto\"==(\"horizontal\"==s?e:i)?(x=\"fixed\",y=25*this.model.color_mapper.palette.length,k={percent:.3},z={percent:.8}):(x=\"fit\",y=void 0),\"horizontal\"==s){const t=\"auto\"==e?void 0:e,o=\"auto\"==i?25:i;w.set_sizing({width_policy:x,height_policy:\"min\",width:y,min_width:k,max_width:z,halign:r,valign:a,margin:v}),w.center_panel.set_sizing({width_policy:\"auto\"==e?\"fit\":\"fixed\",height_policy:\"fixed\",width:t,height:o})}else{const t=\"auto\"==e?25:e,o=\"auto\"==i?void 0:i;w.set_sizing({width_policy:\"min\",height_policy:x,height:y,min_height:k,max_height:z,halign:r,valign:a,margin:v}),w.center_panel.set_sizing({width_policy:\"fixed\",height_policy:\"auto\"==i?\"fit\":\"fixed\",width:t,height:o})}c.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),h.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),u.set_sizing({width_policy:\"min\",height_policy:\"fit\"}),p.set_sizing({width_policy:\"min\",height_policy:\"fit\"});const{_title_view:S}=this;null!=S&&(\"horizontal\"==s?(S.panel=new B.Panel(\"above\"),S.update_layout(),c.children.push(S.layout)):(S.panel=new B.Panel(\"left\"),S.update_layout(),u.children.push(S.layout)));const{panel:M}=this,O=null!=M&&s==M.orientation?M.side:\"horizontal\"==s?\"below\":\"right\",R=(()=>{switch(O){case\"above\":return c;case\"below\":return h;case\"left\":return u;case\"right\":return p}})(),{_axis_view:F}=this;if(F.panel=new B.Panel(O),F.update_layout(),R.children.push(F.layout),null!=this.panel){const t=new j.Grid([{layout:w,row:0,col:0}]);t.absolute=!0,\"horizontal\"==s?t.set_sizing({width_policy:\"max\",height_policy:\"min\"}):t.set_sizing({width_policy:\"min\",height_policy:\"max\"}),this.layout=t}else this.layout=this._inner_layout;const{visible:I}=this.model;this.layout.sizing.visible=I,this._set_canvas_image()}_render(){var t;const{ctx:e}=this.layer;e.save(),this._paint_bbox(e,this._inner_layout.bbox),this._paint_image(e,this._inner_layout.center_panel.bbox),null===(t=this._title_view)||void 0===t||t.render(),this._axis_view.render(),e.restore()}_paint_bbox(t,e){const{x:i,y:o}=e;let{width:n,height:a}=e;i+n>=this.parent.canvas_view.bbox.width&&(n-=1),o+a>=this.parent.canvas_view.bbox.height&&(a-=1),t.save(),this.visuals.background_fill.doit&&(this.visuals.background_fill.set_value(t),t.fillRect(i,o,n,a)),this.visuals.border_line.doit&&(this.visuals.border_line.set_value(t),t.strokeRect(i,o,n,a)),t.restore()}_paint_image(t,e){const{x:i,y:o,width:n,height:a}=e;t.save(),t.setImageSmoothingEnabled(!1),t.globalAlpha=this.model.scale_alpha,t.drawImage(this._image,i,o,n,a),this.visuals.bar_line.doit&&(this.visuals.bar_line.set_value(t),t.strokeRect(i,o,n,a)),t.restore()}serializable_state(){const t=super.serializable_state(),{children:e=[]}=t,i=(0,a.__rest)(t,[\"children\"]);return null!=this._title_view&&e.push(this._title_view.serializable_state()),e.push(this._axis_view.serializable_state()),Object.assign(Object.assign({},i),{children:e})}}i.ColorBarView=O,O.__name__=\"ColorBarView\";class R extends s.Annotation{constructor(t){super(t)}}i.ColorBar=R,r=R,R.__name__=\"ColorBar\",r.prototype.default_view=O,r.mixins([[\"major_label_\",k.Text],[\"title_\",k.Text],[\"major_tick_\",k.Line],[\"minor_tick_\",k.Line],[\"border_\",k.Line],[\"bar_\",k.Line],[\"background_\",k.Fill]]),r.define((({Alpha:t,Number:e,String:i,Tuple:o,Dict:n,Or:a,Ref:r,Auto:s,Nullable:l})=>({location:[a(y.Anchor,o(e,e)),\"top_right\"],orientation:[a(y.Orientation,s),\"auto\"],title:[l(i),null],title_standoff:[e,2],width:[a(e,s),\"auto\"],height:[a(e,s),\"auto\"],scale_alpha:[t,1],ticker:[a(r(h.Ticker),s),\"auto\"],formatter:[a(r(p.TickFormatter),s),\"auto\"],major_label_overrides:[n(a(i,r(x.BaseText))),{}],major_label_policy:[r(g.LabelingPolicy),()=>new g.NoOverlap],color_mapper:[r(d.ColorMapper)],label_standoff:[e,5],margin:[e,30],padding:[e,10],major_tick_in:[e,5],major_tick_out:[e,0],minor_tick_in:[e,0],minor_tick_out:[e,0]}))),r.override({background_fill_color:\"#ffffff\",background_fill_alpha:.95,bar_line_color:null,border_line_color:null,major_label_text_font_size:\"11px\",major_tick_line_color:\"#ffffff\",minor_tick_line_color:null,title_text_font_size:\"13px\",title_text_font_style:\"italic\"})},\n", - " function _(t,e,i,s,l){s();const o=t(1);var a;const n=t(119),r=t(20),c=t(120),h=(0,o.__importStar)(t(48));class _ extends n.TextAnnotationView{_get_location(){const t=this.model.offset,e=this.model.standoff/2;let i,s;const{bbox:l}=this.layout;switch(this.panel.side){case\"above\":case\"below\":switch(this.model.vertical_align){case\"top\":s=l.top+e;break;case\"middle\":s=l.vcenter;break;case\"bottom\":s=l.bottom-e}switch(this.model.align){case\"left\":i=l.left+t;break;case\"center\":i=l.hcenter;break;case\"right\":i=l.right-t}break;case\"left\":switch(this.model.vertical_align){case\"top\":i=l.left+e;break;case\"middle\":i=l.hcenter;break;case\"bottom\":i=l.right-e}switch(this.model.align){case\"left\":s=l.bottom-t;break;case\"center\":s=l.vcenter;break;case\"right\":s=l.top+t}break;case\"right\":switch(this.model.vertical_align){case\"top\":i=l.right-e;break;case\"middle\":i=l.hcenter;break;case\"bottom\":i=l.left+e}switch(this.model.align){case\"left\":s=l.top+t;break;case\"center\":s=l.vcenter;break;case\"right\":s=l.bottom-t}}return[i,s]}_render(){const{text:t}=this.model;if(null==t||0==t.length)return;this.model.text_baseline=this.model.vertical_align,this.model.text_align=this.model.align;const[e,i]=this._get_location(),s=this.panel.get_label_angle_heuristic(\"parallel\");(\"canvas\"==this.model.render_mode?this._canvas_text.bind(this):this._css_text.bind(this))(this.layer.ctx,t,e,i,s)}_get_size(){const{text:t}=this.model,e=new c.TextBox({text:t});e.visuals=this.visuals.text.values();const{width:i,height:s}=e.size();return{width:i,height:0==s?0:2+s+this.model.standoff}}}i.TitleView=_,_.__name__=\"TitleView\";class d extends n.TextAnnotation{constructor(t){super(t)}}i.Title=d,a=d,d.__name__=\"Title\",a.prototype.default_view=_,a.mixins([h.Text,[\"border_\",h.Line],[\"background_\",h.Fill]]),a.define((({Number:t,String:e})=>({text:[e,\"\"],vertical_align:[r.VerticalAlign,\"bottom\"],align:[r.TextAlign,\"left\"],offset:[t,0],standoff:[t,10]}))),a.prototype._props.text_align.options.internal=!0,a.prototype._props.text_baseline.options.internal=!0,a.override({text_font_size:\"13px\",text_font_style:\"bold\",text_line_height:1,background_fill_color:null,border_line_color:null})},\n", - " function _(e,t,s,i,l){var n;i();const o=e(40),a=e(43),r=e(20),d=e(120),u=e(123),c=e(11);class h extends o.AnnotationView{update_layout(){const{panel:e}=this;this.layout=null!=e?new u.SideLayout(e,(()=>this.get_size()),!0):void 0}initialize(){super.initialize(),\"css\"==this.model.render_mode&&(this.el=(0,a.div)(),this.plot_view.canvas_view.add_overlay(this.el))}remove(){null!=this.el&&(0,a.remove)(this.el),super.remove()}connect_signals(){super.connect_signals(),\"css\"==this.model.render_mode?this.connect(this.model.change,(()=>this.render())):this.connect(this.model.change,(()=>this.request_render()))}render(){this.model.visible||\"css\"!=this.model.render_mode||(0,a.undisplay)(this.el),super.render()}_canvas_text(e,t,s,i,l){const n=new d.TextBox({text:t});n.angle=l,n.position={sx:s,sy:i},n.visuals=this.visuals.text.values();const{background_fill:o,border_line:a}=this.visuals;if(o.doit||a.doit){const{p0:t,p1:s,p2:i,p3:l}=n.rect();e.beginPath(),e.moveTo(t.x,t.y),e.lineTo(s.x,s.y),e.lineTo(i.x,i.y),e.lineTo(l.x,l.y),e.closePath(),this.visuals.background_fill.apply(e),this.visuals.border_line.apply(e)}this.visuals.text.doit&&n.paint(e)}_css_text(e,t,s,i,l){const{el:n}=this;(0,c.assert)(null!=n),(0,a.undisplay)(n),n.textContent=t,this.visuals.text.set_value(e),n.style.position=\"absolute\",n.style.left=`${s}px`,n.style.top=`${i}px`,n.style.color=e.fillStyle,n.style.font=e.font,n.style.lineHeight=\"normal\",n.style.whiteSpace=\"pre\";const[o,r]=(()=>{switch(this.visuals.text.text_align.get_value()){case\"left\":return[\"left\",\"0%\"];case\"center\":return[\"center\",\"-50%\"];case\"right\":return[\"right\",\"-100%\"]}})(),[d,u]=(()=>{switch(this.visuals.text.text_baseline.get_value()){case\"top\":return[\"top\",\"0%\"];case\"middle\":return[\"center\",\"-50%\"];case\"bottom\":return[\"bottom\",\"-100%\"];default:return[\"center\",\"-50%\"]}})();let h=`translate(${r}, ${u})`;l&&(h+=`rotate(${l}rad)`),n.style.transformOrigin=`${o} ${d}`,n.style.transform=h,this.layout,this.visuals.background_fill.doit&&(this.visuals.background_fill.set_value(e),n.style.backgroundColor=e.fillStyle),this.visuals.border_line.doit&&(this.visuals.border_line.set_value(e),n.style.borderStyle=e.lineDash.length<2?\"solid\":\"dashed\",n.style.borderWidth=`${e.lineWidth}px`,n.style.borderColor=e.strokeStyle),(0,a.display)(n)}}s.TextAnnotationView=h,h.__name__=\"TextAnnotationView\";class _ extends o.Annotation{constructor(e){super(e)}}s.TextAnnotation=_,n=_,_.__name__=\"TextAnnotation\",n.define((()=>({render_mode:[r.RenderMode,\"canvas\"]})))},\n", - " function _(t,e,s,i,n){i();const h=t(65),o=t(121),r=t(9),a=t(8),c=t(122),_=t(22);s.text_width=(()=>{const t=document.createElement(\"canvas\").getContext(\"2d\");let e=\"\";return(s,i)=>(i!=e&&(e=i,t.font=i),t.measureText(s).width)})();class l{constructor(){this._position={sx:0,sy:0},this.font_size_scale=1,this.align=\"left\",this._base_font_size=13,this._x_anchor=\"left\",this._y_anchor=\"center\"}set base_font_size(t){null!=t&&(this._base_font_size=t)}get base_font_size(){return this._base_font_size}set position(t){this._position=t}get position(){return this._position}infer_text_height(){return\"ascent_descent\"}bbox(){const{p0:t,p1:e,p2:s,p3:i}=this.rect(),n=Math.min(t.x,e.x,s.x,i.x),o=Math.min(t.y,e.y,s.y,i.y),r=Math.max(t.x,e.x,s.x,i.x),a=Math.max(t.y,e.y,s.y,i.y);return new h.BBox({left:n,right:r,top:o,bottom:a})}size(){const{width:t,height:e}=this._size(),{angle:s}=this;if(s){const i=Math.cos(Math.abs(s)),n=Math.sin(Math.abs(s));return{width:Math.abs(t*i+e*n),height:Math.abs(t*n+e*i)}}return{width:t,height:e}}rect(){const t=this._rect(),{angle:e}=this;if(e){const{sx:s,sy:i}=this.position,n=new c.AffineTransform;return n.translate(s,i),n.rotate(e),n.translate(-s,-i),n.apply_rect(t)}return t}paint_rect(t){const{p0:e,p1:s,p2:i,p3:n}=this.rect();t.save(),t.strokeStyle=\"red\",t.lineWidth=1,t.beginPath();const{round:h}=Math;t.moveTo(h(e.x),h(e.y)),t.lineTo(h(s.x),h(s.y)),t.lineTo(h(i.x),h(i.y)),t.lineTo(h(n.x),h(n.y)),t.closePath(),t.stroke(),t.restore()}paint_bbox(t){const{x:e,y:s,width:i,height:n}=this.bbox();t.save(),t.strokeStyle=\"blue\",t.lineWidth=1,t.beginPath();const{round:h}=Math;t.moveTo(h(e),h(s)),t.lineTo(h(e),h(s+n)),t.lineTo(h(e+i),h(s+n)),t.lineTo(h(e+i),h(s)),t.closePath(),t.stroke(),t.restore()}}s.GraphicsBox=l,l.__name__=\"GraphicsBox\";class x extends l{constructor({text:t}){super(),this.text=t}set visuals(t){const e=t.color,s=t.alpha,i=t.font_style;let n=t.font_size;const h=t.font,{font_size_scale:r,base_font_size:a}=this,c=(0,o.parse_css_font_size)(n);if(null!=c){let{value:t,unit:e}=c;t*=r,\"em\"==e&&a&&(t*=a,e=\"px\"),n=`${t}${e}`}const l=`${i} ${n} ${h}`;this.font=l,this.color=(0,_.color2css)(e,s),this.line_height=t.line_height;const x=t.align;this._x_anchor=x;const u=t.baseline;this._y_anchor=(()=>{switch(u){case\"top\":return\"top\";case\"middle\":return\"center\";case\"bottom\":return\"bottom\";default:return\"baseline\"}})()}infer_text_height(){if(this.text.includes(\"\\n\"))return\"ascent_descent\";{function t(t){for(const e of new Set(t))if(!(\"0\"<=e&&e<=\"9\"))switch(e){case\",\":case\".\":case\"+\":case\"-\":case\"\\u2212\":case\"e\":continue;default:return!1}return!0}return t(this.text)?\"cap\":\"ascent_descent\"}}_text_line(t){var e;const s=null!==(e=this.text_height_metric)&&void 0!==e?e:this.infer_text_height(),i=(()=>{switch(s){case\"x\":case\"x_descent\":return t.x_height;case\"cap\":case\"cap_descent\":return t.cap_height;case\"ascent\":case\"ascent_descent\":return t.ascent}})(),n=(()=>{switch(s){case\"x\":case\"cap\":case\"ascent\":return 0;case\"x_descent\":case\"cap_descent\":case\"ascent_descent\":return t.descent}})();return{height:i+n,ascent:i,descent:n}}get nlines(){return this.text.split(\"\\n\").length}_size(){var t,e;const{font:i}=this,n=(0,o.font_metrics)(i),h=(this.line_height-1)*n.height,a=\"\"==this.text,c=this.text.split(\"\\n\"),_=c.length,l=c.map((t=>(0,s.text_width)(t,i))),x=this._text_line(n).height*_,u=\"%\"==(null===(t=this.width)||void 0===t?void 0:t.unit)?this.width.value:1,p=\"%\"==(null===(e=this.height)||void 0===e?void 0:e.unit)?this.height.value:1;return{width:(0,r.max)(l)*u,height:a?0:(x+h*(_-1))*p,metrics:n}}_computed_position(t,e,s){const{width:i,height:n}=t,{sx:h,sy:o,x_anchor:r=this._x_anchor,y_anchor:c=this._y_anchor}=this.position;return{x:h-(()=>{if((0,a.isNumber)(r))return r*i;switch(r){case\"left\":return 0;case\"center\":return.5*i;case\"right\":return i}})(),y:o-(()=>{var t;if((0,a.isNumber)(c))return c*n;switch(c){case\"top\":return 0;case\"center\":return.5*n;case\"bottom\":return n;case\"baseline\":if(1!=s)return.5*n;switch(null!==(t=this.text_height_metric)&&void 0!==t?t:this.infer_text_height()){case\"x\":case\"x_descent\":return e.x_height;case\"cap\":case\"cap_descent\":return e.cap_height;case\"ascent\":case\"ascent_descent\":return e.ascent}}})()}}_rect(){const{width:t,height:e,metrics:s}=this._size(),i=this.text.split(\"\\n\").length,{x:n,y:o}=this._computed_position({width:t,height:e},s,i);return new h.BBox({x:n,y:o,width:t,height:e}).rect}paint(t){var e,i;const{font:n}=this,h=(0,o.font_metrics)(n),a=(this.line_height-1)*h.height,c=this.text.split(\"\\n\"),_=c.length,l=c.map((t=>(0,s.text_width)(t,n))),x=this._text_line(h),u=x.height*_,p=\"%\"==(null===(e=this.width)||void 0===e?void 0:e.unit)?this.width.value:1,f=\"%\"==(null===(i=this.height)||void 0===i?void 0:i.unit)?this.height.value:1,g=(0,r.max)(l)*p,d=(u+a*(_-1))*f;t.save(),t.fillStyle=this.color,t.font=this.font,t.textAlign=\"left\",t.textBaseline=\"alphabetic\";const{sx:b,sy:m}=this.position,{align:y}=this,{angle:w}=this;w&&(t.translate(b,m),t.rotate(w),t.translate(-b,-m));let{x:v,y:z}=this._computed_position({width:g,height:d},h,_);if(\"justify\"==y)for(let e=0;e<_;e++){let i=v;const h=c[e].split(\" \"),o=h.length,_=h.map((t=>(0,s.text_width)(t,n))),l=(g-(0,r.sum)(_))/(o-1);for(let e=0;e{switch(y){case\"left\":return 0;case\"center\":return.5*(g-l[e]);case\"right\":return g-l[e]}})();t.fillStyle=this.color,t.fillText(c[e],s,z+x.ascent),z+=x.height+a}t.restore()}}s.TextBox=x,x.__name__=\"TextBox\";class u extends l{constructor(t,e){super(),this.base=t,this.expo=e}get children(){return[this.base,this.expo]}set base_font_size(t){super.base_font_size=t,this.base.base_font_size=t,this.expo.base_font_size=t}set position(t){this._position=t;const e=this.base.size(),s=this.expo.size(),i=this._shift_scale()*e.height,n=Math.max(e.height,i+s.height);this.base.position={sx:0,x_anchor:\"left\",sy:n,y_anchor:\"bottom\"},this.expo.position={sx:e.width,x_anchor:\"left\",sy:i,y_anchor:\"bottom\"}}get position(){return this._position}set visuals(t){this.expo.font_size_scale=.7,this.base.visuals=t,this.expo.visuals=t}_shift_scale(){if(this.base instanceof x&&1==this.base.nlines){const{x_height:t,cap_height:e}=(0,o.font_metrics)(this.base.font);return t/e}return 2/3}infer_text_height(){return this.base.infer_text_height()}_rect(){const t=this.base.bbox(),e=this.expo.bbox(),s=t.union(e),{x:i,y:n}=this._computed_position();return s.translate(i,n).rect}_size(){const t=this.base.size(),e=this.expo.size();return{width:t.width+e.width,height:Math.max(t.height,this._shift_scale()*t.height+e.height)}}paint(t){t.save();const{angle:e}=this;if(e){const{sx:s,sy:i}=this.position;t.translate(s,i),t.rotate(e),t.translate(-s,-i)}const{x:s,y:i}=this._computed_position();t.translate(s,i),this.base.paint(t),this.expo.paint(t),t.restore()}paint_bbox(t){super.paint_bbox(t);const{x:e,y:s}=this._computed_position();t.save(),t.translate(e,s);for(const e of this.children)e.paint_bbox(t);t.restore()}_computed_position(){const{width:t,height:e}=this._size(),{sx:s,sy:i,x_anchor:n=this._x_anchor,y_anchor:h=this._y_anchor}=this.position;return{x:s-(()=>{if((0,a.isNumber)(n))return n*t;switch(n){case\"left\":return 0;case\"center\":return.5*t;case\"right\":return t}})(),y:i-(()=>{if((0,a.isNumber)(h))return h*e;switch(h){case\"top\":return 0;case\"center\":return.5*e;case\"bottom\":return e;case\"baseline\":return.5*e}})()}}}s.BaseExpo=u,u.__name__=\"BaseExpo\";class p{constructor(t){this.items=t}set base_font_size(t){for(const e of this.items)e.base_font_size=t}get length(){return this.items.length}set visuals(t){for(const e of this.items)e.visuals=t;const e={x:0,cap:1,ascent:2,x_descent:3,cap_descent:4,ascent_descent:5},s=(0,r.max_by)(this.items.map((t=>t.infer_text_height())),(t=>e[t]));for(const t of this.items)t.text_height_metric=s}set angle(t){for(const e of this.items)e.angle=t}max_size(){let t=0,e=0;for(const s of this.items){const i=s.size();t=Math.max(t,i.width),e=Math.max(e,i.height)}return{width:t,height:e}}}s.GraphicsBoxes=p,p.__name__=\"GraphicsBoxes\"},\n", - " function _(t,e,n,r,l){r();const a=t(11),c=(()=>{try{return\"undefined\"!=typeof OffscreenCanvas&&null!=new OffscreenCanvas(0,0).getContext(\"2d\")}catch(t){return!1}})()?(t,e)=>new OffscreenCanvas(t,e):(t,e)=>{const n=document.createElement(\"canvas\");return n.width=t,n.height=e,n},o=(()=>{const t=c(0,0).getContext(\"2d\");return e=>{t.font=e;const n=t.measureText(\"M\"),r=t.measureText(\"x\"),l=t.measureText(\"\\xc5\\u015ag|\"),c=l.fontBoundingBoxAscent,o=l.fontBoundingBoxDescent;if(null!=c&&null!=o)return{height:c+o,ascent:c,descent:o,cap_height:n.actualBoundingBoxAscent,x_height:r.actualBoundingBoxAscent};const s=l.actualBoundingBoxAscent,u=l.actualBoundingBoxDescent;if(null!=s&&null!=u)return{height:s+u,ascent:s,descent:u,cap_height:n.actualBoundingBoxAscent,x_height:r.actualBoundingBoxAscent};(0,a.unreachable)()}})(),s=(()=>{const t=c(0,0).getContext(\"2d\");return(e,n)=>{t.font=n;const r=t.measureText(e),l=r.actualBoundingBoxAscent,c=r.actualBoundingBoxDescent;if(null!=l&&null!=c)return{width:r.width,height:l+c,ascent:l,descent:c};(0,a.unreachable)()}})(),u=(()=>{const t=document.createElement(\"canvas\"),e=t.getContext(\"2d\");let n=-1,r=-1;return(l,a=1)=>{e.font=l;const{width:c}=e.measureText(\"M\"),o=c*a,s=Math.ceil(o),u=Math.ceil(2*o),i=Math.ceil(1.5*o);n{let e=0;for(let n=0;n<=i;n++)for(let r=0;r{let e=t.length-4;for(let n=u;n>=i;n--)for(let r=0;r{const t=document.createElement(\"canvas\"),e=t.getContext(\"2d\");let n=-1,r=-1;return(l,a,c=1)=>{e.font=a;const{width:o}=e.measureText(\"M\"),s=o*c,u=Math.ceil(s),i=Math.ceil(2*s),f=Math.ceil(1.5*s);(n{let e=0;for(let n=0;n<=f;n++)for(let r=0;r{let e=t.length-4;for(let n=i;n>=f;n--)for(let r=0;r{try{return o(\"normal 10px sans-serif\"),o}catch(t){return u}})(),h=(()=>{try{return s(\"A\",\"normal 10px sans-serif\"),s}catch(t){return i}})(),g=new Map;function d(t){let e=g.get(t);return null==e&&(e={font:f(t),glyphs:new Map},g.set(t,e)),e.font}n.font_metrics=d,n.glyph_metrics=function(t,e){let n=g.get(e);null==n&&(d(e),n=g.get(e));let r=n.glyphs.get(t);return null==r&&(r=h(t,e),n.glyphs.set(t,r)),r},n.parse_css_font_size=function(t){const e=t.match(/^\\s*(\\d+(\\.\\d+)?)(\\w+)\\s*$/);if(null!=e){const[,t,,n]=e,r=Number(t);if(isFinite(r))return{value:r,unit:n}}return null}},\n", - " function _(t,s,r,n,i){n();const{sin:e,cos:a}=Math;class h{constructor(t=1,s=0,r=0,n=1,i=0,e=0){this.a=t,this.b=s,this.c=r,this.d=n,this.e=i,this.f=e}toString(){const{a:t,b:s,c:r,d:n,e:i,f:e}=this;return`matrix(${t}, ${s}, ${r}, ${n}, ${i}, ${e})`}static from_DOMMatrix(t){const{a:s,b:r,c:n,d:i,e,f:a}=t;return new h(s,r,n,i,e,a)}to_DOMMatrix(){const{a:t,b:s,c:r,d:n,e:i,f:e}=this;return new DOMMatrix([t,s,r,n,i,e])}clone(){const{a:t,b:s,c:r,d:n,e:i,f:e}=this;return new h(t,s,r,n,i,e)}get is_identity(){const{a:t,b:s,c:r,d:n,e:i,f:e}=this;return 1==t&&0==s&&0==r&&1==n&&0==i&&0==e}apply_point(t){const[s,r]=this.apply(t.x,t.y);return{x:s,y:r}}apply_rect(t){return{p0:this.apply_point(t.p0),p1:this.apply_point(t.p1),p2:this.apply_point(t.p2),p3:this.apply_point(t.p3)}}apply(t,s){const{a:r,b:n,c:i,d:e,e:a,f:h}=this;return[r*t+i*s+a,n*t+e*s+h]}iv_apply(t,s){const{a:r,b:n,c:i,d:e,e:a,f:h}=this,c=t.length;for(let o=0;o{const h={max:4,fit:3,min:2,fixed:1};return h[i]>h[t]};if(\"fixed\"!=n&&\"fixed\"!=s)if(n==s){const n=t,s=_(t/e),r=_(h*e),g=h;Math.abs(i.width-n)+Math.abs(i.height-s)<=Math.abs(i.width-r)+Math.abs(i.height-g)?(t=n,h=s):(t=r,h=g)}else r(n,s)?h=_(t/e):t=_(h*e);else\"fixed\"==n?h=_(t/e):\"fixed\"==s&&(t=_(h*e))}return{width:t,height:h}}measure(i){if(!this.sizing.visible)return{width:0,height:0};const t=i=>\"fixed\"==this.sizing.width_policy&&null!=this.sizing.width?this.sizing.width:i,h=i=>\"fixed\"==this.sizing.height_policy&&null!=this.sizing.height?this.sizing.height:i,e=new s.Sizeable(i).shrink_by(this.sizing.margin).map(t,h),n=this._measure(e),r=this.clip_size(n,e),g=t(r.width),l=h(r.height),a=this.apply_aspect(e,{width:g,height:l});return Object.assign(Object.assign({},n),a)}compute(i={}){const t=this.measure({width:null!=i.width&&this.is_width_expanding()?i.width:1/0,height:null!=i.height&&this.is_height_expanding()?i.height:1/0}),{width:h,height:e}=t,n=new r.BBox({left:0,top:0,width:h,height:e});let s;if(null!=t.inner){const{left:i,top:n,right:g,bottom:l}=t.inner;s=new r.BBox({left:i,top:n,right:h-g,bottom:e-l})}this.set_geometry(n,s)}get xview(){return this.bbox.xview}get yview(){return this.bbox.yview}clip_size(i,t){function h(i,t,h,e){return null==h?h=0:(0,g.isNumber)(h)||(h=Math.round(h.percent*t)),null==e?e=1/0:(0,g.isNumber)(e)||(e=Math.round(e.percent*t)),a(h,l(i,e))}return{width:h(i.width,t.width,this.sizing.min_width,this.sizing.max_width),height:h(i.height,t.height,this.sizing.min_height,this.sizing.max_height)}}has_size_changed(){const{_dirty:i}=this;return this._dirty=!1,i}}h.Layoutable=o,o.__name__=\"Layoutable\";class d extends o{_measure(i){const{width_policy:t,height_policy:h}=this.sizing;return{width:(()=>{const{width:h}=this.sizing;if(i.width==1/0)return null!=h?h:0;switch(t){case\"fixed\":return null!=h?h:0;case\"min\":return null!=h?l(i.width,h):0;case\"fit\":return null!=h?l(i.width,h):i.width;case\"max\":return null!=h?a(i.width,h):i.width}})(),height:(()=>{const{height:t}=this.sizing;if(i.height==1/0)return null!=t?t:0;switch(h){case\"fixed\":return null!=t?t:0;case\"min\":return null!=t?l(i.height,t):0;case\"fit\":return null!=t?l(i.height,t):i.height;case\"max\":return null!=t?a(i.height,t):i.height}})()}}}h.LayoutItem=d,d.__name__=\"LayoutItem\";class u extends o{_measure(i){const t=this._content_size(),h=i.bounded_to(this.sizing.size).bounded_to(t);return{width:(()=>{switch(this.sizing.width_policy){case\"fixed\":return null!=this.sizing.width?this.sizing.width:t.width;case\"min\":return t.width;case\"fit\":return h.width;case\"max\":return Math.max(t.width,h.width)}})(),height:(()=>{switch(this.sizing.height_policy){case\"fixed\":return null!=this.sizing.height?this.sizing.height:t.height;case\"min\":return t.height;case\"fit\":return h.height;case\"max\":return Math.max(t.height,h.height)}})()}}}h.ContentLayoutable=u,u.__name__=\"ContentLayoutable\"},\n", - " function _(e,t,s,a,_){a();const r=e(62),n=e(61),g=e(58),i=e(63),c=e(67),h=e(65),l=e(13),o=e(11);class x{constructor(e,t,s,a,_={},r={},n={},g={}){this.in_x_scale=e,this.in_y_scale=t,this.x_range=s,this.y_range=a,this.extra_x_ranges=_,this.extra_y_ranges=r,this.extra_x_scales=n,this.extra_y_scales=g,this._bbox=new h.BBox,(0,o.assert)(null==e.source_range&&null==e.target_range),(0,o.assert)(null==t.source_range&&null==t.target_range),this._configure_scales()}get bbox(){return this._bbox}_get_ranges(e,t){return new Map((0,l.entries)(Object.assign(Object.assign({},t),{default:e})))}_get_scales(e,t,s,a){var _;const g=new Map((0,l.entries)(Object.assign(Object.assign({},t),{default:e}))),h=new Map;for(const[t,l]of s){if(l instanceof c.FactorRange!=e instanceof r.CategoricalScale)throw new Error(`Range ${l.type} is incompatible is Scale ${e.type}`);e instanceof n.LogScale&&l instanceof i.DataRange1d&&(l.scale_hint=\"log\");const s=(null!==(_=g.get(t))&&void 0!==_?_:e).clone();s.setv({source_range:l,target_range:a}),h.set(t,s)}return h}_configure_frame_ranges(){const{bbox:e}=this;this._x_target=new g.Range1d({start:e.left,end:e.right}),this._y_target=new g.Range1d({start:e.bottom,end:e.top})}_configure_scales(){this._configure_frame_ranges(),this._x_ranges=this._get_ranges(this.x_range,this.extra_x_ranges),this._y_ranges=this._get_ranges(this.y_range,this.extra_y_ranges),this._x_scales=this._get_scales(this.in_x_scale,this.extra_x_scales,this._x_ranges,this._x_target),this._y_scales=this._get_scales(this.in_y_scale,this.extra_y_scales,this._y_ranges,this._y_target)}_update_scales(){this._configure_frame_ranges();for(const[,e]of this._x_scales)e.target_range=this._x_target;for(const[,e]of this._y_scales)e.target_range=this._y_target}set_geometry(e){this._bbox=e,this._update_scales()}get x_target(){return this._x_target}get y_target(){return this._y_target}get x_ranges(){return this._x_ranges}get y_ranges(){return this._y_ranges}get x_scales(){return this._x_scales}get y_scales(){return this._y_scales}get x_scale(){return this._x_scales.get(\"default\")}get y_scale(){return this._y_scales.get(\"default\")}get xscales(){return(0,l.to_object)(this.x_scales)}get yscales(){return(0,l.to_object)(this.y_scales)}}s.CartesianFrame=x,x.__name__=\"CartesianFrame\"},\n", - " function _(i,s,x,A,o){A(),o(\"Axis\",i(128).Axis),o(\"CategoricalAxis\",i(140).CategoricalAxis),o(\"ContinuousAxis\",i(143).ContinuousAxis),o(\"DatetimeAxis\",i(144).DatetimeAxis),o(\"LinearAxis\",i(145).LinearAxis),o(\"LogAxis\",i(162).LogAxis),o(\"MercatorAxis\",i(165).MercatorAxis)},\n", - " function _(t,e,i,s,a){s();const o=t(1);var l;const n=t(129),_=t(130),r=t(131),h=t(132),c=(0,o.__importStar)(t(48)),b=t(20),u=t(24),m=t(123),d=t(9),x=t(13),f=t(8),g=t(120),p=t(67),v=t(133),w=t(113),j=t(11),k=t(8),y=t(134),{abs:z}=Math;class M extends n.GuideRendererView{constructor(){super(...arguments),this._axis_label_view=null,this._major_label_views=new Map}async lazy_initialize(){await super.lazy_initialize(),await this._init_axis_label(),await this._init_major_labels()}async _init_axis_label(){const{axis_label:t}=this.model;if(null!=t){const e=(0,k.isString)(t)?(0,y.parse_delimited_string)(t):t;this._axis_label_view=await(0,w.build_view)(e,{parent:this})}else this._axis_label_view=null}async _init_major_labels(){const{major_label_overrides:t}=this.model;for(const[e,i]of(0,x.entries)(t)){const t=(0,k.isString)(i)?(0,y.parse_delimited_string)(i):i;this._major_label_views.set(e,await(0,w.build_view)(t,{parent:this}))}}update_layout(){this.layout=new m.SideLayout(this.panel,(()=>this.get_size()),!0),this.layout.on_resize((()=>this._coordinates=void 0))}get_size(){const{visible:t,fixed_location:e}=this.model;if(t&&null==e&&this.is_renderable){const{extents:t}=this;return{width:0,height:Math.round(t.tick+t.tick_label+t.axis_label)}}return{width:0,height:0}}get is_renderable(){const[t,e]=this.ranges;return t.is_valid&&e.is_valid}_render(){var t;if(!this.is_renderable)return;const{tick_coords:e,extents:i}=this,s=this.layer.ctx;s.save(),this._draw_rule(s,i),this._draw_major_ticks(s,i,e),this._draw_minor_ticks(s,i,e),this._draw_major_labels(s,i,e),this._draw_axis_label(s,i,e),null===(t=this._paint)||void 0===t||t.call(this,s,i,e),s.restore()}connect_signals(){super.connect_signals();const{axis_label:t,major_label_overrides:e}=this.model.properties;this.on_change(t,(async()=>{var t;null===(t=this._axis_label_view)||void 0===t||t.remove(),await this._init_axis_label()})),this.on_change(e,(async()=>{for(const t of this._major_label_views.values())t.remove();await this._init_major_labels()})),this.connect(this.model.change,(()=>this.plot_view.request_layout()))}get needs_clip(){return null!=this.model.fixed_location}_draw_rule(t,e){if(!this.visuals.axis_line.doit)return;const[i,s]=this.rule_coords,[a,o]=this.coordinates.map_to_screen(i,s),[l,n]=this.normals,[_,r]=this.offsets;this.visuals.axis_line.set_value(t),t.beginPath();for(let e=0;e0?s+i+3:0}_draw_axis_label(t,e,i){if(null==this._axis_label_view||null!=this.model.fixed_location)return;const[s,a]=(()=>{const{bbox:t}=this.layout;switch(this.panel.side){case\"above\":return[t.hcenter,t.bottom];case\"below\":return[t.hcenter,t.top];case\"left\":return[t.right,t.vcenter];case\"right\":return[t.left,t.vcenter]}})(),[o,l]=this.normals,n=e.tick+e.tick_label+this.model.axis_label_standoff,{vertical_align:_,align:r}=this.panel.get_label_text_heuristics(\"parallel\"),h={sx:s+o*n,sy:a+l*n,x_anchor:r,y_anchor:_},c=this._axis_label_view.graphics();c.visuals=this.visuals.axis_label_text.values(),c.angle=this.panel.get_label_angle_heuristic(\"parallel\"),this.plot_view.base_font_size&&(c.base_font_size=this.plot_view.base_font_size),c.position=h,c.align=r,c.paint(t)}_draw_ticks(t,e,i,s,a){if(!a.doit)return;const[o,l]=e,[n,_]=this.coordinates.map_to_screen(o,l),[r,h]=this.normals,[c,b]=this.offsets,[u,m]=[r*(c-i),h*(b-i)],[d,x]=[r*(c+s),h*(b+s)];a.set_value(t),t.beginPath();for(let e=0;et.bbox())),M=(()=>{const[t]=this.ranges;return t.is_reversed?0==this.dimension?(t,e)=>z[t].left-z[e].right:(t,e)=>z[e].top-z[t].bottom:0==this.dimension?(t,e)=>z[e].left-z[t].right:(t,e)=>z[t].top-z[e].bottom})(),{major_label_policy:O}=this.model,T=O.filter(k,z,M),A=[...T.ones()];if(0!=A.length){const t=this.parent.canvas_view.bbox,e=e=>{const i=z[e];if(i.left<0){const t=-i.left,{position:s}=y[e];y[e].position=Object.assign(Object.assign({},s),{sx:s.sx+t})}else if(i.right>t.width){const s=i.right-t.width,{position:a}=y[e];y[e].position=Object.assign(Object.assign({},a),{sx:a.sx-s})}},i=e=>{const i=z[e];if(i.top<0){const t=-i.top,{position:s}=y[e];y[e].position=Object.assign(Object.assign({},s),{sy:s.sy+t})}else if(i.bottom>t.height){const s=i.bottom-t.height,{position:a}=y[e];y[e].position=Object.assign(Object.assign({},a),{sy:a.sy-s})}},s=A[0],a=A[A.length-1];0==this.dimension?(e(s),e(a)):(i(s),i(a))}for(const e of T){y[e].paint(t)}}_tick_extent(){return this.model.major_tick_out}_tick_label_extents(){const t=this.tick_coords.major,e=this.compute_labels(t[this.dimension]),i=this.model.major_label_orientation,s=this.model.major_label_standoff,a=this.visuals.major_label_text;return[this._oriented_labels_extent(e,i,s,a)]}get extents(){const t=this._tick_label_extents();return{tick:this._tick_extent(),tick_labels:t,tick_label:(0,d.sum)(t),axis_label:this._axis_label_extent()}}_oriented_labels_extent(t,e,i,s){if(0==t.length||!s.doit)return 0;const a=this.panel.get_label_angle_heuristic(e);t.visuals=s.values(),t.angle=a,t.base_font_size=this.plot_view.base_font_size;const o=t.max_size(),l=0==this.dimension?o.height:o.width;return l>0?i+l+3:0}get normals(){return this.panel.normals}get dimension(){return this.panel.dimension}compute_labels(t){const e=this.model.formatter.format_graphics(t,this),{_major_label_views:i}=this,s=new Set;for(let a=0;az(l-n)?(t=r(_(a,o),l),s=_(r(a,o),n)):(t=_(a,o),s=r(a,o)),[t,s]}}get rule_coords(){const t=this.dimension,e=(t+1)%2,[i]=this.ranges,[s,a]=this.computed_bounds,o=[new Array(2),new Array(2)];return o[t][0]=Math.max(s,i.min),o[t][1]=Math.min(a,i.max),o[t][0]>o[t][1]&&(o[t][0]=o[t][1]=NaN),o[e][0]=this.loc,o[e][1]=this.loc,o}get tick_coords(){const t=this.dimension,e=(t+1)%2,[i]=this.ranges,[s,a]=this.computed_bounds,o=this.model.ticker.get_ticks(s,a,i,this.loc),l=o.major,n=o.minor,_=[[],[]],r=[[],[]],[h,c]=[i.min,i.max];for(let i=0;ic||(_[t].push(l[i]),_[e].push(this.loc));for(let i=0;ic||(r[t].push(n[i]),r[e].push(this.loc));return{major:_,minor:r}}get loc(){const{fixed_location:t}=this.model;if(null!=t){if((0,f.isNumber)(t))return t;const[,e]=this.ranges;if(e instanceof p.FactorRange)return e.synthetic(t);(0,j.unreachable)()}const[,e]=this.ranges;switch(this.panel.side){case\"left\":case\"below\":return e.start;case\"right\":case\"above\":return e.end}}serializable_state(){return Object.assign(Object.assign({},super.serializable_state()),{bbox:this.layout.bbox.box})}remove(){var t;null===(t=this._axis_label_view)||void 0===t||t.remove();for(const t of this._major_label_views.values())t.remove();super.remove()}has_finished(){if(!super.has_finished())return!1;if(null!=this._axis_label_view&&!this._axis_label_view.has_finished())return!1;for(const t of this._major_label_views.values())if(!t.has_finished())return!1;return!0}}i.AxisView=M,M.__name__=\"AxisView\";class O extends n.GuideRenderer{constructor(t){super(t)}}i.Axis=O,l=O,O.__name__=\"Axis\",l.prototype.default_view=M,l.mixins([[\"axis_\",c.Line],[\"major_tick_\",c.Line],[\"minor_tick_\",c.Line],[\"major_label_\",c.Text],[\"axis_label_\",c.Text]]),l.define((({Any:t,Int:e,Number:i,String:s,Ref:a,Dict:o,Tuple:l,Or:n,Nullable:c,Auto:u})=>({bounds:[n(l(i,i),u),\"auto\"],ticker:[a(_.Ticker)],formatter:[a(r.TickFormatter)],axis_label:[c(n(s,a(v.BaseText))),null],axis_label_standoff:[e,5],major_label_standoff:[e,5],major_label_orientation:[n(b.TickLabelOrientation,i),\"horizontal\"],major_label_overrides:[o(n(s,a(v.BaseText))),{}],major_label_policy:[a(h.LabelingPolicy),()=>new h.AllLabels],major_tick_in:[i,2],major_tick_out:[i,6],minor_tick_in:[i,0],minor_tick_out:[i,4],fixed_location:[c(n(i,t)),null]}))),l.override({axis_line_color:\"black\",major_tick_line_color:\"black\",minor_tick_line_color:\"black\",major_label_text_font_size:\"11px\",major_label_text_align:\"center\",major_label_text_baseline:\"alphabetic\",axis_label_text_font_size:\"13px\",axis_label_text_font_style:\"italic\"})},\n", - " function _(e,r,d,n,i){var s;n();const _=e(41);class u extends _.RendererView{}d.GuideRendererView=u,u.__name__=\"GuideRendererView\";class c extends _.Renderer{constructor(e){super(e)}}d.GuideRenderer=c,s=c,c.__name__=\"GuideRenderer\",s.override({level:\"guide\"})},\n", - " function _(c,e,n,s,o){s();const r=c(53);class t extends r.Model{constructor(c){super(c)}}n.Ticker=t,t.__name__=\"Ticker\"},\n", - " function _(t,o,r,e,c){e();const n=t(53),a=t(120);class m extends n.Model{constructor(t){super(t)}format_graphics(t,o){return this.doFormat(t,o).map((t=>new a.TextBox({text:t})))}compute(t,o){return this.doFormat([t],null!=o?o:{loc:0})[0]}v_compute(t,o){return this.doFormat(t,null!=o?o:{loc:0})}}r.TickFormatter=m,m.__name__=\"TickFormatter\"},\n", - " function _(e,n,s,t,i){var c,r;t();const l=e(53),o=e(13),a=e(34),u=e(8),d=e(24);class _ extends l.Model{constructor(e){super(e)}}s.LabelingPolicy=_,_.__name__=\"LabelingPolicy\";class f extends _{constructor(e){super(e)}filter(e,n,s){return e}}s.AllLabels=f,f.__name__=\"AllLabels\";class m extends _{constructor(e){super(e)}filter(e,n,s){const{min_distance:t}=this;let i=null;for(const n of e)null!=i&&s(i,n)({min_distance:[e,5]})));class b extends _{constructor(e){super(e)}get names(){return(0,o.keys)(this.args)}get values(){return(0,o.values)(this.args)}get func(){const e=(0,a.use_strict)(this.code);return new d.GeneratorFunction(\"indices\",\"bboxes\",\"distance\",...this.names,e)}filter(e,n,s){const t=Object.create(null),i=this.func.call(t,e,n,s,...this.values);let c=i.next();if(c.done&&void 0!==c.value){const{value:n}=c;return n instanceof d.Indices?n:void 0===n?e:(0,u.isIterable)(n)?d.Indices.from_indices(e.size,n):d.Indices.all_unset(e.size)}{const n=[];do{n.push(c.value),c=i.next()}while(!c.done);return d.Indices.from_indices(e.size,n)}}}s.CustomLabelingPolicy=b,r=b,b.__name__=\"CustomLabelingPolicy\",r.define((({Unknown:e,String:n,Dict:s})=>({args:[s(e),{}],code:[n,\"\"]})))},\n", - " function _(e,s,t,n,a){var _;n();const x=e(53),c=e(42);class i extends c.View{}t.BaseTextView=i,i.__name__=\"BaseTextView\";class o extends x.Model{constructor(e){super(e)}}t.BaseText=o,_=o,o.__name__=\"BaseText\",_.define((({String:e})=>({text:[e]})))},\n", - " function _(n,e,t,i,r){i();const s=n(135),l=n(139),d=[{start:\"$$\",end:\"$$\",inline:!1},{start:\"\\\\[\",end:\"\\\\]\",inline:!1},{start:\"\\\\(\",end:\"\\\\)\",inline:!0}];t.parse_delimited_string=function(n){for(const e of d){const t=n.indexOf(e.start),i=t+e.start.length;if(0==t){const t=n.indexOf(e.end,i),r=t;if(t==n.length-e.end.length)return new s.TeX({text:n.slice(i,r),inline:e.inline});break}}return new l.PlainText({text:n})}},\n", - " function _(t,e,s,i,n){var o,r,a;i();const h=t(8),_=t(136),l=t(22),c=t(120),d=t(121),u=t(122),g=t(65),p=t(133),x=t(137);class m extends p.BaseTextView{constructor(){super(...arguments),this._position={sx:0,sy:0},this.align=\"left\",this._x_anchor=\"left\",this._y_anchor=\"center\",this._base_font_size=13,this.font_size_scale=1,this.svg_image=null}graphics(){return this}infer_text_height(){return\"ascent_descent\"}set base_font_size(t){null!=t&&(this._base_font_size=t)}get base_font_size(){return this._base_font_size}get has_image_loaded(){return null!=this.svg_image}_rect(){const{width:t,height:e}=this._size(),{x:s,y:i}=this._computed_position();return new g.BBox({x:s,y:i,width:t,height:e}).rect}set position(t){this._position=t}get position(){return this._position}get text(){return this.model.text}get provider(){return x.default_provider}async lazy_initialize(){await super.lazy_initialize(),\"not_started\"==this.provider.status&&await this.provider.fetch(),\"not_started\"!=this.provider.status&&\"loading\"!=this.provider.status||this.provider.ready.connect((()=>this.load_image())),\"loaded\"==this.provider.status&&await this.load_image()}connect_signals(){super.connect_signals(),this.on_change(this.model.properties.text,(()=>this.load_image()))}set visuals(t){const e=t.color,s=t.alpha,i=t.font_style;let n=t.font_size;const o=t.font,{font_size_scale:r,_base_font_size:a}=this,h=(0,d.parse_css_font_size)(n);if(null!=h){let{value:t,unit:e}=h;t*=r,\"em\"==e&&a&&(t*=a,e=\"px\"),n=`${t}${e}`}const _=`${i} ${n} ${o}`;this.font=_,this.color=(0,l.color2css)(e,s)}_computed_position(){const{width:t,height:e}=this._size(),{sx:s,sy:i,x_anchor:n=this._x_anchor,y_anchor:o=this._y_anchor}=this.position;return{x:s-(()=>{if((0,h.isNumber)(n))return n*t;switch(n){case\"left\":return 0;case\"center\":return.5*t;case\"right\":return t}})(),y:i-(()=>{if((0,h.isNumber)(o))return o*e;switch(o){case\"top\":return 0;case\"center\":return.5*e;case\"bottom\":return e;case\"baseline\":return.5*e}})()}}size(){const{width:t,height:e}=this._size(),{angle:s}=this;if(s){const i=Math.cos(Math.abs(s)),n=Math.sin(Math.abs(s));return{width:Math.abs(t*i+e*n),height:Math.abs(t*n+e*i)}}return{width:t,height:e}}get_text_dimensions(){return{width:(0,c.text_width)(this.model.text,this.font),height:(0,d.font_metrics)(this.font).height}}get_image_dimensions(){var t,e,s,i;const n=parseFloat(null!==(e=null===(t=this.svg_element.getAttribute(\"height\"))||void 0===t?void 0:t.replace(/([A-z])/g,\"\"))&&void 0!==e?e:\"0\"),o=parseFloat(null!==(i=null===(s=this.svg_element.getAttribute(\"width\"))||void 0===s?void 0:s.replace(/([A-z])/g,\"\"))&&void 0!==i?i:\"0\");return{width:(0,d.font_metrics)(this.font).x_height*o,height:(0,d.font_metrics)(this.font).x_height*n}}_size(){return this.has_image_loaded?this.get_image_dimensions():this.get_text_dimensions()}bbox(){const{p0:t,p1:e,p2:s,p3:i}=this.rect(),n=Math.min(t.x,e.x,s.x,i.x),o=Math.min(t.y,e.y,s.y,i.y),r=Math.max(t.x,e.x,s.x,i.x),a=Math.max(t.y,e.y,s.y,i.y);return new g.BBox({left:n,right:r,top:o,bottom:a})}rect(){const t=this._rect(),{angle:e}=this;if(e){const{sx:s,sy:i}=this.position,n=new u.AffineTransform;return n.translate(s,i),n.rotate(e),n.translate(-s,-i),n.apply_rect(t)}return t}paint_rect(t){const{p0:e,p1:s,p2:i,p3:n}=this.rect();t.save(),t.strokeStyle=\"red\",t.lineWidth=1,t.beginPath();const{round:o}=Math;t.moveTo(o(e.x),o(e.y)),t.lineTo(o(s.x),o(s.y)),t.lineTo(o(i.x),o(i.y)),t.lineTo(o(n.x),o(n.y)),t.closePath(),t.stroke(),t.restore()}paint_bbox(t){const{x:e,y:s,width:i,height:n}=this.bbox();t.save(),t.strokeStyle=\"blue\",t.lineWidth=1,t.beginPath();const{round:o}=Math;t.moveTo(o(e),o(s)),t.lineTo(o(e),o(s+n)),t.lineTo(o(e+i),o(s+n)),t.lineTo(o(e+i),o(s)),t.closePath(),t.stroke(),t.restore()}async load_image(){if(null==this.provider.MathJax)return null;const t=this._process_text(this.model.text);if(null==t)return this._has_finished=!0,null;const e=t.children[0];this.svg_element=e,e.setAttribute(\"font\",this.font),e.setAttribute(\"stroke\",this.color);const s=e.outerHTML,i=new Blob([s],{type:\"image/svg+xml\"}),n=URL.createObjectURL(i);try{this.svg_image=await(0,_.load_image)(n)}finally{URL.revokeObjectURL(n)}return this.parent.request_layout(),this.svg_image}paint(t){t.save();const{sx:e,sy:s}=this.position;this.angle&&(t.translate(e,s),t.rotate(this.angle),t.translate(-e,-s));const{x:i,y:n}=this._computed_position();if(null!=this.svg_image){const{width:e,height:s}=this.get_image_dimensions();t.drawImage(this.svg_image,i,n,e,s)}else t.fillStyle=this.color,t.font=this.font,t.textAlign=\"left\",t.textBaseline=\"alphabetic\",t.fillText(this.model.text,i,n+(0,d.font_metrics)(this.font).ascent);t.restore(),this._has_finished||\"failed\"!=this.provider.status&&!this.has_image_loaded||(this._has_finished=!0,this.parent.notify_finished_after_paint())}}s.MathTextView=m,m.__name__=\"MathTextView\";class f extends p.BaseText{constructor(t){super(t)}}s.MathText=f,f.__name__=\"MathText\";class v extends m{_process_text(t){}}s.AsciiView=v,v.__name__=\"AsciiView\";class y extends f{constructor(t){super(t)}}s.Ascii=y,o=y,y.__name__=\"Ascii\",o.prototype.default_view=v;class w extends m{_process_text(t){var e;return null===(e=this.provider.MathJax)||void 0===e?void 0:e.mathml2svg(t.trim())}}s.MathMLView=w,w.__name__=\"MathMLView\";class b extends f{constructor(t){super(t)}}s.MathML=b,r=b,b.__name__=\"MathML\",r.prototype.default_view=w;class M extends m{_process_text(t){var e;return null===(e=this.provider.MathJax)||void 0===e?void 0:e.tex2svg(t,void 0,this.model.macros)}}s.TeXView=M,M.__name__=\"TeXView\";class T extends f{constructor(t){super(t)}}s.TeX=T,a=T,T.__name__=\"TeX\",a.prototype.default_view=M,a.define((({Boolean:t,Number:e,String:s,Dict:i,Tuple:n,Or:o})=>({macros:[i(o(s,n(s,e))),{}],inline:[t,!1]})))},\n", - " function _(i,e,t,s,o){s();const a=i(19);t.load_image=async function(i,e){return new n(i,e).promise};class n{constructor(i,e={}){this._image=new Image,this._finished=!1;const{attempts:t=1,timeout:s=1}=e;this.promise=new Promise(((o,n)=>{this._image.crossOrigin=\"anonymous\";let r=0;this._image.onerror=()=>{if(++r==t){const s=`unable to load ${i} image after ${t} attempts`;if(a.logger.warn(s),null==this._image.crossOrigin)return void(null!=e.failed&&e.failed());a.logger.warn(`attempting to load ${i} without a cross origin policy`),this._image.crossOrigin=null,r=0}setTimeout((()=>this._image.src=i),s)},this._image.onload=()=>{this._finished=!0,null!=e.loaded&&e.loaded(this._image),o(this._image)},this._image.src=i}))}get finished(){return this._finished}get image(){if(this._finished)return this._image;throw new Error(\"not loaded yet\")}}t.ImageLoader=n,n.__name__=\"ImageLoader\"},\n", - " function _(t,e,a,s,n){var r=this&&this.__createBinding||(Object.create?function(t,e,a,s){void 0===s&&(s=a),Object.defineProperty(t,s,{enumerable:!0,get:function(){return e[a]}})}:function(t,e,a,s){void 0===s&&(s=a),t[s]=e[a]}),i=this&&this.__setModuleDefault||(Object.create?function(t,e){Object.defineProperty(t,\"default\",{enumerable:!0,value:e})}:function(t,e){t.default=e}),d=this&&this.__importStar||function(t){if(t&&t.__esModule)return t;var 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l.AxisView{_paint(t,s,o){this._draw_group_separators(t,s,o)}_draw_group_separators(t,s,o){const[e]=this.ranges,[i,r]=this.computed_bounds;if(!e.tops||e.tops.length<2||!this.visuals.separator_line.doit)return;const a=this.dimension,l=(a+1)%2,_=[[],[]];let n=0;for(let t=0;ti&&pnew h.GraphicsBoxes(t.map((t=>(0,m.isString)(t)?new h.TextBox({text:t}):t))),_=t=>l(this.model.formatter.doFormat(t,this));if(1==t.levels){const t=_(i.major);a.push([t,r.major,this.model.major_label_orientation,this.visuals.major_label_text])}else if(2==t.levels){const t=_(i.major.map((t=>t[1])));a.push([t,r.major,this.model.major_label_orientation,this.visuals.major_label_text]),a.push([l(i.tops),r.tops,this.model.group_label_orientation,this.visuals.group_text])}else if(3==t.levels){const t=_(i.major.map((t=>t[2]))),s=i.mids.map((t=>t[1]));a.push([t,r.major,this.model.major_label_orientation,this.visuals.major_label_text]),a.push([l(s),r.mids,this.model.subgroup_label_orientation,this.visuals.subgroup_text]),a.push([l(i.tops),r.tops,this.model.group_label_orientation,this.visuals.group_text])}return a}get tick_coords(){const t=this.dimension,s=(t+1)%2,[o]=this.ranges,[e,i]=this.computed_bounds,r=this.model.ticker.get_ticks(e,i,o,this.loc),a={major:[[],[]],mids:[[],[]],tops:[[],[]],minor:[[],[]]};return a.major[t]=r.major,a.major[s]=r.major.map((()=>this.loc)),3==o.levels&&(a.mids[t]=r.mids,a.mids[s]=r.mids.map((()=>this.loc))),o.levels>1&&(a.tops[t]=r.tops,a.tops[s]=r.tops.map((()=>this.loc))),a}}o.CategoricalAxisView=u,u.__name__=\"CategoricalAxisView\";class d extends l.Axis{constructor(t){super(t)}}o.CategoricalAxis=d,a=d,d.__name__=\"CategoricalAxis\",a.prototype.default_view=u,a.mixins([[\"separator_\",p.Line],[\"group_\",p.Text],[\"subgroup_\",p.Text]]),a.define((({Number:t,Or:s})=>({group_label_orientation:[s(c.TickLabelOrientation,t),\"parallel\"],subgroup_label_orientation:[s(c.TickLabelOrientation,t),\"parallel\"]}))),a.override({ticker:()=>new _.CategoricalTicker,formatter:()=>new n.CategoricalTickFormatter,separator_line_color:\"lightgrey\",separator_line_width:2,group_text_font_style:\"bold\",group_text_font_size:\"11px\",group_text_color:\"grey\",subgroup_text_font_style:\"bold\",subgroup_text_font_size:\"11px\"})},\n", - " function _(t,c,o,s,e){s();const r=t(130);class i extends r.Ticker{constructor(t){super(t)}get_ticks(t,c,o,s){var e,r;return{major:this._collect(o.factors,o,t,c),minor:[],tops:this._collect(null!==(e=o.tops)&&void 0!==e?e:[],o,t,c),mids:this._collect(null!==(r=o.mids)&&void 0!==r?r:[],o,t,c)}}_collect(t,c,o,s){const e=[];for(const r of t){const t=c.synthetic(r);t>o&&tnew _.DatetimeTicker,formatter:()=>new m.DatetimeTickFormatter})},\n", - " function _(e,i,s,n,r){var t;n();const a=e(143),o=e(146),c=e(147);class _ extends a.ContinuousAxisView{}s.LinearAxisView=_,_.__name__=\"LinearAxisView\";class u extends a.ContinuousAxis{constructor(e){super(e)}}s.LinearAxis=u,t=u,u.__name__=\"LinearAxis\",t.prototype.default_view=_,t.override({ticker:()=>new c.BasicTicker,formatter:()=>new o.BasicTickFormatter})},\n", - " function _(i,t,e,n,o){var r;n();const s=i(131),c=i(34);function _(i){let t=\"\";for(const e of i)t+=\"-\"==e?\"\\u2212\":e;return t}e.unicode_replace=_;class a extends s.TickFormatter{constructor(i){super(i),this.last_precision=3}get scientific_limit_low(){return 10**this.power_limit_low}get scientific_limit_high(){return 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Date(t)),s=(0,r.last_month_no_later_than)(new Date(e));s.setUTCMonth(s.getUTCMonth()+1);const o=[],a=n;for(;o.push((0,r.copy_date)(a)),a.setUTCMonth(a.getUTCMonth()+1),!(a>s););return o}(t,e),a=this.days,i=this.interval,_=(0,c.concat)(o.map((t=>((t,e)=>{const n=t.getUTCMonth(),s=[];for(const o of a){const a=(0,r.copy_date)(t);a.setUTCDate(o),new Date(a.getTime()+e/2).getUTCMonth()==n&&s.push(a)}return s})(t,i))));return{major:_.map((t=>t.getTime())).filter((n=>t<=n&&n<=e)),minor:[]}}}n.DaysTicker=_,a=_,_.__name__=\"DaysTicker\",a.define((({Int:t,Array:e})=>({days:[e(t),[]]}))),a.override({num_minor_ticks:0})},\n", - " function _(e,n,t,r,i){var a;r();const l=e(149);class s extends l.ContinuousTicker{constructor(e){super(e)}get_interval(e,n,t){return this.interval}get_min_interval(){return this.interval}get_max_interval(){return this.interval}}t.SingleIntervalTicker=s,a=s,s.__name__=\"SingleIntervalTicker\",a.define((({Number:e})=>({interval:[e]})))},\n", - " function _(t,n,e,_,E){function N(t){return new Date(t.getTime())}function O(t){const n=N(t);return n.setUTCDate(1),n.setUTCHours(0),n.setUTCMinutes(0),n.setUTCSeconds(0),n.setUTCMilliseconds(0),n}_(),e.ONE_MILLI=1,e.ONE_SECOND=1e3,e.ONE_MINUTE=60*e.ONE_SECOND,e.ONE_HOUR=60*e.ONE_MINUTE,e.ONE_DAY=24*e.ONE_HOUR,e.ONE_MONTH=30*e.ONE_DAY,e.ONE_YEAR=365*e.ONE_DAY,e.copy_date=N,e.last_month_no_later_than=O,e.last_year_no_later_than=function(t){const n=O(t);return n.setUTCMonth(0),n}},\n", - " function _(t,e,n,a,r){var s;a();const i=t(158),o=t(159),l=t(9);class _ extends i.SingleIntervalTicker{constructor(t){super(t)}initialize(){super.initialize();const t=this.months;t.length>1?this.interval=(t[1]-t[0])*o.ONE_MONTH:this.interval=12*o.ONE_MONTH}get_ticks_no_defaults(t,e,n,a){const r=function(t,e){const n=(0,o.last_year_no_later_than)(new Date(t)),a=(0,o.last_year_no_later_than)(new Date(e));a.setUTCFullYear(a.getUTCFullYear()+1);const r=[],s=n;for(;r.push((0,o.copy_date)(s)),s.setUTCFullYear(s.getUTCFullYear()+1),!(s>a););return r}(t,e),s=this.months;return{major:(0,l.concat)(r.map((t=>s.map((e=>{const n=(0,o.copy_date)(t);return n.setUTCMonth(e),n}))))).map((t=>t.getTime())).filter((n=>t<=n&&n<=e)),minor:[]}}}n.MonthsTicker=_,s=_,_.__name__=\"MonthsTicker\",s.define((({Int:t,Array:e})=>({months:[e(t),[]]})))},\n", - " function _(e,t,a,i,r){i();const n=e(147),_=e(158),s=e(159);class c extends _.SingleIntervalTicker{constructor(e){super(e)}initialize(){super.initialize(),this.interval=s.ONE_YEAR,this.basic_ticker=new n.BasicTicker({num_minor_ticks:0})}get_ticks_no_defaults(e,t,a,i){const r=(0,s.last_year_no_later_than)(new Date(e)).getUTCFullYear(),n=(0,s.last_year_no_later_than)(new Date(t)).getUTCFullYear();return{major:this.basic_ticker.get_ticks_no_defaults(r,n,a,i).major.map((e=>Date.UTC(e,0,1))).filter((a=>e<=a&&a<=t)),minor:[]}}}a.YearsTicker=c,c.__name__=\"YearsTicker\"},\n", - " function _(e,o,i,s,t){var n;s();const r=e(143),_=e(163),c=e(164);class a extends r.ContinuousAxisView{}i.LogAxisView=a,a.__name__=\"LogAxisView\";class u extends r.ContinuousAxis{constructor(e){super(e)}}i.LogAxis=u,n=u,u.__name__=\"LogAxis\",n.prototype.default_view=a,n.override({ticker:()=>new c.LogTicker,formatter:()=>new _.LogTickFormatter})},\n", - " function _(e,t,n,o,r){var i;o();const a=e(131),s=e(146),c=e(164),l=e(120),{abs:u,log:x,round:_}=Math;class p extends a.TickFormatter{constructor(e){super(e)}initialize(){super.initialize(),this.basic_formatter=new s.BasicTickFormatter}format_graphics(e,t){var n,o;if(0==e.length)return[];const r=null!==(o=null===(n=this.ticker)||void 0===n?void 0:n.base)&&void 0!==o?o:10,i=this._exponents(e,r);return null==i?this.basic_formatter.format_graphics(e,t):i.map((e=>{if(u(e)u(e)({ticker:[n(t(c.LogTicker)),null],min_exponent:[e,0]})))},\n", - " function _(t,o,e,s,n){var r;s();const i=t(148),a=t(9);class c extends i.AdaptiveTicker{constructor(t){super(t)}get_ticks_no_defaults(t,o,e,s){const n=this.num_minor_ticks,r=[],i=this.base,c=Math.log(t)/Math.log(i),f=Math.log(o)/Math.log(i),l=f-c;let h;if(isFinite(l))if(l<2){const e=this.get_interval(t,o,s),i=Math.floor(t/e),c=Math.ceil(o/e);if(h=(0,a.range)(i,c+1).filter((t=>0!=t)).map((t=>t*e)).filter((e=>t<=e&&e<=o)),n>0&&h.length>0){const t=e/n,o=(0,a.range)(0,n).map((o=>o*t));for(const t of o.slice(1))r.push(h[0]-t);for(const t of h)for(const e of o)r.push(t+e)}}else{const t=Math.ceil(.999999*c),o=Math.floor(1.000001*f),e=Math.ceil((o-t)/9);if(h=(0,a.range)(t-1,o+1,e).map((t=>i**t)),n>0&&h.length>0){const t=i**e/n,o=(0,a.range)(1,n+1).map((o=>o*t));for(const t of o)r.push(h[0]/t);r.push(h[0]);for(const t of h)for(const e of o)r.push(t*e)}}else h=[];return{major:h.filter((e=>t<=e&&e<=o)),minor:r.filter((e=>t<=e&&e<=o))}}}e.LogTicker=c,r=c,c.__name__=\"LogTicker\",r.override({mantissas:[1,5]})},\n", - " function _(e,r,t,i,a){var o;i();const s=e(128),c=e(145),n=e(166),_=e(167);class x extends s.AxisView{}t.MercatorAxisView=x,x.__name__=\"MercatorAxisView\";class d extends c.LinearAxis{constructor(e){super(e)}}t.MercatorAxis=d,o=d,d.__name__=\"MercatorAxis\",o.prototype.default_view=x,o.override({ticker:()=>new _.MercatorTicker({dimension:\"lat\"}),formatter:()=>new n.MercatorTickFormatter({dimension:\"lat\"})})},\n", - " function _(r,t,e,o,n){var i;o();const c=r(146),s=r(20),a=r(78);class l extends c.BasicTickFormatter{constructor(r){super(r)}doFormat(r,t){if(null==this.dimension)throw new Error(\"MercatorTickFormatter.dimension not configured\");if(0==r.length)return[];const e=r.length,o=new Array(e);if(\"lon\"==this.dimension)for(let n=0;n({dimension:[r(s.LatLon),null]})))},\n", - " function _(t,o,n,s,r){var e;s();const i=t(147),c=t(20),_=t(78);class a extends i.BasicTicker{constructor(t){super(t)}get_ticks_no_defaults(t,o,n,s){if(null==this.dimension)throw new Error(`${this}.dimension wasn't configured`);return[t,o]=(0,_.clip_mercator)(t,o,this.dimension),\"lon\"==this.dimension?this._get_ticks_lon(t,o,n,s):this._get_ticks_lat(t,o,n,s)}_get_ticks_lon(t,o,n,s){const[r]=_.wgs84_mercator.invert(t,n),[e,i]=_.wgs84_mercator.invert(o,n),c=super.get_ticks_no_defaults(r,e,n,s),a=[];for(const t of c.major)if((0,_.in_bounds)(t,\"lon\")){const[o]=_.wgs84_mercator.compute(t,i);a.push(o)}const m=[];for(const t of c.minor)if((0,_.in_bounds)(t,\"lon\")){const[o]=_.wgs84_mercator.compute(t,i);m.push(o)}return{major:a,minor:m}}_get_ticks_lat(t,o,n,s){const[,r]=_.wgs84_mercator.invert(n,t),[e,i]=_.wgs84_mercator.invert(n,o),c=super.get_ticks_no_defaults(r,i,n,s),a=[];for(const t of c.major)if((0,_.in_bounds)(t,\"lat\")){const[,o]=_.wgs84_mercator.compute(e,t);a.push(o)}const m=[];for(const t of c.minor)if((0,_.in_bounds)(t,\"lat\")){const[,o]=_.wgs84_mercator.compute(e,t);m.push(o)}return{major:a,minor:m}}}n.MercatorTicker=a,e=a,a.__name__=\"MercatorTicker\",e.define((({Nullable:t})=>({dimension:[t(c.LatLon),null]})))},\n", - " function _(e,i,r,c,k){c(),k(\"AdaptiveTicker\",e(148).AdaptiveTicker),k(\"BasicTicker\",e(147).BasicTicker),k(\"CategoricalTicker\",e(141).CategoricalTicker),k(\"CompositeTicker\",e(156).CompositeTicker),k(\"ContinuousTicker\",e(149).ContinuousTicker),k(\"DatetimeTicker\",e(155).DatetimeTicker),k(\"DaysTicker\",e(157).DaysTicker),k(\"FixedTicker\",e(169).FixedTicker),k(\"LogTicker\",e(164).LogTicker),k(\"MercatorTicker\",e(167).MercatorTicker),k(\"MonthsTicker\",e(160).MonthsTicker),k(\"SingleIntervalTicker\",e(158).SingleIntervalTicker),k(\"Ticker\",e(130).Ticker),k(\"YearsTicker\",e(161).YearsTicker),k(\"BinnedTicker\",e(170).BinnedTicker)},\n", - " function _(r,t,e,i,n){var s;i();const _=r(149);class c extends _.ContinuousTicker{constructor(r){super(r)}get_ticks_no_defaults(r,t,e,i){return{major:this.ticks,minor:this.minor_ticks}}get_interval(r,t,e){return 0}get_min_interval(){return 0}get_max_interval(){return 0}}e.FixedTicker=c,s=c,c.__name__=\"FixedTicker\",s.define((({Number:r,Array:t})=>({ticks:[t(r),[]],minor_ticks:[t(r),[]]})))},\n", - " function _(e,n,t,r,i){var o;r();const a=e(130),s=e(171),c=e(12);class m extends a.Ticker{constructor(e){super(e)}get_ticks(e,n,t,r){const{binning:i}=this.mapper.metrics,o=Math.max(0,(0,c.left_edge_index)(e,i)),a=Math.min((0,c.left_edge_index)(n,i)+1,i.length-1),s=[];for(let e=o;e<=a;e++)s.push(i[e]);const{num_major_ticks:m}=this,_=[],h=\"auto\"==m?s.length:m,l=Math.max(1,Math.floor(s.length/h));for(let e=0;e({mapper:[n(s.ScanningColorMapper)],num_major_ticks:[t(e,r),8]})))},\n", - " function _(n,e,i,r,o){r();const t=n(172),a=n(12);class c extends t.ContinuousColorMapper{constructor(n){super(n)}cmap(n,e,i,r,o){if(no.binning[o.binning.length-1])return r;return e[(0,a.left_edge_index)(n,o.binning)]}}i.ScanningColorMapper=c,c.__name__=\"ScanningColorMapper\"},\n", - " function _(t,e,o,n,s){var l;n();const c=t(173),i=t(175),a=t(9),h=t(8);class r extends c.ColorMapper{constructor(t){super(t),this._scan_data=null}connect_signals(){super.connect_signals();const t=()=>{for(const[t]of this.domain)this.connect(t.view.change,(()=>this.update_data())),this.connect(t.data_source.selected.change,(()=>this.update_data()))};this.connect(this.properties.domain.change,(()=>t())),t()}update_data(){const{domain:t,palette:e}=this,o=[...this._collect(t)];this._scan_data=this.scan(o,e.length),this.metrics_change.emit(),this.change.emit()}get metrics(){return null==this._scan_data&&this.update_data(),this._scan_data}*_collect(t){for(const[e,o]of t)for(const t of(0,h.isArray)(o)?o:[o]){let o=e.data_source.get_column(t);o=e.view.indices.select(o);const n=e.view.masked,s=e.data_source.selected.indices;let l;if(null!=n&&s.length>0?l=(0,a.intersection)([...n],s):null!=n?l=[...n]:s.length>0&&(l=s),null!=l&&(o=(0,a.map)(l,(t=>o[t]))),o.length>0&&!(0,h.isNumber)(o[0]))for(const t of o)yield*t;else yield*o}}_v_compute(t,e,o,n){const{nan_color:s}=n;let{low_color:l,high_color:c}=n;null==l&&(l=o[0]),null==c&&(c=o[o.length-1]);const{domain:i}=this,h=(0,a.is_empty)(i)?t:[...this._collect(i)];this._scan_data=this.scan(h,o.length),this.metrics_change.emit();for(let n=0,i=t.length;n({high:[a(t),null],low:[a(t),null],high_color:[a(n),null],low_color:[a(n),null],domain:[c(l(o(i.GlyphRenderer),s(e,c(e)))),[]]})))},\n", - " function _(e,r,t,n,o){var a;n();const c=e(174),i=e(15),_=e(24),l=e(22),s=e(27);function p(e){return(0,l.encode_rgba)((0,l.color2rgba)(e))}function u(e){const r=new Uint32Array(e.length);for(let t=0,n=e.length;te))),r}get rgba_mapper(){const e=this,r=u(this.palette),t=this._colors(p);return{v_compute(n){const o=new _.ColorArray(n.length);return e._v_compute(n,o,r,t),new Uint8ClampedArray((0,s.to_big_endian)(o).buffer)}}}_colors(e){return{nan_color:e(this.nan_color)}}}t.ColorMapper=h,a=h,h.__name__=\"ColorMapper\",a.define((({Color:e,Array:r})=>({palette:[r(e)],nan_color:[e,\"gray\"]})))},\n", - " function _(r,e,n,s,o){s();const p=r(56);class t extends p.Transform{constructor(r){super(r)}compute(r){throw new Error(\"mapping single values is not supported\")}}n.Mapper=t,t.__name__=\"Mapper\"},\n", - " function _(e,t,i,s,l){var h;s();const n=e(176),o=e(177),a=e(186),c=e(187),_=e(189),r=e(179),d=e(70),p=e(190),g=e(24),u=e(12),y=e(13),m=e(113),v=e(67),f={fill:{},line:{}},w={fill:{fill_alpha:.3,fill_color:\"grey\"},line:{line_alpha:.3,line_color:\"grey\"}},b={fill:{fill_alpha:.2},line:{}},V={fill:{fill_alpha:.2},line:{}};class x extends n.DataRendererView{get glyph_view(){return this.glyph}async lazy_initialize(){var e;await super.lazy_initialize();const t=this.model.glyph;this.glyph=await this.build_glyph_view(t);const i=\"fill\"in this.glyph.visuals,s=\"line\"in this.glyph.visuals,l=Object.assign({},t.attributes);function h(e){const h=(0,y.clone)(l);return i&&(0,y.extend)(h,e.fill),s&&(0,y.extend)(h,e.line),new t.constructor(h)}function n(e,t){return t instanceof r.Glyph?t:h(\"auto\"==t?e:{fill:{},line:{}})}delete l.id;let{selection_glyph:o,nonselection_glyph:a,hover_glyph:c,muted_glyph:_}=this.model;o=n(f,o),this.selection_glyph=await this.build_glyph_view(o),a=n(b,a),this.nonselection_glyph=await this.build_glyph_view(a),null!=c&&(this.hover_glyph=await this.build_glyph_view(c)),_=n(V,_),this.muted_glyph=await this.build_glyph_view(_);const d=n(w,\"auto\");this.decimated_glyph=await this.build_glyph_view(d),this.selection_glyph.set_base(this.glyph),this.nonselection_glyph.set_base(this.glyph),null===(e=this.hover_glyph)||void 0===e||e.set_base(this.glyph),this.muted_glyph.set_base(this.glyph),this.decimated_glyph.set_base(this.glyph),this.set_data()}async build_glyph_view(e){return(0,m.build_view)(e,{parent:this})}remove(){var e;this.glyph.remove(),this.selection_glyph.remove(),this.nonselection_glyph.remove(),null===(e=this.hover_glyph)||void 0===e||e.remove(),this.muted_glyph.remove(),this.decimated_glyph.remove(),super.remove()}connect_signals(){super.connect_signals();const e=()=>this.request_render(),t=()=>this.update_data();this.connect(this.model.change,e),this.connect(this.glyph.model.change,t),this.connect(this.selection_glyph.model.change,t),this.connect(this.nonselection_glyph.model.change,t),null!=this.hover_glyph&&this.connect(this.hover_glyph.model.change,t),this.connect(this.muted_glyph.model.change,t),this.connect(this.decimated_glyph.model.change,t),this.connect(this.model.data_source.change,t),this.connect(this.model.data_source.streaming,t),this.connect(this.model.data_source.patching,(e=>this.update_data(e))),this.connect(this.model.data_source.selected.change,e),this.connect(this.model.data_source._select,e),null!=this.hover_glyph&&this.connect(this.model.data_source.inspect,e),this.connect(this.model.properties.view.change,t),this.connect(this.model.view.properties.indices.change,t),this.connect(this.model.view.properties.masked.change,(()=>this.set_visuals())),this.connect(this.model.properties.visible.change,(()=>this.plot_view.invalidate_dataranges=!0));const{x_ranges:i,y_ranges:s}=this.plot_view.frame;for(const[,e]of i)e instanceof v.FactorRange&&this.connect(e.change,t);for(const[,e]of s)e instanceof v.FactorRange&&this.connect(e.change,t);const{transformchange:l,exprchange:h}=this.model.glyph;this.connect(l,t),this.connect(h,t)}_update_masked_indices(){const e=this.glyph.mask_data();return this.model.view.masked=e,e}update_data(e){this.set_data(e),this.request_render()}set_data(e){const t=this.model.data_source;this.all_indices=this.model.view.indices;const{all_indices:i}=this;this.glyph.set_data(t,i,e),this.set_visuals(),this._update_masked_indices();const{lod_factor:s}=this.plot_model,l=this.all_indices.count;this.decimated=new g.Indices(l);for(let e=0;e!n||n.is_empty()?[]:n.selected_glyph?this.model.view.convert_indices_from_subset(i):n.indices.length>0?n.indices:Object.keys(n.multiline_indices).map((e=>parseInt(e))))()),d=(0,u.filter)(i,(e=>r.has(t[e]))),{lod_threshold:p}=this.plot_model;let g,y,m;if(null!=this.model.document&&this.model.document.interactive_duration()>0&&!e&&null!=p&&t.length>p?(i=[...this.decimated],g=this.decimated_glyph,y=this.decimated_glyph,m=this.selection_glyph):(g=this.model.muted?this.muted_glyph:this.glyph,y=this.nonselection_glyph,m=this.selection_glyph),null!=this.hover_glyph&&d.length){const e=new Set(i);for(const t of d)e.delete(t);i=[...e]}if(h.length){const e={};for(const t of h)e[t]=!0;const l=new Array,n=new Array;if(this.glyph instanceof o.LineView)for(const i of t)null!=e[i]?l.push(i):n.push(i);else for(const s of i)null!=e[t[s]]?l.push(s):n.push(s);y.render(s,n),m.render(s,l),null!=this.hover_glyph&&(this.glyph instanceof o.LineView?this.hover_glyph.render(s,this.model.view.convert_indices_from_subset(d)):this.hover_glyph.render(s,d))}else if(this.glyph instanceof o.LineView)this.hover_glyph&&d.length?this.hover_glyph.render(s,this.model.view.convert_indices_from_subset(d)):g.render(s,t);else if(this.glyph instanceof a.PatchView||this.glyph instanceof c.HAreaView||this.glyph instanceof _.VAreaView)if(0==n.selected_glyphs.length||null==this.hover_glyph)g.render(s,t);else for(const e of n.selected_glyphs)e==this.glyph.model&&this.hover_glyph.render(s,t);else g.render(s,i),this.hover_glyph&&d.length&&this.hover_glyph.render(s,d);s.restore()}draw_legend(e,t,i,s,l,h,n,o){0!=this.glyph.data_size&&(null==o&&(o=this.model.get_reference_point(h,n)),this.glyph.draw_legend_for_index(e,{x0:t,x1:i,y0:s,y1:l},o))}hit_test(e){if(!this.model.visible)return null;const t=this.glyph.hit_test(e);return null==t?null:this.model.view.convert_selection_from_subset(t)}}i.GlyphRendererView=x,x.__name__=\"GlyphRendererView\";class G extends n.DataRenderer{constructor(e){super(e)}initialize(){super.initialize(),this.view.source!=this.data_source&&(this.view.source=this.data_source,this.view.compute_indices())}get_reference_point(e,t){if(null!=e){const i=this.data_source.get_column(e);if(null!=i)for(const[e,s]of Object.entries(this.view.indices_map))if(i[parseInt(e)]==t)return s}return 0}get_selection_manager(){return this.data_source.selection_manager}}i.GlyphRenderer=G,h=G,G.__name__=\"GlyphRenderer\",h.prototype.default_view=x,h.define((({Boolean:e,Auto:t,Or:i,Ref:s,Null:l,Nullable:h})=>({data_source:[s(d.ColumnarDataSource)],view:[s(p.CDSView),e=>new p.CDSView({source:e.data_source})],glyph:[s(r.Glyph)],hover_glyph:[h(s(r.Glyph)),null],nonselection_glyph:[i(s(r.Glyph),t,l),\"auto\"],selection_glyph:[i(s(r.Glyph),t,l),\"auto\"],muted_glyph:[i(s(r.Glyph),t,l),\"auto\"],muted:[e,!1]})))},\n", - " function _(e,r,t,a,n){var s;a();const c=e(41);class _ extends c.RendererView{get xscale(){return this.coordinates.x_scale}get yscale(){return this.coordinates.y_scale}}t.DataRendererView=_,_.__name__=\"DataRendererView\";class i extends c.Renderer{constructor(e){super(e)}get selection_manager(){return this.get_selection_manager()}}t.DataRenderer=i,s=i,i.__name__=\"DataRenderer\",s.override({level:\"glyph\"})},\n", - " function _(e,t,i,s,n){s();const l=e(1);var _;const r=e(178),o=e(184),a=(0,l.__importStar)(e(48)),h=(0,l.__importStar)(e(185)),c=e(72);class d extends r.XYGlyphView{async lazy_initialize(){await super.lazy_initialize();const{webgl:t}=this.renderer.plot_view.canvas_view;if(null==t?void 0:t.regl_wrapper.has_webgl){const{LineGL:i}=await Promise.resolve().then((()=>(0,l.__importStar)(e(421))));this.glglyph=new i(t.regl_wrapper,this)}}_render(e,t,i){const{sx:s,sy:n}=null!=i?i:this;let l=null;const _=e=>null!=l&&e-l!=1;let r=!0;e.beginPath();for(const i of t){const t=s[i],o=n[i];isFinite(t+o)?r||_(i)?(e.moveTo(t,o),r=!1):e.lineTo(t,o):r=!0,l=i}this.visuals.line.set_value(e),e.stroke()}_hit_point(e){const t=new c.Selection,i={x:e.sx,y:e.sy};let s=9999;const n=Math.max(2,this.line_width.value/2);for(let e=0,l=this.sx.length-1;e({x:[c.XCoordinateSpec,{field:\"x\"}],y:[c.YCoordinateSpec,{field:\"y\"}]})))},\n", - " function _(e,t,s,i,n){i();const r=e(1),a=(0,r.__importStar)(e(18)),o=(0,r.__importStar)(e(65)),_=(0,r.__importStar)(e(45)),l=e(42),c=e(53),h=e(19),d=e(24),u=e(8),f=e(180),p=e(12),g=e(26),y=e(181),x=e(67),v=e(72),{abs:b,ceil:m}=Math;class w extends l.View{constructor(){super(...arguments),this._index=null,this._data_size=null,this._nohit_warned=new Set}get renderer(){return this.parent}get has_webgl(){return null!=this.glglyph}get index(){const{_index:e}=this;if(null!=e)return e;throw new Error(`${this}.index_data() wasn't called`)}get data_size(){const{_data_size:e}=this;if(null!=e)return e;throw new Error(`${this}.set_data() wasn't called`)}initialize(){super.initialize(),this.visuals=new _.Visuals(this)}request_render(){this.parent.request_render()}get canvas(){return this.renderer.parent.canvas_view}render(e,t,s){var i;null!=this.glglyph&&(this.renderer.needs_webgl_blit=this.glglyph.render(e,t,null!==(i=this.base)&&void 0!==i?i:this),this.renderer.needs_webgl_blit)||this._render(e,t,null!=s?s:this.base)}has_finished(){return!0}notify_finished(){this.renderer.notify_finished()}_bounds(e){return e}bounds(){return this._bounds(this.index.bbox)}log_bounds(){const{x0:e,x1:t}=this.index.bounds(o.positive_x()),{y0:s,y1:i}=this.index.bounds(o.positive_y());return this._bounds({x0:e,y0:s,x1:t,y1:i})}get_anchor_point(e,t,[s,i]){switch(e){case\"center\":case\"center_center\":{const[e,n]=this.scenterxy(t,s,i);return{x:e,y:n}}default:return null}}scenterx(e,t,s){return this.scenterxy(e,t,s)[0]}scentery(e,t,s){return this.scenterxy(e,t,s)[1]}sdist(e,t,s,i=\"edge\",n=!1){const r=t.length,a=new d.ScreenArray(r),o=e.s_compute;if(\"center\"==i)for(let e=0;em(e))),a}draw_legend_for_index(e,t,s){}hit_test(e){switch(e.type){case\"point\":if(null!=this._hit_point)return this._hit_point(e);break;case\"span\":if(null!=this._hit_span)return this._hit_span(e);break;case\"rect\":if(null!=this._hit_rect)return this._hit_rect(e);break;case\"poly\":if(null!=this._hit_poly)return this._hit_poly(e)}return this._nohit_warned.has(e.type)||(h.logger.debug(`'${e.type}' selection not available for ${this.model.type}`),this._nohit_warned.add(e.type)),null}_hit_rect_against_index(e){const{sx0:t,sx1:s,sy0:i,sy1:n}=e,[r,a]=this.renderer.coordinates.x_scale.r_invert(t,s),[o,_]=this.renderer.coordinates.y_scale.r_invert(i,n),l=[...this.index.indices({x0:r,x1:a,y0:o,y1:_})];return new v.Selection({indices:l})}_project_data(){}*_iter_visuals(){for(const e of this.visuals)for(const t of e)(t instanceof a.VectorSpec||t instanceof a.ScalarSpec)&&(yield t)}set_base(e){e!=this&&e instanceof this.constructor&&(this.base=e)}_configure(e,t){Object.defineProperty(this,(0,u.isString)(e)?e:e.attr,Object.assign({configurable:!0,enumerable:!0},t))}set_visuals(e,t){var s;for(const s of this._iter_visuals()){const{base:i}=this;if(null!=i){const e=i.model.properties[s.attr];if(null!=e&&(0,g.is_equal)(s.get_value(),e.get_value())){this._configure(s,{get:()=>i[`${s.attr}`]});continue}}const n=s.uniform(e).select(t);this._configure(s,{value:n})}for(const e of this.visuals)e.update();this._set_visuals(),null===(s=this.glglyph)||void 0===s||s.set_visuals_changed()}_set_visuals(){}set_data(e,t,s){var i;const{x_source:n,y_source:r}=this.renderer.coordinates,o=new Set(this._iter_visuals());this._data_size=t.count;for(const s of this.model)if((s instanceof a.VectorSpec||s instanceof a.ScalarSpec)&&!o.has(s))if(s instanceof a.BaseCoordinateSpec){const i=s.array(e);let o=t.select(i);const _=\"x\"==s.dimension?n:r;if(_ instanceof x.FactorRange)if(s instanceof a.CoordinateSpec)o=_.v_synthetic(o);else if(s instanceof a.CoordinateSeqSpec)for(let e=0;e{const s=new Uint32Array(r);for(let a=0;a>1;t[s]>i?e=s:n=s+1}return t[n]}class r extends d.default{get boxes(){return this._boxes}search_indices(i,t,n,e){if(this._pos!==this._boxes.length)throw new Error(\"Data not yet indexed - call index.finish().\");let s=this._boxes.length-4;const d=[],x=new o.Indices(this.numItems);for(;void 0!==s;){const o=Math.min(s+4*this.nodeSize,h(s,this._levelBounds));for(let h=s;h>2],r=this._boxes[h+0],l=this._boxes[h+1],a=this._boxes[h+2],_=this._boxes[h+3];na||t>_||(s<4*this.numItems?x.set(o):d.push(o)))}s=d.pop()}return x}}r.__name__=\"_FlatBush\";class l{constructor(i){this.index=null,i>0&&(this.index=new r(i))}add_rect(i,t,n,e){var s;isFinite(i+t+n+e)?null===(s=this.index)||void 0===s||s.add(i,t,n,e):this.add_empty()}add_point(i,t){var n;isFinite(i+t)?null===(n=this.index)||void 0===n||n.add(i,t,i,t):this.add_empty()}add_empty(){var i;null===(i=this.index)||void 0===i||i.add(1/0,1/0,-1/0,-1/0)}finish(){var i;null===(i=this.index)||void 0===i||i.finish()}_normalize(i){let{x0:t,y0:n,x1:e,y1:s}=i;return t>e&&([t,e]=[e,t]),n>s&&([n,s]=[s,n]),{x0:t,y0:n,x1:e,y1:s}}get bbox(){if(null==this.index)return(0,x.empty)();{const{minX:i,minY:t,maxX:n,maxY:e}=this.index;return{x0:i,y0:t,x1:n,y1:e}}}indices(i){if(null==this.index)return new o.Indices(0);{const{x0:t,y0:n,x1:e,y1:s}=this._normalize(i);return this.index.search_indices(t,n,e,s)}}bounds(i){const t=(0,x.empty)();if(null==this.index)return t;const{boxes:n}=this.index;for(const e of this.indices(i)){const s=n[4*e+0],d=n[4*e+1],o=n[4*e+2],x=n[4*e+3];s>=i.x0&&st.x1&&(t.x1=o),d>=i.y0&&dt.y1&&(t.y1=x)}return t}}n.SpatialIndex=l,l.__name__=\"SpatialIndex\"},\n", - " function _(t,s,i,e,h){e();const n=(0,t(1).__importDefault)(t(183)),o=[Int8Array,Uint8Array,Uint8ClampedArray,Int16Array,Uint16Array,Int32Array,Uint32Array,Float32Array,Float64Array];class r{static from(t){if(!(t instanceof ArrayBuffer))throw new Error(\"Data must be an instance of ArrayBuffer.\");const[s,i]=new Uint8Array(t,0,2);if(251!==s)throw new Error(\"Data does not appear to be in a Flatbush format.\");if(i>>4!=3)throw new Error(`Got v${i>>4} data when expected v3.`);const[e]=new Uint16Array(t,2,1),[h]=new Uint32Array(t,4,1);return new r(h,e,o[15&i],t)}constructor(t,s=16,i=Float64Array,e){if(void 0===t)throw new Error(\"Missing required argument: numItems.\");if(isNaN(t)||t<=0)throw new Error(`Unpexpected numItems value: ${t}.`);this.numItems=+t,this.nodeSize=Math.min(Math.max(+s,2),65535);let h=t,r=h;this._levelBounds=[4*h];do{h=Math.ceil(h/this.nodeSize),r+=h,this._levelBounds.push(4*r)}while(1!==h);this.ArrayType=i||Float64Array,this.IndexArrayType=r<16384?Uint16Array:Uint32Array;const a=o.indexOf(this.ArrayType),_=4*r*this.ArrayType.BYTES_PER_ELEMENT;if(a<0)throw new Error(`Unexpected typed array class: ${i}.`);e&&e instanceof ArrayBuffer?(this.data=e,this._boxes=new this.ArrayType(this.data,8,4*r),this._indices=new this.IndexArrayType(this.data,8+_,r),this._pos=4*r,this.minX=this._boxes[this._pos-4],this.minY=this._boxes[this._pos-3],this.maxX=this._boxes[this._pos-2],this.maxY=this._boxes[this._pos-1]):(this.data=new ArrayBuffer(8+_+r*this.IndexArrayType.BYTES_PER_ELEMENT),this._boxes=new this.ArrayType(this.data,8,4*r),this._indices=new this.IndexArrayType(this.data,8+_,r),this._pos=0,this.minX=1/0,this.minY=1/0,this.maxX=-1/0,this.maxY=-1/0,new Uint8Array(this.data,0,2).set([251,48+a]),new Uint16Array(this.data,2,1)[0]=s,new Uint32Array(this.data,4,1)[0]=t),this._queue=new n.default}add(t,s,i,e){const h=this._pos>>2;return this._indices[h]=h,this._boxes[this._pos++]=t,this._boxes[this._pos++]=s,this._boxes[this._pos++]=i,this._boxes[this._pos++]=e,tthis.maxX&&(this.maxX=i),e>this.maxY&&(this.maxY=e),h}finish(){if(this._pos>>2!==this.numItems)throw new Error(`Added ${this._pos>>2} items when expected ${this.numItems}.`);if(this.numItems<=this.nodeSize)return this._boxes[this._pos++]=this.minX,this._boxes[this._pos++]=this.minY,this._boxes[this._pos++]=this.maxX,void(this._boxes[this._pos++]=this.maxY);const t=this.maxX-this.minX,s=this.maxY-this.minY,i=new Uint32Array(this.numItems);for(let e=0;e>2]=t,this._boxes[this._pos++]=e,this._boxes[this._pos++]=h,this._boxes[this._pos++]=n,this._boxes[this._pos++]=o}}}search(t,s,i,e,h){if(this._pos!==this._boxes.length)throw new Error(\"Data not yet indexed - call index.finish().\");let n=this._boxes.length-4;const o=[],r=[];for(;void 0!==n;){const a=Math.min(n+4*this.nodeSize,_(n,this._levelBounds));for(let _=n;_>2];ithis._boxes[_+2]||s>this._boxes[_+3]||(n<4*this.numItems?(void 0===h||h(a))&&r.push(a):o.push(a)))}n=o.pop()}return r}neighbors(t,s,i=1/0,e=1/0,h){if(this._pos!==this._boxes.length)throw new Error(\"Data not yet indexed - call index.finish().\");let n=this._boxes.length-4;const o=this._queue,r=[],x=e*e;for(;void 0!==n;){const 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i=t^s,e=65535^i,h=65535^(t|s),n=t&(65535^s),o=i|e>>1,r=i>>1^i,a=h>>1^e&n>>1^h,_=i&h>>1^n>>1^n;i=o,e=r,h=a,n=_,o=i&i>>2^e&e>>2,r=i&e>>2^e&(i^e)>>2,a^=i&h>>2^e&n>>2,_^=e&h>>2^(i^e)&n>>2,i=o,e=r,h=a,n=_,o=i&i>>4^e&e>>4,r=i&e>>4^e&(i^e)>>4,a^=i&h>>4^e&n>>4,_^=e&h>>4^(i^e)&n>>4,i=o,e=r,h=a,n=_,a^=i&h>>8^e&n>>8,_^=e&h>>8^(i^e)&n>>8,i=a^a>>1,e=_^_>>1;let x=t^s,d=e|65535^(x|i);return x=16711935&(x|x<<8),x=252645135&(x|x<<4),x=858993459&(x|x<<2),x=1431655765&(x|x<<1),d=16711935&(d|d<<8),d=252645135&(d|d<<4),d=858993459&(d|d<<2),d=1431655765&(d|d<<1),(d<<1|x)>>>0}i.default=r},\n", - " function _(s,t,i,h,e){h();i.default=class{constructor(){this.ids=[],this.values=[],this.length=0}clear(){this.length=0}push(s,t){let i=this.length++;for(this.ids[i]=s,this.values[i]=t;i>0;){const s=i-1>>1,h=this.values[s];if(t>=h)break;this.ids[i]=this.ids[s],this.values[i]=h,i=s}this.ids[i]=s,this.values[i]=t}pop(){if(0===this.length)return;const s=this.ids[0];if(this.length--,this.length>0){const s=this.ids[0]=this.ids[this.length],t=this.values[0]=this.values[this.length],i=this.length>>1;let h=0;for(;h=t)break;this.ids[h]=e,this.values[h]=l,h=s}this.ids[h]=s,this.values[h]=t}return s}peek(){if(0!==this.length)return this.ids[0]}peekValue(){if(0!==this.length)return this.values[0]}}},\n", - " function _(e,n,a,t,i){t();const l=(0,e(1).__importStar)(e(185));function r(e,n,{x0:a,x1:t,y0:i,y1:l},r){n.save(),n.beginPath(),n.moveTo(a,(i+l)/2),n.lineTo(t,(i+l)/2),e.line.apply(n,r),n.restore()}function c(e,n,{x0:a,x1:t,y0:i,y1:l},r){var c,o;const _=.1*Math.abs(t-a),s=.1*Math.abs(l-i),y=a+_,p=t-_,g=i+s,h=l-s;n.beginPath(),n.rect(y,g,p-y,h-g),e.fill.apply(n,r),null===(c=e.hatch)||void 0===c||c.apply(n,r),null===(o=e.line)||void 0===o||o.apply(n,r)}a.generic_line_scalar_legend=function(e,n,{x0:a,x1:t,y0:i,y1:l}){n.save(),n.beginPath(),n.moveTo(a,(i+l)/2),n.lineTo(t,(i+l)/2),e.line.apply(n),n.restore()},a.generic_line_vector_legend=r,a.generic_line_legend=r,a.generic_area_scalar_legend=function(e,n,{x0:a,x1:t,y0:i,y1:l}){var r,c;const o=.1*Math.abs(t-a),_=.1*Math.abs(l-i),s=a+o,y=t-o,p=i+_,g=l-_;n.beginPath(),n.rect(s,p,y-s,g-p),e.fill.apply(n),null===(r=e.hatch)||void 0===r||r.apply(n),null===(c=e.line)||void 0===c||c.apply(n)},a.generic_area_vector_legend=c,a.generic_area_legend=c,a.line_interpolation=function(e,n,a,t,i,r){const{sx:c,sy:o}=n;let _,s,y,p;\"point\"==n.type?([y,p]=e.yscale.r_invert(o-1,o+1),[_,s]=e.xscale.r_invert(c-1,c+1)):\"v\"==n.direction?([y,p]=e.yscale.r_invert(o,o),[_,s]=[Math.min(a-1,i-1),Math.max(a+1,i+1)]):([_,s]=e.xscale.r_invert(c,c),[y,p]=[Math.min(t-1,r-1),Math.max(t+1,r+1)]);const{x:g,y:h}=l.check_2_segments_intersect(_,y,s,p,a,t,i,r);return[g,h]}},\n", - " function _(t,n,e,i,r){function s(t,n){return(t.x-n.x)**2+(t.y-n.y)**2}function o(t,n,e){const i=s(n,e);if(0==i)return s(t,n);const r=((t.x-n.x)*(e.x-n.x)+(t.y-n.y)*(e.y-n.y))/i;if(r<0)return s(t,n);if(r>1)return s(t,e);return s(t,{x:n.x+r*(e.x-n.x),y:n.y+r*(e.y-n.y)})}i(),e.point_in_poly=function(t,n,e,i){let r=!1,s=e[e.length-1],o=i[i.length-1];for(let u=0;u0&&_<1&&h>0&&h<1,x:t+_*(e-t),y:n+_*(i-n)}}}},\n", - " function _(t,s,e,i,a){i();const l=t(1);var n;const _=t(178),o=t(184),c=(0,l.__importStar)(t(185)),h=(0,l.__importStar)(t(48)),r=t(72);class p extends _.XYGlyphView{_render(t,s,e){const{sx:i,sy:a}=null!=e?e:this;let l=!0;t.beginPath();for(const e of s){const s=i[e],n=a[e];isFinite(s+n)?l?(t.moveTo(s,n),l=!1):t.lineTo(s,n):(t.closePath(),l=!0)}t.closePath(),this.visuals.fill.apply(t),this.visuals.hatch.apply(t),this.visuals.line.apply(t)}draw_legend_for_index(t,s,e){(0,o.generic_area_scalar_legend)(this.visuals,t,s)}_hit_point(t){const s=new r.Selection;return c.point_in_poly(t.sx,t.sy,this.sx,this.sy)&&(s.add_to_selected_glyphs(this.model),s.view=this),s}}e.PatchView=p,p.__name__=\"PatchView\";class d extends _.XYGlyph{constructor(t){super(t)}}e.Patch=d,n=d,d.__name__=\"Patch\",n.prototype.default_view=p,n.mixins([h.LineScalar,h.FillScalar,h.HatchScalar])},\n", - " function _(e,t,s,i,r){i();const n=e(1);var a;const _=e(24),h=e(188),o=(0,n.__importStar)(e(185)),l=(0,n.__importStar)(e(18)),c=e(72);class d extends h.AreaView{_index_data(e){const{min:t,max:s}=Math,{data_size:i}=this;for(let r=0;r=0;t--)e.lineTo(r[t],n[t]);e.closePath(),this.visuals.fill.apply(e),this.visuals.hatch.apply(e)}_hit_point(e){const t=this.sy.length,s=new _.ScreenArray(2*t),i=new _.ScreenArray(2*t);for(let e=0,r=t;e({x1:[l.XCoordinateSpec,{field:\"x1\"}],x2:[l.XCoordinateSpec,{field:\"x2\"}],y:[l.YCoordinateSpec,{field:\"y\"}]})))},\n", - " function _(e,a,r,_,s){_();const n=e(1);var c;const i=e(179),l=e(184),t=(0,n.__importStar)(e(48));class o extends i.GlyphView{draw_legend_for_index(e,a,r){(0,l.generic_area_scalar_legend)(this.visuals,e,a)}}r.AreaView=o,o.__name__=\"AreaView\";class d extends i.Glyph{constructor(e){super(e)}}r.Area=d,c=d,d.__name__=\"Area\",c.mixins([t.FillScalar,t.HatchScalar])},\n", - " function _(e,t,s,i,r){i();const n=e(1);var a;const _=e(24),h=e(188),o=(0,n.__importStar)(e(185)),l=(0,n.__importStar)(e(18)),c=e(72);class y extends h.AreaView{_index_data(e){const{min:t,max:s}=Math,{data_size:i}=this;for(let r=0;r=0;t--)e.lineTo(i[t],n[t]);e.closePath(),this.visuals.fill.apply(e),this.visuals.hatch.apply(e)}scenterxy(e){return[this.sx[e],(this.sy1[e]+this.sy2[e])/2]}_hit_point(e){const t=this.sx.length,s=new _.ScreenArray(2*t),i=new _.ScreenArray(2*t);for(let e=0,r=t;e({x:[l.XCoordinateSpec,{field:\"x\"}],y1:[l.YCoordinateSpec,{field:\"y1\"}],y2:[l.YCoordinateSpec,{field:\"y2\"}]})))},\n", - " function _(e,i,s,t,n){var c;t();const o=e(53),r=e(24),u=e(191),_=e(70);class a extends o.Model{constructor(e){super(e)}initialize(){super.initialize(),this.compute_indices()}connect_signals(){super.connect_signals(),this.connect(this.properties.filters.change,(()=>this.compute_indices()));const e=()=>{const e=()=>this.compute_indices();null!=this.source&&(this.connect(this.source.change,e),this.source instanceof _.ColumnarDataSource&&(this.connect(this.source.streaming,e),this.connect(this.source.patching,e)))};let i=null!=this.source;i?e():this.connect(this.properties.source.change,(()=>{i||(e(),i=!0)}))}compute_indices(){var e;const{source:i}=this;if(null==i)return;const s=null!==(e=i.get_length())&&void 0!==e?e:1,t=r.Indices.all_set(s);for(const e of this.filters)t.intersect(e.compute_indices(i));this.indices=t,this._indices=[...t],this.indices_map_to_subset()}indices_map_to_subset(){this.indices_map={};for(let e=0;ethis._indices[e]))}convert_selection_to_subset(e){return e.map((e=>this.indices_map[e]))}convert_indices_from_subset(e){return e.map((e=>this._indices[e]))}}s.CDSView=a,c=a,a.__name__=\"CDSView\",c.define((({Array:e,Ref:i})=>({filters:[e(i(u.Filter)),[]],source:[i(_.ColumnarDataSource)]}))),c.internal((({Int:e,Dict:i,Ref:s,Nullable:t})=>({indices:[s(r.Indices)],indices_map:[i(e),{}],masked:[t(s(r.Indices)),null]})))},\n", - " function _(e,t,n,s,c){s();const o=e(53);class r extends o.Model{constructor(e){super(e)}}n.Filter=r,r.__name__=\"Filter\"},\n", - " function _(t,r,a,e,c){e(),c(\"BasicTickFormatter\",t(146).BasicTickFormatter),c(\"CategoricalTickFormatter\",t(142).CategoricalTickFormatter),c(\"DatetimeTickFormatter\",t(150).DatetimeTickFormatter),c(\"FuncTickFormatter\",t(193).FuncTickFormatter),c(\"LogTickFormatter\",t(163).LogTickFormatter),c(\"MercatorTickFormatter\",t(166).MercatorTickFormatter),c(\"NumeralTickFormatter\",t(194).NumeralTickFormatter),c(\"PrintfTickFormatter\",t(195).PrintfTickFormatter),c(\"TickFormatter\",t(131).TickFormatter)},\n", - " function _(t,e,n,s,r){var c;s();const i=t(131),a=t(13),u=t(34);class o extends i.TickFormatter{constructor(t){super(t)}get names(){return(0,a.keys)(this.args)}get values(){return(0,a.values)(this.args)}_make_func(){const t=(0,u.use_strict)(this.code);return new Function(\"tick\",\"index\",\"ticks\",...this.names,t)}doFormat(t,e){const n=this._make_func().bind({});return t.map(((t,e,s)=>`${n(t,e,s,...this.values)}`))}}n.FuncTickFormatter=o,c=o,o.__name__=\"FuncTickFormatter\",c.define((({Unknown:t,String:e,Dict:n})=>({args:[n(t),{}],code:[e,\"\"]})))},\n", - " function _(r,n,t,o,e){o();var a;const u=(0,r(1).__importStar)(r(153)),c=r(131),i=r(20);class s extends c.TickFormatter{constructor(r){super(r)}get _rounding_fn(){switch(this.rounding){case\"round\":case\"nearest\":return Math.round;case\"floor\":case\"rounddown\":return Math.floor;case\"ceil\":case\"roundup\":return Math.ceil}}doFormat(r,n){const{format:t,language:o,_rounding_fn:e}=this;return r.map((r=>u.format(r,t,o,e)))}}t.NumeralTickFormatter=s,a=s,s.__name__=\"NumeralTickFormatter\",a.define((({String:r})=>({format:[r,\"0,0\"],language:[r,\"en\"],rounding:[i.RoundingFunction,\"round\"]})))},\n", - " function _(t,r,n,o,a){var e;o();const i=t(131),s=t(152);class c extends i.TickFormatter{constructor(t){super(t)}doFormat(t,r){return t.map((t=>(0,s.sprintf)(this.format,t)))}}n.PrintfTickFormatter=c,e=c,c.__name__=\"PrintfTickFormatter\",e.define((({String:t})=>({format:[t,\"%s\"]})))},\n", - " function _(r,o,a,p,e){p(),e(\"CategoricalColorMapper\",r(197).CategoricalColorMapper),e(\"CategoricalMarkerMapper\",r(199).CategoricalMarkerMapper),e(\"CategoricalPatternMapper\",r(200).CategoricalPatternMapper),e(\"ContinuousColorMapper\",r(172).ContinuousColorMapper),e(\"ColorMapper\",r(173).ColorMapper),e(\"LinearColorMapper\",r(201).LinearColorMapper),e(\"LogColorMapper\",r(202).LogColorMapper),e(\"ScanningColorMapper\",r(171).ScanningColorMapper),e(\"EqHistColorMapper\",r(203).EqHistColorMapper)},\n", - " function _(t,o,r,a,e){var c;a();const s=t(198),l=t(173),n=t(67);class _ extends l.ColorMapper{constructor(t){super(t)}_v_compute(t,o,r,{nan_color:a}){(0,s.cat_v_compute)(t,this.factors,r,o,this.start,this.end,a)}}r.CategoricalColorMapper=_,c=_,_.__name__=\"CategoricalColorMapper\",c.define((({Number:t,Nullable:o})=>({factors:[n.FactorSeq],start:[t,0],end:[o(t),null]})))},\n", - " function _(n,t,e,l,i){l();const c=n(12),u=n(8);function f(n,t){if(n.length!=t.length)return!1;for(let e=0,l=n.length;ef(n,h)))),s=_<0||_>=e.length?r:e[_],l[g]=s}}},\n", - " function _(e,r,a,t,s){var c;t();const l=e(198),n=e(67),u=e(174),o=e(20);class p extends u.Mapper{constructor(e){super(e)}v_compute(e){const r=new Array(e.length);return(0,l.cat_v_compute)(e,this.factors,this.markers,r,this.start,this.end,this.default_value),r}}a.CategoricalMarkerMapper=p,c=p,p.__name__=\"CategoricalMarkerMapper\",c.define((({Number:e,Array:r,Nullable:a})=>({factors:[n.FactorSeq],markers:[r(o.MarkerType)],start:[e,0],end:[a(e),null],default_value:[o.MarkerType,\"circle\"]})))},\n", - " function _(t,e,a,r,n){var s;r();const c=t(198),l=t(67),p=t(174),u=t(20);class o extends p.Mapper{constructor(t){super(t)}v_compute(t){const e=new Array(t.length);return(0,c.cat_v_compute)(t,this.factors,this.patterns,e,this.start,this.end,this.default_value),e}}a.CategoricalPatternMapper=o,s=o,o.__name__=\"CategoricalPatternMapper\",s.define((({Number:t,Array:e,Nullable:a})=>({factors:[l.FactorSeq],patterns:[e(u.HatchPatternType)],start:[t,0],end:[a(t),null],default_value:[u.HatchPatternType,\" \"]})))},\n", - " function _(n,r,o,t,a){t();const e=n(172),i=n(12);class s extends e.ContinuousColorMapper{constructor(n){super(n)}scan(n,r){const o=null!=this.low?this.low:(0,i.min)(n),t=null!=this.high?this.high:(0,i.max)(n);return{max:t,min:o,norm_factor:1/(t-o),normed_interval:1/r}}cmap(n,r,o,t,a){const e=r.length-1;if(n==a.max)return r[e];const i=(n-a.min)*a.norm_factor,s=Math.floor(i/a.normed_interval);return s<0?o:s>e?t:r[s]}}o.LinearColorMapper=s,s.__name__=\"LinearColorMapper\"},\n", - " function _(o,t,n,r,l){r();const a=o(172),s=o(12);class e extends a.ContinuousColorMapper{constructor(o){super(o)}scan(o,t){const n=null!=this.low?this.low:(0,s.min)(o),r=null!=this.high?this.high:(0,s.max)(o);return{max:r,min:n,scale:t/(Math.log(r)-Math.log(n))}}cmap(o,t,n,r,l){const a=t.length-1;if(o>l.max)return r;if(o==l.max)return t[a];if(oa&&(e=a),t[e]}}n.LogColorMapper=e,e.__name__=\"LogColorMapper\"},\n", - " function _(n,t,e,i,o){var s;i();const r=n(171),a=n(12),l=n(9),c=n(19);class h extends r.ScanningColorMapper{constructor(n){super(n)}scan(n,t){const e=null!=this.low?this.low:(0,a.min)(n),i=null!=this.high?this.high:(0,a.max)(n),o=this.bins,s=(0,l.linspace)(e,i,o+1),r=(0,a.bin_counts)(n,s),h=new Array(o);for(let n=0,t=s.length;nn/p));let m=t-1,f=[],M=0,_=2*t;for(;m!=t&&M<4&&0!=m;){const n=_/m;if(n>1e3)break;_=Math.round(Math.max(t*n,t));const e=(0,l.range)(0,_),i=(0,a.map)(u,(n=>n*(_-1)));f=(0,a.interpolate)(e,i,h);m=(0,l.uniq)(f).length-1,M++}if(0==m){f=[e,i];for(let n=0;n({bins:[n,65536]})))},\n", - " function _(a,e,l,c,n){c(),n(\"CategoricalScale\",a(62).CategoricalScale),n(\"ContinuousScale\",a(60).ContinuousScale),n(\"LinearScale\",a(59).LinearScale),n(\"LinearInterpolationScale\",a(205).LinearInterpolationScale),n(\"LogScale\",a(61).LogScale),n(\"Scale\",a(55).Scale)},\n", - " function _(e,r,n,t,a){var i;t();const s=e(55),o=e(59),c=e(12);class _ extends s.Scale{constructor(e){super(e)}connect_signals(){super.connect_signals();const{source_range:e,target_range:r}=this.properties;this.on_change([e,r],(()=>{this.linear_scale=new o.LinearScale({source_range:this.source_range,target_range:this.target_range})}))}get s_compute(){throw new Error(\"not implemented\")}get s_invert(){throw new Error(\"not implemented\")}compute(e){return e}v_compute(e){const{binning:r}=this,{start:n,end:t}=this.source_range,a=n,i=t,s=r.length,o=(t-n)/(s-1),_=new Float64Array(s);for(let e=0;e{if(ei)return i;const n=(0,c.left_edge_index)(e,r);if(-1==n)return a;if(n>=s-1)return i;const t=r[n],o=(e-t)/(r[n+1]-t),l=_[n];return l+o*(_[n+1]-l)}));return this.linear_scale.v_compute(l)}invert(e){return e}v_invert(e){return new Float64Array(e)}}n.LinearInterpolationScale=_,i=_,_.__name__=\"LinearInterpolationScale\",i.internal((({Arrayable:e,Ref:r})=>({binning:[e],linear_scale:[r(o.LinearScale),e=>new o.LinearScale({source_range:e.source_range,target_range:e.target_range})]})))},\n", - " function _(a,n,e,g,R){g(),R(\"DataRange\",a(64).DataRange),R(\"DataRange1d\",a(63).DataRange1d),R(\"FactorRange\",a(67).FactorRange),R(\"Range\",a(57).Range),R(\"Range1d\",a(58).Range1d)},\n", - " function _(a,o,i,t,e){t();var n=a(124);e(\"Sizeable\",n.Sizeable),e(\"SizingPolicy\",n.SizingPolicy);var c=a(125);e(\"Layoutable\",c.Layoutable),e(\"LayoutItem\",c.LayoutItem);var r=a(208);e(\"HStack\",r.HStack),e(\"VStack\",r.VStack);var l=a(209);e(\"Grid\",l.Grid),e(\"Row\",l.Row),e(\"Column\",l.Column);var S=a(210);e(\"ContentBox\",S.ContentBox),e(\"VariadicBox\",S.VariadicBox)},\n", - " function _(t,e,h,i,r){i();const n=t(125),o=t(65);class s extends n.Layoutable{constructor(){super(...arguments),this.children=[]}*[Symbol.iterator](){yield*this.children}}h.Stack=s,s.__name__=\"Stack\";class c extends s{_measure(t){let e=0,h=0;for(const t of this.children){const i=t.measure({width:0,height:0});e+=i.width,h=Math.max(h,i.height)}return{width:e,height:h}}_set_geometry(t,e){super._set_geometry(t,e);const h=this.absolute?t.top:0;let i=this.absolute?t.left:0;const{height:r}=t;for(const t of this.children){const{width:e}=t.measure({width:0,height:0});t.set_geometry(new o.BBox({left:i,width:e,top:h,height:r})),i+=e}}}h.HStack=c,c.__name__=\"HStack\";class a extends s{_measure(t){let e=0,h=0;for(const t of this.children){const i=t.measure({width:0,height:0});e=Math.max(e,i.width),h+=i.height}return{width:e,height:h}}_set_geometry(t,e){super._set_geometry(t,e);const h=this.absolute?t.left:0;let i=this.absolute?t.top:0;const{width:r}=t;for(const t of this.children){const{height:e}=t.measure({width:0,height:0});t.set_geometry(new o.BBox({top:i,height:e,left:h,width:r})),i+=e}}}h.VStack=a,a.__name__=\"VStack\";class l extends n.Layoutable{constructor(){super(...arguments),this.children=[]}*[Symbol.iterator](){yield*this.children}_measure(t){const{width_policy:e,height_policy:h}=this.sizing,{min:i,max:r}=Math;let n=0,o=0;for(const e of this.children){const{width:h,height:i}=e.measure(t);n=r(n,h),o=r(o,i)}return{width:(()=>{const{width:h}=this.sizing;if(t.width==1/0)return\"fixed\"==e&&null!=h?h:n;switch(e){case\"fixed\":return null!=h?h:n;case\"min\":return n;case\"fit\":return null!=h?i(t.width,h):t.width;case\"max\":return null!=h?r(t.width,h):t.width}})(),height:(()=>{const{height:e}=this.sizing;if(t.height==1/0)return\"fixed\"==h&&null!=e?e:o;switch(h){case\"fixed\":return null!=e?e:o;case\"min\":return o;case\"fit\":return null!=e?i(t.height,e):t.height;case\"max\":return null!=e?r(t.height,e):t.height}})()}}_set_geometry(t,e){super._set_geometry(t,e);const h=this.absolute?t:t.relative(),{left:i,right:r,top:n,bottom:s}=h,c=Math.round(h.vcenter),a=Math.round(h.hcenter);for(const e of this.children){const{margin:h,halign:l,valign:d}=e.sizing,{width:u,height:g,inner:_}=e.measure(t),w=(()=>{switch(`${d}_${l}`){case\"start_start\":return new o.BBox({left:i+h.left,top:n+h.top,width:u,height:g});case\"start_center\":return new o.BBox({hcenter:a,top:n+h.top,width:u,height:g});case\"start_end\":return new o.BBox({right:r-h.right,top:n+h.top,width:u,height:g});case\"center_start\":return new o.BBox({left:i+h.left,vcenter:c,width:u,height:g});case\"center_center\":return new o.BBox({hcenter:a,vcenter:c,width:u,height:g});case\"center_end\":return new o.BBox({right:r-h.right,vcenter:c,width:u,height:g});case\"end_start\":return new o.BBox({left:i+h.left,bottom:s-h.bottom,width:u,height:g});case\"end_center\":return new o.BBox({hcenter:a,bottom:s-h.bottom,width:u,height:g});case\"end_end\":return new o.BBox({right:r-h.right,bottom:s-h.bottom,width:u,height:g})}})(),m=null==_?w:new o.BBox({left:w.left+_.left,top:w.top+_.top,right:w.right-_.right,bottom:w.bottom-_.bottom});e.set_geometry(w,m)}}}h.NodeLayout=l,l.__name__=\"NodeLayout\"},\n", - " function _(t,i,s,e,o){e();const n=t(124),l=t(125),r=t(8),h=t(65),c=t(9),{max:a,round:g}=Math;class p{constructor(t){this.def=t,this._map=new Map}get(t){let i=this._map.get(t);return void 0===i&&(i=this.def(),this._map.set(t,i)),i}apply(t,i){const s=this.get(t);this._map.set(t,i(s))}}p.__name__=\"DefaultMap\";class f{constructor(){this._items=[],this._nrows=0,this._ncols=0}get nrows(){return this._nrows}get ncols(){return this._ncols}add(t,i){const{r1:s,c1:e}=t;this._nrows=a(this._nrows,s+1),this._ncols=a(this._ncols,e+1),this._items.push({span:t,data:i})}at(t,i){return this._items.filter((({span:s})=>s.r0<=t&&t<=s.r1&&s.c0<=i&&i<=s.c1)).map((({data:t})=>t))}row(t){return this._items.filter((({span:i})=>i.r0<=t&&t<=i.r1)).map((({data:t})=>t))}col(t){return this._items.filter((({span:i})=>i.c0<=t&&t<=i.c1)).map((({data:t})=>t))}foreach(t){for(const{span:i,data:s}of this._items)t(i,s)}map(t){const i=new f;for(const{span:s,data:e}of this._items)i.add(s,t(s,e));return i}}f.__name__=\"Container\";class _ extends l.Layoutable{constructor(t=[]){super(),this.items=t,this.rows=\"auto\",this.cols=\"auto\",this.spacing=0}*[Symbol.iterator](){for(const{layout:t}of this.items)yield t}is_width_expanding(){if(super.is_width_expanding())return!0;if(\"fixed\"==this.sizing.width_policy)return!1;const{cols:t}=this._state;return(0,c.some)(t,(t=>\"max\"==t.policy))}is_height_expanding(){if(super.is_height_expanding())return!0;if(\"fixed\"==this.sizing.height_policy)return!1;const{rows:t}=this._state;return(0,c.some)(t,(t=>\"max\"==t.policy))}_init(){var t,i,s,e;super._init();const o=new f;for(const{layout:t,row:i,col:s,row_span:e,col_span:n}of this.items)if(t.sizing.visible){const l=i,r=s,h=i+(null!=e?e:1)-1,c=s+(null!=n?n:1)-1;o.add({r0:l,c0:r,r1:h,c1:c},t)}const{nrows:n,ncols:l}=o,h=new Array(n);for(let s=0;s{var t;const i=(0,r.isPlainObject)(this.rows)?null!==(t=this.rows[s])&&void 0!==t?t:this.rows[\"*\"]:this.rows;return null==i?{policy:\"auto\"}:(0,r.isNumber)(i)?{policy:\"fixed\",height:i}:(0,r.isString)(i)?{policy:i}:i})(),n=null!==(t=e.align)&&void 0!==t?t:\"auto\";if(\"fixed\"==e.policy)h[s]={policy:\"fixed\",height:e.height,align:n};else if(\"min\"==e.policy)h[s]={policy:\"min\",align:n};else if(\"fit\"==e.policy||\"max\"==e.policy)h[s]={policy:e.policy,flex:null!==(i=e.flex)&&void 0!==i?i:1,align:n};else{if(\"auto\"!=e.policy)throw new Error(\"unrechable\");(0,c.some)(o.row(s),(t=>t.is_height_expanding()))?h[s]={policy:\"max\",flex:1,align:n}:h[s]={policy:\"min\",align:n}}}const a=new Array(l);for(let t=0;t{var i;const s=(0,r.isPlainObject)(this.cols)?null!==(i=this.cols[t])&&void 0!==i?i:this.cols[\"*\"]:this.cols;return null==s?{policy:\"auto\"}:(0,r.isNumber)(s)?{policy:\"fixed\",width:s}:(0,r.isString)(s)?{policy:s}:s})(),n=null!==(s=i.align)&&void 0!==s?s:\"auto\";if(\"fixed\"==i.policy)a[t]={policy:\"fixed\",width:i.width,align:n};else if(\"min\"==i.policy)a[t]={policy:\"min\",align:n};else if(\"fit\"==i.policy||\"max\"==i.policy)a[t]={policy:i.policy,flex:null!==(e=i.flex)&&void 0!==e?e:1,align:n};else{if(\"auto\"!=i.policy)throw new Error(\"unrechable\");(0,c.some)(o.col(t),(t=>t.is_width_expanding()))?a[t]={policy:\"max\",flex:1,align:n}:a[t]={policy:\"min\",align:n}}}const[g,p]=(0,r.isNumber)(this.spacing)?[this.spacing,this.spacing]:this.spacing;this._state={items:o,nrows:n,ncols:l,rows:h,cols:a,rspacing:g,cspacing:p}}_measure_totals(t,i){const{nrows:s,ncols:e,rspacing:o,cspacing:n}=this._state;return{height:(0,c.sum)(t)+(s-1)*o,width:(0,c.sum)(i)+(e-1)*n}}_measure_cells(t){const{items:i,nrows:s,ncols:e,rows:o,cols:l,rspacing:r,cspacing:h}=this._state,c=new Array(s);for(let t=0;t{const{r0:e,c0:f,r1:d,c1:u}=i,w=(d-e)*r,m=(u-f)*h;let y=0;for(let i=e;i<=d;i++)y+=t(i,f).height;y+=w;let x=0;for(let i=f;i<=u;i++)x+=t(e,i).width;x+=m;const b=s.measure({width:x,height:y});_.add(i,{layout:s,size_hint:b});const z=new n.Sizeable(b).grow_by(s.sizing.margin);z.height-=w,z.width-=m;const v=[];for(let t=e;t<=d;t++){const i=o[t];\"fixed\"==i.policy?z.height-=i.height:v.push(t)}if(z.height>0){const t=g(z.height/v.length);for(const i of v)c[i]=a(c[i],t)}const j=[];for(let t=f;t<=u;t++){const i=l[t];\"fixed\"==i.policy?z.width-=i.width:j.push(t)}if(z.width>0){const t=g(z.width/j.length);for(const i of j)p[i]=a(p[i],t)}}));return{size:this._measure_totals(c,p),row_heights:c,col_widths:p,size_hints:_}}_measure_grid(t){const{nrows:i,ncols:s,rows:e,cols:o,rspacing:n,cspacing:l}=this._state,r=this._measure_cells(((t,i)=>{const s=e[t],n=o[i];return{width:\"fixed\"==n.policy?n.width:1/0,height:\"fixed\"==s.policy?s.height:1/0}}));let h;h=\"fixed\"==this.sizing.height_policy&&null!=this.sizing.height?this.sizing.height:t.height!=1/0&&this.is_height_expanding()?t.height:r.size.height;let c,p=0;for(let t=0;t0)for(let t=0;ti?i:e,t--}}}c=\"fixed\"==this.sizing.width_policy&&null!=this.sizing.width?this.sizing.width:t.width!=1/0&&this.is_width_expanding()?t.width:r.size.width;let f=0;for(let t=0;t0)for(let t=0;ts?s:o,t--}}}const{row_heights:_,col_widths:d,size_hints:u}=this._measure_cells(((t,i)=>({width:r.col_widths[i],height:r.row_heights[t]})));return{size:this._measure_totals(_,d),row_heights:_,col_widths:d,size_hints:u}}_measure(t){const{size:i}=this._measure_grid(t);return i}_set_geometry(t,i){super._set_geometry(t,i);const{nrows:s,ncols:e,rspacing:o,cspacing:n}=this._state,{row_heights:l,col_widths:r,size_hints:c}=this._measure_grid(t),f=this._state.rows.map(((t,i)=>Object.assign(Object.assign({},t),{top:0,height:l[i],get bottom(){return this.top+this.height}}))),_=this._state.cols.map(((t,i)=>Object.assign(Object.assign({},t),{left:0,width:r[i],get right(){return this.left+this.width}}))),d=c.map(((t,i)=>Object.assign(Object.assign({},i),{outer:new h.BBox,inner:new h.BBox})));for(let i=0,e=this.absolute?t.top:0;i{const{layout:r,size_hint:c}=l,{sizing:a}=r,{width:p,height:d}=c,u=function(t,i){let s=(i-t)*n;for(let e=t;e<=i;e++)s+=_[e].width;return s}(i,e),w=function(t,i){let s=(i-t)*o;for(let e=t;e<=i;e++)s+=f[e].height;return s}(t,s),m=i==e&&\"auto\"!=_[i].align?_[i].align:a.halign,y=t==s&&\"auto\"!=f[t].align?f[t].align:a.valign;let x=_[i].left;\"start\"==m?x+=a.margin.left:\"center\"==m?x+=g((u-p)/2):\"end\"==m&&(x+=u-a.margin.right-p);let b=f[t].top;\"start\"==y?b+=a.margin.top:\"center\"==y?b+=g((w-d)/2):\"end\"==y&&(b+=w-a.margin.bottom-d),l.outer=new h.BBox({left:x,top:b,width:p,height:d})}));const u=f.map((()=>({start:new p((()=>0)),end:new p((()=>0))}))),w=_.map((()=>({start:new p((()=>0)),end:new p((()=>0))})));d.foreach((({r0:t,c0:i,r1:s,c1:e},{size_hint:o,outer:n})=>{const{inner:l}=o;null!=l&&(u[t].start.apply(n.top,(t=>a(t,l.top))),u[s].end.apply(f[s].bottom-n.bottom,(t=>a(t,l.bottom))),w[i].start.apply(n.left,(t=>a(t,l.left))),w[e].end.apply(_[e].right-n.right,(t=>a(t,l.right))))})),d.foreach((({r0:t,c0:i,r1:s,c1:e},o)=>{const{size_hint:n,outer:l}=o,r=t=>{const i=this.absolute?l:l.relative(),s=i.left+t.left,e=i.top+t.top,o=i.right-t.right,n=i.bottom-t.bottom;return new h.BBox({left:s,top:e,right:o,bottom:n})};if(null!=n.inner){let h=r(n.inner);if(!1!==n.align){const o=u[t].start.get(l.top),n=u[s].end.get(f[s].bottom-l.bottom),c=w[i].start.get(l.left),a=w[e].end.get(_[e].right-l.right);try{h=r({top:o,bottom:n,left:c,right:a})}catch(t){}}o.inner=h}else o.inner=l})),d.foreach(((t,{layout:i,outer:s,inner:e})=>{i.set_geometry(s,e)}))}}s.Grid=_,_.__name__=\"Grid\";class d extends _{constructor(t){super(),this.items=t.map(((t,i)=>({layout:t,row:0,col:i}))),this.rows=\"fit\"}}s.Row=d,d.__name__=\"Row\";class u extends _{constructor(t){super(),this.items=t.map(((t,i)=>({layout:t,row:i,col:0}))),this.cols=\"fit\"}}s.Column=u,u.__name__=\"Column\"},\n", - " function _(e,t,s,n,i){n();const a=e(125),c=e(124),o=e(43);class r extends a.ContentLayoutable{constructor(e){super(),this.content_size=(0,o.unsized)(e,(()=>new c.Sizeable((0,o.size)(e))))}_content_size(){return this.content_size}}s.ContentBox=r,r.__name__=\"ContentBox\";class _ extends a.Layoutable{constructor(e){super(),this.el=e}_measure(e){const t=new c.Sizeable(e).bounded_to(this.sizing.size);return(0,o.sized)(this.el,t,(()=>{const e=new c.Sizeable((0,o.content_size)(this.el)),{border:t,padding:s}=(0,o.extents)(this.el);return e.grow_by(t).grow_by(s).map(Math.ceil)}))}}s.VariadicBox=_,_.__name__=\"VariadicBox\";class h extends _{constructor(e){super(e),this._cache=new Map}_measure(e){const{width:t,height:s}=e,n=`${t},${s}`;let i=this._cache.get(n);return null==i&&(i=super._measure(e),this._cache.set(n,i)),i}invalidate_cache(){this._cache.clear()}}s.CachedVariadicBox=h,h.__name__=\"CachedVariadicBox\"},\n", - " function _(t,e,i,h,o){h();const s=t(124),r=t(125),n=t(65);class g extends r.Layoutable{constructor(){super(...arguments),this.min_border={left:0,top:0,right:0,bottom:0},this.padding={left:0,top:0,right:0,bottom:0}}*[Symbol.iterator](){yield this.top_panel,yield this.bottom_panel,yield this.left_panel,yield this.right_panel,yield this.center_panel}_measure(t){t=new s.Sizeable({width:\"fixed\"==this.sizing.width_policy||t.width==1/0?this.sizing.width:t.width,height:\"fixed\"==this.sizing.height_policy||t.height==1/0?this.sizing.height:t.height});const e=this.left_panel.measure({width:0,height:t.height}),i=Math.max(e.width,this.min_border.left)+this.padding.left,h=this.right_panel.measure({width:0,height:t.height}),o=Math.max(h.width,this.min_border.right)+this.padding.right,r=this.top_panel.measure({width:t.width,height:0}),n=Math.max(r.height,this.min_border.top)+this.padding.top,g=this.bottom_panel.measure({width:t.width,height:0}),a=Math.max(g.height,this.min_border.bottom)+this.padding.bottom,d=new s.Sizeable(t).shrink_by({left:i,right:o,top:n,bottom:a}),l=this.center_panel.measure(d);return{width:i+l.width+o,height:n+l.height+a,inner:{left:i,right:o,top:n,bottom:a},align:(()=>{const{width_policy:t,height_policy:e}=this.center_panel.sizing;return\"fixed\"!=t&&\"fixed\"!=e})()}}_set_geometry(t,e){super._set_geometry(t,e),this.center_panel.set_geometry(e);const i=this.left_panel.measure({width:0,height:t.height}),h=this.right_panel.measure({width:0,height:t.height}),o=this.top_panel.measure({width:t.width,height:0}),s=this.bottom_panel.measure({width:t.width,height:0}),{left:r,top:g,right:a,bottom:d}=e;this.top_panel.set_geometry(new n.BBox({left:r,right:a,bottom:g,height:o.height})),this.bottom_panel.set_geometry(new n.BBox({left:r,right:a,top:d,height:s.height})),this.left_panel.set_geometry(new n.BBox({top:g,bottom:d,right:r,width:i.width})),this.right_panel.set_geometry(new n.BBox({top:g,bottom:d,left:a,width:h.width}))}}i.BorderLayout=g,g.__name__=\"BorderLayout\"},\n", - " function _(t,e,i,s,l){s();const n=t(1);var o;const a=t(119),_=t(10),d=t(20),h=t(120),r=t(123),u=(0,n.__importStar)(t(48));class c extends a.TextAnnotationView{update_layout(){const{panel:t}=this;this.layout=null!=t?new r.SideLayout(t,(()=>this.get_size()),!1):void 0}_get_size(){const{text:t}=this.model,e=new h.TextBox({text:t}),{angle:i,angle_units:s}=this.model;e.angle=(0,_.resolve_angle)(i,s),e.visuals=this.visuals.text.values();const{width:l,height:n}=e.size();return{width:l,height:n}}_render(){const{angle:t,angle_units:e}=this.model,i=(0,_.resolve_angle)(t,e),s=null!=this.layout?this.layout:this.plot_view.frame,l=this.coordinates.x_scale,n=this.coordinates.y_scale;let o=\"data\"==this.model.x_units?l.compute(this.model.x):s.bbox.xview.compute(this.model.x),a=\"data\"==this.model.y_units?n.compute(this.model.y):s.bbox.yview.compute(this.model.y);o+=this.model.x_offset,a-=this.model.y_offset;(\"canvas\"==this.model.render_mode?this._canvas_text.bind(this):this._css_text.bind(this))(this.layer.ctx,this.model.text,o,a,i)}}i.LabelView=c,c.__name__=\"LabelView\";class x extends a.TextAnnotation{constructor(t){super(t)}}i.Label=x,o=x,x.__name__=\"Label\",o.prototype.default_view=c,o.mixins([u.Text,[\"border_\",u.Line],[\"background_\",u.Fill]]),o.define((({Number:t,String:e,Angle:i})=>({x:[t],x_units:[d.SpatialUnits,\"data\"],y:[t],y_units:[d.SpatialUnits,\"data\"],text:[e,\"\"],angle:[i,0],angle_units:[d.AngleUnits,\"rad\"],x_offset:[t,0],y_offset:[t,0]}))),o.override({background_fill_color:null,border_line_color:null})},\n", - " function _(t,e,s,i,l){i();const o=t(1);var a;const r=t(69),n=(0,o.__importStar)(t(48)),d=t(20),_=t(43),c=t(120),h=(0,o.__importStar)(t(18)),u=t(11);class v extends r.DataAnnotationView{set_data(t){var e;if(super.set_data(t),null===(e=this.els)||void 0===e||e.forEach((t=>(0,_.remove)(t))),\"css\"==this.model.render_mode){const t=this.els=[...this.text].map((()=>(0,_.div)({style:{display:\"none\"}})));for(const e of t)this.plot_view.canvas_view.add_overlay(e)}else delete this.els}remove(){var t;null===(t=this.els)||void 0===t||t.forEach((t=>(0,_.remove)(t))),super.remove()}_rerender(){\"css\"==this.model.render_mode?this.render():this.request_render()}map_data(){const{x_scale:t,y_scale:e}=this.coordinates,s=null!=this.layout?this.layout:this.plot_view.frame;this.sx=\"data\"==this.model.x_units?t.v_compute(this._x):s.bbox.xview.v_compute(this._x),this.sy=\"data\"==this.model.y_units?e.v_compute(this._y):s.bbox.yview.v_compute(this._y)}paint(){const t=\"canvas\"==this.model.render_mode?this._v_canvas_text.bind(this):this._v_css_text.bind(this),{ctx:e}=this.layer;for(let s=0,i=this.text.length;s{switch(this.visuals.text.text_align.get(e)){case\"left\":return[\"left\",\"0%\"];case\"center\":return[\"center\",\"-50%\"];case\"right\":return[\"right\",\"-100%\"]}})(),[d,c]=(()=>{switch(this.visuals.text.text_baseline.get(e)){case\"top\":return[\"top\",\"0%\"];case\"middle\":return[\"center\",\"-50%\"];case\"bottom\":return[\"bottom\",\"-100%\"];default:return[\"center\",\"-50%\"]}})();let h=`translate(${n}, ${c})`;o&&(h+=`rotate(${o}rad)`),a.style.transformOrigin=`${r} ${d}`,a.style.transform=h,this.layout,this.visuals.background_fill.doit&&(this.visuals.background_fill.set_vectorize(t,e),a.style.backgroundColor=t.fillStyle),this.visuals.border_line.doit&&(this.visuals.border_line.set_vectorize(t,e),a.style.borderStyle=t.lineDash.length<2?\"solid\":\"dashed\",a.style.borderWidth=`${t.lineWidth}px`,a.style.borderColor=t.strokeStyle),(0,_.display)(a)}}s.LabelSetView=v,v.__name__=\"LabelSetView\";class x extends r.DataAnnotation{constructor(t){super(t)}}s.LabelSet=x,a=x,x.__name__=\"LabelSet\",a.prototype.default_view=v,a.mixins([n.TextVector,[\"border_\",n.LineVector],[\"background_\",n.FillVector]]),a.define((()=>({x:[h.XCoordinateSpec,{field:\"x\"}],y:[h.YCoordinateSpec,{field:\"y\"}],x_units:[d.SpatialUnits,\"data\"],y_units:[d.SpatialUnits,\"data\"],text:[h.StringSpec,{field:\"text\"}],angle:[h.AngleSpec,0],x_offset:[h.NumberSpec,{value:0}],y_offset:[h.NumberSpec,{value:0}],render_mode:[d.RenderMode,\"canvas\"]}))),a.override({background_fill_color:null,border_line_color:null})},\n", - " function _(t,e,i,l,s){l();const n=t(1);var o;const h=t(40),a=t(215),_=t(20),r=(0,n.__importStar)(t(48)),d=t(15),c=t(123),g=t(121),m=t(65),b=t(9),f=t(8),u=t(11);class x extends h.AnnotationView{update_layout(){const{panel:t}=this;this.layout=null!=t?new c.SideLayout(t,(()=>this.get_size())):void 0}cursor(t,e){return\"none\"==this.model.click_policy?null:\"pointer\"}get legend_padding(){return null!=this.model.border_line_color?this.model.padding:0}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render())),this.connect(this.model.item_change,(()=>this.request_render()))}compute_legend_bbox(){const t=this.model.get_legend_names(),{glyph_height:e,glyph_width:i}=this.model,{label_height:l,label_width:s}=this.model;this.max_label_height=(0,b.max)([(0,g.font_metrics)(this.visuals.label_text.font_value()).height,l,e]);const{ctx:n}=this.layer;n.save(),this.visuals.label_text.set_value(n),this.text_widths=new Map;for(const e of t)this.text_widths.set(e,(0,b.max)([n.measureText(e).width,s]));this.visuals.title_text.set_value(n),this.title_height=this.model.title?(0,g.font_metrics)(this.visuals.title_text.font_value()).height+this.model.title_standoff:0,this.title_width=this.model.title?n.measureText(this.model.title).width:0,n.restore();const o=Math.max((0,b.max)([...this.text_widths.values()]),0),h=this.model.margin,{legend_padding:a}=this,_=this.model.spacing,{label_standoff:r}=this.model;let d,c;if(\"vertical\"==this.model.orientation)d=t.length*this.max_label_height+Math.max(t.length-1,0)*_+2*a+this.title_height,c=(0,b.max)([o+i+r+2*a,this.title_width+2*a]);else{let e=2*a+Math.max(t.length-1,0)*_;for(const[,t]of this.text_widths)e+=(0,b.max)([t,s])+i+r;c=(0,b.max)([this.title_width+2*a,e]),d=this.max_label_height+this.title_height+2*a}const x=null!=this.layout?this.layout:this.plot_view.frame,[p,w]=x.bbox.ranges,{location:v}=this.model;let y,k;if((0,f.isString)(v))switch(v){case\"top_left\":y=p.start+h,k=w.start+h;break;case\"top\":case\"top_center\":y=(p.end+p.start)/2-c/2,k=w.start+h;break;case\"top_right\":y=p.end-h-c,k=w.start+h;break;case\"bottom_right\":y=p.end-h-c,k=w.end-h-d;break;case\"bottom\":case\"bottom_center\":y=(p.end+p.start)/2-c/2,k=w.end-h-d;break;case\"bottom_left\":y=p.start+h,k=w.end-h-d;break;case\"left\":case\"center_left\":y=p.start+h,k=(w.end+w.start)/2-d/2;break;case\"center\":case\"center_center\":y=(p.end+p.start)/2-c/2,k=(w.end+w.start)/2-d/2;break;case\"right\":case\"center_right\":y=p.end-h-c,k=(w.end+w.start)/2-d/2}else if((0,f.isArray)(v)&&2==v.length){const[t,e]=v;y=x.bbox.xview.compute(t),k=x.bbox.yview.compute(e)-d}else(0,u.unreachable)();return new m.BBox({left:y,top:k,width:c,height:d})}interactive_bbox(){return this.compute_legend_bbox()}interactive_hit(t,e){return this.interactive_bbox().contains(t,e)}on_hit(t,e){let i;const{glyph_width:l}=this.model,{legend_padding:s}=this,n=this.model.spacing,{label_standoff:o}=this.model;let h=i=s;const a=this.compute_legend_bbox(),_=\"vertical\"==this.model.orientation;for(const r of this.model.items){const d=r.get_labels_list_from_label_prop();for(const c of d){const d=a.x+h,g=a.y+i+this.title_height;let b,f;[b,f]=_?[a.width-2*s,this.max_label_height]:[this.text_widths.get(c)+l+o,this.max_label_height];if(new m.BBox({left:d,top:g,width:b,height:f}).contains(t,e)){switch(this.model.click_policy){case\"hide\":for(const t of r.renderers)t.visible=!t.visible;break;case\"mute\":for(const t of r.renderers)t.muted=!t.muted}return!0}_?i+=this.max_label_height+n:h+=this.text_widths.get(c)+l+o+n}}return!1}_render(){if(0==this.model.items.length)return;if(!(0,b.some)(this.model.items,(t=>t.visible)))return;for(const t of this.model.items)t.legend=this.model;const{ctx:t}=this.layer,e=this.compute_legend_bbox();t.save(),this._draw_legend_box(t,e),this._draw_legend_items(t,e),this._draw_title(t,e),t.restore()}_draw_legend_box(t,e){t.beginPath(),t.rect(e.x,e.y,e.width,e.height),this.visuals.background_fill.apply(t),this.visuals.border_line.apply(t)}_draw_legend_items(t,e){const{glyph_width:i,glyph_height:l}=this.model,{legend_padding:s}=this,n=this.model.spacing,{label_standoff:o}=this.model;let h=s,a=s;const _=\"vertical\"==this.model.orientation;for(const r of this.model.items){if(!r.visible)continue;const d=r.get_labels_list_from_label_prop(),c=r.get_field_from_label_prop();if(0==d.length)continue;const g=(()=>{switch(this.model.click_policy){case\"none\":return!0;case\"hide\":return(0,b.every)(r.renderers,(t=>t.visible));case\"mute\":return(0,b.every)(r.renderers,(t=>!t.muted))}})();for(const m of d){const d=e.x+h,b=e.y+a+this.title_height,f=d+i,u=b+l;_?a+=this.max_label_height+n:h+=this.text_widths.get(m)+i+o+n,this.visuals.label_text.set_value(t),t.fillText(m,f+o,b+this.max_label_height/2);for(const e of r.renderers){const i=this.plot_view.renderer_view(e);null==i||i.draw_legend(t,d,f,b,u,c,m,r.index)}if(!g){let l,n;[l,n]=_?[e.width-2*s,this.max_label_height]:[this.text_widths.get(m)+i+o,this.max_label_height],t.beginPath(),t.rect(d,b,l,n),this.visuals.inactive_fill.set_value(t),t.fill()}}}}_draw_title(t,e){const{title:i}=this.model;i&&this.visuals.title_text.doit&&(t.save(),t.translate(e.x0,e.y0+this.title_height),this.visuals.title_text.set_value(t),t.fillText(i,this.legend_padding,this.legend_padding-this.model.title_standoff),t.restore())}_get_size(){const{width:t,height:e}=this.compute_legend_bbox();return{width:t+2*this.model.margin,height:e+2*this.model.margin}}}i.LegendView=x,x.__name__=\"LegendView\";class p extends h.Annotation{constructor(t){super(t)}initialize(){super.initialize(),this.item_change=new d.Signal0(this,\"item_change\")}get_legend_names(){const t=[];for(const e of this.items){const i=e.get_labels_list_from_label_prop();t.push(...i)}return t}}i.Legend=p,o=p,p.__name__=\"Legend\",o.prototype.default_view=x,o.mixins([[\"label_\",r.Text],[\"title_\",r.Text],[\"inactive_\",r.Fill],[\"border_\",r.Line],[\"background_\",r.Fill]]),o.define((({Number:t,String:e,Array:i,Tuple:l,Or:s,Ref:n,Nullable:o})=>({orientation:[_.Orientation,\"vertical\"],location:[s(_.LegendLocation,l(t,t)),\"top_right\"],title:[o(e),null],title_standoff:[t,5],label_standoff:[t,5],glyph_height:[t,20],glyph_width:[t,20],label_height:[t,20],label_width:[t,20],margin:[t,10],padding:[t,10],spacing:[t,3],items:[i(n(a.LegendItem)),[]],click_policy:[_.LegendClickPolicy,\"none\"]}))),o.override({border_line_color:\"#e5e5e5\",border_line_alpha:.5,border_line_width:1,background_fill_color:\"#ffffff\",background_fill_alpha:.95,inactive_fill_color:\"white\",inactive_fill_alpha:.7,label_text_font_size:\"13px\",label_text_baseline:\"middle\",title_text_font_size:\"13px\",title_text_font_style:\"italic\"})},\n", - " function _(e,r,l,n,t){n();const i=e(1);var s;const o=e(53),a=e(175),_=e(70),u=e(216),d=(0,i.__importStar)(e(18)),c=e(19),f=e(9);class h extends o.Model{constructor(e){super(e)}_check_data_sources_on_renderers(){if(null!=this.get_field_from_label_prop()){if(this.renderers.length<1)return!1;const e=this.renderers[0].data_source;if(null!=e)for(const r of this.renderers)if(r.data_source!=e)return!1}return!0}_check_field_label_on_data_source(){const e=this.get_field_from_label_prop();if(null!=e){if(this.renderers.length<1)return!1;const r=this.renderers[0].data_source;if(null!=r&&!(0,f.includes)(r.columns(),e))return!1}return!0}initialize(){super.initialize(),this.legend=null,this.connect(this.change,(()=>{var e;return null===(e=this.legend)||void 0===e?void 0:e.item_change.emit()}));this._check_data_sources_on_renderers()||c.logger.error(\"Non matching data sources on legend item renderers\");this._check_field_label_on_data_source()||c.logger.error(`Bad column name on label: ${this.label}`)}get_field_from_label_prop(){const{label:e}=this;return(0,u.isField)(e)?e.field:null}get_labels_list_from_label_prop(){if(!this.visible)return[];if((0,u.isValue)(this.label)){const{value:e}=this.label;return null!=e?[e]:[]}const e=this.get_field_from_label_prop();if(null!=e){let r;if(!this.renderers[0]||null==this.renderers[0].data_source)return[\"No source found\"];if(r=this.renderers[0].data_source,r instanceof _.ColumnarDataSource){const l=r.get_column(e);return null!=l?(0,f.uniq)(Array.from(l)):[\"Invalid field\"]}}return[]}}l.LegendItem=h,s=h,h.__name__=\"LegendItem\",s.define((({Boolean:e,Int:r,Array:l,Ref:n,Nullable:t})=>({label:[d.NullStringSpec,null],renderers:[l(n(a.GlyphRenderer)),[]],index:[t(r),null],visible:[e,!0]})))},\n", - " function _(i,n,e,t,u){t();const c=i(8);e.isValue=function(i){return(0,c.isPlainObject)(i)&&\"value\"in i},e.isField=function(i){return(0,c.isPlainObject)(i)&&\"field\"in i},e.isExpr=function(i){return(0,c.isPlainObject)(i)&&\"expr\"in i}},\n", - " function _(t,n,e,s,i){s();const o=t(1);var a;const l=t(40),c=(0,o.__importStar)(t(48)),r=t(20);class _ extends l.AnnotationView{connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render()))}_render(){const{xs:t,ys:n}=this.model;if(t.length!=n.length)return;const e=t.length;if(e<3)return;const{frame:s}=this.plot_view,{ctx:i}=this.layer,o=this.coordinates.x_scale,a=this.coordinates.y_scale,{screen:l}=this.model;function c(t,n,e,s){return l?t:\"data\"==n?e.v_compute(t):s.v_compute(t)}const r=c(t,this.model.xs_units,o,s.bbox.xview),_=c(n,this.model.ys_units,a,s.bbox.yview);i.beginPath();for(let t=0;t({xs:[n(t),[]],xs_units:[r.SpatialUnits,\"data\"],ys:[n(t),[]],ys_units:[r.SpatialUnits,\"data\"]}))),a.internal((({Boolean:t})=>({screen:[t,!1]}))),a.override({fill_color:\"#fff9ba\",fill_alpha:.4,line_color:\"#cccccc\",line_alpha:.3})},\n", - " function _(e,t,n,o,i){o();const s=e(1);var l;const r=e(40),c=(0,s.__importStar)(e(48));class a extends r.AnnotationView{connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render()))}_render(){const{gradient:e,y_intercept:t}=this.model;if(null==e||null==t)return;const{frame:n}=this.plot_view,o=this.coordinates.x_scale,i=this.coordinates.y_scale;let s,l,r,c;if(0==e)s=i.compute(t),l=s,r=n.bbox.left,c=r+n.bbox.width;else{s=n.bbox.top,l=s+n.bbox.height;const a=(i.invert(s)-t)/e,_=(i.invert(l)-t)/e;r=o.compute(a),c=o.compute(_)}const{ctx:a}=this.layer;a.save(),a.beginPath(),this.visuals.line.set_value(a),a.moveTo(r,s),a.lineTo(c,l),a.stroke(),a.restore()}}n.SlopeView=a,a.__name__=\"SlopeView\";class _ extends r.Annotation{constructor(e){super(e)}}n.Slope=_,l=_,_.__name__=\"Slope\",l.prototype.default_view=a,l.mixins(c.Line),l.define((({Number:e,Nullable:t})=>({gradient:[t(e),null],y_intercept:[t(e),null]}))),l.override({line_color:\"black\"})},\n", - " function _(e,t,i,o,n){o();const s=e(1);var l;const a=e(40),r=(0,s.__importStar)(e(48)),c=e(20);class d extends a.AnnotationView{connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.plot_view.request_paint(this)))}_render(){const{location:e}=this.model;if(null==e)return;const{frame:t}=this.plot_view,i=this.coordinates.x_scale,o=this.coordinates.y_scale,n=(t,i)=>\"data\"==this.model.location_units?t.compute(e):this.model.for_hover?e:i.compute(e);let s,l,a,r;\"width\"==this.model.dimension?(a=n(o,t.bbox.yview),l=t.bbox.left,r=t.bbox.width,s=this.model.line_width):(a=t.bbox.top,l=n(i,t.bbox.xview),r=this.model.line_width,s=t.bbox.height);const{ctx:c}=this.layer;c.save(),c.beginPath(),this.visuals.line.set_value(c),c.moveTo(l,a),\"width\"==this.model.dimension?c.lineTo(l+r,a):c.lineTo(l,a+s),c.stroke(),c.restore()}}i.SpanView=d,d.__name__=\"SpanView\";class _ extends a.Annotation{constructor(e){super(e)}}i.Span=_,l=_,_.__name__=\"Span\",l.prototype.default_view=d,l.mixins(r.Line),l.define((({Number:e,Nullable:t})=>({render_mode:[c.RenderMode,\"canvas\"],location:[t(e),null],location_units:[c.SpatialUnits,\"data\"],dimension:[c.Dimension,\"width\"]}))),l.internal((({Boolean:e})=>({for_hover:[e,!1]}))),l.override({line_color:\"black\"})},\n", - " function _(i,e,t,o,l){var s;o();const a=i(40),_=i(221),n=i(113),r=i(43),h=i(123),b=i(65);class v extends a.AnnotationView{constructor(){super(...arguments),this._invalidate_toolbar=!0,this._previous_bbox=new b.BBox}update_layout(){this.layout=new h.SideLayout(this.panel,(()=>this.get_size()),!0)}initialize(){super.initialize(),this.el=(0,r.div)(),this.plot_view.canvas_view.add_event(this.el)}async lazy_initialize(){await super.lazy_initialize(),this._toolbar_view=await(0,n.build_view)(this.model.toolbar,{parent:this}),this.plot_view.visibility_callbacks.push((i=>this._toolbar_view.set_visibility(i)))}remove(){this._toolbar_view.remove(),(0,r.remove)(this.el),super.remove()}render(){this.model.visible||(0,r.undisplay)(this.el),super.render()}_render(){const{bbox:i}=this.layout;this._previous_bbox.equals(i)||((0,r.position)(this.el,i),this._previous_bbox=i,this._invalidate_toolbar=!0),this._invalidate_toolbar&&(this.el.style.position=\"absolute\",this.el.style.overflow=\"hidden\",(0,r.empty)(this.el),this.el.appendChild(this._toolbar_view.el),this._toolbar_view.layout.bbox=i,this._toolbar_view.render(),this._invalidate_toolbar=!1),(0,r.display)(this.el)}_get_size(){const{tools:i,logo:e}=this.model.toolbar;return{width:30*i.length+(null!=e?25:0)+15,height:30}}}t.ToolbarPanelView=v,v.__name__=\"ToolbarPanelView\";class d extends a.Annotation{constructor(i){super(i)}}t.ToolbarPanel=d,s=d,d.__name__=\"ToolbarPanel\",s.prototype.default_view=v,s.define((({Ref:i})=>({toolbar:[i(_.Toolbar)]})))},\n", - " function _(t,e,s,i,o){var c;i();const n=t(8),a=t(9),l=t(13),r=t(222),_=t(223),u=t(232),p=t(233);function v(t){switch(t){case\"tap\":return\"active_tap\";case\"pan\":return\"active_drag\";case\"pinch\":case\"scroll\":return\"active_scroll\";case\"multi\":return\"active_multi\"}return null}function h(t){return\"tap\"==t||\"pan\"==t}s.Drag=r.Tool,s.Inspection=r.Tool,s.Scroll=r.Tool,s.Tap=r.Tool;class f extends p.ToolbarBase{constructor(t){super(t)}connect_signals(){super.connect_signals();const{tools:t,active_drag:e,active_inspect:s,active_scroll:i,active_tap:o,active_multi:c}=this.properties;this.on_change([t,e,s,i,o,c],(()=>this._init_tools()))}_init_tools(){if(super._init_tools(),\"auto\"==this.active_inspect);else if(this.active_inspect instanceof u.InspectTool){let t=!1;for(const e of this.inspectors)e!=this.active_inspect?e.active=!1:t=!0;t||(this.active_inspect=null)}else if((0,n.isArray)(this.active_inspect)){const t=(0,a.intersection)(this.active_inspect,this.inspectors);t.length!=this.active_inspect.length&&(this.active_inspect=t);for(const t of this.inspectors)(0,a.includes)(this.active_inspect,t)||(t.active=!1)}else if(null==this.active_inspect)for(const t of this.inspectors)t.active=!1;const t=t=>{t.active?this._active_change(t):t.active=!0};for(const t of(0,l.values)(this.gestures)){t.tools=(0,a.sort_by)(t.tools,(t=>t.default_order));for(const e of t.tools)this.connect(e.properties.active.change,(()=>this._active_change(e)))}for(const[e,s]of(0,l.entries)(this.gestures)){const i=v(e);if(i){const o=this[i];\"auto\"==o?0!=s.tools.length&&h(e)&&t(s.tools[0]):null!=o&&((0,a.includes)(this.tools,o)?t(o):this[i]=null)}}}}s.Toolbar=f,c=f,f.__name__=\"Toolbar\",c.prototype.default_view=p.ToolbarBaseView,c.define((({Or:t,Ref:e,Auto:i,Null:o})=>({active_drag:[t(e(s.Drag),i,o),\"auto\"],active_inspect:[t(e(s.Inspection),i,o),\"auto\"],active_scroll:[t(e(s.Scroll),i,o),\"auto\"],active_tap:[t(e(s.Tap),i,o),\"auto\"],active_multi:[t(e(_.GestureTool),i,o),\"auto\"]})))},\n", - " function _(t,e,n,o,s){var i;o();const a=t(42),r=t(9),l=t(53);class c extends a.View{get plot_view(){return this.parent}get plot_model(){return this.parent.model}connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,(()=>{this.model.active?this.activate():this.deactivate()}))}activate(){}deactivate(){}}n.ToolView=c,c.__name__=\"ToolView\";class _ extends l.Model{constructor(t){super(t)}get synthetic_renderers(){return[]}_get_dim_limits([t,e],[n,o],s,i){const a=s.bbox.h_range;let l;\"width\"==i||\"both\"==i?(l=[(0,r.min)([t,n]),(0,r.max)([t,n])],l=[(0,r.max)([l[0],a.start]),(0,r.min)([l[1],a.end])]):l=[a.start,a.end];const c=s.bbox.v_range;let _;return\"height\"==i||\"both\"==i?(_=[(0,r.min)([e,o]),(0,r.max)([e,o])],_=[(0,r.max)([_[0],c.start]),(0,r.min)([_[1],c.end])]):_=[c.start,c.end],[l,_]}static register_alias(t,e){this.prototype._known_aliases.set(t,e)}static from_string(t){const e=this.prototype._known_aliases.get(t);if(null!=e)return e();{const e=[...this.prototype._known_aliases.keys()];throw new Error(`unexpected tool name '${t}', possible tools are ${e.join(\", \")}`)}}}n.Tool=_,i=_,_.__name__=\"Tool\",i.prototype._known_aliases=new Map,i.define((({String:t,Nullable:e})=>({description:[e(t),null]}))),i.internal((({Boolean:t})=>({active:[t,!1]})))},\n", - " function _(e,o,t,s,n){s();const u=e(224),_=e(231);class l extends u.ButtonToolView{}t.GestureToolView=l,l.__name__=\"GestureToolView\";class i extends u.ButtonTool{constructor(e){super(e),this.button_view=_.OnOffButtonView}}t.GestureTool=i,i.__name__=\"GestureTool\"},\n", - " function _(t,e,o,s,i){s();const n=t(1);var l;const r=(0,n.__importDefault)(t(225)),a=t(226),u=t(222),h=t(43),_=t(34),d=t(8),c=t(9),m=(0,n.__importStar)(t(227)),p=m,v=(0,n.__importDefault)(t(228)),f=(0,n.__importDefault)(t(229)),g=t(230);class b extends a.DOMView{initialize(){super.initialize();const t=this.model.menu;if(null!=t){const e=this.parent.model.toolbar_location,o=\"left\"==e||\"above\"==e,s=this.parent.model.horizontal?\"vertical\":\"horizontal\";this._menu=new g.ContextMenu(o?(0,c.reversed)(t):t,{orientation:s,prevent_hide:t=>t.target==this.el})}this._hammer=new r.default(this.el,{touchAction:\"auto\",inputClass:r.default.TouchMouseInput}),this.connect(this.model.change,(()=>this.render())),this._hammer.on(\"tap\",(t=>{var e;(null===(e=this._menu)||void 0===e?void 0:e.is_open)?this._menu.hide():t.target==this.el&&this._clicked()})),this._hammer.on(\"press\",(()=>this._pressed())),this.el.addEventListener(\"keydown\",(t=>{t.keyCode==h.Keys.Enter&&this._clicked()}))}remove(){var t;this._hammer.destroy(),null===(t=this._menu)||void 0===t||t.remove(),super.remove()}styles(){return[...super.styles(),m.default,v.default,f.default]}css_classes(){return super.css_classes().concat(p.toolbar_button)}render(){(0,h.empty)(this.el);const t=this.model.computed_icon;(0,d.isString)(t)&&((0,_.startsWith)(t,\"data:image\")?this.el.style.backgroundImage=`url(\"${t}\")`:this.el.classList.add(t)),this.el.title=this.model.tooltip,this.el.tabIndex=0,null!=this._menu&&this.root.el.appendChild(this._menu.el)}_pressed(){var t;const e=(()=>{switch(this.parent.model.toolbar_location){case\"right\":return{left_of:this.el};case\"left\":return{right_of:this.el};case\"above\":return{below:this.el};case\"below\":return{above:this.el}}})();null===(t=this._menu)||void 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i,n,s,o,a=t.lastInterval||e,h=e.timeStamp-a.timeStamp;if(8!=e.eventType&&(h>25||a.velocity===r)){var c=e.deltaX-a.deltaX,l=e.deltaY-a.deltaY,p=U(h,c,l);n=p.x,s=p.y,i=u(p.x)>u(p.y)?p.x:p.y,o=V(c,l),t.lastInterval=e}else i=a.velocity,n=a.velocityX,s=a.velocityY,o=a.direction;e.velocity=i,e.velocityX=n,e.velocityY=s,e.direction=o}(i,e);var f,v;var d=t.element;_(e.srcEvent.target,d)&&(d=e.srcEvent.target);e.target=d}(t,i),t.emit(\"hammer.input\",i),t.recognize(i),t.session.prevInput=i}function H(t){for(var e=[],i=0;i=u(e)?t<0?2:4:e<0?8:16}function j(t,e,i){i||(i=F);var n=e[i[0]]-t[i[0]],r=e[i[1]]-t[i[1]];return Math.sqrt(n*n+r*r)}function G(t,e,i){i||(i=F);var n=e[i[0]]-t[i[0]],r=e[i[1]]-t[i[1]];return 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pointercancel\";function it(){this.evEl=tt,this.evWin=et,q.apply(this,arguments),this.store=this.manager.session.pointerEvents=[]}t.MSPointerEvent&&!t.PointerEvent&&(tt=\"MSPointerDown\",et=\"MSPointerMove MSPointerUp MSPointerCancel\"),g(it,q,{handler:function(t){var e=this.store,i=!1,n=t.type.toLowerCase().replace(\"ms\",\"\"),r=K[n],s=Q[t.pointerType]||t.pointerType,o=s==N,a=b(e,t.pointerId,\"pointerId\");1&r&&(0===t.button||o)?a<0&&(e.push(t),a=e.length-1):12&r&&(i=!0),a<0||(e[a]=t,this.callback(this.manager,r,{pointers:e,changedPointers:[t],pointerType:s,srcEvent:t}),i&&e.splice(a,1))}});var nt={touchstart:1,touchmove:2,touchend:4,touchcancel:8},rt=\"touchstart\",st=\"touchstart touchmove touchend touchcancel\";function ot(){this.evTarget=rt,this.evWin=st,this.started=!1,q.apply(this,arguments)}function at(t,e){var i=P(t.touches),n=P(t.changedTouches);return 12&e&&(i=D(i.concat(n),\"identifier\",!0)),[i,n]}g(ot,q,{handler:function(t){var e=nt[t.type];if(1===e&&(this.started=!0),this.started){var i=at.call(this,t,e);12&e&&i[0].length-i[1].length==0&&(this.started=!1),this.callback(this.manager,e,{pointers:i[0],changedPointers:i[1],pointerType:N,srcEvent:t})}}});var ht={touchstart:1,touchmove:2,touchend:4,touchcancel:8},ut=\"touchstart touchmove touchend touchcancel\";function ct(){this.evTarget=ut,this.targetIds={},q.apply(this,arguments)}function lt(t,e){var i=P(t.touches),n=this.targetIds;if(3&e&&1===i.length)return n[i[0].identifier]=!0,[i,i];var r,s,o=P(t.changedTouches),a=[],h=this.target;if(s=i.filter((function(t){return _(t.target,h)})),1===e)for(r=0;r-1&&n.splice(t,1)}),2500)}}function dt(t){for(var e=t.srcEvent.clientX,i=t.srcEvent.clientY,n=0;n-1&&this.requireFail.splice(e,1),this},hasRequireFailures:function(){return this.requireFail.length>0},canRecognizeWith:function(t){return!!this.simultaneous[t.id]},emit:function(t){var e=this,i=this.state;function n(i){e.manager.emit(i,t)}i<8&&n(e.options.event+Dt(i)),n(e.options.event),t.additionalEvent&&n(t.additionalEvent),i>=8&&n(e.options.event+Dt(i))},tryEmit:function(t){if(this.canEmit())return this.emit(t);this.state=bt},canEmit:function(){for(var t=0;te.threshold&&r&e.direction},attrTest:function(t){return Ot.prototype.attrTest.call(this,t)&&(2&this.state||!(2&this.state)&&this.directionTest(t))},emit:function(t){this.pX=t.deltaX,this.pY=t.deltaY;var e=xt(t.direction);e&&(t.additionalEvent=this.options.event+e),this._super.emit.call(this,t)}}),g(Mt,Ot,{defaults:{event:\"pinch\",threshold:0,pointers:2},getTouchAction:function(){return[It]},attrTest:function(t){return this._super.attrTest.call(this,t)&&(Math.abs(t.scale-1)>this.options.threshold||2&this.state)},emit:function(t){if(1!==t.scale){var e=t.scale<1?\"in\":\"out\";t.additionalEvent=this.options.event+e}this._super.emit.call(this,t)}}),g(zt,Pt,{defaults:{event:\"press\",pointers:1,time:251,threshold:9},getTouchAction:function(){return[yt]},process:function(t){var e=this.options,i=t.pointers.length===e.pointers,n=t.distancee.time;if(this._input=t,!n||!i||12&t.eventType&&!r)this.reset();else if(1&t.eventType)this.reset(),this._timer=l((function(){this.state=8,this.tryEmit()}),e.time,this);else if(4&t.eventType)return 8;return bt},reset:function(){clearTimeout(this._timer)},emit:function(t){8===this.state&&(t&&4&t.eventType?this.manager.emit(this.options.event+\"up\",t):(this._input.timeStamp=c(),this.manager.emit(this.options.event,this._input)))}}),g(Nt,Ot,{defaults:{event:\"rotate\",threshold:0,pointers:2},getTouchAction:function(){return[It]},attrTest:function(t){return this._super.attrTest.call(this,t)&&(Math.abs(t.rotation)>this.options.threshold||2&this.state)}}),g(Xt,Ot,{defaults:{event:\"swipe\",threshold:10,velocity:.3,direction:30,pointers:1},getTouchAction:function(){return Rt.prototype.getTouchAction.call(this)},attrTest:function(t){var e,i=this.options.direction;return 30&i?e=t.overallVelocity:6&i?e=t.overallVelocityX:i&Y&&(e=t.overallVelocityY),this._super.attrTest.call(this,t)&&i&t.offsetDirection&&t.distance>this.options.threshold&&t.maxPointers==this.options.pointers&&u(e)>this.options.velocity&&4&t.eventType},emit:function(t){var e=xt(t.offsetDirection);e&&this.manager.emit(this.options.event+e,t),this.manager.emit(this.options.event,t)}}),g(Yt,Pt,{defaults:{event:\"tap\",pointers:1,taps:1,interval:300,time:250,threshold:9,posThreshold:10},getTouchAction:function(){return[Et]},process:function(t){var e=this.options,i=t.pointers.length===e.pointers,n=t.distance .bk-divider{cursor:default;overflow:hidden;background-color:#e5e5e5;}.bk-root .bk-context-menu.bk-horizontal > .bk-divider{width:1px;margin:5px 0;}.bk-root .bk-context-menu.bk-vertical > .bk-divider{height:1px;margin:0 5px;}.bk-root .bk-context-menu > :not(.bk-divider){border:1px solid transparent;}.bk-root .bk-context-menu > :not(.bk-divider).bk-active{border-color:#26aae1;}.bk-root .bk-context-menu > :not(.bk-divider):hover{background-color:#f9f9f9;}.bk-root .bk-context-menu > :not(.bk-divider):focus,.bk-root .bk-context-menu > :not(.bk-divider):focus-visible{outline:1px dotted #26aae1;outline-offset:-1px;}.bk-root .bk-context-menu > :not(.bk-divider)::-moz-focus-inner{border:0;}.bk-root .bk-context-menu.bk-horizontal > :not(.bk-divider):first-child{border-top-left-radius:4px;border-bottom-left-radius:4px;}.bk-root .bk-context-menu.bk-horizontal > :not(.bk-divider):last-child{border-top-right-radius:4px;border-bottom-right-radius:4px;}.bk-root .bk-context-menu.bk-vertical > :not(.bk-divider):first-child{border-top-left-radius:4px;border-top-right-radius:4px;}.bk-root .bk-context-menu.bk-vertical > :not(.bk-divider):last-child{border-bottom-left-radius:4px;border-bottom-right-radius:4px;}.bk-root .bk-menu{position:absolute;left:0;width:100%;z-index:100;cursor:pointer;font-size:12px;background-color:#fff;border:1px solid #ccc;border-radius:4px;box-shadow:0 6px 12px rgba(0, 0, 0, 0.175);}.bk-root .bk-menu.bk-above{bottom:100%;}.bk-root .bk-menu.bk-below{top:100%;}.bk-root .bk-menu > .bk-divider{height:1px;margin:7.5px 0;overflow:hidden;background-color:#e5e5e5;}.bk-root .bk-menu > :not(.bk-divider){padding:6px 12px;}.bk-root .bk-menu > :not(.bk-divider):hover,.bk-root .bk-menu > :not(.bk-divider).bk-active{background-color:#e6e6e6;}.bk-root .bk-caret{display:inline-block;vertical-align:middle;width:0;height:0;margin:0 5px;}.bk-root .bk-caret.bk-down{border-top:4px solid;}.bk-root .bk-caret.bk-up{border-bottom:4px solid;}.bk-root .bk-caret.bk-down,.bk-root .bk-caret.bk-up{border-right:4px solid transparent;border-left:4px solid transparent;}.bk-root .bk-caret.bk-left{border-right:4px solid;}.bk-root .bk-caret.bk-right{border-left:4px solid;}.bk-root .bk-caret.bk-left,.bk-root .bk-caret.bk-right{border-top:4px solid transparent;border-bottom:4px solid transparent;}\"},\n", - " function _(t,e,i,n,o){n();const s=t(1),l=t(43),h=t(9),r=(0,s.__importStar)(t(229));class d{constructor(t,e={}){var i,n;this.items=t,this.el=(0,l.div)(),this._open=!1,this._item_click=t=>{var e;null===(e=t.handler)||void 0===e||e.call(t),this.hide()},this._on_mousedown=t=>{var e;const{target:i}=t;i instanceof Node&&this.el.contains(i)||(null===(e=this.prevent_hide)||void 0===e?void 0:e.call(this,t))||this.hide()},this._on_keydown=t=>{t.keyCode==l.Keys.Esc&&this.hide()},this._on_blur=()=>{this.hide()},this.orientation=null!==(i=e.orientation)&&void 0!==i?i:\"vertical\",this.reversed=null!==(n=e.reversed)&&void 0!==n&&n,this.prevent_hide=e.prevent_hide,(0,l.undisplay)(this.el)}get is_open(){return this._open}get can_open(){return 0!=this.items.length}remove(){(0,l.remove)(this.el),this._unlisten()}_listen(){document.addEventListener(\"mousedown\",this._on_mousedown),document.addEventListener(\"keydown\",this._on_keydown),window.addEventListener(\"blur\",this._on_blur)}_unlisten(){document.removeEventListener(\"mousedown\",this._on_mousedown),document.removeEventListener(\"keydown\",this._on_keydown),window.removeEventListener(\"blur\",this._on_blur)}_position(t){const e=this.el.parentElement;if(null!=e){const i=(()=>{if(\"left_of\"in t){const{left:e,top:i}=t.left_of.getBoundingClientRect();return{right:e,top:i}}if(\"right_of\"in t){const{top:e,right:i}=t.right_of.getBoundingClientRect();return{left:i,top:e}}if(\"below\"in t){const{left:e,bottom:i}=t.below.getBoundingClientRect();return{left:e,top:i}}if(\"above\"in t){const{left:e,top:i}=t.above.getBoundingClientRect();return{left:e,bottom:i}}return t})(),n=e.getBoundingClientRect();this.el.style.left=null!=i.left?i.left-n.left+\"px\":\"\",this.el.style.top=null!=i.top?i.top-n.top+\"px\":\"\",this.el.style.right=null!=i.right?n.right-i.right+\"px\":\"\",this.el.style.bottom=null!=i.bottom?n.bottom-i.bottom+\"px\":\"\"}}render(){var t;(0,l.empty)(this.el,!0),(0,l.classes)(this.el).add(\"bk-context-menu\",`bk-${this.orientation}`);const e=this.reversed?(0,h.reversed)(this.items):this.items;for(const i of e){let e;if(null==i)e=(0,l.div)({class:r.divider});else{if(null!=i.if&&!i.if())continue;if(null!=i.content)e=i.content;else{const n=null!=i.icon?(0,l.div)({class:[\"bk-menu-icon\",i.icon]}):null,o=[(null===(t=i.active)||void 0===t?void 0:t.call(i))?\"bk-active\":null,i.class];e=(0,l.div)({class:o,title:i.tooltip,tabIndex:0},n,i.label,i.content),e.addEventListener(\"click\",(()=>{this._item_click(i)})),e.addEventListener(\"keydown\",(t=>{t.keyCode==l.Keys.Enter&&this._item_click(i)}))}}this.el.appendChild(e)}}show(t){if(0!=this.items.length&&!this._open){if(this.render(),0==this.el.children.length)return;this._position(null!=t?t:{left:0,top:0}),(0,l.display)(this.el),this._listen(),this._open=!0}}hide(){this._open&&(this._open=!1,this._unlisten(),(0,l.undisplay)(this.el))}toggle(t){this._open?this.hide():this.show(t)}}i.ContextMenu=d,d.__name__=\"ContextMenu\"},\n", - " function _(t,e,i,n,o){n();const s=t(1),c=t(224),l=(0,s.__importStar)(t(227)),a=t(43);class _ extends c.ButtonToolButtonView{render(){super.render(),(0,a.classes)(this.el).toggle(l.active,this.model.active)}_clicked(){const{active:t}=this.model;this.model.active=!t}}i.OnOffButtonView=_,_.__name__=\"OnOffButtonView\"},\n", - " function _(e,o,t,n,s){var c;n();const l=e(224),_=e(231);class i extends l.ButtonToolView{}t.InspectToolView=i,i.__name__=\"InspectToolView\";class a extends l.ButtonTool{constructor(e){super(e),this.event_type=\"move\"}}t.InspectTool=a,c=a,a.__name__=\"InspectTool\",c.prototype.button_view=_.OnOffButtonView,c.define((({Boolean:e})=>({toggleable:[e,!0]}))),c.override({active:!0})},\n", - " function _(t,o,e,l,i){l();const s=t(1);var n,a;const r=t(19),c=t(43),h=t(113),_=t(226),u=t(20),v=t(9),d=t(234),p=t(13),b=t(8),g=t(235),f=t(65),m=t(53),w=t(222),y=t(223),T=t(238),z=t(239),x=t(232),B=t(230),C=(0,s.__importStar)(t(227)),k=C,L=(0,s.__importStar)(t(240)),M=L;class S extends m.Model{constructor(t){super(t)}get visible(){var t;return!this.autohide||null!==(t=this._visible)&&void 0!==t&&t}}e.ToolbarViewModel=S,n=S,S.__name__=\"ToolbarViewModel\",n.define((({Boolean:t})=>({autohide:[t,!1]}))),n.internal((({Boolean:t,Nullable:o})=>({_visible:[o(t),null]})));class $ extends _.DOMView{constructor(){super(...arguments),this.layout={bbox:new f.BBox}}initialize(){super.initialize(),this._tool_button_views=new Map,this._toolbar_view_model=new S({autohide:this.model.autohide});const{toolbar_location:t}=this.model,o=\"left\"==t||\"above\"==t,e=this.model.horizontal?\"vertical\":\"horizontal\";this._overflow_menu=new B.ContextMenu([],{orientation:e,reversed:o})}async lazy_initialize(){await super.lazy_initialize(),await this._build_tool_button_views()}connect_signals(){super.connect_signals(),this.connect(this.model.properties.tools.change,(async()=>{await this._build_tool_button_views(),this.render()})),this.connect(this.model.properties.autohide.change,(()=>{this._toolbar_view_model.autohide=this.model.autohide,this._on_visible_change()})),this.connect(this._toolbar_view_model.properties._visible.change,(()=>this._on_visible_change()))}styles(){return[...super.styles(),C.default,L.default]}remove(){(0,h.remove_views)(this._tool_button_views),super.remove()}async _build_tool_button_views(){const t=null!=this.model._proxied_tools?this.model._proxied_tools:this.model.tools;await(0,h.build_views)(this._tool_button_views,t,{parent:this},(t=>t.button_view))}set_visibility(t){t!=this._toolbar_view_model._visible&&(this._toolbar_view_model._visible=t)}_on_visible_change(){const{visible:t}=this._toolbar_view_model;(0,c.classes)(this.el).toggle(k.toolbar_hidden,!t)}render(){(0,c.empty)(this.el),this.el.classList.add(k.toolbar),this.el.classList.add(k[this.model.toolbar_location]),this._toolbar_view_model.autohide=this.model.autohide,this._on_visible_change();const{horizontal:t}=this.model;let o=0;if(null!=this.model.logo){const e=\"grey\"===this.model.logo?M.grey:null,l=(0,c.a)({href:\"https://bokeh.org/\",target:\"_blank\",class:[M.logo,M.logo_small,e]});this.el.appendChild(l);const{width:i,height:s}=l.getBoundingClientRect();o+=t?i:s}for(const[,t]of this._tool_button_views)t.render();const e=[],l=t=>this._tool_button_views.get(t).el,{gestures:i}=this.model;for(const t of(0,p.values)(i))e.push(t.tools.map(l));e.push(this.model.actions.map(l)),e.push(this.model.inspectors.filter((t=>t.toggleable)).map(l));const s=e.filter((t=>0!=t.length)),n=()=>(0,c.div)({class:k.divider}),{bbox:a}=this.layout;let r=!1;this.root.el.appendChild(this._overflow_menu.el);const h=(0,c.div)({class:k.tool_overflow,tabIndex:0},t?\"\\u22ee\":\"\\u22ef\"),_=()=>{const t=(()=>{switch(this.model.toolbar_location){case\"right\":return{left_of:h};case\"left\":return{right_of:h};case\"above\":return{below:h};case\"below\":return{above:h}}})();this._overflow_menu.toggle(t)};h.addEventListener(\"click\",(()=>{_()})),h.addEventListener(\"keydown\",(t=>{t.keyCode==c.Keys.Enter&&_()}));for(const e of(0,d.join)(s,n))if(r)this._overflow_menu.items.push({content:e,class:t?k.right:k.above});else{this.el.appendChild(e);const{width:l,height:i}=e.getBoundingClientRect();if(o+=t?l:i,r=t?o>a.width-15:o>a.height-15,r){this.el.removeChild(e),this.el.appendChild(h);const{items:t}=this._overflow_menu;t.splice(0,t.length),t.push({content:e})}}}update_layout(){}update_position(){}after_layout(){this._has_finished=!0}export(t,o=!0){const e=\"png\"==t?\"canvas\":\"svg\",l=new g.CanvasLayer(e,o);return l.resize(0,0),l}}function V(){return{pan:{tools:[],active:null},scroll:{tools:[],active:null},pinch:{tools:[],active:null},tap:{tools:[],active:null},doubletap:{tools:[],active:null},press:{tools:[],active:null},pressup:{tools:[],active:null},rotate:{tools:[],active:null},move:{tools:[],active:null},multi:{tools:[],active:null}}}e.ToolbarBaseView=$,$.__name__=\"ToolbarBaseView\";class A extends m.Model{constructor(t){super(t)}initialize(){super.initialize(),this._init_tools()}_init_tools(){const t=function(t,o){if(t.length!=o.length)return!0;const e=new Set(o.map((t=>t.id)));return(0,v.some)(t,(t=>!e.has(t.id)))},o=this.tools.filter((t=>t instanceof x.InspectTool));t(this.inspectors,o)&&(this.inspectors=o);const e=this.tools.filter((t=>t instanceof z.HelpTool));t(this.help,e)&&(this.help=e);const l=this.tools.filter((t=>t instanceof T.ActionTool));t(this.actions,l)&&(this.actions=l);const i=(t,o)=>{t in this.gestures||r.logger.warn(`Toolbar: unknown event type '${t}' for tool: ${o}`)},s={pan:{tools:[],active:null},scroll:{tools:[],active:null},pinch:{tools:[],active:null},tap:{tools:[],active:null},doubletap:{tools:[],active:null},press:{tools:[],active:null},pressup:{tools:[],active:null},rotate:{tools:[],active:null},move:{tools:[],active:null},multi:{tools:[],active:null}};for(const t of this.tools)if(t instanceof y.GestureTool&&t.event_type)if((0,b.isString)(t.event_type))s[t.event_type].tools.push(t),i(t.event_type,t);else{s.multi.tools.push(t);for(const o of t.event_type)i(o,t)}for(const o of Object.keys(s)){const e=this.gestures[o];t(e.tools,s[o].tools)&&(e.tools=s[o].tools),e.active&&(0,v.every)(e.tools,(t=>t.id!=e.active.id))&&(e.active=null)}}get horizontal(){return\"above\"===this.toolbar_location||\"below\"===this.toolbar_location}get vertical(){return\"left\"===this.toolbar_location||\"right\"===this.toolbar_location}_active_change(t){const{event_type:o}=t;if(null==o)return;const e=(0,b.isString)(o)?[o]:o;for(const o of e)if(t.active){const e=this.gestures[o].active;null!=e&&t!=e&&(r.logger.debug(`Toolbar: deactivating tool: ${e} for event type '${o}'`),e.active=!1),this.gestures[o].active=t,r.logger.debug(`Toolbar: activating tool: ${t} for event type '${o}'`)}else this.gestures[o].active=null}}e.ToolbarBase=A,a=A,A.__name__=\"ToolbarBase\",a.prototype.default_view=$,a.define((({Boolean:t,Array:o,Ref:e,Nullable:l})=>({tools:[o(e(w.Tool)),[]],logo:[l(u.Logo),\"normal\"],autohide:[t,!1]}))),a.internal((({Array:t,Struct:o,Ref:e,Nullable:l})=>{const i=o({tools:t(e(y.GestureTool)),active:l(e(w.Tool))});return{gestures:[o({pan:i,scroll:i,pinch:i,tap:i,doubletap:i,press:i,pressup:i,rotate:i,move:i,multi:i}),V],actions:[t(e(T.ActionTool)),[]],inspectors:[t(e(x.InspectTool)),[]],help:[t(e(z.HelpTool)),[]],toolbar_location:[u.Location,\"right\"]}}))},\n", - " function _(n,o,e,t,f){t();const r=n(9);function*i(n,o){const e=n.length;if(o>e)return;const t=(0,r.range)(o);for(yield t.map((o=>n[o]));;){let f;for(const n of(0,r.reversed)((0,r.range)(o)))if(t[n]!=n+e-o){f=n;break}if(null==f)return;t[f]+=1;for(const n of(0,r.range)(f+1,o))t[n]=t[n-1]+1;yield t.map((o=>n[o]))}}e.enumerate=function*(n){let o=0;for(const e of n)yield[e,o++]},e.join=function*(n,o){let 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.bk-logo-notebook{display:inline-block;vertical-align:middle;margin-right:5px;}\"},\n", - " function _(e,t,s,i,l){i();const o=e(1);var n;const a=e(40),h=e(20),r=e(43),c=(0,o.__importStar)(e(242)),d=c;class p extends a.AnnotationView{initialize(){super.initialize(),this.el=(0,r.div)({class:d.tooltip}),(0,r.undisplay)(this.el),this.plot_view.canvas_view.add_overlay(this.el)}remove(){(0,r.remove)(this.el),super.remove()}connect_signals(){super.connect_signals(),this.connect(this.model.properties.content.change,(()=>this.render())),this.connect(this.model.properties.position.change,(()=>this._reposition()))}styles(){return[...super.styles(),c.default]}render(){this.model.visible||(0,r.undisplay)(this.el),super.render()}_render(){const{content:e}=this.model;null!=e?((0,r.empty)(this.el),(0,r.classes)(this.el).toggle(\"bk-tooltip-custom\",this.model.custom),this.el.appendChild(e),this.model.show_arrow&&this.el.classList.add(d.tooltip_arrow)):(0,r.undisplay)(this.el)}_reposition(){const{position:e}=this.model;if(null==e)return void(0,r.undisplay)(this.el);const[t,s]=e,i=(()=>{const e=this.parent.layout.bbox.relative(),{attachment:i}=this.model;switch(i){case\"horizontal\":return t({attachment:[h.TooltipAttachment,\"horizontal\"],inner_only:[e,!0],show_arrow:[e,!0]}))),n.internal((({Boolean:e,Number:t,Tuple:s,Ref:i,Nullable:l})=>({position:[l(s(t,t)),null],content:[i(HTMLElement),()=>(0,r.div)()],custom:[e]}))),n.override({level:\"overlay\"})},\n", - " function _(o,t,r,e,l){e(),r.root=\"bk-root\",r.tooltip=\"bk-tooltip\",r.left=\"bk-left\",r.tooltip_arrow=\"bk-tooltip-arrow\",r.right=\"bk-right\",r.above=\"bk-above\",r.below=\"bk-below\",r.tooltip_row_label=\"bk-tooltip-row-label\",r.tooltip_row_value=\"bk-tooltip-row-value\",r.tooltip_color_block=\"bk-tooltip-color-block\",r.default='.bk-root{}.bk-root .bk-tooltip{font-weight:300;font-size:12px;position:absolute;padding:5px;border:1px solid #e5e5e5;color:#2f2f2f;background-color:white;pointer-events:none;opacity:0.95;z-index:100;}.bk-root .bk-tooltip > div:not(:first-child){margin-top:5px;border-top:#e5e5e5 1px dashed;}.bk-root .bk-tooltip.bk-left.bk-tooltip-arrow::before{position:absolute;margin:-7px 0 0 0;top:50%;width:0;height:0;border-style:solid;border-width:7px 0 7px 0;border-color:transparent;content:\" \";display:block;left:-10px;border-right-width:10px;border-right-color:#909599;}.bk-root .bk-tooltip.bk-left::before{left:-10px;border-right-width:10px;border-right-color:#909599;}.bk-root .bk-tooltip.bk-right.bk-tooltip-arrow::after{position:absolute;margin:-7px 0 0 0;top:50%;width:0;height:0;border-style:solid;border-width:7px 0 7px 0;border-color:transparent;content:\" \";display:block;right:-10px;border-left-width:10px;border-left-color:#909599;}.bk-root .bk-tooltip.bk-right::after{right:-10px;border-left-width:10px;border-left-color:#909599;}.bk-root .bk-tooltip.bk-above::before{position:absolute;margin:0 0 0 -7px;left:50%;width:0;height:0;border-style:solid;border-width:0 7px 0 7px;border-color:transparent;content:\" \";display:block;top:-10px;border-bottom-width:10px;border-bottom-color:#909599;}.bk-root .bk-tooltip.bk-below::after{position:absolute;margin:0 0 0 -7px;left:50%;width:0;height:0;border-style:solid;border-width:0 7px 0 7px;border-color:transparent;content:\" \";display:block;bottom:-10px;border-top-width:10px;border-top-color:#909599;}.bk-root .bk-tooltip-row-label{text-align:right;color:#26aae1;}.bk-root .bk-tooltip-row-value{color:default;}.bk-root .bk-tooltip-color-block{width:12px;height:12px;margin-left:5px;margin-right:5px;outline:#dddddd solid 1px;display:inline-block;}'},\n", - " function _(e,t,s,i,r){var a;i();const l=e(115),_=e(112),h=e(113),o=e(48);class n extends l.UpperLowerView{async lazy_initialize(){await super.lazy_initialize();const{lower_head:e,upper_head:t}=this.model;null!=e&&(this.lower_head=await(0,h.build_view)(e,{parent:this})),null!=t&&(this.upper_head=await(0,h.build_view)(t,{parent:this}))}set_data(e){var t,s;super.set_data(e),null===(t=this.lower_head)||void 0===t||t.set_data(e),null===(s=this.upper_head)||void 0===s||s.set_data(e)}paint(e){if(this.visuals.line.doit)for(let t=0,s=this._lower_sx.length;t({lower_head:[t(e(_.ArrowHead)),()=>new _.TeeHead({size:10})],upper_head:[t(e(_.ArrowHead)),()=>new _.TeeHead({size:10})]}))),a.override({level:\"underlay\"})},\n", - " function _(n,o,t,u,e){u(),e(\"CustomJS\",n(245).CustomJS),e(\"OpenURL\",n(247).OpenURL)},\n", - " function _(t,e,s,n,c){var a;n();const r=t(246),u=t(13),o=t(34);class i extends r.Callback{constructor(t){super(t)}get names(){return(0,u.keys)(this.args)}get values(){return(0,u.values)(this.args)}get func(){const t=(0,o.use_strict)(this.code);return new Function(...this.names,\"cb_obj\",\"cb_data\",t)}execute(t,e={}){return this.func.apply(t,this.values.concat(t,e))}}s.CustomJS=i,a=i,i.__name__=\"CustomJS\",a.define((({Unknown:t,String:e,Dict:s})=>({args:[s(t),{}],code:[e,\"\"]})))},\n", - " function _(c,a,l,n,s){n();const e=c(53);class o extends e.Model{constructor(c){super(c)}}l.Callback=o,o.__name__=\"Callback\"},\n", - " function _(e,t,n,o,i){var s;o();const c=e(246),r=e(152),a=e(8);class d extends c.Callback{constructor(e){super(e)}navigate(e){this.same_tab?window.location.href=e:window.open(e)}execute(e,{source:t}){const n=e=>{const n=(0,r.replace_placeholders)(this.url,t,e,void 0,void 0,encodeURI);if(!(0,a.isString)(n))throw new Error(\"HTML output is not supported in this context\");this.navigate(n)},{selected:o}=t;for(const e of o.indices)n(e);for(const e of o.line_indices)n(e)}}n.OpenURL=d,s=d,d.__name__=\"OpenURL\",s.define((({Boolean:e,String:t})=>({url:[t,\"http://\"],same_tab:[e,!1]})))},\n", - " function _(a,n,i,e,r){e(),r(\"Canvas\",a(249).Canvas),r(\"CartesianFrame\",a(126).CartesianFrame),r(\"CoordinateMapping\",a(54).CoordinateMapping)},\n", - " function _(e,t,i,s,a){var r,l=this&&this.__createBinding||(Object.create?function(e,t,i,s){void 0===s&&(s=i),Object.defineProperty(e,s,{enumerable:!0,get:function(){return t[i]}})}:function(e,t,i,s){void 0===s&&(s=i),e[s]=t[i]}),n=this&&this.__setModuleDefault||(Object.create?function(e,t){Object.defineProperty(e,\"default\",{enumerable:!0,value:t})}:function(e,t){e.default=t}),o=this&&this.__importStar||function(e){if(e&&e.__esModule)return e;var t={};if(null!=e)for(var i in e)\"default\"!==i&&Object.prototype.hasOwnProperty.call(e,i)&&l(t,e,i);return n(t,e),t};s();const h=e(14),c=e(226),u=e(19),_=e(43),d=e(20),p=e(13),b=e(250),v=e(65),g=e(138),w=e(235);const y=(()=>{let t;return async()=>void 0!==t?t:t=await async function(){const t=document.createElement(\"canvas\"),i=t.getContext(\"webgl\",{premultipliedAlpha:!0});if(null!=i){const s=await(0,g.load_module)(Promise.resolve().then((()=>o(e(410)))));if(null!=s){const e=s.get_regl(i);if(e.has_webgl)return{canvas:t,regl_wrapper:e};u.logger.trace(\"WebGL is supported, but not the required extensions\")}else u.logger.trace(\"WebGL is supported, but bokehjs(.min).js bundle is not available\")}else u.logger.trace(\"WebGL is not supported\");return null}()})(),m={position:\"absolute\",top:\"0\",left:\"0\",width:\"100%\",height:\"100%\"};class f extends c.DOMView{constructor(){super(...arguments),this.bbox=new v.BBox,this.webgl=null}initialize(){super.initialize(),this.underlays_el=(0,_.div)({style:m}),this.primary=this.create_layer(),this.overlays=this.create_layer(),this.overlays_el=(0,_.div)({style:m}),this.events_el=(0,_.div)({class:\"bk-canvas-events\",style:m});const e=[this.underlays_el,this.primary.el,this.overlays.el,this.overlays_el,this.events_el];(0,p.extend)(this.el.style,m),(0,_.append)(this.el,...e),this.ui_event_bus=new b.UIEventBus(this)}async lazy_initialize(){await super.lazy_initialize(),\"webgl\"==this.model.output_backend&&(this.webgl=await y())}remove(){this.ui_event_bus.destroy(),super.remove()}add_underlay(e){this.underlays_el.appendChild(e)}add_overlay(e){this.overlays_el.appendChild(e)}add_event(e){this.events_el.appendChild(e)}get pixel_ratio(){return this.primary.pixel_ratio}resize(e,t){this.bbox=new v.BBox({left:0,top:0,width:e,height:t}),this.primary.resize(e,t),this.overlays.resize(e,t)}prepare_webgl(e){const{webgl:t}=this;if(null!=t){const{width:i,height:s}=this.bbox;t.canvas.width=this.pixel_ratio*i,t.canvas.height=this.pixel_ratio*s;const[a,r,l,n]=e,{xview:o,yview:h}=this.bbox,c=o.compute(a),u=h.compute(r+n),_=this.pixel_ratio;t.regl_wrapper.set_scissor(_*c,_*u,_*l,_*n),this._clear_webgl()}}blit_webgl(e){const{webgl:t}=this;if(null!=t){if(u.logger.debug(\"Blitting WebGL canvas\"),e.restore(),e.drawImage(t.canvas,0,0),e.save(),this.model.hidpi){const t=this.pixel_ratio;e.scale(t,t),e.translate(.5,.5)}this._clear_webgl()}}_clear_webgl(){const{webgl:e}=this;if(null!=e){const{regl_wrapper:t,canvas:i}=e;t.clear(i.width,i.height)}}compose(){const e=this.create_layer(),{width:t,height:i}=this.bbox;return e.resize(t,i),e.ctx.drawImage(this.primary.canvas,0,0),e.ctx.drawImage(this.overlays.canvas,0,0),e}create_layer(){const{output_backend:e,hidpi:t}=this.model;return new w.CanvasLayer(e,t)}to_blob(){return this.compose().to_blob()}}i.CanvasView=f,f.__name__=\"CanvasView\";class x extends h.HasProps{constructor(e){super(e)}}i.Canvas=x,r=x,x.__name__=\"Canvas\",r.prototype.default_view=f,r.internal((({Boolean:e})=>({hidpi:[e,!0],output_backend:[d.OutputBackend,\"canvas\"]})))},\n", - " function _(t,e,s,n,i){n();const r=t(1),a=(0,r.__importDefault)(t(225)),_=t(15),h=t(19),o=t(43),l=(0,r.__importStar)(t(251)),c=t(252),p=t(9),u=t(8),v=t(27),d=t(230);class g{constructor(t){this.canvas_view=t,this.pan_start=new _.Signal(this,\"pan:start\"),this.pan=new _.Signal(this,\"pan\"),this.pan_end=new _.Signal(this,\"pan:end\"),this.pinch_start=new _.Signal(this,\"pinch:start\"),this.pinch=new _.Signal(this,\"pinch\"),this.pinch_end=new _.Signal(this,\"pinch:end\"),this.rotate_start=new _.Signal(this,\"rotate:start\"),this.rotate=new _.Signal(this,\"rotate\"),this.rotate_end=new _.Signal(this,\"rotate:end\"),this.tap=new _.Signal(this,\"tap\"),this.doubletap=new _.Signal(this,\"doubletap\"),this.press=new _.Signal(this,\"press\"),this.pressup=new _.Signal(this,\"pressup\"),this.move_enter=new _.Signal(this,\"move:enter\"),this.move=new _.Signal(this,\"move\"),this.move_exit=new _.Signal(this,\"move:exit\"),this.scroll=new _.Signal(this,\"scroll\"),this.keydown=new _.Signal(this,\"keydown\"),this.keyup=new _.Signal(this,\"keyup\"),this.hammer=new a.default(this.hit_area,{touchAction:\"auto\",inputClass:a.default.TouchMouseInput}),this._prev_move=null,this._curr_pan=null,this._curr_pinch=null,this._curr_rotate=null,this._configure_hammerjs(),this.hit_area.addEventListener(\"mousemove\",(t=>this._mouse_move(t))),this.hit_area.addEventListener(\"mouseenter\",(t=>this._mouse_enter(t))),this.hit_area.addEventListener(\"mouseleave\",(t=>this._mouse_exit(t))),this.hit_area.addEventListener(\"contextmenu\",(t=>this._context_menu(t))),this.hit_area.addEventListener(\"wheel\",(t=>this._mouse_wheel(t))),document.addEventListener(\"keydown\",this),document.addEventListener(\"keyup\",this),this.menu=new d.ContextMenu([],{prevent_hide:t=>2==t.button&&t.target==this.hit_area}),this.hit_area.appendChild(this.menu.el)}get hit_area(){return this.canvas_view.events_el}destroy(){this.menu.remove(),this.hammer.destroy(),document.removeEventListener(\"keydown\",this),document.removeEventListener(\"keyup\",this)}handleEvent(t){\"keydown\"==t.type?this._key_down(t):\"keyup\"==t.type&&this._key_up(t)}_configure_hammerjs(){this.hammer.get(\"doubletap\").recognizeWith(\"tap\"),this.hammer.get(\"tap\").requireFailure(\"doubletap\"),this.hammer.get(\"doubletap\").dropRequireFailure(\"tap\"),this.hammer.on(\"doubletap\",(t=>this._doubletap(t))),this.hammer.on(\"tap\",(t=>this._tap(t))),this.hammer.on(\"press\",(t=>this._press(t))),this.hammer.on(\"pressup\",(t=>this._pressup(t))),this.hammer.get(\"pan\").set({direction:a.default.DIRECTION_ALL}),this.hammer.on(\"panstart\",(t=>this._pan_start(t))),this.hammer.on(\"pan\",(t=>this._pan(t))),this.hammer.on(\"panend\",(t=>this._pan_end(t))),this.hammer.get(\"pinch\").set({enable:!0}),this.hammer.on(\"pinchstart\",(t=>this._pinch_start(t))),this.hammer.on(\"pinch\",(t=>this._pinch(t))),this.hammer.on(\"pinchend\",(t=>this._pinch_end(t))),this.hammer.get(\"rotate\").set({enable:!0}),this.hammer.on(\"rotatestart\",(t=>this._rotate_start(t))),this.hammer.on(\"rotate\",(t=>this._rotate(t))),this.hammer.on(\"rotateend\",(t=>this._rotate_end(t)))}register_tool(t){const e=t.model.event_type;null!=e&&((0,u.isString)(e)?this._register_tool(t,e):e.forEach(((e,s)=>this._register_tool(t,e,s<1))))}_register_tool(t,e,s=!0){const n=t,{id:i}=n.model,r=t=>e=>{e.id==i&&t(e.e)},a=t=>e=>{t(e.e)};switch(e){case\"pan\":null!=n._pan_start&&n.connect(this.pan_start,r(n._pan_start.bind(n))),null!=n._pan&&n.connect(this.pan,r(n._pan.bind(n))),null!=n._pan_end&&n.connect(this.pan_end,r(n._pan_end.bind(n)));break;case\"pinch\":null!=n._pinch_start&&n.connect(this.pinch_start,r(n._pinch_start.bind(n))),null!=n._pinch&&n.connect(this.pinch,r(n._pinch.bind(n))),null!=n._pinch_end&&n.connect(this.pinch_end,r(n._pinch_end.bind(n)));break;case\"rotate\":null!=n._rotate_start&&n.connect(this.rotate_start,r(n._rotate_start.bind(n))),null!=n._rotate&&n.connect(this.rotate,r(n._rotate.bind(n))),null!=n._rotate_end&&n.connect(this.rotate_end,r(n._rotate_end.bind(n)));break;case\"move\":null!=n._move_enter&&n.connect(this.move_enter,r(n._move_enter.bind(n))),null!=n._move&&n.connect(this.move,r(n._move.bind(n))),null!=n._move_exit&&n.connect(this.move_exit,r(n._move_exit.bind(n)));break;case\"tap\":null!=n._tap&&n.connect(this.tap,r(n._tap.bind(n))),null!=n._doubletap&&n.connect(this.doubletap,r(n._doubletap.bind(n)));break;case\"press\":null!=n._press&&n.connect(this.press,r(n._press.bind(n))),null!=n._pressup&&n.connect(this.pressup,r(n._pressup.bind(n)));break;case\"scroll\":null!=n._scroll&&n.connect(this.scroll,r(n._scroll.bind(n)));break;default:throw new Error(`unsupported event_type: ${e}`)}s&&(null!=n._keydown&&n.connect(this.keydown,a(n._keydown.bind(n))),null!=n._keyup&&n.connect(this.keyup,a(n._keyup.bind(n))),v.is_mobile&&null!=n._scroll&&\"pinch\"==e&&(h.logger.debug(\"Registering scroll on touch screen\"),n.connect(this.scroll,r(n._scroll.bind(n)))))}_hit_test_renderers(t,e,s){var n;const i=t.get_renderer_views();for(const t of(0,p.reversed)(i))if(null===(n=t.interactive_hit)||void 0===n?void 0:n.call(t,e,s))return t;return null}set_cursor(t=\"default\"){this.hit_area.style.cursor=t}_hit_test_frame(t,e,s){return t.frame.bbox.contains(e,s)}_hit_test_canvas(t,e,s){return t.layout.bbox.contains(e,s)}_hit_test_plot(t,e){for(const s of this.canvas_view.plot_views)if(s.layout.bbox.relative().contains(t,e))return s;return null}_trigger(t,e,s){var n;const{sx:i,sy:r}=e,a=this._hit_test_plot(i,r),_=t=>{const[s,n]=[i,r];return Object.assign(Object.assign({},e),{sx:s,sy:n})};if(\"panstart\"==e.type||\"pan\"==e.type||\"panend\"==e.type){let n;if(\"panstart\"==e.type&&null!=a?(this._curr_pan={plot_view:a},n=a):\"pan\"==e.type&&null!=this._curr_pan?n=this._curr_pan.plot_view:\"panend\"==e.type&&null!=this._curr_pan?(n=this._curr_pan.plot_view,this._curr_pan=null):n=null,null!=n){const e=_();this.__trigger(n,t,e,s)}}else if(\"pinchstart\"==e.type||\"pinch\"==e.type||\"pinchend\"==e.type){let n;if(\"pinchstart\"==e.type&&null!=a?(this._curr_pinch={plot_view:a},n=a):\"pinch\"==e.type&&null!=this._curr_pinch?n=this._curr_pinch.plot_view:\"pinchend\"==e.type&&null!=this._curr_pinch?(n=this._curr_pinch.plot_view,this._curr_pinch=null):n=null,null!=n){const e=_();this.__trigger(n,t,e,s)}}else if(\"rotatestart\"==e.type||\"rotate\"==e.type||\"rotateend\"==e.type){let n;if(\"rotatestart\"==e.type&&null!=a?(this._curr_rotate={plot_view:a},n=a):\"rotate\"==e.type&&null!=this._curr_rotate?n=this._curr_rotate.plot_view:\"rotateend\"==e.type&&null!=this._curr_rotate?(n=this._curr_rotate.plot_view,this._curr_rotate=null):n=null,null!=n){const e=_();this.__trigger(n,t,e,s)}}else if(\"mouseenter\"==e.type||\"mousemove\"==e.type||\"mouseleave\"==e.type){const h=null===(n=this._prev_move)||void 0===n?void 0:n.plot_view;if(null!=h&&(\"mouseleave\"==e.type||h!=a)){const{sx:t,sy:e}=_();this.__trigger(h,this.move_exit,{type:\"mouseleave\",sx:t,sy:e,shiftKey:!1,ctrlKey:!1},s)}if(null!=a&&(\"mouseenter\"==e.type||h!=a)){const{sx:t,sy:e}=_();this.__trigger(a,this.move_enter,{type:\"mouseenter\",sx:t,sy:e,shiftKey:!1,ctrlKey:!1},s)}if(null!=a&&\"mousemove\"==e.type){const e=_();this.__trigger(a,t,e,s)}this._prev_move={sx:i,sy:r,plot_view:a}}else if(null!=a){const e=_();this.__trigger(a,t,e,s)}}__trigger(t,e,s,n){var i,r;const a=t.model.toolbar.gestures,_=e.name.split(\":\")[0],h=this._hit_test_renderers(t,s.sx,s.sy),o=this._hit_test_canvas(t,s.sx,s.sy);switch(_){case\"move\":{const n=a[_].active;null!=n&&this.trigger(e,s,n.id);const r=t.model.toolbar.inspectors.filter((t=>t.active));let l=\"default\";null!=h?(l=null!==(i=h.cursor(s.sx,s.sy))&&void 0!==i?i:l,(0,p.is_empty)(r)||(e=this.move_exit)):this._hit_test_frame(t,s.sx,s.sy)&&((0,p.is_empty)(r)||(l=\"crosshair\")),this.set_cursor(l),t.set_toolbar_visibility(o),r.map((t=>this.trigger(e,s,t.id)));break}case\"tap\":{const{target:t}=n;if(null!=t&&t!=this.hit_area)return;null!=h&&null!=h.on_hit&&h.on_hit(s.sx,s.sy);const i=a[_].active;null!=i&&this.trigger(e,s,i.id);break}case\"doubletap\":{const t=null!==(r=a.doubletap.active)&&void 0!==r?r:a.tap.active;null!=t&&this.trigger(e,s,t.id);break}case\"scroll\":{const t=a[v.is_mobile?\"pinch\":\"scroll\"].active;null!=t&&(n.preventDefault(),n.stopPropagation(),this.trigger(e,s,t.id));break}case\"pan\":{const t=a[_].active;null!=t&&(n.preventDefault(),this.trigger(e,s,t.id));break}default:{const t=a[_].active;null!=t&&this.trigger(e,s,t.id)}}this._trigger_bokeh_event(t,s)}trigger(t,e,s=null){t.emit({id:s,e})}_trigger_bokeh_event(t,e){const s=(()=>{const{sx:s,sy:n}=e,i=t.frame.x_scale.invert(s),r=t.frame.y_scale.invert(n);switch(e.type){case\"wheel\":return new l.MouseWheel(s,n,i,r,e.delta);case\"mousemove\":return new l.MouseMove(s,n,i,r);case\"mouseenter\":return new l.MouseEnter(s,n,i,r);case\"mouseleave\":return new l.MouseLeave(s,n,i,r);case\"tap\":return new l.Tap(s,n,i,r);case\"doubletap\":return new l.DoubleTap(s,n,i,r);case\"press\":return new l.Press(s,n,i,r);case\"pressup\":return new l.PressUp(s,n,i,r);case\"pan\":return new l.Pan(s,n,i,r,e.deltaX,e.deltaY);case\"panstart\":return new l.PanStart(s,n,i,r);case\"panend\":return new l.PanEnd(s,n,i,r);case\"pinch\":return new l.Pinch(s,n,i,r,e.scale);case\"pinchstart\":return new l.PinchStart(s,n,i,r);case\"pinchend\":return new l.PinchEnd(s,n,i,r);case\"rotate\":return new l.Rotate(s,n,i,r,e.rotation);case\"rotatestart\":return new l.RotateStart(s,n,i,r);case\"rotateend\":return new l.RotateEnd(s,n,i,r);default:return}})();null!=s&&t.model.trigger_event(s)}_get_sxy(t){const{pageX:e,pageY:s}=function(t){return\"undefined\"!=typeof TouchEvent&&t instanceof TouchEvent}(t)?(0!=t.touches.length?t.touches:t.changedTouches)[0]:t,{left:n,top:i}=(0,o.offset)(this.hit_area);return{sx:e-n,sy:s-i}}_pan_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t.srcEvent)),{deltaX:t.deltaX,deltaY:t.deltaY,shiftKey:t.srcEvent.shiftKey,ctrlKey:t.srcEvent.ctrlKey})}_pinch_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t.srcEvent)),{scale:t.scale,shiftKey:t.srcEvent.shiftKey,ctrlKey:t.srcEvent.ctrlKey})}_rotate_event(t){return 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x=p-l;e.translate(t,u),e.rotate(l),e.beginPath(),e.moveTo(c,0),e.arc(0,0,c,0,x,d),e.rotate(x),e.lineTo(h,0),e.arc(0,0,h,0,-x,!d),e.closePath(),e.rotate(-x-l),e.translate(-t,-u),this.visuals.fill.apply(e,s),this.visuals.hatch.apply(e,s),this.visuals.line.apply(e,s)}}_hit_point(e){const{sx:t,sy:s}=e,i=this.renderer.xscale.invert(t),r=this.renderer.yscale.invert(s);let n,a,o,_;if(\"data\"==this.model.properties.outer_radius.units)n=i-this.max_outer_radius,o=i+this.max_outer_radius,a=r-this.max_outer_radius,_=r+this.max_outer_radius;else{const e=t-this.max_outer_radius,i=t+this.max_outer_radius;[n,o]=this.renderer.xscale.r_invert(e,i);const r=s-this.max_outer_radius,d=s+this.max_outer_radius;[a,_]=this.renderer.yscale.r_invert(r,d)}const d=[];for(const e of this.index.indices({x0:n,x1:o,y0:a,y1:_})){const t=this.souter_radius[e]**2,s=this.sinner_radius[e]**2,[n,a]=this.renderer.xscale.r_compute(i,this._x[e]),[o,_]=this.renderer.yscale.r_compute(r,this._y[e]),u=(n-a)**2+(o-_)**2;u<=t&&u>=s&&d.push(e)}const u=\"anticlock\"==this.model.direction,h=[];for(const e of d){const i=Math.atan2(s-this.sy[e],t-this.sx[e]);(0,l.angle_between)(-i,-this.start_angle.get(e),-this.end_angle.get(e),u)&&h.push(e)}return new p.Selection({indices:h})}draw_legend_for_index(e,t,s){(0,_.generic_area_vector_legend)(this.visuals,e,t,s)}scenterxy(e){const t=(this.sinner_radius[e]+this.souter_radius[e])/2,s=(this.start_angle.get(e)+this.end_angle.get(e))/2;return[this.sx[e]+t*Math.cos(s),this.sy[e]+t*Math.sin(s)]}}s.AnnularWedgeView=x,x.__name__=\"AnnularWedgeView\";class g extends o.XYGlyph{constructor(e){super(e)}}s.AnnularWedge=g,a=g,g.__name__=\"AnnularWedge\",a.prototype.default_view=x,a.mixins([d.LineVector,d.FillVector,d.HatchVector]),a.define((({})=>({direction:[h.Direction,\"anticlock\"],inner_radius:[c.DistanceSpec,{field:\"inner_radius\"}],outer_radius:[c.DistanceSpec,{field:\"outer_radius\"}],start_angle:[c.AngleSpec,{field:\"start_angle\"}],end_angle:[c.AngleSpec,{field:\"end_angle\"}]})))},\n", - " function _(s,e,i,r,t){r();const n=s(1);var a;const u=s(178),o=s(24),_=s(48),d=(0,n.__importStar)(s(18)),h=s(27),c=s(72);class l extends u.XYGlyphView{_map_data(){\"data\"==this.model.properties.inner_radius.units?this.sinner_radius=this.sdist(this.renderer.xscale,this._x,this.inner_radius):this.sinner_radius=(0,o.to_screen)(this.inner_radius),\"data\"==this.model.properties.outer_radius.units?this.souter_radius=this.sdist(this.renderer.xscale,this._x,this.outer_radius):this.souter_radius=(0,o.to_screen)(this.outer_radius)}_render(s,e,i){const{sx:r,sy:t,sinner_radius:n,souter_radius:a}=null!=i?i:this;for(const i of e){const e=r[i],u=t[i],o=n[i],_=a[i];if(isFinite(e+u+o+_)){if(s.beginPath(),h.is_ie)for(const i of[!1,!0])s.moveTo(e,u),s.arc(e,u,o,0,Math.PI,i),s.moveTo(e+_,u),s.arc(e,u,_,Math.PI,0,!i);else s.arc(e,u,o,0,2*Math.PI,!0),s.moveTo(e+_,u),s.arc(e,u,_,2*Math.PI,0,!1);this.visuals.fill.apply(s,i),this.visuals.hatch.apply(s,i),this.visuals.line.apply(s,i)}}}_hit_point(s){const{sx:e,sy:i}=s,r=this.renderer.xscale.invert(e),t=this.renderer.yscale.invert(i);let n,a,u,o;if(\"data\"==this.model.properties.outer_radius.units)n=r-this.max_outer_radius,u=r+this.max_outer_radius,a=t-this.max_outer_radius,o=t+this.max_outer_radius;else{const s=e-this.max_outer_radius,r=e+this.max_outer_radius;[n,u]=this.renderer.xscale.r_invert(s,r);const t=i-this.max_outer_radius,_=i+this.max_outer_radius;[a,o]=this.renderer.yscale.r_invert(t,_)}const _=[];for(const s of this.index.indices({x0:n,x1:u,y0:a,y1:o})){const e=this.souter_radius[s]**2,i=this.sinner_radius[s]**2,[n,a]=this.renderer.xscale.r_compute(r,this._x[s]),[u,o]=this.renderer.yscale.r_compute(t,this._y[s]),d=(n-a)**2+(u-o)**2;d<=e&&d>=i&&_.push(s)}return new c.Selection({indices:_})}draw_legend_for_index(s,{x0:e,y0:i,x1:r,y1:t},n){const a=n+1,u=new Array(a);u[n]=(e+r)/2;const o=new Array(a);o[n]=(i+t)/2;const _=.5*Math.min(Math.abs(r-e),Math.abs(t-i)),d=new Array(a);d[n]=.4*_;const h=new Array(a);h[n]=.8*_,this._render(s,[n],{sx:u,sy:o,sinner_radius:d,souter_radius:h})}}i.AnnulusView=l,l.__name__=\"AnnulusView\";class x extends u.XYGlyph{constructor(s){super(s)}}i.Annulus=x,a=x,x.__name__=\"Annulus\",a.prototype.default_view=l,a.mixins([_.LineVector,_.FillVector,_.HatchVector]),a.define((({})=>({inner_radius:[d.DistanceSpec,{field:\"inner_radius\"}],outer_radius:[d.DistanceSpec,{field:\"outer_radius\"}]})))},\n", - " function _(e,i,s,t,n){t();const r=e(1);var a;const c=e(178),d=e(184),l=e(48),_=e(24),o=e(20),u=(0,r.__importStar)(e(18));class h extends c.XYGlyphView{_map_data(){\"data\"==this.model.properties.radius.units?this.sradius=this.sdist(this.renderer.xscale,this._x,this.radius):this.sradius=(0,_.to_screen)(this.radius)}_render(e,i,s){if(this.visuals.line.doit){const{sx:t,sy:n,sradius:r,start_angle:a,end_angle:c}=null!=s?s:this,d=\"anticlock\"==this.model.direction;for(const s of i){const i=t[s],l=n[s],_=r[s],o=a.get(s),u=c.get(s);isFinite(i+l+_+o+u)&&(e.beginPath(),e.arc(i,l,_,o,u,d),this.visuals.line.set_vectorize(e,s),e.stroke())}}}draw_legend_for_index(e,i,s){(0,d.generic_line_vector_legend)(this.visuals,e,i,s)}}s.ArcView=h,h.__name__=\"ArcView\";class g extends c.XYGlyph{constructor(e){super(e)}}s.Arc=g,a=g,g.__name__=\"Arc\",a.prototype.default_view=h,a.mixins(l.LineVector),a.define((({})=>({direction:[o.Direction,\"anticlock\"],radius:[u.DistanceSpec,{field:\"radius\"}],start_angle:[u.AngleSpec,{field:\"start_angle\"}],end_angle:[u.AngleSpec,{field:\"end_angle\"}]})))},\n", - " function _(e,t,i,n,s){n();const o=e(1);var c;const r=e(48),a=e(179),_=e(184),d=e(78),l=(0,o.__importStar)(e(18));function x(e,t,i,n,s,o,c,r){const a=[],_=[[],[]];for(let _=0;_<=2;_++){let d,l,x;if(0===_?(l=6*e-12*i+6*s,d=-3*e+9*i-9*s+3*c,x=3*i-3*e):(l=6*t-12*n+6*o,d=-3*t+9*n-9*o+3*r,x=3*n-3*t),Math.abs(d)<1e-12){if(Math.abs(l)<1e-12)continue;const e=-x/l;0({x0:[l.XCoordinateSpec,{field:\"x0\"}],y0:[l.YCoordinateSpec,{field:\"y0\"}],x1:[l.XCoordinateSpec,{field:\"x1\"}],y1:[l.YCoordinateSpec,{field:\"y1\"}],cx0:[l.XCoordinateSpec,{field:\"cx0\"}],cy0:[l.YCoordinateSpec,{field:\"cy0\"}],cx1:[l.XCoordinateSpec,{field:\"cx1\"}],cy1:[l.YCoordinateSpec,{field:\"cy1\"}]}))),c.mixins(r.LineVector)},\n", - " function _(s,i,e,t,r){t();const a=s(1);var n;const h=s(178),d=s(48),l=s(24),c=s(20),_=(0,a.__importStar)(s(185)),u=(0,a.__importStar)(s(18)),o=s(9),x=s(12),m=s(72);class p extends h.XYGlyphView{async lazy_initialize(){await super.lazy_initialize();const{webgl:i}=this.renderer.plot_view.canvas_view;if(null==i?void 0:i.regl_wrapper.has_webgl){const{MarkerGL:e}=await Promise.resolve().then((()=>(0,a.__importStar)(s(426))));this.glglyph=new e(i.regl_wrapper,this,\"circle\")}}get use_radius(){return!(this.radius.is_Scalar()&&isNaN(this.radius.value))}_set_data(s){super._set_data(s);const i=(()=>{if(this.use_radius)return 2*this.max_radius;{const{size:s}=this;return s.is_Scalar()?s.value:(0,x.max)(s.array)}})();this._configure(\"max_size\",{value:i})}_map_data(){if(this.use_radius)if(\"data\"==this.model.properties.radius.units)switch(this.model.radius_dimension){case\"x\":this.sradius=this.sdist(this.renderer.xscale,this._x,this.radius);break;case\"y\":this.sradius=this.sdist(this.renderer.yscale,this._y,this.radius);break;case\"max\":{const s=this.sdist(this.renderer.xscale,this._x,this.radius),i=this.sdist(this.renderer.yscale,this._y,this.radius);this.sradius=(0,x.map)(s,((s,e)=>Math.max(s,i[e])));break}case\"min\":{const s=this.sdist(this.renderer.xscale,this._x,this.radius),i=this.sdist(this.renderer.yscale,this._y,this.radius);this.sradius=(0,x.map)(s,((s,e)=>Math.min(s,i[e])));break}}else this.sradius=(0,l.to_screen)(this.radius);else{const s=l.ScreenArray.from(this.size);this.sradius=(0,x.map)(s,(s=>s/2))}}_mask_data(){const{frame:s}=this.renderer.plot_view,i=s.x_target,e=s.y_target;let t,r;return this.use_radius&&\"data\"==this.model.properties.radius.units?(t=i.map((s=>this.renderer.xscale.invert(s))).widen(this.max_radius),r=e.map((s=>this.renderer.yscale.invert(s))).widen(this.max_radius)):(t=i.widen(this.max_size).map((s=>this.renderer.xscale.invert(s))),r=e.widen(this.max_size).map((s=>this.renderer.yscale.invert(s)))),this.index.indices({x0:t.start,x1:t.end,y0:r.start,y1:r.end})}_render(s,i,e){const{sx:t,sy:r,sradius:a}=null!=e?e:this;for(const e of i){const i=t[e],n=r[e],h=a[e];isFinite(i+n+h)&&(s.beginPath(),s.arc(i,n,h,0,2*Math.PI,!1),this.visuals.fill.apply(s,e),this.visuals.hatch.apply(s,e),this.visuals.line.apply(s,e))}}_hit_point(s){const{sx:i,sy:e}=s,t=this.renderer.xscale.invert(i),r=this.renderer.yscale.invert(e),{hit_dilation:a}=this.model;let n,h,d,l;if(this.use_radius&&\"data\"==this.model.properties.radius.units)n=t-this.max_radius*a,h=t+this.max_radius*a,d=r-this.max_radius*a,l=r+this.max_radius*a;else{const s=i-this.max_size*a,t=i+this.max_size*a;[n,h]=this.renderer.xscale.r_invert(s,t);const r=e-this.max_size*a,c=e+this.max_size*a;[d,l]=this.renderer.yscale.r_invert(r,c)}const c=this.index.indices({x0:n,x1:h,y0:d,y1:l}),_=[];if(this.use_radius&&\"data\"==this.model.properties.radius.units)for(const s of c){const i=(this.sradius[s]*a)**2,[e,n]=this.renderer.xscale.r_compute(t,this._x[s]),[h,d]=this.renderer.yscale.r_compute(r,this._y[s]);(e-n)**2+(h-d)**2<=i&&_.push(s)}else for(const s of c){const t=(this.sradius[s]*a)**2;(this.sx[s]-i)**2+(this.sy[s]-e)**2<=t&&_.push(s)}return new m.Selection({indices:_})}_hit_span(s){const{sx:i,sy:e}=s,t=this.bounds();let r,a,n,h;if(\"h\"==s.direction){let s,e;if(n=t.y0,h=t.y1,this.use_radius&&\"data\"==this.model.properties.radius.units)s=i-this.max_radius,e=i+this.max_radius,[r,a]=this.renderer.xscale.r_invert(s,e);else{const t=this.max_size/2;s=i-t,e=i+t,[r,a]=this.renderer.xscale.r_invert(s,e)}}else{let s,i;if(r=t.x0,a=t.x1,this.use_radius&&\"data\"==this.model.properties.radius.units)s=e-this.max_radius,i=e+this.max_radius,[n,h]=this.renderer.yscale.r_invert(s,i);else{const t=this.max_size/2;s=e-t,i=e+t,[n,h]=this.renderer.yscale.r_invert(s,i)}}const d=[...this.index.indices({x0:r,x1:a,y0:n,y1:h})];return new m.Selection({indices:d})}_hit_rect(s){const{sx0:i,sx1:e,sy0:t,sy1:r}=s,[a,n]=this.renderer.xscale.r_invert(i,e),[h,d]=this.renderer.yscale.r_invert(t,r),l=[...this.index.indices({x0:a,x1:n,y0:h,y1:d})];return new m.Selection({indices:l})}_hit_poly(s){const{sx:i,sy:e}=s,t=(0,o.range)(0,this.sx.length),r=[];for(let s=0,a=t.length;s({angle:[u.AngleSpec,0],size:[u.ScreenSizeSpec,{value:4}],radius:[u.NullDistanceSpec,null],radius_dimension:[c.RadiusDimension,\"x\"],hit_dilation:[s,1]})))},\n", - " function _(e,l,s,i,_){var p;i();const t=e(274);class a extends t.EllipseOvalView{}s.EllipseView=a,a.__name__=\"EllipseView\";class n extends t.EllipseOval{constructor(e){super(e)}}s.Ellipse=n,p=n,n.__name__=\"Ellipse\",p.prototype.default_view=a},\n", - " function _(t,s,e,i,h){i();const n=t(1),r=t(275),a=(0,n.__importStar)(t(185)),l=t(24),_=t(72),o=(0,n.__importStar)(t(18));class d extends r.CenterRotatableView{_map_data(){\"data\"==this.model.properties.width.units?this.sw=this.sdist(this.renderer.xscale,this._x,this.width,\"center\"):this.sw=(0,l.to_screen)(this.width),\"data\"==this.model.properties.height.units?this.sh=this.sdist(this.renderer.yscale,this._y,this.height,\"center\"):this.sh=(0,l.to_screen)(this.height)}_render(t,s,e){const{sx:i,sy:h,sw:n,sh:r,angle:a}=null!=e?e:this;for(const e of s){const s=i[e],l=h[e],_=n[e],o=r[e],d=a.get(e);isFinite(s+l+_+o+d)&&(t.beginPath(),t.ellipse(s,l,_/2,o/2,d,0,2*Math.PI),this.visuals.fill.apply(t,e),this.visuals.hatch.apply(t,e),this.visuals.line.apply(t,e))}}_hit_point(t){let s,e,i,h,n,r,l,o,d;const{sx:c,sy:p}=t,w=this.renderer.xscale.invert(c),x=this.renderer.yscale.invert(p);\"data\"==this.model.properties.width.units?(s=w-this.max_width,e=w+this.max_width):(r=c-this.max_width,l=c+this.max_width,[s,e]=this.renderer.xscale.r_invert(r,l)),\"data\"==this.model.properties.height.units?(i=x-this.max_height,h=x+this.max_height):(o=p-this.max_height,d=p+this.max_height,[i,h]=this.renderer.yscale.r_invert(o,d));const m=this.index.indices({x0:s,x1:e,y0:i,y1:h}),y=[];for(const t of m)n=a.point_in_ellipse(c,p,this.angle.get(t),this.sh[t]/2,this.sw[t]/2,this.sx[t],this.sy[t]),n&&y.push(t);return new _.Selection({indices:y})}draw_legend_for_index(t,{x0:s,y0:e,x1:i,y1:h},n){const r=n+1,a=new Array(r);a[n]=(s+i)/2;const l=new Array(r);l[n]=(e+h)/2;const _=this.sw[n]/this.sh[n],d=.8*Math.min(Math.abs(i-s),Math.abs(h-e)),c=new Array(r),p=new Array(r);_>1?(c[n]=d,p[n]=d/_):(c[n]=d*_,p[n]=d);const w=new o.UniformScalar(0,r);this._render(t,[n],{sx:a,sy:l,sw:c,sh:p,angle:w})}}e.EllipseOvalView=d,d.__name__=\"EllipseOvalView\";class c extends r.CenterRotatable{constructor(t){super(t)}}e.EllipseOval=c,c.__name__=\"EllipseOval\"},\n", - " function _(e,t,i,a,n){a();const s=e(1);var r;const h=e(178),o=e(48),_=(0,s.__importStar)(e(18));class c extends h.XYGlyphView{get max_w2(){return\"data\"==this.model.properties.width.units?this.max_width/2:0}get max_h2(){return\"data\"==this.model.properties.height.units?this.max_height/2:0}_bounds({x0:e,x1:t,y0:i,y1:a}){const{max_w2:n,max_h2:s}=this;return{x0:e-n,x1:t+n,y0:i-s,y1:a+s}}}i.CenterRotatableView=c,c.__name__=\"CenterRotatableView\";class l extends h.XYGlyph{constructor(e){super(e)}}i.CenterRotatable=l,r=l,l.__name__=\"CenterRotatable\",r.mixins([o.LineVector,o.FillVector,o.HatchVector]),r.define((({})=>({angle:[_.AngleSpec,0],width:[_.DistanceSpec,{field:\"width\"}],height:[_.DistanceSpec,{field:\"height\"}]})))},\n", - " function _(t,e,s,i,h){i();const r=t(1);var a;const n=t(277),o=t(24),_=(0,r.__importStar)(t(18));class c extends n.BoxView{scenterxy(t){return[(this.sleft[t]+this.sright[t])/2,this.sy[t]]}_lrtb(t){const e=this._left[t],s=this._right[t],i=this._y[t],h=this.height.get(t)/2;return[Math.min(e,s),Math.max(e,s),i+h,i-h]}_map_data(){this.sy=this.renderer.yscale.v_compute(this._y),this.sh=this.sdist(this.renderer.yscale,this._y,this.height,\"center\"),this.sleft=this.renderer.xscale.v_compute(this._left),this.sright=this.renderer.xscale.v_compute(this._right);const t=this.sy.length;this.stop=new o.ScreenArray(t),this.sbottom=new o.ScreenArray(t);for(let e=0;e({left:[_.XCoordinateSpec,{value:0}],y:[_.YCoordinateSpec,{field:\"y\"}],height:[_.NumberSpec,{value:1}],right:[_.XCoordinateSpec,{field:\"right\"}]})))},\n", - " function _(t,e,s,r,i){var n;r();const a=t(48),h=t(179),o=t(184),c=t(72);class _ extends h.GlyphView{get_anchor_point(t,e,s){const r=Math.min(this.sleft[e],this.sright[e]),i=Math.max(this.sright[e],this.sleft[e]),n=Math.min(this.stop[e],this.sbottom[e]),a=Math.max(this.sbottom[e],this.stop[e]);switch(t){case\"top_left\":return{x:r,y:n};case\"top\":case\"top_center\":return{x:(r+i)/2,y:n};case\"top_right\":return{x:i,y:n};case\"bottom_left\":return{x:r,y:a};case\"bottom\":case\"bottom_center\":return{x:(r+i)/2,y:a};case\"bottom_right\":return{x:i,y:a};case\"left\":case\"center_left\":return{x:r,y:(n+a)/2};case\"center\":case\"center_center\":return{x:(r+i)/2,y:(n+a)/2};case\"right\":case\"center_right\":return{x:i,y:(n+a)/2}}}_index_data(t){const{min:e,max:s}=Math,{data_size:r}=this;for(let i=0;i({r:[l.NumberSpec,{field:\"r\"}],q:[l.NumberSpec,{field:\"q\"}],scale:[l.NumberSpec,1],size:[e,1],aspect_scale:[e,1],orientation:[_.HexTileOrientation,\"pointytop\"]}))),a.override({line_color:null})},\n", - " function _(e,a,t,_,r){var n;_();const s=e(280),o=e(173),i=e(201);class p extends s.ImageBaseView{connect_signals(){super.connect_signals(),this.connect(this.model.color_mapper.change,(()=>this._update_image()))}_update_image(){null!=this.image_data&&(this._set_data(null),this.renderer.request_render())}_flat_img_to_buf8(e){return this.model.color_mapper.rgba_mapper.v_compute(e)}}t.ImageView=p,p.__name__=\"ImageView\";class m extends s.ImageBase{constructor(e){super(e)}}t.Image=m,n=m,m.__name__=\"Image\",n.prototype.default_view=p,n.define((({Ref:e})=>({color_mapper:[e(o.ColorMapper),()=>new i.LinearColorMapper({palette:[\"#000000\",\"#252525\",\"#525252\",\"#737373\",\"#969696\",\"#bdbdbd\",\"#d9d9d9\",\"#f0f0f0\",\"#ffffff\"]})]})))},\n", - " function _(e,t,i,s,a){s();const h=e(1);var n;const r=e(178),_=e(24),d=(0,h.__importStar)(e(18)),l=e(72),g=e(9),o=e(29),c=e(11);class m extends r.XYGlyphView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.global_alpha.change,(()=>this.renderer.request_render()))}_render(e,t,i){const{image_data:s,sx:a,sy:h,sw:n,sh:r,global_alpha:_}=null!=i?i:this,d=e.getImageSmoothingEnabled();e.setImageSmoothingEnabled(!1);const l=_.is_Scalar();l&&(e.globalAlpha=_.value);for(const i of t){const t=s[i],_=a[i],d=h[i],g=n[i],o=r[i],c=this.global_alpha.get(i);if(null==t||!isFinite(_+d+g+o+c))continue;l||(e.globalAlpha=c);const m=d;e.translate(0,m),e.scale(1,-1),e.translate(0,-m),e.drawImage(t,0|_,0|d,g,o),e.translate(0,m),e.scale(1,-1),e.translate(0,-m)}e.setImageSmoothingEnabled(d)}_set_data(e){this._set_width_heigh_data();for(let t=0,i=this.image.length;t({image:[d.NDArraySpec,{field:\"image\"}],dw:[d.DistanceSpec,{field:\"dw\"}],dh:[d.DistanceSpec,{field:\"dh\"}],global_alpha:[d.NumberSpec,{value:1}],dilate:[e,!1]})))},\n", - " function _(e,a,t,r,_){var n;r();const s=e(280),m=e(8);class i extends s.ImageBaseView{_flat_img_to_buf8(e){let a;return a=(0,m.isArray)(e)?new Uint32Array(e):e,new Uint8ClampedArray(a.buffer)}}t.ImageRGBAView=i,i.__name__=\"ImageRGBAView\";class g extends s.ImageBase{constructor(e){super(e)}}t.ImageRGBA=g,n=g,g.__name__=\"ImageRGBA\",n.prototype.default_view=i},\n", - " function _(e,t,s,r,a){r();const i=e(1);var n;const o=e(178),c=e(24),_=e(20),h=(0,i.__importStar)(e(18)),l=e(12),d=e(136);class m extends o.XYGlyphView{constructor(){super(...arguments),this._images_rendered=!1,this._set_data_iteration=0}connect_signals(){super.connect_signals(),this.connect(this.model.properties.global_alpha.change,(()=>this.renderer.request_render()))}_index_data(e){const{data_size:t}=this;for(let s=0;s{this._set_data_iteration==r&&(this.image[a]=e,this.renderer.request_render())},attempts:t+1,timeout:s})}const a=\"data\"==this.model.properties.w.units,i=\"data\"==this.model.properties.h.units,n=this._x.length,o=new c.ScreenArray(a?2*n:n),_=new c.ScreenArray(i?2*n:n),{anchor:h}=this.model;function m(e,t){switch(h){case\"top_left\":case\"bottom_left\":case\"left\":case\"center_left\":return[e,e+t];case\"top\":case\"top_center\":case\"bottom\":case\"bottom_center\":case\"center\":case\"center_center\":return[e-t/2,e+t/2];case\"top_right\":case\"bottom_right\":case\"right\":case\"center_right\":return[e-t,e]}}function g(e,t){switch(h){case\"top_left\":case\"top\":case\"top_center\":case\"top_right\":return[e,e-t];case\"bottom_left\":case\"bottom\":case\"bottom_center\":case\"bottom_right\":return[e+t,e];case\"left\":case\"center_left\":case\"center\":case\"center_center\":case\"right\":case\"center_right\":return[e+t/2,e-t/2]}}if(a)for(let e=0;e({url:[h.StringSpec,{field:\"url\"}],anchor:[_.Anchor,\"top_left\"],global_alpha:[h.NumberSpec,{value:1}],angle:[h.AngleSpec,0],w:[h.NullDistanceSpec,null],h:[h.NullDistanceSpec,null],dilate:[e,!1],retry_attempts:[t,0],retry_timeout:[t,0]})))},\n", - " function _(e,t,s,i,n){i();const o=e(1);var r;const l=e(78),_=e(48),c=(0,o.__importStar)(e(185)),h=(0,o.__importStar)(e(18)),a=e(12),d=e(13),x=e(179),y=e(184),g=e(72);class p extends x.GlyphView{_project_data(){l.inplace.project_xy(this._xs.array,this._ys.array)}_index_data(e){const{data_size:t}=this;for(let s=0;s0&&o.set(e,s)}return new g.Selection({indices:[...o.keys()],multiline_indices:(0,d.to_object)(o)})}get_interpolation_hit(e,t,s){const i=this._xs.get(e),n=this._ys.get(e),o=i[t],r=n[t],l=i[t+1],_=n[t+1];return(0,y.line_interpolation)(this.renderer,s,o,r,l,_)}draw_legend_for_index(e,t,s){(0,y.generic_line_vector_legend)(this.visuals,e,t,s)}scenterxy(){throw new Error(`${this}.scenterxy() is not implemented`)}}s.MultiLineView=p,p.__name__=\"MultiLineView\";class u extends x.Glyph{constructor(e){super(e)}}s.MultiLine=u,r=u,u.__name__=\"MultiLine\",r.prototype.default_view=p,r.define((({})=>({xs:[h.XCoordinateSeqSpec,{field:\"xs\"}],ys:[h.YCoordinateSeqSpec,{field:\"ys\"}]}))),r.mixins(_.LineVector)},\n", - " function _(t,e,s,n,i){n();const o=t(1);var r;const l=t(181),h=t(179),a=t(184),_=t(12),c=t(12),d=t(48),x=(0,o.__importStar)(t(185)),y=(0,o.__importStar)(t(18)),f=t(72),g=t(11);class p extends h.GlyphView{_project_data(){}_index_data(t){const{min:e,max:s}=Math,{data_size:n}=this;for(let i=0;i1&&c.length>1)for(let s=1,n=i.length;s1){let r=!1;for(let t=1;t({xs:[y.XCoordinateSeqSeqSeqSpec,{field:\"xs\"}],ys:[y.YCoordinateSeqSeqSeqSpec,{field:\"ys\"}]}))),r.mixins([d.LineVector,d.FillVector,d.HatchVector])},\n", - " function _(a,e,l,s,_){var t;s();const i=a(274),n=a(12);class p extends i.EllipseOvalView{_map_data(){super._map_data(),(0,n.mul)(this.sw,.75)}}l.OvalView=p,p.__name__=\"OvalView\";class v extends i.EllipseOval{constructor(a){super(a)}}l.Oval=v,t=v,v.__name__=\"Oval\",t.prototype.default_view=p},\n", - " function _(e,t,s,i,n){i();const r=e(1);var a;const o=e(179),c=e(184),_=e(12),h=e(48),l=(0,r.__importStar)(e(185)),d=(0,r.__importStar)(e(18)),y=e(72),p=e(11),x=e(78);class f extends o.GlyphView{_project_data(){x.inplace.project_xy(this._xs.array,this._ys.array)}_index_data(e){const{data_size:t}=this;for(let s=0;s({xs:[d.XCoordinateSeqSpec,{field:\"xs\"}],ys:[d.YCoordinateSeqSpec,{field:\"ys\"}]}))),a.mixins([h.LineVector,h.FillVector,h.HatchVector])},\n", - " function _(t,e,o,i,s){i();const r=t(1);var n;const _=t(277),d=(0,r.__importStar)(t(18));class a extends _.BoxView{scenterxy(t){return[this.sleft[t]/2+this.sright[t]/2,this.stop[t]/2+this.sbottom[t]/2]}_lrtb(t){return[this._left[t],this._right[t],this._top[t],this._bottom[t]]}}o.QuadView=a,a.__name__=\"QuadView\";class c extends _.Box{constructor(t){super(t)}}o.Quad=c,n=c,c.__name__=\"Quad\",n.prototype.default_view=a,n.define((({})=>({right:[d.XCoordinateSpec,{field:\"right\"}],bottom:[d.YCoordinateSpec,{field:\"bottom\"}],left:[d.XCoordinateSpec,{field:\"left\"}],top:[d.YCoordinateSpec,{field:\"top\"}]})))},\n", - " function _(e,t,i,n,s){n();const c=e(1);var o;const r=e(48),a=e(78),_=e(179),d=e(184),l=(0,c.__importStar)(e(18));function x(e,t,i){if(t==(e+i)/2)return[e,i];{const n=(e-t)/(e-2*t+i),s=e*(1-n)**2+2*t*(1-n)*n+i*n**2;return[Math.min(e,i,s),Math.max(e,i,s)]}}class y extends _.GlyphView{_project_data(){a.inplace.project_xy(this._x0,this._y0),a.inplace.project_xy(this._x1,this._y1)}_index_data(e){const{_x0:t,_x1:i,_y0:n,_y1:s,_cx:c,_cy:o,data_size:r}=this;for(let a=0;a({x0:[l.XCoordinateSpec,{field:\"x0\"}],y0:[l.YCoordinateSpec,{field:\"y0\"}],x1:[l.XCoordinateSpec,{field:\"x1\"}],y1:[l.YCoordinateSpec,{field:\"y1\"}],cx:[l.XCoordinateSpec,{field:\"cx\"}],cy:[l.YCoordinateSpec,{field:\"cy\"}]}))),o.mixins(r.LineVector)},\n", - " function _(e,t,s,i,n){i();const l=e(1);var a;const r=e(178),o=e(184),h=e(48),_=e(24),c=(0,l.__importStar)(e(18));class g extends r.XYGlyphView{_map_data(){\"data\"==this.model.properties.length.units?this.slength=this.sdist(this.renderer.xscale,this._x,this.length):this.slength=(0,_.to_screen)(this.length);const{width:e,height:t}=this.renderer.plot_view.frame.bbox,s=2*(e+t),{slength:i}=this;for(let e=0,t=i.length;e({length:[c.DistanceSpec,0],angle:[c.AngleSpec,0]})))},\n", - " function _(t,e,s,i,r){var n,h=this&&this.__createBinding||(Object.create?function(t,e,s,i){void 0===i&&(i=s),Object.defineProperty(t,i,{enumerable:!0,get:function(){return e[s]}})}:function(t,e,s,i){void 0===i&&(i=s),t[i]=e[s]}),a=this&&this.__setModuleDefault||(Object.create?function(t,e){Object.defineProperty(t,\"default\",{enumerable:!0,value:e})}:function(t,e){t.default=e}),l=this&&this.__importStar||function(t){if(t&&t.__esModule)return t;var e={};if(null!=t)for(var s in t)\"default\"!==s&&Object.prototype.hasOwnProperty.call(t,s)&&h(e,t,s);return a(e,t),e};i();const o=t(275),c=t(184),_=t(24),d=t(12),f=t(72);class y extends o.CenterRotatableView{async lazy_initialize(){await super.lazy_initialize();const{webgl:e}=this.renderer.plot_view.canvas_view;if(null==e?void 0:e.regl_wrapper.has_webgl){const{RectGL:s}=await Promise.resolve().then((()=>l(t(425))));this.glglyph=new s(e.regl_wrapper,this)}}_map_data(){if(\"data\"==this.model.properties.width.units)[this.sw,this.sx0]=this._map_dist_corner_for_data_side_length(this._x,this.width,this.renderer.xscale);else{this.sw=(0,_.to_screen)(this.width);const t=this.sx.length;this.sx0=new _.ScreenArray(t);for(let e=0;e({dilate:[t,!1]})))},\n", - " function _(e,t,s,r,i){r();const a=e(1);var n;const l=e(292),_=e(293),c=(0,a.__importStar)(e(18));class o extends l.MarkerView{async lazy_initialize(){await super.lazy_initialize();const{webgl:t}=this.renderer.plot_view.canvas_view;if(null==t?void 0:t.regl_wrapper.has_webgl){const{MarkerGL:t}=await Promise.resolve().then((()=>(0,a.__importStar)(e(426))));this.glcls=t}}_init_webgl(){const{webgl:e}=this.renderer.plot_view.canvas_view;if(null!=e){const{regl_wrapper:t}=e;if(t.has_webgl){const e=new Set(null!=this.base?this.base.marker:this.marker);if(1==e.size){const[s]=[...e],r=this.glcls;if(null==r?void 0:r.is_supported(s)){const{glglyph:e}=this;if(null==e||e.marker_type!=s)return void(this.glglyph=new r(t,this,s))}}}}delete this.glglyph}_set_visuals(){this._init_webgl()}_render(e,t,s){const{sx:r,sy:i,size:a,angle:n,marker:l}=null!=s?s:this;for(const s of t){const t=r[s],c=i[s],o=a.get(s),g=n.get(s),h=l.get(s);if(!isFinite(t+c+o+g)||null==h)continue;const w=o/2;e.beginPath(),e.translate(t,c),g&&e.rotate(g),_.marker_funcs[h](e,s,w,this.visuals),g&&e.rotate(-g),e.translate(-t,-c)}}draw_legend_for_index(e,{x0:t,x1:s,y0:r,y1:i},a){const n=a+1,l=this.marker.get(a),_=Object.assign(Object.assign({},this._get_legend_args({x0:t,x1:s,y0:r,y1:i},a)),{marker:new c.UniformScalar(l,n)});this._render(e,[a],_)}}s.ScatterView=o,o.__name__=\"ScatterView\";class g extends l.Marker{constructor(e){super(e)}}s.Scatter=g,n=g,g.__name__=\"Scatter\",n.prototype.default_view=o,n.define((()=>({marker:[c.MarkerSpec,{value:\"circle\"}]})))},\n", - " function _(e,t,s,n,i){n();const r=e(1);var a;const c=e(178),o=e(48),_=(0,r.__importStar)(e(185)),h=(0,r.__importStar)(e(18)),l=e(9),x=e(72);class d extends c.XYGlyphView{_render(e,t,s){const{sx:n,sy:i,size:r,angle:a}=null!=s?s:this;for(const s of t){const t=n[s],c=i[s],o=r.get(s),_=a.get(s);if(!isFinite(t+c+o+_))continue;const h=o/2;e.beginPath(),e.translate(t,c),_&&e.rotate(_),this._render_one(e,s,h,this.visuals),_&&e.rotate(-_),e.translate(-t,-c)}}_mask_data(){const{x_target:e,y_target:t}=this.renderer.plot_view.frame,s=e.widen(this.max_size).map((e=>this.renderer.xscale.invert(e))),n=t.widen(this.max_size).map((e=>this.renderer.yscale.invert(e)));return this.index.indices({x0:s.start,x1:s.end,y0:n.start,y1:n.end})}_hit_point(e){const{sx:t,sy:s}=e,{max_size:n}=this,{hit_dilation:i}=this.model,r=t-n*i,a=t+n*i,[c,o]=this.renderer.xscale.r_invert(r,a),_=s-n*i,h=s+n*i,[l,d]=this.renderer.yscale.r_invert(_,h),y=this.index.indices({x0:c,x1:o,y0:l,y1:d}),g=[];for(const e of y){const n=this.size.get(e)/2*i;Math.abs(this.sx[e]-t)<=n&&Math.abs(this.sy[e]-s)<=n&&g.push(e)}return new x.Selection({indices:g})}_hit_span(e){const{sx:t,sy:s}=e,n=this.bounds(),i=this.max_size/2;let r,a,c,o;if(\"h\"==e.direction){c=n.y0,o=n.y1;const e=t-i,s=t+i;[r,a]=this.renderer.xscale.r_invert(e,s)}else{r=n.x0,a=n.x1;const e=s-i,t=s+i;[c,o]=this.renderer.yscale.r_invert(e,t)}const _=[...this.index.indices({x0:r,x1:a,y0:c,y1:o})];return new x.Selection({indices:_})}_hit_rect(e){const{sx0:t,sx1:s,sy0:n,sy1:i}=e,[r,a]=this.renderer.xscale.r_invert(t,s),[c,o]=this.renderer.yscale.r_invert(n,i),_=[...this.index.indices({x0:r,x1:a,y0:c,y1:o})];return new x.Selection({indices:_})}_hit_poly(e){const{sx:t,sy:s}=e,n=(0,l.range)(0,this.sx.length),i=[];for(let e=0,r=n.length;e({size:[h.ScreenSizeSpec,{value:4}],angle:[h.AngleSpec,0],hit_dilation:[e,1]})))},\n", - " function _(l,o,n,t,i){t();const e=Math.sqrt(3),a=Math.sqrt(5),c=(a+1)/4,p=Math.sqrt((5-a)/8),r=(a-1)/4,h=Math.sqrt((5+a)/8);function u(l,o){l.rotate(Math.PI/4),s(l,o),l.rotate(-Math.PI/4)}function f(l,o){const n=o*e,t=n/3;l.moveTo(-n/2,-t),l.lineTo(0,0),l.lineTo(n/2,-t),l.lineTo(0,0),l.lineTo(0,o)}function s(l,o){l.moveTo(0,o),l.lineTo(0,-o),l.moveTo(-o,0),l.lineTo(o,0)}function T(l,o){l.moveTo(0,o),l.lineTo(o/1.5,0),l.lineTo(0,-o),l.lineTo(-o/1.5,0),l.closePath()}function y(l,o){const n=o*e,t=n/3;l.moveTo(-o,t),l.lineTo(o,t),l.lineTo(0,t-n),l.closePath()}function v(l,o,n,t){l.arc(0,0,n,0,2*Math.PI,!1),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}function d(l,o,n,t){T(l,n),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}function _(l,o,n,t){!function(l,o){l.beginPath(),l.arc(0,0,o/4,0,2*Math.PI,!1),l.closePath()}(l,n),t.line.set_vectorize(l,o),l.fillStyle=l.strokeStyle,l.fill()}function P(l,o,n,t){!function(l,o){const n=o/2,t=e*n;l.moveTo(o,0),l.lineTo(n,-t),l.lineTo(-n,-t),l.lineTo(-o,0),l.lineTo(-n,t),l.lineTo(n,t),l.closePath()}(l,n),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}function m(l,o,n,t){const i=2*n;l.rect(-n,-n,i,i),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}function q(l,o,n,t){!function(l,o){const n=Math.sqrt(5-2*a)*o;l.moveTo(0,-o),l.lineTo(n*r,n*h-o),l.lineTo(n*(1+r),n*h-o),l.lineTo(n*(1+r-c),n*(h+p)-o),l.lineTo(n*(1+2*r-c),n*(2*h+p)-o),l.lineTo(0,2*n*h-o),l.lineTo(-n*(1+2*r-c),n*(2*h+p)-o),l.lineTo(-n*(1+r-c),n*(h+p)-o),l.lineTo(-n*(1+r),n*h-o),l.lineTo(-n*r,n*h-o),l.closePath()}(l,n),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}function M(l,o,n,t){y(l,n),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}n.marker_funcs={asterisk:function(l,o,n,t){s(l,n),u(l,n),t.line.apply(l,o)},circle:v,circle_cross:function(l,o,n,t){l.arc(0,0,n,0,2*Math.PI,!1),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),s(l,n),l.stroke())},circle_dot:function(l,o,n,t){v(l,o,n,t),_(l,o,n,t)},circle_y:function(l,o,n,t){l.arc(0,0,n,0,2*Math.PI,!1),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),f(l,n),l.stroke())},circle_x:function(l,o,n,t){l.arc(0,0,n,0,2*Math.PI,!1),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),u(l,n),l.stroke())},cross:function(l,o,n,t){s(l,n),t.line.apply(l,o)},diamond:d,diamond_dot:function(l,o,n,t){d(l,o,n,t),_(l,o,n,t)},diamond_cross:function(l,o,n,t){T(l,n),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),l.moveTo(0,n),l.lineTo(0,-n),l.moveTo(-n/1.5,0),l.lineTo(n/1.5,0),l.stroke())},dot:_,hex:P,hex_dot:function(l,o,n,t){P(l,o,n,t),_(l,o,n,t)},inverted_triangle:function(l,o,n,t){l.rotate(Math.PI),y(l,n),l.rotate(-Math.PI),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)},plus:function(l,o,n,t){const i=3*n/8,e=[i,i,n,n,i,i,-i,-i,-n,-n,-i,-i],a=[n,i,i,-i,-i,-n,-n,-i,-i,i,i,n];l.beginPath();for(let o=0;o<12;o++)l.lineTo(e[o],a[o]);l.closePath(),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)},square:m,square_cross:function(l,o,n,t){const i=2*n;l.rect(-n,-n,i,i),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),s(l,n),l.stroke())},square_dot:function(l,o,n,t){m(l,o,n,t),_(l,o,n,t)},square_pin:function(l,o,n,t){const i=3*n/8;l.moveTo(-n,-n),l.quadraticCurveTo(0,-i,n,-n),l.quadraticCurveTo(i,0,n,n),l.quadraticCurveTo(0,i,-n,n),l.quadraticCurveTo(-i,0,-n,-n),l.closePath(),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)},square_x:function(l,o,n,t){const i=2*n;l.rect(-n,-n,i,i),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),l.moveTo(-n,n),l.lineTo(n,-n),l.moveTo(-n,-n),l.lineTo(n,n),l.stroke())},star:q,star_dot:function(l,o,n,t){q(l,o,n,t),_(l,o,n,t)},triangle:M,triangle_dot:function(l,o,n,t){M(l,o,n,t),_(l,o,n,t)},triangle_pin:function(l,o,n,t){const i=n*e,a=i/3,c=3*a/8;l.moveTo(-n,a),l.quadraticCurveTo(0,c,n,a),l.quadraticCurveTo(e*c/2,c/2,0,a-i),l.quadraticCurveTo(-e*c/2,c/2,-n,a),l.closePath(),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)},dash:function(l,o,n,t){!function(l,o){l.moveTo(-o,0),l.lineTo(o,0)}(l,n),t.line.apply(l,o)},x:function(l,o,n,t){u(l,n),t.line.apply(l,o)},y:function(l,o,n,t){f(l,n),t.line.apply(l,o)}}},\n", - " function _(e,t,s,i,n){i();const r=e(1);var o;const _=(0,r.__importStar)(e(185)),h=(0,r.__importStar)(e(18)),c=e(48),a=e(78),d=e(179),x=e(184),l=e(72);class y extends d.GlyphView{_project_data(){a.inplace.project_xy(this._x0,this._y0),a.inplace.project_xy(this._x1,this._y1)}_index_data(e){const{min:t,max:s}=Math,{_x0:i,_x1:n,_y0:r,_y1:o,data_size:_}=this;for(let h=0;h<_;h++){const _=i[h],c=n[h],a=r[h],d=o[h];e.add_rect(t(_,c),t(a,d),s(_,c),s(a,d))}}_render(e,t,s){if(this.visuals.line.doit){const{sx0:i,sy0:n,sx1:r,sy1:o}=null!=s?s:this;for(const s of t){const t=i[s],_=n[s],h=r[s],c=o[s];isFinite(t+_+h+c)&&(e.beginPath(),e.moveTo(t,_),e.lineTo(h,c),this.visuals.line.set_vectorize(e,s),e.stroke())}}}_hit_point(e){const{sx:t,sy:s}=e,i={x:t,y:s},[n,r]=this.renderer.xscale.r_invert(t-2,t+2),[o,h]=this.renderer.yscale.r_invert(s-2,s+2),c=this.index.indices({x0:n,y0:o,x1:r,y1:h}),a=[];for(const e of c){const t=Math.max(2,this.line_width.get(e)/2)**2,s={x:this.sx0[e],y:this.sy0[e]},n={x:this.sx1[e],y:this.sy1[e]};_.dist_to_segment_squared(i,s,n)({x0:[h.XCoordinateSpec,{field:\"x0\"}],y0:[h.YCoordinateSpec,{field:\"y0\"}],x1:[h.XCoordinateSpec,{field:\"x1\"}],y1:[h.YCoordinateSpec,{field:\"y1\"}]}))),o.mixins(c.LineVector)},\n", - " function _(t,e,s,i,n){i();const o=t(1);var _;const l=t(178),a=(0,o.__importStar)(t(48)),c=t(296);class r extends l.XYGlyphView{_set_data(){const{tension:t,closed:e}=this.model;[this._xt,this._yt]=(0,c.catmullrom_spline)(this._x,this._y,20,t,e)}_map_data(){const{x_scale:t,y_scale:e}=this.renderer.coordinates;this.sxt=t.v_compute(this._xt),this.syt=e.v_compute(this._yt)}_render(t,e,s){const{sxt:i,syt:n}=null!=s?s:this;let o=!0;t.beginPath();const _=i.length;for(let e=0;e<_;e++){const s=i[e],_=n[e];isFinite(s+_)?o?(t.moveTo(s,_),o=!1):t.lineTo(s,_):o=!0}this.visuals.line.set_value(t),t.stroke()}}s.SplineView=r,r.__name__=\"SplineView\";class h extends l.XYGlyph{constructor(t){super(t)}}s.Spline=h,_=h,h.__name__=\"Spline\",_.prototype.default_view=r,_.mixins(a.LineScalar),_.define((({Boolean:t,Number:e})=>({tension:[e,.5],closed:[t,!1]})))},\n", - " function _(n,t,e,o,s){o();const c=n(24),l=n(11);e.catmullrom_spline=function(n,t,e=10,o=.5,s=!1){(0,l.assert)(n.length==t.length);const r=n.length,f=s?r+1:r,w=(0,c.infer_type)(n,t),i=new w(f+2),u=new w(f+2);i.set(n,1),u.set(t,1),s?(i[0]=n[r-1],u[0]=t[r-1],i[f]=n[0],u[f]=t[0],i[f+1]=n[1],u[f+1]=t[1]):(i[0]=n[0],u[0]=t[0],i[f+1]=n[r-1],u[f+1]=t[r-1]);const g=new w(4*(e+1));for(let n=0,t=0;n<=e;n++){const o=n/e,s=o**2,c=o*s;g[t++]=2*c-3*s+1,g[t++]=-2*c+3*s,g[t++]=c-2*s+o,g[t++]=c-s}const h=new w((f-1)*(e+1)),_=new w((f-1)*(e+1));for(let n=1,t=0;n1&&(e.stroke(),o=!1)}o?(e.lineTo(t,r),e.lineTo(a,c)):(e.beginPath(),e.moveTo(s[n],i[n]),o=!0),l=n}e.lineTo(s[a-1],i[a-1]),e.stroke()}}draw_legend_for_index(e,t,n){(0,r.generic_line_scalar_legend)(this.visuals,e,t)}}n.StepView=f,f.__name__=\"StepView\";class u extends a.XYGlyph{constructor(e){super(e)}}n.Step=u,l=u,u.__name__=\"Step\",l.prototype.default_view=f,l.mixins(c.LineScalar),l.define((()=>({mode:[_.StepMode,\"before\"]})))},\n", - " function _(t,e,s,i,n){i();const o=t(1);var _;const h=t(178),l=t(48),r=(0,o.__importStar)(t(185)),a=(0,o.__importStar)(t(18)),c=t(121),x=t(11),u=t(72);class f extends h.XYGlyphView{_rotate_point(t,e,s,i,n){return[(t-s)*Math.cos(n)-(e-i)*Math.sin(n)+s,(t-s)*Math.sin(n)+(e-i)*Math.cos(n)+i]}_text_bounds(t,e,s,i){return[[t,t+s,t+s,t,t],[e,e,e-i,e-i,e]]}_render(t,e,s){const{sx:i,sy:n,x_offset:o,y_offset:_,angle:h,text:l}=null!=s?s:this;this._sys=[],this._sxs=[];for(const s of e){const e=this._sxs[s]=[],r=this._sys[s]=[],a=i[s],x=n[s],u=o.get(s),f=_.get(s),p=h.get(s),g=l.get(s);if(isFinite(a+x+u+f+p)&&null!=g&&this.visuals.text.doit){const i=`${g}`;t.save(),t.translate(a+u,x+f),t.rotate(p),this.visuals.text.set_vectorize(t,s);const n=this.visuals.text.font_value(s),{height:o}=(0,c.font_metrics)(n),_=this.text_line_height.get(s)*o;if(-1==i.indexOf(\"\\n\")){t.fillText(i,0,0);const s=a+u,n=x+f,o=t.measureText(i).width,[h,l]=this._text_bounds(s,n,o,_);e.push(h),r.push(l)}else{const n=i.split(\"\\n\"),o=_*n.length,h=this.text_baseline.get(s);let l;switch(h){case\"top\":l=0;break;case\"middle\":l=-o/2+_/2;break;case\"bottom\":l=-o+_;break;default:l=0,console.warn(`'${h}' baseline not supported with multi line text`)}for(const s of n){t.fillText(s,0,l);const i=a+u,n=l+x+f,o=t.measureText(s).width,[h,c]=this._text_bounds(i,n,o,_);e.push(h),r.push(c),l+=_}}t.restore()}}}_hit_point(t){const{sx:e,sy:s}=t,i=[];for(let t=0;t({text:[a.NullStringSpec,{field:\"text\"}],angle:[a.AngleSpec,0],x_offset:[a.NumberSpec,0],y_offset:[a.NumberSpec,0]})))},\n", - " function _(t,s,e,i,r){i();const h=t(1);var o;const a=t(277),n=t(24),_=(0,h.__importStar)(t(18));class c extends a.BoxView{scenterxy(t){return[this.sx[t],(this.stop[t]+this.sbottom[t])/2]}_lrtb(t){const s=this.width.get(t)/2,e=this._x[t],i=this._top[t],r=this._bottom[t];return[e-s,e+s,Math.max(i,r),Math.min(i,r)]}_map_data(){this.sx=this.renderer.xscale.v_compute(this._x),this.sw=this.sdist(this.renderer.xscale,this._x,this.width,\"center\"),this.stop=this.renderer.yscale.v_compute(this._top),this.sbottom=this.renderer.yscale.v_compute(this._bottom);const t=this.sx.length;this.sleft=new n.ScreenArray(t),this.sright=new n.ScreenArray(t);for(let s=0;s({x:[_.XCoordinateSpec,{field:\"x\"}],bottom:[_.YCoordinateSpec,{value:0}],width:[_.NumberSpec,{value:1}],top:[_.YCoordinateSpec,{field:\"top\"}]})))},\n", - " function _(e,s,t,i,n){i();const r=e(1);var a;const c=e(178),l=e(184),d=e(48),o=e(24),h=e(20),_=(0,r.__importStar)(e(18)),u=e(10),g=e(72);class p extends c.XYGlyphView{_map_data(){\"data\"==this.model.properties.radius.units?this.sradius=this.sdist(this.renderer.xscale,this._x,this.radius):this.sradius=(0,o.to_screen)(this.radius)}_render(e,s,t){const{sx:i,sy:n,sradius:r,start_angle:a,end_angle:c}=null!=t?t:this,l=\"anticlock\"==this.model.direction;for(const t of s){const s=i[t],d=n[t],o=r[t],h=a.get(t),_=c.get(t);isFinite(s+d+o+h+_)&&(e.beginPath(),e.arc(s,d,o,h,_,l),e.lineTo(s,d),e.closePath(),this.visuals.fill.apply(e,t),this.visuals.hatch.apply(e,t),this.visuals.line.apply(e,t))}}_hit_point(e){let s,t,i,n,r,a,c,l,d;const{sx:o,sy:h}=e,_=this.renderer.xscale.invert(o),p=this.renderer.yscale.invert(h),x=2*this.max_radius;\"data\"===this.model.properties.radius.units?(a=_-x,c=_+x,l=p-x,d=p+x):(t=o-x,i=o+x,[a,c]=this.renderer.xscale.r_invert(t,i),n=h-x,r=h+x,[l,d]=this.renderer.yscale.r_invert(n,r));const y=[];for(const e of this.index.indices({x0:a,x1:c,y0:l,y1:d})){const a=this.sradius[e]**2;[t,i]=this.renderer.xscale.r_compute(_,this._x[e]),[n,r]=this.renderer.yscale.r_compute(p,this._y[e]),s=(t-i)**2+(n-r)**2,s<=a&&y.push(e)}const f=\"anticlock\"==this.model.direction,m=[];for(const e of y){const s=Math.atan2(h-this.sy[e],o-this.sx[e]);(0,u.angle_between)(-s,-this.start_angle.get(e),-this.end_angle.get(e),f)&&m.push(e)}return new g.Selection({indices:m})}draw_legend_for_index(e,s,t){(0,l.generic_area_vector_legend)(this.visuals,e,s,t)}scenterxy(e){const s=this.sradius[e]/2,t=(this.start_angle.get(e)+this.end_angle.get(e))/2;return[this.sx[e]+s*Math.cos(t),this.sy[e]+s*Math.sin(t)]}}t.WedgeView=p,p.__name__=\"WedgeView\";class x extends c.XYGlyph{constructor(e){super(e)}}t.Wedge=x,a=x,x.__name__=\"Wedge\",a.prototype.default_view=p,a.mixins([d.LineVector,d.FillVector,d.HatchVector]),a.define((({})=>({direction:[h.Direction,\"anticlock\"],radius:[_.DistanceSpec,{field:\"radius\"}],start_angle:[_.AngleSpec,{field:\"start_angle\"}],end_angle:[_.AngleSpec,{field:\"end_angle\"}]})))},\n", - " function _(t,_,r,o,a){o();const e=t(1);(0,e.__exportStar)(t(302),r),(0,e.__exportStar)(t(303),r),(0,e.__exportStar)(t(304),r)},\n", - " function _(e,t,d,n,s){n();const o=e(53),r=e(12),_=e(9),i=e(72);class c extends o.Model{constructor(e){super(e)}_hit_test(e,t,d){if(!t.model.visible)return null;const n=d.glyph.hit_test(e);return null==n?null:d.model.view.convert_selection_from_subset(n)}}d.GraphHitTestPolicy=c,c.__name__=\"GraphHitTestPolicy\";class a extends c{constructor(e){super(e)}hit_test(e,t){return this._hit_test(e,t,t.edge_view)}do_selection(e,t,d,n){if(null==e)return!1;const s=t.edge_renderer.data_source.selected;return s.update(e,d,n),t.edge_renderer.data_source._select.emit(),!s.is_empty()}do_inspection(e,t,d,n,s){if(null==e)return!1;const{edge_renderer:o}=d.model,r=o.get_selection_manager().get_or_create_inspector(d.edge_view.model);return r.update(e,n,s),d.edge_view.model.data_source.setv({inspected:r},{silent:!0}),d.edge_view.model.data_source.inspect.emit([d.edge_view.model,{geometry:t}]),!r.is_empty()}}d.EdgesOnly=a,a.__name__=\"EdgesOnly\";class l extends c{constructor(e){super(e)}hit_test(e,t){return this._hit_test(e,t,t.node_view)}do_selection(e,t,d,n){if(null==e)return!1;const s=t.node_renderer.data_source.selected;return s.update(e,d,n),t.node_renderer.data_source._select.emit(),!s.is_empty()}do_inspection(e,t,d,n,s){if(null==e)return!1;const{node_renderer:o}=d.model,r=o.get_selection_manager().get_or_create_inspector(d.node_view.model);return r.update(e,n,s),d.node_view.model.data_source.setv({inspected:r},{silent:!0}),d.node_view.model.data_source.inspect.emit([d.node_view.model,{geometry:t}]),!r.is_empty()}}d.NodesOnly=l,l.__name__=\"NodesOnly\";class u extends c{constructor(e){super(e)}hit_test(e,t){return this._hit_test(e,t,t.node_view)}get_linked_edges(e,t,d){let n=[];\"selection\"==d?n=e.selected.indices.map((t=>e.data.index[t])):\"inspection\"==d&&(n=e.inspected.indices.map((t=>e.data.index[t])));const s=[];for(let e=0;e(0,r.indexOf)(e.data.index,t)));return new i.Selection({indices:o})}do_selection(e,t,d,n){if(null==e)return!1;const s=t.edge_renderer.data_source.selected;s.update(e,d,n);const o=t.node_renderer.data_source.selected,r=this.get_linked_nodes(t.node_renderer.data_source,t.edge_renderer.data_source,\"selection\");return o.update(r,d,n),t.edge_renderer.data_source._select.emit(),!s.is_empty()}do_inspection(e,t,d,n,s){if(null==e)return!1;const o=d.edge_view.model.data_source.selection_manager.get_or_create_inspector(d.edge_view.model);o.update(e,n,s),d.edge_view.model.data_source.setv({inspected:o},{silent:!0});const r=d.node_view.model.data_source.selection_manager.get_or_create_inspector(d.node_view.model),_=this.get_linked_nodes(d.node_view.model.data_source,d.edge_view.model.data_source,\"inspection\");return r.update(_,n,s),d.node_view.model.data_source.setv({inspected:r},{silent:!0}),d.edge_view.model.data_source.inspect.emit([d.edge_view.model,{geometry:t}]),!o.is_empty()}}d.EdgesAndLinkedNodes=m,m.__name__=\"EdgesAndLinkedNodes\"},\n", - " function _(e,o,t,r,n){var s;r();const a=e(53),d=e(260);class _ extends a.Model{constructor(e){super(e)}get node_coordinates(){return new u({layout:this})}get edge_coordinates(){return new i({layout:this})}}t.LayoutProvider=_,_.__name__=\"LayoutProvider\";class c extends d.CoordinateTransform{constructor(e){super(e)}}t.GraphCoordinates=c,s=c,c.__name__=\"GraphCoordinates\",s.define((({Ref:e})=>({layout:[e(_)]})));class u extends c{constructor(e){super(e)}_v_compute(e){const[o,t]=this.layout.get_node_coordinates(e);return{x:o,y:t}}}t.NodeCoordinates=u,u.__name__=\"NodeCoordinates\";class i extends c{constructor(e){super(e)}_v_compute(e){const[o,t]=this.layout.get_edge_coordinates(e);return{x:o,y:t}}}t.EdgeCoordinates=i,i.__name__=\"EdgeCoordinates\"},\n", - " function _(t,a,l,e,n){var o;e();const r=t(303);class u extends r.LayoutProvider{constructor(t){super(t)}get_node_coordinates(t){var a;const l=null!==(a=t.data.index)&&void 0!==a?a:[],e=l.length,n=new Float64Array(e),o=new Float64Array(e);for(let t=0;t({graph_layout:[l(a(t,t)),{}]})))},\n", - " function _(i,d,n,r,G){r(),G(\"Grid\",i(306).Grid)},\n", - " function _(i,e,n,s,t){s();const r=i(1);var o;const d=i(127),_=i(129),a=i(130),l=(0,r.__importStar)(i(48)),h=i(8);class c extends _.GuideRendererView{_render(){const i=this.layer.ctx;i.save(),this._draw_regions(i),this._draw_minor_grids(i),this._draw_grids(i),i.restore()}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render()))}_draw_regions(i){if(!this.visuals.band_fill.doit&&!this.visuals.band_hatch.doit)return;const[e,n]=this.grid_coords(\"major\",!1);for(let s=0;sn[1]&&(t=n[1]);else{[s,t]=n;for(const i of this.plot_view.axis_views)i.dimension==this.model.dimension&&i.model.x_range_name==this.model.x_range_name&&i.model.y_range_name==this.model.y_range_name&&([s,t]=i.computed_bounds)}return[s,t]}grid_coords(i,e=!0){const n=this.model.dimension,s=(n+1)%2,[t,r]=this.ranges();let[o,d]=this.computed_bounds();[o,d]=[Math.min(o,d),Math.max(o,d)];const _=[[],[]],a=this.model.get_ticker();if(null==a)return _;const l=a.get_ticks(o,d,t,r.min)[i],h=t.min,c=t.max,u=r.min,m=r.max;e||(l[0]!=h&&l.splice(0,0,h),l[l.length-1]!=c&&l.push(c));for(let i=0;i({bounds:[r(t(i,i),e),\"auto\"],dimension:[n(0,1),0],axis:[o(s(d.Axis)),null],ticker:[o(s(a.Ticker)),null]}))),o.override({level:\"underlay\",band_fill_color:null,band_fill_alpha:0,grid_line_color:\"#e5e5e5\",minor_grid_line_color:null})},\n", - " function _(o,a,x,B,e){B(),e(\"Box\",o(308).Box),e(\"Column\",o(310).Column),e(\"GridBox\",o(311).GridBox),e(\"HTMLBox\",o(312).HTMLBox),e(\"LayoutDOM\",o(309).LayoutDOM),e(\"Panel\",o(313).Panel),e(\"Row\",o(314).Row),e(\"Spacer\",o(315).Spacer),e(\"Tabs\",o(316).Tabs),e(\"WidgetBox\",o(319).WidgetBox)},\n", - " function _(e,n,s,t,c){var i;t();const o=e(309);class r extends o.LayoutDOMView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.children.change,(()=>this.rebuild()))}get child_models(){return this.model.children}}s.BoxView=r,r.__name__=\"BoxView\";class a extends o.LayoutDOM{constructor(e){super(e)}}s.Box=a,i=a,a.__name__=\"Box\",i.define((({Number:e,Array:n,Ref:s})=>({children:[n(s(o.LayoutDOM)),[]],spacing:[e,0]})))},\n", - " function _(t,i,e,s,o){var l;s();const n=t(53),h=t(20),a=t(43),r=t(19),_=t(8),c=t(22),u=t(121),d=t(113),p=t(226),m=t(207),g=t(44),w=t(235);class f extends p.DOMView{constructor(){super(...arguments),this._offset_parent=null,this._viewport={}}get is_layout_root(){return this.is_root||!(this.parent instanceof f)}get base_font_size(){const t=getComputedStyle(this.el).fontSize,i=(0,u.parse_css_font_size)(t);if(null!=i){const{value:t,unit:e}=i;if(\"px\"==e)return t}return null}initialize(){super.initialize(),this.el.style.position=this.is_layout_root?\"relative\":\"absolute\",this._child_views=new Map}async lazy_initialize(){await super.lazy_initialize(),await this.build_child_views()}remove(){for(const t of this.child_views)t.remove();this._child_views.clear(),super.remove()}connect_signals(){super.connect_signals(),this.is_layout_root&&(this._on_resize=()=>this.resize_layout(),window.addEventListener(\"resize\",this._on_resize),this._parent_observer=setInterval((()=>{const t=this.el.offsetParent;this._offset_parent!=t&&(this._offset_parent=t,null!=t&&(this.compute_viewport(),this.invalidate_layout()))}),250));const t=this.model.properties;this.on_change([t.width,t.height,t.min_width,t.min_height,t.max_width,t.max_height,t.margin,t.width_policy,t.height_policy,t.sizing_mode,t.aspect_ratio,t.visible],(()=>this.invalidate_layout())),this.on_change([t.background,t.css_classes],(()=>this.invalidate_render()))}disconnect_signals(){null!=this._parent_observer&&clearTimeout(this._parent_observer),null!=this._on_resize&&window.removeEventListener(\"resize\",this._on_resize),super.disconnect_signals()}css_classes(){return super.css_classes().concat(this.model.css_classes)}get child_views(){return this.child_models.map((t=>this._child_views.get(t)))}async build_child_views(){await(0,d.build_views)(this._child_views,this.child_models,{parent:this})}render(){super.render(),(0,a.empty)(this.el);const{background:t}=this.model;this.el.style.backgroundColor=null!=t?(0,c.color2css)(t):\"\",(0,a.classes)(this.el).clear().add(...this.css_classes());for(const t of this.child_views)this.el.appendChild(t.el),t.render()}update_layout(){for(const t of this.child_views)t.update_layout();this._update_layout()}update_position(){this.el.style.display=this.model.visible?\"block\":\"none\";const t=this.is_layout_root?this.layout.sizing.margin:void 0;(0,a.position)(this.el,this.layout.bbox,t);for(const t of this.child_views)t.update_position()}after_layout(){for(const t of this.child_views)t.after_layout();this._has_finished=!0}compute_viewport(){this._viewport=this._viewport_size()}renderTo(t){t.appendChild(this.el),this._offset_parent=this.el.offsetParent,this.compute_viewport(),this.build(),this.notify_finished()}build(){if(!this.is_layout_root)throw new Error(`${this.toString()} is not a root layout`);return this.render(),this.update_layout(),this.compute_layout(),this}async rebuild(){await this.build_child_views(),this.invalidate_render()}compute_layout(){const t=Date.now();this.layout.compute(this._viewport),this.update_position(),this.after_layout(),r.logger.debug(`layout computed in ${Date.now()-t} ms`)}resize_layout(){this.root.compute_viewport(),this.root.compute_layout()}invalidate_layout(){this.root.update_layout(),this.root.compute_layout()}invalidate_render(){this.render(),this.invalidate_layout()}has_finished(){if(!super.has_finished())return!1;for(const t of this.child_views)if(!t.has_finished())return!1;return!0}_width_policy(){return null!=this.model.width?\"fixed\":\"fit\"}_height_policy(){return null!=this.model.height?\"fixed\":\"fit\"}box_sizing(){let{width_policy:t,height_policy:i,aspect_ratio:e}=this.model;\"auto\"==t&&(t=this._width_policy()),\"auto\"==i&&(i=this._height_policy());const{sizing_mode:s}=this.model;if(null!=s)if(\"fixed\"==s)t=i=\"fixed\";else if(\"stretch_both\"==s)t=i=\"max\";else if(\"stretch_width\"==s)t=\"max\";else if(\"stretch_height\"==s)i=\"max\";else switch(null==e&&(e=\"auto\"),s){case\"scale_width\":t=\"max\",i=\"min\";break;case\"scale_height\":t=\"min\",i=\"max\";break;case\"scale_both\":t=\"max\",i=\"max\"}const o={width_policy:t,height_policy:i},{min_width:l,min_height:n}=this.model;null!=l&&(o.min_width=l),null!=n&&(o.min_height=n);const{width:h,height:a}=this.model;null!=h&&(o.width=h),null!=a&&(o.height=a);const{max_width:r,max_height:c}=this.model;null!=r&&(o.max_width=r),null!=c&&(o.max_height=c),\"auto\"==e&&null!=h&&null!=a?o.aspect=h/a:(0,_.isNumber)(e)&&(o.aspect=e);const{margin:u}=this.model;if(null!=u)if((0,_.isNumber)(u))o.margin={top:u,right:u,bottom:u,left:u};else if(2==u.length){const[t,i]=u;o.margin={top:t,right:i,bottom:t,left:i}}else{const[t,i,e,s]=u;o.margin={top:t,right:i,bottom:e,left:s}}o.visible=this.model.visible;const{align:d}=this.model;return(0,_.isArray)(d)?[o.halign,o.valign]=d:o.halign=o.valign=d,o}_viewport_size(){return(0,a.undisplayed)(this.el,(()=>{let t=this.el;for(;t=t.parentElement;){if(t.classList.contains(g.root))continue;if(t==document.body){const{margin:{left:t,right:i,top:e,bottom:s}}=(0,a.extents)(document.body);return{width:Math.ceil(document.documentElement.clientWidth-t-i),height:Math.ceil(document.documentElement.clientHeight-e-s)}}const{padding:{left:i,right:e,top:s,bottom:o}}=(0,a.extents)(t),{width:l,height:n}=t.getBoundingClientRect(),h=Math.ceil(l-i-e),r=Math.ceil(n-s-o);if(h>0||r>0)return{width:h>0?h:void 0,height:r>0?r:void 0}}return{}}))}export(t,i=!0){const e=\"png\"==t?\"canvas\":\"svg\",s=new w.CanvasLayer(e,i),{width:o,height:l}=this.layout.bbox;s.resize(o,l);for(const e of this.child_views){const o=e.export(t,i),{x:l,y:n}=e.layout.bbox;s.ctx.drawImage(o.canvas,l,n)}return s}serializable_state(){return Object.assign(Object.assign({},super.serializable_state()),{bbox:this.layout.bbox.box,children:this.child_views.map((t=>t.serializable_state()))})}}e.LayoutDOMView=f,f.__name__=\"LayoutDOMView\";class y extends n.Model{constructor(t){super(t)}}e.LayoutDOM=y,l=y,y.__name__=\"LayoutDOM\",l.define((t=>{const{Boolean:i,Number:e,String:s,Auto:o,Color:l,Array:n,Tuple:a,Or:r,Null:_,Nullable:c}=t,u=a(e,e),d=a(e,e,e,e);return{width:[c(e),null],height:[c(e),null],min_width:[c(e),null],min_height:[c(e),null],max_width:[c(e),null],max_height:[c(e),null],margin:[c(r(e,u,d)),[0,0,0,0]],width_policy:[r(m.SizingPolicy,o),\"auto\"],height_policy:[r(m.SizingPolicy,o),\"auto\"],aspect_ratio:[r(e,o,_),null],sizing_mode:[c(h.SizingMode),null],visible:[i,!0],disabled:[i,!1],align:[r(h.Align,a(h.Align,h.Align)),\"start\"],background:[c(l),null],css_classes:[n(s),[]]}}))},\n", - " function _(o,s,t,i,e){var n;i();const a=o(308),l=o(209);class u extends a.BoxView{_update_layout(){const o=this.child_views.map((o=>o.layout));this.layout=new l.Column(o),this.layout.rows=this.model.rows,this.layout.spacing=[this.model.spacing,0],this.layout.set_sizing(this.box_sizing())}}t.ColumnView=u,u.__name__=\"ColumnView\";class _ extends a.Box{constructor(o){super(o)}}t.Column=_,n=_,_.__name__=\"Column\",n.prototype.default_view=u,n.define((({Any:o})=>({rows:[o,\"auto\"]})))},\n", - " function _(s,o,t,i,e){var n;i();const l=s(309),a=s(209);class r extends l.LayoutDOMView{connect_signals(){super.connect_signals();const{children:s,rows:o,cols:t,spacing:i}=this.model.properties;this.on_change([s,o,t,i],(()=>this.rebuild()))}get child_models(){return this.model.children.map((([s])=>s))}_update_layout(){this.layout=new a.Grid,this.layout.rows=this.model.rows,this.layout.cols=this.model.cols,this.layout.spacing=this.model.spacing;for(const[s,o,t,i,e]of this.model.children){const n=this._child_views.get(s);this.layout.items.push({layout:n.layout,row:o,col:t,row_span:i,col_span:e})}this.layout.set_sizing(this.box_sizing())}}t.GridBoxView=r,r.__name__=\"GridBoxView\";class c extends l.LayoutDOM{constructor(s){super(s)}}t.GridBox=c,n=c,c.__name__=\"GridBox\",n.prototype.default_view=r,n.define((({Any:s,Int:o,Number:t,Tuple:i,Array:e,Ref:n,Or:a,Opt:r})=>({children:[e(i(n(l.LayoutDOM),o,o,r(o),r(o))),[]],rows:[s,\"auto\"],cols:[s,\"auto\"],spacing:[a(t,i(t,t)),0]})))},\n", - " function _(t,e,o,s,n){s();const _=t(309),i=t(207);class a extends _.LayoutDOMView{get child_models(){return[]}_update_layout(){this.layout=new i.ContentBox(this.el),this.layout.set_sizing(this.box_sizing())}}o.HTMLBoxView=a,a.__name__=\"HTMLBoxView\";class u extends _.LayoutDOM{constructor(t){super(t)}}o.HTMLBox=u,u.__name__=\"HTMLBox\"},\n", - " function _(e,n,l,a,o){var t;a();const s=e(53),c=e(309);class d extends s.Model{constructor(e){super(e)}}l.Panel=d,t=d,d.__name__=\"Panel\",t.define((({Boolean:e,String:n,Ref:l})=>({title:[n,\"\"],child:[l(c.LayoutDOM)],closable:[e,!1],disabled:[e,!1]})))},\n", - " function _(o,s,t,i,e){var a;i();const n=o(308),l=o(209);class _ extends n.BoxView{_update_layout(){const o=this.child_views.map((o=>o.layout));this.layout=new l.Row(o),this.layout.cols=this.model.cols,this.layout.spacing=[0,this.model.spacing],this.layout.set_sizing(this.box_sizing())}}t.RowView=_,_.__name__=\"RowView\";class c extends n.Box{constructor(o){super(o)}}t.Row=c,a=c,c.__name__=\"Row\",a.prototype.default_view=_,a.define((({Any:o})=>({cols:[o,\"auto\"]})))},\n", - " function _(e,t,a,s,_){var o;s();const i=e(309),n=e(207);class u extends i.LayoutDOMView{get child_models(){return[]}_update_layout(){this.layout=new n.LayoutItem,this.layout.set_sizing(this.box_sizing())}}a.SpacerView=u,u.__name__=\"SpacerView\";class c extends i.LayoutDOM{constructor(e){super(e)}}a.Spacer=c,o=c,c.__name__=\"Spacer\",o.prototype.default_view=u},\n", - " function _(e,t,s,i,l){i();const h=e(1);var a;const o=e(207),d=e(43),r=e(9),c=e(10),n=e(20),_=e(309),p=e(313),b=(0,h.__importStar)(e(317)),m=b,u=(0,h.__importStar)(e(318)),g=u,v=(0,h.__importStar)(e(229)),w=v;class f extends _.LayoutDOMView{constructor(){super(...arguments),this._scroll_index=0}connect_signals(){super.connect_signals(),this.connect(this.model.properties.tabs.change,(()=>this.rebuild())),this.connect(this.model.properties.active.change,(()=>this.on_active_change()))}styles(){return[...super.styles(),u.default,v.default,b.default]}get child_models(){return this.model.tabs.map((e=>e.child))}_update_layout(){const e=this.model.tabs_location,t=\"above\"==e||\"below\"==e,{scroll_el:s,headers_el:i}=this;this.header=new class extends o.ContentBox{_measure(e){const l=(0,d.size)(s),h=(0,d.children)(i).slice(0,3).map((e=>(0,d.size)(e))),{width:a,height:o}=super._measure(e);if(t){const t=l.width+(0,r.sum)(h.map((e=>e.width)));return{width:e.width!=1/0?e.width:t,height:o}}{const t=l.height+(0,r.sum)(h.map((e=>e.height)));return{width:a,height:e.height!=1/0?e.height:t}}}}(this.header_el),t?this.header.set_sizing({width_policy:\"fit\",height_policy:\"fixed\"}):this.header.set_sizing({width_policy:\"fixed\",height_policy:\"fit\"});let l=1,h=1;switch(e){case\"above\":l-=1;break;case\"below\":l+=1;break;case\"left\":h-=1;break;case\"right\":h+=1}const a={layout:this.header,row:l,col:h},c=this.child_views.map((e=>({layout:e.layout,row:1,col:1})));this.layout=new o.Grid([a,...c]),this.layout.set_sizing(this.box_sizing())}update_position(){super.update_position(),this.header_el.style.position=\"absolute\",(0,d.position)(this.header_el,this.header.bbox);const e=this.model.tabs_location,t=\"above\"==e||\"below\"==e,s=(0,d.size)(this.scroll_el),i=(0,d.scroll_size)(this.headers_el);if(t){const{width:e}=this.header.bbox;i.width>e?(this.wrapper_el.style.maxWidth=e-s.width+\"px\",(0,d.display)(this.scroll_el),this.do_scroll(this.model.active)):(this.wrapper_el.style.maxWidth=\"\",(0,d.undisplay)(this.scroll_el))}else{const{height:e}=this.header.bbox;i.height>e?(this.wrapper_el.style.maxHeight=e-s.height+\"px\",(0,d.display)(this.scroll_el),this.do_scroll(this.model.active)):(this.wrapper_el.style.maxHeight=\"\",(0,d.undisplay)(this.scroll_el))}const{child_views:l}=this;for(const e of l)(0,d.hide)(e.el);const h=l[this.model.active];null!=h&&(0,d.show)(h.el)}render(){super.render();const{active:e}=this.model,t=this.model.tabs.map(((t,s)=>{const i=(0,d.div)({class:[m.tab,s==e?m.active:null]},t.title);if(i.addEventListener(\"click\",(e=>{this.model.disabled||e.target==e.currentTarget&&this.change_active(s)})),t.closable){const e=(0,d.div)({class:m.close});e.addEventListener(\"click\",(e=>{if(e.target==e.currentTarget){this.model.tabs=(0,r.remove_at)(this.model.tabs,s);const e=this.model.tabs.length;this.model.active>e-1&&(this.model.active=e-1)}})),i.appendChild(e)}return(this.model.disabled||t.disabled)&&i.classList.add(m.disabled),i}));this.headers_el=(0,d.div)({class:[m.headers]},t),this.wrapper_el=(0,d.div)({class:m.headers_wrapper},this.headers_el),this.left_el=(0,d.div)({class:[g.btn,g.btn_default],disabled:\"\"},(0,d.div)({class:[w.caret,m.left]})),this.right_el=(0,d.div)({class:[g.btn,g.btn_default]},(0,d.div)({class:[w.caret,m.right]})),this.left_el.addEventListener(\"click\",(()=>this.do_scroll(\"left\"))),this.right_el.addEventListener(\"click\",(()=>this.do_scroll(\"right\"))),this.scroll_el=(0,d.div)({class:g.btn_group},this.left_el,this.right_el);const s=this.model.tabs_location;this.header_el=(0,d.div)({class:[m.tabs_header,m[s]]},this.scroll_el,this.wrapper_el),this.el.appendChild(this.header_el)}do_scroll(e){const t=this.model.tabs.length;\"left\"==e?this._scroll_index-=1:\"right\"==e?this._scroll_index+=1:this._scroll_index=e,this._scroll_index=(0,c.clamp)(this._scroll_index,0,t-1),0==this._scroll_index?this.left_el.setAttribute(\"disabled\",\"\"):this.left_el.removeAttribute(\"disabled\"),this._scroll_index==t-1?this.right_el.setAttribute(\"disabled\",\"\"):this.right_el.removeAttribute(\"disabled\");const s=(0,d.children)(this.headers_el).slice(0,this._scroll_index).map((e=>e.getBoundingClientRect())),i=this.model.tabs_location;if(\"above\"==i||\"below\"==i){const e=-(0,r.sum)(s.map((e=>e.width)));this.headers_el.style.left=`${e}px`}else{const e=-(0,r.sum)(s.map((e=>e.height)));this.headers_el.style.top=`${e}px`}}change_active(e){e!=this.model.active&&(this.model.active=e)}on_active_change(){const e=this.model.active,t=(0,d.children)(this.headers_el);for(const e of t)e.classList.remove(m.active);t[e].classList.add(m.active);const{child_views:s}=this;for(const e of s)(0,d.hide)(e.el);(0,d.show)(s[e].el)}}s.TabsView=f,f.__name__=\"TabsView\";class x extends _.LayoutDOM{constructor(e){super(e)}}s.Tabs=x,a=x,x.__name__=\"Tabs\",a.prototype.default_view=f,a.define((({Int:e,Array:t,Ref:s})=>({tabs:[t(s(p.Panel)),[]],tabs_location:[n.Location,\"above\"],active:[e,0]})))},\n", - " function _(e,r,b,o,t){o(),b.root=\"bk-root\",b.tabs_header=\"bk-tabs-header\",b.btn_group=\"bk-btn-group\",b.btn=\"bk-btn\",b.headers_wrapper=\"bk-headers-wrapper\",b.above=\"bk-above\",b.right=\"bk-right\",b.below=\"bk-below\",b.left=\"bk-left\",b.headers=\"bk-headers\",b.tab=\"bk-tab\",b.active=\"bk-active\",b.close=\"bk-close\",b.disabled=\"bk-disabled\",b.default='.bk-root .bk-tabs-header{display:flex;flex-wrap:nowrap;align-items:center;overflow:hidden;user-select:none;-ms-user-select:none;-moz-user-select:none;-webkit-user-select:none;}.bk-root .bk-tabs-header .bk-btn-group{height:auto;margin-right:5px;}.bk-root .bk-tabs-header .bk-btn-group > .bk-btn{flex-grow:0;height:auto;padding:4px 4px;}.bk-root .bk-tabs-header .bk-headers-wrapper{flex-grow:1;overflow:hidden;color:#666666;}.bk-root .bk-tabs-header.bk-above .bk-headers-wrapper{border-bottom:1px solid #e6e6e6;}.bk-root .bk-tabs-header.bk-right .bk-headers-wrapper{border-left:1px solid #e6e6e6;}.bk-root .bk-tabs-header.bk-below .bk-headers-wrapper{border-top:1px solid #e6e6e6;}.bk-root .bk-tabs-header.bk-left .bk-headers-wrapper{border-right:1px solid #e6e6e6;}.bk-root .bk-tabs-header.bk-above,.bk-root .bk-tabs-header.bk-below{flex-direction:row;}.bk-root .bk-tabs-header.bk-above .bk-headers,.bk-root .bk-tabs-header.bk-below .bk-headers{flex-direction:row;}.bk-root .bk-tabs-header.bk-left,.bk-root .bk-tabs-header.bk-right{flex-direction:column;}.bk-root .bk-tabs-header.bk-left .bk-headers,.bk-root .bk-tabs-header.bk-right .bk-headers{flex-direction:column;}.bk-root .bk-tabs-header .bk-headers{position:relative;display:flex;flex-wrap:nowrap;align-items:center;}.bk-root .bk-tabs-header .bk-tab{padding:4px 8px;border:solid transparent;white-space:nowrap;cursor:pointer;}.bk-root .bk-tabs-header .bk-tab:hover{background-color:#f2f2f2;}.bk-root .bk-tabs-header .bk-tab.bk-active{color:#4d4d4d;background-color:white;border-color:#e6e6e6;}.bk-root .bk-tabs-header .bk-tab .bk-close{margin-left:10px;}.bk-root .bk-tabs-header .bk-tab.bk-disabled{cursor:not-allowed;pointer-events:none;opacity:0.65;}.bk-root .bk-tabs-header.bk-above .bk-tab{border-width:3px 1px 0px 1px;border-radius:4px 4px 0 0;}.bk-root .bk-tabs-header.bk-right .bk-tab{border-width:1px 3px 1px 0px;border-radius:0 4px 4px 0;}.bk-root .bk-tabs-header.bk-below .bk-tab{border-width:0px 1px 3px 1px;border-radius:0 0 4px 4px;}.bk-root .bk-tabs-header.bk-left .bk-tab{border-width:1px 0px 1px 3px;border-radius:4px 0 0 4px;}.bk-root .bk-close{display:inline-block;width:10px;height:10px;vertical-align:middle;background-image:url(\\'data:image/svg+xml;utf8, \\');}.bk-root .bk-close:hover{background-image:url(\\'data:image/svg+xml;utf8, \\');}'},\n", - " function _(o,b,r,t,e){t(),r.root=\"bk-root\",r.btn=\"bk-btn\",r.active=\"bk-active\",r.btn_default=\"bk-btn-default\",r.btn_primary=\"bk-btn-primary\",r.btn_success=\"bk-btn-success\",r.btn_warning=\"bk-btn-warning\",r.btn_danger=\"bk-btn-danger\",r.btn_light=\"bk-btn-light\",r.btn_group=\"bk-btn-group\",r.vertical=\"bk-vertical\",r.horizontal=\"bk-horizontal\",r.dropdown_toggle=\"bk-dropdown-toggle\",r.default=\".bk-root .bk-btn{height:100%;display:inline-block;text-align:center;vertical-align:middle;white-space:nowrap;cursor:pointer;padding:6px 12px;font-size:12px;border:1px solid transparent;border-radius:4px;outline:0;user-select:none;-ms-user-select:none;-moz-user-select:none;-webkit-user-select:none;}.bk-root .bk-btn:hover,.bk-root .bk-btn:focus{text-decoration:none;}.bk-root .bk-btn:active,.bk-root .bk-btn.bk-active{background-image:none;box-shadow:inset 0 3px 5px rgba(0, 0, 0, 0.125);}.bk-root .bk-btn[disabled]{cursor:not-allowed;pointer-events:none;opacity:0.65;box-shadow:none;}.bk-root .bk-btn-default{color:#333;background-color:#fff;border-color:#ccc;}.bk-root .bk-btn-default:hover{background-color:#f5f5f5;border-color:#b8b8b8;}.bk-root .bk-btn-default.bk-active{background-color:#ebebeb;border-color:#adadad;}.bk-root .bk-btn-default[disabled],.bk-root .bk-btn-default[disabled]:hover,.bk-root .bk-btn-default[disabled]:focus,.bk-root .bk-btn-default[disabled]:active,.bk-root .bk-btn-default[disabled].bk-active{background-color:#e6e6e6;border-color:#ccc;}.bk-root .bk-btn-primary{color:#fff;background-color:#428bca;border-color:#357ebd;}.bk-root .bk-btn-primary:hover{background-color:#3681c1;border-color:#2c699e;}.bk-root .bk-btn-primary.bk-active{background-color:#3276b1;border-color:#285e8e;}.bk-root .bk-btn-primary[disabled],.bk-root .bk-btn-primary[disabled]:hover,.bk-root .bk-btn-primary[disabled]:focus,.bk-root .bk-btn-primary[disabled]:active,.bk-root .bk-btn-primary[disabled].bk-active{background-color:#506f89;border-color:#357ebd;}.bk-root .bk-btn-success{color:#fff;background-color:#5cb85c;border-color:#4cae4c;}.bk-root .bk-btn-success:hover{background-color:#4eb24e;border-color:#409240;}.bk-root .bk-btn-success.bk-active{background-color:#47a447;border-color:#398439;}.bk-root .bk-btn-success[disabled],.bk-root .bk-btn-success[disabled]:hover,.bk-root .bk-btn-success[disabled]:focus,.bk-root .bk-btn-success[disabled]:active,.bk-root .bk-btn-success[disabled].bk-active{background-color:#667b66;border-color:#4cae4c;}.bk-root .bk-btn-warning{color:#fff;background-color:#f0ad4e;border-color:#eea236;}.bk-root .bk-btn-warning:hover{background-color:#eea43b;border-color:#e89014;}.bk-root .bk-btn-warning.bk-active{background-color:#ed9c28;border-color:#d58512;}.bk-root .bk-btn-warning[disabled],.bk-root .bk-btn-warning[disabled]:hover,.bk-root .bk-btn-warning[disabled]:focus,.bk-root .bk-btn-warning[disabled]:active,.bk-root .bk-btn-warning[disabled].bk-active{background-color:#c89143;border-color:#eea236;}.bk-root .bk-btn-danger{color:#fff;background-color:#d9534f;border-color:#d43f3a;}.bk-root .bk-btn-danger:hover{background-color:#d5433e;border-color:#bd2d29;}.bk-root .bk-btn-danger.bk-active{background-color:#d2322d;border-color:#ac2925;}.bk-root .bk-btn-danger[disabled],.bk-root .bk-btn-danger[disabled]:hover,.bk-root .bk-btn-danger[disabled]:focus,.bk-root .bk-btn-danger[disabled]:active,.bk-root .bk-btn-danger[disabled].bk-active{background-color:#a55350;border-color:#d43f3a;}.bk-root .bk-btn-light{color:#333;background-color:#fff;border-color:#ccc;border-color:transparent;}.bk-root .bk-btn-light:hover{background-color:#f5f5f5;border-color:#b8b8b8;}.bk-root .bk-btn-light.bk-active{background-color:#ebebeb;border-color:#adadad;}.bk-root .bk-btn-light[disabled],.bk-root .bk-btn-light[disabled]:hover,.bk-root .bk-btn-light[disabled]:focus,.bk-root .bk-btn-light[disabled]:active,.bk-root .bk-btn-light[disabled].bk-active{background-color:#e6e6e6;border-color:#ccc;}.bk-root .bk-btn-group{height:100%;display:flex;flex-wrap:nowrap;align-items:center;}.bk-root .bk-btn-group:not(.bk-vertical),.bk-root .bk-btn-group.bk-horizontal{flex-direction:row;}.bk-root .bk-btn-group.bk-vertical{flex-direction:column;}.bk-root .bk-btn-group > .bk-btn{flex-grow:1;}.bk-root .bk-btn-group:not(.bk-vertical) > .bk-btn + .bk-btn{margin-left:-1px;}.bk-root .bk-btn-group.bk-vertical > .bk-btn + .bk-btn{margin-top:-1px;}.bk-root .bk-btn-group:not(.bk-vertical) > .bk-btn:first-child:not(:last-child){border-bottom-right-radius:0;border-top-right-radius:0;}.bk-root .bk-btn-group.bk-vertical > .bk-btn:first-child:not(:last-child){border-bottom-left-radius:0;border-bottom-right-radius:0;}.bk-root .bk-btn-group:not(.bk-vertical) > .bk-btn:not(:first-child):last-child{border-bottom-left-radius:0;border-top-left-radius:0;}.bk-root .bk-btn-group.bk-vertical > .bk-btn:not(:first-child):last-child{border-top-left-radius:0;border-top-right-radius:0;}.bk-root .bk-btn-group > .bk-btn:not(:first-child):not(:last-child){border-radius:0;}.bk-root .bk-btn-group.bk-vertical > .bk-btn{width:100%;}.bk-root .bk-btn-group .bk-dropdown-toggle{flex:0 0 0;padding:6px 6px;}\"},\n", - " function _(e,t,o,n,_){var i;n();const s=e(310);class d extends s.ColumnView{}o.WidgetBoxView=d,d.__name__=\"WidgetBoxView\";class a extends s.Column{constructor(e){super(e)}}o.WidgetBox=a,i=a,a.__name__=\"WidgetBox\",i.prototype.default_view=d},\n", - " function _(t,a,i,e,M){e();var T=t(135);M(\"MathText\",T.MathText),M(\"Ascii\",T.Ascii),M(\"MathML\",T.MathML),M(\"TeX\",T.TeX),M(\"PlainText\",t(139).PlainText)},\n", - " function _(r,o,t,e,n){e(),n(\"CustomJSTransform\",r(322).CustomJSTransform),n(\"Dodge\",r(323).Dodge),n(\"Interpolator\",r(325).Interpolator),n(\"Jitter\",r(326).Jitter),n(\"LinearInterpolator\",r(327).LinearInterpolator),n(\"StepInterpolator\",r(328).StepInterpolator),n(\"Transform\",r(56).Transform)},\n", - " function _(r,t,s,n,e){var a;n();const u=r(56),o=r(13),m=r(34);class _ extends u.Transform{constructor(r){super(r)}get names(){return(0,o.keys)(this.args)}get values(){return(0,o.values)(this.args)}_make_transform(r,t){return new Function(...this.names,r,(0,m.use_strict)(t))}get scalar_transform(){return this._make_transform(\"x\",this.func)}get vector_transform(){return this._make_transform(\"xs\",this.v_func)}compute(r){return this.scalar_transform(...this.values,r)}v_compute(r){return this.vector_transform(...this.values,r)}}s.CustomJSTransform=_,a=_,_.__name__=\"CustomJSTransform\",a.define((({Unknown:r,String:t,Dict:s})=>({args:[s(r),{}],func:[t,\"\"],v_func:[t,\"\"]})))},\n", - " function _(e,n,r,o,s){var t;o();const u=e(324);class a extends u.RangeTransform{constructor(e){super(e)}_compute(e){return e+this.value}}r.Dodge=a,t=a,a.__name__=\"Dodge\",t.define((({Number:e})=>({value:[e,0]})))},\n", - " function _(e,n,t,r,a){var s;r();const c=e(56),o=e(57),i=e(67),u=e(24),h=e(8),l=e(11);class g extends c.Transform{constructor(e){super(e)}v_compute(e){let n;this.range instanceof i.FactorRange?n=this.range.v_synthetic(e):(0,h.isArrayableOf)(e,h.isNumber)?n=e:(0,l.unreachable)();const t=new((0,u.infer_type)(n))(n.length);for(let e=0;e({range:[n(e(o.Range)),null]})))},\n", - " function _(t,e,r,n,s){var o;n();const i=t(56),a=t(70),h=t(24),l=t(9),d=t(8);class c extends i.Transform{constructor(t){super(t),this._sorted_dirty=!0}connect_signals(){super.connect_signals(),this.connect(this.change,(()=>this._sorted_dirty=!0))}v_compute(t){const e=new((0,h.infer_type)(t))(t.length);for(let r=0;ro*(e[t]-e[r]))),this._x_sorted=new((0,h.infer_type)(e))(n),this._y_sorted=new((0,h.infer_type)(r))(n);for(let t=0;t({x:[o(r,s(e))],y:[o(r,s(e))],data:[i(n(a.ColumnarDataSource)),null],clip:[t,!0]})))},\n", - " function _(t,s,e,i,r){i();const n=t(1);var o;const a=t(324),u=t(67),h=t(20),c=t(8),m=t(12),f=(0,n.__importStar)(t(10)),_=t(11);class p extends a.RangeTransform{constructor(t){super(t)}v_compute(t){var s;let e;this.range instanceof u.FactorRange?e=this.range.v_synthetic(t):(0,c.isArrayableOf)(t,c.isNumber)?e=t:(0,_.unreachable)();const i=e.length;(null===(s=this.previous_offsets)||void 0===s?void 0:s.length)!=i&&(this.previous_offsets=new Array(i),this.previous_offsets=(0,m.map)(this.previous_offsets,(()=>this._compute())));const r=this.previous_offsets;return(0,m.map)(e,((t,s)=>r[s]+t))}_compute(){switch(this.distribution){case\"uniform\":return this.mean+(f.random()-.5)*this.width;case\"normal\":return f.rnorm(this.mean,this.width)}}}e.Jitter=p,o=p,p.__name__=\"Jitter\",o.define((({Number:t})=>({mean:[t,0],width:[t,1],distribution:[h.Distribution,\"uniform\"]})))},\n", - " function _(t,s,_,r,e){r();const i=t(9),o=t(325);class n extends o.Interpolator{constructor(t){super(t)}compute(t){if(this.sort(!1),this.clip){if(tthis._x_sorted[this._x_sorted.length-1])return NaN}else{if(tthis._x_sorted[this._x_sorted.length-1])return this._y_sorted[this._y_sorted.length-1]}if(t==this._x_sorted[0])return this._y_sorted[0];const s=(0,i.find_last_index)(this._x_sorted,(s=>sthis._x_sorted[this._x_sorted.length-1])return NaN}else{if(tthis._x_sorted[this._x_sorted.length-1])return this._y_sorted[this._y_sorted.length-1]}let e;switch(this.mode){case\"after\":e=(0,d.find_last_index)(this._x_sorted,(e=>t>=e));break;case\"before\":e=(0,d.find_index)(this._x_sorted,(e=>t<=e));break;case\"center\":{const s=(0,d.map)(this._x_sorted,(e=>Math.abs(e-t))),r=(0,d.min)(s);e=(0,d.find_index)(s,(t=>r===t));break}default:throw new Error(`unknown mode: ${this.mode}`)}return-1!=e?this._y_sorted[e]:NaN}}s.StepInterpolator=h,_=h,h.__name__=\"StepInterpolator\",_.define((()=>({mode:[n.StepMode,\"after\"]})))},\n", - " function _(p,o,t,a,n){a(),n(\"MapOptions\",p(330).MapOptions),n(\"GMapOptions\",p(330).GMapOptions),n(\"GMapPlot\",p(330).GMapPlot),n(\"Plot\",p(331).Plot)},\n", - " function _(e,t,n,o,a){var s,p,_;o();const i=e(331),r=e(53),l=e(58),c=e(336);a(\"GMapPlotView\",c.GMapPlotView);class d extends r.Model{constructor(e){super(e)}}n.MapOptions=d,s=d,d.__name__=\"MapOptions\",s.define((({Int:e,Number:t})=>({lat:[t],lng:[t],zoom:[e,12]})));class u extends d{constructor(e){super(e)}}n.GMapOptions=u,p=u,u.__name__=\"GMapOptions\",p.define((({Boolean:e,Int:t,String:n})=>({map_type:[n,\"roadmap\"],scale_control:[e,!1],styles:[n],tilt:[t,45]})));class M extends i.Plot{constructor(e){super(e),this.use_map=!0}}n.GMapPlot=M,_=M,M.__name__=\"GMapPlot\",_.prototype.default_view=c.GMapPlotView,_.define((({String:e,Ref:t})=>({map_options:[t(u)],api_key:[e],api_version:[e,\"3.43\"]}))),_.override({x_range:()=>new l.Range1d,y_range:()=>new l.Range1d})},\n", - " function _(e,t,r,n,i){n();const o=e(1);var a;const s=(0,o.__importStar)(e(48)),l=(0,o.__importStar)(e(18)),_=e(15),c=e(20),h=e(9),d=e(13),u=e(8),g=e(309),p=e(128),f=e(306),b=e(40),w=e(118),y=e(59),m=e(221),x=e(57),v=e(55),A=e(75),S=e(41),R=e(176),D=e(175),L=e(63),P=e(332);i(\"PlotView\",P.PlotView);class k extends g.LayoutDOM{constructor(e){super(e),this.use_map=!1}_doc_attached(){super._doc_attached(),this._push_changes([[this.properties.inner_height,null,this.inner_height],[this.properties.inner_width,null,this.inner_width]])}initialize(){super.initialize(),this.reset=new _.Signal0(this,\"reset\");for(const e of(0,d.values)(this.extra_x_ranges).concat(this.x_range)){let t=e.plots;(0,u.isArray)(t)&&(t=t.concat(this),e.setv({plots:t},{silent:!0}))}for(const e of(0,d.values)(this.extra_y_ranges).concat(this.y_range)){let t=e.plots;(0,u.isArray)(t)&&(t=t.concat(this),e.setv({plots:t},{silent:!0}))}}add_layout(e,t=\"center\"){const r=this.properties[t].get_value();this.setv({[t]:[...r,e]})}remove_layout(e){const t=t=>{(0,h.remove_by)(t,(t=>t==e))};t(this.left),t(this.right),t(this.above),t(this.below),t(this.center)}get data_renderers(){return this.renderers.filter((e=>e instanceof R.DataRenderer))}add_renderers(...e){this.renderers=this.renderers.concat(e)}add_glyph(e,t=new A.ColumnDataSource,r={}){const n=new D.GlyphRenderer(Object.assign(Object.assign({},r),{data_source:t,glyph:e}));return this.add_renderers(n),n}add_tools(...e){this.toolbar.tools=this.toolbar.tools.concat(e)}get panels(){return[...this.side_panels,...this.center]}get side_panels(){const{above:e,below:t,left:r,right:n}=this;return(0,h.concat)([e,t,r,n])}}r.Plot=k,a=k,k.__name__=\"Plot\",a.prototype.default_view=P.PlotView,a.mixins([[\"outline_\",s.Line],[\"background_\",s.Fill],[\"border_\",s.Fill]]),a.define((({Boolean:e,Number:t,String:r,Array:n,Dict:i,Or:o,Ref:a,Null:s,Nullable:_})=>({toolbar:[a(m.Toolbar),()=>new m.Toolbar],toolbar_location:[_(c.Location),\"right\"],toolbar_sticky:[e,!0],plot_width:[l.Alias(\"width\")],plot_height:[l.Alias(\"height\")],frame_width:[_(t),null],frame_height:[_(t),null],title:[o(a(w.Title),r,s),\"\",{convert:e=>(0,u.isString)(e)?new w.Title({text:e}):e}],title_location:[_(c.Location),\"above\"],above:[n(o(a(b.Annotation),a(p.Axis))),[]],below:[n(o(a(b.Annotation),a(p.Axis))),[]],left:[n(o(a(b.Annotation),a(p.Axis))),[]],right:[n(o(a(b.Annotation),a(p.Axis))),[]],center:[n(o(a(b.Annotation),a(f.Grid))),[]],renderers:[n(a(S.Renderer)),[]],x_range:[a(x.Range),()=>new L.DataRange1d],y_range:[a(x.Range),()=>new L.DataRange1d],x_scale:[a(v.Scale),()=>new y.LinearScale],y_scale:[a(v.Scale),()=>new y.LinearScale],extra_x_ranges:[i(a(x.Range)),{}],extra_y_ranges:[i(a(x.Range)),{}],extra_x_scales:[i(a(v.Scale)),{}],extra_y_scales:[i(a(v.Scale)),{}],lod_factor:[t,10],lod_interval:[t,300],lod_threshold:[_(t),2e3],lod_timeout:[t,500],hidpi:[e,!0],output_backend:[c.OutputBackend,\"canvas\"],min_border:[_(t),5],min_border_top:[_(t),null],min_border_left:[_(t),null],min_border_bottom:[_(t),null],min_border_right:[_(t),null],inner_width:[t,0],inner_height:[t,0],outer_width:[t,0],outer_height:[t,0],match_aspect:[e,!1],aspect_scale:[t,1],reset_policy:[c.ResetPolicy,\"standard\"]}))),a.override({width:600,height:600,outline_line_color:\"#e5e5e5\",border_fill_color:\"#ffffff\",background_fill_color:\"#ffffff\"})},\n", - " function _(e,t,i,s,a){s();const n=e(1),o=e(126),l=e(249),r=e(309),_=e(40),h=e(118),d=e(128),u=e(220),c=e(251),p=e(113),v=e(45),g=e(19),b=e(251),m=e(333),y=e(8),w=e(9),f=e(235),x=e(208),z=e(211),k=e(209),q=e(123),M=e(65),R=e(334),V=e(335),S=e(28);class O extends r.LayoutDOMView{constructor(){super(...arguments),this._outer_bbox=new M.BBox,this._inner_bbox=new M.BBox,this._needs_paint=!0,this._needs_layout=!1,this._invalidated_painters=new Set,this._invalidate_all=!0,this._needs_notify=!1}get canvas(){return this.canvas_view}get state(){return this._state_manager}set invalidate_dataranges(e){this._range_manager.invalidate_dataranges=e}renderer_view(e){const t=this.renderer_views.get(e);if(null==t)for(const[,t]of this.renderer_views){const i=t.renderer_view(e);if(null!=i)return i}return t}get is_paused(){return null!=this._is_paused&&0!==this._is_paused}get child_models(){return[]}pause(){null==this._is_paused?this._is_paused=1:this._is_paused+=1}unpause(e=!1){if(null==this._is_paused)throw new Error(\"wasn't paused\");this._is_paused-=1,0!=this._is_paused||e||this.request_paint(\"everything\")}notify_finished_after_paint(){this._needs_notify=!0}request_render(){this.request_paint(\"everything\")}request_paint(e){this.invalidate_painters(e),this.schedule_paint()}invalidate_painters(e){if(\"everything\"==e)this._invalidate_all=!0;else if((0,y.isArray)(e))for(const t of e)this._invalidated_painters.add(t);else this._invalidated_painters.add(e)}schedule_paint(){if(!this.is_paused){const e=this.throttled_paint();this._ready=this._ready.then((()=>e))}}request_layout(){this._needs_layout=!0,this.request_paint(\"everything\")}reset(){\"standard\"==this.model.reset_policy&&(this.state.clear(),this.reset_range(),this.reset_selection()),this.model.trigger_event(new c.Reset)}remove(){(0,p.remove_views)(this.renderer_views),(0,p.remove_views)(this.tool_views),this.canvas_view.remove(),super.remove()}render(){super.render(),this.el.appendChild(this.canvas_view.el),this.canvas_view.render()}initialize(){this.pause(),super.initialize(),this.lod_started=!1,this.visuals=new v.Visuals(this),this._initial_state={selection:new Map,dimensions:{width:0,height:0}},this.visibility_callbacks=[],this.renderer_views=new Map,this.tool_views=new Map,this.frame=new o.CartesianFrame(this.model.x_scale,this.model.y_scale,this.model.x_range,this.model.y_range,this.model.extra_x_ranges,this.model.extra_y_ranges,this.model.extra_x_scales,this.model.extra_y_scales),this._range_manager=new R.RangeManager(this),this._state_manager=new V.StateManager(this,this._initial_state),this.throttled_paint=(0,m.throttle)((()=>this.repaint()),1e3/60);const{title_location:e,title:t}=this.model;null!=e&&null!=t&&(this._title=t instanceof h.Title?t:new h.Title({text:t}));const{toolbar_location:i,toolbar:s}=this.model;null!=i&&null!=s&&(this._toolbar=new u.ToolbarPanel({toolbar:s}),s.toolbar_location=i)}async lazy_initialize(){await super.lazy_initialize();const{hidpi:e,output_backend:t}=this.model,i=new l.Canvas({hidpi:e,output_backend:t});this.canvas_view=await(0,p.build_view)(i,{parent:this}),this.canvas_view.plot_views=[this],await this.build_renderer_views(),await this.build_tool_views(),this._range_manager.update_dataranges(),this.unpause(!0),g.logger.debug(\"PlotView initialized\")}_width_policy(){return null==this.model.frame_width?super._width_policy():\"min\"}_height_policy(){return null==this.model.frame_height?super._height_policy():\"min\"}_update_layout(){var e,t,i,s,a;this.layout=new z.BorderLayout,this.layout.set_sizing(this.box_sizing());const n=(0,w.copy)(this.model.above),o=(0,w.copy)(this.model.below),l=(0,w.copy)(this.model.left),r=(0,w.copy)(this.model.right),d=e=>{switch(e){case\"above\":return n;case\"below\":return o;case\"left\":return l;case\"right\":return r}},{title_location:c,title:p}=this.model;null!=c&&null!=p&&d(c).push(this._title);const{toolbar_location:v,toolbar:g}=this.model;if(null!=v&&null!=g){const e=d(v);let t=!0;if(this.model.toolbar_sticky)for(let i=0;i{var i;const s=this.renderer_view(t);return s.panel=new q.Panel(e),null===(i=s.update_layout)||void 0===i||i.call(s),s.layout},m=(e,t)=>{const i=\"above\"==e||\"below\"==e,s=[];for(const a of t)if((0,y.isArray)(a)){const t=a.map((t=>{const s=b(e,t);if(t instanceof u.ToolbarPanel){const e=i?\"width_policy\":\"height_policy\";s.set_sizing(Object.assign(Object.assign({},s.sizing),{[e]:\"min\"}))}return s}));let n;i?(n=new k.Row(t),n.set_sizing({width_policy:\"max\",height_policy:\"min\"})):(n=new k.Column(t),n.set_sizing({width_policy:\"min\",height_policy:\"max\"})),n.absolute=!0,s.push(n)}else s.push(b(e,a));return s},f=null!==(e=this.model.min_border)&&void 0!==e?e:0;this.layout.min_border={left:null!==(t=this.model.min_border_left)&&void 0!==t?t:f,top:null!==(i=this.model.min_border_top)&&void 0!==i?i:f,right:null!==(s=this.model.min_border_right)&&void 0!==s?s:f,bottom:null!==(a=this.model.min_border_bottom)&&void 0!==a?a:f};const M=new x.NodeLayout,R=new x.VStack,V=new x.VStack,S=new x.HStack,O=new x.HStack;M.absolute=!0,R.absolute=!0,V.absolute=!0,S.absolute=!0,O.absolute=!0,M.children=this.model.center.filter((e=>e instanceof _.Annotation)).map((e=>{var t;const i=this.renderer_view(e);return null===(t=i.update_layout)||void 0===t||t.call(i),i.layout})).filter((e=>null!=e));const{frame_width:P,frame_height:j}=this.model;M.set_sizing(Object.assign(Object.assign({},null!=P?{width_policy:\"fixed\",width:P}:{width_policy:\"fit\"}),null!=j?{height_policy:\"fixed\",height:j}:{height_policy:\"fit\"})),M.on_resize((e=>this.frame.set_geometry(e))),R.children=(0,w.reversed)(m(\"above\",n)),V.children=m(\"below\",o),S.children=(0,w.reversed)(m(\"left\",l)),O.children=m(\"right\",r),R.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),V.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),S.set_sizing({width_policy:\"min\",height_policy:\"fit\"}),O.set_sizing({width_policy:\"min\",height_policy:\"fit\"}),this.layout.center_panel=M,this.layout.top_panel=R,this.layout.bottom_panel=V,this.layout.left_panel=S,this.layout.right_panel=O}get axis_views(){const e=[];for(const[,t]of this.renderer_views)t instanceof d.AxisView&&e.push(t);return e}set_toolbar_visibility(e){for(const t of this.visibility_callbacks)t(e)}update_range(e,t){this.pause(),this._range_manager.update(e,t),this.unpause()}reset_range(){this.update_range(null),this.trigger_ranges_update_event()}trigger_ranges_update_event(){const{x_range:e,y_range:t}=this.model;this.model.trigger_event(new b.RangesUpdate(e.start,e.end,t.start,t.end))}get_selection(){const e=new Map;for(const t of this.model.data_renderers){const{selected:i}=t.selection_manager.source;e.set(t,i)}return e}update_selection(e){for(const t of this.model.data_renderers){const i=t.selection_manager.source;if(null!=e){const s=e.get(t);null!=s&&i.selected.update(s,!0)}else i.selection_manager.clear()}}reset_selection(){this.update_selection(null)}_invalidate_layout(){(()=>{var e;for(const t of this.model.side_panels){const i=this.renderer_views.get(t);if(null===(e=i.layout)||void 0===e?void 0:e.has_size_changed())return this.invalidate_painters(i),!0}return!1})()&&this.root.compute_layout()}get_renderer_views(){return this.computed_renderers.map((e=>this.renderer_views.get(e)))}*_compute_renderers(){const{above:e,below:t,left:i,right:s,center:a,renderers:n}=this.model;yield*n,yield*e,yield*t,yield*i,yield*s,yield*a,null!=this._title&&(yield this._title),null!=this._toolbar&&(yield this._toolbar);for(const e of this.model.toolbar.tools)null!=e.overlay&&(yield e.overlay),yield*e.synthetic_renderers}async build_renderer_views(){this.computed_renderers=[...this._compute_renderers()],await(0,p.build_views)(this.renderer_views,this.computed_renderers,{parent:this})}async build_tool_views(){const e=this.model.toolbar.tools;(await(0,p.build_views)(this.tool_views,e,{parent:this})).map((e=>this.canvas_view.ui_event_bus.register_tool(e)))}connect_signals(){super.connect_signals();const{x_ranges:e,y_ranges:t}=this.frame;for(const[,t]of e)this.connect(t.change,(()=>{this._needs_layout=!0,this.request_paint(\"everything\")}));for(const[,e]of t)this.connect(e.change,(()=>{this._needs_layout=!0,this.request_paint(\"everything\")}));const{above:i,below:s,left:a,right:n,center:o,renderers:l}=this.model.properties;this.on_change([i,s,a,n,o,l],(async()=>await this.build_renderer_views())),this.connect(this.model.toolbar.properties.tools.change,(async()=>{await this.build_renderer_views(),await this.build_tool_views()})),this.connect(this.model.change,(()=>this.request_paint(\"everything\"))),this.connect(this.model.reset,(()=>this.reset()))}has_finished(){if(!super.has_finished())return!1;if(this.model.visible)for(const[,e]of this.renderer_views)if(!e.has_finished())return!1;return!0}after_layout(){var e;super.after_layout();for(const[,t]of this.renderer_views)t instanceof _.AnnotationView&&(null===(e=t.after_layout)||void 0===e||e.call(t));if(this._needs_layout=!1,this.model.setv({inner_width:Math.round(this.frame.bbox.width),inner_height:Math.round(this.frame.bbox.height),outer_width:Math.round(this.layout.bbox.width),outer_height:Math.round(this.layout.bbox.height)},{no_change:!0}),!1!==this.model.match_aspect&&(this.pause(),this._range_manager.update_dataranges(),this.unpause(!0)),!this._outer_bbox.equals(this.layout.bbox)){const{width:e,height:t}=this.layout.bbox;this.canvas_view.resize(e,t),this._outer_bbox=this.layout.bbox,this._invalidate_all=!0,this._needs_paint=!0}const{inner_bbox:t}=this.layout;this._inner_bbox.equals(t)||(this._inner_bbox=t,this._needs_paint=!0),this._needs_paint&&this.paint()}repaint(){this._needs_layout&&this._invalidate_layout(),this.paint()}paint(){this.is_paused||(this.model.visible&&(g.logger.trace(`${this.toString()}.paint()`),this._actual_paint()),this._needs_notify&&(this._needs_notify=!1,this.notify_finished()))}_actual_paint(){var e;const{document:t}=this.model;if(null!=t){const e=t.interactive_duration();e>=0&&e{t.interactive_duration()>this.model.lod_timeout&&t.interactive_stop(),this.request_paint(\"everything\")}),this.model.lod_timeout):t.interactive_stop()}this._range_manager.invalidate_dataranges&&(this._range_manager.update_dataranges(),this._invalidate_layout());let i=!1,s=!1;if(this._invalidate_all)i=!0,s=!0;else for(const e of this._invalidated_painters){const{level:t}=e.model;if(\"overlay\"!=t?i=!0:s=!0,i&&s)break}this._invalidated_painters.clear(),this._invalidate_all=!1;const a=[this.frame.bbox.left,this.frame.bbox.top,this.frame.bbox.width,this.frame.bbox.height],{primary:n,overlays:o}=this.canvas_view;i&&(n.prepare(),this.canvas_view.prepare_webgl(a),this._map_hook(n.ctx,a),this._paint_empty(n.ctx,a),this._paint_outline(n.ctx,a),this._paint_levels(n.ctx,\"image\",a,!0),this._paint_levels(n.ctx,\"underlay\",a,!0),this._paint_levels(n.ctx,\"glyph\",a,!0),this._paint_levels(n.ctx,\"guide\",a,!1),this._paint_levels(n.ctx,\"annotation\",a,!1),n.finish()),(s||S.settings.wireframe)&&(o.prepare(),this._paint_levels(o.ctx,\"overlay\",a,!1),S.settings.wireframe&&this._paint_layout(o.ctx,this.layout),o.finish()),null==this._initial_state.range&&(this._initial_state.range=null!==(e=this._range_manager.compute_initial())&&void 0!==e?e:void 0),this._needs_paint=!1}_paint_levels(e,t,i,s){for(const a of this.computed_renderers){if(a.level!=t)continue;const n=this.renderer_views.get(a);e.save(),(s||n.needs_clip)&&(e.beginPath(),e.rect(...i),e.clip()),n.render(),e.restore(),n.has_webgl&&n.needs_webgl_blit&&this.canvas_view.blit_webgl(e)}}_paint_layout(e,t){const{x:i,y:s,width:a,height:n}=t.bbox;e.strokeStyle=\"blue\",e.strokeRect(i,s,a,n);for(const a of t)e.save(),t.absolute||e.translate(i,s),this._paint_layout(e,a),e.restore()}_map_hook(e,t){}_paint_empty(e,t){const[i,s,a,n]=[0,0,this.layout.bbox.width,this.layout.bbox.height],[o,l,r,_]=t;this.visuals.border_fill.doit&&(this.visuals.border_fill.set_value(e),e.fillRect(i,s,a,n),e.clearRect(o,l,r,_)),this.visuals.background_fill.doit&&(this.visuals.background_fill.set_value(e),e.fillRect(o,l,r,_))}_paint_outline(e,t){if(this.visuals.outline_line.doit){e.save(),this.visuals.outline_line.set_value(e);let[i,s,a,n]=t;i+a==this.layout.bbox.width&&(a-=1),s+n==this.layout.bbox.height&&(n-=1),e.strokeRect(i,s,a,n),e.restore()}}to_blob(){return this.canvas_view.to_blob()}export(e,t=!0){const i=\"png\"==e?\"canvas\":\"svg\",s=new f.CanvasLayer(i,t),{width:a,height:n}=this.layout.bbox;s.resize(a,n);const{canvas:o}=this.canvas_view.compose();return s.ctx.drawImage(o,0,0),s}serializable_state(){const e=super.serializable_state(),{children:t}=e,i=(0,n.__rest)(e,[\"children\"]),s=this.get_renderer_views().map((e=>e.serializable_state())).filter((e=>null!=e.bbox));return Object.assign(Object.assign({},i),{children:[...null!=t?t:[],...s]})}}i.PlotView=O,O.__name__=\"PlotView\"},\n", - " function _(t,n,e,o,u){o(),e.throttle=function(t,n){let e=null,o=0,u=!1;return function(){return new Promise(((r,i)=>{const l=function(){o=Date.now(),e=null,u=!1;try{t(),r()}catch(t){i(t)}},a=Date.now(),c=n-(a-o);c<=0&&!u?(null!=e&&clearTimeout(e),u=!0,requestAnimationFrame(l)):e||u?r():e=setTimeout((()=>requestAnimationFrame(l)),c)}))}}},\n", - " function _(t,n,e,a,s){a();const o=t(63),r=t(19);class l{constructor(t){this.parent=t,this.invalidate_dataranges=!0}get frame(){return this.parent.frame}update(t,n){const{x_ranges:e,y_ranges:a}=this.frame;if(null==t){for(const[,t]of e)t.reset();for(const[,t]of a)t.reset();this.update_dataranges()}else{const s=[];for(const[n,a]of e)s.push([a,t.xrs.get(n)]);for(const[n,e]of a)s.push([e,t.yrs.get(n)]);(null==n?void 0:n.scrolling)&&this._update_ranges_together(s),this._update_ranges_individually(s,n)}}reset(){this.update(null)}_update_dataranges(t){const n=new Map,e=new Map;let a=!1;for(const[,n]of t.x_ranges)n instanceof o.DataRange1d&&\"log\"==n.scale_hint&&(a=!0);for(const[,n]of t.y_ranges)n instanceof o.DataRange1d&&\"log\"==n.scale_hint&&(a=!0);for(const t of this.parent.model.data_renderers){const s=this.parent.renderer_view(t);if(null==s)continue;const o=s.glyph_view.bounds();if(null!=o&&n.set(t,o),a){const n=s.glyph_view.log_bounds();null!=n&&e.set(t,n)}}let s=!1,l=!1;const i=t.x_target.span,d=t.y_target.span;let u;!1!==this.parent.model.match_aspect&&0!=i&&0!=d&&(u=1/this.parent.model.aspect_scale*(i/d));for(const[,a]of t.x_ranges){if(a instanceof o.DataRange1d){const t=\"log\"==a.scale_hint?e:n;a.update(t,0,this.parent.model,u),a.follow&&(s=!0)}null!=a.bounds&&(l=!0)}for(const[,a]of t.y_ranges){if(a instanceof o.DataRange1d){const t=\"log\"==a.scale_hint?e:n;a.update(t,1,this.parent.model,u),a.follow&&(s=!0)}null!=a.bounds&&(l=!0)}if(s&&l){r.logger.warn(\"Follow enabled so bounds are unset.\");for(const[,n]of t.x_ranges)n.bounds=null;for(const[,n]of t.y_ranges)n.bounds=null}}update_dataranges(){this._update_dataranges(this.frame);for(const t of this.parent.model.renderers){const{coordinates:n}=t;null!=n&&this._update_dataranges(n)}null!=this.compute_initial()&&(this.invalidate_dataranges=!1)}compute_initial(){let t=!0;const{x_ranges:n,y_ranges:e}=this.frame,a=new Map,s=new Map;for(const[e,s]of n){const{start:n,end:o}=s;if(null==n||null==o||isNaN(n+o)){t=!1;break}a.set(e,{start:n,end:o})}if(t)for(const[n,a]of e){const{start:e,end:o}=a;if(null==e||null==o||isNaN(e+o)){t=!1;break}s.set(n,{start:e,end:o})}return t?{xrs:a,yrs:s}:(r.logger.warn(\"could not set initial ranges\"),null)}_update_ranges_together(t){let n=1;for(const[e,a]of t)n=Math.min(n,this._get_weight_to_constrain_interval(e,a));if(n<1)for(const[e,a]of t)a.start=n*a.start+(1-n)*e.start,a.end=n*a.end+(1-n)*e.end}_update_ranges_individually(t,n){const e=!!(null==n?void 0:n.panning),a=!!(null==n?void 0:n.scrolling);let s=!1;for(const[n,o]of t){if(!a){const t=this._get_weight_to_constrain_interval(n,o);t<1&&(o.start=t*o.start+(1-t)*n.start,o.end=t*o.end+(1-t)*n.end)}if(null!=n.bounds&&\"auto\"!=n.bounds){const[t,r]=n.bounds,l=Math.abs(o.end-o.start);n.is_reversed?(null!=t&&t>=o.end&&(s=!0,o.end=t,(e||a)&&(o.start=t+l)),null!=r&&r<=o.start&&(s=!0,o.start=r,(e||a)&&(o.end=r-l))):(null!=t&&t>=o.start&&(s=!0,o.start=t,(e||a)&&(o.end=t+l)),null!=r&&r<=o.end&&(s=!0,o.end=r,(e||a)&&(o.start=r-l)))}}if(!(a&&s&&(null==n?void 0:n.maintain_focus)))for(const[n,e]of t)n.have_updated_interactively=!0,n.start==e.start&&n.end==e.end||n.setv(e)}_get_weight_to_constrain_interval(t,n){const{min_interval:e}=t;let{max_interval:a}=t;if(null!=t.bounds&&\"auto\"!=t.bounds){const[n,e]=t.bounds;if(null!=n&&null!=e){const t=Math.abs(e-n);a=null!=a?Math.min(a,t):t}}let s=1;if(null!=e||null!=a){const o=Math.abs(t.end-t.start),r=Math.abs(n.end-n.start);null!=e&&e>0&&r0&&r>a&&(s=(a-o)/(r-o)),s=Math.max(0,Math.min(1,s))}return s}}e.RangeManager=l,l.__name__=\"RangeManager\"},\n", - " function _(t,i,s,e,n){e();const h=t(15);class a{constructor(t,i){this.parent=t,this.initial_state=i,this.changed=new h.Signal0(this.parent,\"state_changed\"),this.history=[],this.index=-1}_do_state_change(t){const i=null!=this.history[t]?this.history[t].state:this.initial_state;return null!=i.range&&this.parent.update_range(i.range),null!=i.selection&&this.parent.update_selection(i.selection),i}push(t,i){const{history:s,index:e}=this,n=null!=s[e]?s[e].state:{},h=Object.assign(Object.assign(Object.assign({},this.initial_state),n),i);this.history=this.history.slice(0,this.index+1),this.history.push({type:t,state:h}),this.index=this.history.length-1,this.changed.emit()}clear(){this.history=[],this.index=-1,this.changed.emit()}undo(){if(this.can_undo){this.index-=1;const t=this._do_state_change(this.index);return this.changed.emit(),t}return null}redo(){if(this.can_redo){this.index+=1;const t=this._do_state_change(this.index);return this.changed.emit(),t}return null}get can_undo(){return this.index>=0}get can_redo(){return this.indexm.emit();const s=encodeURIComponent,o=document.createElement(\"script\");o.type=\"text/javascript\",o.src=`https://maps.googleapis.com/maps/api/js?v=${s(e)}&key=${s(t)}&callback=_bokeh_gmaps_callback`,document.body.appendChild(o)}(t,e)}m.connect((()=>this.request_paint(\"everything\")))}this.unpause()}remove(){(0,p.remove)(this.map_el),super.remove()}update_range(t,e){var s,o;if(null==t)this.map.setCenter({lat:this.initial_lat,lng:this.initial_lng}),this.map.setOptions({zoom:this.initial_zoom}),super.update_range(null,e);else if(null!=t.sdx||null!=t.sdy)this.map.panBy(null!==(s=t.sdx)&&void 0!==s?s:0,null!==(o=t.sdy)&&void 0!==o?o:0),super.update_range(t,e);else if(null!=t.factor){if(10!==this.zoom_count)return void(this.zoom_count+=1);this.zoom_count=0,this.pause(),super.update_range(t,e);const s=t.factor<0?-1:1,o=this.map.getZoom();if(null!=o){const t=o+s;if(t>=2){this.map.setZoom(t);const[e,s]=this._get_projected_bounds();s-e<0&&this.map.setZoom(o)}}this.unpause()}this._set_bokeh_ranges()}_build_map(){const{maps:t}=google;this.map_types={satellite:t.MapTypeId.SATELLITE,terrain:t.MapTypeId.TERRAIN,roadmap:t.MapTypeId.ROADMAP,hybrid:t.MapTypeId.HYBRID};const e=this.model.map_options,s={center:new t.LatLng(e.lat,e.lng),zoom:e.zoom,disableDefaultUI:!0,mapTypeId:this.map_types[e.map_type],scaleControl:e.scale_control,tilt:e.tilt};null!=e.styles&&(s.styles=JSON.parse(e.styles)),this.map_el=(0,p.div)({style:{position:\"absolute\"}}),this.canvas_view.add_underlay(this.map_el),this.map=new t.Map(this.map_el,s),t.event.addListener(this.map,\"idle\",(()=>this._set_bokeh_ranges())),t.event.addListener(this.map,\"bounds_changed\",(()=>this._set_bokeh_ranges())),t.event.addListenerOnce(this.map,\"tilesloaded\",(()=>this._render_finished())),this.connect(this.model.properties.map_options.change,(()=>this._update_options())),this.connect(this.model.map_options.properties.styles.change,(()=>this._update_styles())),this.connect(this.model.map_options.properties.lat.change,(()=>this._update_center(\"lat\"))),this.connect(this.model.map_options.properties.lng.change,(()=>this._update_center(\"lng\"))),this.connect(this.model.map_options.properties.zoom.change,(()=>this._update_zoom())),this.connect(this.model.map_options.properties.map_type.change,(()=>this._update_map_type())),this.connect(this.model.map_options.properties.scale_control.change,(()=>this._update_scale_control())),this.connect(this.model.map_options.properties.tilt.change,(()=>this._update_tilt()))}_render_finished(){this._tiles_loaded=!0,this.notify_finished()}has_finished(){return super.has_finished()&&!0===this._tiles_loaded}_get_latlon_bounds(){const t=this.map.getBounds(),e=t.getNorthEast(),s=t.getSouthWest();return[s.lng(),e.lng(),s.lat(),e.lat()]}_get_projected_bounds(){const[t,e,s,o]=this._get_latlon_bounds(),[i,a]=l.wgs84_mercator.compute(t,s),[n,p]=l.wgs84_mercator.compute(e,o);return[i,n,a,p]}_set_bokeh_ranges(){const[t,e,s,o]=this._get_projected_bounds();this.frame.x_range.setv({start:t,end:e}),this.frame.y_range.setv({start:s,end:o})}_update_center(t){var e;const s=null===(e=this.map.getCenter())||void 0===e?void 0:e.toJSON();null!=s&&(s[t]=this.model.map_options[t],this.map.setCenter(s),this._set_bokeh_ranges())}_update_map_type(){this.map.setOptions({mapTypeId:this.map_types[this.model.map_options.map_type]})}_update_scale_control(){this.map.setOptions({scaleControl:this.model.map_options.scale_control})}_update_tilt(){this.map.setOptions({tilt:this.model.map_options.tilt})}_update_options(){this._update_styles(),this._update_center(\"lat\"),this._update_center(\"lng\"),this._update_zoom(),this._update_map_type()}_update_styles(){this.map.setOptions({styles:JSON.parse(this.model.map_options.styles)})}_update_zoom(){this.map.setOptions({zoom:this.model.map_options.zoom}),this._set_bokeh_ranges()}_map_hook(t,e){if(null==this.map&&\"undefined\"!=typeof google&&null!=google.maps&&this._build_map(),null!=this.map_el){const[t,s,o,i]=e;this.map_el.style.top=`${s}px`,this.map_el.style.left=`${t}px`,this.map_el.style.width=`${o}px`,this.map_el.style.height=`${i}px`}}_paint_empty(t,e){const s=this.layout.bbox.width,o=this.layout.bbox.height,[i,a,n,p]=e;t.clearRect(0,0,s,o),t.beginPath(),t.moveTo(0,0),t.lineTo(0,o),t.lineTo(s,o),t.lineTo(s,0),t.lineTo(0,0),t.moveTo(i,a),t.lineTo(i+n,a),t.lineTo(i+n,a+p),t.lineTo(i,a+p),t.lineTo(i,a),t.closePath(),null!=this.model.border_fill_color&&(t.fillStyle=(0,_.color2css)(this.model.border_fill_color),t.fill())}}s.GMapPlotView=d,d.__name__=\"GMapPlotView\"},\n", - " function _(t,_,n,o,r){o();(0,t(1).__exportStar)(t(132),n)},\n", - " function _(e,r,d,n,R){n(),R(\"GlyphRenderer\",e(175).GlyphRenderer),R(\"GraphRenderer\",e(339).GraphRenderer),R(\"GuideRenderer\",e(129).GuideRenderer);var G=e(41);R(\"Renderer\",G.Renderer),R(\"RendererGroup\",G.RendererGroup)},\n", - " function _(e,r,i,n,t){var o;n();const s=e(176),d=e(175),a=e(303),p=e(302),l=e(113),_=e(178),h=e(283),y=e(286);class c extends s.DataRendererView{get glyph_view(){return this.node_view.glyph}async lazy_initialize(){await super.lazy_initialize(),this.apply_coordinates();const{parent:e}=this,{edge_renderer:r,node_renderer:i}=this.model;this.edge_view=await(0,l.build_view)(r,{parent:e}),this.node_view=await(0,l.build_view)(i,{parent:e})}connect_signals(){super.connect_signals(),this.connect(this.model.layout_provider.change,(()=>{this.apply_coordinates(),this.edge_view.set_data(),this.node_view.set_data(),this.request_render()}))}apply_coordinates(){const{edge_renderer:e,node_renderer:r}=this.model;if(!(e.glyph instanceof h.MultiLine||e.glyph instanceof y.Patches))throw new Error(`${this}.edge_renderer.glyph must be a MultiLine glyph`);if(!(r.glyph instanceof _.XYGlyph))throw new Error(`${this}.node_renderer.glyph must be a XYGlyph glyph`);const i=this.model.layout_provider.edge_coordinates,n=this.model.layout_provider.node_coordinates;e.glyph.properties.xs.internal=!0,e.glyph.properties.ys.internal=!0,r.glyph.properties.x.internal=!0,r.glyph.properties.y.internal=!0,e.glyph.xs={expr:i.x},e.glyph.ys={expr:i.y},r.glyph.x={expr:n.x},r.glyph.y={expr:n.y}}remove(){this.edge_view.remove(),this.node_view.remove(),super.remove()}_render(){this.edge_view.render(),this.node_view.render()}renderer_view(e){if(e instanceof d.GlyphRenderer){if(e==this.edge_view.model)return this.edge_view;if(e==this.node_view.model)return this.node_view}return super.renderer_view(e)}}i.GraphRendererView=c,c.__name__=\"GraphRendererView\";class g extends s.DataRenderer{constructor(e){super(e)}get_selection_manager(){return this.node_renderer.data_source.selection_manager}}i.GraphRenderer=g,o=g,g.__name__=\"GraphRenderer\",o.prototype.default_view=c,o.define((({Ref:e})=>({layout_provider:[e(a.LayoutProvider)],node_renderer:[e(d.GlyphRenderer)],edge_renderer:[e(d.GlyphRenderer)],selection_policy:[e(p.GraphHitTestPolicy),()=>new p.NodesOnly],inspection_policy:[e(p.GraphHitTestPolicy),()=>new p.NodesOnly]})))},\n", - " function _(e,t,n,o,c){o();(0,e(1).__exportStar)(e(74),n),c(\"Selection\",e(72).Selection)},\n", - " function _(a,e,S,o,r){o(),r(\"ServerSentDataSource\",a(342).ServerSentDataSource),r(\"AjaxDataSource\",a(344).AjaxDataSource),r(\"ColumnDataSource\",a(75).ColumnDataSource),r(\"ColumnarDataSource\",a(70).ColumnarDataSource),r(\"CDSView\",a(190).CDSView),r(\"DataSource\",a(71).DataSource),r(\"GeoJSONDataSource\",a(345).GeoJSONDataSource),r(\"WebDataSource\",a(343).WebDataSource)},\n", - " function _(e,t,i,a,s){a();const n=e(343);class r extends n.WebDataSource{constructor(e){super(e),this.initialized=!1}setup(){if(!this.initialized){this.initialized=!0;new EventSource(this.data_url).onmessage=e=>{var t;this.load_data(JSON.parse(e.data),this.mode,null!==(t=this.max_size)&&void 0!==t?t:void 0)}}}}i.ServerSentDataSource=r,r.__name__=\"ServerSentDataSource\"},\n", - " function _(e,t,a,n,r){var s;n();const l=e(75),o=e(20);class c extends l.ColumnDataSource{constructor(e){super(e)}get_column(e){const t=this.data[e];return null!=t?t:[]}get_length(){var e;return null!==(e=super.get_length())&&void 0!==e?e:0}initialize(){super.initialize(),this.setup()}load_data(e,t,a){const{adapter:n}=this;let r;switch(r=null!=n?n.execute(this,{response:e}):e,t){case\"replace\":this.data=r;break;case\"append\":{const e=this.data;for(const t of this.columns()){const n=Array.from(e[t]),s=Array.from(r[t]),l=n.concat(s);r[t]=null!=a?l.slice(-a):l}this.data=r;break}}}}a.WebDataSource=c,s=c,c.__name__=\"WebDataSource\",s.define((({Any:e,Int:t,String:a,Nullable:n})=>({max_size:[n(t),null],mode:[o.UpdateMode,\"replace\"],adapter:[n(e),null],data_url:[a]})))},\n", - " function _(t,e,i,s,a){var n;s();const r=t(343),o=t(20),l=t(19),d=t(13);class h extends r.WebDataSource{constructor(t){super(t),this.interval=null,this.initialized=!1}destroy(){null!=this.interval&&clearInterval(this.interval),super.destroy()}setup(){if(!this.initialized&&(this.initialized=!0,this.get_data(this.mode),null!=this.polling_interval)){const t=()=>this.get_data(this.mode,this.max_size,this.if_modified);this.interval=setInterval(t,this.polling_interval)}}get_data(t,e=null,i=!1){const s=this.prepare_request();s.addEventListener(\"load\",(()=>this.do_load(s,t,null!=e?e:void 0))),s.addEventListener(\"error\",(()=>this.do_error(s))),s.send()}prepare_request(){const t=new XMLHttpRequest;t.open(this.method,this.data_url,!0),t.withCredentials=!1,t.setRequestHeader(\"Content-Type\",this.content_type);const e=this.http_headers;for(const[i,s]of(0,d.entries)(e))t.setRequestHeader(i,s);return t}do_load(t,e,i){if(200===t.status){const s=JSON.parse(t.responseText);this.load_data(s,e,i)}}do_error(t){l.logger.error(`Failed to fetch JSON from ${this.data_url} with code ${t.status}`)}}i.AjaxDataSource=h,n=h,h.__name__=\"AjaxDataSource\",n.define((({Boolean:t,Int:e,String:i,Dict:s,Nullable:a})=>({polling_interval:[a(e),null],content_type:[i,\"application/json\"],http_headers:[s(i),{}],method:[o.HTTPMethod,\"POST\"],if_modified:[t,!1]})))},\n", - " function _(e,t,o,r,n){var s;r();const a=e(70),i=e(19),l=e(9),c=e(13);function _(e){return null!=e?e:NaN}const{hasOwnProperty:g}=Object.prototype;class u extends a.ColumnarDataSource{constructor(e){super(e)}initialize(){super.initialize(),this._update_data()}connect_signals(){super.connect_signals(),this.connect(this.properties.geojson.change,(()=>this._update_data()))}_update_data(){this.data=this.geojson_to_column_data()}_get_new_list_array(e){return(0,l.range)(0,e).map((e=>[]))}_get_new_nan_array(e){return(0,l.range)(0,e).map((e=>NaN))}_add_properties(e,t,o,r){var n;const s=null!==(n=e.properties)&&void 0!==n?n:{};for(const[e,n]of(0,c.entries)(s))g.call(t,e)||(t[e]=this._get_new_nan_array(r)),t[e][o]=_(n)}_add_geometry(e,t,o){function r(e,t){return e.concat([[NaN,NaN,NaN]]).concat(t)}switch(e.type){case\"Point\":{const[r,n,s]=e.coordinates;t.x[o]=r,t.y[o]=n,t.z[o]=_(s);break}case\"LineString\":{const{coordinates:r}=e;for(let e=0;e1&&i.logger.warn(\"Bokeh does not support Polygons with holes in, only exterior ring used.\");const r=e.coordinates[0];for(let e=0;e1&&i.logger.warn(\"Bokeh does not support Polygons with holes in, only exterior ring used.\"),n.push(t[0]);const s=n.reduce(r);for(let e=0;e({geojson:[e]}))),s.internal((({Dict:e,Arrayable:t})=>({data:[e(t),{}]})))},\n", - " function _(e,r,T,o,S){o(),S(\"BBoxTileSource\",e(347).BBoxTileSource),S(\"MercatorTileSource\",e(348).MercatorTileSource),S(\"QUADKEYTileSource\",e(351).QUADKEYTileSource),S(\"TileRenderer\",e(352).TileRenderer),S(\"TileSource\",e(349).TileSource),S(\"TMSTileSource\",e(355).TMSTileSource),S(\"WMTSTileSource\",e(353).WMTSTileSource)},\n", - " function _(e,t,r,o,l){var i;o();const n=e(348);class s extends n.MercatorTileSource{constructor(e){super(e)}get_image_url(e,t,r){const o=this.string_lookup_replace(this.url,this.extra_url_vars);let l,i,n,s;return this.use_latlon?[i,s,l,n]=this.get_tile_geographic_bounds(e,t,r):[i,s,l,n]=this.get_tile_meter_bounds(e,t,r),o.replace(\"{XMIN}\",i.toString()).replace(\"{YMIN}\",s.toString()).replace(\"{XMAX}\",l.toString()).replace(\"{YMAX}\",n.toString())}}r.BBoxTileSource=s,i=s,s.__name__=\"BBoxTileSource\",i.define((({Boolean:e})=>({use_latlon:[e,!1]})))},\n", - " function _(t,e,i,_,s){var r;_();const o=t(349),n=t(9),l=t(350);class u extends o.TileSource{constructor(t){super(t)}initialize(){super.initialize(),this._resolutions=(0,n.range)(this.min_zoom,this.max_zoom+1).map((t=>this.get_resolution(t)))}_computed_initial_resolution(){return null!=this.initial_resolution?this.initial_resolution:2*Math.PI*6378137/this.tile_size}is_valid_tile(t,e,i){return!(!this.wrap_around&&(t<0||t>=2**i))&&!(e<0||e>=2**i)}parent_by_tile_xyz(t,e,i){const _=this.tile_xyz_to_quadkey(t,e,i),s=_.substring(0,_.length-1);return this.quadkey_to_tile_xyz(s)}get_resolution(t){return this._computed_initial_resolution()/2**t}get_resolution_by_extent(t,e,i){return[(t[2]-t[0])/i,(t[3]-t[1])/e]}get_level_by_extent(t,e,i){const _=(t[2]-t[0])/i,s=(t[3]-t[1])/e,r=Math.max(_,s);let o=0;for(const t of this._resolutions){if(r>t){if(0==o)return 0;if(o>0)return o-1}o+=1}return o-1}get_closest_level_by_extent(t,e,i){const _=(t[2]-t[0])/i,s=(t[3]-t[1])/e,r=Math.max(_,s),o=this._resolutions.reduce((function(t,e){return Math.abs(e-r)e?(u=o-s,a*=t):(u*=e,a=n-r)}const h=(u-(o-s))/2,c=(a-(n-r))/2;return[s-h,r-c,o+h,n+c]}tms_to_wmts(t,e,i){return[t,2**i-1-e,i]}wmts_to_tms(t,e,i){return[t,2**i-1-e,i]}pixels_to_meters(t,e,i){const _=this.get_resolution(i);return[t*_-this.x_origin_offset,e*_-this.y_origin_offset]}meters_to_pixels(t,e,i){const _=this.get_resolution(i);return[(t+this.x_origin_offset)/_,(e+this.y_origin_offset)/_]}pixels_to_tile(t,e){let i=Math.ceil(t/this.tile_size);i=0===i?i:i-1;return[i,Math.max(Math.ceil(e/this.tile_size)-1,0)]}pixels_to_raster(t,e,i){return[t,(this.tile_size<=l;t--)for(let i=n;i<=u;i++)this.is_valid_tile(i,t,e)&&h.push([i,t,e,this.get_tile_meter_bounds(i,t,e)]);return this.sort_tiles_from_center(h,[n,l,u,a]),h}quadkey_to_tile_xyz(t){let e=0,i=0;const _=t.length;for(let s=_;s>0;s--){const r=1<0;s--){const i=1<0;)if(s=s.substring(0,s.length-1),[t,e,i]=this.quadkey_to_tile_xyz(s),[t,e,i]=this.denormalize_xyz(t,e,i,_),this.tiles.has(this.tile_xyz_to_key(t,e,i)))return[t,e,i];return[0,0,0]}normalize_xyz(t,e,i){if(this.wrap_around){const _=2**i;return[(t%_+_)%_,e,i]}return[t,e,i]}denormalize_xyz(t,e,i,_){return[t+_*2**i,e,i]}denormalize_meters(t,e,i,_){return[t+2*_*Math.PI*6378137,e]}calculate_world_x_by_tile_xyz(t,e,i){return Math.floor(t/2**i)}}i.MercatorTileSource=u,r=u,u.__name__=\"MercatorTileSource\",r.define((({Boolean:t})=>({snap_to_zoom:[t,!1],wrap_around:[t,!0]}))),r.override({x_origin_offset:20037508.34,y_origin_offset:20037508.34,initial_resolution:156543.03392804097})},\n", - " function _(e,t,r,i,n){var l;i();const a=e(53),s=e(13);class c extends a.Model{constructor(e){super(e)}initialize(){super.initialize(),this.tiles=new Map,this._normalize_case()}connect_signals(){super.connect_signals(),this.connect(this.change,(()=>this._clear_cache()))}string_lookup_replace(e,t){let r=e;for(const[e,i]of(0,s.entries)(t))r=r.replace(`{${e}}`,i);return r}_normalize_case(){const e=this.url.replace(\"{x}\",\"{X}\").replace(\"{y}\",\"{Y}\").replace(\"{z}\",\"{Z}\").replace(\"{q}\",\"{Q}\").replace(\"{xmin}\",\"{XMIN}\").replace(\"{ymin}\",\"{YMIN}\").replace(\"{xmax}\",\"{XMAX}\").replace(\"{ymax}\",\"{YMAX}\");this.url=e}_clear_cache(){this.tiles=new Map}tile_xyz_to_key(e,t,r){return`${e}:${t}:${r}`}key_to_tile_xyz(e){const[t,r,i]=e.split(\":\").map((e=>parseInt(e)));return[t,r,i]}sort_tiles_from_center(e,t){const[r,i,n,l]=t,a=(n-r)/2+r,s=(l-i)/2+i;e.sort((function(e,t){return Math.sqrt((a-e[0])**2+(s-e[1])**2)-Math.sqrt((a-t[0])**2+(s-t[1])**2)}))}get_image_url(e,t,r){return this.string_lookup_replace(this.url,this.extra_url_vars).replace(\"{X}\",e.toString()).replace(\"{Y}\",t.toString()).replace(\"{Z}\",r.toString())}}r.TileSource=c,l=c,c.__name__=\"TileSource\",l.define((({Number:e,String:t,Dict:r,Nullable:i})=>({url:[t,\"\"],tile_size:[e,256],max_zoom:[e,30],min_zoom:[e,0],extra_url_vars:[r(t),{}],attribution:[t,\"\"],x_origin_offset:[e],y_origin_offset:[e],initial_resolution:[i(e),null]})))},\n", - " function _(t,e,r,n,o){n();const c=t(78);function _(t,e){return c.wgs84_mercator.compute(t,e)}function g(t,e){return c.wgs84_mercator.invert(t,e)}r.geographic_to_meters=_,r.meters_to_geographic=g,r.geographic_extent_to_meters=function(t){const[e,r,n,o]=t,[c,g]=_(e,r),[i,u]=_(n,o);return[c,g,i,u]},r.meters_extent_to_geographic=function(t){const[e,r,n,o]=t,[c,_]=g(e,r),[i,u]=g(n,o);return[c,_,i,u]}},\n", - " function _(e,t,r,s,_){s();const o=e(348);class c extends o.MercatorTileSource{constructor(e){super(e)}get_image_url(e,t,r){const s=this.string_lookup_replace(this.url,this.extra_url_vars),[_,o,c]=this.tms_to_wmts(e,t,r),i=this.tile_xyz_to_quadkey(_,o,c);return s.replace(\"{Q}\",i)}}r.QUADKEYTileSource=c,c.__name__=\"QUADKEYTileSource\"},\n", - " function _(t,e,i,s,_){s();const n=t(1);var a;const o=t(349),r=t(353),h=t(41),l=t(58),d=t(43),m=t(136),c=t(9),u=t(8),p=(0,n.__importStar)(t(354));class g extends h.RendererView{initialize(){this._tiles=[],super.initialize()}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render())),this.connect(this.model.tile_source.change,(()=>this.request_render()))}remove(){null!=this.attribution_el&&(0,d.removeElement)(this.attribution_el),super.remove()}styles(){return[...super.styles(),p.default]}get_extent(){return[this.x_range.start,this.y_range.start,this.x_range.end,this.y_range.end]}get map_plot(){return this.plot_model}get map_canvas(){return this.layer.ctx}get map_frame(){return this.plot_view.frame}get x_range(){return this.map_plot.x_range}get y_range(){return this.map_plot.y_range}_set_data(){this.extent=this.get_extent(),this._last_height=void 0,this._last_width=void 0}_update_attribution(){null!=this.attribution_el&&(0,d.removeElement)(this.attribution_el);const{attribution:t}=this.model.tile_source;if((0,u.isString)(t)&&t.length>0){const{layout:e,frame:i}=this.plot_view,s=e.bbox.width-i.bbox.right,_=e.bbox.height-i.bbox.bottom,n=i.bbox.width;this.attribution_el=(0,d.div)({class:p.tile_attribution,style:{position:\"absolute\",right:`${s}px`,bottom:`${_}px`,\"max-width\":n-4+\"px\",padding:\"2px\",\"background-color\":\"rgba(255,255,255,0.5)\",\"font-size\":\"9px\",\"line-height\":\"1.05\",\"white-space\":\"nowrap\",overflow:\"hidden\",\"text-overflow\":\"ellipsis\"}}),this.plot_view.canvas_view.add_event(this.attribution_el),this.attribution_el.innerHTML=t,this.attribution_el.title=this.attribution_el.textContent.replace(/\\s*\\n\\s*/g,\" \")}}_map_data(){this.initial_extent=this.get_extent();const t=this.model.tile_source.get_level_by_extent(this.initial_extent,this.map_frame.bbox.height,this.map_frame.bbox.width),e=this.model.tile_source.snap_to_zoom_level(this.initial_extent,this.map_frame.bbox.height,this.map_frame.bbox.width,t);this.x_range.start=e[0],this.y_range.start=e[1],this.x_range.end=e[2],this.y_range.end=e[3],this.x_range instanceof l.Range1d&&(this.x_range.reset_start=e[0],this.x_range.reset_end=e[2]),this.y_range instanceof l.Range1d&&(this.y_range.reset_start=e[1],this.y_range.reset_end=e[3]),this._update_attribution()}_create_tile(t,e,i,s,_=!1){const n=this.model.tile_source.tile_xyz_to_quadkey(t,e,i),a=this.model.tile_source.tile_xyz_to_key(t,e,i);if(this.model.tile_source.tiles.has(a))return;const[o,r,h]=this.model.tile_source.normalize_xyz(t,e,i),l=this.model.tile_source.get_image_url(o,r,h),d={img:void 0,tile_coords:[t,e,i],normalized_coords:[o,r,h],quadkey:n,cache_key:a,bounds:s,loaded:!1,finished:!1,x_coord:s[0],y_coord:s[3]};this.model.tile_source.tiles.set(a,d),this._tiles.push(d),new m.ImageLoader(l,{loaded:t=>{Object.assign(d,{img:t,loaded:!0}),_?(d.finished=!0,this.notify_finished()):this.request_render()},failed(){d.finished=!0}})}_enforce_aspect_ratio(){if(this._last_height!==this.map_frame.bbox.height||this._last_width!==this.map_frame.bbox.width){const t=this.get_extent(),e=this.model.tile_source.get_level_by_extent(t,this.map_frame.bbox.height,this.map_frame.bbox.width),i=this.model.tile_source.snap_to_zoom_level(t,this.map_frame.bbox.height,this.map_frame.bbox.width,e);this.x_range.setv({start:i[0],end:i[2]}),this.y_range.setv({start:i[1],end:i[3]}),this.extent=i,this._last_height=this.map_frame.bbox.height,this._last_width=this.map_frame.bbox.width}}has_finished(){if(!super.has_finished())return!1;if(0==this._tiles.length)return!1;for(const t of this._tiles)if(!t.finished)return!1;return!0}_render(){null==this.map_initialized&&(this._set_data(),this._map_data(),this.map_initialized=!0),this._enforce_aspect_ratio(),this._update(),null!=this.prefetch_timer&&clearTimeout(this.prefetch_timer),this.prefetch_timer=setTimeout(this._prefetch_tiles.bind(this),500),this.has_finished()&&this.notify_finished()}_draw_tile(t){const e=this.model.tile_source.tiles.get(t);if(null!=e&&e.loaded){const[[t],[i]]=this.coordinates.map_to_screen([e.bounds[0]],[e.bounds[3]]),[[s],[_]]=this.coordinates.map_to_screen([e.bounds[2]],[e.bounds[1]]),n=s-t,a=_-i,o=t,r=i,h=this.map_canvas.getImageSmoothingEnabled();this.map_canvas.setImageSmoothingEnabled(this.model.smoothing),this.map_canvas.drawImage(e.img,o,r,n,a),this.map_canvas.setImageSmoothingEnabled(h),e.finished=!0}}_set_rect(){const t=this.plot_model.outline_line_width,e=this.map_frame.bbox.left+t/2,i=this.map_frame.bbox.top+t/2,s=this.map_frame.bbox.width-t,_=this.map_frame.bbox.height-t;this.map_canvas.rect(e,i,s,_),this.map_canvas.clip()}_render_tiles(t){this.map_canvas.save(),this._set_rect(),this.map_canvas.globalAlpha=this.model.alpha;for(const e of t)this._draw_tile(e);this.map_canvas.restore()}_prefetch_tiles(){const{tile_source:t}=this.model,e=this.get_extent(),i=this.map_frame.bbox.height,s=this.map_frame.bbox.width,_=this.model.tile_source.get_level_by_extent(e,i,s),n=this.model.tile_source.get_tiles_by_extent(e,_);for(let e=0,i=Math.min(10,n.length);ei&&(s=this.extent,o=i,r=!0),r&&(this.x_range.setv({start:s[0],end:s[2]}),this.y_range.setv({start:s[1],end:s[3]})),this.extent=s;const h=t.get_tiles_by_extent(s,o),l=[],d=[],m=[],u=[];for(const e of h){const[i,s,n]=e,a=t.tile_xyz_to_key(i,s,n),o=t.tiles.get(a);if(null!=o&&o.loaded)d.push(a);else if(this.model.render_parents){const[e,a,o]=t.get_closest_parent_by_tile_xyz(i,s,n),r=t.tile_xyz_to_key(e,a,o),h=t.tiles.get(r);if(null!=h&&h.loaded&&!(0,c.includes)(m,r)&&m.push(r),_){const e=t.children_by_tile_xyz(i,s,n);for(const[i,s,_]of e){const e=t.tile_xyz_to_key(i,s,_);t.tiles.has(e)&&u.push(e)}}}null==o&&l.push(e)}this._render_tiles(m),this._render_tiles(u),this._render_tiles(d),null!=this.render_timer&&clearTimeout(this.render_timer),this.render_timer=setTimeout((()=>this._fetch_tiles(l)),65)}}i.TileRendererView=g,g.__name__=\"TileRendererView\";class b extends h.Renderer{constructor(t){super(t)}}i.TileRenderer=b,a=b,b.__name__=\"TileRenderer\",a.prototype.default_view=g,a.define((({Boolean:t,Number:e,Ref:i})=>({alpha:[e,1],smoothing:[t,!0],tile_source:[i(o.TileSource),()=>new r.WMTSTileSource],render_parents:[t,!0]}))),a.override({level:\"image\"})},\n", - " function _(t,e,r,o,s){o();const c=t(348);class i extends c.MercatorTileSource{constructor(t){super(t)}get_image_url(t,e,r){const o=this.string_lookup_replace(this.url,this.extra_url_vars),[s,c,i]=this.tms_to_wmts(t,e,r);return o.replace(\"{X}\",s.toString()).replace(\"{Y}\",c.toString()).replace(\"{Z}\",i.toString())}}r.WMTSTileSource=i,i.__name__=\"WMTSTileSource\"},\n", - " function _(t,o,i,b,r){b(),i.root=\"bk-root\",i.tile_attribution=\"bk-tile-attribution\",i.default=\".bk-root .bk-tile-attribution a{color:black;}\"},\n", - " function _(e,r,t,c,o){c();const i=e(348);class l extends i.MercatorTileSource{constructor(e){super(e)}get_image_url(e,r,t){return this.string_lookup_replace(this.url,this.extra_url_vars).replace(\"{X}\",e.toString()).replace(\"{Y}\",r.toString()).replace(\"{Z}\",t.toString())}}t.TMSTileSource=l,l.__name__=\"TMSTileSource\"},\n", - " function _(e,t,u,a,r){a(),r(\"CanvasTexture\",e(357).CanvasTexture),r(\"ImageURLTexture\",e(359).ImageURLTexture),r(\"Texture\",e(358).Texture)},\n", - " function _(t,e,n,c,s){var r;c();const o=t(358),a=t(34);class u extends o.Texture{constructor(t){super(t)}get func(){const t=(0,a.use_strict)(this.code);return new Function(\"ctx\",\"color\",\"scale\",\"weight\",t)}get_pattern(t,e,n){const c=document.createElement(\"canvas\");c.width=e,c.height=e;const s=c.getContext(\"2d\");return this.func.call(this,s,t,e,n),c}}n.CanvasTexture=u,r=u,u.__name__=\"CanvasTexture\",r.define((({String:t})=>({code:[t]})))},\n", - " function _(e,t,n,r,o){var i;r();const s=e(53),u=e(20);class c extends s.Model{constructor(e){super(e)}}n.Texture=c,i=c,c.__name__=\"Texture\",i.define((()=>({repetition:[u.TextureRepetition,\"repeat\"]})))},\n", - " function _(e,t,i,r,n){var a;r();const s=e(358),o=e(136);class u extends s.Texture{constructor(e){super(e)}initialize(){super.initialize(),this._loader=new o.ImageLoader(this.url)}get_pattern(e,t,i){const{_loader:r}=this;return this._loader.finished?r.image:r.promise}}i.ImageURLTexture=u,a=u,u.__name__=\"ImageURLTexture\",a.define((({String:e})=>({url:[e]})))},\n", - " function _(o,l,T,e,t){e(),t(\"ActionTool\",o(238).ActionTool),t(\"CustomAction\",o(361).CustomAction),t(\"HelpTool\",o(239).HelpTool),t(\"RedoTool\",o(362).RedoTool),t(\"ResetTool\",o(363).ResetTool),t(\"SaveTool\",o(364).SaveTool),t(\"UndoTool\",o(365).UndoTool),t(\"ZoomInTool\",o(366).ZoomInTool),t(\"ZoomOutTool\",o(369).ZoomOutTool),t(\"ButtonTool\",o(224).ButtonTool),t(\"EditTool\",o(370).EditTool),t(\"BoxEditTool\",o(371).BoxEditTool),t(\"FreehandDrawTool\",o(372).FreehandDrawTool),t(\"PointDrawTool\",o(373).PointDrawTool),t(\"PolyDrawTool\",o(374).PolyDrawTool),t(\"PolyTool\",o(375).PolyTool),t(\"PolyEditTool\",o(376).PolyEditTool),t(\"BoxSelectTool\",o(377).BoxSelectTool),t(\"BoxZoomTool\",o(379).BoxZoomTool),t(\"GestureTool\",o(223).GestureTool),t(\"LassoSelectTool\",o(380).LassoSelectTool),t(\"LineEditTool\",o(382).LineEditTool),t(\"PanTool\",o(384).PanTool),t(\"PolySelectTool\",o(381).PolySelectTool),t(\"RangeTool\",o(385).RangeTool),t(\"SelectTool\",o(378).SelectTool),t(\"TapTool\",o(386).TapTool),t(\"WheelPanTool\",o(387).WheelPanTool),t(\"WheelZoomTool\",o(388).WheelZoomTool),t(\"CrosshairTool\",o(389).CrosshairTool),t(\"CustomJSHover\",o(390).CustomJSHover),t(\"HoverTool\",o(391).HoverTool),t(\"InspectTool\",o(232).InspectTool),t(\"Tool\",o(222).Tool),t(\"ToolProxy\",o(394).ToolProxy),t(\"Toolbar\",o(221).Toolbar),t(\"ToolbarBase\",o(233).ToolbarBase),t(\"ProxyToolbar\",o(395).ProxyToolbar),t(\"ToolbarBox\",o(395).ToolbarBox)},\n", - " function _(t,o,e,s,n){var c;s();const i=t(238);class u extends i.ActionToolButtonView{css_classes(){return super.css_classes().concat(\"bk-toolbar-button-custom-action\")}}e.CustomActionButtonView=u,u.__name__=\"CustomActionButtonView\";class l extends i.ActionToolView{doit(){var t;null===(t=this.model.callback)||void 0===t||t.execute(this.model)}}e.CustomActionView=l,l.__name__=\"CustomActionView\";class a extends i.ActionTool{constructor(t){super(t),this.tool_name=\"Custom Action\",this.button_view=u}}e.CustomAction=a,c=a,a.__name__=\"CustomAction\",c.prototype.default_view=l,c.define((({Any:t,String:o,Nullable:e})=>({callback:[e(t)],icon:[o]}))),c.override({description:\"Perform a Custom Action\"})},\n", - " function _(e,o,t,i,s){var n;i();const l=e(238),_=e(228);class d extends l.ActionToolView{connect_signals(){super.connect_signals(),this.connect(this.plot_view.state.changed,(()=>this.model.disabled=!this.plot_view.state.can_redo))}doit(){const e=this.plot_view.state.redo();null!=(null==e?void 0:e.range)&&this.plot_view.trigger_ranges_update_event()}}t.RedoToolView=d,d.__name__=\"RedoToolView\";class a extends l.ActionTool{constructor(e){super(e),this.tool_name=\"Redo\",this.icon=_.tool_icon_redo}}t.RedoTool=a,n=a,a.__name__=\"RedoTool\",n.prototype.default_view=d,n.override({disabled:!0}),n.register_alias(\"redo\",(()=>new a))},\n", - " function _(e,o,t,s,i){var _;s();const n=e(238),l=e(228);class c extends n.ActionToolView{doit(){this.plot_view.reset()}}t.ResetToolView=c,c.__name__=\"ResetToolView\";class r extends n.ActionTool{constructor(e){super(e),this.tool_name=\"Reset\",this.icon=l.tool_icon_reset}}t.ResetTool=r,_=r,r.__name__=\"ResetTool\",_.prototype.default_view=c,_.register_alias(\"reset\",(()=>new r))},\n", - " function _(e,o,t,a,i){var s;a();const c=e(238),n=e(228);class l extends c.ActionToolView{async copy(){const e=await this.plot_view.to_blob(),o=new ClipboardItem({[e.type]:Promise.resolve(e)});await navigator.clipboard.write([o])}async save(e){const o=await this.plot_view.to_blob(),t=document.createElement(\"a\");t.href=URL.createObjectURL(o),t.download=e,t.target=\"_blank\",t.dispatchEvent(new MouseEvent(\"click\"))}doit(e=\"save\"){switch(e){case\"save\":this.save(\"bokeh_plot\");break;case\"copy\":this.copy()}}}t.SaveToolView=l,l.__name__=\"SaveToolView\";class r extends c.ActionTool{constructor(e){super(e),this.tool_name=\"Save\",this.icon=n.tool_icon_save}get menu(){return[{icon:\"bk-tool-icon-copy-to-clipboard\",tooltip:\"Copy image to clipboard\",if:()=>\"undefined\"!=typeof ClipboardItem,handler:()=>{this.do.emit(\"copy\")}}]}}t.SaveTool=r,s=r,r.__name__=\"SaveTool\",s.prototype.default_view=l,s.register_alias(\"save\",(()=>new r))},\n", - " function _(o,e,t,n,i){var s;n();const l=o(238),_=o(228);class d extends l.ActionToolView{connect_signals(){super.connect_signals(),this.connect(this.plot_view.state.changed,(()=>this.model.disabled=!this.plot_view.state.can_undo))}doit(){const o=this.plot_view.state.undo();null!=(null==o?void 0:o.range)&&this.plot_view.trigger_ranges_update_event()}}t.UndoToolView=d,d.__name__=\"UndoToolView\";class a extends l.ActionTool{constructor(o){super(o),this.tool_name=\"Undo\",this.icon=_.tool_icon_undo}}t.UndoTool=a,s=a,a.__name__=\"UndoTool\",s.prototype.default_view=d,s.override({disabled:!0}),s.register_alias(\"undo\",(()=>new a))},\n", - " function _(o,n,e,i,s){var t;i();const _=o(367),m=o(228);class a extends _.ZoomBaseToolView{}e.ZoomInToolView=a,a.__name__=\"ZoomInToolView\";class l extends _.ZoomBaseTool{constructor(o){super(o),this.sign=1,this.tool_name=\"Zoom In\",this.icon=m.tool_icon_zoom_in}}e.ZoomInTool=l,t=l,l.__name__=\"ZoomInTool\",t.prototype.default_view=a,t.register_alias(\"zoom_in\",(()=>new l({dimensions:\"both\"}))),t.register_alias(\"xzoom_in\",(()=>new l({dimensions:\"width\"}))),t.register_alias(\"yzoom_in\",(()=>new l({dimensions:\"height\"})))},\n", - " function _(o,t,e,i,s){var n;i();const a=o(238),_=o(20),l=o(368);class m extends a.ActionToolView{doit(){var o;const t=this.plot_view.frame,e=this.model.dimensions,i=\"width\"==e||\"both\"==e,s=\"height\"==e||\"both\"==e,n=(0,l.scale_range)(t,this.model.sign*this.model.factor,i,s);this.plot_view.state.push(\"zoom_out\",{range:n}),this.plot_view.update_range(n,{scrolling:!0,maintain_focus:this.model.maintain_focus}),null===(o=this.model.document)||void 0===o||o.interactive_start(this.plot_model),this.plot_view.trigger_ranges_update_event()}}e.ZoomBaseToolView=m,m.__name__=\"ZoomBaseToolView\";class h extends a.ActionTool{constructor(o){super(o),this.maintain_focus=!0}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}e.ZoomBaseTool=h,n=h,h.__name__=\"ZoomBaseTool\",n.define((({Percent:o})=>({factor:[o,.1],dimensions:[_.Dimensions,\"both\"]})))},\n", - " function _(n,t,o,r,s){r();const c=n(10);function e(n,t,o){const[r,s]=[n.start,n.end],c=null!=o?o:(s+r)/2;return[r-(r-c)*t,s-(s-c)*t]}function a(n,[t,o]){const r=new Map;for(const[s,c]of n){const[n,e]=c.r_invert(t,o);r.set(s,{start:n,end:e})}return r}o.scale_highlow=e,o.get_info=a,o.scale_range=function(n,t,o=!0,r=!0,s){t=(0,c.clamp)(t,-.9,.9);const l=o?t:0,[u,i]=e(n.bbox.h_range,l,null!=s?s.x:void 0),_=a(n.x_scales,[u,i]),f=r?t:0,[g,x]=e(n.bbox.v_range,f,null!=s?s.y:void 0);return{xrs:_,yrs:a(n.y_scales,[g,x]),factor:t}}},\n", - " function _(o,e,t,i,s){var n;i();const _=o(367),a=o(228);class m extends _.ZoomBaseToolView{}t.ZoomOutToolView=m,m.__name__=\"ZoomOutToolView\";class l extends _.ZoomBaseTool{constructor(o){super(o),this.sign=-1,this.tool_name=\"Zoom Out\",this.icon=a.tool_icon_zoom_out}}t.ZoomOutTool=l,n=l,l.__name__=\"ZoomOutTool\",n.prototype.default_view=m,n.define((({Boolean:o})=>({maintain_focus:[o,!0]}))),n.register_alias(\"zoom_out\",(()=>new l({dimensions:\"both\"}))),n.register_alias(\"xzoom_out\",(()=>new l({dimensions:\"width\"}))),n.register_alias(\"yzoom_out\",(()=>new l({dimensions:\"height\"})))},\n", - " function _(e,t,s,o,n){var r;o();const i=e(9),c=e(8),a=e(11),_=e(175),l=e(223);class d extends l.GestureToolView{constructor(){super(...arguments),this._mouse_in_frame=!0}_select_mode(e){const{shiftKey:t,ctrlKey:s}=e;return t||s?t&&!s?\"append\":!t&&s?\"intersect\":t&&s?\"subtract\":void(0,a.unreachable)():\"replace\"}_move_enter(e){this._mouse_in_frame=!0}_move_exit(e){this._mouse_in_frame=!1}_map_drag(e,t,s){if(!this.plot_view.frame.bbox.contains(e,t))return null;const o=this.plot_view.renderer_view(s);if(null==o)return null;return[o.coordinates.x_scale.invert(e),o.coordinates.y_scale.invert(t)]}_delete_selected(e){const t=e.data_source,s=t.selected.indices;s.sort();for(const e of t.columns()){const o=t.get_array(e);for(let e=0;e({custom_icon:[n(t),null],empty_value:[e],renderers:[s(o(_.GlyphRenderer)),[]]})))},\n", - " function _(e,t,s,i,_){var o;i();const n=e(43),a=e(20),d=e(370),l=e(228);class r extends d.EditToolView{_tap(e){null==this._draw_basepoint&&null==this._basepoint&&this._select_event(e,this._select_mode(e),this.model.renderers)}_keyup(e){if(this.model.active&&this._mouse_in_frame)for(const t of this.model.renderers)if(e.keyCode===n.Keys.Backspace)this._delete_selected(t);else if(e.keyCode==n.Keys.Esc){t.data_source.selection_manager.clear()}}_set_extent([e,t],[s,i],_,o=!1){const n=this.model.renderers[0],a=this.plot_view.renderer_view(n);if(null==a)return;const d=n.glyph,l=n.data_source,[r,h]=a.coordinates.x_scale.r_invert(e,t),[p,u]=a.coordinates.y_scale.r_invert(s,i),[c,m]=[(r+h)/2,(p+u)/2],[f,b]=[h-r,u-p],[y,x]=[d.x.field,d.y.field],[w,v]=[d.width.field,d.height.field];if(_)this._pop_glyphs(l,this.model.num_objects),y&&l.get_array(y).push(c),x&&l.get_array(x).push(m),w&&l.get_array(w).push(f),v&&l.get_array(v).push(b),this._pad_empty_columns(l,[y,x,w,v]);else{const e=l.data[y].length-1;y&&(l.data[y][e]=c),x&&(l.data[x][e]=m),w&&(l.data[w][e]=f),v&&(l.data[v][e]=b)}this._emit_cds_changes(l,!0,!1,o)}_update_box(e,t=!1,s=!1){if(null==this._draw_basepoint)return;const i=[e.sx,e.sy],_=this.plot_view.frame,o=this.model.dimensions,n=this.model._get_dim_limits(this._draw_basepoint,i,_,o);if(null!=n){const[e,i]=n;this._set_extent(e,i,t,s)}}_doubletap(e){this.model.active&&(null!=this._draw_basepoint?(this._update_box(e,!1,!0),this._draw_basepoint=null):(this._draw_basepoint=[e.sx,e.sy],this._select_event(e,\"append\",this.model.renderers),this._update_box(e,!0,!1)))}_move(e){this._update_box(e,!1,!1)}_pan_start(e){if(e.shiftKey){if(null!=this._draw_basepoint)return;this._draw_basepoint=[e.sx,e.sy],this._update_box(e,!0,!1)}else{if(null!=this._basepoint)return;this._select_event(e,\"append\",this.model.renderers),this._basepoint=[e.sx,e.sy]}}_pan(e,t=!1,s=!1){if(e.shiftKey){if(null==this._draw_basepoint)return;this._update_box(e,t,s)}else{if(null==this._basepoint)return;this._drag_points(e,this.model.renderers)}}_pan_end(e){if(this._pan(e,!1,!0),e.shiftKey)this._draw_basepoint=null;else{this._basepoint=null;for(const e of this.model.renderers)this._emit_cds_changes(e.data_source,!1,!0,!0)}}}s.BoxEditToolView=r,r.__name__=\"BoxEditToolView\";class h extends d.EditTool{constructor(e){super(e),this.tool_name=\"Box Edit Tool\",this.icon=l.tool_icon_box_edit,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=1}}s.BoxEditTool=h,o=h,h.__name__=\"BoxEditTool\",o.prototype.default_view=r,o.define((({Int:e})=>({dimensions:[a.Dimensions,\"both\"],num_objects:[e,0]})))},\n", - " function _(e,t,a,s,r){var _;s();const d=e(43),o=e(8),n=e(370),i=e(228);class l extends n.EditToolView{_draw(e,t,a=!1){if(!this.model.active)return;const s=this.model.renderers[0],r=this._map_drag(e.sx,e.sy,s);if(null==r)return;const[_,d]=r,n=s.data_source,i=s.glyph,[l,h]=[i.xs.field,i.ys.field];if(\"new\"==t)this._pop_glyphs(n,this.model.num_objects),l&&n.get_array(l).push([_]),h&&n.get_array(h).push([d]),this._pad_empty_columns(n,[l,h]);else if(\"add\"==t){if(l){const e=n.data[l].length-1;let t=n.get_array(l)[e];(0,o.isArray)(t)||(t=Array.from(t),n.data[l][e]=t),t.push(_)}if(h){const e=n.data[h].length-1;let t=n.get_array(h)[e];(0,o.isArray)(t)||(t=Array.from(t),n.data[h][e]=t),t.push(d)}}this._emit_cds_changes(n,!0,!0,a)}_pan_start(e){this._draw(e,\"new\")}_pan(e){this._draw(e,\"add\")}_pan_end(e){this._draw(e,\"add\",!0)}_tap(e){this._select_event(e,this._select_mode(e),this.model.renderers)}_keyup(e){if(this.model.active&&this._mouse_in_frame)for(const t of this.model.renderers)e.keyCode===d.Keys.Esc?t.data_source.selection_manager.clear():e.keyCode===d.Keys.Backspace&&this._delete_selected(t)}}a.FreehandDrawToolView=l,l.__name__=\"FreehandDrawToolView\";class h extends n.EditTool{constructor(e){super(e),this.tool_name=\"Freehand Draw Tool\",this.icon=i.tool_icon_freehand_draw,this.event_type=[\"pan\",\"tap\"],this.default_order=3}}a.FreehandDrawTool=h,_=h,h.__name__=\"FreehandDrawTool\",_.prototype.default_view=l,_.define((({Int:e})=>({num_objects:[e,0]}))),_.register_alias(\"freehand_draw\",(()=>new h))},\n", - " function _(e,t,s,o,a){var i;o();const n=e(43),_=e(370),r=e(228);class d extends _.EditToolView{_tap(e){if(this._select_event(e,this._select_mode(e),this.model.renderers).length||!this.model.add)return;const t=this.model.renderers[0],s=this._map_drag(e.sx,e.sy,t);if(null==s)return;const o=t.glyph,a=t.data_source,[i,n]=[o.x.field,o.y.field],[_,r]=s;this._pop_glyphs(a,this.model.num_objects),i&&a.get_array(i).push(_),n&&a.get_array(n).push(r),this._pad_empty_columns(a,[i,n]),a.change.emit(),a.data=a.data,a.properties.data.change.emit()}_keyup(e){if(this.model.active&&this._mouse_in_frame)for(const t of this.model.renderers)e.keyCode===n.Keys.Backspace?this._delete_selected(t):e.keyCode==n.Keys.Esc&&t.data_source.selection_manager.clear()}_pan_start(e){this.model.drag&&(this._select_event(e,\"append\",this.model.renderers),this._basepoint=[e.sx,e.sy])}_pan(e){this.model.drag&&null!=this._basepoint&&this._drag_points(e,this.model.renderers)}_pan_end(e){if(this.model.drag){this._pan(e);for(const e of this.model.renderers)this._emit_cds_changes(e.data_source,!1,!0,!0);this._basepoint=null}}}s.PointDrawToolView=d,d.__name__=\"PointDrawToolView\";class l extends _.EditTool{constructor(e){super(e),this.tool_name=\"Point Draw Tool\",this.icon=r.tool_icon_point_draw,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=2}}s.PointDrawTool=l,i=l,l.__name__=\"PointDrawTool\",i.prototype.default_view=d,i.define((({Boolean:e,Int:t})=>({add:[e,!0],drag:[e,!0],num_objects:[t,0]})))},\n", - " function _(e,t,s,i,a){var r;i();const o=e(43),n=e(8),d=e(375),_=e(228);class h extends d.PolyToolView{constructor(){super(...arguments),this._drawing=!1,this._initialized=!1}_tap(e){this._drawing?this._draw(e,\"add\",!0):this._select_event(e,this._select_mode(e),this.model.renderers)}_draw(e,t,s=!1){const i=this.model.renderers[0],a=this._map_drag(e.sx,e.sy,i);if(this._initialized||this.activate(),null==a)return;const[r,o]=this._snap_to_vertex(e,...a),d=i.data_source,_=i.glyph,[h,l]=[_.xs.field,_.ys.field];if(\"new\"==t)this._pop_glyphs(d,this.model.num_objects),h&&d.get_array(h).push([r,r]),l&&d.get_array(l).push([o,o]),this._pad_empty_columns(d,[h,l]);else if(\"edit\"==t){if(h){const e=d.data[h][d.data[h].length-1];e[e.length-1]=r}if(l){const e=d.data[l][d.data[l].length-1];e[e.length-1]=o}}else if(\"add\"==t){if(h){const e=d.data[h].length-1;let t=d.get_array(h)[e];const s=t[t.length-1];t[t.length-1]=r,(0,n.isArray)(t)||(t=Array.from(t),d.data[h][e]=t),t.push(s)}if(l){const e=d.data[l].length-1;let t=d.get_array(l)[e];const s=t[t.length-1];t[t.length-1]=o,(0,n.isArray)(t)||(t=Array.from(t),d.data[l][e]=t),t.push(s)}}this._emit_cds_changes(d,!0,!1,s)}_show_vertices(){if(!this.model.active)return;const e=[],t=[];for(let s=0;sthis._show_vertices()))}this._initialized=!0}}deactivate(){this._drawing&&(this._remove(),this._drawing=!1),this.model.vertex_renderer&&this._hide_vertices()}}s.PolyDrawToolView=h,h.__name__=\"PolyDrawToolView\";class l extends d.PolyTool{constructor(e){super(e),this.tool_name=\"Polygon Draw Tool\",this.icon=_.tool_icon_poly_draw,this.event_type=[\"pan\",\"tap\",\"move\"],this.default_order=3}}s.PolyDrawTool=l,r=l,l.__name__=\"PolyDrawTool\",r.prototype.default_view=h,r.define((({Boolean:e,Int:t})=>({drag:[e,!0],num_objects:[t,0]})))},\n", - " function _(e,r,t,s,o){var _;s();const d=e(8),i=e(370);class l extends i.EditToolView{_set_vertices(e,r){const t=this.model.vertex_renderer.glyph,s=this.model.vertex_renderer.data_source,[o,_]=[t.x.field,t.y.field];o&&((0,d.isArray)(e)?s.data[o]=e:t.x={value:e}),_&&((0,d.isArray)(r)?s.data[_]=r:t.y={value:r}),this._emit_cds_changes(s,!0,!0,!1)}_hide_vertices(){this._set_vertices([],[])}_snap_to_vertex(e,r,t){if(this.model.vertex_renderer){const s=this._select_event(e,\"replace\",[this.model.vertex_renderer]),o=this.model.vertex_renderer.data_source,_=this.model.vertex_renderer.glyph,[d,i]=[_.x.field,_.y.field];if(s.length){const e=o.selected.indices[0];d&&(r=o.data[d][e]),i&&(t=o.data[i][e]),o.selection_manager.clear()}}return[r,t]}}t.PolyToolView=l,l.__name__=\"PolyToolView\";class n extends i.EditTool{constructor(e){super(e)}}t.PolyTool=n,_=n,n.__name__=\"PolyTool\",_.define((({AnyRef:e})=>({vertex_renderer:[e()]})))},\n", - " function _(e,t,s,r,i){var _;r();const d=e(43),n=e(8),l=e(375),a=e(228);class c extends l.PolyToolView{constructor(){super(...arguments),this._drawing=!1,this._cur_index=null}_doubletap(e){if(!this.model.active)return;const t=this._map_drag(e.sx,e.sy,this.model.vertex_renderer);if(null==t)return;const[s,r]=t,i=this._select_event(e,\"replace\",[this.model.vertex_renderer]),_=this.model.vertex_renderer.data_source,d=this.model.vertex_renderer.glyph,[n,l]=[d.x.field,d.y.field];if(i.length&&null!=this._selected_renderer){const e=_.selected.indices[0];this._drawing?(this._drawing=!1,_.selection_manager.clear()):(_.selected.indices=[e+1],n&&_.get_array(n).splice(e+1,0,s),l&&_.get_array(l).splice(e+1,0,r),this._drawing=!0),_.change.emit(),this._emit_cds_changes(this._selected_renderer.data_source)}else this._show_vertices(e)}_show_vertices(e){if(!this.model.active)return;const t=this.model.renderers[0],s=()=>this._update_vertices(t),r=null==t?void 0:t.data_source,i=this._select_event(e,\"replace\",this.model.renderers);if(!i.length)return this._set_vertices([],[]),this._selected_renderer=null,this._drawing=!1,this._cur_index=null,void(null!=r&&r.disconnect(r.properties.data.change,s));null!=r&&r.connect(r.properties.data.change,s),this._cur_index=i[0].data_source.selected.indices[0],this._update_vertices(i[0])}_update_vertices(e){const t=e.glyph,s=e.data_source,r=this._cur_index,[i,_]=[t.xs.field,t.ys.field];if(this._drawing)return;if(null==r&&(i||_))return;let d,l;i&&null!=r?(d=s.data[i][r],(0,n.isArray)(d)||(s.data[i][r]=d=Array.from(d))):d=t.xs.value,_&&null!=r?(l=s.data[_][r],(0,n.isArray)(l)||(s.data[_][r]=l=Array.from(l))):l=t.ys.value,this._selected_renderer=e,this._set_vertices(d,l)}_move(e){if(this._drawing&&null!=this._selected_renderer){const t=this.model.vertex_renderer,s=t.data_source,r=t.glyph,i=this._map_drag(e.sx,e.sy,t);if(null==i)return;let[_,d]=i;const n=s.selected.indices;[_,d]=this._snap_to_vertex(e,_,d),s.selected.indices=n;const[l,a]=[r.x.field,r.y.field],c=n[0];l&&(s.data[l][c]=_),a&&(s.data[a][c]=d),s.change.emit(),this._selected_renderer.data_source.change.emit()}}_tap(e){const t=this.model.vertex_renderer,s=this._map_drag(e.sx,e.sy,t);if(null==s)return;if(this._drawing&&this._selected_renderer){let[r,i]=s;const _=t.data_source,d=t.glyph,[n,l]=[d.x.field,d.y.field],a=_.selected.indices;[r,i]=this._snap_to_vertex(e,r,i);const c=a[0];if(_.selected.indices=[c+1],n){const e=_.get_array(n),t=e[c];e[c]=r,e.splice(c+1,0,t)}if(l){const e=_.get_array(l),t=e[c];e[c]=i,e.splice(c+1,0,t)}return _.change.emit(),void this._emit_cds_changes(this._selected_renderer.data_source,!0,!1,!0)}const r=this._select_mode(e);this._select_event(e,r,[t]),this._select_event(e,r,this.model.renderers)}_remove_vertex(){if(!this._drawing||!this._selected_renderer)return;const e=this.model.vertex_renderer,t=e.data_source,s=e.glyph,r=t.selected.indices[0],[i,_]=[s.x.field,s.y.field];i&&t.get_array(i).splice(r,1),_&&t.get_array(_).splice(r,1),t.change.emit(),this._emit_cds_changes(this._selected_renderer.data_source)}_pan_start(e){this._select_event(e,\"append\",[this.model.vertex_renderer]),this._basepoint=[e.sx,e.sy]}_pan(e){null!=this._basepoint&&(this._drag_points(e,[this.model.vertex_renderer]),this._selected_renderer&&this._selected_renderer.data_source.change.emit())}_pan_end(e){null!=this._basepoint&&(this._drag_points(e,[this.model.vertex_renderer]),this._emit_cds_changes(this.model.vertex_renderer.data_source,!1,!0,!0),this._selected_renderer&&this._emit_cds_changes(this._selected_renderer.data_source),this._basepoint=null)}_keyup(e){if(!this.model.active||!this._mouse_in_frame)return;let t;t=this._selected_renderer?[this.model.vertex_renderer]:this.model.renderers;for(const s of t)e.keyCode===d.Keys.Backspace?(this._delete_selected(s),this._selected_renderer&&this._emit_cds_changes(this._selected_renderer.data_source)):e.keyCode==d.Keys.Esc&&(this._drawing?(this._remove_vertex(),this._drawing=!1):this._selected_renderer&&this._hide_vertices(),s.data_source.selection_manager.clear())}deactivate(){this._selected_renderer&&(this._drawing&&(this._remove_vertex(),this._drawing=!1),this._hide_vertices())}}s.PolyEditToolView=c,c.__name__=\"PolyEditToolView\";class o extends l.PolyTool{constructor(e){super(e),this.tool_name=\"Poly Edit Tool\",this.icon=a.tool_icon_poly_edit,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=4}}s.PolyEditTool=o,_=o,o.__name__=\"PolyEditTool\",_.prototype.default_view=c},\n", - " function _(e,t,o,s,i){var l;s();const n=e(378),_=e(116),c=e(20),r=e(228);class a extends n.SelectToolView{_compute_limits(e){const t=this.plot_view.frame,o=this.model.dimensions;let s=this._base_point;if(\"center\"==this.model.origin){const[t,o]=s,[i,l]=e;s=[t-(i-t),o-(l-o)]}return this.model._get_dim_limits(s,e,t,o)}_pan_start(e){const{sx:t,sy:o}=e;this._base_point=[t,o]}_pan(e){const{sx:t,sy:o}=e,s=[t,o],[i,l]=this._compute_limits(s);this.model.overlay.update({left:i[0],right:i[1],top:l[0],bottom:l[1]}),this.model.select_every_mousemove&&this._do_select(i,l,!1,this._select_mode(e))}_pan_end(e){const{sx:t,sy:o}=e,s=[t,o],[i,l]=this._compute_limits(s);this._do_select(i,l,!0,this._select_mode(e)),this.model.overlay.update({left:null,right:null,top:null,bottom:null}),this._base_point=null,this.plot_view.state.push(\"box_select\",{selection:this.plot_view.get_selection()})}_do_select([e,t],[o,s],i,l=\"replace\"){const n={type:\"rect\",sx0:e,sx1:t,sy0:o,sy1:s};this._select(n,i,l)}}o.BoxSelectToolView=a,a.__name__=\"BoxSelectToolView\";const h=()=>new _.BoxAnnotation({level:\"overlay\",top_units:\"screen\",left_units:\"screen\",bottom_units:\"screen\",right_units:\"screen\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:2,line_dash:[4,4]});class m extends n.SelectTool{constructor(e){super(e),this.tool_name=\"Box Select\",this.icon=r.tool_icon_box_select,this.event_type=\"pan\",this.default_order=30}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}o.BoxSelectTool=m,l=m,m.__name__=\"BoxSelectTool\",l.prototype.default_view=a,l.define((({Boolean:e,Ref:t})=>({dimensions:[c.Dimensions,\"both\"],select_every_mousemove:[e,!1],overlay:[t(_.BoxAnnotation),h],origin:[c.BoxOrigin,\"corner\"]}))),l.register_alias(\"box_select\",(()=>new m)),l.register_alias(\"xbox_select\",(()=>new m({dimensions:\"width\"}))),l.register_alias(\"ybox_select\",(()=>new m({dimensions:\"height\"})))},\n", - " function _(e,t,s,n,r){var o;n();const c=e(223),i=e(175),a=e(339),l=e(176),d=e(66),_=e(20),h=e(43),p=e(251),u=e(15),m=e(11);class v extends c.GestureToolView{connect_signals(){super.connect_signals(),this.model.clear.connect((()=>this._clear()))}get computed_renderers(){const{renderers:e,names:t}=this.model,s=this.plot_model.data_renderers;return(0,d.compute_renderers)(e,s,t)}_computed_renderers_by_data_source(){var e;const t=new Map;for(const s of this.computed_renderers){let n;if(s instanceof i.GlyphRenderer)n=s.data_source;else{if(!(s instanceof a.GraphRenderer))continue;n=s.node_renderer.data_source}const r=null!==(e=t.get(n))&&void 0!==e?e:[];t.set(n,[...r,s])}return t}_select_mode(e){const{shiftKey:t,ctrlKey:s}=e;return t||s?t&&!s?\"append\":!t&&s?\"intersect\":t&&s?\"subtract\":void(0,m.unreachable)():this.model.mode}_keyup(e){e.keyCode==h.Keys.Esc&&this._clear()}_clear(){for(const e of this.computed_renderers)e.get_selection_manager().clear();const e=this.computed_renderers.map((e=>this.plot_view.renderer_view(e)));this.plot_view.request_paint(e)}_select(e,t,s){const n=this._computed_renderers_by_data_source();for(const[,r]of n){const n=r[0].get_selection_manager(),o=[];for(const e of r){const t=this.plot_view.renderer_view(e);null!=t&&o.push(t)}n.select(o,e,t,s)}null!=this.model.callback&&this._emit_callback(e),this._emit_selection_event(e,t)}_emit_selection_event(e,t=!0){const{x_scale:s,y_scale:n}=this.plot_view.frame;let r;switch(e.type){case\"point\":{const{sx:t,sy:o}=e,c=s.invert(t),i=n.invert(o);r=Object.assign(Object.assign({},e),{x:c,y:i});break}case\"span\":{const{sx:t,sy:o}=e,c=s.invert(t),i=n.invert(o);r=Object.assign(Object.assign({},e),{x:c,y:i});break}case\"rect\":{const{sx0:t,sx1:o,sy0:c,sy1:i}=e,[a,l]=s.r_invert(t,o),[d,_]=n.r_invert(c,i);r=Object.assign(Object.assign({},e),{x0:a,y0:d,x1:l,y1:_});break}case\"poly\":{const{sx:t,sy:o}=e,c=s.v_invert(t),i=n.v_invert(o);r=Object.assign(Object.assign({},e),{x:c,y:i});break}}this.plot_model.trigger_event(new p.SelectionGeometry(r,t))}}s.SelectToolView=v,v.__name__=\"SelectToolView\";class b extends c.GestureTool{constructor(e){super(e)}initialize(){super.initialize(),this.clear=new u.Signal0(this,\"clear\")}get menu(){return[{icon:\"bk-tool-icon-replace-mode\",tooltip:\"Replace the current selection\",active:()=>\"replace\"==this.mode,handler:()=>{this.mode=\"replace\",this.active=!0}},{icon:\"bk-tool-icon-append-mode\",tooltip:\"Append to the current selection (Shift)\",active:()=>\"append\"==this.mode,handler:()=>{this.mode=\"append\",this.active=!0}},{icon:\"bk-tool-icon-intersect-mode\",tooltip:\"Intersect with the current selection (Ctrl)\",active:()=>\"intersect\"==this.mode,handler:()=>{this.mode=\"intersect\",this.active=!0}},{icon:\"bk-tool-icon-subtract-mode\",tooltip:\"Subtract from the current selection (Shift+Ctrl)\",active:()=>\"subtract\"==this.mode,handler:()=>{this.mode=\"subtract\",this.active=!0}},null,{icon:\"bk-tool-icon-clear-selection\",tooltip:\"Clear the current selection (Esc)\",handler:()=>{this.clear.emit()}}]}}s.SelectTool=b,o=b,b.__name__=\"SelectTool\",o.define((({String:e,Array:t,Ref:s,Or:n,Auto:r})=>({renderers:[n(t(s(l.DataRenderer)),r),\"auto\"],names:[t(e),[]],mode:[_.SelectionMode,\"replace\"]})))},\n", - " function _(t,o,e,s,i){var n;s();const _=t(223),a=t(116),l=t(20),r=t(228);class h extends _.GestureToolView{_match_aspect(t,o,e){const s=e.bbox.aspect,i=e.bbox.h_range.end,n=e.bbox.h_range.start,_=e.bbox.v_range.end,a=e.bbox.v_range.start;let l=Math.abs(t[0]-o[0]),r=Math.abs(t[1]-o[1]);const h=0==r?0:l/r,[c]=h>=s?[1,h/s]:[s/h,1];let m,p,d,b;return t[0]<=o[0]?(m=t[0],p=t[0]+l*c,p>i&&(p=i)):(p=t[0],m=t[0]-l*c,m_&&(d=_)):(d=t[1],b=t[1]-l/s,bnew a.BoxAnnotation({level:\"overlay\",top_units:\"screen\",left_units:\"screen\",bottom_units:\"screen\",right_units:\"screen\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:2,line_dash:[4,4]});class m extends _.GestureTool{constructor(t){super(t),this.tool_name=\"Box Zoom\",this.icon=r.tool_icon_box_zoom,this.event_type=\"pan\",this.default_order=20}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}e.BoxZoomTool=m,n=m,m.__name__=\"BoxZoomTool\",n.prototype.default_view=h,n.define((({Boolean:t,Ref:o})=>({dimensions:[l.Dimensions,\"both\"],overlay:[o(a.BoxAnnotation),c],match_aspect:[t,!1],origin:[l.BoxOrigin,\"corner\"]}))),n.register_alias(\"box_zoom\",(()=>new m({dimensions:\"both\"}))),n.register_alias(\"xbox_zoom\",(()=>new m({dimensions:\"width\"}))),n.register_alias(\"ybox_zoom\",(()=>new m({dimensions:\"height\"})))},\n", - " function _(s,e,t,o,_){var l;o();const i=s(378),a=s(217),c=s(381),n=s(43),h=s(228);class r extends i.SelectToolView{constructor(){super(...arguments),this.sxs=[],this.sys=[]}connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,(()=>this._active_change()))}_active_change(){this.model.active||this._clear_overlay()}_keyup(s){s.keyCode==n.Keys.Enter&&this._clear_overlay()}_pan_start(s){this.sxs=[],this.sys=[];const{sx:e,sy:t}=s;this._append_overlay(e,t)}_pan(s){const[e,t]=this.plot_view.frame.bbox.clip(s.sx,s.sy);this._append_overlay(e,t),this.model.select_every_mousemove&&this._do_select(this.sxs,this.sys,!1,this._select_mode(s))}_pan_end(s){const{sxs:e,sys:t}=this;this._clear_overlay(),this._do_select(e,t,!0,this._select_mode(s)),this.plot_view.state.push(\"lasso_select\",{selection:this.plot_view.get_selection()})}_append_overlay(s,e){const{sxs:t,sys:o}=this;t.push(s),o.push(e),this.model.overlay.update({xs:t,ys:o})}_clear_overlay(){this.sxs=[],this.sys=[],this.model.overlay.update({xs:this.sxs,ys:this.sys})}_do_select(s,e,t,o){const _={type:\"poly\",sx:s,sy:e};this._select(_,t,o)}}t.LassoSelectToolView=r,r.__name__=\"LassoSelectToolView\";class y extends i.SelectTool{constructor(s){super(s),this.tool_name=\"Lasso Select\",this.icon=h.tool_icon_lasso_select,this.event_type=\"pan\",this.default_order=12}}t.LassoSelectTool=y,l=y,y.__name__=\"LassoSelectTool\",l.prototype.default_view=r,l.define((({Boolean:s,Ref:e})=>({select_every_mousemove:[s,!0],overlay:[e(a.PolyAnnotation),c.DEFAULT_POLY_OVERLAY]}))),l.register_alias(\"lasso_select\",(()=>new y))},\n", - " function _(e,t,s,l,o){var i;l();const a=e(378),_=e(217),c=e(43),n=e(9),h=e(228);class y extends a.SelectToolView{initialize(){super.initialize(),this.data={sx:[],sy:[]}}connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,(()=>this._active_change()))}_active_change(){this.model.active||this._clear_data()}_keyup(e){e.keyCode==c.Keys.Enter&&this._clear_data()}_doubletap(e){this._do_select(this.data.sx,this.data.sy,!0,this._select_mode(e)),this.plot_view.state.push(\"poly_select\",{selection:this.plot_view.get_selection()}),this._clear_data()}_clear_data(){this.data={sx:[],sy:[]},this.model.overlay.update({xs:[],ys:[]})}_tap(e){const{sx:t,sy:s}=e;this.plot_view.frame.bbox.contains(t,s)&&(this.data.sx.push(t),this.data.sy.push(s),this.model.overlay.update({xs:(0,n.copy)(this.data.sx),ys:(0,n.copy)(this.data.sy)}))}_do_select(e,t,s,l){const o={type:\"poly\",sx:e,sy:t};this._select(o,s,l)}}s.PolySelectToolView=y,y.__name__=\"PolySelectToolView\";s.DEFAULT_POLY_OVERLAY=()=>new _.PolyAnnotation({level:\"overlay\",xs_units:\"screen\",ys_units:\"screen\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:2,line_dash:[4,4]});class d extends a.SelectTool{constructor(e){super(e),this.tool_name=\"Poly Select\",this.icon=h.tool_icon_polygon_select,this.event_type=\"tap\",this.default_order=11}}s.PolySelectTool=d,i=d,d.__name__=\"PolySelectTool\",i.prototype.default_view=y,i.define((({Ref:e})=>({overlay:[e(_.PolyAnnotation),s.DEFAULT_POLY_OVERLAY]}))),i.register_alias(\"poly_select\",(()=>new d))},\n", - " function _(e,t,s,i,r){var n;i();const _=e(20),d=e(383),o=e(228);class l extends d.LineToolView{constructor(){super(...arguments),this._drawing=!1}_doubletap(e){if(!this.model.active)return;const t=this.model.renderers;for(const s of t){1==this._select_event(e,\"replace\",[s]).length&&(this._selected_renderer=s)}this._show_intersections(),this._update_line_cds()}_show_intersections(){if(!this.model.active)return;if(null==this._selected_renderer)return;if(!this.model.renderers.length)return this._set_intersection([],[]),this._selected_renderer=null,void(this._drawing=!1);const e=this._selected_renderer.data_source,t=this._selected_renderer.glyph,[s,i]=[t.x.field,t.y.field],r=e.get_array(s),n=e.get_array(i);this._set_intersection(r,n)}_tap(e){const t=this.model.intersection_renderer;if(null==this._map_drag(e.sx,e.sy,t))return;if(this._drawing&&this._selected_renderer){const s=this._select_mode(e);if(0==this._select_event(e,s,[t]).length)return}const s=this._select_mode(e);this._select_event(e,s,[t]),this._select_event(e,s,this.model.renderers)}_update_line_cds(){if(null==this._selected_renderer)return;const e=this.model.intersection_renderer.glyph,t=this.model.intersection_renderer.data_source,[s,i]=[e.x.field,e.y.field];if(s&&i){const e=t.data[s],r=t.data[i];this._selected_renderer.data_source.data[s]=e,this._selected_renderer.data_source.data[i]=r}this._emit_cds_changes(this._selected_renderer.data_source,!0,!0,!1)}_pan_start(e){this._select_event(e,\"append\",[this.model.intersection_renderer]),this._basepoint=[e.sx,e.sy]}_pan(e){null!=this._basepoint&&(this._drag_points(e,[this.model.intersection_renderer],this.model.dimensions),this._selected_renderer&&this._selected_renderer.data_source.change.emit())}_pan_end(e){null!=this._basepoint&&(this._drag_points(e,[this.model.intersection_renderer]),this._emit_cds_changes(this.model.intersection_renderer.data_source,!1,!0,!0),this._selected_renderer&&this._emit_cds_changes(this._selected_renderer.data_source),this._basepoint=null)}activate(){this._drawing=!0}deactivate(){this._selected_renderer&&(this._drawing&&(this._drawing=!1),this._hide_intersections())}}s.LineEditToolView=l,l.__name__=\"LineEditToolView\";class h extends d.LineTool{constructor(e){super(e),this.tool_name=\"Line Edit Tool\",this.icon=o.tool_icon_line_edit,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=4}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}s.LineEditTool=h,n=h,h.__name__=\"LineEditTool\",n.prototype.default_view=l,n.define((()=>({dimensions:[_.Dimensions,\"both\"]})))},\n", - " function _(e,i,n,t,s){var o;t();const r=e(8),_=e(370);class d extends _.EditToolView{_set_intersection(e,i){const n=this.model.intersection_renderer.glyph,t=this.model.intersection_renderer.data_source,[s,o]=[n.x.field,n.y.field];s&&((0,r.isArray)(e)?t.data[s]=e:n.x={value:e}),o&&((0,r.isArray)(i)?t.data[o]=i:n.y={value:i}),this._emit_cds_changes(t,!0,!0,!1)}_hide_intersections(){this._set_intersection([],[])}}n.LineToolView=d,d.__name__=\"LineToolView\";class a extends _.EditTool{constructor(e){super(e)}}n.LineTool=a,o=a,a.__name__=\"LineTool\",o.define((({AnyRef:e})=>({intersection_renderer:[e()]})))},\n", - " function _(t,s,n,e,i){e();const o=t(1);var a;const _=t(223),l=t(20),r=(0,o.__importStar)(t(228));function h(t,s,n){const e=new Map;for(const[i,o]of t){const[t,a]=o.r_invert(s,n);e.set(i,{start:t,end:a})}return e}n.update_ranges=h;class d extends _.GestureToolView{_pan_start(t){var s;this.last_dx=0,this.last_dy=0;const{sx:n,sy:e}=t,i=this.plot_view.frame.bbox;if(!i.contains(n,e)){const t=i.h_range,s=i.v_range;(nt.end)&&(this.v_axis_only=!0),(es.end)&&(this.h_axis_only=!0)}null===(s=this.model.document)||void 0===s||s.interactive_start(this.plot_model)}_pan(t){var s;this._update(t.deltaX,t.deltaY),null===(s=this.model.document)||void 0===s||s.interactive_start(this.plot_model)}_pan_end(t){this.h_axis_only=!1,this.v_axis_only=!1,null!=this.pan_info&&this.plot_view.state.push(\"pan\",{range:this.pan_info}),this.plot_view.trigger_ranges_update_event()}_update(t,s){const n=this.plot_view.frame,e=t-this.last_dx,i=s-this.last_dy,o=n.bbox.h_range,a=o.start-e,_=o.end-e,l=n.bbox.v_range,r=l.start-i,d=l.end-i,p=this.model.dimensions;let c,u,m,v,x,g;\"width\"!=p&&\"both\"!=p||this.v_axis_only?(c=o.start,u=o.end,m=0):(c=a,u=_,m=-e),\"height\"!=p&&\"both\"!=p||this.h_axis_only?(v=l.start,x=l.end,g=0):(v=r,x=d,g=-i),this.last_dx=t,this.last_dy=s;const{x_scales:w,y_scales:y}=n,f=h(w,c,u),b=h(y,v,x);this.pan_info={xrs:f,yrs:b,sdx:m,sdy:g},this.plot_view.update_range(this.pan_info,{panning:!0})}}n.PanToolView=d,d.__name__=\"PanToolView\";class p extends _.GestureTool{constructor(t){super(t),this.tool_name=\"Pan\",this.event_type=\"pan\",this.default_order=10}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}n.PanTool=p,a=p,p.__name__=\"PanTool\",a.prototype.default_view=d,a.define((()=>({dimensions:[l.Dimensions,\"both\",{on_update(t,s){switch(t){case\"both\":s.icon=r.tool_icon_pan;break;case\"width\":s.icon=r.tool_icon_xpan;break;case\"height\":s.icon=r.tool_icon_ypan}}}]}))),a.register_alias(\"pan\",(()=>new p({dimensions:\"both\"}))),a.register_alias(\"xpan\",(()=>new p({dimensions:\"width\"}))),a.register_alias(\"ypan\",(()=>new p({dimensions:\"height\"})))},\n", - " function _(e,t,i,s,n){var l;s();const a=e(116),r=e(58),o=e(19),_=e(223),h=e(228);function d(e){switch(e){case 1:return 2;case 2:return 1;case 4:return 5;case 5:return 4;default:return e}}function u(e,t,i,s){if(null==t)return!1;const n=i.compute(t);return Math.abs(e-n)n.right)&&(l=!1)}if(null!=n.bottom&&null!=n.top){const e=s.invert(t);(en.top)&&(l=!1)}return l}function g(e,t,i){let s=0;return e>=i.start&&e<=i.end&&(s+=1),t>=i.start&&t<=i.end&&(s+=1),s}function y(e,t,i,s){const n=t.compute(e),l=t.invert(n+i);return l>=s.start&&l<=s.end?l:e}function f(e,t,i){return e>t.start?(t.end=e,i):(t.end=t.start,t.start=e,d(i))}function v(e,t,i){return e=o&&(e.start=a,e.end=r)}i.flip_side=d,i.is_near=u,i.is_inside=c,i.sides_inside=g,i.compute_value=y,i.update_range_end_side=f,i.update_range_start_side=v,i.update_range=m;class p extends _.GestureToolView{initialize(){super.initialize(),this.side=0,this.model.update_overlay_from_ranges()}connect_signals(){super.connect_signals(),null!=this.model.x_range&&this.connect(this.model.x_range.change,(()=>this.model.update_overlay_from_ranges())),null!=this.model.y_range&&this.connect(this.model.y_range.change,(()=>this.model.update_overlay_from_ranges()))}_pan_start(e){this.last_dx=0,this.last_dy=0;const t=this.model.x_range,i=this.model.y_range,{frame:s}=this.plot_view,n=s.x_scale,l=s.y_scale,r=this.model.overlay,{left:o,right:_,top:h,bottom:d}=r,g=this.model.overlay.line_width+a.EDGE_TOLERANCE;null!=t&&this.model.x_interaction&&(u(e.sx,o,n,g)?this.side=1:u(e.sx,_,n,g)?this.side=2:c(e.sx,e.sy,n,l,r)&&(this.side=3)),null!=i&&this.model.y_interaction&&(0==this.side&&u(e.sy,d,l,g)&&(this.side=4),0==this.side&&u(e.sy,h,l,g)?this.side=5:c(e.sx,e.sy,n,l,this.model.overlay)&&(3==this.side?this.side=7:this.side=6))}_pan(e){const t=this.plot_view.frame,i=e.deltaX-this.last_dx,s=e.deltaY-this.last_dy,n=this.model.x_range,l=this.model.y_range,a=t.x_scale,r=t.y_scale;if(null!=n)if(3==this.side||7==this.side)m(n,a,i,t.x_range);else if(1==this.side){const e=y(n.start,a,i,t.x_range);this.side=v(e,n,this.side)}else if(2==this.side){const e=y(n.end,a,i,t.x_range);this.side=f(e,n,this.side)}if(null!=l)if(6==this.side||7==this.side)m(l,r,s,t.y_range);else if(4==this.side){const e=y(l.start,r,s,t.y_range);this.side=v(e,l,this.side)}else if(5==this.side){const e=y(l.end,r,s,t.y_range);this.side=f(e,l,this.side)}this.last_dx=e.deltaX,this.last_dy=e.deltaY}_pan_end(e){this.side=0,this.plot_view.trigger_ranges_update_event()}}i.RangeToolView=p,p.__name__=\"RangeToolView\";const x=()=>new a.BoxAnnotation({level:\"overlay\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:.5,line_dash:[2,2]});class w extends _.GestureTool{constructor(e){super(e),this.tool_name=\"Range Tool\",this.icon=h.tool_icon_range,this.event_type=\"pan\",this.default_order=1}initialize(){super.initialize(),this.overlay.in_cursor=\"grab\",this.overlay.ew_cursor=null!=this.x_range&&this.x_interaction?\"ew-resize\":null,this.overlay.ns_cursor=null!=this.y_range&&this.y_interaction?\"ns-resize\":null}update_overlay_from_ranges(){null==this.x_range&&null==this.y_range&&(this.overlay.left=null,this.overlay.right=null,this.overlay.bottom=null,this.overlay.top=null,o.logger.warn(\"RangeTool not configured with any Ranges.\")),null==this.x_range?(this.overlay.left=null,this.overlay.right=null):(this.overlay.left=this.x_range.start,this.overlay.right=this.x_range.end),null==this.y_range?(this.overlay.bottom=null,this.overlay.top=null):(this.overlay.bottom=this.y_range.start,this.overlay.top=this.y_range.end)}}i.RangeTool=w,l=w,w.__name__=\"RangeTool\",l.prototype.default_view=p,l.define((({Boolean:e,Ref:t,Nullable:i})=>({x_range:[i(t(r.Range1d)),null],x_interaction:[e,!0],y_range:[i(t(r.Range1d)),null],y_interaction:[e,!0],overlay:[t(a.BoxAnnotation),x]})))},\n", - " function _(e,t,s,o,i){var l;o();const a=e(378),n=e(20),c=e(228);class _ extends a.SelectToolView{_tap(e){\"tap\"==this.model.gesture&&this._handle_tap(e)}_doubletap(e){\"doubletap\"==this.model.gesture&&this._handle_tap(e)}_handle_tap(e){const{sx:t,sy:s}=e,o={type:\"point\",sx:t,sy:s};this._select(o,!0,this._select_mode(e))}_select(e,t,s){const{callback:o}=this.model;if(\"select\"==this.model.behavior){const i=this._computed_renderers_by_data_source();for(const[,l]of i){const i=l[0].get_selection_manager(),a=l.map((e=>this.plot_view.renderer_view(e))).filter((e=>null!=e));if(i.select(a,e,t,s)&&null!=o){const t=a[0].coordinates.x_scale.invert(e.sx),s=a[0].coordinates.y_scale.invert(e.sy),l={geometries:Object.assign(Object.assign({},e),{x:t,y:s}),source:i.source};o.execute(this.model,l)}}this._emit_selection_event(e),this.plot_view.state.push(\"tap\",{selection:this.plot_view.get_selection()})}else for(const t of this.computed_renderers){const s=this.plot_view.renderer_view(t);if(null==s)continue;const i=t.get_selection_manager();if(i.inspect(s,e)&&null!=o){const t=s.coordinates.x_scale.invert(e.sx),l=s.coordinates.y_scale.invert(e.sy),a={geometries:Object.assign(Object.assign({},e),{x:t,y:l}),source:i.source};o.execute(this.model,a)}}}}s.TapToolView=_,_.__name__=\"TapToolView\";class r extends a.SelectTool{constructor(e){super(e),this.tool_name=\"Tap\",this.icon=c.tool_icon_tap_select,this.event_type=\"tap\",this.default_order=10}}s.TapTool=r,l=r,r.__name__=\"TapTool\",l.prototype.default_view=_,l.define((({Any:e,Enum:t,Nullable:s})=>({behavior:[n.TapBehavior,\"select\"],gesture:[t(\"tap\",\"doubletap\"),\"tap\"],callback:[s(e)]}))),l.register_alias(\"click\",(()=>new r({behavior:\"inspect\"}))),l.register_alias(\"tap\",(()=>new r)),l.register_alias(\"doubletap\",(()=>new r({gesture:\"doubletap\"})))},\n", - " function _(e,t,s,n,i){var a;n();const o=e(223),l=e(20),_=e(228),r=e(384);class h extends o.GestureToolView{_scroll(e){let t=this.model.speed*e.delta;t>.9?t=.9:t<-.9&&(t=-.9),this._update_ranges(t)}_update_ranges(e){var t;const{frame:s}=this.plot_view,n=s.bbox.h_range,i=s.bbox.v_range,[a,o]=[n.start,n.end],[l,_]=[i.start,i.end];let h,d,p,c;switch(this.model.dimension){case\"height\":{const t=Math.abs(_-l);h=a,d=o,p=l-t*e,c=_-t*e;break}case\"width\":{const t=Math.abs(o-a);h=a-t*e,d=o-t*e,p=l,c=_;break}}const{x_scales:g,y_scales:u}=s,w={xrs:(0,r.update_ranges)(g,h,d),yrs:(0,r.update_ranges)(u,p,c),factor:e};this.plot_view.state.push(\"wheel_pan\",{range:w}),this.plot_view.update_range(w,{scrolling:!0}),null===(t=this.model.document)||void 0===t||t.interactive_start(this.plot_model,(()=>this.plot_view.trigger_ranges_update_event()))}}s.WheelPanToolView=h,h.__name__=\"WheelPanToolView\";class d extends o.GestureTool{constructor(e){super(e),this.tool_name=\"Wheel Pan\",this.icon=_.tool_icon_wheel_pan,this.event_type=\"scroll\",this.default_order=12}get tooltip(){return this._get_dim_tooltip(this.dimension)}}s.WheelPanTool=d,a=d,d.__name__=\"WheelPanTool\",a.prototype.default_view=h,a.define((()=>({dimension:[l.Dimension,\"width\"]}))),a.internal((({Number:e})=>({speed:[e,.001]}))),a.register_alias(\"xwheel_pan\",(()=>new d({dimension:\"width\"}))),a.register_alias(\"ywheel_pan\",(()=>new d({dimension:\"height\"})))},\n", - " function _(e,o,t,s,i){var n;s();const l=e(223),_=e(368),h=e(20),a=e(27),r=e(228);class m extends l.GestureToolView{_pinch(e){const{sx:o,sy:t,scale:s,ctrlKey:i,shiftKey:n}=e;let l;l=s>=1?20*(s-1):-20/s,this._scroll({type:\"wheel\",sx:o,sy:t,delta:l,ctrlKey:i,shiftKey:n})}_scroll(e){var o;const{frame:t}=this.plot_view,s=t.bbox.h_range,i=t.bbox.v_range,{sx:n,sy:l}=e,h=this.model.dimensions,a=(\"width\"==h||\"both\"==h)&&s.startthis.plot_view.trigger_ranges_update_event()))}}t.WheelZoomToolView=m,m.__name__=\"WheelZoomToolView\";class d extends l.GestureTool{constructor(e){super(e),this.tool_name=\"Wheel Zoom\",this.icon=r.tool_icon_wheel_zoom,this.event_type=a.is_mobile?\"pinch\":\"scroll\",this.default_order=10}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}t.WheelZoomTool=d,n=d,d.__name__=\"WheelZoomTool\",n.prototype.default_view=m,n.define((({Boolean:e,Number:o})=>({dimensions:[h.Dimensions,\"both\"],maintain_focus:[e,!0],zoom_on_axis:[e,!0],speed:[o,1/600]}))),n.register_alias(\"wheel_zoom\",(()=>new d({dimensions:\"both\"}))),n.register_alias(\"xwheel_zoom\",(()=>new d({dimensions:\"width\"}))),n.register_alias(\"ywheel_zoom\",(()=>new d({dimensions:\"height\"})))},\n", - " function _(i,e,s,t,o){var n;t();const l=i(232),a=i(219),h=i(20),r=i(13),_=i(228);class c extends l.InspectToolView{_move(i){if(!this.model.active)return;const{sx:e,sy:s}=i;this.plot_view.frame.bbox.contains(e,s)?this._update_spans(e,s):this._update_spans(null,null)}_move_exit(i){this._update_spans(null,null)}_update_spans(i,e){const s=this.model.dimensions;\"width\"!=s&&\"both\"!=s||(this.model.spans.width.location=e),\"height\"!=s&&\"both\"!=s||(this.model.spans.height.location=i)}}s.CrosshairToolView=c,c.__name__=\"CrosshairToolView\";class p extends l.InspectTool{constructor(i){super(i),this.tool_name=\"Crosshair\",this.icon=_.tool_icon_crosshair}get tooltip(){return this._get_dim_tooltip(this.dimensions)}get synthetic_renderers(){return(0,r.values)(this.spans)}}s.CrosshairTool=p,n=p,p.__name__=\"CrosshairTool\",(()=>{function i(i,e){return new a.Span({for_hover:!0,dimension:e,location_units:\"screen\",level:\"overlay\",line_color:i.line_color,line_width:i.line_width,line_alpha:i.line_alpha})}n.prototype.default_view=c,n.define((({Alpha:i,Number:e,Color:s})=>({dimensions:[h.Dimensions,\"both\"],line_color:[s,\"black\"],line_width:[e,1],line_alpha:[i,1]}))),n.internal((({Struct:e,Ref:s})=>({spans:[e({width:s(a.Span),height:s(a.Span)}),e=>({width:i(e,\"width\"),height:i(e,\"height\")})]}))),n.register_alias(\"crosshair\",(()=>new p))})()},\n", - " function _(e,s,t,r,n){var o;r();const a=e(53),u=e(13),c=e(34);class i extends a.Model{constructor(e){super(e)}get values(){return(0,u.values)(this.args)}_make_code(e,s,t,r){return new Function(...(0,u.keys)(this.args),e,s,t,(0,c.use_strict)(r))}format(e,s,t){return this._make_code(\"value\",\"format\",\"special_vars\",this.code)(...this.values,e,s,t)}}t.CustomJSHover=i,o=i,i.__name__=\"CustomJSHover\",o.define((({Unknown:e,String:s,Dict:t})=>({args:[t(e),{}],code:[s,\"\"]})))},\n", - " function _(e,t,n,s,o){s();const i=e(1);var r;const l=e(232),a=e(390),c=e(241),_=e(175),d=e(339),p=e(176),h=e(177),u=e(283),m=(0,i.__importStar)(e(185)),y=e(152),f=e(43),v=e(22),x=e(13),w=e(234),g=e(8),b=e(113),k=e(20),C=e(228),S=e(15),T=e(66),$=(0,i.__importStar)(e(242)),R=e(392);function M(e,t,n,s,o,i){const r={x:o[e],y:i[e]},l={x:o[e+1],y:i[e+1]};let a,c;if(\"span\"==t.type)\"h\"==t.direction?(a=Math.abs(r.x-n),c=Math.abs(l.x-n)):(a=Math.abs(r.y-s),c=Math.abs(l.y-s));else{const e={x:n,y:s};a=m.dist_2_pts(r,e),c=m.dist_2_pts(l,e)}return adelete this._template_el)),this.on_change([e,t,n],(async()=>await this._update_ttmodels()))}async _update_ttmodels(){const{_ttmodels:e,computed_renderers:t}=this;e.clear();const{tooltips:n}=this.model;if(null!=n)for(const t of this.computed_renderers){const s=new c.Tooltip({custom:(0,g.isString)(n)||(0,g.isFunction)(n),attachment:this.model.attachment,show_arrow:this.model.show_arrow});t instanceof _.GlyphRenderer?e.set(t,s):t instanceof d.GraphRenderer&&(e.set(t.node_renderer,s),e.set(t.edge_renderer,s))}const s=await(0,b.build_views)(this._ttviews,[...e.values()],{parent:this.plot_view});for(const e of s)e.render();const o=[...function*(){for(const e of t)e instanceof _.GlyphRenderer?yield e:e instanceof d.GraphRenderer&&(yield e.node_renderer,yield e.edge_renderer)}()],i=this._slots.get(this._update);if(null!=i){const e=new Set(o.map((e=>e.data_source)));S.Signal.disconnect_receiver(this,i,e)}for(const e of o)this.connect(e.data_source.inspect,this._update)}get computed_renderers(){const{renderers:e,names:t}=this.model,n=this.plot_model.data_renderers;return(0,T.compute_renderers)(e,n,t)}get ttmodels(){return this._ttmodels}_clear(){this._inspect(1/0,1/0);for(const[,e]of this.ttmodels)e.clear()}_move(e){if(!this.model.active)return;const{sx:t,sy:n}=e;this.plot_view.frame.bbox.contains(t,n)?this._inspect(t,n):this._clear()}_move_exit(){this._clear()}_inspect(e,t){let n;if(\"mouse\"==this.model.mode)n={type:\"point\",sx:e,sy:t};else{n={type:\"span\",direction:\"vline\"==this.model.mode?\"h\":\"v\",sx:e,sy:t}}for(const e of this.computed_renderers){const t=e.get_selection_manager(),s=this.plot_view.renderer_view(e);null!=s&&t.inspect(s,n)}this._emit_callback(n)}_update([e,{geometry:t}]){var n,s;if(!this.model.active)return;if(\"point\"!=t.type&&\"span\"!=t.type)return;if(!(e instanceof _.GlyphRenderer))return;if(\"ignore\"==this.model.muted_policy&&e.muted)return;const o=this.ttmodels.get(e);if(null==o)return;const i=e.get_selection_manager(),r=i.inspectors.get(e),l=e.view.convert_selection_to_subset(r);if(r.is_empty())return void o.clear();const a=i.source,c=this.plot_view.renderer_view(e);if(null==c)return;const{sx:d,sy:p}=t,m=c.coordinates.x_scale,y=c.coordinates.y_scale,v=m.invert(d),w=y.invert(p),{glyph:g}=c,b=[];if(g instanceof h.LineView)for(const n of l.line_indices){let s,o,i=g._x[n+1],r=g._y[n+1],c=n;switch(this.model.line_policy){case\"interp\":[i,r]=g.get_interpolation_hit(n,t),s=m.compute(i),o=y.compute(r);break;case\"prev\":[[s,o],c]=G(g.sx,g.sy,n);break;case\"next\":[[s,o],c]=G(g.sx,g.sy,n+1);break;case\"nearest\":[[s,o],c]=M(n,t,d,p,g.sx,g.sy),i=g._x[c],r=g._y[c];break;default:[s,o]=[d,p]}const _={index:c,x:v,y:w,sx:d,sy:p,data_x:i,data_y:r,rx:s,ry:o,indices:l.line_indices,name:e.name};b.push([s,o,this._render_tooltips(a,c,_)])}for(const t of r.image_indices){const n={index:t.index,x:v,y:w,sx:d,sy:p,name:e.name},s=this._render_tooltips(a,t,n);b.push([d,p,s])}for(const o of l.indices)if(g instanceof u.MultiLineView&&!(0,x.isEmpty)(l.multiline_indices))for(const n of l.multiline_indices[o.toString()]){let s,i,r,c=g._xs.get(o)[n],h=g._ys.get(o)[n],u=n;switch(this.model.line_policy){case\"interp\":[c,h]=g.get_interpolation_hit(o,n,t),s=m.compute(c),i=y.compute(h);break;case\"prev\":[[s,i],u]=G(g.sxs.get(o),g.sys.get(o),n);break;case\"next\":[[s,i],u]=G(g.sxs.get(o),g.sys.get(o),n+1);break;case\"nearest\":[[s,i],u]=M(n,t,d,p,g.sxs.get(o),g.sys.get(o)),c=g._xs.get(o)[u],h=g._ys.get(o)[u];break;default:throw new Error(\"shouldn't have happened\")}r=e instanceof _.GlyphRenderer?e.view.convert_indices_from_subset([o])[0]:o;const f={index:r,x:v,y:w,sx:d,sy:p,data_x:c,data_y:h,segment_index:u,indices:l.multiline_indices,name:e.name};b.push([s,i,this._render_tooltips(a,r,f)])}else{const t=null===(n=g._x)||void 0===n?void 0:n[o],i=null===(s=g._y)||void 0===s?void 0:s[o];let r,c,h;if(\"snap_to_data\"==this.model.point_policy){let e=g.get_anchor_point(this.model.anchor,o,[d,p]);if(null==e&&(e=g.get_anchor_point(\"center\",o,[d,p]),null==e))continue;r=e.x,c=e.y}else[r,c]=[d,p];h=e instanceof _.GlyphRenderer?e.view.convert_indices_from_subset([o])[0]:o;const u={index:h,x:v,y:w,sx:d,sy:p,data_x:t,data_y:i,indices:l.indices,name:e.name};b.push([r,c,this._render_tooltips(a,h,u)])}if(0==b.length)o.clear();else{const{content:e}=o;(0,f.empty)(o.content);for(const[,,t]of b)null!=t&&e.appendChild(t);const[t,n]=b[b.length-1];o.setv({position:[t,n]},{check_eq:!1})}}_emit_callback(e){const{callback:t}=this.model;if(null!=t)for(const n of this.computed_renderers){if(!(n instanceof _.GlyphRenderer))continue;const s=this.plot_view.renderer_view(n);if(null==s)continue;const{x_scale:o,y_scale:i}=s.coordinates,r=o.invert(e.sx),l=i.invert(e.sy),a=n.data_source.inspected;t.execute(this.model,{geometry:Object.assign({x:r,y:l},e),renderer:n,index:a})}}_create_template(e){const t=(0,f.div)({style:{display:\"table\",borderSpacing:\"2px\"}});for(const[n]of e){const e=(0,f.div)({style:{display:\"table-row\"}});t.appendChild(e);const s=(0,f.div)({style:{display:\"table-cell\"},class:$.tooltip_row_label},0!=n.length?`${n}: `:\"\");e.appendChild(s);const o=(0,f.span)();o.dataset.value=\"\";const i=(0,f.span)({class:$.tooltip_color_block},\" \");i.dataset.swatch=\"\",(0,f.undisplay)(i);const r=(0,f.div)({style:{display:\"table-cell\"},class:$.tooltip_row_value},o,i);e.appendChild(r)}return t}_render_template(e,t,n,s,o){const i=e.cloneNode(!0),r=i.querySelectorAll(\"[data-value]\"),l=i.querySelectorAll(\"[data-swatch]\"),a=/\\$color(\\[.*\\])?:(\\w*)/,c=/\\$swatch:(\\w*)/;for(const[[,e],i]of(0,w.enumerate)(t)){const t=e.match(c),_=e.match(a);if(null!=t||null!=_){if(null!=t){const[,e]=t,o=n.get_column(e);if(null==o)r[i].textContent=`${e} unknown`;else{const e=(0,g.isNumber)(s)?o[s]:null;null!=e&&(l[i].style.backgroundColor=(0,v.color2css)(e),(0,f.display)(l[i]))}}if(null!=_){const[,e=\"\",t]=_,o=n.get_column(t);if(null==o){r[i].textContent=`${t} unknown`;continue}const a=e.indexOf(\"hex\")>=0,c=e.indexOf(\"swatch\")>=0,d=(0,g.isNumber)(s)?o[s]:null;if(null==d){r[i].textContent=\"(null)\";continue}r[i].textContent=a?(0,v.color2hex)(d):(0,v.color2css)(d),c&&(l[i].style.backgroundColor=(0,v.color2css)(d),(0,f.display)(l[i]))}}else{const t=(0,y.replace_placeholders)(e.replace(\"$~\",\"$data_\"),n,s,this.model.formatters,o);if((0,g.isString)(t))r[i].textContent=t;else for(const e of t)r[i].appendChild(e)}}return i}_render_tooltips(e,t,n){var s;const{tooltips:o}=this.model;if((0,g.isString)(o)){const s=(0,y.replace_placeholders)({html:o},e,t,this.model.formatters,n);return(0,f.div)(s)}if((0,g.isFunction)(o))return o(e,n);if(o instanceof R.Template)return this._template_view.update(e,t,n),this._template_view.el;if(null!=o){const i=null!==(s=this._template_el)&&void 0!==s?s:this._template_el=this._create_template(o);return this._render_template(i,o,e,t,n)}return null}}n.HoverToolView=z,z.__name__=\"HoverToolView\";class A extends l.InspectTool{constructor(e){super(e),this.tool_name=\"Hover\",this.icon=C.tool_icon_hover}}n.HoverTool=A,r=A,A.__name__=\"HoverTool\",r.prototype.default_view=z,r.define((({Any:e,Boolean:t,String:n,Array:s,Tuple:o,Dict:i,Or:r,Ref:l,Function:c,Auto:_,Nullable:d})=>({tooltips:[d(r(l(R.Template),n,s(o(n,n)),c())),[[\"index\",\"$index\"],[\"data (x, y)\",\"($x, $y)\"],[\"screen (x, y)\",\"($sx, $sy)\"]]],formatters:[i(r(l(a.CustomJSHover),y.FormatterType)),{}],renderers:[r(s(l(p.DataRenderer)),_),\"auto\"],names:[s(n),[]],mode:[k.HoverMode,\"mouse\"],muted_policy:[k.MutedPolicy,\"show\"],point_policy:[k.PointPolicy,\"snap_to_data\"],line_policy:[k.LinePolicy,\"nearest\"],show_arrow:[t,!0],anchor:[k.Anchor,\"center\"],attachment:[k.TooltipAttachment,\"horizontal\"],callback:[d(e)]}))),r.register_alias(\"hover\",(()=>new A))},\n", - " function _(e,t,s,n,a){n();const l=e(1);var i,_,o,r,c,d,p,u,m,w,f,h,x;const v=e(53),y=e(309),V=e(393);a(\"Styles\",V.Styles);const g=e(43),T=e(42),b=e(226),R=e(113),D=e(8),M=e(13),S=(0,l.__importStar)(e(242)),O=e(152);class C extends b.DOMView{}s.DOMNodeView=C,C.__name__=\"DOMNodeView\";class z extends v.Model{constructor(e){super(e)}}s.DOMNode=z,z.__name__=\"DOMNode\",z.__module__=\"bokeh.models.dom\";class P extends C{render(){super.render(),this.el.textContent=this.model.content}_createElement(){return document.createTextNode(\"\")}}s.TextView=P,P.__name__=\"TextView\";class A extends z{constructor(e){super(e)}}s.Text=A,i=A,A.__name__=\"Text\",i.prototype.default_view=P,i.define((({String:e})=>({content:[e,\"\"]})));class N extends C{}s.PlaceholderView=N,N.__name__=\"PlaceholderView\",N.tag_name=\"span\";class E extends z{constructor(e){super(e)}}s.Placeholder=E,_=E,E.__name__=\"Placeholder\",_.define((({})=>({})));class G extends N{update(e,t,s){this.el.textContent=t.toString()}}s.IndexView=G,G.__name__=\"IndexView\";class I extends E{constructor(e){super(e)}}s.Index=I,o=I,I.__name__=\"Index\",o.prototype.default_view=G,o.define((({})=>({})));class k extends N{update(e,t,s){const n=(0,O._get_column_value)(this.model.field,e,t),a=null==n?\"???\":`${n}`;this.el.textContent=a}}s.ValueRefView=k,k.__name__=\"ValueRefView\";class $ extends E{constructor(e){super(e)}}s.ValueRef=$,r=$,$.__name__=\"ValueRef\",r.prototype.default_view=k,r.define((({String:e})=>({field:[e]})));class B extends k{render(){super.render(),this.value_el=(0,g.span)(),this.swatch_el=(0,g.span)({class:S.tooltip_color_block},\" \"),this.el.appendChild(this.value_el),this.el.appendChild(this.swatch_el)}update(e,t,s){const n=(0,O._get_column_value)(this.model.field,e,t),a=null==n?\"???\":`${n}`;this.el.textContent=a}}s.ColorRefView=B,B.__name__=\"ColorRefView\";class L extends ${constructor(e){super(e)}}s.ColorRef=L,c=L,L.__name__=\"ColorRef\",c.prototype.default_view=B,c.define((({Boolean:e})=>({hex:[e,!0],swatch:[e,!0]})));class j extends C{constructor(){super(...arguments),this.child_views=new Map}async lazy_initialize(){await super.lazy_initialize();const e=this.model.children.filter((e=>e instanceof v.Model));await(0,R.build_views)(this.child_views,e,{parent:this})}render(){super.render();const{style:e}=this.model;if(null!=e)if(e instanceof V.Styles)for(const t of e){const e=t.get_value();if((0,D.isString)(e)){const s=t.attr.replace(/_/g,\"-\");this.el.style.hasOwnProperty(s)&&this.el.style.setProperty(s,e)}}else for(const[t,s]of(0,M.entries)(e)){const e=t.replace(/_/g,\"-\");this.el.style.hasOwnProperty(e)&&this.el.style.setProperty(e,s)}for(const e of this.model.children)if((0,D.isString)(e)){const t=document.createTextNode(e);this.el.appendChild(t)}else{this.child_views.get(e).renderTo(this.el)}}}s.DOMElementView=j,j.__name__=\"DOMElementView\";class q extends z{constructor(e){super(e)}}s.DOMElement=q,d=q,q.__name__=\"DOMElement\",d.define((({String:e,Array:t,Dict:s,Or:n,Nullable:a,Ref:l})=>({style:[a(n(l(V.Styles),s(e))),null],children:[t(n(e,l(z),l(y.LayoutDOM))),[]]})));class F extends T.View{}s.ActionView=F,F.__name__=\"ActionView\";class H extends v.Model{constructor(e){super(e)}}s.Action=H,p=H,H.__name__=\"Action\",H.__module__=\"bokeh.models.dom\",p.define((({})=>({})));class J extends j{constructor(){super(...arguments),this.action_views=new Map}async lazy_initialize(){await super.lazy_initialize(),await(0,R.build_views)(this.action_views,this.model.actions,{parent:this})}remove(){(0,R.remove_views)(this.action_views),super.remove()}update(e,t,s={}){!function n(a){for(const l of a.child_views.values())l instanceof N?l.update(e,t,s):l instanceof j&&n(l)}(this);for(const n of this.action_views.values())n.update(e,t,s)}}s.TemplateView=J,J.__name__=\"TemplateView\",J.tag_name=\"div\";class K extends q{}s.Template=K,u=K,K.__name__=\"Template\",u.prototype.default_view=J,u.define((({Array:e,Ref:t})=>({actions:[e(t(H)),[]]})));class Q extends j{}s.SpanView=Q,Q.__name__=\"SpanView\",Q.tag_name=\"span\";class U extends q{}s.Span=U,m=U,U.__name__=\"Span\",m.prototype.default_view=Q;class W extends j{}s.DivView=W,W.__name__=\"DivView\",W.tag_name=\"div\";class X extends q{}s.Div=X,w=X,X.__name__=\"Div\",w.prototype.default_view=W;class Y extends j{}s.TableView=Y,Y.__name__=\"TableView\",Y.tag_name=\"table\";class Z extends q{}s.Table=Z,f=Z,Z.__name__=\"Table\",f.prototype.default_view=Y;class ee extends j{}s.TableRowView=ee,ee.__name__=\"TableRowView\",ee.tag_name=\"tr\";class te extends q{}s.TableRow=te,h=te,te.__name__=\"TableRow\",h.prototype.default_view=ee;const se=e(41),ne=e(234);class ae extends F{update(e,t,s){for(const[e,s]of(0,ne.enumerate)(this.model.groups))e.visible=t==s}}s.ToggleGroupView=ae,ae.__name__=\"ToggleGroupView\";class le extends H{constructor(e){super(e)}}s.ToggleGroup=le,x=le,le.__name__=\"ToggleGroup\",x.prototype.default_view=ae,x.define((({Array:e,Ref:t})=>({groups:[e(t(se.RendererGroup)),[]]})))},\n", - " function _(l,n,u,_,e){var t;_();const o=l(53);class r extends 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- " function _(t,o,e,n,s){var i;n();const l=t(15),c=t(53),r=t(224),a=t(232),u=t(234);class h extends c.Model{constructor(t){super(t)}get button_view(){return this.tools[0].button_view}get event_type(){return this.tools[0].event_type}get tooltip(){return this.tools[0].tooltip}get tool_name(){return this.tools[0].tool_name}get icon(){return this.tools[0].computed_icon}get computed_icon(){return this.icon}get toggleable(){const t=this.tools[0];return t instanceof a.InspectTool&&t.toggleable}initialize(){super.initialize(),this.do=new l.Signal0(this,\"do\")}connect_signals(){super.connect_signals(),this.connect(this.do,(()=>this.doit())),this.connect(this.properties.active.change,(()=>this.set_active()));for(const t of this.tools)this.connect(t.properties.active.change,(()=>{this.active=t.active}))}doit(){for(const t of this.tools)t.do.emit()}set_active(){for(const t of this.tools)t.active=this.active}get menu(){const{menu:t}=this.tools[0];if(null==t)return null;const o=[];for(const[e,n]of(0,u.enumerate)(t))if(null==e)o.push(null);else{const t=()=>{var t,o,e;for(const s of this.tools)null===(e=null===(o=null===(t=s.menu)||void 0===t?void 0:t[n])||void 0===o?void 0:o.handler)||void 0===e||e.call(o)};o.push(Object.assign(Object.assign({},e),{handler:t}))}return o}}e.ToolProxy=h,i=h,h.__name__=\"ToolProxy\",i.define((({Boolean:t,Array:o,Ref:e})=>({tools:[o(e(r.ButtonTool)),[]],active:[t,!1],disabled:[t,!1]})))},\n", - " function _(o,t,s,e,i){var n,r;e();const l=o(20),c=o(9),h=o(13),a=o(233),_=o(221),p=o(394),u=o(309),f=o(207);class y extends a.ToolbarBase{constructor(o){super(o)}initialize(){super.initialize(),this._merge_tools()}_merge_tools(){this._proxied_tools=[];const o={},t={},s={},e=[],i=[];for(const o of this.help)(0,c.includes)(i,o.redirect)||(e.push(o),i.push(o.redirect));this._proxied_tools.push(...e),this.help=e;for(const[o,t]of(0,h.entries)(this.gestures)){o in s||(s[o]={});for(const e of t.tools)e.type in s[o]||(s[o][e.type]=[]),s[o][e.type].push(e)}for(const t of this.inspectors)t.type in o||(o[t.type]=[]),o[t.type].push(t);for(const o of this.actions)o.type in t||(t[o.type]=[]),t[o.type].push(o);const n=(o,t=!1)=>{const s=new p.ToolProxy({tools:o,active:t});return this._proxied_tools.push(s),s};for(const o of(0,h.keys)(s)){const t=this.gestures[o];t.tools=[];for(const e of(0,h.keys)(s[o])){const i=s[o][e];if(i.length>0)if(\"multi\"==o)for(const o of i){const s=n([o]);t.tools.push(s),this.connect(s.properties.active.change,(()=>this._active_change(s)))}else{const o=n(i);t.tools.push(o),this.connect(o.properties.active.change,(()=>this._active_change(o)))}}}this.actions=[];for(const[o,s]of(0,h.entries)(t))if(\"CustomAction\"==o)for(const o of s)this.actions.push(n([o]));else s.length>0&&this.actions.push(n(s));this.inspectors=[];for(const t of(0,h.values)(o))t.length>0&&this.inspectors.push(n(t,!0));for(const[o,t]of(0,h.entries)(this.gestures))0!=t.tools.length&&(t.tools=(0,c.sort_by)(t.tools,(o=>o.default_order)),\"pinch\"!=o&&\"scroll\"!=o&&\"multi\"!=o&&(t.tools[0].active=!0))}}s.ProxyToolbar=y,n=y,y.__name__=\"ProxyToolbar\",n.define((({Array:o,Ref:t})=>({toolbars:[o(t(_.Toolbar)),[]]})));class d extends u.LayoutDOMView{initialize(){this.model.toolbar.toolbar_location=this.model.toolbar_location,super.initialize()}get child_models(){return[this.model.toolbar]}_update_layout(){this.layout=new f.ContentBox(this.child_views[0].el);const{toolbar:o}=this.model;o.horizontal?this.layout.set_sizing({width_policy:\"fit\",min_width:100,height_policy:\"fixed\"}):this.layout.set_sizing({width_policy:\"fixed\",height_policy:\"fit\",min_height:100})}after_layout(){super.after_layout();const o=this.child_views[0];o.layout.bbox=this.layout.bbox,o.render()}}s.ToolbarBoxView=d,d.__name__=\"ToolbarBoxView\";class b extends u.LayoutDOM{constructor(o){super(o)}}s.ToolbarBox=b,r=b,b.__name__=\"ToolbarBox\",r.prototype.default_view=d,r.define((({Ref:o})=>({toolbar:[o(a.ToolbarBase)],toolbar_location:[l.Location,\"right\"]})))},\n", - " function _(e,n,r,t,o){t();const s=e(1),u=e(53),c=(0,s.__importStar)(e(21)),a=e(8),l=e(13);r.resolve_defs=function(e,n){var r,t,o,s;function i(e){return null!=e.module?`${e.module}.${e.name}`:e.name}function f(e){if((0,a.isString)(e))switch(e){case\"Any\":return c.Any;case\"Unknown\":return c.Unknown;case\"Boolean\":return c.Boolean;case\"Number\":return c.Number;case\"Int\":return c.Int;case\"String\":return c.String;case\"Null\":return c.Null}else switch(e[0]){case\"Nullable\":{const[,n]=e;return c.Nullable(f(n))}case\"Or\":{const[,...n]=e;return c.Or(...n.map(f))}case\"Tuple\":{const[,n,...r]=e;return c.Tuple(f(n),...r.map(f))}case\"Array\":{const[,n]=e;return c.Array(f(n))}case\"Struct\":{const[,...n]=e,r=n.map((([e,n])=>[e,f(n)]));return c.Struct((0,l.to_object)(r))}case\"Dict\":{const[,n]=e;return c.Dict(f(n))}case\"Map\":{const[,n,r]=e;return c.Map(f(n),f(r))}case\"Enum\":{const[,...n]=e;return c.Enum(...n)}case\"Ref\":{const[,r]=e,t=n.get(i(r));if(null!=t)return c.Ref(t);throw new Error(`${i(r)} wasn't defined before referencing it`)}case\"AnyRef\":return c.AnyRef()}}for(const c of e){const e=(()=>{if(null==c.extends)return u.Model;{const e=n.get(i(c.extends));if(null!=e)return e;throw new Error(`base model ${i(c.extends)} of ${i(c)} is not defined`)}})(),a=((s=class extends e{}).__name__=c.name,s.__module__=c.module,s);for(const e of null!==(r=c.properties)&&void 0!==r?r:[]){const n=f(null!==(t=e.kind)&&void 0!==t?t:\"Unknown\");a.define({[e.name]:[n,e.default]})}for(const e of null!==(o=c.overrides)&&void 0!==o?o:[])a.override({[e.name]:e.default});n.register(a)}}},\n", - " function _(n,e,t,o,i){o();const d=n(5),c=n(226),s=n(113),a=n(43),l=n(398);t.index={},t.add_document_standalone=async function(n,e,o=[],i=!1){const u=new Map;async function f(i){let d;const f=n.roots().indexOf(i),r=o[f];null!=r?d=r:e.classList.contains(l.BOKEH_ROOT)?d=e:(d=(0,a.div)({class:l.BOKEH_ROOT}),e.appendChild(d));const w=await(0,s.build_view)(i,{parent:null});return w instanceof c.DOMView&&w.renderTo(d),u.set(i,w),t.index[i.id]=w,w}for(const e of n.roots())await f(e);return i&&(window.document.title=n.title()),n.on_change((n=>{n instanceof d.RootAddedEvent?f(n.model):n instanceof d.RootRemovedEvent?function(n){const e=u.get(n);null!=e&&(e.remove(),u.delete(n),delete t.index[n.id])}(n.model):i&&n instanceof d.TitleChangedEvent&&(window.document.title=n.title)})),[...u.values()]}},\n", - " function _(o,e,n,t,r){t();const l=o(43),d=o(44);function u(o){let e=document.getElementById(o);if(null==e)throw new Error(`Error rendering Bokeh model: could not find #${o} HTML tag`);if(!document.body.contains(e))throw new Error(`Error rendering Bokeh model: element #${o} must be under `);if(\"SCRIPT\"==e.tagName){const o=(0,l.div)({class:n.BOKEH_ROOT});(0,l.replaceWith)(e,o),e=o}return e}n.BOKEH_ROOT=d.root,n._resolve_element=function(o){const{elementid:e}=o;return null!=e?u(e):document.body},n._resolve_root_elements=function(o){const e=[];if(null!=o.root_ids&&null!=o.roots)for(const n of o.root_ids)e.push(u(o.roots[n]));return e}},\n", - " function _(n,o,t,s,e){s();const c=n(400),r=n(19),a=n(397);t._get_ws_url=function(n,o){let t,s=\"ws:\";return\"https:\"==window.location.protocol&&(s=\"wss:\"),null!=o?(t=document.createElement(\"a\"),t.href=o):t=window.location,null!=n?\"/\"==n&&(n=\"\"):n=t.pathname.replace(/\\/+$/,\"\"),`${s}//${t.host}${n}/ws`};const i={};t.add_document_from_session=async function(n,o,t,s=[],e=!1){const l=window.location.search.substr(1);let d;try{d=await function(n,o,t){const s=(0,c.parse_token)(o).session_id;n in i||(i[n]={});const e=i[n];return s in e||(e[s]=(0,c.pull_session)(n,o,t)),e[s]}(n,o,l)}catch(n){const t=(0,c.parse_token)(o).session_id;throw r.logger.error(`Failed to load Bokeh session ${t}: ${n}`),n}return(0,a.add_document_standalone)(d.document,t,s,e)}},\n", - " function _(e,s,n,t,o){t();const r=e(19),i=e(5),c=e(401),l=e(402),_=e(403);n.DEFAULT_SERVER_WEBSOCKET_URL=\"ws://localhost:5006/ws\",n.DEFAULT_TOKEN=\"eyJzZXNzaW9uX2lkIjogImRlZmF1bHQifQ\";let h=0;function a(e){let s=e.split(\".\")[0];const n=s.length%4;return 0!=n&&(s+=\"=\".repeat(4-n)),JSON.parse(atob(s.replace(/_/g,\"/\").replace(/-/g,\"+\")))}n.parse_token=a;class d{constructor(e=n.DEFAULT_SERVER_WEBSOCKET_URL,s=n.DEFAULT_TOKEN,t=null){this.url=e,this.token=s,this.args_string=t,this._number=h++,this.socket=null,this.session=null,this.closed_permanently=!1,this._current_handler=null,this._pending_replies=new Map,this._pending_messages=[],this._receiver=new l.Receiver,this.id=a(s).session_id.split(\".\")[0],r.logger.debug(`Creating websocket ${this._number} to '${this.url}' session '${this.id}'`)}async connect(){if(this.closed_permanently)throw new Error(\"Cannot connect() a closed ClientConnection\");if(null!=this.socket)throw new Error(\"Already connected\");this._current_handler=null,this._pending_replies.clear(),this._pending_messages=[];try{let e=`${this.url}`;return null!=this.args_string&&this.args_string.length>0&&(e+=`?${this.args_string}`),this.socket=new WebSocket(e,[\"bokeh\",this.token]),new Promise(((e,s)=>{this.socket.binaryType=\"arraybuffer\",this.socket.onopen=()=>this._on_open(e,s),this.socket.onmessage=e=>this._on_message(e),this.socket.onclose=e=>this._on_close(e,s),this.socket.onerror=()=>this._on_error(s)}))}catch(e){throw r.logger.error(`websocket creation failed to url: ${this.url}`),r.logger.error(` - ${e}`),e}}close(){this.closed_permanently||(r.logger.debug(`Permanently closing websocket connection ${this._number}`),this.closed_permanently=!0,null!=this.socket&&this.socket.close(1e3,`close method called on ClientConnection ${this._number}`),this.session._connection_closed())}_schedule_reconnect(e){setTimeout((()=>{this.closed_permanently||r.logger.info(`Websocket connection ${this._number} disconnected, will not attempt to reconnect`)}),e)}send(e){if(null==this.socket)throw new Error(`not connected so cannot send ${e}`);e.send(this.socket)}async send_with_reply(e){const s=await new Promise(((s,n)=>{this._pending_replies.set(e.msgid(),{resolve:s,reject:n}),this.send(e)}));if(\"ERROR\"===s.msgtype())throw new Error(`Error reply ${s.content.text}`);return s}async _pull_doc_json(){const e=c.Message.create(\"PULL-DOC-REQ\",{}),s=await this.send_with_reply(e);if(!(\"doc\"in s.content))throw new Error(\"No 'doc' field in PULL-DOC-REPLY\");return s.content.doc}async _repull_session_doc(e,s){var n;r.logger.debug(this.session?\"Repulling session\":\"Pulling session for first time\");try{const n=await this._pull_doc_json();if(null==this.session)if(this.closed_permanently)r.logger.debug(\"Got new document after connection was already closed\"),s(new Error(\"The connection has been closed\"));else{const s=i.Document.from_json(n),t=i.Document._compute_patch_since_json(n,s);if(t.events.length>0){r.logger.debug(`Sending ${t.events.length} changes from model construction back to server`);const e=c.Message.create(\"PATCH-DOC\",{},t);this.send(e)}this.session=new _.ClientSession(this,s,this.id);for(const e of this._pending_messages)this.session.handle(e);this._pending_messages=[],r.logger.debug(\"Created a new session from new pulled doc\"),e(this.session)}else this.session.document.replace_with_json(n),r.logger.debug(\"Updated existing session with new pulled doc\")}catch(e){null===(n=console.trace)||void 0===n||n.call(console,e),r.logger.error(`Failed to repull session ${e}`),s(e instanceof Error?e:`${e}`)}}_on_open(e,s){r.logger.info(`Websocket connection ${this._number} is now 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t.def(e.shared.vao,\".currentVAO?\",e.shared.vao,\".currentVAO.count:-1\")}));return m}return null}(),h=l(br,!1);return{elements:s,primitive:m,count:p,instances:h,offset:d,vao:f,vaoActive:i,elementsActive:u,static:a}}(e,d),A=function(e,t){var r=e.static,n=e.dynamic,i={};return k.forEach((function(e){var o=E(e);function f(t,a){if(e in r){var f=t(r[e]);i[o]=an((function(){return f}))}else if(e in n){var u=n[e];i[o]=on(u,(function(e,t){return a(e,t,e.invoke(t,u))}))}}switch(e){case Nt:case It:case Vt:case er:case Mt:case ir:case Xt:case Kt:case Jt:case Gt:return f((function(r){return _.commandType(r,\"boolean\",e,t.commandStr),r}),(function(t,r,n){return _.optional((function(){t.assert(r,\"typeof \"+n+'===\"boolean\"',\"invalid flag \"+e,t.commandStr)})),n}));case Wt:return f((function(r){return _.commandParameter(r,$r,\"invalid \"+e,t.commandStr),$r[r]}),(function(t,r,n){var a=t.constants.compareFuncs;return _.optional((function(){t.assert(r,n+\" in \"+a,\"invalid \"+e+\", must be one of 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_.optional((function(){e.assert(t,e.shared.isArrayLike+\"(\"+r+\")&&\"+r+\".length===4\",\"blend.color must be a 4d array\")})),V(4,(function(e){return t.def(\"+\",r,\"[\",e,\"]\")}))}));case tr:return f((function(e){return _.commandType(e,\"number\",o,t.commandStr),0|e}),(function(e,t,r){return _.optional((function(){e.assert(t,\"typeof \"+r+'===\"number\"',\"invalid stencil.mask\")})),t.def(r,\"|0\")}));case rr:return f((function(r){_.commandType(r,\"object\",o,t.commandStr);var n=r.cmp||\"keep\",a=r.ref||0,i=\"mask\"in r?r.mask:-1;return _.commandParameter(n,$r,e+\".cmp\",t.commandStr),_.commandType(a,\"number\",e+\".ref\",t.commandStr),_.commandType(i,\"number\",e+\".mask\",t.commandStr),[$r[n],a,i]}),(function(e,t,r){var n=e.constants.compareFuncs;return _.optional((function(){function a(){e.assert(t,Array.prototype.join.call(arguments,\"\"),\"invalid stencil.func\")}a(r+\"&&typeof \",r,'===\"object\"'),a('!(\"cmp\" in ',r,\")||(\",r,\".cmp in \",n,\")\")})),[t.def('\"cmp\" in 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_.commandType(r,\"number\",o+\".factor\",t.commandStr),_.commandType(n,\"number\",o+\".units\",t.commandStr),[r,n]}),(function(t,r,n){return _.optional((function(){t.assert(r,n+\"&&typeof \"+n+'===\"object\"',\"invalid \"+e)})),[r.def(n,\".factor|0\"),r.def(n,\".units|0\")]}));case qt:return f((function(e){var r=0;return\"front\"===e?r=Hr:\"back\"===e&&(r=Nr),_.command(!!r,o,t.commandStr),r}),(function(e,t,r){return _.optional((function(){e.assert(t,r+'===\"front\"||'+r+'===\"back\"',\"invalid cull.face\")})),t.def(r,'===\"front\"?',Hr,\":\",Nr)}));case Yt:return f((function(e){return _.command(\"number\"==typeof e&&e>=a.lineWidthDims[0]&&e<=a.lineWidthDims[1],\"invalid line width, must be a positive number between \"+a.lineWidthDims[0]+\" and \"+a.lineWidthDims[1],t.commandStr),e}),(function(e,t,r){return _.optional((function(){e.assert(t,\"typeof \"+r+'===\"number\"&&'+r+\">=\"+a.lineWidthDims[0]+\"&&\"+r+\"<=\"+a.lineWidthDims[1],\"invalid line width\")})),r}));case Qt:return f((function(e){return _.commandParameter(e,Zr,o,t.commandStr),Zr[e]}),(function(e,t,r){return _.optional((function(){e.assert(t,r+'===\"cw\"||'+r+'===\"ccw\"',\"invalid frontFace, must be one of cw,ccw\")})),t.def(r+'===\"cw\"?2304:'+qr)}));case Ht:return f((function(e){return _.command(me(e)&&4===e.length,\"color.mask must be length 4 array\",t.commandStr),e.map((function(e){return!!e}))}),(function(e,t,r){return _.optional((function(){e.assert(t,e.shared.isArrayLike+\"(\"+r+\")&&\"+r+\".length===4\",\"invalid color.mask\")})),V(4,(function(e){return\"!!\"+r+\"[\"+e+\"]\"}))}));case Zt:return f((function(e){_.command(\"object\"==typeof e&&e,o,t.commandStr);var r=\"value\"in e?e.value:1,n=!!e.invert;return _.command(\"number\"==typeof r&&r>=0&&r<=1,\"sample.coverage.value must be a number between 0 and 1\",t.commandStr),[r,n]}),(function(e,t,r){return _.optional((function(){e.assert(t,r+\"&&typeof \"+r+'===\"object\"',\"invalid sample.coverage\")})),[t.def('\"value\" in 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t=x[e];t&&(A[e]=t)}O(fr),O(E(or));var T=Object.keys(A).length>0,D={framebuffer:y,draw:w,shader:S,state:A,dirty:T,scopeVAO:null,drawVAO:null,useVAO:!1,attributes:{}};if(D.profile=function(e){var t,r=e.static,n=e.dynamic;if(ur in r){var a=!!r[ur];(t=an((function(e,t){return a}))).enable=a}else if(ur in n){var i=n[ur];t=on(i,(function(e,t){return e.invoke(t,i)}))}return t}(e),D.uniforms=function(e,t){var r=e.static,n=e.dynamic,a={};return Object.keys(r).forEach((function(e){var n,i=r[e];if(\"number\"==typeof i||\"boolean\"==typeof i)n=an((function(){return i}));else if(\"function\"==typeof i){var o=i._reglType;\"texture2d\"===o||\"textureCube\"===o?n=an((function(e){return e.link(i)})):\"framebuffer\"===o||\"framebufferCube\"===o?(_.command(i.color.length>0,'missing color attachment for framebuffer sent to uniform \"'+e+'\"',t.commandStr),n=an((function(e){return e.link(i.color[0])}))):_.commandRaise('invalid data for uniform \"'+e+'\"',t.commandStr)}else me(i)?n=an((function(t){return 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e=0;e=0},read:z,destroy:function(){I.length=0,le(),V&&(V.removeEventListener(cn,de),V.removeEventListener(ln,me)),k.clear(),E.clear(),O.clear(),A.clear(),S.clear(),w.clear(),x.clear(),m&&m.clear(),q.forEach((function(e){e()}))},_gl:a,_refresh:xe,poll:function(){ye(),m&&m.update()},now:we,stats:l});return n.onDone(null,Ae),Ae}},\"object\"==typeof r&&void 0!==t?t.exports=o():\"function\"==typeof define&&define.amd?define(o):i.createREGL=o()},\n", - " 413: function _(t,e,s,a,r){a();const n=t(414),_=t(12);class o{constructor(t){this._regl=t,this._map=new Map}_create_texture(t){const e=t.length;let s=0;const a=[];let r=0,_=0;for(let n=0;nc[f+1]&&f++;const a=t[f],n=c[f]+.5*a;let o=.5*a-Math.abs(s-n);f%2==1&&(o=-o),m[e]=Math.round(255*(o-r)/(_-r))}return[[s,u,r,_],this._regl.texture({shape:[l,1,1],data:m,wrapS:\"repeat\",format:\"alpha\",type:\"uint8\",mag:\"linear\",min:\"linear\"})]}_get_key(t){return t.join(\",\")}_get_or_create(t){const e=this._get_key(t);let s=this._map.get(e);if(null==s){const a=(0,n.gcd)(t);if(a>1){t=(0,_.map)(t,(t=>t/a)),s=this._get_or_create(t);const[r,n,o]=s;s=[r,n,a],this._map.set(e,s)}else{const[r,n]=this._create_texture(t);s=[r,n,a],this._map.set(e,s)}}return s}get(t){return t.length%2==1&&(t=t.slice(0,-1)),this._get_or_create(t)}}s.DashCache=o,o.__name__=\"DashCache\"},\n", - " 414: function _(n,t,e,r,o){function u(n,t){let e,r;n>t?(e=n,r=t):(e=t,r=n);let o=e%r;for(;0!=o;)e=r,r=o,o=e%r;return r}r(),e.gcd=function(n){let t=n[0];for(let e=1;e u_miter_limit);\\n miter_too_large_end = (miter_factor_end > u_miter_limit);\\n }\\n\\n float sign_at_start = -sign(a_position.x); // +ve at segment start, -ve end.\\n vec2 point = sign_at_start > 0.0 ? a_point_start : a_point_end;\\n vec2 adjacent_point =\\n sign_at_start > 0.0 ? (has_start_cap ? a_point_start : a_point_prev)\\n : (has_end_cap ? a_point_end : a_point_next);\\n\\n if ( (has_start_cap && sign_at_start > 0.0) ||\\n (has_end_cap && sign_at_start < 0.0) ) {\\n // Cap.\\n xy = point - segment_right*(halfwidth*a_position.y);\\n if (cap_type == butt_cap)\\n xy -= sign_at_start*0.5*u_antialias*segment_along;\\n else\\n xy -= sign_at_start*halfwidth*segment_along;\\n }\\n else { // Join.\\n // +ve if turning to right, -ve if to left.\\n float turn_sign = sign_at_start > 0.0 ? turn_right_start : turn_right_end;\\n\\n vec2 adjacent_right = sign_at_start*normalize(right_vector(point - adjacent_point));\\n vec2 point_right = normalize(segment_right + adjacent_right);\\n float miter_factor = sign_at_start > 0.0 ? miter_factor_start : miter_factor_end;\\n bool miter_too_large = sign_at_start > 0.0 ? miter_too_large_start : miter_too_large_end;\\n\\n if (abs(a_position.x) > 1.5) {\\n // Outer point, meets prev/next segment.\\n float factor; // multiplied by halfwidth...\\n\\n if (join_type == bevel_join || (join_type == miter_join && miter_too_large))\\n factor = 1.0 / miter_factor; // cos_theta.\\n else if (join_type == round_join &&\\n miter_factor > min_miter_factor_round_join_mesh)\\n factor = 1.0;\\n else // miter, or round (small angle only).\\n factor = miter_factor;\\n\\n xy = point - point_right*(halfwidth*turn_sign*factor);\\n v_coords.y = turn_sign*halfwidth*factor / miter_factor;\\n }\\n else if (turn_sign*a_position.y < 0.0) {\\n // Inner point, meets prev/next segment.\\n float len = halfwidth*miter_factor;\\n float segment_len = v_segment_length;\\n float adjacent_len = distance(point, adjacent_point);\\n\\n if (len <= min(segment_len, adjacent_len))\\n // Normal behaviour.\\n xy = point - point_right*(len*a_position.y);\\n else\\n // For short wide line segments the inner point using the above\\n // calculation can be outside of the line. Here clipping it.\\n xy = point + segment_right*(halfwidth*turn_sign);\\n }\\n else {\\n // Point along outside edge.\\n xy = point - segment_right*(halfwidth*a_position.y);\\n if (join_type == round_join &&\\n miter_factor > min_miter_factor_round_join_mesh) {\\n xy = line_intersection(xy, segment_along,\\n point - turn_sign*point_right*halfwidth,\\n right_vector(point_right));\\n }\\n }\\n }\\n\\n vec2 pos = xy + 0.5; // Bokeh's offset.\\n pos /= u_canvas_size / u_pixel_ratio; // in 0..1\\n gl_Position = vec4(2.0*pos.x - 1.0, 1.0 - 2.0*pos.y, 0.0, 1.0);\\n\\n v_coords.x = dot(xy - a_point_start, segment_along);\\n v_flags = float(int(has_start_cap) +\\n 2*int(has_end_cap) +\\n 4*int(miter_too_large_start) +\\n 8*int(miter_too_large_end));\\n v_cos_theta_turn_right_start = cos_theta_start*turn_right_start;\\n v_cos_theta_turn_right_end = cos_theta_end*turn_right_end;\\n\\n#ifdef DASHED\\n v_length_so_far = a_length_so_far;\\n#endif\\n}\\n\"},\n", - " 416: function _(n,t,a,i,e){i();a.default=\"\\nprecision mediump float;\\n\\nconst int butt_cap = 0;\\nconst int round_cap = 1;\\nconst int square_cap = 2;\\n\\nconst int miter_join = 0;\\nconst int round_join = 1;\\nconst int bevel_join = 2;\\n\\nuniform float u_linewidth;\\nuniform float u_antialias;\\nuniform float u_line_join;\\nuniform float u_line_cap;\\nuniform vec4 u_line_color;\\n#ifdef DASHED\\nuniform sampler2D u_dash_tex;\\nuniform vec4 u_dash_tex_info;\\nuniform float u_dash_scale;\\nuniform float u_dash_offset;\\n#endif\\n\\nvarying float v_segment_length;\\nvarying vec2 v_coords;\\nvarying float v_flags;\\nvarying float v_cos_theta_turn_right_start;\\nvarying float v_cos_theta_turn_right_end;\\n#ifdef DASHED\\nvarying float v_length_so_far;\\n#endif\\n\\nfloat cross_z(in vec2 v0, in vec2 v1)\\n{\\n return v0.x*v1.y - v0.y*v1.x;\\n}\\n\\nfloat point_line_side(in vec2 point, in vec2 start, in vec2 end)\\n{\\n // +ve if point to right of line.\\n // Alternatively could do dot product with right_vector.\\n return cross_z(point - start, end - start);\\n}\\n\\nfloat point_line_distance(in vec2 point, in vec2 start, in vec2 end)\\n{\\n return point_line_side(point, start, end) / distance(start, end);\\n}\\n\\nvec2 right_vector(in vec2 v)\\n{\\n return vec2(v.y, -v.x);\\n}\\n\\nfloat bevel_join_distance(in float sign_start, in float halfwidth)\\n{\\n float cos_theta_turn_right = sign_start > 0.0 ? v_cos_theta_turn_right_start\\n : v_cos_theta_turn_right_end;\\n float cos_theta = abs(cos_theta_turn_right);\\n float turn_right = sign(cos_theta_turn_right);\\n float distance_along = sign_start > 0.0 ? 0.0 : v_segment_length;\\n\\n // In v_coords reference frame (x is along segment, y across).\\n vec2 line_start = vec2(distance_along, halfwidth*turn_right);\\n float sin_alpha = cos_theta;\\n float cos_alpha = sqrt(1.0 - sin_alpha*sin_alpha);\\n vec2 line_along = vec2(-sign_start*turn_right*sin_alpha, -cos_alpha);\\n\\n return halfwidth + sign_start*point_line_distance(\\n v_coords, line_start, line_start+line_along);\\n}\\n\\nfloat cap(in int cap_type, in float x, in float y)\\n{\\n // x is distance along segment in direction away from end of segment,\\n // y is distance across segment.\\n if (cap_type == butt_cap)\\n return max(0.5*u_linewidth - x, abs(y));\\n else if (cap_type == square_cap)\\n return max(-x, abs(y));\\n else // cap_type == round_cap\\n return distance(vec2(min(x, 0.0), y), vec2(0.0, 0.0));\\n}\\n\\nfloat distance_to_alpha(in float dist)\\n{\\n return 1.0 - smoothstep(0.5*(u_linewidth - u_antialias),\\n 0.5*(u_linewidth + u_antialias), dist);\\n}\\n\\n#ifdef DASHED\\nfloat dash_distance(in float x)\\n{\\n // x is in direction of v_coords.x, i.e. along segment.\\n float tex_length = u_dash_tex_info.x;\\n float tex_offset = u_dash_tex_info.y;\\n float tex_dist_min = u_dash_tex_info.z;\\n float tex_dist_max = u_dash_tex_info.w;\\n\\n // Apply offset.\\n x += v_length_so_far - u_dash_scale*tex_offset + u_dash_offset;\\n\\n // Interpolate within texture to obtain distance to dash.\\n float dist = texture2D(u_dash_tex,\\n vec2(x / (tex_length*u_dash_scale), 0.0)).a;\\n\\n // Scale distance within min and max limits.\\n dist = tex_dist_min + dist*(tex_dist_max - tex_dist_min);\\n\\n return u_dash_scale*dist;\\n}\\n\\nmat2 rotation_matrix(in float sign_start)\\n{\\n // Rotation matrix for v_coords from this segment to prev or next segment.\\n float cos_theta_turn_right = sign_start > 0.0 ? v_cos_theta_turn_right_start\\n : v_cos_theta_turn_right_end;\\n float cos_theta = abs(cos_theta_turn_right);\\n float turn_right = sign(cos_theta_turn_right);\\n\\n float sin_theta = sqrt(1.0 - cos_theta*cos_theta)*sign_start*turn_right;\\n float cos_2theta = 2.0*cos_theta*cos_theta - 1.0;\\n float sin_2theta = 2.0*sin_theta*cos_theta;\\n return mat2(cos_2theta, -sin_2theta, sin_2theta, cos_2theta);\\n}\\n#endif\\n\\nvoid main()\\n{\\n int join_type = int(u_line_join + 0.5);\\n int cap_type = int(u_line_cap + 0.5);\\n float halfwidth = 0.5*(u_linewidth + u_antialias);\\n\\n // Extract flags.\\n int flags = int(v_flags + 0.5);\\n bool miter_too_large_end = (flags / 8 > 0);\\n flags -= 8*int(miter_too_large_end);\\n bool miter_too_large_start = (flags / 4 > 0);\\n flags -= 4*int(miter_too_large_start);\\n bool has_end_cap = (flags / 2 > 0);\\n flags -= 2*int(has_end_cap);\\n bool has_start_cap = flags > 0;\\n\\n float dist = v_coords.y; // For straight segment, and miter join.\\n\\n if (v_coords.x <= 0.5*u_antialias) {\\n // At start of segment, either cap or join.\\n if (has_start_cap)\\n dist = cap(cap_type, v_coords.x, v_coords.y);\\n else if (join_type == round_join)\\n dist = distance(v_coords, vec2(0.0, 0.0));\\n else if (join_type == bevel_join ||\\n (join_type == miter_join && miter_too_large_start))\\n dist = max(abs(dist), bevel_join_distance(1.0, halfwidth));\\n // else a miter join which uses the default dist calculation.\\n }\\n else if (v_coords.x >= v_segment_length - 0.5*u_antialias) {\\n // At end of segment, either cap or join.\\n if (has_end_cap)\\n dist = cap(cap_type, v_segment_length - v_coords.x, v_coords.y);\\n else if (join_type == round_join)\\n dist = distance(v_coords, vec2(v_segment_length, 0));\\n else if ((join_type == bevel_join ||\\n (join_type == miter_join && miter_too_large_end)))\\n dist = max(abs(dist), bevel_join_distance(-1.0, halfwidth));\\n // else a miter join which uses the default dist calculation.\\n }\\n\\n float alpha = distance_to_alpha(abs(dist));\\n\\n#ifdef DASHED\\n if (u_dash_tex_info.x >= 0.0) {\\n // Dashes in straight segments (outside of joins) are easily calculated.\\n dist = dash_distance(v_coords.x);\\n\\n if (!has_start_cap && cap_type == butt_cap) {\\n if (v_coords.x < 0.5*u_antialias) {\\n // Outer of start join rendered solid color or not at all\\n // depending on whether corner point is in dash or gap, with\\n // antialiased ends.\\n dist = (dash_distance(0.0) > 0.0 ? 0.5*u_antialias - v_coords.x\\n : -0.5*u_linewidth);\\n\\n // Also consider antialiased end of dash just outside corner.\\n float end_dist = dash_distance(0.5*u_antialias) + v_coords.x -\\n 0.5*u_antialias;\\n dist = max(dist, end_dist);\\n }\\n\\n vec2 prev_coords = rotation_matrix(1.0)*v_coords;\\n\\n if (abs(prev_coords.y) < halfwidth &&\\n prev_coords.x < 0.5*u_antialias) {\\n // Extend dashes across from previous segment, with antialiased\\n // end.\\n float new_dist = dash_distance(min(prev_coords.x,\\n -0.5*u_antialias));\\n\\n if (prev_coords.x > -0.5*u_antialias)\\n new_dist -= prev_coords.x + 0.5*u_antialias;\\n\\n new_dist = min(new_dist, 0.5*u_linewidth - abs(prev_coords.y));\\n dist = max(dist, new_dist);\\n }\\n }\\n\\n if (!has_end_cap && cap_type == butt_cap) {\\n if (v_coords.x > v_segment_length - 0.5*u_antialias) {\\n // Similar for end join.\\n dist = (dash_distance(v_segment_length) > 0.0\\n ? v_coords.x - v_segment_length + 0.5*u_antialias\\n : -0.5*u_linewidth);\\n\\n float end_dist =\\n dash_distance(v_segment_length - 0.5*u_antialias) -\\n v_coords.x + v_segment_length - 0.5*u_antialias;\\n dist = max(dist, end_dist);\\n }\\n\\n vec2 next_coords =\\n rotation_matrix(-1.0)*(v_coords - vec2(v_segment_length, 0.0));\\n\\n if (abs(next_coords.y) < halfwidth &&\\n next_coords.x > -0.5*u_antialias) {\\n // Extend dashes across from next segment, with antialiased end.\\n float new_dist = dash_distance(v_segment_length +\\n max(next_coords.x, 0.5*u_antialias));\\n\\n if (next_coords.x < 0.5*u_antialias)\\n new_dist += next_coords.x - 0.5*u_antialias;\\n\\n new_dist = min(new_dist, 0.5*u_linewidth - abs(next_coords.y));\\n dist = max(dist, new_dist);\\n }\\n }\\n\\n dist = cap(cap_type, dist, v_coords.y);\\n\\n float dash_alpha = distance_to_alpha(dist);\\n alpha = min(alpha, dash_alpha);\\n }\\n#endif\\n\\n alpha = u_line_color.a*alpha;\\n gl_FragColor = vec4(u_line_color.rgb*alpha, alpha); // Premultiplied alpha.\\n}\\n\"},\n", - " 417: function _(n,i,o,a,t){a();o.default=\"\\nprecision mediump float;\\n\\nattribute vec2 a_position;\\nattribute vec2 a_center;\\nattribute float a_size;\\nattribute float a_angle; // in radians\\nattribute float a_linewidth;\\nattribute vec4 a_line_color;\\nattribute vec4 a_fill_color;\\nattribute float a_show;\\n\\nuniform float u_pixel_ratio;\\nuniform vec2 u_canvas_size;\\nuniform float u_antialias;\\n\\nvarying float v_linewidth;\\nvarying float v_size;\\nvarying vec4 v_line_color;\\nvarying vec4 v_fill_color;\\nvarying vec2 v_coords;\\n\\nvoid main()\\n{\\n v_size = a_size;\\n v_linewidth = a_linewidth;\\n v_line_color = a_line_color;\\n v_fill_color = a_fill_color;\\n\\n if (a_show < 0.5) {\\n // Do not show this marker.\\n gl_Position = vec4(-2.0, -2.0, 0.0, 1.0);\\n return;\\n }\\n\\n float enclosing_size = v_size + 2.0*v_linewidth + 3.0*u_antialias;\\n\\n // Coordinates in rotated frame with respect to center of marker, used in\\n // distance functions in fragment shader.\\n v_coords = a_position*enclosing_size;\\n\\n float c = cos(-a_angle);\\n float s = sin(-a_angle);\\n mat2 rotation = mat2(c, -s, s, c);\\n\\n vec2 pos = a_center + rotation*v_coords;\\n pos += 0.5; // make up for Bokeh's offset\\n pos /= u_canvas_size / u_pixel_ratio; // in 0..1\\n gl_Position = vec4(2.0*pos.x - 1.0, 1.0 - 2.0*pos.y, 0.0, 1.0);\\n}\\n\"},\n", - " 418: function _(n,a,e,t,s){t();e.default=\"\\nprecision mediump float;\\n\\nconst float SQRT_2 = 1.4142135623730951;\\nconst float SQRT_3 = sqrt(3.0);\\nconst float PI = 3.14159265358979323846264;\\n\\nconst float IN_ANGLE = 0.6283185307179586; // PI/5. = 36 degrees (star of 5 pikes)\\n//const float OUT_ANGLE = PI/2. - IN_ANGLE; // External angle for regular stars\\nconst float COS_A = 0.8090169943749475; // cos(IN_ANGLE)\\nconst float SIN_A = 0.5877852522924731; // sin(IN_ANGLE)\\nconst float COS_B = 0.5877852522924731; // cos(OUT_ANGLE)\\nconst float SIN_B = 0.8090169943749475; // sin(OUT_ANGLE)\\n\\nuniform float u_antialias;\\n\\nvarying vec4 v_line_color;\\nvarying vec4 v_fill_color;\\nvarying float v_linewidth;\\nvarying float v_size;\\nvarying vec2 v_coords;\\n\\n#ifdef USE_ASTERISK\\n// asterisk\\nfloat marker(vec2 P, float size)\\n{\\n // Masks\\n float diamond = max(abs(SQRT_2 / 2.0 * (P.x - P.y)), abs(SQRT_2 / 2.0 * (P.x + P.y))) - size / 2.0;\\n float square = max(abs(P.x), abs(P.y)) - size / 2.0;\\n // Shapes\\n float X = min(abs(P.x - P.y), abs(P.x + P.y));\\n float cross = min(abs(P.x), abs(P.y));\\n // Result is union of masked shapes\\n float result = min(max(X, diamond), max(cross, square));\\n return max(result - v_linewidth/2.0 + u_antialias/2.0, 0.0);\\n}\\n#endif\\n\\n#ifdef USE_CIRCLE\\n// circle\\nfloat marker(vec2 P, float size)\\n{\\n return length(P) - size/2.0;\\n}\\n#endif\\n\\n#ifdef USE_DOT\\nfloat marker(vec2 P, float size)\\n{\\n return max(length(P) - size/8.0 - v_linewidth/15.0 + u_antialias, 0.0);\\n}\\n#endif\\n\\n#ifdef USE_CIRCLE_DOT\\nfloat marker(vec2 P, float size)\\n{\\n float circle = length(P) - size/2.0;\\n float dot_ = min(size/8.0 + v_linewidth/15.0 - u_antialias - length(P), 0.0);\\n return max(circle, dot_);\\n}\\n#endif\\n\\n#ifdef USE_SQUARE\\n// square\\nfloat marker(vec2 P, float size)\\n{\\n return max(abs(P.x), abs(P.y)) - size/2.0;\\n}\\n#endif\\n\\n#ifdef USE_SQUARE_DOT\\nfloat marker(vec2 P, float size)\\n{\\n float square = max(abs(P.x), abs(P.y)) - size/2.0;\\n float dot_ = min(size/8.0 + v_linewidth/15.0 - u_antialias - length(P), 0.0);\\n return max(square, dot_);\\n}\\n#endif\\n\\n#ifdef USE_DIAMOND\\n// diamond\\nfloat marker(vec2 P, float size)\\n{\\n float x = SQRT_2 / 2.0 * (P.x * 1.5 - P.y);\\n float y = SQRT_2 / 2.0 * (P.x * 1.5 + P.y);\\n float r1 = max(abs(x), abs(y)) - size / (2.0 * SQRT_2);\\n return r1 / SQRT_2;\\n}\\n#endif\\n\\n#ifdef USE_DIAMOND_DOT\\nfloat marker(vec2 P, float size)\\n{\\n float x = SQRT_2 / 2.0 * (P.x * 1.5 - P.y);\\n float y = SQRT_2 / 2.0 * (P.x * 1.5 + P.y);\\n float r1 = max(abs(x), abs(y)) - size / (2.0 * SQRT_2);\\n float diamond = r1 / SQRT_2;\\n float dot_ = min(size/8.0 + v_linewidth/15.0 - u_antialias - length(P), 0.0);\\n return max(diamond, dot_);\\n}\\n#endif\\n\\n#ifdef USE_HEX\\n// hex\\nfloat marker(vec2 P, float size)\\n{\\n vec2 q = abs(P);\\n return max(q.y * 0.57735 + q.x - 1.0 * size/2.0, q.y - 0.866 * size/2.0);\\n}\\n#endif\\n\\n#ifdef USE_HEX_DOT\\nfloat marker(vec2 P, float size)\\n{\\n vec2 q = abs(P);\\n float hex = max(q.y * 0.57735 + q.x - 1.0 * size/2.0, q.y - 0.866 * size/2.0);\\n float dot_ = min(size/8.0 + v_linewidth/15.0 - u_antialias - length(P), 0.0);\\n return max(hex, dot_);\\n}\\n#endif\\n\\n#ifdef USE_STAR\\n// star\\n// https://iquilezles.org/www/articles/distfunctions2d/distfunctions2d.htm\\nfloat marker(vec2 P, float size)\\n{\\n float bn = mod(atan(P.x, -P.y), 2.0*IN_ANGLE) - IN_ANGLE;\\n P = length(P)*vec2(cos(bn), abs(sin(bn)));\\n P -= size*vec2(COS_A, SIN_A)/2.;\\n P += vec2(COS_B, SIN_B)*clamp(-(P.x*COS_B + P.y*SIN_B), 0.0, size*SIN_A/SIN_B/2.);\\n return length(P)*sign(P.x);\\n}\\n#endif\\n\\n#ifdef USE_STAR_DOT\\nfloat marker(vec2 P, float size)\\n{\\n float dot_ = min(size/8.0 + v_linewidth/15.0 - u_antialias - length(P), 0.0);\\n float bn = mod(atan(P.x, -P.y), 2.0*IN_ANGLE) - IN_ANGLE;\\n P = length(P)*vec2(cos(bn), abs(sin(bn)));\\n P -= size*vec2(COS_A, SIN_A)/2.;\\n P += vec2(COS_B, SIN_B)*clamp(-(P.x*COS_B + P.y*SIN_B), 0.0, size*SIN_A/SIN_B/2.);\\n float star = length(P)*sign(P.x);\\n return max(star, dot_);\\n}\\n#endif\\n\\n#ifdef USE_TRIANGLE\\n// triangle\\nfloat marker(vec2 P, float size)\\n{\\n P.y -= size * 0.3;\\n float x = SQRT_2 / 2.0 * (P.x * 1.7 - P.y);\\n float y = SQRT_2 / 2.0 * (P.x * 1.7 + P.y);\\n float r1 = max(abs(x), abs(y)) - size / 1.6;\\n float r2 = P.y;\\n return max(r1 / SQRT_2, r2); // Intersect diamond with rectangle\\n}\\n#endif\\n\\n#ifdef USE_TRIANGLE_DOT\\nfloat marker(vec2 P, float size)\\n{\\n float dot_ = min(size/8.0 + v_linewidth/15.0 - u_antialias - length(P), 0.0);\\n P.y -= size * 0.3;\\n float x = SQRT_2 / 2.0 * (P.x * 1.7 - P.y);\\n float y = SQRT_2 / 2.0 * (P.x * 1.7 + P.y);\\n float r1 = max(abs(x), abs(y)) - size / 1.6;\\n float r2 = P.y;\\n float triangle = max(r1 / SQRT_2, r2); // Intersect diamond with rectangle\\n return max(triangle, dot_);\\n}\\n#endif\\n\\n#ifdef USE_INVERTED_TRIANGLE\\n// inverted_triangle\\nfloat marker(vec2 P, float size)\\n{\\n P.y += size * 0.3;\\n float x = SQRT_2 / 2.0 * (P.x * 1.7 - P.y);\\n float y = SQRT_2 / 2.0 * (P.x * 1.7 + P.y);\\n float r1 = max(abs(x), abs(y)) - size / 1.6;\\n float r2 = - P.y;\\n return max(r1 / SQRT_2, r2); // Intersect diamond with rectangle\\n}\\n#endif\\n\\n#ifdef USE_CROSS\\n// cross\\nfloat marker(vec2 P, float size)\\n{\\n float square = max(abs(P.x), abs(P.y)) - size / 2.0;\\n float cross = min(abs(P.x), abs(P.y));\\n cross = max(cross - v_linewidth/2.0 + u_antialias/2.0, 0.0);\\n return max(square, cross);\\n}\\n#endif\\n\\n#ifdef USE_DASH\\nfloat marker(vec2 P, float size)\\n{\\n float square = max(abs(P.x), abs(P.y)) - size / 2.0;\\n float cross = abs(P.y);\\n cross = max(cross - v_linewidth/2.0 + u_antialias/2.0, 0.0);\\n return max(square, cross);\\n}\\n#endif\\n\\n#ifdef USE_CIRCLE_CROSS\\n// circle_cross\\nfloat marker(vec2 P, float size)\\n{\\n // Define quadrants\\n float qs = size / 2.0; // quadrant size\\n float s1 = max(abs(P.x - qs), abs(P.y - qs)) - qs;\\n float s2 = max(abs(P.x + qs), abs(P.y - qs)) - qs;\\n float s3 = max(abs(P.x - qs), abs(P.y + qs)) - qs;\\n float s4 = max(abs(P.x + qs), abs(P.y + qs)) - qs;\\n // Intersect main shape with quadrants (to form cross)\\n float circle = length(P) - size/2.0;\\n float c1 = max(circle, s1);\\n float c2 = max(circle, s2);\\n float c3 = max(circle, s3);\\n float c4 = max(circle, s4);\\n // Union\\n return min(min(min(c1, c2), c3), c4);\\n}\\n#endif\\n\\n#ifdef USE_SQUARE_CROSS\\n// square_cross\\nfloat marker(vec2 P, float size)\\n{\\n // Define quadrants\\n float qs = size / 2.0; // quadrant size\\n float s1 = max(abs(P.x - qs), abs(P.y - qs)) - qs;\\n float s2 = max(abs(P.x + qs), abs(P.y - qs)) - qs;\\n float s3 = max(abs(P.x - qs), abs(P.y + qs)) - qs;\\n float s4 = max(abs(P.x + qs), abs(P.y + qs)) - qs;\\n // Intersect main shape with quadrants (to form cross)\\n float square = max(abs(P.x), abs(P.y)) - size/2.0;\\n float c1 = max(square, s1);\\n float c2 = max(square, s2);\\n float c3 = max(square, s3);\\n float c4 = max(square, s4);\\n // Union\\n return min(min(min(c1, c2), c3), c4);\\n}\\n#endif\\n\\n#ifdef USE_DIAMOND_CROSS\\n// diamond_cross\\nfloat marker(vec2 P, float size)\\n{\\n // Define quadrants\\n float qs = size / 2.0; // quadrant size\\n float s1 = max(abs(P.x - qs), abs(P.y - qs)) - qs;\\n float s2 = max(abs(P.x + qs), abs(P.y - qs)) - qs;\\n float s3 = max(abs(P.x - qs), abs(P.y + qs)) - qs;\\n float s4 = max(abs(P.x + qs), abs(P.y + qs)) - qs;\\n // Intersect main shape with quadrants (to form cross)\\n float x = SQRT_2 / 2.0 * (P.x * 1.5 - P.y);\\n float y = SQRT_2 / 2.0 * (P.x * 1.5 + P.y);\\n float diamond = max(abs(x), abs(y)) - size / (2.0 * SQRT_2);\\n diamond /= SQRT_2;\\n float c1 = max(diamond, s1);\\n float c2 = max(diamond, s2);\\n float c3 = max(diamond, s3);\\n float c4 = max(diamond, s4);\\n // Union\\n return min(min(min(c1, c2), c3), c4);\\n}\\n#endif\\n\\n#ifdef USE_X\\n// x\\nfloat marker(vec2 P, float size)\\n{\\n float circle = length(P) - size / 2.0;\\n float X = min(abs(P.x - P.y), abs(P.x + P.y));\\n X = max(X - v_linewidth/2.0, 0.0);\\n return max(circle, X);\\n}\\n#endif\\n\\n#ifdef USE_Y\\nfloat marker(vec2 P, float size)\\n{\\n float circle = length(P) - size / 2.0;\\n\\n float dx = 1.0 / SQRT_3;\\n float dy = SQRT_2 / SQRT_3;\\n\\n // Sideways distance from the three spokes.\\n float d0 = abs(P.x);\\n float d1 = abs(dot(P, vec2(dx, dy)));\\n float d2 = abs(dot(P, vec2(dx, -dy)));\\n\\n // Clip each spoke to semicircle.\\n d0 = max(d0, -P.y);\\n d1 = max(d1, dot(P, vec2(-dy, dx)));\\n d2 = max(d2, dot(P, vec2(dy, dx)));\\n\\n float Y = min(min(d0, d1), d2);\\n Y = max(Y - v_linewidth/2.0 + u_antialias/2.0, 0.0);\\n return max(circle, Y);\\n}\\n#endif\\n\\n#ifdef USE_CIRCLE_X\\n// circle_x\\nfloat marker(vec2 P, float size)\\n{\\n float x = P.x - P.y;\\n float y = P.x + P.y;\\n // Define quadrants\\n float qs = size / 2.0; // quadrant size\\n float s1 = max(abs(x - qs), abs(y - qs)) - qs;\\n float s2 = max(abs(x + qs), abs(y - qs)) - qs;\\n float s3 = max(abs(x - qs), abs(y + qs)) - qs;\\n float s4 = max(abs(x + qs), abs(y + qs)) - qs;\\n // Intersect main shape with quadrants (to form cross)\\n float circle = length(P) - size/2.0;\\n float c1 = max(circle, s1);\\n float c2 = max(circle, s2);\\n float c3 = max(circle, s3);\\n float c4 = max(circle, s4);\\n // Union\\n return min(min(min(c1, c2), c3), c4);\\n}\\n#endif\\n\\n#ifdef USE_CIRCLE_Y\\nfloat marker(vec2 P, float size)\\n{\\n float circle = length(P) - size/2.0;\\n\\n float dx = 1.0 / SQRT_3;\\n float dy = SQRT_2 / SQRT_3;\\n\\n // Sideways distance from the three spokes.\\n float d0 = abs(P.x);\\n float d1 = abs(dot(P, vec2(dx, dy)));\\n float d2 = abs(dot(P, vec2(dx, -dy)));\\n\\n // Clip each spoke to semicircle.\\n d0 = max(d0, -P.y);\\n d1 = max(d1, dot(P, vec2(-dy, dx)));\\n d2 = max(d2, dot(P, vec2(dy, dx)));\\n\\n float Y = min(min(d0, d1), d2);\\n Y = min(v_linewidth/2.0 - u_antialias/2.0 - Y, 0.0);\\n\\n return max(circle, Y);\\n}\\n#endif\\n\\n#ifdef USE_SQUARE_X\\n// square_x\\nfloat marker(vec2 P, float size)\\n{\\n float x = P.x - P.y;\\n float y = P.x + P.y;\\n // Define quadrants\\n float qs = size / 2.0; // quadrant size\\n float s1 = max(abs(x - qs), abs(y - qs)) - qs;\\n float s2 = max(abs(x + qs), abs(y - qs)) - qs;\\n float s3 = max(abs(x - qs), abs(y + qs)) - qs;\\n float s4 = max(abs(x + qs), abs(y + qs)) - qs;\\n // Intersect main shape with quadrants (to form cross)\\n float square = max(abs(P.x), abs(P.y)) - size/2.0;\\n float c1 = max(square, s1);\\n float c2 = max(square, s2);\\n float c3 = max(square, s3);\\n float c4 = max(square, s4);\\n // Union\\n return min(min(min(c1, c2), c3), c4);\\n}\\n#endif\\n\\n#ifdef USE_PLUS\\nfloat marker(vec2 P, float size)\\n{\\n vec2 size2 = vec2(size*0.5, size*0.2);\\n P = abs(P);\\n P = (P.y > P.x) ? P.yx : P.xy;\\n vec2 q = P - size2;\\n float k = max(q.y, q.x);\\n vec2 w = (k > 0.0) ? q : vec2(size2.y - P.x, -k);\\n return sign(k)*length(max(w, 0.0));\\n}\\n#endif\\n\\n#ifdef USE_SQUARE_PIN\\nfloat marker(vec2 P, float size)\\n{\\n float actual_size = size*1.2;\\n float radius = 0.75*actual_size; // Radius of curvature of edges.\\n float offset = actual_size/2.0 + sqrt(radius*radius - actual_size*actual_size/4.0);\\n vec2 centerx = vec2(offset, 0.0);\\n vec2 centery = vec2(0.0, offset);\\n\\n float right = length(P - centerx);\\n float left = length(P + centerx);\\n float up = length(P - centery);\\n float down = length(P + centery);\\n float pin = radius - min(min(right, left), min(up, down));\\n\\n float circle = length(P) - actual_size*0.6;\\n return max(circle, pin);\\n}\\n#endif\\n\\n#ifdef USE_TRIANGLE_PIN\\nfloat marker(vec2 P, float size)\\n{\\n float actual_size = size*1.2;\\n float radius = 1.2*actual_size; // Radius of curvature of edges.\\n\\n float angle = 2.0*PI / 3.0;\\n float c = cos(angle);\\n float s = sin(angle);\\n mat2 rotation = mat2(c, -s, s, c);\\n\\n // Half the length of straight triangle edge.\\n float half_edge = actual_size*SQRT_3/4.0;\\n // Distance from center of triangle to middle of straight edge.\\n float centre_middle_edge = 0.25*actual_size;\\n float offset = centre_middle_edge + sqrt(radius*radius - half_edge*half_edge);\\n // Centre of curvature.\\n vec2 center = vec2(0.0, offset);\\n\\n float dist0 = length(P - center);\\n P = rotation*P;\\n float dist1 = length(P - center);\\n P = rotation*P;\\n float dist2 = length(P - center);\\n float pin = radius - min(min(dist0, dist1), dist2);\\n\\n float circle = length(P) - actual_size / 2.0;\\n return max(circle, pin);\\n}\\n#endif\\n\\nvec4 outline(float distance, float linewidth, float antialias, vec4 line_color,\\n vec4 fill_color)\\n{\\n vec4 frag_color;\\n float t = min(linewidth/2.0 - antialias, 0.0); // Line half-width.\\n float signed_distance = distance;\\n float border_distance = abs(signed_distance) - t;\\n float alpha = border_distance/antialias;\\n alpha = exp(-alpha*alpha);\\n\\n // If line alpha is zero, it probably means no outline. To avoid a dark\\n // outline shining through due to antialiasing, we set the line color to the\\n // fill color.\\n float select = float(bool(line_color.a));\\n line_color.rgb = select*line_color.rgb + (1.0 - select)*fill_color.rgb;\\n // Similarly, if we want a transparent fill.\\n select = float(bool(fill_color.a));\\n fill_color.rgb = select*fill_color.rgb + (1.0 - select)*line_color.rgb;\\n\\n if (border_distance < 0.0)\\n frag_color = line_color;\\n else if (signed_distance < 0.0)\\n frag_color = mix(fill_color, line_color, sqrt(alpha));\\n else {\\n if (abs(signed_distance) < linewidth/2.0 + antialias)\\n frag_color = vec4(line_color.rgb, line_color.a*alpha);\\n else\\n discard;\\n }\\n return frag_color;\\n}\\n\\nvoid main()\\n{\\n float distance = marker(v_coords, v_size);\\n gl_FragColor = outline(\\n distance, v_linewidth, u_antialias, v_line_color, v_fill_color);\\n gl_FragColor.rgb *= gl_FragColor.a; // Premultiplied alpha.\\n}\\n\"},\n", - " 419: function _(n,t,a,i,e){i();a.default=\"\\nprecision mediump float;\\n\\nattribute vec2 a_position;\\nattribute vec2 a_center;\\nattribute float a_width;\\nattribute float a_height;\\nattribute float a_angle; // In radians\\nattribute float a_linewidth;\\nattribute vec4 a_line_color;\\nattribute vec4 a_fill_color;\\nattribute float a_line_join;\\nattribute float a_show;\\n#ifdef HATCH\\nattribute float a_hatch_pattern;\\nattribute float a_hatch_scale;\\nattribute float a_hatch_weight;\\nattribute vec4 a_hatch_color;\\n#endif\\n\\nuniform float u_pixel_ratio;\\nuniform vec2 u_canvas_size;\\nuniform float u_antialias;\\n\\nvarying float v_linewidth;\\nvarying vec2 v_size; // 2D size for rects compared to 1D for markers.\\nvarying vec4 v_line_color;\\nvarying vec4 v_fill_color;\\nvarying float v_line_join;\\nvarying vec2 v_coords;\\n#ifdef HATCH\\nvarying float v_hatch_pattern;\\nvarying float v_hatch_scale;\\nvarying float v_hatch_weight;\\nvarying vec4 v_hatch_color;\\nvarying vec2 v_hatch_coords;\\n#endif\\n\\nvoid main()\\n{\\n if (a_show < 0.5) {\\n // Do not show this rect.\\n gl_Position = vec4(-2.0, -2.0, 0.0, 1.0);\\n return;\\n }\\n\\n v_size = vec2(a_width, a_height);\\n v_linewidth = a_linewidth;\\n v_line_color = a_line_color;\\n v_fill_color = a_fill_color;\\n v_line_join = a_line_join;\\n\\n if (v_linewidth < 1.0) {\\n // Linewidth less than 1 is implemented as 1 but with reduced alpha.\\n v_line_color.a *= v_linewidth;\\n v_linewidth = 1.0;\\n }\\n\\n#ifdef HATCH\\n v_hatch_pattern = a_hatch_pattern;\\n v_hatch_scale = a_hatch_scale;\\n v_hatch_weight = a_hatch_weight;\\n v_hatch_color = a_hatch_color;\\n#endif\\n\\n vec2 enclosing_size = v_size + v_linewidth + u_antialias;\\n\\n // Coordinates in rotated frame with respect to center of marker, used for\\n // distance functions in fragment shader.\\n v_coords = a_position*enclosing_size;\\n\\n float c = cos(-a_angle);\\n float s = sin(-a_angle);\\n mat2 rotation = mat2(c, -s, s, c);\\n\\n vec2 pos = a_center + rotation*v_coords;\\n#ifdef HATCH\\n // Coordinates for hatching in unrotated frame of reference.\\n v_hatch_coords = pos - 0.5;\\n#endif\\n pos += 0.5; // Make up for Bokeh's offset.\\n pos /= u_canvas_size / u_pixel_ratio; // 0 to 1.\\n gl_Position = vec4(2.0*pos.x - 1.0, 1.0 - 2.0*pos.y, 0.0, 1.0);\\n}\\n\"},\n", - " 420: function _(n,a,t,o,r){o();t.default=\"\\nprecision mediump float;\\n\\nconst float SQRT2 = sqrt(2.0);\\nconst float INVSQRT2 = 1.0/SQRT2;\\nconst float PI = 3.14159265358979323846;\\n\\nconst int miter_join = 0;\\nconst int round_join = 1;\\nconst int bevel_join = 2;\\n#ifdef HATCH\\nconst int hatch_dot = 1;\\nconst int hatch_ring = 2;\\nconst int hatch_horizontal_line = 3;\\nconst int hatch_vertical_line = 4;\\nconst int hatch_cross = 5;\\nconst int hatch_horizontal_dash = 6;\\nconst int hatch_vertical_dash = 7;\\nconst int hatch_spiral = 8;\\nconst int hatch_right_diagonal_line = 9;\\nconst int hatch_left_diagonal_line = 10;\\nconst int hatch_diagonal_cross = 11;\\nconst int hatch_right_diagonal_dash = 12;\\nconst int hatch_left_diagonal_dash = 13;\\nconst int hatch_horizontal_wave = 14;\\nconst int hatch_vertical_wave = 15;\\nconst int hatch_criss_cross = 16;\\n#endif\\n\\nuniform float u_antialias;\\n\\nvarying float v_linewidth;\\nvarying vec2 v_size;\\nvarying vec4 v_line_color;\\nvarying vec4 v_fill_color;\\nvarying float v_line_join;\\nvarying vec2 v_coords;\\n#ifdef HATCH\\nvarying float v_hatch_pattern;\\nvarying float v_hatch_scale;\\nvarying float v_hatch_weight;\\nvarying vec4 v_hatch_color;\\nvarying vec2 v_hatch_coords;\\n#endif\\n\\n// Distance is zero on edge of marker, +ve outside and -ve inside.\\nfloat marker_distance(vec2 p, int line_join)\\n{\\n vec2 dist2 = abs(p) - v_size/2.0;\\n float dist = max(dist2.x, dist2.y);\\n\\n if (dist2.x > 0.0 && dist2.y > 0.0) {\\n // Outside of corner needs correct join, default is miter.\\n if (line_join == round_join)\\n dist = length(dist2);\\n else if (line_join == bevel_join) {\\n vec2 normal = vec2(INVSQRT2, INVSQRT2);\\n dist = dot(dist2, normal) + 0.5*v_linewidth*(1.0 - INVSQRT2);\\n }\\n }\\n\\n return dist;\\n}\\n\\n// Convert distance from edge of marker to fraction in range 0 to 1, depending\\n// on antialiasing width.\\nfloat distance_to_fraction(float dist)\\n{\\n return 1.0 - smoothstep(-0.5*u_antialias, 0.5*u_antialias, dist);\\n}\\n\\n// Return fraction from 0 (no fill color) to 1 (full fill color).\\nfloat fill_fraction(float dist)\\n{\\n return distance_to_fraction(dist);\\n}\\n\\n// Return fraction in range 0 (no line color) to 1 (full line color).\\nfloat line_fraction(float dist)\\n{\\n return distance_to_fraction(abs(dist) - 0.5*v_linewidth);\\n}\\n\\n// Return fraction (in range 0 to 1) of a color, with premultiplied alpha.\\nvec4 fractional_color(vec4 color, float fraction)\\n{\\n color.a *= fraction;\\n color.rgb *= color.a;\\n return color;\\n}\\n\\n// Blend colors that have premultiplied alpha.\\nvec4 blend_colors(vec4 src, vec4 dest)\\n{\\n return (1.0 - src.a)*dest + src;\\n}\\n\\n#ifdef HATCH\\n// Wrap coordinate(s) by removing integer part to give distance from center of\\n// repeat, in the range -0.5 to +0.5.\\nfloat wrap(float x)\\n{\\n return fract(x) - 0.5;\\n}\\n\\nvec2 wrap(vec2 xy)\\n{\\n return fract(xy) - 0.5;\\n}\\n\\n// Return fraction from 0 (no hatch color) to 1 (full hatch color).\\nfloat hatch_fraction(vec2 coords, int hatch_pattern)\\n{\\n float scale = v_hatch_scale; // Hatch repeat distance.\\n\\n // Coordinates and linewidth/halfwidth are scaled to hatch repeat distance.\\n coords = coords / scale;\\n float halfwidth = 0.5*v_hatch_weight / scale; // Half the hatch linewidth.\\n\\n // Default is to return fraction of zero, i.e. no pattern.\\n float dist = u_antialias;\\n\\n if (hatch_pattern == hatch_dot) {\\n const float dot_radius = 0.25;\\n dist = length(wrap(coords)) - dot_radius;\\n }\\n else if (hatch_pattern == hatch_ring) {\\n const float ring_radius = 0.25;\\n dist = abs(length(wrap(coords)) - ring_radius) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_horizontal_line) {\\n dist = abs(wrap(coords.y)) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_vertical_line) {\\n dist = abs(wrap(coords.x)) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_cross) {\\n dist = min(abs(wrap(coords.x)), abs(wrap(coords.y))) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_horizontal_dash) {\\n // Dashes have square caps.\\n const float halflength = 0.25;\\n dist = max(abs(wrap(coords.y)),\\n abs(wrap(coords.x) + 0.25) - halflength) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_vertical_dash) {\\n const float halflength = 0.25;\\n dist = max(abs(wrap(coords.x)),\\n abs(wrap(coords.y) + 0.25) - halflength) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_spiral) {\\n vec2 wrap2 = wrap(coords);\\n float angle = wrap(atan(wrap2.y, wrap2.x) / (2.0*PI));\\n // Canvas spiral radius increases by scale*pi/15 each rotation.\\n const float dr = PI/15.0;\\n float radius = length(wrap2);\\n // At any angle, spiral lines are equally spaced dr apart.\\n // Find distance to nearest of these lines.\\n float frac = fract((radius - dr*angle) / dr); // 0 to 1.\\n dist = dr*(abs(frac - 0.5));\\n dist = min(dist, radius) - halfwidth; // Consider center point also.\\n }\\n else if (hatch_pattern == hatch_right_diagonal_line) {\\n dist = abs(wrap(2.0*coords.x + coords.y))/sqrt(5.0) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_left_diagonal_line) {\\n dist = abs(wrap(2.0*coords.x - coords.y))/sqrt(5.0) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_diagonal_cross) {\\n coords = vec2(coords.x + coords.y + 0.5, coords.x - coords.y + 0.5);\\n dist = min(abs(wrap(coords.x)), abs(wrap(coords.y))) / SQRT2 - halfwidth;\\n }\\n else if (hatch_pattern == hatch_right_diagonal_dash) {\\n float across = coords.x + coords.y + 0.5;\\n dist = abs(wrap(across)) / SQRT2; // Distance to nearest solid line.\\n\\n across = floor(across); // Offset for dash.\\n float along = wrap(0.5*(coords.x - coords.y + across));\\n const float halflength = 0.25;\\n along = abs(along) - halflength; // Distance along line.\\n\\n dist = max(dist, along) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_left_diagonal_dash) {\\n float across = coords.x - coords.y + 0.5;\\n dist = abs(wrap(across)) / SQRT2; // Distance to nearest solid line.\\n\\n across = floor(across); // Offset for dash.\\n float along = wrap(0.5*(coords.x + coords.y + across));\\n const float halflength = 0.25;\\n along = abs(along) - halflength; // Distance along line.\\n\\n dist = max(dist, along) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_horizontal_wave) {\\n float wrapx = wrap(coords.x);\\n float wrapy = wrap(coords.y - 0.25 + abs(wrapx));\\n dist = abs(wrapy) / SQRT2 - halfwidth;\\n }\\n else if (hatch_pattern == hatch_vertical_wave) {\\n float wrapy = wrap(coords.y);\\n float wrapx = wrap(coords.x - 0.25 + abs(wrapy));\\n dist = abs(wrapx) / SQRT2 - halfwidth;\\n }\\n else if (hatch_pattern == hatch_criss_cross) {\\n float plus = min(abs(wrap(coords.x)), abs(wrap(coords.y)));\\n\\n coords = vec2(coords.x + coords.y + 0.5, coords.x - coords.y + 0.5);\\n float X = min(abs(wrap(coords.x)), abs(wrap(coords.y))) / SQRT2;\\n\\n dist = min(plus, X) - halfwidth;\\n }\\n\\n return distance_to_fraction(dist*scale);\\n}\\n#endif\\n\\nvoid main()\\n{\\n int line_join = int(v_line_join + 0.5);\\n#ifdef HATCH\\n int hatch_pattern = int(v_hatch_pattern + 0.5);\\n#endif\\n\\n float dist = marker_distance(v_coords, line_join);\\n\\n float fill_frac = fill_fraction(dist);\\n vec4 color = fractional_color(v_fill_color, fill_frac);\\n\\n#ifdef HATCH\\n if (hatch_pattern > 0 && fill_frac > 0.0) {\\n float hatch_frac = hatch_fraction(v_hatch_coords, hatch_pattern);\\n vec4 hatch_color = fractional_color(v_hatch_color, hatch_frac*fill_frac);\\n color = blend_colors(hatch_color, color);\\n }\\n#endif\\n\\n float line_frac = line_fraction(dist);\\n if (line_frac > 0.0) {\\n vec4 line_color = fractional_color(v_line_color, line_frac);\\n color = blend_colors(line_color, color);\\n }\\n\\n gl_FragColor = color;\\n}\\n\"},\n", - " 421: function _(s,i,t,e,_){e();const h=s(422),l=s(22),a=s(46),n=s(423),o=s(424),r=-1e4;class p extends h.BaseGLGlyph{constructor(s,i){super(s,i),this.glyph=i,this._antialias=1.5,this._miter_limit=5}draw(s,i,t){const e=i.glglyph;this.visuals_changed&&(this._set_visuals(),this.visuals_changed=!1),e.data_changed&&(e._set_data(),e.data_changed=!1);const _=this.glyph.visuals.line,h=n.cap_lookup[_.line_cap.value],l=n.join_lookup[_.line_join.value];if(this._is_dashed()){const s={scissor:this.regl_wrapper.scissor,viewport:this.regl_wrapper.viewport,canvas_size:[t.width,t.height],pixel_ratio:t.pixel_ratio,line_color:this._color,linewidth:this._linewidth,antialias:this._antialias,miter_limit:this._miter_limit,points:e._points,nsegments:e._nsegments,line_join:l,line_cap:h,length_so_far:e._length_so_far,dash_tex:this._dash_tex,dash_tex_info:this._dash_tex_info,dash_scale:this._dash_scale,dash_offset:this._dash_offset};this.regl_wrapper.dashed_line()(s)}else{const s={scissor:this.regl_wrapper.scissor,viewport:this.regl_wrapper.viewport,canvas_size:[t.width,t.height],pixel_ratio:t.pixel_ratio,line_color:this._color,linewidth:this._linewidth,antialias:this._antialias,miter_limit:this._miter_limit,points:e._points,nsegments:e._nsegments,line_join:l,line_cap:h};this.regl_wrapper.solid_line()(s)}}_is_dashed(){return this._line_dash.length>0}_set_data(){const s=this.glyph.sx.length;this._nsegments=s-1,null==this._is_closed&&(this._is_closed=this.glyph.sx[0]==this.glyph.sx[s-1]&&this.glyph.sy[0]==this.glyph.sy[s-1]&&isFinite(this.glyph.sx[0])&&isFinite(this.glyph.sy[0])),null==this._points&&(this._points=new o.Float32Buffer(this.regl_wrapper));const i=this._points.get_sized_array(2*(s+2));for(let t=1;t-9e3&&i[2*e+4]>-9e3&&(t+=Math.sqrt((i[2*e+4]-i[2*e+2])**2+(i[2*e+5]-i[2*e+3])**2));this._length_so_far.update()}}_set_visuals(){const s=this.glyph.visuals.line,i=(0,l.color2rgba)(s.line_color.value,s.line_alpha.value);this._color=i.map((s=>s/255)),this._linewidth=s.line_width.value,this._linewidth<1&&(this._color[3]*=this._linewidth,this._linewidth=1),this._line_dash=(0,a.resolve_line_dash)(s.line_dash.value),1==this._line_dash.length&&this._line_dash.push(this._line_dash[0]),this._is_dashed()&&([this._dash_tex_info,this._dash_tex,this._dash_scale]=this.regl_wrapper.get_dash(this._line_dash),this._dash_offset=s.line_dash_offset.value)}}t.LineGL=p,p.__name__=\"LineGL\"},\n", - " 422: function _(e,t,s,i,h){i();class a{constructor(e,t){this.glyph=t,this.nvertices=0,this.size_changed=!1,this.data_changed=!1,this.visuals_changed=!1,this.regl_wrapper=e}set_data_changed(){const{data_size:e}=this.glyph;e!=this.nvertices&&(this.nvertices=e,this.size_changed=!0),this.data_changed=!0}set_visuals_changed(){this.visuals_changed=!0}render(e,t,s){if(0==t.length)return!0;const{width:i,height:h}=this.glyph.renderer.plot_view.canvas_view.webgl.canvas,a={pixel_ratio:this.glyph.renderer.plot_view.canvas_view.pixel_ratio,width:i,height:h};return this.draw(t,s,a),!0}}s.BaseGLGlyph=a,a.__name__=\"BaseGLGlyph\"},\n", - " 423: function _(a,o,i,n,l){n();const t=a(52);i.cap_lookup={butt:0,round:1,square:2},i.join_lookup={miter:0,round:1,bevel:2};const _={blank:0,dot:1,ring:2,horizontal_line:3,vertical_line:4,cross:5,horizontal_dash:6,vertical_dash:7,spiral:8,right_diagonal_line:9,left_diagonal_line:10,diagonal_cross:11,right_diagonal_dash:12,left_diagonal_dash:13,horizontal_wave:14,vertical_wave:15,criss_cross:16};i.hatch_pattern_to_index=function(a){var o,i;return null!==(i=_[null!==(o=t.hatch_aliases[a])&&void 0!==o?o:a])&&void 0!==i?i:0}},\n", - " 424: function _(r,t,a,e,s){e();const i=r(423),_=r(22);class n{constructor(r){this.regl_wrapper=r,this.is_scalar=!0}get_sized_array(r){return null!=this.array&&this.array.length==r||(this.array=this.new_array(r)),this.array}is_normalized(){return!1}get length(){return null!=this.array?this.array.length:0}set_from_array(r){const t=r.length,a=this.get_sized_array(t);for(let e=0;ethis.render()))}remove(){null!=this.icon_view&&this.icon_view.remove(),super.remove()}styles(){return[...super.styles(),d.default]}_render_button(...t){return(0,c.button)({type:\"button\",disabled:this.model.disabled,class:[h.btn,h[`btn_${this.model.button_type}`]]},...t)}render(){super.render(),this.button_el=this._render_button(this.model.label),this.button_el.addEventListener(\"click\",(()=>this.click())),null!=this.icon_view&&(\"\"!=this.model.label?(0,c.prepend)(this.button_el,this.icon_view.el,(0,c.nbsp)()):(0,c.prepend)(this.button_el,this.icon_view.el),this.icon_view.render()),this.group_el=(0,c.div)({class:h.btn_group},this.button_el),this.el.appendChild(this.group_el)}click(){}}n.AbstractButtonView=b,b.__name__=\"AbstractButtonView\";class p extends _.Control{constructor(t){super(t)}}n.AbstractButton=p,o=p,p.__name__=\"AbstractButton\",o.define((({String:t,Ref:e,Nullable:n})=>({label:[t,\"Button\"],icon:[n(e(a.AbstractIcon)),null],button_type:[r.ButtonType,\"default\"]})))},\n", - " 439: function _(t,e,o,s,n){s();const i=t(508),l=t(43);class c extends i.WidgetView{connect_signals(){super.connect_signals();const t=this.model.properties;this.on_change(t.disabled,(()=>{for(const t of this.controls())(0,l.toggle_attribute)(t,\"disabled\",this.model.disabled)}))}}o.ControlView=c,c.__name__=\"ControlView\";class r extends i.Widget{constructor(t){super(t)}}o.Control=r,r.__name__=\"Control\"},\n", - " 508: function _(i,e,t,n,o){var r;n();const s=i(312);class _ extends s.HTMLBoxView{get orientation(){return\"horizontal\"}get default_size(){return this.model.default_size}_width_policy(){return\"horizontal\"==this.orientation?super._width_policy():\"fixed\"}_height_policy(){return\"horizontal\"==this.orientation?\"fixed\":super._height_policy()}box_sizing(){const i=super.box_sizing();return\"horizontal\"==this.orientation?null==i.width&&(i.width=this.default_size):null==i.height&&(i.height=this.default_size),i}}t.WidgetView=_,_.__name__=\"WidgetView\";class h extends s.HTMLBox{constructor(i){super(i)}}t.Widget=h,r=h,h.__name__=\"Widget\",r.define((({Number:i})=>({default_size:[i,300]}))),r.override({margin:[5,5,5,5]})},\n", - " 441: function _(c,t,s,n,e){n();const o=c(53),_=c(226);class a extends _.DOMView{}s.AbstractIconView=a,a.__name__=\"AbstractIconView\";class r extends o.Model{constructor(c){super(c)}}s.AbstractIcon=r,r.__name__=\"AbstractIcon\"},\n", - " 442: function _(e,t,n,s,i){s();const h=e(1);var o;const _=e(443),u=e(43),r=e(10),c=(0,h.__importStar)(e(229)),a=c;class l extends _.TextInputView{constructor(){super(...arguments),this._open=!1,this._last_value=\"\",this._hover_index=0}styles(){return[...super.styles(),c.default]}render(){super.render(),this.input_el.addEventListener(\"keydown\",(e=>this._keydown(e))),this.input_el.addEventListener(\"keyup\",(e=>this._keyup(e))),this.menu=(0,u.div)({class:[a.menu,a.below]}),this.menu.addEventListener(\"click\",(e=>this._menu_click(e))),this.menu.addEventListener(\"mouseover\",(e=>this._menu_hover(e))),this.el.appendChild(this.menu),(0,u.undisplay)(this.menu)}change_input(){this._open&&this.menu.children.length>0?(this.model.value=this.menu.children[this._hover_index].textContent,this.input_el.focus(),this._hide_menu()):this.model.restrict||super.change_input()}_update_completions(e){(0,u.empty)(this.menu);for(const t of e){const e=(0,u.div)(t);this.menu.appendChild(e)}e.length>0&&this.menu.children[0].classList.add(a.active)}_show_menu(){if(!this._open){this._open=!0,this._hover_index=0,this._last_value=this.model.value,(0,u.display)(this.menu);const e=t=>{const{target:n}=t;n instanceof HTMLElement&&!this.el.contains(n)&&(document.removeEventListener(\"click\",e),this._hide_menu())};document.addEventListener(\"click\",e)}}_hide_menu(){this._open&&(this._open=!1,(0,u.undisplay)(this.menu))}_menu_click(e){e.target!=e.currentTarget&&e.target instanceof Element&&(this.model.value=e.target.textContent,this.input_el.focus(),this._hide_menu())}_menu_hover(e){if(e.target!=e.currentTarget&&e.target instanceof Element){let t=0;for(t=0;t0&&(this.menu.children[this._hover_index].classList.remove(a.active),this._hover_index=(0,r.clamp)(e,0,t-1),this.menu.children[this._hover_index].classList.add(a.active))}_keydown(e){}_keyup(e){switch(e.keyCode){case u.Keys.Enter:this.change_input();break;case u.Keys.Esc:this._hide_menu();break;case u.Keys.Up:this._bump_hover(this._hover_index-1);break;case u.Keys.Down:this._bump_hover(this._hover_index+1);break;default:{const e=this.input_el.value;if(e.lengthe:e=>e.toLowerCase();for(const n of this.model.completions)s(n).startsWith(s(e))&&t.push(n);this._update_completions(t),0==t.length?this._hide_menu():this._show_menu()}}}}n.AutocompleteInputView=l,l.__name__=\"AutocompleteInputView\";class d extends _.TextInput{constructor(e){super(e)}}n.AutocompleteInput=d,o=d,d.__name__=\"AutocompleteInput\",o.prototype.default_view=l,o.define((({Boolean:e,Int:t,String:n,Array:s})=>({completions:[s(n),[]],min_characters:[t,2],case_sensitive:[e,!0],restrict:[e,!0]})))},\n", - " 443: function _(t,e,n,p,_){p();const u=t(1);var i;const s=t(444),r=t(43),x=(0,u.__importStar)(t(446));class a extends s.TextLikeInputView{_render_input(){this.input_el=(0,r.input)({type:\"text\",class:x.input})}}n.TextInputView=a,a.__name__=\"TextInputView\";class c extends s.TextLikeInput{constructor(t){super(t)}}n.TextInput=c,i=c,c.__name__=\"TextInput\",i.prototype.default_view=a},\n", - " 444: function _(e,t,n,i,l){var s;i();const h=e(445);class a extends h.InputWidgetView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.name.change,(()=>{var e;return this.input_el.name=null!==(e=this.model.name)&&void 0!==e?e:\"\"})),this.connect(this.model.properties.value.change,(()=>this.input_el.value=this.model.value)),this.connect(this.model.properties.value_input.change,(()=>this.input_el.value=this.model.value_input)),this.connect(this.model.properties.disabled.change,(()=>this.input_el.disabled=this.model.disabled)),this.connect(this.model.properties.placeholder.change,(()=>this.input_el.placeholder=this.model.placeholder)),this.connect(this.model.properties.max_length.change,(()=>{const{max_length:e}=this.model;null!=e?this.input_el.maxLength=e:this.input_el.removeAttribute(\"maxLength\")}))}render(){var e;super.render(),this._render_input();const{input_el:t}=this;t.name=null!==(e=this.model.name)&&void 0!==e?e:\"\",t.value=this.model.value,t.disabled=this.model.disabled,t.placeholder=this.model.placeholder,null!=this.model.max_length&&(t.maxLength=this.model.max_length),t.addEventListener(\"change\",(()=>this.change_input())),t.addEventListener(\"input\",(()=>this.change_input_value())),this.group_el.appendChild(t)}change_input(){this.model.value=this.input_el.value,super.change_input()}change_input_value(){this.model.value_input=this.input_el.value,super.change_input()}}n.TextLikeInputView=a,a.__name__=\"TextLikeInputView\";class u extends h.InputWidget{constructor(e){super(e)}}n.TextLikeInput=u,s=u,u.__name__=\"TextLikeInput\",s.define((({Int:e,String:t,Nullable:n})=>({value:[t,\"\"],value_input:[t,\"\"],placeholder:[t,\"\"],max_length:[n(e),null]})))},\n", - " 445: function _(e,t,n,s,l){s();const i=e(1);var o;const r=e(439),_=e(43),p=(0,i.__importStar)(e(446)),a=p;class c extends r.ControlView{*controls(){yield this.input_el}connect_signals(){super.connect_signals(),this.connect(this.model.properties.title.change,(()=>{this.label_el.textContent=this.model.title}))}styles(){return[...super.styles(),p.default]}render(){super.render();const{title:e}=this.model;this.label_el=(0,_.label)({style:{display:0==e.length?\"none\":\"\"}},e),this.group_el=(0,_.div)({class:a.input_group},this.label_el),this.el.appendChild(this.group_el)}change_input(){}}n.InputWidgetView=c,c.__name__=\"InputWidgetView\";class d extends r.Control{constructor(e){super(e)}}n.InputWidget=d,o=d,d.__name__=\"InputWidget\",o.define((({String:e})=>({title:[e,\"\"]})))},\n", - " 446: function _(o,p,t,n,i){n(),t.root=\"bk-root\",t.input=\"bk-input\",t.input_group=\"bk-input-group\",t.inline=\"bk-inline\",t.spin_wrapper=\"bk-spin-wrapper\",t.spin_btn=\"bk-spin-btn\",t.spin_btn_up=\"bk-spin-btn-up\",t.spin_btn_down=\"bk-spin-btn-down\",t.default='.bk-root .bk-input{display:inline-block;width:100%;flex-grow:1;min-height:31px;padding:0 12px;background-color:#fff;border:1px solid #ccc;border-radius:4px;}.bk-root .bk-input:focus{border-color:#66afe9;outline:0;box-shadow:inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 8px rgba(102, 175, 233, 0.6);}.bk-root .bk-input::placeholder,.bk-root .bk-input:-ms-input-placeholder,.bk-root .bk-input::-moz-placeholder,.bk-root .bk-input::-webkit-input-placeholder{color:#999;opacity:1;}.bk-root .bk-input[disabled]{cursor:not-allowed;background-color:#eee;opacity:1;}.bk-root select:not([multiple]).bk-input,.bk-root select:not([size]).bk-input{height:auto;appearance:none;-webkit-appearance:none;background-image:url(\\'data:image/svg+xml;utf8,\\');background-position:right 0.5em center;background-size:8px 6px;background-repeat:no-repeat;}.bk-root select[multiple].bk-input,.bk-root select[size].bk-input,.bk-root textarea.bk-input{height:auto;}.bk-root .bk-input-group{width:100%;height:100%;display:inline-flex;flex-wrap:nowrap;align-items:start;flex-direction:column;white-space:nowrap;}.bk-root .bk-input-group.bk-inline{flex-direction:row;}.bk-root .bk-input-group.bk-inline > *:not(:first-child){margin-left:5px;}.bk-root .bk-input-group input[type=\"checkbox\"] + span,.bk-root .bk-input-group input[type=\"radio\"] + span{position:relative;top:-2px;margin-left:3px;}.bk-root .bk-input-group > .bk-spin-wrapper{display:inherit;width:inherit;height:inherit;position:relative;overflow:hidden;padding:0;vertical-align:middle;}.bk-root .bk-input-group > .bk-spin-wrapper input{padding-right:20px;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn{position:absolute;display:block;height:50%;min-height:0;min-width:0;width:30px;padding:0;margin:0;right:0;border:none;background:none;cursor:pointer;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn:before{content:\"\";display:inline-block;transform:translateY(-50%);border-left:5px solid transparent;border-right:5px solid transparent;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-up{top:0;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-up:before{border-bottom:5px solid black;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-up:disabled:before{border-bottom-color:grey;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-down{bottom:0;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-down:before{border-top:5px solid black;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-down:disabled:before{border-top-color:grey;}'},\n", - " 447: function _(t,e,n,o,c){var s;o();const u=t(438),r=t(251);class i extends u.AbstractButtonView{click(){this.model.trigger_event(new r.ButtonClick),super.click()}}n.ButtonView=i,i.__name__=\"ButtonView\";class _ extends u.AbstractButton{constructor(t){super(t)}}n.Button=_,s=_,_.__name__=\"Button\",s.prototype.default_view=i,s.override({label:\"Button\"})},\n", - " 448: function _(t,e,o,c,a){c();const s=t(1);var n;const i=t(449),r=t(43),u=(0,s.__importStar)(t(318));class _ extends i.ButtonGroupView{get active(){return new Set(this.model.active)}change_active(t){const{active:e}=this;e.has(t)?e.delete(t):e.add(t),this.model.active=[...e].sort()}_update_active(){const{active:t}=this;this._buttons.forEach(((e,o)=>{(0,r.classes)(e).toggle(u.active,t.has(o))}))}}o.CheckboxButtonGroupView=_,_.__name__=\"CheckboxButtonGroupView\";class h extends i.ButtonGroup{constructor(t){super(t)}}o.CheckboxButtonGroup=h,n=h,h.__name__=\"CheckboxButtonGroup\",n.prototype.default_view=_,n.define((({Int:t,Array:e})=>({active:[e(t),[]]})))},\n", - " 449: function _(t,e,n,s,i){s();const o=t(1);var r;const a=t(450),l=t(20),d=t(43),u=(0,o.__importStar)(t(318)),_=u;class c extends a.OrientedControlView{get default_size(){return\"horizontal\"==this.orientation?this.model.default_size:void 0}*controls(){yield*this._buttons}connect_signals(){super.connect_signals();const t=this.model.properties;this.on_change(t.button_type,(()=>this.render())),this.on_change(t.labels,(()=>this.render())),this.on_change(t.active,(()=>this._update_active()))}styles(){return[...super.styles(),u.default]}render(){super.render(),this._buttons=this.model.labels.map(((t,e)=>{const n=(0,d.div)({class:[_.btn,_[`btn_${this.model.button_type}`]],disabled:this.model.disabled},t);return n.addEventListener(\"click\",(()=>this.change_active(e))),n})),this._update_active();const t=\"horizontal\"==this.model.orientation?_.horizontal:_.vertical,e=(0,d.div)({class:[_.btn_group,t]},this._buttons);this.el.appendChild(e)}}n.ButtonGroupView=c,c.__name__=\"ButtonGroupView\";class h extends a.OrientedControl{constructor(t){super(t)}}n.ButtonGroup=h,r=h,h.__name__=\"ButtonGroup\",r.define((({String:t,Array:e})=>({labels:[e(t),[]],button_type:[l.ButtonType,\"default\"]})))},\n", - " 450: function _(n,t,e,o,r){var i;o();const a=n(439),l=n(20);class s extends a.ControlView{get orientation(){return this.model.orientation}}e.OrientedControlView=s,s.__name__=\"OrientedControlView\";class _ extends a.Control{constructor(n){super(n)}}e.OrientedControl=_,i=_,_.__name__=\"OrientedControl\",i.define((()=>({orientation:[l.Orientation,\"horizontal\"]})))},\n", - " 451: function _(e,t,n,i,s){i();const o=e(1);var a;const c=e(452),l=e(43),d=e(9),p=(0,o.__importStar)(e(446));class r extends c.InputGroupView{render(){super.render();const e=(0,l.div)({class:[p.input_group,this.model.inline?p.inline:null]});this.el.appendChild(e);const{active:t,labels:n}=this.model;this._inputs=[];for(let i=0;ithis.change_active(i))),this._inputs.push(s),this.model.disabled&&(s.disabled=!0),(0,d.includes)(t,i)&&(s.checked=!0);const o=(0,l.label)(s,(0,l.span)(n[i]));e.appendChild(o)}}change_active(e){const t=new Set(this.model.active);t.has(e)?t.delete(e):t.add(e),this.model.active=[...t].sort()}}n.CheckboxGroupView=r,r.__name__=\"CheckboxGroupView\";class h extends c.InputGroup{constructor(e){super(e)}}n.CheckboxGroup=h,a=h,h.__name__=\"CheckboxGroup\",a.prototype.default_view=r,a.define((({Boolean:e,Int:t,String:n,Array:i})=>({active:[i(t),[]],labels:[i(n),[]],inline:[e,!1]})))},\n", - " 452: function _(n,t,e,s,o){s();const r=n(1),u=n(439),c=(0,r.__importDefault)(n(446));class _ extends u.ControlView{*controls(){yield*this._inputs}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.render()))}styles(){return[...super.styles(),c.default]}}e.InputGroupView=_,_.__name__=\"InputGroupView\";class i extends u.Control{constructor(n){super(n)}}e.InputGroup=i,i.__name__=\"InputGroup\"},\n", - " 453: function _(e,t,i,n,o){n();const s=e(1);var l;const r=e(445),c=e(43),a=e(22),d=(0,s.__importStar)(e(446));class h extends r.InputWidgetView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.name.change,(()=>{var e;return this.input_el.name=null!==(e=this.model.name)&&void 0!==e?e:\"\"})),this.connect(this.model.properties.color.change,(()=>this.input_el.value=(0,a.color2hexrgb)(this.model.color))),this.connect(this.model.properties.disabled.change,(()=>this.input_el.disabled=this.model.disabled))}render(){super.render(),this.input_el=(0,c.input)({type:\"color\",class:d.input,name:this.model.name,value:this.model.color,disabled:this.model.disabled}),this.input_el.addEventListener(\"change\",(()=>this.change_input())),this.group_el.appendChild(this.input_el)}change_input(){this.model.color=this.input_el.value,super.change_input()}}i.ColorPickerView=h,h.__name__=\"ColorPickerView\";class p extends r.InputWidget{constructor(e){super(e)}}i.ColorPicker=p,l=p,p.__name__=\"ColorPicker\",l.prototype.default_view=h,l.define((({Color:e})=>({color:[e,\"#000000\"]})))},\n", - " 454: function _(e,t,i,n,s){n();const a=e(1);var l;const o=(0,a.__importDefault)(e(455)),d=e(445),r=e(43),c=e(20),u=e(8),h=(0,a.__importStar)(e(446)),_=(0,a.__importDefault)(e(456));function p(e){const t=[];for(const i of e)if((0,u.isString)(i))t.push(i);else{const[e,n]=i;t.push({from:e,to:n})}return t}class m extends d.InputWidgetView{connect_signals(){super.connect_signals();const{value:e,min_date:t,max_date:i,disabled_dates:n,enabled_dates:s,position:a,inline:l}=this.model.properties;this.connect(e.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.setDate(this.model.value)})),this.connect(t.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"minDate\",this.model.min_date)})),this.connect(i.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"maxDate\",this.model.max_date)})),this.connect(n.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"disable\",this.model.disabled_dates)})),this.connect(s.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"enable\",this.model.enabled_dates)})),this.connect(a.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"position\",this.model.position)})),this.connect(l.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"inline\",this.model.inline)}))}remove(){var e;null===(e=this._picker)||void 0===e||e.destroy(),super.remove()}styles(){return[...super.styles(),_.default]}render(){var e,t;null==this._picker&&(super.render(),this.input_el=(0,r.input)({type:\"text\",class:h.input,disabled:this.model.disabled}),this.group_el.appendChild(this.input_el),this._picker=(0,o.default)(this.input_el,{defaultDate:this.model.value,minDate:null!==(e=this.model.min_date)&&void 0!==e?e:void 0,maxDate:null!==(t=this.model.max_date)&&void 0!==t?t:void 0,inline:this.model.inline,position:this.model.position,disable:p(this.model.disabled_dates),enable:p(this.model.enabled_dates),onChange:(e,t,i)=>this._on_change(e,t,i)}))}_on_change(e,t,i){this.model.value=t,this.change_input()}}i.DatePickerView=m,m.__name__=\"DatePickerView\";class v extends d.InputWidget{constructor(e){super(e)}}i.DatePicker=v,l=v,v.__name__=\"DatePicker\",l.prototype.default_view=m,l.define((({Boolean:e,String:t,Array:i,Tuple:n,Or:s,Nullable:a})=>{const l=i(s(t,n(t,t)));return{value:[t],min_date:[a(t),null],max_date:[a(t),null],disabled_dates:[l,[]],enabled_dates:[l,[]],position:[c.CalendarPosition,\"auto\"],inline:[e,!1]}}))},\n", - " 455: function _(e,n,t,a,i){\n", - " /* flatpickr v4.6.6, @license MIT */var o,r;o=this,r=function(){\"use strict\";\n", - " /*! *****************************************************************************\n", - " Copyright (c) Microsoft Corporation.\n", - " \n", - " Permission to use, copy, modify, and/or distribute this software for any\n", - " purpose with or without fee is hereby granted.\n", - " \n", - " THE SOFTWARE IS PROVIDED \"AS IS\" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH\n", - " REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY\n", - " AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,\n", - " INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM\n", - " LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR\n", - " OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR\n", - " PERFORMANCE OF THIS SOFTWARE.\n", - " ***************************************************************************** */var e=function(){return e=Object.assign||function(e){for(var n,t=1,a=arguments.length;t\",noCalendar:!1,now:new Date,onChange:[],onClose:[],onDayCreate:[],onDestroy:[],onKeyDown:[],onMonthChange:[],onOpen:[],onParseConfig:[],onReady:[],onValueUpdate:[],onYearChange:[],onPreCalendarPosition:[],plugins:[],position:\"auto\",positionElement:void 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e.slice().map((function(e){return\"string\"==typeof e||\"number\"==typeof e||e instanceof Date?w.parseDate(e,void 0,!0):e&&\"object\"==typeof e&&e.from&&e.to?{from:w.parseDate(e.from,void 0),to:w.parseDate(e.to,void 0)}:e})).filter((function(e){return e}))}function pe(e,n){if(void 0!==w.config){var t=w.config[e];if(void 0!==t&&t.length>0)for(var a=0;t[a]&&a1||\"static\"===w.config.monthSelectorType?w.monthElements[n].textContent=h(t.getMonth(),w.config.shorthandCurrentMonth,w.l10n)+\" \":w.monthsDropdownContainer.value=t.getMonth().toString(),e.value=t.getFullYear().toString()})),w._hidePrevMonthArrow=void 0!==w.config.minDate&&(w.currentYear===w.config.minDate.getFullYear()?w.currentMonth<=w.config.minDate.getMonth():w.currentYearw.config.maxDate.getMonth():w.currentYear>w.config.maxDate.getFullYear()))}function we(e){return w.selectedDates.map((function(n){return w.formatDate(n,e)})).filter((function(e,n,t){return\"range\"!==w.config.mode||w.config.enableTime||t.indexOf(e)===n})).join(\"range\"!==w.config.mode?w.config.conjunction:w.l10n.rangeSeparator)}function be(e){void 0===e&&(e=!0),void 0!==w.mobileInput&&w.mobileFormatStr&&(w.mobileInput.value=void 0!==w.latestSelectedDateObj?w.formatDate(w.latestSelectedDateObj,w.mobileFormatStr):\"\"),w.input.value=we(w.config.dateFormat),void 0!==w.altInput&&(w.altInput.value=we(w.config.altFormat)),!1!==e&&pe(\"onValueUpdate\")}function Ce(e){var n=g(e),t=w.prevMonthNav.contains(n),a=w.nextMonthNav.contains(n);t||a?G(t?-1:1):w.yearElements.indexOf(n)>=0?n.select():n.classList.contains(\"arrowUp\")?w.changeYear(w.currentYear+1):n.classList.contains(\"arrowDown\")&&w.changeYear(w.currentYear-1)}return function(){w.element=w.input=p,w.isOpen=!1,function(){var n=[\"wrap\",\"weekNumbers\",\"allowInput\",\"allowInvalidPreload\",\"clickOpens\",\"time_24hr\",\"enableTime\",\"noCalendar\",\"altInput\",\"shorthandCurrentMonth\",\"inline\",\"static\",\"enableSeconds\",\"disableMobile\"],i=e(e({},JSON.parse(JSON.stringify(p.dataset||{}))),v),o={};w.config.parseDate=i.parseDate,w.config.formatDate=i.formatDate,Object.defineProperty(w.config,\"enable\",{get:function(){return w.config._enable},set:function(e){w.config._enable=ge(e)}}),Object.defineProperty(w.config,\"disable\",{get:function(){return w.config._disable},set:function(e){w.config._disable=ge(e)}});var r=\"time\"===i.mode;if(!i.dateFormat&&(i.enableTime||r)){var l=k.defaultConfig.dateFormat||a.dateFormat;o.dateFormat=i.noCalendar||r?\"H:i\"+(i.enableSeconds?\":S\":\"\"):l+\" H:i\"+(i.enableSeconds?\":S\":\"\")}if(i.altInput&&(i.enableTime||r)&&!i.altFormat){var d=k.defaultConfig.altFormat||a.altFormat;o.altFormat=i.noCalendar||r?\"h:i\"+(i.enableSeconds?\":S K\":\" K\"):d+\" h:i\"+(i.enableSeconds?\":S\":\"\")+\" K\"}Object.defineProperty(w.config,\"minDate\",{get:function(){return w.config._minDate},set:oe(\"min\")}),Object.defineProperty(w.config,\"maxDate\",{get:function(){return w.config._maxDate},set:oe(\"max\")});var s=function(e){return function(n){w.config[\"min\"===e?\"_minTime\":\"_maxTime\"]=w.parseDate(n,\"H:i:S\")}};Object.defineProperty(w.config,\"minTime\",{get:function(){return w.config._minTime},set:s(\"min\")}),Object.defineProperty(w.config,\"maxTime\",{get:function(){return w.config._maxTime},set:s(\"max\")}),\"time\"===i.mode&&(w.config.noCalendar=!0,w.config.enableTime=!0),Object.assign(w.config,o,i);for(var u=0;u-1?w.config[m]=c(f[m]).map(x).concat(w.config[m]):void 0===i[m]&&(w.config[m]=f[m])}i.altInputClass||(w.config.altInputClass=re().className+\" \"+w.config.altInputClass),pe(\"onParseConfig\")}(),le(),w.input=re(),w.input?(w.input._type=w.input.type,w.input.type=\"text\",w.input.classList.add(\"flatpickr-input\"),w._input=w.input,w.config.altInput&&(w.altInput=s(w.input.nodeName,w.config.altInputClass),w._input=w.altInput,w.altInput.placeholder=w.input.placeholder,w.altInput.disabled=w.input.disabled,w.altInput.required=w.input.required,w.altInput.tabIndex=w.input.tabIndex,w.altInput.type=\"text\",w.input.setAttribute(\"type\",\"hidden\"),!w.config.static&&w.input.parentNode&&w.input.parentNode.insertBefore(w.altInput,w.input.nextSibling)),w.config.allowInput||w._input.setAttribute(\"readonly\",\"readonly\"),w._positionElement=w.config.positionElement||w._input):w.config.errorHandler(new Error(\"Invalid input element specified\")),function(){w.selectedDates=[],w.now=w.parseDate(w.config.now)||new Date;var e=w.config.defaultDate||(\"INPUT\"!==w.input.nodeName&&\"TEXTAREA\"!==w.input.nodeName||!w.input.placeholder||w.input.value!==w.input.placeholder?w.input.value:null);e&&me(e,w.config.dateFormat),w._initialDate=w.selectedDates.length>0?w.selectedDates[0]:w.config.minDate&&w.config.minDate.getTime()>w.now.getTime()?w.config.minDate:w.config.maxDate&&w.config.maxDate.getTime()0&&(w.latestSelectedDateObj=w.selectedDates[0]),void 0!==w.config.minTime&&(w.config.minTime=w.parseDate(w.config.minTime,\"H:i\")),void 0!==w.config.maxTime&&(w.config.maxTime=w.parseDate(w.config.maxTime,\"H:i\")),w.minDateHasTime=!!w.config.minDate&&(w.config.minDate.getHours()>0||w.config.minDate.getMinutes()>0||w.config.minDate.getSeconds()>0),w.maxDateHasTime=!!w.config.maxDate&&(w.config.maxDate.getHours()>0||w.config.maxDate.getMinutes()>0||w.config.maxDate.getSeconds()>0)}(),w.utils={getDaysInMonth:function(e,n){return void 0===e&&(e=w.currentMonth),void 0===n&&(n=w.currentYear),1===e&&(n%4==0&&n%100!=0||n%400==0)?29:w.l10n.daysInMonth[e]}},w.isMobile||function(){var e=window.document.createDocumentFragment();if(w.calendarContainer=s(\"div\",\"flatpickr-calendar\"),w.calendarContainer.tabIndex=-1,!w.config.noCalendar){if(e.appendChild((w.monthNav=s(\"div\",\"flatpickr-months\"),w.yearElements=[],w.monthElements=[],w.prevMonthNav=s(\"span\",\"flatpickr-prev-month\"),w.prevMonthNav.innerHTML=w.config.prevArrow,w.nextMonthNav=s(\"span\",\"flatpickr-next-month\"),w.nextMonthNav.innerHTML=w.config.nextArrow,q(),Object.defineProperty(w,\"_hidePrevMonthArrow\",{get:function(){return w.__hidePrevMonthArrow},set:function(e){w.__hidePrevMonthArrow!==e&&(d(w.prevMonthNav,\"flatpickr-disabled\",e),w.__hidePrevMonthArrow=e)}}),Object.defineProperty(w,\"_hideNextMonthArrow\",{get:function(){return w.__hideNextMonthArrow},set:function(e){w.__hideNextMonthArrow!==e&&(d(w.nextMonthNav,\"flatpickr-disabled\",e),w.__hideNextMonthArrow=e)}}),w.currentYearElement=w.yearElements[0],De(),w.monthNav)),w.innerContainer=s(\"div\",\"flatpickr-innerContainer\"),w.config.weekNumbers){var n=function(){w.calendarContainer.classList.add(\"hasWeeks\");var e=s(\"div\",\"flatpickr-weekwrapper\");e.appendChild(s(\"span\",\"flatpickr-weekday\",w.l10n.weekAbbreviation));var n=s(\"div\",\"flatpickr-weeks\");return e.appendChild(n),{weekWrapper:e,weekNumbers:n}}(),t=n.weekWrapper,a=n.weekNumbers;w.innerContainer.appendChild(t),w.weekNumbers=a,w.weekWrapper=t}w.rContainer=s(\"div\",\"flatpickr-rContainer\"),w.rContainer.appendChild($()),w.daysContainer||(w.daysContainer=s(\"div\",\"flatpickr-days\"),w.daysContainer.tabIndex=-1),J(),w.rContainer.appendChild(w.daysContainer),w.innerContainer.appendChild(w.rContainer),e.appendChild(w.innerContainer)}w.config.enableTime&&e.appendChild(function(){w.calendarContainer.classList.add(\"hasTime\"),w.config.noCalendar&&w.calendarContainer.classList.add(\"noCalendar\"),w.timeContainer=s(\"div\",\"flatpickr-time\"),w.timeContainer.tabIndex=-1;var e=s(\"span\",\"flatpickr-time-separator\",\":\"),n=m(\"flatpickr-hour\",{\"aria-label\":w.l10n.hourAriaLabel});w.hourElement=n.getElementsByTagName(\"input\")[0];var t=m(\"flatpickr-minute\",{\"aria-label\":w.l10n.minuteAriaLabel});if(w.minuteElement=t.getElementsByTagName(\"input\")[0],w.hourElement.tabIndex=w.minuteElement.tabIndex=-1,w.hourElement.value=o(w.latestSelectedDateObj?w.latestSelectedDateObj.getHours():w.config.time_24hr?w.config.defaultHour:function(e){switch(e%24){case 0:case 12:return 12;default:return 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a=m(\"flatpickr-second\");w.secondElement=a.getElementsByTagName(\"input\")[0],w.secondElement.value=o(w.latestSelectedDateObj?w.latestSelectedDateObj.getSeconds():w.config.defaultSeconds),w.secondElement.setAttribute(\"step\",w.minuteElement.getAttribute(\"step\")),w.secondElement.setAttribute(\"min\",\"0\"),w.secondElement.setAttribute(\"max\",\"59\"),w.timeContainer.appendChild(s(\"span\",\"flatpickr-time-separator\",\":\")),w.timeContainer.appendChild(a)}return w.config.time_24hr||(w.amPM=s(\"span\",\"flatpickr-am-pm\",w.l10n.amPM[r((w.latestSelectedDateObj?w.hourElement.value:w.config.defaultHour)>11)]),w.amPM.title=w.l10n.toggleTitle,w.amPM.tabIndex=-1,w.timeContainer.appendChild(w.amPM)),w.timeContainer}()),d(w.calendarContainer,\"rangeMode\",\"range\"===w.config.mode),d(w.calendarContainer,\"animate\",!0===w.config.animate),d(w.calendarContainer,\"multiMonth\",w.config.showMonths>1),w.calendarContainer.appendChild(e);var i=void 0!==w.config.appendTo&&void 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null!==o&&!1!==o&&(o=Number(o.toFixed(a))),null!==s&&!1!==s&&(s=Number(s.toFixed(a))),[s,o]}f(b=w,r.cssClasses.target),0===r.dir?f(b,r.cssClasses.ltr):f(b,r.cssClasses.rtl),0===r.ort?f(b,r.cssClasses.horizontal):f(b,r.cssClasses.vertical),f(b,\"rtl\"===getComputedStyle(b).direction?r.cssClasses.textDirectionRtl:r.cssClasses.textDirectionLtr),a=T(b,r.cssClasses.base),function(t,e){var n=T(e,r.cssClasses.connects);p=[],(m=[]).push(z(n,t[0]));for(var i=0;i=0&&t .noUi-tooltip{-webkit-transform:translate(50%, 0);transform:translate(50%, 0);left:auto;bottom:10px;}.bk-root .noUi-vertical .noUi-origin > .noUi-tooltip{-webkit-transform:translate(0, -18px);transform:translate(0, -18px);top:auto;right:28px;}.bk-root .noUi-handle{cursor:grab;cursor:-webkit-grab;}.bk-root .noUi-handle.noUi-active{cursor:grabbing;cursor:-webkit-grabbing;}.bk-root .noUi-handle:after,.bk-root .noUi-handle:before{display:none;}.bk-root .noUi-tooltip{display:none;white-space:nowrap;}.bk-root .noUi-handle:hover 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i=e.split(this.options.tokenSeparator),n=0,s=i.length;n0&&void 0!==arguments[0]?arguments[0]:[],t=arguments.length>1?arguments[1]:void 0,i=this.list,n={},s=[];if(\"string\"==typeof i[0]){for(var r=0,o=i.length;r1)throw new Error(\"Key weight has to be > 0 and <= 1\");p=p.name}else a[p]={weight:1};this._analyze({key:p,value:this.options.getFn(h,p),record:h,index:c},{resultMap:n,results:s,tokenSearchers:e,fullSearcher:t})}return{weights:a,results:s}}},{key:\"_analyze\",value:function(e,t){var i=e.key,n=e.arrayIndex,s=void 0===n?-1:n,r=e.value,o=e.record,c=e.index,l=t.tokenSearchers,h=void 0===l?[]:l,u=t.fullSearcher,d=void 0===u?[]:u,p=t.resultMap,m=void 0===p?{}:p,f=t.results,v=void 0===f?[]:f;if(null!=r){var g=!1,_=-1,b=0;if(\"string\"==typeof r){this._log(\"\\nKey: \".concat(\"\"===i?\"-\":i));var y=d.search(r);if(this._log('Full text: \"'.concat(r,'\", score: ').concat(y.score)),this.options.tokenize){for(var E=r.split(this.options.tokenSeparator),I=[],S=0;S-1&&(P=(P+_)/2),this._log(\"Score average:\",P);var D=!this.options.tokenize||!this.options.matchAllTokens||b>=h.length;if(this._log(\"\\nCheck Matches: \".concat(D)),(g||y.isMatch)&&D){var M=m[c];M?M.output.push({key:i,arrayIndex:s,value:r,score:P,matchedIndices:y.matchedIndices}):(m[c]={item:o,output:[{key:i,arrayIndex:s,value:r,score:P,matchedIndices:y.matchedIndices}]},v.push(m[c]))}}else if(a(r))for(var N=0,F=r.length;N-1&&(o.arrayIndex=r.arrayIndex),t.matches.push(o)}}})),this.options.includeScore&&s.push((function(e,t){t.score=e.score}));for(var r=0,o=e.length;ri)return s(e,this.pattern,n);var o=this.options,a=o.location,c=o.distance,l=o.threshold,h=o.findAllMatches,u=o.minMatchCharLength;return r(e,this.pattern,this.patternAlphabet,{location:a,distance:c,threshold:l,findAllMatches:h,minMatchCharLength:u})}}])&&n(t.prototype,i),a&&n(t,a),e}();e.exports=a},function(e,t){var i=/[\\-\\[\\]\\/\\{\\}\\(\\)\\*\\+\\?\\.\\\\\\^\\$\\|]/g;e.exports=function(e,t){var n=arguments.length>2&&void 0!==arguments[2]?arguments[2]:/ +/g,s=new RegExp(t.replace(i,\"\\\\$&\").replace(n,\"|\")),r=e.match(s),o=!!r,a=[];if(o)for(var c=0,l=r.length;c=P;N-=1){var F=N-1,j=i[e.charAt(F)];if(j&&(E[F]=1),M[N]=(M[N+1]<<1|1)&j,0!==T&&(M[N]|=(O[N+1]|O[N])<<1|1|O[N+1]),M[N]&L&&(C=n(t,{errors:T,currentLocation:F,expectedLocation:v,distance:l}))<=_){if(_=C,(b=F)<=v)break;P=Math.max(1,2*v-b)}}if(n(t,{errors:T+1,currentLocation:v,expectedLocation:v,distance:l})>_)break;O=M}return{isMatch:b>=0,score:0===C?.001:C,matchedIndices:s(E,f)}}},function(e,t){e.exports=function(e,t){var i=t.errors,n=void 0===i?0:i,s=t.currentLocation,r=void 0===s?0:s,o=t.expectedLocation,a=void 0===o?0:o,c=t.distance,l=void 0===c?100:c,h=n/e.length,u=Math.abs(a-r);return l?h+u/l:u?1:h}},function(e,t){e.exports=function(){for(var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:[],t=arguments.length>1&&void 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e(e){var t=e.element,i=e.type,n=e.classNames,s=e.position;this.element=t,this.classNames=n,this.type=i,this.position=s,this.isOpen=!1,this.isFlipped=!1,this.isFocussed=!1,this.isDisabled=!1,this.isLoading=!1,this._onFocus=this._onFocus.bind(this),this._onBlur=this._onBlur.bind(this)}var t=e.prototype;return t.addEventListeners=function(){this.element.addEventListener(\"focus\",this._onFocus),this.element.addEventListener(\"blur\",this._onBlur)},t.removeEventListeners=function(){this.element.removeEventListener(\"focus\",this._onFocus),this.element.removeEventListener(\"blur\",this._onBlur)},t.shouldFlip=function(e){if(\"number\"!=typeof e)return!1;var t=!1;return\"auto\"===this.position?t=!window.matchMedia(\"(min-height: 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0===t&&(t=document.createElement(\"div\")),e.nextSibling?e.parentNode.insertBefore(t,e.nextSibling):e.parentNode.appendChild(t),t.appendChild(e)}(e,this.element)},t.unwrap=function(e){this.element.parentNode.insertBefore(e,this.element),this.element.parentNode.removeChild(this.element)},t.addLoadingState=function(){this.element.classList.add(this.classNames.loadingState),this.element.setAttribute(\"aria-busy\",\"true\"),this.isLoading=!0},t.removeLoadingState=function(){this.element.classList.remove(this.classNames.loadingState),this.element.removeAttribute(\"aria-busy\"),this.isLoading=!1},t._onFocus=function(){this.isFocussed=!0},t._onBlur=function(){this.isFocussed=!1},e}();function le(e,t){for(var i=0;i0?this.element.scrollTop+o-s:e.offsetTop;requestAnimationFrame((function(){i._animateScroll(a,t)}))}},t._scrollDown=function(e,t,i){var n=(i-e)/t,s=n>1?n:1;this.element.scrollTop=e+s},t._scrollUp=function(e,t,i){var n=(e-i)/t,s=n>1?n:1;this.element.scrollTop=e-s},t._animateScroll=function(e,t){var i=this,n=this.element.scrollTop,s=!1;t>0?(this._scrollDown(n,4,e),ne&&(s=!0)),s&&requestAnimationFrame((function(){i._animateScroll(e,t)}))},e}();function de(e,t){for(var i=0;i0?\"treeitem\":\"option\"),Object.assign(g.dataset,{choice:\"\",id:l,value:h,selectText:i}),m?(g.classList.add(a),g.dataset.choiceDisabled=\"\",g.setAttribute(\"aria-disabled\",\"true\")):(g.classList.add(r),g.dataset.choiceSelectable=\"\"),g},input:function(e,t){var i=e.input,n=e.inputCloned,s=Object.assign(document.createElement(\"input\"),{type:\"text\",className:i+\" \"+n,autocomplete:\"off\",autocapitalize:\"off\",spellcheck:!1});return s.setAttribute(\"role\",\"textbox\"),s.setAttribute(\"aria-autocomplete\",\"list\"),s.setAttribute(\"aria-label\",t),s},dropdown:function(e){var t=e.list,i=e.listDropdown,n=document.createElement(\"div\");return n.classList.add(t,i),n.setAttribute(\"aria-expanded\",\"false\"),n},notice:function(e,t,i){var n=e.item,s=e.itemChoice,r=e.noResults,o=e.noChoices;void 0===i&&(i=\"\");var a=[n,s];return\"no-choices\"===i?a.push(o):\"no-results\"===i&&a.push(r),Object.assign(document.createElement(\"div\"),{innerHTML:t,className:a.join(\" \")})},option:function(e){var t=e.label,i=e.value,n=e.customProperties,s=e.active,r=e.disabled,o=new Option(t,i,!1,s);return n&&(o.dataset.customProperties=n),o.disabled=r,o}},be=function(e){return void 0===e&&(e=!0),{type:q,active:e}},ye=function(e,t){return{type:$,id:e,highlighted:t}},Ee=function(e){var t=e.value,i=e.id,n=e.active,s=e.disabled;return{type:z,value:t,id:i,active:n,disabled:s}},Ie=function(e){return{type:\"SET_IS_LOADING\",isLoading:e}};function Se(e,t){for(var i=0;i=0?this._store.getGroupById(s):null;return this._store.dispatch(ye(i,!0)),t&&this.passedElement.triggerEvent(H,{id:i,value:o,label:c,groupValue:l&&l.value?l.value:null}),this},r.unhighlightItem=function(e){if(!e)return this;var t=e.id,i=e.groupId,n=void 0===i?-1:i,s=e.value,r=void 0===s?\"\":s,o=e.label,a=void 0===o?\"\":o,c=n>=0?this._store.getGroupById(n):null;return this._store.dispatch(ye(t,!1)),this.passedElement.triggerEvent(H,{id:t,value:r,label:a,groupValue:c&&c.value?c.value:null}),this},r.highlightAll=function(){var e=this;return this._store.items.forEach((function(t){return e.highlightItem(t)})),this},r.unhighlightAll=function(){var e=this;return this._store.items.forEach((function(t){return e.unhighlightItem(t)})),this},r.removeActiveItemsByValue=function(e){var t=this;return this._store.activeItems.filter((function(t){return t.value===e})).forEach((function(e){return t._removeItem(e)})),this},r.removeActiveItems=function(e){var t=this;return this._store.activeItems.filter((function(t){return t.id!==e})).forEach((function(e){return t._removeItem(e)})),this},r.removeHighlightedItems=function(e){var t=this;return void 0===e&&(e=!1),this._store.highlightedActiveItems.forEach((function(i){t._removeItem(i),e&&t._triggerChange(i.value)})),this},r.showDropdown=function(e){var t=this;return this.dropdown.isActive||requestAnimationFrame((function(){t.dropdown.show(),t.containerOuter.open(t.dropdown.distanceFromTopWindow),!e&&t._canSearch&&t.input.focus(),t.passedElement.triggerEvent(D,{})})),this},r.hideDropdown=function(e){var t=this;return this.dropdown.isActive?(requestAnimationFrame((function(){t.dropdown.hide(),t.containerOuter.close(),!e&&t._canSearch&&(t.input.removeActiveDescendant(),t.input.blur()),t.passedElement.triggerEvent(M,{})})),this):this},r.getValue=function(e){void 0===e&&(e=!1);var t=this._store.activeItems.reduce((function(t,i){var n=e?i.value:i;return t.push(n),t}),[]);return this._isSelectOneElement?t[0]:t},r.setValue=function(e){var t=this;return this.initialised?(e.forEach((function(e){return t._setChoiceOrItem(e)})),this):this},r.setChoiceByValue=function(e){var t=this;return!this.initialised||this._isTextElement||(Array.isArray(e)?e:[e]).forEach((function(e){return t._findAndSelectChoiceByValue(e)})),this},r.setChoices=function(e,t,i,n){var s=this;if(void 0===e&&(e=[]),void 0===t&&(t=\"value\"),void 0===i&&(i=\"label\"),void 0===n&&(n=!1),!this.initialised)throw new ReferenceError(\"setChoices was called on a non-initialized instance of Choices\");if(!this._isSelectElement)throw new TypeError(\"setChoices can't be used with INPUT based Choices\");if(\"string\"!=typeof t||!t)throw new TypeError(\"value parameter must be a name of 'value' field in passed objects\");if(n&&this.clearChoices(),\"function\"==typeof e){var r=e(this);if(\"function\"==typeof Promise&&r instanceof Promise)return new Promise((function(e){return requestAnimationFrame(e)})).then((function(){return s._handleLoadingState(!0)})).then((function(){return r})).then((function(e){return s.setChoices(e,t,i,n)})).catch((function(e){s.config.silent||console.error(e)})).then((function(){return s._handleLoadingState(!1)})).then((function(){return s}));if(!Array.isArray(r))throw new TypeError(\".setChoices first argument function must return either array of choices or Promise, got: \"+typeof r);return this.setChoices(r,t,i,!1)}if(!Array.isArray(e))throw new TypeError(\".setChoices must be called either with array of choices with a function resulting into Promise of array of choices\");return this.containerOuter.removeLoadingState(),this._startLoading(),e.forEach((function(e){e.choices?s._addGroup({id:parseInt(e.id,10)||null,group:e,valueKey:t,labelKey:i}):s._addChoice({value:e[t],label:e[i],isSelected:e.selected,isDisabled:e.disabled,customProperties:e.customProperties,placeholder:e.placeholder})})),this._stopLoading(),this},r.clearChoices=function(){return this._store.dispatch({type:U}),this},r.clearStore=function(){return this._store.dispatch({type:\"CLEAR_ALL\"}),this},r.clearInput=function(){var e=!this._isSelectOneElement;return this.input.clear(e),!this._isTextElement&&this._canSearch&&(this._isSearching=!1,this._store.dispatch(be(!0))),this},r._render=function(){if(!this._store.isLoading()){this._currentState=this._store.state;var e=this._currentState.choices!==this._prevState.choices||this._currentState.groups!==this._prevState.groups||this._currentState.items!==this._prevState.items,t=this._isSelectElement,i=this._currentState.items!==this._prevState.items;e&&(t&&this._renderChoices(),i&&this._renderItems(),this._prevState=this._currentState)}},r._renderChoices=function(){var e=this,t=this._store,i=t.activeGroups,n=t.activeChoices,s=document.createDocumentFragment();if(this.choiceList.clear(),this.config.resetScrollPosition&&requestAnimationFrame((function(){return e.choiceList.scrollToTop()})),i.length>=1&&!this._isSearching){var r=n.filter((function(e){return!0===e.placeholder&&-1===e.groupId}));r.length>=1&&(s=this._createChoicesFragment(r,s)),s=this._createGroupsFragment(i,n,s)}else n.length>=1&&(s=this._createChoicesFragment(n,s));if(s.childNodes&&s.childNodes.length>0){var o=this._store.activeItems,a=this._canAddItem(o,this.input.value);a.response?(this.choiceList.append(s),this._highlightChoice()):this.choiceList.append(this._getTemplate(\"notice\",a.notice))}else{var c,l;this._isSearching?(l=\"function\"==typeof this.config.noResultsText?this.config.noResultsText():this.config.noResultsText,c=this._getTemplate(\"notice\",l,\"no-results\")):(l=\"function\"==typeof this.config.noChoicesText?this.config.noChoicesText():this.config.noChoicesText,c=this._getTemplate(\"notice\",l,\"no-choices\")),this.choiceList.append(c)}},r._renderItems=function(){var e=this._store.activeItems||[];this.itemList.clear();var t=this._createItemsFragment(e);t.childNodes&&this.itemList.append(t)},r._createGroupsFragment=function(e,t,i){var n=this;return void 0===i&&(i=document.createDocumentFragment()),this.config.shouldSort&&e.sort(this.config.sorter),e.forEach((function(e){var s=function(e){return t.filter((function(t){return n._isSelectOneElement?t.groupId===e.id:t.groupId===e.id&&(\"always\"===n.config.renderSelectedChoices||!t.selected)}))}(e);if(s.length>=1){var r=n._getTemplate(\"choiceGroup\",e);i.appendChild(r),n._createChoicesFragment(s,i,!0)}})),i},r._createChoicesFragment=function(e,t,i){var n=this;void 0===t&&(t=document.createDocumentFragment()),void 0===i&&(i=!1);var s=this.config,r=s.renderSelectedChoices,o=s.searchResultLimit,a=s.renderChoiceLimit,c=this._isSearching?w:this.config.sorter,l=function(e){if(\"auto\"!==r||n._isSelectOneElement||!e.selected){var i=n._getTemplate(\"choice\",e,n.config.itemSelectText);t.appendChild(i)}},h=e;\"auto\"!==r||this._isSelectOneElement||(h=e.filter((function(e){return!e.selected})));var u=h.reduce((function(e,t){return t.placeholder?e.placeholderChoices.push(t):e.normalChoices.push(t),e}),{placeholderChoices:[],normalChoices:[]}),d=u.placeholderChoices,p=u.normalChoices;(this.config.shouldSort||this._isSearching)&&p.sort(c);var m=h.length,f=this._isSelectOneElement?[].concat(d,p):p;this._isSearching?m=o:a&&a>0&&!i&&(m=a);for(var v=0;v=n){var o=s?this._searchChoices(e):0;this.passedElement.triggerEvent(j,{value:e,resultCount:o})}else r&&(this._isSearching=!1,this._store.dispatch(be(!0)))}},r._canAddItem=function(e,t){var i=!0,n=\"function\"==typeof this.config.addItemText?this.config.addItemText(t):this.config.addItemText;if(!this._isSelectOneElement){var s=function(e,t,i){return void 0===i&&(i=\"value\"),e.some((function(e){return\"string\"==typeof t?e[i]===t.trim():e[i]===t}))}(e,t);this.config.maxItemCount>0&&this.config.maxItemCount<=e.length&&(i=!1,n=\"function\"==typeof this.config.maxItemText?this.config.maxItemText(this.config.maxItemCount):this.config.maxItemText),!this.config.duplicateItemsAllowed&&s&&i&&(i=!1,n=\"function\"==typeof this.config.uniqueItemText?this.config.uniqueItemText(t):this.config.uniqueItemText),this._isTextElement&&this.config.addItems&&i&&\"function\"==typeof this.config.addItemFilter&&!this.config.addItemFilter(t)&&(i=!1,n=\"function\"==typeof this.config.customAddItemText?this.config.customAddItemText(t):this.config.customAddItemText)}return{response:i,notice:n}},r._searchChoices=function(e){var t=\"string\"==typeof e?e.trim():e,i=\"string\"==typeof this._currentValue?this._currentValue.trim():this._currentValue;if(t.length<1&&t===i+\" \")return 0;var n=this._store.searchableChoices,r=t,o=[].concat(this.config.searchFields),a=Object.assign(this.config.fuseOptions,{keys:o}),c=new s.a(n,a).search(r);return this._currentValue=t,this._highlightPosition=0,this._isSearching=!0,this._store.dispatch(function(e){return{type:G,results:e}}(c)),c.length},r._addEventListeners=function(){var e=document.documentElement;e.addEventListener(\"touchend\",this._onTouchEnd,!0),this.containerOuter.element.addEventListener(\"keydown\",this._onKeyDown,!0),this.containerOuter.element.addEventListener(\"mousedown\",this._onMouseDown,!0),e.addEventListener(\"click\",this._onClick,{passive:!0}),e.addEventListener(\"touchmove\",this._onTouchMove,{passive:!0}),this.dropdown.element.addEventListener(\"mouseover\",this._onMouseOver,{passive:!0}),this._isSelectOneElement&&(this.containerOuter.element.addEventListener(\"focus\",this._onFocus,{passive:!0}),this.containerOuter.element.addEventListener(\"blur\",this._onBlur,{passive:!0})),this.input.element.addEventListener(\"keyup\",this._onKeyUp,{passive:!0}),this.input.element.addEventListener(\"focus\",this._onFocus,{passive:!0}),this.input.element.addEventListener(\"blur\",this._onBlur,{passive:!0}),this.input.element.form&&this.input.element.form.addEventListener(\"reset\",this._onFormReset,{passive:!0}),this.input.addEventListeners()},r._removeEventListeners=function(){var e=document.documentElement;e.removeEventListener(\"touchend\",this._onTouchEnd,!0),this.containerOuter.element.removeEventListener(\"keydown\",this._onKeyDown,!0),this.containerOuter.element.removeEventListener(\"mousedown\",this._onMouseDown,!0),e.removeEventListener(\"click\",this._onClick),e.removeEventListener(\"touchmove\",this._onTouchMove),this.dropdown.element.removeEventListener(\"mouseover\",this._onMouseOver),this._isSelectOneElement&&(this.containerOuter.element.removeEventListener(\"focus\",this._onFocus),this.containerOuter.element.removeEventListener(\"blur\",this._onBlur)),this.input.element.removeEventListener(\"keyup\",this._onKeyUp),this.input.element.removeEventListener(\"focus\",this._onFocus),this.input.element.removeEventListener(\"blur\",this._onBlur),this.input.element.form&&this.input.element.form.removeEventListener(\"reset\",this._onFormReset),this.input.removeEventListeners()},r._onKeyDown=function(e){var t,i=e.target,n=e.keyCode,s=e.ctrlKey,r=e.metaKey,o=this._store.activeItems,a=this.input.isFocussed,c=this.dropdown.isActive,l=this.itemList.hasChildren(),h=String.fromCharCode(n),u=J,d=Y,p=Z,m=Q,f=ee,v=te,g=ie,_=ne,b=se,y=s||r;!this._isTextElement&&/[a-zA-Z0-9-_ ]/.test(h)&&this.showDropdown();var E=((t={})[m]=this._onAKey,t[p]=this._onEnterKey,t[f]=this._onEscapeKey,t[v]=this._onDirectionKey,t[_]=this._onDirectionKey,t[g]=this._onDirectionKey,t[b]=this._onDirectionKey,t[d]=this._onDeleteKey,t[u]=this._onDeleteKey,t);E[n]&&E[n]({event:e,target:i,keyCode:n,metaKey:r,activeItems:o,hasFocusedInput:a,hasActiveDropdown:c,hasItems:l,hasCtrlDownKeyPressed:y})},r._onKeyUp=function(e){var t=e.target,i=e.keyCode,n=this.input.value,s=this._store.activeItems,r=this._canAddItem(s,n),o=J,a=Y;if(this._isTextElement)if(r.notice&&n){var c=this._getTemplate(\"notice\",r.notice);this.dropdown.element.innerHTML=c.outerHTML,this.showDropdown(!0)}else this.hideDropdown(!0);else{var l=(i===o||i===a)&&!t.value,h=!this._isTextElement&&this._isSearching,u=this._canSearch&&r.response;l&&h?(this._isSearching=!1,this._store.dispatch(be(!0))):u&&this._handleSearch(this.input.value)}this._canSearch=this.config.searchEnabled},r._onAKey=function(e){var t=e.hasItems;e.hasCtrlDownKeyPressed&&t&&(this._canSearch=!1,this.config.removeItems&&!this.input.value&&this.input.element===document.activeElement&&this.highlightAll())},r._onEnterKey=function(e){var t=e.event,i=e.target,n=e.activeItems,s=e.hasActiveDropdown,r=Z,o=i.hasAttribute(\"data-button\");if(this._isTextElement&&i.value){var a=this.input.value;this._canAddItem(n,a).response&&(this.hideDropdown(!0),this._addItem({value:a}),this._triggerChange(a),this.clearInput())}if(o&&(this._handleButtonAction(n,i),t.preventDefault()),s){var c=this.dropdown.getChild(\".\"+this.config.classNames.highlightedState);c&&(n[0]&&(n[0].keyCode=r),this._handleChoiceAction(n,c)),t.preventDefault()}else this._isSelectOneElement&&(this.showDropdown(),t.preventDefault())},r._onEscapeKey=function(e){e.hasActiveDropdown&&(this.hideDropdown(!0),this.containerOuter.focus())},r._onDirectionKey=function(e){var t,i,n,s=e.event,r=e.hasActiveDropdown,o=e.keyCode,a=e.metaKey,c=ie,l=ne,h=se;if(r||this._isSelectOneElement){this.showDropdown(),this._canSearch=!1;var u,d=o===c||o===h?1:-1,p=\"[data-choice-selectable]\";if(a||o===h||o===l)u=d>0?this.dropdown.element.querySelector(\"[data-choice-selectable]:last-of-type\"):this.dropdown.element.querySelector(p);else{var m=this.dropdown.element.querySelector(\".\"+this.config.classNames.highlightedState);u=m?function(e,t,i){if(void 0===i&&(i=1),e instanceof Element&&\"string\"==typeof t){for(var n=(i>0?\"next\":\"previous\")+\"ElementSibling\",s=e[n];s;){if(s.matches(t))return s;s=s[n]}return s}}(m,p,d):this.dropdown.element.querySelector(p)}u&&(t=u,i=this.choiceList.element,void 0===(n=d)&&(n=1),t&&(n>0?i.scrollTop+i.offsetHeight>=t.offsetTop+t.offsetHeight:t.offsetTop>=i.scrollTop)||this.choiceList.scrollToChildElement(u,d),this._highlightChoice(u)),s.preventDefault()}},r._onDeleteKey=function(e){var t=e.event,i=e.target,n=e.hasFocusedInput,s=e.activeItems;!n||i.value||this._isSelectOneElement||(this._handleBackspace(s),t.preventDefault())},r._onTouchMove=function(){this._wasTap&&(this._wasTap=!1)},r._onTouchEnd=function(e){var t=(e||e.touches[0]).target;this._wasTap&&this.containerOuter.element.contains(t)&&((t===this.containerOuter.element||t===this.containerInner.element)&&(this._isTextElement?this.input.focus():this._isSelectMultipleElement&&this.showDropdown()),e.stopPropagation()),this._wasTap=!0},r._onMouseDown=function(e){var t=e.target;if(t instanceof HTMLElement){if(we&&this.choiceList.element.contains(t)){var i=this.choiceList.element.firstElementChild,n=\"ltr\"===this._direction?e.offsetX>=i.offsetWidth:e.offsetX0&&this.unhighlightAll(),this.containerOuter.removeFocusState(),this.hideDropdown(!0))},r._onFocus=function(e){var t,i=this,n=e.target;this.containerOuter.element.contains(n)&&((t={}).text=function(){n===i.input.element&&i.containerOuter.addFocusState()},t[\"select-one\"]=function(){i.containerOuter.addFocusState(),n===i.input.element&&i.showDropdown(!0)},t[\"select-multiple\"]=function(){n===i.input.element&&(i.showDropdown(!0),i.containerOuter.addFocusState())},t)[this.passedElement.element.type]()},r._onBlur=function(e){var t=this,i=e.target;if(this.containerOuter.element.contains(i)&&!this._isScrollingOnIe){var n,s=this._store.activeItems.some((function(e){return e.highlighted}));((n={}).text=function(){i===t.input.element&&(t.containerOuter.removeFocusState(),s&&t.unhighlightAll(),t.hideDropdown(!0))},n[\"select-one\"]=function(){t.containerOuter.removeFocusState(),(i===t.input.element||i===t.containerOuter.element&&!t._canSearch)&&t.hideDropdown(!0)},n[\"select-multiple\"]=function(){i===t.input.element&&(t.containerOuter.removeFocusState(),t.hideDropdown(!0),s&&t.unhighlightAll())},n)[this.passedElement.element.type]()}else this._isScrollingOnIe=!1,this.input.element.focus()},r._onFormReset=function(){this._store.dispatch({type:\"RESET_TO\",state:this._initialState})},r._highlightChoice=function(e){var t=this;void 0===e&&(e=null);var i=Array.from(this.dropdown.element.querySelectorAll(\"[data-choice-selectable]\"));if(i.length){var n=e;Array.from(this.dropdown.element.querySelectorAll(\".\"+this.config.classNames.highlightedState)).forEach((function(e){e.classList.remove(t.config.classNames.highlightedState),e.setAttribute(\"aria-selected\",\"false\")})),n?this._highlightPosition=i.indexOf(n):(n=i.length>this._highlightPosition?i[this._highlightPosition]:i[i.length-1])||(n=i[0]),n.classList.add(this.config.classNames.highlightedState),n.setAttribute(\"aria-selected\",\"true\"),this.passedElement.triggerEvent(B,{el:n}),this.dropdown.isActive&&(this.input.setActiveDescendant(n.id),this.containerOuter.setActiveDescendant(n.id))}},r._addItem=function(e){var t=e.value,i=e.label,n=void 0===i?null:i,s=e.choiceId,r=void 0===s?-1:s,o=e.groupId,a=void 0===o?-1:o,c=e.customProperties,l=void 0===c?null:c,h=e.placeholder,u=void 0!==h&&h,d=e.keyCode,p=void 0===d?null:d,m=\"string\"==typeof t?t.trim():t,f=p,v=l,g=this._store.items,_=n||m,b=r||-1,y=a>=0?this._store.getGroupById(a):null,E=g?g.length+1:1;return this.config.prependValue&&(m=this.config.prependValue+m.toString()),this.config.appendValue&&(m+=this.config.appendValue.toString()),this._store.dispatch(function(e){var t=e.value,i=e.label,n=e.id,s=e.choiceId,r=e.groupId,o=e.customProperties,a=e.placeholder,c=e.keyCode;return{type:W,value:t,label:i,id:n,choiceId:s,groupId:r,customProperties:o,placeholder:a,keyCode:c}}({value:m,label:_,id:E,choiceId:b,groupId:a,customProperties:l,placeholder:u,keyCode:f})),this._isSelectOneElement&&this.removeActiveItems(E),this.passedElement.triggerEvent(K,{id:E,value:m,label:_,customProperties:v,groupValue:y&&y.value?y.value:void 0,keyCode:f}),this},r._removeItem=function(e){if(!e||!E(\"Object\",e))return this;var t=e.id,i=e.value,n=e.label,s=e.choiceId,r=e.groupId,o=r>=0?this._store.getGroupById(r):null;return this._store.dispatch(function(e,t){return{type:X,id:e,choiceId:t}}(t,s)),o&&o.value?this.passedElement.triggerEvent(R,{id:t,value:i,label:n,groupValue:o.value}):this.passedElement.triggerEvent(R,{id:t,value:i,label:n}),this},r._addChoice=function(e){var t=e.value,i=e.label,n=void 0===i?null:i,s=e.isSelected,r=void 0!==s&&s,o=e.isDisabled,a=void 0!==o&&o,c=e.groupId,l=void 0===c?-1:c,h=e.customProperties,u=void 0===h?null:h,d=e.placeholder,p=void 0!==d&&d,m=e.keyCode,f=void 0===m?null:m;if(null!=t){var v=this._store.choices,g=n||t,_=v?v.length+1:1,b=this._baseId+\"-\"+this._idNames.itemChoice+\"-\"+_;this._store.dispatch(function(e){var t=e.value,i=e.label,n=e.id,s=e.groupId,r=e.disabled,o=e.elementId,a=e.customProperties,c=e.placeholder,l=e.keyCode;return{type:V,value:t,label:i,id:n,groupId:s,disabled:r,elementId:o,customProperties:a,placeholder:c,keyCode:l}}({id:_,groupId:l,elementId:b,value:t,label:g,disabled:a,customProperties:u,placeholder:p,keyCode:f})),r&&this._addItem({value:t,label:g,choiceId:_,customProperties:u,placeholder:p,keyCode:f})}},r._addGroup=function(e){var t=this,i=e.group,n=e.id,s=e.valueKey,r=void 0===s?\"value\":s,o=e.labelKey,a=void 0===o?\"label\":o,c=E(\"Object\",i)?i.choices:Array.from(i.getElementsByTagName(\"OPTION\")),l=n||Math.floor((new Date).valueOf()*Math.random()),h=!!i.disabled&&i.disabled;c?(this._store.dispatch(Ee({value:i.label,id:l,active:!0,disabled:h})),c.forEach((function(e){var i=e.disabled||e.parentNode&&e.parentNode.disabled;t._addChoice({value:e[r],label:E(\"Object\",e)?e[a]:e.innerHTML,isSelected:e.selected,isDisabled:i,groupId:l,customProperties:e.customProperties,placeholder:e.placeholder})}))):this._store.dispatch(Ee({value:i.label,id:i.id,active:!1,disabled:i.disabled}))},r._getTemplate=function(e){var t;if(!e)return null;for(var i=this.config.classNames,n=arguments.length,s=new Array(n>1?n-1:0),r=1;r{var e;return this.input_el.name=null!==(e=this.model.name)&&void 0!==e?e:\"\"})),this.connect(this.model.properties.value.change,(()=>{this.input_el.value=this.format_value,this.old_value=this.input_el.value})),this.connect(this.model.properties.low.change,(()=>{const{value:e,low:t,high:l}=this.model;null!=t&&null!=l&&(0,p.assert)(t<=l,\"Invalid bounds, low must be inferior to high\"),null!=e&&null!=t&&e{const{value:e,low:t,high:l}=this.model;null!=t&&null!=l&&(0,p.assert)(l>=t,\"Invalid bounds, high must be superior to low\"),null!=e&&null!=l&&e>l&&(this.model.value=l)})),this.connect(this.model.properties.high.change,(()=>this.input_el.placeholder=this.model.placeholder)),this.connect(this.model.properties.disabled.change,(()=>this.input_el.disabled=this.model.disabled)),this.connect(this.model.properties.placeholder.change,(()=>this.input_el.placeholder=this.model.placeholder))}get format_value(){return null!=this.model.value?this.model.pretty(this.model.value):\"\"}_set_input_filter(e){this.input_el.addEventListener(\"input\",(()=>{const{selectionStart:t,selectionEnd:l}=this.input_el;if(e(this.input_el.value))this.old_value=this.input_el.value;else{const e=this.old_value.length-this.input_el.value.length;this.input_el.value=this.old_value,t&&l&&this.input_el.setSelectionRange(t-1,l+e)}}))}render(){super.render(),this.input_el=(0,r.input)({type:\"text\",class:_.input,name:this.model.name,value:this.format_value,disabled:this.model.disabled,placeholder:this.model.placeholder}),this.old_value=this.format_value,this.set_input_filter(),this.input_el.addEventListener(\"change\",(()=>this.change_input())),this.input_el.addEventListener(\"focusout\",(()=>this.input_el.value=this.format_value)),this.group_el.appendChild(this.input_el)}set_input_filter(){\"int\"==this.model.mode?this._set_input_filter((e=>m.test(e))):\"float\"==this.model.mode&&this._set_input_filter((e=>c.test(e)))}bound_value(e){let t=e;const{low:l,high:i}=this.model;return t=null!=l?Math.max(l,t):t,t=null!=i?Math.min(i,t):t,t}get value(){let e=\"\"!=this.input_el.value?Number(this.input_el.value):null;return null!=e&&(e=this.bound_value(e)),e}change_input(){null==this.value?this.model.value=null:Number.isNaN(this.value)||(this.model.value=this.value)}}l.NumericInputView=v,v.__name__=\"NumericInputView\";class g extends o.InputWidget{constructor(e){super(e)}_formatter(e,t){return(0,d.isString)(t)?h.format(e,t):t.doFormat([e],{loc:0})[0]}pretty(e){return null!=this.format?this._formatter(e,this.format):`${e}`}}l.NumericInput=g,u=g,g.__name__=\"NumericInput\",u.prototype.default_view=v,u.define((({Number:e,String:t,Enum:l,Ref:i,Or:n,Nullable:s})=>({value:[s(e),null],placeholder:[t,\"\"],mode:[l(\"int\",\"float\"),\"int\"],format:[s(n(t,i(a.TickFormatter))),null],low:[s(e),null],high:[s(e),null]})))},\n", - " 475: function _(e,t,r,s,n){var a;s();const o=e(464),_=e(43);class p extends o.MarkupView{render(){super.render();const e=(0,_.pre)({style:{overflow:\"auto\"}},this.model.text);this.markup_el.appendChild(e)}}r.PreTextView=p,p.__name__=\"PreTextView\";class u extends o.Markup{constructor(e){super(e)}}r.PreText=u,a=u,u.__name__=\"PreText\",a.prototype.default_view=p},\n", - " 476: function _(t,o,e,a,i){a();const n=t(1);var u;const s=t(449),c=t(43),_=(0,n.__importStar)(t(318));class r extends s.ButtonGroupView{change_active(t){this.model.active!==t&&(this.model.active=t)}_update_active(){const{active:t}=this.model;this._buttons.forEach(((o,e)=>{(0,c.classes)(o).toggle(_.active,t===e)}))}}e.RadioButtonGroupView=r,r.__name__=\"RadioButtonGroupView\";class l extends s.ButtonGroup{constructor(t){super(t)}}e.RadioButtonGroup=l,u=l,l.__name__=\"RadioButtonGroup\",u.prototype.default_view=r,u.define((({Int:t,Nullable:o})=>({active:[o(t),null]})))},\n", - " 477: function _(e,n,i,t,a){t();const s=e(1);var l;const o=e(43),d=e(34),p=e(452),r=(0,s.__importStar)(e(446));class u extends p.InputGroupView{render(){super.render();const e=(0,o.div)({class:[r.input_group,this.model.inline?r.inline:null]});this.el.appendChild(e);const n=(0,d.uniqueId)(),{active:i,labels:t}=this.model;this._inputs=[];for(let a=0;athis.change_active(a))),this._inputs.push(s),this.model.disabled&&(s.disabled=!0),a==i&&(s.checked=!0);const l=(0,o.label)(s,(0,o.span)(t[a]));e.appendChild(l)}}change_active(e){this.model.active=e}}i.RadioGroupView=u,u.__name__=\"RadioGroupView\";class c extends p.InputGroup{constructor(e){super(e)}}i.RadioGroup=c,l=c,c.__name__=\"RadioGroup\",l.prototype.default_view=u,l.define((({Boolean:e,Int:n,String:i,Array:t,Nullable:a})=>({active:[a(n),null],labels:[t(i),[]],inline:[e,!1]})))},\n", - " 478: function _(e,r,t,a,i){a();var n;const o=(0,e(1).__importStar)(e(153)),s=e(458),_=e(8);class d extends s.AbstractRangeSliderView{}t.RangeSliderView=d,d.__name__=\"RangeSliderView\";class c extends s.AbstractSlider{constructor(e){super(e),this.behaviour=\"drag\",this.connected=[!1,!0,!1]}_formatter(e,r){return(0,_.isString)(r)?o.format(e,r):r.compute(e)}}t.RangeSlider=c,n=c,c.__name__=\"RangeSlider\",n.prototype.default_view=d,n.override({format:\"0[.]00\"})},\n", - " 479: function _(e,t,n,s,i){s();const l=e(1);var u;const a=e(43),o=e(8),p=e(13),_=e(445),r=(0,l.__importStar)(e(446));class c extends _.InputWidgetView{constructor(){super(...arguments),this._known_values=new Set}connect_signals(){super.connect_signals();const{value:e,options:t}=this.model.properties;this.on_change(e,(()=>{this._update_value()})),this.on_change(t,(()=>{(0,a.empty)(this.input_el),(0,a.append)(this.input_el,...this.options_el()),this._update_value()}))}options_el(){const{_known_values:e}=this;function t(t){return t.map((t=>{let n,s;return(0,o.isString)(t)?n=s=t:[n,s]=t,e.add(n),(0,a.option)({value:n},s)}))}e.clear();const{options:n}=this.model;return(0,o.isArray)(n)?t(n):(0,p.entries)(n).map((([e,n])=>(0,a.optgroup)({label:e},t(n))))}render(){super.render(),this.input_el=(0,a.select)({class:r.input,name:this.model.name,disabled:this.model.disabled},this.options_el()),this._update_value(),this.input_el.addEventListener(\"change\",(()=>this.change_input())),this.group_el.appendChild(this.input_el)}change_input(){const e=this.input_el.value;this.model.value=e,super.change_input()}_update_value(){const{value:e}=this.model;this._known_values.has(e)?this.input_el.value=e:this.input_el.removeAttribute(\"value\")}}n.SelectView=c,c.__name__=\"SelectView\";class h extends _.InputWidget{constructor(e){super(e)}}n.Select=h,u=h,h.__name__=\"Select\",u.prototype.default_view=c,u.define((({String:e,Array:t,Tuple:n,Dict:s,Or:i})=>{const l=t(i(e,n(e,e)));return{value:[e,\"\"],options:[i(l,s(l)),[]]}}))},\n", - " 480: function _(e,t,r,i,a){i();var o;const s=(0,e(1).__importStar)(e(153)),_=e(458),n=e(8);class c extends _.AbstractSliderView{}r.SliderView=c,c.__name__=\"SliderView\";class d extends _.AbstractSlider{constructor(e){super(e),this.behaviour=\"tap\",this.connected=[!0,!1]}_formatter(e,t){return(0,n.isString)(t)?s.format(e,t):t.compute(e)}}r.Slider=d,o=d,d.__name__=\"Slider\",o.prototype.default_view=c,o.override({format:\"0[.]00\"})},\n", - " 481: function _(e,t,i,n,s){var l;n();const o=e(474),r=e(43),{min:a,max:h,floor:_,abs:u}=Math;function d(e){return _(e)!==e?e.toFixed(16).replace(/0+$/,\"\").split(\".\")[1].length:0}class p extends o.NumericInputView{*buttons(){yield this.btn_up_el,yield this.btn_down_el}initialize(){super.initialize(),this._handles={interval:void 0,timeout:void 0},this._interval=200}connect_signals(){super.connect_signals();const e=this.model.properties;this.on_change(e.disabled,(()=>{for(const e of this.buttons())(0,r.toggle_attribute)(e,\"disabled\",this.model.disabled)}))}render(){super.render(),this.wrapper_el=(0,r.div)({class:\"bk-spin-wrapper\"}),this.group_el.replaceChild(this.wrapper_el,this.input_el),this.btn_up_el=(0,r.button)({class:\"bk-spin-btn bk-spin-btn-up\"}),this.btn_down_el=(0,r.button)({class:\"bk-spin-btn bk-spin-btn-down\"}),this.wrapper_el.appendChild(this.input_el),this.wrapper_el.appendChild(this.btn_up_el),this.wrapper_el.appendChild(this.btn_down_el);for(const e of this.buttons())(0,r.toggle_attribute)(e,\"disabled\",this.model.disabled),e.addEventListener(\"mousedown\",(e=>this._btn_mouse_down(e))),e.addEventListener(\"mouseup\",(()=>this._btn_mouse_up())),e.addEventListener(\"mouseleave\",(()=>this._btn_mouse_leave()));this.input_el.addEventListener(\"keydown\",(e=>this._input_key_down(e))),this.input_el.addEventListener(\"keyup\",(()=>this.model.value_throttled=this.model.value)),this.input_el.addEventListener(\"wheel\",(e=>this._input_mouse_wheel(e))),this.input_el.addEventListener(\"wheel\",function(e,t,i=!1){let n;return function(...s){const l=this,o=i&&void 0===n;void 0!==n&&clearTimeout(n),n=setTimeout((function(){n=void 0,i||e.apply(l,s)}),t),o&&e.apply(l,s)}}((()=>{this.model.value_throttled=this.model.value}),this.model.wheel_wait,!1))}get precision(){const{low:e,high:t,step:i}=this.model,n=d;return h(n(u(null!=e?e:0)),n(u(null!=t?t:0)),n(u(i)))}remove(){this._stop_incrementation(),super.remove()}_start_incrementation(e){clearInterval(this._handles.interval),this._counter=0;const{step:t}=this.model,i=e=>{if(this._counter+=1,this._counter%5==0){const t=Math.floor(this._counter/5);t<10?(clearInterval(this._handles.interval),this._handles.interval=setInterval((()=>i(e)),this._interval/(t+1))):t>=10&&t<=13&&(clearInterval(this._handles.interval),this._handles.interval=setInterval((()=>i(2*e)),this._interval/10))}this.increment(e)};this._handles.interval=setInterval((()=>i(e*t)),this._interval)}_stop_incrementation(){clearTimeout(this._handles.timeout),this._handles.timeout=void 0,clearInterval(this._handles.interval),this._handles.interval=void 0,this.model.value_throttled=this.model.value}_btn_mouse_down(e){e.preventDefault();const t=e.currentTarget===this.btn_up_el?1:-1;this.increment(t*this.model.step),this.input_el.focus(),this._handles.timeout=setTimeout((()=>this._start_incrementation(t)),this._interval)}_btn_mouse_up(){this._stop_incrementation()}_btn_mouse_leave(){this._stop_incrementation()}_input_mouse_wheel(e){if(document.activeElement===this.input_el){e.preventDefault();const t=e.deltaY>0?-1:1;this.increment(t*this.model.step)}}_input_key_down(e){switch(e.keyCode){case r.Keys.Up:return e.preventDefault(),this.increment(this.model.step);case r.Keys.Down:return e.preventDefault(),this.increment(-this.model.step);case r.Keys.PageUp:return e.preventDefault(),this.increment(this.model.page_step_multiplier*this.model.step);case r.Keys.PageDown:return e.preventDefault(),this.increment(-this.model.page_step_multiplier*this.model.step)}}adjust_to_precision(e){return this.bound_value(Number(e.toFixed(this.precision)))}increment(e){const{low:t,high:i}=this.model;null==this.model.value?e>0?this.model.value=null!=t?t:null!=i?a(0,i):0:e<0&&(this.model.value=null!=i?i:null!=t?h(t,0):0):this.model.value=this.adjust_to_precision(this.model.value+e)}change_input(){super.change_input(),this.model.value_throttled=this.model.value}}i.SpinnerView=p,p.__name__=\"SpinnerView\";class m extends o.NumericInput{constructor(e){super(e)}}i.Spinner=m,l=m,m.__name__=\"Spinner\",l.prototype.default_view=p,l.define((({Number:e,Nullable:t})=>({value_throttled:[t(e),null],step:[e,1],page_step_multiplier:[e,10],wheel_wait:[e,100]}))),l.override({mode:\"float\"})},\n", - " 482: function _(e,t,s,n,i){n();const o=e(1);var r;const c=e(444),l=e(43),p=(0,o.__importStar)(e(446));class _ extends c.TextLikeInputView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.rows.change,(()=>this.input_el.rows=this.model.rows)),this.connect(this.model.properties.cols.change,(()=>this.input_el.cols=this.model.cols))}_render_input(){this.input_el=(0,l.textarea)({class:p.input})}render(){super.render(),this.input_el.cols=this.model.cols,this.input_el.rows=this.model.rows}}s.TextAreaInputView=_,_.__name__=\"TextAreaInputView\";class a extends c.TextLikeInput{constructor(e){super(e)}}s.TextAreaInput=a,r=a,a.__name__=\"TextAreaInput\",r.prototype.default_view=_,r.define((({Int:e})=>({cols:[e,20],rows:[e,2]}))),r.override({max_length:500})},\n", - " 483: function _(e,t,s,c,i){c();const o=e(1);var a;const n=e(438),l=e(43),_=(0,o.__importStar)(e(318));class r extends n.AbstractButtonView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,(()=>this._update_active()))}render(){super.render(),this._update_active()}click(){this.model.active=!this.model.active,super.click()}_update_active(){(0,l.classes)(this.button_el).toggle(_.active,this.model.active)}}s.ToggleView=r,r.__name__=\"ToggleView\";class g extends n.AbstractButton{constructor(e){super(e)}}s.Toggle=g,a=g,g.__name__=\"Toggle\",a.prototype.default_view=r,a.define((({Boolean:e})=>({active:[e,!1]}))),a.override({label:\"Toggle\"})},\n", - " }, 436, {\"models/widgets/main\":436,\"models/widgets/index\":437,\"models/widgets/abstract_button\":438,\"models/widgets/control\":439,\"models/widgets/widget\":508,\"models/widgets/abstract_icon\":441,\"models/widgets/autocomplete_input\":442,\"models/widgets/text_input\":443,\"models/widgets/text_like_input\":444,\"models/widgets/input_widget\":445,\"styles/widgets/inputs.css\":446,\"models/widgets/button\":447,\"models/widgets/checkbox_button_group\":448,\"models/widgets/button_group\":449,\"models/widgets/oriented_control\":450,\"models/widgets/checkbox_group\":451,\"models/widgets/input_group\":452,\"models/widgets/color_picker\":453,\"models/widgets/date_picker\":454,\"styles/widgets/flatpickr.css\":456,\"models/widgets/date_range_slider\":457,\"models/widgets/abstract_slider\":458,\"styles/widgets/sliders.css\":460,\"styles/widgets/nouislider.css\":461,\"models/widgets/date_slider\":462,\"models/widgets/div\":463,\"models/widgets/markup\":464,\"styles/clearfix.css\":465,\"models/widgets/dropdown\":466,\"models/widgets/file_input\":467,\"models/widgets/multiselect\":468,\"models/widgets/paragraph\":469,\"models/widgets/password_input\":470,\"models/widgets/multichoice\":471,\"styles/widgets/choices.css\":473,\"models/widgets/numeric_input\":474,\"models/widgets/pretext\":475,\"models/widgets/radio_button_group\":476,\"models/widgets/radio_group\":477,\"models/widgets/range_slider\":478,\"models/widgets/selectbox\":479,\"models/widgets/slider\":480,\"models/widgets/spinner\":481,\"models/widgets/textarea_input\":482,\"models/widgets/toggle\":483}, {});});\n", - "\n", - " /* END bokeh-widgets.min.js */\n", - " },\n", - " \n", - " function(Bokeh) {\n", - " /* BEGIN bokeh-tables.min.js */\n", - " /*!\n", - " * Copyright (c) 2012 - 2021, Anaconda, Inc., and Bokeh Contributors\n", - " * All rights reserved.\n", - " * \n", - " * Redistribution and use in source and binary forms, with or without modification,\n", - " * are permitted provided that the following conditions are met:\n", - " * \n", - " * Redistributions of source code must retain the above copyright notice,\n", - " * this list of conditions and the following disclaimer.\n", - " * \n", - " * Redistributions in binary form must reproduce the above copyright notice,\n", - " * this list of conditions and the following disclaimer in the documentation\n", - " * and/or other materials provided with the distribution.\n", - " * \n", - " * Neither the name of Anaconda nor the names of any contributors\n", - " * may be used to endorse or promote products derived from this software\n", - " * without specific prior written permission.\n", - " * \n", - " * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\n", - " * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n", - " * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE\n", - " * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE\n", - " * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR\n", - " * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF\n", - " * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS\n", - " * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN\n", - " * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)\n", - " * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF\n", - " * THE POSSIBILITY OF SUCH DAMAGE.\n", - " */\n", - " (function(root, factory) {\n", - " factory(root[\"Bokeh\"], \"2.4.2\");\n", - " })(this, function(Bokeh, version) {\n", - " let define;\n", - " return (function(modules, entry, aliases, externals) {\n", - " const bokeh = typeof Bokeh !== \"undefined\" && (version != null ? Bokeh[version] : Bokeh);\n", - " if (bokeh != null) {\n", - " return bokeh.register_plugin(modules, entry, aliases);\n", - " } else {\n", - " throw new Error(\"Cannot find Bokeh \" + version + \". You have to load it prior to loading plugins.\");\n", - " }\n", - " })\n", - " ({\n", - " 484: function _(t,e,o,r,s){r();const _=(0,t(1).__importStar)(t(485));o.Tables=_;(0,t(7).register_models)(_)},\n", - " 485: function _(g,a,r,e,t){e();const o=g(1);(0,o.__exportStar)(g(486),r),(0,o.__exportStar)(g(489),r),t(\"DataTable\",g(492).DataTable),t(\"TableColumn\",g(510).TableColumn),t(\"TableWidget\",g(509).TableWidget);var n=g(512);t(\"AvgAggregator\",n.AvgAggregator),t(\"MinAggregator\",n.MinAggregator),t(\"MaxAggregator\",n.MaxAggregator),t(\"SumAggregator\",n.SumAggregator);var A=g(513);t(\"GroupingInfo\",A.GroupingInfo),t(\"DataCube\",A.DataCube)},\n", - " 486: function _(e,t,i,s,a){s();const r=e(1);var l,n,u,d,o,p,_,c,h;const E=e(43),V=e(226),m=e(53),f=e(487),v=(0,r.__importStar)(e(488));class w extends V.DOMView{constructor(e){const{model:t,parent:i}=e.column;super(Object.assign({model:t,parent:i},e)),this.args=e,this.initialize(),this.render()}get emptyValue(){return null}initialize(){super.initialize(),this.inputEl=this._createInput(),this.defaultValue=null}async lazy_initialize(){throw new Error(\"unsupported\")}css_classes(){return super.css_classes().concat(v.cell_editor)}render(){super.render(),this.args.container.append(this.el),this.el.appendChild(this.inputEl),this.renderEditor(),this.disableNavigation()}renderEditor(){}disableNavigation(){this.inputEl.addEventListener(\"keydown\",(e=>{switch(e.keyCode){case E.Keys.Left:case E.Keys.Right:case E.Keys.Up:case E.Keys.Down:case E.Keys.PageUp:case E.Keys.PageDown:e.stopImmediatePropagation()}}))}destroy(){this.remove()}focus(){this.inputEl.focus()}show(){}hide(){}position(){}getValue(){return this.inputEl.value}setValue(e){this.inputEl.value=e}serializeValue(){return this.getValue()}isValueChanged(){return!(\"\"==this.getValue()&&null==this.defaultValue)&&this.getValue()!==this.defaultValue}applyValue(e,t){const i=this.args.grid.getData(),s=i.index.indexOf(e[f.DTINDEX_NAME]);i.setField(s,this.args.column.field,t)}loadValue(e){const t=e[this.args.column.field];this.defaultValue=null!=t?t:this.emptyValue,this.setValue(this.defaultValue)}validateValue(e){if(this.args.column.validator){const t=this.args.column.validator(e);if(!t.valid)return t}return{valid:!0,msg:null}}validate(){return this.validateValue(this.getValue())}}i.CellEditorView=w,w.__name__=\"CellEditorView\";class g extends m.Model{}i.CellEditor=g,g.__name__=\"CellEditor\";class x extends w{get emptyValue(){return\"\"}_createInput(){return(0,E.input)({type:\"text\"})}renderEditor(){this.inputEl.focus(),this.inputEl.select()}loadValue(e){super.loadValue(e),this.inputEl.defaultValue=this.defaultValue,this.inputEl.select()}}i.StringEditorView=x,x.__name__=\"StringEditorView\";class y extends g{}i.StringEditor=y,l=y,y.__name__=\"StringEditor\",l.prototype.default_view=x,l.define((({String:e,Array:t})=>({completions:[t(e),[]]})));class I extends w{_createInput(){return(0,E.textarea)()}renderEditor(){this.inputEl.focus(),this.inputEl.select()}}i.TextEditorView=I,I.__name__=\"TextEditorView\";class b extends g{}i.TextEditor=b,n=b,b.__name__=\"TextEditor\",n.prototype.default_view=I;class N extends w{_createInput(){return(0,E.select)()}renderEditor(){for(const e of this.model.options)this.inputEl.appendChild((0,E.option)({value:e},e));this.focus()}}i.SelectEditorView=N,N.__name__=\"SelectEditorView\";class C extends g{}i.SelectEditor=C,u=C,C.__name__=\"SelectEditor\",u.prototype.default_view=N,u.define((({String:e,Array:t})=>({options:[t(e),[]]})));class D extends w{_createInput(){return(0,E.input)({type:\"text\"})}}i.PercentEditorView=D,D.__name__=\"PercentEditorView\";class S extends g{}i.PercentEditor=S,d=S,S.__name__=\"PercentEditor\",d.prototype.default_view=D;class k extends w{_createInput(){return(0,E.input)({type:\"checkbox\"})}renderEditor(){this.focus()}loadValue(e){this.defaultValue=!!e[this.args.column.field],this.inputEl.checked=this.defaultValue}serializeValue(){return this.inputEl.checked}}i.CheckboxEditorView=k,k.__name__=\"CheckboxEditorView\";class z extends g{}i.CheckboxEditor=z,o=z,z.__name__=\"CheckboxEditor\",o.prototype.default_view=k;class P extends w{_createInput(){return(0,E.input)({type:\"text\"})}renderEditor(){this.inputEl.focus(),this.inputEl.select()}remove(){super.remove()}serializeValue(){var e;return null!==(e=parseInt(this.getValue(),10))&&void 0!==e?e:0}loadValue(e){super.loadValue(e),this.inputEl.defaultValue=this.defaultValue,this.inputEl.select()}validateValue(e){return isNaN(e)?{valid:!1,msg:\"Please enter a valid integer\"}:super.validateValue(e)}}i.IntEditorView=P,P.__name__=\"IntEditorView\";class T extends g{}i.IntEditor=T,p=T,T.__name__=\"IntEditor\",p.prototype.default_view=P,p.define((({Int:e})=>({step:[e,1]})));class K extends w{_createInput(){return(0,E.input)({type:\"text\"})}renderEditor(){this.inputEl.focus(),this.inputEl.select()}remove(){super.remove()}serializeValue(){var e;return null!==(e=parseFloat(this.getValue()))&&void 0!==e?e:0}loadValue(e){super.loadValue(e),this.inputEl.defaultValue=this.defaultValue,this.inputEl.select()}validateValue(e){return isNaN(e)?{valid:!1,msg:\"Please enter a valid number\"}:super.validateValue(e)}}i.NumberEditorView=K,K.__name__=\"NumberEditorView\";class A extends g{}i.NumberEditor=A,_=A,A.__name__=\"NumberEditor\",_.prototype.default_view=K,_.define((({Number:e})=>({step:[e,.01]})));class M extends w{_createInput(){return(0,E.input)({type:\"text\"})}}i.TimeEditorView=M,M.__name__=\"TimeEditorView\";class O extends g{}i.TimeEditor=O,c=O,O.__name__=\"TimeEditor\",c.prototype.default_view=M;class F extends w{_createInput(){return(0,E.input)({type:\"text\"})}get emptyValue(){return new Date}renderEditor(){this.inputEl.focus(),this.inputEl.select()}destroy(){super.destroy()}show(){super.show()}hide(){super.hide()}position(){return super.position()}getValue(){}setValue(e){}}i.DateEditorView=F,F.__name__=\"DateEditorView\";class L extends g{}i.DateEditor=L,h=L,L.__name__=\"DateEditor\",h.prototype.default_view=F},\n", - " 487: function _(_,n,i,t,d){t(),i.DTINDEX_NAME=\"__bkdt_internal_index__\"},\n", - " 488: function _(e,l,o,t,r){t(),o.root=\"bk-root\",o.data_table=\"bk-data-table\",o.cell_special_defaults=\"bk-cell-special-defaults\",o.cell_select=\"bk-cell-select\",o.cell_index=\"bk-cell-index\",o.header_index=\"bk-header-index\",o.cell_editor=\"bk-cell-editor\",o.cell_editor_completion=\"bk-cell-editor-completion\",o.default='.bk-root .bk-data-table{box-sizing:content-box;font-size:11px;}.bk-root .bk-data-table input[type=\"checkbox\"]{margin-left:4px;margin-right:4px;}.bk-root .bk-cell-special-defaults{border-right-color:silver;border-right-style:solid;background:#f5f5f5;}.bk-root .bk-cell-select{border-right-color:silver;border-right-style:solid;background:#f5f5f5;}.bk-root .slick-cell.bk-cell-index{border-right-color:silver;border-right-style:solid;background:#f5f5f5;text-align:right;background:#f0f0f0;color:#909090;}.bk-root .bk-header-index .slick-column-name{float:right;}.bk-root .slick-row.selected .bk-cell-index{background-color:transparent;}.bk-root .slick-row.odd{background:#f0f0f0;}.bk-root .slick-cell{padding-left:4px;padding-right:4px;border-right-color:transparent;border:0.25px solid transparent;}.bk-root .slick-cell .bk{line-height:inherit;}.bk-root .slick-cell.active{border-style:dashed;}.bk-root .slick-cell.selected{background-color:#F0F8FF;}.bk-root .slick-cell.editable{padding-left:0;padding-right:0;}.bk-root .bk-cell-editor{display:contents;}.bk-root .bk-cell-editor input,.bk-root .bk-cell-editor select{width:100%;height:100%;border:0;margin:0;padding:0;outline:0;background:transparent;vertical-align:baseline;}.bk-root .bk-cell-editor input{padding-left:4px;padding-right:4px;}.bk-root .bk-cell-editor-completion{font-size:11px;}'},\n", - " 489: function _(t,e,r,n,a){n();const o=t(1);var l,s,i,c,u,m;const _=(0,o.__importDefault)(t(151)),d=(0,o.__importStar)(t(153)),f=t(490),g=t(43),h=t(20),F=t(8),p=t(34),b=t(22),S=t(53);class x extends S.Model{constructor(t){super(t)}doFormat(t,e,r,n,a){return null==r?\"\":`${r}`.replace(/&/g,\"&\").replace(//g,\">\")}}r.CellFormatter=x,x.__name__=\"CellFormatter\";class M extends x{constructor(t){super(t)}doFormat(t,e,r,n,a){const{font_style:o,text_align:l,text_color:s}=this,i=(0,g.div)(null==r?\"\":`${r}`);switch(o){case\"bold\":i.style.fontWeight=\"bold\";break;case\"italic\":i.style.fontStyle=\"italic\"}return 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w.globalEval(e),e}}}),w.ajaxPrefilter(\"script\",(function(e){void 0===e.cache&&(e.cache=!1),e.crossDomain&&(e.type=\"GET\")})),w.ajaxTransport(\"script\",(function(e){var t,n;if(e.crossDomain||e.scriptAttrs)return{send:function(r,i){t=w(\"" + ] + }, + "metadata": { + "application/vnd.holoviews_exec.v0+json": { + "id": "5d341d63-083a-419a-a084-d2f096d315e1" + } + }, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ] }, "metadata": {}, "output_type": "display_data" @@ -1953,20 +703,20 @@ { "data": { "application/javascript": [ - "\n", "(function(root) {\n", " function now() {\n", " return new Date();\n", " }\n", "\n", - " var force = true;\n", + " const force = false;\n", + " const version = '3.8.2'.replace('rc', '-rc.').replace('.dev', '-dev.');\n", + " const reloading = true;\n", + " const Bokeh = root.Bokeh;\n", + " const BK_RE = /^https:\\/\\/cdn\\.bokeh\\.org\\/bokeh\\/(release|dev)\\/bokeh-/;\n", + " const PN_RE = /^https:\\/\\/cdn\\.holoviz\\.org\\/panel\\/[^/]+\\/dist\\/panel/i;\n", "\n", - " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", - " root._bokeh_onload_callbacks = [];\n", - " root._bokeh_is_loading = undefined;\n", - " }\n", - "\n", - " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", + " // Set a timeout for this load but only if we are not already initializing\n", + " if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n", " root._bokeh_timeout = Date.now() + 5000;\n", " root._bokeh_failed_load = false;\n", " }\n", @@ -1978,26 +728,28 @@ " callback();\n", " });\n", " } finally {\n", - " delete root._bokeh_onload_callbacks\n", + " delete root._bokeh_onload_callbacks;\n", " }\n", " console.debug(\"Bokeh: all callbacks have finished\");\n", " }\n", "\n", - " function load_libs(css_urls, js_urls, js_modules, callback) {\n", + " function load_libs(css_urls, js_urls, js_modules, js_exports, Bokeh, callback) {\n", " if (css_urls == null) css_urls = [];\n", " if (js_urls == null) js_urls = [];\n", " if (js_modules == null) js_modules = [];\n", + " if (js_exports == null) js_exports = {};\n", "\n", " root._bokeh_onload_callbacks.push(callback);\n", + "\n", " if (root._bokeh_is_loading > 0) {\n", + " // Don't load bokeh if it is still initializing\n", " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", " return null;\n", - " }\n", - " if (js_urls.length === 0 && js_modules.length === 0) {\n", + " } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n", + " // There is nothing to load\n", " run_callbacks();\n", " return null;\n", " }\n", - " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", "\n", " function on_load() {\n", " root._bokeh_is_loading--;\n", @@ -2006,13 +758,36 @@ " run_callbacks()\n", " }\n", " }\n", + " window._bokeh_on_load = on_load\n", "\n", - " function on_error() {\n", - " console.error(\"failed to load \" + url);\n", + " function on_error(e) {\n", + " const src_el = e.srcElement\n", + " console.error(\"failed to load \" + (src_el.href || src_el.src));\n", " }\n", "\n", - " for (var i = 0; i < css_urls.length; i++) {\n", - " var url = css_urls[i];\n", + " const skip = [];\n", + " if (window.requirejs) {\n", + " window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n", + " root._bokeh_is_loading = css_urls.length + 0;\n", + " } else {\n", + " root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n", + " }\n", + "\n", + " const existing_stylesheets = []\n", + " const links = document.getElementsByTagName('link')\n", + " for (let i = 0; i < links.length; i++) {\n", + " const link = links[i]\n", + " if (link.href != null) {\n", + " existing_stylesheets.push(link.href)\n", + " }\n", + " }\n", + " for (let i = 0; i < css_urls.length; i++) {\n", + " const url = css_urls[i];\n", + " const escaped = encodeURI(url)\n", + " if (existing_stylesheets.indexOf(escaped) !== -1) {\n", + " on_load()\n", + " continue;\n", + " }\n", " const element = document.createElement(\"link\");\n", " element.onload = on_load;\n", " element.onerror = on_error;\n", @@ -2021,25 +796,27 @@ " element.href = url;\n", " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", " document.body.appendChild(element);\n", + " } var existing_scripts = []\n", + " const scripts = document.getElementsByTagName('script')\n", + " for (let i = 0; i < scripts.length; i++) {\n", + " var script = scripts[i]\n", + " if (script.src != null) {\n", + " existing_scripts.push(script.src)\n", + " }\n", " }\n", - "\n", - " var skip = [];\n", - " if (window.requirejs) {\n", - " window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n", - " \n", - " root._bokeh_is_loading = css_urls.length + 0;\n", - " } else {\n", - " root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length;\n", - " }\n", - " for (var i = 0; i < js_urls.length; i++) {\n", - " var url = js_urls[i];\n", - " if (skip.indexOf(url) >= 0) {\n", - "\tif (!window.requirejs) {\n", - "\t on_load();\n", - "\t}\n", - "\tcontinue;\n", + " for (let i = 0; i < js_urls.length; i++) {\n", + " const url = js_urls[i];\n", + " const escaped = encodeURI(url)\n", + " const shouldSkip = skip.includes(escaped) || existing_scripts.includes(escaped)\n", + " const isBokehOrPanel = BK_RE.test(escaped) || PN_RE.test(escaped)\n", + " const missingOrBroken = Bokeh == null || Bokeh.Panel == null || (Bokeh.version != version && !Bokeh.versions?.has(version)) || Bokeh.versions?.get(version)?.Panel == null;\n", + " if (shouldSkip && !(isBokehOrPanel && missingOrBroken)) {\n", + " if (!window.requirejs) {\n", + " on_load();\n", + " }\n", + " continue;\n", " }\n", - " var element = document.createElement('script');\n", + " const element = document.createElement('script');\n", " element.onload = on_load;\n", " element.onerror = on_error;\n", " element.async = false;\n", @@ -2047,13 +824,14 @@ " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", " document.head.appendChild(element);\n", " }\n", - " for (var i = 0; i < js_modules.length; i++) {\n", - " var url = js_modules[i];\n", - " if (skip.indexOf(url) >= 0) {\n", - "\tif (!window.requirejs) {\n", - "\t on_load();\n", - "\t}\n", - "\tcontinue;\n", + " for (let i = 0; i < js_modules.length; i++) {\n", + " const url = js_modules[i];\n", + " const escaped = encodeURI(url)\n", + " if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n", + " if (!window.requirejs) {\n", + " on_load();\n", + " }\n", + " continue;\n", " }\n", " var element = document.createElement('script');\n", " element.onload = on_load;\n", @@ -2064,6 +842,27 @@ " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", " document.head.appendChild(element);\n", " }\n", + " for (const name in js_exports) {\n", + " const url = js_exports[name];\n", + " const escaped = encodeURI(url)\n", + " if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n", + " if (!window.requirejs) {\n", + " on_load();\n", + " }\n", + " continue;\n", + " }\n", + " var element = document.createElement('script');\n", + " element.onerror = on_error;\n", + " element.async = false;\n", + " element.type = \"module\";\n", + " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", + " element.textContent = `\n", + " import ${name} from \"${url}\"\n", + " window.${name} = ${name}\n", + " window._bokeh_on_load()\n", + " `\n", + " document.head.appendChild(element);\n", + " }\n", " if (!js_urls.length && !js_modules.length) {\n", " on_load()\n", " }\n", @@ -2075,1525 +874,88 @@ " document.body.appendChild(element);\n", " }\n", "\n", - " var js_urls = [];\n", - " var js_modules = [];\n", - " var css_urls = [];\n", - " var inline_js = [\n", - " function(Bokeh) {\n", - " inject_raw_css(\".bk.alert {\\n padding: 0.75rem 1.25rem;\\n border: 1px solid transparent;\\n border-radius: 0.25rem;\\n /* Don't set margin because that will not render correctly! */\\n /* margin-bottom: 1rem; */\\n margin-top: 15px;\\n margin-bottom: 15px;\\n}\\n.bk.alert a {\\n color: rgb(11, 46, 19); /* #002752; */\\n font-weight: 700;\\n text-decoration: rgb(11, 46, 19);\\n text-decoration-color: rgb(11, 46, 19);\\n text-decoration-line: none;\\n text-decoration-style: solid;\\n text-decoration-thickness: auto;\\n }\\n.bk.alert a:hover {\\n color: rgb(11, 46, 19);\\n font-weight: 700;\\n text-decoration: underline;\\n}\\n\\n.bk.alert-primary {\\n color: #004085;\\n background-color: #cce5ff;\\n border-color: #b8daff;\\n}\\n.bk.alert-primary hr {\\n border-top-color: #9fcdff;\\n}\\n\\n.bk.alert-secondary {\\n color: #383d41;\\n background-color: #e2e3e5;\\n border-color: #d6d8db;\\n }\\n.bk.alert-secondary hr {\\n border-top-color: #c8cbcf;\\n}\\n\\n.bk.alert-success {\\n color: #155724;\\n background-color: #d4edda;\\n border-color: #c3e6cb;\\n }\\n\\n.bk.alert-success hr {\\n border-top-color: #b1dfbb;\\n}\\n\\n.bk.alert-info {\\n color: #0c5460;\\n background-color: #d1ecf1;\\n border-color: #bee5eb;\\n }\\n.bk.alert-info hr {\\n border-top-color: #abdde5;\\n}\\n\\n.bk.alert-warning {\\n color: #856404;\\n background-color: #fff3cd;\\n border-color: #ffeeba;\\n }\\n\\n.bk.alert-warning hr {\\n border-top-color: #ffe8a1;\\n}\\n\\n.bk.alert-danger {\\n color: #721c24;\\n background-color: #f8d7da;\\n border-color: #f5c6cb;\\n}\\n.bk.alert-danger hr {\\n border-top-color: #f1b0b7;\\n}\\n\\n.bk.alert-light {\\n color: #818182;\\n background-color: #fefefe;\\n border-color: #fdfdfe;\\n }\\n.bk.alert-light hr {\\n border-top-color: #ececf6;\\n}\\n\\n.bk.alert-dark {\\n color: #1b1e21;\\n background-color: #d6d8d9;\\n border-color: #c6c8ca;\\n }\\n.bk.alert-dark hr {\\n border-top-color: #b9bbbe;\\n}\\n\\n\\n/* adjf\\u00e6l */\\n\\n.bk.alert-primary a {\\n color: #002752;\\n}\\n\\n.bk.alert-secondary a {\\n color: #202326;\\n}\\n\\n\\n.bk.alert-success a {\\n color: #0b2e13;\\n}\\n\\n\\n.bk.alert-info a {\\n color: #062c33;\\n}\\n\\n\\n.bk.alert-warning a {\\n color: #533f03;\\n}\\n\\n\\n.bk.alert-danger a {\\n color: #491217;\\n}\\n\\n.bk.alert-light a {\\n color: #686868;\\n}\\n\\n.bk.alert-dark a {\\n color: #040505;\\n}\");\n", - " },\n", - " function(Bokeh) {\n", - " inject_raw_css(\".bk.card {\\n border: 1px solid rgba(0,0,0,.125);\\n border-radius: 0.25rem;\\n}\\n.bk.accordion {\\n border: 1px solid rgba(0,0,0,.125);\\n}\\n.bk.card-header {\\n align-items: center;\\n background-color: rgba(0, 0, 0, 0.03);\\n border-radius: 0.25rem;\\n display: inline-flex;\\n justify-content: start;\\n width: 100%;\\n}\\n.bk.accordion-header {\\n align-items: center;\\n background-color: rgba(0, 0, 0, 0.03);\\n border-radius: 0;\\n display: flex;\\n justify-content: start;\\n width: 100%;\\n}\\n.bk.card-button {\\n background-color: transparent;\\n margin-left: 0.5em;\\n}\\n.bk.card-header-row {\\n position: relative !important;\\n}\\n.bk.card-title {\\n align-items: center;\\n font-size: 1.4em;\\n font-weight: bold;\\n overflow-wrap: break-word;\\n}\\n.bk.card-header-row > .bk {\\n overflow-wrap: break-word;\\n text-align: center;\\n}\\n\");\n", - " },\n", - " function(Bokeh) {\n", - " inject_raw_css(\".bk.panel-widget-box {\\n min-height: 20px;\\n background-color: #f5f5f5;\\n border: 1px solid #e3e3e3;\\n border-radius: 4px;\\n -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.05);\\n box-shadow: inset 0 1px 1px rgba(0,0,0,.05);\\n overflow-x: hidden;\\n overflow-y: hidden;\\n}\\n\\n.scrollable {\\n overflow: scroll;\\n}\\n\\nprogress {\\n appearance: none;\\n -moz-appearance: none;\\n -webkit-appearance: none;\\n border: none;\\n height: 20px;\\n background-color: whiteSmoke;\\n border-radius: 3px;\\n box-shadow: 0 2px 3px rgba(0,0,0,.5) inset;\\n color: royalblue;\\n position: relative;\\n margin: 0 0 1.5em;\\n}\\n\\nprogress[value]::-webkit-progress-bar {\\n background-color: whiteSmoke;\\n border-radius: 3px;\\n box-shadow: 0 2px 3px rgba(0,0,0,.5) inset;\\n}\\n\\nprogress[value]::-webkit-progress-value {\\n position: relative;\\n background-size: 35px 20px, 100% 100%, 100% 100%;\\n border-radius:3px;\\n}\\n\\nprogress.active:not([value])::before {\\n background-position: 10%;\\n animation-name: stripes;\\n animation-duration: 3s;\\n animation-timing-function: linear;\\n animation-iteration-count: infinite;\\n}\\n\\nprogress[value]::-moz-progress-bar {\\n background-size: 35px 20px, 100% 100%, 100% 100%;\\n border-radius:3px;\\n}\\n\\nprogress:not([value])::-moz-progress-bar {\\n border-radius:3px;\\n background: linear-gradient(-45deg, transparent 33%, rgba(0, 0, 0, 0.2) 33%, rgba(0, 0, 0, 0.2) 66%, transparent 66%) left/2.5em 1.5em;\\n}\\n\\nprogress.active:not([value])::-moz-progress-bar {\\n background-position: 10%;\\n animation-name: stripes;\\n animation-duration: 3s;\\n animation-timing-function: linear;\\n animation-iteration-count: infinite;\\n}\\n\\nprogress.active:not([value])::-webkit-progress-bar {\\n background-position: 10%;\\n animation-name: stripes;\\n animation-duration: 3s;\\n animation-timing-function: linear;\\n animation-iteration-count: infinite;\\n}\\n\\nprogress.primary[value]::-webkit-progress-value { background-color: #007bff; }\\nprogress.primary:not([value])::before { background-color: #007bff; }\\nprogress.primary:not([value])::-webkit-progress-bar { background-color: #007bff; }\\nprogress.primary::-moz-progress-bar { background-color: #007bff; }\\n\\nprogress.secondary[value]::-webkit-progress-value { background-color: #6c757d; }\\nprogress.secondary:not([value])::before { background-color: #6c757d; }\\nprogress.secondary:not([value])::-webkit-progress-bar { background-color: #6c757d; }\\nprogress.secondary::-moz-progress-bar { background-color: #6c757d; }\\n\\nprogress.success[value]::-webkit-progress-value { background-color: #28a745; }\\nprogress.success:not([value])::before { background-color: #28a745; }\\nprogress.success:not([value])::-webkit-progress-bar { background-color: #28a745; }\\nprogress.success::-moz-progress-bar { background-color: #28a745; }\\n\\nprogress.danger[value]::-webkit-progress-value { background-color: #dc3545; }\\nprogress.danger:not([value])::before { background-color: #dc3545; }\\nprogress.danger:not([value])::-webkit-progress-bar { background-color: #dc3545; }\\nprogress.danger::-moz-progress-bar { background-color: #dc3545; }\\n\\nprogress.warning[value]::-webkit-progress-value { background-color: #ffc107; }\\nprogress.warning:not([value])::before { background-color: #ffc107; }\\nprogress.warning:not([value])::-webkit-progress-bar { background-color: #ffc107; }\\nprogress.warning::-moz-progress-bar { background-color: #ffc107; }\\n\\nprogress.info[value]::-webkit-progress-value { background-color: #17a2b8; }\\nprogress.info:not([value])::before { background-color: #17a2b8; }\\nprogress.info:not([value])::-webkit-progress-bar { background-color: #17a2b8; }\\nprogress.info::-moz-progress-bar { background-color: #17a2b8; }\\n\\nprogress.light[value]::-webkit-progress-value { background-color: #f8f9fa; }\\nprogress.light:not([value])::before { background-color: #f8f9fa; }\\nprogress.light:not([value])::-webkit-progress-bar { background-color: #f8f9fa; }\\nprogress.light::-moz-progress-bar { background-color: #f8f9fa; }\\n\\nprogress.dark[value]::-webkit-progress-value { background-color: #343a40; }\\nprogress.dark:not([value])::-webkit-progress-bar { background-color: #343a40; }\\nprogress.dark:not([value])::before { background-color: #343a40; }\\nprogress.dark::-moz-progress-bar { background-color: #343a40; }\\n\\nprogress:not([value])::-webkit-progress-bar {\\n border-radius: 3px;\\n background: linear-gradient(-45deg, transparent 33%, rgba(0, 0, 0, 0.2) 33%, rgba(0, 0, 0, 0.2) 66%, transparent 66%) left/2.5em 1.5em;\\n}\\nprogress:not([value])::before {\\n content:\\\" \\\";\\n position:absolute;\\n height: 20px;\\n top:0;\\n left:0;\\n right:0;\\n bottom:0;\\n border-radius: 3px;\\n background: linear-gradient(-45deg, transparent 33%, rgba(0, 0, 0, 0.2) 33%, rgba(0, 0, 0, 0.2) 66%, transparent 66%) left/2.5em 1.5em;\\n}\\n\\n@keyframes stripes {\\n from {background-position: 0%}\\n to {background-position: 100%}\\n}\\n\\n.bk-root .bk.loader {\\n overflow: hidden;\\n}\\n\\n.bk.loader::after {\\n content: \\\"\\\";\\n border-radius: 50%;\\n -webkit-mask-image: radial-gradient(transparent 50%, rgba(0, 0, 0, 1) 54%);\\n width: 100%;\\n height: 100%;\\n left: 0;\\n top: 0;\\n position: absolute;\\n}\\n\\n.bk-root .bk.loader.dark::after {\\n background: #0f0f0f;\\n}\\n\\n.bk-root .bk.loader.light::after {\\n background: #f0f0f0;\\n}\\n\\n.bk-root .bk.loader.spin::after {\\n animation: spin 2s linear infinite;\\n}\\n\\n.bk-root div.bk.loader.spin.primary-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #007bff 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.secondary-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #6c757d 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.success-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #28a745 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.danger-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #dc3545 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.warning-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #ffc107 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.info-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #17a2b8 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.light-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #f8f9fa 50%);\\n}\\n\\n.bk-root div.bk.loader.dark-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #343a40 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.primary-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #007bff 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.secondary-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #6c757d 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.success-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #28a745 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.danger-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #dc3545 50%)\\n}\\n\\n.bk-root div.bk.loader.spin.warning-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #ffc107 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.info-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #17a2b8 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.light-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #f8f9fa 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.dark-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #343a40 50%);\\n}\\n\\n/* Safari */\\n@-webkit-keyframes spin {\\n 0% { -webkit-transform: rotate(0deg); }\\n 100% { -webkit-transform: rotate(360deg); }\\n}\\n\\n@keyframes spin {\\n 0% { transform: rotate(0deg); }\\n 100% { transform: rotate(360deg); }\\n}\\n\\n.dot div {\\n height: 100%;\\n width: 100%;\\n border: 1px solid #000 !important;\\n background-color: #fff;\\n border-radius: 50%;\\n display: inline-block;\\n}\\n\\n.dot-filled div {\\n height: 100%;\\n width: 100%;\\n border: 1px solid #000 !important;\\n border-radius: 50%;\\n display: inline-block;\\n}\\n\\n.dot-filled.primary div {\\n background-color: #007bff;\\n}\\n\\n.dot-filled.secondary div {\\n background-color: #6c757d;\\n}\\n\\n.dot-filled.success div {\\n background-color: #28a745;\\n}\\n\\n.dot-filled.danger div {\\n background-color: #dc3545;\\n}\\n\\n.dot-filled.warning div {\\n background-color: #ffc107;\\n}\\n\\n.dot-filled.info div {\\n background-color: #17a2b8;\\n}\\n\\n.dot-filled.dark div {\\n background-color: #343a40;\\n}\\n\\n.dot-filled.light div {\\n background-color: #f8f9fa;\\n}\\n\\n/* Slider editor */\\n.slider-edit .bk-input-group .bk-input {\\n border: 0;\\n border-radius: 0;\\n min-height: 0;\\n padding-left: 0;\\n padding-right: 0;\\n font-weight: bold;\\n}\\n\\n.slider-edit .bk-input-group .bk-spin-wrapper {\\n display: contents;\\n}\\n\\n.slider-edit .bk-input-group .bk-spin-wrapper .bk.bk-spin-btn-up {\\n top: -6px;\\n}\\n\\n.slider-edit .bk-input-group .bk-spin-wrapper .bk.bk-spin-btn-down {\\n bottom: 3px;\\n}\\n\\n/* JSON Pane */\\n.bk-root .json-formatter-row .json-formatter-string, .bk-root .json-formatter-row .json-formatter-stringifiable {\\n white-space: pre-wrap;\\n}\\n\");\n", - " },\n", - " function(Bokeh) {\n", - " inject_raw_css(\".codehilite .hll { background-color: #ffffcc }\\n.codehilite { background: #f8f8f8; }\\n.codehilite .c { color: #408080; font-style: italic } /* Comment */\\n.codehilite .err { border: 1px solid #FF0000 } /* Error */\\n.codehilite .k { color: #008000; font-weight: bold } /* Keyword */\\n.codehilite .o { color: #666666 } /* Operator */\\n.codehilite .ch { color: #408080; font-style: italic } /* Comment.Hashbang */\\n.codehilite .cm { color: #408080; font-style: italic } /* Comment.Multiline */\\n.codehilite .cp { color: #BC7A00 } /* Comment.Preproc */\\n.codehilite .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */\\n.codehilite .c1 { color: #408080; font-style: italic } /* Comment.Single */\\n.codehilite .cs { color: #408080; font-style: italic } /* Comment.Special */\\n.codehilite .gd { color: #A00000 } /* Generic.Deleted */\\n.codehilite .ge { font-style: italic } /* Generic.Emph */\\n.codehilite .gr { color: #FF0000 } /* Generic.Error */\\n.codehilite .gh { color: #000080; font-weight: bold } /* Generic.Heading */\\n.codehilite .gi { color: #00A000 } /* Generic.Inserted */\\n.codehilite .go { color: #888888 } /* Generic.Output */\\n.codehilite .gp { color: #000080; font-weight: bold } /* Generic.Prompt */\\n.codehilite .gs { font-weight: bold } /* Generic.Strong */\\n.codehilite .gu { color: #800080; font-weight: bold } /* Generic.Subheading */\\n.codehilite .gt { color: #0044DD } /* Generic.Traceback */\\n.codehilite .kc { color: #008000; font-weight: bold } /* Keyword.Constant */\\n.codehilite .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */\\n.codehilite .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */\\n.codehilite .kp { color: #008000 } /* Keyword.Pseudo */\\n.codehilite .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */\\n.codehilite .kt { color: #B00040 } /* Keyword.Type */\\n.codehilite .m { color: #666666 } /* Literal.Number */\\n.codehilite .s { color: #BA2121 } /* Literal.String */\\n.codehilite .na { color: #7D9029 } /* Name.Attribute */\\n.codehilite .nb { color: #008000 } /* Name.Builtin */\\n.codehilite .nc { color: #0000FF; font-weight: bold } /* Name.Class */\\n.codehilite .no { color: #880000 } /* Name.Constant */\\n.codehilite .nd { color: #AA22FF } /* Name.Decorator */\\n.codehilite .ni { color: #999999; font-weight: bold } /* Name.Entity */\\n.codehilite .ne { color: #D2413A; font-weight: bold } /* Name.Exception */\\n.codehilite .nf { color: #0000FF } /* Name.Function */\\n.codehilite .nl { color: #A0A000 } /* Name.Label */\\n.codehilite .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */\\n.codehilite .nt { color: #008000; font-weight: bold } /* Name.Tag */\\n.codehilite .nv { color: #19177C } /* Name.Variable */\\n.codehilite .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */\\n.codehilite .w { color: #bbbbbb } /* Text.Whitespace */\\n.codehilite .mb { color: #666666 } /* Literal.Number.Bin */\\n.codehilite .mf { color: #666666 } /* Literal.Number.Float */\\n.codehilite .mh { color: #666666 } /* Literal.Number.Hex */\\n.codehilite .mi { color: #666666 } /* Literal.Number.Integer */\\n.codehilite .mo { color: #666666 } /* Literal.Number.Oct */\\n.codehilite .sa { color: #BA2121 } /* Literal.String.Affix */\\n.codehilite .sb { color: #BA2121 } /* Literal.String.Backtick */\\n.codehilite .sc { color: #BA2121 } /* Literal.String.Char */\\n.codehilite .dl { color: #BA2121 } /* Literal.String.Delimiter */\\n.codehilite .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */\\n.codehilite .s2 { color: #BA2121 } /* Literal.String.Double */\\n.codehilite .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */\\n.codehilite .sh { color: #BA2121 } /* Literal.String.Heredoc */\\n.codehilite .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */\\n.codehilite .sx { color: #008000 } /* Literal.String.Other */\\n.codehilite .sr { color: #BB6688 } /* Literal.String.Regex */\\n.codehilite .s1 { color: #BA2121 } /* Literal.String.Single */\\n.codehilite .ss { color: #19177C } /* Literal.String.Symbol */\\n.codehilite .bp { color: #008000 } /* Name.Builtin.Pseudo */\\n.codehilite .fm { color: #0000FF } /* Name.Function.Magic */\\n.codehilite .vc { color: #19177C } /* Name.Variable.Class */\\n.codehilite .vg { color: #19177C } /* Name.Variable.Global */\\n.codehilite .vi { color: #19177C } /* Name.Variable.Instance */\\n.codehilite .vm { color: #19177C } /* Name.Variable.Magic */\\n.codehilite .il { color: #666666 } /* Literal.Number.Integer.Long */\\n\\n.markdown h1 { margin-block-start: 0.34em }\\n.markdown h2 { margin-block-start: 0.42em }\\n.markdown h3 { margin-block-start: 0.5em }\\n.markdown h4 { margin-block-start: 0.67em }\\n.markdown h5 { margin-block-start: 0.84em }\\n.markdown h6 { margin-block-start: 1.17em }\\n.markdown ul { padding-inline-start: 2em }\\n.markdown ol { padding-inline-start: 2em }\\n.markdown strong { font-weight: 600 }\\n.markdown a { color: -webkit-link }\\n.markdown a { color: -moz-hyperlinkText }\\n\");\n", - " },\n", - " function(Bokeh) {\n", - " inject_raw_css(\".json-formatter-row {\\n font-family: monospace;\\n}\\n.json-formatter-row,\\n.json-formatter-row a,\\n.json-formatter-row a:hover {\\n color: black;\\n text-decoration: none;\\n}\\n.json-formatter-row .json-formatter-row {\\n margin-left: 1rem;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty {\\n opacity: 0.5;\\n margin-left: 1rem;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty:after {\\n display: none;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-object:after {\\n content: \\\"No properties\\\";\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-array:after {\\n content: \\\"[]\\\";\\n}\\n.json-formatter-row .json-formatter-string,\\n.json-formatter-row .json-formatter-stringifiable {\\n color: green;\\n white-space: pre;\\n word-wrap: break-word;\\n}\\n.json-formatter-row .json-formatter-number {\\n color: blue;\\n}\\n.json-formatter-row .json-formatter-boolean {\\n color: red;\\n}\\n.json-formatter-row .json-formatter-null {\\n color: #855A00;\\n}\\n.json-formatter-row .json-formatter-undefined {\\n color: #ca0b69;\\n}\\n.json-formatter-row .json-formatter-function {\\n color: #FF20ED;\\n}\\n.json-formatter-row .json-formatter-date {\\n background-color: rgba(0, 0, 0, 0.05);\\n}\\n.json-formatter-row .json-formatter-url {\\n text-decoration: underline;\\n color: blue;\\n cursor: pointer;\\n}\\n.json-formatter-row .json-formatter-bracket {\\n color: blue;\\n}\\n.json-formatter-row .json-formatter-key {\\n color: #00008B;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-row .json-formatter-toggler-link {\\n cursor: pointer;\\n}\\n.json-formatter-row .json-formatter-toggler {\\n line-height: 1.2rem;\\n font-size: 0.7rem;\\n vertical-align: middle;\\n opacity: 0.6;\\n cursor: pointer;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-row .json-formatter-toggler:after {\\n display: inline-block;\\n transition: transform 100ms ease-in;\\n content: \\\"\\\\25BA\\\";\\n}\\n.json-formatter-row > a > .json-formatter-preview-text {\\n opacity: 0;\\n transition: opacity 0.15s ease-in;\\n font-style: italic;\\n}\\n.json-formatter-row:hover > a > .json-formatter-preview-text {\\n opacity: 0.6;\\n}\\n.json-formatter-row.json-formatter-open > .json-formatter-toggler-link .json-formatter-toggler:after {\\n transform: rotate(90deg);\\n}\\n.json-formatter-row.json-formatter-open > .json-formatter-children:after {\\n display: inline-block;\\n}\\n.json-formatter-row.json-formatter-open > a > .json-formatter-preview-text {\\n display: none;\\n}\\n.json-formatter-row.json-formatter-open.json-formatter-empty:after {\\n display: block;\\n}\\n.json-formatter-dark.json-formatter-row {\\n font-family: monospace;\\n}\\n.json-formatter-dark.json-formatter-row,\\n.json-formatter-dark.json-formatter-row a,\\n.json-formatter-dark.json-formatter-row a:hover {\\n color: white;\\n text-decoration: none;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-row {\\n margin-left: 1rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty {\\n opacity: 0.5;\\n margin-left: 1rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty:after {\\n display: none;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-object:after {\\n content: \\\"No properties\\\";\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-array:after {\\n content: \\\"[]\\\";\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-string,\\n.json-formatter-dark.json-formatter-row .json-formatter-stringifiable {\\n color: #31F031;\\n white-space: pre;\\n word-wrap: break-word;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-number {\\n color: #66C2FF;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-boolean {\\n color: #EC4242;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-null {\\n color: #EEC97D;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-undefined {\\n color: #ef8fbe;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-function {\\n color: #FD48CB;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-date {\\n background-color: rgba(255, 255, 255, 0.05);\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-url {\\n text-decoration: underline;\\n color: #027BFF;\\n cursor: pointer;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-bracket {\\n color: #9494FF;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-key {\\n color: #23A0DB;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler-link {\\n cursor: pointer;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler {\\n line-height: 1.2rem;\\n font-size: 0.7rem;\\n vertical-align: middle;\\n opacity: 0.6;\\n cursor: pointer;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler:after {\\n display: inline-block;\\n transition: transform 100ms ease-in;\\n content: \\\"\\\\25BA\\\";\\n}\\n.json-formatter-dark.json-formatter-row > a > .json-formatter-preview-text {\\n opacity: 0;\\n transition: opacity 0.15s ease-in;\\n font-style: italic;\\n}\\n.json-formatter-dark.json-formatter-row:hover > a > .json-formatter-preview-text {\\n opacity: 0.6;\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open > .json-formatter-toggler-link .json-formatter-toggler:after {\\n transform: rotate(90deg);\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open > .json-formatter-children:after {\\n display: inline-block;\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open > a > .json-formatter-preview-text {\\n display: none;\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open.json-formatter-empty:after {\\n display: block;\\n}\\n\");\n", - " },\n", - " function(Bokeh) {\n", - " inject_raw_css(\".bk.pn-loading:before {\\n position: absolute;\\n height: 100%;\\n width: 100%;\\n content: '';\\n z-index: 1000;\\n background-color: rgb(255,255,255,0.50);\\n border-color: lightgray;\\n background-repeat: no-repeat;\\n background-position: center;\\n background-size: auto 50%;\\n border-width: 1px;\\n cursor: progress;\\n}\\n.bk.pn-loading.arcs:hover:before {\\n cursor: progress;\\n}\\n\");\n", - " },\n", - " function(Bokeh) {\n", - " inject_raw_css(\"table.panel-df {\\n margin-left: auto;\\n margin-right: auto;\\n border: none;\\n border-collapse: collapse;\\n border-spacing: 0;\\n color: black;\\n font-size: 12px;\\n table-layout: fixed;\\n width: 100%;\\n}\\n\\n.panel-df tr, .panel-df th, .panel-df td {\\n text-align: right;\\n vertical-align: middle;\\n padding: 0.5em 0.5em !important;\\n line-height: normal;\\n white-space: normal;\\n max-width: none;\\n border: none;\\n}\\n\\n.panel-df tbody {\\n display: table-row-group;\\n vertical-align: middle;\\n border-color: inherit;\\n}\\n\\n.panel-df tbody tr:nth-child(odd) {\\n background: #f5f5f5;\\n}\\n\\n.panel-df thead {\\n border-bottom: 1px solid black;\\n vertical-align: bottom;\\n}\\n\\n.panel-df tr:hover {\\n background: lightblue !important;\\n cursor: pointer;\\n}\\n\");\n", - " },\n", - " function(Bokeh) {\n", - " inject_raw_css(\"\\n .bk.pn-loading.arcs:before {\\n background-image: 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* \n", - " * Redistribution and use in source and binary forms, with or without modification,\n", - " * are permitted provided that the following conditions are met:\n", - " * \n", - " * Redistributions of source code must retain the above copyright notice,\n", - " * this list of conditions and the following disclaimer.\n", - " * \n", - " * Redistributions in binary form must reproduce the above copyright notice,\n", - " * this list of conditions and the following disclaimer in the documentation\n", - " * and/or other materials provided with the distribution.\n", - " * \n", - " * Neither the name of Anaconda nor the names of any contributors\n", - " * may be used to endorse or promote products derived from this software\n", - " * without specific prior written permission.\n", - " * \n", - " * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\n", - " * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n", - " * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE\n", - " * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE\n", - " * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR\n", - " * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF\n", - " * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS\n", - " * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN\n", - " * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)\n", - " * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF\n", - " * THE POSSIBILITY OF SUCH DAMAGE.\n", - " */\n", - " (function(root, factory) {\n", - " const bokeh = factory();\n", - " bokeh.__bokeh__ = true;\n", - " if (typeof root.Bokeh === \"undefined\" || typeof root.Bokeh.__bokeh__ === \"undefined\") {\n", - " root.Bokeh = bokeh;\n", - " }\n", - " const Bokeh = root.Bokeh;\n", - " Bokeh[bokeh.version] = bokeh;\n", - " })(this, function() {\n", - " let define;\n", - " const parent_require = typeof require 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e)n.set(t.id,t);for(const e of s)e.detach_document();for(const e of o)e.attach_document(this);this._all_models=n}roots(){return this._roots}add_root(e,t){if(l.logger.debug(`Adding root: ${e}`),!(0,g.includes)(this._roots,e)){this._push_all_models_freeze();try{this._roots.push(e)}finally{this._pop_all_models_freeze()}this._trigger_on_change(new S.RootAddedEvent(this,e,t))}}remove_root(e,t){const s=this._roots.indexOf(e);if(!(s<0)){this._push_all_models_freeze();try{this._roots.splice(s,1)}finally{this._pop_all_models_freeze()}this._trigger_on_change(new S.RootRemovedEvent(this,e,t))}}title(){return this._title}set_title(e,t){e!==this._title&&(this._title=e,this._trigger_on_change(new S.TitleChangedEvent(this,e,t)))}get_model_by_id(e){var t;return null!==(t=this._all_models.get(e))&&void 0!==t?t:null}get_model_by_name(e){const t=[];for(const s of this._all_models.values())s instanceof M.Model&&s.name==e&&t.push(s);switch(t.length){case 0:return null;case 1:return t[0];default:throw new Error(`Multiple models are named '${e}'`)}}on_message(e,t){const s=this._message_callbacks.get(e);null==s?this._message_callbacks.set(e,new Set([t])):s.add(t)}remove_on_message(e,t){var s;null===(s=this._message_callbacks.get(e))||void 0===s||s.delete(t)}_trigger_on_message(e,t){const s=this._message_callbacks.get(e);if(null!=s)for(const e of s)e(t)}on_change(e,t=!1){this._callbacks.has(e)||this._callbacks.set(e,t)}remove_on_change(e){this._callbacks.delete(e)}_trigger_on_change(e){for(const[t,s]of this._callbacks)if(!s&&e instanceof S.DocumentEventBatch)for(const s of e.events)t(s);else t(e)}_notify_change(e,t,s,o,n){this._trigger_on_change(new S.ModelChangedEvent(this,e,t,s,o,null==n?void 0:n.setter_id,null==n?void 0:n.hint))}static _instantiate_object(e,t,s,o){const n=Object.assign(Object.assign({},s),{id:e,__deferred__:!0});return new(o.get(t))(n)}static _instantiate_references_json(e,t,s){var o;const n=new Map;for(const i of e){const e=i.id,r=i.type,a=null!==(o=i.attributes)&&void 0!==o?o:{};let l=t.get(e);null==l&&(l=E._instantiate_object(e,r,a,s),null!=i.subtype&&l.set_subtype(i.subtype)),n.set(l.id,l)}return n}static _resolve_refs(e,t,s,o){function n(e){var i;if((0,f.is_ref)(e)){const o=null!==(i=t.get(e.id))&&void 0!==i?i:s.get(e.id);if(null!=o)return o;throw new Error(`reference ${JSON.stringify(e)} isn't known (not in Document?)`)}if((0,u.is_NDArray_ref)(e)){const{buffer:t,dtype:s,shape:n}=(0,u.decode_NDArray)(e,o);return(0,m.ndarray)(t,{dtype:s,shape:n})}return(0,b.isArray)(e)?function(e){const t=[];for(const s of e)t.push(n(s));return t}(e):(0,b.isPlainObject)(e)?function(e){const t={};for(const[s,o]of(0,v.entries)(e))t[s]=n(o);return t}(e):e}return n(e)}static _initialize_references_json(e,t,s,o){const n=new Map;for(const{id:i,attributes:r}of e){const e=!t.has(i),a=e?s.get(i):t.get(i),l=E._resolve_refs(r,t,s,o);a.setv(l,{silent:!0}),n.set(i,{instance:a,is_new:e})}const i=[],r=new Set;function a(e){if(e instanceof c.HasProps){if(n.has(e.id)&&!r.has(e.id)){r.add(e.id);const{instance:t,is_new:s}=n.get(e.id),{attributes:o}=t;for(const e of(0,v.values)(o))a(e);s&&(t.finalize(),i.push(t))}}else if((0,b.isArray)(e))for(const t of e)a(t);else if((0,b.isPlainObject)(e))for(const t of(0,v.values)(e))a(t)}for(const e of n.values())a(e.instance);for(const e of i)e.connect_signals()}static _event_for_attribute_change(e,t,s,o,n){if(o.get_model_by_id(e.id).property(t).syncable){const i={kind:\"ModelChanged\",model:{id:e.id},attr:t,new:s};return c.HasProps._json_record_references(o,s,n,{recursive:!0}),i}return null}static _events_to_sync_objects(e,t,s,o){const n=Object.keys(e.attributes),i=Object.keys(t.attributes),r=(0,g.difference)(n,i),a=(0,g.difference)(i,n),_=(0,g.intersection)(n,i),c=[];for(const e of r)l.logger.warn(`Server sent key ${e} but we don't seem to have it in our JSON`);for(const n of a){const i=t.attributes[n];c.push(E._event_for_attribute_change(e,n,i,s,o))}for(const n of _){const i=e.attributes[n],r=t.attributes[n];null==i&&null==r||(null==i||null==r?c.push(E._event_for_attribute_change(e,n,r,s,o)):\"data\"==n||(0,w.is_equal)(i,r)||c.push(E._event_for_attribute_change(e,n,r,s,o)))}return c.filter((e=>null!=e))}static _compute_patch_since_json(e,t){const s=t.to_json(!1);function o(e){const t=new Map;for(const s of e.roots.references)t.set(s.id,s);return t}const n=o(e),i=new Map,r=[];for(const t of e.roots.root_ids)i.set(t,n.get(t)),r.push(t);const a=o(s),l=new Map,_=[];for(const e of s.roots.root_ids)l.set(e,a.get(e)),_.push(e);if(r.sort(),_.sort(),(0,g.difference)(r,_).length>0||(0,g.difference)(_,r).length>0)throw new Error(\"Not implemented: computing add/remove of document roots\");const c=new Set;let h=[];for(const e of t._all_models.keys())if(n.has(e)){const s=E._events_to_sync_objects(n.get(e),a.get(e),t,c);h=h.concat(s)}const f=new d.Serializer({include_defaults:!1});return f.to_serializable([...c]),{references:[...f.definitions],events:h}}to_json_string(e=!0){return JSON.stringify(this.to_json(e))}to_json(e=!0){const t=new d.Serializer({include_defaults:e}),s=t.to_serializable(this._roots);return{version:a.version,title:this._title,roots:{root_ids:s.map((e=>e.id)),references:[...t.definitions]}}}static from_json_string(e){const t=JSON.parse(e);return E.from_json(t)}static from_json(e){l.logger.debug(\"Creating Document from JSON\");const t=e.version,s=-1!==t.indexOf(\"+\")||-1!==t.indexOf(\"-\"),o=`Library versions: JS (${a.version}) / Python (${t})`;s||a.version.replace(/-(dev|rc)\\./,\"$1\")==t?l.logger.debug(o):(l.logger.warn(\"JS/Python version mismatch\"),l.logger.warn(o));const n=new r.ModelResolver;null!=e.defs&&(0,j.resolve_defs)(e.defs,n);const i=e.roots,_=i.root_ids,c=i.references,d=E._instantiate_references_json(c,new Map,n);E._initialize_references_json(c,new Map,d,new Map);const h=new E({resolver:n});for(const e of _){const t=d.get(e);null!=t&&h.add_root(t)}return h.set_title(e.title),h}replace_with_json(e){E.from_json(e).destructively_move(this)}create_json_patch_string(e){return JSON.stringify(this.create_json_patch(e))}create_json_patch(e){for(const t of e)if(t.document!=this)throw new Error(\"Cannot create a patch using events from a different document\");const t=new d.Serializer,s=t.to_serializable(e);for(const e of this._all_models.values())t.remove_def(e);return{events:s,references:[...t.definitions]}}apply_json_patch(e,t=new Map,s){const o=e.references,n=e.events,i=E._instantiate_references_json(o,this._all_models,this._resolver);t instanceof Map||(t=new Map(t));for(const e of n)switch(e.kind){case\"RootAdded\":case\"RootRemoved\":case\"ModelChanged\":{const t=e.model.id,s=this._all_models.get(t);if(null!=s)i.set(t,s);else if(!i.has(t))throw l.logger.warn(`Got an event for unknown model ${e.model}\"`),new Error(\"event model wasn't known\");break}}const r=new Map(this._all_models),a=new Map;for(const[e,t]of i)r.has(e)||a.set(e,t);E._initialize_references_json(o,r,a,t);for(const e of n)switch(e.kind){case\"MessageSent\":{const{msg_type:s,msg_data:o}=e;let n;if(void 0===o){if(1!=t.size)throw new Error(\"expected exactly one buffer\");{const[[,e]]=t;n=e}}else n=E._resolve_refs(o,r,a,t);this._trigger_on_message(s,n);break}case\"ModelChanged\":{const o=e.model.id,n=this._all_models.get(o);if(null==n)throw new Error(`Cannot apply patch to ${o} which is not in the document`);const i=e.attr,l=E._resolve_refs(e.new,r,a,t);n.setv({[i]:l},{setter_id:s});break}case\"ColumnDataChanged\":{const o=e.column_source.id,n=this._all_models.get(o);if(null==n)throw new Error(`Cannot stream to ${o} which is not in the document`);const i=E._resolve_refs(e.new,new Map,new Map,t);if(null!=e.cols)for(const e in n.data)e in i||(i[e]=n.data[e]);n.setv({data:i},{setter_id:s,check_eq:!1});break}case\"ColumnsStreamed\":{const t=e.column_source.id,o=this._all_models.get(t);if(null==o)throw new 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extends((0,c.Signalable)()){constructor(e={}){var t,s;super(),this._subtype=void 0,this.document=null,this.destroyed=new c.Signal0(this,\"destroyed\"),this.change=new c.Signal0(this,\"change\"),this.transformchange=new c.Signal0(this,\"transformchange\"),this.exprchange=new c.Signal0(this,\"exprchange\"),this.properties={},this._watchers=new WeakMap,this._pending=!1,this._changing=!1;const n=e instanceof Map?e.get.bind(e):t=>e[t];this.id=null!==(t=n(\"id\"))&&void 0!==t?t:(0,u.uniqueId)();for(const[e,{type:t,default_value:s,options:r}]of(0,l.entries)(this._props)){let i;t instanceof _.PropertyAlias?Object.defineProperty(this.properties,e,{get:()=>this.properties[t.attr],configurable:!1,enumerable:!1}):(i=t instanceof h.Kind?new _.PrimitiveProperty(this,e,t,s,n(e),r):new t(this,e,h.Any,s,n(e),r),this.properties[e]=i)}null!==(s=n(\"__deferred__\"))&&void 0!==s&&s||(this.finalize(),this.connect_signals())}get is_syncable(){return!0}set type(e){console.warn(\"prototype.type = 'ModelName' 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t&&(this.set_value(e),e.stroke()),t}values(){return{color:this.line_color.get_value(),alpha:this.line_alpha.get_value(),width:this.line_width.get_value(),join:this.line_join.get_value(),cap:this.line_cap.get_value(),dash:this.line_dash.get_value(),offset:this.line_dash_offset.get_value()}}set_value(e){const t=this.line_color.get_value(),i=this.line_alpha.get_value();e.strokeStyle=(0,o.color2css)(t,i),e.lineWidth=this.line_width.get_value(),e.lineJoin=this.line_join.get_value(),e.lineCap=this.line_cap.get_value(),e.lineDash=r(this.line_dash.get_value()),e.lineDashOffset=this.line_dash_offset.get_value()}}i.Line=u,u.__name__=\"Line\";class c extends n.VisualUniforms{get doit(){const e=this.line_color.value,t=this.line_alpha.value,i=this.line_width.value;return!(0==e||0==t||0==i)}apply(e){const{doit:t}=this;return t&&(this.set_value(e),e.stroke()),t}values(){return{color:this.line_color.value,alpha:this.line_alpha.value,width:this.line_width.value,join:this.line_join.value,cap:this.line_cap.value,dash:this.line_dash.value,offset:this.line_dash_offset.value}}set_value(e){const t=this.line_color.value,i=this.line_alpha.value;e.strokeStyle=(0,o.color2css)(t,i),e.lineWidth=this.line_width.value,e.lineJoin=this.line_join.value,e.lineCap=this.line_cap.value,e.lineDash=r(this.line_dash.value),e.lineDashOffset=this.line_dash_offset.value}}i.LineScalar=c,c.__name__=\"LineScalar\";class d extends n.VisualUniforms{get doit(){const{line_color:e}=this;if(e.is_Scalar()&&0==e.value)return!1;const{line_alpha:t}=this;if(t.is_Scalar()&&0==t.value)return!1;const{line_width:i}=this;return!i.is_Scalar()||0!=i.value}apply(e,t){const{doit:i}=this;return i&&(this.set_vectorize(e,t),e.stroke()),i}values(e){return{color:this.line_color.get(e),alpha:this.line_alpha.get(e),width:this.line_width.get(e),join:this.line_join.get(e),cap:this.line_cap.get(e),dash:this.line_dash.get(e),offset:this.line_dash_offset.get(e)}}set_vectorize(e,t){const i=this.line_color.get(t),l=this.line_alpha.get(t),s=this.line_width.get(t),a=this.line_join.get(t),n=this.line_cap.get(t),h=this.line_dash.get(t),_=this.line_dash_offset.get(t);e.strokeStyle=(0,o.color2css)(i,l),e.lineWidth=s,e.lineJoin=a,e.lineCap=n,e.lineDash=r(h),e.lineDashOffset=_}}i.LineVector=d,d.__name__=\"LineVector\",u.prototype.type=\"line\",u.prototype.attrs=Object.keys(h.Line),c.prototype.type=\"line\",c.prototype.attrs=Object.keys(h.LineScalar),d.prototype.type=\"line\",d.prototype.attrs=Object.keys(h.LineVector)},\n", - " function _(t,s,o,i,r){i();class e{constructor(t,s=\"\"){this.obj=t,this.prefix=s;const o=this;this._props=[];for(const i of this.attrs){const r=t.model.properties[s+i];r.change.connect((()=>this.update())),o[i]=r,this._props.push(r)}}*[Symbol.iterator](){yield*this._props}update(){}}o.VisualProperties=e,e.__name__=\"VisualProperties\";class p{constructor(t,s=\"\"){this.obj=t,this.prefix=s;for(const o of this.attrs)Object.defineProperty(this,o,{get:()=>t[s+o]})}*[Symbol.iterator](){for(const t of this.attrs)yield this.obj.model.properties[this.prefix+t]}update(){}}o.VisualUniforms=p,p.__name__=\"VisualUniforms\"},\n", - " function _(e,l,t,a,c){a();const r=e(1),o=(0,r.__importStar)(e(18)),n=e(20),i=(0,r.__importStar)(e(21)),_=e(13);t.Line={line_color:[i.Nullable(i.Color),\"black\"],line_alpha:[i.Alpha,1],line_width:[i.Number,1],line_join:[n.LineJoin,\"bevel\"],line_cap:[n.LineCap,\"butt\"],line_dash:[i.Or(n.LineDash,i.Array(i.Number)),[]],line_dash_offset:[i.Number,0]},t.Fill={fill_color:[i.Nullable(i.Color),\"gray\"],fill_alpha:[i.Alpha,1]},t.Hatch={hatch_color:[i.Nullable(i.Color),\"black\"],hatch_alpha:[i.Alpha,1],hatch_scale:[i.Number,12],hatch_pattern:[i.Nullable(i.Or(n.HatchPatternType,i.String)),null],hatch_weight:[i.Number,1],hatch_extra:[i.Dict(i.AnyRef()),{}]},t.Text={text_color:[i.Nullable(i.Color),\"#444444\"],text_alpha:[i.Alpha,1],text_font:[o.Font,\"helvetica\"],text_font_size:[i.FontSize,\"16px\"],text_font_style:[n.FontStyle,\"normal\"],text_align:[n.TextAlign,\"left\"],text_baseline:[n.TextBaseline,\"bottom\"],text_line_height:[i.Number,1.2]},t.LineScalar={line_color:[o.ColorScalar,\"black\"],line_alpha:[o.NumberScalar,1],line_width:[o.NumberScalar,1],line_join:[o.LineJoinScalar,\"bevel\"],line_cap:[o.LineCapScalar,\"butt\"],line_dash:[o.LineDashScalar,[]],line_dash_offset:[o.NumberScalar,0]},t.FillScalar={fill_color:[o.ColorScalar,\"gray\"],fill_alpha:[o.NumberScalar,1]},t.HatchScalar={hatch_color:[o.ColorScalar,\"black\"],hatch_alpha:[o.NumberScalar,1],hatch_scale:[o.NumberScalar,12],hatch_pattern:[o.NullStringScalar,null],hatch_weight:[o.NumberScalar,1],hatch_extra:[o.AnyScalar,{}]},t.TextScalar={text_color:[o.ColorScalar,\"#444444\"],text_alpha:[o.NumberScalar,1],text_font:[o.FontScalar,\"helvetica\"],text_font_size:[o.FontSizeScalar,\"16px\"],text_font_style:[o.FontStyleScalar,\"normal\"],text_align:[o.TextAlignScalar,\"left\"],text_baseline:[o.TextBaselineScalar,\"bottom\"],text_line_height:[o.NumberScalar,1.2]},t.LineVector={line_color:[o.ColorSpec,\"black\"],line_alpha:[o.NumberSpec,1],line_width:[o.NumberSpec,1],line_join:[o.LineJoinSpec,\"bevel\"],line_cap:[o.LineCapSpec,\"butt\"],line_dash:[o.LineDashSpec,[]],line_dash_offset:[o.NumberSpec,0]},t.FillVector={fill_color:[o.ColorSpec,\"gray\"],fill_alpha:[o.NumberSpec,1]},t.HatchVector={hatch_color:[o.ColorSpec,\"black\"],hatch_alpha:[o.NumberSpec,1],hatch_scale:[o.NumberSpec,12],hatch_pattern:[o.NullStringSpec,null],hatch_weight:[o.NumberSpec,1],hatch_extra:[o.AnyScalar,{}]},t.TextVector={text_color:[o.ColorSpec,\"#444444\"],text_alpha:[o.NumberSpec,1],text_font:[o.FontSpec,\"helvetica\"],text_font_size:[o.FontSizeSpec,\"16px\"],text_font_style:[o.FontStyleSpec,\"normal\"],text_align:[o.TextAlignSpec,\"left\"],text_baseline:[o.TextBaselineSpec,\"bottom\"],text_line_height:[o.NumberSpec,1.2]},t.attrs_of=function(e,l,t,a=!1){const c={};for(const r of(0,_.keys)(t)){const t=`${l}${r}`,o=e[t];c[a?t:r]=o}return c}},\n", - " function _(l,t,e,i,s){i();const a=l(1),o=l(47),r=(0,a.__importStar)(l(48)),_=l(22);class c extends o.VisualProperties{get doit(){const l=this.fill_color.get_value(),t=this.fill_alpha.get_value();return!(null==l||0==t)}apply(l,t){const{doit:e}=this;return e&&(this.set_value(l),l.fill(t)),e}values(){return{color:this.fill_color.get_value(),alpha:this.fill_alpha.get_value()}}set_value(l){const t=this.fill_color.get_value(),e=this.fill_alpha.get_value();l.fillStyle=(0,_.color2css)(t,e)}}e.Fill=c,c.__name__=\"Fill\";class h extends o.VisualUniforms{get doit(){const l=this.fill_color.value,t=this.fill_alpha.value;return!(0==l||0==t)}apply(l,t){const{doit:e}=this;return e&&(this.set_value(l),l.fill(t)),e}values(){return{color:this.fill_color.value,alpha:this.fill_alpha.value}}set_value(l){const t=this.fill_color.value,e=this.fill_alpha.value;l.fillStyle=(0,_.color2css)(t,e)}}e.FillScalar=h,h.__name__=\"FillScalar\";class u extends o.VisualUniforms{get doit(){const{fill_color:l}=this;if(l.is_Scalar()&&0==l.value)return!1;const{fill_alpha:t}=this;return!t.is_Scalar()||0!=t.value}apply(l,t,e){const{doit:i}=this;return i&&(this.set_vectorize(l,t),l.fill(e)),i}values(l){return{color:this.fill_color.get(l),alpha:this.fill_alpha.get(l)}}set_vectorize(l,t){const e=this.fill_color.get(t),i=this.fill_alpha.get(t);l.fillStyle=(0,_.color2css)(e,i)}}e.FillVector=u,u.__name__=\"FillVector\",c.prototype.type=\"fill\",c.prototype.attrs=Object.keys(r.Fill),h.prototype.type=\"fill\",h.prototype.attrs=Object.keys(r.FillScalar),u.prototype.type=\"fill\",u.prototype.attrs=Object.keys(r.FillVector)},\n", - " function _(t,e,l,s,_){s();const i=t(1),a=t(47),o=(0,i.__importStar)(t(48)),n=t(22);class h extends a.VisualProperties{get doit(){const t=this.text_color.get_value(),e=this.text_alpha.get_value();return!(null==t||0==e)}values(){return{color:this.text_color.get_value(),alpha:this.text_alpha.get_value(),font:this.text_font.get_value(),font_size:this.text_font_size.get_value(),font_style:this.text_font_style.get_value(),align:this.text_align.get_value(),baseline:this.text_baseline.get_value(),line_height:this.text_line_height.get_value()}}set_value(t){const e=this.text_color.get_value(),l=this.text_alpha.get_value();t.fillStyle=(0,n.color2css)(e,l),t.font=this.font_value(),t.textAlign=this.text_align.get_value(),t.textBaseline=this.text_baseline.get_value()}font_value(){return`${this.text_font_style.get_value()} ${this.text_font_size.get_value()} ${this.text_font.get_value()}`}}l.Text=h,h.__name__=\"Text\";class x extends a.VisualUniforms{get doit(){const t=this.text_color.value,e=this.text_alpha.value;return!(0==t||0==e)}values(){return{color:this.text_color.value,alpha:this.text_alpha.value,font:this.text_font.value,font_size:this.text_font_size.value,font_style:this.text_font_style.value,align:this.text_align.value,baseline:this.text_baseline.value,line_height:this.text_line_height.value}}set_value(t){const e=this.text_color.value,l=this.text_alpha.value,s=this.font_value(),_=this.text_align.value,i=this.text_baseline.value;t.fillStyle=(0,n.color2css)(e,l),t.font=s,t.textAlign=_,t.textBaseline=i}font_value(){return`${this.text_font_style.value} ${this.text_font_size.value} ${this.text_font.value}`}}l.TextScalar=x,x.__name__=\"TextScalar\";class u extends a.VisualUniforms{values(t){return{color:this.text_color.get(t),alpha:this.text_alpha.get(t),font:this.text_font.get(t),font_size:this.text_font_size.get(t),font_style:this.text_font_style.get(t),align:this.text_align.get(t),baseline:this.text_baseline.get(t),line_height:this.text_line_height.get(t)}}get doit(){const{text_color:t}=this;if(t.is_Scalar()&&0==t.value)return!1;const{text_alpha:e}=this;return!e.is_Scalar()||0!=e.value}set_vectorize(t,e){const l=this.text_color.get(e),s=this.text_alpha.get(e),_=this.font_value(e),i=this.text_align.get(e),a=this.text_baseline.get(e);t.fillStyle=(0,n.color2css)(l,s),t.font=_,t.textAlign=i,t.textBaseline=a}font_value(t){return`${this.text_font_style.get(t)} ${this.text_font_size.get(t)} ${this.text_font.get(t)}`}}l.TextVector=u,u.__name__=\"TextVector\",h.prototype.type=\"text\",h.prototype.attrs=Object.keys(o.Text),x.prototype.type=\"text\",x.prototype.attrs=Object.keys(o.TextScalar),u.prototype.type=\"text\",u.prototype.attrs=Object.keys(o.TextVector)},\n", - " function _(t,e,a,r,i){r();const h=t(1),s=t(47),n=t(52),c=(0,h.__importStar)(t(18)),_=(0,h.__importStar)(t(48));class l extends s.VisualProperties{constructor(){super(...arguments),this._update_iteration=0}update(){if(this._update_iteration++,this._hatch_image=null,!this.doit)return;const t=this.hatch_color.get_value(),e=this.hatch_alpha.get_value(),a=this.hatch_scale.get_value(),r=this.hatch_pattern.get_value(),i=this.hatch_weight.get_value(),h=t=>{this._hatch_image=t},s=this.hatch_extra.get_value()[r];if(null!=s){const r=s.get_pattern(t,e,a,i);if(r instanceof Promise){const{_update_iteration:t}=this;r.then((e=>{this._update_iteration==t&&(h(e),this.obj.request_render())}))}else h(r)}else{const s=this.obj.canvas.create_layer(),c=(0,n.get_pattern)(s,r,t,e,a,i);h(c)}}get doit(){const t=this.hatch_color.get_value(),e=this.hatch_alpha.get_value(),a=this.hatch_pattern.get_value();return!(null==t||0==e||\" \"==a||\"blank\"==a||null==a)}apply(t,e){const{doit:a}=this;return a&&(this.set_value(t),t.layer.undo_transform((()=>t.fill(e)))),a}set_value(t){const e=this.pattern(t);t.fillStyle=null!=e?e:\"transparent\"}pattern(t){const e=this._hatch_image;return null==e?null:t.createPattern(e,this.repetition())}repetition(){const t=this.hatch_pattern.get_value(),e=this.hatch_extra.get_value()[t];if(null==e)return\"repeat\";switch(e.repetition){case\"repeat\":return\"repeat\";case\"repeat_x\":return\"repeat-x\";case\"repeat_y\":return\"repeat-y\";case\"no_repeat\":return\"no-repeat\"}}}a.Hatch=l,l.__name__=\"Hatch\";class o extends s.VisualUniforms{constructor(){super(...arguments),this._static_doit=!1,this._update_iteration=0}_compute_static_doit(){const t=this.hatch_color.value,e=this.hatch_alpha.value,a=this.hatch_pattern.value;return!(null==t||0==e||\" \"==a||\"blank\"==a||null==a)}update(){this._update_iteration++;const t=this.hatch_color.length;if(this._hatch_image=new c.UniformScalar(null,t),this._static_doit=this._compute_static_doit(),!this._static_doit)return;const e=this.hatch_color.value,a=this.hatch_alpha.value,r=this.hatch_scale.value,i=this.hatch_pattern.value,h=this.hatch_weight.value,s=e=>{this._hatch_image=new c.UniformScalar(e,t)},_=this.hatch_extra.value[i];if(null!=_){const t=_.get_pattern(e,a,r,h);if(t instanceof Promise){const{_update_iteration:e}=this;t.then((t=>{this._update_iteration==e&&(s(t),this.obj.request_render())}))}else s(t)}else{const t=this.obj.canvas.create_layer(),c=(0,n.get_pattern)(t,i,e,a,r,h);s(c)}}get doit(){return this._static_doit}apply(t,e){const{doit:a}=this;return a&&(this.set_value(t),t.layer.undo_transform((()=>t.fill(e)))),a}set_value(t){var e;t.fillStyle=null!==(e=this.pattern(t))&&void 0!==e?e:\"transparent\"}pattern(t){const e=this._hatch_image.value;return null==e?null:t.createPattern(e,this.repetition())}repetition(){const t=this.hatch_pattern.value,e=this.hatch_extra.value[t];if(null==e)return\"repeat\";switch(e.repetition){case\"repeat\":return\"repeat\";case\"repeat_x\":return\"repeat-x\";case\"repeat_y\":return\"repeat-y\";case\"no_repeat\":return\"no-repeat\"}}}a.HatchScalar=o,o.__name__=\"HatchScalar\";class u extends s.VisualUniforms{constructor(){super(...arguments),this._static_doit=!1,this._update_iteration=0}_compute_static_doit(){const{hatch_color:t}=this;if(t.is_Scalar()&&0==t.value)return!1;const{hatch_alpha:e}=this;if(e.is_Scalar()&&0==e.value)return!1;const{hatch_pattern:a}=this;if(a.is_Scalar()){const t=a.value;if(\" \"==t||\"blank\"==t||null==t)return!1}return!0}update(){this._update_iteration++;const t=this.hatch_color.length;if(this._hatch_image=new c.UniformScalar(null,t),this._static_doit=this._compute_static_doit(),!this._static_doit)return;const e=(t,e,a,r,i,h)=>{const s=this.hatch_extra.value[t];if(null!=s){const t=s.get_pattern(e,a,r,i);if(t instanceof Promise){const{_update_iteration:e}=this;t.then((t=>{this._update_iteration==e&&(h(t),this.obj.request_render())}))}else h(t)}else{const s=this.obj.canvas.create_layer(),c=(0,n.get_pattern)(s,t,e,a,r,i);h(c)}};if(this.hatch_color.is_Scalar()&&this.hatch_alpha.is_Scalar()&&this.hatch_scale.is_Scalar()&&this.hatch_pattern.is_Scalar()&&this.hatch_weight.is_Scalar()){const a=this.hatch_color.value,r=this.hatch_alpha.value,i=this.hatch_scale.value;e(this.hatch_pattern.value,a,r,i,this.hatch_weight.value,(e=>{this._hatch_image=new c.UniformScalar(e,t)}))}else{const a=new Array(t);a.fill(null),this._hatch_image=new c.UniformVector(a);for(let r=0;r{a[r]=t}))}}}get doit(){return this._static_doit}apply(t,e,a){const{doit:r}=this;return r&&(this.set_vectorize(t,e),t.layer.undo_transform((()=>t.fill(a)))),r}set_vectorize(t,e){var a;t.fillStyle=null!==(a=this.pattern(t,e))&&void 0!==a?a:\"transparent\"}pattern(t,e){const a=this._hatch_image.get(e);return null==a?null:t.createPattern(a,this.repetition(e))}repetition(t){const e=this.hatch_pattern.get(t),a=this.hatch_extra.value[e];if(null==a)return\"repeat\";switch(a.repetition){case\"repeat\":return\"repeat\";case\"repeat_x\":return\"repeat-x\";case\"repeat_y\":return\"repeat-y\";case\"no_repeat\":return\"no-repeat\"}}}a.HatchVector=u,u.__name__=\"HatchVector\",l.prototype.type=\"hatch\",l.prototype.attrs=Object.keys(_.Hatch),o.prototype.type=\"hatch\",o.prototype.attrs=Object.keys(_.HatchScalar),u.prototype.type=\"hatch\",u.prototype.attrs=Object.keys(_.HatchVector)},\n", - " function _(e,o,a,s,r){s();const i=e(22);function l(e,o,a){e.moveTo(0,a+.5),e.lineTo(o,a+.5),e.stroke()}function n(e,o,a){e.moveTo(a+.5,0),e.lineTo(a+.5,o),e.stroke()}function t(e,o){e.moveTo(0,o),e.lineTo(o,0),e.stroke(),e.moveTo(0,0),e.lineTo(o,o),e.stroke()}a.hatch_aliases={\" \":\"blank\",\".\":\"dot\",o:\"ring\",\"-\":\"horizontal_line\",\"|\":\"vertical_line\",\"+\":\"cross\",'\"':\"horizontal_dash\",\":\":\"vertical_dash\",\"@\":\"spiral\",\"/\":\"right_diagonal_line\",\"\\\\\":\"left_diagonal_line\",x:\"diagonal_cross\",\",\":\"right_diagonal_dash\",\"`\":\"left_diagonal_dash\",v:\"horizontal_wave\",\">\":\"vertical_wave\",\"*\":\"criss_cross\"},a.get_pattern=function(e,o,s,r,c,k){return e.resize(c,c),e.prepare(),function(e,o,s,r,c,k){var _;const T=c,v=T/2,h=v/2,d=(0,i.color2css)(s,r);switch(e.strokeStyle=d,e.fillStyle=d,e.lineCap=\"square\",e.lineWidth=k,null!==(_=a.hatch_aliases[o])&&void 0!==_?_:o){case\"blank\":break;case\"dot\":e.arc(v,v,v/2,0,2*Math.PI,!0),e.fill();break;case\"ring\":e.arc(v,v,v/2,0,2*Math.PI,!0),e.stroke();break;case\"horizontal_line\":l(e,T,v);break;case\"vertical_line\":n(e,T,v);break;case\"cross\":l(e,T,v),n(e,T,v);break;case\"horizontal_dash\":l(e,v,v);break;case\"vertical_dash\":n(e,v,v);break;case\"spiral\":{const o=T/30;e.moveTo(v,v);for(let a=0;a<360;a++){const s=.1*a,r=v+o*s*Math.cos(s),i=v+o*s*Math.sin(s);e.lineTo(r,i)}e.stroke();break}case\"right_diagonal_line\":e.moveTo(.5-h,T),e.lineTo(h+.5,0),e.stroke(),e.moveTo(h+.5,T),e.lineTo(3*h+.5,0),e.stroke(),e.moveTo(3*h+.5,T),e.lineTo(5*h+.5,0),e.stroke(),e.stroke();break;case\"left_diagonal_line\":e.moveTo(h+.5,T),e.lineTo(.5-h,0),e.stroke(),e.moveTo(3*h+.5,T),e.lineTo(h+.5,0),e.stroke(),e.moveTo(5*h+.5,T),e.lineTo(3*h+.5,0),e.stroke(),e.stroke();break;case\"diagonal_cross\":t(e,T);break;case\"right_diagonal_dash\":e.moveTo(h+.5,3*h+.5),e.lineTo(3*h+.5,h+.5),e.stroke();break;case\"left_diagonal_dash\":e.moveTo(h+.5,h+.5),e.lineTo(3*h+.5,3*h+.5),e.stroke();break;case\"horizontal_wave\":e.moveTo(0,h),e.lineTo(v,3*h),e.lineTo(T,h),e.stroke();break;case\"vertical_wave\":e.moveTo(h,0),e.lineTo(3*h,v),e.lineTo(h,T),e.stroke();break;case\"criss_cross\":t(e,T),l(e,T,v),n(e,T,v)}}(e.ctx,o,s,r,c,k),e.canvas}},\n", - " function _(e,t,s,n,c){var a;n();const i=e(14),r=e(8),l=e(13),o=e(26),_=e(19);class h extends i.HasProps{constructor(e){super(e)}get is_syncable(){return this.syncable}[o.equals](e,t){return t.eq(this.id,e.id)&&super[o.equals](e,t)}initialize(){super.initialize(),this._js_callbacks=new Map}connect_signals(){super.connect_signals(),this._update_property_callbacks(),this.connect(this.properties.js_property_callbacks.change,(()=>this._update_property_callbacks())),this.connect(this.properties.js_event_callbacks.change,(()=>this._update_event_callbacks())),this.connect(this.properties.subscribed_events.change,(()=>this._update_event_callbacks()))}_process_event(e){var t;for(const s of null!==(t=this.js_event_callbacks[e.event_name])&&void 0!==t?t:[])s.execute(e);null!=this.document&&this.subscribed_events.some((t=>t==e.event_name))&&this.document.event_manager.send_event(e)}trigger_event(e){null!=this.document&&(e.origin=this,this.document.event_manager.trigger(e))}_update_event_callbacks(){null!=this.document?this.document.event_manager.subscribed_models.add(this):_.logger.warn(\"WARNING: Document not defined for updating event callbacks\")}_update_property_callbacks(){const e=e=>{const[t,s=null]=e.split(\":\");return null!=s?this.properties[s][t]:this[t]};for(const[t,s]of this._js_callbacks){const n=e(t);for(const e of s)this.disconnect(n,e)}this._js_callbacks.clear();for(const[t,s]of(0,l.entries)(this.js_property_callbacks)){const n=s.map((e=>()=>e.execute(this)));this._js_callbacks.set(t,n);const c=e(t);for(const e of n)this.connect(c,e)}}_doc_attached(){(0,l.isEmpty)(this.js_event_callbacks)&&0==this.subscribed_events.length||this._update_event_callbacks()}_doc_detached(){this.document.event_manager.subscribed_models.delete(this)}select(e){if((0,r.isString)(e))return[...this.references()].filter((t=>t instanceof h&&t.name===e));if(e.prototype instanceof i.HasProps)return[...this.references()].filter((t=>t instanceof e));throw new Error(\"invalid selector\")}select_one(e){const t=this.select(e);switch(t.length){case 0:return null;case 1:return t[0];default:throw new Error(\"found more than one object matching given selector\")}}}s.Model=h,a=h,h.__name__=\"Model\",a.define((({Any:e,Unknown:t,Boolean:s,String:n,Array:c,Dict:a,Nullable:i})=>({tags:[c(t),[]],name:[i(n),null],js_property_callbacks:[a(c(e)),{}],js_event_callbacks:[a(c(e)),{}],subscribed_events:[c(n),[]],syncable:[s,!0]})))},\n", - " function _(e,t,s,a,r){var c,n;a();const _=e(12),o=e(53),i=e(55),l=e(59),u=e(61),g=e(62),h=e(57),p=e(63),m=e(67);class x{constructor(e,t){this.x_scale=e,this.y_scale=t,this.x_source=this.x_scale.source_range,this.y_source=this.y_scale.source_range,this.ranges=[this.x_source,this.y_source],this.scales=[this.x_scale,this.y_scale]}map_to_screen(e,t){return[this.x_scale.v_compute(e),this.y_scale.v_compute(t)]}map_from_screen(e,t){return[this.x_scale.v_invert(e),this.y_scale.v_invert(t)]}}s.CoordinateTransform=x,x.__name__=\"CoordinateTransform\";class y extends o.Model{constructor(e){super(e)}get x_ranges(){return new Map([[\"default\",this.x_source]])}get y_ranges(){return new Map([[\"default\",this.y_source]])}_get_scale(e,t,s){if(e instanceof m.FactorRange!=t instanceof g.CategoricalScale)throw new Error(`Range ${e.type} is incompatible is Scale ${t.type}`);t instanceof u.LogScale&&e instanceof p.DataRange1d&&(e.scale_hint=\"log\");const a=t.clone();return a.setv({source_range:e,target_range:s}),a}get_transform(e){const{x_source:t,x_scale:s,x_target:a}=this,r=this._get_scale(t,s,a),{y_source:c,y_scale:n,y_target:_}=this,o=this._get_scale(c,n,_),i=new v({source_scale:r,source_range:r.source_range,target_scale:e.x_scale,target_range:e.x_target}),l=new v({source_scale:o,source_range:o.source_range,target_scale:e.y_scale,target_range:e.y_target});return new x(i,l)}}s.CoordinateMapping=y,c=y,y.__name__=\"CoordinateMapping\",c.define((({Ref:e})=>({x_source:[e(h.Range),()=>new p.DataRange1d],y_source:[e(h.Range),()=>new p.DataRange1d],x_scale:[e(i.Scale),()=>new l.LinearScale],y_scale:[e(i.Scale),()=>new l.LinearScale],x_target:[e(h.Range)],y_target:[e(h.Range)]})));class v extends i.Scale{constructor(e){super(e)}get s_compute(){const e=this.source_scale.s_compute,t=this.target_scale.s_compute;return s=>t(e(s))}get s_invert(){const e=this.source_scale.s_invert,t=this.target_scale.s_invert;return s=>e(t(s))}compute(e){return this.s_compute(e)}v_compute(e){const{s_compute:t}=this;return(0,_.map)(e,t)}invert(e){return this.s_invert(e)}v_invert(e){const{s_invert:t}=this;return(0,_.map)(e,t)}}s.CompositeScale=v,n=v,v.__name__=\"CompositeScale\",n.internal((({Ref:e})=>({source_scale:[e(i.Scale)],target_scale:[e(i.Scale)]})))},\n", - " function _(e,t,r,n,s){var _;n();const a=e(56),c=e(57),o=e(58),i=e(24);class u extends a.Transform{constructor(e){super(e)}compute(e){return this.s_compute(e)}v_compute(e){const t=new i.ScreenArray(e.length),{s_compute:r}=this;for(let n=0;n({source_range:[e(c.Range)],target_range:[e(o.Range1d)]})))},\n", - " function _(n,s,o,r,c){r();const e=n(53);class t extends e.Model{constructor(n){super(n)}}o.Transform=t,t.__name__=\"Transform\"},\n", - " function _(e,t,n,i,s){var r;i();const a=e(53);class l extends a.Model{constructor(e){super(e),this.have_updated_interactively=!1}get is_reversed(){return this.start>this.end}get is_valid(){return isFinite(this.min)&&isFinite(this.max)}get span(){return Math.abs(this.end-this.start)}}n.Range=l,r=l,l.__name__=\"Range\",r.define((({Number:e,Tuple:t,Or:n,Auto:i,Nullable:s})=>({bounds:[s(n(t(s(e),s(e)),i)),null],min_interval:[s(e),null],max_interval:[s(e),null]}))),r.internal((({Array:e,AnyRef:t})=>({plots:[e(t()),[]]})))},\n", - " function _(t,e,s,n,r){var a;n();const i=t(57);class _ extends i.Range{constructor(t){super(t)}_set_auto_bounds(){if(\"auto\"==this.bounds){const t=Math.min(this._reset_start,this._reset_end),e=Math.max(this._reset_start,this._reset_end);this.setv({bounds:[t,e]},{silent:!0})}}initialize(){super.initialize(),this._set_auto_bounds()}get min(){return Math.min(this.start,this.end)}get max(){return Math.max(this.start,this.end)}reset(){this._set_auto_bounds();const{_reset_start:t,_reset_end:e}=this;this.start!=t||this.end!=e?this.setv({start:t,end:e}):this.change.emit()}map(t){return new _({start:t(this.start),end:t(this.end)})}widen(t){let{start:e,end:s}=this;return this.is_reversed?(e+=t,s-=t):(e-=t,s+=t),new _({start:e,end:s})}}s.Range1d=_,a=_,_.__name__=\"Range1d\",a.define((({Number:t,Nullable:e})=>({start:[t,0],end:[t,1],reset_start:[e(t),null,{on_update(t,e){e._reset_start=null!=t?t:e.start}}],reset_end:[e(t),null,{on_update(t,e){e._reset_end=null!=t?t:e.end}}]})))},\n", - " function _(t,e,n,r,s){r();const a=t(60);class _ extends a.ContinuousScale{constructor(t){super(t)}get s_compute(){const[t,e]=this._linear_compute_state();return n=>t*n+e}get s_invert(){const[t,e]=this._linear_compute_state();return n=>(n-e)/t}_linear_compute_state(){const t=this.source_range.start,e=this.source_range.end,n=this.target_range.start,r=(this.target_range.end-n)/(e-t);return[r,-r*t+n]}}n.LinearScale=_,_.__name__=\"LinearScale\"},\n", - " function _(n,c,o,s,e){s();const t=n(55);class u extends t.Scale{constructor(n){super(n)}}o.ContinuousScale=u,u.__name__=\"ContinuousScale\"},\n", - " function _(t,e,a,o,s){o();const r=t(60);class n extends r.ContinuousScale{constructor(t){super(t)}get s_compute(){const[t,e,a,o]=this._compute_state();return s=>{if(0==a)return 0;{const r=(Math.log(s)-o)/a;return isFinite(r)?r*t+e:NaN}}}get s_invert(){const[t,e,a,o]=this._compute_state();return s=>{const r=(s-e)/t;return Math.exp(a*r+o)}}_get_safe_factor(t,e){let a=t<0?0:t,o=e<0?0:e;if(a==o)if(0==a)[a,o]=[1,10];else{const t=Math.log(a)/Math.log(10);a=10**Math.floor(t),o=Math.ceil(t)!=Math.floor(t)?10**Math.ceil(t):10**(Math.ceil(t)+1)}return[a,o]}_compute_state(){const t=this.source_range.start,e=this.source_range.end,a=this.target_range.start,o=this.target_range.end-a,[s,r]=this._get_safe_factor(t,e);let n,c;0==s?(n=Math.log(r),c=0):(n=Math.log(r)-Math.log(s),c=Math.log(s));return[o,a,n,c]}}a.LogScale=n,n.__name__=\"LogScale\"},\n", - " function _(t,e,c,a,s){a();const n=t(55),r=t(59),{_linear_compute_state:o}=r.LinearScale.prototype;class l extends n.Scale{constructor(t){super(t)}get s_compute(){const[t,e]=o.call(this),c=this.source_range;return a=>t*c.synthetic(a)+e}get s_invert(){const[t,e]=o.call(this);return c=>(c-e)/t}}c.CategoricalScale=l,l.__name__=\"CategoricalScale\"},\n", - " function _(t,i,n,e,a){e();const s=t(1);var l;const _=t(64),o=t(20),r=t(9),h=t(19),d=(0,s.__importStar)(t(65)),u=t(66);class g extends _.DataRange{constructor(t){super(t),this.have_updated_interactively=!1}initialize(){super.initialize(),this._initial_start=this.start,this._initial_end=this.end,this._initial_range_padding=this.range_padding,this._initial_range_padding_units=this.range_padding_units,this._initial_follow=this.follow,this._initial_follow_interval=this.follow_interval,this._initial_default_span=this.default_span,this._plot_bounds=new Map}get min(){return Math.min(this.start,this.end)}get max(){return Math.max(this.start,this.end)}computed_renderers(){const{renderers:t,names:i}=this,n=(0,r.concat)(this.plots.map((t=>t.data_renderers)));return(0,u.compute_renderers)(0==t.length?\"auto\":t,n,i)}_compute_plot_bounds(t,i){let n=d.empty();for(const e of t){const t=i.get(e);null==t||!e.visible&&this.only_visible||(n=d.union(n,t))}return n}adjust_bounds_for_aspect(t,i){const n=d.empty();let e=t.x1-t.x0;e<=0&&(e=1);let a=t.y1-t.y0;a<=0&&(a=1);const s=.5*(t.x1+t.x0),l=.5*(t.y1+t.y0);return el&&(\"start\"==this.follow?a=e+s*l:\"end\"==this.follow&&(e=a-s*l)),[e,a]}update(t,i,n,e){if(this.have_updated_interactively)return;const a=this.computed_renderers();let s=this._compute_plot_bounds(a,t);null!=e&&(s=this.adjust_bounds_for_aspect(s,e)),this._plot_bounds.set(n,s);const[l,_]=this._compute_min_max(this._plot_bounds.entries(),i);let[o,r]=this._compute_range(l,_);null!=this._initial_start&&(\"log\"==this.scale_hint?this._initial_start>0&&(o=this._initial_start):o=this._initial_start),null!=this._initial_end&&(\"log\"==this.scale_hint?this._initial_end>0&&(r=this._initial_end):r=this._initial_end);let h=!1;\"auto\"==this.bounds&&(this.setv({bounds:[o,r]},{silent:!0}),h=!0);const[d,u]=[this.start,this.end];if(o!=d||r!=u){const t={};o!=d&&(t.start=o),r!=u&&(t.end=r),this.setv(t),h=!1}h&&this.change.emit()}reset(){this.have_updated_interactively=!1,this.setv({range_padding:this._initial_range_padding,range_padding_units:this._initial_range_padding_units,follow:this._initial_follow,follow_interval:this._initial_follow_interval,default_span:this._initial_default_span},{silent:!0}),this.change.emit()}}n.DataRange1d=g,l=g,g.__name__=\"DataRange1d\",l.define((({Boolean:t,Number:i,Nullable:n})=>({start:[i],end:[i],range_padding:[i,.1],range_padding_units:[o.PaddingUnits,\"percent\"],flipped:[t,!1],follow:[n(o.StartEnd),null],follow_interval:[n(i),null],default_span:[i,2],only_visible:[t,!1]}))),l.internal((({Enum:t})=>({scale_hint:[t(\"log\",\"auto\"),\"auto\"]})))},\n", - " function _(e,n,a,r,s){var t;r();const c=e(57);class _ extends c.Range{constructor(e){super(e)}}a.DataRange=_,t=_,_.__name__=\"DataRange\",t.define((({String:e,Array:n,AnyRef:a})=>({names:[n(e),[]],renderers:[n(a()),[]]})))},\n", - " function _(t,i,e,h,r){h();const s=t(24),n=t(26),{min:x,max:y}=Math;e.empty=function(){return{x0:1/0,y0:1/0,x1:-1/0,y1:-1/0}},e.positive_x=function(){return{x0:Number.MIN_VALUE,y0:-1/0,x1:1/0,y1:1/0}},e.positive_y=function(){return{x0:-1/0,y0:Number.MIN_VALUE,x1:1/0,y1:1/0}},e.union=function(t,i){return{x0:x(t.x0,i.x0),x1:y(t.x1,i.x1),y0:x(t.y0,i.y0),y1:y(t.y1,i.y1)}};class o{constructor(t){if(null==t)this.x0=0,this.y0=0,this.x1=0,this.y1=0;else if(\"x0\"in t){const{x0:i,y0:e,x1:h,y1:r}=t;if(!(i<=h&&e<=r))throw new Error(`invalid bbox {x0: ${i}, y0: ${e}, x1: ${h}, y1: ${r}}`);this.x0=i,this.y0=e,this.x1=h,this.y1=r}else if(\"x\"in t){const{x:i,y:e,width:h,height:r}=t;if(!(h>=0&&r>=0))throw new Error(`invalid bbox {x: ${i}, y: ${e}, width: ${h}, height: ${r}}`);this.x0=i,this.y0=e,this.x1=i+h,this.y1=e+r}else{let i,e,h,r;if(\"width\"in t)if(\"left\"in t)i=t.left,e=i+t.width;else if(\"right\"in t)e=t.right,i=e-t.width;else{const h=t.width/2;i=t.hcenter-h,e=t.hcenter+h}else i=t.left,e=t.right;if(\"height\"in t)if(\"top\"in t)h=t.top,r=h+t.height;else if(\"bottom\"in t)r=t.bottom,h=r-t.height;else{const i=t.height/2;h=t.vcenter-i,r=t.vcenter+i}else h=t.top,r=t.bottom;if(!(i<=e&&h<=r))throw new Error(`invalid bbox {left: ${i}, top: ${h}, right: ${e}, bottom: ${r}}`);this.x0=i,this.y0=h,this.x1=e,this.y1=r}}static from_rect({left:t,right:i,top:e,bottom:h}){return new o({x0:Math.min(t,i),y0:Math.min(e,h),x1:Math.max(t,i),y1:Math.max(e,h)})}equals(t){return this.x0==t.x0&&this.y0==t.y0&&this.x1==t.x1&&this.y1==t.y1}[n.equals](t,i){return i.eq(this.x0,t.x0)&&i.eq(this.y0,t.y0)&&i.eq(this.x1,t.x1)&&i.eq(this.y1,t.y1)}toString(){return`BBox({left: ${this.left}, top: ${this.top}, width: ${this.width}, height: ${this.height}})`}get left(){return this.x0}get top(){return this.y0}get right(){return this.x1}get bottom(){return this.y1}get p0(){return[this.x0,this.y0]}get p1(){return[this.x1,this.y1]}get x(){return this.x0}get y(){return this.y0}get width(){return this.x1-this.x0}get height(){return this.y1-this.y0}get size(){return{width:this.width,height:this.height}}get rect(){const{x0:t,y0:i,x1:e,y1:h}=this;return{p0:{x:t,y:i},p1:{x:e,y:i},p2:{x:e,y:h},p3:{x:t,y:h}}}get box(){const{x:t,y:i,width:e,height:h}=this;return{x:t,y:i,width:e,height:h}}get h_range(){return{start:this.x0,end:this.x1}}get v_range(){return{start:this.y0,end:this.y1}}get ranges(){return[this.h_range,this.v_range]}get aspect(){return this.width/this.height}get hcenter(){return(this.left+this.right)/2}get vcenter(){return(this.top+this.bottom)/2}get area(){return this.width*this.height}relative(){const{width:t,height:i}=this;return new o({x:0,y:0,width:t,height:i})}translate(t,i){const{x:e,y:h,width:r,height:s}=this;return new o({x:t+e,y:i+h,width:r,height:s})}relativize(t,i){return[t-this.x,i-this.y]}contains(t,i){return this.x0<=t&&t<=this.x1&&this.y0<=i&&i<=this.y1}clip(t,i){return tthis.x1&&(t=this.x1),ithis.y1&&(i=this.y1),[t,i]}grow_by(t){return new o({left:this.left-t,right:this.right+t,top:this.top-t,bottom:this.bottom+t})}shrink_by(t){return new o({left:this.left+t,right:this.right-t,top:this.top+t,bottom:this.bottom-t})}union(t){return new o({x0:x(this.x0,t.x0),y0:x(this.y0,t.y0),x1:y(this.x1,t.x1),y1:y(this.y1,t.y1)})}intersection(t){return this.intersects(t)?new o({x0:y(this.x0,t.x0),y0:y(this.y0,t.y0),x1:x(this.x1,t.x1),y1:x(this.y1,t.y1)}):null}intersects(t){return!(t.x1this.x1||t.y1this.y1)}get xview(){return{compute:t=>this.left+t,v_compute:t=>{const i=new s.ScreenArray(t.length),e=this.left;for(let h=0;hthis.bottom-t,v_compute:t=>{const i=new s.ScreenArray(t.length),e=this.bottom;for(let h=0;h0&&(r=r.filter((n=>(0,l.includes)(t,n.name)))),r}},\n", - " function _(t,n,e,i,s){var r;i();const a=t(57),o=t(20),g=t(21),p=t(24),c=t(9),l=t(8),u=t(11);function h(t,n,e=0){const i=new Map;for(let s=0;sa.get(t).value)));r.set(t,{value:l/s,mapping:a}),o+=s+n+p}return[r,(a.size-1)*n+g]}function _(t,n,e,i,s=0){var r;const a=new Map,o=new Map;for(const[n,e,i]of t){const t=null!==(r=o.get(n))&&void 0!==r?r:[];o.set(n,[...t,[e,i]])}let g=s,p=0;for(const[t,s]of o){const r=s.length,[o,l]=d(s,e,i,g);p+=l;const u=(0,c.sum)(s.map((([t])=>o.get(t).value)));a.set(t,{value:u/r,mapping:o}),g+=r+n+l}return[a,(o.size-1)*n+p]}e.Factor=(0,g.Or)(g.String,(0,g.Tuple)(g.String,g.String),(0,g.Tuple)(g.String,g.String,g.String)),e.FactorSeq=(0,g.Or)((0,g.Array)(g.String),(0,g.Array)((0,g.Tuple)(g.String,g.String)),(0,g.Array)((0,g.Tuple)(g.String,g.String,g.String))),e.map_one_level=h,e.map_two_levels=d,e.map_three_levels=_;class f extends a.Range{constructor(t){super(t)}get min(){return this.start}get max(){return this.end}initialize(){super.initialize(),this._init(!0)}connect_signals(){super.connect_signals(),this.connect(this.properties.factors.change,(()=>this.reset())),this.connect(this.properties.factor_padding.change,(()=>this.reset())),this.connect(this.properties.group_padding.change,(()=>this.reset())),this.connect(this.properties.subgroup_padding.change,(()=>this.reset())),this.connect(this.properties.range_padding.change,(()=>this.reset())),this.connect(this.properties.range_padding_units.change,(()=>this.reset()))}reset(){this._init(!1),this.change.emit()}_lookup(t){switch(t.length){case 1:{const[n]=t,e=this._mapping.get(n);return null!=e?e.value:NaN}case 2:{const[n,e]=t,i=this._mapping.get(n);if(null!=i){const t=i.mapping.get(e);if(null!=t)return t.value}return NaN}case 3:{const[n,e,i]=t,s=this._mapping.get(n);if(null!=s){const t=s.mapping.get(e);if(null!=t){const n=t.mapping.get(i);if(null!=n)return n.value}}return NaN}default:(0,u.unreachable)()}}synthetic(t){if((0,l.isNumber)(t))return t;if((0,l.isString)(t))return this._lookup([t]);let n=0;const e=t[t.length-1];return(0,l.isNumber)(e)&&(n=e,t=t.slice(0,-1)),this._lookup(t)+n}v_synthetic(t){const n=t.length,e=new p.ScreenArray(n);for(let i=0;i{if((0,c.every)(this.factors,l.isString)){const t=this.factors,[n,e]=h(t,this.factor_padding);return{levels:1,mapping:n,tops:null,mids:null,inside_padding:e}}if((0,c.every)(this.factors,(t=>(0,l.isArray)(t)&&2==t.length&&(0,l.isString)(t[0])&&(0,l.isString)(t[1])))){const t=this.factors,[n,e]=d(t,this.group_padding,this.factor_padding),i=[...n.keys()];return{levels:2,mapping:n,tops:i,mids:null,inside_padding:e}}if((0,c.every)(this.factors,(t=>(0,l.isArray)(t)&&3==t.length&&(0,l.isString)(t[0])&&(0,l.isString)(t[1])&&(0,l.isString)(t[2])))){const t=this.factors,[n,e]=_(t,this.group_padding,this.subgroup_padding,this.factor_padding),i=[...n.keys()],s=[];for(const[t,e]of n)for(const n of e.mapping.keys())s.push([t,n]);return{levels:3,mapping:n,tops:i,mids:s,inside_padding:e}}(0,u.unreachable)()})();this._mapping=e,this.tops=i,this.mids=s;let a=0,o=this.factors.length+r;if(\"percent\"==this.range_padding_units){const t=(o-a)*this.range_padding/2;a-=t,o+=t}else a-=this.range_padding,o+=this.range_padding;this.setv({start:a,end:o,levels:n},{silent:t}),\"auto\"==this.bounds&&this.setv({bounds:[a,o]},{silent:!0})}}e.FactorRange=f,r=f,f.__name__=\"FactorRange\",r.define((({Number:t})=>({factors:[e.FactorSeq,[]],factor_padding:[t,0],subgroup_padding:[t,.8],group_padding:[t,1.4],range_padding:[t,0],range_padding_units:[o.PaddingUnits,\"percent\"],start:[t],end:[t]}))),r.internal((({Number:t,String:n,Array:e,Tuple:i,Nullable:s})=>({levels:[t],mids:[s(e(i(n,n))),null],tops:[s(e(n)),null]})))},\n", - " function _(t,e,s,a,i){a();const n=t(1);var _;const r=t(69),o=t(112),l=t(48),d=t(20),h=t(24),c=t(113),u=(0,n.__importStar)(t(18)),v=t(10);class p extends r.DataAnnotationView{async lazy_initialize(){await super.lazy_initialize();const{start:t,end:e}=this.model;null!=t&&(this.start=await(0,c.build_view)(t,{parent:this})),null!=e&&(this.end=await(0,c.build_view)(e,{parent:this}))}set_data(t){var e,s;super.set_data(t),null===(e=this.start)||void 0===e||e.set_data(t),null===(s=this.end)||void 0===s||s.set_data(t)}remove(){var t,e;null===(t=this.start)||void 0===t||t.remove(),null===(e=this.end)||void 0===e||e.remove(),super.remove()}map_data(){const{frame:t}=this.plot_view;\"data\"==this.model.start_units?(this._sx_start=this.coordinates.x_scale.v_compute(this._x_start),this._sy_start=this.coordinates.y_scale.v_compute(this._y_start)):(this._sx_start=t.bbox.xview.v_compute(this._x_start),this._sy_start=t.bbox.yview.v_compute(this._y_start)),\"data\"==this.model.end_units?(this._sx_end=this.coordinates.x_scale.v_compute(this._x_end),this._sy_end=this.coordinates.y_scale.v_compute(this._y_end)):(this._sx_end=t.bbox.xview.v_compute(this._x_end),this._sy_end=t.bbox.yview.v_compute(this._y_end));const{_sx_start:e,_sy_start:s,_sx_end:a,_sy_end:i}=this,n=e.length,_=this._angles=new h.ScreenArray(n);for(let t=0;t({x_start:[u.XCoordinateSpec,{field:\"x_start\"}],y_start:[u.YCoordinateSpec,{field:\"y_start\"}],start_units:[d.SpatialUnits,\"data\"],start:[e(t(o.ArrowHead)),null],x_end:[u.XCoordinateSpec,{field:\"x_end\"}],y_end:[u.YCoordinateSpec,{field:\"y_end\"}],end_units:[d.SpatialUnits,\"data\"],end:[e(t(o.ArrowHead)),()=>new o.OpenHead]})))},\n", - " function _(t,e,n,s,a){s();const o=t(1);var i;const c=t(40),r=t(70),_=t(75),l=t(78),h=(0,o.__importStar)(t(18));class d extends c.AnnotationView{constructor(){super(...arguments),this._initial_set_data=!1}connect_signals(){super.connect_signals();const t=()=>{this.set_data(this.model.source),this._rerender()};this.connect(this.model.change,t),this.connect(this.model.source.streaming,t),this.connect(this.model.source.patching,t),this.connect(this.model.source.change,t)}_rerender(){this.request_render()}set_data(t){const e=this;for(const n of this.model)if(n instanceof h.VectorSpec||n instanceof h.ScalarSpec)if(n instanceof h.BaseCoordinateSpec){const s=n.array(t);e[`_${n.attr}`]=s}else{const s=n.uniform(t);e[`${n.attr}`]=s}this.plot_model.use_map&&(null!=e._x&&l.inplace.project_xy(e._x,e._y),null!=e._xs&&l.inplace.project_xsys(e._xs,e._ys));for(const t of this.visuals)t.update()}_render(){this._initial_set_data||(this.set_data(this.model.source),this._initial_set_data=!0),this.map_data(),this.paint(this.layer.ctx)}}n.DataAnnotationView=d,d.__name__=\"DataAnnotationView\";class u extends c.Annotation{constructor(t){super(t)}}n.DataAnnotation=u,i=u,u.__name__=\"DataAnnotation\",i.define((({Ref:t})=>({source:[t(r.ColumnarDataSource),()=>new _.ColumnDataSource]})))},\n", - " function _(t,e,n,s,a){var i;s();const r=t(71),l=t(15),c=t(19),o=t(73),h=t(8),u=t(9),g=t(13),d=t(72),_=t(74),m=t(29);class w extends r.DataSource{constructor(t){super(t),this.selection_manager=new o.SelectionManager(this)}get_array(t){let e=this.data[t];return null==e?this.data[t]=e=[]:(0,h.isArray)(e)||(this.data[t]=e=Array.from(e)),e}initialize(){super.initialize(),this._select=new l.Signal0(this,\"select\"),this.inspect=new l.Signal(this,\"inspect\"),this.streaming=new l.Signal0(this,\"streaming\"),this.patching=new l.Signal(this,\"patching\")}get_column(t){const e=this.data[t];return null!=e?e:null}columns(){return(0,g.keys)(this.data)}get_length(t=!0){const e=(0,u.uniq)((0,g.values)(this.data).map((t=>(0,m.is_NDArray)(t)?t.shape[0]:t.length)));switch(e.length){case 0:return null;case 1:return e[0];default:{const n=\"data source has columns of inconsistent lengths\";if(t)return c.logger.warn(n),e.sort()[0];throw new Error(n)}}}get length(){var t;return null!==(t=this.get_length())&&void 0!==t?t:0}clear(){const t={};for(const e of this.columns())t[e]=new this.data[e].constructor(0);this.data=t}}n.ColumnarDataSource=w,i=w,w.__name__=\"ColumnarDataSource\",i.define((({Ref:t})=>({selection_policy:[t(_.SelectionPolicy),()=>new _.UnionRenderers]}))),i.internal((({AnyRef:t})=>({inspected:[t(),()=>new d.Selection]})))},\n", - " function _(e,c,n,t,o){var a;t();const s=e(53),r=e(72);class l extends s.Model{constructor(e){super(e)}}n.DataSource=l,a=l,l.__name__=\"DataSource\",a.define((({Ref:e})=>({selected:[e(r.Selection),()=>new r.Selection]})))},\n", - " function _(i,e,s,t,n){var l;t();const c=i(53),d=i(9),h=i(13);class _ extends c.Model{constructor(i){super(i)}get_view(){return this.view}get selected_glyph(){return this.selected_glyphs.length>0?this.selected_glyphs[0]:null}add_to_selected_glyphs(i){this.selected_glyphs.push(i)}update(i,e=!0,s=\"replace\"){switch(s){case\"replace\":this.indices=i.indices,this.line_indices=i.line_indices,this.multiline_indices=i.multiline_indices,this.image_indices=i.image_indices,this.view=i.view,this.selected_glyphs=i.selected_glyphs;break;case\"append\":this.update_through_union(i);break;case\"intersect\":this.update_through_intersection(i);break;case\"subtract\":this.update_through_subtraction(i)}}clear(){this.indices=[],this.line_indices=[],this.multiline_indices={},this.image_indices=[],this.view=null,this.selected_glyphs=[]}map(i){return new _(Object.assign(Object.assign({},this.attributes),{indices:this.indices.map(i),multiline_indices:(0,h.to_object)((0,h.entries)(this.multiline_indices).map((([e,s])=>[i(Number(e)),s]))),image_indices:this.image_indices.map((e=>Object.assign(Object.assign({},e),{index:i(e.index)})))}))}is_empty(){return 0==this.indices.length&&0==this.line_indices.length&&0==this.image_indices.length}update_through_union(i){this.indices=(0,d.union)(this.indices,i.indices),this.selected_glyphs=(0,d.union)(i.selected_glyphs,this.selected_glyphs),this.line_indices=(0,d.union)(i.line_indices,this.line_indices),this.view=i.view,this.multiline_indices=(0,h.merge)(i.multiline_indices,this.multiline_indices)}update_through_intersection(i){this.indices=(0,d.intersection)(this.indices,i.indices),this.selected_glyphs=(0,d.union)(i.selected_glyphs,this.selected_glyphs),this.line_indices=(0,d.union)(i.line_indices,this.line_indices),this.view=i.view,this.multiline_indices=(0,h.merge)(i.multiline_indices,this.multiline_indices)}update_through_subtraction(i){this.indices=(0,d.difference)(this.indices,i.indices),this.selected_glyphs=(0,d.union)(i.selected_glyphs,this.selected_glyphs),this.line_indices=(0,d.union)(i.line_indices,this.line_indices),this.view=i.view,this.multiline_indices=(0,h.merge)(i.multiline_indices,this.multiline_indices)}}s.Selection=_,l=_,_.__name__=\"Selection\",l.define((({Int:i,Array:e,Dict:s})=>({indices:[e(i),[]],line_indices:[e(i),[]],multiline_indices:[s(e(i)),{}]}))),l.internal((({Int:i,Array:e,AnyRef:s,Struct:t,Nullable:n})=>({selected_glyphs:[e(s()),[]],view:[n(s()),null],image_indices:[e(t({index:i,dim1:i,dim2:i,flat_index:i})),[]]})))},\n", - " function _(e,t,o,s,c){s();const n=e(72);function i(e){return\"GlyphRenderer\"==e.model.type}function l(e){return\"GraphRenderer\"==e.model.type}class r{constructor(e){this.source=e,this.inspectors=new Map}select(e,t,o,s=\"replace\"){const c=[],n=[];for(const t of e)i(t)?c.push(t):l(t)&&n.push(t);let r=!1;for(const e of n){const c=e.model.selection_policy.hit_test(t,e);r=r||e.model.selection_policy.do_selection(c,e.model,o,s)}if(c.length>0){const e=this.source.selection_policy.hit_test(t,c);r=r||this.source.selection_policy.do_selection(e,this.source,o,s)}return r}inspect(e,t){let o=!1;if(i(e)){const s=e.hit_test(t);if(null!=s){o=!s.is_empty();const c=this.get_or_create_inspector(e.model);c.update(s,!0,\"replace\"),this.source.setv({inspected:c},{silent:!0}),this.source.inspect.emit([e.model,{geometry:t}])}}else if(l(e)){const s=e.model.inspection_policy.hit_test(t,e);o=o||e.model.inspection_policy.do_inspection(s,t,e,!1,\"replace\")}return o}clear(e){this.source.selected.clear(),null!=e&&this.get_or_create_inspector(e.model).clear()}get_or_create_inspector(e){let t=this.inspectors.get(e);return null==t&&(t=new n.Selection,this.inspectors.set(e,t)),t}}o.SelectionManager=r,r.__name__=\"SelectionManager\"},\n", - " function _(e,t,n,s,o){s();const r=e(53);class c extends r.Model{do_selection(e,t,n,s){return null!=e&&(t.selected.update(e,n,s),t._select.emit(),!t.selected.is_empty())}}n.SelectionPolicy=c,c.__name__=\"SelectionPolicy\";class l extends c{hit_test(e,t){const n=[];for(const s of t){const t=s.hit_test(e);null!=t&&n.push(t)}if(n.length>0){const e=n[0];for(const t of n)e.update_through_intersection(t);return e}return null}}n.IntersectRenderers=l,l.__name__=\"IntersectRenderers\";class _ extends c{hit_test(e,t){const n=[];for(const s of t){const t=s.hit_test(e);null!=t&&n.push(t)}if(n.length>0){const e=n[0];for(const t of n)e.update_through_union(t);return e}return null}}n.UnionRenderers=_,_.__name__=\"UnionRenderers\"},\n", - " function _(t,n,e,s,o){s();const r=t(1);var l;const c=t(70),i=t(8),a=t(13),u=(0,r.__importStar)(t(76)),h=t(77),d=t(35);function f(t,n,e){if((0,i.isArray)(t)){const s=t.concat(n);return null!=e&&s.length>e?s.slice(-e):s}if((0,i.isTypedArray)(t)){const s=t.length+n.length;if(null!=e&&s>e){const o=s-e,r=t.length;let l;t.length({data:[t(n),{}]})))},\n", - " function _(t,n,o,e,c){e(),o.concat=function(t,...n){let o=t.length;for(const t of n)o+=t.length;const e=new t.constructor(o);e.set(t,0);let c=t.length;for(const t of n)e.set(t,c),c+=t.length;return e}},\n", - " function _(n,o,t,e,f){function c(...n){const o=new Set;for(const t of n)for(const n of t)o.add(n);return o}e(),t.union=c,t.intersection=function(n,...o){const t=new Set;n:for(const e of n){for(const n of o)if(!n.has(e))continue n;t.add(e)}return t},t.difference=function(n,...o){const t=new Set(n);for(const n of c(...o))t.delete(n);return t}},\n", - " function _(n,t,e,o,r){o();const c=n(1),l=(0,c.__importDefault)(n(79)),i=(0,c.__importDefault)(n(80)),u=n(24),a=new i.default(\"GOOGLE\"),s=new i.default(\"WGS84\"),f=(0,l.default)(s,a);e.wgs84_mercator={compute:(n,t)=>isFinite(n)&&isFinite(t)?f.forward([n,t]):[NaN,NaN],invert:(n,t)=>isFinite(n)&&isFinite(t)?f.inverse([n,t]):[NaN,NaN]};const _={lon:[-20026376.39,20026376.39],lat:[-20048966.1,20048966.1]},p={lon:[-180,180],lat:[-85.06,85.06]},{min:g,max:h}=Math;function m(n,t){const o=g(n.length,t.length),r=(0,u.infer_type)(n,t),c=new r(o),l=new r(o);return e.inplace.project_xy(n,t,c,l),[c,l]}e.clip_mercator=function(n,t,e){const[o,r]=_[e];return[h(n,o),g(t,r)]},e.in_bounds=function(n,t){const[e,o]=p[t];return e2?void 0!==e.name&&\"geocent\"===e.name||void 0!==n.name&&\"geocent\"===n.name?\"number\"==typeof o.z?[o.x,o.y,o.z].concat(t.splice(3)):[o.x,o.y,t[2]].concat(t.splice(3)):[o.x,o.y].concat(t.splice(2)):[o.x,o.y]):(a=(0,c.default)(e,n,t,r),2===(i=Object.keys(t)).length||i.forEach((function(r){if(void 0!==e.name&&\"geocent\"===e.name||void 0!==n.name&&\"geocent\"===n.name){if(\"x\"===r||\"y\"===r||\"z\"===r)return}else if(\"x\"===r||\"y\"===r)return;a[r]=t[r]})),a)}function l(e){return e instanceof i.default?e:e.oProj?e.oProj:(0,i.default)(e)}t.default=function(e,n,t){e=l(e);var r,o=!1;return void 0===n?(n=e,e=u,o=!0):(void 0!==n.x||Array.isArray(n))&&(t=n,n=e,e=u,o=!0),n=l(n),t?f(e,n,t):(r={forward:function(t,r){return f(e,n,t,r)},inverse:function(t,r){return f(n,e,t,r)}},o&&(r.oProj=n),r)}},\n", - " function _(t,e,a,s,i){s();const l=t(1),u=(0,l.__importDefault)(t(81)),r=(0,l.__importDefault)(t(92)),d=(0,l.__importDefault)(t(93)),o=t(101),f=(0,l.__importDefault)(t(103)),p=(0,l.__importDefault)(t(104)),m=(0,l.__importDefault)(t(88)),n=t(105);function h(t,e){if(!(this instanceof h))return new h(t);e=e||function(t){if(t)throw t};var a=(0,u.default)(t);if(\"object\"==typeof a){var s=h.projections.get(a.projName);if(s){if(a.datumCode&&\"none\"!==a.datumCode){var i=(0,m.default)(f.default,a.datumCode);i&&(a.datum_params=a.datum_params||(i.towgs84?i.towgs84.split(\",\"):null),a.ellps=i.ellipse,a.datumName=i.datumName?i.datumName:a.datumCode)}a.k0=a.k0||1,a.axis=a.axis||\"enu\",a.ellps=a.ellps||\"wgs84\",a.lat1=a.lat1||a.lat0;var l=(0,o.sphere)(a.a,a.b,a.rf,a.ellps,a.sphere),d=(0,o.eccentricity)(l.a,l.b,l.rf,a.R_A),_=(0,n.getNadgrids)(a.nadgrids),c=a.datum||(0,p.default)(a.datumCode,a.datum_params,l.a,l.b,d.es,d.ep2,_);(0,r.default)(this,a),(0,r.default)(this,s),this.a=l.a,this.b=l.b,this.rf=l.rf,this.sphere=l.sphere,this.es=d.es,this.e=d.e,this.ep2=d.ep2,this.datum=c,this.init(),e(null,this)}else e(t)}else e(t)}h.projections=d.default,h.projections.start(),a.default=h},\n", - " function _(t,r,n,u,e){u();const f=t(1),i=(0,f.__importDefault)(t(82)),a=(0,f.__importDefault)(t(89)),o=(0,f.__importDefault)(t(84)),l=(0,f.__importDefault)(t(88));var C=[\"PROJECTEDCRS\",\"PROJCRS\",\"GEOGCS\",\"GEOCCS\",\"PROJCS\",\"LOCAL_CS\",\"GEODCRS\",\"GEODETICCRS\",\"GEODETICDATUM\",\"ENGCRS\",\"ENGINEERINGCRS\"];var d=[\"3857\",\"900913\",\"3785\",\"102113\"];n.default=function(t){if(!function(t){return\"string\"==typeof t}(t))return t;if(function(t){return t in i.default}(t))return i.default[t];if(function(t){return C.some((function(r){return t.indexOf(r)>-1}))}(t)){var r=(0,a.default)(t);if(function(t){var r=(0,l.default)(t,\"authority\");if(r){var n=(0,l.default)(r,\"epsg\");return n&&d.indexOf(n)>-1}}(r))return i.default[\"EPSG:3857\"];var n=function(t){var r=(0,l.default)(t,\"extension\");if(r)return(0,l.default)(r,\"proj4\")}(r);return n?(0,o.default)(n):r}return function(t){return\"+\"===t[0]}(t)?(0,o.default)(t):void 0}},\n", - " function _(t,r,i,e,n){e();const f=t(1),a=(0,f.__importDefault)(t(83)),l=(0,f.__importDefault)(t(84)),u=(0,f.__importDefault)(t(89));function o(t){var r=this;if(2===arguments.length){var i=arguments[1];\"string\"==typeof i?\"+\"===i.charAt(0)?o[t]=(0,l.default)(arguments[1]):o[t]=(0,u.default)(arguments[1]):o[t]=i}else if(1===arguments.length){if(Array.isArray(t))return t.map((function(t){Array.isArray(t)?o.apply(r,t):o(t)}));if(\"string\"==typeof t){if(t in o)return o[t]}else\"EPSG\"in t?o[\"EPSG:\"+t.EPSG]=t:\"ESRI\"in t?o[\"ESRI:\"+t.ESRI]=t:\"IAU2000\"in t?o[\"IAU2000:\"+t.IAU2000]=t:console.log(t);return}}(0,a.default)(o),i.default=o},\n", - " function _(t,l,G,S,e){S(),G.default=function(t){t(\"EPSG:4326\",\"+title=WGS 84 (long/lat) +proj=longlat +ellps=WGS84 +datum=WGS84 +units=degrees\"),t(\"EPSG:4269\",\"+title=NAD83 (long/lat) +proj=longlat +a=6378137.0 +b=6356752.31414036 +ellps=GRS80 +datum=NAD83 +units=degrees\"),t(\"EPSG:3857\",\"+title=WGS 84 / Pseudo-Mercator +proj=merc +a=6378137 +b=6378137 +lat_ts=0.0 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o.push(!0),t[o[0].toLowerCase()]=o[1],t}),{}),c={proj:\"projName\",datum:\"datumCode\",rf:function(t){u.rf=parseFloat(t)},lat_0:function(t){u.lat0=t*r.D2R},lat_1:function(t){u.lat1=t*r.D2R},lat_2:function(t){u.lat2=t*r.D2R},lat_ts:function(t){u.lat_ts=t*r.D2R},lon_0:function(t){u.long0=t*r.D2R},lon_1:function(t){u.long1=t*r.D2R},lon_2:function(t){u.long2=t*r.D2R},alpha:function(t){u.alpha=parseFloat(t)*r.D2R},gamma:function(t){u.rectified_grid_angle=parseFloat(t)},lonc:function(t){u.longc=t*r.D2R},x_0:function(t){u.x0=parseFloat(t)},y_0:function(t){u.y0=parseFloat(t)},k_0:function(t){u.k0=parseFloat(t)},k:function(t){u.k0=parseFloat(t)},a:function(t){u.a=parseFloat(t)},b:function(t){u.b=parseFloat(t)},r_a:function(){u.R_A=!0},zone:function(t){u.zone=parseInt(t,10)},south:function(){u.utmSouth=!0},towgs84:function(t){u.datum_params=t.split(\",\").map((function(t){return parseFloat(t)}))},to_meter:function(t){u.to_meter=parseFloat(t)},units:function(t){u.units=t;var n=(0,l.default)(f.default,t);n&&(u.to_meter=n.to_meter)},from_greenwich:function(t){u.from_greenwich=t*r.D2R},pm:function(t){var n=(0,l.default)(i.default,t);u.from_greenwich=(n||parseFloat(t))*r.D2R},nadgrids:function(t){\"@null\"===t?u.datumCode=\"none\":u.nadgrids=t},axis:function(t){var n=\"ewnsud\";3===t.length&&-1!==n.indexOf(t.substr(0,1))&&-1!==n.indexOf(t.substr(1,1))&&-1!==n.indexOf(t.substr(2,1))&&(u.axis=t)},approx:function(){u.approx=!0}};for(n in e)o=e[n],n in c?\"function\"==typeof(a=c[n])?a(o):u[a]=o:u[n]=o;return\"string\"==typeof u.datumCode&&\"WGS84\"!==u.datumCode&&(u.datumCode=u.datumCode.toLowerCase()),u}},\n", - " function _(S,_,P,R,I){R(),P.PJD_3PARAM=1,P.PJD_7PARAM=2,P.PJD_GRIDSHIFT=3,P.PJD_WGS84=4,P.PJD_NODATUM=5,P.SRS_WGS84_SEMIMAJOR=6378137,P.SRS_WGS84_SEMIMINOR=6356752.314,P.SRS_WGS84_ESQUARED=.0066943799901413165,P.SEC_TO_RAD=484813681109536e-20,P.HALF_PI=Math.PI/2,P.SIXTH=.16666666666666666,P.RA4=.04722222222222222,P.RA6=.022156084656084655,P.EPSLN=1e-10,P.D2R=.017453292519943295,P.R2D=57.29577951308232,P.FORTPI=Math.PI/4,P.TWO_PI=2*Math.PI,P.SPI=3.14159265359},\n", - " function _(o,r,a,e,s){e();var n={};a.default=n,n.greenwich=0,n.lisbon=-9.131906111111,n.paris=2.337229166667,n.bogota=-74.080916666667,n.madrid=-3.687938888889,n.rome=12.452333333333,n.bern=7.439583333333,n.jakarta=106.807719444444,n.ferro=-17.666666666667,n.brussels=4.367975,n.stockholm=18.058277777778,n.athens=23.7163375,n.oslo=10.722916666667},\n", - " function _(t,e,f,o,u){o(),f.default={ft:{to_meter:.3048},\"us-ft\":{to_meter:1200/3937}}},\n", - " function _(e,r,t,a,n){a();var o=/[\\s_\\-\\/\\(\\)]/g;t.default=function(e,r){if(e[r])return e[r];for(var t,a=Object.keys(e),n=r.toLowerCase().replace(o,\"\"),f=-1;++f0?90:-90),e.lat_ts=e.lat1)}(n),n}},\n", - " function _(t,e,r,i,s){i(),r.default=function(t){return new d(t).output()};var h=/\\s/,o=/[A-Za-z]/,n=/[A-Za-z84]/,a=/[,\\]]/,u=/[\\d\\.E\\-\\+]/;function d(t){if(\"string\"!=typeof t)throw new Error(\"not a string\");this.text=t.trim(),this.level=0,this.place=0,this.root=null,this.stack=[],this.currentObject=null,this.state=1}d.prototype.readCharicter=function(){var t=this.text[this.place++];if(4!==this.state)for(;h.test(t);){if(this.place>=this.text.length)return;t=this.text[this.place++]}switch(this.state){case 1:return this.neutral(t);case 2:return this.keyword(t);case 4:return this.quoted(t);case 5:return this.afterquote(t);case 3:return this.number(t);case-1:return}},d.prototype.afterquote=function(t){if('\"'===t)return this.word+='\"',void(this.state=4);if(a.test(t))return this.word=this.word.trim(),void this.afterItem(t);throw new Error(\"havn't handled \\\"\"+t+'\" in afterquote yet, index '+this.place)},d.prototype.afterItem=function(t){return\",\"===t?(null!==this.word&&this.currentObject.push(this.word),this.word=null,void(this.state=1)):\"]\"===t?(this.level--,null!==this.word&&(this.currentObject.push(this.word),this.word=null),this.state=1,this.currentObject=this.stack.pop(),void(this.currentObject||(this.state=-1))):void 0},d.prototype.number=function(t){if(!u.test(t)){if(a.test(t))return this.word=parseFloat(this.word),void this.afterItem(t);throw new Error(\"havn't handled \\\"\"+t+'\" in number yet, index '+this.place)}this.word+=t},d.prototype.quoted=function(t){'\"'!==t?this.word+=t:this.state=5},d.prototype.keyword=function(t){if(n.test(t))this.word+=t;else{if(\"[\"===t){var e=[];return e.push(this.word),this.level++,null===this.root?this.root=e:this.currentObject.push(e),this.stack.push(this.currentObject),this.currentObject=e,void(this.state=1)}if(!a.test(t))throw new Error(\"havn't handled \\\"\"+t+'\" in keyword yet, index '+this.place);this.afterItem(t)}},d.prototype.neutral=function(t){if(o.test(t))return this.word=t,void(this.state=2);if('\"'===t)return this.word=\"\",void(this.state=4);if(u.test(t))return this.word=t,void(this.state=3);if(!a.test(t))throw new Error(\"havn't handled \\\"\"+t+'\" in neutral yet, index '+this.place);this.afterItem(t)},d.prototype.output=function(){for(;this.place90&&a*o.R2D<-90&&h*o.R2D>180&&h*o.R2D<-180)return null;if(Math.abs(Math.abs(a)-o.HALF_PI)<=o.EPSLN)return null;if(this.sphere)i=this.x0+this.a*this.k0*(0,n.default)(h-this.long0),s=this.y0+this.a*this.k0*Math.log(Math.tan(o.FORTPI+.5*a));else{var e=Math.sin(a),r=(0,l.default)(this.e,a,e);i=this.x0+this.a*this.k0*(0,n.default)(h-this.long0),s=this.y0-this.a*this.k0*Math.log(r)}return t.x=i,t.y=s,t}function M(t){var i,s,h=t.x-this.x0,a=t.y-this.y0;if(this.sphere)s=o.HALF_PI-2*Math.atan(Math.exp(-a/(this.a*this.k0)));else{var e=Math.exp(-a/(this.a*this.k0));if(-9999===(s=(0,u.default)(this.e,e)))return null}return i=(0,n.default)(this.long0+h/(this.a*this.k0)),t.x=i,t.y=s,t}s.init=f,s.forward=_,s.inverse=M,s.names=[\"Mercator\",\"Popular Visualisation Pseudo Mercator\",\"Mercator_1SP\",\"Mercator_Auxiliary_Sphere\",\"merc\"],s.default={init:f,forward:_,inverse:M,names:s.names}},\n", - " function _(t,n,r,u,a){u(),r.default=function(t,n,r){var u=t*n;return r/Math.sqrt(1-u*u)}},\n", - " function _(t,n,u,a,f){a();const e=t(1),o=t(85),_=(0,e.__importDefault)(t(97));u.default=function(t){return Math.abs(t)<=o.SPI?t:t-(0,_.default)(t)*o.TWO_PI}},\n", - " function _(n,t,u,f,c){f(),u.default=function(n){return n<0?-1:1}},\n", - " function _(t,n,a,o,u){o();const c=t(85);a.default=function(t,n,a){var o=t*a,u=.5*t;return o=Math.pow((1-o)/(1+o),u),Math.tan(.5*(c.HALF_PI-n))/o}},\n", - " function _(t,a,n,r,f){r();const h=t(85);n.default=function(t,a){for(var n,r,f=.5*t,o=h.HALF_PI-2*Math.atan(a),u=0;u<=15;u++)if(n=t*Math.sin(o),o+=r=h.HALF_PI-2*Math.atan(a*Math.pow((1-n)/(1+n),f))-o,Math.abs(r)<=1e-10)return o;return-9999}},\n", - " function _(n,i,e,t,r){function a(){}function f(n){return n}t(),e.init=a,e.forward=f,e.inverse=f,e.names=[\"longlat\",\"identity\"],e.default={init:a,forward:f,inverse:f,names:e.names}},\n", - " function _(t,r,e,a,n){a();const f=t(1),i=t(85),u=(0,f.__importStar)(t(102)),c=(0,f.__importDefault)(t(88));e.eccentricity=function(t,r,e,a){var n=t*t,f=r*r,u=(n-f)/n,c=0;return a?(n=(t*=1-u*(i.SIXTH+u*(i.RA4+u*i.RA6)))*t,u=0):c=Math.sqrt(u),{es:u,e:c,ep2:(n-f)/f}},e.sphere=function(t,r,e,a,n){if(!t){var f=(0,c.default)(u.default,a);f||(f=u.WGS84),t=f.a,r=f.b,e=f.rf}return e&&!r&&(r=(1-1/e)*t),(0===e||Math.abs(t-r)3&&(0===s.datum_params[3]&&0===s.datum_params[4]&&0===s.datum_params[5]&&0===s.datum_params[6]||(s.datum_type=d.PJD_7PARAM,s.datum_params[3]*=d.SEC_TO_RAD,s.datum_params[4]*=d.SEC_TO_RAD,s.datum_params[5]*=d.SEC_TO_RAD,s.datum_params[6]=s.datum_params[6]/1e6+1))),r&&(s.datum_type=d.PJD_GRIDSHIFT,s.grids=r),s.a=_,s.b=t,s.es=u,s.ep2=p,s}},\n", - " function _(t,e,n,r,i){r();var u={};function l(t){if(0===t.length)return null;var e=\"@\"===t[0];return e&&(t=t.slice(1)),\"null\"===t?{name:\"null\",mandatory:!e,grid:null,isNull:!0}:{name:t,mandatory:!e,grid:u[t]||null,isNull:!1}}function o(t){return t/3600*Math.PI/180}function a(t,e,n){return String.fromCharCode.apply(null,new Uint8Array(t.buffer.slice(e,n)))}function d(t){return t.map((function(t){return[o(t.longitudeShift),o(t.latitudeShift)]}))}function g(t,e,n){return{name:a(t,e+8,e+16).trim(),parent:a(t,e+24,e+24+8).trim(),lowerLatitude:t.getFloat64(e+72,n),upperLatitude:t.getFloat64(e+88,n),lowerLongitude:t.getFloat64(e+104,n),upperLongitude:t.getFloat64(e+120,n),latitudeInterval:t.getFloat64(e+136,n),longitudeInterval:t.getFloat64(e+152,n),gridNodeCount:t.getInt32(e+168,n)}}function s(t,e,n,r){for(var i=e+176,u=[],l=0;l1&&console.log(\"Only single NTv2 subgrids are currently supported, subsequent sub grids are ignored\");var l=function(t,e,n){for(var r=176,i=[],u=0;ua.y||f>a.x||N1e-12&&Math.abs(n.y)>1e-12);if(d<0)return console.log(\"Inverse grid shift iterator failed to converge.\"),a;a.x=(0,u.default)(l.x+t.ll[0]),a.y=l.y+t.ll[1]}else isNaN(l.x)||(a.x=r.x+l.x,a.y=r.y+l.y);return a}function f(r,e){var t,a={x:r.x/e.del[0],y:r.y/e.del[1]},i=Math.floor(a.x),l=Math.floor(a.y),n=a.x-1*i,o=a.y-1*l,u={x:Number.NaN,y:Number.NaN};if(i<0||i>=e.lim[0])return u;if(l<0||l>=e.lim[1])return u;t=l*e.lim[0]+i;var d=e.cvs[t][0],s=e.cvs[t][1];t++;var y=e.cvs[t][0],f=e.cvs[t][1];t+=e.lim[0];var x=e.cvs[t][0],m=e.cvs[t][1];t--;var N=e.cvs[t][0],c=e.cvs[t][1],_=n*o,g=n*(1-o),v=(1-n)*(1-o),S=(1-n)*o;return u.x=v*d+g*y+S*N+_*x,u.y=v*s+g*f+S*c+_*m,u}t.default=function(r,e,t){if((0,o.compareDatums)(r,e))return t;if(r.datum_type===n.PJD_NODATUM||e.datum_type===n.PJD_NODATUM)return t;var a=r.a,i=r.es;if(r.datum_type===n.PJD_GRIDSHIFT){if(0!==s(r,!1,t))return;a=n.SRS_WGS84_SEMIMAJOR,i=n.SRS_WGS84_ESQUARED}var l=e.a,u=e.b,y=e.es;if(e.datum_type===n.PJD_GRIDSHIFT&&(l=n.SRS_WGS84_SEMIMAJOR,u=n.SRS_WGS84_SEMIMINOR,y=n.SRS_WGS84_ESQUARED),i===y&&a===l&&!d(r.datum_type)&&!d(e.datum_type))return t;if(t=(0,o.geodeticToGeocentric)(t,i,a),d(r.datum_type)&&(t=(0,o.geocentricToWgs84)(t,r.datum_type,r.datum_params)),d(e.datum_type)&&(t=(0,o.geocentricFromWgs84)(t,e.datum_type,e.datum_params)),t=(0,o.geocentricToGeodetic)(t,y,l,u),e.datum_type===n.PJD_GRIDSHIFT&&0!==s(e,!0,t))return;return t},t.applyGridShift=s},\n", - 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n>Math.PI&&(n-=2*Math.PI),s=Math.sin(d),e=Math.cos(d),_=s*s,{x:((m=r/Math.sqrt(1-t*_))+i)*e*Math.cos(n),y:(m+i)*e*Math.sin(n),z:(m*(1-t)+i)*s}},r.geocentricToGeodetic=function(a,t,r,m){var s,_,e,n,d,i,p,P,y,z,M,o,A,c,x,h=1e-12,f=a.x,I=a.y,F=a.z?a.z:0;if(s=Math.sqrt(f*f+I*I),_=Math.sqrt(f*f+I*I+F*F),s/r1e-24&&A<30);return{x:c,y:Math.atan(M/Math.abs(z)),z:x}},r.geocentricToWgs84=function(a,t,r){if(t===u.PJD_3PARAM)return{x:a.x+r[0],y:a.y+r[1],z:a.z+r[2]};if(t===u.PJD_7PARAM){var m=r[0],s=r[1],_=r[2],e=r[3],n=r[4],d=r[5],i=r[6];return{x:i*(a.x-d*a.y+n*a.z)+m,y:i*(d*a.x+a.y-e*a.z)+s,z:i*(-n*a.x+e*a.y+a.z)+_}}},r.geocentricFromWgs84=function(a,t,r){if(t===u.PJD_3PARAM)return{x:a.x-r[0],y:a.y-r[1],z:a.z-r[2]};if(t===u.PJD_7PARAM){var m=r[0],s=r[1],_=r[2],e=r[3],n=r[4],d=r[5],i=r[6],p=(a.x-m)/i,P=(a.y-s)/i,y=(a.z-_)/i;return{x:p+d*P-n*y,y:-d*p+P+e*y,z:n*p-e*P+y}}}},\n", - " function _(e,a,i,r,s){r(),i.default=function(e,a,i){var r,s,n,c=i.x,d=i.y,f=i.z||0,u={};for(n=0;n<3;n++)if(!a||2!==n||void 0!==i.z)switch(0===n?(r=c,s=-1!==\"ew\".indexOf(e.axis[n])?\"x\":\"y\"):1===n?(r=d,s=-1!==\"ns\".indexOf(e.axis[n])?\"y\":\"x\"):(r=f,s=\"z\"),e.axis[n]){case\"e\":u[s]=r;break;case\"w\":u[s]=-r;break;case\"n\":u[s]=r;break;case\"s\":u[s]=-r;break;case\"u\":void 0!==i[s]&&(u.z=r);break;case\"d\":void 0!==i[s]&&(u.z=-r);break;default:return null}return u}},\n", - " function _(n,t,e,u,f){u(),e.default=function(n){var t={x:n[0],y:n[1]};return n.length>2&&(t.z=n[2]),n.length>3&&(t.m=n[3]),t}},\n", - " function _(e,i,n,t,r){function o(e){if(\"function\"==typeof Number.isFinite){if(Number.isFinite(e))return;throw new TypeError(\"coordinates must be finite numbers\")}if(\"number\"!=typeof e||e!=e||!isFinite(e))throw new TypeError(\"coordinates must be finite numbers\")}t(),n.default=function(e){o(e.x),o(e.y)}},\n", - " function _(e,i,s,t,o){t();const n=e(1);var l,a,r,_,c;const d=e(53),v=e(42),u=(0,n.__importStar)(e(45)),h=e(48),m=(0,n.__importStar)(e(18));class T extends v.View{initialize(){super.initialize(),this.visuals=new u.Visuals(this)}request_render(){this.parent.request_render()}get canvas(){return this.parent.canvas}set_data(e){const i=this;for(const s of this.model){if(!(s instanceof m.VectorSpec||s instanceof m.ScalarSpec))continue;const t=s.uniform(e);i[`${s.attr}`]=t}}}s.ArrowHeadView=T,T.__name__=\"ArrowHeadView\";class p extends d.Model{constructor(e){super(e)}}s.ArrowHead=p,l=p,p.__name__=\"ArrowHead\",l.define((()=>({size:[m.NumberSpec,25]})));class V extends T{clip(e,i){this.visuals.line.set_vectorize(e,i);const s=this.size.get(i);e.moveTo(.5*s,s),e.lineTo(.5*s,-2),e.lineTo(-.5*s,-2),e.lineTo(-.5*s,s),e.lineTo(0,0),e.lineTo(.5*s,s)}render(e,i){if(this.visuals.line.doit){this.visuals.line.set_vectorize(e,i);const s=this.size.get(i);e.beginPath(),e.moveTo(.5*s,s),e.lineTo(0,0),e.lineTo(-.5*s,s),e.stroke()}}}s.OpenHeadView=V,V.__name__=\"OpenHeadView\";class f extends p{constructor(e){super(e)}}s.OpenHead=f,a=f,f.__name__=\"OpenHead\",a.prototype.default_view=V,a.mixins(h.LineVector);class w extends T{clip(e,i){this.visuals.line.set_vectorize(e,i);const s=this.size.get(i);e.moveTo(.5*s,s),e.lineTo(.5*s,-2),e.lineTo(-.5*s,-2),e.lineTo(-.5*s,s),e.lineTo(.5*s,s)}render(e,i){this.visuals.fill.doit&&(this.visuals.fill.set_vectorize(e,i),this._normal(e,i),e.fill()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(e,i),this._normal(e,i),e.stroke())}_normal(e,i){const s=this.size.get(i);e.beginPath(),e.moveTo(.5*s,s),e.lineTo(0,0),e.lineTo(-.5*s,s),e.closePath()}}s.NormalHeadView=w,w.__name__=\"NormalHeadView\";class H extends p{constructor(e){super(e)}}s.NormalHead=H,r=H,H.__name__=\"NormalHead\",r.prototype.default_view=w,r.mixins([h.LineVector,h.FillVector]),r.override({fill_color:\"black\"});class z extends T{clip(e,i){this.visuals.line.set_vectorize(e,i);const s=this.size.get(i);e.moveTo(.5*s,s),e.lineTo(.5*s,-2),e.lineTo(-.5*s,-2),e.lineTo(-.5*s,s),e.lineTo(0,.5*s),e.lineTo(.5*s,s)}render(e,i){this.visuals.fill.doit&&(this.visuals.fill.set_vectorize(e,i),this._vee(e,i),e.fill()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(e,i),this._vee(e,i),e.stroke())}_vee(e,i){const s=this.size.get(i);e.beginPath(),e.moveTo(.5*s,s),e.lineTo(0,0),e.lineTo(-.5*s,s),e.lineTo(0,.5*s),e.closePath()}}s.VeeHeadView=z,z.__name__=\"VeeHeadView\";class x extends p{constructor(e){super(e)}}s.VeeHead=x,_=x,x.__name__=\"VeeHead\",_.prototype.default_view=z,_.mixins([h.LineVector,h.FillVector]),_.override({fill_color:\"black\"});class g extends T{render(e,i){if(this.visuals.line.doit){this.visuals.line.set_vectorize(e,i);const s=this.size.get(i);e.beginPath(),e.moveTo(.5*s,0),e.lineTo(-.5*s,0),e.stroke()}}clip(e,i){}}s.TeeHeadView=g,g.__name__=\"TeeHeadView\";class b extends p{constructor(e){super(e)}}s.TeeHead=b,c=b,b.__name__=\"TeeHead\",c.prototype.default_view=g,c.mixins(h.LineVector)},\n", - " function _(n,e,t,i,o){i();const s=n(9);async function c(n,e,t){const i=new n(Object.assign(Object.assign({},t),{model:e}));return i.initialize(),await i.lazy_initialize(),i}t.build_view=async function(n,e={parent:null},t=(n=>n.default_view)){const i=await c(t(n),n,e);return i.connect_signals(),i},t.build_views=async function(n,e,t={parent:null},i=(n=>n.default_view)){const o=(0,s.difference)([...n.keys()],e);for(const e of o)n.get(e).remove(),n.delete(e);const a=[],f=e.filter((e=>!n.has(e)));for(const e of f){const o=await c(i(e),e,t);n.set(e,o),a.push(o)}for(const n of a)n.connect_signals();return a},t.remove_views=function(n){for(const[e,t]of n)t.remove(),n.delete(e)}},\n", - " function _(e,s,_,i,l){i();const t=e(1);var o;const r=e(115),p=(0,t.__importStar)(e(48));class h extends r.UpperLowerView{paint(e){e.beginPath(),e.moveTo(this._lower_sx[0],this._lower_sy[0]);for(let s=0,_=this._lower_sx.length;s<_;s++)e.lineTo(this._lower_sx[s],this._lower_sy[s]);for(let s=this._upper_sx.length-1;s>=0;s--)e.lineTo(this._upper_sx[s],this._upper_sy[s]);e.closePath(),this.visuals.fill.apply(e),e.beginPath(),e.moveTo(this._lower_sx[0],this._lower_sy[0]);for(let s=0,_=this._lower_sx.length;s<_;s++)e.lineTo(this._lower_sx[s],this._lower_sy[s]);this.visuals.line.apply(e),e.beginPath(),e.moveTo(this._upper_sx[0],this._upper_sy[0]);for(let s=0,_=this._upper_sx.length;s<_;s++)e.lineTo(this._upper_sx[s],this._upper_sy[s]);this.visuals.line.apply(e)}}_.BandView=h,h.__name__=\"BandView\";class n extends r.UpperLower{constructor(e){super(e)}}_.Band=n,o=n,n.__name__=\"Band\",o.prototype.default_view=h,o.mixins([p.Line,p.Fill]),o.override({fill_color:\"#fff9ba\",fill_alpha:.4,line_color:\"#cccccc\",line_alpha:.3})},\n", - " function _(e,t,i,s,o){s();const r=e(1);var n;const p=e(69),a=e(20),_=(0,r.__importStar)(e(18));class h extends p.DataAnnotationView{map_data(){const{frame:e}=this.plot_view,t=this.model.dimension,i=this.coordinates.x_scale,s=this.coordinates.y_scale,o=\"height\"==t?s:i,r=\"height\"==t?i:s,n=\"height\"==t?e.bbox.yview:e.bbox.xview,p=\"height\"==t?e.bbox.xview:e.bbox.yview;let a,_,h;a=\"data\"==this.model.properties.lower.units?o.v_compute(this._lower):n.v_compute(this._lower),_=\"data\"==this.model.properties.upper.units?o.v_compute(this._upper):n.v_compute(this._upper),h=\"data\"==this.model.properties.base.units?r.v_compute(this._base):p.v_compute(this._base);const[d,c]=\"height\"==t?[1,0]:[0,1],u=[a,h],l=[_,h];this._lower_sx=u[d],this._lower_sy=u[c],this._upper_sx=l[d],this._upper_sy=l[c]}}i.UpperLowerView=h,h.__name__=\"UpperLowerView\";class d extends _.CoordinateSpec{get dimension(){return\"width\"==this.obj.dimension?\"x\":\"y\"}get units(){var e;return null!==(e=this.spec.units)&&void 0!==e?e:\"data\"}}i.XOrYCoordinateSpec=d,d.__name__=\"XOrYCoordinateSpec\";class c extends p.DataAnnotation{constructor(e){super(e)}}i.UpperLower=c,n=c,c.__name__=\"UpperLower\",n.define((()=>({dimension:[a.Dimension,\"height\"],lower:[d,{field:\"lower\"}],upper:[d,{field:\"upper\"}],base:[d,{field:\"base\"}]})))},\n", - " function _(t,o,i,n,e){n();const s=t(1);var l;const r=t(40),a=(0,s.__importStar)(t(48)),c=t(20),h=t(65);i.EDGE_TOLERANCE=2.5;class b extends r.AnnotationView{constructor(){super(...arguments),this.bbox=new h.BBox}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render()))}_render(){const{left:t,right:o,top:i,bottom:n}=this.model;if(null==t&&null==o&&null==i&&null==n)return;const{frame:e}=this.plot_view,s=this.coordinates.x_scale,l=this.coordinates.y_scale,r=(t,o,i,n,e)=>{let s;return s=null!=t?this.model.screen?t:\"data\"==o?i.compute(t):n.compute(t):e,s};this.bbox=h.BBox.from_rect({left:r(t,this.model.left_units,s,e.bbox.xview,e.bbox.left),right:r(o,this.model.right_units,s,e.bbox.xview,e.bbox.right),top:r(i,this.model.top_units,l,e.bbox.yview,e.bbox.top),bottom:r(n,this.model.bottom_units,l,e.bbox.yview,e.bbox.bottom)}),this._paint_box()}_paint_box(){const{ctx:t}=this.layer;t.save();const{left:o,top:i,width:n,height:e}=this.bbox;t.beginPath(),t.rect(o,i,n,e),this.visuals.fill.apply(t),this.visuals.hatch.apply(t),this.visuals.line.apply(t),t.restore()}interactive_bbox(){const t=this.model.line_width+i.EDGE_TOLERANCE;return this.bbox.grow_by(t)}interactive_hit(t,o){if(null==this.model.in_cursor)return!1;return this.interactive_bbox().contains(t,o)}cursor(t,o){const{left:i,right:n,bottom:e,top:s}=this.bbox;return Math.abs(t-i)<3||Math.abs(t-n)<3?this.model.ew_cursor:Math.abs(o-e)<3||Math.abs(o-s)<3?this.model.ns_cursor:this.bbox.contains(t,o)?this.model.in_cursor:null}}i.BoxAnnotationView=b,b.__name__=\"BoxAnnotationView\";class u extends r.Annotation{constructor(t){super(t)}update({left:t,right:o,top:i,bottom:n}){this.setv({left:t,right:o,top:i,bottom:n,screen:!0})}}i.BoxAnnotation=u,l=u,u.__name__=\"BoxAnnotation\",l.prototype.default_view=b,l.mixins([a.Line,a.Fill,a.Hatch]),l.define((({Number:t,Nullable:o})=>({top:[o(t),null],top_units:[c.SpatialUnits,\"data\"],bottom:[o(t),null],bottom_units:[c.SpatialUnits,\"data\"],left:[o(t),null],left_units:[c.SpatialUnits,\"data\"],right:[o(t),null],right_units:[c.SpatialUnits,\"data\"],render_mode:[c.RenderMode,\"canvas\"]}))),l.internal((({Boolean:t,String:o,Nullable:i})=>({screen:[t,!1],ew_cursor:[i(o),null],ns_cursor:[i(o),null],in_cursor:[i(o),null]}))),l.override({fill_color:\"#fff9ba\",fill_alpha:.4,line_color:\"#cccccc\",line_alpha:.3})},\n", - " function _(t,e,i,o,n){o();const a=t(1);var r;const s=t(40),l=t(118),_=t(126),c=t(127),h=t(130),u=t(168),p=t(131),m=t(192),g=t(132),d=t(173),f=t(172),w=t(196),b=t(204),v=t(206),x=t(133),y=t(20),k=(0,a.__importStar)(t(48)),z=t(9),j=t(207),C=t(208),L=t(211),B=t(123),S=t(11),M=t(113),T=t(65),A=t(8);class O extends s.AnnotationView{get orientation(){return this._orientation}initialize(){super.initialize();const{ticker:t,formatter:e,color_mapper:i}=this.model;this._ticker=\"auto\"!=t?t:(()=>{switch(!0){case i instanceof w.LogColorMapper:return new u.LogTicker;case i instanceof w.ScanningColorMapper:return new u.BinnedTicker({mapper:i});case i instanceof w.CategoricalColorMapper:return new u.CategoricalTicker;default:return new u.BasicTicker}})(),this._formatter=\"auto\"!=e?e:(()=>{switch(!0){case this._ticker instanceof u.LogTicker:return new m.LogTickFormatter;case i instanceof w.CategoricalColorMapper:return new m.CategoricalTickFormatter;default:return new m.BasicTickFormatter}})(),this._major_range=(()=>{if(i instanceof w.CategoricalColorMapper){const{factors:t}=i;return new v.FactorRange({factors:t})}if(i instanceof f.ContinuousColorMapper){const{min:t,max:e}=i.metrics;return new v.Range1d({start:t,end:e})}(0,S.unreachable)()})(),this._major_scale=(()=>{if(i instanceof w.LinearColorMapper)return new b.LinearScale;if(i instanceof w.LogColorMapper)return new b.LogScale;if(i instanceof w.ScanningColorMapper){const{binning:t}=i.metrics;return new b.LinearInterpolationScale({binning:t})}if(i instanceof w.CategoricalColorMapper)return new b.CategoricalScale;(0,S.unreachable)()})(),this._minor_range=new v.Range1d({start:0,end:1}),this._minor_scale=new b.LinearScale;const o=k.attrs_of(this.model,\"major_label_\",k.Text,!0),n=k.attrs_of(this.model,\"major_tick_\",k.Line,!0),a=k.attrs_of(this.model,\"minor_tick_\",k.Line,!0),r=k.attrs_of(this.model,\"title_\",k.Text),s=i instanceof w.CategoricalColorMapper?c.CategoricalAxis:i instanceof w.LogColorMapper?c.LogAxis:c.LinearAxis;this._axis=new s(Object.assign(Object.assign(Object.assign({ticker:this._ticker,formatter:this._formatter,major_tick_in:this.model.major_tick_in,major_tick_out:this.model.major_tick_out,minor_tick_in:this.model.minor_tick_in,minor_tick_out:this.model.minor_tick_out,major_label_standoff:this.model.label_standoff,major_label_overrides:this.model.major_label_overrides,major_label_policy:this.model.major_label_policy,axis_line_color:null},o),n),a));const{title:_}=this.model;_&&(this._title=new l.Title(Object.assign({text:_,standoff:this.model.title_standoff},r)))}async lazy_initialize(){await super.lazy_initialize();const t=this,e={get parent(){return t.parent},get root(){return t.root},get frame(){return t._frame},get canvas_view(){return t.parent.canvas_view},request_layout(){t.parent.request_layout()}};this._axis_view=await(0,M.build_view)(this._axis,{parent:e}),null!=this._title&&(this._title_view=await(0,M.build_view)(this._title,{parent:e}))}remove(){var t;null===(t=this._title_view)||void 0===t||t.remove(),this._axis_view.remove(),super.remove()}connect_signals(){super.connect_signals(),this.connect(this._ticker.change,(()=>this.request_render())),this.connect(this._formatter.change,(()=>this.request_render())),this.connect(this.model.color_mapper.metrics_change,(()=>{const t=this._major_range,e=this._major_scale,{color_mapper:i}=this.model;if(i instanceof f.ContinuousColorMapper&&t instanceof v.Range1d){const{min:e,max:o}=i.metrics;t.setv({start:e,end:o})}if(i instanceof w.ScanningColorMapper&&e instanceof b.LinearInterpolationScale){const{binning:t}=i.metrics;e.binning=t}this._set_canvas_image(),this.plot_view.request_layout()}))}_set_canvas_image(){const{orientation:t}=this,e=(()=>{const{palette:e}=this.model.color_mapper;return\"vertical\"==t?(0,z.reversed)(e):e})(),[i,o]=\"vertical\"==t?[1,e.length]:[e.length,1],n=this._image=document.createElement(\"canvas\");n.width=i,n.height=o;const a=n.getContext(\"2d\"),r=a.getImageData(0,0,i,o),s=new w.LinearColorMapper({palette:e}).rgba_mapper.v_compute((0,z.range)(0,e.length));r.data.set(s),a.putImageData(r,0,0)}update_layout(){const{location:t,width:e,height:i,padding:o,margin:n}=this.model,[a,r]=(()=>{if(!(0,A.isString)(t))return[\"end\",\"start\"];switch(t){case\"top_left\":return[\"start\",\"start\"];case\"top\":case\"top_center\":return[\"start\",\"center\"];case\"top_right\":return[\"start\",\"end\"];case\"bottom_left\":return[\"end\",\"start\"];case\"bottom\":case\"bottom_center\":return[\"end\",\"center\"];case\"bottom_right\":return[\"end\",\"end\"];case\"left\":case\"center_left\":return[\"center\",\"start\"];case\"center\":case\"center_center\":return[\"center\",\"center\"];case\"right\":case\"center_right\":return[\"center\",\"end\"]}})(),s=this._orientation=(()=>{const{orientation:t}=this.model;return\"auto\"==t?null!=this.panel?this.panel.is_horizontal?\"horizontal\":\"vertical\":\"start\"==r||\"end\"==r||\"center\"==r&&\"center\"==a?\"vertical\":\"horizontal\":t})(),l=new C.NodeLayout,c=new C.VStack,h=new C.VStack,u=new C.HStack,p=new C.HStack;l.absolute=!0,c.absolute=!0,h.absolute=!0,u.absolute=!0,p.absolute=!0;const[m,g,d,f]=(()=>\"horizontal\"==s?[this._major_scale,this._minor_scale,this._major_range,this._minor_range]:[this._minor_scale,this._major_scale,this._minor_range,this._major_range])();this._frame=new _.CartesianFrame(m,g,d,f),l.on_resize((t=>this._frame.set_geometry(t)));const w=new L.BorderLayout;this._inner_layout=w,w.absolute=!0,w.center_panel=l,w.top_panel=c,w.bottom_panel=h,w.left_panel=u,w.right_panel=p;const b={left:o,right:o,top:o,bottom:o},v=(()=>{if(null==this.panel){if((0,A.isString)(t))return{left:n,right:n,top:n,bottom:n};{const[e,i]=t;return{left:e,right:n,top:n,bottom:i}}}if(!(0,A.isString)(t)){const[e,i]=t;return w.fixup_geometry=(t,o)=>{const n=t,a=this.layout.bbox,{width:r,height:s}=t;if(t=new T.BBox({left:a.left+e,bottom:a.bottom-i,width:r,height:s}),null!=o){const e=t.left-n.left,i=t.top-n.top,{left:a,top:r,width:s,height:l}=o;o=new T.BBox({left:a+e,top:r+i,width:s,height:l})}return[t,o]},{left:e,right:0,top:0,bottom:i}}w.fixup_geometry=(t,e)=>{const i=t;if(\"horizontal\"==s){const{top:e,width:i,height:o}=t;if(\"end\"==r){const{right:n}=this.layout.bbox;t=new T.BBox({right:n,top:e,width:i,height:o})}else if(\"center\"==r){const{hcenter:n}=this.layout.bbox;t=new T.BBox({hcenter:Math.round(n),top:e,width:i,height:o})}}else{const{left:e,width:i,height:o}=t;if(\"end\"==a){const{bottom:n}=this.layout.bbox;t=new T.BBox({left:e,bottom:n,width:i,height:o})}else if(\"center\"==a){const{vcenter:n}=this.layout.bbox;t=new T.BBox({left:e,vcenter:Math.round(n),width:i,height:o})}}if(null!=e){const o=t.left-i.left,n=t.top-i.top,{left:a,top:r,width:s,height:l}=e;e=new T.BBox({left:a+o,top:r+n,width:s,height:l})}return[t,e]}})();let x,y,k,z;if(w.padding=b,null!=this.panel?(x=\"max\",y=void 0,k=void 0,z=void 0):\"auto\"==(\"horizontal\"==s?e:i)?(x=\"fixed\",y=25*this.model.color_mapper.palette.length,k={percent:.3},z={percent:.8}):(x=\"fit\",y=void 0),\"horizontal\"==s){const t=\"auto\"==e?void 0:e,o=\"auto\"==i?25:i;w.set_sizing({width_policy:x,height_policy:\"min\",width:y,min_width:k,max_width:z,halign:r,valign:a,margin:v}),w.center_panel.set_sizing({width_policy:\"auto\"==e?\"fit\":\"fixed\",height_policy:\"fixed\",width:t,height:o})}else{const t=\"auto\"==e?25:e,o=\"auto\"==i?void 0:i;w.set_sizing({width_policy:\"min\",height_policy:x,height:y,min_height:k,max_height:z,halign:r,valign:a,margin:v}),w.center_panel.set_sizing({width_policy:\"fixed\",height_policy:\"auto\"==i?\"fit\":\"fixed\",width:t,height:o})}c.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),h.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),u.set_sizing({width_policy:\"min\",height_policy:\"fit\"}),p.set_sizing({width_policy:\"min\",height_policy:\"fit\"});const{_title_view:S}=this;null!=S&&(\"horizontal\"==s?(S.panel=new B.Panel(\"above\"),S.update_layout(),c.children.push(S.layout)):(S.panel=new B.Panel(\"left\"),S.update_layout(),u.children.push(S.layout)));const{panel:M}=this,O=null!=M&&s==M.orientation?M.side:\"horizontal\"==s?\"below\":\"right\",R=(()=>{switch(O){case\"above\":return c;case\"below\":return h;case\"left\":return u;case\"right\":return p}})(),{_axis_view:F}=this;if(F.panel=new B.Panel(O),F.update_layout(),R.children.push(F.layout),null!=this.panel){const t=new j.Grid([{layout:w,row:0,col:0}]);t.absolute=!0,\"horizontal\"==s?t.set_sizing({width_policy:\"max\",height_policy:\"min\"}):t.set_sizing({width_policy:\"min\",height_policy:\"max\"}),this.layout=t}else this.layout=this._inner_layout;const{visible:I}=this.model;this.layout.sizing.visible=I,this._set_canvas_image()}_render(){var t;const{ctx:e}=this.layer;e.save(),this._paint_bbox(e,this._inner_layout.bbox),this._paint_image(e,this._inner_layout.center_panel.bbox),null===(t=this._title_view)||void 0===t||t.render(),this._axis_view.render(),e.restore()}_paint_bbox(t,e){const{x:i,y:o}=e;let{width:n,height:a}=e;i+n>=this.parent.canvas_view.bbox.width&&(n-=1),o+a>=this.parent.canvas_view.bbox.height&&(a-=1),t.save(),this.visuals.background_fill.doit&&(this.visuals.background_fill.set_value(t),t.fillRect(i,o,n,a)),this.visuals.border_line.doit&&(this.visuals.border_line.set_value(t),t.strokeRect(i,o,n,a)),t.restore()}_paint_image(t,e){const{x:i,y:o,width:n,height:a}=e;t.save(),t.setImageSmoothingEnabled(!1),t.globalAlpha=this.model.scale_alpha,t.drawImage(this._image,i,o,n,a),this.visuals.bar_line.doit&&(this.visuals.bar_line.set_value(t),t.strokeRect(i,o,n,a)),t.restore()}serializable_state(){const t=super.serializable_state(),{children:e=[]}=t,i=(0,a.__rest)(t,[\"children\"]);return null!=this._title_view&&e.push(this._title_view.serializable_state()),e.push(this._axis_view.serializable_state()),Object.assign(Object.assign({},i),{children:e})}}i.ColorBarView=O,O.__name__=\"ColorBarView\";class R extends s.Annotation{constructor(t){super(t)}}i.ColorBar=R,r=R,R.__name__=\"ColorBar\",r.prototype.default_view=O,r.mixins([[\"major_label_\",k.Text],[\"title_\",k.Text],[\"major_tick_\",k.Line],[\"minor_tick_\",k.Line],[\"border_\",k.Line],[\"bar_\",k.Line],[\"background_\",k.Fill]]),r.define((({Alpha:t,Number:e,String:i,Tuple:o,Dict:n,Or:a,Ref:r,Auto:s,Nullable:l})=>({location:[a(y.Anchor,o(e,e)),\"top_right\"],orientation:[a(y.Orientation,s),\"auto\"],title:[l(i),null],title_standoff:[e,2],width:[a(e,s),\"auto\"],height:[a(e,s),\"auto\"],scale_alpha:[t,1],ticker:[a(r(h.Ticker),s),\"auto\"],formatter:[a(r(p.TickFormatter),s),\"auto\"],major_label_overrides:[n(a(i,r(x.BaseText))),{}],major_label_policy:[r(g.LabelingPolicy),()=>new g.NoOverlap],color_mapper:[r(d.ColorMapper)],label_standoff:[e,5],margin:[e,30],padding:[e,10],major_tick_in:[e,5],major_tick_out:[e,0],minor_tick_in:[e,0],minor_tick_out:[e,0]}))),r.override({background_fill_color:\"#ffffff\",background_fill_alpha:.95,bar_line_color:null,border_line_color:null,major_label_text_font_size:\"11px\",major_tick_line_color:\"#ffffff\",minor_tick_line_color:null,title_text_font_size:\"13px\",title_text_font_style:\"italic\"})},\n", - " function _(t,e,i,s,l){s();const o=t(1);var a;const n=t(119),r=t(20),c=t(120),h=(0,o.__importStar)(t(48));class _ extends n.TextAnnotationView{_get_location(){const t=this.model.offset,e=this.model.standoff/2;let i,s;const{bbox:l}=this.layout;switch(this.panel.side){case\"above\":case\"below\":switch(this.model.vertical_align){case\"top\":s=l.top+e;break;case\"middle\":s=l.vcenter;break;case\"bottom\":s=l.bottom-e}switch(this.model.align){case\"left\":i=l.left+t;break;case\"center\":i=l.hcenter;break;case\"right\":i=l.right-t}break;case\"left\":switch(this.model.vertical_align){case\"top\":i=l.left+e;break;case\"middle\":i=l.hcenter;break;case\"bottom\":i=l.right-e}switch(this.model.align){case\"left\":s=l.bottom-t;break;case\"center\":s=l.vcenter;break;case\"right\":s=l.top+t}break;case\"right\":switch(this.model.vertical_align){case\"top\":i=l.right-e;break;case\"middle\":i=l.hcenter;break;case\"bottom\":i=l.left+e}switch(this.model.align){case\"left\":s=l.top+t;break;case\"center\":s=l.vcenter;break;case\"right\":s=l.bottom-t}}return[i,s]}_render(){const{text:t}=this.model;if(null==t||0==t.length)return;this.model.text_baseline=this.model.vertical_align,this.model.text_align=this.model.align;const[e,i]=this._get_location(),s=this.panel.get_label_angle_heuristic(\"parallel\");(\"canvas\"==this.model.render_mode?this._canvas_text.bind(this):this._css_text.bind(this))(this.layer.ctx,t,e,i,s)}_get_size(){const{text:t}=this.model,e=new c.TextBox({text:t});e.visuals=this.visuals.text.values();const{width:i,height:s}=e.size();return{width:i,height:0==s?0:2+s+this.model.standoff}}}i.TitleView=_,_.__name__=\"TitleView\";class d extends n.TextAnnotation{constructor(t){super(t)}}i.Title=d,a=d,d.__name__=\"Title\",a.prototype.default_view=_,a.mixins([h.Text,[\"border_\",h.Line],[\"background_\",h.Fill]]),a.define((({Number:t,String:e})=>({text:[e,\"\"],vertical_align:[r.VerticalAlign,\"bottom\"],align:[r.TextAlign,\"left\"],offset:[t,0],standoff:[t,10]}))),a.prototype._props.text_align.options.internal=!0,a.prototype._props.text_baseline.options.internal=!0,a.override({text_font_size:\"13px\",text_font_style:\"bold\",text_line_height:1,background_fill_color:null,border_line_color:null})},\n", - " function _(e,t,s,i,l){var n;i();const o=e(40),a=e(43),r=e(20),d=e(120),u=e(123),c=e(11);class h extends o.AnnotationView{update_layout(){const{panel:e}=this;this.layout=null!=e?new u.SideLayout(e,(()=>this.get_size()),!0):void 0}initialize(){super.initialize(),\"css\"==this.model.render_mode&&(this.el=(0,a.div)(),this.plot_view.canvas_view.add_overlay(this.el))}remove(){null!=this.el&&(0,a.remove)(this.el),super.remove()}connect_signals(){super.connect_signals(),\"css\"==this.model.render_mode?this.connect(this.model.change,(()=>this.render())):this.connect(this.model.change,(()=>this.request_render()))}render(){this.model.visible||\"css\"!=this.model.render_mode||(0,a.undisplay)(this.el),super.render()}_canvas_text(e,t,s,i,l){const n=new d.TextBox({text:t});n.angle=l,n.position={sx:s,sy:i},n.visuals=this.visuals.text.values();const{background_fill:o,border_line:a}=this.visuals;if(o.doit||a.doit){const{p0:t,p1:s,p2:i,p3:l}=n.rect();e.beginPath(),e.moveTo(t.x,t.y),e.lineTo(s.x,s.y),e.lineTo(i.x,i.y),e.lineTo(l.x,l.y),e.closePath(),this.visuals.background_fill.apply(e),this.visuals.border_line.apply(e)}this.visuals.text.doit&&n.paint(e)}_css_text(e,t,s,i,l){const{el:n}=this;(0,c.assert)(null!=n),(0,a.undisplay)(n),n.textContent=t,this.visuals.text.set_value(e),n.style.position=\"absolute\",n.style.left=`${s}px`,n.style.top=`${i}px`,n.style.color=e.fillStyle,n.style.font=e.font,n.style.lineHeight=\"normal\",n.style.whiteSpace=\"pre\";const[o,r]=(()=>{switch(this.visuals.text.text_align.get_value()){case\"left\":return[\"left\",\"0%\"];case\"center\":return[\"center\",\"-50%\"];case\"right\":return[\"right\",\"-100%\"]}})(),[d,u]=(()=>{switch(this.visuals.text.text_baseline.get_value()){case\"top\":return[\"top\",\"0%\"];case\"middle\":return[\"center\",\"-50%\"];case\"bottom\":return[\"bottom\",\"-100%\"];default:return[\"center\",\"-50%\"]}})();let h=`translate(${r}, ${u})`;l&&(h+=`rotate(${l}rad)`),n.style.transformOrigin=`${o} ${d}`,n.style.transform=h,this.layout,this.visuals.background_fill.doit&&(this.visuals.background_fill.set_value(e),n.style.backgroundColor=e.fillStyle),this.visuals.border_line.doit&&(this.visuals.border_line.set_value(e),n.style.borderStyle=e.lineDash.length<2?\"solid\":\"dashed\",n.style.borderWidth=`${e.lineWidth}px`,n.style.borderColor=e.strokeStyle),(0,a.display)(n)}}s.TextAnnotationView=h,h.__name__=\"TextAnnotationView\";class _ extends o.Annotation{constructor(e){super(e)}}s.TextAnnotation=_,n=_,_.__name__=\"TextAnnotation\",n.define((()=>({render_mode:[r.RenderMode,\"canvas\"]})))},\n", - " function _(t,e,s,i,n){i();const h=t(65),o=t(121),r=t(9),a=t(8),c=t(122),_=t(22);s.text_width=(()=>{const t=document.createElement(\"canvas\").getContext(\"2d\");let e=\"\";return(s,i)=>(i!=e&&(e=i,t.font=i),t.measureText(s).width)})();class l{constructor(){this._position={sx:0,sy:0},this.font_size_scale=1,this.align=\"left\",this._base_font_size=13,this._x_anchor=\"left\",this._y_anchor=\"center\"}set base_font_size(t){null!=t&&(this._base_font_size=t)}get base_font_size(){return this._base_font_size}set position(t){this._position=t}get position(){return this._position}infer_text_height(){return\"ascent_descent\"}bbox(){const{p0:t,p1:e,p2:s,p3:i}=this.rect(),n=Math.min(t.x,e.x,s.x,i.x),o=Math.min(t.y,e.y,s.y,i.y),r=Math.max(t.x,e.x,s.x,i.x),a=Math.max(t.y,e.y,s.y,i.y);return new h.BBox({left:n,right:r,top:o,bottom:a})}size(){const{width:t,height:e}=this._size(),{angle:s}=this;if(s){const i=Math.cos(Math.abs(s)),n=Math.sin(Math.abs(s));return{width:Math.abs(t*i+e*n),height:Math.abs(t*n+e*i)}}return{width:t,height:e}}rect(){const t=this._rect(),{angle:e}=this;if(e){const{sx:s,sy:i}=this.position,n=new c.AffineTransform;return n.translate(s,i),n.rotate(e),n.translate(-s,-i),n.apply_rect(t)}return t}paint_rect(t){const{p0:e,p1:s,p2:i,p3:n}=this.rect();t.save(),t.strokeStyle=\"red\",t.lineWidth=1,t.beginPath();const{round:h}=Math;t.moveTo(h(e.x),h(e.y)),t.lineTo(h(s.x),h(s.y)),t.lineTo(h(i.x),h(i.y)),t.lineTo(h(n.x),h(n.y)),t.closePath(),t.stroke(),t.restore()}paint_bbox(t){const{x:e,y:s,width:i,height:n}=this.bbox();t.save(),t.strokeStyle=\"blue\",t.lineWidth=1,t.beginPath();const{round:h}=Math;t.moveTo(h(e),h(s)),t.lineTo(h(e),h(s+n)),t.lineTo(h(e+i),h(s+n)),t.lineTo(h(e+i),h(s)),t.closePath(),t.stroke(),t.restore()}}s.GraphicsBox=l,l.__name__=\"GraphicsBox\";class x extends l{constructor({text:t}){super(),this.text=t}set visuals(t){const e=t.color,s=t.alpha,i=t.font_style;let n=t.font_size;const h=t.font,{font_size_scale:r,base_font_size:a}=this,c=(0,o.parse_css_font_size)(n);if(null!=c){let{value:t,unit:e}=c;t*=r,\"em\"==e&&a&&(t*=a,e=\"px\"),n=`${t}${e}`}const l=`${i} ${n} ${h}`;this.font=l,this.color=(0,_.color2css)(e,s),this.line_height=t.line_height;const x=t.align;this._x_anchor=x;const u=t.baseline;this._y_anchor=(()=>{switch(u){case\"top\":return\"top\";case\"middle\":return\"center\";case\"bottom\":return\"bottom\";default:return\"baseline\"}})()}infer_text_height(){if(this.text.includes(\"\\n\"))return\"ascent_descent\";{function t(t){for(const e of new Set(t))if(!(\"0\"<=e&&e<=\"9\"))switch(e){case\",\":case\".\":case\"+\":case\"-\":case\"\\u2212\":case\"e\":continue;default:return!1}return!0}return t(this.text)?\"cap\":\"ascent_descent\"}}_text_line(t){var e;const s=null!==(e=this.text_height_metric)&&void 0!==e?e:this.infer_text_height(),i=(()=>{switch(s){case\"x\":case\"x_descent\":return t.x_height;case\"cap\":case\"cap_descent\":return t.cap_height;case\"ascent\":case\"ascent_descent\":return t.ascent}})(),n=(()=>{switch(s){case\"x\":case\"cap\":case\"ascent\":return 0;case\"x_descent\":case\"cap_descent\":case\"ascent_descent\":return t.descent}})();return{height:i+n,ascent:i,descent:n}}get nlines(){return this.text.split(\"\\n\").length}_size(){var t,e;const{font:i}=this,n=(0,o.font_metrics)(i),h=(this.line_height-1)*n.height,a=\"\"==this.text,c=this.text.split(\"\\n\"),_=c.length,l=c.map((t=>(0,s.text_width)(t,i))),x=this._text_line(n).height*_,u=\"%\"==(null===(t=this.width)||void 0===t?void 0:t.unit)?this.width.value:1,p=\"%\"==(null===(e=this.height)||void 0===e?void 0:e.unit)?this.height.value:1;return{width:(0,r.max)(l)*u,height:a?0:(x+h*(_-1))*p,metrics:n}}_computed_position(t,e,s){const{width:i,height:n}=t,{sx:h,sy:o,x_anchor:r=this._x_anchor,y_anchor:c=this._y_anchor}=this.position;return{x:h-(()=>{if((0,a.isNumber)(r))return r*i;switch(r){case\"left\":return 0;case\"center\":return.5*i;case\"right\":return i}})(),y:o-(()=>{var t;if((0,a.isNumber)(c))return c*n;switch(c){case\"top\":return 0;case\"center\":return.5*n;case\"bottom\":return n;case\"baseline\":if(1!=s)return.5*n;switch(null!==(t=this.text_height_metric)&&void 0!==t?t:this.infer_text_height()){case\"x\":case\"x_descent\":return e.x_height;case\"cap\":case\"cap_descent\":return e.cap_height;case\"ascent\":case\"ascent_descent\":return e.ascent}}})()}}_rect(){const{width:t,height:e,metrics:s}=this._size(),i=this.text.split(\"\\n\").length,{x:n,y:o}=this._computed_position({width:t,height:e},s,i);return new h.BBox({x:n,y:o,width:t,height:e}).rect}paint(t){var e,i;const{font:n}=this,h=(0,o.font_metrics)(n),a=(this.line_height-1)*h.height,c=this.text.split(\"\\n\"),_=c.length,l=c.map((t=>(0,s.text_width)(t,n))),x=this._text_line(h),u=x.height*_,p=\"%\"==(null===(e=this.width)||void 0===e?void 0:e.unit)?this.width.value:1,f=\"%\"==(null===(i=this.height)||void 0===i?void 0:i.unit)?this.height.value:1,g=(0,r.max)(l)*p,d=(u+a*(_-1))*f;t.save(),t.fillStyle=this.color,t.font=this.font,t.textAlign=\"left\",t.textBaseline=\"alphabetic\";const{sx:b,sy:m}=this.position,{align:y}=this,{angle:w}=this;w&&(t.translate(b,m),t.rotate(w),t.translate(-b,-m));let{x:v,y:z}=this._computed_position({width:g,height:d},h,_);if(\"justify\"==y)for(let e=0;e<_;e++){let i=v;const h=c[e].split(\" \"),o=h.length,_=h.map((t=>(0,s.text_width)(t,n))),l=(g-(0,r.sum)(_))/(o-1);for(let e=0;e{switch(y){case\"left\":return 0;case\"center\":return.5*(g-l[e]);case\"right\":return g-l[e]}})();t.fillStyle=this.color,t.fillText(c[e],s,z+x.ascent),z+=x.height+a}t.restore()}}s.TextBox=x,x.__name__=\"TextBox\";class u extends l{constructor(t,e){super(),this.base=t,this.expo=e}get children(){return[this.base,this.expo]}set base_font_size(t){super.base_font_size=t,this.base.base_font_size=t,this.expo.base_font_size=t}set position(t){this._position=t;const e=this.base.size(),s=this.expo.size(),i=this._shift_scale()*e.height,n=Math.max(e.height,i+s.height);this.base.position={sx:0,x_anchor:\"left\",sy:n,y_anchor:\"bottom\"},this.expo.position={sx:e.width,x_anchor:\"left\",sy:i,y_anchor:\"bottom\"}}get position(){return this._position}set visuals(t){this.expo.font_size_scale=.7,this.base.visuals=t,this.expo.visuals=t}_shift_scale(){if(this.base instanceof x&&1==this.base.nlines){const{x_height:t,cap_height:e}=(0,o.font_metrics)(this.base.font);return t/e}return 2/3}infer_text_height(){return this.base.infer_text_height()}_rect(){const t=this.base.bbox(),e=this.expo.bbox(),s=t.union(e),{x:i,y:n}=this._computed_position();return s.translate(i,n).rect}_size(){const t=this.base.size(),e=this.expo.size();return{width:t.width+e.width,height:Math.max(t.height,this._shift_scale()*t.height+e.height)}}paint(t){t.save();const{angle:e}=this;if(e){const{sx:s,sy:i}=this.position;t.translate(s,i),t.rotate(e),t.translate(-s,-i)}const{x:s,y:i}=this._computed_position();t.translate(s,i),this.base.paint(t),this.expo.paint(t),t.restore()}paint_bbox(t){super.paint_bbox(t);const{x:e,y:s}=this._computed_position();t.save(),t.translate(e,s);for(const e of this.children)e.paint_bbox(t);t.restore()}_computed_position(){const{width:t,height:e}=this._size(),{sx:s,sy:i,x_anchor:n=this._x_anchor,y_anchor:h=this._y_anchor}=this.position;return{x:s-(()=>{if((0,a.isNumber)(n))return n*t;switch(n){case\"left\":return 0;case\"center\":return.5*t;case\"right\":return t}})(),y:i-(()=>{if((0,a.isNumber)(h))return h*e;switch(h){case\"top\":return 0;case\"center\":return.5*e;case\"bottom\":return e;case\"baseline\":return.5*e}})()}}}s.BaseExpo=u,u.__name__=\"BaseExpo\";class p{constructor(t){this.items=t}set base_font_size(t){for(const e of this.items)e.base_font_size=t}get length(){return this.items.length}set visuals(t){for(const e of this.items)e.visuals=t;const e={x:0,cap:1,ascent:2,x_descent:3,cap_descent:4,ascent_descent:5},s=(0,r.max_by)(this.items.map((t=>t.infer_text_height())),(t=>e[t]));for(const t of this.items)t.text_height_metric=s}set angle(t){for(const e of this.items)e.angle=t}max_size(){let t=0,e=0;for(const s of this.items){const i=s.size();t=Math.max(t,i.width),e=Math.max(e,i.height)}return{width:t,height:e}}}s.GraphicsBoxes=p,p.__name__=\"GraphicsBoxes\"},\n", - " function _(t,e,n,r,l){r();const a=t(11),c=(()=>{try{return\"undefined\"!=typeof OffscreenCanvas&&null!=new OffscreenCanvas(0,0).getContext(\"2d\")}catch(t){return!1}})()?(t,e)=>new OffscreenCanvas(t,e):(t,e)=>{const n=document.createElement(\"canvas\");return n.width=t,n.height=e,n},o=(()=>{const t=c(0,0).getContext(\"2d\");return e=>{t.font=e;const n=t.measureText(\"M\"),r=t.measureText(\"x\"),l=t.measureText(\"\\xc5\\u015ag|\"),c=l.fontBoundingBoxAscent,o=l.fontBoundingBoxDescent;if(null!=c&&null!=o)return{height:c+o,ascent:c,descent:o,cap_height:n.actualBoundingBoxAscent,x_height:r.actualBoundingBoxAscent};const s=l.actualBoundingBoxAscent,u=l.actualBoundingBoxDescent;if(null!=s&&null!=u)return{height:s+u,ascent:s,descent:u,cap_height:n.actualBoundingBoxAscent,x_height:r.actualBoundingBoxAscent};(0,a.unreachable)()}})(),s=(()=>{const t=c(0,0).getContext(\"2d\");return(e,n)=>{t.font=n;const r=t.measureText(e),l=r.actualBoundingBoxAscent,c=r.actualBoundingBoxDescent;if(null!=l&&null!=c)return{width:r.width,height:l+c,ascent:l,descent:c};(0,a.unreachable)()}})(),u=(()=>{const t=document.createElement(\"canvas\"),e=t.getContext(\"2d\");let n=-1,r=-1;return(l,a=1)=>{e.font=l;const{width:c}=e.measureText(\"M\"),o=c*a,s=Math.ceil(o),u=Math.ceil(2*o),i=Math.ceil(1.5*o);n{let e=0;for(let n=0;n<=i;n++)for(let r=0;r{let e=t.length-4;for(let n=u;n>=i;n--)for(let r=0;r{const t=document.createElement(\"canvas\"),e=t.getContext(\"2d\");let n=-1,r=-1;return(l,a,c=1)=>{e.font=a;const{width:o}=e.measureText(\"M\"),s=o*c,u=Math.ceil(s),i=Math.ceil(2*s),f=Math.ceil(1.5*s);(n{let e=0;for(let n=0;n<=f;n++)for(let r=0;r{let e=t.length-4;for(let n=i;n>=f;n--)for(let r=0;r{try{return o(\"normal 10px sans-serif\"),o}catch(t){return u}})(),h=(()=>{try{return s(\"A\",\"normal 10px sans-serif\"),s}catch(t){return i}})(),g=new Map;function d(t){let e=g.get(t);return null==e&&(e={font:f(t),glyphs:new Map},g.set(t,e)),e.font}n.font_metrics=d,n.glyph_metrics=function(t,e){let n=g.get(e);null==n&&(d(e),n=g.get(e));let r=n.glyphs.get(t);return null==r&&(r=h(t,e),n.glyphs.set(t,r)),r},n.parse_css_font_size=function(t){const e=t.match(/^\\s*(\\d+(\\.\\d+)?)(\\w+)\\s*$/);if(null!=e){const[,t,,n]=e,r=Number(t);if(isFinite(r))return{value:r,unit:n}}return null}},\n", - " function _(t,s,r,n,i){n();const{sin:e,cos:a}=Math;class h{constructor(t=1,s=0,r=0,n=1,i=0,e=0){this.a=t,this.b=s,this.c=r,this.d=n,this.e=i,this.f=e}toString(){const{a:t,b:s,c:r,d:n,e:i,f:e}=this;return`matrix(${t}, ${s}, ${r}, ${n}, ${i}, ${e})`}static from_DOMMatrix(t){const{a:s,b:r,c:n,d:i,e,f:a}=t;return new h(s,r,n,i,e,a)}to_DOMMatrix(){const{a:t,b:s,c:r,d:n,e:i,f:e}=this;return new DOMMatrix([t,s,r,n,i,e])}clone(){const{a:t,b:s,c:r,d:n,e:i,f:e}=this;return new h(t,s,r,n,i,e)}get is_identity(){const{a:t,b:s,c:r,d:n,e:i,f:e}=this;return 1==t&&0==s&&0==r&&1==n&&0==i&&0==e}apply_point(t){const[s,r]=this.apply(t.x,t.y);return{x:s,y:r}}apply_rect(t){return{p0:this.apply_point(t.p0),p1:this.apply_point(t.p1),p2:this.apply_point(t.p2),p3:this.apply_point(t.p3)}}apply(t,s){const{a:r,b:n,c:i,d:e,e:a,f:h}=this;return[r*t+i*s+a,n*t+e*s+h]}iv_apply(t,s){const{a:r,b:n,c:i,d:e,e:a,f:h}=this,c=t.length;for(let o=0;o{const h={max:4,fit:3,min:2,fixed:1};return h[i]>h[t]};if(\"fixed\"!=n&&\"fixed\"!=s)if(n==s){const n=t,s=_(t/e),r=_(h*e),g=h;Math.abs(i.width-n)+Math.abs(i.height-s)<=Math.abs(i.width-r)+Math.abs(i.height-g)?(t=n,h=s):(t=r,h=g)}else r(n,s)?h=_(t/e):t=_(h*e);else\"fixed\"==n?h=_(t/e):\"fixed\"==s&&(t=_(h*e))}return{width:t,height:h}}measure(i){if(!this.sizing.visible)return{width:0,height:0};const t=i=>\"fixed\"==this.sizing.width_policy&&null!=this.sizing.width?this.sizing.width:i,h=i=>\"fixed\"==this.sizing.height_policy&&null!=this.sizing.height?this.sizing.height:i,e=new s.Sizeable(i).shrink_by(this.sizing.margin).map(t,h),n=this._measure(e),r=this.clip_size(n,e),g=t(r.width),l=h(r.height),a=this.apply_aspect(e,{width:g,height:l});return Object.assign(Object.assign({},n),a)}compute(i={}){const t=this.measure({width:null!=i.width&&this.is_width_expanding()?i.width:1/0,height:null!=i.height&&this.is_height_expanding()?i.height:1/0}),{width:h,height:e}=t,n=new r.BBox({left:0,top:0,width:h,height:e});let s;if(null!=t.inner){const{left:i,top:n,right:g,bottom:l}=t.inner;s=new r.BBox({left:i,top:n,right:h-g,bottom:e-l})}this.set_geometry(n,s)}get xview(){return this.bbox.xview}get yview(){return this.bbox.yview}clip_size(i,t){function h(i,t,h,e){return null==h?h=0:(0,g.isNumber)(h)||(h=Math.round(h.percent*t)),null==e?e=1/0:(0,g.isNumber)(e)||(e=Math.round(e.percent*t)),a(h,l(i,e))}return{width:h(i.width,t.width,this.sizing.min_width,this.sizing.max_width),height:h(i.height,t.height,this.sizing.min_height,this.sizing.max_height)}}has_size_changed(){const{_dirty:i}=this;return this._dirty=!1,i}}h.Layoutable=o,o.__name__=\"Layoutable\";class d extends o{_measure(i){const{width_policy:t,height_policy:h}=this.sizing;return{width:(()=>{const{width:h}=this.sizing;if(i.width==1/0)return null!=h?h:0;switch(t){case\"fixed\":return null!=h?h:0;case\"min\":return null!=h?l(i.width,h):0;case\"fit\":return null!=h?l(i.width,h):i.width;case\"max\":return null!=h?a(i.width,h):i.width}})(),height:(()=>{const{height:t}=this.sizing;if(i.height==1/0)return null!=t?t:0;switch(h){case\"fixed\":return null!=t?t:0;case\"min\":return null!=t?l(i.height,t):0;case\"fit\":return null!=t?l(i.height,t):i.height;case\"max\":return null!=t?a(i.height,t):i.height}})()}}}h.LayoutItem=d,d.__name__=\"LayoutItem\";class u extends o{_measure(i){const t=this._content_size(),h=i.bounded_to(this.sizing.size).bounded_to(t);return{width:(()=>{switch(this.sizing.width_policy){case\"fixed\":return null!=this.sizing.width?this.sizing.width:t.width;case\"min\":return t.width;case\"fit\":return h.width;case\"max\":return Math.max(t.width,h.width)}})(),height:(()=>{switch(this.sizing.height_policy){case\"fixed\":return null!=this.sizing.height?this.sizing.height:t.height;case\"min\":return t.height;case\"fit\":return h.height;case\"max\":return Math.max(t.height,h.height)}})()}}}h.ContentLayoutable=u,u.__name__=\"ContentLayoutable\"},\n", - " function _(e,t,s,a,_){a();const r=e(62),n=e(61),g=e(58),i=e(63),c=e(67),h=e(65),l=e(13),o=e(11);class x{constructor(e,t,s,a,_={},r={},n={},g={}){this.in_x_scale=e,this.in_y_scale=t,this.x_range=s,this.y_range=a,this.extra_x_ranges=_,this.extra_y_ranges=r,this.extra_x_scales=n,this.extra_y_scales=g,this._bbox=new h.BBox,(0,o.assert)(null==e.source_range&&null==e.target_range),(0,o.assert)(null==t.source_range&&null==t.target_range),this._configure_scales()}get bbox(){return this._bbox}_get_ranges(e,t){return new Map((0,l.entries)(Object.assign(Object.assign({},t),{default:e})))}_get_scales(e,t,s,a){var _;const g=new Map((0,l.entries)(Object.assign(Object.assign({},t),{default:e}))),h=new Map;for(const[t,l]of s){if(l instanceof c.FactorRange!=e instanceof r.CategoricalScale)throw new Error(`Range ${l.type} is incompatible is Scale ${e.type}`);e instanceof n.LogScale&&l instanceof i.DataRange1d&&(l.scale_hint=\"log\");const s=(null!==(_=g.get(t))&&void 0!==_?_:e).clone();s.setv({source_range:l,target_range:a}),h.set(t,s)}return h}_configure_frame_ranges(){const{bbox:e}=this;this._x_target=new g.Range1d({start:e.left,end:e.right}),this._y_target=new g.Range1d({start:e.bottom,end:e.top})}_configure_scales(){this._configure_frame_ranges(),this._x_ranges=this._get_ranges(this.x_range,this.extra_x_ranges),this._y_ranges=this._get_ranges(this.y_range,this.extra_y_ranges),this._x_scales=this._get_scales(this.in_x_scale,this.extra_x_scales,this._x_ranges,this._x_target),this._y_scales=this._get_scales(this.in_y_scale,this.extra_y_scales,this._y_ranges,this._y_target)}_update_scales(){this._configure_frame_ranges();for(const[,e]of this._x_scales)e.target_range=this._x_target;for(const[,e]of this._y_scales)e.target_range=this._y_target}set_geometry(e){this._bbox=e,this._update_scales()}get x_target(){return this._x_target}get y_target(){return this._y_target}get x_ranges(){return this._x_ranges}get y_ranges(){return this._y_ranges}get x_scales(){return this._x_scales}get y_scales(){return this._y_scales}get x_scale(){return this._x_scales.get(\"default\")}get y_scale(){return this._y_scales.get(\"default\")}get xscales(){return(0,l.to_object)(this.x_scales)}get yscales(){return(0,l.to_object)(this.y_scales)}}s.CartesianFrame=x,x.__name__=\"CartesianFrame\"},\n", - " function _(i,s,x,A,o){A(),o(\"Axis\",i(128).Axis),o(\"CategoricalAxis\",i(140).CategoricalAxis),o(\"ContinuousAxis\",i(143).ContinuousAxis),o(\"DatetimeAxis\",i(144).DatetimeAxis),o(\"LinearAxis\",i(145).LinearAxis),o(\"LogAxis\",i(162).LogAxis),o(\"MercatorAxis\",i(165).MercatorAxis)},\n", - " function _(t,e,i,s,a){s();const o=t(1);var l;const n=t(129),_=t(130),r=t(131),h=t(132),c=(0,o.__importStar)(t(48)),b=t(20),u=t(24),m=t(123),d=t(9),x=t(13),f=t(8),g=t(120),p=t(67),v=t(133),w=t(113),j=t(11),k=t(8),y=t(134),{abs:z}=Math;class M extends n.GuideRendererView{constructor(){super(...arguments),this._axis_label_view=null,this._major_label_views=new Map}async lazy_initialize(){await super.lazy_initialize(),await this._init_axis_label(),await this._init_major_labels()}async _init_axis_label(){const{axis_label:t}=this.model;if(null!=t){const e=(0,k.isString)(t)?(0,y.parse_delimited_string)(t):t;this._axis_label_view=await(0,w.build_view)(e,{parent:this})}else this._axis_label_view=null}async _init_major_labels(){const{major_label_overrides:t}=this.model;for(const[e,i]of(0,x.entries)(t)){const t=(0,k.isString)(i)?(0,y.parse_delimited_string)(i):i;this._major_label_views.set(e,await(0,w.build_view)(t,{parent:this}))}}update_layout(){this.layout=new m.SideLayout(this.panel,(()=>this.get_size()),!0),this.layout.on_resize((()=>this._coordinates=void 0))}get_size(){const{visible:t,fixed_location:e}=this.model;if(t&&null==e&&this.is_renderable){const{extents:t}=this;return{width:0,height:Math.round(t.tick+t.tick_label+t.axis_label)}}return{width:0,height:0}}get is_renderable(){const[t,e]=this.ranges;return t.is_valid&&e.is_valid}_render(){var t;if(!this.is_renderable)return;const{tick_coords:e,extents:i}=this,s=this.layer.ctx;s.save(),this._draw_rule(s,i),this._draw_major_ticks(s,i,e),this._draw_minor_ticks(s,i,e),this._draw_major_labels(s,i,e),this._draw_axis_label(s,i,e),null===(t=this._paint)||void 0===t||t.call(this,s,i,e),s.restore()}connect_signals(){super.connect_signals();const{axis_label:t,major_label_overrides:e}=this.model.properties;this.on_change(t,(async()=>{var t;null===(t=this._axis_label_view)||void 0===t||t.remove(),await this._init_axis_label()})),this.on_change(e,(async()=>{for(const t of this._major_label_views.values())t.remove();await this._init_major_labels()})),this.connect(this.model.change,(()=>this.plot_view.request_layout()))}get needs_clip(){return null!=this.model.fixed_location}_draw_rule(t,e){if(!this.visuals.axis_line.doit)return;const[i,s]=this.rule_coords,[a,o]=this.coordinates.map_to_screen(i,s),[l,n]=this.normals,[_,r]=this.offsets;this.visuals.axis_line.set_value(t),t.beginPath();for(let e=0;e0?s+i+3:0}_draw_axis_label(t,e,i){if(null==this._axis_label_view||null!=this.model.fixed_location)return;const[s,a]=(()=>{const{bbox:t}=this.layout;switch(this.panel.side){case\"above\":return[t.hcenter,t.bottom];case\"below\":return[t.hcenter,t.top];case\"left\":return[t.right,t.vcenter];case\"right\":return[t.left,t.vcenter]}})(),[o,l]=this.normals,n=e.tick+e.tick_label+this.model.axis_label_standoff,{vertical_align:_,align:r}=this.panel.get_label_text_heuristics(\"parallel\"),h={sx:s+o*n,sy:a+l*n,x_anchor:r,y_anchor:_},c=this._axis_label_view.graphics();c.visuals=this.visuals.axis_label_text.values(),c.angle=this.panel.get_label_angle_heuristic(\"parallel\"),this.plot_view.base_font_size&&(c.base_font_size=this.plot_view.base_font_size),c.position=h,c.align=r,c.paint(t)}_draw_ticks(t,e,i,s,a){if(!a.doit)return;const[o,l]=e,[n,_]=this.coordinates.map_to_screen(o,l),[r,h]=this.normals,[c,b]=this.offsets,[u,m]=[r*(c-i),h*(b-i)],[d,x]=[r*(c+s),h*(b+s)];a.set_value(t),t.beginPath();for(let e=0;et.bbox())),M=(()=>{const[t]=this.ranges;return t.is_reversed?0==this.dimension?(t,e)=>z[t].left-z[e].right:(t,e)=>z[e].top-z[t].bottom:0==this.dimension?(t,e)=>z[e].left-z[t].right:(t,e)=>z[t].top-z[e].bottom})(),{major_label_policy:O}=this.model,T=O.filter(k,z,M),A=[...T.ones()];if(0!=A.length){const t=this.parent.canvas_view.bbox,e=e=>{const i=z[e];if(i.left<0){const t=-i.left,{position:s}=y[e];y[e].position=Object.assign(Object.assign({},s),{sx:s.sx+t})}else if(i.right>t.width){const s=i.right-t.width,{position:a}=y[e];y[e].position=Object.assign(Object.assign({},a),{sx:a.sx-s})}},i=e=>{const i=z[e];if(i.top<0){const t=-i.top,{position:s}=y[e];y[e].position=Object.assign(Object.assign({},s),{sy:s.sy+t})}else if(i.bottom>t.height){const s=i.bottom-t.height,{position:a}=y[e];y[e].position=Object.assign(Object.assign({},a),{sy:a.sy-s})}},s=A[0],a=A[A.length-1];0==this.dimension?(e(s),e(a)):(i(s),i(a))}for(const e of T){y[e].paint(t)}}_tick_extent(){return this.model.major_tick_out}_tick_label_extents(){const t=this.tick_coords.major,e=this.compute_labels(t[this.dimension]),i=this.model.major_label_orientation,s=this.model.major_label_standoff,a=this.visuals.major_label_text;return[this._oriented_labels_extent(e,i,s,a)]}get extents(){const t=this._tick_label_extents();return{tick:this._tick_extent(),tick_labels:t,tick_label:(0,d.sum)(t),axis_label:this._axis_label_extent()}}_oriented_labels_extent(t,e,i,s){if(0==t.length||!s.doit)return 0;const a=this.panel.get_label_angle_heuristic(e);t.visuals=s.values(),t.angle=a,t.base_font_size=this.plot_view.base_font_size;const o=t.max_size(),l=0==this.dimension?o.height:o.width;return l>0?i+l+3:0}get normals(){return this.panel.normals}get dimension(){return this.panel.dimension}compute_labels(t){const e=this.model.formatter.format_graphics(t,this),{_major_label_views:i}=this,s=new Set;for(let a=0;az(l-n)?(t=r(_(a,o),l),s=_(r(a,o),n)):(t=_(a,o),s=r(a,o)),[t,s]}}get rule_coords(){const t=this.dimension,e=(t+1)%2,[i]=this.ranges,[s,a]=this.computed_bounds,o=[new Array(2),new Array(2)];return o[t][0]=Math.max(s,i.min),o[t][1]=Math.min(a,i.max),o[t][0]>o[t][1]&&(o[t][0]=o[t][1]=NaN),o[e][0]=this.loc,o[e][1]=this.loc,o}get tick_coords(){const t=this.dimension,e=(t+1)%2,[i]=this.ranges,[s,a]=this.computed_bounds,o=this.model.ticker.get_ticks(s,a,i,this.loc),l=o.major,n=o.minor,_=[[],[]],r=[[],[]],[h,c]=[i.min,i.max];for(let i=0;ic||(_[t].push(l[i]),_[e].push(this.loc));for(let i=0;ic||(r[t].push(n[i]),r[e].push(this.loc));return{major:_,minor:r}}get loc(){const{fixed_location:t}=this.model;if(null!=t){if((0,f.isNumber)(t))return t;const[,e]=this.ranges;if(e instanceof p.FactorRange)return e.synthetic(t);(0,j.unreachable)()}const[,e]=this.ranges;switch(this.panel.side){case\"left\":case\"below\":return e.start;case\"right\":case\"above\":return e.end}}serializable_state(){return Object.assign(Object.assign({},super.serializable_state()),{bbox:this.layout.bbox.box})}remove(){var t;null===(t=this._axis_label_view)||void 0===t||t.remove();for(const t of this._major_label_views.values())t.remove();super.remove()}has_finished(){if(!super.has_finished())return!1;if(null!=this._axis_label_view&&!this._axis_label_view.has_finished())return!1;for(const t of this._major_label_views.values())if(!t.has_finished())return!1;return!0}}i.AxisView=M,M.__name__=\"AxisView\";class O extends n.GuideRenderer{constructor(t){super(t)}}i.Axis=O,l=O,O.__name__=\"Axis\",l.prototype.default_view=M,l.mixins([[\"axis_\",c.Line],[\"major_tick_\",c.Line],[\"minor_tick_\",c.Line],[\"major_label_\",c.Text],[\"axis_label_\",c.Text]]),l.define((({Any:t,Int:e,Number:i,String:s,Ref:a,Dict:o,Tuple:l,Or:n,Nullable:c,Auto:u})=>({bounds:[n(l(i,i),u),\"auto\"],ticker:[a(_.Ticker)],formatter:[a(r.TickFormatter)],axis_label:[c(n(s,a(v.BaseText))),null],axis_label_standoff:[e,5],major_label_standoff:[e,5],major_label_orientation:[n(b.TickLabelOrientation,i),\"horizontal\"],major_label_overrides:[o(n(s,a(v.BaseText))),{}],major_label_policy:[a(h.LabelingPolicy),()=>new h.AllLabels],major_tick_in:[i,2],major_tick_out:[i,6],minor_tick_in:[i,0],minor_tick_out:[i,4],fixed_location:[c(n(i,t)),null]}))),l.override({axis_line_color:\"black\",major_tick_line_color:\"black\",minor_tick_line_color:\"black\",major_label_text_font_size:\"11px\",major_label_text_align:\"center\",major_label_text_baseline:\"alphabetic\",axis_label_text_font_size:\"13px\",axis_label_text_font_style:\"italic\"})},\n", - " function _(e,r,d,n,i){var s;n();const _=e(41);class u extends _.RendererView{}d.GuideRendererView=u,u.__name__=\"GuideRendererView\";class c extends _.Renderer{constructor(e){super(e)}}d.GuideRenderer=c,s=c,c.__name__=\"GuideRenderer\",s.override({level:\"guide\"})},\n", - " function _(c,e,n,s,o){s();const r=c(53);class t extends r.Model{constructor(c){super(c)}}n.Ticker=t,t.__name__=\"Ticker\"},\n", - " function _(t,o,r,e,c){e();const n=t(53),a=t(120);class m extends n.Model{constructor(t){super(t)}format_graphics(t,o){return this.doFormat(t,o).map((t=>new a.TextBox({text:t})))}compute(t,o){return this.doFormat([t],null!=o?o:{loc:0})[0]}v_compute(t,o){return this.doFormat(t,null!=o?o:{loc:0})}}r.TickFormatter=m,m.__name__=\"TickFormatter\"},\n", - " function _(e,n,s,t,i){var c,r;t();const l=e(53),o=e(13),a=e(34),u=e(8),d=e(24);class _ extends l.Model{constructor(e){super(e)}}s.LabelingPolicy=_,_.__name__=\"LabelingPolicy\";class f extends _{constructor(e){super(e)}filter(e,n,s){return e}}s.AllLabels=f,f.__name__=\"AllLabels\";class m extends _{constructor(e){super(e)}filter(e,n,s){const{min_distance:t}=this;let i=null;for(const n of e)null!=i&&s(i,n)({min_distance:[e,5]})));class b extends _{constructor(e){super(e)}get names(){return(0,o.keys)(this.args)}get values(){return(0,o.values)(this.args)}get func(){const e=(0,a.use_strict)(this.code);return new d.GeneratorFunction(\"indices\",\"bboxes\",\"distance\",...this.names,e)}filter(e,n,s){const t=Object.create(null),i=this.func.call(t,e,n,s,...this.values);let c=i.next();if(c.done&&void 0!==c.value){const{value:n}=c;return n instanceof d.Indices?n:void 0===n?e:(0,u.isIterable)(n)?d.Indices.from_indices(e.size,n):d.Indices.all_unset(e.size)}{const n=[];do{n.push(c.value),c=i.next()}while(!c.done);return d.Indices.from_indices(e.size,n)}}}s.CustomLabelingPolicy=b,r=b,b.__name__=\"CustomLabelingPolicy\",r.define((({Unknown:e,String:n,Dict:s})=>({args:[s(e),{}],code:[n,\"\"]})))},\n", - " function _(e,s,t,n,a){var _;n();const x=e(53),c=e(42);class i extends c.View{}t.BaseTextView=i,i.__name__=\"BaseTextView\";class o extends x.Model{constructor(e){super(e)}}t.BaseText=o,_=o,o.__name__=\"BaseText\",_.define((({String:e})=>({text:[e]})))},\n", - " function _(n,e,t,i,r){i();const s=n(135),l=n(139),d=[{start:\"$$\",end:\"$$\",inline:!1},{start:\"\\\\[\",end:\"\\\\]\",inline:!1},{start:\"\\\\(\",end:\"\\\\)\",inline:!0}];t.parse_delimited_string=function(n){for(const e of d){const t=n.indexOf(e.start),i=t+e.start.length;if(0==t){const t=n.indexOf(e.end,i),r=t;if(t==n.length-e.end.length)return new s.TeX({text:n.slice(i,r),inline:e.inline});break}}return new l.PlainText({text:n})}},\n", - " function _(t,e,s,i,n){var o,r,a;i();const h=t(8),_=t(136),l=t(22),c=t(120),d=t(121),u=t(122),g=t(65),p=t(133),x=t(137);class m extends p.BaseTextView{constructor(){super(...arguments),this._position={sx:0,sy:0},this.align=\"left\",this._x_anchor=\"left\",this._y_anchor=\"center\",this._base_font_size=13,this.font_size_scale=1,this.svg_image=null}graphics(){return this}infer_text_height(){return\"ascent_descent\"}set base_font_size(t){null!=t&&(this._base_font_size=t)}get base_font_size(){return this._base_font_size}get has_image_loaded(){return null!=this.svg_image}_rect(){const{width:t,height:e}=this._size(),{x:s,y:i}=this._computed_position();return new g.BBox({x:s,y:i,width:t,height:e}).rect}set position(t){this._position=t}get position(){return this._position}get text(){return this.model.text}get provider(){return x.default_provider}async lazy_initialize(){await super.lazy_initialize(),\"not_started\"==this.provider.status&&await this.provider.fetch(),\"not_started\"!=this.provider.status&&\"loading\"!=this.provider.status||this.provider.ready.connect((()=>this.load_image())),\"loaded\"==this.provider.status&&await this.load_image()}connect_signals(){super.connect_signals(),this.on_change(this.model.properties.text,(()=>this.load_image()))}set visuals(t){const e=t.color,s=t.alpha,i=t.font_style;let n=t.font_size;const o=t.font,{font_size_scale:r,_base_font_size:a}=this,h=(0,d.parse_css_font_size)(n);if(null!=h){let{value:t,unit:e}=h;t*=r,\"em\"==e&&a&&(t*=a,e=\"px\"),n=`${t}${e}`}const _=`${i} ${n} ${o}`;this.font=_,this.color=(0,l.color2css)(e,s)}_computed_position(){const{width:t,height:e}=this._size(),{sx:s,sy:i,x_anchor:n=this._x_anchor,y_anchor:o=this._y_anchor}=this.position;return{x:s-(()=>{if((0,h.isNumber)(n))return n*t;switch(n){case\"left\":return 0;case\"center\":return.5*t;case\"right\":return t}})(),y:i-(()=>{if((0,h.isNumber)(o))return o*e;switch(o){case\"top\":return 0;case\"center\":return.5*e;case\"bottom\":return e;case\"baseline\":return.5*e}})()}}size(){const{width:t,height:e}=this._size(),{angle:s}=this;if(s){const i=Math.cos(Math.abs(s)),n=Math.sin(Math.abs(s));return{width:Math.abs(t*i+e*n),height:Math.abs(t*n+e*i)}}return{width:t,height:e}}get_text_dimensions(){return{width:(0,c.text_width)(this.model.text,this.font),height:(0,d.font_metrics)(this.font).height}}get_image_dimensions(){var t,e,s,i;const n=parseFloat(null!==(e=null===(t=this.svg_element.getAttribute(\"height\"))||void 0===t?void 0:t.replace(/([A-z])/g,\"\"))&&void 0!==e?e:\"0\"),o=parseFloat(null!==(i=null===(s=this.svg_element.getAttribute(\"width\"))||void 0===s?void 0:s.replace(/([A-z])/g,\"\"))&&void 0!==i?i:\"0\");return{width:(0,d.font_metrics)(this.font).x_height*o,height:(0,d.font_metrics)(this.font).x_height*n}}_size(){return this.has_image_loaded?this.get_image_dimensions():this.get_text_dimensions()}bbox(){const{p0:t,p1:e,p2:s,p3:i}=this.rect(),n=Math.min(t.x,e.x,s.x,i.x),o=Math.min(t.y,e.y,s.y,i.y),r=Math.max(t.x,e.x,s.x,i.x),a=Math.max(t.y,e.y,s.y,i.y);return new g.BBox({left:n,right:r,top:o,bottom:a})}rect(){const t=this._rect(),{angle:e}=this;if(e){const{sx:s,sy:i}=this.position,n=new u.AffineTransform;return n.translate(s,i),n.rotate(e),n.translate(-s,-i),n.apply_rect(t)}return t}paint_rect(t){const{p0:e,p1:s,p2:i,p3:n}=this.rect();t.save(),t.strokeStyle=\"red\",t.lineWidth=1,t.beginPath();const{round:o}=Math;t.moveTo(o(e.x),o(e.y)),t.lineTo(o(s.x),o(s.y)),t.lineTo(o(i.x),o(i.y)),t.lineTo(o(n.x),o(n.y)),t.closePath(),t.stroke(),t.restore()}paint_bbox(t){const{x:e,y:s,width:i,height:n}=this.bbox();t.save(),t.strokeStyle=\"blue\",t.lineWidth=1,t.beginPath();const{round:o}=Math;t.moveTo(o(e),o(s)),t.lineTo(o(e),o(s+n)),t.lineTo(o(e+i),o(s+n)),t.lineTo(o(e+i),o(s)),t.closePath(),t.stroke(),t.restore()}async load_image(){if(null==this.provider.MathJax)return null;const t=this._process_text(this.model.text);if(null==t)return this._has_finished=!0,null;const e=t.children[0];this.svg_element=e,e.setAttribute(\"font\",this.font),e.setAttribute(\"stroke\",this.color);const s=e.outerHTML,i=new Blob([s],{type:\"image/svg+xml\"}),n=URL.createObjectURL(i);try{this.svg_image=await(0,_.load_image)(n)}finally{URL.revokeObjectURL(n)}return this.parent.request_layout(),this.svg_image}paint(t){t.save();const{sx:e,sy:s}=this.position;this.angle&&(t.translate(e,s),t.rotate(this.angle),t.translate(-e,-s));const{x:i,y:n}=this._computed_position();if(null!=this.svg_image){const{width:e,height:s}=this.get_image_dimensions();t.drawImage(this.svg_image,i,n,e,s)}else t.fillStyle=this.color,t.font=this.font,t.textAlign=\"left\",t.textBaseline=\"alphabetic\",t.fillText(this.model.text,i,n+(0,d.font_metrics)(this.font).ascent);t.restore(),this._has_finished||\"failed\"!=this.provider.status&&!this.has_image_loaded||(this._has_finished=!0,this.parent.notify_finished_after_paint())}}s.MathTextView=m,m.__name__=\"MathTextView\";class f extends p.BaseText{constructor(t){super(t)}}s.MathText=f,f.__name__=\"MathText\";class v extends m{_process_text(t){}}s.AsciiView=v,v.__name__=\"AsciiView\";class y extends f{constructor(t){super(t)}}s.Ascii=y,o=y,y.__name__=\"Ascii\",o.prototype.default_view=v;class w extends m{_process_text(t){var e;return null===(e=this.provider.MathJax)||void 0===e?void 0:e.mathml2svg(t.trim())}}s.MathMLView=w,w.__name__=\"MathMLView\";class b extends f{constructor(t){super(t)}}s.MathML=b,r=b,b.__name__=\"MathML\",r.prototype.default_view=w;class M extends m{_process_text(t){var e;return null===(e=this.provider.MathJax)||void 0===e?void 0:e.tex2svg(t,void 0,this.model.macros)}}s.TeXView=M,M.__name__=\"TeXView\";class T extends f{constructor(t){super(t)}}s.TeX=T,a=T,T.__name__=\"TeX\",a.prototype.default_view=M,a.define((({Boolean:t,Number:e,String:s,Dict:i,Tuple:n,Or:o})=>({macros:[i(o(s,n(s,e))),{}],inline:[t,!1]})))},\n", - " function _(i,e,t,s,o){s();const a=i(19);t.load_image=async function(i,e){return new n(i,e).promise};class n{constructor(i,e={}){this._image=new Image,this._finished=!1;const{attempts:t=1,timeout:s=1}=e;this.promise=new Promise(((o,n)=>{this._image.crossOrigin=\"anonymous\";let r=0;this._image.onerror=()=>{if(++r==t){const s=`unable to load ${i} image after ${t} attempts`;if(a.logger.warn(s),null==this._image.crossOrigin)return void(null!=e.failed&&e.failed());a.logger.warn(`attempting to load ${i} without a cross origin policy`),this._image.crossOrigin=null,r=0}setTimeout((()=>this._image.src=i),s)},this._image.onload=()=>{this._finished=!0,null!=e.loaded&&e.loaded(this._image),o(this._image)},this._image.src=i}))}get finished(){return this._finished}get image(){if(this._finished)return this._image;throw new Error(\"not loaded yet\")}}t.ImageLoader=n,n.__name__=\"ImageLoader\"},\n", - " function _(t,e,a,s,n){var r=this&&this.__createBinding||(Object.create?function(t,e,a,s){void 0===s&&(s=a),Object.defineProperty(t,s,{enumerable:!0,get:function(){return e[a]}})}:function(t,e,a,s){void 0===s&&(s=a),t[s]=e[a]}),i=this&&this.__setModuleDefault||(Object.create?function(t,e){Object.defineProperty(t,\"default\",{enumerable:!0,value:e})}:function(t,e){t.default=e}),d=this&&this.__importStar||function(t){if(t&&t.__esModule)return t;var e={};if(null!=t)for(var a in t)\"default\"!==a&&Object.prototype.hasOwnProperty.call(t,a)&&r(e,t,a);return i(e,t),e};s();const o=t(15),u=t(138);class c{constructor(){this.ready=new o.Signal0(this,\"ready\"),this.status=\"not_started\"}}a.MathJaxProvider=c,c.__name__=\"MathJaxProvider\";class h extends c{get MathJax(){return null}async fetch(){this.status=\"failed\"}}a.NoProvider=h,h.__name__=\"NoProvider\";class l extends c{get MathJax(){return\"undefined\"!=typeof MathJax?MathJax:null}async fetch(){const t=document.createElement(\"script\");t.src=\"https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-svg.js\",t.onload=()=>{this.status=\"loaded\",this.ready.emit()},t.onerror=()=>{this.status=\"failed\"},this.status=\"loading\",document.head.appendChild(t)}}a.CDNProvider=l,l.__name__=\"CDNProvider\";class _ extends c{get MathJax(){return this._mathjax}async fetch(){this.status=\"loading\";try{const e=await(0,u.load_module)(Promise.resolve().then((()=>d(t(515)))));this._mathjax=e,this.status=\"loaded\",this.ready.emit()}catch(t){this.status=\"failed\"}}}a.BundleProvider=_,_.__name__=\"BundleProvider\",a.default_provider=new _},\n", - " function _(n,r,o,t,c){t(),o.load_module=async function(n){try{return await n}catch(n){if((r=n)instanceof Error&&\"code\"in r&&\"MODULE_NOT_FOUND\"===n.code)return null;throw n}var r}},\n", - " function _(e,t,i,n,s){var a;n();const x=e(133),_=e(120);class l extends x.BaseTextView{initialize(){super.initialize(),this._has_finished=!0}graphics(){return new _.TextBox({text:this.model.text})}}i.PlainTextView=l,l.__name__=\"PlainTextView\";class r extends x.BaseText{constructor(e){super(e)}}i.PlainText=r,a=r,r.__name__=\"PlainText\",a.prototype.default_view=l},\n", - " function _(t,s,o,e,i){e();const r=t(1);var a;const l=t(128),_=t(141),n=t(142),p=(0,r.__importStar)(t(48)),c=t(20),h=t(120),m=t(8);class u extends l.AxisView{_paint(t,s,o){this._draw_group_separators(t,s,o)}_draw_group_separators(t,s,o){const[e]=this.ranges,[i,r]=this.computed_bounds;if(!e.tops||e.tops.length<2||!this.visuals.separator_line.doit)return;const a=this.dimension,l=(a+1)%2,_=[[],[]];let n=0;for(let t=0;ti&&pnew h.GraphicsBoxes(t.map((t=>(0,m.isString)(t)?new h.TextBox({text:t}):t))),_=t=>l(this.model.formatter.doFormat(t,this));if(1==t.levels){const t=_(i.major);a.push([t,r.major,this.model.major_label_orientation,this.visuals.major_label_text])}else if(2==t.levels){const t=_(i.major.map((t=>t[1])));a.push([t,r.major,this.model.major_label_orientation,this.visuals.major_label_text]),a.push([l(i.tops),r.tops,this.model.group_label_orientation,this.visuals.group_text])}else if(3==t.levels){const t=_(i.major.map((t=>t[2]))),s=i.mids.map((t=>t[1]));a.push([t,r.major,this.model.major_label_orientation,this.visuals.major_label_text]),a.push([l(s),r.mids,this.model.subgroup_label_orientation,this.visuals.subgroup_text]),a.push([l(i.tops),r.tops,this.model.group_label_orientation,this.visuals.group_text])}return a}get tick_coords(){const t=this.dimension,s=(t+1)%2,[o]=this.ranges,[e,i]=this.computed_bounds,r=this.model.ticker.get_ticks(e,i,o,this.loc),a={major:[[],[]],mids:[[],[]],tops:[[],[]],minor:[[],[]]};return a.major[t]=r.major,a.major[s]=r.major.map((()=>this.loc)),3==o.levels&&(a.mids[t]=r.mids,a.mids[s]=r.mids.map((()=>this.loc))),o.levels>1&&(a.tops[t]=r.tops,a.tops[s]=r.tops.map((()=>this.loc))),a}}o.CategoricalAxisView=u,u.__name__=\"CategoricalAxisView\";class d extends l.Axis{constructor(t){super(t)}}o.CategoricalAxis=d,a=d,d.__name__=\"CategoricalAxis\",a.prototype.default_view=u,a.mixins([[\"separator_\",p.Line],[\"group_\",p.Text],[\"subgroup_\",p.Text]]),a.define((({Number:t,Or:s})=>({group_label_orientation:[s(c.TickLabelOrientation,t),\"parallel\"],subgroup_label_orientation:[s(c.TickLabelOrientation,t),\"parallel\"]}))),a.override({ticker:()=>new _.CategoricalTicker,formatter:()=>new n.CategoricalTickFormatter,separator_line_color:\"lightgrey\",separator_line_width:2,group_text_font_style:\"bold\",group_text_font_size:\"11px\",group_text_color:\"grey\",subgroup_text_font_style:\"bold\",subgroup_text_font_size:\"11px\"})},\n", - " function _(t,c,o,s,e){s();const r=t(130);class i extends r.Ticker{constructor(t){super(t)}get_ticks(t,c,o,s){var e,r;return{major:this._collect(o.factors,o,t,c),minor:[],tops:this._collect(null!==(e=o.tops)&&void 0!==e?e:[],o,t,c),mids:this._collect(null!==(r=o.mids)&&void 0!==r?r:[],o,t,c)}}_collect(t,c,o,s){const e=[];for(const r of t){const t=c.synthetic(r);t>o&&tnew _.DatetimeTicker,formatter:()=>new m.DatetimeTickFormatter})},\n", - " function _(e,i,s,n,r){var t;n();const a=e(143),o=e(146),c=e(147);class _ extends a.ContinuousAxisView{}s.LinearAxisView=_,_.__name__=\"LinearAxisView\";class u extends a.ContinuousAxis{constructor(e){super(e)}}s.LinearAxis=u,t=u,u.__name__=\"LinearAxis\",t.prototype.default_view=_,t.override({ticker:()=>new c.BasicTicker,formatter:()=>new o.BasicTickFormatter})},\n", - " function _(i,t,e,n,o){var r;n();const s=i(131),c=i(34);function _(i){let t=\"\";for(const e of i)t+=\"-\"==e?\"\\u2212\":e;return t}e.unicode_replace=_;class a extends s.TickFormatter{constructor(i){super(i),this.last_precision=3}get scientific_limit_low(){return 10**this.power_limit_low}get scientific_limit_high(){return 10**this.power_limit_high}_need_sci(i){if(!this.use_scientific)return!1;const{scientific_limit_high:t}=this,{scientific_limit_low:e}=this,n=i.length<2?0:Math.abs(i[1]-i[0])/1e4;for(const o of i){const i=Math.abs(o);if(!(i<=n)&&(i>=t||i<=e))return!0}return!1}_format_with_precision(i,t,e){return t?i.map((i=>_(i.toExponential(e)))):i.map((i=>_((0,c.to_fixed)(i,e))))}_auto_precision(i,t){const e=new Array(i.length),n=this.last_precision<=15;i:for(let o=this.last_precision;n?o<=15:o>=1;n?o++:o--){if(t){e[0]=i[0].toExponential(o);for(let t=1;t({precision:[n(t,e),\"auto\"],use_scientific:[i,!0],power_limit_high:[t,5],power_limit_low:[t,-3]})))},\n", - " function _(c,e,s,i,n){i();const r=c(148);class t extends r.AdaptiveTicker{constructor(c){super(c)}}s.BasicTicker=t,t.__name__=\"BasicTicker\"},\n", - " function _(t,i,a,s,e){var n;s();const r=t(149),_=t(9),l=t(10);class h extends r.ContinuousTicker{constructor(t){super(t)}get_min_interval(){return this.min_interval}get_max_interval(){var t;return null!==(t=this.max_interval)&&void 0!==t?t:1/0}initialize(){super.initialize();const t=(0,_.nth)(this.mantissas,-1)/this.base,i=(0,_.nth)(this.mantissas,0)*this.base;this.extended_mantissas=[t,...this.mantissas,i],this.base_factor=0===this.get_min_interval()?1:this.get_min_interval()}get_interval(t,i,a){const s=i-t,e=this.get_ideal_interval(t,i,a),n=Math.floor((0,l.log)(e/this.base_factor,this.base)),r=this.base**n*this.base_factor,h=this.extended_mantissas,m=h.map((t=>Math.abs(a-s/(t*r)))),v=h[(0,_.argmin)(m)]*r;return(0,l.clamp)(v,this.get_min_interval(),this.get_max_interval())}}a.AdaptiveTicker=h,n=h,h.__name__=\"AdaptiveTicker\",n.define((({Number:t,Array:i,Nullable:a})=>({base:[t,10],mantissas:[i(t),[1,2,5]],min_interval:[t,0],max_interval:[a(t),null]})))},\n", - " function _(t,n,i,s,e){var o;s();const r=t(130),c=t(9);class _ extends r.Ticker{constructor(t){super(t)}get_ticks(t,n,i,s){return this.get_ticks_no_defaults(t,n,s,this.desired_num_ticks)}get_ticks_no_defaults(t,n,i,s){const e=this.get_interval(t,n,s),o=Math.floor(t/e),r=Math.ceil(n/e);let _;_=isFinite(o)&&isFinite(r)?(0,c.range)(o,r+1):[];const u=_.map((t=>t*e)).filter((i=>t<=i&&i<=n)),a=this.num_minor_ticks,f=[];if(a>0&&u.length>0){const i=e/a,s=(0,c.range)(0,a).map((t=>t*i));for(const i of s.slice(1)){const s=u[0]-i;t<=s&&s<=n&&f.push(s)}for(const i of u)for(const e of s){const s=i+e;t<=s&&s<=n&&f.push(s)}}return{major:u,minor:f}}get_ideal_interval(t,n,i){return(n-t)/i}}i.ContinuousTicker=_,o=_,_.__name__=\"ContinuousTicker\",o.define((({Int:t})=>({num_minor_ticks:[t,5],desired_num_ticks:[t,6]})))},\n", - " function _(s,t,e,n,i){n();var r;const o=(0,s(1).__importDefault)(s(151)),a=s(131),c=s(19),u=s(152),m=s(9),h=s(8);function d(s){return(0,o.default)(s,\"%Y %m %d %H %M %S\").split(/\\s+/).map((s=>parseInt(s,10)))}function l(s,t){if((0,h.isFunction)(t))return t(s);{const e=(0,u.sprintf)(\"$1%06d\",function(s){return Math.round(s/1e3%1*1e6)}(s));return-1==(t=t.replace(/((^|[^%])(%%)*)%f/,e)).indexOf(\"%\")?t:(0,o.default)(s,t)}}const f=[\"microseconds\",\"milliseconds\",\"seconds\",\"minsec\",\"minutes\",\"hourmin\",\"hours\",\"days\",\"months\",\"years\"];class _ extends a.TickFormatter{constructor(s){super(s),this.strip_leading_zeros=!0}initialize(){super.initialize(),this._update_width_formats()}_update_width_formats(){const s=+(0,o.default)(new Date),t=function(t){const e=t.map((t=>l(s,t).length)),n=(0,m.sort_by)((0,m.zip)(e,t),(([s])=>s));return(0,m.unzip)(n)};this._width_formats={microseconds:t(this.microseconds),milliseconds:t(this.milliseconds),seconds:t(this.seconds),minsec:t(this.minsec),minutes:t(this.minutes),hourmin:t(this.hourmin),hours:t(this.hours),days:t(this.days),months:t(this.months),years:t(this.years)}}_get_resolution_str(s,t){const e=1.1*s;switch(!1){case!(e<.001):return\"microseconds\";case!(e<1):return\"milliseconds\";case!(e<60):return t>=60?\"minsec\":\"seconds\";case!(e<3600):return t>=3600?\"hourmin\":\"minutes\";case!(e<86400):return\"hours\";case!(e<2678400):return\"days\";case!(e<31536e3):return\"months\";default:return\"years\"}}doFormat(s,t){if(0==s.length)return[];const e=Math.abs(s[s.length-1]-s[0])/1e3,n=e/(s.length-1),i=this._get_resolution_str(n,e),[,[r]]=this._width_formats[i],o=[],a=f.indexOf(i),u={};for(const s of f)u[s]=0;u.seconds=5,u.minsec=4,u.minutes=4,u.hourmin=3,u.hours=3;for(const t of s){let s,e;try{e=d(t),s=l(t,r)}catch(s){c.logger.warn(`unable to format tick for timestamp value ${t}`),c.logger.warn(` - ${s}`),o.push(\"ERR\");continue}let n=!1,m=a;for(;0==e[u[f[m]]];){let r;if(m+=1,m==f.length)break;if((\"minsec\"==i||\"hourmin\"==i)&&!n){if(\"minsec\"==i&&0==e[4]&&0!=e[5]||\"hourmin\"==i&&0==e[3]&&0!=e[4]){r=this._width_formats[f[a-1]][1][0],s=l(t,r);break}n=!0}r=this._width_formats[f[m]][1][0],s=l(t,r)}if(this.strip_leading_zeros){let t=s.replace(/^0+/g,\"\");t!=s&&isNaN(parseInt(t))&&(t=`0${t}`),o.push(t)}else o.push(s)}return o}}e.DatetimeTickFormatter=_,r=_,_.__name__=\"DatetimeTickFormatter\",r.define((({String:s,Array:t})=>({microseconds:[t(s),[\"%fus\"]],milliseconds:[t(s),[\"%3Nms\",\"%S.%3Ns\"]],seconds:[t(s),[\"%Ss\"]],minsec:[t(s),[\":%M:%S\"]],minutes:[t(s),[\":%M\",\"%Mm\"]],hourmin:[t(s),[\"%H:%M\"]],hours:[t(s),[\"%Hh\",\"%H:%M\"]],days:[t(s),[\"%m/%d\",\"%a%d\"]],months:[t(s),[\"%m/%Y\",\"%b %Y\"]],years:[t(s),[\"%Y\"]]})))},\n", - " function _(e,t,n,r,o){!function(e){\"object\"==typeof t&&t.exports?t.exports=e():\"function\"==typeof define?define(e):this.tz=e()}((function(){function e(e,t,n){var r,o=t.day[1];do{r=new 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c.AdaptiveTicker({mantissas:[1,2,4,6,8,12],base:24,min_interval:T.ONE_HOUR,max_interval:12*T.ONE_HOUR,num_minor_ticks:0}),new _.DaysTicker({days:(0,t.range)(1,32)}),new _.DaysTicker({days:(0,t.range)(1,31,3)}),new _.DaysTicker({days:[1,8,15,22]}),new _.DaysTicker({days:[1,15]}),new k.MonthsTicker({months:(0,t.range)(0,12,1)}),new k.MonthsTicker({months:(0,t.range)(0,12,2)}),new k.MonthsTicker({months:(0,t.range)(0,12,4)}),new k.MonthsTicker({months:(0,t.range)(0,12,6)}),new o.YearsTicker({})]})},\n", - " function _(t,e,i,r,s){var n;r();const _=t(149),a=t(9);class l extends _.ContinuousTicker{constructor(t){super(t)}get min_intervals(){return this.tickers.map((t=>t.get_min_interval()))}get max_intervals(){return this.tickers.map((t=>t.get_max_interval()))}get_min_interval(){return this.min_intervals[0]}get_max_interval(){return this.max_intervals[0]}get_best_ticker(t,e,i){const r=e-t,s=this.get_ideal_interval(t,e,i),n=[(0,a.sorted_index)(this.min_intervals,s)-1,(0,a.sorted_index)(this.max_intervals,s)],_=[this.min_intervals[n[0]],this.max_intervals[n[1]]].map((t=>Math.abs(i-r/t)));let l;if((0,a.is_empty)(_.filter((t=>!isNaN(t)))))l=this.tickers[0];else{const t=n[(0,a.argmin)(_)];l=this.tickers[t]}return l}get_interval(t,e,i){return this.get_best_ticker(t,e,i).get_interval(t,e,i)}get_ticks_no_defaults(t,e,i,r){return this.get_best_ticker(t,e,r).get_ticks_no_defaults(t,e,i,r)}}i.CompositeTicker=l,n=l,l.__name__=\"CompositeTicker\",n.define((({Array:t,Ref:e})=>({tickers:[t(e(_.ContinuousTicker)),[]]})))},\n", - " function _(t,e,n,s,o){var a;s();const i=t(158),r=t(159),c=t(9);class _ extends i.SingleIntervalTicker{constructor(t){super(t)}initialize(){super.initialize();const t=this.days;t.length>1?this.interval=(t[1]-t[0])*r.ONE_DAY:this.interval=31*r.ONE_DAY}get_ticks_no_defaults(t,e,n,s){const o=function(t,e){const n=(0,r.last_month_no_later_than)(new Date(t)),s=(0,r.last_month_no_later_than)(new Date(e));s.setUTCMonth(s.getUTCMonth()+1);const o=[],a=n;for(;o.push((0,r.copy_date)(a)),a.setUTCMonth(a.getUTCMonth()+1),!(a>s););return o}(t,e),a=this.days,i=this.interval,_=(0,c.concat)(o.map((t=>((t,e)=>{const n=t.getUTCMonth(),s=[];for(const o of a){const a=(0,r.copy_date)(t);a.setUTCDate(o),new Date(a.getTime()+e/2).getUTCMonth()==n&&s.push(a)}return s})(t,i))));return{major:_.map((t=>t.getTime())).filter((n=>t<=n&&n<=e)),minor:[]}}}n.DaysTicker=_,a=_,_.__name__=\"DaysTicker\",a.define((({Int:t,Array:e})=>({days:[e(t),[]]}))),a.override({num_minor_ticks:0})},\n", - " function _(e,n,t,r,i){var a;r();const l=e(149);class s extends l.ContinuousTicker{constructor(e){super(e)}get_interval(e,n,t){return this.interval}get_min_interval(){return this.interval}get_max_interval(){return this.interval}}t.SingleIntervalTicker=s,a=s,s.__name__=\"SingleIntervalTicker\",a.define((({Number:e})=>({interval:[e]})))},\n", - " function _(t,n,e,_,E){function N(t){return new Date(t.getTime())}function O(t){const n=N(t);return n.setUTCDate(1),n.setUTCHours(0),n.setUTCMinutes(0),n.setUTCSeconds(0),n.setUTCMilliseconds(0),n}_(),e.ONE_MILLI=1,e.ONE_SECOND=1e3,e.ONE_MINUTE=60*e.ONE_SECOND,e.ONE_HOUR=60*e.ONE_MINUTE,e.ONE_DAY=24*e.ONE_HOUR,e.ONE_MONTH=30*e.ONE_DAY,e.ONE_YEAR=365*e.ONE_DAY,e.copy_date=N,e.last_month_no_later_than=O,e.last_year_no_later_than=function(t){const n=O(t);return n.setUTCMonth(0),n}},\n", - " function _(t,e,n,a,r){var s;a();const i=t(158),o=t(159),l=t(9);class _ extends i.SingleIntervalTicker{constructor(t){super(t)}initialize(){super.initialize();const t=this.months;t.length>1?this.interval=(t[1]-t[0])*o.ONE_MONTH:this.interval=12*o.ONE_MONTH}get_ticks_no_defaults(t,e,n,a){const r=function(t,e){const n=(0,o.last_year_no_later_than)(new Date(t)),a=(0,o.last_year_no_later_than)(new Date(e));a.setUTCFullYear(a.getUTCFullYear()+1);const r=[],s=n;for(;r.push((0,o.copy_date)(s)),s.setUTCFullYear(s.getUTCFullYear()+1),!(s>a););return r}(t,e),s=this.months;return{major:(0,l.concat)(r.map((t=>s.map((e=>{const n=(0,o.copy_date)(t);return n.setUTCMonth(e),n}))))).map((t=>t.getTime())).filter((n=>t<=n&&n<=e)),minor:[]}}}n.MonthsTicker=_,s=_,_.__name__=\"MonthsTicker\",s.define((({Int:t,Array:e})=>({months:[e(t),[]]})))},\n", - " function _(e,t,a,i,r){i();const n=e(147),_=e(158),s=e(159);class c extends _.SingleIntervalTicker{constructor(e){super(e)}initialize(){super.initialize(),this.interval=s.ONE_YEAR,this.basic_ticker=new n.BasicTicker({num_minor_ticks:0})}get_ticks_no_defaults(e,t,a,i){const r=(0,s.last_year_no_later_than)(new Date(e)).getUTCFullYear(),n=(0,s.last_year_no_later_than)(new Date(t)).getUTCFullYear();return{major:this.basic_ticker.get_ticks_no_defaults(r,n,a,i).major.map((e=>Date.UTC(e,0,1))).filter((a=>e<=a&&a<=t)),minor:[]}}}a.YearsTicker=c,c.__name__=\"YearsTicker\"},\n", - " function _(e,o,i,s,t){var 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i.AdaptiveTicker{constructor(t){super(t)}get_ticks_no_defaults(t,o,e,s){const n=this.num_minor_ticks,r=[],i=this.base,c=Math.log(t)/Math.log(i),f=Math.log(o)/Math.log(i),l=f-c;let h;if(isFinite(l))if(l<2){const e=this.get_interval(t,o,s),i=Math.floor(t/e),c=Math.ceil(o/e);if(h=(0,a.range)(i,c+1).filter((t=>0!=t)).map((t=>t*e)).filter((e=>t<=e&&e<=o)),n>0&&h.length>0){const t=e/n,o=(0,a.range)(0,n).map((o=>o*t));for(const t of o.slice(1))r.push(h[0]-t);for(const t of h)for(const e of o)r.push(t+e)}}else{const t=Math.ceil(.999999*c),o=Math.floor(1.000001*f),e=Math.ceil((o-t)/9);if(h=(0,a.range)(t-1,o+1,e).map((t=>i**t)),n>0&&h.length>0){const t=i**e/n,o=(0,a.range)(1,n+1).map((o=>o*t));for(const t of o)r.push(h[0]/t);r.push(h[0]);for(const t of h)for(const e of o)r.push(t*e)}}else h=[];return{major:h.filter((e=>t<=e&&e<=o)),minor:r.filter((e=>t<=e&&e<=o))}}}e.LogTicker=c,r=c,c.__name__=\"LogTicker\",r.override({mantissas:[1,5]})},\n", - " function _(e,r,t,i,a){var o;i();const s=e(128),c=e(145),n=e(166),_=e(167);class x extends s.AxisView{}t.MercatorAxisView=x,x.__name__=\"MercatorAxisView\";class d extends c.LinearAxis{constructor(e){super(e)}}t.MercatorAxis=d,o=d,d.__name__=\"MercatorAxis\",o.prototype.default_view=x,o.override({ticker:()=>new _.MercatorTicker({dimension:\"lat\"}),formatter:()=>new n.MercatorTickFormatter({dimension:\"lat\"})})},\n", - " function _(r,t,e,o,n){var i;o();const c=r(146),s=r(20),a=r(78);class l extends c.BasicTickFormatter{constructor(r){super(r)}doFormat(r,t){if(null==this.dimension)throw new Error(\"MercatorTickFormatter.dimension not configured\");if(0==r.length)return[];const e=r.length,o=new Array(e);if(\"lon\"==this.dimension)for(let n=0;n({dimension:[r(s.LatLon),null]})))},\n", - " function _(t,o,n,s,r){var e;s();const i=t(147),c=t(20),_=t(78);class a extends i.BasicTicker{constructor(t){super(t)}get_ticks_no_defaults(t,o,n,s){if(null==this.dimension)throw new Error(`${this}.dimension wasn't 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c.minor)if((0,_.in_bounds)(t,\"lat\")){const[,o]=_.wgs84_mercator.compute(e,t);m.push(o)}return{major:a,minor:m}}}n.MercatorTicker=a,e=a,a.__name__=\"MercatorTicker\",e.define((({Nullable:t})=>({dimension:[t(c.LatLon),null]})))},\n", - " function _(e,i,r,c,k){c(),k(\"AdaptiveTicker\",e(148).AdaptiveTicker),k(\"BasicTicker\",e(147).BasicTicker),k(\"CategoricalTicker\",e(141).CategoricalTicker),k(\"CompositeTicker\",e(156).CompositeTicker),k(\"ContinuousTicker\",e(149).ContinuousTicker),k(\"DatetimeTicker\",e(155).DatetimeTicker),k(\"DaysTicker\",e(157).DaysTicker),k(\"FixedTicker\",e(169).FixedTicker),k(\"LogTicker\",e(164).LogTicker),k(\"MercatorTicker\",e(167).MercatorTicker),k(\"MonthsTicker\",e(160).MonthsTicker),k(\"SingleIntervalTicker\",e(158).SingleIntervalTicker),k(\"Ticker\",e(130).Ticker),k(\"YearsTicker\",e(161).YearsTicker),k(\"BinnedTicker\",e(170).BinnedTicker)},\n", - " function _(r,t,e,i,n){var s;i();const _=r(149);class c extends 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this.glyph.visuals,s=\"line\"in this.glyph.visuals,l=Object.assign({},t.attributes);function h(e){const h=(0,y.clone)(l);return i&&(0,y.extend)(h,e.fill),s&&(0,y.extend)(h,e.line),new t.constructor(h)}function n(e,t){return t instanceof r.Glyph?t:h(\"auto\"==t?e:{fill:{},line:{}})}delete l.id;let{selection_glyph:o,nonselection_glyph:a,hover_glyph:c,muted_glyph:_}=this.model;o=n(f,o),this.selection_glyph=await this.build_glyph_view(o),a=n(b,a),this.nonselection_glyph=await this.build_glyph_view(a),null!=c&&(this.hover_glyph=await this.build_glyph_view(c)),_=n(V,_),this.muted_glyph=await this.build_glyph_view(_);const d=n(w,\"auto\");this.decimated_glyph=await this.build_glyph_view(d),this.selection_glyph.set_base(this.glyph),this.nonselection_glyph.set_base(this.glyph),null===(e=this.hover_glyph)||void 0===e||e.set_base(this.glyph),this.muted_glyph.set_base(this.glyph),this.decimated_glyph.set_base(this.glyph),this.set_data()}async build_glyph_view(e){return(0,m.build_view)(e,{parent:this})}remove(){var e;this.glyph.remove(),this.selection_glyph.remove(),this.nonselection_glyph.remove(),null===(e=this.hover_glyph)||void 0===e||e.remove(),this.muted_glyph.remove(),this.decimated_glyph.remove(),super.remove()}connect_signals(){super.connect_signals();const e=()=>this.request_render(),t=()=>this.update_data();this.connect(this.model.change,e),this.connect(this.glyph.model.change,t),this.connect(this.selection_glyph.model.change,t),this.connect(this.nonselection_glyph.model.change,t),null!=this.hover_glyph&&this.connect(this.hover_glyph.model.change,t),this.connect(this.muted_glyph.model.change,t),this.connect(this.decimated_glyph.model.change,t),this.connect(this.model.data_source.change,t),this.connect(this.model.data_source.streaming,t),this.connect(this.model.data_source.patching,(e=>this.update_data(e))),this.connect(this.model.data_source.selected.change,e),this.connect(this.model.data_source._select,e),null!=this.hover_glyph&&this.connect(this.model.data_source.inspect,e),this.connect(this.model.properties.view.change,t),this.connect(this.model.view.properties.indices.change,t),this.connect(this.model.view.properties.masked.change,(()=>this.set_visuals())),this.connect(this.model.properties.visible.change,(()=>this.plot_view.invalidate_dataranges=!0));const{x_ranges:i,y_ranges:s}=this.plot_view.frame;for(const[,e]of i)e instanceof v.FactorRange&&this.connect(e.change,t);for(const[,e]of s)e instanceof v.FactorRange&&this.connect(e.change,t);const{transformchange:l,exprchange:h}=this.model.glyph;this.connect(l,t),this.connect(h,t)}_update_masked_indices(){const e=this.glyph.mask_data();return this.model.view.masked=e,e}update_data(e){this.set_data(e),this.request_render()}set_data(e){const t=this.model.data_source;this.all_indices=this.model.view.indices;const{all_indices:i}=this;this.glyph.set_data(t,i,e),this.set_visuals(),this._update_masked_indices();const{lod_factor:s}=this.plot_model,l=this.all_indices.count;this.decimated=new g.Indices(l);for(let e=0;e!n||n.is_empty()?[]:n.selected_glyph?this.model.view.convert_indices_from_subset(i):n.indices.length>0?n.indices:Object.keys(n.multiline_indices).map((e=>parseInt(e))))()),d=(0,u.filter)(i,(e=>r.has(t[e]))),{lod_threshold:p}=this.plot_model;let g,y,m;if(null!=this.model.document&&this.model.document.interactive_duration()>0&&!e&&null!=p&&t.length>p?(i=[...this.decimated],g=this.decimated_glyph,y=this.decimated_glyph,m=this.selection_glyph):(g=this.model.muted?this.muted_glyph:this.glyph,y=this.nonselection_glyph,m=this.selection_glyph),null!=this.hover_glyph&&d.length){const e=new Set(i);for(const t of d)e.delete(t);i=[...e]}if(h.length){const e={};for(const t of h)e[t]=!0;const l=new Array,n=new Array;if(this.glyph instanceof o.LineView)for(const i of t)null!=e[i]?l.push(i):n.push(i);else for(const s of i)null!=e[t[s]]?l.push(s):n.push(s);y.render(s,n),m.render(s,l),null!=this.hover_glyph&&(this.glyph instanceof o.LineView?this.hover_glyph.render(s,this.model.view.convert_indices_from_subset(d)):this.hover_glyph.render(s,d))}else if(this.glyph instanceof o.LineView)this.hover_glyph&&d.length?this.hover_glyph.render(s,this.model.view.convert_indices_from_subset(d)):g.render(s,t);else if(this.glyph instanceof a.PatchView||this.glyph instanceof c.HAreaView||this.glyph instanceof _.VAreaView)if(0==n.selected_glyphs.length||null==this.hover_glyph)g.render(s,t);else for(const e of n.selected_glyphs)e==this.glyph.model&&this.hover_glyph.render(s,t);else g.render(s,i),this.hover_glyph&&d.length&&this.hover_glyph.render(s,d);s.restore()}draw_legend(e,t,i,s,l,h,n,o){0!=this.glyph.data_size&&(null==o&&(o=this.model.get_reference_point(h,n)),this.glyph.draw_legend_for_index(e,{x0:t,x1:i,y0:s,y1:l},o))}hit_test(e){if(!this.model.visible)return null;const t=this.glyph.hit_test(e);return null==t?null:this.model.view.convert_selection_from_subset(t)}}i.GlyphRendererView=x,x.__name__=\"GlyphRendererView\";class G extends n.DataRenderer{constructor(e){super(e)}initialize(){super.initialize(),this.view.source!=this.data_source&&(this.view.source=this.data_source,this.view.compute_indices())}get_reference_point(e,t){if(null!=e){const i=this.data_source.get_column(e);if(null!=i)for(const[e,s]of Object.entries(this.view.indices_map))if(i[parseInt(e)]==t)return s}return 0}get_selection_manager(){return this.data_source.selection_manager}}i.GlyphRenderer=G,h=G,G.__name__=\"GlyphRenderer\",h.prototype.default_view=x,h.define((({Boolean:e,Auto:t,Or:i,Ref:s,Null:l,Nullable:h})=>({data_source:[s(d.ColumnarDataSource)],view:[s(p.CDSView),e=>new p.CDSView({source:e.data_source})],glyph:[s(r.Glyph)],hover_glyph:[h(s(r.Glyph)),null],nonselection_glyph:[i(s(r.Glyph),t,l),\"auto\"],selection_glyph:[i(s(r.Glyph),t,l),\"auto\"],muted_glyph:[i(s(r.Glyph),t,l),\"auto\"],muted:[e,!1]})))},\n", - " function _(e,r,t,a,n){var s;a();const c=e(41);class _ extends c.RendererView{get xscale(){return this.coordinates.x_scale}get yscale(){return this.coordinates.y_scale}}t.DataRendererView=_,_.__name__=\"DataRendererView\";class i extends c.Renderer{constructor(e){super(e)}get selection_manager(){return this.get_selection_manager()}}t.DataRenderer=i,s=i,i.__name__=\"DataRenderer\",s.override({level:\"glyph\"})},\n", - " function _(e,t,i,s,n){s();const l=e(1);var _;const r=e(178),o=e(184),a=(0,l.__importStar)(e(48)),h=(0,l.__importStar)(e(185)),c=e(72);class d extends r.XYGlyphView{async lazy_initialize(){await super.lazy_initialize();const{webgl:t}=this.renderer.plot_view.canvas_view;if(null==t?void 0:t.regl_wrapper.has_webgl){const{LineGL:i}=await Promise.resolve().then((()=>(0,l.__importStar)(e(421))));this.glglyph=new i(t.regl_wrapper,this)}}_render(e,t,i){const{sx:s,sy:n}=null!=i?i:this;let l=null;const _=e=>null!=l&&e-l!=1;let r=!0;e.beginPath();for(const i of t){const t=s[i],o=n[i];isFinite(t+o)?r||_(i)?(e.moveTo(t,o),r=!1):e.lineTo(t,o):r=!0,l=i}this.visuals.line.set_value(e),e.stroke()}_hit_point(e){const t=new c.Selection,i={x:e.sx,y:e.sy};let s=9999;const n=Math.max(2,this.line_width.value/2);for(let e=0,l=this.sx.length-1;e({x:[c.XCoordinateSpec,{field:\"x\"}],y:[c.YCoordinateSpec,{field:\"y\"}]})))},\n", - " function _(e,t,s,i,n){i();const r=e(1),a=(0,r.__importStar)(e(18)),o=(0,r.__importStar)(e(65)),_=(0,r.__importStar)(e(45)),l=e(42),c=e(53),h=e(19),d=e(24),u=e(8),f=e(180),p=e(12),g=e(26),y=e(181),x=e(67),v=e(72),{abs:b,ceil:m}=Math;class w extends l.View{constructor(){super(...arguments),this._index=null,this._data_size=null,this._nohit_warned=new Set}get renderer(){return this.parent}get has_webgl(){return null!=this.glglyph}get index(){const{_index:e}=this;if(null!=e)return e;throw new Error(`${this}.index_data() wasn't called`)}get data_size(){const{_data_size:e}=this;if(null!=e)return e;throw new Error(`${this}.set_data() wasn't called`)}initialize(){super.initialize(),this.visuals=new _.Visuals(this)}request_render(){this.parent.request_render()}get canvas(){return this.renderer.parent.canvas_view}render(e,t,s){var i;null!=this.glglyph&&(this.renderer.needs_webgl_blit=this.glglyph.render(e,t,null!==(i=this.base)&&void 0!==i?i:this),this.renderer.needs_webgl_blit)||this._render(e,t,null!=s?s:this.base)}has_finished(){return!0}notify_finished(){this.renderer.notify_finished()}_bounds(e){return e}bounds(){return this._bounds(this.index.bbox)}log_bounds(){const{x0:e,x1:t}=this.index.bounds(o.positive_x()),{y0:s,y1:i}=this.index.bounds(o.positive_y());return this._bounds({x0:e,y0:s,x1:t,y1:i})}get_anchor_point(e,t,[s,i]){switch(e){case\"center\":case\"center_center\":{const[e,n]=this.scenterxy(t,s,i);return{x:e,y:n}}default:return null}}scenterx(e,t,s){return this.scenterxy(e,t,s)[0]}scentery(e,t,s){return this.scenterxy(e,t,s)[1]}sdist(e,t,s,i=\"edge\",n=!1){const r=t.length,a=new d.ScreenArray(r),o=e.s_compute;if(\"center\"==i)for(let e=0;em(e))),a}draw_legend_for_index(e,t,s){}hit_test(e){switch(e.type){case\"point\":if(null!=this._hit_point)return this._hit_point(e);break;case\"span\":if(null!=this._hit_span)return this._hit_span(e);break;case\"rect\":if(null!=this._hit_rect)return this._hit_rect(e);break;case\"poly\":if(null!=this._hit_poly)return this._hit_poly(e)}return this._nohit_warned.has(e.type)||(h.logger.debug(`'${e.type}' selection not available for ${this.model.type}`),this._nohit_warned.add(e.type)),null}_hit_rect_against_index(e){const{sx0:t,sx1:s,sy0:i,sy1:n}=e,[r,a]=this.renderer.coordinates.x_scale.r_invert(t,s),[o,_]=this.renderer.coordinates.y_scale.r_invert(i,n),l=[...this.index.indices({x0:r,x1:a,y0:o,y1:_})];return new v.Selection({indices:l})}_project_data(){}*_iter_visuals(){for(const e of this.visuals)for(const t of e)(t instanceof a.VectorSpec||t instanceof a.ScalarSpec)&&(yield t)}set_base(e){e!=this&&e instanceof this.constructor&&(this.base=e)}_configure(e,t){Object.defineProperty(this,(0,u.isString)(e)?e:e.attr,Object.assign({configurable:!0,enumerable:!0},t))}set_visuals(e,t){var s;for(const s of this._iter_visuals()){const{base:i}=this;if(null!=i){const e=i.model.properties[s.attr];if(null!=e&&(0,g.is_equal)(s.get_value(),e.get_value())){this._configure(s,{get:()=>i[`${s.attr}`]});continue}}const n=s.uniform(e).select(t);this._configure(s,{value:n})}for(const e of this.visuals)e.update();this._set_visuals(),null===(s=this.glglyph)||void 0===s||s.set_visuals_changed()}_set_visuals(){}set_data(e,t,s){var i;const{x_source:n,y_source:r}=this.renderer.coordinates,o=new Set(this._iter_visuals());this._data_size=t.count;for(const s of this.model)if((s instanceof a.VectorSpec||s instanceof a.ScalarSpec)&&!o.has(s))if(s instanceof a.BaseCoordinateSpec){const i=s.array(e);let o=t.select(i);const _=\"x\"==s.dimension?n:r;if(_ instanceof x.FactorRange)if(s instanceof a.CoordinateSpec)o=_.v_synthetic(o);else if(s instanceof a.CoordinateSeqSpec)for(let e=0;e{const s=new Uint32Array(r);for(let a=0;a>1;t[s]>i?e=s:n=s+1}return t[n]}class r extends d.default{get boxes(){return this._boxes}search_indices(i,t,n,e){if(this._pos!==this._boxes.length)throw new Error(\"Data not yet indexed - call index.finish().\");let s=this._boxes.length-4;const d=[],x=new o.Indices(this.numItems);for(;void 0!==s;){const o=Math.min(s+4*this.nodeSize,h(s,this._levelBounds));for(let h=s;h>2],r=this._boxes[h+0],l=this._boxes[h+1],a=this._boxes[h+2],_=this._boxes[h+3];na||t>_||(s<4*this.numItems?x.set(o):d.push(o)))}s=d.pop()}return x}}r.__name__=\"_FlatBush\";class l{constructor(i){this.index=null,i>0&&(this.index=new r(i))}add_rect(i,t,n,e){var s;isFinite(i+t+n+e)?null===(s=this.index)||void 0===s||s.add(i,t,n,e):this.add_empty()}add_point(i,t){var n;isFinite(i+t)?null===(n=this.index)||void 0===n||n.add(i,t,i,t):this.add_empty()}add_empty(){var i;null===(i=this.index)||void 0===i||i.add(1/0,1/0,-1/0,-1/0)}finish(){var i;null===(i=this.index)||void 0===i||i.finish()}_normalize(i){let{x0:t,y0:n,x1:e,y1:s}=i;return t>e&&([t,e]=[e,t]),n>s&&([n,s]=[s,n]),{x0:t,y0:n,x1:e,y1:s}}get bbox(){if(null==this.index)return(0,x.empty)();{const{minX:i,minY:t,maxX:n,maxY:e}=this.index;return{x0:i,y0:t,x1:n,y1:e}}}indices(i){if(null==this.index)return new o.Indices(0);{const{x0:t,y0:n,x1:e,y1:s}=this._normalize(i);return this.index.search_indices(t,n,e,s)}}bounds(i){const t=(0,x.empty)();if(null==this.index)return t;const{boxes:n}=this.index;for(const e of this.indices(i)){const s=n[4*e+0],d=n[4*e+1],o=n[4*e+2],x=n[4*e+3];s>=i.x0&&st.x1&&(t.x1=o),d>=i.y0&&dt.y1&&(t.y1=x)}return t}}n.SpatialIndex=l,l.__name__=\"SpatialIndex\"},\n", - " function _(t,s,i,e,h){e();const n=(0,t(1).__importDefault)(t(183)),o=[Int8Array,Uint8Array,Uint8ClampedArray,Int16Array,Uint16Array,Int32Array,Uint32Array,Float32Array,Float64Array];class r{static from(t){if(!(t instanceof ArrayBuffer))throw new Error(\"Data must be an instance of ArrayBuffer.\");const[s,i]=new Uint8Array(t,0,2);if(251!==s)throw new Error(\"Data does not appear to be in a Flatbush format.\");if(i>>4!=3)throw new Error(`Got 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this.children){const{height:e}=t.measure({width:0,height:0});t.set_geometry(new o.BBox({top:i,height:e,left:h,width:r})),i+=e}}}h.VStack=a,a.__name__=\"VStack\";class l extends n.Layoutable{constructor(){super(...arguments),this.children=[]}*[Symbol.iterator](){yield*this.children}_measure(t){const{width_policy:e,height_policy:h}=this.sizing,{min:i,max:r}=Math;let n=0,o=0;for(const e of this.children){const{width:h,height:i}=e.measure(t);n=r(n,h),o=r(o,i)}return{width:(()=>{const{width:h}=this.sizing;if(t.width==1/0)return\"fixed\"==e&&null!=h?h:n;switch(e){case\"fixed\":return null!=h?h:n;case\"min\":return n;case\"fit\":return null!=h?i(t.width,h):t.width;case\"max\":return null!=h?r(t.width,h):t.width}})(),height:(()=>{const{height:e}=this.sizing;if(t.height==1/0)return\"fixed\"==h&&null!=e?e:o;switch(h){case\"fixed\":return null!=e?e:o;case\"min\":return o;case\"fit\":return null!=e?i(t.height,e):t.height;case\"max\":return null!=e?r(t.height,e):t.height}})()}}_set_geometry(t,e){super._set_geometry(t,e);const h=this.absolute?t:t.relative(),{left:i,right:r,top:n,bottom:s}=h,c=Math.round(h.vcenter),a=Math.round(h.hcenter);for(const e of this.children){const{margin:h,halign:l,valign:d}=e.sizing,{width:u,height:g,inner:_}=e.measure(t),w=(()=>{switch(`${d}_${l}`){case\"start_start\":return new o.BBox({left:i+h.left,top:n+h.top,width:u,height:g});case\"start_center\":return new o.BBox({hcenter:a,top:n+h.top,width:u,height:g});case\"start_end\":return new o.BBox({right:r-h.right,top:n+h.top,width:u,height:g});case\"center_start\":return new o.BBox({left:i+h.left,vcenter:c,width:u,height:g});case\"center_center\":return new o.BBox({hcenter:a,vcenter:c,width:u,height:g});case\"center_end\":return new o.BBox({right:r-h.right,vcenter:c,width:u,height:g});case\"end_start\":return new o.BBox({left:i+h.left,bottom:s-h.bottom,width:u,height:g});case\"end_center\":return new o.BBox({hcenter:a,bottom:s-h.bottom,width:u,height:g});case\"end_end\":return new o.BBox({right:r-h.right,bottom:s-h.bottom,width:u,height:g})}})(),m=null==_?w:new o.BBox({left:w.left+_.left,top:w.top+_.top,right:w.right-_.right,bottom:w.bottom-_.bottom});e.set_geometry(w,m)}}}h.NodeLayout=l,l.__name__=\"NodeLayout\"},\n", - " function _(t,i,s,e,o){e();const n=t(124),l=t(125),r=t(8),h=t(65),c=t(9),{max:a,round:g}=Math;class p{constructor(t){this.def=t,this._map=new Map}get(t){let i=this._map.get(t);return void 0===i&&(i=this.def(),this._map.set(t,i)),i}apply(t,i){const s=this.get(t);this._map.set(t,i(s))}}p.__name__=\"DefaultMap\";class f{constructor(){this._items=[],this._nrows=0,this._ncols=0}get nrows(){return this._nrows}get ncols(){return this._ncols}add(t,i){const{r1:s,c1:e}=t;this._nrows=a(this._nrows,s+1),this._ncols=a(this._ncols,e+1),this._items.push({span:t,data:i})}at(t,i){return this._items.filter((({span:s})=>s.r0<=t&&t<=s.r1&&s.c0<=i&&i<=s.c1)).map((({data:t})=>t))}row(t){return this._items.filter((({span:i})=>i.r0<=t&&t<=i.r1)).map((({data:t})=>t))}col(t){return this._items.filter((({span:i})=>i.c0<=t&&t<=i.c1)).map((({data:t})=>t))}foreach(t){for(const{span:i,data:s}of this._items)t(i,s)}map(t){const i=new f;for(const{span:s,data:e}of this._items)i.add(s,t(s,e));return i}}f.__name__=\"Container\";class _ extends l.Layoutable{constructor(t=[]){super(),this.items=t,this.rows=\"auto\",this.cols=\"auto\",this.spacing=0}*[Symbol.iterator](){for(const{layout:t}of this.items)yield t}is_width_expanding(){if(super.is_width_expanding())return!0;if(\"fixed\"==this.sizing.width_policy)return!1;const{cols:t}=this._state;return(0,c.some)(t,(t=>\"max\"==t.policy))}is_height_expanding(){if(super.is_height_expanding())return!0;if(\"fixed\"==this.sizing.height_policy)return!1;const{rows:t}=this._state;return(0,c.some)(t,(t=>\"max\"==t.policy))}_init(){var t,i,s,e;super._init();const o=new f;for(const{layout:t,row:i,col:s,row_span:e,col_span:n}of this.items)if(t.sizing.visible){const l=i,r=s,h=i+(null!=e?e:1)-1,c=s+(null!=n?n:1)-1;o.add({r0:l,c0:r,r1:h,c1:c},t)}const{nrows:n,ncols:l}=o,h=new Array(n);for(let s=0;s{var t;const i=(0,r.isPlainObject)(this.rows)?null!==(t=this.rows[s])&&void 0!==t?t:this.rows[\"*\"]:this.rows;return null==i?{policy:\"auto\"}:(0,r.isNumber)(i)?{policy:\"fixed\",height:i}:(0,r.isString)(i)?{policy:i}:i})(),n=null!==(t=e.align)&&void 0!==t?t:\"auto\";if(\"fixed\"==e.policy)h[s]={policy:\"fixed\",height:e.height,align:n};else if(\"min\"==e.policy)h[s]={policy:\"min\",align:n};else if(\"fit\"==e.policy||\"max\"==e.policy)h[s]={policy:e.policy,flex:null!==(i=e.flex)&&void 0!==i?i:1,align:n};else{if(\"auto\"!=e.policy)throw new Error(\"unrechable\");(0,c.some)(o.row(s),(t=>t.is_height_expanding()))?h[s]={policy:\"max\",flex:1,align:n}:h[s]={policy:\"min\",align:n}}}const a=new Array(l);for(let t=0;t{var i;const s=(0,r.isPlainObject)(this.cols)?null!==(i=this.cols[t])&&void 0!==i?i:this.cols[\"*\"]:this.cols;return null==s?{policy:\"auto\"}:(0,r.isNumber)(s)?{policy:\"fixed\",width:s}:(0,r.isString)(s)?{policy:s}:s})(),n=null!==(s=i.align)&&void 0!==s?s:\"auto\";if(\"fixed\"==i.policy)a[t]={policy:\"fixed\",width:i.width,align:n};else if(\"min\"==i.policy)a[t]={policy:\"min\",align:n};else if(\"fit\"==i.policy||\"max\"==i.policy)a[t]={policy:i.policy,flex:null!==(e=i.flex)&&void 0!==e?e:1,align:n};else{if(\"auto\"!=i.policy)throw new Error(\"unrechable\");(0,c.some)(o.col(t),(t=>t.is_width_expanding()))?a[t]={policy:\"max\",flex:1,align:n}:a[t]={policy:\"min\",align:n}}}const[g,p]=(0,r.isNumber)(this.spacing)?[this.spacing,this.spacing]:this.spacing;this._state={items:o,nrows:n,ncols:l,rows:h,cols:a,rspacing:g,cspacing:p}}_measure_totals(t,i){const{nrows:s,ncols:e,rspacing:o,cspacing:n}=this._state;return{height:(0,c.sum)(t)+(s-1)*o,width:(0,c.sum)(i)+(e-1)*n}}_measure_cells(t){const{items:i,nrows:s,ncols:e,rows:o,cols:l,rspacing:r,cspacing:h}=this._state,c=new Array(s);for(let t=0;t{const{r0:e,c0:f,r1:d,c1:u}=i,w=(d-e)*r,m=(u-f)*h;let y=0;for(let i=e;i<=d;i++)y+=t(i,f).height;y+=w;let x=0;for(let i=f;i<=u;i++)x+=t(e,i).width;x+=m;const b=s.measure({width:x,height:y});_.add(i,{layout:s,size_hint:b});const z=new n.Sizeable(b).grow_by(s.sizing.margin);z.height-=w,z.width-=m;const v=[];for(let t=e;t<=d;t++){const i=o[t];\"fixed\"==i.policy?z.height-=i.height:v.push(t)}if(z.height>0){const t=g(z.height/v.length);for(const i of v)c[i]=a(c[i],t)}const j=[];for(let t=f;t<=u;t++){const i=l[t];\"fixed\"==i.policy?z.width-=i.width:j.push(t)}if(z.width>0){const t=g(z.width/j.length);for(const i of j)p[i]=a(p[i],t)}}));return{size:this._measure_totals(c,p),row_heights:c,col_widths:p,size_hints:_}}_measure_grid(t){const{nrows:i,ncols:s,rows:e,cols:o,rspacing:n,cspacing:l}=this._state,r=this._measure_cells(((t,i)=>{const s=e[t],n=o[i];return{width:\"fixed\"==n.policy?n.width:1/0,height:\"fixed\"==s.policy?s.height:1/0}}));let h;h=\"fixed\"==this.sizing.height_policy&&null!=this.sizing.height?this.sizing.height:t.height!=1/0&&this.is_height_expanding()?t.height:r.size.height;let c,p=0;for(let t=0;t0)for(let t=0;ti?i:e,t--}}}c=\"fixed\"==this.sizing.width_policy&&null!=this.sizing.width?this.sizing.width:t.width!=1/0&&this.is_width_expanding()?t.width:r.size.width;let f=0;for(let t=0;t0)for(let t=0;ts?s:o,t--}}}const{row_heights:_,col_widths:d,size_hints:u}=this._measure_cells(((t,i)=>({width:r.col_widths[i],height:r.row_heights[t]})));return{size:this._measure_totals(_,d),row_heights:_,col_widths:d,size_hints:u}}_measure(t){const{size:i}=this._measure_grid(t);return i}_set_geometry(t,i){super._set_geometry(t,i);const{nrows:s,ncols:e,rspacing:o,cspacing:n}=this._state,{row_heights:l,col_widths:r,size_hints:c}=this._measure_grid(t),f=this._state.rows.map(((t,i)=>Object.assign(Object.assign({},t),{top:0,height:l[i],get bottom(){return this.top+this.height}}))),_=this._state.cols.map(((t,i)=>Object.assign(Object.assign({},t),{left:0,width:r[i],get right(){return this.left+this.width}}))),d=c.map(((t,i)=>Object.assign(Object.assign({},i),{outer:new h.BBox,inner:new h.BBox})));for(let i=0,e=this.absolute?t.top:0;i{const{layout:r,size_hint:c}=l,{sizing:a}=r,{width:p,height:d}=c,u=function(t,i){let s=(i-t)*n;for(let e=t;e<=i;e++)s+=_[e].width;return s}(i,e),w=function(t,i){let s=(i-t)*o;for(let e=t;e<=i;e++)s+=f[e].height;return s}(t,s),m=i==e&&\"auto\"!=_[i].align?_[i].align:a.halign,y=t==s&&\"auto\"!=f[t].align?f[t].align:a.valign;let x=_[i].left;\"start\"==m?x+=a.margin.left:\"center\"==m?x+=g((u-p)/2):\"end\"==m&&(x+=u-a.margin.right-p);let b=f[t].top;\"start\"==y?b+=a.margin.top:\"center\"==y?b+=g((w-d)/2):\"end\"==y&&(b+=w-a.margin.bottom-d),l.outer=new h.BBox({left:x,top:b,width:p,height:d})}));const u=f.map((()=>({start:new p((()=>0)),end:new p((()=>0))}))),w=_.map((()=>({start:new p((()=>0)),end:new p((()=>0))})));d.foreach((({r0:t,c0:i,r1:s,c1:e},{size_hint:o,outer:n})=>{const{inner:l}=o;null!=l&&(u[t].start.apply(n.top,(t=>a(t,l.top))),u[s].end.apply(f[s].bottom-n.bottom,(t=>a(t,l.bottom))),w[i].start.apply(n.left,(t=>a(t,l.left))),w[e].end.apply(_[e].right-n.right,(t=>a(t,l.right))))})),d.foreach((({r0:t,c0:i,r1:s,c1:e},o)=>{const{size_hint:n,outer:l}=o,r=t=>{const i=this.absolute?l:l.relative(),s=i.left+t.left,e=i.top+t.top,o=i.right-t.right,n=i.bottom-t.bottom;return new h.BBox({left:s,top:e,right:o,bottom:n})};if(null!=n.inner){let h=r(n.inner);if(!1!==n.align){const o=u[t].start.get(l.top),n=u[s].end.get(f[s].bottom-l.bottom),c=w[i].start.get(l.left),a=w[e].end.get(_[e].right-l.right);try{h=r({top:o,bottom:n,left:c,right:a})}catch(t){}}o.inner=h}else o.inner=l})),d.foreach(((t,{layout:i,outer:s,inner:e})=>{i.set_geometry(s,e)}))}}s.Grid=_,_.__name__=\"Grid\";class d extends _{constructor(t){super(),this.items=t.map(((t,i)=>({layout:t,row:0,col:i}))),this.rows=\"fit\"}}s.Row=d,d.__name__=\"Row\";class u extends _{constructor(t){super(),this.items=t.map(((t,i)=>({layout:t,row:i,col:0}))),this.cols=\"fit\"}}s.Column=u,u.__name__=\"Column\"},\n", - " function _(e,t,s,n,i){n();const a=e(125),c=e(124),o=e(43);class r extends a.ContentLayoutable{constructor(e){super(),this.content_size=(0,o.unsized)(e,(()=>new c.Sizeable((0,o.size)(e))))}_content_size(){return this.content_size}}s.ContentBox=r,r.__name__=\"ContentBox\";class _ extends a.Layoutable{constructor(e){super(),this.el=e}_measure(e){const t=new c.Sizeable(e).bounded_to(this.sizing.size);return(0,o.sized)(this.el,t,(()=>{const e=new c.Sizeable((0,o.content_size)(this.el)),{border:t,padding:s}=(0,o.extents)(this.el);return e.grow_by(t).grow_by(s).map(Math.ceil)}))}}s.VariadicBox=_,_.__name__=\"VariadicBox\";class h extends _{constructor(e){super(e),this._cache=new Map}_measure(e){const{width:t,height:s}=e,n=`${t},${s}`;let i=this._cache.get(n);return null==i&&(i=super._measure(e),this._cache.set(n,i)),i}invalidate_cache(){this._cache.clear()}}s.CachedVariadicBox=h,h.__name__=\"CachedVariadicBox\"},\n", - " function _(t,e,i,h,o){h();const s=t(124),r=t(125),n=t(65);class g extends r.Layoutable{constructor(){super(...arguments),this.min_border={left:0,top:0,right:0,bottom:0},this.padding={left:0,top:0,right:0,bottom:0}}*[Symbol.iterator](){yield this.top_panel,yield this.bottom_panel,yield this.left_panel,yield this.right_panel,yield this.center_panel}_measure(t){t=new s.Sizeable({width:\"fixed\"==this.sizing.width_policy||t.width==1/0?this.sizing.width:t.width,height:\"fixed\"==this.sizing.height_policy||t.height==1/0?this.sizing.height:t.height});const e=this.left_panel.measure({width:0,height:t.height}),i=Math.max(e.width,this.min_border.left)+this.padding.left,h=this.right_panel.measure({width:0,height:t.height}),o=Math.max(h.width,this.min_border.right)+this.padding.right,r=this.top_panel.measure({width:t.width,height:0}),n=Math.max(r.height,this.min_border.top)+this.padding.top,g=this.bottom_panel.measure({width:t.width,height:0}),a=Math.max(g.height,this.min_border.bottom)+this.padding.bottom,d=new s.Sizeable(t).shrink_by({left:i,right:o,top:n,bottom:a}),l=this.center_panel.measure(d);return{width:i+l.width+o,height:n+l.height+a,inner:{left:i,right:o,top:n,bottom:a},align:(()=>{const{width_policy:t,height_policy:e}=this.center_panel.sizing;return\"fixed\"!=t&&\"fixed\"!=e})()}}_set_geometry(t,e){super._set_geometry(t,e),this.center_panel.set_geometry(e);const i=this.left_panel.measure({width:0,height:t.height}),h=this.right_panel.measure({width:0,height:t.height}),o=this.top_panel.measure({width:t.width,height:0}),s=this.bottom_panel.measure({width:t.width,height:0}),{left:r,top:g,right:a,bottom:d}=e;this.top_panel.set_geometry(new n.BBox({left:r,right:a,bottom:g,height:o.height})),this.bottom_panel.set_geometry(new n.BBox({left:r,right:a,top:d,height:s.height})),this.left_panel.set_geometry(new n.BBox({top:g,bottom:d,right:r,width:i.width})),this.right_panel.set_geometry(new n.BBox({top:g,bottom:d,left:a,width:h.width}))}}i.BorderLayout=g,g.__name__=\"BorderLayout\"},\n", - " function _(t,e,i,s,l){s();const n=t(1);var o;const a=t(119),_=t(10),d=t(20),h=t(120),r=t(123),u=(0,n.__importStar)(t(48));class c extends a.TextAnnotationView{update_layout(){const{panel:t}=this;this.layout=null!=t?new r.SideLayout(t,(()=>this.get_size()),!1):void 0}_get_size(){const{text:t}=this.model,e=new h.TextBox({text:t}),{angle:i,angle_units:s}=this.model;e.angle=(0,_.resolve_angle)(i,s),e.visuals=this.visuals.text.values();const{width:l,height:n}=e.size();return{width:l,height:n}}_render(){const{angle:t,angle_units:e}=this.model,i=(0,_.resolve_angle)(t,e),s=null!=this.layout?this.layout:this.plot_view.frame,l=this.coordinates.x_scale,n=this.coordinates.y_scale;let o=\"data\"==this.model.x_units?l.compute(this.model.x):s.bbox.xview.compute(this.model.x),a=\"data\"==this.model.y_units?n.compute(this.model.y):s.bbox.yview.compute(this.model.y);o+=this.model.x_offset,a-=this.model.y_offset;(\"canvas\"==this.model.render_mode?this._canvas_text.bind(this):this._css_text.bind(this))(this.layer.ctx,this.model.text,o,a,i)}}i.LabelView=c,c.__name__=\"LabelView\";class x extends a.TextAnnotation{constructor(t){super(t)}}i.Label=x,o=x,x.__name__=\"Label\",o.prototype.default_view=c,o.mixins([u.Text,[\"border_\",u.Line],[\"background_\",u.Fill]]),o.define((({Number:t,String:e,Angle:i})=>({x:[t],x_units:[d.SpatialUnits,\"data\"],y:[t],y_units:[d.SpatialUnits,\"data\"],text:[e,\"\"],angle:[i,0],angle_units:[d.AngleUnits,\"rad\"],x_offset:[t,0],y_offset:[t,0]}))),o.override({background_fill_color:null,border_line_color:null})},\n", - " function _(t,e,s,i,l){i();const o=t(1);var a;const r=t(69),n=(0,o.__importStar)(t(48)),d=t(20),_=t(43),c=t(120),h=(0,o.__importStar)(t(18)),u=t(11);class v extends r.DataAnnotationView{set_data(t){var e;if(super.set_data(t),null===(e=this.els)||void 0===e||e.forEach((t=>(0,_.remove)(t))),\"css\"==this.model.render_mode){const t=this.els=[...this.text].map((()=>(0,_.div)({style:{display:\"none\"}})));for(const e of t)this.plot_view.canvas_view.add_overlay(e)}else delete this.els}remove(){var t;null===(t=this.els)||void 0===t||t.forEach((t=>(0,_.remove)(t))),super.remove()}_rerender(){\"css\"==this.model.render_mode?this.render():this.request_render()}map_data(){const{x_scale:t,y_scale:e}=this.coordinates,s=null!=this.layout?this.layout:this.plot_view.frame;this.sx=\"data\"==this.model.x_units?t.v_compute(this._x):s.bbox.xview.v_compute(this._x),this.sy=\"data\"==this.model.y_units?e.v_compute(this._y):s.bbox.yview.v_compute(this._y)}paint(){const t=\"canvas\"==this.model.render_mode?this._v_canvas_text.bind(this):this._v_css_text.bind(this),{ctx:e}=this.layer;for(let s=0,i=this.text.length;s{switch(this.visuals.text.text_align.get(e)){case\"left\":return[\"left\",\"0%\"];case\"center\":return[\"center\",\"-50%\"];case\"right\":return[\"right\",\"-100%\"]}})(),[d,c]=(()=>{switch(this.visuals.text.text_baseline.get(e)){case\"top\":return[\"top\",\"0%\"];case\"middle\":return[\"center\",\"-50%\"];case\"bottom\":return[\"bottom\",\"-100%\"];default:return[\"center\",\"-50%\"]}})();let h=`translate(${n}, ${c})`;o&&(h+=`rotate(${o}rad)`),a.style.transformOrigin=`${r} ${d}`,a.style.transform=h,this.layout,this.visuals.background_fill.doit&&(this.visuals.background_fill.set_vectorize(t,e),a.style.backgroundColor=t.fillStyle),this.visuals.border_line.doit&&(this.visuals.border_line.set_vectorize(t,e),a.style.borderStyle=t.lineDash.length<2?\"solid\":\"dashed\",a.style.borderWidth=`${t.lineWidth}px`,a.style.borderColor=t.strokeStyle),(0,_.display)(a)}}s.LabelSetView=v,v.__name__=\"LabelSetView\";class x extends r.DataAnnotation{constructor(t){super(t)}}s.LabelSet=x,a=x,x.__name__=\"LabelSet\",a.prototype.default_view=v,a.mixins([n.TextVector,[\"border_\",n.LineVector],[\"background_\",n.FillVector]]),a.define((()=>({x:[h.XCoordinateSpec,{field:\"x\"}],y:[h.YCoordinateSpec,{field:\"y\"}],x_units:[d.SpatialUnits,\"data\"],y_units:[d.SpatialUnits,\"data\"],text:[h.StringSpec,{field:\"text\"}],angle:[h.AngleSpec,0],x_offset:[h.NumberSpec,{value:0}],y_offset:[h.NumberSpec,{value:0}],render_mode:[d.RenderMode,\"canvas\"]}))),a.override({background_fill_color:null,border_line_color:null})},\n", - " function _(t,e,i,l,s){l();const n=t(1);var o;const h=t(40),a=t(215),_=t(20),r=(0,n.__importStar)(t(48)),d=t(15),c=t(123),g=t(121),m=t(65),b=t(9),f=t(8),u=t(11);class x extends h.AnnotationView{update_layout(){const{panel:t}=this;this.layout=null!=t?new c.SideLayout(t,(()=>this.get_size())):void 0}cursor(t,e){return\"none\"==this.model.click_policy?null:\"pointer\"}get legend_padding(){return null!=this.model.border_line_color?this.model.padding:0}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render())),this.connect(this.model.item_change,(()=>this.request_render()))}compute_legend_bbox(){const t=this.model.get_legend_names(),{glyph_height:e,glyph_width:i}=this.model,{label_height:l,label_width:s}=this.model;this.max_label_height=(0,b.max)([(0,g.font_metrics)(this.visuals.label_text.font_value()).height,l,e]);const{ctx:n}=this.layer;n.save(),this.visuals.label_text.set_value(n),this.text_widths=new Map;for(const e of t)this.text_widths.set(e,(0,b.max)([n.measureText(e).width,s]));this.visuals.title_text.set_value(n),this.title_height=this.model.title?(0,g.font_metrics)(this.visuals.title_text.font_value()).height+this.model.title_standoff:0,this.title_width=this.model.title?n.measureText(this.model.title).width:0,n.restore();const o=Math.max((0,b.max)([...this.text_widths.values()]),0),h=this.model.margin,{legend_padding:a}=this,_=this.model.spacing,{label_standoff:r}=this.model;let d,c;if(\"vertical\"==this.model.orientation)d=t.length*this.max_label_height+Math.max(t.length-1,0)*_+2*a+this.title_height,c=(0,b.max)([o+i+r+2*a,this.title_width+2*a]);else{let e=2*a+Math.max(t.length-1,0)*_;for(const[,t]of this.text_widths)e+=(0,b.max)([t,s])+i+r;c=(0,b.max)([this.title_width+2*a,e]),d=this.max_label_height+this.title_height+2*a}const x=null!=this.layout?this.layout:this.plot_view.frame,[p,w]=x.bbox.ranges,{location:v}=this.model;let y,k;if((0,f.isString)(v))switch(v){case\"top_left\":y=p.start+h,k=w.start+h;break;case\"top\":case\"top_center\":y=(p.end+p.start)/2-c/2,k=w.start+h;break;case\"top_right\":y=p.end-h-c,k=w.start+h;break;case\"bottom_right\":y=p.end-h-c,k=w.end-h-d;break;case\"bottom\":case\"bottom_center\":y=(p.end+p.start)/2-c/2,k=w.end-h-d;break;case\"bottom_left\":y=p.start+h,k=w.end-h-d;break;case\"left\":case\"center_left\":y=p.start+h,k=(w.end+w.start)/2-d/2;break;case\"center\":case\"center_center\":y=(p.end+p.start)/2-c/2,k=(w.end+w.start)/2-d/2;break;case\"right\":case\"center_right\":y=p.end-h-c,k=(w.end+w.start)/2-d/2}else if((0,f.isArray)(v)&&2==v.length){const[t,e]=v;y=x.bbox.xview.compute(t),k=x.bbox.yview.compute(e)-d}else(0,u.unreachable)();return new m.BBox({left:y,top:k,width:c,height:d})}interactive_bbox(){return this.compute_legend_bbox()}interactive_hit(t,e){return this.interactive_bbox().contains(t,e)}on_hit(t,e){let i;const{glyph_width:l}=this.model,{legend_padding:s}=this,n=this.model.spacing,{label_standoff:o}=this.model;let h=i=s;const a=this.compute_legend_bbox(),_=\"vertical\"==this.model.orientation;for(const r of this.model.items){const d=r.get_labels_list_from_label_prop();for(const c of d){const d=a.x+h,g=a.y+i+this.title_height;let b,f;[b,f]=_?[a.width-2*s,this.max_label_height]:[this.text_widths.get(c)+l+o,this.max_label_height];if(new m.BBox({left:d,top:g,width:b,height:f}).contains(t,e)){switch(this.model.click_policy){case\"hide\":for(const t of r.renderers)t.visible=!t.visible;break;case\"mute\":for(const t of r.renderers)t.muted=!t.muted}return!0}_?i+=this.max_label_height+n:h+=this.text_widths.get(c)+l+o+n}}return!1}_render(){if(0==this.model.items.length)return;if(!(0,b.some)(this.model.items,(t=>t.visible)))return;for(const t of this.model.items)t.legend=this.model;const{ctx:t}=this.layer,e=this.compute_legend_bbox();t.save(),this._draw_legend_box(t,e),this._draw_legend_items(t,e),this._draw_title(t,e),t.restore()}_draw_legend_box(t,e){t.beginPath(),t.rect(e.x,e.y,e.width,e.height),this.visuals.background_fill.apply(t),this.visuals.border_line.apply(t)}_draw_legend_items(t,e){const{glyph_width:i,glyph_height:l}=this.model,{legend_padding:s}=this,n=this.model.spacing,{label_standoff:o}=this.model;let h=s,a=s;const _=\"vertical\"==this.model.orientation;for(const r of this.model.items){if(!r.visible)continue;const d=r.get_labels_list_from_label_prop(),c=r.get_field_from_label_prop();if(0==d.length)continue;const g=(()=>{switch(this.model.click_policy){case\"none\":return!0;case\"hide\":return(0,b.every)(r.renderers,(t=>t.visible));case\"mute\":return(0,b.every)(r.renderers,(t=>!t.muted))}})();for(const m of d){const d=e.x+h,b=e.y+a+this.title_height,f=d+i,u=b+l;_?a+=this.max_label_height+n:h+=this.text_widths.get(m)+i+o+n,this.visuals.label_text.set_value(t),t.fillText(m,f+o,b+this.max_label_height/2);for(const e of r.renderers){const i=this.plot_view.renderer_view(e);null==i||i.draw_legend(t,d,f,b,u,c,m,r.index)}if(!g){let l,n;[l,n]=_?[e.width-2*s,this.max_label_height]:[this.text_widths.get(m)+i+o,this.max_label_height],t.beginPath(),t.rect(d,b,l,n),this.visuals.inactive_fill.set_value(t),t.fill()}}}}_draw_title(t,e){const{title:i}=this.model;i&&this.visuals.title_text.doit&&(t.save(),t.translate(e.x0,e.y0+this.title_height),this.visuals.title_text.set_value(t),t.fillText(i,this.legend_padding,this.legend_padding-this.model.title_standoff),t.restore())}_get_size(){const{width:t,height:e}=this.compute_legend_bbox();return{width:t+2*this.model.margin,height:e+2*this.model.margin}}}i.LegendView=x,x.__name__=\"LegendView\";class p extends h.Annotation{constructor(t){super(t)}initialize(){super.initialize(),this.item_change=new d.Signal0(this,\"item_change\")}get_legend_names(){const t=[];for(const e of this.items){const i=e.get_labels_list_from_label_prop();t.push(...i)}return t}}i.Legend=p,o=p,p.__name__=\"Legend\",o.prototype.default_view=x,o.mixins([[\"label_\",r.Text],[\"title_\",r.Text],[\"inactive_\",r.Fill],[\"border_\",r.Line],[\"background_\",r.Fill]]),o.define((({Number:t,String:e,Array:i,Tuple:l,Or:s,Ref:n,Nullable:o})=>({orientation:[_.Orientation,\"vertical\"],location:[s(_.LegendLocation,l(t,t)),\"top_right\"],title:[o(e),null],title_standoff:[t,5],label_standoff:[t,5],glyph_height:[t,20],glyph_width:[t,20],label_height:[t,20],label_width:[t,20],margin:[t,10],padding:[t,10],spacing:[t,3],items:[i(n(a.LegendItem)),[]],click_policy:[_.LegendClickPolicy,\"none\"]}))),o.override({border_line_color:\"#e5e5e5\",border_line_alpha:.5,border_line_width:1,background_fill_color:\"#ffffff\",background_fill_alpha:.95,inactive_fill_color:\"white\",inactive_fill_alpha:.7,label_text_font_size:\"13px\",label_text_baseline:\"middle\",title_text_font_size:\"13px\",title_text_font_style:\"italic\"})},\n", - " function _(e,r,l,n,t){n();const i=e(1);var s;const o=e(53),a=e(175),_=e(70),u=e(216),d=(0,i.__importStar)(e(18)),c=e(19),f=e(9);class h extends o.Model{constructor(e){super(e)}_check_data_sources_on_renderers(){if(null!=this.get_field_from_label_prop()){if(this.renderers.length<1)return!1;const e=this.renderers[0].data_source;if(null!=e)for(const r of this.renderers)if(r.data_source!=e)return!1}return!0}_check_field_label_on_data_source(){const e=this.get_field_from_label_prop();if(null!=e){if(this.renderers.length<1)return!1;const r=this.renderers[0].data_source;if(null!=r&&!(0,f.includes)(r.columns(),e))return!1}return!0}initialize(){super.initialize(),this.legend=null,this.connect(this.change,(()=>{var e;return null===(e=this.legend)||void 0===e?void 0:e.item_change.emit()}));this._check_data_sources_on_renderers()||c.logger.error(\"Non matching data sources on legend item renderers\");this._check_field_label_on_data_source()||c.logger.error(`Bad column name on label: ${this.label}`)}get_field_from_label_prop(){const{label:e}=this;return(0,u.isField)(e)?e.field:null}get_labels_list_from_label_prop(){if(!this.visible)return[];if((0,u.isValue)(this.label)){const{value:e}=this.label;return null!=e?[e]:[]}const e=this.get_field_from_label_prop();if(null!=e){let r;if(!this.renderers[0]||null==this.renderers[0].data_source)return[\"No source found\"];if(r=this.renderers[0].data_source,r instanceof _.ColumnarDataSource){const l=r.get_column(e);return null!=l?(0,f.uniq)(Array.from(l)):[\"Invalid field\"]}}return[]}}l.LegendItem=h,s=h,h.__name__=\"LegendItem\",s.define((({Boolean:e,Int:r,Array:l,Ref:n,Nullable:t})=>({label:[d.NullStringSpec,null],renderers:[l(n(a.GlyphRenderer)),[]],index:[t(r),null],visible:[e,!0]})))},\n", - " function _(i,n,e,t,u){t();const c=i(8);e.isValue=function(i){return(0,c.isPlainObject)(i)&&\"value\"in i},e.isField=function(i){return(0,c.isPlainObject)(i)&&\"field\"in i},e.isExpr=function(i){return(0,c.isPlainObject)(i)&&\"expr\"in i}},\n", - " function _(t,n,e,s,i){s();const o=t(1);var a;const l=t(40),c=(0,o.__importStar)(t(48)),r=t(20);class _ extends l.AnnotationView{connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render()))}_render(){const{xs:t,ys:n}=this.model;if(t.length!=n.length)return;const e=t.length;if(e<3)return;const{frame:s}=this.plot_view,{ctx:i}=this.layer,o=this.coordinates.x_scale,a=this.coordinates.y_scale,{screen:l}=this.model;function c(t,n,e,s){return l?t:\"data\"==n?e.v_compute(t):s.v_compute(t)}const r=c(t,this.model.xs_units,o,s.bbox.xview),_=c(n,this.model.ys_units,a,s.bbox.yview);i.beginPath();for(let t=0;t({xs:[n(t),[]],xs_units:[r.SpatialUnits,\"data\"],ys:[n(t),[]],ys_units:[r.SpatialUnits,\"data\"]}))),a.internal((({Boolean:t})=>({screen:[t,!1]}))),a.override({fill_color:\"#fff9ba\",fill_alpha:.4,line_color:\"#cccccc\",line_alpha:.3})},\n", - " function _(e,t,n,o,i){o();const s=e(1);var l;const r=e(40),c=(0,s.__importStar)(e(48));class a extends r.AnnotationView{connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render()))}_render(){const{gradient:e,y_intercept:t}=this.model;if(null==e||null==t)return;const{frame:n}=this.plot_view,o=this.coordinates.x_scale,i=this.coordinates.y_scale;let s,l,r,c;if(0==e)s=i.compute(t),l=s,r=n.bbox.left,c=r+n.bbox.width;else{s=n.bbox.top,l=s+n.bbox.height;const a=(i.invert(s)-t)/e,_=(i.invert(l)-t)/e;r=o.compute(a),c=o.compute(_)}const{ctx:a}=this.layer;a.save(),a.beginPath(),this.visuals.line.set_value(a),a.moveTo(r,s),a.lineTo(c,l),a.stroke(),a.restore()}}n.SlopeView=a,a.__name__=\"SlopeView\";class _ extends r.Annotation{constructor(e){super(e)}}n.Slope=_,l=_,_.__name__=\"Slope\",l.prototype.default_view=a,l.mixins(c.Line),l.define((({Number:e,Nullable:t})=>({gradient:[t(e),null],y_intercept:[t(e),null]}))),l.override({line_color:\"black\"})},\n", - " function _(e,t,i,o,n){o();const s=e(1);var l;const a=e(40),r=(0,s.__importStar)(e(48)),c=e(20);class d extends a.AnnotationView{connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.plot_view.request_paint(this)))}_render(){const{location:e}=this.model;if(null==e)return;const{frame:t}=this.plot_view,i=this.coordinates.x_scale,o=this.coordinates.y_scale,n=(t,i)=>\"data\"==this.model.location_units?t.compute(e):this.model.for_hover?e:i.compute(e);let s,l,a,r;\"width\"==this.model.dimension?(a=n(o,t.bbox.yview),l=t.bbox.left,r=t.bbox.width,s=this.model.line_width):(a=t.bbox.top,l=n(i,t.bbox.xview),r=this.model.line_width,s=t.bbox.height);const{ctx:c}=this.layer;c.save(),c.beginPath(),this.visuals.line.set_value(c),c.moveTo(l,a),\"width\"==this.model.dimension?c.lineTo(l+r,a):c.lineTo(l,a+s),c.stroke(),c.restore()}}i.SpanView=d,d.__name__=\"SpanView\";class _ extends a.Annotation{constructor(e){super(e)}}i.Span=_,l=_,_.__name__=\"Span\",l.prototype.default_view=d,l.mixins(r.Line),l.define((({Number:e,Nullable:t})=>({render_mode:[c.RenderMode,\"canvas\"],location:[t(e),null],location_units:[c.SpatialUnits,\"data\"],dimension:[c.Dimension,\"width\"]}))),l.internal((({Boolean:e})=>({for_hover:[e,!1]}))),l.override({line_color:\"black\"})},\n", - " function _(i,e,t,o,l){var s;o();const a=i(40),_=i(221),n=i(113),r=i(43),h=i(123),b=i(65);class v extends a.AnnotationView{constructor(){super(...arguments),this._invalidate_toolbar=!0,this._previous_bbox=new b.BBox}update_layout(){this.layout=new h.SideLayout(this.panel,(()=>this.get_size()),!0)}initialize(){super.initialize(),this.el=(0,r.div)(),this.plot_view.canvas_view.add_event(this.el)}async lazy_initialize(){await super.lazy_initialize(),this._toolbar_view=await(0,n.build_view)(this.model.toolbar,{parent:this}),this.plot_view.visibility_callbacks.push((i=>this._toolbar_view.set_visibility(i)))}remove(){this._toolbar_view.remove(),(0,r.remove)(this.el),super.remove()}render(){this.model.visible||(0,r.undisplay)(this.el),super.render()}_render(){const{bbox:i}=this.layout;this._previous_bbox.equals(i)||((0,r.position)(this.el,i),this._previous_bbox=i,this._invalidate_toolbar=!0),this._invalidate_toolbar&&(this.el.style.position=\"absolute\",this.el.style.overflow=\"hidden\",(0,r.empty)(this.el),this.el.appendChild(this._toolbar_view.el),this._toolbar_view.layout.bbox=i,this._toolbar_view.render(),this._invalidate_toolbar=!1),(0,r.display)(this.el)}_get_size(){const{tools:i,logo:e}=this.model.toolbar;return{width:30*i.length+(null!=e?25:0)+15,height:30}}}t.ToolbarPanelView=v,v.__name__=\"ToolbarPanelView\";class d extends a.Annotation{constructor(i){super(i)}}t.ToolbarPanel=d,s=d,d.__name__=\"ToolbarPanel\",s.prototype.default_view=v,s.define((({Ref:i})=>({toolbar:[i(_.Toolbar)]})))},\n", - " function _(t,e,s,i,o){var c;i();const n=t(8),a=t(9),l=t(13),r=t(222),_=t(223),u=t(232),p=t(233);function v(t){switch(t){case\"tap\":return\"active_tap\";case\"pan\":return\"active_drag\";case\"pinch\":case\"scroll\":return\"active_scroll\";case\"multi\":return\"active_multi\"}return null}function h(t){return\"tap\"==t||\"pan\"==t}s.Drag=r.Tool,s.Inspection=r.Tool,s.Scroll=r.Tool,s.Tap=r.Tool;class f extends p.ToolbarBase{constructor(t){super(t)}connect_signals(){super.connect_signals();const{tools:t,active_drag:e,active_inspect:s,active_scroll:i,active_tap:o,active_multi:c}=this.properties;this.on_change([t,e,s,i,o,c],(()=>this._init_tools()))}_init_tools(){if(super._init_tools(),\"auto\"==this.active_inspect);else if(this.active_inspect instanceof u.InspectTool){let t=!1;for(const e of this.inspectors)e!=this.active_inspect?e.active=!1:t=!0;t||(this.active_inspect=null)}else if((0,n.isArray)(this.active_inspect)){const t=(0,a.intersection)(this.active_inspect,this.inspectors);t.length!=this.active_inspect.length&&(this.active_inspect=t);for(const t of this.inspectors)(0,a.includes)(this.active_inspect,t)||(t.active=!1)}else if(null==this.active_inspect)for(const t of this.inspectors)t.active=!1;const t=t=>{t.active?this._active_change(t):t.active=!0};for(const t of(0,l.values)(this.gestures)){t.tools=(0,a.sort_by)(t.tools,(t=>t.default_order));for(const e of t.tools)this.connect(e.properties.active.change,(()=>this._active_change(e)))}for(const[e,s]of(0,l.entries)(this.gestures)){const i=v(e);if(i){const o=this[i];\"auto\"==o?0!=s.tools.length&&h(e)&&t(s.tools[0]):null!=o&&((0,a.includes)(this.tools,o)?t(o):this[i]=null)}}}}s.Toolbar=f,c=f,f.__name__=\"Toolbar\",c.prototype.default_view=p.ToolbarBaseView,c.define((({Or:t,Ref:e,Auto:i,Null:o})=>({active_drag:[t(e(s.Drag),i,o),\"auto\"],active_inspect:[t(e(s.Inspection),i,o),\"auto\"],active_scroll:[t(e(s.Scroll),i,o),\"auto\"],active_tap:[t(e(s.Tap),i,o),\"auto\"],active_multi:[t(e(_.GestureTool),i,o),\"auto\"]})))},\n", - " function _(t,e,n,o,s){var i;o();const a=t(42),r=t(9),l=t(53);class c extends a.View{get plot_view(){return this.parent}get plot_model(){return this.parent.model}connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,(()=>{this.model.active?this.activate():this.deactivate()}))}activate(){}deactivate(){}}n.ToolView=c,c.__name__=\"ToolView\";class _ extends l.Model{constructor(t){super(t)}get synthetic_renderers(){return[]}_get_dim_limits([t,e],[n,o],s,i){const a=s.bbox.h_range;let l;\"width\"==i||\"both\"==i?(l=[(0,r.min)([t,n]),(0,r.max)([t,n])],l=[(0,r.max)([l[0],a.start]),(0,r.min)([l[1],a.end])]):l=[a.start,a.end];const c=s.bbox.v_range;let _;return\"height\"==i||\"both\"==i?(_=[(0,r.min)([e,o]),(0,r.max)([e,o])],_=[(0,r.max)([_[0],c.start]),(0,r.min)([_[1],c.end])]):_=[c.start,c.end],[l,_]}static register_alias(t,e){this.prototype._known_aliases.set(t,e)}static from_string(t){const e=this.prototype._known_aliases.get(t);if(null!=e)return e();{const e=[...this.prototype._known_aliases.keys()];throw new Error(`unexpected tool name '${t}', possible tools are ${e.join(\", \")}`)}}}n.Tool=_,i=_,_.__name__=\"Tool\",i.prototype._known_aliases=new Map,i.define((({String:t,Nullable:e})=>({description:[e(t),null]}))),i.internal((({Boolean:t})=>({active:[t,!1]})))},\n", - " function _(e,o,t,s,n){s();const u=e(224),_=e(231);class l extends u.ButtonToolView{}t.GestureToolView=l,l.__name__=\"GestureToolView\";class i extends u.ButtonTool{constructor(e){super(e),this.button_view=_.OnOffButtonView}}t.GestureTool=i,i.__name__=\"GestureTool\"},\n", - " function _(t,e,o,s,i){s();const n=t(1);var l;const r=(0,n.__importDefault)(t(225)),a=t(226),u=t(222),h=t(43),_=t(34),d=t(8),c=t(9),m=(0,n.__importStar)(t(227)),p=m,v=(0,n.__importDefault)(t(228)),f=(0,n.__importDefault)(t(229)),g=t(230);class b extends a.DOMView{initialize(){super.initialize();const t=this.model.menu;if(null!=t){const e=this.parent.model.toolbar_location,o=\"left\"==e||\"above\"==e,s=this.parent.model.horizontal?\"vertical\":\"horizontal\";this._menu=new g.ContextMenu(o?(0,c.reversed)(t):t,{orientation:s,prevent_hide:t=>t.target==this.el})}this._hammer=new r.default(this.el,{touchAction:\"auto\",inputClass:r.default.TouchMouseInput}),this.connect(this.model.change,(()=>this.render())),this._hammer.on(\"tap\",(t=>{var e;(null===(e=this._menu)||void 0===e?void 0:e.is_open)?this._menu.hide():t.target==this.el&&this._clicked()})),this._hammer.on(\"press\",(()=>this._pressed())),this.el.addEventListener(\"keydown\",(t=>{t.keyCode==h.Keys.Enter&&this._clicked()}))}remove(){var t;this._hammer.destroy(),null===(t=this._menu)||void 0===t||t.remove(),super.remove()}styles(){return[...super.styles(),m.default,v.default,f.default]}css_classes(){return super.css_classes().concat(p.toolbar_button)}render(){(0,h.empty)(this.el);const t=this.model.computed_icon;(0,d.isString)(t)&&((0,_.startsWith)(t,\"data:image\")?this.el.style.backgroundImage=`url(\"${t}\")`:this.el.classList.add(t)),this.el.title=this.model.tooltip,this.el.tabIndex=0,null!=this._menu&&this.root.el.appendChild(this._menu.el)}_pressed(){var t;const e=(()=>{switch(this.parent.model.toolbar_location){case\"right\":return{left_of:this.el};case\"left\":return{right_of:this.el};case\"above\":return{below:this.el};case\"below\":return{above:this.el}}})();null===(t=this._menu)||void 0===t||t.toggle(e)}}o.ButtonToolButtonView=b,b.__name__=\"ButtonToolButtonView\";class w extends u.ToolView{}o.ButtonToolView=w,w.__name__=\"ButtonToolView\";class y extends u.Tool{constructor(t){super(t)}_get_dim_tooltip(t){const{description:e,tool_name:o}=this;return null!=e?e:\"both\"==t?o:`${o} (${\"width\"==t?\"x\":\"y\"}-axis)`}get tooltip(){var t;return null!==(t=this.description)&&void 0!==t?t:this.tool_name}get computed_icon(){return this.icon}get menu(){return null}}o.ButtonTool=y,l=y,y.__name__=\"ButtonTool\",l.internal((({Boolean:t})=>({disabled:[t,!1]})))},\n", - " function _(t,e,i,n,r){\n", - " /*! Hammer.JS - v2.0.7 - 2016-04-22\n", - " * http://hammerjs.github.io/\n", - " *\n", - " * Copyright (c) 2016 Jorik Tangelder;\n", - " * Licensed under the MIT license */\n", - " !function(t,i,n,r){\"use strict\";var s,o=[\"\",\"webkit\",\"Moz\",\"MS\",\"ms\",\"o\"],a=i.createElement(\"div\"),h=Math.round,u=Math.abs,c=Date.now;function l(t,e,i){return setTimeout(T(t,i),e)}function p(t,e,i){return!!Array.isArray(t)&&(f(t,i[e],i),!0)}function f(t,e,i){var n;if(t)if(t.forEach)t.forEach(e,i);else if(t.length!==r)for(n=0;n\\s*\\(/gm,\"{anonymous}()@\"):\"Unknown Stack Trace\",s=t.console&&(t.console.warn||t.console.log);return s&&s.call(t.console,r,n),e.apply(this,arguments)}}s=\"function\"!=typeof Object.assign?function(t){if(t===r||null===t)throw new TypeError(\"Cannot convert undefined or null to object\");for(var e=Object(t),i=1;i-1}function S(t){return t.trim().split(/\\s+/g)}function b(t,e,i){if(t.indexOf&&!i)return t.indexOf(e);for(var n=0;ni[e]})):n.sort()),n}function x(t,e){for(var i,n,s=e[0].toUpperCase()+e.slice(1),a=0;a1&&!i.firstMultiple?i.firstMultiple=H(e):1===s&&(i.firstMultiple=!1);var o=i.firstInput,a=i.firstMultiple,h=a?a.center:o.center,l=e.center=L(n);e.timeStamp=c(),e.deltaTime=e.timeStamp-o.timeStamp,e.angle=G(h,l),e.distance=j(h,l),function(t,e){var i=e.center,n=t.offsetDelta||{},r=t.prevDelta||{},s=t.prevInput||{};1!==e.eventType&&4!==s.eventType||(r=t.prevDelta={x:s.deltaX||0,y:s.deltaY||0},n=t.offsetDelta={x:i.x,y:i.y});e.deltaX=r.x+(i.x-n.x),e.deltaY=r.y+(i.y-n.y)}(i,e),e.offsetDirection=V(e.deltaX,e.deltaY);var p=U(e.deltaTime,e.deltaX,e.deltaY);e.overallVelocityX=p.x,e.overallVelocityY=p.y,e.overallVelocity=u(p.x)>u(p.y)?p.x:p.y,e.scale=a?(f=a.pointers,v=n,j(v[0],v[1],W)/j(f[0],f[1],W)):1,e.rotation=a?function(t,e){return G(e[1],e[0],W)+G(t[1],t[0],W)}(a.pointers,n):0,e.maxPointers=i.prevInput?e.pointers.length>i.prevInput.maxPointers?e.pointers.length:i.prevInput.maxPointers:e.pointers.length,function(t,e){var i,n,s,o,a=t.lastInterval||e,h=e.timeStamp-a.timeStamp;if(8!=e.eventType&&(h>25||a.velocity===r)){var c=e.deltaX-a.deltaX,l=e.deltaY-a.deltaY,p=U(h,c,l);n=p.x,s=p.y,i=u(p.x)>u(p.y)?p.x:p.y,o=V(c,l),t.lastInterval=e}else i=a.velocity,n=a.velocityX,s=a.velocityY,o=a.direction;e.velocity=i,e.velocityX=n,e.velocityY=s,e.direction=o}(i,e);var f,v;var d=t.element;_(e.srcEvent.target,d)&&(d=e.srcEvent.target);e.target=d}(t,i),t.emit(\"hammer.input\",i),t.recognize(i),t.session.prevInput=i}function H(t){for(var e=[],i=0;i=u(e)?t<0?2:4:e<0?8:16}function j(t,e,i){i||(i=F);var n=e[i[0]]-t[i[0]],r=e[i[1]]-t[i[1]];return Math.sqrt(n*n+r*r)}function G(t,e,i){i||(i=F);var n=e[i[0]]-t[i[0]],r=e[i[1]]-t[i[1]];return 180*Math.atan2(r,n)/Math.PI}q.prototype={handler:function(){},init:function(){this.evEl&&I(this.element,this.evEl,this.domHandler),this.evTarget&&I(this.target,this.evTarget,this.domHandler),this.evWin&&I(O(this.element),this.evWin,this.domHandler)},destroy:function(){this.evEl&&A(this.element,this.evEl,this.domHandler),this.evTarget&&A(this.target,this.evTarget,this.domHandler),this.evWin&&A(O(this.element),this.evWin,this.domHandler)}};var Z={mousedown:1,mousemove:2,mouseup:4},B=\"mousedown\",$=\"mousemove mouseup\";function J(){this.evEl=B,this.evWin=$,this.pressed=!1,q.apply(this,arguments)}g(J,q,{handler:function(t){var e=Z[t.type];1&e&&0===t.button&&(this.pressed=!0),2&e&&1!==t.which&&(e=4),this.pressed&&(4&e&&(this.pressed=!1),this.callback(this.manager,e,{pointers:[t],changedPointers:[t],pointerType:X,srcEvent:t}))}});var K={pointerdown:1,pointermove:2,pointerup:4,pointercancel:8,pointerout:8},Q={2:N,3:\"pen\",4:X,5:\"kinect\"},tt=\"pointerdown\",et=\"pointermove pointerup pointercancel\";function it(){this.evEl=tt,this.evWin=et,q.apply(this,arguments),this.store=this.manager.session.pointerEvents=[]}t.MSPointerEvent&&!t.PointerEvent&&(tt=\"MSPointerDown\",et=\"MSPointerMove MSPointerUp MSPointerCancel\"),g(it,q,{handler:function(t){var e=this.store,i=!1,n=t.type.toLowerCase().replace(\"ms\",\"\"),r=K[n],s=Q[t.pointerType]||t.pointerType,o=s==N,a=b(e,t.pointerId,\"pointerId\");1&r&&(0===t.button||o)?a<0&&(e.push(t),a=e.length-1):12&r&&(i=!0),a<0||(e[a]=t,this.callback(this.manager,r,{pointers:e,changedPointers:[t],pointerType:s,srcEvent:t}),i&&e.splice(a,1))}});var nt={touchstart:1,touchmove:2,touchend:4,touchcancel:8},rt=\"touchstart\",st=\"touchstart touchmove touchend touchcancel\";function ot(){this.evTarget=rt,this.evWin=st,this.started=!1,q.apply(this,arguments)}function at(t,e){var i=P(t.touches),n=P(t.changedTouches);return 12&e&&(i=D(i.concat(n),\"identifier\",!0)),[i,n]}g(ot,q,{handler:function(t){var e=nt[t.type];if(1===e&&(this.started=!0),this.started){var i=at.call(this,t,e);12&e&&i[0].length-i[1].length==0&&(this.started=!1),this.callback(this.manager,e,{pointers:i[0],changedPointers:i[1],pointerType:N,srcEvent:t})}}});var ht={touchstart:1,touchmove:2,touchend:4,touchcancel:8},ut=\"touchstart touchmove touchend touchcancel\";function ct(){this.evTarget=ut,this.targetIds={},q.apply(this,arguments)}function lt(t,e){var i=P(t.touches),n=this.targetIds;if(3&e&&1===i.length)return n[i[0].identifier]=!0,[i,i];var r,s,o=P(t.changedTouches),a=[],h=this.target;if(s=i.filter((function(t){return _(t.target,h)})),1===e)for(r=0;r-1&&n.splice(t,1)}),2500)}}function dt(t){for(var e=t.srcEvent.clientX,i=t.srcEvent.clientY,n=0;n-1&&this.requireFail.splice(e,1),this},hasRequireFailures:function(){return this.requireFail.length>0},canRecognizeWith:function(t){return!!this.simultaneous[t.id]},emit:function(t){var e=this,i=this.state;function n(i){e.manager.emit(i,t)}i<8&&n(e.options.event+Dt(i)),n(e.options.event),t.additionalEvent&&n(t.additionalEvent),i>=8&&n(e.options.event+Dt(i))},tryEmit:function(t){if(this.canEmit())return this.emit(t);this.state=bt},canEmit:function(){for(var t=0;te.threshold&&r&e.direction},attrTest:function(t){return Ot.prototype.attrTest.call(this,t)&&(2&this.state||!(2&this.state)&&this.directionTest(t))},emit:function(t){this.pX=t.deltaX,this.pY=t.deltaY;var e=xt(t.direction);e&&(t.additionalEvent=this.options.event+e),this._super.emit.call(this,t)}}),g(Mt,Ot,{defaults:{event:\"pinch\",threshold:0,pointers:2},getTouchAction:function(){return[It]},attrTest:function(t){return this._super.attrTest.call(this,t)&&(Math.abs(t.scale-1)>this.options.threshold||2&this.state)},emit:function(t){if(1!==t.scale){var e=t.scale<1?\"in\":\"out\";t.additionalEvent=this.options.event+e}this._super.emit.call(this,t)}}),g(zt,Pt,{defaults:{event:\"press\",pointers:1,time:251,threshold:9},getTouchAction:function(){return[yt]},process:function(t){var e=this.options,i=t.pointers.length===e.pointers,n=t.distancee.time;if(this._input=t,!n||!i||12&t.eventType&&!r)this.reset();else if(1&t.eventType)this.reset(),this._timer=l((function(){this.state=8,this.tryEmit()}),e.time,this);else if(4&t.eventType)return 8;return bt},reset:function(){clearTimeout(this._timer)},emit:function(t){8===this.state&&(t&&4&t.eventType?this.manager.emit(this.options.event+\"up\",t):(this._input.timeStamp=c(),this.manager.emit(this.options.event,this._input)))}}),g(Nt,Ot,{defaults:{event:\"rotate\",threshold:0,pointers:2},getTouchAction:function(){return[It]},attrTest:function(t){return this._super.attrTest.call(this,t)&&(Math.abs(t.rotation)>this.options.threshold||2&this.state)}}),g(Xt,Ot,{defaults:{event:\"swipe\",threshold:10,velocity:.3,direction:30,pointers:1},getTouchAction:function(){return Rt.prototype.getTouchAction.call(this)},attrTest:function(t){var e,i=this.options.direction;return 30&i?e=t.overallVelocity:6&i?e=t.overallVelocityX:i&Y&&(e=t.overallVelocityY),this._super.attrTest.call(this,t)&&i&t.offsetDirection&&t.distance>this.options.threshold&&t.maxPointers==this.options.pointers&&u(e)>this.options.velocity&&4&t.eventType},emit:function(t){var e=xt(t.offsetDirection);e&&this.manager.emit(this.options.event+e,t),this.manager.emit(this.options.event,t)}}),g(Yt,Pt,{defaults:{event:\"tap\",pointers:1,taps:1,interval:300,time:250,threshold:9,posThreshold:10},getTouchAction:function(){return[Et]},process:function(t){var e=this.options,i=t.pointers.length===e.pointers,n=t.distance .bk-divider{cursor:default;overflow:hidden;background-color:#e5e5e5;}.bk-root .bk-context-menu.bk-horizontal > .bk-divider{width:1px;margin:5px 0;}.bk-root .bk-context-menu.bk-vertical > .bk-divider{height:1px;margin:0 5px;}.bk-root .bk-context-menu > :not(.bk-divider){border:1px solid transparent;}.bk-root .bk-context-menu > :not(.bk-divider).bk-active{border-color:#26aae1;}.bk-root .bk-context-menu > :not(.bk-divider):hover{background-color:#f9f9f9;}.bk-root .bk-context-menu > :not(.bk-divider):focus,.bk-root .bk-context-menu > :not(.bk-divider):focus-visible{outline:1px dotted #26aae1;outline-offset:-1px;}.bk-root .bk-context-menu > :not(.bk-divider)::-moz-focus-inner{border:0;}.bk-root .bk-context-menu.bk-horizontal > :not(.bk-divider):first-child{border-top-left-radius:4px;border-bottom-left-radius:4px;}.bk-root .bk-context-menu.bk-horizontal > :not(.bk-divider):last-child{border-top-right-radius:4px;border-bottom-right-radius:4px;}.bk-root .bk-context-menu.bk-vertical > :not(.bk-divider):first-child{border-top-left-radius:4px;border-top-right-radius:4px;}.bk-root .bk-context-menu.bk-vertical > :not(.bk-divider):last-child{border-bottom-left-radius:4px;border-bottom-right-radius:4px;}.bk-root .bk-menu{position:absolute;left:0;width:100%;z-index:100;cursor:pointer;font-size:12px;background-color:#fff;border:1px solid #ccc;border-radius:4px;box-shadow:0 6px 12px rgba(0, 0, 0, 0.175);}.bk-root .bk-menu.bk-above{bottom:100%;}.bk-root .bk-menu.bk-below{top:100%;}.bk-root .bk-menu > .bk-divider{height:1px;margin:7.5px 0;overflow:hidden;background-color:#e5e5e5;}.bk-root .bk-menu > :not(.bk-divider){padding:6px 12px;}.bk-root .bk-menu > :not(.bk-divider):hover,.bk-root .bk-menu > :not(.bk-divider).bk-active{background-color:#e6e6e6;}.bk-root .bk-caret{display:inline-block;vertical-align:middle;width:0;height:0;margin:0 5px;}.bk-root .bk-caret.bk-down{border-top:4px solid;}.bk-root .bk-caret.bk-up{border-bottom:4px solid;}.bk-root .bk-caret.bk-down,.bk-root .bk-caret.bk-up{border-right:4px solid transparent;border-left:4px solid transparent;}.bk-root .bk-caret.bk-left{border-right:4px solid;}.bk-root .bk-caret.bk-right{border-left:4px solid;}.bk-root .bk-caret.bk-left,.bk-root .bk-caret.bk-right{border-top:4px solid transparent;border-bottom:4px solid transparent;}\"},\n", - " function _(t,e,i,n,o){n();const s=t(1),l=t(43),h=t(9),r=(0,s.__importStar)(t(229));class d{constructor(t,e={}){var i,n;this.items=t,this.el=(0,l.div)(),this._open=!1,this._item_click=t=>{var e;null===(e=t.handler)||void 0===e||e.call(t),this.hide()},this._on_mousedown=t=>{var e;const{target:i}=t;i instanceof Node&&this.el.contains(i)||(null===(e=this.prevent_hide)||void 0===e?void 0:e.call(this,t))||this.hide()},this._on_keydown=t=>{t.keyCode==l.Keys.Esc&&this.hide()},this._on_blur=()=>{this.hide()},this.orientation=null!==(i=e.orientation)&&void 0!==i?i:\"vertical\",this.reversed=null!==(n=e.reversed)&&void 0!==n&&n,this.prevent_hide=e.prevent_hide,(0,l.undisplay)(this.el)}get is_open(){return this._open}get can_open(){return 0!=this.items.length}remove(){(0,l.remove)(this.el),this._unlisten()}_listen(){document.addEventListener(\"mousedown\",this._on_mousedown),document.addEventListener(\"keydown\",this._on_keydown),window.addEventListener(\"blur\",this._on_blur)}_unlisten(){document.removeEventListener(\"mousedown\",this._on_mousedown),document.removeEventListener(\"keydown\",this._on_keydown),window.removeEventListener(\"blur\",this._on_blur)}_position(t){const e=this.el.parentElement;if(null!=e){const i=(()=>{if(\"left_of\"in t){const{left:e,top:i}=t.left_of.getBoundingClientRect();return{right:e,top:i}}if(\"right_of\"in t){const{top:e,right:i}=t.right_of.getBoundingClientRect();return{left:i,top:e}}if(\"below\"in t){const{left:e,bottom:i}=t.below.getBoundingClientRect();return{left:e,top:i}}if(\"above\"in t){const{left:e,top:i}=t.above.getBoundingClientRect();return{left:e,bottom:i}}return t})(),n=e.getBoundingClientRect();this.el.style.left=null!=i.left?i.left-n.left+\"px\":\"\",this.el.style.top=null!=i.top?i.top-n.top+\"px\":\"\",this.el.style.right=null!=i.right?n.right-i.right+\"px\":\"\",this.el.style.bottom=null!=i.bottom?n.bottom-i.bottom+\"px\":\"\"}}render(){var t;(0,l.empty)(this.el,!0),(0,l.classes)(this.el).add(\"bk-context-menu\",`bk-${this.orientation}`);const e=this.reversed?(0,h.reversed)(this.items):this.items;for(const i of e){let e;if(null==i)e=(0,l.div)({class:r.divider});else{if(null!=i.if&&!i.if())continue;if(null!=i.content)e=i.content;else{const n=null!=i.icon?(0,l.div)({class:[\"bk-menu-icon\",i.icon]}):null,o=[(null===(t=i.active)||void 0===t?void 0:t.call(i))?\"bk-active\":null,i.class];e=(0,l.div)({class:o,title:i.tooltip,tabIndex:0},n,i.label,i.content),e.addEventListener(\"click\",(()=>{this._item_click(i)})),e.addEventListener(\"keydown\",(t=>{t.keyCode==l.Keys.Enter&&this._item_click(i)}))}}this.el.appendChild(e)}}show(t){if(0!=this.items.length&&!this._open){if(this.render(),0==this.el.children.length)return;this._position(null!=t?t:{left:0,top:0}),(0,l.display)(this.el),this._listen(),this._open=!0}}hide(){this._open&&(this._open=!1,this._unlisten(),(0,l.undisplay)(this.el))}toggle(t){this._open?this.hide():this.show(t)}}i.ContextMenu=d,d.__name__=\"ContextMenu\"},\n", - " function _(t,e,i,n,o){n();const s=t(1),c=t(224),l=(0,s.__importStar)(t(227)),a=t(43);class _ extends c.ButtonToolButtonView{render(){super.render(),(0,a.classes)(this.el).toggle(l.active,this.model.active)}_clicked(){const{active:t}=this.model;this.model.active=!t}}i.OnOffButtonView=_,_.__name__=\"OnOffButtonView\"},\n", - " function _(e,o,t,n,s){var c;n();const l=e(224),_=e(231);class i extends l.ButtonToolView{}t.InspectToolView=i,i.__name__=\"InspectToolView\";class a extends l.ButtonTool{constructor(e){super(e),this.event_type=\"move\"}}t.InspectTool=a,c=a,a.__name__=\"InspectTool\",c.prototype.button_view=_.OnOffButtonView,c.define((({Boolean:e})=>({toggleable:[e,!0]}))),c.override({active:!0})},\n", - " function _(t,o,e,l,i){l();const s=t(1);var n,a;const r=t(19),c=t(43),h=t(113),_=t(226),u=t(20),v=t(9),d=t(234),p=t(13),b=t(8),g=t(235),f=t(65),m=t(53),w=t(222),y=t(223),T=t(238),z=t(239),x=t(232),B=t(230),C=(0,s.__importStar)(t(227)),k=C,L=(0,s.__importStar)(t(240)),M=L;class S extends m.Model{constructor(t){super(t)}get visible(){var t;return!this.autohide||null!==(t=this._visible)&&void 0!==t&&t}}e.ToolbarViewModel=S,n=S,S.__name__=\"ToolbarViewModel\",n.define((({Boolean:t})=>({autohide:[t,!1]}))),n.internal((({Boolean:t,Nullable:o})=>({_visible:[o(t),null]})));class $ extends _.DOMView{constructor(){super(...arguments),this.layout={bbox:new f.BBox}}initialize(){super.initialize(),this._tool_button_views=new Map,this._toolbar_view_model=new S({autohide:this.model.autohide});const{toolbar_location:t}=this.model,o=\"left\"==t||\"above\"==t,e=this.model.horizontal?\"vertical\":\"horizontal\";this._overflow_menu=new B.ContextMenu([],{orientation:e,reversed:o})}async lazy_initialize(){await super.lazy_initialize(),await this._build_tool_button_views()}connect_signals(){super.connect_signals(),this.connect(this.model.properties.tools.change,(async()=>{await this._build_tool_button_views(),this.render()})),this.connect(this.model.properties.autohide.change,(()=>{this._toolbar_view_model.autohide=this.model.autohide,this._on_visible_change()})),this.connect(this._toolbar_view_model.properties._visible.change,(()=>this._on_visible_change()))}styles(){return[...super.styles(),C.default,L.default]}remove(){(0,h.remove_views)(this._tool_button_views),super.remove()}async _build_tool_button_views(){const t=null!=this.model._proxied_tools?this.model._proxied_tools:this.model.tools;await(0,h.build_views)(this._tool_button_views,t,{parent:this},(t=>t.button_view))}set_visibility(t){t!=this._toolbar_view_model._visible&&(this._toolbar_view_model._visible=t)}_on_visible_change(){const{visible:t}=this._toolbar_view_model;(0,c.classes)(this.el).toggle(k.toolbar_hidden,!t)}render(){(0,c.empty)(this.el),this.el.classList.add(k.toolbar),this.el.classList.add(k[this.model.toolbar_location]),this._toolbar_view_model.autohide=this.model.autohide,this._on_visible_change();const{horizontal:t}=this.model;let o=0;if(null!=this.model.logo){const e=\"grey\"===this.model.logo?M.grey:null,l=(0,c.a)({href:\"https://bokeh.org/\",target:\"_blank\",class:[M.logo,M.logo_small,e]});this.el.appendChild(l);const{width:i,height:s}=l.getBoundingClientRect();o+=t?i:s}for(const[,t]of this._tool_button_views)t.render();const e=[],l=t=>this._tool_button_views.get(t).el,{gestures:i}=this.model;for(const t of(0,p.values)(i))e.push(t.tools.map(l));e.push(this.model.actions.map(l)),e.push(this.model.inspectors.filter((t=>t.toggleable)).map(l));const s=e.filter((t=>0!=t.length)),n=()=>(0,c.div)({class:k.divider}),{bbox:a}=this.layout;let r=!1;this.root.el.appendChild(this._overflow_menu.el);const h=(0,c.div)({class:k.tool_overflow,tabIndex:0},t?\"\\u22ee\":\"\\u22ef\"),_=()=>{const t=(()=>{switch(this.model.toolbar_location){case\"right\":return{left_of:h};case\"left\":return{right_of:h};case\"above\":return{below:h};case\"below\":return{above:h}}})();this._overflow_menu.toggle(t)};h.addEventListener(\"click\",(()=>{_()})),h.addEventListener(\"keydown\",(t=>{t.keyCode==c.Keys.Enter&&_()}));for(const e of(0,d.join)(s,n))if(r)this._overflow_menu.items.push({content:e,class:t?k.right:k.above});else{this.el.appendChild(e);const{width:l,height:i}=e.getBoundingClientRect();if(o+=t?l:i,r=t?o>a.width-15:o>a.height-15,r){this.el.removeChild(e),this.el.appendChild(h);const{items:t}=this._overflow_menu;t.splice(0,t.length),t.push({content:e})}}}update_layout(){}update_position(){}after_layout(){this._has_finished=!0}export(t,o=!0){const e=\"png\"==t?\"canvas\":\"svg\",l=new g.CanvasLayer(e,o);return l.resize(0,0),l}}function V(){return{pan:{tools:[],active:null},scroll:{tools:[],active:null},pinch:{tools:[],active:null},tap:{tools:[],active:null},doubletap:{tools:[],active:null},press:{tools:[],active:null},pressup:{tools:[],active:null},rotate:{tools:[],active:null},move:{tools:[],active:null},multi:{tools:[],active:null}}}e.ToolbarBaseView=$,$.__name__=\"ToolbarBaseView\";class A extends m.Model{constructor(t){super(t)}initialize(){super.initialize(),this._init_tools()}_init_tools(){const t=function(t,o){if(t.length!=o.length)return!0;const e=new Set(o.map((t=>t.id)));return(0,v.some)(t,(t=>!e.has(t.id)))},o=this.tools.filter((t=>t instanceof x.InspectTool));t(this.inspectors,o)&&(this.inspectors=o);const e=this.tools.filter((t=>t instanceof z.HelpTool));t(this.help,e)&&(this.help=e);const l=this.tools.filter((t=>t instanceof T.ActionTool));t(this.actions,l)&&(this.actions=l);const i=(t,o)=>{t in this.gestures||r.logger.warn(`Toolbar: unknown event type '${t}' for tool: ${o}`)},s={pan:{tools:[],active:null},scroll:{tools:[],active:null},pinch:{tools:[],active:null},tap:{tools:[],active:null},doubletap:{tools:[],active:null},press:{tools:[],active:null},pressup:{tools:[],active:null},rotate:{tools:[],active:null},move:{tools:[],active:null},multi:{tools:[],active:null}};for(const t of this.tools)if(t instanceof y.GestureTool&&t.event_type)if((0,b.isString)(t.event_type))s[t.event_type].tools.push(t),i(t.event_type,t);else{s.multi.tools.push(t);for(const o of t.event_type)i(o,t)}for(const o of Object.keys(s)){const e=this.gestures[o];t(e.tools,s[o].tools)&&(e.tools=s[o].tools),e.active&&(0,v.every)(e.tools,(t=>t.id!=e.active.id))&&(e.active=null)}}get horizontal(){return\"above\"===this.toolbar_location||\"below\"===this.toolbar_location}get vertical(){return\"left\"===this.toolbar_location||\"right\"===this.toolbar_location}_active_change(t){const{event_type:o}=t;if(null==o)return;const e=(0,b.isString)(o)?[o]:o;for(const o of e)if(t.active){const e=this.gestures[o].active;null!=e&&t!=e&&(r.logger.debug(`Toolbar: deactivating tool: ${e} for event type '${o}'`),e.active=!1),this.gestures[o].active=t,r.logger.debug(`Toolbar: activating tool: ${t} for event type '${o}'`)}else this.gestures[o].active=null}}e.ToolbarBase=A,a=A,A.__name__=\"ToolbarBase\",a.prototype.default_view=$,a.define((({Boolean:t,Array:o,Ref:e,Nullable:l})=>({tools:[o(e(w.Tool)),[]],logo:[l(u.Logo),\"normal\"],autohide:[t,!1]}))),a.internal((({Array:t,Struct:o,Ref:e,Nullable:l})=>{const i=o({tools:t(e(y.GestureTool)),active:l(e(w.Tool))});return{gestures:[o({pan:i,scroll:i,pinch:i,tap:i,doubletap:i,press:i,pressup:i,rotate:i,move:i,multi:i}),V],actions:[t(e(T.ActionTool)),[]],inspectors:[t(e(x.InspectTool)),[]],help:[t(e(z.HelpTool)),[]],toolbar_location:[u.Location,\"right\"]}}))},\n", - " function _(n,o,e,t,f){t();const r=n(9);function*i(n,o){const e=n.length;if(o>e)return;const t=(0,r.range)(o);for(yield t.map((o=>n[o]));;){let f;for(const n of(0,r.reversed)((0,r.range)(o)))if(t[n]!=n+e-o){f=n;break}if(null==f)return;t[f]+=1;for(const n of(0,r.range)(f+1,o))t[n]=t[n-1]+1;yield t.map((o=>n[o]))}}e.enumerate=function*(n){let o=0;for(const e of n)yield[e,o++]},e.join=function*(n,o){let e=!0;for(const t of n)e?e=!1:null!=o&&(yield o()),yield*t},e.combinations=i,e.subsets=function*(n){for(const o of(0,r.range)(n.length+1))yield*i(n,o)}},\n", - " function _(t,e,s,i,n){i();const o=t(236),a=t(65),r=t(43);function h(t){!function(t){void 0===t.lineDash&&Object.defineProperty(t,\"lineDash\",{get:()=>t.getLineDash(),set:e=>t.setLineDash(e)})}(t),function(t){t.setImageSmoothingEnabled=e=>{t.imageSmoothingEnabled=e,t.mozImageSmoothingEnabled=e,t.oImageSmoothingEnabled=e,t.webkitImageSmoothingEnabled=e,t.msImageSmoothingEnabled=e},t.getImageSmoothingEnabled=()=>{const e=t.imageSmoothingEnabled;return null==e||e}}(t),function(t){t.ellipse||(t.ellipse=function(e,s,i,n,o,a,r,h=!1){const l=.551784;t.translate(e,s),t.rotate(o);let c=i,g=n;h&&(c=-i,g=-n),t.moveTo(-c,0),t.bezierCurveTo(-c,g*l,-c*l,g,0,g),t.bezierCurveTo(c*l,g,c,g*l,c,0),t.bezierCurveTo(c,-g*l,c*l,-g,0,-g),t.bezierCurveTo(-c*l,-g,-c,-g*l,-c,0),t.rotate(-o),t.translate(-e,-s)})}(t)}const l={position:\"absolute\",top:\"0\",left:\"0\",width:\"100%\",height:\"100%\"};class c{constructor(t,e){switch(this.backend=t,this.hidpi=e,this.pixel_ratio=1,this.bbox=new a.BBox,t){case\"webgl\":case\"canvas\":{this._el=this._canvas=(0,r.canvas)({style:l});const t=this.canvas.getContext(\"2d\");if(null==t)throw new Error(\"unable to obtain 2D rendering context\");this._ctx=t,e&&(this.pixel_ratio=devicePixelRatio);break}case\"svg\":{const t=new o.SVGRenderingContext2D;this._ctx=t,this._canvas=t.get_svg(),this._el=(0,r.div)({style:l},this._canvas);break}}this._ctx.layer=this,h(this._ctx)}get canvas(){return this._canvas}get ctx(){return this._ctx}get el(){return this._el}resize(t,e){this.bbox=new a.BBox({left:0,top:0,width:t,height:e});const s=this._ctx instanceof o.SVGRenderingContext2D?this._ctx:this.canvas;s.width=t*this.pixel_ratio,s.height=e*this.pixel_ratio}undo_transform(t){const{ctx:e}=this;if(void 0===e.getTransform)t(e);else{const s=e.getTransform();e.setTransform(this._base_transform);try{t(e)}finally{e.setTransform(s)}}}prepare(){const{ctx:t,hidpi:e,pixel_ratio:s}=this;t.save(),e&&(t.scale(s,s),t.translate(.5,.5)),void 0!==t.getTransform&&(this._base_transform=t.getTransform()),this.clear()}clear(){const{x:t,y:e,width:s,height:i}=this.bbox;this.ctx.clearRect(t,e,s,i)}finish(){this.ctx.restore()}to_blob(){const{_canvas:t}=this;if(t instanceof HTMLCanvasElement)return null!=t.msToBlob?Promise.resolve(t.msToBlob()):new Promise(((e,s)=>{t.toBlob((t=>null!=t?e(t):s()),\"image/png\")}));{const t=this._ctx.get_serialized_svg(!0),e=new Blob([t],{type:\"image/svg+xml\"});return Promise.resolve(e)}}}s.CanvasLayer=c,c.__name__=\"CanvasLayer\"},\n", - " function _(t,e,i,s,r){s();const n=t(122),a=t(8),o=t(237),l=t(10),h=t(43);function _(t){var e;const i={left:\"start\",right:\"end\",center:\"middle\",start:\"start\",end:\"end\"};return null!==(e=i[t])&&void 0!==e?e:i.start}function c(t){var e;const i={alphabetic:\"alphabetic\",hanging:\"hanging\",top:\"text-before-edge\",bottom:\"text-after-edge\",middle:\"central\"};return null!==(e=i[t])&&void 0!==e?e:i.alphabetic}const p=function(t,e){const i=new Map,s=t.split(\",\");e=null!=e?e:10;for(let t=0;t=0?Math.acos(e):-Math.acos(e)}const v=b(f),A=b(g);this.lineTo(d+f[0]*r,m+f[1]*r),this.arc(d,m,r,v,A)}stroke(){\"path\"===this.__currentElement.nodeName&&this.__currentElement.setAttribute(\"paint-order\",\"fill\"),this.__applyCurrentDefaultPath(),this.__applyStyleToCurrentElement(\"stroke\"),null!=this._clip_path&&this.__currentElement.setAttribute(\"clip-path\",this._clip_path)}fill(t,e){let i=null;if(t instanceof Path2D)i=t;else{if(\"evenodd\"!=t&&\"nonzero\"!=t&&null!=t||null!=e)throw new Error(\"invalid arguments\");e=t}if(null!=i)throw new Error(\"not implemented\");\"none\"!=this.__currentElement.getAttribute(\"fill\")&&this.__init_element(),\"path\"===this.__currentElement.nodeName&&this.__currentElement.setAttribute(\"paint-order\",\"stroke\"),this.__applyCurrentDefaultPath(),this.__applyStyleToCurrentElement(\"fill\"),null!=e&&this.__currentElement.setAttribute(\"fill-rule\",e),null!=this._clip_path&&this.__currentElement.setAttribute(\"clip-path\",this._clip_path)}rect(t,e,i,s){isFinite(t+e+i+s)&&(this.moveTo(t,e),this.lineTo(t+i,e),this.lineTo(t+i,e+s),this.lineTo(t,e+s),this.lineTo(t,e))}fillRect(t,e,i,s){isFinite(t+e+i+s)&&(this.beginPath(),this.rect(t,e,i,s),this.fill())}strokeRect(t,e,i,s){isFinite(t+e+i+s)&&(this.beginPath(),this.rect(t,e,i,s),this.stroke())}__clearCanvas(){(0,h.empty)(this.__defs),(0,h.empty)(this.__root),this.__root.appendChild(this.__defs),this.__currentElement=this.__root}clearRect(t,e,i,s){if(!isFinite(t+e+i+s))return;if(0===t&&0===e&&i===this.width&&s===this.height)return void this.__clearCanvas();const r=this.__createElement(\"rect\",{x:t,y:e,width:i,height:s,fill:\"#FFFFFF\"},!0);this._apply_transform(r),this.__root.appendChild(r)}createLinearGradient(t,e,i,s){if(!isFinite(t+e+i+s))throw new Error(\"The provided double value is non-finite\");const[r,n]=this._transform.apply(t,e),[a,o]=this._transform.apply(i,s),l=this.__createElement(\"linearGradient\",{id:this._random_string(),x1:`${r}px`,x2:`${a}px`,y1:`${n}px`,y2:`${o}px`,gradientUnits:\"userSpaceOnUse\"},!1);return this.__defs.appendChild(l),new d(l,this)}createRadialGradient(t,e,i,s,r,n){if(!isFinite(t+e+i+s+r+n))throw new Error(\"The provided double value is non-finite\");const[a,o]=this._transform.apply(t,e),[l,h]=this._transform.apply(s,r),_=this.__createElement(\"radialGradient\",{id:this._random_string(),cx:`${l}px`,cy:`${h}px`,r:`${n}px`,r0:`${i}px`,fx:`${a}px`,fy:`${o}px`,gradientUnits:\"userSpaceOnUse\"},!1);return this.__defs.appendChild(_),new d(_,this)}__parseFont(){var t,e,i,s,r;const 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negative\");const h=o?a-n:n-a;n%=2*Math.PI,a%=2*Math.PI;const _=t+i*Math.cos(n),c=e+s*Math.sin(n);this.lineTo(_,c);const p=180*r/Math.PI,u=o?0:1;if(Math.abs(n-a)<2*l.float32_epsilon&&!(Math.abs(h)<2*l.float32_epsilon&&h<0)){const r=t+i*Math.cos(n+Math.PI),a=e+s*Math.sin(n+Math.PI),[o,l]=this._transform.apply(_,c),[h,d]=this._transform.apply(r,a);this.__addPathCommand(o,l,`A ${i} ${s} ${p} 0 ${u} ${h} ${d} A ${i} ${s} ${p} 0 ${u} ${o} ${l}`)}else{const r=t+i*Math.cos(a),l=e+s*Math.sin(a);let h=a-n;h<0&&(h+=2*Math.PI);const _=o!==h>Math.PI?1:0,[c,d]=this._transform.apply(r,l);this.__addPathCommand(c,d,`A ${i} ${s} ${p} ${_} ${u} ${c} ${d}`)}}clip(){const t=this.__createElement(\"clipPath\"),e=this._random_string();this.__applyCurrentDefaultPath(),t.setAttribute(\"id\",e),t.appendChild(this.__currentElement),this.__defs.appendChild(t),this._clip_path=`url(#${e})`}drawImage(t,...e){let i,s,r,n,a,o,l,h;if(2==e.length){if([i,s]=e,!isFinite(i+s))return;a=0,o=0,l=t.width,h=t.height,r=l,n=h}else if(4==e.length){if([i,s,r,n]=e,!isFinite(i+s+r+n))return;a=0,o=0,l=t.width,h=t.height}else{if(8!==e.length)throw new Error(`Inavlid number of arguments passed to drawImage: ${arguments.length}`);if([a,o,l,h,i,s,r,n]=e,!isFinite(a+o+l+h+i+s+r+n))return}const _=this.__root,c=this._transform.clone().translate(i,s);if(t instanceof f||t instanceof SVGSVGElement){const e=(t instanceof SVGSVGElement?t:t.get_svg()).cloneNode(!0);let i;c.is_identity&&1==this.globalAlpha&&null==this._clip_path?i=_:(i=this.__createElement(\"g\"),c.is_identity||this._apply_transform(i,c),1!=this.globalAlpha&&i.setAttribute(\"opacity\",`${this.globalAlpha}`),null!=this._clip_path&&i.setAttribute(\"clip-path\",this._clip_path),_.appendChild(i));for(const t of[...e.childNodes])if(t instanceof SVGDefsElement){for(const e of[...t.childNodes])if(e instanceof Element){const t=e.getAttribute(\"id\");this.__ids.add(t),this.__defs.appendChild(e.cloneNode(!0))}}else i.appendChild(t.cloneNode(!0))}else if(t instanceof HTMLImageElement||t instanceof SVGImageElement){const e=this.__createElement(\"image\");if(e.setAttribute(\"width\",`${r}`),e.setAttribute(\"height\",`${n}`),e.setAttribute(\"preserveAspectRatio\",\"none\"),1!=this.globalAlpha&&e.setAttribute(\"opacity\",`${this.globalAlpha}`),a||o||l!==t.width||h!==t.height){const e=this.__document.createElement(\"canvas\");e.width=r,e.height=n;e.getContext(\"2d\").drawImage(t,a,o,l,h,0,0,r,n),t=e}this._apply_transform(e,c);const i=t instanceof HTMLCanvasElement?t.toDataURL():t.getAttribute(\"src\");if(e.setAttribute(\"href\",i),null!=this._clip_path){const t=this.__createElement(\"g\");t.setAttribute(\"clip-path\",this._clip_path),t.appendChild(e),_.appendChild(t)}else _.appendChild(e)}else if(t instanceof HTMLCanvasElement){const 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DOMMatrix?t[0]:new DOMMatrix(Object.values(!t[0])),this._transform=n.AffineTransform.from_DOMMatrix(e)}resetTransform(){this._transform=new n.AffineTransform}isPointInPath(...t){throw new Error(\"not implemented\")}isPointInStroke(...t){throw new Error(\"not implemented\")}createImageData(...t){throw new Error(\"not implemented\")}getImageData(t,e,i,s){throw new Error(\"not implemented\")}putImageData(...t){throw new Error(\"not implemented\")}drawFocusIfNeeded(...t){throw new Error(\"not implemented\")}scrollPathIntoView(...t){throw new Error(\"not implemented\")}}i.SVGRenderingContext2D=f,f.__name__=\"SVGRenderingContext2D\",f.__random=o.random},\n", - " function _(e,t,s,n,r){n();const o=2147483647;class i{constructor(e){this.seed=e%o,this.seed<=0&&(this.seed+=2147483646)}integer(){return this.seed=48271*this.seed%o,this.seed}float(){return(this.integer()-1)/2147483646}floats(e,t=0,s=1){const n=new Array(e);for(let r=0;rthis.doit(o)))}}n.ActionToolView=_,_.__name__=\"ActionToolView\";class d extends s.ButtonTool{constructor(o){super(o),this.button_view=l,this.do=new c.Signal(this,\"do\")}}n.ActionTool=d,d.__name__=\"ActionTool\"},\n", - " function _(o,e,t,l,i){var s;l();const n=o(238),r=o(228);class c extends n.ActionToolView{doit(){window.open(this.model.redirect)}}t.HelpToolView=c,c.__name__=\"HelpToolView\";class _ extends n.ActionTool{constructor(o){super(o),this.tool_name=\"Help\",this.icon=r.tool_icon_help}}t.HelpTool=_,s=_,_.__name__=\"HelpTool\",s.prototype.default_view=c,s.define((({String:o})=>({redirect:[o,\"https://docs.bokeh.org/en/latest/docs/user_guide/tools.html\"]}))),s.override({description:\"Click the question mark to learn more about Bokeh plot tools.\"}),s.register_alias(\"help\",(()=>new _))},\n", - " function _(o,l,g,A,r){A(),g.root=\"bk-root\",g.logo=\"bk-logo\",g.grey=\"bk-grey\",g.logo_small=\"bk-logo-small\",g.logo_notebook=\"bk-logo-notebook\",g.default=\".bk-root .bk-logo{margin:5px;position:relative;display:block;background-repeat:no-repeat;}.bk-root .bk-logo.bk-grey{filter:url(\\\"data:image/svg+xml;utf8,#grayscale\\\");filter:gray;-webkit-filter:grayscale(100%);}.bk-root .bk-logo-small{width:20px;height:20px;background-image:url(data:image/png;base64,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);}.bk-root .bk-logo-notebook{display:inline-block;vertical-align:middle;margin-right:5px;}\"},\n", - " function _(e,t,s,i,l){i();const o=e(1);var n;const a=e(40),h=e(20),r=e(43),c=(0,o.__importStar)(e(242)),d=c;class p extends a.AnnotationView{initialize(){super.initialize(),this.el=(0,r.div)({class:d.tooltip}),(0,r.undisplay)(this.el),this.plot_view.canvas_view.add_overlay(this.el)}remove(){(0,r.remove)(this.el),super.remove()}connect_signals(){super.connect_signals(),this.connect(this.model.properties.content.change,(()=>this.render())),this.connect(this.model.properties.position.change,(()=>this._reposition()))}styles(){return[...super.styles(),c.default]}render(){this.model.visible||(0,r.undisplay)(this.el),super.render()}_render(){const{content:e}=this.model;null!=e?((0,r.empty)(this.el),(0,r.classes)(this.el).toggle(\"bk-tooltip-custom\",this.model.custom),this.el.appendChild(e),this.model.show_arrow&&this.el.classList.add(d.tooltip_arrow)):(0,r.undisplay)(this.el)}_reposition(){const{position:e}=this.model;if(null==e)return void(0,r.undisplay)(this.el);const[t,s]=e,i=(()=>{const e=this.parent.layout.bbox.relative(),{attachment:i}=this.model;switch(i){case\"horizontal\":return t({attachment:[h.TooltipAttachment,\"horizontal\"],inner_only:[e,!0],show_arrow:[e,!0]}))),n.internal((({Boolean:e,Number:t,Tuple:s,Ref:i,Nullable:l})=>({position:[l(s(t,t)),null],content:[i(HTMLElement),()=>(0,r.div)()],custom:[e]}))),n.override({level:\"overlay\"})},\n", - " function _(o,t,r,e,l){e(),r.root=\"bk-root\",r.tooltip=\"bk-tooltip\",r.left=\"bk-left\",r.tooltip_arrow=\"bk-tooltip-arrow\",r.right=\"bk-right\",r.above=\"bk-above\",r.below=\"bk-below\",r.tooltip_row_label=\"bk-tooltip-row-label\",r.tooltip_row_value=\"bk-tooltip-row-value\",r.tooltip_color_block=\"bk-tooltip-color-block\",r.default='.bk-root{}.bk-root .bk-tooltip{font-weight:300;font-size:12px;position:absolute;padding:5px;border:1px solid #e5e5e5;color:#2f2f2f;background-color:white;pointer-events:none;opacity:0.95;z-index:100;}.bk-root .bk-tooltip > div:not(:first-child){margin-top:5px;border-top:#e5e5e5 1px dashed;}.bk-root .bk-tooltip.bk-left.bk-tooltip-arrow::before{position:absolute;margin:-7px 0 0 0;top:50%;width:0;height:0;border-style:solid;border-width:7px 0 7px 0;border-color:transparent;content:\" \";display:block;left:-10px;border-right-width:10px;border-right-color:#909599;}.bk-root .bk-tooltip.bk-left::before{left:-10px;border-right-width:10px;border-right-color:#909599;}.bk-root .bk-tooltip.bk-right.bk-tooltip-arrow::after{position:absolute;margin:-7px 0 0 0;top:50%;width:0;height:0;border-style:solid;border-width:7px 0 7px 0;border-color:transparent;content:\" \";display:block;right:-10px;border-left-width:10px;border-left-color:#909599;}.bk-root .bk-tooltip.bk-right::after{right:-10px;border-left-width:10px;border-left-color:#909599;}.bk-root .bk-tooltip.bk-above::before{position:absolute;margin:0 0 0 -7px;left:50%;width:0;height:0;border-style:solid;border-width:0 7px 0 7px;border-color:transparent;content:\" \";display:block;top:-10px;border-bottom-width:10px;border-bottom-color:#909599;}.bk-root .bk-tooltip.bk-below::after{position:absolute;margin:0 0 0 -7px;left:50%;width:0;height:0;border-style:solid;border-width:0 7px 0 7px;border-color:transparent;content:\" \";display:block;bottom:-10px;border-top-width:10px;border-top-color:#909599;}.bk-root .bk-tooltip-row-label{text-align:right;color:#26aae1;}.bk-root .bk-tooltip-row-value{color:default;}.bk-root .bk-tooltip-color-block{width:12px;height:12px;margin-left:5px;margin-right:5px;outline:#dddddd solid 1px;display:inline-block;}'},\n", - " function _(e,t,s,i,r){var a;i();const l=e(115),_=e(112),h=e(113),o=e(48);class n extends l.UpperLowerView{async lazy_initialize(){await super.lazy_initialize();const{lower_head:e,upper_head:t}=this.model;null!=e&&(this.lower_head=await(0,h.build_view)(e,{parent:this})),null!=t&&(this.upper_head=await(0,h.build_view)(t,{parent:this}))}set_data(e){var t,s;super.set_data(e),null===(t=this.lower_head)||void 0===t||t.set_data(e),null===(s=this.upper_head)||void 0===s||s.set_data(e)}paint(e){if(this.visuals.line.doit)for(let t=0,s=this._lower_sx.length;t({lower_head:[t(e(_.ArrowHead)),()=>new _.TeeHead({size:10})],upper_head:[t(e(_.ArrowHead)),()=>new _.TeeHead({size:10})]}))),a.override({level:\"underlay\"})},\n", - " function _(n,o,t,u,e){u(),e(\"CustomJS\",n(245).CustomJS),e(\"OpenURL\",n(247).OpenURL)},\n", - " function _(t,e,s,n,c){var a;n();const r=t(246),u=t(13),o=t(34);class i extends r.Callback{constructor(t){super(t)}get names(){return(0,u.keys)(this.args)}get values(){return(0,u.values)(this.args)}get func(){const t=(0,o.use_strict)(this.code);return new Function(...this.names,\"cb_obj\",\"cb_data\",t)}execute(t,e={}){return this.func.apply(t,this.values.concat(t,e))}}s.CustomJS=i,a=i,i.__name__=\"CustomJS\",a.define((({Unknown:t,String:e,Dict:s})=>({args:[s(t),{}],code:[e,\"\"]})))},\n", - " function _(c,a,l,n,s){n();const e=c(53);class o extends e.Model{constructor(c){super(c)}}l.Callback=o,o.__name__=\"Callback\"},\n", - " function _(e,t,n,o,i){var s;o();const c=e(246),r=e(152),a=e(8);class d extends c.Callback{constructor(e){super(e)}navigate(e){this.same_tab?window.location.href=e:window.open(e)}execute(e,{source:t}){const n=e=>{const n=(0,r.replace_placeholders)(this.url,t,e,void 0,void 0,encodeURI);if(!(0,a.isString)(n))throw new Error(\"HTML output is not supported in this context\");this.navigate(n)},{selected:o}=t;for(const e of o.indices)n(e);for(const e of o.line_indices)n(e)}}n.OpenURL=d,s=d,d.__name__=\"OpenURL\",s.define((({Boolean:e,String:t})=>({url:[t,\"http://\"],same_tab:[e,!1]})))},\n", - " function _(a,n,i,e,r){e(),r(\"Canvas\",a(249).Canvas),r(\"CartesianFrame\",a(126).CartesianFrame),r(\"CoordinateMapping\",a(54).CoordinateMapping)},\n", - " function _(e,t,i,s,a){var r,l=this&&this.__createBinding||(Object.create?function(e,t,i,s){void 0===s&&(s=i),Object.defineProperty(e,s,{enumerable:!0,get:function(){return t[i]}})}:function(e,t,i,s){void 0===s&&(s=i),e[s]=t[i]}),n=this&&this.__setModuleDefault||(Object.create?function(e,t){Object.defineProperty(e,\"default\",{enumerable:!0,value:t})}:function(e,t){e.default=t}),o=this&&this.__importStar||function(e){if(e&&e.__esModule)return e;var t={};if(null!=e)for(var i in e)\"default\"!==i&&Object.prototype.hasOwnProperty.call(e,i)&&l(t,e,i);return n(t,e),t};s();const h=e(14),c=e(226),u=e(19),_=e(43),d=e(20),p=e(13),b=e(250),v=e(65),g=e(138),w=e(235);const y=(()=>{let t;return async()=>void 0!==t?t:t=await async function(){const t=document.createElement(\"canvas\"),i=t.getContext(\"webgl\",{premultipliedAlpha:!0});if(null!=i){const s=await(0,g.load_module)(Promise.resolve().then((()=>o(e(410)))));if(null!=s){const e=s.get_regl(i);if(e.has_webgl)return{canvas:t,regl_wrapper:e};u.logger.trace(\"WebGL is supported, but not the required extensions\")}else u.logger.trace(\"WebGL is supported, but bokehjs(.min).js bundle is not available\")}else u.logger.trace(\"WebGL is not supported\");return null}()})(),m={position:\"absolute\",top:\"0\",left:\"0\",width:\"100%\",height:\"100%\"};class f extends c.DOMView{constructor(){super(...arguments),this.bbox=new v.BBox,this.webgl=null}initialize(){super.initialize(),this.underlays_el=(0,_.div)({style:m}),this.primary=this.create_layer(),this.overlays=this.create_layer(),this.overlays_el=(0,_.div)({style:m}),this.events_el=(0,_.div)({class:\"bk-canvas-events\",style:m});const e=[this.underlays_el,this.primary.el,this.overlays.el,this.overlays_el,this.events_el];(0,p.extend)(this.el.style,m),(0,_.append)(this.el,...e),this.ui_event_bus=new b.UIEventBus(this)}async lazy_initialize(){await super.lazy_initialize(),\"webgl\"==this.model.output_backend&&(this.webgl=await y())}remove(){this.ui_event_bus.destroy(),super.remove()}add_underlay(e){this.underlays_el.appendChild(e)}add_overlay(e){this.overlays_el.appendChild(e)}add_event(e){this.events_el.appendChild(e)}get pixel_ratio(){return this.primary.pixel_ratio}resize(e,t){this.bbox=new v.BBox({left:0,top:0,width:e,height:t}),this.primary.resize(e,t),this.overlays.resize(e,t)}prepare_webgl(e){const{webgl:t}=this;if(null!=t){const{width:i,height:s}=this.bbox;t.canvas.width=this.pixel_ratio*i,t.canvas.height=this.pixel_ratio*s;const[a,r,l,n]=e,{xview:o,yview:h}=this.bbox,c=o.compute(a),u=h.compute(r+n),_=this.pixel_ratio;t.regl_wrapper.set_scissor(_*c,_*u,_*l,_*n),this._clear_webgl()}}blit_webgl(e){const{webgl:t}=this;if(null!=t){if(u.logger.debug(\"Blitting WebGL canvas\"),e.restore(),e.drawImage(t.canvas,0,0),e.save(),this.model.hidpi){const t=this.pixel_ratio;e.scale(t,t),e.translate(.5,.5)}this._clear_webgl()}}_clear_webgl(){const{webgl:e}=this;if(null!=e){const{regl_wrapper:t,canvas:i}=e;t.clear(i.width,i.height)}}compose(){const e=this.create_layer(),{width:t,height:i}=this.bbox;return e.resize(t,i),e.ctx.drawImage(this.primary.canvas,0,0),e.ctx.drawImage(this.overlays.canvas,0,0),e}create_layer(){const{output_backend:e,hidpi:t}=this.model;return new w.CanvasLayer(e,t)}to_blob(){return this.compose().to_blob()}}i.CanvasView=f,f.__name__=\"CanvasView\";class x extends h.HasProps{constructor(e){super(e)}}i.Canvas=x,r=x,x.__name__=\"Canvas\",r.prototype.default_view=f,r.internal((({Boolean:e})=>({hidpi:[e,!0],output_backend:[d.OutputBackend,\"canvas\"]})))},\n", - " function _(t,e,s,n,i){n();const r=t(1),a=(0,r.__importDefault)(t(225)),_=t(15),h=t(19),o=t(43),l=(0,r.__importStar)(t(251)),c=t(252),p=t(9),u=t(8),v=t(27),d=t(230);class g{constructor(t){this.canvas_view=t,this.pan_start=new _.Signal(this,\"pan:start\"),this.pan=new _.Signal(this,\"pan\"),this.pan_end=new _.Signal(this,\"pan:end\"),this.pinch_start=new _.Signal(this,\"pinch:start\"),this.pinch=new _.Signal(this,\"pinch\"),this.pinch_end=new _.Signal(this,\"pinch:end\"),this.rotate_start=new _.Signal(this,\"rotate:start\"),this.rotate=new _.Signal(this,\"rotate\"),this.rotate_end=new _.Signal(this,\"rotate:end\"),this.tap=new _.Signal(this,\"tap\"),this.doubletap=new _.Signal(this,\"doubletap\"),this.press=new _.Signal(this,\"press\"),this.pressup=new _.Signal(this,\"pressup\"),this.move_enter=new _.Signal(this,\"move:enter\"),this.move=new _.Signal(this,\"move\"),this.move_exit=new _.Signal(this,\"move:exit\"),this.scroll=new _.Signal(this,\"scroll\"),this.keydown=new _.Signal(this,\"keydown\"),this.keyup=new _.Signal(this,\"keyup\"),this.hammer=new a.default(this.hit_area,{touchAction:\"auto\",inputClass:a.default.TouchMouseInput}),this._prev_move=null,this._curr_pan=null,this._curr_pinch=null,this._curr_rotate=null,this._configure_hammerjs(),this.hit_area.addEventListener(\"mousemove\",(t=>this._mouse_move(t))),this.hit_area.addEventListener(\"mouseenter\",(t=>this._mouse_enter(t))),this.hit_area.addEventListener(\"mouseleave\",(t=>this._mouse_exit(t))),this.hit_area.addEventListener(\"contextmenu\",(t=>this._context_menu(t))),this.hit_area.addEventListener(\"wheel\",(t=>this._mouse_wheel(t))),document.addEventListener(\"keydown\",this),document.addEventListener(\"keyup\",this),this.menu=new d.ContextMenu([],{prevent_hide:t=>2==t.button&&t.target==this.hit_area}),this.hit_area.appendChild(this.menu.el)}get hit_area(){return this.canvas_view.events_el}destroy(){this.menu.remove(),this.hammer.destroy(),document.removeEventListener(\"keydown\",this),document.removeEventListener(\"keyup\",this)}handleEvent(t){\"keydown\"==t.type?this._key_down(t):\"keyup\"==t.type&&this._key_up(t)}_configure_hammerjs(){this.hammer.get(\"doubletap\").recognizeWith(\"tap\"),this.hammer.get(\"tap\").requireFailure(\"doubletap\"),this.hammer.get(\"doubletap\").dropRequireFailure(\"tap\"),this.hammer.on(\"doubletap\",(t=>this._doubletap(t))),this.hammer.on(\"tap\",(t=>this._tap(t))),this.hammer.on(\"press\",(t=>this._press(t))),this.hammer.on(\"pressup\",(t=>this._pressup(t))),this.hammer.get(\"pan\").set({direction:a.default.DIRECTION_ALL}),this.hammer.on(\"panstart\",(t=>this._pan_start(t))),this.hammer.on(\"pan\",(t=>this._pan(t))),this.hammer.on(\"panend\",(t=>this._pan_end(t))),this.hammer.get(\"pinch\").set({enable:!0}),this.hammer.on(\"pinchstart\",(t=>this._pinch_start(t))),this.hammer.on(\"pinch\",(t=>this._pinch(t))),this.hammer.on(\"pinchend\",(t=>this._pinch_end(t))),this.hammer.get(\"rotate\").set({enable:!0}),this.hammer.on(\"rotatestart\",(t=>this._rotate_start(t))),this.hammer.on(\"rotate\",(t=>this._rotate(t))),this.hammer.on(\"rotateend\",(t=>this._rotate_end(t)))}register_tool(t){const e=t.model.event_type;null!=e&&((0,u.isString)(e)?this._register_tool(t,e):e.forEach(((e,s)=>this._register_tool(t,e,s<1))))}_register_tool(t,e,s=!0){const n=t,{id:i}=n.model,r=t=>e=>{e.id==i&&t(e.e)},a=t=>e=>{t(e.e)};switch(e){case\"pan\":null!=n._pan_start&&n.connect(this.pan_start,r(n._pan_start.bind(n))),null!=n._pan&&n.connect(this.pan,r(n._pan.bind(n))),null!=n._pan_end&&n.connect(this.pan_end,r(n._pan_end.bind(n)));break;case\"pinch\":null!=n._pinch_start&&n.connect(this.pinch_start,r(n._pinch_start.bind(n))),null!=n._pinch&&n.connect(this.pinch,r(n._pinch.bind(n))),null!=n._pinch_end&&n.connect(this.pinch_end,r(n._pinch_end.bind(n)));break;case\"rotate\":null!=n._rotate_start&&n.connect(this.rotate_start,r(n._rotate_start.bind(n))),null!=n._rotate&&n.connect(this.rotate,r(n._rotate.bind(n))),null!=n._rotate_end&&n.connect(this.rotate_end,r(n._rotate_end.bind(n)));break;case\"move\":null!=n._move_enter&&n.connect(this.move_enter,r(n._move_enter.bind(n))),null!=n._move&&n.connect(this.move,r(n._move.bind(n))),null!=n._move_exit&&n.connect(this.move_exit,r(n._move_exit.bind(n)));break;case\"tap\":null!=n._tap&&n.connect(this.tap,r(n._tap.bind(n))),null!=n._doubletap&&n.connect(this.doubletap,r(n._doubletap.bind(n)));break;case\"press\":null!=n._press&&n.connect(this.press,r(n._press.bind(n))),null!=n._pressup&&n.connect(this.pressup,r(n._pressup.bind(n)));break;case\"scroll\":null!=n._scroll&&n.connect(this.scroll,r(n._scroll.bind(n)));break;default:throw new Error(`unsupported event_type: ${e}`)}s&&(null!=n._keydown&&n.connect(this.keydown,a(n._keydown.bind(n))),null!=n._keyup&&n.connect(this.keyup,a(n._keyup.bind(n))),v.is_mobile&&null!=n._scroll&&\"pinch\"==e&&(h.logger.debug(\"Registering scroll on touch screen\"),n.connect(this.scroll,r(n._scroll.bind(n)))))}_hit_test_renderers(t,e,s){var n;const i=t.get_renderer_views();for(const t of(0,p.reversed)(i))if(null===(n=t.interactive_hit)||void 0===n?void 0:n.call(t,e,s))return t;return null}set_cursor(t=\"default\"){this.hit_area.style.cursor=t}_hit_test_frame(t,e,s){return t.frame.bbox.contains(e,s)}_hit_test_canvas(t,e,s){return t.layout.bbox.contains(e,s)}_hit_test_plot(t,e){for(const s of this.canvas_view.plot_views)if(s.layout.bbox.relative().contains(t,e))return s;return null}_trigger(t,e,s){var n;const{sx:i,sy:r}=e,a=this._hit_test_plot(i,r),_=t=>{const[s,n]=[i,r];return Object.assign(Object.assign({},e),{sx:s,sy:n})};if(\"panstart\"==e.type||\"pan\"==e.type||\"panend\"==e.type){let n;if(\"panstart\"==e.type&&null!=a?(this._curr_pan={plot_view:a},n=a):\"pan\"==e.type&&null!=this._curr_pan?n=this._curr_pan.plot_view:\"panend\"==e.type&&null!=this._curr_pan?(n=this._curr_pan.plot_view,this._curr_pan=null):n=null,null!=n){const e=_();this.__trigger(n,t,e,s)}}else if(\"pinchstart\"==e.type||\"pinch\"==e.type||\"pinchend\"==e.type){let n;if(\"pinchstart\"==e.type&&null!=a?(this._curr_pinch={plot_view:a},n=a):\"pinch\"==e.type&&null!=this._curr_pinch?n=this._curr_pinch.plot_view:\"pinchend\"==e.type&&null!=this._curr_pinch?(n=this._curr_pinch.plot_view,this._curr_pinch=null):n=null,null!=n){const e=_();this.__trigger(n,t,e,s)}}else if(\"rotatestart\"==e.type||\"rotate\"==e.type||\"rotateend\"==e.type){let 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a=t.model.toolbar.gestures,_=e.name.split(\":\")[0],h=this._hit_test_renderers(t,s.sx,s.sy),o=this._hit_test_canvas(t,s.sx,s.sy);switch(_){case\"move\":{const n=a[_].active;null!=n&&this.trigger(e,s,n.id);const r=t.model.toolbar.inspectors.filter((t=>t.active));let l=\"default\";null!=h?(l=null!==(i=h.cursor(s.sx,s.sy))&&void 0!==i?i:l,(0,p.is_empty)(r)||(e=this.move_exit)):this._hit_test_frame(t,s.sx,s.sy)&&((0,p.is_empty)(r)||(l=\"crosshair\")),this.set_cursor(l),t.set_toolbar_visibility(o),r.map((t=>this.trigger(e,s,t.id)));break}case\"tap\":{const{target:t}=n;if(null!=t&&t!=this.hit_area)return;null!=h&&null!=h.on_hit&&h.on_hit(s.sx,s.sy);const i=a[_].active;null!=i&&this.trigger(e,s,i.id);break}case\"doubletap\":{const t=null!==(r=a.doubletap.active)&&void 0!==r?r:a.tap.active;null!=t&&this.trigger(e,s,t.id);break}case\"scroll\":{const t=a[v.is_mobile?\"pinch\":\"scroll\"].active;null!=t&&(n.preventDefault(),n.stopPropagation(),this.trigger(e,s,t.id));break}case\"pan\":{const t=a[_].active;null!=t&&(n.preventDefault(),this.trigger(e,s,t.id));break}default:{const t=a[_].active;null!=t&&this.trigger(e,s,t.id)}}this._trigger_bokeh_event(t,s)}trigger(t,e,s=null){t.emit({id:s,e})}_trigger_bokeh_event(t,e){const s=(()=>{const{sx:s,sy:n}=e,i=t.frame.x_scale.invert(s),r=t.frame.y_scale.invert(n);switch(e.type){case\"wheel\":return new l.MouseWheel(s,n,i,r,e.delta);case\"mousemove\":return new l.MouseMove(s,n,i,r);case\"mouseenter\":return new l.MouseEnter(s,n,i,r);case\"mouseleave\":return new l.MouseLeave(s,n,i,r);case\"tap\":return new l.Tap(s,n,i,r);case\"doubletap\":return new l.DoubleTap(s,n,i,r);case\"press\":return new l.Press(s,n,i,r);case\"pressup\":return new l.PressUp(s,n,i,r);case\"pan\":return new l.Pan(s,n,i,r,e.deltaX,e.deltaY);case\"panstart\":return new l.PanStart(s,n,i,r);case\"panend\":return new l.PanEnd(s,n,i,r);case\"pinch\":return new l.Pinch(s,n,i,r,e.scale);case\"pinchstart\":return new l.PinchStart(s,n,i,r);case\"pinchend\":return new 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Object.assign(Object.assign({type:t.type},this._get_sxy(t.srcEvent)),{rotation:t.rotation,shiftKey:t.srcEvent.shiftKey,ctrlKey:t.srcEvent.ctrlKey})}_tap_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t.srcEvent)),{shiftKey:t.srcEvent.shiftKey,ctrlKey:t.srcEvent.ctrlKey})}_move_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t)),{shiftKey:t.shiftKey,ctrlKey:t.ctrlKey})}_scroll_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t)),{delta:(0,c.getDeltaY)(t),shiftKey:t.shiftKey,ctrlKey:t.ctrlKey})}_key_event(t){return{type:t.type,keyCode:t.keyCode}}_pan_start(t){const 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y{};s.Tap=M,M.__name__=\"Tap\",s.Tap=M=a([o(\"tap\")],M);let f=class extends y{};s.DoubleTap=f,f.__name__=\"DoubleTap\",s.DoubleTap=f=a([o(\"doubletap\")],f);let S=class extends y{};s.Press=S,S.__name__=\"Press\",s.Press=S=a([o(\"press\")],S);let D=class extends y{};s.PressUp=D,D.__name__=\"PressUp\",s.PressUp=D=a([o(\"pressup\")],D);let k=class extends y{};s.PanStart=k,k.__name__=\"PanStart\",s.PanStart=k=a([o(\"panstart\")],k);let L=class extends y{};s.PanEnd=L,L.__name__=\"PanEnd\",s.PanEnd=L=a([o(\"panend\")],L);let U=class extends y{};s.PinchStart=U,U.__name__=\"PinchStart\",s.PinchStart=U=a([o(\"pinchstart\")],U);let C=class extends y{};s.PinchEnd=C,C.__name__=\"PinchEnd\",s.PinchEnd=C=a([o(\"pinchend\")],C);let T=class extends y{};s.RotateStart=T,T.__name__=\"RotateStart\",s.RotateStart=T=a([o(\"rotatestart\")],T);let B=class extends y{};s.RotateEnd=B,B.__name__=\"RotateEnd\",s.RotateEnd=B=a([o(\"rotateend\")],B)},\n", - " function _(t,e,n,l,o){\n", - " /*!\n", - " * jQuery 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function _(e,n,t,o,r){var i;o();const l=e(254);class u extends l.Expression{constructor(e){super(e)}_v_compute(e){var n;const t=new Float64Array(null!==(n=e.get_length())&&void 0!==n?n:0),o=e.data[this.field],r=this.include_zero?1:0;t[0]=this.include_zero?0:o[0];for(let e=1;e({field:[n],include_zero:[e,!1]})))},\n", - " function _(i,n,l,t,e){var a;t();const u=i(254),r=i(9);class s extends u.ScalarExpression{constructor(i){super(i)}_compute(i){var n,l;const t=null!==(n=i.data[this.field])&&void 0!==n?n:[];return Math.min(null!==(l=this.initial)&&void 0!==l?l:1/0,(0,r.min)(t))}}l.Minimum=s,a=s,s.__name__=\"Minimum\",a.define((({Number:i,String:n,Nullable:l})=>({field:[n],initial:[l(i),null]})))},\n", - " function _(i,a,n,l,t){var e;l();const u=i(254),r=i(9);class s extends u.ScalarExpression{constructor(i){super(i)}_compute(i){var a,n;const l=null!==(a=i.data[this.field])&&void 0!==a?a:[];return Math.max(null!==(n=this.initial)&&void 0!==n?n:-1/0,(0,r.max)(l))}}n.Maximum=s,e=s,s.__name__=\"Maximum\",e.define((({Number:i,String:a,Nullable:n})=>({field:[a],initial:[n(i),null]})))},\n", - " function _(n,e,t,o,r){var s;o();const _=n(254);class m extends _.Expression{constructor(n){super(n)}get x(){return new c({transform:this})}get y(){return new u({transform:this})}}t.CoordinateTransform=m,m.__name__=\"CoordinateTransform\";class a extends _.Expression{constructor(n){super(n)}}t.XYComponent=a,s=a,a.__name__=\"XYComponent\",s.define((({Ref:n})=>({transform:[n(m)]})));class c extends a{constructor(n){super(n)}_v_compute(n){return this.transform.v_compute(n).x}}t.XComponent=c,c.__name__=\"XComponent\";class u extends a{constructor(n){super(n)}_v_compute(n){return this.transform.v_compute(n).y}}t.YComponent=u,u.__name__=\"YComponent\"},\n", - " function _(r,t,n,e,o){e();const i=r(1);var a;const s=r(260),c=r(20),l=(0,i.__importStar)(r(18));class d extends s.CoordinateTransform{constructor(r){super(r)}_v_compute(r){const t=this.properties.radius.uniform(r),n=this.properties.angle.uniform(r),e=\"anticlock\"==this.direction?-1:1,o=Math.min(t.length,n.length),i=new Float64Array(o),a=new Float64Array(o);for(let r=0;r({radius:[l.DistanceSpec,{field:\"radius\"}],angle:[l.AngleSpec,{field:\"angle\"}],direction:[c.Direction,\"anticlock\"]})))},\n", - " function _(e,t,l,r,i){r(),i(\"BooleanFilter\",e(263).BooleanFilter),i(\"CustomJSFilter\",e(264).CustomJSFilter),i(\"Filter\",e(191).Filter),i(\"GroupFilter\",e(265).GroupFilter),i(\"IndexFilter\",e(266).IndexFilter)},\n", - " function _(e,n,l,o,s){var t;o();const a=e(191),r=e(24);class c extends a.Filter{constructor(e){super(e)}compute_indices(e){const n=e.length,{booleans:l}=this;return null==l?r.Indices.all_set(n):r.Indices.from_booleans(n,l)}}l.BooleanFilter=c,t=c,c.__name__=\"BooleanFilter\",t.define((({Boolean:e,Array:n,Nullable:l})=>({booleans:[l(n(e)),null]})))},\n", - " function _(e,n,r,s,t){var i;s();const o=e(191),c=e(24),u=e(13),a=e(8),l=e(34);class f extends o.Filter{constructor(e){super(e)}get names(){return(0,u.keys)(this.args)}get values(){return(0,u.values)(this.args)}get func(){const e=(0,l.use_strict)(this.code);return new Function(...this.names,\"source\",e)}compute_indices(e){const n=e.length,r=this.func(...this.values,e);if(null==r)return c.Indices.all_set(n);if((0,a.isArrayOf)(r,a.isInteger))return c.Indices.from_indices(n,r);if((0,a.isArrayOf)(r,a.isBoolean))return c.Indices.from_booleans(n,r);throw new Error(`expect an array of integers or booleans, or null, got ${r}`)}}r.CustomJSFilter=f,i=f,f.__name__=\"CustomJSFilter\",i.define((({Unknown:e,String:n,Dict:r})=>({args:[r(e),{}],code:[n,\"\"]})))},\n", - " function _(n,e,t,o,r){var u;o();const s=n(191),c=n(24),i=n(19);class l extends s.Filter{constructor(n){super(n)}compute_indices(n){const e=n.get_column(this.column_name);if(null==e)return i.logger.warn(`${this}: groupby column '${this.column_name}' not found in the data source`),new c.Indices(n.length,1);{const t=new c.Indices(n.length);for(let n=0;n({column_name:[n],group:[n]})))},\n", - " function _(e,n,i,s,t){var l;s();const c=e(191),r=e(24);class d extends c.Filter{constructor(e){super(e)}compute_indices(e){const n=e.length,{indices:i}=this;return null==i?r.Indices.all_set(n):r.Indices.from_indices(n,i)}}i.IndexFilter=d,l=d,d.__name__=\"IndexFilter\",l.define((({Int:e,Array:n,Nullable:i})=>({indices:[i(n(e)),null]})))},\n", - " function _(e,a,l,i,t){i(),t(\"AnnularWedge\",e(268).AnnularWedge),t(\"Annulus\",e(269).Annulus),t(\"Arc\",e(270).Arc),t(\"Bezier\",e(271).Bezier),t(\"Circle\",e(272).Circle),t(\"Ellipse\",e(273).Ellipse),t(\"EllipseOval\",e(274).EllipseOval),t(\"Glyph\",e(179).Glyph),t(\"HArea\",e(187).HArea),t(\"HBar\",e(276).HBar),t(\"HexTile\",e(278).HexTile),t(\"Image\",e(279).Image),t(\"ImageRGBA\",e(281).ImageRGBA),t(\"ImageURL\",e(282).ImageURL),t(\"Line\",e(177).Line),t(\"MultiLine\",e(283).MultiLine),t(\"MultiPolygons\",e(284).MultiPolygons),t(\"Oval\",e(285).Oval),t(\"Patch\",e(186).Patch),t(\"Patches\",e(286).Patches),t(\"Quad\",e(287).Quad),t(\"Quadratic\",e(288).Quadratic),t(\"Ray\",e(289).Ray),t(\"Rect\",e(290).Rect),t(\"Scatter\",e(291).Scatter),t(\"Segment\",e(294).Segment),t(\"Spline\",e(295).Spline),t(\"Step\",e(297).Step),t(\"Text\",e(298).Text),t(\"VArea\",e(189).VArea),t(\"VBar\",e(299).VBar),t(\"Wedge\",e(300).Wedge)},\n", - " function _(e,t,s,i,r){i();const n=e(1);var a;const o=e(178),_=e(184),d=e(48),u=e(24),h=e(20),c=(0,n.__importStar)(e(18)),l=e(10),p=e(72);class x extends o.XYGlyphView{_map_data(){\"data\"==this.model.properties.inner_radius.units?this.sinner_radius=this.sdist(this.renderer.xscale,this._x,this.inner_radius):this.sinner_radius=(0,u.to_screen)(this.inner_radius),\"data\"==this.model.properties.outer_radius.units?this.souter_radius=this.sdist(this.renderer.xscale,this._x,this.outer_radius):this.souter_radius=(0,u.to_screen)(this.outer_radius)}_render(e,t,s){const{sx:i,sy:r,start_angle:n,end_angle:a,sinner_radius:o,souter_radius:_}=null!=s?s:this,d=\"anticlock\"==this.model.direction;for(const s of t){const t=i[s],u=r[s],h=o[s],c=_[s],l=n.get(s),p=a.get(s);if(!isFinite(t+u+h+c+l+p))continue;const x=p-l;e.translate(t,u),e.rotate(l),e.beginPath(),e.moveTo(c,0),e.arc(0,0,c,0,x,d),e.rotate(x),e.lineTo(h,0),e.arc(0,0,h,0,-x,!d),e.closePath(),e.rotate(-x-l),e.translate(-t,-u),this.visuals.fill.apply(e,s),this.visuals.hatch.apply(e,s),this.visuals.line.apply(e,s)}}_hit_point(e){const{sx:t,sy:s}=e,i=this.renderer.xscale.invert(t),r=this.renderer.yscale.invert(s);let n,a,o,_;if(\"data\"==this.model.properties.outer_radius.units)n=i-this.max_outer_radius,o=i+this.max_outer_radius,a=r-this.max_outer_radius,_=r+this.max_outer_radius;else{const e=t-this.max_outer_radius,i=t+this.max_outer_radius;[n,o]=this.renderer.xscale.r_invert(e,i);const r=s-this.max_outer_radius,d=s+this.max_outer_radius;[a,_]=this.renderer.yscale.r_invert(r,d)}const d=[];for(const e of this.index.indices({x0:n,x1:o,y0:a,y1:_})){const t=this.souter_radius[e]**2,s=this.sinner_radius[e]**2,[n,a]=this.renderer.xscale.r_compute(i,this._x[e]),[o,_]=this.renderer.yscale.r_compute(r,this._y[e]),u=(n-a)**2+(o-_)**2;u<=t&&u>=s&&d.push(e)}const u=\"anticlock\"==this.model.direction,h=[];for(const e of d){const i=Math.atan2(s-this.sy[e],t-this.sx[e]);(0,l.angle_between)(-i,-this.start_angle.get(e),-this.end_angle.get(e),u)&&h.push(e)}return new p.Selection({indices:h})}draw_legend_for_index(e,t,s){(0,_.generic_area_vector_legend)(this.visuals,e,t,s)}scenterxy(e){const t=(this.sinner_radius[e]+this.souter_radius[e])/2,s=(this.start_angle.get(e)+this.end_angle.get(e))/2;return[this.sx[e]+t*Math.cos(s),this.sy[e]+t*Math.sin(s)]}}s.AnnularWedgeView=x,x.__name__=\"AnnularWedgeView\";class g extends o.XYGlyph{constructor(e){super(e)}}s.AnnularWedge=g,a=g,g.__name__=\"AnnularWedge\",a.prototype.default_view=x,a.mixins([d.LineVector,d.FillVector,d.HatchVector]),a.define((({})=>({direction:[h.Direction,\"anticlock\"],inner_radius:[c.DistanceSpec,{field:\"inner_radius\"}],outer_radius:[c.DistanceSpec,{field:\"outer_radius\"}],start_angle:[c.AngleSpec,{field:\"start_angle\"}],end_angle:[c.AngleSpec,{field:\"end_angle\"}]})))},\n", - " function _(s,e,i,r,t){r();const n=s(1);var a;const u=s(178),o=s(24),_=s(48),d=(0,n.__importStar)(s(18)),h=s(27),c=s(72);class l extends u.XYGlyphView{_map_data(){\"data\"==this.model.properties.inner_radius.units?this.sinner_radius=this.sdist(this.renderer.xscale,this._x,this.inner_radius):this.sinner_radius=(0,o.to_screen)(this.inner_radius),\"data\"==this.model.properties.outer_radius.units?this.souter_radius=this.sdist(this.renderer.xscale,this._x,this.outer_radius):this.souter_radius=(0,o.to_screen)(this.outer_radius)}_render(s,e,i){const{sx:r,sy:t,sinner_radius:n,souter_radius:a}=null!=i?i:this;for(const i of e){const e=r[i],u=t[i],o=n[i],_=a[i];if(isFinite(e+u+o+_)){if(s.beginPath(),h.is_ie)for(const i of[!1,!0])s.moveTo(e,u),s.arc(e,u,o,0,Math.PI,i),s.moveTo(e+_,u),s.arc(e,u,_,Math.PI,0,!i);else s.arc(e,u,o,0,2*Math.PI,!0),s.moveTo(e+_,u),s.arc(e,u,_,2*Math.PI,0,!1);this.visuals.fill.apply(s,i),this.visuals.hatch.apply(s,i),this.visuals.line.apply(s,i)}}}_hit_point(s){const{sx:e,sy:i}=s,r=this.renderer.xscale.invert(e),t=this.renderer.yscale.invert(i);let n,a,u,o;if(\"data\"==this.model.properties.outer_radius.units)n=r-this.max_outer_radius,u=r+this.max_outer_radius,a=t-this.max_outer_radius,o=t+this.max_outer_radius;else{const s=e-this.max_outer_radius,r=e+this.max_outer_radius;[n,u]=this.renderer.xscale.r_invert(s,r);const t=i-this.max_outer_radius,_=i+this.max_outer_radius;[a,o]=this.renderer.yscale.r_invert(t,_)}const _=[];for(const s of this.index.indices({x0:n,x1:u,y0:a,y1:o})){const e=this.souter_radius[s]**2,i=this.sinner_radius[s]**2,[n,a]=this.renderer.xscale.r_compute(r,this._x[s]),[u,o]=this.renderer.yscale.r_compute(t,this._y[s]),d=(n-a)**2+(u-o)**2;d<=e&&d>=i&&_.push(s)}return new c.Selection({indices:_})}draw_legend_for_index(s,{x0:e,y0:i,x1:r,y1:t},n){const a=n+1,u=new Array(a);u[n]=(e+r)/2;const o=new Array(a);o[n]=(i+t)/2;const _=.5*Math.min(Math.abs(r-e),Math.abs(t-i)),d=new Array(a);d[n]=.4*_;const h=new Array(a);h[n]=.8*_,this._render(s,[n],{sx:u,sy:o,sinner_radius:d,souter_radius:h})}}i.AnnulusView=l,l.__name__=\"AnnulusView\";class x extends u.XYGlyph{constructor(s){super(s)}}i.Annulus=x,a=x,x.__name__=\"Annulus\",a.prototype.default_view=l,a.mixins([_.LineVector,_.FillVector,_.HatchVector]),a.define((({})=>({inner_radius:[d.DistanceSpec,{field:\"inner_radius\"}],outer_radius:[d.DistanceSpec,{field:\"outer_radius\"}]})))},\n", - " function _(e,i,s,t,n){t();const r=e(1);var a;const c=e(178),d=e(184),l=e(48),_=e(24),o=e(20),u=(0,r.__importStar)(e(18));class h extends c.XYGlyphView{_map_data(){\"data\"==this.model.properties.radius.units?this.sradius=this.sdist(this.renderer.xscale,this._x,this.radius):this.sradius=(0,_.to_screen)(this.radius)}_render(e,i,s){if(this.visuals.line.doit){const{sx:t,sy:n,sradius:r,start_angle:a,end_angle:c}=null!=s?s:this,d=\"anticlock\"==this.model.direction;for(const s of i){const i=t[s],l=n[s],_=r[s],o=a.get(s),u=c.get(s);isFinite(i+l+_+o+u)&&(e.beginPath(),e.arc(i,l,_,o,u,d),this.visuals.line.set_vectorize(e,s),e.stroke())}}}draw_legend_for_index(e,i,s){(0,d.generic_line_vector_legend)(this.visuals,e,i,s)}}s.ArcView=h,h.__name__=\"ArcView\";class g extends c.XYGlyph{constructor(e){super(e)}}s.Arc=g,a=g,g.__name__=\"Arc\",a.prototype.default_view=h,a.mixins(l.LineVector),a.define((({})=>({direction:[o.Direction,\"anticlock\"],radius:[u.DistanceSpec,{field:\"radius\"}],start_angle:[u.AngleSpec,{field:\"start_angle\"}],end_angle:[u.AngleSpec,{field:\"end_angle\"}]})))},\n", - " function _(e,t,i,n,s){n();const o=e(1);var c;const r=e(48),a=e(179),_=e(184),d=e(78),l=(0,o.__importStar)(e(18));function x(e,t,i,n,s,o,c,r){const a=[],_=[[],[]];for(let _=0;_<=2;_++){let d,l,x;if(0===_?(l=6*e-12*i+6*s,d=-3*e+9*i-9*s+3*c,x=3*i-3*e):(l=6*t-12*n+6*o,d=-3*t+9*n-9*o+3*r,x=3*n-3*t),Math.abs(d)<1e-12){if(Math.abs(l)<1e-12)continue;const e=-x/l;0({x0:[l.XCoordinateSpec,{field:\"x0\"}],y0:[l.YCoordinateSpec,{field:\"y0\"}],x1:[l.XCoordinateSpec,{field:\"x1\"}],y1:[l.YCoordinateSpec,{field:\"y1\"}],cx0:[l.XCoordinateSpec,{field:\"cx0\"}],cy0:[l.YCoordinateSpec,{field:\"cy0\"}],cx1:[l.XCoordinateSpec,{field:\"cx1\"}],cy1:[l.YCoordinateSpec,{field:\"cy1\"}]}))),c.mixins(r.LineVector)},\n", - " function _(s,i,e,t,r){t();const a=s(1);var n;const h=s(178),d=s(48),l=s(24),c=s(20),_=(0,a.__importStar)(s(185)),u=(0,a.__importStar)(s(18)),o=s(9),x=s(12),m=s(72);class p extends h.XYGlyphView{async lazy_initialize(){await super.lazy_initialize();const{webgl:i}=this.renderer.plot_view.canvas_view;if(null==i?void 0:i.regl_wrapper.has_webgl){const{MarkerGL:e}=await Promise.resolve().then((()=>(0,a.__importStar)(s(426))));this.glglyph=new e(i.regl_wrapper,this,\"circle\")}}get use_radius(){return!(this.radius.is_Scalar()&&isNaN(this.radius.value))}_set_data(s){super._set_data(s);const i=(()=>{if(this.use_radius)return 2*this.max_radius;{const{size:s}=this;return s.is_Scalar()?s.value:(0,x.max)(s.array)}})();this._configure(\"max_size\",{value:i})}_map_data(){if(this.use_radius)if(\"data\"==this.model.properties.radius.units)switch(this.model.radius_dimension){case\"x\":this.sradius=this.sdist(this.renderer.xscale,this._x,this.radius);break;case\"y\":this.sradius=this.sdist(this.renderer.yscale,this._y,this.radius);break;case\"max\":{const s=this.sdist(this.renderer.xscale,this._x,this.radius),i=this.sdist(this.renderer.yscale,this._y,this.radius);this.sradius=(0,x.map)(s,((s,e)=>Math.max(s,i[e])));break}case\"min\":{const s=this.sdist(this.renderer.xscale,this._x,this.radius),i=this.sdist(this.renderer.yscale,this._y,this.radius);this.sradius=(0,x.map)(s,((s,e)=>Math.min(s,i[e])));break}}else this.sradius=(0,l.to_screen)(this.radius);else{const s=l.ScreenArray.from(this.size);this.sradius=(0,x.map)(s,(s=>s/2))}}_mask_data(){const{frame:s}=this.renderer.plot_view,i=s.x_target,e=s.y_target;let t,r;return this.use_radius&&\"data\"==this.model.properties.radius.units?(t=i.map((s=>this.renderer.xscale.invert(s))).widen(this.max_radius),r=e.map((s=>this.renderer.yscale.invert(s))).widen(this.max_radius)):(t=i.widen(this.max_size).map((s=>this.renderer.xscale.invert(s))),r=e.widen(this.max_size).map((s=>this.renderer.yscale.invert(s)))),this.index.indices({x0:t.start,x1:t.end,y0:r.start,y1:r.end})}_render(s,i,e){const{sx:t,sy:r,sradius:a}=null!=e?e:this;for(const e of i){const i=t[e],n=r[e],h=a[e];isFinite(i+n+h)&&(s.beginPath(),s.arc(i,n,h,0,2*Math.PI,!1),this.visuals.fill.apply(s,e),this.visuals.hatch.apply(s,e),this.visuals.line.apply(s,e))}}_hit_point(s){const{sx:i,sy:e}=s,t=this.renderer.xscale.invert(i),r=this.renderer.yscale.invert(e),{hit_dilation:a}=this.model;let n,h,d,l;if(this.use_radius&&\"data\"==this.model.properties.radius.units)n=t-this.max_radius*a,h=t+this.max_radius*a,d=r-this.max_radius*a,l=r+this.max_radius*a;else{const s=i-this.max_size*a,t=i+this.max_size*a;[n,h]=this.renderer.xscale.r_invert(s,t);const r=e-this.max_size*a,c=e+this.max_size*a;[d,l]=this.renderer.yscale.r_invert(r,c)}const c=this.index.indices({x0:n,x1:h,y0:d,y1:l}),_=[];if(this.use_radius&&\"data\"==this.model.properties.radius.units)for(const s of c){const i=(this.sradius[s]*a)**2,[e,n]=this.renderer.xscale.r_compute(t,this._x[s]),[h,d]=this.renderer.yscale.r_compute(r,this._y[s]);(e-n)**2+(h-d)**2<=i&&_.push(s)}else for(const s of c){const t=(this.sradius[s]*a)**2;(this.sx[s]-i)**2+(this.sy[s]-e)**2<=t&&_.push(s)}return new m.Selection({indices:_})}_hit_span(s){const{sx:i,sy:e}=s,t=this.bounds();let r,a,n,h;if(\"h\"==s.direction){let s,e;if(n=t.y0,h=t.y1,this.use_radius&&\"data\"==this.model.properties.radius.units)s=i-this.max_radius,e=i+this.max_radius,[r,a]=this.renderer.xscale.r_invert(s,e);else{const t=this.max_size/2;s=i-t,e=i+t,[r,a]=this.renderer.xscale.r_invert(s,e)}}else{let s,i;if(r=t.x0,a=t.x1,this.use_radius&&\"data\"==this.model.properties.radius.units)s=e-this.max_radius,i=e+this.max_radius,[n,h]=this.renderer.yscale.r_invert(s,i);else{const t=this.max_size/2;s=e-t,i=e+t,[n,h]=this.renderer.yscale.r_invert(s,i)}}const d=[...this.index.indices({x0:r,x1:a,y0:n,y1:h})];return new m.Selection({indices:d})}_hit_rect(s){const{sx0:i,sx1:e,sy0:t,sy1:r}=s,[a,n]=this.renderer.xscale.r_invert(i,e),[h,d]=this.renderer.yscale.r_invert(t,r),l=[...this.index.indices({x0:a,x1:n,y0:h,y1:d})];return new m.Selection({indices:l})}_hit_poly(s){const{sx:i,sy:e}=s,t=(0,o.range)(0,this.sx.length),r=[];for(let s=0,a=t.length;s({angle:[u.AngleSpec,0],size:[u.ScreenSizeSpec,{value:4}],radius:[u.NullDistanceSpec,null],radius_dimension:[c.RadiusDimension,\"x\"],hit_dilation:[s,1]})))},\n", - " function _(e,l,s,i,_){var p;i();const t=e(274);class a extends t.EllipseOvalView{}s.EllipseView=a,a.__name__=\"EllipseView\";class n extends t.EllipseOval{constructor(e){super(e)}}s.Ellipse=n,p=n,n.__name__=\"Ellipse\",p.prototype.default_view=a},\n", - " function _(t,s,e,i,h){i();const n=t(1),r=t(275),a=(0,n.__importStar)(t(185)),l=t(24),_=t(72),o=(0,n.__importStar)(t(18));class d extends r.CenterRotatableView{_map_data(){\"data\"==this.model.properties.width.units?this.sw=this.sdist(this.renderer.xscale,this._x,this.width,\"center\"):this.sw=(0,l.to_screen)(this.width),\"data\"==this.model.properties.height.units?this.sh=this.sdist(this.renderer.yscale,this._y,this.height,\"center\"):this.sh=(0,l.to_screen)(this.height)}_render(t,s,e){const{sx:i,sy:h,sw:n,sh:r,angle:a}=null!=e?e:this;for(const e of s){const s=i[e],l=h[e],_=n[e],o=r[e],d=a.get(e);isFinite(s+l+_+o+d)&&(t.beginPath(),t.ellipse(s,l,_/2,o/2,d,0,2*Math.PI),this.visuals.fill.apply(t,e),this.visuals.hatch.apply(t,e),this.visuals.line.apply(t,e))}}_hit_point(t){let s,e,i,h,n,r,l,o,d;const{sx:c,sy:p}=t,w=this.renderer.xscale.invert(c),x=this.renderer.yscale.invert(p);\"data\"==this.model.properties.width.units?(s=w-this.max_width,e=w+this.max_width):(r=c-this.max_width,l=c+this.max_width,[s,e]=this.renderer.xscale.r_invert(r,l)),\"data\"==this.model.properties.height.units?(i=x-this.max_height,h=x+this.max_height):(o=p-this.max_height,d=p+this.max_height,[i,h]=this.renderer.yscale.r_invert(o,d));const m=this.index.indices({x0:s,x1:e,y0:i,y1:h}),y=[];for(const t of m)n=a.point_in_ellipse(c,p,this.angle.get(t),this.sh[t]/2,this.sw[t]/2,this.sx[t],this.sy[t]),n&&y.push(t);return new _.Selection({indices:y})}draw_legend_for_index(t,{x0:s,y0:e,x1:i,y1:h},n){const r=n+1,a=new Array(r);a[n]=(s+i)/2;const l=new Array(r);l[n]=(e+h)/2;const _=this.sw[n]/this.sh[n],d=.8*Math.min(Math.abs(i-s),Math.abs(h-e)),c=new Array(r),p=new Array(r);_>1?(c[n]=d,p[n]=d/_):(c[n]=d*_,p[n]=d);const w=new o.UniformScalar(0,r);this._render(t,[n],{sx:a,sy:l,sw:c,sh:p,angle:w})}}e.EllipseOvalView=d,d.__name__=\"EllipseOvalView\";class c extends r.CenterRotatable{constructor(t){super(t)}}e.EllipseOval=c,c.__name__=\"EllipseOval\"},\n", - " function _(e,t,i,a,n){a();const s=e(1);var r;const h=e(178),o=e(48),_=(0,s.__importStar)(e(18));class c extends h.XYGlyphView{get max_w2(){return\"data\"==this.model.properties.width.units?this.max_width/2:0}get max_h2(){return\"data\"==this.model.properties.height.units?this.max_height/2:0}_bounds({x0:e,x1:t,y0:i,y1:a}){const{max_w2:n,max_h2:s}=this;return{x0:e-n,x1:t+n,y0:i-s,y1:a+s}}}i.CenterRotatableView=c,c.__name__=\"CenterRotatableView\";class l extends h.XYGlyph{constructor(e){super(e)}}i.CenterRotatable=l,r=l,l.__name__=\"CenterRotatable\",r.mixins([o.LineVector,o.FillVector,o.HatchVector]),r.define((({})=>({angle:[_.AngleSpec,0],width:[_.DistanceSpec,{field:\"width\"}],height:[_.DistanceSpec,{field:\"height\"}]})))},\n", - " function _(t,e,s,i,h){i();const r=t(1);var a;const n=t(277),o=t(24),_=(0,r.__importStar)(t(18));class c extends n.BoxView{scenterxy(t){return[(this.sleft[t]+this.sright[t])/2,this.sy[t]]}_lrtb(t){const e=this._left[t],s=this._right[t],i=this._y[t],h=this.height.get(t)/2;return[Math.min(e,s),Math.max(e,s),i+h,i-h]}_map_data(){this.sy=this.renderer.yscale.v_compute(this._y),this.sh=this.sdist(this.renderer.yscale,this._y,this.height,\"center\"),this.sleft=this.renderer.xscale.v_compute(this._left),this.sright=this.renderer.xscale.v_compute(this._right);const t=this.sy.length;this.stop=new o.ScreenArray(t),this.sbottom=new o.ScreenArray(t);for(let e=0;e({left:[_.XCoordinateSpec,{value:0}],y:[_.YCoordinateSpec,{field:\"y\"}],height:[_.NumberSpec,{value:1}],right:[_.XCoordinateSpec,{field:\"right\"}]})))},\n", - " function _(t,e,s,r,i){var n;r();const a=t(48),h=t(179),o=t(184),c=t(72);class _ extends h.GlyphView{get_anchor_point(t,e,s){const r=Math.min(this.sleft[e],this.sright[e]),i=Math.max(this.sright[e],this.sleft[e]),n=Math.min(this.stop[e],this.sbottom[e]),a=Math.max(this.sbottom[e],this.stop[e]);switch(t){case\"top_left\":return{x:r,y:n};case\"top\":case\"top_center\":return{x:(r+i)/2,y:n};case\"top_right\":return{x:i,y:n};case\"bottom_left\":return{x:r,y:a};case\"bottom\":case\"bottom_center\":return{x:(r+i)/2,y:a};case\"bottom_right\":return{x:i,y:a};case\"left\":case\"center_left\":return{x:r,y:(n+a)/2};case\"center\":case\"center_center\":return{x:(r+i)/2,y:(n+a)/2};case\"right\":case\"center_right\":return{x:i,y:(n+a)/2}}}_index_data(t){const{min:e,max:s}=Math,{data_size:r}=this;for(let i=0;i({r:[l.NumberSpec,{field:\"r\"}],q:[l.NumberSpec,{field:\"q\"}],scale:[l.NumberSpec,1],size:[e,1],aspect_scale:[e,1],orientation:[_.HexTileOrientation,\"pointytop\"]}))),a.override({line_color:null})},\n", - " function _(e,a,t,_,r){var n;_();const s=e(280),o=e(173),i=e(201);class p extends s.ImageBaseView{connect_signals(){super.connect_signals(),this.connect(this.model.color_mapper.change,(()=>this._update_image()))}_update_image(){null!=this.image_data&&(this._set_data(null),this.renderer.request_render())}_flat_img_to_buf8(e){return this.model.color_mapper.rgba_mapper.v_compute(e)}}t.ImageView=p,p.__name__=\"ImageView\";class m extends s.ImageBase{constructor(e){super(e)}}t.Image=m,n=m,m.__name__=\"Image\",n.prototype.default_view=p,n.define((({Ref:e})=>({color_mapper:[e(o.ColorMapper),()=>new i.LinearColorMapper({palette:[\"#000000\",\"#252525\",\"#525252\",\"#737373\",\"#969696\",\"#bdbdbd\",\"#d9d9d9\",\"#f0f0f0\",\"#ffffff\"]})]})))},\n", - " function _(e,t,i,s,a){s();const h=e(1);var n;const r=e(178),_=e(24),d=(0,h.__importStar)(e(18)),l=e(72),g=e(9),o=e(29),c=e(11);class m extends r.XYGlyphView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.global_alpha.change,(()=>this.renderer.request_render()))}_render(e,t,i){const{image_data:s,sx:a,sy:h,sw:n,sh:r,global_alpha:_}=null!=i?i:this,d=e.getImageSmoothingEnabled();e.setImageSmoothingEnabled(!1);const l=_.is_Scalar();l&&(e.globalAlpha=_.value);for(const i of t){const t=s[i],_=a[i],d=h[i],g=n[i],o=r[i],c=this.global_alpha.get(i);if(null==t||!isFinite(_+d+g+o+c))continue;l||(e.globalAlpha=c);const m=d;e.translate(0,m),e.scale(1,-1),e.translate(0,-m),e.drawImage(t,0|_,0|d,g,o),e.translate(0,m),e.scale(1,-1),e.translate(0,-m)}e.setImageSmoothingEnabled(d)}_set_data(e){this._set_width_heigh_data();for(let t=0,i=this.image.length;t({image:[d.NDArraySpec,{field:\"image\"}],dw:[d.DistanceSpec,{field:\"dw\"}],dh:[d.DistanceSpec,{field:\"dh\"}],global_alpha:[d.NumberSpec,{value:1}],dilate:[e,!1]})))},\n", - " function _(e,a,t,r,_){var n;r();const s=e(280),m=e(8);class i extends s.ImageBaseView{_flat_img_to_buf8(e){let a;return a=(0,m.isArray)(e)?new Uint32Array(e):e,new Uint8ClampedArray(a.buffer)}}t.ImageRGBAView=i,i.__name__=\"ImageRGBAView\";class g extends s.ImageBase{constructor(e){super(e)}}t.ImageRGBA=g,n=g,g.__name__=\"ImageRGBA\",n.prototype.default_view=i},\n", - " function _(e,t,s,r,a){r();const i=e(1);var n;const o=e(178),c=e(24),_=e(20),h=(0,i.__importStar)(e(18)),l=e(12),d=e(136);class m extends o.XYGlyphView{constructor(){super(...arguments),this._images_rendered=!1,this._set_data_iteration=0}connect_signals(){super.connect_signals(),this.connect(this.model.properties.global_alpha.change,(()=>this.renderer.request_render()))}_index_data(e){const{data_size:t}=this;for(let s=0;s{this._set_data_iteration==r&&(this.image[a]=e,this.renderer.request_render())},attempts:t+1,timeout:s})}const a=\"data\"==this.model.properties.w.units,i=\"data\"==this.model.properties.h.units,n=this._x.length,o=new c.ScreenArray(a?2*n:n),_=new c.ScreenArray(i?2*n:n),{anchor:h}=this.model;function m(e,t){switch(h){case\"top_left\":case\"bottom_left\":case\"left\":case\"center_left\":return[e,e+t];case\"top\":case\"top_center\":case\"bottom\":case\"bottom_center\":case\"center\":case\"center_center\":return[e-t/2,e+t/2];case\"top_right\":case\"bottom_right\":case\"right\":case\"center_right\":return[e-t,e]}}function g(e,t){switch(h){case\"top_left\":case\"top\":case\"top_center\":case\"top_right\":return[e,e-t];case\"bottom_left\":case\"bottom\":case\"bottom_center\":case\"bottom_right\":return[e+t,e];case\"left\":case\"center_left\":case\"center\":case\"center_center\":case\"right\":case\"center_right\":return[e+t/2,e-t/2]}}if(a)for(let e=0;e({url:[h.StringSpec,{field:\"url\"}],anchor:[_.Anchor,\"top_left\"],global_alpha:[h.NumberSpec,{value:1}],angle:[h.AngleSpec,0],w:[h.NullDistanceSpec,null],h:[h.NullDistanceSpec,null],dilate:[e,!1],retry_attempts:[t,0],retry_timeout:[t,0]})))},\n", - " function _(e,t,s,i,n){i();const o=e(1);var r;const l=e(78),_=e(48),c=(0,o.__importStar)(e(185)),h=(0,o.__importStar)(e(18)),a=e(12),d=e(13),x=e(179),y=e(184),g=e(72);class p extends x.GlyphView{_project_data(){l.inplace.project_xy(this._xs.array,this._ys.array)}_index_data(e){const{data_size:t}=this;for(let s=0;s0&&o.set(e,s)}return new g.Selection({indices:[...o.keys()],multiline_indices:(0,d.to_object)(o)})}get_interpolation_hit(e,t,s){const i=this._xs.get(e),n=this._ys.get(e),o=i[t],r=n[t],l=i[t+1],_=n[t+1];return(0,y.line_interpolation)(this.renderer,s,o,r,l,_)}draw_legend_for_index(e,t,s){(0,y.generic_line_vector_legend)(this.visuals,e,t,s)}scenterxy(){throw new Error(`${this}.scenterxy() is not implemented`)}}s.MultiLineView=p,p.__name__=\"MultiLineView\";class u extends x.Glyph{constructor(e){super(e)}}s.MultiLine=u,r=u,u.__name__=\"MultiLine\",r.prototype.default_view=p,r.define((({})=>({xs:[h.XCoordinateSeqSpec,{field:\"xs\"}],ys:[h.YCoordinateSeqSpec,{field:\"ys\"}]}))),r.mixins(_.LineVector)},\n", - " function _(t,e,s,n,i){n();const o=t(1);var r;const l=t(181),h=t(179),a=t(184),_=t(12),c=t(12),d=t(48),x=(0,o.__importStar)(t(185)),y=(0,o.__importStar)(t(18)),f=t(72),g=t(11);class p extends h.GlyphView{_project_data(){}_index_data(t){const{min:e,max:s}=Math,{data_size:n}=this;for(let i=0;i1&&c.length>1)for(let s=1,n=i.length;s1){let r=!1;for(let t=1;t({xs:[y.XCoordinateSeqSeqSeqSpec,{field:\"xs\"}],ys:[y.YCoordinateSeqSeqSeqSpec,{field:\"ys\"}]}))),r.mixins([d.LineVector,d.FillVector,d.HatchVector])},\n", - " function _(a,e,l,s,_){var t;s();const i=a(274),n=a(12);class p extends i.EllipseOvalView{_map_data(){super._map_data(),(0,n.mul)(this.sw,.75)}}l.OvalView=p,p.__name__=\"OvalView\";class v extends i.EllipseOval{constructor(a){super(a)}}l.Oval=v,t=v,v.__name__=\"Oval\",t.prototype.default_view=p},\n", - " function _(e,t,s,i,n){i();const r=e(1);var a;const o=e(179),c=e(184),_=e(12),h=e(48),l=(0,r.__importStar)(e(185)),d=(0,r.__importStar)(e(18)),y=e(72),p=e(11),x=e(78);class f extends o.GlyphView{_project_data(){x.inplace.project_xy(this._xs.array,this._ys.array)}_index_data(e){const{data_size:t}=this;for(let s=0;s({xs:[d.XCoordinateSeqSpec,{field:\"xs\"}],ys:[d.YCoordinateSeqSpec,{field:\"ys\"}]}))),a.mixins([h.LineVector,h.FillVector,h.HatchVector])},\n", - " function _(t,e,o,i,s){i();const r=t(1);var n;const _=t(277),d=(0,r.__importStar)(t(18));class a extends _.BoxView{scenterxy(t){return[this.sleft[t]/2+this.sright[t]/2,this.stop[t]/2+this.sbottom[t]/2]}_lrtb(t){return[this._left[t],this._right[t],this._top[t],this._bottom[t]]}}o.QuadView=a,a.__name__=\"QuadView\";class c extends _.Box{constructor(t){super(t)}}o.Quad=c,n=c,c.__name__=\"Quad\",n.prototype.default_view=a,n.define((({})=>({right:[d.XCoordinateSpec,{field:\"right\"}],bottom:[d.YCoordinateSpec,{field:\"bottom\"}],left:[d.XCoordinateSpec,{field:\"left\"}],top:[d.YCoordinateSpec,{field:\"top\"}]})))},\n", - " function _(e,t,i,n,s){n();const c=e(1);var o;const r=e(48),a=e(78),_=e(179),d=e(184),l=(0,c.__importStar)(e(18));function x(e,t,i){if(t==(e+i)/2)return[e,i];{const n=(e-t)/(e-2*t+i),s=e*(1-n)**2+2*t*(1-n)*n+i*n**2;return[Math.min(e,i,s),Math.max(e,i,s)]}}class y extends _.GlyphView{_project_data(){a.inplace.project_xy(this._x0,this._y0),a.inplace.project_xy(this._x1,this._y1)}_index_data(e){const{_x0:t,_x1:i,_y0:n,_y1:s,_cx:c,_cy:o,data_size:r}=this;for(let a=0;a({x0:[l.XCoordinateSpec,{field:\"x0\"}],y0:[l.YCoordinateSpec,{field:\"y0\"}],x1:[l.XCoordinateSpec,{field:\"x1\"}],y1:[l.YCoordinateSpec,{field:\"y1\"}],cx:[l.XCoordinateSpec,{field:\"cx\"}],cy:[l.YCoordinateSpec,{field:\"cy\"}]}))),o.mixins(r.LineVector)},\n", - " function _(e,t,s,i,n){i();const l=e(1);var a;const r=e(178),o=e(184),h=e(48),_=e(24),c=(0,l.__importStar)(e(18));class g extends r.XYGlyphView{_map_data(){\"data\"==this.model.properties.length.units?this.slength=this.sdist(this.renderer.xscale,this._x,this.length):this.slength=(0,_.to_screen)(this.length);const{width:e,height:t}=this.renderer.plot_view.frame.bbox,s=2*(e+t),{slength:i}=this;for(let e=0,t=i.length;e({length:[c.DistanceSpec,0],angle:[c.AngleSpec,0]})))},\n", - " function _(t,e,s,i,r){var n,h=this&&this.__createBinding||(Object.create?function(t,e,s,i){void 0===i&&(i=s),Object.defineProperty(t,i,{enumerable:!0,get:function(){return e[s]}})}:function(t,e,s,i){void 0===i&&(i=s),t[i]=e[s]}),a=this&&this.__setModuleDefault||(Object.create?function(t,e){Object.defineProperty(t,\"default\",{enumerable:!0,value:e})}:function(t,e){t.default=e}),l=this&&this.__importStar||function(t){if(t&&t.__esModule)return t;var e={};if(null!=t)for(var s in t)\"default\"!==s&&Object.prototype.hasOwnProperty.call(t,s)&&h(e,t,s);return a(e,t),e};i();const o=t(275),c=t(184),_=t(24),d=t(12),f=t(72);class y extends o.CenterRotatableView{async lazy_initialize(){await super.lazy_initialize();const{webgl:e}=this.renderer.plot_view.canvas_view;if(null==e?void 0:e.regl_wrapper.has_webgl){const{RectGL:s}=await Promise.resolve().then((()=>l(t(425))));this.glglyph=new s(e.regl_wrapper,this)}}_map_data(){if(\"data\"==this.model.properties.width.units)[this.sw,this.sx0]=this._map_dist_corner_for_data_side_length(this._x,this.width,this.renderer.xscale);else{this.sw=(0,_.to_screen)(this.width);const t=this.sx.length;this.sx0=new _.ScreenArray(t);for(let e=0;e({dilate:[t,!1]})))},\n", - " function _(e,t,s,r,i){r();const a=e(1);var n;const l=e(292),_=e(293),c=(0,a.__importStar)(e(18));class o extends l.MarkerView{async lazy_initialize(){await super.lazy_initialize();const{webgl:t}=this.renderer.plot_view.canvas_view;if(null==t?void 0:t.regl_wrapper.has_webgl){const{MarkerGL:t}=await Promise.resolve().then((()=>(0,a.__importStar)(e(426))));this.glcls=t}}_init_webgl(){const{webgl:e}=this.renderer.plot_view.canvas_view;if(null!=e){const{regl_wrapper:t}=e;if(t.has_webgl){const e=new Set(null!=this.base?this.base.marker:this.marker);if(1==e.size){const[s]=[...e],r=this.glcls;if(null==r?void 0:r.is_supported(s)){const{glglyph:e}=this;if(null==e||e.marker_type!=s)return void(this.glglyph=new r(t,this,s))}}}}delete this.glglyph}_set_visuals(){this._init_webgl()}_render(e,t,s){const{sx:r,sy:i,size:a,angle:n,marker:l}=null!=s?s:this;for(const s of t){const t=r[s],c=i[s],o=a.get(s),g=n.get(s),h=l.get(s);if(!isFinite(t+c+o+g)||null==h)continue;const w=o/2;e.beginPath(),e.translate(t,c),g&&e.rotate(g),_.marker_funcs[h](e,s,w,this.visuals),g&&e.rotate(-g),e.translate(-t,-c)}}draw_legend_for_index(e,{x0:t,x1:s,y0:r,y1:i},a){const n=a+1,l=this.marker.get(a),_=Object.assign(Object.assign({},this._get_legend_args({x0:t,x1:s,y0:r,y1:i},a)),{marker:new c.UniformScalar(l,n)});this._render(e,[a],_)}}s.ScatterView=o,o.__name__=\"ScatterView\";class g extends l.Marker{constructor(e){super(e)}}s.Scatter=g,n=g,g.__name__=\"Scatter\",n.prototype.default_view=o,n.define((()=>({marker:[c.MarkerSpec,{value:\"circle\"}]})))},\n", - " function _(e,t,s,n,i){n();const r=e(1);var a;const c=e(178),o=e(48),_=(0,r.__importStar)(e(185)),h=(0,r.__importStar)(e(18)),l=e(9),x=e(72);class d extends c.XYGlyphView{_render(e,t,s){const{sx:n,sy:i,size:r,angle:a}=null!=s?s:this;for(const s of t){const t=n[s],c=i[s],o=r.get(s),_=a.get(s);if(!isFinite(t+c+o+_))continue;const h=o/2;e.beginPath(),e.translate(t,c),_&&e.rotate(_),this._render_one(e,s,h,this.visuals),_&&e.rotate(-_),e.translate(-t,-c)}}_mask_data(){const{x_target:e,y_target:t}=this.renderer.plot_view.frame,s=e.widen(this.max_size).map((e=>this.renderer.xscale.invert(e))),n=t.widen(this.max_size).map((e=>this.renderer.yscale.invert(e)));return this.index.indices({x0:s.start,x1:s.end,y0:n.start,y1:n.end})}_hit_point(e){const{sx:t,sy:s}=e,{max_size:n}=this,{hit_dilation:i}=this.model,r=t-n*i,a=t+n*i,[c,o]=this.renderer.xscale.r_invert(r,a),_=s-n*i,h=s+n*i,[l,d]=this.renderer.yscale.r_invert(_,h),y=this.index.indices({x0:c,x1:o,y0:l,y1:d}),g=[];for(const e of y){const n=this.size.get(e)/2*i;Math.abs(this.sx[e]-t)<=n&&Math.abs(this.sy[e]-s)<=n&&g.push(e)}return new x.Selection({indices:g})}_hit_span(e){const{sx:t,sy:s}=e,n=this.bounds(),i=this.max_size/2;let r,a,c,o;if(\"h\"==e.direction){c=n.y0,o=n.y1;const e=t-i,s=t+i;[r,a]=this.renderer.xscale.r_invert(e,s)}else{r=n.x0,a=n.x1;const e=s-i,t=s+i;[c,o]=this.renderer.yscale.r_invert(e,t)}const _=[...this.index.indices({x0:r,x1:a,y0:c,y1:o})];return new x.Selection({indices:_})}_hit_rect(e){const{sx0:t,sx1:s,sy0:n,sy1:i}=e,[r,a]=this.renderer.xscale.r_invert(t,s),[c,o]=this.renderer.yscale.r_invert(n,i),_=[...this.index.indices({x0:r,x1:a,y0:c,y1:o})];return new x.Selection({indices:_})}_hit_poly(e){const{sx:t,sy:s}=e,n=(0,l.range)(0,this.sx.length),i=[];for(let e=0,r=n.length;e({size:[h.ScreenSizeSpec,{value:4}],angle:[h.AngleSpec,0],hit_dilation:[e,1]})))},\n", - " function _(l,o,n,t,i){t();const e=Math.sqrt(3),a=Math.sqrt(5),c=(a+1)/4,p=Math.sqrt((5-a)/8),r=(a-1)/4,h=Math.sqrt((5+a)/8);function u(l,o){l.rotate(Math.PI/4),s(l,o),l.rotate(-Math.PI/4)}function f(l,o){const n=o*e,t=n/3;l.moveTo(-n/2,-t),l.lineTo(0,0),l.lineTo(n/2,-t),l.lineTo(0,0),l.lineTo(0,o)}function s(l,o){l.moveTo(0,o),l.lineTo(0,-o),l.moveTo(-o,0),l.lineTo(o,0)}function T(l,o){l.moveTo(0,o),l.lineTo(o/1.5,0),l.lineTo(0,-o),l.lineTo(-o/1.5,0),l.closePath()}function y(l,o){const n=o*e,t=n/3;l.moveTo(-o,t),l.lineTo(o,t),l.lineTo(0,t-n),l.closePath()}function v(l,o,n,t){l.arc(0,0,n,0,2*Math.PI,!1),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}function d(l,o,n,t){T(l,n),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}function _(l,o,n,t){!function(l,o){l.beginPath(),l.arc(0,0,o/4,0,2*Math.PI,!1),l.closePath()}(l,n),t.line.set_vectorize(l,o),l.fillStyle=l.strokeStyle,l.fill()}function P(l,o,n,t){!function(l,o){const n=o/2,t=e*n;l.moveTo(o,0),l.lineTo(n,-t),l.lineTo(-n,-t),l.lineTo(-o,0),l.lineTo(-n,t),l.lineTo(n,t),l.closePath()}(l,n),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}function m(l,o,n,t){const i=2*n;l.rect(-n,-n,i,i),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}function q(l,o,n,t){!function(l,o){const n=Math.sqrt(5-2*a)*o;l.moveTo(0,-o),l.lineTo(n*r,n*h-o),l.lineTo(n*(1+r),n*h-o),l.lineTo(n*(1+r-c),n*(h+p)-o),l.lineTo(n*(1+2*r-c),n*(2*h+p)-o),l.lineTo(0,2*n*h-o),l.lineTo(-n*(1+2*r-c),n*(2*h+p)-o),l.lineTo(-n*(1+r-c),n*(h+p)-o),l.lineTo(-n*(1+r),n*h-o),l.lineTo(-n*r,n*h-o),l.closePath()}(l,n),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}function M(l,o,n,t){y(l,n),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}n.marker_funcs={asterisk:function(l,o,n,t){s(l,n),u(l,n),t.line.apply(l,o)},circle:v,circle_cross:function(l,o,n,t){l.arc(0,0,n,0,2*Math.PI,!1),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),s(l,n),l.stroke())},circle_dot:function(l,o,n,t){v(l,o,n,t),_(l,o,n,t)},circle_y:function(l,o,n,t){l.arc(0,0,n,0,2*Math.PI,!1),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),f(l,n),l.stroke())},circle_x:function(l,o,n,t){l.arc(0,0,n,0,2*Math.PI,!1),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),u(l,n),l.stroke())},cross:function(l,o,n,t){s(l,n),t.line.apply(l,o)},diamond:d,diamond_dot:function(l,o,n,t){d(l,o,n,t),_(l,o,n,t)},diamond_cross:function(l,o,n,t){T(l,n),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),l.moveTo(0,n),l.lineTo(0,-n),l.moveTo(-n/1.5,0),l.lineTo(n/1.5,0),l.stroke())},dot:_,hex:P,hex_dot:function(l,o,n,t){P(l,o,n,t),_(l,o,n,t)},inverted_triangle:function(l,o,n,t){l.rotate(Math.PI),y(l,n),l.rotate(-Math.PI),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)},plus:function(l,o,n,t){const i=3*n/8,e=[i,i,n,n,i,i,-i,-i,-n,-n,-i,-i],a=[n,i,i,-i,-i,-n,-n,-i,-i,i,i,n];l.beginPath();for(let o=0;o<12;o++)l.lineTo(e[o],a[o]);l.closePath(),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)},square:m,square_cross:function(l,o,n,t){const i=2*n;l.rect(-n,-n,i,i),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),s(l,n),l.stroke())},square_dot:function(l,o,n,t){m(l,o,n,t),_(l,o,n,t)},square_pin:function(l,o,n,t){const i=3*n/8;l.moveTo(-n,-n),l.quadraticCurveTo(0,-i,n,-n),l.quadraticCurveTo(i,0,n,n),l.quadraticCurveTo(0,i,-n,n),l.quadraticCurveTo(-i,0,-n,-n),l.closePath(),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)},square_x:function(l,o,n,t){const i=2*n;l.rect(-n,-n,i,i),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),l.moveTo(-n,n),l.lineTo(n,-n),l.moveTo(-n,-n),l.lineTo(n,n),l.stroke())},star:q,star_dot:function(l,o,n,t){q(l,o,n,t),_(l,o,n,t)},triangle:M,triangle_dot:function(l,o,n,t){M(l,o,n,t),_(l,o,n,t)},triangle_pin:function(l,o,n,t){const i=n*e,a=i/3,c=3*a/8;l.moveTo(-n,a),l.quadraticCurveTo(0,c,n,a),l.quadraticCurveTo(e*c/2,c/2,0,a-i),l.quadraticCurveTo(-e*c/2,c/2,-n,a),l.closePath(),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)},dash:function(l,o,n,t){!function(l,o){l.moveTo(-o,0),l.lineTo(o,0)}(l,n),t.line.apply(l,o)},x:function(l,o,n,t){u(l,n),t.line.apply(l,o)},y:function(l,o,n,t){f(l,n),t.line.apply(l,o)}}},\n", - " function _(e,t,s,i,n){i();const r=e(1);var o;const _=(0,r.__importStar)(e(185)),h=(0,r.__importStar)(e(18)),c=e(48),a=e(78),d=e(179),x=e(184),l=e(72);class y extends d.GlyphView{_project_data(){a.inplace.project_xy(this._x0,this._y0),a.inplace.project_xy(this._x1,this._y1)}_index_data(e){const{min:t,max:s}=Math,{_x0:i,_x1:n,_y0:r,_y1:o,data_size:_}=this;for(let h=0;h<_;h++){const _=i[h],c=n[h],a=r[h],d=o[h];e.add_rect(t(_,c),t(a,d),s(_,c),s(a,d))}}_render(e,t,s){if(this.visuals.line.doit){const{sx0:i,sy0:n,sx1:r,sy1:o}=null!=s?s:this;for(const s of t){const t=i[s],_=n[s],h=r[s],c=o[s];isFinite(t+_+h+c)&&(e.beginPath(),e.moveTo(t,_),e.lineTo(h,c),this.visuals.line.set_vectorize(e,s),e.stroke())}}}_hit_point(e){const{sx:t,sy:s}=e,i={x:t,y:s},[n,r]=this.renderer.xscale.r_invert(t-2,t+2),[o,h]=this.renderer.yscale.r_invert(s-2,s+2),c=this.index.indices({x0:n,y0:o,x1:r,y1:h}),a=[];for(const e of c){const t=Math.max(2,this.line_width.get(e)/2)**2,s={x:this.sx0[e],y:this.sy0[e]},n={x:this.sx1[e],y:this.sy1[e]};_.dist_to_segment_squared(i,s,n)({x0:[h.XCoordinateSpec,{field:\"x0\"}],y0:[h.YCoordinateSpec,{field:\"y0\"}],x1:[h.XCoordinateSpec,{field:\"x1\"}],y1:[h.YCoordinateSpec,{field:\"y1\"}]}))),o.mixins(c.LineVector)},\n", - " function _(t,e,s,i,n){i();const o=t(1);var _;const l=t(178),a=(0,o.__importStar)(t(48)),c=t(296);class r extends l.XYGlyphView{_set_data(){const{tension:t,closed:e}=this.model;[this._xt,this._yt]=(0,c.catmullrom_spline)(this._x,this._y,20,t,e)}_map_data(){const{x_scale:t,y_scale:e}=this.renderer.coordinates;this.sxt=t.v_compute(this._xt),this.syt=e.v_compute(this._yt)}_render(t,e,s){const{sxt:i,syt:n}=null!=s?s:this;let o=!0;t.beginPath();const _=i.length;for(let e=0;e<_;e++){const s=i[e],_=n[e];isFinite(s+_)?o?(t.moveTo(s,_),o=!1):t.lineTo(s,_):o=!0}this.visuals.line.set_value(t),t.stroke()}}s.SplineView=r,r.__name__=\"SplineView\";class h extends l.XYGlyph{constructor(t){super(t)}}s.Spline=h,_=h,h.__name__=\"Spline\",_.prototype.default_view=r,_.mixins(a.LineScalar),_.define((({Boolean:t,Number:e})=>({tension:[e,.5],closed:[t,!1]})))},\n", - " function _(n,t,e,o,s){o();const c=n(24),l=n(11);e.catmullrom_spline=function(n,t,e=10,o=.5,s=!1){(0,l.assert)(n.length==t.length);const r=n.length,f=s?r+1:r,w=(0,c.infer_type)(n,t),i=new w(f+2),u=new w(f+2);i.set(n,1),u.set(t,1),s?(i[0]=n[r-1],u[0]=t[r-1],i[f]=n[0],u[f]=t[0],i[f+1]=n[1],u[f+1]=t[1]):(i[0]=n[0],u[0]=t[0],i[f+1]=n[r-1],u[f+1]=t[r-1]);const g=new w(4*(e+1));for(let n=0,t=0;n<=e;n++){const o=n/e,s=o**2,c=o*s;g[t++]=2*c-3*s+1,g[t++]=-2*c+3*s,g[t++]=c-2*s+o,g[t++]=c-s}const h=new w((f-1)*(e+1)),_=new w((f-1)*(e+1));for(let n=1,t=0;n1&&(e.stroke(),o=!1)}o?(e.lineTo(t,r),e.lineTo(a,c)):(e.beginPath(),e.moveTo(s[n],i[n]),o=!0),l=n}e.lineTo(s[a-1],i[a-1]),e.stroke()}}draw_legend_for_index(e,t,n){(0,r.generic_line_scalar_legend)(this.visuals,e,t)}}n.StepView=f,f.__name__=\"StepView\";class u extends a.XYGlyph{constructor(e){super(e)}}n.Step=u,l=u,u.__name__=\"Step\",l.prototype.default_view=f,l.mixins(c.LineScalar),l.define((()=>({mode:[_.StepMode,\"before\"]})))},\n", - " function _(t,e,s,i,n){i();const o=t(1);var _;const h=t(178),l=t(48),r=(0,o.__importStar)(t(185)),a=(0,o.__importStar)(t(18)),c=t(121),x=t(11),u=t(72);class f extends h.XYGlyphView{_rotate_point(t,e,s,i,n){return[(t-s)*Math.cos(n)-(e-i)*Math.sin(n)+s,(t-s)*Math.sin(n)+(e-i)*Math.cos(n)+i]}_text_bounds(t,e,s,i){return[[t,t+s,t+s,t,t],[e,e,e-i,e-i,e]]}_render(t,e,s){const{sx:i,sy:n,x_offset:o,y_offset:_,angle:h,text:l}=null!=s?s:this;this._sys=[],this._sxs=[];for(const s of e){const e=this._sxs[s]=[],r=this._sys[s]=[],a=i[s],x=n[s],u=o.get(s),f=_.get(s),p=h.get(s),g=l.get(s);if(isFinite(a+x+u+f+p)&&null!=g&&this.visuals.text.doit){const i=`${g}`;t.save(),t.translate(a+u,x+f),t.rotate(p),this.visuals.text.set_vectorize(t,s);const n=this.visuals.text.font_value(s),{height:o}=(0,c.font_metrics)(n),_=this.text_line_height.get(s)*o;if(-1==i.indexOf(\"\\n\")){t.fillText(i,0,0);const s=a+u,n=x+f,o=t.measureText(i).width,[h,l]=this._text_bounds(s,n,o,_);e.push(h),r.push(l)}else{const n=i.split(\"\\n\"),o=_*n.length,h=this.text_baseline.get(s);let l;switch(h){case\"top\":l=0;break;case\"middle\":l=-o/2+_/2;break;case\"bottom\":l=-o+_;break;default:l=0,console.warn(`'${h}' baseline not supported with multi line text`)}for(const s of n){t.fillText(s,0,l);const i=a+u,n=l+x+f,o=t.measureText(s).width,[h,c]=this._text_bounds(i,n,o,_);e.push(h),r.push(c),l+=_}}t.restore()}}}_hit_point(t){const{sx:e,sy:s}=t,i=[];for(let t=0;t({text:[a.NullStringSpec,{field:\"text\"}],angle:[a.AngleSpec,0],x_offset:[a.NumberSpec,0],y_offset:[a.NumberSpec,0]})))},\n", - " function _(t,s,e,i,r){i();const h=t(1);var o;const a=t(277),n=t(24),_=(0,h.__importStar)(t(18));class c extends a.BoxView{scenterxy(t){return[this.sx[t],(this.stop[t]+this.sbottom[t])/2]}_lrtb(t){const s=this.width.get(t)/2,e=this._x[t],i=this._top[t],r=this._bottom[t];return[e-s,e+s,Math.max(i,r),Math.min(i,r)]}_map_data(){this.sx=this.renderer.xscale.v_compute(this._x),this.sw=this.sdist(this.renderer.xscale,this._x,this.width,\"center\"),this.stop=this.renderer.yscale.v_compute(this._top),this.sbottom=this.renderer.yscale.v_compute(this._bottom);const t=this.sx.length;this.sleft=new n.ScreenArray(t),this.sright=new n.ScreenArray(t);for(let s=0;s({x:[_.XCoordinateSpec,{field:\"x\"}],bottom:[_.YCoordinateSpec,{value:0}],width:[_.NumberSpec,{value:1}],top:[_.YCoordinateSpec,{field:\"top\"}]})))},\n", - " function _(e,s,t,i,n){i();const r=e(1);var a;const c=e(178),l=e(184),d=e(48),o=e(24),h=e(20),_=(0,r.__importStar)(e(18)),u=e(10),g=e(72);class p extends c.XYGlyphView{_map_data(){\"data\"==this.model.properties.radius.units?this.sradius=this.sdist(this.renderer.xscale,this._x,this.radius):this.sradius=(0,o.to_screen)(this.radius)}_render(e,s,t){const{sx:i,sy:n,sradius:r,start_angle:a,end_angle:c}=null!=t?t:this,l=\"anticlock\"==this.model.direction;for(const t of s){const s=i[t],d=n[t],o=r[t],h=a.get(t),_=c.get(t);isFinite(s+d+o+h+_)&&(e.beginPath(),e.arc(s,d,o,h,_,l),e.lineTo(s,d),e.closePath(),this.visuals.fill.apply(e,t),this.visuals.hatch.apply(e,t),this.visuals.line.apply(e,t))}}_hit_point(e){let s,t,i,n,r,a,c,l,d;const{sx:o,sy:h}=e,_=this.renderer.xscale.invert(o),p=this.renderer.yscale.invert(h),x=2*this.max_radius;\"data\"===this.model.properties.radius.units?(a=_-x,c=_+x,l=p-x,d=p+x):(t=o-x,i=o+x,[a,c]=this.renderer.xscale.r_invert(t,i),n=h-x,r=h+x,[l,d]=this.renderer.yscale.r_invert(n,r));const y=[];for(const e of this.index.indices({x0:a,x1:c,y0:l,y1:d})){const a=this.sradius[e]**2;[t,i]=this.renderer.xscale.r_compute(_,this._x[e]),[n,r]=this.renderer.yscale.r_compute(p,this._y[e]),s=(t-i)**2+(n-r)**2,s<=a&&y.push(e)}const f=\"anticlock\"==this.model.direction,m=[];for(const e of y){const s=Math.atan2(h-this.sy[e],o-this.sx[e]);(0,u.angle_between)(-s,-this.start_angle.get(e),-this.end_angle.get(e),f)&&m.push(e)}return new g.Selection({indices:m})}draw_legend_for_index(e,s,t){(0,l.generic_area_vector_legend)(this.visuals,e,s,t)}scenterxy(e){const s=this.sradius[e]/2,t=(this.start_angle.get(e)+this.end_angle.get(e))/2;return[this.sx[e]+s*Math.cos(t),this.sy[e]+s*Math.sin(t)]}}t.WedgeView=p,p.__name__=\"WedgeView\";class x extends c.XYGlyph{constructor(e){super(e)}}t.Wedge=x,a=x,x.__name__=\"Wedge\",a.prototype.default_view=p,a.mixins([d.LineVector,d.FillVector,d.HatchVector]),a.define((({})=>({direction:[h.Direction,\"anticlock\"],radius:[_.DistanceSpec,{field:\"radius\"}],start_angle:[_.AngleSpec,{field:\"start_angle\"}],end_angle:[_.AngleSpec,{field:\"end_angle\"}]})))},\n", - " function _(t,_,r,o,a){o();const e=t(1);(0,e.__exportStar)(t(302),r),(0,e.__exportStar)(t(303),r),(0,e.__exportStar)(t(304),r)},\n", - " function _(e,t,d,n,s){n();const o=e(53),r=e(12),_=e(9),i=e(72);class c extends o.Model{constructor(e){super(e)}_hit_test(e,t,d){if(!t.model.visible)return null;const n=d.glyph.hit_test(e);return null==n?null:d.model.view.convert_selection_from_subset(n)}}d.GraphHitTestPolicy=c,c.__name__=\"GraphHitTestPolicy\";class a extends c{constructor(e){super(e)}hit_test(e,t){return this._hit_test(e,t,t.edge_view)}do_selection(e,t,d,n){if(null==e)return!1;const s=t.edge_renderer.data_source.selected;return s.update(e,d,n),t.edge_renderer.data_source._select.emit(),!s.is_empty()}do_inspection(e,t,d,n,s){if(null==e)return!1;const{edge_renderer:o}=d.model,r=o.get_selection_manager().get_or_create_inspector(d.edge_view.model);return r.update(e,n,s),d.edge_view.model.data_source.setv({inspected:r},{silent:!0}),d.edge_view.model.data_source.inspect.emit([d.edge_view.model,{geometry:t}]),!r.is_empty()}}d.EdgesOnly=a,a.__name__=\"EdgesOnly\";class l extends c{constructor(e){super(e)}hit_test(e,t){return this._hit_test(e,t,t.node_view)}do_selection(e,t,d,n){if(null==e)return!1;const s=t.node_renderer.data_source.selected;return s.update(e,d,n),t.node_renderer.data_source._select.emit(),!s.is_empty()}do_inspection(e,t,d,n,s){if(null==e)return!1;const{node_renderer:o}=d.model,r=o.get_selection_manager().get_or_create_inspector(d.node_view.model);return r.update(e,n,s),d.node_view.model.data_source.setv({inspected:r},{silent:!0}),d.node_view.model.data_source.inspect.emit([d.node_view.model,{geometry:t}]),!r.is_empty()}}d.NodesOnly=l,l.__name__=\"NodesOnly\";class u extends c{constructor(e){super(e)}hit_test(e,t){return this._hit_test(e,t,t.node_view)}get_linked_edges(e,t,d){let n=[];\"selection\"==d?n=e.selected.indices.map((t=>e.data.index[t])):\"inspection\"==d&&(n=e.inspected.indices.map((t=>e.data.index[t])));const s=[];for(let e=0;e(0,r.indexOf)(e.data.index,t)));return new i.Selection({indices:o})}do_selection(e,t,d,n){if(null==e)return!1;const s=t.edge_renderer.data_source.selected;s.update(e,d,n);const o=t.node_renderer.data_source.selected,r=this.get_linked_nodes(t.node_renderer.data_source,t.edge_renderer.data_source,\"selection\");return o.update(r,d,n),t.edge_renderer.data_source._select.emit(),!s.is_empty()}do_inspection(e,t,d,n,s){if(null==e)return!1;const o=d.edge_view.model.data_source.selection_manager.get_or_create_inspector(d.edge_view.model);o.update(e,n,s),d.edge_view.model.data_source.setv({inspected:o},{silent:!0});const r=d.node_view.model.data_source.selection_manager.get_or_create_inspector(d.node_view.model),_=this.get_linked_nodes(d.node_view.model.data_source,d.edge_view.model.data_source,\"inspection\");return r.update(_,n,s),d.node_view.model.data_source.setv({inspected:r},{silent:!0}),d.edge_view.model.data_source.inspect.emit([d.edge_view.model,{geometry:t}]),!o.is_empty()}}d.EdgesAndLinkedNodes=m,m.__name__=\"EdgesAndLinkedNodes\"},\n", - " function _(e,o,t,r,n){var s;r();const a=e(53),d=e(260);class _ extends a.Model{constructor(e){super(e)}get node_coordinates(){return new u({layout:this})}get edge_coordinates(){return new i({layout:this})}}t.LayoutProvider=_,_.__name__=\"LayoutProvider\";class c extends d.CoordinateTransform{constructor(e){super(e)}}t.GraphCoordinates=c,s=c,c.__name__=\"GraphCoordinates\",s.define((({Ref:e})=>({layout:[e(_)]})));class u extends c{constructor(e){super(e)}_v_compute(e){const[o,t]=this.layout.get_node_coordinates(e);return{x:o,y:t}}}t.NodeCoordinates=u,u.__name__=\"NodeCoordinates\";class i extends c{constructor(e){super(e)}_v_compute(e){const[o,t]=this.layout.get_edge_coordinates(e);return{x:o,y:t}}}t.EdgeCoordinates=i,i.__name__=\"EdgeCoordinates\"},\n", - " function _(t,a,l,e,n){var o;e();const r=t(303);class u extends r.LayoutProvider{constructor(t){super(t)}get_node_coordinates(t){var a;const l=null!==(a=t.data.index)&&void 0!==a?a:[],e=l.length,n=new Float64Array(e),o=new Float64Array(e);for(let t=0;t({graph_layout:[l(a(t,t)),{}]})))},\n", - " function _(i,d,n,r,G){r(),G(\"Grid\",i(306).Grid)},\n", - " function _(i,e,n,s,t){s();const r=i(1);var o;const d=i(127),_=i(129),a=i(130),l=(0,r.__importStar)(i(48)),h=i(8);class c extends _.GuideRendererView{_render(){const i=this.layer.ctx;i.save(),this._draw_regions(i),this._draw_minor_grids(i),this._draw_grids(i),i.restore()}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render()))}_draw_regions(i){if(!this.visuals.band_fill.doit&&!this.visuals.band_hatch.doit)return;const[e,n]=this.grid_coords(\"major\",!1);for(let s=0;sn[1]&&(t=n[1]);else{[s,t]=n;for(const i of this.plot_view.axis_views)i.dimension==this.model.dimension&&i.model.x_range_name==this.model.x_range_name&&i.model.y_range_name==this.model.y_range_name&&([s,t]=i.computed_bounds)}return[s,t]}grid_coords(i,e=!0){const n=this.model.dimension,s=(n+1)%2,[t,r]=this.ranges();let[o,d]=this.computed_bounds();[o,d]=[Math.min(o,d),Math.max(o,d)];const _=[[],[]],a=this.model.get_ticker();if(null==a)return _;const l=a.get_ticks(o,d,t,r.min)[i],h=t.min,c=t.max,u=r.min,m=r.max;e||(l[0]!=h&&l.splice(0,0,h),l[l.length-1]!=c&&l.push(c));for(let i=0;i({bounds:[r(t(i,i),e),\"auto\"],dimension:[n(0,1),0],axis:[o(s(d.Axis)),null],ticker:[o(s(a.Ticker)),null]}))),o.override({level:\"underlay\",band_fill_color:null,band_fill_alpha:0,grid_line_color:\"#e5e5e5\",minor_grid_line_color:null})},\n", - " function _(o,a,x,B,e){B(),e(\"Box\",o(308).Box),e(\"Column\",o(310).Column),e(\"GridBox\",o(311).GridBox),e(\"HTMLBox\",o(312).HTMLBox),e(\"LayoutDOM\",o(309).LayoutDOM),e(\"Panel\",o(313).Panel),e(\"Row\",o(314).Row),e(\"Spacer\",o(315).Spacer),e(\"Tabs\",o(316).Tabs),e(\"WidgetBox\",o(319).WidgetBox)},\n", - " function _(e,n,s,t,c){var i;t();const o=e(309);class r extends o.LayoutDOMView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.children.change,(()=>this.rebuild()))}get child_models(){return this.model.children}}s.BoxView=r,r.__name__=\"BoxView\";class a extends o.LayoutDOM{constructor(e){super(e)}}s.Box=a,i=a,a.__name__=\"Box\",i.define((({Number:e,Array:n,Ref:s})=>({children:[n(s(o.LayoutDOM)),[]],spacing:[e,0]})))},\n", - " function _(t,i,e,s,o){var l;s();const n=t(53),h=t(20),a=t(43),r=t(19),_=t(8),c=t(22),u=t(121),d=t(113),p=t(226),m=t(207),g=t(44),w=t(235);class f extends p.DOMView{constructor(){super(...arguments),this._offset_parent=null,this._viewport={}}get is_layout_root(){return this.is_root||!(this.parent instanceof f)}get base_font_size(){const t=getComputedStyle(this.el).fontSize,i=(0,u.parse_css_font_size)(t);if(null!=i){const{value:t,unit:e}=i;if(\"px\"==e)return t}return null}initialize(){super.initialize(),this.el.style.position=this.is_layout_root?\"relative\":\"absolute\",this._child_views=new Map}async lazy_initialize(){await super.lazy_initialize(),await this.build_child_views()}remove(){for(const t of this.child_views)t.remove();this._child_views.clear(),super.remove()}connect_signals(){super.connect_signals(),this.is_layout_root&&(this._on_resize=()=>this.resize_layout(),window.addEventListener(\"resize\",this._on_resize),this._parent_observer=setInterval((()=>{const t=this.el.offsetParent;this._offset_parent!=t&&(this._offset_parent=t,null!=t&&(this.compute_viewport(),this.invalidate_layout()))}),250));const t=this.model.properties;this.on_change([t.width,t.height,t.min_width,t.min_height,t.max_width,t.max_height,t.margin,t.width_policy,t.height_policy,t.sizing_mode,t.aspect_ratio,t.visible],(()=>this.invalidate_layout())),this.on_change([t.background,t.css_classes],(()=>this.invalidate_render()))}disconnect_signals(){null!=this._parent_observer&&clearTimeout(this._parent_observer),null!=this._on_resize&&window.removeEventListener(\"resize\",this._on_resize),super.disconnect_signals()}css_classes(){return super.css_classes().concat(this.model.css_classes)}get child_views(){return this.child_models.map((t=>this._child_views.get(t)))}async build_child_views(){await(0,d.build_views)(this._child_views,this.child_models,{parent:this})}render(){super.render(),(0,a.empty)(this.el);const{background:t}=this.model;this.el.style.backgroundColor=null!=t?(0,c.color2css)(t):\"\",(0,a.classes)(this.el).clear().add(...this.css_classes());for(const t of this.child_views)this.el.appendChild(t.el),t.render()}update_layout(){for(const t of this.child_views)t.update_layout();this._update_layout()}update_position(){this.el.style.display=this.model.visible?\"block\":\"none\";const t=this.is_layout_root?this.layout.sizing.margin:void 0;(0,a.position)(this.el,this.layout.bbox,t);for(const t of this.child_views)t.update_position()}after_layout(){for(const t of this.child_views)t.after_layout();this._has_finished=!0}compute_viewport(){this._viewport=this._viewport_size()}renderTo(t){t.appendChild(this.el),this._offset_parent=this.el.offsetParent,this.compute_viewport(),this.build(),this.notify_finished()}build(){if(!this.is_layout_root)throw new Error(`${this.toString()} is not a root layout`);return this.render(),this.update_layout(),this.compute_layout(),this}async rebuild(){await this.build_child_views(),this.invalidate_render()}compute_layout(){const t=Date.now();this.layout.compute(this._viewport),this.update_position(),this.after_layout(),r.logger.debug(`layout computed in ${Date.now()-t} ms`)}resize_layout(){this.root.compute_viewport(),this.root.compute_layout()}invalidate_layout(){this.root.update_layout(),this.root.compute_layout()}invalidate_render(){this.render(),this.invalidate_layout()}has_finished(){if(!super.has_finished())return!1;for(const t of this.child_views)if(!t.has_finished())return!1;return!0}_width_policy(){return null!=this.model.width?\"fixed\":\"fit\"}_height_policy(){return null!=this.model.height?\"fixed\":\"fit\"}box_sizing(){let{width_policy:t,height_policy:i,aspect_ratio:e}=this.model;\"auto\"==t&&(t=this._width_policy()),\"auto\"==i&&(i=this._height_policy());const{sizing_mode:s}=this.model;if(null!=s)if(\"fixed\"==s)t=i=\"fixed\";else if(\"stretch_both\"==s)t=i=\"max\";else if(\"stretch_width\"==s)t=\"max\";else if(\"stretch_height\"==s)i=\"max\";else switch(null==e&&(e=\"auto\"),s){case\"scale_width\":t=\"max\",i=\"min\";break;case\"scale_height\":t=\"min\",i=\"max\";break;case\"scale_both\":t=\"max\",i=\"max\"}const o={width_policy:t,height_policy:i},{min_width:l,min_height:n}=this.model;null!=l&&(o.min_width=l),null!=n&&(o.min_height=n);const{width:h,height:a}=this.model;null!=h&&(o.width=h),null!=a&&(o.height=a);const{max_width:r,max_height:c}=this.model;null!=r&&(o.max_width=r),null!=c&&(o.max_height=c),\"auto\"==e&&null!=h&&null!=a?o.aspect=h/a:(0,_.isNumber)(e)&&(o.aspect=e);const{margin:u}=this.model;if(null!=u)if((0,_.isNumber)(u))o.margin={top:u,right:u,bottom:u,left:u};else if(2==u.length){const[t,i]=u;o.margin={top:t,right:i,bottom:t,left:i}}else{const[t,i,e,s]=u;o.margin={top:t,right:i,bottom:e,left:s}}o.visible=this.model.visible;const{align:d}=this.model;return(0,_.isArray)(d)?[o.halign,o.valign]=d:o.halign=o.valign=d,o}_viewport_size(){return(0,a.undisplayed)(this.el,(()=>{let t=this.el;for(;t=t.parentElement;){if(t.classList.contains(g.root))continue;if(t==document.body){const{margin:{left:t,right:i,top:e,bottom:s}}=(0,a.extents)(document.body);return{width:Math.ceil(document.documentElement.clientWidth-t-i),height:Math.ceil(document.documentElement.clientHeight-e-s)}}const{padding:{left:i,right:e,top:s,bottom:o}}=(0,a.extents)(t),{width:l,height:n}=t.getBoundingClientRect(),h=Math.ceil(l-i-e),r=Math.ceil(n-s-o);if(h>0||r>0)return{width:h>0?h:void 0,height:r>0?r:void 0}}return{}}))}export(t,i=!0){const e=\"png\"==t?\"canvas\":\"svg\",s=new w.CanvasLayer(e,i),{width:o,height:l}=this.layout.bbox;s.resize(o,l);for(const e of this.child_views){const o=e.export(t,i),{x:l,y:n}=e.layout.bbox;s.ctx.drawImage(o.canvas,l,n)}return s}serializable_state(){return Object.assign(Object.assign({},super.serializable_state()),{bbox:this.layout.bbox.box,children:this.child_views.map((t=>t.serializable_state()))})}}e.LayoutDOMView=f,f.__name__=\"LayoutDOMView\";class y extends n.Model{constructor(t){super(t)}}e.LayoutDOM=y,l=y,y.__name__=\"LayoutDOM\",l.define((t=>{const{Boolean:i,Number:e,String:s,Auto:o,Color:l,Array:n,Tuple:a,Or:r,Null:_,Nullable:c}=t,u=a(e,e),d=a(e,e,e,e);return{width:[c(e),null],height:[c(e),null],min_width:[c(e),null],min_height:[c(e),null],max_width:[c(e),null],max_height:[c(e),null],margin:[c(r(e,u,d)),[0,0,0,0]],width_policy:[r(m.SizingPolicy,o),\"auto\"],height_policy:[r(m.SizingPolicy,o),\"auto\"],aspect_ratio:[r(e,o,_),null],sizing_mode:[c(h.SizingMode),null],visible:[i,!0],disabled:[i,!1],align:[r(h.Align,a(h.Align,h.Align)),\"start\"],background:[c(l),null],css_classes:[n(s),[]]}}))},\n", - " function _(o,s,t,i,e){var n;i();const a=o(308),l=o(209);class u extends a.BoxView{_update_layout(){const o=this.child_views.map((o=>o.layout));this.layout=new l.Column(o),this.layout.rows=this.model.rows,this.layout.spacing=[this.model.spacing,0],this.layout.set_sizing(this.box_sizing())}}t.ColumnView=u,u.__name__=\"ColumnView\";class _ extends a.Box{constructor(o){super(o)}}t.Column=_,n=_,_.__name__=\"Column\",n.prototype.default_view=u,n.define((({Any:o})=>({rows:[o,\"auto\"]})))},\n", - " function _(s,o,t,i,e){var n;i();const l=s(309),a=s(209);class r extends l.LayoutDOMView{connect_signals(){super.connect_signals();const{children:s,rows:o,cols:t,spacing:i}=this.model.properties;this.on_change([s,o,t,i],(()=>this.rebuild()))}get child_models(){return this.model.children.map((([s])=>s))}_update_layout(){this.layout=new a.Grid,this.layout.rows=this.model.rows,this.layout.cols=this.model.cols,this.layout.spacing=this.model.spacing;for(const[s,o,t,i,e]of this.model.children){const n=this._child_views.get(s);this.layout.items.push({layout:n.layout,row:o,col:t,row_span:i,col_span:e})}this.layout.set_sizing(this.box_sizing())}}t.GridBoxView=r,r.__name__=\"GridBoxView\";class c extends l.LayoutDOM{constructor(s){super(s)}}t.GridBox=c,n=c,c.__name__=\"GridBox\",n.prototype.default_view=r,n.define((({Any:s,Int:o,Number:t,Tuple:i,Array:e,Ref:n,Or:a,Opt:r})=>({children:[e(i(n(l.LayoutDOM),o,o,r(o),r(o))),[]],rows:[s,\"auto\"],cols:[s,\"auto\"],spacing:[a(t,i(t,t)),0]})))},\n", - " function _(t,e,o,s,n){s();const _=t(309),i=t(207);class a extends _.LayoutDOMView{get child_models(){return[]}_update_layout(){this.layout=new i.ContentBox(this.el),this.layout.set_sizing(this.box_sizing())}}o.HTMLBoxView=a,a.__name__=\"HTMLBoxView\";class u extends _.LayoutDOM{constructor(t){super(t)}}o.HTMLBox=u,u.__name__=\"HTMLBox\"},\n", - " function _(e,n,l,a,o){var t;a();const s=e(53),c=e(309);class d extends s.Model{constructor(e){super(e)}}l.Panel=d,t=d,d.__name__=\"Panel\",t.define((({Boolean:e,String:n,Ref:l})=>({title:[n,\"\"],child:[l(c.LayoutDOM)],closable:[e,!1],disabled:[e,!1]})))},\n", - " function _(o,s,t,i,e){var a;i();const n=o(308),l=o(209);class _ extends n.BoxView{_update_layout(){const o=this.child_views.map((o=>o.layout));this.layout=new l.Row(o),this.layout.cols=this.model.cols,this.layout.spacing=[0,this.model.spacing],this.layout.set_sizing(this.box_sizing())}}t.RowView=_,_.__name__=\"RowView\";class c extends n.Box{constructor(o){super(o)}}t.Row=c,a=c,c.__name__=\"Row\",a.prototype.default_view=_,a.define((({Any:o})=>({cols:[o,\"auto\"]})))},\n", - " function _(e,t,a,s,_){var o;s();const i=e(309),n=e(207);class u extends i.LayoutDOMView{get child_models(){return[]}_update_layout(){this.layout=new n.LayoutItem,this.layout.set_sizing(this.box_sizing())}}a.SpacerView=u,u.__name__=\"SpacerView\";class c extends i.LayoutDOM{constructor(e){super(e)}}a.Spacer=c,o=c,c.__name__=\"Spacer\",o.prototype.default_view=u},\n", - " function _(e,t,s,i,l){i();const h=e(1);var a;const o=e(207),d=e(43),r=e(9),c=e(10),n=e(20),_=e(309),p=e(313),b=(0,h.__importStar)(e(317)),m=b,u=(0,h.__importStar)(e(318)),g=u,v=(0,h.__importStar)(e(229)),w=v;class f extends _.LayoutDOMView{constructor(){super(...arguments),this._scroll_index=0}connect_signals(){super.connect_signals(),this.connect(this.model.properties.tabs.change,(()=>this.rebuild())),this.connect(this.model.properties.active.change,(()=>this.on_active_change()))}styles(){return[...super.styles(),u.default,v.default,b.default]}get child_models(){return this.model.tabs.map((e=>e.child))}_update_layout(){const e=this.model.tabs_location,t=\"above\"==e||\"below\"==e,{scroll_el:s,headers_el:i}=this;this.header=new class extends o.ContentBox{_measure(e){const l=(0,d.size)(s),h=(0,d.children)(i).slice(0,3).map((e=>(0,d.size)(e))),{width:a,height:o}=super._measure(e);if(t){const t=l.width+(0,r.sum)(h.map((e=>e.width)));return{width:e.width!=1/0?e.width:t,height:o}}{const t=l.height+(0,r.sum)(h.map((e=>e.height)));return{width:a,height:e.height!=1/0?e.height:t}}}}(this.header_el),t?this.header.set_sizing({width_policy:\"fit\",height_policy:\"fixed\"}):this.header.set_sizing({width_policy:\"fixed\",height_policy:\"fit\"});let l=1,h=1;switch(e){case\"above\":l-=1;break;case\"below\":l+=1;break;case\"left\":h-=1;break;case\"right\":h+=1}const a={layout:this.header,row:l,col:h},c=this.child_views.map((e=>({layout:e.layout,row:1,col:1})));this.layout=new o.Grid([a,...c]),this.layout.set_sizing(this.box_sizing())}update_position(){super.update_position(),this.header_el.style.position=\"absolute\",(0,d.position)(this.header_el,this.header.bbox);const e=this.model.tabs_location,t=\"above\"==e||\"below\"==e,s=(0,d.size)(this.scroll_el),i=(0,d.scroll_size)(this.headers_el);if(t){const{width:e}=this.header.bbox;i.width>e?(this.wrapper_el.style.maxWidth=e-s.width+\"px\",(0,d.display)(this.scroll_el),this.do_scroll(this.model.active)):(this.wrapper_el.style.maxWidth=\"\",(0,d.undisplay)(this.scroll_el))}else{const{height:e}=this.header.bbox;i.height>e?(this.wrapper_el.style.maxHeight=e-s.height+\"px\",(0,d.display)(this.scroll_el),this.do_scroll(this.model.active)):(this.wrapper_el.style.maxHeight=\"\",(0,d.undisplay)(this.scroll_el))}const{child_views:l}=this;for(const e of l)(0,d.hide)(e.el);const h=l[this.model.active];null!=h&&(0,d.show)(h.el)}render(){super.render();const{active:e}=this.model,t=this.model.tabs.map(((t,s)=>{const i=(0,d.div)({class:[m.tab,s==e?m.active:null]},t.title);if(i.addEventListener(\"click\",(e=>{this.model.disabled||e.target==e.currentTarget&&this.change_active(s)})),t.closable){const e=(0,d.div)({class:m.close});e.addEventListener(\"click\",(e=>{if(e.target==e.currentTarget){this.model.tabs=(0,r.remove_at)(this.model.tabs,s);const e=this.model.tabs.length;this.model.active>e-1&&(this.model.active=e-1)}})),i.appendChild(e)}return(this.model.disabled||t.disabled)&&i.classList.add(m.disabled),i}));this.headers_el=(0,d.div)({class:[m.headers]},t),this.wrapper_el=(0,d.div)({class:m.headers_wrapper},this.headers_el),this.left_el=(0,d.div)({class:[g.btn,g.btn_default],disabled:\"\"},(0,d.div)({class:[w.caret,m.left]})),this.right_el=(0,d.div)({class:[g.btn,g.btn_default]},(0,d.div)({class:[w.caret,m.right]})),this.left_el.addEventListener(\"click\",(()=>this.do_scroll(\"left\"))),this.right_el.addEventListener(\"click\",(()=>this.do_scroll(\"right\"))),this.scroll_el=(0,d.div)({class:g.btn_group},this.left_el,this.right_el);const s=this.model.tabs_location;this.header_el=(0,d.div)({class:[m.tabs_header,m[s]]},this.scroll_el,this.wrapper_el),this.el.appendChild(this.header_el)}do_scroll(e){const t=this.model.tabs.length;\"left\"==e?this._scroll_index-=1:\"right\"==e?this._scroll_index+=1:this._scroll_index=e,this._scroll_index=(0,c.clamp)(this._scroll_index,0,t-1),0==this._scroll_index?this.left_el.setAttribute(\"disabled\",\"\"):this.left_el.removeAttribute(\"disabled\"),this._scroll_index==t-1?this.right_el.setAttribute(\"disabled\",\"\"):this.right_el.removeAttribute(\"disabled\");const s=(0,d.children)(this.headers_el).slice(0,this._scroll_index).map((e=>e.getBoundingClientRect())),i=this.model.tabs_location;if(\"above\"==i||\"below\"==i){const e=-(0,r.sum)(s.map((e=>e.width)));this.headers_el.style.left=`${e}px`}else{const e=-(0,r.sum)(s.map((e=>e.height)));this.headers_el.style.top=`${e}px`}}change_active(e){e!=this.model.active&&(this.model.active=e)}on_active_change(){const e=this.model.active,t=(0,d.children)(this.headers_el);for(const e of t)e.classList.remove(m.active);t[e].classList.add(m.active);const{child_views:s}=this;for(const e of s)(0,d.hide)(e.el);(0,d.show)(s[e].el)}}s.TabsView=f,f.__name__=\"TabsView\";class x extends _.LayoutDOM{constructor(e){super(e)}}s.Tabs=x,a=x,x.__name__=\"Tabs\",a.prototype.default_view=f,a.define((({Int:e,Array:t,Ref:s})=>({tabs:[t(s(p.Panel)),[]],tabs_location:[n.Location,\"above\"],active:[e,0]})))},\n", - " function _(e,r,b,o,t){o(),b.root=\"bk-root\",b.tabs_header=\"bk-tabs-header\",b.btn_group=\"bk-btn-group\",b.btn=\"bk-btn\",b.headers_wrapper=\"bk-headers-wrapper\",b.above=\"bk-above\",b.right=\"bk-right\",b.below=\"bk-below\",b.left=\"bk-left\",b.headers=\"bk-headers\",b.tab=\"bk-tab\",b.active=\"bk-active\",b.close=\"bk-close\",b.disabled=\"bk-disabled\",b.default='.bk-root .bk-tabs-header{display:flex;flex-wrap:nowrap;align-items:center;overflow:hidden;user-select:none;-ms-user-select:none;-moz-user-select:none;-webkit-user-select:none;}.bk-root .bk-tabs-header .bk-btn-group{height:auto;margin-right:5px;}.bk-root .bk-tabs-header .bk-btn-group > .bk-btn{flex-grow:0;height:auto;padding:4px 4px;}.bk-root .bk-tabs-header .bk-headers-wrapper{flex-grow:1;overflow:hidden;color:#666666;}.bk-root .bk-tabs-header.bk-above .bk-headers-wrapper{border-bottom:1px solid #e6e6e6;}.bk-root .bk-tabs-header.bk-right .bk-headers-wrapper{border-left:1px solid #e6e6e6;}.bk-root .bk-tabs-header.bk-below .bk-headers-wrapper{border-top:1px solid #e6e6e6;}.bk-root .bk-tabs-header.bk-left .bk-headers-wrapper{border-right:1px solid #e6e6e6;}.bk-root .bk-tabs-header.bk-above,.bk-root .bk-tabs-header.bk-below{flex-direction:row;}.bk-root .bk-tabs-header.bk-above .bk-headers,.bk-root .bk-tabs-header.bk-below .bk-headers{flex-direction:row;}.bk-root .bk-tabs-header.bk-left,.bk-root .bk-tabs-header.bk-right{flex-direction:column;}.bk-root .bk-tabs-header.bk-left .bk-headers,.bk-root .bk-tabs-header.bk-right .bk-headers{flex-direction:column;}.bk-root .bk-tabs-header .bk-headers{position:relative;display:flex;flex-wrap:nowrap;align-items:center;}.bk-root .bk-tabs-header .bk-tab{padding:4px 8px;border:solid transparent;white-space:nowrap;cursor:pointer;}.bk-root .bk-tabs-header .bk-tab:hover{background-color:#f2f2f2;}.bk-root .bk-tabs-header .bk-tab.bk-active{color:#4d4d4d;background-color:white;border-color:#e6e6e6;}.bk-root .bk-tabs-header .bk-tab .bk-close{margin-left:10px;}.bk-root .bk-tabs-header .bk-tab.bk-disabled{cursor:not-allowed;pointer-events:none;opacity:0.65;}.bk-root .bk-tabs-header.bk-above .bk-tab{border-width:3px 1px 0px 1px;border-radius:4px 4px 0 0;}.bk-root .bk-tabs-header.bk-right .bk-tab{border-width:1px 3px 1px 0px;border-radius:0 4px 4px 0;}.bk-root .bk-tabs-header.bk-below .bk-tab{border-width:0px 1px 3px 1px;border-radius:0 0 4px 4px;}.bk-root .bk-tabs-header.bk-left .bk-tab{border-width:1px 0px 1px 3px;border-radius:4px 0 0 4px;}.bk-root .bk-close{display:inline-block;width:10px;height:10px;vertical-align:middle;background-image:url(\\'data:image/svg+xml;utf8, \\');}.bk-root .bk-close:hover{background-image:url(\\'data:image/svg+xml;utf8, \\');}'},\n", - " function _(o,b,r,t,e){t(),r.root=\"bk-root\",r.btn=\"bk-btn\",r.active=\"bk-active\",r.btn_default=\"bk-btn-default\",r.btn_primary=\"bk-btn-primary\",r.btn_success=\"bk-btn-success\",r.btn_warning=\"bk-btn-warning\",r.btn_danger=\"bk-btn-danger\",r.btn_light=\"bk-btn-light\",r.btn_group=\"bk-btn-group\",r.vertical=\"bk-vertical\",r.horizontal=\"bk-horizontal\",r.dropdown_toggle=\"bk-dropdown-toggle\",r.default=\".bk-root .bk-btn{height:100%;display:inline-block;text-align:center;vertical-align:middle;white-space:nowrap;cursor:pointer;padding:6px 12px;font-size:12px;border:1px solid transparent;border-radius:4px;outline:0;user-select:none;-ms-user-select:none;-moz-user-select:none;-webkit-user-select:none;}.bk-root .bk-btn:hover,.bk-root .bk-btn:focus{text-decoration:none;}.bk-root .bk-btn:active,.bk-root .bk-btn.bk-active{background-image:none;box-shadow:inset 0 3px 5px rgba(0, 0, 0, 0.125);}.bk-root .bk-btn[disabled]{cursor:not-allowed;pointer-events:none;opacity:0.65;box-shadow:none;}.bk-root .bk-btn-default{color:#333;background-color:#fff;border-color:#ccc;}.bk-root .bk-btn-default:hover{background-color:#f5f5f5;border-color:#b8b8b8;}.bk-root .bk-btn-default.bk-active{background-color:#ebebeb;border-color:#adadad;}.bk-root .bk-btn-default[disabled],.bk-root .bk-btn-default[disabled]:hover,.bk-root .bk-btn-default[disabled]:focus,.bk-root .bk-btn-default[disabled]:active,.bk-root .bk-btn-default[disabled].bk-active{background-color:#e6e6e6;border-color:#ccc;}.bk-root .bk-btn-primary{color:#fff;background-color:#428bca;border-color:#357ebd;}.bk-root .bk-btn-primary:hover{background-color:#3681c1;border-color:#2c699e;}.bk-root .bk-btn-primary.bk-active{background-color:#3276b1;border-color:#285e8e;}.bk-root .bk-btn-primary[disabled],.bk-root .bk-btn-primary[disabled]:hover,.bk-root .bk-btn-primary[disabled]:focus,.bk-root .bk-btn-primary[disabled]:active,.bk-root .bk-btn-primary[disabled].bk-active{background-color:#506f89;border-color:#357ebd;}.bk-root .bk-btn-success{color:#fff;background-color:#5cb85c;border-color:#4cae4c;}.bk-root .bk-btn-success:hover{background-color:#4eb24e;border-color:#409240;}.bk-root .bk-btn-success.bk-active{background-color:#47a447;border-color:#398439;}.bk-root .bk-btn-success[disabled],.bk-root .bk-btn-success[disabled]:hover,.bk-root .bk-btn-success[disabled]:focus,.bk-root .bk-btn-success[disabled]:active,.bk-root .bk-btn-success[disabled].bk-active{background-color:#667b66;border-color:#4cae4c;}.bk-root .bk-btn-warning{color:#fff;background-color:#f0ad4e;border-color:#eea236;}.bk-root .bk-btn-warning:hover{background-color:#eea43b;border-color:#e89014;}.bk-root .bk-btn-warning.bk-active{background-color:#ed9c28;border-color:#d58512;}.bk-root .bk-btn-warning[disabled],.bk-root .bk-btn-warning[disabled]:hover,.bk-root .bk-btn-warning[disabled]:focus,.bk-root .bk-btn-warning[disabled]:active,.bk-root .bk-btn-warning[disabled].bk-active{background-color:#c89143;border-color:#eea236;}.bk-root .bk-btn-danger{color:#fff;background-color:#d9534f;border-color:#d43f3a;}.bk-root .bk-btn-danger:hover{background-color:#d5433e;border-color:#bd2d29;}.bk-root .bk-btn-danger.bk-active{background-color:#d2322d;border-color:#ac2925;}.bk-root .bk-btn-danger[disabled],.bk-root .bk-btn-danger[disabled]:hover,.bk-root .bk-btn-danger[disabled]:focus,.bk-root .bk-btn-danger[disabled]:active,.bk-root .bk-btn-danger[disabled].bk-active{background-color:#a55350;border-color:#d43f3a;}.bk-root .bk-btn-light{color:#333;background-color:#fff;border-color:#ccc;border-color:transparent;}.bk-root .bk-btn-light:hover{background-color:#f5f5f5;border-color:#b8b8b8;}.bk-root .bk-btn-light.bk-active{background-color:#ebebeb;border-color:#adadad;}.bk-root .bk-btn-light[disabled],.bk-root .bk-btn-light[disabled]:hover,.bk-root .bk-btn-light[disabled]:focus,.bk-root .bk-btn-light[disabled]:active,.bk-root .bk-btn-light[disabled].bk-active{background-color:#e6e6e6;border-color:#ccc;}.bk-root .bk-btn-group{height:100%;display:flex;flex-wrap:nowrap;align-items:center;}.bk-root .bk-btn-group:not(.bk-vertical),.bk-root .bk-btn-group.bk-horizontal{flex-direction:row;}.bk-root .bk-btn-group.bk-vertical{flex-direction:column;}.bk-root .bk-btn-group > .bk-btn{flex-grow:1;}.bk-root .bk-btn-group:not(.bk-vertical) > .bk-btn + .bk-btn{margin-left:-1px;}.bk-root .bk-btn-group.bk-vertical > .bk-btn + .bk-btn{margin-top:-1px;}.bk-root .bk-btn-group:not(.bk-vertical) > .bk-btn:first-child:not(:last-child){border-bottom-right-radius:0;border-top-right-radius:0;}.bk-root .bk-btn-group.bk-vertical > 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T=t(135);M(\"MathText\",T.MathText),M(\"Ascii\",T.Ascii),M(\"MathML\",T.MathML),M(\"TeX\",T.TeX),M(\"PlainText\",t(139).PlainText)},\n", - " function _(r,o,t,e,n){e(),n(\"CustomJSTransform\",r(322).CustomJSTransform),n(\"Dodge\",r(323).Dodge),n(\"Interpolator\",r(325).Interpolator),n(\"Jitter\",r(326).Jitter),n(\"LinearInterpolator\",r(327).LinearInterpolator),n(\"StepInterpolator\",r(328).StepInterpolator),n(\"Transform\",r(56).Transform)},\n", - " function _(r,t,s,n,e){var a;n();const u=r(56),o=r(13),m=r(34);class _ extends u.Transform{constructor(r){super(r)}get names(){return(0,o.keys)(this.args)}get values(){return(0,o.values)(this.args)}_make_transform(r,t){return new Function(...this.names,r,(0,m.use_strict)(t))}get scalar_transform(){return this._make_transform(\"x\",this.func)}get vector_transform(){return this._make_transform(\"xs\",this.v_func)}compute(r){return this.scalar_transform(...this.values,r)}v_compute(r){return this.vector_transform(...this.values,r)}}s.CustomJSTransform=_,a=_,_.__name__=\"CustomJSTransform\",a.define((({Unknown:r,String:t,Dict:s})=>({args:[s(r),{}],func:[t,\"\"],v_func:[t,\"\"]})))},\n", - " function _(e,n,r,o,s){var t;o();const u=e(324);class a extends u.RangeTransform{constructor(e){super(e)}_compute(e){return e+this.value}}r.Dodge=a,t=a,a.__name__=\"Dodge\",t.define((({Number:e})=>({value:[e,0]})))},\n", - " function _(e,n,t,r,a){var s;r();const c=e(56),o=e(57),i=e(67),u=e(24),h=e(8),l=e(11);class g extends c.Transform{constructor(e){super(e)}v_compute(e){let n;this.range instanceof i.FactorRange?n=this.range.v_synthetic(e):(0,h.isArrayableOf)(e,h.isNumber)?n=e:(0,l.unreachable)();const t=new((0,u.infer_type)(n))(n.length);for(let e=0;e({range:[n(e(o.Range)),null]})))},\n", - " function _(t,e,r,n,s){var o;n();const i=t(56),a=t(70),h=t(24),l=t(9),d=t(8);class c extends i.Transform{constructor(t){super(t),this._sorted_dirty=!0}connect_signals(){super.connect_signals(),this.connect(this.change,(()=>this._sorted_dirty=!0))}v_compute(t){const e=new((0,h.infer_type)(t))(t.length);for(let r=0;ro*(e[t]-e[r]))),this._x_sorted=new((0,h.infer_type)(e))(n),this._y_sorted=new((0,h.infer_type)(r))(n);for(let t=0;t({x:[o(r,s(e))],y:[o(r,s(e))],data:[i(n(a.ColumnarDataSource)),null],clip:[t,!0]})))},\n", - " function _(t,s,e,i,r){i();const n=t(1);var o;const a=t(324),u=t(67),h=t(20),c=t(8),m=t(12),f=(0,n.__importStar)(t(10)),_=t(11);class p extends a.RangeTransform{constructor(t){super(t)}v_compute(t){var s;let e;this.range instanceof u.FactorRange?e=this.range.v_synthetic(t):(0,c.isArrayableOf)(t,c.isNumber)?e=t:(0,_.unreachable)();const i=e.length;(null===(s=this.previous_offsets)||void 0===s?void 0:s.length)!=i&&(this.previous_offsets=new Array(i),this.previous_offsets=(0,m.map)(this.previous_offsets,(()=>this._compute())));const 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A.ColumnDataSource,r={}){const n=new D.GlyphRenderer(Object.assign(Object.assign({},r),{data_source:t,glyph:e}));return this.add_renderers(n),n}add_tools(...e){this.toolbar.tools=this.toolbar.tools.concat(e)}get panels(){return[...this.side_panels,...this.center]}get side_panels(){const{above:e,below:t,left:r,right:n}=this;return(0,h.concat)([e,t,r,n])}}r.Plot=k,a=k,k.__name__=\"Plot\",a.prototype.default_view=P.PlotView,a.mixins([[\"outline_\",s.Line],[\"background_\",s.Fill],[\"border_\",s.Fill]]),a.define((({Boolean:e,Number:t,String:r,Array:n,Dict:i,Or:o,Ref:a,Null:s,Nullable:_})=>({toolbar:[a(m.Toolbar),()=>new m.Toolbar],toolbar_location:[_(c.Location),\"right\"],toolbar_sticky:[e,!0],plot_width:[l.Alias(\"width\")],plot_height:[l.Alias(\"height\")],frame_width:[_(t),null],frame_height:[_(t),null],title:[o(a(w.Title),r,s),\"\",{convert:e=>(0,u.isString)(e)?new w.Title({text:e}):e}],title_location:[_(c.Location),\"above\"],above:[n(o(a(b.Annotation),a(p.Axis))),[]],below:[n(o(a(b.Annotation),a(p.Axis))),[]],left:[n(o(a(b.Annotation),a(p.Axis))),[]],right:[n(o(a(b.Annotation),a(p.Axis))),[]],center:[n(o(a(b.Annotation),a(f.Grid))),[]],renderers:[n(a(S.Renderer)),[]],x_range:[a(x.Range),()=>new L.DataRange1d],y_range:[a(x.Range),()=>new L.DataRange1d],x_scale:[a(v.Scale),()=>new y.LinearScale],y_scale:[a(v.Scale),()=>new y.LinearScale],extra_x_ranges:[i(a(x.Range)),{}],extra_y_ranges:[i(a(x.Range)),{}],extra_x_scales:[i(a(v.Scale)),{}],extra_y_scales:[i(a(v.Scale)),{}],lod_factor:[t,10],lod_interval:[t,300],lod_threshold:[_(t),2e3],lod_timeout:[t,500],hidpi:[e,!0],output_backend:[c.OutputBackend,\"canvas\"],min_border:[_(t),5],min_border_top:[_(t),null],min_border_left:[_(t),null],min_border_bottom:[_(t),null],min_border_right:[_(t),null],inner_width:[t,0],inner_height:[t,0],outer_width:[t,0],outer_height:[t,0],match_aspect:[e,!1],aspect_scale:[t,1],reset_policy:[c.ResetPolicy,\"standard\"]}))),a.override({width:600,height:600,outline_line_color:\"#e5e5e5\",border_fill_color:\"#ffffff\",background_fill_color:\"#ffffff\"})},\n", - " function _(e,t,i,s,a){s();const n=e(1),o=e(126),l=e(249),r=e(309),_=e(40),h=e(118),d=e(128),u=e(220),c=e(251),p=e(113),v=e(45),g=e(19),b=e(251),m=e(333),y=e(8),w=e(9),f=e(235),x=e(208),z=e(211),k=e(209),q=e(123),M=e(65),R=e(334),V=e(335),S=e(28);class O extends r.LayoutDOMView{constructor(){super(...arguments),this._outer_bbox=new M.BBox,this._inner_bbox=new M.BBox,this._needs_paint=!0,this._needs_layout=!1,this._invalidated_painters=new Set,this._invalidate_all=!0,this._needs_notify=!1}get canvas(){return this.canvas_view}get state(){return this._state_manager}set invalidate_dataranges(e){this._range_manager.invalidate_dataranges=e}renderer_view(e){const t=this.renderer_views.get(e);if(null==t)for(const[,t]of this.renderer_views){const i=t.renderer_view(e);if(null!=i)return i}return t}get is_paused(){return null!=this._is_paused&&0!==this._is_paused}get child_models(){return[]}pause(){null==this._is_paused?this._is_paused=1:this._is_paused+=1}unpause(e=!1){if(null==this._is_paused)throw new Error(\"wasn't paused\");this._is_paused-=1,0!=this._is_paused||e||this.request_paint(\"everything\")}notify_finished_after_paint(){this._needs_notify=!0}request_render(){this.request_paint(\"everything\")}request_paint(e){this.invalidate_painters(e),this.schedule_paint()}invalidate_painters(e){if(\"everything\"==e)this._invalidate_all=!0;else if((0,y.isArray)(e))for(const t of e)this._invalidated_painters.add(t);else this._invalidated_painters.add(e)}schedule_paint(){if(!this.is_paused){const e=this.throttled_paint();this._ready=this._ready.then((()=>e))}}request_layout(){this._needs_layout=!0,this.request_paint(\"everything\")}reset(){\"standard\"==this.model.reset_policy&&(this.state.clear(),this.reset_range(),this.reset_selection()),this.model.trigger_event(new c.Reset)}remove(){(0,p.remove_views)(this.renderer_views),(0,p.remove_views)(this.tool_views),this.canvas_view.remove(),super.remove()}render(){super.render(),this.el.appendChild(this.canvas_view.el),this.canvas_view.render()}initialize(){this.pause(),super.initialize(),this.lod_started=!1,this.visuals=new v.Visuals(this),this._initial_state={selection:new Map,dimensions:{width:0,height:0}},this.visibility_callbacks=[],this.renderer_views=new Map,this.tool_views=new Map,this.frame=new o.CartesianFrame(this.model.x_scale,this.model.y_scale,this.model.x_range,this.model.y_range,this.model.extra_x_ranges,this.model.extra_y_ranges,this.model.extra_x_scales,this.model.extra_y_scales),this._range_manager=new R.RangeManager(this),this._state_manager=new V.StateManager(this,this._initial_state),this.throttled_paint=(0,m.throttle)((()=>this.repaint()),1e3/60);const{title_location:e,title:t}=this.model;null!=e&&null!=t&&(this._title=t instanceof h.Title?t:new h.Title({text:t}));const{toolbar_location:i,toolbar:s}=this.model;null!=i&&null!=s&&(this._toolbar=new u.ToolbarPanel({toolbar:s}),s.toolbar_location=i)}async lazy_initialize(){await super.lazy_initialize();const{hidpi:e,output_backend:t}=this.model,i=new l.Canvas({hidpi:e,output_backend:t});this.canvas_view=await(0,p.build_view)(i,{parent:this}),this.canvas_view.plot_views=[this],await this.build_renderer_views(),await this.build_tool_views(),this._range_manager.update_dataranges(),this.unpause(!0),g.logger.debug(\"PlotView initialized\")}_width_policy(){return null==this.model.frame_width?super._width_policy():\"min\"}_height_policy(){return null==this.model.frame_height?super._height_policy():\"min\"}_update_layout(){var e,t,i,s,a;this.layout=new z.BorderLayout,this.layout.set_sizing(this.box_sizing());const n=(0,w.copy)(this.model.above),o=(0,w.copy)(this.model.below),l=(0,w.copy)(this.model.left),r=(0,w.copy)(this.model.right),d=e=>{switch(e){case\"above\":return n;case\"below\":return o;case\"left\":return l;case\"right\":return r}},{title_location:c,title:p}=this.model;null!=c&&null!=p&&d(c).push(this._title);const{toolbar_location:v,toolbar:g}=this.model;if(null!=v&&null!=g){const e=d(v);let t=!0;if(this.model.toolbar_sticky)for(let i=0;i{var i;const s=this.renderer_view(t);return s.panel=new q.Panel(e),null===(i=s.update_layout)||void 0===i||i.call(s),s.layout},m=(e,t)=>{const i=\"above\"==e||\"below\"==e,s=[];for(const a of t)if((0,y.isArray)(a)){const t=a.map((t=>{const s=b(e,t);if(t instanceof u.ToolbarPanel){const e=i?\"width_policy\":\"height_policy\";s.set_sizing(Object.assign(Object.assign({},s.sizing),{[e]:\"min\"}))}return s}));let n;i?(n=new k.Row(t),n.set_sizing({width_policy:\"max\",height_policy:\"min\"})):(n=new k.Column(t),n.set_sizing({width_policy:\"min\",height_policy:\"max\"})),n.absolute=!0,s.push(n)}else s.push(b(e,a));return s},f=null!==(e=this.model.min_border)&&void 0!==e?e:0;this.layout.min_border={left:null!==(t=this.model.min_border_left)&&void 0!==t?t:f,top:null!==(i=this.model.min_border_top)&&void 0!==i?i:f,right:null!==(s=this.model.min_border_right)&&void 0!==s?s:f,bottom:null!==(a=this.model.min_border_bottom)&&void 0!==a?a:f};const M=new x.NodeLayout,R=new x.VStack,V=new x.VStack,S=new x.HStack,O=new x.HStack;M.absolute=!0,R.absolute=!0,V.absolute=!0,S.absolute=!0,O.absolute=!0,M.children=this.model.center.filter((e=>e instanceof _.Annotation)).map((e=>{var t;const i=this.renderer_view(e);return null===(t=i.update_layout)||void 0===t||t.call(i),i.layout})).filter((e=>null!=e));const{frame_width:P,frame_height:j}=this.model;M.set_sizing(Object.assign(Object.assign({},null!=P?{width_policy:\"fixed\",width:P}:{width_policy:\"fit\"}),null!=j?{height_policy:\"fixed\",height:j}:{height_policy:\"fit\"})),M.on_resize((e=>this.frame.set_geometry(e))),R.children=(0,w.reversed)(m(\"above\",n)),V.children=m(\"below\",o),S.children=(0,w.reversed)(m(\"left\",l)),O.children=m(\"right\",r),R.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),V.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),S.set_sizing({width_policy:\"min\",height_policy:\"fit\"}),O.set_sizing({width_policy:\"min\",height_policy:\"fit\"}),this.layout.center_panel=M,this.layout.top_panel=R,this.layout.bottom_panel=V,this.layout.left_panel=S,this.layout.right_panel=O}get axis_views(){const e=[];for(const[,t]of this.renderer_views)t instanceof d.AxisView&&e.push(t);return e}set_toolbar_visibility(e){for(const t of this.visibility_callbacks)t(e)}update_range(e,t){this.pause(),this._range_manager.update(e,t),this.unpause()}reset_range(){this.update_range(null),this.trigger_ranges_update_event()}trigger_ranges_update_event(){const{x_range:e,y_range:t}=this.model;this.model.trigger_event(new b.RangesUpdate(e.start,e.end,t.start,t.end))}get_selection(){const e=new Map;for(const t of this.model.data_renderers){const{selected:i}=t.selection_manager.source;e.set(t,i)}return e}update_selection(e){for(const t of this.model.data_renderers){const i=t.selection_manager.source;if(null!=e){const s=e.get(t);null!=s&&i.selected.update(s,!0)}else i.selection_manager.clear()}}reset_selection(){this.update_selection(null)}_invalidate_layout(){(()=>{var e;for(const t of this.model.side_panels){const i=this.renderer_views.get(t);if(null===(e=i.layout)||void 0===e?void 0:e.has_size_changed())return this.invalidate_painters(i),!0}return!1})()&&this.root.compute_layout()}get_renderer_views(){return this.computed_renderers.map((e=>this.renderer_views.get(e)))}*_compute_renderers(){const{above:e,below:t,left:i,right:s,center:a,renderers:n}=this.model;yield*n,yield*e,yield*t,yield*i,yield*s,yield*a,null!=this._title&&(yield this._title),null!=this._toolbar&&(yield this._toolbar);for(const e of this.model.toolbar.tools)null!=e.overlay&&(yield e.overlay),yield*e.synthetic_renderers}async build_renderer_views(){this.computed_renderers=[...this._compute_renderers()],await(0,p.build_views)(this.renderer_views,this.computed_renderers,{parent:this})}async build_tool_views(){const e=this.model.toolbar.tools;(await(0,p.build_views)(this.tool_views,e,{parent:this})).map((e=>this.canvas_view.ui_event_bus.register_tool(e)))}connect_signals(){super.connect_signals();const{x_ranges:e,y_ranges:t}=this.frame;for(const[,t]of e)this.connect(t.change,(()=>{this._needs_layout=!0,this.request_paint(\"everything\")}));for(const[,e]of t)this.connect(e.change,(()=>{this._needs_layout=!0,this.request_paint(\"everything\")}));const{above:i,below:s,left:a,right:n,center:o,renderers:l}=this.model.properties;this.on_change([i,s,a,n,o,l],(async()=>await this.build_renderer_views())),this.connect(this.model.toolbar.properties.tools.change,(async()=>{await this.build_renderer_views(),await this.build_tool_views()})),this.connect(this.model.change,(()=>this.request_paint(\"everything\"))),this.connect(this.model.reset,(()=>this.reset()))}has_finished(){if(!super.has_finished())return!1;if(this.model.visible)for(const[,e]of this.renderer_views)if(!e.has_finished())return!1;return!0}after_layout(){var e;super.after_layout();for(const[,t]of this.renderer_views)t instanceof _.AnnotationView&&(null===(e=t.after_layout)||void 0===e||e.call(t));if(this._needs_layout=!1,this.model.setv({inner_width:Math.round(this.frame.bbox.width),inner_height:Math.round(this.frame.bbox.height),outer_width:Math.round(this.layout.bbox.width),outer_height:Math.round(this.layout.bbox.height)},{no_change:!0}),!1!==this.model.match_aspect&&(this.pause(),this._range_manager.update_dataranges(),this.unpause(!0)),!this._outer_bbox.equals(this.layout.bbox)){const{width:e,height:t}=this.layout.bbox;this.canvas_view.resize(e,t),this._outer_bbox=this.layout.bbox,this._invalidate_all=!0,this._needs_paint=!0}const{inner_bbox:t}=this.layout;this._inner_bbox.equals(t)||(this._inner_bbox=t,this._needs_paint=!0),this._needs_paint&&this.paint()}repaint(){this._needs_layout&&this._invalidate_layout(),this.paint()}paint(){this.is_paused||(this.model.visible&&(g.logger.trace(`${this.toString()}.paint()`),this._actual_paint()),this._needs_notify&&(this._needs_notify=!1,this.notify_finished()))}_actual_paint(){var e;const{document:t}=this.model;if(null!=t){const e=t.interactive_duration();e>=0&&e{t.interactive_duration()>this.model.lod_timeout&&t.interactive_stop(),this.request_paint(\"everything\")}),this.model.lod_timeout):t.interactive_stop()}this._range_manager.invalidate_dataranges&&(this._range_manager.update_dataranges(),this._invalidate_layout());let i=!1,s=!1;if(this._invalidate_all)i=!0,s=!0;else for(const e of this._invalidated_painters){const{level:t}=e.model;if(\"overlay\"!=t?i=!0:s=!0,i&&s)break}this._invalidated_painters.clear(),this._invalidate_all=!1;const a=[this.frame.bbox.left,this.frame.bbox.top,this.frame.bbox.width,this.frame.bbox.height],{primary:n,overlays:o}=this.canvas_view;i&&(n.prepare(),this.canvas_view.prepare_webgl(a),this._map_hook(n.ctx,a),this._paint_empty(n.ctx,a),this._paint_outline(n.ctx,a),this._paint_levels(n.ctx,\"image\",a,!0),this._paint_levels(n.ctx,\"underlay\",a,!0),this._paint_levels(n.ctx,\"glyph\",a,!0),this._paint_levels(n.ctx,\"guide\",a,!1),this._paint_levels(n.ctx,\"annotation\",a,!1),n.finish()),(s||S.settings.wireframe)&&(o.prepare(),this._paint_levels(o.ctx,\"overlay\",a,!1),S.settings.wireframe&&this._paint_layout(o.ctx,this.layout),o.finish()),null==this._initial_state.range&&(this._initial_state.range=null!==(e=this._range_manager.compute_initial())&&void 0!==e?e:void 0),this._needs_paint=!1}_paint_levels(e,t,i,s){for(const a of this.computed_renderers){if(a.level!=t)continue;const n=this.renderer_views.get(a);e.save(),(s||n.needs_clip)&&(e.beginPath(),e.rect(...i),e.clip()),n.render(),e.restore(),n.has_webgl&&n.needs_webgl_blit&&this.canvas_view.blit_webgl(e)}}_paint_layout(e,t){const{x:i,y:s,width:a,height:n}=t.bbox;e.strokeStyle=\"blue\",e.strokeRect(i,s,a,n);for(const a of t)e.save(),t.absolute||e.translate(i,s),this._paint_layout(e,a),e.restore()}_map_hook(e,t){}_paint_empty(e,t){const[i,s,a,n]=[0,0,this.layout.bbox.width,this.layout.bbox.height],[o,l,r,_]=t;this.visuals.border_fill.doit&&(this.visuals.border_fill.set_value(e),e.fillRect(i,s,a,n),e.clearRect(o,l,r,_)),this.visuals.background_fill.doit&&(this.visuals.background_fill.set_value(e),e.fillRect(o,l,r,_))}_paint_outline(e,t){if(this.visuals.outline_line.doit){e.save(),this.visuals.outline_line.set_value(e);let[i,s,a,n]=t;i+a==this.layout.bbox.width&&(a-=1),s+n==this.layout.bbox.height&&(n-=1),e.strokeRect(i,s,a,n),e.restore()}}to_blob(){return this.canvas_view.to_blob()}export(e,t=!0){const i=\"png\"==e?\"canvas\":\"svg\",s=new f.CanvasLayer(i,t),{width:a,height:n}=this.layout.bbox;s.resize(a,n);const{canvas:o}=this.canvas_view.compose();return s.ctx.drawImage(o,0,0),s}serializable_state(){const e=super.serializable_state(),{children:t}=e,i=(0,n.__rest)(e,[\"children\"]),s=this.get_renderer_views().map((e=>e.serializable_state())).filter((e=>null!=e.bbox));return Object.assign(Object.assign({},i),{children:[...null!=t?t:[],...s]})}}i.PlotView=O,O.__name__=\"PlotView\"},\n", - " function _(t,n,e,o,u){o(),e.throttle=function(t,n){let e=null,o=0,u=!1;return function(){return new Promise(((r,i)=>{const l=function(){o=Date.now(),e=null,u=!1;try{t(),r()}catch(t){i(t)}},a=Date.now(),c=n-(a-o);c<=0&&!u?(null!=e&&clearTimeout(e),u=!0,requestAnimationFrame(l)):e||u?r():e=setTimeout((()=>requestAnimationFrame(l)),c)}))}}},\n", - " function _(t,n,e,a,s){a();const o=t(63),r=t(19);class l{constructor(t){this.parent=t,this.invalidate_dataranges=!0}get frame(){return this.parent.frame}update(t,n){const{x_ranges:e,y_ranges:a}=this.frame;if(null==t){for(const[,t]of e)t.reset();for(const[,t]of a)t.reset();this.update_dataranges()}else{const s=[];for(const[n,a]of e)s.push([a,t.xrs.get(n)]);for(const[n,e]of a)s.push([e,t.yrs.get(n)]);(null==n?void 0:n.scrolling)&&this._update_ranges_together(s),this._update_ranges_individually(s,n)}}reset(){this.update(null)}_update_dataranges(t){const n=new Map,e=new Map;let a=!1;for(const[,n]of t.x_ranges)n instanceof o.DataRange1d&&\"log\"==n.scale_hint&&(a=!0);for(const[,n]of t.y_ranges)n instanceof o.DataRange1d&&\"log\"==n.scale_hint&&(a=!0);for(const t of this.parent.model.data_renderers){const s=this.parent.renderer_view(t);if(null==s)continue;const o=s.glyph_view.bounds();if(null!=o&&n.set(t,o),a){const n=s.glyph_view.log_bounds();null!=n&&e.set(t,n)}}let s=!1,l=!1;const i=t.x_target.span,d=t.y_target.span;let u;!1!==this.parent.model.match_aspect&&0!=i&&0!=d&&(u=1/this.parent.model.aspect_scale*(i/d));for(const[,a]of t.x_ranges){if(a instanceof o.DataRange1d){const t=\"log\"==a.scale_hint?e:n;a.update(t,0,this.parent.model,u),a.follow&&(s=!0)}null!=a.bounds&&(l=!0)}for(const[,a]of t.y_ranges){if(a instanceof o.DataRange1d){const t=\"log\"==a.scale_hint?e:n;a.update(t,1,this.parent.model,u),a.follow&&(s=!0)}null!=a.bounds&&(l=!0)}if(s&&l){r.logger.warn(\"Follow enabled so bounds are unset.\");for(const[,n]of t.x_ranges)n.bounds=null;for(const[,n]of t.y_ranges)n.bounds=null}}update_dataranges(){this._update_dataranges(this.frame);for(const t of this.parent.model.renderers){const{coordinates:n}=t;null!=n&&this._update_dataranges(n)}null!=this.compute_initial()&&(this.invalidate_dataranges=!1)}compute_initial(){let t=!0;const{x_ranges:n,y_ranges:e}=this.frame,a=new Map,s=new Map;for(const[e,s]of n){const{start:n,end:o}=s;if(null==n||null==o||isNaN(n+o)){t=!1;break}a.set(e,{start:n,end:o})}if(t)for(const[n,a]of e){const{start:e,end:o}=a;if(null==e||null==o||isNaN(e+o)){t=!1;break}s.set(n,{start:e,end:o})}return t?{xrs:a,yrs:s}:(r.logger.warn(\"could not set initial ranges\"),null)}_update_ranges_together(t){let n=1;for(const[e,a]of t)n=Math.min(n,this._get_weight_to_constrain_interval(e,a));if(n<1)for(const[e,a]of t)a.start=n*a.start+(1-n)*e.start,a.end=n*a.end+(1-n)*e.end}_update_ranges_individually(t,n){const e=!!(null==n?void 0:n.panning),a=!!(null==n?void 0:n.scrolling);let s=!1;for(const[n,o]of t){if(!a){const t=this._get_weight_to_constrain_interval(n,o);t<1&&(o.start=t*o.start+(1-t)*n.start,o.end=t*o.end+(1-t)*n.end)}if(null!=n.bounds&&\"auto\"!=n.bounds){const[t,r]=n.bounds,l=Math.abs(o.end-o.start);n.is_reversed?(null!=t&&t>=o.end&&(s=!0,o.end=t,(e||a)&&(o.start=t+l)),null!=r&&r<=o.start&&(s=!0,o.start=r,(e||a)&&(o.end=r-l))):(null!=t&&t>=o.start&&(s=!0,o.start=t,(e||a)&&(o.end=t+l)),null!=r&&r<=o.end&&(s=!0,o.end=r,(e||a)&&(o.start=r-l)))}}if(!(a&&s&&(null==n?void 0:n.maintain_focus)))for(const[n,e]of t)n.have_updated_interactively=!0,n.start==e.start&&n.end==e.end||n.setv(e)}_get_weight_to_constrain_interval(t,n){const{min_interval:e}=t;let{max_interval:a}=t;if(null!=t.bounds&&\"auto\"!=t.bounds){const[n,e]=t.bounds;if(null!=n&&null!=e){const t=Math.abs(e-n);a=null!=a?Math.min(a,t):t}}let s=1;if(null!=e||null!=a){const o=Math.abs(t.end-t.start),r=Math.abs(n.end-n.start);null!=e&&e>0&&r0&&r>a&&(s=(a-o)/(r-o)),s=Math.max(0,Math.min(1,s))}return s}}e.RangeManager=l,l.__name__=\"RangeManager\"},\n", - " function _(t,i,s,e,n){e();const h=t(15);class a{constructor(t,i){this.parent=t,this.initial_state=i,this.changed=new h.Signal0(this.parent,\"state_changed\"),this.history=[],this.index=-1}_do_state_change(t){const i=null!=this.history[t]?this.history[t].state:this.initial_state;return null!=i.range&&this.parent.update_range(i.range),null!=i.selection&&this.parent.update_selection(i.selection),i}push(t,i){const{history:s,index:e}=this,n=null!=s[e]?s[e].state:{},h=Object.assign(Object.assign(Object.assign({},this.initial_state),n),i);this.history=this.history.slice(0,this.index+1),this.history.push({type:t,state:h}),this.index=this.history.length-1,this.changed.emit()}clear(){this.history=[],this.index=-1,this.changed.emit()}undo(){if(this.can_undo){this.index-=1;const t=this._do_state_change(this.index);return this.changed.emit(),t}return null}redo(){if(this.can_redo){this.index+=1;const t=this._do_state_change(this.index);return this.changed.emit(),t}return null}get can_undo(){return this.index>=0}get can_redo(){return this.indexm.emit();const s=encodeURIComponent,o=document.createElement(\"script\");o.type=\"text/javascript\",o.src=`https://maps.googleapis.com/maps/api/js?v=${s(e)}&key=${s(t)}&callback=_bokeh_gmaps_callback`,document.body.appendChild(o)}(t,e)}m.connect((()=>this.request_paint(\"everything\")))}this.unpause()}remove(){(0,p.remove)(this.map_el),super.remove()}update_range(t,e){var s,o;if(null==t)this.map.setCenter({lat:this.initial_lat,lng:this.initial_lng}),this.map.setOptions({zoom:this.initial_zoom}),super.update_range(null,e);else if(null!=t.sdx||null!=t.sdy)this.map.panBy(null!==(s=t.sdx)&&void 0!==s?s:0,null!==(o=t.sdy)&&void 0!==o?o:0),super.update_range(t,e);else if(null!=t.factor){if(10!==this.zoom_count)return void(this.zoom_count+=1);this.zoom_count=0,this.pause(),super.update_range(t,e);const s=t.factor<0?-1:1,o=this.map.getZoom();if(null!=o){const t=o+s;if(t>=2){this.map.setZoom(t);const[e,s]=this._get_projected_bounds();s-e<0&&this.map.setZoom(o)}}this.unpause()}this._set_bokeh_ranges()}_build_map(){const{maps:t}=google;this.map_types={satellite:t.MapTypeId.SATELLITE,terrain:t.MapTypeId.TERRAIN,roadmap:t.MapTypeId.ROADMAP,hybrid:t.MapTypeId.HYBRID};const e=this.model.map_options,s={center:new t.LatLng(e.lat,e.lng),zoom:e.zoom,disableDefaultUI:!0,mapTypeId:this.map_types[e.map_type],scaleControl:e.scale_control,tilt:e.tilt};null!=e.styles&&(s.styles=JSON.parse(e.styles)),this.map_el=(0,p.div)({style:{position:\"absolute\"}}),this.canvas_view.add_underlay(this.map_el),this.map=new t.Map(this.map_el,s),t.event.addListener(this.map,\"idle\",(()=>this._set_bokeh_ranges())),t.event.addListener(this.map,\"bounds_changed\",(()=>this._set_bokeh_ranges())),t.event.addListenerOnce(this.map,\"tilesloaded\",(()=>this._render_finished())),this.connect(this.model.properties.map_options.change,(()=>this._update_options())),this.connect(this.model.map_options.properties.styles.change,(()=>this._update_styles())),this.connect(this.model.map_options.properties.lat.change,(()=>this._update_center(\"lat\"))),this.connect(this.model.map_options.properties.lng.change,(()=>this._update_center(\"lng\"))),this.connect(this.model.map_options.properties.zoom.change,(()=>this._update_zoom())),this.connect(this.model.map_options.properties.map_type.change,(()=>this._update_map_type())),this.connect(this.model.map_options.properties.scale_control.change,(()=>this._update_scale_control())),this.connect(this.model.map_options.properties.tilt.change,(()=>this._update_tilt()))}_render_finished(){this._tiles_loaded=!0,this.notify_finished()}has_finished(){return super.has_finished()&&!0===this._tiles_loaded}_get_latlon_bounds(){const t=this.map.getBounds(),e=t.getNorthEast(),s=t.getSouthWest();return[s.lng(),e.lng(),s.lat(),e.lat()]}_get_projected_bounds(){const[t,e,s,o]=this._get_latlon_bounds(),[i,a]=l.wgs84_mercator.compute(t,s),[n,p]=l.wgs84_mercator.compute(e,o);return[i,n,a,p]}_set_bokeh_ranges(){const[t,e,s,o]=this._get_projected_bounds();this.frame.x_range.setv({start:t,end:e}),this.frame.y_range.setv({start:s,end:o})}_update_center(t){var e;const s=null===(e=this.map.getCenter())||void 0===e?void 0:e.toJSON();null!=s&&(s[t]=this.model.map_options[t],this.map.setCenter(s),this._set_bokeh_ranges())}_update_map_type(){this.map.setOptions({mapTypeId:this.map_types[this.model.map_options.map_type]})}_update_scale_control(){this.map.setOptions({scaleControl:this.model.map_options.scale_control})}_update_tilt(){this.map.setOptions({tilt:this.model.map_options.tilt})}_update_options(){this._update_styles(),this._update_center(\"lat\"),this._update_center(\"lng\"),this._update_zoom(),this._update_map_type()}_update_styles(){this.map.setOptions({styles:JSON.parse(this.model.map_options.styles)})}_update_zoom(){this.map.setOptions({zoom:this.model.map_options.zoom}),this._set_bokeh_ranges()}_map_hook(t,e){if(null==this.map&&\"undefined\"!=typeof google&&null!=google.maps&&this._build_map(),null!=this.map_el){const[t,s,o,i]=e;this.map_el.style.top=`${s}px`,this.map_el.style.left=`${t}px`,this.map_el.style.width=`${o}px`,this.map_el.style.height=`${i}px`}}_paint_empty(t,e){const s=this.layout.bbox.width,o=this.layout.bbox.height,[i,a,n,p]=e;t.clearRect(0,0,s,o),t.beginPath(),t.moveTo(0,0),t.lineTo(0,o),t.lineTo(s,o),t.lineTo(s,0),t.lineTo(0,0),t.moveTo(i,a),t.lineTo(i+n,a),t.lineTo(i+n,a+p),t.lineTo(i,a+p),t.lineTo(i,a),t.closePath(),null!=this.model.border_fill_color&&(t.fillStyle=(0,_.color2css)(this.model.border_fill_color),t.fill())}}s.GMapPlotView=d,d.__name__=\"GMapPlotView\"},\n", - " function _(t,_,n,o,r){o();(0,t(1).__exportStar)(t(132),n)},\n", - " function _(e,r,d,n,R){n(),R(\"GlyphRenderer\",e(175).GlyphRenderer),R(\"GraphRenderer\",e(339).GraphRenderer),R(\"GuideRenderer\",e(129).GuideRenderer);var G=e(41);R(\"Renderer\",G.Renderer),R(\"RendererGroup\",G.RendererGroup)},\n", - " function _(e,r,i,n,t){var o;n();const s=e(176),d=e(175),a=e(303),p=e(302),l=e(113),_=e(178),h=e(283),y=e(286);class c extends s.DataRendererView{get glyph_view(){return this.node_view.glyph}async lazy_initialize(){await super.lazy_initialize(),this.apply_coordinates();const{parent:e}=this,{edge_renderer:r,node_renderer:i}=this.model;this.edge_view=await(0,l.build_view)(r,{parent:e}),this.node_view=await(0,l.build_view)(i,{parent:e})}connect_signals(){super.connect_signals(),this.connect(this.model.layout_provider.change,(()=>{this.apply_coordinates(),this.edge_view.set_data(),this.node_view.set_data(),this.request_render()}))}apply_coordinates(){const{edge_renderer:e,node_renderer:r}=this.model;if(!(e.glyph instanceof h.MultiLine||e.glyph instanceof y.Patches))throw new Error(`${this}.edge_renderer.glyph must be a MultiLine glyph`);if(!(r.glyph instanceof _.XYGlyph))throw new Error(`${this}.node_renderer.glyph must be a XYGlyph glyph`);const i=this.model.layout_provider.edge_coordinates,n=this.model.layout_provider.node_coordinates;e.glyph.properties.xs.internal=!0,e.glyph.properties.ys.internal=!0,r.glyph.properties.x.internal=!0,r.glyph.properties.y.internal=!0,e.glyph.xs={expr:i.x},e.glyph.ys={expr:i.y},r.glyph.x={expr:n.x},r.glyph.y={expr:n.y}}remove(){this.edge_view.remove(),this.node_view.remove(),super.remove()}_render(){this.edge_view.render(),this.node_view.render()}renderer_view(e){if(e instanceof d.GlyphRenderer){if(e==this.edge_view.model)return this.edge_view;if(e==this.node_view.model)return this.node_view}return super.renderer_view(e)}}i.GraphRendererView=c,c.__name__=\"GraphRendererView\";class g extends s.DataRenderer{constructor(e){super(e)}get_selection_manager(){return this.node_renderer.data_source.selection_manager}}i.GraphRenderer=g,o=g,g.__name__=\"GraphRenderer\",o.prototype.default_view=c,o.define((({Ref:e})=>({layout_provider:[e(a.LayoutProvider)],node_renderer:[e(d.GlyphRenderer)],edge_renderer:[e(d.GlyphRenderer)],selection_policy:[e(p.GraphHitTestPolicy),()=>new p.NodesOnly],inspection_policy:[e(p.GraphHitTestPolicy),()=>new p.NodesOnly]})))},\n", - " function _(e,t,n,o,c){o();(0,e(1).__exportStar)(e(74),n),c(\"Selection\",e(72).Selection)},\n", - " function _(a,e,S,o,r){o(),r(\"ServerSentDataSource\",a(342).ServerSentDataSource),r(\"AjaxDataSource\",a(344).AjaxDataSource),r(\"ColumnDataSource\",a(75).ColumnDataSource),r(\"ColumnarDataSource\",a(70).ColumnarDataSource),r(\"CDSView\",a(190).CDSView),r(\"DataSource\",a(71).DataSource),r(\"GeoJSONDataSource\",a(345).GeoJSONDataSource),r(\"WebDataSource\",a(343).WebDataSource)},\n", - " function _(e,t,i,a,s){a();const n=e(343);class r extends n.WebDataSource{constructor(e){super(e),this.initialized=!1}setup(){if(!this.initialized){this.initialized=!0;new EventSource(this.data_url).onmessage=e=>{var t;this.load_data(JSON.parse(e.data),this.mode,null!==(t=this.max_size)&&void 0!==t?t:void 0)}}}}i.ServerSentDataSource=r,r.__name__=\"ServerSentDataSource\"},\n", - " function _(e,t,a,n,r){var s;n();const l=e(75),o=e(20);class c extends l.ColumnDataSource{constructor(e){super(e)}get_column(e){const t=this.data[e];return null!=t?t:[]}get_length(){var e;return null!==(e=super.get_length())&&void 0!==e?e:0}initialize(){super.initialize(),this.setup()}load_data(e,t,a){const{adapter:n}=this;let r;switch(r=null!=n?n.execute(this,{response:e}):e,t){case\"replace\":this.data=r;break;case\"append\":{const e=this.data;for(const t of this.columns()){const n=Array.from(e[t]),s=Array.from(r[t]),l=n.concat(s);r[t]=null!=a?l.slice(-a):l}this.data=r;break}}}}a.WebDataSource=c,s=c,c.__name__=\"WebDataSource\",s.define((({Any:e,Int:t,String:a,Nullable:n})=>({max_size:[n(t),null],mode:[o.UpdateMode,\"replace\"],adapter:[n(e),null],data_url:[a]})))},\n", - " function _(t,e,i,s,a){var n;s();const r=t(343),o=t(20),l=t(19),d=t(13);class h extends r.WebDataSource{constructor(t){super(t),this.interval=null,this.initialized=!1}destroy(){null!=this.interval&&clearInterval(this.interval),super.destroy()}setup(){if(!this.initialized&&(this.initialized=!0,this.get_data(this.mode),null!=this.polling_interval)){const t=()=>this.get_data(this.mode,this.max_size,this.if_modified);this.interval=setInterval(t,this.polling_interval)}}get_data(t,e=null,i=!1){const s=this.prepare_request();s.addEventListener(\"load\",(()=>this.do_load(s,t,null!=e?e:void 0))),s.addEventListener(\"error\",(()=>this.do_error(s))),s.send()}prepare_request(){const t=new XMLHttpRequest;t.open(this.method,this.data_url,!0),t.withCredentials=!1,t.setRequestHeader(\"Content-Type\",this.content_type);const e=this.http_headers;for(const[i,s]of(0,d.entries)(e))t.setRequestHeader(i,s);return t}do_load(t,e,i){if(200===t.status){const s=JSON.parse(t.responseText);this.load_data(s,e,i)}}do_error(t){l.logger.error(`Failed to fetch JSON from ${this.data_url} with code ${t.status}`)}}i.AjaxDataSource=h,n=h,h.__name__=\"AjaxDataSource\",n.define((({Boolean:t,Int:e,String:i,Dict:s,Nullable:a})=>({polling_interval:[a(e),null],content_type:[i,\"application/json\"],http_headers:[s(i),{}],method:[o.HTTPMethod,\"POST\"],if_modified:[t,!1]})))},\n", - " function _(e,t,o,r,n){var s;r();const a=e(70),i=e(19),l=e(9),c=e(13);function _(e){return null!=e?e:NaN}const{hasOwnProperty:g}=Object.prototype;class u extends a.ColumnarDataSource{constructor(e){super(e)}initialize(){super.initialize(),this._update_data()}connect_signals(){super.connect_signals(),this.connect(this.properties.geojson.change,(()=>this._update_data()))}_update_data(){this.data=this.geojson_to_column_data()}_get_new_list_array(e){return(0,l.range)(0,e).map((e=>[]))}_get_new_nan_array(e){return(0,l.range)(0,e).map((e=>NaN))}_add_properties(e,t,o,r){var n;const s=null!==(n=e.properties)&&void 0!==n?n:{};for(const[e,n]of(0,c.entries)(s))g.call(t,e)||(t[e]=this._get_new_nan_array(r)),t[e][o]=_(n)}_add_geometry(e,t,o){function r(e,t){return e.concat([[NaN,NaN,NaN]]).concat(t)}switch(e.type){case\"Point\":{const[r,n,s]=e.coordinates;t.x[o]=r,t.y[o]=n,t.z[o]=_(s);break}case\"LineString\":{const{coordinates:r}=e;for(let e=0;e1&&i.logger.warn(\"Bokeh does not support Polygons with holes in, only exterior ring used.\");const r=e.coordinates[0];for(let e=0;e1&&i.logger.warn(\"Bokeh does not support Polygons with holes in, only exterior ring used.\"),n.push(t[0]);const s=n.reduce(r);for(let e=0;e({geojson:[e]}))),s.internal((({Dict:e,Arrayable:t})=>({data:[e(t),{}]})))},\n", - " function _(e,r,T,o,S){o(),S(\"BBoxTileSource\",e(347).BBoxTileSource),S(\"MercatorTileSource\",e(348).MercatorTileSource),S(\"QUADKEYTileSource\",e(351).QUADKEYTileSource),S(\"TileRenderer\",e(352).TileRenderer),S(\"TileSource\",e(349).TileSource),S(\"TMSTileSource\",e(355).TMSTileSource),S(\"WMTSTileSource\",e(353).WMTSTileSource)},\n", - " function _(e,t,r,o,l){var i;o();const n=e(348);class s extends n.MercatorTileSource{constructor(e){super(e)}get_image_url(e,t,r){const o=this.string_lookup_replace(this.url,this.extra_url_vars);let l,i,n,s;return this.use_latlon?[i,s,l,n]=this.get_tile_geographic_bounds(e,t,r):[i,s,l,n]=this.get_tile_meter_bounds(e,t,r),o.replace(\"{XMIN}\",i.toString()).replace(\"{YMIN}\",s.toString()).replace(\"{XMAX}\",l.toString()).replace(\"{YMAX}\",n.toString())}}r.BBoxTileSource=s,i=s,s.__name__=\"BBoxTileSource\",i.define((({Boolean:e})=>({use_latlon:[e,!1]})))},\n", - " function _(t,e,i,_,s){var r;_();const o=t(349),n=t(9),l=t(350);class u extends o.TileSource{constructor(t){super(t)}initialize(){super.initialize(),this._resolutions=(0,n.range)(this.min_zoom,this.max_zoom+1).map((t=>this.get_resolution(t)))}_computed_initial_resolution(){return null!=this.initial_resolution?this.initial_resolution:2*Math.PI*6378137/this.tile_size}is_valid_tile(t,e,i){return!(!this.wrap_around&&(t<0||t>=2**i))&&!(e<0||e>=2**i)}parent_by_tile_xyz(t,e,i){const _=this.tile_xyz_to_quadkey(t,e,i),s=_.substring(0,_.length-1);return this.quadkey_to_tile_xyz(s)}get_resolution(t){return this._computed_initial_resolution()/2**t}get_resolution_by_extent(t,e,i){return[(t[2]-t[0])/i,(t[3]-t[1])/e]}get_level_by_extent(t,e,i){const _=(t[2]-t[0])/i,s=(t[3]-t[1])/e,r=Math.max(_,s);let o=0;for(const t of this._resolutions){if(r>t){if(0==o)return 0;if(o>0)return o-1}o+=1}return o-1}get_closest_level_by_extent(t,e,i){const _=(t[2]-t[0])/i,s=(t[3]-t[1])/e,r=Math.max(_,s),o=this._resolutions.reduce((function(t,e){return Math.abs(e-r)e?(u=o-s,a*=t):(u*=e,a=n-r)}const h=(u-(o-s))/2,c=(a-(n-r))/2;return[s-h,r-c,o+h,n+c]}tms_to_wmts(t,e,i){return[t,2**i-1-e,i]}wmts_to_tms(t,e,i){return[t,2**i-1-e,i]}pixels_to_meters(t,e,i){const _=this.get_resolution(i);return[t*_-this.x_origin_offset,e*_-this.y_origin_offset]}meters_to_pixels(t,e,i){const _=this.get_resolution(i);return[(t+this.x_origin_offset)/_,(e+this.y_origin_offset)/_]}pixels_to_tile(t,e){let i=Math.ceil(t/this.tile_size);i=0===i?i:i-1;return[i,Math.max(Math.ceil(e/this.tile_size)-1,0)]}pixels_to_raster(t,e,i){return[t,(this.tile_size<=l;t--)for(let i=n;i<=u;i++)this.is_valid_tile(i,t,e)&&h.push([i,t,e,this.get_tile_meter_bounds(i,t,e)]);return this.sort_tiles_from_center(h,[n,l,u,a]),h}quadkey_to_tile_xyz(t){let e=0,i=0;const _=t.length;for(let s=_;s>0;s--){const r=1<0;s--){const i=1<0;)if(s=s.substring(0,s.length-1),[t,e,i]=this.quadkey_to_tile_xyz(s),[t,e,i]=this.denormalize_xyz(t,e,i,_),this.tiles.has(this.tile_xyz_to_key(t,e,i)))return[t,e,i];return[0,0,0]}normalize_xyz(t,e,i){if(this.wrap_around){const _=2**i;return[(t%_+_)%_,e,i]}return[t,e,i]}denormalize_xyz(t,e,i,_){return[t+_*2**i,e,i]}denormalize_meters(t,e,i,_){return[t+2*_*Math.PI*6378137,e]}calculate_world_x_by_tile_xyz(t,e,i){return Math.floor(t/2**i)}}i.MercatorTileSource=u,r=u,u.__name__=\"MercatorTileSource\",r.define((({Boolean:t})=>({snap_to_zoom:[t,!1],wrap_around:[t,!0]}))),r.override({x_origin_offset:20037508.34,y_origin_offset:20037508.34,initial_resolution:156543.03392804097})},\n", - " function _(e,t,r,i,n){var l;i();const a=e(53),s=e(13);class c extends a.Model{constructor(e){super(e)}initialize(){super.initialize(),this.tiles=new Map,this._normalize_case()}connect_signals(){super.connect_signals(),this.connect(this.change,(()=>this._clear_cache()))}string_lookup_replace(e,t){let r=e;for(const[e,i]of(0,s.entries)(t))r=r.replace(`{${e}}`,i);return r}_normalize_case(){const e=this.url.replace(\"{x}\",\"{X}\").replace(\"{y}\",\"{Y}\").replace(\"{z}\",\"{Z}\").replace(\"{q}\",\"{Q}\").replace(\"{xmin}\",\"{XMIN}\").replace(\"{ymin}\",\"{YMIN}\").replace(\"{xmax}\",\"{XMAX}\").replace(\"{ymax}\",\"{YMAX}\");this.url=e}_clear_cache(){this.tiles=new Map}tile_xyz_to_key(e,t,r){return`${e}:${t}:${r}`}key_to_tile_xyz(e){const[t,r,i]=e.split(\":\").map((e=>parseInt(e)));return[t,r,i]}sort_tiles_from_center(e,t){const[r,i,n,l]=t,a=(n-r)/2+r,s=(l-i)/2+i;e.sort((function(e,t){return Math.sqrt((a-e[0])**2+(s-e[1])**2)-Math.sqrt((a-t[0])**2+(s-t[1])**2)}))}get_image_url(e,t,r){return this.string_lookup_replace(this.url,this.extra_url_vars).replace(\"{X}\",e.toString()).replace(\"{Y}\",t.toString()).replace(\"{Z}\",r.toString())}}r.TileSource=c,l=c,c.__name__=\"TileSource\",l.define((({Number:e,String:t,Dict:r,Nullable:i})=>({url:[t,\"\"],tile_size:[e,256],max_zoom:[e,30],min_zoom:[e,0],extra_url_vars:[r(t),{}],attribution:[t,\"\"],x_origin_offset:[e],y_origin_offset:[e],initial_resolution:[i(e),null]})))},\n", - " function _(t,e,r,n,o){n();const c=t(78);function _(t,e){return c.wgs84_mercator.compute(t,e)}function g(t,e){return c.wgs84_mercator.invert(t,e)}r.geographic_to_meters=_,r.meters_to_geographic=g,r.geographic_extent_to_meters=function(t){const[e,r,n,o]=t,[c,g]=_(e,r),[i,u]=_(n,o);return[c,g,i,u]},r.meters_extent_to_geographic=function(t){const[e,r,n,o]=t,[c,_]=g(e,r),[i,u]=g(n,o);return[c,_,i,u]}},\n", - " function _(e,t,r,s,_){s();const o=e(348);class c extends o.MercatorTileSource{constructor(e){super(e)}get_image_url(e,t,r){const s=this.string_lookup_replace(this.url,this.extra_url_vars),[_,o,c]=this.tms_to_wmts(e,t,r),i=this.tile_xyz_to_quadkey(_,o,c);return s.replace(\"{Q}\",i)}}r.QUADKEYTileSource=c,c.__name__=\"QUADKEYTileSource\"},\n", - " function _(t,e,i,s,_){s();const n=t(1);var a;const o=t(349),r=t(353),h=t(41),l=t(58),d=t(43),m=t(136),c=t(9),u=t(8),p=(0,n.__importStar)(t(354));class g extends h.RendererView{initialize(){this._tiles=[],super.initialize()}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render())),this.connect(this.model.tile_source.change,(()=>this.request_render()))}remove(){null!=this.attribution_el&&(0,d.removeElement)(this.attribution_el),super.remove()}styles(){return[...super.styles(),p.default]}get_extent(){return[this.x_range.start,this.y_range.start,this.x_range.end,this.y_range.end]}get map_plot(){return this.plot_model}get map_canvas(){return this.layer.ctx}get map_frame(){return this.plot_view.frame}get x_range(){return this.map_plot.x_range}get y_range(){return this.map_plot.y_range}_set_data(){this.extent=this.get_extent(),this._last_height=void 0,this._last_width=void 0}_update_attribution(){null!=this.attribution_el&&(0,d.removeElement)(this.attribution_el);const{attribution:t}=this.model.tile_source;if((0,u.isString)(t)&&t.length>0){const{layout:e,frame:i}=this.plot_view,s=e.bbox.width-i.bbox.right,_=e.bbox.height-i.bbox.bottom,n=i.bbox.width;this.attribution_el=(0,d.div)({class:p.tile_attribution,style:{position:\"absolute\",right:`${s}px`,bottom:`${_}px`,\"max-width\":n-4+\"px\",padding:\"2px\",\"background-color\":\"rgba(255,255,255,0.5)\",\"font-size\":\"9px\",\"line-height\":\"1.05\",\"white-space\":\"nowrap\",overflow:\"hidden\",\"text-overflow\":\"ellipsis\"}}),this.plot_view.canvas_view.add_event(this.attribution_el),this.attribution_el.innerHTML=t,this.attribution_el.title=this.attribution_el.textContent.replace(/\\s*\\n\\s*/g,\" \")}}_map_data(){this.initial_extent=this.get_extent();const t=this.model.tile_source.get_level_by_extent(this.initial_extent,this.map_frame.bbox.height,this.map_frame.bbox.width),e=this.model.tile_source.snap_to_zoom_level(this.initial_extent,this.map_frame.bbox.height,this.map_frame.bbox.width,t);this.x_range.start=e[0],this.y_range.start=e[1],this.x_range.end=e[2],this.y_range.end=e[3],this.x_range instanceof l.Range1d&&(this.x_range.reset_start=e[0],this.x_range.reset_end=e[2]),this.y_range instanceof l.Range1d&&(this.y_range.reset_start=e[1],this.y_range.reset_end=e[3]),this._update_attribution()}_create_tile(t,e,i,s,_=!1){const n=this.model.tile_source.tile_xyz_to_quadkey(t,e,i),a=this.model.tile_source.tile_xyz_to_key(t,e,i);if(this.model.tile_source.tiles.has(a))return;const[o,r,h]=this.model.tile_source.normalize_xyz(t,e,i),l=this.model.tile_source.get_image_url(o,r,h),d={img:void 0,tile_coords:[t,e,i],normalized_coords:[o,r,h],quadkey:n,cache_key:a,bounds:s,loaded:!1,finished:!1,x_coord:s[0],y_coord:s[3]};this.model.tile_source.tiles.set(a,d),this._tiles.push(d),new m.ImageLoader(l,{loaded:t=>{Object.assign(d,{img:t,loaded:!0}),_?(d.finished=!0,this.notify_finished()):this.request_render()},failed(){d.finished=!0}})}_enforce_aspect_ratio(){if(this._last_height!==this.map_frame.bbox.height||this._last_width!==this.map_frame.bbox.width){const t=this.get_extent(),e=this.model.tile_source.get_level_by_extent(t,this.map_frame.bbox.height,this.map_frame.bbox.width),i=this.model.tile_source.snap_to_zoom_level(t,this.map_frame.bbox.height,this.map_frame.bbox.width,e);this.x_range.setv({start:i[0],end:i[2]}),this.y_range.setv({start:i[1],end:i[3]}),this.extent=i,this._last_height=this.map_frame.bbox.height,this._last_width=this.map_frame.bbox.width}}has_finished(){if(!super.has_finished())return!1;if(0==this._tiles.length)return!1;for(const t of this._tiles)if(!t.finished)return!1;return!0}_render(){null==this.map_initialized&&(this._set_data(),this._map_data(),this.map_initialized=!0),this._enforce_aspect_ratio(),this._update(),null!=this.prefetch_timer&&clearTimeout(this.prefetch_timer),this.prefetch_timer=setTimeout(this._prefetch_tiles.bind(this),500),this.has_finished()&&this.notify_finished()}_draw_tile(t){const e=this.model.tile_source.tiles.get(t);if(null!=e&&e.loaded){const[[t],[i]]=this.coordinates.map_to_screen([e.bounds[0]],[e.bounds[3]]),[[s],[_]]=this.coordinates.map_to_screen([e.bounds[2]],[e.bounds[1]]),n=s-t,a=_-i,o=t,r=i,h=this.map_canvas.getImageSmoothingEnabled();this.map_canvas.setImageSmoothingEnabled(this.model.smoothing),this.map_canvas.drawImage(e.img,o,r,n,a),this.map_canvas.setImageSmoothingEnabled(h),e.finished=!0}}_set_rect(){const t=this.plot_model.outline_line_width,e=this.map_frame.bbox.left+t/2,i=this.map_frame.bbox.top+t/2,s=this.map_frame.bbox.width-t,_=this.map_frame.bbox.height-t;this.map_canvas.rect(e,i,s,_),this.map_canvas.clip()}_render_tiles(t){this.map_canvas.save(),this._set_rect(),this.map_canvas.globalAlpha=this.model.alpha;for(const e of t)this._draw_tile(e);this.map_canvas.restore()}_prefetch_tiles(){const{tile_source:t}=this.model,e=this.get_extent(),i=this.map_frame.bbox.height,s=this.map_frame.bbox.width,_=this.model.tile_source.get_level_by_extent(e,i,s),n=this.model.tile_source.get_tiles_by_extent(e,_);for(let e=0,i=Math.min(10,n.length);ei&&(s=this.extent,o=i,r=!0),r&&(this.x_range.setv({start:s[0],end:s[2]}),this.y_range.setv({start:s[1],end:s[3]})),this.extent=s;const h=t.get_tiles_by_extent(s,o),l=[],d=[],m=[],u=[];for(const e of h){const[i,s,n]=e,a=t.tile_xyz_to_key(i,s,n),o=t.tiles.get(a);if(null!=o&&o.loaded)d.push(a);else if(this.model.render_parents){const[e,a,o]=t.get_closest_parent_by_tile_xyz(i,s,n),r=t.tile_xyz_to_key(e,a,o),h=t.tiles.get(r);if(null!=h&&h.loaded&&!(0,c.includes)(m,r)&&m.push(r),_){const e=t.children_by_tile_xyz(i,s,n);for(const[i,s,_]of e){const e=t.tile_xyz_to_key(i,s,_);t.tiles.has(e)&&u.push(e)}}}null==o&&l.push(e)}this._render_tiles(m),this._render_tiles(u),this._render_tiles(d),null!=this.render_timer&&clearTimeout(this.render_timer),this.render_timer=setTimeout((()=>this._fetch_tiles(l)),65)}}i.TileRendererView=g,g.__name__=\"TileRendererView\";class b extends h.Renderer{constructor(t){super(t)}}i.TileRenderer=b,a=b,b.__name__=\"TileRenderer\",a.prototype.default_view=g,a.define((({Boolean:t,Number:e,Ref:i})=>({alpha:[e,1],smoothing:[t,!0],tile_source:[i(o.TileSource),()=>new r.WMTSTileSource],render_parents:[t,!0]}))),a.override({level:\"image\"})},\n", - " function _(t,e,r,o,s){o();const c=t(348);class i extends c.MercatorTileSource{constructor(t){super(t)}get_image_url(t,e,r){const o=this.string_lookup_replace(this.url,this.extra_url_vars),[s,c,i]=this.tms_to_wmts(t,e,r);return o.replace(\"{X}\",s.toString()).replace(\"{Y}\",c.toString()).replace(\"{Z}\",i.toString())}}r.WMTSTileSource=i,i.__name__=\"WMTSTileSource\"},\n", - " function _(t,o,i,b,r){b(),i.root=\"bk-root\",i.tile_attribution=\"bk-tile-attribution\",i.default=\".bk-root .bk-tile-attribution a{color:black;}\"},\n", - " function _(e,r,t,c,o){c();const i=e(348);class l extends i.MercatorTileSource{constructor(e){super(e)}get_image_url(e,r,t){return this.string_lookup_replace(this.url,this.extra_url_vars).replace(\"{X}\",e.toString()).replace(\"{Y}\",r.toString()).replace(\"{Z}\",t.toString())}}t.TMSTileSource=l,l.__name__=\"TMSTileSource\"},\n", - " function _(e,t,u,a,r){a(),r(\"CanvasTexture\",e(357).CanvasTexture),r(\"ImageURLTexture\",e(359).ImageURLTexture),r(\"Texture\",e(358).Texture)},\n", - " function _(t,e,n,c,s){var r;c();const o=t(358),a=t(34);class u extends o.Texture{constructor(t){super(t)}get func(){const t=(0,a.use_strict)(this.code);return new Function(\"ctx\",\"color\",\"scale\",\"weight\",t)}get_pattern(t,e,n){const c=document.createElement(\"canvas\");c.width=e,c.height=e;const s=c.getContext(\"2d\");return this.func.call(this,s,t,e,n),c}}n.CanvasTexture=u,r=u,u.__name__=\"CanvasTexture\",r.define((({String:t})=>({code:[t]})))},\n", - " function _(e,t,n,r,o){var i;r();const s=e(53),u=e(20);class c extends s.Model{constructor(e){super(e)}}n.Texture=c,i=c,c.__name__=\"Texture\",i.define((()=>({repetition:[u.TextureRepetition,\"repeat\"]})))},\n", - " function _(e,t,i,r,n){var a;r();const s=e(358),o=e(136);class u extends s.Texture{constructor(e){super(e)}initialize(){super.initialize(),this._loader=new o.ImageLoader(this.url)}get_pattern(e,t,i){const{_loader:r}=this;return this._loader.finished?r.image:r.promise}}i.ImageURLTexture=u,a=u,u.__name__=\"ImageURLTexture\",a.define((({String:e})=>({url:[e]})))},\n", - " function _(o,l,T,e,t){e(),t(\"ActionTool\",o(238).ActionTool),t(\"CustomAction\",o(361).CustomAction),t(\"HelpTool\",o(239).HelpTool),t(\"RedoTool\",o(362).RedoTool),t(\"ResetTool\",o(363).ResetTool),t(\"SaveTool\",o(364).SaveTool),t(\"UndoTool\",o(365).UndoTool),t(\"ZoomInTool\",o(366).ZoomInTool),t(\"ZoomOutTool\",o(369).ZoomOutTool),t(\"ButtonTool\",o(224).ButtonTool),t(\"EditTool\",o(370).EditTool),t(\"BoxEditTool\",o(371).BoxEditTool),t(\"FreehandDrawTool\",o(372).FreehandDrawTool),t(\"PointDrawTool\",o(373).PointDrawTool),t(\"PolyDrawTool\",o(374).PolyDrawTool),t(\"PolyTool\",o(375).PolyTool),t(\"PolyEditTool\",o(376).PolyEditTool),t(\"BoxSelectTool\",o(377).BoxSelectTool),t(\"BoxZoomTool\",o(379).BoxZoomTool),t(\"GestureTool\",o(223).GestureTool),t(\"LassoSelectTool\",o(380).LassoSelectTool),t(\"LineEditTool\",o(382).LineEditTool),t(\"PanTool\",o(384).PanTool),t(\"PolySelectTool\",o(381).PolySelectTool),t(\"RangeTool\",o(385).RangeTool),t(\"SelectTool\",o(378).SelectTool),t(\"TapTool\",o(386).TapTool),t(\"WheelPanTool\",o(387).WheelPanTool),t(\"WheelZoomTool\",o(388).WheelZoomTool),t(\"CrosshairTool\",o(389).CrosshairTool),t(\"CustomJSHover\",o(390).CustomJSHover),t(\"HoverTool\",o(391).HoverTool),t(\"InspectTool\",o(232).InspectTool),t(\"Tool\",o(222).Tool),t(\"ToolProxy\",o(394).ToolProxy),t(\"Toolbar\",o(221).Toolbar),t(\"ToolbarBase\",o(233).ToolbarBase),t(\"ProxyToolbar\",o(395).ProxyToolbar),t(\"ToolbarBox\",o(395).ToolbarBox)},\n", - " function _(t,o,e,s,n){var c;s();const i=t(238);class u extends i.ActionToolButtonView{css_classes(){return super.css_classes().concat(\"bk-toolbar-button-custom-action\")}}e.CustomActionButtonView=u,u.__name__=\"CustomActionButtonView\";class l extends i.ActionToolView{doit(){var t;null===(t=this.model.callback)||void 0===t||t.execute(this.model)}}e.CustomActionView=l,l.__name__=\"CustomActionView\";class a extends i.ActionTool{constructor(t){super(t),this.tool_name=\"Custom Action\",this.button_view=u}}e.CustomAction=a,c=a,a.__name__=\"CustomAction\",c.prototype.default_view=l,c.define((({Any:t,String:o,Nullable:e})=>({callback:[e(t)],icon:[o]}))),c.override({description:\"Perform a Custom Action\"})},\n", - " function _(e,o,t,i,s){var n;i();const l=e(238),_=e(228);class d extends l.ActionToolView{connect_signals(){super.connect_signals(),this.connect(this.plot_view.state.changed,(()=>this.model.disabled=!this.plot_view.state.can_redo))}doit(){const e=this.plot_view.state.redo();null!=(null==e?void 0:e.range)&&this.plot_view.trigger_ranges_update_event()}}t.RedoToolView=d,d.__name__=\"RedoToolView\";class a extends l.ActionTool{constructor(e){super(e),this.tool_name=\"Redo\",this.icon=_.tool_icon_redo}}t.RedoTool=a,n=a,a.__name__=\"RedoTool\",n.prototype.default_view=d,n.override({disabled:!0}),n.register_alias(\"redo\",(()=>new a))},\n", - " function _(e,o,t,s,i){var _;s();const n=e(238),l=e(228);class c extends n.ActionToolView{doit(){this.plot_view.reset()}}t.ResetToolView=c,c.__name__=\"ResetToolView\";class r extends n.ActionTool{constructor(e){super(e),this.tool_name=\"Reset\",this.icon=l.tool_icon_reset}}t.ResetTool=r,_=r,r.__name__=\"ResetTool\",_.prototype.default_view=c,_.register_alias(\"reset\",(()=>new r))},\n", - " function _(e,o,t,a,i){var s;a();const c=e(238),n=e(228);class l extends c.ActionToolView{async copy(){const e=await this.plot_view.to_blob(),o=new ClipboardItem({[e.type]:Promise.resolve(e)});await navigator.clipboard.write([o])}async save(e){const o=await this.plot_view.to_blob(),t=document.createElement(\"a\");t.href=URL.createObjectURL(o),t.download=e,t.target=\"_blank\",t.dispatchEvent(new MouseEvent(\"click\"))}doit(e=\"save\"){switch(e){case\"save\":this.save(\"bokeh_plot\");break;case\"copy\":this.copy()}}}t.SaveToolView=l,l.__name__=\"SaveToolView\";class r extends c.ActionTool{constructor(e){super(e),this.tool_name=\"Save\",this.icon=n.tool_icon_save}get menu(){return[{icon:\"bk-tool-icon-copy-to-clipboard\",tooltip:\"Copy image to clipboard\",if:()=>\"undefined\"!=typeof ClipboardItem,handler:()=>{this.do.emit(\"copy\")}}]}}t.SaveTool=r,s=r,r.__name__=\"SaveTool\",s.prototype.default_view=l,s.register_alias(\"save\",(()=>new r))},\n", - " function _(o,e,t,n,i){var s;n();const l=o(238),_=o(228);class d extends l.ActionToolView{connect_signals(){super.connect_signals(),this.connect(this.plot_view.state.changed,(()=>this.model.disabled=!this.plot_view.state.can_undo))}doit(){const o=this.plot_view.state.undo();null!=(null==o?void 0:o.range)&&this.plot_view.trigger_ranges_update_event()}}t.UndoToolView=d,d.__name__=\"UndoToolView\";class a extends l.ActionTool{constructor(o){super(o),this.tool_name=\"Undo\",this.icon=_.tool_icon_undo}}t.UndoTool=a,s=a,a.__name__=\"UndoTool\",s.prototype.default_view=d,s.override({disabled:!0}),s.register_alias(\"undo\",(()=>new a))},\n", - " function _(o,n,e,i,s){var t;i();const _=o(367),m=o(228);class a extends _.ZoomBaseToolView{}e.ZoomInToolView=a,a.__name__=\"ZoomInToolView\";class l extends _.ZoomBaseTool{constructor(o){super(o),this.sign=1,this.tool_name=\"Zoom In\",this.icon=m.tool_icon_zoom_in}}e.ZoomInTool=l,t=l,l.__name__=\"ZoomInTool\",t.prototype.default_view=a,t.register_alias(\"zoom_in\",(()=>new l({dimensions:\"both\"}))),t.register_alias(\"xzoom_in\",(()=>new l({dimensions:\"width\"}))),t.register_alias(\"yzoom_in\",(()=>new l({dimensions:\"height\"})))},\n", - " function _(o,t,e,i,s){var n;i();const a=o(238),_=o(20),l=o(368);class m extends a.ActionToolView{doit(){var o;const t=this.plot_view.frame,e=this.model.dimensions,i=\"width\"==e||\"both\"==e,s=\"height\"==e||\"both\"==e,n=(0,l.scale_range)(t,this.model.sign*this.model.factor,i,s);this.plot_view.state.push(\"zoom_out\",{range:n}),this.plot_view.update_range(n,{scrolling:!0,maintain_focus:this.model.maintain_focus}),null===(o=this.model.document)||void 0===o||o.interactive_start(this.plot_model),this.plot_view.trigger_ranges_update_event()}}e.ZoomBaseToolView=m,m.__name__=\"ZoomBaseToolView\";class h extends a.ActionTool{constructor(o){super(o),this.maintain_focus=!0}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}e.ZoomBaseTool=h,n=h,h.__name__=\"ZoomBaseTool\",n.define((({Percent:o})=>({factor:[o,.1],dimensions:[_.Dimensions,\"both\"]})))},\n", - " function _(n,t,o,r,s){r();const c=n(10);function e(n,t,o){const[r,s]=[n.start,n.end],c=null!=o?o:(s+r)/2;return[r-(r-c)*t,s-(s-c)*t]}function a(n,[t,o]){const r=new Map;for(const[s,c]of n){const[n,e]=c.r_invert(t,o);r.set(s,{start:n,end:e})}return r}o.scale_highlow=e,o.get_info=a,o.scale_range=function(n,t,o=!0,r=!0,s){t=(0,c.clamp)(t,-.9,.9);const l=o?t:0,[u,i]=e(n.bbox.h_range,l,null!=s?s.x:void 0),_=a(n.x_scales,[u,i]),f=r?t:0,[g,x]=e(n.bbox.v_range,f,null!=s?s.y:void 0);return{xrs:_,yrs:a(n.y_scales,[g,x]),factor:t}}},\n", - " function _(o,e,t,i,s){var n;i();const _=o(367),a=o(228);class m extends _.ZoomBaseToolView{}t.ZoomOutToolView=m,m.__name__=\"ZoomOutToolView\";class l extends _.ZoomBaseTool{constructor(o){super(o),this.sign=-1,this.tool_name=\"Zoom Out\",this.icon=a.tool_icon_zoom_out}}t.ZoomOutTool=l,n=l,l.__name__=\"ZoomOutTool\",n.prototype.default_view=m,n.define((({Boolean:o})=>({maintain_focus:[o,!0]}))),n.register_alias(\"zoom_out\",(()=>new l({dimensions:\"both\"}))),n.register_alias(\"xzoom_out\",(()=>new l({dimensions:\"width\"}))),n.register_alias(\"yzoom_out\",(()=>new l({dimensions:\"height\"})))},\n", - " function _(e,t,s,o,n){var r;o();const i=e(9),c=e(8),a=e(11),_=e(175),l=e(223);class d extends l.GestureToolView{constructor(){super(...arguments),this._mouse_in_frame=!0}_select_mode(e){const{shiftKey:t,ctrlKey:s}=e;return t||s?t&&!s?\"append\":!t&&s?\"intersect\":t&&s?\"subtract\":void(0,a.unreachable)():\"replace\"}_move_enter(e){this._mouse_in_frame=!0}_move_exit(e){this._mouse_in_frame=!1}_map_drag(e,t,s){if(!this.plot_view.frame.bbox.contains(e,t))return null;const o=this.plot_view.renderer_view(s);if(null==o)return null;return[o.coordinates.x_scale.invert(e),o.coordinates.y_scale.invert(t)]}_delete_selected(e){const t=e.data_source,s=t.selected.indices;s.sort();for(const e of t.columns()){const o=t.get_array(e);for(let e=0;e({custom_icon:[n(t),null],empty_value:[e],renderers:[s(o(_.GlyphRenderer)),[]]})))},\n", - " function _(e,t,s,i,_){var o;i();const n=e(43),a=e(20),d=e(370),l=e(228);class r extends d.EditToolView{_tap(e){null==this._draw_basepoint&&null==this._basepoint&&this._select_event(e,this._select_mode(e),this.model.renderers)}_keyup(e){if(this.model.active&&this._mouse_in_frame)for(const t of this.model.renderers)if(e.keyCode===n.Keys.Backspace)this._delete_selected(t);else if(e.keyCode==n.Keys.Esc){t.data_source.selection_manager.clear()}}_set_extent([e,t],[s,i],_,o=!1){const n=this.model.renderers[0],a=this.plot_view.renderer_view(n);if(null==a)return;const d=n.glyph,l=n.data_source,[r,h]=a.coordinates.x_scale.r_invert(e,t),[p,u]=a.coordinates.y_scale.r_invert(s,i),[c,m]=[(r+h)/2,(p+u)/2],[f,b]=[h-r,u-p],[y,x]=[d.x.field,d.y.field],[w,v]=[d.width.field,d.height.field];if(_)this._pop_glyphs(l,this.model.num_objects),y&&l.get_array(y).push(c),x&&l.get_array(x).push(m),w&&l.get_array(w).push(f),v&&l.get_array(v).push(b),this._pad_empty_columns(l,[y,x,w,v]);else{const e=l.data[y].length-1;y&&(l.data[y][e]=c),x&&(l.data[x][e]=m),w&&(l.data[w][e]=f),v&&(l.data[v][e]=b)}this._emit_cds_changes(l,!0,!1,o)}_update_box(e,t=!1,s=!1){if(null==this._draw_basepoint)return;const i=[e.sx,e.sy],_=this.plot_view.frame,o=this.model.dimensions,n=this.model._get_dim_limits(this._draw_basepoint,i,_,o);if(null!=n){const[e,i]=n;this._set_extent(e,i,t,s)}}_doubletap(e){this.model.active&&(null!=this._draw_basepoint?(this._update_box(e,!1,!0),this._draw_basepoint=null):(this._draw_basepoint=[e.sx,e.sy],this._select_event(e,\"append\",this.model.renderers),this._update_box(e,!0,!1)))}_move(e){this._update_box(e,!1,!1)}_pan_start(e){if(e.shiftKey){if(null!=this._draw_basepoint)return;this._draw_basepoint=[e.sx,e.sy],this._update_box(e,!0,!1)}else{if(null!=this._basepoint)return;this._select_event(e,\"append\",this.model.renderers),this._basepoint=[e.sx,e.sy]}}_pan(e,t=!1,s=!1){if(e.shiftKey){if(null==this._draw_basepoint)return;this._update_box(e,t,s)}else{if(null==this._basepoint)return;this._drag_points(e,this.model.renderers)}}_pan_end(e){if(this._pan(e,!1,!0),e.shiftKey)this._draw_basepoint=null;else{this._basepoint=null;for(const e of this.model.renderers)this._emit_cds_changes(e.data_source,!1,!0,!0)}}}s.BoxEditToolView=r,r.__name__=\"BoxEditToolView\";class h extends d.EditTool{constructor(e){super(e),this.tool_name=\"Box Edit Tool\",this.icon=l.tool_icon_box_edit,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=1}}s.BoxEditTool=h,o=h,h.__name__=\"BoxEditTool\",o.prototype.default_view=r,o.define((({Int:e})=>({dimensions:[a.Dimensions,\"both\"],num_objects:[e,0]})))},\n", - " function _(e,t,a,s,r){var _;s();const d=e(43),o=e(8),n=e(370),i=e(228);class l extends n.EditToolView{_draw(e,t,a=!1){if(!this.model.active)return;const s=this.model.renderers[0],r=this._map_drag(e.sx,e.sy,s);if(null==r)return;const[_,d]=r,n=s.data_source,i=s.glyph,[l,h]=[i.xs.field,i.ys.field];if(\"new\"==t)this._pop_glyphs(n,this.model.num_objects),l&&n.get_array(l).push([_]),h&&n.get_array(h).push([d]),this._pad_empty_columns(n,[l,h]);else if(\"add\"==t){if(l){const e=n.data[l].length-1;let t=n.get_array(l)[e];(0,o.isArray)(t)||(t=Array.from(t),n.data[l][e]=t),t.push(_)}if(h){const e=n.data[h].length-1;let t=n.get_array(h)[e];(0,o.isArray)(t)||(t=Array.from(t),n.data[h][e]=t),t.push(d)}}this._emit_cds_changes(n,!0,!0,a)}_pan_start(e){this._draw(e,\"new\")}_pan(e){this._draw(e,\"add\")}_pan_end(e){this._draw(e,\"add\",!0)}_tap(e){this._select_event(e,this._select_mode(e),this.model.renderers)}_keyup(e){if(this.model.active&&this._mouse_in_frame)for(const t of this.model.renderers)e.keyCode===d.Keys.Esc?t.data_source.selection_manager.clear():e.keyCode===d.Keys.Backspace&&this._delete_selected(t)}}a.FreehandDrawToolView=l,l.__name__=\"FreehandDrawToolView\";class h extends n.EditTool{constructor(e){super(e),this.tool_name=\"Freehand Draw Tool\",this.icon=i.tool_icon_freehand_draw,this.event_type=[\"pan\",\"tap\"],this.default_order=3}}a.FreehandDrawTool=h,_=h,h.__name__=\"FreehandDrawTool\",_.prototype.default_view=l,_.define((({Int:e})=>({num_objects:[e,0]}))),_.register_alias(\"freehand_draw\",(()=>new h))},\n", - " function _(e,t,s,o,a){var i;o();const n=e(43),_=e(370),r=e(228);class d extends _.EditToolView{_tap(e){if(this._select_event(e,this._select_mode(e),this.model.renderers).length||!this.model.add)return;const t=this.model.renderers[0],s=this._map_drag(e.sx,e.sy,t);if(null==s)return;const o=t.glyph,a=t.data_source,[i,n]=[o.x.field,o.y.field],[_,r]=s;this._pop_glyphs(a,this.model.num_objects),i&&a.get_array(i).push(_),n&&a.get_array(n).push(r),this._pad_empty_columns(a,[i,n]),a.change.emit(),a.data=a.data,a.properties.data.change.emit()}_keyup(e){if(this.model.active&&this._mouse_in_frame)for(const t of this.model.renderers)e.keyCode===n.Keys.Backspace?this._delete_selected(t):e.keyCode==n.Keys.Esc&&t.data_source.selection_manager.clear()}_pan_start(e){this.model.drag&&(this._select_event(e,\"append\",this.model.renderers),this._basepoint=[e.sx,e.sy])}_pan(e){this.model.drag&&null!=this._basepoint&&this._drag_points(e,this.model.renderers)}_pan_end(e){if(this.model.drag){this._pan(e);for(const e of this.model.renderers)this._emit_cds_changes(e.data_source,!1,!0,!0);this._basepoint=null}}}s.PointDrawToolView=d,d.__name__=\"PointDrawToolView\";class l extends _.EditTool{constructor(e){super(e),this.tool_name=\"Point Draw Tool\",this.icon=r.tool_icon_point_draw,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=2}}s.PointDrawTool=l,i=l,l.__name__=\"PointDrawTool\",i.prototype.default_view=d,i.define((({Boolean:e,Int:t})=>({add:[e,!0],drag:[e,!0],num_objects:[t,0]})))},\n", - " function _(e,t,s,i,a){var r;i();const o=e(43),n=e(8),d=e(375),_=e(228);class h extends d.PolyToolView{constructor(){super(...arguments),this._drawing=!1,this._initialized=!1}_tap(e){this._drawing?this._draw(e,\"add\",!0):this._select_event(e,this._select_mode(e),this.model.renderers)}_draw(e,t,s=!1){const i=this.model.renderers[0],a=this._map_drag(e.sx,e.sy,i);if(this._initialized||this.activate(),null==a)return;const[r,o]=this._snap_to_vertex(e,...a),d=i.data_source,_=i.glyph,[h,l]=[_.xs.field,_.ys.field];if(\"new\"==t)this._pop_glyphs(d,this.model.num_objects),h&&d.get_array(h).push([r,r]),l&&d.get_array(l).push([o,o]),this._pad_empty_columns(d,[h,l]);else if(\"edit\"==t){if(h){const e=d.data[h][d.data[h].length-1];e[e.length-1]=r}if(l){const e=d.data[l][d.data[l].length-1];e[e.length-1]=o}}else if(\"add\"==t){if(h){const e=d.data[h].length-1;let t=d.get_array(h)[e];const s=t[t.length-1];t[t.length-1]=r,(0,n.isArray)(t)||(t=Array.from(t),d.data[h][e]=t),t.push(s)}if(l){const e=d.data[l].length-1;let t=d.get_array(l)[e];const s=t[t.length-1];t[t.length-1]=o,(0,n.isArray)(t)||(t=Array.from(t),d.data[l][e]=t),t.push(s)}}this._emit_cds_changes(d,!0,!1,s)}_show_vertices(){if(!this.model.active)return;const e=[],t=[];for(let s=0;sthis._show_vertices()))}this._initialized=!0}}deactivate(){this._drawing&&(this._remove(),this._drawing=!1),this.model.vertex_renderer&&this._hide_vertices()}}s.PolyDrawToolView=h,h.__name__=\"PolyDrawToolView\";class l extends d.PolyTool{constructor(e){super(e),this.tool_name=\"Polygon Draw Tool\",this.icon=_.tool_icon_poly_draw,this.event_type=[\"pan\",\"tap\",\"move\"],this.default_order=3}}s.PolyDrawTool=l,r=l,l.__name__=\"PolyDrawTool\",r.prototype.default_view=h,r.define((({Boolean:e,Int:t})=>({drag:[e,!0],num_objects:[t,0]})))},\n", - " function _(e,r,t,s,o){var _;s();const d=e(8),i=e(370);class l extends i.EditToolView{_set_vertices(e,r){const t=this.model.vertex_renderer.glyph,s=this.model.vertex_renderer.data_source,[o,_]=[t.x.field,t.y.field];o&&((0,d.isArray)(e)?s.data[o]=e:t.x={value:e}),_&&((0,d.isArray)(r)?s.data[_]=r:t.y={value:r}),this._emit_cds_changes(s,!0,!0,!1)}_hide_vertices(){this._set_vertices([],[])}_snap_to_vertex(e,r,t){if(this.model.vertex_renderer){const s=this._select_event(e,\"replace\",[this.model.vertex_renderer]),o=this.model.vertex_renderer.data_source,_=this.model.vertex_renderer.glyph,[d,i]=[_.x.field,_.y.field];if(s.length){const e=o.selected.indices[0];d&&(r=o.data[d][e]),i&&(t=o.data[i][e]),o.selection_manager.clear()}}return[r,t]}}t.PolyToolView=l,l.__name__=\"PolyToolView\";class n extends i.EditTool{constructor(e){super(e)}}t.PolyTool=n,_=n,n.__name__=\"PolyTool\",_.define((({AnyRef:e})=>({vertex_renderer:[e()]})))},\n", - " function _(e,t,s,r,i){var _;r();const d=e(43),n=e(8),l=e(375),a=e(228);class c extends l.PolyToolView{constructor(){super(...arguments),this._drawing=!1,this._cur_index=null}_doubletap(e){if(!this.model.active)return;const t=this._map_drag(e.sx,e.sy,this.model.vertex_renderer);if(null==t)return;const[s,r]=t,i=this._select_event(e,\"replace\",[this.model.vertex_renderer]),_=this.model.vertex_renderer.data_source,d=this.model.vertex_renderer.glyph,[n,l]=[d.x.field,d.y.field];if(i.length&&null!=this._selected_renderer){const e=_.selected.indices[0];this._drawing?(this._drawing=!1,_.selection_manager.clear()):(_.selected.indices=[e+1],n&&_.get_array(n).splice(e+1,0,s),l&&_.get_array(l).splice(e+1,0,r),this._drawing=!0),_.change.emit(),this._emit_cds_changes(this._selected_renderer.data_source)}else this._show_vertices(e)}_show_vertices(e){if(!this.model.active)return;const t=this.model.renderers[0],s=()=>this._update_vertices(t),r=null==t?void 0:t.data_source,i=this._select_event(e,\"replace\",this.model.renderers);if(!i.length)return this._set_vertices([],[]),this._selected_renderer=null,this._drawing=!1,this._cur_index=null,void(null!=r&&r.disconnect(r.properties.data.change,s));null!=r&&r.connect(r.properties.data.change,s),this._cur_index=i[0].data_source.selected.indices[0],this._update_vertices(i[0])}_update_vertices(e){const t=e.glyph,s=e.data_source,r=this._cur_index,[i,_]=[t.xs.field,t.ys.field];if(this._drawing)return;if(null==r&&(i||_))return;let d,l;i&&null!=r?(d=s.data[i][r],(0,n.isArray)(d)||(s.data[i][r]=d=Array.from(d))):d=t.xs.value,_&&null!=r?(l=s.data[_][r],(0,n.isArray)(l)||(s.data[_][r]=l=Array.from(l))):l=t.ys.value,this._selected_renderer=e,this._set_vertices(d,l)}_move(e){if(this._drawing&&null!=this._selected_renderer){const t=this.model.vertex_renderer,s=t.data_source,r=t.glyph,i=this._map_drag(e.sx,e.sy,t);if(null==i)return;let[_,d]=i;const n=s.selected.indices;[_,d]=this._snap_to_vertex(e,_,d),s.selected.indices=n;const[l,a]=[r.x.field,r.y.field],c=n[0];l&&(s.data[l][c]=_),a&&(s.data[a][c]=d),s.change.emit(),this._selected_renderer.data_source.change.emit()}}_tap(e){const t=this.model.vertex_renderer,s=this._map_drag(e.sx,e.sy,t);if(null==s)return;if(this._drawing&&this._selected_renderer){let[r,i]=s;const _=t.data_source,d=t.glyph,[n,l]=[d.x.field,d.y.field],a=_.selected.indices;[r,i]=this._snap_to_vertex(e,r,i);const c=a[0];if(_.selected.indices=[c+1],n){const e=_.get_array(n),t=e[c];e[c]=r,e.splice(c+1,0,t)}if(l){const e=_.get_array(l),t=e[c];e[c]=i,e.splice(c+1,0,t)}return _.change.emit(),void this._emit_cds_changes(this._selected_renderer.data_source,!0,!1,!0)}const r=this._select_mode(e);this._select_event(e,r,[t]),this._select_event(e,r,this.model.renderers)}_remove_vertex(){if(!this._drawing||!this._selected_renderer)return;const e=this.model.vertex_renderer,t=e.data_source,s=e.glyph,r=t.selected.indices[0],[i,_]=[s.x.field,s.y.field];i&&t.get_array(i).splice(r,1),_&&t.get_array(_).splice(r,1),t.change.emit(),this._emit_cds_changes(this._selected_renderer.data_source)}_pan_start(e){this._select_event(e,\"append\",[this.model.vertex_renderer]),this._basepoint=[e.sx,e.sy]}_pan(e){null!=this._basepoint&&(this._drag_points(e,[this.model.vertex_renderer]),this._selected_renderer&&this._selected_renderer.data_source.change.emit())}_pan_end(e){null!=this._basepoint&&(this._drag_points(e,[this.model.vertex_renderer]),this._emit_cds_changes(this.model.vertex_renderer.data_source,!1,!0,!0),this._selected_renderer&&this._emit_cds_changes(this._selected_renderer.data_source),this._basepoint=null)}_keyup(e){if(!this.model.active||!this._mouse_in_frame)return;let t;t=this._selected_renderer?[this.model.vertex_renderer]:this.model.renderers;for(const s of t)e.keyCode===d.Keys.Backspace?(this._delete_selected(s),this._selected_renderer&&this._emit_cds_changes(this._selected_renderer.data_source)):e.keyCode==d.Keys.Esc&&(this._drawing?(this._remove_vertex(),this._drawing=!1):this._selected_renderer&&this._hide_vertices(),s.data_source.selection_manager.clear())}deactivate(){this._selected_renderer&&(this._drawing&&(this._remove_vertex(),this._drawing=!1),this._hide_vertices())}}s.PolyEditToolView=c,c.__name__=\"PolyEditToolView\";class o extends l.PolyTool{constructor(e){super(e),this.tool_name=\"Poly Edit Tool\",this.icon=a.tool_icon_poly_edit,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=4}}s.PolyEditTool=o,_=o,o.__name__=\"PolyEditTool\",_.prototype.default_view=c},\n", - " function _(e,t,o,s,i){var l;s();const n=e(378),_=e(116),c=e(20),r=e(228);class a extends n.SelectToolView{_compute_limits(e){const t=this.plot_view.frame,o=this.model.dimensions;let s=this._base_point;if(\"center\"==this.model.origin){const[t,o]=s,[i,l]=e;s=[t-(i-t),o-(l-o)]}return this.model._get_dim_limits(s,e,t,o)}_pan_start(e){const{sx:t,sy:o}=e;this._base_point=[t,o]}_pan(e){const{sx:t,sy:o}=e,s=[t,o],[i,l]=this._compute_limits(s);this.model.overlay.update({left:i[0],right:i[1],top:l[0],bottom:l[1]}),this.model.select_every_mousemove&&this._do_select(i,l,!1,this._select_mode(e))}_pan_end(e){const{sx:t,sy:o}=e,s=[t,o],[i,l]=this._compute_limits(s);this._do_select(i,l,!0,this._select_mode(e)),this.model.overlay.update({left:null,right:null,top:null,bottom:null}),this._base_point=null,this.plot_view.state.push(\"box_select\",{selection:this.plot_view.get_selection()})}_do_select([e,t],[o,s],i,l=\"replace\"){const n={type:\"rect\",sx0:e,sx1:t,sy0:o,sy1:s};this._select(n,i,l)}}o.BoxSelectToolView=a,a.__name__=\"BoxSelectToolView\";const h=()=>new _.BoxAnnotation({level:\"overlay\",top_units:\"screen\",left_units:\"screen\",bottom_units:\"screen\",right_units:\"screen\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:2,line_dash:[4,4]});class m extends n.SelectTool{constructor(e){super(e),this.tool_name=\"Box Select\",this.icon=r.tool_icon_box_select,this.event_type=\"pan\",this.default_order=30}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}o.BoxSelectTool=m,l=m,m.__name__=\"BoxSelectTool\",l.prototype.default_view=a,l.define((({Boolean:e,Ref:t})=>({dimensions:[c.Dimensions,\"both\"],select_every_mousemove:[e,!1],overlay:[t(_.BoxAnnotation),h],origin:[c.BoxOrigin,\"corner\"]}))),l.register_alias(\"box_select\",(()=>new m)),l.register_alias(\"xbox_select\",(()=>new m({dimensions:\"width\"}))),l.register_alias(\"ybox_select\",(()=>new m({dimensions:\"height\"})))},\n", - " function _(e,t,s,n,r){var o;n();const c=e(223),i=e(175),a=e(339),l=e(176),d=e(66),_=e(20),h=e(43),p=e(251),u=e(15),m=e(11);class v extends c.GestureToolView{connect_signals(){super.connect_signals(),this.model.clear.connect((()=>this._clear()))}get computed_renderers(){const{renderers:e,names:t}=this.model,s=this.plot_model.data_renderers;return(0,d.compute_renderers)(e,s,t)}_computed_renderers_by_data_source(){var e;const t=new Map;for(const s of this.computed_renderers){let n;if(s instanceof i.GlyphRenderer)n=s.data_source;else{if(!(s instanceof a.GraphRenderer))continue;n=s.node_renderer.data_source}const r=null!==(e=t.get(n))&&void 0!==e?e:[];t.set(n,[...r,s])}return t}_select_mode(e){const{shiftKey:t,ctrlKey:s}=e;return t||s?t&&!s?\"append\":!t&&s?\"intersect\":t&&s?\"subtract\":void(0,m.unreachable)():this.model.mode}_keyup(e){e.keyCode==h.Keys.Esc&&this._clear()}_clear(){for(const e of this.computed_renderers)e.get_selection_manager().clear();const e=this.computed_renderers.map((e=>this.plot_view.renderer_view(e)));this.plot_view.request_paint(e)}_select(e,t,s){const n=this._computed_renderers_by_data_source();for(const[,r]of n){const n=r[0].get_selection_manager(),o=[];for(const e of r){const t=this.plot_view.renderer_view(e);null!=t&&o.push(t)}n.select(o,e,t,s)}null!=this.model.callback&&this._emit_callback(e),this._emit_selection_event(e,t)}_emit_selection_event(e,t=!0){const{x_scale:s,y_scale:n}=this.plot_view.frame;let r;switch(e.type){case\"point\":{const{sx:t,sy:o}=e,c=s.invert(t),i=n.invert(o);r=Object.assign(Object.assign({},e),{x:c,y:i});break}case\"span\":{const{sx:t,sy:o}=e,c=s.invert(t),i=n.invert(o);r=Object.assign(Object.assign({},e),{x:c,y:i});break}case\"rect\":{const{sx0:t,sx1:o,sy0:c,sy1:i}=e,[a,l]=s.r_invert(t,o),[d,_]=n.r_invert(c,i);r=Object.assign(Object.assign({},e),{x0:a,y0:d,x1:l,y1:_});break}case\"poly\":{const{sx:t,sy:o}=e,c=s.v_invert(t),i=n.v_invert(o);r=Object.assign(Object.assign({},e),{x:c,y:i});break}}this.plot_model.trigger_event(new p.SelectionGeometry(r,t))}}s.SelectToolView=v,v.__name__=\"SelectToolView\";class b extends c.GestureTool{constructor(e){super(e)}initialize(){super.initialize(),this.clear=new u.Signal0(this,\"clear\")}get menu(){return[{icon:\"bk-tool-icon-replace-mode\",tooltip:\"Replace the current selection\",active:()=>\"replace\"==this.mode,handler:()=>{this.mode=\"replace\",this.active=!0}},{icon:\"bk-tool-icon-append-mode\",tooltip:\"Append to the current selection (Shift)\",active:()=>\"append\"==this.mode,handler:()=>{this.mode=\"append\",this.active=!0}},{icon:\"bk-tool-icon-intersect-mode\",tooltip:\"Intersect with the current selection (Ctrl)\",active:()=>\"intersect\"==this.mode,handler:()=>{this.mode=\"intersect\",this.active=!0}},{icon:\"bk-tool-icon-subtract-mode\",tooltip:\"Subtract from the current selection (Shift+Ctrl)\",active:()=>\"subtract\"==this.mode,handler:()=>{this.mode=\"subtract\",this.active=!0}},null,{icon:\"bk-tool-icon-clear-selection\",tooltip:\"Clear the current selection (Esc)\",handler:()=>{this.clear.emit()}}]}}s.SelectTool=b,o=b,b.__name__=\"SelectTool\",o.define((({String:e,Array:t,Ref:s,Or:n,Auto:r})=>({renderers:[n(t(s(l.DataRenderer)),r),\"auto\"],names:[t(e),[]],mode:[_.SelectionMode,\"replace\"]})))},\n", - " function _(t,o,e,s,i){var n;s();const _=t(223),a=t(116),l=t(20),r=t(228);class h extends _.GestureToolView{_match_aspect(t,o,e){const s=e.bbox.aspect,i=e.bbox.h_range.end,n=e.bbox.h_range.start,_=e.bbox.v_range.end,a=e.bbox.v_range.start;let l=Math.abs(t[0]-o[0]),r=Math.abs(t[1]-o[1]);const h=0==r?0:l/r,[c]=h>=s?[1,h/s]:[s/h,1];let m,p,d,b;return t[0]<=o[0]?(m=t[0],p=t[0]+l*c,p>i&&(p=i)):(p=t[0],m=t[0]-l*c,m_&&(d=_)):(d=t[1],b=t[1]-l/s,bnew a.BoxAnnotation({level:\"overlay\",top_units:\"screen\",left_units:\"screen\",bottom_units:\"screen\",right_units:\"screen\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:2,line_dash:[4,4]});class m extends _.GestureTool{constructor(t){super(t),this.tool_name=\"Box Zoom\",this.icon=r.tool_icon_box_zoom,this.event_type=\"pan\",this.default_order=20}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}e.BoxZoomTool=m,n=m,m.__name__=\"BoxZoomTool\",n.prototype.default_view=h,n.define((({Boolean:t,Ref:o})=>({dimensions:[l.Dimensions,\"both\"],overlay:[o(a.BoxAnnotation),c],match_aspect:[t,!1],origin:[l.BoxOrigin,\"corner\"]}))),n.register_alias(\"box_zoom\",(()=>new m({dimensions:\"both\"}))),n.register_alias(\"xbox_zoom\",(()=>new m({dimensions:\"width\"}))),n.register_alias(\"ybox_zoom\",(()=>new m({dimensions:\"height\"})))},\n", - " function _(s,e,t,o,_){var l;o();const i=s(378),a=s(217),c=s(381),n=s(43),h=s(228);class r extends i.SelectToolView{constructor(){super(...arguments),this.sxs=[],this.sys=[]}connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,(()=>this._active_change()))}_active_change(){this.model.active||this._clear_overlay()}_keyup(s){s.keyCode==n.Keys.Enter&&this._clear_overlay()}_pan_start(s){this.sxs=[],this.sys=[];const{sx:e,sy:t}=s;this._append_overlay(e,t)}_pan(s){const[e,t]=this.plot_view.frame.bbox.clip(s.sx,s.sy);this._append_overlay(e,t),this.model.select_every_mousemove&&this._do_select(this.sxs,this.sys,!1,this._select_mode(s))}_pan_end(s){const{sxs:e,sys:t}=this;this._clear_overlay(),this._do_select(e,t,!0,this._select_mode(s)),this.plot_view.state.push(\"lasso_select\",{selection:this.plot_view.get_selection()})}_append_overlay(s,e){const{sxs:t,sys:o}=this;t.push(s),o.push(e),this.model.overlay.update({xs:t,ys:o})}_clear_overlay(){this.sxs=[],this.sys=[],this.model.overlay.update({xs:this.sxs,ys:this.sys})}_do_select(s,e,t,o){const _={type:\"poly\",sx:s,sy:e};this._select(_,t,o)}}t.LassoSelectToolView=r,r.__name__=\"LassoSelectToolView\";class y extends i.SelectTool{constructor(s){super(s),this.tool_name=\"Lasso Select\",this.icon=h.tool_icon_lasso_select,this.event_type=\"pan\",this.default_order=12}}t.LassoSelectTool=y,l=y,y.__name__=\"LassoSelectTool\",l.prototype.default_view=r,l.define((({Boolean:s,Ref:e})=>({select_every_mousemove:[s,!0],overlay:[e(a.PolyAnnotation),c.DEFAULT_POLY_OVERLAY]}))),l.register_alias(\"lasso_select\",(()=>new y))},\n", - " function _(e,t,s,l,o){var i;l();const a=e(378),_=e(217),c=e(43),n=e(9),h=e(228);class y extends a.SelectToolView{initialize(){super.initialize(),this.data={sx:[],sy:[]}}connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,(()=>this._active_change()))}_active_change(){this.model.active||this._clear_data()}_keyup(e){e.keyCode==c.Keys.Enter&&this._clear_data()}_doubletap(e){this._do_select(this.data.sx,this.data.sy,!0,this._select_mode(e)),this.plot_view.state.push(\"poly_select\",{selection:this.plot_view.get_selection()}),this._clear_data()}_clear_data(){this.data={sx:[],sy:[]},this.model.overlay.update({xs:[],ys:[]})}_tap(e){const{sx:t,sy:s}=e;this.plot_view.frame.bbox.contains(t,s)&&(this.data.sx.push(t),this.data.sy.push(s),this.model.overlay.update({xs:(0,n.copy)(this.data.sx),ys:(0,n.copy)(this.data.sy)}))}_do_select(e,t,s,l){const o={type:\"poly\",sx:e,sy:t};this._select(o,s,l)}}s.PolySelectToolView=y,y.__name__=\"PolySelectToolView\";s.DEFAULT_POLY_OVERLAY=()=>new _.PolyAnnotation({level:\"overlay\",xs_units:\"screen\",ys_units:\"screen\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:2,line_dash:[4,4]});class d extends a.SelectTool{constructor(e){super(e),this.tool_name=\"Poly Select\",this.icon=h.tool_icon_polygon_select,this.event_type=\"tap\",this.default_order=11}}s.PolySelectTool=d,i=d,d.__name__=\"PolySelectTool\",i.prototype.default_view=y,i.define((({Ref:e})=>({overlay:[e(_.PolyAnnotation),s.DEFAULT_POLY_OVERLAY]}))),i.register_alias(\"poly_select\",(()=>new d))},\n", - " function _(e,t,s,i,r){var n;i();const _=e(20),d=e(383),o=e(228);class l extends d.LineToolView{constructor(){super(...arguments),this._drawing=!1}_doubletap(e){if(!this.model.active)return;const t=this.model.renderers;for(const s of t){1==this._select_event(e,\"replace\",[s]).length&&(this._selected_renderer=s)}this._show_intersections(),this._update_line_cds()}_show_intersections(){if(!this.model.active)return;if(null==this._selected_renderer)return;if(!this.model.renderers.length)return this._set_intersection([],[]),this._selected_renderer=null,void(this._drawing=!1);const e=this._selected_renderer.data_source,t=this._selected_renderer.glyph,[s,i]=[t.x.field,t.y.field],r=e.get_array(s),n=e.get_array(i);this._set_intersection(r,n)}_tap(e){const t=this.model.intersection_renderer;if(null==this._map_drag(e.sx,e.sy,t))return;if(this._drawing&&this._selected_renderer){const s=this._select_mode(e);if(0==this._select_event(e,s,[t]).length)return}const s=this._select_mode(e);this._select_event(e,s,[t]),this._select_event(e,s,this.model.renderers)}_update_line_cds(){if(null==this._selected_renderer)return;const e=this.model.intersection_renderer.glyph,t=this.model.intersection_renderer.data_source,[s,i]=[e.x.field,e.y.field];if(s&&i){const e=t.data[s],r=t.data[i];this._selected_renderer.data_source.data[s]=e,this._selected_renderer.data_source.data[i]=r}this._emit_cds_changes(this._selected_renderer.data_source,!0,!0,!1)}_pan_start(e){this._select_event(e,\"append\",[this.model.intersection_renderer]),this._basepoint=[e.sx,e.sy]}_pan(e){null!=this._basepoint&&(this._drag_points(e,[this.model.intersection_renderer],this.model.dimensions),this._selected_renderer&&this._selected_renderer.data_source.change.emit())}_pan_end(e){null!=this._basepoint&&(this._drag_points(e,[this.model.intersection_renderer]),this._emit_cds_changes(this.model.intersection_renderer.data_source,!1,!0,!0),this._selected_renderer&&this._emit_cds_changes(this._selected_renderer.data_source),this._basepoint=null)}activate(){this._drawing=!0}deactivate(){this._selected_renderer&&(this._drawing&&(this._drawing=!1),this._hide_intersections())}}s.LineEditToolView=l,l.__name__=\"LineEditToolView\";class h extends d.LineTool{constructor(e){super(e),this.tool_name=\"Line Edit Tool\",this.icon=o.tool_icon_line_edit,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=4}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}s.LineEditTool=h,n=h,h.__name__=\"LineEditTool\",n.prototype.default_view=l,n.define((()=>({dimensions:[_.Dimensions,\"both\"]})))},\n", - " function _(e,i,n,t,s){var o;t();const r=e(8),_=e(370);class d extends _.EditToolView{_set_intersection(e,i){const n=this.model.intersection_renderer.glyph,t=this.model.intersection_renderer.data_source,[s,o]=[n.x.field,n.y.field];s&&((0,r.isArray)(e)?t.data[s]=e:n.x={value:e}),o&&((0,r.isArray)(i)?t.data[o]=i:n.y={value:i}),this._emit_cds_changes(t,!0,!0,!1)}_hide_intersections(){this._set_intersection([],[])}}n.LineToolView=d,d.__name__=\"LineToolView\";class a extends _.EditTool{constructor(e){super(e)}}n.LineTool=a,o=a,a.__name__=\"LineTool\",o.define((({AnyRef:e})=>({intersection_renderer:[e()]})))},\n", - " function _(t,s,n,e,i){e();const o=t(1);var a;const _=t(223),l=t(20),r=(0,o.__importStar)(t(228));function h(t,s,n){const e=new Map;for(const[i,o]of t){const[t,a]=o.r_invert(s,n);e.set(i,{start:t,end:a})}return e}n.update_ranges=h;class d extends _.GestureToolView{_pan_start(t){var s;this.last_dx=0,this.last_dy=0;const{sx:n,sy:e}=t,i=this.plot_view.frame.bbox;if(!i.contains(n,e)){const t=i.h_range,s=i.v_range;(nt.end)&&(this.v_axis_only=!0),(es.end)&&(this.h_axis_only=!0)}null===(s=this.model.document)||void 0===s||s.interactive_start(this.plot_model)}_pan(t){var s;this._update(t.deltaX,t.deltaY),null===(s=this.model.document)||void 0===s||s.interactive_start(this.plot_model)}_pan_end(t){this.h_axis_only=!1,this.v_axis_only=!1,null!=this.pan_info&&this.plot_view.state.push(\"pan\",{range:this.pan_info}),this.plot_view.trigger_ranges_update_event()}_update(t,s){const n=this.plot_view.frame,e=t-this.last_dx,i=s-this.last_dy,o=n.bbox.h_range,a=o.start-e,_=o.end-e,l=n.bbox.v_range,r=l.start-i,d=l.end-i,p=this.model.dimensions;let c,u,m,v,x,g;\"width\"!=p&&\"both\"!=p||this.v_axis_only?(c=o.start,u=o.end,m=0):(c=a,u=_,m=-e),\"height\"!=p&&\"both\"!=p||this.h_axis_only?(v=l.start,x=l.end,g=0):(v=r,x=d,g=-i),this.last_dx=t,this.last_dy=s;const{x_scales:w,y_scales:y}=n,f=h(w,c,u),b=h(y,v,x);this.pan_info={xrs:f,yrs:b,sdx:m,sdy:g},this.plot_view.update_range(this.pan_info,{panning:!0})}}n.PanToolView=d,d.__name__=\"PanToolView\";class p extends _.GestureTool{constructor(t){super(t),this.tool_name=\"Pan\",this.event_type=\"pan\",this.default_order=10}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}n.PanTool=p,a=p,p.__name__=\"PanTool\",a.prototype.default_view=d,a.define((()=>({dimensions:[l.Dimensions,\"both\",{on_update(t,s){switch(t){case\"both\":s.icon=r.tool_icon_pan;break;case\"width\":s.icon=r.tool_icon_xpan;break;case\"height\":s.icon=r.tool_icon_ypan}}}]}))),a.register_alias(\"pan\",(()=>new p({dimensions:\"both\"}))),a.register_alias(\"xpan\",(()=>new p({dimensions:\"width\"}))),a.register_alias(\"ypan\",(()=>new p({dimensions:\"height\"})))},\n", - " function _(e,t,i,s,n){var l;s();const a=e(116),r=e(58),o=e(19),_=e(223),h=e(228);function d(e){switch(e){case 1:return 2;case 2:return 1;case 4:return 5;case 5:return 4;default:return e}}function u(e,t,i,s){if(null==t)return!1;const n=i.compute(t);return Math.abs(e-n)n.right)&&(l=!1)}if(null!=n.bottom&&null!=n.top){const e=s.invert(t);(en.top)&&(l=!1)}return l}function g(e,t,i){let s=0;return e>=i.start&&e<=i.end&&(s+=1),t>=i.start&&t<=i.end&&(s+=1),s}function y(e,t,i,s){const n=t.compute(e),l=t.invert(n+i);return l>=s.start&&l<=s.end?l:e}function f(e,t,i){return e>t.start?(t.end=e,i):(t.end=t.start,t.start=e,d(i))}function v(e,t,i){return e=o&&(e.start=a,e.end=r)}i.flip_side=d,i.is_near=u,i.is_inside=c,i.sides_inside=g,i.compute_value=y,i.update_range_end_side=f,i.update_range_start_side=v,i.update_range=m;class p extends _.GestureToolView{initialize(){super.initialize(),this.side=0,this.model.update_overlay_from_ranges()}connect_signals(){super.connect_signals(),null!=this.model.x_range&&this.connect(this.model.x_range.change,(()=>this.model.update_overlay_from_ranges())),null!=this.model.y_range&&this.connect(this.model.y_range.change,(()=>this.model.update_overlay_from_ranges()))}_pan_start(e){this.last_dx=0,this.last_dy=0;const t=this.model.x_range,i=this.model.y_range,{frame:s}=this.plot_view,n=s.x_scale,l=s.y_scale,r=this.model.overlay,{left:o,right:_,top:h,bottom:d}=r,g=this.model.overlay.line_width+a.EDGE_TOLERANCE;null!=t&&this.model.x_interaction&&(u(e.sx,o,n,g)?this.side=1:u(e.sx,_,n,g)?this.side=2:c(e.sx,e.sy,n,l,r)&&(this.side=3)),null!=i&&this.model.y_interaction&&(0==this.side&&u(e.sy,d,l,g)&&(this.side=4),0==this.side&&u(e.sy,h,l,g)?this.side=5:c(e.sx,e.sy,n,l,this.model.overlay)&&(3==this.side?this.side=7:this.side=6))}_pan(e){const t=this.plot_view.frame,i=e.deltaX-this.last_dx,s=e.deltaY-this.last_dy,n=this.model.x_range,l=this.model.y_range,a=t.x_scale,r=t.y_scale;if(null!=n)if(3==this.side||7==this.side)m(n,a,i,t.x_range);else if(1==this.side){const e=y(n.start,a,i,t.x_range);this.side=v(e,n,this.side)}else if(2==this.side){const e=y(n.end,a,i,t.x_range);this.side=f(e,n,this.side)}if(null!=l)if(6==this.side||7==this.side)m(l,r,s,t.y_range);else if(4==this.side){const e=y(l.start,r,s,t.y_range);this.side=v(e,l,this.side)}else if(5==this.side){const e=y(l.end,r,s,t.y_range);this.side=f(e,l,this.side)}this.last_dx=e.deltaX,this.last_dy=e.deltaY}_pan_end(e){this.side=0,this.plot_view.trigger_ranges_update_event()}}i.RangeToolView=p,p.__name__=\"RangeToolView\";const x=()=>new a.BoxAnnotation({level:\"overlay\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:.5,line_dash:[2,2]});class w extends _.GestureTool{constructor(e){super(e),this.tool_name=\"Range Tool\",this.icon=h.tool_icon_range,this.event_type=\"pan\",this.default_order=1}initialize(){super.initialize(),this.overlay.in_cursor=\"grab\",this.overlay.ew_cursor=null!=this.x_range&&this.x_interaction?\"ew-resize\":null,this.overlay.ns_cursor=null!=this.y_range&&this.y_interaction?\"ns-resize\":null}update_overlay_from_ranges(){null==this.x_range&&null==this.y_range&&(this.overlay.left=null,this.overlay.right=null,this.overlay.bottom=null,this.overlay.top=null,o.logger.warn(\"RangeTool not configured with any Ranges.\")),null==this.x_range?(this.overlay.left=null,this.overlay.right=null):(this.overlay.left=this.x_range.start,this.overlay.right=this.x_range.end),null==this.y_range?(this.overlay.bottom=null,this.overlay.top=null):(this.overlay.bottom=this.y_range.start,this.overlay.top=this.y_range.end)}}i.RangeTool=w,l=w,w.__name__=\"RangeTool\",l.prototype.default_view=p,l.define((({Boolean:e,Ref:t,Nullable:i})=>({x_range:[i(t(r.Range1d)),null],x_interaction:[e,!0],y_range:[i(t(r.Range1d)),null],y_interaction:[e,!0],overlay:[t(a.BoxAnnotation),x]})))},\n", - " function _(e,t,s,o,i){var l;o();const a=e(378),n=e(20),c=e(228);class _ extends a.SelectToolView{_tap(e){\"tap\"==this.model.gesture&&this._handle_tap(e)}_doubletap(e){\"doubletap\"==this.model.gesture&&this._handle_tap(e)}_handle_tap(e){const{sx:t,sy:s}=e,o={type:\"point\",sx:t,sy:s};this._select(o,!0,this._select_mode(e))}_select(e,t,s){const{callback:o}=this.model;if(\"select\"==this.model.behavior){const i=this._computed_renderers_by_data_source();for(const[,l]of i){const i=l[0].get_selection_manager(),a=l.map((e=>this.plot_view.renderer_view(e))).filter((e=>null!=e));if(i.select(a,e,t,s)&&null!=o){const t=a[0].coordinates.x_scale.invert(e.sx),s=a[0].coordinates.y_scale.invert(e.sy),l={geometries:Object.assign(Object.assign({},e),{x:t,y:s}),source:i.source};o.execute(this.model,l)}}this._emit_selection_event(e),this.plot_view.state.push(\"tap\",{selection:this.plot_view.get_selection()})}else for(const t of this.computed_renderers){const s=this.plot_view.renderer_view(t);if(null==s)continue;const i=t.get_selection_manager();if(i.inspect(s,e)&&null!=o){const t=s.coordinates.x_scale.invert(e.sx),l=s.coordinates.y_scale.invert(e.sy),a={geometries:Object.assign(Object.assign({},e),{x:t,y:l}),source:i.source};o.execute(this.model,a)}}}}s.TapToolView=_,_.__name__=\"TapToolView\";class r extends a.SelectTool{constructor(e){super(e),this.tool_name=\"Tap\",this.icon=c.tool_icon_tap_select,this.event_type=\"tap\",this.default_order=10}}s.TapTool=r,l=r,r.__name__=\"TapTool\",l.prototype.default_view=_,l.define((({Any:e,Enum:t,Nullable:s})=>({behavior:[n.TapBehavior,\"select\"],gesture:[t(\"tap\",\"doubletap\"),\"tap\"],callback:[s(e)]}))),l.register_alias(\"click\",(()=>new r({behavior:\"inspect\"}))),l.register_alias(\"tap\",(()=>new r)),l.register_alias(\"doubletap\",(()=>new r({gesture:\"doubletap\"})))},\n", - " function _(e,t,s,n,i){var a;n();const o=e(223),l=e(20),_=e(228),r=e(384);class h extends o.GestureToolView{_scroll(e){let t=this.model.speed*e.delta;t>.9?t=.9:t<-.9&&(t=-.9),this._update_ranges(t)}_update_ranges(e){var t;const{frame:s}=this.plot_view,n=s.bbox.h_range,i=s.bbox.v_range,[a,o]=[n.start,n.end],[l,_]=[i.start,i.end];let h,d,p,c;switch(this.model.dimension){case\"height\":{const t=Math.abs(_-l);h=a,d=o,p=l-t*e,c=_-t*e;break}case\"width\":{const t=Math.abs(o-a);h=a-t*e,d=o-t*e,p=l,c=_;break}}const{x_scales:g,y_scales:u}=s,w={xrs:(0,r.update_ranges)(g,h,d),yrs:(0,r.update_ranges)(u,p,c),factor:e};this.plot_view.state.push(\"wheel_pan\",{range:w}),this.plot_view.update_range(w,{scrolling:!0}),null===(t=this.model.document)||void 0===t||t.interactive_start(this.plot_model,(()=>this.plot_view.trigger_ranges_update_event()))}}s.WheelPanToolView=h,h.__name__=\"WheelPanToolView\";class d extends o.GestureTool{constructor(e){super(e),this.tool_name=\"Wheel Pan\",this.icon=_.tool_icon_wheel_pan,this.event_type=\"scroll\",this.default_order=12}get tooltip(){return this._get_dim_tooltip(this.dimension)}}s.WheelPanTool=d,a=d,d.__name__=\"WheelPanTool\",a.prototype.default_view=h,a.define((()=>({dimension:[l.Dimension,\"width\"]}))),a.internal((({Number:e})=>({speed:[e,.001]}))),a.register_alias(\"xwheel_pan\",(()=>new d({dimension:\"width\"}))),a.register_alias(\"ywheel_pan\",(()=>new d({dimension:\"height\"})))},\n", - " function _(e,o,t,s,i){var n;s();const l=e(223),_=e(368),h=e(20),a=e(27),r=e(228);class m extends l.GestureToolView{_pinch(e){const{sx:o,sy:t,scale:s,ctrlKey:i,shiftKey:n}=e;let l;l=s>=1?20*(s-1):-20/s,this._scroll({type:\"wheel\",sx:o,sy:t,delta:l,ctrlKey:i,shiftKey:n})}_scroll(e){var o;const{frame:t}=this.plot_view,s=t.bbox.h_range,i=t.bbox.v_range,{sx:n,sy:l}=e,h=this.model.dimensions,a=(\"width\"==h||\"both\"==h)&&s.startthis.plot_view.trigger_ranges_update_event()))}}t.WheelZoomToolView=m,m.__name__=\"WheelZoomToolView\";class d extends l.GestureTool{constructor(e){super(e),this.tool_name=\"Wheel Zoom\",this.icon=r.tool_icon_wheel_zoom,this.event_type=a.is_mobile?\"pinch\":\"scroll\",this.default_order=10}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}t.WheelZoomTool=d,n=d,d.__name__=\"WheelZoomTool\",n.prototype.default_view=m,n.define((({Boolean:e,Number:o})=>({dimensions:[h.Dimensions,\"both\"],maintain_focus:[e,!0],zoom_on_axis:[e,!0],speed:[o,1/600]}))),n.register_alias(\"wheel_zoom\",(()=>new d({dimensions:\"both\"}))),n.register_alias(\"xwheel_zoom\",(()=>new d({dimensions:\"width\"}))),n.register_alias(\"ywheel_zoom\",(()=>new d({dimensions:\"height\"})))},\n", - " function _(i,e,s,t,o){var n;t();const l=i(232),a=i(219),h=i(20),r=i(13),_=i(228);class c extends l.InspectToolView{_move(i){if(!this.model.active)return;const{sx:e,sy:s}=i;this.plot_view.frame.bbox.contains(e,s)?this._update_spans(e,s):this._update_spans(null,null)}_move_exit(i){this._update_spans(null,null)}_update_spans(i,e){const s=this.model.dimensions;\"width\"!=s&&\"both\"!=s||(this.model.spans.width.location=e),\"height\"!=s&&\"both\"!=s||(this.model.spans.height.location=i)}}s.CrosshairToolView=c,c.__name__=\"CrosshairToolView\";class p extends l.InspectTool{constructor(i){super(i),this.tool_name=\"Crosshair\",this.icon=_.tool_icon_crosshair}get tooltip(){return this._get_dim_tooltip(this.dimensions)}get synthetic_renderers(){return(0,r.values)(this.spans)}}s.CrosshairTool=p,n=p,p.__name__=\"CrosshairTool\",(()=>{function i(i,e){return new a.Span({for_hover:!0,dimension:e,location_units:\"screen\",level:\"overlay\",line_color:i.line_color,line_width:i.line_width,line_alpha:i.line_alpha})}n.prototype.default_view=c,n.define((({Alpha:i,Number:e,Color:s})=>({dimensions:[h.Dimensions,\"both\"],line_color:[s,\"black\"],line_width:[e,1],line_alpha:[i,1]}))),n.internal((({Struct:e,Ref:s})=>({spans:[e({width:s(a.Span),height:s(a.Span)}),e=>({width:i(e,\"width\"),height:i(e,\"height\")})]}))),n.register_alias(\"crosshair\",(()=>new p))})()},\n", - " function _(e,s,t,r,n){var o;r();const a=e(53),u=e(13),c=e(34);class i extends a.Model{constructor(e){super(e)}get values(){return(0,u.values)(this.args)}_make_code(e,s,t,r){return new Function(...(0,u.keys)(this.args),e,s,t,(0,c.use_strict)(r))}format(e,s,t){return this._make_code(\"value\",\"format\",\"special_vars\",this.code)(...this.values,e,s,t)}}t.CustomJSHover=i,o=i,i.__name__=\"CustomJSHover\",o.define((({Unknown:e,String:s,Dict:t})=>({args:[t(e),{}],code:[s,\"\"]})))},\n", - " function _(e,t,n,s,o){s();const i=e(1);var r;const l=e(232),a=e(390),c=e(241),_=e(175),d=e(339),p=e(176),h=e(177),u=e(283),m=(0,i.__importStar)(e(185)),y=e(152),f=e(43),v=e(22),x=e(13),w=e(234),g=e(8),b=e(113),k=e(20),C=e(228),S=e(15),T=e(66),$=(0,i.__importStar)(e(242)),R=e(392);function M(e,t,n,s,o,i){const r={x:o[e],y:i[e]},l={x:o[e+1],y:i[e+1]};let a,c;if(\"span\"==t.type)\"h\"==t.direction?(a=Math.abs(r.x-n),c=Math.abs(l.x-n)):(a=Math.abs(r.y-s),c=Math.abs(l.y-s));else{const e={x:n,y:s};a=m.dist_2_pts(r,e),c=m.dist_2_pts(l,e)}return adelete this._template_el)),this.on_change([e,t,n],(async()=>await this._update_ttmodels()))}async _update_ttmodels(){const{_ttmodels:e,computed_renderers:t}=this;e.clear();const{tooltips:n}=this.model;if(null!=n)for(const t of this.computed_renderers){const s=new c.Tooltip({custom:(0,g.isString)(n)||(0,g.isFunction)(n),attachment:this.model.attachment,show_arrow:this.model.show_arrow});t instanceof _.GlyphRenderer?e.set(t,s):t instanceof d.GraphRenderer&&(e.set(t.node_renderer,s),e.set(t.edge_renderer,s))}const s=await(0,b.build_views)(this._ttviews,[...e.values()],{parent:this.plot_view});for(const e of s)e.render();const o=[...function*(){for(const e of t)e instanceof _.GlyphRenderer?yield e:e instanceof d.GraphRenderer&&(yield e.node_renderer,yield e.edge_renderer)}()],i=this._slots.get(this._update);if(null!=i){const e=new Set(o.map((e=>e.data_source)));S.Signal.disconnect_receiver(this,i,e)}for(const e of o)this.connect(e.data_source.inspect,this._update)}get computed_renderers(){const{renderers:e,names:t}=this.model,n=this.plot_model.data_renderers;return(0,T.compute_renderers)(e,n,t)}get ttmodels(){return this._ttmodels}_clear(){this._inspect(1/0,1/0);for(const[,e]of this.ttmodels)e.clear()}_move(e){if(!this.model.active)return;const{sx:t,sy:n}=e;this.plot_view.frame.bbox.contains(t,n)?this._inspect(t,n):this._clear()}_move_exit(){this._clear()}_inspect(e,t){let n;if(\"mouse\"==this.model.mode)n={type:\"point\",sx:e,sy:t};else{n={type:\"span\",direction:\"vline\"==this.model.mode?\"h\":\"v\",sx:e,sy:t}}for(const e of this.computed_renderers){const t=e.get_selection_manager(),s=this.plot_view.renderer_view(e);null!=s&&t.inspect(s,n)}this._emit_callback(n)}_update([e,{geometry:t}]){var n,s;if(!this.model.active)return;if(\"point\"!=t.type&&\"span\"!=t.type)return;if(!(e instanceof _.GlyphRenderer))return;if(\"ignore\"==this.model.muted_policy&&e.muted)return;const o=this.ttmodels.get(e);if(null==o)return;const i=e.get_selection_manager(),r=i.inspectors.get(e),l=e.view.convert_selection_to_subset(r);if(r.is_empty())return void o.clear();const a=i.source,c=this.plot_view.renderer_view(e);if(null==c)return;const{sx:d,sy:p}=t,m=c.coordinates.x_scale,y=c.coordinates.y_scale,v=m.invert(d),w=y.invert(p),{glyph:g}=c,b=[];if(g instanceof h.LineView)for(const n of l.line_indices){let s,o,i=g._x[n+1],r=g._y[n+1],c=n;switch(this.model.line_policy){case\"interp\":[i,r]=g.get_interpolation_hit(n,t),s=m.compute(i),o=y.compute(r);break;case\"prev\":[[s,o],c]=G(g.sx,g.sy,n);break;case\"next\":[[s,o],c]=G(g.sx,g.sy,n+1);break;case\"nearest\":[[s,o],c]=M(n,t,d,p,g.sx,g.sy),i=g._x[c],r=g._y[c];break;default:[s,o]=[d,p]}const _={index:c,x:v,y:w,sx:d,sy:p,data_x:i,data_y:r,rx:s,ry:o,indices:l.line_indices,name:e.name};b.push([s,o,this._render_tooltips(a,c,_)])}for(const t of r.image_indices){const n={index:t.index,x:v,y:w,sx:d,sy:p,name:e.name},s=this._render_tooltips(a,t,n);b.push([d,p,s])}for(const o of l.indices)if(g instanceof u.MultiLineView&&!(0,x.isEmpty)(l.multiline_indices))for(const n of l.multiline_indices[o.toString()]){let s,i,r,c=g._xs.get(o)[n],h=g._ys.get(o)[n],u=n;switch(this.model.line_policy){case\"interp\":[c,h]=g.get_interpolation_hit(o,n,t),s=m.compute(c),i=y.compute(h);break;case\"prev\":[[s,i],u]=G(g.sxs.get(o),g.sys.get(o),n);break;case\"next\":[[s,i],u]=G(g.sxs.get(o),g.sys.get(o),n+1);break;case\"nearest\":[[s,i],u]=M(n,t,d,p,g.sxs.get(o),g.sys.get(o)),c=g._xs.get(o)[u],h=g._ys.get(o)[u];break;default:throw new Error(\"shouldn't have happened\")}r=e instanceof _.GlyphRenderer?e.view.convert_indices_from_subset([o])[0]:o;const f={index:r,x:v,y:w,sx:d,sy:p,data_x:c,data_y:h,segment_index:u,indices:l.multiline_indices,name:e.name};b.push([s,i,this._render_tooltips(a,r,f)])}else{const t=null===(n=g._x)||void 0===n?void 0:n[o],i=null===(s=g._y)||void 0===s?void 0:s[o];let r,c,h;if(\"snap_to_data\"==this.model.point_policy){let e=g.get_anchor_point(this.model.anchor,o,[d,p]);if(null==e&&(e=g.get_anchor_point(\"center\",o,[d,p]),null==e))continue;r=e.x,c=e.y}else[r,c]=[d,p];h=e instanceof _.GlyphRenderer?e.view.convert_indices_from_subset([o])[0]:o;const u={index:h,x:v,y:w,sx:d,sy:p,data_x:t,data_y:i,indices:l.indices,name:e.name};b.push([r,c,this._render_tooltips(a,h,u)])}if(0==b.length)o.clear();else{const{content:e}=o;(0,f.empty)(o.content);for(const[,,t]of b)null!=t&&e.appendChild(t);const[t,n]=b[b.length-1];o.setv({position:[t,n]},{check_eq:!1})}}_emit_callback(e){const{callback:t}=this.model;if(null!=t)for(const n of this.computed_renderers){if(!(n instanceof _.GlyphRenderer))continue;const s=this.plot_view.renderer_view(n);if(null==s)continue;const{x_scale:o,y_scale:i}=s.coordinates,r=o.invert(e.sx),l=i.invert(e.sy),a=n.data_source.inspected;t.execute(this.model,{geometry:Object.assign({x:r,y:l},e),renderer:n,index:a})}}_create_template(e){const t=(0,f.div)({style:{display:\"table\",borderSpacing:\"2px\"}});for(const[n]of e){const e=(0,f.div)({style:{display:\"table-row\"}});t.appendChild(e);const s=(0,f.div)({style:{display:\"table-cell\"},class:$.tooltip_row_label},0!=n.length?`${n}: `:\"\");e.appendChild(s);const o=(0,f.span)();o.dataset.value=\"\";const i=(0,f.span)({class:$.tooltip_color_block},\" \");i.dataset.swatch=\"\",(0,f.undisplay)(i);const r=(0,f.div)({style:{display:\"table-cell\"},class:$.tooltip_row_value},o,i);e.appendChild(r)}return t}_render_template(e,t,n,s,o){const i=e.cloneNode(!0),r=i.querySelectorAll(\"[data-value]\"),l=i.querySelectorAll(\"[data-swatch]\"),a=/\\$color(\\[.*\\])?:(\\w*)/,c=/\\$swatch:(\\w*)/;for(const[[,e],i]of(0,w.enumerate)(t)){const t=e.match(c),_=e.match(a);if(null!=t||null!=_){if(null!=t){const[,e]=t,o=n.get_column(e);if(null==o)r[i].textContent=`${e} unknown`;else{const e=(0,g.isNumber)(s)?o[s]:null;null!=e&&(l[i].style.backgroundColor=(0,v.color2css)(e),(0,f.display)(l[i]))}}if(null!=_){const[,e=\"\",t]=_,o=n.get_column(t);if(null==o){r[i].textContent=`${t} unknown`;continue}const a=e.indexOf(\"hex\")>=0,c=e.indexOf(\"swatch\")>=0,d=(0,g.isNumber)(s)?o[s]:null;if(null==d){r[i].textContent=\"(null)\";continue}r[i].textContent=a?(0,v.color2hex)(d):(0,v.color2css)(d),c&&(l[i].style.backgroundColor=(0,v.color2css)(d),(0,f.display)(l[i]))}}else{const t=(0,y.replace_placeholders)(e.replace(\"$~\",\"$data_\"),n,s,this.model.formatters,o);if((0,g.isString)(t))r[i].textContent=t;else for(const e of t)r[i].appendChild(e)}}return i}_render_tooltips(e,t,n){var s;const{tooltips:o}=this.model;if((0,g.isString)(o)){const s=(0,y.replace_placeholders)({html:o},e,t,this.model.formatters,n);return(0,f.div)(s)}if((0,g.isFunction)(o))return o(e,n);if(o instanceof R.Template)return this._template_view.update(e,t,n),this._template_view.el;if(null!=o){const i=null!==(s=this._template_el)&&void 0!==s?s:this._template_el=this._create_template(o);return this._render_template(i,o,e,t,n)}return null}}n.HoverToolView=z,z.__name__=\"HoverToolView\";class A extends l.InspectTool{constructor(e){super(e),this.tool_name=\"Hover\",this.icon=C.tool_icon_hover}}n.HoverTool=A,r=A,A.__name__=\"HoverTool\",r.prototype.default_view=z,r.define((({Any:e,Boolean:t,String:n,Array:s,Tuple:o,Dict:i,Or:r,Ref:l,Function:c,Auto:_,Nullable:d})=>({tooltips:[d(r(l(R.Template),n,s(o(n,n)),c())),[[\"index\",\"$index\"],[\"data (x, y)\",\"($x, $y)\"],[\"screen (x, y)\",\"($sx, $sy)\"]]],formatters:[i(r(l(a.CustomJSHover),y.FormatterType)),{}],renderers:[r(s(l(p.DataRenderer)),_),\"auto\"],names:[s(n),[]],mode:[k.HoverMode,\"mouse\"],muted_policy:[k.MutedPolicy,\"show\"],point_policy:[k.PointPolicy,\"snap_to_data\"],line_policy:[k.LinePolicy,\"nearest\"],show_arrow:[t,!0],anchor:[k.Anchor,\"center\"],attachment:[k.TooltipAttachment,\"horizontal\"],callback:[d(e)]}))),r.register_alias(\"hover\",(()=>new A))},\n", - " function _(e,t,s,n,a){n();const l=e(1);var i,_,o,r,c,d,p,u,m,w,f,h,x;const v=e(53),y=e(309),V=e(393);a(\"Styles\",V.Styles);const g=e(43),T=e(42),b=e(226),R=e(113),D=e(8),M=e(13),S=(0,l.__importStar)(e(242)),O=e(152);class C extends b.DOMView{}s.DOMNodeView=C,C.__name__=\"DOMNodeView\";class z extends v.Model{constructor(e){super(e)}}s.DOMNode=z,z.__name__=\"DOMNode\",z.__module__=\"bokeh.models.dom\";class P extends C{render(){super.render(),this.el.textContent=this.model.content}_createElement(){return document.createTextNode(\"\")}}s.TextView=P,P.__name__=\"TextView\";class A extends z{constructor(e){super(e)}}s.Text=A,i=A,A.__name__=\"Text\",i.prototype.default_view=P,i.define((({String:e})=>({content:[e,\"\"]})));class N extends C{}s.PlaceholderView=N,N.__name__=\"PlaceholderView\",N.tag_name=\"span\";class E extends z{constructor(e){super(e)}}s.Placeholder=E,_=E,E.__name__=\"Placeholder\",_.define((({})=>({})));class G extends N{update(e,t,s){this.el.textContent=t.toString()}}s.IndexView=G,G.__name__=\"IndexView\";class I extends E{constructor(e){super(e)}}s.Index=I,o=I,I.__name__=\"Index\",o.prototype.default_view=G,o.define((({})=>({})));class k extends N{update(e,t,s){const n=(0,O._get_column_value)(this.model.field,e,t),a=null==n?\"???\":`${n}`;this.el.textContent=a}}s.ValueRefView=k,k.__name__=\"ValueRefView\";class $ extends E{constructor(e){super(e)}}s.ValueRef=$,r=$,$.__name__=\"ValueRef\",r.prototype.default_view=k,r.define((({String:e})=>({field:[e]})));class B extends k{render(){super.render(),this.value_el=(0,g.span)(),this.swatch_el=(0,g.span)({class:S.tooltip_color_block},\" \"),this.el.appendChild(this.value_el),this.el.appendChild(this.swatch_el)}update(e,t,s){const n=(0,O._get_column_value)(this.model.field,e,t),a=null==n?\"???\":`${n}`;this.el.textContent=a}}s.ColorRefView=B,B.__name__=\"ColorRefView\";class L extends ${constructor(e){super(e)}}s.ColorRef=L,c=L,L.__name__=\"ColorRef\",c.prototype.default_view=B,c.define((({Boolean:e})=>({hex:[e,!0],swatch:[e,!0]})));class j extends C{constructor(){super(...arguments),this.child_views=new Map}async lazy_initialize(){await super.lazy_initialize();const e=this.model.children.filter((e=>e instanceof v.Model));await(0,R.build_views)(this.child_views,e,{parent:this})}render(){super.render();const{style:e}=this.model;if(null!=e)if(e instanceof V.Styles)for(const t of e){const e=t.get_value();if((0,D.isString)(e)){const s=t.attr.replace(/_/g,\"-\");this.el.style.hasOwnProperty(s)&&this.el.style.setProperty(s,e)}}else for(const[t,s]of(0,M.entries)(e)){const e=t.replace(/_/g,\"-\");this.el.style.hasOwnProperty(e)&&this.el.style.setProperty(e,s)}for(const e of this.model.children)if((0,D.isString)(e)){const t=document.createTextNode(e);this.el.appendChild(t)}else{this.child_views.get(e).renderTo(this.el)}}}s.DOMElementView=j,j.__name__=\"DOMElementView\";class q extends z{constructor(e){super(e)}}s.DOMElement=q,d=q,q.__name__=\"DOMElement\",d.define((({String:e,Array:t,Dict:s,Or:n,Nullable:a,Ref:l})=>({style:[a(n(l(V.Styles),s(e))),null],children:[t(n(e,l(z),l(y.LayoutDOM))),[]]})));class F extends T.View{}s.ActionView=F,F.__name__=\"ActionView\";class H extends v.Model{constructor(e){super(e)}}s.Action=H,p=H,H.__name__=\"Action\",H.__module__=\"bokeh.models.dom\",p.define((({})=>({})));class J extends j{constructor(){super(...arguments),this.action_views=new Map}async lazy_initialize(){await super.lazy_initialize(),await(0,R.build_views)(this.action_views,this.model.actions,{parent:this})}remove(){(0,R.remove_views)(this.action_views),super.remove()}update(e,t,s={}){!function n(a){for(const l of a.child_views.values())l instanceof N?l.update(e,t,s):l instanceof j&&n(l)}(this);for(const n of this.action_views.values())n.update(e,t,s)}}s.TemplateView=J,J.__name__=\"TemplateView\",J.tag_name=\"div\";class K extends q{}s.Template=K,u=K,K.__name__=\"Template\",u.prototype.default_view=J,u.define((({Array:e,Ref:t})=>({actions:[e(t(H)),[]]})));class Q extends j{}s.SpanView=Q,Q.__name__=\"SpanView\",Q.tag_name=\"span\";class U extends q{}s.Span=U,m=U,U.__name__=\"Span\",m.prototype.default_view=Q;class W extends j{}s.DivView=W,W.__name__=\"DivView\",W.tag_name=\"div\";class X extends q{}s.Div=X,w=X,X.__name__=\"Div\",w.prototype.default_view=W;class Y extends j{}s.TableView=Y,Y.__name__=\"TableView\",Y.tag_name=\"table\";class Z extends q{}s.Table=Z,f=Z,Z.__name__=\"Table\",f.prototype.default_view=Y;class ee extends j{}s.TableRowView=ee,ee.__name__=\"TableRowView\",ee.tag_name=\"tr\";class te extends q{}s.TableRow=te,h=te,te.__name__=\"TableRow\",h.prototype.default_view=ee;const se=e(41),ne=e(234);class ae extends F{update(e,t,s){for(const[e,s]of(0,ne.enumerate)(this.model.groups))e.visible=t==s}}s.ToggleGroupView=ae,ae.__name__=\"ToggleGroupView\";class le extends H{constructor(e){super(e)}}s.ToggleGroup=le,x=le,le.__name__=\"ToggleGroup\",x.prototype.default_view=ae,x.define((({Array:e,Ref:t})=>({groups:[e(t(se.RendererGroup)),[]]})))},\n", - " function _(l,n,u,_,e){var t;_();const o=l(53);class r extends 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- " function _(t,o,e,n,s){var i;n();const l=t(15),c=t(53),r=t(224),a=t(232),u=t(234);class h extends c.Model{constructor(t){super(t)}get button_view(){return this.tools[0].button_view}get event_type(){return this.tools[0].event_type}get tooltip(){return this.tools[0].tooltip}get tool_name(){return this.tools[0].tool_name}get icon(){return this.tools[0].computed_icon}get computed_icon(){return this.icon}get toggleable(){const t=this.tools[0];return t instanceof a.InspectTool&&t.toggleable}initialize(){super.initialize(),this.do=new l.Signal0(this,\"do\")}connect_signals(){super.connect_signals(),this.connect(this.do,(()=>this.doit())),this.connect(this.properties.active.change,(()=>this.set_active()));for(const t of this.tools)this.connect(t.properties.active.change,(()=>{this.active=t.active}))}doit(){for(const t of this.tools)t.do.emit()}set_active(){for(const t of this.tools)t.active=this.active}get menu(){const{menu:t}=this.tools[0];if(null==t)return null;const o=[];for(const[e,n]of(0,u.enumerate)(t))if(null==e)o.push(null);else{const t=()=>{var t,o,e;for(const s of this.tools)null===(e=null===(o=null===(t=s.menu)||void 0===t?void 0:t[n])||void 0===o?void 0:o.handler)||void 0===e||e.call(o)};o.push(Object.assign(Object.assign({},e),{handler:t}))}return o}}e.ToolProxy=h,i=h,h.__name__=\"ToolProxy\",i.define((({Boolean:t,Array:o,Ref:e})=>({tools:[o(e(r.ButtonTool)),[]],active:[t,!1],disabled:[t,!1]})))},\n", - " function _(o,t,s,e,i){var n,r;e();const l=o(20),c=o(9),h=o(13),a=o(233),_=o(221),p=o(394),u=o(309),f=o(207);class y extends a.ToolbarBase{constructor(o){super(o)}initialize(){super.initialize(),this._merge_tools()}_merge_tools(){this._proxied_tools=[];const o={},t={},s={},e=[],i=[];for(const o of this.help)(0,c.includes)(i,o.redirect)||(e.push(o),i.push(o.redirect));this._proxied_tools.push(...e),this.help=e;for(const[o,t]of(0,h.entries)(this.gestures)){o in s||(s[o]={});for(const e of t.tools)e.type in s[o]||(s[o][e.type]=[]),s[o][e.type].push(e)}for(const t of this.inspectors)t.type in o||(o[t.type]=[]),o[t.type].push(t);for(const o of this.actions)o.type in t||(t[o.type]=[]),t[o.type].push(o);const n=(o,t=!1)=>{const s=new p.ToolProxy({tools:o,active:t});return this._proxied_tools.push(s),s};for(const o of(0,h.keys)(s)){const t=this.gestures[o];t.tools=[];for(const e of(0,h.keys)(s[o])){const i=s[o][e];if(i.length>0)if(\"multi\"==o)for(const o of i){const s=n([o]);t.tools.push(s),this.connect(s.properties.active.change,(()=>this._active_change(s)))}else{const o=n(i);t.tools.push(o),this.connect(o.properties.active.change,(()=>this._active_change(o)))}}}this.actions=[];for(const[o,s]of(0,h.entries)(t))if(\"CustomAction\"==o)for(const o of s)this.actions.push(n([o]));else s.length>0&&this.actions.push(n(s));this.inspectors=[];for(const t of(0,h.values)(o))t.length>0&&this.inspectors.push(n(t,!0));for(const[o,t]of(0,h.entries)(this.gestures))0!=t.tools.length&&(t.tools=(0,c.sort_by)(t.tools,(o=>o.default_order)),\"pinch\"!=o&&\"scroll\"!=o&&\"multi\"!=o&&(t.tools[0].active=!0))}}s.ProxyToolbar=y,n=y,y.__name__=\"ProxyToolbar\",n.define((({Array:o,Ref:t})=>({toolbars:[o(t(_.Toolbar)),[]]})));class d extends u.LayoutDOMView{initialize(){this.model.toolbar.toolbar_location=this.model.toolbar_location,super.initialize()}get child_models(){return[this.model.toolbar]}_update_layout(){this.layout=new f.ContentBox(this.child_views[0].el);const{toolbar:o}=this.model;o.horizontal?this.layout.set_sizing({width_policy:\"fit\",min_width:100,height_policy:\"fixed\"}):this.layout.set_sizing({width_policy:\"fixed\",height_policy:\"fit\",min_height:100})}after_layout(){super.after_layout();const o=this.child_views[0];o.layout.bbox=this.layout.bbox,o.render()}}s.ToolbarBoxView=d,d.__name__=\"ToolbarBoxView\";class b extends u.LayoutDOM{constructor(o){super(o)}}s.ToolbarBox=b,r=b,b.__name__=\"ToolbarBox\",r.prototype.default_view=d,r.define((({Ref:o})=>({toolbar:[o(a.ToolbarBase)],toolbar_location:[l.Location,\"right\"]})))},\n", - " function _(e,n,r,t,o){t();const s=e(1),u=e(53),c=(0,s.__importStar)(e(21)),a=e(8),l=e(13);r.resolve_defs=function(e,n){var r,t,o,s;function i(e){return null!=e.module?`${e.module}.${e.name}`:e.name}function f(e){if((0,a.isString)(e))switch(e){case\"Any\":return c.Any;case\"Unknown\":return c.Unknown;case\"Boolean\":return c.Boolean;case\"Number\":return c.Number;case\"Int\":return c.Int;case\"String\":return c.String;case\"Null\":return c.Null}else switch(e[0]){case\"Nullable\":{const[,n]=e;return c.Nullable(f(n))}case\"Or\":{const[,...n]=e;return c.Or(...n.map(f))}case\"Tuple\":{const[,n,...r]=e;return c.Tuple(f(n),...r.map(f))}case\"Array\":{const[,n]=e;return c.Array(f(n))}case\"Struct\":{const[,...n]=e,r=n.map((([e,n])=>[e,f(n)]));return c.Struct((0,l.to_object)(r))}case\"Dict\":{const[,n]=e;return c.Dict(f(n))}case\"Map\":{const[,n,r]=e;return c.Map(f(n),f(r))}case\"Enum\":{const[,...n]=e;return c.Enum(...n)}case\"Ref\":{const[,r]=e,t=n.get(i(r));if(null!=t)return c.Ref(t);throw new Error(`${i(r)} wasn't defined before referencing it`)}case\"AnyRef\":return c.AnyRef()}}for(const c of e){const e=(()=>{if(null==c.extends)return u.Model;{const e=n.get(i(c.extends));if(null!=e)return e;throw new Error(`base model ${i(c.extends)} of ${i(c)} is not defined`)}})(),a=((s=class extends e{}).__name__=c.name,s.__module__=c.module,s);for(const e of null!==(r=c.properties)&&void 0!==r?r:[]){const n=f(null!==(t=e.kind)&&void 0!==t?t:\"Unknown\");a.define({[e.name]:[n,e.default]})}for(const e of null!==(o=c.overrides)&&void 0!==o?o:[])a.override({[e.name]:e.default});n.register(a)}}},\n", - " function _(n,e,t,o,i){o();const d=n(5),c=n(226),s=n(113),a=n(43),l=n(398);t.index={},t.add_document_standalone=async function(n,e,o=[],i=!1){const u=new Map;async function f(i){let d;const f=n.roots().indexOf(i),r=o[f];null!=r?d=r:e.classList.contains(l.BOKEH_ROOT)?d=e:(d=(0,a.div)({class:l.BOKEH_ROOT}),e.appendChild(d));const w=await(0,s.build_view)(i,{parent:null});return w instanceof c.DOMView&&w.renderTo(d),u.set(i,w),t.index[i.id]=w,w}for(const e of n.roots())await f(e);return i&&(window.document.title=n.title()),n.on_change((n=>{n instanceof d.RootAddedEvent?f(n.model):n instanceof d.RootRemovedEvent?function(n){const e=u.get(n);null!=e&&(e.remove(),u.delete(n),delete t.index[n.id])}(n.model):i&&n instanceof d.TitleChangedEvent&&(window.document.title=n.title)})),[...u.values()]}},\n", - " function _(o,e,n,t,r){t();const l=o(43),d=o(44);function u(o){let e=document.getElementById(o);if(null==e)throw new Error(`Error rendering Bokeh model: could not find #${o} HTML tag`);if(!document.body.contains(e))throw new Error(`Error rendering Bokeh model: element #${o} must be under `);if(\"SCRIPT\"==e.tagName){const o=(0,l.div)({class:n.BOKEH_ROOT});(0,l.replaceWith)(e,o),e=o}return e}n.BOKEH_ROOT=d.root,n._resolve_element=function(o){const{elementid:e}=o;return null!=e?u(e):document.body},n._resolve_root_elements=function(o){const e=[];if(null!=o.root_ids&&null!=o.roots)for(const n of o.root_ids)e.push(u(o.roots[n]));return e}},\n", - " function _(n,o,t,s,e){s();const c=n(400),r=n(19),a=n(397);t._get_ws_url=function(n,o){let t,s=\"ws:\";return\"https:\"==window.location.protocol&&(s=\"wss:\"),null!=o?(t=document.createElement(\"a\"),t.href=o):t=window.location,null!=n?\"/\"==n&&(n=\"\"):n=t.pathname.replace(/\\/+$/,\"\"),`${s}//${t.host}${n}/ws`};const i={};t.add_document_from_session=async function(n,o,t,s=[],e=!1){const l=window.location.search.substr(1);let d;try{d=await function(n,o,t){const s=(0,c.parse_token)(o).session_id;n in i||(i[n]={});const e=i[n];return s in e||(e[s]=(0,c.pull_session)(n,o,t)),e[s]}(n,o,l)}catch(n){const t=(0,c.parse_token)(o).session_id;throw r.logger.error(`Failed to load Bokeh session ${t}: ${n}`),n}return(0,a.add_document_standalone)(d.document,t,s,e)}},\n", - " function _(e,s,n,t,o){t();const r=e(19),i=e(5),c=e(401),l=e(402),_=e(403);n.DEFAULT_SERVER_WEBSOCKET_URL=\"ws://localhost:5006/ws\",n.DEFAULT_TOKEN=\"eyJzZXNzaW9uX2lkIjogImRlZmF1bHQifQ\";let h=0;function a(e){let s=e.split(\".\")[0];const n=s.length%4;return 0!=n&&(s+=\"=\".repeat(4-n)),JSON.parse(atob(s.replace(/_/g,\"/\").replace(/-/g,\"+\")))}n.parse_token=a;class d{constructor(e=n.DEFAULT_SERVER_WEBSOCKET_URL,s=n.DEFAULT_TOKEN,t=null){this.url=e,this.token=s,this.args_string=t,this._number=h++,this.socket=null,this.session=null,this.closed_permanently=!1,this._current_handler=null,this._pending_replies=new Map,this._pending_messages=[],this._receiver=new l.Receiver,this.id=a(s).session_id.split(\".\")[0],r.logger.debug(`Creating websocket ${this._number} to '${this.url}' session '${this.id}'`)}async connect(){if(this.closed_permanently)throw new Error(\"Cannot connect() a closed ClientConnection\");if(null!=this.socket)throw new Error(\"Already connected\");this._current_handler=null,this._pending_replies.clear(),this._pending_messages=[];try{let e=`${this.url}`;return null!=this.args_string&&this.args_string.length>0&&(e+=`?${this.args_string}`),this.socket=new WebSocket(e,[\"bokeh\",this.token]),new Promise(((e,s)=>{this.socket.binaryType=\"arraybuffer\",this.socket.onopen=()=>this._on_open(e,s),this.socket.onmessage=e=>this._on_message(e),this.socket.onclose=e=>this._on_close(e,s),this.socket.onerror=()=>this._on_error(s)}))}catch(e){throw r.logger.error(`websocket creation failed to url: ${this.url}`),r.logger.error(` - ${e}`),e}}close(){this.closed_permanently||(r.logger.debug(`Permanently closing websocket connection ${this._number}`),this.closed_permanently=!0,null!=this.socket&&this.socket.close(1e3,`close method called on ClientConnection 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connection was already closed\"),s(new Error(\"The connection has been closed\"));else{const s=i.Document.from_json(n),t=i.Document._compute_patch_since_json(n,s);if(t.events.length>0){r.logger.debug(`Sending ${t.events.length} changes from model construction back to server`);const e=c.Message.create(\"PATCH-DOC\",{},t);this.send(e)}this.session=new _.ClientSession(this,s,this.id);for(const e of this._pending_messages)this.session.handle(e);this._pending_messages=[],r.logger.debug(\"Created a new session from new pulled doc\"),e(this.session)}else this.session.document.replace_with_json(n),r.logger.debug(\"Updated existing session with new pulled doc\")}catch(e){null===(n=console.trace)||void 0===n||n.call(console,e),r.logger.error(`Failed to repull session ${e}`),s(e instanceof Error?e:`${e}`)}}_on_open(e,s){r.logger.info(`Websocket connection ${this._number} is now 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this.request_server_info()}_document_changed(e){if(e.setter_id===this.id)return;const t=e instanceof c.DocumentEventBatch?e.events:[e],n=this.document.create_json_patch(t),s=i.Message.create(\"PATCH-DOC\",{},n);this._connection.send(s)}_handle_patch(e){this.document.apply_json_patch(e.content,e.buffers,this.id)}_handle_ok(e){_.logger.trace(`Unhandled OK reply to ${e.reqid()}`)}_handle_error(e){_.logger.error(`Unhandled ERROR reply to ${e.reqid()}: ${e.content.text}`)}}n.ClientSession=r,r.__name__=\"ClientSession\"},\n", - " function _(e,o,t,n,r){n();const s=e(1),l=e(5),i=e(402),a=e(19),c=e(43),g=e(13),f=e(397),u=e(398),m=(0,s.__importDefault)(e(44)),p=(0,s.__importDefault)(e(240)),d=(0,s.__importDefault)(e(405));function _(e,o){o.buffers.length>0?e.consume(o.buffers[0].buffer):e.consume(o.content.data);const t=e.message;null!=t&&this.apply_json_patch(t.content,t.buffers)}function b(e,o){if(\"undefined\"!=typeof Jupyter&&null!=Jupyter.notebook.kernel){a.logger.info(`Registering Jupyter 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t.def(e.shared.vao,\".currentVAO?\",e.shared.vao,\".currentVAO.count:-1\")}));return m}return null}(),h=l(br,!1);return{elements:s,primitive:m,count:p,instances:h,offset:d,vao:f,vaoActive:i,elementsActive:u,static:a}}(e,d),A=function(e,t){var r=e.static,n=e.dynamic,i={};return k.forEach((function(e){var o=E(e);function f(t,a){if(e in r){var f=t(r[e]);i[o]=an((function(){return f}))}else if(e in n){var u=n[e];i[o]=on(u,(function(e,t){return a(e,t,e.invoke(t,u))}))}}switch(e){case Nt:case It:case Vt:case er:case Mt:case ir:case Xt:case Kt:case Jt:case Gt:return f((function(r){return _.commandType(r,\"boolean\",e,t.commandStr),r}),(function(t,r,n){return _.optional((function(){t.assert(r,\"typeof \"+n+'===\"boolean\"',\"invalid flag \"+e,t.commandStr)})),n}));case Wt:return f((function(r){return _.commandParameter(r,$r,\"invalid \"+e,t.commandStr),$r[r]}),(function(t,r,n){var a=t.constants.compareFuncs;return _.optional((function(){t.assert(r,n+\" in \"+a,\"invalid \"+e+\", must be one of 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_.optional((function(){e.assert(t,e.shared.isArrayLike+\"(\"+r+\")&&\"+r+\".length===4\",\"blend.color must be a 4d array\")})),V(4,(function(e){return t.def(\"+\",r,\"[\",e,\"]\")}))}));case tr:return f((function(e){return _.commandType(e,\"number\",o,t.commandStr),0|e}),(function(e,t,r){return _.optional((function(){e.assert(t,\"typeof \"+r+'===\"number\"',\"invalid stencil.mask\")})),t.def(r,\"|0\")}));case rr:return f((function(r){_.commandType(r,\"object\",o,t.commandStr);var n=r.cmp||\"keep\",a=r.ref||0,i=\"mask\"in r?r.mask:-1;return _.commandParameter(n,$r,e+\".cmp\",t.commandStr),_.commandType(a,\"number\",e+\".ref\",t.commandStr),_.commandType(i,\"number\",e+\".mask\",t.commandStr),[$r[n],a,i]}),(function(e,t,r){var n=e.constants.compareFuncs;return _.optional((function(){function a(){e.assert(t,Array.prototype.join.call(arguments,\"\"),\"invalid stencil.func\")}a(r+\"&&typeof \",r,'===\"object\"'),a('!(\"cmp\" in ',r,\")||(\",r,\".cmp in \",n,\")\")})),[t.def('\"cmp\" in 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_.commandType(r,\"number\",o+\".factor\",t.commandStr),_.commandType(n,\"number\",o+\".units\",t.commandStr),[r,n]}),(function(t,r,n){return _.optional((function(){t.assert(r,n+\"&&typeof \"+n+'===\"object\"',\"invalid \"+e)})),[r.def(n,\".factor|0\"),r.def(n,\".units|0\")]}));case qt:return f((function(e){var r=0;return\"front\"===e?r=Hr:\"back\"===e&&(r=Nr),_.command(!!r,o,t.commandStr),r}),(function(e,t,r){return _.optional((function(){e.assert(t,r+'===\"front\"||'+r+'===\"back\"',\"invalid cull.face\")})),t.def(r,'===\"front\"?',Hr,\":\",Nr)}));case Yt:return f((function(e){return _.command(\"number\"==typeof e&&e>=a.lineWidthDims[0]&&e<=a.lineWidthDims[1],\"invalid line width, must be a positive number between \"+a.lineWidthDims[0]+\" and \"+a.lineWidthDims[1],t.commandStr),e}),(function(e,t,r){return _.optional((function(){e.assert(t,\"typeof \"+r+'===\"number\"&&'+r+\">=\"+a.lineWidthDims[0]+\"&&\"+r+\"<=\"+a.lineWidthDims[1],\"invalid line width\")})),r}));case Qt:return f((function(e){return _.commandParameter(e,Zr,o,t.commandStr),Zr[e]}),(function(e,t,r){return _.optional((function(){e.assert(t,r+'===\"cw\"||'+r+'===\"ccw\"',\"invalid frontFace, must be one of cw,ccw\")})),t.def(r+'===\"cw\"?2304:'+qr)}));case Ht:return f((function(e){return _.command(me(e)&&4===e.length,\"color.mask must be length 4 array\",t.commandStr),e.map((function(e){return!!e}))}),(function(e,t,r){return _.optional((function(){e.assert(t,e.shared.isArrayLike+\"(\"+r+\")&&\"+r+\".length===4\",\"invalid color.mask\")})),V(4,(function(e){return\"!!\"+r+\"[\"+e+\"]\"}))}));case Zt:return f((function(e){_.command(\"object\"==typeof e&&e,o,t.commandStr);var r=\"value\"in e?e.value:1,n=!!e.invert;return _.command(\"number\"==typeof r&&r>=0&&r<=1,\"sample.coverage.value must be a number between 0 and 1\",t.commandStr),[r,n]}),(function(e,t,r){return _.optional((function(){e.assert(t,r+\"&&typeof \"+r+'===\"object\"',\"invalid sample.coverage\")})),[t.def('\"value\" in 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t=x[e];t&&(A[e]=t)}O(fr),O(E(or));var T=Object.keys(A).length>0,D={framebuffer:y,draw:w,shader:S,state:A,dirty:T,scopeVAO:null,drawVAO:null,useVAO:!1,attributes:{}};if(D.profile=function(e){var t,r=e.static,n=e.dynamic;if(ur in r){var a=!!r[ur];(t=an((function(e,t){return a}))).enable=a}else if(ur in n){var i=n[ur];t=on(i,(function(e,t){return e.invoke(t,i)}))}return t}(e),D.uniforms=function(e,t){var r=e.static,n=e.dynamic,a={};return Object.keys(r).forEach((function(e){var n,i=r[e];if(\"number\"==typeof i||\"boolean\"==typeof i)n=an((function(){return i}));else if(\"function\"==typeof i){var o=i._reglType;\"texture2d\"===o||\"textureCube\"===o?n=an((function(e){return e.link(i)})):\"framebuffer\"===o||\"framebufferCube\"===o?(_.command(i.color.length>0,'missing color attachment for framebuffer sent to uniform \"'+e+'\"',t.commandStr),n=an((function(e){return e.link(i.color[0])}))):_.commandRaise('invalid data for uniform \"'+e+'\"',t.commandStr)}else me(i)?n=an((function(t){return 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e=0;e=0},read:z,destroy:function(){I.length=0,le(),V&&(V.removeEventListener(cn,de),V.removeEventListener(ln,me)),k.clear(),E.clear(),O.clear(),A.clear(),S.clear(),w.clear(),x.clear(),m&&m.clear(),q.forEach((function(e){e()}))},_gl:a,_refresh:xe,poll:function(){ye(),m&&m.update()},now:we,stats:l});return n.onDone(null,Ae),Ae}},\"object\"==typeof r&&void 0!==t?t.exports=o():\"function\"==typeof define&&define.amd?define(o):i.createREGL=o()},\n", - " 413: function _(t,e,s,a,r){a();const n=t(414),_=t(12);class o{constructor(t){this._regl=t,this._map=new Map}_create_texture(t){const e=t.length;let s=0;const a=[];let r=0,_=0;for(let n=0;nc[f+1]&&f++;const a=t[f],n=c[f]+.5*a;let o=.5*a-Math.abs(s-n);f%2==1&&(o=-o),m[e]=Math.round(255*(o-r)/(_-r))}return[[s,u,r,_],this._regl.texture({shape:[l,1,1],data:m,wrapS:\"repeat\",format:\"alpha\",type:\"uint8\",mag:\"linear\",min:\"linear\"})]}_get_key(t){return t.join(\",\")}_get_or_create(t){const e=this._get_key(t);let s=this._map.get(e);if(null==s){const a=(0,n.gcd)(t);if(a>1){t=(0,_.map)(t,(t=>t/a)),s=this._get_or_create(t);const[r,n,o]=s;s=[r,n,a],this._map.set(e,s)}else{const[r,n]=this._create_texture(t);s=[r,n,a],this._map.set(e,s)}}return s}get(t){return t.length%2==1&&(t=t.slice(0,-1)),this._get_or_create(t)}}s.DashCache=o,o.__name__=\"DashCache\"},\n", - " 414: function _(n,t,e,r,o){function u(n,t){let e,r;n>t?(e=n,r=t):(e=t,r=n);let o=e%r;for(;0!=o;)e=r,r=o,o=e%r;return r}r(),e.gcd=function(n){let t=n[0];for(let e=1;e u_miter_limit);\\n miter_too_large_end = (miter_factor_end > u_miter_limit);\\n }\\n\\n float sign_at_start = -sign(a_position.x); // +ve at segment start, -ve end.\\n vec2 point = sign_at_start > 0.0 ? a_point_start : a_point_end;\\n vec2 adjacent_point =\\n sign_at_start > 0.0 ? (has_start_cap ? a_point_start : a_point_prev)\\n : (has_end_cap ? a_point_end : a_point_next);\\n\\n if ( (has_start_cap && sign_at_start > 0.0) ||\\n (has_end_cap && sign_at_start < 0.0) ) {\\n // Cap.\\n xy = point - segment_right*(halfwidth*a_position.y);\\n if (cap_type == butt_cap)\\n xy -= sign_at_start*0.5*u_antialias*segment_along;\\n else\\n xy -= sign_at_start*halfwidth*segment_along;\\n }\\n else { // Join.\\n // +ve if turning to right, -ve if to left.\\n float turn_sign = sign_at_start > 0.0 ? turn_right_start : turn_right_end;\\n\\n vec2 adjacent_right = sign_at_start*normalize(right_vector(point - adjacent_point));\\n vec2 point_right = normalize(segment_right + adjacent_right);\\n float miter_factor = sign_at_start > 0.0 ? miter_factor_start : miter_factor_end;\\n bool miter_too_large = sign_at_start > 0.0 ? miter_too_large_start : miter_too_large_end;\\n\\n if (abs(a_position.x) > 1.5) {\\n // Outer point, meets prev/next segment.\\n float factor; // multiplied by halfwidth...\\n\\n if (join_type == bevel_join || (join_type == miter_join && miter_too_large))\\n factor = 1.0 / miter_factor; // cos_theta.\\n else if (join_type == round_join &&\\n miter_factor > min_miter_factor_round_join_mesh)\\n factor = 1.0;\\n else // miter, or round (small angle only).\\n factor = miter_factor;\\n\\n xy = point - point_right*(halfwidth*turn_sign*factor);\\n v_coords.y = turn_sign*halfwidth*factor / miter_factor;\\n }\\n else if (turn_sign*a_position.y < 0.0) {\\n // Inner point, meets prev/next segment.\\n float len = halfwidth*miter_factor;\\n float segment_len = v_segment_length;\\n float adjacent_len = distance(point, adjacent_point);\\n\\n if (len <= min(segment_len, adjacent_len))\\n // Normal behaviour.\\n xy = point - point_right*(len*a_position.y);\\n else\\n // For short wide line segments the inner point using the above\\n // calculation can be outside of the line. Here clipping it.\\n xy = point + segment_right*(halfwidth*turn_sign);\\n }\\n else {\\n // Point along outside edge.\\n xy = point - segment_right*(halfwidth*a_position.y);\\n if (join_type == round_join &&\\n miter_factor > min_miter_factor_round_join_mesh) {\\n xy = line_intersection(xy, segment_along,\\n point - turn_sign*point_right*halfwidth,\\n right_vector(point_right));\\n }\\n }\\n }\\n\\n vec2 pos = xy + 0.5; // Bokeh's offset.\\n pos /= u_canvas_size / u_pixel_ratio; // in 0..1\\n gl_Position = vec4(2.0*pos.x - 1.0, 1.0 - 2.0*pos.y, 0.0, 1.0);\\n\\n v_coords.x = dot(xy - a_point_start, segment_along);\\n v_flags = float(int(has_start_cap) +\\n 2*int(has_end_cap) +\\n 4*int(miter_too_large_start) +\\n 8*int(miter_too_large_end));\\n v_cos_theta_turn_right_start = cos_theta_start*turn_right_start;\\n v_cos_theta_turn_right_end = cos_theta_end*turn_right_end;\\n\\n#ifdef DASHED\\n v_length_so_far = a_length_so_far;\\n#endif\\n}\\n\"},\n", - " 416: function _(n,t,a,i,e){i();a.default=\"\\nprecision mediump float;\\n\\nconst int butt_cap = 0;\\nconst int round_cap = 1;\\nconst int square_cap = 2;\\n\\nconst int miter_join = 0;\\nconst int round_join = 1;\\nconst int bevel_join = 2;\\n\\nuniform float u_linewidth;\\nuniform float u_antialias;\\nuniform float u_line_join;\\nuniform float u_line_cap;\\nuniform vec4 u_line_color;\\n#ifdef DASHED\\nuniform sampler2D u_dash_tex;\\nuniform vec4 u_dash_tex_info;\\nuniform float u_dash_scale;\\nuniform float u_dash_offset;\\n#endif\\n\\nvarying float v_segment_length;\\nvarying vec2 v_coords;\\nvarying float v_flags;\\nvarying float v_cos_theta_turn_right_start;\\nvarying float v_cos_theta_turn_right_end;\\n#ifdef DASHED\\nvarying float v_length_so_far;\\n#endif\\n\\nfloat cross_z(in vec2 v0, in vec2 v1)\\n{\\n return v0.x*v1.y - v0.y*v1.x;\\n}\\n\\nfloat point_line_side(in vec2 point, in vec2 start, in vec2 end)\\n{\\n // +ve if point to right of line.\\n // Alternatively could do dot product with right_vector.\\n return cross_z(point - start, end - start);\\n}\\n\\nfloat point_line_distance(in vec2 point, in vec2 start, in vec2 end)\\n{\\n return point_line_side(point, start, end) / distance(start, end);\\n}\\n\\nvec2 right_vector(in vec2 v)\\n{\\n return vec2(v.y, -v.x);\\n}\\n\\nfloat bevel_join_distance(in float sign_start, in float halfwidth)\\n{\\n float cos_theta_turn_right = sign_start > 0.0 ? v_cos_theta_turn_right_start\\n : v_cos_theta_turn_right_end;\\n float cos_theta = abs(cos_theta_turn_right);\\n float turn_right = sign(cos_theta_turn_right);\\n float distance_along = sign_start > 0.0 ? 0.0 : v_segment_length;\\n\\n // In v_coords reference frame (x is along segment, y across).\\n vec2 line_start = vec2(distance_along, halfwidth*turn_right);\\n float sin_alpha = cos_theta;\\n float cos_alpha = sqrt(1.0 - sin_alpha*sin_alpha);\\n vec2 line_along = vec2(-sign_start*turn_right*sin_alpha, -cos_alpha);\\n\\n return halfwidth + sign_start*point_line_distance(\\n v_coords, line_start, line_start+line_along);\\n}\\n\\nfloat cap(in int cap_type, in float x, in float y)\\n{\\n // x is distance along segment in direction away from end of segment,\\n // y is distance across segment.\\n if (cap_type == butt_cap)\\n return max(0.5*u_linewidth - x, abs(y));\\n else if (cap_type == square_cap)\\n return max(-x, abs(y));\\n else // cap_type == round_cap\\n return distance(vec2(min(x, 0.0), y), vec2(0.0, 0.0));\\n}\\n\\nfloat distance_to_alpha(in float dist)\\n{\\n return 1.0 - smoothstep(0.5*(u_linewidth - u_antialias),\\n 0.5*(u_linewidth + u_antialias), dist);\\n}\\n\\n#ifdef DASHED\\nfloat dash_distance(in float x)\\n{\\n // x is in direction of v_coords.x, i.e. along segment.\\n float tex_length = u_dash_tex_info.x;\\n float tex_offset = u_dash_tex_info.y;\\n float tex_dist_min = u_dash_tex_info.z;\\n float tex_dist_max = u_dash_tex_info.w;\\n\\n // Apply offset.\\n x += v_length_so_far - u_dash_scale*tex_offset + u_dash_offset;\\n\\n // Interpolate within texture to obtain distance to dash.\\n float dist = texture2D(u_dash_tex,\\n vec2(x / (tex_length*u_dash_scale), 0.0)).a;\\n\\n // Scale distance within min and max limits.\\n dist = tex_dist_min + dist*(tex_dist_max - tex_dist_min);\\n\\n return u_dash_scale*dist;\\n}\\n\\nmat2 rotation_matrix(in float sign_start)\\n{\\n // Rotation matrix for v_coords from this segment to prev or next segment.\\n float cos_theta_turn_right = sign_start > 0.0 ? v_cos_theta_turn_right_start\\n : v_cos_theta_turn_right_end;\\n float cos_theta = abs(cos_theta_turn_right);\\n float turn_right = sign(cos_theta_turn_right);\\n\\n float sin_theta = sqrt(1.0 - cos_theta*cos_theta)*sign_start*turn_right;\\n float cos_2theta = 2.0*cos_theta*cos_theta - 1.0;\\n float sin_2theta = 2.0*sin_theta*cos_theta;\\n return mat2(cos_2theta, -sin_2theta, sin_2theta, cos_2theta);\\n}\\n#endif\\n\\nvoid main()\\n{\\n int join_type = int(u_line_join + 0.5);\\n int cap_type = int(u_line_cap + 0.5);\\n float halfwidth = 0.5*(u_linewidth + u_antialias);\\n\\n // Extract flags.\\n int flags = int(v_flags + 0.5);\\n bool miter_too_large_end = (flags / 8 > 0);\\n flags -= 8*int(miter_too_large_end);\\n bool miter_too_large_start = (flags / 4 > 0);\\n flags -= 4*int(miter_too_large_start);\\n bool has_end_cap = (flags / 2 > 0);\\n flags -= 2*int(has_end_cap);\\n bool has_start_cap = flags > 0;\\n\\n float dist = v_coords.y; // For straight segment, and miter join.\\n\\n if (v_coords.x <= 0.5*u_antialias) {\\n // At start of segment, either cap or join.\\n if (has_start_cap)\\n dist = cap(cap_type, v_coords.x, v_coords.y);\\n else if (join_type == round_join)\\n dist = distance(v_coords, vec2(0.0, 0.0));\\n else if (join_type == bevel_join ||\\n (join_type == miter_join && miter_too_large_start))\\n dist = max(abs(dist), bevel_join_distance(1.0, halfwidth));\\n // else a miter join which uses the default dist calculation.\\n }\\n else if (v_coords.x >= v_segment_length - 0.5*u_antialias) {\\n // At end of segment, either cap or join.\\n if (has_end_cap)\\n dist = cap(cap_type, v_segment_length - v_coords.x, v_coords.y);\\n else if (join_type == round_join)\\n dist = distance(v_coords, vec2(v_segment_length, 0));\\n else if ((join_type == bevel_join ||\\n (join_type == miter_join && miter_too_large_end)))\\n dist = max(abs(dist), bevel_join_distance(-1.0, halfwidth));\\n // else a miter join which uses the default dist calculation.\\n }\\n\\n float alpha = distance_to_alpha(abs(dist));\\n\\n#ifdef DASHED\\n if (u_dash_tex_info.x >= 0.0) {\\n // Dashes in straight segments (outside of joins) are easily calculated.\\n dist = dash_distance(v_coords.x);\\n\\n if (!has_start_cap && cap_type == butt_cap) {\\n if (v_coords.x < 0.5*u_antialias) {\\n // Outer of start join rendered solid color or not at all\\n // depending on whether corner point is in dash or gap, with\\n // antialiased ends.\\n dist = (dash_distance(0.0) > 0.0 ? 0.5*u_antialias - v_coords.x\\n : -0.5*u_linewidth);\\n\\n // Also consider antialiased end of dash just outside corner.\\n float end_dist = dash_distance(0.5*u_antialias) + v_coords.x -\\n 0.5*u_antialias;\\n dist = max(dist, end_dist);\\n }\\n\\n vec2 prev_coords = rotation_matrix(1.0)*v_coords;\\n\\n if (abs(prev_coords.y) < halfwidth &&\\n prev_coords.x < 0.5*u_antialias) {\\n // Extend dashes across from previous segment, with antialiased\\n // end.\\n float new_dist = dash_distance(min(prev_coords.x,\\n -0.5*u_antialias));\\n\\n if (prev_coords.x > -0.5*u_antialias)\\n new_dist -= prev_coords.x + 0.5*u_antialias;\\n\\n new_dist = min(new_dist, 0.5*u_linewidth - abs(prev_coords.y));\\n dist = max(dist, new_dist);\\n }\\n }\\n\\n if (!has_end_cap && cap_type == butt_cap) {\\n if (v_coords.x > v_segment_length - 0.5*u_antialias) {\\n // Similar for end join.\\n dist = (dash_distance(v_segment_length) > 0.0\\n ? v_coords.x - v_segment_length + 0.5*u_antialias\\n : -0.5*u_linewidth);\\n\\n float end_dist =\\n dash_distance(v_segment_length - 0.5*u_antialias) -\\n v_coords.x + v_segment_length - 0.5*u_antialias;\\n dist = max(dist, end_dist);\\n }\\n\\n vec2 next_coords =\\n rotation_matrix(-1.0)*(v_coords - vec2(v_segment_length, 0.0));\\n\\n if (abs(next_coords.y) < halfwidth &&\\n next_coords.x > -0.5*u_antialias) {\\n // Extend dashes across from next segment, with antialiased end.\\n float new_dist = dash_distance(v_segment_length +\\n max(next_coords.x, 0.5*u_antialias));\\n\\n if (next_coords.x < 0.5*u_antialias)\\n new_dist += next_coords.x - 0.5*u_antialias;\\n\\n new_dist = min(new_dist, 0.5*u_linewidth - abs(next_coords.y));\\n dist = max(dist, new_dist);\\n }\\n }\\n\\n dist = cap(cap_type, dist, v_coords.y);\\n\\n float dash_alpha = distance_to_alpha(dist);\\n alpha = min(alpha, dash_alpha);\\n }\\n#endif\\n\\n alpha = u_line_color.a*alpha;\\n gl_FragColor = vec4(u_line_color.rgb*alpha, alpha); // Premultiplied alpha.\\n}\\n\"},\n", - " 417: function _(n,i,o,a,t){a();o.default=\"\\nprecision mediump float;\\n\\nattribute vec2 a_position;\\nattribute vec2 a_center;\\nattribute float a_size;\\nattribute float a_angle; // in radians\\nattribute float a_linewidth;\\nattribute vec4 a_line_color;\\nattribute vec4 a_fill_color;\\nattribute float a_show;\\n\\nuniform float u_pixel_ratio;\\nuniform vec2 u_canvas_size;\\nuniform float u_antialias;\\n\\nvarying float v_linewidth;\\nvarying float v_size;\\nvarying vec4 v_line_color;\\nvarying vec4 v_fill_color;\\nvarying vec2 v_coords;\\n\\nvoid main()\\n{\\n v_size = a_size;\\n v_linewidth = a_linewidth;\\n v_line_color = a_line_color;\\n v_fill_color = a_fill_color;\\n\\n if (a_show < 0.5) {\\n // Do not show this marker.\\n gl_Position = vec4(-2.0, -2.0, 0.0, 1.0);\\n return;\\n }\\n\\n float enclosing_size = v_size + 2.0*v_linewidth + 3.0*u_antialias;\\n\\n // Coordinates in rotated frame with respect to center of marker, used in\\n // distance functions in fragment shader.\\n v_coords = a_position*enclosing_size;\\n\\n float c = cos(-a_angle);\\n float s = sin(-a_angle);\\n mat2 rotation = mat2(c, -s, s, c);\\n\\n vec2 pos = a_center + rotation*v_coords;\\n pos += 0.5; // make up for Bokeh's offset\\n pos /= u_canvas_size / u_pixel_ratio; // in 0..1\\n gl_Position = vec4(2.0*pos.x - 1.0, 1.0 - 2.0*pos.y, 0.0, 1.0);\\n}\\n\"},\n", - " 418: function _(n,a,e,t,s){t();e.default=\"\\nprecision mediump float;\\n\\nconst float SQRT_2 = 1.4142135623730951;\\nconst float SQRT_3 = sqrt(3.0);\\nconst float PI = 3.14159265358979323846264;\\n\\nconst float IN_ANGLE = 0.6283185307179586; // PI/5. = 36 degrees (star of 5 pikes)\\n//const float OUT_ANGLE = PI/2. - IN_ANGLE; // External angle for regular stars\\nconst float COS_A = 0.8090169943749475; // cos(IN_ANGLE)\\nconst float SIN_A = 0.5877852522924731; // sin(IN_ANGLE)\\nconst float COS_B = 0.5877852522924731; // cos(OUT_ANGLE)\\nconst float SIN_B = 0.8090169943749475; // sin(OUT_ANGLE)\\n\\nuniform float u_antialias;\\n\\nvarying vec4 v_line_color;\\nvarying vec4 v_fill_color;\\nvarying float v_linewidth;\\nvarying float v_size;\\nvarying vec2 v_coords;\\n\\n#ifdef USE_ASTERISK\\n// asterisk\\nfloat marker(vec2 P, float size)\\n{\\n // Masks\\n float diamond = max(abs(SQRT_2 / 2.0 * (P.x - P.y)), abs(SQRT_2 / 2.0 * (P.x + P.y))) - size / 2.0;\\n float square = max(abs(P.x), abs(P.y)) - size / 2.0;\\n // Shapes\\n float X = min(abs(P.x - P.y), abs(P.x + P.y));\\n float cross = min(abs(P.x), abs(P.y));\\n // Result is union of masked shapes\\n float result = min(max(X, diamond), max(cross, square));\\n return max(result - v_linewidth/2.0 + u_antialias/2.0, 0.0);\\n}\\n#endif\\n\\n#ifdef USE_CIRCLE\\n// circle\\nfloat marker(vec2 P, float size)\\n{\\n return length(P) - size/2.0;\\n}\\n#endif\\n\\n#ifdef USE_DOT\\nfloat marker(vec2 P, float size)\\n{\\n return max(length(P) - size/8.0 - v_linewidth/15.0 + u_antialias, 0.0);\\n}\\n#endif\\n\\n#ifdef USE_CIRCLE_DOT\\nfloat marker(vec2 P, float size)\\n{\\n float circle = length(P) - size/2.0;\\n float dot_ = min(size/8.0 + v_linewidth/15.0 - u_antialias - length(P), 0.0);\\n return max(circle, dot_);\\n}\\n#endif\\n\\n#ifdef USE_SQUARE\\n// square\\nfloat marker(vec2 P, float size)\\n{\\n return max(abs(P.x), abs(P.y)) - size/2.0;\\n}\\n#endif\\n\\n#ifdef USE_SQUARE_DOT\\nfloat marker(vec2 P, float size)\\n{\\n float square = max(abs(P.x), abs(P.y)) - size/2.0;\\n float dot_ = min(size/8.0 + v_linewidth/15.0 - u_antialias - length(P), 0.0);\\n return max(square, dot_);\\n}\\n#endif\\n\\n#ifdef USE_DIAMOND\\n// diamond\\nfloat marker(vec2 P, float size)\\n{\\n float x = SQRT_2 / 2.0 * (P.x * 1.5 - P.y);\\n float y = SQRT_2 / 2.0 * (P.x * 1.5 + P.y);\\n float r1 = max(abs(x), abs(y)) - size / (2.0 * SQRT_2);\\n return r1 / SQRT_2;\\n}\\n#endif\\n\\n#ifdef USE_DIAMOND_DOT\\nfloat marker(vec2 P, float size)\\n{\\n float x = SQRT_2 / 2.0 * (P.x * 1.5 - P.y);\\n float y = SQRT_2 / 2.0 * (P.x * 1.5 + P.y);\\n float r1 = max(abs(x), abs(y)) - size / (2.0 * SQRT_2);\\n float diamond = r1 / SQRT_2;\\n float dot_ = min(size/8.0 + v_linewidth/15.0 - u_antialias - length(P), 0.0);\\n return max(diamond, dot_);\\n}\\n#endif\\n\\n#ifdef USE_HEX\\n// hex\\nfloat marker(vec2 P, float size)\\n{\\n vec2 q = abs(P);\\n return max(q.y * 0.57735 + q.x - 1.0 * size/2.0, q.y - 0.866 * size/2.0);\\n}\\n#endif\\n\\n#ifdef USE_HEX_DOT\\nfloat marker(vec2 P, float size)\\n{\\n vec2 q = abs(P);\\n float hex = max(q.y * 0.57735 + q.x - 1.0 * size/2.0, q.y - 0.866 * size/2.0);\\n float dot_ = min(size/8.0 + v_linewidth/15.0 - u_antialias - length(P), 0.0);\\n return max(hex, dot_);\\n}\\n#endif\\n\\n#ifdef USE_STAR\\n// star\\n// https://iquilezles.org/www/articles/distfunctions2d/distfunctions2d.htm\\nfloat marker(vec2 P, float size)\\n{\\n float bn = mod(atan(P.x, -P.y), 2.0*IN_ANGLE) - IN_ANGLE;\\n P = length(P)*vec2(cos(bn), abs(sin(bn)));\\n P -= size*vec2(COS_A, SIN_A)/2.;\\n P += vec2(COS_B, SIN_B)*clamp(-(P.x*COS_B + P.y*SIN_B), 0.0, size*SIN_A/SIN_B/2.);\\n return length(P)*sign(P.x);\\n}\\n#endif\\n\\n#ifdef USE_STAR_DOT\\nfloat marker(vec2 P, float size)\\n{\\n float dot_ = min(size/8.0 + v_linewidth/15.0 - u_antialias - length(P), 0.0);\\n float bn = mod(atan(P.x, -P.y), 2.0*IN_ANGLE) - IN_ANGLE;\\n P = length(P)*vec2(cos(bn), abs(sin(bn)));\\n P -= size*vec2(COS_A, SIN_A)/2.;\\n P += vec2(COS_B, SIN_B)*clamp(-(P.x*COS_B + P.y*SIN_B), 0.0, size*SIN_A/SIN_B/2.);\\n float star = length(P)*sign(P.x);\\n return max(star, dot_);\\n}\\n#endif\\n\\n#ifdef USE_TRIANGLE\\n// triangle\\nfloat marker(vec2 P, float size)\\n{\\n P.y -= size * 0.3;\\n float x = SQRT_2 / 2.0 * (P.x * 1.7 - P.y);\\n float y = SQRT_2 / 2.0 * (P.x * 1.7 + P.y);\\n float r1 = max(abs(x), abs(y)) - size / 1.6;\\n float r2 = P.y;\\n return max(r1 / SQRT_2, r2); // Intersect diamond with rectangle\\n}\\n#endif\\n\\n#ifdef USE_TRIANGLE_DOT\\nfloat marker(vec2 P, float size)\\n{\\n float dot_ = min(size/8.0 + v_linewidth/15.0 - u_antialias - length(P), 0.0);\\n P.y -= size * 0.3;\\n float x = SQRT_2 / 2.0 * (P.x * 1.7 - P.y);\\n float y = SQRT_2 / 2.0 * (P.x * 1.7 + P.y);\\n float r1 = max(abs(x), abs(y)) - size / 1.6;\\n float r2 = P.y;\\n float triangle = max(r1 / SQRT_2, r2); // Intersect diamond with rectangle\\n return max(triangle, dot_);\\n}\\n#endif\\n\\n#ifdef USE_INVERTED_TRIANGLE\\n// inverted_triangle\\nfloat marker(vec2 P, float size)\\n{\\n P.y += size * 0.3;\\n float x = SQRT_2 / 2.0 * (P.x * 1.7 - P.y);\\n float y = SQRT_2 / 2.0 * (P.x * 1.7 + P.y);\\n float r1 = max(abs(x), abs(y)) - size / 1.6;\\n float r2 = - P.y;\\n return max(r1 / SQRT_2, r2); // Intersect diamond with rectangle\\n}\\n#endif\\n\\n#ifdef USE_CROSS\\n// cross\\nfloat marker(vec2 P, float size)\\n{\\n float square = max(abs(P.x), abs(P.y)) - size / 2.0;\\n float cross = min(abs(P.x), abs(P.y));\\n cross = max(cross - v_linewidth/2.0 + u_antialias/2.0, 0.0);\\n return max(square, cross);\\n}\\n#endif\\n\\n#ifdef USE_DASH\\nfloat marker(vec2 P, float size)\\n{\\n float square = max(abs(P.x), abs(P.y)) - size / 2.0;\\n float cross = abs(P.y);\\n cross = max(cross - v_linewidth/2.0 + u_antialias/2.0, 0.0);\\n return max(square, cross);\\n}\\n#endif\\n\\n#ifdef USE_CIRCLE_CROSS\\n// circle_cross\\nfloat marker(vec2 P, float size)\\n{\\n // Define quadrants\\n float qs = size / 2.0; // quadrant size\\n float s1 = max(abs(P.x - qs), abs(P.y - qs)) - qs;\\n float s2 = max(abs(P.x + qs), abs(P.y - qs)) - qs;\\n float s3 = max(abs(P.x - qs), abs(P.y + qs)) - qs;\\n float s4 = max(abs(P.x + qs), abs(P.y + qs)) - qs;\\n // Intersect main shape with quadrants (to form cross)\\n float circle = length(P) - size/2.0;\\n float c1 = max(circle, s1);\\n float c2 = max(circle, s2);\\n float c3 = max(circle, s3);\\n float c4 = max(circle, s4);\\n // Union\\n return min(min(min(c1, c2), c3), c4);\\n}\\n#endif\\n\\n#ifdef USE_SQUARE_CROSS\\n// square_cross\\nfloat marker(vec2 P, float size)\\n{\\n // Define quadrants\\n float qs = size / 2.0; // quadrant size\\n float s1 = max(abs(P.x - qs), abs(P.y - qs)) - qs;\\n float s2 = max(abs(P.x + qs), abs(P.y - qs)) - qs;\\n float s3 = max(abs(P.x - qs), abs(P.y + qs)) - qs;\\n float s4 = max(abs(P.x + qs), abs(P.y + qs)) - qs;\\n // Intersect main shape with quadrants (to form cross)\\n float square = max(abs(P.x), abs(P.y)) - size/2.0;\\n float c1 = max(square, s1);\\n float c2 = max(square, s2);\\n float c3 = max(square, s3);\\n float c4 = max(square, s4);\\n // Union\\n return min(min(min(c1, c2), c3), c4);\\n}\\n#endif\\n\\n#ifdef USE_DIAMOND_CROSS\\n// diamond_cross\\nfloat marker(vec2 P, float size)\\n{\\n // Define quadrants\\n float qs = size / 2.0; // quadrant size\\n float s1 = max(abs(P.x - qs), abs(P.y - qs)) - qs;\\n float s2 = max(abs(P.x + qs), abs(P.y - qs)) - qs;\\n float s3 = max(abs(P.x - qs), abs(P.y + qs)) - qs;\\n float s4 = max(abs(P.x + qs), abs(P.y + qs)) - qs;\\n // Intersect main shape with quadrants (to form cross)\\n float x = SQRT_2 / 2.0 * (P.x * 1.5 - P.y);\\n float y = SQRT_2 / 2.0 * (P.x * 1.5 + P.y);\\n float diamond = max(abs(x), abs(y)) - size / (2.0 * SQRT_2);\\n diamond /= SQRT_2;\\n float c1 = max(diamond, s1);\\n float c2 = max(diamond, s2);\\n float c3 = max(diamond, s3);\\n float c4 = max(diamond, s4);\\n // Union\\n return min(min(min(c1, c2), c3), c4);\\n}\\n#endif\\n\\n#ifdef USE_X\\n// x\\nfloat marker(vec2 P, float size)\\n{\\n float circle = length(P) - size / 2.0;\\n float X = min(abs(P.x - P.y), abs(P.x + P.y));\\n X = max(X - v_linewidth/2.0, 0.0);\\n return max(circle, X);\\n}\\n#endif\\n\\n#ifdef USE_Y\\nfloat marker(vec2 P, float size)\\n{\\n float circle = length(P) - size / 2.0;\\n\\n float dx = 1.0 / SQRT_3;\\n float dy = SQRT_2 / SQRT_3;\\n\\n // Sideways distance from the three spokes.\\n float d0 = abs(P.x);\\n float d1 = abs(dot(P, vec2(dx, dy)));\\n float d2 = abs(dot(P, vec2(dx, -dy)));\\n\\n // Clip each spoke to semicircle.\\n d0 = max(d0, -P.y);\\n d1 = max(d1, dot(P, vec2(-dy, dx)));\\n d2 = max(d2, dot(P, vec2(dy, dx)));\\n\\n float Y = min(min(d0, d1), d2);\\n Y = max(Y - v_linewidth/2.0 + u_antialias/2.0, 0.0);\\n return max(circle, Y);\\n}\\n#endif\\n\\n#ifdef USE_CIRCLE_X\\n// circle_x\\nfloat marker(vec2 P, float size)\\n{\\n float x = P.x - P.y;\\n float y = P.x + P.y;\\n // Define quadrants\\n float qs = size / 2.0; // quadrant size\\n float s1 = max(abs(x - qs), abs(y - qs)) - qs;\\n float s2 = max(abs(x + qs), abs(y - qs)) - qs;\\n float s3 = max(abs(x - qs), abs(y + qs)) - qs;\\n float s4 = max(abs(x + qs), abs(y + qs)) - qs;\\n // Intersect main shape with quadrants (to form cross)\\n float circle = length(P) - size/2.0;\\n float c1 = max(circle, s1);\\n float c2 = max(circle, s2);\\n float c3 = max(circle, s3);\\n float c4 = max(circle, s4);\\n // Union\\n return min(min(min(c1, c2), c3), c4);\\n}\\n#endif\\n\\n#ifdef USE_CIRCLE_Y\\nfloat marker(vec2 P, float size)\\n{\\n float circle = length(P) - size/2.0;\\n\\n float dx = 1.0 / SQRT_3;\\n float dy = SQRT_2 / SQRT_3;\\n\\n // Sideways distance from the three spokes.\\n float d0 = abs(P.x);\\n float d1 = abs(dot(P, vec2(dx, dy)));\\n float d2 = abs(dot(P, vec2(dx, -dy)));\\n\\n // Clip each spoke to semicircle.\\n d0 = max(d0, -P.y);\\n d1 = max(d1, dot(P, vec2(-dy, dx)));\\n d2 = max(d2, dot(P, vec2(dy, dx)));\\n\\n float Y = min(min(d0, d1), d2);\\n Y = min(v_linewidth/2.0 - u_antialias/2.0 - Y, 0.0);\\n\\n return max(circle, Y);\\n}\\n#endif\\n\\n#ifdef USE_SQUARE_X\\n// square_x\\nfloat marker(vec2 P, float size)\\n{\\n float x = P.x - P.y;\\n float y = P.x + P.y;\\n // Define quadrants\\n float qs = size / 2.0; // quadrant size\\n float s1 = max(abs(x - qs), abs(y - qs)) - qs;\\n float s2 = max(abs(x + qs), abs(y - qs)) - qs;\\n float s3 = max(abs(x - qs), abs(y + qs)) - qs;\\n float s4 = max(abs(x + qs), abs(y + qs)) - qs;\\n // Intersect main shape with quadrants (to form cross)\\n float square = max(abs(P.x), abs(P.y)) - size/2.0;\\n float c1 = max(square, s1);\\n float c2 = max(square, s2);\\n float c3 = max(square, s3);\\n float c4 = max(square, s4);\\n // Union\\n return min(min(min(c1, c2), c3), c4);\\n}\\n#endif\\n\\n#ifdef USE_PLUS\\nfloat marker(vec2 P, float size)\\n{\\n vec2 size2 = vec2(size*0.5, size*0.2);\\n P = abs(P);\\n P = (P.y > P.x) ? P.yx : P.xy;\\n vec2 q = P - size2;\\n float k = max(q.y, q.x);\\n vec2 w = (k > 0.0) ? q : vec2(size2.y - P.x, -k);\\n return sign(k)*length(max(w, 0.0));\\n}\\n#endif\\n\\n#ifdef USE_SQUARE_PIN\\nfloat marker(vec2 P, float size)\\n{\\n float actual_size = size*1.2;\\n float radius = 0.75*actual_size; // Radius of curvature of edges.\\n float offset = actual_size/2.0 + sqrt(radius*radius - actual_size*actual_size/4.0);\\n vec2 centerx = vec2(offset, 0.0);\\n vec2 centery = vec2(0.0, offset);\\n\\n float right = length(P - centerx);\\n float left = length(P + centerx);\\n float up = length(P - centery);\\n float down = length(P + centery);\\n float pin = radius - min(min(right, left), min(up, down));\\n\\n float circle = length(P) - actual_size*0.6;\\n return max(circle, pin);\\n}\\n#endif\\n\\n#ifdef USE_TRIANGLE_PIN\\nfloat marker(vec2 P, float size)\\n{\\n float actual_size = size*1.2;\\n float radius = 1.2*actual_size; // Radius of curvature of edges.\\n\\n float angle = 2.0*PI / 3.0;\\n float c = cos(angle);\\n float s = sin(angle);\\n mat2 rotation = mat2(c, -s, s, c);\\n\\n // Half the length of straight triangle edge.\\n float half_edge = actual_size*SQRT_3/4.0;\\n // Distance from center of triangle to middle of straight edge.\\n float centre_middle_edge = 0.25*actual_size;\\n float offset = centre_middle_edge + sqrt(radius*radius - half_edge*half_edge);\\n // Centre of curvature.\\n vec2 center = vec2(0.0, offset);\\n\\n float dist0 = length(P - center);\\n P = rotation*P;\\n float dist1 = length(P - center);\\n P = rotation*P;\\n float dist2 = length(P - center);\\n float pin = radius - min(min(dist0, dist1), dist2);\\n\\n float circle = length(P) - actual_size / 2.0;\\n return max(circle, pin);\\n}\\n#endif\\n\\nvec4 outline(float distance, float linewidth, float antialias, vec4 line_color,\\n vec4 fill_color)\\n{\\n vec4 frag_color;\\n float t = min(linewidth/2.0 - antialias, 0.0); // Line half-width.\\n float signed_distance = distance;\\n float border_distance = abs(signed_distance) - t;\\n float alpha = border_distance/antialias;\\n alpha = exp(-alpha*alpha);\\n\\n // If line alpha is zero, it probably means no outline. To avoid a dark\\n // outline shining through due to antialiasing, we set the line color to the\\n // fill color.\\n float select = float(bool(line_color.a));\\n line_color.rgb = select*line_color.rgb + (1.0 - select)*fill_color.rgb;\\n // Similarly, if we want a transparent fill.\\n select = float(bool(fill_color.a));\\n fill_color.rgb = select*fill_color.rgb + (1.0 - select)*line_color.rgb;\\n\\n if (border_distance < 0.0)\\n frag_color = line_color;\\n else if (signed_distance < 0.0)\\n frag_color = mix(fill_color, line_color, sqrt(alpha));\\n else {\\n if (abs(signed_distance) < linewidth/2.0 + antialias)\\n frag_color = vec4(line_color.rgb, line_color.a*alpha);\\n else\\n discard;\\n }\\n return frag_color;\\n}\\n\\nvoid main()\\n{\\n float distance = marker(v_coords, v_size);\\n gl_FragColor = outline(\\n distance, v_linewidth, u_antialias, v_line_color, v_fill_color);\\n gl_FragColor.rgb *= gl_FragColor.a; // Premultiplied alpha.\\n}\\n\"},\n", - " 419: function _(n,t,a,i,e){i();a.default=\"\\nprecision mediump float;\\n\\nattribute vec2 a_position;\\nattribute vec2 a_center;\\nattribute float a_width;\\nattribute float a_height;\\nattribute float a_angle; // In radians\\nattribute float a_linewidth;\\nattribute vec4 a_line_color;\\nattribute vec4 a_fill_color;\\nattribute float a_line_join;\\nattribute float a_show;\\n#ifdef HATCH\\nattribute float a_hatch_pattern;\\nattribute float a_hatch_scale;\\nattribute float a_hatch_weight;\\nattribute vec4 a_hatch_color;\\n#endif\\n\\nuniform float u_pixel_ratio;\\nuniform vec2 u_canvas_size;\\nuniform float u_antialias;\\n\\nvarying float v_linewidth;\\nvarying vec2 v_size; // 2D size for rects compared to 1D for markers.\\nvarying vec4 v_line_color;\\nvarying vec4 v_fill_color;\\nvarying float v_line_join;\\nvarying vec2 v_coords;\\n#ifdef HATCH\\nvarying float v_hatch_pattern;\\nvarying float v_hatch_scale;\\nvarying float v_hatch_weight;\\nvarying vec4 v_hatch_color;\\nvarying vec2 v_hatch_coords;\\n#endif\\n\\nvoid main()\\n{\\n if (a_show < 0.5) {\\n // Do not show this rect.\\n gl_Position = vec4(-2.0, -2.0, 0.0, 1.0);\\n return;\\n }\\n\\n v_size = vec2(a_width, a_height);\\n v_linewidth = a_linewidth;\\n v_line_color = a_line_color;\\n v_fill_color = a_fill_color;\\n v_line_join = a_line_join;\\n\\n if (v_linewidth < 1.0) {\\n // Linewidth less than 1 is implemented as 1 but with reduced alpha.\\n v_line_color.a *= v_linewidth;\\n v_linewidth = 1.0;\\n }\\n\\n#ifdef HATCH\\n v_hatch_pattern = a_hatch_pattern;\\n v_hatch_scale = a_hatch_scale;\\n v_hatch_weight = a_hatch_weight;\\n v_hatch_color = a_hatch_color;\\n#endif\\n\\n vec2 enclosing_size = v_size + v_linewidth + u_antialias;\\n\\n // Coordinates in rotated frame with respect to center of marker, used for\\n // distance functions in fragment shader.\\n v_coords = a_position*enclosing_size;\\n\\n float c = cos(-a_angle);\\n float s = sin(-a_angle);\\n mat2 rotation = mat2(c, -s, s, c);\\n\\n vec2 pos = a_center + rotation*v_coords;\\n#ifdef HATCH\\n // Coordinates for hatching in unrotated frame of reference.\\n v_hatch_coords = pos - 0.5;\\n#endif\\n pos += 0.5; // Make up for Bokeh's offset.\\n pos /= u_canvas_size / u_pixel_ratio; // 0 to 1.\\n gl_Position = vec4(2.0*pos.x - 1.0, 1.0 - 2.0*pos.y, 0.0, 1.0);\\n}\\n\"},\n", - " 420: function _(n,a,t,o,r){o();t.default=\"\\nprecision mediump float;\\n\\nconst float SQRT2 = sqrt(2.0);\\nconst float INVSQRT2 = 1.0/SQRT2;\\nconst float PI = 3.14159265358979323846;\\n\\nconst int miter_join = 0;\\nconst int round_join = 1;\\nconst int bevel_join = 2;\\n#ifdef HATCH\\nconst int hatch_dot = 1;\\nconst int hatch_ring = 2;\\nconst int hatch_horizontal_line = 3;\\nconst int hatch_vertical_line = 4;\\nconst int hatch_cross = 5;\\nconst int hatch_horizontal_dash = 6;\\nconst int hatch_vertical_dash = 7;\\nconst int hatch_spiral = 8;\\nconst int hatch_right_diagonal_line = 9;\\nconst int hatch_left_diagonal_line = 10;\\nconst int hatch_diagonal_cross = 11;\\nconst int hatch_right_diagonal_dash = 12;\\nconst int hatch_left_diagonal_dash = 13;\\nconst int hatch_horizontal_wave = 14;\\nconst int hatch_vertical_wave = 15;\\nconst int hatch_criss_cross = 16;\\n#endif\\n\\nuniform float u_antialias;\\n\\nvarying float v_linewidth;\\nvarying vec2 v_size;\\nvarying vec4 v_line_color;\\nvarying vec4 v_fill_color;\\nvarying float v_line_join;\\nvarying vec2 v_coords;\\n#ifdef HATCH\\nvarying float v_hatch_pattern;\\nvarying float v_hatch_scale;\\nvarying float v_hatch_weight;\\nvarying vec4 v_hatch_color;\\nvarying vec2 v_hatch_coords;\\n#endif\\n\\n// Distance is zero on edge of marker, +ve outside and -ve inside.\\nfloat marker_distance(vec2 p, int line_join)\\n{\\n vec2 dist2 = abs(p) - v_size/2.0;\\n float dist = max(dist2.x, dist2.y);\\n\\n if (dist2.x > 0.0 && dist2.y > 0.0) {\\n // Outside of corner needs correct join, default is miter.\\n if (line_join == round_join)\\n dist = length(dist2);\\n else if (line_join == bevel_join) {\\n vec2 normal = vec2(INVSQRT2, INVSQRT2);\\n dist = dot(dist2, normal) + 0.5*v_linewidth*(1.0 - INVSQRT2);\\n }\\n }\\n\\n return dist;\\n}\\n\\n// Convert distance from edge of marker to fraction in range 0 to 1, depending\\n// on antialiasing width.\\nfloat distance_to_fraction(float dist)\\n{\\n return 1.0 - smoothstep(-0.5*u_antialias, 0.5*u_antialias, dist);\\n}\\n\\n// Return fraction from 0 (no fill color) to 1 (full fill color).\\nfloat fill_fraction(float dist)\\n{\\n return distance_to_fraction(dist);\\n}\\n\\n// Return fraction in range 0 (no line color) to 1 (full line color).\\nfloat line_fraction(float dist)\\n{\\n return distance_to_fraction(abs(dist) - 0.5*v_linewidth);\\n}\\n\\n// Return fraction (in range 0 to 1) of a color, with premultiplied alpha.\\nvec4 fractional_color(vec4 color, float fraction)\\n{\\n color.a *= fraction;\\n color.rgb *= color.a;\\n return color;\\n}\\n\\n// Blend colors that have premultiplied alpha.\\nvec4 blend_colors(vec4 src, vec4 dest)\\n{\\n return (1.0 - src.a)*dest + src;\\n}\\n\\n#ifdef HATCH\\n// Wrap coordinate(s) by removing integer part to give distance from center of\\n// repeat, in the range -0.5 to +0.5.\\nfloat wrap(float x)\\n{\\n return fract(x) - 0.5;\\n}\\n\\nvec2 wrap(vec2 xy)\\n{\\n return fract(xy) - 0.5;\\n}\\n\\n// Return fraction from 0 (no hatch color) to 1 (full hatch color).\\nfloat hatch_fraction(vec2 coords, int hatch_pattern)\\n{\\n float scale = v_hatch_scale; // Hatch repeat distance.\\n\\n // Coordinates and linewidth/halfwidth are scaled to hatch repeat distance.\\n coords = coords / scale;\\n float halfwidth = 0.5*v_hatch_weight / scale; // Half the hatch linewidth.\\n\\n // Default is to return fraction of zero, i.e. no pattern.\\n float dist = u_antialias;\\n\\n if (hatch_pattern == hatch_dot) {\\n const float dot_radius = 0.25;\\n dist = length(wrap(coords)) - dot_radius;\\n }\\n else if (hatch_pattern == hatch_ring) {\\n const float ring_radius = 0.25;\\n dist = abs(length(wrap(coords)) - ring_radius) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_horizontal_line) {\\n dist = abs(wrap(coords.y)) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_vertical_line) {\\n dist = abs(wrap(coords.x)) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_cross) {\\n dist = min(abs(wrap(coords.x)), abs(wrap(coords.y))) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_horizontal_dash) {\\n // Dashes have square caps.\\n const float halflength = 0.25;\\n dist = max(abs(wrap(coords.y)),\\n abs(wrap(coords.x) + 0.25) - halflength) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_vertical_dash) {\\n const float halflength = 0.25;\\n dist = max(abs(wrap(coords.x)),\\n abs(wrap(coords.y) + 0.25) - halflength) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_spiral) {\\n vec2 wrap2 = wrap(coords);\\n float angle = wrap(atan(wrap2.y, wrap2.x) / (2.0*PI));\\n // Canvas spiral radius increases by scale*pi/15 each rotation.\\n const float dr = PI/15.0;\\n float radius = length(wrap2);\\n // At any angle, spiral lines are equally spaced dr apart.\\n // Find distance to nearest of these lines.\\n float frac = fract((radius - dr*angle) / dr); // 0 to 1.\\n dist = dr*(abs(frac - 0.5));\\n dist = min(dist, radius) - halfwidth; // Consider center point also.\\n }\\n else if (hatch_pattern == hatch_right_diagonal_line) {\\n dist = abs(wrap(2.0*coords.x + coords.y))/sqrt(5.0) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_left_diagonal_line) {\\n dist = abs(wrap(2.0*coords.x - coords.y))/sqrt(5.0) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_diagonal_cross) {\\n coords = vec2(coords.x + coords.y + 0.5, coords.x - coords.y + 0.5);\\n dist = min(abs(wrap(coords.x)), abs(wrap(coords.y))) / SQRT2 - halfwidth;\\n }\\n else if (hatch_pattern == hatch_right_diagonal_dash) {\\n float across = coords.x + coords.y + 0.5;\\n dist = abs(wrap(across)) / SQRT2; // Distance to nearest solid line.\\n\\n across = floor(across); // Offset for dash.\\n float along = wrap(0.5*(coords.x - coords.y + across));\\n const float halflength = 0.25;\\n along = abs(along) - halflength; // Distance along line.\\n\\n dist = max(dist, along) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_left_diagonal_dash) {\\n float across = coords.x - coords.y + 0.5;\\n dist = abs(wrap(across)) / SQRT2; // Distance to nearest solid line.\\n\\n across = floor(across); // Offset for dash.\\n float along = wrap(0.5*(coords.x + coords.y + across));\\n const float halflength = 0.25;\\n along = abs(along) - halflength; // Distance along line.\\n\\n dist = max(dist, along) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_horizontal_wave) {\\n float wrapx = wrap(coords.x);\\n float wrapy = wrap(coords.y - 0.25 + abs(wrapx));\\n dist = abs(wrapy) / SQRT2 - halfwidth;\\n }\\n else if (hatch_pattern == hatch_vertical_wave) {\\n float wrapy = wrap(coords.y);\\n float wrapx = wrap(coords.x - 0.25 + abs(wrapy));\\n dist = abs(wrapx) / SQRT2 - halfwidth;\\n }\\n else if (hatch_pattern == hatch_criss_cross) {\\n float plus = min(abs(wrap(coords.x)), abs(wrap(coords.y)));\\n\\n coords = vec2(coords.x + coords.y + 0.5, coords.x - coords.y + 0.5);\\n float X = min(abs(wrap(coords.x)), abs(wrap(coords.y))) / SQRT2;\\n\\n dist = min(plus, X) - halfwidth;\\n }\\n\\n return distance_to_fraction(dist*scale);\\n}\\n#endif\\n\\nvoid main()\\n{\\n int line_join = int(v_line_join + 0.5);\\n#ifdef HATCH\\n int hatch_pattern = int(v_hatch_pattern + 0.5);\\n#endif\\n\\n float dist = marker_distance(v_coords, line_join);\\n\\n float fill_frac = fill_fraction(dist);\\n vec4 color = fractional_color(v_fill_color, fill_frac);\\n\\n#ifdef HATCH\\n if (hatch_pattern > 0 && fill_frac > 0.0) {\\n float hatch_frac = hatch_fraction(v_hatch_coords, hatch_pattern);\\n vec4 hatch_color = fractional_color(v_hatch_color, hatch_frac*fill_frac);\\n color = blend_colors(hatch_color, color);\\n }\\n#endif\\n\\n float line_frac = line_fraction(dist);\\n if (line_frac > 0.0) {\\n vec4 line_color = fractional_color(v_line_color, line_frac);\\n color = blend_colors(line_color, color);\\n }\\n\\n gl_FragColor = color;\\n}\\n\"},\n", - " 421: function _(s,i,t,e,_){e();const h=s(422),l=s(22),a=s(46),n=s(423),o=s(424),r=-1e4;class p extends h.BaseGLGlyph{constructor(s,i){super(s,i),this.glyph=i,this._antialias=1.5,this._miter_limit=5}draw(s,i,t){const e=i.glglyph;this.visuals_changed&&(this._set_visuals(),this.visuals_changed=!1),e.data_changed&&(e._set_data(),e.data_changed=!1);const _=this.glyph.visuals.line,h=n.cap_lookup[_.line_cap.value],l=n.join_lookup[_.line_join.value];if(this._is_dashed()){const s={scissor:this.regl_wrapper.scissor,viewport:this.regl_wrapper.viewport,canvas_size:[t.width,t.height],pixel_ratio:t.pixel_ratio,line_color:this._color,linewidth:this._linewidth,antialias:this._antialias,miter_limit:this._miter_limit,points:e._points,nsegments:e._nsegments,line_join:l,line_cap:h,length_so_far:e._length_so_far,dash_tex:this._dash_tex,dash_tex_info:this._dash_tex_info,dash_scale:this._dash_scale,dash_offset:this._dash_offset};this.regl_wrapper.dashed_line()(s)}else{const s={scissor:this.regl_wrapper.scissor,viewport:this.regl_wrapper.viewport,canvas_size:[t.width,t.height],pixel_ratio:t.pixel_ratio,line_color:this._color,linewidth:this._linewidth,antialias:this._antialias,miter_limit:this._miter_limit,points:e._points,nsegments:e._nsegments,line_join:l,line_cap:h};this.regl_wrapper.solid_line()(s)}}_is_dashed(){return this._line_dash.length>0}_set_data(){const s=this.glyph.sx.length;this._nsegments=s-1,null==this._is_closed&&(this._is_closed=this.glyph.sx[0]==this.glyph.sx[s-1]&&this.glyph.sy[0]==this.glyph.sy[s-1]&&isFinite(this.glyph.sx[0])&&isFinite(this.glyph.sy[0])),null==this._points&&(this._points=new o.Float32Buffer(this.regl_wrapper));const i=this._points.get_sized_array(2*(s+2));for(let t=1;t-9e3&&i[2*e+4]>-9e3&&(t+=Math.sqrt((i[2*e+4]-i[2*e+2])**2+(i[2*e+5]-i[2*e+3])**2));this._length_so_far.update()}}_set_visuals(){const s=this.glyph.visuals.line,i=(0,l.color2rgba)(s.line_color.value,s.line_alpha.value);this._color=i.map((s=>s/255)),this._linewidth=s.line_width.value,this._linewidth<1&&(this._color[3]*=this._linewidth,this._linewidth=1),this._line_dash=(0,a.resolve_line_dash)(s.line_dash.value),1==this._line_dash.length&&this._line_dash.push(this._line_dash[0]),this._is_dashed()&&([this._dash_tex_info,this._dash_tex,this._dash_scale]=this.regl_wrapper.get_dash(this._line_dash),this._dash_offset=s.line_dash_offset.value)}}t.LineGL=p,p.__name__=\"LineGL\"},\n", - " 422: function _(e,t,s,i,h){i();class a{constructor(e,t){this.glyph=t,this.nvertices=0,this.size_changed=!1,this.data_changed=!1,this.visuals_changed=!1,this.regl_wrapper=e}set_data_changed(){const{data_size:e}=this.glyph;e!=this.nvertices&&(this.nvertices=e,this.size_changed=!0),this.data_changed=!0}set_visuals_changed(){this.visuals_changed=!0}render(e,t,s){if(0==t.length)return!0;const{width:i,height:h}=this.glyph.renderer.plot_view.canvas_view.webgl.canvas,a={pixel_ratio:this.glyph.renderer.plot_view.canvas_view.pixel_ratio,width:i,height:h};return this.draw(t,s,a),!0}}s.BaseGLGlyph=a,a.__name__=\"BaseGLGlyph\"},\n", - " 423: function _(a,o,i,n,l){n();const t=a(52);i.cap_lookup={butt:0,round:1,square:2},i.join_lookup={miter:0,round:1,bevel:2};const _={blank:0,dot:1,ring:2,horizontal_line:3,vertical_line:4,cross:5,horizontal_dash:6,vertical_dash:7,spiral:8,right_diagonal_line:9,left_diagonal_line:10,diagonal_cross:11,right_diagonal_dash:12,left_diagonal_dash:13,horizontal_wave:14,vertical_wave:15,criss_cross:16};i.hatch_pattern_to_index=function(a){var o,i;return null!==(i=_[null!==(o=t.hatch_aliases[a])&&void 0!==o?o:a])&&void 0!==i?i:0}},\n", - " 424: function _(r,t,a,e,s){e();const i=r(423),_=r(22);class n{constructor(r){this.regl_wrapper=r,this.is_scalar=!0}get_sized_array(r){return null!=this.array&&this.array.length==r||(this.array=this.new_array(r)),this.array}is_normalized(){return!1}get length(){return null!=this.array?this.array.length:0}set_from_array(r){const t=r.length,a=this.get_sized_array(t);for(let e=0;ethis.render()))}remove(){null!=this.icon_view&&this.icon_view.remove(),super.remove()}styles(){return[...super.styles(),d.default]}_render_button(...t){return(0,c.button)({type:\"button\",disabled:this.model.disabled,class:[h.btn,h[`btn_${this.model.button_type}`]]},...t)}render(){super.render(),this.button_el=this._render_button(this.model.label),this.button_el.addEventListener(\"click\",(()=>this.click())),null!=this.icon_view&&(\"\"!=this.model.label?(0,c.prepend)(this.button_el,this.icon_view.el,(0,c.nbsp)()):(0,c.prepend)(this.button_el,this.icon_view.el),this.icon_view.render()),this.group_el=(0,c.div)({class:h.btn_group},this.button_el),this.el.appendChild(this.group_el)}click(){}}n.AbstractButtonView=b,b.__name__=\"AbstractButtonView\";class p extends _.Control{constructor(t){super(t)}}n.AbstractButton=p,o=p,p.__name__=\"AbstractButton\",o.define((({String:t,Ref:e,Nullable:n})=>({label:[t,\"Button\"],icon:[n(e(a.AbstractIcon)),null],button_type:[r.ButtonType,\"default\"]})))},\n", - " 439: function _(t,e,o,s,n){s();const i=t(508),l=t(43);class c extends i.WidgetView{connect_signals(){super.connect_signals();const t=this.model.properties;this.on_change(t.disabled,(()=>{for(const t of this.controls())(0,l.toggle_attribute)(t,\"disabled\",this.model.disabled)}))}}o.ControlView=c,c.__name__=\"ControlView\";class r extends i.Widget{constructor(t){super(t)}}o.Control=r,r.__name__=\"Control\"},\n", - " 508: function _(i,e,t,n,o){var r;n();const s=i(312);class _ extends s.HTMLBoxView{get orientation(){return\"horizontal\"}get default_size(){return this.model.default_size}_width_policy(){return\"horizontal\"==this.orientation?super._width_policy():\"fixed\"}_height_policy(){return\"horizontal\"==this.orientation?\"fixed\":super._height_policy()}box_sizing(){const i=super.box_sizing();return\"horizontal\"==this.orientation?null==i.width&&(i.width=this.default_size):null==i.height&&(i.height=this.default_size),i}}t.WidgetView=_,_.__name__=\"WidgetView\";class h extends s.HTMLBox{constructor(i){super(i)}}t.Widget=h,r=h,h.__name__=\"Widget\",r.define((({Number:i})=>({default_size:[i,300]}))),r.override({margin:[5,5,5,5]})},\n", - " 441: function _(c,t,s,n,e){n();const o=c(53),_=c(226);class a extends _.DOMView{}s.AbstractIconView=a,a.__name__=\"AbstractIconView\";class r extends o.Model{constructor(c){super(c)}}s.AbstractIcon=r,r.__name__=\"AbstractIcon\"},\n", - " 442: function _(e,t,n,s,i){s();const h=e(1);var o;const _=e(443),u=e(43),r=e(10),c=(0,h.__importStar)(e(229)),a=c;class l extends _.TextInputView{constructor(){super(...arguments),this._open=!1,this._last_value=\"\",this._hover_index=0}styles(){return[...super.styles(),c.default]}render(){super.render(),this.input_el.addEventListener(\"keydown\",(e=>this._keydown(e))),this.input_el.addEventListener(\"keyup\",(e=>this._keyup(e))),this.menu=(0,u.div)({class:[a.menu,a.below]}),this.menu.addEventListener(\"click\",(e=>this._menu_click(e))),this.menu.addEventListener(\"mouseover\",(e=>this._menu_hover(e))),this.el.appendChild(this.menu),(0,u.undisplay)(this.menu)}change_input(){this._open&&this.menu.children.length>0?(this.model.value=this.menu.children[this._hover_index].textContent,this.input_el.focus(),this._hide_menu()):this.model.restrict||super.change_input()}_update_completions(e){(0,u.empty)(this.menu);for(const t of e){const e=(0,u.div)(t);this.menu.appendChild(e)}e.length>0&&this.menu.children[0].classList.add(a.active)}_show_menu(){if(!this._open){this._open=!0,this._hover_index=0,this._last_value=this.model.value,(0,u.display)(this.menu);const e=t=>{const{target:n}=t;n instanceof HTMLElement&&!this.el.contains(n)&&(document.removeEventListener(\"click\",e),this._hide_menu())};document.addEventListener(\"click\",e)}}_hide_menu(){this._open&&(this._open=!1,(0,u.undisplay)(this.menu))}_menu_click(e){e.target!=e.currentTarget&&e.target instanceof Element&&(this.model.value=e.target.textContent,this.input_el.focus(),this._hide_menu())}_menu_hover(e){if(e.target!=e.currentTarget&&e.target instanceof Element){let t=0;for(t=0;t0&&(this.menu.children[this._hover_index].classList.remove(a.active),this._hover_index=(0,r.clamp)(e,0,t-1),this.menu.children[this._hover_index].classList.add(a.active))}_keydown(e){}_keyup(e){switch(e.keyCode){case u.Keys.Enter:this.change_input();break;case u.Keys.Esc:this._hide_menu();break;case u.Keys.Up:this._bump_hover(this._hover_index-1);break;case u.Keys.Down:this._bump_hover(this._hover_index+1);break;default:{const e=this.input_el.value;if(e.lengthe:e=>e.toLowerCase();for(const n of this.model.completions)s(n).startsWith(s(e))&&t.push(n);this._update_completions(t),0==t.length?this._hide_menu():this._show_menu()}}}}n.AutocompleteInputView=l,l.__name__=\"AutocompleteInputView\";class d extends _.TextInput{constructor(e){super(e)}}n.AutocompleteInput=d,o=d,d.__name__=\"AutocompleteInput\",o.prototype.default_view=l,o.define((({Boolean:e,Int:t,String:n,Array:s})=>({completions:[s(n),[]],min_characters:[t,2],case_sensitive:[e,!0],restrict:[e,!0]})))},\n", - " 443: function _(t,e,n,p,_){p();const u=t(1);var i;const s=t(444),r=t(43),x=(0,u.__importStar)(t(446));class a extends s.TextLikeInputView{_render_input(){this.input_el=(0,r.input)({type:\"text\",class:x.input})}}n.TextInputView=a,a.__name__=\"TextInputView\";class c extends s.TextLikeInput{constructor(t){super(t)}}n.TextInput=c,i=c,c.__name__=\"TextInput\",i.prototype.default_view=a},\n", - " 444: function _(e,t,n,i,l){var s;i();const h=e(445);class a extends h.InputWidgetView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.name.change,(()=>{var e;return this.input_el.name=null!==(e=this.model.name)&&void 0!==e?e:\"\"})),this.connect(this.model.properties.value.change,(()=>this.input_el.value=this.model.value)),this.connect(this.model.properties.value_input.change,(()=>this.input_el.value=this.model.value_input)),this.connect(this.model.properties.disabled.change,(()=>this.input_el.disabled=this.model.disabled)),this.connect(this.model.properties.placeholder.change,(()=>this.input_el.placeholder=this.model.placeholder)),this.connect(this.model.properties.max_length.change,(()=>{const{max_length:e}=this.model;null!=e?this.input_el.maxLength=e:this.input_el.removeAttribute(\"maxLength\")}))}render(){var e;super.render(),this._render_input();const{input_el:t}=this;t.name=null!==(e=this.model.name)&&void 0!==e?e:\"\",t.value=this.model.value,t.disabled=this.model.disabled,t.placeholder=this.model.placeholder,null!=this.model.max_length&&(t.maxLength=this.model.max_length),t.addEventListener(\"change\",(()=>this.change_input())),t.addEventListener(\"input\",(()=>this.change_input_value())),this.group_el.appendChild(t)}change_input(){this.model.value=this.input_el.value,super.change_input()}change_input_value(){this.model.value_input=this.input_el.value,super.change_input()}}n.TextLikeInputView=a,a.__name__=\"TextLikeInputView\";class u extends h.InputWidget{constructor(e){super(e)}}n.TextLikeInput=u,s=u,u.__name__=\"TextLikeInput\",s.define((({Int:e,String:t,Nullable:n})=>({value:[t,\"\"],value_input:[t,\"\"],placeholder:[t,\"\"],max_length:[n(e),null]})))},\n", - " 445: function _(e,t,n,s,l){s();const i=e(1);var o;const r=e(439),_=e(43),p=(0,i.__importStar)(e(446)),a=p;class c extends r.ControlView{*controls(){yield this.input_el}connect_signals(){super.connect_signals(),this.connect(this.model.properties.title.change,(()=>{this.label_el.textContent=this.model.title}))}styles(){return[...super.styles(),p.default]}render(){super.render();const{title:e}=this.model;this.label_el=(0,_.label)({style:{display:0==e.length?\"none\":\"\"}},e),this.group_el=(0,_.div)({class:a.input_group},this.label_el),this.el.appendChild(this.group_el)}change_input(){}}n.InputWidgetView=c,c.__name__=\"InputWidgetView\";class d extends r.Control{constructor(e){super(e)}}n.InputWidget=d,o=d,d.__name__=\"InputWidget\",o.define((({String:e})=>({title:[e,\"\"]})))},\n", - " 446: function _(o,p,t,n,i){n(),t.root=\"bk-root\",t.input=\"bk-input\",t.input_group=\"bk-input-group\",t.inline=\"bk-inline\",t.spin_wrapper=\"bk-spin-wrapper\",t.spin_btn=\"bk-spin-btn\",t.spin_btn_up=\"bk-spin-btn-up\",t.spin_btn_down=\"bk-spin-btn-down\",t.default='.bk-root .bk-input{display:inline-block;width:100%;flex-grow:1;min-height:31px;padding:0 12px;background-color:#fff;border:1px solid #ccc;border-radius:4px;}.bk-root .bk-input:focus{border-color:#66afe9;outline:0;box-shadow:inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 8px rgba(102, 175, 233, 0.6);}.bk-root .bk-input::placeholder,.bk-root .bk-input:-ms-input-placeholder,.bk-root .bk-input::-moz-placeholder,.bk-root .bk-input::-webkit-input-placeholder{color:#999;opacity:1;}.bk-root .bk-input[disabled]{cursor:not-allowed;background-color:#eee;opacity:1;}.bk-root select:not([multiple]).bk-input,.bk-root select:not([size]).bk-input{height:auto;appearance:none;-webkit-appearance:none;background-image:url(\\'data:image/svg+xml;utf8,\\');background-position:right 0.5em center;background-size:8px 6px;background-repeat:no-repeat;}.bk-root select[multiple].bk-input,.bk-root select[size].bk-input,.bk-root textarea.bk-input{height:auto;}.bk-root .bk-input-group{width:100%;height:100%;display:inline-flex;flex-wrap:nowrap;align-items:start;flex-direction:column;white-space:nowrap;}.bk-root .bk-input-group.bk-inline{flex-direction:row;}.bk-root .bk-input-group.bk-inline > *:not(:first-child){margin-left:5px;}.bk-root .bk-input-group input[type=\"checkbox\"] + span,.bk-root .bk-input-group input[type=\"radio\"] + span{position:relative;top:-2px;margin-left:3px;}.bk-root .bk-input-group > .bk-spin-wrapper{display:inherit;width:inherit;height:inherit;position:relative;overflow:hidden;padding:0;vertical-align:middle;}.bk-root .bk-input-group > .bk-spin-wrapper input{padding-right:20px;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn{position:absolute;display:block;height:50%;min-height:0;min-width:0;width:30px;padding:0;margin:0;right:0;border:none;background:none;cursor:pointer;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn:before{content:\"\";display:inline-block;transform:translateY(-50%);border-left:5px solid transparent;border-right:5px solid transparent;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-up{top:0;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-up:before{border-bottom:5px solid black;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-up:disabled:before{border-bottom-color:grey;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-down{bottom:0;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-down:before{border-top:5px solid black;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-down:disabled:before{border-top-color:grey;}'},\n", - " 447: function _(t,e,n,o,c){var s;o();const u=t(438),r=t(251);class i extends u.AbstractButtonView{click(){this.model.trigger_event(new r.ButtonClick),super.click()}}n.ButtonView=i,i.__name__=\"ButtonView\";class _ extends u.AbstractButton{constructor(t){super(t)}}n.Button=_,s=_,_.__name__=\"Button\",s.prototype.default_view=i,s.override({label:\"Button\"})},\n", - " 448: function _(t,e,o,c,a){c();const s=t(1);var n;const i=t(449),r=t(43),u=(0,s.__importStar)(t(318));class _ extends i.ButtonGroupView{get active(){return new Set(this.model.active)}change_active(t){const{active:e}=this;e.has(t)?e.delete(t):e.add(t),this.model.active=[...e].sort()}_update_active(){const{active:t}=this;this._buttons.forEach(((e,o)=>{(0,r.classes)(e).toggle(u.active,t.has(o))}))}}o.CheckboxButtonGroupView=_,_.__name__=\"CheckboxButtonGroupView\";class h extends i.ButtonGroup{constructor(t){super(t)}}o.CheckboxButtonGroup=h,n=h,h.__name__=\"CheckboxButtonGroup\",n.prototype.default_view=_,n.define((({Int:t,Array:e})=>({active:[e(t),[]]})))},\n", - " 449: function _(t,e,n,s,i){s();const o=t(1);var r;const a=t(450),l=t(20),d=t(43),u=(0,o.__importStar)(t(318)),_=u;class c extends a.OrientedControlView{get default_size(){return\"horizontal\"==this.orientation?this.model.default_size:void 0}*controls(){yield*this._buttons}connect_signals(){super.connect_signals();const t=this.model.properties;this.on_change(t.button_type,(()=>this.render())),this.on_change(t.labels,(()=>this.render())),this.on_change(t.active,(()=>this._update_active()))}styles(){return[...super.styles(),u.default]}render(){super.render(),this._buttons=this.model.labels.map(((t,e)=>{const n=(0,d.div)({class:[_.btn,_[`btn_${this.model.button_type}`]],disabled:this.model.disabled},t);return n.addEventListener(\"click\",(()=>this.change_active(e))),n})),this._update_active();const t=\"horizontal\"==this.model.orientation?_.horizontal:_.vertical,e=(0,d.div)({class:[_.btn_group,t]},this._buttons);this.el.appendChild(e)}}n.ButtonGroupView=c,c.__name__=\"ButtonGroupView\";class h extends a.OrientedControl{constructor(t){super(t)}}n.ButtonGroup=h,r=h,h.__name__=\"ButtonGroup\",r.define((({String:t,Array:e})=>({labels:[e(t),[]],button_type:[l.ButtonType,\"default\"]})))},\n", - " 450: function _(n,t,e,o,r){var i;o();const a=n(439),l=n(20);class s extends a.ControlView{get orientation(){return this.model.orientation}}e.OrientedControlView=s,s.__name__=\"OrientedControlView\";class _ extends a.Control{constructor(n){super(n)}}e.OrientedControl=_,i=_,_.__name__=\"OrientedControl\",i.define((()=>({orientation:[l.Orientation,\"horizontal\"]})))},\n", - " 451: function _(e,t,n,i,s){i();const o=e(1);var a;const c=e(452),l=e(43),d=e(9),p=(0,o.__importStar)(e(446));class r extends c.InputGroupView{render(){super.render();const e=(0,l.div)({class:[p.input_group,this.model.inline?p.inline:null]});this.el.appendChild(e);const{active:t,labels:n}=this.model;this._inputs=[];for(let i=0;ithis.change_active(i))),this._inputs.push(s),this.model.disabled&&(s.disabled=!0),(0,d.includes)(t,i)&&(s.checked=!0);const o=(0,l.label)(s,(0,l.span)(n[i]));e.appendChild(o)}}change_active(e){const t=new Set(this.model.active);t.has(e)?t.delete(e):t.add(e),this.model.active=[...t].sort()}}n.CheckboxGroupView=r,r.__name__=\"CheckboxGroupView\";class h extends c.InputGroup{constructor(e){super(e)}}n.CheckboxGroup=h,a=h,h.__name__=\"CheckboxGroup\",a.prototype.default_view=r,a.define((({Boolean:e,Int:t,String:n,Array:i})=>({active:[i(t),[]],labels:[i(n),[]],inline:[e,!1]})))},\n", - " 452: function _(n,t,e,s,o){s();const r=n(1),u=n(439),c=(0,r.__importDefault)(n(446));class _ extends u.ControlView{*controls(){yield*this._inputs}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.render()))}styles(){return[...super.styles(),c.default]}}e.InputGroupView=_,_.__name__=\"InputGroupView\";class i extends u.Control{constructor(n){super(n)}}e.InputGroup=i,i.__name__=\"InputGroup\"},\n", - " 453: function _(e,t,i,n,o){n();const s=e(1);var l;const r=e(445),c=e(43),a=e(22),d=(0,s.__importStar)(e(446));class h extends r.InputWidgetView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.name.change,(()=>{var e;return this.input_el.name=null!==(e=this.model.name)&&void 0!==e?e:\"\"})),this.connect(this.model.properties.color.change,(()=>this.input_el.value=(0,a.color2hexrgb)(this.model.color))),this.connect(this.model.properties.disabled.change,(()=>this.input_el.disabled=this.model.disabled))}render(){super.render(),this.input_el=(0,c.input)({type:\"color\",class:d.input,name:this.model.name,value:this.model.color,disabled:this.model.disabled}),this.input_el.addEventListener(\"change\",(()=>this.change_input())),this.group_el.appendChild(this.input_el)}change_input(){this.model.color=this.input_el.value,super.change_input()}}i.ColorPickerView=h,h.__name__=\"ColorPickerView\";class p extends r.InputWidget{constructor(e){super(e)}}i.ColorPicker=p,l=p,p.__name__=\"ColorPicker\",l.prototype.default_view=h,l.define((({Color:e})=>({color:[e,\"#000000\"]})))},\n", - " 454: function _(e,t,i,n,s){n();const a=e(1);var l;const o=(0,a.__importDefault)(e(455)),d=e(445),r=e(43),c=e(20),u=e(8),h=(0,a.__importStar)(e(446)),_=(0,a.__importDefault)(e(456));function p(e){const t=[];for(const i of e)if((0,u.isString)(i))t.push(i);else{const[e,n]=i;t.push({from:e,to:n})}return t}class m extends d.InputWidgetView{connect_signals(){super.connect_signals();const{value:e,min_date:t,max_date:i,disabled_dates:n,enabled_dates:s,position:a,inline:l}=this.model.properties;this.connect(e.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.setDate(this.model.value)})),this.connect(t.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"minDate\",this.model.min_date)})),this.connect(i.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"maxDate\",this.model.max_date)})),this.connect(n.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"disable\",this.model.disabled_dates)})),this.connect(s.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"enable\",this.model.enabled_dates)})),this.connect(a.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"position\",this.model.position)})),this.connect(l.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"inline\",this.model.inline)}))}remove(){var e;null===(e=this._picker)||void 0===e||e.destroy(),super.remove()}styles(){return[...super.styles(),_.default]}render(){var e,t;null==this._picker&&(super.render(),this.input_el=(0,r.input)({type:\"text\",class:h.input,disabled:this.model.disabled}),this.group_el.appendChild(this.input_el),this._picker=(0,o.default)(this.input_el,{defaultDate:this.model.value,minDate:null!==(e=this.model.min_date)&&void 0!==e?e:void 0,maxDate:null!==(t=this.model.max_date)&&void 0!==t?t:void 0,inline:this.model.inline,position:this.model.position,disable:p(this.model.disabled_dates),enable:p(this.model.enabled_dates),onChange:(e,t,i)=>this._on_change(e,t,i)}))}_on_change(e,t,i){this.model.value=t,this.change_input()}}i.DatePickerView=m,m.__name__=\"DatePickerView\";class v extends d.InputWidget{constructor(e){super(e)}}i.DatePicker=v,l=v,v.__name__=\"DatePicker\",l.prototype.default_view=m,l.define((({Boolean:e,String:t,Array:i,Tuple:n,Or:s,Nullable:a})=>{const l=i(s(t,n(t,t)));return{value:[t],min_date:[a(t),null],max_date:[a(t),null],disabled_dates:[l,[]],enabled_dates:[l,[]],position:[c.CalendarPosition,\"auto\"],inline:[e,!1]}}))},\n", - " 455: function _(e,n,t,a,i){\n", - " /* flatpickr v4.6.6, @license MIT */var o,r;o=this,r=function(){\"use strict\";\n", - " /*! *****************************************************************************\n", - " Copyright (c) Microsoft Corporation.\n", - " \n", - " Permission to use, copy, modify, and/or distribute this software for any\n", - " purpose with or without fee is hereby granted.\n", - " \n", - " THE SOFTWARE IS PROVIDED \"AS IS\" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH\n", - " REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY\n", - " AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,\n", - " INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM\n", - " LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR\n", - " OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR\n", - " PERFORMANCE OF THIS SOFTWARE.\n", - " ***************************************************************************** */var e=function(){return e=Object.assign||function(e){for(var n,t=1,a=arguments.length;t\",noCalendar:!1,now:new Date,onChange:[],onClose:[],onDayCreate:[],onDestroy:[],onKeyDown:[],onMonthChange:[],onOpen:[],onParseConfig:[],onReady:[],onValueUpdate:[],onYearChange:[],onPreCalendarPosition:[],plugins:[],position:\"auto\",positionElement:void 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e.slice().map((function(e){return\"string\"==typeof e||\"number\"==typeof e||e instanceof Date?w.parseDate(e,void 0,!0):e&&\"object\"==typeof e&&e.from&&e.to?{from:w.parseDate(e.from,void 0),to:w.parseDate(e.to,void 0)}:e})).filter((function(e){return e}))}function pe(e,n){if(void 0!==w.config){var t=w.config[e];if(void 0!==t&&t.length>0)for(var a=0;t[a]&&a1||\"static\"===w.config.monthSelectorType?w.monthElements[n].textContent=h(t.getMonth(),w.config.shorthandCurrentMonth,w.l10n)+\" \":w.monthsDropdownContainer.value=t.getMonth().toString(),e.value=t.getFullYear().toString()})),w._hidePrevMonthArrow=void 0!==w.config.minDate&&(w.currentYear===w.config.minDate.getFullYear()?w.currentMonth<=w.config.minDate.getMonth():w.currentYearw.config.maxDate.getMonth():w.currentYear>w.config.maxDate.getFullYear()))}function we(e){return w.selectedDates.map((function(n){return w.formatDate(n,e)})).filter((function(e,n,t){return\"range\"!==w.config.mode||w.config.enableTime||t.indexOf(e)===n})).join(\"range\"!==w.config.mode?w.config.conjunction:w.l10n.rangeSeparator)}function be(e){void 0===e&&(e=!0),void 0!==w.mobileInput&&w.mobileFormatStr&&(w.mobileInput.value=void 0!==w.latestSelectedDateObj?w.formatDate(w.latestSelectedDateObj,w.mobileFormatStr):\"\"),w.input.value=we(w.config.dateFormat),void 0!==w.altInput&&(w.altInput.value=we(w.config.altFormat)),!1!==e&&pe(\"onValueUpdate\")}function Ce(e){var n=g(e),t=w.prevMonthNav.contains(n),a=w.nextMonthNav.contains(n);t||a?G(t?-1:1):w.yearElements.indexOf(n)>=0?n.select():n.classList.contains(\"arrowUp\")?w.changeYear(w.currentYear+1):n.classList.contains(\"arrowDown\")&&w.changeYear(w.currentYear-1)}return function(){w.element=w.input=p,w.isOpen=!1,function(){var n=[\"wrap\",\"weekNumbers\",\"allowInput\",\"allowInvalidPreload\",\"clickOpens\",\"time_24hr\",\"enableTime\",\"noCalendar\",\"altInput\",\"shorthandCurrentMonth\",\"inline\",\"static\",\"enableSeconds\",\"disableMobile\"],i=e(e({},JSON.parse(JSON.stringify(p.dataset||{}))),v),o={};w.config.parseDate=i.parseDate,w.config.formatDate=i.formatDate,Object.defineProperty(w.config,\"enable\",{get:function(){return w.config._enable},set:function(e){w.config._enable=ge(e)}}),Object.defineProperty(w.config,\"disable\",{get:function(){return w.config._disable},set:function(e){w.config._disable=ge(e)}});var r=\"time\"===i.mode;if(!i.dateFormat&&(i.enableTime||r)){var l=k.defaultConfig.dateFormat||a.dateFormat;o.dateFormat=i.noCalendar||r?\"H:i\"+(i.enableSeconds?\":S\":\"\"):l+\" H:i\"+(i.enableSeconds?\":S\":\"\")}if(i.altInput&&(i.enableTime||r)&&!i.altFormat){var d=k.defaultConfig.altFormat||a.altFormat;o.altFormat=i.noCalendar||r?\"h:i\"+(i.enableSeconds?\":S K\":\" K\"):d+\" h:i\"+(i.enableSeconds?\":S\":\"\")+\" K\"}Object.defineProperty(w.config,\"minDate\",{get:function(){return w.config._minDate},set:oe(\"min\")}),Object.defineProperty(w.config,\"maxDate\",{get:function(){return w.config._maxDate},set:oe(\"max\")});var s=function(e){return function(n){w.config[\"min\"===e?\"_minTime\":\"_maxTime\"]=w.parseDate(n,\"H:i:S\")}};Object.defineProperty(w.config,\"minTime\",{get:function(){return w.config._minTime},set:s(\"min\")}),Object.defineProperty(w.config,\"maxTime\",{get:function(){return w.config._maxTime},set:s(\"max\")}),\"time\"===i.mode&&(w.config.noCalendar=!0,w.config.enableTime=!0),Object.assign(w.config,o,i);for(var u=0;u-1?w.config[m]=c(f[m]).map(x).concat(w.config[m]):void 0===i[m]&&(w.config[m]=f[m])}i.altInputClass||(w.config.altInputClass=re().className+\" \"+w.config.altInputClass),pe(\"onParseConfig\")}(),le(),w.input=re(),w.input?(w.input._type=w.input.type,w.input.type=\"text\",w.input.classList.add(\"flatpickr-input\"),w._input=w.input,w.config.altInput&&(w.altInput=s(w.input.nodeName,w.config.altInputClass),w._input=w.altInput,w.altInput.placeholder=w.input.placeholder,w.altInput.disabled=w.input.disabled,w.altInput.required=w.input.required,w.altInput.tabIndex=w.input.tabIndex,w.altInput.type=\"text\",w.input.setAttribute(\"type\",\"hidden\"),!w.config.static&&w.input.parentNode&&w.input.parentNode.insertBefore(w.altInput,w.input.nextSibling)),w.config.allowInput||w._input.setAttribute(\"readonly\",\"readonly\"),w._positionElement=w.config.positionElement||w._input):w.config.errorHandler(new Error(\"Invalid input element specified\")),function(){w.selectedDates=[],w.now=w.parseDate(w.config.now)||new Date;var e=w.config.defaultDate||(\"INPUT\"!==w.input.nodeName&&\"TEXTAREA\"!==w.input.nodeName||!w.input.placeholder||w.input.value!==w.input.placeholder?w.input.value:null);e&&me(e,w.config.dateFormat),w._initialDate=w.selectedDates.length>0?w.selectedDates[0]:w.config.minDate&&w.config.minDate.getTime()>w.now.getTime()?w.config.minDate:w.config.maxDate&&w.config.maxDate.getTime()0&&(w.latestSelectedDateObj=w.selectedDates[0]),void 0!==w.config.minTime&&(w.config.minTime=w.parseDate(w.config.minTime,\"H:i\")),void 0!==w.config.maxTime&&(w.config.maxTime=w.parseDate(w.config.maxTime,\"H:i\")),w.minDateHasTime=!!w.config.minDate&&(w.config.minDate.getHours()>0||w.config.minDate.getMinutes()>0||w.config.minDate.getSeconds()>0),w.maxDateHasTime=!!w.config.maxDate&&(w.config.maxDate.getHours()>0||w.config.maxDate.getMinutes()>0||w.config.maxDate.getSeconds()>0)}(),w.utils={getDaysInMonth:function(e,n){return void 0===e&&(e=w.currentMonth),void 0===n&&(n=w.currentYear),1===e&&(n%4==0&&n%100!=0||n%400==0)?29:w.l10n.daysInMonth[e]}},w.isMobile||function(){var e=window.document.createDocumentFragment();if(w.calendarContainer=s(\"div\",\"flatpickr-calendar\"),w.calendarContainer.tabIndex=-1,!w.config.noCalendar){if(e.appendChild((w.monthNav=s(\"div\",\"flatpickr-months\"),w.yearElements=[],w.monthElements=[],w.prevMonthNav=s(\"span\",\"flatpickr-prev-month\"),w.prevMonthNav.innerHTML=w.config.prevArrow,w.nextMonthNav=s(\"span\",\"flatpickr-next-month\"),w.nextMonthNav.innerHTML=w.config.nextArrow,q(),Object.defineProperty(w,\"_hidePrevMonthArrow\",{get:function(){return w.__hidePrevMonthArrow},set:function(e){w.__hidePrevMonthArrow!==e&&(d(w.prevMonthNav,\"flatpickr-disabled\",e),w.__hidePrevMonthArrow=e)}}),Object.defineProperty(w,\"_hideNextMonthArrow\",{get:function(){return w.__hideNextMonthArrow},set:function(e){w.__hideNextMonthArrow!==e&&(d(w.nextMonthNav,\"flatpickr-disabled\",e),w.__hideNextMonthArrow=e)}}),w.currentYearElement=w.yearElements[0],De(),w.monthNav)),w.innerContainer=s(\"div\",\"flatpickr-innerContainer\"),w.config.weekNumbers){var n=function(){w.calendarContainer.classList.add(\"hasWeeks\");var e=s(\"div\",\"flatpickr-weekwrapper\");e.appendChild(s(\"span\",\"flatpickr-weekday\",w.l10n.weekAbbreviation));var n=s(\"div\",\"flatpickr-weeks\");return e.appendChild(n),{weekWrapper:e,weekNumbers:n}}(),t=n.weekWrapper,a=n.weekNumbers;w.innerContainer.appendChild(t),w.weekNumbers=a,w.weekWrapper=t}w.rContainer=s(\"div\",\"flatpickr-rContainer\"),w.rContainer.appendChild($()),w.daysContainer||(w.daysContainer=s(\"div\",\"flatpickr-days\"),w.daysContainer.tabIndex=-1),J(),w.rContainer.appendChild(w.daysContainer),w.innerContainer.appendChild(w.rContainer),e.appendChild(w.innerContainer)}w.config.enableTime&&e.appendChild(function(){w.calendarContainer.classList.add(\"hasTime\"),w.config.noCalendar&&w.calendarContainer.classList.add(\"noCalendar\"),w.timeContainer=s(\"div\",\"flatpickr-time\"),w.timeContainer.tabIndex=-1;var e=s(\"span\",\"flatpickr-time-separator\",\":\"),n=m(\"flatpickr-hour\",{\"aria-label\":w.l10n.hourAriaLabel});w.hourElement=n.getElementsByTagName(\"input\")[0];var t=m(\"flatpickr-minute\",{\"aria-label\":w.l10n.minuteAriaLabel});if(w.minuteElement=t.getElementsByTagName(\"input\")[0],w.hourElement.tabIndex=w.minuteElement.tabIndex=-1,w.hourElement.value=o(w.latestSelectedDateObj?w.latestSelectedDateObj.getHours():w.config.time_24hr?w.config.defaultHour:function(e){switch(e%24){case 0:case 12:return 12;default:return 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a=m(\"flatpickr-second\");w.secondElement=a.getElementsByTagName(\"input\")[0],w.secondElement.value=o(w.latestSelectedDateObj?w.latestSelectedDateObj.getSeconds():w.config.defaultSeconds),w.secondElement.setAttribute(\"step\",w.minuteElement.getAttribute(\"step\")),w.secondElement.setAttribute(\"min\",\"0\"),w.secondElement.setAttribute(\"max\",\"59\"),w.timeContainer.appendChild(s(\"span\",\"flatpickr-time-separator\",\":\")),w.timeContainer.appendChild(a)}return w.config.time_24hr||(w.amPM=s(\"span\",\"flatpickr-am-pm\",w.l10n.amPM[r((w.latestSelectedDateObj?w.hourElement.value:w.config.defaultHour)>11)]),w.amPM.title=w.l10n.toggleTitle,w.amPM.tabIndex=-1,w.timeContainer.appendChild(w.amPM)),w.timeContainer}()),d(w.calendarContainer,\"rangeMode\",\"range\"===w.config.mode),d(w.calendarContainer,\"animate\",!0===w.config.animate),d(w.calendarContainer,\"multiMonth\",w.config.showMonths>1),w.calendarContainer.appendChild(e);var i=void 0!==w.config.appendTo&&void 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null!==o&&!1!==o&&(o=Number(o.toFixed(a))),null!==s&&!1!==s&&(s=Number(s.toFixed(a))),[s,o]}f(b=w,r.cssClasses.target),0===r.dir?f(b,r.cssClasses.ltr):f(b,r.cssClasses.rtl),0===r.ort?f(b,r.cssClasses.horizontal):f(b,r.cssClasses.vertical),f(b,\"rtl\"===getComputedStyle(b).direction?r.cssClasses.textDirectionRtl:r.cssClasses.textDirectionLtr),a=T(b,r.cssClasses.base),function(t,e){var n=T(e,r.cssClasses.connects);p=[],(m=[]).push(z(n,t[0]));for(var i=0;i=0&&t .noUi-tooltip{-webkit-transform:translate(50%, 0);transform:translate(50%, 0);left:auto;bottom:10px;}.bk-root .noUi-vertical .noUi-origin > .noUi-tooltip{-webkit-transform:translate(0, -18px);transform:translate(0, -18px);top:auto;right:28px;}.bk-root .noUi-handle{cursor:grab;cursor:-webkit-grab;}.bk-root .noUi-handle.noUi-active{cursor:grabbing;cursor:-webkit-grabbing;}.bk-root .noUi-handle:after,.bk-root .noUi-handle:before{display:none;}.bk-root .noUi-tooltip{display:none;white-space:nowrap;}.bk-root .noUi-handle:hover 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i=e.split(this.options.tokenSeparator),n=0,s=i.length;n0&&void 0!==arguments[0]?arguments[0]:[],t=arguments.length>1?arguments[1]:void 0,i=this.list,n={},s=[];if(\"string\"==typeof i[0]){for(var r=0,o=i.length;r1)throw new Error(\"Key weight has to be > 0 and <= 1\");p=p.name}else a[p]={weight:1};this._analyze({key:p,value:this.options.getFn(h,p),record:h,index:c},{resultMap:n,results:s,tokenSearchers:e,fullSearcher:t})}return{weights:a,results:s}}},{key:\"_analyze\",value:function(e,t){var i=e.key,n=e.arrayIndex,s=void 0===n?-1:n,r=e.value,o=e.record,c=e.index,l=t.tokenSearchers,h=void 0===l?[]:l,u=t.fullSearcher,d=void 0===u?[]:u,p=t.resultMap,m=void 0===p?{}:p,f=t.results,v=void 0===f?[]:f;if(null!=r){var g=!1,_=-1,b=0;if(\"string\"==typeof r){this._log(\"\\nKey: \".concat(\"\"===i?\"-\":i));var y=d.search(r);if(this._log('Full text: \"'.concat(r,'\", score: ').concat(y.score)),this.options.tokenize){for(var E=r.split(this.options.tokenSeparator),I=[],S=0;S-1&&(P=(P+_)/2),this._log(\"Score average:\",P);var D=!this.options.tokenize||!this.options.matchAllTokens||b>=h.length;if(this._log(\"\\nCheck Matches: \".concat(D)),(g||y.isMatch)&&D){var M=m[c];M?M.output.push({key:i,arrayIndex:s,value:r,score:P,matchedIndices:y.matchedIndices}):(m[c]={item:o,output:[{key:i,arrayIndex:s,value:r,score:P,matchedIndices:y.matchedIndices}]},v.push(m[c]))}}else if(a(r))for(var N=0,F=r.length;N-1&&(o.arrayIndex=r.arrayIndex),t.matches.push(o)}}})),this.options.includeScore&&s.push((function(e,t){t.score=e.score}));for(var r=0,o=e.length;ri)return s(e,this.pattern,n);var o=this.options,a=o.location,c=o.distance,l=o.threshold,h=o.findAllMatches,u=o.minMatchCharLength;return r(e,this.pattern,this.patternAlphabet,{location:a,distance:c,threshold:l,findAllMatches:h,minMatchCharLength:u})}}])&&n(t.prototype,i),a&&n(t,a),e}();e.exports=a},function(e,t){var i=/[\\-\\[\\]\\/\\{\\}\\(\\)\\*\\+\\?\\.\\\\\\^\\$\\|]/g;e.exports=function(e,t){var n=arguments.length>2&&void 0!==arguments[2]?arguments[2]:/ +/g,s=new RegExp(t.replace(i,\"\\\\$&\").replace(n,\"|\")),r=e.match(s),o=!!r,a=[];if(o)for(var c=0,l=r.length;c=P;N-=1){var F=N-1,j=i[e.charAt(F)];if(j&&(E[F]=1),M[N]=(M[N+1]<<1|1)&j,0!==T&&(M[N]|=(O[N+1]|O[N])<<1|1|O[N+1]),M[N]&L&&(C=n(t,{errors:T,currentLocation:F,expectedLocation:v,distance:l}))<=_){if(_=C,(b=F)<=v)break;P=Math.max(1,2*v-b)}}if(n(t,{errors:T+1,currentLocation:v,expectedLocation:v,distance:l})>_)break;O=M}return{isMatch:b>=0,score:0===C?.001:C,matchedIndices:s(E,f)}}},function(e,t){e.exports=function(e,t){var i=t.errors,n=void 0===i?0:i,s=t.currentLocation,r=void 0===s?0:s,o=t.expectedLocation,a=void 0===o?0:o,c=t.distance,l=void 0===c?100:c,h=n/e.length,u=Math.abs(a-r);return l?h+u/l:u?1:h}},function(e,t){e.exports=function(){for(var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:[],t=arguments.length>1&&void 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e(e){var t=e.element,i=e.type,n=e.classNames,s=e.position;this.element=t,this.classNames=n,this.type=i,this.position=s,this.isOpen=!1,this.isFlipped=!1,this.isFocussed=!1,this.isDisabled=!1,this.isLoading=!1,this._onFocus=this._onFocus.bind(this),this._onBlur=this._onBlur.bind(this)}var t=e.prototype;return t.addEventListeners=function(){this.element.addEventListener(\"focus\",this._onFocus),this.element.addEventListener(\"blur\",this._onBlur)},t.removeEventListeners=function(){this.element.removeEventListener(\"focus\",this._onFocus),this.element.removeEventListener(\"blur\",this._onBlur)},t.shouldFlip=function(e){if(\"number\"!=typeof e)return!1;var t=!1;return\"auto\"===this.position?t=!window.matchMedia(\"(min-height: 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0===t&&(t=document.createElement(\"div\")),e.nextSibling?e.parentNode.insertBefore(t,e.nextSibling):e.parentNode.appendChild(t),t.appendChild(e)}(e,this.element)},t.unwrap=function(e){this.element.parentNode.insertBefore(e,this.element),this.element.parentNode.removeChild(this.element)},t.addLoadingState=function(){this.element.classList.add(this.classNames.loadingState),this.element.setAttribute(\"aria-busy\",\"true\"),this.isLoading=!0},t.removeLoadingState=function(){this.element.classList.remove(this.classNames.loadingState),this.element.removeAttribute(\"aria-busy\"),this.isLoading=!1},t._onFocus=function(){this.isFocussed=!0},t._onBlur=function(){this.isFocussed=!1},e}();function le(e,t){for(var i=0;i0?this.element.scrollTop+o-s:e.offsetTop;requestAnimationFrame((function(){i._animateScroll(a,t)}))}},t._scrollDown=function(e,t,i){var n=(i-e)/t,s=n>1?n:1;this.element.scrollTop=e+s},t._scrollUp=function(e,t,i){var n=(e-i)/t,s=n>1?n:1;this.element.scrollTop=e-s},t._animateScroll=function(e,t){var i=this,n=this.element.scrollTop,s=!1;t>0?(this._scrollDown(n,4,e),ne&&(s=!0)),s&&requestAnimationFrame((function(){i._animateScroll(e,t)}))},e}();function de(e,t){for(var i=0;i0?\"treeitem\":\"option\"),Object.assign(g.dataset,{choice:\"\",id:l,value:h,selectText:i}),m?(g.classList.add(a),g.dataset.choiceDisabled=\"\",g.setAttribute(\"aria-disabled\",\"true\")):(g.classList.add(r),g.dataset.choiceSelectable=\"\"),g},input:function(e,t){var i=e.input,n=e.inputCloned,s=Object.assign(document.createElement(\"input\"),{type:\"text\",className:i+\" \"+n,autocomplete:\"off\",autocapitalize:\"off\",spellcheck:!1});return s.setAttribute(\"role\",\"textbox\"),s.setAttribute(\"aria-autocomplete\",\"list\"),s.setAttribute(\"aria-label\",t),s},dropdown:function(e){var t=e.list,i=e.listDropdown,n=document.createElement(\"div\");return n.classList.add(t,i),n.setAttribute(\"aria-expanded\",\"false\"),n},notice:function(e,t,i){var n=e.item,s=e.itemChoice,r=e.noResults,o=e.noChoices;void 0===i&&(i=\"\");var a=[n,s];return\"no-choices\"===i?a.push(o):\"no-results\"===i&&a.push(r),Object.assign(document.createElement(\"div\"),{innerHTML:t,className:a.join(\" \")})},option:function(e){var t=e.label,i=e.value,n=e.customProperties,s=e.active,r=e.disabled,o=new Option(t,i,!1,s);return n&&(o.dataset.customProperties=n),o.disabled=r,o}},be=function(e){return void 0===e&&(e=!0),{type:q,active:e}},ye=function(e,t){return{type:$,id:e,highlighted:t}},Ee=function(e){var t=e.value,i=e.id,n=e.active,s=e.disabled;return{type:z,value:t,id:i,active:n,disabled:s}},Ie=function(e){return{type:\"SET_IS_LOADING\",isLoading:e}};function Se(e,t){for(var i=0;i=0?this._store.getGroupById(s):null;return this._store.dispatch(ye(i,!0)),t&&this.passedElement.triggerEvent(H,{id:i,value:o,label:c,groupValue:l&&l.value?l.value:null}),this},r.unhighlightItem=function(e){if(!e)return this;var t=e.id,i=e.groupId,n=void 0===i?-1:i,s=e.value,r=void 0===s?\"\":s,o=e.label,a=void 0===o?\"\":o,c=n>=0?this._store.getGroupById(n):null;return this._store.dispatch(ye(t,!1)),this.passedElement.triggerEvent(H,{id:t,value:r,label:a,groupValue:c&&c.value?c.value:null}),this},r.highlightAll=function(){var e=this;return this._store.items.forEach((function(t){return e.highlightItem(t)})),this},r.unhighlightAll=function(){var e=this;return this._store.items.forEach((function(t){return e.unhighlightItem(t)})),this},r.removeActiveItemsByValue=function(e){var t=this;return this._store.activeItems.filter((function(t){return t.value===e})).forEach((function(e){return t._removeItem(e)})),this},r.removeActiveItems=function(e){var t=this;return this._store.activeItems.filter((function(t){return t.id!==e})).forEach((function(e){return t._removeItem(e)})),this},r.removeHighlightedItems=function(e){var t=this;return void 0===e&&(e=!1),this._store.highlightedActiveItems.forEach((function(i){t._removeItem(i),e&&t._triggerChange(i.value)})),this},r.showDropdown=function(e){var t=this;return this.dropdown.isActive||requestAnimationFrame((function(){t.dropdown.show(),t.containerOuter.open(t.dropdown.distanceFromTopWindow),!e&&t._canSearch&&t.input.focus(),t.passedElement.triggerEvent(D,{})})),this},r.hideDropdown=function(e){var t=this;return this.dropdown.isActive?(requestAnimationFrame((function(){t.dropdown.hide(),t.containerOuter.close(),!e&&t._canSearch&&(t.input.removeActiveDescendant(),t.input.blur()),t.passedElement.triggerEvent(M,{})})),this):this},r.getValue=function(e){void 0===e&&(e=!1);var t=this._store.activeItems.reduce((function(t,i){var n=e?i.value:i;return t.push(n),t}),[]);return this._isSelectOneElement?t[0]:t},r.setValue=function(e){var t=this;return this.initialised?(e.forEach((function(e){return t._setChoiceOrItem(e)})),this):this},r.setChoiceByValue=function(e){var t=this;return!this.initialised||this._isTextElement||(Array.isArray(e)?e:[e]).forEach((function(e){return t._findAndSelectChoiceByValue(e)})),this},r.setChoices=function(e,t,i,n){var s=this;if(void 0===e&&(e=[]),void 0===t&&(t=\"value\"),void 0===i&&(i=\"label\"),void 0===n&&(n=!1),!this.initialised)throw new ReferenceError(\"setChoices was called on a non-initialized instance of Choices\");if(!this._isSelectElement)throw new TypeError(\"setChoices can't be used with INPUT based Choices\");if(\"string\"!=typeof t||!t)throw new TypeError(\"value parameter must be a name of 'value' field in passed objects\");if(n&&this.clearChoices(),\"function\"==typeof e){var r=e(this);if(\"function\"==typeof Promise&&r instanceof Promise)return new Promise((function(e){return requestAnimationFrame(e)})).then((function(){return s._handleLoadingState(!0)})).then((function(){return r})).then((function(e){return s.setChoices(e,t,i,n)})).catch((function(e){s.config.silent||console.error(e)})).then((function(){return s._handleLoadingState(!1)})).then((function(){return s}));if(!Array.isArray(r))throw new TypeError(\".setChoices first argument function must return either array of choices or Promise, got: \"+typeof r);return this.setChoices(r,t,i,!1)}if(!Array.isArray(e))throw new TypeError(\".setChoices must be called either with array of choices with a function resulting into Promise of array of choices\");return this.containerOuter.removeLoadingState(),this._startLoading(),e.forEach((function(e){e.choices?s._addGroup({id:parseInt(e.id,10)||null,group:e,valueKey:t,labelKey:i}):s._addChoice({value:e[t],label:e[i],isSelected:e.selected,isDisabled:e.disabled,customProperties:e.customProperties,placeholder:e.placeholder})})),this._stopLoading(),this},r.clearChoices=function(){return this._store.dispatch({type:U}),this},r.clearStore=function(){return this._store.dispatch({type:\"CLEAR_ALL\"}),this},r.clearInput=function(){var e=!this._isSelectOneElement;return this.input.clear(e),!this._isTextElement&&this._canSearch&&(this._isSearching=!1,this._store.dispatch(be(!0))),this},r._render=function(){if(!this._store.isLoading()){this._currentState=this._store.state;var e=this._currentState.choices!==this._prevState.choices||this._currentState.groups!==this._prevState.groups||this._currentState.items!==this._prevState.items,t=this._isSelectElement,i=this._currentState.items!==this._prevState.items;e&&(t&&this._renderChoices(),i&&this._renderItems(),this._prevState=this._currentState)}},r._renderChoices=function(){var e=this,t=this._store,i=t.activeGroups,n=t.activeChoices,s=document.createDocumentFragment();if(this.choiceList.clear(),this.config.resetScrollPosition&&requestAnimationFrame((function(){return e.choiceList.scrollToTop()})),i.length>=1&&!this._isSearching){var r=n.filter((function(e){return!0===e.placeholder&&-1===e.groupId}));r.length>=1&&(s=this._createChoicesFragment(r,s)),s=this._createGroupsFragment(i,n,s)}else n.length>=1&&(s=this._createChoicesFragment(n,s));if(s.childNodes&&s.childNodes.length>0){var o=this._store.activeItems,a=this._canAddItem(o,this.input.value);a.response?(this.choiceList.append(s),this._highlightChoice()):this.choiceList.append(this._getTemplate(\"notice\",a.notice))}else{var c,l;this._isSearching?(l=\"function\"==typeof this.config.noResultsText?this.config.noResultsText():this.config.noResultsText,c=this._getTemplate(\"notice\",l,\"no-results\")):(l=\"function\"==typeof this.config.noChoicesText?this.config.noChoicesText():this.config.noChoicesText,c=this._getTemplate(\"notice\",l,\"no-choices\")),this.choiceList.append(c)}},r._renderItems=function(){var e=this._store.activeItems||[];this.itemList.clear();var t=this._createItemsFragment(e);t.childNodes&&this.itemList.append(t)},r._createGroupsFragment=function(e,t,i){var n=this;return void 0===i&&(i=document.createDocumentFragment()),this.config.shouldSort&&e.sort(this.config.sorter),e.forEach((function(e){var s=function(e){return t.filter((function(t){return n._isSelectOneElement?t.groupId===e.id:t.groupId===e.id&&(\"always\"===n.config.renderSelectedChoices||!t.selected)}))}(e);if(s.length>=1){var r=n._getTemplate(\"choiceGroup\",e);i.appendChild(r),n._createChoicesFragment(s,i,!0)}})),i},r._createChoicesFragment=function(e,t,i){var n=this;void 0===t&&(t=document.createDocumentFragment()),void 0===i&&(i=!1);var s=this.config,r=s.renderSelectedChoices,o=s.searchResultLimit,a=s.renderChoiceLimit,c=this._isSearching?w:this.config.sorter,l=function(e){if(\"auto\"!==r||n._isSelectOneElement||!e.selected){var i=n._getTemplate(\"choice\",e,n.config.itemSelectText);t.appendChild(i)}},h=e;\"auto\"!==r||this._isSelectOneElement||(h=e.filter((function(e){return!e.selected})));var u=h.reduce((function(e,t){return t.placeholder?e.placeholderChoices.push(t):e.normalChoices.push(t),e}),{placeholderChoices:[],normalChoices:[]}),d=u.placeholderChoices,p=u.normalChoices;(this.config.shouldSort||this._isSearching)&&p.sort(c);var m=h.length,f=this._isSelectOneElement?[].concat(d,p):p;this._isSearching?m=o:a&&a>0&&!i&&(m=a);for(var v=0;v=n){var o=s?this._searchChoices(e):0;this.passedElement.triggerEvent(j,{value:e,resultCount:o})}else r&&(this._isSearching=!1,this._store.dispatch(be(!0)))}},r._canAddItem=function(e,t){var i=!0,n=\"function\"==typeof this.config.addItemText?this.config.addItemText(t):this.config.addItemText;if(!this._isSelectOneElement){var s=function(e,t,i){return void 0===i&&(i=\"value\"),e.some((function(e){return\"string\"==typeof t?e[i]===t.trim():e[i]===t}))}(e,t);this.config.maxItemCount>0&&this.config.maxItemCount<=e.length&&(i=!1,n=\"function\"==typeof this.config.maxItemText?this.config.maxItemText(this.config.maxItemCount):this.config.maxItemText),!this.config.duplicateItemsAllowed&&s&&i&&(i=!1,n=\"function\"==typeof this.config.uniqueItemText?this.config.uniqueItemText(t):this.config.uniqueItemText),this._isTextElement&&this.config.addItems&&i&&\"function\"==typeof this.config.addItemFilter&&!this.config.addItemFilter(t)&&(i=!1,n=\"function\"==typeof this.config.customAddItemText?this.config.customAddItemText(t):this.config.customAddItemText)}return{response:i,notice:n}},r._searchChoices=function(e){var t=\"string\"==typeof e?e.trim():e,i=\"string\"==typeof this._currentValue?this._currentValue.trim():this._currentValue;if(t.length<1&&t===i+\" \")return 0;var n=this._store.searchableChoices,r=t,o=[].concat(this.config.searchFields),a=Object.assign(this.config.fuseOptions,{keys:o}),c=new s.a(n,a).search(r);return this._currentValue=t,this._highlightPosition=0,this._isSearching=!0,this._store.dispatch(function(e){return{type:G,results:e}}(c)),c.length},r._addEventListeners=function(){var e=document.documentElement;e.addEventListener(\"touchend\",this._onTouchEnd,!0),this.containerOuter.element.addEventListener(\"keydown\",this._onKeyDown,!0),this.containerOuter.element.addEventListener(\"mousedown\",this._onMouseDown,!0),e.addEventListener(\"click\",this._onClick,{passive:!0}),e.addEventListener(\"touchmove\",this._onTouchMove,{passive:!0}),this.dropdown.element.addEventListener(\"mouseover\",this._onMouseOver,{passive:!0}),this._isSelectOneElement&&(this.containerOuter.element.addEventListener(\"focus\",this._onFocus,{passive:!0}),this.containerOuter.element.addEventListener(\"blur\",this._onBlur,{passive:!0})),this.input.element.addEventListener(\"keyup\",this._onKeyUp,{passive:!0}),this.input.element.addEventListener(\"focus\",this._onFocus,{passive:!0}),this.input.element.addEventListener(\"blur\",this._onBlur,{passive:!0}),this.input.element.form&&this.input.element.form.addEventListener(\"reset\",this._onFormReset,{passive:!0}),this.input.addEventListeners()},r._removeEventListeners=function(){var e=document.documentElement;e.removeEventListener(\"touchend\",this._onTouchEnd,!0),this.containerOuter.element.removeEventListener(\"keydown\",this._onKeyDown,!0),this.containerOuter.element.removeEventListener(\"mousedown\",this._onMouseDown,!0),e.removeEventListener(\"click\",this._onClick),e.removeEventListener(\"touchmove\",this._onTouchMove),this.dropdown.element.removeEventListener(\"mouseover\",this._onMouseOver),this._isSelectOneElement&&(this.containerOuter.element.removeEventListener(\"focus\",this._onFocus),this.containerOuter.element.removeEventListener(\"blur\",this._onBlur)),this.input.element.removeEventListener(\"keyup\",this._onKeyUp),this.input.element.removeEventListener(\"focus\",this._onFocus),this.input.element.removeEventListener(\"blur\",this._onBlur),this.input.element.form&&this.input.element.form.removeEventListener(\"reset\",this._onFormReset),this.input.removeEventListeners()},r._onKeyDown=function(e){var t,i=e.target,n=e.keyCode,s=e.ctrlKey,r=e.metaKey,o=this._store.activeItems,a=this.input.isFocussed,c=this.dropdown.isActive,l=this.itemList.hasChildren(),h=String.fromCharCode(n),u=J,d=Y,p=Z,m=Q,f=ee,v=te,g=ie,_=ne,b=se,y=s||r;!this._isTextElement&&/[a-zA-Z0-9-_ ]/.test(h)&&this.showDropdown();var E=((t={})[m]=this._onAKey,t[p]=this._onEnterKey,t[f]=this._onEscapeKey,t[v]=this._onDirectionKey,t[_]=this._onDirectionKey,t[g]=this._onDirectionKey,t[b]=this._onDirectionKey,t[d]=this._onDeleteKey,t[u]=this._onDeleteKey,t);E[n]&&E[n]({event:e,target:i,keyCode:n,metaKey:r,activeItems:o,hasFocusedInput:a,hasActiveDropdown:c,hasItems:l,hasCtrlDownKeyPressed:y})},r._onKeyUp=function(e){var t=e.target,i=e.keyCode,n=this.input.value,s=this._store.activeItems,r=this._canAddItem(s,n),o=J,a=Y;if(this._isTextElement)if(r.notice&&n){var c=this._getTemplate(\"notice\",r.notice);this.dropdown.element.innerHTML=c.outerHTML,this.showDropdown(!0)}else this.hideDropdown(!0);else{var l=(i===o||i===a)&&!t.value,h=!this._isTextElement&&this._isSearching,u=this._canSearch&&r.response;l&&h?(this._isSearching=!1,this._store.dispatch(be(!0))):u&&this._handleSearch(this.input.value)}this._canSearch=this.config.searchEnabled},r._onAKey=function(e){var t=e.hasItems;e.hasCtrlDownKeyPressed&&t&&(this._canSearch=!1,this.config.removeItems&&!this.input.value&&this.input.element===document.activeElement&&this.highlightAll())},r._onEnterKey=function(e){var t=e.event,i=e.target,n=e.activeItems,s=e.hasActiveDropdown,r=Z,o=i.hasAttribute(\"data-button\");if(this._isTextElement&&i.value){var a=this.input.value;this._canAddItem(n,a).response&&(this.hideDropdown(!0),this._addItem({value:a}),this._triggerChange(a),this.clearInput())}if(o&&(this._handleButtonAction(n,i),t.preventDefault()),s){var c=this.dropdown.getChild(\".\"+this.config.classNames.highlightedState);c&&(n[0]&&(n[0].keyCode=r),this._handleChoiceAction(n,c)),t.preventDefault()}else this._isSelectOneElement&&(this.showDropdown(),t.preventDefault())},r._onEscapeKey=function(e){e.hasActiveDropdown&&(this.hideDropdown(!0),this.containerOuter.focus())},r._onDirectionKey=function(e){var t,i,n,s=e.event,r=e.hasActiveDropdown,o=e.keyCode,a=e.metaKey,c=ie,l=ne,h=se;if(r||this._isSelectOneElement){this.showDropdown(),this._canSearch=!1;var u,d=o===c||o===h?1:-1,p=\"[data-choice-selectable]\";if(a||o===h||o===l)u=d>0?this.dropdown.element.querySelector(\"[data-choice-selectable]:last-of-type\"):this.dropdown.element.querySelector(p);else{var m=this.dropdown.element.querySelector(\".\"+this.config.classNames.highlightedState);u=m?function(e,t,i){if(void 0===i&&(i=1),e instanceof Element&&\"string\"==typeof t){for(var n=(i>0?\"next\":\"previous\")+\"ElementSibling\",s=e[n];s;){if(s.matches(t))return s;s=s[n]}return s}}(m,p,d):this.dropdown.element.querySelector(p)}u&&(t=u,i=this.choiceList.element,void 0===(n=d)&&(n=1),t&&(n>0?i.scrollTop+i.offsetHeight>=t.offsetTop+t.offsetHeight:t.offsetTop>=i.scrollTop)||this.choiceList.scrollToChildElement(u,d),this._highlightChoice(u)),s.preventDefault()}},r._onDeleteKey=function(e){var t=e.event,i=e.target,n=e.hasFocusedInput,s=e.activeItems;!n||i.value||this._isSelectOneElement||(this._handleBackspace(s),t.preventDefault())},r._onTouchMove=function(){this._wasTap&&(this._wasTap=!1)},r._onTouchEnd=function(e){var t=(e||e.touches[0]).target;this._wasTap&&this.containerOuter.element.contains(t)&&((t===this.containerOuter.element||t===this.containerInner.element)&&(this._isTextElement?this.input.focus():this._isSelectMultipleElement&&this.showDropdown()),e.stopPropagation()),this._wasTap=!0},r._onMouseDown=function(e){var t=e.target;if(t instanceof HTMLElement){if(we&&this.choiceList.element.contains(t)){var i=this.choiceList.element.firstElementChild,n=\"ltr\"===this._direction?e.offsetX>=i.offsetWidth:e.offsetX0&&this.unhighlightAll(),this.containerOuter.removeFocusState(),this.hideDropdown(!0))},r._onFocus=function(e){var t,i=this,n=e.target;this.containerOuter.element.contains(n)&&((t={}).text=function(){n===i.input.element&&i.containerOuter.addFocusState()},t[\"select-one\"]=function(){i.containerOuter.addFocusState(),n===i.input.element&&i.showDropdown(!0)},t[\"select-multiple\"]=function(){n===i.input.element&&(i.showDropdown(!0),i.containerOuter.addFocusState())},t)[this.passedElement.element.type]()},r._onBlur=function(e){var t=this,i=e.target;if(this.containerOuter.element.contains(i)&&!this._isScrollingOnIe){var n,s=this._store.activeItems.some((function(e){return e.highlighted}));((n={}).text=function(){i===t.input.element&&(t.containerOuter.removeFocusState(),s&&t.unhighlightAll(),t.hideDropdown(!0))},n[\"select-one\"]=function(){t.containerOuter.removeFocusState(),(i===t.input.element||i===t.containerOuter.element&&!t._canSearch)&&t.hideDropdown(!0)},n[\"select-multiple\"]=function(){i===t.input.element&&(t.containerOuter.removeFocusState(),t.hideDropdown(!0),s&&t.unhighlightAll())},n)[this.passedElement.element.type]()}else this._isScrollingOnIe=!1,this.input.element.focus()},r._onFormReset=function(){this._store.dispatch({type:\"RESET_TO\",state:this._initialState})},r._highlightChoice=function(e){var t=this;void 0===e&&(e=null);var i=Array.from(this.dropdown.element.querySelectorAll(\"[data-choice-selectable]\"));if(i.length){var n=e;Array.from(this.dropdown.element.querySelectorAll(\".\"+this.config.classNames.highlightedState)).forEach((function(e){e.classList.remove(t.config.classNames.highlightedState),e.setAttribute(\"aria-selected\",\"false\")})),n?this._highlightPosition=i.indexOf(n):(n=i.length>this._highlightPosition?i[this._highlightPosition]:i[i.length-1])||(n=i[0]),n.classList.add(this.config.classNames.highlightedState),n.setAttribute(\"aria-selected\",\"true\"),this.passedElement.triggerEvent(B,{el:n}),this.dropdown.isActive&&(this.input.setActiveDescendant(n.id),this.containerOuter.setActiveDescendant(n.id))}},r._addItem=function(e){var t=e.value,i=e.label,n=void 0===i?null:i,s=e.choiceId,r=void 0===s?-1:s,o=e.groupId,a=void 0===o?-1:o,c=e.customProperties,l=void 0===c?null:c,h=e.placeholder,u=void 0!==h&&h,d=e.keyCode,p=void 0===d?null:d,m=\"string\"==typeof t?t.trim():t,f=p,v=l,g=this._store.items,_=n||m,b=r||-1,y=a>=0?this._store.getGroupById(a):null,E=g?g.length+1:1;return this.config.prependValue&&(m=this.config.prependValue+m.toString()),this.config.appendValue&&(m+=this.config.appendValue.toString()),this._store.dispatch(function(e){var t=e.value,i=e.label,n=e.id,s=e.choiceId,r=e.groupId,o=e.customProperties,a=e.placeholder,c=e.keyCode;return{type:W,value:t,label:i,id:n,choiceId:s,groupId:r,customProperties:o,placeholder:a,keyCode:c}}({value:m,label:_,id:E,choiceId:b,groupId:a,customProperties:l,placeholder:u,keyCode:f})),this._isSelectOneElement&&this.removeActiveItems(E),this.passedElement.triggerEvent(K,{id:E,value:m,label:_,customProperties:v,groupValue:y&&y.value?y.value:void 0,keyCode:f}),this},r._removeItem=function(e){if(!e||!E(\"Object\",e))return this;var t=e.id,i=e.value,n=e.label,s=e.choiceId,r=e.groupId,o=r>=0?this._store.getGroupById(r):null;return this._store.dispatch(function(e,t){return{type:X,id:e,choiceId:t}}(t,s)),o&&o.value?this.passedElement.triggerEvent(R,{id:t,value:i,label:n,groupValue:o.value}):this.passedElement.triggerEvent(R,{id:t,value:i,label:n}),this},r._addChoice=function(e){var t=e.value,i=e.label,n=void 0===i?null:i,s=e.isSelected,r=void 0!==s&&s,o=e.isDisabled,a=void 0!==o&&o,c=e.groupId,l=void 0===c?-1:c,h=e.customProperties,u=void 0===h?null:h,d=e.placeholder,p=void 0!==d&&d,m=e.keyCode,f=void 0===m?null:m;if(null!=t){var v=this._store.choices,g=n||t,_=v?v.length+1:1,b=this._baseId+\"-\"+this._idNames.itemChoice+\"-\"+_;this._store.dispatch(function(e){var t=e.value,i=e.label,n=e.id,s=e.groupId,r=e.disabled,o=e.elementId,a=e.customProperties,c=e.placeholder,l=e.keyCode;return{type:V,value:t,label:i,id:n,groupId:s,disabled:r,elementId:o,customProperties:a,placeholder:c,keyCode:l}}({id:_,groupId:l,elementId:b,value:t,label:g,disabled:a,customProperties:u,placeholder:p,keyCode:f})),r&&this._addItem({value:t,label:g,choiceId:_,customProperties:u,placeholder:p,keyCode:f})}},r._addGroup=function(e){var t=this,i=e.group,n=e.id,s=e.valueKey,r=void 0===s?\"value\":s,o=e.labelKey,a=void 0===o?\"label\":o,c=E(\"Object\",i)?i.choices:Array.from(i.getElementsByTagName(\"OPTION\")),l=n||Math.floor((new Date).valueOf()*Math.random()),h=!!i.disabled&&i.disabled;c?(this._store.dispatch(Ee({value:i.label,id:l,active:!0,disabled:h})),c.forEach((function(e){var i=e.disabled||e.parentNode&&e.parentNode.disabled;t._addChoice({value:e[r],label:E(\"Object\",e)?e[a]:e.innerHTML,isSelected:e.selected,isDisabled:i,groupId:l,customProperties:e.customProperties,placeholder:e.placeholder})}))):this._store.dispatch(Ee({value:i.label,id:i.id,active:!1,disabled:i.disabled}))},r._getTemplate=function(e){var t;if(!e)return null;for(var i=this.config.classNames,n=arguments.length,s=new Array(n>1?n-1:0),r=1;r{var e;return this.input_el.name=null!==(e=this.model.name)&&void 0!==e?e:\"\"})),this.connect(this.model.properties.value.change,(()=>{this.input_el.value=this.format_value,this.old_value=this.input_el.value})),this.connect(this.model.properties.low.change,(()=>{const{value:e,low:t,high:l}=this.model;null!=t&&null!=l&&(0,p.assert)(t<=l,\"Invalid bounds, low must be inferior to high\"),null!=e&&null!=t&&e{const{value:e,low:t,high:l}=this.model;null!=t&&null!=l&&(0,p.assert)(l>=t,\"Invalid bounds, high must be superior to low\"),null!=e&&null!=l&&e>l&&(this.model.value=l)})),this.connect(this.model.properties.high.change,(()=>this.input_el.placeholder=this.model.placeholder)),this.connect(this.model.properties.disabled.change,(()=>this.input_el.disabled=this.model.disabled)),this.connect(this.model.properties.placeholder.change,(()=>this.input_el.placeholder=this.model.placeholder))}get format_value(){return null!=this.model.value?this.model.pretty(this.model.value):\"\"}_set_input_filter(e){this.input_el.addEventListener(\"input\",(()=>{const{selectionStart:t,selectionEnd:l}=this.input_el;if(e(this.input_el.value))this.old_value=this.input_el.value;else{const e=this.old_value.length-this.input_el.value.length;this.input_el.value=this.old_value,t&&l&&this.input_el.setSelectionRange(t-1,l+e)}}))}render(){super.render(),this.input_el=(0,r.input)({type:\"text\",class:_.input,name:this.model.name,value:this.format_value,disabled:this.model.disabled,placeholder:this.model.placeholder}),this.old_value=this.format_value,this.set_input_filter(),this.input_el.addEventListener(\"change\",(()=>this.change_input())),this.input_el.addEventListener(\"focusout\",(()=>this.input_el.value=this.format_value)),this.group_el.appendChild(this.input_el)}set_input_filter(){\"int\"==this.model.mode?this._set_input_filter((e=>m.test(e))):\"float\"==this.model.mode&&this._set_input_filter((e=>c.test(e)))}bound_value(e){let t=e;const{low:l,high:i}=this.model;return t=null!=l?Math.max(l,t):t,t=null!=i?Math.min(i,t):t,t}get value(){let e=\"\"!=this.input_el.value?Number(this.input_el.value):null;return null!=e&&(e=this.bound_value(e)),e}change_input(){null==this.value?this.model.value=null:Number.isNaN(this.value)||(this.model.value=this.value)}}l.NumericInputView=v,v.__name__=\"NumericInputView\";class g extends o.InputWidget{constructor(e){super(e)}_formatter(e,t){return(0,d.isString)(t)?h.format(e,t):t.doFormat([e],{loc:0})[0]}pretty(e){return null!=this.format?this._formatter(e,this.format):`${e}`}}l.NumericInput=g,u=g,g.__name__=\"NumericInput\",u.prototype.default_view=v,u.define((({Number:e,String:t,Enum:l,Ref:i,Or:n,Nullable:s})=>({value:[s(e),null],placeholder:[t,\"\"],mode:[l(\"int\",\"float\"),\"int\"],format:[s(n(t,i(a.TickFormatter))),null],low:[s(e),null],high:[s(e),null]})))},\n", - " 475: function _(e,t,r,s,n){var a;s();const o=e(464),_=e(43);class p extends o.MarkupView{render(){super.render();const e=(0,_.pre)({style:{overflow:\"auto\"}},this.model.text);this.markup_el.appendChild(e)}}r.PreTextView=p,p.__name__=\"PreTextView\";class u extends o.Markup{constructor(e){super(e)}}r.PreText=u,a=u,u.__name__=\"PreText\",a.prototype.default_view=p},\n", - " 476: function _(t,o,e,a,i){a();const n=t(1);var u;const s=t(449),c=t(43),_=(0,n.__importStar)(t(318));class r extends s.ButtonGroupView{change_active(t){this.model.active!==t&&(this.model.active=t)}_update_active(){const{active:t}=this.model;this._buttons.forEach(((o,e)=>{(0,c.classes)(o).toggle(_.active,t===e)}))}}e.RadioButtonGroupView=r,r.__name__=\"RadioButtonGroupView\";class l extends s.ButtonGroup{constructor(t){super(t)}}e.RadioButtonGroup=l,u=l,l.__name__=\"RadioButtonGroup\",u.prototype.default_view=r,u.define((({Int:t,Nullable:o})=>({active:[o(t),null]})))},\n", - " 477: function _(e,n,i,t,a){t();const s=e(1);var l;const o=e(43),d=e(34),p=e(452),r=(0,s.__importStar)(e(446));class u extends p.InputGroupView{render(){super.render();const e=(0,o.div)({class:[r.input_group,this.model.inline?r.inline:null]});this.el.appendChild(e);const n=(0,d.uniqueId)(),{active:i,labels:t}=this.model;this._inputs=[];for(let a=0;athis.change_active(a))),this._inputs.push(s),this.model.disabled&&(s.disabled=!0),a==i&&(s.checked=!0);const l=(0,o.label)(s,(0,o.span)(t[a]));e.appendChild(l)}}change_active(e){this.model.active=e}}i.RadioGroupView=u,u.__name__=\"RadioGroupView\";class c extends p.InputGroup{constructor(e){super(e)}}i.RadioGroup=c,l=c,c.__name__=\"RadioGroup\",l.prototype.default_view=u,l.define((({Boolean:e,Int:n,String:i,Array:t,Nullable:a})=>({active:[a(n),null],labels:[t(i),[]],inline:[e,!1]})))},\n", - " 478: function _(e,r,t,a,i){a();var n;const o=(0,e(1).__importStar)(e(153)),s=e(458),_=e(8);class d extends s.AbstractRangeSliderView{}t.RangeSliderView=d,d.__name__=\"RangeSliderView\";class c extends s.AbstractSlider{constructor(e){super(e),this.behaviour=\"drag\",this.connected=[!1,!0,!1]}_formatter(e,r){return(0,_.isString)(r)?o.format(e,r):r.compute(e)}}t.RangeSlider=c,n=c,c.__name__=\"RangeSlider\",n.prototype.default_view=d,n.override({format:\"0[.]00\"})},\n", - " 479: function _(e,t,n,s,i){s();const l=e(1);var u;const a=e(43),o=e(8),p=e(13),_=e(445),r=(0,l.__importStar)(e(446));class c extends _.InputWidgetView{constructor(){super(...arguments),this._known_values=new Set}connect_signals(){super.connect_signals();const{value:e,options:t}=this.model.properties;this.on_change(e,(()=>{this._update_value()})),this.on_change(t,(()=>{(0,a.empty)(this.input_el),(0,a.append)(this.input_el,...this.options_el()),this._update_value()}))}options_el(){const{_known_values:e}=this;function t(t){return t.map((t=>{let n,s;return(0,o.isString)(t)?n=s=t:[n,s]=t,e.add(n),(0,a.option)({value:n},s)}))}e.clear();const{options:n}=this.model;return(0,o.isArray)(n)?t(n):(0,p.entries)(n).map((([e,n])=>(0,a.optgroup)({label:e},t(n))))}render(){super.render(),this.input_el=(0,a.select)({class:r.input,name:this.model.name,disabled:this.model.disabled},this.options_el()),this._update_value(),this.input_el.addEventListener(\"change\",(()=>this.change_input())),this.group_el.appendChild(this.input_el)}change_input(){const e=this.input_el.value;this.model.value=e,super.change_input()}_update_value(){const{value:e}=this.model;this._known_values.has(e)?this.input_el.value=e:this.input_el.removeAttribute(\"value\")}}n.SelectView=c,c.__name__=\"SelectView\";class h extends _.InputWidget{constructor(e){super(e)}}n.Select=h,u=h,h.__name__=\"Select\",u.prototype.default_view=c,u.define((({String:e,Array:t,Tuple:n,Dict:s,Or:i})=>{const l=t(i(e,n(e,e)));return{value:[e,\"\"],options:[i(l,s(l)),[]]}}))},\n", - " 480: function _(e,t,r,i,a){i();var o;const s=(0,e(1).__importStar)(e(153)),_=e(458),n=e(8);class c extends _.AbstractSliderView{}r.SliderView=c,c.__name__=\"SliderView\";class d extends _.AbstractSlider{constructor(e){super(e),this.behaviour=\"tap\",this.connected=[!0,!1]}_formatter(e,t){return(0,n.isString)(t)?s.format(e,t):t.compute(e)}}r.Slider=d,o=d,d.__name__=\"Slider\",o.prototype.default_view=c,o.override({format:\"0[.]00\"})},\n", - " 481: function _(e,t,i,n,s){var l;n();const o=e(474),r=e(43),{min:a,max:h,floor:_,abs:u}=Math;function d(e){return _(e)!==e?e.toFixed(16).replace(/0+$/,\"\").split(\".\")[1].length:0}class p extends o.NumericInputView{*buttons(){yield this.btn_up_el,yield this.btn_down_el}initialize(){super.initialize(),this._handles={interval:void 0,timeout:void 0},this._interval=200}connect_signals(){super.connect_signals();const e=this.model.properties;this.on_change(e.disabled,(()=>{for(const e of this.buttons())(0,r.toggle_attribute)(e,\"disabled\",this.model.disabled)}))}render(){super.render(),this.wrapper_el=(0,r.div)({class:\"bk-spin-wrapper\"}),this.group_el.replaceChild(this.wrapper_el,this.input_el),this.btn_up_el=(0,r.button)({class:\"bk-spin-btn bk-spin-btn-up\"}),this.btn_down_el=(0,r.button)({class:\"bk-spin-btn bk-spin-btn-down\"}),this.wrapper_el.appendChild(this.input_el),this.wrapper_el.appendChild(this.btn_up_el),this.wrapper_el.appendChild(this.btn_down_el);for(const e of this.buttons())(0,r.toggle_attribute)(e,\"disabled\",this.model.disabled),e.addEventListener(\"mousedown\",(e=>this._btn_mouse_down(e))),e.addEventListener(\"mouseup\",(()=>this._btn_mouse_up())),e.addEventListener(\"mouseleave\",(()=>this._btn_mouse_leave()));this.input_el.addEventListener(\"keydown\",(e=>this._input_key_down(e))),this.input_el.addEventListener(\"keyup\",(()=>this.model.value_throttled=this.model.value)),this.input_el.addEventListener(\"wheel\",(e=>this._input_mouse_wheel(e))),this.input_el.addEventListener(\"wheel\",function(e,t,i=!1){let n;return function(...s){const l=this,o=i&&void 0===n;void 0!==n&&clearTimeout(n),n=setTimeout((function(){n=void 0,i||e.apply(l,s)}),t),o&&e.apply(l,s)}}((()=>{this.model.value_throttled=this.model.value}),this.model.wheel_wait,!1))}get precision(){const{low:e,high:t,step:i}=this.model,n=d;return h(n(u(null!=e?e:0)),n(u(null!=t?t:0)),n(u(i)))}remove(){this._stop_incrementation(),super.remove()}_start_incrementation(e){clearInterval(this._handles.interval),this._counter=0;const{step:t}=this.model,i=e=>{if(this._counter+=1,this._counter%5==0){const t=Math.floor(this._counter/5);t<10?(clearInterval(this._handles.interval),this._handles.interval=setInterval((()=>i(e)),this._interval/(t+1))):t>=10&&t<=13&&(clearInterval(this._handles.interval),this._handles.interval=setInterval((()=>i(2*e)),this._interval/10))}this.increment(e)};this._handles.interval=setInterval((()=>i(e*t)),this._interval)}_stop_incrementation(){clearTimeout(this._handles.timeout),this._handles.timeout=void 0,clearInterval(this._handles.interval),this._handles.interval=void 0,this.model.value_throttled=this.model.value}_btn_mouse_down(e){e.preventDefault();const t=e.currentTarget===this.btn_up_el?1:-1;this.increment(t*this.model.step),this.input_el.focus(),this._handles.timeout=setTimeout((()=>this._start_incrementation(t)),this._interval)}_btn_mouse_up(){this._stop_incrementation()}_btn_mouse_leave(){this._stop_incrementation()}_input_mouse_wheel(e){if(document.activeElement===this.input_el){e.preventDefault();const t=e.deltaY>0?-1:1;this.increment(t*this.model.step)}}_input_key_down(e){switch(e.keyCode){case r.Keys.Up:return e.preventDefault(),this.increment(this.model.step);case r.Keys.Down:return e.preventDefault(),this.increment(-this.model.step);case r.Keys.PageUp:return e.preventDefault(),this.increment(this.model.page_step_multiplier*this.model.step);case r.Keys.PageDown:return e.preventDefault(),this.increment(-this.model.page_step_multiplier*this.model.step)}}adjust_to_precision(e){return this.bound_value(Number(e.toFixed(this.precision)))}increment(e){const{low:t,high:i}=this.model;null==this.model.value?e>0?this.model.value=null!=t?t:null!=i?a(0,i):0:e<0&&(this.model.value=null!=i?i:null!=t?h(t,0):0):this.model.value=this.adjust_to_precision(this.model.value+e)}change_input(){super.change_input(),this.model.value_throttled=this.model.value}}i.SpinnerView=p,p.__name__=\"SpinnerView\";class m extends o.NumericInput{constructor(e){super(e)}}i.Spinner=m,l=m,m.__name__=\"Spinner\",l.prototype.default_view=p,l.define((({Number:e,Nullable:t})=>({value_throttled:[t(e),null],step:[e,1],page_step_multiplier:[e,10],wheel_wait:[e,100]}))),l.override({mode:\"float\"})},\n", - " 482: function _(e,t,s,n,i){n();const o=e(1);var r;const c=e(444),l=e(43),p=(0,o.__importStar)(e(446));class _ extends c.TextLikeInputView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.rows.change,(()=>this.input_el.rows=this.model.rows)),this.connect(this.model.properties.cols.change,(()=>this.input_el.cols=this.model.cols))}_render_input(){this.input_el=(0,l.textarea)({class:p.input})}render(){super.render(),this.input_el.cols=this.model.cols,this.input_el.rows=this.model.rows}}s.TextAreaInputView=_,_.__name__=\"TextAreaInputView\";class a extends c.TextLikeInput{constructor(e){super(e)}}s.TextAreaInput=a,r=a,a.__name__=\"TextAreaInput\",r.prototype.default_view=_,r.define((({Int:e})=>({cols:[e,20],rows:[e,2]}))),r.override({max_length:500})},\n", - " 483: function _(e,t,s,c,i){c();const o=e(1);var a;const n=e(438),l=e(43),_=(0,o.__importStar)(e(318));class r extends n.AbstractButtonView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,(()=>this._update_active()))}render(){super.render(),this._update_active()}click(){this.model.active=!this.model.active,super.click()}_update_active(){(0,l.classes)(this.button_el).toggle(_.active,this.model.active)}}s.ToggleView=r,r.__name__=\"ToggleView\";class g extends n.AbstractButton{constructor(e){super(e)}}s.Toggle=g,a=g,g.__name__=\"Toggle\",a.prototype.default_view=r,a.define((({Boolean:e})=>({active:[e,!1]}))),a.override({label:\"Toggle\"})},\n", - " }, 436, {\"models/widgets/main\":436,\"models/widgets/index\":437,\"models/widgets/abstract_button\":438,\"models/widgets/control\":439,\"models/widgets/widget\":508,\"models/widgets/abstract_icon\":441,\"models/widgets/autocomplete_input\":442,\"models/widgets/text_input\":443,\"models/widgets/text_like_input\":444,\"models/widgets/input_widget\":445,\"styles/widgets/inputs.css\":446,\"models/widgets/button\":447,\"models/widgets/checkbox_button_group\":448,\"models/widgets/button_group\":449,\"models/widgets/oriented_control\":450,\"models/widgets/checkbox_group\":451,\"models/widgets/input_group\":452,\"models/widgets/color_picker\":453,\"models/widgets/date_picker\":454,\"styles/widgets/flatpickr.css\":456,\"models/widgets/date_range_slider\":457,\"models/widgets/abstract_slider\":458,\"styles/widgets/sliders.css\":460,\"styles/widgets/nouislider.css\":461,\"models/widgets/date_slider\":462,\"models/widgets/div\":463,\"models/widgets/markup\":464,\"styles/clearfix.css\":465,\"models/widgets/dropdown\":466,\"models/widgets/file_input\":467,\"models/widgets/multiselect\":468,\"models/widgets/paragraph\":469,\"models/widgets/password_input\":470,\"models/widgets/multichoice\":471,\"styles/widgets/choices.css\":473,\"models/widgets/numeric_input\":474,\"models/widgets/pretext\":475,\"models/widgets/radio_button_group\":476,\"models/widgets/radio_group\":477,\"models/widgets/range_slider\":478,\"models/widgets/selectbox\":479,\"models/widgets/slider\":480,\"models/widgets/spinner\":481,\"models/widgets/textarea_input\":482,\"models/widgets/toggle\":483}, {});});\n", - "\n", - " /* END bokeh-widgets.min.js */\n", - " },\n", - " \n", - " function(Bokeh) {\n", - " /* BEGIN bokeh-tables.min.js */\n", - " /*!\n", - " * Copyright (c) 2012 - 2021, Anaconda, Inc., and Bokeh Contributors\n", - " * All rights reserved.\n", - " * \n", - " * Redistribution and use in source and binary forms, with or without modification,\n", - " * are permitted provided that the following conditions are met:\n", - " * \n", - " * Redistributions of source code must retain the above copyright notice,\n", - " * this list of conditions and the following disclaimer.\n", - " * \n", - " * Redistributions in binary form must reproduce the above copyright notice,\n", - " * this list of conditions and the following disclaimer in the documentation\n", - " * and/or other materials provided with the distribution.\n", - " * \n", - " * Neither the name of Anaconda nor the names of any contributors\n", - " * may be used to endorse or promote products derived from this software\n", - " * without specific prior written permission.\n", - " * \n", - " * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\n", - " * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n", - " * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE\n", - " * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE\n", - " * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR\n", - " * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF\n", - " * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS\n", - " * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN\n", - " * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)\n", - " * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF\n", - " * THE POSSIBILITY OF SUCH DAMAGE.\n", - " */\n", - " (function(root, factory) {\n", - " factory(root[\"Bokeh\"], \"2.4.2\");\n", - " })(this, function(Bokeh, version) {\n", - " let define;\n", - " return (function(modules, entry, aliases, externals) {\n", - " const bokeh = typeof Bokeh !== \"undefined\" && (version != null ? Bokeh[version] : Bokeh);\n", - " if (bokeh != null) {\n", - " return bokeh.register_plugin(modules, entry, aliases);\n", - " } else {\n", - " throw new Error(\"Cannot find Bokeh \" + version + \". You have to load it prior to loading plugins.\");\n", - " }\n", - " })\n", - " ({\n", - " 484: function _(t,e,o,r,s){r();const _=(0,t(1).__importStar)(t(485));o.Tables=_;(0,t(7).register_models)(_)},\n", - " 485: function _(g,a,r,e,t){e();const o=g(1);(0,o.__exportStar)(g(486),r),(0,o.__exportStar)(g(489),r),t(\"DataTable\",g(492).DataTable),t(\"TableColumn\",g(510).TableColumn),t(\"TableWidget\",g(509).TableWidget);var n=g(512);t(\"AvgAggregator\",n.AvgAggregator),t(\"MinAggregator\",n.MinAggregator),t(\"MaxAggregator\",n.MaxAggregator),t(\"SumAggregator\",n.SumAggregator);var A=g(513);t(\"GroupingInfo\",A.GroupingInfo),t(\"DataCube\",A.DataCube)},\n", - " 486: function _(e,t,i,s,a){s();const r=e(1);var l,n,u,d,o,p,_,c,h;const E=e(43),V=e(226),m=e(53),f=e(487),v=(0,r.__importStar)(e(488));class w extends V.DOMView{constructor(e){const{model:t,parent:i}=e.column;super(Object.assign({model:t,parent:i},e)),this.args=e,this.initialize(),this.render()}get emptyValue(){return null}initialize(){super.initialize(),this.inputEl=this._createInput(),this.defaultValue=null}async lazy_initialize(){throw new Error(\"unsupported\")}css_classes(){return super.css_classes().concat(v.cell_editor)}render(){super.render(),this.args.container.append(this.el),this.el.appendChild(this.inputEl),this.renderEditor(),this.disableNavigation()}renderEditor(){}disableNavigation(){this.inputEl.addEventListener(\"keydown\",(e=>{switch(e.keyCode){case E.Keys.Left:case E.Keys.Right:case E.Keys.Up:case E.Keys.Down:case E.Keys.PageUp:case E.Keys.PageDown:e.stopImmediatePropagation()}}))}destroy(){this.remove()}focus(){this.inputEl.focus()}show(){}hide(){}position(){}getValue(){return this.inputEl.value}setValue(e){this.inputEl.value=e}serializeValue(){return this.getValue()}isValueChanged(){return!(\"\"==this.getValue()&&null==this.defaultValue)&&this.getValue()!==this.defaultValue}applyValue(e,t){const i=this.args.grid.getData(),s=i.index.indexOf(e[f.DTINDEX_NAME]);i.setField(s,this.args.column.field,t)}loadValue(e){const t=e[this.args.column.field];this.defaultValue=null!=t?t:this.emptyValue,this.setValue(this.defaultValue)}validateValue(e){if(this.args.column.validator){const t=this.args.column.validator(e);if(!t.valid)return t}return{valid:!0,msg:null}}validate(){return this.validateValue(this.getValue())}}i.CellEditorView=w,w.__name__=\"CellEditorView\";class g extends m.Model{}i.CellEditor=g,g.__name__=\"CellEditor\";class x extends w{get emptyValue(){return\"\"}_createInput(){return(0,E.input)({type:\"text\"})}renderEditor(){this.inputEl.focus(),this.inputEl.select()}loadValue(e){super.loadValue(e),this.inputEl.defaultValue=this.defaultValue,this.inputEl.select()}}i.StringEditorView=x,x.__name__=\"StringEditorView\";class y extends g{}i.StringEditor=y,l=y,y.__name__=\"StringEditor\",l.prototype.default_view=x,l.define((({String:e,Array:t})=>({completions:[t(e),[]]})));class I extends w{_createInput(){return(0,E.textarea)()}renderEditor(){this.inputEl.focus(),this.inputEl.select()}}i.TextEditorView=I,I.__name__=\"TextEditorView\";class b extends g{}i.TextEditor=b,n=b,b.__name__=\"TextEditor\",n.prototype.default_view=I;class N extends w{_createInput(){return(0,E.select)()}renderEditor(){for(const e of this.model.options)this.inputEl.appendChild((0,E.option)({value:e},e));this.focus()}}i.SelectEditorView=N,N.__name__=\"SelectEditorView\";class C extends g{}i.SelectEditor=C,u=C,C.__name__=\"SelectEditor\",u.prototype.default_view=N,u.define((({String:e,Array:t})=>({options:[t(e),[]]})));class D extends w{_createInput(){return(0,E.input)({type:\"text\"})}}i.PercentEditorView=D,D.__name__=\"PercentEditorView\";class S extends g{}i.PercentEditor=S,d=S,S.__name__=\"PercentEditor\",d.prototype.default_view=D;class k extends w{_createInput(){return(0,E.input)({type:\"checkbox\"})}renderEditor(){this.focus()}loadValue(e){this.defaultValue=!!e[this.args.column.field],this.inputEl.checked=this.defaultValue}serializeValue(){return this.inputEl.checked}}i.CheckboxEditorView=k,k.__name__=\"CheckboxEditorView\";class z extends g{}i.CheckboxEditor=z,o=z,z.__name__=\"CheckboxEditor\",o.prototype.default_view=k;class P extends w{_createInput(){return(0,E.input)({type:\"text\"})}renderEditor(){this.inputEl.focus(),this.inputEl.select()}remove(){super.remove()}serializeValue(){var e;return null!==(e=parseInt(this.getValue(),10))&&void 0!==e?e:0}loadValue(e){super.loadValue(e),this.inputEl.defaultValue=this.defaultValue,this.inputEl.select()}validateValue(e){return isNaN(e)?{valid:!1,msg:\"Please enter a valid integer\"}:super.validateValue(e)}}i.IntEditorView=P,P.__name__=\"IntEditorView\";class T extends g{}i.IntEditor=T,p=T,T.__name__=\"IntEditor\",p.prototype.default_view=P,p.define((({Int:e})=>({step:[e,1]})));class K extends w{_createInput(){return(0,E.input)({type:\"text\"})}renderEditor(){this.inputEl.focus(),this.inputEl.select()}remove(){super.remove()}serializeValue(){var e;return null!==(e=parseFloat(this.getValue()))&&void 0!==e?e:0}loadValue(e){super.loadValue(e),this.inputEl.defaultValue=this.defaultValue,this.inputEl.select()}validateValue(e){return isNaN(e)?{valid:!1,msg:\"Please enter a valid number\"}:super.validateValue(e)}}i.NumberEditorView=K,K.__name__=\"NumberEditorView\";class A extends g{}i.NumberEditor=A,_=A,A.__name__=\"NumberEditor\",_.prototype.default_view=K,_.define((({Number:e})=>({step:[e,.01]})));class M extends w{_createInput(){return(0,E.input)({type:\"text\"})}}i.TimeEditorView=M,M.__name__=\"TimeEditorView\";class O extends g{}i.TimeEditor=O,c=O,O.__name__=\"TimeEditor\",c.prototype.default_view=M;class F extends w{_createInput(){return(0,E.input)({type:\"text\"})}get emptyValue(){return new Date}renderEditor(){this.inputEl.focus(),this.inputEl.select()}destroy(){super.destroy()}show(){super.show()}hide(){super.hide()}position(){return super.position()}getValue(){}setValue(e){}}i.DateEditorView=F,F.__name__=\"DateEditorView\";class L extends g{}i.DateEditor=L,h=L,L.__name__=\"DateEditor\",h.prototype.default_view=F},\n", - " 487: function _(_,n,i,t,d){t(),i.DTINDEX_NAME=\"__bkdt_internal_index__\"},\n", - " 488: function _(e,l,o,t,r){t(),o.root=\"bk-root\",o.data_table=\"bk-data-table\",o.cell_special_defaults=\"bk-cell-special-defaults\",o.cell_select=\"bk-cell-select\",o.cell_index=\"bk-cell-index\",o.header_index=\"bk-header-index\",o.cell_editor=\"bk-cell-editor\",o.cell_editor_completion=\"bk-cell-editor-completion\",o.default='.bk-root .bk-data-table{box-sizing:content-box;font-size:11px;}.bk-root .bk-data-table input[type=\"checkbox\"]{margin-left:4px;margin-right:4px;}.bk-root .bk-cell-special-defaults{border-right-color:silver;border-right-style:solid;background:#f5f5f5;}.bk-root .bk-cell-select{border-right-color:silver;border-right-style:solid;background:#f5f5f5;}.bk-root .slick-cell.bk-cell-index{border-right-color:silver;border-right-style:solid;background:#f5f5f5;text-align:right;background:#f0f0f0;color:#909090;}.bk-root .bk-header-index .slick-column-name{float:right;}.bk-root .slick-row.selected .bk-cell-index{background-color:transparent;}.bk-root .slick-row.odd{background:#f0f0f0;}.bk-root .slick-cell{padding-left:4px;padding-right:4px;border-right-color:transparent;border:0.25px solid transparent;}.bk-root .slick-cell .bk{line-height:inherit;}.bk-root .slick-cell.active{border-style:dashed;}.bk-root .slick-cell.selected{background-color:#F0F8FF;}.bk-root .slick-cell.editable{padding-left:0;padding-right:0;}.bk-root .bk-cell-editor{display:contents;}.bk-root .bk-cell-editor input,.bk-root .bk-cell-editor select{width:100%;height:100%;border:0;margin:0;padding:0;outline:0;background:transparent;vertical-align:baseline;}.bk-root .bk-cell-editor input{padding-left:4px;padding-right:4px;}.bk-root .bk-cell-editor-completion{font-size:11px;}'},\n", - " 489: function _(t,e,r,n,a){n();const o=t(1);var l,s,i,c,u,m;const _=(0,o.__importDefault)(t(151)),d=(0,o.__importStar)(t(153)),f=t(490),g=t(43),h=t(20),F=t(8),p=t(34),b=t(22),S=t(53);class x extends S.Model{constructor(t){super(t)}doFormat(t,e,r,n,a){return null==r?\"\":`${r}`.replace(/&/g,\"&\").replace(//g,\">\")}}r.CellFormatter=x,x.__name__=\"CellFormatter\";class M extends x{constructor(t){super(t)}doFormat(t,e,r,n,a){const{font_style:o,text_align:l,text_color:s}=this,i=(0,g.div)(null==r?\"\":`${r}`);switch(o){case\"bold\":i.style.fontWeight=\"bold\";break;case\"italic\":i.style.fontStyle=\"italic\"}return 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HSP2 BUILD and RUN SIMULATION

Place this Jupyter Notebook in a directory with one UCI and one or more WDM files.

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Required Python Imports

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In [1]:
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import HSP2
-import HSP2tools
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-from glob import glob
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HSP2tools.versions()
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Version
HSP20.7.2
HSP2tools0.7.1
PYTHON2.7.11 | 64-bit | (default, Jun 11 2016, 11:33...
IPYTHON5.3.0
H5PY2.7.0
MATPLOTLIB2.0.0
NETWORKX1.11
NUMBA0.31.0
NUMPY1.11.3
PANDAS0.19.2
PYTABLES3.3.0
WDMTOOLBOX0.8.2 MOD RTH
osWindows-10-10.0.15063
processorIntel64 Family 6 Model 94 Stepping 3, GenuineI...
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BUILD HDF5 FILE From UCI and WDM files

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Get the name of the UCI file.

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uciname = glob('*.uci')[0]
-uciname
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Out[3]:
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'calleg.uci'
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Create HDF5 filename from the leading part of the UCI filename.

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HDFname = uciname.split('.')[0] + '.h5'
-HDFname
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'calleg.h5'
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In [5]:
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!del {HDFname}
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Create the HDF5 file filled with the UCI data

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HSP2tools.readUCI(uciname, HDFname)
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C:\Users\rober\Desktop\dev\HSP2tools\uciReader.py:445: FutureWarning: convert_objects is deprecated.  Use the data-type specific converters pd.to_datetime, pd.to_timedelta and pd.to_numeric.
-  df = df.convert_objects(convert_numeric=True)
-C:\Users\rober\Desktop\dev\HSP2tools\uciReader.py:442: FutureWarning: convert_objects is deprecated.  Use the data-type specific converters pd.to_datetime, pd.to_timedelta and pd.to_numeric.
-  dff = dff.convert_objects(convert_numeric=True)
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uciReader is Done
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HSP2tools.cleanup(HDFname)
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Cleanup done
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Add the timeseries data to the HDF5 file.

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wdmnames = glob('*.wdm')
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['calleg.wdm']
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In [9]:
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for name in wdmnames:
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Processing WDM file calleg.wdm
-/TIMESERIES/TS1169 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 EVAP
-/TIMESERIES/TS187 H 1987-09-30T00:00:00 2002-10-01T00:00:00 131520 PREC
-/TIMESERIES/TS1171 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 EVAP
-/TIMESERIES/TS234 H 1987-09-30T00:00:00 2002-10-01T00:00:00 131520 PREC
-/TIMESERIES/TS249 H 1987-09-30T00:00:00 2002-10-01T00:00:00 131520 PREC
-/TIMESERIES/TS193 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 PREC
-/TIMESERIES/TS196 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 PREC
-/TIMESERIES/TS154 H 1987-09-30T00:00:00 2002-10-01T00:00:00 131520 PREC
-/TIMESERIES/TS227 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 PREC
-/TIMESERIES/TS250 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 PREC
-/TIMESERIES/TS141 H 1987-09-30T00:00:00 2002-10-01T00:00:00 131520 PREC
-/TIMESERIES/TS49 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 PREC
-/TIMESERIES/TS169 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 PREC
-/TIMESERIES/TS188 H 1987-09-30T00:00:00 2002-10-01T00:00:00 131520 PREC
-/TIMESERIES/TS1239 H 1987-10-01T00:00:00 2003-12-01T00:00:00 141720 EVAP
-/TIMESERIES/TS194 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 PREC
-/TIMESERIES/TS190 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 PREC
-/TIMESERIES/TS175 H 1987-09-30T00:00:00 2002-10-01T00:00:00 131520 PREC
-/TIMESERIES/TS259 H 1987-09-30T00:00:00 2002-10-01T00:00:00 131520 PREC
-/TIMESERIES/TS177 H 1987-09-30T00:00:00 2002-10-01T00:00:00 131520 PREC
-/TIMESERIES/TS6001 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 IRRIG
-/TIMESERIES/TS242 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 PREC
-/TIMESERIES/TS402 M 1987-10-01T00:00:00 2003-11-01T00:00:00 193 PUMPOUT
-/TIMESERIES/TS401 M 1987-10-01T00:00:00 2003-11-01T00:00:00 193 PUMPOUT
-/TIMESERIES/TS6250 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 IRRIG
-/TIMESERIES/TS6141 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 IRRIG
-/TIMESERIES/TS6049 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 IRRIG
-/TIMESERIES/TS6194 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 IRRIG
-/TIMESERIES/TS238 H 1987-09-30T00:00:00 2002-10-01T00:00:00 131520 PREC
-/TIMESERIES/TS6238 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 IRRIG
-/TIMESERIES/TS6190 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 IRRIG
-/TIMESERIES/TS6175 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 IRRIG
-/TIMESERIES/TS6259 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 IRRIG
-/TIMESERIES/TS6177 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 IRRIG
-/TIMESERIES/TS2239 H 1987-10-01T00:00:00 2002-10-01T00:00:00 131496 EVAP
-/TIMESERIES/TS403 M 1987-10-01T00:00:00 2003-11-01T00:00:00 193 PUMPIN
-/TIMESERIES/TS404 M 1987-10-01T00:00:00 2003-11-01T00:00:00 193 PUMPIN
-/TIMESERIES/TS406 M 1987-10-01T00:00:00 2003-11-01T00:00:00 193 PUMPIN
-/TIMESERIES/TS407 M 1987-10-01T00:00:00 2003-11-01T00:00:00 193 PUMPIN
-/TIMESERIES/TS405 M 1987-10-01T00:00:00 2003-11-01T00:00:00 193 PUMPIN
-/TIMESERIES/TS325 D 1987-01-01T00:00:00 2003-09-07T00:00:00 6093 FLOW
-/TIMESERIES/TS335 M 1987-01-01T00:00:00 2002-12-01T00:00:00 191 FLOW
-/TIMESERIES/TS307 M 1980-01-01T00:00:00 2003-01-01T00:00:00 276 FLOW
-/TIMESERIES/TS304 D 1987-01-01T00:00:00 2003-09-07T00:00:00 6093 FLOW
-/TIMESERIES/TS301 D 1987-01-01T00:00:00 2002-12-01T00:00:00 5813 FLOW
-/TIMESERIES/TS1311 D 1969-10-01T00:00:00 2002-10-01T00:00:00 12053 FLOW
-/TIMESERIES/TS311 D 1969-10-01T00:00:00 2003-10-01T00:00:00 12418 FLOW
-/TIMESERIES/TS303 D 1985-09-01T00:00:00 2003-10-01T00:00:00 6604 FLOW
-/TIMESERIES/TS302 D 1987-10-01T00:00:00 2003-10-01T00:00:00 5844 FLOW
-/TIMESERIES/TS305 D 1987-01-01T00:00:00 2002-10-23T00:00:00 5774 FLOW
-Done with calleg.wdm
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In [10]:
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!rename {HDFname} temp.h5
-!ptrepack temp.h5 {HDFname}
-!del temp.h5
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RUN simulation

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Get HDF5 filename (in case you didn't need to run the above)

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hdfname =  glob('*.h5')[0]
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HSP2.run(hdfname,saveall=True)
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2017-04-21 22:24:06.80   Run Started for file calleg.h5
-2017-04-21 22:24:06.85     Start 1993-10-01 00:00    Stop 2002-09-30 23:59
-2017-04-21 22:24:07.20   Finished setup
-2017-04-21 22:24:07.20      PERLND P011   DELT=60
-2017-04-21 22:24:14.16      PERLND P012   DELT=60
-2017-04-21 22:24:14.28      PERLND P013   DELT=60
-2017-04-21 22:24:14.41      PERLND P014   DELT=60
-2017-04-21 22:24:14.53      PERLND P015   DELT=60
-2017-04-21 22:24:14.66      IMPLND I011   DELT=60
-2017-04-21 22:24:15.74      PERLND P021   DELT=60
-2017-04-21 22:24:15.86      PERLND P022   DELT=60
-2017-04-21 22:24:16.00      PERLND P023   DELT=60
-2017-04-21 22:24:16.11      PERLND P024   DELT=60
-2017-04-21 22:24:16.25      PERLND P025   DELT=60
-2017-04-21 22:24:16.38      IMPLND I021   DELT=60
-2017-04-21 22:24:16.43      RCHRES R001   DELT=60
-2017-04-21 22:24:22.66      PERLND P031   DELT=60
-2017-04-21 22:24:22.80      PERLND P041   DELT=60
-2017-04-21 22:24:22.93      PERLND P042   DELT=60
-2017-04-21 22:24:23.05      PERLND P043   DELT=60
-2017-04-21 22:24:23.18      IMPLND I041   DELT=60
-2017-04-21 22:24:23.22      RCHRES R021   DELT=60
-2017-04-21 22:24:23.32      RCHRES R022   DELT=60
-2017-04-21 22:24:23.41      RCHRES R023   DELT=60
-2017-04-21 22:24:23.51      PERLND P051   DELT=60
-2017-04-21 22:24:23.63      PERLND P052   DELT=60
-2017-04-21 22:24:23.76      PERLND P053   DELT=60
-2017-04-21 22:24:23.88      PERLND P054   DELT=60
-2017-04-21 22:24:24.01      PERLND P055   DELT=60
-2017-04-21 22:24:24.13      IMPLND I051   DELT=60
-2017-04-21 22:24:24.18      RCHRES R011   DELT=60
-2017-04-21 22:24:24.47      RCHRES R024   DELT=60
-2017-04-21 22:24:24.58      PERLND P061   DELT=60
-2017-04-21 22:24:24.72      PERLND P062   DELT=60
-2017-04-21 22:24:24.85      IMPLND I061   DELT=60
-2017-04-21 22:24:24.90      PERLND P071   DELT=60
-2017-04-21 22:24:25.04      PERLND P072   DELT=60
-2017-04-21 22:24:25.15      PERLND P073   DELT=60
-2017-04-21 22:24:25.29      PERLND P074   DELT=60
-2017-04-21 22:24:25.41      PERLND P075   DELT=60
-2017-04-21 22:24:25.54      IMPLND I071   DELT=60
-2017-04-21 22:24:25.58      RCHRES R031   DELT=60
-2017-04-21 22:24:25.77      RCHRES R071   DELT=60
-2017-04-21 22:24:25.88      PERLND P081   DELT=60
-2017-04-21 22:24:26.02      PERLND P082   DELT=60
-2017-04-21 22:24:26.15      PERLND P083   DELT=60
-2017-04-21 22:24:26.27      PERLND P084   DELT=60
-2017-04-21 22:24:26.40      PERLND P085   DELT=60
-2017-04-21 22:24:26.52      IMPLND I081   DELT=60
-2017-04-21 22:24:26.57      PERLND P091   DELT=60
-2017-04-21 22:24:26.69      RCHRES R043   DELT=60
-2017-04-21 22:24:26.79      PERLND P101   DELT=60
-2017-04-21 22:24:26.93         Message count 30   Message PWATER: Reduced AGWO value to available
-2017-04-21 22:24:26.93         Message count 20285   Message PWATER: Reset AGWS to zero
-2017-04-21 22:24:26.93      PERLND P102   DELT=60
-2017-04-21 22:24:27.05      IMPLND I101   DELT=60
-2017-04-21 22:24:27.10      RCHRES R041   DELT=60
-2017-04-21 22:24:27.19      RCHRES R042   DELT=60
-2017-04-21 22:24:27.32      RCHRES R044   DELT=60
-2017-04-21 22:24:27.43      PERLND P111   DELT=60
-2017-04-21 22:24:27.55      PERLND P112   DELT=60
-2017-04-21 22:24:27.68      PERLND P113   DELT=60
-2017-04-21 22:24:27.82      IMPLND I111   DELT=60
-2017-04-21 22:24:27.86      RCHRES R045   DELT=60
-2017-04-21 22:24:27.99      PERLND P121   DELT=60
-2017-04-21 22:24:28.13      PERLND P122   DELT=60
-2017-04-21 22:24:28.26      PERLND P123   DELT=60
-2017-04-21 22:24:28.38      PERLND P124   DELT=60
-2017-04-21 22:24:28.51      PERLND P125   DELT=60
-2017-04-21 22:24:28.63      IMPLND I121   DELT=60
-2017-04-21 22:24:28.68      RCHRES R002   DELT=60
-2017-04-21 22:24:31.19      RCHRES R025   DELT=60
-2017-04-21 22:24:31.48      RCHRES R003   DELT=60
-2017-04-21 22:24:31.84      RCHRES R004   DELT=60
-2017-04-21 22:24:32.11      RCHRES R904   DELT=60
-2017-04-21 22:24:32.20      PERLND P131   DELT=60
-2017-04-21 22:24:32.33      PERLND P132   DELT=60
-2017-04-21 22:24:32.45      PERLND P133   DELT=60
-2017-04-21 22:24:32.58      PERLND P134   DELT=60
-2017-04-21 22:24:32.70      PERLND P135   DELT=60
-2017-04-21 22:24:32.83      IMPLND I131   DELT=60
-2017-04-21 22:24:32.87      RCHRES R061   DELT=60
-2017-04-21 22:24:32.97      RCHRES R062   DELT=60
-2017-04-21 22:24:33.10      RCHRES R063   DELT=60
-2017-04-21 22:24:33.22      RCHRES R064   DELT=60
-2017-04-21 22:24:33.36      RCHRES R964   DELT=60
-2017-04-21 22:24:33.49      RCHRES R091   DELT=60
-2017-04-21 22:24:33.65      PERLND P141   DELT=60
-2017-04-21 22:24:33.79      PERLND P142   DELT=60
-2017-04-21 22:24:33.91      PERLND P143   DELT=60
-2017-04-21 22:24:34.04      PERLND P144   DELT=60
-2017-04-21 22:24:34.17      PERLND P145   DELT=60
-2017-04-21 22:24:34.29      IMPLND I141   DELT=60
-2017-04-21 22:24:34.34      RCHRES R005   DELT=60
-2017-04-21 22:24:35.34      RCHRES R046   DELT=60
-2017-04-21 22:24:35.54      RCHRES R065   DELT=60
-2017-04-21 22:24:35.78      RCHRES R072   DELT=60
-2017-04-21 22:24:35.97      PERLND P151   DELT=60
-2017-04-21 22:24:36.11      PERLND P152   DELT=60
-2017-04-21 22:24:36.23      IMPLND I151   DELT=60
-2017-04-21 22:24:36.28      RCHRES R051   DELT=60
-2017-04-21 22:24:36.39      RCHRES R952   DELT=60
-2017-04-21 22:24:36.50      RCHRES R052   DELT=60
-2017-04-21 22:24:36.69      RCHRES R006   DELT=60
-2017-04-21 22:24:36.84      RCHRES R081   DELT=60
-2017-04-21 22:24:36.97      PERLND P161   DELT=60
-2017-04-21 22:24:37.09      PERLND P162   DELT=60
-2017-04-21 22:24:37.22      PERLND P163   DELT=60
-2017-04-21 22:24:37.34      PERLND P164   DELT=60
-2017-04-21 22:24:37.48      PERLND P165   DELT=60
-2017-04-21 22:24:37.59      IMPLND I161   DELT=60
-2017-04-21 22:24:37.64      RCHRES R101   DELT=60
-2017-04-21 22:24:37.78      RCHRES R102   DELT=60
-2017-04-21 22:24:37.87      RCHRES R103   DELT=60
-2017-04-21 22:24:37.98      RCHRES R104   DELT=60
-2017-04-21 22:24:38.08      RCHRES R105   DELT=60
-2017-04-21 22:24:38.17      PERLND P171   DELT=60
-2017-04-21 22:24:38.29      PERLND P172   DELT=60
-2017-04-21 22:24:38.42      PERLND P173   DELT=60
-2017-04-21 22:24:38.54      PERLND P174   DELT=60
-2017-04-21 22:24:38.67      PERLND P175   DELT=60
-2017-04-21 22:24:38.79      IMPLND I171   DELT=60
-2017-04-21 22:24:38.84      PERLND P181   DELT=60
-2017-04-21 22:24:38.97      PERLND P182   DELT=60
-2017-04-21 22:24:39.08      PERLND P183   DELT=60
-2017-04-21 22:24:39.20      PERLND P184   DELT=60
-2017-04-21 22:24:39.33      PERLND P185   DELT=60
-2017-04-21 22:24:39.47         Message count 1533   Message PWATER: Reduced AGWO value to available
-2017-04-21 22:24:39.47         Message count 71712   Message PWATER: Reset AGWS to zero
-2017-04-21 22:24:39.47      IMPLND I181   DELT=60
-2017-04-21 22:24:39.51      RCHRES R107   DELT=60
-2017-04-21 22:24:39.73      RCHRES R106   DELT=60
-2017-04-21 22:24:39.89      RCHRES R108   DELT=60
-2017-04-21 22:24:40.00      RCHRES R007   DELT=60
-2017-04-21 22:24:40.16      RCHRES R082   DELT=60
-2017-04-21 22:24:40.42      RCHRES R092   DELT=60
-2017-04-21 22:24:40.66      RCHRES R008   DELT=60
-2017-04-21 22:24:40.83      RCHRES R009   DELT=60
-2017-04-21 22:24:40.95      RCHRES R109   DELT=60
-2017-04-21 22:24:41.17      RCHRES R010   DELT=60
-2017-04-21 22:24:41.39      PERLND P191   DELT=60
-2017-04-21 22:24:41.53      PERLND P192   DELT=60
-2017-04-21 22:24:41.66      PERLND P193   DELT=60
-2017-04-21 22:24:41.77      PERLND P194   DELT=60
-2017-04-21 22:24:41.89      PERLND P195   DELT=60
-2017-04-21 22:24:42.02      IMPLND I191   DELT=60
-2017-04-21 22:24:42.06      PERLND P201   DELT=60
-2017-04-21 22:24:42.20      PERLND P202   DELT=60
-2017-04-21 22:24:42.31      PERLND P203   DELT=60
-2017-04-21 22:24:42.43      PERLND P204   DELT=60
-2017-04-21 22:24:42.56      PERLND P205   DELT=60
-2017-04-21 22:24:42.68      PERLND P206   DELT=60
-2017-04-21 22:24:42.81      IMPLND I201   DELT=60
-2017-04-21 22:24:42.85      PERLND P211   DELT=60
-2017-04-21 22:24:43.00      PERLND P212   DELT=60
-2017-04-21 22:24:43.11      PERLND P213   DELT=60
-2017-04-21 22:24:43.23      PERLND P214   DELT=60
-2017-04-21 22:24:43.34      PERLND P215   DELT=60
-2017-04-21 22:24:43.47      PERLND P216   DELT=60
-2017-04-21 22:24:43.59      IMPLND I211   DELT=60
-2017-04-21 22:24:43.64      PERLND P221   DELT=60
-2017-04-21 22:24:43.76      PERLND P222   DELT=60
-2017-04-21 22:24:43.87      PERLND P224   DELT=60
-2017-04-21 22:24:44.00      PERLND P225   DELT=60
-2017-04-21 22:24:44.11      PERLND P226   DELT=60
-2017-04-21 22:24:44.25      IMPLND I221   DELT=60
-2017-04-21 22:24:44.28      PERLND P231   DELT=60
-2017-04-21 22:24:44.41      PERLND P232   DELT=60
-2017-04-21 22:24:44.53      PERLND P234   DELT=60
-2017-04-21 22:24:44.66      PERLND P235   DELT=60
-2017-04-21 22:24:44.78      IMPLND I231   DELT=60
-2017-04-21 22:24:44.81      PERLND P241   DELT=60
-2017-04-21 22:24:44.95      PERLND P242   DELT=60
-2017-04-21 22:24:45.06      PERLND P243   DELT=60
-2017-04-21 22:24:45.19      PERLND P244   DELT=60
-2017-04-21 22:24:45.30      PERLND P245   DELT=60
-2017-04-21 22:24:45.41      IMPLND I241   DELT=60
-2017-04-21 22:24:45.45      PERLND P251   DELT=60
-2017-04-21 22:24:45.58      PERLND P252   DELT=60
-2017-04-21 22:24:45.70      PERLND P253   DELT=60
-2017-04-21 22:24:45.83      PERLND P254   DELT=60
-2017-04-21 22:24:45.94      PERLND P255   DELT=60
-2017-04-21 22:24:46.05      PERLND P256   DELT=60
-2017-04-21 22:24:46.18      IMPLND I251   DELT=60
-2017-04-21 22:24:46.23      PERLND P261   DELT=60
-2017-04-21 22:24:46.35      PERLND P266   DELT=60
-2017-04-21 22:24:46.48      PERLND P271   DELT=60
-2017-04-21 22:24:46.60      PERLND P272   DELT=60
-2017-04-21 22:24:46.73      PERLND P275   DELT=60
-2017-04-21 22:24:46.84      PERLND P276   DELT=60
-2017-04-21 22:24:46.96      IMPLND I271   DELT=60
-2017-04-21 22:24:47.01      PERLND P281   DELT=60
-2017-04-21 22:24:47.15      PERLND P282   DELT=60
-2017-04-21 22:24:47.26      PERLND P283   DELT=60
-2017-04-21 22:24:47.38      PERLND P285   DELT=60
-2017-04-21 22:24:47.49      PERLND P286   DELT=60
-2017-04-21 22:24:47.63      IMPLND I281   DELT=60
-2017-04-21 22:24:47.68      PERLND P291   DELT=60
-2017-04-21 22:24:47.81      PERLND P292   DELT=60
-2017-04-21 22:24:47.93      PERLND P293   DELT=60
-2017-04-21 22:24:48.06      PERLND P294   DELT=60
-2017-04-21 22:24:48.18      PERLND P295   DELT=60
-2017-04-21 22:24:48.29      PERLND P296   DELT=60
-2017-04-21 22:24:48.43      IMPLND I291   DELT=60
-2017-04-21 22:24:48.46      PERLND P301   DELT=60
-2017-04-21 22:24:48.59      PERLND P302   DELT=60
-2017-04-21 22:24:48.71      PERLND P303   DELT=60
-2017-04-21 22:24:48.82      PERLND P304   DELT=60
-2017-04-21 22:24:48.93      PERLND P305   DELT=60
-2017-04-21 22:24:49.06      PERLND P306   DELT=60
-2017-04-21 22:24:49.19      IMPLND I301   DELT=60
-2017-04-21 22:24:49.24      RCHRES R201   DELT=60
-2017-04-21 22:24:49.38      RCHRES R190   DELT=60
-2017-04-21 22:24:49.50      RCHRES R202   DELT=60
-2017-04-21 22:24:49.63      RCHRES R191   DELT=60
-2017-04-21 22:24:49.79      RCHRES R203   DELT=60
-2017-04-21 22:24:49.94      RCHRES R211   DELT=60
-2017-04-21 22:24:50.05      RCHRES R212   DELT=60
-2017-04-21 22:24:50.19      RCHRES R192   DELT=60
-2017-04-21 22:24:50.33      RCHRES R204   DELT=60
-2017-04-21 22:24:50.50      RCHRES R221   DELT=60
-2017-04-21 22:24:50.66      RCHRES R222   DELT=60
-2017-04-21 22:24:50.74      RCHRES R223   DELT=60
-2017-04-21 22:24:50.91      RCHRES R193   DELT=60
-2017-04-21 22:24:51.02      RCHRES R205   DELT=60
-2017-04-21 22:24:51.17      RCHRES R225   DELT=60
-2017-04-21 22:24:51.33      RCHRES R194   DELT=60
-2017-04-21 22:24:51.42      RCHRES R206   DELT=60
-2017-04-21 22:24:51.57      RCHRES R227   DELT=60
-2017-04-21 22:24:51.74      RCHRES R207   DELT=60
-2017-04-21 22:24:51.86      RCHRES R231   DELT=60
-2017-04-21 22:24:52.00      RCHRES R232   DELT=60
-2017-04-21 22:24:52.10      RCHRES R233   DELT=60
-2017-04-21 22:24:52.24      RCHRES R241   DELT=60
-2017-04-21 22:24:52.38      RCHRES R242   DELT=60
-2017-04-21 22:24:52.47      RCHRES R243   DELT=60
-2017-04-21 22:24:52.60      RCHRES R301   DELT=60
-2017-04-21 22:24:52.75      RCHRES R311   DELT=60
-2017-04-21 22:24:52.85      RCHRES R302   DELT=60
-2017-04-21 22:24:53.00      RCHRES R303   DELT=60
-2017-04-21 22:24:53.16      RCHRES R401   DELT=60
-2017-04-21 22:24:53.30      RCHRES R411   DELT=60
-2017-04-21 22:24:53.42      RCHRES R402   DELT=60
-2017-04-21 22:24:53.57      RCHRES R421   DELT=60
-2017-04-21 22:24:53.69      RCHRES R422   DELT=60
-2017-04-21 22:24:53.80      RCHRES R423   DELT=60
-2017-04-21 22:24:53.92      RCHRES R403   DELT=60
-2017-04-21 22:24:54.07      RCHRES R431   DELT=60
-2017-04-21 22:24:54.21      RCHRES R404   DELT=60
-2017-04-21 22:24:54.34      RCHRES R441   DELT=60
-2017-04-21 22:24:54.48      RCHRES R443   DELT=60
-2017-04-21 22:24:54.59      RCHRES R442   DELT=60
-2017-04-21 22:24:54.75      RCHRES R405   DELT=60
-2017-04-21 22:24:54.90      RCHRES R406   DELT=60
-2017-04-21 22:24:55.06      RCHRES R407   DELT=60
-2017-04-21 22:24:55.21      RCHRES R408   DELT=60
-2017-04-21 22:24:55.37      RCHRES R195   DELT=60
-2017-04-21 22:24:55.46      RCHRES R304   DELT=60
-2017-04-21 22:24:55.64      RCHRES R305   DELT=60
-2017-04-21 22:24:55.81      RCHRES R306   DELT=60
-2017-04-21 22:24:55.93      RCHRES R500   DELT=60
-2017-04-21 22:24:56.04      RCHRES R501   DELT=60
-2017-04-21 22:24:56.21      RCHRES R513   DELT=60
-2017-04-21 22:24:56.36      RCHRES R514   DELT=60
-2017-04-21 22:24:56.45      RCHRES R502   DELT=60
-2017-04-21 22:24:56.72      RCHRES R510   DELT=60
-2017-04-21 22:24:56.86      RCHRES R511   DELT=60
-2017-04-21 22:24:57.06      RCHRES R512   DELT=60
-2017-04-21 22:24:57.23      RCHRES R503   DELT=60
-2017-04-21 22:24:57.50      RCHRES R523   DELT=60
-2017-04-21 22:24:57.62      RCHRES R524   DELT=60
-2017-04-21 22:24:57.72      RCHRES R525   DELT=60
-2017-04-21 22:24:57.82      RCHRES R526   DELT=60
-2017-04-21 22:24:57.93      RCHRES R521   DELT=60
-2017-04-21 22:24:58.12      RCHRES R522   DELT=60
-2017-04-21 22:24:58.29      RCHRES R531   DELT=60
-2017-04-21 22:24:58.43      RCHRES R504   DELT=60
-2017-04-21 22:24:58.55      RCHRES R505   DELT=60
-2017-04-21 22:24:58.69      RCHRES R506   DELT=60
-2017-04-21 22:24:58.83      RCHRES R541   DELT=60
-2017-04-21 22:24:58.96      RCHRES R542   DELT=60
-2017-04-21 22:24:59.10      RCHRES R307   DELT=60
-2017-04-21 22:24:59.24   Run completed
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In [ ]:
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In [5]:
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%timeit HSP2.run(hdfname, saveall=True)
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2017-04-21 22:28:09.93   Run Started for file calleg.h5
-2017-04-21 22:28:09.95     Start 1993-10-01 00:00    Stop 2002-09-30 23:59
-2017-04-21 22:28:10.31   Finished setup
-2017-04-21 22:28:10.31      PERLND P011   DELT=60
-2017-04-21 22:28:10.46      PERLND P012   DELT=60
-2017-04-21 22:28:10.58      PERLND P013   DELT=60
-2017-04-21 22:28:10.71      PERLND P014   DELT=60
-2017-04-21 22:28:10.83      PERLND P015   DELT=60
-2017-04-21 22:28:10.94      IMPLND I011   DELT=60
-2017-04-21 22:28:11.00      PERLND P021   DELT=60
-2017-04-21 22:28:11.11      PERLND P022   DELT=60
-2017-04-21 22:28:11.22      PERLND P023   DELT=60
-2017-04-21 22:28:11.35      PERLND P024   DELT=60
-2017-04-21 22:28:11.46      PERLND P025   DELT=60
-2017-04-21 22:28:11.57      IMPLND I021   DELT=60
-2017-04-21 22:28:11.61      RCHRES R001   DELT=60
-2017-04-21 22:28:11.88      PERLND P031   DELT=60
-2017-04-21 22:28:12.00      PERLND P041   DELT=60
-2017-04-21 22:28:12.12      PERLND P042   DELT=60
-2017-04-21 22:28:12.23      PERLND P043   DELT=60
-2017-04-21 22:28:12.34      IMPLND I041   DELT=60
-2017-04-21 22:28:12.39      RCHRES R021   DELT=60
-2017-04-21 22:28:12.48      RCHRES R022   DELT=60
-2017-04-21 22:28:12.57      RCHRES R023   DELT=60
-2017-04-21 22:28:12.65      PERLND P051   DELT=60
-2017-04-21 22:28:12.78      PERLND P052   DELT=60
-2017-04-21 22:28:12.89      PERLND P053   DELT=60
-2017-04-21 22:28:13      PERLND P054   DELT=60
-2017-04-21 22:28:13.11      PERLND P055   DELT=60
-2017-04-21 22:28:13.23      IMPLND I051   DELT=60
-2017-04-21 22:28:13.26      RCHRES R011   DELT=60
-2017-04-21 22:28:13.56      RCHRES R024   DELT=60
-2017-04-21 22:28:13.67      PERLND P061   DELT=60
-2017-04-21 22:28:13.79      PERLND P062   DELT=60
-2017-04-21 22:28:13.92      IMPLND I061   DELT=60
-2017-04-21 22:28:13.96      PERLND P071   DELT=60
-2017-04-21 22:28:14.09      PERLND P072   DELT=60
-2017-04-21 22:28:14.20      PERLND P073   DELT=60
-2017-04-21 22:28:14.32      PERLND P074   DELT=60
-2017-04-21 22:28:14.43      PERLND P075   DELT=60
-2017-04-21 22:28:14.54      IMPLND I071   DELT=60
-2017-04-21 22:28:14.59      RCHRES R031   DELT=60
-2017-04-21 22:28:14.78      RCHRES R071   DELT=60
-2017-04-21 22:28:14.90      PERLND P081   DELT=60
-2017-04-21 22:28:15.03      PERLND P082   DELT=60
-2017-04-21 22:28:15.13      PERLND P083   DELT=60
-2017-04-21 22:28:15.24      PERLND P084   DELT=60
-2017-04-21 22:28:15.35      PERLND P085   DELT=60
-2017-04-21 22:28:15.48      IMPLND I081   DELT=60
-2017-04-21 22:28:15.53      PERLND P091   DELT=60
-2017-04-21 22:28:15.65      RCHRES R043   DELT=60
-2017-04-21 22:28:15.74      PERLND P101   DELT=60
-2017-04-21 22:28:15.87         Message count 30   Message PWATER: Reduced AGWO value to available
-2017-04-21 22:28:15.87         Message count 20285   Message PWATER: Reset AGWS to zero
-2017-04-21 22:28:15.87      PERLND P102   DELT=60
-2017-04-21 22:28:15.99      IMPLND I101   DELT=60
-2017-04-21 22:28:16.04      RCHRES R041   DELT=60
-2017-04-21 22:28:16.13      RCHRES R042   DELT=60
-2017-04-21 22:28:16.24      RCHRES R044   DELT=60
-2017-04-21 22:28:16.36      PERLND P111   DELT=60
-2017-04-21 22:28:16.49      PERLND P112   DELT=60
-2017-04-21 22:28:16.60      PERLND P113   DELT=60
-2017-04-21 22:28:16.72      IMPLND I111   DELT=60
-2017-04-21 22:28:16.77      RCHRES R045   DELT=60
-2017-04-21 22:28:16.89      PERLND P121   DELT=60
-2017-04-21 22:28:17.02      PERLND P122   DELT=60
-2017-04-21 22:28:17.14      PERLND P123   DELT=60
-2017-04-21 22:28:17.27      PERLND P124   DELT=60
-2017-04-21 22:28:17.38      PERLND P125   DELT=60
-2017-04-21 22:28:17.50      IMPLND I121   DELT=60
-2017-04-21 22:28:17.55      RCHRES R002   DELT=60
-2017-04-21 22:28:18.28      RCHRES R025   DELT=60
-2017-04-21 22:28:18.58      RCHRES R003   DELT=60
-2017-04-21 22:28:18.96      RCHRES R004   DELT=60
-2017-04-21 22:28:19.25      RCHRES R904   DELT=60
-2017-04-21 22:28:19.35      PERLND P131   DELT=60
-2017-04-21 22:28:19.49      PERLND P132   DELT=60
-2017-04-21 22:28:19.60      PERLND P133   DELT=60
-2017-04-21 22:28:19.72      PERLND P134   DELT=60
-2017-04-21 22:28:19.85      PERLND P135   DELT=60
-2017-04-21 22:28:19.96      IMPLND I131   DELT=60
-2017-04-21 22:28:20.00      RCHRES R061   DELT=60
-2017-04-21 22:28:20.11      RCHRES R062   DELT=60
-2017-04-21 22:28:20.22      RCHRES R063   DELT=60
-2017-04-21 22:28:20.36      RCHRES R064   DELT=60
-2017-04-21 22:28:20.50      RCHRES R964   DELT=60
-2017-04-21 22:28:20.62      RCHRES R091   DELT=60
-2017-04-21 22:28:20.78      PERLND P141   DELT=60
-2017-04-21 22:28:20.90      PERLND P142   DELT=60
-2017-04-21 22:28:21.03      PERLND P143   DELT=60
-2017-04-21 22:28:21.14      PERLND P144   DELT=60
-2017-04-21 22:28:21.25      PERLND P145   DELT=60
-2017-04-21 22:28:21.36      IMPLND I141   DELT=60
-2017-04-21 22:28:21.40      RCHRES R005   DELT=60
-2017-04-21 22:28:22.40      RCHRES R046   DELT=60
-2017-04-21 22:28:22.61      RCHRES R065   DELT=60
-2017-04-21 22:28:22.86      RCHRES R072   DELT=60
-2017-04-21 22:28:23.06      PERLND P151   DELT=60
-2017-04-21 22:28:23.20      PERLND P152   DELT=60
-2017-04-21 22:28:23.31      IMPLND I151   DELT=60
-2017-04-21 22:28:23.36      RCHRES R051   DELT=60
-2017-04-21 22:28:23.47      RCHRES R952   DELT=60
-2017-04-21 22:28:23.58      RCHRES R052   DELT=60
-2017-04-21 22:28:23.76      RCHRES R006   DELT=60
-2017-04-21 22:28:23.90      RCHRES R081   DELT=60
-2017-04-21 22:28:24.03      PERLND P161   DELT=60
-2017-04-21 22:28:24.15      PERLND P162   DELT=60
-2017-04-21 22:28:24.29      PERLND P163   DELT=60
-2017-04-21 22:28:24.41      PERLND P164   DELT=60
-2017-04-21 22:28:24.52      PERLND P165   DELT=60
-2017-04-21 22:28:24.66      IMPLND I161   DELT=60
-2017-04-21 22:28:24.71      RCHRES R101   DELT=60
-2017-04-21 22:28:24.85      RCHRES R102   DELT=60
-2017-04-21 22:28:24.94      RCHRES R103   DELT=60
-2017-04-21 22:28:25.05      RCHRES R104   DELT=60
-2017-04-21 22:28:25.15      RCHRES R105   DELT=60
-2017-04-21 22:28:25.24      PERLND P171   DELT=60
-2017-04-21 22:28:25.37      PERLND P172   DELT=60
-2017-04-21 22:28:25.49      PERLND P173   DELT=60
-2017-04-21 22:28:25.60      PERLND P174   DELT=60
-2017-04-21 22:28:25.73      PERLND P175   DELT=60
-2017-04-21 22:28:25.85      IMPLND I171   DELT=60
-2017-04-21 22:28:25.90      PERLND P181   DELT=60
-2017-04-21 22:28:26.02      PERLND P182   DELT=60
-2017-04-21 22:28:26.15      PERLND P183   DELT=60
-2017-04-21 22:28:26.29      PERLND P184   DELT=60
-2017-04-21 22:28:26.40      PERLND P185   DELT=60
-2017-04-21 22:28:26.52         Message count 1533   Message PWATER: Reduced AGWO value to available
-2017-04-21 22:28:26.52         Message count 71712   Message PWATER: Reset AGWS to zero
-2017-04-21 22:28:26.52      IMPLND I181   DELT=60
-2017-04-21 22:28:26.58      RCHRES R107   DELT=60
-2017-04-21 22:28:26.79      RCHRES R106   DELT=60
-2017-04-21 22:28:26.94      RCHRES R108   DELT=60
-2017-04-21 22:28:27.06      RCHRES R007   DELT=60
-2017-04-21 22:28:27.24      RCHRES R082   DELT=60
-2017-04-21 22:28:27.50      RCHRES R092   DELT=60
-2017-04-21 22:28:27.75      RCHRES R008   DELT=60
-2017-04-21 22:28:27.91      RCHRES R009   DELT=60
-2017-04-21 22:28:28.03      RCHRES R109   DELT=60
-2017-04-21 22:28:28.24      RCHRES R010   DELT=60
-2017-04-21 22:28:28.45      PERLND P191   DELT=60
-2017-04-21 22:28:28.59      PERLND P192   DELT=60
-2017-04-21 22:28:28.71      PERLND P193   DELT=60
-2017-04-21 22:28:28.84      PERLND P194   DELT=60
-2017-04-21 22:28:28.96      PERLND P195   DELT=60
-2017-04-21 22:28:29.09      IMPLND I191   DELT=60
-2017-04-21 22:28:29.13      PERLND P201   DELT=60
-2017-04-21 22:28:29.26      PERLND P202   DELT=60
-2017-04-21 22:28:29.38      PERLND P203   DELT=60
-2017-04-21 22:28:29.51      PERLND P204   DELT=60
-2017-04-21 22:28:29.63      PERLND P205   DELT=60
-2017-04-21 22:28:29.76      PERLND P206   DELT=60
-2017-04-21 22:28:29.90      IMPLND I201   DELT=60
-2017-04-21 22:28:29.95      PERLND P211   DELT=60
-2017-04-21 22:28:30.07      PERLND P212   DELT=60
-2017-04-21 22:28:30.20      PERLND P213   DELT=60
-2017-04-21 22:28:30.32      PERLND P214   DELT=60
-2017-04-21 22:28:30.43      PERLND P215   DELT=60
-2017-04-21 22:28:30.56      PERLND P216   DELT=60
-2017-04-21 22:28:30.70      IMPLND I211   DELT=60
-2017-04-21 22:28:30.74      PERLND P221   DELT=60
-2017-04-21 22:28:30.89      PERLND P222   DELT=60
-2017-04-21 22:28:30.99      PERLND P224   DELT=60
-2017-04-21 22:28:31.12      PERLND P225   DELT=60
-2017-04-21 22:28:31.24      PERLND P226   DELT=60
-2017-04-21 22:28:31.37      IMPLND I221   DELT=60
-2017-04-21 22:28:31.43      PERLND P231   DELT=60
-2017-04-21 22:28:31.54      PERLND P232   DELT=60
-2017-04-21 22:28:31.68      PERLND P234   DELT=60
-2017-04-21 22:28:31.81      PERLND P235   DELT=60
-2017-04-21 22:28:31.92      IMPLND I231   DELT=60
-2017-04-21 22:28:31.96      PERLND P241   DELT=60
-2017-04-21 22:28:32.09      PERLND P242   DELT=60
-2017-04-21 22:28:32.21      PERLND P243   DELT=60
-2017-04-21 22:28:32.33      PERLND P244   DELT=60
-2017-04-21 22:28:32.44      PERLND P245   DELT=60
-2017-04-21 22:28:32.57      IMPLND I241   DELT=60
-2017-04-21 22:28:32.61      PERLND P251   DELT=60
-2017-04-21 22:28:32.75      PERLND P252   DELT=60
-2017-04-21 22:28:32.88      PERLND P253   DELT=60
-2017-04-21 22:28:32.99      PERLND P254   DELT=60
-2017-04-21 22:28:33.11      PERLND P255   DELT=60
-2017-04-21 22:28:33.22      PERLND P256   DELT=60
-2017-04-21 22:28:33.35      IMPLND I251   DELT=60
-2017-04-21 22:28:33.39      PERLND P261   DELT=60
-2017-04-21 22:28:33.52      PERLND P266   DELT=60
-2017-04-21 22:28:33.66      PERLND P271   DELT=60
-2017-04-21 22:28:33.78      PERLND P272   DELT=60
-2017-04-21 22:28:33.91      PERLND P275   DELT=60
-2017-04-21 22:28:34.03      PERLND P276   DELT=60
-2017-04-21 22:28:34.16      IMPLND I271   DELT=60
-2017-04-21 22:28:34.21      PERLND P281   DELT=60
-2017-04-21 22:28:34.33      PERLND P282   DELT=60
-2017-04-21 22:28:34.44      PERLND P283   DELT=60
-2017-04-21 22:28:34.57      PERLND P285   DELT=60
-2017-04-21 22:28:34.69      PERLND P286   DELT=60
-2017-04-21 22:28:34.82      IMPLND I281   DELT=60
-2017-04-21 22:28:34.86      PERLND P291   DELT=60
-2017-04-21 22:28:34.99      PERLND P292   DELT=60
-2017-04-21 22:28:35.11      PERLND P293   DELT=60
-2017-04-21 22:28:35.22      PERLND P294   DELT=60
-2017-04-21 22:28:35.36      PERLND P295   DELT=60
-2017-04-21 22:28:35.47      PERLND P296   DELT=60
-2017-04-21 22:28:35.60      IMPLND I291   DELT=60
-2017-04-21 22:28:35.66      PERLND P301   DELT=60
-2017-04-21 22:28:35.79      PERLND P302   DELT=60
-2017-04-21 22:28:35.91      PERLND P303   DELT=60
-2017-04-21 22:28:36.02      PERLND P304   DELT=60
-2017-04-21 22:28:36.14      PERLND P305   DELT=60
-2017-04-21 22:28:36.25      PERLND P306   DELT=60
-2017-04-21 22:28:36.39      IMPLND I301   DELT=60
-2017-04-21 22:28:36.43      RCHRES R201   DELT=60
-2017-04-21 22:28:36.58      RCHRES R190   DELT=60
-2017-04-21 22:28:36.70      RCHRES R202   DELT=60
-2017-04-21 22:28:36.84      RCHRES R191   DELT=60
-2017-04-21 22:28:36.98      RCHRES R203   DELT=60
-2017-04-21 22:28:37.15      RCHRES R211   DELT=60
-2017-04-21 22:28:37.26      RCHRES R212   DELT=60
-2017-04-21 22:28:37.40      RCHRES R192   DELT=60
-2017-04-21 22:28:37.53      RCHRES R204   DELT=60
-2017-04-21 22:28:37.70      RCHRES R221   DELT=60
-2017-04-21 22:28:37.86      RCHRES R222   DELT=60
-2017-04-21 22:28:37.95      RCHRES R223   DELT=60
-2017-04-21 22:28:38.12      RCHRES R193   DELT=60
-2017-04-21 22:28:38.23      RCHRES R205   DELT=60
-2017-04-21 22:28:38.40      RCHRES R225   DELT=60
-2017-04-21 22:28:38.56      RCHRES R194   DELT=60
-2017-04-21 22:28:38.65      RCHRES R206   DELT=60
-2017-04-21 22:28:38.81      RCHRES R227   DELT=60
-2017-04-21 22:28:38.97      RCHRES R207   DELT=60
-2017-04-21 22:28:39.12      RCHRES R231   DELT=60
-2017-04-21 22:28:39.24      RCHRES R232   DELT=60
-2017-04-21 22:28:39.33      RCHRES R233   DELT=60
-2017-04-21 22:28:39.49      RCHRES R241   DELT=60
-2017-04-21 22:28:39.63      RCHRES R242   DELT=60
-2017-04-21 22:28:39.74      RCHRES R243   DELT=60
-2017-04-21 22:28:39.85      RCHRES R301   DELT=60
-2017-04-21 22:28:40.02      RCHRES R311   DELT=60
-2017-04-21 22:28:40.12      RCHRES R302   DELT=60
-2017-04-21 22:28:40.29      RCHRES R303   DELT=60
-2017-04-21 22:28:40.43      RCHRES R401   DELT=60
-2017-04-21 22:28:40.57      RCHRES R411   DELT=60
-2017-04-21 22:28:40.69      RCHRES R402   DELT=60
-2017-04-21 22:28:40.85      RCHRES R421   DELT=60
-2017-04-21 22:28:40.98      RCHRES R422   DELT=60
-2017-04-21 22:28:41.08      RCHRES R423   DELT=60
-2017-04-21 22:28:41.21      RCHRES R403   DELT=60
-2017-04-21 22:28:41.37      RCHRES R431   DELT=60
-2017-04-21 22:28:41.51      RCHRES R404   DELT=60
-2017-04-21 22:28:41.66      RCHRES R441   DELT=60
-2017-04-21 22:28:41.79      RCHRES R443   DELT=60
-2017-04-21 22:28:41.90      RCHRES R442   DELT=60
-2017-04-21 22:28:42.05      RCHRES R405   DELT=60
-2017-04-21 22:28:42.19      RCHRES R406   DELT=60
-2017-04-21 22:28:42.37      RCHRES R407   DELT=60
-2017-04-21 22:28:42.52      RCHRES R408   DELT=60
-2017-04-21 22:28:42.68      RCHRES R195   DELT=60
-2017-04-21 22:28:42.77      RCHRES R304   DELT=60
-2017-04-21 22:28:42.94      RCHRES R305   DELT=60
-2017-04-21 22:28:43.13      RCHRES R306   DELT=60
-2017-04-21 22:28:43.25      RCHRES R500   DELT=60
-2017-04-21 22:28:43.36      RCHRES R501   DELT=60
-2017-04-21 22:28:43.55      RCHRES R513   DELT=60
-2017-04-21 22:28:43.67      RCHRES R514   DELT=60
-2017-04-21 22:28:43.78      RCHRES R502   DELT=60
-2017-04-21 22:28:44.05      RCHRES R510   DELT=60
-2017-04-21 22:28:44.19      RCHRES R511   DELT=60
-2017-04-21 22:28:44.39      RCHRES R512   DELT=60
-2017-04-21 22:28:44.55      RCHRES R503   DELT=60
-2017-04-21 22:28:44.83      RCHRES R523   DELT=60
-2017-04-21 22:28:44.95      RCHRES R524   DELT=60
-2017-04-21 22:28:45.05      RCHRES R525   DELT=60
-2017-04-21 22:28:45.16      RCHRES R526   DELT=60
-2017-04-21 22:28:45.25      RCHRES R521   DELT=60
-2017-04-21 22:28:45.42      RCHRES R522   DELT=60
-2017-04-21 22:28:45.59      RCHRES R531   DELT=60
-2017-04-21 22:28:45.74      RCHRES R504   DELT=60
-2017-04-21 22:28:45.86      RCHRES R505   DELT=60
-2017-04-21 22:28:45.99      RCHRES R506   DELT=60
-2017-04-21 22:28:46.11      RCHRES R541   DELT=60
-2017-04-21 22:28:46.24      RCHRES R542   DELT=60
-2017-04-21 22:28:46.38      RCHRES R307   DELT=60
-2017-04-21 22:28:46.52   Run completed
-2017-04-21 22:28:47.22   Run Started for file calleg.h5
-2017-04-21 22:28:47.23     Start 1993-10-01 00:00    Stop 2002-09-30 23:59
-2017-04-21 22:28:47.59   Finished setup
-2017-04-21 22:28:47.61      PERLND P011   DELT=60
-2017-04-21 22:28:47.73      PERLND P012   DELT=60
-2017-04-21 22:28:47.84      PERLND P013   DELT=60
-2017-04-21 22:28:47.95      PERLND P014   DELT=60
-2017-04-21 22:28:48.06      PERLND P015   DELT=60
-2017-04-21 22:28:48.17      IMPLND I011   DELT=60
-2017-04-21 22:28:48.22      PERLND P021   DELT=60
-2017-04-21 22:28:48.34      PERLND P022   DELT=60
-2017-04-21 22:28:48.45      PERLND P023   DELT=60
-2017-04-21 22:28:48.56      PERLND P024   DELT=60
-2017-04-21 22:28:48.67      PERLND P025   DELT=60
-2017-04-21 22:28:48.78      IMPLND I021   DELT=60
-2017-04-21 22:28:48.83      RCHRES R001   DELT=60
-2017-04-21 22:28:49.09      PERLND P031   DELT=60
-2017-04-21 22:28:49.21      PERLND P041   DELT=60
-2017-04-21 22:28:49.34      PERLND P042   DELT=60
-2017-04-21 22:28:49.46      PERLND P043   DELT=60
-2017-04-21 22:28:49.56      IMPLND I041   DELT=60
-2017-04-21 22:28:49.61      RCHRES R021   DELT=60
-2017-04-21 22:28:49.69      RCHRES R022   DELT=60
-2017-04-21 22:28:49.78      RCHRES R023   DELT=60
-2017-04-21 22:28:49.88      PERLND P051   DELT=60
-2017-04-21 22:28:49.99      PERLND P052   DELT=60
-2017-04-21 22:28:50.10      PERLND P053   DELT=60
-2017-04-21 22:28:50.21      PERLND P054   DELT=60
-2017-04-21 22:28:50.33      PERLND P055   DELT=60
-2017-04-21 22:28:50.44      IMPLND I051   DELT=60
-2017-04-21 22:28:50.49      RCHRES R011   DELT=60
-2017-04-21 22:28:50.75      RCHRES R024   DELT=60
-2017-04-21 22:28:50.88      PERLND P061   DELT=60
-2017-04-21 22:28:51.00      PERLND P062   DELT=60
-2017-04-21 22:28:51.12      IMPLND I061   DELT=60
-2017-04-21 22:28:51.15      PERLND P071   DELT=60
-2017-04-21 22:28:51.28      PERLND P072   DELT=60
-2017-04-21 22:28:51.39      PERLND P073   DELT=60
-2017-04-21 22:28:51.50      PERLND P074   DELT=60
-2017-04-21 22:28:51.60      PERLND P075   DELT=60
-2017-04-21 22:28:51.71      IMPLND I071   DELT=60
-2017-04-21 22:28:51.76      RCHRES R031   DELT=60
-2017-04-21 22:28:51.95      RCHRES R071   DELT=60
-2017-04-21 22:28:52.06      PERLND P081   DELT=60
-2017-04-21 22:28:52.18      PERLND P082   DELT=60
-2017-04-21 22:28:52.29      PERLND P083   DELT=60
-2017-04-21 22:28:52.42      PERLND P084   DELT=60
-2017-04-21 22:28:52.53      PERLND P085   DELT=60
-2017-04-21 22:28:52.64      IMPLND I081   DELT=60
-2017-04-21 22:28:52.68      PERLND P091   DELT=60
-2017-04-21 22:28:52.81      RCHRES R043   DELT=60
-2017-04-21 22:28:52.90      PERLND P101   DELT=60
-2017-04-21 22:28:53.03         Message count 30   Message PWATER: Reduced AGWO value to available
-2017-04-21 22:28:53.03         Message count 20285   Message PWATER: Reset AGWS to zero
-2017-04-21 22:28:53.03      PERLND P102   DELT=60
-2017-04-21 22:28:53.15      IMPLND I101   DELT=60
-2017-04-21 22:28:53.20      RCHRES R041   DELT=60
-2017-04-21 22:28:53.28      RCHRES R042   DELT=60
-2017-04-21 22:28:53.40      RCHRES R044   DELT=60
-2017-04-21 22:28:53.50      PERLND P111   DELT=60
-2017-04-21 22:28:53.64      PERLND P112   DELT=60
-2017-04-21 22:28:53.82      PERLND P113   DELT=60
-2017-04-21 22:28:54.01      IMPLND I111   DELT=60
-2017-04-21 22:28:54.07      RCHRES R045   DELT=60
-2017-04-21 22:28:54.26      PERLND P121   DELT=60
-2017-04-21 22:28:54.45      PERLND P122   DELT=60
-2017-04-21 22:28:54.57      PERLND P123   DELT=60
-2017-04-21 22:28:54.68      PERLND P124   DELT=60
-2017-04-21 22:28:54.79      PERLND P125   DELT=60
-2017-04-21 22:28:54.92      IMPLND I121   DELT=60
-2017-04-21 22:28:54.95      RCHRES R002   DELT=60
-2017-04-21 22:28:55.66      RCHRES R025   DELT=60
-2017-04-21 22:28:55.96      RCHRES R003   DELT=60
-2017-04-21 22:28:56.30      RCHRES R004   DELT=60
-2017-04-21 22:28:56.57      RCHRES R904   DELT=60
-2017-04-21 22:28:56.66      PERLND P131   DELT=60
-2017-04-21 22:28:56.79      PERLND P132   DELT=60
-2017-04-21 22:28:56.91      PERLND P133   DELT=60
-2017-04-21 22:28:57.02      PERLND P134   DELT=60
-2017-04-21 22:28:57.14      PERLND P135   DELT=60
-2017-04-21 22:28:57.27      IMPLND I131   DELT=60
-2017-04-21 22:28:57.30      RCHRES R061   DELT=60
-2017-04-21 22:28:57.41      RCHRES R062   DELT=60
-2017-04-21 22:28:57.52      RCHRES R063   DELT=60
-2017-04-21 22:28:57.64      RCHRES R064   DELT=60
-2017-04-21 22:28:57.79      RCHRES R964   DELT=60
-2017-04-21 22:28:57.89      RCHRES R091   DELT=60
-2017-04-21 22:28:58.05      PERLND P141   DELT=60
-2017-04-21 22:28:58.18      PERLND P142   DELT=60
-2017-04-21 22:28:58.30      PERLND P143   DELT=60
-2017-04-21 22:28:58.41      PERLND P144   DELT=60
-2017-04-21 22:28:58.54      PERLND P145   DELT=60
-2017-04-21 22:28:58.64      IMPLND I141   DELT=60
-2017-04-21 22:28:58.69      RCHRES R005   DELT=60
-2017-04-21 22:28:59.69      RCHRES R046   DELT=60
-2017-04-21 22:28:59.90      RCHRES R065   DELT=60
-2017-04-21 22:29:00.15      RCHRES R072   DELT=60
-2017-04-21 22:29:00.34      PERLND P151   DELT=60
-2017-04-21 22:29:00.47      PERLND P152   DELT=60
-2017-04-21 22:29:00.59      IMPLND I151   DELT=60
-2017-04-21 22:29:00.64      RCHRES R051   DELT=60
-2017-04-21 22:29:00.73      RCHRES R952   DELT=60
-2017-04-21 22:29:00.84      RCHRES R052   DELT=60
-2017-04-21 22:29:01.03      RCHRES R006   DELT=60
-2017-04-21 22:29:01.19      RCHRES R081   DELT=60
-2017-04-21 22:29:01.30      PERLND P161   DELT=60
-2017-04-21 22:29:01.44      PERLND P162   DELT=60
-2017-04-21 22:29:01.55      PERLND P163   DELT=60
-2017-04-21 22:29:01.67      PERLND P164   DELT=60
-2017-04-21 22:29:01.78      PERLND P165   DELT=60
-2017-04-21 22:29:01.89      IMPLND I161   DELT=60
-2017-04-21 22:29:01.94      RCHRES R101   DELT=60
-2017-04-21 22:29:02.08      RCHRES R102   DELT=60
-2017-04-21 22:29:02.17      RCHRES R103   DELT=60
-2017-04-21 22:29:02.28      RCHRES R104   DELT=60
-2017-04-21 22:29:02.37      RCHRES R105   DELT=60
-2017-04-21 22:29:02.45      PERLND P171   DELT=60
-2017-04-21 22:29:02.59      PERLND P172   DELT=60
-2017-04-21 22:29:02.72      PERLND P173   DELT=60
-2017-04-21 22:29:02.84      PERLND P174   DELT=60
-2017-04-21 22:29:02.95      PERLND P175   DELT=60
-2017-04-21 22:29:03.08      IMPLND I171   DELT=60
-2017-04-21 22:29:03.14      PERLND P181   DELT=60
-2017-04-21 22:29:03.25      PERLND P182   DELT=60
-2017-04-21 22:29:03.37      PERLND P183   DELT=60
-2017-04-21 22:29:03.50      PERLND P184   DELT=60
-2017-04-21 22:29:03.62      PERLND P185   DELT=60
-2017-04-21 22:29:03.75         Message count 1533   Message PWATER: Reduced AGWO value to available
-2017-04-21 22:29:03.75         Message count 71712   Message PWATER: Reset AGWS to zero
-2017-04-21 22:29:03.75      IMPLND I181   DELT=60
-2017-04-21 22:29:03.80      RCHRES R107   DELT=60
-2017-04-21 22:29:04.01      RCHRES R106   DELT=60
-2017-04-21 22:29:04.17      RCHRES R108   DELT=60
-2017-04-21 22:29:04.28      RCHRES R007   DELT=60
-2017-04-21 22:29:04.45      RCHRES R082   DELT=60
-2017-04-21 22:29:04.70      RCHRES R092   DELT=60
-2017-04-21 22:29:04.94      RCHRES R008   DELT=60
-2017-04-21 22:29:05.11      RCHRES R009   DELT=60
-2017-04-21 22:29:05.23      RCHRES R109   DELT=60
-2017-04-21 22:29:05.45      RCHRES R010   DELT=60
-2017-04-21 22:29:05.65      PERLND P191   DELT=60
-2017-04-21 22:29:05.80      PERLND P192   DELT=60
-2017-04-21 22:29:05.92      PERLND P193   DELT=60
-2017-04-21 22:29:06.05      PERLND P194   DELT=60
-2017-04-21 22:29:06.17      PERLND P195   DELT=60
-2017-04-21 22:29:06.28      IMPLND I191   DELT=60
-2017-04-21 22:29:06.34      PERLND P201   DELT=60
-2017-04-21 22:29:06.47      PERLND P202   DELT=60
-2017-04-21 22:29:06.59      PERLND P203   DELT=60
-2017-04-21 22:29:06.72      PERLND P204   DELT=60
-2017-04-21 22:29:06.84      PERLND P205   DELT=60
-2017-04-21 22:29:06.97      PERLND P206   DELT=60
-2017-04-21 22:29:07.11      IMPLND I201   DELT=60
-2017-04-21 22:29:07.15      PERLND P211   DELT=60
-2017-04-21 22:29:07.29      PERLND P212   DELT=60
-2017-04-21 22:29:07.40      PERLND P213   DELT=60
-2017-04-21 22:29:07.52      PERLND P214   DELT=60
-2017-04-21 22:29:07.65      PERLND P215   DELT=60
-2017-04-21 22:29:07.77      PERLND P216   DELT=60
-2017-04-21 22:29:07.90      IMPLND I211   DELT=60
-2017-04-21 22:29:07.95      PERLND P221   DELT=60
-2017-04-21 22:29:08.09      PERLND P222   DELT=60
-2017-04-21 22:29:08.21      PERLND P224   DELT=60
-2017-04-21 22:29:08.32      PERLND P225   DELT=60
-2017-04-21 22:29:08.43      PERLND P226   DELT=60
-2017-04-21 22:29:08.57      IMPLND I221   DELT=60
-2017-04-21 22:29:08.62      PERLND P231   DELT=60
-2017-04-21 22:29:08.74      PERLND P232   DELT=60
-2017-04-21 22:29:08.87      PERLND P234   DELT=60
-2017-04-21 22:29:08.98      PERLND P235   DELT=60
-2017-04-21 22:29:09.11      IMPLND I231   DELT=60
-2017-04-21 22:29:09.14      PERLND P241   DELT=60
-2017-04-21 22:29:09.27      PERLND P242   DELT=60
-2017-04-21 22:29:09.39      PERLND P243   DELT=60
-2017-04-21 22:29:09.52      PERLND P244   DELT=60
-2017-04-21 22:29:09.63      PERLND P245   DELT=60
-2017-04-21 22:29:09.75      IMPLND I241   DELT=60
-2017-04-21 22:29:09.80      PERLND P251   DELT=60
-2017-04-21 22:29:09.92      PERLND P252   DELT=60
-2017-04-21 22:29:10.03      PERLND P253   DELT=60
-2017-04-21 22:29:10.16      PERLND P254   DELT=60
-2017-04-21 22:29:10.27      PERLND P255   DELT=60
-2017-04-21 22:29:10.38      PERLND P256   DELT=60
-2017-04-21 22:29:10.50      IMPLND I251   DELT=60
-2017-04-21 22:29:10.55      PERLND P261   DELT=60
-2017-04-21 22:29:10.67      PERLND P266   DELT=60
-2017-04-21 22:29:10.83      PERLND P271   DELT=60
-2017-04-21 22:29:10.96      PERLND P272   DELT=60
-2017-04-21 22:29:11.07      PERLND P275   DELT=60
-2017-04-21 22:29:11.17      PERLND P276   DELT=60
-2017-04-21 22:29:11.31      IMPLND I271   DELT=60
-2017-04-21 22:29:11.36      PERLND P281   DELT=60
-2017-04-21 22:29:11.48      PERLND P282   DELT=60
-2017-04-21 22:29:11.59      PERLND P283   DELT=60
-2017-04-21 22:29:11.72      PERLND P285   DELT=60
-2017-04-21 22:29:11.83      PERLND P286   DELT=60
-2017-04-21 22:29:11.96      IMPLND I281   DELT=60
-2017-04-21 22:29:12.01      PERLND P291   DELT=60
-2017-04-21 22:29:12.14      PERLND P292   DELT=60
-2017-04-21 22:29:12.25      PERLND P293   DELT=60
-2017-04-21 22:29:12.37      PERLND P294   DELT=60
-2017-04-21 22:29:12.48      PERLND P295   DELT=60
-2017-04-21 22:29:12.59      PERLND P296   DELT=60
-2017-04-21 22:29:12.73      IMPLND I291   DELT=60
-2017-04-21 22:29:12.78      PERLND P301   DELT=60
-2017-04-21 22:29:12.89      PERLND P302   DELT=60
-2017-04-21 22:29:13.01      PERLND P303   DELT=60
-2017-04-21 22:29:13.12      PERLND P304   DELT=60
-2017-04-21 22:29:13.25      PERLND P305   DELT=60
-2017-04-21 22:29:13.35      PERLND P306   DELT=60
-2017-04-21 22:29:13.50      IMPLND I301   DELT=60
-2017-04-21 22:29:13.54      RCHRES R201   DELT=60
-2017-04-21 22:29:13.68      RCHRES R190   DELT=60
-2017-04-21 22:29:13.79      RCHRES R202   DELT=60
-2017-04-21 22:29:13.93      RCHRES R191   DELT=60
-2017-04-21 22:29:14.07      RCHRES R203   DELT=60
-2017-04-21 22:29:14.24      RCHRES R211   DELT=60
-2017-04-21 22:29:14.35      RCHRES R212   DELT=60
-2017-04-21 22:29:14.49      RCHRES R192   DELT=60
-2017-04-21 22:29:14.61      RCHRES R204   DELT=60
-2017-04-21 22:29:14.79      RCHRES R221   DELT=60
-2017-04-21 22:29:14.96      RCHRES R222   DELT=60
-2017-04-21 22:29:15.05      RCHRES R223   DELT=60
-2017-04-21 22:29:15.21      RCHRES R193   DELT=60
-2017-04-21 22:29:15.32      RCHRES R205   DELT=60
-2017-04-21 22:29:15.49      RCHRES R225   DELT=60
-2017-04-21 22:29:15.63      RCHRES R194   DELT=60
-2017-04-21 22:29:15.74      RCHRES R206   DELT=60
-2017-04-21 22:29:15.90      RCHRES R227   DELT=60
-2017-04-21 22:29:16.04      RCHRES R207   DELT=60
-2017-04-21 22:29:16.18      RCHRES R231   DELT=60
-2017-04-21 22:29:16.32      RCHRES R232   DELT=60
-2017-04-21 22:29:16.41      RCHRES R233   DELT=60
-2017-04-21 22:29:16.55      RCHRES R241   DELT=60
-2017-04-21 22:29:16.69      RCHRES R242   DELT=60
-2017-04-21 22:29:16.80      RCHRES R243   DELT=60
-2017-04-21 22:29:16.91      RCHRES R301   DELT=60
-2017-04-21 22:29:17.08      RCHRES R311   DELT=60
-2017-04-21 22:29:17.18      RCHRES R302   DELT=60
-2017-04-21 22:29:17.35      RCHRES R303   DELT=60
-2017-04-21 22:29:17.49      RCHRES R401   DELT=60
-2017-04-21 22:29:17.65      RCHRES R411   DELT=60
-2017-04-21 22:29:17.77      RCHRES R402   DELT=60
-2017-04-21 22:29:17.91      RCHRES R421   DELT=60
-2017-04-21 22:29:18.05      RCHRES R422   DELT=60
-2017-04-21 22:29:18.14      RCHRES R423   DELT=60
-2017-04-21 22:29:18.27      RCHRES R403   DELT=60
-2017-04-21 22:29:18.42      RCHRES R431   DELT=60
-2017-04-21 22:29:18.56      RCHRES R404   DELT=60
-2017-04-21 22:29:18.70      RCHRES R441   DELT=60
-2017-04-21 22:29:18.84      RCHRES R443   DELT=60
-2017-04-21 22:29:18.95      RCHRES R442   DELT=60
-2017-04-21 22:29:19.11      RCHRES R405   DELT=60
-2017-04-21 22:29:19.25      RCHRES R406   DELT=60
-2017-04-21 22:29:19.41      RCHRES R407   DELT=60
-2017-04-21 22:29:19.58      RCHRES R408   DELT=60
-2017-04-21 22:29:19.73      RCHRES R195   DELT=60
-2017-04-21 22:29:19.83      RCHRES R304   DELT=60
-2017-04-21 22:29:20.00      RCHRES R305   DELT=60
-2017-04-21 22:29:20.17      RCHRES R306   DELT=60
-2017-04-21 22:29:20.31      RCHRES R500   DELT=60
-2017-04-21 22:29:20.44      RCHRES R501   DELT=60
-2017-04-21 22:29:20.59      RCHRES R513   DELT=60
-2017-04-21 22:29:20.73      RCHRES R514   DELT=60
-2017-04-21 22:29:20.84      RCHRES R502   DELT=60
-2017-04-21 22:29:21.09      RCHRES R510   DELT=60
-2017-04-21 22:29:21.25      RCHRES R511   DELT=60
-2017-04-21 22:29:21.45      RCHRES R512   DELT=60
-2017-04-21 22:29:21.62      RCHRES R503   DELT=60
-2017-04-21 22:29:21.91      RCHRES R523   DELT=60
-2017-04-21 22:29:22.03      RCHRES R524   DELT=60
-2017-04-21 22:29:22.13      RCHRES R525   DELT=60
-2017-04-21 22:29:22.24      RCHRES R526   DELT=60
-2017-04-21 22:29:22.35      RCHRES R521   DELT=60
-2017-04-21 22:29:22.51      RCHRES R522   DELT=60
-2017-04-21 22:29:22.71      RCHRES R531   DELT=60
-2017-04-21 22:29:22.85      RCHRES R504   DELT=60
-2017-04-21 22:29:22.99      RCHRES R505   DELT=60
-2017-04-21 22:29:23.13      RCHRES R506   DELT=60
-2017-04-21 22:29:23.26      RCHRES R541   DELT=60
-2017-04-21 22:29:23.37      RCHRES R542   DELT=60
-2017-04-21 22:29:23.51      RCHRES R307   DELT=60
-2017-04-21 22:29:23.65   Run completed
-2017-04-21 22:29:24.45   Run Started for file calleg.h5
-2017-04-21 22:29:24.46     Start 1993-10-01 00:00    Stop 2002-09-30 23:59
-2017-04-21 22:29:24.82   Finished setup
-2017-04-21 22:29:24.82      PERLND P011   DELT=60
-2017-04-21 22:29:24.95      PERLND P012   DELT=60
-2017-04-21 22:29:25.06      PERLND P013   DELT=60
-2017-04-21 22:29:25.17      PERLND P014   DELT=60
-2017-04-21 22:29:25.28      PERLND P015   DELT=60
-2017-04-21 22:29:25.40      IMPLND I011   DELT=60
-2017-04-21 22:29:25.43      PERLND P021   DELT=60
-2017-04-21 22:29:25.56      PERLND P022   DELT=60
-2017-04-21 22:29:25.67      PERLND P023   DELT=60
-2017-04-21 22:29:25.79      PERLND P024   DELT=60
-2017-04-21 22:29:25.90      PERLND P025   DELT=60
-2017-04-21 22:29:26.01      IMPLND I021   DELT=60
-2017-04-21 22:29:26.06      RCHRES R001   DELT=60
-2017-04-21 22:29:26.30      PERLND P031   DELT=60
-2017-04-21 22:29:26.43      PERLND P041   DELT=60
-2017-04-21 22:29:26.55      PERLND P042   DELT=60
-2017-04-21 22:29:26.66      PERLND P043   DELT=60
-2017-04-21 22:29:26.77      IMPLND I041   DELT=60
-2017-04-21 22:29:26.82      RCHRES R021   DELT=60
-2017-04-21 22:29:26.90      RCHRES R022   DELT=60
-2017-04-21 22:29:26.99      RCHRES R023   DELT=60
-2017-04-21 22:29:27.07      PERLND P051   DELT=60
-2017-04-21 22:29:27.20      PERLND P052   DELT=60
-2017-04-21 22:29:27.30      PERLND P053   DELT=60
-2017-04-21 22:29:27.43      PERLND P054   DELT=60
-2017-04-21 22:29:27.52      PERLND P055   DELT=60
-2017-04-21 22:29:27.65      IMPLND I051   DELT=60
-2017-04-21 22:29:27.70      RCHRES R011   DELT=60
-2017-04-21 22:29:27.96      RCHRES R024   DELT=60
-2017-04-21 22:29:28.09      PERLND P061   DELT=60
-2017-04-21 22:29:28.21      PERLND P062   DELT=60
-2017-04-21 22:29:28.32      IMPLND I061   DELT=60
-2017-04-21 22:29:28.37      PERLND P071   DELT=60
-2017-04-21 22:29:28.49      PERLND P072   DELT=60
-2017-04-21 22:29:28.60      PERLND P073   DELT=60
-2017-04-21 22:29:28.73      PERLND P074   DELT=60
-2017-04-21 22:29:28.84      PERLND P075   DELT=60
-2017-04-21 22:29:28.95      IMPLND I071   DELT=60
-2017-04-21 22:29:28.99      RCHRES R031   DELT=60
-2017-04-21 22:29:29.16      RCHRES R071   DELT=60
-2017-04-21 22:29:29.27      PERLND P081   DELT=60
-2017-04-21 22:29:29.40      PERLND P082   DELT=60
-2017-04-21 22:29:29.51      PERLND P083   DELT=60
-2017-04-21 22:29:29.63      PERLND P084   DELT=60
-2017-04-21 22:29:29.74      PERLND P085   DELT=60
-2017-04-21 22:29:29.87      IMPLND I081   DELT=60
-2017-04-21 22:29:29.91      PERLND P091   DELT=60
-2017-04-21 22:29:30.02      RCHRES R043   DELT=60
-2017-04-21 22:29:30.13      PERLND P101   DELT=60
-2017-04-21 22:29:30.24         Message count 30   Message PWATER: Reduced AGWO value to available
-2017-04-21 22:29:30.24         Message count 20285   Message PWATER: Reset AGWS to zero
-2017-04-21 22:29:30.24      PERLND P102   DELT=60
-2017-04-21 22:29:30.37      IMPLND I101   DELT=60
-2017-04-21 22:29:30.41      RCHRES R041   DELT=60
-2017-04-21 22:29:30.49      RCHRES R042   DELT=60
-2017-04-21 22:29:30.60      RCHRES R044   DELT=60
-2017-04-21 22:29:30.76      PERLND P111   DELT=60
-2017-04-21 22:29:30.98      PERLND P112   DELT=60
-2017-04-21 22:29:31.16      PERLND P113   DELT=60
-2017-04-21 22:29:31.37      IMPLND I111   DELT=60
-2017-04-21 22:29:31.41      RCHRES R045   DELT=60
-2017-04-21 22:29:31.54      PERLND P121   DELT=60
-2017-04-21 22:29:31.68      PERLND P122   DELT=60
-2017-04-21 22:29:31.79      PERLND P123   DELT=60
-2017-04-21 22:29:31.91      PERLND P124   DELT=60
-2017-04-21 22:29:32.02      PERLND P125   DELT=60
-2017-04-21 22:29:32.13      IMPLND I121   DELT=60
-2017-04-21 22:29:32.18      RCHRES R002   DELT=60
-2017-04-21 22:29:32.87      RCHRES R025   DELT=60
-2017-04-21 22:29:33.15      RCHRES R003   DELT=60
-2017-04-21 22:29:33.48      RCHRES R004   DELT=60
-2017-04-21 22:29:33.74      RCHRES R904   DELT=60
-2017-04-21 22:29:33.84      PERLND P131   DELT=60
-2017-04-21 22:29:33.96      PERLND P132   DELT=60
-2017-04-21 22:29:34.07      PERLND P133   DELT=60
-2017-04-21 22:29:34.21      PERLND P134   DELT=60
-2017-04-21 22:29:34.32      PERLND P135   DELT=60
-2017-04-21 22:29:34.42      IMPLND I131   DELT=60
-2017-04-21 22:29:34.47      RCHRES R061   DELT=60
-2017-04-21 22:29:34.57      RCHRES R062   DELT=60
-2017-04-21 22:29:34.67      RCHRES R063   DELT=60
-2017-04-21 22:29:34.80      RCHRES R064   DELT=60
-2017-04-21 22:29:34.94      RCHRES R964   DELT=60
-2017-04-21 22:29:35.06      RCHRES R091   DELT=60
-2017-04-21 22:29:35.22      PERLND P141   DELT=60
-2017-04-21 22:29:35.35      PERLND P142   DELT=60
-2017-04-21 22:29:35.46      PERLND P143   DELT=60
-2017-04-21 22:29:35.58      PERLND P144   DELT=60
-2017-04-21 22:29:35.69      PERLND P145   DELT=60
-2017-04-21 22:29:35.80      IMPLND I141   DELT=60
-2017-04-21 22:29:35.85      RCHRES R005   DELT=60
-2017-04-21 22:29:36.83      RCHRES R046   DELT=60
-2017-04-21 22:29:37.04      RCHRES R065   DELT=60
-2017-04-21 22:29:37.27      RCHRES R072   DELT=60
-2017-04-21 22:29:37.46      PERLND P151   DELT=60
-2017-04-21 22:29:37.58      PERLND P152   DELT=60
-2017-04-21 22:29:37.71      IMPLND I151   DELT=60
-2017-04-21 22:29:37.76      RCHRES R051   DELT=60
-2017-04-21 22:29:37.87      RCHRES R952   DELT=60
-2017-04-21 22:29:37.97      RCHRES R052   DELT=60
-2017-04-21 22:29:38.17      RCHRES R006   DELT=60
-2017-04-21 22:29:38.31      RCHRES R081   DELT=60
-2017-04-21 22:29:38.44      PERLND P161   DELT=60
-2017-04-21 22:29:38.55      PERLND P162   DELT=60
-2017-04-21 22:29:38.67      PERLND P163   DELT=60
-2017-04-21 22:29:38.78      PERLND P164   DELT=60
-2017-04-21 22:29:38.89      PERLND P165   DELT=60
-2017-04-21 22:29:39.02      IMPLND I161   DELT=60
-2017-04-21 22:29:39.06      RCHRES R101   DELT=60
-2017-04-21 22:29:39.19      RCHRES R102   DELT=60
-2017-04-21 22:29:39.28      RCHRES R103   DELT=60
-2017-04-21 22:29:39.39      RCHRES R104   DELT=60
-2017-04-21 22:29:39.48      RCHRES R105   DELT=60
-2017-04-21 22:29:39.58      PERLND P171   DELT=60
-2017-04-21 22:29:39.70      PERLND P172   DELT=60
-2017-04-21 22:29:39.81      PERLND P173   DELT=60
-2017-04-21 22:29:39.94      PERLND P174   DELT=60
-2017-04-21 22:29:40.05      PERLND P175   DELT=60
-2017-04-21 22:29:40.16      IMPLND I171   DELT=60
-2017-04-21 22:29:40.20      PERLND P181   DELT=60
-2017-04-21 22:29:40.31      PERLND P182   DELT=60
-2017-04-21 22:29:40.44      PERLND P183   DELT=60
-2017-04-21 22:29:40.55      PERLND P184   DELT=60
-2017-04-21 22:29:40.66      PERLND P185   DELT=60
-2017-04-21 22:29:40.78         Message count 1533   Message PWATER: Reduced AGWO value to available
-2017-04-21 22:29:40.78         Message count 71712   Message PWATER: Reset AGWS to zero
-2017-04-21 22:29:40.78      IMPLND I181   DELT=60
-2017-04-21 22:29:40.83      RCHRES R107   DELT=60
-2017-04-21 22:29:41.04      RCHRES R106   DELT=60
-2017-04-21 22:29:41.19      RCHRES R108   DELT=60
-2017-04-21 22:29:41.30      RCHRES R007   DELT=60
-2017-04-21 22:29:41.47      RCHRES R082   DELT=60
-2017-04-21 22:29:41.72      RCHRES R092   DELT=60
-2017-04-21 22:29:41.96      RCHRES R008   DELT=60
-2017-04-21 22:29:42.12      RCHRES R009   DELT=60
-2017-04-21 22:29:42.25      RCHRES R109   DELT=60
-2017-04-21 22:29:42.44      RCHRES R010   DELT=60
-2017-04-21 22:29:42.64      PERLND P191   DELT=60
-2017-04-21 22:29:42.79      PERLND P192   DELT=60
-2017-04-21 22:29:42.91      PERLND P193   DELT=60
-2017-04-21 22:29:43.04      PERLND P194   DELT=60
-2017-04-21 22:29:43.16      PERLND P195   DELT=60
-2017-04-21 22:29:43.29      IMPLND I191   DELT=60
-2017-04-21 22:29:43.35      PERLND P201   DELT=60
-2017-04-21 22:29:43.47      PERLND P202   DELT=60
-2017-04-21 22:29:43.61      PERLND P203   DELT=60
-2017-04-21 22:29:43.74      PERLND P204   DELT=60
-2017-04-21 22:29:43.88      PERLND P205   DELT=60
-2017-04-21 22:29:44.00      PERLND P206   DELT=60
-2017-04-21 22:29:44.13      IMPLND I201   DELT=60
-2017-04-21 22:29:44.19      PERLND P211   DELT=60
-2017-04-21 22:29:44.32      PERLND P212   DELT=60
-2017-04-21 22:29:44.44      PERLND P213   DELT=60
-2017-04-21 22:29:44.57      PERLND P214   DELT=60
-2017-04-21 22:29:44.69      PERLND P215   DELT=60
-2017-04-21 22:29:44.83      PERLND P216   DELT=60
-2017-04-21 22:29:44.97      IMPLND I211   DELT=60
-2017-04-21 22:29:45.02      PERLND P221   DELT=60
-2017-04-21 22:29:45.16      PERLND P222   DELT=60
-2017-04-21 22:29:45.27      PERLND P224   DELT=60
-2017-04-21 22:29:45.40      PERLND P225   DELT=60
-2017-04-21 22:29:45.52      PERLND P226   DELT=60
-2017-04-21 22:29:45.66      IMPLND I221   DELT=60
-2017-04-21 22:29:45.71      PERLND P231   DELT=60
-2017-04-21 22:29:45.83      PERLND P232   DELT=60
-2017-04-21 22:29:45.96      PERLND P234   DELT=60
-2017-04-21 22:29:46.08      PERLND P235   DELT=60
-2017-04-21 22:29:46.22      IMPLND I231   DELT=60
-2017-04-21 22:29:46.28      PERLND P241   DELT=60
-2017-04-21 22:29:46.40      PERLND P242   DELT=60
-2017-04-21 22:29:46.53      PERLND P243   DELT=60
-2017-04-21 22:29:46.64      PERLND P244   DELT=60
-2017-04-21 22:29:46.76      PERLND P245   DELT=60
-2017-04-21 22:29:46.87      IMPLND I241   DELT=60
-2017-04-21 22:29:46.92      PERLND P251   DELT=60
-2017-04-21 22:29:47.04      PERLND P252   DELT=60
-2017-04-21 22:29:47.17      PERLND P253   DELT=60
-2017-04-21 22:29:47.28      PERLND P254   DELT=60
-2017-04-21 22:29:47.40      PERLND P255   DELT=60
-2017-04-21 22:29:47.53      PERLND P256   DELT=60
-2017-04-21 22:29:47.67      IMPLND I251   DELT=60
-2017-04-21 22:29:47.72      PERLND P261   DELT=60
-2017-04-21 22:29:47.86      PERLND P266   DELT=60
-2017-04-21 22:29:47.98      PERLND P271   DELT=60
-2017-04-21 22:29:48.11      PERLND P272   DELT=60
-2017-04-21 22:29:48.23      PERLND P275   DELT=60
-2017-04-21 22:29:48.36      PERLND P276   DELT=60
-2017-04-21 22:29:48.48      IMPLND I271   DELT=60
-2017-04-21 22:29:48.53      PERLND P281   DELT=60
-2017-04-21 22:29:48.67      PERLND P282   DELT=60
-2017-04-21 22:29:48.78      PERLND P283   DELT=60
-2017-04-21 22:29:48.89      PERLND P285   DELT=60
-2017-04-21 22:29:49.01      PERLND P286   DELT=60
-2017-04-21 22:29:49.15      IMPLND I281   DELT=60
-2017-04-21 22:29:49.20      PERLND P291   DELT=60
-2017-04-21 22:29:49.32      PERLND P292   DELT=60
-2017-04-21 22:29:49.43      PERLND P293   DELT=60
-2017-04-21 22:29:49.54      PERLND P294   DELT=60
-2017-04-21 22:29:49.68      PERLND P295   DELT=60
-2017-04-21 22:29:49.79      PERLND P296   DELT=60
-2017-04-21 22:29:49.92      IMPLND I291   DELT=60
-2017-04-21 22:29:49.96      PERLND P301   DELT=60
-2017-04-21 22:29:50.09      PERLND P302   DELT=60
-2017-04-21 22:29:50.20      PERLND P303   DELT=60
-2017-04-21 22:29:50.32      PERLND P304   DELT=60
-2017-04-21 22:29:50.45      PERLND P305   DELT=60
-2017-04-21 22:29:50.56      PERLND P306   DELT=60
-2017-04-21 22:29:50.68      IMPLND I301   DELT=60
-2017-04-21 22:29:50.73      RCHRES R201   DELT=60
-2017-04-21 22:29:50.88      RCHRES R190   DELT=60
-2017-04-21 22:29:50.99      RCHRES R202   DELT=60
-2017-04-21 22:29:51.13      RCHRES R191   DELT=60
-2017-04-21 22:29:51.28      RCHRES R203   DELT=60
-2017-04-21 22:29:51.45      RCHRES R211   DELT=60
-2017-04-21 22:29:51.54      RCHRES R212   DELT=60
-2017-04-21 22:29:51.70      RCHRES R192   DELT=60
-2017-04-21 22:29:51.82      RCHRES R204   DELT=60
-2017-04-21 22:29:51.99      RCHRES R221   DELT=60
-2017-04-21 22:29:52.13      RCHRES R222   DELT=60
-2017-04-21 22:29:52.24      RCHRES R223   DELT=60
-2017-04-21 22:29:52.40      RCHRES R193   DELT=60
-2017-04-21 22:29:52.51      RCHRES R205   DELT=60
-2017-04-21 22:29:52.68      RCHRES R225   DELT=60
-2017-04-21 22:29:52.84      RCHRES R194   DELT=60
-2017-04-21 22:29:52.95      RCHRES R206   DELT=60
-2017-04-21 22:29:53.12      RCHRES R227   DELT=60
-2017-04-21 22:29:53.25      RCHRES R207   DELT=60
-2017-04-21 22:29:53.41      RCHRES R231   DELT=60
-2017-04-21 22:29:53.54      RCHRES R232   DELT=60
-2017-04-21 22:29:53.65      RCHRES R233   DELT=60
-2017-04-21 22:29:53.78      RCHRES R241   DELT=60
-2017-04-21 22:29:53.92      RCHRES R242   DELT=60
-2017-04-21 22:29:54.03      RCHRES R243   DELT=60
-2017-04-21 22:29:54.15      RCHRES R301   DELT=60
-2017-04-21 22:29:54.36      RCHRES R311   DELT=60
-2017-04-21 22:29:54.45      RCHRES R302   DELT=60
-2017-04-21 22:29:54.64      RCHRES R303   DELT=60
-2017-04-21 22:29:54.81      RCHRES R401   DELT=60
-2017-04-21 22:29:54.95      RCHRES R411   DELT=60
-2017-04-21 22:29:55.09      RCHRES R402   DELT=60
-2017-04-21 22:29:55.23      RCHRES R421   DELT=60
-2017-04-21 22:29:55.37      RCHRES R422   DELT=60
-2017-04-21 22:29:55.48      RCHRES R423   DELT=60
-2017-04-21 22:29:55.62      RCHRES R403   DELT=60
-2017-04-21 22:29:55.79      RCHRES R431   DELT=60
-2017-04-21 22:29:55.93      RCHRES R404   DELT=60
-2017-04-21 22:29:56.08      RCHRES R441   DELT=60
-2017-04-21 22:29:56.22      RCHRES R443   DELT=60
-2017-04-21 22:29:56.33      RCHRES R442   DELT=60
-2017-04-21 22:29:56.49      RCHRES R405   DELT=60
-2017-04-21 22:29:56.64      RCHRES R406   DELT=60
-2017-04-21 22:29:56.80      RCHRES R407   DELT=60
-2017-04-21 22:29:56.97      RCHRES R408   DELT=60
-2017-04-21 22:29:57.15      RCHRES R195   DELT=60
-2017-04-21 22:29:57.26      RCHRES R304   DELT=60
-2017-04-21 22:29:57.45      RCHRES R305   DELT=60
-2017-04-21 22:29:57.62      RCHRES R306   DELT=60
-2017-04-21 22:29:57.77      RCHRES R500   DELT=60
-2017-04-21 22:29:57.90      RCHRES R501   DELT=60
-2017-04-21 22:29:58.07      RCHRES R513   DELT=60
-2017-04-21 22:29:58.20      RCHRES R514   DELT=60
-2017-04-21 22:29:58.31      RCHRES R502   DELT=60
-2017-04-21 22:29:58.59      RCHRES R510   DELT=60
-2017-04-21 22:29:58.74      RCHRES R511   DELT=60
-2017-04-21 22:29:58.96      RCHRES R512   DELT=60
-2017-04-21 22:29:59.11      RCHRES R503   DELT=60
-2017-04-21 22:29:59.39      RCHRES R523   DELT=60
-2017-04-21 22:29:59.52      RCHRES R524   DELT=60
-2017-04-21 22:29:59.63      RCHRES R525   DELT=60
-2017-04-21 22:29:59.75      RCHRES R526   DELT=60
-2017-04-21 22:29:59.86      RCHRES R521   DELT=60
-2017-04-21 22:30:00.04      RCHRES R522   DELT=60
-2017-04-21 22:30:00.21      RCHRES R531   DELT=60
-2017-04-21 22:30:00.36      RCHRES R504   DELT=60
-2017-04-21 22:30:00.49      RCHRES R505   DELT=60
-2017-04-21 22:30:00.61      RCHRES R506   DELT=60
-2017-04-21 22:30:00.75      RCHRES R541   DELT=60
-2017-04-21 22:30:00.86      RCHRES R542   DELT=60
-2017-04-21 22:30:01.00      RCHRES R307   DELT=60
-2017-04-21 22:30:01.14   Run completed
-2017-04-21 22:30:02.01   Run Started for file calleg.h5
-2017-04-21 22:30:02.03     Start 1993-10-01 00:00    Stop 2002-09-30 23:59
-2017-04-21 22:30:02.37   Finished setup
-2017-04-21 22:30:02.39      PERLND P011   DELT=60
-2017-04-21 22:30:02.51      PERLND P012   DELT=60
-2017-04-21 22:30:02.64      PERLND P013   DELT=60
-2017-04-21 22:30:02.75      PERLND P014   DELT=60
-2017-04-21 22:30:02.87      PERLND P015   DELT=60
-2017-04-21 22:30:02.98      IMPLND I011   DELT=60
-2017-04-21 22:30:03.03      PERLND P021   DELT=60
-2017-04-21 22:30:03.15      PERLND P022   DELT=60
-2017-04-21 22:30:03.26      PERLND P023   DELT=60
-2017-04-21 22:30:03.39      PERLND P024   DELT=60
-2017-04-21 22:30:03.50      PERLND P025   DELT=60
-2017-04-21 22:30:03.62      IMPLND I021   DELT=60
-2017-04-21 22:30:03.67      RCHRES R001   DELT=60
-2017-04-21 22:30:03.94      PERLND P031   DELT=60
-2017-04-21 22:30:04.08      PERLND P041   DELT=60
-2017-04-21 22:30:04.19      PERLND P042   DELT=60
-2017-04-21 22:30:04.31      PERLND P043   DELT=60
-2017-04-21 22:30:04.42      IMPLND I041   DELT=60
-2017-04-21 22:30:04.47      RCHRES R021   DELT=60
-2017-04-21 22:30:04.54      RCHRES R022   DELT=60
-2017-04-21 22:30:04.64      RCHRES R023   DELT=60
-2017-04-21 22:30:04.73      PERLND P051   DELT=60
-2017-04-21 22:30:04.86      PERLND P052   DELT=60
-2017-04-21 22:30:04.97      PERLND P053   DELT=60
-2017-04-21 22:30:05.09      PERLND P054   DELT=60
-2017-04-21 22:30:05.20      PERLND P055   DELT=60
-2017-04-21 22:30:05.33      IMPLND I051   DELT=60
-2017-04-21 22:30:05.37      RCHRES R011   DELT=60
-2017-04-21 22:30:05.67      RCHRES R024   DELT=60
-2017-04-21 22:30:05.78      PERLND P061   DELT=60
-2017-04-21 22:30:05.92      PERLND P062   DELT=60
-2017-04-21 22:30:06.03      IMPLND I061   DELT=60
-2017-04-21 22:30:06.08      PERLND P071   DELT=60
-2017-04-21 22:30:06.19      PERLND P072   DELT=60
-2017-04-21 22:30:06.31      PERLND P073   DELT=60
-2017-04-21 22:30:06.44      PERLND P074   DELT=60
-2017-04-21 22:30:06.55      PERLND P075   DELT=60
-2017-04-21 22:30:06.65      IMPLND I071   DELT=60
-2017-04-21 22:30:06.70      RCHRES R031   DELT=60
-2017-04-21 22:30:06.89      RCHRES R071   DELT=60
-2017-04-21 22:30:07.00      PERLND P081   DELT=60
-2017-04-21 22:30:07.12      PERLND P082   DELT=60
-2017-04-21 22:30:07.23      PERLND P083   DELT=60
-2017-04-21 22:30:07.34      PERLND P084   DELT=60
-2017-04-21 22:30:07.45      PERLND P085   DELT=60
-2017-04-21 22:30:07.58      IMPLND I081   DELT=60
-2017-04-21 22:30:07.61      PERLND P091   DELT=60
-2017-04-21 22:30:07.73      RCHRES R043   DELT=60
-2017-04-21 22:30:07.83      PERLND P101   DELT=60
-2017-04-21 22:30:07.95         Message count 30   Message PWATER: Reduced AGWO value to available
-2017-04-21 22:30:07.97         Message count 20285   Message PWATER: Reset AGWS to zero
-2017-04-21 22:30:07.97      PERLND P102   DELT=60
-2017-04-21 22:30:08.09      IMPLND I101   DELT=60
-2017-04-21 22:30:08.14      RCHRES R041   DELT=60
-2017-04-21 22:30:08.22      RCHRES R042   DELT=60
-2017-04-21 22:30:08.33      RCHRES R044   DELT=60
-2017-04-21 22:30:08.44      PERLND P111   DELT=60
-2017-04-21 22:30:08.56      PERLND P112   DELT=60
-2017-04-21 22:30:08.67      PERLND P113   DELT=60
-2017-04-21 22:30:08.78      IMPLND I111   DELT=60
-2017-04-21 22:30:08.83      RCHRES R045   DELT=60
-2017-04-21 22:30:08.95      PERLND P121   DELT=60
-2017-04-21 22:30:09.08      PERLND P122   DELT=60
-2017-04-21 22:30:09.19      PERLND P123   DELT=60
-2017-04-21 22:30:09.30      PERLND P124   DELT=60
-2017-04-21 22:30:09.43      PERLND P125   DELT=60
-2017-04-21 22:30:09.54      IMPLND I121   DELT=60
-2017-04-21 22:30:09.59      RCHRES R002   DELT=60
-2017-04-21 22:30:10.29      RCHRES R025   DELT=60
-2017-04-21 22:30:10.57      RCHRES R003   DELT=60
-2017-04-21 22:30:10.93      RCHRES R004   DELT=60
-2017-04-21 22:30:11.20      RCHRES R904   DELT=60
-2017-04-21 22:30:11.29      PERLND P131   DELT=60
-2017-04-21 22:30:11.43      PERLND P132   DELT=60
-2017-04-21 22:30:11.54      PERLND P133   DELT=60
-2017-04-21 22:30:11.66      PERLND P134   DELT=60
-2017-04-21 22:30:11.77      PERLND P135   DELT=60
-2017-04-21 22:30:11.90      IMPLND I131   DELT=60
-2017-04-21 22:30:11.95      RCHRES R061   DELT=60
-2017-04-21 22:30:12.04      RCHRES R062   DELT=60
-2017-04-21 22:30:12.15      RCHRES R063   DELT=60
-2017-04-21 22:30:12.27      RCHRES R064   DELT=60
-2017-04-21 22:30:12.41      RCHRES R964   DELT=60
-2017-04-21 22:30:12.54      RCHRES R091   DELT=60
-2017-04-21 22:30:12.68      PERLND P141   DELT=60
-2017-04-21 22:30:12.82      PERLND P142   DELT=60
-2017-04-21 22:30:12.93      PERLND P143   DELT=60
-2017-04-21 22:30:13.04      PERLND P144   DELT=60
-2017-04-21 22:30:13.18      PERLND P145   DELT=60
-2017-04-21 22:30:13.29      IMPLND I141   DELT=60
-2017-04-21 22:30:13.33      RCHRES R005   DELT=60
-2017-04-21 22:30:14.33      RCHRES R046   DELT=60
-2017-04-21 22:30:14.52      RCHRES R065   DELT=60
-2017-04-21 22:30:14.79      RCHRES R072   DELT=60
-2017-04-21 22:30:14.99      PERLND P151   DELT=60
-2017-04-21 22:30:15.13      PERLND P152   DELT=60
-2017-04-21 22:30:15.24      IMPLND I151   DELT=60
-2017-04-21 22:30:15.29      RCHRES R051   DELT=60
-2017-04-21 22:30:15.39      RCHRES R952   DELT=60
-2017-04-21 22:30:15.50      RCHRES R052   DELT=60
-2017-04-21 22:30:15.68      RCHRES R006   DELT=60
-2017-04-21 22:30:15.83      RCHRES R081   DELT=60
-2017-04-21 22:30:15.96      PERLND P161   DELT=60
-2017-04-21 22:30:16.08      PERLND P162   DELT=60
-2017-04-21 22:30:16.21      PERLND P163   DELT=60
-2017-04-21 22:30:16.33      PERLND P164   DELT=60
-2017-04-21 22:30:16.44      PERLND P165   DELT=60
-2017-04-21 22:30:16.57      IMPLND I161   DELT=60
-2017-04-21 22:30:16.61      RCHRES R101   DELT=60
-2017-04-21 22:30:16.74      RCHRES R102   DELT=60
-2017-04-21 22:30:16.83      RCHRES R103   DELT=60
-2017-04-21 22:30:16.94      RCHRES R104   DELT=60
-2017-04-21 22:30:17.04      RCHRES R105   DELT=60
-2017-04-21 22:30:17.13      PERLND P171   DELT=60
-2017-04-21 22:30:17.27      PERLND P172   DELT=60
-2017-04-21 22:30:17.39      PERLND P173   DELT=60
-2017-04-21 22:30:17.52      PERLND P174   DELT=60
-2017-04-21 22:30:17.63      PERLND P175   DELT=60
-2017-04-21 22:30:17.75      IMPLND I171   DELT=60
-2017-04-21 22:30:17.80      PERLND P181   DELT=60
-2017-04-21 22:30:17.91      PERLND P182   DELT=60
-2017-04-21 22:30:18.03      PERLND P183   DELT=60
-2017-04-21 22:30:18.16      PERLND P184   DELT=60
-2017-04-21 22:30:18.27      PERLND P185   DELT=60
-2017-04-21 22:30:18.39         Message count 1533   Message PWATER: Reduced AGWO value to available
-2017-04-21 22:30:18.39         Message count 71712   Message PWATER: Reset AGWS to zero
-2017-04-21 22:30:18.39      IMPLND I181   DELT=60
-2017-04-21 22:30:18.44      RCHRES R107   DELT=60
-2017-04-21 22:30:18.64      RCHRES R106   DELT=60
-2017-04-21 22:30:18.80      RCHRES R108   DELT=60
-2017-04-21 22:30:18.91      RCHRES R007   DELT=60
-2017-04-21 22:30:19.08      RCHRES R082   DELT=60
-2017-04-21 22:30:19.35      RCHRES R092   DELT=60
-2017-04-21 22:30:19.59      RCHRES R008   DELT=60
-2017-04-21 22:30:19.76      RCHRES R009   DELT=60
-2017-04-21 22:30:19.88      RCHRES R109   DELT=60
-2017-04-21 22:30:20.09      RCHRES R010   DELT=60
-2017-04-21 22:30:20.30      PERLND P191   DELT=60
-2017-04-21 22:30:20.43      PERLND P192   DELT=60
-2017-04-21 22:30:20.56      PERLND P193   DELT=60
-2017-04-21 22:30:20.70      PERLND P194   DELT=60
-2017-04-21 22:30:20.82      PERLND P195   DELT=60
-2017-04-21 22:30:20.95      IMPLND I191   DELT=60
-2017-04-21 22:30:20.99      PERLND P201   DELT=60
-2017-04-21 22:30:21.13      PERLND P202   DELT=60
-2017-04-21 22:30:21.25      PERLND P203   DELT=60
-2017-04-21 22:30:21.38      PERLND P204   DELT=60
-2017-04-21 22:30:21.50      PERLND P205   DELT=60
-2017-04-21 22:30:21.63      PERLND P206   DELT=60
-2017-04-21 22:30:21.77      IMPLND I201   DELT=60
-2017-04-21 22:30:21.82      PERLND P211   DELT=60
-2017-04-21 22:30:21.94      PERLND P212   DELT=60
-2017-04-21 22:30:22.07      PERLND P213   DELT=60
-2017-04-21 22:30:22.19      PERLND P214   DELT=60
-2017-04-21 22:30:22.32      PERLND P215   DELT=60
-2017-04-21 22:30:22.44      PERLND P216   DELT=60
-2017-04-21 22:30:22.58      IMPLND I211   DELT=60
-2017-04-21 22:30:22.63      PERLND P221   DELT=60
-2017-04-21 22:30:22.77      PERLND P222   DELT=60
-2017-04-21 22:30:22.90      PERLND P224   DELT=60
-2017-04-21 22:30:23.02      PERLND P225   DELT=60
-2017-04-21 22:30:23.15      PERLND P226   DELT=60
-2017-04-21 22:30:23.29      IMPLND I221   DELT=60
-2017-04-21 22:30:23.33      PERLND P231   DELT=60
-2017-04-21 22:30:23.46      PERLND P232   DELT=60
-2017-04-21 22:30:23.57      PERLND P234   DELT=60
-2017-04-21 22:30:23.71      PERLND P235   DELT=60
-2017-04-21 22:30:23.83      IMPLND I231   DELT=60
-2017-04-21 22:30:23.88      PERLND P241   DELT=60
-2017-04-21 22:30:24.00      PERLND P242   DELT=60
-2017-04-21 22:30:24.11      PERLND P243   DELT=60
-2017-04-21 22:30:24.22      PERLND P244   DELT=60
-2017-04-21 22:30:24.35      PERLND P245   DELT=60
-2017-04-21 22:30:24.47      IMPLND I241   DELT=60
-2017-04-21 22:30:24.52      PERLND P251   DELT=60
-2017-04-21 22:30:24.65      PERLND P252   DELT=60
-2017-04-21 22:30:24.77      PERLND P253   DELT=60
-2017-04-21 22:30:24.90      PERLND P254   DELT=60
-2017-04-21 22:30:25.00      PERLND P255   DELT=60
-2017-04-21 22:30:25.12      PERLND P256   DELT=60
-2017-04-21 22:30:25.26      IMPLND I251   DELT=60
-2017-04-21 22:30:25.31      PERLND P261   DELT=60
-2017-04-21 22:30:25.44      PERLND P266   DELT=60
-2017-04-21 22:30:25.58      PERLND P271   DELT=60
-2017-04-21 22:30:25.72      PERLND P272   DELT=60
-2017-04-21 22:30:25.84      PERLND P275   DELT=60
-2017-04-21 22:30:25.95      PERLND P276   DELT=60
-2017-04-21 22:30:26.09      IMPLND I271   DELT=60
-2017-04-21 22:30:26.12      PERLND P281   DELT=60
-2017-04-21 22:30:26.26      PERLND P282   DELT=60
-2017-04-21 22:30:26.37      PERLND P283   DELT=60
-2017-04-21 22:30:26.50      PERLND P285   DELT=60
-2017-04-21 22:30:26.61      PERLND P286   DELT=60
-2017-04-21 22:30:26.76      IMPLND I281   DELT=60
-2017-04-21 22:30:26.80      PERLND P291   DELT=60
-2017-04-21 22:30:26.92      PERLND P292   DELT=60
-2017-04-21 22:30:27.05      PERLND P293   DELT=60
-2017-04-21 22:30:27.17      PERLND P294   DELT=60
-2017-04-21 22:30:27.30      PERLND P295   DELT=60
-2017-04-21 22:30:27.42      PERLND P296   DELT=60
-2017-04-21 22:30:27.55      IMPLND I291   DELT=60
-2017-04-21 22:30:27.59      PERLND P301   DELT=60
-2017-04-21 22:30:27.72      PERLND P302   DELT=60
-2017-04-21 22:30:27.84      PERLND P303   DELT=60
-2017-04-21 22:30:27.95      PERLND P304   DELT=60
-2017-04-21 22:30:28.08      PERLND P305   DELT=60
-2017-04-21 22:30:28.19      PERLND P306   DELT=60
-2017-04-21 22:30:28.33      IMPLND I301   DELT=60
-2017-04-21 22:30:28.36      RCHRES R201   DELT=60
-2017-04-21 22:30:28.52      RCHRES R190   DELT=60
-2017-04-21 22:30:28.64      RCHRES R202   DELT=60
-2017-04-21 22:30:28.78      RCHRES R191   DELT=60
-2017-04-21 22:30:28.92      RCHRES R203   DELT=60
-2017-04-21 22:30:29.08      RCHRES R211   DELT=60
-2017-04-21 22:30:29.18      RCHRES R212   DELT=60
-2017-04-21 22:30:29.34      RCHRES R192   DELT=60
-2017-04-21 22:30:29.46      RCHRES R204   DELT=60
-2017-04-21 22:30:29.63      RCHRES R221   DELT=60
-2017-04-21 22:30:29.81      RCHRES R222   DELT=60
-2017-04-21 22:30:29.90      RCHRES R223   DELT=60
-2017-04-21 22:30:30.06      RCHRES R193   DELT=60
-2017-04-21 22:30:30.18      RCHRES R205   DELT=60
-2017-04-21 22:30:30.35      RCHRES R225   DELT=60
-2017-04-21 22:30:30.49      RCHRES R194   DELT=60
-2017-04-21 22:30:30.59      RCHRES R206   DELT=60
-2017-04-21 22:30:30.74      RCHRES R227   DELT=60
-2017-04-21 22:30:30.90      RCHRES R207   DELT=60
-2017-04-21 22:30:31.04      RCHRES R231   DELT=60
-2017-04-21 22:30:31.18      RCHRES R232   DELT=60
-2017-04-21 22:30:31.27      RCHRES R233   DELT=60
-2017-04-21 22:30:31.40      RCHRES R241   DELT=60
-2017-04-21 22:30:31.56      RCHRES R242   DELT=60
-2017-04-21 22:30:31.65      RCHRES R243   DELT=60
-2017-04-21 22:30:31.77      RCHRES R301   DELT=60
-2017-04-21 22:30:31.95      RCHRES R311   DELT=60
-2017-04-21 22:30:32.04      RCHRES R302   DELT=60
-2017-04-21 22:30:32.21      RCHRES R303   DELT=60
-2017-04-21 22:30:32.37      RCHRES R401   DELT=60
-2017-04-21 22:30:32.53      RCHRES R411   DELT=60
-2017-04-21 22:30:32.65      RCHRES R402   DELT=60
-2017-04-21 22:30:32.79      RCHRES R421   DELT=60
-2017-04-21 22:30:32.93      RCHRES R422   DELT=60
-2017-04-21 22:30:33.03      RCHRES R423   DELT=60
-2017-04-21 22:30:33.17      RCHRES R403   DELT=60
-2017-04-21 22:30:33.32      RCHRES R431   DELT=60
-2017-04-21 22:30:33.46      RCHRES R404   DELT=60
-2017-04-21 22:30:33.60      RCHRES R441   DELT=60
-2017-04-21 22:30:33.74      RCHRES R443   DELT=60
-2017-04-21 22:30:33.85      RCHRES R442   DELT=60
-2017-04-21 22:30:34.01      RCHRES R405   DELT=60
-2017-04-21 22:30:34.15      RCHRES R406   DELT=60
-2017-04-21 22:30:34.32      RCHRES R407   DELT=60
-2017-04-21 22:30:34.49      RCHRES R408   DELT=60
-2017-04-21 22:30:34.65      RCHRES R195   DELT=60
-2017-04-21 22:30:34.74      RCHRES R304   DELT=60
-2017-04-21 22:30:34.92      RCHRES R305   DELT=60
-2017-04-21 22:30:35.09      RCHRES R306   DELT=60
-2017-04-21 22:30:35.23      RCHRES R500   DELT=60
-2017-04-21 22:30:35.34      RCHRES R501   DELT=60
-2017-04-21 22:30:35.51      RCHRES R513   DELT=60
-2017-04-21 22:30:35.63      RCHRES R514   DELT=60
-2017-04-21 22:30:35.74      RCHRES R502   DELT=60
-2017-04-21 22:30:36.01      RCHRES R510   DELT=60
-2017-04-21 22:30:36.15      RCHRES R511   DELT=60
-2017-04-21 22:30:36.37      RCHRES R512   DELT=60
-2017-04-21 22:30:36.53      RCHRES R503   DELT=60
-2017-04-21 22:30:36.81      RCHRES R523   DELT=60
-2017-04-21 22:30:36.93      RCHRES R524   DELT=60
-2017-04-21 22:30:37.04      RCHRES R525   DELT=60
-2017-04-21 22:30:37.15      RCHRES R526   DELT=60
-2017-04-21 22:30:37.24      RCHRES R521   DELT=60
-2017-04-21 22:30:37.41      RCHRES R522   DELT=60
-2017-04-21 22:30:37.58      RCHRES R531   DELT=60
-2017-04-21 22:30:37.74      RCHRES R504   DELT=60
-2017-04-21 22:30:37.86      RCHRES R505   DELT=60
-2017-04-21 22:30:37.99      RCHRES R506   DELT=60
-2017-04-21 22:30:38.11      RCHRES R541   DELT=60
-2017-04-21 22:30:38.24      RCHRES R542   DELT=60
-2017-04-21 22:30:38.38      RCHRES R307   DELT=60
-2017-04-21 22:30:38.52   Run completed
-1 loop, best of 3: 36.5 s per loop
-
-
-
- -
-
- -
Development note (SAVEALL = FALSE) - -SAVEALL = FALSE -2017-04-21 22:27:24.17 Run completed -1 loop, best of 3: 31.4 s per loop -Ratio of HSP2/HSPF 31.4/24.4 = 1.3 - -SAVEALL = TRUE -2017-04-21 22:30:38.52 Run completed -1 loop, best of 3: 36.5 s per loop -Ratio of HSP2/HSPF 38.1/24.4 = 1.5 -
-
- - - - - - diff --git a/tests/Calleg/notebooks-py2/Build_and_Run.ipynb b/tests/Calleg/notebooks-py2/Build_and_Run.ipynb deleted file mode 100755 index 6bfb6fc7..00000000 --- a/tests/Calleg/notebooks-py2/Build_and_Run.ipynb +++ /dev/null @@ -1,524 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "# HSP2 BUILD and RUN SIMULATION\n", - "\n", - "Place this Jupyter Notebook in a directory with one UCI and one or more WDM files." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "## Required Python Imports" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.execute_input": "2024-04-26T01:48:10.243437Z", - "iopub.status.busy": "2024-04-26T01:48:10.243107Z", - "iopub.status.idle": "2024-04-26T01:48:10.246213Z", - "shell.execute_reply": "2024-04-26T01:48:10.245737Z", - "shell.execute_reply.started": "2024-04-26T01:48:10.243419Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "from glob import glob\n", - "\n", - "import HSP2\n", - "import HSP2tools\n", - "from HSP2.utilities import versions" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.execute_input": "2024-04-26T01:48:11.182429Z", - "iopub.status.busy": "2024-04-26T01:48:11.181849Z", - "iopub.status.idle": "2024-04-26T01:48:11.189802Z", - "shell.execute_reply": "2024-04-26T01:48:11.189330Z", - "shell.execute_reply.started": "2024-04-26T01:48:11.182411Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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version
Python3.10.14 | packaged by conda-forge | (main, Mar...
HSP20.11.0a1
numpy1.26.4
numba0.59.1
pandas2.2.2
osLinux-5.15.0-91-generic-x86_64-with-glibc2.35
processorx86_64
Date/Time2024-04-25 21:48:11
\n", - "
" - ], - "text/plain": [ - " version\n", - "Python 3.10.14 | packaged by conda-forge | (main, Mar...\n", - "HSP2 0.11.0a1\n", - "numpy 1.26.4\n", - "numba 0.59.1\n", - "pandas 2.2.2\n", - "os Linux-5.15.0-91-generic-x86_64-with-glibc2.35\n", - "processor x86_64\n", - "Date/Time 2024-04-25 21:48:11" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "versions()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "## BUILD HDF5 FILE From UCI and WDM files" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Get the name of the UCI file." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.execute_input": "2024-04-26T01:48:16.797185Z", - "iopub.status.busy": "2024-04-26T01:48:16.796938Z", - "iopub.status.idle": "2024-04-26T01:48:16.809263Z", - "shell.execute_reply": "2024-04-26T01:48:16.808709Z", - "shell.execute_reply.started": "2024-04-26T01:48:16.797169Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [ - { - "ename": "IndexError", - "evalue": "list index out of range", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[5], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m uciname \u001b[38;5;241m=\u001b[39m \u001b[43mglob\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m*.uci\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[1;32m 2\u001b[0m uciname\n", - "\u001b[0;31mIndexError\u001b[0m: list index out of range" - ] - } - ], - "source": [ - "uciname = glob(\"*.uci\")[0]\n", - "uciname" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Create HDF5 filename from the leading part of the UCI filename." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T01:45:40.180497Z", - "iopub.status.idle": "2024-04-26T01:45:40.180657Z", - "shell.execute_reply": "2024-04-26T01:45:40.180580Z", - "shell.execute_reply.started": "2024-04-26T01:45:40.180573Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "HDFname = uciname.split(\".\")[0] + \".h5\"\n", - "HDFname" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T01:45:40.181277Z", - "iopub.status.idle": "2024-04-26T01:45:40.181534Z", - "shell.execute_reply": "2024-04-26T01:45:40.181446Z", - "shell.execute_reply.started": "2024-04-26T01:45:40.181437Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "!del {HDFname}" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Create the HDF5 file filled with the UCI data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T01:45:40.182018Z", - "iopub.status.idle": "2024-04-26T01:45:40.182191Z", - "shell.execute_reply": "2024-04-26T01:45:40.182108Z", - "shell.execute_reply.started": "2024-04-26T01:45:40.182100Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "HSP2tools.readUCI(uciname, HDFname)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T01:45:40.182597Z", - "iopub.status.idle": "2024-04-26T01:45:40.182739Z", - "shell.execute_reply": "2024-04-26T01:45:40.182681Z", - "shell.execute_reply.started": "2024-04-26T01:45:40.182675Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "HSP2tools.cleanup(HDFname)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Add the timeseries data to the HDF5 file." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T01:45:40.183177Z", - "iopub.status.idle": "2024-04-26T01:45:40.183294Z", - "shell.execute_reply": "2024-04-26T01:45:40.183241Z", - "shell.execute_reply.started": "2024-04-26T01:45:40.183235Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "wdmnames = glob(\"*.wdm\")\n", - "wdmnames" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T01:45:40.183569Z", - "iopub.status.idle": "2024-04-26T01:45:40.183678Z", - "shell.execute_reply": "2024-04-26T01:45:40.183628Z", - "shell.execute_reply.started": "2024-04-26T01:45:40.183623Z" - }, - "jupyter": { - "outputs_hidden": false - }, - "scrolled": true - }, - "outputs": [], - "source": [ - "for name in wdmnames:\n", - " HSP2tools.ReadWDM(name, HDFname)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T01:45:40.184025Z", - "iopub.status.idle": "2024-04-26T01:45:40.184126Z", - "shell.execute_reply": "2024-04-26T01:45:40.184078Z", - "shell.execute_reply.started": "2024-04-26T01:45:40.184073Z" - } - }, - "outputs": [], - "source": [ - "!rename {HDFname} temp.h5\n", - "!ptrepack temp.h5 {HDFname}\n", - "!del temp.h5" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "## RUN simulation" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Get HDF5 filename (in case you didn't need to run the above)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T01:45:40.184543Z", - "iopub.status.idle": "2024-04-26T01:45:40.184642Z", - "shell.execute_reply": "2024-04-26T01:45:40.184595Z", - "shell.execute_reply.started": "2024-04-26T01:45:40.184590Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "hdfname = glob(\"*.h5\")[0]\n", - "hdfname" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T01:45:40.184883Z", - "iopub.status.idle": "2024-04-26T01:45:40.184981Z", - "shell.execute_reply": "2024-04-26T01:45:40.184934Z", - "shell.execute_reply.started": "2024-04-26T01:45:40.184929Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "HSP2.run(hdfname, saveall=True)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T01:45:40.185177Z", - "iopub.status.idle": "2024-04-26T01:45:40.185282Z", - "shell.execute_reply": "2024-04-26T01:45:40.185234Z", - "shell.execute_reply.started": "2024-04-26T01:45:40.185229Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "%timeit HSP2.run(hdfname, saveall=True)" - ] - }, - { - "cell_type": "raw", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Development note (SAVEALL = FALSE)\n", - "\n", - "SAVEALL = FALSE\n", - "2017-04-21 22:27:24.17 Run completed\n", - "1 loop, best of 3: 31.4 s per loop\n", - "Ratio of HSP2/HSPF 31.4/24.4 = 1.3\n", - "\n", - "SAVEALL = TRUE\n", - "2017-04-21 22:30:38.52 Run completed\n", - "1 loop, best of 3: 36.5 s per loop\n", - "Ratio of HSP2/HSPF 36.5/24.4 = 1.5" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/tests/Calleg/notebooks-py2/TESTcalleg.html b/tests/Calleg/notebooks-py2/TESTcalleg.html deleted file mode 100644 index 393f9e89..00000000 --- a/tests/Calleg/notebooks-py2/TESTcalleg.html +++ /dev/null @@ -1,37161 +0,0 @@ - - - -TESTcalleg - - - - - - - - - - - - - - - - - - - -
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-This Jupyter Notebook Copyright 2016 by RESPEC, INC. All rights reserved.

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$\textbf{HSP}^{\textbf{2}}\ \text{and}\ \textbf{HSP2}\ $ Copyright 2016 by RESPEC INC. and released under this License

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Calleg TEST NOTEBOOK for HSP$^2$ (WORST CASE COMPARISONS)

This Notebook will compare the results of running HSPF and HSP$^2$ for the basic hydrology (PWATER, IWATER, and HYDR) to confirm the proper calculations of HSP$^2$

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Calleg is a real watershed and has

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  • 27 IMPLND segments,
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  • 129 PERLND segments,
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  • 119 RCHRES segments,
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  • 9 years of simulation time with hourly time steps (78,888 timesteps)
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Required Python imports and setup

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In [1]:
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import numpy as np
-import pandas as pd
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-pd.options.display.max_rows    = 25
-pd.options.display.max_columns = 20
-pd.options.display.float_format = '{:.4f}'.format  # display 2 digits after the decimal point
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-import matplotlib.pyplot as plt
-%matplotlib inline
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-import hspfbintoolbox
-import HSP2
-import HSP2tools
-HSP2tools.versions()
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Out[1]:
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Version
HSP20.7.2
HSP2tools0.7.1
PYTHON2.7.11 | 64-bit | (default, Jun 11 2016, 11:33...
IPYTHON5.3.0
H5PY2.7.0
MATPLOTLIB2.0.0
NETWORKX1.11
NUMBA0.31.0
NUMPY1.11.3
PANDAS0.19.2
PYTABLES3.3.0
WDMTOOLBOX0.8.2 MOD RTH
osWindows-10-10.0.15063
processorIntel64 Family 6 Model 94 Stepping 3, GenuineI...
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Setup paths to the necessary datafiles

This assumes the calleg.uci and calleg.wdm files are located in the current working directory for this Notebook. This will create the binary output file, calleg.hbn, along with a number of other standard HSPF outputs.

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In [2]:
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wdmpath = 'calleg.wdm'
-ucipath = 'calleg.uci'
-hdfpathx = 'callegx.h5'
-hdfpath = 'calleg.h5'
-hbnpath = 'calleg.hbn'
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Run HSPF

Using the Basins 4.1 WinHspfLt executable to run calleg.uci.

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This assumes the calleg.uci and calleg.wdm files are located in the current working directory for this Notebook. This will create the binary output file, calleg.hbn, along with a number of other standard HSPF outputs.

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In [3]:
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!echo %date% - %time%
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-!C:\BASINS41\models\HSPF\bin\WinHspfLt.exe {ucipath}
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-!echo %date% - %time%
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Fri 04/14/2017 - 16:20:53.76
-Fri 04/14/2017 - 16:21:17.46
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For development, save the best time for reference:

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1 loop, best of 3: 24.4 s per loop -
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Now run HSP$^2$ on the calleg watershed

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HSP2.run(hdfpath)
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%timeit HSP2.run(hdfpath)
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Development note: - -SAVEALL = FALSE (new SAVE table for hot restart by default) -2017-04-16 09:05:26.10 Run completed -1 loop, best of 3: 32.3 s per loop -Ratio of HSP2/HSPF 32.3/24.4 = 1.3 - -SAVEALL = TRUE -2017-04-11 10:18:22.86 Run completed -1 loop, best of 3: 38.1 s per loop -Ratio of HSP2/HSPF 38.1/24.4 = 1.6 -
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Determine Available Calculated Results

Now use Tim Cera's hspfbintoolbox.py to determine the available timeseries created by HSPF and stored into the HBN binary file.

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Time interval codes: {5: 'yearly', 4: 'monthly', 3: 'daily', 2: 'bivl'}.

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No daily available, so use monthly (4) timeseries for analysis.

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In [3]:
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keys = hspfbintoolbox.catalog(hbnpath).keys()
-keys[:5]  # show only the first 5 as a check
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Out[3]:
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[(u'IMPLND', 51, u'IWATER', u'PET', 5),
- (u'PERLND', 72, u'PWATER', u'UZI', 5),
- (u'PERLND', 101, u'PWATER', u'BASET', 4),
- (u'PERLND', 242, u'PWATER', u'PERO', 4),
- (u'PERLND', 296, u'PWATER', u'SUPY', 5)]
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Automate checking IMPLNDs for SURO

Extract the keys (calculated above) for IMPLD + IWATER + SURO. For each key, compute several columns. The final column shows the percent difference of the sum of the SURO for the entire run between HSPF and HSP2.

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In [170]:
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segments = [str(key[1]) for key in keys if key[0]=='IMPLND' and key[2]=='IWATER' and key[3]=='SURO' and key[4]==4]
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-dfimplnd = pd.DataFrame()
-for seg in segments:  
-    path = 'IMPLND,' + seg + ',IWATER,SURO'
-    hspf = hspfbintoolbox.extract(hbnpath, 'monthly', path).values
-           
-    path = 'RESULTS/IMPLND' + '_I' + '{:0>3s}'.format(seg) + '/IWATER'
-    hsp2 = pd.read_hdf(hdfpath, path)['SURO'].resample('MS').sum().values
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-    #dfimplnd.at[seg, 'Max Diff'] =  (hspf - hsp2).max()
-    dfimplnd.at[seg, 'Sum of HSPF'] = hspf.sum()
-    dfimplnd.at[seg, 'Sum of HSP2'] = hsp2.sum()
-    dfimplnd.at[seg, '%diff of Sum'] = 100.0 * (hspf.sum() - hsp2.sum()) / hspf.sum()
-    dfimplnd.at[seg, 'abs(%diff of Sum)'] = 100.0 * abs(hspf.sum() - hsp2.sum()) / hspf.sum()
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-dfimplnd = dfimplnd.sort_values(by=['abs(%diff of Sum)'])
-dfimplnd
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Out[170]:
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- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Sum of HSPFSum of HSP2%diff of Sumabs(%diff of Sum)
291117.5699117.5699-0.00000.0000
281137.7904137.79040.00000.0000
101144.1288144.1288-0.00000.0000
21122.5966122.59660.00000.0000
51120.2708120.27080.00000.0000
81118.7938118.7938-0.00000.0000
41141.2890141.28900.00000.0000
271136.4228136.42280.00000.0000
251116.6337116.63370.00000.0000
201172.5608172.5608-0.00000.0000
191125.6937125.69370.00000.0000
221126.6460126.64600.00000.0000
...............
121126.2947126.29470.00000.0000
131126.2947126.29470.00000.0000
161131.2695131.26950.00000.0000
211125.3008125.3008-0.00000.0000
11131.6821131.68210.00000.0000
61133.6036133.60360.00000.0000
151133.6036133.60360.00000.0000
301119.8081119.8081-0.00000.0000
171115.9610115.96100.00000.0000
181115.9610115.96100.00000.0000
241120.2066120.20660.00000.0000
231135.5890135.58900.00000.0000
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27 rows × 4 columns

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Look at the statistics for the percent difference column

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In [171]:
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dfimplnd['%diff of Sum'].hist()
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Out[171]:
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<matplotlib.axes._subplots.AxesSubplot at 0x1b0466d8>
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dfimplnd['%diff of Sum'].describe()
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Out[172]:
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count   27.0000
-mean     0.0000
-std      0.0000
-min     -0.0000
-25%      0.0000
-50%      0.0000
-75%      0.0000
-max      0.0000
-Name: %diff of Sum, dtype: float64
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In [173]:
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ils = dfimplnd.index[-1]
-print 'WORST IMPLND SEGMENT IS', ils
-print '%diff of the total SURO sum of', dfimplnd.loc[ils,'%diff of Sum']
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WORST IMPLND SEGMENT IS 231
-%diff of the total SURO sum of 7.81454022292e-06
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Define a function to read HSPF and HSP2 data, and plot together for IMPLND

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In [174]:
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def imp(ils, name, how='sum'):
-    # Use Tim Cera's HBN reader to get the HSPF data  
-    path = 'IMPLND,' + str(ils) + ',IWATER,' + name
-    hspf = hspfbintoolbox.extract(hbnpath, 'monthly', path)
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-    # Now read the corresponding HSP2 data and comvert to monthly, MS (Month Start) to match hspfbintoolbox data.
-    path = '/RESULTS/IMPLND' + '_I' + '{:0>3s}'.format(str(ils)) + '/IWATER'                                                   
-    hsp2 = pd.read_hdf(hdfpath, path)
-    if how == 'sum':
-        hsp2 = hsp2.resample('MS').sum()
-    elif how == 'last':
-        hsp2 = hsp2.resample('MS').last()
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-    hsp2 = hsp2[name]
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-    plt.figure(figsize=(10,8))
-    plt.plot(hspf.index, hspf, label='HSPF', color='r')
-    plt.plot(hsp2.index, hsp2, label='HSP2', color='b')
-    plt.legend()
-    plt.title('IMPLND ' + 'I' + '{:0>3s}'.format(str(ils)) + ', IWATER ' +  name)
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-    return hspf, hsp2
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IMPLND IWATER SURO, Monthly

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hspf, hsp2 = imp(ils, 'SURO', 'sum')
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plt.scatter(hspf, hsp2)
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-plt.plot([0.0, top], [0.0, top])
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[<matplotlib.lines.Line2D at 0x1b18bb70>]
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IMPLND IWATER IMPEV, Monthly

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hspf, hsp2 = imp(ils, 'IMPEV')
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plt.scatter(hspf, hsp2)
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[<matplotlib.lines.Line2D at 0x1bca6be0>]
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IMPLND IWATER PET, Monthly

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hspf, hsp2 = imp(ils, 'PET')
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IMPLND IWATER RETS, Monthly

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IMPLND IWATER SUPY, Monthly

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IMPLND IWATER SURS, Monthly

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hspf, hsp2 = imp(ils, 'SURS', 'last')
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[<matplotlib.lines.Line2D at 0x1a791978>]
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Automate checking PERLNDs for PERO

Define routine to read HSPF and HSP2 data and plot together

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In [45]:
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def per(pls, name, how='sum'):
-    # Use Tim Cera's HBN reader to get the HSPF data  
-    path = 'PERLND,' + str(pls) + ',PWATER,' + name
-    hspf = hspfbintoolbox.extract(hbnpath, 'monthly', path)
-    
-    # Now read the corresponding HSP2 data and comvert to monthly
-    path = '/RESULTS/PERLND' +  '_P' + '{:0>3s}'.format(str(pls)) + '/PWATER'
-    if how == 'sum':
-        hsp2 = pd.read_hdf(hdfpath, path)[name].resample('MS').sum()
-    elif how == 'last':
-        hsp2 = pd.read_hdf(hdfpath, path)[name].resample('MS').last()
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-    plt.figure(figsize=(10,8))
-    plt.plot(hspf.index, hspf, label='HSPF', color='r')
-    plt.plot(hsp2.index, hsp2, label='HSP2', color='b')
-    plt.legend()
-    plt.title('PERLND ' + 'P' + '{:0>3s}'.format(str(pls))+ ', PWATER ' +  name)
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-    return hspf, hsp2
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Now find all available monthly data

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In [46]:
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segments = [str(key[1]) for key in keys if key[0]=='PERLND' and key[2]=='PWATER' and key[3]=='PERO' and key[4]==4]
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-dfperlnd = pd.DataFrame()
-for seg in segments:  
-    path = 'PERLND,' + seg + ',PWATER,PERO'
-    hspf = hspfbintoolbox.extract(hbnpath, 'monthly', path).values
-  
-    path =  'RESULTS/PERLND' +  '_P' + '{:0>3s}'.format(str(seg)) + '/PWATER'   
-    hsp2 = pd.read_hdf(hdfpath, path)['PERO'].resample('MS').sum().values
-
-    #dfperlnd.at[seg, 'Max Diff'] =  (hspf - hsp2).max()
-    dfperlnd.at[seg, 'Sum of HSPF'] = hspf.sum()
-    dfperlnd.at[seg, 'Sum of HSP2'] = hsp2.sum()
-    dfperlnd.at[seg, '%diff of Sum'] = 100.0 * (hspf.sum() - hsp2.sum()) / hspf.sum()
-    dfperlnd.at[seg, 'abs(%diff of Sum)'] = 100.0 * abs(hspf.sum() - hsp2.sum()) / hspf.sum()
-
-dfperlnd = dfperlnd.sort_values(by=['abs(%diff of Sum)'])    
-dfperlnd
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Out[46]:
- - -
-
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Sum of HSPFSum of HSP2%diff of Sumabs(%diff of Sum)
5564.785964.7859-0.00000.0000
22629.427029.4270-0.00000.0000
22245.914545.9145-0.00000.0000
12456.812956.8129-0.00000.0000
23585.654385.6543-0.00000.0000
7113.870913.8709-0.00000.0000
27544.851944.85190.00000.0000
13549.447249.4472-0.00000.0000
2357.903557.9035-0.00000.0000
20110.971510.9715-0.00000.0000
8245.838645.83860.00000.0000
28597.231497.2315-0.00000.0000
...............
18234.972734.9728-0.00010.0001
23480.864480.8645-0.00010.0001
24361.399461.39930.00010.0001
2516.86826.8682-0.00010.0001
28636.991136.9912-0.00020.0002
15234.490534.4905-0.00020.0002
1117.12597.12590.00020.0002
19578.479578.47940.00020.0002
30672.724872.7249-0.00020.0002
12559.803559.8037-0.00030.0003
18514.789814.7901-0.00250.0025
1016.13336.13250.01280.0128
-

129 rows × 4 columns

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In [47]:
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dfperlnd['%diff of Sum'].hist(bins=40)
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Out[47]:
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<matplotlib.axes._subplots.AxesSubplot at 0x10a98ba8>
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In [48]:
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dfperlnd['%diff of Sum'].describe()
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Out[48]:
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count   129.0000
-mean      0.0001
-std       0.0012
-min      -0.0025
-25%      -0.0001
-50%      -0.0000
-75%      -0.0000
-max       0.0128
-Name: %diff of Sum, dtype: float64
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The PERLND segments are ordered in assending "abs(%diff of Sum)", so the last entry is the worst case (by this measure.)

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In [49]:
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pls = dfperlnd.index[-1]
-print 'WORST PERLND SEGMENT IS', pls
-print '%diff of the total PERO sum of', dfperlnd.loc[pls,'%diff of Sum']
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WORST PERLND SEGMENT IS 101
-%diff of the total PERO sum of 0.0128203408491
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PERLND PWATER AGWO

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In [50]:
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hspf, hsp2 = per(pls, 'AGWO')
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In [51]:
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plt.scatter(hspf, hsp2)
-top = 1.05 * max(hspf.values.max(), hsp2.values.max())
-plt.plot([0.0, top], [0.0, top])
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Out[51]:
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[<matplotlib.lines.Line2D at 0x1337ee80>]
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PERLND PWATER BASET

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In [52]:
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hspf, hsp2 = per(pls, 'BASET')
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In [53]:
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plt.scatter(hspf, hsp2)
-top = 1.05 * max(hspf.values.max(), hsp2.values.max())
-plt.plot([0.0, top], [0.0, top])
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Out[53]:
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[<matplotlib.lines.Line2D at 0x110a2da0>]
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PERLND PWATER CEPE
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In [54]:
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hspf, hsp2 = per(pls, 'CEPE')
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In [55]:
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plt.scatter(hspf, hsp2)
-top = 1.05 * max(hspf.values.max(), hsp2.values.max())
-plt.plot([0.0, top], [0.0, top])
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Out[55]:
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[<matplotlib.lines.Line2D at 0xf638dd8>]
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PERLND PWATER IFWI

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In [56]:
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hspf, hsp2 = per(pls, 'IFWI')
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In [57]:
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plt.scatter(hspf, hsp2)
-top = 1.05 * max(hspf.values.max(), hsp2.values.max())
-plt.plot([0.0, top], [0.0, top])
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Out[57]:
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[<matplotlib.lines.Line2D at 0x1322bef0>]
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PERLND PWATER IFWO

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In [58]:
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hspf, hsp2 = per(pls, 'IFWO')
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In [59]:
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plt.scatter(hspf, hsp2)
-top = 1.05 * max(hspf.values.max(), hsp2.values.max())
-plt.plot([0.0, top], [0.0, top])
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Out[59]:
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[<matplotlib.lines.Line2D at 0x139c9a58>]
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PERLND PWATER IGWI

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In [60]:
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hspf, hsp2 = per(pls, 'IGWI')
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In [61]:
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plt.scatter(hspf, hsp2)
-top = 1.05 * max(hspf.values.max(), hsp2.values.max())
-plt.plot([0.0, top], [0.0, top])
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Out[61]:
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[<matplotlib.lines.Line2D at 0x13716e80>]
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PERLND PWATER INFIL

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In [62]:
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hspf, hsp2 = per(pls, 'INFIL')
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In [63]:
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plt.scatter(hspf, hsp2)
-top = 1.05 * max(hspf.values.max(), hsp2.values.max())
-plt.plot([0.0, top], [0.0, top])
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Out[63]:
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[<matplotlib.lines.Line2D at 0x13f7a320>]
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PERLND PWATER LZET

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In [64]:
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hspf, hsp2 = per(pls, 'LZET')
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In [65]:
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plt.scatter(hspf, hsp2)
-top = 1.05 * max(hspf.values.max(), hsp2.values.max())
-plt.plot([0.0, top], [0.0, top])
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Out[65]:
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[<matplotlib.lines.Line2D at 0x139c9828>]
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PERLND PWATER PERC

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In [66]:
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hspf, hsp2 = per(pls, 'PERC')
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In [67]:
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plt.scatter(hspf, hsp2)
-top = 1.05 * max(hspf.values.max(), hsp2.values.max())
-plt.plot([0.0, top], [0.0, top])
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Out[67]:
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[<matplotlib.lines.Line2D at 0x117be2e8>]
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PERLND PWATER PERO

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In [68]:
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hspf, hsp2 = per(pls, 'PERO')
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In [69]:
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plt.scatter(hspf, hsp2)
-top = 1.05 * max(hspf.values.max(), hsp2.values.max())
-plt.plot([0.0, top], [0.0, top])
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Out[69]:
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[<matplotlib.lines.Line2D at 0x120dce80>]
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PERLND PWATER PERS

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In [70]:
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hspf, hsp2 = per(pls, 'PERS', 'last')
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In [71]:
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plt.scatter(hspf, hsp2)
-top = 1.05 * max(hspf.values.max(), hsp2.values.max())
-plt.plot([0.0, top], [0.0, top])
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Out[71]:
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[<matplotlib.lines.Line2D at 0x14857978>]
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PERLND PWATER PET, Monthly

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In [72]:
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hspf, hsp2 = per(pls, 'PET')
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In [73]:
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plt.scatter(hspf, hsp2)
-top = 1.05 * max(hspf.values.max(), hsp2.values.max())
-plt.plot([0.0, top], [0.0, top])
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Out[73]:
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[<matplotlib.lines.Line2D at 0x1499a400>]
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PERLND PWATER SUPY

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In [74]:
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hspf, hsp2 = per(pls, 'SUPY')
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In [75]:
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plt.scatter(hspf, hsp2)
-top = 1.05 * max(hspf.values.max(), hsp2.values.max())
-plt.plot([0.0, top], [0.0, top])
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Out[75]:
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[<matplotlib.lines.Line2D at 0x1505fa90>]
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PERLND PWATER SURO

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In [76]:
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hspf, hsp2 = per(pls, 'SURO')
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In [77]:
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plt.scatter(hspf, hsp2)
-top = 1.05 * max(hspf.values.max(), hsp2.values.max())
-plt.plot([0.0, top], [0.0, top])
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Out[77]:
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[<matplotlib.lines.Line2D at 0x11e5a9e8>]
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PERLND PWATER TAET

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In [78]:
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hspf, hsp2 = per(pls, 'TAET')
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In [79]:
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plt.scatter(hspf, hsp2)
-top = 1.05 * max(hspf.values.max(), hsp2.values.max())
-plt.plot([0.0, top], [0.0, top])
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Out[79]:
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[<matplotlib.lines.Line2D at 0x13e36cf8>]
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PERLND PWATER UZET

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In [80]:
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hspf, hsp2 = per(pls, 'UZET')
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In [81]:
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plt.scatter(hspf, hsp2)
-top = 1.05 * max(hspf.values.max(), hsp2.values.max())
-plt.plot([0.0, top], [0.0, top])
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Out[81]:
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[<matplotlib.lines.Line2D at 0x13f7e4a8>]
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PERLND PWATER UZI

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In [82]:
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hspf, hsp2 = per(pls, 'UZI')
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In [83]:
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plt.scatter(hspf, hsp2)
-top = 1.05 * max(hspf.values.max(), hsp2.values.max())
-plt.plot([0.0, top], [0.0, top])
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Out[83]:
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[<matplotlib.lines.Line2D at 0x154cf4a8>]
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In [ ]:
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RCHRES

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Define routine to read HSPF and HSP2, plot together for RCHRES

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In [244]:
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def rch(rid, name, how='sum'):
-    # Use Tim Cera's HBN reader to get the HSPF data  
-    path = 'RCHRES,' + str(rid) + ',HYDR,' + name
-    hspf = hspfbintoolbox.extract(hbnpath, 'monthly', path)
-    
-    # Now read the corresponding HSP2 data and comvert to monthly
-    path = '/RESULTS/RCHRES' +   '_R' + '{:0>3s}'.format(str(rid)) + '/HYDR'
-    if how == 'sum':
-        hsp2 = pd.read_hdf(hdfpath, path)[name].resample('MS').sum()
-    elif how == 'last':
-        hsp2 = pd.read_hdf(hdfpath, path)[name].resample('MS').last()
-    
-    plt.figure(figsize=(10,8))
-    plt.plot(hspf.index, hspf, label='HSPF', color='r')
-    plt.plot(hsp2.index, hsp2, label='HSP2', color='b')
-    plt.legend()
-    plt.title('RCHRES ' +   'R' + '{:0>3s}'.format(str(rid)) + ', HYDR ' +  name)
-    
-    return hspf, hsp2
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Automate checking RCHRESs for ROVOL

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In [245]:
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segments = [str(key[1]) for key in keys if key[0]=='RCHRES' and key[2]=='HYDR' and key[3]=='ROVOL' and key[4]==4]
-
-dfrchres = pd.DataFrame()
-for seg in segments:  
-    path = 'RCHRES,' + seg + ',HYDR,ROVOL'
-    hspf = hspfbintoolbox.extract(hbnpath, 'monthly', path).values
-
-    path = 'RESULTS/RCHRES'+   '_R' + '{:0>3s}'.format(str(seg)) +'/HYDR' 
-    hsp2 = pd.read_hdf(hdfpath, path)['ROVOL'].resample('MS').sum().values
-    
-    #dfrchres.at[seg, 'Max Diff'] =  (hspf - hsp2).max()
-    dfrchres.at[seg, 'Sum of HSPF'] = hspf.sum()
-    dfrchres.at[seg, 'Sum of HSP2'] = hsp2.sum()
-    dfrchres.at[seg, '%diff of Sum'] = 100.0 * (hspf.sum() - hsp2.sum()) / hspf.sum()
-    dfrchres.at[seg, 'abs(%diff of Sum)'] = 100.0 * abs(hspf.sum() - hsp2.sum()) / hspf.sum()    
-
-dfrchres = dfrchres.sort_values(by ='abs(%diff of Sum)')    
-dfrchres
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Out[245]:
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- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Sum of HSPFSum of HSP2%diff of Sumabs(%diff of Sum)
525755.3912755.3912-0.00000.0000
1934381.47304381.47270.00000.0000
952709.6680709.66780.00000.0000
50472021.951972021.93750.00000.0000
964754.5005754.50030.00000.0000
40124895.403524895.39650.00000.0000
114362.42494362.42330.00000.0000
64659.7574659.7577-0.00000.0000
4214785.92454785.9263-0.00000.0000
50358696.583458696.6055-0.00000.0000
40254092.217054092.2383-0.00000.0000
52127894.395727894.38480.00000.0000
...............
2116396.13286395.64210.00770.0077
22310951.649910950.78030.00790.0079
2279763.93449763.13180.00820.0082
1955182.86345183.3047-0.00850.0085
1917559.51057558.62160.01180.0118
421649.16481648.96730.01200.0120
411284.56061284.40430.01220.0122
2224995.35784994.42680.01860.0186
2215001.44455000.51120.01870.0187
1909018.73649016.99510.01930.0193
2256018.11286016.86820.02070.0207
407254032.0347251524.59380.98710.9871
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119 rows × 4 columns

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In [246]:
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dfrchres['%diff of Sum'].hist(bins=40)
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<matplotlib.axes._subplots.AxesSubplot at 0x211bb828>
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In [247]:
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dfrchres['%diff of Sum'].describe()
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Out[247]:
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count   119.0000
-mean      0.0094
-std       0.0905
-min      -0.0085
-25%      -0.0002
-50%      -0.0000
-75%       0.0003
-max       0.9871
-Name: %diff of Sum, dtype: float64
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The RCHRES segments are ordered in assending "abs(%diff of Sum)", so the last entry is the worst case (by this measure.)

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In [248]:
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rid = dfrchres.index[-1]
-print 'WORST RCHRES SEGMENT IS', rid
-print '%diff of the total PERO sum of', dfrchres.loc[rid,'%diff of Sum']
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WORST RCHRES SEGMENT IS 407
-%diff of the total PERO sum of 0.987056975411
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In [249]:
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dfrchres.loc[str(rid),:]    #['%diff of Sum'].describe()
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Out[249]:
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Sum of HSPF         254032.0347
-Sum of HSP2         251524.5938
-%diff of Sum             0.9871
-abs(%diff of Sum)        0.9871
-Name: 407, dtype: float64
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RCHRES HYDR IVOL

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hspf, hsp2 = rch(rid, 'IVOL')
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plt.scatter(hspf, hsp2)
-top = 1.05 * max(hspf.values.max(), hsp2.values.max())
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[<matplotlib.lines.Line2D at 0x199ca240>]
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RCHRES HYDR PRSUPY

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hspf, hsp2 = rch(rid, 'PRSUPY')
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plt.scatter(hspf, hsp2)
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[<matplotlib.lines.Line2D at 0x19aaf9b0>]
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RCHRES HYDR ROVOL

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hspf, hsp2 = rch(rid, 'ROVOL')
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plt.scatter(hspf, hsp2)
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[<matplotlib.lines.Line2D at 0x1f4eaf98>]
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RCHRES HYDR VOL

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hspf, hsp2 = rch(rid, 'VOL', 'last')
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plt.scatter(hspf, hsp2)
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RCHRES HYDR VOLEV

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hspf, hsp2 = rch(rid, 'VOLEV')
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plt.scatter(hspf, hsp2)
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- - - - - - diff --git a/tests/Calleg/notebooks-py2/TESTcalleg.ipynb b/tests/Calleg/notebooks-py2/TESTcalleg.ipynb deleted file mode 100755 index 783d9644..00000000 --- a/tests/Calleg/notebooks-py2/TESTcalleg.ipynb +++ /dev/null @@ -1,1325 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "This Jupyter Notebook Copyright 2016 by RESPEC, INC. All rights reserved.\n", - "\n", - "$\\textbf{HSP}^{\\textbf{2}}\\ \\text{and}\\ \\textbf{HSP2}\\ $ Copyright 2016 by RESPEC INC. and released under this [License](LegalInformation/License.txt)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Calleg TEST NOTEBOOK for HSP$^2$ (WORST CASE COMPARISONS)\n", - "\n", - "This Notebook will compare the results of running HSPF and HSP$^2$ for the basic hydrology (PWATER, IWATER, and HYDR) to confirm the proper calculations of HSP$^2$\n", - "\n", - "Calleg is a real watershed and has\n", - "+ 27 IMPLND segments,\n", - "+ 129 PERLND segments,\n", - "+ 119 RCHRES segments,\n", - "+ 9 years of simulation time with hourly time steps (78,888 timesteps)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Required Python imports and setup" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "import pandas as pd\n", - "\n", - "pd.options.display.max_rows = 25\n", - "pd.options.display.max_columns = 20\n", - "pd.options.display.float_format = '{:.4f}'.format # display 2 digits after the decimal point\n", - "\n", - "import matplotlib.pyplot as plt\n", - "%matplotlib inline\n", - "\n", - "import hspfbintoolbox\n", - "import HSP2\n", - "import HSP2tools\n", - "HSP2tools.versions()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Setup paths to the necessary datafiles\n", - "This assumes the calleg.uci and calleg.wdm files are located in the current working directory for this Notebook. This will create the binary output file, calleg.hbn, along with a number of other standard HSPF outputs." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "wdmpath = 'calleg.wdm'\n", - "ucipath = 'calleg.uci'\n", - "hdfpathx = 'callegx.h5'\n", - "hdfpath = 'calleg.h5'\n", - "hbnpath = 'calleg.hbn'" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Run HSPF\n", - "\n", - "Using the Basins 4.1 WinHspfLt executable to run calleg.uci.\n", - "\n", - "This assumes the calleg.uci and calleg.wdm files are located in the current working directory for this Notebook. This will create the binary output file, calleg.hbn, along with a number of other standard HSPF outputs." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "!echo %date% - %time%\n", - "\n", - "!C:\\BASINS41\\models\\HSPF\\bin\\WinHspfLt.exe {ucipath}\n", - " \n", - "!echo %date% - %time%" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For development, save the best time for reference:" - ] - }, - { - "cell_type": "raw", - "metadata": {}, - "source": [ - "1 loop, best of 3: 24.4 s per loop" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now run HSP$^2$ on the calleg watershed" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "HSP2.run(hdfpath)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%timeit HSP2.run(hdfpath)" - ] - }, - { - "cell_type": "raw", - "metadata": {}, - "source": [ - "Development note:\n", - "\n", - "SAVEALL = FALSE (new SAVE table for hot restart by default)\n", - "2017-04-16 09:05:26.10 Run completed\n", - "1 loop, best of 3: 32.3 s per loop\n", - "Ratio of HSP2/HSPF 32.3/24.4 = 1.3\n", - "\n", - "SAVEALL = TRUE\n", - "2017-04-11 10:18:22.86 Run completed\n", - "1 loop, best of 3: 38.1 s per loop\n", - "Ratio of HSP2/HSPF 38.1/24.4 = 1.6" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Determine Available Calculated Results\n", - "\n", - "Now use Tim Cera's hspfbintoolbox.py to determine the available timeseries created by HSPF and stored into the HBN binary file.\n", - "\n", - "Time interval codes: {5: 'yearly', 4: 'monthly', 3: 'daily', 2: 'bivl'}.\n", - "\n", - "No daily available, so use monthly (4) timeseries for analysis." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "keys = hspfbintoolbox.catalog(hbnpath).keys()\n", - "keys[:5] # show only the first 5 as a check" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Automate checking IMPLNDs for SURO\n", - "\n", - "Extract the keys (calculated above) for IMPLD + IWATER + SURO. For each key, compute several columns. The final column shows the percent difference of the sum of the SURO for the entire run between HSPF and HSP2." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "segments = [str(key[1]) for key in keys if key[0]=='IMPLND' and key[2]=='IWATER' and key[3]=='SURO' and key[4]==4]\n", - "\n", - "dfimplnd = pd.DataFrame()\n", - "for seg in segments: \n", - " path = 'IMPLND,' + seg + ',IWATER,SURO'\n", - " hspf = hspfbintoolbox.extract(hbnpath, 'monthly', path).values\n", - " \n", - " path = 'RESULTS/IMPLND' + '_I' + '{:0>3s}'.format(seg) + '/IWATER'\n", - " hsp2 = pd.read_hdf(hdfpath, path)['SURO'].resample('MS').sum().values\n", - " \n", - " #dfimplnd.at[seg, 'Max Diff'] = (hspf - hsp2).max()\n", - " dfimplnd.at[seg, 'Sum of HSPF'] = hspf.sum()\n", - " dfimplnd.at[seg, 'Sum of HSP2'] = hsp2.sum()\n", - " dfimplnd.at[seg, '%diff of Sum'] = 100.0 * (hspf.sum() - hsp2.sum()) / hspf.sum()\n", - " dfimplnd.at[seg, 'abs(%diff of Sum)'] = 100.0 * abs(hspf.sum() - hsp2.sum()) / hspf.sum()\n", - "\n", - "dfimplnd = dfimplnd.sort_values(by=['abs(%diff of Sum)'])\n", - "dfimplnd" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Look at the statistics for the percent difference column" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "dfimplnd['%diff of Sum'].hist()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "dfimplnd['%diff of Sum'].describe()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "ils = dfimplnd.index[-1]\n", - "print 'WORST IMPLND SEGMENT IS', ils\n", - "print '%diff of the total SURO sum of', dfimplnd.loc[ils,'%diff of Sum']" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Define a function to read HSPF and HSP2 data, and plot together for IMPLND" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def imp(ils, name, how='sum'):\n", - " # Use Tim Cera's HBN reader to get the HSPF data \n", - " path = 'IMPLND,' + str(ils) + ',IWATER,' + name\n", - " hspf = hspfbintoolbox.extract(hbnpath, 'monthly', path)\n", - "\n", - " # Now read the corresponding HSP2 data and comvert to monthly, MS (Month Start) to match hspfbintoolbox data.\n", - " path = '/RESULTS/IMPLND' + '_I' + '{:0>3s}'.format(str(ils)) + '/IWATER' \n", - " hsp2 = pd.read_hdf(hdfpath, path)\n", - " if how == 'sum':\n", - " hsp2 = hsp2.resample('MS').sum()\n", - " elif how == 'last':\n", - " hsp2 = hsp2.resample('MS').last()\n", - " \n", - " hsp2 = hsp2[name]\n", - " \n", - " plt.figure(figsize=(10,8))\n", - " plt.plot(hspf.index, hspf, label='HSPF', color='r')\n", - " plt.plot(hsp2.index, hsp2, label='HSP2', color='b')\n", - " plt.legend()\n", - " plt.title('IMPLND ' + 'I' + '{:0>3s}'.format(str(ils)) + ', IWATER ' + name)\n", - " \n", - " return hspf, hsp2" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### IMPLND IWATER SURO, Monthly" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = imp(ils, 'SURO', 'sum')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### IMPLND IWATER IMPEV, Monthly" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = imp(ils, 'IMPEV')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### IMPLND IWATER PET, Monthly" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = imp(ils, 'PET')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### IMPLND IWATER RETS, Monthly" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = imp(ils, 'RETS', 'last')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### IMPLND IWATER SUPY, Monthly" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = imp(ils, 'SUPY')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### IMPLND IWATER SURS, Monthly" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = imp(ils, 'SURS', 'last')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Automate checking PERLNDs for PERO\n", - "\n", - "### Define routine to read HSPF and HSP2 data and plot together" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def per(pls, name, how='sum'):\n", - " # Use Tim Cera's HBN reader to get the HSPF data \n", - " path = 'PERLND,' + str(pls) + ',PWATER,' + name\n", - " hspf = hspfbintoolbox.extract(hbnpath, 'monthly', path)\n", - " \n", - " # Now read the corresponding HSP2 data and comvert to monthly\n", - " path = '/RESULTS/PERLND' + '_P' + '{:0>3s}'.format(str(pls)) + '/PWATER'\n", - " if how == 'sum':\n", - " hsp2 = pd.read_hdf(hdfpath, path)[name].resample('MS').sum()\n", - " elif how == 'last':\n", - " hsp2 = pd.read_hdf(hdfpath, path)[name].resample('MS').last()\n", - " \n", - " plt.figure(figsize=(10,8))\n", - " plt.plot(hspf.index, hspf, label='HSPF', color='r')\n", - " plt.plot(hsp2.index, hsp2, label='HSP2', color='b')\n", - " plt.legend()\n", - " plt.title('PERLND ' + 'P' + '{:0>3s}'.format(str(pls))+ ', PWATER ' + name)\n", - " \n", - " return hspf, hsp2" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Now find all available monthly data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "segments = [str(key[1]) for key in keys if key[0]=='PERLND' and key[2]=='PWATER' and key[3]=='PERO' and key[4]==4]\n", - "\n", - "dfperlnd = pd.DataFrame()\n", - "for seg in segments: \n", - " path = 'PERLND,' + seg + ',PWATER,PERO'\n", - " hspf = hspfbintoolbox.extract(hbnpath, 'monthly', path).values\n", - " \n", - " path = 'RESULTS/PERLND' + '_P' + '{:0>3s}'.format(str(seg)) + '/PWATER' \n", - " hsp2 = pd.read_hdf(hdfpath, path)['PERO'].resample('MS').sum().values\n", - "\n", - " #dfperlnd.at[seg, 'Max Diff'] = (hspf - hsp2).max()\n", - " dfperlnd.at[seg, 'Sum of HSPF'] = hspf.sum()\n", - " dfperlnd.at[seg, 'Sum of HSP2'] = hsp2.sum()\n", - " dfperlnd.at[seg, '%diff of Sum'] = 100.0 * (hspf.sum() - hsp2.sum()) / hspf.sum()\n", - " dfperlnd.at[seg, 'abs(%diff of Sum)'] = 100.0 * abs(hspf.sum() - hsp2.sum()) / hspf.sum()\n", - "\n", - "dfperlnd = dfperlnd.sort_values(by=['abs(%diff of Sum)']) \n", - "dfperlnd" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "dfperlnd['%diff of Sum'].hist(bins=40)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "dfperlnd['%diff of Sum'].describe()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The PERLND segments are ordered in assending \"abs(%diff of Sum)\", so the last entry is the worst case (by this measure.)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "pls = dfperlnd.index[-1]\n", - "print 'WORST PERLND SEGMENT IS', pls\n", - "print '%diff of the total PERO sum of', dfperlnd.loc[pls,'%diff of Sum']" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER AGWO" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, 'AGWO')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER BASET" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, 'BASET')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### PERLND PWATER CEPE" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, 'CEPE')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER IFWI" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, 'IFWI')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER IFWO" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, 'IFWO')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER IGWI" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, 'IGWI')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER INFIL" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, 'INFIL')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER LZET" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, 'LZET')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER PERC" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, 'PERC')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER PERO" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, 'PERO')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER PERS" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, 'PERS', 'last')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER PET, Monthly" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, 'PET')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER SUPY" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, 'SUPY')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER SURO" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, 'SURO')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER TAET" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, 'TAET')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER UZET" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, 'UZET')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER UZI" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, 'UZI')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## RCHRES" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Define routine to read HSPF and HSP2, plot together for RCHRES" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def rch(rid, name, how='sum'):\n", - " # Use Tim Cera's HBN reader to get the HSPF data \n", - " path = 'RCHRES,' + str(rid) + ',HYDR,' + name\n", - " hspf = hspfbintoolbox.extract(hbnpath, 'monthly', path)\n", - " \n", - " # Now read the corresponding HSP2 data and comvert to monthly\n", - " path = '/RESULTS/RCHRES' + '_R' + '{:0>3s}'.format(str(rid)) + '/HYDR'\n", - " if how == 'sum':\n", - " hsp2 = pd.read_hdf(hdfpath, path)[name].resample('MS').sum()\n", - " elif how == 'last':\n", - " hsp2 = pd.read_hdf(hdfpath, path)[name].resample('MS').last()\n", - " \n", - " plt.figure(figsize=(10,8))\n", - " plt.plot(hspf.index, hspf, label='HSPF', color='r')\n", - " plt.plot(hsp2.index, hsp2, label='HSP2', color='b')\n", - " plt.legend()\n", - " plt.title('RCHRES ' + 'R' + '{:0>3s}'.format(str(rid)) + ', HYDR ' + name)\n", - " \n", - " return hspf, hsp2" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Automate checking RCHRESs for ROVOL" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "segments = [str(key[1]) for key in keys if key[0]=='RCHRES' and key[2]=='HYDR' and key[3]=='ROVOL' and key[4]==4]\n", - "\n", - "dfrchres = pd.DataFrame()\n", - "for seg in segments: \n", - " path = 'RCHRES,' + seg + ',HYDR,ROVOL'\n", - " hspf = hspfbintoolbox.extract(hbnpath, 'monthly', path).values\n", - "\n", - " path = 'RESULTS/RCHRES'+ '_R' + '{:0>3s}'.format(str(seg)) +'/HYDR' \n", - " hsp2 = pd.read_hdf(hdfpath, path)['ROVOL'].resample('MS').sum().values\n", - " \n", - " #dfrchres.at[seg, 'Max Diff'] = (hspf - hsp2).max()\n", - " dfrchres.at[seg, 'Sum of HSPF'] = hspf.sum()\n", - " dfrchres.at[seg, 'Sum of HSP2'] = hsp2.sum()\n", - " dfrchres.at[seg, '%diff of Sum'] = 100.0 * (hspf.sum() - hsp2.sum()) / hspf.sum()\n", - " dfrchres.at[seg, 'abs(%diff of Sum)'] = 100.0 * abs(hspf.sum() - hsp2.sum()) / hspf.sum() \n", - "\n", - "dfrchres = dfrchres.sort_values(by ='abs(%diff of Sum)') \n", - "dfrchres" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "dfrchres['%diff of Sum'].hist(bins=40)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "dfrchres['%diff of Sum'].describe()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The RCHRES segments are ordered in assending \"abs(%diff of Sum)\", so the last entry is the worst case (by this measure.)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "rid = dfrchres.index[-1]\n", - "print 'WORST RCHRES SEGMENT IS', rid\n", - "print '%diff of the total PERO sum of', dfrchres.loc[rid,'%diff of Sum']" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "dfrchres.loc[str(rid),:] #['%diff of Sum'].describe()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### RCHRES HYDR IVOL" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = rch(rid, 'IVOL')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### RCHRES HYDR PRSUPY" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = rch(rid, 'PRSUPY')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### RCHRES HYDR ROVOL" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = rch(rid, 'ROVOL')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### RCHRES HYDR VOL" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = rch(rid, 'VOL', 'last')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### RCHRES HYDR VOLEV" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hspf, hsp2 = rch(rid, 'VOLEV')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.values.max(), hsp2.values.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.4" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/tests/Calleg/notebooks-py2/Test_Migration_of_HSPF_to_HSP2.ipynb b/tests/Calleg/notebooks-py2/Test_Migration_of_HSPF_to_HSP2.ipynb deleted file mode 100644 index c3be60fe..00000000 --- a/tests/Calleg/notebooks-py2/Test_Migration_of_HSPF_to_HSP2.ipynb +++ /dev/null @@ -1,1873 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "This Jupyter Notebook Copyright 2017 by RESPEC, INC. All rights reserved." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Calleg TEST NOTEBOOK for HSP$^2$ \n", - "# Developed for Windows Plaform\n", - "\n", - "This Notebook will compare the results of running HSPF and HSP$^2$ for the basic hydrology (PWATER, IWATER, and HYDR) to confirm the proper calculations of HSP$^2$. This notebook requires HSPF to be installed and currently runs WinHSPF Lite from BASINS install C:\\BASINS41\\models\\HSPF\\bin\\WinHspfLt.exe. It is setup to run using the Calleguas example provided in the repo at " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Required Python imports and setup" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "execution": { - "iopub.execute_input": "2024-04-26T01:50:57.850746Z", - "iopub.status.busy": "2024-04-26T01:50:57.850179Z", - "iopub.status.idle": "2024-04-26T01:50:58.427802Z", - "shell.execute_reply": "2024-04-26T01:50:58.427342Z", - "shell.execute_reply.started": "2024-04-26T01:50:57.850724Z" - }, - "scrolled": true - }, - "outputs": [ - { - "ename": "AttributeError", - "evalue": "module 'HSP2tools' has no attribute 'reset_tutorial'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[3], line 26\u001b[0m\n\u001b[1;32m 22\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mHSP2tools\u001b[39;00m\n\u001b[1;32m 24\u001b[0m get_ipython()\u001b[38;5;241m.\u001b[39mrun_line_magic(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmatplotlib\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124minline\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m---> 26\u001b[0m \u001b[43mHSP2tools\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreset_tutorial\u001b[49m() \u001b[38;5;66;03m# make a new copy of the tutorial's data\u001b[39;00m\n\u001b[1;32m 27\u001b[0m HSP2tools\u001b[38;5;241m.\u001b[39mversions() \u001b[38;5;66;03m# display version information below\u001b[39;00m\n", - "\u001b[0;31mAttributeError\u001b[0m: module 'HSP2tools' has no attribute 'reset_tutorial'" - ] - } - ], - "source": [ - "import os\n", - "import site\n", - "\n", - "site.addsitedir(\n", - " os.getcwd().rsplit(\"\\\\\", 1)[0] + \"\\\\\"\n", - ") # adds your path to the HSP2 software.\n", - "\n", - "import shutil\n", - "\n", - "import numpy as np\n", - "import pandas as pd\n", - "\n", - "pd.options.display.max_rows = 18\n", - "pd.options.display.max_columns = 10\n", - "pd.options.display.float_format = (\n", - " \"{:.2f}\".format\n", - ") # display 2 digits after the decimal point\n", - "\n", - "import matplotlib.pyplot as plt\n", - "\n", - "import HSP2\n", - "import HSP2tools\n", - "\n", - "%matplotlib inline\n", - "\n", - "HSP2tools.reset_tutorial() # make a new copy of the tutorial's data\n", - "HSP2tools.versions() # display version information below" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Setup paths to the necessary datafiles\n", - "This assumes the calleg.uci and calleg.wdm files are located in the current working directory for this Notebook. This will create the binary output file, calleg.hbn, along with a number of other standard HSPF outputs." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.569525Z", - "iopub.status.idle": "2024-04-26T01:48:56.569838Z", - "shell.execute_reply": "2024-04-26T01:48:56.569725Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.569713Z" - } - }, - "outputs": [], - "source": [ - "wdmname = \"TutorialData/calleg.wdm\"\n", - "uciname = \"TutorialData/calleg.uci\"\n", - "hdfname = \"TutorialData/calleg.h5\"\n", - "hbnname = \"TutorialData/calleg.hbn\"" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Run HSPF\n", - "\n", - "Using the Basins 4.1 WinHspfLt executable to run calleg.uci.\n", - "\n", - "This assumes the calleg.uci and calleg.wdm files are located in the current working directory for this Notebook. This will create the binary output file, calleg.hbn, along with a number of other standard HSPF outputs." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.570553Z", - "iopub.status.idle": "2024-04-26T01:48:56.570777Z", - "shell.execute_reply": "2024-04-26T01:48:56.570682Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.570673Z" - } - }, - "outputs": [], - "source": [ - "%time !C:\\BASINS41\\models\\HSPF\\bin\\WinHspfLt.exe {uciname}" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Run HSP$^2$\n", - "\n", - "This assumes the calleg.h5 file has been created. If not, the following lines can be used to create the HDF5 file (see Tutorial 4 for details.)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.571304Z", - "iopub.status.idle": "2024-04-26T01:48:56.571467Z", - "shell.execute_reply": "2024-04-26T01:48:56.571397Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.571390Z" - } - }, - "outputs": [], - "source": [ - "HSP2tools.makeH5()\n", - "HSP2tools.readUCI(uciname, hdfname)\n", - "HSP2tools.ReadWDM(wdmname, hdfname)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now run HSP$^2$ on the calleg watershed" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.572074Z", - "iopub.status.idle": "2024-04-26T01:48:56.572333Z", - "shell.execute_reply": "2024-04-26T01:48:56.572235Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.572227Z" - } - }, - "outputs": [], - "source": [ - "%time HSP2.run(hdfname, saveall=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Determine Available Calculated Results\n", - "\n", - "Now use Tim Cera's hspfbintoolbox.py to determine the available timeseries created by HSPF and stored into the HBN binary file." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.572834Z", - "iopub.status.idle": "2024-04-26T01:48:56.573025Z", - "shell.execute_reply": "2024-04-26T01:48:56.572933Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.572924Z" - } - }, - "outputs": [], - "source": [ - "!ptrepack TutorialData\\calleg.h5 TutorialData\\packedCalleg.h5" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.573537Z", - "iopub.status.idle": "2024-04-26T01:48:56.573826Z", - "shell.execute_reply": "2024-04-26T01:48:56.573728Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.573719Z" - } - }, - "outputs": [], - "source": [ - "import hspfbintoolbox" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.574249Z", - "iopub.status.idle": "2024-04-26T01:48:56.574508Z", - "shell.execute_reply": "2024-04-26T01:48:56.574416Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.574408Z" - }, - "scrolled": true - }, - "outputs": [], - "source": [ - "keys = sorted(hspfbintoolbox.catalog(hbnname).keys())\n", - "df_keys = pd.DataFrame(data=keys)\n", - "df_keys" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Automate checking IMPLNDs for SURO\n", - "\n", - "Extract the keys (calculated above) for IMPLD + IWATER + SURO. For each key, compute several columns. The final column shows the percent difference of the sum of the SURO for the entire run between HSPF and HSP2." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.574929Z", - "iopub.status.idle": "2024-04-26T01:48:56.575107Z", - "shell.execute_reply": "2024-04-26T01:48:56.575023Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.575015Z" - } - }, - "outputs": [], - "source": [ - "segments = []\n", - "for operation, segment, optype, variable, freq in keys:\n", - " if (\n", - " str(operation) == \"IMPLND\"\n", - " and str(optype) == \"IWATER\"\n", - " and str(variable) == \"SURO\"\n", - " and freq == 4\n", - " ):\n", - " segments.append(str(segment))\n", - "\n", - "dfimplnd = pd.DataFrame()\n", - "for seg in segments:\n", - " path = \"IMPLND,\" + seg + \",IWATER,SURO\"\n", - " hspf, units_flag = HSP2tools.get_HBNdata(hbnname, path)\n", - " hspf = hspf[\"M\"].values\n", - "\n", - " path = \"/RESULTS/IMPLND\" + \"_I\" + \"{:0>3s}\".format(str(seg)) + \"/IWATER\"\n", - " hsp2 = pd.read_hdf(hdfname, path)[\"SURO\"]\n", - " hsp2 = hsp2.resample(\"M\").sum().values\n", - "\n", - " dfimplnd.at[seg, \"Max Diff\"] = (hspf - hsp2).max()\n", - " dfimplnd.at[seg, \"Sum of HSPF\"] = hspf.sum()\n", - " dfimplnd.at[seg, \"Sum of HSP2\"] = hsp2.sum()\n", - " dfimplnd.at[seg, \"%diff of Sum\"] = 100.0 * (hspf.sum() - hsp2.sum()) / hspf.sum()\n", - " dfimplnd.at[seg, \"abs(%diff of Sum)\"] = (\n", - " 100.0 * abs(hspf.sum() - hsp2.sum()) / hspf.sum()\n", - " )\n", - "\n", - "dfimplnd = dfimplnd.sort_values(by=[\"abs(%diff of Sum)\"])\n", - "dfimplnd" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Look at the statistics for the percent difference column" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.575628Z", - "iopub.status.idle": "2024-04-26T01:48:56.575764Z", - "shell.execute_reply": "2024-04-26T01:48:56.575705Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.575699Z" - } - }, - "outputs": [], - "source": [ - "dfimplnd[\"%diff of Sum\"].describe()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - } - }, - "source": [ - "### Now look at the worst case\n", - "The IMPLND segments are ordered in assending \"abs(%diff of Sum)\", so the last entry is the worst case (by this measure.)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.576241Z", - "iopub.status.idle": "2024-04-26T01:48:56.576408Z", - "shell.execute_reply": "2024-04-26T01:48:56.576354Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.576348Z" - } - }, - "outputs": [], - "source": [ - "ils = dfimplnd.index[-1]\n", - "print(\"WORST IMPLND SEGMENT IS \", ils)\n", - "print(\"%diff of the total SURO sum of\", dfimplnd.loc[ils, \"%diff of Sum\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Define a function to read HSPF and HSP2 data, and plot together for IMPLND" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.576720Z", - "iopub.status.idle": "2024-04-26T01:48:56.576826Z", - "shell.execute_reply": "2024-04-26T01:48:56.576776Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.576771Z" - } - }, - "outputs": [], - "source": [ - "def imp(ils, name, how=\"sum\"):\n", - " # Use Tim Cera's HBN reader to get the HSPF data\n", - " path = \"IMPLND,\" + str(ils) + \",IWATER,\" + name\n", - " hspf, units_flag = HSP2tools.get_HBNdata(hbnname, path)\n", - " # There may be both monthly and annual timeseries available. Get the monthly timeseries.\n", - " hspf = hspf[\"M\"]\n", - "\n", - " # Now read the corresponding HSP2 data and comvert to monthly\n", - " path = \"/RESULTS/IMPLND\" + \"_I\" + \"{:0>3s}\".format(str(ils)) + \"/IWATER\"\n", - " hsp2 = pd.read_hdf(hdfname, path)\n", - " if how == \"sum\":\n", - " hsp2 = hsp2.resample(\"M\").sum()\n", - " elif how == \"last\":\n", - " hsp2 = hsp2.resample(\"M\").last()\n", - "\n", - " hsp2 = hsp2[name]\n", - "\n", - " plt.figure(figsize=(16, 8))\n", - " plt.plot(hspf.index, hspf, label=\"HSPF\", color=\"r\")\n", - " plt.plot(hsp2.index, hsp2, label=\"HSP2\", color=\"b\", linestyle=\"--\")\n", - " plt.legend()\n", - " plt.title(\"IMPLND \" + \"I\" + \"{:0>3s}\".format(str(ils)) + \", IWATER \" + name)\n", - "\n", - " return hspf, hsp2" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - } - }, - "source": [ - "#### IMPLND IWATER SURO, Monthly" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.577176Z", - "iopub.status.idle": "2024-04-26T01:48:56.577285Z", - "shell.execute_reply": "2024-04-26T01:48:56.577232Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.577227Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = imp(ils, \"SURO\", \"sum\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.577591Z", - "iopub.status.idle": "2024-04-26T01:48:56.577694Z", - "shell.execute_reply": "2024-04-26T01:48:56.577645Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.577641Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - } - }, - "source": [ - "#### IMPLND IWATER IMPEV, Monthly" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.578053Z", - "iopub.status.idle": "2024-04-26T01:48:56.578171Z", - "shell.execute_reply": "2024-04-26T01:48:56.578116Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.578111Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = imp(ils, \"IMPEV\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.578574Z", - "iopub.status.idle": "2024-04-26T01:48:56.578689Z", - "shell.execute_reply": "2024-04-26T01:48:56.578635Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.578630Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### IMPLND IWATER PET, Monthly" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.579059Z", - "iopub.status.idle": "2024-04-26T01:48:56.579165Z", - "shell.execute_reply": "2024-04-26T01:48:56.579115Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.579110Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = imp(ils, \"PET\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.579402Z", - "iopub.status.idle": "2024-04-26T01:48:56.579504Z", - "shell.execute_reply": "2024-04-26T01:48:56.579455Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.579450Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### IMPLND IWATER RETS, Monthly" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.579884Z", - "iopub.status.idle": "2024-04-26T01:48:56.579989Z", - "shell.execute_reply": "2024-04-26T01:48:56.579938Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.579934Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = imp(ils, \"RETS\", \"last\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.580300Z", - "iopub.status.idle": "2024-04-26T01:48:56.580416Z", - "shell.execute_reply": "2024-04-26T01:48:56.580362Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.580356Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### IMPLND IWATER SUPY, Monthly" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.580679Z", - "iopub.status.idle": "2024-04-26T01:48:56.580784Z", - "shell.execute_reply": "2024-04-26T01:48:56.580734Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.580729Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = imp(ils, \"SUPY\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.581131Z", - "iopub.status.idle": "2024-04-26T01:48:56.581239Z", - "shell.execute_reply": "2024-04-26T01:48:56.581187Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.581182Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - } - }, - "source": [ - "#### IMPLND IWATER SURS, Monthly" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.581538Z", - "iopub.status.idle": "2024-04-26T01:48:56.581656Z", - "shell.execute_reply": "2024-04-26T01:48:56.581602Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.581596Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = imp(ils, \"SURS\", \"last\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.581995Z", - "iopub.status.idle": "2024-04-26T01:48:56.582128Z", - "shell.execute_reply": "2024-04-26T01:48:56.582053Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.582048Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Automate checking PERLNDs for PERO" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.582729Z", - "iopub.status.idle": "2024-04-26T01:48:56.582908Z", - "shell.execute_reply": "2024-04-26T01:48:56.582825Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.582818Z" - } - }, - "outputs": [], - "source": [ - "# With Large HBNs this currently takes a while (need to speed up the HBN Read)\n", - "segments = []\n", - "for operation, segment, optype, variable, freq in keys:\n", - " if (\n", - " str(operation) == \"PERLND\"\n", - " and str(optype) == \"PWATER\"\n", - " and str(variable) == \"PERO\"\n", - " and freq == 4\n", - " ):\n", - " segments.append(str(segment))\n", - "\n", - "dfperlnd = pd.DataFrame()\n", - "for seg in segments:\n", - " path = \"PERLND,\" + seg + \",PWATER,PERO\"\n", - " hspf, units_flag = HSP2tools.get_HBNdata(hbnname, path)\n", - " hspf = hspf[\"M\"].values\n", - "\n", - " path = \"RESULTS/PERLND\" + \"_P\" + \"{:0>3s}\".format(str(seg)) + \"/PWATER\"\n", - " hsp2 = pd.read_hdf(hdfname, path)[\"PERO\"]\n", - " hsp2 = hsp2.resample(\"M\").sum().values\n", - "\n", - " dfperlnd.at[seg, \"Max Diff\"] = (hspf - hsp2).max()\n", - " dfperlnd.at[seg, \"Sum of HSPF\"] = hspf.sum()\n", - " dfperlnd.at[seg, \"Sum of HSP2\"] = hsp2.sum()\n", - " dfperlnd.at[seg, \"%diff of Sum\"] = 100.0 * (hspf.sum() - hsp2.sum()) / hspf.sum()\n", - " dfperlnd.at[seg, \"abs(%diff of Sum)\"] = (\n", - " 100.0 * abs(hspf.sum() - hsp2.sum()) / hspf.sum()\n", - " )\n", - "\n", - "dfperlnd = dfperlnd.sort_values(by=[\"abs(%diff of Sum)\"])\n", - "dfperlnd" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.583534Z", - "iopub.status.idle": "2024-04-26T01:48:56.583705Z", - "shell.execute_reply": "2024-04-26T01:48:56.583629Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.583622Z" - } - }, - "outputs": [], - "source": [ - "dfperlnd[\"%diff of Sum\"].describe()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The PERLND segments are ordered in assending \"abs(%diff of Sum)\", so the last entry is the worst case (by this measure.)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.584164Z", - "iopub.status.idle": "2024-04-26T01:48:56.584307Z", - "shell.execute_reply": "2024-04-26T01:48:56.584241Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.584234Z" - } - }, - "outputs": [], - "source": [ - "pls = dfperlnd.index[-1]\n", - "print(\"WORST PERLND SEGMENT IS \", pls)\n", - "print(\"%diff of the total PERO sum of\", dfperlnd.loc[pls, \"%diff of Sum\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Define routine to read HSPF and HSP2 data and plot together" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.584635Z", - "iopub.status.idle": "2024-04-26T01:48:56.584768Z", - "shell.execute_reply": "2024-04-26T01:48:56.584705Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.584699Z" - } - }, - "outputs": [], - "source": [ - "def per(pls, name, how=\"sum\"):\n", - " # Use Tim Cera's HBN reader to get the HSPF data\n", - " path = \"PERLND,\" + str(pls) + \",PWATER,\" + name\n", - " hspf, units_flag = HSP2tools.get_HBNdata(hbnname, path)\n", - " # There may be both monthly and annual timeseries available. Get the monthly timeseries.\n", - " hspf = hspf[\"M\"]\n", - "\n", - " # Now read the corresponding HSP2 data and comvert to monthly\n", - " path = \"/RESULTS/PERLND\" + \"_P\" + \"{:0>3s}\".format(str(pls)) + \"/PWATER\"\n", - " if how == \"sum\":\n", - " hsp2 = pd.read_hdf(hdfname, path)[name].resample(\"M\").sum()\n", - " elif how == \"last\":\n", - " hsp2 = pd.read_hdf(hdfname, path)[name].resample(\"M\").last()\n", - "\n", - " plt.figure(figsize=(16, 8))\n", - " plt.plot(hspf.index, hspf, label=\"HSPF\", color=\"r\")\n", - " plt.plot(hsp2.index, hsp2, label=\"HSP2\", color=\"b\", linestyle=\"--\")\n", - " plt.legend()\n", - " plt.title(\"PERLND \" + \"P\" + \"{:0>3s}\".format(str(pls)) + \", PWATER \" + name)\n", - "\n", - " return hspf, hsp2" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER AGWO" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.585131Z", - "iopub.status.idle": "2024-04-26T01:48:56.585238Z", - "shell.execute_reply": "2024-04-26T01:48:56.585188Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.585183Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, \"AGWO\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.585742Z", - "iopub.status.idle": "2024-04-26T01:48:56.586151Z", - "shell.execute_reply": "2024-04-26T01:48:56.586065Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.586054Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER BASET" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.586640Z", - "iopub.status.idle": "2024-04-26T01:48:56.586812Z", - "shell.execute_reply": "2024-04-26T01:48:56.586743Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.586734Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, \"BASET\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.588417Z", - "iopub.status.idle": "2024-04-26T01:48:56.588717Z", - "shell.execute_reply": "2024-04-26T01:48:56.588624Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.588614Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### PERLND PWATER CEPE" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.589294Z", - "iopub.status.idle": "2024-04-26T01:48:56.589452Z", - "shell.execute_reply": "2024-04-26T01:48:56.589384Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.589378Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, \"CEPE\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.589817Z", - "iopub.status.idle": "2024-04-26T01:48:56.589955Z", - "shell.execute_reply": "2024-04-26T01:48:56.589890Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.589884Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER IFWI" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.590363Z", - "iopub.status.idle": "2024-04-26T01:48:56.590497Z", - "shell.execute_reply": "2024-04-26T01:48:56.590434Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.590428Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, \"IFWI\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.590957Z", - "iopub.status.idle": "2024-04-26T01:48:56.591069Z", - "shell.execute_reply": "2024-04-26T01:48:56.591017Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.591011Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER IFWO" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.591592Z", - "iopub.status.idle": "2024-04-26T01:48:56.591730Z", - "shell.execute_reply": "2024-04-26T01:48:56.591664Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.591658Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, \"IFWO\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.592185Z", - "iopub.status.idle": "2024-04-26T01:48:56.592326Z", - "shell.execute_reply": "2024-04-26T01:48:56.592260Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.592254Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER IGWI" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.592705Z", - "iopub.status.idle": "2024-04-26T01:48:56.592817Z", - "shell.execute_reply": "2024-04-26T01:48:56.592766Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.592760Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, \"IGWI\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.593228Z", - "iopub.status.idle": "2024-04-26T01:48:56.593353Z", - "shell.execute_reply": "2024-04-26T01:48:56.593287Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.593280Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER INFIL" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.594170Z", - "iopub.status.idle": "2024-04-26T01:48:56.594369Z", - "shell.execute_reply": "2024-04-26T01:48:56.594300Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.594293Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, \"INFIL\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.594832Z", - "iopub.status.idle": "2024-04-26T01:48:56.595272Z", - "shell.execute_reply": "2024-04-26T01:48:56.595160Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.595149Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER LZET" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.595768Z", - "iopub.status.idle": "2024-04-26T01:48:56.595995Z", - "shell.execute_reply": "2024-04-26T01:48:56.595887Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.595876Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, \"LZET\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.596573Z", - "iopub.status.idle": "2024-04-26T01:48:56.596757Z", - "shell.execute_reply": "2024-04-26T01:48:56.596673Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.596664Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER PERC" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.597129Z", - "iopub.status.idle": "2024-04-26T01:48:56.597299Z", - "shell.execute_reply": "2024-04-26T01:48:56.597218Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.597210Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, \"PERC\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.597912Z", - "iopub.status.idle": "2024-04-26T01:48:56.598169Z", - "shell.execute_reply": "2024-04-26T01:48:56.598085Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.598077Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER PERO" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.598596Z", - "iopub.status.idle": "2024-04-26T01:48:56.598774Z", - "shell.execute_reply": "2024-04-26T01:48:56.598688Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.598680Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, \"PERO\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.599335Z", - "iopub.status.idle": "2024-04-26T01:48:56.599503Z", - "shell.execute_reply": "2024-04-26T01:48:56.599423Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.599415Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER PERS" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.600009Z", - "iopub.status.idle": "2024-04-26T01:48:56.600192Z", - "shell.execute_reply": "2024-04-26T01:48:56.600098Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.600090Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, \"PERS\", \"last\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.600770Z", - "iopub.status.idle": "2024-04-26T01:48:56.600942Z", - "shell.execute_reply": "2024-04-26T01:48:56.600859Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.600852Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER PET" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.601759Z", - "iopub.status.idle": "2024-04-26T01:48:56.601984Z", - "shell.execute_reply": "2024-04-26T01:48:56.601901Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.601893Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, \"PET\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.602414Z", - "iopub.status.idle": "2024-04-26T01:48:56.602582Z", - "shell.execute_reply": "2024-04-26T01:48:56.602503Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.602495Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - } - }, - "source": [ - "#### PERLND PWATER SUPY" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.603013Z", - "iopub.status.idle": "2024-04-26T01:48:56.603200Z", - "shell.execute_reply": "2024-04-26T01:48:56.603108Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.603099Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, \"SUPY\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.603882Z", - "iopub.status.idle": "2024-04-26T01:48:56.604080Z", - "shell.execute_reply": "2024-04-26T01:48:56.603994Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.603986Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER SURO" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.604721Z", - "iopub.status.idle": "2024-04-26T01:48:56.604884Z", - "shell.execute_reply": "2024-04-26T01:48:56.604815Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.604808Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, \"SURO\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.605318Z", - "iopub.status.idle": "2024-04-26T01:48:56.605446Z", - "shell.execute_reply": "2024-04-26T01:48:56.605389Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.605383Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER TAET" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.605829Z", - "iopub.status.idle": "2024-04-26T01:48:56.605974Z", - "shell.execute_reply": "2024-04-26T01:48:56.605904Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.605898Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, \"TAET\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.606654Z", - "iopub.status.idle": "2024-04-26T01:48:56.606884Z", - "shell.execute_reply": "2024-04-26T01:48:56.606775Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.606766Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER UZET" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.607728Z", - "iopub.status.idle": "2024-04-26T01:48:56.608020Z", - "shell.execute_reply": "2024-04-26T01:48:56.607887Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.607873Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, \"UZET\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.608595Z", - "iopub.status.idle": "2024-04-26T01:48:56.608740Z", - "shell.execute_reply": "2024-04-26T01:48:56.608677Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.608671Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER UZI" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.609227Z", - "iopub.status.idle": "2024-04-26T01:48:56.609346Z", - "shell.execute_reply": "2024-04-26T01:48:56.609290Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.609284Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = per(pls, \"UZI\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.609606Z", - "iopub.status.idle": "2024-04-26T01:48:56.609744Z", - "shell.execute_reply": "2024-04-26T01:48:56.609679Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.609672Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## RCHRES" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Automate checking RCHRESs for ROVOL" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.610125Z", - "iopub.status.idle": "2024-04-26T01:48:56.610258Z", - "shell.execute_reply": "2024-04-26T01:48:56.610198Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.610193Z" - } - }, - "outputs": [], - "source": [ - "# With Large HBNs this currently takes a while (need to speed up the HBN Read)\n", - "segments = []\n", - "for operation, segment, optype, variable, freq in keys:\n", - " if (\n", - " str(operation) == \"RCHRES\"\n", - " and str(optype) == \"HYDR\"\n", - " and str(variable) == \"ROVOL\"\n", - " and freq == 4\n", - " ):\n", - " segments.append(str(segment))\n", - "\n", - "dfrchres = pd.DataFrame()\n", - "for seg in segments:\n", - " string = \"RCHRES,\" + seg + \",HYDR,ROVOL\"\n", - " hspf, units_flag = HSP2tools.get_HBNdata(hbnname, string)\n", - " hspf = hspf[\"M\"].values\n", - "\n", - " string = \"RESULTS/RCHRES\" + \"_R\" + \"{:0>3s}\".format(str(seg)) + \"/HYDR\"\n", - " hsp2 = pd.read_hdf(hdfname, string)[\"ROVOL\"]\n", - " hsp2 = hsp2.resample(\"M\").sum().values\n", - "\n", - " dfrchres.at[seg, \"Max Diff\"] = (hspf - hsp2).max()\n", - " dfrchres.at[seg, \"Sum of HSPF\"] = hspf.sum()\n", - " dfrchres.at[seg, \"Sum of HSP2\"] = hsp2.sum()\n", - " dfrchres.at[seg, \"%diff of Sum\"] = 100.0 * (hspf.sum() - hsp2.sum()) / hspf.sum()\n", - " dfrchres.at[seg, \"abs(%diff of Sum)\"] = (\n", - " 100.0 * abs(hspf.sum() - hsp2.sum()) / hspf.sum()\n", - " )\n", - "\n", - "dfrchres = dfrchres.sort_values(by=[\"abs(%diff of Sum)\"])\n", - "dfrchres" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.610923Z", - "iopub.status.idle": "2024-04-26T01:48:56.611101Z", - "shell.execute_reply": "2024-04-26T01:48:56.611036Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.611029Z" - } - }, - "outputs": [], - "source": [ - "dfrchres[\"%diff of Sum\"].describe()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The RCHRES segments are ordered in assending \"abs(%diff of Sum)\", so the last entry is the worst case (by this measure.)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.611633Z", - "iopub.status.idle": "2024-04-26T01:48:56.611867Z", - "shell.execute_reply": "2024-04-26T01:48:56.611766Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.611756Z" - } - }, - "outputs": [], - "source": [ - "rid = dfrchres.index[-1]\n", - "print(\"WORST RCHRES SEGMENT IS \", rid)\n", - "print(\"%diff of the total ROVOL sum of\", dfrchres.loc[rid, \"%diff of Sum\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Define routine to read HSPF and HSP2, plot together for RCHRES" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.612743Z", - "iopub.status.idle": "2024-04-26T01:48:56.612890Z", - "shell.execute_reply": "2024-04-26T01:48:56.612831Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.612825Z" - } - }, - "outputs": [], - "source": [ - "def rch(rid, name, how=\"sum\"):\n", - " # Use Tim Cera's HBN reader to get the HSPF data\n", - " path = \"RCHRES,\" + str(rid) + \",HYDR,\" + name\n", - " hspf, units_flag = HSP2tools.get_HBNdata(hbnname, path)\n", - " # There may be both monthly and annual timeseries available. Get the monthly timeseries.\n", - " hspf = hspf[\"M\"]\n", - "\n", - " # Now read the corresponding HSP2 data and comvert to monthly\n", - " path = \"/RESULTS/RCHRES\" + \"_R\" + \"{:0>3s}\".format(str(rid)) + \"/HYDR\"\n", - " if how == \"sum\":\n", - " hsp2 = pd.read_hdf(hdfname, path)[name].resample(\"M\").sum()\n", - " elif how == \"last\":\n", - " hsp2 = pd.read_hdf(hdfname, path)[name].resample(\"M\").last()\n", - "\n", - " plt.figure(figsize=(16, 8))\n", - " plt.plot(hspf.index, hspf, label=\"HSPF\", color=\"r\")\n", - " plt.plot(hsp2.index, hsp2, label=\"HSP2\", color=\"b\", linestyle=\"--\")\n", - " plt.legend()\n", - " plt.title(\"RCHRES \" + \"R\" + \"{:0>3s}\".format(str(rid)) + \", HYDR \" + name)\n", - "\n", - " return hspf, hsp2" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### RCHRES HYDR IVOL" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.613459Z", - "iopub.status.idle": "2024-04-26T01:48:56.613600Z", - "shell.execute_reply": "2024-04-26T01:48:56.613536Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.613530Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = rch(rid, \"IVOL\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.614093Z", - "iopub.status.idle": "2024-04-26T01:48:56.614237Z", - "shell.execute_reply": "2024-04-26T01:48:56.614172Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.614166Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### RCHRES HYDR PRSUPY" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.614641Z", - "iopub.status.idle": "2024-04-26T01:48:56.614835Z", - "shell.execute_reply": "2024-04-26T01:48:56.614743Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.614734Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = rch(rid, \"PRSUPY\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.615194Z", - "iopub.status.idle": "2024-04-26T01:48:56.615349Z", - "shell.execute_reply": "2024-04-26T01:48:56.615276Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.615269Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### RCHRES HYDR ROVOL" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.615755Z", - "iopub.status.idle": "2024-04-26T01:48:56.615904Z", - "shell.execute_reply": "2024-04-26T01:48:56.615834Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.615827Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = rch(rid, \"ROVOL\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.616294Z", - "iopub.status.idle": "2024-04-26T01:48:56.616433Z", - "shell.execute_reply": "2024-04-26T01:48:56.616368Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.616362Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### RCHRES HYDR VOL" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.616710Z", - "iopub.status.idle": "2024-04-26T01:48:56.616842Z", - "shell.execute_reply": "2024-04-26T01:48:56.616778Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.616772Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = rch(rid, \"VOL\", \"last\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.617154Z", - "iopub.status.idle": "2024-04-26T01:48:56.617293Z", - "shell.execute_reply": "2024-04-26T01:48:56.617227Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.617220Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### RCHRES HYDR VOLEV" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.617656Z", - "iopub.status.idle": "2024-04-26T01:48:56.617788Z", - "shell.execute_reply": "2024-04-26T01:48:56.617724Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.617718Z" - } - }, - "outputs": [], - "source": [ - "hspf, hsp2 = rch(rid, \"VOLEV\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-04-26T01:48:56.618107Z", - "iopub.status.idle": "2024-04-26T01:48:56.618232Z", - "shell.execute_reply": "2024-04-26T01:48:56.618172Z", - "shell.execute_reply.started": "2024-04-26T01:48:56.618166Z" - } - }, - "outputs": [], - "source": [ - "plt.scatter(hspf, hsp2)\n", - "top = 1.05 * max(hspf.max(), hsp2.max())\n", - "plt.plot([0.0, top], [0.0, top])" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/tests/GLWACSO/WDM_Testing/rpo772/rpo772.OUT.txt b/tests/GLWACSO/WDM_Testing/rpo772/rpo772.OUT.txt index f7eb471c..a7491a68 100644 --- a/tests/GLWACSO/WDM_Testing/rpo772/rpo772.OUT.txt +++ b/tests/GLWACSO/WDM_Testing/rpo772/rpo772.OUT.txt @@ -1,7 +1,7 @@ - OUTPUT LEVEL IS BLOCK - UPDATE OPTION IS NO + OUTPUT LEVEL IS BLOCK + UPDATE OPTION IS NO - WDM FILE: rpo772.wdm + WDM FILE: rpo772.wdm MAXREC : 20 FREREC : 15 diff --git a/tests/GLWACSO/WDM_Testing/rpo772/rpo772.exp b/tests/GLWACSO/WDM_Testing/rpo772/rpo772.exp index 39d2c0c5..ae9ec52e 100644 --- a/tests/GLWACSO/WDM_Testing/rpo772/rpo772.exp +++ b/tests/GLWACSO/WDM_Testing/rpo772/rpo772.exp @@ -1,88 +1,88 @@ -DATE -WDMSFL -SYSTEM -COMMENT -END COMMENT +DATE +WDMSFL +SYSTEM +COMMENT +END COMMENT DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 - LABEL - DATCRE 20180725155945 - DATMOD 20201203103319 - TCODE 2 - TSSTEP 15 - IDSCEN RPO_SWMM - IDLOCN RCH472 - IDCONS PO4P - TSTYPE PO4P - TGROUP 6 - COMPFG 1 - TSFORM 1 - TSFILL -999.0 - VBTIME 2 - TSBYR 2000 - DESCRP - - NONZRO 20640 - NUMZRO 0 - MAXVAL 2186.987 - MINVAL 36.72578 - MEANVL 63.24305 - STDDEV 141.3873 - SKEWCF 9.005717 - END LABEL + LABEL + DATCRE 20180725155945 + DATMOD 20201203103319 + TCODE 2 + TSSTEP 15 + IDSCEN RPO_SWMM + IDLOCN RCH472 + IDCONS PO4P + TSTYPE PO4P + TGROUP 6 + COMPFG 1 + TSFORM 1 + TSFILL -999.0 + VBTIME 2 + TSBYR 2000 + DESCRP + + NONZRO 20640 + NUMZRO 0 + MAXVAL 2186.987 + MINVAL 36.72578 + MEANVL 63.24305 + STDDEV 141.3873 + SKEWCF 9.005717 + END LABEL DATA STARTS: 2004 3 31 0 0 0 ENDS: 2017 10 31 24 0 0 - 2004 3 30 24 0 0 2 15 0 1 0 41.3837 - 2004 3 30 24 15 0 2 15 0 169 1 0.00000 - 2004 4 1 18 30 0 2 15 0 6 0 8.480000E-020.166700 - 0.167000 0.166700 0.166500 0.166200 + 2004 3 30 24 0 0 2 15 0 1 0 41.3837 + 2004 3 30 24 15 0 2 15 0 169 1 0.00000 + 2004 4 1 18 30 0 2 15 0 6 0 8.480000E-020.166700 + 0.167000 0.166700 0.166500 0.166200 2004 4 1 20 0 0 2 15 0 2 0 6.600000E-033.000000E-04 - 2004 4 1 20 30 0 2 15 0 1060 1 0.00000 - 2004 4 12 21 30 0 2 15 0 21 0 8.950000E-020.176000 - 0.176300 0.175800 0.175100 0.173800 0.171500 0.167900 - 0.163800 0.159700 0.156300 0.153800 0.151700 0.149700 + 2004 4 1 20 30 0 2 15 0 1060 1 0.00000 + 2004 4 12 21 30 0 2 15 0 21 0 8.950000E-020.176000 + 0.176300 0.175800 0.175100 0.173800 0.171500 0.167900 + 0.163800 0.159700 0.156300 0.153800 0.151700 0.149700 0.148300 0.147800 2.700000E-022.300000E-039.000000E-045.000000E-04 3.000000E-04 2004 4 13 2 45 0 2 15 0 2 1 2.000000E-04 2004 4 13 3 15 0 2 15 0 2 1 1.000000E-04 - 2004 4 13 3 45 0 2 15 0 751 1 0.00000 + 2004 4 13 3 45 0 2 15 0 751 1 0.00000 2004 4 20 23 30 0 2 15 0 1 0 8.290000E-02 - 2004 4 20 23 45 0 2 15 0 2 1 0.162900 - 2004 4 21 0 15 0 2 15 0 15 0 0.161000 0.157200 - 0.152500 0.145900 0.136600 0.127300 0.118600 0.113300 + 2004 4 20 23 45 0 2 15 0 2 1 0.162900 + 2004 4 21 0 15 0 2 15 0 15 0 0.161000 0.157200 + 0.152500 0.145900 0.136600 0.127300 0.118600 0.113300 0.111900 0.111500 1.890000E-021.300000E-035.000000E-043.000000E-04 2.000000E-04 2004 4 21 4 0 0 2 15 0 3 1 1.000000E-04 - 2004 4 21 4 45 0 2 15 0 38 1 0.00000 - 2004 4 21 14 15 0 2 15 0 6 0 0.113000 0.113800 + 2004 4 21 4 45 0 2 15 0 38 1 0.00000 + 2004 4 21 14 15 0 2 15 0 6 0 0.113000 0.113800 0.113400 6.570000E-021.600000E-031.000000E-04 - 2004 4 21 15 45 0 2 15 0 2 1 0.00000 - 2004 4 21 16 15 0 2 15 0 9 0 6.760000E-020.113100 + 2004 4 21 15 45 0 2 15 0 2 1 0.00000 + 2004 4 21 16 15 0 2 15 0 9 0 6.760000E-020.113100 0.112800 0.112400 1.950000E-021.400000E-035.000000E-043.000000E-04 2.000000E-04 2004 4 21 18 30 0 2 15 0 3 1 1.000000E-04 - 2004 4 21 19 15 0 2 15 0 313 1 0.00000 - 2004 4 25 1 30 0 2 15 0 4 0 6.560000E-020.128900 + 2004 4 21 19 15 0 2 15 0 313 1 0.00000 + 2004 4 25 1 30 0 2 15 0 4 0 6.560000E-020.128900 5.600000E-033.000000E-04 - 2004 4 25 2 30 0 2 15 0 10 1 0.00000 - 2004 4 25 5 0 0 2 15 0 12 0 0.129300 0.125900 - 0.119100 0.111800 0.107000 0.105100 0.104100 0.103300 + 2004 4 25 2 30 0 2 15 0 10 1 0.00000 + 2004 4 25 5 0 0 2 15 0 12 0 0.129300 0.125900 + 0.119100 0.111800 0.107000 0.105100 0.104100 0.103300 0.102700 6.110000E-022.200000E-035.000000E-04 2004 4 25 8 0 0 2 15 0 2 1 2.000000E-04 2004 4 25 8 30 0 2 15 0 2 1 1.000000E-04 - 2004 4 25 9 0 0 2 15 0 15 0 0.102100 0.101600 + 2004 4 25 9 0 0 2 15 0 15 0 0.102100 0.101600 9.950000E-029.710000E-029.500000E-029.360000E-029.230000E-029.110000E-02 9.020000E-028.990000E-021.640000E-021.400000E-035.000000E-043.000000E-04 2.000000E-04 2004 4 25 12 45 0 2 15 0 3 1 1.000000E-04 - 2004 4 25 13 30 0 2 15 0 100 1 0.00000 + 2004 4 25 13 30 0 2 15 0 100 1 0.00000 2004 4 26 14 30 0 2 15 0 4 0 4.990000E-029.810000E-02 4.200000E-032.000000E-04 - 2004 4 26 15 30 0 2 15 0 430 1 0.00000 - 2004 5 1 3 0 0 2 15 0 20 0 0.121600 0.105100 + 2004 4 26 15 30 0 2 15 0 430 1 0.00000 + 2004 5 1 3 0 0 2 15 0 20 0 0.121600 0.105100 8.820000E-027.390000E-026.500000E-026.050000E-025.660000E-025.310000E-02 5.050000E-024.890000E-024.760000E-024.640000E-024.550000E-024.490000E-02 4.460000E-024.420000E-024.400000E-027.100000E-036.000000E-042.000000E-04 2004 5 1 8 0 0 2 15 0 3 1 1.000000E-04 - 2004 5 1 8 45 0 2 15 0 25 1 0.00000 + 2004 5 1 8 45 0 2 15 0 25 1 0.00000 2004 5 1 15 0 0 2 15 0 68 0 4.650000E-024.790000E-02 4.770000E-024.730000E-024.680000E-024.640000E-024.610000E-024.570000E-02 4.540000E-024.520000E-024.490000E-024.460000E-024.360000E-024.130000E-02 @@ -105,7 +105,7 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2004 5 2 11 30 0 2 15 0 2 1 4.800000E-03 2004 5 2 12 0 0 2 15 0 2 1 4.700000E-03 2004 5 2 12 30 0 2 15 0 2 0 3.000000E-041.000000E-04 - 2004 5 2 13 0 0 2 15 0 428 1 0.00000 + 2004 5 2 13 0 0 2 15 0 428 1 0.00000 2004 5 6 24 0 0 2 15 0 10 0 6.470000E-026.170000E-02 5.710000E-025.260000E-024.990000E-024.920000E-024.900000E-022.500000E-03 4.000000E-042.000000E-04 @@ -114,21 +114,21 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 3.330000E-022.770000E-022.490000E-022.440000E-022.430000E-023.900000E-03 3.000000E-04 2004 5 7 5 15 0 2 15 0 2 1 1.000000E-04 - 2004 5 7 5 45 0 2 15 0 73 1 0.00000 + 2004 5 7 5 45 0 2 15 0 73 1 0.00000 2004 5 7 24 0 0 2 15 0 13 0 3.540000E-023.450000E-02 3.260000E-023.060000E-022.910000E-022.800000E-022.710000E-022.620000E-02 2.570000E-022.550000E-021.550000E-028.000000E-043.000000E-04 2004 5 8 3 15 0 2 15 0 3 1 1.000000E-04 - 2004 5 8 4 0 0 2 15 0 10 1 0.00000 + 2004 5 8 4 0 0 2 15 0 10 1 0.00000 2004 5 8 6 30 0 2 15 0 4 0 1.410000E-022.770000E-02 1.300000E-031.000000E-04 - 2004 5 8 7 30 0 2 15 0 70 1 0.00000 + 2004 5 8 7 30 0 2 15 0 70 1 0.00000 2004 5 9 1 0 0 2 15 0 16 0 3.700000E-023.810000E-02 3.800000E-023.770000E-023.720000E-023.650000E-023.580000E-023.520000E-02 3.460000E-023.430000E-023.400000E-023.380000E-023.360000E-025.500000E-03 4.000000E-042.000000E-04 2004 5 9 5 0 0 2 15 0 2 1 1.000000E-04 - 2004 5 9 5 30 0 2 15 0 54 1 0.00000 + 2004 5 9 5 30 0 2 15 0 54 1 0.00000 2004 5 9 19 0 0 2 15 0 31 0 4.150000E-023.930000E-02 3.610000E-023.300000E-023.110000E-023.050000E-023.020000E-022.990000E-02 2.690000E-022.070000E-021.580000E-021.200000E-029.500000E-037.900000E-03 @@ -140,28 +140,28 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2004 5 10 4 15 0 2 15 0 2 1 2.100000E-03 2004 5 10 4 45 0 2 15 0 3 1 2.000000E-03 2004 5 10 5 30 0 2 15 0 1 0 3.000000E-04 - 2004 5 10 5 45 0 2 15 0 55 1 0.00000 + 2004 5 10 5 45 0 2 15 0 55 1 0.00000 2004 5 10 19 30 0 2 15 0 3 0 5.900000E-031.160000E-02 5.000000E-04 - 2004 5 10 20 15 0 2 15 0 11 1 0.00000 + 2004 5 10 20 15 0 2 15 0 11 1 0.00000 2004 5 10 23 0 0 2 15 0 9 0 1.360000E-021.340000E-02 1.300000E-021.250000E-021.210000E-021.200000E-027.000000E-032.000000E-04 1.000000E-04 - 2004 5 11 1 15 0 2 15 0 3 1 0.00000 + 2004 5 11 1 15 0 2 15 0 3 1 0.00000 2004 5 11 2 0 0 2 15 0 8 0 1.280000E-021.250000E-02 1.210000E-021.170000E-021.130000E-021.110000E-021.100000E-021.080000E-02 2004 5 11 4 0 0 2 15 0 2 1 1.070000E-02 2004 5 11 4 30 0 2 15 0 1 0 7.000000E-04 2004 5 11 4 45 0 2 15 0 2 1 1.000000E-04 - 2004 5 11 5 15 0 2 15 0 236 1 0.00000 + 2004 5 11 5 15 0 2 15 0 236 1 0.00000 2004 5 13 16 15 0 2 15 0 6 0 4.570000E-024.600000E-02 4.590000E-022.700000E-028.000000E-041.000000E-04 - 2004 5 13 17 45 0 2 15 0 10 1 0.00000 + 2004 5 13 17 45 0 2 15 0 10 1 0.00000 2004 5 13 20 15 0 2 15 0 9 0 4.690000E-024.720000E-02 4.700000E-024.670000E-022.870000E-021.500000E-035.000000E-043.000000E-04 2.000000E-04 2004 5 13 22 30 0 2 15 0 3 1 1.000000E-04 - 2004 5 13 23 15 0 2 15 0 63 1 0.00000 + 2004 5 13 23 15 0 2 15 0 63 1 0.00000 2004 5 14 15 0 0 2 15 0 14 0 5.510000E-025.260000E-02 4.870000E-024.480000E-024.220000E-024.100000E-024.010000E-023.930000E-02 3.880000E-023.860000E-027.000000E-037.000000E-043.000000E-042.000000E-04 @@ -171,25 +171,25 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 3.210000E-023.170000E-023.150000E-023.120000E-023.110000E-025.000000E-03 4.000000E-04 2004 5 14 22 45 0 2 15 0 3 1 1.000000E-04 - 2004 5 14 23 30 0 2 15 0 250 1 0.00000 + 2004 5 14 23 30 0 2 15 0 250 1 0.00000 2004 5 17 14 0 0 2 15 0 18 0 6.370000E-026.270000E-02 6.020000E-025.730000E-025.420000E-025.090000E-024.780000E-024.480000E-02 4.250000E-024.100000E-023.960000E-023.840000E-023.750000E-023.730000E-02 2.270000E-021.100000E-034.000000E-042.000000E-04 2004 5 17 18 30 0 2 15 0 4 1 1.000000E-04 - 2004 5 17 19 30 0 2 15 0 306 1 0.00000 + 2004 5 17 19 30 0 2 15 0 306 1 0.00000 2004 5 20 24 0 0 2 15 0 11 0 6.480000E-024.270000E-02 2.760000E-021.780000E-021.250000E-029.400000E-037.000000E-035.100000E-03 4.100000E-033.900000E-033.800000E-03 2004 5 21 2 45 0 2 15 0 2 1 3.700000E-03 2004 5 21 3 15 0 2 15 0 2 0 3.600000E-036.000000E-04 - 2004 5 21 3 45 0 2 15 0 41 1 0.00000 + 2004 5 21 3 45 0 2 15 0 41 1 0.00000 2004 5 21 14 0 0 2 15 0 4 0 8.800000E-035.000000E-03 2.500000E-031.000000E-03 2004 5 21 15 0 0 2 15 0 2 0 6.000000E-044.000000E-04 2004 5 21 15 30 0 2 15 0 2 1 3.000000E-04 2004 5 21 16 0 0 2 15 0 6 1 2.000000E-04 - 2004 5 21 17 30 0 2 15 0 22 1 0.00000 + 2004 5 21 17 30 0 2 15 0 22 1 0.00000 2004 5 21 23 0 0 2 15 0 4 0 4.000000E-033.800000E-03 3.500000E-033.100000E-03 2004 5 21 24 0 0 2 15 0 3 1 2.900000E-03 @@ -197,65 +197,65 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2004 5 22 1 30 0 2 15 0 4 1 2.700000E-03 2004 5 22 2 30 0 2 15 0 3 1 2.600000E-03 2004 5 22 3 15 0 2 15 0 1 0 4.000000E-04 - 2004 5 22 3 30 0 2 15 0 6 1 0.00000 + 2004 5 22 3 30 0 2 15 0 6 1 0.00000 2004 5 22 5 0 0 2 15 0 2 1 3.800000E-03 2004 5 22 5 30 0 2 15 0 6 0 3.700000E-033.600000E-03 3.100000E-032.300000E-031.600000E-031.200000E-03 2004 5 22 7 0 0 2 15 0 4 1 9.000000E-04 2004 5 22 8 0 0 2 15 0 2 0 8.000000E-045.000000E-04 - 2004 5 22 8 30 0 2 15 0 58 1 0.00000 + 2004 5 22 8 30 0 2 15 0 58 1 0.00000 2004 5 22 23 0 0 2 15 0 5 0 1.090000E-021.050000E-02 9.700000E-039.000000E-038.600000E-03 2004 5 23 0 15 0 2 15 0 2 1 8.500000E-03 2004 5 23 0 45 0 2 15 0 2 0 5.000000E-041.000000E-04 - 2004 5 23 1 15 0 2 15 0 67 1 0.00000 + 2004 5 23 1 15 0 2 15 0 67 1 0.00000 2004 5 23 18 0 0 2 15 0 12 0 1.910000E-021.610000E-02 1.330000E-021.090000E-028.500000E-036.200000E-034.400000E-033.000000E-03 2.400000E-032.300000E-032.200000E-031.400000E-03 2004 5 23 21 0 0 2 15 0 3 1 2.300000E-03 2004 5 23 21 45 0 2 15 0 3 1 2.200000E-03 - 2004 5 23 22 30 0 2 15 0 3 0 1.000000E-04 0.00000 + 2004 5 23 22 30 0 2 15 0 3 0 1.000000E-04 0.00000 1.700000E-03 2004 5 23 23 15 0 2 15 0 2 1 2.700000E-03 2004 5 23 23 45 0 2 15 0 2 1 2.600000E-03 2004 5 24 0 15 0 2 15 0 2 0 5.000000E-041.000000E-04 - 2004 5 24 0 45 0 2 15 0 5 1 0.00000 + 2004 5 24 0 45 0 2 15 0 5 1 0.00000 2004 5 24 2 0 0 2 15 0 4 0 3.400000E-032.600000E-03 1.900000E-031.300000E-03 2004 5 24 3 0 0 2 15 0 5 1 1.000000E-03 2004 5 24 4 15 0 2 15 0 1 0 6.000000E-04 - 2004 5 24 4 30 0 2 15 0 114 1 0.00000 + 2004 5 24 4 30 0 2 15 0 114 1 0.00000 2004 5 25 9 0 0 2 15 0 8 0 1.970000E-022.010000E-02 1.990000E-021.960000E-021.930000E-021.920000E-023.200000E-033.000000E-04 2004 5 25 11 0 0 2 15 0 2 1 1.000000E-04 - 2004 5 25 11 30 0 2 15 0 196 1 0.00000 + 2004 5 25 11 30 0 2 15 0 196 1 0.00000 2004 5 27 12 30 0 2 15 0 3 0 2.430000E-024.770000E-02 4.780000E-02 2004 5 27 13 15 0 2 15 0 2 1 4.770000E-02 2004 5 27 13 45 0 2 15 0 3 0 4.760000E-022.000000E-03 1.000000E-04 - 2004 5 27 14 30 0 2 15 0 302 1 0.00000 + 2004 5 27 14 30 0 2 15 0 302 1 0.00000 2004 5 30 18 0 0 2 15 0 18 0 8.110000E-027.980000E-02 7.670000E-027.300000E-026.910000E-026.480000E-026.080000E-025.700000E-02 5.440000E-025.330000E-025.240000E-025.170000E-025.120000E-025.110000E-02 3.200000E-036.000000E-043.000000E-042.000000E-04 2004 5 30 22 30 0 2 15 0 3 1 1.000000E-04 - 2004 5 30 23 15 0 2 15 0 13 1 0.00000 + 2004 5 30 23 15 0 2 15 0 13 1 0.00000 2004 5 31 2 30 0 2 15 0 4 0 2.720000E-025.340000E-02 2.500000E-032.000000E-04 - 2004 5 31 3 30 0 2 15 0 15 1 0.00000 + 2004 5 31 3 30 0 2 15 0 15 1 0.00000 2004 5 31 7 15 0 2 15 0 6 0 5.500000E-025.540000E-02 5.520000E-023.250000E-029.000000E-041.000000E-04 - 2004 5 31 8 45 0 2 15 0 9 1 0.00000 + 2004 5 31 8 45 0 2 15 0 9 1 0.00000 2004 5 31 11 0 0 2 15 0 12 0 5.640000E-025.570000E-02 5.400000E-025.210000E-025.060000E-024.990000E-024.950000E-024.910000E-02 4.890000E-027.800000E-036.000000E-042.000000E-04 2004 5 31 14 0 0 2 15 0 3 1 1.000000E-04 - 2004 5 31 14 45 0 2 15 0 131 1 0.00000 + 2004 5 31 14 45 0 2 15 0 131 1 0.00000 2004 6 1 23 30 0 2 15 0 4 0 3.300000E-026.490000E-02 3.300000E-033.000000E-04 2004 6 2 0 30 0 2 15 0 2 1 1.000000E-04 - 2004 6 2 1 0 0 2 15 0 52 1 0.00000 + 2004 6 2 1 0 0 2 15 0 52 1 0.00000 2004 6 2 14 0 0 2 15 0 29 0 6.970000E-026.200000E-02 5.350000E-024.600000E-024.190000E-024.070000E-024.000000E-023.950000E-02 3.880000E-023.790000E-023.700000E-023.610000E-023.550000E-023.530000E-02 @@ -264,22 +264,22 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 1.000000E-035.000000E-043.000000E-04 2004 6 2 21 15 0 2 15 0 2 1 2.000000E-04 2004 6 2 21 45 0 2 15 0 2 1 1.000000E-04 - 2004 6 2 22 15 0 2 15 0 17 1 0.00000 + 2004 6 2 22 15 0 2 15 0 17 1 0.00000 2004 6 3 2 30 0 2 15 0 3 0 1.590000E-023.130000E-02 1.600000E-03 2004 6 3 3 15 0 2 15 0 2 1 1.000000E-04 - 2004 6 3 3 45 0 2 15 0 615 1 0.00000 + 2004 6 3 3 45 0 2 15 0 615 1 0.00000 2004 6 9 13 30 0 2 15 0 16 0 4.970000E-029.770000E-02 8.520000E-025.850000E-023.940000E-022.660000E-022.110000E-021.970000E-02 1.870000E-021.770000E-021.710000E-021.700000E-021.060000E-028.000000E-04 3.000000E-042.000000E-04 2004 6 9 17 30 0 2 15 0 3 1 1.000000E-04 - 2004 6 9 18 15 0 2 15 0 3 1 0.00000 + 2004 6 9 18 15 0 2 15 0 3 1 0.00000 2004 6 9 19 0 0 2 15 0 12 0 1.800000E-021.610000E-02 1.410000E-021.230000E-021.120000E-021.070000E-021.030000E-021.000000E-02 9.800000E-039.700000E-031.800000E-033.000000E-04 2004 6 9 22 0 0 2 15 0 2 1 1.000000E-04 - 2004 6 9 22 30 0 2 15 0 10 1 0.00000 + 2004 6 9 22 30 0 2 15 0 10 1 0.00000 2004 6 10 1 0 0 2 15 0 8 0 1.200000E-021.190000E-02 1.150000E-021.110000E-021.080000E-021.070000E-021.060000E-021.050000E-02 2004 6 10 3 0 0 2 15 0 2 1 1.040000E-02 @@ -290,7 +290,7 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2004 6 10 6 15 0 2 15 0 3 0 1.900000E-034.000000E-04 2.000000E-04 2004 6 10 7 0 0 2 15 0 3 1 1.000000E-04 - 2004 6 10 7 45 0 2 15 0 6 1 0.00000 + 2004 6 10 7 45 0 2 15 0 6 1 0.00000 2004 6 10 9 15 0 2 15 0 9 0 1.080000E-021.090000E-02 1.080000E-021.070000E-021.050000E-021.040000E-021.020000E-021.000000E-02 9.900000E-03 @@ -298,7 +298,7 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2004 6 10 12 0 0 2 15 0 4 0 9.700000E-032.100000E-03 4.000000E-042.000000E-04 2004 6 10 13 0 0 2 15 0 3 1 1.000000E-04 - 2004 6 10 13 45 0 2 15 0 6 1 0.00000 + 2004 6 10 13 45 0 2 15 0 6 1 0.00000 2004 6 10 15 15 0 2 15 0 1 0 1.150000E-02 2004 6 10 15 30 0 2 15 0 2 1 1.160000E-02 2004 6 10 16 0 0 2 15 0 10 0 1.140000E-021.120000E-02 @@ -326,91 +326,91 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2004 6 11 13 15 0 2 15 0 4 1 3.100000E-03 2004 6 11 14 15 0 2 15 0 1 0 7.000000E-04 2004 6 11 14 30 0 2 15 0 2 1 1.000000E-04 - 2004 6 11 15 0 0 2 15 0 70 1 0.00000 + 2004 6 11 15 0 0 2 15 0 70 1 0.00000 2004 6 12 8 30 0 2 15 0 1 0 7.900000E-03 2004 6 12 8 45 0 2 15 0 2 1 1.540000E-02 2004 6 12 9 15 0 2 15 0 8 0 1.520000E-021.490000E-02 1.440000E-021.410000E-021.400000E-022.600000E-034.000000E-042.000000E-04 2004 6 12 11 15 0 2 15 0 3 1 1.000000E-04 - 2004 6 12 12 0 0 2 15 0 126 1 0.00000 + 2004 6 12 12 0 0 2 15 0 126 1 0.00000 2004 6 13 19 30 0 2 15 0 1 0 1.740000E-02 2004 6 13 19 45 0 2 15 0 3 1 3.420000E-02 2004 6 13 20 30 0 2 15 0 8 0 3.400000E-023.380000E-02 3.350000E-022.170000E-022.100000E-039.000000E-045.000000E-043.000000E-04 2004 6 13 22 30 0 2 15 0 2 1 2.000000E-04 2004 6 13 23 0 0 2 15 0 1 0 1.000000E-04 - 2004 6 13 23 15 0 2 15 0 63 1 0.00000 + 2004 6 13 23 15 0 2 15 0 63 1 0.00000 2004 6 14 15 0 0 2 15 0 15 0 4.230000E-024.300000E-02 4.240000E-024.130000E-024.000000E-023.880000E-023.760000E-023.640000E-02 3.560000E-023.540000E-026.600000E-039.000000E-044.000000E-043.000000E-04 2.000000E-04 2004 6 14 18 45 0 2 15 0 3 1 1.000000E-04 - 2004 6 14 19 30 0 2 15 0 176 1 0.00000 + 2004 6 14 19 30 0 2 15 0 176 1 0.00000 2004 6 16 15 30 0 2 15 0 4 0 3.000000E-025.890000E-02 3.000000E-033.000000E-04 2004 6 16 16 30 0 2 15 0 2 1 1.000000E-04 - 2004 6 16 17 0 0 2 15 0 24 1 0.00000 + 2004 6 16 17 0 0 2 15 0 24 1 0.00000 2004 6 16 23 0 0 2 15 0 18 0 6.040000E-026.210000E-02 6.190000E-026.140000E-026.020000E-025.830000E-025.610000E-025.400000E-02 5.230000E-025.110000E-025.010000E-024.910000E-024.850000E-024.830000E-02 3.500000E-031.000000E-035.000000E-043.000000E-04 2004 6 17 3 30 0 2 15 0 2 1 2.000000E-04 2004 6 17 4 0 0 2 15 0 2 1 1.000000E-04 - 2004 6 17 4 30 0 2 15 0 10 1 0.00000 + 2004 6 17 4 30 0 2 15 0 10 1 0.00000 2004 6 17 7 0 0 2 15 0 11 0 4.950000E-025.030000E-02 4.950000E-024.820000E-024.720000E-024.700000E-029.000000E-031.400000E-03 7.000000E-044.000000E-043.000000E-04 2004 6 17 9 45 0 2 15 0 2 1 2.000000E-04 2004 6 17 10 15 0 2 15 0 1 0 1.000000E-04 - 2004 6 17 10 30 0 2 15 0 22 1 0.00000 + 2004 6 17 10 30 0 2 15 0 22 1 0.00000 2004 6 17 16 0 0 2 15 0 12 0 5.040000E-024.810000E-02 4.450000E-024.090000E-023.880000E-023.840000E-023.820000E-023.800000E-03 1.300000E-037.000000E-045.000000E-043.000000E-04 2004 6 17 19 0 0 2 15 0 2 1 2.000000E-04 2004 6 17 19 30 0 2 15 0 1 0 1.000000E-04 - 2004 6 17 19 45 0 2 15 0 359 1 0.00000 + 2004 6 17 19 45 0 2 15 0 359 1 0.00000 2004 6 21 13 30 0 2 15 0 4 0 4.090000E-028.040000E-02 4.100000E-034.000000E-04 2004 6 21 14 30 0 2 15 0 2 1 1.000000E-04 - 2004 6 21 15 0 0 2 15 0 16 1 0.00000 + 2004 6 21 15 0 0 2 15 0 16 1 0.00000 2004 6 21 19 0 0 2 15 0 13 0 8.070000E-028.200000E-02 8.080000E-027.870000E-027.710000E-027.660000E-021.470000E-022.300000E-03 1.100000E-036.000000E-044.000000E-043.000000E-042.000000E-04 2004 6 21 22 15 0 2 15 0 2 1 1.000000E-04 - 2004 6 21 22 45 0 2 15 0 7 1 0.00000 + 2004 6 21 22 45 0 2 15 0 7 1 0.00000 2004 6 22 0 30 0 2 15 0 4 0 3.960000E-027.780000E-02 4.000000E-034.000000E-04 2004 6 22 1 30 0 2 15 0 2 1 1.000000E-04 - 2004 6 22 2 0 0 2 15 0 586 1 0.00000 - 2004 6 28 4 30 0 2 15 0 19 0 6.130000E-020.120600 - 0.120800 0.120600 0.120500 0.120300 0.120000 0.119600 + 2004 6 22 2 0 0 2 15 0 586 1 0.00000 + 2004 6 28 4 30 0 2 15 0 19 0 6.130000E-020.120600 + 0.120800 0.120600 0.120500 0.120300 0.120000 0.119600 0.119100 0.118400 0.118000 7.700000E-031.900000E-039.000000E-04 6.000000E-044.000000E-043.000000E-042.000000E-041.000000E-04 - 2004 6 28 9 15 0 2 15 0 583 1 0.00000 - 2004 7 4 11 0 0 2 15 0 23 0 0.138300 0.142300 - 0.141700 0.140600 0.139100 0.137900 0.136900 0.136000 + 2004 6 28 9 15 0 2 15 0 583 1 0.00000 + 2004 7 4 11 0 0 2 15 0 23 0 0.138300 0.142300 + 0.141700 0.140600 0.139100 0.137900 0.136900 0.136000 0.126400 0.105200 8.640000E-027.090000E-026.340000E-026.220000E-02 6.190000E-027.800000E-033.100000E-031.700000E-031.200000E-038.000000E-04 6.000000E-044.000000E-042.000000E-04 - 2004 7 4 16 45 0 2 15 0 225 1 0.00000 + 2004 7 4 16 45 0 2 15 0 225 1 0.00000 2004 7 7 1 0 0 2 15 0 21 0 8.520000E-028.240000E-02 7.740000E-027.220000E-026.830000E-026.620000E-026.440000E-026.270000E-02 6.150000E-026.080000E-026.030000E-025.980000E-025.960000E-025.700000E-03 2.000000E-031.100000E-037.000000E-045.000000E-044.000000E-042.000000E-04 1.000000E-04 - 2004 7 7 6 15 0 2 15 0 461 1 0.00000 - 2004 7 12 1 30 0 2 15 0 19 0 5.220000E-020.102600 - 0.102800 0.102600 0.102500 0.102300 0.102000 0.101200 + 2004 7 7 6 15 0 2 15 0 461 1 0.00000 + 2004 7 12 1 30 0 2 15 0 19 0 5.220000E-020.102600 + 0.102800 0.102600 0.102500 0.102300 0.102000 0.101200 0.100200 9.900000E-029.820000E-021.790000E-023.100000E-031.400000E-03 9.000000E-046.000000E-045.000000E-044.000000E-042.000000E-04 - 2004 7 12 6 15 0 2 15 0 19 1 0.00000 + 2004 7 12 6 15 0 2 15 0 19 1 0.00000 2004 7 12 11 0 0 2 15 0 8 0 8.040000E-024.540000E-02 2.520000E-021.350000E-029.100000E-038.400000E-038.000000E-037.700000E-03 2004 7 12 13 0 0 2 15 0 2 1 7.400000E-03 2004 7 12 13 30 0 2 15 0 3 0 1.700000E-034.000000E-04 2.000000E-04 2004 7 12 14 15 0 2 15 0 4 1 1.000000E-04 - 2004 7 12 15 15 0 2 15 0 131 1 0.00000 + 2004 7 12 15 15 0 2 15 0 131 1 0.00000 2004 7 13 24 0 0 2 15 0 9 0 2.670000E-021.950000E-02 1.400000E-021.000000E-028.100000E-037.400000E-036.900000E-036.400000E-03 6.100000E-03 @@ -418,7 +418,7 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2004 7 14 2 45 0 2 15 0 2 1 5.900000E-03 2004 7 14 3 15 0 2 15 0 2 0 5.000000E-042.000000E-04 2004 7 14 3 45 0 2 15 0 2 1 1.000000E-04 - 2004 7 14 4 15 0 2 15 0 55 1 0.00000 + 2004 7 14 4 15 0 2 15 0 55 1 0.00000 2004 7 14 18 0 0 2 15 0 4 0 1.540000E-021.580000E-02 1.560000E-021.540000E-02 2004 7 14 19 0 0 2 15 0 2 1 1.510000E-02 @@ -426,7 +426,7 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 5.000000E-043.000000E-04 2004 7 14 20 30 0 2 15 0 2 1 2.000000E-04 2004 7 14 21 0 0 2 15 0 1 0 1.000000E-04 - 2004 7 14 21 15 0 2 15 0 183 1 0.00000 + 2004 7 14 21 15 0 2 15 0 183 1 0.00000 2004 7 16 19 0 0 2 15 0 35 0 4.230000E-024.300000E-02 4.230000E-024.120000E-024.030000E-023.980000E-023.950000E-023.920000E-02 3.900000E-023.700000E-031.300000E-037.000000E-043.890000E-023.910000E-02 @@ -435,37 +435,37 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2.990000E-022.960000E-022.950000E-022.800000E-031.000000E-035.000000E-04 4.000000E-043.000000E-042.000000E-04 2004 7 17 3 45 0 2 15 0 2 1 1.000000E-04 - 2004 7 17 4 15 0 2 15 0 9 1 0.00000 + 2004 7 17 4 15 0 2 15 0 9 1 0.00000 2004 7 17 6 30 0 2 15 0 4 0 1.630000E-023.200000E-02 1.900000E-033.000000E-04 2004 7 17 7 30 0 2 15 0 3 1 1.000000E-04 - 2004 7 17 8 15 0 2 15 0 127 1 0.00000 + 2004 7 17 8 15 0 2 15 0 127 1 0.00000 2004 7 18 16 0 0 2 15 0 17 0 4.910000E-024.400000E-02 3.820000E-023.310000E-022.760000E-022.210000E-021.770000E-021.410000E-02 1.240000E-021.200000E-021.180000E-021.160000E-021.150000E-027.800000E-03 1.200000E-035.000000E-043.000000E-04 2004 7 18 20 15 0 2 15 0 2 1 2.000000E-04 2004 7 18 20 45 0 2 15 0 2 1 1.000000E-04 - 2004 7 18 21 15 0 2 15 0 17 1 0.00000 + 2004 7 18 21 15 0 2 15 0 17 1 0.00000 2004 7 19 1 30 0 2 15 0 3 0 7.900000E-031.550000E-02 9.000000E-04 2004 7 19 2 15 0 2 15 0 2 1 1.000000E-04 - 2004 7 19 2 45 0 2 15 0 123 1 0.00000 + 2004 7 19 2 45 0 2 15 0 123 1 0.00000 2004 7 20 9 30 0 2 15 0 4 0 1.770000E-023.470000E-02 2.100000E-033.000000E-04 2004 7 20 10 30 0 2 15 0 3 1 1.000000E-04 - 2004 7 20 11 15 0 2 15 0 141 1 0.00000 + 2004 7 20 11 15 0 2 15 0 141 1 0.00000 2004 7 21 22 30 0 2 15 0 25 0 2.750000E-025.400000E-02 5.360000E-025.080000E-024.720000E-024.370000E-024.110000E-023.960000E-02 3.830000E-023.710000E-023.590000E-023.480000E-023.370000E-023.260000E-02 3.180000E-023.140000E-023.120000E-023.090000E-023.080000E-022.900000E-03 1.000000E-035.000000E-044.000000E-043.000000E-042.000000E-04 2004 7 22 4 45 0 2 15 0 2 1 1.000000E-04 - 2004 7 22 5 15 0 2 15 0 457 1 0.00000 + 2004 7 22 5 15 0 2 15 0 457 1 0.00000 2004 7 26 23 30 0 2 15 0 6 0 4.310000E-028.470000E-02 5.000000E-037.000000E-043.000000E-042.000000E-04 2004 7 27 1 0 0 2 15 0 3 1 1.000000E-04 - 2004 7 27 1 45 0 2 15 0 7 1 0.00000 + 2004 7 27 1 45 0 2 15 0 7 1 0.00000 2004 7 27 3 30 0 2 15 0 41 0 4.370000E-028.590000E-02 8.530000E-028.140000E-027.610000E-027.090000E-026.470000E-025.740000E-02 5.080000E-024.490000E-024.000000E-023.600000E-023.240000E-022.920000E-02 @@ -475,7 +475,7 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 1.110000E-029.900000E-039.300000E-039.100000E-039.000000E-038.900000E-03 8.800000E-037.000000E-042.000000E-04 2004 7 27 13 45 0 2 15 0 3 1 1.000000E-04 - 2004 7 27 14 30 0 2 15 0 2 1 0.00000 + 2004 7 27 14 30 0 2 15 0 2 1 0.00000 2004 7 27 15 0 0 2 15 0 6 0 1.000000E-029.800000E-03 9.500000E-039.200000E-038.900000E-038.800000E-03 2004 7 27 16 30 0 2 15 0 2 1 8.700000E-03 @@ -503,7 +503,7 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2004 7 28 5 30 0 2 15 0 2 1 5.600000E-03 2004 7 28 6 0 0 2 15 0 2 0 3.400000E-032.000000E-04 2004 7 28 6 30 0 2 15 0 2 1 1.000000E-04 - 2004 7 28 7 0 0 2 15 0 240 1 0.00000 + 2004 7 28 7 0 0 2 15 0 240 1 0.00000 2004 7 30 19 0 0 2 15 0 34 0 4.270000E-024.200000E-02 4.040000E-023.840000E-023.700000E-023.630000E-023.570000E-023.520000E-02 3.480000E-023.430000E-023.390000E-023.350000E-023.310000E-023.260000E-02 @@ -514,19 +514,19 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2004 7 31 3 30 0 2 15 0 8 0 2.540000E-022.490000E-02 2.460000E-021.530000E-021.200000E-035.000000E-043.000000E-042.000000E-04 2004 7 31 5 30 0 2 15 0 3 1 1.000000E-04 - 2004 7 31 6 15 0 2 15 0 9 1 0.00000 + 2004 7 31 6 15 0 2 15 0 9 1 0.00000 2004 7 31 8 30 0 2 15 0 4 0 1.370000E-022.700000E-02 1.600000E-032.000000E-04 2004 7 31 9 30 0 2 15 0 2 1 1.000000E-04 - 2004 7 31 10 0 0 2 15 0 252 1 0.00000 + 2004 7 31 10 0 0 2 15 0 252 1 0.00000 2004 8 3 1 0 0 2 15 0 12 0 4.900000E-022.770000E-02 1.530000E-027.700000E-035.000000E-034.500000E-034.300000E-034.200000E-03 4.100000E-034.000000E-039.000000E-042.000000E-04 2004 8 3 4 0 0 2 15 0 2 1 1.000000E-04 - 2004 8 3 4 30 0 2 15 0 8 1 0.00000 + 2004 8 3 4 30 0 2 15 0 8 1 0.00000 2004 8 3 6 30 0 2 15 0 3 0 3.100000E-036.200000E-03 4.000000E-04 - 2004 8 3 7 15 0 2 15 0 83 1 0.00000 + 2004 8 3 7 15 0 2 15 0 83 1 0.00000 2004 8 4 4 0 0 2 15 0 24 0 1.960000E-021.720000E-02 1.460000E-021.240000E-021.030000E-028.400000E-036.800000E-035.500000E-03 4.800000E-034.700000E-034.600000E-034.500000E-034.400000E-034.100000E-03 @@ -539,58 +539,58 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2004 8 4 12 30 0 2 15 0 2 1 1.300000E-03 2004 8 4 13 0 0 2 15 0 5 1 1.200000E-03 2004 8 4 14 15 0 2 15 0 2 0 8.000000E-041.000000E-04 - 2004 8 4 14 45 0 2 15 0 981 1 0.00000 - 2004 8 14 20 0 0 2 15 0 21 0 0.110000 0.106400 + 2004 8 4 14 45 0 2 15 0 981 1 0.00000 + 2004 8 14 20 0 0 2 15 0 21 0 0.110000 0.106400 9.990000E-029.320000E-028.860000E-028.670000E-028.530000E-028.420000E-02 8.320000E-028.250000E-028.190000E-028.130000E-028.100000E-027.000000E-03 2.300000E-031.200000E-038.000000E-046.000000E-044.000000E-043.000000E-04 2.000000E-04 - 2004 8 15 1 15 0 2 15 0 59 1 0.00000 + 2004 8 15 1 15 0 2 15 0 59 1 0.00000 2004 8 15 16 0 0 2 15 0 18 0 8.690000E-028.620000E-02 8.420000E-028.140000E-027.880000E-027.710000E-027.550000E-027.410000E-02 7.310000E-027.290000E-021.020000E-024.200000E-032.300000E-031.600000E-03 1.100000E-039.000000E-045.000000E-042.000000E-04 - 2004 8 15 20 30 0 2 15 0 32 1 0.00000 + 2004 8 15 20 30 0 2 15 0 32 1 0.00000 2004 8 16 4 30 0 2 15 0 5 0 3.900000E-027.660000E-02 4.400000E-036.000000E-042.000000E-04 2004 8 16 5 45 0 2 15 0 4 1 1.000000E-04 - 2004 8 16 6 45 0 2 15 0 413 1 0.00000 - 2004 8 20 14 0 0 2 15 0 29 0 0.107600 0.110000 + 2004 8 16 6 45 0 2 15 0 413 1 0.00000 + 2004 8 20 14 0 0 2 15 0 29 0 0.107600 0.110000 0.109100 0.107200 0.104400 0.100700 9.700000E-029.340000E-02 9.060000E-028.890000E-028.760000E-028.650000E-028.540000E-028.430000E-02 8.320000E-028.210000E-028.120000E-028.050000E-028.000000E-027.940000E-02 7.910000E-026.900000E-032.300000E-031.200000E-038.000000E-046.000000E-04 4.000000E-043.000000E-042.000000E-04 - 2004 8 20 21 15 0 2 15 0 25 1 0.00000 + 2004 8 20 21 15 0 2 15 0 25 1 0.00000 2004 8 21 3 30 0 2 15 0 6 0 4.170000E-028.190000E-02 4.700000E-036.000000E-043.000000E-042.000000E-04 2004 8 21 5 0 0 2 15 0 3 1 1.000000E-04 - 2004 8 21 5 45 0 2 15 0 453 1 0.00000 - 2004 8 25 23 0 0 2 15 0 12 0 0.113300 0.115800 + 2004 8 21 5 45 0 2 15 0 453 1 0.00000 + 2004 8 25 23 0 0 2 15 0 12 0 0.113300 0.115800 0.114800 0.112800 0.111200 0.110700 1.230000E-024.600000E-03 2.500000E-031.700000E-031.200000E-039.000000E-04 - 2004 8 26 2 0 0 2 15 0 2 1 0.00000 - 2004 8 26 2 30 0 2 15 0 11 0 5.630000E-020.110800 + 2004 8 26 2 0 0 2 15 0 2 1 0.00000 + 2004 8 26 2 30 0 2 15 0 11 0 5.630000E-020.110800 2.490000E-023.200000E-031.400000E-039.000000E-046.000000E-044.000000E-04 3.000000E-042.000000E-041.000000E-04 - 2004 8 26 5 15 0 2 15 0 131 1 0.00000 - 2004 8 27 14 0 0 2 15 0 17 0 0.115400 0.118800 - 0.118300 0.117400 0.116100 0.115100 0.114300 0.113500 + 2004 8 26 5 15 0 2 15 0 131 1 0.00000 + 2004 8 27 14 0 0 2 15 0 17 0 0.115400 0.118800 + 0.118300 0.117400 0.116100 0.115100 0.114300 0.113500 0.113100 9.800000E-033.200000E-031.700000E-031.100000E-038.000000E-04 6.000000E-045.000000E-043.000000E-04 - 2004 8 27 18 15 0 2 15 0 47 1 0.00000 + 2004 8 27 18 15 0 2 15 0 47 1 0.00000 2004 8 28 6 0 0 2 15 0 9 0 9.380000E-025.340000E-02 2.990000E-021.670000E-029.500000E-035.100000E-032.500000E-031.200000E-03 7.000000E-04 2004 8 28 8 15 0 2 15 0 2 1 6.000000E-04 2004 8 28 8 45 0 2 15 0 6 1 5.000000E-04 - 2004 8 28 10 15 0 2 15 0 17 1 0.00000 + 2004 8 28 10 15 0 2 15 0 17 1 0.00000 2004 8 28 14 30 0 2 15 0 3 0 1.800000E-033.600000E-03 2.000000E-04 - 2004 8 28 15 15 0 2 15 0 17 1 0.00000 + 2004 8 28 15 15 0 2 15 0 17 1 0.00000 2004 8 28 19 30 0 2 15 0 3 0 3.500000E-036.800000E-03 4.000000E-04 - 2004 8 28 20 15 0 2 15 0 45 1 0.00000 + 2004 8 28 20 15 0 2 15 0 45 1 0.00000 2004 8 29 7 30 0 2 15 0 1 0 7.400000E-03 2004 8 29 7 45 0 2 15 0 2 1 1.460000E-02 2004 8 29 8 15 0 2 15 0 17 0 1.440000E-021.410000E-02 @@ -600,20 +600,20 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2004 8 29 12 30 0 2 15 0 2 1 6.500000E-03 2004 8 29 13 0 0 2 15 0 2 0 6.400000E-035.000000E-04 2004 8 29 13 30 0 2 15 0 3 1 1.000000E-04 - 2004 8 29 14 15 0 2 15 0 169 1 0.00000 + 2004 8 29 14 15 0 2 15 0 169 1 0.00000 2004 8 31 8 30 0 2 15 0 4 0 1.710000E-023.370000E-02 1.900000E-032.000000E-04 2004 8 31 9 30 0 2 15 0 2 1 1.000000E-04 - 2004 8 31 10 0 0 2 15 0 404 1 0.00000 + 2004 8 31 10 0 0 2 15 0 404 1 0.00000 2004 9 4 15 0 0 2 15 0 13 0 8.120000E-027.800000E-02 7.270000E-026.730000E-026.350000E-026.150000E-025.980000E-025.830000E-02 5.720000E-025.690000E-029.700000E-031.000000E-034.000000E-04 2004 9 4 18 15 0 2 15 0 2 1 2.000000E-04 2004 9 4 18 45 0 2 15 0 3 1 1.000000E-04 - 2004 9 4 19 30 0 2 15 0 44 1 0.00000 + 2004 9 4 19 30 0 2 15 0 44 1 0.00000 2004 9 5 6 30 0 2 15 0 5 0 3.190000E-026.270000E-02 3.000000E-032.000000E-041.000000E-04 - 2004 9 5 7 45 0 2 15 0 161 1 0.00000 + 2004 9 5 7 45 0 2 15 0 161 1 0.00000 2004 9 6 24 0 0 2 15 0 28 0 7.920000E-027.410000E-02 6.710000E-026.050000E-025.410000E-024.790000E-024.230000E-023.740000E-02 3.320000E-022.970000E-022.660000E-022.380000E-022.160000E-022.000000E-02 @@ -623,7 +623,7 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2004 9 7 7 0 0 2 15 0 2 1 9.600000E-03 2004 9 7 7 30 0 2 15 0 2 0 7.000000E-042.000000E-04 2004 9 7 8 0 0 2 15 0 2 1 1.000000E-04 - 2004 9 7 8 30 0 2 15 0 144 1 0.00000 + 2004 9 7 8 30 0 2 15 0 144 1 0.00000 2004 9 8 20 30 0 2 15 0 3 0 1.660000E-023.270000E-02 3.280000E-02 2004 9 8 21 15 0 2 15 0 2 1 3.270000E-02 @@ -631,34 +631,34 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 3.210000E-023.160000E-023.100000E-023.060000E-023.050000E-026.300000E-03 1.000000E-035.000000E-043.000000E-042.000000E-04 2004 9 9 0 45 0 2 15 0 3 1 1.000000E-04 - 2004 9 9 1 30 0 2 15 0 1943 1 0.00000 - 2004 9 29 7 15 0 2 15 0 281 1 0.00000 - 2004 10 2 5 30 0 2 15 0 23 0 8.000000E-020.157200 - 0.157400 0.156700 0.155200 0.152900 0.149600 0.145300 - 0.140900 0.136400 0.132100 0.128000 0.124000 0.120000 - 0.116700 0.114200 0.111900 0.109800 0.108200 0.107600 + 2004 9 9 1 30 0 2 15 0 1943 1 0.00000 + 2004 9 29 7 15 0 2 15 0 281 1 0.00000 + 2004 10 2 5 30 0 2 15 0 23 0 8.000000E-020.157200 + 0.157400 0.156700 0.155200 0.152900 0.149600 0.145300 + 0.140900 0.136400 0.132100 0.128000 0.124000 0.120000 + 0.116700 0.114200 0.111900 0.109800 0.108200 0.107600 0.107300 4.100000E-032.000000E-04 - 2004 10 2 11 15 0 2 15 0 615 1 0.00000 - 2004 10 8 21 0 0 2 15 0 9 0 0.133500 0.137400 + 2004 10 2 11 15 0 2 15 0 615 1 0.00000 + 2004 10 8 21 0 0 2 15 0 9 0 0.133500 0.137400 0.136900 0.135900 0.134600 0.134000 7.580000E-021.600000E-03 1.000000E-04 - 2004 10 8 23 15 0 2 15 0 19 1 0.00000 - 2004 10 9 4 0 0 2 15 0 9 0 0.132800 0.132700 + 2004 10 8 23 15 0 2 15 0 19 1 0.00000 + 2004 10 9 4 0 0 2 15 0 9 0 0.132800 0.132700 0.129400 0.125500 0.122700 0.121800 0.121300 1.670000E-02 4.000000E-04 - 2004 10 9 6 15 0 2 15 0 443 1 0.00000 - 2004 10 13 21 0 0 2 15 0 24 0 0.135500 0.139500 - 0.139000 0.137900 0.136400 0.135300 0.134300 0.133400 - 0.132500 0.131600 0.130800 0.130000 0.128600 0.126000 - 0.123100 0.120000 0.117600 0.116200 0.115300 0.114400 + 2004 10 9 6 15 0 2 15 0 443 1 0.00000 + 2004 10 13 21 0 0 2 15 0 24 0 0.135500 0.139500 + 0.139000 0.137900 0.136400 0.135300 0.134300 0.133400 + 0.132500 0.131600 0.130800 0.130000 0.128600 0.126000 + 0.123100 0.120000 0.117600 0.116200 0.115300 0.114400 0.113800 0.113500 4.200000E-032.000000E-04 - 2004 10 14 3 0 0 2 15 0 14 1 0.00000 - 2004 10 14 6 30 0 2 15 0 6 0 0.113500 0.113900 + 2004 10 14 3 0 0 2 15 0 14 1 0.00000 + 2004 10 14 6 30 0 2 15 0 6 0 0.113500 0.113900 0.113500 6.510000E-021.500000E-031.000000E-04 - 2004 10 14 8 0 0 2 15 0 90 1 0.00000 + 2004 10 14 8 0 0 2 15 0 90 1 0.00000 2004 10 15 6 30 0 2 15 0 1 0 6.010000E-02 - 2004 10 15 6 45 0 2 15 0 2 1 0.118200 - 2004 10 15 7 15 0 2 15 0 24 0 0.116900 0.114000 + 2004 10 15 6 45 0 2 15 0 2 1 0.118200 + 2004 10 15 7 15 0 2 15 0 24 0 0.116900 0.114000 0.110700 0.107400 0.104600 0.101900 9.930000E-029.720000E-02 9.570000E-029.430000E-029.310000E-029.110000E-028.770000E-028.390000E-02 8.030000E-027.750000E-027.600000E-027.490000E-027.390000E-027.320000E-02 @@ -671,130 +671,130 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 4.240000E-024.140000E-024.080000E-024.020000E-023.970000E-023.920000E-02 3.890000E-023.860000E-023.840000E-023.820000E-023.810000E-021.500000E-03 1.000000E-04 - 2004 10 15 23 0 0 2 15 0 26 1 0.00000 + 2004 10 15 23 0 0 2 15 0 26 1 0.00000 2004 10 16 5 30 0 2 15 0 4 0 2.130000E-024.180000E-02 6.600000E-032.000000E-04 - 2004 10 16 6 30 0 2 15 0 6 1 0.00000 + 2004 10 16 6 30 0 2 15 0 6 1 0.00000 2004 10 16 8 0 0 2 15 0 20 0 3.160000E-024.280000E-02 4.250000E-024.200000E-024.150000E-024.100000E-024.050000E-024.000000E-02 3.960000E-023.940000E-022.230000E-025.000000E-043.760000E-023.940000E-02 3.930000E-023.910000E-023.890000E-023.880000E-021.600000E-031.000000E-04 - 2004 10 16 13 0 0 2 15 0 26 1 0.00000 + 2004 10 16 13 0 0 2 15 0 26 1 0.00000 2004 10 16 19 30 0 2 15 0 4 0 2.160000E-024.250000E-02 6.800000E-032.000000E-04 - 2004 10 16 20 30 0 2 15 0 184 1 0.00000 + 2004 10 16 20 30 0 2 15 0 184 1 0.00000 2004 10 18 18 30 0 2 15 0 4 0 3.310000E-026.510000E-02 2.500000E-031.000000E-04 - 2004 10 18 19 30 0 2 15 0 462 1 0.00000 - 2004 10 23 15 0 0 2 15 0 29 0 0.105900 0.105100 + 2004 10 18 19 30 0 2 15 0 462 1 0.00000 + 2004 10 23 15 0 0 2 15 0 29 0 0.105900 0.105100 0.102700 9.920000E-029.630000E-029.460000E-029.320000E-029.200000E-02 9.110000E-029.070000E-025.110000E-021.000000E-038.990000E-028.700000E-02 8.340000E-027.980000E-027.630000E-027.290000E-026.970000E-026.670000E-02 6.400000E-026.190000E-025.990000E-025.800000E-025.670000E-025.620000E-02 5.610000E-027.700000E-032.000000E-04 - 2004 10 23 22 15 0 2 15 0 8 1 0.00000 + 2004 10 23 22 15 0 2 15 0 8 1 0.00000 2004 10 24 0 15 0 2 15 0 6 0 5.430000E-025.700000E-02 5.670000E-025.650000E-023.170000E-026.000000E-04 - 2004 10 24 1 45 0 2 15 0 477 1 0.00000 - 2004 10 29 1 0 0 2 15 0 20 0 9.850000E-020.101400 + 2004 10 24 1 45 0 2 15 0 477 1 0.00000 + 2004 10 29 1 0 0 2 15 0 20 0 9.850000E-020.101400 0.101000 0.100200 9.620000E-028.770000E-027.910000E-027.130000E-02 6.430000E-025.800000E-025.230000E-024.710000E-024.400000E-024.310000E-02 4.270000E-024.230000E-024.210000E-024.200000E-026.400000E-032.000000E-04 - 2004 10 29 6 0 0 2 15 0 14 1 0.00000 + 2004 10 29 6 0 0 2 15 0 14 1 0.00000 2004 10 29 9 30 0 2 15 0 11 0 4.360000E-024.380000E-02 4.180000E-023.670000E-023.180000E-022.760000E-022.510000E-022.430000E-02 2.380000E-022.330000E-022.300000E-02 2004 10 29 12 15 0 2 15 0 2 1 2.280000E-02 2004 10 29 12 45 0 2 15 0 8 0 9.000000E-042.270000E-02 2.280000E-022.270000E-022.260000E-022.250000E-022.240000E-029.000000E-04 - 2004 10 29 14 45 0 2 15 0 53 1 0.00000 + 2004 10 29 14 45 0 2 15 0 53 1 0.00000 2004 10 30 4 0 0 2 15 0 12 0 2.970000E-023.050000E-02 3.040000E-023.020000E-022.880000E-022.570000E-022.270000E-022.010000E-02 1.860000E-021.810000E-021.780000E-021.750000E-02 2004 10 30 7 0 0 2 15 0 2 1 1.730000E-02 2004 10 30 7 30 0 2 15 0 2 0 9.700000E-032.000000E-04 - 2004 10 30 8 0 0 2 15 0 160 1 0.00000 - 2004 10 31 24 0 0 2 15 31 5856 1 -999.000 - 2004 12 31 24 0 0 6 1 31 1 1 -999.000 - 2005 12 31 24 0 0 6 1 31 1 1 -999.000 - 2006 12 31 24 0 0 6 1 31 1 1 -999.000 - 2007 12 31 24 0 0 6 1 31 1 1 -999.000 - 2008 12 31 24 0 0 6 1 31 1 1 -999.000 - 2009 12 31 24 0 0 6 1 31 1 1 -999.000 - 2010 12 31 24 0 0 6 1 31 1 1 -999.000 - 2011 12 31 24 0 0 6 1 31 1 1 -999.000 - 2012 12 31 24 0 0 6 1 31 1 1 -999.000 - 2013 12 31 24 0 0 6 1 31 1 1 -999.000 - 2014 12 31 24 0 0 6 1 31 1 1 -999.000 - 2015 12 31 24 0 0 2 1 31 32000 1 -999.000 - 2016 1 23 5 20 0 2 1 31 32000 1 -999.000 - 2016 2 14 10 40 0 2 1 31 32000 1 -999.000 - 2016 3 7 16 0 0 2 1 31 32000 1 -999.000 - 2016 3 29 21 20 0 2 1 31 32000 1 -999.000 - 2016 4 21 2 40 0 2 1 31 32000 1 -999.000 - 2016 5 13 8 0 0 2 1 31 32000 1 -999.000 - 2016 6 4 13 20 0 2 1 31 32000 1 -999.000 - 2016 6 26 18 40 0 2 1 31 32000 1 -999.000 - 2016 7 18 24 0 0 2 1 31 32000 1 -999.000 - 2016 8 10 5 20 0 2 1 31 32000 1 -999.000 - 2016 9 1 10 40 0 2 1 31 32000 1 -999.000 - 2016 9 23 16 0 0 2 1 31 32000 1 -999.000 - 2016 10 15 21 20 0 2 1 31 32000 1 -999.000 - 2016 11 7 2 40 0 2 1 31 32000 1 -999.000 - 2016 11 29 8 0 0 2 1 31 32000 1 -999.000 - 2016 12 21 13 20 0 2 1 31 13615 1 -999.000 - 2016 12 31 0 15 0 2 15 0 95 1 0.00000 - 2016 12 31 24 0 0 2 15 0 171 1 0.00000 - 2017 1 2 18 45 0 2 15 0 16 0 0.168700 0.167100 + 2004 10 30 8 0 0 2 15 0 160 1 0.00000 + 2004 10 31 24 0 0 2 15 31 5856 1 -999.000 + 2004 12 31 24 0 0 6 1 31 1 1 -999.000 + 2005 12 31 24 0 0 6 1 31 1 1 -999.000 + 2006 12 31 24 0 0 6 1 31 1 1 -999.000 + 2007 12 31 24 0 0 6 1 31 1 1 -999.000 + 2008 12 31 24 0 0 6 1 31 1 1 -999.000 + 2009 12 31 24 0 0 6 1 31 1 1 -999.000 + 2010 12 31 24 0 0 6 1 31 1 1 -999.000 + 2011 12 31 24 0 0 6 1 31 1 1 -999.000 + 2012 12 31 24 0 0 6 1 31 1 1 -999.000 + 2013 12 31 24 0 0 6 1 31 1 1 -999.000 + 2014 12 31 24 0 0 6 1 31 1 1 -999.000 + 2015 12 31 24 0 0 2 1 31 32000 1 -999.000 + 2016 1 23 5 20 0 2 1 31 32000 1 -999.000 + 2016 2 14 10 40 0 2 1 31 32000 1 -999.000 + 2016 3 7 16 0 0 2 1 31 32000 1 -999.000 + 2016 3 29 21 20 0 2 1 31 32000 1 -999.000 + 2016 4 21 2 40 0 2 1 31 32000 1 -999.000 + 2016 5 13 8 0 0 2 1 31 32000 1 -999.000 + 2016 6 4 13 20 0 2 1 31 32000 1 -999.000 + 2016 6 26 18 40 0 2 1 31 32000 1 -999.000 + 2016 7 18 24 0 0 2 1 31 32000 1 -999.000 + 2016 8 10 5 20 0 2 1 31 32000 1 -999.000 + 2016 9 1 10 40 0 2 1 31 32000 1 -999.000 + 2016 9 23 16 0 0 2 1 31 32000 1 -999.000 + 2016 10 15 21 20 0 2 1 31 32000 1 -999.000 + 2016 11 7 2 40 0 2 1 31 32000 1 -999.000 + 2016 11 29 8 0 0 2 1 31 32000 1 -999.000 + 2016 12 21 13 20 0 2 1 31 13615 1 -999.000 + 2016 12 31 0 15 0 2 15 0 95 1 0.00000 + 2016 12 31 24 0 0 2 15 0 171 1 0.00000 + 2017 1 2 18 45 0 2 15 0 16 0 0.168700 0.167100 0.163900 0.161000 0.160000 0.159400 0.159200 5.400000E-03 - 1.000000E-04 0.00000 0.157800 0.156600 0.156000 0.155700 + 1.000000E-04 0.00000 0.157800 0.156600 0.156000 0.155700 4.900000E-031.000000E-04 - 2017 1 2 22 45 0 2 15 0 2 1 0.00000 - 2017 1 2 23 15 0 2 15 0 25 0 0.153600 0.153100 + 2017 1 2 22 45 0 2 15 0 2 1 0.00000 + 2017 1 2 23 15 0 2 15 0 25 0 0.153600 0.153100 0.148000 0.136800 0.121200 0.103800 8.750000E-027.240000E-02 6.370000E-026.080000E-025.990000E-025.930000E-025.850000E-025.810000E-02 5.570000E-025.080000E-024.750000E-024.550000E-024.420000E-024.310000E-02 4.270000E-024.260000E-024.250000E-025.500000E-031.000000E-04 - 2017 1 3 5 30 0 2 15 0 2 1 0.00000 + 2017 1 3 5 30 0 2 15 0 2 1 0.00000 2017 1 3 6 0 0 2 15 0 5 0 4.260000E-024.220000E-02 4.210000E-024.200000E-021.300000E-03 - 2017 1 3 7 15 0 2 15 0 47 1 0.00000 + 2017 1 3 7 15 0 2 15 0 47 1 0.00000 2017 1 3 19 0 0 2 15 0 8 0 4.820000E-024.800000E-02 4.740000E-024.690000E-024.670000E-024.660000E-026.000000E-031.000000E-04 - 2017 1 3 21 0 0 2 15 0 246 1 0.00000 + 2017 1 3 21 0 0 2 15 0 246 1 0.00000 2017 1 6 10 30 0 2 15 0 4 0 7.500000E-027.490000E-02 1.090000E-023.000000E-04 - 2017 1 6 11 30 0 2 15 0 342 1 0.00000 - 2017 1 10 1 0 0 2 15 0 35 0 0.103900 0.103400 + 2017 1 6 11 30 0 2 15 0 342 1 0.00000 + 2017 1 10 1 0 0 2 15 0 35 0 0.103900 0.103400 0.101200 9.920000E-029.700000E-029.320000E-028.870000E-028.570000E-02 8.370000E-028.260000E-028.220000E-028.200000E-028.180000E-028.070000E-02 7.710000E-027.260000E-026.940000E-026.630000E-026.290000E-025.860000E-02 5.540000E-025.300000E-025.140000E-025.010000E-024.880000E-024.750000E-02 4.690000E-024.670000E-024.650000E-024.630000E-024.570000E-024.550000E-02 4.540000E-022.510000E-024.000000E-04 - 2017 1 10 9 45 0 2 15 0 3 1 0.00000 + 2017 1 10 9 45 0 2 15 0 3 1 0.00000 2017 1 10 10 30 0 2 15 0 26 0 4.570000E-024.530000E-02 4.510000E-024.500000E-024.470000E-024.420000E-024.400000E-024.390000E-02 2.430000E-024.340000E-024.260000E-024.210000E-024.190000E-024.180000E-02 2.320000E-024.000000E-04 0.00000 4.190000E-024.110000E-023.830000E-02 3.690000E-023.640000E-023.630000E-023.620000E-022.000000E-023.000000E-04 - 2017 1 10 17 0 0 2 15 0 7 1 0.00000 + 2017 1 10 17 0 0 2 15 0 7 1 0.00000 2017 1 10 18 45 0 2 15 0 16 0 3.700000E-023.670000E-02 3.660000E-023.620000E-023.570000E-023.510000E-023.410000E-023.080000E-02 2.950000E-022.860000E-022.740000E-022.700000E-022.690000E-022.680000E-02 1.480000E-022.000000E-04 - 2017 1 10 22 45 0 2 15 0 77 1 0.00000 + 2017 1 10 22 45 0 2 15 0 77 1 0.00000 2017 1 11 18 0 0 2 15 0 12 0 3.780000E-023.600000E-02 3.540000E-023.520000E-023.510000E-023.500000E-023.390000E-023.360000E-02 3.340000E-023.330000E-024.100000E-031.000000E-04 - 2017 1 11 21 0 0 2 15 0 3 1 0.00000 + 2017 1 11 21 0 0 2 15 0 3 1 0.00000 2017 1 11 21 45 0 2 15 0 6 0 3.360000E-023.370000E-02 3.320000E-023.080000E-022.980000E-022.950000E-02 2017 1 11 23 15 0 2 15 0 2 1 2.930000E-02 2017 1 11 23 45 0 2 15 0 13 0 3.600000E-032.920000E-02 2.800000E-022.670000E-022.580000E-022.470000E-022.420000E-022.410000E-02 2.370000E-022.350000E-022.340000E-022.330000E-027.000000E-04 - 2017 1 12 3 0 0 2 15 0 25 1 0.00000 + 2017 1 12 3 0 0 2 15 0 25 1 0.00000 2017 1 12 9 15 0 2 15 0 9 0 2.720000E-022.260000E-02 1.760000E-021.380000E-021.260000E-021.240000E-021.210000E-021.180000E-02 1.170000E-02 @@ -802,16 +802,16 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2017 1 12 12 0 0 2 15 0 2 0 1.150000E-021.140000E-02 2017 1 12 12 30 0 2 15 0 2 1 1.130000E-02 2017 1 12 13 0 0 2 15 0 1 0 4.000000E-04 - 2017 1 12 13 15 0 2 15 0 378 1 0.00000 + 2017 1 12 13 15 0 2 15 0 378 1 0.00000 2017 1 16 11 45 0 2 15 0 4 0 6.370000E-026.350000E-02 9.300000E-032.000000E-04 - 2017 1 16 12 45 0 2 15 0 4 1 0.00000 + 2017 1 16 12 45 0 2 15 0 4 1 0.00000 2017 1 16 13 45 0 2 15 0 10 0 6.390000E-023.630000E-02 7.000000E-04 0.00000 6.390000E-026.300000E-026.200000E-026.160000E-02 6.140000E-026.110000E-02 2017 1 16 16 15 0 2 15 0 5 0 6.030000E-026.000000E-02 5.990000E-023.320000E-025.000000E-04 - 2017 1 16 17 30 0 2 15 0 6 1 0.00000 + 2017 1 16 17 30 0 2 15 0 6 1 0.00000 2017 1 16 19 0 0 2 15 0 45 0 6.050000E-025.980000E-02 5.880000E-025.760000E-025.660000E-025.570000E-025.530000E-025.430000E-02 5.130000E-024.960000E-024.860000E-024.770000E-024.740000E-024.670000E-02 @@ -823,63 +823,63 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2.040000E-02 2017 1 17 6 15 0 2 15 0 2 1 2.030000E-02 2017 1 17 6 45 0 2 15 0 1 0 6.000000E-04 - 2017 1 17 7 0 0 2 15 0 2 1 0.00000 + 2017 1 17 7 0 0 2 15 0 2 1 0.00000 2017 1 17 7 30 0 2 15 0 9 0 2.030000E-021.970000E-02 1.940000E-021.930000E-021.860000E-021.700000E-021.620000E-021.580000E-02 1.570000E-02 2017 1 17 9 45 0 2 15 0 2 1 1.560000E-02 2017 1 17 10 15 0 2 15 0 6 0 5.000000E-041.570000E-02 1.560000E-021.550000E-021.540000E-021.900000E-03 - 2017 1 17 11 45 0 2 15 0 21 1 0.00000 + 2017 1 17 11 45 0 2 15 0 21 1 0.00000 2017 1 17 17 0 0 2 15 0 5 0 1.890000E-021.880000E-02 1.870000E-021.860000E-026.000000E-04 - 2017 1 17 18 15 0 2 15 0 48 1 0.00000 + 2017 1 17 18 15 0 2 15 0 48 1 0.00000 2017 1 18 6 15 0 2 15 0 5 0 2.630000E-022.610000E-02 2.600000E-021.430000E-022.000000E-04 - 2017 1 18 7 30 0 2 15 0 190 1 0.00000 + 2017 1 18 7 30 0 2 15 0 190 1 0.00000 2017 1 20 7 0 0 2 15 0 15 0 5.240000E-025.210000E-02 5.090000E-024.930000E-024.790000E-024.620000E-024.410000E-024.170000E-02 3.940000E-023.810000E-023.750000E-023.730000E-023.720000E-022.040000E-02 3.000000E-04 - 2017 1 20 10 45 0 2 15 0 271 1 0.00000 + 2017 1 20 10 45 0 2 15 0 271 1 0.00000 2017 1 23 6 30 0 2 15 0 4 0 7.040000E-027.030000E-02 1.030000E-023.000000E-04 - 2017 1 23 7 30 0 2 15 0 10 1 0.00000 + 2017 1 23 7 30 0 2 15 0 10 1 0.00000 2017 1 23 10 0 0 2 15 0 12 0 7.130000E-024.080000E-02 7.080000E-026.940000E-026.640000E-026.380000E-026.150000E-026.050000E-02 6.010000E-025.990000E-023.270000E-025.000000E-04 - 2017 1 23 13 0 0 2 15 0 64 1 0.00000 + 2017 1 23 13 0 0 2 15 0 64 1 0.00000 2017 1 24 5 0 0 2 15 0 9 0 6.710000E-026.680000E-02 6.670000E-026.630000E-026.550000E-026.520000E-026.510000E-023.610000E-02 6.000000E-04 - 2017 1 24 7 15 0 2 15 0 79 1 0.00000 + 2017 1 24 7 15 0 2 15 0 79 1 0.00000 2017 1 25 3 0 0 2 15 0 8 0 7.360000E-027.330000E-02 7.220000E-027.170000E-027.150000E-027.130000E-022.400000E-031.000000E-04 - 2017 1 25 5 0 0 2 15 0 155 1 0.00000 + 2017 1 25 5 0 0 2 15 0 155 1 0.00000 2017 1 26 19 45 0 2 15 0 6 0 8.630000E-028.560000E-02 8.530000E-028.510000E-022.800000E-031.000000E-04 - 2017 1 26 21 15 0 2 15 0 389 1 0.00000 - 2017 1 30 22 30 0 2 15 0 37 0 0.114000 0.113600 - 0.113100 0.111600 0.110900 0.110500 0.109000 0.108200 + 2017 1 26 21 15 0 2 15 0 389 1 0.00000 + 2017 1 30 22 30 0 2 15 0 37 0 0.114000 0.113600 + 0.113100 0.111600 0.110900 0.110500 0.109000 0.108200 0.106400 0.104400 0.103100 0.101100 9.920000E-029.750000E-02 9.460000E-029.210000E-028.970000E-028.740000E-028.580000E-028.420000E-02 8.190000E-028.000000E-027.830000E-027.720000E-027.550000E-027.400000E-02 7.240000E-027.020000E-026.830000E-026.680000E-026.540000E-026.450000E-02 6.340000E-026.300000E-026.280000E-023.420000E-025.000000E-04 - 2017 1 31 7 45 0 2 15 0 37 1 0.00000 + 2017 1 31 7 45 0 2 15 0 37 1 0.00000 2017 1 31 17 0 0 2 15 0 6 0 6.700000E-026.660000E-02 6.630000E-026.620000E-028.700000E-032.000000E-04 - 2017 1 31 18 30 0 2 15 0 38 1 0.00000 + 2017 1 31 18 30 0 2 15 0 38 1 0.00000 2017 2 1 4 0 0 2 15 0 17 0 7.040000E-027.010000E-02 6.980000E-026.870000E-026.720000E-026.570000E-026.510000E-026.480000E-02 6.470000E-026.060000E-025.580000E-025.370000E-025.300000E-025.280000E-02 5.270000E-027.200000E-032.000000E-04 - 2017 2 1 8 15 0 2 15 0 35 1 0.00000 + 2017 2 1 8 15 0 2 15 0 35 1 0.00000 2017 2 1 17 0 0 2 15 0 13 0 5.700000E-025.680000E-02 3.130000E-025.000000E-045.540000E-025.620000E-025.500000E-025.370000E-02 5.240000E-025.190000E-025.170000E-025.160000E-021.800000E-03 - 2017 2 1 20 15 0 2 15 0 529 1 0.00000 - 2017 2 7 8 30 0 2 15 0 38 0 0.102600 0.101400 + 2017 2 1 20 15 0 2 15 0 529 1 0.00000 + 2017 2 7 8 30 0 2 15 0 38 0 0.102600 0.101400 9.470000E-029.100000E-028.870000E-028.790000E-028.750000E-028.700000E-02 8.590000E-028.550000E-028.530000E-028.460000E-027.750000E-026.150000E-02 4.820000E-024.160000E-023.800000E-023.570000E-023.390000E-023.100000E-02 @@ -888,46 +888,46 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 1.530000E-021.520000E-021.480000E-021.360000E-021.280000E-021.250000E-02 2017 2 7 18 0 0 2 15 0 2 1 1.240000E-02 2017 2 7 18 30 0 2 15 0 2 0 6.800000E-031.000000E-04 - 2017 2 7 19 0 0 2 15 0 389 1 0.00000 + 2017 2 7 19 0 0 2 15 0 389 1 0.00000 2017 2 11 20 15 0 2 15 0 18 0 6.550000E-028.800000E-03 6.470000E-026.520000E-022.300000E-036.470000E-026.400000E-026.220000E-02 6.140000E-026.100000E-026.060000E-025.980000E-025.860000E-025.820000E-02 5.800000E-025.790000E-022.200000E-031.000000E-04 - 2017 2 12 0 45 0 2 15 0 7 1 0.00000 + 2017 2 12 0 45 0 2 15 0 7 1 0.00000 2017 2 12 2 30 0 2 15 0 29 0 5.870000E-025.790000E-02 5.670000E-025.560000E-025.530000E-025.480000E-025.410000E-025.380000E-02 5.370000E-025.270000E-025.070000E-024.900000E-024.720000E-024.610000E-02 4.450000E-024.340000E-024.290000E-024.270000E-023.820000E-023.390000E-02 3.200000E-023.150000E-023.130000E-023.110000E-023.070000E-023.050000E-02 3.040000E-024.100000E-031.000000E-04 - 2017 2 12 9 45 0 2 15 0 241 1 0.00000 + 2017 2 12 9 45 0 2 15 0 241 1 0.00000 2017 2 14 22 0 0 2 15 0 4 0 6.200000E-026.190000E-02 2.200000E-031.000000E-04 - 2017 2 14 23 0 0 2 15 0 870 1 0.00000 - 2017 2 24 0 30 0 2 15 0 16 0 0.127400 0.126900 - 0.125300 0.124200 0.123700 0.120600 0.118500 0.117800 - 0.117500 0.117200 0.112800 0.110100 0.109300 0.108900 + 2017 2 14 23 0 0 2 15 0 870 1 0.00000 + 2017 2 24 0 30 0 2 15 0 16 0 0.127400 0.126900 + 0.125300 0.124200 0.123700 0.120600 0.118500 0.117800 + 0.117500 0.117200 0.112800 0.110100 0.109300 0.108900 5.980000E-029.000000E-04 - 2017 2 24 4 30 0 2 15 0 45 1 0.00000 + 2017 2 24 4 30 0 2 15 0 45 1 0.00000 2017 2 24 15 45 0 2 15 0 8 0 7.820000E-023.100000E-02 2.490000E-022.430000E-022.410000E-022.400000E-021.330000E-022.000000E-04 - 2017 2 24 17 45 0 2 15 0 18 1 0.00000 + 2017 2 24 17 45 0 2 15 0 18 1 0.00000 2017 2 24 22 15 0 2 15 0 6 0 2.700000E-022.040000E-02 1.560000E-021.400000E-021.290000E-021.260000E-02 2017 2 24 23 45 0 2 15 0 2 1 1.250000E-02 2017 2 25 0 15 0 2 15 0 2 0 6.900000E-031.000000E-04 - 2017 2 25 0 45 0 2 15 0 312 1 0.00000 + 2017 2 25 0 45 0 2 15 0 312 1 0.00000 2017 2 28 6 45 0 2 15 0 11 0 5.680000E-025.660000E-02 5.610000E-025.520000E-025.430000E-025.320000E-025.190000E-025.140000E-02 5.120000E-025.100000E-021.700000E-03 - 2017 2 28 9 30 0 2 15 0 34 1 0.00000 + 2017 2 28 9 30 0 2 15 0 34 1 0.00000 2017 2 28 18 0 0 2 15 0 4 0 5.520000E-025.500000E-02 3.070000E-025.000000E-04 - 2017 2 28 19 0 0 2 15 0 6 1 0.00000 + 2017 2 28 19 0 0 2 15 0 6 1 0.00000 2017 2 28 20 30 0 2 15 0 9 0 5.580000E-025.400000E-02 4.860000E-024.550000E-024.490000E-024.470000E-024.450000E-025.900000E-03 1.000000E-04 - 2017 2 28 22 45 0 2 15 0 2 1 0.00000 + 2017 2 28 22 45 0 2 15 0 2 1 0.00000 2017 2 28 23 15 0 2 15 0 26 0 4.480000E-024.390000E-02 4.280000E-024.170000E-022.740000E-021.620000E-021.440000E-021.380000E-02 1.370000E-021.350000E-021.320000E-021.310000E-021.280000E-021.250000E-02 @@ -935,90 +935,90 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 5.600000E-035.000000E-034.600000E-034.200000E-033.900000E-033.700000E-03 2017 3 1 5 45 0 2 15 0 3 1 3.600000E-03 2017 3 1 6 30 0 2 15 0 1 0 5.000000E-04 - 2017 3 1 6 45 0 2 15 0 28 1 0.00000 + 2017 3 1 6 45 0 2 15 0 28 1 0.00000 2017 3 1 13 45 0 2 15 0 2 0 8.500000E-031.200000E-03 - 2017 3 1 14 15 0 2 15 0 184 1 0.00000 - 2017 3 3 12 15 0 2 15 0 287 1 0.00000 + 2017 3 1 14 15 0 2 15 0 184 1 0.00000 + 2017 3 3 12 15 0 2 15 0 287 1 0.00000 2017 3 6 12 0 0 2 15 0 3 0 7.180000E-021.050000E-02 3.000000E-04 - 2017 3 6 12 45 0 2 15 0 3 1 0.00000 + 2017 3 6 12 45 0 2 15 0 3 1 0.00000 2017 3 6 13 30 0 2 15 0 4 0 7.140000E-027.200000E-02 3.000000E-031.000000E-04 - 2017 3 6 14 30 0 2 15 0 23 1 0.00000 + 2017 3 6 14 30 0 2 15 0 23 1 0.00000 2017 3 6 20 15 0 2 15 0 11 0 7.440000E-021.090000E-02 3.000000E-04 0.00000 7.420000E-027.430000E-027.390000E-027.330000E-02 7.300000E-021.000000E-023.000000E-04 - 2017 3 6 23 0 0 2 15 0 17 1 0.00000 + 2017 3 6 23 0 0 2 15 0 17 1 0.00000 2017 3 7 3 15 0 2 15 0 3 0 7.470000E-027.350000E-02 7.310000E-02 2017 3 7 4 0 0 2 15 0 3 0 7.290000E-023.000000E-03 1.000000E-04 - 2017 3 7 4 45 0 2 15 0 3 1 0.00000 + 2017 3 7 4 45 0 2 15 0 3 1 0.00000 2017 3 7 5 30 0 2 15 0 12 0 7.240000E-027.110000E-02 6.910000E-026.170000E-025.960000E-025.910000E-025.880000E-025.800000E-02 5.760000E-025.750000E-022.400000E-031.000000E-04 - 2017 3 7 8 30 0 2 15 0 11 1 0.00000 + 2017 3 7 8 30 0 2 15 0 11 1 0.00000 2017 3 7 11 15 0 2 15 0 4 0 5.870000E-025.850000E-02 8.700000E-033.000000E-04 - 2017 3 7 12 15 0 2 15 0 547 1 0.00000 + 2017 3 7 12 15 0 2 15 0 547 1 0.00000 2017 3 13 5 0 0 2 15 0 50 0 0.107700 6.190000E-02 - 1.400000E-031.000000E-040.107300 6.280000E-021.600000E-030.103800 - 0.106500 0.106100 1.550000E-025.000000E-040.105200 0.104400 - 0.102700 0.102000 0.101700 4.000000E-032.000000E-040.101300 + 1.400000E-031.000000E-040.107300 6.280000E-021.600000E-030.103800 + 0.106500 0.106100 1.550000E-025.000000E-040.105200 0.104400 + 0.102700 0.102000 0.101700 4.000000E-032.000000E-040.101300 0.100400 9.960000E-029.830000E-029.730000E-029.590000E-029.410000E-02 9.340000E-029.300000E-029.120000E-028.890000E-028.730000E-028.580000E-02 8.380000E-028.180000E-027.980000E-027.780000E-027.590000E-027.440000E-02 7.200000E-027.080000E-026.970000E-026.920000E-026.820000E-026.770000E-02 6.750000E-026.680000E-026.630000E-026.610000E-021.000000E-024.000000E-04 - 2017 3 13 17 30 0 2 15 0 379 1 0.00000 + 2017 3 13 17 30 0 2 15 0 379 1 0.00000 2017 3 17 16 15 0 2 15 0 23 0 0.100300 9.970000E-02 9.630000E-029.160000E-028.810000E-028.560000E-028.400000E-028.190000E-02 7.910000E-027.830000E-027.800000E-024.540000E-021.200000E-031.000000E-04 0.00000 7.800000E-027.740000E-027.670000E-027.570000E-027.530000E-02 4.280000E-029.000000E-041.000000E-04 - 2017 3 17 22 0 0 2 15 0 30 1 0.00000 + 2017 3 17 22 0 0 2 15 0 30 1 0.00000 2017 3 18 5 30 0 2 15 0 23 0 7.820000E-027.730000E-02 7.600000E-027.520000E-027.410000E-027.380000E-024.170000E-027.320000E-02 7.250000E-027.120000E-027.030000E-026.920000E-026.780000E-026.520000E-02 6.220000E-026.030000E-025.870000E-025.760000E-025.670000E-025.630000E-02 5.620000E-022.500000E-031.000000E-04 - 2017 3 18 11 15 0 2 15 0 160 1 0.00000 + 2017 3 18 11 15 0 2 15 0 160 1 0.00000 2017 3 20 3 15 0 2 15 0 10 0 7.410000E-027.360000E-02 6.970000E-026.470000E-026.170000E-026.070000E-026.030000E-026.020000E-02 2.700000E-032.000000E-04 - 2017 3 20 5 45 0 2 15 0 7 1 0.00000 + 2017 3 20 5 45 0 2 15 0 7 1 0.00000 2017 3 20 7 30 0 2 15 0 3 0 6.120000E-021.880000E-02 4.200000E-03 2017 3 20 8 15 0 2 15 0 3 1 3.800000E-03 2017 3 20 9 0 0 2 15 0 2 0 2.200000E-031.000000E-04 - 2017 3 20 9 30 0 2 15 0 37 1 0.00000 + 2017 3 20 9 30 0 2 15 0 37 1 0.00000 2017 3 20 18 45 0 2 15 0 2 0 1.030000E-021.500000E-03 - 2017 3 20 19 15 0 2 15 0 2 1 0.00000 + 2017 3 20 19 15 0 2 15 0 2 1 0.00000 2017 3 20 19 45 0 2 15 0 3 0 1.030000E-021.080000E-02 4.000000E-04 - 2017 3 20 20 30 0 2 15 0 297 1 0.00000 + 2017 3 20 20 30 0 2 15 0 297 1 0.00000 2017 3 23 22 45 0 2 15 0 17 0 5.380000E-025.350000E-02 5.200000E-025.000000E-024.700000E-024.430000E-024.150000E-024.080000E-02 4.060000E-024.000000E-023.730000E-023.520000E-023.430000E-023.400000E-02 3.390000E-025.200000E-032.000000E-04 - 2017 3 24 3 0 0 2 15 0 91 1 0.00000 + 2017 3 24 3 0 0 2 15 0 91 1 0.00000 2017 3 25 1 45 0 2 15 0 5 0 4.660000E-024.640000E-02 4.620000E-021.900000E-031.000000E-04 - 2017 3 25 3 0 0 2 15 0 127 1 0.00000 + 2017 3 25 3 0 0 2 15 0 127 1 0.00000 2017 3 26 10 45 0 2 15 0 15 0 6.200000E-026.170000E-02 5.760000E-025.530000E-025.420000E-025.170000E-025.080000E-025.050000E-02 5.040000E-024.870000E-024.980000E-024.950000E-024.940000E-022.300000E-03 1.000000E-04 - 2017 3 26 14 30 0 2 15 0 6 1 0.00000 + 2017 3 26 14 30 0 2 15 0 6 1 0.00000 2017 3 26 16 0 0 2 15 0 24 0 5.020000E-024.920000E-02 4.880000E-024.840000E-024.780000E-024.760000E-022.720000E-024.610000E-02 4.700000E-024.680000E-024.670000E-022.200000E-034.630000E-024.580000E-02 4.510000E-024.480000E-024.470000E-022.200000E-031.000000E-044.460000E-02 4.430000E-024.420000E-021.700000E-031.000000E-04 - 2017 3 26 22 0 0 2 15 0 295 1 0.00000 + 2017 3 26 22 0 0 2 15 0 295 1 0.00000 2017 3 29 23 45 0 2 15 0 7 0 7.780000E-027.630000E-02 7.470000E-027.420000E-027.400000E-022.900000E-031.000000E-04 - 2017 3 30 1 30 0 2 15 0 22 1 0.00000 + 2017 3 30 1 30 0 2 15 0 22 1 0.00000 2017 3 30 7 0 0 2 15 0 18 0 7.590000E-027.050000E-02 5.540000E-024.500000E-023.960000E-023.560000E-023.030000E-022.490000E-02 2.090000E-021.740000E-021.490000E-021.290000E-029.900000E-037.900000E-03 @@ -1032,39 +1032,39 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 3.400000E-032.700000E-032.200000E-03 2017 3 30 17 0 0 2 15 0 4 1 2.000000E-03 2017 3 30 18 0 0 2 15 0 1 0 1.000000E-04 - 2017 3 30 18 15 0 2 15 0 2 1 0.00000 + 2017 3 30 18 15 0 2 15 0 2 1 0.00000 2017 3 30 18 45 0 2 15 0 9 0 2.600000E-032.500000E-03 2.200000E-031.900000E-031.600000E-031.500000E-031.300000E-031.100000E-03 1.000000E-03 2017 3 30 21 0 0 2 15 0 3 1 9.000000E-04 2017 3 30 21 45 0 2 15 0 1 0 1.000000E-04 - 2017 3 30 22 0 0 2 15 0 3 1 0.00000 + 2017 3 30 22 0 0 2 15 0 3 1 0.00000 2017 3 30 22 45 0 2 15 0 2 0 1.600000E-031.500000E-03 2017 3 30 23 15 0 2 15 0 4 1 1.400000E-03 2017 3 31 0 15 0 2 15 0 1 0 2.000000E-04 - 2017 3 31 0 30 0 2 15 0 337 1 0.00000 - 2017 4 3 12 45 0 2 15 0 10 0 0.169500 0.167900 + 2017 3 31 0 30 0 2 15 0 337 1 0.00000 + 2017 4 3 12 45 0 2 15 0 10 0 0.169500 0.167900 0.165900 0.163500 0.162100 0.161600 8.300000E-039.000000E-04 4.000000E-042.000000E-04 2017 4 3 15 15 0 2 15 0 3 1 1.000000E-04 - 2017 4 3 16 0 0 2 15 0 6 1 0.00000 + 2017 4 3 16 0 0 2 15 0 6 1 0.00000 2017 4 3 17 30 0 2 15 0 22 0 0.161500 9.520000E-02 - 2.700000E-030.160000 0.159100 0.158700 0.156700 0.155900 - 9.480000E-020.154700 0.153200 0.146900 0.140300 0.135600 + 2.700000E-030.160000 0.159100 0.158700 0.156700 0.155900 + 9.480000E-020.154700 0.153200 0.146900 0.140300 0.135600 0.132500 0.129700 0.128700 0.128400 8.000000E-031.200000E-03 5.000000E-043.000000E-04 2017 4 3 23 0 0 2 15 0 2 1 2.000000E-04 2017 4 3 23 30 0 2 15 0 2 1 1.000000E-04 - 2017 4 3 24 0 0 2 15 0 4 1 0.00000 - 2017 4 4 1 0 0 2 15 0 25 0 0.128800 0.126800 + 2017 4 3 24 0 0 2 15 0 4 1 0.00000 + 2017 4 4 1 0 0 2 15 0 25 0 0.128800 0.126800 0.126000 7.470000E-020.122400 0.124300 0.123700 1.900000E-02 - 1.000000E-033.000000E-042.000000E-041.000000E-040.123400 0.121200 - 0.119900 0.119500 5.400000E-035.000000E-040.118900 0.116100 + 1.000000E-033.000000E-042.000000E-041.000000E-040.123400 0.121200 + 0.119900 0.119500 5.400000E-035.000000E-040.118900 0.116100 0.115200 0.114900 6.600000E-039.000000E-044.000000E-04 2017 4 4 7 15 0 2 15 0 2 1 2.000000E-04 2017 4 4 7 45 0 2 15 0 2 1 1.000000E-04 - 2017 4 4 8 15 0 2 15 0 127 1 0.00000 - 2017 4 5 16 0 0 2 15 0 21 0 0.122400 0.106000 + 2017 4 4 8 15 0 2 15 0 127 1 0.00000 + 2017 4 5 16 0 0 2 15 0 21 0 0.122400 0.106000 9.530000E-029.200000E-029.110000E-028.150000E-027.580000E-026.920000E-02 6.310000E-025.930000E-025.220000E-024.470000E-023.880000E-022.390000E-02 1.670000E-021.350000E-021.200000E-021.090000E-021.020000E-029.800000E-03 @@ -1075,10 +1075,10 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 7.200000E-03 2017 4 5 24 0 0 2 15 0 2 1 7.100000E-03 2017 4 5 24 30 0 2 15 0 2 0 4.200000E-031.000000E-04 - 2017 4 6 1 0 0 2 15 0 19 1 0.00000 + 2017 4 6 1 0 0 2 15 0 19 1 0.00000 2017 4 6 5 45 0 2 15 0 3 0 1.050000E-021.700000E-03 1.000000E-04 - 2017 4 6 6 30 0 2 15 0 15 1 0.00000 + 2017 4 6 6 30 0 2 15 0 15 1 0.00000 2017 4 6 10 15 0 2 15 0 1 0 1.330000E-02 2017 4 6 10 30 0 2 15 0 2 1 1.320000E-02 2017 4 6 11 0 0 2 15 0 3 0 1.260000E-021.320000E-02 @@ -1094,7 +1094,7 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2017 4 6 18 0 0 2 15 0 2 1 9.500000E-03 2017 4 6 18 30 0 2 15 0 7 0 6.000000E-049.600000E-03 9.500000E-039.400000E-039.300000E-031.400000E-031.000000E-04 - 2017 4 6 20 15 0 2 15 0 4 1 0.00000 + 2017 4 6 20 15 0 2 15 0 4 1 0.00000 2017 4 6 21 15 0 2 15 0 3 0 1.020000E-021.010000E-02 1.600000E-03 2017 4 6 22 0 0 2 15 0 2 1 1.010000E-02 @@ -1104,65 +1104,65 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2017 4 6 24 0 0 2 15 0 1 0 5.000000E-04 2017 4 6 24 15 0 2 15 0 4 0 9.500000E-039.400000E-03 5.500000E-032.000000E-04 - 2017 4 7 1 15 0 2 15 0 330 1 0.00000 + 2017 4 7 1 15 0 2 15 0 330 1 0.00000 2017 4 10 11 45 0 2 15 0 7 0 4.950000E-024.610000E-02 4.530000E-024.510000E-026.800000E-033.000000E-041.000000E-04 - 2017 4 10 13 30 0 2 15 0 15 1 0.00000 + 2017 4 10 13 30 0 2 15 0 15 1 0.00000 2017 4 10 17 15 0 2 15 0 3 0 4.730000E-027.500000E-03 3.000000E-04 - 2017 4 10 18 0 0 2 15 0 21 1 0.00000 + 2017 4 10 18 0 0 2 15 0 21 1 0.00000 2017 4 10 23 15 0 2 15 0 11 0 5.010000E-024.910000E-02 4.660000E-023.480000E-022.180000E-021.200000E-029.300000E-037.700000E-03 7.000000E-036.700000E-036.200000E-03 2017 4 11 2 0 0 2 15 0 3 1 5.900000E-03 2017 4 11 2 45 0 2 15 0 1 0 3.000000E-04 - 2017 4 11 3 0 0 2 15 0 392 1 0.00000 + 2017 4 11 3 0 0 2 15 0 392 1 0.00000 2017 4 15 5 0 0 2 15 0 9 0 6.160000E-023.630000E-02 1.000000E-031.000000E-04 0.00000 6.170000E-023.640000E-021.000000E-03 1.000000E-04 - 2017 4 15 7 15 0 2 15 0 417 1 0.00000 + 2017 4 15 7 15 0 2 15 0 417 1 0.00000 2017 4 19 15 30 0 2 15 0 17 0 0.100400 9.650000E-02 8.830000E-027.450000E-024.930000E-023.910000E-023.540000E-023.220000E-02 2.900000E-022.670000E-022.480000E-022.360000E-022.330000E-022.320000E-02 3.800000E-032.000000E-041.000000E-04 - 2017 4 19 19 45 0 2 15 0 44 1 0.00000 + 2017 4 19 19 45 0 2 15 0 44 1 0.00000 2017 4 20 6 45 0 2 15 0 9 0 3.020000E-022.890000E-02 2.710000E-022.620000E-022.600000E-022.590000E-021.400000E-032.000000E-04 1.000000E-04 - 2017 4 20 9 0 0 2 15 0 20 1 0.00000 + 2017 4 20 9 0 0 2 15 0 20 1 0.00000 2017 4 20 14 0 0 2 15 0 13 0 2.930000E-022.640000E-02 2.910000E-022.790000E-021.410000E-028.400000E-037.200000E-036.400000E-03 5.700000E-035.600000E-035.500000E-033.300000E-031.000000E-04 - 2017 4 20 17 15 0 2 15 0 3 1 0.00000 + 2017 4 20 17 15 0 2 15 0 3 1 0.00000 2017 4 20 18 0 0 2 15 0 2 1 6.200000E-03 2017 4 20 18 30 0 2 15 0 1 0 9.000000E-04 - 2017 4 20 18 45 0 2 15 0 644 1 0.00000 + 2017 4 20 18 45 0 2 15 0 644 1 0.00000 2017 4 27 11 45 0 2 15 0 5 0 8.720000E-028.690000E-02 8.660000E-023.500000E-032.000000E-04 - 2017 4 27 13 0 0 2 15 0 236 1 0.00000 - 2017 4 29 24 0 0 2 15 0 17 0 0.104900 0.104400 + 2017 4 27 13 0 0 2 15 0 236 1 0.00000 + 2017 4 29 24 0 0 2 15 0 17 0 0.104900 0.104400 1.510000E-025.000000E-040.103900 0.100400 9.870000E-027.890000E-02 6.670000E-025.520000E-025.050000E-024.970000E-024.940000E-023.000000E-02 1.300000E-033.000000E-042.000000E-04 2017 4 30 4 15 0 2 15 0 3 1 1.000000E-04 - 2017 4 30 5 0 0 2 15 0 27 1 0.00000 + 2017 4 30 5 0 0 2 15 0 27 1 0.00000 2017 4 30 11 45 0 2 15 0 13 0 5.350000E-025.340000E-02 5.280000E-025.290000E-025.160000E-025.120000E-025.080000E-024.960000E-02 4.900000E-024.880000E-028.400000E-036.000000E-042.000000E-04 2017 4 30 15 0 0 2 15 0 3 1 1.000000E-04 - 2017 4 30 15 45 0 2 15 0 8 1 0.00000 + 2017 4 30 15 45 0 2 15 0 8 1 0.00000 2017 4 30 17 45 0 2 15 0 26 0 5.050000E-025.000000E-02 4.960000E-024.940000E-024.880000E-024.850000E-022.940000E-021.300000E-03 3.000000E-042.000000E-044.880000E-024.850000E-024.830000E-022.100000E-03 2.000000E-041.000000E-044.850000E-024.710000E-024.480000E-023.870000E-02 3.660000E-023.620000E-023.610000E-026.300000E-035.000000E-042.000000E-04 2017 5 1 0 15 0 2 15 0 2 1 1.000000E-04 - 2017 5 1 0 45 0 2 15 0 10 1 0.00000 + 2017 5 1 0 45 0 2 15 0 10 1 0.00000 2017 5 1 3 15 0 2 15 0 11 0 3.820000E-023.800000E-02 3.770000E-022.350000E-023.730000E-023.710000E-023.660000E-023.630000E-02 2.160000E-028.000000E-042.000000E-04 2017 5 1 6 0 0 2 15 0 3 1 1.000000E-04 - 2017 5 1 6 45 0 2 15 0 4 1 0.00000 + 2017 5 1 6 45 0 2 15 0 4 1 0.00000 2017 5 1 7 45 0 2 15 0 10 0 3.740000E-023.620000E-02 3.700000E-023.650000E-023.410000E-023.290000E-023.260000E-021.900000E-02 6.000000E-042.000000E-04 @@ -1171,10 +1171,10 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 3.170000E-023.140000E-023.120000E-023.080000E-023.070000E-021.800000E-03 3.000000E-04 2017 5 1 13 0 0 2 15 0 3 1 1.000000E-04 - 2017 5 1 13 45 0 2 15 0 64 1 0.00000 + 2017 5 1 13 45 0 2 15 0 64 1 0.00000 2017 5 2 5 45 0 2 15 0 4 0 4.060000E-024.050000E-02 2.200000E-032.000000E-04 - 2017 5 2 6 45 0 2 15 0 192 1 0.00000 + 2017 5 2 6 45 0 2 15 0 192 1 0.00000 2017 5 4 6 45 0 2 15 0 57 0 6.430000E-026.330000E-02 6.140000E-025.860000E-025.570000E-025.290000E-024.950000E-024.560000E-02 4.170000E-023.910000E-023.630000E-023.380000E-023.220000E-023.150000E-02 @@ -1189,11 +1189,11 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2017 5 4 21 0 0 2 15 0 2 1 4.600000E-03 2017 5 4 21 30 0 2 15 0 3 0 4.500000E-037.000000E-04 1.000000E-04 - 2017 5 4 22 15 0 2 15 0 5 1 0.00000 + 2017 5 4 22 15 0 2 15 0 5 1 0.00000 2017 5 4 23 30 0 2 15 0 2 1 5.800000E-03 2017 5 4 24 0 0 2 15 0 8 0 5.600000E-035.700000E-03 5.600000E-035.500000E-035.400000E-035.300000E-033.200000E-031.000000E-04 - 2017 5 5 2 0 0 2 15 0 10 1 0.00000 + 2017 5 5 2 0 0 2 15 0 10 1 0.00000 2017 5 5 4 30 0 2 15 0 2 0 7.300000E-037.000000E-03 2017 5 5 5 0 0 2 15 0 2 1 7.200000E-03 2017 5 5 5 30 0 2 15 0 2 1 7.100000E-03 @@ -1217,17 +1217,17 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2017 5 5 17 15 0 2 15 0 3 1 1.400000E-03 2017 5 5 18 0 0 2 15 0 3 1 1.300000E-03 2017 5 5 18 45 0 2 15 0 1 0 2.000000E-04 - 2017 5 5 19 0 0 2 15 0 504 1 0.00000 + 2017 5 5 19 0 0 2 15 0 504 1 0.00000 2017 5 11 1 0 0 2 15 0 16 0 7.110000E-027.090000E-02 6.990000E-026.760000E-026.230000E-025.890000E-025.620000E-025.370000E-02 5.210000E-025.070000E-025.010000E-024.940000E-024.900000E-022.860000E-02 1.000000E-032.000000E-04 2017 5 11 5 0 0 2 15 0 3 1 1.000000E-04 - 2017 5 11 5 45 0 2 15 0 18 1 0.00000 + 2017 5 11 5 45 0 2 15 0 18 1 0.00000 2017 5 11 10 15 0 2 15 0 7 0 4.220000E-023.990000E-02 3.940000E-023.930000E-022.300000E-034.000000E-042.000000E-04 2017 5 11 12 0 0 2 15 0 3 1 1.000000E-04 - 2017 5 11 12 45 0 2 15 0 442 1 0.00000 + 2017 5 11 12 45 0 2 15 0 442 1 0.00000 2017 5 16 3 15 0 2 15 0 8 0 8.870000E-028.670000E-02 8.490000E-028.440000E-021.310000E-029.000000E-043.000000E-042.000000E-04 2017 5 16 5 15 0 2 15 0 2 1 1.000000E-04 @@ -1236,36 +1236,36 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 7.000000E-044.000000E-04 2017 5 16 8 15 0 2 15 0 2 1 2.000000E-04 2017 5 16 8 45 0 2 15 0 3 1 1.000000E-04 - 2017 5 16 9 30 0 2 15 0 336 1 0.00000 + 2017 5 16 9 30 0 2 15 0 336 1 0.00000 2017 5 19 21 30 0 2 15 0 5 0 8.730000E-025.230000E-02 1.700000E-032.000000E-041.000000E-04 - 2017 5 19 22 45 0 2 15 0 65 1 0.00000 + 2017 5 19 22 45 0 2 15 0 65 1 0.00000 2017 5 20 15 0 0 2 15 0 13 0 9.290000E-029.180000E-02 8.620000E-027.890000E-027.450000E-027.250000E-027.200000E-024.400000E-02 2.200000E-037.000000E-044.000000E-043.000000E-042.000000E-04 2017 5 20 18 15 0 2 15 0 3 1 1.000000E-04 - 2017 5 20 19 0 0 2 15 0 23 1 0.00000 + 2017 5 20 19 0 0 2 15 0 23 1 0.00000 2017 5 21 0 45 0 2 15 0 8 0 7.340000E-026.070000E-02 5.620000E-023.550000E-022.860000E-029.800000E-038.300000E-037.800000E-03 2017 5 21 2 45 0 2 15 0 2 1 7.700000E-03 2017 5 21 3 15 0 2 15 0 2 0 4.000000E-041.000000E-04 - 2017 5 21 3 45 0 2 15 0 14 1 0.00000 + 2017 5 21 3 45 0 2 15 0 14 1 0.00000 2017 5 21 7 15 0 2 15 0 2 0 1.040000E-021.800000E-03 2017 5 21 7 45 0 2 15 0 2 1 1.050000E-02 2017 5 21 8 15 0 2 15 0 2 0 6.000000E-041.000000E-04 - 2017 5 21 8 45 0 2 15 0 5 1 0.00000 + 2017 5 21 8 45 0 2 15 0 5 1 0.00000 2017 5 21 10 0 0 2 15 0 4 0 1.180000E-021.150000E-02 1.100000E-021.060000E-02 2017 5 21 11 0 0 2 15 0 2 1 1.040000E-02 2017 5 21 11 30 0 2 15 0 2 0 2.000000E-032.000000E-04 2017 5 21 12 0 0 2 15 0 2 1 1.000000E-04 - 2017 5 21 12 30 0 2 15 0 11 1 0.00000 + 2017 5 21 12 30 0 2 15 0 11 1 0.00000 2017 5 21 15 15 0 2 15 0 7 0 1.110000E-028.600000E-03 8.400000E-038.300000E-035.000000E-032.000000E-041.000000E-04 - 2017 5 21 17 0 0 2 15 0 271 1 0.00000 + 2017 5 21 17 0 0 2 15 0 271 1 0.00000 2017 5 24 12 45 0 2 15 0 4 0 4.870000E-028.200000E-03 4.000000E-041.000000E-04 - 2017 5 24 13 45 0 2 15 0 16 1 0.00000 + 2017 5 24 13 45 0 2 15 0 16 1 0.00000 2017 5 24 17 45 0 2 15 0 17 0 5.060000E-024.920000E-02 4.860000E-024.840000E-022.700000E-034.000000E-042.000000E-044.870000E-02 4.830000E-024.640000E-024.440000E-024.340000E-024.290000E-024.270000E-02 @@ -1275,7 +1275,7 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 3.730000E-023.580000E-023.540000E-023.530000E-022.200000E-034.000000E-04 2.000000E-04 2017 5 25 1 0 0 2 15 0 3 1 1.000000E-04 - 2017 5 25 1 45 0 2 15 0 15 1 0.00000 + 2017 5 25 1 45 0 2 15 0 15 1 0.00000 2017 5 25 5 30 0 2 15 0 24 0 3.830000E-023.710000E-02 3.130000E-022.070000E-021.390000E-021.090000E-021.020000E-021.000000E-02 9.900000E-031.700000E-032.000000E-041.000000E-04 0.00000 1.060000E-02 @@ -1283,83 +1283,83 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 3.500000E-033.000000E-032.700000E-032.600000E-03 2017 5 25 11 30 0 2 15 0 2 1 2.500000E-03 2017 5 25 12 0 0 2 15 0 1 0 4.000000E-04 - 2017 5 25 12 15 0 2 15 0 4 1 0.00000 + 2017 5 25 12 15 0 2 15 0 4 1 0.00000 2017 5 25 13 15 0 2 15 0 1 0 3.500000E-03 2017 5 25 13 30 0 2 15 0 2 1 3.400000E-03 2017 5 25 14 0 0 2 15 0 2 1 3.300000E-03 2017 5 25 14 30 0 2 15 0 2 1 3.200000E-03 2017 5 25 15 0 0 2 15 0 1 0 2.000000E-04 - 2017 5 25 15 15 0 2 15 0 292 1 0.00000 + 2017 5 25 15 15 0 2 15 0 292 1 0.00000 2017 5 28 16 15 0 2 15 0 10 0 4.760000E-022.850000E-02 4.250000E-024.740000E-024.440000E-024.710000E-022.760000E-029.000000E-04 2.000000E-041.000000E-04 - 2017 5 28 18 45 0 2 15 0 9 1 0.00000 + 2017 5 28 18 45 0 2 15 0 9 1 0.00000 2017 5 28 21 0 0 2 15 0 12 0 4.850000E-024.290000E-02 3.970000E-023.820000E-023.780000E-023.710000E-023.690000E-022.300000E-02 1.400000E-035.000000E-043.000000E-042.000000E-04 2017 5 28 24 0 0 2 15 0 3 1 1.000000E-04 - 2017 5 28 24 45 0 2 15 0 60 1 0.00000 + 2017 5 28 24 45 0 2 15 0 60 1 0.00000 2017 5 29 15 45 0 2 15 0 16 0 4.600000E-022.760000E-02 9.000000E-044.580000E-024.540000E-022.670000E-029.000000E-042.000000E-04 4.370000E-022.880000E-022.760000E-022.740000E-022.730000E-022.000000E-03 5.000000E-042.000000E-04 2017 5 29 19 45 0 2 15 0 4 1 1.000000E-04 - 2017 5 29 20 45 0 2 15 0 112 1 0.00000 + 2017 5 29 20 45 0 2 15 0 112 1 0.00000 2017 5 31 0 45 0 2 15 0 5 0 4.400000E-024.380000E-02 7.200000E-033.000000E-041.000000E-04 - 2017 5 31 2 0 0 2 15 0 223 1 0.00000 + 2017 5 31 2 0 0 2 15 0 223 1 0.00000 2017 6 2 9 45 0 2 15 0 8 0 6.440000E-025.680000E-02 5.580000E-025.560000E-023.800000E-031.000000E-035.000000E-043.000000E-04 2017 6 2 11 45 0 2 15 0 2 1 2.000000E-04 2017 6 2 12 15 0 2 15 0 2 1 1.000000E-04 - 2017 6 2 12 45 0 2 15 0 178 1 0.00000 + 2017 6 2 12 45 0 2 15 0 178 1 0.00000 2017 6 4 9 15 0 2 15 0 3 0 7.610000E-024.440000E-02 1.200000E-03 2017 6 4 10 0 0 2 15 0 2 1 1.000000E-04 - 2017 6 4 10 30 0 2 15 0 961 1 0.00000 + 2017 6 4 10 30 0 2 15 0 961 1 0.00000 2017 6 14 10 45 0 2 15 0 10 0 0.129300 6.790000E-02 6.150000E-026.060000E-026.030000E-024.700000E-031.300000E-037.000000E-04 4.000000E-043.000000E-04 2017 6 14 13 15 0 2 15 0 2 1 2.000000E-04 2017 6 14 13 45 0 2 15 0 1 0 1.000000E-04 - 2017 6 14 14 0 0 2 15 0 60 1 0.00000 + 2017 6 14 14 0 0 2 15 0 60 1 0.00000 2017 6 15 5 0 0 2 15 0 3 0 6.790000E-023.970000E-02 1.100000E-03 2017 6 15 5 45 0 2 15 0 2 1 1.000000E-04 - 2017 6 15 6 15 0 2 15 0 32 1 0.00000 + 2017 6 15 6 15 0 2 15 0 32 1 0.00000 2017 6 15 14 15 0 2 15 0 4 0 7.140000E-023.300000E-03 2.000000E-041.000000E-04 - 2017 6 15 15 15 0 2 15 0 20 1 0.00000 + 2017 6 15 15 15 0 2 15 0 20 1 0.00000 2017 6 15 20 15 0 2 15 0 4 0 7.360000E-023.400000E-03 2.000000E-041.000000E-04 - 2017 6 15 21 15 0 2 15 0 169 1 0.00000 + 2017 6 15 21 15 0 2 15 0 169 1 0.00000 2017 6 17 15 30 0 2 15 0 10 0 8.960000E-025.000000E-02 3.460000E-023.330000E-023.300000E-022.110000E-021.800000E-038.000000E-04 4.000000E-043.000000E-04 2017 6 17 18 0 0 2 15 0 2 1 2.000000E-04 2017 6 17 18 30 0 2 15 0 1 0 1.000000E-04 - 2017 6 17 18 45 0 2 15 0 17 1 0.00000 + 2017 6 17 18 45 0 2 15 0 17 1 0.00000 2017 6 17 23 0 0 2 15 0 3 0 3.640000E-025.500000E-03 2.000000E-04 - 2017 6 17 23 45 0 2 15 0 153 1 0.00000 + 2017 6 17 23 45 0 2 15 0 153 1 0.00000 2017 6 19 14 0 0 2 15 0 12 0 5.620000E-025.450000E-02 5.180000E-024.940000E-024.760000E-024.660000E-024.630000E-029.500000E-03 1.700000E-038.000000E-045.000000E-043.000000E-04 2017 6 19 17 0 0 2 15 0 2 1 2.000000E-04 2017 6 19 17 30 0 2 15 0 1 0 1.000000E-04 - 2017 6 19 17 45 0 2 15 0 97 1 0.00000 + 2017 6 19 17 45 0 2 15 0 97 1 0.00000 2017 6 20 18 0 0 2 15 0 13 0 5.920000E-029.000000E-03 5.890000E-029.200000E-035.870000E-025.860000E-023.300000E-035.000000E-04 5.830000E-025.810000E-023.500000E-038.000000E-044.000000E-04 2017 6 20 21 15 0 2 15 0 2 1 2.000000E-04 2017 6 20 21 45 0 2 15 0 3 1 1.000000E-04 - 2017 6 20 22 30 0 2 15 0 130 1 0.00000 + 2017 6 20 22 30 0 2 15 0 130 1 0.00000 2017 6 22 7 0 0 2 15 0 17 0 7.310000E-023.300000E-03 7.240000E-024.370000E-021.500000E-032.000000E-047.210000E-027.300000E-02 4.900000E-036.000000E-042.000000E-041.000000E-047.320000E-027.310000E-02 4.100000E-035.000000E-042.000000E-04 2017 6 22 11 15 0 2 15 0 3 1 1.000000E-04 - 2017 6 22 12 0 0 2 15 0 29 1 0.00000 + 2017 6 22 12 0 0 2 15 0 29 1 0.00000 2017 6 22 19 15 0 2 15 0 34 0 7.050000E-025.020000E-02 3.830000E-023.130000E-022.690000E-022.360000E-022.110000E-021.910000E-02 1.760000E-021.630000E-021.530000E-021.440000E-021.370000E-021.300000E-02 @@ -1386,7 +1386,7 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 1.000000E-047.300000E-037.200000E-035.000000E-041.000000E-04 2017 6 23 12 0 0 2 15 0 2 1 7.500000E-03 2017 6 23 12 30 0 2 15 0 3 0 4.000000E-041.000000E-04 - 0.00000 + 0.00000 2017 6 23 13 15 0 2 15 0 2 1 8.000000E-03 2017 6 23 13 45 0 2 15 0 1 0 1.500000E-03 2017 6 23 14 0 0 2 15 0 2 1 8.000000E-03 @@ -1397,28 +1397,28 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2017 6 23 16 30 0 2 15 0 2 1 8.800000E-03 2017 6 23 17 0 0 2 15 0 2 0 1.800000E-033.000000E-04 2017 6 23 17 30 0 2 15 0 3 1 1.000000E-04 - 2017 6 23 18 15 0 2 15 0 254 1 0.00000 + 2017 6 23 18 15 0 2 15 0 254 1 0.00000 2017 6 26 9 45 0 2 15 0 8 0 4.320000E-023.800000E-02 3.740000E-023.730000E-022.500000E-036.000000E-043.000000E-042.000000E-04 2017 6 26 11 45 0 2 15 0 3 1 1.000000E-04 - 2017 6 26 12 30 0 2 15 0 20 1 0.00000 + 2017 6 26 12 30 0 2 15 0 20 1 0.00000 2017 6 26 17 30 0 2 15 0 3 0 4.090000E-021.900000E-03 1.000000E-04 - 2017 6 26 18 15 0 2 15 0 11 1 0.00000 + 2017 6 26 18 15 0 2 15 0 11 1 0.00000 2017 6 26 21 0 0 2 15 0 7 0 4.260000E-026.400000E-03 3.000000E-044.090000E-024.270000E-022.700000E-033.000000E-04 2017 6 26 22 45 0 2 15 0 2 1 1.000000E-04 - 2017 6 26 23 15 0 2 15 0 213 1 0.00000 + 2017 6 26 23 15 0 2 15 0 213 1 0.00000 2017 6 29 4 30 0 2 15 0 4 0 6.880000E-021.040000E-02 5.000000E-041.000000E-04 - 2017 6 29 5 30 0 2 15 0 79 1 0.00000 + 2017 6 29 5 30 0 2 15 0 79 1 0.00000 2017 6 30 1 15 0 2 15 0 16 0 7.700000E-027.660000E-02 4.650000E-027.290000E-027.540000E-027.050000E-026.480000E-026.120000E-02 5.790000E-025.530000E-025.370000E-025.250000E-025.210000E-028.700000E-03 1.000000E-034.000000E-04 2017 6 30 5 15 0 2 15 0 2 1 2.000000E-04 2017 6 30 5 45 0 2 15 0 3 1 1.000000E-04 - 2017 6 30 6 30 0 2 15 0 39 1 0.00000 + 2017 6 30 6 30 0 2 15 0 39 1 0.00000 2017 6 30 16 15 0 2 15 0 23 0 5.770000E-025.420000E-02 4.900000E-024.570000E-024.480000E-024.390000E-024.360000E-024.330000E-02 4.250000E-024.080000E-023.820000E-023.610000E-023.520000E-023.500000E-02 @@ -1426,8 +1426,8 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 8.000000E-045.000000E-043.000000E-04 2017 6 30 22 0 0 2 15 0 2 1 2.000000E-04 2017 6 30 22 30 0 2 15 0 1 0 1.000000E-04 - 2017 6 30 22 45 0 2 15 0 265 1 0.00000 - 2017 7 3 17 0 0 2 15 0 331 1 0.00000 + 2017 6 30 22 45 0 2 15 0 265 1 0.00000 + 2017 7 3 17 0 0 2 15 0 331 1 0.00000 2017 7 7 3 45 0 2 15 0 10 0 9.850000E-028.130000E-02 6.760000E-026.410000E-025.340000E-024.400000E-023.900000E-023.400000E-02 2.900000E-022.640000E-02 @@ -1436,100 +1436,100 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 3.000000E-04 2017 7 7 8 30 0 2 15 0 2 1 2.000000E-04 2017 7 7 9 0 0 2 15 0 2 1 1.000000E-04 - 2017 7 7 9 30 0 2 15 0 38 1 0.00000 + 2017 7 7 9 30 0 2 15 0 38 1 0.00000 2017 7 7 19 0 0 2 15 0 4 0 2.160000E-024.800000E-03 1.600000E-031.100000E-03 2017 7 7 20 0 0 2 15 0 3 1 1.000000E-03 2017 7 7 20 45 0 2 15 0 2 0 9.000000E-041.000000E-04 - 2017 7 7 21 15 0 2 15 0 240 1 0.00000 + 2017 7 7 21 15 0 2 15 0 240 1 0.00000 2017 7 10 9 15 0 2 15 0 19 0 3.880000E-023.270000E-02 2.690000E-022.290000E-022.040000E-021.880000E-021.720000E-021.620000E-02 1.550000E-021.500000E-021.460000E-021.430000E-021.390000E-021.380000E-02 1.360000E-021.350000E-021.600000E-036.000000E-043.000000E-04 2017 7 10 14 0 0 2 15 0 2 1 2.000000E-04 2017 7 10 14 30 0 2 15 0 2 1 1.000000E-04 - 2017 7 10 15 0 0 2 15 0 93 1 0.00000 + 2017 7 10 15 0 0 2 15 0 93 1 0.00000 2017 7 11 14 15 0 2 15 0 3 0 2.910000E-021.600000E-03 2.000000E-04 2017 7 11 15 0 0 2 15 0 2 1 1.000000E-04 - 2017 7 11 15 30 0 2 15 0 82 1 0.00000 + 2017 7 11 15 30 0 2 15 0 82 1 0.00000 2017 7 12 12 0 0 2 15 0 8 0 3.650000E-022.750000E-02 2.610000E-022.570000E-021.600000E-021.300000E-036.000000E-043.000000E-04 2017 7 12 14 0 0 2 15 0 2 1 2.000000E-04 2017 7 12 14 30 0 2 15 0 2 1 1.000000E-04 - 2017 7 12 15 0 0 2 15 0 54 1 0.00000 + 2017 7 12 15 0 0 2 15 0 54 1 0.00000 2017 7 13 4 30 0 2 15 0 15 0 3.450000E-023.310000E-02 3.000000E-022.780000E-022.630000E-022.430000E-022.170000E-022.010000E-02 1.980000E-021.950000E-021.940000E-024.300000E-031.000000E-035.000000E-04 3.000000E-04 2017 7 13 8 15 0 2 15 0 2 1 2.000000E-04 2017 7 13 8 45 0 2 15 0 2 1 1.000000E-04 - 2017 7 13 9 15 0 2 15 0 865 1 0.00000 + 2017 7 13 9 15 0 2 15 0 865 1 0.00000 2017 7 22 9 30 0 2 15 0 6 0 0.110400 6.630000E-02 2.500000E-036.000000E-043.000000E-042.000000E-04 2017 7 22 11 0 0 2 15 0 3 1 1.000000E-04 - 2017 7 22 11 45 0 2 15 0 361 1 0.00000 + 2017 7 22 11 45 0 2 15 0 361 1 0.00000 2017 7 26 6 0 0 2 15 0 5 0 0.129800 7.800000E-02 2.900000E-037.000000E-043.000000E-04 2017 7 26 7 15 0 2 15 0 2 1 2.000000E-04 2017 7 26 7 45 0 2 15 0 3 1 1.000000E-04 - 2017 7 26 8 30 0 2 15 0 578 1 0.00000 - 2017 8 1 9 0 0 2 15 0 12 0 0.148700 0.121400 + 2017 7 26 8 30 0 2 15 0 578 1 0.00000 + 2017 8 1 9 0 0 2 15 0 12 0 0.148700 0.121400 0.118200 0.117500 2.980000E-028.100000E-034.100000E-032.600000E-03 1.900000E-031.400000E-031.100000E-036.000000E-04 - 2017 8 1 12 0 0 2 15 0 112 1 0.00000 + 2017 8 1 12 0 0 2 15 0 112 1 0.00000 2017 8 2 16 0 0 2 15 0 1 0 9.700000E-03 - 2017 8 2 16 15 0 2 15 0 141 1 0.00000 + 2017 8 2 16 15 0 2 15 0 141 1 0.00000 2017 8 4 3 30 0 2 15 0 1 0 2.300000E-02 2017 8 4 3 45 0 2 15 0 2 1 2.290000E-02 2017 8 4 4 15 0 2 15 0 2 0 1.500000E-032.000000E-04 2017 8 4 4 45 0 2 15 0 2 1 1.000000E-04 - 2017 8 4 5 15 0 2 15 0 673 1 0.00000 + 2017 8 4 5 15 0 2 15 0 673 1 0.00000 2017 8 11 5 30 0 2 15 0 11 0 9.790000E-029.660000E-02 9.600000E-022.340000E-024.600000E-032.200000E-031.400000E-031.000000E-03 7.000000E-046.000000E-043.000000E-04 - 2017 8 11 8 15 0 2 15 0 127 1 0.00000 - 2017 8 12 16 0 0 2 15 0 6 0 0.105800 0.105200 + 2017 8 11 8 15 0 2 15 0 127 1 0.00000 + 2017 8 12 16 0 0 2 15 0 6 0 0.105800 0.105200 1.710000E-021.000000E-033.000000E-042.000000E-04 2017 8 12 17 30 0 2 15 0 3 1 1.000000E-04 - 2017 8 12 18 15 0 2 15 0 8 1 0.00000 - 2017 8 12 20 15 0 2 15 0 11 0 0.105300 0.103900 + 2017 8 12 18 15 0 2 15 0 8 1 0.00000 + 2017 8 12 20 15 0 2 15 0 11 0 0.105300 0.103900 0.103500 1.160000E-023.500000E-031.800000E-031.200000E-039.000000E-04 7.000000E-045.000000E-043.000000E-04 - 2017 8 12 23 0 0 2 15 0 16 1 0.00000 + 2017 8 12 23 0 0 2 15 0 16 1 0.00000 2017 8 13 3 0 0 2 15 0 4 0 0.104900 5.600000E-03 6.000000E-042.000000E-04 2017 8 13 4 0 0 2 15 0 4 1 1.000000E-04 - 2017 8 13 5 0 0 2 15 0 200 1 0.00000 + 2017 8 13 5 0 0 2 15 0 200 1 0.00000 2017 8 15 7 0 0 2 15 0 17 0 0.117800 7.030000E-02 0.116700 0.114200 0.111900 7.860000E-027.170000E-026.970000E-02 6.920000E-021.670000E-024.300000E-032.100000E-031.400000E-031.000000E-03 7.000000E-046.000000E-043.000000E-04 - 2017 8 15 11 15 0 2 15 0 172 1 0.00000 + 2017 8 15 11 15 0 2 15 0 172 1 0.00000 2017 8 17 6 15 0 2 15 0 15 0 8.670000E-028.620000E-02 5.160000E-023.950000E-023.140000E-023.000000E-022.970000E-025.200000E-03 2.900000E-022.810000E-022.790000E-025.500000E-031.000000E-035.000000E-04 3.000000E-04 2017 8 17 10 0 0 2 15 0 2 1 2.000000E-04 2017 8 17 10 30 0 2 15 0 2 1 1.000000E-04 - 2017 8 17 11 0 0 2 15 0 4 1 0.00000 + 2017 8 17 11 0 0 2 15 0 4 1 0.00000 2017 8 17 12 0 0 2 15 0 17 0 2.950000E-022.880000E-02 2.660000E-022.380000E-022.130000E-021.900000E-021.670000E-021.520000E-02 1.360000E-021.260000E-021.210000E-021.200000E-027.900000E-031.000000E-03 4.000000E-043.000000E-042.000000E-04 2017 8 17 16 15 0 2 15 0 3 1 1.000000E-04 - 2017 8 17 17 0 0 2 15 0 467 1 0.00000 + 2017 8 17 17 0 0 2 15 0 467 1 0.00000 2017 8 22 13 45 0 2 15 0 9 0 4.630000E-023.630000E-02 3.550000E-023.540000E-023.300000E-031.200000E-036.000000E-044.000000E-04 3.000000E-04 2017 8 22 16 0 0 2 15 0 2 1 2.000000E-04 2017 8 22 16 30 0 2 15 0 1 0 1.000000E-04 - 2017 8 22 16 45 0 2 15 0 559 1 0.00000 + 2017 8 22 16 45 0 2 15 0 559 1 0.00000 2017 8 28 12 30 0 2 15 0 9 0 9.630000E-025.740000E-02 2.000000E-034.000000E-049.460000E-025.740000E-022.000000E-034.000000E-04 2.000000E-04 2017 8 28 14 45 0 2 15 0 3 1 1.000000E-04 - 2017 8 28 15 30 0 2 15 0 8 1 0.00000 + 2017 8 28 15 30 0 2 15 0 8 1 0.00000 2017 8 28 17 30 0 2 15 0 14 0 9.180000E-025.130000E-02 3.270000E-023.030000E-022.960000E-022.910000E-022.900000E-023.500000E-03 1.300000E-031.500000E-026.000000E-035.200000E-035.000000E-034.900000E-03 @@ -1539,7 +1539,7 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2017 8 28 23 30 0 2 15 0 2 1 2.900000E-03 2017 8 28 24 0 0 2 15 0 1 0 3.000000E-04 2017 8 28 24 15 0 2 15 0 2 1 1.000000E-04 - 2017 8 28 24 45 0 2 15 0 50 1 0.00000 + 2017 8 28 24 45 0 2 15 0 50 1 0.00000 2017 8 29 13 15 0 2 15 0 11 0 1.210000E-022.000000E-03 1.120000E-021.220000E-021.160000E-021.110000E-021.080000E-021.070000E-02 7.100000E-039.000000E-044.000000E-04 @@ -1549,93 +1549,93 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2017 8 29 17 15 0 2 15 0 2 1 1.160000E-02 2017 8 29 17 45 0 2 15 0 2 0 9.000000E-043.000000E-04 2017 8 29 18 15 0 2 15 0 3 1 1.000000E-04 - 2017 8 29 19 0 0 2 15 0 20 1 0.00000 + 2017 8 29 19 0 0 2 15 0 20 1 0.00000 2017 8 29 24 0 0 2 15 0 4 0 1.580000E-029.400000E-03 3.000000E-041.000000E-04 - 2017 8 30 1 0 0 2 15 0 21 1 0.00000 + 2017 8 30 1 0 0 2 15 0 21 1 0.00000 2017 8 30 6 15 0 2 15 0 4 0 1.950000E-023.200000E-03 2.000000E-041.000000E-04 - 2017 8 30 7 15 0 2 15 0 374 1 0.00000 + 2017 8 30 7 15 0 2 15 0 374 1 0.00000 2017 9 3 4 45 0 2 15 0 10 0 6.860000E-026.390000E-02 6.250000E-026.180000E-026.100000E-026.080000E-023.600000E-037.000000E-04 3.000000E-042.000000E-04 2017 9 3 7 15 0 2 15 0 3 1 1.000000E-04 - 2017 9 3 8 0 0 2 15 0 84 1 0.00000 - 2017 9 4 5 0 0 2 15 0 50 1 0.00000 + 2017 9 3 8 0 0 2 15 0 84 1 0.00000 + 2017 9 4 5 0 0 2 15 0 50 1 0.00000 2017 9 4 17 30 0 2 15 0 11 0 6.730000E-024.400000E-02 3.630000E-022.350000E-021.960000E-021.830000E-021.800000E-021.790000E-02 3.400000E-034.000000E-042.000000E-04 2017 9 4 20 15 0 2 15 0 3 1 1.000000E-04 - 2017 9 4 21 0 0 2 15 0 41 1 0.00000 + 2017 9 4 21 0 0 2 15 0 41 1 0.00000 2017 9 5 7 15 0 2 15 0 2 0 2.110000E-022.000000E-02 2017 9 5 7 45 0 2 15 0 2 1 1.980000E-02 2017 9 5 8 15 0 2 15 0 3 0 1.500000E-034.000000E-04 2.000000E-04 2017 9 5 9 0 0 2 15 0 3 1 1.000000E-04 - 2017 9 5 9 45 0 2 15 0 218 1 0.00000 + 2017 9 5 9 45 0 2 15 0 218 1 0.00000 2017 9 7 16 15 0 2 15 0 8 0 5.130000E-025.010000E-02 4.740000E-024.590000E-024.540000E-022.670000E-021.000000E-033.000000E-04 2017 9 7 18 15 0 2 15 0 3 1 1.000000E-04 - 2017 9 7 19 0 0 2 15 0 46 1 0.00000 + 2017 9 7 19 0 0 2 15 0 46 1 0.00000 2017 9 8 6 30 0 2 15 0 5 0 5.180000E-023.140000E-02 1.100000E-032.000000E-041.000000E-04 - 2017 9 8 7 45 0 2 15 0 283 1 0.00000 + 2017 9 8 7 45 0 2 15 0 283 1 0.00000 2017 9 11 6 30 0 2 15 0 4 0 8.260000E-021.440000E-02 8.000000E-042.000000E-04 2017 9 11 7 30 0 2 15 0 2 1 1.000000E-04 - 2017 9 11 8 0 0 2 15 0 574 1 0.00000 + 2017 9 11 8 0 0 2 15 0 574 1 0.00000 2017 9 17 7 30 0 2 15 0 4 0 0.122700 2.140000E-02 1.200000E-033.000000E-04 2017 9 17 8 30 0 2 15 0 3 1 1.000000E-04 - 2017 9 17 9 15 0 2 15 0 202 1 0.00000 - 2017 9 19 11 45 0 2 15 0 19 0 0.132100 0.130500 - 0.123700 0.117900 0.114700 0.112400 0.111200 0.110900 - 8.900000E-032.400000E-030.110500 0.107800 0.103700 0.102200 + 2017 9 17 9 15 0 2 15 0 202 1 0.00000 + 2017 9 19 11 45 0 2 15 0 19 0 0.132100 0.130500 + 0.123700 0.117900 0.114700 0.112400 0.111200 0.110900 + 8.900000E-032.400000E-030.110500 0.107800 0.103700 0.102200 0.101800 5.600000E-031.000000E-035.000000E-043.000000E-04 2017 9 19 16 30 0 2 15 0 2 1 2.000000E-04 2017 9 19 17 0 0 2 15 0 2 1 1.000000E-04 - 2017 9 19 17 30 0 2 15 0 1208 1 0.00000 + 2017 9 19 17 30 0 2 15 0 1208 1 0.00000 2017 10 2 7 30 0 2 15 0 3 0 0.151700 2.160000E-02 6.000000E-04 - 2017 10 2 8 15 0 2 15 0 342 1 0.00000 - 2017 10 5 21 45 0 2 15 0 16 0 0.157200 0.155500 - 0.151400 0.149900 0.149400 8.550000E-020.145500 0.135600 - 0.132600 0.129600 0.124900 0.122900 0.122100 0.121800 + 2017 10 2 8 15 0 2 15 0 342 1 0.00000 + 2017 10 5 21 45 0 2 15 0 16 0 0.157200 0.155500 + 0.151400 0.149900 0.149400 8.550000E-020.145500 0.135600 + 0.132600 0.129600 0.124900 0.122900 0.122100 0.121800 4.600000E-032.000000E-04 - 2017 10 6 1 45 0 2 15 0 6 1 0.00000 - 2017 10 6 3 15 0 2 15 0 3 0 0.121800 0.120900 - 0.120500 - 2017 10 6 4 0 0 2 15 0 37 0 0.118800 0.117400 - 0.115700 0.115100 0.114900 4.600000E-030.113700 0.107300 + 2017 10 6 1 45 0 2 15 0 6 1 0.00000 + 2017 10 6 3 15 0 2 15 0 3 0 0.121800 0.120900 + 0.120500 + 2017 10 6 4 0 0 2 15 0 37 0 0.118800 0.117400 + 0.115700 0.115100 0.114900 4.600000E-030.113700 0.107300 9.840000E-029.080000E-028.230000E-027.720000E-027.220000E-026.920000E-02 6.600000E-026.190000E-025.990000E-025.860000E-025.800000E-025.770000E-02 3.230000E-025.740000E-024.810000E-024.420000E-024.300000E-024.240000E-02 4.220000E-024.210000E-024.190000E-024.100000E-024.050000E-024.020000E-02 3.960000E-023.940000E-023.930000E-025.900000E-032.000000E-04 - 2017 10 6 13 15 0 2 15 0 26 1 0.00000 + 2017 10 6 13 15 0 2 15 0 26 1 0.00000 2017 10 6 19 45 0 2 15 0 8 0 4.310000E-024.300000E-02 1.700000E-034.290000E-024.260000E-024.240000E-022.450000E-026.000000E-04 - 2017 10 6 21 45 0 2 15 0 14 1 0.00000 + 2017 10 6 21 45 0 2 15 0 14 1 0.00000 2017 10 7 1 15 0 2 15 0 11 0 4.450000E-024.430000E-02 4.360000E-024.260000E-024.220000E-024.210000E-024.160000E-024.130000E-02 4.110000E-025.500000E-031.000000E-04 - 2017 10 7 4 0 0 2 15 0 69 1 0.00000 + 2017 10 7 4 0 0 2 15 0 69 1 0.00000 2017 10 7 21 15 0 2 15 0 12 0 5.020000E-027.100000E-03 2.000000E-04 0.00000 4.960000E-024.250000E-023.750000E-023.650000E-02 3.620000E-023.610000E-024.900000E-031.000000E-04 - 2017 10 8 0 15 0 2 15 0 95 1 0.00000 + 2017 10 8 0 15 0 2 15 0 95 1 0.00000 2017 10 8 24 0 0 2 15 0 4 0 4.910000E-024.900000E-02 1.900000E-031.000000E-04 - 2017 10 9 1 0 0 2 15 0 7 1 0.00000 + 2017 10 9 1 0 0 2 15 0 7 1 0.00000 2017 10 9 2 45 0 2 15 0 3 0 5.000000E-027.100000E-03 2.000000E-04 - 2017 10 9 3 30 0 2 15 0 111 1 0.00000 + 2017 10 9 3 30 0 2 15 0 111 1 0.00000 2017 10 10 7 15 0 2 15 0 4 0 6.350000E-026.330000E-02 2.500000E-031.000000E-04 - 2017 10 10 8 15 0 2 15 0 70 1 0.00000 + 2017 10 10 8 15 0 2 15 0 70 1 0.00000 2017 10 11 1 45 0 2 15 0 8 0 7.120000E-027.100000E-02 2.800000E-031.000000E-046.610000E-027.100000E-021.080000E-023.000000E-04 - 2017 10 11 3 45 0 2 15 0 3 1 0.00000 + 2017 10 11 3 45 0 2 15 0 3 1 0.00000 2017 10 11 4 30 0 2 15 0 26 0 6.990000E-026.570000E-02 6.270000E-025.650000E-025.320000E-025.030000E-024.340000E-023.550000E-02 3.180000E-023.090000E-022.990000E-022.660000E-022.420000E-022.310000E-02 @@ -1650,20 +1650,20 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2017 10 11 15 0 0 2 15 0 4 1 8.400000E-03 2017 10 11 16 0 0 2 15 0 2 1 8.300000E-03 2017 10 11 16 30 0 2 15 0 2 0 4.600000E-031.000000E-04 - 2017 10 11 17 0 0 2 15 0 65 1 0.00000 + 2017 10 11 17 0 0 2 15 0 65 1 0.00000 2017 10 12 9 15 0 2 15 0 2 1 1.910000E-02 2017 10 12 9 45 0 2 15 0 2 0 1.900000E-021.890000E-02 2017 10 12 10 15 0 2 15 0 2 1 1.870000E-02 2017 10 12 10 45 0 2 15 0 2 0 1.070000E-023.000000E-04 - 2017 10 12 11 15 0 2 15 0 183 1 0.00000 + 2017 10 12 11 15 0 2 15 0 183 1 0.00000 2017 10 14 9 0 0 2 15 0 13 0 4.540000E-024.530000E-02 1.800000E-034.470000E-024.190000E-024.060000E-024.020000E-023.980000E-02 3.930000E-023.910000E-023.900000E-021.700000E-031.000000E-04 - 2017 10 14 12 15 0 2 15 0 5 1 0.00000 + 2017 10 14 12 15 0 2 15 0 5 1 0.00000 2017 10 14 13 30 0 2 15 0 11 0 3.970000E-023.930000E-02 3.850000E-023.780000E-023.680000E-023.530000E-023.440000E-023.410000E-02 3.390000E-021.940000E-024.000000E-04 - 2017 10 14 16 15 0 2 15 0 3 1 0.00000 + 2017 10 14 16 15 0 2 15 0 3 1 0.00000 2017 10 14 17 0 0 2 15 0 15 0 3.450000E-023.420000E-02 3.410000E-023.370000E-023.340000E-023.290000E-023.260000E-023.250000E-02 3.190000E-023.120000E-023.030000E-022.970000E-022.950000E-022.920000E-02 @@ -1672,25 +1672,25 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 2017 10 14 21 15 0 2 15 0 10 0 1.300000E-031.000000E-04 2.860000E-022.410000E-022.080000E-022.000000E-021.980000E-021.970000E-02 1.120000E-022.000000E-04 - 2017 10 14 23 45 0 2 15 0 48 1 0.00000 + 2017 10 14 23 45 0 2 15 0 48 1 0.00000 2017 10 15 11 45 0 2 15 0 3 0 2.730000E-021.560000E-02 3.000000E-04 - 2017 10 15 12 30 0 2 15 0 773 1 0.00000 + 2017 10 15 12 30 0 2 15 0 773 1 0.00000 2017 10 23 13 45 0 2 15 0 19 0 0.107300 9.600000E-02 8.460000E-028.090000E-027.870000E-027.700000E-027.460000E-027.260000E-02 7.030000E-026.600000E-026.120000E-025.610000E-025.080000E-024.760000E-02 4.590000E-024.470000E-024.370000E-024.270000E-024.210000E-02 2017 10 23 18 30 0 2 15 0 2 1 4.190000E-02 2017 10 23 19 0 0 2 15 0 2 0 1.900000E-031.000000E-04 - 2017 10 23 19 30 0 2 15 0 6 1 0.00000 + 2017 10 23 19 30 0 2 15 0 6 1 0.00000 2017 10 23 21 0 0 2 15 0 17 0 4.300000E-024.260000E-02 4.180000E-024.090000E-024.050000E-023.980000E-023.950000E-023.940000E-02 3.880000E-023.860000E-023.810000E-023.750000E-023.700000E-023.680000E-02 3.670000E-021.400000E-031.000000E-04 - 2017 10 24 1 15 0 2 15 0 13 1 0.00000 + 2017 10 24 1 15 0 2 15 0 13 1 0.00000 2017 10 24 4 30 0 2 15 0 7 0 3.880000E-023.860000E-02 3.810000E-023.780000E-023.760000E-022.160000E-025.000000E-04 - 2017 10 24 6 15 0 2 15 0 49 1 0.00000 + 2017 10 24 6 15 0 2 15 0 49 1 0.00000 2017 10 24 18 30 0 2 15 0 27 0 4.450000E-024.440000E-02 1.700000E-033.990000E-024.440000E-026.600000E-034.430000E-024.390000E-02 4.320000E-024.290000E-024.210000E-024.120000E-024.040000E-023.990000E-02 @@ -1699,20 +1699,20 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 3.140000E-02 2017 10 25 1 15 0 2 15 0 2 1 3.110000E-02 2017 10 25 1 45 0 2 15 0 2 0 4.600000E-031.000000E-04 - 2017 10 25 2 15 0 2 15 0 9 1 0.00000 + 2017 10 25 2 15 0 2 15 0 9 1 0.00000 2017 10 25 4 30 0 2 15 0 1 0 3.240000E-02 2017 10 25 4 45 0 2 15 0 2 1 3.220000E-02 2017 10 25 5 15 0 2 15 0 2 0 1.400000E-031.000000E-04 2017 10 25 5 45 0 2 15 0 2 1 3.220000E-02 2017 10 25 6 15 0 2 15 0 2 1 3.200000E-02 2017 10 25 6 45 0 2 15 0 2 0 1.300000E-031.000000E-04 - 2017 10 25 7 15 0 2 15 0 12 1 0.00000 + 2017 10 25 7 15 0 2 15 0 12 1 0.00000 2017 10 25 10 15 0 2 15 0 4 0 3.380000E-023.370000E-02 1.920000E-024.000000E-04 - 2017 10 25 11 15 0 2 15 0 85 1 0.00000 + 2017 10 25 11 15 0 2 15 0 85 1 0.00000 2017 10 26 8 30 0 2 15 0 3 0 4.540000E-026.500000E-03 2.000000E-04 - 2017 10 26 9 15 0 2 15 0 125 1 0.00000 + 2017 10 26 9 15 0 2 15 0 125 1 0.00000 2017 10 27 16 30 0 2 15 0 38 0 6.090000E-026.080000E-02 6.050000E-025.990000E-025.920000E-025.800000E-025.660000E-025.550000E-02 5.400000E-025.210000E-024.980000E-024.790000E-024.560000E-024.360000E-02 @@ -1720,9 +1720,9 @@ DSN 772 TYPE TIME NDN 10 NUP 10 NSA 30 NSP 100 NDP 300 3.460000E-023.390000E-023.320000E-023.210000E-023.130000E-023.050000E-02 2.970000E-022.900000E-022.860000E-022.850000E-022.840000E-021.200000E-03 1.000000E-042.860000E-022.840000E-022.830000E-021.610000E-024.000000E-04 - 2017 10 28 2 0 0 2 15 0 255 1 0.00000 + 2017 10 28 2 0 0 2 15 0 255 1 0.00000 2017 10 30 17 45 0 2 15 0 3 0 6.180000E-023.520000E-02 7.000000E-04 - 2017 10 30 18 30 0 2 15 0 118 1 0.00000 + 2017 10 30 18 30 0 2 15 0 118 1 0.00000 END DATA -END DSN +END DSN diff --git a/tests/GRW_Plaster/HSPF.uci b/tests/GRW_Plaster/HSPF.uci index 609270b4..c68c9630 100644 --- a/tests/GRW_Plaster/HSPF.uci +++ b/tests/GRW_Plaster/HSPF.uci @@ -32,7 +32,7 @@ END FILES ******************************************************************** *** OPN SEQUENCE *** ******************************************************************** - + OPN SEQUENCE INGRP INDELT 01:00 @@ -91,7 +91,7 @@ OPN SEQUENCE RCHRES 73 RCHRES 72 RCHRES 71 - + END INGRP END OPN SEQUENCE @@ -105,61 +105,61 @@ PERLND x - x ATMP SNOW PWAT SED PST PWG PQAL MSTL PEST NITR PHOS TRAC *** 111 984 1 1 1 1 0 0 1 0 0 0 0 0 END ACTIVITY - + PRINT-INFO ********************* Print-flags ************************* PIVL PYR x - x ATMP SNOW PWAT SED PST PWG PQAL MSTL PEST NITR PHOS TRAC ********* 111 984 6 6 6 6 6 6 6 6 6 6 6 6 1 12 END PRINT-INFO - + BINARY-INFO ********************* Print-flags ************************* PIVL PYR x - x ATMP SNOW PWAT SED PST PWG PQAL MSTL PEST NITR PHOS TRAC ********* 111 984 6 6 6 6 6 6 6 6 6 6 6 6 1 12 END BINARY-INFO - + GEN-INFO *** Name Unit-systems Printer BinaryOut *** t-series Engl Metr Engl Metr *** x - x in out - 111 114WETLANDS-AB 1 1 1 0 92 - 121 124WETLANDS-CD 1 1 1 0 92 - 171 174WETLANDS-AB 1 1 1 0 92 - 181 184WETLANDS-CD 1 1 1 0 92 - 211 214FOREST-AB 1 1 1 0 92 - 221 224FOREST-CD 1 1 1 0 92 - 271 274FOREST-AB 1 1 1 0 92 - 281 284FOREST-CD 1 1 1 0 92 - 311 314GRASS-AB 1 1 1 0 92 - 321 324GRASS-CD 1 1 1 0 92 - 371 374GRASS-AB 1 1 1 0 92 - 381 384GRASS-CD 1 1 1 0 92 - 411 414PASTURE-AB 1 1 1 0 92 - 421 424PASTURE-CD 1 1 1 0 92 - 471 474PASTURE-AB 1 1 1 0 92 - 481 484PASTURE-CD 1 1 1 0 92 - 511 514CROP-AB 1 1 1 0 92 - 521 524CROP-CD 1 1 1 0 92 - 531 534CROP-TILE 1 1 1 0 92 - 571 574CROP-AB 1 1 1 0 92 - 581 584CROP-CD 1 1 1 0 92 - 591 594CROP-TILE 1 1 1 0 92 - 611 614DEV-OPEN-AB 1 1 1 0 92 - 621 624DEV-OPEN-CD 1 1 1 0 92 - 671 674DEV-OPEN-AB 1 1 1 0 92 - 681 684DEV-OPEN-CD 1 1 1 0 92 - 711 714DEV-LOW-AB 1 1 1 0 92 - 721 724DEV-LOW-CD 1 1 1 0 92 - 771 774DEV-LOW-AB 1 1 1 0 92 - 781 784DEV-LOW-CD 1 1 1 0 92 - 811 814DEV-MED-AB 1 1 1 0 92 - 821 824DEV-MED-CD 1 1 1 0 92 - 871 874DEV-MED-AB 1 1 1 0 92 - 881 884DEV-MED-CD 1 1 1 0 92 - 911 914DEV-HIGH-AB 1 1 1 0 92 - 921 924DEV-HIGH-CD 1 1 1 0 92 - 971 974DEV-HIGH-AB 1 1 1 0 92 - 981 984DEV-HIGH-CD 1 1 1 0 92 + 111 114WETLANDS-AB 1 1 1 0 92 + 121 124WETLANDS-CD 1 1 1 0 92 + 171 174WETLANDS-AB 1 1 1 0 92 + 181 184WETLANDS-CD 1 1 1 0 92 + 211 214FOREST-AB 1 1 1 0 92 + 221 224FOREST-CD 1 1 1 0 92 + 271 274FOREST-AB 1 1 1 0 92 + 281 284FOREST-CD 1 1 1 0 92 + 311 314GRASS-AB 1 1 1 0 92 + 321 324GRASS-CD 1 1 1 0 92 + 371 374GRASS-AB 1 1 1 0 92 + 381 384GRASS-CD 1 1 1 0 92 + 411 414PASTURE-AB 1 1 1 0 92 + 421 424PASTURE-CD 1 1 1 0 92 + 471 474PASTURE-AB 1 1 1 0 92 + 481 484PASTURE-CD 1 1 1 0 92 + 511 514CROP-AB 1 1 1 0 92 + 521 524CROP-CD 1 1 1 0 92 + 531 534CROP-TILE 1 1 1 0 92 + 571 574CROP-AB 1 1 1 0 92 + 581 584CROP-CD 1 1 1 0 92 + 591 594CROP-TILE 1 1 1 0 92 + 611 614DEV-OPEN-AB 1 1 1 0 92 + 621 624DEV-OPEN-CD 1 1 1 0 92 + 671 674DEV-OPEN-AB 1 1 1 0 92 + 681 684DEV-OPEN-CD 1 1 1 0 92 + 711 714DEV-LOW-AB 1 1 1 0 92 + 721 724DEV-LOW-CD 1 1 1 0 92 + 771 774DEV-LOW-AB 1 1 1 0 92 + 781 784DEV-LOW-CD 1 1 1 0 92 + 811 814DEV-MED-AB 1 1 1 0 92 + 821 824DEV-MED-CD 1 1 1 0 92 + 871 874DEV-MED-AB 1 1 1 0 92 + 881 884DEV-MED-CD 1 1 1 0 92 + 911 914DEV-HIGH-AB 1 1 1 0 92 + 921 924DEV-HIGH-CD 1 1 1 0 92 + 971 974DEV-HIGH-AB 1 1 1 0 92 + 981 984DEV-HIGH-CD 1 1 1 0 92 END GEN-INFO ******************************************************************** @@ -519,161 +519,161 @@ PERLND PWAT-PARM2 *** < PLS> FOREST LZSN INFILT LSUR SLSUR KVARY AGWRC *** x - x (in) (in/hr) (ft) (1/in) (1/day) - 111 0.00 10.0 0.08 500. 0.0339 1.0 0.999 - 112 0.00 10.0 0.08 500. 0.0204 1.0 0.999 - 113 0.00 10.0 0.08 500. 0.0200 1.0 0.999 - 111 0.00 10.0 0.08 500. 0.0339 1.0 0.999 - 112 0.00 10.0 0.08 500. 0.0204 1.0 0.999 - 113 0.00 10.0 0.08 500. 0.0200 1.0 0.999 - 114 0.00 10.0 0.08 500. 0.0188 1.0 0.999 - 121 0.00 10.0 0.08 500. 0.0223 1.0 0.999 - 122 0.00 10.0 0.08 500. 0.0161 1.0 0.999 - 123 0.00 10.0 0.08 500. 0.0182 1.0 0.999 - 124 0.00 10.0 0.08 500. 0.0164 1.0 0.999 - 171 0.00 10.0 0.08 500. 0.0339 1.0 0.999 - 172 0.00 10.0 0.08 500. 0.0204 1.0 0.999 - 173 0.00 10.0 0.08 500. 0.0200 1.0 0.999 - 174 0.00 10.0 0.08 500. 0.0188 1.0 0.999 - 181 0.00 10.0 0.08 500. 0.0223 1.0 0.999 - 182 0.00 10.0 0.08 500. 0.0161 1.0 0.999 - 183 0.00 10.0 0.08 500. 0.0182 1.0 0.999 - 184 0.00 10.0 0.08 500. 0.0164 1.0 0.999 - 211 0.09 10.0 0.24 350. 0.0708 1.0 0.999 - 212 0.18 10.0 0.24 350. 0.0163 1.0 0.999 - 213 0.24 10.0 0.24 350. 0.0208 1.0 0.999 - 214 0.11 10.0 0.24 350. 0.0335 1.0 0.999 - 221 0.04 10.0 0.19 350. 0.0651 1.0 0.999 - 222 0.07 10.0 0.19 350. 0.0375 1.0 0.999 - 223 0.18 10.0 0.19 350. 0.0243 1.0 0.999 - 224 0.05 10.0 0.19 350. 0.0364 1.0 0.999 - 271 0.09 10.0 0.24 350. 0.0708 1.0 0.999 - 272 0.18 10.0 0.24 350. 0.0163 1.0 0.999 - 273 0.24 10.0 0.24 350. 0.0208 1.0 0.999 - 274 0.11 10.0 0.24 350. 0.0335 1.0 0.999 - 281 0.04 10.0 0.19 350. 0.0651 1.0 0.999 - 282 0.07 10.0 0.19 350. 0.0375 1.0 0.999 - 283 0.18 10.0 0.19 350. 0.0243 1.0 0.999 - 284 0.05 10.0 0.19 350. 0.0364 1.0 0.999 - 311 0.00 8.0 0.22 350. 0.0572 1.0 0.998 - 312 0.00 8.0 0.22 350. 0.0111 1.0 0.998 - 313 0.00 8.0 0.22 350. 0.0320 1.0 0.998 - 314 0.00 8.0 0.22 350. 0.0320 1.0 0.998 - 321 0.00 8.0 0.18 350. 0.0342 1.0 0.998 - 322 0.00 8.0 0.18 350. 0.0179 1.0 0.998 - 323 0.00 8.0 0.18 350. 0.0292 1.0 0.998 - 324 0.00 8.0 0.18 350. 0.0278 1.0 0.998 - 371 0.00 8.0 0.22 350. 0.0572 1.0 0.998 - 372 0.00 8.0 0.22 350. 0.0111 1.0 0.998 - 373 0.00 8.0 0.22 350. 0.0320 1.0 0.998 - 374 0.00 8.0 0.22 350. 0.0320 1.0 0.998 - 381 0.00 8.0 0.18 350. 0.0342 1.0 0.998 - 382 0.00 8.0 0.18 350. 0.0179 1.0 0.998 - 383 0.00 8.0 0.18 350. 0.0292 1.0 0.998 - 384 0.00 8.0 0.18 350. 0.0278 1.0 0.998 - 411 0.00 8.0 0.22 300. 0.0381 1.0 0.998 - 412 0.00 8.0 0.22 300. 0.0120 1.0 0.998 - 413 0.00 8.0 0.22 300. 0.0129 1.0 0.998 - 414 0.00 8.0 0.22 300. 0.0319 1.0 0.998 - 421 0.00 8.0 0.18 300. 0.0331 1.0 0.998 - 422 0.00 8.0 0.18 300. 0.0220 1.0 0.998 - 423 0.00 8.0 0.18 300. 0.0178 1.0 0.998 - 424 0.00 8.0 0.18 300. 0.0296 1.0 0.998 - 471 0.00 8.0 0.22 300. 0.0381 1.0 0.998 - 472 0.00 8.0 0.22 300. 0.0120 1.0 0.998 - 473 0.00 8.0 0.22 300. 0.0129 1.0 0.998 - 474 0.00 8.0 0.22 300. 0.0319 1.0 0.998 - 481 0.00 8.0 0.18 300. 0.0331 1.0 0.998 - 482 0.00 8.0 0.18 300. 0.0220 1.0 0.998 - 483 0.00 8.0 0.18 300. 0.0178 1.0 0.998 - 484 0.00 8.0 0.18 300. 0.0296 1.0 0.998 - 511 0.00 7.0 0.19 300. 0.0314 1.0 0.997 - 512 0.00 7.0 0.19 300. 0.0096 1.0 0.997 - 513 0.00 7.0 0.19 300. 0.0104 1.0 0.997 - 514 0.00 7.0 0.19 300. 0.0276 1.0 0.997 - 521 0.00 7.0 0.14 300. 0.0346 1.0 0.997 - 522 0.00 7.0 0.14 300. 0.0120 1.0 0.997 - 523 0.00 7.0 0.14 300. 0.0159 1.0 0.997 - 524 0.00 7.0 0.14 300. 0.0272 1.0 0.997 - 531 0.00 6.0 0.22 300. 0.0220 1.0 0.999 - 532 0.00 6.0 0.22 300. 0.0161 1.0 0.999 - 533 0.00 6.0 0.22 300. 0.0147 1.0 0.999 - 534 0.00 6.0 0.22 300. 0.0186 1.0 0.999 - 571 0.00 7.0 0.19 300. 0.0314 1.0 0.997 - 572 0.00 7.0 0.19 300. 0.0096 1.0 0.997 - 573 0.00 7.0 0.19 300. 0.0104 1.0 0.997 - 574 0.00 7.0 0.19 300. 0.0276 1.0 0.997 - 581 0.00 7.0 0.14 300. 0.0346 1.0 0.997 - 582 0.00 7.0 0.14 300. 0.0120 1.0 0.997 - 583 0.00 7.0 0.14 300. 0.0159 1.0 0.997 - 584 0.00 7.0 0.14 300. 0.0272 1.0 0.997 - 591 0.00 6.0 0.22 300. 0.0220 1.0 0.999 - 592 0.00 6.0 0.22 300. 0.0161 1.0 0.999 - 593 0.00 6.0 0.22 300. 0.0147 1.0 0.999 - 594 0.00 6.0 0.22 300. 0.0186 1.0 0.999 - 611 0.00 8.0 0.20 250. 0.0450 1.0 0.980 - 612 0.00 8.0 0.20 250. 0.0161 1.0 0.980 - 613 0.00 8.0 0.20 250. 0.0211 1.0 0.980 - 614 0.00 8.0 0.20 250. 0.0316 1.0 0.980 - 621 0.00 8.0 0.14 250. 0.0397 1.0 0.980 - 622 0.00 8.0 0.14 250. 0.0295 1.0 0.980 - 623 0.00 8.0 0.14 250. 0.0200 1.0 0.980 - 624 0.00 8.0 0.14 250. 0.0282 1.0 0.980 - 671 0.00 8.0 0.20 250. 0.0450 1.0 0.980 - 672 0.00 8.0 0.20 250. 0.0161 1.0 0.980 - 673 0.00 8.0 0.20 250. 0.0211 1.0 0.980 - 674 0.00 8.0 0.20 250. 0.0316 1.0 0.980 - 681 0.00 8.0 0.14 250. 0.0397 1.0 0.980 - 682 0.00 8.0 0.14 250. 0.0295 1.0 0.980 - 683 0.00 8.0 0.14 250. 0.0200 1.0 0.980 - 684 0.00 8.0 0.14 250. 0.0282 1.0 0.980 - 711 0.00 7.0 0.18 200. 0.0370 1.0 0.970 - 712 0.00 7.0 0.18 200. 0.0123 1.0 0.970 - 713 0.00 7.0 0.18 200. 0.0180 1.0 0.970 - 714 0.00 7.0 0.18 200. 0.0266 1.0 0.970 - 721 0.00 7.0 0.14 200. 0.0312 1.0 0.970 - 722 0.00 7.0 0.14 200. 0.0197 1.0 0.970 - 723 0.00 7.0 0.14 200. 0.0174 1.0 0.970 - 724 0.00 7.0 0.14 200. 0.0256 1.0 0.970 - 771 0.00 7.0 0.18 200. 0.0370 1.0 0.970 - 772 0.00 7.0 0.18 200. 0.0123 1.0 0.970 - 773 0.00 7.0 0.18 200. 0.0180 1.0 0.970 - 774 0.00 7.0 0.18 200. 0.0266 1.0 0.970 - 781 0.00 7.0 0.14 200. 0.0312 1.0 0.970 - 782 0.00 7.0 0.14 200. 0.0197 1.0 0.970 - 783 0.00 7.0 0.14 200. 0.0174 1.0 0.970 - 784 0.00 7.0 0.14 200. 0.0256 1.0 0.970 - 811 0.00 6.0 0.16 200. 0.0325 1.0 0.960 - 812 0.00 6.0 0.16 200. 0.0140 1.0 0.960 - 813 0.00 6.0 0.16 200. 0.0166 1.0 0.960 - 814 0.00 6.0 0.16 200. 0.0205 1.0 0.960 - 821 0.00 6.0 0.12 200. 0.0277 1.0 0.960 - 822 0.00 6.0 0.12 200. 0.0213 1.0 0.960 - 823 0.00 6.0 0.12 200. 0.0232 1.0 0.960 - 824 0.00 6.0 0.12 200. 0.0158 1.0 0.960 - 871 0.00 6.0 0.16 200. 0.0325 1.0 0.960 - 872 0.00 6.0 0.16 200. 0.0140 1.0 0.960 - 873 0.00 6.0 0.16 200. 0.0166 1.0 0.960 - 874 0.00 6.0 0.16 200. 0.0205 1.0 0.960 - 881 0.00 6.0 0.12 200. 0.0277 1.0 0.960 - 882 0.00 6.0 0.12 200. 0.0213 1.0 0.960 - 883 0.00 6.0 0.12 200. 0.0232 1.0 0.960 - 884 0.00 6.0 0.12 200. 0.0158 1.0 0.960 - 911 0.00 5.0 0.10 150. 0.0271 1.0 0.950 - 912 0.00 5.0 0.10 150. 0.0093 1.0 0.950 - 913 0.00 5.0 0.10 150. 0.0120 1.0 0.950 - 914 0.00 5.0 0.10 150. 0.0292 1.0 0.950 - 921 0.00 5.0 0.06 150. 0.0233 1.0 0.950 - 922 0.00 5.0 0.06 150. 0.0198 1.0 0.950 - 923 0.00 5.0 0.06 150. 0.0177 1.0 0.950 - 924 0.00 5.0 0.06 150. 0.0168 1.0 0.950 - 971 0.00 5.0 0.10 150. 0.0271 1.0 0.950 - 972 0.00 5.0 0.10 150. 0.0093 1.0 0.950 - 973 0.00 5.0 0.10 150. 0.0120 1.0 0.950 - 974 0.00 5.0 0.10 150. 0.0292 1.0 0.950 - 981 0.00 5.0 0.06 150. 0.0233 1.0 0.950 - 982 0.00 5.0 0.06 150. 0.0198 1.0 0.950 - 983 0.00 5.0 0.06 150. 0.0177 1.0 0.950 - 984 0.00 5.0 0.06 150. 0.0168 1.0 0.950 + 111 0.00 10.0 0.08 500. 0.0339 1.0 0.999 + 112 0.00 10.0 0.08 500. 0.0204 1.0 0.999 + 113 0.00 10.0 0.08 500. 0.0200 1.0 0.999 + 111 0.00 10.0 0.08 500. 0.0339 1.0 0.999 + 112 0.00 10.0 0.08 500. 0.0204 1.0 0.999 + 113 0.00 10.0 0.08 500. 0.0200 1.0 0.999 + 114 0.00 10.0 0.08 500. 0.0188 1.0 0.999 + 121 0.00 10.0 0.08 500. 0.0223 1.0 0.999 + 122 0.00 10.0 0.08 500. 0.0161 1.0 0.999 + 123 0.00 10.0 0.08 500. 0.0182 1.0 0.999 + 124 0.00 10.0 0.08 500. 0.0164 1.0 0.999 + 171 0.00 10.0 0.08 500. 0.0339 1.0 0.999 + 172 0.00 10.0 0.08 500. 0.0204 1.0 0.999 + 173 0.00 10.0 0.08 500. 0.0200 1.0 0.999 + 174 0.00 10.0 0.08 500. 0.0188 1.0 0.999 + 181 0.00 10.0 0.08 500. 0.0223 1.0 0.999 + 182 0.00 10.0 0.08 500. 0.0161 1.0 0.999 + 183 0.00 10.0 0.08 500. 0.0182 1.0 0.999 + 184 0.00 10.0 0.08 500. 0.0164 1.0 0.999 + 211 0.09 10.0 0.24 350. 0.0708 1.0 0.999 + 212 0.18 10.0 0.24 350. 0.0163 1.0 0.999 + 213 0.24 10.0 0.24 350. 0.0208 1.0 0.999 + 214 0.11 10.0 0.24 350. 0.0335 1.0 0.999 + 221 0.04 10.0 0.19 350. 0.0651 1.0 0.999 + 222 0.07 10.0 0.19 350. 0.0375 1.0 0.999 + 223 0.18 10.0 0.19 350. 0.0243 1.0 0.999 + 224 0.05 10.0 0.19 350. 0.0364 1.0 0.999 + 271 0.09 10.0 0.24 350. 0.0708 1.0 0.999 + 272 0.18 10.0 0.24 350. 0.0163 1.0 0.999 + 273 0.24 10.0 0.24 350. 0.0208 1.0 0.999 + 274 0.11 10.0 0.24 350. 0.0335 1.0 0.999 + 281 0.04 10.0 0.19 350. 0.0651 1.0 0.999 + 282 0.07 10.0 0.19 350. 0.0375 1.0 0.999 + 283 0.18 10.0 0.19 350. 0.0243 1.0 0.999 + 284 0.05 10.0 0.19 350. 0.0364 1.0 0.999 + 311 0.00 8.0 0.22 350. 0.0572 1.0 0.998 + 312 0.00 8.0 0.22 350. 0.0111 1.0 0.998 + 313 0.00 8.0 0.22 350. 0.0320 1.0 0.998 + 314 0.00 8.0 0.22 350. 0.0320 1.0 0.998 + 321 0.00 8.0 0.18 350. 0.0342 1.0 0.998 + 322 0.00 8.0 0.18 350. 0.0179 1.0 0.998 + 323 0.00 8.0 0.18 350. 0.0292 1.0 0.998 + 324 0.00 8.0 0.18 350. 0.0278 1.0 0.998 + 371 0.00 8.0 0.22 350. 0.0572 1.0 0.998 + 372 0.00 8.0 0.22 350. 0.0111 1.0 0.998 + 373 0.00 8.0 0.22 350. 0.0320 1.0 0.998 + 374 0.00 8.0 0.22 350. 0.0320 1.0 0.998 + 381 0.00 8.0 0.18 350. 0.0342 1.0 0.998 + 382 0.00 8.0 0.18 350. 0.0179 1.0 0.998 + 383 0.00 8.0 0.18 350. 0.0292 1.0 0.998 + 384 0.00 8.0 0.18 350. 0.0278 1.0 0.998 + 411 0.00 8.0 0.22 300. 0.0381 1.0 0.998 + 412 0.00 8.0 0.22 300. 0.0120 1.0 0.998 + 413 0.00 8.0 0.22 300. 0.0129 1.0 0.998 + 414 0.00 8.0 0.22 300. 0.0319 1.0 0.998 + 421 0.00 8.0 0.18 300. 0.0331 1.0 0.998 + 422 0.00 8.0 0.18 300. 0.0220 1.0 0.998 + 423 0.00 8.0 0.18 300. 0.0178 1.0 0.998 + 424 0.00 8.0 0.18 300. 0.0296 1.0 0.998 + 471 0.00 8.0 0.22 300. 0.0381 1.0 0.998 + 472 0.00 8.0 0.22 300. 0.0120 1.0 0.998 + 473 0.00 8.0 0.22 300. 0.0129 1.0 0.998 + 474 0.00 8.0 0.22 300. 0.0319 1.0 0.998 + 481 0.00 8.0 0.18 300. 0.0331 1.0 0.998 + 482 0.00 8.0 0.18 300. 0.0220 1.0 0.998 + 483 0.00 8.0 0.18 300. 0.0178 1.0 0.998 + 484 0.00 8.0 0.18 300. 0.0296 1.0 0.998 + 511 0.00 7.0 0.19 300. 0.0314 1.0 0.997 + 512 0.00 7.0 0.19 300. 0.0096 1.0 0.997 + 513 0.00 7.0 0.19 300. 0.0104 1.0 0.997 + 514 0.00 7.0 0.19 300. 0.0276 1.0 0.997 + 521 0.00 7.0 0.14 300. 0.0346 1.0 0.997 + 522 0.00 7.0 0.14 300. 0.0120 1.0 0.997 + 523 0.00 7.0 0.14 300. 0.0159 1.0 0.997 + 524 0.00 7.0 0.14 300. 0.0272 1.0 0.997 + 531 0.00 6.0 0.22 300. 0.0220 1.0 0.999 + 532 0.00 6.0 0.22 300. 0.0161 1.0 0.999 + 533 0.00 6.0 0.22 300. 0.0147 1.0 0.999 + 534 0.00 6.0 0.22 300. 0.0186 1.0 0.999 + 571 0.00 7.0 0.19 300. 0.0314 1.0 0.997 + 572 0.00 7.0 0.19 300. 0.0096 1.0 0.997 + 573 0.00 7.0 0.19 300. 0.0104 1.0 0.997 + 574 0.00 7.0 0.19 300. 0.0276 1.0 0.997 + 581 0.00 7.0 0.14 300. 0.0346 1.0 0.997 + 582 0.00 7.0 0.14 300. 0.0120 1.0 0.997 + 583 0.00 7.0 0.14 300. 0.0159 1.0 0.997 + 584 0.00 7.0 0.14 300. 0.0272 1.0 0.997 + 591 0.00 6.0 0.22 300. 0.0220 1.0 0.999 + 592 0.00 6.0 0.22 300. 0.0161 1.0 0.999 + 593 0.00 6.0 0.22 300. 0.0147 1.0 0.999 + 594 0.00 6.0 0.22 300. 0.0186 1.0 0.999 + 611 0.00 8.0 0.20 250. 0.0450 1.0 0.980 + 612 0.00 8.0 0.20 250. 0.0161 1.0 0.980 + 613 0.00 8.0 0.20 250. 0.0211 1.0 0.980 + 614 0.00 8.0 0.20 250. 0.0316 1.0 0.980 + 621 0.00 8.0 0.14 250. 0.0397 1.0 0.980 + 622 0.00 8.0 0.14 250. 0.0295 1.0 0.980 + 623 0.00 8.0 0.14 250. 0.0200 1.0 0.980 + 624 0.00 8.0 0.14 250. 0.0282 1.0 0.980 + 671 0.00 8.0 0.20 250. 0.0450 1.0 0.980 + 672 0.00 8.0 0.20 250. 0.0161 1.0 0.980 + 673 0.00 8.0 0.20 250. 0.0211 1.0 0.980 + 674 0.00 8.0 0.20 250. 0.0316 1.0 0.980 + 681 0.00 8.0 0.14 250. 0.0397 1.0 0.980 + 682 0.00 8.0 0.14 250. 0.0295 1.0 0.980 + 683 0.00 8.0 0.14 250. 0.0200 1.0 0.980 + 684 0.00 8.0 0.14 250. 0.0282 1.0 0.980 + 711 0.00 7.0 0.18 200. 0.0370 1.0 0.970 + 712 0.00 7.0 0.18 200. 0.0123 1.0 0.970 + 713 0.00 7.0 0.18 200. 0.0180 1.0 0.970 + 714 0.00 7.0 0.18 200. 0.0266 1.0 0.970 + 721 0.00 7.0 0.14 200. 0.0312 1.0 0.970 + 722 0.00 7.0 0.14 200. 0.0197 1.0 0.970 + 723 0.00 7.0 0.14 200. 0.0174 1.0 0.970 + 724 0.00 7.0 0.14 200. 0.0256 1.0 0.970 + 771 0.00 7.0 0.18 200. 0.0370 1.0 0.970 + 772 0.00 7.0 0.18 200. 0.0123 1.0 0.970 + 773 0.00 7.0 0.18 200. 0.0180 1.0 0.970 + 774 0.00 7.0 0.18 200. 0.0266 1.0 0.970 + 781 0.00 7.0 0.14 200. 0.0312 1.0 0.970 + 782 0.00 7.0 0.14 200. 0.0197 1.0 0.970 + 783 0.00 7.0 0.14 200. 0.0174 1.0 0.970 + 784 0.00 7.0 0.14 200. 0.0256 1.0 0.970 + 811 0.00 6.0 0.16 200. 0.0325 1.0 0.960 + 812 0.00 6.0 0.16 200. 0.0140 1.0 0.960 + 813 0.00 6.0 0.16 200. 0.0166 1.0 0.960 + 814 0.00 6.0 0.16 200. 0.0205 1.0 0.960 + 821 0.00 6.0 0.12 200. 0.0277 1.0 0.960 + 822 0.00 6.0 0.12 200. 0.0213 1.0 0.960 + 823 0.00 6.0 0.12 200. 0.0232 1.0 0.960 + 824 0.00 6.0 0.12 200. 0.0158 1.0 0.960 + 871 0.00 6.0 0.16 200. 0.0325 1.0 0.960 + 872 0.00 6.0 0.16 200. 0.0140 1.0 0.960 + 873 0.00 6.0 0.16 200. 0.0166 1.0 0.960 + 874 0.00 6.0 0.16 200. 0.0205 1.0 0.960 + 881 0.00 6.0 0.12 200. 0.0277 1.0 0.960 + 882 0.00 6.0 0.12 200. 0.0213 1.0 0.960 + 883 0.00 6.0 0.12 200. 0.0232 1.0 0.960 + 884 0.00 6.0 0.12 200. 0.0158 1.0 0.960 + 911 0.00 5.0 0.10 150. 0.0271 1.0 0.950 + 912 0.00 5.0 0.10 150. 0.0093 1.0 0.950 + 913 0.00 5.0 0.10 150. 0.0120 1.0 0.950 + 914 0.00 5.0 0.10 150. 0.0292 1.0 0.950 + 921 0.00 5.0 0.06 150. 0.0233 1.0 0.950 + 922 0.00 5.0 0.06 150. 0.0198 1.0 0.950 + 923 0.00 5.0 0.06 150. 0.0177 1.0 0.950 + 924 0.00 5.0 0.06 150. 0.0168 1.0 0.950 + 971 0.00 5.0 0.10 150. 0.0271 1.0 0.950 + 972 0.00 5.0 0.10 150. 0.0093 1.0 0.950 + 973 0.00 5.0 0.10 150. 0.0120 1.0 0.950 + 974 0.00 5.0 0.10 150. 0.0292 1.0 0.950 + 981 0.00 5.0 0.06 150. 0.0233 1.0 0.950 + 982 0.00 5.0 0.06 150. 0.0198 1.0 0.950 + 983 0.00 5.0 0.06 150. 0.0177 1.0 0.950 + 984 0.00 5.0 0.06 150. 0.0168 1.0 0.950 END PWAT-PARM2 PWAT-PARM3 @@ -684,8 +684,8 @@ PERLND PWAT-PARM4 *** See monthly variable tables for certain monthly variable parameters *** -*** CEPSC UZSN NSUR INTFW IRC LZETP -*** x - x (in) (in) (1/day) +*** CEPSC UZSN NSUR INTFW IRC LZETP +*** x - x (in) (in) (1/day) 111 114 0.10 0.50 0.25 3.0 0.80 0.5 121 124 0.10 0.50 0.25 3.0 0.80 0.5 171 174 0.10 0.50 0.25 3.0 0.80 0.5 @@ -724,52 +724,52 @@ PERLND 921 924 0.10 0.50 0.25 1.0 0.30 0.5 971 974 0.10 0.50 0.25 1.0 0.30 0.5 981 984 0.10 0.50 0.25 1.0 0.30 0.5 - END PWAT-PARM4 + END PWAT-PARM4 PWAT-STATE1 *** < PLS> PWATER state variables (in) *** x - x CEPS SURS UZS IFWS LZS AGWS GWVS - 111 114 0.0 0.0 0.8 3. 10. 12. 0.60 - 121 124 0.0 0.0 0.8 3. 10. 12. 0.60 - 171 174 0.0 0.0 0.8 3. 10. 12. 0.60 - 181 184 0.0 0.0 0.8 3. 10. 12. 0.60 - 211 214 0.0 0.0 0.7 2. 10. 14. 0.80 - 221 224 0.0 0.0 0.7 2. 10. 13. 0.80 - 271 274 0.0 0.0 0.7 2. 10. 14. 0.80 - 281 284 0.0 0.0 0.7 2. 10. 13. 0.80 - 311 314 0.0 0.0 0.6 2. 8. 7. 0.90 - 321 324 0.0 0.0 0.6 2. 8. 7. 0.90 - 371 374 0.0 0.0 0.6 2. 8. 7. 0.90 - 381 384 0.0 0.0 0.6 2. 8. 7. 0.90 - 411 414 0.0 0.0 0.6 2. 8. 7. 0.90 - 421 424 0.0 0.0 0.6 2. 8. 7. 0.90 - 471 474 0.0 0.0 0.6 2. 8. 7. 0.90 - 481 484 0.0 0.0 0.6 2. 8. 7. 0.90 - 511 514 0.0 0.0 0.4 2. 6. 5. 0.90 - 521 524 0.0 0.0 0.4 2. 6. 4. 0.80 - 531 534 0.0 0.0 0.2 4. 5. 14. 0.90 - 571 574 0.0 0.0 0.4 2. 6. 5. 0.90 - 581 584 0.0 0.0 0.4 2. 6. 4. 0.80 - 591 594 0.0 0.0 0.2 4. 5. 14. 0.90 - 611 614 0.0 0.0 0.3 2. 4. 2. 0.70 - 621 624 0.0 0.0 0.3 2. 4. 2. 0.70 - 671 674 0.0 0.0 0.3 2. 4. 2. 0.70 - 681 684 0.0 0.0 0.3 2. 4. 2. 0.70 - 711 714 0.0 0.0 0.3 1. 3. 2. 0.70 - 721 724 0.0 0.0 0.3 1. 3. 1. 0.60 - 771 774 0.0 0.0 0.3 1. 3. 2. 0.70 - 781 784 0.0 0.0 0.3 1. 3. 1. 0.60 - 811 814 0.0 0.0 0.2 1. 2. 1. 0.60 - 821 824 0.0 0.0 0.2 1. 2. 1. 0.40 - 871 874 0.0 0.0 0.2 1. 2. 1. 0.60 - 881 884 0.0 0.0 0.2 1. 2. 1. 0.40 - 911 914 0.0 0.0 0.2 1. 2. 1. 0.60 - 921 924 0.0 0.0 0.2 1. 2. 1. 0.40 - 971 974 0.0 0.0 0.2 1. 2. 1. 0.60 - 981 984 0.0 0.0 0.2 1. 2. 1. 0.40 + 111 114 0.0 0.0 0.8 3. 10. 12. 0.60 + 121 124 0.0 0.0 0.8 3. 10. 12. 0.60 + 171 174 0.0 0.0 0.8 3. 10. 12. 0.60 + 181 184 0.0 0.0 0.8 3. 10. 12. 0.60 + 211 214 0.0 0.0 0.7 2. 10. 14. 0.80 + 221 224 0.0 0.0 0.7 2. 10. 13. 0.80 + 271 274 0.0 0.0 0.7 2. 10. 14. 0.80 + 281 284 0.0 0.0 0.7 2. 10. 13. 0.80 + 311 314 0.0 0.0 0.6 2. 8. 7. 0.90 + 321 324 0.0 0.0 0.6 2. 8. 7. 0.90 + 371 374 0.0 0.0 0.6 2. 8. 7. 0.90 + 381 384 0.0 0.0 0.6 2. 8. 7. 0.90 + 411 414 0.0 0.0 0.6 2. 8. 7. 0.90 + 421 424 0.0 0.0 0.6 2. 8. 7. 0.90 + 471 474 0.0 0.0 0.6 2. 8. 7. 0.90 + 481 484 0.0 0.0 0.6 2. 8. 7. 0.90 + 511 514 0.0 0.0 0.4 2. 6. 5. 0.90 + 521 524 0.0 0.0 0.4 2. 6. 4. 0.80 + 531 534 0.0 0.0 0.2 4. 5. 14. 0.90 + 571 574 0.0 0.0 0.4 2. 6. 5. 0.90 + 581 584 0.0 0.0 0.4 2. 6. 4. 0.80 + 591 594 0.0 0.0 0.2 4. 5. 14. 0.90 + 611 614 0.0 0.0 0.3 2. 4. 2. 0.70 + 621 624 0.0 0.0 0.3 2. 4. 2. 0.70 + 671 674 0.0 0.0 0.3 2. 4. 2. 0.70 + 681 684 0.0 0.0 0.3 2. 4. 2. 0.70 + 711 714 0.0 0.0 0.3 1. 3. 2. 0.70 + 721 724 0.0 0.0 0.3 1. 3. 1. 0.60 + 771 774 0.0 0.0 0.3 1. 3. 2. 0.70 + 781 784 0.0 0.0 0.3 1. 3. 1. 0.60 + 811 814 0.0 0.0 0.2 1. 2. 1. 0.60 + 821 824 0.0 0.0 0.2 1. 2. 1. 0.40 + 871 874 0.0 0.0 0.2 1. 2. 1. 0.60 + 881 884 0.0 0.0 0.2 1. 2. 1. 0.40 + 911 914 0.0 0.0 0.2 1. 2. 1. 0.60 + 921 924 0.0 0.0 0.2 1. 2. 1. 0.40 + 971 974 0.0 0.0 0.2 1. 2. 1. 0.60 + 981 984 0.0 0.0 0.2 1. 2. 1. 0.40 END PWAT-STATE1 - MON-INTERCEP + MON-INTERCEP *** Interception storage capacity at start of each month (in) *** x - x JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 111 114 0.06 0.06 0.06 0.07 0.08 0.08 0.10 0.10 0.08 0.07 0.06 0.06 @@ -810,10 +810,10 @@ PERLND 921 924 0.03 0.03 0.03 0.03 0.03 0.04 0.04 0.04 0.04 0.03 0.03 0.03 971 974 0.03 0.03 0.03 0.03 0.03 0.04 0.04 0.04 0.04 0.03 0.03 0.03 981 984 0.03 0.03 0.03 0.03 0.03 0.04 0.04 0.04 0.04 0.03 0.03 0.03 - END MON-INTERCEP + END MON-INTERCEP - MON-UZSN -*** Upper zone storage at start of each month (inches) + MON-UZSN +*** Upper zone storage at start of each month (inches) *** x - x JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 111 114 0.60 0.60 0.60 0.60 0.80 0.80 0.80 0.80 0.80 0.80 0.80 0.60 121 124 0.60 0.60 0.60 0.60 0.80 0.80 0.80 0.80 0.80 0.80 0.80 0.60 @@ -853,11 +853,11 @@ PERLND 921 924 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 971 974 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 981 984 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 - END MON-UZSN + END MON-UZSN - MON-MANNING -*** Manning's n at start of each month -*** x - x JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC + MON-MANNING +*** Manning's n at start of each month +*** x - x JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 111 114 0.30 0.30 0.30 0.32 0.32 0.34 0.35 0.35 0.35 0.34 0.32 0.32 121 124 0.30 0.30 0.30 0.32 0.32 0.34 0.35 0.35 0.35 0.34 0.32 0.32 171 174 0.30 0.30 0.30 0.32 0.32 0.34 0.35 0.35 0.35 0.34 0.32 0.32 @@ -896,11 +896,11 @@ PERLND 921 924 0.16 0.16 0.16 0.18 0.18 0.20 0.21 0.21 0.21 0.20 0.18 0.18 971 974 0.16 0.16 0.16 0.18 0.18 0.20 0.21 0.21 0.21 0.20 0.18 0.18 981 984 0.16 0.16 0.16 0.18 0.18 0.20 0.21 0.21 0.21 0.20 0.18 0.18 - END MON-MANNING + END MON-MANNING - MON-LZETPARM -*** Lower zone evapotranspiration parm at start of each month -*** x - x JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC + MON-LZETPARM +*** Lower zone evapotranspiration parm at start of each month +*** x - x JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 111 114 0.70 0.70 0.75 0.80 0.85 0.90 0.90 0.90 0.85 0.80 0.75 0.70 121 124 0.70 0.70 0.75 0.80 0.85 0.90 0.90 0.90 0.85 0.80 0.75 0.70 171 174 0.70 0.70 0.75 0.80 0.85 0.90 0.90 0.90 0.85 0.80 0.75 0.70 @@ -1109,7 +1109,7 @@ PERLND END SED-PARM2 SED-PARM3 -*** +*** *** x - x KSER JSER KGER JGER 111 0.55 2.0 0.00 2.5 112 0.53 2.0 0.00 2.5 @@ -1386,11 +1386,11 @@ PERLND *** *** x - x NQUAL *** 111 984 2 - END NQUALS + END NQUALS - PQL-AD-FLAGS + PQL-AD-FLAGS Atmospheric Deposition Flags *** -*** Dry (F) and wet (C) nitrogen & dry phosphorus deposition represented by time series(-1) *** +*** Dry (F) and wet (C) nitrogen & dry phosphorus deposition represented by time series(-1) *** *** QUAL1 QUAL2 QUAL3 QUAL4 QUAL5 QUAL6 QUAL7 QUAL8 QUAL9 QUAL10 *** *** x - x F C F C F C F C F C F C F C F C F C F C *** 111 984 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 @@ -1450,7 +1450,7 @@ PERLND 981 984 2.8E+10 0.0E+00 0.0E+00 6.0E+09 5.6E+10 7.0E-01 3.40E+4 1.70E+4 END QUAL-INPUT - MON-IFLW-CONC + MON-IFLW-CONC Interflow Concentration of Bacteria (#cfu/ft3) *** # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** 111 114 3E+3 3E+3 3E+3 3E+3 3E+3 3E+3 3E+3 3E+3 3E+3 3E+3 3E+3 3E+3 @@ -1781,7 +1781,7 @@ IMPLND END SNOW-FLAGS SNOW-PARM1 -*** < ILS> LAT MELEV SHADE SNOWCF COVIND +*** < ILS> LAT MELEV SHADE SNOWCF COVIND *** x - x degrees (ft) (in) 611 43.0 739 0.15 1.30 3 612 42.9 653 0.15 1.30 3 @@ -1827,7 +1827,7 @@ IMPLND IWAT-PARM2 *** LSUR SLSUR NSUR RETSC -*** x - x (ft) (ft) +*** x - x (ft) (ft) 611 150. 0.0421 0.05 0.120 612 150. 0.0232 0.05 0.120 613 150. 0.0208 0.05 0.120 @@ -1845,7 +1845,7 @@ IMPLND 913 150. 0.0132 0.05 0.120 914 150. 0.0187 0.05 0.120 END IWAT-PARM2 - + IWAT-PARM3 *** PETMAX PETMIN *** x - x (deg F) (deg F) @@ -1928,31 +1928,31 @@ IMPLND ******************************************************************** *** Impervious Land Segments -- Quality Constituents *** ******************************************************************** - + ***NQUAL 1 = Escherichia coli NQUALS *** *** x - x NQUAL ** 611 914 1 - END NQUALS - + END NQUALS + IQL-AD-FLAGS *** Atmospheric Deposition Flags *** *** QUAL1 QUAL2 QUAL3 QUAL4 QUAL5 QUAL6 QUAL7 QUAL8 QUAL9 QUAL10 *** *** x - x F C F C F C F C F C F C F C F C F C F C *** 611 914 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 END IQL-AD-FLAGS - + ******************************************************************** *** NQUAL 1 = Escherichia coli *** ******************************************************************** - + QUAL-PROPS # #<--QUALID--> QTID QSD VPFW QSO VQO *** 611 914 E.COLI CFU 0 0 1 0 END QUAL-PROPS - + QUAL-INPUT # # SQO POTFW ACQOP SQOLIM WSQOP *** 611 1.5E+09 0.0E+00 3.0E+08 3.0E+09 5.00E-1 @@ -2077,7 +2077,7 @@ RCHRES *** x - x FG FG FG FG possible exit *** possible exit possible exit 11 331 0 1 1 1 4 0 0 0 0 0 0 0 0 0 1 0 0 0 0 END HYDR-PARM1 - + HYDR-PARM2 *** RCHRES FTBW FTBU LEN DELTH STCOR KS DB50 *** x - x (miles) (ft) (ft) (in) @@ -2148,7 +2148,7 @@ RCHRES 321 0. 321 8.412 175.6 0.0 0.5 0.01 331 0. 331 16.847 139.94 0.0 0.5 0.01 END HYDR-PARM2 - + HYDR-INIT *** Initial conditions for HYDR section *** RCHRES VOL CAT Initial value of COLIND initial value of OUTDGT @@ -2393,13 +2393,13 @@ RCHRES SAND-PM *** RCHRES D W RHO KSAND EXPSND -*** x - x (in) (in/sec) (gm/cm3) +*** x - x (in) (in/sec) (gm/cm3) 11 0.010 2.00 2.65 0.300 2.000 12 0.010 2.00 2.65 0.300 2.000 13 0.010 2.00 2.65 0.300 2.000 21 0.010 2.00 2.65 0.300 2.000 22 0.010 2.00 2.65 0.300 2.000 - 23 0.010 2.00 2.65 0.300 2.000 + 23 0.010 2.00 2.65 0.300 2.000 31 0.010 2.00 2.65 0.300 2.000 32 0.010 2.00 2.65 0.300 2.000 41 0.010 2.00 2.65 0.300 2.000 @@ -2626,7 +2626,7 @@ RCHRES *** x - x NGQL TPFG PHFG ROFG CDFG SDFG PYFG LAT 11 331 1 3 0 0 0 0 0 40 END GQ-GENDATA - + GQ-AD-FLAGS *** x - x 11 331 0 0 0 0 0 0 0 0 @@ -2634,9 +2634,9 @@ RCHRES MON-WATEMP *** x - x JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC*** - 11 99 34. 35. 43. 53. 60. 65. 67. 66. 60. 52. 45. 36. - 101 116 33. 34. 42. 51. 63. 72. 77. 75. 69. 56. 45. 38. - 201 331 34. 35. 43. 53. 60. 65. 67. 66. 60. 52. 45. 36. + 11 99 34. 35. 43. 53. 60. 65. 67. 66. 60. 52. 45. 36. + 101 116 33. 34. 42. 51. 63. 72. 77. 75. 69. 56. 45. 38. + 201 331 34. 35. 43. 53. 60. 65. 67. 66. 60. 52. 45. 36. END MON-WATEMP ******************************************************************** @@ -2648,7 +2648,7 @@ RCHRES *** x - x GQUID DQAL CONCID CONV QTYID 11 331 E.COLI 5.00 #cfu 0.00353 #cfu END GQ-QALDATA - + GQ-QALFG *** x - x HDRL OXID PHOT VOLT BIOD GEN SDAS 11 331 0 0 0 0 0 1 0 @@ -2670,13 +2670,13 @@ END RCHRES *** Specification of time series supplied to operations *** *** EXT SOURCES *** ************************************************************************** - + EXT SOURCES <-Volume-> SsysSgap<--Mult-->Tran <-Target vols> <-Grp> <-Member-> *** x x tem strg<-factor->strg x x x x *** ***Pervious Land Segments*** - + ***Precipitation (stored as inches/hour) WDM1 112 PREC ENGL 1.00SAME PERLND 111 EXTNL PREC WDM1 121 PREC ENGL 1.00SAME PERLND 112 EXTNL PREC @@ -2833,19 +2833,19 @@ WDM1 905 PREC ENGL 1.00SAME PERLND 984 EXTNL PREC ***Air Temperature (stored as hourly deg. F) WDM1 113 ATEM ENGL 1.00SAME PERLND 111 984 EXTNL GATMP - + ***Cloud Cover (stored as hourly tenths) WDM1 118 CLOU ENGL 1.00SAME PERLND 111 984 EXTNL CLOUD - + ***Dew Point Temperature (stored as hourly deg. F) WDM1 117 DEWP ENGL 1.00SAME PERLND 111 984 EXTNL DTMPG - + ***Solar Radiation (stored as Langleys/hour) WDM1 115 SOLR ENGL 1.00SAME PERLND 111 984 EXTNL SOLRAD - + ***Wind Movement (stored as miles/hour) WDM1 114 WIND ENGL 1.00SAME PERLND 111 984 EXTNL WINMOV - + ***Potential Evapotranspiration (stored as inches/hour) WDM1 116 PEVT ENGL 1.00SAME PERLND 111 984 EXTNL PETINP @@ -2869,22 +2869,22 @@ WDM1 112 PREC ENGL 1.00SAME IMPLND 911 EXTNL PREC WDM1 121 PREC ENGL 1.00SAME IMPLND 912 EXTNL PREC WDM1 131 PREC ENGL 1.00SAME IMPLND 913 EXTNL PREC WDM1 905 PREC ENGL 1.00SAME IMPLND 914 EXTNL PREC - + ***Air Temperature (stored as hourly deg. F) WDM1 113 ATEM ENGL 1.00SAME IMPLND 611 914 EXTNL GATMP - + ***Cloud Cover (stored as hourly tenths) WDM1 118 CLOU ENGL 1.00SAME IMPLND 611 914 EXTNL CLOUD - + ***Dew Point Temperature (stored as hourly deg. F) WDM1 117 DEWP ENGL 1.00SAME IMPLND 611 914 EXTNL DTMPG - + ***Solar Radiation (stored as Langleys/hour) WDM1 115 SOLR ENGL 1.00SAME IMPLND 611 914 EXTNL SOLRAD - + ***Wind Movement (stored as miles/hour) WDM1 114 WIND ENGL 1.00SAME IMPLND 611 914 EXTNL WINMOV - + ***Potential Evapotranspiration (stored as inches/hour) WDM1 116 PEVT ENGL 1.00SAME IMPLND 611 914 EXTNL PETINP @@ -3066,8 +3066,8 @@ WDM1 827 TSSM ENGL 1.000E+0 DIV RCHRES 203 INFLOW ISED 3 WDM1 727 FCM ENGL 1.000E+0 DIV RCHRES 203 INFLOW IDQAL 1 END EXT SOURCES - - + + ******************************************************************************* *** Specification of linkages: land segments to reaches & between reaches *** *** SCHEMATIC *** @@ -3775,18 +3775,18 @@ END SCHEMATIC *** Specification of which time series will be output *** *** EXT TARGETS *** ************************************************************************** - + EXT TARGETS <-Volume-> <-Grp> <-Member-><--Mult-->Tran <-Volume-> Tsys Aggr Amd *** x x x<-factor->strg x qf tem strg strg*** END EXT TARGETS - + ************************************************************************** *** Tables specifying detailed time series connections *** *** MASS-LINK *** ************************************************************************** - + MASS-LINK *** Pervious Land Segments & non-MS4 *** @@ -3871,7 +3871,7 @@ END MASS-LINK *** RCHRES Geometric & Hydraulic Properties Function Tables *** *** FTABLEs *** ************************************************************************** - + FTABLES diff --git a/tests/HDF5_compare.ipynb b/tests/HDF5_compare.ipynb index 6fb09396..4bd99ba3 100644 --- a/tests/HDF5_compare.ipynb +++ b/tests/HDF5_compare.ipynb @@ -70,7 +70,8 @@ "source": [ "# An alternate approach to confirming the environment, using Python\n", "import os\n", - "os.environ['CONDA_DEFAULT_ENV']" + "\n", + "os.environ[\"CONDA_DEFAULT_ENV\"]" ] }, { @@ -95,9 +96,9 @@ "metadata": {}, "outputs": [], "source": [ - "import tables # PyTables\n", "import h5py\n", - "import pandas as pd" + "import pandas as pd\n", + "import tables # PyTables" ] }, { @@ -186,8 +187,8 @@ ], "source": [ "# use the Path module to construct file paths\n", - "project_folder = Path('Documents/Python/limno.HSPsquared/')\n", - "data_folder = Path('_LargeFileStash/')\n", + "project_folder = Path(\"Documents/Python/limno.HSPsquared/\")\n", + "data_folder = Path(\"_LargeFileStash/\")\n", "\n", "file_to_open = Path.cwd() / data_folder / \"hsp2.h5\"\n", "file_to_open" @@ -212,10 +213,10 @@ } ], "source": [ - "# list test files \n", + "# list test files\n", "paths = [\n", - " Path.cwd() / data_folder / 'calleg_hsp2_dev_input.h5',\n", - " Path.cwd() / data_folder / 'calleg_hsp2_devWDM_input-parts.h5',\n", + " Path.cwd() / data_folder / \"calleg_hsp2_dev_input.h5\",\n", + " Path.cwd() / data_folder / \"calleg_hsp2_devWDM_input-parts.h5\",\n", "]\n", "paths" ] @@ -925,7 +926,7 @@ } ], "source": [ - "ds0 = store0.select('/TIMESERIES/SUMMARY')\n", + "ds0 = store0.select(\"/TIMESERIES/SUMMARY\")\n", "ds0" ] }, @@ -957,7 +958,7 @@ } ], "source": [ - "ds0.loc['TS9906']" + "ds0.loc[\"TS9906\"]" ] }, { @@ -989,7 +990,7 @@ } ], "source": [ - "ds0ts = store0.select('/TIMESERIES/TS9906')\n", + "ds0ts = store0.select(\"/TIMESERIES/TS9906\")\n", "ds0ts" ] }, @@ -1286,7 +1287,7 @@ } ], "source": [ - "ds1 = store1.select('/TIMESERIES/SUMMARY')\n", + "ds1 = store1.select(\"/TIMESERIES/SUMMARY\")\n", "ds1" ] }, @@ -1617,11 +1618,11 @@ "\n", "for key in store0.keys()[100:]:\n", " ds0_ = store0.select(key)\n", - "# print(ds0_)\n", + " # print(ds0_)\n", " ds1_ = store1.select(key)\n", - "# print(ds1_)\n", + " # print(ds1_)\n", " compare = ds0_ == ds1_\n", - "# compare_info = ds0_.info() == ds1_.info()\n", + " # compare_info = ds0_.info() == ds1_.info()\n", "\n", " compares.append([key, compare_info, compare])" ] @@ -1776,7 +1777,7 @@ } ], "source": [ - "store1.select('/CONTROL/GLOBAL')" + "store1.select(\"/CONTROL/GLOBAL\")" ] }, { @@ -4735,7 +4736,7 @@ "source": [ "# Open HSP2 HDF5 file with PyTables\n", "h5file0 = tables.open_file(\n", - " paths[0],\n", + " paths[0],\n", ")\n", "# For a PyTables file, a dump of the object tree can be easily displayed\n", "# Warning: Output is quite verbose!\n", @@ -4791,7 +4792,7 @@ "outputs": [], "source": [ "h5file1 = tables.open_file(\n", - " paths[1],\n", + " paths[1],\n", ")\n", "# h5file1" ] @@ -5011,7 +5012,7 @@ "outputs": [], "source": [ "for key in h5py_file.keys():\n", - " print(key)" + " print(key)" ] }, { @@ -5021,7 +5022,7 @@ "metadata": {}, "outputs": [], "source": [ - "h5py_file['CONTROL'].keys()" + "h5py_file[\"CONTROL\"].keys()" ] }, { @@ -5031,7 +5032,7 @@ "metadata": {}, "outputs": [], "source": [ - "h5py_file['CONTROL']['GLOBAL'].keys()" + "h5py_file[\"CONTROL\"][\"GLOBAL\"].keys()" ] }, { @@ -5054,7 +5055,7 @@ "source": [ "for name in h5py_file:\n", " for subname in h5py_file[name]:\n", - " print(name+r'\\ '+subname)\n", + " print(name + r\"\\ \" + subname)\n", "# print(r'')\n", "# for subsubname in h5py_file[name][subname]:\n", "# print(name+r'\\ '+subname+r'\\ '+subsubname)" @@ -5109,7 +5110,6 @@ "metadata": {}, "outputs": [], "source": [ - "\n", "!h5dump '/Users/aaufdenkampe/Documents/Python/limno.HSPsquared/HSP2notebooks/Data/hsp2.h5'\n", "\n", "# WARNING: This is extremely verbose!!!!" @@ -5140,7 +5140,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.14" + "version": "3.11.11" }, "toc-autonumbering": false }, diff --git a/tests/ZRW_WestIndian/HSPF.WDM b/tests/ZRW_WestIndian/HSPF.WDM deleted file mode 100644 index d20499bd..00000000 Binary files a/tests/ZRW_WestIndian/HSPF.WDM and /dev/null differ diff --git a/tests/ZRW_WestIndian/HSPF.uci b/tests/ZRW_WestIndian/HSPF.uci index cc62e609..cd6d85ef 100644 --- a/tests/ZRW_WestIndian/HSPF.uci +++ b/tests/ZRW_WestIndian/HSPF.uci @@ -17,14 +17,13 @@ FILES MESSU 24 HSPF.ECH 25 HSPF.OUT WDM1 26 Met4.WDM -WDM2 27 HSPF.WDM WDM3 28 ZUMBROSCEN.WDM BINO 92 HSPF.HBN END FILES OPN SEQUENCE INGRP INDELT 01:00 - + ***Pervious Land Segments*** PERLND 5 PERLND 20 @@ -202,7 +201,7 @@ PERLND ******************************************************************** *** Pervious Land Segments -- Hydrology *** ******************************************************************** - + ATEMP-DAT *** ELDAT AIRTEMP *** x - x (ft) (deg F) @@ -1100,7 +1099,7 @@ PERLND 209 45. 35. 2. 2. 0.00 0.002 0.000 210 45. 35. 2. 2. 0.00 0.002 0.000 END PWAT-PARM3 - + PWAT-PARM4 *** CEPSC UZSN NSUR INTFW IRC LZETP *** x - x (in) (in) (1/day) @@ -1114,7 +1113,7 @@ PERLND 181 195 0. 0.10 0.10 0. 1.0E-30 0. 196 210 0. 0.20 0.15 0. 1.0E-30 0. END PWAT-PARM4 - + PWAT-PARM5 *** FZG FZGL *** x - x @@ -1804,7 +1803,7 @@ PERLND 209 0.63 0.63 0.63 0.63 0.63 0.63 0.63 0.63 0.63 0.63 0.63 0.63 210 0.63 0.63 0.63 0.63 0.63 0.63 0.63 0.63 0.63 0.63 0.63 0.63 END MON-IRC - + MON-LZETPARM *** Lower zone evapotranspiration parm at start of each month *** x - x JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC @@ -2245,7 +2244,7 @@ PERLND END SED-PARM2 SED-PARM3 -*** +*** *** x - x KSER JSER KGER JGER 1 1.20 2.00 0.38 2.50 2 1.20 2.00 0.38 2.50 @@ -2563,7 +2562,7 @@ PERLND 1 30 38. 42. 45. 47. 50. 50. 52. 50. 50. 48. 45. 42. 31 45 38. 42. 45. 47. 50. 50. 52. 50. 50. 48. 45. 42. 46 75 35. 35. 40. 42. 45. 50. 52. 50. 50. 48. 45. 42. - 76 105 35. 35. 40. 42. 45. 50. 52. 50. 50. 48. 45. 42. + 76 105 35. 35. 40. 42. 45. 50. 52. 50. 50. 48. 45. 42. 106 120 32. 32. 37. 44. 47. 52. 54. 55. 55. 53. 44. 40. 121 135 32. 32. 37. 44. 47. 52. 54. 55. 55. 53. 44. 40. 136 150 32. 32. 37. 44. 47. 52. 54. 55. 55. 53. 44. 40. @@ -2576,7 +2575,7 @@ PERLND *** x - x AIRTC SLTMP ULTMP LGTMP 1 210 32. 32. 32. 45. END PSTEMP-TEMPS - + ******************************************************************** *** Pervious Land Segments -- Water Temperature & Dissolved Gas *** ******************************************************************** @@ -2626,16 +2625,16 @@ PERLND *** *** x - x NQUAL ** 1 210 4 - END NQUALS + END NQUALS - PQL-AD-FLAGS + PQL-AD-FLAGS Atmospheric Deposition Flags *** QUAL1 QUAL2 QUAL3 QUAL4 *** # - # F C F C F C F C *** 1 210 -1 -1 -1 -1 0 0 0 0 END PQL-AD-FLAGS -***Total Ammonia Nitrogen*** +***Total Ammonia Nitrogen*** QUAL-PROPS *** Identifiers and Flags @@ -2654,7 +2653,7 @@ PERLND 196 210 0.100 0.550 END QUAL-INPUT - MON-ACCUM + MON-ACCUM ACCUMULATION RATE OF NH4 (lb NH4-N/AC.DAY) *** # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** 1 30.0012.0016.0020.0048.0048.0048.0048.0048.0048.0032.0016.0012 @@ -2666,9 +2665,9 @@ PERLND 166 180.0032.0032.0036.0088.0088.0088.0088.0088.0088.0088.0036.0032 181 195.0036.0036.0040.0100.0100.0100.0100.0100.0100.0100.0040.0036 196 210.0320.0320.0320.0320.0300.0300.0300.0300.0300.0320.0320.0320 - END MON-ACCUM - - MON-SQOLIM + END MON-ACCUM + + MON-SQOLIM STORAGE LIMIT OF NH4 (lb NH4-N/AC) *** # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC*** 1 30.0036.0048.0060.0144.0144.0144.0144.0144.0144.0096.0048.0036 @@ -2680,9 +2679,9 @@ PERLND 166 180.0096.0096.0108.0264.0264.0264.0264.0264.0264.0264.0108.0096 181 195.0108.0108.0120.0300.0300.0300.0300.0300.0300.0300.0120.0108 196 210.0960.0960.0960.0960.0900.0900.0900.0900.0900.0960.0960.0960 - END MON-SQOLIM - - MON-IFLW-CONC + END MON-SQOLIM + + MON-IFLW-CONC Interflow Concentration of NH4-N (mg/l) *** # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** 1 30 .045 .045 .045 .023 .023 .023 .023 .023 .023 .045 .045 .045 @@ -2694,9 +2693,9 @@ PERLND 166 180 .125 .125 .125 .095 .095 .095 .095 .095 .095 .125 .125 .125 181 195 .133 .133 .133 .100 .100 .100 .100 .100 .100 .133 .133 .133 196 210 .750 .750 .750 .720 .720 .720 .720 .720 .720 .750 .750 .750 - END MON-IFLW-CONC - - MON-GRND-CONC + END MON-IFLW-CONC + + MON-GRND-CONC Active Groundwater Concentration of NH4-N (mg/l) *** # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** 1 30 .060 .060 .060 .038 .038 .038 .038 .038 .038 .060 .060 .060 @@ -2710,14 +2709,14 @@ PERLND 181 195 .080 .080 .080 .075 .075 .075 .075 .075 .075 .080 .080 .080 196 210 .700 .700 .700 .680 .680 .680 .680 .680 .680 .700 .700 .700 - END MON-GRND-CONC + END MON-GRND-CONC -***Nitrite plus Nitrate*** - - QUAL-PROPS +***Nitrite plus Nitrate*** + + QUAL-PROPS # #<--QUALID--> QTID QSD VPFW VPFS QSO VQO QIFW VIQC QAGW VAQC *** 1 210 NO2+NO3 LBS 0 0 0 1 1 1 3 1 3 - END QUAL-PROPS + END QUAL-PROPS QUAL-INPUT # # SQO POTFW POTFS ACQOP SQOLIM WSQOP IOQC AOQC *** @@ -2729,8 +2728,8 @@ PERLND 151 195 0.450 0.500 196 210 5.000 0.550 END QUAL-INPUT - - MON-ACCUM + + MON-ACCUM ACCUMULATION RATE NO2 NO3 (lb NO3-N/AC.DAY) *** # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** 1 30 .013 .015 .016 .018 .018 .018 .016 .013 .010 .016 .020 .018 @@ -2742,9 +2741,9 @@ PERLND 166 180 .034 .049 .064 .068 .068 .078 .078 .078 .078 .064 .049 .034 181 195 .040 .050 .070 .080 .080 .080 .080 .080 .080 .070 .050 .040 196 210 .350 .350 .350 .350 .300 .300 .300 .300 .300 .350 .350 .350 - END MON-ACCUM - - MON-SQOLIM + END MON-ACCUM + + MON-SQOLIM STORAGE RATE OF NO2 NO3 (lb NO3-N/AC) *** # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** 1 30 .078 .090 .096 .108 .108 .108 .096 .078 .060 .096 .120 .108 @@ -2756,9 +2755,9 @@ PERLND 166 180 .204 .294 .384 .408 .408 .468 .468 .468 .468 .384 .294 .204 181 195 .240 .300 .420 .480 .480 .480 .480 .480 .480 .420 .300 .240 196 210 2.10 2.10 2.10 2.10 1.80 1.80 1.80 1.80 1.80 2.10 2.10 2.10 - END MON-SQOLIM - - MON-IFLW-CONC + END MON-SQOLIM + + MON-IFLW-CONC Interflow Concentration of NO3-N (mg/l) *** # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** 1 30 1.2 1.0 1.0 1.2 1.4 1.4 1.2 1.0 1.0 1.0 1.2 1.4 @@ -2773,9 +2772,9 @@ PERLND 181 195 2.4 2.0 2.0 2.4 2.8 2.8 2.4 2.0 2.0 2.0 2.4 2.8 196 210 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 20.0 - END MON-IFLW-CONC - - MON-GRND-CONC + END MON-IFLW-CONC + + MON-GRND-CONC Active Groundwater Concentration of NO3-N (mg/l) *** # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** 1 30 .60 .50 .50 .60 .70 .70 .60 .50 .50 .50 .60 .70 @@ -2790,16 +2789,16 @@ PERLND 181 195 1.2 1.0 1.0 1.2 1.4 1.4 1.2 1.0 1.0 1.0 1.2 1.4 196 210 12.0 10.0 10.0 12.0 14.0 14.0 12.0 10.0 10.0 10.0 12.0 14.0 - END MON-GRND-CONC - -***Ortho-Phosphorus*** - - QUAL-PROPS + END MON-GRND-CONC + +***Ortho-Phosphorus*** + + QUAL-PROPS # #<--QUALID--> QTID QSD VPFW VPFS QSO VQO QIFW VIQC QAGW VAQC *** 1 210 PO4 LBS 1 1 0 0 0 1 3 1 3 - END QUAL-PROPS + END QUAL-PROPS - QUAL-INPUT + QUAL-INPUT # # SQO POTFW POTFS ACQOP SQOLIM WSQOP IOQC AOQC *** 1 30 0.017 0.05 0.5 31 45 0.020 0.5 @@ -2809,9 +2808,9 @@ PERLND 121 150 0.380 0.70 0.5 151 195 0.040 0.5 196 210 0.040 0.5 - END QUAL-INPUT - - MON-POTFW + END QUAL-INPUT + + MON-POTFW # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** 1 30 .180 .180 .180 .180 .180 .180 .180 .180 .180 .180 .180 .180 31 45 .180 .180 .180 .180 .180 .180 .180 .180 .180 .180 .180 .180 @@ -2822,11 +2821,11 @@ PERLND 136 150 1.0 1.0 2.5 4.0 4.0 3.0 3.0 3.0 4.0 4.0 2.5 1.0 151 165 1.6 1.6 1.6 1.7 1.7 1.6 1.6 1.7 1.7 1.6 1.6 1.6 166 180 1.7 1.7 1.7 1.8 1.7 1.7 1.7 1.8 1.8 1.7 1.7 1.7 - 181 195 1.8 1.8 1.8 1.9 1.9 1.8 1.8 1.9 1.9 1.8 1.8 1.8 + 181 195 1.8 1.8 1.8 1.9 1.9 1.8 1.8 1.9 1.9 1.8 1.8 1.8 196 210 5.7 5.7 5.7 5.0 5.0 4.8 4.8 4.8 5.0 5.0 5.0 5.0 - END MON-POTFW - - MON-IFLW-CONC + END MON-POTFW + + MON-IFLW-CONC Interflow Concentration of PO4-P (mg/l) *** # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** 1 30 .050 .050 .050 .050 .050 .050 .050 .050 .050 .050 .050 .050 @@ -2841,9 +2840,9 @@ PERLND 181 195 .100 .100 .100 .100 .100 .100 .100 .100 .100 .100 .100 .100 196 210 .500 .500 .500 .500 .500 .500 .500 .500 .500 .500 .500 .500 - END MON-IFLW-CONC - - MON-GRND-CONC + END MON-IFLW-CONC + + MON-GRND-CONC Active Groundwater Concentration of PO4-P (mg/l) *** # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** 1 30 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 @@ -2858,15 +2857,15 @@ PERLND 181 195 .030 .030 .030 .030 .030 .030 .030 .030 .030 .030 .030 .030 196 210 .100 .100 .100 .100 .100 .100 .100 .100 .100 .100 .100 .100 - END MON-GRND-CONC + END MON-GRND-CONC -***Biochemical Oxygen Demand (Organic Nutrients)*** +***Biochemical Oxygen Demand (Organic Nutrients)*** - QUAL-PROPS + QUAL-PROPS # #<--QUALID--> QTID QSD VPFW VPFS QSO VQO QIFW VIQC QAGW VAQC *** 1 210 BOD LBS 1 0 0 0 0 1 3 1 3 - END QUAL-PROPS - + END QUAL-PROPS + QUAL-INPUT # # SQO POTFW POTFS ACQOP SQOLIM WSQOP IOQC AOQC *** 1 30 1.00 8.5 0.05 0.50 @@ -2881,7 +2880,7 @@ PERLND 196 210 7.00 141.0 0.50 END QUAL-INPUT - MON-IFLW-CONC + MON-IFLW-CONC Interflow Concentration of ORG (mg/l) *** # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** 1 30 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 @@ -3014,8 +3013,8 @@ IMPLND END SNOW-FLAGS SNOW-PARM1 -*** < ILS> LAT MELEV SHADE SNOWCF COVIND -*** x - x degrees (ft) (in) +*** < ILS> LAT MELEV SHADE SNOWCF COVIND +*** x - x degrees (ft) (in) 151 44.3 889 0.15 1.15 4.0 152 44.3 999 0.15 1.15 4.0 153 44.2 1080 0.15 1.15 4.0 @@ -3148,7 +3147,7 @@ IMPLND *** x - x RETS SURS 151 195 0.001 0.001 END IWAT-STATE1 - + ******************************************************************** *** Impervious Land Segments -- Sediment *** ******************************************************************** @@ -3180,7 +3179,7 @@ IMPLND ******************************************************************** ***Impervious Land Segments -- Water Temperature & Dissolved Gas *** -******************************************************************** +******************************************************************** IWT-PARM1 *** Flags for section IWTGAS @@ -3194,14 +3193,14 @@ IMPLND *** x - x (ft) (deg F) (deg F/F) 151 165 1027. 34. 0.3 166 180 1027. 34. 0.3 - 181 195 1027. 34. 0.3 + 181 195 1027. 34. 0.3 END IWT-PARM2 MON-AWTF *** Value of AWTF at start of each month (deg F) *** x - x JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 151 165 29. 29. 30. 34. 54. 63. 65. 64. 60. 48. 35. 30. - 166 180 29. 29. 30. 34. 54. 63. 65. 64. 60. 48. 35. 30. + 166 180 29. 29. 30. 34. 54. 63. 65. 64. 60. 48. 35. 30. 181 195 29. 29. 30. 34. 54. 63. 65. 64. 60. 48. 35. 30. END MON-AWTF @@ -3220,7 +3219,7 @@ IMPLND ***NQUAL 1 = NH3 ***NQUAL 2 = NO2+NO3 ***NQUAL 3 = PO4 -***NQUAL 4 = BOD +***NQUAL 4 = BOD NQUALS # # NQAL *** @@ -3233,7 +3232,7 @@ IMPLND # - # F C F C F C F C *** 151 195 -1 -1 -1 -1 0 0 0 0 END IQL-AD-FLAGS - + ***Total Ammonia Nitrogen*** QUAL-PROPS @@ -3259,7 +3258,7 @@ IMPLND END QUAL-INPUT ***Ortho-Phosphorus*** - + QUAL-PROPS # #<--QUALID--> QTID QSD VPFW QSO VQO *** 151 195 ORTHO P LBS 0 0 1 0 @@ -3892,7 +3891,7 @@ RCHRES SAND-PM *** RCHRES D W RHO KSAND EXPSND -*** x - x (in) (in/sec) (gm/cm3) +*** x - x (in) (in/sec) (gm/cm3) 1 0.005 2.00 2.5 1.000 3.0 2 0.005 2.00 2.5 1.000 3.0 3 0.005 2.00 2.5 1.000 2.5 @@ -4273,13 +4272,13 @@ RCHRES 508 612 1.047 .200 -1.673 .969 END OX-REAPARM - OX-CFOREA - RCHRES CFOREA*** - # - # *** + OX-CFOREA + RCHRES CFOREA*** + # - # *** ***Lakes 110 1.0 507 1.0 - END OX-CFOREA + END OX-CFOREA OX-BENPARM RCHRES BENOD TCBEN EXPOD BRBOD(1) BRBOD(2) EXPREL*** @@ -4287,16 +4286,16 @@ RCHRES 1 612 75. 1.074 1.22 1.00 10.0 2.82 END OX-BENPARM - OX-INIT + OX-INIT RCHRES DOX BOD SATDO *** # - # mg/l mg/l mg/l *** 1 612 12.8 3.5 13.5 - END OX-INIT + END OX-INIT NUT-FLAGS *** RCHRES Nutrient flags *** x - x NH3 NO2 PO4 AMV DEN ADNH ADPO PHFL - 1 612 1 1 1 0 1 1 1 + 1 612 1 1 1 0 1 1 1 END NUT-FLAGS NUT-AD-FLAGS @@ -4330,13 +4329,13 @@ RCHRES 1 612 .050 .012 1.070 .002 1.04 5. END NUT-NITDENIT - NUT-BEDCONC - RCHRES Bed concentrations of NH4 & PO4 (mg/kg) *** + NUT-BEDCONC + RCHRES Bed concentrations of NH4 & PO4 (mg/kg) *** # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** 1 612 30. 70. 70. 10. 500. 1000. - END NUT-BEDCONC + END NUT-BEDCONC - NUT-ADSPARM + NUT-ADSPARM RCHRES Partition coefficients for NH4 AND PO4 (ml/g) *** # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** 1 612 10. 50. 100. 100. 1000. 10000. @@ -4344,15 +4343,15 @@ RCHRES NUT-DINIT RCHRES NO3 TAM NO2 PO4 PH *** - # - # mg/l mg/l mg/l mg/l *** + # - # mg/l mg/l mg/l mg/l *** 1 612 4.00 .10 0. .050 7. END NUT-DINIT - NUT-ADSINIT + NUT-ADSINIT RCHRES Initial suspended NH4 and PO4 concentrations (mg/kg) *** # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** 1 612 0. 0. 0. 0. 0. 0. - END NUT-ADSINIT + END NUT-ADSINIT NUT-NH3VOLAT RCHRES EXPNVG EXPNVL *** @@ -4369,17 +4368,17 @@ RCHRES PLNK-PARM1 RCHRES RATCLP NONREF LITSED ALNPR EXTB MALGR *** # - # /ft /hr *** - 1 87 .68 .75 0.0015 0.50 .12 .100 - 100 109 .68 .75 0.0015 0.50 .12 .045 - 110 .68 .75 0.0015 0.50 .03 .030 - 111 506 .68 .75 0.0015 0.50 .12 .045 - 507 .68 .75 0.0015 0.50 .03 .030 - 508 612 .68 .75 0.0015 0.50 .12 .045 + 1 87 .68 .75 0.0015 0.50 .12 .100 + 100 109 .68 .75 0.0015 0.50 .12 .045 + 110 .68 .75 0.0015 0.50 .03 .030 + 111 506 .68 .75 0.0015 0.50 .12 .045 + 507 .68 .75 0.0015 0.50 .03 .030 + 508 612 .68 .75 0.0015 0.50 .12 .045 END PLNK-PARM1 PLNK-PARM2 - RCHRES CMMLT CMMN CMMNP CMMP TALGRH TALGRL TALGRM *** - # - # y/min mg/l mg/l mg/l deg F deg F degF *** +*** RCHRES CMMLT CMMN CMMNP CMMP TALGRH TALGRL TALGRM +*** # - # y/min mg/l mg/l mg/l deg F deg F degF 1 109 .033 0.045 .01 .015 95. 20. 77 110 .033 0.045 .005 .025 95. 20. 67 111 506 .033 0.045 .01 .015 95. 20. 77 @@ -4389,11 +4388,11 @@ RCHRES PLNK-PARM3 RCHRES ALR20 ALDH ALDL OXALD NALDH PALDH *** - # - # /hr /hr /hr /hr mg/l mg/l *** + # - # /hr /hr /hr /hr mg/l mg/l *** 1 109 .005 .02 .001 .03 .010 .002 110 .005 .005 .001 .03 .010 .002 111 506 .005 .02 .001 .03 .010 .002 - 507 .005 .005 .001 .03 .010 .002 + 507 .005 .005 .001 .03 .010 .002 508 612 .005 .02 .001 .03 .010 .002 END PLNK-PARM3 @@ -4537,558 +4536,558 @@ EXT SOURCES ***Pervious Land Segments*** ***Precipitation (stored as inches/hour) -WDM1 136 PREC ENGL 1.00SAME PERLND 1 EXTNL PREC -WDM1 137 PREC ENGL 1.00SAME PERLND 2 EXTNL PREC -WDM1 138 PREC ENGL 1.00SAME PERLND 3 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME PERLND 4 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME PERLND 5 EXTNL PREC -WDM1 141 PREC ENGL 1.00SAME PERLND 6 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME PERLND 7 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME PERLND 8 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME PERLND 9 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME PERLND 10 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME PERLND 11 EXTNL PREC -WDM1 147 PREC ENGL 1.00SAME PERLND 12 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME PERLND 13 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME PERLND 14 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME PERLND 15 EXTNL PREC -WDM1 136 PREC ENGL 1.00SAME PERLND 16 EXTNL PREC -WDM1 137 PREC ENGL 1.00SAME PERLND 17 EXTNL PREC -WDM1 138 PREC ENGL 1.00SAME PERLND 18 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME PERLND 19 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME PERLND 20 EXTNL PREC -WDM1 141 PREC ENGL 1.00SAME PERLND 21 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME PERLND 22 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME PERLND 23 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME PERLND 24 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME PERLND 25 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME PERLND 26 EXTNL PREC -WDM1 147 PREC ENGL 1.00SAME PERLND 27 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME PERLND 28 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME PERLND 29 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME PERLND 30 EXTNL PREC -WDM1 136 PREC ENGL 1.00SAME PERLND 31 EXTNL PREC -WDM1 137 PREC ENGL 1.00SAME PERLND 32 EXTNL PREC -WDM1 138 PREC ENGL 1.00SAME PERLND 33 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME PERLND 34 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME PERLND 35 EXTNL PREC -WDM1 141 PREC ENGL 1.00SAME PERLND 36 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME PERLND 37 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME PERLND 38 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME PERLND 39 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME PERLND 40 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME PERLND 41 EXTNL PREC -WDM1 147 PREC ENGL 1.00SAME PERLND 42 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME PERLND 43 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME PERLND 44 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME PERLND 45 EXTNL PREC -WDM1 136 PREC ENGL 1.00SAME PERLND 46 EXTNL PREC -WDM1 137 PREC ENGL 1.00SAME PERLND 47 EXTNL PREC -WDM1 138 PREC ENGL 1.00SAME PERLND 48 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME PERLND 49 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME PERLND 50 EXTNL PREC -WDM1 141 PREC ENGL 1.00SAME PERLND 51 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME PERLND 52 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME PERLND 53 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME PERLND 54 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME PERLND 55 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME PERLND 56 EXTNL PREC -WDM1 147 PREC ENGL 1.00SAME PERLND 57 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME PERLND 58 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME PERLND 59 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME PERLND 60 EXTNL PREC -WDM1 136 PREC ENGL 1.00SAME PERLND 61 EXTNL PREC -WDM1 137 PREC ENGL 1.00SAME PERLND 62 EXTNL PREC -WDM1 138 PREC ENGL 1.00SAME PERLND 63 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME PERLND 64 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME PERLND 65 EXTNL PREC -WDM1 141 PREC ENGL 1.00SAME PERLND 66 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME PERLND 67 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME PERLND 68 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME PERLND 69 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME PERLND 70 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME PERLND 71 EXTNL PREC -WDM1 147 PREC ENGL 1.00SAME PERLND 72 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME PERLND 73 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME PERLND 74 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME PERLND 75 EXTNL PREC -WDM1 136 PREC ENGL 1.00SAME PERLND 76 EXTNL PREC -WDM1 137 PREC ENGL 1.00SAME PERLND 77 EXTNL PREC -WDM1 138 PREC ENGL 1.00SAME PERLND 78 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME PERLND 79 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME PERLND 80 EXTNL PREC -WDM1 141 PREC ENGL 1.00SAME PERLND 81 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME PERLND 82 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME PERLND 83 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME PERLND 84 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME PERLND 85 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME PERLND 86 EXTNL PREC -WDM1 147 PREC ENGL 1.00SAME PERLND 87 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME PERLND 88 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME PERLND 89 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME PERLND 90 EXTNL PREC -WDM1 136 PREC ENGL 1.00SAME PERLND 91 EXTNL PREC -WDM1 137 PREC ENGL 1.00SAME PERLND 92 EXTNL PREC -WDM1 138 PREC ENGL 1.00SAME PERLND 93 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME PERLND 94 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME PERLND 95 EXTNL PREC -WDM1 141 PREC ENGL 1.00SAME PERLND 96 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME PERLND 97 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME PERLND 98 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME PERLND 99 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME PERLND 100 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME PERLND 101 EXTNL PREC -WDM1 147 PREC ENGL 1.00SAME PERLND 102 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME PERLND 103 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME PERLND 104 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME PERLND 105 EXTNL PREC -WDM1 136 PREC ENGL 1.00SAME PERLND 106 EXTNL PREC -WDM1 137 PREC ENGL 1.00SAME PERLND 107 EXTNL PREC -WDM1 138 PREC ENGL 1.00SAME PERLND 108 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME PERLND 109 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME PERLND 110 EXTNL PREC -WDM1 141 PREC ENGL 1.00SAME PERLND 111 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME PERLND 112 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME PERLND 113 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME PERLND 114 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME PERLND 115 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME PERLND 116 EXTNL PREC -WDM1 147 PREC ENGL 1.00SAME PERLND 117 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME PERLND 118 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME PERLND 119 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME PERLND 120 EXTNL PREC -WDM1 136 PREC ENGL 1.00SAME PERLND 121 EXTNL PREC -WDM1 137 PREC ENGL 1.00SAME PERLND 122 EXTNL PREC -WDM1 138 PREC ENGL 1.00SAME PERLND 123 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME PERLND 124 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME PERLND 125 EXTNL PREC -WDM1 141 PREC ENGL 1.00SAME PERLND 126 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME PERLND 127 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME PERLND 128 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME PERLND 129 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME PERLND 130 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME PERLND 131 EXTNL PREC -WDM1 147 PREC ENGL 1.00SAME PERLND 132 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME PERLND 133 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME PERLND 134 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME PERLND 135 EXTNL PREC -WDM1 136 PREC ENGL 1.00SAME PERLND 136 EXTNL PREC -WDM1 137 PREC ENGL 1.00SAME PERLND 137 EXTNL PREC -WDM1 138 PREC ENGL 1.00SAME PERLND 138 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME PERLND 139 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME PERLND 140 EXTNL PREC -WDM1 141 PREC ENGL 1.00SAME PERLND 141 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME PERLND 142 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME PERLND 143 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME PERLND 144 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME PERLND 145 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME PERLND 146 EXTNL PREC -WDM1 147 PREC ENGL 1.00SAME PERLND 147 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME PERLND 148 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME PERLND 149 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME PERLND 150 EXTNL PREC -WDM1 136 PREC ENGL 1.00SAME PERLND 151 EXTNL PREC -WDM1 137 PREC ENGL 1.00SAME PERLND 152 EXTNL PREC -WDM1 138 PREC ENGL 1.00SAME PERLND 153 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME PERLND 154 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME PERLND 155 EXTNL PREC -WDM1 141 PREC ENGL 1.00SAME PERLND 156 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME PERLND 157 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME PERLND 158 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME PERLND 159 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME PERLND 160 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME PERLND 161 EXTNL PREC -WDM1 147 PREC ENGL 1.00SAME PERLND 162 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME PERLND 163 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME PERLND 164 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME PERLND 165 EXTNL PREC -WDM1 136 PREC ENGL 1.00SAME PERLND 166 EXTNL PREC -WDM1 137 PREC ENGL 1.00SAME PERLND 167 EXTNL PREC -WDM1 138 PREC ENGL 1.00SAME PERLND 168 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME PERLND 169 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME PERLND 170 EXTNL PREC -WDM1 141 PREC ENGL 1.00SAME PERLND 171 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME PERLND 172 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME PERLND 173 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME PERLND 174 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME PERLND 175 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME PERLND 176 EXTNL PREC -WDM1 147 PREC ENGL 1.00SAME PERLND 177 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME PERLND 178 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME PERLND 179 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME PERLND 180 EXTNL PREC -WDM1 136 PREC ENGL 1.00SAME PERLND 181 EXTNL PREC -WDM1 137 PREC ENGL 1.00SAME PERLND 182 EXTNL PREC -WDM1 138 PREC ENGL 1.00SAME PERLND 183 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME PERLND 184 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME PERLND 185 EXTNL PREC -WDM1 141 PREC ENGL 1.00SAME PERLND 186 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME PERLND 187 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME PERLND 188 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME PERLND 189 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME PERLND 190 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME PERLND 191 EXTNL PREC -WDM1 147 PREC ENGL 1.00SAME PERLND 192 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME PERLND 193 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME PERLND 194 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME PERLND 195 EXTNL PREC -WDM1 136 PREC ENGL 1.00SAME PERLND 196 EXTNL PREC -WDM1 137 PREC ENGL 1.00SAME PERLND 197 EXTNL PREC -WDM1 138 PREC ENGL 1.00SAME PERLND 198 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME PERLND 199 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME PERLND 200 EXTNL PREC -WDM1 141 PREC ENGL 1.00SAME PERLND 201 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME PERLND 202 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME PERLND 203 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME PERLND 204 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME PERLND 205 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME PERLND 206 EXTNL PREC -WDM1 147 PREC ENGL 1.00SAME PERLND 207 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME PERLND 208 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME PERLND 1 EXTNL PREC +WDM1 137 PREC ENGL 1.00SAME PERLND 2 EXTNL PREC +WDM1 138 PREC ENGL 1.00SAME PERLND 3 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME PERLND 4 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME PERLND 5 EXTNL PREC +WDM1 141 PREC ENGL 1.00SAME PERLND 6 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME PERLND 7 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME PERLND 8 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME PERLND 9 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME PERLND 10 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME PERLND 11 EXTNL PREC +WDM1 147 PREC ENGL 1.00SAME PERLND 12 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME PERLND 13 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME PERLND 14 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME PERLND 15 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME PERLND 16 EXTNL PREC +WDM1 137 PREC ENGL 1.00SAME PERLND 17 EXTNL PREC +WDM1 138 PREC ENGL 1.00SAME PERLND 18 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME PERLND 19 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME PERLND 20 EXTNL PREC +WDM1 141 PREC ENGL 1.00SAME PERLND 21 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME PERLND 22 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME PERLND 23 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME PERLND 24 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME PERLND 25 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME PERLND 26 EXTNL PREC +WDM1 147 PREC ENGL 1.00SAME PERLND 27 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME PERLND 28 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME PERLND 29 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME PERLND 30 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME PERLND 31 EXTNL PREC +WDM1 137 PREC ENGL 1.00SAME PERLND 32 EXTNL PREC +WDM1 138 PREC ENGL 1.00SAME PERLND 33 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME PERLND 34 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME PERLND 35 EXTNL PREC +WDM1 141 PREC ENGL 1.00SAME PERLND 36 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME PERLND 37 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME PERLND 38 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME PERLND 39 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME PERLND 40 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME PERLND 41 EXTNL PREC +WDM1 147 PREC ENGL 1.00SAME PERLND 42 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME PERLND 43 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME PERLND 44 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME PERLND 45 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME PERLND 46 EXTNL PREC +WDM1 137 PREC ENGL 1.00SAME PERLND 47 EXTNL PREC +WDM1 138 PREC ENGL 1.00SAME PERLND 48 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME PERLND 49 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME PERLND 50 EXTNL PREC +WDM1 141 PREC ENGL 1.00SAME PERLND 51 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME PERLND 52 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME PERLND 53 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME PERLND 54 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME PERLND 55 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME PERLND 56 EXTNL PREC +WDM1 147 PREC ENGL 1.00SAME PERLND 57 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME PERLND 58 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME PERLND 59 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME PERLND 60 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME PERLND 61 EXTNL PREC +WDM1 137 PREC ENGL 1.00SAME PERLND 62 EXTNL PREC +WDM1 138 PREC ENGL 1.00SAME PERLND 63 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME PERLND 64 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME PERLND 65 EXTNL PREC +WDM1 141 PREC ENGL 1.00SAME PERLND 66 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME PERLND 67 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME PERLND 68 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME PERLND 69 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME PERLND 70 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME PERLND 71 EXTNL PREC +WDM1 147 PREC ENGL 1.00SAME PERLND 72 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME PERLND 73 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME PERLND 74 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME PERLND 75 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME PERLND 76 EXTNL PREC +WDM1 137 PREC ENGL 1.00SAME PERLND 77 EXTNL PREC +WDM1 138 PREC ENGL 1.00SAME PERLND 78 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME PERLND 79 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME PERLND 80 EXTNL PREC +WDM1 141 PREC ENGL 1.00SAME PERLND 81 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME PERLND 82 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME PERLND 83 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME PERLND 84 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME PERLND 85 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME PERLND 86 EXTNL PREC +WDM1 147 PREC ENGL 1.00SAME PERLND 87 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME PERLND 88 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME PERLND 89 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME PERLND 90 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME PERLND 91 EXTNL PREC +WDM1 137 PREC ENGL 1.00SAME PERLND 92 EXTNL PREC +WDM1 138 PREC ENGL 1.00SAME PERLND 93 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME PERLND 94 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME PERLND 95 EXTNL PREC +WDM1 141 PREC ENGL 1.00SAME PERLND 96 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME PERLND 97 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME PERLND 98 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME PERLND 99 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME PERLND 100 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME PERLND 101 EXTNL PREC +WDM1 147 PREC ENGL 1.00SAME PERLND 102 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME PERLND 103 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME PERLND 104 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME PERLND 105 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME PERLND 106 EXTNL PREC +WDM1 137 PREC ENGL 1.00SAME PERLND 107 EXTNL PREC +WDM1 138 PREC ENGL 1.00SAME PERLND 108 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME PERLND 109 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME PERLND 110 EXTNL PREC +WDM1 141 PREC ENGL 1.00SAME PERLND 111 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME PERLND 112 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME PERLND 113 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME PERLND 114 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME PERLND 115 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME PERLND 116 EXTNL PREC +WDM1 147 PREC ENGL 1.00SAME PERLND 117 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME PERLND 118 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME PERLND 119 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME PERLND 120 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME PERLND 121 EXTNL PREC +WDM1 137 PREC ENGL 1.00SAME PERLND 122 EXTNL PREC +WDM1 138 PREC ENGL 1.00SAME PERLND 123 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME PERLND 124 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME PERLND 125 EXTNL PREC +WDM1 141 PREC ENGL 1.00SAME PERLND 126 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME PERLND 127 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME PERLND 128 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME PERLND 129 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME PERLND 130 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME PERLND 131 EXTNL PREC +WDM1 147 PREC ENGL 1.00SAME PERLND 132 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME PERLND 133 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME PERLND 134 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME PERLND 135 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME PERLND 136 EXTNL PREC +WDM1 137 PREC ENGL 1.00SAME PERLND 137 EXTNL PREC +WDM1 138 PREC ENGL 1.00SAME PERLND 138 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME PERLND 139 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME PERLND 140 EXTNL PREC +WDM1 141 PREC ENGL 1.00SAME PERLND 141 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME PERLND 142 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME PERLND 143 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME PERLND 144 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME PERLND 145 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME PERLND 146 EXTNL PREC +WDM1 147 PREC ENGL 1.00SAME PERLND 147 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME PERLND 148 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME PERLND 149 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME PERLND 150 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME PERLND 151 EXTNL PREC +WDM1 137 PREC ENGL 1.00SAME PERLND 152 EXTNL PREC +WDM1 138 PREC ENGL 1.00SAME PERLND 153 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME PERLND 154 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME PERLND 155 EXTNL PREC +WDM1 141 PREC ENGL 1.00SAME PERLND 156 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME PERLND 157 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME PERLND 158 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME PERLND 159 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME PERLND 160 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME PERLND 161 EXTNL PREC +WDM1 147 PREC ENGL 1.00SAME PERLND 162 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME PERLND 163 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME PERLND 164 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME PERLND 165 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME PERLND 166 EXTNL PREC +WDM1 137 PREC ENGL 1.00SAME PERLND 167 EXTNL PREC +WDM1 138 PREC ENGL 1.00SAME PERLND 168 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME PERLND 169 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME PERLND 170 EXTNL PREC +WDM1 141 PREC ENGL 1.00SAME PERLND 171 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME PERLND 172 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME PERLND 173 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME PERLND 174 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME PERLND 175 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME PERLND 176 EXTNL PREC +WDM1 147 PREC ENGL 1.00SAME PERLND 177 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME PERLND 178 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME PERLND 179 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME PERLND 180 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME PERLND 181 EXTNL PREC +WDM1 137 PREC ENGL 1.00SAME PERLND 182 EXTNL PREC +WDM1 138 PREC ENGL 1.00SAME PERLND 183 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME PERLND 184 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME PERLND 185 EXTNL PREC +WDM1 141 PREC ENGL 1.00SAME PERLND 186 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME PERLND 187 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME PERLND 188 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME PERLND 189 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME PERLND 190 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME PERLND 191 EXTNL PREC +WDM1 147 PREC ENGL 1.00SAME PERLND 192 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME PERLND 193 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME PERLND 194 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME PERLND 195 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME PERLND 196 EXTNL PREC +WDM1 137 PREC ENGL 1.00SAME PERLND 197 EXTNL PREC +WDM1 138 PREC ENGL 1.00SAME PERLND 198 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME PERLND 199 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME PERLND 200 EXTNL PREC +WDM1 141 PREC ENGL 1.00SAME PERLND 201 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME PERLND 202 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME PERLND 203 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME PERLND 204 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME PERLND 205 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME PERLND 206 EXTNL PREC +WDM1 147 PREC ENGL 1.00SAME PERLND 207 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME PERLND 208 EXTNL PREC WDM1 149 PREC ENGL 1.00SAME PERLND 209 EXTNL PREC WDM1 150 PREC ENGL 1.00SAME PERLND 210 EXTNL PREC ***Air Temperature (stored as hourly deg. F) -WDM1 283 ATEM ENGL 1.00SAME PERLND 1 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 2 4 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 5 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 6 7 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 8 11 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 12 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME PERLND 13 14 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 15 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 16 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 17 19 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 20 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 21 22 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 23 26 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 27 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME PERLND 28 29 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 30 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 31 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 32 34 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 35 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 36 37 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 38 41 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 42 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME PERLND 43 44 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 45 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 46 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 47 49 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 50 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 51 52 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 53 56 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 57 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME PERLND 58 59 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 60 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 61 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 62 64 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 65 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 66 67 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 68 71 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 72 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME PERLND 73 74 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 75 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 76 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 77 79 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 80 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 81 82 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 83 86 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 87 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME PERLND 88 89 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 90 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 91 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 92 94 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 95 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 96 97 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 98 101 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 102 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME PERLND 103 104 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 105 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 106 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 107 109 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 110 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 111 112 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 113 116 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 117 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME PERLND 118 119 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 120 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 121 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 122 124 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 125 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 126 127 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 128 131 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 132 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME PERLND 133 134 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 135 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 136 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 137 139 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 140 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 141 142 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 143 146 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 147 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME PERLND 148 149 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 150 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 151 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 152 154 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 155 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 156 157 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 158 161 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 162 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME PERLND 163 164 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 165 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 166 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 167 169 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 170 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 171 172 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 173 176 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 177 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME PERLND 178 179 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 180 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 181 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 182 184 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 185 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 186 187 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 188 191 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 192 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME PERLND 193 194 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 195 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 196 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 197 199 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME PERLND 200 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 201 202 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 203 206 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME PERLND 207 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME PERLND 208 209 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME PERLND 210 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 1 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 2 4 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 5 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 6 7 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 8 11 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 12 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME PERLND 13 14 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 15 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 16 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 17 19 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 20 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 21 22 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 23 26 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 27 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME PERLND 28 29 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 30 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 31 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 32 34 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 35 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 36 37 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 38 41 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 42 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME PERLND 43 44 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 45 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 46 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 47 49 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 50 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 51 52 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 53 56 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 57 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME PERLND 58 59 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 60 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 61 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 62 64 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 65 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 66 67 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 68 71 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 72 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME PERLND 73 74 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 75 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 76 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 77 79 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 80 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 81 82 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 83 86 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 87 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME PERLND 88 89 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 90 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 91 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 92 94 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 95 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 96 97 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 98 101 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 102 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME PERLND 103 104 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 105 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 106 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 107 109 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 110 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 111 112 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 113 116 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 117 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME PERLND 118 119 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 120 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 121 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 122 124 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 125 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 126 127 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 128 131 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 132 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME PERLND 133 134 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 135 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 136 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 137 139 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 140 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 141 142 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 143 146 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 147 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME PERLND 148 149 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 150 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 151 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 152 154 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 155 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 156 157 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 158 161 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 162 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME PERLND 163 164 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 165 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 166 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 167 169 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 170 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 171 172 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 173 176 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 177 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME PERLND 178 179 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 180 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 181 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 182 184 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 185 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 186 187 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 188 191 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 192 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME PERLND 193 194 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 195 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 196 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 197 199 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME PERLND 200 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 201 202 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 203 206 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME PERLND 207 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME PERLND 208 209 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME PERLND 210 EXTNL GATMP ***Dew Point Temperature (stored as hourly deg. F) -WDM1 287 DEWP ENGL 1.00SAME PERLND 1 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 2 4 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 5 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 6 7 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 8 11 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 12 EXTNL DTMPG -WDM1 277 DEWP ENGL 1.00SAME PERLND 13 14 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 15 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 16 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 17 19 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 20 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 21 22 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 23 26 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 27 EXTNL DTMPG -WDM1 277 DEWP ENGL 1.00SAME PERLND 28 29 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 30 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 31 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 32 34 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 35 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 36 37 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 38 41 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 42 EXTNL DTMPG -WDM1 277 DEWP ENGL 1.00SAME PERLND 43 44 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 45 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 46 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 47 49 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 50 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 51 52 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 53 56 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 57 EXTNL DTMPG -WDM1 277 DEWP ENGL 1.00SAME PERLND 58 59 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 60 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 61 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 62 64 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 65 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 66 67 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 68 71 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 72 EXTNL DTMPG -WDM1 277 DEWP ENGL 1.00SAME PERLND 73 74 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 75 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 76 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 77 79 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 80 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 81 82 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 83 86 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 87 EXTNL DTMPG -WDM1 277 DEWP ENGL 1.00SAME PERLND 88 89 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 90 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 91 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 92 94 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 95 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 96 97 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 98 101 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 102 EXTNL DTMPG -WDM1 277 DEWP ENGL 1.00SAME PERLND 103 104 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 105 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 106 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 107 109 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 110 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 111 112 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 113 116 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 117 EXTNL DTMPG -WDM1 277 DEWP ENGL 1.00SAME PERLND 118 119 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 120 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 121 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 122 124 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 125 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 126 127 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 128 131 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 132 EXTNL DTMPG -WDM1 277 DEWP ENGL 1.00SAME PERLND 133 134 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 135 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 136 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 137 139 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 140 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 141 142 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 143 146 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 147 EXTNL DTMPG -WDM1 277 DEWP ENGL 1.00SAME PERLND 148 149 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 150 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 151 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 152 154 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 155 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 156 157 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 158 161 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 162 EXTNL DTMPG -WDM1 277 DEWP ENGL 1.00SAME PERLND 163 164 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 165 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 166 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 167 169 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 170 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 171 172 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 173 176 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 177 EXTNL DTMPG -WDM1 277 DEWP ENGL 1.00SAME PERLND 178 179 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 180 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 181 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 182 184 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 185 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 186 187 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 188 191 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 192 EXTNL DTMPG -WDM1 277 DEWP ENGL 1.00SAME PERLND 193 194 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 195 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 196 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 197 199 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME PERLND 200 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 201 202 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 203 206 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME PERLND 207 EXTNL DTMPG -WDM1 277 DEWP ENGL 1.00SAME PERLND 208 209 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME PERLND 210 EXTNL DTMPG - -***Cloud Cover (stored as hourly tenths) -WDM1 288 CLOU ENGL 1.00SAME PERLND 1 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 2 4 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 5 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 6 7 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 8 11 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 12 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME PERLND 13 14 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 15 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 16 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 17 19 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 20 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 21 22 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 23 26 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 27 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME PERLND 28 29 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 30 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 31 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 32 34 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 35 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 36 37 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 38 41 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 42 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME PERLND 43 44 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 45 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 46 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 47 49 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 50 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 51 52 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 53 56 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 57 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME PERLND 58 59 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 60 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 61 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 62 64 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 65 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 66 67 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 68 71 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 72 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME PERLND 73 74 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 75 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 76 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 77 79 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 80 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 81 82 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 83 86 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 87 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME PERLND 88 89 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 90 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 91 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 92 94 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 95 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 96 97 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 98 101 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 102 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME PERLND 103 104 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 105 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 106 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 107 109 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 110 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 111 112 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 113 116 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 117 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME PERLND 118 119 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 120 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 121 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 122 124 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 125 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 126 127 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 128 131 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 132 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME PERLND 133 134 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 135 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 136 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 137 139 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 140 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 141 142 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 143 146 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 147 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME PERLND 148 149 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 150 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 151 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 152 154 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 155 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 156 157 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 158 161 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 162 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME PERLND 163 164 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 165 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 166 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 167 169 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 170 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 171 172 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 173 176 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 177 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME PERLND 178 179 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 180 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 181 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 182 184 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 185 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 186 187 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 188 191 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 192 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME PERLND 193 194 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 195 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 196 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 197 199 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME PERLND 200 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 201 202 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 203 206 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME PERLND 207 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME PERLND 208 209 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME PERLND 210 EXTNL CLOUD +WDM1 287 DEWP ENGL 1.00SAME PERLND 1 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 2 4 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 5 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 6 7 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 8 11 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 12 EXTNL DTMPG +WDM1 277 DEWP ENGL 1.00SAME PERLND 13 14 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 15 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 16 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 17 19 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 20 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 21 22 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 23 26 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 27 EXTNL DTMPG +WDM1 277 DEWP ENGL 1.00SAME PERLND 28 29 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 30 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 31 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 32 34 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 35 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 36 37 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 38 41 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 42 EXTNL DTMPG +WDM1 277 DEWP ENGL 1.00SAME PERLND 43 44 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 45 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 46 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 47 49 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 50 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 51 52 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 53 56 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 57 EXTNL DTMPG +WDM1 277 DEWP ENGL 1.00SAME PERLND 58 59 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 60 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 61 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 62 64 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 65 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 66 67 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 68 71 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 72 EXTNL DTMPG +WDM1 277 DEWP ENGL 1.00SAME PERLND 73 74 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 75 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 76 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 77 79 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 80 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 81 82 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 83 86 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 87 EXTNL DTMPG +WDM1 277 DEWP ENGL 1.00SAME PERLND 88 89 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 90 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 91 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 92 94 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 95 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 96 97 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 98 101 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 102 EXTNL DTMPG +WDM1 277 DEWP ENGL 1.00SAME PERLND 103 104 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 105 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 106 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 107 109 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 110 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 111 112 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 113 116 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 117 EXTNL DTMPG +WDM1 277 DEWP ENGL 1.00SAME PERLND 118 119 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 120 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 121 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 122 124 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 125 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 126 127 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 128 131 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 132 EXTNL DTMPG +WDM1 277 DEWP ENGL 1.00SAME PERLND 133 134 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 135 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 136 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 137 139 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 140 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 141 142 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 143 146 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 147 EXTNL DTMPG +WDM1 277 DEWP ENGL 1.00SAME PERLND 148 149 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 150 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 151 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 152 154 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 155 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 156 157 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 158 161 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 162 EXTNL DTMPG +WDM1 277 DEWP ENGL 1.00SAME PERLND 163 164 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 165 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 166 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 167 169 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 170 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 171 172 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 173 176 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 177 EXTNL DTMPG +WDM1 277 DEWP ENGL 1.00SAME PERLND 178 179 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 180 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 181 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 182 184 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 185 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 186 187 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 188 191 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 192 EXTNL DTMPG +WDM1 277 DEWP ENGL 1.00SAME PERLND 193 194 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 195 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 196 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 197 199 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME PERLND 200 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 201 202 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 203 206 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME PERLND 207 EXTNL DTMPG +WDM1 277 DEWP ENGL 1.00SAME PERLND 208 209 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME PERLND 210 EXTNL DTMPG + +***Cloud Cover (stored as hourly tenths) +WDM1 288 CLOU ENGL 1.00SAME PERLND 1 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 2 4 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 5 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 6 7 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 8 11 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 12 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME PERLND 13 14 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 15 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 16 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 17 19 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 20 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 21 22 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 23 26 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 27 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME PERLND 28 29 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 30 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 31 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 32 34 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 35 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 36 37 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 38 41 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 42 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME PERLND 43 44 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 45 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 46 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 47 49 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 50 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 51 52 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 53 56 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 57 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME PERLND 58 59 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 60 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 61 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 62 64 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 65 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 66 67 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 68 71 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 72 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME PERLND 73 74 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 75 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 76 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 77 79 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 80 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 81 82 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 83 86 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 87 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME PERLND 88 89 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 90 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 91 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 92 94 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 95 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 96 97 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 98 101 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 102 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME PERLND 103 104 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 105 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 106 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 107 109 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 110 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 111 112 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 113 116 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 117 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME PERLND 118 119 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 120 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 121 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 122 124 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 125 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 126 127 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 128 131 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 132 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME PERLND 133 134 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 135 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 136 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 137 139 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 140 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 141 142 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 143 146 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 147 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME PERLND 148 149 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 150 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 151 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 152 154 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 155 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 156 157 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 158 161 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 162 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME PERLND 163 164 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 165 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 166 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 167 169 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 170 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 171 172 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 173 176 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 177 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME PERLND 178 179 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 180 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 181 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 182 184 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 185 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 186 187 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 188 191 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 192 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME PERLND 193 194 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 195 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 196 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 197 199 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME PERLND 200 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 201 202 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 203 206 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME PERLND 207 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME PERLND 208 209 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME PERLND 210 EXTNL CLOUD ***Solar Radiation (stored as Langleys/hour) WDM1 285 SOLR ENGL 1.00SAME PERLND 1 EXTNL SOLRAD @@ -5436,130 +5435,130 @@ WDM1 909 PEVT ENGL 0.79 PERLND 210 EXTNL PETINP ***Impervious Land Segments*** ***Precipitation (stored as inches/hour) -WDM1 136 PREC ENGL 1.00SAME IMPLND 151 EXTNL PREC -WDM1 137 PREC ENGL 1.00SAME IMPLND 152 EXTNL PREC -WDM1 138 PREC ENGL 1.00SAME IMPLND 153 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME IMPLND 154 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME IMPLND 155 EXTNL PREC -WDM1 141 PREC ENGL 1.00SAME IMPLND 156 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME IMPLND 157 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME IMPLND 158 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME IMPLND 159 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME IMPLND 160 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME IMPLND 161 EXTNL PREC -WDM1 147 PREC ENGL 1.00SAME IMPLND 162 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME IMPLND 163 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME IMPLND 164 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME IMPLND 165 EXTNL PREC -WDM1 136 PREC ENGL 1.00SAME IMPLND 166 EXTNL PREC -WDM1 137 PREC ENGL 1.00SAME IMPLND 167 EXTNL PREC -WDM1 138 PREC ENGL 1.00SAME IMPLND 168 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME IMPLND 169 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME IMPLND 170 EXTNL PREC -WDM1 141 PREC ENGL 1.00SAME IMPLND 171 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME IMPLND 172 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME IMPLND 173 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME IMPLND 174 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME IMPLND 175 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME IMPLND 176 EXTNL PREC -WDM1 147 PREC ENGL 1.00SAME IMPLND 177 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME IMPLND 178 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME IMPLND 179 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME IMPLND 180 EXTNL PREC -WDM1 136 PREC ENGL 1.00SAME IMPLND 181 EXTNL PREC -WDM1 137 PREC ENGL 1.00SAME IMPLND 182 EXTNL PREC -WDM1 138 PREC ENGL 1.00SAME IMPLND 183 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME IMPLND 184 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME IMPLND 185 EXTNL PREC -WDM1 141 PREC ENGL 1.00SAME IMPLND 186 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME IMPLND 187 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME IMPLND 188 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME IMPLND 189 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME IMPLND 190 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME IMPLND 191 EXTNL PREC -WDM1 147 PREC ENGL 1.00SAME IMPLND 192 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME IMPLND 193 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME IMPLND 194 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME IMPLND 195 EXTNL PREC - -***Air Temperature (stored as hourly deg. F) -WDM1 283 ATEM ENGL 1.00SAME IMPLND 151 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME IMPLND 152 154 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME IMPLND 155 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME IMPLND 156 157 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME IMPLND 158 161 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME IMPLND 162 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME IMPLND 163 164 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME IMPLND 165 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME IMPLND 166 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME IMPLND 167 169 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME IMPLND 170 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME IMPLND 171 172 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME IMPLND 173 176 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME IMPLND 177 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME IMPLND 178 179 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME IMPLND 180 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME IMPLND 181 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME IMPLND 182 184 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME IMPLND 185 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME IMPLND 186 187 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME IMPLND 188 191 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME IMPLND 192 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME IMPLND 193 194 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME IMPLND 195 EXTNL GATMP +WDM1 136 PREC ENGL 1.00SAME IMPLND 151 EXTNL PREC +WDM1 137 PREC ENGL 1.00SAME IMPLND 152 EXTNL PREC +WDM1 138 PREC ENGL 1.00SAME IMPLND 153 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME IMPLND 154 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME IMPLND 155 EXTNL PREC +WDM1 141 PREC ENGL 1.00SAME IMPLND 156 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME IMPLND 157 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME IMPLND 158 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME IMPLND 159 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME IMPLND 160 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME IMPLND 161 EXTNL PREC +WDM1 147 PREC ENGL 1.00SAME IMPLND 162 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME IMPLND 163 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME IMPLND 164 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME IMPLND 165 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME IMPLND 166 EXTNL PREC +WDM1 137 PREC ENGL 1.00SAME IMPLND 167 EXTNL PREC +WDM1 138 PREC ENGL 1.00SAME IMPLND 168 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME IMPLND 169 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME IMPLND 170 EXTNL PREC +WDM1 141 PREC ENGL 1.00SAME IMPLND 171 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME IMPLND 172 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME IMPLND 173 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME IMPLND 174 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME IMPLND 175 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME IMPLND 176 EXTNL PREC +WDM1 147 PREC ENGL 1.00SAME IMPLND 177 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME IMPLND 178 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME IMPLND 179 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME IMPLND 180 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME IMPLND 181 EXTNL PREC +WDM1 137 PREC ENGL 1.00SAME IMPLND 182 EXTNL PREC +WDM1 138 PREC ENGL 1.00SAME IMPLND 183 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME IMPLND 184 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME IMPLND 185 EXTNL PREC +WDM1 141 PREC ENGL 1.00SAME IMPLND 186 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME IMPLND 187 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME IMPLND 188 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME IMPLND 189 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME IMPLND 190 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME IMPLND 191 EXTNL PREC +WDM1 147 PREC ENGL 1.00SAME IMPLND 192 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME IMPLND 193 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME IMPLND 194 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME IMPLND 195 EXTNL PREC + +***Air Temperature (stored as hourly deg. F) +WDM1 283 ATEM ENGL 1.00SAME IMPLND 151 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME IMPLND 152 154 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME IMPLND 155 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME IMPLND 156 157 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME IMPLND 158 161 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME IMPLND 162 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME IMPLND 163 164 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME IMPLND 165 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME IMPLND 166 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME IMPLND 167 169 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME IMPLND 170 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME IMPLND 171 172 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME IMPLND 173 176 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME IMPLND 177 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME IMPLND 178 179 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME IMPLND 180 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME IMPLND 181 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME IMPLND 182 184 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME IMPLND 185 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME IMPLND 186 187 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME IMPLND 188 191 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME IMPLND 192 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME IMPLND 193 194 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME IMPLND 195 EXTNL GATMP ***Dew Point Temperature (stored as hourly deg. F) -WDM1 287 DEWP ENGL 1.00SAME IMPLND 151 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME IMPLND 152 154 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME IMPLND 155 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME IMPLND 156 157 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME IMPLND 158 161 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME IMPLND 162 EXTNL DTMPG -WDM1 277 DEWP ENGL 1.00SAME IMPLND 163 164 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME IMPLND 165 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME IMPLND 166 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME IMPLND 167 169 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME IMPLND 170 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME IMPLND 171 172 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME IMPLND 173 176 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME IMPLND 177 EXTNL DTMPG -WDM1 277 DEWP ENGL 1.00SAME IMPLND 178 179 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME IMPLND 180 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME IMPLND 181 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME IMPLND 182 184 EXTNL DTMPG -WDM1 287 DEWP ENGL 1.00SAME IMPLND 185 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME IMPLND 186 187 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME IMPLND 188 191 EXTNL DTMPG -WDM1 267 DEWP ENGL 1.00SAME IMPLND 192 EXTNL DTMPG -WDM1 277 DEWP ENGL 1.00SAME IMPLND 193 194 EXTNL DTMPG -WDM1 904 DEWP ENGL 1.00SAME IMPLND 195 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME IMPLND 151 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME IMPLND 152 154 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME IMPLND 155 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME IMPLND 156 157 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME IMPLND 158 161 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME IMPLND 162 EXTNL DTMPG +WDM1 277 DEWP ENGL 1.00SAME IMPLND 163 164 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME IMPLND 165 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME IMPLND 166 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME IMPLND 167 169 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME IMPLND 170 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME IMPLND 171 172 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME IMPLND 173 176 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME IMPLND 177 EXTNL DTMPG +WDM1 277 DEWP ENGL 1.00SAME IMPLND 178 179 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME IMPLND 180 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME IMPLND 181 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME IMPLND 182 184 EXTNL DTMPG +WDM1 287 DEWP ENGL 1.00SAME IMPLND 185 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME IMPLND 186 187 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME IMPLND 188 191 EXTNL DTMPG +WDM1 267 DEWP ENGL 1.00SAME IMPLND 192 EXTNL DTMPG +WDM1 277 DEWP ENGL 1.00SAME IMPLND 193 194 EXTNL DTMPG +WDM1 904 DEWP ENGL 1.00SAME IMPLND 195 EXTNL DTMPG ***Cloud Cover (stored as hourly tenths) -WDM1 288 CLOU ENGL 1.00SAME IMPLND 151 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME IMPLND 152 154 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME IMPLND 155 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME IMPLND 156 157 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME IMPLND 158 161 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME IMPLND 162 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME IMPLND 163 164 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME IMPLND 165 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME IMPLND 166 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME IMPLND 167 169 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME IMPLND 170 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME IMPLND 171 172 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME IMPLND 173 176 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME IMPLND 177 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME IMPLND 178 179 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME IMPLND 180 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME IMPLND 181 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME IMPLND 182 184 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME IMPLND 185 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME IMPLND 186 187 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME IMPLND 188 191 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME IMPLND 192 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME IMPLND 193 194 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME IMPLND 195 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME IMPLND 151 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME IMPLND 152 154 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME IMPLND 155 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME IMPLND 156 157 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME IMPLND 158 161 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME IMPLND 162 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME IMPLND 163 164 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME IMPLND 165 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME IMPLND 166 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME IMPLND 167 169 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME IMPLND 170 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME IMPLND 171 172 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME IMPLND 173 176 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME IMPLND 177 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME IMPLND 178 179 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME IMPLND 180 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME IMPLND 181 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME IMPLND 182 184 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME IMPLND 185 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME IMPLND 186 187 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME IMPLND 188 191 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME IMPLND 192 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME IMPLND 193 194 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME IMPLND 195 EXTNL CLOUD ***Solar Radiation (stored as Langleys/hour) WDM1 285 SOLR ENGL 1.00SAME IMPLND 151 EXTNL SOLRAD @@ -5643,139 +5642,139 @@ WDM1 909 PEVT ENGL 0.79 IMPLND 195 EXTNL PETINP ***Reach Segments*** ***Precipitation (stored as inches/hour) -WDM1 136 PREC ENGL 1.00SAME RCHRES 1 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME RCHRES 2 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME RCHRES 3 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME RCHRES 4 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME RCHRES 5 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME RCHRES 6 EXTNL PREC -WDM1 137 PREC ENGL 1.00SAME RCHRES 7 EXTNL PREC -WDM1 137 PREC ENGL 1.00SAME RCHRES 8 EXTNL PREC -WDM1 140 PREC ENGL 1.00SAME RCHRES 9 EXTNL PREC -WDM1 138 PREC ENGL 1.00SAME RCHRES 10 EXTNL PREC -WDM1 138 PREC ENGL 1.00SAME RCHRES 11 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME RCHRES 12 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME RCHRES 13 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME RCHRES 14 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME RCHRES 15 EXTNL PREC -WDM1 138 PREC ENGL 1.00SAME RCHRES 16 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME RCHRES 20 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME RCHRES 21 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME RCHRES 30 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME RCHRES 31 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME RCHRES 32 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME RCHRES 33 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME RCHRES 34 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME RCHRES 35 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME RCHRES 40 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME RCHRES 50 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME RCHRES 51 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME RCHRES 52 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME RCHRES 53 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME RCHRES 54 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME RCHRES 55 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME RCHRES 60 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME RCHRES 61 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME RCHRES 62 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME RCHRES 63 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME RCHRES 64 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME RCHRES 65 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME RCHRES 66 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME RCHRES 67 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME RCHRES 68 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME RCHRES 69 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME RCHRES 70 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME RCHRES 71 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME RCHRES 72 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME RCHRES 73 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME RCHRES 74 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME RCHRES 75 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME RCHRES 76 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME RCHRES 77 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME RCHRES 78 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME RCHRES 79 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME RCHRES 80 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME RCHRES 81 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME RCHRES 82 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME RCHRES 83 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME RCHRES 84 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME RCHRES 85 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME RCHRES 86 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME RCHRES 87 EXTNL PREC -WDM1 136 PREC ENGL 1.00SAME RCHRES 100 EXTNL PREC -WDM1 136 PREC ENGL 1.00SAME RCHRES 101 EXTNL PREC -WDM1 136 PREC ENGL 1.00SAME RCHRES 102 EXTNL PREC -WDM1 136 PREC ENGL 1.00SAME RCHRES 103 EXTNL PREC -WDM1 137 PREC ENGL 1.00SAME RCHRES 104 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME RCHRES 105 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME RCHRES 106 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME RCHRES 107 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME RCHRES 108 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME RCHRES 109 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME RCHRES 110 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME RCHRES 200 EXTNL PREC -WDM1 142 PREC ENGL 1.00SAME RCHRES 201 EXTNL PREC -WDM1 141 PREC ENGL 1.00SAME RCHRES 202 EXTNL PREC -WDM1 141 PREC ENGL 1.00SAME RCHRES 203 EXTNL PREC -WDM1 141 PREC ENGL 1.00SAME RCHRES 204 EXTNL PREC -WDM1 147 PREC ENGL 1.00SAME RCHRES 205 EXTNL PREC -WDM1 147 PREC ENGL 1.00SAME RCHRES 206 EXTNL PREC -WDM1 147 PREC ENGL 1.00SAME RCHRES 207 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME RCHRES 300 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME RCHRES 301 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME RCHRES 302 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME RCHRES 303 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME RCHRES 304 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME RCHRES 305 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME RCHRES 306 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME RCHRES 307 EXTNL PREC -WDM1 143 PREC ENGL 1.00SAME RCHRES 400 EXTNL PREC -WDM1 148 PREC ENGL 1.00SAME RCHRES 401 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME RCHRES 500 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME RCHRES 501 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME RCHRES 502 EXTNL PREC -WDM1 144 PREC ENGL 1.00SAME RCHRES 503 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME RCHRES 504 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME RCHRES 505 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME RCHRES 506 EXTNL PREC -WDM1 149 PREC ENGL 1.00SAME RCHRES 507 EXTNL PREC -WDM1 139 PREC ENGL 1.00SAME RCHRES 600 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME RCHRES 601 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME RCHRES 602 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME RCHRES 603 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME RCHRES 604 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME RCHRES 605 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME RCHRES 606 EXTNL PREC -WDM1 145 PREC ENGL 1.00SAME RCHRES 607 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME RCHRES 608 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME RCHRES 609 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME RCHRES 610 EXTNL PREC -WDM1 146 PREC ENGL 1.00SAME RCHRES 611 EXTNL PREC -WDM1 150 PREC ENGL 1.00SAME RCHRES 612 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME RCHRES 1 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME RCHRES 2 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME RCHRES 3 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME RCHRES 4 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME RCHRES 5 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME RCHRES 6 EXTNL PREC +WDM1 137 PREC ENGL 1.00SAME RCHRES 7 EXTNL PREC +WDM1 137 PREC ENGL 1.00SAME RCHRES 8 EXTNL PREC +WDM1 140 PREC ENGL 1.00SAME RCHRES 9 EXTNL PREC +WDM1 138 PREC ENGL 1.00SAME RCHRES 10 EXTNL PREC +WDM1 138 PREC ENGL 1.00SAME RCHRES 11 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME RCHRES 12 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME RCHRES 13 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME RCHRES 14 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME RCHRES 15 EXTNL PREC +WDM1 138 PREC ENGL 1.00SAME RCHRES 16 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME RCHRES 20 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME RCHRES 21 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME RCHRES 30 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME RCHRES 31 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME RCHRES 32 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME RCHRES 33 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME RCHRES 34 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME RCHRES 35 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME RCHRES 40 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME RCHRES 50 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME RCHRES 51 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME RCHRES 52 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME RCHRES 53 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME RCHRES 54 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME RCHRES 55 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME RCHRES 60 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME RCHRES 61 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME RCHRES 62 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME RCHRES 63 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME RCHRES 64 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME RCHRES 65 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME RCHRES 66 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME RCHRES 67 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME RCHRES 68 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME RCHRES 69 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME RCHRES 70 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME RCHRES 71 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME RCHRES 72 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME RCHRES 73 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME RCHRES 74 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME RCHRES 75 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME RCHRES 76 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME RCHRES 77 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME RCHRES 78 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME RCHRES 79 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME RCHRES 80 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME RCHRES 81 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME RCHRES 82 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME RCHRES 83 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME RCHRES 84 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME RCHRES 85 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME RCHRES 86 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME RCHRES 87 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME RCHRES 100 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME RCHRES 101 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME RCHRES 102 EXTNL PREC +WDM1 136 PREC ENGL 1.00SAME RCHRES 103 EXTNL PREC +WDM1 137 PREC ENGL 1.00SAME RCHRES 104 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME RCHRES 105 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME RCHRES 106 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME RCHRES 107 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME RCHRES 108 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME RCHRES 109 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME RCHRES 110 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME RCHRES 200 EXTNL PREC +WDM1 142 PREC ENGL 1.00SAME RCHRES 201 EXTNL PREC +WDM1 141 PREC ENGL 1.00SAME RCHRES 202 EXTNL PREC +WDM1 141 PREC ENGL 1.00SAME RCHRES 203 EXTNL PREC +WDM1 141 PREC ENGL 1.00SAME RCHRES 204 EXTNL PREC +WDM1 147 PREC ENGL 1.00SAME RCHRES 205 EXTNL PREC +WDM1 147 PREC ENGL 1.00SAME RCHRES 206 EXTNL PREC +WDM1 147 PREC ENGL 1.00SAME RCHRES 207 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME RCHRES 300 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME RCHRES 301 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME RCHRES 302 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME RCHRES 303 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME RCHRES 304 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME RCHRES 305 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME RCHRES 306 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME RCHRES 307 EXTNL PREC +WDM1 143 PREC ENGL 1.00SAME RCHRES 400 EXTNL PREC +WDM1 148 PREC ENGL 1.00SAME RCHRES 401 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME RCHRES 500 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME RCHRES 501 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME RCHRES 502 EXTNL PREC +WDM1 144 PREC ENGL 1.00SAME RCHRES 503 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME RCHRES 504 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME RCHRES 505 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME RCHRES 506 EXTNL PREC +WDM1 149 PREC ENGL 1.00SAME RCHRES 507 EXTNL PREC +WDM1 139 PREC ENGL 1.00SAME RCHRES 600 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME RCHRES 601 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME RCHRES 602 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME RCHRES 603 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME RCHRES 604 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME RCHRES 605 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME RCHRES 606 EXTNL PREC +WDM1 145 PREC ENGL 1.00SAME RCHRES 607 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME RCHRES 608 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME RCHRES 609 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME RCHRES 610 EXTNL PREC +WDM1 146 PREC ENGL 1.00SAME RCHRES 611 EXTNL PREC +WDM1 150 PREC ENGL 1.00SAME RCHRES 612 EXTNL PREC ***Air Temperature (stored as hourly deg. F) -WDM1 283 ATEM ENGL 1.00SAME RCHRES 1 6 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME RCHRES 7 8 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME RCHRES 9 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME RCHRES 10 11 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME RCHRES 12 14 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME RCHRES 15 16 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME RCHRES 20 21 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME RCHRES 30 31 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME RCHRES 32 40 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME RCHRES 50 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME RCHRES 51 55 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME RCHRES 60 87 EXTNL GATMP -WDM1 283 ATEM ENGL 1.00SAME RCHRES 100 103 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME RCHRES 104 200 EXTNL GATMP -WDM1 263 ATEM ENGL 1.00SAME RCHRES 201 207 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME RCHRES 300 305 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME RCHRES 306 307 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME RCHRES 400 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME RCHRES 401 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME RCHRES 500 503 EXTNL GATMP -WDM1 273 ATEM ENGL 1.00SAME RCHRES 504 507 EXTNL GATMP -WDM1 902 ATEM ENGL 1.00SAME RCHRES 600 612 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME RCHRES 1 6 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME RCHRES 7 8 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME RCHRES 9 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME RCHRES 10 11 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME RCHRES 12 14 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME RCHRES 15 16 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME RCHRES 20 21 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME RCHRES 30 31 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME RCHRES 32 40 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME RCHRES 50 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME RCHRES 51 55 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME RCHRES 60 87 EXTNL GATMP +WDM1 283 ATEM ENGL 1.00SAME RCHRES 100 103 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME RCHRES 104 200 EXTNL GATMP +WDM1 263 ATEM ENGL 1.00SAME RCHRES 201 207 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME RCHRES 300 305 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME RCHRES 306 307 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME RCHRES 400 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME RCHRES 401 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME RCHRES 500 503 EXTNL GATMP +WDM1 273 ATEM ENGL 1.00SAME RCHRES 504 507 EXTNL GATMP +WDM1 902 ATEM ENGL 1.00SAME RCHRES 600 612 EXTNL GATMP ***Dew Point Temperature (stored as hourly deg. F) @@ -5804,28 +5803,28 @@ WDM1 904 DEWP ENGL 1.00SAME RCHRES 600 612 EXTNL DEWTMP ***Cloud Cover (tenths) -WDM1 288 CLOU ENGL 1.00SAME RCHRES 1 6 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME RCHRES 7 8 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME RCHRES 9 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME RCHRES 10 11 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME RCHRES 12 14 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME RCHRES 15 16 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME RCHRES 20 21 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME RCHRES 30 31 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME RCHRES 32 40 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME RCHRES 50 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME RCHRES 51 55 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME RCHRES 60 87 EXTNL CLOUD -WDM1 288 CLOU ENGL 1.00SAME RCHRES 100 103 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME RCHRES 104 200 EXTNL CLOUD -WDM1 268 CLOU ENGL 1.00SAME RCHRES 201 207 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME RCHRES 300 305 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME RCHRES 306 307 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME RCHRES 400 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME RCHRES 401 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME RCHRES 500 503 EXTNL CLOUD -WDM1 278 CLOU ENGL 1.00SAME RCHRES 504 507 EXTNL CLOUD -WDM1 905 CLOU ENGL 1.00SAME RCHRES 600 612 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME RCHRES 1 6 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME RCHRES 7 8 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME RCHRES 9 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME RCHRES 10 11 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME RCHRES 12 14 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME RCHRES 15 16 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME RCHRES 20 21 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME RCHRES 30 31 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME RCHRES 32 40 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME RCHRES 50 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME RCHRES 51 55 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME RCHRES 60 87 EXTNL CLOUD +WDM1 288 CLOU ENGL 1.00SAME RCHRES 100 103 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME RCHRES 104 200 EXTNL CLOUD +WDM1 268 CLOU ENGL 1.00SAME RCHRES 201 207 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME RCHRES 300 305 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME RCHRES 306 307 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME RCHRES 400 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME RCHRES 401 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME RCHRES 500 503 EXTNL CLOUD +WDM1 278 CLOU ENGL 1.00SAME RCHRES 504 507 EXTNL CLOUD +WDM1 905 CLOU ENGL 1.00SAME RCHRES 600 612 EXTNL CLOUD ***Solar Radiation (stored as Langleys/hour) @@ -5854,53 +5853,53 @@ WDM1 908 SOLR ENGL 1.00SAME RCHRES 600 612 EXTNL SOLRAD ***Wind Movement (stored as miles/hour) -WDM1 284 WIND ENGL 1.00SAME RCHRES 1 6 EXTNL WIND -WDM1 903 WIND ENGL 1.00SAME RCHRES 7 8 EXTNL WIND -WDM1 284 WIND ENGL 1.00SAME RCHRES 9 EXTNL WIND -WDM1 903 WIND ENGL 1.00SAME RCHRES 10 11 EXTNL WIND -WDM1 264 WIND ENGL 1.00SAME RCHRES 12 14 EXTNL WIND -WDM1 903 WIND ENGL 1.00SAME RCHRES 15 16 EXTNL WIND -WDM1 264 WIND ENGL 1.00SAME RCHRES 20 21 EXTNL WIND -WDM1 903 WIND ENGL 1.00SAME RCHRES 30 31 EXTNL WIND -WDM1 274 WIND ENGL 1.00SAME RCHRES 32 40 EXTNL WIND -WDM1 903 WIND ENGL 1.00SAME RCHRES 50 EXTNL WIND -WDM1 274 WIND ENGL 1.00SAME RCHRES 51 55 EXTNL WIND -WDM1 903 WIND ENGL 1.00SAME RCHRES 60 87 EXTNL WIND -WDM1 284 WIND ENGL 1.00SAME RCHRES 100 103 EXTNL WIND -WDM1 903 WIND ENGL 1.00SAME RCHRES 104 200 EXTNL WIND -WDM1 264 WIND ENGL 1.00SAME RCHRES 201 207 EXTNL WIND -WDM1 903 WIND ENGL 1.00SAME RCHRES 300 305 EXTNL WIND -WDM1 274 WIND ENGL 1.00SAME RCHRES 306 307 EXTNL WIND -WDM1 903 WIND ENGL 1.00SAME RCHRES 400 EXTNL WIND -WDM1 274 WIND ENGL 1.00SAME RCHRES 401 EXTNL WIND -WDM1 903 WIND ENGL 1.00SAME RCHRES 500 503 EXTNL WIND -WDM1 274 WIND ENGL 1.00SAME RCHRES 504 507 EXTNL WIND -WDM1 903 WIND ENGL 1.00SAME RCHRES 600 612 EXTNL WIND +WDM1 284 WIND ENGL 1.00SAME RCHRES 1 6 EXTNL WIND +WDM1 903 WIND ENGL 1.00SAME RCHRES 7 8 EXTNL WIND +WDM1 284 WIND ENGL 1.00SAME RCHRES 9 EXTNL WIND +WDM1 903 WIND ENGL 1.00SAME RCHRES 10 11 EXTNL WIND +WDM1 264 WIND ENGL 1.00SAME RCHRES 12 14 EXTNL WIND +WDM1 903 WIND ENGL 1.00SAME RCHRES 15 16 EXTNL WIND +WDM1 264 WIND ENGL 1.00SAME RCHRES 20 21 EXTNL WIND +WDM1 903 WIND ENGL 1.00SAME RCHRES 30 31 EXTNL WIND +WDM1 274 WIND ENGL 1.00SAME RCHRES 32 40 EXTNL WIND +WDM1 903 WIND ENGL 1.00SAME RCHRES 50 EXTNL WIND +WDM1 274 WIND ENGL 1.00SAME RCHRES 51 55 EXTNL WIND +WDM1 903 WIND ENGL 1.00SAME RCHRES 60 87 EXTNL WIND +WDM1 284 WIND ENGL 1.00SAME RCHRES 100 103 EXTNL WIND +WDM1 903 WIND ENGL 1.00SAME RCHRES 104 200 EXTNL WIND +WDM1 264 WIND ENGL 1.00SAME RCHRES 201 207 EXTNL WIND +WDM1 903 WIND ENGL 1.00SAME RCHRES 300 305 EXTNL WIND +WDM1 274 WIND ENGL 1.00SAME RCHRES 306 307 EXTNL WIND +WDM1 903 WIND ENGL 1.00SAME RCHRES 400 EXTNL WIND +WDM1 274 WIND ENGL 1.00SAME RCHRES 401 EXTNL WIND +WDM1 903 WIND ENGL 1.00SAME RCHRES 500 503 EXTNL WIND +WDM1 274 WIND ENGL 1.00SAME RCHRES 504 507 EXTNL WIND +WDM1 903 WIND ENGL 1.00SAME RCHRES 600 612 EXTNL WIND ***Potential Evapotranspiration (stored as inches/hour) -WDM1 286 PEVT ENGL 0.80 RCHRES 1 6 EXTNL POTEV -WDM1 909 PEVT ENGL 0.80 RCHRES 7 8 EXTNL POTEV -WDM1 286 PEVT ENGL 0.80 RCHRES 9 EXTNL POTEV -WDM1 909 PEVT ENGL 0.80 RCHRES 10 11 EXTNL POTEV -WDM1 266 PEVT ENGL 0.80 RCHRES 12 14 EXTNL POTEV -WDM1 909 PEVT ENGL 0.80 RCHRES 15 16 EXTNL POTEV -WDM1 266 PEVT ENGL 0.80 RCHRES 20 21 EXTNL POTEV -WDM1 909 PEVT ENGL 0.80 RCHRES 30 31 EXTNL POTEV -WDM1 276 PEVT ENGL 0.80 RCHRES 32 40 EXTNL POTEV -WDM1 909 PEVT ENGL 0.80 RCHRES 50 EXTNL POTEV -WDM1 276 PEVT ENGL 0.80 RCHRES 51 55 EXTNL POTEV -WDM1 909 PEVT ENGL 0.80 RCHRES 60 87 EXTNL POTEV -WDM1 286 PEVT ENGL 0.80 RCHRES 100 103 EXTNL POTEV -WDM1 909 PEVT ENGL 0.80 RCHRES 104 200 EXTNL POTEV -WDM1 266 PEVT ENGL 0.80 RCHRES 201 207 EXTNL POTEV -WDM1 909 PEVT ENGL 0.80 RCHRES 300 305 EXTNL POTEV -WDM1 276 PEVT ENGL 0.80 RCHRES 306 307 EXTNL POTEV -WDM1 909 PEVT ENGL 0.80 RCHRES 400 EXTNL POTEV -WDM1 276 PEVT ENGL 0.80 RCHRES 401 EXTNL POTEV -WDM1 909 PEVT ENGL 0.80 RCHRES 500 503 EXTNL POTEV -WDM1 276 PEVT ENGL 0.80 RCHRES 504 507 EXTNL POTEV -WDM1 909 PEVT ENGL 0.80 RCHRES 600 612 EXTNL POTEV +WDM1 286 PEVT ENGL 0.80 RCHRES 1 6 EXTNL POTEV +WDM1 909 PEVT ENGL 0.80 RCHRES 7 8 EXTNL POTEV +WDM1 286 PEVT ENGL 0.80 RCHRES 9 EXTNL POTEV +WDM1 909 PEVT ENGL 0.80 RCHRES 10 11 EXTNL POTEV +WDM1 266 PEVT ENGL 0.80 RCHRES 12 14 EXTNL POTEV +WDM1 909 PEVT ENGL 0.80 RCHRES 15 16 EXTNL POTEV +WDM1 266 PEVT ENGL 0.80 RCHRES 20 21 EXTNL POTEV +WDM1 909 PEVT ENGL 0.80 RCHRES 30 31 EXTNL POTEV +WDM1 276 PEVT ENGL 0.80 RCHRES 32 40 EXTNL POTEV +WDM1 909 PEVT ENGL 0.80 RCHRES 50 EXTNL POTEV +WDM1 276 PEVT ENGL 0.80 RCHRES 51 55 EXTNL POTEV +WDM1 909 PEVT ENGL 0.80 RCHRES 60 87 EXTNL POTEV +WDM1 286 PEVT ENGL 0.80 RCHRES 100 103 EXTNL POTEV +WDM1 909 PEVT ENGL 0.80 RCHRES 104 200 EXTNL POTEV +WDM1 266 PEVT ENGL 0.80 RCHRES 201 207 EXTNL POTEV +WDM1 909 PEVT ENGL 0.80 RCHRES 300 305 EXTNL POTEV +WDM1 276 PEVT ENGL 0.80 RCHRES 306 307 EXTNL POTEV +WDM1 909 PEVT ENGL 0.80 RCHRES 400 EXTNL POTEV +WDM1 276 PEVT ENGL 0.80 RCHRES 401 EXTNL POTEV +WDM1 909 PEVT ENGL 0.80 RCHRES 500 503 EXTNL POTEV +WDM1 276 PEVT ENGL 0.80 RCHRES 504 507 EXTNL POTEV +WDM1 909 PEVT ENGL 0.80 RCHRES 600 612 EXTNL POTEV ********************************************************************* @@ -5912,7 +5911,7 @@ WDM1 909 PEVT ENGL 0.80 RCHRES 600 612 EXTNL POTEV *** Discharge: FLOW (stored as MG/day) * 3.0689 acre-ft/MG = acre-ft/day *** TSS Silt Fractionation: TSS (stored as lbs/day) * 5E-4 ton/lb * 0.40 (Silt/Total) = ton/day *** *Net conversion factor = 2.0E-4 -*** TSS Clay Fractionation TSS: (stored as lbs/day) * 5E-4 ton/lb * 0.60 (Clay/Total) = ton/day +*** TSS Clay Fractionation TSS: (stored as lbs/day) * 5E-4 ton/lb * 0.60 (Clay/Total) = ton/day *** *Net conversion factor = 3.0E-4 *** Dissolved Oxygen: DOX(stored as lbs/day) = no conversion factor *** BOD Ultimate: BOD5(stored as lbs/day) * 2.5 (assumed BODU/BOD5) = lbs/day @@ -5925,7 +5924,7 @@ WDM1 909 PEVT ENGL 0.80 RCHRES 600 612 EXTNL POTEV *** *Net conversion factor = 0.1072 *** Ortho-Phosphorus: TP (stored as lbs/day) * 0.7235 (assumed fraction of TP) = lbs/day *** Organic Refractory Phosphorus: TP (stored as lbs/day) * 0.2765 (assumed fraction of TP) = lbs/day -*** Organic Refractory Carbon: BOD5 (stored as lbs/day) * 2.5 (assumed BODU/BOD5) * 0.2699 (assumed fraction of BODU) = lbs/day +*** Organic Refractory Carbon: BOD5 (stored as lbs/day) * 2.5 (assumed BODU/BOD5) * 0.2699 (assumed fraction of BODU) = lbs/day *** *Net conversion factor = 0.6748 *** DIV time series transform function is used for all to convert /day to /hour @@ -6368,7 +6367,7 @@ WDM3 627 HEAT ENGL 1.0000 DIV RCHRES 606 INFLOW IHEAT 1 *** Atmospheric Deposition *** ********************************************************************* -*** Dry Atmospheric Deposition Inputs +*** Dry Atmospheric Deposition Inputs *** Stored as "kg/ha/day" *** Multiply by 0.404687 ha/acre and 2.204623 lb/kg to convert to lb/acre/day *** Multiply by 0.778 for NH4, by 0.226 for NO3 to convert to elemental N @@ -6563,7 +6562,7 @@ PERLND SEDMNT WSSD 1 0.350 RCHRES INFLOW ISED 3 PERLND SEDMNT SCRSD 1 0.190 RCHRES INFLOW ISED 1 PERLND SEDMNT SCRSD 1 0.610 RCHRES INFLOW ISED 2 PERLND SEDMNT SCRSD 1 0.200 RCHRES INFLOW ISED 3 - + *** Assume 5 mg/l clay in groundwater outflow (AGWO)*** *** AGWO (in/hr) * 5 (mg/L) * PLS_Area (acres) * [1 ft/12 in] * [1 ton/9.072E+8 mg] * [1.233E+6 L/acre-ft] = Clay Load (tons/hr) *** *** Net conversion factor = 5.66E-4 @@ -6572,23 +6571,23 @@ PERLND PWATER AGWO 5.66E-4 RCHRES INFLOW ISED 3 PERLND PWTGAS POHT RCHRES INFLOW IHEAT PERLND PWTGAS PODOXM RCHRES INFLOW OXIF 1 PERLND PQUAL POQUAL 1 RCHRES INFLOW NUIF1 2 -PERLND PQUAL POQUAL 2 RCHRES INFLOW NUIF1 1 -PERLND PQUAL SOQUAL 3 0.100 RCHRES INFLOW NUIF1 4 -PERLND PQUAL SOQUAL 3 0.580 RCHRES INFLOW NUIF2 2 2 -PERLND PQUAL SOQUAL 3 0.32 RCHRES INFLOW NUIF2 3 2 -PERLND PQUAL IOQUAL 3 1.00 RCHRES INFLOW NUIF1 4 -PERLND PQUAL AOQUAL 3 1.00 RCHRES INFLOW NUIF1 4 -PERLND PQUAL SOQUAL 4 0.40 RCHRES INFLOW OXIF 2 -PERLND PQUAL IOQUAL 4 0.32 RCHRES INFLOW OXIF 2 -PERLND PQUAL AOQUAL 4 0.40 RCHRES INFLOW OXIF 2 -PERLND PQUAL SOQUAL 4 0.0407 RCHRES INFLOW PKIF 3 -PERLND PQUAL AOQUAL 4 0.0488 RCHRES INFLOW PKIF 3 -PERLND PQUAL IOQUAL 4 0.0407 RCHRES INFLOW PKIF 3 +PERLND PQUAL POQUAL 2 RCHRES INFLOW NUIF1 1 +PERLND PQUAL SOQUAL 3 0.100 RCHRES INFLOW NUIF1 4 +PERLND PQUAL SOQUAL 3 0.580 RCHRES INFLOW NUIF2 2 2 +PERLND PQUAL SOQUAL 3 0.32 RCHRES INFLOW NUIF2 3 2 +PERLND PQUAL IOQUAL 3 1.00 RCHRES INFLOW NUIF1 4 +PERLND PQUAL AOQUAL 3 1.00 RCHRES INFLOW NUIF1 4 +PERLND PQUAL SOQUAL 4 0.40 RCHRES INFLOW OXIF 2 +PERLND PQUAL IOQUAL 4 0.32 RCHRES INFLOW OXIF 2 +PERLND PQUAL AOQUAL 4 0.40 RCHRES INFLOW OXIF 2 +PERLND PQUAL SOQUAL 4 0.0407 RCHRES INFLOW PKIF 3 +PERLND PQUAL AOQUAL 4 0.0488 RCHRES INFLOW PKIF 3 +PERLND PQUAL IOQUAL 4 0.0407 RCHRES INFLOW PKIF 3 PERLND PQUAL SOQUAL 4 0.0051 RCHRES INFLOW PKIF 4 -PERLND PQUAL IOQUAL 4 0.0051 RCHRES INFLOW PKIF 4 -PERLND PQUAL AOQUAL 4 0.0040 RCHRES INFLOW PKIF 4 -PERLND PQUAL POQUAL 4 0.570 RCHRES INFLOW PKIF 5 - END MASS-LINK 1 +PERLND PQUAL IOQUAL 4 0.0051 RCHRES INFLOW PKIF 4 +PERLND PQUAL AOQUAL 4 0.0040 RCHRES INFLOW PKIF 4 +PERLND PQUAL POQUAL 4 0.570 RCHRES INFLOW PKIF 5 + END MASS-LINK 1 *** IMPLNDs (EIA) *** MASS-LINK 2 @@ -6596,20 +6595,20 @@ PERLND PQUAL POQUAL 4 0.570 RCHRES INFLOW PKIF 5 x x<-factor->strg x x *** ***Conversion of Runoff from inches to ac-ft = 0.083333*** IMPLND IWATER SURO 0.0833333 RCHRES INFLOW IVOL -IMPLND SOLIDS SOSLD 0.050 RCHRES INFLOW ISED 1 -IMPLND SOLIDS SOSLD 0.600 RCHRES INFLOW ISED 2 +IMPLND SOLIDS SOSLD 0.050 RCHRES INFLOW ISED 1 +IMPLND SOLIDS SOSLD 0.600 RCHRES INFLOW ISED 2 IMPLND SOLIDS SOSLD 0.350 RCHRES INFLOW ISED 3 IMPLND IWTGAS SOHT RCHRES INFLOW IHEAT IMPLND IWTGAS SODOXM RCHRES INFLOW OXIF 1 IMPLND IQUAL SOQUAL 1 RCHRES INFLOW NUIF1 2 -IMPLND IQUAL SOQUAL 2 RCHRES INFLOW NUIF1 1 -IMPLND IQUAL SOQUAL 3 RCHRES INFLOW NUIF1 4 -IMPLND IQUAL SOQUAL 4 0.40 RCHRES INFLOW OXIF 2 -IMPLND IQUAL SOQUAL 4 0.0407 RCHRES INFLOW PKIF 3 -IMPLND IQUAL SOQUAL 4 0.0051 RCHRES INFLOW PKIF 4 -IMPLND IQUAL SOQUAL 4 0.570 RCHRES INFLOW PKIF 5 +IMPLND IQUAL SOQUAL 2 RCHRES INFLOW NUIF1 1 +IMPLND IQUAL SOQUAL 3 RCHRES INFLOW NUIF1 4 +IMPLND IQUAL SOQUAL 4 0.40 RCHRES INFLOW OXIF 2 +IMPLND IQUAL SOQUAL 4 0.0407 RCHRES INFLOW PKIF 3 +IMPLND IQUAL SOQUAL 4 0.0051 RCHRES INFLOW PKIF 4 +IMPLND IQUAL SOQUAL 4 0.570 RCHRES INFLOW PKIF 5 END MASS-LINK 2 - + *** RCHRES *** MASS-LINK 5 <-Volume-> <-Grp> <-Member-><--Mult-->Tran <-Target vols> <-Grp> <-Member-> *** @@ -6663,10 +6662,10 @@ PERLND PQUAL POQUAL 4 0.570 RCHRES INFLOW PKIF 5 x x<-factor->strg x x *** ***Conversion of Runoff from inches to ac-ft = 0.083333*** IMPLND IWATER SURO 0.0833333 RCHRES INFLOW IVOL -IMPLND SOLIDS SOSLD 0.050 RCHRES INFLOW ISED 1 -IMPLND SOLIDS SOSLD 0.600 RCHRES INFLOW ISED 2 +IMPLND SOLIDS SOSLD 0.050 RCHRES INFLOW ISED 1 +IMPLND SOLIDS SOSLD 0.600 RCHRES INFLOW ISED 2 IMPLND SOLIDS SOSLD 0.350 RCHRES INFLOW ISED 3 -IMPLND IWTGAS SOHT RCHRES INFLOW IHEAT +IMPLND IWTGAS SOHT RCHRES INFLOW IHEAT IMPLND IWTGAS SODOXM RCHRES INFLOW OXIF 1 IMPLND IQUAL SOQUAL 1 RCHRES INFLOW NUIF1 2 IMPLND IQUAL SOQUAL 2 RCHRES INFLOW NUIF1 1 @@ -6674,7 +6673,7 @@ IMPLND IQUAL SOQUAL 3 RCHRES INFLOW NUIF1 4 IMPLND IQUAL SOQUAL 4 0.40 RCHRES INFLOW OXIF 2 IMPLND IQUAL SOQUAL 4 0.0407 RCHRES INFLOW PKIF 3 IMPLND IQUAL SOQUAL 4 0.0051 RCHRES INFLOW PKIF 4 -IMPLND IQUAL SOQUAL 4 0.570 RCHRES INFLOW PKIF 5 +IMPLND IQUAL SOQUAL 4 0.570 RCHRES INFLOW PKIF 5 END MASS-LINK 12 ********************************************************************* @@ -6721,16 +6720,16 @@ END MASS-LINK GENER OPCODE - #thru# code *** - 101 115 25 - 201 215 19 + #thru# code *** + 101 115 25 + 201 215 19 301 315 18 END OPCODE PARM *** Set minimum surface runoff depth to 0.1 inch for calculation of sediment concentration in tile drainage *** *** to prevent divide by zero error *** - #thru# constant *** + #thru# constant *** 101 115 0.1 END PARM END GENER diff --git a/tests/convert/conversion_test.py b/tests/convert/conversion_test.py index 10aa10fb..a7aeb648 100644 --- a/tests/convert/conversion_test.py +++ b/tests/convert/conversion_test.py @@ -1,16 +1,17 @@ from datetime import datetime -from tests.convert.regression_base import RegressTest -if __name__ == '__main__': - #compare_cases = ['test05', 'test09', 'test10', 'test10b', 'Calleg', 'GRW_Plaster', 'ZRW_WestIndian'] - #compare_cases = ['test10'] # control test cases for comparison - compare_case = 'GLWACSO' +from tests.convert.regression_base import RegressTest + +if __name__ == "__main__": + # compare_cases = ['test05', 'test09', 'test10', 'test10b', 'Calleg', 'GRW_Plaster', 'ZRW_WestIndian'] + # compare_cases = ['test10'] # control test cases for comparison + compare_case = "GLWACSO" start = datetime.now() - # test = RegressTest(compare_case, ids=['434'],activites=['GQUAL'],threads=1) - test = RegressTest('test10') + # test = RegressTest(compare_case, ids=['434'],activites=['GQUAL'],threads=1) + test = RegressTest("test10") results = test.run_test() test.generate_report(test.html_file, results) - print(f'runtime: {datetime.now() - start}') \ No newline at end of file + print(f"runtime: {datetime.now() - start}") diff --git a/tests/convert/regression_base.py b/tests/convert/regression_base.py index 88bc23fe..0eeb9ba9 100644 --- a/tests/convert/regression_base.py +++ b/tests/convert/regression_base.py @@ -1,37 +1,47 @@ -from datetime import time -import os import inspect +import os import webbrowser -from hsp2.hsp2tools.HBNOutput import HBNOutput -from hsp2.hsp2tools.HDF5 import HDF5 -import pandas as pd -import numpy as np - +from concurrent.futures import ThreadPoolExecutor, as_completed from typing import Dict, List, Tuple, Union -from concurrent.futures import ThreadPoolExecutor, as_completed, thread +import numpy as np +import pandas as pd + +from hsp2.hsp2tools.HBNOutput import HBNOutput +from hsp2.hsp2tools.HDF5 import HDF5 +OperationsTuple = Tuple[str, str, str, str, str] +ResultsTuple = Tuple[bool, bool, bool, float] -OperationsTuple = Tuple[str,str,str,str,str] -ResultsTuple = Tuple[bool,bool,bool,float] -class RegressTest(object): - def __init__(self, compare_case:str, operations:List[str]=[], activities:List[str]=[], - tcodes:List[str] = ['2'], ids:List[str] = [], threads:int=os.cpu_count() - 1) -> None: +class RegressTest: + def __init__( + self, + compare_case: str, + operations: List[str] = [], + activities: List[str] = [], + tcodes: List[str] = ["2"], + ids: List[str] = [], + threads: int = os.cpu_count() - 1, + ) -> None: self.compare_case = compare_case self.operations = operations self.activities = activities self.tcodes = tcodes self.ids = ids self.threads = threads - + self.quiet = False # allows users to set this later self._init_files() def _init_files(self): - current_directory = os.path.dirname(os.path.abspath(inspect.getframeinfo(inspect.currentframe()).filename)) + current_directory = os.path.dirname( + os.path.abspath(inspect.getframeinfo(inspect.currentframe()).filename) + ) source_root_path = os.path.split(os.path.split(current_directory)[0])[0] tests_root_dir = os.path.join(source_root_path, "tests") - self.html_file = os.path.join(tests_root_dir, f'HSPF_HSP2_{self.compare_case}.html') + self.html_file = os.path.join( + tests_root_dir, f"HSPF_HSP2_{self.compare_case}.html" + ) test_dirs = os.listdir(tests_root_dir) for test_dir in test_dirs: @@ -42,30 +52,34 @@ def _init_files(self): self._get_hbn_data(test_root) def _get_hbn_data(self, test_dir: str) -> None: - sub_dir = os.path.join(test_dir, 'HSPFresults') + sub_dir = os.path.join(test_dir, "HSPFresults") self.hspf_data_collection = {} for file in os.listdir(sub_dir): - if file.lower().endswith('.hbn'): + if file.lower().endswith(".hbn"): hspf_data = HBNOutput(os.path.join(test_dir, sub_dir, file)) hspf_data.read_data() for key in hspf_data.output_dictionary.keys(): self.hspf_data_collection[key] = hspf_data - def get_hspf_time_series(self, ops:OperationsTuple) -> Union[pd.Series,None]: + def get_hspf_time_series(self, ops: OperationsTuple) -> Union[pd.Series, None]: operation, activity, id, constituent, tcode = ops - key = f'{operation}_{activity}_{id}_{tcode}' + key = f"{operation}_{activity}_{id}_{tcode}" hspf_data = self.hspf_data_collection[key] - series = hspf_data.get_time_series(operation, int(id), constituent, activity, 'hourly') + series = hspf_data.get_time_series( + operation, int(id), constituent, activity, "hourly" + ) return series def _get_hdf5_data(self, test_dir: str) -> None: - sub_dir = os.path.join(test_dir, 'HSP2results') + sub_dir = os.path.join(test_dir, "HSP2results") for file in os.listdir(sub_dir): - if file.lower().endswith('.h5') or file.lower().endswith('.hdf'): + if file.lower().endswith(".h5") or file.lower().endswith(".hdf"): self.hsp2_data = HDF5(os.path.join(sub_dir, file)) break - def should_compare(self, operation:str, activity:str, id:str, tcode:str) -> bool: + def should_compare( + self, operation: str, activity: str, id: str, tcode: str + ) -> bool: if len(self.operations) > 0 and operation not in self.operations: return False if len(self.activities) > 0 and activity not in self.activities: @@ -76,41 +90,48 @@ def should_compare(self, operation:str, activity:str, id:str, tcode:str) -> bool return False return True - def generate_report(self, file:str, results: Dict[OperationsTuple,ResultsTuple]) -> None: + def generate_report( + self, file: str, results: Dict[OperationsTuple, ResultsTuple] + ) -> None: html = self.make_html_report(results) - self.write_html(file,html) - webbrowser.open_new_tab('file://' + file) + self.write_html(file, html) + webbrowser.open_new_tab("file://" + file) - def make_html_report(self, results_dict:Dict[OperationsTuple,ResultsTuple]) -> str: + def make_html_report( + self, results_dict: Dict[OperationsTuple, ResultsTuple] + ) -> str: """populates html table""" style_th = 'style="text-align:left"' style_header = 'style="border:1px solid; background-color:#EEEEEE"' - html = f'

CONVERSION TEST REPORT

\n' - html += f'\n' + html = "

CONVERSION TEST REPORT

\n" + html += '
\n' for key in self.hspf_data_collection.keys(): - operation, activity, opn_id, tcode = key.split('_') + operation, activity, opn_id, tcode = key.split("_") if not self.should_compare(operation, activity, opn_id, tcode): continue - html += f'\n' - html += f'\n' + html += f"\n" + html += f"\n" hspf_data = self.hspf_data_collection[key] for cons in hspf_data.output_dictionary[key]: - result = results_dict[(operation,activity,opn_id, cons, tcode)] + result = results_dict[(operation, activity, opn_id, cons, tcode)] no_data_hsp2, no_data_hspf, match, diff = result - html += self.make_html_comp_row(cons, no_data_hsp2, no_data_hspf, match, diff) + html += self.make_html_comp_row( + cons, no_data_hsp2, no_data_hspf, match, diff + ) - html += f'
{key}
ConstituentMax DiffMatchNote
{key}
ConstituentMax DiffMatchNote
\n' - html += f"\n" + html += "\n" + html += "\n" return html - def make_html_comp_row(self, con:str, no_data_hsp2:bool, - no_data_hspf:bool, match:bool, diff:float) -> str: + def make_html_comp_row( + self, con: str, no_data_hsp2: bool, no_data_hspf: bool, match: bool, diff: float + ) -> str: """populates each constituents rows""" - diffsOnly= False + diffsOnly = False eliminateNotIns = True - html = '' + html = "" if diffsOnly: if no_data_hsp2 or no_data_hspf: pass @@ -118,39 +139,41 @@ def make_html_comp_row(self, con:str, no_data_hsp2:bool, if match: pass else: - match_symbol = f'X' - html = f'-{con}{diff}{match_symbol}\n' + match_symbol = 'X' + html = f"-{con}{diff}{match_symbol}\n" else: if no_data_hsp2 or no_data_hspf: if not eliminateNotIns: - html = f'-{con}NANA' - html += f'{"Not in HSP2" if no_data_hsp2 else ""}
' - html += f'{"Not in HSPF" if no_data_hspf else ""}' - html += f'\n' + html = f"-{con}NANA" + html += f"{'Not in HSP2' if no_data_hsp2 else ''}
" + html += f"{'Not in HSPF' if no_data_hspf else ''}" + html += "\n" else: if match: - match_symbol = f'✓' + match_symbol = ( + '✓' + ) else: - match_symbol = f'X' - html = f'-{con}{diff}{match_symbol}\n' + match_symbol = 'X' + html = f"-{con}{diff}{match_symbol}\n" return html - def write_html(self, file:str, html:str) -> None: - with open(file, 'w') as f: + def write_html(self, file: str, html: str) -> None: + with open(file, "w") as f: f.write(html) - def run_test(self) -> Dict[OperationsTuple,ResultsTuple]: + def run_test(self) -> Dict[OperationsTuple, ResultsTuple]: futures = {} results_dict = {} with ThreadPoolExecutor(max_workers=self.threads) as executor: for key in self.hspf_data_collection.keys(): - (operation, activity, opn_id, tcode) = key.split('_') + (operation, activity, opn_id, tcode) = key.split("_") if not self.should_compare(operation, activity, opn_id, tcode): continue hspf_data = self.hspf_data_collection[key] for cons in hspf_data.output_dictionary[key]: - params = (operation,activity,opn_id,cons,tcode) + params = (operation, activity, opn_id, cons, tcode) futures[executor.submit(self.check_con, params)] = params for future in as_completed(futures): @@ -159,10 +182,9 @@ def run_test(self) -> Dict[OperationsTuple,ResultsTuple]: return results_dict - def check_con(self, params:OperationsTuple) -> ResultsTuple: + def check_con(self, params: OperationsTuple) -> ResultsTuple: """Performs comparision of single constituent""" operation, activity, id, constituent, tcode = params - print(f' {operation}_{id} {activity} {constituent}\n') ts_hsp2 = self.hsp2_data.get_time_series(operation, id, constituent, activity) ts_hspf = self.get_hspf_time_series(params) @@ -173,69 +195,136 @@ def check_con(self, params:OperationsTuple) -> ResultsTuple: if no_data_hsp2 or no_data_hspf: return (no_data_hsp2, no_data_hspf, False, 0) else: - #Special case, for some parameters (e.g PLANK.BENAL1) HSPF results look to be array. - #Working assumption is that only the first index of that array are the values of interest. + # Special case, for some parameters (e.g PLANK.BENAL1) HSPF results look to be array. + # Working assumption is that only the first index of that array are the values of interest. if len(ts_hspf.shape) > 1: - ts_hspf = ts_hspf.iloc[:,0] + ts_hspf = ts_hspf.iloc[:, 0] tolerance = 1e-2 # may want to change default to max(abs(ts_hsp2.values.min()), abs(ts_hsp2.values.max())) * 1e-3 # if heat related term, compute special tolerance - if constituent == 'IHEAT' or constituent == 'ROHEAT' or constituent.startswith('OHEAT') or \ - constituent == 'QSOLAR' or constituent == 'QLONGW' or constituent == 'QEVAP' or \ - constituent == 'QCON' or constituent == 'QPREC' or constituent == 'QBED': - tolerance = max(abs(ts_hsp2.values.min()), abs(ts_hsp2.values.max())) * 1e-4 - elif constituent == 'QTOTAL' or constituent == 'HTEXCH' : - tolerance = max(abs(ts_hsp2.values.min()), abs(ts_hsp2.values.max())) * 1e-3 - - ts_hsp2, ts_hspf = self.validate_time_series(ts_hsp2, ts_hspf, operation, activity, id, constituent) + if ( + constituent == "IHEAT" + or constituent == "ROHEAT" + or constituent.startswith("OHEAT") + or constituent == "QSOLAR" + or constituent == "QLONGW" + or constituent == "QEVAP" + or constituent == "QCON" + or constituent == "QPREC" + or constituent == "QBED" + ): + tolerance = ( + max(abs(ts_hsp2.values.min()), abs(ts_hsp2.values.max())) * 1e-4 + ) + elif constituent == "QTOTAL" or constituent == "HTEXCH": + tolerance = ( + max(abs(ts_hsp2.values.min()), abs(ts_hsp2.values.max())) * 1e-3 + ) + + ts_hsp2, ts_hspf = self.validate_time_series( + ts_hsp2, ts_hspf, operation, activity, id, constituent + ) match, diff = self.compare_time_series(ts_hsp2, ts_hspf, tolerance) + if not match: + print(operation, activity, id, constituent, tcode) + print(match, diff) + print(ts_hsp2.values) + print(ts_hspf.values) return (no_data_hsp2, no_data_hspf, match, diff) - def fill_nan_and_null(self, timeseries:pd.Series, replacement_value:float = 0.0) -> pd.Series: + def fill_nan_and_null( + self, timeseries: pd.Series, replacement_value: float = 0.0 + ) -> pd.Series: """Replaces any nan or HSPF nulls -1.0e30 with provided replacement_value""" timeseries = timeseries.fillna(replacement_value) timeseries = timeseries.where(timeseries > -1.0e25, replacement_value) return timeseries - def validate_time_series(self, ts_hsp2:pd.Series, ts_hspf:pd.Series, operation:str, - activity:str, id:str, cons:str) -> Tuple[pd.Series, pd.Series]: - """ validates a corrects time series to avoid false differences """ + def validate_time_series( + self, + ts_hsp2: pd.Series, + ts_hspf: pd.Series, + operation: str, + activity: str, + id: str, + cons: str, + ) -> Tuple[pd.Series, pd.Series]: + """validates a corrects time series to avoid false differences""" # In some test cases it looked like HSP2 was executing for a single extra time step # Trim h5 (HSP2) results to be same length as hbn (HSPF) # This is a bandaid to get testing working. Long term should identify why HSP2 runs for additional time step. if len(ts_hsp2) > len(ts_hspf): - ts_hsp2 = ts_hsp2[0:len(ts_hspf)] + ts_hsp2 = ts_hsp2[0 : len(ts_hspf)] ts_hsp2 = self.fill_nan_and_null(ts_hsp2) ts_hspf = self.fill_nan_and_null(ts_hspf) ### special cases # if tiny suro in one and no suro in the other, don't trigger on suro-dependent numbers - if activity == 'PWTGAS' and cons in ['SOTMP', 'SODOX', 'SOCO2']: - ts_suro_hsp2 = self.hsp2_data.get_time_series(operation, id, 'SURO', 'PWATER') + if activity == "PWTGAS" and cons in ["SOTMP", "SODOX", "SOCO2"]: + ts_suro_hsp2 = self.hsp2_data.get_time_series( + operation, id, "SURO", "PWATER" + ) ts_suro_hsp2 = self.fill_nan_and_null(ts_suro_hsp2) - ts_suro_hspf = self.get_hspf_time_series((operation, 'PWATER', id, 'SURO', 2)) + ts_suro_hspf = self.get_hspf_time_series( + (operation, "PWATER", id, "SURO", 2) + ) ts_suro_hspf = self.fill_nan_and_null(ts_suro_hspf) - idx_zero_suro_hsp2 = ts_suro_hsp2 == 0 idx_low_suro_hsp2 = ts_suro_hsp2 < 1.0e-8 idx_zero_suro_hspf = ts_suro_hspf == 0 idx_low_suro_hspf = ts_suro_hspf < 1.0e-8 - ts_hsp2.loc[idx_zero_suro_hsp2 & idx_low_suro_hspf] = ts_hspf.loc[idx_zero_suro_hsp2 & idx_low_suro_hspf] = 0 - ts_hspf.loc[idx_zero_suro_hspf & idx_low_suro_hsp2] = ts_hsp2.loc[idx_zero_suro_hspf & idx_low_suro_hsp2] = 0 + ts_hsp2.loc[idx_zero_suro_hsp2 & idx_low_suro_hspf] = ts_hspf.loc[ + idx_zero_suro_hsp2 & idx_low_suro_hspf + ] = 0 + ts_hspf.loc[idx_zero_suro_hspf & idx_low_suro_hsp2] = ts_hsp2.loc[ + idx_zero_suro_hspf & idx_low_suro_hsp2 + ] = 0 # if volume in reach is going to zero, small concentration differences are not signficant - if (activity == 'SEDTRN' and cons in ['SSEDCLAY', 'SSEDTOT']) or \ - (activity == 'OXRX' and cons in ['BODCONC', 'DOXCONC']) or \ - (activity == 'NUTRX' and cons in ['TAMCONCDIS', 'NH4CONCDIS', 'NH3CONCDIS', 'NO3CONCDIS', 'NO2CONCDIS', 'PO4CONCDIS', - 'PO4CONCSUSPSAND', 'PO4CONCSUSPSILT', 'PO4CONCSUSPCLAY', 'NH4CONCSUSPSAND', 'NH4CONCSUSPSILT', 'NH4CONCSUSPCLAY']) or \ - (activity == 'PLANK' and cons in ['PHYTO', 'PHYCLA', 'ZOO', 'CTOTORGCONC', 'POTBOD', 'NTOTCONC', 'PTOTCONC', 'NTOTORGCONC', 'PTOTORGCONC']) or \ - (activity == 'PHCARB' and cons in ['TICCONC', 'CO2CONC']): + if ( + (activity == "SEDTRN" and cons in ["SSEDCLAY", "SSEDTOT"]) + or (activity == "OXRX" and cons in ["BODCONC", "DOXCONC"]) + or ( + activity == "NUTRX" + and cons + in [ + "TAMCONCDIS", + "NH4CONCDIS", + "NH3CONCDIS", + "NO3CONCDIS", + "NO2CONCDIS", + "PO4CONCDIS", + "PO4CONCSUSPSAND", + "PO4CONCSUSPSILT", + "PO4CONCSUSPCLAY", + "NH4CONCSUSPSAND", + "NH4CONCSUSPSILT", + "NH4CONCSUSPCLAY", + ] + ) + or ( + activity == "PLANK" + and cons + in [ + "PHYTO", + "PHYCLA", + "ZOO", + "CTOTORGCONC", + "POTBOD", + "NTOTCONC", + "PTOTCONC", + "NTOTORGCONC", + "PTOTORGCONC", + ] + ) + or (activity == "PHCARB" and cons in ["TICCONC", "CO2CONC"]) + ): ts_vol_hsp2 = self.hsp2_data.get_time_series(operation, id, "VOL", "HYDR") ts_vol_hsp2 = self.fill_nan_and_null(ts_vol_hsp2) @@ -246,8 +335,9 @@ def validate_time_series(self, ts_hsp2:pd.Series, ts_hspf:pd.Series, operation:s return ts_hsp2, ts_hspf - def compare_time_series(self, ts_hsp2:pd.Series, ts_hspf:pd.Series, tol:float) -> Tuple[bool, float]: - + def compare_time_series( + self, ts_hsp2: pd.Series, ts_hspf: pd.Series, tol: float + ) -> Tuple[bool, float]: max_diff1 = (ts_hspf.values - ts_hsp2.values).max() max_diff2 = (ts_hsp2.values - ts_hspf.values).max() max_diff = max(max_diff1, max_diff2) diff --git a/tests/ipwater/data/Flow_Test.plt b/tests/ipwater/data/Flow_Test.plt index 39c3e991..6b56df7a 100644 --- a/tests/ipwater/data/Flow_Test.plt +++ b/tests/ipwater/data/Flow_Test.plt @@ -2,10 +2,10 @@ Av Time interval: 60 mins Last month in printout year: 9 Av No. of curves plotted: Point-valued: 0 Mean-valued: 7 Total 7 Av Label flag: 0 Pivl: 1 Idelt: 60 - Av Plot title: Average Output flow (cfs) - Av Y-axis label: + Av Plot title: Average Output flow (cfs) + Av Y-axis label: Av Scale info: Ymin: 0.0000 Threshold:-0.10000E+33 - Av Ymax: 100.00 + Av Ymax: 100.00 Av Time: 30.000 intervals/inch Av Data for each curve (Point-valued first, then mean-valued): Av Label LINTYP INTEQ COLCOD TRAN TRANCOD @@ -24,13 +24,13 @@ Av Date/time Values Av Av 2017 12 31 24 0-1.0000000E+30-1.0000000E+30-1.0000000E+30-1.0000000E+30-1.0000000E+30-1.0000000E+30-1.0000000E+30 - Av 2018 1 1 1 0 500.0000 0.000000 1.4692564E-03 2.4298239E-03 6.0976162E-03 0.000000 0.000000 - Av 2018 1 1 2 0 0.2766384 0.000000 1.4475825E-03 2.4300206E-03 1.9394598E-03 0.000000 0.000000 - Av 2018 1 1 3 0 0.4479387 0.000000 1.4262284E-03 2.4301915E-03 8.0480397E-04 0.000000 0.000000 - Av 2018 1 1 4 0 0.3750470 0.000000 1.4051893E-03 2.4303370E-03 3.9847003E-04 0.000000 0.000000 - Av 2018 1 1 5 0 0.3936203 0.000000 1.3844606E-03 2.4304576E-03 2.2315262E-04 0.000000 0.000000 - Av 2018 1 1 6 0 0.3826022 0.000000 1.3640376E-03 2.4305538E-03 1.3668223E-04 0.000000 0.000000 - Av 2018 1 1 7 0 0.3827823 0.000000 1.3439159E-03 2.4306260E-03 8.9559166E-05 0.000000 0.000000 + Av 2018 1 1 1 0 500.0000 0.000000 1.4692564E-03 2.4298239E-03 6.0976162E-03 0.000000 0.000000 + Av 2018 1 1 2 0 0.2766384 0.000000 1.4475825E-03 2.4300206E-03 1.9394598E-03 0.000000 0.000000 + Av 2018 1 1 3 0 0.4479387 0.000000 1.4262284E-03 2.4301915E-03 8.0480397E-04 0.000000 0.000000 + Av 2018 1 1 4 0 0.3750470 0.000000 1.4051893E-03 2.4303370E-03 3.9847003E-04 0.000000 0.000000 + Av 2018 1 1 5 0 0.3936203 0.000000 1.3844606E-03 2.4304576E-03 2.2315262E-04 0.000000 0.000000 + Av 2018 1 1 6 0 0.3826022 0.000000 1.3640376E-03 2.4305538E-03 1.3668223E-04 0.000000 0.000000 + Av 2018 1 1 7 0 0.3827823 0.000000 1.3439159E-03 2.4306260E-03 8.9559166E-05 0.000000 0.000000 Av 2018 1 1 8 0 0.3732951 0.000000 1.3240911E-03 2.3400784E-03 6.1830673E-05 0.000000 4.1179982E-04 Av 2018 1 1 9 0 0.3454389 0.000000 1.3045588E-03 2.0195283E-03 4.4495540E-05 0.000000 1.8689601E-03 Av 2018 1 1 10 0 0.3114849 0.000000 1.2853144E-03 1.7442536E-03 3.3115422E-05 0.000000 3.1202205E-03 @@ -40,21 +40,21 @@ Av 2018 1 1 14 0 0.2980402 0.000000 1.2111345E-03 1.7440433E-03 0.000000 0.000000 3.1202205E-03 Av 2018 1 1 15 0 0.3148406 0.000000 1.1932683E-03 2.0192151E-03 0.000000 0.000000 1.8689601E-03 Av 2018 1 1 16 0 0.3473737 0.000000 1.1756658E-03 2.3396639E-03 0.000000 0.000000 4.1179982E-04 - Av 2018 1 1 17 0 0.3618242 0.000000 1.1583229E-03 2.4301133E-03 0.000000 0.000000 0.000000 - Av 2018 1 1 18 0 0.3606456 0.000000 1.1412358E-03 2.4299470E-03 0.000000 0.000000 0.000000 - Av 2018 1 1 19 0 0.3587267 0.000000 1.1244009E-03 2.4297610E-03 0.000000 0.000000 0.000000 - Av 2018 1 1 20 0 0.3570966 0.000000 1.1078141E-03 2.4295559E-03 0.000000 0.000000 0.000000 - Av 2018 1 1 21 0 0.3553969 0.000000 1.0914721E-03 2.4293319E-03 0.000000 0.000000 0.000000 - Av 2018 1 1 22 0 0.3537519 0.000000 1.0753712E-03 2.4290895E-03 0.000000 0.000000 0.000000 - Av 2018 1 1 23 0 0.3521179 0.000000 1.0595077E-03 2.4288287E-03 0.000000 0.000000 0.000000 - Av 2018 1 1 24 0 0.3505096 0.000000 1.0438784E-03 2.4285500E-03 0.000000 0.000000 0.000000 - Av 2018 1 2 1 0 0.3456632 0.000000 1.0284794E-03 2.3802982E-03 0.000000 0.000000 0.000000 - Av 2018 1 2 2 0 0.3419758 0.000000 1.0133078E-03 2.3800477E-03 0.000000 0.000000 0.000000 - Av 2018 1 2 3 0 0.3411764 0.000000 9.9835987E-04 2.3797806E-03 0.000000 0.000000 0.000000 - Av 2018 1 2 4 0 0.3394006 0.000000 9.8363252E-04 2.3794968E-03 0.000000 0.000000 0.000000 - Av 2018 1 2 5 0 0.3379918 0.000000 9.6912234E-04 2.3791962E-03 0.000000 0.000000 0.000000 - Av 2018 1 2 6 0 0.3364826 0.000000 9.5482630E-04 2.3788798E-03 0.000000 0.000000 0.000000 - Av 2018 1 2 7 0 0.3350349 0.000000 9.4074110E-04 2.3785473E-03 0.000000 0.000000 0.000000 + Av 2018 1 1 17 0 0.3618242 0.000000 1.1583229E-03 2.4301133E-03 0.000000 0.000000 0.000000 + Av 2018 1 1 18 0 0.3606456 0.000000 1.1412358E-03 2.4299470E-03 0.000000 0.000000 0.000000 + Av 2018 1 1 19 0 0.3587267 0.000000 1.1244009E-03 2.4297610E-03 0.000000 0.000000 0.000000 + Av 2018 1 1 20 0 0.3570966 0.000000 1.1078141E-03 2.4295559E-03 0.000000 0.000000 0.000000 + Av 2018 1 1 21 0 0.3553969 0.000000 1.0914721E-03 2.4293319E-03 0.000000 0.000000 0.000000 + Av 2018 1 1 22 0 0.3537519 0.000000 1.0753712E-03 2.4290895E-03 0.000000 0.000000 0.000000 + Av 2018 1 1 23 0 0.3521179 0.000000 1.0595077E-03 2.4288287E-03 0.000000 0.000000 0.000000 + Av 2018 1 1 24 0 0.3505096 0.000000 1.0438784E-03 2.4285500E-03 0.000000 0.000000 0.000000 + Av 2018 1 2 1 0 0.3456632 0.000000 1.0284794E-03 2.3802982E-03 0.000000 0.000000 0.000000 + Av 2018 1 2 2 0 0.3419758 0.000000 1.0133078E-03 2.3800477E-03 0.000000 0.000000 0.000000 + Av 2018 1 2 3 0 0.3411764 0.000000 9.9835987E-04 2.3797806E-03 0.000000 0.000000 0.000000 + Av 2018 1 2 4 0 0.3394006 0.000000 9.8363252E-04 2.3794968E-03 0.000000 0.000000 0.000000 + Av 2018 1 2 5 0 0.3379918 0.000000 9.6912234E-04 2.3791962E-03 0.000000 0.000000 0.000000 + Av 2018 1 2 6 0 0.3364826 0.000000 9.5482630E-04 2.3788798E-03 0.000000 0.000000 0.000000 + Av 2018 1 2 7 0 0.3350349 0.000000 9.4074110E-04 2.3785473E-03 0.000000 0.000000 0.000000 Av 2018 1 2 8 0 0.3269997 0.000000 9.2686369E-04 2.2819724E-03 0.000000 0.000000 4.3739582E-04 Av 2018 1 2 9 0 0.2985543 0.000000 9.1319100E-04 1.9497968E-03 0.000000 0.000000 1.9456330E-03 Av 2018 1 2 10 0 0.2644181 0.000000 8.9972001E-04 1.6657196E-03 0.000000 0.000000 3.2351722E-03 @@ -64,21 +64,21 @@ Av 2018 1 2 14 0 0.2531557 0.000000 8.4779406E-04 1.6640581E-03 0.000000 0.000000 3.2351722E-03 Av 2018 1 2 15 0 0.2711424 0.000000 8.3528779E-04 1.9473055E-03 0.000000 0.000000 1.9456330E-03 Av 2018 1 2 16 0 0.3052593 0.000000 8.2296599E-04 2.2786530E-03 0.000000 0.000000 4.3739582E-04 - Av 2018 1 2 17 0 0.3209632 0.000000 8.1082596E-04 2.3744013E-03 0.000000 0.000000 0.000000 - Av 2018 1 2 18 0 0.3203880 0.000000 7.9886505E-04 2.3739093E-03 0.000000 0.000000 0.000000 - Av 2018 1 2 19 0 0.3189069 0.000000 7.8708050E-04 2.3734041E-03 0.000000 0.000000 0.000000 - Av 2018 1 2 20 0 0.3177629 0.000000 7.7546982E-04 2.3728861E-03 0.000000 0.000000 0.000000 - Av 2018 1 2 21 0 0.3165233 0.000000 7.6403044E-04 2.3723550E-03 0.000000 0.000000 0.000000 - Av 2018 1 2 22 0 0.3153382 0.000000 7.5275975E-04 2.3718113E-03 0.000000 0.000000 0.000000 - Av 2018 1 2 23 0 0.3141553 0.000000 7.4165541E-04 2.3712551E-03 0.000000 0.000000 0.000000 - Av 2018 1 2 24 0 0.3129924 0.000000 7.3071476E-04 2.3706867E-03 0.000000 0.000000 0.000000 - Av 2018 1 3 1 0 0.3086827 0.000000 7.1993558E-04 2.3235946E-03 0.000000 0.000000 0.000000 - Av 2018 1 3 2 0 0.3054917 0.000000 7.0931541E-04 2.3230661E-03 0.000000 0.000000 0.000000 - Av 2018 1 3 3 0 0.3050961 0.000000 6.9885195E-04 2.3225257E-03 0.000000 0.000000 0.000000 - Av 2018 1 3 4 0 0.3037481 0.000000 6.8854273E-04 2.3219741E-03 0.000000 0.000000 0.000000 - Av 2018 1 3 5 0 0.3027505 0.000000 6.7838567E-04 2.3214112E-03 0.000000 0.000000 0.000000 - Av 2018 1 3 6 0 0.3016500 0.000000 6.6837837E-04 2.3208368E-03 0.000000 0.000000 0.000000 - Av 2018 1 3 7 0 0.3006040 0.000000 6.5851881E-04 2.3202514E-03 0.000000 0.000000 0.000000 + Av 2018 1 2 17 0 0.3209632 0.000000 8.1082596E-04 2.3744013E-03 0.000000 0.000000 0.000000 + Av 2018 1 2 18 0 0.3203880 0.000000 7.9886505E-04 2.3739093E-03 0.000000 0.000000 0.000000 + Av 2018 1 2 19 0 0.3189069 0.000000 7.8708050E-04 2.3734041E-03 0.000000 0.000000 0.000000 + Av 2018 1 2 20 0 0.3177629 0.000000 7.7546982E-04 2.3728861E-03 0.000000 0.000000 0.000000 + Av 2018 1 2 21 0 0.3165233 0.000000 7.6403044E-04 2.3723550E-03 0.000000 0.000000 0.000000 + Av 2018 1 2 22 0 0.3153382 0.000000 7.5275975E-04 2.3718113E-03 0.000000 0.000000 0.000000 + Av 2018 1 2 23 0 0.3141553 0.000000 7.4165541E-04 2.3712551E-03 0.000000 0.000000 0.000000 + Av 2018 1 2 24 0 0.3129924 0.000000 7.3071476E-04 2.3706867E-03 0.000000 0.000000 0.000000 + Av 2018 1 3 1 0 0.3086827 0.000000 7.1993558E-04 2.3235946E-03 0.000000 0.000000 0.000000 + Av 2018 1 3 2 0 0.3054917 0.000000 7.0931541E-04 2.3230661E-03 0.000000 0.000000 0.000000 + Av 2018 1 3 3 0 0.3050961 0.000000 6.9885195E-04 2.3225257E-03 0.000000 0.000000 0.000000 + Av 2018 1 3 4 0 0.3037481 0.000000 6.8854273E-04 2.3219741E-03 0.000000 0.000000 0.000000 + Av 2018 1 3 5 0 0.3027505 0.000000 6.7838567E-04 2.3214112E-03 0.000000 0.000000 0.000000 + Av 2018 1 3 6 0 0.3016500 0.000000 6.6837837E-04 2.3208368E-03 0.000000 0.000000 0.000000 + Av 2018 1 3 7 0 0.3006040 0.000000 6.5851881E-04 2.3202514E-03 0.000000 0.000000 0.000000 Av 2018 1 3 8 0 0.2921284 0.000000 6.4880459E-04 2.2111682E-03 0.000000 0.000000 4.9312349E-04 Av 2018 1 3 9 0 0.2613306 0.000000 6.3923374E-04 1.8465028E-03 0.000000 0.000000 2.1479344E-03 Av 2018 1 3 10 0 0.2245641 0.000000 6.2980404E-04 1.5360708E-03 0.000000 0.000000 3.5561835E-03 @@ -88,21 +88,21 @@ Av 2018 1 3 14 0 0.2142617 0.000000 5.9345580E-04 1.5334985E-03 0.000000 0.000000 3.5561835E-03 Av 2018 1 3 15 0 0.2343696 0.000000 5.8470137E-04 1.8426389E-03 0.000000 0.000000 2.1479344E-03 Av 2018 1 3 16 0 0.2721907 0.000000 5.7607610E-04 2.2060017E-03 0.000000 0.000000 4.9312349E-04 - 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Av 2018 1 5 4 0 0.2680774 8.1124490E-05 3.5682763E-04 2.2418411E-03 0.000000 1.9999960E-02 0.000000 - Av 2018 1 5 5 0 0.3625344 8.1287610E-05 3.5877695E-04 2.2602980E-03 1.2620229E-02 1.9999960E-02 0.000000 - Av 2018 1 5 6 0 0.3503632 0.000000 3.5708680E-04 2.2691365E-03 3.8989303E-03 0.000000 0.000000 - Av 2018 1 5 7 0 0.2705059 0.000000 3.5181921E-04 2.2681353E-03 1.3822505E-03 0.000000 0.000000 + Av 2018 1 4 17 0 0.2703497 0.000000 3.9730466E-04 2.2497787E-03 0.000000 2.9999940E-02 0.000000 + Av 2018 1 4 18 0 0.2685758 0.000000 3.9144381E-04 2.2488397E-03 0.000000 0.000000 0.000000 + Av 2018 1 4 19 0 0.2649415 0.000000 3.8566938E-04 2.2478951E-03 0.000000 0.000000 0.000000 + Av 2018 1 4 20 0 0.2652977 0.000000 3.7998016E-04 2.2469454E-03 0.000000 0.000000 0.000000 + Av 2018 1 4 21 0 0.2642770 0.000000 3.7437485E-04 2.2459906E-03 0.000000 0.000000 0.000000 + Av 2018 1 4 22 0 0.2637457 0.000000 3.6885223E-04 2.2450301E-03 0.000000 0.000000 0.000000 + Av 2018 1 4 23 0 0.2652602 0.000000 3.6341109E-04 2.2440648E-03 0.000000 1.9999960E-02 0.000000 + Av 2018 1 4 24 0 0.2638682 0.000000 3.5805019E-04 2.2430944E-03 0.000000 0.000000 0.000000 + Av 2018 1 5 1 0 0.2616372 0.000000 3.5276840E-04 2.1987760E-03 0.000000 2.9999940E-02 0.000000 + Av 2018 1 5 2 0 0.2742999 1.6192393E-04 3.5476207E-04 2.2107791E-03 0.000000 2.9999940E-02 0.000000 + Av 2018 1 5 3 0 0.2714513 2.0294829E-05 3.5759364E-04 2.2280579E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 1 5 4 0 0.2680774 8.1124490E-05 3.5682763E-04 2.2418411E-03 0.000000 1.9999960E-02 0.000000 + Av 2018 1 5 5 0 0.3625344 8.1287610E-05 3.5877695E-04 2.2602980E-03 1.2620229E-02 1.9999960E-02 0.000000 + Av 2018 1 5 6 0 0.3503632 0.000000 3.5708680E-04 2.2691365E-03 3.8989303E-03 0.000000 0.000000 + Av 2018 1 5 7 0 0.2705059 0.000000 3.5181921E-04 2.2681353E-03 1.3822505E-03 0.000000 0.000000 Av 2018 1 5 8 0 0.7216234 1.0122319E-04 4.0450250E-04 2.1650153E-03 6.4418711E-02 7.9999842E-02 5.8421458E-04 Av 2018 1 5 9 0 0.8579881 2.8689532E-04 4.7192292E-04 1.8018335E-03 4.3853831E-02 3.9999921E-02 2.4346784E-03 Av 2018 1 5 10 0 0.3697414 9.6791331E-10 4.8068378E-04 1.4762494E-03 8.1133200E-03 0.000000 3.9930348E-03 @@ -136,21 +136,21 @@ Av 2018 1 5 14 0 0.2138880 0.000000 4.6538617E-04 1.5039076E-03 1.0311512E-03 0.000000 3.9930348E-03 Av 2018 1 5 15 0 0.2256642 0.000000 4.5852101E-04 1.8457351E-03 4.8697469E-04 0.000000 2.4346784E-03 Av 2018 1 5 16 0 0.2665905 0.000000 4.5175711E-04 2.2518202E-03 2.6372896E-04 0.000000 5.8421458E-04 - Av 2018 1 5 17 0 0.2856997 0.000000 4.4509297E-04 2.3793241E-03 1.5759299E-04 0.000000 0.000000 - Av 2018 1 5 18 0 0.2868600 0.000000 4.3852717E-04 2.3782947E-03 1.0133593E-04 9.9999802E-03 0.000000 - Av 2018 1 5 19 0 0.2848283 0.000000 4.3205821E-04 2.3772595E-03 6.8938949E-05 0.000000 0.000000 - Av 2018 1 5 20 0 0.2830145 0.000000 4.2568470E-04 2.3762183E-03 4.9029954E-05 0.000000 0.000000 - Av 2018 1 5 21 0 0.3012888 1.4630097E-05 4.2006010E-04 2.3795057E-03 2.4487113E-03 9.9999802E-03 0.000000 - Av 2018 1 5 22 0 0.4079811 8.4822044E-05 4.1831352E-04 2.3927528E-03 1.5389800E-02 1.9999960E-02 0.000000 - Av 2018 1 5 23 0 0.7260745 4.1146232E-05 4.5019304E-04 2.4251393E-03 5.2534629E-02 5.9999879E-02 0.000000 - Av 2018 1 5 24 0 0.6336814 2.5103323E-05 4.7877984E-04 2.4538850E-03 1.7499704E-02 9.9999802E-03 0.000000 - Av 2018 1 6 1 0 0.3261445 0.000000 4.7283815E-04 2.4098936E-03 4.2170519E-03 0.000000 0.000000 - Av 2018 1 6 2 0 0.3164066 0.000000 4.6586301E-04 2.4088705E-03 1.4674879E-03 0.000000 0.000000 - Av 2018 1 6 3 0 0.2944473 0.000000 4.5899081E-04 2.4078414E-03 6.4574182E-04 0.000000 0.000000 - Av 2018 1 6 4 0 0.2933064 0.000000 4.5221997E-04 2.4068060E-03 3.3286875E-04 0.000000 0.000000 - Av 2018 1 6 5 0 0.2895651 0.000000 4.4554900E-04 2.4057645E-03 1.9188963E-04 0.000000 0.000000 - Av 2018 1 6 6 0 0.2883785 0.000000 4.3897648E-04 2.4047166E-03 1.2009546E-04 0.000000 0.000000 - Av 2018 1 6 7 0 0.2870016 0.000000 4.3250088E-04 2.4036630E-03 8.0005055E-05 0.000000 0.000000 + Av 2018 1 5 17 0 0.2856997 0.000000 4.4509297E-04 2.3793241E-03 1.5759299E-04 0.000000 0.000000 + Av 2018 1 5 18 0 0.2868600 0.000000 4.3852717E-04 2.3782947E-03 1.0133593E-04 9.9999802E-03 0.000000 + Av 2018 1 5 19 0 0.2848283 0.000000 4.3205821E-04 2.3772595E-03 6.8938949E-05 0.000000 0.000000 + Av 2018 1 5 20 0 0.2830145 0.000000 4.2568470E-04 2.3762183E-03 4.9029954E-05 0.000000 0.000000 + Av 2018 1 5 21 0 0.3012888 1.4630097E-05 4.2006010E-04 2.3795057E-03 2.4487113E-03 9.9999802E-03 0.000000 + Av 2018 1 5 22 0 0.4079811 8.4822044E-05 4.1831352E-04 2.3927528E-03 1.5389800E-02 1.9999960E-02 0.000000 + Av 2018 1 5 23 0 0.7260745 4.1146232E-05 4.5019304E-04 2.4251393E-03 5.2534629E-02 5.9999879E-02 0.000000 + Av 2018 1 5 24 0 0.6336814 2.5103323E-05 4.7877984E-04 2.4538850E-03 1.7499704E-02 9.9999802E-03 0.000000 + Av 2018 1 6 1 0 0.3261445 0.000000 4.7283815E-04 2.4098936E-03 4.2170519E-03 0.000000 0.000000 + Av 2018 1 6 2 0 0.3164066 0.000000 4.6586301E-04 2.4088705E-03 1.4674879E-03 0.000000 0.000000 + Av 2018 1 6 3 0 0.2944473 0.000000 4.5899081E-04 2.4078414E-03 6.4574182E-04 0.000000 0.000000 + Av 2018 1 6 4 0 0.2933064 0.000000 4.5221997E-04 2.4068060E-03 3.3286875E-04 0.000000 0.000000 + Av 2018 1 6 5 0 0.2895651 0.000000 4.4554900E-04 2.4057645E-03 1.9188963E-04 0.000000 0.000000 + Av 2018 1 6 6 0 0.2883785 0.000000 4.3897648E-04 2.4047166E-03 1.2009546E-04 0.000000 0.000000 + Av 2018 1 6 7 0 0.2870016 0.000000 4.3250088E-04 2.4036630E-03 8.0005055E-05 0.000000 0.000000 Av 2018 1 6 8 0 0.2777464 0.000000 4.2612079E-04 2.2816535E-03 5.5960158E-05 0.000000 5.4977124E-04 Av 2018 1 6 9 0 0.2459727 0.000000 4.1983486E-04 1.9089247E-03 4.0696301E-05 0.000000 2.2391505E-03 Av 2018 1 6 10 0 0.2102572 0.000000 4.1364162E-04 1.5966648E-03 1.9329824E-04 0.000000 3.6536439E-03 @@ -160,21 +160,21 @@ Av 2018 1 6 14 0 0.2031353 0.000000 3.9016848E-04 1.5973509E-03 2.3790896E-04 0.000000 3.6536439E-03 Av 2018 1 6 15 0 0.2221521 0.000000 3.8441291E-04 1.9074345E-03 1.4436220E-04 0.000000 2.2391505E-03 Av 2018 1 6 16 0 0.2603278 0.000000 3.7874220E-04 2.2779873E-03 9.3917282E-05 0.000000 5.4977124E-04 - Av 2018 1 6 17 0 0.2792812 0.000000 3.7315517E-04 2.3978211E-03 6.4476859E-05 0.000000 0.000000 - Av 2018 1 6 18 0 0.2797371 0.000000 3.6765053E-04 2.3967000E-03 4.6191650E-05 0.000000 0.000000 - Av 2018 1 6 19 0 0.2784780 0.000000 3.6222712E-04 2.3955735E-03 3.4251643E-05 0.000000 0.000000 - Av 2018 1 6 20 0 0.2789014 0.000000 3.5688368E-04 2.3944422E-03 1.7430617E-04 0.000000 0.000000 - Av 2018 1 6 21 0 0.2776466 0.000000 3.5161912E-04 2.3933060E-03 0.000000 0.000000 0.000000 - Av 2018 1 6 22 0 0.2760337 0.000000 3.4643218E-04 2.3921647E-03 0.000000 0.000000 0.000000 - Av 2018 1 6 23 0 0.2757395 0.000000 3.4132178E-04 2.3910184E-03 0.000000 0.000000 0.000000 - Av 2018 1 6 24 0 0.2749963 0.000000 3.3628673E-04 2.3898673E-03 0.000000 0.000000 0.000000 - Av 2018 1 7 1 0 0.2712280 0.000000 3.3132595E-04 2.3417480E-03 0.000000 0.000000 0.000000 - Av 2018 1 7 2 0 0.2685256 0.000000 3.2643840E-04 2.3406576E-03 0.000000 0.000000 0.000000 - Av 2018 1 7 3 0 0.2686575 0.000000 3.2162291E-04 2.3395626E-03 0.000000 0.000000 0.000000 - Av 2018 1 7 4 0 0.2678130 0.000000 3.1687849E-04 2.3384630E-03 0.000000 0.000000 0.000000 - Av 2018 1 7 5 0 0.2673169 0.000000 3.1220401E-04 2.3373587E-03 0.000000 0.000000 0.000000 - Av 2018 1 7 6 0 0.2667086 0.000000 3.0759853E-04 2.3362502E-03 0.000000 0.000000 0.000000 - Av 2018 1 7 7 0 0.2661479 0.000000 3.0306095E-04 2.3351368E-03 0.000000 0.000000 0.000000 + Av 2018 1 6 17 0 0.2792812 0.000000 3.7315517E-04 2.3978211E-03 6.4476859E-05 0.000000 0.000000 + Av 2018 1 6 18 0 0.2797371 0.000000 3.6765053E-04 2.3967000E-03 4.6191650E-05 0.000000 0.000000 + Av 2018 1 6 19 0 0.2784780 0.000000 3.6222712E-04 2.3955735E-03 3.4251643E-05 0.000000 0.000000 + Av 2018 1 6 20 0 0.2789014 0.000000 3.5688368E-04 2.3944422E-03 1.7430617E-04 0.000000 0.000000 + Av 2018 1 6 21 0 0.2776466 0.000000 3.5161912E-04 2.3933060E-03 0.000000 0.000000 0.000000 + Av 2018 1 6 22 0 0.2760337 0.000000 3.4643218E-04 2.3921647E-03 0.000000 0.000000 0.000000 + Av 2018 1 6 23 0 0.2757395 0.000000 3.4132178E-04 2.3910184E-03 0.000000 0.000000 0.000000 + Av 2018 1 6 24 0 0.2749963 0.000000 3.3628673E-04 2.3898673E-03 0.000000 0.000000 0.000000 + Av 2018 1 7 1 0 0.2712280 0.000000 3.3132595E-04 2.3417480E-03 0.000000 0.000000 0.000000 + Av 2018 1 7 2 0 0.2685256 0.000000 3.2643840E-04 2.3406576E-03 0.000000 0.000000 0.000000 + Av 2018 1 7 3 0 0.2686575 0.000000 3.2162291E-04 2.3395626E-03 0.000000 0.000000 0.000000 + Av 2018 1 7 4 0 0.2678130 0.000000 3.1687849E-04 2.3384630E-03 0.000000 0.000000 0.000000 + Av 2018 1 7 5 0 0.2673169 0.000000 3.1220401E-04 2.3373587E-03 0.000000 0.000000 0.000000 + Av 2018 1 7 6 0 0.2667086 0.000000 3.0759853E-04 2.3362502E-03 0.000000 0.000000 0.000000 + Av 2018 1 7 7 0 0.2661479 0.000000 3.0306095E-04 2.3351368E-03 0.000000 0.000000 0.000000 Av 2018 1 7 8 0 0.2574595 0.000000 2.9859031E-04 2.2153938E-03 0.000000 0.000000 5.3920748E-04 Av 2018 1 7 9 0 0.2274263 0.000000 2.9418565E-04 1.8609082E-03 0.000000 0.000000 2.1454052E-03 Av 2018 1 7 10 0 0.1951840 3.2967712E-06 2.8999415E-04 1.5678592E-03 0.000000 1.9999960E-02 3.4819990E-03 @@ -184,21 +184,21 @@ Av 2018 1 7 14 0 0.1935038 0.000000 2.7529069E-04 1.5808425E-03 8.1171159E-04 0.000000 3.4819990E-03 Av 2018 1 7 15 0 0.2133504 6.9905207E-07 2.7126115E-04 1.8747542E-03 4.0124907E-04 9.9999802E-03 2.1454052E-03 Av 2018 1 7 16 0 0.3925340 1.6326430E-04 2.7463565E-04 2.2414962E-03 1.9471329E-02 2.9999940E-02 5.3920748E-04 - Av 2018 1 7 17 0 0.4474072 1.8777841E-05 2.7873821E-04 2.3779178E-03 1.2234838E-02 9.9999802E-03 0.000000 - Av 2018 1 7 18 0 0.3660031 2.0451218E-05 2.7638883E-04 2.3872261E-03 1.0514800E-02 9.9999802E-03 0.000000 - Av 2018 1 7 19 0 0.3286087 0.000000 2.7322824E-04 2.3914555E-03 2.9081728E-03 0.000000 0.000000 - Av 2018 1 7 20 0 0.3221015 2.0407917E-05 2.7011725E-04 2.3955351E-03 7.6449295E-03 9.9999802E-03 0.000000 - Av 2018 1 7 21 0 0.3734655 2.0398453E-05 2.6796703E-04 2.4050644E-03 9.6528502E-03 9.9999802E-03 0.000000 - Av 2018 1 7 22 0 0.3205903 0.000000 2.6492897E-04 2.4092845E-03 2.7727550E-03 0.000000 0.000000 - Av 2018 1 7 23 0 0.2776372 0.000000 2.6102082E-04 2.4080311E-03 1.0634791E-03 0.000000 0.000000 - Av 2018 1 7 24 0 0.2764273 0.000000 2.5717038E-04 2.4067739E-03 4.9922534E-04 0.000000 0.000000 - Av 2018 1 8 1 0 0.2675420 0.000000 2.5337673E-04 2.3581355E-03 2.6921902E-04 0.000000 0.000000 - Av 2018 1 8 2 0 0.2644317 0.000000 2.4963901E-04 2.3569427E-03 1.6037427E-04 0.000000 0.000000 - Av 2018 1 8 3 0 0.3062667 1.8943201E-05 2.4681067E-04 2.3608804E-03 5.9534418E-03 9.9999802E-03 0.000000 - Av 2018 1 8 4 0 0.3064687 0.000000 2.4401983E-04 2.3648827E-03 2.3078285E-03 0.000000 0.000000 - Av 2018 1 8 5 0 0.2695767 0.000000 2.4042015E-04 2.3636676E-03 9.2212833E-04 0.000000 0.000000 - Av 2018 1 8 6 0 0.2690964 0.000000 2.3687357E-04 2.3624492E-03 4.4497458E-04 0.000000 0.000000 - Av 2018 1 8 7 0 0.2640163 0.000000 2.3337929E-04 2.3612271E-03 2.4468181E-04 0.000000 0.000000 + Av 2018 1 7 17 0 0.4474072 1.8777841E-05 2.7873821E-04 2.3779178E-03 1.2234838E-02 9.9999802E-03 0.000000 + Av 2018 1 7 18 0 0.3660031 2.0451218E-05 2.7638883E-04 2.3872261E-03 1.0514800E-02 9.9999802E-03 0.000000 + Av 2018 1 7 19 0 0.3286087 0.000000 2.7322824E-04 2.3914555E-03 2.9081728E-03 0.000000 0.000000 + Av 2018 1 7 20 0 0.3221015 2.0407917E-05 2.7011725E-04 2.3955351E-03 7.6449295E-03 9.9999802E-03 0.000000 + Av 2018 1 7 21 0 0.3734655 2.0398453E-05 2.6796703E-04 2.4050644E-03 9.6528502E-03 9.9999802E-03 0.000000 + Av 2018 1 7 22 0 0.3205903 0.000000 2.6492897E-04 2.4092845E-03 2.7727550E-03 0.000000 0.000000 + Av 2018 1 7 23 0 0.2776372 0.000000 2.6102082E-04 2.4080311E-03 1.0634791E-03 0.000000 0.000000 + Av 2018 1 7 24 0 0.2764273 0.000000 2.5717038E-04 2.4067739E-03 4.9922534E-04 0.000000 0.000000 + Av 2018 1 8 1 0 0.2675420 0.000000 2.5337673E-04 2.3581355E-03 2.6921902E-04 0.000000 0.000000 + Av 2018 1 8 2 0 0.2644317 0.000000 2.4963901E-04 2.3569427E-03 1.6037427E-04 0.000000 0.000000 + Av 2018 1 8 3 0 0.3062667 1.8943201E-05 2.4681067E-04 2.3608804E-03 5.9534418E-03 9.9999802E-03 0.000000 + Av 2018 1 8 4 0 0.3064687 0.000000 2.4401983E-04 2.3648827E-03 2.3078285E-03 0.000000 0.000000 + Av 2018 1 8 5 0 0.2695767 0.000000 2.4042015E-04 2.3636676E-03 9.2212833E-04 0.000000 0.000000 + Av 2018 1 8 6 0 0.2690964 0.000000 2.3687357E-04 2.3624492E-03 4.4497458E-04 0.000000 0.000000 + Av 2018 1 8 7 0 0.2640163 0.000000 2.3337929E-04 2.3612271E-03 2.4468181E-04 0.000000 0.000000 Av 2018 1 8 8 0 0.2547965 0.000000 2.2993659E-04 2.2383027E-03 1.4785757E-04 0.000000 5.5317639E-04 Av 2018 1 8 9 0 0.2240013 0.000000 2.2654465E-04 1.8858844E-03 9.5887910E-05 0.000000 2.1494906E-03 Av 2018 1 8 10 0 0.1896629 0.000000 2.2320278E-04 1.5943123E-03 6.5667227E-05 0.000000 3.4692169E-03 @@ -208,21 +208,21 @@ Av 2018 1 8 14 0 0.1819253 0.000000 2.1032097E-04 1.5893490E-03 0.000000 0.000000 3.4692169E-03 Av 2018 1 8 15 0 0.2002124 0.000000 2.0721841E-04 1.8784401E-03 0.000000 0.000000 2.1494906E-03 Av 2018 1 8 16 0 0.2371179 0.000000 2.0416161E-04 2.2283772E-03 0.000000 0.000000 5.5317639E-04 - Av 2018 1 8 17 0 0.2583496 1.0069431E-06 2.0119535E-04 2.3500528E-03 0.000000 1.9999960E-02 0.000000 - Av 2018 1 8 18 0 0.2588902 0.000000 1.9827260E-04 2.3500554E-03 0.000000 0.000000 0.000000 - Av 2018 1 8 19 0 0.2559855 0.000000 1.9534776E-04 2.3487911E-03 0.000000 0.000000 0.000000 - Av 2018 1 8 20 0 0.2564290 0.000000 1.9246608E-04 2.3475236E-03 0.000000 0.000000 0.000000 - Av 2018 1 8 21 0 0.2557136 0.000000 1.8962690E-04 2.3462533E-03 0.000000 0.000000 0.000000 - Av 2018 1 8 22 0 0.2835785 1.9681416E-05 1.8771786E-04 2.3502219E-03 3.7282887E-03 9.9999802E-03 0.000000 - Av 2018 1 8 23 0 0.5004605 9.2463251E-06 2.0004598E-04 2.3720991E-03 3.2185584E-02 3.9999921E-02 0.000000 - Av 2018 1 8 24 0 0.9311697 1.5317685E-04 2.6933648E-04 2.4162605E-03 7.3467493E-02 7.9999842E-02 0.000000 - Av 2018 1 9 1 0 1.104488 5.0816347E-04 3.7086767E-04 2.4199851E-03 7.0868731E-02 6.9999859E-02 0.000000 - Av 2018 1 9 2 0 1.245900 4.2550804E-04 5.1305373E-04 2.4740133E-03 9.6294224E-02 9.9999800E-02 0.000000 - Av 2018 1 9 3 0 1.266568 8.6205272E-04 6.6047075E-04 2.5288796E-03 7.3350690E-02 6.9999859E-02 0.000000 - Av 2018 1 9 4 0 0.7734203 1.0154564E-04 7.1035611E-04 2.5656803E-03 2.7681751E-02 1.9999960E-02 0.000000 - Av 2018 1 9 5 0 0.8275715 8.8750443E-05 7.5921882E-04 2.6020778E-03 6.3251041E-02 6.9999859E-02 0.000000 - Av 2018 1 9 6 0 0.9480546 2.8434070E-04 8.2206522E-04 2.6475280E-03 4.3701351E-02 3.9999921E-02 0.000000 - Av 2018 1 9 7 0 0.5242016 5.3844240E-09 8.2941464E-04 2.6663304E-03 8.0935070E-03 0.000000 0.000000 + Av 2018 1 8 17 0 0.2583496 1.0069431E-06 2.0119535E-04 2.3500528E-03 0.000000 1.9999960E-02 0.000000 + Av 2018 1 8 18 0 0.2588902 0.000000 1.9827260E-04 2.3500554E-03 0.000000 0.000000 0.000000 + Av 2018 1 8 19 0 0.2559855 0.000000 1.9534776E-04 2.3487911E-03 0.000000 0.000000 0.000000 + Av 2018 1 8 20 0 0.2564290 0.000000 1.9246608E-04 2.3475236E-03 0.000000 0.000000 0.000000 + Av 2018 1 8 21 0 0.2557136 0.000000 1.8962690E-04 2.3462533E-03 0.000000 0.000000 0.000000 + Av 2018 1 8 22 0 0.2835785 1.9681416E-05 1.8771786E-04 2.3502219E-03 3.7282887E-03 9.9999802E-03 0.000000 + Av 2018 1 8 23 0 0.5004605 9.2463251E-06 2.0004598E-04 2.3720991E-03 3.2185584E-02 3.9999921E-02 0.000000 + Av 2018 1 8 24 0 0.9311697 1.5317685E-04 2.6933648E-04 2.4162605E-03 7.3467493E-02 7.9999842E-02 0.000000 + Av 2018 1 9 1 0 1.104488 5.0816347E-04 3.7086767E-04 2.4199851E-03 7.0868731E-02 6.9999859E-02 0.000000 + Av 2018 1 9 2 0 1.245900 4.2550804E-04 5.1305373E-04 2.4740133E-03 9.6294224E-02 9.9999800E-02 0.000000 + Av 2018 1 9 3 0 1.266568 8.6205272E-04 6.6047075E-04 2.5288796E-03 7.3350690E-02 6.9999859E-02 0.000000 + Av 2018 1 9 4 0 0.7734203 1.0154564E-04 7.1035611E-04 2.5656803E-03 2.7681751E-02 1.9999960E-02 0.000000 + Av 2018 1 9 5 0 0.8275715 8.8750443E-05 7.5921882E-04 2.6020778E-03 6.3251041E-02 6.9999859E-02 0.000000 + Av 2018 1 9 6 0 0.9480546 2.8434070E-04 8.2206522E-04 2.6475280E-03 4.3701351E-02 3.9999921E-02 0.000000 + Av 2018 1 9 7 0 0.5242016 5.3844240E-09 8.2941464E-04 2.6663304E-03 8.0935070E-03 0.000000 0.000000 Av 2018 1 9 8 0 0.5718786 1.4365188E-05 8.3587295E-04 2.5531610E-03 3.3185832E-02 3.9999921E-02 5.9668976E-04 Av 2018 1 9 9 0 0.5708481 2.5476033E-05 8.4330770E-04 2.2104299E-03 1.4327581E-02 9.9999802E-03 2.2638519E-03 Av 2018 1 9 10 0 0.3613071 1.7490091E-05 8.3282602E-04 1.9188847E-03 9.2425365E-03 9.9999802E-03 3.6326693E-03 @@ -232,21 +232,21 @@ Av 2018 1 9 14 0 0.2793860 0.000000 7.8668451E-04 1.9284228E-03 4.2843653E-04 0.000000 3.6326693E-03 Av 2018 1 9 15 0 0.2952628 0.000000 7.7507965E-04 2.2285683E-03 2.3708088E-04 0.000000 2.2638519E-03 Av 2018 1 9 16 0 0.3318326 0.000000 7.6364604E-04 2.5943383E-03 1.4393360E-04 0.000000 5.9668976E-04 - Av 2018 1 9 17 0 0.3505576 0.000000 7.5238099E-04 2.7245930E-03 9.3675117E-05 0.000000 0.000000 - Av 2018 1 9 18 0 0.3508385 0.000000 7.4128219E-04 2.7235649E-03 6.4330314E-05 0.000000 0.000000 - Av 2018 1 9 19 0 0.3487801 0.000000 7.3034712E-04 2.7225262E-03 4.6097975E-05 0.000000 0.000000 - Av 2018 1 9 20 0 0.3476742 0.000000 7.1957341E-04 2.7214766E-03 3.4189030E-05 0.000000 0.000000 - Av 2018 1 9 21 0 0.3473319 0.000000 7.0895854E-04 2.7204165E-03 1.7411496E-04 0.000000 0.000000 - Av 2018 1 9 22 0 0.3456421 0.000000 6.9850025E-04 2.7193457E-03 0.000000 0.000000 0.000000 - Av 2018 1 9 23 0 0.3434898 0.000000 6.8819633E-04 2.7182647E-03 0.000000 0.000000 0.000000 - Av 2018 1 9 24 0 0.3427007 0.000000 6.7804434E-04 2.7171739E-03 0.000000 0.000000 0.000000 - Av 2018 1 10 1 0 0.3377104 0.000000 6.6804216E-04 2.6609332E-03 0.000000 0.000000 0.000000 - Av 2018 1 10 2 0 0.3342054 0.000000 6.5818749E-04 2.6599073E-03 0.000000 0.000000 0.000000 - Av 2018 1 10 3 0 0.3339548 0.000000 6.4847816E-04 2.6588717E-03 0.000000 0.000000 0.000000 - Av 2018 1 10 4 0 0.3338305 0.000000 6.3891208E-04 2.6578265E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 1 10 5 0 0.3324407 0.000000 6.2948710E-04 2.6567718E-03 0.000000 0.000000 0.000000 - Av 2018 1 10 6 0 0.3302691 0.000000 6.2020117E-04 2.6557075E-03 0.000000 0.000000 0.000000 - Av 2018 1 10 7 0 0.3296264 0.000000 6.1105221E-04 2.6546344E-03 0.000000 0.000000 0.000000 + Av 2018 1 9 17 0 0.3505576 0.000000 7.5238099E-04 2.7245930E-03 9.3675117E-05 0.000000 0.000000 + Av 2018 1 9 18 0 0.3508385 0.000000 7.4128219E-04 2.7235649E-03 6.4330314E-05 0.000000 0.000000 + Av 2018 1 9 19 0 0.3487801 0.000000 7.3034712E-04 2.7225262E-03 4.6097975E-05 0.000000 0.000000 + Av 2018 1 9 20 0 0.3476742 0.000000 7.1957341E-04 2.7214766E-03 3.4189030E-05 0.000000 0.000000 + Av 2018 1 9 21 0 0.3473319 0.000000 7.0895854E-04 2.7204165E-03 1.7411496E-04 0.000000 0.000000 + Av 2018 1 9 22 0 0.3456421 0.000000 6.9850025E-04 2.7193457E-03 0.000000 0.000000 0.000000 + Av 2018 1 9 23 0 0.3434898 0.000000 6.8819633E-04 2.7182647E-03 0.000000 0.000000 0.000000 + Av 2018 1 9 24 0 0.3427007 0.000000 6.7804434E-04 2.7171739E-03 0.000000 0.000000 0.000000 + Av 2018 1 10 1 0 0.3377104 0.000000 6.6804216E-04 2.6609332E-03 0.000000 0.000000 0.000000 + Av 2018 1 10 2 0 0.3342054 0.000000 6.5818749E-04 2.6599073E-03 0.000000 0.000000 0.000000 + Av 2018 1 10 3 0 0.3339548 0.000000 6.4847816E-04 2.6588717E-03 0.000000 0.000000 0.000000 + Av 2018 1 10 4 0 0.3338305 0.000000 6.3891208E-04 2.6578265E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 1 10 5 0 0.3324407 0.000000 6.2948710E-04 2.6567718E-03 0.000000 0.000000 0.000000 + Av 2018 1 10 6 0 0.3302691 0.000000 6.2020117E-04 2.6557075E-03 0.000000 0.000000 0.000000 + Av 2018 1 10 7 0 0.3296264 0.000000 6.1105221E-04 2.6546344E-03 0.000000 0.000000 0.000000 Av 2018 1 10 8 0 0.3287012 9.1379961E-06 6.0245662E-04 2.5364787E-03 9.3791221E-04 9.9999802E-03 5.4834702E-04 Av 2018 1 10 9 0 0.3020168 0.000000 5.9398572E-04 2.2128031E-03 6.5103685E-04 0.000000 2.0310974E-03 Av 2018 1 10 10 0 0.2637452 0.000000 5.8522349E-04 1.9458078E-03 3.3510628E-04 0.000000 3.2396743E-03 @@ -256,21 +256,21 @@ Av 2018 1 10 14 0 0.2517400 0.000000 5.5144826E-04 1.9412888E-03 5.6170549E-05 0.000000 3.2396743E-03 Av 2018 1 10 15 0 0.2687274 0.000000 5.4331351E-04 2.2060249E-03 4.0833362E-05 0.000000 2.0310974E-03 Av 2018 1 10 16 0 0.3030169 0.000000 5.3529878E-04 2.5310712E-03 1.9368852E-04 0.000000 5.4834702E-04 - Av 2018 1 10 17 0 0.3213711 0.000000 5.2740227E-04 2.6505408E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 1 10 18 0 0.3222531 2.6719285E-06 5.1974470E-04 2.6513315E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 1 10 19 0 0.3198092 0.000000 5.1219948E-04 2.6521627E-03 0.000000 0.000000 0.000000 - Av 2018 1 10 20 0 0.3182055 0.000000 5.0464371E-04 2.6509673E-03 0.000000 0.000000 0.000000 - Av 2018 1 10 21 0 0.3175810 0.000000 4.9719942E-04 2.6497648E-03 0.000000 0.000000 0.000000 - Av 2018 1 10 22 0 0.3166301 0.000000 4.8986496E-04 2.6485545E-03 0.000000 0.000000 0.000000 - Av 2018 1 10 23 0 0.3158064 0.000000 4.8263869E-04 2.6473368E-03 0.000000 0.000000 0.000000 - Av 2018 1 10 24 0 0.3149522 0.000000 4.7551902E-04 2.6461119E-03 0.000000 0.000000 0.000000 - Av 2018 1 11 1 0 0.3104964 0.000000 4.6850438E-04 2.5915198E-03 0.000000 0.000000 0.000000 - Av 2018 1 11 2 0 0.3073117 0.000000 4.6159321E-04 2.5903636E-03 0.000000 0.000000 0.000000 - Av 2018 1 11 3 0 0.5049261 1.2109655E-05 4.7173069E-04 2.6080881E-03 2.7900640E-02 3.9999921E-02 0.000000 - Av 2018 1 11 4 0 0.9707266 2.0906121E-04 5.5198721E-04 2.6547604E-03 7.2912388E-02 7.9999842E-02 0.000000 - Av 2018 1 11 5 0 0.8327173 1.1327815E-04 6.1905384E-04 2.6944124E-03 2.8075963E-02 1.9999960E-02 0.000000 - Av 2018 1 11 6 0 0.6307669 1.3770124E-05 6.3345738E-04 2.7243956E-03 3.7861962E-02 3.9999921E-02 0.000000 - Av 2018 1 11 7 0 0.6099029 2.7194745E-05 6.4363016E-04 2.7490759E-03 1.5153815E-02 9.9999802E-03 0.000000 + Av 2018 1 10 17 0 0.3213711 0.000000 5.2740227E-04 2.6505408E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 1 10 18 0 0.3222531 2.6719285E-06 5.1974470E-04 2.6513315E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 1 10 19 0 0.3198092 0.000000 5.1219948E-04 2.6521627E-03 0.000000 0.000000 0.000000 + Av 2018 1 10 20 0 0.3182055 0.000000 5.0464371E-04 2.6509673E-03 0.000000 0.000000 0.000000 + Av 2018 1 10 21 0 0.3175810 0.000000 4.9719942E-04 2.6497648E-03 0.000000 0.000000 0.000000 + Av 2018 1 10 22 0 0.3166301 0.000000 4.8986496E-04 2.6485545E-03 0.000000 0.000000 0.000000 + Av 2018 1 10 23 0 0.3158064 0.000000 4.8263869E-04 2.6473368E-03 0.000000 0.000000 0.000000 + Av 2018 1 10 24 0 0.3149522 0.000000 4.7551902E-04 2.6461119E-03 0.000000 0.000000 0.000000 + Av 2018 1 11 1 0 0.3104964 0.000000 4.6850438E-04 2.5915198E-03 0.000000 0.000000 0.000000 + Av 2018 1 11 2 0 0.3073117 0.000000 4.6159321E-04 2.5903636E-03 0.000000 0.000000 0.000000 + Av 2018 1 11 3 0 0.5049261 1.2109655E-05 4.7173069E-04 2.6080881E-03 2.7900640E-02 3.9999921E-02 0.000000 + Av 2018 1 11 4 0 0.9707266 2.0906121E-04 5.5198721E-04 2.6547604E-03 7.2912388E-02 7.9999842E-02 0.000000 + Av 2018 1 11 5 0 0.8327173 1.1327815E-04 6.1905384E-04 2.6944124E-03 2.8075963E-02 1.9999960E-02 0.000000 + Av 2018 1 11 6 0 0.6307669 1.3770124E-05 6.3345738E-04 2.7243956E-03 3.7861962E-02 3.9999921E-02 0.000000 + Av 2018 1 11 7 0 0.6099029 2.7194745E-05 6.4363016E-04 2.7490759E-03 1.5153815E-02 9.9999802E-03 0.000000 Av 2018 1 11 8 0 0.8428523 1.4673601E-04 7.0959039E-04 2.6341444E-03 6.9162287E-02 7.9999842E-02 6.7703659E-04 Av 2018 1 11 9 0 0.8303623 1.1550896E-04 7.7829190E-04 2.2847764E-03 2.7305957E-02 1.9999960E-02 2.4482016E-03 Av 2018 1 11 10 0 0.4444183 8.6333544E-05 7.7609561E-04 1.9905274E-03 1.9343739E-02 1.9999960E-02 3.8808482E-03 @@ -280,21 +280,21 @@ Av 2018 1 11 14 0 0.4482535 1.5764899E-04 9.0115593E-04 2.0997343E-03 1.8297855E-02 2.9999940E-02 3.8808482E-03 Av 2018 1 11 15 0 1.345631 1.1791049E-03 1.1109198E-03 2.4581891E-03 0.1198663 0.1399997 2.4482016E-03 Av 2018 1 11 16 0 1.139884 4.5030036E-05 1.3113499E-03 2.8860169E-03 2.3143375E-02 9.9999802E-03 6.7703659E-04 - Av 2018 1 11 17 0 0.3816950 0.000000 1.2940844E-03 3.0417894E-03 5.1567010E-03 0.000000 0.000000 - Av 2018 1 11 18 0 0.5017881 0.000000 1.2749946E-03 3.0411468E-03 1.7095139E-03 0.000000 0.000000 - Av 2018 1 11 19 0 0.4272810 0.000000 1.2561864E-03 3.0404807E-03 7.2868983E-04 0.000000 0.000000 - Av 2018 1 11 20 0 0.4414404 0.000000 1.2376558E-03 3.0397917E-03 3.6747899E-04 0.000000 0.000000 - Av 2018 1 11 21 0 0.5780551 6.8711884E-06 1.2316398E-03 3.0550633E-03 2.0970562E-02 2.9999940E-02 0.000000 - Av 2018 1 11 22 0 0.6218432 3.2025913E-05 1.2271402E-03 3.0770840E-03 1.2945795E-02 9.9999802E-03 0.000000 - Av 2018 1 11 23 0 0.4829141 0.000000 1.2105186E-03 3.0827653E-03 3.3873832E-03 0.000000 0.000000 - Av 2018 1 11 24 0 0.4945701 3.0262738E-05 1.1940683E-03 3.0882158E-03 7.8461915E-03 9.9999802E-03 0.000000 - Av 2018 1 12 1 0 0.5314367 2.8271988E-05 1.1791685E-03 3.0349824E-03 9.6864067E-03 9.9999802E-03 0.000000 - Av 2018 1 12 2 0 0.5282405 3.0113310E-05 1.1644830E-03 3.0465941E-03 9.9593038E-03 9.9999802E-03 0.000000 - Av 2018 1 12 3 0 0.5910248 1.2016415E-04 1.1542906E-03 3.0639449E-03 1.7574299E-02 1.9999960E-02 0.000000 - Av 2018 1 12 4 0 0.6453133 1.2014168E-04 1.1484211E-03 3.0869674E-03 1.9738378E-02 1.9999960E-02 0.000000 - Av 2018 1 12 5 0 0.8779826 7.4028227E-05 1.1874152E-03 3.1254964E-03 5.3053916E-02 5.9999879E-02 0.000000 - Av 2018 1 12 6 0 0.8499308 1.3532670E-04 1.2263318E-03 3.1651058E-03 2.5646107E-02 1.9999960E-02 0.000000 - Av 2018 1 12 7 0 0.6449540 1.2265875E-04 1.2202496E-03 3.1890017E-03 2.1035453E-02 1.9999960E-02 0.000000 + Av 2018 1 11 17 0 0.3816950 0.000000 1.2940844E-03 3.0417894E-03 5.1567010E-03 0.000000 0.000000 + Av 2018 1 11 18 0 0.5017881 0.000000 1.2749946E-03 3.0411468E-03 1.7095139E-03 0.000000 0.000000 + Av 2018 1 11 19 0 0.4272810 0.000000 1.2561864E-03 3.0404807E-03 7.2868983E-04 0.000000 0.000000 + Av 2018 1 11 20 0 0.4414404 0.000000 1.2376558E-03 3.0397917E-03 3.6747899E-04 0.000000 0.000000 + Av 2018 1 11 21 0 0.5780551 6.8711884E-06 1.2316398E-03 3.0550633E-03 2.0970562E-02 2.9999940E-02 0.000000 + Av 2018 1 11 22 0 0.6218432 3.2025913E-05 1.2271402E-03 3.0770840E-03 1.2945795E-02 9.9999802E-03 0.000000 + Av 2018 1 11 23 0 0.4829141 0.000000 1.2105186E-03 3.0827653E-03 3.3873832E-03 0.000000 0.000000 + Av 2018 1 11 24 0 0.4945701 3.0262738E-05 1.1940683E-03 3.0882158E-03 7.8461915E-03 9.9999802E-03 0.000000 + Av 2018 1 12 1 0 0.5314367 2.8271988E-05 1.1791685E-03 3.0349824E-03 9.6864067E-03 9.9999802E-03 0.000000 + Av 2018 1 12 2 0 0.5282405 3.0113310E-05 1.1644830E-03 3.0465941E-03 9.9593038E-03 9.9999802E-03 0.000000 + Av 2018 1 12 3 0 0.5910248 1.2016415E-04 1.1542906E-03 3.0639449E-03 1.7574299E-02 1.9999960E-02 0.000000 + Av 2018 1 12 4 0 0.6453133 1.2014168E-04 1.1484211E-03 3.0869674E-03 1.9738378E-02 1.9999960E-02 0.000000 + Av 2018 1 12 5 0 0.8779826 7.4028227E-05 1.1874152E-03 3.1254964E-03 5.3053916E-02 5.9999879E-02 0.000000 + Av 2018 1 12 6 0 0.8499308 1.3532670E-04 1.2263318E-03 3.1651058E-03 2.5646107E-02 1.9999960E-02 0.000000 + Av 2018 1 12 7 0 0.6449540 1.2265875E-04 1.2202496E-03 3.1890017E-03 2.1035453E-02 1.9999960E-02 0.000000 Av 2018 1 12 8 0 0.6682868 1.2262273E-04 1.2136744E-03 3.0454660E-03 2.0197554E-02 1.9999960E-02 7.5880537E-04 Av 2018 1 12 9 0 0.4979912 0.000000 1.2014703E-03 2.6344298E-03 4.6765227E-03 0.000000 2.6788071E-03 Av 2018 1 12 10 0 0.3653578 0.000000 1.1837466E-03 2.2945437E-03 1.5875300E-03 0.000000 4.2194063E-03 @@ -304,21 +304,21 @@ Av 2018 1 12 14 0 0.3443866 0.000000 1.1154285E-03 2.2905157E-03 1.2461010E-04 0.000000 4.2194063E-03 Av 2018 1 12 15 0 0.3654594 0.000000 1.0989743E-03 2.6283902E-03 8.2625644E-05 0.000000 2.6788071E-03 Av 2018 1 12 16 0 0.4074717 0.000000 1.0827626E-03 3.0497133E-03 5.7580244E-05 0.000000 7.5880537E-04 - Av 2018 1 12 17 0 0.4306308 0.000000 1.0667902E-03 3.2155542E-03 4.1749980E-05 0.000000 0.000000 - Av 2018 1 12 18 0 0.4326597 0.000000 1.0510533E-03 3.2144389E-03 1.9628512E-04 0.000000 0.000000 - Av 2018 1 12 19 0 0.4293951 0.000000 1.0355486E-03 3.2133050E-03 0.000000 0.000000 0.000000 - Av 2018 1 12 20 0 0.4269499 0.000000 1.0202726E-03 3.2121530E-03 0.000000 0.000000 0.000000 - Av 2018 1 12 21 0 0.4255818 0.000000 1.0052220E-03 3.2109828E-03 0.000000 0.000000 0.000000 - Av 2018 1 12 22 0 0.4238672 0.000000 9.9039334E-04 3.2097949E-03 0.000000 0.000000 0.000000 - Av 2018 1 12 23 0 0.4223006 0.000000 9.7578357E-04 3.2085897E-03 0.000000 0.000000 0.000000 - Av 2018 1 12 24 0 0.4207097 0.000000 9.6138928E-04 3.2073671E-03 0.000000 0.000000 0.000000 - Av 2018 1 13 1 0 0.4145612 0.000000 9.4720733E-04 3.1385303E-03 0.000000 0.000000 0.000000 - Av 2018 1 13 2 0 0.4100312 0.000000 9.3323452E-04 3.1373855E-03 0.000000 0.000000 0.000000 - Av 2018 1 13 3 0 0.4095649 0.000000 9.1946783E-04 3.1362243E-03 0.000000 0.000000 0.000000 - Av 2018 1 13 4 0 0.4077113 0.000000 9.0590422E-04 3.1350474E-03 0.000000 0.000000 0.000000 - Av 2018 1 13 5 0 0.4063652 0.000000 8.9254073E-04 3.1338546E-03 0.000000 0.000000 0.000000 - Av 2018 1 13 6 0 0.4048675 0.000000 8.7937433E-04 3.1326462E-03 0.000000 0.000000 0.000000 - Av 2018 1 13 7 0 0.4034471 0.000000 8.6640217E-04 3.1314229E-03 0.000000 0.000000 0.000000 + Av 2018 1 12 17 0 0.4306308 0.000000 1.0667902E-03 3.2155542E-03 4.1749980E-05 0.000000 0.000000 + Av 2018 1 12 18 0 0.4326597 0.000000 1.0510533E-03 3.2144389E-03 1.9628512E-04 0.000000 0.000000 + Av 2018 1 12 19 0 0.4293951 0.000000 1.0355486E-03 3.2133050E-03 0.000000 0.000000 0.000000 + Av 2018 1 12 20 0 0.4269499 0.000000 1.0202726E-03 3.2121530E-03 0.000000 0.000000 0.000000 + Av 2018 1 12 21 0 0.4255818 0.000000 1.0052220E-03 3.2109828E-03 0.000000 0.000000 0.000000 + Av 2018 1 12 22 0 0.4238672 0.000000 9.9039334E-04 3.2097949E-03 0.000000 0.000000 0.000000 + Av 2018 1 12 23 0 0.4223006 0.000000 9.7578357E-04 3.2085897E-03 0.000000 0.000000 0.000000 + Av 2018 1 12 24 0 0.4207097 0.000000 9.6138928E-04 3.2073671E-03 0.000000 0.000000 0.000000 + Av 2018 1 13 1 0 0.4145612 0.000000 9.4720733E-04 3.1385303E-03 0.000000 0.000000 0.000000 + Av 2018 1 13 2 0 0.4100312 0.000000 9.3323452E-04 3.1373855E-03 0.000000 0.000000 0.000000 + Av 2018 1 13 3 0 0.4095649 0.000000 9.1946783E-04 3.1362243E-03 0.000000 0.000000 0.000000 + Av 2018 1 13 4 0 0.4077113 0.000000 9.0590422E-04 3.1350474E-03 0.000000 0.000000 0.000000 + Av 2018 1 13 5 0 0.4063652 0.000000 8.9254073E-04 3.1338546E-03 0.000000 0.000000 0.000000 + Av 2018 1 13 6 0 0.4048675 0.000000 8.7937433E-04 3.1326462E-03 0.000000 0.000000 0.000000 + Av 2018 1 13 7 0 0.4034471 0.000000 8.6640217E-04 3.1314229E-03 0.000000 0.000000 0.000000 Av 2018 1 13 8 0 0.3888130 0.000000 8.5362140E-04 2.9375027E-03 0.000000 0.000000 8.7582530E-04 Av 2018 1 13 9 0 0.3464852 0.000000 8.4102916E-04 2.4647713E-03 0.000000 0.000000 3.0189068E-03 Av 2018 1 13 10 0 0.3013575 0.000000 8.2862267E-04 2.0883661E-03 0.000000 0.000000 4.7240756E-03 @@ -328,21 +328,21 @@ Av 2018 1 13 14 0 0.2883922 0.000000 7.8079995E-04 2.0831525E-03 0.000000 0.000000 4.7240756E-03 Av 2018 1 13 15 0 0.3126231 0.000000 7.6928199E-04 2.4569521E-03 0.000000 0.000000 3.0189068E-03 Av 2018 1 13 16 0 0.3604207 0.000000 7.5793383E-04 2.9270791E-03 0.000000 0.000000 8.7582530E-04 - Av 2018 1 13 17 0 0.3875595 0.000000 7.4675312E-04 3.1183965E-03 0.000000 0.000000 0.000000 - Av 2018 1 13 18 0 0.3896297 0.000000 7.3573733E-04 3.1170198E-03 0.000000 0.000000 0.000000 - Av 2018 1 13 19 0 0.3872360 0.000000 7.2488404E-04 3.1156300E-03 0.000000 0.000000 0.000000 - Av 2018 1 13 20 0 0.3864147 0.000000 7.1419089E-04 3.1142281E-03 0.000000 0.000000 0.000000 - Av 2018 1 13 21 0 0.3850665 0.000000 7.0365542E-04 3.1128135E-03 0.000000 0.000000 0.000000 - Av 2018 1 13 22 0 0.3839211 0.000000 6.9327542E-04 3.1113867E-03 0.000000 0.000000 0.000000 - Av 2018 1 13 23 0 0.3827246 0.000000 6.8304851E-04 3.1099480E-03 0.000000 0.000000 0.000000 - Av 2018 1 13 24 0 0.3815649 0.000000 6.7297247E-04 3.1084975E-03 0.000000 0.000000 0.000000 - Av 2018 1 14 1 0 0.3759884 0.000000 6.6304510E-04 3.0419417E-03 0.000000 0.000000 0.000000 - Av 2018 1 14 2 0 0.3719735 0.000000 6.5326411E-04 3.0405766E-03 0.000000 0.000000 0.000000 - Av 2018 1 14 3 0 0.3718639 0.000000 6.4362743E-04 3.0392003E-03 0.000000 0.000000 0.000000 - 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Av 2018 1 17 4 0 0.3089513 0.000000 2.5850211E-04 2.7932646E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 1 17 5 0 0.3080989 0.000000 2.5468881E-04 2.7916594E-03 0.000000 0.000000 0.000000 - Av 2018 1 17 6 0 0.3064705 0.000000 2.5093177E-04 2.7900496E-03 0.000000 0.000000 0.000000 - Av 2018 1 17 7 0 0.3063109 0.000000 2.4723011E-04 2.7884354E-03 0.000000 0.000000 0.000000 + Av 2018 1 16 17 0 0.3172434 0.000000 3.0441137E-04 2.8701858E-03 0.000000 0.000000 0.000000 + Av 2018 1 16 18 0 0.3206659 0.000000 2.9992082E-04 2.8685364E-03 0.000000 0.000000 0.000000 + Av 2018 1 16 19 0 0.3186457 0.000000 2.9549649E-04 2.8668819E-03 0.000000 0.000000 0.000000 + Av 2018 1 16 20 0 0.3185261 0.000000 2.9113749E-04 2.8652223E-03 0.000000 0.000000 0.000000 + Av 2018 1 16 21 0 0.3177539 0.000000 2.8684275E-04 2.8635575E-03 0.000000 0.000000 0.000000 + Av 2018 1 16 22 0 0.3172165 0.000000 2.8261135E-04 2.8618877E-03 0.000000 0.000000 0.000000 + Av 2018 1 16 23 0 0.3166054 0.000000 2.7844240E-04 2.8602129E-03 0.000000 0.000000 0.000000 + Av 2018 1 16 24 0 0.3160276 0.000000 2.7433492E-04 2.8585333E-03 0.000000 0.000000 0.000000 + Av 2018 1 17 1 0 0.3114510 0.000000 2.7028806E-04 2.7980516E-03 0.000000 0.000000 0.000000 + Av 2018 1 17 2 0 0.3082789 0.000000 2.6630086E-04 2.7964606E-03 0.000000 0.000000 0.000000 + Av 2018 1 17 3 0 0.3086275 0.000000 2.6237252E-04 2.7948648E-03 0.000000 0.000000 0.000000 + Av 2018 1 17 4 0 0.3089513 0.000000 2.5850211E-04 2.7932646E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 1 17 5 0 0.3080989 0.000000 2.5468881E-04 2.7916594E-03 0.000000 0.000000 0.000000 + Av 2018 1 17 6 0 0.3064705 0.000000 2.5093177E-04 2.7900496E-03 0.000000 0.000000 0.000000 + Av 2018 1 17 7 0 0.3063109 0.000000 2.4723011E-04 2.7884354E-03 0.000000 0.000000 0.000000 Av 2018 1 17 8 0 0.2926070 0.000000 2.4358308E-04 2.5964023E-03 0.000000 0.000000 8.6552056E-04 Av 2018 1 17 9 0 0.2557357 0.000000 2.3998984E-04 2.1874174E-03 0.000000 0.000000 2.7171646E-03 Av 2018 1 17 10 0 0.2186382 0.000000 2.3644960E-04 1.8736357E-03 0.000000 0.000000 4.1360483E-03 @@ -424,21 +424,21 @@ Av 2018 1 17 14 0 0.2103324 0.000000 2.2280327E-04 1.8670836E-03 0.000000 0.000000 4.1360483E-03 Av 2018 1 17 15 0 0.2320402 0.000000 2.1951657E-04 2.1775896E-03 0.000000 9.9999802E-03 2.7171646E-03 Av 2018 1 17 16 0 0.5139687 4.0584699E-05 2.5192503E-04 2.6079812E-03 3.3176910E-02 7.9999842E-02 8.6552056E-04 - Av 2018 1 17 17 0 1.378949 1.1839111E-03 4.5876307E-04 2.8519421E-03 0.1172509 0.1299997 0.000000 - Av 2018 1 17 18 0 2.101897 4.1571553E-03 8.3048403E-04 2.9109695E-03 0.1293380 0.1299997 0.000000 - Av 2018 1 17 19 0 1.636094 4.2472759E-04 1.1152725E-03 2.9702694E-03 8.5381992E-02 7.9999842E-02 0.000000 - Av 2018 1 17 20 0 1.645212 2.7268708E-03 1.4004528E-03 3.0308294E-03 0.1161438 0.1199998 0.000000 - Av 2018 1 17 21 0 1.154158 1.3481325E-06 1.5871437E-03 3.0637237E-03 1.5923824E-02 0.000000 0.000000 - Av 2018 1 17 22 0 0.3642214 0.000000 1.5637943E-03 3.0648231E-03 3.9384700E-03 0.000000 0.000000 - Av 2018 1 17 23 0 0.5369710 0.000000 1.5407259E-03 3.0645479E-03 1.3929461E-03 0.000000 0.000000 - Av 2018 1 17 24 0 0.4512031 0.000000 1.5179978E-03 3.0642431E-03 6.1953056E-04 0.000000 0.000000 - Av 2018 1 18 1 0 0.5713512 1.3190707E-04 1.5018494E-03 3.0111689E-03 1.3849576E-02 1.9999960E-02 0.000000 - Av 2018 1 18 2 0 0.8345879 4.9275062E-05 1.5262061E-03 3.0471005E-03 4.3827418E-02 4.9999900E-02 0.000000 - Av 2018 1 18 3 0 0.8252210 1.4900189E-04 1.5508565E-03 3.0841182E-03 2.4356401E-02 1.9999960E-02 0.000000 - Av 2018 1 18 4 0 0.5589417 0.000000 1.5350099E-03 3.0964608E-03 5.3487280E-03 0.000000 0.000000 - Av 2018 1 18 5 0 0.4817344 0.000000 1.5123661E-03 3.0961081E-03 1.7573922E-03 0.000000 0.000000 - Av 2018 1 18 6 0 0.4741944 0.000000 1.4900564E-03 3.0957267E-03 7.4474065E-04 0.000000 0.000000 - Av 2018 1 18 7 0 0.4643542 0.000000 1.4680757E-03 3.0953167E-03 3.7407252E-04 0.000000 0.000000 + Av 2018 1 17 17 0 1.378949 1.1839111E-03 4.5876307E-04 2.8519421E-03 0.1172509 0.1299997 0.000000 + Av 2018 1 17 18 0 2.101897 4.1571553E-03 8.3048403E-04 2.9109695E-03 0.1293380 0.1299997 0.000000 + Av 2018 1 17 19 0 1.636094 4.2472759E-04 1.1152725E-03 2.9702694E-03 8.5381992E-02 7.9999842E-02 0.000000 + Av 2018 1 17 20 0 1.645212 2.7268708E-03 1.4004528E-03 3.0308294E-03 0.1161438 0.1199998 0.000000 + Av 2018 1 17 21 0 1.154158 1.3481325E-06 1.5871437E-03 3.0637237E-03 1.5923824E-02 0.000000 0.000000 + Av 2018 1 17 22 0 0.3642214 0.000000 1.5637943E-03 3.0648231E-03 3.9384700E-03 0.000000 0.000000 + Av 2018 1 17 23 0 0.5369710 0.000000 1.5407259E-03 3.0645479E-03 1.3929461E-03 0.000000 0.000000 + Av 2018 1 17 24 0 0.4512031 0.000000 1.5179978E-03 3.0642431E-03 6.1953056E-04 0.000000 0.000000 + Av 2018 1 18 1 0 0.5713512 1.3190707E-04 1.5018494E-03 3.0111689E-03 1.3849576E-02 1.9999960E-02 0.000000 + Av 2018 1 18 2 0 0.8345879 4.9275062E-05 1.5262061E-03 3.0471005E-03 4.3827418E-02 4.9999900E-02 0.000000 + Av 2018 1 18 3 0 0.8252210 1.4900189E-04 1.5508565E-03 3.0841182E-03 2.4356401E-02 1.9999960E-02 0.000000 + Av 2018 1 18 4 0 0.5589417 0.000000 1.5350099E-03 3.0964608E-03 5.3487280E-03 0.000000 0.000000 + Av 2018 1 18 5 0 0.4817344 0.000000 1.5123661E-03 3.0961081E-03 1.7573922E-03 0.000000 0.000000 + Av 2018 1 18 6 0 0.4741944 0.000000 1.4900564E-03 3.0957267E-03 7.4474065E-04 0.000000 0.000000 + Av 2018 1 18 7 0 0.4643542 0.000000 1.4680757E-03 3.0953167E-03 3.7407252E-04 0.000000 0.000000 Av 2018 1 18 8 0 0.4491490 0.000000 1.4464193E-03 2.9202348E-03 2.1165557E-04 0.000000 7.9383602E-04 Av 2018 1 18 9 0 0.4130361 0.000000 1.4250823E-03 2.5584111E-03 1.3063430E-04 0.000000 2.4363752E-03 Av 2018 1 18 10 0 0.3782466 0.000000 1.4040602E-03 2.2838823E-03 8.6098706E-05 0.000000 3.6819964E-03 @@ -448,21 +448,21 @@ Av 2018 1 18 14 0 0.9095135 2.0934416E-04 1.4304820E-03 2.3479660E-03 6.5959550E-02 7.9999842E-02 3.6819964E-03 Av 2018 1 18 15 0 0.7743890 1.0766330E-06 1.5029737E-03 2.6540281E-03 1.1403943E-02 0.000000 2.4363752E-03 Av 2018 1 18 16 0 0.4165743 0.000000 1.4808534E-03 3.0160851E-03 3.0869748E-03 0.000000 7.9383602E-04 - Av 2018 1 18 17 0 0.5053150 0.000000 1.4590085E-03 3.1901721E-03 1.1554473E-03 0.000000 0.000000 - Av 2018 1 18 18 0 0.4660420 0.000000 1.4374858E-03 3.1895877E-03 5.3360756E-04 0.000000 0.000000 - Av 2018 1 18 19 0 0.4707955 0.000000 1.4162806E-03 3.1889759E-03 2.8447842E-04 0.000000 0.000000 - Av 2018 1 18 20 0 0.4637136 0.000000 1.3953883E-03 3.1883377E-03 1.6804926E-04 0.000000 0.000000 - Av 2018 1 18 21 0 0.5749425 4.4628632E-06 1.3845008E-03 3.2021031E-03 1.5788527E-02 2.9999940E-02 0.000000 - Av 2018 1 18 22 0 0.7934500 4.1514522E-05 1.3996370E-03 3.2377695E-03 3.6020946E-02 3.9999921E-02 0.000000 - Av 2018 1 18 23 0 0.7180324 3.7396319E-05 1.4065560E-03 3.2660903E-03 1.5027071E-02 9.9999802E-03 0.000000 - Av 2018 1 18 24 0 0.5710185 3.3813751E-05 1.3891939E-03 3.2788431E-03 1.1110618E-02 9.9999802E-03 0.000000 - Av 2018 1 19 1 0 0.5301046 0.000000 1.3703059E-03 3.2150825E-03 3.0284689E-03 0.000000 0.000000 - Av 2018 1 19 2 0 0.4656693 0.000000 1.3500918E-03 3.2143570E-03 1.1385201E-03 0.000000 0.000000 - Av 2018 1 19 3 0 0.4682533 0.000000 1.3301759E-03 3.2136068E-03 5.2732951E-04 0.000000 0.000000 - Av 2018 1 19 4 0 0.4587433 0.000000 1.3105536E-03 3.2128321E-03 2.8170802E-04 0.000000 0.000000 - Av 2018 1 19 5 0 0.4568458 0.000000 1.2912209E-03 3.2120335E-03 1.6666176E-04 0.000000 0.000000 - Av 2018 1 19 6 0 0.4974632 3.1036507E-05 1.2736545E-03 3.2174794E-03 5.9616626E-03 9.9999802E-03 0.000000 - Av 2018 1 19 7 0 0.5483717 3.3056072E-05 1.2579178E-03 3.2295217E-03 9.3331784E-03 9.9999802E-03 0.000000 + Av 2018 1 18 17 0 0.5053150 0.000000 1.4590085E-03 3.1901721E-03 1.1554473E-03 0.000000 0.000000 + Av 2018 1 18 18 0 0.4660420 0.000000 1.4374858E-03 3.1895877E-03 5.3360756E-04 0.000000 0.000000 + Av 2018 1 18 19 0 0.4707955 0.000000 1.4162806E-03 3.1889759E-03 2.8447842E-04 0.000000 0.000000 + Av 2018 1 18 20 0 0.4637136 0.000000 1.3953883E-03 3.1883377E-03 1.6804926E-04 0.000000 0.000000 + Av 2018 1 18 21 0 0.5749425 4.4628632E-06 1.3845008E-03 3.2021031E-03 1.5788527E-02 2.9999940E-02 0.000000 + Av 2018 1 18 22 0 0.7934500 4.1514522E-05 1.3996370E-03 3.2377695E-03 3.6020946E-02 3.9999921E-02 0.000000 + Av 2018 1 18 23 0 0.7180324 3.7396319E-05 1.4065560E-03 3.2660903E-03 1.5027071E-02 9.9999802E-03 0.000000 + Av 2018 1 18 24 0 0.5710185 3.3813751E-05 1.3891939E-03 3.2788431E-03 1.1110618E-02 9.9999802E-03 0.000000 + Av 2018 1 19 1 0 0.5301046 0.000000 1.3703059E-03 3.2150825E-03 3.0284689E-03 0.000000 0.000000 + Av 2018 1 19 2 0 0.4656693 0.000000 1.3500918E-03 3.2143570E-03 1.1385201E-03 0.000000 0.000000 + Av 2018 1 19 3 0 0.4682533 0.000000 1.3301759E-03 3.2136068E-03 5.2732951E-04 0.000000 0.000000 + Av 2018 1 19 4 0 0.4587433 0.000000 1.3105536E-03 3.2128321E-03 2.8170802E-04 0.000000 0.000000 + Av 2018 1 19 5 0 0.4568458 0.000000 1.2912209E-03 3.2120335E-03 1.6666176E-04 0.000000 0.000000 + Av 2018 1 19 6 0 0.4974632 3.1036507E-05 1.2736545E-03 3.2174794E-03 5.9616626E-03 9.9999802E-03 0.000000 + Av 2018 1 19 7 0 0.5483717 3.3056072E-05 1.2579178E-03 3.2295217E-03 9.3331784E-03 9.9999802E-03 0.000000 Av 2018 1 19 8 0 0.4927633 0.000000 1.2409317E-03 3.0685675E-03 2.7402365E-03 0.000000 7.5773790E-04 Av 2018 1 19 9 0 0.4156336 0.000000 1.2226261E-03 2.7339852E-03 1.0538073E-03 0.000000 2.2743894E-03 Av 2018 1 19 10 0 0.3845844 0.000000 1.2045904E-03 2.4827321E-03 4.9556949E-04 0.000000 3.4121722E-03 @@ -472,21 +472,21 @@ Av 2018 1 19 14 0 0.3650334 0.000000 1.1350694E-03 2.4787546E-03 6.9588124E-05 0.000000 3.4121722E-03 Av 2018 1 19 15 0 0.3800210 0.000000 1.1183254E-03 2.7280210E-03 4.9440685E-05 0.000000 2.2743894E-03 Av 2018 1 19 16 0 0.4122012 0.000000 1.1018284E-03 3.0606186E-03 3.6413367E-05 0.000000 7.5773790E-04 - Av 2018 1 19 17 0 0.4338248 0.000000 1.0855747E-03 3.2262357E-03 1.8082449E-04 0.000000 0.000000 - Av 2018 1 19 18 0 0.4351464 0.000000 1.0695608E-03 3.2251312E-03 0.000000 0.000000 0.000000 - Av 2018 1 19 19 0 0.4325566 0.000000 1.0537831E-03 3.2240078E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 1 19 20 0 0.4327673 1.2221574E-06 1.0382966E-03 3.2241864E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 1 19 21 0 0.6190782 2.0523981E-05 1.0472309E-03 3.2456503E-03 2.6452908E-02 3.9999921E-02 0.000000 - Av 2018 1 19 22 0 0.6568687 3.5084016E-05 1.0575338E-03 3.2734245E-03 1.3997563E-02 9.9999802E-03 0.000000 - Av 2018 1 19 23 0 0.4833615 0.000000 1.0436033E-03 3.2792490E-03 3.5860587E-03 0.000000 0.000000 - Av 2018 1 19 24 0 0.4514013 0.000000 1.0282085E-03 3.2780110E-03 1.2965366E-03 0.000000 0.000000 - Av 2018 1 20 1 0 0.4816562 2.9644385E-05 1.0144593E-03 3.2133288E-03 6.8471823E-03 9.9999802E-03 0.000000 - Av 2018 1 20 2 0 0.4730189 0.000000 1.0009060E-03 3.2185672E-03 2.4410719E-03 0.000000 0.000000 - Av 2018 1 20 3 0 0.4309523 0.000000 9.8614115E-04 3.2173777E-03 9.6334371E-04 0.000000 0.000000 - Av 2018 1 20 4 0 0.4299712 0.000000 9.7159395E-04 3.2161709E-03 4.6098157E-04 0.000000 0.000000 - Av 2018 1 20 5 0 0.4233517 0.000000 9.5726142E-04 3.2149472E-03 2.5198329E-04 0.000000 0.000000 - Av 2018 1 20 6 0 0.4214507 0.000000 9.4314042E-04 3.2137069E-03 1.5160567E-04 0.000000 0.000000 - Av 2018 1 20 7 0 0.4189910 0.000000 9.2922762E-04 3.2124503E-03 9.7992328E-05 0.000000 0.000000 + Av 2018 1 19 17 0 0.4338248 0.000000 1.0855747E-03 3.2262357E-03 1.8082449E-04 0.000000 0.000000 + Av 2018 1 19 18 0 0.4351464 0.000000 1.0695608E-03 3.2251312E-03 0.000000 0.000000 0.000000 + Av 2018 1 19 19 0 0.4325566 0.000000 1.0537831E-03 3.2240078E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 1 19 20 0 0.4327673 1.2221574E-06 1.0382966E-03 3.2241864E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 1 19 21 0 0.6190782 2.0523981E-05 1.0472309E-03 3.2456503E-03 2.6452908E-02 3.9999921E-02 0.000000 + Av 2018 1 19 22 0 0.6568687 3.5084016E-05 1.0575338E-03 3.2734245E-03 1.3997563E-02 9.9999802E-03 0.000000 + Av 2018 1 19 23 0 0.4833615 0.000000 1.0436033E-03 3.2792490E-03 3.5860587E-03 0.000000 0.000000 + Av 2018 1 19 24 0 0.4514013 0.000000 1.0282085E-03 3.2780110E-03 1.2965366E-03 0.000000 0.000000 + Av 2018 1 20 1 0 0.4816562 2.9644385E-05 1.0144593E-03 3.2133288E-03 6.8471823E-03 9.9999802E-03 0.000000 + Av 2018 1 20 2 0 0.4730189 0.000000 1.0009060E-03 3.2185672E-03 2.4410719E-03 0.000000 0.000000 + Av 2018 1 20 3 0 0.4309523 0.000000 9.8614115E-04 3.2173777E-03 9.6334371E-04 0.000000 0.000000 + Av 2018 1 20 4 0 0.4299712 0.000000 9.7159395E-04 3.2161709E-03 4.6098157E-04 0.000000 0.000000 + Av 2018 1 20 5 0 0.4233517 0.000000 9.5726142E-04 3.2149472E-03 2.5198329E-04 0.000000 0.000000 + Av 2018 1 20 6 0 0.4214507 0.000000 9.4314042E-04 3.2137069E-03 1.5160567E-04 0.000000 0.000000 + Av 2018 1 20 7 0 0.4189910 0.000000 9.2922762E-04 3.2124503E-03 9.7992328E-05 0.000000 0.000000 Av 2018 1 20 8 0 0.4056526 0.000000 9.1552001E-04 3.0424600E-03 6.6934314E-05 0.000000 7.6689903E-04 Av 2018 1 20 9 0 0.3739592 0.000000 9.0201467E-04 2.7144307E-03 4.7758112E-05 0.000000 2.2520837E-03 Av 2018 1 20 10 0 0.3437753 0.000000 8.8870851E-04 2.4707450E-03 3.5296252E-05 0.000000 3.3538188E-03 @@ -496,21 +496,21 @@ Av 2018 1 20 14 0 0.3329032 0.000000 8.3741813E-04 2.4653776E-03 0.000000 0.000000 3.3538188E-03 Av 2018 1 20 15 0 0.3478991 0.000000 8.2506490E-04 2.7063806E-03 0.000000 0.000000 2.2520837E-03 Av 2018 1 20 16 0 0.3798159 0.000000 8.1289385E-04 3.0317288E-03 0.000000 0.000000 7.6689903E-04 - Av 2018 1 20 17 0 0.4008285 0.000000 8.0090237E-04 3.1990400E-03 0.000000 0.000000 0.000000 - Av 2018 1 20 18 0 0.4032755 0.000000 7.8908779E-04 3.1976195E-03 0.000000 0.000000 0.000000 - Av 2018 1 20 19 0 0.4006371 0.000000 7.7744754E-04 3.1961855E-03 0.000000 0.000000 0.000000 - Av 2018 1 20 20 0 0.3997886 0.000000 7.6597894E-04 3.1947379E-03 0.000000 0.000000 0.000000 - Av 2018 1 20 21 0 0.3983391 0.000000 7.5467955E-04 3.1932774E-03 0.000000 0.000000 0.000000 - Av 2018 1 20 22 0 0.3971196 0.000000 7.4354687E-04 3.1918043E-03 0.000000 0.000000 0.000000 - Av 2018 1 20 23 0 0.3958409 0.000000 7.3257840E-04 3.1903181E-03 0.000000 0.000000 0.000000 - Av 2018 1 20 24 0 0.3946032 0.000000 7.2177168E-04 3.1888194E-03 0.000000 0.000000 0.000000 - Av 2018 1 21 1 0 0.3888022 0.000000 7.1112445E-04 3.1200589E-03 0.000000 0.000000 0.000000 - Av 2018 1 21 2 0 0.3846155 0.000000 7.0063426E-04 3.1186494E-03 0.000000 0.000000 0.000000 - Av 2018 1 21 3 0 0.3844639 0.000000 6.9029880E-04 3.1172279E-03 0.000000 0.000000 0.000000 - Av 2018 1 21 4 0 0.3829285 0.000000 6.8011577E-04 3.1157944E-03 0.000000 0.000000 0.000000 - Av 2018 1 21 5 0 0.3832218 0.000000 6.7008304E-04 3.1143494E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 1 21 6 0 0.6344705 4.3400265E-05 6.9801882E-04 3.1378178E-03 3.4985084E-02 5.9999879E-02 0.000000 - Av 2018 1 21 7 0 0.7862390 1.4450979E-04 7.3888758E-04 3.1794205E-03 3.1714529E-02 2.9999940E-02 0.000000 + Av 2018 1 20 17 0 0.4008285 0.000000 8.0090237E-04 3.1990400E-03 0.000000 0.000000 0.000000 + Av 2018 1 20 18 0 0.4032755 0.000000 7.8908779E-04 3.1976195E-03 0.000000 0.000000 0.000000 + Av 2018 1 20 19 0 0.4006371 0.000000 7.7744754E-04 3.1961855E-03 0.000000 0.000000 0.000000 + Av 2018 1 20 20 0 0.3997886 0.000000 7.6597894E-04 3.1947379E-03 0.000000 0.000000 0.000000 + Av 2018 1 20 21 0 0.3983391 0.000000 7.5467955E-04 3.1932774E-03 0.000000 0.000000 0.000000 + Av 2018 1 20 22 0 0.3971196 0.000000 7.4354687E-04 3.1918043E-03 0.000000 0.000000 0.000000 + Av 2018 1 20 23 0 0.3958409 0.000000 7.3257840E-04 3.1903181E-03 0.000000 0.000000 0.000000 + Av 2018 1 20 24 0 0.3946032 0.000000 7.2177168E-04 3.1888194E-03 0.000000 0.000000 0.000000 + Av 2018 1 21 1 0 0.3888022 0.000000 7.1112445E-04 3.1200589E-03 0.000000 0.000000 0.000000 + Av 2018 1 21 2 0 0.3846155 0.000000 7.0063426E-04 3.1186494E-03 0.000000 0.000000 0.000000 + Av 2018 1 21 3 0 0.3844639 0.000000 6.9029880E-04 3.1172279E-03 0.000000 0.000000 0.000000 + Av 2018 1 21 4 0 0.3829285 0.000000 6.8011577E-04 3.1157944E-03 0.000000 0.000000 0.000000 + Av 2018 1 21 5 0 0.3832218 0.000000 6.7008304E-04 3.1143494E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 1 21 6 0 0.6344705 4.3400265E-05 6.9801882E-04 3.1378178E-03 3.4985084E-02 5.9999879E-02 0.000000 + Av 2018 1 21 7 0 0.7862390 1.4450979E-04 7.3888758E-04 3.1794205E-03 3.1714529E-02 2.9999940E-02 0.000000 Av 2018 1 21 8 0 0.6425518 1.2160616E-04 7.4729125E-04 3.0324969E-03 2.2054559E-02 1.9999960E-02 7.9763250E-04 Av 2018 1 21 9 0 0.6256043 6.6698722E-06 7.5451971E-04 2.7317570E-03 2.7780682E-02 2.9999940E-02 2.2925888E-03 Av 2018 1 21 10 0 0.5795583 1.0275703E-04 7.6071033E-04 2.5183125E-03 1.9685164E-02 1.9999960E-02 3.3887289E-03 @@ -520,21 +520,21 @@ Av 2018 1 21 14 0 0.3285535 0.000000 9.1341487E-04 2.6227720E-03 3.1184522E-03 0.000000 3.3887289E-03 Av 2018 1 21 15 0 0.4100916 0.000000 8.9994055E-04 2.8624127E-03 1.1645189E-03 0.000000 2.2925888E-03 Av 2018 1 21 16 0 0.4011348 0.000000 8.8666502E-04 3.1897780E-03 5.3696288E-04 0.000000 7.9763250E-04 - Av 2018 1 21 17 0 0.4308803 0.000000 8.7358529E-04 3.3637166E-03 2.8595622E-04 0.000000 0.000000 - Av 2018 1 21 18 0 0.4280884 0.000000 8.6069858E-04 3.3621613E-03 1.6878832E-04 0.000000 0.000000 - Av 2018 1 21 19 0 0.4258963 0.000000 8.4800192E-04 3.3605914E-03 1.0753073E-04 0.000000 0.000000 - Av 2018 1 21 20 0 0.4240782 0.000000 8.3549257E-04 3.3590072E-03 7.2626259E-05 0.000000 0.000000 - Av 2018 1 21 21 0 0.4224251 0.000000 8.2316773E-04 3.3574090E-03 5.1355793E-05 0.000000 0.000000 - Av 2018 1 21 22 0 0.4208819 0.000000 8.1102474E-04 3.3557967E-03 3.7678845E-05 0.000000 0.000000 - Av 2018 1 21 23 0 0.6707938 4.0390067E-05 8.3552976E-04 3.3794676E-03 3.4776736E-02 5.9999879E-02 0.000000 - Av 2018 1 21 24 0 0.6424109 1.5973424E-07 8.5950061E-04 3.4048958E-03 7.6723294E-03 0.000000 0.000000 - Av 2018 1 22 1 0 0.4180143 0.000000 8.4682932E-04 3.3309725E-03 2.3029675E-03 0.000000 0.000000 - Av 2018 1 22 2 0 0.4911351 2.9022001E-05 8.3573797E-04 3.3359237E-03 7.3719695E-03 9.9999802E-03 0.000000 - Av 2018 1 22 3 0 0.4663143 0.000000 8.2480337E-04 3.3410108E-03 2.5117320E-03 0.000000 0.000000 - Av 2018 1 22 4 0 0.5825109 7.4943205E-06 8.2604436E-04 3.3571294E-03 2.2904158E-02 2.9999940E-02 0.000000 - Av 2018 1 22 5 0 1.056580 2.7774036E-04 9.2368171E-04 3.4052609E-03 7.1644306E-02 7.9999842E-02 0.000000 - Av 2018 1 22 6 0 0.9561386 1.5256203E-04 1.0134405E-03 3.4500137E-03 2.8004961E-02 1.9999960E-02 0.000000 - Av 2018 1 22 7 0 0.5202370 0.000000 1.0058350E-03 3.4626205E-03 5.9090545E-03 0.000000 0.000000 + Av 2018 1 21 17 0 0.4308803 0.000000 8.7358529E-04 3.3637166E-03 2.8595622E-04 0.000000 0.000000 + Av 2018 1 21 18 0 0.4280884 0.000000 8.6069858E-04 3.3621613E-03 1.6878832E-04 0.000000 0.000000 + Av 2018 1 21 19 0 0.4258963 0.000000 8.4800192E-04 3.3605914E-03 1.0753073E-04 0.000000 0.000000 + Av 2018 1 21 20 0 0.4240782 0.000000 8.3549257E-04 3.3590072E-03 7.2626259E-05 0.000000 0.000000 + Av 2018 1 21 21 0 0.4224251 0.000000 8.2316773E-04 3.3574090E-03 5.1355793E-05 0.000000 0.000000 + Av 2018 1 21 22 0 0.4208819 0.000000 8.1102474E-04 3.3557967E-03 3.7678845E-05 0.000000 0.000000 + Av 2018 1 21 23 0 0.6707938 4.0390067E-05 8.3552976E-04 3.3794676E-03 3.4776736E-02 5.9999879E-02 0.000000 + Av 2018 1 21 24 0 0.6424109 1.5973424E-07 8.5950061E-04 3.4048958E-03 7.6723294E-03 0.000000 0.000000 + Av 2018 1 22 1 0 0.4180143 0.000000 8.4682932E-04 3.3309725E-03 2.3029675E-03 0.000000 0.000000 + Av 2018 1 22 2 0 0.4911351 2.9022001E-05 8.3573797E-04 3.3359237E-03 7.3719695E-03 9.9999802E-03 0.000000 + Av 2018 1 22 3 0 0.4663143 0.000000 8.2480337E-04 3.3410108E-03 2.5117320E-03 0.000000 0.000000 + Av 2018 1 22 4 0 0.5825109 7.4943205E-06 8.2604436E-04 3.3571294E-03 2.2904158E-02 2.9999940E-02 0.000000 + Av 2018 1 22 5 0 1.056580 2.7774036E-04 9.2368171E-04 3.4052609E-03 7.1644306E-02 7.9999842E-02 0.000000 + Av 2018 1 22 6 0 0.9561386 1.5256203E-04 1.0134405E-03 3.4500137E-03 2.8004961E-02 1.9999960E-02 0.000000 + Av 2018 1 22 7 0 0.5202370 0.000000 1.0058350E-03 3.4626205E-03 5.9090545E-03 0.000000 0.000000 Av 2018 1 22 8 0 0.4659767 0.000000 9.9099730E-04 3.2825957E-03 1.8942144E-03 0.000000 8.1133831E-04 Av 2018 1 22 9 0 0.4133975 0.000000 9.7637856E-04 2.9571909E-03 7.9001620E-04 0.000000 2.2834192E-03 Av 2018 1 22 10 0 0.3810199 0.000000 9.6197549E-04 2.7210168E-03 3.9250252E-04 0.000000 3.3498311E-03 @@ -544,21 +544,21 @@ Av 2018 1 22 14 0 0.3655856 0.000000 9.0645661E-04 2.7146025E-03 6.1320265E-05 0.000000 3.3498311E-03 Av 2018 1 22 15 0 0.3798483 0.000000 8.9308491E-04 2.9475708E-03 4.4167253E-05 0.000000 2.2834192E-03 Av 2018 1 22 16 0 0.4109389 0.000000 8.7991048E-04 3.2697713E-03 3.2894866E-05 0.000000 8.1133831E-04 - Av 2018 1 22 17 0 0.4334092 0.000000 8.6693047E-04 3.4465936E-03 1.7013081E-04 0.000000 0.000000 - Av 2018 1 22 18 0 0.4356307 0.000000 8.5414184E-04 3.4449070E-03 0.000000 0.000000 0.000000 - Av 2018 1 22 19 0 0.4317472 0.000000 8.4154191E-04 3.4432062E-03 0.000000 0.000000 0.000000 - Av 2018 1 22 20 0 0.4311659 0.000000 8.2912785E-04 3.4414912E-03 0.000000 0.000000 0.000000 - Av 2018 1 22 21 0 0.4294595 0.000000 8.1689691E-04 3.4397624E-03 0.000000 0.000000 0.000000 - Av 2018 1 22 22 0 0.4281672 0.000000 8.0484641E-04 3.4380197E-03 0.000000 0.000000 0.000000 - Av 2018 1 22 23 0 0.4267534 0.000000 7.9297367E-04 3.4362634E-03 0.000000 0.000000 0.000000 - Av 2018 1 22 24 0 0.4254040 0.000000 7.8127609E-04 3.4344944E-03 0.000000 0.000000 0.000000 - Av 2018 1 23 1 0 0.4190545 0.000000 7.6975103E-04 3.3591297E-03 0.000000 0.000000 0.000000 - Av 2018 1 23 2 0 0.4144740 0.000000 7.5839605E-04 3.3574649E-03 0.000000 0.000000 0.000000 - Av 2018 1 23 3 0 0.4143080 0.000000 7.4720854E-04 3.3557874E-03 0.000000 0.000000 0.000000 - Av 2018 1 23 4 0 0.4126279 0.000000 7.3618605E-04 3.3540970E-03 0.000000 0.000000 0.000000 - Av 2018 1 23 5 0 0.5013758 1.4499389E-04 7.3235040E-04 3.3659427E-03 1.0761120E-02 3.9999921E-02 0.000000 - Av 2018 1 23 6 0 0.6102266 1.2238249E-04 7.3446875E-04 3.3908139E-03 1.8502656E-02 1.9999960E-02 0.000000 - Av 2018 1 23 7 0 0.6340044 1.2249278E-04 7.3547772E-04 3.4147375E-03 1.9847091E-02 1.9999960E-02 0.000000 + Av 2018 1 22 17 0 0.4334092 0.000000 8.6693047E-04 3.4465936E-03 1.7013081E-04 0.000000 0.000000 + Av 2018 1 22 18 0 0.4356307 0.000000 8.5414184E-04 3.4449070E-03 0.000000 0.000000 0.000000 + Av 2018 1 22 19 0 0.4317472 0.000000 8.4154191E-04 3.4432062E-03 0.000000 0.000000 0.000000 + Av 2018 1 22 20 0 0.4311659 0.000000 8.2912785E-04 3.4414912E-03 0.000000 0.000000 0.000000 + Av 2018 1 22 21 0 0.4294595 0.000000 8.1689691E-04 3.4397624E-03 0.000000 0.000000 0.000000 + Av 2018 1 22 22 0 0.4281672 0.000000 8.0484641E-04 3.4380197E-03 0.000000 0.000000 0.000000 + Av 2018 1 22 23 0 0.4267534 0.000000 7.9297367E-04 3.4362634E-03 0.000000 0.000000 0.000000 + Av 2018 1 22 24 0 0.4254040 0.000000 7.8127609E-04 3.4344944E-03 0.000000 0.000000 0.000000 + Av 2018 1 23 1 0 0.4190545 0.000000 7.6975103E-04 3.3591297E-03 0.000000 0.000000 0.000000 + Av 2018 1 23 2 0 0.4144740 0.000000 7.5839605E-04 3.3574649E-03 0.000000 0.000000 0.000000 + Av 2018 1 23 3 0 0.4143080 0.000000 7.4720854E-04 3.3557874E-03 0.000000 0.000000 0.000000 + Av 2018 1 23 4 0 0.4126279 0.000000 7.3618605E-04 3.3540970E-03 0.000000 0.000000 0.000000 + Av 2018 1 23 5 0 0.5013758 1.4499389E-04 7.3235040E-04 3.3659427E-03 1.0761120E-02 3.9999921E-02 0.000000 + Av 2018 1 23 6 0 0.6102266 1.2238249E-04 7.3446875E-04 3.3908139E-03 1.8502656E-02 1.9999960E-02 0.000000 + Av 2018 1 23 7 0 0.6340044 1.2249278E-04 7.3547772E-04 3.4147375E-03 1.9847091E-02 1.9999960E-02 0.000000 Av 2018 1 23 8 0 0.9233590 1.2994310E-04 8.0341846E-04 3.2546434E-03 6.1644554E-02 6.9999859E-02 9.1685937E-04 Av 2018 1 23 9 0 1.051203 5.0787593E-04 9.0358389E-04 2.9560870E-03 5.1374204E-02 4.9999900E-02 2.5277573E-03 Av 2018 1 23 10 0 1.156359 4.0957460E-04 1.0517162E-03 2.7600122E-03 8.2495540E-02 8.9999817E-02 3.6802255E-03 @@ -568,21 +568,21 @@ Av 2018 1 23 14 0 0.7169392 2.2872040E-05 1.2516583E-03 2.9110583E-03 1.4265044E-02 9.9999802E-03 3.6802255E-03 Av 2018 1 23 15 0 0.4907013 1.7538141E-05 1.2351616E-03 3.1742449E-03 8.1672389E-03 9.9999802E-03 2.5277573E-03 Av 2018 1 23 16 0 0.5256723 0.000000 1.2177931E-03 3.5323766E-03 2.4125669E-03 0.000000 9.1685937E-04 - Av 2018 1 23 17 0 0.5285907 1.8350025E-05 1.2007250E-03 3.7377230E-03 5.0201779E-03 9.9999802E-03 0.000000 - Av 2018 1 23 18 0 0.6477181 1.3689620E-04 1.1905913E-03 3.7549373E-03 1.6269792E-02 1.9999960E-02 0.000000 - Av 2018 1 23 19 0 0.8872443 4.9752318E-05 1.2214998E-03 3.7942743E-03 4.4162877E-02 4.9999900E-02 0.000000 - Av 2018 1 23 20 0 0.8054104 4.0520703E-05 1.2470736E-03 3.8286517E-03 1.6300917E-02 9.9999802E-03 0.000000 - Av 2018 1 23 21 0 0.6065118 3.4630466E-05 1.2323448E-03 3.8421613E-03 1.1368449E-02 9.9999802E-03 0.000000 - Av 2018 1 23 22 0 0.9285449 9.4063165E-05 1.2767497E-03 3.8780160E-03 5.0977744E-02 5.9999879E-02 0.000000 - Av 2018 1 23 23 0 0.9358042 1.5781526E-04 1.3262461E-03 3.9222213E-03 2.5488771E-02 1.9999960E-02 0.000000 - Av 2018 1 23 24 0 0.6699251 3.5284083E-05 1.3161078E-03 3.9427029E-03 1.3045406E-02 9.9999802E-03 0.000000 - Av 2018 1 24 1 0 1.685878 2.6766097E-03 1.6072735E-03 3.8942136E-03 0.1305144 0.1499997 0.000000 - Av 2018 1 24 2 0 1.993753 2.2600247E-03 2.0018797E-03 3.9608874E-03 7.7682868E-02 6.9999859E-02 0.000000 - Av 2018 1 24 3 0 1.152510 3.2202493E-05 2.1153104E-03 4.0185358E-03 4.5014352E-02 3.9999921E-02 0.000000 - Av 2018 1 24 4 0 1.498041 1.1716470E-03 2.3189634E-03 4.0768306E-03 9.2482239E-02 9.9999800E-02 0.000000 - Av 2018 1 24 5 0 1.674074 1.7464395E-03 2.5722957E-03 4.1434024E-03 6.4412497E-02 5.9999879E-02 0.000000 - Av 2018 1 24 6 0 1.221787 3.6714275E-05 2.6552405E-03 4.2005526E-03 4.3387607E-02 3.9999921E-02 0.000000 - Av 2018 1 24 7 0 1.323707 5.0096656E-04 2.7617579E-03 4.2591309E-03 6.6045724E-02 6.9999859E-02 0.000000 + Av 2018 1 23 17 0 0.5285907 1.8350025E-05 1.2007250E-03 3.7377230E-03 5.0201779E-03 9.9999802E-03 0.000000 + Av 2018 1 23 18 0 0.6477181 1.3689620E-04 1.1905913E-03 3.7549373E-03 1.6269792E-02 1.9999960E-02 0.000000 + Av 2018 1 23 19 0 0.8872443 4.9752318E-05 1.2214998E-03 3.7942743E-03 4.4162877E-02 4.9999900E-02 0.000000 + Av 2018 1 23 20 0 0.8054104 4.0520703E-05 1.2470736E-03 3.8286517E-03 1.6300917E-02 9.9999802E-03 0.000000 + Av 2018 1 23 21 0 0.6065118 3.4630466E-05 1.2323448E-03 3.8421613E-03 1.1368449E-02 9.9999802E-03 0.000000 + Av 2018 1 23 22 0 0.9285449 9.4063165E-05 1.2767497E-03 3.8780160E-03 5.0977744E-02 5.9999879E-02 0.000000 + Av 2018 1 23 23 0 0.9358042 1.5781526E-04 1.3262461E-03 3.9222213E-03 2.5488771E-02 1.9999960E-02 0.000000 + Av 2018 1 23 24 0 0.6699251 3.5284083E-05 1.3161078E-03 3.9427029E-03 1.3045406E-02 9.9999802E-03 0.000000 + Av 2018 1 24 1 0 1.685878 2.6766097E-03 1.6072735E-03 3.8942136E-03 0.1305144 0.1499997 0.000000 + Av 2018 1 24 2 0 1.993753 2.2600247E-03 2.0018797E-03 3.9608874E-03 7.7682868E-02 6.9999859E-02 0.000000 + Av 2018 1 24 3 0 1.152510 3.2202493E-05 2.1153104E-03 4.0185358E-03 4.5014352E-02 3.9999921E-02 0.000000 + Av 2018 1 24 4 0 1.498041 1.1716470E-03 2.3189634E-03 4.0768306E-03 9.2482239E-02 9.9999800E-02 0.000000 + Av 2018 1 24 5 0 1.674074 1.7464395E-03 2.5722957E-03 4.1434024E-03 6.4412497E-02 5.9999879E-02 0.000000 + Av 2018 1 24 6 0 1.221787 3.6714275E-05 2.6552405E-03 4.2005526E-03 4.3387607E-02 3.9999921E-02 0.000000 + Av 2018 1 24 7 0 1.323707 5.0096656E-04 2.7617579E-03 4.2591309E-03 6.6045724E-02 6.9999859E-02 0.000000 Av 2018 1 24 8 0 1.680340 1.8841212E-03 2.9822306E-03 4.1158935E-03 7.8538358E-02 7.9999842E-02 9.6541626E-04 Av 2018 1 24 9 0 1.323195 3.0496402E-04 3.1101860E-03 3.8106719E-03 3.5824727E-02 2.9999940E-02 2.6084874E-03 Av 2018 1 24 10 0 0.8245123 3.0785013E-05 3.0872547E-03 3.5826182E-03 1.2638091E-02 9.9999802E-03 3.7688504E-03 @@ -592,21 +592,21 @@ Av 2018 1 24 14 0 0.7236009 5.7725094E-05 2.9459947E-03 3.6343439E-03 6.1857025E-03 1.9999960E-02 3.7688504E-03 Av 2018 1 24 15 0 0.9221233 2.9766255E-05 2.9367022E-03 3.9222268E-03 2.9843235E-02 3.9999921E-02 2.6084874E-03 Av 2018 1 24 16 0 1.002054 1.5877967E-04 2.9324256E-03 4.3223044E-03 2.0153586E-02 1.9999960E-02 9.6541626E-04 - Av 2018 1 24 17 0 0.8340920 0.000000 2.8970109E-03 4.5483983E-03 4.6691955E-03 0.000000 0.000000 - Av 2018 1 24 18 0 0.7612574 0.000000 2.8542753E-03 4.5474907E-03 1.5856423E-03 0.000000 0.000000 - Av 2018 1 24 19 0 1.093861 1.4406582E-04 2.8913796E-03 4.5791366E-03 4.6545327E-02 5.9999879E-02 0.000000 - Av 2018 1 24 20 0 1.039660 9.6840552E-07 2.9275930E-03 4.6135848E-03 9.2258258E-03 0.000000 0.000000 - Av 2018 1 24 21 0 0.7410390 0.000000 2.8844543E-03 4.6138465E-03 2.6406674E-03 0.000000 0.000000 - Av 2018 1 24 22 0 0.7832025 0.000000 2.8419041E-03 4.6127718E-03 1.0240019E-03 0.000000 0.000000 - Av 2018 1 24 23 0 0.7480010 0.000000 2.7999815E-03 4.6116398E-03 4.8425328E-04 0.000000 0.000000 - Av 2018 1 24 24 0 0.7492546 0.000000 2.7586774E-03 4.6104514E-03 2.6250549E-04 0.000000 0.000000 - Av 2018 1 25 1 0 0.7337750 0.000000 2.7179825E-03 4.5049558E-03 1.5697173E-04 0.000000 0.000000 - Av 2018 1 25 2 0 0.7253282 0.000000 2.6778879E-03 4.5038550E-03 1.0099000E-04 0.000000 0.000000 - Av 2018 1 25 3 0 0.7221044 0.000000 2.6383849E-03 4.5027025E-03 6.8732028E-05 0.000000 0.000000 - Av 2018 1 25 4 0 0.7173829 0.000000 2.5994645E-03 4.5014988E-03 4.8898917E-05 0.000000 0.000000 - Av 2018 1 25 5 0 0.7133858 0.000000 2.5611185E-03 4.5002447E-03 3.6054214E-05 0.000000 0.000000 - Av 2018 1 25 6 0 0.9835899 7.3717696E-05 2.5769994E-03 4.5286100E-03 3.7496213E-02 4.9999900E-02 0.000000 - Av 2018 1 25 7 0 1.778064 2.2057008E-03 2.8455995E-03 4.5940047E-03 0.1010569 0.1099998 0.000000 + Av 2018 1 24 17 0 0.8340920 0.000000 2.8970109E-03 4.5483983E-03 4.6691955E-03 0.000000 0.000000 + Av 2018 1 24 18 0 0.7612574 0.000000 2.8542753E-03 4.5474907E-03 1.5856423E-03 0.000000 0.000000 + Av 2018 1 24 19 0 1.093861 1.4406582E-04 2.8913796E-03 4.5791366E-03 4.6545327E-02 5.9999879E-02 0.000000 + Av 2018 1 24 20 0 1.039660 9.6840552E-07 2.9275930E-03 4.6135848E-03 9.2258258E-03 0.000000 0.000000 + Av 2018 1 24 21 0 0.7410390 0.000000 2.8844543E-03 4.6138465E-03 2.6406674E-03 0.000000 0.000000 + Av 2018 1 24 22 0 0.7832025 0.000000 2.8419041E-03 4.6127718E-03 1.0240019E-03 0.000000 0.000000 + Av 2018 1 24 23 0 0.7480010 0.000000 2.7999815E-03 4.6116398E-03 4.8425328E-04 0.000000 0.000000 + Av 2018 1 24 24 0 0.7492546 0.000000 2.7586774E-03 4.6104514E-03 2.6250549E-04 0.000000 0.000000 + Av 2018 1 25 1 0 0.7337750 0.000000 2.7179825E-03 4.5049558E-03 1.5697173E-04 0.000000 0.000000 + Av 2018 1 25 2 0 0.7253282 0.000000 2.6778879E-03 4.5038550E-03 1.0099000E-04 0.000000 0.000000 + Av 2018 1 25 3 0 0.7221044 0.000000 2.6383849E-03 4.5027025E-03 6.8732028E-05 0.000000 0.000000 + Av 2018 1 25 4 0 0.7173829 0.000000 2.5994645E-03 4.5014988E-03 4.8898917E-05 0.000000 0.000000 + Av 2018 1 25 5 0 0.7133858 0.000000 2.5611185E-03 4.5002447E-03 3.6054214E-05 0.000000 0.000000 + Av 2018 1 25 6 0 0.9835899 7.3717696E-05 2.5769994E-03 4.5286100E-03 3.7496213E-02 4.9999900E-02 0.000000 + Av 2018 1 25 7 0 1.778064 2.2057008E-03 2.8455995E-03 4.5940047E-03 0.1010569 0.1099998 0.000000 Av 2018 1 25 8 0 1.576632 5.1609951E-04 3.0813231E-03 4.4630305E-03 3.9632142E-02 2.9999940E-02 8.6400204E-04 Av 2018 1 25 9 0 0.8735477 4.0669693E-05 3.0635055E-03 4.1799014E-03 1.4553867E-02 9.9999802E-03 2.2888938E-03 Av 2018 1 25 10 0 0.7908225 0.000000 3.0203336E-03 3.9682817E-03 3.6892868E-03 0.000000 3.2817847E-03 @@ -616,21 +616,21 @@ Av 2018 1 25 14 0 0.7104824 2.5242418E-05 2.8472936E-03 3.9705671E-03 2.5077923E-03 9.9999802E-03 3.2817847E-03 Av 2018 1 25 15 0 0.9200668 3.0153622E-05 2.8383201E-03 4.2190291E-03 2.8768750E-02 3.9999921E-02 2.2888938E-03 Av 2018 1 25 16 0 1.343855 4.4021718E-04 2.9358200E-03 4.5923511E-03 6.2221106E-02 6.9999859E-02 8.6400204E-04 - Av 2018 1 25 17 0 1.116656 1.3664292E-06 2.9997991E-03 4.8193228E-03 1.0701873E-02 0.000000 0.000000 - Av 2018 1 25 18 0 0.9231930 1.3656299E-05 2.9754960E-03 4.8404820E-03 2.5046073E-02 2.9999940E-02 0.000000 - Av 2018 1 25 19 0 1.081319 1.9187733E-04 2.9609932E-03 4.8766630E-03 2.1295432E-02 1.9999960E-02 0.000000 - Av 2018 1 25 20 0 0.8831620 0.000000 2.9268751E-03 4.8914677E-03 4.8579071E-03 0.000000 0.000000 - Av 2018 1 25 21 0 0.7964040 0.000000 2.8836993E-03 4.8898295E-03 1.6340031E-03 0.000000 0.000000 - Av 2018 1 25 22 0 0.7922910 0.000000 2.8411602E-03 4.8881359E-03 7.0314412E-04 0.000000 0.000000 - Av 2018 1 25 23 0 0.8889916 1.8149690E-04 2.8083439E-03 4.9017509E-03 1.3916790E-02 1.9999960E-02 0.000000 - Av 2018 1 25 24 0 0.8758044 0.000000 2.7759667E-03 4.9161143E-03 4.0831249E-03 0.000000 0.000000 - Av 2018 1 26 1 0 0.7676672 0.000000 2.7350166E-03 4.8018713E-03 1.4318272E-03 0.000000 0.000000 - Av 2018 1 26 2 0 0.7684255 0.000000 2.6946708E-03 4.8001609E-03 6.3324417E-04 0.000000 0.000000 - Av 2018 1 26 3 0 0.7549813 0.000000 2.6549203E-03 4.7984016E-03 3.2757156E-04 0.000000 0.000000 - Av 2018 1 26 4 0 0.7968520 4.1558375E-05 2.6178402E-03 4.8045423E-03 6.1420328E-03 9.9999802E-03 0.000000 - Av 2018 1 26 5 0 0.8452662 4.4190772E-05 2.5835137E-03 4.8190956E-03 9.3715712E-03 9.9999802E-03 0.000000 - Av 2018 1 26 6 0 0.8517351 4.4010241E-05 2.5498169E-03 4.8338613E-03 9.9171875E-03 9.9999802E-03 0.000000 - Av 2018 1 26 7 0 0.7966056 0.000000 2.5144008E-03 4.8403637E-03 2.7986150E-03 0.000000 0.000000 + Av 2018 1 25 17 0 1.116656 1.3664292E-06 2.9997991E-03 4.8193228E-03 1.0701873E-02 0.000000 0.000000 + Av 2018 1 25 18 0 0.9231930 1.3656299E-05 2.9754960E-03 4.8404820E-03 2.5046073E-02 2.9999940E-02 0.000000 + Av 2018 1 25 19 0 1.081319 1.9187733E-04 2.9609932E-03 4.8766630E-03 2.1295432E-02 1.9999960E-02 0.000000 + Av 2018 1 25 20 0 0.8831620 0.000000 2.9268751E-03 4.8914677E-03 4.8579071E-03 0.000000 0.000000 + Av 2018 1 25 21 0 0.7964040 0.000000 2.8836993E-03 4.8898295E-03 1.6340031E-03 0.000000 0.000000 + Av 2018 1 25 22 0 0.7922910 0.000000 2.8411602E-03 4.8881359E-03 7.0314412E-04 0.000000 0.000000 + Av 2018 1 25 23 0 0.8889916 1.8149690E-04 2.8083439E-03 4.9017509E-03 1.3916790E-02 1.9999960E-02 0.000000 + Av 2018 1 25 24 0 0.8758044 0.000000 2.7759667E-03 4.9161143E-03 4.0831249E-03 0.000000 0.000000 + Av 2018 1 26 1 0 0.7676672 0.000000 2.7350166E-03 4.8018713E-03 1.4318272E-03 0.000000 0.000000 + Av 2018 1 26 2 0 0.7684255 0.000000 2.6946708E-03 4.8001609E-03 6.3324417E-04 0.000000 0.000000 + Av 2018 1 26 3 0 0.7549813 0.000000 2.6549203E-03 4.7984016E-03 3.2757156E-04 0.000000 0.000000 + Av 2018 1 26 4 0 0.7968520 4.1558375E-05 2.6178402E-03 4.8045423E-03 6.1420328E-03 9.9999802E-03 0.000000 + Av 2018 1 26 5 0 0.8452662 4.4190772E-05 2.5835137E-03 4.8190956E-03 9.3715712E-03 9.9999802E-03 0.000000 + Av 2018 1 26 6 0 0.8517351 4.4010241E-05 2.5498169E-03 4.8338613E-03 9.9171875E-03 9.9999802E-03 0.000000 + Av 2018 1 26 7 0 0.7966056 0.000000 2.5144008E-03 4.8403637E-03 2.7986150E-03 0.000000 0.000000 Av 2018 1 26 8 0 0.7328025 0.000000 2.4773094E-03 4.6453597E-03 1.0711489E-03 0.000000 8.7701750E-04 Av 2018 1 26 9 0 0.6996149 0.000000 2.4407653E-03 4.3348102E-03 5.0211878E-04 0.000000 2.2790446E-03 Av 2018 1 26 10 0 0.6647271 0.000000 2.4047601E-03 4.1206898E-03 2.7051152E-04 0.000000 3.2425632E-03 @@ -640,21 +640,21 @@ Av 2018 1 26 14 0 0.6437029 0.000000 2.2659730E-03 4.1116951E-03 4.9750539E-05 0.000000 3.2425632E-03 Av 2018 1 26 15 0 0.6561582 0.000000 2.2325462E-03 4.3213223E-03 3.6618545E-05 9.9999802E-03 2.2790446E-03 Av 2018 1 26 16 0 0.7708062 5.2405585E-06 2.2108748E-03 4.6446598E-03 1.1893631E-02 2.9999940E-02 8.7701750E-04 - Av 2018 1 26 17 0 0.9021636 1.6007348E-04 2.1975106E-03 4.8683179E-03 1.8122045E-02 1.9999960E-02 0.000000 - Av 2018 1 26 18 0 0.9347689 1.6749691E-04 2.1815174E-03 4.8969276E-03 1.9706212E-02 1.9999960E-02 0.000000 - Av 2018 1 26 19 0 0.8170191 0.000000 2.1577154E-03 4.9104951E-03 4.6272329E-03 0.000000 0.000000 - Av 2018 1 26 20 0 0.7162018 0.000000 2.1258856E-03 4.9078604E-03 1.5748150E-03 0.000000 0.000000 - Av 2018 1 26 21 0 0.8301650 1.6567786E-04 2.1028593E-03 4.9205488E-03 1.4490287E-02 1.9999960E-02 0.000000 - Av 2018 1 26 22 0 1.460168 7.7936955E-04 2.2813901E-03 4.9703578E-03 8.7115109E-02 9.9999800E-02 0.000000 - Av 2018 1 26 23 0 1.844571 2.3673368E-03 2.5672717E-03 5.0423238E-03 7.2845608E-02 6.9999859E-02 0.000000 - Av 2018 1 26 24 0 1.677805 4.0872695E-04 2.7940471E-03 5.1154094E-03 7.9121292E-02 7.9999842E-02 0.000000 - Av 2018 1 27 1 0 1.459761 8.2852348E-04 2.9399060E-03 5.0616125E-03 4.5183945E-02 3.9999921E-02 0.000000 - Av 2018 1 27 2 0 1.186927 1.5079606E-05 2.9594612E-03 5.1116166E-03 3.2355618E-02 2.9999940E-02 0.000000 - Av 2018 1 27 3 0 1.014727 5.0717623E-05 2.9395602E-03 5.1417770E-03 1.4152899E-02 9.9999802E-03 0.000000 - Av 2018 1 27 4 0 0.9251471 4.6644596E-05 2.9011085E-03 5.1575801E-03 1.0928930E-02 9.9999802E-03 0.000000 - Av 2018 1 27 5 0 0.9260039 4.6454861E-05 2.8630109E-03 5.1729931E-03 1.0218748E-02 9.9999802E-03 0.000000 - Av 2018 1 27 6 0 0.8617823 0.000000 2.8231158E-03 5.1797424E-03 2.8476417E-03 0.000000 0.000000 - Av 2018 1 27 7 0 0.8115897 0.000000 2.7814705E-03 5.1774960E-03 1.0856388E-03 0.000000 0.000000 + Av 2018 1 26 17 0 0.9021636 1.6007348E-04 2.1975106E-03 4.8683179E-03 1.8122045E-02 1.9999960E-02 0.000000 + Av 2018 1 26 18 0 0.9347689 1.6749691E-04 2.1815174E-03 4.8969276E-03 1.9706212E-02 1.9999960E-02 0.000000 + Av 2018 1 26 19 0 0.8170191 0.000000 2.1577154E-03 4.9104951E-03 4.6272329E-03 0.000000 0.000000 + Av 2018 1 26 20 0 0.7162018 0.000000 2.1258856E-03 4.9078604E-03 1.5748150E-03 0.000000 0.000000 + Av 2018 1 26 21 0 0.8301650 1.6567786E-04 2.1028593E-03 4.9205488E-03 1.4490287E-02 1.9999960E-02 0.000000 + Av 2018 1 26 22 0 1.460168 7.7936955E-04 2.2813901E-03 4.9703578E-03 8.7115109E-02 9.9999800E-02 0.000000 + Av 2018 1 26 23 0 1.844571 2.3673368E-03 2.5672717E-03 5.0423238E-03 7.2845608E-02 6.9999859E-02 0.000000 + Av 2018 1 26 24 0 1.677805 4.0872695E-04 2.7940471E-03 5.1154094E-03 7.9121292E-02 7.9999842E-02 0.000000 + Av 2018 1 27 1 0 1.459761 8.2852348E-04 2.9399060E-03 5.0616125E-03 4.5183945E-02 3.9999921E-02 0.000000 + Av 2018 1 27 2 0 1.186927 1.5079606E-05 2.9594612E-03 5.1116166E-03 3.2355618E-02 2.9999940E-02 0.000000 + Av 2018 1 27 3 0 1.014727 5.0717623E-05 2.9395602E-03 5.1417770E-03 1.4152899E-02 9.9999802E-03 0.000000 + Av 2018 1 27 4 0 0.9251471 4.6644596E-05 2.9011085E-03 5.1575801E-03 1.0928930E-02 9.9999802E-03 0.000000 + Av 2018 1 27 5 0 0.9260039 4.6454861E-05 2.8630109E-03 5.1729931E-03 1.0218748E-02 9.9999802E-03 0.000000 + Av 2018 1 27 6 0 0.8617823 0.000000 2.8231158E-03 5.1797424E-03 2.8476417E-03 0.000000 0.000000 + Av 2018 1 27 7 0 0.8115897 0.000000 2.7814705E-03 5.1774960E-03 1.0856388E-03 0.000000 0.000000 Av 2018 1 27 8 0 0.7917055 0.000000 2.7404395E-03 4.9498319E-03 5.0757197E-04 0.000000 1.0243985E-03 Av 2018 1 27 9 0 0.7477059 0.000000 2.7000136E-03 4.5981184E-03 2.7294323E-04 0.000000 2.6124311E-03 Av 2018 1 27 10 0 0.7145879 0.000000 2.6601842E-03 4.3590399E-03 1.6225487E-04 0.000000 3.6882644E-03 @@ -664,21 +664,21 @@ Av 2018 1 27 14 0 0.6917187 0.000000 2.5066561E-03 4.3489942E-03 3.6787911E-05 0.000000 3.6882644E-03 Av 2018 1 27 15 0 0.7048386 0.000000 2.4696789E-03 4.5830547E-03 1.8193795E-04 0.000000 2.6124311E-03 Av 2018 1 27 16 0 0.7349716 0.000000 2.4332474E-03 4.9297563E-03 0.000000 0.000000 1.0243985E-03 - Av 2018 1 27 17 0 0.7574947 0.000000 2.3973533E-03 5.1524159E-03 0.000000 0.000000 0.000000 - Av 2018 1 27 18 0 0.7637077 0.000000 2.3619884E-03 5.1496672E-03 0.000000 1.9999960E-02 0.000000 - Av 2018 1 27 19 0 0.8326211 1.7313428E-04 2.3359137E-03 5.1627615E-03 8.6882450E-03 1.9999960E-02 0.000000 - Av 2018 1 27 20 0 0.9888178 1.3305474E-05 2.3299996E-03 5.1989872E-03 2.5861122E-02 2.9999940E-02 0.000000 - Av 2018 1 27 21 0 1.079413 9.1126254E-05 2.3357184E-03 5.2422434E-03 2.9611114E-02 2.9999940E-02 0.000000 - Av 2018 1 27 22 0 1.035198 1.7991713E-04 2.3306594E-03 5.2794758E-03 2.1754820E-02 1.9999960E-02 0.000000 - Av 2018 1 27 23 0 0.9938840 1.7418862E-04 2.3142032E-03 5.3097825E-03 2.0332620E-02 1.9999960E-02 0.000000 - Av 2018 1 27 24 0 0.8758327 0.000000 2.2888631E-03 5.3237327E-03 4.6990020E-03 0.000000 0.000000 - Av 2018 1 28 1 0 0.7617941 0.000000 2.2550987E-03 5.1972419E-03 1.5933164E-03 0.000000 0.000000 - Av 2018 1 28 2 0 0.7608514 0.000000 2.2218325E-03 5.1942645E-03 6.8925787E-04 0.000000 0.000000 - Av 2018 1 28 3 0 0.7478451 0.000000 2.1890569E-03 5.1912507E-03 3.5114115E-04 0.000000 0.000000 - Av 2018 1 28 4 0 0.7442152 0.000000 2.1567650E-03 5.1882006E-03 2.0071164E-04 0.000000 0.000000 - Av 2018 1 28 5 0 0.7391671 0.000000 2.1249491E-03 5.1851165E-03 1.2482204E-04 0.000000 0.000000 - Av 2018 1 28 6 0 0.7354078 0.000000 2.0936029E-03 5.1819971E-03 8.2748295E-05 0.000000 0.000000 - Av 2018 1 28 7 0 0.7316043 0.000000 2.0627191E-03 5.1788446E-03 5.7655885E-05 0.000000 0.000000 + Av 2018 1 27 17 0 0.7574947 0.000000 2.3973533E-03 5.1524159E-03 0.000000 0.000000 0.000000 + Av 2018 1 27 18 0 0.7637077 0.000000 2.3619884E-03 5.1496672E-03 0.000000 1.9999960E-02 0.000000 + Av 2018 1 27 19 0 0.8326211 1.7313428E-04 2.3359137E-03 5.1627615E-03 8.6882450E-03 1.9999960E-02 0.000000 + Av 2018 1 27 20 0 0.9888178 1.3305474E-05 2.3299996E-03 5.1989872E-03 2.5861122E-02 2.9999940E-02 0.000000 + Av 2018 1 27 21 0 1.079413 9.1126254E-05 2.3357184E-03 5.2422434E-03 2.9611114E-02 2.9999940E-02 0.000000 + Av 2018 1 27 22 0 1.035198 1.7991713E-04 2.3306594E-03 5.2794758E-03 2.1754820E-02 1.9999960E-02 0.000000 + Av 2018 1 27 23 0 0.9938840 1.7418862E-04 2.3142032E-03 5.3097825E-03 2.0332620E-02 1.9999960E-02 0.000000 + Av 2018 1 27 24 0 0.8758327 0.000000 2.2888631E-03 5.3237327E-03 4.6990020E-03 0.000000 0.000000 + Av 2018 1 28 1 0 0.7617941 0.000000 2.2550987E-03 5.1972419E-03 1.5933164E-03 0.000000 0.000000 + Av 2018 1 28 2 0 0.7608514 0.000000 2.2218325E-03 5.1942645E-03 6.8925787E-04 0.000000 0.000000 + Av 2018 1 28 3 0 0.7478451 0.000000 2.1890569E-03 5.1912507E-03 3.5114115E-04 0.000000 0.000000 + Av 2018 1 28 4 0 0.7442152 0.000000 2.1567650E-03 5.1882006E-03 2.0071164E-04 0.000000 0.000000 + Av 2018 1 28 5 0 0.7391671 0.000000 2.1249491E-03 5.1851165E-03 1.2482204E-04 0.000000 0.000000 + Av 2018 1 28 6 0 0.7354078 0.000000 2.0936029E-03 5.1819971E-03 8.2748295E-05 0.000000 0.000000 + Av 2018 1 28 7 0 0.7316043 0.000000 2.0627191E-03 5.1788446E-03 5.7655885E-05 0.000000 0.000000 Av 2018 1 28 8 0 0.7062654 0.000000 2.0322907E-03 4.8588915E-03 4.1799070E-05 0.000000 1.4398530E-03 Av 2018 1 28 9 0 0.6569508 0.000000 2.0023112E-03 4.3793088E-03 1.9642356E-04 0.000000 3.6051469E-03 Av 2018 1 28 10 0 0.6147618 0.000000 1.9727738E-03 4.0580784E-03 0.000000 0.000000 5.0505144E-03 @@ -688,21 +688,21 @@ Av 2018 1 28 14 0 0.5948862 0.000000 1.8589181E-03 4.0447745E-03 0.000000 0.000000 5.0505144E-03 Av 2018 1 28 15 0 0.6134736 0.000000 1.8314961E-03 4.3593557E-03 0.000000 0.000000 3.6051469E-03 Av 2018 1 28 16 0 0.6574109 0.000000 1.8044787E-03 4.8322934E-03 0.000000 0.000000 1.4398530E-03 - Av 2018 1 28 17 0 0.6925067 0.000000 1.7778599E-03 5.1456057E-03 0.000000 0.000000 0.000000 - Av 2018 1 28 18 0 0.6980104 0.000000 1.7516337E-03 5.1421234E-03 0.000000 0.000000 0.000000 - Av 2018 1 28 19 0 0.6920841 0.000000 1.7257944E-03 5.1386142E-03 0.000000 0.000000 0.000000 - Av 2018 1 28 20 0 0.6901808 0.000000 1.7003362E-03 5.1350789E-03 0.000000 0.000000 0.000000 - Av 2018 1 28 21 0 0.6869265 0.000000 1.6752536E-03 5.1315175E-03 0.000000 0.000000 0.000000 - Av 2018 1 28 22 0 0.6841891 0.000000 1.6505410E-03 5.1279319E-03 0.000000 0.000000 0.000000 - Av 2018 1 28 23 0 0.6813185 0.000000 1.6261928E-03 5.1243212E-03 0.000000 0.000000 0.000000 - Av 2018 1 28 24 0 0.6785401 0.000000 1.6022039E-03 5.1206858E-03 0.000000 0.000000 0.000000 - Av 2018 1 29 1 0 0.6677581 0.000000 1.5785689E-03 4.9990364E-03 0.000000 0.000000 0.000000 - Av 2018 1 29 2 0 0.6598213 0.000000 1.5552825E-03 4.9956157E-03 0.000000 0.000000 0.000000 - Av 2018 1 29 3 0 0.6589736 0.000000 1.5323397E-03 4.9921726E-03 0.000000 0.000000 0.000000 - Av 2018 1 29 4 0 0.6557043 0.000000 1.5097354E-03 4.9887067E-03 0.000000 0.000000 0.000000 - Av 2018 1 29 5 0 0.6533195 0.000000 1.4874644E-03 4.9852189E-03 0.000000 0.000000 0.000000 - Av 2018 1 29 6 0 0.6506692 0.000000 1.4655220E-03 4.9817092E-03 0.000000 0.000000 0.000000 - Av 2018 1 29 7 0 0.6481526 0.000000 1.4439032E-03 4.9781781E-03 0.000000 0.000000 0.000000 + Av 2018 1 28 17 0 0.6925067 0.000000 1.7778599E-03 5.1456057E-03 0.000000 0.000000 0.000000 + Av 2018 1 28 18 0 0.6980104 0.000000 1.7516337E-03 5.1421234E-03 0.000000 0.000000 0.000000 + Av 2018 1 28 19 0 0.6920841 0.000000 1.7257944E-03 5.1386142E-03 0.000000 0.000000 0.000000 + Av 2018 1 28 20 0 0.6901808 0.000000 1.7003362E-03 5.1350789E-03 0.000000 0.000000 0.000000 + Av 2018 1 28 21 0 0.6869265 0.000000 1.6752536E-03 5.1315175E-03 0.000000 0.000000 0.000000 + Av 2018 1 28 22 0 0.6841891 0.000000 1.6505410E-03 5.1279319E-03 0.000000 0.000000 0.000000 + Av 2018 1 28 23 0 0.6813185 0.000000 1.6261928E-03 5.1243212E-03 0.000000 0.000000 0.000000 + Av 2018 1 28 24 0 0.6785401 0.000000 1.6022039E-03 5.1206858E-03 0.000000 0.000000 0.000000 + Av 2018 1 29 1 0 0.6677581 0.000000 1.5785689E-03 4.9990364E-03 0.000000 0.000000 0.000000 + Av 2018 1 29 2 0 0.6598213 0.000000 1.5552825E-03 4.9956157E-03 0.000000 0.000000 0.000000 + Av 2018 1 29 3 0 0.6589736 0.000000 1.5323397E-03 4.9921726E-03 0.000000 0.000000 0.000000 + Av 2018 1 29 4 0 0.6557043 0.000000 1.5097354E-03 4.9887067E-03 0.000000 0.000000 0.000000 + Av 2018 1 29 5 0 0.6533195 0.000000 1.4874644E-03 4.9852189E-03 0.000000 0.000000 0.000000 + Av 2018 1 29 6 0 0.6506692 0.000000 1.4655220E-03 4.9817092E-03 0.000000 0.000000 0.000000 + Av 2018 1 29 7 0 0.6481526 0.000000 1.4439032E-03 4.9781781E-03 0.000000 0.000000 0.000000 Av 2018 1 29 8 0 0.6262124 0.000000 1.4226035E-03 4.6920991E-03 0.000000 0.000000 1.2842142E-03 Av 2018 1 29 9 0 0.5827451 0.000000 1.4016178E-03 4.2762039E-03 0.000000 0.000000 3.1584054E-03 Av 2018 1 29 10 0 0.5476259 0.000000 1.3809417E-03 4.0015527E-03 0.000000 0.000000 4.3904893E-03 @@ -712,21 +712,21 @@ Av 2018 1 29 14 0 0.5350683 0.000000 1.3012427E-03 3.9869868E-03 0.000000 9.9999802E-03 4.3904893E-03 Av 2018 1 29 15 0 0.5530595 5.3888118E-07 1.2820747E-03 4.2554121E-03 0.000000 1.9999960E-02 3.1584054E-03 Av 2018 1 29 16 0 1.283491 1.1765050E-03 1.4973371E-03 4.7011902E-03 8.4848255E-02 0.1199998 1.2842142E-03 - 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Av 2018 1 30 3 0 0.7260689 0.000000 2.1073937E-03 5.0597931E-03 3.2715368E-04 0.000000 0.000000 - Av 2018 1 30 4 0 0.7226816 0.000000 2.0763061E-03 5.0569689E-03 1.8911096E-04 0.000000 0.000000 - Av 2018 1 30 5 0 0.7178629 0.000000 2.0456773E-03 5.0541083E-03 1.1859881E-04 0.000000 0.000000 - Av 2018 1 30 6 0 0.7142687 0.000000 2.0155003E-03 5.0512129E-03 7.9132828E-05 0.000000 0.000000 - Av 2018 1 30 7 0 0.7106230 0.000000 1.9857686E-03 5.0482834E-03 5.5419230E-05 0.000000 0.000000 + Av 2018 1 29 17 0 1.883273 2.8179015E-03 1.8516462E-03 5.0550280E-03 8.0607526E-02 7.9999842E-02 0.000000 + Av 2018 1 29 18 0 1.823492 8.3391176E-04 2.1768038E-03 5.1270761E-03 9.7747229E-02 9.9999800E-02 0.000000 + Av 2018 1 29 19 0 1.219048 5.4369152E-06 2.3537057E-03 5.1662694E-03 1.4149946E-02 0.000000 0.000000 + Av 2018 1 29 20 0 0.7167690 0.000000 2.3192610E-03 5.1668012E-03 3.6144583E-03 0.000000 0.000000 + Av 2018 1 29 21 0 0.7989510 0.000000 2.2850481E-03 5.1640277E-03 1.3043988E-03 0.000000 0.000000 + Av 2018 1 29 22 0 0.7448176 0.000000 2.2513401E-03 5.1612128E-03 5.8794441E-04 0.000000 0.000000 + Av 2018 1 29 23 0 0.8613567 1.7877120E-04 2.2272530E-03 5.1741465E-03 1.3823263E-02 1.9999960E-02 0.000000 + Av 2018 1 29 24 0 0.8430924 0.000000 2.2034764E-03 5.1881876E-03 4.0726690E-03 0.000000 0.000000 + Av 2018 1 30 1 0 0.7381168 0.000000 2.1709716E-03 5.0653322E-03 1.4290296E-03 0.000000 0.000000 + Av 2018 1 30 2 0 0.7383235 0.000000 2.1389464E-03 5.0625810E-03 6.3226046E-04 0.000000 0.000000 + Av 2018 1 30 3 0 0.7260689 0.000000 2.1073937E-03 5.0597931E-03 3.2715368E-04 0.000000 0.000000 + Av 2018 1 30 4 0 0.7226816 0.000000 2.0763061E-03 5.0569689E-03 1.8911096E-04 0.000000 0.000000 + Av 2018 1 30 5 0 0.7178629 0.000000 2.0456773E-03 5.0541083E-03 1.1859881E-04 0.000000 0.000000 + Av 2018 1 30 6 0 0.7142687 0.000000 2.0155003E-03 5.0512129E-03 7.9132828E-05 0.000000 0.000000 + Av 2018 1 30 7 0 0.7106230 0.000000 1.9857686E-03 5.0482834E-03 5.5419230E-05 0.000000 0.000000 Av 2018 1 30 8 0 0.6904846 0.000000 1.9564754E-03 4.8020096E-03 4.0343581E-05 0.000000 1.1059542E-03 Av 2018 1 30 9 0 0.6536356 0.000000 1.9276142E-03 4.4542770E-03 1.9229148E-04 0.000000 2.6729351E-03 Av 2018 1 30 10 0 0.6228609 0.000000 1.8991788E-03 4.2281672E-03 0.000000 0.000000 3.6869391E-03 @@ -736,21 +736,21 @@ Av 2018 1 30 14 0 0.6054006 0.000000 1.7895709E-03 4.2157387E-03 0.000000 0.000000 3.6869391E-03 Av 2018 1 30 15 0 0.6176338 0.000000 1.7631719E-03 4.4356375E-03 0.000000 0.000000 2.6729351E-03 Av 2018 1 30 16 0 0.6483931 0.000000 1.7371624E-03 4.7771623E-03 0.000000 0.000000 1.1059542E-03 - Av 2018 1 30 17 0 0.6741517 0.000000 1.7115364E-03 5.0172326E-03 0.000000 0.000000 0.000000 - Av 2018 1 30 18 0 0.6780168 0.000000 1.6862885E-03 5.0139655E-03 0.000000 0.000000 0.000000 - Av 2018 1 30 19 0 0.6728214 0.000000 1.6614131E-03 5.0106714E-03 0.000000 0.000000 0.000000 - Av 2018 1 30 20 0 0.6708231 0.000000 1.6369047E-03 5.0073504E-03 0.000000 0.000000 0.000000 - Av 2018 1 30 21 0 0.6677590 0.000000 1.6127577E-03 5.0040032E-03 0.000000 0.000000 0.000000 - Av 2018 1 30 22 0 0.6651107 0.000000 1.5889669E-03 5.0006304E-03 0.000000 0.000000 0.000000 - Av 2018 1 30 23 0 0.6623625 0.000000 1.5655272E-03 4.9972320E-03 0.000000 0.000000 0.000000 - Av 2018 1 30 24 0 0.6596929 0.000000 1.5424333E-03 4.9938089E-03 0.000000 0.000000 0.000000 - Av 2018 1 31 1 0 0.6492377 0.000000 1.5196799E-03 4.8755393E-03 0.000000 0.000000 0.000000 - Av 2018 1 31 2 0 0.6415495 0.000000 1.4972623E-03 4.8723198E-03 0.000000 0.000000 0.000000 - Av 2018 1 31 3 0 0.6407598 0.000000 1.4751753E-03 4.8690769E-03 0.000000 0.000000 0.000000 - Av 2018 1 31 4 0 0.6376129 0.000000 1.4534141E-03 4.8658107E-03 0.000000 0.000000 0.000000 - Av 2018 1 31 5 0 0.6353264 0.000000 1.4319740E-03 4.8625218E-03 0.000000 0.000000 0.000000 - Av 2018 1 31 6 0 0.6327811 0.000000 1.4108501E-03 4.8592109E-03 0.000000 0.000000 0.000000 - Av 2018 1 31 7 0 0.6303654 0.000000 1.3900379E-03 4.8558777E-03 0.000000 0.000000 0.000000 + Av 2018 1 30 17 0 0.6741517 0.000000 1.7115364E-03 5.0172326E-03 0.000000 0.000000 0.000000 + Av 2018 1 30 18 0 0.6780168 0.000000 1.6862885E-03 5.0139655E-03 0.000000 0.000000 0.000000 + Av 2018 1 30 19 0 0.6728214 0.000000 1.6614131E-03 5.0106714E-03 0.000000 0.000000 0.000000 + Av 2018 1 30 20 0 0.6708231 0.000000 1.6369047E-03 5.0073504E-03 0.000000 0.000000 0.000000 + Av 2018 1 30 21 0 0.6677590 0.000000 1.6127577E-03 5.0040032E-03 0.000000 0.000000 0.000000 + Av 2018 1 30 22 0 0.6651107 0.000000 1.5889669E-03 5.0006304E-03 0.000000 0.000000 0.000000 + Av 2018 1 30 23 0 0.6623625 0.000000 1.5655272E-03 4.9972320E-03 0.000000 0.000000 0.000000 + Av 2018 1 30 24 0 0.6596929 0.000000 1.5424333E-03 4.9938089E-03 0.000000 0.000000 0.000000 + Av 2018 1 31 1 0 0.6492377 0.000000 1.5196799E-03 4.8755393E-03 0.000000 0.000000 0.000000 + Av 2018 1 31 2 0 0.6415495 0.000000 1.4972623E-03 4.8723198E-03 0.000000 0.000000 0.000000 + Av 2018 1 31 3 0 0.6407598 0.000000 1.4751753E-03 4.8690769E-03 0.000000 0.000000 0.000000 + Av 2018 1 31 4 0 0.6376129 0.000000 1.4534141E-03 4.8658107E-03 0.000000 0.000000 0.000000 + Av 2018 1 31 5 0 0.6353264 0.000000 1.4319740E-03 4.8625218E-03 0.000000 0.000000 0.000000 + Av 2018 1 31 6 0 0.6327811 0.000000 1.4108501E-03 4.8592109E-03 0.000000 0.000000 0.000000 + Av 2018 1 31 7 0 0.6303654 0.000000 1.3900379E-03 4.8558777E-03 0.000000 0.000000 0.000000 Av 2018 1 31 8 0 0.6120033 0.000000 1.3695327E-03 4.6205590E-03 0.000000 0.000000 1.0543842E-03 Av 2018 1 31 9 0 0.5773009 0.000000 1.3493298E-03 4.2979759E-03 0.000000 0.000000 2.5053269E-03 Av 2018 1 31 10 0 0.5503144 0.000000 1.3294250E-03 4.0913555E-03 0.000000 0.000000 3.4290773E-03 @@ -760,21 +760,21 @@ Av 2018 1 31 14 0 0.5372451 0.000000 1.2526994E-03 4.0775733E-03 0.000000 0.000000 3.4290773E-03 Av 2018 1 31 15 0 0.5488988 0.000000 1.2342202E-03 4.2773047E-03 0.000000 0.000000 2.5053269E-03 Av 2018 1 31 16 0 0.5777451 0.000000 1.2160136E-03 4.5930003E-03 0.000000 0.000000 1.0543842E-03 - Av 2018 1 31 17 0 0.6026236 0.000000 1.1980754E-03 4.8214342E-03 0.000000 0.000000 0.000000 - Av 2018 1 31 18 0 0.6070030 0.000000 1.1804019E-03 4.8178863E-03 0.000000 0.000000 0.000000 - Av 2018 1 31 19 0 0.6026130 0.000000 1.1629891E-03 4.8143207E-03 0.000000 0.000000 0.000000 - Av 2018 1 31 20 0 0.6013050 0.000000 1.1458332E-03 4.8107379E-03 0.000000 0.000000 0.000000 - Av 2018 1 31 21 0 0.5989577 0.000000 1.1289304E-03 4.8071379E-03 0.000000 0.000000 0.000000 - Av 2018 1 31 22 0 0.5970036 0.000000 1.1122769E-03 4.8035216E-03 0.000000 0.000000 0.000000 - Av 2018 1 31 23 0 0.5949442 0.000000 1.0958691E-03 4.7998889E-03 0.000000 0.000000 0.000000 - Av 2018 1 31 24 0 0.5929523 0.000000 1.0797033E-03 4.7962400E-03 0.000000 0.000000 0.000000 - Av 2018 2 1 1 0 0.5835149 0.000000 1.0637761E-03 4.6828897E-03 0.000000 0.000000 0.000000 - Av 2018 2 1 2 0 0.5767129 0.000000 1.0480836E-03 4.6794503E-03 0.000000 0.000000 0.000000 - Av 2018 2 1 3 0 0.5764930 0.000000 1.0326228E-03 4.6759960E-03 0.000000 0.000000 0.000000 - Av 2018 2 1 4 0 0.5740136 0.000000 1.0173901E-03 4.6725268E-03 0.000000 0.000000 0.000000 - Av 2018 2 1 5 0 0.5723485 0.000000 1.0023819E-03 4.6690428E-03 0.000000 0.000000 0.000000 - Av 2018 2 1 6 0 0.5704286 0.000000 9.8759518E-04 4.6655443E-03 0.000000 0.000000 0.000000 - Av 2018 2 1 7 0 0.5686253 0.000000 9.7302662E-04 4.6620313E-03 0.000000 0.000000 0.000000 + Av 2018 1 31 17 0 0.6026236 0.000000 1.1980754E-03 4.8214342E-03 0.000000 0.000000 0.000000 + Av 2018 1 31 18 0 0.6070030 0.000000 1.1804019E-03 4.8178863E-03 0.000000 0.000000 0.000000 + Av 2018 1 31 19 0 0.6026130 0.000000 1.1629891E-03 4.8143207E-03 0.000000 0.000000 0.000000 + Av 2018 1 31 20 0 0.6013050 0.000000 1.1458332E-03 4.8107379E-03 0.000000 0.000000 0.000000 + Av 2018 1 31 21 0 0.5989577 0.000000 1.1289304E-03 4.8071379E-03 0.000000 0.000000 0.000000 + Av 2018 1 31 22 0 0.5970036 0.000000 1.1122769E-03 4.8035216E-03 0.000000 0.000000 0.000000 + Av 2018 1 31 23 0 0.5949442 0.000000 1.0958691E-03 4.7998889E-03 0.000000 0.000000 0.000000 + Av 2018 1 31 24 0 0.5929523 0.000000 1.0797033E-03 4.7962400E-03 0.000000 0.000000 0.000000 + Av 2018 2 1 1 0 0.5835149 0.000000 1.0637761E-03 4.6828897E-03 0.000000 0.000000 0.000000 + Av 2018 2 1 2 0 0.5767129 0.000000 1.0480836E-03 4.6794503E-03 0.000000 0.000000 0.000000 + Av 2018 2 1 3 0 0.5764930 0.000000 1.0326228E-03 4.6759960E-03 0.000000 0.000000 0.000000 + Av 2018 2 1 4 0 0.5740136 0.000000 1.0173901E-03 4.6725268E-03 0.000000 0.000000 0.000000 + Av 2018 2 1 5 0 0.5723485 0.000000 1.0023819E-03 4.6690428E-03 0.000000 0.000000 0.000000 + Av 2018 2 1 6 0 0.5704286 0.000000 9.8759518E-04 4.6655443E-03 0.000000 0.000000 0.000000 + Av 2018 2 1 7 0 0.5686253 0.000000 9.7302662E-04 4.6620313E-03 0.000000 0.000000 0.000000 Av 2018 2 1 8 0 0.5493590 0.000000 9.5867302E-04 4.4044275E-03 0.000000 0.000000 1.1548953E-03 Av 2018 2 1 9 0 0.5125375 0.000000 9.4453106E-04 4.0562632E-03 0.000000 0.000000 2.7213660E-03 Av 2018 2 1 10 0 0.4843789 0.000000 9.3059771E-04 3.8351240E-03 0.000000 0.000000 3.7103889E-03 @@ -784,21 +784,21 @@ Av 2018 2 1 14 0 0.4772497 0.000000 8.7688974E-04 3.8207765E-03 0.000000 1.9999960E-02 3.7103889E-03 Av 2018 2 1 15 0 0.4880873 0.000000 8.6395425E-04 4.0347427E-03 0.000000 0.000000 2.7213660E-03 Av 2018 2 1 16 0 0.5207224 0.000000 8.5120957E-04 4.3757362E-03 0.000000 1.9999960E-02 1.1548953E-03 - Av 2018 2 1 17 0 0.5729140 1.3389533E-04 8.4550562E-04 4.6405965E-03 1.3806984E-03 2.9999940E-02 0.000000 - Av 2018 2 1 18 0 0.6849232 1.4367934E-04 8.4720866E-04 4.6674712E-03 1.4771973E-02 1.9999960E-02 0.000000 - Av 2018 2 1 19 0 0.6535602 0.000000 8.4203132E-04 4.6799267E-03 4.1757626E-03 0.000000 0.000000 - Av 2018 2 1 20 0 0.5602914 0.000000 8.2961004E-04 4.6761734E-03 1.4565276E-03 0.000000 0.000000 - Av 2018 2 1 21 0 0.6140440 3.5793280E-05 8.1920566E-04 4.6803905E-03 6.9389008E-03 9.9999802E-03 0.000000 - Av 2018 2 1 22 0 0.6013445 0.000000 8.0894557E-04 4.6852846E-03 2.4537784E-03 0.000000 0.000000 - Av 2018 2 1 23 0 0.5596842 0.000000 7.9701236E-04 4.6814717E-03 9.6724310E-04 0.000000 0.000000 - Av 2018 2 1 24 0 0.5585117 0.000000 7.8525522E-04 4.6776487E-03 4.6248763E-04 0.000000 0.000000 - Av 2018 2 2 1 0 0.5447133 0.000000 7.7367149E-04 4.5671859E-03 2.5266752E-04 0.000000 0.000000 - Av 2018 2 2 2 0 0.5380890 0.000000 7.6225860E-04 4.5635886E-03 1.5195587E-04 0.000000 0.000000 - Av 2018 2 2 3 0 0.5373147 0.000000 7.5101410E-04 4.5599937E-03 9.8188524E-05 0.000000 0.000000 - Av 2018 2 2 4 0 0.5350010 0.000000 7.3993544E-04 4.5563886E-03 6.7052220E-05 0.000000 0.000000 - Av 2018 2 2 5 0 0.5334785 0.000000 7.2902022E-04 4.5527732E-03 4.7833077E-05 0.000000 0.000000 - Av 2018 2 2 6 0 0.5318282 0.000000 7.1826600E-04 4.5491476E-03 3.5346129E-05 0.000000 0.000000 - Av 2018 2 2 7 0 0.5313399 0.000000 7.0767046E-04 4.5455117E-03 1.7762635E-04 0.000000 0.000000 + Av 2018 2 1 17 0 0.5729140 1.3389533E-04 8.4550562E-04 4.6405965E-03 1.3806984E-03 2.9999940E-02 0.000000 + Av 2018 2 1 18 0 0.6849232 1.4367934E-04 8.4720866E-04 4.6674712E-03 1.4771973E-02 1.9999960E-02 0.000000 + Av 2018 2 1 19 0 0.6535602 0.000000 8.4203132E-04 4.6799267E-03 4.1757626E-03 0.000000 0.000000 + Av 2018 2 1 20 0 0.5602914 0.000000 8.2961004E-04 4.6761734E-03 1.4565276E-03 0.000000 0.000000 + Av 2018 2 1 21 0 0.6140440 3.5793280E-05 8.1920566E-04 4.6803905E-03 6.9389008E-03 9.9999802E-03 0.000000 + Av 2018 2 1 22 0 0.6013445 0.000000 8.0894557E-04 4.6852846E-03 2.4537784E-03 0.000000 0.000000 + Av 2018 2 1 23 0 0.5596842 0.000000 7.9701236E-04 4.6814717E-03 9.6724310E-04 0.000000 0.000000 + Av 2018 2 1 24 0 0.5585117 0.000000 7.8525522E-04 4.6776487E-03 4.6248763E-04 0.000000 0.000000 + Av 2018 2 2 1 0 0.5447133 0.000000 7.7367149E-04 4.5671859E-03 2.5266752E-04 0.000000 0.000000 + Av 2018 2 2 2 0 0.5380890 0.000000 7.6225860E-04 4.5635886E-03 1.5195587E-04 0.000000 0.000000 + Av 2018 2 2 3 0 0.5373147 0.000000 7.5101410E-04 4.5599937E-03 9.8188524E-05 0.000000 0.000000 + Av 2018 2 2 4 0 0.5350010 0.000000 7.3993544E-04 4.5563886E-03 6.7052220E-05 0.000000 0.000000 + Av 2018 2 2 5 0 0.5334785 0.000000 7.2902022E-04 4.5527732E-03 4.7833077E-05 0.000000 0.000000 + Av 2018 2 2 6 0 0.5318282 0.000000 7.1826600E-04 4.5491476E-03 3.5346129E-05 0.000000 0.000000 + Av 2018 2 2 7 0 0.5313399 0.000000 7.0767046E-04 4.5455117E-03 1.7762635E-04 0.000000 0.000000 Av 2018 2 2 8 0 0.5079587 0.000000 6.9723121E-04 4.2303577E-03 0.000000 0.000000 1.4159492E-03 Av 2018 2 2 9 0 0.4634224 0.000000 6.8694592E-04 3.8160835E-03 0.000000 0.000000 3.2824003E-03 Av 2018 2 2 10 0 0.4313948 0.000000 6.7681237E-04 3.5575544E-03 0.000000 0.000000 4.4408767E-03 @@ -808,21 +808,21 @@ Av 2018 2 2 14 0 0.4210006 0.000000 6.3775131E-04 3.5428065E-03 0.000000 0.000000 4.4408767E-03 Av 2018 2 2 15 0 0.4370531 0.000000 6.2834343E-04 3.7939623E-03 0.000000 0.000000 3.2824003E-03 Av 2018 2 2 16 0 0.4753284 0.000000 6.1907439E-04 4.2008641E-03 0.000000 0.000000 1.4159492E-03 - Av 2018 2 2 17 0 0.5097852 0.000000 6.0994201E-04 4.5086467E-03 0.000000 0.000000 0.000000 - Av 2018 2 2 18 0 0.5174357 0.000000 6.0094445E-04 4.5049130E-03 0.000000 0.000000 0.000000 - Av 2018 2 2 19 0 0.5130540 0.000000 5.9207954E-04 4.5011709E-03 0.000000 0.000000 0.000000 - Av 2018 2 2 20 0 0.5128728 0.000000 5.8334548E-04 4.4974210E-03 0.000000 0.000000 0.000000 - Av 2018 2 2 21 0 0.5112476 0.000000 5.7474017E-04 4.4936636E-03 0.000000 0.000000 0.000000 - Av 2018 2 2 22 0 0.5101408 0.000000 5.6626182E-04 4.4898982E-03 0.000000 0.000000 0.000000 - Av 2018 2 2 23 0 0.5088699 0.000000 5.5790856E-04 4.4861259E-03 0.000000 0.000000 0.000000 - Av 2018 2 2 24 0 0.5076720 0.000000 5.4967857E-04 4.4823461E-03 0.000000 0.000000 0.000000 - Av 2018 2 3 1 0 0.4995634 0.000000 5.4156996E-04 4.3769921E-03 0.000000 0.000000 0.000000 - Av 2018 2 3 2 0 0.4938881 0.000000 5.3358090E-04 4.3734200E-03 0.000000 0.000000 0.000000 - Av 2018 2 3 3 0 0.4942980 0.000000 5.2570977E-04 4.3698410E-03 0.000000 0.000000 0.000000 - Av 2018 2 3 4 0 0.4926069 0.000000 5.1795476E-04 4.3662544E-03 0.000000 0.000000 0.000000 - Av 2018 2 3 5 0 0.4916610 0.000000 5.1031413E-04 4.3626614E-03 0.000000 0.000000 0.000000 - Av 2018 2 3 6 0 0.4904706 0.000000 5.0278619E-04 4.3590614E-03 0.000000 0.000000 0.000000 - Av 2018 2 3 7 0 0.4893795 0.000000 4.9536931E-04 4.3554548E-03 0.000000 0.000000 0.000000 + Av 2018 2 2 17 0 0.5097852 0.000000 6.0994201E-04 4.5086467E-03 0.000000 0.000000 0.000000 + Av 2018 2 2 18 0 0.5174357 0.000000 6.0094445E-04 4.5049130E-03 0.000000 0.000000 0.000000 + Av 2018 2 2 19 0 0.5130540 0.000000 5.9207954E-04 4.5011709E-03 0.000000 0.000000 0.000000 + Av 2018 2 2 20 0 0.5128728 0.000000 5.8334548E-04 4.4974210E-03 0.000000 0.000000 0.000000 + Av 2018 2 2 21 0 0.5112476 0.000000 5.7474017E-04 4.4936636E-03 0.000000 0.000000 0.000000 + Av 2018 2 2 22 0 0.5101408 0.000000 5.6626182E-04 4.4898982E-03 0.000000 0.000000 0.000000 + Av 2018 2 2 23 0 0.5088699 0.000000 5.5790856E-04 4.4861259E-03 0.000000 0.000000 0.000000 + Av 2018 2 2 24 0 0.5076720 0.000000 5.4967857E-04 4.4823461E-03 0.000000 0.000000 0.000000 + Av 2018 2 3 1 0 0.4995634 0.000000 5.4156996E-04 4.3769921E-03 0.000000 0.000000 0.000000 + Av 2018 2 3 2 0 0.4938881 0.000000 5.3358090E-04 4.3734200E-03 0.000000 0.000000 0.000000 + Av 2018 2 3 3 0 0.4942980 0.000000 5.2570977E-04 4.3698410E-03 0.000000 0.000000 0.000000 + Av 2018 2 3 4 0 0.4926069 0.000000 5.1795476E-04 4.3662544E-03 0.000000 0.000000 0.000000 + Av 2018 2 3 5 0 0.4916610 0.000000 5.1031413E-04 4.3626614E-03 0.000000 0.000000 0.000000 + Av 2018 2 3 6 0 0.4904706 0.000000 5.0278619E-04 4.3590614E-03 0.000000 0.000000 0.000000 + Av 2018 2 3 7 0 0.4893795 0.000000 4.9536931E-04 4.3554548E-03 0.000000 0.000000 0.000000 Av 2018 2 3 8 0 0.4639218 0.000000 4.8806181E-04 3.9970810E-03 0.000000 0.000000 1.6125501E-03 Av 2018 2 3 9 0 0.4157785 0.000000 4.8086213E-04 3.5388172E-03 0.000000 0.000000 3.6791130E-03 Av 2018 2 3 10 0 0.3809034 0.000000 4.7376868E-04 3.2579280E-03 0.000000 0.000000 4.9394011E-03 @@ -832,21 +832,21 @@ Av 2018 2 3 14 0 0.3714097 0.000000 4.4642587E-04 3.2433639E-03 0.000000 0.000000 4.9394011E-03 Av 2018 2 3 15 0 0.3905798 0.000000 4.3984037E-04 3.5169711E-03 0.000000 9.9999802E-03 3.6791130E-03 Av 2018 2 3 16 0 0.4326829 0.000000 4.3335202E-04 3.9679538E-03 0.000000 0.000000 1.6125501E-03 - Av 2018 2 3 17 0 0.4708380 0.000000 4.2695939E-04 4.3190480E-03 0.000000 0.000000 0.000000 - Av 2018 2 3 18 0 0.4805361 0.000000 4.2066109E-04 4.3153758E-03 0.000000 0.000000 0.000000 - Av 2018 2 3 19 0 0.4758151 0.000000 4.1445566E-04 4.3116985E-03 0.000000 0.000000 0.000000 - Av 2018 2 3 20 0 0.4761195 0.000000 4.0834179E-04 4.3080156E-03 0.000000 0.000000 0.000000 - Av 2018 2 3 21 0 0.4746881 0.000000 4.0231811E-04 4.3043275E-03 0.000000 0.000000 0.000000 - Av 2018 2 3 22 0 0.4738718 0.000000 3.9638329E-04 4.3006344E-03 0.000000 0.000000 0.000000 - Av 2018 2 3 23 0 0.4728529 0.000000 3.9053601E-04 4.2969361E-03 0.000000 0.000000 0.000000 - Av 2018 2 3 24 0 0.4719157 0.000000 3.8477499E-04 4.2932336E-03 0.000000 0.000000 0.000000 - Av 2018 2 4 1 0 0.4643925 0.000000 3.7909896E-04 4.1928519E-03 0.000000 0.000000 0.000000 - Av 2018 2 4 2 0 0.4591843 0.000000 3.7350666E-04 4.1893488E-03 0.000000 0.000000 0.000000 - Av 2018 2 4 3 0 0.4597646 0.000000 3.6799686E-04 4.1858410E-03 0.000000 0.000000 0.000000 - Av 2018 2 4 4 0 0.4583427 0.000000 3.6256833E-04 4.1823285E-03 0.000000 0.000000 0.000000 - Av 2018 2 4 5 0 0.4576272 0.000000 3.5721989E-04 4.1788113E-03 0.000000 0.000000 0.000000 - Av 2018 2 4 6 0 0.4566763 0.000000 3.5195032E-04 4.1752895E-03 0.000000 0.000000 0.000000 - Av 2018 2 4 7 0 0.4558173 0.000000 3.4675849E-04 4.1717635E-03 0.000000 0.000000 0.000000 + Av 2018 2 3 17 0 0.4708380 0.000000 4.2695939E-04 4.3190480E-03 0.000000 0.000000 0.000000 + Av 2018 2 3 18 0 0.4805361 0.000000 4.2066109E-04 4.3153758E-03 0.000000 0.000000 0.000000 + Av 2018 2 3 19 0 0.4758151 0.000000 4.1445566E-04 4.3116985E-03 0.000000 0.000000 0.000000 + Av 2018 2 3 20 0 0.4761195 0.000000 4.0834179E-04 4.3080156E-03 0.000000 0.000000 0.000000 + Av 2018 2 3 21 0 0.4746881 0.000000 4.0231811E-04 4.3043275E-03 0.000000 0.000000 0.000000 + Av 2018 2 3 22 0 0.4738718 0.000000 3.9638329E-04 4.3006344E-03 0.000000 0.000000 0.000000 + Av 2018 2 3 23 0 0.4728529 0.000000 3.9053601E-04 4.2969361E-03 0.000000 0.000000 0.000000 + Av 2018 2 3 24 0 0.4719157 0.000000 3.8477499E-04 4.2932336E-03 0.000000 0.000000 0.000000 + Av 2018 2 4 1 0 0.4643925 0.000000 3.7909896E-04 4.1928519E-03 0.000000 0.000000 0.000000 + Av 2018 2 4 2 0 0.4591843 0.000000 3.7350666E-04 4.1893488E-03 0.000000 0.000000 0.000000 + Av 2018 2 4 3 0 0.4597646 0.000000 3.6799686E-04 4.1858410E-03 0.000000 0.000000 0.000000 + Av 2018 2 4 4 0 0.4583427 0.000000 3.6256833E-04 4.1823285E-03 0.000000 0.000000 0.000000 + Av 2018 2 4 5 0 0.4576272 0.000000 3.5721989E-04 4.1788113E-03 0.000000 0.000000 0.000000 + Av 2018 2 4 6 0 0.4566763 0.000000 3.5195032E-04 4.1752895E-03 0.000000 0.000000 0.000000 + Av 2018 2 4 7 0 0.4558173 0.000000 3.4675849E-04 4.1717635E-03 0.000000 0.000000 0.000000 Av 2018 2 4 8 0 0.4285043 0.000000 3.4164326E-04 3.7829462E-03 0.000000 0.000000 1.7513033E-03 Av 2018 2 4 9 0 0.3774878 0.000000 3.3660349E-04 3.2991657E-03 0.000000 0.000000 3.9342381E-03 Av 2018 2 4 10 0 0.3414800 0.000000 3.3163806E-04 3.0080243E-03 0.000000 0.000000 5.2415212E-03 @@ -856,21 +856,21 @@ Av 2018 2 4 14 0 0.3326928 0.000000 3.1249807E-04 2.9938277E-03 0.000000 0.000000 5.2415212E-03 Av 2018 2 4 15 0 0.3514605 0.000000 3.0788826E-04 3.2778715E-03 0.000000 0.000000 3.9342381E-03 Av 2018 2 4 16 0 0.3964210 0.000000 3.0334640E-04 3.7545548E-03 0.000000 0.000000 1.7513033E-03 - Av 2018 2 4 17 0 0.4389859 0.000000 2.9887157E-04 4.1362755E-03 0.000000 0.000000 0.000000 - Av 2018 2 4 18 0 0.4495043 0.000000 2.9446278E-04 4.1327057E-03 0.000000 0.000000 0.000000 - Av 2018 2 4 19 0 0.4447669 0.000000 2.9011897E-04 4.1291327E-03 0.000000 0.000000 0.000000 - Av 2018 2 4 20 0 0.4453425 0.000000 2.8583925E-04 4.1255560E-03 0.000000 0.000000 0.000000 - Av 2018 2 4 21 0 0.4440788 0.000000 2.8162269E-04 4.1219760E-03 0.000000 0.000000 0.000000 - Av 2018 2 4 22 0 0.4434628 0.000000 2.7746829E-04 4.1183932E-03 0.000000 0.000000 0.000000 - Av 2018 2 4 23 0 0.4426295 0.000000 2.7337519E-04 4.1148067E-03 0.000000 0.000000 0.000000 - Av 2018 2 4 24 0 0.4418796 0.000000 2.6934250E-04 4.1112169E-03 0.000000 0.000000 0.000000 - Av 2018 2 5 1 0 0.4348593 0.000000 2.6536928E-04 4.0156501E-03 0.000000 0.000000 0.000000 - Av 2018 2 5 2 0 0.4300402 0.000000 2.6145467E-04 4.0122508E-03 0.000000 0.000000 0.000000 - Av 2018 2 5 3 0 0.4307256 0.000000 2.5759780E-04 4.0088482E-03 0.000000 0.000000 0.000000 - Av 2018 2 5 4 0 0.4295045 0.000000 2.5379783E-04 4.0054424E-03 0.000000 0.000000 0.000000 - Av 2018 2 5 5 0 0.4289535 0.000000 2.5005391E-04 4.0020337E-03 0.000000 0.000000 0.000000 - Av 2018 2 5 6 0 0.4281767 0.000000 2.4636521E-04 3.9986223E-03 0.000000 0.000000 0.000000 - Av 2018 2 5 7 0 0.4274854 0.000000 2.4273094E-04 3.9952076E-03 0.000000 0.000000 0.000000 + Av 2018 2 4 17 0 0.4389859 0.000000 2.9887157E-04 4.1362755E-03 0.000000 0.000000 0.000000 + Av 2018 2 4 18 0 0.4495043 0.000000 2.9446278E-04 4.1327057E-03 0.000000 0.000000 0.000000 + Av 2018 2 4 19 0 0.4447669 0.000000 2.9011897E-04 4.1291327E-03 0.000000 0.000000 0.000000 + Av 2018 2 4 20 0 0.4453425 0.000000 2.8583925E-04 4.1255560E-03 0.000000 0.000000 0.000000 + Av 2018 2 4 21 0 0.4440788 0.000000 2.8162269E-04 4.1219760E-03 0.000000 0.000000 0.000000 + Av 2018 2 4 22 0 0.4434628 0.000000 2.7746829E-04 4.1183932E-03 0.000000 0.000000 0.000000 + Av 2018 2 4 23 0 0.4426295 0.000000 2.7337519E-04 4.1148067E-03 0.000000 0.000000 0.000000 + Av 2018 2 4 24 0 0.4418796 0.000000 2.6934250E-04 4.1112169E-03 0.000000 0.000000 0.000000 + Av 2018 2 5 1 0 0.4348593 0.000000 2.6536928E-04 4.0156501E-03 0.000000 0.000000 0.000000 + Av 2018 2 5 2 0 0.4300402 0.000000 2.6145467E-04 4.0122508E-03 0.000000 0.000000 0.000000 + Av 2018 2 5 3 0 0.4307256 0.000000 2.5759780E-04 4.0088482E-03 0.000000 0.000000 0.000000 + Av 2018 2 5 4 0 0.4295045 0.000000 2.5379783E-04 4.0054424E-03 0.000000 0.000000 0.000000 + Av 2018 2 5 5 0 0.4289535 0.000000 2.5005391E-04 4.0020337E-03 0.000000 0.000000 0.000000 + Av 2018 2 5 6 0 0.4281767 0.000000 2.4636521E-04 3.9986223E-03 0.000000 0.000000 0.000000 + Av 2018 2 5 7 0 0.4274854 0.000000 2.4273094E-04 3.9952076E-03 0.000000 0.000000 0.000000 Av 2018 2 5 8 0 0.4017569 0.000000 2.3915028E-04 3.6270544E-03 0.000000 0.000000 1.6578892E-03 Av 2018 2 5 9 0 0.3544343 0.000000 2.3562243E-04 3.1812717E-03 0.000000 0.000000 3.6686303E-03 Av 2018 2 5 10 0 0.3218587 0.000000 2.3214663E-04 2.9178532E-03 0.000000 0.000000 4.8504267E-03 @@ -880,21 +880,21 @@ Av 2018 2 5 14 0 0.3142480 0.000000 2.1874865E-04 2.9041348E-03 0.000000 0.000000 4.8504267E-03 Av 2018 2 5 15 0 0.3312837 0.000000 2.1552177E-04 3.1606946E-03 0.000000 0.000000 3.6686303E-03 Av 2018 2 5 16 0 0.3725534 0.000000 2.1234248E-04 3.5996190E-03 0.000000 0.000000 1.6578892E-03 - Av 2018 2 5 17 0 0.4125866 0.000000 2.0921009E-04 3.9609144E-03 0.000000 0.000000 0.000000 - Av 2018 2 5 18 0 0.4227686 0.000000 2.0612391E-04 3.9574718E-03 0.000000 0.000000 0.000000 - Av 2018 2 5 19 0 0.4183439 0.000000 2.0308325E-04 3.9540264E-03 0.000000 0.000000 0.000000 - Av 2018 2 5 20 0 0.4190040 0.000000 2.0008745E-04 3.9505796E-03 0.000000 0.000000 0.000000 - Av 2018 2 5 21 0 0.4179018 0.000000 1.9713586E-04 3.9471299E-03 0.000000 0.000000 0.000000 - Av 2018 2 5 22 0 0.4174180 0.000000 1.9422779E-04 3.9436789E-03 0.000000 0.000000 0.000000 - Av 2018 2 5 23 0 0.4167249 0.000000 1.9136263E-04 3.9402256E-03 0.000000 0.000000 0.000000 - Av 2018 2 5 24 0 0.4161100 0.000000 1.8853974E-04 3.9367704E-03 0.000000 0.000000 0.000000 - Av 2018 2 6 1 0 0.4095297 0.000000 1.8575847E-04 3.8458344E-03 0.000000 0.000000 0.000000 - Av 2018 2 6 2 0 0.4050415 0.000000 1.8301824E-04 3.8425594E-03 0.000000 0.000000 0.000000 - Av 2018 2 6 3 0 0.4057873 0.000000 1.8031844E-04 3.8392823E-03 0.000000 0.000000 0.000000 - Av 2018 2 6 4 0 0.4047183 0.000000 1.7765847E-04 3.8360031E-03 0.000000 0.000000 0.000000 - Av 2018 2 6 5 0 0.4042855 0.000000 1.7503773E-04 3.8327223E-03 0.000000 0.000000 0.000000 - Av 2018 2 6 6 0 0.4036365 0.000000 1.7245565E-04 3.8294394E-03 0.000000 0.000000 0.000000 - Av 2018 2 6 7 0 0.4030677 0.000000 1.6991165E-04 3.8261549E-03 0.000000 0.000000 0.000000 + Av 2018 2 5 17 0 0.4125866 0.000000 2.0921009E-04 3.9609144E-03 0.000000 0.000000 0.000000 + Av 2018 2 5 18 0 0.4227686 0.000000 2.0612391E-04 3.9574718E-03 0.000000 0.000000 0.000000 + Av 2018 2 5 19 0 0.4183439 0.000000 2.0308325E-04 3.9540264E-03 0.000000 0.000000 0.000000 + Av 2018 2 5 20 0 0.4190040 0.000000 2.0008745E-04 3.9505796E-03 0.000000 0.000000 0.000000 + Av 2018 2 5 21 0 0.4179018 0.000000 1.9713586E-04 3.9471299E-03 0.000000 0.000000 0.000000 + Av 2018 2 5 22 0 0.4174180 0.000000 1.9422779E-04 3.9436789E-03 0.000000 0.000000 0.000000 + Av 2018 2 5 23 0 0.4167249 0.000000 1.9136263E-04 3.9402256E-03 0.000000 0.000000 0.000000 + Av 2018 2 5 24 0 0.4161100 0.000000 1.8853974E-04 3.9367704E-03 0.000000 0.000000 0.000000 + Av 2018 2 6 1 0 0.4095297 0.000000 1.8575847E-04 3.8458344E-03 0.000000 0.000000 0.000000 + Av 2018 2 6 2 0 0.4050415 0.000000 1.8301824E-04 3.8425594E-03 0.000000 0.000000 0.000000 + Av 2018 2 6 3 0 0.4057873 0.000000 1.8031844E-04 3.8392823E-03 0.000000 0.000000 0.000000 + Av 2018 2 6 4 0 0.4047183 0.000000 1.7765847E-04 3.8360031E-03 0.000000 0.000000 0.000000 + Av 2018 2 6 5 0 0.4042855 0.000000 1.7503773E-04 3.8327223E-03 0.000000 0.000000 0.000000 + Av 2018 2 6 6 0 0.4036365 0.000000 1.7245565E-04 3.8294394E-03 0.000000 0.000000 0.000000 + Av 2018 2 6 7 0 0.4030677 0.000000 1.6991165E-04 3.8261549E-03 0.000000 0.000000 0.000000 Av 2018 2 6 8 0 0.3789758 0.000000 1.6740520E-04 3.4801217E-03 0.000000 0.000000 1.5579397E-03 Av 2018 2 6 9 0 0.3353522 0.000000 1.6493571E-04 3.0721906E-03 0.000000 0.000000 3.3972249E-03 Av 2018 2 6 10 0 0.3060719 0.000000 1.6250265E-04 2.8356228E-03 0.000000 0.000000 4.4575403E-03 @@ -904,21 +904,21 @@ Av 2018 2 6 14 0 0.2994261 0.000000 1.5312407E-04 2.8221998E-03 0.000000 0.000000 4.4575403E-03 Av 2018 2 6 15 0 0.3147398 0.000000 1.5086525E-04 3.0520563E-03 0.000000 0.000000 3.3972249E-03 Av 2018 2 6 16 0 0.3523199 0.000000 1.4863975E-04 3.4532677E-03 0.000000 0.000000 1.5579397E-03 - Av 2018 2 6 17 0 0.3896656 0.000000 1.4644708E-04 3.7925709E-03 0.000000 0.000000 0.000000 - Av 2018 2 6 18 0 0.3993962 0.000000 1.4428677E-04 3.7891234E-03 0.000000 0.000000 0.000000 - Av 2018 2 6 19 0 0.3952530 0.000000 1.4215830E-04 3.7856763E-03 0.000000 0.000000 0.000000 - Av 2018 2 6 20 0 0.3959381 0.000000 1.4006125E-04 3.7822290E-03 0.000000 0.000000 0.000000 - Av 2018 2 6 21 0 0.3949485 0.000000 1.3799511E-04 3.7787820E-03 0.000000 0.000000 0.000000 - Av 2018 2 6 22 0 0.3945455 0.000000 1.3595948E-04 3.7753349E-03 0.000000 0.000000 0.000000 - Av 2018 2 6 23 0 0.3939427 0.000000 1.3395386E-04 3.7718881E-03 0.000000 0.000000 0.000000 - Av 2018 2 6 24 0 0.3934134 0.000000 1.3197784E-04 3.7684413E-03 0.000000 0.000000 0.000000 - Av 2018 2 7 1 0 0.3872132 0.000000 1.3003095E-04 3.6818485E-03 0.000000 0.000000 0.000000 - Av 2018 2 7 2 0 0.3830006 0.000000 1.2811279E-04 3.6785759E-03 0.000000 0.000000 0.000000 - Av 2018 2 7 3 0 0.3837619 0.000000 1.2622292E-04 3.6753032E-03 0.000000 0.000000 0.000000 - Av 2018 2 7 4 0 0.3827976 0.000000 1.2436093E-04 3.6720308E-03 0.000000 0.000000 0.000000 - Av 2018 2 7 5 0 0.3824371 0.000000 1.2252641E-04 3.6687581E-03 0.000000 0.000000 0.000000 - Av 2018 2 7 6 0 0.3818702 0.000000 1.2071895E-04 3.6654854E-03 0.000000 0.000000 0.000000 - Av 2018 2 7 7 0 0.3813788 0.000000 1.1893816E-04 3.6622132E-03 0.000000 0.000000 0.000000 + Av 2018 2 6 17 0 0.3896656 0.000000 1.4644708E-04 3.7925709E-03 0.000000 0.000000 0.000000 + Av 2018 2 6 18 0 0.3993962 0.000000 1.4428677E-04 3.7891234E-03 0.000000 0.000000 0.000000 + Av 2018 2 6 19 0 0.3952530 0.000000 1.4215830E-04 3.7856763E-03 0.000000 0.000000 0.000000 + Av 2018 2 6 20 0 0.3959381 0.000000 1.4006125E-04 3.7822290E-03 0.000000 0.000000 0.000000 + Av 2018 2 6 21 0 0.3949485 0.000000 1.3799511E-04 3.7787820E-03 0.000000 0.000000 0.000000 + Av 2018 2 6 22 0 0.3945455 0.000000 1.3595948E-04 3.7753349E-03 0.000000 0.000000 0.000000 + Av 2018 2 6 23 0 0.3939427 0.000000 1.3395386E-04 3.7718881E-03 0.000000 0.000000 0.000000 + Av 2018 2 6 24 0 0.3934134 0.000000 1.3197784E-04 3.7684413E-03 0.000000 0.000000 0.000000 + Av 2018 2 7 1 0 0.3872132 0.000000 1.3003095E-04 3.6818485E-03 0.000000 0.000000 0.000000 + Av 2018 2 7 2 0 0.3830006 0.000000 1.2811279E-04 3.6785759E-03 0.000000 0.000000 0.000000 + Av 2018 2 7 3 0 0.3837619 0.000000 1.2622292E-04 3.6753032E-03 0.000000 0.000000 0.000000 + Av 2018 2 7 4 0 0.3827976 0.000000 1.2436093E-04 3.6720308E-03 0.000000 0.000000 0.000000 + Av 2018 2 7 5 0 0.3824371 0.000000 1.2252641E-04 3.6687581E-03 0.000000 0.000000 0.000000 + Av 2018 2 7 6 0 0.3818702 0.000000 1.2071895E-04 3.6654854E-03 0.000000 0.000000 0.000000 + Av 2018 2 7 7 0 0.3813788 0.000000 1.1893816E-04 3.6622132E-03 0.000000 0.000000 0.000000 Av 2018 2 7 8 0 0.3543479 0.000000 1.1718363E-04 3.2720985E-03 0.000000 0.000000 1.7583742E-03 Av 2018 2 7 9 0 0.3060992 0.000000 1.1545499E-04 2.8240827E-03 0.000000 0.000000 3.7799187E-03 Av 2018 2 7 10 0 0.2745724 0.000000 1.1375184E-04 2.5694771E-03 0.000000 0.000000 4.9222764E-03 @@ -928,21 +928,21 @@ Av 2018 2 7 14 0 0.2679208 0.000000 1.0718684E-04 2.5561461E-03 0.000000 0.000000 4.9222764E-03 Av 2018 2 7 15 0 0.2845287 0.000000 1.0560566E-04 2.8040868E-03 0.000000 0.000000 3.7799187E-03 Av 2018 2 7 16 0 0.3257143 0.000000 1.0404782E-04 3.2454340E-03 0.000000 0.000000 1.7583742E-03 - Av 2018 2 7 17 0 0.3676434 0.000000 1.0251295E-04 3.6288749E-03 0.000000 0.000000 0.000000 - Av 2018 2 7 18 0 0.3788861 0.000000 1.0100072E-04 3.6254718E-03 0.000000 0.000000 0.000000 - Av 2018 2 7 19 0 0.3743105 0.000000 9.9510806E-05 3.6220697E-03 0.000000 0.000000 0.000000 - Av 2018 2 7 20 0 0.3752383 0.000000 9.8042867E-05 3.6186695E-03 0.000000 0.000000 0.000000 - Av 2018 2 7 21 0 0.3742557 0.000000 9.6596581E-05 3.6152704E-03 0.000000 0.000000 0.000000 - Av 2018 2 7 22 0 0.3739405 0.000000 9.5171628E-05 3.6118727E-03 0.000000 0.000000 0.000000 - Av 2018 2 7 23 0 0.3733963 0.000000 9.3767689E-05 3.6084764E-03 0.000000 0.000000 0.000000 - Av 2018 2 7 24 0 0.3729347 0.000000 9.2384471E-05 3.6050817E-03 0.000000 0.000000 0.000000 - Av 2018 2 8 1 0 0.3670831 0.000000 9.1021655E-05 3.5227367E-03 0.000000 0.000000 0.000000 - Av 2018 2 8 2 0 0.3631198 0.000000 8.9678935E-05 3.5195085E-03 0.000000 0.000000 0.000000 - Av 2018 2 8 3 0 0.3638781 0.000000 8.8356035E-05 3.5162815E-03 0.000000 0.000000 0.000000 - Av 2018 2 8 4 0 0.3629976 0.000000 8.7052642E-05 3.5130559E-03 0.000000 0.000000 0.000000 - Av 2018 2 8 5 0 0.3626897 0.000000 8.5768479E-05 3.5098318E-03 0.000000 0.000000 0.000000 - Av 2018 2 8 6 0 0.3621855 0.000000 8.4503263E-05 3.5066090E-03 0.000000 0.000000 0.000000 - Av 2018 2 8 7 0 0.3617523 0.000000 8.3256709E-05 3.5033871E-03 0.000000 0.000000 0.000000 + Av 2018 2 7 17 0 0.3676434 0.000000 1.0251295E-04 3.6288749E-03 0.000000 0.000000 0.000000 + Av 2018 2 7 18 0 0.3788861 0.000000 1.0100072E-04 3.6254718E-03 0.000000 0.000000 0.000000 + Av 2018 2 7 19 0 0.3743105 0.000000 9.9510806E-05 3.6220697E-03 0.000000 0.000000 0.000000 + Av 2018 2 7 20 0 0.3752383 0.000000 9.8042867E-05 3.6186695E-03 0.000000 0.000000 0.000000 + Av 2018 2 7 21 0 0.3742557 0.000000 9.6596581E-05 3.6152704E-03 0.000000 0.000000 0.000000 + Av 2018 2 7 22 0 0.3739405 0.000000 9.5171628E-05 3.6118727E-03 0.000000 0.000000 0.000000 + Av 2018 2 7 23 0 0.3733963 0.000000 9.3767689E-05 3.6084764E-03 0.000000 0.000000 0.000000 + Av 2018 2 7 24 0 0.3729347 0.000000 9.2384471E-05 3.6050817E-03 0.000000 0.000000 0.000000 + Av 2018 2 8 1 0 0.3670831 0.000000 9.1021655E-05 3.5227367E-03 0.000000 0.000000 0.000000 + Av 2018 2 8 2 0 0.3631198 0.000000 8.9678935E-05 3.5195085E-03 0.000000 0.000000 0.000000 + Av 2018 2 8 3 0 0.3638781 0.000000 8.8356035E-05 3.5162815E-03 0.000000 0.000000 0.000000 + Av 2018 2 8 4 0 0.3629976 0.000000 8.7052642E-05 3.5130559E-03 0.000000 0.000000 0.000000 + Av 2018 2 8 5 0 0.3626897 0.000000 8.5768479E-05 3.5098318E-03 0.000000 0.000000 0.000000 + Av 2018 2 8 6 0 0.3621855 0.000000 8.4503263E-05 3.5066090E-03 0.000000 0.000000 0.000000 + Av 2018 2 8 7 0 0.3617523 0.000000 8.3256709E-05 3.5033871E-03 0.000000 0.000000 0.000000 Av 2018 2 8 8 0 0.3359229 0.000000 8.2028550E-05 3.1299097E-03 0.000000 0.000000 1.6829869E-03 Av 2018 2 8 9 0 0.2905410 0.000000 8.0818500E-05 2.7119981E-03 0.000000 0.000000 3.5679410E-03 Av 2018 2 8 10 0 0.2616478 0.000000 7.9626298E-05 2.4792082E-03 0.000000 0.000000 4.6114018E-03 @@ -952,21 +952,21 @@ Av 2018 2 8 14 0 0.2556550 0.000000 7.5030795E-05 2.4661710E-03 0.000000 0.000000 4.6114018E-03 Av 2018 2 8 15 0 0.2708366 0.000000 7.3923977E-05 2.6924429E-03 0.000000 0.000000 3.5679410E-03 Av 2018 2 8 16 0 0.3090419 0.000000 7.2833478E-05 3.1038336E-03 0.000000 0.000000 1.6829869E-03 - Av 2018 2 8 17 0 0.3488819 0.000000 7.1759066E-05 3.4707866E-03 0.000000 0.000000 0.000000 - Av 2018 2 8 18 0 0.3597856 0.000000 7.0700509E-05 3.4674818E-03 0.000000 0.000000 0.000000 - Av 2018 2 8 19 0 0.3554025 0.000000 6.9657566E-05 3.4641791E-03 0.000000 0.000000 0.000000 - Av 2018 2 8 20 0 0.3563372 0.000000 6.8630012E-05 3.4608785E-03 0.000000 0.000000 0.000000 - Av 2018 2 8 21 0 0.3554253 0.000000 6.7617613E-05 3.4575802E-03 0.000000 0.000000 0.000000 - Av 2018 2 8 22 0 0.3551578 0.000000 6.6620145E-05 3.4542840E-03 0.000000 0.000000 0.000000 - Av 2018 2 8 23 0 0.3546685 0.000000 6.5637389E-05 3.4509900E-03 0.000000 0.000000 0.000000 - Av 2018 2 8 24 0 0.3542585 0.000000 6.4669141E-05 3.4476977E-03 0.000000 0.000000 0.000000 - Av 2018 2 9 1 0 0.3487328 0.000000 6.3715168E-05 3.3694867E-03 0.000000 0.000000 0.000000 - Av 2018 2 9 2 0 0.3449985 0.000000 6.2775267E-05 3.3663523E-03 0.000000 0.000000 0.000000 - Av 2018 2 9 3 0 0.3457444 0.000000 6.1849234E-05 3.3632198E-03 0.000000 0.000000 0.000000 - Av 2018 2 9 4 0 0.3449346 0.000000 6.0936862E-05 3.3600894E-03 0.000000 0.000000 0.000000 - Av 2018 2 9 5 0 0.3446679 0.000000 6.0037946E-05 3.3569608E-03 0.000000 0.000000 0.000000 - Av 2018 2 9 6 0 0.3442143 0.000000 5.9152291E-05 3.3538342E-03 0.000000 0.000000 0.000000 - Av 2018 2 9 7 0 0.3438278 0.000000 5.8279697E-05 3.3507096E-03 0.000000 0.000000 0.000000 + Av 2018 2 8 17 0 0.3488819 0.000000 7.1759066E-05 3.4707866E-03 0.000000 0.000000 0.000000 + Av 2018 2 8 18 0 0.3597856 0.000000 7.0700509E-05 3.4674818E-03 0.000000 0.000000 0.000000 + Av 2018 2 8 19 0 0.3554025 0.000000 6.9657566E-05 3.4641791E-03 0.000000 0.000000 0.000000 + Av 2018 2 8 20 0 0.3563372 0.000000 6.8630012E-05 3.4608785E-03 0.000000 0.000000 0.000000 + Av 2018 2 8 21 0 0.3554253 0.000000 6.7617613E-05 3.4575802E-03 0.000000 0.000000 0.000000 + Av 2018 2 8 22 0 0.3551578 0.000000 6.6620145E-05 3.4542840E-03 0.000000 0.000000 0.000000 + Av 2018 2 8 23 0 0.3546685 0.000000 6.5637389E-05 3.4509900E-03 0.000000 0.000000 0.000000 + Av 2018 2 8 24 0 0.3542585 0.000000 6.4669141E-05 3.4476977E-03 0.000000 0.000000 0.000000 + Av 2018 2 9 1 0 0.3487328 0.000000 6.3715168E-05 3.3694867E-03 0.000000 0.000000 0.000000 + Av 2018 2 9 2 0 0.3449985 0.000000 6.2775267E-05 3.3663523E-03 0.000000 0.000000 0.000000 + Av 2018 2 9 3 0 0.3457444 0.000000 6.1849234E-05 3.3632198E-03 0.000000 0.000000 0.000000 + Av 2018 2 9 4 0 0.3449346 0.000000 6.0936862E-05 3.3600894E-03 0.000000 0.000000 0.000000 + Av 2018 2 9 5 0 0.3446679 0.000000 6.0037946E-05 3.3569608E-03 0.000000 0.000000 0.000000 + Av 2018 2 9 6 0 0.3442143 0.000000 5.9152291E-05 3.3538342E-03 0.000000 0.000000 0.000000 + Av 2018 2 9 7 0 0.3438278 0.000000 5.8279697E-05 3.3507096E-03 0.000000 0.000000 0.000000 Av 2018 2 9 8 0 0.3213543 0.000000 5.7419980E-05 3.0255369E-03 0.000000 0.000000 1.4638634E-03 Av 2018 2 9 9 0 0.2825024 0.000000 5.6572946E-05 2.6708825E-03 0.000000 0.000000 3.0617346E-03 Av 2018 2 9 10 0 0.2583934 0.000000 5.5738408E-05 2.4772494E-03 0.000000 0.000000 3.9276741E-03 @@ -976,21 +976,21 @@ Av 2018 2 9 14 0 0.2533248 0.000000 5.2521551E-05 2.4646712E-03 0.000000 0.000000 3.9276741E-03 Av 2018 2 9 15 0 0.2658947 0.000000 5.1746778E-05 2.6520158E-03 0.000000 0.000000 3.0617346E-03 Av 2018 2 9 16 0 0.2980768 0.000000 5.0983428E-05 3.0003795E-03 0.000000 0.000000 1.4638634E-03 - Av 2018 2 9 17 0 0.3324502 0.000000 5.0231345E-05 3.3192590E-03 0.000000 0.000000 0.000000 - Av 2018 2 9 18 0 0.3420136 0.000000 4.9490354E-05 3.3160893E-03 0.000000 0.000000 0.000000 - Av 2018 2 9 19 0 0.3381578 0.000000 4.8760296E-05 3.3129219E-03 0.000000 0.000000 0.000000 - Av 2018 2 9 20 0 0.3389697 0.000000 4.8041002E-05 3.3097565E-03 0.000000 0.000000 0.000000 - Av 2018 2 9 21 0 0.3381604 0.000000 4.7332320E-05 3.3065935E-03 0.000000 0.000000 0.000000 - Av 2018 2 9 22 0 0.3379166 0.000000 4.6634093E-05 3.3034331E-03 0.000000 0.000000 0.000000 - Av 2018 2 9 23 0 0.3374779 0.000000 4.5946166E-05 3.3002750E-03 0.000000 0.000000 0.000000 - Av 2018 2 9 24 0 0.3371086 0.000000 4.5268389E-05 3.2971194E-03 0.000000 0.000000 0.000000 - Av 2018 2 10 1 0 0.3318878 0.000000 4.4600612E-05 3.2228909E-03 0.000000 0.000000 0.000000 - Av 2018 2 10 2 0 0.3283653 0.000000 4.3942684E-05 3.2198832E-03 0.000000 0.000000 0.000000 - Av 2018 2 10 3 0 0.3290928 0.000000 4.3294462E-05 3.2168778E-03 0.000000 0.000000 0.000000 - Av 2018 2 10 4 0 0.3283442 0.000000 4.2655800E-05 3.2138748E-03 0.000000 0.000000 0.000000 - Av 2018 2 10 5 0 0.3281104 0.000000 4.2026561E-05 3.2108738E-03 0.000000 0.000000 0.000000 - Av 2018 2 10 6 0 0.3276992 0.000000 4.1406602E-05 3.2078750E-03 0.000000 0.000000 0.000000 - Av 2018 2 10 7 0 0.3273512 0.000000 4.0795789E-05 3.2048784E-03 0.000000 0.000000 0.000000 + Av 2018 2 9 17 0 0.3324502 0.000000 5.0231345E-05 3.3192590E-03 0.000000 0.000000 0.000000 + Av 2018 2 9 18 0 0.3420136 0.000000 4.9490354E-05 3.3160893E-03 0.000000 0.000000 0.000000 + Av 2018 2 9 19 0 0.3381578 0.000000 4.8760296E-05 3.3129219E-03 0.000000 0.000000 0.000000 + Av 2018 2 9 20 0 0.3389697 0.000000 4.8041002E-05 3.3097565E-03 0.000000 0.000000 0.000000 + Av 2018 2 9 21 0 0.3381604 0.000000 4.7332320E-05 3.3065935E-03 0.000000 0.000000 0.000000 + Av 2018 2 9 22 0 0.3379166 0.000000 4.6634093E-05 3.3034331E-03 0.000000 0.000000 0.000000 + Av 2018 2 9 23 0 0.3374779 0.000000 4.5946166E-05 3.3002750E-03 0.000000 0.000000 0.000000 + Av 2018 2 9 24 0 0.3371086 0.000000 4.5268389E-05 3.2971194E-03 0.000000 0.000000 0.000000 + Av 2018 2 10 1 0 0.3318878 0.000000 4.4600612E-05 3.2228909E-03 0.000000 0.000000 0.000000 + Av 2018 2 10 2 0 0.3283653 0.000000 4.3942684E-05 3.2198832E-03 0.000000 0.000000 0.000000 + Av 2018 2 10 3 0 0.3290928 0.000000 4.3294462E-05 3.2168778E-03 0.000000 0.000000 0.000000 + Av 2018 2 10 4 0 0.3283442 0.000000 4.2655800E-05 3.2138748E-03 0.000000 0.000000 0.000000 + Av 2018 2 10 5 0 0.3281104 0.000000 4.2026561E-05 3.2108738E-03 0.000000 0.000000 0.000000 + Av 2018 2 10 6 0 0.3276992 0.000000 4.1406602E-05 3.2078750E-03 0.000000 0.000000 0.000000 + Av 2018 2 10 7 0 0.3273512 0.000000 4.0795789E-05 3.2048784E-03 0.000000 0.000000 0.000000 Av 2018 2 10 8 0 0.3062798 0.000000 4.0193987E-05 2.8996633E-03 0.000000 0.000000 1.3737304E-03 Av 2018 2 10 9 0 0.2704058 0.000000 3.9601062E-05 2.5750389E-03 0.000000 0.000000 2.8356893E-03 Av 2018 2 10 10 0 0.2487304 0.000000 3.9016886E-05 2.4015228E-03 0.000000 0.000000 3.6107833E-03 @@ -1000,21 +1000,21 @@ Av 2018 2 10 14 0 0.2442023 0.000000 3.6765086E-05 2.3894941E-03 0.000000 0.000000 3.6107833E-03 Av 2018 2 10 15 0 0.2554488 0.000000 3.6222744E-05 2.5569964E-03 0.000000 0.000000 2.8356893E-03 Av 2018 2 10 16 0 0.2847248 0.000000 3.5688405E-05 2.8756051E-03 0.000000 0.000000 1.3737304E-03 - Av 2018 2 10 17 0 0.3167506 0.000000 3.5161942E-05 3.1748028E-03 0.000000 0.000000 0.000000 - Av 2018 2 10 18 0 0.3258199 0.000000 3.4643250E-05 3.1717806E-03 0.000000 0.000000 0.000000 - Av 2018 2 10 19 0 0.3221859 0.000000 3.4132205E-05 3.1687610E-03 0.000000 0.000000 0.000000 - Av 2018 2 10 20 0 0.3229704 0.000000 3.3628701E-05 3.1657438E-03 0.000000 0.000000 0.000000 - Av 2018 2 10 21 0 0.3222199 0.000000 3.3132626E-05 3.1627291E-03 0.000000 0.000000 0.000000 - Av 2018 2 10 22 0 0.3220044 0.000000 3.2643868E-05 3.1597167E-03 0.000000 0.000000 0.000000 - Av 2018 2 10 23 0 0.3216042 0.000000 3.2162319E-05 3.1567069E-03 0.000000 0.000000 0.000000 - Av 2018 2 10 24 0 0.3212696 0.000000 3.1687876E-05 3.1536995E-03 0.000000 0.000000 0.000000 - Av 2018 2 11 1 0 0.3163325 0.000000 3.1220432E-05 3.0832724E-03 0.000000 0.000000 0.000000 - Av 2018 2 11 2 0 0.3130061 0.000000 3.0759878E-05 3.0804037E-03 0.000000 0.000000 0.000000 - Av 2018 2 11 3 0 0.3137109 0.000000 3.0306121E-05 3.0775371E-03 0.000000 0.000000 0.000000 - Av 2018 2 11 4 0 0.3130153 0.000000 2.9859058E-05 3.0746732E-03 0.000000 0.000000 0.000000 - Av 2018 2 11 5 0 0.3128078 0.000000 2.9418588E-05 3.0718113E-03 0.000000 0.000000 0.000000 - Av 2018 2 11 6 0 0.3124318 0.000000 2.8984618E-05 3.0689519E-03 0.000000 0.000000 0.000000 - Av 2018 2 11 7 0 0.3121156 0.000000 2.8557050E-05 3.0660944E-03 0.000000 0.000000 0.000000 + Av 2018 2 10 17 0 0.3167506 0.000000 3.5161942E-05 3.1748028E-03 0.000000 0.000000 0.000000 + Av 2018 2 10 18 0 0.3258199 0.000000 3.4643250E-05 3.1717806E-03 0.000000 0.000000 0.000000 + Av 2018 2 10 19 0 0.3221859 0.000000 3.4132205E-05 3.1687610E-03 0.000000 0.000000 0.000000 + Av 2018 2 10 20 0 0.3229704 0.000000 3.3628701E-05 3.1657438E-03 0.000000 0.000000 0.000000 + Av 2018 2 10 21 0 0.3222199 0.000000 3.3132626E-05 3.1627291E-03 0.000000 0.000000 0.000000 + Av 2018 2 10 22 0 0.3220044 0.000000 3.2643868E-05 3.1597167E-03 0.000000 0.000000 0.000000 + Av 2018 2 10 23 0 0.3216042 0.000000 3.2162319E-05 3.1567069E-03 0.000000 0.000000 0.000000 + Av 2018 2 10 24 0 0.3212696 0.000000 3.1687876E-05 3.1536995E-03 0.000000 0.000000 0.000000 + Av 2018 2 11 1 0 0.3163325 0.000000 3.1220432E-05 3.0832724E-03 0.000000 0.000000 0.000000 + Av 2018 2 11 2 0 0.3130061 0.000000 3.0759878E-05 3.0804037E-03 0.000000 0.000000 0.000000 + Av 2018 2 11 3 0 0.3137109 0.000000 3.0306121E-05 3.0775371E-03 0.000000 0.000000 0.000000 + Av 2018 2 11 4 0 0.3130153 0.000000 2.9859058E-05 3.0746732E-03 0.000000 0.000000 0.000000 + Av 2018 2 11 5 0 0.3128078 0.000000 2.9418588E-05 3.0718113E-03 0.000000 0.000000 0.000000 + Av 2018 2 11 6 0 0.3124318 0.000000 2.8984618E-05 3.0689519E-03 0.000000 0.000000 0.000000 + Av 2018 2 11 7 0 0.3121156 0.000000 2.8557050E-05 3.0660944E-03 0.000000 0.000000 0.000000 Av 2018 2 11 8 0 0.2908558 0.000000 2.8135788E-05 2.7577344E-03 0.000000 0.000000 1.3886583E-03 Av 2018 2 11 9 0 0.2551841 0.000000 2.7720740E-05 2.4377676E-03 0.000000 0.000000 2.8300802E-03 Av 2018 2 11 10 0 0.2342197 0.000000 2.7311817E-05 2.2705521E-03 0.000000 0.000000 3.5771730E-03 @@ -1024,21 +1024,21 @@ Av 2018 2 11 14 0 0.2299549 0.000000 2.5735557E-05 2.2591001E-03 0.000000 0.000000 3.5771730E-03 Av 2018 2 11 15 0 0.2408116 0.000000 2.5355917E-05 2.4205898E-03 0.000000 0.000000 2.8300802E-03 Av 2018 2 11 16 0 0.2695277 0.000000 2.4981877E-05 2.7348297E-03 0.000000 0.000000 1.3886583E-03 - Av 2018 2 11 17 0 0.3016968 0.000000 2.4613355E-05 3.0374606E-03 0.000000 0.000000 0.000000 - Av 2018 2 11 18 0 0.3109783 0.000000 2.4250268E-05 3.0345882E-03 0.000000 0.000000 0.000000 - Av 2018 2 11 19 0 0.3073119 0.000000 2.3892540E-05 3.0317183E-03 0.000000 0.000000 0.000000 - Av 2018 2 11 20 0 0.3081487 0.000000 2.3540088E-05 3.0288508E-03 0.000000 0.000000 0.000000 - Av 2018 2 11 21 0 0.3074207 0.000000 2.3192833E-05 3.0259858E-03 0.000000 0.000000 0.000000 - Av 2018 2 11 22 0 0.3072378 0.000000 2.2850703E-05 3.0231231E-03 0.000000 0.000000 0.000000 - Av 2018 2 11 23 0 0.3068664 0.000000 2.2513619E-05 3.0202630E-03 0.000000 0.000000 0.000000 - Av 2018 2 11 24 0 0.3065616 0.000000 2.2181508E-05 3.0174055E-03 0.000000 0.000000 0.000000 - Av 2018 2 12 1 0 0.3018889 0.000000 2.1854295E-05 2.9505903E-03 0.000000 0.000000 0.000000 - Av 2018 2 12 2 0 0.2987444 0.000000 2.1531911E-05 2.9478623E-03 0.000000 0.000000 0.000000 - Av 2018 2 12 3 0 0.2994238 0.000000 2.1214280E-05 2.9451367E-03 0.000000 0.000000 0.000000 - Av 2018 2 12 4 0 0.2987745 0.000000 2.0901336E-05 2.9424131E-03 0.000000 0.000000 0.000000 - Av 2018 2 12 5 0 0.2985881 0.000000 2.0593008E-05 2.9396918E-03 0.000000 0.000000 0.000000 - Av 2018 2 12 6 0 0.2982417 0.000000 2.0289230E-05 2.9369730E-03 0.000000 0.000000 0.000000 - Av 2018 2 12 7 0 0.2979519 0.000000 1.9989931E-05 2.9342563E-03 0.000000 0.000000 0.000000 + Av 2018 2 11 17 0 0.3016968 0.000000 2.4613355E-05 3.0374606E-03 0.000000 0.000000 0.000000 + Av 2018 2 11 18 0 0.3109783 0.000000 2.4250268E-05 3.0345882E-03 0.000000 0.000000 0.000000 + Av 2018 2 11 19 0 0.3073119 0.000000 2.3892540E-05 3.0317183E-03 0.000000 0.000000 0.000000 + Av 2018 2 11 20 0 0.3081487 0.000000 2.3540088E-05 3.0288508E-03 0.000000 0.000000 0.000000 + Av 2018 2 11 21 0 0.3074207 0.000000 2.3192833E-05 3.0259858E-03 0.000000 0.000000 0.000000 + Av 2018 2 11 22 0 0.3072378 0.000000 2.2850703E-05 3.0231231E-03 0.000000 0.000000 0.000000 + Av 2018 2 11 23 0 0.3068664 0.000000 2.2513619E-05 3.0202630E-03 0.000000 0.000000 0.000000 + Av 2018 2 11 24 0 0.3065616 0.000000 2.2181508E-05 3.0174055E-03 0.000000 0.000000 0.000000 + Av 2018 2 12 1 0 0.3018889 0.000000 2.1854295E-05 2.9505903E-03 0.000000 0.000000 0.000000 + Av 2018 2 12 2 0 0.2987444 0.000000 2.1531911E-05 2.9478623E-03 0.000000 0.000000 0.000000 + Av 2018 2 12 3 0 0.2994238 0.000000 2.1214280E-05 2.9451367E-03 0.000000 0.000000 0.000000 + Av 2018 2 12 4 0 0.2987745 0.000000 2.0901336E-05 2.9424131E-03 0.000000 0.000000 0.000000 + Av 2018 2 12 5 0 0.2985881 0.000000 2.0593008E-05 2.9396918E-03 0.000000 0.000000 0.000000 + Av 2018 2 12 6 0 0.2982417 0.000000 2.0289230E-05 2.9369730E-03 0.000000 0.000000 0.000000 + Av 2018 2 12 7 0 0.2979519 0.000000 1.9989931E-05 2.9342563E-03 0.000000 0.000000 0.000000 Av 2018 2 12 8 0 0.2792255 0.000000 1.9695050E-05 2.6625798E-03 0.000000 0.000000 1.2225544E-03 Av 2018 2 12 9 0 0.2482755 0.000000 1.9404517E-05 2.3874615E-03 0.000000 0.000000 2.4607619E-03 Av 2018 2 12 10 0 0.2305706 0.000000 1.9118268E-05 2.2468236E-03 0.000000 0.000000 3.0876924E-03 @@ -1048,20 +1048,20 @@ Av 2018 2 12 14 0 0.2269068 0.000000 1.8014887E-05 2.2359553E-03 0.000000 0.000000 3.0876924E-03 Av 2018 2 12 15 0 0.2359913 0.000000 1.7749138E-05 2.3711591E-03 0.000000 0.000000 2.4607619E-03 Av 2018 2 12 16 0 0.2604927 0.000000 1.7487311E-05 2.6408427E-03 0.000000 0.000000 1.2225544E-03 - Av 2018 2 12 17 0 0.2886028 0.000000 1.7229346E-05 2.9070831E-03 0.000000 0.000000 0.000000 - Av 2018 2 12 18 0 0.2968287 0.000000 1.6975186E-05 2.9043630E-03 0.000000 0.000000 0.000000 - Av 2018 2 12 19 0 0.2935647 0.000000 1.6724774E-05 2.9016451E-03 0.000000 0.000000 0.000000 - Av 2018 2 12 20 0 0.2942967 0.000000 1.6478058E-05 2.8989296E-03 0.000000 0.000000 0.000000 - Av 2018 2 12 21 0 0.2936401 0.000000 1.6234981E-05 2.8962165E-03 0.000000 0.000000 0.000000 - Av 2018 2 12 22 0 0.2934671 0.000000 1.5995491E-05 2.8935059E-03 0.000000 0.000000 0.000000 - Av 2018 2 12 23 0 0.2931268 0.000000 1.5759531E-05 2.8907976E-03 0.000000 0.000000 0.000000 - Av 2018 2 12 24 0 0.2928454 0.000000 1.5527054E-05 2.8880916E-03 0.000000 0.000000 0.000000 - Av 2018 2 13 1 0 0.2884212 0.000000 1.5298006E-05 2.8247037E-03 0.000000 0.000000 0.000000 - Av 2018 2 13 2 0 0.2854461 0.000000 1.5072337E-05 2.8221188E-03 0.000000 0.000000 0.000000 - Av 2018 2 13 3 0 0.2860990 0.000000 1.4849997E-05 2.8195360E-03 0.000000 0.000000 0.000000 - Av 2018 2 13 4 0 0.2854912 0.000000 1.4630935E-05 2.8169556E-03 0.000000 0.000000 0.000000 - Av 2018 2 13 5 0 0.2853225 0.000000 1.4415105E-05 2.8143772E-03 0.000000 0.000000 0.000000 - Av 2018 2 13 6 0 0.2850018 0.000000 1.4202460E-05 2.8118012E-03 0.000000 0.000000 0.000000 + Av 2018 2 12 17 0 0.2886028 0.000000 1.7229346E-05 2.9070831E-03 0.000000 0.000000 0.000000 + Av 2018 2 12 18 0 0.2968287 0.000000 1.6975186E-05 2.9043630E-03 0.000000 0.000000 0.000000 + Av 2018 2 12 19 0 0.2935647 0.000000 1.6724774E-05 2.9016451E-03 0.000000 0.000000 0.000000 + Av 2018 2 12 20 0 0.2942967 0.000000 1.6478058E-05 2.8989296E-03 0.000000 0.000000 0.000000 + Av 2018 2 12 21 0 0.2936401 0.000000 1.6234981E-05 2.8962165E-03 0.000000 0.000000 0.000000 + Av 2018 2 12 22 0 0.2934671 0.000000 1.5995491E-05 2.8935059E-03 0.000000 0.000000 0.000000 + Av 2018 2 12 23 0 0.2931268 0.000000 1.5759531E-05 2.8907976E-03 0.000000 0.000000 0.000000 + Av 2018 2 12 24 0 0.2928454 0.000000 1.5527054E-05 2.8880916E-03 0.000000 0.000000 0.000000 + Av 2018 2 13 1 0 0.2884212 0.000000 1.5298006E-05 2.8247037E-03 0.000000 0.000000 0.000000 + Av 2018 2 13 2 0 0.2854461 0.000000 1.5072337E-05 2.8221188E-03 0.000000 0.000000 0.000000 + Av 2018 2 13 3 0 0.2860990 0.000000 1.4849997E-05 2.8195360E-03 0.000000 0.000000 0.000000 + Av 2018 2 13 4 0 0.2854912 0.000000 1.4630935E-05 2.8169556E-03 0.000000 0.000000 0.000000 + Av 2018 2 13 5 0 0.2853225 0.000000 1.4415105E-05 2.8143772E-03 0.000000 0.000000 0.000000 + Av 2018 2 13 6 0 0.2850018 0.000000 1.4202460E-05 2.8118012E-03 0.000000 0.000000 0.000000 Av 2018 2 13 7 0 0.2845082 0.000000 1.3992952E-05 2.8059185E-03 0.000000 0.000000 1.5039573E-05 Av 2018 2 13 8 0 0.2644322 0.000000 1.3786534E-05 2.5164373E-03 0.000000 0.000000 1.3191733E-03 Av 2018 2 13 9 0 0.2317707 0.000000 1.3583161E-05 2.2269576E-03 0.000000 0.000000 2.6233071E-03 @@ -1073,19 +1073,19 @@ Av 2018 2 13 15 0 0.2192158 0.000000 1.2424398E-05 2.2115195E-03 0.000000 0.000000 2.6233071E-03 Av 2018 2 13 16 0 0.2448976 0.000000 1.2241118E-05 2.4958525E-03 0.000000 0.000000 1.3191733E-03 Av 2018 2 13 17 0 0.2748374 0.000000 1.2060542E-05 2.7801858E-03 0.000000 0.000000 1.5039573E-05 - Av 2018 2 13 18 0 0.2839071 0.000000 1.1882630E-05 2.7809201E-03 0.000000 0.000000 0.000000 - Av 2018 2 13 19 0 0.2806062 0.000000 1.1707342E-05 2.7783478E-03 0.000000 0.000000 0.000000 - Av 2018 2 13 20 0 0.2813809 0.000000 1.1534640E-05 2.7757778E-03 0.000000 0.000000 0.000000 - Av 2018 2 13 21 0 0.2807392 0.000000 1.1364486E-05 2.7732104E-03 0.000000 0.000000 0.000000 - Av 2018 2 13 22 0 0.2805906 0.000000 1.1196842E-05 2.7706448E-03 0.000000 0.000000 0.000000 - Av 2018 2 13 23 0 0.2802712 0.000000 1.1031671E-05 2.7680818E-03 0.000000 0.000000 0.000000 - Av 2018 2 13 24 0 0.2800119 0.000000 1.0868936E-05 2.7655209E-03 0.000000 0.000000 0.000000 - Av 2018 2 14 1 0 0.2803662 0.000000 1.0708603E-05 2.7053745E-03 0.000000 3.9999921E-02 0.000000 - Av 2018 2 14 2 0 0.2828006 0.000000 1.0550634E-05 2.7029268E-03 0.000000 5.9999879E-02 0.000000 - Av 2018 2 14 3 0 0.4403059 9.1544527E-05 7.3153562E-05 2.7264638E-03 2.0874603E-02 7.9999842E-02 0.000000 - Av 2018 2 14 4 0 0.4827097 2.5516298E-05 1.3583161E-04 2.7600217E-03 1.2984007E-02 9.9999802E-03 0.000000 - Av 2018 2 14 5 0 0.3933345 2.0615134E-05 1.3618841E-04 2.7712500E-03 1.0679265E-02 9.9999802E-03 0.000000 - Av 2018 2 14 6 0 0.4061346 2.0636868E-05 1.3629135E-04 2.7817681E-03 1.0160663E-02 9.9999802E-03 0.000000 + Av 2018 2 13 18 0 0.2839071 0.000000 1.1882630E-05 2.7809201E-03 0.000000 0.000000 0.000000 + Av 2018 2 13 19 0 0.2806062 0.000000 1.1707342E-05 2.7783478E-03 0.000000 0.000000 0.000000 + Av 2018 2 13 20 0 0.2813809 0.000000 1.1534640E-05 2.7757778E-03 0.000000 0.000000 0.000000 + Av 2018 2 13 21 0 0.2807392 0.000000 1.1364486E-05 2.7732104E-03 0.000000 0.000000 0.000000 + Av 2018 2 13 22 0 0.2805906 0.000000 1.1196842E-05 2.7706448E-03 0.000000 0.000000 0.000000 + Av 2018 2 13 23 0 0.2802712 0.000000 1.1031671E-05 2.7680818E-03 0.000000 0.000000 0.000000 + Av 2018 2 13 24 0 0.2800119 0.000000 1.0868936E-05 2.7655209E-03 0.000000 0.000000 0.000000 + Av 2018 2 14 1 0 0.2803662 0.000000 1.0708603E-05 2.7053745E-03 0.000000 3.9999921E-02 0.000000 + Av 2018 2 14 2 0 0.2828006 0.000000 1.0550634E-05 2.7029268E-03 0.000000 5.9999879E-02 0.000000 + Av 2018 2 14 3 0 0.4403059 9.1544527E-05 7.3153562E-05 2.7264638E-03 2.0874603E-02 7.9999842E-02 0.000000 + Av 2018 2 14 4 0 0.4827097 2.5516298E-05 1.3583161E-04 2.7600217E-03 1.2984007E-02 9.9999802E-03 0.000000 + Av 2018 2 14 5 0 0.3933345 2.0615134E-05 1.3618841E-04 2.7712500E-03 1.0679265E-02 9.9999802E-03 0.000000 + Av 2018 2 14 6 0 0.4061346 2.0636868E-05 1.3629135E-04 2.7817681E-03 1.0160663E-02 9.9999802E-03 0.000000 Av 2018 2 14 7 0 0.4557224 8.2634389E-05 1.3957729E-04 2.7867923E-03 1.7618828E-02 1.9999960E-02 4.9273956E-05 Av 2018 2 14 8 0 0.3775826 0.000000 1.4173973E-04 2.4952723E-03 4.4510956E-03 0.000000 1.4214641E-03 Av 2018 2 14 9 0 0.2463439 0.000000 1.3964885E-04 2.1908479E-03 1.5290648E-03 0.000000 2.7936543E-03 @@ -1097,19 +1097,19 @@ Av 2018 2 14 15 0 0.4737266 8.1485048E-08 1.9358229E-04 2.2268812E-03 8.3097741E-03 0.000000 2.7936543E-03 Av 2018 2 14 16 0 0.2567826 0.000000 1.9073083E-04 2.5266497E-03 2.4437669E-03 0.000000 1.4214641E-03 Av 2018 2 14 17 0 0.3231431 0.000000 1.8791725E-04 2.8259633E-03 9.6417137E-04 0.000000 4.9273956E-05 - Av 2018 2 14 18 0 0.3072450 0.000000 1.8514517E-04 2.8342376E-03 4.6130127E-04 0.000000 0.000000 - Av 2018 2 14 19 0 0.3079553 0.000000 1.8241399E-04 2.8316737E-03 2.5212858E-04 0.000000 0.000000 - Av 2018 2 14 20 0 0.3048880 0.000000 1.7972308E-04 2.8291116E-03 1.5168004E-04 0.000000 0.000000 - Av 2018 2 14 21 0 0.3041965 0.000000 1.7707190E-04 2.8265517E-03 9.8034026E-05 0.000000 0.000000 - Av 2018 2 14 22 0 0.3031560 0.000000 1.7445981E-04 2.8239936E-03 6.6959357E-05 0.000000 0.000000 - Av 2018 2 14 23 0 0.3100412 3.3882113E-06 1.7206042E-04 2.8239840E-03 9.2604186E-04 9.9999802E-03 0.000000 - Av 2018 2 14 24 0 0.3569797 2.1401942E-05 1.7079589E-04 2.8304656E-03 6.9075241E-03 9.9999802E-03 0.000000 - Av 2018 2 15 1 0 0.3461196 0.000000 1.6937124E-04 2.7754933E-03 2.4494496E-03 0.000000 0.000000 - Av 2018 2 15 2 0 0.3026928 0.000000 1.6687275E-04 2.7730302E-03 9.6591527E-04 0.000000 0.000000 - Av 2018 2 15 3 0 0.3036174 0.000000 1.6441112E-04 2.7705689E-03 4.6197494E-04 0.000000 0.000000 - Av 2018 2 15 4 0 0.3417650 2.1404270E-05 1.6308649E-04 2.7742549E-03 6.2669171E-03 9.9999802E-03 0.000000 - Av 2018 2 15 5 0 0.3417448 0.000000 1.6177593E-04 2.7786472E-03 2.3567998E-03 0.000000 0.000000 - Av 2018 2 15 6 0 0.3027939 0.000000 1.5938947E-04 2.7761746E-03 9.3734666E-04 0.000000 0.000000 + Av 2018 2 14 18 0 0.3072450 0.000000 1.8514517E-04 2.8342376E-03 4.6130127E-04 0.000000 0.000000 + Av 2018 2 14 19 0 0.3079553 0.000000 1.8241399E-04 2.8316737E-03 2.5212858E-04 0.000000 0.000000 + Av 2018 2 14 20 0 0.3048880 0.000000 1.7972308E-04 2.8291116E-03 1.5168004E-04 0.000000 0.000000 + Av 2018 2 14 21 0 0.3041965 0.000000 1.7707190E-04 2.8265517E-03 9.8034026E-05 0.000000 0.000000 + Av 2018 2 14 22 0 0.3031560 0.000000 1.7445981E-04 2.8239936E-03 6.6959357E-05 0.000000 0.000000 + Av 2018 2 14 23 0 0.3100412 3.3882113E-06 1.7206042E-04 2.8239840E-03 9.2604186E-04 9.9999802E-03 0.000000 + Av 2018 2 14 24 0 0.3569797 2.1401942E-05 1.7079589E-04 2.8304656E-03 6.9075241E-03 9.9999802E-03 0.000000 + Av 2018 2 15 1 0 0.3461196 0.000000 1.6937124E-04 2.7754933E-03 2.4494496E-03 0.000000 0.000000 + Av 2018 2 15 2 0 0.3026928 0.000000 1.6687275E-04 2.7730302E-03 9.6591527E-04 0.000000 0.000000 + Av 2018 2 15 3 0 0.3036174 0.000000 1.6441112E-04 2.7705689E-03 4.6197494E-04 0.000000 0.000000 + Av 2018 2 15 4 0 0.3417650 2.1404270E-05 1.6308649E-04 2.7742549E-03 6.2669171E-03 9.9999802E-03 0.000000 + Av 2018 2 15 5 0 0.3417448 0.000000 1.6177593E-04 2.7786472E-03 2.3567998E-03 0.000000 0.000000 + Av 2018 2 15 6 0 0.3027939 0.000000 1.5938947E-04 2.7761746E-03 9.3734666E-04 0.000000 0.000000 Av 2018 2 15 7 0 0.3014292 0.000000 1.5703823E-04 2.7547071E-03 4.5090396E-04 0.000000 8.6348708E-05 Av 2018 2 15 8 0 0.2737547 0.000000 1.5472167E-04 2.4381406E-03 2.4739269E-04 0.000000 1.5140625E-03 Av 2018 2 15 9 0 0.2376900 0.000000 1.5243927E-04 2.1215766E-03 1.4925154E-04 0.000000 2.9417765E-03 @@ -1121,19 +1121,19 @@ Av 2018 2 15 15 0 0.2220133 0.000000 1.3943487E-04 2.1068137E-03 0.000000 0.000000 2.9417765E-03 Av 2018 2 15 16 0 0.2486295 0.000000 1.3737798E-04 2.4184573E-03 0.000000 0.000000 1.5140625E-03 Av 2018 2 15 17 0 0.2817291 0.000000 1.3535145E-04 2.7301025E-03 0.000000 0.000000 8.6348708E-05 - Av 2018 2 15 18 0 0.2924017 0.000000 1.3335480E-04 2.7466493E-03 0.000000 0.000000 0.000000 - Av 2018 2 15 19 0 0.2893889 0.000000 1.3138760E-04 2.7442011E-03 0.000000 0.000000 0.000000 - Av 2018 2 15 20 0 0.2898386 0.000000 1.2944943E-04 2.7417550E-03 0.000000 0.000000 0.000000 - Av 2018 2 15 21 0 0.2890885 0.000000 1.2753985E-04 2.7393107E-03 0.000000 0.000000 0.000000 - Av 2018 2 15 22 0 0.2887597 0.000000 1.2565844E-04 2.7368683E-03 0.000000 0.000000 0.000000 - Av 2018 2 15 23 0 0.2882885 0.000000 1.2380477E-04 2.7344278E-03 0.000000 0.000000 0.000000 - Av 2018 2 15 24 0 0.2878708 0.000000 1.2197847E-04 2.7319894E-03 0.000000 0.000000 0.000000 - Av 2018 2 16 1 0 0.2835839 0.000000 1.2017909E-04 2.6728215E-03 0.000000 0.000000 0.000000 - Av 2018 2 16 2 0 0.2806534 0.000000 1.1840627E-04 2.6704918E-03 0.000000 0.000000 0.000000 - Av 2018 2 16 3 0 0.2811168 0.000000 1.1665959E-04 2.6681640E-03 0.000000 0.000000 0.000000 - Av 2018 2 16 4 0 0.2815417 0.000000 1.1493867E-04 2.6658380E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 2 16 5 0 0.2819881 0.000000 1.1324315E-04 2.6635139E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 2 16 6 0 0.3404470 7.5389777E-05 1.1545057E-04 2.6718471E-03 7.6396810E-03 1.9999960E-02 0.000000 + Av 2018 2 15 18 0 0.2924017 0.000000 1.3335480E-04 2.7466493E-03 0.000000 0.000000 0.000000 + Av 2018 2 15 19 0 0.2893889 0.000000 1.3138760E-04 2.7442011E-03 0.000000 0.000000 0.000000 + Av 2018 2 15 20 0 0.2898386 0.000000 1.2944943E-04 2.7417550E-03 0.000000 0.000000 0.000000 + Av 2018 2 15 21 0 0.2890885 0.000000 1.2753985E-04 2.7393107E-03 0.000000 0.000000 0.000000 + Av 2018 2 15 22 0 0.2887597 0.000000 1.2565844E-04 2.7368683E-03 0.000000 0.000000 0.000000 + Av 2018 2 15 23 0 0.2882885 0.000000 1.2380477E-04 2.7344278E-03 0.000000 0.000000 0.000000 + Av 2018 2 15 24 0 0.2878708 0.000000 1.2197847E-04 2.7319894E-03 0.000000 0.000000 0.000000 + Av 2018 2 16 1 0 0.2835839 0.000000 1.2017909E-04 2.6728215E-03 0.000000 0.000000 0.000000 + Av 2018 2 16 2 0 0.2806534 0.000000 1.1840627E-04 2.6704918E-03 0.000000 0.000000 0.000000 + Av 2018 2 16 3 0 0.2811168 0.000000 1.1665959E-04 2.6681640E-03 0.000000 0.000000 0.000000 + Av 2018 2 16 4 0 0.2815417 0.000000 1.1493867E-04 2.6658380E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 2 16 5 0 0.2819881 0.000000 1.1324315E-04 2.6635139E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 2 16 6 0 0.3404470 7.5389777E-05 1.1545057E-04 2.6718471E-03 7.6396810E-03 1.9999960E-02 0.000000 Av 2018 2 16 7 0 0.3895285 2.1355983E-05 1.1870520E-04 2.6590985E-03 9.9622970E-03 9.9999802E-03 1.2910836E-04 Av 2018 2 16 8 0 0.3089498 0.000000 1.1804762E-04 2.3302794E-03 2.8030102E-03 0.000000 1.6437764E-03 Av 2018 2 16 9 0 0.2281379 0.000000 1.1630623E-04 1.9946904E-03 1.0724507E-03 0.000000 3.1584445E-03 @@ -1145,19 +1145,19 @@ Av 2018 2 16 15 0 0.2055538 0.000000 1.0638428E-04 1.9805576E-03 4.9773658E-05 0.000000 3.1584445E-03 Av 2018 2 16 16 0 0.2346159 0.000000 1.0481494E-04 2.3114355E-03 3.6633843E-05 0.000000 1.6437764E-03 Av 2018 2 16 17 0 0.2704429 0.000000 1.0326876E-04 2.6423149E-03 1.8148049E-04 0.000000 1.2910836E-04 - Av 2018 2 16 18 0 0.2819441 0.000000 1.0174538E-04 2.6683731E-03 0.000000 0.000000 0.000000 - Av 2018 2 16 19 0 0.2781317 0.000000 1.0024448E-04 2.6660294E-03 0.000000 0.000000 0.000000 - Av 2018 2 16 20 0 0.2800730 0.000000 9.8765711E-05 2.6636873E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 2 16 21 0 0.2788804 0.000000 9.7308759E-05 2.6613472E-03 0.000000 0.000000 0.000000 - Av 2018 2 16 22 0 0.2787758 0.000000 9.5873307E-05 2.6590086E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 2 16 23 0 0.2783009 0.000000 9.4459028E-05 2.6566719E-03 0.000000 0.000000 0.000000 - Av 2018 2 16 24 0 0.2768262 0.000000 9.3065610E-05 2.6543373E-03 0.000000 0.000000 0.000000 - Av 2018 2 17 1 0 0.2731123 0.000000 9.1692746E-05 2.5972310E-03 0.000000 0.000000 0.000000 - Av 2018 2 17 2 0 0.2701868 0.000000 9.0340131E-05 2.5950000E-03 0.000000 0.000000 0.000000 - Av 2018 2 17 3 0 0.2707186 0.000000 8.9007466E-05 2.5927704E-03 0.000000 0.000000 0.000000 - Av 2018 2 17 4 0 0.2700511 0.000000 8.7694469E-05 2.5905424E-03 0.000000 0.000000 0.000000 - Av 2018 2 17 5 0 0.3195246 6.3511216E-05 8.9669949E-05 2.5980715E-03 6.2238937E-03 1.9999960E-02 0.000000 - Av 2018 2 17 6 0 0.3201135 0.000000 9.1600108E-05 2.6067731E-03 2.4171590E-03 0.000000 0.000000 + Av 2018 2 16 18 0 0.2819441 0.000000 1.0174538E-04 2.6683731E-03 0.000000 0.000000 0.000000 + Av 2018 2 16 19 0 0.2781317 0.000000 1.0024448E-04 2.6660294E-03 0.000000 0.000000 0.000000 + Av 2018 2 16 20 0 0.2800730 0.000000 9.8765711E-05 2.6636873E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 2 16 21 0 0.2788804 0.000000 9.7308759E-05 2.6613472E-03 0.000000 0.000000 0.000000 + Av 2018 2 16 22 0 0.2787758 0.000000 9.5873307E-05 2.6590086E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 2 16 23 0 0.2783009 0.000000 9.4459028E-05 2.6566719E-03 0.000000 0.000000 0.000000 + Av 2018 2 16 24 0 0.2768262 0.000000 9.3065610E-05 2.6543373E-03 0.000000 0.000000 0.000000 + Av 2018 2 17 1 0 0.2731123 0.000000 9.1692746E-05 2.5972310E-03 0.000000 0.000000 0.000000 + Av 2018 2 17 2 0 0.2701868 0.000000 9.0340131E-05 2.5950000E-03 0.000000 0.000000 0.000000 + Av 2018 2 17 3 0 0.2707186 0.000000 8.9007466E-05 2.5927704E-03 0.000000 0.000000 0.000000 + Av 2018 2 17 4 0 0.2700511 0.000000 8.7694469E-05 2.5905424E-03 0.000000 0.000000 0.000000 + Av 2018 2 17 5 0 0.3195246 6.3511216E-05 8.9669949E-05 2.5980715E-03 6.2238937E-03 1.9999960E-02 0.000000 + Av 2018 2 17 6 0 0.3201135 0.000000 9.1600108E-05 2.6067731E-03 2.4171590E-03 0.000000 0.000000 Av 2018 2 17 7 0 0.4423553 1.9184529E-04 1.0012730E-04 2.5817817E-03 2.2857944E-02 2.9999940E-02 1.7360263E-04 Av 2018 2 17 8 0 0.4522977 2.0951487E-05 1.0955925E-04 2.2561573E-03 1.3049036E-02 9.9999802E-03 1.7492826E-03 Av 2018 2 17 9 0 0.2551467 0.000000 1.0901718E-04 1.9138404E-03 3.4070977E-03 0.000000 3.3249627E-03 @@ -1169,19 +1169,19 @@ Av 2018 2 17 15 0 0.1976302 0.000000 9.9894060E-05 1.9039332E-03 1.0216179E-04 0.000000 3.3249627E-03 Av 2018 2 17 16 0 0.2275612 0.000000 9.8420467E-05 2.2482923E-03 6.9432506E-05 0.000000 1.7492826E-03 Av 2018 2 17 17 0 0.2636820 0.000000 9.6968608E-05 2.5926533E-03 4.9342274E-05 0.000000 1.7360263E-04 - Av 2018 2 17 18 0 0.2767103 0.000000 9.5538177E-05 2.6285590E-03 3.6348159E-05 0.000000 0.000000 - Av 2018 2 17 19 0 0.2751822 0.000000 9.4128838E-05 2.6262740E-03 1.8063019E-04 0.000000 0.000000 - Av 2018 2 17 20 0 0.2749661 0.000000 9.2740287E-05 2.6239904E-03 0.000000 0.000000 0.000000 - Av 2018 2 17 21 0 0.2733165 0.000000 9.1372225E-05 2.6217089E-03 0.000000 0.000000 0.000000 - Av 2018 2 17 22 0 0.2733956 0.000000 9.0024347E-05 2.6194286E-03 0.000000 0.000000 0.000000 - Av 2018 2 17 23 0 0.2728765 0.000000 8.8696339E-05 2.6171501E-03 0.000000 0.000000 0.000000 - Av 2018 2 17 24 0 0.2736906 0.000000 8.7387933E-05 2.6148735E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 2 18 1 0 0.2692682 0.000000 8.6098822E-05 2.5588246E-03 0.000000 0.000000 0.000000 - Av 2018 2 18 2 0 0.2655538 0.000000 8.4828731E-05 2.5566488E-03 0.000000 0.000000 0.000000 - Av 2018 2 18 3 0 0.2663784 0.000000 8.3577375E-05 2.5544746E-03 0.000000 0.000000 0.000000 - Av 2018 2 18 4 0 0.4644711 1.3975664E-05 1.0310284E-04 2.5721302E-03 2.7905138E-02 4.9999900E-02 0.000000 - Av 2018 2 18 5 0 0.5014578 2.3621556E-05 1.2345589E-04 2.5983928E-03 1.4249536E-02 9.9999802E-03 0.000000 - Av 2018 2 18 6 0 0.4323662 8.7638517E-05 1.2736810E-04 2.6141577E-03 1.8676003E-02 1.9999960E-02 0.000000 + Av 2018 2 17 18 0 0.2767103 0.000000 9.5538177E-05 2.6285590E-03 3.6348159E-05 0.000000 0.000000 + Av 2018 2 17 19 0 0.2751822 0.000000 9.4128838E-05 2.6262740E-03 1.8063019E-04 0.000000 0.000000 + Av 2018 2 17 20 0 0.2749661 0.000000 9.2740287E-05 2.6239904E-03 0.000000 0.000000 0.000000 + Av 2018 2 17 21 0 0.2733165 0.000000 9.1372225E-05 2.6217089E-03 0.000000 0.000000 0.000000 + Av 2018 2 17 22 0 0.2733956 0.000000 9.0024347E-05 2.6194286E-03 0.000000 0.000000 0.000000 + Av 2018 2 17 23 0 0.2728765 0.000000 8.8696339E-05 2.6171501E-03 0.000000 0.000000 0.000000 + Av 2018 2 17 24 0 0.2736906 0.000000 8.7387933E-05 2.6148735E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 2 18 1 0 0.2692682 0.000000 8.6098822E-05 2.5588246E-03 0.000000 0.000000 0.000000 + Av 2018 2 18 2 0 0.2655538 0.000000 8.4828731E-05 2.5566488E-03 0.000000 0.000000 0.000000 + Av 2018 2 18 3 0 0.2663784 0.000000 8.3577375E-05 2.5544746E-03 0.000000 0.000000 0.000000 + Av 2018 2 18 4 0 0.4644711 1.3975664E-05 1.0310284E-04 2.5721302E-03 2.7905138E-02 4.9999900E-02 0.000000 + Av 2018 2 18 5 0 0.5014578 2.3621556E-05 1.2345589E-04 2.5983928E-03 1.4249536E-02 9.9999802E-03 0.000000 + Av 2018 2 18 6 0 0.4323662 8.7638517E-05 1.2736810E-04 2.6141577E-03 1.8676003E-02 1.9999960E-02 0.000000 Av 2018 2 18 7 0 0.4407494 2.2005182E-05 1.3112364E-04 2.5934237E-03 1.1968967E-02 9.9999802E-03 1.6779335E-04 Av 2018 2 18 8 0 0.3045878 0.000000 1.3031940E-04 2.3249898E-03 3.1984115E-03 0.000000 1.4080814E-03 Av 2018 2 18 9 0 0.2382493 0.000000 1.2839699E-04 2.0498629E-03 1.1874530E-03 0.000000 2.6483694E-03 @@ -1193,19 +1193,19 @@ Av 2018 2 18 15 0 0.2418753 0.000000 8.5306814E-04 2.1564069E-03 5.5043176E-03 0.000000 2.6483694E-03 Av 2018 2 18 16 0 0.3918004 0.000000 8.4048399E-04 2.4274297E-03 1.7958308E-03 0.000000 1.4080814E-03 Av 2018 2 18 17 0 0.5135661 1.1401213E-05 8.4653927E-04 2.7158845E-03 2.4765057E-02 3.9999921E-02 1.6779335E-04 - Av 2018 2 18 18 0 0.6421961 1.2469657E-04 8.5886841E-04 2.7821772E-03 2.1410527E-02 1.9999960E-02 0.000000 - Av 2018 2 18 19 0 0.4625523 0.000000 8.5262128E-04 2.7932881E-03 4.8767505E-03 0.000000 0.000000 - Av 2018 2 18 20 0 0.3778898 0.000000 8.4004377E-04 2.7913922E-03 1.6388030E-03 0.000000 0.000000 - Av 2018 2 18 21 0 0.3770272 0.000000 8.2765176E-04 2.7894937E-03 7.0477655E-04 0.000000 0.000000 - Av 2018 2 18 22 0 0.3666925 0.000000 8.1544265E-04 2.7875933E-03 3.5759510E-04 0.000000 0.000000 - Av 2018 2 18 23 0 0.3649769 0.000000 8.0341357E-04 2.7856901E-03 2.0380582E-04 0.000000 0.000000 - Av 2018 2 18 24 0 0.3621217 0.000000 7.9156191E-04 2.7837849E-03 1.2647099E-04 0.000000 0.000000 - Av 2018 2 19 1 0 0.3564990 0.000000 7.7988516E-04 2.7238631E-03 8.3701329E-05 0.000000 0.000000 - Av 2018 2 19 2 0 0.3522213 0.000000 7.6838059E-04 2.7220550E-03 5.8243044E-05 0.000000 0.000000 - Av 2018 2 19 3 0 0.3516290 0.000000 7.5704575E-04 2.7202447E-03 4.2179883E-05 0.000000 0.000000 - Av 2018 2 19 4 0 0.3510060 0.000000 7.4587815E-04 2.7184321E-03 1.9749510E-04 0.000000 0.000000 - Av 2018 2 19 5 0 0.3491831 0.000000 7.3487527E-04 2.7166172E-03 0.000000 0.000000 0.000000 - Av 2018 2 19 6 0 0.3467442 0.000000 7.2403467E-04 2.7148002E-03 0.000000 0.000000 0.000000 + Av 2018 2 18 18 0 0.6421961 1.2469657E-04 8.5886841E-04 2.7821772E-03 2.1410527E-02 1.9999960E-02 0.000000 + Av 2018 2 18 19 0 0.4625523 0.000000 8.5262128E-04 2.7932881E-03 4.8767505E-03 0.000000 0.000000 + Av 2018 2 18 20 0 0.3778898 0.000000 8.4004377E-04 2.7913922E-03 1.6388030E-03 0.000000 0.000000 + Av 2018 2 18 21 0 0.3770272 0.000000 8.2765176E-04 2.7894937E-03 7.0477655E-04 0.000000 0.000000 + Av 2018 2 18 22 0 0.3666925 0.000000 8.1544265E-04 2.7875933E-03 3.5759510E-04 0.000000 0.000000 + Av 2018 2 18 23 0 0.3649769 0.000000 8.0341357E-04 2.7856901E-03 2.0380582E-04 0.000000 0.000000 + Av 2018 2 18 24 0 0.3621217 0.000000 7.9156191E-04 2.7837849E-03 1.2647099E-04 0.000000 0.000000 + Av 2018 2 19 1 0 0.3564990 0.000000 7.7988516E-04 2.7238631E-03 8.3701329E-05 0.000000 0.000000 + Av 2018 2 19 2 0 0.3522213 0.000000 7.6838059E-04 2.7220550E-03 5.8243044E-05 0.000000 0.000000 + Av 2018 2 19 3 0 0.3516290 0.000000 7.5704575E-04 2.7202447E-03 4.2179883E-05 0.000000 0.000000 + Av 2018 2 19 4 0 0.3510060 0.000000 7.4587815E-04 2.7184321E-03 1.9749510E-04 0.000000 0.000000 + Av 2018 2 19 5 0 0.3491831 0.000000 7.3487527E-04 2.7166172E-03 0.000000 0.000000 0.000000 + Av 2018 2 19 6 0 0.3467442 0.000000 7.2403467E-04 2.7148002E-03 0.000000 0.000000 0.000000 Av 2018 2 19 7 0 0.3432289 0.000000 7.1335403E-04 2.6742471E-03 0.000000 0.000000 1.7606484E-04 Av 2018 2 19 8 0 0.3235809 0.000000 7.0283090E-04 2.4311806E-03 0.000000 0.000000 1.2726331E-03 Av 2018 2 19 9 0 0.3872737 1.0716815E-04 6.9801358E-04 2.1988736E-03 1.1891852E-02 1.9999960E-02 2.3692013E-03 @@ -1217,19 +1217,19 @@ Av 2018 2 19 15 0 0.2843395 0.000000 6.4359442E-04 2.1998251E-03 1.1505595E-04 0.000000 2.3692013E-03 Av 2018 2 19 16 0 0.3040301 0.000000 6.3410035E-04 2.4392097E-03 7.7061028E-05 0.000000 1.2726331E-03 Av 2018 2 19 17 0 0.3282655 0.000000 6.2474638E-04 2.6785927E-03 5.4130811E-05 0.000000 1.7606484E-04 - Av 2018 2 19 18 0 0.3372390 0.000000 6.1553041E-04 2.7154628E-03 3.9501567E-05 0.000000 0.000000 - Av 2018 2 19 19 0 0.3361976 0.000000 6.0645037E-04 2.7135969E-03 1.8987383E-04 0.000000 0.000000 - Av 2018 2 19 20 0 0.3348128 0.000000 5.9750426E-04 2.7117291E-03 0.000000 0.000000 0.000000 - Av 2018 2 19 21 0 0.3325436 0.000000 5.8869016E-04 2.7098595E-03 0.000000 0.000000 0.000000 - Av 2018 2 19 22 0 0.3318896 0.000000 5.8000605E-04 2.7079880E-03 0.000000 0.000000 0.000000 - Av 2018 2 19 23 0 0.3306912 0.000000 5.7145010E-04 2.7061149E-03 0.000000 0.000000 0.000000 - Av 2018 2 19 24 0 0.3296992 0.000000 5.6302035E-04 2.7042401E-03 0.000000 0.000000 0.000000 - Av 2018 2 20 1 0 0.3248470 0.000000 5.5471488E-04 2.6463594E-03 0.000000 0.000000 0.000000 - Av 2018 2 20 2 0 0.3213602 0.000000 5.4653198E-04 2.6445785E-03 0.000000 0.000000 0.000000 - Av 2018 2 20 3 0 0.3212267 0.000000 5.3846976E-04 2.6427961E-03 0.000000 0.000000 0.000000 - Av 2018 2 20 4 0 0.3199433 0.000000 5.3052645E-04 2.6410120E-03 0.000000 0.000000 0.000000 - Av 2018 2 20 5 0 0.3190756 0.000000 5.2270037E-04 2.6392261E-03 0.000000 0.000000 0.000000 - Av 2018 2 20 6 0 0.3180789 0.000000 5.1498978E-04 2.6374387E-03 0.000000 0.000000 0.000000 + Av 2018 2 19 18 0 0.3372390 0.000000 6.1553041E-04 2.7154628E-03 3.9501567E-05 0.000000 0.000000 + Av 2018 2 19 19 0 0.3361976 0.000000 6.0645037E-04 2.7135969E-03 1.8987383E-04 0.000000 0.000000 + Av 2018 2 19 20 0 0.3348128 0.000000 5.9750426E-04 2.7117291E-03 0.000000 0.000000 0.000000 + Av 2018 2 19 21 0 0.3325436 0.000000 5.8869016E-04 2.7098595E-03 0.000000 0.000000 0.000000 + Av 2018 2 19 22 0 0.3318896 0.000000 5.8000605E-04 2.7079880E-03 0.000000 0.000000 0.000000 + Av 2018 2 19 23 0 0.3306912 0.000000 5.7145010E-04 2.7061149E-03 0.000000 0.000000 0.000000 + Av 2018 2 19 24 0 0.3296992 0.000000 5.6302035E-04 2.7042401E-03 0.000000 0.000000 0.000000 + Av 2018 2 20 1 0 0.3248470 0.000000 5.5471488E-04 2.6463594E-03 0.000000 0.000000 0.000000 + Av 2018 2 20 2 0 0.3213602 0.000000 5.4653198E-04 2.6445785E-03 0.000000 0.000000 0.000000 + Av 2018 2 20 3 0 0.3212267 0.000000 5.3846976E-04 2.6427961E-03 0.000000 0.000000 0.000000 + Av 2018 2 20 4 0 0.3199433 0.000000 5.3052645E-04 2.6410120E-03 0.000000 0.000000 0.000000 + Av 2018 2 20 5 0 0.3190756 0.000000 5.2270037E-04 2.6392261E-03 0.000000 0.000000 0.000000 + Av 2018 2 20 6 0 0.3180789 0.000000 5.1498978E-04 2.6374387E-03 0.000000 0.000000 0.000000 Av 2018 2 20 7 0 0.3140417 0.000000 5.0739280E-04 2.5903806E-03 0.000000 0.000000 2.0576759E-04 Av 2018 2 20 8 0 0.2944076 0.000000 4.9990800E-04 2.3451976E-03 0.000000 0.000000 1.3120959E-03 Av 2018 2 20 9 0 0.2666580 0.000000 4.9253355E-04 2.1000132E-03 0.000000 0.000000 2.4184240E-03 @@ -1241,19 +1241,19 @@ Av 2018 2 20 15 0 0.4151852 9.5371070E-05 5.6184304E-04 2.2356855E-03 1.5256383E-02 1.9999960E-02 2.4184240E-03 Av 2018 2 20 16 0 0.4930716 9.9370904E-05 5.6364946E-04 2.4991995E-03 1.7271670E-02 1.9999960E-02 1.3120959E-03 Av 2018 2 20 17 0 0.4172362 0.000000 5.6047365E-04 2.7524456E-03 4.2120907E-03 0.000000 2.0576759E-04 - Av 2018 2 20 18 0 0.3460414 0.000000 5.5220578E-04 2.7957580E-03 1.4661727E-03 0.000000 0.000000 - Av 2018 2 20 19 0 0.3871518 2.3534785E-05 5.4528349E-04 2.7992551E-03 5.8736582E-03 9.9999802E-03 0.000000 - Av 2018 2 20 20 0 0.3772195 0.000000 5.3845730E-04 2.8034283E-03 2.1689734E-03 0.000000 0.000000 - Av 2018 2 20 21 0 0.3429934 0.000000 5.3051423E-04 2.8014518E-03 8.7851397E-04 0.000000 0.000000 - Av 2018 2 20 22 0 0.3417241 0.000000 5.2268832E-04 2.7994737E-03 4.2785477E-04 0.000000 0.000000 - Av 2018 2 20 23 0 0.3364809 0.000000 5.1497784E-04 2.7974937E-03 2.3681246E-04 0.000000 0.000000 - Av 2018 2 20 24 0 0.3350647 0.000000 5.0738110E-04 2.7955119E-03 1.4379459E-04 0.000000 0.000000 - Av 2018 2 21 1 0 0.3293298 0.000000 4.9989647E-04 2.7352422E-03 9.3596551E-05 0.000000 0.000000 - Av 2018 2 21 2 0 0.3255512 0.000000 4.9252220E-04 2.7333603E-03 6.4282751E-05 0.000000 0.000000 - Av 2018 2 21 3 0 0.3252916 0.000000 4.8525672E-04 2.7314764E-03 4.6067573E-05 0.000000 0.000000 - Av 2018 2 21 4 0 0.3666857 3.0009156E-05 4.7965915E-04 2.7356981E-03 5.7684621E-03 9.9999802E-03 0.000000 - Av 2018 2 21 5 0 0.3673206 0.000000 4.7413638E-04 2.7405911E-03 2.2779452E-03 0.000000 0.000000 - Av 2018 2 21 6 0 0.3301987 0.000000 4.6714212E-04 2.7386867E-03 9.1280078E-04 0.000000 0.000000 + Av 2018 2 20 18 0 0.3460414 0.000000 5.5220578E-04 2.7957580E-03 1.4661727E-03 0.000000 0.000000 + Av 2018 2 20 19 0 0.3871518 2.3534785E-05 5.4528349E-04 2.7992551E-03 5.8736582E-03 9.9999802E-03 0.000000 + Av 2018 2 20 20 0 0.3772195 0.000000 5.3845730E-04 2.8034283E-03 2.1689734E-03 0.000000 0.000000 + Av 2018 2 20 21 0 0.3429934 0.000000 5.3051423E-04 2.8014518E-03 8.7851397E-04 0.000000 0.000000 + Av 2018 2 20 22 0 0.3417241 0.000000 5.2268832E-04 2.7994737E-03 4.2785477E-04 0.000000 0.000000 + Av 2018 2 20 23 0 0.3364809 0.000000 5.1497784E-04 2.7974937E-03 2.3681246E-04 0.000000 0.000000 + Av 2018 2 20 24 0 0.3350647 0.000000 5.0738110E-04 2.7955119E-03 1.4379459E-04 0.000000 0.000000 + Av 2018 2 21 1 0 0.3293298 0.000000 4.9989647E-04 2.7352422E-03 9.3596551E-05 0.000000 0.000000 + Av 2018 2 21 2 0 0.3255512 0.000000 4.9252220E-04 2.7333603E-03 6.4282751E-05 0.000000 0.000000 + Av 2018 2 21 3 0 0.3252916 0.000000 4.8525672E-04 2.7314764E-03 4.6067573E-05 0.000000 0.000000 + Av 2018 2 21 4 0 0.3666857 3.0009156E-05 4.7965915E-04 2.7356981E-03 5.7684621E-03 9.9999802E-03 0.000000 + Av 2018 2 21 5 0 0.3673206 0.000000 4.7413638E-04 2.7405911E-03 2.2779452E-03 0.000000 0.000000 + Av 2018 2 21 6 0 0.3301987 0.000000 4.6714212E-04 2.7386867E-03 9.1280078E-04 0.000000 0.000000 Av 2018 2 21 7 0 0.3261250 0.000000 4.6025103E-04 2.6886084E-03 4.4132926E-04 0.000000 2.1896642E-04 Av 2018 2 21 8 0 0.3029072 0.000000 4.5346163E-04 2.4590138E-03 2.4301148E-04 0.000000 1.2539083E-03 Av 2018 2 21 9 0 0.7284144 1.8765764E-04 5.4341601E-04 2.2548849E-03 6.2184364E-02 7.9999842E-02 2.2888503E-03 @@ -1265,19 +1265,19 @@ Av 2018 2 21 15 0 0.3804899 0.000000 1.4329830E-03 2.3876068E-03 5.9583731E-04 0.000000 2.2888503E-03 Av 2018 2 21 16 0 0.4065285 0.000000 1.4118443E-03 2.6141175E-03 3.1157790E-04 0.000000 1.2539083E-03 Av 2018 2 21 17 0 0.4228519 0.000000 1.3910172E-03 2.8406165E-03 1.8148925E-04 0.000000 2.1896642E-04 - Av 2018 2 21 18 0 0.4317793 0.000000 1.3704976E-03 2.8875892E-03 1.1447349E-04 0.000000 0.000000 - Av 2018 2 21 19 0 0.4283348 0.000000 1.3502806E-03 2.8863770E-03 7.6719451E-05 0.000000 0.000000 - Av 2018 2 21 20 0 0.4262286 0.000000 1.3303618E-03 2.8851540E-03 5.3917909E-05 0.000000 0.000000 - Av 2018 2 21 21 0 0.4238534 0.000000 1.3107369E-03 2.8839193E-03 3.9362174E-05 0.000000 0.000000 - Av 2018 2 21 22 0 0.4227846 0.000000 1.2914015E-03 2.8826734E-03 1.8947161E-04 0.000000 0.000000 - Av 2018 2 21 23 0 0.4201106 0.000000 1.2723512E-03 2.8814166E-03 0.000000 0.000000 0.000000 - Av 2018 2 21 24 0 0.4170119 0.000000 1.2535821E-03 2.8801486E-03 0.000000 0.000000 0.000000 - Av 2018 2 22 1 0 0.4112784 0.000000 1.2350898E-03 2.8184347E-03 0.000000 0.000000 0.000000 - Av 2018 2 22 2 0 0.4078723 0.000000 1.2168703E-03 2.8172454E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 2 22 3 0 0.4064367 0.000000 1.1989195E-03 2.8160454E-03 0.000000 0.000000 0.000000 - Av 2018 2 22 4 0 0.4029822 0.000000 1.1812336E-03 2.8148352E-03 0.000000 0.000000 0.000000 - Av 2018 2 22 5 0 0.4016327 0.000000 1.1638086E-03 2.8136149E-03 0.000000 0.000000 0.000000 - Av 2018 2 22 6 0 0.3995850 0.000000 1.1466405E-03 2.8123844E-03 0.000000 0.000000 0.000000 + Av 2018 2 21 18 0 0.4317793 0.000000 1.3704976E-03 2.8875892E-03 1.1447349E-04 0.000000 0.000000 + Av 2018 2 21 19 0 0.4283348 0.000000 1.3502806E-03 2.8863770E-03 7.6719451E-05 0.000000 0.000000 + Av 2018 2 21 20 0 0.4262286 0.000000 1.3303618E-03 2.8851540E-03 5.3917909E-05 0.000000 0.000000 + Av 2018 2 21 21 0 0.4238534 0.000000 1.3107369E-03 2.8839193E-03 3.9362174E-05 0.000000 0.000000 + Av 2018 2 21 22 0 0.4227846 0.000000 1.2914015E-03 2.8826734E-03 1.8947161E-04 0.000000 0.000000 + Av 2018 2 21 23 0 0.4201106 0.000000 1.2723512E-03 2.8814166E-03 0.000000 0.000000 0.000000 + Av 2018 2 21 24 0 0.4170119 0.000000 1.2535821E-03 2.8801486E-03 0.000000 0.000000 0.000000 + Av 2018 2 22 1 0 0.4112784 0.000000 1.2350898E-03 2.8184347E-03 0.000000 0.000000 0.000000 + Av 2018 2 22 2 0 0.4078723 0.000000 1.2168703E-03 2.8172454E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 2 22 3 0 0.4064367 0.000000 1.1989195E-03 2.8160454E-03 0.000000 0.000000 0.000000 + Av 2018 2 22 4 0 0.4029822 0.000000 1.1812336E-03 2.8148352E-03 0.000000 0.000000 0.000000 + Av 2018 2 22 5 0 0.4016327 0.000000 1.1638086E-03 2.8136149E-03 0.000000 0.000000 0.000000 + Av 2018 2 22 6 0 0.3995850 0.000000 1.1466405E-03 2.8123844E-03 0.000000 0.000000 0.000000 Av 2018 2 22 7 0 0.3935368 0.000000 1.1297258E-03 2.7487676E-03 0.000000 0.000000 2.8352914E-04 Av 2018 2 22 8 0 0.8808008 4.1071288E-04 1.2619809E-03 2.5107001E-03 6.7418143E-02 8.9999817E-02 1.4783437E-03 Av 2018 2 22 9 0 1.224405 1.3698939E-03 1.4683958E-03 2.3009658E-03 6.0770229E-02 5.9999879E-02 2.6731584E-03 @@ -1289,19 +1289,19 @@ Av 2018 2 22 15 0 0.3845078 0.000000 1.4293595E-03 2.3598443E-03 4.0790078E-04 0.000000 2.6731584E-03 Av 2018 2 22 16 0 0.4013280 0.000000 1.4082743E-03 2.6215720E-03 2.2755830E-04 0.000000 1.4783437E-03 Av 2018 2 22 17 0 0.4266888 0.000000 1.3875001E-03 2.8832860E-03 1.3898464E-04 0.000000 2.8352914E-04 - Av 2018 2 22 18 0 0.4362787 0.000000 1.3670323E-03 2.9445039E-03 9.0869893E-05 0.000000 0.000000 - Av 2018 2 22 19 0 0.4337836 0.000000 1.3468665E-03 2.9433321E-03 6.2628511E-05 0.000000 0.000000 - Av 2018 2 22 20 0 0.4314593 0.000000 1.3269981E-03 2.9421472E-03 4.5007982E-05 0.000000 0.000000 - Av 2018 2 22 21 0 0.4292275 0.000000 1.3074228E-03 2.9409493E-03 3.3459277E-05 0.000000 0.000000 - Av 2018 2 22 22 0 0.4280614 0.000000 1.2881362E-03 2.9397390E-03 1.7187594E-04 0.000000 0.000000 - Av 2018 2 22 23 0 0.4254727 0.000000 1.2691342E-03 2.9385160E-03 0.000000 0.000000 0.000000 - Av 2018 2 22 24 0 0.4224749 0.000000 1.2504125E-03 2.9372806E-03 0.000000 0.000000 0.000000 - Av 2018 2 23 1 0 0.4166190 0.000000 1.2319669E-03 2.8741558E-03 0.000000 0.000000 0.000000 - Av 2018 2 23 2 0 0.4117995 0.000000 1.2137934E-03 2.8729986E-03 0.000000 0.000000 0.000000 - Av 2018 2 23 3 0 0.4108660 0.000000 1.1958880E-03 2.8718298E-03 0.000000 0.000000 0.000000 - Av 2018 2 23 4 0 0.4086157 0.000000 1.1782468E-03 2.8706493E-03 0.000000 0.000000 0.000000 - Av 2018 2 23 5 0 0.4068574 0.000000 1.1608658E-03 2.8694575E-03 0.000000 0.000000 0.000000 - Av 2018 2 23 6 0 0.4049616 0.000000 1.1437412E-03 2.8682544E-03 0.000000 0.000000 0.000000 + Av 2018 2 22 18 0 0.4362787 0.000000 1.3670323E-03 2.9445039E-03 9.0869893E-05 0.000000 0.000000 + Av 2018 2 22 19 0 0.4337836 0.000000 1.3468665E-03 2.9433321E-03 6.2628511E-05 0.000000 0.000000 + Av 2018 2 22 20 0 0.4314593 0.000000 1.3269981E-03 2.9421472E-03 4.5007982E-05 0.000000 0.000000 + Av 2018 2 22 21 0 0.4292275 0.000000 1.3074228E-03 2.9409493E-03 3.3459277E-05 0.000000 0.000000 + Av 2018 2 22 22 0 0.4280614 0.000000 1.2881362E-03 2.9397390E-03 1.7187594E-04 0.000000 0.000000 + Av 2018 2 22 23 0 0.4254727 0.000000 1.2691342E-03 2.9385160E-03 0.000000 0.000000 0.000000 + Av 2018 2 22 24 0 0.4224749 0.000000 1.2504125E-03 2.9372806E-03 0.000000 0.000000 0.000000 + Av 2018 2 23 1 0 0.4166190 0.000000 1.2319669E-03 2.8741558E-03 0.000000 0.000000 0.000000 + Av 2018 2 23 2 0 0.4117995 0.000000 1.2137934E-03 2.8729986E-03 0.000000 0.000000 0.000000 + Av 2018 2 23 3 0 0.4108660 0.000000 1.1958880E-03 2.8718298E-03 0.000000 0.000000 0.000000 + Av 2018 2 23 4 0 0.4086157 0.000000 1.1782468E-03 2.8706493E-03 0.000000 0.000000 0.000000 + Av 2018 2 23 5 0 0.4068574 0.000000 1.1608658E-03 2.8694575E-03 0.000000 0.000000 0.000000 + Av 2018 2 23 6 0 0.4049616 0.000000 1.1437412E-03 2.8682544E-03 0.000000 0.000000 0.000000 Av 2018 2 23 7 0 0.3991236 0.000000 1.1268692E-03 2.8083650E-03 0.000000 0.000000 2.6670352E-04 Av 2018 2 23 8 0 0.3794039 0.000000 1.1102462E-03 2.5841801E-03 0.000000 0.000000 1.2801571E-03 Av 2018 2 23 9 0 0.3532924 0.000000 1.0938683E-03 2.3599844E-03 0.000000 0.000000 2.2936107E-03 @@ -1313,19 +1313,19 @@ Av 2018 2 23 15 0 0.3353173 0.000000 1.0005516E-03 2.3523488E-03 0.000000 0.000000 2.2936107E-03 Av 2018 2 23 16 0 0.3526415 0.000000 9.8579191E-04 2.5740007E-03 0.000000 0.000000 1.2801571E-03 Av 2018 2 23 17 0 0.3749947 0.000000 9.7124983E-04 2.7956429E-03 0.000000 0.000000 2.6670352E-04 - Av 2018 2 23 18 0 0.3843769 0.000000 9.5692236E-04 2.8529905E-03 0.000000 0.000000 0.000000 - Av 2018 2 23 19 0 0.3830224 0.000000 9.4280625E-04 2.8516541E-03 0.000000 0.000000 0.000000 - Av 2018 2 23 20 0 0.3814070 0.000000 9.2889846E-04 2.8503081E-03 0.000000 0.000000 0.000000 - Av 2018 2 23 21 0 0.3799092 0.000000 9.1519573E-04 2.8489530E-03 0.000000 0.000000 0.000000 - Av 2018 2 23 22 0 0.3783970 0.000000 9.0169517E-04 2.8475891E-03 0.000000 0.000000 0.000000 - Av 2018 2 23 23 0 0.3769158 0.000000 8.8839373E-04 2.8462159E-03 0.000000 0.000000 0.000000 - Av 2018 2 23 24 0 0.3754494 0.000000 8.7528856E-04 2.8448340E-03 0.000000 0.000000 0.000000 - Av 2018 2 24 1 0 0.3712733 0.000000 8.6237671E-04 2.7839118E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 2 24 2 0 0.7148814 1.5845669E-04 9.3788147E-04 2.8080505E-03 4.6981778E-02 7.9999842E-02 0.000000 - Av 2018 2 24 3 0 0.6716192 8.8401299E-07 1.0118822E-03 2.8361599E-03 9.3841963E-03 0.000000 0.000000 - Av 2018 2 24 4 0 0.4231988 3.7855862E-05 9.9898537E-04 2.8423555E-03 9.8235318E-03 9.9999802E-03 0.000000 - Av 2018 2 24 5 0 0.8121101 1.0973903E-04 1.0575741E-03 2.8728659E-03 5.0572552E-02 5.9999879E-02 0.000000 - Av 2018 2 24 6 0 1.090811 7.2446465E-04 1.1891685E-03 2.9244279E-03 5.9372399E-02 5.9999879E-02 0.000000 + Av 2018 2 23 18 0 0.3843769 0.000000 9.5692236E-04 2.8529905E-03 0.000000 0.000000 0.000000 + Av 2018 2 23 19 0 0.3830224 0.000000 9.4280625E-04 2.8516541E-03 0.000000 0.000000 0.000000 + Av 2018 2 23 20 0 0.3814070 0.000000 9.2889846E-04 2.8503081E-03 0.000000 0.000000 0.000000 + Av 2018 2 23 21 0 0.3799092 0.000000 9.1519573E-04 2.8489530E-03 0.000000 0.000000 0.000000 + Av 2018 2 23 22 0 0.3783970 0.000000 9.0169517E-04 2.8475891E-03 0.000000 0.000000 0.000000 + Av 2018 2 23 23 0 0.3769158 0.000000 8.8839373E-04 2.8462159E-03 0.000000 0.000000 0.000000 + Av 2018 2 23 24 0 0.3754494 0.000000 8.7528856E-04 2.8448340E-03 0.000000 0.000000 0.000000 + Av 2018 2 24 1 0 0.3712733 0.000000 8.6237671E-04 2.7839118E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 2 24 2 0 0.7148814 1.5845669E-04 9.3788147E-04 2.8080505E-03 4.6981778E-02 7.9999842E-02 0.000000 + Av 2018 2 24 3 0 0.6716192 8.8401299E-07 1.0118822E-03 2.8361599E-03 9.3841963E-03 0.000000 0.000000 + Av 2018 2 24 4 0 0.4231988 3.7855862E-05 9.9898537E-04 2.8423555E-03 9.8235318E-03 9.9999802E-03 0.000000 + Av 2018 2 24 5 0 0.8121101 1.0973903E-04 1.0575741E-03 2.8728659E-03 5.0572552E-02 5.9999879E-02 0.000000 + Av 2018 2 24 6 0 1.090811 7.2446465E-04 1.1891685E-03 2.9244279E-03 5.9372399E-02 5.9999879E-02 0.000000 Av 2018 2 24 7 0 0.7732633 4.5628200E-05 1.2498426E-03 2.8796634E-03 1.7851967E-02 9.9999802E-03 3.5683619E-04 Av 2018 2 24 8 0 0.4286162 0.000000 1.2337894E-03 2.6145929E-03 4.2782407E-03 0.000000 1.5908922E-03 Av 2018 2 24 9 0 0.3926792 0.000000 1.2155891E-03 2.3418879E-03 1.4836761E-03 0.000000 2.8249484E-03 @@ -1337,19 +1337,19 @@ Av 2018 2 24 15 0 0.3448215 0.000000 1.1118886E-03 2.3343521E-03 5.6184559E-05 0.000000 2.8249484E-03 Av 2018 2 24 16 0 0.3657544 0.000000 1.0954865E-03 2.6045467E-03 4.0842486E-05 0.000000 1.5908922E-03 Av 2018 2 24 17 0 0.3942196 0.000000 1.0793264E-03 2.8747299E-03 1.9371448E-04 0.000000 3.5683619E-04 - Av 2018 2 24 18 0 0.4056686 0.000000 1.0634045E-03 2.9519137E-03 0.000000 0.000000 0.000000 - Av 2018 2 24 19 0 0.4034249 0.000000 1.0477176E-03 2.9505822E-03 0.000000 0.000000 0.000000 - Av 2018 2 24 20 0 0.4019074 0.000000 1.0322622E-03 2.9492397E-03 0.000000 0.000000 0.000000 - Av 2018 2 24 21 0 0.4001672 0.000000 1.0170346E-03 2.9478865E-03 0.000000 0.000000 0.000000 - Av 2018 2 24 22 0 0.3985337 0.000000 1.0020318E-03 2.9465226E-03 0.000000 0.000000 0.000000 - Av 2018 2 24 23 0 0.3968920 0.000000 9.8725036E-04 2.9451482E-03 0.000000 0.000000 0.000000 - Av 2018 2 24 24 0 0.3952815 0.000000 9.7268680E-04 2.9437633E-03 0.000000 0.000000 0.000000 - Av 2018 2 25 1 0 0.3894734 0.000000 9.5833809E-04 2.8803360E-03 0.000000 0.000000 0.000000 - Av 2018 2 25 2 0 0.3851596 0.000000 9.4420114E-04 2.8790350E-03 0.000000 0.000000 0.000000 - Av 2018 2 25 3 0 0.3845751 0.000000 9.3027262E-04 2.8777237E-03 0.000000 0.000000 0.000000 - Av 2018 2 25 4 0 0.3840506 0.000000 9.1654964E-04 2.8764026E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 2 25 5 0 0.3835343 0.000000 9.0302911E-04 2.8750722E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 2 25 6 0 0.4527320 1.4838573E-04 8.9750532E-04 2.8854508E-03 8.5789757E-03 1.9999960E-02 0.000000 + Av 2018 2 24 18 0 0.4056686 0.000000 1.0634045E-03 2.9519137E-03 0.000000 0.000000 0.000000 + Av 2018 2 24 19 0 0.4034249 0.000000 1.0477176E-03 2.9505822E-03 0.000000 0.000000 0.000000 + Av 2018 2 24 20 0 0.4019074 0.000000 1.0322622E-03 2.9492397E-03 0.000000 0.000000 0.000000 + Av 2018 2 24 21 0 0.4001672 0.000000 1.0170346E-03 2.9478865E-03 0.000000 0.000000 0.000000 + Av 2018 2 24 22 0 0.3985337 0.000000 1.0020318E-03 2.9465226E-03 0.000000 0.000000 0.000000 + Av 2018 2 24 23 0 0.3968920 0.000000 9.8725036E-04 2.9451482E-03 0.000000 0.000000 0.000000 + Av 2018 2 24 24 0 0.3952815 0.000000 9.7268680E-04 2.9437633E-03 0.000000 0.000000 0.000000 + Av 2018 2 25 1 0 0.3894734 0.000000 9.5833809E-04 2.8803360E-03 0.000000 0.000000 0.000000 + Av 2018 2 25 2 0 0.3851596 0.000000 9.4420114E-04 2.8790350E-03 0.000000 0.000000 0.000000 + Av 2018 2 25 3 0 0.3845751 0.000000 9.3027262E-04 2.8777237E-03 0.000000 0.000000 0.000000 + Av 2018 2 25 4 0 0.3840506 0.000000 9.1654964E-04 2.8764026E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 2 25 5 0 0.3835343 0.000000 9.0302911E-04 2.8750722E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 2 25 6 0 0.4527320 1.4838573E-04 8.9750532E-04 2.8854508E-03 8.5789757E-03 1.9999960E-02 0.000000 Av 2018 2 25 7 0 0.4958244 3.7788588E-05 8.9401094E-04 2.8089995E-03 1.0233843E-02 9.9999802E-03 4.2947449E-04 Av 2018 2 25 8 0 0.4538983 3.5259458E-05 8.8465353E-04 2.5211731E-03 9.7294804E-03 9.9999802E-03 1.7916922E-03 Av 2018 2 25 9 0 0.4758103 1.3046864E-04 8.8030996E-04 2.2381111E-03 1.6098194E-02 1.9999960E-02 3.1539102E-03 @@ -1361,19 +1361,19 @@ Av 2018 2 25 15 0 0.4991620 7.6446868E-06 9.1856695E-04 2.3459238E-03 2.1554906E-02 2.9999940E-02 3.1539102E-03 Av 2018 2 25 16 0 0.4777989 2.8541098E-08 9.1975200E-04 2.6616061E-03 5.2920063E-03 0.000000 1.7916922E-03 Av 2018 2 25 17 0 0.3873266 0.000000 9.0618571E-04 2.9599329E-03 1.7433011E-03 0.000000 4.2947449E-04 - Av 2018 2 25 18 0 0.6567500 4.4222092E-05 9.3489332E-04 3.0751766E-03 3.4507502E-02 4.9999900E-02 0.000000 - Av 2018 2 25 19 0 0.6157770 2.1906779E-07 9.6298085E-04 3.0992243E-03 7.5297691E-03 0.000000 0.000000 - Av 2018 2 25 20 0 0.4034687 0.000000 9.4878691E-04 3.0982145E-03 2.2710168E-03 0.000000 0.000000 - Av 2018 2 25 21 0 0.4302088 0.000000 9.3479082E-04 3.0966066E-03 9.1063371E-04 0.000000 0.000000 - Av 2018 2 25 22 0 0.4063665 0.000000 9.2100119E-04 3.0949886E-03 4.4048109E-04 0.000000 0.000000 - Av 2018 2 25 23 0 0.4080374 0.000000 9.0741500E-04 3.0933609E-03 2.4262244E-04 0.000000 0.000000 - Av 2018 2 25 24 0 0.4034066 0.000000 8.9402922E-04 3.0917237E-03 1.4679665E-04 0.000000 0.000000 - Av 2018 2 26 1 0 0.3975178 0.000000 8.8084087E-04 3.0242989E-03 9.5290619E-05 0.000000 0.000000 - Av 2018 2 26 2 0 0.3925469 0.000000 8.6784706E-04 3.0227578E-03 6.5306835E-05 0.000000 0.000000 - Av 2018 2 26 3 0 0.3919826 0.000000 8.5504499E-04 3.0212072E-03 4.6721623E-05 0.000000 0.000000 - Av 2018 2 26 4 0 0.4334928 3.7855571E-05 8.4442936E-04 3.0261630E-03 5.7698688E-03 9.9999802E-03 0.000000 - Av 2018 2 26 5 0 0.4335066 0.000000 8.3396037E-04 3.0317807E-03 2.2781757E-03 0.000000 0.000000 - Av 2018 2 26 6 0 0.3953131 0.000000 8.2165812E-04 3.0301877E-03 9.1287290E-04 0.000000 0.000000 + Av 2018 2 25 18 0 0.6567500 4.4222092E-05 9.3489332E-04 3.0751766E-03 3.4507502E-02 4.9999900E-02 0.000000 + Av 2018 2 25 19 0 0.6157770 2.1906779E-07 9.6298085E-04 3.0992243E-03 7.5297691E-03 0.000000 0.000000 + Av 2018 2 25 20 0 0.4034687 0.000000 9.4878691E-04 3.0982145E-03 2.2710168E-03 0.000000 0.000000 + Av 2018 2 25 21 0 0.4302088 0.000000 9.3479082E-04 3.0966066E-03 9.1063371E-04 0.000000 0.000000 + Av 2018 2 25 22 0 0.4063665 0.000000 9.2100119E-04 3.0949886E-03 4.4048109E-04 0.000000 0.000000 + Av 2018 2 25 23 0 0.4080374 0.000000 9.0741500E-04 3.0933609E-03 2.4262244E-04 0.000000 0.000000 + Av 2018 2 25 24 0 0.4034066 0.000000 8.9402922E-04 3.0917237E-03 1.4679665E-04 0.000000 0.000000 + Av 2018 2 26 1 0 0.3975178 0.000000 8.8084087E-04 3.0242989E-03 9.5290619E-05 0.000000 0.000000 + Av 2018 2 26 2 0 0.3925469 0.000000 8.6784706E-04 3.0227578E-03 6.5306835E-05 0.000000 0.000000 + Av 2018 2 26 3 0 0.3919826 0.000000 8.5504499E-04 3.0212072E-03 4.6721623E-05 0.000000 0.000000 + Av 2018 2 26 4 0 0.4334928 3.7855571E-05 8.4442936E-04 3.0261630E-03 5.7698688E-03 9.9999802E-03 0.000000 + Av 2018 2 26 5 0 0.4335066 0.000000 8.3396037E-04 3.0317807E-03 2.2781757E-03 0.000000 0.000000 + Av 2018 2 26 6 0 0.3953131 0.000000 8.2165812E-04 3.0301877E-03 9.1287290E-04 0.000000 0.000000 Av 2018 2 26 7 0 0.3873695 0.000000 8.0953736E-04 2.9284246E-03 4.4135749E-04 0.000000 4.5527858E-04 Av 2018 2 26 8 0 0.3567594 0.000000 7.9759542E-04 2.6335279E-03 2.4302445E-04 0.000000 1.7884002E-03 Av 2018 2 26 9 0 0.3233899 0.000000 7.8582962E-04 2.3386222E-03 1.4700388E-04 0.000000 3.1215218E-03 @@ -1385,19 +1385,19 @@ Av 2018 2 26 15 0 0.3045746 0.000000 7.1879145E-04 2.3287390E-03 0.000000 0.000000 3.1215218E-03 Av 2018 2 26 16 0 0.3267332 0.000000 7.0818816E-04 2.6203510E-03 0.000000 0.000000 1.7884002E-03 Av 2018 2 26 17 0 0.3575344 0.000000 6.9774123E-04 2.9119554E-03 0.000000 0.000000 4.5527858E-04 - Av 2018 2 26 18 0 0.3721324 0.000000 6.8744848E-04 3.0104264E-03 0.000000 0.000000 0.000000 - Av 2018 2 26 19 0 0.3723008 0.000000 6.7730754E-04 3.0087291E-03 0.000000 0.000000 0.000000 - Av 2018 2 26 20 0 0.3706432 0.000000 6.6731620E-04 3.0070243E-03 0.000000 0.000000 0.000000 - Av 2018 2 26 21 0 0.3696397 0.000000 6.5747224E-04 3.0053125E-03 0.000000 0.000000 0.000000 - Av 2018 2 26 22 0 0.3684277 0.000000 6.4777350E-04 3.0035935E-03 0.000000 0.000000 0.000000 - Av 2018 2 26 23 0 0.3673069 0.000000 6.3821784E-04 3.0018676E-03 0.000000 0.000000 0.000000 - Av 2018 2 26 24 0 0.3661727 0.000000 6.2880316E-04 3.0001346E-03 0.000000 0.000000 0.000000 - Av 2018 2 27 1 0 0.3607502 0.000000 6.1952730E-04 2.9349460E-03 0.000000 0.000000 0.000000 - Av 2018 2 27 2 0 0.3568441 0.000000 6.1038829E-04 2.9333103E-03 0.000000 0.000000 0.000000 - Av 2018 2 27 3 0 0.3567469 0.000000 6.0138415E-04 2.9316682E-03 0.000000 0.000000 0.000000 - Av 2018 2 27 4 0 0.3553425 0.000000 5.9251278E-04 2.9300193E-03 0.000000 0.000000 0.000000 - Av 2018 2 27 5 0 0.3544097 0.000000 5.8377226E-04 2.9283643E-03 0.000000 0.000000 0.000000 - Av 2018 2 27 6 0 0.3533297 0.000000 5.7516072E-04 2.9267024E-03 0.000000 0.000000 0.000000 + Av 2018 2 26 18 0 0.3721324 0.000000 6.8744848E-04 3.0104264E-03 0.000000 0.000000 0.000000 + Av 2018 2 26 19 0 0.3723008 0.000000 6.7730754E-04 3.0087291E-03 0.000000 0.000000 0.000000 + Av 2018 2 26 20 0 0.3706432 0.000000 6.6731620E-04 3.0070243E-03 0.000000 0.000000 0.000000 + Av 2018 2 26 21 0 0.3696397 0.000000 6.5747224E-04 3.0053125E-03 0.000000 0.000000 0.000000 + Av 2018 2 26 22 0 0.3684277 0.000000 6.4777350E-04 3.0035935E-03 0.000000 0.000000 0.000000 + Av 2018 2 26 23 0 0.3673069 0.000000 6.3821784E-04 3.0018676E-03 0.000000 0.000000 0.000000 + Av 2018 2 26 24 0 0.3661727 0.000000 6.2880316E-04 3.0001346E-03 0.000000 0.000000 0.000000 + Av 2018 2 27 1 0 0.3607502 0.000000 6.1952730E-04 2.9349460E-03 0.000000 0.000000 0.000000 + Av 2018 2 27 2 0 0.3568441 0.000000 6.1038829E-04 2.9333103E-03 0.000000 0.000000 0.000000 + Av 2018 2 27 3 0 0.3567469 0.000000 6.0138415E-04 2.9316682E-03 0.000000 0.000000 0.000000 + Av 2018 2 27 4 0 0.3553425 0.000000 5.9251278E-04 2.9300193E-03 0.000000 0.000000 0.000000 + Av 2018 2 27 5 0 0.3544097 0.000000 5.8377226E-04 2.9283643E-03 0.000000 0.000000 0.000000 + Av 2018 2 27 6 0 0.3533297 0.000000 5.7516072E-04 2.9267024E-03 0.000000 0.000000 0.000000 Av 2018 2 27 7 0 0.3450996 0.000000 5.6667620E-04 2.8197020E-03 0.000000 0.000000 4.7878310E-04 Av 2018 2 27 8 0 0.3197560 0.000000 5.5831682E-04 2.5316922E-03 0.000000 0.000000 1.7803090E-03 Av 2018 2 27 9 0 0.2880001 0.000000 5.5008079E-04 2.2436758E-03 0.000000 0.000000 3.0818349E-03 @@ -1409,19 +1409,19 @@ Av 2018 2 27 15 0 0.2726469 0.000000 5.0315406E-04 2.2334680E-03 0.000000 0.000000 3.0818349E-03 Av 2018 2 27 16 0 0.2953635 0.000000 4.9573177E-04 2.5180825E-03 0.000000 0.000000 1.7803090E-03 Av 2018 2 27 17 0 0.3254237 0.000000 4.8841897E-04 2.8026910E-03 0.000000 0.000000 4.7878310E-04 - Av 2018 2 27 18 0 0.3418133 0.000000 4.8121400E-04 2.9062908E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 2 27 19 0 0.3421211 0.000000 4.7411534E-04 2.9045532E-03 0.000000 0.000000 0.000000 - Av 2018 2 27 20 0 0.3395702 0.000000 4.6712140E-04 2.9028098E-03 0.000000 0.000000 0.000000 - Av 2018 2 27 21 0 0.3392765 0.000000 4.6023063E-04 2.9010614E-03 0.000000 0.000000 0.000000 - Av 2018 2 27 22 0 0.3382112 0.000000 4.5344152E-04 2.8993080E-03 0.000000 0.000000 0.000000 - Av 2018 2 27 23 0 0.3374272 0.000000 4.4675253E-04 2.8975492E-03 0.000000 0.000000 0.000000 - Av 2018 2 27 24 0 0.3365582 0.000000 4.4016223E-04 2.8957853E-03 0.000000 0.000000 0.000000 - Av 2018 2 28 1 0 0.3316002 0.000000 4.3366916E-04 2.8332141E-03 0.000000 0.000000 0.000000 - Av 2018 2 28 2 0 0.3280837 0.000000 4.2727188E-04 2.8315464E-03 0.000000 0.000000 0.000000 - Av 2018 2 28 3 0 0.3282166 0.000000 4.2096892E-04 2.8298735E-03 0.000000 0.000000 0.000000 - Av 2018 2 28 4 0 0.3270925 0.000000 4.1475898E-04 2.8281955E-03 0.000000 0.000000 0.000000 - Av 2018 2 28 5 0 0.3264174 0.000000 4.0864063E-04 2.8265130E-03 0.000000 0.000000 0.000000 - Av 2018 2 28 6 0 0.3255979 0.000000 4.0261255E-04 2.8248257E-03 0.000000 0.000000 0.000000 + Av 2018 2 27 18 0 0.3418133 0.000000 4.8121400E-04 2.9062908E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 2 27 19 0 0.3421211 0.000000 4.7411534E-04 2.9045532E-03 0.000000 0.000000 0.000000 + Av 2018 2 27 20 0 0.3395702 0.000000 4.6712140E-04 2.9028098E-03 0.000000 0.000000 0.000000 + Av 2018 2 27 21 0 0.3392765 0.000000 4.6023063E-04 2.9010614E-03 0.000000 0.000000 0.000000 + Av 2018 2 27 22 0 0.3382112 0.000000 4.5344152E-04 2.8993080E-03 0.000000 0.000000 0.000000 + Av 2018 2 27 23 0 0.3374272 0.000000 4.4675253E-04 2.8975492E-03 0.000000 0.000000 0.000000 + Av 2018 2 27 24 0 0.3365582 0.000000 4.4016223E-04 2.8957853E-03 0.000000 0.000000 0.000000 + Av 2018 2 28 1 0 0.3316002 0.000000 4.3366916E-04 2.8332141E-03 0.000000 0.000000 0.000000 + Av 2018 2 28 2 0 0.3280837 0.000000 4.2727188E-04 2.8315464E-03 0.000000 0.000000 0.000000 + Av 2018 2 28 3 0 0.3282166 0.000000 4.2096892E-04 2.8298735E-03 0.000000 0.000000 0.000000 + Av 2018 2 28 4 0 0.3270925 0.000000 4.1475898E-04 2.8281955E-03 0.000000 0.000000 0.000000 + Av 2018 2 28 5 0 0.3264174 0.000000 4.0864063E-04 2.8265130E-03 0.000000 0.000000 0.000000 + Av 2018 2 28 6 0 0.3255979 0.000000 4.0261255E-04 2.8248257E-03 0.000000 0.000000 0.000000 Av 2018 2 28 7 0 0.3172858 0.000000 3.9667339E-04 2.6949686E-03 0.000000 9.9999802E-03 5.8257033E-04 Av 2018 2 28 8 0 0.3061718 8.1586550E-05 3.9513208E-04 2.3775043E-03 1.0038102E-03 3.9999921E-02 2.0599777E-03 Av 2018 2 28 9 0 0.3643641 1.1745211E-04 3.9979917E-04 2.0719634E-03 1.2903497E-02 1.9999960E-02 3.5373850E-03 @@ -1433,19 +1433,19 @@ Av 2018 2 28 15 0 0.3975996 2.2375447E-08 5.1625515E-04 2.2320796E-03 5.4697399E-03 0.000000 3.5373850E-03 Av 2018 2 28 16 0 0.3051990 0.000000 5.0864078E-04 2.5554397E-03 1.7873149E-03 0.000000 2.0599777E-03 Av 2018 2 28 17 0 0.4010149 5.5824858E-05 5.0409598E-04 2.8866422E-03 7.4164928E-03 1.9999960E-02 5.8257033E-04 - Av 2018 2 28 18 0 0.4042187 0.000000 4.9960363E-04 3.0219133E-03 2.5546474E-03 0.000000 0.000000 - Av 2018 2 28 19 0 0.4666163 1.3570269E-04 4.9942738E-04 3.0319449E-03 1.4544673E-02 1.9999960E-02 0.000000 - Av 2018 2 28 20 0 0.8739282 1.6809821E-04 5.9167936E-04 3.0698499E-03 6.0933366E-02 6.9999859E-02 0.000000 - Av 2018 2 28 21 0 0.7710459 4.9460923E-05 6.7758001E-04 3.1053396E-03 1.8629003E-02 9.9999802E-03 0.000000 - Av 2018 2 28 22 0 0.5259811 1.4757780E-04 6.7803089E-04 3.1243002E-03 1.9692915E-02 1.9999960E-02 0.000000 - Av 2018 2 28 23 0 0.9325913 1.7946700E-04 7.7198341E-04 3.1630187E-03 6.1628308E-02 6.9999859E-02 0.000000 - Av 2018 2 28 24 0 0.7349890 1.0184388E-06 8.5633289E-04 3.1925004E-03 1.0804440E-02 0.000000 0.000000 - Av 2018 3 1 1 0 0.3827288 0.000000 8.4375450E-04 3.1235924E-03 2.9668997E-03 0.000000 0.000000 - Av 2018 3 1 2 0 0.4328475 0.000000 8.3130779E-04 3.1218571E-03 1.1206118E-03 0.000000 0.000000 - Av 2018 3 1 3 0 0.4436626 3.8061949E-05 8.2106784E-04 3.1268224E-03 6.7411903E-03 9.9999802E-03 0.000000 - Av 2018 3 1 4 0 0.4481101 0.000000 8.1096886E-04 3.1324439E-03 2.4261887E-03 0.000000 0.000000 - Av 2018 3 1 5 0 0.4021181 0.000000 7.9900579E-04 3.1306678E-03 9.5876987E-04 0.000000 0.000000 - Av 2018 3 1 6 0 0.4028899 0.000000 7.8721927E-04 3.1288837E-03 4.5921313E-04 0.000000 0.000000 + Av 2018 2 28 18 0 0.4042187 0.000000 4.9960363E-04 3.0219133E-03 2.5546474E-03 0.000000 0.000000 + Av 2018 2 28 19 0 0.4666163 1.3570269E-04 4.9942738E-04 3.0319449E-03 1.4544673E-02 1.9999960E-02 0.000000 + Av 2018 2 28 20 0 0.8739282 1.6809821E-04 5.9167936E-04 3.0698499E-03 6.0933366E-02 6.9999859E-02 0.000000 + Av 2018 2 28 21 0 0.7710459 4.9460923E-05 6.7758001E-04 3.1053396E-03 1.8629003E-02 9.9999802E-03 0.000000 + Av 2018 2 28 22 0 0.5259811 1.4757780E-04 6.7803089E-04 3.1243002E-03 1.9692915E-02 1.9999960E-02 0.000000 + Av 2018 2 28 23 0 0.9325913 1.7946700E-04 7.7198341E-04 3.1630187E-03 6.1628308E-02 6.9999859E-02 0.000000 + Av 2018 2 28 24 0 0.7349890 1.0184388E-06 8.5633289E-04 3.1925004E-03 1.0804440E-02 0.000000 0.000000 + Av 2018 3 1 1 0 0.3827288 0.000000 8.4375450E-04 3.1235924E-03 2.9668997E-03 0.000000 0.000000 + Av 2018 3 1 2 0 0.4328475 0.000000 8.3130779E-04 3.1218571E-03 1.1206118E-03 0.000000 0.000000 + Av 2018 3 1 3 0 0.4436626 3.8061949E-05 8.2106784E-04 3.1268224E-03 6.7411903E-03 9.9999802E-03 0.000000 + Av 2018 3 1 4 0 0.4481101 0.000000 8.1096886E-04 3.1324439E-03 2.4261887E-03 0.000000 0.000000 + Av 2018 3 1 5 0 0.4021181 0.000000 7.9900579E-04 3.1306678E-03 9.5876987E-04 0.000000 0.000000 + Av 2018 3 1 6 0 0.4028899 0.000000 7.8721927E-04 3.1288837E-03 4.5921313E-04 0.000000 0.000000 Av 2018 3 1 7 0 0.3850495 0.000000 7.7560649E-04 2.9676436E-03 2.5117918E-04 0.000000 7.2476518E-04 Av 2018 3 1 8 0 0.3540107 0.000000 7.6416513E-04 2.6388890E-03 1.5119390E-04 0.000000 2.2109244E-03 Av 2018 3 1 9 0 0.3464101 2.2400935E-05 7.5408351E-04 2.3153711E-03 3.9284974E-03 9.9999802E-03 3.6970838E-03 @@ -1457,19 +1457,19 @@ Av 2018 3 1 15 0 0.3003720 0.000000 6.9085381E-04 2.3100993E-03 8.5527543E-05 0.000000 3.6970838E-03 Av 2018 3 1 16 0 0.3250386 0.000000 6.8066263E-04 2.6351828E-03 5.9365411E-05 0.000000 2.2109244E-03 Av 2018 3 1 17 0 0.3605737 0.000000 6.7062175E-04 2.9602600E-03 4.2906369E-05 9.9999802E-03 7.2476518E-04 - Av 2018 3 1 18 0 0.3808709 0.000000 6.6072901E-04 3.1178233E-03 1.9952866E-04 0.000000 0.000000 - Av 2018 3 1 19 0 0.3829280 0.000000 6.5098226E-04 3.1159318E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 3 1 20 0 0.3792849 0.000000 6.4137921E-04 3.1140337E-03 0.000000 0.000000 0.000000 - Av 2018 3 1 21 0 0.3776647 0.000000 6.3191785E-04 3.1121292E-03 0.000000 0.000000 0.000000 - Av 2018 3 1 22 0 0.4214872 9.4847252E-05 6.2764110E-04 3.1204047E-03 5.1036556E-03 1.9999960E-02 0.000000 - Av 2018 3 1 23 0 0.4212271 0.000000 6.2340242E-04 3.1299039E-03 2.1117744E-03 0.000000 0.000000 - Av 2018 3 1 24 0 0.3830037 0.000000 6.1420631E-04 3.1279579E-03 8.6033944E-04 0.000000 0.000000 - Av 2018 3 2 1 0 0.3787682 0.000000 6.0514576E-04 3.0593227E-03 4.2066356E-04 0.000000 0.000000 - Av 2018 3 2 2 0 0.3699714 0.000000 5.9621892E-04 3.0574847E-03 2.3348774E-04 0.000000 0.000000 - Av 2018 3 2 3 0 0.3696829 0.000000 5.8742374E-04 3.0556403E-03 1.4207057E-04 0.000000 0.000000 - Av 2018 3 2 4 0 0.3673888 0.000000 5.7875837E-04 3.0537900E-03 9.2620998E-05 0.000000 0.000000 - Av 2018 3 2 5 0 0.3662333 0.000000 5.7022076E-04 3.0519341E-03 6.3691754E-05 0.000000 0.000000 - Av 2018 3 2 6 0 0.3649119 0.000000 5.6180917E-04 3.0500719E-03 4.5689449E-05 0.000000 0.000000 + Av 2018 3 1 18 0 0.3808709 0.000000 6.6072901E-04 3.1178233E-03 1.9952866E-04 0.000000 0.000000 + Av 2018 3 1 19 0 0.3829280 0.000000 6.5098226E-04 3.1159318E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 3 1 20 0 0.3792849 0.000000 6.4137921E-04 3.1140337E-03 0.000000 0.000000 0.000000 + Av 2018 3 1 21 0 0.3776647 0.000000 6.3191785E-04 3.1121292E-03 0.000000 0.000000 0.000000 + Av 2018 3 1 22 0 0.4214872 9.4847252E-05 6.2764110E-04 3.1204047E-03 5.1036556E-03 1.9999960E-02 0.000000 + Av 2018 3 1 23 0 0.4212271 0.000000 6.2340242E-04 3.1299039E-03 2.1117744E-03 0.000000 0.000000 + Av 2018 3 1 24 0 0.3830037 0.000000 6.1420631E-04 3.1279579E-03 8.6033944E-04 0.000000 0.000000 + Av 2018 3 2 1 0 0.3787682 0.000000 6.0514576E-04 3.0593227E-03 4.2066356E-04 0.000000 0.000000 + Av 2018 3 2 2 0 0.3699714 0.000000 5.9621892E-04 3.0574847E-03 2.3348774E-04 0.000000 0.000000 + Av 2018 3 2 3 0 0.3696829 0.000000 5.8742374E-04 3.0556403E-03 1.4207057E-04 0.000000 0.000000 + Av 2018 3 2 4 0 0.3673888 0.000000 5.7875837E-04 3.0537900E-03 9.2620998E-05 0.000000 0.000000 + Av 2018 3 2 5 0 0.3662333 0.000000 5.7022076E-04 3.0519341E-03 6.3691754E-05 0.000000 0.000000 + Av 2018 3 2 6 0 0.3649119 0.000000 5.6180917E-04 3.0500719E-03 4.5689449E-05 0.000000 0.000000 Av 2018 3 2 7 0 0.3525579 0.000000 5.5352156E-04 2.8844434E-03 3.3915781E-05 0.000000 7.4436737E-04 Av 2018 3 2 8 0 0.3233228 0.000000 5.4535625E-04 2.5643064E-03 1.7327885E-04 0.000000 2.1910190E-03 Av 2018 3 2 9 0 0.2883173 0.000000 5.3731137E-04 2.2441638E-03 0.000000 0.000000 3.6376705E-03 @@ -1481,19 +1481,19 @@ Av 2018 3 2 15 0 0.2717527 0.000000 4.9147406E-04 2.2327765E-03 0.000000 0.000000 3.6376705E-03 Av 2018 3 2 16 0 0.2960536 0.000000 4.8422403E-04 2.5491240E-03 0.000000 0.000000 2.1910190E-03 Av 2018 3 2 17 0 0.3299277 0.000000 4.7708096E-04 2.8654658E-03 0.000000 0.000000 7.4436737E-04 - Av 2018 3 2 18 0 0.3499228 0.000000 4.7004331E-04 3.0273006E-03 0.000000 0.000000 0.000000 - Av 2018 3 2 19 0 0.3529754 0.000000 4.6310943E-04 3.0253697E-03 0.000000 0.000000 0.000000 - Av 2018 3 2 20 0 0.3532592 0.000000 4.5627783E-04 3.0234337E-03 0.000000 1.9999960E-02 0.000000 - Av 2018 3 2 21 0 0.3519756 0.000000 4.4954705E-04 3.0214931E-03 0.000000 0.000000 0.000000 - Av 2018 3 2 22 0 0.3487068 0.000000 4.4291551E-04 3.0195480E-03 0.000000 0.000000 0.000000 - Av 2018 3 2 23 0 0.3486843 0.000000 4.3638182E-04 3.0175981E-03 0.000000 0.000000 0.000000 - Av 2018 3 2 24 0 0.3475455 0.000000 4.2994448E-04 3.0156435E-03 0.000000 0.000000 0.000000 - Av 2018 3 3 1 0 0.3424705 0.000000 4.2360212E-04 2.9498562E-03 0.000000 0.000000 0.000000 - Av 2018 3 3 2 0 0.3387841 0.000000 4.1735332E-04 2.9480066E-03 0.000000 0.000000 0.000000 - Av 2018 3 3 3 0 0.3389714 0.000000 4.1119670E-04 2.9461531E-03 0.000000 0.000000 0.000000 - Av 2018 3 3 4 0 0.3378236 0.000000 4.0513091E-04 2.9442948E-03 0.000000 0.000000 0.000000 - Av 2018 3 3 5 0 0.3371517 0.000000 3.9915458E-04 2.9424324E-03 0.000000 0.000000 0.000000 - Av 2018 3 3 6 0 0.3363259 0.000000 3.9326644E-04 2.9405656E-03 0.000000 0.000000 0.000000 + Av 2018 3 2 18 0 0.3499228 0.000000 4.7004331E-04 3.0273006E-03 0.000000 0.000000 0.000000 + Av 2018 3 2 19 0 0.3529754 0.000000 4.6310943E-04 3.0253697E-03 0.000000 0.000000 0.000000 + Av 2018 3 2 20 0 0.3532592 0.000000 4.5627783E-04 3.0234337E-03 0.000000 1.9999960E-02 0.000000 + Av 2018 3 2 21 0 0.3519756 0.000000 4.4954705E-04 3.0214931E-03 0.000000 0.000000 0.000000 + Av 2018 3 2 22 0 0.3487068 0.000000 4.4291551E-04 3.0195480E-03 0.000000 0.000000 0.000000 + Av 2018 3 2 23 0 0.3486843 0.000000 4.3638182E-04 3.0175981E-03 0.000000 0.000000 0.000000 + Av 2018 3 2 24 0 0.3475455 0.000000 4.2994448E-04 3.0156435E-03 0.000000 0.000000 0.000000 + Av 2018 3 3 1 0 0.3424705 0.000000 4.2360212E-04 2.9498562E-03 0.000000 0.000000 0.000000 + Av 2018 3 3 2 0 0.3387841 0.000000 4.1735332E-04 2.9480066E-03 0.000000 0.000000 0.000000 + Av 2018 3 3 3 0 0.3389714 0.000000 4.1119670E-04 2.9461531E-03 0.000000 0.000000 0.000000 + Av 2018 3 3 4 0 0.3378236 0.000000 4.0513091E-04 2.9442948E-03 0.000000 0.000000 0.000000 + Av 2018 3 3 5 0 0.3371517 0.000000 3.9915458E-04 2.9424324E-03 0.000000 0.000000 0.000000 + Av 2018 3 3 6 0 0.3363259 0.000000 3.9326644E-04 2.9405656E-03 0.000000 0.000000 0.000000 Av 2018 3 3 7 0 0.3230401 0.000000 3.8746514E-04 2.7558799E-03 0.000000 0.000000 8.3097443E-04 Av 2018 3 3 8 0 0.2909795 0.000000 3.8174941E-04 2.4163914E-03 0.000000 0.000000 2.3655801E-03 Av 2018 3 3 9 0 0.2548900 0.000000 3.7611803E-04 2.0768989E-03 0.000000 0.000000 3.9001855E-03 @@ -1505,19 +1505,19 @@ Av 2018 3 3 15 0 0.2399619 0.000000 3.4403184E-04 2.0655396E-03 0.000000 0.000000 3.9001855E-03 Av 2018 3 3 16 0 0.2658027 0.000000 3.3895683E-04 2.4012458E-03 0.000000 0.000000 2.3655801E-03 Av 2018 3 3 17 0 0.3020623 0.000000 3.3395668E-04 2.7369489E-03 0.000000 0.000000 8.3097443E-04 - Av 2018 3 3 18 0 0.3241320 0.000000 3.2903030E-04 2.9178495E-03 0.000000 0.000000 0.000000 - Av 2018 3 3 19 0 0.3280501 0.000000 3.2417657E-04 2.9159319E-03 0.000000 0.000000 0.000000 - Av 2018 3 3 20 0 0.3257723 0.000000 3.1939446E-04 2.9140108E-03 0.000000 0.000000 0.000000 - Av 2018 3 3 21 0 0.3256580 0.000000 3.1468287E-04 2.9120862E-03 0.000000 0.000000 0.000000 - Av 2018 3 3 22 0 0.3248004 0.000000 3.1004081E-04 2.9101581E-03 0.000000 0.000000 0.000000 - Av 2018 3 3 23 0 0.3242102 0.000000 3.0546723E-04 2.9082266E-03 0.000000 0.000000 0.000000 - Av 2018 3 3 24 0 0.3235358 0.000000 3.0096111E-04 2.9062917E-03 0.000000 0.000000 0.000000 - Av 2018 3 4 1 0 0.3187510 0.000000 2.9652147E-04 2.8432980E-03 0.000000 0.000000 0.000000 - Av 2018 3 4 2 0 0.3154112 0.000000 2.9214731E-04 2.8414647E-03 0.000000 0.000000 0.000000 - Av 2018 3 4 3 0 0.3157331 0.000000 2.8783770E-04 2.8396284E-03 0.000000 0.000000 0.000000 - Av 2018 3 4 4 0 0.3147901 0.000000 2.8359162E-04 2.8377885E-03 0.000000 0.000000 0.000000 - 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Av 2018 3 4 18 0 0.3033071 0.000000 2.3032125E-04 2.8117136E-03 0.000000 0.000000 0.000000 - Av 2018 3 4 19 0 0.3075563 0.000000 2.2692364E-04 2.8098300E-03 0.000000 0.000000 0.000000 - Av 2018 3 4 20 0 0.3053644 0.000000 2.2357618E-04 2.8079438E-03 0.000000 0.000000 0.000000 - Av 2018 3 4 21 0 0.3054185 0.000000 2.2027807E-04 2.8060549E-03 0.000000 0.000000 0.000000 - Av 2018 3 4 22 0 0.3046980 0.000000 2.1702862E-04 2.8041636E-03 0.000000 0.000000 0.000000 - Av 2018 3 4 23 0 0.3042530 0.000000 2.1382711E-04 2.8022698E-03 0.000000 0.000000 0.000000 - Av 2018 3 4 24 0 0.3037184 0.000000 2.1067282E-04 2.8003736E-03 0.000000 0.000000 0.000000 - Av 2018 3 5 1 0 0.2992546 0.000000 2.0756507E-04 2.7400979E-03 0.000000 0.000000 0.000000 - Av 2018 3 5 2 0 0.2961699 0.000000 2.0450316E-04 2.7382991E-03 0.000000 0.000000 0.000000 - Av 2018 3 5 3 0 0.2965849 0.000000 2.0148641E-04 2.7364979E-03 0.000000 0.000000 0.000000 - Av 2018 3 5 4 0 0.2957888 0.000000 1.9851419E-04 2.7346942E-03 0.000000 0.000000 0.000000 - 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Av 2018 3 5 18 0 0.2856061 0.000000 1.6122486E-04 2.7092057E-03 0.000000 0.000000 0.000000 - Av 2018 3 5 19 0 0.2904645 0.000000 1.5884654E-04 2.7073694E-03 0.000000 0.000000 0.000000 - Av 2018 3 5 20 0 0.2882048 0.000000 1.5650332E-04 2.7055312E-03 0.000000 0.000000 0.000000 - Av 2018 3 5 21 0 0.2884245 0.000000 1.5419464E-04 2.7036911E-03 0.000000 0.000000 0.000000 - Av 2018 3 5 22 0 0.2877865 0.000000 1.5192003E-04 2.7018492E-03 0.000000 0.000000 0.000000 - Av 2018 3 5 23 0 0.2874511 0.000000 1.4967898E-04 2.7000054E-03 0.000000 0.000000 0.000000 - Av 2018 3 5 24 0 0.2870148 0.000000 1.4747097E-04 2.6981598E-03 0.000000 0.000000 0.000000 - Av 2018 3 6 1 0 0.2828266 0.000000 1.4529553E-04 2.6405146E-03 0.000000 0.000000 0.000000 - Av 2018 3 6 2 0 0.2799537 0.000000 1.4315220E-04 2.6387621E-03 0.000000 0.000000 0.000000 - Av 2018 3 6 3 0 0.2804252 0.000000 1.4104048E-04 2.6370077E-03 0.000000 0.000000 0.000000 - Av 2018 3 6 4 0 0.2797379 0.000000 1.3895992E-04 2.6352515E-03 0.000000 0.000000 0.000000 - Av 2018 3 6 5 0 0.2794575 0.000000 1.3691004E-04 2.6334936E-03 0.000000 0.000000 0.000000 - Av 2018 3 6 6 0 0.2790395 0.000000 1.3489040E-04 2.6317339E-03 0.000000 0.000000 0.000000 + Av 2018 3 5 18 0 0.2856061 0.000000 1.6122486E-04 2.7092057E-03 0.000000 0.000000 0.000000 + Av 2018 3 5 19 0 0.2904645 0.000000 1.5884654E-04 2.7073694E-03 0.000000 0.000000 0.000000 + Av 2018 3 5 20 0 0.2882048 0.000000 1.5650332E-04 2.7055312E-03 0.000000 0.000000 0.000000 + Av 2018 3 5 21 0 0.2884245 0.000000 1.5419464E-04 2.7036911E-03 0.000000 0.000000 0.000000 + Av 2018 3 5 22 0 0.2877865 0.000000 1.5192003E-04 2.7018492E-03 0.000000 0.000000 0.000000 + Av 2018 3 5 23 0 0.2874511 0.000000 1.4967898E-04 2.7000054E-03 0.000000 0.000000 0.000000 + Av 2018 3 5 24 0 0.2870148 0.000000 1.4747097E-04 2.6981598E-03 0.000000 0.000000 0.000000 + Av 2018 3 6 1 0 0.2828266 0.000000 1.4529553E-04 2.6405146E-03 0.000000 0.000000 0.000000 + Av 2018 3 6 2 0 0.2799537 0.000000 1.4315220E-04 2.6387621E-03 0.000000 0.000000 0.000000 + Av 2018 3 6 3 0 0.2804252 0.000000 1.4104048E-04 2.6370077E-03 0.000000 0.000000 0.000000 + Av 2018 3 6 4 0 0.2797379 0.000000 1.3895992E-04 2.6352515E-03 0.000000 0.000000 0.000000 + Av 2018 3 6 5 0 0.2794575 0.000000 1.3691004E-04 2.6334936E-03 0.000000 0.000000 0.000000 + Av 2018 3 6 6 0 0.2790395 0.000000 1.3489040E-04 2.6317339E-03 0.000000 0.000000 0.000000 Av 2018 3 6 7 0 0.2640287 0.000000 1.3290056E-04 2.4160596E-03 0.000000 0.000000 9.7233168E-04 Av 2018 3 6 8 0 0.2305952 0.000000 1.3094007E-04 2.0707941E-03 0.000000 0.000000 2.5337061E-03 Av 2018 3 6 9 0 0.1947430 0.000000 1.2900849E-04 1.7255270E-03 0.000000 0.000000 4.0950808E-03 @@ -1577,19 +1577,19 @@ Av 2018 3 6 15 0 0.1822778 0.000000 1.1800294E-04 1.7149050E-03 0.000000 0.000000 4.0950808E-03 Av 2018 3 6 16 0 0.2081842 0.000000 1.1626221E-04 2.0566315E-03 0.000000 0.000000 2.5337061E-03 Av 2018 3 6 17 0 0.2456500 0.000000 1.1454715E-04 2.3983568E-03 0.000000 0.000000 9.7233168E-04 - Av 2018 3 6 18 0 0.2702584 0.000000 1.1285741E-04 2.6104911E-03 0.000000 0.000000 0.000000 - Av 2018 3 6 19 0 0.2758666 0.000000 1.1119259E-04 2.6087109E-03 0.000000 0.000000 0.000000 - Av 2018 3 6 20 0 0.2734500 0.000000 1.0955232E-04 2.6069293E-03 0.000000 0.000000 0.000000 - Av 2018 3 6 21 0 0.2738268 0.000000 1.0793625E-04 2.6051465E-03 0.000000 0.000000 0.000000 - Av 2018 3 6 22 0 0.2732354 0.000000 1.0634402E-04 2.6033621E-03 0.000000 0.000000 0.000000 - Av 2018 3 6 23 0 0.2729837 0.000000 1.0477528E-04 2.6015767E-03 0.000000 0.000000 0.000000 - Av 2018 3 6 24 0 0.2726169 0.000000 1.0322969E-04 2.5997898E-03 0.000000 0.000000 0.000000 - Av 2018 3 7 1 0 0.2686702 0.000000 1.0170689E-04 2.5446794E-03 0.000000 0.000000 0.000000 - Av 2018 3 7 2 0 0.2659773 0.000000 1.0020655E-04 2.5429812E-03 0.000000 0.000000 0.000000 - Av 2018 3 7 3 0 0.2664804 0.000000 9.8728342E-05 2.5412813E-03 0.000000 0.000000 0.000000 - Av 2018 3 7 4 0 0.2658750 0.000000 9.7271943E-05 2.5395800E-03 0.000000 0.000000 0.000000 - Av 2018 3 7 5 0 0.2656577 0.000000 9.5837029E-05 2.5378775E-03 0.000000 0.000000 0.000000 - Av 2018 3 7 6 0 0.2653083 0.000000 9.4423282E-05 2.5361739E-03 0.000000 0.000000 0.000000 + Av 2018 3 6 18 0 0.2702584 0.000000 1.1285741E-04 2.6104911E-03 0.000000 0.000000 0.000000 + Av 2018 3 6 19 0 0.2758666 0.000000 1.1119259E-04 2.6087109E-03 0.000000 0.000000 0.000000 + Av 2018 3 6 20 0 0.2734500 0.000000 1.0955232E-04 2.6069293E-03 0.000000 0.000000 0.000000 + Av 2018 3 6 21 0 0.2738268 0.000000 1.0793625E-04 2.6051465E-03 0.000000 0.000000 0.000000 + Av 2018 3 6 22 0 0.2732354 0.000000 1.0634402E-04 2.6033621E-03 0.000000 0.000000 0.000000 + Av 2018 3 6 23 0 0.2729837 0.000000 1.0477528E-04 2.6015767E-03 0.000000 0.000000 0.000000 + Av 2018 3 6 24 0 0.2726169 0.000000 1.0322969E-04 2.5997898E-03 0.000000 0.000000 0.000000 + Av 2018 3 7 1 0 0.2686702 0.000000 1.0170689E-04 2.5446794E-03 0.000000 0.000000 0.000000 + Av 2018 3 7 2 0 0.2659773 0.000000 1.0020655E-04 2.5429812E-03 0.000000 0.000000 0.000000 + Av 2018 3 7 3 0 0.2664804 0.000000 9.8728342E-05 2.5412813E-03 0.000000 0.000000 0.000000 + Av 2018 3 7 4 0 0.2658750 0.000000 9.7271943E-05 2.5395800E-03 0.000000 0.000000 0.000000 + Av 2018 3 7 5 0 0.2656577 0.000000 9.5837029E-05 2.5378775E-03 0.000000 0.000000 0.000000 + Av 2018 3 7 6 0 0.2653083 0.000000 9.4423282E-05 2.5361739E-03 0.000000 0.000000 0.000000 Av 2018 3 7 7 0 0.2463410 0.000000 9.3030394E-05 2.2617551E-03 0.000000 0.000000 1.2396080E-03 Av 2018 3 7 8 0 0.2051554 0.000000 9.1658054E-05 1.8404543E-03 0.000000 0.000000 3.1468554E-03 Av 2018 3 7 9 0 0.1617130 0.000000 9.0305955E-05 1.4191522E-03 0.000000 0.000000 5.0541027E-03 @@ -1601,19 +1601,19 @@ Av 2018 3 7 15 0 0.1473963 0.000000 8.2602062E-05 1.4085571E-03 0.000000 0.000000 5.0541027E-03 Av 2018 3 7 16 0 0.1790088 0.000000 8.1383550E-05 1.8263222E-03 0.000000 0.000000 3.1468554E-03 Av 2018 3 7 17 0 0.2249100 0.000000 8.0183017E-05 2.2440741E-03 0.000000 0.000000 1.2396080E-03 - Av 2018 3 7 18 0 0.2558391 0.000000 7.9000187E-05 2.5149388E-03 0.000000 0.000000 0.000000 - Av 2018 3 7 19 0 0.2633241 0.000000 7.7834811E-05 2.5130876E-03 0.000000 0.000000 0.000000 - Av 2018 3 7 20 0 0.2603128 0.000000 7.6686621E-05 2.5112364E-03 0.000000 0.000000 0.000000 - Av 2018 3 7 21 0 0.2609534 0.000000 7.5555377E-05 2.5093851E-03 0.000000 0.000000 0.000000 - Av 2018 3 7 22 0 0.2603265 0.000000 7.4440817E-05 2.5075336E-03 0.000000 0.000000 0.000000 - Av 2018 3 7 23 0 0.2601425 0.000000 7.3342700E-05 2.5056824E-03 0.000000 0.000000 0.000000 - Av 2018 3 7 24 0 0.2598068 0.000000 7.2260780E-05 2.5038312E-03 0.000000 0.000000 0.000000 - Av 2018 3 8 1 0 0.2560670 0.000000 7.1194823E-05 2.4510699E-03 0.000000 0.000000 0.000000 - Av 2018 3 8 2 0 0.2535189 0.000000 7.0144582E-05 2.4493057E-03 0.000000 0.000000 0.000000 - Av 2018 3 8 3 0 0.2540235 0.000000 6.9109847E-05 2.4475416E-03 0.000000 0.000000 0.000000 - Av 2018 3 8 4 0 0.2534688 0.000000 6.8090369E-05 2.4457772E-03 0.000000 0.000000 0.000000 - Av 2018 3 8 5 0 0.2532844 0.000000 6.7085930E-05 2.4440128E-03 0.000000 0.000000 0.000000 - Av 2018 3 8 6 0 0.2529732 0.000000 6.6096305E-05 2.4422482E-03 0.000000 0.000000 0.000000 + Av 2018 3 7 18 0 0.2558391 0.000000 7.9000187E-05 2.5149388E-03 0.000000 0.000000 0.000000 + Av 2018 3 7 19 0 0.2633241 0.000000 7.7834811E-05 2.5130876E-03 0.000000 0.000000 0.000000 + Av 2018 3 7 20 0 0.2603128 0.000000 7.6686621E-05 2.5112364E-03 0.000000 0.000000 0.000000 + Av 2018 3 7 21 0 0.2609534 0.000000 7.5555377E-05 2.5093851E-03 0.000000 0.000000 0.000000 + Av 2018 3 7 22 0 0.2603265 0.000000 7.4440817E-05 2.5075336E-03 0.000000 0.000000 0.000000 + Av 2018 3 7 23 0 0.2601425 0.000000 7.3342700E-05 2.5056824E-03 0.000000 0.000000 0.000000 + Av 2018 3 7 24 0 0.2598068 0.000000 7.2260780E-05 2.5038312E-03 0.000000 0.000000 0.000000 + Av 2018 3 8 1 0 0.2560670 0.000000 7.1194823E-05 2.4510699E-03 0.000000 0.000000 0.000000 + Av 2018 3 8 2 0 0.2535189 0.000000 7.0144582E-05 2.4493057E-03 0.000000 0.000000 0.000000 + Av 2018 3 8 3 0 0.2540235 0.000000 6.9109847E-05 2.4475416E-03 0.000000 0.000000 0.000000 + Av 2018 3 8 4 0 0.2534688 0.000000 6.8090369E-05 2.4457772E-03 0.000000 0.000000 0.000000 + Av 2018 3 8 5 0 0.2532844 0.000000 6.7085930E-05 2.4440128E-03 0.000000 0.000000 0.000000 + Av 2018 3 8 6 0 0.2529732 0.000000 6.6096305E-05 2.4422482E-03 0.000000 0.000000 0.000000 Av 2018 3 8 7 0 0.2349457 0.000000 6.5121276E-05 2.1651436E-03 0.000000 9.9999802E-03 1.2515462E-03 Av 2018 3 8 8 0 0.1982062 0.000000 6.4160638E-05 1.7567959E-03 0.000000 3.9999921E-02 3.0996518E-03 Av 2018 3 8 9 0 0.1594345 0.000000 6.3214167E-05 1.3484483E-03 0.000000 5.9999879E-02 4.9477578E-03 @@ -1625,19 +1625,19 @@ Av 2018 3 8 15 0 0.1570836 0.000000 1.5215777E-04 1.4166493E-03 4.0061667E-04 0.000000 4.9477578E-03 Av 2018 3 8 16 0 0.1894773 0.000000 1.4991320E-04 1.8214223E-03 2.2415731E-04 0.000000 3.0996518E-03 Av 2018 3 8 17 0 0.2324008 0.000000 1.4770175E-04 2.2261951E-03 1.3720802E-04 9.9999802E-03 1.2515462E-03 - Av 2018 3 8 18 0 0.2637037 0.000000 1.4552291E-04 2.4997245E-03 8.9858804E-05 9.9999802E-03 0.000000 - Av 2018 3 8 19 0 0.2696092 0.000000 1.4337622E-04 2.4979138E-03 6.2013212E-05 0.000000 0.000000 - Av 2018 3 8 20 0 0.2656333 0.000000 1.4126119E-04 2.4961026E-03 4.4612869E-05 0.000000 0.000000 - Av 2018 3 8 21 0 0.3124181 7.9355792E-05 1.4341167E-04 2.5035506E-03 5.5670976E-03 1.9999960E-02 0.000000 - Av 2018 3 8 22 0 0.3123351 0.000000 1.4550948E-04 2.5121798E-03 2.2233760E-03 0.000000 0.000000 - Av 2018 3 8 23 0 0.2734697 0.000000 1.4336297E-04 2.5103472E-03 8.9568534E-04 0.000000 0.000000 - Av 2018 3 8 24 0 0.2742914 0.000000 1.4124814E-04 2.5085143E-03 4.3461792E-04 0.000000 0.000000 - Av 2018 3 9 1 0 0.2655499 0.000000 1.3916451E-04 2.4556699E-03 2.3992882E-04 0.000000 0.000000 - Av 2018 3 9 2 0 0.2626342 0.000000 1.3711161E-04 2.4539239E-03 1.4540651E-04 0.000000 0.000000 - Av 2018 3 9 3 0 0.2621458 0.000000 1.3508901E-04 2.4521777E-03 9.4506882E-05 0.000000 0.000000 - Av 2018 3 9 4 0 0.2612581 0.000000 1.3309623E-04 2.4504312E-03 6.4833395E-05 0.000000 0.000000 - Av 2018 3 9 5 0 0.2607338 0.000000 1.3113285E-04 2.4486845E-03 4.6419445E-05 0.000000 0.000000 - Av 2018 3 9 6 0 0.2602072 0.000000 1.2919844E-04 2.4469376E-03 3.4403827E-05 0.000000 0.000000 + Av 2018 3 8 18 0 0.2637037 0.000000 1.4552291E-04 2.4997245E-03 8.9858804E-05 9.9999802E-03 0.000000 + Av 2018 3 8 19 0 0.2696092 0.000000 1.4337622E-04 2.4979138E-03 6.2013212E-05 0.000000 0.000000 + Av 2018 3 8 20 0 0.2656333 0.000000 1.4126119E-04 2.4961026E-03 4.4612869E-05 0.000000 0.000000 + Av 2018 3 8 21 0 0.3124181 7.9355792E-05 1.4341167E-04 2.5035506E-03 5.5670976E-03 1.9999960E-02 0.000000 + Av 2018 3 8 22 0 0.3123351 0.000000 1.4550948E-04 2.5121798E-03 2.2233760E-03 0.000000 0.000000 + Av 2018 3 8 23 0 0.2734697 0.000000 1.4336297E-04 2.5103472E-03 8.9568534E-04 0.000000 0.000000 + Av 2018 3 8 24 0 0.2742914 0.000000 1.4124814E-04 2.5085143E-03 4.3461792E-04 0.000000 0.000000 + Av 2018 3 9 1 0 0.2655499 0.000000 1.3916451E-04 2.4556699E-03 2.3992882E-04 0.000000 0.000000 + Av 2018 3 9 2 0 0.2626342 0.000000 1.3711161E-04 2.4539239E-03 1.4540651E-04 0.000000 0.000000 + Av 2018 3 9 3 0 0.2621458 0.000000 1.3508901E-04 2.4521777E-03 9.4506882E-05 0.000000 0.000000 + Av 2018 3 9 4 0 0.2612581 0.000000 1.3309623E-04 2.4504312E-03 6.4833395E-05 0.000000 0.000000 + Av 2018 3 9 5 0 0.2607338 0.000000 1.3113285E-04 2.4486845E-03 4.6419445E-05 0.000000 0.000000 + Av 2018 3 9 6 0 0.2602072 0.000000 1.2919844E-04 2.4469376E-03 3.4403827E-05 0.000000 0.000000 Av 2018 3 9 7 0 0.2413708 0.000000 1.2729254E-04 2.1618383E-03 1.7477035E-04 0.000000 1.2879649E-03 Av 2018 3 9 8 0 0.2002968 0.000000 1.2541479E-04 1.7578949E-03 0.000000 0.000000 3.1161304E-03 Av 2018 3 9 9 0 0.1579389 0.000000 1.2356472E-04 1.3539511E-03 0.000000 0.000000 4.9442956E-03 @@ -1649,19 +1649,19 @@ Av 2018 3 9 15 0 0.1443922 0.000000 1.1302358E-04 1.3434639E-03 0.000000 0.000000 4.9442956E-03 Av 2018 3 9 16 0 0.1749796 0.000000 1.1135630E-04 1.7439120E-03 0.000000 9.9999802E-03 3.1161304E-03 Av 2018 3 9 17 0 0.2188092 0.000000 1.0971362E-04 2.1443598E-03 0.000000 0.000000 1.2879649E-03 - Av 2018 3 9 18 0 0.2491199 0.000000 1.0809517E-04 2.4259638E-03 0.000000 0.000000 0.000000 - Av 2018 3 9 19 0 0.2575012 0.000000 1.0650059E-04 2.4242152E-03 0.000000 0.000000 0.000000 - Av 2018 3 9 20 0 0.2541343 0.000000 1.0492955E-04 2.4224666E-03 0.000000 0.000000 0.000000 - Av 2018 3 9 21 0 0.2548555 0.000000 1.0338167E-04 2.4207181E-03 0.000000 0.000000 0.000000 - Av 2018 3 9 22 0 0.2541583 0.000000 1.0185663E-04 2.4189695E-03 0.000000 0.000000 0.000000 - Av 2018 3 9 23 0 0.2539574 0.000000 1.0035410E-04 2.4172210E-03 0.000000 0.000000 0.000000 - Av 2018 3 9 24 0 0.2535870 0.000000 9.8873708E-05 2.4154724E-03 0.000000 0.000000 0.000000 - Av 2018 3 10 1 0 0.2499708 0.000000 9.7415163E-05 2.3650408E-03 0.000000 0.000000 0.000000 - Av 2018 3 10 2 0 0.2474916 0.000000 9.5978146E-05 2.3633735E-03 0.000000 0.000000 0.000000 - Av 2018 3 10 3 0 0.2479332 0.000000 9.4562318E-05 2.3617065E-03 0.000000 0.000000 0.000000 - Av 2018 3 10 4 0 0.2473622 0.000000 9.3167379E-05 2.3600394E-03 0.000000 0.000000 0.000000 - Av 2018 3 10 5 0 0.2471460 0.000000 9.1793016E-05 2.3583721E-03 0.000000 0.000000 0.000000 - Av 2018 3 10 6 0 0.2468092 0.000000 9.0438924E-05 2.3567046E-03 0.000000 0.000000 0.000000 + Av 2018 3 9 18 0 0.2491199 0.000000 1.0809517E-04 2.4259638E-03 0.000000 0.000000 0.000000 + Av 2018 3 9 19 0 0.2575012 0.000000 1.0650059E-04 2.4242152E-03 0.000000 0.000000 0.000000 + Av 2018 3 9 20 0 0.2541343 0.000000 1.0492955E-04 2.4224666E-03 0.000000 0.000000 0.000000 + Av 2018 3 9 21 0 0.2548555 0.000000 1.0338167E-04 2.4207181E-03 0.000000 0.000000 0.000000 + Av 2018 3 9 22 0 0.2541583 0.000000 1.0185663E-04 2.4189695E-03 0.000000 0.000000 0.000000 + Av 2018 3 9 23 0 0.2539574 0.000000 1.0035410E-04 2.4172210E-03 0.000000 0.000000 0.000000 + Av 2018 3 9 24 0 0.2535870 0.000000 9.8873708E-05 2.4154724E-03 0.000000 0.000000 0.000000 + Av 2018 3 10 1 0 0.2499708 0.000000 9.7415163E-05 2.3650408E-03 0.000000 0.000000 0.000000 + Av 2018 3 10 2 0 0.2474916 0.000000 9.5978146E-05 2.3633735E-03 0.000000 0.000000 0.000000 + Av 2018 3 10 3 0 0.2479332 0.000000 9.4562318E-05 2.3617065E-03 0.000000 0.000000 0.000000 + Av 2018 3 10 4 0 0.2473622 0.000000 9.3167379E-05 2.3600394E-03 0.000000 0.000000 0.000000 + Av 2018 3 10 5 0 0.2471460 0.000000 9.1793016E-05 2.3583721E-03 0.000000 0.000000 0.000000 + Av 2018 3 10 6 0 0.2468092 0.000000 9.0438924E-05 2.3567046E-03 0.000000 0.000000 0.000000 Av 2018 3 10 7 0 0.2255567 0.000000 8.9104804E-05 2.0487304E-03 0.000000 0.000000 1.3923038E-03 Av 2018 3 10 8 0 0.1829710 0.000000 8.7790373E-05 1.6285335E-03 0.000000 0.000000 3.2947117E-03 Av 2018 3 10 9 0 0.1401998 0.000000 8.6495325E-05 1.2083362E-03 0.000000 0.000000 5.1971194E-03 @@ -1673,19 +1673,19 @@ Av 2018 3 10 15 0 0.1264478 0.000000 7.9116522E-05 1.1983315E-03 0.000000 0.000000 5.1971194E-03 Av 2018 3 10 16 0 0.1572213 0.000000 7.7949429E-05 1.6151939E-03 0.000000 0.000000 3.2947117E-03 Av 2018 3 10 17 0 0.2032729 0.000000 7.6799552E-05 2.0320560E-03 0.000000 0.000000 1.3923038E-03 - Av 2018 3 10 18 0 0.2363824 0.000000 7.5666641E-05 2.3366956E-03 0.000000 0.000000 0.000000 - Av 2018 3 10 19 0 0.2454310 0.000000 7.4550437E-05 2.3350280E-03 0.000000 0.000000 0.000000 - Av 2018 3 10 20 0 0.2419076 0.000000 7.3450698E-05 2.3333607E-03 0.000000 0.000000 0.000000 - Av 2018 3 10 21 0 0.2427578 0.000000 7.2367184E-05 2.3316932E-03 0.000000 0.000000 0.000000 - Av 2018 3 10 22 0 0.2420894 0.000000 7.1299663E-05 2.3300259E-03 0.000000 0.000000 0.000000 - Av 2018 3 10 23 0 0.2419513 0.000000 7.0247879E-05 2.3283588E-03 0.000000 0.000000 0.000000 - Av 2018 3 10 24 0 0.2416309 0.000000 6.9211608E-05 2.3266918E-03 0.000000 0.000000 0.000000 - Av 2018 3 11 1 0 0.2382188 0.000000 6.8190631E-05 2.2785580E-03 0.000000 0.000000 0.000000 - Av 2018 3 11 2 0 0.2358890 0.000000 6.7184716E-05 2.2769675E-03 0.000000 0.000000 0.000000 - Av 2018 3 11 3 0 0.2363474 0.000000 6.6193636E-05 2.2753775E-03 0.000000 0.000000 0.000000 - Av 2018 3 11 4 0 0.2358382 0.000000 6.5217173E-05 2.2737873E-03 0.000000 0.000000 0.000000 - Av 2018 3 11 5 0 0.2356675 0.000000 6.4255117E-05 2.2721970E-03 0.000000 0.000000 0.000000 - Av 2018 3 11 6 0 0.2353810 0.000000 6.3307249E-05 2.2706070E-03 0.000000 0.000000 0.000000 + Av 2018 3 10 18 0 0.2363824 0.000000 7.5666641E-05 2.3366956E-03 0.000000 0.000000 0.000000 + Av 2018 3 10 19 0 0.2454310 0.000000 7.4550437E-05 2.3350280E-03 0.000000 0.000000 0.000000 + Av 2018 3 10 20 0 0.2419076 0.000000 7.3450698E-05 2.3333607E-03 0.000000 0.000000 0.000000 + Av 2018 3 10 21 0 0.2427578 0.000000 7.2367184E-05 2.3316932E-03 0.000000 0.000000 0.000000 + Av 2018 3 10 22 0 0.2420894 0.000000 7.1299663E-05 2.3300259E-03 0.000000 0.000000 0.000000 + Av 2018 3 10 23 0 0.2419513 0.000000 7.0247879E-05 2.3283588E-03 0.000000 0.000000 0.000000 + Av 2018 3 10 24 0 0.2416309 0.000000 6.9211608E-05 2.3266918E-03 0.000000 0.000000 0.000000 + Av 2018 3 11 1 0 0.2382188 0.000000 6.8190631E-05 2.2785580E-03 0.000000 0.000000 0.000000 + Av 2018 3 11 2 0 0.2358890 0.000000 6.7184716E-05 2.2769675E-03 0.000000 0.000000 0.000000 + Av 2018 3 11 3 0 0.2363474 0.000000 6.6193636E-05 2.2753775E-03 0.000000 0.000000 0.000000 + Av 2018 3 11 4 0 0.2358382 0.000000 6.5217173E-05 2.2737873E-03 0.000000 0.000000 0.000000 + Av 2018 3 11 5 0 0.2356675 0.000000 6.4255117E-05 2.2721970E-03 0.000000 0.000000 0.000000 + Av 2018 3 11 6 0 0.2353810 0.000000 6.3307249E-05 2.2706070E-03 0.000000 0.000000 0.000000 Av 2018 3 11 7 0 0.2099001 0.000000 6.2373372E-05 1.9001585E-03 0.000000 0.000000 1.6766300E-03 Av 2018 3 11 8 0 0.1599886 0.000000 6.1453262E-05 1.4127526E-03 0.000000 0.000000 3.8848841E-03 Av 2018 3 11 9 0 0.1106794 0.000000 6.0546732E-05 9.2534663E-04 0.000000 0.000000 6.0931384E-03 @@ -1697,19 +1697,19 @@ Av 2018 3 11 15 0 9.5475987E-02 0.000000 5.5381566E-05 9.1580802E-04 0.000000 0.000000 6.0931384E-03 Av 2018 3 11 16 0 0.1309614 0.000000 5.4564603E-05 1.4000344E-03 0.000000 0.000000 3.8848841E-03 Av 2018 3 11 17 0 0.1845640 0.000000 5.3759690E-05 1.8842610E-03 0.000000 0.000000 1.6766300E-03 - Av 2018 3 11 18 0 0.2239346 0.000000 5.2966650E-05 2.2515305E-03 0.000000 0.000000 0.000000 - Av 2018 3 11 19 0 0.2351297 0.000000 5.2185307E-05 2.2499415E-03 0.000000 0.000000 0.000000 - Av 2018 3 11 20 0 0.2309157 0.000000 5.1415493E-05 2.2483524E-03 0.000000 0.000000 0.000000 - Av 2018 3 11 21 0 0.2320612 0.000000 5.0657036E-05 2.2467636E-03 0.000000 0.000000 0.000000 - Av 2018 3 11 22 0 0.2313447 0.000000 4.9909766E-05 2.2451750E-03 0.000000 0.000000 0.000000 - Av 2018 3 11 23 0 0.2312772 0.000000 4.9173515E-05 2.2435861E-03 0.000000 0.000000 0.000000 - Av 2018 3 11 24 0 0.2309854 0.000000 4.8448128E-05 2.2419975E-03 0.000000 0.000000 0.000000 - Av 2018 3 12 1 0 0.2277593 0.000000 4.7733443E-05 2.1960505E-03 0.000000 0.000000 0.000000 - Av 2018 3 12 2 0 0.2255598 0.000000 4.7029298E-05 2.1945343E-03 0.000000 0.000000 0.000000 - Av 2018 3 12 3 0 0.2260236 0.000000 4.6335543E-05 2.1930183E-03 0.000000 0.000000 0.000000 - Av 2018 3 12 4 0 0.2255627 0.000000 4.5652021E-05 2.1915026E-03 0.000000 0.000000 0.000000 - Av 2018 3 12 5 0 0.2254248 0.000000 4.4978580E-05 2.1899869E-03 0.000000 0.000000 0.000000 - Av 2018 3 12 6 0 0.2251759 0.000000 4.4315075E-05 2.1884709E-03 0.000000 0.000000 0.000000 + Av 2018 3 11 18 0 0.2239346 0.000000 5.2966650E-05 2.2515305E-03 0.000000 0.000000 0.000000 + Av 2018 3 11 19 0 0.2351297 0.000000 5.2185307E-05 2.2499415E-03 0.000000 0.000000 0.000000 + Av 2018 3 11 20 0 0.2309157 0.000000 5.1415493E-05 2.2483524E-03 0.000000 0.000000 0.000000 + Av 2018 3 11 21 0 0.2320612 0.000000 5.0657036E-05 2.2467636E-03 0.000000 0.000000 0.000000 + Av 2018 3 11 22 0 0.2313447 0.000000 4.9909766E-05 2.2451750E-03 0.000000 0.000000 0.000000 + Av 2018 3 11 23 0 0.2312772 0.000000 4.9173515E-05 2.2435861E-03 0.000000 0.000000 0.000000 + Av 2018 3 11 24 0 0.2309854 0.000000 4.8448128E-05 2.2419975E-03 0.000000 0.000000 0.000000 + Av 2018 3 12 1 0 0.2277593 0.000000 4.7733443E-05 2.1960505E-03 0.000000 0.000000 0.000000 + Av 2018 3 12 2 0 0.2255598 0.000000 4.7029298E-05 2.1945343E-03 0.000000 0.000000 0.000000 + Av 2018 3 12 3 0 0.2260236 0.000000 4.6335543E-05 2.1930183E-03 0.000000 0.000000 0.000000 + Av 2018 3 12 4 0 0.2255627 0.000000 4.5652021E-05 2.1915026E-03 0.000000 0.000000 0.000000 + Av 2018 3 12 5 0 0.2254248 0.000000 4.4978580E-05 2.1899869E-03 0.000000 0.000000 0.000000 + Av 2018 3 12 6 0 0.2251759 0.000000 4.4315075E-05 2.1884709E-03 0.000000 0.000000 0.000000 Av 2018 3 12 7 0 0.1965687 0.000000 4.3661355E-05 1.7718228E-03 0.000000 0.000000 1.8869663E-03 Av 2018 3 12 8 0 0.1417831 0.000000 4.3017284E-05 1.2426074E-03 0.000000 0.000000 4.2856014E-03 Av 2018 3 12 9 0 8.8535845E-02 0.000000 4.2382711E-05 7.1339181E-04 0.000000 0.000000 6.6842362E-03 @@ -1721,19 +1721,19 @@ Av 2018 3 12 15 0 7.2546586E-02 0.000000 3.8767095E-05 7.0403086E-04 0.000000 0.000000 6.6842362E-03 Av 2018 3 12 16 0 0.1107877 0.000000 3.8195223E-05 1.2301239E-03 0.000000 0.000000 4.2856014E-03 Av 2018 3 12 17 0 0.1691256 0.000000 3.7631784E-05 1.7562080E-03 0.000000 0.000000 1.8869663E-03 - Av 2018 3 12 18 0 0.2128594 0.000000 3.7076657E-05 2.1697199E-03 0.000000 0.000000 0.000000 - Av 2018 3 12 19 0 0.2257180 0.000000 3.6529716E-05 2.1680987E-03 0.000000 0.000000 0.000000 - Av 2018 3 12 20 0 0.2209529 0.000000 3.5990844E-05 2.1664780E-03 0.000000 0.000000 0.000000 - Av 2018 3 12 21 0 0.2223169 0.000000 3.5459925E-05 2.1648579E-03 0.000000 0.000000 0.000000 - Av 2018 3 12 22 0 0.2215509 0.000000 3.4936838E-05 2.1632388E-03 0.000000 0.000000 0.000000 - Av 2018 3 12 23 0 0.2215267 0.000000 3.4421464E-05 2.1616207E-03 0.000000 0.000000 0.000000 - Av 2018 3 12 24 0 0.2212458 0.000000 3.3913693E-05 2.1600029E-03 0.000000 0.000000 0.000000 - Av 2018 3 13 1 0 0.2181797 0.000000 3.3413413E-05 2.1160650E-03 0.000000 0.000000 0.000000 - Av 2018 3 13 2 0 0.2160879 0.000000 3.2920510E-05 2.1145176E-03 0.000000 0.000000 0.000000 - Av 2018 3 13 3 0 0.2165385 0.000000 3.2434880E-05 2.1129712E-03 0.000000 0.000000 0.000000 - Av 2018 3 13 4 0 0.2161062 0.000000 3.1956413E-05 2.1114249E-03 0.000000 0.000000 0.000000 - Av 2018 3 13 5 0 0.2159819 0.000000 3.1485004E-05 2.1098799E-03 0.000000 0.000000 0.000000 - Av 2018 3 13 6 0 0.2157516 0.000000 3.1020554E-05 2.1083353E-03 0.000000 0.000000 0.000000 + Av 2018 3 12 18 0 0.2128594 0.000000 3.7076657E-05 2.1697199E-03 0.000000 0.000000 0.000000 + Av 2018 3 12 19 0 0.2257180 0.000000 3.6529716E-05 2.1680987E-03 0.000000 0.000000 0.000000 + Av 2018 3 12 20 0 0.2209529 0.000000 3.5990844E-05 2.1664780E-03 0.000000 0.000000 0.000000 + Av 2018 3 12 21 0 0.2223169 0.000000 3.5459925E-05 2.1648579E-03 0.000000 0.000000 0.000000 + Av 2018 3 12 22 0 0.2215509 0.000000 3.4936838E-05 2.1632388E-03 0.000000 0.000000 0.000000 + Av 2018 3 12 23 0 0.2215267 0.000000 3.4421464E-05 2.1616207E-03 0.000000 0.000000 0.000000 + Av 2018 3 12 24 0 0.2212458 0.000000 3.3913693E-05 2.1600029E-03 0.000000 0.000000 0.000000 + Av 2018 3 13 1 0 0.2181797 0.000000 3.3413413E-05 2.1160650E-03 0.000000 0.000000 0.000000 + Av 2018 3 13 2 0 0.2160879 0.000000 3.2920510E-05 2.1145176E-03 0.000000 0.000000 0.000000 + Av 2018 3 13 3 0 0.2165385 0.000000 3.2434880E-05 2.1129712E-03 0.000000 0.000000 0.000000 + Av 2018 3 13 4 0 0.2161062 0.000000 3.1956413E-05 2.1114249E-03 0.000000 0.000000 0.000000 + Av 2018 3 13 5 0 0.2159819 0.000000 3.1485004E-05 2.1098799E-03 0.000000 0.000000 0.000000 + Av 2018 3 13 6 0 0.2157516 0.000000 3.1020554E-05 2.1083353E-03 0.000000 0.000000 0.000000 Av 2018 3 13 7 0 0.1929617 0.000000 3.0562951E-05 1.7472124E-03 0.000000 1.9999960E-02 1.6344502E-03 Av 2018 3 13 8 0 0.1511817 0.000000 3.0112100E-05 1.3040033E-03 0.000000 5.9999879E-02 3.6420231E-03 Av 2018 3 13 9 0 0.1161332 1.0621781E-04 3.5337798E-05 8.7110989E-04 0.000000 5.9999879E-02 5.6495960E-03 @@ -1745,19 +1745,19 @@ Av 2018 3 13 15 0 0.1185525 0.000000 9.5000963E-05 9.5790334E-04 9.7511470E-04 0.000000 5.6495960E-03 Av 2018 3 13 16 0 0.1407554 0.000000 9.3599556E-05 1.3979314E-03 4.6552363E-04 0.000000 3.6420231E-03 Av 2018 3 13 17 0 0.1880261 0.000000 9.2218812E-05 1.8379602E-03 2.5404547E-04 0.000000 1.6344502E-03 - Av 2018 3 13 18 0 0.2237570 0.000000 9.0858441E-05 2.1959026E-03 1.5266059E-04 0.000000 0.000000 - Av 2018 3 13 19 0 0.2344472 0.000000 8.9518137E-05 2.1942670E-03 9.8583070E-05 0.000000 0.000000 - Av 2018 3 13 20 0 0.2307732 0.000000 8.8197601E-05 2.1926318E-03 6.7289242E-05 9.9999802E-03 0.000000 - Av 2018 3 13 21 0 0.2313067 0.000000 8.6896544E-05 2.1909976E-03 4.7983685E-05 0.000000 0.000000 - Av 2018 3 13 22 0 0.2617396 4.0008064E-05 8.7754248E-05 2.1961136E-03 3.9914865E-03 1.9999960E-02 0.000000 - Av 2018 3 13 23 0 0.2637064 0.000000 8.8588698E-05 2.2020824E-03 1.7671059E-03 0.000000 0.000000 - Av 2018 3 13 24 0 0.2829620 2.6158295E-05 8.8681118E-05 2.2059944E-03 7.1066893E-03 9.9999802E-03 0.000000 - Av 2018 3 14 1 0 0.2787179 0.000000 8.8765257E-05 2.1670312E-03 2.4766228E-03 0.000000 0.000000 - Av 2018 3 14 2 0 0.3371508 9.1604139E-05 9.2356851E-05 2.1752042E-03 1.4959217E-02 1.9999960E-02 0.000000 - Av 2018 3 14 3 0 0.3301766 0.000000 9.5871226E-05 2.1844388E-03 4.1953670E-03 0.000000 0.000000 - Av 2018 3 14 4 0 0.2332941 0.000000 9.4456969E-05 2.1828299E-03 1.4617352E-03 0.000000 0.000000 - Av 2018 3 14 5 0 0.2424403 0.000000 9.3063580E-05 2.1812220E-03 6.4373086E-04 0.000000 0.000000 - Av 2018 3 14 6 0 0.2311779 0.000000 9.1690745E-05 2.1796145E-03 3.3201795E-04 0.000000 0.000000 + Av 2018 3 13 18 0 0.2237570 0.000000 9.0858441E-05 2.1959026E-03 1.5266059E-04 0.000000 0.000000 + Av 2018 3 13 19 0 0.2344472 0.000000 8.9518137E-05 2.1942670E-03 9.8583070E-05 0.000000 0.000000 + Av 2018 3 13 20 0 0.2307732 0.000000 8.8197601E-05 2.1926318E-03 6.7289242E-05 9.9999802E-03 0.000000 + Av 2018 3 13 21 0 0.2313067 0.000000 8.6896544E-05 2.1909976E-03 4.7983685E-05 0.000000 0.000000 + Av 2018 3 13 22 0 0.2617396 4.0008064E-05 8.7754248E-05 2.1961136E-03 3.9914865E-03 1.9999960E-02 0.000000 + Av 2018 3 13 23 0 0.2637064 0.000000 8.8588698E-05 2.2020824E-03 1.7671059E-03 0.000000 0.000000 + Av 2018 3 13 24 0 0.2829620 2.6158295E-05 8.8681118E-05 2.2059944E-03 7.1066893E-03 9.9999802E-03 0.000000 + Av 2018 3 14 1 0 0.2787179 0.000000 8.8765257E-05 2.1670312E-03 2.4766228E-03 0.000000 0.000000 + Av 2018 3 14 2 0 0.3371508 9.1604139E-05 9.2356851E-05 2.1752042E-03 1.4959217E-02 1.9999960E-02 0.000000 + Av 2018 3 14 3 0 0.3301766 0.000000 9.5871226E-05 2.1844388E-03 4.1953670E-03 0.000000 0.000000 + Av 2018 3 14 4 0 0.2332941 0.000000 9.4456969E-05 2.1828299E-03 1.4617352E-03 0.000000 0.000000 + Av 2018 3 14 5 0 0.2424403 0.000000 9.3063580E-05 2.1812220E-03 6.4373086E-04 0.000000 0.000000 + Av 2018 3 14 6 0 0.2311779 0.000000 9.1690745E-05 2.1796145E-03 3.3201795E-04 0.000000 0.000000 Av 2018 3 14 7 0 0.2108572 0.000000 9.0338166E-05 1.8745668E-03 1.9147656E-04 0.000000 1.3792779E-03 Av 2018 3 14 8 0 0.1706854 0.000000 8.9005531E-05 1.5124204E-03 1.1987322E-04 0.000000 3.0180980E-03 Av 2018 3 14 9 0 0.1342556 0.000000 8.7692562E-05 1.1502746E-03 7.9875659E-05 0.000000 4.6569179E-03 @@ -1769,19 +1769,19 @@ Av 2018 3 14 15 0 0.1216496 0.000000 8.0211619E-05 1.1406580E-03 0.000000 0.000000 4.6569179E-03 Av 2018 3 14 16 0 0.1473371 0.000000 7.9028374E-05 1.4995979E-03 0.000000 0.000000 3.0180980E-03 Av 2018 3 14 17 0 0.1872449 0.000000 7.7862584E-05 1.8585387E-03 0.000000 0.000000 1.3792779E-03 - Av 2018 3 14 18 0 0.2183356 0.000000 7.6713986E-05 2.1603808E-03 0.000000 0.000000 0.000000 - Av 2018 3 14 19 0 0.2278929 0.000000 7.5582335E-05 2.1587827E-03 0.000000 0.000000 0.000000 - Av 2018 3 14 20 0 0.2242000 0.000000 7.4467374E-05 2.1571852E-03 0.000000 0.000000 0.000000 - Av 2018 3 14 21 0 0.2251166 0.000000 7.3368865E-05 2.1555885E-03 0.000000 0.000000 0.000000 - Av 2018 3 14 22 0 0.2244328 0.000000 7.2286566E-05 2.1539924E-03 0.000000 0.000000 0.000000 - Av 2018 3 14 23 0 0.2243077 0.000000 7.1220224E-05 2.1523971E-03 0.000000 0.000000 0.000000 - Av 2018 3 14 24 0 0.2239906 0.000000 7.0169619E-05 2.1508024E-03 0.000000 0.000000 0.000000 - Av 2018 3 15 1 0 0.2208852 0.000000 6.9134505E-05 2.1071541E-03 0.000000 0.000000 0.000000 - Av 2018 3 15 2 0 0.2187560 0.000000 6.8114663E-05 2.1056291E-03 0.000000 0.000000 0.000000 - Av 2018 3 15 3 0 0.2191516 0.000000 6.7109868E-05 2.1041043E-03 0.000000 0.000000 0.000000 - Av 2018 3 15 4 0 0.2186714 0.000000 6.6119894E-05 2.1025804E-03 0.000000 0.000000 0.000000 - Av 2018 3 15 5 0 0.2184978 0.000000 6.5144523E-05 2.1010570E-03 0.000000 0.000000 0.000000 - Av 2018 3 15 6 0 0.2182196 0.000000 6.4183536E-05 2.0995343E-03 0.000000 0.000000 0.000000 + Av 2018 3 14 18 0 0.2183356 0.000000 7.6713986E-05 2.1603808E-03 0.000000 0.000000 0.000000 + Av 2018 3 14 19 0 0.2278929 0.000000 7.5582335E-05 2.1587827E-03 0.000000 0.000000 0.000000 + Av 2018 3 14 20 0 0.2242000 0.000000 7.4467374E-05 2.1571852E-03 0.000000 0.000000 0.000000 + Av 2018 3 14 21 0 0.2251166 0.000000 7.3368865E-05 2.1555885E-03 0.000000 0.000000 0.000000 + Av 2018 3 14 22 0 0.2244328 0.000000 7.2286566E-05 2.1539924E-03 0.000000 0.000000 0.000000 + Av 2018 3 14 23 0 0.2243077 0.000000 7.1220224E-05 2.1523971E-03 0.000000 0.000000 0.000000 + Av 2018 3 14 24 0 0.2239906 0.000000 7.0169619E-05 2.1508024E-03 0.000000 0.000000 0.000000 + Av 2018 3 15 1 0 0.2208852 0.000000 6.9134505E-05 2.1071541E-03 0.000000 0.000000 0.000000 + Av 2018 3 15 2 0 0.2187560 0.000000 6.8114663E-05 2.1056291E-03 0.000000 0.000000 0.000000 + Av 2018 3 15 3 0 0.2191516 0.000000 6.7109868E-05 2.1041043E-03 0.000000 0.000000 0.000000 + Av 2018 3 15 4 0 0.2186714 0.000000 6.6119894E-05 2.1025804E-03 0.000000 0.000000 0.000000 + Av 2018 3 15 5 0 0.2184978 0.000000 6.5144523E-05 2.1010570E-03 0.000000 0.000000 0.000000 + Av 2018 3 15 6 0 0.2182196 0.000000 6.4183536E-05 2.0995343E-03 0.000000 0.000000 0.000000 Av 2018 3 15 7 0 0.1970066 0.000000 6.3236730E-05 1.7913888E-03 0.000000 0.000000 1.3937427E-03 Av 2018 3 15 8 0 0.1589741 0.000000 6.2303887E-05 1.4370775E-03 0.000000 0.000000 2.9973343E-03 Av 2018 3 15 9 0 0.1236932 0.000000 6.1384802E-05 1.0827667E-03 0.000000 0.000000 4.6009258E-03 @@ -1793,19 +1793,19 @@ Av 2018 3 15 15 0 0.1127351 0.000000 5.6148143E-05 1.0736565E-03 0.000000 0.000000 4.6009258E-03 Av 2018 3 15 16 0 0.1375921 0.000000 5.5319870E-05 1.4249305E-03 0.000000 0.000000 2.9973343E-03 Av 2018 3 15 17 0 0.1767808 0.000000 5.4503817E-05 1.7762055E-03 0.000000 0.000000 1.3937427E-03 - Av 2018 3 15 18 0 0.2078595 0.000000 5.3699801E-05 2.0813143E-03 0.000000 0.000000 0.000000 - Av 2018 3 15 19 0 0.2176927 0.000000 5.2907642E-05 2.0798002E-03 0.000000 0.000000 0.000000 - Av 2018 3 15 20 0 0.2179233 0.000000 5.2127172E-05 2.0782868E-03 0.000000 3.9999921E-02 0.000000 - Av 2018 3 15 21 0 0.5960779 1.7810446E-04 1.4653539E-04 2.0983394E-03 5.1269364E-02 9.9999800E-02 0.000000 - Av 2018 3 15 22 0 0.7358053 2.7763017E-04 2.5395298E-04 2.1358789E-03 3.4196667E-02 2.9999940E-02 0.000000 - Av 2018 3 15 23 0 0.3744880 0.000000 2.6500615E-04 2.1508653E-03 6.8089110E-03 0.000000 0.000000 - Av 2018 3 15 24 0 0.3089690 2.8019878E-05 2.6259874E-04 2.1548644E-03 9.0592178E-03 9.9999802E-03 0.000000 - Av 2018 3 16 1 0 0.3012968 0.000000 2.6021941E-04 2.1172627E-03 2.7106509E-03 0.000000 0.000000 - Av 2018 3 16 2 0 0.2434672 0.000000 2.5638076E-04 2.1158156E-03 1.0449812E-03 0.000000 0.000000 - Av 2018 3 16 3 0 0.2928610 2.1245693E-05 2.5373776E-04 2.1192075E-03 6.6936905E-03 9.9999802E-03 0.000000 - Av 2018 3 16 4 0 0.2851633 0.000000 2.5112811E-04 2.1231037E-03 2.4194478E-03 0.000000 0.000000 - Av 2018 3 16 5 0 0.2460653 0.000000 2.4742360E-04 2.1216457E-03 9.5669559E-04 0.000000 0.000000 - Av 2018 3 16 6 0 0.2456381 0.000000 2.4377368E-04 2.1201880E-03 4.5841053E-04 0.000000 0.000000 + Av 2018 3 15 18 0 0.2078595 0.000000 5.3699801E-05 2.0813143E-03 0.000000 0.000000 0.000000 + Av 2018 3 15 19 0 0.2176927 0.000000 5.2907642E-05 2.0798002E-03 0.000000 0.000000 0.000000 + Av 2018 3 15 20 0 0.2179233 0.000000 5.2127172E-05 2.0782868E-03 0.000000 3.9999921E-02 0.000000 + Av 2018 3 15 21 0 0.5960779 1.7810446E-04 1.4653539E-04 2.0983394E-03 5.1269364E-02 9.9999800E-02 0.000000 + Av 2018 3 15 22 0 0.7358053 2.7763017E-04 2.5395298E-04 2.1358789E-03 3.4196667E-02 2.9999940E-02 0.000000 + Av 2018 3 15 23 0 0.3744880 0.000000 2.6500615E-04 2.1508653E-03 6.8089110E-03 0.000000 0.000000 + Av 2018 3 15 24 0 0.3089690 2.8019878E-05 2.6259874E-04 2.1548644E-03 9.0592178E-03 9.9999802E-03 0.000000 + Av 2018 3 16 1 0 0.3012968 0.000000 2.6021941E-04 2.1172627E-03 2.7106509E-03 0.000000 0.000000 + Av 2018 3 16 2 0 0.2434672 0.000000 2.5638076E-04 2.1158156E-03 1.0449812E-03 0.000000 0.000000 + Av 2018 3 16 3 0 0.2928610 2.1245693E-05 2.5373776E-04 2.1192075E-03 6.6936905E-03 9.9999802E-03 0.000000 + Av 2018 3 16 4 0 0.2851633 0.000000 2.5112811E-04 2.1231037E-03 2.4194478E-03 0.000000 0.000000 + Av 2018 3 16 5 0 0.2460653 0.000000 2.4742360E-04 2.1216457E-03 9.5669559E-04 0.000000 0.000000 + Av 2018 3 16 6 0 0.2456381 0.000000 2.4377368E-04 2.1201880E-03 4.5841053E-04 0.000000 0.000000 Av 2018 3 16 7 0 0.2161319 0.000000 2.4017764E-04 1.7655120E-03 2.5081410E-04 0.000000 1.6055395E-03 Av 2018 3 16 8 0 0.1725354 0.000000 2.3663466E-04 1.3701308E-03 1.5100685E-04 0.000000 3.3961036E-03 Av 2018 3 16 9 0 0.1321815 0.000000 2.3314393E-04 9.7474991E-04 9.7656732E-05 0.000000 5.1866677E-03 @@ -1817,19 +1817,19 @@ Av 2018 3 16 15 0 0.1175338 0.000000 2.1325471E-04 9.6601318E-04 0.000000 0.000000 5.1866677E-03 Av 2018 3 16 16 0 0.1452027 0.000000 2.1010886E-04 1.3584818E-03 0.000000 0.000000 3.3961036E-03 Av 2018 3 16 17 0 0.1887258 0.000000 2.0700942E-04 1.7509508E-03 0.000000 0.000000 1.6055395E-03 - Av 2018 3 16 18 0 0.2239926 0.000000 2.0395570E-04 2.1027145E-03 0.000000 0.000000 0.000000 - Av 2018 3 16 19 0 0.2384328 0.000000 2.0094703E-04 2.1012600E-03 0.000000 2.9999940E-02 0.000000 - Av 2018 3 16 20 0 0.2328083 0.000000 1.9798275E-04 2.0998055E-03 0.000000 0.000000 0.000000 - Av 2018 3 16 21 0 0.2309964 0.000000 1.9506220E-04 2.0983515E-03 0.000000 0.000000 0.000000 - Av 2018 3 16 22 0 0.2310349 0.000000 1.9218473E-04 2.0968977E-03 0.000000 0.000000 0.000000 - Av 2018 3 16 23 0 0.2304358 0.000000 1.8934970E-04 2.0954444E-03 0.000000 0.000000 0.000000 - Av 2018 3 16 24 0 0.2300642 0.000000 1.8655648E-04 2.0939910E-03 0.000000 0.000000 0.000000 - Av 2018 3 17 1 0 0.2268592 0.000000 1.8380450E-04 2.0519164E-03 0.000000 0.000000 0.000000 - Av 2018 3 17 2 0 0.2246493 0.000000 1.8109308E-04 2.0505276E-03 0.000000 0.000000 0.000000 - Av 2018 3 17 3 0 0.2248633 0.000000 1.7842169E-04 2.0491390E-03 0.000000 0.000000 0.000000 - Av 2018 3 17 4 0 0.2242399 0.000000 1.7578968E-04 2.0477504E-03 0.000000 0.000000 0.000000 - Av 2018 3 17 5 0 0.2239129 0.000000 1.7319650E-04 2.0463620E-03 0.000000 0.000000 0.000000 - Av 2018 3 17 6 0 0.2234882 0.000000 1.7064158E-04 2.0449741E-03 0.000000 0.000000 0.000000 + Av 2018 3 16 18 0 0.2239926 0.000000 2.0395570E-04 2.1027145E-03 0.000000 0.000000 0.000000 + Av 2018 3 16 19 0 0.2384328 0.000000 2.0094703E-04 2.1012600E-03 0.000000 2.9999940E-02 0.000000 + Av 2018 3 16 20 0 0.2328083 0.000000 1.9798275E-04 2.0998055E-03 0.000000 0.000000 0.000000 + Av 2018 3 16 21 0 0.2309964 0.000000 1.9506220E-04 2.0983515E-03 0.000000 0.000000 0.000000 + Av 2018 3 16 22 0 0.2310349 0.000000 1.9218473E-04 2.0968977E-03 0.000000 0.000000 0.000000 + Av 2018 3 16 23 0 0.2304358 0.000000 1.8934970E-04 2.0954444E-03 0.000000 0.000000 0.000000 + Av 2018 3 16 24 0 0.2300642 0.000000 1.8655648E-04 2.0939910E-03 0.000000 0.000000 0.000000 + Av 2018 3 17 1 0 0.2268592 0.000000 1.8380450E-04 2.0519164E-03 0.000000 0.000000 0.000000 + Av 2018 3 17 2 0 0.2246493 0.000000 1.8109308E-04 2.0505276E-03 0.000000 0.000000 0.000000 + Av 2018 3 17 3 0 0.2248633 0.000000 1.7842169E-04 2.0491390E-03 0.000000 0.000000 0.000000 + Av 2018 3 17 4 0 0.2242399 0.000000 1.7578968E-04 2.0477504E-03 0.000000 0.000000 0.000000 + Av 2018 3 17 5 0 0.2239129 0.000000 1.7319650E-04 2.0463620E-03 0.000000 0.000000 0.000000 + Av 2018 3 17 6 0 0.2234882 0.000000 1.7064158E-04 2.0449741E-03 0.000000 0.000000 0.000000 Av 2018 3 17 7 0 0.1997190 0.000000 1.6812436E-04 1.7017496E-03 0.000000 0.000000 1.5538024E-03 Av 2018 3 17 8 0 0.1588070 0.000000 1.6564426E-04 1.3304934E-03 0.000000 0.000000 3.2350237E-03 Av 2018 3 17 9 0 0.1220092 0.000000 1.6320075E-04 9.5923746E-04 0.000000 0.000000 4.9162451E-03 @@ -1841,19 +1841,19 @@ Av 2018 3 17 15 0 0.1112299 0.000000 1.4927830E-04 9.5091911E-04 0.000000 9.9999802E-03 4.9162451E-03 Av 2018 3 17 16 0 0.1365644 0.000000 1.4707622E-04 1.3194025E-03 0.000000 9.9999802E-03 3.2350237E-03 Av 2018 3 17 17 0 0.1770332 0.000000 1.4490662E-04 1.6878860E-03 0.000000 0.000000 1.5538024E-03 - Av 2018 3 17 18 0 0.2103515 0.000000 1.4276901E-04 2.0283377E-03 0.000000 0.000000 0.000000 - Av 2018 3 17 19 0 0.2216503 0.000000 1.4066295E-04 2.0269530E-03 0.000000 0.000000 0.000000 - Av 2018 3 17 20 0 0.2172494 0.000000 1.3858794E-04 2.0255686E-03 0.000000 0.000000 0.000000 - Av 2018 3 17 21 0 0.2183116 0.000000 1.3654355E-04 2.0241847E-03 0.000000 0.000000 0.000000 - Av 2018 3 17 22 0 0.2174785 0.000000 1.3452931E-04 2.0228007E-03 0.000000 0.000000 0.000000 - Av 2018 3 17 23 0 0.2173084 0.000000 1.3254480E-04 2.0214173E-03 0.000000 0.000000 0.000000 - Av 2018 3 17 24 0 0.2169119 0.000000 1.3058954E-04 2.0200340E-03 0.000000 0.000000 0.000000 - Av 2018 3 18 1 0 0.2139620 0.000000 1.2866316E-04 1.9798542E-03 0.000000 0.000000 0.000000 - Av 2018 3 18 2 0 0.2119080 0.000000 1.2676517E-04 1.9785315E-03 0.000000 0.000000 0.000000 - Av 2018 3 18 3 0 0.2121865 0.000000 1.2489519E-04 1.9772090E-03 0.000000 0.000000 0.000000 - Av 2018 3 18 4 0 0.2116577 0.000000 1.2305279E-04 1.9758868E-03 0.000000 0.000000 0.000000 - Av 2018 3 18 5 0 0.2114134 0.000000 1.2123756E-04 1.9745647E-03 0.000000 0.000000 0.000000 - Av 2018 3 18 6 0 0.2110739 0.000000 1.1944912E-04 1.9732430E-03 0.000000 0.000000 0.000000 + Av 2018 3 17 18 0 0.2103515 0.000000 1.4276901E-04 2.0283377E-03 0.000000 0.000000 0.000000 + Av 2018 3 17 19 0 0.2216503 0.000000 1.4066295E-04 2.0269530E-03 0.000000 0.000000 0.000000 + Av 2018 3 17 20 0 0.2172494 0.000000 1.3858794E-04 2.0255686E-03 0.000000 0.000000 0.000000 + Av 2018 3 17 21 0 0.2183116 0.000000 1.3654355E-04 2.0241847E-03 0.000000 0.000000 0.000000 + Av 2018 3 17 22 0 0.2174785 0.000000 1.3452931E-04 2.0228007E-03 0.000000 0.000000 0.000000 + Av 2018 3 17 23 0 0.2173084 0.000000 1.3254480E-04 2.0214173E-03 0.000000 0.000000 0.000000 + Av 2018 3 17 24 0 0.2169119 0.000000 1.3058954E-04 2.0200340E-03 0.000000 0.000000 0.000000 + Av 2018 3 18 1 0 0.2139620 0.000000 1.2866316E-04 1.9798542E-03 0.000000 0.000000 0.000000 + Av 2018 3 18 2 0 0.2119080 0.000000 1.2676517E-04 1.9785315E-03 0.000000 0.000000 0.000000 + Av 2018 3 18 3 0 0.2121865 0.000000 1.2489519E-04 1.9772090E-03 0.000000 0.000000 0.000000 + Av 2018 3 18 4 0 0.2116577 0.000000 1.2305279E-04 1.9758868E-03 0.000000 0.000000 0.000000 + Av 2018 3 18 5 0 0.2114134 0.000000 1.2123756E-04 1.9745647E-03 0.000000 0.000000 0.000000 + Av 2018 3 18 6 0 0.2110739 0.000000 1.1944912E-04 1.9732430E-03 0.000000 0.000000 0.000000 Av 2018 3 18 7 0 0.1873248 0.000000 1.1768705E-04 1.6291051E-03 0.000000 0.000000 1.5582569E-03 Av 2018 3 18 8 0 0.1471216 0.000000 1.1595097E-04 1.2675938E-03 0.000000 0.000000 3.1954853E-03 Av 2018 3 18 9 0 0.1115201 0.000000 1.1424052E-04 9.0608257E-04 0.000000 0.000000 4.8327134E-03 @@ -1865,19 +1865,19 @@ Av 2018 3 18 15 0 0.1004088 0.000000 1.0449479E-04 8.9816283E-04 0.000000 0.000000 4.8327134E-03 Av 2018 3 18 16 0 0.1250690 0.000000 1.0295332E-04 1.2570340E-03 0.000000 0.000000 3.1954853E-03 Av 2018 3 18 17 0 0.1652519 0.000000 1.0143460E-04 1.6159054E-03 0.000000 0.000000 1.5582569E-03 - Av 2018 3 18 18 0 0.1988792 0.000000 9.9938276E-05 1.9574035E-03 0.000000 0.000000 0.000000 - Av 2018 3 18 19 0 0.2102274 0.000000 9.8464028E-05 1.9560854E-03 0.000000 0.000000 0.000000 - Av 2018 3 18 20 0 0.2059036 0.000000 9.7011529E-05 1.9547676E-03 0.000000 0.000000 0.000000 - Av 2018 3 18 21 0 0.2070320 0.000000 9.5580457E-05 1.9534500E-03 0.000000 0.000000 0.000000 - Av 2018 3 18 22 0 0.2062676 0.000000 9.4170500E-05 1.9521328E-03 0.000000 0.000000 0.000000 - Av 2018 3 18 23 0 0.2061642 0.000000 9.2781331E-05 1.9508159E-03 0.000000 0.000000 0.000000 - Av 2018 3 18 24 0 0.2058339 0.000000 9.1412665E-05 1.9494994E-03 0.000000 0.000000 0.000000 - Av 2018 3 19 1 0 0.2030671 0.000000 9.0064183E-05 1.9111210E-03 0.000000 0.000000 0.000000 - Av 2018 3 19 2 0 0.2011541 0.000000 8.8735600E-05 1.9098612E-03 0.000000 0.000000 0.000000 - Av 2018 3 19 3 0 0.2014689 0.000000 8.7426612E-05 1.9086018E-03 0.000000 0.000000 0.000000 - Av 2018 3 19 4 0 0.2010117 0.000000 8.6136934E-05 1.9073426E-03 0.000000 0.000000 0.000000 - Av 2018 3 19 5 0 0.2008256 0.000000 8.4866275E-05 1.9060835E-03 0.000000 0.000000 0.000000 - Av 2018 3 19 6 0 0.2005479 0.000000 8.3614366E-05 1.9048250E-03 0.000000 0.000000 0.000000 + Av 2018 3 18 18 0 0.1988792 0.000000 9.9938276E-05 1.9574035E-03 0.000000 0.000000 0.000000 + Av 2018 3 18 19 0 0.2102274 0.000000 9.8464028E-05 1.9560854E-03 0.000000 0.000000 0.000000 + Av 2018 3 18 20 0 0.2059036 0.000000 9.7011529E-05 1.9547676E-03 0.000000 0.000000 0.000000 + Av 2018 3 18 21 0 0.2070320 0.000000 9.5580457E-05 1.9534500E-03 0.000000 0.000000 0.000000 + Av 2018 3 18 22 0 0.2062676 0.000000 9.4170500E-05 1.9521328E-03 0.000000 0.000000 0.000000 + Av 2018 3 18 23 0 0.2061642 0.000000 9.2781331E-05 1.9508159E-03 0.000000 0.000000 0.000000 + Av 2018 3 18 24 0 0.2058339 0.000000 9.1412665E-05 1.9494994E-03 0.000000 0.000000 0.000000 + Av 2018 3 19 1 0 0.2030671 0.000000 9.0064183E-05 1.9111210E-03 0.000000 0.000000 0.000000 + Av 2018 3 19 2 0 0.2011541 0.000000 8.8735600E-05 1.9098612E-03 0.000000 0.000000 0.000000 + Av 2018 3 19 3 0 0.2014689 0.000000 8.7426612E-05 1.9086018E-03 0.000000 0.000000 0.000000 + Av 2018 3 19 4 0 0.2010117 0.000000 8.6136934E-05 1.9073426E-03 0.000000 0.000000 0.000000 + Av 2018 3 19 5 0 0.2008256 0.000000 8.4866275E-05 1.9060835E-03 0.000000 0.000000 0.000000 + Av 2018 3 19 6 0 0.2005479 0.000000 8.3614366E-05 1.9048250E-03 0.000000 0.000000 0.000000 Av 2018 3 19 7 0 0.1742935 0.000000 8.2380924E-05 1.5231876E-03 0.000000 0.000000 1.7289958E-03 Av 2018 3 19 8 0 0.1305614 0.000000 8.1165672E-05 1.1335207E-03 0.000000 0.000000 3.4944899E-03 Av 2018 3 19 9 0 9.2439026E-02 0.000000 7.9968355E-05 7.4385421E-04 0.000000 0.000000 5.2599842E-03 @@ -1889,18 +1889,18 @@ Av 2018 3 19 15 0 8.1082627E-02 0.000000 7.3146351E-05 7.3631352E-04 0.000000 0.000000 5.2599842E-03 Av 2018 3 19 16 0 0.1074992 0.000000 7.2067327E-05 1.1234663E-03 0.000000 0.000000 3.4944899E-03 Av 2018 3 19 17 0 0.1509638 0.000000 7.1004222E-05 1.5106197E-03 0.000000 0.000000 1.7289958E-03 - Av 2018 3 19 18 0 0.1879855 0.000000 6.9956797E-05 1.8897435E-03 0.000000 0.000000 0.000000 - Av 2018 3 19 19 0 0.2007813 0.000000 6.8924826E-05 1.8884887E-03 0.000000 0.000000 0.000000 - Av 2018 3 19 20 0 0.1960223 0.000000 6.7908077E-05 1.8872340E-03 0.000000 0.000000 0.000000 - Av 2018 3 19 21 0 0.1973694 0.000000 6.6906330E-05 1.8859797E-03 0.000000 0.000000 0.000000 - Av 2018 3 19 22 0 0.1965955 0.000000 6.5919361E-05 1.8847258E-03 0.000000 0.000000 0.000000 - Av 2018 3 19 23 0 0.1965611 0.000000 6.4946944E-05 1.8834721E-03 0.000000 0.000000 0.000000 - Av 2018 3 19 24 0 0.1962715 0.000000 6.3988875E-05 1.8822188E-03 0.000000 0.000000 0.000000 - Av 2018 3 20 1 0 0.1936666 0.000000 6.3044943E-05 1.8455533E-03 0.000000 0.000000 0.000000 - Av 2018 3 20 2 0 0.1918723 0.000000 6.2114930E-05 1.8443534E-03 0.000000 0.000000 0.000000 - Av 2018 3 20 3 0 0.1922077 0.000000 6.1198632E-05 1.8431537E-03 0.000000 0.000000 0.000000 - Av 2018 3 20 4 0 0.1918045 0.000000 6.0295861E-05 1.8419544E-03 0.000000 0.000000 0.000000 - Av 2018 3 20 5 0 0.1916600 0.000000 5.9406404E-05 1.8407553E-03 0.000000 0.000000 0.000000 + Av 2018 3 19 18 0 0.1879855 0.000000 6.9956797E-05 1.8897435E-03 0.000000 0.000000 0.000000 + Av 2018 3 19 19 0 0.2007813 0.000000 6.8924826E-05 1.8884887E-03 0.000000 0.000000 0.000000 + Av 2018 3 19 20 0 0.1960223 0.000000 6.7908077E-05 1.8872340E-03 0.000000 0.000000 0.000000 + Av 2018 3 19 21 0 0.1973694 0.000000 6.6906330E-05 1.8859797E-03 0.000000 0.000000 0.000000 + Av 2018 3 19 22 0 0.1965955 0.000000 6.5919361E-05 1.8847258E-03 0.000000 0.000000 0.000000 + Av 2018 3 19 23 0 0.1965611 0.000000 6.4946944E-05 1.8834721E-03 0.000000 0.000000 0.000000 + Av 2018 3 19 24 0 0.1962715 0.000000 6.3988875E-05 1.8822188E-03 0.000000 0.000000 0.000000 + Av 2018 3 20 1 0 0.1936666 0.000000 6.3044943E-05 1.8455533E-03 0.000000 0.000000 0.000000 + Av 2018 3 20 2 0 0.1918723 0.000000 6.2114930E-05 1.8443534E-03 0.000000 0.000000 0.000000 + Av 2018 3 20 3 0 0.1922077 0.000000 6.1198632E-05 1.8431537E-03 0.000000 0.000000 0.000000 + Av 2018 3 20 4 0 0.1918045 0.000000 6.0295861E-05 1.8419544E-03 0.000000 0.000000 0.000000 + Av 2018 3 20 5 0 0.1916600 0.000000 5.9406404E-05 1.8407553E-03 0.000000 0.000000 0.000000 Av 2018 3 20 6 0 0.1912390 0.000000 5.8530066E-05 1.8368016E-03 0.000000 0.000000 1.2522619E-05 Av 2018 3 20 7 0 0.1635835 0.000000 5.7666661E-05 1.4358404E-03 0.000000 0.000000 1.8296265E-03 Av 2018 3 20 8 0 0.1183092 0.000000 5.6815989E-05 1.0348794E-03 0.000000 0.000000 3.6467304E-03 @@ -1914,17 +1914,17 @@ Av 2018 3 20 16 0 9.5054649E-02 0.000000 5.0447146E-05 1.0253042E-03 0.000000 0.000000 3.6467304E-03 Av 2018 3 20 17 0 0.1398191 0.000000 4.9702969E-05 1.4238714E-03 0.000000 0.000000 1.8296265E-03 Av 2018 3 20 18 0 0.1785176 0.000000 4.8969770E-05 1.8224381E-03 0.000000 0.000000 1.2522619E-05 - Av 2018 3 20 19 0 0.1922864 0.000000 4.8247388E-05 1.8239960E-03 0.000000 0.000000 0.000000 - Av 2018 3 20 20 0 0.1874271 0.000000 4.7535665E-05 1.8227992E-03 0.000000 0.000000 0.000000 - Av 2018 3 20 21 0 0.1888581 0.000000 4.6834441E-05 1.8216029E-03 0.000000 0.000000 0.000000 - Av 2018 3 20 22 0 0.1881034 0.000000 4.6143559E-05 1.8204068E-03 0.000000 0.000000 0.000000 - Av 2018 3 20 23 0 0.1881101 0.000000 4.5462868E-05 1.8192109E-03 0.000000 0.000000 0.000000 - Av 2018 3 20 24 0 0.1878535 0.000000 4.4792218E-05 1.8180156E-03 0.000000 0.000000 0.000000 - Av 2018 3 21 1 0 0.1853904 0.000000 4.4131462E-05 1.7829777E-03 0.000000 0.000000 0.000000 - Av 2018 3 21 2 0 0.1836993 0.000000 4.3480457E-05 1.7818327E-03 0.000000 0.000000 0.000000 - Av 2018 3 21 3 0 0.1840439 0.000000 4.2839052E-05 1.7806879E-03 0.000000 0.000000 0.000000 - Av 2018 3 21 4 0 0.1836820 0.000000 4.2207110E-05 1.7795435E-03 0.000000 0.000000 0.000000 - Av 2018 3 21 5 0 0.1835671 0.000000 4.1584488E-05 1.7783993E-03 0.000000 0.000000 0.000000 + Av 2018 3 20 19 0 0.1922864 0.000000 4.8247388E-05 1.8239960E-03 0.000000 0.000000 0.000000 + Av 2018 3 20 20 0 0.1874271 0.000000 4.7535665E-05 1.8227992E-03 0.000000 0.000000 0.000000 + Av 2018 3 20 21 0 0.1888581 0.000000 4.6834441E-05 1.8216029E-03 0.000000 0.000000 0.000000 + Av 2018 3 20 22 0 0.1881034 0.000000 4.6143559E-05 1.8204068E-03 0.000000 0.000000 0.000000 + Av 2018 3 20 23 0 0.1881101 0.000000 4.5462868E-05 1.8192109E-03 0.000000 0.000000 0.000000 + Av 2018 3 20 24 0 0.1878535 0.000000 4.4792218E-05 1.8180156E-03 0.000000 0.000000 0.000000 + Av 2018 3 21 1 0 0.1853904 0.000000 4.4131462E-05 1.7829777E-03 0.000000 0.000000 0.000000 + Av 2018 3 21 2 0 0.1836993 0.000000 4.3480457E-05 1.7818327E-03 0.000000 0.000000 0.000000 + Av 2018 3 21 3 0 0.1840439 0.000000 4.2839052E-05 1.7806879E-03 0.000000 0.000000 0.000000 + Av 2018 3 21 4 0 0.1836820 0.000000 4.2207110E-05 1.7795435E-03 0.000000 0.000000 0.000000 + Av 2018 3 21 5 0 0.1835671 0.000000 4.1584488E-05 1.7783993E-03 0.000000 0.000000 0.000000 Av 2018 3 21 6 0 0.1824885 0.000000 4.0971052E-05 1.7643959E-03 0.000000 0.000000 5.8452450E-05 Av 2018 3 21 7 0 0.1562322 0.000000 4.0366667E-05 1.3900273E-03 0.000000 0.000000 1.7549295E-03 Av 2018 3 21 8 0 0.1141449 0.000000 3.9771192E-05 1.0156576E-03 0.000000 0.000000 3.4514065E-03 @@ -1938,17 +1938,17 @@ Av 2018 3 21 16 0 9.2653766E-02 0.000000 3.5312998E-05 1.0063346E-03 0.000000 0.000000 3.4514065E-03 Av 2018 3 21 17 0 0.1349894 0.000000 3.4792076E-05 1.3783886E-03 0.000000 9.9999802E-03 1.7549295E-03 Av 2018 3 21 18 0 0.1717830 0.000000 3.4278837E-05 1.7504431E-03 0.000000 9.9999802E-03 5.8452450E-05 - Av 2018 3 21 19 0 0.1900308 0.000000 3.3773173E-05 1.7621327E-03 0.000000 5.9999879E-02 0.000000 - Av 2018 3 21 20 0 0.2033522 8.3495379E-06 4.9164268E-05 1.7750282E-03 1.8508779E-03 4.9999900E-02 0.000000 - Av 2018 3 21 21 0 0.7373945 3.0549284E-04 1.7283918E-04 1.8096500E-03 7.3862500E-02 8.9999817E-02 0.000000 - Av 2018 3 21 22 0 0.7630845 1.3298409E-04 2.8548448E-04 1.8411726E-03 2.8669957E-02 1.9999960E-02 0.000000 - Av 2018 3 21 23 0 0.2740219 0.000000 2.8838057E-04 1.8513987E-03 6.0085682E-03 0.000000 0.000000 - Av 2018 3 21 24 0 0.2489811 0.000000 2.8412652E-04 1.8502360E-03 1.9181435E-03 0.000000 0.000000 - Av 2018 3 22 1 0 0.2654222 2.1310298E-05 2.8108028E-04 1.8188426E-03 7.1842065E-03 9.9999802E-03 0.000000 - Av 2018 3 22 2 0 0.4208854 6.4087126E-06 2.9166613E-04 1.8359566E-03 2.5114253E-02 2.9999940E-02 0.000000 - Av 2018 3 22 3 0 0.6486779 6.5036627E-05 3.3937642E-04 1.8680643E-03 4.6151422E-02 4.9999900E-02 0.000000 - Av 2018 3 22 4 0 0.9671115 3.9789386E-04 4.7353146E-04 1.9083248E-03 7.5495765E-02 7.9999842E-02 0.000000 - Av 2018 3 22 5 0 0.7575948 1.4286301E-04 5.7460403E-04 1.9408164E-03 2.8220445E-02 1.9999960E-02 0.000000 + Av 2018 3 21 19 0 0.1900308 0.000000 3.3773173E-05 1.7621327E-03 0.000000 5.9999879E-02 0.000000 + Av 2018 3 21 20 0 0.2033522 8.3495379E-06 4.9164268E-05 1.7750282E-03 1.8508779E-03 4.9999900E-02 0.000000 + Av 2018 3 21 21 0 0.7373945 3.0549284E-04 1.7283918E-04 1.8096500E-03 7.3862500E-02 8.9999817E-02 0.000000 + Av 2018 3 21 22 0 0.7630845 1.3298409E-04 2.8548448E-04 1.8411726E-03 2.8669957E-02 1.9999960E-02 0.000000 + Av 2018 3 21 23 0 0.2740219 0.000000 2.8838057E-04 1.8513987E-03 6.0085682E-03 0.000000 0.000000 + Av 2018 3 21 24 0 0.2489811 0.000000 2.8412652E-04 1.8502360E-03 1.9181435E-03 0.000000 0.000000 + Av 2018 3 22 1 0 0.2654222 2.1310298E-05 2.8108028E-04 1.8188426E-03 7.1842065E-03 9.9999802E-03 0.000000 + Av 2018 3 22 2 0 0.4208854 6.4087126E-06 2.9166613E-04 1.8359566E-03 2.5114253E-02 2.9999940E-02 0.000000 + Av 2018 3 22 3 0 0.6486779 6.5036627E-05 3.3937642E-04 1.8680643E-03 4.6151422E-02 4.9999900E-02 0.000000 + Av 2018 3 22 4 0 0.9671115 3.9789386E-04 4.7353146E-04 1.9083248E-03 7.5495765E-02 7.9999842E-02 0.000000 + Av 2018 3 22 5 0 0.7575948 1.4286301E-04 5.7460403E-04 1.9408164E-03 2.8220445E-02 1.9999960E-02 0.000000 Av 2018 3 22 6 0 0.6741672 7.8338853E-05 6.3398160E-04 1.9496371E-03 5.4770347E-02 5.9999879E-02 1.0041802E-04 Av 2018 3 22 7 0 0.9413437 5.2598421E-04 7.4878905E-04 1.6356751E-03 5.9592996E-02 5.9999879E-02 1.7197012E-03 Av 2018 3 22 8 0 0.6107219 1.2378416E-04 8.0836046E-04 1.3111790E-03 2.4591628E-02 1.9999960E-02 3.3389844E-03 @@ -1962,17 +1962,17 @@ Av 2018 3 22 16 0 0.2011442 0.000000 7.4947689E-04 1.3484301E-03 1.0165641E-04 0.000000 3.3389844E-03 Av 2018 3 22 17 0 0.2392005 0.000000 7.3842093E-04 1.7035424E-03 6.9130547E-05 0.000000 1.7197012E-03 Av 2018 3 22 18 0 0.5194328 5.7827190E-05 7.7801151E-04 2.0786971E-03 3.3807501E-02 7.9999842E-02 1.0041802E-04 - Av 2018 3 22 19 0 0.5066289 2.6145028E-07 8.1678247E-04 2.1225077E-03 7.5240941E-03 0.000000 0.000000 - Av 2018 3 22 20 0 0.2889626 0.000000 8.0474775E-04 2.1219561E-03 2.2697411E-03 0.000000 0.000000 - Av 2018 3 22 21 0 0.4250700 1.3459165E-04 8.0014911E-04 2.1311073E-03 1.4780626E-02 1.9999960E-02 0.000000 - Av 2018 3 22 22 0 0.3913476 0.000000 7.9558243E-04 2.1413807E-03 4.1692960E-03 0.000000 0.000000 - Av 2018 3 22 23 0 0.3003615 0.000000 7.8384631E-04 2.1402298E-03 1.4548083E-03 0.000000 0.000000 - Av 2018 3 22 24 0 0.7757732 2.4626509E-04 8.8868075E-04 2.1609890E-03 6.4464942E-02 7.9999842E-02 0.000000 - Av 2018 3 23 1 0 1.374870 1.9288110E-03 1.1435992E-03 2.1631012E-03 8.7685719E-02 8.9999817E-02 0.000000 - Av 2018 3 23 2 0 1.370757 8.5106352E-04 1.4120090E-03 2.2087297E-03 8.1073634E-02 7.9999842E-02 0.000000 - Av 2018 3 23 3 0 0.7996510 5.4227035E-05 1.5272817E-03 2.2390196E-03 2.0379193E-02 9.9999802E-03 0.000000 - Av 2018 3 23 4 0 0.4644881 3.9934646E-05 1.5098391E-03 2.2512611E-03 1.2147402E-02 9.9999802E-03 0.000000 - Av 2018 3 23 5 0 1.373953 1.9635288E-03 1.7747309E-03 2.2794001E-03 0.1124021 0.1299997 0.000000 + Av 2018 3 22 19 0 0.5066289 2.6145028E-07 8.1678247E-04 2.1225077E-03 7.5240941E-03 0.000000 0.000000 + Av 2018 3 22 20 0 0.2889626 0.000000 8.0474775E-04 2.1219561E-03 2.2697411E-03 0.000000 0.000000 + Av 2018 3 22 21 0 0.4250700 1.3459165E-04 8.0014911E-04 2.1311073E-03 1.4780626E-02 1.9999960E-02 0.000000 + Av 2018 3 22 22 0 0.3913476 0.000000 7.9558243E-04 2.1413807E-03 4.1692960E-03 0.000000 0.000000 + Av 2018 3 22 23 0 0.3003615 0.000000 7.8384631E-04 2.1402298E-03 1.4548083E-03 0.000000 0.000000 + Av 2018 3 22 24 0 0.7757732 2.4626509E-04 8.8868075E-04 2.1609890E-03 6.4464942E-02 7.9999842E-02 0.000000 + Av 2018 3 23 1 0 1.374870 1.9288110E-03 1.1435992E-03 2.1631012E-03 8.7685719E-02 8.9999817E-02 0.000000 + Av 2018 3 23 2 0 1.370757 8.5106352E-04 1.4120090E-03 2.2087297E-03 8.1073634E-02 7.9999842E-02 0.000000 + Av 2018 3 23 3 0 0.7996510 5.4227035E-05 1.5272817E-03 2.2390196E-03 2.0379193E-02 9.9999802E-03 0.000000 + Av 2018 3 23 4 0 0.4644881 3.9934646E-05 1.5098391E-03 2.2512611E-03 1.2147402E-02 9.9999802E-03 0.000000 + Av 2018 3 23 5 0 1.373953 1.9635288E-03 1.7747309E-03 2.2794001E-03 0.1124021 0.1299997 0.000000 Av 2018 3 23 6 0 1.257787 2.7492686E-04 2.0470638E-03 2.2854335E-03 3.2792464E-02 1.9999960E-02 1.4130733E-04 Av 2018 3 23 7 0 0.4201995 0.000000 2.0317046E-03 1.9520118E-03 6.6097928E-03 0.000000 1.7190403E-03 Av 2018 3 23 8 0 0.4277742 0.000000 2.0017338E-03 1.6044731E-03 2.0603829E-03 0.000000 3.2967734E-03 @@ -1986,17 +1986,17 @@ Av 2018 3 23 16 0 0.3319864 0.000000 1.7773478E-03 1.6005427E-03 3.3683318E-05 9.9999802E-03 3.2967734E-03 Av 2018 3 23 17 0 0.4078353 1.2861587E-04 1.7581099E-03 1.9566149E-03 4.3070153E-03 1.9999960E-02 1.7190403E-03 Av 2018 3 23 18 0 0.6485110 3.1377691E-05 1.7744894E-03 2.3315086E-03 3.1004019E-02 3.9999921E-02 1.4130733E-04 - Av 2018 3 23 19 0 0.9090396 2.4913219E-04 1.8445327E-03 2.4026935E-03 4.7337703E-02 4.9999900E-02 0.000000 - Av 2018 3 23 20 0 0.9987929 4.5109083E-04 1.9411487E-03 2.4464217E-03 4.9823143E-02 4.9999900E-02 0.000000 - Av 2018 3 23 21 0 1.011619 3.3623111E-04 2.0391564E-03 2.4905868E-03 4.9974784E-02 4.9999900E-02 0.000000 - Av 2018 3 23 22 0 0.8247983 1.4711176E-04 2.0835833E-03 2.5252618E-03 2.4742851E-02 1.9999960E-02 0.000000 - Av 2018 3 23 23 0 0.5581679 1.3740136E-09 2.0637626E-03 2.5375844E-03 5.4092617E-03 0.000000 0.000000 - Av 2018 3 23 24 0 0.5925431 1.8517411E-04 2.0434035E-03 2.5483596E-03 1.6146338E-02 1.9999960E-02 0.000000 - Av 2018 3 24 1 0 0.7350504 1.2768320E-05 2.0440873E-03 2.5228909E-03 2.7560143E-02 2.9999940E-02 0.000000 - Av 2018 3 24 2 0 0.7240584 1.9276286E-04 2.0451304E-03 2.5503305E-03 2.1593248E-02 1.9999960E-02 0.000000 - Av 2018 3 24 3 0 0.5690789 0.000000 2.0254164E-03 2.5622980E-03 4.9065994E-03 0.000000 0.000000 - Av 2018 3 24 4 0 0.4679986 0.000000 1.9955384E-03 2.5617206E-03 1.6463953E-03 0.000000 0.000000 - Av 2018 3 24 5 0 0.4705041 0.000000 1.9661011E-03 2.5611292E-03 7.0735638E-04 0.000000 0.000000 + Av 2018 3 23 19 0 0.9090396 2.4913219E-04 1.8445327E-03 2.4026935E-03 4.7337703E-02 4.9999900E-02 0.000000 + Av 2018 3 23 20 0 0.9987929 4.5109083E-04 1.9411487E-03 2.4464217E-03 4.9823143E-02 4.9999900E-02 0.000000 + Av 2018 3 23 21 0 1.011619 3.3623111E-04 2.0391564E-03 2.4905868E-03 4.9974784E-02 4.9999900E-02 0.000000 + Av 2018 3 23 22 0 0.8247983 1.4711176E-04 2.0835833E-03 2.5252618E-03 2.4742851E-02 1.9999960E-02 0.000000 + Av 2018 3 23 23 0 0.5581679 1.3740136E-09 2.0637626E-03 2.5375844E-03 5.4092617E-03 0.000000 0.000000 + Av 2018 3 23 24 0 0.5925431 1.8517411E-04 2.0434035E-03 2.5483596E-03 1.6146338E-02 1.9999960E-02 0.000000 + Av 2018 3 24 1 0 0.7350504 1.2768320E-05 2.0440873E-03 2.5228909E-03 2.7560143E-02 2.9999940E-02 0.000000 + Av 2018 3 24 2 0 0.7240584 1.9276286E-04 2.0451304E-03 2.5503305E-03 2.1593248E-02 1.9999960E-02 0.000000 + Av 2018 3 24 3 0 0.5690789 0.000000 2.0254164E-03 2.5622980E-03 4.9065994E-03 0.000000 0.000000 + Av 2018 3 24 4 0 0.4679986 0.000000 1.9955384E-03 2.5617206E-03 1.6463953E-03 0.000000 0.000000 + Av 2018 3 24 5 0 0.4705041 0.000000 1.9661011E-03 2.5611292E-03 7.0735638E-04 0.000000 0.000000 Av 2018 3 24 6 0 0.4540900 0.000000 1.9370980E-03 2.5205612E-03 3.5866501E-04 0.000000 1.8164878E-04 Av 2018 3 24 7 0 0.4262314 0.000000 1.9085228E-03 2.1786727E-03 2.0431766E-04 0.000000 1.7328745E-03 Av 2018 3 24 8 0 0.3836082 0.000000 1.8803690E-03 1.8367709E-03 1.2674330E-04 0.000000 3.2841002E-03 @@ -2010,17 +2010,17 @@ Av 2018 3 24 16 0 0.3625055 0.000000 1.6984879E-03 1.8909979E-03 8.9831685E-04 0.000000 3.2841002E-03 Av 2018 3 24 17 0 0.3915738 0.000000 1.6734325E-03 2.2314705E-03 4.3565166E-04 0.000000 1.7328745E-03 Av 2018 3 24 18 0 0.4458291 3.3770229E-05 1.6505904E-03 2.5773786E-03 3.1891144E-03 1.9999960E-02 1.8164878E-04 - Av 2018 3 24 19 0 0.5072557 4.3418720E-05 1.6304468E-03 2.6286799E-03 8.0221221E-03 9.9999802E-03 0.000000 - Av 2018 3 24 20 0 0.5942489 1.7837163E-04 1.6184958E-03 2.6462940E-03 1.7261395E-02 1.9999960E-02 0.000000 - Av 2018 3 24 21 0 0.5353251 0.000000 1.6043137E-03 2.6582184E-03 4.4224779E-03 0.000000 0.000000 - Av 2018 3 24 22 0 0.4825050 4.4502234E-05 1.5830790E-03 2.6636641E-03 8.2478644E-03 9.9999802E-03 0.000000 - Av 2018 3 24 23 0 0.4865374 0.000000 1.5621454E-03 2.6696958E-03 2.6197752E-03 0.000000 0.000000 - Av 2018 3 24 24 0 0.4781292 4.4300032E-05 1.5415221E-03 2.6751142E-03 7.5178174E-03 9.9999802E-03 0.000000 - Av 2018 3 25 1 0 0.5272939 3.3545821E-05 1.5230245E-03 2.6314980E-03 9.6312054E-03 9.9999802E-03 0.000000 - Av 2018 3 25 2 0 0.4682723 0.000000 1.5023820E-03 2.6366259E-03 2.7706288E-03 0.000000 0.000000 - Av 2018 3 25 3 0 0.4733941 4.4013963E-05 1.4826256E-03 2.6420900E-03 7.5849248E-03 9.9999802E-03 0.000000 - Av 2018 3 25 4 0 0.4681488 0.000000 1.4631487E-03 2.6480269E-03 2.5390694E-03 0.000000 0.000000 - Av 2018 3 25 5 0 0.5295296 1.7527539E-04 1.4511489E-03 2.6588717E-03 1.4984915E-02 1.9999960E-02 0.000000 + Av 2018 3 24 19 0 0.5072557 4.3418720E-05 1.6304468E-03 2.6286799E-03 8.0221221E-03 9.9999802E-03 0.000000 + Av 2018 3 24 20 0 0.5942489 1.7837163E-04 1.6184958E-03 2.6462940E-03 1.7261395E-02 1.9999960E-02 0.000000 + Av 2018 3 24 21 0 0.5353251 0.000000 1.6043137E-03 2.6582184E-03 4.4224779E-03 0.000000 0.000000 + Av 2018 3 24 22 0 0.4825050 4.4502234E-05 1.5830790E-03 2.6636641E-03 8.2478644E-03 9.9999802E-03 0.000000 + Av 2018 3 24 23 0 0.4865374 0.000000 1.5621454E-03 2.6696958E-03 2.6197752E-03 0.000000 0.000000 + Av 2018 3 24 24 0 0.4781292 4.4300032E-05 1.5415221E-03 2.6751142E-03 7.5178174E-03 9.9999802E-03 0.000000 + Av 2018 3 25 1 0 0.5272939 3.3545821E-05 1.5230245E-03 2.6314980E-03 9.6312054E-03 9.9999802E-03 0.000000 + Av 2018 3 25 2 0 0.4682723 0.000000 1.5023820E-03 2.6366259E-03 2.7706288E-03 0.000000 0.000000 + Av 2018 3 25 3 0 0.4733941 4.4013963E-05 1.4826256E-03 2.6420900E-03 7.5849248E-03 9.9999802E-03 0.000000 + Av 2018 3 25 4 0 0.4681488 0.000000 1.4631487E-03 2.6480269E-03 2.5390694E-03 0.000000 0.000000 + Av 2018 3 25 5 0 0.5295296 1.7527539E-04 1.4511489E-03 2.6588717E-03 1.4984915E-02 1.9999960E-02 0.000000 Av 2018 3 25 6 0 0.6822573 1.3511948E-05 1.4608712E-03 2.6357318E-03 2.7411301E-02 2.9999940E-02 2.3274083E-04 Av 2018 3 25 7 0 0.5295197 6.4093058E-08 1.4608102E-03 2.2986180E-03 6.0332743E-03 0.000000 1.8420706E-03 Av 2018 3 25 8 0 0.4555577 1.4859276E-04 1.4473964E-03 1.9549238E-03 1.4752591E-02 1.9999960E-02 3.4514004E-03 @@ -2034,17 +2034,17 @@ Av 2018 3 25 16 0 0.3173742 0.000000 1.2924412E-03 1.9585253E-03 5.5193079E-05 0.000000 3.4514004E-03 Av 2018 3 25 17 0 0.3541159 0.000000 1.2733755E-03 2.3114854E-03 4.0195966E-05 0.000000 1.8420706E-03 Av 2018 3 25 18 0 0.3880330 0.000000 1.2545912E-03 2.6644359E-03 1.9186913E-04 0.000000 2.3274083E-04 - Av 2018 3 25 19 0 0.4010476 0.000000 1.2360840E-03 2.7145271E-03 0.000000 0.000000 0.000000 - Av 2018 3 25 20 0 0.3960800 0.000000 1.2178499E-03 2.7134062E-03 0.000000 0.000000 0.000000 - Av 2018 3 25 21 0 0.3951947 0.000000 1.1998847E-03 2.7122758E-03 0.000000 0.000000 0.000000 - Av 2018 3 25 22 0 0.3929251 0.000000 1.1821846E-03 2.7111366E-03 0.000000 0.000000 0.000000 - Av 2018 3 25 23 0 0.3911713 0.000000 1.1647454E-03 2.7099880E-03 0.000000 0.000000 0.000000 - Av 2018 3 25 24 0 0.3892722 0.000000 1.1475637E-03 2.7088311E-03 0.000000 0.000000 0.000000 - Av 2018 3 26 1 0 0.3836721 0.000000 1.1306354E-03 2.6519576E-03 0.000000 0.000000 0.000000 - Av 2018 3 26 2 0 0.3793978 0.000000 1.1139567E-03 2.6508712E-03 0.000000 0.000000 0.000000 - Av 2018 3 26 3 0 0.3784861 0.000000 1.0975241E-03 2.6497764E-03 0.000000 0.000000 0.000000 - Av 2018 3 26 4 0 0.3777564 0.000000 1.0813340E-03 2.6486733E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 3 26 5 0 0.3756758 0.000000 1.0653825E-03 2.6475617E-03 0.000000 0.000000 0.000000 + Av 2018 3 25 19 0 0.4010476 0.000000 1.2360840E-03 2.7145271E-03 0.000000 0.000000 0.000000 + Av 2018 3 25 20 0 0.3960800 0.000000 1.2178499E-03 2.7134062E-03 0.000000 0.000000 0.000000 + Av 2018 3 25 21 0 0.3951947 0.000000 1.1998847E-03 2.7122758E-03 0.000000 0.000000 0.000000 + Av 2018 3 25 22 0 0.3929251 0.000000 1.1821846E-03 2.7111366E-03 0.000000 0.000000 0.000000 + Av 2018 3 25 23 0 0.3911713 0.000000 1.1647454E-03 2.7099880E-03 0.000000 0.000000 0.000000 + Av 2018 3 25 24 0 0.3892722 0.000000 1.1475637E-03 2.7088311E-03 0.000000 0.000000 0.000000 + Av 2018 3 26 1 0 0.3836721 0.000000 1.1306354E-03 2.6519576E-03 0.000000 0.000000 0.000000 + Av 2018 3 26 2 0 0.3793978 0.000000 1.1139567E-03 2.6508712E-03 0.000000 0.000000 0.000000 + Av 2018 3 26 3 0 0.3784861 0.000000 1.0975241E-03 2.6497764E-03 0.000000 0.000000 0.000000 + Av 2018 3 26 4 0 0.3777564 0.000000 1.0813340E-03 2.6486733E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 3 26 5 0 0.3756758 0.000000 1.0653825E-03 2.6475617E-03 0.000000 0.000000 0.000000 Av 2018 3 26 6 0 0.3687901 0.000000 1.0496665E-03 2.5882761E-03 0.000000 0.000000 2.6439241E-04 Av 2018 3 26 7 0 0.3417648 0.000000 1.0341823E-03 2.2492039E-03 0.000000 0.000000 1.8005025E-03 Av 2018 3 26 8 0 0.3026265 0.000000 1.0189264E-03 1.9101239E-03 0.000000 0.000000 3.3366128E-03 @@ -2058,17 +2058,17 @@ Av 2018 3 26 16 0 0.2735689 0.000000 9.0663327E-04 1.9098999E-03 0.000000 0.000000 3.3366128E-03 Av 2018 3 26 17 0 0.3090119 0.000000 8.9325896E-04 2.2466304E-03 0.000000 0.000000 1.8005025E-03 Av 2018 3 26 18 0 0.3409699 0.000000 8.8008202E-04 2.5833545E-03 0.000000 0.000000 2.6439241E-04 - Av 2018 3 26 19 0 0.3550373 0.000000 8.6709944E-04 2.6402930E-03 0.000000 0.000000 0.000000 - Av 2018 3 26 20 0 0.3522119 0.000000 8.5430837E-04 2.6390587E-03 0.000000 0.000000 0.000000 - Av 2018 3 26 21 0 0.3513008 0.000000 8.4170594E-04 2.6378173E-03 0.000000 0.000000 0.000000 - Av 2018 3 26 22 0 0.3497486 0.000000 8.2928949E-04 2.6365693E-03 0.000000 0.000000 0.000000 - Av 2018 3 26 23 0 0.3484434 0.000000 8.1705611E-04 2.6353151E-03 0.000000 0.000000 0.000000 - Av 2018 3 26 24 0 0.3470762 0.000000 8.0500328E-04 2.6340538E-03 0.000000 0.000000 0.000000 - Av 2018 3 27 1 0 0.3420970 0.000000 7.9312822E-04 2.5789626E-03 0.000000 0.000000 0.000000 - Av 2018 3 27 2 0 0.3384027 0.000000 7.8142830E-04 2.5777742E-03 0.000000 0.000000 0.000000 - Av 2018 3 27 3 0 0.3379472 0.000000 7.6990103E-04 2.5765798E-03 0.000000 0.000000 0.000000 - Av 2018 3 27 4 0 0.3363879 0.000000 7.5854379E-04 2.5753789E-03 0.000000 0.000000 0.000000 - Av 2018 3 27 5 0 0.3352346 0.000000 7.4735406E-04 2.5741719E-03 0.000000 0.000000 0.000000 + Av 2018 3 26 19 0 0.3550373 0.000000 8.6709944E-04 2.6402930E-03 0.000000 0.000000 0.000000 + Av 2018 3 26 20 0 0.3522119 0.000000 8.5430837E-04 2.6390587E-03 0.000000 0.000000 0.000000 + Av 2018 3 26 21 0 0.3513008 0.000000 8.4170594E-04 2.6378173E-03 0.000000 0.000000 0.000000 + Av 2018 3 26 22 0 0.3497486 0.000000 8.2928949E-04 2.6365693E-03 0.000000 0.000000 0.000000 + Av 2018 3 26 23 0 0.3484434 0.000000 8.1705611E-04 2.6353151E-03 0.000000 0.000000 0.000000 + Av 2018 3 26 24 0 0.3470762 0.000000 8.0500328E-04 2.6340538E-03 0.000000 0.000000 0.000000 + Av 2018 3 27 1 0 0.3420970 0.000000 7.9312822E-04 2.5789626E-03 0.000000 0.000000 0.000000 + Av 2018 3 27 2 0 0.3384027 0.000000 7.8142830E-04 2.5777742E-03 0.000000 0.000000 0.000000 + Av 2018 3 27 3 0 0.3379472 0.000000 7.6990103E-04 2.5765798E-03 0.000000 0.000000 0.000000 + Av 2018 3 27 4 0 0.3363879 0.000000 7.5854379E-04 2.5753789E-03 0.000000 0.000000 0.000000 + Av 2018 3 27 5 0 0.3352346 0.000000 7.4735406E-04 2.5741719E-03 0.000000 0.000000 0.000000 Av 2018 3 27 6 0 0.3283489 0.000000 7.3632941E-04 2.4910287E-03 0.000000 0.000000 3.7240874E-04 Av 2018 3 27 7 0 0.2953608 0.000000 7.2546740E-04 2.0793208E-03 0.000000 0.000000 2.2382655E-03 Av 2018 3 27 8 0 0.2490084 0.000000 7.1476563E-04 1.6676075E-03 0.000000 0.000000 4.1041221E-03 @@ -2082,17 +2082,17 @@ Av 2018 3 27 16 0 0.2185765 0.000000 6.3464337E-04 1.6576002E-03 0.000000 0.000000 4.1041221E-03 Av 2018 3 27 17 0 0.2620302 0.000000 6.2528136E-04 2.0668129E-03 0.000000 0.000000 2.2382655E-03 Av 2018 3 27 18 0 0.3016115 0.000000 6.1605748E-04 2.4760205E-03 0.000000 0.000000 3.7240874E-04 - 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Av 2018 3 31 19 0 0.2387156 0.000000 1.4573341E-04 2.2275706E-03 0.000000 0.000000 0.000000 - Av 2018 3 31 20 0 0.2392433 0.000000 1.4358362E-04 2.2259238E-03 0.000000 0.000000 0.000000 - Av 2018 3 31 21 0 0.2385462 0.000000 1.4146553E-04 2.2242782E-03 0.000000 0.000000 0.000000 - Av 2018 3 31 22 0 0.2382793 0.000000 1.3937870E-04 2.2226332E-03 0.000000 0.000000 0.000000 - Av 2018 3 31 23 0 0.2378671 0.000000 1.3732264E-04 2.2209887E-03 0.000000 0.000000 0.000000 - Av 2018 3 31 24 0 0.2375097 0.000000 1.3529691E-04 2.2193450E-03 0.000000 0.000000 0.000000 - Av 2018 4 1 1 0 0.2341847 0.000000 1.3330107E-04 2.1742445E-03 0.000000 0.000000 0.000000 - Av 2018 4 1 2 0 0.2319005 0.000000 1.3133467E-04 2.1726724E-03 0.000000 0.000000 0.000000 - Av 2018 4 1 3 0 0.2322159 0.000000 1.2939727E-04 2.1711013E-03 0.000000 0.000000 0.000000 - Av 2018 4 1 4 0 0.2316315 0.000000 1.2748846E-04 2.1695306E-03 0.000000 0.000000 0.000000 - Av 2018 4 1 5 0 0.2313638 0.000000 1.2560780E-04 2.1679606E-03 0.000000 0.000000 0.000000 + Av 2018 3 31 19 0 0.2387156 0.000000 1.4573341E-04 2.2275706E-03 0.000000 0.000000 0.000000 + Av 2018 3 31 20 0 0.2392433 0.000000 1.4358362E-04 2.2259238E-03 0.000000 0.000000 0.000000 + Av 2018 3 31 21 0 0.2385462 0.000000 1.4146553E-04 2.2242782E-03 0.000000 0.000000 0.000000 + Av 2018 3 31 22 0 0.2382793 0.000000 1.3937870E-04 2.2226332E-03 0.000000 0.000000 0.000000 + Av 2018 3 31 23 0 0.2378671 0.000000 1.3732264E-04 2.2209887E-03 0.000000 0.000000 0.000000 + Av 2018 3 31 24 0 0.2375097 0.000000 1.3529691E-04 2.2193450E-03 0.000000 0.000000 0.000000 + Av 2018 4 1 1 0 0.2341847 0.000000 1.3330107E-04 2.1742445E-03 0.000000 0.000000 0.000000 + Av 2018 4 1 2 0 0.2319005 0.000000 1.3133467E-04 2.1726724E-03 0.000000 0.000000 0.000000 + Av 2018 4 1 3 0 0.2322159 0.000000 1.2939727E-04 2.1711013E-03 0.000000 0.000000 0.000000 + Av 2018 4 1 4 0 0.2316315 0.000000 1.2748846E-04 2.1695306E-03 0.000000 0.000000 0.000000 + Av 2018 4 1 5 0 0.2313638 0.000000 1.2560780E-04 2.1679606E-03 0.000000 0.000000 0.000000 Av 2018 4 1 6 0 0.2235560 0.000000 1.2375489E-04 2.0577314E-03 0.000000 0.000000 4.9390923E-04 Av 2018 4 1 7 0 0.1953511 0.000000 1.2192931E-04 1.7195401E-03 0.000000 0.000000 2.0240091E-03 Av 2018 4 1 8 0 0.1586868 0.000000 1.2013066E-04 1.3813477E-03 0.000000 0.000000 3.5541088E-03 @@ -2202,17 +2202,17 @@ Av 2018 4 1 16 0 0.1973560 1.0561597E-04 1.1245102E-04 1.3790918E-03 5.6031300E-03 0.1599997 3.5541088E-03 Av 2018 4 1 17 0 0.2625343 1.3854186E-05 1.1730941E-04 1.7298287E-03 6.7095952E-03 9.9999802E-03 2.0240091E-03 Av 2018 4 1 18 0 0.2843819 1.8814699E-05 1.1736576E-04 2.0742901E-03 7.5836508E-03 9.9999802E-03 4.9390923E-04 - Av 2018 4 1 19 0 0.2761980 0.000000 1.1666063E-04 2.1866215E-03 2.3324592E-03 0.000000 0.000000 - Av 2018 4 1 20 0 0.2388881 0.000000 1.1493971E-04 2.1849545E-03 9.2979294E-04 0.000000 0.000000 - Av 2018 4 1 21 0 0.2385984 0.000000 1.1324416E-04 2.1832883E-03 4.4796374E-04 0.000000 0.000000 - Av 2018 4 1 22 0 0.2335984 0.000000 1.1157364E-04 2.1816231E-03 2.4604934E-04 0.000000 0.000000 - Av 2018 4 1 23 0 0.2328512 0.000000 1.0992774E-04 2.1799589E-03 1.4856113E-04 0.000000 0.000000 - Av 2018 4 1 24 0 0.2316453 0.000000 1.0830614E-04 2.1782957E-03 9.6283606E-05 0.000000 0.000000 - Av 2018 4 2 1 0 0.2281754 0.000000 1.0670845E-04 2.1342023E-03 6.5905799E-05 0.000000 0.000000 - Av 2018 4 2 2 0 0.2257282 0.000000 1.0513434E-04 2.1326097E-03 4.7103505E-05 0.000000 0.000000 - Av 2018 4 2 3 0 0.2259395 0.000000 1.0358344E-04 2.1310181E-03 3.4860270E-05 0.000000 0.000000 - Av 2018 4 2 4 0 0.2263174 0.000000 1.0205542E-04 2.1294274E-03 1.7615763E-04 0.000000 0.000000 - Av 2018 4 2 5 0 0.2255270 0.000000 1.0054994E-04 2.1278376E-03 0.000000 0.000000 0.000000 + Av 2018 4 1 19 0 0.2761980 0.000000 1.1666063E-04 2.1866215E-03 2.3324592E-03 0.000000 0.000000 + Av 2018 4 1 20 0 0.2388881 0.000000 1.1493971E-04 2.1849545E-03 9.2979294E-04 0.000000 0.000000 + Av 2018 4 1 21 0 0.2385984 0.000000 1.1324416E-04 2.1832883E-03 4.4796374E-04 0.000000 0.000000 + Av 2018 4 1 22 0 0.2335984 0.000000 1.1157364E-04 2.1816231E-03 2.4604934E-04 0.000000 0.000000 + Av 2018 4 1 23 0 0.2328512 0.000000 1.0992774E-04 2.1799589E-03 1.4856113E-04 0.000000 0.000000 + Av 2018 4 1 24 0 0.2316453 0.000000 1.0830614E-04 2.1782957E-03 9.6283606E-05 0.000000 0.000000 + Av 2018 4 2 1 0 0.2281754 0.000000 1.0670845E-04 2.1342023E-03 6.5905799E-05 0.000000 0.000000 + Av 2018 4 2 2 0 0.2257282 0.000000 1.0513434E-04 2.1326097E-03 4.7103505E-05 0.000000 0.000000 + Av 2018 4 2 3 0 0.2259395 0.000000 1.0358344E-04 2.1310181E-03 3.4860270E-05 0.000000 0.000000 + Av 2018 4 2 4 0 0.2263174 0.000000 1.0205542E-04 2.1294274E-03 1.7615763E-04 0.000000 0.000000 + Av 2018 4 2 5 0 0.2255270 0.000000 1.0054994E-04 2.1278376E-03 0.000000 0.000000 0.000000 Av 2018 4 2 6 0 0.2159791 0.000000 9.9066674E-05 2.0062784E-03 0.000000 0.000000 5.4531975E-04 Av 2018 4 2 7 0 0.1872396 0.000000 9.7605283E-05 1.6619710E-03 0.000000 0.000000 2.1031357E-03 Av 2018 4 2 8 0 0.1499820 0.000000 9.6165451E-05 1.3176645E-03 0.000000 0.000000 3.6609517E-03 @@ -2226,17 +2226,17 @@ Av 2018 4 2 16 0 0.1305253 0.000000 8.5385684E-05 1.3050023E-03 0.000000 0.000000 3.6609517E-03 Av 2018 4 2 17 0 0.1662088 0.000000 8.4126114E-05 1.6461432E-03 0.000000 0.000000 2.1031357E-03 Av 2018 4 2 18 0 0.2002009 0.000000 8.2885126E-05 1.9872852E-03 0.000000 0.000000 5.4531975E-04 - Av 2018 4 2 19 0 0.2196118 0.000000 8.1662445E-05 2.1056789E-03 0.000000 0.000000 0.000000 - Av 2018 4 2 20 0 0.2206848 0.000000 8.0457794E-05 2.1041031E-03 0.000000 0.000000 0.000000 - Av 2018 4 2 21 0 0.2199351 0.000000 7.9270911E-05 2.1025280E-03 0.000000 0.000000 0.000000 - Av 2018 4 2 22 0 0.2198217 0.000000 7.8101541E-05 2.1009541E-03 0.000000 0.000000 0.000000 - Av 2018 4 2 23 0 0.2194896 0.000000 7.6949422E-05 2.0993811E-03 0.000000 0.000000 0.000000 - Av 2018 4 2 24 0 0.2192360 0.000000 7.5814292E-05 2.0978090E-03 0.000000 0.000000 0.000000 - Av 2018 4 3 1 0 0.2162095 0.000000 7.4695912E-05 2.0557928E-03 0.000000 0.000000 0.000000 - Av 2018 4 3 2 0 0.2141539 0.000000 7.3594034E-05 2.0542869E-03 0.000000 0.000000 0.000000 - Av 2018 4 3 3 0 0.2145154 0.000000 7.2508403E-05 2.0527816E-03 0.000000 0.000000 0.000000 - Av 2018 4 3 4 0 0.2140388 0.000000 7.1438786E-05 2.0512773E-03 0.000000 0.000000 0.000000 - Av 2018 4 3 5 0 0.2138559 0.000000 7.0384951E-05 2.0497739E-03 0.000000 0.000000 0.000000 + Av 2018 4 2 19 0 0.2196118 0.000000 8.1662445E-05 2.1056789E-03 0.000000 0.000000 0.000000 + Av 2018 4 2 20 0 0.2206848 0.000000 8.0457794E-05 2.1041031E-03 0.000000 0.000000 0.000000 + Av 2018 4 2 21 0 0.2199351 0.000000 7.9270911E-05 2.1025280E-03 0.000000 0.000000 0.000000 + Av 2018 4 2 22 0 0.2198217 0.000000 7.8101541E-05 2.1009541E-03 0.000000 0.000000 0.000000 + Av 2018 4 2 23 0 0.2194896 0.000000 7.6949422E-05 2.0993811E-03 0.000000 0.000000 0.000000 + Av 2018 4 2 24 0 0.2192360 0.000000 7.5814292E-05 2.0978090E-03 0.000000 0.000000 0.000000 + Av 2018 4 3 1 0 0.2162095 0.000000 7.4695912E-05 2.0557928E-03 0.000000 0.000000 0.000000 + Av 2018 4 3 2 0 0.2141539 0.000000 7.3594034E-05 2.0542869E-03 0.000000 0.000000 0.000000 + Av 2018 4 3 3 0 0.2145154 0.000000 7.2508403E-05 2.0527816E-03 0.000000 0.000000 0.000000 + Av 2018 4 3 4 0 0.2140388 0.000000 7.1438786E-05 2.0512773E-03 0.000000 0.000000 0.000000 + Av 2018 4 3 5 0 0.2138559 0.000000 7.0384951E-05 2.0497739E-03 0.000000 0.000000 0.000000 Av 2018 4 3 6 0 0.2039892 0.000000 6.9346657E-05 1.9081482E-03 0.000000 0.000000 6.3692295E-04 Av 2018 4 3 7 0 0.1720986 0.000000 6.8323687E-05 1.5352227E-03 0.000000 0.000000 2.3252124E-03 Av 2018 4 3 8 0 0.1321026 0.000000 6.7315807E-05 1.1622983E-03 0.000000 0.000000 4.0135016E-03 @@ -2250,17 +2250,17 @@ Av 2018 4 3 16 0 0.1117263 0.000000 5.9769973E-05 1.1503224E-03 0.000000 0.000000 4.0135016E-03 Av 2018 4 3 17 0 0.1502222 0.000000 5.8888272E-05 1.5202531E-03 0.000000 0.000000 2.3252124E-03 Av 2018 4 3 18 0 0.1871915 0.000000 5.8019574E-05 1.8901846E-03 0.000000 0.000000 6.3692295E-04 - Av 2018 4 3 19 0 0.2089553 0.000000 5.7163696E-05 2.0288164E-03 0.000000 0.000000 0.000000 - Av 2018 4 3 20 0 0.2106466 0.000000 5.6320441E-05 2.0273260E-03 0.000000 0.000000 0.000000 - Av 2018 4 3 21 0 0.2097423 0.000000 5.5489629E-05 2.0258364E-03 0.000000 0.000000 0.000000 - Av 2018 4 3 22 0 0.2097423 0.000000 5.4671069E-05 2.0243477E-03 0.000000 0.000000 0.000000 - Av 2018 4 3 23 0 0.2094297 0.000000 5.3864587E-05 2.0228596E-03 0.000000 0.000000 0.000000 - Av 2018 4 3 24 0 0.2092275 0.000000 5.3069998E-05 2.0213728E-03 0.000000 0.000000 0.000000 - Av 2018 4 4 1 0 0.2063684 0.000000 5.2287131E-05 1.9813227E-03 0.000000 0.000000 0.000000 - Av 2018 4 4 2 0 0.2044389 0.000000 5.1515814E-05 1.9798973E-03 0.000000 0.000000 0.000000 - Av 2018 4 4 3 0 0.2048121 0.000000 5.0755873E-05 1.9784728E-03 0.000000 0.000000 0.000000 - Av 2018 4 4 4 0 0.2043864 0.000000 5.0007144E-05 1.9770493E-03 0.000000 0.000000 0.000000 - Av 2018 4 4 5 0 0.2052123 0.000000 4.9269460E-05 1.9756267E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 4 3 19 0 0.2089553 0.000000 5.7163696E-05 2.0288164E-03 0.000000 0.000000 0.000000 + Av 2018 4 3 20 0 0.2106466 0.000000 5.6320441E-05 2.0273260E-03 0.000000 0.000000 0.000000 + Av 2018 4 3 21 0 0.2097423 0.000000 5.5489629E-05 2.0258364E-03 0.000000 0.000000 0.000000 + Av 2018 4 3 22 0 0.2097423 0.000000 5.4671069E-05 2.0243477E-03 0.000000 0.000000 0.000000 + Av 2018 4 3 23 0 0.2094297 0.000000 5.3864587E-05 2.0228596E-03 0.000000 0.000000 0.000000 + Av 2018 4 3 24 0 0.2092275 0.000000 5.3069998E-05 2.0213728E-03 0.000000 0.000000 0.000000 + Av 2018 4 4 1 0 0.2063684 0.000000 5.2287131E-05 1.9813227E-03 0.000000 0.000000 0.000000 + Av 2018 4 4 2 0 0.2044389 0.000000 5.1515814E-05 1.9798973E-03 0.000000 0.000000 0.000000 + Av 2018 4 4 3 0 0.2048121 0.000000 5.0755873E-05 1.9784728E-03 0.000000 0.000000 0.000000 + Av 2018 4 4 4 0 0.2043864 0.000000 5.0007144E-05 1.9770493E-03 0.000000 0.000000 0.000000 + Av 2018 4 4 5 0 0.2052123 0.000000 4.9269460E-05 1.9756267E-03 0.000000 9.9999802E-03 0.000000 Av 2018 4 4 6 0 0.1931598 0.000000 4.8542657E-05 1.8064480E-03 0.000000 0.000000 7.6253078E-04 Av 2018 4 4 7 0 0.1562622 0.000000 4.7826576E-05 1.3902050E-03 0.000000 0.000000 2.6480847E-03 Av 2018 4 4 8 0 0.1121530 0.000000 4.7121059E-05 9.7396295E-04 0.000000 0.000000 4.5336382E-03 @@ -2274,17 +2274,17 @@ Av 2018 4 4 16 0 9.0024784E-02 0.000000 4.1838975E-05 9.6262922E-04 0.000000 0.000000 4.5336382E-03 Av 2018 4 4 17 0 0.1327962 0.000000 4.1221785E-05 1.3760377E-03 0.000000 0.000000 2.6480847E-03 Av 2018 4 4 18 0 0.1742076 0.000000 4.0613701E-05 1.7894474E-03 0.000000 0.000000 7.6253078E-04 - Av 2018 4 4 19 0 0.1993082 0.000000 4.0014584E-05 1.9557925E-03 0.000000 0.000000 0.000000 - Av 2018 4 4 20 0 0.2017701 0.000000 3.9424307E-05 1.9543818E-03 0.000000 0.000000 0.000000 - Av 2018 4 4 21 0 0.2006429 0.000000 3.8842736E-05 1.9529721E-03 0.000000 0.000000 0.000000 - Av 2018 4 4 22 0 0.2007649 0.000000 3.8269747E-05 1.9515631E-03 0.000000 0.000000 0.000000 - Av 2018 4 4 23 0 0.2004537 0.000000 3.7705209E-05 1.9501548E-03 0.000000 0.000000 0.000000 - Av 2018 4 4 24 0 0.2002945 0.000000 3.7148995E-05 1.9487473E-03 0.000000 0.000000 0.000000 - Av 2018 4 5 1 0 0.1975844 0.000000 3.6600988E-05 1.9105579E-03 0.000000 0.000000 0.000000 - Av 2018 4 5 2 0 0.1957664 0.000000 3.6061068E-05 1.9092084E-03 0.000000 0.000000 0.000000 - Av 2018 4 5 3 0 0.1961424 0.000000 3.5529109E-05 1.9078596E-03 0.000000 0.000000 0.000000 - Av 2018 4 5 4 0 0.1957566 0.000000 3.5005000E-05 1.9065116E-03 0.000000 0.000000 0.000000 - Av 2018 4 5 5 0 0.1956369 0.000000 3.4488625E-05 1.9051643E-03 0.000000 0.000000 0.000000 + Av 2018 4 4 19 0 0.1993082 0.000000 4.0014584E-05 1.9557925E-03 0.000000 0.000000 0.000000 + Av 2018 4 4 20 0 0.2017701 0.000000 3.9424307E-05 1.9543818E-03 0.000000 0.000000 0.000000 + Av 2018 4 4 21 0 0.2006429 0.000000 3.8842736E-05 1.9529721E-03 0.000000 0.000000 0.000000 + Av 2018 4 4 22 0 0.2007649 0.000000 3.8269747E-05 1.9515631E-03 0.000000 0.000000 0.000000 + Av 2018 4 4 23 0 0.2004537 0.000000 3.7705209E-05 1.9501548E-03 0.000000 0.000000 0.000000 + Av 2018 4 4 24 0 0.2002945 0.000000 3.7148995E-05 1.9487473E-03 0.000000 0.000000 0.000000 + Av 2018 4 5 1 0 0.1975844 0.000000 3.6600988E-05 1.9105579E-03 0.000000 0.000000 0.000000 + Av 2018 4 5 2 0 0.1957664 0.000000 3.6061068E-05 1.9092084E-03 0.000000 0.000000 0.000000 + Av 2018 4 5 3 0 0.1961424 0.000000 3.5529109E-05 1.9078596E-03 0.000000 0.000000 0.000000 + Av 2018 4 5 4 0 0.1957566 0.000000 3.5005000E-05 1.9065116E-03 0.000000 0.000000 0.000000 + Av 2018 4 5 5 0 0.1956369 0.000000 3.4488625E-05 1.9051643E-03 0.000000 0.000000 0.000000 Av 2018 4 5 6 0 0.1863874 0.000000 3.3979861E-05 1.7159900E-03 0.000000 3.9999921E-02 8.5376261E-04 Av 2018 4 5 7 0 0.1476637 0.000000 3.3478605E-05 1.2793455E-03 0.000000 9.9999802E-03 2.8323927E-03 Av 2018 4 5 8 0 9.8385304E-02 0.000000 3.2984743E-05 8.4270176E-04 0.000000 9.9999802E-03 4.8110229E-03 @@ -2298,17 +2298,17 @@ Av 2018 4 5 16 0 0.5252742 4.8381444E-05 2.5271700E-04 9.9102245E-04 4.9315616E-02 5.9999879E-02 4.8110229E-03 Av 2018 4 5 17 0 0.4263689 1.8052087E-07 2.9501884E-04 1.4473748E-03 9.1025559E-03 0.000000 2.8323927E-03 Av 2018 4 5 18 0 0.1967736 0.000000 2.9067675E-04 1.8817368E-03 2.6145198E-03 0.000000 8.5376261E-04 - Av 2018 4 5 19 0 0.2637693 0.000000 2.8638879E-04 2.0681128E-03 1.0161259E-03 0.000000 0.000000 - Av 2018 4 5 20 0 0.2380231 0.000000 2.8216411E-04 2.0666614E-03 4.8125032E-04 0.000000 0.000000 - Av 2018 4 5 21 0 0.2410786 0.000000 2.7800174E-04 2.0652104E-03 2.6115371E-04 0.000000 0.000000 - Av 2018 4 5 22 0 0.2370496 0.000000 2.7390078E-04 2.0637601E-03 1.5628464E-04 0.000000 0.000000 - Av 2018 4 5 23 0 0.2366095 0.000000 2.6986032E-04 2.0623102E-03 1.0060715E-04 0.000000 0.000000 - Av 2018 4 5 24 0 0.2354241 0.000000 2.6587947E-04 2.0608611E-03 6.8502901E-05 0.000000 0.000000 - Av 2018 4 6 1 0 0.2320671 0.000000 2.6195732E-04 2.0199241E-03 4.8753740E-05 0.000000 0.000000 - Av 2018 4 6 2 0 0.2296085 0.000000 2.5809306E-04 2.0185371E-03 3.5957884E-05 0.000000 0.000000 - Av 2018 4 6 3 0 0.2813548 4.3742228E-05 2.5669116E-04 2.0239046E-03 6.8107452E-03 1.9999960E-02 0.000000 - Av 2018 4 6 4 0 0.4410648 6.6056182E-06 2.6946337E-04 2.0439632E-03 2.5209192E-02 2.9999940E-02 0.000000 - Av 2018 4 6 5 0 0.4957351 1.1844630E-04 2.8610136E-04 2.0683543E-03 2.1379590E-02 1.9999960E-02 0.000000 + Av 2018 4 5 19 0 0.2637693 0.000000 2.8638879E-04 2.0681128E-03 1.0161259E-03 0.000000 0.000000 + Av 2018 4 5 20 0 0.2380231 0.000000 2.8216411E-04 2.0666614E-03 4.8125032E-04 0.000000 0.000000 + Av 2018 4 5 21 0 0.2410786 0.000000 2.7800174E-04 2.0652104E-03 2.6115371E-04 0.000000 0.000000 + Av 2018 4 5 22 0 0.2370496 0.000000 2.7390078E-04 2.0637601E-03 1.5628464E-04 0.000000 0.000000 + Av 2018 4 5 23 0 0.2366095 0.000000 2.6986032E-04 2.0623102E-03 1.0060715E-04 0.000000 0.000000 + Av 2018 4 5 24 0 0.2354241 0.000000 2.6587947E-04 2.0608611E-03 6.8502901E-05 0.000000 0.000000 + Av 2018 4 6 1 0 0.2320671 0.000000 2.6195732E-04 2.0199241E-03 4.8753740E-05 0.000000 0.000000 + Av 2018 4 6 2 0 0.2296085 0.000000 2.5809306E-04 2.0185371E-03 3.5957884E-05 0.000000 0.000000 + Av 2018 4 6 3 0 0.2813548 4.3742228E-05 2.5669116E-04 2.0239046E-03 6.8107452E-03 1.9999960E-02 0.000000 + Av 2018 4 6 4 0 0.4410648 6.6056182E-06 2.6946337E-04 2.0439632E-03 2.5209192E-02 2.9999940E-02 0.000000 + Av 2018 4 6 5 0 0.4957351 1.1844630E-04 2.8610136E-04 2.0683543E-03 2.1379590E-02 1.9999960E-02 0.000000 Av 2018 4 6 6 0 0.3228117 0.000000 2.8836643E-04 1.8569223E-03 4.8716874E-03 0.000000 1.0059020E-03 Av 2018 4 6 7 0 0.2340748 2.4617753E-05 2.8546766E-04 1.3780540E-03 7.6890751E-03 9.9999802E-03 3.1997545E-03 Av 2018 4 6 8 0 0.2174518 1.6333708E-05 2.8350423E-04 9.0389734E-04 7.2034560E-03 9.9999802E-03 5.3936071E-03 @@ -2322,17 +2322,17 @@ Av 2018 4 6 16 0 0.1036089 0.000000 2.5253094E-04 8.9685072E-04 4.6251127E-05 0.000000 5.3936071E-03 Av 2018 4 6 17 0 0.1525792 0.000000 2.4880571E-04 1.3780377E-03 3.4291388E-05 0.000000 3.1997545E-03 Av 2018 4 6 18 0 0.2015413 0.000000 2.4513542E-04 1.8592257E-03 1.7442748E-04 0.000000 1.0059020E-03 - Av 2018 4 6 19 0 0.2316662 0.000000 2.4151929E-04 2.0790650E-03 0.000000 0.000000 0.000000 - Av 2018 4 6 20 0 0.2344472 0.000000 2.3795648E-04 2.0776063E-03 0.000000 0.000000 0.000000 - Av 2018 4 6 21 0 0.2328015 0.000000 2.3444626E-04 2.0761478E-03 0.000000 0.000000 0.000000 - Av 2018 4 6 22 0 0.2327021 0.000000 2.3098782E-04 2.0746903E-03 0.000000 0.000000 0.000000 - Av 2018 4 6 23 0 0.2320721 0.000000 2.2758039E-04 2.0732330E-03 0.000000 0.000000 0.000000 - Av 2018 4 6 24 0 0.7440261 4.0073387E-04 3.6689063E-04 2.0930755E-03 6.7633711E-02 0.1399997 0.000000 - Av 2018 4 7 1 0 1.452085 2.5250763E-03 6.6426565E-04 2.0950977E-03 9.7031228E-02 9.9999800E-02 0.000000 - Av 2018 4 7 2 0 0.8939666 3.9797906E-05 8.1669114E-04 2.1231060E-03 2.2263670E-02 9.9999802E-03 0.000000 - Av 2018 4 7 3 0 0.9825679 7.9544220E-04 1.0040036E-03 2.1501589E-03 9.7100884E-02 0.1099998 0.000000 - Av 2018 4 7 4 0 1.493872 2.0393913E-03 1.2977559E-03 2.1944237E-03 7.3947757E-02 6.9999859E-02 0.000000 - Av 2018 4 7 5 0 0.7035900 0.000000 1.3904180E-03 2.2170995E-03 1.1675520E-02 0.000000 0.000000 + Av 2018 4 6 19 0 0.2316662 0.000000 2.4151929E-04 2.0790650E-03 0.000000 0.000000 0.000000 + Av 2018 4 6 20 0 0.2344472 0.000000 2.3795648E-04 2.0776063E-03 0.000000 0.000000 0.000000 + Av 2018 4 6 21 0 0.2328015 0.000000 2.3444626E-04 2.0761478E-03 0.000000 0.000000 0.000000 + Av 2018 4 6 22 0 0.2327021 0.000000 2.3098782E-04 2.0746903E-03 0.000000 0.000000 0.000000 + Av 2018 4 6 23 0 0.2320721 0.000000 2.2758039E-04 2.0732330E-03 0.000000 0.000000 0.000000 + Av 2018 4 6 24 0 0.7440261 4.0073387E-04 3.6689063E-04 2.0930755E-03 6.7633711E-02 0.1399997 0.000000 + Av 2018 4 7 1 0 1.452085 2.5250763E-03 6.6426565E-04 2.0950977E-03 9.7031228E-02 9.9999800E-02 0.000000 + Av 2018 4 7 2 0 0.8939666 3.9797906E-05 8.1669114E-04 2.1231060E-03 2.2263670E-02 9.9999802E-03 0.000000 + Av 2018 4 7 3 0 0.9825679 7.9544220E-04 1.0040036E-03 2.1501589E-03 9.7100884E-02 0.1099998 0.000000 + Av 2018 4 7 4 0 1.493872 2.0393913E-03 1.2977559E-03 2.1944237E-03 7.3947757E-02 6.9999859E-02 0.000000 + Av 2018 4 7 5 0 0.7035900 0.000000 1.3904180E-03 2.2170995E-03 1.1675520E-02 0.000000 0.000000 Av 2018 4 7 6 0 0.3304576 0.000000 1.3699072E-03 2.0067587E-03 3.1407399E-03 0.000000 9.5176836E-04 Av 2018 4 7 7 0 0.3419936 0.000000 1.3496989E-03 1.5744767E-03 1.1709271E-03 0.000000 2.9123388E-03 Av 2018 4 7 8 0 0.2583984 0.000000 1.3297887E-03 1.1421903E-03 5.3932954E-04 0.000000 4.8729093E-03 @@ -2346,17 +2346,17 @@ Av 2018 4 7 16 0 1.340678 2.4728514E-03 1.7193212E-03 1.2778204E-03 8.2348235E-02 8.9999817E-02 4.8729093E-03 Av 2018 4 7 17 0 1.320318 6.3551374E-04 2.0060728E-03 1.7555011E-03 7.6001033E-02 7.9999842E-02 2.9123388E-03 Av 2018 4 7 18 0 1.970255 6.2394869E-03 2.4506727E-03 2.2337269E-03 0.1209835 0.1299997 9.5176836E-04 - Av 2018 4 7 19 0 3.482270 1.4775434E-02 3.2432557E-03 2.4906651E-03 0.1646775 0.1699997 0.000000 - Av 2018 4 7 20 0 2.572559 9.9669804E-04 3.9314283E-03 2.5393714E-03 9.7602762E-02 8.9999817E-02 0.000000 - Av 2018 4 7 21 0 2.742428 1.3599158E-02 4.6116444E-03 2.5891892E-03 0.1445245 0.1499997 0.000000 - Av 2018 4 7 22 0 3.957706 1.1404822E-02 5.5942456E-03 2.6397810E-03 0.1585114 0.1599997 0.000000 - Av 2018 4 7 23 0 2.798487 5.6081987E-03 6.3492861E-03 2.6913329E-03 9.7035229E-02 8.9999817E-02 0.000000 - Av 2018 4 7 24 0 1.998101 7.6992635E-04 6.7663770E-03 2.7436889E-03 8.1975721E-02 7.9999842E-02 0.000000 - Av 2018 4 8 1 0 1.644203 1.1614603E-03 6.9543226E-03 2.7351053E-03 4.5517005E-02 3.9999921E-02 0.000000 - Av 2018 4 8 2 0 1.509422 1.4811056E-04 7.0063351E-03 2.7820098E-03 4.9283028E-02 4.9999900E-02 0.000000 - Av 2018 4 8 3 0 1.432694 4.8121536E-04 7.0286407E-03 2.8257109E-03 3.3002842E-02 2.9999940E-02 0.000000 - Av 2018 4 8 4 0 1.207189 6.6967907E-05 6.9643604E-03 2.8530105E-03 1.4252554E-02 9.9999802E-03 0.000000 - Av 2018 4 8 5 0 1.334829 1.4748142E-04 6.9555016E-03 2.8852201E-03 4.3253537E-02 4.9999900E-02 0.000000 + Av 2018 4 7 19 0 3.482270 1.4775434E-02 3.2432557E-03 2.4906651E-03 0.1646775 0.1699997 0.000000 + Av 2018 4 7 20 0 2.572559 9.9669804E-04 3.9314283E-03 2.5393714E-03 9.7602762E-02 8.9999817E-02 0.000000 + Av 2018 4 7 21 0 2.742428 1.3599158E-02 4.6116444E-03 2.5891892E-03 0.1445245 0.1499997 0.000000 + Av 2018 4 7 22 0 3.957706 1.1404822E-02 5.5942456E-03 2.6397810E-03 0.1585114 0.1599997 0.000000 + Av 2018 4 7 23 0 2.798487 5.6081987E-03 6.3492861E-03 2.6913329E-03 9.7035229E-02 8.9999817E-02 0.000000 + Av 2018 4 7 24 0 1.998101 7.6992635E-04 6.7663770E-03 2.7436889E-03 8.1975721E-02 7.9999842E-02 0.000000 + Av 2018 4 8 1 0 1.644203 1.1614603E-03 6.9543226E-03 2.7351053E-03 4.5517005E-02 3.9999921E-02 0.000000 + Av 2018 4 8 2 0 1.509422 1.4811056E-04 7.0063351E-03 2.7820098E-03 4.9283028E-02 4.9999900E-02 0.000000 + Av 2018 4 8 3 0 1.432694 4.8121536E-04 7.0286407E-03 2.8257109E-03 3.3002842E-02 2.9999940E-02 0.000000 + Av 2018 4 8 4 0 1.207189 6.6967907E-05 6.9643604E-03 2.8530105E-03 1.4252554E-02 9.9999802E-03 0.000000 + Av 2018 4 8 5 0 1.334829 1.4748142E-04 6.9555016E-03 2.8852201E-03 4.3253537E-02 4.9999900E-02 0.000000 Av 2018 4 8 6 0 1.882483 2.2962654E-03 7.1764430E-03 2.7459823E-03 7.5252838E-02 7.9999842E-02 8.6830399E-04 Av 2018 4 8 7 0 2.587888 6.5234625E-03 7.6822271E-03 2.4274555E-03 0.1052872 0.1099998 2.5631406E-03 Av 2018 4 8 8 0 2.039917 6.8679161E-04 8.0041261E-03 2.1048547E-03 4.6130668E-02 3.9999921E-02 4.2579775E-03 @@ -2370,17 +2370,17 @@ Av 2018 4 8 16 0 0.9320986 0.000000 7.1623442E-03 2.1524564E-03 7.4399730E-05 0.000000 4.2579775E-03 Av 2018 4 8 17 0 0.9593856 0.000000 7.0566884E-03 2.5268577E-03 5.2468386E-05 0.000000 2.5631406E-03 Av 2018 4 8 18 0 0.9869666 0.000000 6.9525912E-03 2.9011930E-03 3.8411159E-05 0.000000 8.6830399E-04 - Av 2018 4 8 19 0 1.003291 0.000000 6.8500298E-03 3.0936264E-03 1.8671209E-04 0.000000 0.000000 - Av 2018 4 8 20 0 0.9968699 0.000000 6.7489813E-03 3.0949698E-03 0.000000 0.000000 0.000000 - Av 2018 4 8 21 0 0.9843823 0.000000 6.6494234E-03 3.0962513E-03 0.000000 0.000000 0.000000 - Av 2018 4 8 22 0 0.9754654 0.000000 6.5513337E-03 3.0974727E-03 0.000000 0.000000 0.000000 - Av 2018 4 8 23 0 0.9654970 0.000000 6.4546913E-03 3.0986350E-03 0.000000 0.000000 0.000000 - Av 2018 4 8 24 0 0.9560814 0.000000 6.3594743E-03 3.0997396E-03 0.000000 0.000000 0.000000 - Av 2018 4 9 1 0 0.9422098 0.000000 6.2656617E-03 3.0353181E-03 0.000000 0.000000 0.000000 - Av 2018 4 9 2 0 0.9300750 0.000000 6.1732335E-03 3.0363938E-03 0.000000 0.000000 0.000000 - Av 2018 4 9 3 0 0.9219697 0.000000 6.0821688E-03 3.0374161E-03 0.000000 0.000000 0.000000 - Av 2018 4 9 4 0 0.9126399 0.000000 5.9924470E-03 3.0383859E-03 0.000000 0.000000 0.000000 - Av 2018 4 9 5 0 0.9039100 0.000000 5.9040491E-03 3.0393044E-03 0.000000 0.000000 0.000000 + Av 2018 4 8 19 0 1.003291 0.000000 6.8500298E-03 3.0936264E-03 1.8671209E-04 0.000000 0.000000 + Av 2018 4 8 20 0 0.9968699 0.000000 6.7489813E-03 3.0949698E-03 0.000000 0.000000 0.000000 + Av 2018 4 8 21 0 0.9843823 0.000000 6.6494234E-03 3.0962513E-03 0.000000 0.000000 0.000000 + Av 2018 4 8 22 0 0.9754654 0.000000 6.5513337E-03 3.0974727E-03 0.000000 0.000000 0.000000 + Av 2018 4 8 23 0 0.9654970 0.000000 6.4546913E-03 3.0986350E-03 0.000000 0.000000 0.000000 + Av 2018 4 8 24 0 0.9560814 0.000000 6.3594743E-03 3.0997396E-03 0.000000 0.000000 0.000000 + Av 2018 4 9 1 0 0.9422098 0.000000 6.2656617E-03 3.0353181E-03 0.000000 0.000000 0.000000 + Av 2018 4 9 2 0 0.9300750 0.000000 6.1732335E-03 3.0363938E-03 0.000000 0.000000 0.000000 + Av 2018 4 9 3 0 0.9219697 0.000000 6.0821688E-03 3.0374161E-03 0.000000 0.000000 0.000000 + Av 2018 4 9 4 0 0.9126399 0.000000 5.9924470E-03 3.0383859E-03 0.000000 0.000000 0.000000 + Av 2018 4 9 5 0 0.9039100 0.000000 5.9040491E-03 3.0393044E-03 0.000000 0.000000 0.000000 Av 2018 4 9 6 0 0.8770494 0.000000 5.8169551E-03 2.7774477E-03 0.000000 0.000000 1.1942029E-03 Av 2018 4 9 7 0 0.8231169 0.000000 5.7311454E-03 2.2909353E-03 0.000000 0.000000 3.4093440E-03 Av 2018 4 9 8 0 0.7633489 0.000000 5.6466023E-03 1.8043746E-03 0.000000 0.000000 5.6244847E-03 @@ -2394,17 +2394,17 @@ Av 2018 4 9 16 0 0.6764261 0.000000 5.0136400E-03 1.8089085E-03 0.000000 0.000000 5.6244847E-03 Av 2018 4 9 17 0 0.7184291 0.000000 4.9396809E-03 2.2966154E-03 0.000000 0.000000 3.4093440E-03 Av 2018 4 9 18 0 0.7608768 0.000000 4.8668128E-03 2.7842824E-03 0.000000 0.000000 1.1942029E-03 - Av 2018 4 9 19 0 0.7879050 0.000000 4.7950200E-03 3.0473045E-03 0.000000 0.000000 0.000000 - Av 2018 4 9 20 0 0.7869322 0.000000 4.7242860E-03 3.0475636E-03 0.000000 0.000000 0.000000 - Av 2018 4 9 21 0 0.7777620 0.000000 4.6545952E-03 3.0477850E-03 0.000000 0.000000 0.000000 - Av 2018 4 9 22 0 0.7715778 0.000000 4.5859325E-03 3.0479697E-03 0.000000 0.000000 0.000000 - Av 2018 4 9 23 0 0.7644891 0.000000 4.5182831E-03 3.0481180E-03 0.000000 0.000000 0.000000 - Av 2018 4 9 24 0 0.7578467 0.000000 4.4516316E-03 3.0482309E-03 0.000000 0.000000 0.000000 - Av 2018 4 10 1 0 0.7468208 0.000000 4.3859631E-03 2.9841661E-03 0.000000 0.000000 0.000000 - Av 2018 4 10 2 0 0.7374532 0.000000 4.3212627E-03 2.9843014E-03 0.000000 0.000000 0.000000 - Av 2018 4 10 3 0 0.7338415 0.000000 4.2575174E-03 2.9844034E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 4 10 4 0 0.7265105 0.000000 4.1947118E-03 2.9844723E-03 0.000000 0.000000 0.000000 - Av 2018 4 10 5 0 0.7205768 0.000000 4.1328333E-03 2.9845093E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 4 9 19 0 0.7879050 0.000000 4.7950200E-03 3.0473045E-03 0.000000 0.000000 0.000000 + Av 2018 4 9 20 0 0.7869322 0.000000 4.7242860E-03 3.0475636E-03 0.000000 0.000000 0.000000 + Av 2018 4 9 21 0 0.7777620 0.000000 4.6545952E-03 3.0477850E-03 0.000000 0.000000 0.000000 + Av 2018 4 9 22 0 0.7715778 0.000000 4.5859325E-03 3.0479697E-03 0.000000 0.000000 0.000000 + Av 2018 4 9 23 0 0.7644891 0.000000 4.5182831E-03 3.0481180E-03 0.000000 0.000000 0.000000 + Av 2018 4 9 24 0 0.7578467 0.000000 4.4516316E-03 3.0482309E-03 0.000000 0.000000 0.000000 + Av 2018 4 10 1 0 0.7468208 0.000000 4.3859631E-03 2.9841661E-03 0.000000 0.000000 0.000000 + Av 2018 4 10 2 0 0.7374532 0.000000 4.3212627E-03 2.9843014E-03 0.000000 0.000000 0.000000 + Av 2018 4 10 3 0 0.7338415 0.000000 4.2575174E-03 2.9844034E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 4 10 4 0 0.7265105 0.000000 4.1947118E-03 2.9844723E-03 0.000000 0.000000 0.000000 + Av 2018 4 10 5 0 0.7205768 0.000000 4.1328333E-03 2.9845093E-03 0.000000 9.9999802E-03 0.000000 Av 2018 4 10 6 0 0.7011698 0.000000 4.0718676E-03 2.7141413E-03 0.000000 2.9999940E-02 1.2289708E-03 Av 2018 4 10 7 0 0.6517502 0.000000 4.0118014E-03 2.2362620E-03 0.000000 2.9999940E-02 3.4010347E-03 Av 2018 4 10 8 0 0.5935383 4.3595178E-06 3.9528650E-03 1.7603494E-03 0.000000 1.9999960E-02 5.5730990E-03 @@ -2418,17 +2418,17 @@ Av 2018 4 10 16 0 0.5465321 0.000000 3.6861375E-03 1.8139158E-03 2.0908380E-04 0.000000 5.5730990E-03 Av 2018 4 10 17 0 0.5869943 0.000000 3.6317613E-03 2.2914945E-03 1.2927341E-04 0.000000 3.4010347E-03 Av 2018 4 10 18 0 0.6303093 0.000000 3.5781872E-03 2.7690453E-03 8.5316460E-05 0.000000 1.2289708E-03 - Av 2018 4 10 19 0 0.6588898 0.000000 3.5254033E-03 3.0390888E-03 5.9235859E-05 0.000000 0.000000 - Av 2018 4 10 20 0 0.6600732 0.000000 3.4733980E-03 3.0387321E-03 4.2822609E-05 0.000000 0.000000 - Av 2018 4 10 21 0 0.6535484 0.000000 3.4221599E-03 3.0383491E-03 1.9929491E-04 0.000000 0.000000 - Av 2018 4 10 22 0 0.6485611 0.000000 3.3716778E-03 3.0379407E-03 0.000000 0.000000 0.000000 - Av 2018 4 10 23 0 0.6420745 0.000000 3.3219403E-03 3.0375072E-03 0.000000 0.000000 0.000000 - Av 2018 4 10 24 0 0.6375604 0.000000 3.2729364E-03 3.0370485E-03 0.000000 0.000000 0.000000 - Av 2018 4 11 1 0 0.6281177 0.000000 3.2246555E-03 2.9727134E-03 0.000000 0.000000 0.000000 - Av 2018 4 11 2 0 0.6204895 0.000000 3.1770868E-03 2.9723030E-03 0.000000 0.000000 0.000000 - Av 2018 4 11 3 0 0.6166681 0.000000 3.1302196E-03 2.9718690E-03 0.000000 0.000000 0.000000 - Av 2018 4 11 4 0 0.6116146 0.000000 3.0840442E-03 2.9714119E-03 0.000000 0.000000 0.000000 - Av 2018 4 11 5 0 0.6070796 0.000000 3.0385496E-03 2.9709323E-03 0.000000 0.000000 0.000000 + Av 2018 4 10 19 0 0.6588898 0.000000 3.5254033E-03 3.0390888E-03 5.9235859E-05 0.000000 0.000000 + Av 2018 4 10 20 0 0.6600732 0.000000 3.4733980E-03 3.0387321E-03 4.2822609E-05 0.000000 0.000000 + Av 2018 4 10 21 0 0.6535484 0.000000 3.4221599E-03 3.0383491E-03 1.9929491E-04 0.000000 0.000000 + Av 2018 4 10 22 0 0.6485611 0.000000 3.3716778E-03 3.0379407E-03 0.000000 0.000000 0.000000 + Av 2018 4 10 23 0 0.6420745 0.000000 3.3219403E-03 3.0375072E-03 0.000000 0.000000 0.000000 + Av 2018 4 10 24 0 0.6375604 0.000000 3.2729364E-03 3.0370485E-03 0.000000 0.000000 0.000000 + Av 2018 4 11 1 0 0.6281177 0.000000 3.2246555E-03 2.9727134E-03 0.000000 0.000000 0.000000 + Av 2018 4 11 2 0 0.6204895 0.000000 3.1770868E-03 2.9723030E-03 0.000000 0.000000 0.000000 + Av 2018 4 11 3 0 0.6166681 0.000000 3.1302196E-03 2.9718690E-03 0.000000 0.000000 0.000000 + Av 2018 4 11 4 0 0.6116146 0.000000 3.0840442E-03 2.9714119E-03 0.000000 0.000000 0.000000 + Av 2018 4 11 5 0 0.6070796 0.000000 3.0385496E-03 2.9709323E-03 0.000000 0.000000 0.000000 Av 2018 4 11 6 0 0.5849367 0.000000 2.9937262E-03 2.7154724E-03 0.000000 0.000000 1.1588988E-03 Av 2018 4 11 7 0 0.5394530 0.000000 2.9495638E-03 2.2845771E-03 0.000000 0.000000 3.1151315E-03 Av 2018 4 11 8 0 0.4901688 0.000000 2.9060531E-03 1.8536602E-03 0.000000 0.000000 5.0713639E-03 @@ -2442,17 +2442,17 @@ Av 2018 4 11 16 0 0.4421135 0.000000 2.5802960E-03 1.8485528E-03 0.000000 2.9999940E-02 5.0713639E-03 Av 2018 4 11 17 0 0.4827171 2.4290317E-05 2.5435961E-03 2.2829212E-03 0.000000 1.9999960E-02 3.1151315E-03 Av 2018 4 11 18 0 0.9775000 7.4746495E-04 2.7222957E-03 2.7427562E-03 5.5582453E-02 8.9999817E-02 1.1588988E-03 - Av 2018 4 11 19 0 1.155617 5.7316327E-04 2.9281401E-03 3.0425100E-03 3.3826008E-02 2.9999940E-02 0.000000 - Av 2018 4 11 20 0 0.7325097 0.000000 2.9169868E-03 3.0616447E-03 6.7566116E-03 0.000000 0.000000 - Av 2018 4 11 21 0 0.6148997 0.000000 2.8739565E-03 3.0610180E-03 2.0945414E-03 0.000000 0.000000 - Av 2018 4 11 22 0 0.6594780 5.4465730E-05 2.8346227E-03 3.0672604E-03 7.2718826E-03 9.9999802E-03 0.000000 - Av 2018 4 11 23 0 0.6422991 0.000000 2.7958541E-03 3.0740043E-03 2.4986272E-03 0.000000 0.000000 - Av 2018 4 11 24 0 0.6954790 4.9526298E-06 2.7668006E-03 3.0860091E-03 1.4969730E-02 1.9999960E-02 0.000000 - Av 2018 4 12 1 0 0.8506620 3.6149333E-05 2.7641151E-03 3.0502181E-03 2.7404986E-02 2.9999940E-02 0.000000 - Av 2018 4 12 2 0 0.7299386 9.8550963E-08 2.7492167E-03 3.0680622E-03 6.0328282E-03 0.000000 0.000000 - Av 2018 4 12 3 0 0.6407268 5.4124197E-05 2.7117124E-03 3.0746597E-03 8.8088615E-03 9.9999802E-03 0.000000 - Av 2018 4 12 4 0 0.6448221 0.000000 2.6747407E-03 3.0812968E-03 2.6834998E-03 0.000000 0.000000 - Av 2018 4 12 5 0 0.5805148 0.000000 2.6352841E-03 3.0805417E-03 1.0368592E-03 0.000000 0.000000 + Av 2018 4 11 19 0 1.155617 5.7316327E-04 2.9281401E-03 3.0425100E-03 3.3826008E-02 2.9999940E-02 0.000000 + Av 2018 4 11 20 0 0.7325097 0.000000 2.9169868E-03 3.0616447E-03 6.7566116E-03 0.000000 0.000000 + Av 2018 4 11 21 0 0.6148997 0.000000 2.8739565E-03 3.0610180E-03 2.0945414E-03 0.000000 0.000000 + Av 2018 4 11 22 0 0.6594780 5.4465730E-05 2.8346227E-03 3.0672604E-03 7.2718826E-03 9.9999802E-03 0.000000 + Av 2018 4 11 23 0 0.6422991 0.000000 2.7958541E-03 3.0740043E-03 2.4986272E-03 0.000000 0.000000 + Av 2018 4 11 24 0 0.6954790 4.9526298E-06 2.7668006E-03 3.0860091E-03 1.4969730E-02 1.9999960E-02 0.000000 + Av 2018 4 12 1 0 0.8506620 3.6149333E-05 2.7641151E-03 3.0502181E-03 2.7404986E-02 2.9999940E-02 0.000000 + Av 2018 4 12 2 0 0.7299386 9.8550963E-08 2.7492167E-03 3.0680622E-03 6.0328282E-03 0.000000 0.000000 + Av 2018 4 12 3 0 0.6407268 5.4124197E-05 2.7117124E-03 3.0746597E-03 8.8088615E-03 9.9999802E-03 0.000000 + Av 2018 4 12 4 0 0.6448221 0.000000 2.6747407E-03 3.0812968E-03 2.6834998E-03 0.000000 0.000000 + Av 2018 4 12 5 0 0.5805148 0.000000 2.6352841E-03 3.0805417E-03 1.0368592E-03 0.000000 0.000000 Av 2018 4 12 6 0 0.6653036 4.8796428E-06 2.6085044E-03 2.8677795E-03 1.4158284E-02 1.9999960E-02 1.0218808E-03 Av 2018 4 12 7 0 0.7195723 3.1523788E-05 2.5934542E-03 2.5299347E-03 1.8502083E-02 1.9999960E-02 2.6729484E-03 Av 2018 4 12 8 0 0.6873312 1.7556989E-04 2.5764226E-03 2.1910914E-03 1.7618056E-02 1.9999960E-02 4.3240162E-03 @@ -2466,17 +2466,17 @@ Av 2018 4 12 16 0 0.4691746 0.000000 2.3769210E-03 2.2588640E-03 6.2993198E-04 0.000000 4.3240162E-03 Av 2018 4 12 17 0 0.4945084 0.000000 2.3418579E-03 2.6210456E-03 3.2616395E-04 0.000000 2.6729484E-03 Av 2018 4 12 18 0 0.5276607 0.000000 2.3073119E-03 2.9832087E-03 1.8862879E-04 0.000000 1.0218808E-03 - Av 2018 4 12 19 0 0.5502657 0.000000 2.2732755E-03 3.2069329E-03 1.1833873E-04 0.000000 0.000000 - Av 2018 4 12 20 0 0.5523523 0.000000 2.2397412E-03 3.2058256E-03 7.8981073E-05 0.000000 0.000000 - Av 2018 4 12 21 0 0.5465236 0.000000 2.2067016E-03 3.2047010E-03 5.5325021E-05 0.000000 0.000000 - Av 2018 4 12 22 0 0.5436769 0.000000 2.1741493E-03 3.2035594E-03 4.0282102E-05 0.000000 0.000000 - Av 2018 4 12 23 0 0.5410490 0.000000 2.1420771E-03 3.2024009E-03 1.9211565E-04 0.000000 0.000000 - Av 2018 4 12 24 0 0.5372043 0.000000 2.1104780E-03 3.2012255E-03 0.000000 0.000000 0.000000 - Av 2018 4 13 1 0 0.5281906 0.000000 2.0793453E-03 3.1320064E-03 0.000000 0.000000 0.000000 - Av 2018 4 13 2 0 0.5223479 0.000000 2.0486715E-03 3.1309116E-03 0.000000 0.000000 0.000000 - Av 2018 4 13 3 0 0.5200922 0.000000 2.0184503E-03 3.1298012E-03 0.000000 0.000000 0.000000 - Av 2018 4 13 4 0 0.5181941 0.000000 1.9886750E-03 3.1286748E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 4 13 5 0 0.5869015 4.4926542E-06 1.9708751E-03 3.1405606E-03 9.6556414E-03 2.9999940E-02 0.000000 + Av 2018 4 12 19 0 0.5502657 0.000000 2.2732755E-03 3.2069329E-03 1.1833873E-04 0.000000 0.000000 + Av 2018 4 12 20 0 0.5523523 0.000000 2.2397412E-03 3.2058256E-03 7.8981073E-05 0.000000 0.000000 + Av 2018 4 12 21 0 0.5465236 0.000000 2.2067016E-03 3.2047010E-03 5.5325021E-05 0.000000 0.000000 + Av 2018 4 12 22 0 0.5436769 0.000000 2.1741493E-03 3.2035594E-03 4.0282102E-05 0.000000 0.000000 + Av 2018 4 12 23 0 0.5410490 0.000000 2.1420771E-03 3.2024009E-03 1.9211565E-04 0.000000 0.000000 + Av 2018 4 12 24 0 0.5372043 0.000000 2.1104780E-03 3.2012255E-03 0.000000 0.000000 0.000000 + Av 2018 4 13 1 0 0.5281906 0.000000 2.0793453E-03 3.1320064E-03 0.000000 0.000000 0.000000 + Av 2018 4 13 2 0 0.5223479 0.000000 2.0486715E-03 3.1309116E-03 0.000000 0.000000 0.000000 + Av 2018 4 13 3 0 0.5200922 0.000000 2.0184503E-03 3.1298012E-03 0.000000 0.000000 0.000000 + Av 2018 4 13 4 0 0.5181941 0.000000 1.9886750E-03 3.1286748E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 4 13 5 0 0.5869015 4.4926542E-06 1.9708751E-03 3.1405606E-03 9.6556414E-03 2.9999940E-02 0.000000 Av 2018 4 13 6 0 0.7929161 7.0959642E-05 2.0000995E-03 2.9160071E-03 3.4374025E-02 3.9999921E-02 1.1771264E-03 Av 2018 4 13 7 0 0.7132686 5.0101964E-05 2.0200105E-03 2.5437474E-03 1.3966158E-02 9.9999802E-03 3.0012098E-03 Av 2018 4 13 8 0 0.4668210 0.000000 1.9930264E-03 2.1487223E-03 3.5801935E-03 0.000000 4.8252931E-03 @@ -2490,17 +2490,17 @@ Av 2018 4 13 16 0 0.3851809 0.000000 1.7696157E-03 2.1383776E-03 3.9048573E-05 0.000000 4.8252931E-03 Av 2018 4 13 17 0 0.4230295 0.000000 1.7435111E-03 2.5383183E-03 1.8856462E-04 0.000000 3.0012098E-03 Av 2018 4 13 18 0 0.4608896 0.000000 1.7177915E-03 2.9382457E-03 0.000000 0.000000 1.1771264E-03 - Av 2018 4 13 19 0 0.4880579 0.000000 1.6924514E-03 3.1958288E-03 0.000000 0.000000 0.000000 - Av 2018 4 13 20 0 0.4927679 0.000000 1.6674851E-03 3.1944308E-03 0.000000 0.000000 0.000000 - Av 2018 4 13 21 0 0.4875717 0.000000 1.6428870E-03 3.1930197E-03 0.000000 0.000000 0.000000 - Av 2018 4 13 22 0 0.4858679 0.000000 1.6186519E-03 3.1915959E-03 0.000000 0.000000 0.000000 - Av 2018 4 13 23 0 0.4829970 0.000000 1.5947742E-03 3.1901593E-03 0.000000 0.000000 0.000000 - Av 2018 4 13 24 0 0.4805784 0.000000 1.5712488E-03 3.1887102E-03 0.000000 0.000000 0.000000 - Av 2018 4 14 1 0 0.4734475 0.000000 1.5480705E-03 3.1195330E-03 0.000000 0.000000 0.000000 - Av 2018 4 14 2 0 0.4680080 0.000000 1.5252340E-03 3.1181746E-03 0.000000 0.000000 0.000000 - Av 2018 4 14 3 0 0.4666337 0.000000 1.5027345E-03 3.1168042E-03 0.000000 0.000000 0.000000 - Av 2018 4 14 4 0 0.4638897 0.000000 1.4805667E-03 3.1154221E-03 0.000000 0.000000 0.000000 - Av 2018 4 14 5 0 0.4616650 0.000000 1.4587260E-03 3.1140284E-03 0.000000 0.000000 0.000000 + Av 2018 4 13 19 0 0.4880579 0.000000 1.6924514E-03 3.1958288E-03 0.000000 0.000000 0.000000 + Av 2018 4 13 20 0 0.4927679 0.000000 1.6674851E-03 3.1944308E-03 0.000000 0.000000 0.000000 + Av 2018 4 13 21 0 0.4875717 0.000000 1.6428870E-03 3.1930197E-03 0.000000 0.000000 0.000000 + Av 2018 4 13 22 0 0.4858679 0.000000 1.6186519E-03 3.1915959E-03 0.000000 0.000000 0.000000 + Av 2018 4 13 23 0 0.4829970 0.000000 1.5947742E-03 3.1901593E-03 0.000000 0.000000 0.000000 + Av 2018 4 13 24 0 0.4805784 0.000000 1.5712488E-03 3.1887102E-03 0.000000 0.000000 0.000000 + Av 2018 4 14 1 0 0.4734475 0.000000 1.5480705E-03 3.1195330E-03 0.000000 0.000000 0.000000 + Av 2018 4 14 2 0 0.4680080 0.000000 1.5252340E-03 3.1181746E-03 0.000000 0.000000 0.000000 + Av 2018 4 14 3 0 0.4666337 0.000000 1.5027345E-03 3.1168042E-03 0.000000 0.000000 0.000000 + Av 2018 4 14 4 0 0.4638897 0.000000 1.4805667E-03 3.1154221E-03 0.000000 0.000000 0.000000 + Av 2018 4 14 5 0 0.4616650 0.000000 1.4587260E-03 3.1140284E-03 0.000000 0.000000 0.000000 Av 2018 4 14 6 0 0.4378548 0.000000 1.4372076E-03 2.8000064E-03 0.000000 0.000000 1.4209845E-03 Av 2018 4 14 7 0 0.3896836 0.000000 1.4160065E-03 2.3331225E-03 0.000000 0.000000 3.5367443E-03 Av 2018 4 14 8 0 0.3396030 0.000000 1.3951182E-03 1.8662276E-03 0.000000 0.000000 5.6525040E-03 @@ -2514,17 +2514,17 @@ Av 2018 4 14 16 0 0.3030500 0.000000 1.2387309E-03 1.8544201E-03 0.000000 9.9999802E-03 5.6525040E-03 Av 2018 4 14 17 0 0.3513998 0.000000 1.2204576E-03 2.3183653E-03 0.000000 4.9999900E-02 3.5367443E-03 Av 2018 4 14 18 0 0.3944822 0.000000 1.2024539E-03 2.7823006E-03 0.000000 0.000000 1.4209845E-03 - Av 2018 4 14 19 0 0.4254336 0.000000 1.1847158E-03 3.0933758E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 4 14 20 0 0.4492216 1.4839016E-04 1.1756229E-03 3.1034350E-03 0.000000 2.9999940E-02 0.000000 - Av 2018 4 14 21 0 0.5951859 4.0596937E-05 1.2095019E-03 3.1357391E-03 2.0970618E-02 3.9999921E-02 0.000000 - Av 2018 4 14 22 0 0.9532751 4.1035688E-04 1.3342204E-03 3.1828003E-03 5.4179549E-02 5.9999879E-02 0.000000 - Av 2018 4 14 23 0 0.8235737 6.3399988E-05 1.4175248E-03 3.2169092E-03 1.7598687E-02 9.9999802E-03 0.000000 - Av 2018 4 14 24 0 1.080642 7.2524016E-04 1.6095286E-03 3.2499961E-03 7.8468390E-02 8.9999817E-02 0.000000 - Av 2018 4 15 1 0 1.111606 2.5539706E-04 1.8085556E-03 3.2207540E-03 2.8964067E-02 1.9999960E-02 0.000000 - Av 2018 4 15 2 0 0.5578740 0.000000 1.7962655E-03 3.2347345E-03 6.0523446E-03 0.000000 0.000000 - Av 2018 4 15 3 0 0.5420135 0.000000 1.7697677E-03 3.2334127E-03 1.9286339E-03 0.000000 0.000000 - Av 2018 4 15 4 0 0.5080956 0.000000 1.7436609E-03 3.2320768E-03 8.0127351E-04 0.000000 0.000000 - Av 2018 4 15 5 0 0.5057789 0.000000 1.7179392E-03 3.2307263E-03 3.9704761E-04 0.000000 0.000000 + Av 2018 4 14 19 0 0.4254336 0.000000 1.1847158E-03 3.0933758E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 4 14 20 0 0.4492216 1.4839016E-04 1.1756229E-03 3.1034350E-03 0.000000 2.9999940E-02 0.000000 + Av 2018 4 14 21 0 0.5951859 4.0596937E-05 1.2095019E-03 3.1357391E-03 2.0970618E-02 3.9999921E-02 0.000000 + Av 2018 4 14 22 0 0.9532751 4.1035688E-04 1.3342204E-03 3.1828003E-03 5.4179549E-02 5.9999879E-02 0.000000 + Av 2018 4 14 23 0 0.8235737 6.3399988E-05 1.4175248E-03 3.2169092E-03 1.7598687E-02 9.9999802E-03 0.000000 + Av 2018 4 14 24 0 1.080642 7.2524016E-04 1.6095286E-03 3.2499961E-03 7.8468390E-02 8.9999817E-02 0.000000 + Av 2018 4 15 1 0 1.111606 2.5539706E-04 1.8085556E-03 3.2207540E-03 2.8964067E-02 1.9999960E-02 0.000000 + Av 2018 4 15 2 0 0.5578740 0.000000 1.7962655E-03 3.2347345E-03 6.0523446E-03 0.000000 0.000000 + Av 2018 4 15 3 0 0.5420135 0.000000 1.7697677E-03 3.2334127E-03 1.9286339E-03 0.000000 0.000000 + Av 2018 4 15 4 0 0.5080956 0.000000 1.7436609E-03 3.2320768E-03 8.0127351E-04 0.000000 0.000000 + Av 2018 4 15 5 0 0.5057789 0.000000 1.7179392E-03 3.2307263E-03 3.9704761E-04 0.000000 0.000000 Av 2018 4 15 6 0 0.4792757 0.000000 1.6925968E-03 2.9420105E-03 2.2248636E-04 0.000000 1.3061421E-03 Av 2018 4 15 7 0 0.4351496 0.000000 1.6676283E-03 2.5288344E-03 1.3633331E-04 0.000000 3.1779485E-03 Av 2018 4 15 8 0 0.4119428 2.1511507E-05 1.6442467E-03 2.1204459E-03 2.9031695E-03 9.9999802E-03 5.0497553E-03 @@ -2538,17 +2538,17 @@ Av 2018 4 15 16 0 0.5110639 1.3672361E-05 1.8710373E-03 2.3857099E-03 6.8245200E-03 9.9999802E-03 5.0497553E-03 Av 2018 4 15 17 0 0.4890085 0.000000 1.8442096E-03 2.8000963E-03 2.1102685E-03 0.000000 3.1779485E-03 Av 2018 4 15 18 0 0.8025901 1.2907492E-04 1.9020216E-03 3.2361518E-03 4.0697463E-02 5.9999879E-02 1.3061421E-03 - Av 2018 4 15 19 0 1.845182 4.6032998E-03 2.2977516E-03 3.5769574E-03 0.1091890 0.1199998 0.000000 - Av 2018 4 15 20 0 1.368677 5.2399314E-06 2.6016675E-03 3.6072372E-03 1.5749102E-02 0.000000 0.000000 - Av 2018 4 15 21 0 0.4992279 0.000000 2.5635855E-03 3.6085467E-03 3.9070691E-03 0.000000 0.000000 - Av 2018 4 15 22 0 0.6984293 0.000000 2.5257687E-03 3.6072182E-03 1.3844543E-03 0.000000 0.000000 - Av 2018 4 15 23 0 0.6503260 5.5688357E-05 2.4916786E-03 3.6134114E-03 6.8980837E-03 9.9999802E-03 0.000000 - Av 2018 4 15 24 0 0.9607426 1.1368058E-04 2.5371513E-03 3.6457430E-03 4.1615285E-02 4.9999900E-02 0.000000 - Av 2018 4 16 1 0 1.665762 2.7555465E-03 2.8595454E-03 3.6185635E-03 9.2617497E-02 9.9999800E-02 0.000000 - Av 2018 4 16 2 0 2.586326 8.2948608E-03 3.4802326E-03 3.6742864E-03 0.1174530 0.1199998 0.000000 - Av 2018 4 16 3 0 2.387620 2.0420754E-03 4.1149631E-03 3.7307043E-03 0.1018835 9.9999800E-02 0.000000 - Av 2018 4 16 4 0 1.451042 7.2226621E-04 4.3987953E-03 3.7811033E-03 3.9216775E-02 2.9999940E-02 0.000000 - Av 2018 4 16 5 0 0.9819160 0.000000 4.3749050E-03 3.8033079E-03 7.5001377E-03 0.000000 0.000000 + Av 2018 4 15 19 0 1.845182 4.6032998E-03 2.2977516E-03 3.5769574E-03 0.1091890 0.1199998 0.000000 + Av 2018 4 15 20 0 1.368677 5.2399314E-06 2.6016675E-03 3.6072372E-03 1.5749102E-02 0.000000 0.000000 + Av 2018 4 15 21 0 0.4992279 0.000000 2.5635855E-03 3.6085467E-03 3.9070691E-03 0.000000 0.000000 + Av 2018 4 15 22 0 0.6984293 0.000000 2.5257687E-03 3.6072182E-03 1.3844543E-03 0.000000 0.000000 + Av 2018 4 15 23 0 0.6503260 5.5688357E-05 2.4916786E-03 3.6134114E-03 6.8980837E-03 9.9999802E-03 0.000000 + Av 2018 4 15 24 0 0.9607426 1.1368058E-04 2.5371513E-03 3.6457430E-03 4.1615285E-02 4.9999900E-02 0.000000 + Av 2018 4 16 1 0 1.665762 2.7555465E-03 2.8595454E-03 3.6185635E-03 9.2617497E-02 9.9999800E-02 0.000000 + Av 2018 4 16 2 0 2.586326 8.2948608E-03 3.4802326E-03 3.6742864E-03 0.1174530 0.1199998 0.000000 + Av 2018 4 16 3 0 2.387620 2.0420754E-03 4.1149631E-03 3.7307043E-03 0.1018835 9.9999800E-02 0.000000 + Av 2018 4 16 4 0 1.451042 7.2226621E-04 4.3987953E-03 3.7811033E-03 3.9216775E-02 2.9999940E-02 0.000000 + Av 2018 4 16 5 0 0.9819160 0.000000 4.3749050E-03 3.8033079E-03 7.5001377E-03 0.000000 0.000000 Av 2018 4 16 6 0 0.8678002 6.2050865E-05 4.3139099E-03 3.5407655E-03 9.2728827E-03 9.9999802E-03 1.2268154E-03 Av 2018 4 16 7 0 0.8236181 0.000000 4.2537972E-03 3.1756614E-03 2.7337326E-03 0.000000 2.9216520E-03 Av 2018 4 16 8 0 0.7178380 0.000000 4.1910466E-03 2.8022421E-03 1.0518691E-03 0.000000 4.6164887E-03 @@ -2562,17 +2562,17 @@ Av 2018 4 16 16 0 0.6519032 0.000000 3.7212474E-03 2.7963899E-03 1.8075565E-04 0.000000 4.6164887E-03 Av 2018 4 16 17 0 0.6804668 0.000000 3.6663532E-03 3.1683568E-03 0.000000 0.000000 2.9216520E-03 Av 2018 4 16 18 0 0.7130191 0.000000 3.6122685E-03 3.5402894E-03 0.000000 0.000000 1.2268154E-03 - Av 2018 4 16 19 0 0.7384597 0.000000 3.5589819E-03 3.8092230E-03 0.000000 0.000000 0.000000 - Av 2018 4 16 20 0 0.7408507 0.000000 3.5064814E-03 3.8082239E-03 0.000000 0.000000 0.000000 - Av 2018 4 16 21 0 0.7327996 0.000000 3.4547553E-03 3.8071920E-03 0.000000 0.000000 0.000000 - Av 2018 4 16 22 0 0.7284796 0.000000 3.4037922E-03 3.8061279E-03 0.000000 0.000000 0.000000 - Av 2018 4 16 23 0 0.7229607 0.000000 3.3535808E-03 3.8050322E-03 0.000000 0.000000 0.000000 - Av 2018 4 16 24 0 0.7179558 0.000000 3.3041104E-03 3.8039051E-03 0.000000 0.000000 0.000000 - Av 2018 4 17 1 0 0.7071884 0.000000 3.2553694E-03 3.7191566E-03 0.000000 0.000000 0.000000 - Av 2018 4 17 2 0 0.6985290 0.000000 3.2073476E-03 3.7181161E-03 0.000000 0.000000 0.000000 - Av 2018 4 17 3 0 0.6949191 0.000000 3.1600343E-03 3.7170465E-03 0.000000 0.000000 0.000000 - Av 2018 4 17 4 0 0.6896451 0.000000 3.1134191E-03 3.7159480E-03 0.000000 0.000000 0.000000 - Av 2018 4 17 5 0 0.6850399 0.000000 3.0674911E-03 3.7148211E-03 0.000000 0.000000 0.000000 + Av 2018 4 16 19 0 0.7384597 0.000000 3.5589819E-03 3.8092230E-03 0.000000 0.000000 0.000000 + Av 2018 4 16 20 0 0.7408507 0.000000 3.5064814E-03 3.8082239E-03 0.000000 0.000000 0.000000 + Av 2018 4 16 21 0 0.7327996 0.000000 3.4547553E-03 3.8071920E-03 0.000000 0.000000 0.000000 + Av 2018 4 16 22 0 0.7284796 0.000000 3.4037922E-03 3.8061279E-03 0.000000 0.000000 0.000000 + Av 2018 4 16 23 0 0.7229607 0.000000 3.3535808E-03 3.8050322E-03 0.000000 0.000000 0.000000 + Av 2018 4 16 24 0 0.7179558 0.000000 3.3041104E-03 3.8039051E-03 0.000000 0.000000 0.000000 + Av 2018 4 17 1 0 0.7071884 0.000000 3.2553694E-03 3.7191566E-03 0.000000 0.000000 0.000000 + Av 2018 4 17 2 0 0.6985290 0.000000 3.2073476E-03 3.7181161E-03 0.000000 0.000000 0.000000 + Av 2018 4 17 3 0 0.6949191 0.000000 3.1600343E-03 3.7170465E-03 0.000000 0.000000 0.000000 + Av 2018 4 17 4 0 0.6896451 0.000000 3.1134191E-03 3.7159480E-03 0.000000 0.000000 0.000000 + Av 2018 4 17 5 0 0.6850399 0.000000 3.0674911E-03 3.7148211E-03 0.000000 0.000000 0.000000 Av 2018 4 17 6 0 0.6601341 0.000000 3.0222407E-03 3.4204763E-03 0.000000 0.000000 1.3326820E-03 Av 2018 4 17 7 0 0.6155093 0.000000 2.9776581E-03 3.0282622E-03 0.000000 0.000000 3.1101031E-03 Av 2018 4 17 8 0 0.5711406 0.000000 2.9337329E-03 2.6360205E-03 0.000000 0.000000 4.8875241E-03 @@ -2586,17 +2586,17 @@ Av 2018 4 17 16 0 0.5191350 0.000000 2.6048734E-03 2.6254356E-03 0.000000 0.000000 4.8875241E-03 Av 2018 4 17 17 0 0.5528580 0.000000 2.5664475E-03 3.0150372E-03 0.000000 0.000000 3.1101031E-03 Av 2018 4 17 18 0 0.5894190 0.000000 2.5285883E-03 3.4046154E-03 0.000000 0.000000 1.3326820E-03 - Av 2018 4 17 19 0 0.6183777 0.000000 2.4912877E-03 3.6963290E-03 0.000000 0.000000 0.000000 - Av 2018 4 17 20 0 0.6232120 0.000000 2.4545374E-03 3.6948305E-03 0.000000 0.000000 0.000000 - Av 2018 4 17 21 0 0.6163689 0.000000 2.4183290E-03 3.6933103E-03 0.000000 0.000000 0.000000 - Av 2018 4 17 22 0 0.6136563 0.000000 2.3826549E-03 3.6917687E-03 0.000000 0.000000 0.000000 - Av 2018 4 17 23 0 0.6095766 0.000000 2.3475073E-03 3.6902064E-03 0.000000 0.000000 0.000000 - Av 2018 4 17 24 0 0.6060405 0.000000 2.3128777E-03 3.6886232E-03 0.000000 0.000000 0.000000 - Av 2018 4 18 1 0 0.5969040 0.000000 2.2787589E-03 3.6063881E-03 0.000000 0.000000 0.000000 - Av 2018 4 18 2 0 0.5897909 0.000000 2.2451438E-03 3.6049099E-03 0.000000 0.000000 0.000000 - Av 2018 4 18 3 0 0.5875278 0.000000 2.2120243E-03 3.6034123E-03 0.000000 0.000000 0.000000 - Av 2018 4 18 4 0 0.5836425 0.000000 2.1793935E-03 3.6018952E-03 0.000000 0.000000 0.000000 - Av 2018 4 18 5 0 0.5803845 0.000000 2.1472441E-03 3.6003592E-03 0.000000 0.000000 0.000000 + Av 2018 4 17 19 0 0.6183777 0.000000 2.4912877E-03 3.6963290E-03 0.000000 0.000000 0.000000 + Av 2018 4 17 20 0 0.6232120 0.000000 2.4545374E-03 3.6948305E-03 0.000000 0.000000 0.000000 + Av 2018 4 17 21 0 0.6163689 0.000000 2.4183290E-03 3.6933103E-03 0.000000 0.000000 0.000000 + Av 2018 4 17 22 0 0.6136563 0.000000 2.3826549E-03 3.6917687E-03 0.000000 0.000000 0.000000 + Av 2018 4 17 23 0 0.6095766 0.000000 2.3475073E-03 3.6902064E-03 0.000000 0.000000 0.000000 + Av 2018 4 17 24 0 0.6060405 0.000000 2.3128777E-03 3.6886232E-03 0.000000 0.000000 0.000000 + Av 2018 4 18 1 0 0.5969040 0.000000 2.2787589E-03 3.6063881E-03 0.000000 0.000000 0.000000 + Av 2018 4 18 2 0 0.5897909 0.000000 2.2451438E-03 3.6049099E-03 0.000000 0.000000 0.000000 + Av 2018 4 18 3 0 0.5875278 0.000000 2.2120243E-03 3.6034123E-03 0.000000 0.000000 0.000000 + Av 2018 4 18 4 0 0.5836425 0.000000 2.1793935E-03 3.6018952E-03 0.000000 0.000000 0.000000 + Av 2018 4 18 5 0 0.5803845 0.000000 2.1472441E-03 3.6003592E-03 0.000000 0.000000 0.000000 Av 2018 4 18 6 0 0.5541455 0.000000 2.1155688E-03 3.2664936E-03 0.000000 0.000000 1.5105046E-03 Av 2018 4 18 7 0 0.5065528 0.000000 2.0843609E-03 2.8364523E-03 0.000000 0.000000 3.4580869E-03 Av 2018 4 18 8 0 0.4598923 0.000000 2.0536133E-03 2.4063932E-03 0.000000 0.000000 5.4056691E-03 @@ -2610,17 +2610,17 @@ Av 2018 4 18 16 0 0.4160500 0.000000 1.8234113E-03 2.3930429E-03 0.000000 0.000000 5.4056691E-03 Av 2018 4 18 17 0 0.4542471 0.000000 1.7965132E-03 2.8197686E-03 0.000000 0.000000 3.4580869E-03 Av 2018 4 18 18 0 0.4958336 0.000000 1.7700117E-03 3.2464787E-03 0.000000 0.000000 1.5105046E-03 - Av 2018 4 18 19 0 0.5297381 0.000000 1.7439013E-03 3.5770163E-03 0.000000 0.000000 0.000000 - Av 2018 4 18 20 0 0.5369877 0.000000 1.7181761E-03 3.5752279E-03 0.000000 0.000000 0.000000 - Av 2018 4 18 21 0 0.5307529 0.000000 1.6928302E-03 3.5734246E-03 0.000000 0.000000 0.000000 - Av 2018 4 18 22 0 0.5292560 0.000000 1.6678583E-03 3.5716067E-03 0.000000 0.000000 0.000000 - Av 2018 4 18 23 0 0.5261601 0.000000 1.6432548E-03 3.5697741E-03 0.000000 0.000000 0.000000 - Av 2018 4 18 24 0 0.5236679 0.000000 1.6190142E-03 3.5679275E-03 0.000000 0.000000 0.000000 - Av 2018 4 19 1 0 0.5157444 0.000000 1.5951312E-03 3.4885271E-03 0.000000 0.000000 0.000000 - Av 2018 4 19 2 0 0.5097655 0.000000 1.5716006E-03 3.4867940E-03 0.000000 0.000000 0.000000 - Av 2018 4 19 3 0 0.5084341 0.000000 1.5484169E-03 3.4850473E-03 0.000000 0.000000 0.000000 - Av 2018 4 19 4 0 0.5055315 0.000000 1.5255754E-03 3.4832871E-03 0.000000 0.000000 0.000000 - Av 2018 4 19 5 0 0.5032197 0.000000 1.5030708E-03 3.4815136E-03 0.000000 0.000000 0.000000 + Av 2018 4 18 19 0 0.5297381 0.000000 1.7439013E-03 3.5770163E-03 0.000000 0.000000 0.000000 + Av 2018 4 18 20 0 0.5369877 0.000000 1.7181761E-03 3.5752279E-03 0.000000 0.000000 0.000000 + Av 2018 4 18 21 0 0.5307529 0.000000 1.6928302E-03 3.5734246E-03 0.000000 0.000000 0.000000 + Av 2018 4 18 22 0 0.5292560 0.000000 1.6678583E-03 3.5716067E-03 0.000000 0.000000 0.000000 + Av 2018 4 18 23 0 0.5261601 0.000000 1.6432548E-03 3.5697741E-03 0.000000 0.000000 0.000000 + Av 2018 4 18 24 0 0.5236679 0.000000 1.6190142E-03 3.5679275E-03 0.000000 0.000000 0.000000 + Av 2018 4 19 1 0 0.5157444 0.000000 1.5951312E-03 3.4885271E-03 0.000000 0.000000 0.000000 + Av 2018 4 19 2 0 0.5097655 0.000000 1.5716006E-03 3.4867940E-03 0.000000 0.000000 0.000000 + Av 2018 4 19 3 0 0.5084341 0.000000 1.5484169E-03 3.4850473E-03 0.000000 0.000000 0.000000 + Av 2018 4 19 4 0 0.5055315 0.000000 1.5255754E-03 3.4832871E-03 0.000000 0.000000 0.000000 + Av 2018 4 19 5 0 0.5032197 0.000000 1.5030708E-03 3.4815136E-03 0.000000 0.000000 0.000000 Av 2018 4 19 6 0 0.4756335 0.000000 1.4808981E-03 3.1138458E-03 0.000000 0.000000 1.6630981E-03 Av 2018 4 19 7 0 0.4255666 0.000000 1.4590524E-03 2.6553993E-03 0.000000 0.000000 3.7387684E-03 Av 2018 4 19 8 0 0.3771915 0.000000 1.4375291E-03 2.1969397E-03 0.000000 0.000000 5.8144387E-03 @@ -2634,17 +2634,17 @@ Av 2018 4 19 16 0 0.3390864 0.000000 1.2763877E-03 2.1819649E-03 0.000000 0.000000 5.8144387E-03 Av 2018 4 19 17 0 0.3804698 0.000000 1.2575591E-03 2.6365989E-03 0.000000 0.000000 3.7387684E-03 Av 2018 4 19 18 0 0.4257979 0.000000 1.2390080E-03 3.0911830E-03 0.000000 0.000000 1.6630981E-03 - Av 2018 4 19 19 0 0.4636180 0.000000 1.2207307E-03 3.4549700E-03 0.000000 0.000000 0.000000 - Av 2018 4 19 20 0 0.4728032 0.000000 1.2027230E-03 3.4528596E-03 0.000000 0.000000 0.000000 - Av 2018 4 19 21 0 0.4668931 0.000000 1.1849809E-03 3.4507406E-03 0.000000 0.000000 0.000000 - Av 2018 4 19 22 0 0.4662664 0.000000 1.1675006E-03 3.4486135E-03 0.000000 0.000000 0.000000 - Av 2018 4 19 23 0 0.4638368 0.000000 1.1502781E-03 3.4464779E-03 0.000000 0.000000 0.000000 - Av 2018 4 19 24 0 0.4620678 0.000000 1.1333097E-03 3.4443345E-03 0.000000 0.000000 0.000000 - Av 2018 4 20 1 0 0.4550488 0.000000 1.1165916E-03 3.3678061E-03 0.000000 0.000000 0.000000 - Av 2018 4 20 2 0 0.4498973 0.000000 1.1001203E-03 3.3657844E-03 0.000000 0.000000 0.000000 - Av 2018 4 20 3 0 0.4491915 0.000000 1.0838917E-03 3.3637548E-03 0.000000 0.000000 0.000000 - Av 2018 4 20 4 0 0.4469716 0.000000 1.0679027E-03 3.3617178E-03 0.000000 0.000000 0.000000 - Av 2018 4 20 5 0 0.4453094 0.000000 1.0521495E-03 3.3596728E-03 0.000000 0.000000 0.000000 + Av 2018 4 19 19 0 0.4636180 0.000000 1.2207307E-03 3.4549700E-03 0.000000 0.000000 0.000000 + Av 2018 4 19 20 0 0.4728032 0.000000 1.2027230E-03 3.4528596E-03 0.000000 0.000000 0.000000 + Av 2018 4 19 21 0 0.4668931 0.000000 1.1849809E-03 3.4507406E-03 0.000000 0.000000 0.000000 + Av 2018 4 19 22 0 0.4662664 0.000000 1.1675006E-03 3.4486135E-03 0.000000 0.000000 0.000000 + Av 2018 4 19 23 0 0.4638368 0.000000 1.1502781E-03 3.4464779E-03 0.000000 0.000000 0.000000 + Av 2018 4 19 24 0 0.4620678 0.000000 1.1333097E-03 3.4443345E-03 0.000000 0.000000 0.000000 + Av 2018 4 20 1 0 0.4550488 0.000000 1.1165916E-03 3.3678061E-03 0.000000 0.000000 0.000000 + Av 2018 4 20 2 0 0.4498973 0.000000 1.1001203E-03 3.3657844E-03 0.000000 0.000000 0.000000 + Av 2018 4 20 3 0 0.4491915 0.000000 1.0838917E-03 3.3637548E-03 0.000000 0.000000 0.000000 + Av 2018 4 20 4 0 0.4469716 0.000000 1.0679027E-03 3.3617178E-03 0.000000 0.000000 0.000000 + Av 2018 4 20 5 0 0.4453094 0.000000 1.0521495E-03 3.3596728E-03 0.000000 0.000000 0.000000 Av 2018 4 20 6 0 0.4170872 0.000000 1.0366286E-03 2.9727991E-03 0.000000 0.000000 1.7491872E-03 Av 2018 4 20 7 0 0.3662363 0.000000 1.0213366E-03 2.5052654E-03 0.000000 0.000000 3.8649472E-03 Av 2018 4 20 8 0 0.3178191 0.000000 1.0062704E-03 2.0377042E-03 0.000000 0.000000 5.9807072E-03 @@ -2658,17 +2658,17 @@ Av 2018 4 20 16 0 0.2840283 0.000000 8.9347159E-04 2.0191341E-03 0.000000 0.000000 5.9807072E-03 Av 2018 4 20 17 0 0.3264695 0.000000 8.8029151E-04 2.4820669E-03 0.000000 0.000000 3.8649472E-03 Av 2018 4 20 18 0 0.3732801 0.000000 8.6730585E-04 2.9449705E-03 0.000000 0.000000 1.7491872E-03 - Av 2018 4 20 19 0 0.4131310 0.000000 8.5451169E-04 3.3272104E-03 0.000000 0.000000 0.000000 - Av 2018 4 20 20 0 0.4235666 0.000000 8.4190635E-04 3.3246228E-03 0.000000 0.000000 0.000000 - Av 2018 4 20 21 0 0.4178860 0.000000 8.2948687E-04 3.3220337E-03 0.000000 0.000000 0.000000 - Av 2018 4 20 22 0 0.4178340 0.000000 8.1725064E-04 3.3194427E-03 0.000000 0.000000 0.000000 - Av 2018 4 20 23 0 0.4158494 0.000000 8.0519490E-04 3.3168504E-03 0.000000 0.000000 0.000000 - Av 2018 4 20 24 0 0.4145609 0.000000 7.9331698E-04 3.3142564E-03 0.000000 0.000000 0.000000 - Av 2018 4 21 1 0 0.4082268 0.000000 7.8161433E-04 3.2406126E-03 0.000000 0.000000 0.000000 - Av 2018 4 21 2 0 0.4036798 0.000000 7.7008427E-04 3.2381511E-03 0.000000 0.000000 0.000000 - Av 2018 4 21 3 0 0.4033710 0.000000 7.5872435E-04 3.2356880E-03 0.000000 0.000000 0.000000 - Av 2018 4 21 4 0 0.4016113 0.000000 7.4753194E-04 3.2332232E-03 0.000000 0.000000 0.000000 - Av 2018 4 21 5 0 0.4003785 0.000000 7.3650468E-04 3.2307571E-03 0.000000 0.000000 0.000000 + Av 2018 4 20 19 0 0.4131310 0.000000 8.5451169E-04 3.3272104E-03 0.000000 0.000000 0.000000 + Av 2018 4 20 20 0 0.4235666 0.000000 8.4190635E-04 3.3246228E-03 0.000000 0.000000 0.000000 + Av 2018 4 20 21 0 0.4178860 0.000000 8.2948687E-04 3.3220337E-03 0.000000 0.000000 0.000000 + Av 2018 4 20 22 0 0.4178340 0.000000 8.1725064E-04 3.3194427E-03 0.000000 0.000000 0.000000 + Av 2018 4 20 23 0 0.4158494 0.000000 8.0519490E-04 3.3168504E-03 0.000000 0.000000 0.000000 + Av 2018 4 20 24 0 0.4145609 0.000000 7.9331698E-04 3.3142564E-03 0.000000 0.000000 0.000000 + Av 2018 4 21 1 0 0.4082268 0.000000 7.8161433E-04 3.2406126E-03 0.000000 0.000000 0.000000 + Av 2018 4 21 2 0 0.4036798 0.000000 7.7008427E-04 3.2381511E-03 0.000000 0.000000 0.000000 + Av 2018 4 21 3 0 0.4033710 0.000000 7.5872435E-04 3.2356880E-03 0.000000 0.000000 0.000000 + Av 2018 4 21 4 0 0.4016113 0.000000 7.4753194E-04 3.2332232E-03 0.000000 0.000000 0.000000 + Av 2018 4 21 5 0 0.4003785 0.000000 7.3650468E-04 3.2307571E-03 0.000000 0.000000 0.000000 Av 2018 4 21 6 0 0.3734251 0.000000 7.2564004E-04 2.8554939E-03 0.000000 0.000000 1.6945243E-03 Av 2018 4 21 7 0 0.3254744 0.000000 7.1493571E-04 2.4155169E-03 0.000000 0.000000 3.6831801E-03 Av 2018 4 21 8 0 0.2804731 0.000000 7.0438930E-04 1.9755249E-03 0.000000 0.000000 5.6718360E-03 @@ -2682,17 +2682,17 @@ Av 2018 4 21 16 0 0.2512416 0.000000 6.2543008E-04 1.9546016E-03 0.000000 0.000000 5.6718360E-03 Av 2018 4 21 17 0 0.2911510 0.000000 6.1620399E-04 2.3893719E-03 0.000000 0.000000 3.6831801E-03 Av 2018 4 21 18 0 0.3354953 0.000000 6.0711399E-04 2.8241258E-03 0.000000 0.000000 1.6945243E-03 - Av 2018 4 21 19 0 0.3739408 0.000000 5.9815811E-04 3.1941626E-03 0.000000 0.000000 0.000000 - Av 2018 4 21 20 0 0.3845233 0.000000 5.8933435E-04 3.1914019E-03 0.000000 0.000000 0.000000 - Av 2018 4 21 21 0 0.3792784 0.000000 5.8064074E-04 3.1886424E-03 0.000000 0.000000 0.000000 - Av 2018 4 21 22 0 0.3795546 0.000000 5.7207537E-04 3.1858841E-03 0.000000 0.000000 0.000000 - Av 2018 4 21 23 0 0.3779284 0.000000 5.6363636E-04 3.1831267E-03 0.000000 0.000000 0.000000 - Av 2018 4 21 24 0 0.3769809 0.000000 5.5532181E-04 3.1803704E-03 0.000000 0.000000 0.000000 - Av 2018 4 22 1 0 0.3712188 0.000000 5.4712995E-04 3.1099780E-03 0.000000 0.000000 0.000000 - Av 2018 4 22 2 0 0.3671563 0.000000 5.3905894E-04 3.1073536E-03 0.000000 0.000000 0.000000 - Av 2018 4 22 3 0 0.3671237 0.000000 5.3110695E-04 3.1047300E-03 0.000000 0.000000 0.000000 - Av 2018 4 22 4 0 0.3657060 0.000000 5.2327226E-04 3.1021077E-03 0.000000 0.000000 0.000000 - Av 2018 4 22 5 0 0.3647858 0.000000 5.1555317E-04 3.0994860E-03 0.000000 0.000000 0.000000 + Av 2018 4 21 19 0 0.3739408 0.000000 5.9815811E-04 3.1941626E-03 0.000000 0.000000 0.000000 + Av 2018 4 21 20 0 0.3845233 0.000000 5.8933435E-04 3.1914019E-03 0.000000 0.000000 0.000000 + Av 2018 4 21 21 0 0.3792784 0.000000 5.8064074E-04 3.1886424E-03 0.000000 0.000000 0.000000 + Av 2018 4 21 22 0 0.3795546 0.000000 5.7207537E-04 3.1858841E-03 0.000000 0.000000 0.000000 + Av 2018 4 21 23 0 0.3779284 0.000000 5.6363636E-04 3.1831267E-03 0.000000 0.000000 0.000000 + Av 2018 4 21 24 0 0.3769809 0.000000 5.5532181E-04 3.1803704E-03 0.000000 0.000000 0.000000 + Av 2018 4 22 1 0 0.3712188 0.000000 5.4712995E-04 3.1099780E-03 0.000000 0.000000 0.000000 + Av 2018 4 22 2 0 0.3671563 0.000000 5.3905894E-04 3.1073536E-03 0.000000 0.000000 0.000000 + Av 2018 4 22 3 0 0.3671237 0.000000 5.3110695E-04 3.1047300E-03 0.000000 0.000000 0.000000 + Av 2018 4 22 4 0 0.3657060 0.000000 5.2327226E-04 3.1021077E-03 0.000000 0.000000 0.000000 + Av 2018 4 22 5 0 0.3647858 0.000000 5.1555317E-04 3.0994860E-03 0.000000 0.000000 0.000000 Av 2018 4 22 6 0 0.3367916 0.000000 5.0794799E-04 2.7041114E-03 0.000000 0.000000 1.7852454E-03 Av 2018 4 22 7 0 0.2875834 0.000000 5.0045492E-04 2.2537976E-03 0.000000 0.000000 3.8202051E-03 Av 2018 4 22 8 0 0.2420726 0.000000 4.9307244E-04 1.8034759E-03 0.000000 0.000000 5.8551650E-03 @@ -2706,17 +2706,17 @@ Av 2018 4 22 16 0 0.2148775 0.000000 4.3780092E-04 1.7818268E-03 0.000000 0.000000 5.8551650E-03 Av 2018 4 22 17 0 0.2557420 0.000000 4.3134266E-04 2.2267427E-03 0.000000 0.000000 3.8202051E-03 Av 2018 4 22 18 0 0.3014780 0.000000 4.2497969E-04 2.6716497E-03 0.000000 0.000000 1.7852454E-03 - Av 2018 4 22 19 0 0.3418370 0.000000 4.1871058E-04 3.0616156E-03 0.000000 0.000000 0.000000 - Av 2018 4 22 20 0 0.3534676 0.000000 4.1253393E-04 3.0588277E-03 0.000000 0.000000 0.000000 - Av 2018 4 22 21 0 0.3482117 0.000000 4.0644841E-04 3.0560419E-03 0.000000 0.000000 0.000000 - Av 2018 4 22 22 0 0.3488400 0.000000 4.0045267E-04 3.0532584E-03 0.000000 0.000000 0.000000 - Av 2018 4 22 23 0 0.3474347 0.000000 3.9454538E-04 3.0504770E-03 0.000000 0.000000 0.000000 - Av 2018 4 22 24 0 0.3467487 0.000000 3.8872522E-04 3.0476975E-03 0.000000 0.000000 0.000000 - Av 2018 4 23 1 0 0.3414580 0.000000 3.8299093E-04 2.9806523E-03 0.000000 0.000000 0.000000 - Av 2018 4 23 2 0 0.3377886 0.000000 3.7734117E-04 2.9780001E-03 0.000000 0.000000 0.000000 - Av 2018 4 23 3 0 0.3379421 0.000000 3.7177483E-04 2.9753498E-03 0.000000 0.000000 0.000000 - Av 2018 4 23 4 0 0.3367779 0.000000 3.6629057E-04 2.9727013E-03 0.000000 0.000000 0.000000 - Av 2018 4 23 5 0 0.3360832 0.000000 3.6088721E-04 2.9700550E-03 0.000000 0.000000 0.000000 + Av 2018 4 22 19 0 0.3418370 0.000000 4.1871058E-04 3.0616156E-03 0.000000 0.000000 0.000000 + Av 2018 4 22 20 0 0.3534676 0.000000 4.1253393E-04 3.0588277E-03 0.000000 0.000000 0.000000 + Av 2018 4 22 21 0 0.3482117 0.000000 4.0644841E-04 3.0560419E-03 0.000000 0.000000 0.000000 + Av 2018 4 22 22 0 0.3488400 0.000000 4.0045267E-04 3.0532584E-03 0.000000 0.000000 0.000000 + Av 2018 4 22 23 0 0.3474347 0.000000 3.9454538E-04 3.0504770E-03 0.000000 0.000000 0.000000 + Av 2018 4 22 24 0 0.3467487 0.000000 3.8872522E-04 3.0476975E-03 0.000000 0.000000 0.000000 + Av 2018 4 23 1 0 0.3414580 0.000000 3.8299093E-04 2.9806523E-03 0.000000 0.000000 0.000000 + Av 2018 4 23 2 0 0.3377886 0.000000 3.7734117E-04 2.9780001E-03 0.000000 0.000000 0.000000 + Av 2018 4 23 3 0 0.3379421 0.000000 3.7177483E-04 2.9753498E-03 0.000000 0.000000 0.000000 + Av 2018 4 23 4 0 0.3367779 0.000000 3.6629057E-04 2.9727013E-03 0.000000 0.000000 0.000000 + Av 2018 4 23 5 0 0.3360832 0.000000 3.6088721E-04 2.9700550E-03 0.000000 0.000000 0.000000 Av 2018 4 23 6 0 0.3034107 0.000000 3.5556353E-04 2.5028693E-03 0.000000 0.000000 2.1115497E-03 Av 2018 4 23 7 0 0.2466527 0.000000 3.5031841E-04 1.9853907E-03 0.000000 0.000000 4.4517042E-03 Av 2018 4 23 8 0 0.1949354 0.000000 3.4515065E-04 1.4679077E-03 0.000000 0.000000 6.7918589E-03 @@ -2730,17 +2730,17 @@ Av 2018 4 23 16 0 0.1667328 0.000000 3.0646066E-04 1.4463448E-03 0.000000 0.000000 6.7918589E-03 Av 2018 4 23 17 0 0.2137252 0.000000 3.0193987E-04 1.9584438E-03 0.000000 0.000000 4.4517042E-03 Av 2018 4 23 18 0 0.2667015 0.000000 2.9748576E-04 2.4705385E-03 0.000000 0.000000 2.1115497E-03 - Av 2018 4 23 19 0 0.3142637 0.000000 2.9309740E-04 2.9323390E-03 0.000000 0.000000 0.000000 - Av 2018 4 23 20 0 0.3285477 0.000000 2.8877376E-04 2.9295997E-03 0.000000 0.000000 0.000000 - Av 2018 4 23 21 0 0.3226258 0.000000 2.8451392E-04 2.9268630E-03 0.000000 0.000000 0.000000 - Av 2018 4 23 22 0 0.3237385 0.000000 2.8031689E-04 2.9241284E-03 0.000000 0.000000 0.000000 - Av 2018 4 23 23 0 0.3224141 0.000000 2.7618179E-04 2.9213966E-03 0.000000 0.000000 0.000000 - Av 2018 4 23 24 0 0.3219458 0.000000 2.7210766E-04 2.9186674E-03 0.000000 0.000000 0.000000 - Av 2018 4 24 1 0 0.3170436 0.000000 2.6809363E-04 2.8549382E-03 0.000000 0.000000 0.000000 - Av 2018 4 24 2 0 0.3136994 0.000000 2.6413883E-04 2.8523291E-03 0.000000 0.000000 0.000000 - Av 2018 4 24 3 0 0.3139744 0.000000 2.6024238E-04 2.8497225E-03 0.000000 0.000000 0.000000 - Av 2018 4 24 4 0 0.3129991 0.000000 2.5640338E-04 2.8471183E-03 0.000000 0.000000 0.000000 - Av 2018 4 24 5 0 0.3124667 0.000000 2.5262102E-04 2.8445164E-03 0.000000 0.000000 0.000000 + Av 2018 4 23 19 0 0.3142637 0.000000 2.9309740E-04 2.9323390E-03 0.000000 0.000000 0.000000 + Av 2018 4 23 20 0 0.3285477 0.000000 2.8877376E-04 2.9295997E-03 0.000000 0.000000 0.000000 + Av 2018 4 23 21 0 0.3226258 0.000000 2.8451392E-04 2.9268630E-03 0.000000 0.000000 0.000000 + Av 2018 4 23 22 0 0.3237385 0.000000 2.8031689E-04 2.9241284E-03 0.000000 0.000000 0.000000 + Av 2018 4 23 23 0 0.3224141 0.000000 2.7618179E-04 2.9213966E-03 0.000000 0.000000 0.000000 + Av 2018 4 23 24 0 0.3219458 0.000000 2.7210766E-04 2.9186674E-03 0.000000 0.000000 0.000000 + Av 2018 4 24 1 0 0.3170436 0.000000 2.6809363E-04 2.8549382E-03 0.000000 0.000000 0.000000 + Av 2018 4 24 2 0 0.3136994 0.000000 2.6413883E-04 2.8523291E-03 0.000000 0.000000 0.000000 + Av 2018 4 24 3 0 0.3139744 0.000000 2.6024238E-04 2.8497225E-03 0.000000 0.000000 0.000000 + Av 2018 4 24 4 0 0.3129991 0.000000 2.5640338E-04 2.8471183E-03 0.000000 0.000000 0.000000 + Av 2018 4 24 5 0 0.3124667 0.000000 2.5262102E-04 2.8445164E-03 0.000000 0.000000 0.000000 Av 2018 4 24 6 0 0.2724175 0.000000 2.4889444E-04 2.2670762E-03 0.000000 0.000000 2.6129112E-03 Av 2018 4 24 7 0 0.2037413 0.000000 2.4522288E-04 1.6444768E-03 0.000000 0.000000 5.4310965E-03 Av 2018 4 24 8 0 0.1420923 0.000000 2.4160545E-04 1.0218753E-03 0.000000 0.000000 8.2492828E-03 @@ -2754,17 +2754,17 @@ Av 2018 4 24 16 0 0.1109215 0.000000 2.1452246E-04 1.0008952E-03 0.000000 0.000000 8.2492828E-03 Av 2018 4 24 17 0 0.1673711 0.000000 2.1135791E-04 1.6182580E-03 0.000000 0.000000 5.4310965E-03 Av 2018 4 24 18 0 0.2314837 0.000000 2.0824005E-04 2.2356200E-03 0.000000 0.000000 2.6129112E-03 - Av 2018 4 24 19 0 0.2900206 0.000000 2.0516818E-04 2.8078228E-03 0.000000 0.000000 0.000000 - Av 2018 4 24 20 0 0.3082035 0.000000 2.0214161E-04 2.8051869E-03 0.000000 0.000000 0.000000 - Av 2018 4 24 21 0 0.3011149 0.000000 1.9915971E-04 2.8025536E-03 0.000000 0.000000 0.000000 - Av 2018 4 24 22 0 0.3028198 0.000000 1.9622179E-04 2.7999228E-03 0.000000 0.000000 0.000000 - Av 2018 4 24 23 0 0.3014733 0.000000 1.9332720E-04 2.7972944E-03 0.000000 0.000000 0.000000 - Av 2018 4 24 24 0 0.3011941 0.000000 1.9047532E-04 2.7946683E-03 0.000000 0.000000 0.000000 - Av 2018 4 25 1 0 0.2966176 0.000000 1.8766552E-04 2.7341705E-03 0.000000 0.000000 0.000000 - Av 2018 4 25 2 0 0.2935486 0.000000 1.8489716E-04 2.7316578E-03 0.000000 0.000000 0.000000 - Av 2018 4 25 3 0 0.2939010 0.000000 1.8216964E-04 2.7291472E-03 0.000000 0.000000 0.000000 - Av 2018 4 25 4 0 0.2930697 0.000000 1.7948235E-04 2.7266392E-03 0.000000 0.000000 0.000000 - Av 2018 4 25 5 0 0.2926556 0.000000 1.7683470E-04 2.7241332E-03 0.000000 0.000000 0.000000 + Av 2018 4 24 19 0 0.2900206 0.000000 2.0516818E-04 2.8078228E-03 0.000000 0.000000 0.000000 + Av 2018 4 24 20 0 0.3082035 0.000000 2.0214161E-04 2.8051869E-03 0.000000 0.000000 0.000000 + Av 2018 4 24 21 0 0.3011149 0.000000 1.9915971E-04 2.8025536E-03 0.000000 0.000000 0.000000 + Av 2018 4 24 22 0 0.3028198 0.000000 1.9622179E-04 2.7999228E-03 0.000000 0.000000 0.000000 + Av 2018 4 24 23 0 0.3014733 0.000000 1.9332720E-04 2.7972944E-03 0.000000 0.000000 0.000000 + Av 2018 4 24 24 0 0.3011941 0.000000 1.9047532E-04 2.7946683E-03 0.000000 0.000000 0.000000 + Av 2018 4 25 1 0 0.2966176 0.000000 1.8766552E-04 2.7341705E-03 0.000000 0.000000 0.000000 + Av 2018 4 25 2 0 0.2935486 0.000000 1.8489716E-04 2.7316578E-03 0.000000 0.000000 0.000000 + Av 2018 4 25 3 0 0.2939010 0.000000 1.8216964E-04 2.7291472E-03 0.000000 0.000000 0.000000 + Av 2018 4 25 4 0 0.2930697 0.000000 1.7948235E-04 2.7266392E-03 0.000000 0.000000 0.000000 + Av 2018 4 25 5 0 0.2926556 0.000000 1.7683470E-04 2.7241332E-03 0.000000 0.000000 0.000000 Av 2018 4 25 6 0 0.2449008 0.000000 1.7422611E-04 2.0322811E-03 0.000000 0.000000 3.1334013E-03 Av 2018 4 25 7 0 0.1641543 0.000000 1.7165599E-04 1.3055418E-03 0.000000 0.000000 6.4253896E-03 Av 2018 4 25 8 0 9.2737421E-02 0.000000 1.6912380E-04 5.7880301E-04 0.000000 0.000000 9.7173778E-03 @@ -2778,17 +2778,17 @@ Av 2018 4 25 16 0 5.8513135E-02 0.000000 1.5016570E-04 5.5878353E-04 0.000000 0.000000 9.7173778E-03 Av 2018 4 25 17 0 0.1240990 0.000000 1.4795052E-04 1.2805219E-03 0.000000 0.000000 6.4253896E-03 Av 2018 4 25 18 0 0.1991788 0.000000 1.4576802E-04 2.0022620E-03 0.000000 0.000000 3.1334013E-03 - Av 2018 4 25 19 0 0.2688847 0.000000 1.4361771E-04 2.6891152E-03 0.000000 0.000000 0.000000 - Av 2018 4 25 20 0 0.2911290 0.000000 1.4149913E-04 2.6866223E-03 0.000000 0.000000 0.000000 - Av 2018 4 25 21 0 0.2827701 0.000000 1.3941179E-04 2.6841320E-03 0.000000 0.000000 0.000000 - Av 2018 4 25 22 0 0.2850568 0.000000 1.3735525E-04 2.6816439E-03 0.000000 0.000000 0.000000 - Av 2018 4 25 23 0 0.2836463 0.000000 1.3532904E-04 2.6791578E-03 0.000000 0.000000 0.000000 - Av 2018 4 25 24 0 0.2835258 0.000000 1.3333274E-04 2.6766744E-03 0.000000 0.000000 0.000000 - Av 2018 4 26 1 0 0.2792305 0.000000 1.3136587E-04 2.6192854E-03 0.000000 0.000000 0.000000 - Av 2018 4 26 2 0 0.2763979 0.000000 1.2942801E-04 2.6169072E-03 0.000000 0.000000 0.000000 - Av 2018 4 26 3 0 0.2767984 0.000000 1.2751875E-04 2.6145312E-03 0.000000 0.000000 0.000000 - Av 2018 4 26 4 0 0.2760789 0.000000 1.2563766E-04 2.6121575E-03 0.000000 0.000000 0.000000 - Av 2018 4 26 5 0 0.2757529 0.000000 1.2378431E-04 2.6097856E-03 0.000000 0.000000 0.000000 + Av 2018 4 25 19 0 0.2688847 0.000000 1.4361771E-04 2.6891152E-03 0.000000 0.000000 0.000000 + Av 2018 4 25 20 0 0.2911290 0.000000 1.4149913E-04 2.6866223E-03 0.000000 0.000000 0.000000 + Av 2018 4 25 21 0 0.2827701 0.000000 1.3941179E-04 2.6841320E-03 0.000000 0.000000 0.000000 + Av 2018 4 25 22 0 0.2850568 0.000000 1.3735525E-04 2.6816439E-03 0.000000 0.000000 0.000000 + Av 2018 4 25 23 0 0.2836463 0.000000 1.3532904E-04 2.6791578E-03 0.000000 0.000000 0.000000 + Av 2018 4 25 24 0 0.2835258 0.000000 1.3333274E-04 2.6766744E-03 0.000000 0.000000 0.000000 + Av 2018 4 26 1 0 0.2792305 0.000000 1.3136587E-04 2.6192854E-03 0.000000 0.000000 0.000000 + Av 2018 4 26 2 0 0.2763979 0.000000 1.2942801E-04 2.6169072E-03 0.000000 0.000000 0.000000 + Av 2018 4 26 3 0 0.2767984 0.000000 1.2751875E-04 2.6145312E-03 0.000000 0.000000 0.000000 + Av 2018 4 26 4 0 0.2760789 0.000000 1.2563766E-04 2.6121575E-03 0.000000 0.000000 0.000000 + Av 2018 4 26 5 0 0.2757529 0.000000 1.2378431E-04 2.6097856E-03 0.000000 0.000000 0.000000 Av 2018 4 26 6 0 0.2243485 0.000000 1.2195830E-04 1.8632160E-03 0.000000 0.000000 3.3827273E-03 Av 2018 4 26 7 0 0.1386849 0.000000 1.2015922E-04 1.0985843E-03 0.000000 0.000000 6.8475669E-03 Av 2018 4 26 8 0 6.3990191E-02 0.000000 1.1838668E-04 3.3395365E-04 0.000000 0.000000 1.0312406E-02 @@ -2802,16 +2802,16 @@ Av 2018 4 26 16 0 3.1688262E-02 0.000000 1.0511600E-04 3.1510275E-04 0.000000 0.000000 1.0312406E-02 Av 2018 4 26 17 0 9.7046643E-02 0.000000 1.0356537E-04 1.0750209E-03 0.000000 0.000000 6.8475669E-03 Av 2018 4 26 18 0 0.1773287 0.000000 1.0203762E-04 1.8349406E-03 0.000000 0.000000 3.3827273E-03 - Av 2018 4 26 19 0 0.2515842 0.000000 1.0053240E-04 2.5767982E-03 0.000000 0.000000 0.000000 - Av 2018 4 26 20 0 0.2760807 0.000000 9.9049394E-05 2.5744576E-03 0.000000 0.000000 0.000000 - Av 2018 4 26 21 0 0.2670451 0.000000 9.7588258E-05 2.5721192E-03 0.000000 0.000000 0.000000 - Av 2018 4 26 22 0 0.2696722 0.000000 9.6148680E-05 2.5697832E-03 0.000000 0.000000 0.000000 - Av 2018 4 26 23 0 0.2682472 0.000000 9.4730334E-05 2.5674491E-03 0.000000 0.000000 0.000000 - Av 2018 4 26 24 0 0.2682344 0.000000 9.3332914E-05 2.5651171E-03 0.000000 0.000000 0.000000 - Av 2018 4 27 1 0 0.2641929 0.000000 9.1956099E-05 2.5106757E-03 0.000000 0.000000 0.000000 - Av 2018 4 27 2 0 0.2615617 0.000000 9.0599606E-05 2.5084417E-03 0.000000 0.000000 0.000000 - Av 2018 4 27 3 0 0.2619901 0.000000 8.9263121E-05 2.5062095E-03 0.000000 0.000000 0.000000 - Av 2018 4 27 4 0 0.2613577 0.000000 8.7946348E-05 2.5039795E-03 0.000000 0.000000 0.000000 + Av 2018 4 26 19 0 0.2515842 0.000000 1.0053240E-04 2.5767982E-03 0.000000 0.000000 0.000000 + Av 2018 4 26 20 0 0.2760807 0.000000 9.9049394E-05 2.5744576E-03 0.000000 0.000000 0.000000 + Av 2018 4 26 21 0 0.2670451 0.000000 9.7588258E-05 2.5721192E-03 0.000000 0.000000 0.000000 + Av 2018 4 26 22 0 0.2696722 0.000000 9.6148680E-05 2.5697832E-03 0.000000 0.000000 0.000000 + Av 2018 4 26 23 0 0.2682472 0.000000 9.4730334E-05 2.5674491E-03 0.000000 0.000000 0.000000 + Av 2018 4 26 24 0 0.2682344 0.000000 9.3332914E-05 2.5651171E-03 0.000000 0.000000 0.000000 + Av 2018 4 27 1 0 0.2641929 0.000000 9.1956099E-05 2.5106757E-03 0.000000 0.000000 0.000000 + Av 2018 4 27 2 0 0.2615617 0.000000 9.0599606E-05 2.5084417E-03 0.000000 0.000000 0.000000 + Av 2018 4 27 3 0 0.2619901 0.000000 8.9263121E-05 2.5062095E-03 0.000000 0.000000 0.000000 + Av 2018 4 27 4 0 0.2613577 0.000000 8.7946348E-05 2.5039795E-03 0.000000 0.000000 0.000000 Av 2018 4 27 5 0 0.2610768 0.000000 8.6649008E-05 2.5014544E-03 0.000000 0.000000 1.3504465E-06 Av 2018 4 27 6 0 0.2254614 0.000000 8.5370797E-05 1.9847124E-03 0.000000 0.000000 2.3400590E-03 Av 2018 4 27 7 0 0.1670149 0.000000 8.4111452E-05 1.4679725E-03 0.000000 0.000000 4.6787676E-03 @@ -2827,15 +2827,15 @@ Av 2018 4 27 17 0 0.1387900 0.000000 7.2495764E-05 1.4458401E-03 0.000000 0.000000 4.6787676E-03 Av 2018 4 27 18 0 0.1922622 0.000000 7.1426344E-05 1.9581534E-03 0.000000 0.000000 2.3400590E-03 Av 2018 4 27 19 0 0.2434764 0.000000 7.0372691E-05 2.4704689E-03 0.000000 0.000000 1.3504465E-06 - Av 2018 4 27 20 0 0.2604125 0.000000 6.9334586E-05 2.4685676E-03 0.000000 0.000000 0.000000 - Av 2018 4 27 21 0 0.2541054 0.000000 6.8311791E-05 2.4663711E-03 0.000000 0.000000 0.000000 - Av 2018 4 27 22 0 0.2558621 0.000000 6.7304085E-05 2.4641764E-03 0.000000 0.000000 0.000000 - Av 2018 4 27 23 0 0.2548172 0.000000 6.6311251E-05 2.4619836E-03 0.000000 0.000000 0.000000 - Av 2018 4 27 24 0 0.2547488 0.000000 6.5333057E-05 2.4597929E-03 0.000000 0.000000 0.000000 - Av 2018 4 28 1 0 0.2509812 0.000000 6.4369291E-05 2.4081245E-03 0.000000 0.000000 0.000000 - Av 2018 4 28 2 0 0.2485080 0.000000 6.3419742E-05 2.4060251E-03 0.000000 0.000000 0.000000 - Av 2018 4 28 3 0 0.2489547 0.000000 6.2484200E-05 2.4039270E-03 0.000000 0.000000 0.000000 - Av 2018 4 28 4 0 0.2483883 0.000000 6.1562459E-05 2.4018311E-03 0.000000 0.000000 0.000000 + Av 2018 4 27 20 0 0.2604125 0.000000 6.9334586E-05 2.4685676E-03 0.000000 0.000000 0.000000 + Av 2018 4 27 21 0 0.2541054 0.000000 6.8311791E-05 2.4663711E-03 0.000000 0.000000 0.000000 + Av 2018 4 27 22 0 0.2558621 0.000000 6.7304085E-05 2.4641764E-03 0.000000 0.000000 0.000000 + Av 2018 4 27 23 0 0.2548172 0.000000 6.6311251E-05 2.4619836E-03 0.000000 0.000000 0.000000 + Av 2018 4 27 24 0 0.2547488 0.000000 6.5333057E-05 2.4597929E-03 0.000000 0.000000 0.000000 + Av 2018 4 28 1 0 0.2509812 0.000000 6.4369291E-05 2.4081245E-03 0.000000 0.000000 0.000000 + Av 2018 4 28 2 0 0.2485080 0.000000 6.3419742E-05 2.4060251E-03 0.000000 0.000000 0.000000 + Av 2018 4 28 3 0 0.2489547 0.000000 6.2484200E-05 2.4039270E-03 0.000000 0.000000 0.000000 + Av 2018 4 28 4 0 0.2483883 0.000000 6.1562459E-05 2.4018311E-03 0.000000 0.000000 0.000000 Av 2018 4 28 5 0 0.2474443 0.000000 6.0654318E-05 2.3890422E-03 0.000000 0.000000 4.8613361E-05 Av 2018 4 28 6 0 0.2169406 0.000000 5.9759572E-05 1.9530249E-03 0.000000 0.000000 2.0209996E-03 Av 2018 4 28 7 0 0.1678099 0.000000 5.8878020E-05 1.5170093E-03 0.000000 0.000000 3.9933859E-03 @@ -2851,15 +2851,15 @@ Av 2018 4 28 17 0 0.1437253 0.000000 5.0747043E-05 1.4962045E-03 0.000000 0.000000 3.9933859E-03 Av 2018 4 28 18 0 0.1890549 0.000000 4.9998442E-05 1.9280589E-03 0.000000 0.000000 2.0209996E-03 Av 2018 4 28 19 0 0.2361096 0.000000 4.9260885E-05 2.3599153E-03 0.000000 3.9999921E-02 4.8613361E-05 - Av 2018 4 28 20 0 0.2508560 0.000000 4.8534210E-05 2.3685431E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 4 28 21 0 0.2421397 0.000000 4.7818256E-05 2.3664781E-03 0.000000 0.000000 0.000000 - Av 2018 4 28 22 0 0.2436930 0.000000 4.7112859E-05 2.3644147E-03 0.000000 0.000000 0.000000 - Av 2018 4 28 23 0 0.2427775 0.000000 4.6417870E-05 2.3623533E-03 0.000000 0.000000 0.000000 - Av 2018 4 28 24 0 0.2427221 0.000000 4.5733137E-05 2.3602936E-03 0.000000 0.000000 0.000000 - Av 2018 4 29 1 0 0.2391758 0.000000 4.5058499E-05 2.3112346E-03 0.000000 0.000000 0.000000 - Av 2018 4 29 2 0 0.2368504 0.000000 4.4393815E-05 2.3092597E-03 0.000000 0.000000 0.000000 - Av 2018 4 29 3 0 0.2373010 0.000000 4.3738939E-05 2.3072863E-03 0.000000 0.000000 0.000000 - Av 2018 4 29 4 0 0.2367879 0.000000 4.3093722E-05 2.3053149E-03 0.000000 0.000000 0.000000 + Av 2018 4 28 20 0 0.2508560 0.000000 4.8534210E-05 2.3685431E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 4 28 21 0 0.2421397 0.000000 4.7818256E-05 2.3664781E-03 0.000000 0.000000 0.000000 + Av 2018 4 28 22 0 0.2436930 0.000000 4.7112859E-05 2.3644147E-03 0.000000 0.000000 0.000000 + Av 2018 4 28 23 0 0.2427775 0.000000 4.6417870E-05 2.3623533E-03 0.000000 0.000000 0.000000 + Av 2018 4 28 24 0 0.2427221 0.000000 4.5733137E-05 2.3602936E-03 0.000000 0.000000 0.000000 + Av 2018 4 29 1 0 0.2391758 0.000000 4.5058499E-05 2.3112346E-03 0.000000 0.000000 0.000000 + Av 2018 4 29 2 0 0.2368504 0.000000 4.4393815E-05 2.3092597E-03 0.000000 0.000000 0.000000 + Av 2018 4 29 3 0 0.2373010 0.000000 4.3738939E-05 2.3072863E-03 0.000000 0.000000 0.000000 + Av 2018 4 29 4 0 0.2367879 0.000000 4.3093722E-05 2.3053149E-03 0.000000 0.000000 0.000000 Av 2018 4 29 5 0 0.2353758 0.000000 4.2458021E-05 2.2852838E-03 0.000000 0.000000 8.2096383E-05 Av 2018 4 29 6 0 0.2088005 0.000000 4.1831699E-05 1.9109321E-03 0.000000 0.000000 1.7747482E-03 Av 2018 4 29 7 0 0.1667753 0.000000 4.1214615E-05 1.5365821E-03 0.000000 0.000000 3.4673999E-03 @@ -2875,15 +2875,15 @@ Av 2018 4 29 17 0 0.1455989 0.000000 3.5522931E-05 1.5170085E-03 0.000000 0.000000 3.4673999E-03 Av 2018 4 29 18 0 0.1850601 0.000000 3.4998913E-05 1.8874437E-03 0.000000 0.000000 1.7747482E-03 Av 2018 4 29 19 0 0.2218606 0.000000 3.4482622E-05 2.2578808E-03 0.000000 0.000000 8.2096383E-05 - Av 2018 4 29 20 0 0.2354155 0.000000 3.3973949E-05 2.2739971E-03 0.000000 0.000000 0.000000 - Av 2018 4 29 21 0 0.2316047 0.000000 3.3472781E-05 2.2720539E-03 0.000000 0.000000 0.000000 - Av 2018 4 29 22 0 0.2325982 0.000000 3.2979005E-05 2.2701123E-03 0.000000 0.000000 0.000000 - Av 2018 4 29 23 0 0.2319224 0.000000 3.2492513E-05 2.2681723E-03 0.000000 0.000000 0.000000 - Av 2018 4 29 24 0 0.2318283 0.000000 3.2013199E-05 2.2662343E-03 0.000000 0.000000 0.000000 - Av 2018 4 30 1 0 0.2284984 0.000000 3.1540952E-05 2.2196327E-03 0.000000 0.000000 0.000000 - Av 2018 4 30 2 0 0.2262999 0.000000 3.1075673E-05 2.2177733E-03 0.000000 0.000000 0.000000 - Av 2018 4 30 3 0 0.2267490 0.000000 3.0617259E-05 2.2159156E-03 0.000000 0.000000 0.000000 - Av 2018 4 30 4 0 0.2262787 0.000000 3.0165607E-05 2.2140595E-03 0.000000 0.000000 0.000000 + Av 2018 4 29 20 0 0.2354155 0.000000 3.3973949E-05 2.2739971E-03 0.000000 0.000000 0.000000 + Av 2018 4 29 21 0 0.2316047 0.000000 3.3472781E-05 2.2720539E-03 0.000000 0.000000 0.000000 + Av 2018 4 29 22 0 0.2325982 0.000000 3.2979005E-05 2.2701123E-03 0.000000 0.000000 0.000000 + Av 2018 4 29 23 0 0.2319224 0.000000 3.2492513E-05 2.2681723E-03 0.000000 0.000000 0.000000 + Av 2018 4 29 24 0 0.2318283 0.000000 3.2013199E-05 2.2662343E-03 0.000000 0.000000 0.000000 + Av 2018 4 30 1 0 0.2284984 0.000000 3.1540952E-05 2.2196327E-03 0.000000 0.000000 0.000000 + Av 2018 4 30 2 0 0.2262999 0.000000 3.1075673E-05 2.2177733E-03 0.000000 0.000000 0.000000 + Av 2018 4 30 3 0 0.2267490 0.000000 3.0617259E-05 2.2159156E-03 0.000000 0.000000 0.000000 + Av 2018 4 30 4 0 0.2262787 0.000000 3.0165607E-05 2.2140595E-03 0.000000 0.000000 0.000000 Av 2018 4 30 5 0 0.2240148 0.000000 2.9720619E-05 2.1812983E-03 0.000000 0.000000 1.4048502E-04 Av 2018 4 30 6 0 0.1930668 0.000000 2.9282193E-05 1.7509770E-03 0.000000 0.000000 2.0880674E-03 Av 2018 4 30 7 0 0.1449549 0.000000 2.8850234E-05 1.3206572E-03 0.000000 0.000000 4.0356498E-03 @@ -2899,15 +2899,15 @@ Av 2018 4 30 17 0 0.1216205 0.000000 2.4866054E-05 1.3022270E-03 0.000000 0.000000 4.0356498E-03 Av 2018 4 30 18 0 0.1665689 0.000000 2.4499241E-05 1.7288607E-03 0.000000 0.000000 2.0880674E-03 Av 2018 4 30 19 0 0.2091225 0.000000 2.4137838E-05 2.1554958E-03 0.000000 0.000000 1.4048502E-04 - Av 2018 4 30 20 0 0.2254117 0.000000 2.3781768E-05 2.1845712E-03 0.000000 0.000000 0.000000 - Av 2018 4 30 21 0 0.2215640 0.000000 2.3430950E-05 2.1827412E-03 0.000000 0.000000 0.000000 - Av 2018 4 30 22 0 0.2226060 0.000000 2.3085306E-05 2.1809128E-03 0.000000 0.000000 0.000000 - Av 2018 4 30 23 0 0.2219487 0.000000 2.2744762E-05 2.1790860E-03 0.000000 0.000000 0.000000 - Av 2018 4 30 24 0 0.2218832 0.000000 2.2409242E-05 2.1772606E-03 0.000000 0.000000 0.000000 - Av 2018 5 1 1 0 0.2187277 0.000000 2.2078670E-05 2.1329743E-03 0.000000 0.000000 0.000000 - Av 2018 5 1 2 0 0.2166523 0.000000 2.1752976E-05 2.1312225E-03 0.000000 0.000000 0.000000 - Av 2018 5 1 3 0 0.2170920 0.000000 2.1432084E-05 2.1294721E-03 0.000000 0.000000 0.000000 - Av 2018 5 1 4 0 0.2166581 0.000000 2.1115928E-05 2.1277231E-03 0.000000 0.000000 0.000000 + Av 2018 4 30 20 0 0.2254117 0.000000 2.3781768E-05 2.1845712E-03 0.000000 0.000000 0.000000 + Av 2018 4 30 21 0 0.2215640 0.000000 2.3430950E-05 2.1827412E-03 0.000000 0.000000 0.000000 + Av 2018 4 30 22 0 0.2226060 0.000000 2.3085306E-05 2.1809128E-03 0.000000 0.000000 0.000000 + Av 2018 4 30 23 0 0.2219487 0.000000 2.2744762E-05 2.1790860E-03 0.000000 0.000000 0.000000 + Av 2018 4 30 24 0 0.2218832 0.000000 2.2409242E-05 2.1772606E-03 0.000000 0.000000 0.000000 + Av 2018 5 1 1 0 0.2187277 0.000000 2.2078670E-05 2.1329743E-03 0.000000 0.000000 0.000000 + Av 2018 5 1 2 0 0.2166523 0.000000 2.1752976E-05 2.1312225E-03 0.000000 0.000000 0.000000 + Av 2018 5 1 3 0 0.2170920 0.000000 2.1432084E-05 2.1294721E-03 0.000000 0.000000 0.000000 + Av 2018 5 1 4 0 0.2166581 0.000000 2.1115928E-05 2.1277231E-03 0.000000 0.000000 0.000000 Av 2018 5 1 5 0 0.2128252 0.000000 2.0804435E-05 2.0718295E-03 0.000000 0.000000 2.4611858E-04 Av 2018 5 1 6 0 0.1756131 0.000000 2.0497537E-05 1.5647197E-03 0.000000 0.000000 2.5432275E-03 Av 2018 5 1 7 0 0.1192328 0.000000 2.0195166E-05 1.0576108E-03 0.000000 0.000000 4.8403363E-03 @@ -2923,15 +2923,15 @@ Av 2018 5 1 17 0 9.2262030E-02 0.000000 1.7406242E-05 1.0402431E-03 0.000000 0.000000 4.8403363E-03 Av 2018 5 1 18 0 0.1453918 0.000000 1.7149474E-05 1.5438781E-03 0.000000 0.000000 2.5432275E-03 Av 2018 5 1 19 0 0.1955618 0.000000 1.6896491E-05 2.0475143E-03 0.000000 0.000000 2.4611858E-04 - Av 2018 5 1 20 0 0.2160541 0.000000 1.6647242E-05 2.0999345E-03 0.000000 0.000000 0.000000 - Av 2018 5 1 21 0 0.2123614 0.000000 1.6401667E-05 2.0982097E-03 0.000000 0.000000 0.000000 - Av 2018 5 1 22 0 0.2133780 0.000000 1.6159718E-05 2.0964863E-03 0.000000 0.000000 0.000000 - Av 2018 5 1 23 0 0.2127578 0.000000 1.5921336E-05 2.0947645E-03 0.000000 0.000000 0.000000 - Av 2018 5 1 24 0 0.2127074 0.000000 1.5686472E-05 2.0930441E-03 0.000000 0.000000 0.000000 - Av 2018 5 2 1 0 0.2097157 0.000000 1.5455073E-05 2.0509406E-03 0.000000 0.000000 0.000000 - Av 2018 5 2 2 0 0.2077518 0.000000 1.5227085E-05 2.0492887E-03 0.000000 0.000000 0.000000 - Av 2018 5 2 3 0 0.2081795 0.000000 1.5002462E-05 2.0476382E-03 0.000000 0.000000 0.000000 - Av 2018 5 2 4 0 0.2077763 0.000000 1.4781152E-05 2.0459890E-03 0.000000 0.000000 0.000000 + Av 2018 5 1 20 0 0.2160541 0.000000 1.6647242E-05 2.0999345E-03 0.000000 0.000000 0.000000 + Av 2018 5 1 21 0 0.2123614 0.000000 1.6401667E-05 2.0982097E-03 0.000000 0.000000 0.000000 + Av 2018 5 1 22 0 0.2133780 0.000000 1.6159718E-05 2.0964863E-03 0.000000 0.000000 0.000000 + Av 2018 5 1 23 0 0.2127578 0.000000 1.5921336E-05 2.0947645E-03 0.000000 0.000000 0.000000 + Av 2018 5 1 24 0 0.2127074 0.000000 1.5686472E-05 2.0930441E-03 0.000000 0.000000 0.000000 + Av 2018 5 2 1 0 0.2097157 0.000000 1.5455073E-05 2.0509406E-03 0.000000 0.000000 0.000000 + Av 2018 5 2 2 0 0.2077518 0.000000 1.5227085E-05 2.0492887E-03 0.000000 0.000000 0.000000 + Av 2018 5 2 3 0 0.2081795 0.000000 1.5002462E-05 2.0476382E-03 0.000000 0.000000 0.000000 + Av 2018 5 2 4 0 0.2077763 0.000000 1.4781152E-05 2.0459890E-03 0.000000 0.000000 0.000000 Av 2018 5 2 5 0 0.2026658 0.000000 1.4563107E-05 1.9712772E-03 0.000000 0.000000 3.3210893E-04 Av 2018 5 2 6 0 0.1608151 0.000000 1.4348278E-05 1.4083690E-03 0.000000 0.000000 2.8832960E-03 Av 2018 5 2 7 0 9.8466694E-02 0.000000 1.4136618E-05 8.4546290E-04 0.000000 0.000000 5.4344828E-03 @@ -2947,15 +2947,15 @@ Av 2018 5 2 17 0 6.8929091E-02 0.000000 1.2184368E-05 8.2908280E-04 0.000000 0.000000 5.4344828E-03 Av 2018 5 2 18 0 0.1279411 0.000000 1.2004629E-05 1.3887130E-03 0.000000 0.000000 2.8832960E-03 Av 2018 5 2 19 0 0.1836420 0.000000 1.1827542E-05 1.9483446E-03 0.000000 0.000000 3.3210893E-04 - Av 2018 5 2 20 0 0.2073248 0.000000 1.1653066E-05 2.0197807E-03 0.000000 0.000000 0.000000 - Av 2018 5 2 21 0 0.2038377 0.000000 1.1481166E-05 2.0181537E-03 0.000000 0.000000 0.000000 - Av 2018 5 2 22 0 0.2048060 0.000000 1.1311800E-05 2.0165283E-03 0.000000 0.000000 0.000000 - Av 2018 5 2 23 0 0.2042257 0.000000 1.1144934E-05 2.0149041E-03 0.000000 0.000000 0.000000 - Av 2018 5 2 24 0 0.2041843 0.000000 1.0980529E-05 2.0132810E-03 0.000000 0.000000 0.000000 - Av 2018 5 3 1 0 0.2013455 0.000000 1.0818549E-05 1.9732369E-03 0.000000 0.000000 0.000000 - Av 2018 5 3 2 0 0.1994841 0.000000 1.0658958E-05 1.9716781E-03 0.000000 0.000000 0.000000 - Av 2018 5 3 3 0 0.1998980 0.000000 1.0501722E-05 1.9701202E-03 0.000000 0.000000 0.000000 - Av 2018 5 3 4 0 0.1995213 0.000000 1.0346805E-05 1.9685638E-03 0.000000 0.000000 0.000000 + Av 2018 5 2 20 0 0.2073248 0.000000 1.1653066E-05 2.0197807E-03 0.000000 0.000000 0.000000 + Av 2018 5 2 21 0 0.2038377 0.000000 1.1481166E-05 2.0181537E-03 0.000000 0.000000 0.000000 + Av 2018 5 2 22 0 0.2048060 0.000000 1.1311800E-05 2.0165283E-03 0.000000 0.000000 0.000000 + Av 2018 5 2 23 0 0.2042257 0.000000 1.1144934E-05 2.0149041E-03 0.000000 0.000000 0.000000 + Av 2018 5 2 24 0 0.2041843 0.000000 1.0980529E-05 2.0132810E-03 0.000000 0.000000 0.000000 + Av 2018 5 3 1 0 0.2013455 0.000000 1.0818549E-05 1.9732369E-03 0.000000 0.000000 0.000000 + Av 2018 5 3 2 0 0.1994841 0.000000 1.0658958E-05 1.9716781E-03 0.000000 0.000000 0.000000 + Av 2018 5 3 3 0 0.1998980 0.000000 1.0501722E-05 1.9701202E-03 0.000000 0.000000 0.000000 + Av 2018 5 3 4 0 0.1995213 0.000000 1.0346805E-05 1.9685638E-03 0.000000 0.000000 0.000000 Av 2018 5 3 5 0 0.1925871 0.000000 1.0194172E-05 1.8670850E-03 0.000000 0.000000 4.5419755E-04 Av 2018 5 3 6 0 0.1432740 0.000000 1.0043792E-05 1.2122646E-03 0.000000 0.000000 3.4235907E-03 Av 2018 5 3 7 0 7.1025163E-02 0.000000 9.8956307E-06 5.5744511E-04 0.000000 0.000000 6.3929842E-03 @@ -2971,15 +2971,15 @@ Av 2018 5 3 17 0 3.7598699E-02 0.000000 8.5290549E-06 5.4198399E-04 0.000000 0.000000 6.3929842E-03 Av 2018 5 3 18 0 0.1057538 0.000000 8.4032372E-06 1.1937111E-03 0.000000 0.000000 3.4235907E-03 Av 2018 5 3 19 0 0.1706180 0.000000 8.2792767E-06 1.8454394E-03 0.000000 0.000000 4.5419755E-04 - Av 2018 5 3 20 0 0.1992141 0.000000 8.1571434E-06 1.9438261E-03 0.000000 0.000000 0.000000 - Av 2018 5 3 21 0 0.1958711 0.000000 8.0368127E-06 1.9422903E-03 0.000000 0.000000 0.000000 - Av 2018 5 3 22 0 0.1968087 0.000000 7.9182573E-06 1.9407556E-03 0.000000 0.000000 0.000000 - Av 2018 5 3 23 0 0.1962582 0.000000 7.8014509E-06 1.9392223E-03 0.000000 0.000000 0.000000 - Av 2018 5 3 24 0 0.1962256 0.000000 7.6863671E-06 1.9376902E-03 0.000000 0.000000 0.000000 - Av 2018 5 4 1 0 0.1935286 0.000000 7.5729808E-06 1.8995898E-03 0.000000 0.000000 0.000000 - Av 2018 5 4 2 0 0.1917623 0.000000 7.4612672E-06 1.8981174E-03 0.000000 0.000000 0.000000 - Av 2018 5 4 3 0 0.1921614 0.000000 7.3512015E-06 1.8966461E-03 0.000000 0.000000 0.000000 - Av 2018 5 4 4 0 0.1918080 0.000000 7.2427592E-06 1.8951760E-03 0.000000 0.000000 0.000000 + Av 2018 5 3 20 0 0.1992141 0.000000 8.1571434E-06 1.9438261E-03 0.000000 0.000000 0.000000 + Av 2018 5 3 21 0 0.1958711 0.000000 8.0368127E-06 1.9422903E-03 0.000000 0.000000 0.000000 + Av 2018 5 3 22 0 0.1968087 0.000000 7.9182573E-06 1.9407556E-03 0.000000 0.000000 0.000000 + Av 2018 5 3 23 0 0.1962582 0.000000 7.8014509E-06 1.9392223E-03 0.000000 0.000000 0.000000 + Av 2018 5 3 24 0 0.1962256 0.000000 7.6863671E-06 1.9376902E-03 0.000000 0.000000 0.000000 + Av 2018 5 4 1 0 0.1935286 0.000000 7.5729808E-06 1.8995898E-03 0.000000 0.000000 0.000000 + Av 2018 5 4 2 0 0.1917623 0.000000 7.4612672E-06 1.8981174E-03 0.000000 0.000000 0.000000 + Av 2018 5 4 3 0 0.1921614 0.000000 7.3512015E-06 1.8966461E-03 0.000000 0.000000 0.000000 + Av 2018 5 4 4 0 0.1918080 0.000000 7.2427592E-06 1.8951760E-03 0.000000 0.000000 0.000000 Av 2018 5 4 5 0 0.1845796 0.000000 7.1359173E-06 1.7893238E-03 0.000000 0.000000 4.7446901E-04 Av 2018 5 4 6 0 0.1390820 0.000000 7.0306514E-06 1.1930059E-03 0.000000 0.000000 3.1783320E-03 Av 2018 5 4 7 0 7.3498532E-02 0.000000 6.9269386E-06 5.9668929E-04 0.000000 0.000000 5.8821947E-03 @@ -2995,15 +2995,15 @@ Av 2018 5 4 17 0 4.0076725E-02 0.000000 5.9703366E-06 5.8208429E-04 0.000000 0.000000 5.8821947E-03 Av 2018 5 4 18 0 0.1060482 0.000000 5.8822648E-06 1.1754798E-03 0.000000 0.000000 3.1783320E-03 Av 2018 5 4 19 0 0.1637419 0.000000 5.7954921E-06 1.7688766E-03 0.000000 0.000000 4.7446901E-04 - Av 2018 5 4 20 0 0.1911738 0.000000 5.7099992E-06 1.8718077E-03 0.000000 0.000000 0.000000 - Av 2018 5 4 21 0 0.1885560 0.000000 5.6257682E-06 1.8703567E-03 0.000000 0.000000 0.000000 - Av 2018 5 4 22 0 0.1892578 0.000000 5.5427790E-06 1.8689069E-03 0.000000 0.000000 0.000000 - Av 2018 5 4 23 0 0.1888057 0.000000 5.4610146E-06 1.8674582E-03 0.000000 0.000000 0.000000 - Av 2018 5 4 24 0 0.1887551 0.000000 5.3804561E-06 1.8660106E-03 0.000000 0.000000 0.000000 - Av 2018 5 5 1 0 0.1861994 0.000000 5.3010858E-06 1.8297457E-03 0.000000 0.000000 0.000000 - Av 2018 5 5 2 0 0.1845188 0.000000 5.2228866E-06 1.8283539E-03 0.000000 0.000000 0.000000 - Av 2018 5 5 3 0 0.1849035 0.000000 5.1458405E-06 1.8269630E-03 0.000000 0.000000 0.000000 - Av 2018 5 5 4 0 0.1845704 0.000000 5.0699314E-06 1.8255733E-03 0.000000 0.000000 0.000000 + Av 2018 5 4 20 0 0.1911738 0.000000 5.7099992E-06 1.8718077E-03 0.000000 0.000000 0.000000 + Av 2018 5 4 21 0 0.1885560 0.000000 5.6257682E-06 1.8703567E-03 0.000000 0.000000 0.000000 + Av 2018 5 4 22 0 0.1892578 0.000000 5.5427790E-06 1.8689069E-03 0.000000 0.000000 0.000000 + Av 2018 5 4 23 0 0.1888057 0.000000 5.4610146E-06 1.8674582E-03 0.000000 0.000000 0.000000 + Av 2018 5 4 24 0 0.1887551 0.000000 5.3804561E-06 1.8660106E-03 0.000000 0.000000 0.000000 + Av 2018 5 5 1 0 0.1861994 0.000000 5.3010858E-06 1.8297457E-03 0.000000 0.000000 0.000000 + Av 2018 5 5 2 0 0.1845188 0.000000 5.2228866E-06 1.8283539E-03 0.000000 0.000000 0.000000 + Av 2018 5 5 3 0 0.1849035 0.000000 5.1458405E-06 1.8269630E-03 0.000000 0.000000 0.000000 + Av 2018 5 5 4 0 0.1845704 0.000000 5.0699314E-06 1.8255733E-03 0.000000 0.000000 0.000000 Av 2018 5 5 5 0 0.1758012 0.000000 4.9951418E-06 1.6971291E-03 0.000000 0.000000 5.7752465E-04 Av 2018 5 5 6 0 0.1260508 0.000000 4.9214555E-06 1.0531530E-03 0.000000 0.000000 3.4983822E-03 Av 2018 5 5 7 0 5.5481732E-02 0.000000 4.8488564E-06 4.0917797E-04 0.000000 0.000000 6.4192396E-03 @@ -3019,15 +3019,15 @@ Av 2018 5 5 17 0 2.7206797E-02 0.000000 4.1792355E-06 3.9537030E-04 0.000000 0.000000 6.4192396E-03 Av 2018 5 5 18 0 8.8174477E-02 0.000000 4.1175854E-06 1.0365838E-03 0.000000 0.000000 3.4983822E-03 Av 2018 5 5 19 0 0.1541048 0.000000 4.0568443E-06 1.6777985E-03 0.000000 0.000000 5.7752465E-04 - Av 2018 5 5 20 0 0.1834532 0.000000 3.9969996E-06 1.8034810E-03 0.000000 0.000000 0.000000 - Av 2018 5 5 21 0 0.1817300 0.000000 3.9380375E-06 1.8021092E-03 0.000000 0.000000 0.000000 - Av 2018 5 5 22 0 0.1821349 0.000000 3.8799453E-06 1.8007384E-03 0.000000 0.000000 0.000000 - Av 2018 5 5 23 0 0.1818001 0.000000 3.8227099E-06 1.7993685E-03 0.000000 0.000000 0.000000 - Av 2018 5 5 24 0 0.1817227 0.000000 3.7663192E-06 1.7979998E-03 0.000000 0.000000 0.000000 - Av 2018 5 6 1 0 0.1793029 0.000000 3.7107600E-06 1.7634697E-03 0.000000 0.000000 0.000000 - Av 2018 5 6 2 0 0.1777012 0.000000 3.6560205E-06 1.7621529E-03 0.000000 0.000000 0.000000 - Av 2018 5 6 3 0 0.1780719 0.000000 3.6020883E-06 1.7608372E-03 0.000000 0.000000 0.000000 - Av 2018 5 6 4 0 0.1777570 0.000000 3.5489518E-06 1.7595226E-03 0.000000 0.000000 0.000000 + Av 2018 5 5 20 0 0.1834532 0.000000 3.9969996E-06 1.8034810E-03 0.000000 0.000000 0.000000 + Av 2018 5 5 21 0 0.1817300 0.000000 3.9380375E-06 1.8021092E-03 0.000000 0.000000 0.000000 + Av 2018 5 5 22 0 0.1821349 0.000000 3.8799453E-06 1.8007384E-03 0.000000 0.000000 0.000000 + Av 2018 5 5 23 0 0.1818001 0.000000 3.8227099E-06 1.7993685E-03 0.000000 0.000000 0.000000 + Av 2018 5 5 24 0 0.1817227 0.000000 3.7663192E-06 1.7979998E-03 0.000000 0.000000 0.000000 + Av 2018 5 6 1 0 0.1793029 0.000000 3.7107600E-06 1.7634697E-03 0.000000 0.000000 0.000000 + Av 2018 5 6 2 0 0.1777012 0.000000 3.6560205E-06 1.7621529E-03 0.000000 0.000000 0.000000 + Av 2018 5 6 3 0 0.1780719 0.000000 3.6020883E-06 1.7608372E-03 0.000000 0.000000 0.000000 + Av 2018 5 6 4 0 0.1777570 0.000000 3.5489518E-06 1.7595226E-03 0.000000 0.000000 0.000000 Av 2018 5 6 5 0 0.1683363 0.000000 3.4965992E-06 1.6215082E-03 0.000000 0.000000 6.2136672E-04 Av 2018 5 6 6 0 0.1195650 0.000000 3.4450188E-06 9.9794869E-04 0.000000 0.000000 3.4497620E-03 Av 2018 5 6 7 0 5.1456038E-02 0.000000 3.3941994E-06 3.7438993E-04 0.000000 0.000000 6.2781572E-03 @@ -3043,15 +3043,15 @@ Av 2018 5 6 17 0 2.4771504E-02 0.000000 2.9254647E-06 3.6132627E-04 0.000000 0.000000 6.2781572E-03 Av 2018 5 6 18 0 8.2861729E-02 0.000000 2.8823097E-06 9.8227221E-04 0.000000 0.000000 3.4497620E-03 Av 2018 5 6 19 0 0.1470360 0.000000 2.8397910E-06 1.6032191E-03 0.000000 0.000000 6.2136672E-04 - Av 2018 5 6 20 0 0.1762707 0.000000 2.7978997E-06 1.7386207E-03 0.000000 0.000000 0.000000 - Av 2018 5 6 21 0 0.1752570 0.000000 2.7566261E-06 1.7373227E-03 0.000000 0.000000 0.000000 - Av 2018 5 6 22 0 0.1754276 0.000000 2.7159617E-06 1.7360254E-03 0.000000 0.000000 0.000000 - Av 2018 5 6 23 0 0.1751866 0.000000 2.6758971E-06 1.7347294E-03 0.000000 0.000000 0.000000 - Av 2018 5 6 24 0 0.1750889 0.000000 2.6364235E-06 1.7334342E-03 0.000000 0.000000 0.000000 - Av 2018 5 7 1 0 0.1727948 0.000000 2.5975319E-06 1.7005436E-03 0.000000 0.000000 0.000000 - Av 2018 5 7 2 0 0.1712678 0.000000 2.5592142E-06 1.6992970E-03 0.000000 0.000000 0.000000 - Av 2018 5 7 3 0 0.1716242 0.000000 2.5214617E-06 1.6980515E-03 0.000000 0.000000 0.000000 - Av 2018 5 7 4 0 0.1713260 0.000000 2.4842661E-06 1.6968069E-03 0.000000 0.000000 0.000000 + Av 2018 5 6 20 0 0.1762707 0.000000 2.7978997E-06 1.7386207E-03 0.000000 0.000000 0.000000 + Av 2018 5 6 21 0 0.1752570 0.000000 2.7566261E-06 1.7373227E-03 0.000000 0.000000 0.000000 + Av 2018 5 6 22 0 0.1754276 0.000000 2.7159617E-06 1.7360254E-03 0.000000 0.000000 0.000000 + Av 2018 5 6 23 0 0.1751866 0.000000 2.6758971E-06 1.7347294E-03 0.000000 0.000000 0.000000 + Av 2018 5 6 24 0 0.1750889 0.000000 2.6364235E-06 1.7334342E-03 0.000000 0.000000 0.000000 + Av 2018 5 7 1 0 0.1727948 0.000000 2.5975319E-06 1.7005436E-03 0.000000 0.000000 0.000000 + Av 2018 5 7 2 0 0.1712678 0.000000 2.5592142E-06 1.6992970E-03 0.000000 0.000000 0.000000 + Av 2018 5 7 3 0 0.1716242 0.000000 2.5214617E-06 1.6980515E-03 0.000000 0.000000 0.000000 + Av 2018 5 7 4 0 0.1713260 0.000000 2.4842661E-06 1.6968069E-03 0.000000 0.000000 0.000000 Av 2018 5 7 5 0 0.1607025 0.000000 2.4476194E-06 1.5411632E-03 0.000000 0.000000 7.0181757E-04 Av 2018 5 7 6 0 0.1099674 0.000000 2.4115134E-06 9.0021751E-04 0.000000 0.000000 3.6095574E-03 Av 2018 5 7 7 0 4.0198863E-02 0.000000 2.3759396E-06 2.5927287E-04 0.000000 0.000000 6.5172971E-03 @@ -3067,15 +3067,15 @@ Av 2018 5 7 17 0 1.6907766E-02 0.000000 2.0478253E-06 2.4690339E-04 0.000000 0.000000 6.5172971E-03 Av 2018 5 7 18 0 7.1140990E-02 0.000000 2.0176167E-06 8.8537420E-04 0.000000 0.000000 3.6095574E-03 Av 2018 5 7 19 0 0.1390358 0.000000 1.9878537E-06 1.5238459E-03 0.000000 0.000000 7.0181757E-04 - Av 2018 5 7 20 0 0.1693547 0.000000 1.9585298E-06 1.6770157E-03 0.000000 0.000000 0.000000 - Av 2018 5 7 21 0 0.1691817 0.000000 1.9296383E-06 1.6757863E-03 0.000000 0.000000 0.000000 - Av 2018 5 7 22 0 0.1690710 0.000000 1.9011732E-06 1.6745579E-03 0.000000 0.000000 0.000000 - Av 2018 5 7 23 0 0.1689388 0.000000 1.8731278E-06 1.6733304E-03 0.000000 0.000000 0.000000 - Av 2018 5 7 24 0 0.1688142 0.000000 1.8454963E-06 1.6721039E-03 0.000000 0.000000 0.000000 - Av 2018 5 8 1 0 0.1666412 0.000000 1.8182722E-06 1.6407646E-03 0.000000 0.000000 0.000000 - Av 2018 5 8 2 0 0.1651835 0.000000 1.7914499E-06 1.6395836E-03 0.000000 0.000000 0.000000 - Av 2018 5 8 3 0 0.1655263 0.000000 1.7650232E-06 1.6384034E-03 0.000000 0.000000 0.000000 - Av 2018 5 8 4 0 0.1652433 0.000000 1.7389863E-06 1.6372241E-03 0.000000 0.000000 0.000000 + Av 2018 5 7 20 0 0.1693547 0.000000 1.9585298E-06 1.6770157E-03 0.000000 0.000000 0.000000 + Av 2018 5 7 21 0 0.1691817 0.000000 1.9296383E-06 1.6757863E-03 0.000000 0.000000 0.000000 + Av 2018 5 7 22 0 0.1690710 0.000000 1.9011732E-06 1.6745579E-03 0.000000 0.000000 0.000000 + Av 2018 5 7 23 0 0.1689388 0.000000 1.8731278E-06 1.6733304E-03 0.000000 0.000000 0.000000 + Av 2018 5 7 24 0 0.1688142 0.000000 1.8454963E-06 1.6721039E-03 0.000000 0.000000 0.000000 + Av 2018 5 8 1 0 0.1666412 0.000000 1.8182722E-06 1.6407646E-03 0.000000 0.000000 0.000000 + Av 2018 5 8 2 0 0.1651835 0.000000 1.7914499E-06 1.6395836E-03 0.000000 0.000000 0.000000 + Av 2018 5 8 3 0 0.1655263 0.000000 1.7650232E-06 1.6384034E-03 0.000000 0.000000 0.000000 + Av 2018 5 8 4 0 0.1652433 0.000000 1.7389863E-06 1.6372241E-03 0.000000 0.000000 0.000000 Av 2018 5 8 5 0 0.1524437 0.000000 1.7133335E-06 1.4497152E-03 0.000000 0.000000 8.4695622E-04 Av 2018 5 8 6 0 9.5557980E-02 0.000000 1.6880591E-06 7.3933974E-04 0.000000 0.000000 4.0705828E-03 Av 2018 5 8 7 0 2.5748558E-02 0.000000 1.6631576E-06 2.8965296E-05 0.000000 0.000000 7.2942087E-03 @@ -3091,15 +3091,15 @@ Av 2018 5 8 17 0 1.2818401E-03 0.000000 1.4334778E-06 1.7244136E-05 0.000000 0.000000 7.2942087E-03 Av 2018 5 8 18 0 5.0099518E-02 0.000000 1.4123317E-06 7.2527432E-04 0.000000 0.000000 4.0705828E-03 Av 2018 5 8 19 0 0.1293304 0.000000 1.3914977E-06 1.4333056E-03 0.000000 0.000000 8.4695622E-04 - Av 2018 5 8 20 0 0.1625122 0.000000 1.3709708E-06 1.6184702E-03 0.000000 0.000000 0.000000 - Av 2018 5 8 21 0 0.1644032 0.000000 1.3507469E-06 1.6173052E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 5 8 22 0 0.1635847 0.000000 1.3308213E-06 1.6161412E-03 0.000000 0.000000 0.000000 - Av 2018 5 8 23 0 0.1637042 0.000000 1.3111895E-06 1.6149778E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 5 8 24 0 0.1643764 0.000000 1.2918474E-06 1.6138153E-03 0.000000 9.9999802E-03 0.000000 - Av 2018 5 9 1 0 0.1611630 0.000000 1.2727907E-06 1.5839438E-03 0.000000 0.000000 0.000000 - Av 2018 5 9 2 0 0.1592976 0.000000 1.2540149E-06 1.5828239E-03 0.000000 0.000000 0.000000 - Av 2018 5 9 3 0 0.1597916 0.000000 1.2355163E-06 1.5817048E-03 0.000000 0.000000 0.000000 - Av 2018 5 9 4 0 0.1594653 0.000000 1.2172906E-06 1.5805867E-03 0.000000 0.000000 0.000000 + Av 2018 5 8 20 0 0.1625122 0.000000 1.3709708E-06 1.6184702E-03 0.000000 0.000000 0.000000 + Av 2018 5 8 21 0 0.1644032 0.000000 1.3507469E-06 1.6173052E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 5 8 22 0 0.1635847 0.000000 1.3308213E-06 1.6161412E-03 0.000000 0.000000 0.000000 + Av 2018 5 8 23 0 0.1637042 0.000000 1.3111895E-06 1.6149778E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 5 8 24 0 0.1643764 0.000000 1.2918474E-06 1.6138153E-03 0.000000 9.9999802E-03 0.000000 + Av 2018 5 9 1 0 0.1611630 0.000000 1.2727907E-06 1.5839438E-03 0.000000 0.000000 0.000000 + Av 2018 5 9 2 0 0.1592976 0.000000 1.2540149E-06 1.5828239E-03 0.000000 0.000000 0.000000 + Av 2018 5 9 3 0 0.1597916 0.000000 1.2355163E-06 1.5817048E-03 0.000000 0.000000 0.000000 + Av 2018 5 9 4 0 0.1594653 0.000000 1.2172906E-06 1.5805867E-03 0.000000 0.000000 0.000000 Av 2018 5 9 5 0 0.1474981 0.000000 1.1993336E-06 1.4049429E-03 0.000000 0.000000 7.9330144E-04 Av 2018 5 9 6 0 9.7579338E-02 0.000000 1.1816416E-06 7.8885368E-04 0.000000 0.000000 3.5886313E-03 Av 2018 5 9 7 0 3.0947760E-02 0.000000 1.1642104E-06 1.7276523E-04 0.000000 0.000000 6.3839611E-03 @@ -3115,15 +3115,15 @@ Av 2018 5 9 17 0 1.1051370E-02 0.000000 1.0034342E-06 1.6165001E-04 0.000000 0.000000 6.3839611E-03 Av 2018 5 9 18 0 5.9851252E-02 0.000000 9.8863200E-07 7.7551539E-04 0.000000 0.000000 3.5886313E-03 Av 2018 5 9 19 0 0.1262452 0.000000 9.7404813E-07 1.3893815E-03 0.000000 0.000000 7.9330144E-04 - Av 2018 5 9 20 0 0.1567656 0.000000 9.5967937E-07 1.5628021E-03 0.000000 0.000000 0.000000 - Av 2018 5 9 21 0 0.1579125 0.000000 9.4552263E-07 1.5616972E-03 0.000000 0.000000 0.000000 - Av 2018 5 9 22 0 0.1573617 0.000000 9.3157468E-07 1.5605931E-03 0.000000 0.000000 0.000000 - Av 2018 5 9 23 0 0.1574014 0.000000 9.1783244E-07 1.5594898E-03 0.000000 0.000000 0.000000 - Av 2018 5 9 24 0 0.1572358 0.000000 9.0429296E-07 1.5583872E-03 0.000000 0.000000 0.000000 - Av 2018 5 10 1 0 0.1552815 0.000000 8.9095323E-07 1.5299057E-03 0.000000 0.000000 0.000000 - Av 2018 5 10 2 0 0.1539519 0.000000 8.7781029E-07 1.5288431E-03 0.000000 0.000000 0.000000 - Av 2018 5 10 3 0 0.1542681 0.000000 8.6486119E-07 1.5277812E-03 0.000000 0.000000 0.000000 - Av 2018 5 10 4 0 0.1540121 0.000000 8.5210314E-07 1.5267201E-03 0.000000 0.000000 0.000000 + Av 2018 5 9 20 0 0.1567656 0.000000 9.5967937E-07 1.5628021E-03 0.000000 0.000000 0.000000 + Av 2018 5 9 21 0 0.1579125 0.000000 9.4552263E-07 1.5616972E-03 0.000000 0.000000 0.000000 + Av 2018 5 9 22 0 0.1573617 0.000000 9.3157468E-07 1.5605931E-03 0.000000 0.000000 0.000000 + Av 2018 5 9 23 0 0.1574014 0.000000 9.1783244E-07 1.5594898E-03 0.000000 0.000000 0.000000 + Av 2018 5 9 24 0 0.1572358 0.000000 9.0429296E-07 1.5583872E-03 0.000000 0.000000 0.000000 + Av 2018 5 10 1 0 0.1552815 0.000000 8.9095323E-07 1.5299057E-03 0.000000 0.000000 0.000000 + Av 2018 5 10 2 0 0.1539519 0.000000 8.7781029E-07 1.5288431E-03 0.000000 0.000000 0.000000 + Av 2018 5 10 3 0 0.1542681 0.000000 8.6486119E-07 1.5277812E-03 0.000000 0.000000 0.000000 + Av 2018 5 10 4 0 0.1540121 0.000000 8.5210314E-07 1.5267201E-03 0.000000 0.000000 0.000000 Av 2018 5 10 5 0 0.1448332 0.000000 8.3953330E-07 1.3798177E-03 0.000000 9.9999802E-03 6.6291797E-04 Av 2018 5 10 6 0 0.1059979 0.000000 8.2714888E-07 8.9985901E-04 0.000000 9.9999802E-03 2.8397322E-03 Av 2018 5 10 7 0 5.3193837E-02 0.000000 8.1494710E-07 4.1990075E-04 0.000000 0.000000 5.0165467E-03 @@ -3139,15 +3139,15 @@ Av 2018 5 10 17 0 2.7858060E-02 0.000000 7.0240395E-07 4.0935213E-04 0.000000 0.000000 5.0165467E-03 Av 2018 5 10 18 0 7.8323200E-02 0.000000 6.9204236E-07 8.8720047E-04 0.000000 0.000000 2.8397322E-03 Av 2018 5 10 19 0 0.1256979 0.000000 6.8183368E-07 1.3650494E-03 0.000000 0.000000 6.6291797E-04 - Av 2018 5 10 20 0 0.1516728 0.000000 6.7177558E-07 1.5098420E-03 0.000000 0.000000 0.000000 - Av 2018 5 10 21 0 0.1524516 0.000000 6.6186584E-07 1.5087932E-03 0.000000 0.000000 0.000000 - Av 2018 5 10 22 0 0.1520370 0.000000 6.5210230E-07 1.5077454E-03 0.000000 0.000000 0.000000 - Av 2018 5 10 23 0 0.1520375 0.000000 6.4248275E-07 1.5066982E-03 0.000000 0.000000 0.000000 - Av 2018 5 10 24 0 0.1518938 0.000000 6.3300513E-07 1.5056516E-03 0.000000 0.000000 0.000000 - Av 2018 5 11 1 0 0.1500257 0.000000 6.2366729E-07 1.4784866E-03 0.000000 0.000000 0.000000 - Av 2018 5 11 2 0 0.1487597 0.000000 6.1446724E-07 1.4774776E-03 0.000000 0.000000 0.000000 - Av 2018 5 11 3 0 0.1490616 0.000000 6.0540293E-07 1.4764692E-03 0.000000 0.000000 0.000000 - Av 2018 5 11 4 0 0.1488184 0.000000 5.9647226E-07 1.4754615E-03 0.000000 0.000000 0.000000 + Av 2018 5 10 20 0 0.1516728 0.000000 6.7177558E-07 1.5098420E-03 0.000000 0.000000 0.000000 + Av 2018 5 10 21 0 0.1524516 0.000000 6.6186584E-07 1.5087932E-03 0.000000 0.000000 0.000000 + Av 2018 5 10 22 0 0.1520370 0.000000 6.5210230E-07 1.5077454E-03 0.000000 0.000000 0.000000 + Av 2018 5 10 23 0 0.1520375 0.000000 6.4248275E-07 1.5066982E-03 0.000000 0.000000 0.000000 + Av 2018 5 10 24 0 0.1518938 0.000000 6.3300513E-07 1.5056516E-03 0.000000 0.000000 0.000000 + Av 2018 5 11 1 0 0.1500257 0.000000 6.2366729E-07 1.4784866E-03 0.000000 0.000000 0.000000 + Av 2018 5 11 2 0 0.1487597 0.000000 6.1446724E-07 1.4774776E-03 0.000000 0.000000 0.000000 + Av 2018 5 11 3 0 0.1490616 0.000000 6.0540293E-07 1.4764692E-03 0.000000 0.000000 0.000000 + Av 2018 5 11 4 0 0.1488184 0.000000 5.9647226E-07 1.4754615E-03 0.000000 0.000000 0.000000 Av 2018 5 11 5 0 0.1376735 0.000000 5.8767336E-07 1.3121117E-03 0.000000 0.000000 7.3792151E-04 Av 2018 5 11 6 0 9.6205622E-02 0.000000 5.7900428E-07 8.1150571E-04 0.000000 0.000000 3.0088292E-03 Av 2018 5 11 7 0 4.2366497E-02 0.000000 5.7046310E-07 3.1090039E-04 0.000000 0.000000 5.2797371E-03 @@ -3163,15 +3163,15 @@ Av 2018 5 11 17 0 2.0476611E-02 0.000000 4.9168278E-07 3.0088192E-04 0.000000 0.000000 5.2797371E-03 Av 2018 5 11 18 0 6.7578800E-02 0.000000 4.8442968E-07 7.9948350E-04 0.000000 0.000000 3.0088292E-03 Av 2018 5 11 19 0 0.1189056 0.000000 4.7728361E-07 1.2980858E-03 0.000000 0.000000 7.3792151E-04 - Av 2018 5 11 20 0 0.1460287 0.000000 4.7024290E-07 1.4594318E-03 0.000000 0.000000 0.000000 - Av 2018 5 11 21 0 0.1475403 0.000000 4.6330609E-07 1.4584358E-03 0.000000 0.000000 0.000000 - Av 2018 5 11 22 0 0.1468785 0.000000 4.5647158E-07 1.4574404E-03 0.000000 0.000000 0.000000 - Av 2018 5 11 23 0 0.1469725 0.000000 4.4973791E-07 1.4564458E-03 0.000000 0.000000 0.000000 - Av 2018 5 11 24 0 0.1468038 0.000000 4.4310357E-07 1.4554517E-03 0.000000 0.000000 0.000000 - Av 2018 5 12 1 0 0.1450331 0.000000 4.3656709E-07 1.4295343E-03 0.000000 0.000000 0.000000 - Av 2018 5 12 2 0 0.1438218 0.000000 4.3012705E-07 1.4285754E-03 0.000000 0.000000 0.000000 - Av 2018 5 12 3 0 0.1441118 0.000000 4.2378198E-07 1.4276170E-03 0.000000 0.000000 0.000000 - Av 2018 5 12 4 0 0.1438800 0.000000 4.1753052E-07 1.4266594E-03 0.000000 0.000000 0.000000 + Av 2018 5 11 20 0 0.1460287 0.000000 4.7024290E-07 1.4594318E-03 0.000000 0.000000 0.000000 + Av 2018 5 11 21 0 0.1475403 0.000000 4.6330609E-07 1.4584358E-03 0.000000 0.000000 0.000000 + Av 2018 5 11 22 0 0.1468785 0.000000 4.5647158E-07 1.4574404E-03 0.000000 0.000000 0.000000 + Av 2018 5 11 23 0 0.1469725 0.000000 4.4973791E-07 1.4564458E-03 0.000000 0.000000 0.000000 + Av 2018 5 11 24 0 0.1468038 0.000000 4.4310357E-07 1.4554517E-03 0.000000 0.000000 0.000000 + Av 2018 5 12 1 0 0.1450331 0.000000 4.3656709E-07 1.4295343E-03 0.000000 0.000000 0.000000 + Av 2018 5 12 2 0 0.1438218 0.000000 4.3012705E-07 1.4285754E-03 0.000000 0.000000 0.000000 + Av 2018 5 12 3 0 0.1441118 0.000000 4.2378198E-07 1.4276170E-03 0.000000 0.000000 0.000000 + Av 2018 5 12 4 0 0.1438800 0.000000 4.1753052E-07 1.4266594E-03 0.000000 0.000000 0.000000 Av 2018 5 12 5 0 0.1291680 0.000000 4.1137127E-07 1.2110828E-03 0.000000 0.000000 9.7554334E-04 Av 2018 5 12 6 0 7.7028736E-02 0.000000 4.0530290E-07 5.8806688E-04 0.000000 0.000000 3.8030869E-03 Av 2018 5 12 7 0 1.9812338E-02 0.000000 3.9932405E-07 0.000000 0.000000 0.000000 6.6306307E-03 @@ -3187,15 +3187,15 @@ Av 2018 5 12 17 0 2.3735047E-05 0.000000 3.4417789E-07 0.000000 0.000000 0.000000 6.6306307E-03 Av 2018 5 12 18 0 3.9202437E-02 0.000000 3.3910072E-07 5.7664013E-04 0.000000 0.000000 3.8030869E-03 Av 2018 5 12 19 0 0.1069158 0.000000 3.3409842E-07 1.1977516E-03 0.000000 0.000000 9.7554334E-04 - Av 2018 5 12 20 0 0.1400893 0.000000 3.2916995E-07 1.4114237E-03 0.000000 0.000000 0.000000 - Av 2018 5 12 21 0 0.1430661 0.000000 3.2431416E-07 1.4104769E-03 0.000000 0.000000 0.000000 - Av 2018 5 12 22 0 0.1419018 0.000000 3.1953002E-07 1.4095308E-03 0.000000 0.000000 0.000000 - Av 2018 5 12 23 0 0.1421774 0.000000 3.1481645E-07 1.4085852E-03 0.000000 0.000000 0.000000 - Av 2018 5 12 24 0 0.1419525 0.000000 3.1017242E-07 1.4076404E-03 0.000000 0.000000 0.000000 - Av 2018 5 13 1 0 0.1402853 0.000000 3.0559690E-07 1.3829061E-03 0.000000 0.000000 0.000000 - Av 2018 5 13 2 0 0.1391219 0.000000 3.0108885E-07 1.3819942E-03 0.000000 0.000000 0.000000 - Av 2018 5 13 3 0 0.1394020 0.000000 2.9664733E-07 1.3810828E-03 0.000000 0.000000 0.000000 - Av 2018 5 13 4 0 0.1391603 0.000000 0.000000 1.3801720E-03 0.000000 0.000000 0.000000 + Av 2018 5 12 20 0 0.1400893 0.000000 3.2916995E-07 1.4114237E-03 0.000000 0.000000 0.000000 + Av 2018 5 12 21 0 0.1430661 0.000000 3.2431416E-07 1.4104769E-03 0.000000 0.000000 0.000000 + Av 2018 5 12 22 0 0.1419018 0.000000 3.1953002E-07 1.4095308E-03 0.000000 0.000000 0.000000 + Av 2018 5 12 23 0 0.1421774 0.000000 3.1481645E-07 1.4085852E-03 0.000000 0.000000 0.000000 + Av 2018 5 12 24 0 0.1419525 0.000000 3.1017242E-07 1.4076404E-03 0.000000 0.000000 0.000000 + Av 2018 5 13 1 0 0.1402853 0.000000 3.0559690E-07 1.3829061E-03 0.000000 0.000000 0.000000 + Av 2018 5 13 2 0 0.1391219 0.000000 3.0108885E-07 1.3819942E-03 0.000000 0.000000 0.000000 + Av 2018 5 13 3 0 0.1394020 0.000000 2.9664733E-07 1.3810828E-03 0.000000 0.000000 0.000000 + Av 2018 5 13 4 0 0.1391603 0.000000 0.000000 1.3801720E-03 0.000000 0.000000 0.000000 Av 2018 5 13 5 0 0.1191772 0.000000 0.000000 1.0875959E-03 0.000000 0.000000 1.3257539E-03 Av 2018 5 13 6 0 5.1516153E-02 0.000000 0.000000 2.8701487E-04 0.000000 0.000000 4.9606240E-03 Av 2018 5 13 7 0 1.9206273E-03 0.000000 0.000000 0.000000 0.000000 0.000000 8.5954946E-03 @@ -3211,15 +3211,15 @@ Av 2018 5 13 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 8.5954946E-03 Av 2018 5 13 18 0 1.8762602E-02 0.000000 0.000000 2.7614692E-04 0.000000 0.000000 4.9606240E-03 Av 2018 5 13 19 0 8.5217729E-02 0.000000 0.000000 1.0749165E-03 0.000000 0.000000 1.3257539E-03 - 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Av 2018 5 29 20 0 8.1767283E-02 0.000000 0.000000 8.5829210E-04 0.000000 0.000000 0.000000 - Av 2018 5 29 21 0 8.8170648E-02 0.000000 0.000000 8.5784751E-04 0.000000 0.000000 0.000000 - Av 2018 5 29 22 0 8.5883752E-02 0.000000 0.000000 8.5740321E-04 0.000000 0.000000 0.000000 - Av 2018 5 29 23 0 8.6618572E-02 0.000000 0.000000 8.5695914E-04 0.000000 0.000000 0.000000 - Av 2018 5 29 24 0 8.6302727E-02 0.000000 0.000000 8.5651525E-04 0.000000 0.000000 0.000000 - Av 2018 5 30 1 0 8.5593194E-02 0.000000 0.000000 8.4489986E-04 0.000000 0.000000 0.000000 - Av 2018 5 30 2 0 8.5021362E-02 0.000000 0.000000 8.4446796E-04 0.000000 0.000000 0.000000 - Av 2018 5 30 3 0 8.5161515E-02 0.000000 0.000000 8.4403623E-04 0.000000 0.000000 0.000000 - Av 2018 5 30 4 0 8.5054129E-02 0.000000 0.000000 8.4360479E-04 0.000000 0.000000 0.000000 + Av 2018 5 29 20 0 8.1767283E-02 0.000000 0.000000 8.5829210E-04 0.000000 0.000000 0.000000 + Av 2018 5 29 21 0 8.8170648E-02 0.000000 0.000000 8.5784751E-04 0.000000 0.000000 0.000000 + Av 2018 5 29 22 0 8.5883752E-02 0.000000 0.000000 8.5740321E-04 0.000000 0.000000 0.000000 + Av 2018 5 29 23 0 8.6618572E-02 0.000000 0.000000 8.5695914E-04 0.000000 0.000000 0.000000 + Av 2018 5 29 24 0 8.6302727E-02 0.000000 0.000000 8.5651525E-04 0.000000 0.000000 0.000000 + Av 2018 5 30 1 0 8.5593194E-02 0.000000 0.000000 8.4489986E-04 0.000000 0.000000 0.000000 + Av 2018 5 30 2 0 8.5021362E-02 0.000000 0.000000 8.4446796E-04 0.000000 0.000000 0.000000 + Av 2018 5 30 3 0 8.5161515E-02 0.000000 0.000000 8.4403623E-04 0.000000 0.000000 0.000000 + Av 2018 5 30 4 0 8.5054129E-02 0.000000 0.000000 8.4360479E-04 0.000000 0.000000 0.000000 Av 2018 5 30 5 0 6.3991241E-02 0.000000 0.000000 5.3477695E-04 0.000000 0.000000 1.4018026E-03 Av 2018 5 30 6 0 2.1458026E-02 0.000000 0.000000 4.9588096E-05 0.000000 0.000000 3.6052472E-03 Av 2018 5 30 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.8086915E-03 @@ -3619,15 +3619,15 @@ Av 2018 5 30 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.8086915E-03 Av 2018 5 30 18 0 3.0189597E-03 0.000000 0.000000 4.4432876E-05 0.000000 0.000000 3.6052472E-03 Av 2018 5 30 19 0 3.7871927E-02 0.000000 0.000000 5.2876252E-04 0.000000 0.000000 1.4018026E-03 - Av 2018 5 30 20 0 7.9585366E-02 0.000000 0.000000 8.3673111E-04 0.000000 0.000000 0.000000 - Av 2018 5 30 21 0 8.6000577E-02 0.000000 0.000000 8.3630340E-04 0.000000 0.000000 0.000000 - Av 2018 5 30 22 0 8.3711848E-02 0.000000 0.000000 8.3587586E-04 0.000000 0.000000 0.000000 - Av 2018 5 30 23 0 8.4449574E-02 0.000000 0.000000 8.3544856E-04 0.000000 0.000000 0.000000 - Av 2018 5 30 24 0 8.4135011E-02 0.000000 0.000000 8.3502149E-04 0.000000 0.000000 0.000000 - Av 2018 5 31 1 0 8.3459064E-02 0.000000 0.000000 8.2389021E-04 0.000000 0.000000 0.000000 - Av 2018 5 31 2 0 8.2909539E-02 0.000000 0.000000 8.2347449E-04 0.000000 0.000000 0.000000 - Av 2018 5 31 3 0 8.3044134E-02 0.000000 0.000000 8.2305889E-04 0.000000 0.000000 0.000000 - Av 2018 5 31 4 0 8.2940876E-02 0.000000 0.000000 8.2264357E-04 0.000000 0.000000 0.000000 + Av 2018 5 30 20 0 7.9585366E-02 0.000000 0.000000 8.3673111E-04 0.000000 0.000000 0.000000 + Av 2018 5 30 21 0 8.6000577E-02 0.000000 0.000000 8.3630340E-04 0.000000 0.000000 0.000000 + Av 2018 5 30 22 0 8.3711848E-02 0.000000 0.000000 8.3587586E-04 0.000000 0.000000 0.000000 + Av 2018 5 30 23 0 8.4449574E-02 0.000000 0.000000 8.3544856E-04 0.000000 0.000000 0.000000 + Av 2018 5 30 24 0 8.4135011E-02 0.000000 0.000000 8.3502149E-04 0.000000 0.000000 0.000000 + Av 2018 5 31 1 0 8.3459064E-02 0.000000 0.000000 8.2389021E-04 0.000000 0.000000 0.000000 + Av 2018 5 31 2 0 8.2909539E-02 0.000000 0.000000 8.2347449E-04 0.000000 0.000000 0.000000 + Av 2018 5 31 3 0 8.3044134E-02 0.000000 0.000000 8.2305889E-04 0.000000 0.000000 0.000000 + Av 2018 5 31 4 0 8.2940876E-02 0.000000 0.000000 8.2264357E-04 0.000000 0.000000 0.000000 Av 2018 5 31 5 0 6.1594702E-02 0.000000 0.000000 5.0965254E-04 0.000000 0.000000 1.4207994E-03 Av 2018 5 31 6 0 2.0118376E-02 0.000000 0.000000 2.6740483E-05 0.000000 0.000000 3.6139684E-03 Av 2018 5 31 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.8071371E-03 @@ -3643,15 +3643,15 @@ Av 2018 5 31 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.8071371E-03 Av 2018 5 31 18 0 1.4796620E-03 0.000000 0.000000 2.1777581E-05 0.000000 0.000000 3.6139684E-03 Av 2018 5 31 19 0 3.5801861E-02 0.000000 0.000000 5.0386251E-04 0.000000 4.9999900E-02 1.4207994E-03 - Av 2018 5 31 20 0 7.7832386E-02 0.000000 0.000000 8.1602641E-04 0.000000 0.000000 0.000000 - Av 2018 5 31 21 0 8.4431328E-02 0.000000 0.000000 8.1561459E-04 0.000000 9.9999802E-03 0.000000 - Av 2018 5 31 22 0 8.2080871E-02 0.000000 0.000000 8.1520301E-04 0.000000 0.000000 0.000000 - Av 2018 5 31 23 0 8.2208559E-02 0.000000 0.000000 8.1479165E-04 0.000000 0.000000 0.000000 - Av 2018 5 31 24 0 8.2108274E-02 0.000000 0.000000 8.1438047E-04 0.000000 0.000000 0.000000 - Av 2018 6 1 1 0 8.1390291E-02 0.000000 0.000000 8.0371124E-04 0.000000 0.000000 0.000000 - Av 2018 6 1 2 0 8.0887817E-02 0.000000 0.000000 8.0331072E-04 0.000000 0.000000 0.000000 - Av 2018 6 1 3 0 8.1008121E-02 0.000000 0.000000 8.0291042E-04 0.000000 0.000000 0.000000 - Av 2018 6 1 4 0 8.0911905E-02 0.000000 0.000000 8.0251036E-04 0.000000 0.000000 0.000000 + Av 2018 5 31 20 0 7.7832386E-02 0.000000 0.000000 8.1602641E-04 0.000000 0.000000 0.000000 + Av 2018 5 31 21 0 8.4431328E-02 0.000000 0.000000 8.1561459E-04 0.000000 9.9999802E-03 0.000000 + Av 2018 5 31 22 0 8.2080871E-02 0.000000 0.000000 8.1520301E-04 0.000000 0.000000 0.000000 + Av 2018 5 31 23 0 8.2208559E-02 0.000000 0.000000 8.1479165E-04 0.000000 0.000000 0.000000 + Av 2018 5 31 24 0 8.2108274E-02 0.000000 0.000000 8.1438047E-04 0.000000 0.000000 0.000000 + Av 2018 6 1 1 0 8.1390291E-02 0.000000 0.000000 8.0371124E-04 0.000000 0.000000 0.000000 + Av 2018 6 1 2 0 8.0887817E-02 0.000000 0.000000 8.0331072E-04 0.000000 0.000000 0.000000 + Av 2018 6 1 3 0 8.1008121E-02 0.000000 0.000000 8.0291042E-04 0.000000 0.000000 0.000000 + Av 2018 6 1 4 0 8.0911905E-02 0.000000 0.000000 8.0251036E-04 0.000000 0.000000 0.000000 Av 2018 6 1 5 0 5.6935456E-02 0.000000 0.000000 4.5096956E-04 0.000000 0.000000 1.5960950E-03 Av 2018 6 1 6 0 1.6474694E-02 0.000000 0.000000 0.000000 0.000000 0.000000 4.0386668E-03 Av 2018 6 1 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.4812386E-03 @@ -3667,15 +3667,15 @@ Av 2018 6 1 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.4812386E-03 Av 2018 6 1 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.0386668E-03 Av 2018 6 1 19 0 3.0261852E-02 0.000000 0.000000 4.4539222E-04 0.000000 0.000000 1.5960950E-03 - 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Av 2018 6 4 20 0 6.7167111E-02 0.000000 0.000000 7.4097083E-04 0.000000 0.000000 0.000000 - Av 2018 6 4 21 0 7.7310666E-02 0.000000 0.000000 7.4061489E-04 0.000000 0.000000 0.000000 - Av 2018 6 4 22 0 7.3735312E-02 0.000000 0.000000 7.4025913E-04 0.000000 0.000000 0.000000 - Av 2018 6 4 23 0 7.4930161E-02 0.000000 0.000000 7.3990354E-04 0.000000 0.000000 0.000000 - Av 2018 6 4 24 0 7.4466392E-02 0.000000 0.000000 7.3954812E-04 0.000000 0.000000 0.000000 - Av 2018 6 5 1 0 7.3990643E-02 0.000000 0.000000 7.3052809E-04 0.000000 0.000000 0.000000 - Av 2018 6 5 2 0 7.3519640E-02 0.000000 0.000000 7.3018135E-04 0.000000 0.000000 0.000000 - Av 2018 6 5 3 0 7.3636301E-02 0.000000 0.000000 7.2983472E-04 0.000000 0.000000 0.000000 - Av 2018 6 5 4 0 7.3548645E-02 0.000000 0.000000 7.2948833E-04 0.000000 0.000000 0.000000 + Av 2018 6 4 20 0 6.7167111E-02 0.000000 0.000000 7.4097083E-04 0.000000 0.000000 0.000000 + Av 2018 6 4 21 0 7.7310666E-02 0.000000 0.000000 7.4061489E-04 0.000000 0.000000 0.000000 + Av 2018 6 4 22 0 7.3735312E-02 0.000000 0.000000 7.4025913E-04 0.000000 0.000000 0.000000 + Av 2018 6 4 23 0 7.4930161E-02 0.000000 0.000000 7.3990354E-04 0.000000 0.000000 0.000000 + Av 2018 6 4 24 0 7.4466392E-02 0.000000 0.000000 7.3954812E-04 0.000000 0.000000 0.000000 + Av 2018 6 5 1 0 7.3990643E-02 0.000000 0.000000 7.3052809E-04 0.000000 0.000000 0.000000 + Av 2018 6 5 2 0 7.3519640E-02 0.000000 0.000000 7.3018135E-04 0.000000 0.000000 0.000000 + Av 2018 6 5 3 0 7.3636301E-02 0.000000 0.000000 7.2983472E-04 0.000000 0.000000 0.000000 + Av 2018 6 5 4 0 7.3548645E-02 0.000000 0.000000 7.2948833E-04 0.000000 0.000000 0.000000 Av 2018 6 5 5 0 4.7468733E-02 0.000000 0.000000 3.4703303E-04 0.000000 0.000000 1.7368592E-03 Av 2018 6 5 6 0 1.0689092E-02 0.000000 0.000000 0.000000 0.000000 0.000000 4.2416528E-03 Av 2018 6 5 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.7464462E-03 @@ -3763,15 +3763,15 @@ Av 2018 6 5 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.7464462E-03 Av 2018 6 5 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.2416528E-03 Av 2018 6 5 19 0 2.3250680E-02 0.000000 0.000000 3.4220220E-04 0.000000 0.000000 1.7368592E-03 - Av 2018 6 5 20 0 6.4355657E-02 0.000000 0.000000 7.2396739E-04 0.000000 0.000000 0.000000 - Av 2018 6 5 21 0 7.5978503E-02 0.000000 0.000000 7.2362373E-04 0.000000 0.000000 0.000000 - Av 2018 6 5 22 0 7.1890444E-02 0.000000 0.000000 7.2328025E-04 0.000000 0.000000 0.000000 - Av 2018 6 5 23 0 7.3265232E-02 0.000000 0.000000 7.2293688E-04 0.000000 0.000000 0.000000 - Av 2018 6 5 24 0 7.2740562E-02 0.000000 0.000000 7.2259374E-04 0.000000 0.000000 0.000000 - Av 2018 6 6 1 0 7.2311774E-02 0.000000 0.000000 7.1394112E-04 0.000000 0.000000 0.000000 - Av 2018 6 6 2 0 7.1850210E-02 0.000000 0.000000 7.1360607E-04 0.000000 0.000000 0.000000 - Av 2018 6 6 3 0 7.1965188E-02 0.000000 0.000000 7.1327126E-04 0.000000 0.000000 0.000000 - Av 2018 6 6 4 0 7.1879722E-02 0.000000 0.000000 7.1293657E-04 0.000000 0.000000 0.000000 + Av 2018 6 5 20 0 6.4355657E-02 0.000000 0.000000 7.2396739E-04 0.000000 0.000000 0.000000 + Av 2018 6 5 21 0 7.5978503E-02 0.000000 0.000000 7.2362373E-04 0.000000 0.000000 0.000000 + Av 2018 6 5 22 0 7.1890444E-02 0.000000 0.000000 7.2328025E-04 0.000000 0.000000 0.000000 + Av 2018 6 5 23 0 7.3265232E-02 0.000000 0.000000 7.2293688E-04 0.000000 0.000000 0.000000 + Av 2018 6 5 24 0 7.2740562E-02 0.000000 0.000000 7.2259374E-04 0.000000 0.000000 0.000000 + Av 2018 6 6 1 0 7.2311774E-02 0.000000 0.000000 7.1394112E-04 0.000000 0.000000 0.000000 + Av 2018 6 6 2 0 7.1850210E-02 0.000000 0.000000 7.1360607E-04 0.000000 0.000000 0.000000 + Av 2018 6 6 3 0 7.1965188E-02 0.000000 0.000000 7.1327126E-04 0.000000 0.000000 0.000000 + Av 2018 6 6 4 0 7.1879722E-02 0.000000 0.000000 7.1293657E-04 0.000000 0.000000 0.000000 Av 2018 6 6 5 0 4.1637421E-02 0.000000 0.000000 2.6943733E-04 0.000000 0.000000 2.0143851E-03 Av 2018 6 6 6 0 5.6922110E-03 0.000000 0.000000 0.000000 0.000000 0.000000 4.8839408E-03 Av 2018 6 6 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.7534965E-03 @@ -3787,15 +3787,15 @@ Av 2018 6 6 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.7534965E-03 Av 2018 6 6 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.8839408E-03 Av 2018 6 6 19 0 1.7989622E-02 0.000000 0.000000 2.6477023E-04 0.000000 0.000000 2.0143851E-03 - Av 2018 6 6 20 0 5.9812032E-02 0.000000 0.000000 7.0760277E-04 0.000000 0.000000 0.000000 - Av 2018 6 6 21 0 7.5335383E-02 0.000000 0.000000 7.0727069E-04 0.000000 0.000000 0.000000 - Av 2018 6 6 22 0 6.9892660E-02 0.000000 0.000000 7.0693879E-04 0.000000 0.000000 0.000000 - Av 2018 6 6 23 0 7.1740046E-02 0.000000 0.000000 7.0660713E-04 0.000000 0.000000 0.000000 - Av 2018 6 6 24 0 7.1052641E-02 0.000000 0.000000 7.0627558E-04 0.000000 0.000000 0.000000 - Av 2018 6 7 1 0 7.0705093E-02 0.000000 0.000000 6.9797412E-04 0.000000 0.000000 0.000000 - Av 2018 6 7 2 0 7.0239902E-02 0.000000 0.000000 6.9765031E-04 0.000000 0.000000 0.000000 - Av 2018 6 7 3 0 7.0357665E-02 0.000000 0.000000 6.9732667E-04 0.000000 0.000000 0.000000 - Av 2018 6 7 4 0 7.0272744E-02 0.000000 0.000000 6.9700310E-04 0.000000 0.000000 0.000000 + Av 2018 6 6 20 0 5.9812032E-02 0.000000 0.000000 7.0760277E-04 0.000000 0.000000 0.000000 + Av 2018 6 6 21 0 7.5335383E-02 0.000000 0.000000 7.0727069E-04 0.000000 0.000000 0.000000 + Av 2018 6 6 22 0 6.9892660E-02 0.000000 0.000000 7.0693879E-04 0.000000 0.000000 0.000000 + Av 2018 6 6 23 0 7.1740046E-02 0.000000 0.000000 7.0660713E-04 0.000000 0.000000 0.000000 + Av 2018 6 6 24 0 7.1052641E-02 0.000000 0.000000 7.0627558E-04 0.000000 0.000000 0.000000 + Av 2018 6 7 1 0 7.0705093E-02 0.000000 0.000000 6.9797412E-04 0.000000 0.000000 0.000000 + Av 2018 6 7 2 0 7.0239902E-02 0.000000 0.000000 6.9765031E-04 0.000000 0.000000 0.000000 + Av 2018 6 7 3 0 7.0357665E-02 0.000000 0.000000 6.9732667E-04 0.000000 0.000000 0.000000 + Av 2018 6 7 4 0 7.0272744E-02 0.000000 0.000000 6.9700310E-04 0.000000 0.000000 0.000000 Av 2018 6 7 5 0 4.0136658E-02 0.000000 0.000000 2.5503396E-04 0.000000 0.000000 2.0074809E-03 Av 2018 6 7 6 0 4.9945093E-03 0.000000 0.000000 0.000000 0.000000 0.000000 4.8350245E-03 Av 2018 6 7 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.6625678E-03 @@ -3811,15 +3811,15 @@ Av 2018 6 7 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.6625678E-03 Av 2018 6 7 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.8350245E-03 Av 2018 6 7 19 0 1.7021574E-02 0.000000 0.000000 2.5052257E-04 0.000000 0.000000 2.0074809E-03 - Av 2018 6 7 20 0 5.8110081E-02 0.000000 0.000000 6.9184724E-04 0.000000 0.000000 0.000000 - Av 2018 6 7 21 0 7.3786914E-02 0.000000 0.000000 6.9152622E-04 0.000000 0.000000 0.000000 - Av 2018 6 7 22 0 6.8292335E-02 0.000000 0.000000 6.9120544E-04 0.000000 0.000000 0.000000 - Av 2018 6 7 23 0 7.0159271E-02 0.000000 0.000000 6.9088477E-04 0.000000 0.000000 0.000000 - Av 2018 6 7 24 0 6.9466546E-02 0.000000 0.000000 6.9056422E-04 0.000000 0.000000 0.000000 - Av 2018 6 8 1 0 6.9144413E-02 0.000000 0.000000 6.8259850E-04 0.000000 0.000000 0.000000 - Av 2018 6 8 2 0 6.8693921E-02 0.000000 0.000000 6.8228535E-04 0.000000 0.000000 0.000000 - Av 2018 6 8 3 0 6.8808004E-02 0.000000 0.000000 6.8197231E-04 0.000000 0.000000 0.000000 - Av 2018 6 8 4 0 6.8725809E-02 0.000000 0.000000 6.8165944E-04 0.000000 0.000000 0.000000 + Av 2018 6 7 20 0 5.8110081E-02 0.000000 0.000000 6.9184724E-04 0.000000 0.000000 0.000000 + Av 2018 6 7 21 0 7.3786914E-02 0.000000 0.000000 6.9152622E-04 0.000000 0.000000 0.000000 + Av 2018 6 7 22 0 6.8292335E-02 0.000000 0.000000 6.9120544E-04 0.000000 0.000000 0.000000 + Av 2018 6 7 23 0 7.0159271E-02 0.000000 0.000000 6.9088477E-04 0.000000 0.000000 0.000000 + Av 2018 6 7 24 0 6.9466546E-02 0.000000 0.000000 6.9056422E-04 0.000000 0.000000 0.000000 + Av 2018 6 8 1 0 6.9144413E-02 0.000000 0.000000 6.8259850E-04 0.000000 0.000000 0.000000 + Av 2018 6 8 2 0 6.8693921E-02 0.000000 0.000000 6.8228535E-04 0.000000 0.000000 0.000000 + Av 2018 6 8 3 0 6.8808004E-02 0.000000 0.000000 6.8197231E-04 0.000000 0.000000 0.000000 + Av 2018 6 8 4 0 6.8725809E-02 0.000000 0.000000 6.8165944E-04 0.000000 0.000000 0.000000 Av 2018 6 8 5 0 4.1494481E-02 0.000000 0.000000 2.8226644E-04 0.000000 0.000000 1.8140011E-03 Av 2018 6 8 6 0 7.1259579E-03 0.000000 0.000000 0.000000 0.000000 0.000000 4.3426729E-03 Av 2018 6 8 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.8713441E-03 @@ -3835,15 +3835,15 @@ Av 2018 6 8 17 0 4.2100519E-02 0.000000 0.000000 0.000000 6.1963312E-03 3.9999921E-02 6.8713441E-03 Av 2018 6 8 18 0 0.1615182 3.9000067E-08 0.000000 0.000000 1.9494561E-02 2.9999940E-02 4.3426729E-03 Av 2018 6 8 19 0 0.1591740 4.3510241E-08 0.000000 2.8293705E-04 9.0062227E-03 9.9999802E-03 1.8140011E-03 - Av 2018 6 8 20 0 0.2364056 8.8738830E-07 0.000000 6.9043302E-04 2.3796607E-02 2.9999940E-02 0.000000 - Av 2018 6 8 21 0 0.2137733 0.000000 0.000000 6.9753476E-04 5.6085959E-03 0.000000 0.000000 - Av 2018 6 8 22 0 7.0916757E-02 0.000000 0.000000 6.9720991E-04 1.8214205E-03 0.000000 0.000000 - Av 2018 6 8 23 0 8.7642670E-02 0.000000 0.000000 6.9688517E-04 7.6603488E-04 0.000000 0.000000 - Av 2018 6 8 24 0 7.2008014E-02 0.000000 0.000000 6.9656066E-04 3.8277119E-04 0.000000 0.000000 - Av 2018 6 9 1 0 7.3134139E-02 0.000000 0.000000 6.8847445E-04 2.1577156E-04 0.000000 0.000000 - Av 2018 6 9 2 0 7.0473254E-02 0.000000 0.000000 6.8815745E-04 1.3280618E-04 0.000000 0.000000 - Av 2018 6 9 3 0 7.0482805E-02 0.000000 0.000000 6.8784051E-04 8.7344350E-05 0.000000 0.000000 - Av 2018 6 9 4 0 6.9945008E-02 0.000000 0.000000 6.8752375E-04 6.0478458E-05 0.000000 0.000000 + Av 2018 6 8 20 0 0.2364056 8.8738830E-07 0.000000 6.9043302E-04 2.3796607E-02 2.9999940E-02 0.000000 + Av 2018 6 8 21 0 0.2137733 0.000000 0.000000 6.9753476E-04 5.6085959E-03 0.000000 0.000000 + Av 2018 6 8 22 0 7.0916757E-02 0.000000 0.000000 6.9720991E-04 1.8214205E-03 0.000000 0.000000 + Av 2018 6 8 23 0 8.7642670E-02 0.000000 0.000000 6.9688517E-04 7.6603488E-04 0.000000 0.000000 + Av 2018 6 8 24 0 7.2008014E-02 0.000000 0.000000 6.9656066E-04 3.8277119E-04 0.000000 0.000000 + Av 2018 6 9 1 0 7.3134139E-02 0.000000 0.000000 6.8847445E-04 2.1577156E-04 0.000000 0.000000 + Av 2018 6 9 2 0 7.0473254E-02 0.000000 0.000000 6.8815745E-04 1.3280618E-04 0.000000 0.000000 + Av 2018 6 9 3 0 7.0482805E-02 0.000000 0.000000 6.8784051E-04 8.7344350E-05 0.000000 0.000000 + Av 2018 6 9 4 0 6.9945008E-02 0.000000 0.000000 6.8752375E-04 6.0478458E-05 0.000000 0.000000 Av 2018 6 9 5 0 4.5856819E-02 0.000000 0.000000 3.3626554E-04 4.3624972E-05 0.000000 1.5951892E-03 Av 2018 6 9 6 0 1.0897393E-02 0.000000 0.000000 0.000000 3.2530093E-05 0.000000 3.7979474E-03 Av 2018 6 9 7 0 1.1482347E-03 0.000000 0.000000 0.000000 1.6899654E-04 0.000000 6.0007055E-03 @@ -3859,15 +3859,15 @@ Av 2018 6 9 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 1.9999960E-02 6.0007055E-03 Av 2018 6 9 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.7979474E-03 Av 2018 6 9 19 0 2.2547184E-02 0.000000 0.000000 3.3184816E-04 0.000000 0.000000 1.5951892E-03 - Av 2018 6 9 20 0 6.1077617E-02 0.000000 0.000000 6.8247534E-04 0.000000 0.000000 0.000000 - Av 2018 6 9 21 0 7.2078377E-02 0.000000 0.000000 6.8216101E-04 0.000000 9.9999802E-03 0.000000 - Av 2018 6 9 22 0 6.8767220E-02 0.000000 0.000000 6.8184693E-04 0.000000 9.9999802E-03 0.000000 - Av 2018 6 9 23 0 6.9279477E-02 0.000000 0.000000 6.8153290E-04 0.000000 0.000000 0.000000 - Av 2018 6 9 24 0 6.8502098E-02 0.000000 0.000000 6.8121904E-04 0.000000 0.000000 0.000000 - Av 2018 6 10 1 0 6.8787783E-02 0.000000 0.000000 6.7345920E-04 0.000000 9.9999802E-03 0.000000 - Av 2018 6 10 2 0 6.9846004E-02 8.3658741E-10 0.000000 6.7338964E-04 0.000000 2.9999940E-02 0.000000 - Av 2018 6 10 3 0 6.8905517E-02 0.000000 0.000000 6.7333272E-04 0.000000 0.000000 0.000000 - Av 2018 6 10 4 0 6.7518309E-02 0.000000 0.000000 6.7302596E-04 0.000000 0.000000 0.000000 + Av 2018 6 9 20 0 6.1077617E-02 0.000000 0.000000 6.8247534E-04 0.000000 0.000000 0.000000 + Av 2018 6 9 21 0 7.2078377E-02 0.000000 0.000000 6.8216101E-04 0.000000 9.9999802E-03 0.000000 + Av 2018 6 9 22 0 6.8767220E-02 0.000000 0.000000 6.8184693E-04 0.000000 9.9999802E-03 0.000000 + Av 2018 6 9 23 0 6.9279477E-02 0.000000 0.000000 6.8153290E-04 0.000000 0.000000 0.000000 + Av 2018 6 9 24 0 6.8502098E-02 0.000000 0.000000 6.8121904E-04 0.000000 0.000000 0.000000 + Av 2018 6 10 1 0 6.8787783E-02 0.000000 0.000000 6.7345920E-04 0.000000 9.9999802E-03 0.000000 + Av 2018 6 10 2 0 6.9846004E-02 8.3658741E-10 0.000000 6.7338964E-04 0.000000 2.9999940E-02 0.000000 + Av 2018 6 10 3 0 6.8905517E-02 0.000000 0.000000 6.7333272E-04 0.000000 0.000000 0.000000 + Av 2018 6 10 4 0 6.7518309E-02 0.000000 0.000000 6.7302596E-04 0.000000 0.000000 0.000000 Av 2018 6 10 5 0 4.5602508E-02 0.000000 0.000000 3.4490900E-04 0.000000 0.000000 1.4900466E-03 Av 2018 6 10 6 0 1.1489602E-02 0.000000 0.000000 0.000000 0.000000 0.000000 3.5301372E-03 Av 2018 6 10 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.5702277E-03 @@ -3883,15 +3883,15 @@ Av 2018 6 10 17 0 3.4386937E-06 5.0610502E-08 0.000000 0.000000 0.000000 1.9999960E-02 5.5702277E-03 Av 2018 6 10 18 0 1.4382640E-02 2.5774565E-07 0.000000 0.000000 2.0978048E-03 1.9999960E-02 3.5301372E-03 Av 2018 6 10 19 0 0.1193005 3.3587403E-07 0.000000 3.5670013E-04 1.2507714E-02 1.9999960E-02 1.4900466E-03 - Av 2018 6 10 20 0 0.2368474 4.1101100E-07 0.000000 6.9367839E-04 1.7555369E-02 1.9999960E-02 0.000000 - Av 2018 6 10 21 0 0.1628683 0.000000 0.000000 6.9848879E-04 4.3205670E-03 0.000000 0.000000 - Av 2018 6 10 22 0 0.1241264 1.1772185E-07 0.000000 7.0084207E-04 8.2099922E-03 9.9999802E-03 0.000000 - Av 2018 6 10 23 0 0.1263427 0.000000 0.000000 7.0336828E-04 2.6153326E-03 0.000000 0.000000 - Av 2018 6 10 24 0 0.1212062 1.1828652E-07 0.000000 7.0572633E-04 7.5158197E-03 9.9999802E-03 0.000000 - Av 2018 6 11 1 0 0.1222034 0.000000 0.000000 7.0026319E-04 2.5302782E-03 0.000000 0.000000 - Av 2018 6 11 2 0 7.6566890E-02 0.000000 0.000000 6.9993833E-04 9.9060882E-04 0.000000 0.000000 - Av 2018 6 11 3 0 7.8402624E-02 0.000000 0.000000 6.9961359E-04 4.7148301E-04 0.000000 0.000000 - Av 2018 6 11 4 0 7.2734021E-02 0.000000 0.000000 6.9928897E-04 2.5674482E-04 0.000000 0.000000 + Av 2018 6 10 20 0 0.2368474 4.1101100E-07 0.000000 6.9367839E-04 1.7555369E-02 1.9999960E-02 0.000000 + Av 2018 6 10 21 0 0.1628683 0.000000 0.000000 6.9848879E-04 4.3205670E-03 0.000000 0.000000 + Av 2018 6 10 22 0 0.1241264 1.1772185E-07 0.000000 7.0084207E-04 8.2099922E-03 9.9999802E-03 0.000000 + Av 2018 6 10 23 0 0.1263427 0.000000 0.000000 7.0336828E-04 2.6153326E-03 0.000000 0.000000 + Av 2018 6 10 24 0 0.1212062 1.1828652E-07 0.000000 7.0572633E-04 7.5158197E-03 9.9999802E-03 0.000000 + Av 2018 6 11 1 0 0.1222034 0.000000 0.000000 7.0026319E-04 2.5302782E-03 0.000000 0.000000 + Av 2018 6 11 2 0 7.6566890E-02 0.000000 0.000000 6.9993833E-04 9.9060882E-04 0.000000 0.000000 + Av 2018 6 11 3 0 7.8402624E-02 0.000000 0.000000 6.9961359E-04 4.7148301E-04 0.000000 0.000000 + Av 2018 6 11 4 0 7.2734021E-02 0.000000 0.000000 6.9928897E-04 2.5674482E-04 0.000000 0.000000 Av 2018 6 11 5 0 4.4916999E-02 0.000000 0.000000 2.9451505E-04 1.5403905E-04 0.000000 1.8384067E-03 Av 2018 6 11 6 0 8.1744296E-03 0.000000 0.000000 0.000000 9.9353900E-05 0.000000 4.3363045E-03 Av 2018 6 11 7 0 4.6033517E-04 0.000000 0.000000 0.000000 6.7751876E-05 0.000000 6.8342024E-03 @@ -3907,15 +3907,15 @@ Av 2018 6 11 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.8342024E-03 Av 2018 6 11 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.3363045E-03 Av 2018 6 11 19 0 1.9703077E-02 0.000000 0.000000 2.8998876E-04 0.000000 0.000000 1.8384067E-03 - Av 2018 6 11 20 0 6.0013354E-02 0.000000 0.000000 6.9411605E-04 0.000000 0.000000 0.000000 - Av 2018 6 11 21 0 7.3433369E-02 0.000000 0.000000 6.9379399E-04 0.000000 0.000000 0.000000 - Av 2018 6 11 22 0 6.8723358E-02 0.000000 0.000000 6.9347210E-04 0.000000 0.000000 0.000000 - Av 2018 6 11 23 0 7.0317343E-02 0.000000 0.000000 6.9315039E-04 0.000000 0.000000 0.000000 - Av 2018 6 11 24 0 6.9719389E-02 0.000000 0.000000 6.9282879E-04 0.000000 0.000000 0.000000 - Av 2018 6 12 1 0 6.9362417E-02 0.000000 0.000000 6.8483653E-04 0.000000 0.000000 0.000000 - Av 2018 6 12 2 0 6.8922162E-02 0.000000 0.000000 6.8452227E-04 0.000000 0.000000 0.000000 - Av 2018 6 12 3 0 6.9032550E-02 0.000000 0.000000 6.8420824E-04 0.000000 0.000000 0.000000 - Av 2018 6 12 4 0 6.8951502E-02 0.000000 0.000000 6.8389426E-04 0.000000 0.000000 0.000000 + Av 2018 6 11 20 0 6.0013354E-02 0.000000 0.000000 6.9411605E-04 0.000000 0.000000 0.000000 + Av 2018 6 11 21 0 7.3433369E-02 0.000000 0.000000 6.9379399E-04 0.000000 0.000000 0.000000 + Av 2018 6 11 22 0 6.8723358E-02 0.000000 0.000000 6.9347210E-04 0.000000 0.000000 0.000000 + Av 2018 6 11 23 0 7.0317343E-02 0.000000 0.000000 6.9315039E-04 0.000000 0.000000 0.000000 + Av 2018 6 11 24 0 6.9719389E-02 0.000000 0.000000 6.9282879E-04 0.000000 0.000000 0.000000 + Av 2018 6 12 1 0 6.9362417E-02 0.000000 0.000000 6.8483653E-04 0.000000 0.000000 0.000000 + Av 2018 6 12 2 0 6.8922162E-02 0.000000 0.000000 6.8452227E-04 0.000000 0.000000 0.000000 + Av 2018 6 12 3 0 6.9032550E-02 0.000000 0.000000 6.8420824E-04 0.000000 0.000000 0.000000 + Av 2018 6 12 4 0 6.8951502E-02 0.000000 0.000000 6.8389426E-04 0.000000 0.000000 0.000000 Av 2018 6 12 5 0 3.8111873E-02 0.000000 0.000000 2.3160371E-04 0.000000 0.000000 2.0544401E-03 Av 2018 6 12 6 0 3.6308724E-03 0.000000 0.000000 0.000000 0.000000 0.000000 4.8270747E-03 Av 2018 6 12 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.5997096E-03 @@ -3931,15 +3931,15 @@ Av 2018 6 12 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.5997096E-03 Av 2018 6 12 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.8270747E-03 Av 2018 6 12 19 0 1.5438696E-02 0.000000 0.000000 2.2722586E-04 0.000000 0.000000 2.0544401E-03 - Av 2018 6 12 20 0 5.6197286E-02 0.000000 0.000000 6.7889103E-04 0.000000 0.000000 0.000000 - Av 2018 6 12 21 0 7.2692066E-02 0.000000 0.000000 6.7857956E-04 0.000000 0.000000 0.000000 - Av 2018 6 12 22 0 6.6914365E-02 0.000000 0.000000 6.7826820E-04 0.000000 0.000000 0.000000 - Av 2018 6 12 23 0 6.8881020E-02 0.000000 0.000000 6.7795697E-04 0.000000 0.000000 0.000000 - Av 2018 6 12 24 0 6.8154916E-02 0.000000 0.000000 6.7764596E-04 0.000000 0.000000 0.000000 - Av 2018 6 13 1 0 6.7865118E-02 0.000000 0.000000 6.6997582E-04 0.000000 0.000000 0.000000 - Av 2018 6 13 2 0 6.7424089E-02 0.000000 0.000000 6.6967180E-04 0.000000 0.000000 0.000000 - Av 2018 6 13 3 0 6.7536131E-02 0.000000 0.000000 6.6936784E-04 0.000000 0.000000 0.000000 - Av 2018 6 13 4 0 6.7455873E-02 0.000000 0.000000 6.6906406E-04 0.000000 0.000000 0.000000 + Av 2018 6 12 20 0 5.6197286E-02 0.000000 0.000000 6.7889103E-04 0.000000 0.000000 0.000000 + Av 2018 6 12 21 0 7.2692066E-02 0.000000 0.000000 6.7857956E-04 0.000000 0.000000 0.000000 + Av 2018 6 12 22 0 6.6914365E-02 0.000000 0.000000 6.7826820E-04 0.000000 0.000000 0.000000 + Av 2018 6 12 23 0 6.8881020E-02 0.000000 0.000000 6.7795697E-04 0.000000 0.000000 0.000000 + Av 2018 6 12 24 0 6.8154916E-02 0.000000 0.000000 6.7764596E-04 0.000000 0.000000 0.000000 + Av 2018 6 13 1 0 6.7865118E-02 0.000000 0.000000 6.6997582E-04 0.000000 0.000000 0.000000 + Av 2018 6 13 2 0 6.7424089E-02 0.000000 0.000000 6.6967180E-04 0.000000 0.000000 0.000000 + Av 2018 6 13 3 0 6.7536131E-02 0.000000 0.000000 6.6936784E-04 0.000000 0.000000 0.000000 + Av 2018 6 13 4 0 6.7455873E-02 0.000000 0.000000 6.6906406E-04 0.000000 0.000000 0.000000 Av 2018 6 13 5 0 3.9696682E-02 0.000000 0.000000 2.6191803E-04 0.000000 0.000000 1.8492835E-03 Av 2018 6 13 6 0 5.9631765E-03 0.000000 0.000000 0.000000 0.000000 0.000000 4.3303948E-03 Av 2018 6 13 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.8115061E-03 @@ -3955,15 +3955,15 @@ Av 2018 6 13 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.8115061E-03 Av 2018 6 13 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.3303948E-03 Av 2018 6 13 19 0 1.7507983E-02 0.000000 0.000000 2.5768150E-04 0.000000 0.000000 1.8492835E-03 - Av 2018 6 13 20 0 5.6550406E-02 0.000000 0.000000 6.6422235E-04 0.000000 0.000000 0.000000 - Av 2018 6 13 21 0 7.0576653E-02 0.000000 0.000000 6.6392089E-04 0.000000 0.000000 0.000000 - Av 2018 6 13 22 0 6.5658644E-02 0.000000 0.000000 6.6361960E-04 0.000000 0.000000 0.000000 - Av 2018 6 13 23 0 6.7327753E-02 0.000000 0.000000 6.6331844E-04 0.000000 0.000000 0.000000 - Av 2018 6 13 24 0 6.6706471E-02 0.000000 0.000000 6.6301739E-04 0.000000 0.000000 0.000000 - Av 2018 6 14 1 0 6.6401839E-02 0.000000 0.000000 6.5565540E-04 0.000000 0.000000 0.000000 - Av 2018 6 14 2 0 6.5987557E-02 0.000000 0.000000 6.5536104E-04 0.000000 0.000000 0.000000 - Av 2018 6 14 3 0 6.6091605E-02 0.000000 0.000000 6.5506675E-04 0.000000 0.000000 0.000000 - Av 2018 6 14 4 0 6.6015452E-02 0.000000 0.000000 6.5477268E-04 0.000000 0.000000 0.000000 + Av 2018 6 13 20 0 5.6550406E-02 0.000000 0.000000 6.6422235E-04 0.000000 0.000000 0.000000 + Av 2018 6 13 21 0 7.0576653E-02 0.000000 0.000000 6.6392089E-04 0.000000 0.000000 0.000000 + Av 2018 6 13 22 0 6.5658644E-02 0.000000 0.000000 6.6361960E-04 0.000000 0.000000 0.000000 + Av 2018 6 13 23 0 6.7327753E-02 0.000000 0.000000 6.6331844E-04 0.000000 0.000000 0.000000 + Av 2018 6 13 24 0 6.6706471E-02 0.000000 0.000000 6.6301739E-04 0.000000 0.000000 0.000000 + Av 2018 6 14 1 0 6.6401839E-02 0.000000 0.000000 6.5565540E-04 0.000000 0.000000 0.000000 + Av 2018 6 14 2 0 6.5987557E-02 0.000000 0.000000 6.5536104E-04 0.000000 0.000000 0.000000 + Av 2018 6 14 3 0 6.6091605E-02 0.000000 0.000000 6.5506675E-04 0.000000 0.000000 0.000000 + Av 2018 6 14 4 0 6.6015452E-02 0.000000 0.000000 6.5477268E-04 0.000000 0.000000 0.000000 Av 2018 6 14 5 0 3.6986485E-02 0.000000 0.000000 2.2900201E-04 0.000000 0.000000 1.9339848E-03 Av 2018 6 14 6 0 3.9737746E-03 0.000000 0.000000 0.000000 0.000000 0.000000 4.5157247E-03 Av 2018 6 14 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.0974650E-03 @@ -3979,15 +3979,15 @@ Av 2018 6 14 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.0974650E-03 Av 2018 6 14 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.5157247E-03 Av 2018 6 14 19 0 1.5280667E-02 0.000000 0.000000 2.2490000E-04 0.000000 0.000000 1.9339848E-03 - Av 2018 6 14 20 0 5.4136973E-02 0.000000 0.000000 6.5008464E-04 0.000000 0.000000 0.000000 - Av 2018 6 14 21 0 6.9495320E-02 0.000000 0.000000 6.4979278E-04 0.000000 0.000000 0.000000 - Av 2018 6 14 22 0 6.4115435E-02 0.000000 0.000000 6.4950099E-04 0.000000 0.000000 0.000000 - Av 2018 6 14 23 0 6.5946430E-02 0.000000 0.000000 6.4920943E-04 0.000000 0.000000 0.000000 - Av 2018 6 14 24 0 6.5270156E-02 0.000000 0.000000 6.4891792E-04 0.000000 0.000000 0.000000 - Av 2018 6 15 1 0 6.5005325E-02 0.000000 0.000000 6.4185075E-04 0.000000 0.000000 0.000000 - Av 2018 6 15 2 0 6.4597860E-02 0.000000 0.000000 6.4156560E-04 0.000000 0.000000 0.000000 - Av 2018 6 15 3 0 6.4700797E-02 0.000000 0.000000 6.4128049E-04 0.000000 0.000000 0.000000 - Av 2018 6 15 4 0 6.4626276E-02 0.000000 0.000000 6.4099563E-04 0.000000 0.000000 0.000000 + Av 2018 6 14 20 0 5.4136973E-02 0.000000 0.000000 6.5008464E-04 0.000000 0.000000 0.000000 + Av 2018 6 14 21 0 6.9495320E-02 0.000000 0.000000 6.4979278E-04 0.000000 0.000000 0.000000 + Av 2018 6 14 22 0 6.4115435E-02 0.000000 0.000000 6.4950099E-04 0.000000 0.000000 0.000000 + Av 2018 6 14 23 0 6.5946430E-02 0.000000 0.000000 6.4920943E-04 0.000000 0.000000 0.000000 + Av 2018 6 14 24 0 6.5270156E-02 0.000000 0.000000 6.4891792E-04 0.000000 0.000000 0.000000 + Av 2018 6 15 1 0 6.5005325E-02 0.000000 0.000000 6.4185075E-04 0.000000 0.000000 0.000000 + Av 2018 6 15 2 0 6.4597860E-02 0.000000 0.000000 6.4156560E-04 0.000000 0.000000 0.000000 + Av 2018 6 15 3 0 6.4700797E-02 0.000000 0.000000 6.4128049E-04 0.000000 0.000000 0.000000 + Av 2018 6 15 4 0 6.4626276E-02 0.000000 0.000000 6.4099563E-04 0.000000 0.000000 0.000000 Av 2018 6 15 5 0 3.3951178E-02 0.000000 0.000000 1.9106822E-04 0.000000 0.000000 2.0438300E-03 Av 2018 6 15 6 0 1.6330163E-03 0.000000 0.000000 0.000000 0.000000 0.000000 4.7608344E-03 Av 2018 6 15 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.4778385E-03 @@ -4003,15 +4003,15 @@ Av 2018 6 15 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.4778385E-03 Av 2018 6 15 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.7608344E-03 Av 2018 6 15 19 0 1.2711989E-02 0.000000 0.000000 1.8709432E-04 0.000000 0.000000 2.0438300E-03 - 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Av 2018 8 5 20 0 2.7107472E-02 0.000000 0.000000 2.9610514E-04 0.000000 0.000000 0.000000 - Av 2018 8 5 21 0 3.0805256E-02 0.000000 0.000000 2.9600898E-04 0.000000 0.000000 0.000000 - Av 2018 8 5 22 0 2.9506437E-02 0.000000 0.000000 2.9591285E-04 0.000000 0.000000 0.000000 - Av 2018 8 5 23 0 2.9944986E-02 0.000000 0.000000 2.9581675E-04 0.000000 0.000000 0.000000 - Av 2018 8 5 24 0 2.9779442E-02 0.000000 0.000000 2.9572067E-04 0.000000 0.000000 0.000000 - Av 2018 8 6 1 0 2.9764425E-02 0.000000 0.000000 2.9474855E-04 0.000000 0.000000 0.000000 - Av 2018 8 6 2 0 2.9697113E-02 0.000000 0.000000 2.9465312E-04 0.000000 0.000000 0.000000 - Av 2018 8 6 3 0 2.9707555E-02 0.000000 0.000000 2.9455774E-04 0.000000 0.000000 0.000000 - Av 2018 8 6 4 0 2.9690964E-02 0.000000 0.000000 2.9446237E-04 0.000000 0.000000 0.000000 + Av 2018 8 5 20 0 2.7107472E-02 0.000000 0.000000 2.9610514E-04 0.000000 0.000000 0.000000 + Av 2018 8 5 21 0 3.0805256E-02 0.000000 0.000000 2.9600898E-04 0.000000 0.000000 0.000000 + Av 2018 8 5 22 0 2.9506437E-02 0.000000 0.000000 2.9591285E-04 0.000000 0.000000 0.000000 + Av 2018 8 5 23 0 2.9944986E-02 0.000000 0.000000 2.9581675E-04 0.000000 0.000000 0.000000 + Av 2018 8 5 24 0 2.9779442E-02 0.000000 0.000000 2.9572067E-04 0.000000 0.000000 0.000000 + Av 2018 8 6 1 0 2.9764425E-02 0.000000 0.000000 2.9474855E-04 0.000000 0.000000 0.000000 + Av 2018 8 6 2 0 2.9697113E-02 0.000000 0.000000 2.9465312E-04 0.000000 0.000000 0.000000 + Av 2018 8 6 3 0 2.9707555E-02 0.000000 0.000000 2.9455774E-04 0.000000 0.000000 0.000000 + Av 2018 8 6 4 0 2.9690964E-02 0.000000 0.000000 2.9446237E-04 0.000000 0.000000 0.000000 Av 2018 8 6 5 0 2.1300344E-02 0.000000 0.000000 1.7128719E-04 0.000000 0.000000 5.5945379E-04 Av 2018 8 6 6 0 6.4554061E-03 0.000000 0.000000 0.000000 0.000000 0.000000 4.5103631E-03 Av 2018 8 6 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 8.4612733E-03 @@ -5251,15 +5251,15 @@ Av 2018 8 6 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 8.4612733E-03 Av 2018 8 6 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.5103631E-03 Av 2018 8 6 19 0 1.1547518E-02 0.000000 0.000000 1.6995572E-04 0.000000 0.000000 5.5945379E-04 - 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Av 2018 8 10 20 0 2.9598838E-02 0.000000 0.000000 2.8089978E-04 0.000000 0.000000 0.000000 - Av 2018 8 10 21 0 2.7873173E-02 0.000000 0.000000 2.8080985E-04 0.000000 0.000000 0.000000 - Av 2018 8 10 22 0 2.8460983E-02 0.000000 0.000000 2.8071995E-04 0.000000 0.000000 0.000000 - Av 2018 8 10 23 0 2.8244382E-02 0.000000 0.000000 2.8063005E-04 0.000000 0.000000 0.000000 - Av 2018 8 10 24 0 2.8307483E-02 0.000000 0.000000 2.8054020E-04 0.000000 0.000000 0.000000 - Av 2018 8 11 1 0 2.8224152E-02 0.000000 0.000000 2.7972652E-04 0.000000 0.000000 0.000000 - Av 2018 8 11 2 0 2.8191773E-02 0.000000 0.000000 2.7963720E-04 0.000000 0.000000 0.000000 - Av 2018 8 11 3 0 2.8190894E-02 0.000000 0.000000 2.7954788E-04 0.000000 0.000000 0.000000 - Av 2018 8 11 4 0 2.8179064E-02 0.000000 0.000000 2.7945859E-04 0.000000 0.000000 0.000000 + Av 2018 8 10 20 0 2.9598838E-02 0.000000 0.000000 2.8089978E-04 0.000000 0.000000 0.000000 + Av 2018 8 10 21 0 2.7873173E-02 0.000000 0.000000 2.8080985E-04 0.000000 0.000000 0.000000 + Av 2018 8 10 22 0 2.8460983E-02 0.000000 0.000000 2.8071995E-04 0.000000 0.000000 0.000000 + Av 2018 8 10 23 0 2.8244382E-02 0.000000 0.000000 2.8063005E-04 0.000000 0.000000 0.000000 + Av 2018 8 10 24 0 2.8307483E-02 0.000000 0.000000 2.8054020E-04 0.000000 0.000000 0.000000 + Av 2018 8 11 1 0 2.8224152E-02 0.000000 0.000000 2.7972652E-04 0.000000 0.000000 0.000000 + Av 2018 8 11 2 0 2.8191773E-02 0.000000 0.000000 2.7963720E-04 0.000000 0.000000 0.000000 + Av 2018 8 11 3 0 2.8190894E-02 0.000000 0.000000 2.7954788E-04 0.000000 0.000000 0.000000 + Av 2018 8 11 4 0 2.8179064E-02 0.000000 0.000000 2.7945859E-04 0.000000 0.000000 0.000000 Av 2018 8 11 5 0 2.6892936E-02 0.000000 0.000000 2.6060382E-04 0.000000 0.000000 8.5297768E-05 Av 2018 8 11 6 0 1.2804900E-02 0.000000 0.000000 0.000000 0.000000 0.000000 3.5460778E-03 Av 2018 8 11 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.0068575E-03 @@ -5371,15 +5371,15 @@ Av 2018 8 11 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.0068575E-03 Av 2018 8 11 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.5460778E-03 Av 2018 8 11 19 0 1.7621841E-02 0.000000 0.000000 2.5935727E-04 0.000000 0.000000 8.5297768E-05 - 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Av 2018 8 13 19 0 1.8518193E-02 0.000000 0.000000 2.7254972E-04 0.000000 0.000000 0.000000 - Av 2018 8 13 20 0 3.0591561E-02 0.000000 0.000000 2.7246310E-04 0.000000 0.000000 0.000000 - Av 2018 8 13 21 0 2.6381776E-02 0.000000 0.000000 2.7237652E-04 0.000000 0.000000 0.000000 - Av 2018 8 13 22 0 2.7833793E-02 0.000000 0.000000 2.7228997E-04 0.000000 0.000000 0.000000 - Av 2018 8 13 23 0 2.7317153E-02 0.000000 0.000000 2.7220344E-04 0.000000 0.000000 0.000000 - Av 2018 8 13 24 0 2.7485035E-02 0.000000 0.000000 2.7211691E-04 0.000000 0.000000 0.000000 - Av 2018 8 14 1 0 2.7371041E-02 0.000000 0.000000 2.7138481E-04 0.000000 0.000000 0.000000 - Av 2018 8 14 2 0 2.7355090E-02 0.000000 0.000000 2.7129878E-04 0.000000 0.000000 0.000000 - Av 2018 8 14 3 0 2.7348947E-02 0.000000 0.000000 2.7121278E-04 0.000000 0.000000 0.000000 - Av 2018 8 14 4 0 2.7339395E-02 0.000000 0.000000 2.7112677E-04 0.000000 0.000000 0.000000 - Av 2018 8 14 5 0 2.7331032E-02 0.000000 0.000000 2.7104083E-04 0.000000 0.000000 0.000000 + Av 2018 8 13 19 0 1.8518193E-02 0.000000 0.000000 2.7254972E-04 0.000000 0.000000 0.000000 + Av 2018 8 13 20 0 3.0591561E-02 0.000000 0.000000 2.7246310E-04 0.000000 0.000000 0.000000 + Av 2018 8 13 21 0 2.6381776E-02 0.000000 0.000000 2.7237652E-04 0.000000 0.000000 0.000000 + Av 2018 8 13 22 0 2.7833793E-02 0.000000 0.000000 2.7228997E-04 0.000000 0.000000 0.000000 + Av 2018 8 13 23 0 2.7317153E-02 0.000000 0.000000 2.7220344E-04 0.000000 0.000000 0.000000 + Av 2018 8 13 24 0 2.7485035E-02 0.000000 0.000000 2.7211691E-04 0.000000 0.000000 0.000000 + Av 2018 8 14 1 0 2.7371041E-02 0.000000 0.000000 2.7138481E-04 0.000000 0.000000 0.000000 + Av 2018 8 14 2 0 2.7355090E-02 0.000000 0.000000 2.7129878E-04 0.000000 0.000000 0.000000 + Av 2018 8 14 3 0 2.7348947E-02 0.000000 0.000000 2.7121278E-04 0.000000 0.000000 0.000000 + Av 2018 8 14 4 0 2.7339395E-02 0.000000 0.000000 2.7112677E-04 0.000000 0.000000 0.000000 + Av 2018 8 14 5 0 2.7331032E-02 0.000000 0.000000 2.7104083E-04 0.000000 0.000000 0.000000 Av 2018 8 14 6 0 1.3663269E-02 0.000000 0.000000 0.000000 0.000000 0.000000 4.4278651E-03 Av 2018 8 14 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 9.0798326E-03 Av 2018 8 14 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.3731800E-02 @@ -5442,17 +5442,17 @@ Av 2018 8 14 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.3731800E-02 Av 2018 8 14 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 9.0798326E-03 Av 2018 8 14 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.4278651E-03 - Av 2018 8 14 19 0 1.8334104E-02 0.000000 0.000000 2.6984030E-04 0.000000 0.000000 0.000000 - Av 2018 8 14 20 0 3.0287465E-02 0.000000 0.000000 2.6975476E-04 0.000000 0.000000 0.000000 - Av 2018 8 14 21 0 2.6119551E-02 0.000000 0.000000 2.6966922E-04 0.000000 0.000000 0.000000 - Av 2018 8 14 22 0 2.7557150E-02 0.000000 0.000000 2.6958372E-04 0.000000 0.000000 0.000000 - Av 2018 8 14 23 0 2.7045671E-02 0.000000 0.000000 2.6949827E-04 0.000000 0.000000 0.000000 - Av 2018 8 14 24 0 2.7211905E-02 0.000000 0.000000 2.6941282E-04 0.000000 0.000000 0.000000 - Av 2018 8 15 1 0 2.7100265E-02 0.000000 0.000000 2.6870589E-04 0.000000 0.000000 0.000000 - Av 2018 8 15 2 0 2.7085276E-02 0.000000 0.000000 2.6862090E-04 0.000000 0.000000 0.000000 - Av 2018 8 15 3 0 2.7078941E-02 0.000000 0.000000 2.6853592E-04 0.000000 0.000000 0.000000 - Av 2018 8 15 4 0 2.7069598E-02 0.000000 0.000000 2.6845100E-04 0.000000 0.000000 0.000000 - Av 2018 8 15 5 0 2.7061306E-02 0.000000 0.000000 2.6836607E-04 0.000000 0.000000 0.000000 + Av 2018 8 14 19 0 1.8334104E-02 0.000000 0.000000 2.6984030E-04 0.000000 0.000000 0.000000 + Av 2018 8 14 20 0 3.0287465E-02 0.000000 0.000000 2.6975476E-04 0.000000 0.000000 0.000000 + Av 2018 8 14 21 0 2.6119551E-02 0.000000 0.000000 2.6966922E-04 0.000000 0.000000 0.000000 + Av 2018 8 14 22 0 2.7557150E-02 0.000000 0.000000 2.6958372E-04 0.000000 0.000000 0.000000 + Av 2018 8 14 23 0 2.7045671E-02 0.000000 0.000000 2.6949827E-04 0.000000 0.000000 0.000000 + Av 2018 8 14 24 0 2.7211905E-02 0.000000 0.000000 2.6941282E-04 0.000000 0.000000 0.000000 + Av 2018 8 15 1 0 2.7100265E-02 0.000000 0.000000 2.6870589E-04 0.000000 0.000000 0.000000 + Av 2018 8 15 2 0 2.7085276E-02 0.000000 0.000000 2.6862090E-04 0.000000 0.000000 0.000000 + Av 2018 8 15 3 0 2.7078941E-02 0.000000 0.000000 2.6853592E-04 0.000000 0.000000 0.000000 + Av 2018 8 15 4 0 2.7069598E-02 0.000000 0.000000 2.6845100E-04 0.000000 0.000000 0.000000 + Av 2018 8 15 5 0 2.7061306E-02 0.000000 0.000000 2.6836607E-04 0.000000 0.000000 0.000000 Av 2018 8 15 6 0 1.3528441E-02 0.000000 0.000000 0.000000 0.000000 0.000000 3.9541298E-03 Av 2018 8 15 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 8.2189022E-03 Av 2018 8 15 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.2483675E-02 @@ -5466,17 +5466,17 @@ Av 2018 8 15 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.2483675E-02 Av 2018 8 15 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 8.2189022E-03 Av 2018 8 15 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.9541298E-03 - Av 2018 8 15 19 0 1.8153362E-02 0.000000 0.000000 2.6718015E-04 0.000000 0.000000 0.000000 - Av 2018 8 15 20 0 2.9988896E-02 0.000000 0.000000 2.6709563E-04 0.000000 0.000000 0.000000 - Av 2018 8 15 21 0 2.5862092E-02 0.000000 0.000000 2.6701114E-04 0.000000 0.000000 0.000000 - Av 2018 8 15 22 0 2.7285539E-02 0.000000 0.000000 2.6692668E-04 0.000000 0.000000 0.000000 - Av 2018 8 15 23 0 2.6779119E-02 0.000000 0.000000 2.6684225E-04 0.000000 0.000000 0.000000 - Av 2018 8 15 24 0 2.6943736E-02 0.000000 0.000000 2.6675785E-04 0.000000 0.000000 0.000000 - Av 2018 8 16 1 0 2.6834376E-02 0.000000 0.000000 2.6607516E-04 0.000000 0.000000 0.000000 - Av 2018 8 16 2 0 2.6820313E-02 0.000000 0.000000 2.6599120E-04 0.000000 0.000000 0.000000 - Av 2018 8 16 3 0 2.6813794E-02 0.000000 0.000000 2.6590723E-04 0.000000 0.000000 0.000000 - Av 2018 8 16 4 0 2.6804654E-02 0.000000 0.000000 2.6582333E-04 0.000000 0.000000 0.000000 - Av 2018 8 16 5 0 2.6796430E-02 0.000000 0.000000 2.6573942E-04 0.000000 0.000000 0.000000 + Av 2018 8 15 19 0 1.8153362E-02 0.000000 0.000000 2.6718015E-04 0.000000 0.000000 0.000000 + Av 2018 8 15 20 0 2.9988896E-02 0.000000 0.000000 2.6709563E-04 0.000000 0.000000 0.000000 + Av 2018 8 15 21 0 2.5862092E-02 0.000000 0.000000 2.6701114E-04 0.000000 0.000000 0.000000 + Av 2018 8 15 22 0 2.7285539E-02 0.000000 0.000000 2.6692668E-04 0.000000 0.000000 0.000000 + Av 2018 8 15 23 0 2.6779119E-02 0.000000 0.000000 2.6684225E-04 0.000000 0.000000 0.000000 + Av 2018 8 15 24 0 2.6943736E-02 0.000000 0.000000 2.6675785E-04 0.000000 0.000000 0.000000 + Av 2018 8 16 1 0 2.6834376E-02 0.000000 0.000000 2.6607516E-04 0.000000 0.000000 0.000000 + Av 2018 8 16 2 0 2.6820313E-02 0.000000 0.000000 2.6599120E-04 0.000000 0.000000 0.000000 + Av 2018 8 16 3 0 2.6813794E-02 0.000000 0.000000 2.6590723E-04 0.000000 0.000000 0.000000 + Av 2018 8 16 4 0 2.6804654E-02 0.000000 0.000000 2.6582333E-04 0.000000 0.000000 0.000000 + Av 2018 8 16 5 0 2.6796430E-02 0.000000 0.000000 2.6573942E-04 0.000000 0.000000 0.000000 Av 2018 8 16 6 0 1.3396037E-02 0.000000 0.000000 0.000000 0.000000 0.000000 3.5312304E-03 Av 2018 8 16 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.4447659E-03 Av 2018 8 16 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.1358301E-02 @@ -5490,17 +5490,17 @@ Av 2018 8 16 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.1358301E-02 Av 2018 8 16 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.4447659E-03 Av 2018 8 16 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.5312304E-03 - Av 2018 8 16 19 0 1.7975861E-02 0.000000 0.000000 2.6456770E-04 0.000000 0.000000 0.000000 - Av 2018 8 16 20 0 2.9695682E-02 0.000000 0.000000 2.6448420E-04 0.000000 0.000000 0.000000 - Av 2018 8 16 21 0 2.5609251E-02 0.000000 0.000000 2.6440073E-04 0.000000 0.000000 0.000000 - Av 2018 8 16 22 0 2.7018800E-02 0.000000 0.000000 2.6431729E-04 0.000000 0.000000 0.000000 - Av 2018 8 16 23 0 2.6517350E-02 0.000000 0.000000 2.6423388E-04 0.000000 0.000000 0.000000 - Av 2018 8 16 24 0 2.6680373E-02 0.000000 0.000000 2.6415047E-04 0.000000 0.000000 0.000000 - Av 2018 8 17 1 0 2.6573222E-02 0.000000 0.000000 2.6349112E-04 0.000000 0.000000 0.000000 - Av 2018 8 17 2 0 2.6560042E-02 0.000000 0.000000 2.6340815E-04 0.000000 0.000000 0.000000 - Av 2018 8 17 3 0 2.6553351E-02 0.000000 0.000000 2.6332520E-04 0.000000 0.000000 0.000000 - Av 2018 8 17 4 0 2.6544409E-02 0.000000 0.000000 2.6324228E-04 0.000000 0.000000 0.000000 - Av 2018 8 17 5 0 2.6536254E-02 0.000000 0.000000 2.6315940E-04 0.000000 0.000000 0.000000 + Av 2018 8 16 19 0 1.7975861E-02 0.000000 0.000000 2.6456770E-04 0.000000 0.000000 0.000000 + Av 2018 8 16 20 0 2.9695682E-02 0.000000 0.000000 2.6448420E-04 0.000000 0.000000 0.000000 + Av 2018 8 16 21 0 2.5609251E-02 0.000000 0.000000 2.6440073E-04 0.000000 0.000000 0.000000 + Av 2018 8 16 22 0 2.7018800E-02 0.000000 0.000000 2.6431729E-04 0.000000 0.000000 0.000000 + Av 2018 8 16 23 0 2.6517350E-02 0.000000 0.000000 2.6423388E-04 0.000000 0.000000 0.000000 + Av 2018 8 16 24 0 2.6680373E-02 0.000000 0.000000 2.6415047E-04 0.000000 0.000000 0.000000 + Av 2018 8 17 1 0 2.6573222E-02 0.000000 0.000000 2.6349112E-04 0.000000 0.000000 0.000000 + Av 2018 8 17 2 0 2.6560042E-02 0.000000 0.000000 2.6340815E-04 0.000000 0.000000 0.000000 + Av 2018 8 17 3 0 2.6553351E-02 0.000000 0.000000 2.6332520E-04 0.000000 0.000000 0.000000 + Av 2018 8 17 4 0 2.6544409E-02 0.000000 0.000000 2.6324228E-04 0.000000 0.000000 0.000000 + Av 2018 8 17 5 0 2.6536254E-02 0.000000 0.000000 2.6315940E-04 0.000000 0.000000 0.000000 Av 2018 8 17 6 0 1.3265985E-02 0.000000 0.000000 0.000000 0.000000 0.000000 2.8974102E-03 Av 2018 8 17 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.2001008E-03 Av 2018 8 17 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 9.5027918E-03 @@ -5514,17 +5514,17 @@ Av 2018 8 17 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 9.5027918E-03 Av 2018 8 17 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.2001008E-03 Av 2018 8 17 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.8974102E-03 - Av 2018 8 17 19 0 1.7801506E-02 0.000000 0.000000 2.6200156E-04 0.000000 0.000000 0.000000 - Av 2018 8 17 20 0 2.9407665E-02 0.000000 0.000000 2.6191905E-04 0.000000 0.000000 0.000000 - Av 2018 8 17 21 0 2.5360890E-02 0.000000 0.000000 2.6183657E-04 0.000000 0.000000 0.000000 - Av 2018 8 17 22 0 2.6756782E-02 0.000000 0.000000 2.6175412E-04 0.000000 0.000000 0.000000 - Av 2018 8 17 23 0 2.6260216E-02 0.000000 0.000000 2.6167170E-04 0.000000 0.000000 0.000000 - Av 2018 8 17 24 0 2.6421677E-02 0.000000 0.000000 2.6158927E-04 0.000000 0.000000 0.000000 - Av 2018 8 18 1 0 2.6316663E-02 0.000000 0.000000 2.6095239E-04 0.000000 0.000000 0.000000 - Av 2018 8 18 2 0 2.6304334E-02 0.000000 0.000000 2.6087041E-04 0.000000 0.000000 0.000000 - Av 2018 8 18 3 0 2.6297480E-02 0.000000 0.000000 2.6078842E-04 0.000000 0.000000 0.000000 - Av 2018 8 18 4 0 2.6288725E-02 0.000000 0.000000 2.6070650E-04 0.000000 0.000000 0.000000 - Av 2018 8 18 5 0 2.6280638E-02 0.000000 0.000000 2.6062457E-04 0.000000 0.000000 0.000000 + Av 2018 8 17 19 0 1.7801506E-02 0.000000 0.000000 2.6200156E-04 0.000000 0.000000 0.000000 + Av 2018 8 17 20 0 2.9407665E-02 0.000000 0.000000 2.6191905E-04 0.000000 0.000000 0.000000 + Av 2018 8 17 21 0 2.5360890E-02 0.000000 0.000000 2.6183657E-04 0.000000 0.000000 0.000000 + Av 2018 8 17 22 0 2.6756782E-02 0.000000 0.000000 2.6175412E-04 0.000000 0.000000 0.000000 + Av 2018 8 17 23 0 2.6260216E-02 0.000000 0.000000 2.6167170E-04 0.000000 0.000000 0.000000 + Av 2018 8 17 24 0 2.6421677E-02 0.000000 0.000000 2.6158927E-04 0.000000 0.000000 0.000000 + Av 2018 8 18 1 0 2.6316663E-02 0.000000 0.000000 2.6095239E-04 0.000000 0.000000 0.000000 + Av 2018 8 18 2 0 2.6304334E-02 0.000000 0.000000 2.6087041E-04 0.000000 0.000000 0.000000 + Av 2018 8 18 3 0 2.6297480E-02 0.000000 0.000000 2.6078842E-04 0.000000 0.000000 0.000000 + Av 2018 8 18 4 0 2.6288725E-02 0.000000 0.000000 2.6070650E-04 0.000000 0.000000 0.000000 + Av 2018 8 18 5 0 2.6280638E-02 0.000000 0.000000 2.6062457E-04 0.000000 0.000000 0.000000 Av 2018 8 18 6 0 1.3138208E-02 0.000000 0.000000 0.000000 0.000000 0.000000 2.9299501E-03 Av 2018 8 18 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.3684741E-03 Av 2018 8 18 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 9.8069981E-03 @@ -5538,17 +5538,17 @@ Av 2018 8 18 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 9.8069981E-03 Av 2018 8 18 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.3684741E-03 Av 2018 8 18 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.9299501E-03 - Av 2018 8 18 19 0 1.7630203E-02 0.000000 0.000000 2.5948032E-04 0.000000 0.000000 0.000000 - Av 2018 8 18 20 0 2.9124686E-02 0.000000 0.000000 2.5939877E-04 0.000000 0.000000 0.000000 - Av 2018 8 18 21 0 2.5116874E-02 0.000000 0.000000 2.5931728E-04 0.000000 0.000000 0.000000 - Av 2018 8 18 22 0 2.6499351E-02 0.000000 0.000000 2.5923579E-04 0.000000 0.000000 0.000000 - Av 2018 8 18 23 0 2.6007582E-02 0.000000 0.000000 2.5915433E-04 0.000000 0.000000 0.000000 - Av 2018 8 18 24 0 2.6167506E-02 0.000000 0.000000 2.5907290E-04 0.000000 0.000000 0.000000 - Av 2018 8 19 1 0 2.6064562E-02 0.000000 0.000000 2.5845764E-04 0.000000 0.000000 0.000000 - Av 2018 8 19 2 0 2.6053049E-02 0.000000 0.000000 2.5837659E-04 0.000000 0.000000 0.000000 - Av 2018 8 19 3 0 2.6046040E-02 0.000000 0.000000 2.5829556E-04 0.000000 0.000000 0.000000 - Av 2018 8 19 4 0 2.6037466E-02 0.000000 0.000000 2.5821457E-04 0.000000 0.000000 0.000000 - Av 2018 8 19 5 0 2.6029442E-02 0.000000 0.000000 2.5813360E-04 0.000000 0.000000 0.000000 + Av 2018 8 18 19 0 1.7630203E-02 0.000000 0.000000 2.5948032E-04 0.000000 0.000000 0.000000 + Av 2018 8 18 20 0 2.9124686E-02 0.000000 0.000000 2.5939877E-04 0.000000 0.000000 0.000000 + Av 2018 8 18 21 0 2.5116874E-02 0.000000 0.000000 2.5931728E-04 0.000000 0.000000 0.000000 + Av 2018 8 18 22 0 2.6499351E-02 0.000000 0.000000 2.5923579E-04 0.000000 0.000000 0.000000 + Av 2018 8 18 23 0 2.6007582E-02 0.000000 0.000000 2.5915433E-04 0.000000 0.000000 0.000000 + Av 2018 8 18 24 0 2.6167506E-02 0.000000 0.000000 2.5907290E-04 0.000000 0.000000 0.000000 + Av 2018 8 19 1 0 2.6064562E-02 0.000000 0.000000 2.5845764E-04 0.000000 0.000000 0.000000 + Av 2018 8 19 2 0 2.6053049E-02 0.000000 0.000000 2.5837659E-04 0.000000 0.000000 0.000000 + Av 2018 8 19 3 0 2.6046040E-02 0.000000 0.000000 2.5829556E-04 0.000000 0.000000 0.000000 + Av 2018 8 19 4 0 2.6037466E-02 0.000000 0.000000 2.5821457E-04 0.000000 0.000000 0.000000 + Av 2018 8 19 5 0 2.6029442E-02 0.000000 0.000000 2.5813360E-04 0.000000 0.000000 0.000000 Av 2018 8 19 6 0 1.3012643E-02 0.000000 0.000000 0.000000 0.000000 0.000000 3.1343007E-03 Av 2018 8 19 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.9254488E-03 Av 2018 8 19 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.0716598E-02 @@ -5562,17 +5562,17 @@ Av 2018 8 19 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.0716598E-02 Av 2018 8 19 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.9254488E-03 Av 2018 8 19 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.1343007E-03 - Av 2018 8 19 19 0 1.7461859E-02 0.000000 0.000000 2.5700266E-04 0.000000 0.000000 0.000000 - Av 2018 8 19 20 0 2.8846595E-02 0.000000 0.000000 2.5692204E-04 0.000000 0.000000 0.000000 - Av 2018 8 19 21 0 2.4877071E-02 0.000000 0.000000 2.5684148E-04 0.000000 0.000000 0.000000 - Av 2018 8 19 22 0 2.6246365E-02 0.000000 0.000000 2.5676095E-04 0.000000 0.000000 0.000000 - Av 2018 8 19 23 0 2.5759308E-02 0.000000 0.000000 2.5668042E-04 0.000000 0.000000 0.000000 - Av 2018 8 19 24 0 2.5917724E-02 0.000000 0.000000 2.5659995E-04 0.000000 0.000000 0.000000 - Av 2018 8 20 1 0 2.5816787E-02 0.000000 0.000000 2.5600556E-04 0.000000 0.000000 0.000000 - Av 2018 8 20 2 0 2.5806054E-02 0.000000 0.000000 2.5592544E-04 0.000000 0.000000 0.000000 - Av 2018 8 20 3 0 2.5798900E-02 0.000000 0.000000 2.5584534E-04 0.000000 0.000000 0.000000 - Av 2018 8 20 4 0 2.5790505E-02 0.000000 0.000000 2.5576528E-04 0.000000 0.000000 0.000000 - Av 2018 8 20 5 0 2.5782546E-02 0.000000 0.000000 2.5568521E-04 0.000000 0.000000 0.000000 + Av 2018 8 19 19 0 1.7461859E-02 0.000000 0.000000 2.5700266E-04 0.000000 0.000000 0.000000 + Av 2018 8 19 20 0 2.8846595E-02 0.000000 0.000000 2.5692204E-04 0.000000 0.000000 0.000000 + Av 2018 8 19 21 0 2.4877071E-02 0.000000 0.000000 2.5684148E-04 0.000000 0.000000 0.000000 + Av 2018 8 19 22 0 2.6246365E-02 0.000000 0.000000 2.5676095E-04 0.000000 0.000000 0.000000 + Av 2018 8 19 23 0 2.5759308E-02 0.000000 0.000000 2.5668042E-04 0.000000 0.000000 0.000000 + Av 2018 8 19 24 0 2.5917724E-02 0.000000 0.000000 2.5659995E-04 0.000000 0.000000 0.000000 + Av 2018 8 20 1 0 2.5816787E-02 0.000000 0.000000 2.5600556E-04 0.000000 0.000000 0.000000 + Av 2018 8 20 2 0 2.5806054E-02 0.000000 0.000000 2.5592544E-04 0.000000 0.000000 0.000000 + Av 2018 8 20 3 0 2.5798900E-02 0.000000 0.000000 2.5584534E-04 0.000000 0.000000 0.000000 + Av 2018 8 20 4 0 2.5790505E-02 0.000000 0.000000 2.5576528E-04 0.000000 0.000000 0.000000 + Av 2018 8 20 5 0 2.5782546E-02 0.000000 0.000000 2.5568521E-04 0.000000 0.000000 0.000000 Av 2018 8 20 6 0 1.2889225E-02 0.000000 0.000000 0.000000 0.000000 0.000000 3.3010631E-03 Av 2018 8 20 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.4210358E-03 Av 2018 8 20 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.1541009E-02 @@ -5586,17 +5586,17 @@ Av 2018 8 20 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.1541009E-02 Av 2018 8 20 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.4210358E-03 Av 2018 8 20 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.3010631E-03 - Av 2018 8 20 19 0 1.7296385E-02 0.000000 0.000000 2.5456722E-04 0.000000 0.000000 0.000000 - Av 2018 8 20 20 0 2.8573249E-02 0.000000 0.000000 2.5448753E-04 0.000000 0.000000 0.000000 - Av 2018 8 20 21 0 2.4641359E-02 0.000000 0.000000 2.5440790E-04 0.000000 0.000000 0.000000 - Av 2018 8 20 22 0 2.5997691E-02 0.000000 0.000000 2.5432828E-04 0.000000 0.000000 0.000000 - Av 2018 8 20 23 0 2.5515262E-02 0.000000 0.000000 2.5424868E-04 0.000000 0.000000 0.000000 - Av 2018 8 20 24 0 2.5672194E-02 0.000000 0.000000 2.5416911E-04 0.000000 0.000000 0.000000 - Av 2018 8 21 1 0 2.5573198E-02 0.000000 0.000000 2.5359477E-04 0.000000 0.000000 0.000000 - Av 2018 8 21 2 0 2.5563216E-02 0.000000 0.000000 2.5351558E-04 0.000000 0.000000 0.000000 - Av 2018 8 21 3 0 2.5555927E-02 0.000000 0.000000 2.5343639E-04 0.000000 0.000000 0.000000 - Av 2018 8 21 4 0 2.5547702E-02 0.000000 0.000000 2.5335723E-04 0.000000 0.000000 0.000000 - Av 2018 8 21 5 0 2.5539804E-02 0.000000 0.000000 2.5327809E-04 0.000000 0.000000 0.000000 + Av 2018 8 20 19 0 1.7296385E-02 0.000000 0.000000 2.5456722E-04 0.000000 0.000000 0.000000 + Av 2018 8 20 20 0 2.8573249E-02 0.000000 0.000000 2.5448753E-04 0.000000 0.000000 0.000000 + Av 2018 8 20 21 0 2.4641359E-02 0.000000 0.000000 2.5440790E-04 0.000000 0.000000 0.000000 + Av 2018 8 20 22 0 2.5997691E-02 0.000000 0.000000 2.5432828E-04 0.000000 0.000000 0.000000 + Av 2018 8 20 23 0 2.5515262E-02 0.000000 0.000000 2.5424868E-04 0.000000 0.000000 0.000000 + Av 2018 8 20 24 0 2.5672194E-02 0.000000 0.000000 2.5416911E-04 0.000000 0.000000 0.000000 + Av 2018 8 21 1 0 2.5573198E-02 0.000000 0.000000 2.5359477E-04 0.000000 0.000000 0.000000 + Av 2018 8 21 2 0 2.5563216E-02 0.000000 0.000000 2.5351558E-04 0.000000 0.000000 0.000000 + Av 2018 8 21 3 0 2.5555927E-02 0.000000 0.000000 2.5343639E-04 0.000000 0.000000 0.000000 + Av 2018 8 21 4 0 2.5547702E-02 0.000000 0.000000 2.5335723E-04 0.000000 0.000000 0.000000 + Av 2018 8 21 5 0 2.5539804E-02 0.000000 0.000000 2.5327809E-04 0.000000 0.000000 0.000000 Av 2018 8 21 6 0 1.2767886E-02 0.000000 0.000000 0.000000 0.000000 0.000000 3.6232243E-03 Av 2018 8 21 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 8.2948599E-03 Av 2018 8 21 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.2966495E-02 @@ -5610,17 +5610,17 @@ Av 2018 8 21 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.2966495E-02 Av 2018 8 21 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 8.2948599E-03 Av 2018 8 21 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.6232243E-03 - Av 2018 8 21 19 0 1.7133696E-02 0.000000 0.000000 2.5217276E-04 0.000000 0.000000 0.000000 - Av 2018 8 21 20 0 2.8304502E-02 0.000000 0.000000 2.5209400E-04 0.000000 0.000000 0.000000 - Av 2018 8 21 21 0 2.4409611E-02 0.000000 0.000000 2.5201525E-04 0.000000 0.000000 0.000000 - Av 2018 8 21 22 0 2.5753202E-02 0.000000 0.000000 2.5193655E-04 0.000000 0.000000 0.000000 - Av 2018 8 21 23 0 2.5275327E-02 0.000000 0.000000 2.5185785E-04 0.000000 0.000000 0.000000 - Av 2018 8 21 24 0 2.5430799E-02 0.000000 0.000000 2.5177919E-04 0.000000 0.000000 0.000000 - Av 2018 8 22 1 0 2.5333688E-02 0.000000 0.000000 2.5122421E-04 0.000000 0.000000 0.000000 - Av 2018 8 22 2 0 2.5324423E-02 0.000000 0.000000 2.5114589E-04 0.000000 0.000000 0.000000 - Av 2018 8 22 3 0 2.5317002E-02 0.000000 0.000000 2.5106757E-04 0.000000 0.000000 0.000000 - Av 2018 8 22 4 0 2.5308944E-02 0.000000 0.000000 2.5098931E-04 0.000000 0.000000 0.000000 - Av 2018 8 22 5 0 2.5301110E-02 0.000000 0.000000 2.5091105E-04 0.000000 0.000000 0.000000 + Av 2018 8 21 19 0 1.7133696E-02 0.000000 0.000000 2.5217276E-04 0.000000 0.000000 0.000000 + Av 2018 8 21 20 0 2.8304502E-02 0.000000 0.000000 2.5209400E-04 0.000000 0.000000 0.000000 + Av 2018 8 21 21 0 2.4409611E-02 0.000000 0.000000 2.5201525E-04 0.000000 0.000000 0.000000 + Av 2018 8 21 22 0 2.5753202E-02 0.000000 0.000000 2.5193655E-04 0.000000 0.000000 0.000000 + Av 2018 8 21 23 0 2.5275327E-02 0.000000 0.000000 2.5185785E-04 0.000000 0.000000 0.000000 + Av 2018 8 21 24 0 2.5430799E-02 0.000000 0.000000 2.5177919E-04 0.000000 0.000000 0.000000 + Av 2018 8 22 1 0 2.5333688E-02 0.000000 0.000000 2.5122421E-04 0.000000 0.000000 0.000000 + Av 2018 8 22 2 0 2.5324423E-02 0.000000 0.000000 2.5114589E-04 0.000000 0.000000 0.000000 + Av 2018 8 22 3 0 2.5317002E-02 0.000000 0.000000 2.5106757E-04 0.000000 0.000000 0.000000 + Av 2018 8 22 4 0 2.5308944E-02 0.000000 0.000000 2.5098931E-04 0.000000 0.000000 0.000000 + Av 2018 8 22 5 0 2.5301110E-02 0.000000 0.000000 2.5091105E-04 0.000000 0.000000 0.000000 Av 2018 8 22 6 0 1.2648568E-02 0.000000 0.000000 0.000000 0.000000 0.000000 3.3757191E-03 Av 2018 8 22 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.8779738E-03 Av 2018 8 22 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.2380229E-02 @@ -5634,17 +5634,17 @@ Av 2018 8 22 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.2380229E-02 Av 2018 8 22 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.8779738E-03 Av 2018 8 22 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.3757191E-03 - Av 2018 8 22 19 0 1.6973710E-02 0.000000 0.000000 2.4981811E-04 0.000000 0.000000 0.000000 - Av 2018 8 22 20 0 2.8040219E-02 0.000000 0.000000 2.4974023E-04 0.000000 0.000000 0.000000 - Av 2018 8 22 21 0 2.4181716E-02 0.000000 0.000000 2.4966238E-04 0.000000 0.000000 0.000000 - Av 2018 8 22 22 0 2.5512774E-02 0.000000 0.000000 2.4958455E-04 0.000000 0.000000 0.000000 - Av 2018 8 22 23 0 2.5039377E-02 0.000000 0.000000 2.4950673E-04 0.000000 0.000000 0.000000 - Av 2018 8 22 24 0 2.5193410E-02 0.000000 0.000000 2.4942897E-04 0.000000 0.000000 0.000000 - Av 2018 8 23 1 0 2.5098125E-02 0.000000 0.000000 2.4889258E-04 0.000000 0.000000 0.000000 - Av 2018 8 23 2 0 2.5089547E-02 0.000000 0.000000 2.4881511E-04 0.000000 0.000000 0.000000 - Av 2018 8 23 3 0 2.5082007E-02 0.000000 0.000000 2.4873769E-04 0.000000 0.000000 0.000000 - Av 2018 8 23 4 0 2.5074109E-02 0.000000 0.000000 2.4866030E-04 0.000000 0.000000 0.000000 - Av 2018 8 23 5 0 2.5066338E-02 0.000000 0.000000 2.4858292E-04 0.000000 0.000000 0.000000 + Av 2018 8 22 19 0 1.6973710E-02 0.000000 0.000000 2.4981811E-04 0.000000 0.000000 0.000000 + Av 2018 8 22 20 0 2.8040219E-02 0.000000 0.000000 2.4974023E-04 0.000000 0.000000 0.000000 + Av 2018 8 22 21 0 2.4181716E-02 0.000000 0.000000 2.4966238E-04 0.000000 0.000000 0.000000 + Av 2018 8 22 22 0 2.5512774E-02 0.000000 0.000000 2.4958455E-04 0.000000 0.000000 0.000000 + Av 2018 8 22 23 0 2.5039377E-02 0.000000 0.000000 2.4950673E-04 0.000000 0.000000 0.000000 + Av 2018 8 22 24 0 2.5193410E-02 0.000000 0.000000 2.4942897E-04 0.000000 0.000000 0.000000 + Av 2018 8 23 1 0 2.5098125E-02 0.000000 0.000000 2.4889258E-04 0.000000 0.000000 0.000000 + Av 2018 8 23 2 0 2.5089547E-02 0.000000 0.000000 2.4881511E-04 0.000000 0.000000 0.000000 + Av 2018 8 23 3 0 2.5082007E-02 0.000000 0.000000 2.4873769E-04 0.000000 0.000000 0.000000 + Av 2018 8 23 4 0 2.5074109E-02 0.000000 0.000000 2.4866030E-04 0.000000 0.000000 0.000000 + Av 2018 8 23 5 0 2.5066338E-02 0.000000 0.000000 2.4858292E-04 0.000000 0.000000 0.000000 Av 2018 8 23 6 0 1.2531211E-02 0.000000 0.000000 0.000000 0.000000 0.000000 2.5592037E-03 Av 2018 8 23 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.0947249E-03 Av 2018 8 23 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 9.6302461E-03 @@ -5658,17 +5658,17 @@ Av 2018 8 23 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 9.6302461E-03 Av 2018 8 23 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.0947249E-03 Av 2018 8 23 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.5592037E-03 - Av 2018 8 23 19 0 1.6816350E-02 0.000000 0.000000 2.4750209E-04 0.000000 0.000000 0.000000 - Av 2018 8 23 20 0 2.7780272E-02 0.000000 0.000000 2.4742508E-04 0.000000 0.000000 0.000000 - Av 2018 8 23 21 0 2.3957558E-02 0.000000 0.000000 2.4734810E-04 0.000000 0.000000 0.000000 - Av 2018 8 23 22 0 2.5276288E-02 0.000000 0.000000 2.4727112E-04 0.000000 0.000000 0.000000 - Av 2018 8 23 23 0 2.4807295E-02 0.000000 0.000000 2.4719417E-04 0.000000 0.000000 0.000000 - Av 2018 8 23 24 0 2.4959914E-02 0.000000 0.000000 2.4711725E-04 0.000000 0.000000 0.000000 - Av 2018 8 24 1 0 2.4866395E-02 0.000000 0.000000 2.4659879E-04 0.000000 0.000000 0.000000 - Av 2018 8 24 2 0 2.4858482E-02 0.000000 0.000000 2.4652219E-04 0.000000 0.000000 0.000000 - Av 2018 8 24 3 0 2.4850825E-02 0.000000 0.000000 2.4644562E-04 0.000000 0.000000 0.000000 - Av 2018 8 24 4 0 2.4843086E-02 0.000000 0.000000 2.4636908E-04 0.000000 0.000000 0.000000 - Av 2018 8 24 5 0 2.4835374E-02 0.000000 0.000000 2.4629253E-04 0.000000 0.000000 0.000000 + Av 2018 8 23 19 0 1.6816350E-02 0.000000 0.000000 2.4750209E-04 0.000000 0.000000 0.000000 + Av 2018 8 23 20 0 2.7780272E-02 0.000000 0.000000 2.4742508E-04 0.000000 0.000000 0.000000 + Av 2018 8 23 21 0 2.3957558E-02 0.000000 0.000000 2.4734810E-04 0.000000 0.000000 0.000000 + Av 2018 8 23 22 0 2.5276288E-02 0.000000 0.000000 2.4727112E-04 0.000000 0.000000 0.000000 + Av 2018 8 23 23 0 2.4807295E-02 0.000000 0.000000 2.4719417E-04 0.000000 0.000000 0.000000 + Av 2018 8 23 24 0 2.4959914E-02 0.000000 0.000000 2.4711725E-04 0.000000 0.000000 0.000000 + Av 2018 8 24 1 0 2.4866395E-02 0.000000 0.000000 2.4659879E-04 0.000000 0.000000 0.000000 + Av 2018 8 24 2 0 2.4858482E-02 0.000000 0.000000 2.4652219E-04 0.000000 0.000000 0.000000 + Av 2018 8 24 3 0 2.4850825E-02 0.000000 0.000000 2.4644562E-04 0.000000 0.000000 0.000000 + Av 2018 8 24 4 0 2.4843086E-02 0.000000 0.000000 2.4636908E-04 0.000000 0.000000 0.000000 + Av 2018 8 24 5 0 2.4835374E-02 0.000000 0.000000 2.4629253E-04 0.000000 0.000000 0.000000 Av 2018 8 24 6 0 1.2415756E-02 0.000000 0.000000 0.000000 0.000000 0.000000 2.0235390E-03 Av 2018 8 24 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.9234331E-03 Av 2018 8 24 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.8233266E-03 @@ -5682,17 +5682,17 @@ Av 2018 8 24 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.8233266E-03 Av 2018 8 24 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.9234331E-03 Av 2018 8 24 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.0235390E-03 - 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Av 2018 8 25 19 0 1.6509207E-02 0.000000 0.000000 2.4298156E-04 0.000000 0.000000 0.000000 - Av 2018 8 25 20 0 2.7272895E-02 0.000000 0.000000 2.4290622E-04 0.000000 0.000000 0.000000 - Av 2018 8 25 21 0 2.3520026E-02 0.000000 0.000000 2.4283089E-04 0.000000 0.000000 0.000000 - Av 2018 8 25 22 0 2.4814699E-02 0.000000 0.000000 2.4275559E-04 0.000000 0.000000 0.000000 - Av 2018 8 25 23 0 2.4354298E-02 0.000000 0.000000 2.4268031E-04 0.000000 0.000000 0.000000 - Av 2018 8 25 24 0 2.4504155E-02 0.000000 0.000000 2.4260505E-04 0.000000 0.000000 0.000000 - Av 2018 8 26 1 0 2.4414014E-02 0.000000 0.000000 2.4212051E-04 0.000000 0.000000 0.000000 - Av 2018 8 26 2 0 2.4407344E-02 0.000000 0.000000 2.4204557E-04 0.000000 0.000000 0.000000 - Av 2018 8 26 3 0 2.4399480E-02 0.000000 0.000000 2.4197064E-04 0.000000 0.000000 0.000000 - Av 2018 8 26 4 0 2.4392031E-02 0.000000 0.000000 2.4189572E-04 0.000000 0.000000 0.000000 - Av 2018 8 26 5 0 2.4384443E-02 0.000000 0.000000 2.4182085E-04 0.000000 0.000000 0.000000 + Av 2018 8 25 19 0 1.6509207E-02 0.000000 0.000000 2.4298156E-04 0.000000 0.000000 0.000000 + Av 2018 8 25 20 0 2.7272895E-02 0.000000 0.000000 2.4290622E-04 0.000000 0.000000 0.000000 + Av 2018 8 25 21 0 2.3520026E-02 0.000000 0.000000 2.4283089E-04 0.000000 0.000000 0.000000 + Av 2018 8 25 22 0 2.4814699E-02 0.000000 0.000000 2.4275559E-04 0.000000 0.000000 0.000000 + Av 2018 8 25 23 0 2.4354298E-02 0.000000 0.000000 2.4268031E-04 0.000000 0.000000 0.000000 + Av 2018 8 25 24 0 2.4504155E-02 0.000000 0.000000 2.4260505E-04 0.000000 0.000000 0.000000 + Av 2018 8 26 1 0 2.4414014E-02 0.000000 0.000000 2.4212051E-04 0.000000 0.000000 0.000000 + Av 2018 8 26 2 0 2.4407344E-02 0.000000 0.000000 2.4204557E-04 0.000000 0.000000 0.000000 + Av 2018 8 26 3 0 2.4399480E-02 0.000000 0.000000 2.4197064E-04 0.000000 0.000000 0.000000 + Av 2018 8 26 4 0 2.4392031E-02 0.000000 0.000000 2.4189572E-04 0.000000 0.000000 0.000000 + Av 2018 8 26 5 0 2.4384443E-02 0.000000 0.000000 2.4182085E-04 0.000000 0.000000 0.000000 Av 2018 8 26 6 0 1.2190345E-02 0.000000 0.000000 0.000000 0.000000 0.000000 1.8296378E-03 Av 2018 8 26 7 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.6648574E-03 Av 2018 8 26 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.5000771E-03 @@ -5730,17 +5730,17 @@ Av 2018 8 26 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.5000771E-03 Av 2018 8 26 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.6648574E-03 Av 2018 8 26 18 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.8296378E-03 - 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Av 2018 9 11 19 0 1.7835625E-02 0.000000 0.000000 2.0956909E-04 0.000000 0.000000 0.000000 - Av 2018 9 11 20 0 2.2272119E-02 0.000000 0.000000 2.0950557E-04 0.000000 0.000000 0.000000 - Av 2018 9 11 21 0 2.0720880E-02 0.000000 0.000000 2.0944208E-04 0.000000 0.000000 0.000000 - Av 2018 9 11 22 0 2.1572353E-02 0.000000 0.000000 2.0937862E-04 0.000000 9.9999802E-03 0.000000 - Av 2018 9 11 23 0 2.1267664E-02 0.000000 0.000000 2.0931516E-04 0.000000 0.000000 0.000000 - Av 2018 9 11 24 0 2.1044267E-02 0.000000 0.000000 2.0925172E-04 0.000000 0.000000 0.000000 - Av 2018 9 12 1 0 2.1098701E-02 0.000000 0.000000 2.0897306E-04 0.000000 0.000000 0.000000 - Av 2018 9 12 2 0 2.2325676E-02 0.000000 0.000000 2.0890980E-04 0.000000 3.9999921E-02 0.000000 - Av 2018 9 12 3 0 2.1890452E-02 0.000000 0.000000 2.0884656E-04 0.000000 0.000000 0.000000 - Av 2018 9 12 4 0 2.0764057E-02 0.000000 0.000000 2.0878333E-04 0.000000 0.000000 0.000000 - Av 2018 9 12 5 0 2.1147123E-02 0.000000 0.000000 2.0872011E-04 0.000000 0.000000 0.000000 + Av 2018 9 11 19 0 1.7835625E-02 0.000000 0.000000 2.0956909E-04 0.000000 0.000000 0.000000 + Av 2018 9 11 20 0 2.2272119E-02 0.000000 0.000000 2.0950557E-04 0.000000 0.000000 0.000000 + Av 2018 9 11 21 0 2.0720880E-02 0.000000 0.000000 2.0944208E-04 0.000000 0.000000 0.000000 + Av 2018 9 11 22 0 2.1572353E-02 0.000000 0.000000 2.0937862E-04 0.000000 9.9999802E-03 0.000000 + Av 2018 9 11 23 0 2.1267664E-02 0.000000 0.000000 2.0931516E-04 0.000000 0.000000 0.000000 + Av 2018 9 11 24 0 2.1044267E-02 0.000000 0.000000 2.0925172E-04 0.000000 0.000000 0.000000 + Av 2018 9 12 1 0 2.1098701E-02 0.000000 0.000000 2.0897306E-04 0.000000 0.000000 0.000000 + Av 2018 9 12 2 0 2.2325676E-02 0.000000 0.000000 2.0890980E-04 0.000000 3.9999921E-02 0.000000 + Av 2018 9 12 3 0 2.1890452E-02 0.000000 0.000000 2.0884656E-04 0.000000 0.000000 0.000000 + Av 2018 9 12 4 0 2.0764057E-02 0.000000 0.000000 2.0878333E-04 0.000000 0.000000 0.000000 + Av 2018 9 12 5 0 2.1147123E-02 0.000000 0.000000 2.0872011E-04 0.000000 0.000000 0.000000 Av 2018 9 12 6 0 1.3664407E-02 0.000000 0.000000 1.0084185E-04 0.000000 0.000000 4.9006852E-04 Av 2018 9 12 7 0 3.1962369E-03 0.000000 0.000000 0.000000 0.000000 0.000000 2.9454287E-03 Av 2018 9 12 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.4007890E-03 @@ -6138,17 +6138,17 @@ Av 2018 9 12 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.1199998 5.4007890E-03 Av 2018 9 12 17 0 0.4547126 7.1890216E-10 0.000000 0.000000 6.6924348E-02 0.1199998 2.9454287E-03 Av 2018 9 12 18 0 0.4547126 0.000000 0.000000 1.0036235E-04 1.1858476E-02 0.000000 4.9006852E-04 - 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Av 2018 9 13 19 0 1.9827299E-02 0.000000 0.000000 2.0646374E-04 0.000000 4.9999900E-02 0.000000 - Av 2018 9 13 20 0 2.2424841E-02 0.000000 0.000000 2.0640125E-04 0.000000 0.000000 0.000000 - Av 2018 9 13 21 0 2.0246007E-02 0.000000 0.000000 2.0633879E-04 0.000000 0.000000 0.000000 - Av 2018 9 13 22 0 2.0995121E-02 0.000000 0.000000 2.0627635E-04 0.000000 0.000000 0.000000 - Av 2018 9 13 23 0 2.0726163E-02 0.000000 0.000000 2.0621392E-04 0.000000 0.000000 0.000000 - Av 2018 9 13 24 0 2.0811200E-02 0.000000 0.000000 2.0615151E-04 0.000000 0.000000 0.000000 - Av 2018 9 14 1 0 2.0759307E-02 0.000000 0.000000 2.0588536E-04 0.000000 0.000000 0.000000 - Av 2018 9 14 2 0 2.0755038E-02 0.000000 0.000000 2.0582310E-04 0.000000 0.000000 0.000000 - Av 2018 9 14 3 0 2.0748066E-02 0.000000 0.000000 2.0576089E-04 0.000000 0.000000 0.000000 - Av 2018 9 14 4 0 2.0742036E-02 0.000000 0.000000 2.0569869E-04 0.000000 0.000000 0.000000 - Av 2018 9 14 5 0 2.0735681E-02 0.000000 0.000000 2.0563649E-04 0.000000 0.000000 0.000000 + Av 2018 9 13 19 0 1.9827299E-02 0.000000 0.000000 2.0646374E-04 0.000000 4.9999900E-02 0.000000 + Av 2018 9 13 20 0 2.2424841E-02 0.000000 0.000000 2.0640125E-04 0.000000 0.000000 0.000000 + Av 2018 9 13 21 0 2.0246007E-02 0.000000 0.000000 2.0633879E-04 0.000000 0.000000 0.000000 + Av 2018 9 13 22 0 2.0995121E-02 0.000000 0.000000 2.0627635E-04 0.000000 0.000000 0.000000 + Av 2018 9 13 23 0 2.0726163E-02 0.000000 0.000000 2.0621392E-04 0.000000 0.000000 0.000000 + Av 2018 9 13 24 0 2.0811200E-02 0.000000 0.000000 2.0615151E-04 0.000000 0.000000 0.000000 + Av 2018 9 14 1 0 2.0759307E-02 0.000000 0.000000 2.0588536E-04 0.000000 0.000000 0.000000 + Av 2018 9 14 2 0 2.0755038E-02 0.000000 0.000000 2.0582310E-04 0.000000 0.000000 0.000000 + Av 2018 9 14 3 0 2.0748066E-02 0.000000 0.000000 2.0576089E-04 0.000000 0.000000 0.000000 + Av 2018 9 14 4 0 2.0742036E-02 0.000000 0.000000 2.0569869E-04 0.000000 0.000000 0.000000 + Av 2018 9 14 5 0 2.0735681E-02 0.000000 0.000000 2.0563649E-04 0.000000 0.000000 0.000000 Av 2018 9 14 6 0 1.4500037E-02 0.000000 0.000000 1.1408322E-04 0.000000 0.000000 4.1586868E-04 Av 2018 9 14 7 0 4.1337418E-03 0.000000 0.000000 0.000000 0.000000 0.000000 3.2914700E-03 Av 2018 9 14 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.1670714E-03 @@ -6186,17 +6186,17 @@ Av 2018 9 14 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.1670714E-03 Av 2018 9 14 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.2914700E-03 Av 2018 9 14 18 0 7.7007101E-03 0.000000 0.000000 1.1333861E-04 0.000000 0.000000 4.1586868E-04 - Av 2018 9 14 19 0 1.8935904E-02 0.000000 0.000000 2.0476780E-04 0.000000 0.000000 0.000000 - Av 2018 9 14 20 0 2.1237213E-02 0.000000 0.000000 2.0470590E-04 0.000000 0.000000 0.000000 - Av 2018 9 14 21 0 2.0428617E-02 0.000000 0.000000 2.0464402E-04 0.000000 0.000000 0.000000 - Av 2018 9 14 22 0 2.0701366E-02 0.000000 0.000000 2.0458216E-04 0.000000 0.000000 0.000000 - Av 2018 9 14 23 0 2.0598123E-02 0.000000 0.000000 2.0452031E-04 0.000000 0.000000 0.000000 - Av 2018 9 14 24 0 2.0625617E-02 0.000000 0.000000 2.0445848E-04 0.000000 0.000000 0.000000 - Av 2018 9 15 1 0 2.0594325E-02 0.000000 0.000000 2.0420045E-04 0.000000 0.000000 0.000000 - Av 2018 9 15 2 0 2.0583484E-02 0.000000 0.000000 2.0413878E-04 0.000000 0.000000 0.000000 - Av 2018 9 15 3 0 2.0578872E-02 0.000000 0.000000 2.0407712E-04 0.000000 0.000000 0.000000 - Av 2018 9 15 4 0 2.0572100E-02 0.000000 0.000000 2.0401548E-04 0.000000 0.000000 0.000000 - Av 2018 9 15 5 0 2.0566080E-02 0.000000 0.000000 2.0395385E-04 0.000000 0.000000 0.000000 + Av 2018 9 14 19 0 1.8935904E-02 0.000000 0.000000 2.0476780E-04 0.000000 0.000000 0.000000 + Av 2018 9 14 20 0 2.1237213E-02 0.000000 0.000000 2.0470590E-04 0.000000 0.000000 0.000000 + Av 2018 9 14 21 0 2.0428617E-02 0.000000 0.000000 2.0464402E-04 0.000000 0.000000 0.000000 + Av 2018 9 14 22 0 2.0701366E-02 0.000000 0.000000 2.0458216E-04 0.000000 0.000000 0.000000 + Av 2018 9 14 23 0 2.0598123E-02 0.000000 0.000000 2.0452031E-04 0.000000 0.000000 0.000000 + Av 2018 9 14 24 0 2.0625617E-02 0.000000 0.000000 2.0445848E-04 0.000000 0.000000 0.000000 + Av 2018 9 15 1 0 2.0594325E-02 0.000000 0.000000 2.0420045E-04 0.000000 0.000000 0.000000 + Av 2018 9 15 2 0 2.0583484E-02 0.000000 0.000000 2.0413878E-04 0.000000 0.000000 0.000000 + Av 2018 9 15 3 0 2.0578872E-02 0.000000 0.000000 2.0407712E-04 0.000000 0.000000 0.000000 + Av 2018 9 15 4 0 2.0572100E-02 0.000000 0.000000 2.0401548E-04 0.000000 0.000000 0.000000 + Av 2018 9 15 5 0 2.0566080E-02 0.000000 0.000000 2.0395385E-04 0.000000 0.000000 0.000000 Av 2018 9 15 6 0 1.5553607E-02 0.000000 0.000000 1.3036584E-04 0.000000 0.000000 3.3421096E-04 Av 2018 9 15 7 0 5.2721729E-03 0.000000 0.000000 0.000000 0.000000 0.000000 3.1882715E-03 Av 2018 9 15 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.0423319E-03 @@ -6210,17 +6210,17 @@ Av 2018 9 15 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 9.9999802E-03 6.0423319E-03 Av 2018 9 15 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.1882715E-03 Av 2018 9 15 18 0 8.8074841E-03 0.000000 0.000000 1.2962805E-04 0.000000 0.000000 3.3421096E-04 - Av 2018 9 15 19 0 1.9544058E-02 0.000000 0.000000 2.0309312E-04 0.000000 0.000000 0.000000 - Av 2018 9 15 20 0 2.0798219E-02 0.000000 0.000000 2.0303178E-04 0.000000 0.000000 0.000000 - Av 2018 9 15 21 0 2.0353803E-02 0.000000 0.000000 2.0297046E-04 0.000000 0.000000 0.000000 - Av 2018 9 15 22 0 2.0500001E-02 0.000000 0.000000 2.0290917E-04 0.000000 0.000000 0.000000 - Av 2018 9 15 23 0 2.0440837E-02 0.000000 0.000000 2.0284789E-04 0.000000 0.000000 0.000000 - Av 2018 9 15 24 0 2.0766385E-02 0.000000 0.000000 2.0278663E-04 0.000000 9.9999802E-03 0.000000 - Av 2018 9 16 1 0 2.0949490E-02 0.000000 0.000000 2.0253642E-04 0.000000 9.9999802E-03 0.000000 - Av 2018 9 16 2 0 2.1498900E-02 0.000000 0.000000 2.0247530E-04 0.000000 2.9999940E-02 0.000000 - Av 2018 9 16 3 0 2.1632023E-02 0.000000 0.000000 2.0241420E-04 0.000000 1.9999960E-02 0.000000 - Av 2018 9 16 4 0 2.0629901E-02 0.000000 0.000000 2.0235313E-04 0.000000 0.000000 0.000000 - Av 2018 9 16 5 0 0.5148370 1.4486436E-09 0.000000 2.0241663E-04 7.2002880E-02 0.1699997 0.000000 + Av 2018 9 15 19 0 1.9544058E-02 0.000000 0.000000 2.0309312E-04 0.000000 0.000000 0.000000 + Av 2018 9 15 20 0 2.0798219E-02 0.000000 0.000000 2.0303178E-04 0.000000 0.000000 0.000000 + Av 2018 9 15 21 0 2.0353803E-02 0.000000 0.000000 2.0297046E-04 0.000000 0.000000 0.000000 + Av 2018 9 15 22 0 2.0500001E-02 0.000000 0.000000 2.0290917E-04 0.000000 0.000000 0.000000 + Av 2018 9 15 23 0 2.0440837E-02 0.000000 0.000000 2.0284789E-04 0.000000 0.000000 0.000000 + Av 2018 9 15 24 0 2.0766385E-02 0.000000 0.000000 2.0278663E-04 0.000000 9.9999802E-03 0.000000 + Av 2018 9 16 1 0 2.0949490E-02 0.000000 0.000000 2.0253642E-04 0.000000 9.9999802E-03 0.000000 + Av 2018 9 16 2 0 2.1498900E-02 0.000000 0.000000 2.0247530E-04 0.000000 2.9999940E-02 0.000000 + Av 2018 9 16 3 0 2.1632023E-02 0.000000 0.000000 2.0241420E-04 0.000000 1.9999960E-02 0.000000 + Av 2018 9 16 4 0 2.0629901E-02 0.000000 0.000000 2.0235313E-04 0.000000 0.000000 0.000000 + Av 2018 9 16 5 0 0.5148370 1.4486436E-09 0.000000 2.0241663E-04 7.2002880E-02 0.1699997 0.000000 Av 2018 9 16 6 0 1.274823 6.3046435E-09 0.000000 1.5509533E-04 0.1331785 0.1399997 2.1689011E-04 Av 2018 9 16 7 0 0.7700667 0.000000 0.000000 0.000000 1.7826051E-02 0.000000 2.6385244E-03 Av 2018 9 16 8 0 2.9037701E-02 0.000000 0.000000 0.000000 4.2737527E-03 0.000000 5.0601587E-03 @@ -6234,17 +6234,17 @@ Av 2018 9 16 16 0 5.5995272E-03 0.000000 0.000000 0.000000 8.2413526E-04 0.000000 5.0601587E-03 Av 2018 9 16 17 0 6.3525490E-03 0.000000 0.000000 0.000000 4.0623380E-04 0.000000 2.6385244E-03 Av 2018 9 16 18 0 1.2650927E-02 0.000000 0.000000 1.5631953E-04 2.2678105E-04 0.000000 2.1689011E-04 - Av 2018 9 16 19 0 2.2561293E-02 0.000000 0.000000 2.0397348E-04 1.3857904E-04 0.000000 0.000000 - Av 2018 9 16 20 0 2.1426100E-02 0.000000 0.000000 2.0391162E-04 9.0639252E-05 0.000000 0.000000 - Av 2018 9 16 21 0 2.1295421E-02 0.000000 0.000000 2.0384979E-04 6.2488252E-05 0.000000 0.000000 - Av 2018 9 16 22 0 2.1021809E-02 0.000000 0.000000 2.0378797E-04 4.4917961E-05 0.000000 0.000000 - Av 2018 9 16 23 0 2.0910904E-02 0.000000 0.000000 2.0372619E-04 3.3398901E-05 0.000000 0.000000 - Av 2018 9 16 24 0 2.1802412E-02 0.000000 0.000000 2.0366440E-04 1.7168984E-04 0.000000 0.000000 - Av 2018 9 17 1 0 2.1242607E-02 0.000000 0.000000 2.0338925E-04 0.000000 0.000000 0.000000 - Av 2018 9 17 2 0 2.0247841E-02 0.000000 0.000000 2.0332764E-04 0.000000 0.000000 0.000000 - Av 2018 9 17 3 0 2.0585360E-02 0.000000 0.000000 2.0326606E-04 0.000000 0.000000 0.000000 - Av 2018 9 17 4 0 2.0459633E-02 0.000000 0.000000 2.0320449E-04 0.000000 0.000000 0.000000 - Av 2018 9 17 5 0 2.0494984E-02 0.000000 0.000000 2.0314293E-04 0.000000 0.000000 0.000000 + Av 2018 9 16 19 0 2.2561293E-02 0.000000 0.000000 2.0397348E-04 1.3857904E-04 0.000000 0.000000 + Av 2018 9 16 20 0 2.1426100E-02 0.000000 0.000000 2.0391162E-04 9.0639252E-05 0.000000 0.000000 + Av 2018 9 16 21 0 2.1295421E-02 0.000000 0.000000 2.0384979E-04 6.2488252E-05 0.000000 0.000000 + Av 2018 9 16 22 0 2.1021809E-02 0.000000 0.000000 2.0378797E-04 4.4917961E-05 0.000000 0.000000 + Av 2018 9 16 23 0 2.0910904E-02 0.000000 0.000000 2.0372619E-04 3.3398901E-05 0.000000 0.000000 + Av 2018 9 16 24 0 2.1802412E-02 0.000000 0.000000 2.0366440E-04 1.7168984E-04 0.000000 0.000000 + Av 2018 9 17 1 0 2.1242607E-02 0.000000 0.000000 2.0338925E-04 0.000000 0.000000 0.000000 + Av 2018 9 17 2 0 2.0247841E-02 0.000000 0.000000 2.0332764E-04 0.000000 0.000000 0.000000 + Av 2018 9 17 3 0 2.0585360E-02 0.000000 0.000000 2.0326606E-04 0.000000 0.000000 0.000000 + Av 2018 9 17 4 0 2.0459633E-02 0.000000 0.000000 2.0320449E-04 0.000000 0.000000 0.000000 + Av 2018 9 17 5 0 2.0494984E-02 0.000000 0.000000 2.0314293E-04 0.000000 0.000000 0.000000 Av 2018 9 17 6 0 1.8026680E-02 0.000000 0.000000 1.6713238E-04 0.000000 0.000000 1.6340462E-04 Av 2018 9 17 7 0 7.7918158E-03 0.000000 0.000000 0.000000 0.000000 0.000000 2.7983736E-03 Av 2018 9 17 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.4333424E-03 @@ -6258,17 +6258,17 @@ Av 2018 9 17 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.4333424E-03 Av 2018 9 17 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.7983736E-03 Av 2018 9 17 18 0 1.1305614E-02 0.000000 0.000000 1.6639539E-04 0.000000 0.000000 1.6340462E-04 - 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Av 2018 9 21 18 0 1.3302907E-02 0.000000 0.000000 1.9579142E-04 0.000000 0.000000 0.000000 - Av 2018 9 21 19 0 2.1976260E-02 0.000000 0.000000 1.9573234E-04 0.000000 0.000000 0.000000 - Av 2018 9 21 20 0 1.8952429E-02 0.000000 0.000000 1.9567327E-04 0.000000 0.000000 0.000000 - Av 2018 9 21 21 0 1.9995818E-02 0.000000 0.000000 1.9561424E-04 0.000000 0.000000 0.000000 - Av 2018 9 21 22 0 1.9625001E-02 0.000000 0.000000 1.9555520E-04 0.000000 0.000000 0.000000 - Av 2018 9 21 23 0 1.9745916E-02 0.000000 0.000000 1.9549619E-04 0.000000 0.000000 0.000000 - Av 2018 9 21 24 0 1.9695856E-02 0.000000 0.000000 1.9543720E-04 0.000000 0.000000 0.000000 - Av 2018 9 22 1 0 1.9693241E-02 0.000000 0.000000 1.9520152E-04 0.000000 0.000000 0.000000 - Av 2018 9 22 2 0 1.9674137E-02 0.000000 0.000000 1.9514267E-04 0.000000 0.000000 0.000000 - Av 2018 9 22 3 0 1.9672785E-02 0.000000 0.000000 1.9508383E-04 0.000000 0.000000 0.000000 - Av 2018 9 22 4 0 1.9665260E-02 0.000000 0.000000 1.9502502E-04 0.000000 0.000000 0.000000 - 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Av 2018 9 22 18 0 1.3195016E-02 0.000000 0.000000 1.9420352E-04 0.000000 0.000000 0.000000 - Av 2018 9 22 19 0 2.1798031E-02 0.000000 0.000000 1.9414497E-04 0.000000 0.000000 0.000000 - Av 2018 9 22 20 0 1.8798735E-02 0.000000 0.000000 1.9408645E-04 0.000000 0.000000 0.000000 - Av 2018 9 22 21 0 1.9833665E-02 0.000000 0.000000 1.9402795E-04 0.000000 0.000000 0.000000 - Av 2018 9 22 22 0 1.9465860E-02 0.000000 0.000000 1.9396945E-04 0.000000 0.000000 0.000000 - Av 2018 9 22 23 0 1.9585801E-02 0.000000 0.000000 1.9391098E-04 0.000000 0.000000 0.000000 - Av 2018 9 22 24 0 1.9536152E-02 0.000000 0.000000 1.9385252E-04 0.000000 0.000000 0.000000 - Av 2018 9 23 1 0 1.9533914E-02 0.000000 0.000000 1.9362391E-04 0.000000 0.000000 0.000000 - Av 2018 9 23 2 0 1.9515198E-02 0.000000 0.000000 1.9356560E-04 0.000000 0.000000 0.000000 - Av 2018 9 23 3 0 1.9513782E-02 0.000000 0.000000 1.9350731E-04 0.000000 0.000000 0.000000 - Av 2018 9 23 4 0 1.9506350E-02 0.000000 0.000000 1.9344901E-04 0.000000 0.000000 0.000000 - Av 2018 9 23 5 0 1.9501014E-02 0.000000 0.000000 1.9339073E-04 0.000000 0.000000 0.000000 - Av 2018 9 23 6 0 1.9494953E-02 0.000000 0.000000 1.9333248E-04 0.000000 0.000000 0.000000 + Av 2018 9 22 18 0 1.3195016E-02 0.000000 0.000000 1.9420352E-04 0.000000 0.000000 0.000000 + Av 2018 9 22 19 0 2.1798031E-02 0.000000 0.000000 1.9414497E-04 0.000000 0.000000 0.000000 + Av 2018 9 22 20 0 1.8798735E-02 0.000000 0.000000 1.9408645E-04 0.000000 0.000000 0.000000 + Av 2018 9 22 21 0 1.9833665E-02 0.000000 0.000000 1.9402795E-04 0.000000 0.000000 0.000000 + Av 2018 9 22 22 0 1.9465860E-02 0.000000 0.000000 1.9396945E-04 0.000000 0.000000 0.000000 + Av 2018 9 22 23 0 1.9585801E-02 0.000000 0.000000 1.9391098E-04 0.000000 0.000000 0.000000 + Av 2018 9 22 24 0 1.9536152E-02 0.000000 0.000000 1.9385252E-04 0.000000 0.000000 0.000000 + Av 2018 9 23 1 0 1.9533914E-02 0.000000 0.000000 1.9362391E-04 0.000000 0.000000 0.000000 + Av 2018 9 23 2 0 1.9515198E-02 0.000000 0.000000 1.9356560E-04 0.000000 0.000000 0.000000 + Av 2018 9 23 3 0 1.9513782E-02 0.000000 0.000000 1.9350731E-04 0.000000 0.000000 0.000000 + Av 2018 9 23 4 0 1.9506350E-02 0.000000 0.000000 1.9344901E-04 0.000000 0.000000 0.000000 + Av 2018 9 23 5 0 1.9501014E-02 0.000000 0.000000 1.9339073E-04 0.000000 0.000000 0.000000 + Av 2018 9 23 6 0 1.9494953E-02 0.000000 0.000000 1.9333248E-04 0.000000 0.000000 0.000000 Av 2018 9 23 7 0 9.7460579E-03 0.000000 0.000000 0.000000 0.000000 0.000000 2.3894100E-03 Av 2018 9 23 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.0541791E-03 Av 2018 9 23 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.7189482E-03 @@ -6401,19 +6401,19 @@ Av 2018 9 23 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.7189482E-03 Av 2018 9 23 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.0541791E-03 Av 2018 9 23 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.3894100E-03 - Av 2018 9 23 18 0 1.3088430E-02 0.000000 0.000000 1.9263478E-04 0.000000 0.000000 0.000000 - Av 2018 9 23 19 0 2.1621954E-02 0.000000 0.000000 1.9257674E-04 0.000000 0.000000 0.000000 - Av 2018 9 23 20 0 1.8646888E-02 0.000000 0.000000 1.9251874E-04 0.000000 0.000000 0.000000 - Av 2018 9 23 21 0 1.9673463E-02 0.000000 0.000000 1.9246075E-04 0.000000 0.000000 0.000000 - Av 2018 9 23 22 0 1.9308634E-02 0.000000 0.000000 1.9240277E-04 0.000000 0.000000 0.000000 - Av 2018 9 23 23 0 1.9427612E-02 0.000000 0.000000 1.9234483E-04 0.000000 0.000000 0.000000 - Av 2018 9 23 24 0 1.9378368E-02 0.000000 0.000000 1.9228688E-04 0.000000 0.000000 0.000000 - Av 2018 9 24 1 0 1.9376485E-02 0.000000 0.000000 1.9206508E-04 0.000000 0.000000 0.000000 - Av 2018 9 24 2 0 1.9358143E-02 0.000000 0.000000 1.9200728E-04 0.000000 0.000000 0.000000 - Av 2018 9 24 3 0 1.9356668E-02 0.000000 0.000000 1.9194951E-04 0.000000 0.000000 0.000000 - Av 2018 9 24 4 0 1.9349331E-02 0.000000 0.000000 1.9189176E-04 0.000000 0.000000 0.000000 - Av 2018 9 24 5 0 1.9344036E-02 0.000000 0.000000 1.9183401E-04 0.000000 0.000000 0.000000 - Av 2018 9 24 6 0 1.9338030E-02 0.000000 0.000000 1.9177629E-04 0.000000 0.000000 0.000000 + Av 2018 9 23 18 0 1.3088430E-02 0.000000 0.000000 1.9263478E-04 0.000000 0.000000 0.000000 + Av 2018 9 23 19 0 2.1621954E-02 0.000000 0.000000 1.9257674E-04 0.000000 0.000000 0.000000 + Av 2018 9 23 20 0 1.8646888E-02 0.000000 0.000000 1.9251874E-04 0.000000 0.000000 0.000000 + Av 2018 9 23 21 0 1.9673463E-02 0.000000 0.000000 1.9246075E-04 0.000000 0.000000 0.000000 + Av 2018 9 23 22 0 1.9308634E-02 0.000000 0.000000 1.9240277E-04 0.000000 0.000000 0.000000 + Av 2018 9 23 23 0 1.9427612E-02 0.000000 0.000000 1.9234483E-04 0.000000 0.000000 0.000000 + Av 2018 9 23 24 0 1.9378368E-02 0.000000 0.000000 1.9228688E-04 0.000000 0.000000 0.000000 + Av 2018 9 24 1 0 1.9376485E-02 0.000000 0.000000 1.9206508E-04 0.000000 0.000000 0.000000 + Av 2018 9 24 2 0 1.9358143E-02 0.000000 0.000000 1.9200728E-04 0.000000 0.000000 0.000000 + Av 2018 9 24 3 0 1.9356668E-02 0.000000 0.000000 1.9194951E-04 0.000000 0.000000 0.000000 + Av 2018 9 24 4 0 1.9349331E-02 0.000000 0.000000 1.9189176E-04 0.000000 0.000000 0.000000 + Av 2018 9 24 5 0 1.9344036E-02 0.000000 0.000000 1.9183401E-04 0.000000 0.000000 0.000000 + Av 2018 9 24 6 0 1.9338030E-02 0.000000 0.000000 1.9177629E-04 0.000000 0.000000 0.000000 Av 2018 9 24 7 0 9.6676089E-03 0.000000 0.000000 0.000000 0.000000 0.000000 2.3245071E-03 Av 2018 9 24 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.9990034E-03 Av 2018 9 24 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.6734996E-03 @@ -6425,19 +6425,19 @@ Av 2018 9 24 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.6734996E-03 Av 2018 9 24 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.9990034E-03 Av 2018 9 24 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.3245071E-03 - Av 2018 9 24 18 0 1.2983117E-02 0.000000 0.000000 1.9108479E-04 0.000000 0.000000 0.000000 - Av 2018 9 24 19 0 2.1447983E-02 0.000000 0.000000 1.9102728E-04 0.000000 0.000000 0.000000 - Av 2018 9 24 20 0 1.8496860E-02 0.000000 0.000000 1.9096979E-04 0.000000 0.000000 0.000000 - Av 2018 9 24 21 0 1.9515179E-02 0.000000 0.000000 1.9091231E-04 0.000000 0.000000 0.000000 - Av 2018 9 24 22 0 1.9153293E-02 0.000000 0.000000 1.9085486E-04 0.000000 0.000000 0.000000 - Av 2018 9 24 23 0 1.9271318E-02 0.000000 0.000000 1.9079742E-04 0.000000 0.000000 0.000000 - Av 2018 9 24 24 0 1.9222476E-02 0.000000 0.000000 1.9074000E-04 0.000000 0.000000 0.000000 - Av 2018 9 25 1 0 1.9220933E-02 0.000000 0.000000 1.9052478E-04 0.000000 0.000000 0.000000 - Av 2018 9 25 2 0 1.9202953E-02 0.000000 0.000000 1.9046749E-04 0.000000 0.000000 0.000000 - Av 2018 9 25 3 0 1.9201420E-02 0.000000 0.000000 1.9041021E-04 0.000000 0.000000 0.000000 - Av 2018 9 25 4 0 1.9194171E-02 0.000000 0.000000 1.9035295E-04 0.000000 0.000000 0.000000 - 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Av 2018 9 25 18 0 1.2879048E-02 0.000000 0.000000 1.8955312E-04 0.000000 0.000000 0.000000 - Av 2018 9 25 19 0 2.1276064E-02 0.000000 0.000000 1.8949612E-04 0.000000 0.000000 0.000000 - Av 2018 9 25 20 0 1.8348604E-02 0.000000 0.000000 1.8943915E-04 0.000000 0.000000 0.000000 - Av 2018 9 25 21 0 1.9358765E-02 0.000000 0.000000 1.8938218E-04 0.000000 0.000000 0.000000 - Av 2018 9 25 22 0 1.8999785E-02 0.000000 0.000000 1.8932523E-04 0.000000 0.000000 0.000000 - Av 2018 9 25 23 0 1.9116871E-02 0.000000 0.000000 1.8926832E-04 0.000000 0.000000 0.000000 - Av 2018 9 25 24 0 1.9068426E-02 0.000000 0.000000 1.8921141E-04 0.000000 0.000000 0.000000 - Av 2018 9 26 1 0 1.9067211E-02 0.000000 0.000000 1.8900253E-04 0.000000 0.000000 0.000000 - Av 2018 9 26 2 0 1.9049581E-02 0.000000 0.000000 1.8894575E-04 0.000000 0.000000 0.000000 - Av 2018 9 26 3 0 1.9047998E-02 0.000000 0.000000 1.8888897E-04 0.000000 0.000000 0.000000 - Av 2018 9 26 4 0 1.9040834E-02 0.000000 0.000000 1.8883221E-04 0.000000 0.000000 0.000000 - Av 2018 9 26 5 0 1.9035615E-02 0.000000 0.000000 1.8877549E-04 0.000000 0.000000 0.000000 - Av 2018 9 26 6 0 1.9029722E-02 0.000000 0.000000 1.8871877E-04 0.000000 0.000000 0.000000 + Av 2018 9 25 18 0 1.2879048E-02 0.000000 0.000000 1.8955312E-04 0.000000 0.000000 0.000000 + Av 2018 9 25 19 0 2.1276064E-02 0.000000 0.000000 1.8949612E-04 0.000000 0.000000 0.000000 + Av 2018 9 25 20 0 1.8348604E-02 0.000000 0.000000 1.8943915E-04 0.000000 0.000000 0.000000 + Av 2018 9 25 21 0 1.9358765E-02 0.000000 0.000000 1.8938218E-04 0.000000 0.000000 0.000000 + Av 2018 9 25 22 0 1.8999785E-02 0.000000 0.000000 1.8932523E-04 0.000000 0.000000 0.000000 + Av 2018 9 25 23 0 1.9116871E-02 0.000000 0.000000 1.8926832E-04 0.000000 0.000000 0.000000 + Av 2018 9 25 24 0 1.9068426E-02 0.000000 0.000000 1.8921141E-04 0.000000 0.000000 0.000000 + Av 2018 9 26 1 0 1.9067211E-02 0.000000 0.000000 1.8900253E-04 0.000000 0.000000 0.000000 + Av 2018 9 26 2 0 1.9049581E-02 0.000000 0.000000 1.8894575E-04 0.000000 0.000000 0.000000 + Av 2018 9 26 3 0 1.9047998E-02 0.000000 0.000000 1.8888897E-04 0.000000 0.000000 0.000000 + Av 2018 9 26 4 0 1.9040834E-02 0.000000 0.000000 1.8883221E-04 0.000000 0.000000 0.000000 + Av 2018 9 26 5 0 1.9035615E-02 0.000000 0.000000 1.8877549E-04 0.000000 0.000000 0.000000 + Av 2018 9 26 6 0 1.9029722E-02 0.000000 0.000000 1.8871877E-04 0.000000 0.000000 0.000000 Av 2018 9 26 7 0 9.5134769E-03 0.000000 0.000000 0.000000 0.000000 0.000000 2.7830633E-03 Av 2018 9 26 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.2014624E-03 Av 2018 9 26 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 9.6198609E-03 @@ -6473,19 +6473,19 @@ Av 2018 9 26 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 9.6198609E-03 Av 2018 9 26 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.2014624E-03 Av 2018 9 26 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.7830633E-03 - Av 2018 9 26 18 0 1.2776205E-02 0.000000 0.000000 1.8803947E-04 0.000000 0.000000 0.000000 - Av 2018 9 26 19 0 2.1106172E-02 0.000000 0.000000 1.8798297E-04 0.000000 0.000000 0.000000 - Av 2018 9 26 20 0 1.8202091E-02 0.000000 0.000000 1.8792647E-04 0.000000 0.000000 0.000000 - Av 2018 9 26 21 0 1.9204192E-02 0.000000 0.000000 1.8787001E-04 0.000000 0.000000 0.000000 - Av 2018 9 26 22 0 1.8848080E-02 0.000000 0.000000 1.8781357E-04 0.000000 0.000000 0.000000 - Av 2018 9 26 23 0 1.8964233E-02 0.000000 0.000000 1.8775713E-04 0.000000 0.000000 0.000000 - Av 2018 9 26 24 0 1.8916178E-02 0.000000 0.000000 1.8770072E-04 0.000000 0.000000 0.000000 - Av 2018 9 27 1 0 1.8915277E-02 0.000000 0.000000 1.8749795E-04 0.000000 0.000000 0.000000 - Av 2018 9 27 2 0 1.8897990E-02 0.000000 0.000000 1.8744166E-04 0.000000 0.000000 0.000000 - Av 2018 9 27 3 0 1.8896352E-02 0.000000 0.000000 1.8738538E-04 0.000000 0.000000 0.000000 - Av 2018 9 27 4 0 1.8889274E-02 0.000000 0.000000 1.8732912E-04 0.000000 0.000000 0.000000 - Av 2018 9 27 5 0 1.8884093E-02 0.000000 0.000000 1.8727288E-04 0.000000 0.000000 0.000000 - Av 2018 9 27 6 0 1.8878251E-02 0.000000 0.000000 1.8721665E-04 0.000000 0.000000 0.000000 + Av 2018 9 26 18 0 1.2776205E-02 0.000000 0.000000 1.8803947E-04 0.000000 0.000000 0.000000 + Av 2018 9 26 19 0 2.1106172E-02 0.000000 0.000000 1.8798297E-04 0.000000 0.000000 0.000000 + Av 2018 9 26 20 0 1.8202091E-02 0.000000 0.000000 1.8792647E-04 0.000000 0.000000 0.000000 + Av 2018 9 26 21 0 1.9204192E-02 0.000000 0.000000 1.8787001E-04 0.000000 0.000000 0.000000 + Av 2018 9 26 22 0 1.8848080E-02 0.000000 0.000000 1.8781357E-04 0.000000 0.000000 0.000000 + Av 2018 9 26 23 0 1.8964233E-02 0.000000 0.000000 1.8775713E-04 0.000000 0.000000 0.000000 + Av 2018 9 26 24 0 1.8916178E-02 0.000000 0.000000 1.8770072E-04 0.000000 0.000000 0.000000 + Av 2018 9 27 1 0 1.8915277E-02 0.000000 0.000000 1.8749795E-04 0.000000 0.000000 0.000000 + Av 2018 9 27 2 0 1.8897990E-02 0.000000 0.000000 1.8744166E-04 0.000000 0.000000 0.000000 + Av 2018 9 27 3 0 1.8896352E-02 0.000000 0.000000 1.8738538E-04 0.000000 0.000000 0.000000 + Av 2018 9 27 4 0 1.8889274E-02 0.000000 0.000000 1.8732912E-04 0.000000 0.000000 0.000000 + Av 2018 9 27 5 0 1.8884093E-02 0.000000 0.000000 1.8727288E-04 0.000000 0.000000 0.000000 + Av 2018 9 27 6 0 1.8878251E-02 0.000000 0.000000 1.8721665E-04 0.000000 0.000000 0.000000 Av 2018 9 27 7 0 9.4377538E-03 0.000000 0.000000 0.000000 0.000000 0.000000 2.8895999E-03 Av 2018 9 27 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.5627419E-03 Av 2018 9 27 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.0235884E-02 @@ -6497,19 +6497,19 @@ Av 2018 9 27 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.0235884E-02 Av 2018 9 27 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.5627419E-03 Av 2018 9 27 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.8895999E-03 - Av 2018 9 27 18 0 1.2674551E-02 0.000000 0.000000 1.8654330E-04 0.000000 0.000000 0.000000 - Av 2018 9 27 19 0 2.0938240E-02 0.000000 0.000000 1.8648729E-04 0.000000 0.000000 0.000000 - Av 2018 9 27 20 0 1.8057272E-02 0.000000 0.000000 1.8643129E-04 0.000000 0.000000 0.000000 - Av 2018 9 27 21 0 1.9051403E-02 0.000000 0.000000 1.8637533E-04 0.000000 0.000000 0.000000 - Av 2018 9 27 22 0 1.8698128E-02 0.000000 0.000000 1.8631936E-04 0.000000 0.000000 0.000000 - Av 2018 9 27 23 0 1.8813360E-02 0.000000 0.000000 1.8626342E-04 0.000000 0.000000 0.000000 - Av 2018 9 27 24 0 1.8765695E-02 0.000000 0.000000 1.8620750E-04 0.000000 0.000000 0.000000 - Av 2018 9 28 1 0 1.8765094E-02 0.000000 0.000000 1.8601064E-04 0.000000 0.000000 0.000000 - Av 2018 9 28 2 0 1.8748134E-02 0.000000 0.000000 1.8595484E-04 0.000000 0.000000 0.000000 - Av 2018 9 28 3 0 1.8746451E-02 0.000000 0.000000 1.8589904E-04 0.000000 0.000000 0.000000 - Av 2018 9 28 4 0 1.8739454E-02 0.000000 0.000000 1.8584327E-04 0.000000 0.000000 0.000000 - Av 2018 9 28 5 0 1.8734310E-02 0.000000 0.000000 1.8578752E-04 0.000000 0.000000 0.000000 - Av 2018 9 28 6 0 1.8728524E-02 0.000000 0.000000 1.8573178E-04 0.000000 0.000000 0.000000 + Av 2018 9 27 18 0 1.2674551E-02 0.000000 0.000000 1.8654330E-04 0.000000 0.000000 0.000000 + Av 2018 9 27 19 0 2.0938240E-02 0.000000 0.000000 1.8648729E-04 0.000000 0.000000 0.000000 + Av 2018 9 27 20 0 1.8057272E-02 0.000000 0.000000 1.8643129E-04 0.000000 0.000000 0.000000 + Av 2018 9 27 21 0 1.9051403E-02 0.000000 0.000000 1.8637533E-04 0.000000 0.000000 0.000000 + Av 2018 9 27 22 0 1.8698128E-02 0.000000 0.000000 1.8631936E-04 0.000000 0.000000 0.000000 + Av 2018 9 27 23 0 1.8813360E-02 0.000000 0.000000 1.8626342E-04 0.000000 0.000000 0.000000 + Av 2018 9 27 24 0 1.8765695E-02 0.000000 0.000000 1.8620750E-04 0.000000 0.000000 0.000000 + Av 2018 9 28 1 0 1.8765094E-02 0.000000 0.000000 1.8601064E-04 0.000000 0.000000 0.000000 + Av 2018 9 28 2 0 1.8748134E-02 0.000000 0.000000 1.8595484E-04 0.000000 0.000000 0.000000 + Av 2018 9 28 3 0 1.8746451E-02 0.000000 0.000000 1.8589904E-04 0.000000 0.000000 0.000000 + Av 2018 9 28 4 0 1.8739454E-02 0.000000 0.000000 1.8584327E-04 0.000000 0.000000 0.000000 + Av 2018 9 28 5 0 1.8734310E-02 0.000000 0.000000 1.8578752E-04 0.000000 0.000000 0.000000 + Av 2018 9 28 6 0 1.8728524E-02 0.000000 0.000000 1.8573178E-04 0.000000 0.000000 0.000000 Av 2018 9 28 7 0 9.3629016E-03 0.000000 0.000000 0.000000 0.000000 0.000000 2.9389861E-03 Av 2018 9 28 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.8098633E-03 Av 2018 9 28 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.0680740E-02 @@ -6521,19 +6521,19 @@ Av 2018 9 28 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.0680740E-02 Av 2018 9 28 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.8098633E-03 Av 2018 9 28 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.9389861E-03 - Av 2018 9 28 18 0 1.2574057E-02 0.000000 0.000000 1.8506426E-04 0.000000 0.000000 0.000000 - Av 2018 9 28 19 0 2.0772230E-02 0.000000 0.000000 1.8500873E-04 0.000000 0.000000 0.000000 - Av 2018 9 28 20 0 1.7914109E-02 0.000000 0.000000 1.8495323E-04 0.000000 0.000000 0.000000 - Av 2018 9 28 21 0 1.8900361E-02 0.000000 0.000000 1.8489774E-04 0.000000 0.000000 0.000000 - Av 2018 9 28 22 0 1.8549893E-02 0.000000 0.000000 1.8484227E-04 0.000000 0.000000 0.000000 - Av 2018 9 28 23 0 1.8664218E-02 0.000000 0.000000 1.8478683E-04 0.000000 0.000000 0.000000 - Av 2018 9 28 24 0 1.8616933E-02 0.000000 0.000000 1.8473140E-04 0.000000 0.000000 0.000000 - Av 2018 9 29 1 0 1.8616620E-02 0.000000 0.000000 1.8454023E-04 0.000000 0.000000 0.000000 - Av 2018 9 29 2 0 1.8599981E-02 0.000000 0.000000 1.8448490E-04 0.000000 0.000000 0.000000 - Av 2018 9 29 3 0 1.8598251E-02 0.000000 0.000000 1.8442961E-04 0.000000 0.000000 0.000000 - Av 2018 9 29 4 0 1.8591341E-02 0.000000 0.000000 1.8437432E-04 0.000000 0.000000 0.000000 - Av 2018 9 29 5 0 1.8586230E-02 0.000000 0.000000 1.8431905E-04 0.000000 0.000000 0.000000 - Av 2018 9 29 6 0 1.8580496E-02 0.000000 0.000000 1.8426380E-04 0.000000 0.000000 0.000000 + Av 2018 9 28 18 0 1.2574057E-02 0.000000 0.000000 1.8506426E-04 0.000000 0.000000 0.000000 + Av 2018 9 28 19 0 2.0772230E-02 0.000000 0.000000 1.8500873E-04 0.000000 0.000000 0.000000 + Av 2018 9 28 20 0 1.7914109E-02 0.000000 0.000000 1.8495323E-04 0.000000 0.000000 0.000000 + Av 2018 9 28 21 0 1.8900361E-02 0.000000 0.000000 1.8489774E-04 0.000000 0.000000 0.000000 + Av 2018 9 28 22 0 1.8549893E-02 0.000000 0.000000 1.8484227E-04 0.000000 0.000000 0.000000 + Av 2018 9 28 23 0 1.8664218E-02 0.000000 0.000000 1.8478683E-04 0.000000 0.000000 0.000000 + Av 2018 9 28 24 0 1.8616933E-02 0.000000 0.000000 1.8473140E-04 0.000000 0.000000 0.000000 + Av 2018 9 29 1 0 1.8616620E-02 0.000000 0.000000 1.8454023E-04 0.000000 0.000000 0.000000 + Av 2018 9 29 2 0 1.8599981E-02 0.000000 0.000000 1.8448490E-04 0.000000 0.000000 0.000000 + Av 2018 9 29 3 0 1.8598251E-02 0.000000 0.000000 1.8442961E-04 0.000000 0.000000 0.000000 + Av 2018 9 29 4 0 1.8591341E-02 0.000000 0.000000 1.8437432E-04 0.000000 0.000000 0.000000 + Av 2018 9 29 5 0 1.8586230E-02 0.000000 0.000000 1.8431905E-04 0.000000 0.000000 0.000000 + Av 2018 9 29 6 0 1.8580496E-02 0.000000 0.000000 1.8426380E-04 0.000000 0.000000 0.000000 Av 2018 9 29 7 0 9.2888987E-03 0.000000 0.000000 0.000000 0.000000 0.000000 2.2237787E-03 Av 2018 9 29 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.2622920E-03 Av 2018 9 29 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 8.3008055E-03 @@ -6545,19 +6545,19 @@ Av 2018 9 29 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 8.3008055E-03 Av 2018 9 29 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.2622920E-03 Av 2018 9 29 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 9.9999802E-03 2.2237787E-03 - Av 2018 9 29 18 0 1.2474707E-02 0.000000 0.000000 1.8360202E-04 0.000000 0.000000 0.000000 - Av 2018 9 29 19 0 2.0608108E-02 0.000000 0.000000 1.8354699E-04 0.000000 0.000000 0.000000 - Av 2018 9 29 20 0 1.7772574E-02 0.000000 0.000000 1.8349197E-04 0.000000 0.000000 0.000000 - Av 2018 9 29 21 0 1.8751040E-02 0.000000 0.000000 1.8343698E-04 0.000000 0.000000 0.000000 - Av 2018 9 29 22 0 1.8403344E-02 0.000000 0.000000 1.8338198E-04 0.000000 0.000000 0.000000 - Av 2018 9 29 23 0 1.8516768E-02 0.000000 0.000000 1.8332699E-04 0.000000 0.000000 0.000000 - Av 2018 9 29 24 0 1.8469859E-02 0.000000 0.000000 1.8327203E-04 0.000000 0.000000 0.000000 - Av 2018 9 30 1 0 1.8469822E-02 0.000000 0.000000 1.8308636E-04 0.000000 0.000000 0.000000 - Av 2018 9 30 2 0 1.8453492E-02 0.000000 0.000000 1.8303150E-04 0.000000 0.000000 0.000000 - Av 2018 9 30 3 0 1.8451717E-02 0.000000 0.000000 1.8297667E-04 0.000000 0.000000 0.000000 - Av 2018 9 30 4 0 1.8444885E-02 0.000000 0.000000 1.8292185E-04 0.000000 0.000000 0.000000 - 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Av 2018 10 2 18 0 1.2183255E-02 0.000000 0.000000 1.7931245E-04 0.000000 0.000000 0.000000 - Av 2018 10 2 19 0 2.0126641E-02 0.000000 0.000000 1.7925883E-04 0.000000 0.000000 0.000000 - Av 2018 10 2 20 0 1.7357368E-02 0.000000 0.000000 1.7920521E-04 0.000000 0.000000 0.000000 - Av 2018 10 2 21 0 1.8312981E-02 0.000000 0.000000 1.7915158E-04 0.000000 0.000000 0.000000 - Av 2018 10 2 22 0 1.7973421E-02 0.000000 0.000000 1.7909799E-04 0.000000 0.000000 0.000000 - Av 2018 10 2 23 0 1.8084208E-02 0.000000 0.000000 1.7904441E-04 0.000000 0.000000 0.000000 - Av 2018 10 2 24 0 1.8038405E-02 0.000000 0.000000 1.7899084E-04 0.000000 0.000000 0.000000 - Av 2018 10 3 1 0 1.8039118E-02 0.000000 0.000000 1.7882053E-04 0.000000 0.000000 0.000000 - Av 2018 10 3 2 0 1.8023668E-02 0.000000 0.000000 1.7876706E-04 0.000000 0.000000 0.000000 - Av 2018 10 3 3 0 1.8021777E-02 0.000000 0.000000 1.7871363E-04 0.000000 0.000000 0.000000 - Av 2018 10 3 4 0 1.8015174E-02 0.000000 0.000000 1.7866021E-04 0.000000 0.000000 0.000000 - Av 2018 10 3 5 0 1.8010212E-02 0.000000 0.000000 1.7860680E-04 0.000000 0.000000 0.000000 - Av 2018 10 3 6 0 1.8004680E-02 0.000000 0.000000 1.7855340E-04 0.000000 0.000000 0.000000 + Av 2018 10 2 18 0 1.2183255E-02 0.000000 0.000000 1.7931245E-04 0.000000 0.000000 0.000000 + Av 2018 10 2 19 0 2.0126641E-02 0.000000 0.000000 1.7925883E-04 0.000000 0.000000 0.000000 + Av 2018 10 2 20 0 1.7357368E-02 0.000000 0.000000 1.7920521E-04 0.000000 0.000000 0.000000 + Av 2018 10 2 21 0 1.8312981E-02 0.000000 0.000000 1.7915158E-04 0.000000 0.000000 0.000000 + Av 2018 10 2 22 0 1.7973421E-02 0.000000 0.000000 1.7909799E-04 0.000000 0.000000 0.000000 + Av 2018 10 2 23 0 1.8084208E-02 0.000000 0.000000 1.7904441E-04 0.000000 0.000000 0.000000 + Av 2018 10 2 24 0 1.8038405E-02 0.000000 0.000000 1.7899084E-04 0.000000 0.000000 0.000000 + Av 2018 10 3 1 0 1.8039118E-02 0.000000 0.000000 1.7882053E-04 0.000000 0.000000 0.000000 + Av 2018 10 3 2 0 1.8023668E-02 0.000000 0.000000 1.7876706E-04 0.000000 0.000000 0.000000 + Av 2018 10 3 3 0 1.8021777E-02 0.000000 0.000000 1.7871363E-04 0.000000 0.000000 0.000000 + Av 2018 10 3 4 0 1.8015174E-02 0.000000 0.000000 1.7866021E-04 0.000000 0.000000 0.000000 + Av 2018 10 3 5 0 1.8010212E-02 0.000000 0.000000 1.7860680E-04 0.000000 0.000000 0.000000 + Av 2018 10 3 6 0 1.8004680E-02 0.000000 0.000000 1.7855340E-04 0.000000 0.000000 0.000000 Av 2018 10 3 7 0 9.0010334E-03 0.000000 0.000000 0.000000 0.000000 0.000000 1.3214825E-03 Av 2018 10 3 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.4908361E-03 Av 2018 10 3 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.6601898E-03 @@ -6641,19 +6641,19 @@ Av 2018 10 3 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.6601898E-03 Av 2018 10 3 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.4908361E-03 Av 2018 10 3 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.3214825E-03 - Av 2018 10 3 18 0 1.2088229E-02 0.000000 0.000000 1.7791387E-04 0.000000 0.000000 0.000000 - Av 2018 10 3 19 0 1.9969661E-02 0.000000 0.000000 1.7786068E-04 0.000000 0.000000 0.000000 - Av 2018 10 3 20 0 1.7221991E-02 0.000000 0.000000 1.7780751E-04 0.000000 0.000000 0.000000 - Av 2018 10 3 21 0 1.8170156E-02 0.000000 0.000000 1.7775435E-04 0.000000 0.000000 0.000000 - Av 2018 10 3 22 0 1.7833246E-02 0.000000 0.000000 1.7770121E-04 0.000000 0.000000 0.000000 - Av 2018 10 3 23 0 1.7943172E-02 0.000000 0.000000 1.7764809E-04 0.000000 0.000000 0.000000 - Av 2018 10 3 24 0 1.7897733E-02 0.000000 0.000000 1.7759499E-04 0.000000 0.000000 0.000000 - Av 2018 10 4 1 0 1.7898677E-02 0.000000 0.000000 1.7742944E-04 0.000000 0.000000 0.000000 - Av 2018 10 4 2 0 1.7883498E-02 0.000000 0.000000 1.7737642E-04 0.000000 0.000000 0.000000 - Av 2018 10 4 3 0 1.7881572E-02 0.000000 0.000000 1.7732343E-04 0.000000 0.000000 0.000000 - Av 2018 10 4 4 0 1.7875042E-02 0.000000 0.000000 1.7727044E-04 0.000000 0.000000 0.000000 - Av 2018 10 4 5 0 1.7870113E-02 0.000000 0.000000 1.7721747E-04 0.000000 0.000000 0.000000 - Av 2018 10 4 6 0 1.7864630E-02 0.000000 0.000000 1.7716453E-04 0.000000 0.000000 0.000000 + Av 2018 10 3 18 0 1.2088229E-02 0.000000 0.000000 1.7791387E-04 0.000000 0.000000 0.000000 + Av 2018 10 3 19 0 1.9969661E-02 0.000000 0.000000 1.7786068E-04 0.000000 0.000000 0.000000 + Av 2018 10 3 20 0 1.7221991E-02 0.000000 0.000000 1.7780751E-04 0.000000 0.000000 0.000000 + Av 2018 10 3 21 0 1.8170156E-02 0.000000 0.000000 1.7775435E-04 0.000000 0.000000 0.000000 + Av 2018 10 3 22 0 1.7833246E-02 0.000000 0.000000 1.7770121E-04 0.000000 0.000000 0.000000 + Av 2018 10 3 23 0 1.7943172E-02 0.000000 0.000000 1.7764809E-04 0.000000 0.000000 0.000000 + Av 2018 10 3 24 0 1.7897733E-02 0.000000 0.000000 1.7759499E-04 0.000000 0.000000 0.000000 + Av 2018 10 4 1 0 1.7898677E-02 0.000000 0.000000 1.7742944E-04 0.000000 0.000000 0.000000 + Av 2018 10 4 2 0 1.7883498E-02 0.000000 0.000000 1.7737642E-04 0.000000 0.000000 0.000000 + Av 2018 10 4 3 0 1.7881572E-02 0.000000 0.000000 1.7732343E-04 0.000000 0.000000 0.000000 + Av 2018 10 4 4 0 1.7875042E-02 0.000000 0.000000 1.7727044E-04 0.000000 0.000000 0.000000 + Av 2018 10 4 5 0 1.7870113E-02 0.000000 0.000000 1.7721747E-04 0.000000 0.000000 0.000000 + Av 2018 10 4 6 0 1.7864630E-02 0.000000 0.000000 1.7716453E-04 0.000000 0.000000 0.000000 Av 2018 10 4 7 0 8.9310203E-03 0.000000 0.000000 0.000000 0.000000 0.000000 1.4343989E-03 Av 2018 10 4 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.8988211E-03 Av 2018 10 4 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.3632433E-03 @@ -6665,19 +6665,19 @@ Av 2018 10 4 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.3632433E-03 Av 2018 10 4 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.8988211E-03 Av 2018 10 4 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.4343989E-03 - Av 2018 10 4 18 0 1.1994231E-02 0.000000 0.000000 1.7653040E-04 0.000000 0.000000 0.000000 - Av 2018 10 4 19 0 1.9814376E-02 0.000000 0.000000 1.7647765E-04 0.000000 0.000000 0.000000 - Av 2018 10 4 20 0 1.7088078E-02 0.000000 0.000000 1.7642493E-04 0.000000 0.000000 0.000000 - Av 2018 10 4 21 0 1.8028870E-02 0.000000 0.000000 1.7637221E-04 0.000000 0.000000 0.000000 - Av 2018 10 4 22 0 1.7694585E-02 0.000000 0.000000 1.7631952E-04 0.000000 0.000000 0.000000 - Av 2018 10 4 23 0 1.7803660E-02 0.000000 0.000000 1.7626684E-04 0.000000 0.000000 0.000000 - Av 2018 10 4 24 0 1.7758578E-02 0.000000 0.000000 1.7621419E-04 0.000000 0.000000 0.000000 - Av 2018 10 5 1 0 1.7759740E-02 0.000000 0.000000 1.7605323E-04 0.000000 0.000000 0.000000 - Av 2018 10 5 2 0 1.7744828E-02 0.000000 0.000000 1.7600067E-04 0.000000 0.000000 0.000000 - Av 2018 10 5 3 0 1.7742870E-02 0.000000 0.000000 1.7594811E-04 0.000000 0.000000 0.000000 - Av 2018 10 5 4 0 1.7736411E-02 0.000000 0.000000 1.7589558E-04 0.000000 0.000000 0.000000 - Av 2018 10 5 5 0 1.7731519E-02 0.000000 0.000000 1.7584306E-04 0.000000 0.000000 0.000000 - Av 2018 10 5 6 0 1.7726084E-02 0.000000 0.000000 1.7579056E-04 0.000000 0.000000 0.000000 + Av 2018 10 4 18 0 1.1994231E-02 0.000000 0.000000 1.7653040E-04 0.000000 0.000000 0.000000 + Av 2018 10 4 19 0 1.9814376E-02 0.000000 0.000000 1.7647765E-04 0.000000 0.000000 0.000000 + Av 2018 10 4 20 0 1.7088078E-02 0.000000 0.000000 1.7642493E-04 0.000000 0.000000 0.000000 + Av 2018 10 4 21 0 1.8028870E-02 0.000000 0.000000 1.7637221E-04 0.000000 0.000000 0.000000 + Av 2018 10 4 22 0 1.7694585E-02 0.000000 0.000000 1.7631952E-04 0.000000 0.000000 0.000000 + Av 2018 10 4 23 0 1.7803660E-02 0.000000 0.000000 1.7626684E-04 0.000000 0.000000 0.000000 + Av 2018 10 4 24 0 1.7758578E-02 0.000000 0.000000 1.7621419E-04 0.000000 0.000000 0.000000 + Av 2018 10 5 1 0 1.7759740E-02 0.000000 0.000000 1.7605323E-04 0.000000 0.000000 0.000000 + Av 2018 10 5 2 0 1.7744828E-02 0.000000 0.000000 1.7600067E-04 0.000000 0.000000 0.000000 + Av 2018 10 5 3 0 1.7742870E-02 0.000000 0.000000 1.7594811E-04 0.000000 0.000000 0.000000 + Av 2018 10 5 4 0 1.7736411E-02 0.000000 0.000000 1.7589558E-04 0.000000 0.000000 0.000000 + Av 2018 10 5 5 0 1.7731519E-02 0.000000 0.000000 1.7584306E-04 0.000000 0.000000 0.000000 + Av 2018 10 5 6 0 1.7726084E-02 0.000000 0.000000 1.7579056E-04 0.000000 0.000000 0.000000 Av 2018 10 5 7 0 8.8617560E-03 0.000000 0.000000 0.000000 0.000000 0.000000 1.0521354E-03 Av 2018 10 5 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 2.9999940E-02 2.9479065E-03 Av 2018 10 5 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 1.9999960E-02 4.8436774E-03 @@ -6689,19 +6689,19 @@ Av 2018 10 5 15 0 0.1751103 0.000000 0.000000 0.000000 1.0746576E-02 9.9999802E-03 4.8436774E-03 Av 2018 10 5 16 0 0.1088311 3.6639000E-10 0.000000 0.000000 1.4034630E-02 1.9999960E-02 2.9479065E-03 Av 2018 10 5 17 0 8.9288697E-02 0.000000 0.000000 0.000000 3.7082045E-03 0.000000 1.0521354E-03 - Av 2018 10 5 18 0 2.0975329E-02 0.000000 0.000000 1.7569037E-04 1.3302333E-03 0.000000 0.000000 - Av 2018 10 5 19 0 5.3980827E-02 0.000000 0.000000 1.7564843E-04 4.1097552E-03 9.9999802E-03 0.000000 - Av 2018 10 5 20 0 4.4771843E-02 0.000000 0.000000 1.7561432E-04 1.6646971E-03 0.000000 0.000000 - Av 2018 10 5 21 0 0.2290310 2.5912188E-09 0.000000 1.7562829E-04 3.0626049E-02 3.9999921E-02 0.000000 - Av 2018 10 5 22 0 0.9077531 2.5283196E-08 0.000000 1.7588939E-04 0.1084845 0.1199998 0.000000 - Av 2018 10 5 23 0 0.6904883 2.4536254E-10 0.000000 1.7620400E-04 2.3838505E-02 9.9999802E-03 0.000000 - Av 2018 10 5 24 0 0.1527172 9.9656172E-10 0.000000 1.7623529E-04 2.0714479E-02 1.9999960E-02 0.000000 - Av 2018 10 6 1 0 0.1957240 3.0934080E-10 0.000000 1.7616365E-04 1.2208721E-02 9.9999802E-03 0.000000 - Av 2018 10 6 2 0 0.1647200 1.0447166E-09 0.000000 1.7619875E-04 1.8167142E-02 1.9999960E-02 0.000000 - Av 2018 10 6 3 0 0.1734025 2.7000135E-10 0.000000 1.7624663E-04 1.1917805E-02 9.9999802E-03 0.000000 - Av 2018 10 6 4 0 6.7353733E-02 0.000000 0.000000 1.7623298E-04 3.1883880E-03 0.000000 0.000000 - Av 2018 10 6 5 0 3.0236822E-02 0.000000 0.000000 1.7618020E-04 1.1845864E-03 0.000000 0.000000 - Av 2018 10 6 6 0 2.5170902E-02 0.000000 0.000000 1.7612743E-04 5.4436357E-04 0.000000 0.000000 + Av 2018 10 5 18 0 2.0975329E-02 0.000000 0.000000 1.7569037E-04 1.3302333E-03 0.000000 0.000000 + Av 2018 10 5 19 0 5.3980827E-02 0.000000 0.000000 1.7564843E-04 4.1097552E-03 9.9999802E-03 0.000000 + Av 2018 10 5 20 0 4.4771843E-02 0.000000 0.000000 1.7561432E-04 1.6646971E-03 0.000000 0.000000 + Av 2018 10 5 21 0 0.2290310 2.5912188E-09 0.000000 1.7562829E-04 3.0626049E-02 3.9999921E-02 0.000000 + Av 2018 10 5 22 0 0.9077531 2.5283196E-08 0.000000 1.7588939E-04 0.1084845 0.1199998 0.000000 + Av 2018 10 5 23 0 0.6904883 2.4536254E-10 0.000000 1.7620400E-04 2.3838505E-02 9.9999802E-03 0.000000 + Av 2018 10 5 24 0 0.1527172 9.9656172E-10 0.000000 1.7623529E-04 2.0714479E-02 1.9999960E-02 0.000000 + Av 2018 10 6 1 0 0.1957240 3.0934080E-10 0.000000 1.7616365E-04 1.2208721E-02 9.9999802E-03 0.000000 + Av 2018 10 6 2 0 0.1647200 1.0447166E-09 0.000000 1.7619875E-04 1.8167142E-02 1.9999960E-02 0.000000 + Av 2018 10 6 3 0 0.1734025 2.7000135E-10 0.000000 1.7624663E-04 1.1917805E-02 9.9999802E-03 0.000000 + Av 2018 10 6 4 0 6.7353733E-02 0.000000 0.000000 1.7623298E-04 3.1883880E-03 0.000000 0.000000 + Av 2018 10 6 5 0 3.0236822E-02 0.000000 0.000000 1.7618020E-04 1.1845864E-03 0.000000 0.000000 + Av 2018 10 6 6 0 2.5170902E-02 0.000000 0.000000 1.7612743E-04 5.4436357E-04 0.000000 0.000000 Av 2018 10 6 7 0 1.0598555E-02 0.000000 0.000000 0.000000 2.8920884E-04 0.000000 1.2798238E-03 Av 2018 10 6 8 0 3.5395548E-02 2.1667726E-10 0.000000 0.000000 5.2094953E-03 9.9999802E-03 3.7036939E-03 Av 2018 10 6 9 0 3.6914673E-02 0.000000 0.000000 0.000000 2.0865283E-03 0.000000 6.1275638E-03 @@ -6713,19 +6713,19 @@ Av 2018 10 6 15 0 6.4417010E-04 0.000000 0.000000 0.000000 6.3426829E-05 0.000000 6.1275638E-03 Av 2018 10 6 16 0 4.3614890E-04 0.000000 0.000000 0.000000 4.5519802E-05 0.000000 3.7036939E-03 Av 2018 10 6 17 0 3.4913601E-04 0.000000 0.000000 0.000000 3.3802218E-05 0.000000 1.2798238E-03 - Av 2018 10 6 18 0 1.3201229E-02 0.000000 0.000000 1.7555016E-04 1.7293057E-04 0.000000 0.000000 - Av 2018 10 6 19 0 2.0436464E-02 0.000000 0.000000 1.7549758E-04 0.000000 0.000000 0.000000 - Av 2018 10 6 20 0 1.6738601E-02 0.000000 0.000000 1.7544503E-04 0.000000 0.000000 0.000000 - Av 2018 10 6 21 0 1.8017242E-02 0.000000 0.000000 1.7539250E-04 0.000000 0.000000 0.000000 - Av 2018 10 6 22 0 1.7565507E-02 0.000000 0.000000 1.7533997E-04 0.000000 0.000000 0.000000 - Av 2018 10 6 23 0 1.7715443E-02 0.000000 0.000000 1.7528745E-04 0.000000 0.000000 0.000000 - Av 2018 10 6 24 0 1.7656174E-02 0.000000 0.000000 1.7523495E-04 0.000000 0.000000 0.000000 - Av 2018 10 7 1 0 1.7661501E-02 0.000000 0.000000 1.7506252E-04 0.000000 0.000000 0.000000 - Av 2018 10 7 2 0 1.7644372E-02 0.000000 0.000000 1.7501014E-04 0.000000 0.000000 0.000000 - Av 2018 10 7 3 0 1.7643210E-02 0.000000 0.000000 1.7495776E-04 0.000000 0.000000 0.000000 - Av 2018 10 7 4 0 1.7636498E-02 0.000000 0.000000 1.7490541E-04 0.000000 0.000000 0.000000 - Av 2018 10 7 5 0 1.7631719E-02 0.000000 0.000000 1.7485308E-04 0.000000 0.000000 0.000000 - Av 2018 10 7 6 0 1.7626269E-02 0.000000 0.000000 1.7480073E-04 0.000000 0.000000 0.000000 + Av 2018 10 6 18 0 1.3201229E-02 0.000000 0.000000 1.7555016E-04 1.7293057E-04 0.000000 0.000000 + Av 2018 10 6 19 0 2.0436464E-02 0.000000 0.000000 1.7549758E-04 0.000000 0.000000 0.000000 + Av 2018 10 6 20 0 1.6738601E-02 0.000000 0.000000 1.7544503E-04 0.000000 0.000000 0.000000 + Av 2018 10 6 21 0 1.8017242E-02 0.000000 0.000000 1.7539250E-04 0.000000 0.000000 0.000000 + Av 2018 10 6 22 0 1.7565507E-02 0.000000 0.000000 1.7533997E-04 0.000000 0.000000 0.000000 + Av 2018 10 6 23 0 1.7715443E-02 0.000000 0.000000 1.7528745E-04 0.000000 0.000000 0.000000 + Av 2018 10 6 24 0 1.7656174E-02 0.000000 0.000000 1.7523495E-04 0.000000 0.000000 0.000000 + Av 2018 10 7 1 0 1.7661501E-02 0.000000 0.000000 1.7506252E-04 0.000000 0.000000 0.000000 + Av 2018 10 7 2 0 1.7644372E-02 0.000000 0.000000 1.7501014E-04 0.000000 0.000000 0.000000 + Av 2018 10 7 3 0 1.7643210E-02 0.000000 0.000000 1.7495776E-04 0.000000 0.000000 0.000000 + Av 2018 10 7 4 0 1.7636498E-02 0.000000 0.000000 1.7490541E-04 0.000000 0.000000 0.000000 + Av 2018 10 7 5 0 1.7631719E-02 0.000000 0.000000 1.7485308E-04 0.000000 0.000000 0.000000 + Av 2018 10 7 6 0 1.7626269E-02 0.000000 0.000000 1.7480073E-04 0.000000 0.000000 0.000000 Av 2018 10 7 7 0 8.8118613E-03 0.000000 0.000000 0.000000 0.000000 0.000000 9.9274714E-04 Av 2018 10 7 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.9738797E-03 Av 2018 10 7 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 9.9999802E-03 4.9550119E-03 @@ -6737,19 +6737,19 @@ Av 2018 10 7 15 0 5.8506923E-03 0.000000 0.000000 0.000000 6.6639716E-04 0.000000 4.9550119E-03 Av 2018 10 7 16 0 4.8736408E-03 0.000000 0.000000 0.000000 3.4157460E-04 9.9999802E-03 2.9738797E-03 Av 2018 10 7 17 0 2.0784140E-03 0.000000 0.000000 0.000000 1.9610449E-04 0.000000 9.9274714E-04 - Av 2018 10 7 18 0 1.3269848E-02 0.000000 0.000000 1.7426017E-04 1.2235838E-04 0.000000 0.000000 - Av 2018 10 7 19 0 2.1103710E-02 0.000000 0.000000 1.7421035E-04 1.2775941E-04 9.9999802E-03 0.000000 - Av 2018 10 7 20 0 5.8210701E-02 2.8328467E-10 0.000000 1.7418456E-04 5.9424103E-03 9.9999802E-03 0.000000 - Av 2018 10 7 21 0 0.1602345 1.1502896E-09 0.000000 1.7421594E-04 1.6893914E-02 1.9999960E-02 0.000000 - Av 2018 10 7 22 0 0.2197058 1.1858458E-09 0.000000 1.7428634E-04 1.9660581E-02 1.9999960E-02 0.000000 - Av 2018 10 7 23 0 0.1143129 0.000000 0.000000 1.7431227E-04 4.6236250E-03 0.000000 0.000000 - Av 2018 10 7 24 0 7.2116747E-02 3.0572581E-10 0.000000 1.7428231E-04 8.3216811E-03 9.9999802E-03 0.000000 - Av 2018 10 8 1 0 0.1224793 3.7314604E-10 0.000000 1.7417644E-04 9.7624194E-03 9.9999802E-03 0.000000 - Av 2018 10 8 2 0 0.1166501 3.1462269E-10 0.000000 1.7420117E-04 9.9692000E-03 9.9999802E-03 0.000000 - Av 2018 10 8 3 0 0.1202320 3.1892958E-10 0.000000 1.7422142E-04 9.9959997E-03 9.9999802E-03 0.000000 - Av 2018 10 8 4 0 0.1192176 3.2349942E-10 0.000000 1.7424168E-04 9.9994624E-03 9.9999802E-03 0.000000 - Av 2018 10 8 5 0 0.1195934 3.2787056E-10 0.000000 1.7426192E-04 9.9999094E-03 9.9999802E-03 0.000000 - Av 2018 10 8 6 0 0.1194712 3.3227252E-10 0.000000 1.7428216E-04 9.9999672E-03 9.9999802E-03 0.000000 + Av 2018 10 7 18 0 1.3269848E-02 0.000000 0.000000 1.7426017E-04 1.2235838E-04 0.000000 0.000000 + Av 2018 10 7 19 0 2.1103710E-02 0.000000 0.000000 1.7421035E-04 1.2775941E-04 9.9999802E-03 0.000000 + Av 2018 10 7 20 0 5.8210701E-02 2.8328467E-10 0.000000 1.7418456E-04 5.9424103E-03 9.9999802E-03 0.000000 + Av 2018 10 7 21 0 0.1602345 1.1502896E-09 0.000000 1.7421594E-04 1.6893914E-02 1.9999960E-02 0.000000 + Av 2018 10 7 22 0 0.2197058 1.1858458E-09 0.000000 1.7428634E-04 1.9660581E-02 1.9999960E-02 0.000000 + Av 2018 10 7 23 0 0.1143129 0.000000 0.000000 1.7431227E-04 4.6236250E-03 0.000000 0.000000 + Av 2018 10 7 24 0 7.2116747E-02 3.0572581E-10 0.000000 1.7428231E-04 8.3216811E-03 9.9999802E-03 0.000000 + Av 2018 10 8 1 0 0.1224793 3.7314604E-10 0.000000 1.7417644E-04 9.7624194E-03 9.9999802E-03 0.000000 + Av 2018 10 8 2 0 0.1166501 3.1462269E-10 0.000000 1.7420117E-04 9.9692000E-03 9.9999802E-03 0.000000 + Av 2018 10 8 3 0 0.1202320 3.1892958E-10 0.000000 1.7422142E-04 9.9959997E-03 9.9999802E-03 0.000000 + Av 2018 10 8 4 0 0.1192176 3.2349942E-10 0.000000 1.7424168E-04 9.9994624E-03 9.9999802E-03 0.000000 + Av 2018 10 8 5 0 0.1195934 3.2787056E-10 0.000000 1.7426192E-04 9.9999094E-03 9.9999802E-03 0.000000 + Av 2018 10 8 6 0 0.1194712 3.3227252E-10 0.000000 1.7428216E-04 9.9999672E-03 9.9999802E-03 0.000000 Av 2018 10 8 7 0 5.9768621E-02 0.000000 0.000000 0.000000 2.8066770E-03 0.000000 1.0918215E-03 Av 2018 10 8 8 0 7.2940653E-03 0.000000 0.000000 0.000000 1.0735365E-03 0.000000 3.3939169E-03 Av 2018 10 8 9 0 2.9624272E-02 1.1564933E-10 0.000000 0.000000 3.6433786E-03 9.9999802E-03 5.6960122E-03 @@ -6761,19 +6761,19 @@ Av 2018 10 8 15 0 8.7930867E-04 0.000000 0.000000 0.000000 8.1581995E-05 9.9999802E-03 5.6960122E-03 Av 2018 10 8 16 0 6.4325967E-04 0.000000 0.000000 0.000000 5.6935976E-05 0.000000 3.3939169E-03 Av 2018 10 8 17 0 4.0673997E-04 0.000000 0.000000 0.000000 4.1331441E-05 0.000000 1.0918215E-03 - Av 2018 10 8 18 0 1.3261723E-02 0.000000 0.000000 1.7374493E-04 1.9510234E-04 0.000000 0.000000 - Av 2018 10 8 19 0 2.0320799E-02 0.000000 0.000000 1.7369287E-04 0.000000 0.000000 0.000000 - Av 2018 10 8 20 0 1.6533613E-02 0.000000 0.000000 1.7364082E-04 0.000000 0.000000 0.000000 - Av 2018 10 8 21 0 1.7843381E-02 0.000000 0.000000 1.7358879E-04 0.000000 0.000000 0.000000 - Av 2018 10 8 22 0 1.7380893E-02 0.000000 0.000000 1.7353678E-04 0.000000 0.000000 0.000000 - Av 2018 10 8 23 0 1.7534638E-02 0.000000 0.000000 1.7348479E-04 0.000000 0.000000 0.000000 - Av 2018 10 8 24 0 1.7474115E-02 0.000000 0.000000 1.7343280E-04 0.000000 0.000000 0.000000 - Av 2018 10 9 1 0 1.7479829E-02 0.000000 0.000000 1.7325915E-04 0.000000 0.000000 0.000000 - Av 2018 10 9 2 0 1.7462518E-02 0.000000 0.000000 1.7320727E-04 0.000000 0.000000 0.000000 - Av 2018 10 9 3 0 1.7461486E-02 0.000000 0.000000 1.7315539E-04 0.000000 0.000000 0.000000 - Av 2018 10 9 4 0 1.7454799E-02 0.000000 0.000000 1.7310354E-04 0.000000 0.000000 0.000000 - Av 2018 10 9 5 0 1.7450079E-02 0.000000 0.000000 1.7305171E-04 0.000000 0.000000 0.000000 - Av 2018 10 9 6 0 1.7444678E-02 0.000000 0.000000 1.7299991E-04 0.000000 0.000000 0.000000 + Av 2018 10 8 18 0 1.3261723E-02 0.000000 0.000000 1.7374493E-04 1.9510234E-04 0.000000 0.000000 + Av 2018 10 8 19 0 2.0320799E-02 0.000000 0.000000 1.7369287E-04 0.000000 0.000000 0.000000 + Av 2018 10 8 20 0 1.6533613E-02 0.000000 0.000000 1.7364082E-04 0.000000 0.000000 0.000000 + Av 2018 10 8 21 0 1.7843381E-02 0.000000 0.000000 1.7358879E-04 0.000000 0.000000 0.000000 + Av 2018 10 8 22 0 1.7380893E-02 0.000000 0.000000 1.7353678E-04 0.000000 0.000000 0.000000 + Av 2018 10 8 23 0 1.7534638E-02 0.000000 0.000000 1.7348479E-04 0.000000 0.000000 0.000000 + Av 2018 10 8 24 0 1.7474115E-02 0.000000 0.000000 1.7343280E-04 0.000000 0.000000 0.000000 + Av 2018 10 9 1 0 1.7479829E-02 0.000000 0.000000 1.7325915E-04 0.000000 0.000000 0.000000 + Av 2018 10 9 2 0 1.7462518E-02 0.000000 0.000000 1.7320727E-04 0.000000 0.000000 0.000000 + Av 2018 10 9 3 0 1.7461486E-02 0.000000 0.000000 1.7315539E-04 0.000000 0.000000 0.000000 + Av 2018 10 9 4 0 1.7454799E-02 0.000000 0.000000 1.7310354E-04 0.000000 0.000000 0.000000 + Av 2018 10 9 5 0 1.7450079E-02 0.000000 0.000000 1.7305171E-04 0.000000 0.000000 0.000000 + Av 2018 10 9 6 0 1.7444678E-02 0.000000 0.000000 1.7299991E-04 0.000000 0.000000 0.000000 Av 2018 10 9 7 0 8.7210806E-03 0.000000 0.000000 0.000000 0.000000 0.000000 1.2449662E-03 Av 2018 10 9 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.0268279E-03 Av 2018 10 9 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.8086898E-03 @@ -6785,19 +6785,19 @@ Av 2018 10 9 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.8086898E-03 Av 2018 10 9 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.0268279E-03 Av 2018 10 9 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.2449662E-03 - Av 2018 10 9 18 0 1.1712184E-02 0.000000 0.000000 1.7237925E-04 0.000000 0.000000 0.000000 - Av 2018 10 9 19 0 1.9348430E-02 0.000000 0.000000 1.7232764E-04 0.000000 0.000000 0.000000 - Av 2018 10 9 20 0 1.6686225E-02 0.000000 0.000000 1.7227604E-04 0.000000 0.000000 0.000000 - Av 2018 10 9 21 0 1.7604887E-02 0.000000 0.000000 1.7222446E-04 0.000000 0.000000 0.000000 - Av 2018 10 9 22 0 1.7278451E-02 0.000000 0.000000 1.7217289E-04 0.000000 0.000000 0.000000 - Av 2018 10 9 23 0 1.7384950E-02 0.000000 0.000000 1.7212133E-04 0.000000 0.000000 0.000000 - Av 2018 10 9 24 0 1.7340915E-02 0.000000 0.000000 1.7206979E-04 0.000000 0.000000 0.000000 - Av 2018 10 10 1 0 1.7341260E-02 0.000000 0.000000 1.7190108E-04 0.000000 0.000000 0.000000 - Av 2018 10 10 2 0 1.7326184E-02 0.000000 0.000000 1.7184965E-04 0.000000 0.000000 0.000000 - Av 2018 10 10 3 0 1.7324436E-02 0.000000 0.000000 1.7179822E-04 0.000000 0.000000 0.000000 - Av 2018 10 10 4 0 1.7318057E-02 0.000000 0.000000 1.7174681E-04 0.000000 0.000000 0.000000 - Av 2018 10 10 5 0 1.7313292E-02 0.000000 0.000000 1.7169543E-04 0.000000 0.000000 0.000000 - Av 2018 10 10 6 0 1.7307967E-02 0.000000 0.000000 1.7164405E-04 0.000000 0.000000 0.000000 + Av 2018 10 9 18 0 1.1712184E-02 0.000000 0.000000 1.7237925E-04 0.000000 0.000000 0.000000 + Av 2018 10 9 19 0 1.9348430E-02 0.000000 0.000000 1.7232764E-04 0.000000 0.000000 0.000000 + Av 2018 10 9 20 0 1.6686225E-02 0.000000 0.000000 1.7227604E-04 0.000000 0.000000 0.000000 + Av 2018 10 9 21 0 1.7604887E-02 0.000000 0.000000 1.7222446E-04 0.000000 0.000000 0.000000 + Av 2018 10 9 22 0 1.7278451E-02 0.000000 0.000000 1.7217289E-04 0.000000 0.000000 0.000000 + Av 2018 10 9 23 0 1.7384950E-02 0.000000 0.000000 1.7212133E-04 0.000000 0.000000 0.000000 + Av 2018 10 9 24 0 1.7340915E-02 0.000000 0.000000 1.7206979E-04 0.000000 0.000000 0.000000 + Av 2018 10 10 1 0 1.7341260E-02 0.000000 0.000000 1.7190108E-04 0.000000 0.000000 0.000000 + Av 2018 10 10 2 0 1.7326184E-02 0.000000 0.000000 1.7184965E-04 0.000000 0.000000 0.000000 + Av 2018 10 10 3 0 1.7324436E-02 0.000000 0.000000 1.7179822E-04 0.000000 0.000000 0.000000 + Av 2018 10 10 4 0 1.7318057E-02 0.000000 0.000000 1.7174681E-04 0.000000 0.000000 0.000000 + Av 2018 10 10 5 0 1.7313292E-02 0.000000 0.000000 1.7169543E-04 0.000000 0.000000 0.000000 + Av 2018 10 10 6 0 1.7307967E-02 0.000000 0.000000 1.7164405E-04 0.000000 0.000000 0.000000 Av 2018 10 10 7 0 8.6527262E-03 0.000000 0.000000 0.000000 0.000000 0.000000 1.0079762E-03 Av 2018 10 10 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.4029195E-03 Av 2018 10 10 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.7978630E-03 @@ -6809,19 +6809,19 @@ Av 2018 10 10 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.7978630E-03 Av 2018 10 10 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.4029195E-03 Av 2018 10 10 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.0079762E-03 - 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Av 2018 10 11 5 0 1.7178021E-02 0.000000 0.000000 1.7035397E-04 0.000000 0.000000 0.000000 - Av 2018 10 11 6 0 1.7172743E-02 0.000000 0.000000 1.7030304E-04 0.000000 0.000000 0.000000 + Av 2018 10 10 18 0 1.1620420E-02 0.000000 0.000000 1.7102869E-04 0.000000 0.000000 0.000000 + Av 2018 10 10 19 0 1.9196842E-02 0.000000 0.000000 1.7097752E-04 0.000000 0.000000 0.000000 + Av 2018 10 10 20 0 1.6555499E-02 0.000000 0.000000 1.7092635E-04 0.000000 0.000000 0.000000 + Av 2018 10 10 21 0 1.7466964E-02 0.000000 0.000000 1.7087520E-04 0.000000 0.000000 0.000000 + Av 2018 10 10 22 0 1.7143089E-02 0.000000 0.000000 1.7082406E-04 0.000000 0.000000 0.000000 + Av 2018 10 10 23 0 1.7248757E-02 0.000000 0.000000 1.7077294E-04 0.000000 0.000000 0.000000 + Av 2018 10 10 24 0 1.7205071E-02 0.000000 0.000000 1.7072183E-04 0.000000 0.000000 0.000000 + Av 2018 10 11 1 0 1.7205648E-02 0.000000 0.000000 1.7055791E-04 0.000000 0.000000 0.000000 + Av 2018 10 11 2 0 1.7190844E-02 0.000000 0.000000 1.7050692E-04 0.000000 0.000000 0.000000 + Av 2018 10 11 3 0 1.7189063E-02 0.000000 0.000000 1.7045591E-04 0.000000 0.000000 0.000000 + Av 2018 10 11 4 0 1.7182752E-02 0.000000 0.000000 1.7040494E-04 0.000000 0.000000 0.000000 + Av 2018 10 11 5 0 1.7178021E-02 0.000000 0.000000 1.7035397E-04 0.000000 0.000000 0.000000 + Av 2018 10 11 6 0 1.7172743E-02 0.000000 0.000000 1.7030304E-04 0.000000 0.000000 0.000000 Av 2018 10 11 7 0 8.5851261E-03 0.000000 0.000000 0.000000 0.000000 0.000000 9.1707997E-04 Av 2018 10 11 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.2428089E-03 Av 2018 10 11 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.5685379E-03 @@ -6833,19 +6833,19 @@ Av 2018 10 11 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.5685379E-03 Av 2018 10 11 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.2428089E-03 Av 2018 10 11 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 9.1707997E-04 - Av 2018 10 11 18 0 1.1529660E-02 0.000000 0.000000 1.6969288E-04 0.000000 0.000000 0.000000 - Av 2018 10 11 19 0 1.9046906E-02 0.000000 0.000000 1.6964214E-04 0.000000 0.000000 0.000000 - Av 2018 10 11 20 0 1.6426198E-02 0.000000 0.000000 1.6959141E-04 0.000000 0.000000 0.000000 - Av 2018 10 11 21 0 1.7330550E-02 0.000000 0.000000 1.6954070E-04 0.000000 0.000000 0.000000 - Av 2018 10 11 22 0 1.7009210E-02 0.000000 0.000000 1.6949001E-04 0.000000 0.000000 0.000000 - Av 2018 10 11 23 0 1.7114054E-02 0.000000 0.000000 1.6943931E-04 0.000000 0.000000 0.000000 - Av 2018 10 11 24 0 1.7070711E-02 0.000000 0.000000 1.6938864E-04 0.000000 0.000000 0.000000 - Av 2018 10 12 1 0 1.7071513E-02 0.000000 0.000000 1.6922930E-04 0.000000 0.000000 0.000000 - Av 2018 10 12 2 0 1.7056972E-02 0.000000 0.000000 1.6917873E-04 0.000000 0.000000 0.000000 - Av 2018 10 12 3 0 1.7055158E-02 0.000000 0.000000 1.6912818E-04 0.000000 0.000000 0.000000 - Av 2018 10 12 4 0 1.7048918E-02 0.000000 0.000000 1.6907763E-04 0.000000 0.000000 0.000000 - Av 2018 10 12 5 0 1.7044220E-02 0.000000 0.000000 1.6902709E-04 0.000000 0.000000 0.000000 - Av 2018 10 12 6 0 1.7038988E-02 0.000000 0.000000 1.6897658E-04 0.000000 0.000000 0.000000 + Av 2018 10 11 18 0 1.1529660E-02 0.000000 0.000000 1.6969288E-04 0.000000 0.000000 0.000000 + Av 2018 10 11 19 0 1.9046906E-02 0.000000 0.000000 1.6964214E-04 0.000000 0.000000 0.000000 + Av 2018 10 11 20 0 1.6426198E-02 0.000000 0.000000 1.6959141E-04 0.000000 0.000000 0.000000 + Av 2018 10 11 21 0 1.7330550E-02 0.000000 0.000000 1.6954070E-04 0.000000 0.000000 0.000000 + Av 2018 10 11 22 0 1.7009210E-02 0.000000 0.000000 1.6949001E-04 0.000000 0.000000 0.000000 + Av 2018 10 11 23 0 1.7114054E-02 0.000000 0.000000 1.6943931E-04 0.000000 0.000000 0.000000 + Av 2018 10 11 24 0 1.7070711E-02 0.000000 0.000000 1.6938864E-04 0.000000 0.000000 0.000000 + Av 2018 10 12 1 0 1.7071513E-02 0.000000 0.000000 1.6922930E-04 0.000000 0.000000 0.000000 + Av 2018 10 12 2 0 1.7056972E-02 0.000000 0.000000 1.6917873E-04 0.000000 0.000000 0.000000 + Av 2018 10 12 3 0 1.7055158E-02 0.000000 0.000000 1.6912818E-04 0.000000 0.000000 0.000000 + Av 2018 10 12 4 0 1.7048918E-02 0.000000 0.000000 1.6907763E-04 0.000000 0.000000 0.000000 + Av 2018 10 12 5 0 1.7044220E-02 0.000000 0.000000 1.6902709E-04 0.000000 0.000000 0.000000 + Av 2018 10 12 6 0 1.7038988E-02 0.000000 0.000000 1.6897658E-04 0.000000 0.000000 0.000000 Av 2018 10 12 7 0 8.5182581E-03 0.000000 0.000000 0.000000 0.000000 0.000000 9.2906709E-04 Av 2018 10 12 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.4546466E-03 Av 2018 10 12 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.9802262E-03 @@ -6857,19 +6857,19 @@ Av 2018 10 12 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.9802262E-03 Av 2018 10 12 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.4546466E-03 Av 2018 10 12 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 9.2906709E-04 - Av 2018 10 12 18 0 1.1439886E-02 0.000000 0.000000 1.6837160E-04 0.000000 0.000000 0.000000 - Av 2018 10 12 19 0 1.8898603E-02 0.000000 0.000000 1.6832128E-04 0.000000 0.000000 0.000000 - Av 2018 10 12 20 0 1.6298303E-02 0.000000 0.000000 1.6827097E-04 0.000000 0.000000 0.000000 - Av 2018 10 12 21 0 1.7195616E-02 0.000000 0.000000 1.6822068E-04 0.000000 0.000000 0.000000 - Av 2018 10 12 22 0 1.6876779E-02 0.000000 0.000000 1.6817042E-04 0.000000 0.000000 0.000000 - Av 2018 10 12 23 0 1.6980812E-02 0.000000 0.000000 1.6812015E-04 0.000000 0.000000 0.000000 - Av 2018 10 12 24 0 1.6937811E-02 0.000000 0.000000 1.6806991E-04 0.000000 0.000000 0.000000 - Av 2018 10 13 1 0 1.6938824E-02 0.000000 0.000000 1.6791502E-04 0.000000 0.000000 0.000000 - Av 2018 10 13 2 0 1.6924541E-02 0.000000 0.000000 1.6786487E-04 0.000000 0.000000 0.000000 - Av 2018 10 13 3 0 1.6922694E-02 0.000000 0.000000 1.6781474E-04 0.000000 0.000000 0.000000 - Av 2018 10 13 4 0 1.6916525E-02 0.000000 0.000000 1.6776462E-04 0.000000 0.000000 0.000000 - Av 2018 10 13 5 0 1.6911861E-02 0.000000 0.000000 1.6771450E-04 0.000000 0.000000 0.000000 - Av 2018 10 13 6 0 1.6906675E-02 0.000000 0.000000 1.6766442E-04 0.000000 0.000000 0.000000 + Av 2018 10 12 18 0 1.1439886E-02 0.000000 0.000000 1.6837160E-04 0.000000 0.000000 0.000000 + Av 2018 10 12 19 0 1.8898603E-02 0.000000 0.000000 1.6832128E-04 0.000000 0.000000 0.000000 + Av 2018 10 12 20 0 1.6298303E-02 0.000000 0.000000 1.6827097E-04 0.000000 0.000000 0.000000 + Av 2018 10 12 21 0 1.7195616E-02 0.000000 0.000000 1.6822068E-04 0.000000 0.000000 0.000000 + Av 2018 10 12 22 0 1.6876779E-02 0.000000 0.000000 1.6817042E-04 0.000000 0.000000 0.000000 + Av 2018 10 12 23 0 1.6980812E-02 0.000000 0.000000 1.6812015E-04 0.000000 0.000000 0.000000 + Av 2018 10 12 24 0 1.6937811E-02 0.000000 0.000000 1.6806991E-04 0.000000 0.000000 0.000000 + Av 2018 10 13 1 0 1.6938824E-02 0.000000 0.000000 1.6791502E-04 0.000000 0.000000 0.000000 + Av 2018 10 13 2 0 1.6924541E-02 0.000000 0.000000 1.6786487E-04 0.000000 0.000000 0.000000 + Av 2018 10 13 3 0 1.6922694E-02 0.000000 0.000000 1.6781474E-04 0.000000 0.000000 0.000000 + Av 2018 10 13 4 0 1.6916525E-02 0.000000 0.000000 1.6776462E-04 0.000000 0.000000 0.000000 + Av 2018 10 13 5 0 1.6911861E-02 0.000000 0.000000 1.6771450E-04 0.000000 0.000000 0.000000 + Av 2018 10 13 6 0 1.6906675E-02 0.000000 0.000000 1.6766442E-04 0.000000 0.000000 0.000000 Av 2018 10 13 7 0 8.4521109E-03 0.000000 0.000000 0.000000 0.000000 0.000000 8.2651130E-04 Av 2018 10 13 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.2466562E-03 Av 2018 10 13 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.6668008E-03 @@ -6881,19 +6881,19 @@ Av 2018 10 13 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.6668008E-03 Av 2018 10 13 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.2466562E-03 Av 2018 10 13 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 8.2651130E-04 - Av 2018 10 13 18 0 1.1351076E-02 0.000000 0.000000 1.6706449E-04 0.000000 0.000000 0.000000 - Av 2018 10 13 19 0 1.8751891E-02 0.000000 0.000000 1.6701459E-04 0.000000 0.000000 0.000000 - Av 2018 10 13 20 0 1.6171783E-02 0.000000 0.000000 1.6696472E-04 0.000000 0.000000 0.000000 - Av 2018 10 13 21 0 1.7062131E-02 0.000000 0.000000 1.6691485E-04 0.000000 0.000000 0.000000 - Av 2018 10 13 22 0 1.6745776E-02 0.000000 0.000000 1.6686501E-04 0.000000 0.000000 0.000000 - Av 2018 10 13 23 0 1.6849002E-02 0.000000 0.000000 1.6681515E-04 0.000000 0.000000 0.000000 - Av 2018 10 13 24 0 1.6806336E-02 0.000000 0.000000 1.6676533E-04 0.000000 0.000000 0.000000 - Av 2018 10 14 1 0 1.6807552E-02 0.000000 0.000000 1.6661471E-04 0.000000 0.000000 0.000000 - Av 2018 10 14 2 0 1.6793519E-02 0.000000 0.000000 1.6656499E-04 0.000000 0.000000 0.000000 - Av 2018 10 14 3 0 1.6791642E-02 0.000000 0.000000 1.6651528E-04 0.000000 0.000000 0.000000 - Av 2018 10 14 4 0 1.6785540E-02 0.000000 0.000000 1.6646557E-04 0.000000 0.000000 0.000000 - Av 2018 10 14 5 0 1.6780909E-02 0.000000 0.000000 1.6641589E-04 0.000000 0.000000 0.000000 - Av 2018 10 14 6 0 1.6775768E-02 0.000000 0.000000 1.6636621E-04 0.000000 0.000000 0.000000 + Av 2018 10 13 18 0 1.1351076E-02 0.000000 0.000000 1.6706449E-04 0.000000 0.000000 0.000000 + Av 2018 10 13 19 0 1.8751891E-02 0.000000 0.000000 1.6701459E-04 0.000000 0.000000 0.000000 + Av 2018 10 13 20 0 1.6171783E-02 0.000000 0.000000 1.6696472E-04 0.000000 0.000000 0.000000 + Av 2018 10 13 21 0 1.7062131E-02 0.000000 0.000000 1.6691485E-04 0.000000 0.000000 0.000000 + Av 2018 10 13 22 0 1.6745776E-02 0.000000 0.000000 1.6686501E-04 0.000000 0.000000 0.000000 + Av 2018 10 13 23 0 1.6849002E-02 0.000000 0.000000 1.6681515E-04 0.000000 0.000000 0.000000 + Av 2018 10 13 24 0 1.6806336E-02 0.000000 0.000000 1.6676533E-04 0.000000 0.000000 0.000000 + Av 2018 10 14 1 0 1.6807552E-02 0.000000 0.000000 1.6661471E-04 0.000000 0.000000 0.000000 + Av 2018 10 14 2 0 1.6793519E-02 0.000000 0.000000 1.6656499E-04 0.000000 0.000000 0.000000 + Av 2018 10 14 3 0 1.6791642E-02 0.000000 0.000000 1.6651528E-04 0.000000 0.000000 0.000000 + Av 2018 10 14 4 0 1.6785540E-02 0.000000 0.000000 1.6646557E-04 0.000000 0.000000 0.000000 + Av 2018 10 14 5 0 1.6780909E-02 0.000000 0.000000 1.6641589E-04 0.000000 0.000000 0.000000 + Av 2018 10 14 6 0 1.6775768E-02 0.000000 0.000000 1.6636621E-04 0.000000 0.000000 0.000000 Av 2018 10 14 7 0 8.3866669E-03 0.000000 0.000000 6.9874513E-06 0.000000 0.000000 7.2422321E-04 Av 2018 10 14 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.0213322E-03 Av 2018 10 14 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.3184410E-03 @@ -6905,19 +6905,19 @@ Av 2018 10 14 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.3184410E-03 Av 2018 10 14 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.0213322E-03 Av 2018 10 14 17 0 4.4107263E-04 0.000000 0.000000 6.4916821E-06 0.000000 0.000000 7.2422321E-04 - Av 2018 10 14 18 0 1.1550918E-02 0.000000 0.000000 1.6577130E-04 0.000000 0.000000 0.000000 - Av 2018 10 14 19 0 1.8506702E-02 0.000000 0.000000 1.6572182E-04 0.000000 0.000000 0.000000 - Av 2018 10 14 20 0 1.6081393E-02 0.000000 0.000000 1.6567236E-04 0.000000 0.000000 0.000000 - Av 2018 10 14 21 0 1.6917974E-02 0.000000 0.000000 1.6562290E-04 0.000000 0.000000 0.000000 - Av 2018 10 14 22 0 1.6620366E-02 0.000000 0.000000 1.6557345E-04 0.000000 0.000000 0.000000 - Av 2018 10 14 23 0 1.6717128E-02 0.000000 0.000000 1.6552403E-04 0.000000 0.000000 0.000000 - Av 2018 10 14 24 0 1.6676769E-02 0.000000 0.000000 1.6547463E-04 0.000000 0.000000 0.000000 - Av 2018 10 15 1 0 1.6677495E-02 0.000000 0.000000 1.6532817E-04 0.000000 0.000000 0.000000 - Av 2018 10 15 2 0 1.6663939E-02 0.000000 0.000000 1.6527883E-04 0.000000 0.000000 0.000000 - Av 2018 10 15 3 0 1.6661951E-02 0.000000 0.000000 1.6522953E-04 0.000000 0.000000 0.000000 - Av 2018 10 15 4 0 1.6655944E-02 0.000000 0.000000 1.6518024E-04 0.000000 0.000000 0.000000 - Av 2018 10 15 5 0 1.6651336E-02 0.000000 0.000000 1.6513097E-04 0.000000 0.000000 0.000000 - Av 2018 10 15 6 0 1.6646245E-02 0.000000 0.000000 1.6508173E-04 0.000000 0.000000 0.000000 + Av 2018 10 14 18 0 1.1550918E-02 0.000000 0.000000 1.6577130E-04 0.000000 0.000000 0.000000 + Av 2018 10 14 19 0 1.8506702E-02 0.000000 0.000000 1.6572182E-04 0.000000 0.000000 0.000000 + Av 2018 10 14 20 0 1.6081393E-02 0.000000 0.000000 1.6567236E-04 0.000000 0.000000 0.000000 + Av 2018 10 14 21 0 1.6917974E-02 0.000000 0.000000 1.6562290E-04 0.000000 0.000000 0.000000 + Av 2018 10 14 22 0 1.6620366E-02 0.000000 0.000000 1.6557345E-04 0.000000 0.000000 0.000000 + Av 2018 10 14 23 0 1.6717128E-02 0.000000 0.000000 1.6552403E-04 0.000000 0.000000 0.000000 + Av 2018 10 14 24 0 1.6676769E-02 0.000000 0.000000 1.6547463E-04 0.000000 0.000000 0.000000 + Av 2018 10 15 1 0 1.6677495E-02 0.000000 0.000000 1.6532817E-04 0.000000 0.000000 0.000000 + Av 2018 10 15 2 0 1.6663939E-02 0.000000 0.000000 1.6527883E-04 0.000000 0.000000 0.000000 + Av 2018 10 15 3 0 1.6661951E-02 0.000000 0.000000 1.6522953E-04 0.000000 0.000000 0.000000 + Av 2018 10 15 4 0 1.6655944E-02 0.000000 0.000000 1.6518024E-04 0.000000 0.000000 0.000000 + Av 2018 10 15 5 0 1.6651336E-02 0.000000 0.000000 1.6513097E-04 0.000000 0.000000 0.000000 + Av 2018 10 15 6 0 1.6646245E-02 0.000000 0.000000 1.6508173E-04 0.000000 0.000000 0.000000 Av 2018 10 15 7 0 8.3219158E-03 0.000000 0.000000 0.000000 0.000000 0.000000 7.7170797E-04 Av 2018 10 15 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.4405261E-03 Av 2018 10 15 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.1093443E-03 @@ -6929,19 +6929,19 @@ Av 2018 10 15 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.1093443E-03 Av 2018 10 15 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.4405261E-03 Av 2018 10 15 17 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 7.7170797E-04 - Av 2018 10 15 18 0 1.1176271E-02 0.000000 0.000000 1.6449174E-04 0.000000 0.000000 0.000000 - Av 2018 10 15 19 0 1.8463120E-02 0.000000 0.000000 1.6444267E-04 0.000000 0.000000 0.000000 - Av 2018 10 15 20 0 1.5922751E-02 0.000000 0.000000 1.6439361E-04 0.000000 0.000000 0.000000 - Av 2018 10 15 21 0 1.6799396E-02 0.000000 0.000000 1.6434457E-04 0.000000 0.000000 0.000000 - Av 2018 10 15 22 0 1.6487915E-02 0.000000 0.000000 1.6429555E-04 0.000000 0.000000 0.000000 - Av 2018 10 15 23 0 1.6589560E-02 0.000000 0.000000 1.6424654E-04 0.000000 0.000000 0.000000 - Av 2018 10 15 24 0 1.6547557E-02 0.000000 0.000000 1.6419754E-04 0.000000 0.000000 0.000000 - Av 2018 10 16 1 0 1.6549151E-02 0.000000 0.000000 1.6405506E-04 0.000000 0.000000 0.000000 - Av 2018 10 16 2 0 1.6535595E-02 0.000000 0.000000 1.6400615E-04 0.000000 0.000000 0.000000 - Av 2018 10 16 3 0 1.6533663E-02 0.000000 0.000000 1.6395726E-04 0.000000 0.000000 0.000000 - Av 2018 10 16 4 0 1.6527690E-02 0.000000 0.000000 1.6390836E-04 0.000000 0.000000 0.000000 - 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Av 2018 10 16 18 0 1.1090241E-02 0.000000 0.000000 1.6322554E-04 0.000000 0.000000 0.000000 - Av 2018 10 16 19 0 1.8321000E-02 0.000000 0.000000 1.6317688E-04 0.000000 0.000000 0.000000 - Av 2018 10 16 20 0 1.5800189E-02 0.000000 0.000000 1.6312824E-04 0.000000 0.000000 0.000000 - Av 2018 10 16 21 0 1.6670087E-02 0.000000 0.000000 1.6307959E-04 0.000000 0.000000 0.000000 - Av 2018 10 16 22 0 1.6361007E-02 0.000000 0.000000 1.6303097E-04 0.000000 0.000000 0.000000 - Av 2018 10 16 23 0 1.6461872E-02 0.000000 0.000000 1.6298237E-04 0.000000 0.000000 0.000000 - Av 2018 10 16 24 0 1.6420199E-02 0.000000 0.000000 1.6293379E-04 0.000000 0.000000 0.000000 - Av 2018 10 17 1 0 1.6421970E-02 0.000000 0.000000 1.6279516E-04 0.000000 0.000000 0.000000 - Av 2018 10 17 2 0 1.6408637E-02 0.000000 0.000000 1.6274666E-04 0.000000 0.000000 0.000000 - Av 2018 10 17 3 0 1.6406683E-02 0.000000 0.000000 1.6269817E-04 0.000000 0.000000 0.000000 - Av 2018 10 17 4 0 1.6400773E-02 0.000000 0.000000 1.6264968E-04 0.000000 0.000000 0.000000 - Av 2018 10 17 5 0 1.6396241E-02 0.000000 0.000000 1.6260121E-04 0.000000 0.000000 0.000000 - Av 2018 10 17 6 0 1.6391233E-02 0.000000 0.000000 1.6255277E-04 0.000000 0.000000 0.000000 + Av 2018 10 16 18 0 1.1090241E-02 0.000000 0.000000 1.6322554E-04 0.000000 0.000000 0.000000 + Av 2018 10 16 19 0 1.8321000E-02 0.000000 0.000000 1.6317688E-04 0.000000 0.000000 0.000000 + Av 2018 10 16 20 0 1.5800189E-02 0.000000 0.000000 1.6312824E-04 0.000000 0.000000 0.000000 + Av 2018 10 16 21 0 1.6670087E-02 0.000000 0.000000 1.6307959E-04 0.000000 0.000000 0.000000 + Av 2018 10 16 22 0 1.6361007E-02 0.000000 0.000000 1.6303097E-04 0.000000 0.000000 0.000000 + Av 2018 10 16 23 0 1.6461872E-02 0.000000 0.000000 1.6298237E-04 0.000000 0.000000 0.000000 + Av 2018 10 16 24 0 1.6420199E-02 0.000000 0.000000 1.6293379E-04 0.000000 0.000000 0.000000 + Av 2018 10 17 1 0 1.6421970E-02 0.000000 0.000000 1.6279516E-04 0.000000 0.000000 0.000000 + Av 2018 10 17 2 0 1.6408637E-02 0.000000 0.000000 1.6274666E-04 0.000000 0.000000 0.000000 + Av 2018 10 17 3 0 1.6406683E-02 0.000000 0.000000 1.6269817E-04 0.000000 0.000000 0.000000 + Av 2018 10 17 4 0 1.6400773E-02 0.000000 0.000000 1.6264968E-04 0.000000 0.000000 0.000000 + Av 2018 10 17 5 0 1.6396241E-02 0.000000 0.000000 1.6260121E-04 0.000000 0.000000 0.000000 + Av 2018 10 17 6 0 1.6391233E-02 0.000000 0.000000 1.6255277E-04 0.000000 0.000000 0.000000 Av 2018 10 17 7 0 8.1944279E-03 0.000000 0.000000 4.7258800E-06 0.000000 0.000000 7.1717479E-04 Av 2018 10 17 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.7394071E-03 Av 2018 10 17 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.7616394E-03 @@ -6977,19 +6977,19 @@ Av 2018 10 17 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.7616394E-03 Av 2018 10 17 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.7394071E-03 Av 2018 10 17 17 0 2.8824035E-04 0.000000 0.000000 4.2423053E-06 0.000000 0.000000 7.1717479E-04 - Av 2018 10 17 18 0 1.1193120E-02 0.000000 0.000000 1.6197248E-04 0.000000 0.000000 0.000000 - Av 2018 10 17 19 0 1.8114980E-02 0.000000 0.000000 1.6192422E-04 0.000000 0.000000 0.000000 - Av 2018 10 17 20 0 1.5701629E-02 0.000000 0.000000 1.6187597E-04 0.000000 0.000000 0.000000 - Av 2018 10 17 21 0 1.6534217E-02 0.000000 0.000000 1.6182773E-04 0.000000 0.000000 0.000000 - Av 2018 10 17 22 0 1.6238164E-02 0.000000 0.000000 1.6177951E-04 0.000000 0.000000 0.000000 - Av 2018 10 17 23 0 1.6334552E-02 0.000000 0.000000 1.6173131E-04 0.000000 0.000000 0.000000 - Av 2018 10 17 24 0 1.6294491E-02 0.000000 0.000000 1.6168313E-04 0.000000 0.000000 0.000000 - Av 2018 10 18 1 0 1.6295981E-02 0.000000 0.000000 1.6154822E-04 0.000000 0.000000 0.000000 - Av 2018 10 18 2 0 1.6283028E-02 0.000000 0.000000 1.6150012E-04 0.000000 0.000000 0.000000 - Av 2018 10 18 3 0 1.6280996E-02 0.000000 0.000000 1.6145202E-04 0.000000 0.000000 0.000000 - Av 2018 10 18 4 0 1.6275166E-02 0.000000 0.000000 1.6140392E-04 0.000000 0.000000 0.000000 - Av 2018 10 18 5 0 1.6270660E-02 0.000000 0.000000 1.6135586E-04 0.000000 0.000000 0.000000 - Av 2018 10 18 6 0 1.6265696E-02 0.000000 0.000000 1.6130781E-04 0.000000 0.000000 0.000000 + Av 2018 10 17 18 0 1.1193120E-02 0.000000 0.000000 1.6197248E-04 0.000000 0.000000 0.000000 + Av 2018 10 17 19 0 1.8114980E-02 0.000000 0.000000 1.6192422E-04 0.000000 0.000000 0.000000 + Av 2018 10 17 20 0 1.5701629E-02 0.000000 0.000000 1.6187597E-04 0.000000 0.000000 0.000000 + Av 2018 10 17 21 0 1.6534217E-02 0.000000 0.000000 1.6182773E-04 0.000000 0.000000 0.000000 + Av 2018 10 17 22 0 1.6238164E-02 0.000000 0.000000 1.6177951E-04 0.000000 0.000000 0.000000 + Av 2018 10 17 23 0 1.6334552E-02 0.000000 0.000000 1.6173131E-04 0.000000 0.000000 0.000000 + Av 2018 10 17 24 0 1.6294491E-02 0.000000 0.000000 1.6168313E-04 0.000000 0.000000 0.000000 + Av 2018 10 18 1 0 1.6295981E-02 0.000000 0.000000 1.6154822E-04 0.000000 0.000000 0.000000 + Av 2018 10 18 2 0 1.6283028E-02 0.000000 0.000000 1.6150012E-04 0.000000 0.000000 0.000000 + Av 2018 10 18 3 0 1.6280996E-02 0.000000 0.000000 1.6145202E-04 0.000000 0.000000 0.000000 + Av 2018 10 18 4 0 1.6275166E-02 0.000000 0.000000 1.6140392E-04 0.000000 0.000000 0.000000 + Av 2018 10 18 5 0 1.6270660E-02 0.000000 0.000000 1.6135586E-04 0.000000 0.000000 0.000000 + Av 2018 10 18 6 0 1.6265696E-02 0.000000 0.000000 1.6130781E-04 0.000000 0.000000 0.000000 Av 2018 10 18 7 0 8.1316689E-03 0.000000 0.000000 3.4640223E-05 0.000000 0.000000 5.7554338E-04 Av 2018 10 18 8 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.2958414E-03 Av 2018 10 18 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.0161394E-03 @@ -7001,19 +7001,19 @@ Av 2018 10 18 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.0161394E-03 Av 2018 10 18 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.2958414E-03 Av 2018 10 18 17 0 2.3210177E-03 0.000000 0.000000 3.4160606E-05 0.000000 0.000000 5.7554338E-04 - Av 2018 10 18 18 0 1.2434819E-02 0.000000 0.000000 1.6073229E-04 0.000000 0.000000 0.000000 - Av 2018 10 18 19 0 1.7514728E-02 0.000000 0.000000 1.6068442E-04 0.000000 0.000000 0.000000 - Av 2018 10 18 20 0 1.5741894E-02 0.000000 0.000000 1.6063655E-04 0.000000 0.000000 0.000000 - Av 2018 10 18 21 0 1.6351823E-02 0.000000 0.000000 1.6058871E-04 0.000000 0.000000 0.000000 - Av 2018 10 18 22 0 1.6133245E-02 0.000000 0.000000 1.6054089E-04 0.000000 0.000000 0.000000 - Av 2018 10 18 23 0 1.6202748E-02 0.000000 0.000000 1.6049309E-04 0.000000 0.000000 0.000000 - Av 2018 10 18 24 0 1.6172085E-02 0.000000 0.000000 1.6044528E-04 0.000000 0.000000 0.000000 - Av 2018 10 19 1 0 1.6170578E-02 0.000000 0.000000 1.6031398E-04 0.000000 0.000000 0.000000 - Av 2018 10 19 2 0 1.6158938E-02 0.000000 0.000000 1.6026625E-04 0.000000 0.000000 0.000000 - Av 2018 10 19 3 0 1.6156500E-02 0.000000 0.000000 1.6021855E-04 0.000000 0.000000 0.000000 - Av 2018 10 19 4 0 1.6150866E-02 0.000000 0.000000 1.6017085E-04 0.000000 0.000000 0.000000 - Av 2018 10 19 5 0 1.6146345E-02 0.000000 0.000000 1.6012318E-04 0.000000 0.000000 0.000000 - Av 2018 10 19 6 0 1.6141441E-02 0.000000 0.000000 1.6007553E-04 0.000000 0.000000 0.000000 + Av 2018 10 18 18 0 1.2434819E-02 0.000000 0.000000 1.6073229E-04 0.000000 0.000000 0.000000 + Av 2018 10 18 19 0 1.7514728E-02 0.000000 0.000000 1.6068442E-04 0.000000 0.000000 0.000000 + Av 2018 10 18 20 0 1.5741894E-02 0.000000 0.000000 1.6063655E-04 0.000000 0.000000 0.000000 + Av 2018 10 18 21 0 1.6351823E-02 0.000000 0.000000 1.6058871E-04 0.000000 0.000000 0.000000 + Av 2018 10 18 22 0 1.6133245E-02 0.000000 0.000000 1.6054089E-04 0.000000 0.000000 0.000000 + Av 2018 10 18 23 0 1.6202748E-02 0.000000 0.000000 1.6049309E-04 0.000000 0.000000 0.000000 + Av 2018 10 18 24 0 1.6172085E-02 0.000000 0.000000 1.6044528E-04 0.000000 0.000000 0.000000 + Av 2018 10 19 1 0 1.6170578E-02 0.000000 0.000000 1.6031398E-04 0.000000 0.000000 0.000000 + Av 2018 10 19 2 0 1.6158938E-02 0.000000 0.000000 1.6026625E-04 0.000000 0.000000 0.000000 + Av 2018 10 19 3 0 1.6156500E-02 0.000000 0.000000 1.6021855E-04 0.000000 0.000000 0.000000 + Av 2018 10 19 4 0 1.6150866E-02 0.000000 0.000000 1.6017085E-04 0.000000 0.000000 0.000000 + Av 2018 10 19 5 0 1.6146345E-02 0.000000 0.000000 1.6012318E-04 0.000000 0.000000 0.000000 + Av 2018 10 19 6 0 1.6141441E-02 0.000000 0.000000 1.6007553E-04 0.000000 0.000000 0.000000 Av 2018 10 19 7 0 8.4839612E-03 0.000000 0.000000 4.7601054E-05 0.000000 0.000000 5.1103102E-04 Av 2018 10 19 8 0 4.1441451E-04 0.000000 0.000000 0.000000 0.000000 0.000000 3.2586360E-03 Av 2018 10 19 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.0062408E-03 @@ -7025,19 +7025,19 @@ Av 2018 10 19 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 6.0062408E-03 Av 2018 10 19 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.2586360E-03 Av 2018 10 19 17 0 3.2018980E-03 0.000000 0.000000 4.7125352E-05 0.000000 0.000000 5.1103102E-04 - Av 2018 10 19 18 0 1.2925999E-02 0.000000 0.000000 1.5950468E-04 0.000000 0.000000 0.000000 - Av 2018 10 19 19 0 1.7177148E-02 0.000000 0.000000 1.5945719E-04 0.000000 0.000000 0.000000 - Av 2018 10 19 20 0 1.5692536E-02 0.000000 0.000000 1.5940974E-04 0.000000 0.000000 0.000000 - Av 2018 10 19 21 0 1.6202301E-02 0.000000 0.000000 1.5936230E-04 0.000000 0.000000 0.000000 - Av 2018 10 19 22 0 1.6018605E-02 0.000000 0.000000 1.5931486E-04 0.000000 0.000000 0.000000 - Av 2018 10 19 23 0 1.6076032E-02 0.000000 0.000000 1.5926744E-04 0.000000 0.000000 0.000000 - Av 2018 10 19 24 0 1.6049620E-02 0.000000 0.000000 1.5922003E-04 0.000000 0.000000 0.000000 - Av 2018 10 20 1 0 1.6046898E-02 0.000000 0.000000 1.5909220E-04 0.000000 0.000000 0.000000 - Av 2018 10 20 2 0 1.6035944E-02 0.000000 0.000000 1.5904487E-04 0.000000 0.000000 0.000000 - Av 2018 10 20 3 0 1.6033322E-02 0.000000 0.000000 1.5899756E-04 0.000000 0.000000 0.000000 - Av 2018 10 20 4 0 1.6027804E-02 0.000000 0.000000 1.5895025E-04 0.000000 0.000000 0.000000 - Av 2018 10 20 5 0 1.6023297E-02 0.000000 0.000000 1.5890296E-04 0.000000 0.000000 0.000000 - Av 2018 10 20 6 0 1.6018439E-02 0.000000 0.000000 1.5885568E-04 0.000000 0.000000 0.000000 + Av 2018 10 19 18 0 1.2925999E-02 0.000000 0.000000 1.5950468E-04 0.000000 0.000000 0.000000 + Av 2018 10 19 19 0 1.7177148E-02 0.000000 0.000000 1.5945719E-04 0.000000 0.000000 0.000000 + Av 2018 10 19 20 0 1.5692536E-02 0.000000 0.000000 1.5940974E-04 0.000000 0.000000 0.000000 + Av 2018 10 19 21 0 1.6202301E-02 0.000000 0.000000 1.5936230E-04 0.000000 0.000000 0.000000 + Av 2018 10 19 22 0 1.6018605E-02 0.000000 0.000000 1.5931486E-04 0.000000 0.000000 0.000000 + Av 2018 10 19 23 0 1.6076032E-02 0.000000 0.000000 1.5926744E-04 0.000000 0.000000 0.000000 + Av 2018 10 19 24 0 1.6049620E-02 0.000000 0.000000 1.5922003E-04 0.000000 0.000000 0.000000 + Av 2018 10 20 1 0 1.6046898E-02 0.000000 0.000000 1.5909220E-04 0.000000 0.000000 0.000000 + Av 2018 10 20 2 0 1.6035944E-02 0.000000 0.000000 1.5904487E-04 0.000000 0.000000 0.000000 + Av 2018 10 20 3 0 1.6033322E-02 0.000000 0.000000 1.5899756E-04 0.000000 0.000000 0.000000 + Av 2018 10 20 4 0 1.6027804E-02 0.000000 0.000000 1.5895025E-04 0.000000 0.000000 0.000000 + Av 2018 10 20 5 0 1.6023297E-02 0.000000 0.000000 1.5890296E-04 0.000000 0.000000 0.000000 + Av 2018 10 20 6 0 1.6018439E-02 0.000000 0.000000 1.5885568E-04 0.000000 0.000000 0.000000 Av 2018 10 20 7 0 9.3834195E-03 0.000000 0.000000 6.1401493E-05 0.000000 0.000000 4.4275878E-04 Av 2018 10 20 8 0 1.3753675E-03 0.000000 0.000000 0.000000 0.000000 0.000000 3.2003520E-03 Av 2018 10 20 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.9579452E-03 @@ -7049,19 +7049,19 @@ Av 2018 10 20 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.9579452E-03 Av 2018 10 20 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.2003520E-03 Av 2018 10 20 17 0 4.1398210E-03 0.000000 0.000000 6.0929648E-05 0.000000 0.000000 4.4275878E-04 - Av 2018 10 20 18 0 1.3455232E-02 0.000000 0.000000 1.5828948E-04 0.000000 0.000000 0.000000 - Av 2018 10 20 19 0 1.6828025E-02 0.000000 0.000000 1.5824239E-04 0.000000 0.000000 0.000000 - Av 2018 10 20 20 0 1.5648875E-02 0.000000 0.000000 1.5819530E-04 0.000000 0.000000 0.000000 - Av 2018 10 20 21 0 1.6052479E-02 0.000000 0.000000 1.5814824E-04 0.000000 0.000000 0.000000 - Av 2018 10 20 22 0 1.5905749E-02 0.000000 0.000000 1.5810119E-04 0.000000 0.000000 0.000000 - Av 2018 10 20 23 0 1.5950376E-02 0.000000 0.000000 1.5805416E-04 0.000000 0.000000 0.000000 - Av 2018 10 20 24 0 1.5928470E-02 0.000000 0.000000 1.5800714E-04 0.000000 0.000000 0.000000 - Av 2018 10 21 1 0 1.5924433E-02 0.000000 0.000000 1.5788266E-04 0.000000 0.000000 0.000000 - Av 2018 10 21 2 0 1.5914189E-02 0.000000 0.000000 1.5783570E-04 0.000000 0.000000 0.000000 - Av 2018 10 21 3 0 1.5911371E-02 0.000000 0.000000 1.5778877E-04 0.000000 0.000000 0.000000 - Av 2018 10 21 4 0 1.5905974E-02 0.000000 0.000000 1.5774186E-04 0.000000 0.000000 0.000000 - Av 2018 10 21 5 0 1.5901476E-02 0.000000 0.000000 1.5769496E-04 0.000000 0.000000 0.000000 - Av 2018 10 21 6 0 1.5896667E-02 0.000000 0.000000 1.5764806E-04 0.000000 0.000000 0.000000 + Av 2018 10 20 18 0 1.3455232E-02 0.000000 0.000000 1.5828948E-04 0.000000 0.000000 0.000000 + Av 2018 10 20 19 0 1.6828025E-02 0.000000 0.000000 1.5824239E-04 0.000000 0.000000 0.000000 + Av 2018 10 20 20 0 1.5648875E-02 0.000000 0.000000 1.5819530E-04 0.000000 0.000000 0.000000 + Av 2018 10 20 21 0 1.6052479E-02 0.000000 0.000000 1.5814824E-04 0.000000 0.000000 0.000000 + Av 2018 10 20 22 0 1.5905749E-02 0.000000 0.000000 1.5810119E-04 0.000000 0.000000 0.000000 + Av 2018 10 20 23 0 1.5950376E-02 0.000000 0.000000 1.5805416E-04 0.000000 0.000000 0.000000 + Av 2018 10 20 24 0 1.5928470E-02 0.000000 0.000000 1.5800714E-04 0.000000 0.000000 0.000000 + Av 2018 10 21 1 0 1.5924433E-02 0.000000 0.000000 1.5788266E-04 0.000000 0.000000 0.000000 + Av 2018 10 21 2 0 1.5914189E-02 0.000000 0.000000 1.5783570E-04 0.000000 0.000000 0.000000 + Av 2018 10 21 3 0 1.5911371E-02 0.000000 0.000000 1.5778877E-04 0.000000 0.000000 0.000000 + Av 2018 10 21 4 0 1.5905974E-02 0.000000 0.000000 1.5774186E-04 0.000000 0.000000 0.000000 + Av 2018 10 21 5 0 1.5901476E-02 0.000000 0.000000 1.5769496E-04 0.000000 0.000000 0.000000 + Av 2018 10 21 6 0 1.5896667E-02 0.000000 0.000000 1.5764806E-04 0.000000 0.000000 0.000000 Av 2018 10 21 7 0 1.0264747E-02 0.000000 0.000000 7.4929900E-05 0.000000 0.000000 3.7577850E-04 Av 2018 10 21 8 0 2.3175739E-03 0.000000 0.000000 0.000000 0.000000 0.000000 3.1534426E-03 Av 2018 10 21 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.9311069E-03 @@ -7073,19 +7073,19 @@ Av 2018 10 21 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.9311069E-03 Av 2018 10 21 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.1534426E-03 Av 2018 10 21 17 0 5.0592585E-03 0.000000 0.000000 7.4461881E-05 0.000000 0.000000 3.7577850E-04 - Av 2018 10 21 18 0 1.3973232E-02 0.000000 0.000000 1.5708643E-04 0.000000 0.000000 0.000000 - Av 2018 10 21 19 0 1.6484456E-02 0.000000 0.000000 1.5703973E-04 0.000000 0.000000 0.000000 - Av 2018 10 21 20 0 1.5604936E-02 0.000000 0.000000 1.5699302E-04 0.000000 0.000000 0.000000 - Av 2018 10 21 21 0 1.5904408E-02 0.000000 0.000000 1.5694633E-04 0.000000 0.000000 0.000000 - Av 2018 10 21 22 0 1.5793934E-02 0.000000 0.000000 1.5689967E-04 0.000000 0.000000 0.000000 - Av 2018 10 21 23 0 1.5826005E-02 0.000000 0.000000 1.5685301E-04 0.000000 0.000000 0.000000 - Av 2018 10 21 24 0 1.5808515E-02 0.000000 0.000000 1.5680636E-04 0.000000 0.000000 0.000000 - Av 2018 10 22 1 0 1.5803190E-02 0.000000 0.000000 1.5668513E-04 0.000000 0.000000 0.000000 - Av 2018 10 22 2 0 1.5793640E-02 0.000000 0.000000 1.5663855E-04 0.000000 0.000000 0.000000 - Av 2018 10 22 3 0 1.5790634E-02 0.000000 0.000000 1.5659200E-04 0.000000 0.000000 0.000000 - Av 2018 10 22 4 0 1.5785353E-02 0.000000 0.000000 1.5654546E-04 0.000000 0.000000 0.000000 - Av 2018 10 22 5 0 1.5780866E-02 0.000000 0.000000 1.5649894E-04 0.000000 0.000000 0.000000 - Av 2018 10 22 6 0 1.5776105E-02 0.000000 0.000000 1.5645241E-04 0.000000 0.000000 0.000000 + Av 2018 10 21 18 0 1.3973232E-02 0.000000 0.000000 1.5708643E-04 0.000000 0.000000 0.000000 + Av 2018 10 21 19 0 1.6484456E-02 0.000000 0.000000 1.5703973E-04 0.000000 0.000000 0.000000 + Av 2018 10 21 20 0 1.5604936E-02 0.000000 0.000000 1.5699302E-04 0.000000 0.000000 0.000000 + Av 2018 10 21 21 0 1.5904408E-02 0.000000 0.000000 1.5694633E-04 0.000000 0.000000 0.000000 + Av 2018 10 21 22 0 1.5793934E-02 0.000000 0.000000 1.5689967E-04 0.000000 0.000000 0.000000 + Av 2018 10 21 23 0 1.5826005E-02 0.000000 0.000000 1.5685301E-04 0.000000 0.000000 0.000000 + Av 2018 10 21 24 0 1.5808515E-02 0.000000 0.000000 1.5680636E-04 0.000000 0.000000 0.000000 + Av 2018 10 22 1 0 1.5803190E-02 0.000000 0.000000 1.5668513E-04 0.000000 0.000000 0.000000 + Av 2018 10 22 2 0 1.5793640E-02 0.000000 0.000000 1.5663855E-04 0.000000 0.000000 0.000000 + Av 2018 10 22 3 0 1.5790634E-02 0.000000 0.000000 1.5659200E-04 0.000000 0.000000 0.000000 + Av 2018 10 22 4 0 1.5785353E-02 0.000000 0.000000 1.5654546E-04 0.000000 0.000000 0.000000 + Av 2018 10 22 5 0 1.5780866E-02 0.000000 0.000000 1.5649894E-04 0.000000 0.000000 0.000000 + Av 2018 10 22 6 0 1.5776105E-02 0.000000 0.000000 1.5645241E-04 0.000000 0.000000 0.000000 Av 2018 10 22 7 0 1.1438633E-02 0.000000 0.000000 9.2750837E-05 0.000000 0.000000 2.8934123E-04 Av 2018 10 22 8 0 3.5517337E-03 0.000000 0.000000 0.000000 0.000000 0.000000 2.9155067E-03 Av 2018 10 22 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.5416720E-03 @@ -7097,19 +7097,19 @@ Av 2018 10 22 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.5416720E-03 Av 2018 10 22 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.9155067E-03 Av 2018 10 22 17 0 6.2703448E-03 0.000000 0.000000 9.2286587E-05 0.000000 0.000000 2.8934123E-04 - Av 2018 10 22 18 0 1.4682284E-02 0.000000 0.000000 1.5589531E-04 0.000000 0.000000 0.000000 - Av 2018 10 22 19 0 1.6076081E-02 0.000000 0.000000 1.5584899E-04 0.000000 0.000000 0.000000 - Av 2018 10 22 20 0 1.5585149E-02 0.000000 0.000000 1.5580266E-04 0.000000 0.000000 0.000000 - Av 2018 10 22 21 0 1.5749555E-02 0.000000 0.000000 1.5575635E-04 0.000000 0.000000 0.000000 - Av 2018 10 22 22 0 1.5686098E-02 0.000000 0.000000 1.5571006E-04 0.000000 0.000000 0.000000 - Av 2018 10 22 23 0 1.5701875E-02 0.000000 0.000000 1.5566379E-04 0.000000 0.000000 0.000000 - Av 2018 10 22 24 0 1.5690099E-02 0.000000 0.000000 1.5561751E-04 0.000000 0.000000 0.000000 - Av 2018 10 23 1 0 1.5683025E-02 0.000000 0.000000 1.5549939E-04 0.000000 0.000000 0.000000 - Av 2018 10 23 2 0 1.5674321E-02 0.000000 0.000000 1.5545319E-04 0.000000 0.000000 0.000000 - Av 2018 10 23 3 0 1.5671071E-02 0.000000 0.000000 1.5540702E-04 0.000000 0.000000 0.000000 - Av 2018 10 23 4 0 1.5665928E-02 0.000000 0.000000 1.5536086E-04 0.000000 0.000000 0.000000 - Av 2018 10 23 5 0 1.5661443E-02 0.000000 0.000000 1.5531469E-04 0.000000 0.000000 0.000000 - Av 2018 10 23 6 0 1.5656730E-02 0.000000 0.000000 1.5526854E-04 0.000000 0.000000 0.000000 + Av 2018 10 22 18 0 1.4682284E-02 0.000000 0.000000 1.5589531E-04 0.000000 0.000000 0.000000 + Av 2018 10 22 19 0 1.6076081E-02 0.000000 0.000000 1.5584899E-04 0.000000 0.000000 0.000000 + Av 2018 10 22 20 0 1.5585149E-02 0.000000 0.000000 1.5580266E-04 0.000000 0.000000 0.000000 + Av 2018 10 22 21 0 1.5749555E-02 0.000000 0.000000 1.5575635E-04 0.000000 0.000000 0.000000 + Av 2018 10 22 22 0 1.5686098E-02 0.000000 0.000000 1.5571006E-04 0.000000 0.000000 0.000000 + Av 2018 10 22 23 0 1.5701875E-02 0.000000 0.000000 1.5566379E-04 0.000000 0.000000 0.000000 + Av 2018 10 22 24 0 1.5690099E-02 0.000000 0.000000 1.5561751E-04 0.000000 0.000000 0.000000 + Av 2018 10 23 1 0 1.5683025E-02 0.000000 0.000000 1.5549939E-04 0.000000 0.000000 0.000000 + Av 2018 10 23 2 0 1.5674321E-02 0.000000 0.000000 1.5545319E-04 0.000000 0.000000 0.000000 + Av 2018 10 23 3 0 1.5671071E-02 0.000000 0.000000 1.5540702E-04 0.000000 0.000000 0.000000 + Av 2018 10 23 4 0 1.5665928E-02 0.000000 0.000000 1.5536086E-04 0.000000 0.000000 0.000000 + Av 2018 10 23 5 0 1.5661443E-02 0.000000 0.000000 1.5531469E-04 0.000000 0.000000 0.000000 + Av 2018 10 23 6 0 1.5656730E-02 0.000000 0.000000 1.5526854E-04 0.000000 0.000000 0.000000 Av 2018 10 23 7 0 1.2672460E-02 0.000000 0.000000 1.1144701E-04 0.000000 0.000000 1.9897913E-04 Av 2018 10 23 8 0 4.8452425E-03 0.000000 0.000000 0.000000 0.000000 0.000000 2.5333541E-03 Av 2018 10 23 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.8677293E-03 @@ -7121,19 +7121,19 @@ Av 2018 10 23 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.8677293E-03 Av 2018 10 23 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 9.9999802E-03 2.5333541E-03 Av 2018 10 23 17 0 7.5408961E-03 0.000000 0.000000 1.1098648E-04 0.000000 0.000000 1.9897913E-04 - Av 2018 10 23 18 0 1.5694873E-02 0.000000 0.000000 1.5471592E-04 0.000000 9.9999802E-03 0.000000 - Av 2018 10 23 19 0 1.5827704E-02 0.000000 0.000000 1.5466995E-04 0.000000 0.000000 0.000000 - Av 2018 10 23 20 0 1.5511319E-02 0.000000 0.000000 1.5462399E-04 0.000000 0.000000 0.000000 - Av 2018 10 23 21 0 1.5615086E-02 0.000000 0.000000 1.5457807E-04 0.000000 0.000000 0.000000 - Av 2018 10 23 22 0 1.5572765E-02 0.000000 0.000000 1.5453214E-04 0.000000 0.000000 0.000000 - Av 2018 10 23 23 0 1.5581241E-02 0.000000 0.000000 1.5448623E-04 0.000000 0.000000 0.000000 - Av 2018 10 23 24 0 1.5572056E-02 0.000000 0.000000 1.5444033E-04 0.000000 0.000000 0.000000 - Av 2018 10 24 1 0 1.5564311E-02 0.000000 0.000000 1.5432524E-04 0.000000 0.000000 0.000000 - Av 2018 10 24 2 0 1.5556071E-02 0.000000 0.000000 1.5427942E-04 0.000000 0.000000 0.000000 - Av 2018 10 24 3 0 1.5552711E-02 0.000000 0.000000 1.5423361E-04 0.000000 0.000000 0.000000 - Av 2018 10 24 4 0 1.5547656E-02 0.000000 0.000000 1.5418782E-04 0.000000 0.000000 0.000000 - Av 2018 10 24 5 0 1.5543189E-02 0.000000 0.000000 1.5414202E-04 0.000000 0.000000 0.000000 - Av 2018 10 24 6 0 1.5538521E-02 0.000000 0.000000 1.5409625E-04 0.000000 0.000000 0.000000 + Av 2018 10 23 18 0 1.5694873E-02 0.000000 0.000000 1.5471592E-04 0.000000 9.9999802E-03 0.000000 + Av 2018 10 23 19 0 1.5827704E-02 0.000000 0.000000 1.5466995E-04 0.000000 0.000000 0.000000 + Av 2018 10 23 20 0 1.5511319E-02 0.000000 0.000000 1.5462399E-04 0.000000 0.000000 0.000000 + Av 2018 10 23 21 0 1.5615086E-02 0.000000 0.000000 1.5457807E-04 0.000000 0.000000 0.000000 + Av 2018 10 23 22 0 1.5572765E-02 0.000000 0.000000 1.5453214E-04 0.000000 0.000000 0.000000 + Av 2018 10 23 23 0 1.5581241E-02 0.000000 0.000000 1.5448623E-04 0.000000 0.000000 0.000000 + Av 2018 10 23 24 0 1.5572056E-02 0.000000 0.000000 1.5444033E-04 0.000000 0.000000 0.000000 + Av 2018 10 24 1 0 1.5564311E-02 0.000000 0.000000 1.5432524E-04 0.000000 0.000000 0.000000 + Av 2018 10 24 2 0 1.5556071E-02 0.000000 0.000000 1.5427942E-04 0.000000 0.000000 0.000000 + Av 2018 10 24 3 0 1.5552711E-02 0.000000 0.000000 1.5423361E-04 0.000000 0.000000 0.000000 + Av 2018 10 24 4 0 1.5547656E-02 0.000000 0.000000 1.5418782E-04 0.000000 0.000000 0.000000 + Av 2018 10 24 5 0 1.5543189E-02 0.000000 0.000000 1.5414202E-04 0.000000 0.000000 0.000000 + Av 2018 10 24 6 0 1.5538521E-02 0.000000 0.000000 1.5409625E-04 0.000000 0.000000 0.000000 Av 2018 10 24 7 0 1.3420416E-02 0.000000 0.000000 1.2299963E-04 0.000000 0.000000 1.4114031E-04 Av 2018 10 24 8 0 5.6522945E-03 0.000000 0.000000 0.000000 0.000000 0.000000 2.4747937E-03 Av 2018 10 24 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.8084473E-03 @@ -7145,19 +7145,19 @@ Av 2018 10 24 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.8084473E-03 Av 2018 10 24 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.4747937E-03 Av 2018 10 24 17 0 8.3260806E-03 0.000000 0.000000 1.2254278E-04 0.000000 0.000000 1.4114031E-04 - Av 2018 10 24 18 0 1.5863737E-02 0.000000 0.000000 1.5354803E-04 0.000000 0.000000 0.000000 - Av 2018 10 24 19 0 1.5346359E-02 0.000000 0.000000 1.5350243E-04 0.000000 0.000000 0.000000 - Av 2018 10 24 20 0 1.5520061E-02 0.000000 0.000000 1.5345686E-04 0.000000 0.000000 0.000000 - Av 2018 10 24 21 0 1.5453469E-02 0.000000 0.000000 1.5341128E-04 0.000000 0.000000 0.000000 - Av 2018 10 24 22 0 1.5470432E-02 0.000000 0.000000 1.5336572E-04 0.000000 0.000000 0.000000 - Av 2018 10 24 23 0 1.5458345E-02 0.000000 0.000000 1.5332019E-04 0.000000 0.000000 0.000000 - Av 2018 10 24 24 0 1.5456360E-02 0.000000 0.000000 1.5327465E-04 0.000000 0.000000 0.000000 - Av 2018 10 25 1 0 1.5446335E-02 0.000000 0.000000 1.5316249E-04 0.000000 0.000000 0.000000 - Av 2018 10 25 2 0 1.5439110E-02 0.000000 0.000000 1.5311701E-04 0.000000 0.000000 0.000000 - Av 2018 10 25 3 0 1.5435445E-02 0.000000 0.000000 1.5307157E-04 0.000000 0.000000 0.000000 - Av 2018 10 25 4 0 1.5430545E-02 0.000000 0.000000 1.5302614E-04 0.000000 0.000000 0.000000 - Av 2018 10 25 5 0 1.5426076E-02 0.000000 0.000000 1.5298072E-04 0.000000 0.000000 0.000000 - Av 2018 10 25 6 0 1.5421459E-02 0.000000 0.000000 1.5293530E-04 0.000000 0.000000 0.000000 + Av 2018 10 24 18 0 1.5863737E-02 0.000000 0.000000 1.5354803E-04 0.000000 0.000000 0.000000 + Av 2018 10 24 19 0 1.5346359E-02 0.000000 0.000000 1.5350243E-04 0.000000 0.000000 0.000000 + Av 2018 10 24 20 0 1.5520061E-02 0.000000 0.000000 1.5345686E-04 0.000000 0.000000 0.000000 + Av 2018 10 24 21 0 1.5453469E-02 0.000000 0.000000 1.5341128E-04 0.000000 0.000000 0.000000 + Av 2018 10 24 22 0 1.5470432E-02 0.000000 0.000000 1.5336572E-04 0.000000 0.000000 0.000000 + Av 2018 10 24 23 0 1.5458345E-02 0.000000 0.000000 1.5332019E-04 0.000000 0.000000 0.000000 + Av 2018 10 24 24 0 1.5456360E-02 0.000000 0.000000 1.5327465E-04 0.000000 0.000000 0.000000 + Av 2018 10 25 1 0 1.5446335E-02 0.000000 0.000000 1.5316249E-04 0.000000 0.000000 0.000000 + Av 2018 10 25 2 0 1.5439110E-02 0.000000 0.000000 1.5311701E-04 0.000000 0.000000 0.000000 + Av 2018 10 25 3 0 1.5435445E-02 0.000000 0.000000 1.5307157E-04 0.000000 0.000000 0.000000 + Av 2018 10 25 4 0 1.5430545E-02 0.000000 0.000000 1.5302614E-04 0.000000 0.000000 0.000000 + Av 2018 10 25 5 0 1.5426076E-02 0.000000 0.000000 1.5298072E-04 0.000000 0.000000 0.000000 + Av 2018 10 25 6 0 1.5421459E-02 0.000000 0.000000 1.5293530E-04 0.000000 0.000000 0.000000 Av 2018 10 25 7 0 1.4212362E-02 0.000000 0.000000 1.3519326E-04 0.000000 0.000000 8.0439262E-05 Av 2018 10 25 8 0 6.5027666E-03 0.000000 0.000000 0.000000 0.000000 0.000000 2.3205266E-03 Av 2018 10 25 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.5606140E-03 @@ -7169,19 +7169,19 @@ Av 2018 10 25 15 0 9.7858876E-02 2.7699851E-10 0.000000 0.000000 1.1777279E-02 1.9999960E-02 4.5606140E-03 Av 2018 10 25 16 0 0.1491365 3.2790312E-10 0.000000 0.000000 1.4857100E-02 1.9999960E-02 2.3205266E-03 Av 2018 10 25 17 0 0.2321801 1.0740572E-09 0.000000 1.3506785E-04 2.5012631E-02 2.9999940E-02 8.0439262E-05 - Av 2018 10 25 18 0 0.4878216 5.2599334E-09 0.000000 1.5289786E-04 5.4359328E-02 5.9999879E-02 0.000000 - Av 2018 10 25 19 0 0.4059489 6.7454248E-10 0.000000 1.5307365E-04 2.5721440E-02 1.9999960E-02 0.000000 - Av 2018 10 25 20 0 9.5704757E-02 0.000000 0.000000 1.5310170E-04 5.5612195E-03 0.000000 0.000000 - Av 2018 10 25 21 0 3.7606210E-02 0.000000 0.000000 1.5305619E-04 1.8098112E-03 0.000000 0.000000 - Av 2018 10 25 22 0 2.5194740E-02 0.000000 0.000000 1.5301067E-04 7.6218823E-04 0.000000 0.000000 - Av 2018 10 25 23 0 1.9797565E-02 0.000000 0.000000 1.5296516E-04 3.8120383E-04 0.000000 0.000000 - Av 2018 10 25 24 0 1.7950412E-02 0.000000 0.000000 1.5291969E-04 2.1503132E-04 0.000000 0.000000 - Av 2018 10 26 1 0 0.4491722 1.1444418E-08 0.000000 1.5294700E-04 6.3421935E-02 7.9999842E-02 0.000000 - Av 2018 10 26 2 0 0.4405725 2.1554049E-10 0.000000 1.5321633E-04 1.9310543E-02 9.9999802E-03 0.000000 - Av 2018 10 26 3 0 4.1172735E-02 0.000000 0.000000 1.5320758E-04 4.5277043E-03 0.000000 0.000000 - Av 2018 10 26 4 0 9.4183728E-02 2.1881241E-10 0.000000 1.5318066E-04 8.2866307E-03 9.9999802E-03 0.000000 - Av 2018 10 26 5 0 6.2816396E-02 0.000000 0.000000 1.5317192E-04 2.6243036E-03 0.000000 0.000000 - Av 2018 10 26 6 0 2.3724064E-02 0.000000 0.000000 1.5312633E-04 1.0190753E-03 0.000000 0.000000 + Av 2018 10 25 18 0 0.4878216 5.2599334E-09 0.000000 1.5289786E-04 5.4359328E-02 5.9999879E-02 0.000000 + Av 2018 10 25 19 0 0.4059489 6.7454248E-10 0.000000 1.5307365E-04 2.5721440E-02 1.9999960E-02 0.000000 + Av 2018 10 25 20 0 9.5704757E-02 0.000000 0.000000 1.5310170E-04 5.5612195E-03 0.000000 0.000000 + Av 2018 10 25 21 0 3.7606210E-02 0.000000 0.000000 1.5305619E-04 1.8098112E-03 0.000000 0.000000 + Av 2018 10 25 22 0 2.5194740E-02 0.000000 0.000000 1.5301067E-04 7.6218823E-04 0.000000 0.000000 + Av 2018 10 25 23 0 1.9797565E-02 0.000000 0.000000 1.5296516E-04 3.8120383E-04 0.000000 0.000000 + Av 2018 10 25 24 0 1.7950412E-02 0.000000 0.000000 1.5291969E-04 2.1503132E-04 0.000000 0.000000 + Av 2018 10 26 1 0 0.4491722 1.1444418E-08 0.000000 1.5294700E-04 6.3421935E-02 7.9999842E-02 0.000000 + Av 2018 10 26 2 0 0.4405725 2.1554049E-10 0.000000 1.5321633E-04 1.9310543E-02 9.9999802E-03 0.000000 + Av 2018 10 26 3 0 4.1172735E-02 0.000000 0.000000 1.5320758E-04 4.5277043E-03 0.000000 0.000000 + Av 2018 10 26 4 0 9.4183728E-02 2.1881241E-10 0.000000 1.5318066E-04 8.2866307E-03 9.9999802E-03 0.000000 + Av 2018 10 26 5 0 6.2816396E-02 0.000000 0.000000 1.5317192E-04 2.6243036E-03 0.000000 0.000000 + Av 2018 10 26 6 0 2.3724064E-02 0.000000 0.000000 1.5312633E-04 1.0190753E-03 0.000000 0.000000 Av 2018 10 26 7 0 2.2337707E-02 0.000000 0.000000 1.4691793E-04 4.8237556E-04 0.000000 2.8012877E-05 Av 2018 10 26 8 0 8.4190397E-03 0.000000 0.000000 0.000000 2.6166046E-04 0.000000 2.4571070E-03 Av 2018 10 26 9 0 2.9610490E-02 1.3068610E-10 0.000000 0.000000 4.3580541E-03 9.9999802E-03 4.8862011E-03 @@ -7193,20 +7193,20 @@ Av 2018 10 26 15 0 8.7276666E-04 0.000000 0.000000 0.000000 8.7760374E-05 0.000000 4.8862011E-03 Av 2018 10 26 16 0 7.2541763E-04 0.000000 0.000000 0.000000 6.0732829E-05 9.9999802E-03 2.4571070E-03 Av 2018 10 26 17 0 3.7416816E-02 1.6452474E-10 0.000000 1.4652140E-04 3.9729793E-03 2.9999940E-02 2.8012877E-05 - Av 2018 10 26 18 0 0.2559752 3.6323107E-09 0.000000 1.5274438E-04 3.2243073E-02 3.9999921E-02 0.000000 - Av 2018 10 26 19 0 0.3105415 9.8242725E-10 0.000000 1.5289082E-04 2.2742769E-02 1.9999960E-02 0.000000 - Av 2018 10 26 20 0 0.2670634 2.2820661E-09 0.000000 1.5300210E-04 2.8571529E-02 2.9999940E-02 0.000000 - Av 2018 10 26 21 0 0.2190896 2.6715247E-10 0.000000 1.5311294E-04 1.3685858E-02 9.9999802E-03 0.000000 - Av 2018 10 26 22 0 6.2855273E-02 0.000000 0.000000 1.5311205E-04 3.5276699E-03 0.000000 0.000000 - Av 2018 10 26 23 0 3.1615261E-02 0.000000 0.000000 1.5306642E-04 1.2803186E-03 0.000000 0.000000 - Av 2018 10 26 24 0 2.2438776E-02 0.000000 0.000000 1.5302080E-04 5.7926570E-04 0.000000 0.000000 - Av 2018 10 27 1 0 1.8987190E-02 0.000000 0.000000 1.5289446E-04 3.0442339E-04 0.000000 0.000000 - Av 2018 10 27 2 0 1.7449336E-02 0.000000 0.000000 1.5285324E-04 1.7796367E-04 0.000000 0.000000 - Av 2018 10 27 3 0 1.6674533E-02 0.000000 0.000000 1.5280773E-04 1.1255500E-04 0.000000 0.000000 - Av 2018 10 27 4 0 1.6242199E-02 0.000000 0.000000 1.5276221E-04 7.5592405E-05 0.000000 0.000000 - Av 2018 10 27 5 0 1.5983155E-02 0.000000 0.000000 1.5271670E-04 5.3214459E-05 0.000000 0.000000 - Av 2018 10 27 6 0 1.5817748E-02 0.000000 0.000000 1.5267121E-04 3.8901075E-05 0.000000 0.000000 - Av 2018 10 27 7 0 1.6785804E-02 0.000000 0.000000 1.5262574E-04 1.8813703E-04 0.000000 0.000000 + Av 2018 10 26 18 0 0.2559752 3.6323107E-09 0.000000 1.5274438E-04 3.2243073E-02 3.9999921E-02 0.000000 + Av 2018 10 26 19 0 0.3105415 9.8242725E-10 0.000000 1.5289082E-04 2.2742769E-02 1.9999960E-02 0.000000 + Av 2018 10 26 20 0 0.2670634 2.2820661E-09 0.000000 1.5300210E-04 2.8571529E-02 2.9999940E-02 0.000000 + Av 2018 10 26 21 0 0.2190896 2.6715247E-10 0.000000 1.5311294E-04 1.3685858E-02 9.9999802E-03 0.000000 + Av 2018 10 26 22 0 6.2855273E-02 0.000000 0.000000 1.5311205E-04 3.5276699E-03 0.000000 0.000000 + Av 2018 10 26 23 0 3.1615261E-02 0.000000 0.000000 1.5306642E-04 1.2803186E-03 0.000000 0.000000 + Av 2018 10 26 24 0 2.2438776E-02 0.000000 0.000000 1.5302080E-04 5.7926570E-04 0.000000 0.000000 + Av 2018 10 27 1 0 1.8987190E-02 0.000000 0.000000 1.5289446E-04 3.0442339E-04 0.000000 0.000000 + Av 2018 10 27 2 0 1.7449336E-02 0.000000 0.000000 1.5285324E-04 1.7796367E-04 0.000000 0.000000 + Av 2018 10 27 3 0 1.6674533E-02 0.000000 0.000000 1.5280773E-04 1.1255500E-04 0.000000 0.000000 + Av 2018 10 27 4 0 1.6242199E-02 0.000000 0.000000 1.5276221E-04 7.5592405E-05 0.000000 0.000000 + Av 2018 10 27 5 0 1.5983155E-02 0.000000 0.000000 1.5271670E-04 5.3214459E-05 0.000000 0.000000 + Av 2018 10 27 6 0 1.5817748E-02 0.000000 0.000000 1.5267121E-04 3.8901075E-05 0.000000 0.000000 + Av 2018 10 27 7 0 1.6785804E-02 0.000000 0.000000 1.5262574E-04 1.8813703E-04 0.000000 0.000000 Av 2018 10 27 8 0 8.9097582E-03 0.000000 0.000000 0.000000 0.000000 0.000000 2.2963274E-03 Av 2018 10 27 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.6220566E-03 Av 2018 10 27 10 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.7996218E-03 @@ -7216,21 +7216,21 @@ Av 2018 10 27 14 0 0.6050822 3.3318276E-08 0.000000 0.000000 8.9055315E-02 0.1399997 5.7996218E-03 Av 2018 10 27 15 0 1.376895 7.8850540E-08 0.000000 0.000000 0.1395028 0.1499997 4.6220566E-03 Av 2018 10 27 16 0 1.399068 9.4847813E-08 0.000000 0.000000 0.1268002 0.1299997 2.2963274E-03 - Av 2018 10 27 17 0 0.8183650 1.9343101E-08 0.000000 1.5518497E-04 5.6904797E-02 4.9999900E-02 0.000000 - Av 2018 10 27 18 0 0.6074784 4.4650928E-08 0.000000 1.5570017E-04 6.8135493E-02 6.9999859E-02 0.000000 - Av 2018 10 27 19 0 0.5295079 9.3483470E-09 0.000000 1.5622823E-04 3.5531871E-02 2.9999940E-02 0.000000 - Av 2018 10 27 20 0 1.019251 2.4310381E-07 0.000000 1.5688629E-04 0.1353221 0.1499997 0.000000 - Av 2018 10 27 21 0 2.242934 9.4052962E-07 0.000000 1.5882996E-04 0.2313124 0.2399995 0.000000 - Av 2018 10 27 22 0 2.527349 1.8234141E-06 0.000000 1.6189941E-04 0.2301082 0.2299995 0.000000 - Av 2018 10 27 23 0 1.190527 6.0880052E-09 0.000000 1.6416069E-04 3.3622228E-02 9.9999802E-03 0.000000 - Av 2018 10 27 24 0 0.2190675 5.5196466E-08 0.000000 1.6442226E-04 3.0597458E-02 2.9999940E-02 0.000000 - Av 2018 10 28 1 0 0.2190675 0.000000 0.000000 1.6452654E-04 6.2929154E-03 0.000000 0.000000 - Av 2018 10 28 2 0 2.4669096E-02 0.000000 0.000000 1.6448820E-04 1.9859015E-03 0.000000 0.000000 - Av 2018 10 28 3 0 3.2834738E-02 0.000000 0.000000 1.6443789E-04 8.1989146E-04 0.000000 0.000000 - Av 2018 10 28 4 0 1.9244142E-02 0.000000 0.000000 1.6438760E-04 4.0453294E-04 0.000000 0.000000 - Av 2018 10 28 5 0 1.9927641E-02 0.000000 0.000000 1.6433733E-04 2.2598737E-04 0.000000 0.000000 - Av 2018 10 28 6 0 1.7873332E-02 0.000000 0.000000 1.6428708E-04 1.3816464E-04 0.000000 0.000000 - Av 2018 10 28 7 0 1.7659593E-02 0.000000 0.000000 1.6423684E-04 9.0403490E-05 0.000000 0.000000 + Av 2018 10 27 17 0 0.8183650 1.9343101E-08 0.000000 1.5518497E-04 5.6904797E-02 4.9999900E-02 0.000000 + Av 2018 10 27 18 0 0.6074784 4.4650928E-08 0.000000 1.5570017E-04 6.8135493E-02 6.9999859E-02 0.000000 + Av 2018 10 27 19 0 0.5295079 9.3483470E-09 0.000000 1.5622823E-04 3.5531871E-02 2.9999940E-02 0.000000 + Av 2018 10 27 20 0 1.019251 2.4310381E-07 0.000000 1.5688629E-04 0.1353221 0.1499997 0.000000 + Av 2018 10 27 21 0 2.242934 9.4052962E-07 0.000000 1.5882996E-04 0.2313124 0.2399995 0.000000 + Av 2018 10 27 22 0 2.527349 1.8234141E-06 0.000000 1.6189941E-04 0.2301082 0.2299995 0.000000 + Av 2018 10 27 23 0 1.190527 6.0880052E-09 0.000000 1.6416069E-04 3.3622228E-02 9.9999802E-03 0.000000 + Av 2018 10 27 24 0 0.2190675 5.5196466E-08 0.000000 1.6442226E-04 3.0597458E-02 2.9999940E-02 0.000000 + Av 2018 10 28 1 0 0.2190675 0.000000 0.000000 1.6452654E-04 6.2929154E-03 0.000000 0.000000 + Av 2018 10 28 2 0 2.4669096E-02 0.000000 0.000000 1.6448820E-04 1.9859015E-03 0.000000 0.000000 + Av 2018 10 28 3 0 3.2834738E-02 0.000000 0.000000 1.6443789E-04 8.1989146E-04 0.000000 0.000000 + Av 2018 10 28 4 0 1.9244142E-02 0.000000 0.000000 1.6438760E-04 4.0453294E-04 0.000000 0.000000 + Av 2018 10 28 5 0 1.9927641E-02 0.000000 0.000000 1.6433733E-04 2.2598737E-04 0.000000 0.000000 + Av 2018 10 28 6 0 1.7873332E-02 0.000000 0.000000 1.6428708E-04 1.3816464E-04 0.000000 0.000000 + Av 2018 10 28 7 0 1.7659593E-02 0.000000 0.000000 1.6423684E-04 9.0403490E-05 0.000000 0.000000 Av 2018 10 28 8 0 8.6354027E-03 0.000000 0.000000 0.000000 6.2344814E-05 0.000000 2.2782898E-03 Av 2018 10 28 9 0 3.0456614E-04 0.000000 0.000000 0.000000 4.4825876E-05 0.000000 4.6431459E-03 Av 2018 10 28 10 0 3.7829057E-04 0.000000 0.000000 0.000000 3.3337139E-05 0.000000 5.8688568E-03 @@ -7240,21 +7240,21 @@ Av 2018 10 28 14 0 2.6775908E-02 0.000000 0.000000 0.000000 3.9408631E-03 0.000000 5.8688568E-03 Av 2018 10 28 15 0 2.6775908E-02 0.000000 0.000000 0.000000 1.3935922E-03 0.000000 4.6431459E-03 Av 2018 10 28 16 0 0.5429031 9.2712008E-07 0.000000 0.000000 7.9894900E-02 0.1199998 2.2782898E-03 - Av 2018 10 28 17 0 0.5429031 0.000000 0.000000 1.7068078E-04 1.3249120E-02 0.000000 0.000000 - Av 2018 10 28 18 0 3.5001136E-02 0.000000 0.000000 1.7062783E-04 3.4451699E-03 0.000000 0.000000 - Av 2018 10 28 19 0 4.2963009E-02 0.000000 0.000000 1.7057490E-04 1.2572788E-03 0.000000 0.000000 - Av 2018 10 28 20 0 2.0658560E-02 0.000000 0.000000 1.7052199E-04 5.7092489E-04 0.000000 0.000000 - Av 2018 10 28 21 0 2.1908140E-02 0.000000 0.000000 1.7046911E-04 3.0080584E-04 0.000000 0.000000 - Av 2018 10 28 22 0 1.8784363E-02 0.000000 0.000000 1.7041623E-04 1.7617490E-04 0.000000 0.000000 - Av 2018 10 28 23 0 1.8577658E-02 0.000000 0.000000 1.7036338E-04 1.1157910E-04 0.000000 0.000000 - Av 2018 10 28 24 0 0.4363533 6.6002946E-07 0.000000 1.7094165E-04 6.1293449E-02 7.9999842E-02 0.000000 - Av 2018 10 29 1 0 0.4792929 5.2256532E-08 0.000000 1.7197247E-04 2.7210224E-02 1.9999960E-02 0.000000 - Av 2018 10 29 2 0 0.1917498 4.8245035E-08 0.000000 1.7242602E-04 2.1306241E-02 1.9999960E-02 0.000000 - Av 2018 10 29 3 0 0.1398055 0.000000 0.000000 1.7269583E-04 4.8596789E-03 0.000000 0.000000 - Av 2018 10 29 4 0 2.2835221E-02 0.000000 0.000000 1.7264206E-04 1.6344544E-03 0.000000 0.000000 - Av 2018 10 29 5 0 7.4897185E-02 1.2228463E-08 0.000000 1.7267304E-04 7.0365155E-03 9.9999802E-03 0.000000 - Av 2018 10 29 6 0 6.2461842E-02 0.000000 0.000000 1.7278196E-04 2.4671310E-03 0.000000 0.000000 - Av 2018 10 29 7 0 2.5119301E-02 0.000000 0.000000 1.7272813E-04 9.7133522E-04 0.000000 0.000000 + Av 2018 10 28 17 0 0.5429031 0.000000 0.000000 1.7068078E-04 1.3249120E-02 0.000000 0.000000 + Av 2018 10 28 18 0 3.5001136E-02 0.000000 0.000000 1.7062783E-04 3.4451699E-03 0.000000 0.000000 + Av 2018 10 28 19 0 4.2963009E-02 0.000000 0.000000 1.7057490E-04 1.2572788E-03 0.000000 0.000000 + Av 2018 10 28 20 0 2.0658560E-02 0.000000 0.000000 1.7052199E-04 5.7092489E-04 0.000000 0.000000 + Av 2018 10 28 21 0 2.1908140E-02 0.000000 0.000000 1.7046911E-04 3.0080584E-04 0.000000 0.000000 + Av 2018 10 28 22 0 1.8784363E-02 0.000000 0.000000 1.7041623E-04 1.7617490E-04 0.000000 0.000000 + Av 2018 10 28 23 0 1.8577658E-02 0.000000 0.000000 1.7036338E-04 1.1157910E-04 0.000000 0.000000 + Av 2018 10 28 24 0 0.4363533 6.6002946E-07 0.000000 1.7094165E-04 6.1293449E-02 7.9999842E-02 0.000000 + Av 2018 10 29 1 0 0.4792929 5.2256532E-08 0.000000 1.7197247E-04 2.7210224E-02 1.9999960E-02 0.000000 + Av 2018 10 29 2 0 0.1917498 4.8245035E-08 0.000000 1.7242602E-04 2.1306241E-02 1.9999960E-02 0.000000 + Av 2018 10 29 3 0 0.1398055 0.000000 0.000000 1.7269583E-04 4.8596789E-03 0.000000 0.000000 + Av 2018 10 29 4 0 2.2835221E-02 0.000000 0.000000 1.7264206E-04 1.6344544E-03 0.000000 0.000000 + Av 2018 10 29 5 0 7.4897185E-02 1.2228463E-08 0.000000 1.7267304E-04 7.0365155E-03 9.9999802E-03 0.000000 + Av 2018 10 29 6 0 6.2461842E-02 0.000000 0.000000 1.7278196E-04 2.4671310E-03 0.000000 0.000000 + Av 2018 10 29 7 0 2.5119301E-02 0.000000 0.000000 1.7272813E-04 9.7133522E-04 0.000000 0.000000 Av 2018 10 29 8 0 1.4719424E-02 0.000000 0.000000 0.000000 4.6406660E-04 0.000000 1.9651509E-03 Av 2018 10 29 9 0 1.7216020E-03 0.000000 0.000000 0.000000 2.5338444E-04 0.000000 4.0565147E-03 Av 2018 10 29 10 0 2.0898529E-03 0.000000 0.000000 0.000000 1.5232257E-04 0.000000 5.1653031E-03 @@ -7264,21 +7264,21 @@ Av 2018 10 29 14 0 1.0181225E-02 2.3304327E-09 0.000000 0.000000 1.4513604E-03 2.9999940E-02 5.1653031E-03 Av 2018 10 29 15 0 1.2276974E-02 0.000000 0.000000 0.000000 8.6746609E-04 0.000000 4.0565147E-03 Av 2018 10 29 16 0 4.3474948E-03 0.000000 0.000000 0.000000 4.2348748E-04 0.000000 1.9651509E-03 - Av 2018 10 29 17 0 1.4638361E-02 0.000000 0.000000 1.7229869E-04 2.3479467E-04 0.000000 0.000000 - Av 2018 10 29 18 0 2.0885076E-02 0.000000 0.000000 1.7224500E-04 1.4274882E-04 0.000000 0.000000 - Av 2018 10 29 19 0 1.7742362E-02 0.000000 0.000000 1.7219133E-04 9.3005023E-05 0.000000 0.000000 - Av 2018 10 29 20 0 1.8292256E-02 0.000000 0.000000 1.7213768E-04 6.3924512E-05 0.000000 0.000000 - Av 2018 10 29 21 0 1.8066768E-02 0.000000 0.000000 1.7208404E-04 4.5838431E-05 9.9999802E-03 0.000000 - Av 2018 10 29 22 0 1.7934669E-02 0.000000 0.000000 1.7203043E-04 3.4015466E-05 0.000000 0.000000 - Av 2018 10 29 23 0 1.8547801E-02 0.000000 0.000000 1.7197683E-04 1.7358418E-04 0.000000 0.000000 - Av 2018 10 29 24 0 1.8096212E-02 0.000000 0.000000 1.7192325E-04 0.000000 0.000000 0.000000 - Av 2018 10 30 1 0 1.7045429E-02 0.000000 0.000000 1.7155886E-04 0.000000 0.000000 0.000000 - Av 2018 10 30 2 0 1.7382743E-02 0.000000 0.000000 1.7151037E-04 0.000000 0.000000 0.000000 - Av 2018 10 30 3 0 1.7258538E-02 0.000000 0.000000 1.7145704E-04 0.000000 0.000000 0.000000 - Av 2018 10 30 4 0 1.7294478E-02 0.000000 0.000000 1.7140371E-04 0.000000 0.000000 0.000000 - Av 2018 10 30 5 0 1.7274735E-02 0.000000 0.000000 1.7135039E-04 0.000000 0.000000 0.000000 - Av 2018 10 30 6 0 1.7274356E-02 0.000000 0.000000 1.7129708E-04 0.000000 0.000000 0.000000 - Av 2018 10 30 7 0 1.7267246E-02 0.000000 0.000000 1.7124381E-04 0.000000 0.000000 0.000000 + Av 2018 10 29 17 0 1.4638361E-02 0.000000 0.000000 1.7229869E-04 2.3479467E-04 0.000000 0.000000 + Av 2018 10 29 18 0 2.0885076E-02 0.000000 0.000000 1.7224500E-04 1.4274882E-04 0.000000 0.000000 + Av 2018 10 29 19 0 1.7742362E-02 0.000000 0.000000 1.7219133E-04 9.3005023E-05 0.000000 0.000000 + Av 2018 10 29 20 0 1.8292256E-02 0.000000 0.000000 1.7213768E-04 6.3924512E-05 0.000000 0.000000 + Av 2018 10 29 21 0 1.8066768E-02 0.000000 0.000000 1.7208404E-04 4.5838431E-05 9.9999802E-03 0.000000 + Av 2018 10 29 22 0 1.7934669E-02 0.000000 0.000000 1.7203043E-04 3.4015466E-05 0.000000 0.000000 + Av 2018 10 29 23 0 1.8547801E-02 0.000000 0.000000 1.7197683E-04 1.7358418E-04 0.000000 0.000000 + Av 2018 10 29 24 0 1.8096212E-02 0.000000 0.000000 1.7192325E-04 0.000000 0.000000 0.000000 + Av 2018 10 30 1 0 1.7045429E-02 0.000000 0.000000 1.7155886E-04 0.000000 0.000000 0.000000 + Av 2018 10 30 2 0 1.7382743E-02 0.000000 0.000000 1.7151037E-04 0.000000 0.000000 0.000000 + Av 2018 10 30 3 0 1.7258538E-02 0.000000 0.000000 1.7145704E-04 0.000000 0.000000 0.000000 + Av 2018 10 30 4 0 1.7294478E-02 0.000000 0.000000 1.7140371E-04 0.000000 0.000000 0.000000 + Av 2018 10 30 5 0 1.7274735E-02 0.000000 0.000000 1.7135039E-04 0.000000 0.000000 0.000000 + Av 2018 10 30 6 0 1.7274356E-02 0.000000 0.000000 1.7129708E-04 0.000000 0.000000 0.000000 + Av 2018 10 30 7 0 1.7267246E-02 0.000000 0.000000 1.7124381E-04 0.000000 0.000000 0.000000 Av 2018 10 30 8 0 8.6327437E-03 0.000000 0.000000 0.000000 0.000000 0.000000 2.0142517E-03 Av 2018 10 30 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.2128954E-03 Av 2018 10 30 10 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.4044137E-03 @@ -7288,21 +7288,21 @@ Av 2018 10 30 14 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.4044137E-03 Av 2018 10 30 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.2128954E-03 Av 2018 10 30 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.0142517E-03 - Av 2018 10 30 17 0 1.1598900E-02 0.000000 0.000000 1.7071195E-04 0.000000 0.000000 0.000000 - Av 2018 10 30 18 0 1.9161152E-02 0.000000 0.000000 1.7065887E-04 0.000000 0.000000 0.000000 - Av 2018 10 30 19 0 1.6524477E-02 0.000000 0.000000 1.7060580E-04 0.000000 0.000000 0.000000 - Av 2018 10 30 20 0 1.7434061E-02 0.000000 0.000000 1.7055274E-04 0.000000 0.000000 0.000000 - Av 2018 10 30 21 0 1.7390281E-02 0.000000 0.000000 1.7049970E-04 0.000000 9.9999802E-03 0.000000 - Av 2018 10 30 22 0 1.7692842E-02 0.000000 0.000000 1.7044666E-04 0.000000 9.9999802E-03 0.000000 - Av 2018 10 30 23 0 1.7300734E-02 0.000000 0.000000 1.7039364E-04 0.000000 0.000000 0.000000 - Av 2018 10 30 24 0 0.1567751 1.2679575E-07 0.000000 1.7060572E-04 2.0341696E-02 4.9999900E-02 0.000000 - Av 2018 10 31 1 0 0.2522455 5.5602548E-08 0.000000 1.7094532E-04 2.0838534E-02 1.9999960E-02 0.000000 - Av 2018 10 31 2 0 0.1635656 1.2830900E-08 0.000000 1.7136107E-04 1.2231315E-02 9.9999802E-03 0.000000 - Av 2018 10 31 3 0 7.2587073E-02 0.000000 0.000000 1.7148808E-04 3.2496096E-03 0.000000 0.000000 - 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Av 2018 10 31 17 0 1.1600934E-02 0.000000 0.000000 1.7074189E-04 0.000000 0.000000 0.000000 - Av 2018 10 31 18 0 1.9164506E-02 0.000000 0.000000 1.7068870E-04 0.000000 0.000000 0.000000 - Av 2018 10 31 19 0 1.6527358E-02 0.000000 0.000000 1.7063553E-04 0.000000 0.000000 0.000000 - Av 2018 10 31 20 0 1.7437093E-02 0.000000 0.000000 1.7058238E-04 0.000000 0.000000 0.000000 - Av 2018 10 31 21 0 1.7113551E-02 0.000000 0.000000 1.7052925E-04 0.000000 0.000000 0.000000 - Av 2018 10 31 22 0 1.7218832E-02 0.000000 0.000000 1.7047614E-04 0.000000 0.000000 0.000000 - Av 2018 10 31 23 0 1.7175008E-02 0.000000 0.000000 1.7042305E-04 0.000000 0.000000 0.000000 - Av 2018 10 31 24 0 1.7183032E-02 0.000000 0.000000 1.7036998E-04 0.000000 0.000000 0.000000 - Av 2018 11 1 1 0 1.7152078E-02 0.000000 0.000000 1.7000853E-04 0.000000 0.000000 0.000000 - Av 2018 11 1 2 0 1.7134691E-02 0.000000 0.000000 1.6995567E-04 0.000000 0.000000 0.000000 - Av 2018 11 1 3 0 1.7133556E-02 0.000000 0.000000 1.6990285E-04 0.000000 0.000000 0.000000 - 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Av 2018 11 1 17 0 1.1493783E-02 0.000000 0.000000 1.6916485E-04 0.000000 0.000000 0.000000 - Av 2018 11 1 18 0 1.8987503E-02 0.000000 0.000000 1.6911226E-04 0.000000 0.000000 0.000000 - Av 2018 11 1 19 0 1.6374726E-02 0.000000 0.000000 1.6905970E-04 0.000000 0.000000 0.000000 - Av 2018 11 1 20 0 1.7276067E-02 0.000000 0.000000 1.6900714E-04 0.000000 0.000000 0.000000 - Av 2018 11 1 21 0 1.6955523E-02 0.000000 0.000000 1.6895460E-04 0.000000 0.000000 0.000000 - Av 2018 11 1 22 0 1.7059840E-02 0.000000 0.000000 1.6890207E-04 0.000000 0.000000 0.000000 - Av 2018 11 1 23 0 1.7016433E-02 0.000000 0.000000 1.6884957E-04 0.000000 0.000000 0.000000 - Av 2018 11 1 24 0 1.7024390E-02 0.000000 0.000000 1.6879707E-04 0.000000 0.000000 0.000000 - Av 2018 11 2 1 0 1.6994316E-02 0.000000 0.000000 1.6844767E-04 0.000000 0.000000 0.000000 - Av 2018 11 2 2 0 1.6977482E-02 0.000000 0.000000 1.6839539E-04 0.000000 0.000000 0.000000 - Av 2018 11 2 3 0 1.7816246E-02 0.000000 0.000000 1.6834313E-04 0.000000 2.9999940E-02 0.000000 - Av 2018 11 2 4 0 1.8418867E-02 0.000000 0.000000 1.6829091E-04 0.000000 2.9999940E-02 0.000000 - Av 2018 11 2 5 0 0.1068504 7.9019863E-08 0.000000 1.6846410E-04 1.3036600E-02 2.9999940E-02 0.000000 - Av 2018 11 2 6 0 0.1023148 0.000000 0.000000 1.6885326E-04 3.9850306E-03 0.000000 0.000000 - Av 2018 11 2 7 0 2.3991471E-02 0.000000 0.000000 1.6880079E-04 1.4055029E-03 0.000000 0.000000 + Av 2018 11 1 17 0 1.1493783E-02 0.000000 0.000000 1.6916485E-04 0.000000 0.000000 0.000000 + Av 2018 11 1 18 0 1.8987503E-02 0.000000 0.000000 1.6911226E-04 0.000000 0.000000 0.000000 + Av 2018 11 1 19 0 1.6374726E-02 0.000000 0.000000 1.6905970E-04 0.000000 0.000000 0.000000 + Av 2018 11 1 20 0 1.7276067E-02 0.000000 0.000000 1.6900714E-04 0.000000 0.000000 0.000000 + Av 2018 11 1 21 0 1.6955523E-02 0.000000 0.000000 1.6895460E-04 0.000000 0.000000 0.000000 + Av 2018 11 1 22 0 1.7059840E-02 0.000000 0.000000 1.6890207E-04 0.000000 0.000000 0.000000 + Av 2018 11 1 23 0 1.7016433E-02 0.000000 0.000000 1.6884957E-04 0.000000 0.000000 0.000000 + Av 2018 11 1 24 0 1.7024390E-02 0.000000 0.000000 1.6879707E-04 0.000000 0.000000 0.000000 + Av 2018 11 2 1 0 1.6994316E-02 0.000000 0.000000 1.6844767E-04 0.000000 0.000000 0.000000 + Av 2018 11 2 2 0 1.6977482E-02 0.000000 0.000000 1.6839539E-04 0.000000 0.000000 0.000000 + Av 2018 11 2 3 0 1.7816246E-02 0.000000 0.000000 1.6834313E-04 0.000000 2.9999940E-02 0.000000 + Av 2018 11 2 4 0 1.8418867E-02 0.000000 0.000000 1.6829091E-04 0.000000 2.9999940E-02 0.000000 + Av 2018 11 2 5 0 0.1068504 7.9019863E-08 0.000000 1.6846410E-04 1.3036600E-02 2.9999940E-02 0.000000 + Av 2018 11 2 6 0 0.1023148 0.000000 0.000000 1.6885326E-04 3.9850306E-03 0.000000 0.000000 + Av 2018 11 2 7 0 2.3991471E-02 0.000000 0.000000 1.6880079E-04 1.4055029E-03 0.000000 0.000000 Av 2018 11 2 8 0 1.9433938E-02 0.000000 0.000000 0.000000 6.2396954E-04 0.000000 2.1785758E-03 Av 2018 11 2 9 0 2.1988517E-03 0.000000 0.000000 0.000000 3.2362575E-04 0.000000 4.7165430E-03 Av 2018 11 2 10 0 2.6172639E-03 0.000000 0.000000 0.000000 1.8739094E-04 0.000000 6.1652227E-03 @@ -7360,21 +7360,21 @@ Av 2018 11 2 14 0 3.7714245E-04 0.000000 0.000000 0.000000 4.0123890E-05 0.000000 6.1652227E-03 Av 2018 11 2 15 0 1.3620019E-03 0.000000 0.000000 0.000000 1.9166266E-04 0.000000 4.7165430E-03 Av 2018 11 2 16 0 1.2176766E-03 0.000000 0.000000 0.000000 0.000000 0.000000 2.1785758E-03 - Av 2018 11 2 17 0 1.1433458E-02 0.000000 0.000000 1.6827699E-04 0.000000 0.000000 0.000000 - Av 2018 11 2 18 0 1.8887848E-02 0.000000 0.000000 1.6822469E-04 0.000000 0.000000 0.000000 - Av 2018 11 2 19 0 1.6288785E-02 0.000000 0.000000 1.6817242E-04 0.000000 0.000000 0.000000 - Av 2018 11 2 20 0 1.7185401E-02 0.000000 0.000000 1.6812018E-04 0.000000 0.000000 0.000000 - Av 2018 11 2 21 0 1.6866541E-02 0.000000 0.000000 1.6806793E-04 0.000000 0.000000 0.000000 - Av 2018 11 2 22 0 1.6970312E-02 0.000000 0.000000 1.6801570E-04 0.000000 0.000000 0.000000 - Av 2018 11 2 23 0 1.6927134E-02 0.000000 0.000000 1.6796349E-04 0.000000 0.000000 0.000000 - Av 2018 11 2 24 0 1.6935054E-02 0.000000 0.000000 1.6791129E-04 0.000000 0.000000 0.000000 - Av 2018 11 3 1 0 1.6905276E-02 0.000000 0.000000 1.6756575E-04 0.000000 0.000000 0.000000 - Av 2018 11 3 2 0 1.6888622E-02 0.000000 0.000000 1.6751378E-04 0.000000 0.000000 0.000000 - Av 2018 11 3 3 0 1.6887350E-02 0.000000 0.000000 1.6746181E-04 0.000000 0.000000 0.000000 - Av 2018 11 3 4 0 1.6880732E-02 0.000000 0.000000 1.6740986E-04 0.000000 0.000000 0.000000 - Av 2018 11 3 5 0 1.6875975E-02 0.000000 0.000000 1.6735792E-04 0.000000 0.000000 0.000000 - Av 2018 11 3 6 0 1.6870571E-02 0.000000 0.000000 1.6730600E-04 0.000000 0.000000 0.000000 - Av 2018 11 3 7 0 1.6865395E-02 0.000000 0.000000 1.6725410E-04 0.000000 0.000000 0.000000 + Av 2018 11 2 17 0 1.1433458E-02 0.000000 0.000000 1.6827699E-04 0.000000 0.000000 0.000000 + Av 2018 11 2 18 0 1.8887848E-02 0.000000 0.000000 1.6822469E-04 0.000000 0.000000 0.000000 + Av 2018 11 2 19 0 1.6288785E-02 0.000000 0.000000 1.6817242E-04 0.000000 0.000000 0.000000 + Av 2018 11 2 20 0 1.7185401E-02 0.000000 0.000000 1.6812018E-04 0.000000 0.000000 0.000000 + Av 2018 11 2 21 0 1.6866541E-02 0.000000 0.000000 1.6806793E-04 0.000000 0.000000 0.000000 + Av 2018 11 2 22 0 1.6970312E-02 0.000000 0.000000 1.6801570E-04 0.000000 0.000000 0.000000 + Av 2018 11 2 23 0 1.6927134E-02 0.000000 0.000000 1.6796349E-04 0.000000 0.000000 0.000000 + Av 2018 11 2 24 0 1.6935054E-02 0.000000 0.000000 1.6791129E-04 0.000000 0.000000 0.000000 + Av 2018 11 3 1 0 1.6905276E-02 0.000000 0.000000 1.6756575E-04 0.000000 0.000000 0.000000 + Av 2018 11 3 2 0 1.6888622E-02 0.000000 0.000000 1.6751378E-04 0.000000 0.000000 0.000000 + Av 2018 11 3 3 0 1.6887350E-02 0.000000 0.000000 1.6746181E-04 0.000000 0.000000 0.000000 + Av 2018 11 3 4 0 1.6880732E-02 0.000000 0.000000 1.6740986E-04 0.000000 0.000000 0.000000 + Av 2018 11 3 5 0 1.6875975E-02 0.000000 0.000000 1.6735792E-04 0.000000 0.000000 0.000000 + Av 2018 11 3 6 0 1.6870571E-02 0.000000 0.000000 1.6730600E-04 0.000000 0.000000 0.000000 + Av 2018 11 3 7 0 1.6865395E-02 0.000000 0.000000 1.6725410E-04 0.000000 0.000000 0.000000 Av 2018 11 3 8 0 8.4313741E-03 0.000000 0.000000 0.000000 0.000000 0.000000 1.9461166E-03 Av 2018 11 3 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.2747245E-03 Av 2018 11 3 10 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.6302738E-03 @@ -7384,21 +7384,21 @@ Av 2018 11 3 14 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 5.6302738E-03 Av 2018 11 3 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.2747245E-03 Av 2018 11 3 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 9.9999802E-03 1.9461166E-03 - Av 2018 11 3 17 0 1.1328757E-02 0.000000 0.000000 1.6673600E-04 0.000000 9.9999802E-03 0.000000 - Av 2018 11 3 18 0 1.8714890E-02 0.000000 0.000000 1.6668429E-04 0.000000 0.000000 0.000000 - Av 2018 11 3 19 0 1.6139640E-02 0.000000 0.000000 1.6663258E-04 0.000000 0.000000 0.000000 - Av 2018 11 3 20 0 1.7028052E-02 0.000000 0.000000 1.6658088E-04 0.000000 0.000000 0.000000 - Av 2018 11 3 21 0 1.6712118E-02 0.000000 0.000000 1.6652921E-04 0.000000 0.000000 0.000000 - Av 2018 11 3 22 0 1.6814951E-02 0.000000 0.000000 1.6647755E-04 0.000000 0.000000 0.000000 - Av 2018 11 3 23 0 1.6772177E-02 0.000000 0.000000 1.6642590E-04 0.000000 0.000000 0.000000 - Av 2018 11 3 24 0 1.6780034E-02 0.000000 0.000000 1.6637429E-04 0.000000 0.000000 0.000000 - Av 2018 11 4 1 0 1.6751096E-02 0.000000 0.000000 1.6604022E-04 0.000000 0.000000 0.000000 - Av 2018 11 4 2 0 1.7290864E-02 0.000000 0.000000 1.6598881E-04 0.000000 1.9999960E-02 0.000000 - Av 2018 11 4 3 0 1.8274762E-02 0.000000 0.000000 1.6593740E-04 0.000000 3.9999921E-02 0.000000 - Av 2018 11 4 4 0 0.1319942 1.1158311E-07 0.000000 1.6614760E-04 1.6733816E-02 2.9999940E-02 0.000000 - Av 2018 11 4 5 0 0.2298955 5.3706163E-08 0.000000 1.6679465E-04 2.0079745E-02 1.9999960E-02 0.000000 - Av 2018 11 4 6 0 0.1644758 1.3607454E-08 0.000000 1.6719151E-04 1.2092318E-02 9.9999802E-03 0.000000 - Av 2018 11 4 7 0 7.0590779E-02 0.000000 0.000000 1.6731946E-04 3.2225254E-03 0.000000 0.000000 + Av 2018 11 3 17 0 1.1328757E-02 0.000000 0.000000 1.6673600E-04 0.000000 9.9999802E-03 0.000000 + Av 2018 11 3 18 0 1.8714890E-02 0.000000 0.000000 1.6668429E-04 0.000000 0.000000 0.000000 + Av 2018 11 3 19 0 1.6139640E-02 0.000000 0.000000 1.6663258E-04 0.000000 0.000000 0.000000 + Av 2018 11 3 20 0 1.7028052E-02 0.000000 0.000000 1.6658088E-04 0.000000 0.000000 0.000000 + Av 2018 11 3 21 0 1.6712118E-02 0.000000 0.000000 1.6652921E-04 0.000000 0.000000 0.000000 + Av 2018 11 3 22 0 1.6814951E-02 0.000000 0.000000 1.6647755E-04 0.000000 0.000000 0.000000 + Av 2018 11 3 23 0 1.6772177E-02 0.000000 0.000000 1.6642590E-04 0.000000 0.000000 0.000000 + Av 2018 11 3 24 0 1.6780034E-02 0.000000 0.000000 1.6637429E-04 0.000000 0.000000 0.000000 + Av 2018 11 4 1 0 1.6751096E-02 0.000000 0.000000 1.6604022E-04 0.000000 0.000000 0.000000 + Av 2018 11 4 2 0 1.7290864E-02 0.000000 0.000000 1.6598881E-04 0.000000 1.9999960E-02 0.000000 + Av 2018 11 4 3 0 1.8274762E-02 0.000000 0.000000 1.6593740E-04 0.000000 3.9999921E-02 0.000000 + Av 2018 11 4 4 0 0.1319942 1.1158311E-07 0.000000 1.6614760E-04 1.6733816E-02 2.9999940E-02 0.000000 + Av 2018 11 4 5 0 0.2298955 5.3706163E-08 0.000000 1.6679465E-04 2.0079745E-02 1.9999960E-02 0.000000 + Av 2018 11 4 6 0 0.1644758 1.3607454E-08 0.000000 1.6719151E-04 1.2092318E-02 9.9999802E-03 0.000000 + Av 2018 11 4 7 0 7.0590779E-02 0.000000 0.000000 1.6731946E-04 3.2225254E-03 0.000000 0.000000 Av 2018 11 4 8 0 1.6770832E-02 0.000000 0.000000 0.000000 1.1943391E-03 0.000000 1.7644628E-03 Av 2018 11 4 9 0 5.8735060E-03 0.000000 0.000000 0.000000 5.4794928E-04 0.000000 3.9338167E-03 Av 2018 11 4 10 0 3.5055564E-03 0.000000 0.000000 0.000000 2.9078135E-04 0.000000 5.2209389E-03 @@ -7408,21 +7408,21 @@ Av 2018 11 4 14 0 5.8947783E-04 0.000000 0.000000 0.000000 5.1847590E-05 9.9999802E-03 5.2209389E-03 Av 2018 11 4 15 0 4.1261851E-04 0.000000 0.000000 0.000000 3.8002803E-05 0.000000 3.9338167E-03 Av 2018 11 4 16 0 1.3314119E-03 0.000000 0.000000 0.000000 1.8551879E-04 0.000000 1.7644628E-03 - Av 2018 11 4 17 0 1.2117947E-02 0.000000 0.000000 1.6680038E-04 0.000000 0.000000 0.000000 - Av 2018 11 4 18 0 1.8449223E-02 0.000000 0.000000 1.6674856E-04 0.000000 0.000000 0.000000 - Av 2018 11 4 19 0 1.6240742E-02 0.000000 0.000000 1.6669676E-04 0.000000 0.000000 0.000000 - Av 2018 11 4 20 0 1.7001612E-02 0.000000 0.000000 1.6664497E-04 0.000000 0.000000 0.000000 - Av 2018 11 4 21 0 1.6730014E-02 0.000000 0.000000 1.6659319E-04 0.000000 0.000000 0.000000 - Av 2018 11 4 22 0 1.6817417E-02 0.000000 0.000000 1.6654143E-04 0.000000 0.000000 0.000000 - Av 2018 11 4 23 0 1.6779993E-02 0.000000 0.000000 1.6648968E-04 0.000000 0.000000 0.000000 - Av 2018 11 4 24 0 1.6785976E-02 0.000000 0.000000 1.6643797E-04 0.000000 0.000000 0.000000 - Av 2018 11 5 1 0 1.6757190E-02 0.000000 0.000000 1.6609662E-04 0.000000 0.000000 0.000000 - Av 2018 11 5 2 0 1.6740505E-02 0.000000 0.000000 1.6604509E-04 0.000000 0.000000 0.000000 - Av 2018 11 5 3 0 1.6739305E-02 0.000000 0.000000 1.6599360E-04 0.000000 0.000000 0.000000 - Av 2018 11 5 4 0 1.6732726E-02 0.000000 0.000000 1.6594211E-04 0.000000 0.000000 0.000000 - Av 2018 11 5 5 0 1.6728019E-02 0.000000 0.000000 1.6589065E-04 0.000000 0.000000 0.000000 - Av 2018 11 5 6 0 1.6722664E-02 0.000000 0.000000 1.6583921E-04 0.000000 0.000000 0.000000 - Av 2018 11 5 7 0 1.6717538E-02 0.000000 0.000000 1.6578779E-04 0.000000 0.000000 0.000000 + Av 2018 11 4 17 0 1.2117947E-02 0.000000 0.000000 1.6680038E-04 0.000000 0.000000 0.000000 + Av 2018 11 4 18 0 1.8449223E-02 0.000000 0.000000 1.6674856E-04 0.000000 0.000000 0.000000 + Av 2018 11 4 19 0 1.6240742E-02 0.000000 0.000000 1.6669676E-04 0.000000 0.000000 0.000000 + Av 2018 11 4 20 0 1.7001612E-02 0.000000 0.000000 1.6664497E-04 0.000000 0.000000 0.000000 + Av 2018 11 4 21 0 1.6730014E-02 0.000000 0.000000 1.6659319E-04 0.000000 0.000000 0.000000 + Av 2018 11 4 22 0 1.6817417E-02 0.000000 0.000000 1.6654143E-04 0.000000 0.000000 0.000000 + Av 2018 11 4 23 0 1.6779993E-02 0.000000 0.000000 1.6648968E-04 0.000000 0.000000 0.000000 + Av 2018 11 4 24 0 1.6785976E-02 0.000000 0.000000 1.6643797E-04 0.000000 0.000000 0.000000 + Av 2018 11 5 1 0 1.6757190E-02 0.000000 0.000000 1.6609662E-04 0.000000 0.000000 0.000000 + Av 2018 11 5 2 0 1.6740505E-02 0.000000 0.000000 1.6604509E-04 0.000000 0.000000 0.000000 + Av 2018 11 5 3 0 1.6739305E-02 0.000000 0.000000 1.6599360E-04 0.000000 0.000000 0.000000 + Av 2018 11 5 4 0 1.6732726E-02 0.000000 0.000000 1.6594211E-04 0.000000 0.000000 0.000000 + Av 2018 11 5 5 0 1.6728019E-02 0.000000 0.000000 1.6589065E-04 0.000000 0.000000 0.000000 + Av 2018 11 5 6 0 1.6722664E-02 0.000000 0.000000 1.6583921E-04 0.000000 0.000000 0.000000 + Av 2018 11 5 7 0 1.6717538E-02 0.000000 0.000000 1.6578779E-04 0.000000 0.000000 0.000000 Av 2018 11 5 8 0 8.3574569E-03 0.000000 0.000000 0.000000 0.000000 0.000000 1.5920062E-03 Av 2018 11 5 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.6040156E-03 Av 2018 11 5 10 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.8200218E-03 @@ -7432,21 +7432,21 @@ Av 2018 11 5 14 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.8200218E-03 Av 2018 11 5 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.6040156E-03 Av 2018 11 5 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.5920062E-03 - Av 2018 11 5 17 0 1.1229444E-02 0.000000 0.000000 1.6527432E-04 0.000000 0.000000 0.000000 - Av 2018 11 5 18 0 1.8550828E-02 0.000000 0.000000 1.6522307E-04 0.000000 0.000000 0.000000 - Av 2018 11 5 19 0 1.5998153E-02 0.000000 0.000000 1.6517182E-04 0.000000 0.000000 0.000000 - Av 2018 11 5 20 0 1.6878780E-02 0.000000 0.000000 1.6512060E-04 0.000000 0.000000 0.000000 - Av 2018 11 5 21 0 1.6565619E-02 0.000000 0.000000 1.6506940E-04 0.000000 0.000000 0.000000 - Av 2018 11 5 22 0 1.6667550E-02 0.000000 0.000000 1.6501821E-04 0.000000 0.000000 0.000000 - Av 2018 11 5 23 0 1.6625151E-02 0.000000 0.000000 1.6496703E-04 0.000000 0.000000 0.000000 - Av 2018 11 5 24 0 1.6632941E-02 0.000000 0.000000 1.6491585E-04 0.000000 0.000000 0.000000 - Av 2018 11 6 1 0 1.6604330E-02 0.000000 0.000000 1.6458583E-04 0.000000 0.000000 0.000000 - Av 2018 11 6 2 0 1.7141864E-02 0.000000 0.000000 1.6453488E-04 0.000000 1.9999960E-02 0.000000 - Av 2018 11 6 3 0 1.6948037E-02 0.000000 0.000000 1.6448395E-04 0.000000 0.000000 0.000000 - Av 2018 11 6 4 0 1.6455041E-02 0.000000 0.000000 1.6443302E-04 0.000000 0.000000 0.000000 - Av 2018 11 6 5 0 1.6619541E-02 0.000000 0.000000 1.6438210E-04 0.000000 0.000000 0.000000 - Av 2018 11 6 6 0 1.6555425E-02 0.000000 0.000000 1.6433120E-04 0.000000 0.000000 0.000000 - Av 2018 11 6 7 0 1.6570803E-02 0.000000 0.000000 1.6428033E-04 0.000000 0.000000 0.000000 + Av 2018 11 5 17 0 1.1229444E-02 0.000000 0.000000 1.6527432E-04 0.000000 0.000000 0.000000 + Av 2018 11 5 18 0 1.8550828E-02 0.000000 0.000000 1.6522307E-04 0.000000 0.000000 0.000000 + Av 2018 11 5 19 0 1.5998153E-02 0.000000 0.000000 1.6517182E-04 0.000000 0.000000 0.000000 + Av 2018 11 5 20 0 1.6878780E-02 0.000000 0.000000 1.6512060E-04 0.000000 0.000000 0.000000 + Av 2018 11 5 21 0 1.6565619E-02 0.000000 0.000000 1.6506940E-04 0.000000 0.000000 0.000000 + Av 2018 11 5 22 0 1.6667550E-02 0.000000 0.000000 1.6501821E-04 0.000000 0.000000 0.000000 + Av 2018 11 5 23 0 1.6625151E-02 0.000000 0.000000 1.6496703E-04 0.000000 0.000000 0.000000 + Av 2018 11 5 24 0 1.6632941E-02 0.000000 0.000000 1.6491585E-04 0.000000 0.000000 0.000000 + Av 2018 11 6 1 0 1.6604330E-02 0.000000 0.000000 1.6458583E-04 0.000000 0.000000 0.000000 + Av 2018 11 6 2 0 1.7141864E-02 0.000000 0.000000 1.6453488E-04 0.000000 1.9999960E-02 0.000000 + Av 2018 11 6 3 0 1.6948037E-02 0.000000 0.000000 1.6448395E-04 0.000000 0.000000 0.000000 + Av 2018 11 6 4 0 1.6455041E-02 0.000000 0.000000 1.6443302E-04 0.000000 0.000000 0.000000 + Av 2018 11 6 5 0 1.6619541E-02 0.000000 0.000000 1.6438210E-04 0.000000 0.000000 0.000000 + Av 2018 11 6 6 0 1.6555425E-02 0.000000 0.000000 1.6433120E-04 0.000000 0.000000 0.000000 + Av 2018 11 6 7 0 1.6570803E-02 0.000000 0.000000 1.6428033E-04 0.000000 0.000000 0.000000 Av 2018 11 6 8 0 8.2786530E-03 0.000000 0.000000 0.000000 0.000000 0.000000 1.4102453E-03 Av 2018 11 6 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.2430855E-03 Av 2018 11 6 10 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.3708030E-03 @@ -7456,21 +7456,21 @@ Av 2018 11 6 14 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.3708030E-03 Av 2018 11 6 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.2430855E-03 Av 2018 11 6 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.4102453E-03 - Av 2018 11 6 17 0 1.1127398E-02 0.000000 0.000000 1.6377242E-04 0.000000 0.000000 0.000000 - Av 2018 11 6 18 0 1.8382255E-02 0.000000 0.000000 1.6372171E-04 0.000000 0.000000 0.000000 - Av 2018 11 6 19 0 1.5852788E-02 0.000000 0.000000 1.6367102E-04 0.000000 0.000000 0.000000 - Av 2018 11 6 20 0 1.6725419E-02 0.000000 0.000000 1.6362034E-04 0.000000 0.000000 0.000000 - Av 2018 11 6 21 0 1.6415112E-02 0.000000 0.000000 1.6356968E-04 0.000000 0.000000 0.000000 - Av 2018 11 6 22 0 1.6516127E-02 0.000000 0.000000 1.6351904E-04 0.000000 0.000000 0.000000 - Av 2018 11 6 23 0 1.6474124E-02 0.000000 0.000000 1.6346843E-04 0.000000 0.000000 0.000000 - Av 2018 11 6 24 0 1.6481850E-02 0.000000 0.000000 1.6341780E-04 0.000000 0.000000 0.000000 - Av 2018 11 7 1 0 1.6729837E-02 0.000000 0.000000 1.6309870E-04 0.000000 9.9999802E-03 0.000000 - Av 2018 11 7 2 0 1.6618503E-02 0.000000 0.000000 1.6304829E-04 0.000000 0.000000 0.000000 - Av 2018 11 7 3 0 1.6374571E-02 0.000000 0.000000 1.6299791E-04 0.000000 0.000000 0.000000 - Av 2018 11 7 4 0 1.6452542E-02 0.000000 0.000000 1.6294752E-04 0.000000 0.000000 0.000000 - Av 2018 11 7 5 0 1.6418584E-02 0.000000 0.000000 1.6289714E-04 0.000000 0.000000 0.000000 - Av 2018 11 7 6 0 1.6423548E-02 0.000000 0.000000 1.6284679E-04 0.000000 0.000000 0.000000 - Av 2018 11 7 7 0 1.6414981E-02 0.000000 0.000000 1.6279645E-04 0.000000 0.000000 0.000000 + Av 2018 11 6 17 0 1.1127398E-02 0.000000 0.000000 1.6377242E-04 0.000000 0.000000 0.000000 + Av 2018 11 6 18 0 1.8382255E-02 0.000000 0.000000 1.6372171E-04 0.000000 0.000000 0.000000 + Av 2018 11 6 19 0 1.5852788E-02 0.000000 0.000000 1.6367102E-04 0.000000 0.000000 0.000000 + Av 2018 11 6 20 0 1.6725419E-02 0.000000 0.000000 1.6362034E-04 0.000000 0.000000 0.000000 + Av 2018 11 6 21 0 1.6415112E-02 0.000000 0.000000 1.6356968E-04 0.000000 0.000000 0.000000 + Av 2018 11 6 22 0 1.6516127E-02 0.000000 0.000000 1.6351904E-04 0.000000 0.000000 0.000000 + Av 2018 11 6 23 0 1.6474124E-02 0.000000 0.000000 1.6346843E-04 0.000000 0.000000 0.000000 + Av 2018 11 6 24 0 1.6481850E-02 0.000000 0.000000 1.6341780E-04 0.000000 0.000000 0.000000 + Av 2018 11 7 1 0 1.6729837E-02 0.000000 0.000000 1.6309870E-04 0.000000 9.9999802E-03 0.000000 + Av 2018 11 7 2 0 1.6618503E-02 0.000000 0.000000 1.6304829E-04 0.000000 0.000000 0.000000 + Av 2018 11 7 3 0 1.6374571E-02 0.000000 0.000000 1.6299791E-04 0.000000 0.000000 0.000000 + Av 2018 11 7 4 0 1.6452542E-02 0.000000 0.000000 1.6294752E-04 0.000000 0.000000 0.000000 + Av 2018 11 7 5 0 1.6418584E-02 0.000000 0.000000 1.6289714E-04 0.000000 0.000000 0.000000 + Av 2018 11 7 6 0 1.6423548E-02 0.000000 0.000000 1.6284679E-04 0.000000 0.000000 0.000000 + Av 2018 11 7 7 0 1.6414981E-02 0.000000 0.000000 1.6279645E-04 0.000000 0.000000 0.000000 Av 2018 11 7 8 0 8.2071517E-03 0.000000 0.000000 0.000000 0.000000 0.000000 1.3495007E-03 Av 2018 11 7 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.1538694E-03 Av 2018 11 7 10 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.2834878E-03 @@ -7480,21 +7480,21 @@ Av 2018 11 7 14 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.2834878E-03 Av 2018 11 7 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.1538694E-03 Av 2018 11 7 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.3495007E-03 - Av 2018 11 7 17 0 1.1026944E-02 0.000000 0.000000 1.6229395E-04 0.000000 0.000000 0.000000 - Av 2018 11 7 18 0 1.8216312E-02 0.000000 0.000000 1.6224377E-04 0.000000 0.000000 0.000000 - Av 2018 11 7 19 0 1.5709691E-02 0.000000 0.000000 1.6219362E-04 0.000000 0.000000 0.000000 - Av 2018 11 7 20 0 1.6574452E-02 0.000000 0.000000 1.6214349E-04 0.000000 0.000000 0.000000 - Av 2018 11 7 21 0 1.6266953E-02 0.000000 0.000000 1.6209338E-04 0.000000 0.000000 0.000000 - Av 2018 11 7 22 0 1.6367067E-02 0.000000 0.000000 1.6204329E-04 0.000000 0.000000 0.000000 - Av 2018 11 7 23 0 1.6325450E-02 0.000000 0.000000 1.6199319E-04 0.000000 0.000000 0.000000 - Av 2018 11 7 24 0 1.6333114E-02 0.000000 0.000000 1.6194311E-04 0.000000 0.000000 0.000000 - Av 2018 11 8 1 0 1.6306080E-02 0.000000 0.000000 1.6163454E-04 0.000000 0.000000 0.000000 - Av 2018 11 8 2 0 1.6291123E-02 0.000000 0.000000 1.6158464E-04 0.000000 0.000000 0.000000 - Av 2018 11 8 3 0 1.6289547E-02 0.000000 0.000000 1.6153479E-04 0.000000 0.000000 0.000000 - Av 2018 11 8 4 0 1.6283320E-02 0.000000 0.000000 1.6148493E-04 0.000000 0.000000 0.000000 - Av 2018 11 8 5 0 1.6278714E-02 0.000000 0.000000 1.6143511E-04 0.000000 0.000000 0.000000 - Av 2018 11 8 6 0 1.6273545E-02 0.000000 0.000000 1.6138529E-04 0.000000 0.000000 0.000000 - Av 2018 11 8 7 0 1.6268572E-02 0.000000 0.000000 1.6133547E-04 0.000000 0.000000 0.000000 + Av 2018 11 7 17 0 1.1026944E-02 0.000000 0.000000 1.6229395E-04 0.000000 0.000000 0.000000 + Av 2018 11 7 18 0 1.8216312E-02 0.000000 0.000000 1.6224377E-04 0.000000 0.000000 0.000000 + Av 2018 11 7 19 0 1.5709691E-02 0.000000 0.000000 1.6219362E-04 0.000000 0.000000 0.000000 + Av 2018 11 7 20 0 1.6574452E-02 0.000000 0.000000 1.6214349E-04 0.000000 0.000000 0.000000 + Av 2018 11 7 21 0 1.6266953E-02 0.000000 0.000000 1.6209338E-04 0.000000 0.000000 0.000000 + Av 2018 11 7 22 0 1.6367067E-02 0.000000 0.000000 1.6204329E-04 0.000000 0.000000 0.000000 + Av 2018 11 7 23 0 1.6325450E-02 0.000000 0.000000 1.6199319E-04 0.000000 0.000000 0.000000 + Av 2018 11 7 24 0 1.6333114E-02 0.000000 0.000000 1.6194311E-04 0.000000 0.000000 0.000000 + Av 2018 11 8 1 0 1.6306080E-02 0.000000 0.000000 1.6163454E-04 0.000000 0.000000 0.000000 + Av 2018 11 8 2 0 1.6291123E-02 0.000000 0.000000 1.6158464E-04 0.000000 0.000000 0.000000 + Av 2018 11 8 3 0 1.6289547E-02 0.000000 0.000000 1.6153479E-04 0.000000 0.000000 0.000000 + Av 2018 11 8 4 0 1.6283320E-02 0.000000 0.000000 1.6148493E-04 0.000000 0.000000 0.000000 + Av 2018 11 8 5 0 1.6278714E-02 0.000000 0.000000 1.6143511E-04 0.000000 0.000000 0.000000 + Av 2018 11 8 6 0 1.6273545E-02 0.000000 0.000000 1.6138529E-04 0.000000 0.000000 0.000000 + Av 2018 11 8 7 0 1.6268572E-02 0.000000 0.000000 1.6133547E-04 0.000000 0.000000 0.000000 Av 2018 11 8 8 0 8.1330165E-03 0.000000 0.000000 0.000000 0.000000 0.000000 1.2197548E-03 Av 2018 11 8 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.8982644E-03 Av 2018 11 8 10 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.9668968E-03 @@ -7504,21 +7504,21 @@ Av 2018 11 8 14 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.9668968E-03 Av 2018 11 8 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.8982644E-03 Av 2018 11 8 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.2197548E-03 - Av 2018 11 8 17 0 1.0928040E-02 0.000000 0.000000 1.6083827E-04 0.000000 0.000000 0.000000 - Av 2018 11 8 18 0 1.8052932E-02 0.000000 0.000000 1.6078865E-04 0.000000 0.000000 0.000000 - Av 2018 11 8 19 0 1.5568799E-02 0.000000 0.000000 1.6073901E-04 0.000000 0.000000 0.000000 - Av 2018 11 8 20 0 1.6425811E-02 0.000000 0.000000 1.6068941E-04 0.000000 0.000000 0.000000 - Av 2018 11 8 21 0 1.6121082E-02 0.000000 0.000000 1.6063981E-04 0.000000 0.000000 0.000000 - Av 2018 11 8 22 0 1.6220301E-02 0.000000 0.000000 1.6059024E-04 0.000000 0.000000 0.000000 - Av 2018 11 8 23 0 1.6179066E-02 0.000000 0.000000 1.6054069E-04 0.000000 0.000000 0.000000 - Av 2018 11 8 24 0 1.6186669E-02 0.000000 0.000000 1.6049115E-04 0.000000 0.000000 0.000000 - Av 2018 11 9 1 0 1.6160382E-02 0.000000 0.000000 1.6019269E-04 0.000000 0.000000 0.000000 - Av 2018 11 9 2 0 1.6145891E-02 0.000000 0.000000 1.6014333E-04 0.000000 0.000000 0.000000 - Av 2018 11 9 3 0 1.6144222E-02 0.000000 0.000000 1.6009397E-04 0.000000 0.000000 0.000000 - 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Av 2018 11 9 17 0 1.0830641E-02 0.000000 0.000000 1.5940476E-04 0.000000 0.000000 0.000000 - Av 2018 11 9 18 0 1.7892035E-02 0.000000 0.000000 1.5935565E-04 0.000000 0.000000 0.000000 - Av 2018 11 9 19 0 1.5430052E-02 0.000000 0.000000 1.5930654E-04 0.000000 0.000000 0.000000 - Av 2018 11 9 20 0 1.6279433E-02 0.000000 0.000000 1.5925744E-04 0.000000 0.000000 0.000000 - Av 2018 11 9 21 0 1.5977426E-02 0.000000 0.000000 1.5920837E-04 0.000000 0.000000 0.000000 - Av 2018 11 9 22 0 1.6075769E-02 0.000000 0.000000 1.5915932E-04 0.000000 0.000000 0.000000 - Av 2018 11 9 23 0 1.6034909E-02 0.000000 0.000000 1.5911028E-04 0.000000 0.000000 0.000000 - Av 2018 11 9 24 0 1.6042454E-02 0.000000 0.000000 1.5906127E-04 0.000000 0.000000 0.000000 - Av 2018 11 10 1 0 1.6016886E-02 0.000000 0.000000 1.5877257E-04 0.000000 0.000000 0.000000 - Av 2018 11 10 2 0 1.6002841E-02 0.000000 0.000000 1.5872372E-04 0.000000 0.000000 0.000000 - Av 2018 11 10 3 0 1.6001089E-02 0.000000 0.000000 1.5867488E-04 0.000000 0.000000 0.000000 - 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Av 2018 11 10 17 0 1.0734707E-02 0.000000 0.000000 1.5799281E-04 0.000000 0.000000 0.000000 - Av 2018 11 10 18 0 1.7733557E-02 0.000000 0.000000 1.5794419E-04 0.000000 0.000000 0.000000 - Av 2018 11 10 19 0 1.5293390E-02 0.000000 0.000000 1.5789560E-04 0.000000 0.000000 0.000000 - Av 2018 11 10 20 0 1.6135257E-02 0.000000 0.000000 1.5784703E-04 0.000000 0.000000 0.000000 - Av 2018 11 10 21 0 1.5835933E-02 0.000000 0.000000 1.5779847E-04 0.000000 0.000000 0.000000 - Av 2018 11 10 22 0 1.5933413E-02 0.000000 0.000000 1.5774992E-04 0.000000 0.000000 0.000000 - Av 2018 11 10 23 0 1.5892919E-02 0.000000 0.000000 1.5770138E-04 0.000000 0.000000 0.000000 - Av 2018 11 10 24 0 1.5900405E-02 0.000000 0.000000 1.5765286E-04 0.000000 0.000000 0.000000 - Av 2018 11 11 1 0 1.5875531E-02 0.000000 0.000000 1.5737358E-04 0.000000 0.000000 0.000000 - Av 2018 11 11 2 0 1.5861921E-02 0.000000 0.000000 1.5732524E-04 0.000000 0.000000 0.000000 - Av 2018 11 11 3 0 1.5860084E-02 0.000000 0.000000 1.5727691E-04 0.000000 0.000000 0.000000 - Av 2018 11 11 4 0 1.5854156E-02 0.000000 0.000000 1.5722858E-04 0.000000 0.000000 0.000000 - Av 2018 11 11 5 0 1.5849652E-02 0.000000 0.000000 1.5718029E-04 0.000000 0.000000 0.000000 - Av 2018 11 11 6 0 1.5844654E-02 0.000000 0.000000 1.5713199E-04 0.000000 0.000000 0.000000 - Av 2018 11 11 7 0 1.5839830E-02 0.000000 0.000000 1.5708372E-04 0.000000 0.000000 0.000000 + Av 2018 11 10 17 0 1.0734707E-02 0.000000 0.000000 1.5799281E-04 0.000000 0.000000 0.000000 + Av 2018 11 10 18 0 1.7733557E-02 0.000000 0.000000 1.5794419E-04 0.000000 0.000000 0.000000 + Av 2018 11 10 19 0 1.5293390E-02 0.000000 0.000000 1.5789560E-04 0.000000 0.000000 0.000000 + Av 2018 11 10 20 0 1.6135257E-02 0.000000 0.000000 1.5784703E-04 0.000000 0.000000 0.000000 + Av 2018 11 10 21 0 1.5835933E-02 0.000000 0.000000 1.5779847E-04 0.000000 0.000000 0.000000 + Av 2018 11 10 22 0 1.5933413E-02 0.000000 0.000000 1.5774992E-04 0.000000 0.000000 0.000000 + Av 2018 11 10 23 0 1.5892919E-02 0.000000 0.000000 1.5770138E-04 0.000000 0.000000 0.000000 + Av 2018 11 10 24 0 1.5900405E-02 0.000000 0.000000 1.5765286E-04 0.000000 0.000000 0.000000 + Av 2018 11 11 1 0 1.5875531E-02 0.000000 0.000000 1.5737358E-04 0.000000 0.000000 0.000000 + Av 2018 11 11 2 0 1.5861921E-02 0.000000 0.000000 1.5732524E-04 0.000000 0.000000 0.000000 + Av 2018 11 11 3 0 1.5860084E-02 0.000000 0.000000 1.5727691E-04 0.000000 0.000000 0.000000 + Av 2018 11 11 4 0 1.5854156E-02 0.000000 0.000000 1.5722858E-04 0.000000 0.000000 0.000000 + Av 2018 11 11 5 0 1.5849652E-02 0.000000 0.000000 1.5718029E-04 0.000000 0.000000 0.000000 + Av 2018 11 11 6 0 1.5844654E-02 0.000000 0.000000 1.5713199E-04 0.000000 0.000000 0.000000 + Av 2018 11 11 7 0 1.5839830E-02 0.000000 0.000000 1.5708372E-04 0.000000 0.000000 0.000000 Av 2018 11 11 8 0 7.9186875E-03 0.000000 0.000000 0.000000 0.000000 0.000000 1.1183207E-03 Av 2018 11 11 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.8000849E-03 Av 2018 11 11 10 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.9226883E-03 @@ -7576,21 +7576,21 @@ Av 2018 11 11 14 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.9226883E-03 Av 2018 11 11 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.8000849E-03 Av 2018 11 11 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 9.9999802E-03 1.1183207E-03 - Av 2018 11 11 17 0 1.0640197E-02 0.000000 0.000000 1.5660180E-04 0.000000 0.000000 0.000000 - Av 2018 11 11 18 0 1.7577434E-02 0.000000 0.000000 1.5655371E-04 0.000000 0.000000 0.000000 - Av 2018 11 11 19 0 1.5158758E-02 0.000000 0.000000 1.5650560E-04 0.000000 0.000000 0.000000 - Av 2018 11 11 20 0 1.5993217E-02 0.000000 0.000000 1.5645751E-04 0.000000 0.000000 0.000000 - Av 2018 11 11 21 0 1.5696535E-02 0.000000 0.000000 1.5640944E-04 0.000000 0.000000 0.000000 - Av 2018 11 11 22 0 1.5793163E-02 0.000000 0.000000 1.5636139E-04 0.000000 0.000000 0.000000 - Av 2018 11 11 23 0 1.5753036E-02 0.000000 0.000000 1.5631337E-04 0.000000 0.000000 0.000000 - Av 2018 11 11 24 0 1.5760463E-02 0.000000 0.000000 1.5626533E-04 0.000000 0.000000 0.000000 - Av 2018 11 12 1 0 1.5736258E-02 0.000000 0.000000 1.5599512E-04 0.000000 0.000000 0.000000 - Av 2018 11 12 2 0 1.5723063E-02 0.000000 0.000000 1.5594726E-04 0.000000 0.000000 0.000000 - Av 2018 11 12 3 0 1.5721148E-02 0.000000 0.000000 1.5589943E-04 0.000000 0.000000 0.000000 - Av 2018 11 12 4 0 1.5715312E-02 0.000000 0.000000 1.5585159E-04 0.000000 0.000000 0.000000 - Av 2018 11 12 5 0 1.5710844E-02 0.000000 0.000000 1.5580378E-04 0.000000 0.000000 0.000000 - Av 2018 11 12 6 0 1.5705902E-02 0.000000 0.000000 1.5575599E-04 0.000000 0.000000 0.000000 - Av 2018 11 12 7 0 1.5701126E-02 0.000000 0.000000 1.5570820E-04 0.000000 0.000000 0.000000 + Av 2018 11 11 17 0 1.0640197E-02 0.000000 0.000000 1.5660180E-04 0.000000 0.000000 0.000000 + Av 2018 11 11 18 0 1.7577434E-02 0.000000 0.000000 1.5655371E-04 0.000000 0.000000 0.000000 + Av 2018 11 11 19 0 1.5158758E-02 0.000000 0.000000 1.5650560E-04 0.000000 0.000000 0.000000 + Av 2018 11 11 20 0 1.5993217E-02 0.000000 0.000000 1.5645751E-04 0.000000 0.000000 0.000000 + Av 2018 11 11 21 0 1.5696535E-02 0.000000 0.000000 1.5640944E-04 0.000000 0.000000 0.000000 + Av 2018 11 11 22 0 1.5793163E-02 0.000000 0.000000 1.5636139E-04 0.000000 0.000000 0.000000 + Av 2018 11 11 23 0 1.5753036E-02 0.000000 0.000000 1.5631337E-04 0.000000 0.000000 0.000000 + Av 2018 11 11 24 0 1.5760463E-02 0.000000 0.000000 1.5626533E-04 0.000000 0.000000 0.000000 + Av 2018 11 12 1 0 1.5736258E-02 0.000000 0.000000 1.5599512E-04 0.000000 0.000000 0.000000 + Av 2018 11 12 2 0 1.5723063E-02 0.000000 0.000000 1.5594726E-04 0.000000 0.000000 0.000000 + Av 2018 11 12 3 0 1.5721148E-02 0.000000 0.000000 1.5589943E-04 0.000000 0.000000 0.000000 + Av 2018 11 12 4 0 1.5715312E-02 0.000000 0.000000 1.5585159E-04 0.000000 0.000000 0.000000 + Av 2018 11 12 5 0 1.5710844E-02 0.000000 0.000000 1.5580378E-04 0.000000 0.000000 0.000000 + Av 2018 11 12 6 0 1.5705902E-02 0.000000 0.000000 1.5575599E-04 0.000000 0.000000 0.000000 + Av 2018 11 12 7 0 1.5701126E-02 0.000000 0.000000 1.5570820E-04 0.000000 0.000000 0.000000 Av 2018 11 12 8 0 7.8493468E-03 0.000000 0.000000 0.000000 0.000000 0.000000 1.1576373E-03 Av 2018 11 12 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.9522183E-03 Av 2018 11 12 10 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.1679805E-03 @@ -7600,21 +7600,21 @@ Av 2018 11 12 14 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.1679805E-03 Av 2018 11 12 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.9522183E-03 Av 2018 11 12 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.1576373E-03 - Av 2018 11 12 17 0 1.0547070E-02 0.000000 0.000000 1.5523117E-04 0.000000 0.000000 0.000000 - Av 2018 11 12 18 0 1.7423594E-02 0.000000 0.000000 1.5518356E-04 0.000000 0.000000 0.000000 - Av 2018 11 12 19 0 1.5026094E-02 0.000000 0.000000 1.5513595E-04 0.000000 0.000000 0.000000 - Av 2018 11 12 20 0 1.5853258E-02 0.000000 0.000000 1.5508835E-04 0.000000 0.000000 0.000000 - Av 2018 11 12 21 0 1.5559180E-02 0.000000 0.000000 1.5504076E-04 0.000000 0.000000 0.000000 - Av 2018 11 12 22 0 1.5654968E-02 0.000000 0.000000 1.5499321E-04 0.000000 0.000000 0.000000 - Av 2018 11 12 23 0 1.5615201E-02 0.000000 0.000000 1.5494566E-04 0.000000 0.000000 0.000000 - Av 2018 11 12 24 0 1.5622567E-02 0.000000 0.000000 1.5489812E-04 0.000000 0.000000 0.000000 - Av 2018 11 13 1 0 1.5599010E-02 0.000000 0.000000 1.5463664E-04 0.000000 0.000000 0.000000 - Av 2018 11 13 2 0 1.5586217E-02 0.000000 0.000000 1.5458927E-04 0.000000 0.000000 0.000000 - Av 2018 11 13 3 0 1.5584228E-02 0.000000 0.000000 1.5454191E-04 0.000000 0.000000 0.000000 - 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Av 2018 11 19 17 0 9.9310400E-03 0.000000 0.000000 1.4616449E-04 0.000000 0.000000 0.000000 - Av 2018 11 19 18 0 1.6405949E-02 0.000000 0.000000 1.4612004E-04 0.000000 0.000000 0.000000 - Av 2018 11 19 19 0 1.4148528E-02 0.000000 0.000000 1.4607562E-04 0.000000 0.000000 0.000000 - Av 2018 11 19 20 0 1.4927417E-02 0.000000 0.000000 1.4603121E-04 0.000000 0.000000 0.000000 - Av 2018 11 19 21 0 1.4650555E-02 0.000000 0.000000 1.4598679E-04 0.000000 0.000000 0.000000 - Av 2018 11 19 22 0 1.4740789E-02 0.000000 0.000000 1.4594241E-04 0.000000 0.000000 0.000000 - Av 2018 11 19 23 0 1.4703384E-02 0.000000 0.000000 1.4589803E-04 0.000000 0.000000 0.000000 - Av 2018 11 19 24 0 1.4710359E-02 0.000000 0.000000 1.4585366E-04 0.000000 0.000000 0.000000 - Av 2018 11 20 1 0 1.4690748E-02 0.000000 0.000000 1.4564508E-04 0.000000 0.000000 0.000000 - Av 2018 11 20 2 0 1.4680390E-02 0.000000 0.000000 1.4560085E-04 0.000000 0.000000 0.000000 - Av 2018 11 20 3 0 1.4677981E-02 0.000000 0.000000 1.4555662E-04 0.000000 0.000000 0.000000 - Av 2018 11 20 4 0 1.4672810E-02 0.000000 0.000000 1.4551241E-04 0.000000 0.000000 0.000000 - Av 2018 11 20 5 0 1.4668602E-02 0.000000 0.000000 1.4546822E-04 0.000000 0.000000 0.000000 - Av 2018 11 20 6 0 1.4664060E-02 0.000000 0.000000 1.4542403E-04 0.000000 0.000000 0.000000 - Av 2018 11 20 7 0 1.4659636E-02 0.000000 0.000000 1.4537986E-04 0.000000 0.000000 0.000000 + Av 2018 11 19 17 0 9.9310400E-03 0.000000 0.000000 1.4616449E-04 0.000000 0.000000 0.000000 + Av 2018 11 19 18 0 1.6405949E-02 0.000000 0.000000 1.4612004E-04 0.000000 0.000000 0.000000 + Av 2018 11 19 19 0 1.4148528E-02 0.000000 0.000000 1.4607562E-04 0.000000 0.000000 0.000000 + Av 2018 11 19 20 0 1.4927417E-02 0.000000 0.000000 1.4603121E-04 0.000000 0.000000 0.000000 + Av 2018 11 19 21 0 1.4650555E-02 0.000000 0.000000 1.4598679E-04 0.000000 0.000000 0.000000 + Av 2018 11 19 22 0 1.4740789E-02 0.000000 0.000000 1.4594241E-04 0.000000 0.000000 0.000000 + Av 2018 11 19 23 0 1.4703384E-02 0.000000 0.000000 1.4589803E-04 0.000000 0.000000 0.000000 + Av 2018 11 19 24 0 1.4710359E-02 0.000000 0.000000 1.4585366E-04 0.000000 0.000000 0.000000 + Av 2018 11 20 1 0 1.4690748E-02 0.000000 0.000000 1.4564508E-04 0.000000 0.000000 0.000000 + Av 2018 11 20 2 0 1.4680390E-02 0.000000 0.000000 1.4560085E-04 0.000000 0.000000 0.000000 + Av 2018 11 20 3 0 1.4677981E-02 0.000000 0.000000 1.4555662E-04 0.000000 0.000000 0.000000 + Av 2018 11 20 4 0 1.4672810E-02 0.000000 0.000000 1.4551241E-04 0.000000 0.000000 0.000000 + Av 2018 11 20 5 0 1.4668602E-02 0.000000 0.000000 1.4546822E-04 0.000000 0.000000 0.000000 + Av 2018 11 20 6 0 1.4664060E-02 0.000000 0.000000 1.4542403E-04 0.000000 0.000000 0.000000 + Av 2018 11 20 7 0 1.4659636E-02 0.000000 0.000000 1.4537986E-04 0.000000 0.000000 0.000000 Av 2018 11 20 8 0 7.3286970E-03 0.000000 0.000000 0.000000 0.000000 0.000000 9.5773605E-04 Av 2018 11 20 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.8746943E-03 Av 2018 11 20 10 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.3127844E-03 @@ -7792,21 +7792,21 @@ Av 2018 11 20 14 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.3127844E-03 Av 2018 11 20 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.8746943E-03 Av 2018 11 20 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 9.5773605E-04 - Av 2018 11 20 17 0 9.8477686E-03 0.000000 0.000000 1.4493891E-04 0.000000 0.000000 0.000000 - Av 2018 11 20 18 0 1.6268391E-02 0.000000 0.000000 1.4489489E-04 0.000000 0.000000 0.000000 - Av 2018 11 20 19 0 1.4029903E-02 0.000000 0.000000 1.4485088E-04 0.000000 0.000000 0.000000 - Av 2018 11 20 20 0 1.4802266E-02 0.000000 0.000000 1.4480689E-04 0.000000 0.000000 0.000000 - Av 2018 11 20 21 0 1.4527732E-02 0.000000 0.000000 1.4476292E-04 0.000000 0.000000 0.000000 - Av 2018 11 20 22 0 1.4617214E-02 0.000000 0.000000 1.4471894E-04 0.000000 0.000000 0.000000 - Av 2018 11 20 23 0 1.4580127E-02 0.000000 0.000000 1.4467500E-04 0.000000 0.000000 0.000000 - Av 2018 11 20 24 0 1.4587051E-02 0.000000 0.000000 1.4463106E-04 0.000000 0.000000 0.000000 - Av 2018 11 21 1 0 1.4567927E-02 0.000000 0.000000 1.4442898E-04 0.000000 0.000000 0.000000 - Av 2018 11 21 2 0 1.4557870E-02 0.000000 0.000000 1.4438517E-04 0.000000 0.000000 0.000000 - Av 2018 11 21 3 0 1.4555413E-02 0.000000 0.000000 1.4434136E-04 0.000000 0.000000 0.000000 - Av 2018 11 21 4 0 1.4550315E-02 0.000000 0.000000 1.4429756E-04 0.000000 0.000000 0.000000 - Av 2018 11 21 5 0 1.4546138E-02 0.000000 0.000000 1.4425379E-04 0.000000 0.000000 0.000000 - Av 2018 11 21 6 0 1.4541643E-02 0.000000 0.000000 1.4421003E-04 0.000000 0.000000 0.000000 - Av 2018 11 21 7 0 1.4537260E-02 0.000000 0.000000 1.4416628E-04 0.000000 0.000000 0.000000 + Av 2018 11 20 17 0 9.8477686E-03 0.000000 0.000000 1.4493891E-04 0.000000 0.000000 0.000000 + Av 2018 11 20 18 0 1.6268391E-02 0.000000 0.000000 1.4489489E-04 0.000000 0.000000 0.000000 + Av 2018 11 20 19 0 1.4029903E-02 0.000000 0.000000 1.4485088E-04 0.000000 0.000000 0.000000 + Av 2018 11 20 20 0 1.4802266E-02 0.000000 0.000000 1.4480689E-04 0.000000 0.000000 0.000000 + Av 2018 11 20 21 0 1.4527732E-02 0.000000 0.000000 1.4476292E-04 0.000000 0.000000 0.000000 + Av 2018 11 20 22 0 1.4617214E-02 0.000000 0.000000 1.4471894E-04 0.000000 0.000000 0.000000 + Av 2018 11 20 23 0 1.4580127E-02 0.000000 0.000000 1.4467500E-04 0.000000 0.000000 0.000000 + Av 2018 11 20 24 0 1.4587051E-02 0.000000 0.000000 1.4463106E-04 0.000000 0.000000 0.000000 + Av 2018 11 21 1 0 1.4567927E-02 0.000000 0.000000 1.4442898E-04 0.000000 0.000000 0.000000 + Av 2018 11 21 2 0 1.4557870E-02 0.000000 0.000000 1.4438517E-04 0.000000 0.000000 0.000000 + Av 2018 11 21 3 0 1.4555413E-02 0.000000 0.000000 1.4434136E-04 0.000000 0.000000 0.000000 + Av 2018 11 21 4 0 1.4550315E-02 0.000000 0.000000 1.4429756E-04 0.000000 0.000000 0.000000 + Av 2018 11 21 5 0 1.4546138E-02 0.000000 0.000000 1.4425379E-04 0.000000 0.000000 0.000000 + Av 2018 11 21 6 0 1.4541643E-02 0.000000 0.000000 1.4421003E-04 0.000000 0.000000 0.000000 + Av 2018 11 21 7 0 1.4537260E-02 0.000000 0.000000 1.4416628E-04 0.000000 0.000000 0.000000 Av 2018 11 21 8 0 7.2675198E-03 0.000000 0.000000 0.000000 0.000000 0.000000 8.7512069E-04 Av 2018 11 21 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.6858472E-03 Av 2018 11 21 10 0 0.000000 0.000000 0.000000 0.000000 0.000000 9.9999802E-03 4.0590134E-03 @@ -7816,21 +7816,21 @@ Av 2018 11 21 14 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.0590134E-03 Av 2018 11 21 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.6858472E-03 Av 2018 11 21 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 8.7512069E-04 - Av 2018 11 21 17 0 9.7655952E-03 0.000000 0.000000 1.4372948E-04 0.000000 0.000000 0.000000 - Av 2018 11 21 18 0 1.6132643E-02 0.000000 0.000000 1.4368587E-04 0.000000 0.000000 0.000000 - Av 2018 11 21 19 0 1.3912840E-02 0.000000 0.000000 1.4364229E-04 0.000000 0.000000 0.000000 - Av 2018 11 21 20 0 1.4678763E-02 0.000000 0.000000 1.4359871E-04 0.000000 0.000000 0.000000 - Av 2018 11 21 21 0 1.4406523E-02 0.000000 0.000000 1.4355514E-04 0.000000 0.000000 0.000000 - Av 2018 11 21 22 0 1.4495265E-02 0.000000 0.000000 1.4351158E-04 0.000000 0.000000 0.000000 - Av 2018 11 21 23 0 1.4458492E-02 0.000000 0.000000 1.4346806E-04 0.000000 0.000000 0.000000 - Av 2018 11 21 24 0 1.5500060E-02 0.000000 0.000000 1.4342843E-04 0.000000 3.9999921E-02 0.000000 - Av 2018 11 22 1 0 8.5260369E-02 3.6001123E-07 0.000000 1.4370031E-04 1.0070716E-02 5.9999879E-02 0.000000 - Av 2018 11 22 2 0 0.2412328 9.3824390E-08 0.000000 1.4493689E-04 2.6290035E-02 2.9999940E-02 0.000000 - Av 2018 11 22 3 0 0.1642357 0.000000 0.000000 1.4541642E-04 5.9408727E-03 0.000000 0.000000 - Av 2018 11 22 4 0 2.2799375E-02 0.000000 0.000000 1.4537213E-04 1.9018777E-03 0.000000 0.000000 - Av 2018 11 22 5 0 3.0130792E-02 0.000000 0.000000 1.4532785E-04 7.9252705E-04 0.000000 0.000000 - Av 2018 11 22 6 0 1.7327134E-02 0.000000 0.000000 1.4528360E-04 3.9351758E-04 0.000000 0.000000 - Av 2018 11 22 7 0 1.7888717E-02 0.000000 0.000000 1.4523935E-04 2.2083061E-04 0.000000 0.000000 + Av 2018 11 21 17 0 9.7655952E-03 0.000000 0.000000 1.4372948E-04 0.000000 0.000000 0.000000 + Av 2018 11 21 18 0 1.6132643E-02 0.000000 0.000000 1.4368587E-04 0.000000 0.000000 0.000000 + Av 2018 11 21 19 0 1.3912840E-02 0.000000 0.000000 1.4364229E-04 0.000000 0.000000 0.000000 + Av 2018 11 21 20 0 1.4678763E-02 0.000000 0.000000 1.4359871E-04 0.000000 0.000000 0.000000 + Av 2018 11 21 21 0 1.4406523E-02 0.000000 0.000000 1.4355514E-04 0.000000 0.000000 0.000000 + Av 2018 11 21 22 0 1.4495265E-02 0.000000 0.000000 1.4351158E-04 0.000000 0.000000 0.000000 + Av 2018 11 21 23 0 1.4458492E-02 0.000000 0.000000 1.4346806E-04 0.000000 0.000000 0.000000 + Av 2018 11 21 24 0 1.5500060E-02 0.000000 0.000000 1.4342843E-04 0.000000 3.9999921E-02 0.000000 + Av 2018 11 22 1 0 8.5260369E-02 3.6001123E-07 0.000000 1.4370031E-04 1.0070716E-02 5.9999879E-02 0.000000 + Av 2018 11 22 2 0 0.2412328 9.3824390E-08 0.000000 1.4493689E-04 2.6290035E-02 2.9999940E-02 0.000000 + Av 2018 11 22 3 0 0.1642357 0.000000 0.000000 1.4541642E-04 5.9408727E-03 0.000000 0.000000 + Av 2018 11 22 4 0 2.2799375E-02 0.000000 0.000000 1.4537213E-04 1.9018777E-03 0.000000 0.000000 + Av 2018 11 22 5 0 3.0130792E-02 0.000000 0.000000 1.4532785E-04 7.9252705E-04 0.000000 0.000000 + Av 2018 11 22 6 0 1.7327134E-02 0.000000 0.000000 1.4528360E-04 3.9351758E-04 0.000000 0.000000 + Av 2018 11 22 7 0 1.7888717E-02 0.000000 0.000000 1.4523935E-04 2.2083061E-04 0.000000 0.000000 Av 2018 11 22 8 0 7.8929998E-03 0.000000 0.000000 0.000000 1.3546541E-04 0.000000 8.3965313E-04 Av 2018 11 22 9 0 6.0378673E-04 0.000000 0.000000 0.000000 8.8864996E-05 0.000000 2.6359579E-03 Av 2018 11 22 10 0 7.7407283E-04 0.000000 0.000000 0.000000 6.1407394E-05 0.000000 4.0124361E-03 @@ -7840,21 +7840,21 @@ Av 2018 11 22 14 0 0.7573099 3.9869758E-07 0.000000 0.000000 5.5740803E-02 4.9999900E-02 4.0124361E-03 Av 2018 11 22 15 0 0.2792675 5.0696897E-08 0.000000 0.000000 2.2226937E-02 1.9999960E-02 2.6359579E-03 Av 2018 11 22 16 0 0.1822766 6.0288194E-08 0.000000 0.000000 1.8297786E-02 1.9999960E-02 8.3965313E-04 - Av 2018 11 22 17 0 0.1496724 1.7226615E-08 0.000000 1.5560084E-04 1.1111343E-02 9.9999802E-03 0.000000 - Av 2018 11 22 18 0 0.1159796 1.9949676E-08 0.000000 1.5584857E-04 1.0260871E-02 9.9999802E-03 0.000000 - Av 2018 11 22 19 0 0.1727179 8.0226464E-08 0.000000 1.5620868E-04 1.7646585E-02 1.9999960E-02 0.000000 - Av 2018 11 22 20 0 0.1128772 0.000000 0.000000 1.5658056E-04 4.4535645E-03 0.000000 0.000000 - Av 2018 11 22 21 0 6.8566754E-02 2.0305267E-08 0.000000 1.5663114E-04 8.2593532E-03 9.9999802E-03 0.000000 - Av 2018 11 22 22 0 0.2845231 3.2662649E-07 0.000000 1.5718394E-04 3.3501454E-02 3.9999921E-02 0.000000 - Av 2018 11 22 23 0 0.2184856 0.000000 0.000000 1.5796635E-04 7.1704118E-03 0.000000 0.000000 - Av 2018 11 22 24 0 2.5607180E-02 0.000000 0.000000 1.5791687E-04 2.1896819E-03 0.000000 0.000000 - Av 2018 11 23 1 0 3.3422329E-02 0.000000 0.000000 1.5756288E-04 8.8506332E-04 0.000000 0.000000 - Av 2018 11 23 2 0 1.8725544E-02 0.000000 0.000000 1.5752930E-04 4.3043788E-04 0.000000 0.000000 - Av 2018 11 23 3 0 0.1114479 8.4263739E-08 0.000000 1.5769881E-04 1.3682608E-02 1.9999960E-02 0.000000 - Av 2018 11 23 4 0 0.2089442 8.5297117E-08 0.000000 1.5833348E-04 1.9232217E-02 1.9999960E-02 0.000000 - Av 2018 11 23 5 0 0.1126831 0.000000 0.000000 1.5874911E-04 4.5896852E-03 0.000000 0.000000 - Av 2018 11 23 6 0 0.2316990 3.4534955E-07 0.000000 1.5913237E-04 3.1978473E-02 3.9999921E-02 0.000000 - Av 2018 11 23 7 0 0.2274226 0.000000 0.000000 1.6000133E-04 7.0537855E-03 0.000000 0.000000 + Av 2018 11 22 17 0 0.1496724 1.7226615E-08 0.000000 1.5560084E-04 1.1111343E-02 9.9999802E-03 0.000000 + Av 2018 11 22 18 0 0.1159796 1.9949676E-08 0.000000 1.5584857E-04 1.0260871E-02 9.9999802E-03 0.000000 + Av 2018 11 22 19 0 0.1727179 8.0226464E-08 0.000000 1.5620868E-04 1.7646585E-02 1.9999960E-02 0.000000 + Av 2018 11 22 20 0 0.1128772 0.000000 0.000000 1.5658056E-04 4.4535645E-03 0.000000 0.000000 + Av 2018 11 22 21 0 6.8566754E-02 2.0305267E-08 0.000000 1.5663114E-04 8.2593532E-03 9.9999802E-03 0.000000 + Av 2018 11 22 22 0 0.2845231 3.2662649E-07 0.000000 1.5718394E-04 3.3501454E-02 3.9999921E-02 0.000000 + Av 2018 11 22 23 0 0.2184856 0.000000 0.000000 1.5796635E-04 7.1704118E-03 0.000000 0.000000 + Av 2018 11 22 24 0 2.5607180E-02 0.000000 0.000000 1.5791687E-04 2.1896819E-03 0.000000 0.000000 + Av 2018 11 23 1 0 3.3422329E-02 0.000000 0.000000 1.5756288E-04 8.8506332E-04 0.000000 0.000000 + Av 2018 11 23 2 0 1.8725544E-02 0.000000 0.000000 1.5752930E-04 4.3043788E-04 0.000000 0.000000 + Av 2018 11 23 3 0 0.1114479 8.4263739E-08 0.000000 1.5769881E-04 1.3682608E-02 1.9999960E-02 0.000000 + Av 2018 11 23 4 0 0.2089442 8.5297117E-08 0.000000 1.5833348E-04 1.9232217E-02 1.9999960E-02 0.000000 + Av 2018 11 23 5 0 0.1126831 0.000000 0.000000 1.5874911E-04 4.5896852E-03 0.000000 0.000000 + Av 2018 11 23 6 0 0.2316990 3.4534955E-07 0.000000 1.5913237E-04 3.1978473E-02 3.9999921E-02 0.000000 + Av 2018 11 23 7 0 0.2274226 0.000000 0.000000 1.6000133E-04 7.0537855E-03 0.000000 0.000000 Av 2018 11 23 8 0 6.2074367E-02 2.2261696E-08 0.000000 0.000000 9.1358479E-03 9.9999802E-03 7.3481706E-04 Av 2018 11 23 9 0 0.2677757 3.4784597E-07 0.000000 0.000000 3.3028983E-02 3.9999921E-02 2.3604142E-03 Av 2018 11 23 10 0 0.9363263 3.7673485E-06 0.000000 0.000000 0.1154596 0.1299997 3.6186029E-03 @@ -7864,21 +7864,21 @@ Av 2018 11 23 14 0 0.1771685 0.000000 0.000000 0.000000 7.3873391E-03 0.000000 3.6186029E-03 Av 2018 11 23 15 0 1.5212168E-02 0.000000 0.000000 0.000000 2.2389183E-03 0.000000 2.3604142E-03 Av 2018 11 23 16 0 1.6657054E-02 0.000000 0.000000 9.4658753E-06 9.0057106E-04 0.000000 7.3481706E-04 - Av 2018 11 23 17 0 1.5531771E-02 0.000000 0.000000 1.7107060E-04 4.3653671E-04 0.000000 0.000000 - Av 2018 11 23 18 0 2.2808433E-02 0.000000 0.000000 1.7102018E-04 2.4081113E-04 9.9999802E-03 0.000000 - Av 2018 11 23 19 0 1.8296789E-02 0.000000 0.000000 1.7097467E-04 1.4586220E-04 0.000000 0.000000 - Av 2018 11 23 20 0 1.8502725E-02 0.000000 0.000000 1.7091969E-04 9.4763920E-05 0.000000 0.000000 - Av 2018 11 23 21 0 1.7874159E-02 0.000000 0.000000 1.7086472E-04 6.4988744E-05 0.000000 0.000000 - Av 2018 11 23 22 0 1.7757449E-02 0.000000 0.000000 1.7080976E-04 4.6518628E-05 0.000000 0.000000 - Av 2018 11 23 23 0 1.7583206E-02 0.000000 0.000000 1.7075482E-04 3.4470057E-05 0.000000 0.000000 - Av 2018 11 23 24 0 1.8509096E-02 0.000000 0.000000 1.7069990E-04 1.7497211E-04 0.000000 0.000000 - Av 2018 11 24 1 0 1.7914765E-02 1.4089217E-10 0.000000 1.7019262E-04 0.000000 0.000000 0.000000 - Av 2018 11 24 2 0 1.6895661E-02 0.000000 0.000000 1.7015649E-04 0.000000 0.000000 0.000000 - Av 2018 11 24 3 0 1.7243840E-02 0.000000 0.000000 1.7010191E-04 0.000000 0.000000 0.000000 - Av 2018 11 24 4 0 1.7115358E-02 0.000000 0.000000 1.7004734E-04 0.000000 0.000000 0.000000 - Av 2018 11 24 5 0 1.7152619E-02 0.000000 0.000000 1.6999280E-04 0.000000 0.000000 0.000000 - Av 2018 11 24 6 0 1.7132252E-02 0.000000 0.000000 1.6993827E-04 0.000000 0.000000 0.000000 - Av 2018 11 24 7 0 1.7131925E-02 0.000000 0.000000 1.6988376E-04 0.000000 0.000000 0.000000 + Av 2018 11 23 17 0 1.5531771E-02 0.000000 0.000000 1.7107060E-04 4.3653671E-04 0.000000 0.000000 + Av 2018 11 23 18 0 2.2808433E-02 0.000000 0.000000 1.7102018E-04 2.4081113E-04 9.9999802E-03 0.000000 + Av 2018 11 23 19 0 1.8296789E-02 0.000000 0.000000 1.7097467E-04 1.4586220E-04 0.000000 0.000000 + Av 2018 11 23 20 0 1.8502725E-02 0.000000 0.000000 1.7091969E-04 9.4763920E-05 0.000000 0.000000 + Av 2018 11 23 21 0 1.7874159E-02 0.000000 0.000000 1.7086472E-04 6.4988744E-05 0.000000 0.000000 + Av 2018 11 23 22 0 1.7757449E-02 0.000000 0.000000 1.7080976E-04 4.6518628E-05 0.000000 0.000000 + Av 2018 11 23 23 0 1.7583206E-02 0.000000 0.000000 1.7075482E-04 3.4470057E-05 0.000000 0.000000 + Av 2018 11 23 24 0 1.8509096E-02 0.000000 0.000000 1.7069990E-04 1.7497211E-04 0.000000 0.000000 + Av 2018 11 24 1 0 1.7914765E-02 1.4089217E-10 0.000000 1.7019262E-04 0.000000 0.000000 0.000000 + Av 2018 11 24 2 0 1.6895661E-02 0.000000 0.000000 1.7015649E-04 0.000000 0.000000 0.000000 + Av 2018 11 24 3 0 1.7243840E-02 0.000000 0.000000 1.7010191E-04 0.000000 0.000000 0.000000 + Av 2018 11 24 4 0 1.7115358E-02 0.000000 0.000000 1.7004734E-04 0.000000 0.000000 0.000000 + Av 2018 11 24 5 0 1.7152619E-02 0.000000 0.000000 1.6999280E-04 0.000000 0.000000 0.000000 + Av 2018 11 24 6 0 1.7132252E-02 0.000000 0.000000 1.6993827E-04 0.000000 0.000000 0.000000 + Av 2018 11 24 7 0 1.7131925E-02 0.000000 0.000000 1.6988376E-04 0.000000 0.000000 0.000000 Av 2018 11 24 8 0 8.5632103E-03 0.000000 0.000000 5.6397694E-06 0.000000 0.000000 7.4631593E-04 Av 2018 11 24 9 0 3.2994352E-02 2.8125259E-08 0.000000 0.000000 4.8558093E-03 9.9999802E-03 2.4537633E-03 Av 2018 11 24 10 0 3.5182178E-02 0.000000 0.000000 0.000000 2.0412842E-03 0.000000 3.7880528E-03 @@ -7888,21 +7888,21 @@ Av 2018 11 24 14 0 1.6657654E-03 0.000000 0.000000 0.000000 1.3990280E-04 0.000000 3.7880528E-03 Av 2018 11 24 15 0 9.2783291E-04 0.000000 0.000000 0.000000 9.1391557E-05 0.000000 2.4537633E-03 Av 2018 11 24 16 0 1.0776691E-03 0.000000 0.000000 5.5873534E-06 6.2945597E-05 0.000000 7.4631593E-04 - Av 2018 11 24 17 0 1.2265104E-02 0.000000 0.000000 1.6972238E-04 4.5211375E-05 0.000000 0.000000 - Av 2018 11 24 18 0 1.9330390E-02 0.000000 0.000000 1.6966791E-04 3.3595614E-05 0.000000 0.000000 - Av 2018 11 24 19 0 1.7729789E-02 0.000000 0.000000 1.6961343E-04 1.7229574E-04 0.000000 0.000000 - Av 2018 11 24 20 0 1.8050669E-02 0.000000 0.000000 1.6955899E-04 0.000000 0.000000 0.000000 - Av 2018 11 24 21 0 1.6761050E-02 0.000000 0.000000 1.6950455E-04 0.000000 0.000000 0.000000 - Av 2018 11 24 22 0 1.7202064E-02 0.000000 0.000000 1.6945014E-04 0.000000 0.000000 0.000000 - Av 2018 11 24 23 0 1.7041327E-02 0.000000 0.000000 1.6939575E-04 0.000000 0.000000 0.000000 - Av 2018 11 24 24 0 1.7089827E-02 0.000000 0.000000 1.6934137E-04 0.000000 0.000000 0.000000 - Av 2018 11 25 1 0 1.7035101E-02 0.000000 0.000000 1.6883851E-04 0.000000 0.000000 0.000000 - Av 2018 11 25 2 0 1.7016292E-02 0.000000 0.000000 1.6878445E-04 0.000000 0.000000 0.000000 - Av 2018 11 25 3 0 1.7015487E-02 0.000000 0.000000 1.6873042E-04 0.000000 0.000000 0.000000 - Av 2018 11 25 4 0 1.7008426E-02 0.000000 0.000000 1.6867640E-04 0.000000 0.000000 0.000000 - Av 2018 11 25 5 0 1.7003540E-02 0.000000 0.000000 1.6862238E-04 0.000000 0.000000 0.000000 - Av 2018 11 25 6 0 1.6997902E-02 0.000000 0.000000 1.6856841E-04 0.000000 0.000000 0.000000 - Av 2018 11 25 7 0 1.6992528E-02 0.000000 0.000000 1.6851444E-04 0.000000 0.000000 0.000000 + Av 2018 11 24 17 0 1.2265104E-02 0.000000 0.000000 1.6972238E-04 4.5211375E-05 0.000000 0.000000 + Av 2018 11 24 18 0 1.9330390E-02 0.000000 0.000000 1.6966791E-04 3.3595614E-05 0.000000 0.000000 + Av 2018 11 24 19 0 1.7729789E-02 0.000000 0.000000 1.6961343E-04 1.7229574E-04 0.000000 0.000000 + Av 2018 11 24 20 0 1.8050669E-02 0.000000 0.000000 1.6955899E-04 0.000000 0.000000 0.000000 + Av 2018 11 24 21 0 1.6761050E-02 0.000000 0.000000 1.6950455E-04 0.000000 0.000000 0.000000 + Av 2018 11 24 22 0 1.7202064E-02 0.000000 0.000000 1.6945014E-04 0.000000 0.000000 0.000000 + Av 2018 11 24 23 0 1.7041327E-02 0.000000 0.000000 1.6939575E-04 0.000000 0.000000 0.000000 + Av 2018 11 24 24 0 1.7089827E-02 0.000000 0.000000 1.6934137E-04 0.000000 0.000000 0.000000 + Av 2018 11 25 1 0 1.7035101E-02 0.000000 0.000000 1.6883851E-04 0.000000 0.000000 0.000000 + Av 2018 11 25 2 0 1.7016292E-02 0.000000 0.000000 1.6878445E-04 0.000000 0.000000 0.000000 + Av 2018 11 25 3 0 1.7015487E-02 0.000000 0.000000 1.6873042E-04 0.000000 0.000000 0.000000 + Av 2018 11 25 4 0 1.7008426E-02 0.000000 0.000000 1.6867640E-04 0.000000 0.000000 0.000000 + Av 2018 11 25 5 0 1.7003540E-02 0.000000 0.000000 1.6862238E-04 0.000000 0.000000 0.000000 + Av 2018 11 25 6 0 1.6997902E-02 0.000000 0.000000 1.6856841E-04 0.000000 0.000000 0.000000 + Av 2018 11 25 7 0 1.6992528E-02 0.000000 0.000000 1.6851444E-04 0.000000 0.000000 0.000000 Av 2018 11 25 8 0 8.4948856E-03 0.000000 0.000000 1.4694306E-05 0.000000 0.000000 6.9893722E-04 Av 2018 11 25 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.3526780E-03 Av 2018 11 25 10 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.6569501E-03 @@ -7912,21 +7912,21 @@ Av 2018 11 25 14 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.6569501E-03 Av 2018 11 25 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.3526780E-03 Av 2018 11 25 16 0 9.6911209E-04 0.000000 0.000000 1.4263336E-05 0.000000 0.000000 6.9893722E-04 - Av 2018 11 25 17 0 1.2045133E-02 0.000000 0.000000 1.6797574E-04 0.000000 0.000000 0.000000 - Av 2018 11 25 18 0 1.8634126E-02 0.000000 0.000000 1.6792196E-04 0.000000 0.000000 0.000000 - Av 2018 11 25 19 0 1.6335769E-02 0.000000 0.000000 1.6786820E-04 0.000000 0.000000 0.000000 - Av 2018 11 25 20 0 1.7127626E-02 0.000000 0.000000 1.6781448E-04 0.000000 0.000000 0.000000 - Av 2018 11 25 21 0 1.6844988E-02 0.000000 0.000000 1.6776075E-04 0.000000 0.000000 0.000000 - Av 2018 11 25 22 0 1.6935963E-02 0.000000 0.000000 1.6770704E-04 0.000000 0.000000 0.000000 - Av 2018 11 25 23 0 1.6897034E-02 0.000000 0.000000 1.6765334E-04 0.000000 0.000000 0.000000 - Av 2018 11 25 24 0 1.6903274E-02 0.000000 0.000000 1.6759966E-04 0.000000 0.000000 0.000000 - Av 2018 11 26 1 0 1.6864479E-02 0.000000 0.000000 1.6711430E-04 0.000000 0.000000 0.000000 - Av 2018 11 26 2 0 1.6841365E-02 0.000000 0.000000 1.6706093E-04 0.000000 0.000000 0.000000 - Av 2018 11 26 3 0 1.6842153E-02 0.000000 0.000000 1.6700759E-04 0.000000 0.000000 0.000000 - Av 2018 11 26 4 0 1.6834630E-02 0.000000 0.000000 1.6695425E-04 0.000000 0.000000 0.000000 - Av 2018 11 26 5 0 1.6829997E-02 0.000000 0.000000 1.6690094E-04 0.000000 0.000000 0.000000 - Av 2018 11 26 6 0 1.6824365E-02 0.000000 0.000000 1.6684765E-04 0.000000 0.000000 0.000000 - Av 2018 11 26 7 0 1.6819084E-02 0.000000 0.000000 1.6679437E-04 0.000000 0.000000 0.000000 + Av 2018 11 25 17 0 1.2045133E-02 0.000000 0.000000 1.6797574E-04 0.000000 0.000000 0.000000 + Av 2018 11 25 18 0 1.8634126E-02 0.000000 0.000000 1.6792196E-04 0.000000 0.000000 0.000000 + Av 2018 11 25 19 0 1.6335769E-02 0.000000 0.000000 1.6786820E-04 0.000000 0.000000 0.000000 + Av 2018 11 25 20 0 1.7127626E-02 0.000000 0.000000 1.6781448E-04 0.000000 0.000000 0.000000 + Av 2018 11 25 21 0 1.6844988E-02 0.000000 0.000000 1.6776075E-04 0.000000 0.000000 0.000000 + Av 2018 11 25 22 0 1.6935963E-02 0.000000 0.000000 1.6770704E-04 0.000000 0.000000 0.000000 + Av 2018 11 25 23 0 1.6897034E-02 0.000000 0.000000 1.6765334E-04 0.000000 0.000000 0.000000 + Av 2018 11 25 24 0 1.6903274E-02 0.000000 0.000000 1.6759966E-04 0.000000 0.000000 0.000000 + Av 2018 11 26 1 0 1.6864479E-02 0.000000 0.000000 1.6711430E-04 0.000000 0.000000 0.000000 + Av 2018 11 26 2 0 1.6841365E-02 0.000000 0.000000 1.6706093E-04 0.000000 0.000000 0.000000 + Av 2018 11 26 3 0 1.6842153E-02 0.000000 0.000000 1.6700759E-04 0.000000 0.000000 0.000000 + Av 2018 11 26 4 0 1.6834630E-02 0.000000 0.000000 1.6695425E-04 0.000000 0.000000 0.000000 + Av 2018 11 26 5 0 1.6829997E-02 0.000000 0.000000 1.6690094E-04 0.000000 0.000000 0.000000 + Av 2018 11 26 6 0 1.6824365E-02 0.000000 0.000000 1.6684765E-04 0.000000 0.000000 0.000000 + Av 2018 11 26 7 0 1.6819084E-02 0.000000 0.000000 1.6679437E-04 0.000000 0.000000 0.000000 Av 2018 11 26 8 0 8.4081749E-03 0.000000 0.000000 0.000000 0.000000 0.000000 8.2954630E-04 Av 2018 11 26 9 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.8593866E-03 Av 2018 11 26 10 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.4744536E-03 @@ -7936,21 +7936,21 @@ Av 2018 11 26 14 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.4744536E-03 Av 2018 11 26 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 9.9999802E-03 2.8593866E-03 Av 2018 11 26 16 0 0.000000 0.000000 0.000000 0.000000 0.000000 9.9999802E-03 8.2954630E-04 - Av 2018 11 26 17 0 1.1296587E-02 0.000000 0.000000 1.6626253E-04 0.000000 0.000000 0.000000 - Av 2018 11 26 18 0 1.8989488E-02 0.000000 0.000000 1.6620946E-04 0.000000 9.9999802E-03 0.000000 - Av 2018 11 26 19 0 1.7107144E-02 0.000000 0.000000 1.6615637E-04 0.000000 2.9999940E-02 0.000000 - Av 2018 11 26 20 0 1.9945383E-02 1.5334757E-08 0.000000 1.6619399E-04 3.2524558E-04 9.9999802E-03 0.000000 - Av 2018 11 26 21 0 0.1126539 1.2778949E-07 0.000000 1.6658979E-04 1.3808695E-02 1.9999960E-02 0.000000 - Av 2018 11 26 22 0 0.3806681 8.0768706E-07 0.000000 1.6777488E-04 4.3821260E-02 4.9999900E-02 0.000000 - Av 2018 11 26 23 0 0.4197968 3.0292907E-07 0.000000 1.6961148E-04 3.2637049E-02 2.9999940E-02 0.000000 - Av 2018 11 26 24 0 0.2013284 3.4312976E-08 0.000000 1.7059836E-04 1.4196324E-02 9.9999802E-03 0.000000 - Av 2018 11 27 1 0 0.6455536 3.4932873E-06 0.000000 1.7168239E-04 8.6397059E-02 9.9999800E-02 0.000000 - Av 2018 11 27 2 0 1.217804 5.6344506E-06 0.000000 1.7619258E-04 0.1171034 0.1199998 0.000000 - Av 2018 11 27 3 0 0.6323277 4.6247120E-08 0.000000 1.7993308E-04 2.4082184E-02 9.9999802E-03 0.000000 - Av 2018 11 27 4 0 0.4373095 2.2758068E-06 0.000000 1.8130837E-04 6.2527128E-02 6.9999859E-02 0.000000 - Av 2018 11 27 5 0 1.218283 9.7299890E-06 2.4935235E-07 1.8572368E-04 0.1312269 0.1399997 0.000000 - Av 2018 11 27 6 0 0.8200459 5.5201167E-07 5.0812162E-07 1.9078926E-04 4.2613685E-02 2.9999940E-02 0.000000 - Av 2018 11 27 7 0 9.2582047E-02 0.000000 5.1488405E-07 1.9183820E-04 7.9515027E-03 0.000000 0.000000 + Av 2018 11 26 17 0 1.1296587E-02 0.000000 0.000000 1.6626253E-04 0.000000 0.000000 0.000000 + Av 2018 11 26 18 0 1.8989488E-02 0.000000 0.000000 1.6620946E-04 0.000000 9.9999802E-03 0.000000 + Av 2018 11 26 19 0 1.7107144E-02 0.000000 0.000000 1.6615637E-04 0.000000 2.9999940E-02 0.000000 + Av 2018 11 26 20 0 1.9945383E-02 1.5334757E-08 0.000000 1.6619399E-04 3.2524558E-04 9.9999802E-03 0.000000 + Av 2018 11 26 21 0 0.1126539 1.2778949E-07 0.000000 1.6658979E-04 1.3808695E-02 1.9999960E-02 0.000000 + Av 2018 11 26 22 0 0.3806681 8.0768706E-07 0.000000 1.6777488E-04 4.3821260E-02 4.9999900E-02 0.000000 + Av 2018 11 26 23 0 0.4197968 3.0292907E-07 0.000000 1.6961148E-04 3.2637049E-02 2.9999940E-02 0.000000 + Av 2018 11 26 24 0 0.2013284 3.4312976E-08 0.000000 1.7059836E-04 1.4196324E-02 9.9999802E-03 0.000000 + Av 2018 11 27 1 0 0.6455536 3.4932873E-06 0.000000 1.7168239E-04 8.6397059E-02 9.9999800E-02 0.000000 + Av 2018 11 27 2 0 1.217804 5.6344506E-06 0.000000 1.7619258E-04 0.1171034 0.1199998 0.000000 + Av 2018 11 27 3 0 0.6323277 4.6247120E-08 0.000000 1.7993308E-04 2.4082184E-02 9.9999802E-03 0.000000 + Av 2018 11 27 4 0 0.4373095 2.2758068E-06 0.000000 1.8130837E-04 6.2527128E-02 6.9999859E-02 0.000000 + Av 2018 11 27 5 0 1.218283 9.7299890E-06 2.4935235E-07 1.8572368E-04 0.1312269 0.1399997 0.000000 + Av 2018 11 27 6 0 0.8200459 5.5201167E-07 5.0812162E-07 1.9078926E-04 4.2613685E-02 2.9999940E-02 0.000000 + Av 2018 11 27 7 0 9.2582047E-02 0.000000 5.1488405E-07 1.9183820E-04 7.9515027E-03 0.000000 0.000000 Av 2018 11 27 8 0 5.3509228E-02 0.000000 5.0728875E-07 1.9467290E-05 2.3650380E-03 0.000000 7.8321237E-04 Av 2018 11 27 9 0 6.4200312E-03 0.000000 4.9980542E-07 0.000000 9.3989854E-04 0.000000 2.7649708E-03 Av 2018 11 27 10 0 7.1854303E-03 0.000000 4.9243255E-07 0.000000 4.5189602E-04 0.000000 4.3551233E-03 @@ -7960,21 +7960,21 @@ Av 2018 11 27 14 0 7.5366913E-04 0.000000 4.6401260E-07 0.000000 6.6218279E-05 0.000000 4.3551233E-03 Av 2018 11 27 15 0 5.1216118E-04 0.000000 4.5716769E-07 0.000000 4.7302536E-05 0.000000 2.7649708E-03 Av 2018 11 27 16 0 1.7028046E-03 0.000000 4.5042376E-07 1.8954714E-05 3.4992907E-05 0.000000 7.8321237E-04 - Av 2018 11 27 17 0 1.5178671E-02 0.000000 4.4377930E-07 1.9119745E-04 1.7655941E-04 0.000000 0.000000 - Av 2018 11 27 18 0 2.1958921E-02 0.000000 4.3723287E-07 1.9113350E-04 0.000000 0.000000 0.000000 - Av 2018 11 27 19 0 1.8392175E-02 0.000000 4.3078299E-07 1.9106956E-04 0.000000 0.000000 0.000000 - Av 2018 11 27 20 0 1.9622806E-02 0.000000 4.2442829E-07 1.9100563E-04 0.000000 0.000000 0.000000 - Av 2018 11 27 21 0 1.9185361E-02 0.000000 4.1816730E-07 1.9094172E-04 0.000000 0.000000 0.000000 - Av 2018 11 27 22 0 1.9327939E-02 0.000000 4.1199866E-07 1.9087786E-04 0.000000 0.000000 0.000000 - Av 2018 11 27 23 0 1.9268855E-02 0.000000 4.0592104E-07 1.9081401E-04 0.000000 0.000000 0.000000 - Av 2018 11 27 24 0 1.9279905E-02 0.000000 3.9993307E-07 1.9075020E-04 0.000000 0.000000 0.000000 - Av 2018 11 28 1 0 1.9217938E-02 0.000000 3.9403341E-07 1.8997044E-04 0.000000 0.000000 0.000000 - Av 2018 11 28 2 0 1.9485570E-02 0.000000 3.8822083E-07 1.8990712E-04 0.000000 9.9999802E-03 0.000000 - Av 2018 11 28 3 0 1.9383127E-02 0.000000 3.8249394E-07 1.8984383E-04 0.000000 0.000000 0.000000 - Av 2018 11 28 4 0 1.9105215E-02 0.000000 3.7685155E-07 1.8978058E-04 0.000000 0.000000 0.000000 - Av 2018 11 28 5 0 1.9192491E-02 0.000000 3.7129240E-07 1.8971734E-04 0.000000 0.000000 0.000000 - Av 2018 11 28 6 0 1.9152801E-02 0.000000 3.6581528E-07 1.8965411E-04 0.000000 0.000000 0.000000 - Av 2018 11 28 7 0 1.9461419E-02 0.000000 3.6041894E-07 1.8959089E-04 0.000000 9.9999802E-03 0.000000 + Av 2018 11 27 17 0 1.5178671E-02 0.000000 4.4377930E-07 1.9119745E-04 1.7655941E-04 0.000000 0.000000 + Av 2018 11 27 18 0 2.1958921E-02 0.000000 4.3723287E-07 1.9113350E-04 0.000000 0.000000 0.000000 + Av 2018 11 27 19 0 1.8392175E-02 0.000000 4.3078299E-07 1.9106956E-04 0.000000 0.000000 0.000000 + Av 2018 11 27 20 0 1.9622806E-02 0.000000 4.2442829E-07 1.9100563E-04 0.000000 0.000000 0.000000 + Av 2018 11 27 21 0 1.9185361E-02 0.000000 4.1816730E-07 1.9094172E-04 0.000000 0.000000 0.000000 + Av 2018 11 27 22 0 1.9327939E-02 0.000000 4.1199866E-07 1.9087786E-04 0.000000 0.000000 0.000000 + Av 2018 11 27 23 0 1.9268855E-02 0.000000 4.0592104E-07 1.9081401E-04 0.000000 0.000000 0.000000 + Av 2018 11 27 24 0 1.9279905E-02 0.000000 3.9993307E-07 1.9075020E-04 0.000000 0.000000 0.000000 + Av 2018 11 28 1 0 1.9217938E-02 0.000000 3.9403341E-07 1.8997044E-04 0.000000 0.000000 0.000000 + Av 2018 11 28 2 0 1.9485570E-02 0.000000 3.8822083E-07 1.8990712E-04 0.000000 9.9999802E-03 0.000000 + Av 2018 11 28 3 0 1.9383127E-02 0.000000 3.8249394E-07 1.8984383E-04 0.000000 0.000000 0.000000 + Av 2018 11 28 4 0 1.9105215E-02 0.000000 3.7685155E-07 1.8978058E-04 0.000000 0.000000 0.000000 + Av 2018 11 28 5 0 1.9192491E-02 0.000000 3.7129240E-07 1.8971734E-04 0.000000 0.000000 0.000000 + Av 2018 11 28 6 0 1.9152801E-02 0.000000 3.6581528E-07 1.8965411E-04 0.000000 0.000000 0.000000 + Av 2018 11 28 7 0 1.9461419E-02 0.000000 3.6041894E-07 1.8959089E-04 0.000000 9.9999802E-03 0.000000 Av 2018 11 28 8 0 0.2144598 1.1797897E-06 3.8582189E-07 4.3268941E-05 2.9943544E-02 4.9999900E-02 6.6840206E-04 Av 2018 11 28 9 0 0.5784158 3.1043498E-06 4.9188839E-07 0.000000 6.4087659E-02 6.9999859E-02 2.4169786E-03 Av 2018 11 28 10 0 0.5336847 9.7725251E-07 5.9115268E-07 0.000000 4.1653626E-02 3.9999921E-02 3.8313540E-03 @@ -7984,21 +7984,21 @@ Av 2018 11 28 14 0 0.5698425 1.6000932E-06 7.8627028E-07 0.000000 4.8076801E-02 4.9999900E-02 3.8313540E-03 Av 2018 11 28 15 0 0.2101631 0.000000 8.1703814E-07 0.000000 8.6534442E-03 0.000000 2.4169786E-03 Av 2018 11 28 16 0 8.8174067E-02 1.5416674E-07 8.0910672E-07 5.7997458E-05 1.2387803E-02 1.9999960E-02 6.6840206E-04 - Av 2018 11 28 17 0 9.4776116E-02 0.000000 8.0127188E-07 2.0563800E-04 3.4196542E-03 0.000000 0.000000 - Av 2018 11 28 18 0 2.6821099E-02 0.000000 7.8945186E-07 2.0556750E-04 1.2501227E-03 0.000000 0.000000 - Av 2018 11 28 19 0 3.1065352E-02 0.000000 7.7780618E-07 2.0549701E-04 5.6832685E-04 0.000000 0.000000 - Av 2018 11 28 20 0 2.3120705E-02 0.000000 7.6633233E-07 2.0542655E-04 2.9967667E-04 0.000000 0.000000 - Av 2018 11 28 21 0 2.3203762E-02 0.000000 7.5502771E-07 2.0535612E-04 1.7561573E-04 0.000000 0.000000 - Av 2018 11 28 22 0 2.1883698E-02 0.000000 7.4388987E-07 2.0528572E-04 1.1127369E-04 0.000000 0.000000 - Av 2018 11 28 23 0 2.1646902E-02 0.000000 7.3291631E-07 2.0521534E-04 7.4837997E-05 0.000000 0.000000 - Av 2018 11 28 24 0 2.1320513E-02 0.000000 7.2210463E-07 2.0514497E-04 5.2742729E-05 0.000000 0.000000 - Av 2018 11 29 1 0 2.1115717E-02 0.000000 7.1145286E-07 2.0417695E-04 3.8591421E-05 0.000000 0.000000 - Av 2018 11 29 2 0 2.2029260E-02 0.000000 7.0095825E-07 2.0411413E-04 1.8723721E-04 0.000000 0.000000 - Av 2018 11 29 3 0 2.1438990E-02 0.000000 6.9061798E-07 2.0404447E-04 0.000000 0.000000 0.000000 - Av 2018 11 29 4 0 2.0361202E-02 0.000000 6.8043028E-07 2.0397482E-04 0.000000 0.000000 0.000000 - Av 2018 11 29 5 0 2.0725122E-02 0.000000 6.7039286E-07 2.0390519E-04 0.000000 0.000000 0.000000 - Av 2018 11 29 6 0 2.0587768E-02 0.000000 6.6050353E-07 2.0383559E-04 0.000000 0.000000 0.000000 - Av 2018 11 29 7 0 2.0624734E-02 0.000000 6.5076006E-07 2.0376600E-04 0.000000 0.000000 0.000000 + Av 2018 11 28 17 0 9.4776116E-02 0.000000 8.0127188E-07 2.0563800E-04 3.4196542E-03 0.000000 0.000000 + Av 2018 11 28 18 0 2.6821099E-02 0.000000 7.8945186E-07 2.0556750E-04 1.2501227E-03 0.000000 0.000000 + Av 2018 11 28 19 0 3.1065352E-02 0.000000 7.7780618E-07 2.0549701E-04 5.6832685E-04 0.000000 0.000000 + Av 2018 11 28 20 0 2.3120705E-02 0.000000 7.6633233E-07 2.0542655E-04 2.9967667E-04 0.000000 0.000000 + Av 2018 11 28 21 0 2.3203762E-02 0.000000 7.5502771E-07 2.0535612E-04 1.7561573E-04 0.000000 0.000000 + Av 2018 11 28 22 0 2.1883698E-02 0.000000 7.4388987E-07 2.0528572E-04 1.1127369E-04 0.000000 0.000000 + Av 2018 11 28 23 0 2.1646902E-02 0.000000 7.3291631E-07 2.0521534E-04 7.4837997E-05 0.000000 0.000000 + Av 2018 11 28 24 0 2.1320513E-02 0.000000 7.2210463E-07 2.0514497E-04 5.2742729E-05 0.000000 0.000000 + Av 2018 11 29 1 0 2.1115717E-02 0.000000 7.1145286E-07 2.0417695E-04 3.8591421E-05 0.000000 0.000000 + Av 2018 11 29 2 0 2.2029260E-02 0.000000 7.0095825E-07 2.0411413E-04 1.8723721E-04 0.000000 0.000000 + Av 2018 11 29 3 0 2.1438990E-02 0.000000 6.9061798E-07 2.0404447E-04 0.000000 0.000000 0.000000 + Av 2018 11 29 4 0 2.0361202E-02 0.000000 6.8043028E-07 2.0397482E-04 0.000000 0.000000 0.000000 + Av 2018 11 29 5 0 2.0725122E-02 0.000000 6.7039286E-07 2.0390519E-04 0.000000 0.000000 0.000000 + Av 2018 11 29 6 0 2.0587768E-02 0.000000 6.6050353E-07 2.0383559E-04 0.000000 0.000000 0.000000 + Av 2018 11 29 7 0 2.0624734E-02 0.000000 6.5076006E-07 2.0376600E-04 0.000000 0.000000 0.000000 Av 2018 11 29 8 0 1.0602515E-02 0.000000 6.4116028E-07 5.6846315E-05 0.000000 0.000000 6.6750054E-04 Av 2018 11 29 9 0 3.0413191E-04 0.000000 6.3170216E-07 0.000000 0.000000 0.000000 2.4724465E-03 Av 2018 11 29 10 0 4.2287404E-05 0.000000 6.2238360E-07 0.000000 0.000000 0.000000 3.9436421E-03 @@ -8008,21 +8008,21 @@ Av 2018 11 29 14 0 1.9294890E-05 0.000000 5.8646367E-07 0.000000 0.000000 0.000000 3.9436421E-03 Av 2018 11 29 15 0 2.9559167E-05 0.000000 5.7781244E-07 0.000000 0.000000 0.000000 2.4724465E-03 Av 2018 11 29 16 0 3.8712882E-03 0.000000 5.6928877E-07 5.6290723E-05 0.000000 0.000000 6.6750054E-04 - Av 2018 11 29 17 0 1.6348399E-02 0.000000 5.6089090E-07 2.0307150E-04 0.000000 0.000000 0.000000 - Av 2018 11 29 18 0 2.1981552E-02 0.000000 5.5261683E-07 2.0300217E-04 0.000000 0.000000 0.000000 - Av 2018 11 29 19 0 2.0012319E-02 0.000000 5.4446485E-07 2.0293286E-04 0.000000 0.000000 0.000000 - Av 2018 11 29 20 0 2.0686522E-02 0.000000 5.3643316E-07 2.0286358E-04 0.000000 0.000000 0.000000 - Av 2018 11 29 21 0 2.0441603E-02 0.000000 5.2851993E-07 2.0279434E-04 0.000000 0.000000 0.000000 - Av 2018 11 29 22 0 2.0516289E-02 0.000000 5.2072346E-07 2.0272512E-04 0.000000 0.000000 0.000000 - Av 2018 11 29 23 0 2.0479864E-02 0.000000 5.1304198E-07 2.0265592E-04 0.000000 0.000000 0.000000 - Av 2018 11 29 24 0 2.0482091E-02 0.000000 5.0547379E-07 2.0258674E-04 0.000000 0.000000 0.000000 - Av 2018 11 30 1 0 2.0411981E-02 0.000000 4.9801724E-07 2.0165050E-04 0.000000 0.000000 0.000000 - Av 2018 11 30 2 0 2.0367086E-02 0.000000 4.9067069E-07 2.0158196E-04 0.000000 0.000000 0.000000 - Av 2018 11 30 3 0 2.0372394E-02 0.000000 4.8343253E-07 2.0151345E-04 0.000000 0.000000 0.000000 - Av 2018 11 30 4 0 2.0360261E-02 0.000000 4.7630112E-07 2.0144494E-04 0.000000 0.000000 0.000000 - Av 2018 11 30 5 0 2.0354211E-02 0.000000 4.6927491E-07 2.0137648E-04 0.000000 0.000000 0.000000 - Av 2018 11 30 6 0 2.0346064E-02 0.000000 4.6235240E-07 2.0130801E-04 0.000000 0.000000 0.000000 - Av 2018 11 30 7 0 2.0963546E-02 0.000000 4.5553199E-07 2.0123959E-04 0.000000 1.9999960E-02 0.000000 + Av 2018 11 29 17 0 1.6348399E-02 0.000000 5.6089090E-07 2.0307150E-04 0.000000 0.000000 0.000000 + Av 2018 11 29 18 0 2.1981552E-02 0.000000 5.5261683E-07 2.0300217E-04 0.000000 0.000000 0.000000 + Av 2018 11 29 19 0 2.0012319E-02 0.000000 5.4446485E-07 2.0293286E-04 0.000000 0.000000 0.000000 + Av 2018 11 29 20 0 2.0686522E-02 0.000000 5.3643316E-07 2.0286358E-04 0.000000 0.000000 0.000000 + Av 2018 11 29 21 0 2.0441603E-02 0.000000 5.2851993E-07 2.0279434E-04 0.000000 0.000000 0.000000 + Av 2018 11 29 22 0 2.0516289E-02 0.000000 5.2072346E-07 2.0272512E-04 0.000000 0.000000 0.000000 + Av 2018 11 29 23 0 2.0479864E-02 0.000000 5.1304198E-07 2.0265592E-04 0.000000 0.000000 0.000000 + Av 2018 11 29 24 0 2.0482091E-02 0.000000 5.0547379E-07 2.0258674E-04 0.000000 0.000000 0.000000 + Av 2018 11 30 1 0 2.0411981E-02 0.000000 4.9801724E-07 2.0165050E-04 0.000000 0.000000 0.000000 + Av 2018 11 30 2 0 2.0367086E-02 0.000000 4.9067069E-07 2.0158196E-04 0.000000 0.000000 0.000000 + Av 2018 11 30 3 0 2.0372394E-02 0.000000 4.8343253E-07 2.0151345E-04 0.000000 0.000000 0.000000 + Av 2018 11 30 4 0 2.0360261E-02 0.000000 4.7630112E-07 2.0144494E-04 0.000000 0.000000 0.000000 + Av 2018 11 30 5 0 2.0354211E-02 0.000000 4.6927491E-07 2.0137648E-04 0.000000 0.000000 0.000000 + Av 2018 11 30 6 0 2.0346064E-02 0.000000 4.6235240E-07 2.0130801E-04 0.000000 0.000000 0.000000 + Av 2018 11 30 7 0 2.0963546E-02 0.000000 4.5553199E-07 2.0123959E-04 0.000000 1.9999960E-02 0.000000 Av 2018 11 30 8 0 1.1613772E-02 0.000000 4.4881219E-07 6.7159926E-05 0.000000 0.000000 6.0914212E-04 Av 2018 11 30 9 0 5.2028567E-02 1.9584130E-07 4.4743430E-07 0.000000 7.5460309E-03 1.9999960E-02 2.3110965E-03 Av 2018 11 30 10 0 0.1957503 6.0593766E-07 4.6229832E-07 0.000000 2.3617666E-02 2.9999940E-02 3.7084799E-03 @@ -8032,21 +8032,21 @@ Av 2018 11 30 14 0 3.2023017E-03 0.000000 4.5107959E-07 0.000000 3.8109245E-04 9.9999802E-03 3.7084799E-03 Av 2018 11 30 15 0 0.9888153 2.3524990E-05 1.0769770E-06 0.000000 0.1446579 0.1799996 2.3110965E-03 Av 2018 11 30 16 0 1.641683 2.0313373E-05 2.2443787E-06 8.2524683E-05 0.1396829 0.1399997 6.0914212E-04 - Av 2018 11 30 17 0 0.6552735 1.1739441E-07 2.7656349E-06 2.2274954E-04 2.5688421E-02 9.9999802E-03 0.000000 - Av 2018 11 30 18 0 0.1042413 1.2983118E-07 2.7316432E-06 2.2345004E-04 1.3079060E-02 9.9999802E-03 0.000000 - Av 2018 11 30 19 0 0.1065796 0.000000 2.6949137E-06 2.2389868E-04 3.4128218E-03 0.000000 0.000000 - Av 2018 11 30 20 0 0.1759070 1.1726030E-06 2.6875625E-06 2.2462833E-04 2.3314107E-02 2.9999940E-02 0.000000 - Av 2018 11 30 21 0 0.2199473 1.3231355E-07 2.6838263E-06 2.2637175E-04 1.3230301E-02 9.9999802E-03 0.000000 - Av 2018 11 30 22 0 0.2839497 2.1243914E-06 2.7068181E-06 2.2789241E-04 3.4626663E-02 3.9999921E-02 0.000000 - Av 2018 11 30 23 0 0.2735922 1.3598209E-07 2.7293172E-06 2.3015971E-04 1.4911246E-02 9.9999802E-03 0.000000 - Av 2018 11 30 24 0 0.2800183 2.1831606E-06 2.7536782E-06 2.3184680E-04 3.5047449E-02 3.9999921E-02 0.000000 - Av 2018 12 1 1 0 0.3343550 5.9676796E-07 2.7903079E-06 2.3333487E-04 2.2976622E-02 1.9999960E-02 0.000000 - Av 2018 12 1 2 0 0.1099122 0.000000 2.7657607E-06 2.3444228E-04 5.1300568E-03 0.000000 0.000000 - Av 2018 12 1 3 0 4.0433481E-02 0.000000 2.7249612E-06 2.3435843E-04 1.7028314E-03 0.000000 0.000000 - Av 2018 12 1 4 0 3.4654923E-02 0.000000 2.6847638E-06 2.3427462E-04 7.2644063E-04 0.000000 0.000000 - Av 2018 12 1 5 0 2.7568121E-02 0.000000 2.6451592E-06 2.3419084E-04 3.6655247E-04 0.000000 0.000000 - Av 2018 12 1 6 0 2.6493587E-02 0.000000 2.6061389E-06 2.3410708E-04 2.0808179E-04 0.000000 0.000000 - Av 2018 12 1 7 0 2.5234785E-02 0.000000 2.5676943E-06 2.3402333E-04 1.2874237E-04 0.000000 0.000000 + Av 2018 11 30 17 0 0.6552735 1.1739441E-07 2.7656349E-06 2.2274954E-04 2.5688421E-02 9.9999802E-03 0.000000 + Av 2018 11 30 18 0 0.1042413 1.2983118E-07 2.7316432E-06 2.2345004E-04 1.3079060E-02 9.9999802E-03 0.000000 + Av 2018 11 30 19 0 0.1065796 0.000000 2.6949137E-06 2.2389868E-04 3.4128218E-03 0.000000 0.000000 + Av 2018 11 30 20 0 0.1759070 1.1726030E-06 2.6875625E-06 2.2462833E-04 2.3314107E-02 2.9999940E-02 0.000000 + Av 2018 11 30 21 0 0.2199473 1.3231355E-07 2.6838263E-06 2.2637175E-04 1.3230301E-02 9.9999802E-03 0.000000 + Av 2018 11 30 22 0 0.2839497 2.1243914E-06 2.7068181E-06 2.2789241E-04 3.4626663E-02 3.9999921E-02 0.000000 + Av 2018 11 30 23 0 0.2735922 1.3598209E-07 2.7293172E-06 2.3015971E-04 1.4911246E-02 9.9999802E-03 0.000000 + Av 2018 11 30 24 0 0.2800183 2.1831606E-06 2.7536782E-06 2.3184680E-04 3.5047449E-02 3.9999921E-02 0.000000 + Av 2018 12 1 1 0 0.3343550 5.9676796E-07 2.7903079E-06 2.3333487E-04 2.2976622E-02 1.9999960E-02 0.000000 + Av 2018 12 1 2 0 0.1099122 0.000000 2.7657607E-06 2.3444228E-04 5.1300568E-03 0.000000 0.000000 + Av 2018 12 1 3 0 4.0433481E-02 0.000000 2.7249612E-06 2.3435843E-04 1.7028314E-03 0.000000 0.000000 + Av 2018 12 1 4 0 3.4654923E-02 0.000000 2.6847638E-06 2.3427462E-04 7.2644063E-04 0.000000 0.000000 + Av 2018 12 1 5 0 2.7568121E-02 0.000000 2.6451592E-06 2.3419084E-04 3.6655247E-04 0.000000 0.000000 + Av 2018 12 1 6 0 2.6493587E-02 0.000000 2.6061389E-06 2.3410708E-04 2.0808179E-04 0.000000 0.000000 + Av 2018 12 1 7 0 2.5234785E-02 0.000000 2.5676943E-06 2.3402333E-04 1.2874237E-04 0.000000 0.000000 Av 2018 12 1 8 0 1.6553774E-02 0.000000 2.5298168E-06 1.1256129E-04 8.5010826E-05 0.000000 5.5171980E-04 Av 2018 12 1 9 0 4.0204464E-03 0.000000 2.4924980E-06 0.000000 5.9048201E-05 0.000000 2.1694279E-03 Av 2018 12 1 10 0 4.5698322E-04 0.000000 2.4557296E-06 0.000000 4.2701242E-05 0.000000 3.5112759E-03 @@ -8056,21 +8056,21 @@ Av 2018 12 1 14 0 2.3548250E-04 0.000000 2.3140012E-06 0.000000 0.000000 0.000000 3.5112759E-03 Av 2018 12 1 15 0 1.8927132E-04 0.000000 2.2798661E-06 0.000000 0.000000 0.000000 2.1694279E-03 Av 2018 12 1 16 0 7.8250952E-03 0.000000 2.2462345E-06 1.1189278E-04 0.000000 0.000000 5.5171980E-04 - Av 2018 12 1 17 0 2.1024428E-02 0.000000 2.2130992E-06 2.3318769E-04 0.000000 0.000000 0.000000 - Av 2018 12 1 18 0 2.4670009E-02 0.000000 2.1804524E-06 2.3310429E-04 0.000000 0.000000 0.000000 - Av 2018 12 1 19 0 2.3386672E-02 0.000000 2.1482872E-06 2.3302092E-04 0.000000 0.000000 0.000000 - Av 2018 12 1 20 0 2.3817234E-02 0.000000 2.1165965E-06 2.3293759E-04 0.000000 0.000000 0.000000 - Av 2018 12 1 21 0 2.3651926E-02 0.000000 2.0853736E-06 2.3285428E-04 0.000000 0.000000 0.000000 - Av 2018 12 1 22 0 2.3693874E-02 0.000000 2.0546111E-06 2.3277098E-04 0.000000 0.000000 0.000000 - Av 2018 12 1 23 0 2.3663824E-02 0.000000 2.0243021E-06 2.3268774E-04 0.000000 0.000000 0.000000 - Av 2018 12 1 24 0 0.2629537 3.3681099E-06 2.0888642E-06 2.3404008E-04 3.4825165E-02 6.9999859E-02 0.000000 - Av 2018 12 2 1 0 0.2859833 1.5519706E-07 2.1563771E-06 2.3565917E-04 1.5378670E-02 9.9999802E-03 0.000000 - Av 2018 12 2 2 0 6.5024443E-02 0.000000 2.1289161E-06 2.3617956E-04 3.8401352E-03 0.000000 0.000000 - Av 2018 12 2 3 0 4.5140617E-02 0.000000 2.0975112E-06 2.3609494E-04 1.3662910E-03 0.000000 0.000000 - Av 2018 12 2 4 0 3.0092258E-02 0.000000 2.0665698E-06 2.3601034E-04 6.1007513E-04 0.000000 0.000000 - Av 2018 12 2 5 0 2.8184399E-02 0.000000 2.0360844E-06 2.3592576E-04 3.1769043E-04 0.000000 0.000000 - Av 2018 12 2 6 0 6.6733971E-02 1.4616667E-07 2.0101693E-06 2.3615632E-04 6.1321273E-03 9.9999802E-03 0.000000 - Av 2018 12 2 7 0 6.7090757E-02 0.000000 1.9846161E-06 2.3665857E-04 2.3361864E-03 0.000000 0.000000 + Av 2018 12 1 17 0 2.1024428E-02 0.000000 2.2130992E-06 2.3318769E-04 0.000000 0.000000 0.000000 + Av 2018 12 1 18 0 2.4670009E-02 0.000000 2.1804524E-06 2.3310429E-04 0.000000 0.000000 0.000000 + Av 2018 12 1 19 0 2.3386672E-02 0.000000 2.1482872E-06 2.3302092E-04 0.000000 0.000000 0.000000 + Av 2018 12 1 20 0 2.3817234E-02 0.000000 2.1165965E-06 2.3293759E-04 0.000000 0.000000 0.000000 + Av 2018 12 1 21 0 2.3651926E-02 0.000000 2.0853736E-06 2.3285428E-04 0.000000 0.000000 0.000000 + Av 2018 12 1 22 0 2.3693874E-02 0.000000 2.0546111E-06 2.3277098E-04 0.000000 0.000000 0.000000 + Av 2018 12 1 23 0 2.3663824E-02 0.000000 2.0243021E-06 2.3268774E-04 0.000000 0.000000 0.000000 + Av 2018 12 1 24 0 0.2629537 3.3681099E-06 2.0888642E-06 2.3404008E-04 3.4825165E-02 6.9999859E-02 0.000000 + Av 2018 12 2 1 0 0.2859833 1.5519706E-07 2.1563771E-06 2.3565917E-04 1.5378670E-02 9.9999802E-03 0.000000 + Av 2018 12 2 2 0 6.5024443E-02 0.000000 2.1289161E-06 2.3617956E-04 3.8401352E-03 0.000000 0.000000 + Av 2018 12 2 3 0 4.5140617E-02 0.000000 2.0975112E-06 2.3609494E-04 1.3662910E-03 0.000000 0.000000 + Av 2018 12 2 4 0 3.0092258E-02 0.000000 2.0665698E-06 2.3601034E-04 6.1007513E-04 0.000000 0.000000 + Av 2018 12 2 5 0 2.8184399E-02 0.000000 2.0360844E-06 2.3592576E-04 3.1769043E-04 0.000000 0.000000 + Av 2018 12 2 6 0 6.6733971E-02 1.4616667E-07 2.0101693E-06 2.3615632E-04 6.1321273E-03 9.9999802E-03 0.000000 + Av 2018 12 2 7 0 6.7090757E-02 0.000000 1.9846161E-06 2.3665857E-04 2.3361864E-03 0.000000 0.000000 Av 2018 12 2 8 0 2.4032824E-02 0.000000 1.9553397E-06 1.2999590E-04 9.3095115E-04 0.000000 4.8444440E-04 Av 2018 12 2 9 0 1.0604104E-02 0.000000 1.9264955E-06 0.000000 4.4841479E-04 0.000000 1.9502522E-03 Av 2018 12 2 10 0 1.8021289E-03 0.000000 1.8980766E-06 0.000000 2.4625554E-04 0.000000 3.1738379E-03 @@ -8080,21 +8080,21 @@ Av 2018 12 2 14 0 6.3593552E-04 0.000000 1.7885320E-06 0.000000 4.7126399E-05 0.000000 3.1738379E-03 Av 2018 12 2 15 0 5.3595868E-04 0.000000 1.7621484E-06 0.000000 3.4875524E-05 0.000000 1.9502522E-03 Av 2018 12 2 16 0 1.0252632E-02 0.000000 1.7361539E-06 1.2931766E-04 1.7620387E-04 0.000000 4.8444440E-04 - Av 2018 12 2 17 0 2.2671115E-02 0.000000 1.7105430E-06 2.3581077E-04 0.000000 0.000000 0.000000 - Av 2018 12 2 18 0 2.4386017E-02 0.000000 1.6853097E-06 2.3572617E-04 0.000000 0.000000 0.000000 - Av 2018 12 2 19 0 2.3774832E-02 0.000000 1.6604488E-06 2.3564159E-04 0.000000 0.000000 0.000000 - Av 2018 12 2 20 0 2.3972500E-02 0.000000 1.6359546E-06 2.3555705E-04 0.000000 0.000000 0.000000 - Av 2018 12 2 21 0 2.3888979E-02 0.000000 1.6118217E-06 2.3547253E-04 0.000000 0.000000 0.000000 - Av 2018 12 2 22 0 2.3903282E-02 0.000000 1.5880448E-06 2.3538803E-04 0.000000 0.000000 0.000000 - Av 2018 12 2 23 0 2.3883622E-02 0.000000 1.5646187E-06 2.3530357E-04 0.000000 0.000000 0.000000 - Av 2018 12 2 24 0 2.3875823E-02 0.000000 1.5415380E-06 2.3521914E-04 0.000000 0.000000 0.000000 - Av 2018 12 3 1 0 2.3775578E-02 0.000000 1.5187979E-06 2.3383407E-04 0.000000 0.000000 0.000000 - Av 2018 12 3 2 0 2.3707589E-02 0.000000 1.4963933E-06 2.3375064E-04 0.000000 0.000000 0.000000 - Av 2018 12 3 3 0 2.3716871E-02 0.000000 1.4743191E-06 2.3366723E-04 0.000000 0.000000 0.000000 - Av 2018 12 3 4 0 2.3699336E-02 0.000000 1.4525706E-06 2.3358385E-04 0.000000 0.000000 0.000000 - Av 2018 12 3 5 0 2.3691170E-02 0.000000 1.4311429E-06 2.3350051E-04 0.000000 0.000000 0.000000 - Av 2018 12 3 6 0 2.3679797E-02 0.000000 1.4100312E-06 2.3341720E-04 0.000000 0.000000 0.000000 - Av 2018 12 3 7 0 2.3669586E-02 0.000000 1.3892311E-06 2.3333391E-04 0.000000 0.000000 0.000000 + Av 2018 12 2 17 0 2.2671115E-02 0.000000 1.7105430E-06 2.3581077E-04 0.000000 0.000000 0.000000 + Av 2018 12 2 18 0 2.4386017E-02 0.000000 1.6853097E-06 2.3572617E-04 0.000000 0.000000 0.000000 + Av 2018 12 2 19 0 2.3774832E-02 0.000000 1.6604488E-06 2.3564159E-04 0.000000 0.000000 0.000000 + Av 2018 12 2 20 0 2.3972500E-02 0.000000 1.6359546E-06 2.3555705E-04 0.000000 0.000000 0.000000 + Av 2018 12 2 21 0 2.3888979E-02 0.000000 1.6118217E-06 2.3547253E-04 0.000000 0.000000 0.000000 + Av 2018 12 2 22 0 2.3903282E-02 0.000000 1.5880448E-06 2.3538803E-04 0.000000 0.000000 0.000000 + Av 2018 12 2 23 0 2.3883622E-02 0.000000 1.5646187E-06 2.3530357E-04 0.000000 0.000000 0.000000 + Av 2018 12 2 24 0 2.3875823E-02 0.000000 1.5415380E-06 2.3521914E-04 0.000000 0.000000 0.000000 + Av 2018 12 3 1 0 2.3775578E-02 0.000000 1.5187979E-06 2.3383407E-04 0.000000 0.000000 0.000000 + Av 2018 12 3 2 0 2.3707589E-02 0.000000 1.4963933E-06 2.3375064E-04 0.000000 0.000000 0.000000 + Av 2018 12 3 3 0 2.3716871E-02 0.000000 1.4743191E-06 2.3366723E-04 0.000000 0.000000 0.000000 + Av 2018 12 3 4 0 2.3699336E-02 0.000000 1.4525706E-06 2.3358385E-04 0.000000 0.000000 0.000000 + Av 2018 12 3 5 0 2.3691170E-02 0.000000 1.4311429E-06 2.3350051E-04 0.000000 0.000000 0.000000 + Av 2018 12 3 6 0 2.3679797E-02 0.000000 1.4100312E-06 2.3341720E-04 0.000000 0.000000 0.000000 + Av 2018 12 3 7 0 2.3669586E-02 0.000000 1.3892311E-06 2.3333391E-04 0.000000 0.000000 0.000000 Av 2018 12 3 8 0 1.6438551E-02 0.000000 1.3687378E-06 1.2721791E-04 0.000000 0.000000 4.8196700E-04 Av 2018 12 3 9 0 4.6064584E-03 0.000000 1.3485468E-06 0.000000 0.000000 0.000000 1.9857658E-03 Av 2018 12 3 10 0 9.0274407E-05 0.000000 1.3286536E-06 0.000000 0.000000 0.000000 3.2485810E-03 @@ -8104,21 +8104,21 @@ Av 2018 12 3 14 0 9.2441762E-05 0.000000 1.2519724E-06 0.000000 0.000000 0.000000 3.2485810E-03 Av 2018 12 3 15 0 1.0090297E-04 0.000000 1.2335039E-06 0.000000 0.000000 0.000000 1.9857658E-03 Av 2018 12 3 16 0 8.7129232E-03 0.000000 1.2153077E-06 1.2655288E-04 0.000000 0.000000 4.8196700E-04 - Av 2018 12 3 17 0 2.1526817E-02 0.000000 1.1973800E-06 2.3250264E-04 0.000000 0.000000 0.000000 - Av 2018 12 3 18 0 2.4265254E-02 0.000000 1.1797167E-06 2.3241967E-04 0.000000 0.000000 0.000000 - Av 2018 12 3 19 0 2.3299422E-02 0.000000 1.1623141E-06 2.3233675E-04 0.000000 0.000000 0.000000 - Av 2018 12 3 20 0 2.3621636E-02 0.000000 1.1451682E-06 2.3225385E-04 0.000000 0.000000 0.000000 - Av 2018 12 3 21 0 2.3496021E-02 0.000000 1.1282751E-06 2.3217096E-04 0.000000 0.000000 0.000000 - Av 2018 12 3 22 0 2.3526160E-02 0.000000 1.1116313E-06 2.3208812E-04 0.000000 0.000000 0.000000 - Av 2018 12 3 23 0 2.3502182E-02 0.000000 1.0952330E-06 2.3200530E-04 0.000000 0.000000 0.000000 - Av 2018 12 3 24 0 2.3497056E-02 0.000000 1.0790766E-06 2.3192253E-04 0.000000 0.000000 0.000000 - Av 2018 12 4 1 0 2.3400422E-02 0.000000 1.0631585E-06 2.3058888E-04 0.000000 0.000000 0.000000 - Av 2018 12 4 2 0 2.3335699E-02 0.000000 1.0474753E-06 2.3050704E-04 0.000000 0.000000 0.000000 - Av 2018 12 4 3 0 2.3344971E-02 0.000000 1.0320234E-06 2.3042524E-04 0.000000 0.000000 0.000000 - Av 2018 12 4 4 0 2.3328548E-02 0.000000 1.0167994E-06 2.3034346E-04 0.000000 0.000000 0.000000 - Av 2018 12 4 5 0 2.3321092E-02 0.000000 1.0018000E-06 2.3026169E-04 0.000000 0.000000 0.000000 - Av 2018 12 4 6 0 2.3310553E-02 0.000000 9.8702196E-07 2.3017998E-04 0.000000 0.000000 0.000000 - Av 2018 12 4 7 0 2.3301121E-02 0.000000 9.7246186E-07 2.3009829E-04 0.000000 0.000000 0.000000 + Av 2018 12 3 17 0 2.1526817E-02 0.000000 1.1973800E-06 2.3250264E-04 0.000000 0.000000 0.000000 + Av 2018 12 3 18 0 2.4265254E-02 0.000000 1.1797167E-06 2.3241967E-04 0.000000 0.000000 0.000000 + Av 2018 12 3 19 0 2.3299422E-02 0.000000 1.1623141E-06 2.3233675E-04 0.000000 0.000000 0.000000 + Av 2018 12 3 20 0 2.3621636E-02 0.000000 1.1451682E-06 2.3225385E-04 0.000000 0.000000 0.000000 + Av 2018 12 3 21 0 2.3496021E-02 0.000000 1.1282751E-06 2.3217096E-04 0.000000 0.000000 0.000000 + Av 2018 12 3 22 0 2.3526160E-02 0.000000 1.1116313E-06 2.3208812E-04 0.000000 0.000000 0.000000 + Av 2018 12 3 23 0 2.3502182E-02 0.000000 1.0952330E-06 2.3200530E-04 0.000000 0.000000 0.000000 + Av 2018 12 3 24 0 2.3497056E-02 0.000000 1.0790766E-06 2.3192253E-04 0.000000 0.000000 0.000000 + Av 2018 12 4 1 0 2.3400422E-02 0.000000 1.0631585E-06 2.3058888E-04 0.000000 0.000000 0.000000 + Av 2018 12 4 2 0 2.3335699E-02 0.000000 1.0474753E-06 2.3050704E-04 0.000000 0.000000 0.000000 + Av 2018 12 4 3 0 2.3344971E-02 0.000000 1.0320234E-06 2.3042524E-04 0.000000 0.000000 0.000000 + Av 2018 12 4 4 0 2.3328548E-02 0.000000 1.0167994E-06 2.3034346E-04 0.000000 0.000000 0.000000 + Av 2018 12 4 5 0 2.3321092E-02 0.000000 1.0018000E-06 2.3026169E-04 0.000000 0.000000 0.000000 + Av 2018 12 4 6 0 2.3310553E-02 0.000000 9.8702196E-07 2.3017998E-04 0.000000 0.000000 0.000000 + Av 2018 12 4 7 0 2.3301121E-02 0.000000 9.7246186E-07 2.3009829E-04 0.000000 0.000000 0.000000 Av 2018 12 4 8 0 1.6705753E-02 0.000000 9.5811652E-07 1.3330550E-04 0.000000 0.000000 4.3959613E-04 Av 2018 12 4 9 0 5.0576911E-03 0.000000 9.4398274E-07 0.000000 0.000000 0.000000 1.8527821E-03 Av 2018 12 4 10 0 6.3192085E-05 0.000000 9.3005752E-07 0.000000 0.000000 0.000000 3.0461699E-03 @@ -8128,21 +8128,21 @@ Av 2018 12 4 14 0 5.7123099E-05 0.000000 8.7638080E-07 0.000000 0.000000 0.000000 3.0461699E-03 Av 2018 12 4 15 0 6.5213433E-05 0.000000 8.6345278E-07 0.000000 0.000000 0.000000 1.8527821E-03 Av 2018 12 4 16 0 9.0912934E-03 0.000000 8.5071548E-07 1.3265325E-04 0.000000 0.000000 4.3959613E-04 - Av 2018 12 4 17 0 2.1542132E-02 0.000000 8.3816610E-07 2.2928299E-04 0.000000 0.000000 0.000000 - Av 2018 12 4 18 0 2.3774071E-02 0.000000 8.2580186E-07 2.2920161E-04 0.000000 0.000000 0.000000 - Av 2018 12 4 19 0 2.2985283E-02 0.000000 8.1361998E-07 2.2912027E-04 0.000000 0.000000 0.000000 - Av 2018 12 4 20 0 2.3246858E-02 0.000000 8.0161777E-07 2.2903897E-04 0.000000 0.000000 0.000000 - Av 2018 12 4 21 0 2.3143239E-02 0.000000 7.8979269E-07 2.2895767E-04 0.000000 0.000000 0.000000 - Av 2018 12 4 22 0 2.3166629E-02 0.000000 7.7814195E-07 2.2887642E-04 0.000000 0.000000 0.000000 - Av 2018 12 4 23 0 2.3145886E-02 0.000000 7.6666316E-07 2.2879519E-04 0.000000 0.000000 0.000000 - Av 2018 12 4 24 0 2.3140512E-02 0.000000 7.5535365E-07 2.2871398E-04 0.000000 0.000000 0.000000 - Av 2018 12 5 1 0 2.3048081E-02 0.000000 7.4421104E-07 2.2742974E-04 0.000000 0.000000 0.000000 - Av 2018 12 5 2 0 2.2986002E-02 0.000000 7.3323275E-07 2.2734945E-04 0.000000 0.000000 0.000000 - Av 2018 12 5 3 0 2.2995198E-02 0.000000 7.2241642E-07 2.2726919E-04 0.000000 0.000000 0.000000 - Av 2018 12 5 4 0 2.2979639E-02 0.000000 7.1175970E-07 2.2718895E-04 0.000000 0.000000 0.000000 - Av 2018 12 5 5 0 2.2972710E-02 0.000000 7.0126009E-07 2.2710874E-04 0.000000 0.000000 0.000000 - Av 2018 12 5 6 0 2.2962805E-02 0.000000 6.9091539E-07 2.2702858E-04 0.000000 0.000000 0.000000 - Av 2018 12 5 7 0 2.2953963E-02 0.000000 6.8072336E-07 2.2694842E-04 0.000000 0.000000 0.000000 + Av 2018 12 4 17 0 2.1542132E-02 0.000000 8.3816610E-07 2.2928299E-04 0.000000 0.000000 0.000000 + Av 2018 12 4 18 0 2.3774071E-02 0.000000 8.2580186E-07 2.2920161E-04 0.000000 0.000000 0.000000 + Av 2018 12 4 19 0 2.2985283E-02 0.000000 8.1361998E-07 2.2912027E-04 0.000000 0.000000 0.000000 + Av 2018 12 4 20 0 2.3246858E-02 0.000000 8.0161777E-07 2.2903897E-04 0.000000 0.000000 0.000000 + Av 2018 12 4 21 0 2.3143239E-02 0.000000 7.8979269E-07 2.2895767E-04 0.000000 0.000000 0.000000 + Av 2018 12 4 22 0 2.3166629E-02 0.000000 7.7814195E-07 2.2887642E-04 0.000000 0.000000 0.000000 + Av 2018 12 4 23 0 2.3145886E-02 0.000000 7.6666316E-07 2.2879519E-04 0.000000 0.000000 0.000000 + Av 2018 12 4 24 0 2.3140512E-02 0.000000 7.5535365E-07 2.2871398E-04 0.000000 0.000000 0.000000 + Av 2018 12 5 1 0 2.3048081E-02 0.000000 7.4421104E-07 2.2742974E-04 0.000000 0.000000 0.000000 + Av 2018 12 5 2 0 2.2986002E-02 0.000000 7.3323275E-07 2.2734945E-04 0.000000 0.000000 0.000000 + Av 2018 12 5 3 0 2.2995198E-02 0.000000 7.2241642E-07 2.2726919E-04 0.000000 0.000000 0.000000 + Av 2018 12 5 4 0 2.2979639E-02 0.000000 7.1175970E-07 2.2718895E-04 0.000000 0.000000 0.000000 + Av 2018 12 5 5 0 2.2972710E-02 0.000000 7.0126009E-07 2.2710874E-04 0.000000 0.000000 0.000000 + Av 2018 12 5 6 0 2.2962805E-02 0.000000 6.9091539E-07 2.2702858E-04 0.000000 0.000000 0.000000 + Av 2018 12 5 7 0 2.2953963E-02 0.000000 6.8072336E-07 2.2694842E-04 0.000000 0.000000 0.000000 Av 2018 12 5 8 0 1.6850874E-02 0.000000 6.7068157E-07 1.3737634E-04 0.000000 0.000000 4.0678159E-04 Av 2018 12 5 9 0 5.3762393E-03 0.000000 6.6078798E-07 0.000000 0.000000 0.000000 1.7528168E-03 Av 2018 12 5 10 0 4.4234461E-05 0.000000 6.5104030E-07 0.000000 0.000000 0.000000 2.8954614E-03 @@ -8152,21 +8152,21 @@ Av 2018 12 5 14 0 3.2460219E-05 0.000000 6.1346651E-07 0.000000 0.000000 0.000000 2.8954614E-03 Av 2018 12 5 15 0 4.0284605E-05 0.000000 6.0441693E-07 0.000000 0.000000 0.000000 1.7528168E-03 Av 2018 12 5 16 0 9.3434704E-03 0.000000 5.9550081E-07 1.3673639E-04 0.000000 0.000000 4.0678159E-04 - Av 2018 12 5 17 0 2.1484725E-02 0.000000 5.8671623E-07 2.2614848E-04 0.000000 0.000000 0.000000 - Av 2018 12 5 18 0 2.3334276E-02 0.000000 5.7806130E-07 2.2606865E-04 0.000000 0.000000 0.000000 - Av 2018 12 5 19 0 2.2679154E-02 0.000000 5.6953400E-07 2.2598883E-04 0.000000 0.000000 0.000000 - Av 2018 12 5 20 0 2.2894952E-02 0.000000 5.6113248E-07 2.2590907E-04 0.000000 0.000000 0.000000 - Av 2018 12 5 21 0 2.2807948E-02 0.000000 5.5285489E-07 2.2582931E-04 0.000000 0.000000 0.000000 - Av 2018 12 5 22 0 2.2826247E-02 0.000000 5.4469939E-07 2.2574958E-04 0.000000 0.000000 0.000000 - Av 2018 12 5 23 0 2.2807952E-02 0.000000 5.3666423E-07 2.2566989E-04 0.000000 0.000000 0.000000 - Av 2018 12 5 24 0 2.2802401E-02 0.000000 5.2874759E-07 2.2559024E-04 0.000000 0.000000 0.000000 - Av 2018 12 6 1 0 2.2713821E-02 0.000000 5.2094771E-07 2.2435345E-04 0.000000 0.000000 0.000000 - Av 2018 12 6 2 0 2.2654183E-02 0.000000 5.1326293E-07 2.2427466E-04 0.000000 0.000000 0.000000 - Av 2018 12 6 3 0 2.2663178E-02 0.000000 5.0569145E-07 2.2419589E-04 0.000000 0.000000 0.000000 - Av 2018 12 6 4 0 2.2648327E-02 0.000000 4.9823177E-07 2.2411715E-04 0.000000 0.000000 0.000000 - Av 2018 12 6 5 0 2.2641785E-02 0.000000 4.9088203E-07 2.2403843E-04 0.000000 0.000000 0.000000 - Av 2018 12 6 6 0 2.2632375E-02 0.000000 4.8364075E-07 2.2395975E-04 0.000000 0.000000 0.000000 - Av 2018 12 6 7 0 2.2623979E-02 0.000000 4.7650630E-07 2.2388110E-04 0.000000 0.000000 0.000000 + Av 2018 12 5 17 0 2.1484725E-02 0.000000 5.8671623E-07 2.2614848E-04 0.000000 0.000000 0.000000 + Av 2018 12 5 18 0 2.3334276E-02 0.000000 5.7806130E-07 2.2606865E-04 0.000000 0.000000 0.000000 + Av 2018 12 5 19 0 2.2679154E-02 0.000000 5.6953400E-07 2.2598883E-04 0.000000 0.000000 0.000000 + Av 2018 12 5 20 0 2.2894952E-02 0.000000 5.6113248E-07 2.2590907E-04 0.000000 0.000000 0.000000 + Av 2018 12 5 21 0 2.2807948E-02 0.000000 5.5285489E-07 2.2582931E-04 0.000000 0.000000 0.000000 + Av 2018 12 5 22 0 2.2826247E-02 0.000000 5.4469939E-07 2.2574958E-04 0.000000 0.000000 0.000000 + Av 2018 12 5 23 0 2.2807952E-02 0.000000 5.3666423E-07 2.2566989E-04 0.000000 0.000000 0.000000 + Av 2018 12 5 24 0 2.2802401E-02 0.000000 5.2874759E-07 2.2559024E-04 0.000000 0.000000 0.000000 + Av 2018 12 6 1 0 2.2713821E-02 0.000000 5.2094771E-07 2.2435345E-04 0.000000 0.000000 0.000000 + Av 2018 12 6 2 0 2.2654183E-02 0.000000 5.1326293E-07 2.2427466E-04 0.000000 0.000000 0.000000 + Av 2018 12 6 3 0 2.2663178E-02 0.000000 5.0569145E-07 2.2419589E-04 0.000000 0.000000 0.000000 + Av 2018 12 6 4 0 2.2648327E-02 0.000000 4.9823177E-07 2.2411715E-04 0.000000 0.000000 0.000000 + Av 2018 12 6 5 0 2.2641785E-02 0.000000 4.9088203E-07 2.2403843E-04 0.000000 0.000000 0.000000 + Av 2018 12 6 6 0 2.2632375E-02 0.000000 4.8364075E-07 2.2395975E-04 0.000000 0.000000 0.000000 + Av 2018 12 6 7 0 2.2623979E-02 0.000000 4.7650630E-07 2.2388110E-04 0.000000 0.000000 0.000000 Av 2018 12 6 8 0 1.7001893E-02 0.000000 4.6947707E-07 1.4136631E-04 0.000000 0.000000 3.7470978E-04 Av 2018 12 6 9 0 5.6921346E-03 0.000000 4.6255155E-07 0.000000 0.000000 0.000000 1.6495535E-03 Av 2018 12 6 10 0 3.0964122E-05 0.000000 4.5572818E-07 0.000000 0.000000 0.000000 2.7370425E-03 @@ -8176,21 +8176,21 @@ Av 2018 12 6 14 0 1.5708207E-05 0.000000 4.2942659E-07 0.000000 0.000000 0.000000 2.7370425E-03 Av 2018 12 6 15 0 2.3209566E-05 0.000000 4.2309188E-07 0.000000 0.000000 0.000000 1.6495535E-03 Av 2018 12 6 16 0 9.5978417E-03 0.000000 4.1685061E-07 1.4073825E-04 0.000000 0.000000 3.7470978E-04 - Av 2018 12 6 17 0 2.1436919E-02 0.000000 4.1070140E-07 2.2309602E-04 0.000000 0.000000 0.000000 - Av 2018 12 6 18 0 2.2912461E-02 0.000000 4.0464292E-07 2.2301766E-04 0.000000 0.000000 0.000000 - Av 2018 12 6 19 0 2.2387940E-02 0.000000 3.9867379E-07 2.2293933E-04 0.000000 0.000000 0.000000 - Av 2018 12 6 20 0 2.2558874E-02 0.000000 3.9279274E-07 2.2286102E-04 0.000000 0.000000 0.000000 - Av 2018 12 6 21 0 2.2488005E-02 0.000000 3.8699844E-07 2.2278276E-04 0.000000 0.000000 0.000000 - Av 2018 12 6 22 0 2.2501230E-02 0.000000 3.8128960E-07 2.2270450E-04 0.000000 0.000000 0.000000 - Av 2018 12 6 23 0 2.2485230E-02 0.000000 3.7566497E-07 2.2262630E-04 0.000000 0.000000 0.000000 - Av 2018 12 6 24 0 2.2479409E-02 0.000000 3.7012333E-07 2.2254810E-04 0.000000 0.000000 0.000000 - Av 2018 12 7 1 0 2.2394441E-02 0.000000 3.6466344E-07 2.2135694E-04 0.000000 0.000000 0.000000 - Av 2018 12 7 2 0 2.2337060E-02 0.000000 3.5928409E-07 2.2127958E-04 0.000000 0.000000 0.000000 - Av 2018 12 7 3 0 2.2345778E-02 0.000000 3.5398406E-07 2.2120227E-04 0.000000 0.000000 0.000000 - Av 2018 12 7 4 0 2.2331525E-02 0.000000 3.4876223E-07 2.2112497E-04 0.000000 0.000000 0.000000 - Av 2018 12 7 5 0 2.2325274E-02 0.000000 3.4361744E-07 2.2104768E-04 0.000000 0.000000 0.000000 - Av 2018 12 7 6 0 2.2316253E-02 0.000000 3.3854855E-07 2.2097043E-04 0.000000 0.000000 0.000000 - Av 2018 12 7 7 0 2.2308210E-02 0.000000 3.3355442E-07 2.2089321E-04 0.000000 0.000000 0.000000 + Av 2018 12 6 17 0 2.1436919E-02 0.000000 4.1070140E-07 2.2309602E-04 0.000000 0.000000 0.000000 + Av 2018 12 6 18 0 2.2912461E-02 0.000000 4.0464292E-07 2.2301766E-04 0.000000 0.000000 0.000000 + Av 2018 12 6 19 0 2.2387940E-02 0.000000 3.9867379E-07 2.2293933E-04 0.000000 0.000000 0.000000 + Av 2018 12 6 20 0 2.2558874E-02 0.000000 3.9279274E-07 2.2286102E-04 0.000000 0.000000 0.000000 + Av 2018 12 6 21 0 2.2488005E-02 0.000000 3.8699844E-07 2.2278276E-04 0.000000 0.000000 0.000000 + Av 2018 12 6 22 0 2.2501230E-02 0.000000 3.8128960E-07 2.2270450E-04 0.000000 0.000000 0.000000 + Av 2018 12 6 23 0 2.2485230E-02 0.000000 3.7566497E-07 2.2262630E-04 0.000000 0.000000 0.000000 + Av 2018 12 6 24 0 2.2479409E-02 0.000000 3.7012333E-07 2.2254810E-04 0.000000 0.000000 0.000000 + Av 2018 12 7 1 0 2.2394441E-02 0.000000 3.6466344E-07 2.2135694E-04 0.000000 0.000000 0.000000 + Av 2018 12 7 2 0 2.2337060E-02 0.000000 3.5928409E-07 2.2127958E-04 0.000000 0.000000 0.000000 + Av 2018 12 7 3 0 2.2345778E-02 0.000000 3.5398406E-07 2.2120227E-04 0.000000 0.000000 0.000000 + Av 2018 12 7 4 0 2.2331525E-02 0.000000 3.4876223E-07 2.2112497E-04 0.000000 0.000000 0.000000 + Av 2018 12 7 5 0 2.2325274E-02 0.000000 3.4361744E-07 2.2104768E-04 0.000000 0.000000 0.000000 + Av 2018 12 7 6 0 2.2316253E-02 0.000000 3.3854855E-07 2.2097043E-04 0.000000 0.000000 0.000000 + Av 2018 12 7 7 0 2.2308210E-02 0.000000 3.3355442E-07 2.2089321E-04 0.000000 0.000000 0.000000 Av 2018 12 7 8 0 1.6807880E-02 0.000000 3.2863397E-07 1.4016146E-04 0.000000 0.000000 3.6661170E-04 Av 2018 12 7 9 0 5.6559118E-03 0.000000 3.2378611E-07 0.000000 0.000000 0.000000 1.6474384E-03 Av 2018 12 7 10 0 2.1674889E-05 0.000000 3.1900979E-07 0.000000 0.000000 0.000000 2.7449592E-03 @@ -8200,21 +8200,21 @@ Av 2018 12 7 14 0 2.0423960E-05 0.000000 3.0059869E-07 0.000000 0.000000 0.000000 2.7449592E-03 Av 2018 12 7 15 0 2.2362357E-05 0.000000 2.9616436E-07 0.000000 0.000000 0.000000 1.6474384E-03 Av 2018 12 7 16 0 9.4801029E-03 0.000000 0.000000 1.3954485E-04 0.000000 0.000000 3.6661170E-04 - Av 2018 12 7 17 0 2.1138586E-02 0.000000 0.000000 2.2012249E-04 0.000000 0.000000 0.000000 - Av 2018 12 7 18 0 2.2556826E-02 0.000000 0.000000 2.2004556E-04 0.000000 0.000000 0.000000 - Av 2018 12 7 19 0 2.2053240E-02 0.000000 0.000000 2.1996866E-04 0.000000 0.000000 0.000000 - Av 2018 12 7 20 0 2.2217892E-02 0.000000 0.000000 2.1989179E-04 0.000000 0.000000 0.000000 - Av 2018 12 7 21 0 2.2150198E-02 0.000000 0.000000 2.1981496E-04 0.000000 0.000000 0.000000 - Av 2018 12 7 22 0 2.2163294E-02 0.000000 0.000000 2.1973814E-04 0.000000 0.000000 0.000000 - Av 2018 12 7 23 0 2.2473149E-02 0.000000 0.000000 2.1966133E-04 0.000000 9.9999802E-03 0.000000 - Av 2018 12 7 24 0 2.2684194E-02 0.000000 0.000000 2.1958457E-04 0.000000 9.9999802E-03 0.000000 - Av 2018 12 8 1 0 2.3185868E-02 0.000000 0.000000 2.1843726E-04 0.000000 2.9999940E-02 0.000000 - Av 2018 12 8 2 0 2.2599101E-02 0.000000 0.000000 2.1836130E-04 0.000000 0.000000 0.000000 - Av 2018 12 8 3 0 2.1809733E-02 0.000000 0.000000 2.1828536E-04 0.000000 0.000000 0.000000 - Av 2018 12 8 4 0 2.2073887E-02 0.000000 0.000000 2.1820946E-04 0.000000 0.000000 0.000000 - Av 2018 12 8 5 0 2.1971725E-02 0.000000 0.000000 2.1813357E-04 0.000000 0.000000 0.000000 - Av 2018 12 8 6 0 2.1996936E-02 0.000000 0.000000 2.1805771E-04 0.000000 0.000000 0.000000 - Av 2018 12 8 7 0 2.1977864E-02 0.000000 0.000000 2.1798188E-04 0.000000 0.000000 0.000000 + Av 2018 12 7 17 0 2.1138586E-02 0.000000 0.000000 2.2012249E-04 0.000000 0.000000 0.000000 + Av 2018 12 7 18 0 2.2556826E-02 0.000000 0.000000 2.2004556E-04 0.000000 0.000000 0.000000 + Av 2018 12 7 19 0 2.2053240E-02 0.000000 0.000000 2.1996866E-04 0.000000 0.000000 0.000000 + Av 2018 12 7 20 0 2.2217892E-02 0.000000 0.000000 2.1989179E-04 0.000000 0.000000 0.000000 + Av 2018 12 7 21 0 2.2150198E-02 0.000000 0.000000 2.1981496E-04 0.000000 0.000000 0.000000 + Av 2018 12 7 22 0 2.2163294E-02 0.000000 0.000000 2.1973814E-04 0.000000 0.000000 0.000000 + Av 2018 12 7 23 0 2.2473149E-02 0.000000 0.000000 2.1966133E-04 0.000000 9.9999802E-03 0.000000 + Av 2018 12 7 24 0 2.2684194E-02 0.000000 0.000000 2.1958457E-04 0.000000 9.9999802E-03 0.000000 + Av 2018 12 8 1 0 2.3185868E-02 0.000000 0.000000 2.1843726E-04 0.000000 2.9999940E-02 0.000000 + Av 2018 12 8 2 0 2.2599101E-02 0.000000 0.000000 2.1836130E-04 0.000000 0.000000 0.000000 + Av 2018 12 8 3 0 2.1809733E-02 0.000000 0.000000 2.1828536E-04 0.000000 0.000000 0.000000 + Av 2018 12 8 4 0 2.2073887E-02 0.000000 0.000000 2.1820946E-04 0.000000 0.000000 0.000000 + Av 2018 12 8 5 0 2.1971725E-02 0.000000 0.000000 2.1813357E-04 0.000000 0.000000 0.000000 + Av 2018 12 8 6 0 2.1996936E-02 0.000000 0.000000 2.1805771E-04 0.000000 0.000000 0.000000 + Av 2018 12 8 7 0 2.1977864E-02 0.000000 0.000000 2.1798188E-04 0.000000 0.000000 0.000000 Av 2018 12 8 8 0 1.5630467E-02 0.000000 0.000000 1.2474123E-04 0.000000 0.000000 4.2347665E-04 Av 2018 12 8 9 0 4.6404009E-03 0.000000 0.000000 0.000000 0.000000 0.000000 1.9406244E-03 Av 2018 12 8 10 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.2460338E-03 @@ -8224,21 +8224,21 @@ Av 2018 12 8 14 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.2460338E-03 Av 2018 12 8 15 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.9406244E-03 Av 2018 12 8 16 0 8.4343115E-03 0.000000 0.000000 1.2413572E-04 0.000000 0.000000 4.2347665E-04 - Av 2018 12 8 17 0 2.0260822E-02 0.000000 0.000000 2.1722501E-04 0.000000 0.000000 0.000000 - Av 2018 12 8 18 0 2.2468390E-02 0.000000 0.000000 2.1714947E-04 0.000000 0.000000 0.000000 - Av 2018 12 8 19 0 2.1690536E-02 0.000000 0.000000 2.1707396E-04 0.000000 0.000000 0.000000 - Av 2018 12 8 20 0 2.1950744E-02 0.000000 0.000000 2.1699847E-04 0.000000 0.000000 0.000000 - Av 2018 12 8 21 0 2.1850012E-02 0.000000 0.000000 2.1692300E-04 0.000000 0.000000 0.000000 - Av 2018 12 8 22 0 2.1874785E-02 0.000000 0.000000 2.1684758E-04 0.000000 0.000000 0.000000 - Av 2018 12 8 23 0 2.1855922E-02 0.000000 0.000000 2.1677217E-04 0.000000 0.000000 0.000000 - Av 2018 12 8 24 0 2.1852234E-02 0.000000 0.000000 2.1669678E-04 0.000000 0.000000 0.000000 - Av 2018 12 9 1 0 2.1773301E-02 0.000000 0.000000 2.1559157E-04 0.000000 0.000000 0.000000 - Av 2018 12 9 2 0 2.1720586E-02 0.000000 0.000000 2.1551695E-04 0.000000 0.000000 0.000000 - Av 2018 12 9 3 0 2.1728778E-02 0.000000 0.000000 2.1544236E-04 0.000000 0.000000 0.000000 - Av 2018 12 9 4 0 2.1715794E-02 0.000000 0.000000 2.1536779E-04 0.000000 0.000000 0.000000 - Av 2018 12 9 5 0 2.1710178E-02 0.000000 0.000000 2.1529326E-04 0.000000 0.000000 0.000000 - Av 2018 12 9 6 0 2.1702003E-02 0.000000 0.000000 2.1521874E-04 0.000000 0.000000 0.000000 - Av 2018 12 9 7 0 2.1694722E-02 0.000000 0.000000 2.1514425E-04 0.000000 0.000000 0.000000 + Av 2018 12 8 17 0 2.0260822E-02 0.000000 0.000000 2.1722501E-04 0.000000 0.000000 0.000000 + Av 2018 12 8 18 0 2.2468390E-02 0.000000 0.000000 2.1714947E-04 0.000000 0.000000 0.000000 + Av 2018 12 8 19 0 2.1690536E-02 0.000000 0.000000 2.1707396E-04 0.000000 0.000000 0.000000 + Av 2018 12 8 20 0 2.1950744E-02 0.000000 0.000000 2.1699847E-04 0.000000 0.000000 0.000000 + Av 2018 12 8 21 0 2.1850012E-02 0.000000 0.000000 2.1692300E-04 0.000000 0.000000 0.000000 + Av 2018 12 8 22 0 2.1874785E-02 0.000000 0.000000 2.1684758E-04 0.000000 0.000000 0.000000 + Av 2018 12 8 23 0 2.1855922E-02 0.000000 0.000000 2.1677217E-04 0.000000 0.000000 0.000000 + Av 2018 12 8 24 0 2.1852234E-02 0.000000 0.000000 2.1669678E-04 0.000000 0.000000 0.000000 + Av 2018 12 9 1 0 2.1773301E-02 0.000000 0.000000 2.1559157E-04 0.000000 0.000000 0.000000 + Av 2018 12 9 2 0 2.1720586E-02 0.000000 0.000000 2.1551695E-04 0.000000 0.000000 0.000000 + Av 2018 12 9 3 0 2.1728778E-02 0.000000 0.000000 2.1544236E-04 0.000000 0.000000 0.000000 + Av 2018 12 9 4 0 2.1715794E-02 0.000000 0.000000 2.1536779E-04 0.000000 0.000000 0.000000 + Av 2018 12 9 5 0 2.1710178E-02 0.000000 0.000000 2.1529326E-04 0.000000 0.000000 0.000000 + Av 2018 12 9 6 0 2.1702003E-02 0.000000 0.000000 2.1521874E-04 0.000000 0.000000 0.000000 + Av 2018 12 9 7 0 2.1694722E-02 0.000000 0.000000 2.1514425E-04 0.000000 0.000000 0.000000 Av 2018 12 9 8 0 1.5119158E-02 0.000000 0.000000 1.1861033E-04 0.000000 0.000000 4.3845203E-04 Av 2018 12 9 9 0 4.2737364E-03 0.000000 0.000000 0.000000 0.000000 0.000000 2.0467371E-03 Av 2018 12 9 10 0 0.000000 0.000000 0.000000 0.000000 0.000000 2.9999940E-02 3.4357964E-03 @@ -8248,21 +8248,21 @@ Av 2018 12 9 14 0 0.5660293 3.5912396E-06 4.9296204E-07 0.000000 4.9163695E-02 4.9999900E-02 3.4357964E-03 Av 2018 12 9 15 0 0.4718842 3.7024995E-06 6.9431906E-07 0.000000 4.6938211E-02 4.9999900E-02 2.0467371E-03 Av 2018 12 9 16 0 0.4448526 2.5416600E-06 8.6326855E-07 1.4152125E-04 3.9295699E-02 3.9999921E-02 4.3845203E-04 - Av 2018 12 9 17 0 0.4771020 4.3928349E-06 1.0506933E-06 2.4198984E-04 4.7893614E-02 4.9999900E-02 0.000000 - Av 2018 12 9 18 0 0.6665443 9.0246967E-06 1.4241795E-06 2.4754790E-04 6.6921048E-02 6.9999859E-02 0.000000 - Av 2018 12 9 19 0 0.6962153 7.0365991E-06 1.8701203E-06 2.5403238E-04 6.1124891E-02 5.9999879E-02 0.000000 - Av 2018 12 9 20 0 0.3103138 0.000000 2.0473349E-06 2.5784469E-04 1.0231405E-02 0.000000 0.000000 - Av 2018 12 9 21 0 3.7015405E-02 0.000000 2.0171335E-06 2.5774946E-04 2.8502406E-03 0.000000 0.000000 - Av 2018 12 9 22 0 4.9167484E-02 0.000000 1.9873778E-06 2.5765426E-04 1.0864049E-03 0.000000 0.000000 - Av 2018 12 9 23 0 2.9010013E-02 0.000000 1.9580607E-06 2.5755909E-04 5.0785980E-04 0.000000 0.000000 - Av 2018 12 9 24 0 3.0475922E-02 0.000000 1.9291763E-06 2.5746395E-04 2.7307143E-04 0.000000 0.000000 - Av 2018 12 10 1 0 2.7493561E-02 2.1288778E-10 1.9007241E-06 2.5577788E-04 1.6231954E-04 0.000000 0.000000 - Av 2018 12 10 2 0 2.7258340E-02 0.000000 1.8726915E-06 2.5570716E-04 1.0396021E-04 0.000000 0.000000 - Av 2018 12 10 3 0 0.1713648 1.8414131E-06 1.8992051E-06 2.5674951E-04 2.1174962E-02 2.9999940E-02 0.000000 - Av 2018 12 10 4 0 0.1581078 0.000000 1.9250597E-06 2.5871050E-04 5.4969881E-03 0.000000 0.000000 - Av 2018 12 10 5 0 2.9971752E-02 0.000000 1.8966620E-06 2.5861512E-04 1.7940268E-03 0.000000 0.000000 - Av 2018 12 10 6 0 4.2303152E-02 0.000000 1.8686832E-06 2.5851975E-04 7.5694791E-04 0.000000 0.000000 - Av 2018 12 10 7 0 7.0354015E-02 2.0764891E-07 1.8472385E-06 2.5884961E-04 6.4991750E-03 9.9999802E-03 0.000000 + Av 2018 12 9 17 0 0.4771020 4.3928349E-06 1.0506933E-06 2.4198984E-04 4.7893614E-02 4.9999900E-02 0.000000 + Av 2018 12 9 18 0 0.6665443 9.0246967E-06 1.4241795E-06 2.4754790E-04 6.6921048E-02 6.9999859E-02 0.000000 + Av 2018 12 9 19 0 0.6962153 7.0365991E-06 1.8701203E-06 2.5403238E-04 6.1124891E-02 5.9999879E-02 0.000000 + Av 2018 12 9 20 0 0.3103138 0.000000 2.0473349E-06 2.5784469E-04 1.0231405E-02 0.000000 0.000000 + Av 2018 12 9 21 0 3.7015405E-02 0.000000 2.0171335E-06 2.5774946E-04 2.8502406E-03 0.000000 0.000000 + Av 2018 12 9 22 0 4.9167484E-02 0.000000 1.9873778E-06 2.5765426E-04 1.0864049E-03 0.000000 0.000000 + Av 2018 12 9 23 0 2.9010013E-02 0.000000 1.9580607E-06 2.5755909E-04 5.0785980E-04 0.000000 0.000000 + Av 2018 12 9 24 0 3.0475922E-02 0.000000 1.9291763E-06 2.5746395E-04 2.7307143E-04 0.000000 0.000000 + Av 2018 12 10 1 0 2.7493561E-02 2.1288778E-10 1.9007241E-06 2.5577788E-04 1.6231954E-04 0.000000 0.000000 + Av 2018 12 10 2 0 2.7258340E-02 0.000000 1.8726915E-06 2.5570716E-04 1.0396021E-04 0.000000 0.000000 + Av 2018 12 10 3 0 0.1713648 1.8414131E-06 1.8992051E-06 2.5674951E-04 2.1174962E-02 2.9999940E-02 0.000000 + Av 2018 12 10 4 0 0.1581078 0.000000 1.9250597E-06 2.5871050E-04 5.4969881E-03 0.000000 0.000000 + Av 2018 12 10 5 0 2.9971752E-02 0.000000 1.8966620E-06 2.5861512E-04 1.7940268E-03 0.000000 0.000000 + Av 2018 12 10 6 0 4.2303152E-02 0.000000 1.8686832E-06 2.5851975E-04 7.5694791E-04 0.000000 0.000000 + Av 2018 12 10 7 0 7.0354015E-02 2.0764891E-07 1.8472385E-06 2.5884961E-04 6.4991750E-03 9.9999802E-03 0.000000 Av 2018 12 10 8 0 6.5164320E-02 0.000000 1.8260802E-06 1.6276364E-04 2.3913698E-03 0.000000 4.3979951E-04 Av 2018 12 10 9 0 1.1250056E-02 0.000000 1.7991425E-06 0.000000 9.4804005E-04 0.000000 2.0887314E-03 Av 2018 12 10 10 0 5.7421955E-03 0.000000 1.7726024E-06 0.000000 4.5505690E-04 0.000000 3.5177635E-03 @@ -8272,21 +8272,21 @@ Av 2018 12 10 14 0 8.6011027E-04 0.000000 1.6702994E-06 0.000000 6.6468318E-05 0.000000 3.5177635E-03 Av 2018 12 10 15 0 6.5217586E-04 0.000000 1.6456598E-06 0.000000 4.7461701E-05 0.000000 2.0887314E-03 Av 2018 12 10 16 0 1.1542321E-02 0.000000 1.6213838E-06 1.6199789E-04 3.5098928E-05 0.000000 4.3979951E-04 - Av 2018 12 10 17 0 2.6223298E-02 0.000000 1.5974658E-06 2.5865823E-04 1.7688012E-04 0.000000 0.000000 - Av 2018 12 10 18 0 2.7441405E-02 0.000000 1.5739007E-06 2.5856268E-04 0.000000 0.000000 0.000000 - Av 2018 12 10 19 0 2.5799897E-02 0.000000 1.5506832E-06 2.5846719E-04 0.000000 0.000000 0.000000 - Av 2018 12 10 20 0 2.6354559E-02 0.000000 1.5278083E-06 2.5837176E-04 0.000000 0.000000 0.000000 - Av 2018 12 10 21 0 2.6145646E-02 0.000000 1.5052708E-06 2.5827633E-04 0.000000 0.000000 0.000000 - Av 2018 12 10 22 0 2.6202284E-02 0.000000 1.4830656E-06 2.5818095E-04 0.000000 0.000000 0.000000 - Av 2018 12 10 23 0 2.6166636E-02 0.000000 1.4611880E-06 2.5808558E-04 0.000000 0.000000 0.000000 - Av 2018 12 10 24 0 2.6163122E-02 0.000000 1.4396333E-06 2.5799026E-04 0.000000 0.000000 0.000000 - Av 2018 12 11 1 0 2.6039369E-02 0.000000 1.4183964E-06 2.5628900E-04 0.000000 0.000000 0.000000 - Av 2018 12 11 2 0 0.1020873 8.0704933E-07 1.4212861E-06 2.5701441E-04 1.0982404E-02 3.9999921E-02 0.000000 - Av 2018 12 11 3 0 0.3160325 3.3586639E-06 1.5232926E-06 2.6001022E-04 3.4773294E-02 3.9999921E-02 0.000000 - Av 2018 12 11 4 0 0.2688580 2.1484702E-07 1.6059802E-06 2.6325457E-04 1.4922609E-02 9.9999802E-03 0.000000 - Av 2018 12 11 5 0 7.0930675E-02 0.000000 1.5886304E-06 2.6392582E-04 3.7570428E-03 0.000000 0.000000 - Av 2018 12 11 6 0 4.6064988E-02 0.000000 1.5651956E-06 2.6382788E-04 1.3436215E-03 0.000000 0.000000 - Av 2018 12 11 7 0 3.3257820E-02 0.000000 1.5421065E-06 2.6372998E-04 6.0199806E-04 0.000000 0.000000 + Av 2018 12 10 17 0 2.6223298E-02 0.000000 1.5974658E-06 2.5865823E-04 1.7688012E-04 0.000000 0.000000 + Av 2018 12 10 18 0 2.7441405E-02 0.000000 1.5739007E-06 2.5856268E-04 0.000000 0.000000 0.000000 + Av 2018 12 10 19 0 2.5799897E-02 0.000000 1.5506832E-06 2.5846719E-04 0.000000 0.000000 0.000000 + Av 2018 12 10 20 0 2.6354559E-02 0.000000 1.5278083E-06 2.5837176E-04 0.000000 0.000000 0.000000 + Av 2018 12 10 21 0 2.6145646E-02 0.000000 1.5052708E-06 2.5827633E-04 0.000000 0.000000 0.000000 + Av 2018 12 10 22 0 2.6202284E-02 0.000000 1.4830656E-06 2.5818095E-04 0.000000 0.000000 0.000000 + Av 2018 12 10 23 0 2.6166636E-02 0.000000 1.4611880E-06 2.5808558E-04 0.000000 0.000000 0.000000 + Av 2018 12 10 24 0 2.6163122E-02 0.000000 1.4396333E-06 2.5799026E-04 0.000000 0.000000 0.000000 + Av 2018 12 11 1 0 2.6039369E-02 0.000000 1.4183964E-06 2.5628900E-04 0.000000 0.000000 0.000000 + Av 2018 12 11 2 0 0.1020873 8.0704933E-07 1.4212861E-06 2.5701441E-04 1.0982404E-02 3.9999921E-02 0.000000 + Av 2018 12 11 3 0 0.3160325 3.3586639E-06 1.5232926E-06 2.6001022E-04 3.4773294E-02 3.9999921E-02 0.000000 + Av 2018 12 11 4 0 0.2688580 2.1484702E-07 1.6059802E-06 2.6325457E-04 1.4922609E-02 9.9999802E-03 0.000000 + Av 2018 12 11 5 0 7.0930675E-02 0.000000 1.5886304E-06 2.6392582E-04 3.7570428E-03 0.000000 0.000000 + Av 2018 12 11 6 0 4.6064988E-02 0.000000 1.5651956E-06 2.6382788E-04 1.3436215E-03 0.000000 0.000000 + Av 2018 12 11 7 0 3.3257820E-02 0.000000 1.5421065E-06 2.6372998E-04 6.0199806E-04 0.000000 0.000000 Av 2018 12 11 8 0 2.4017386E-02 0.000000 1.5193581E-06 1.6552657E-04 3.1422664E-04 0.000000 4.4593425E-04 Av 2018 12 11 9 0 7.8437636E-03 0.000000 1.4969452E-06 0.000000 1.8279051E-04 0.000000 2.1517321E-03 Av 2018 12 11 10 0 8.8279002E-04 0.000000 1.4748628E-06 0.000000 1.1517992E-04 0.000000 3.6345629E-03 @@ -8296,21 +8296,21 @@ Av 2018 12 11 14 0 0.2723617 6.3492985E-06 1.5782387E-06 0.000000 3.9912116E-02 5.9999879E-02 3.6345629E-03 Av 2018 12 11 15 0 1.051151 4.1814081E-05 2.9895293E-06 0.000000 0.1249262 0.1399997 2.1517321E-03 Av 2018 12 11 16 0 0.8637607 3.9621655E-06 4.3055679E-06 1.8545428E-04 4.8834331E-02 3.9999921E-02 4.4593425E-04 - Av 2018 12 11 17 0 0.8387243 3.9850791E-05 5.5644823E-06 2.9127294E-04 0.1103821 0.1199998 0.000000 - Av 2018 12 11 18 0 0.9188566 8.0901691E-06 6.9265889E-06 3.0185512E-04 5.7735115E-02 4.9999900E-02 0.000000 - Av 2018 12 11 19 0 0.3642985 3.0071492E-06 7.1615891E-06 3.0730199E-04 3.4075998E-02 2.9999940E-02 0.000000 - Av 2018 12 11 20 0 0.2510265 3.3880829E-07 7.1578493E-06 3.1029977E-04 1.4416214E-02 9.9999802E-03 0.000000 - Av 2018 12 11 21 0 0.1839533 1.3590242E-06 7.1043023E-06 3.1222976E-04 1.8716790E-02 1.9999960E-02 0.000000 - Av 2018 12 11 22 0 0.1390936 0.000000 7.0410019E-06 3.1398871E-04 4.5486316E-03 0.000000 0.000000 - Av 2018 12 11 23 0 0.1343847 1.3691423E-06 6.9792231E-06 3.1496549E-04 1.5831675E-02 1.9999960E-02 0.000000 - Av 2018 12 11 24 0 0.1857937 3.4482693E-07 6.9287653E-06 3.1729389E-04 1.1678774E-02 9.9999802E-03 0.000000 - Av 2018 12 12 1 0 0.1311871 3.6846382E-07 6.8484756E-06 3.1616693E-04 1.0390268E-02 9.9999802E-03 0.000000 - Av 2018 12 12 2 0 8.9271605E-02 0.000000 6.7587489E-06 3.1703111E-04 2.8827742E-03 0.000000 0.000000 - Av 2018 12 12 3 0 3.9976865E-02 0.000000 6.6590464E-06 3.1690561E-04 1.0959815E-03 0.000000 0.000000 - Av 2018 12 12 4 0 4.0974822E-02 0.000000 6.5608151E-06 3.1678015E-04 5.1145384E-04 0.000000 0.000000 - Av 2018 12 12 5 0 3.5017192E-02 0.000000 6.4640326E-06 3.1665474E-04 2.7467092E-04 0.000000 0.000000 - Av 2018 12 12 6 0 3.4691930E-02 0.000000 6.3686784E-06 3.1652936E-04 1.6312566E-04 0.000000 0.000000 - Av 2018 12 12 7 0 3.3618286E-02 0.000000 6.2747304E-06 3.1640407E-04 1.0440646E-04 0.000000 0.000000 + Av 2018 12 11 17 0 0.8387243 3.9850791E-05 5.5644823E-06 2.9127294E-04 0.1103821 0.1199998 0.000000 + Av 2018 12 11 18 0 0.9188566 8.0901691E-06 6.9265889E-06 3.0185512E-04 5.7735115E-02 4.9999900E-02 0.000000 + Av 2018 12 11 19 0 0.3642985 3.0071492E-06 7.1615891E-06 3.0730199E-04 3.4075998E-02 2.9999940E-02 0.000000 + Av 2018 12 11 20 0 0.2510265 3.3880829E-07 7.1578493E-06 3.1029977E-04 1.4416214E-02 9.9999802E-03 0.000000 + Av 2018 12 11 21 0 0.1839533 1.3590242E-06 7.1043023E-06 3.1222976E-04 1.8716790E-02 1.9999960E-02 0.000000 + Av 2018 12 11 22 0 0.1390936 0.000000 7.0410019E-06 3.1398871E-04 4.5486316E-03 0.000000 0.000000 + Av 2018 12 11 23 0 0.1343847 1.3691423E-06 6.9792231E-06 3.1496549E-04 1.5831675E-02 1.9999960E-02 0.000000 + Av 2018 12 11 24 0 0.1857937 3.4482693E-07 6.9287653E-06 3.1729389E-04 1.1678774E-02 9.9999802E-03 0.000000 + Av 2018 12 12 1 0 0.1311871 3.6846382E-07 6.8484756E-06 3.1616693E-04 1.0390268E-02 9.9999802E-03 0.000000 + Av 2018 12 12 2 0 8.9271605E-02 0.000000 6.7587489E-06 3.1703111E-04 2.8827742E-03 0.000000 0.000000 + Av 2018 12 12 3 0 3.9976865E-02 0.000000 6.6590464E-06 3.1690561E-04 1.0959815E-03 0.000000 0.000000 + Av 2018 12 12 4 0 4.0974822E-02 0.000000 6.5608151E-06 3.1678015E-04 5.1145384E-04 0.000000 0.000000 + Av 2018 12 12 5 0 3.5017192E-02 0.000000 6.4640326E-06 3.1665474E-04 2.7467092E-04 0.000000 0.000000 + Av 2018 12 12 6 0 3.4691930E-02 0.000000 6.3686784E-06 3.1652936E-04 1.6312566E-04 0.000000 0.000000 + Av 2018 12 12 7 0 3.3618286E-02 0.000000 6.2747304E-06 3.1640407E-04 1.0440646E-04 0.000000 0.000000 Av 2018 12 12 8 0 2.7415983E-02 0.000000 6.1821684E-06 2.2940169E-04 7.0770868E-05 0.000000 3.9489617E-04 Av 2018 12 12 9 0 1.0637918E-02 0.000000 6.0909715E-06 0.000000 5.0187624E-05 0.000000 1.9330141E-03 Av 2018 12 12 10 0 6.5850839E-04 0.000000 6.0011203E-06 0.000000 3.6907688E-05 0.000000 3.2736841E-03 @@ -8320,21 +8320,21 @@ Av 2018 12 12 14 0 6.1124505E-04 0.000000 5.6547751E-06 0.000000 0.000000 0.000000 3.2736841E-03 Av 2018 12 12 15 0 5.0813693E-04 0.000000 5.5713581E-06 0.000000 0.000000 0.000000 1.9330141E-03 Av 2018 12 12 16 0 1.6075516E-02 0.000000 5.4891721E-06 2.2840142E-04 0.000000 0.000000 3.9489617E-04 - Av 2018 12 12 17 0 3.2079153E-02 0.000000 5.4081979E-06 3.1515377E-04 0.000000 0.000000 0.000000 - Av 2018 12 12 18 0 3.2392595E-02 0.000000 5.3284184E-06 3.1502900E-04 0.000000 0.000000 0.000000 - Av 2018 12 12 19 0 3.2255895E-02 0.000000 5.2498162E-06 3.1490429E-04 0.000000 0.000000 0.000000 - Av 2018 12 12 20 0 3.2275885E-02 0.000000 5.1723732E-06 3.1477964E-04 0.000000 0.000000 0.000000 - Av 2018 12 12 21 0 3.2241553E-02 0.000000 5.0960725E-06 3.1465504E-04 0.000000 0.000000 0.000000 - Av 2018 12 12 22 0 3.2226272E-02 0.000000 5.0208973E-06 3.1453048E-04 0.000000 0.000000 0.000000 - Av 2018 12 12 23 0 3.2204520E-02 0.000000 4.9468313E-06 3.1440594E-04 0.000000 0.000000 0.000000 - Av 2018 12 12 24 0 3.2185175E-02 0.000000 4.8738575E-06 3.1428150E-04 0.000000 0.000000 0.000000 - Av 2018 12 13 1 0 3.1998172E-02 0.000000 4.8019606E-06 3.1169955E-04 0.000000 0.000000 0.000000 - Av 2018 12 13 2 0 3.1869750E-02 0.000000 4.7311241E-06 3.1157714E-04 0.000000 0.000000 0.000000 - Av 2018 12 13 3 0 3.1888217E-02 0.000000 4.6613332E-06 3.1145479E-04 0.000000 0.000000 0.000000 - Av 2018 12 13 4 0 3.1855762E-02 0.000000 4.5925708E-06 3.1133246E-04 0.000000 0.000000 0.000000 - Av 2018 12 13 5 0 3.1841151E-02 0.000000 4.5248230E-06 3.1121017E-04 0.000000 0.000000 0.000000 - Av 2018 12 13 6 0 3.1820476E-02 0.000000 4.4580747E-06 3.1108793E-04 0.000000 0.000000 0.000000 - Av 2018 12 13 7 0 3.1802058E-02 0.000000 4.3923114E-06 3.1096576E-04 0.000000 0.000000 0.000000 + Av 2018 12 12 17 0 3.2079153E-02 0.000000 5.4081979E-06 3.1515377E-04 0.000000 0.000000 0.000000 + Av 2018 12 12 18 0 3.2392595E-02 0.000000 5.3284184E-06 3.1502900E-04 0.000000 0.000000 0.000000 + Av 2018 12 12 19 0 3.2255895E-02 0.000000 5.2498162E-06 3.1490429E-04 0.000000 0.000000 0.000000 + Av 2018 12 12 20 0 3.2275885E-02 0.000000 5.1723732E-06 3.1477964E-04 0.000000 0.000000 0.000000 + Av 2018 12 12 21 0 3.2241553E-02 0.000000 5.0960725E-06 3.1465504E-04 0.000000 0.000000 0.000000 + Av 2018 12 12 22 0 3.2226272E-02 0.000000 5.0208973E-06 3.1453048E-04 0.000000 0.000000 0.000000 + Av 2018 12 12 23 0 3.2204520E-02 0.000000 4.9468313E-06 3.1440594E-04 0.000000 0.000000 0.000000 + Av 2018 12 12 24 0 3.2185175E-02 0.000000 4.8738575E-06 3.1428150E-04 0.000000 0.000000 0.000000 + Av 2018 12 13 1 0 3.1998172E-02 0.000000 4.8019606E-06 3.1169955E-04 0.000000 0.000000 0.000000 + Av 2018 12 13 2 0 3.1869750E-02 0.000000 4.7311241E-06 3.1157714E-04 0.000000 0.000000 0.000000 + Av 2018 12 13 3 0 3.1888217E-02 0.000000 4.6613332E-06 3.1145479E-04 0.000000 0.000000 0.000000 + Av 2018 12 13 4 0 3.1855762E-02 0.000000 4.5925708E-06 3.1133246E-04 0.000000 0.000000 0.000000 + Av 2018 12 13 5 0 3.1841151E-02 0.000000 4.5248230E-06 3.1121017E-04 0.000000 0.000000 0.000000 + Av 2018 12 13 6 0 3.1820476E-02 0.000000 4.4580747E-06 3.1108793E-04 0.000000 0.000000 0.000000 + Av 2018 12 13 7 0 3.1802058E-02 0.000000 4.3923114E-06 3.1096576E-04 0.000000 0.000000 0.000000 Av 2018 12 13 8 0 2.5300838E-02 0.000000 4.3275177E-06 2.1568497E-04 0.000000 0.000000 4.3253941E-04 Av 2018 12 13 9 0 9.4046881E-03 0.000000 4.2636802E-06 0.000000 0.000000 0.000000 2.1443923E-03 Av 2018 12 13 10 0 2.8541926E-04 0.000000 4.2007841E-06 0.000000 0.000000 0.000000 3.6399756E-03 @@ -8344,21 +8344,21 @@ Av 2018 12 13 14 0 3.4042692E-04 0.000000 3.9583424E-06 0.000000 0.000000 0.000000 3.6399756E-03 Av 2018 12 13 15 0 3.7286239E-04 0.000000 3.8999501E-06 0.000000 0.000000 0.000000 2.1443923E-03 Av 2018 12 13 16 0 1.4965396E-02 0.000000 3.8424200E-06 2.1470955E-04 0.000000 0.000000 4.3253941E-04 - Av 2018 12 13 17 0 3.0945249E-02 0.000000 3.7857380E-06 3.0974651E-04 0.000000 0.000000 0.000000 - Av 2018 12 13 18 0 3.1833440E-02 0.000000 3.7298926E-06 3.0962483E-04 0.000000 0.000000 0.000000 - Av 2018 12 13 19 0 3.1500544E-02 0.000000 3.6748709E-06 3.0950320E-04 0.000000 0.000000 0.000000 - Av 2018 12 13 20 0 3.1592354E-02 0.000000 3.6206604E-06 3.0938163E-04 0.000000 0.000000 0.000000 - Av 2018 12 13 21 0 3.1536601E-02 0.000000 3.5672501E-06 3.0926010E-04 0.000000 0.000000 0.000000 - Av 2018 12 13 22 0 3.1532269E-02 0.000000 3.5146275E-06 3.0913862E-04 0.000000 0.000000 0.000000 - Av 2018 12 13 23 0 3.1510174E-02 0.000000 3.4627813E-06 3.0901722E-04 0.000000 0.000000 0.000000 - Av 2018 12 13 24 0 3.1494372E-02 0.000000 3.4116997E-06 3.0889586E-04 0.000000 0.000000 0.000000 - Av 2018 12 14 1 0 3.1316042E-02 0.000000 3.3613719E-06 3.0641313E-04 0.000000 0.000000 0.000000 - Av 2018 12 14 2 0 3.1194458E-02 0.000000 3.3117863E-06 3.0629369E-04 0.000000 0.000000 0.000000 - Av 2018 12 14 3 0 3.1213816E-02 0.000000 3.2629323E-06 3.0617430E-04 0.000000 0.000000 0.000000 - Av 2018 12 14 4 0 3.1184275E-02 0.000000 3.2147989E-06 3.0605495E-04 0.000000 0.000000 0.000000 - Av 2018 12 14 5 0 3.1171840E-02 0.000000 3.1673756E-06 3.0593565E-04 0.000000 0.000000 0.000000 - Av 2018 12 14 6 0 3.1153560E-02 0.000000 3.1206519E-06 3.0581641E-04 0.000000 0.000000 0.000000 - Av 2018 12 14 7 0 3.1137414E-02 0.000000 3.0746173E-06 3.0569721E-04 0.000000 0.000000 0.000000 + Av 2018 12 13 17 0 3.0945249E-02 0.000000 3.7857380E-06 3.0974651E-04 0.000000 0.000000 0.000000 + Av 2018 12 13 18 0 3.1833440E-02 0.000000 3.7298926E-06 3.0962483E-04 0.000000 0.000000 0.000000 + Av 2018 12 13 19 0 3.1500544E-02 0.000000 3.6748709E-06 3.0950320E-04 0.000000 0.000000 0.000000 + Av 2018 12 13 20 0 3.1592354E-02 0.000000 3.6206604E-06 3.0938163E-04 0.000000 0.000000 0.000000 + Av 2018 12 13 21 0 3.1536601E-02 0.000000 3.5672501E-06 3.0926010E-04 0.000000 0.000000 0.000000 + Av 2018 12 13 22 0 3.1532269E-02 0.000000 3.5146275E-06 3.0913862E-04 0.000000 0.000000 0.000000 + Av 2018 12 13 23 0 3.1510174E-02 0.000000 3.4627813E-06 3.0901722E-04 0.000000 0.000000 0.000000 + Av 2018 12 13 24 0 3.1494372E-02 0.000000 3.4116997E-06 3.0889586E-04 0.000000 0.000000 0.000000 + Av 2018 12 14 1 0 3.1316042E-02 0.000000 3.3613719E-06 3.0641313E-04 0.000000 0.000000 0.000000 + Av 2018 12 14 2 0 3.1194458E-02 0.000000 3.3117863E-06 3.0629369E-04 0.000000 0.000000 0.000000 + Av 2018 12 14 3 0 3.1213816E-02 0.000000 3.2629323E-06 3.0617430E-04 0.000000 0.000000 0.000000 + Av 2018 12 14 4 0 3.1184275E-02 0.000000 3.2147989E-06 3.0605495E-04 0.000000 0.000000 0.000000 + Av 2018 12 14 5 0 3.1171840E-02 0.000000 3.1673756E-06 3.0593565E-04 0.000000 0.000000 0.000000 + Av 2018 12 14 6 0 3.1153560E-02 0.000000 3.1206519E-06 3.0581641E-04 0.000000 0.000000 0.000000 + Av 2018 12 14 7 0 3.1137414E-02 0.000000 3.0746173E-06 3.0569721E-04 0.000000 0.000000 0.000000 Av 2018 12 14 8 0 2.5273858E-02 0.000000 3.0292620E-06 2.1974475E-04 0.000000 0.000000 3.9015137E-04 Av 2018 12 14 9 0 9.7094532E-03 0.000000 2.9845755E-06 0.000000 0.000000 0.000000 1.9556016E-03 Av 2018 12 14 10 0 1.9979345E-04 0.000000 2.9405485E-06 0.000000 0.000000 0.000000 3.3259764E-03 @@ -8368,21 +8368,21 @@ Av 2018 12 14 14 0 2.4273807E-04 0.000000 2.7708393E-06 0.000000 0.000000 0.000000 3.3259764E-03 Av 2018 12 14 15 0 2.5139906E-04 0.000000 2.7299650E-06 0.000000 0.000000 0.000000 1.9556016E-03 Av 2018 12 14 16 0 1.5129682E-02 0.000000 2.6896937E-06 2.1879314E-04 0.000000 0.000000 3.9015137E-04 - Av 2018 12 14 17 0 3.0654557E-02 0.000000 2.6500165E-06 3.0450770E-04 0.000000 0.000000 0.000000 - Av 2018 12 14 18 0 3.1069636E-02 0.000000 2.6109246E-06 3.0438902E-04 0.000000 0.000000 0.000000 - Av 2018 12 14 19 0 3.0903913E-02 0.000000 2.5724094E-06 3.0427039E-04 0.000000 0.000000 0.000000 - Av 2018 12 14 20 0 3.0940220E-02 0.000000 2.5344623E-06 3.0415176E-04 0.000000 0.000000 0.000000 - Av 2018 12 14 21 0 3.0906362E-02 0.000000 2.4970750E-06 3.0403322E-04 0.000000 0.000000 0.000000 - Av 2018 12 14 22 0 3.0896986E-02 0.000000 2.4602391E-06 3.0391471E-04 0.000000 0.000000 0.000000 - Av 2018 12 14 23 0 3.0879177E-02 0.000000 2.4239469E-06 3.0379626E-04 0.000000 0.000000 0.000000 - Av 2018 12 14 24 0 3.0864380E-02 0.000000 2.3881898E-06 3.0367784E-04 0.000000 0.000000 0.000000 - Av 2018 12 15 1 0 3.0694433E-02 0.000000 2.3529603E-06 3.0129025E-04 0.000000 0.000000 0.000000 - Av 2018 12 15 2 0 3.0578628E-02 0.000000 2.3182506E-06 3.0117368E-04 0.000000 0.000000 0.000000 - Av 2018 12 15 3 0 3.0598376E-02 0.000000 2.2840527E-06 3.0105715E-04 0.000000 0.000000 0.000000 - Av 2018 12 15 4 0 3.0571068E-02 0.000000 2.2503593E-06 3.0094071E-04 0.000000 0.000000 0.000000 - Av 2018 12 15 5 0 3.0560195E-02 0.000000 2.2171628E-06 3.0082426E-04 0.000000 0.000000 0.000000 - Av 2018 12 15 6 0 3.0543679E-02 0.000000 2.1844562E-06 3.0070791E-04 0.000000 0.000000 0.000000 - Av 2018 12 15 7 0 3.0529201E-02 0.000000 2.1522321E-06 3.0059158E-04 0.000000 0.000000 0.000000 + Av 2018 12 14 17 0 3.0654557E-02 0.000000 2.6500165E-06 3.0450770E-04 0.000000 0.000000 0.000000 + Av 2018 12 14 18 0 3.1069636E-02 0.000000 2.6109246E-06 3.0438902E-04 0.000000 0.000000 0.000000 + Av 2018 12 14 19 0 3.0903913E-02 0.000000 2.5724094E-06 3.0427039E-04 0.000000 0.000000 0.000000 + Av 2018 12 14 20 0 3.0940220E-02 0.000000 2.5344623E-06 3.0415176E-04 0.000000 0.000000 0.000000 + Av 2018 12 14 21 0 3.0906362E-02 0.000000 2.4970750E-06 3.0403322E-04 0.000000 0.000000 0.000000 + Av 2018 12 14 22 0 3.0896986E-02 0.000000 2.4602391E-06 3.0391471E-04 0.000000 0.000000 0.000000 + Av 2018 12 14 23 0 3.0879177E-02 0.000000 2.4239469E-06 3.0379626E-04 0.000000 0.000000 0.000000 + Av 2018 12 14 24 0 3.0864380E-02 0.000000 2.3881898E-06 3.0367784E-04 0.000000 0.000000 0.000000 + Av 2018 12 15 1 0 3.0694433E-02 0.000000 2.3529603E-06 3.0129025E-04 0.000000 0.000000 0.000000 + Av 2018 12 15 2 0 3.0578628E-02 0.000000 2.3182506E-06 3.0117368E-04 0.000000 0.000000 0.000000 + Av 2018 12 15 3 0 3.0598376E-02 0.000000 2.2840527E-06 3.0105715E-04 0.000000 0.000000 0.000000 + Av 2018 12 15 4 0 3.0571068E-02 0.000000 2.2503593E-06 3.0094071E-04 0.000000 0.000000 0.000000 + Av 2018 12 15 5 0 3.0560195E-02 0.000000 2.2171628E-06 3.0082426E-04 0.000000 0.000000 0.000000 + Av 2018 12 15 6 0 3.0543679E-02 0.000000 2.1844562E-06 3.0070791E-04 0.000000 0.000000 0.000000 + Av 2018 12 15 7 0 3.0529201E-02 0.000000 2.1522321E-06 3.0059158E-04 0.000000 0.000000 0.000000 Av 2018 12 15 8 0 2.4793711E-02 0.000000 2.1204833E-06 2.1649543E-04 0.000000 0.000000 3.8172657E-04 Av 2018 12 15 9 0 9.5329871E-03 0.000000 2.0892028E-06 0.000000 0.000000 0.000000 1.9309295E-03 Av 2018 12 15 10 0 1.3985539E-04 0.000000 2.0583836E-06 0.000000 0.000000 0.000000 3.2892691E-03 @@ -8392,21 +8392,21 @@ Av 2018 12 15 14 0 1.6042951E-04 0.000000 1.9395875E-06 0.000000 0.000000 0.000000 3.2892691E-03 Av 2018 12 15 15 0 1.6930263E-04 0.000000 1.9109755E-06 0.000000 0.000000 0.000000 1.9309295E-03 Av 2018 12 15 16 0 1.4829214E-02 0.000000 1.8827857E-06 2.1556679E-04 0.000000 0.000000 3.8172657E-04 - Av 2018 12 15 17 0 3.0086163E-02 0.000000 1.8550116E-06 2.9943074E-04 0.000000 0.000000 0.000000 - Av 2018 12 15 18 0 3.0470330E-02 0.000000 1.8276475E-06 2.9931491E-04 0.000000 0.000000 0.000000 - Av 2018 12 15 19 0 3.0317321E-02 0.000000 1.8006867E-06 2.9919911E-04 0.000000 0.000000 0.000000 - Av 2018 12 15 20 0 3.0351155E-02 0.000000 1.7741238E-06 2.9908336E-04 0.000000 0.000000 0.000000 - Av 2018 12 15 21 0 3.0696731E-02 0.000000 1.7479526E-06 2.9896764E-04 0.000000 9.9999802E-03 0.000000 - Av 2018 12 15 22 0 3.1319596E-02 0.000000 1.7221676E-06 2.9885198E-04 0.000000 1.9999960E-02 0.000000 - Av 2018 12 15 23 0 3.1475209E-02 0.000000 1.6967629E-06 2.9873636E-04 0.000000 1.9999960E-02 0.000000 - Av 2018 12 15 24 0 4.0482011E-02 6.3382998E-07 1.6912836E-06 2.9935542E-04 1.2656109E-03 2.9999940E-02 0.000000 - Av 2018 12 16 1 0 0.1919579 3.2021521E-06 1.7846728E-06 2.9983834E-04 2.2612711E-02 2.9999940E-02 0.000000 - Av 2018 12 16 2 0 0.2204359 3.5320986E-07 1.8676760E-06 3.0300306E-04 1.3159711E-02 9.9999802E-03 0.000000 - Av 2018 12 16 3 0 0.1821379 1.4167940E-06 1.8949034E-06 3.0491297E-04 1.8404521E-02 1.9999960E-02 0.000000 - Av 2018 12 16 4 0 0.1873382 3.5683158E-07 1.9217064E-06 3.0719928E-04 1.1944871E-02 9.9999802E-03 0.000000 - Av 2018 12 16 5 0 8.0894746E-02 0.000000 1.9043780E-06 3.0802342E-04 3.1936916E-03 0.000000 0.000000 - Av 2018 12 16 6 0 4.3735944E-02 0.000000 1.8762854E-06 3.0790333E-04 1.1861034E-03 0.000000 0.000000 - Av 2018 12 16 7 0 3.8639419E-02 0.000000 1.8486073E-06 3.0778334E-04 5.4492190E-04 0.000000 0.000000 + Av 2018 12 15 17 0 3.0086163E-02 0.000000 1.8550116E-06 2.9943074E-04 0.000000 0.000000 0.000000 + Av 2018 12 15 18 0 3.0470330E-02 0.000000 1.8276475E-06 2.9931491E-04 0.000000 0.000000 0.000000 + Av 2018 12 15 19 0 3.0317321E-02 0.000000 1.8006867E-06 2.9919911E-04 0.000000 0.000000 0.000000 + Av 2018 12 15 20 0 3.0351155E-02 0.000000 1.7741238E-06 2.9908336E-04 0.000000 0.000000 0.000000 + Av 2018 12 15 21 0 3.0696731E-02 0.000000 1.7479526E-06 2.9896764E-04 0.000000 9.9999802E-03 0.000000 + Av 2018 12 15 22 0 3.1319596E-02 0.000000 1.7221676E-06 2.9885198E-04 0.000000 1.9999960E-02 0.000000 + Av 2018 12 15 23 0 3.1475209E-02 0.000000 1.6967629E-06 2.9873636E-04 0.000000 1.9999960E-02 0.000000 + Av 2018 12 15 24 0 4.0482011E-02 6.3382998E-07 1.6912836E-06 2.9935542E-04 1.2656109E-03 2.9999940E-02 0.000000 + Av 2018 12 16 1 0 0.1919579 3.2021521E-06 1.7846728E-06 2.9983834E-04 2.2612711E-02 2.9999940E-02 0.000000 + Av 2018 12 16 2 0 0.2204359 3.5320986E-07 1.8676760E-06 3.0300306E-04 1.3159711E-02 9.9999802E-03 0.000000 + Av 2018 12 16 3 0 0.1821379 1.4167940E-06 1.8949034E-06 3.0491297E-04 1.8404521E-02 1.9999960E-02 0.000000 + Av 2018 12 16 4 0 0.1873382 3.5683158E-07 1.9217064E-06 3.0719928E-04 1.1944871E-02 9.9999802E-03 0.000000 + Av 2018 12 16 5 0 8.0894746E-02 0.000000 1.9043780E-06 3.0802342E-04 3.1936916E-03 0.000000 0.000000 + Av 2018 12 16 6 0 4.3735944E-02 0.000000 1.8762854E-06 3.0790333E-04 1.1861034E-03 0.000000 0.000000 + Av 2018 12 16 7 0 3.8639419E-02 0.000000 1.8486073E-06 3.0778334E-04 5.4492190E-04 0.000000 0.000000 Av 2018 12 16 8 0 6.9569379E-02 3.5782313E-07 1.8324525E-06 2.1598731E-04 6.3369027E-03 9.9999802E-03 4.1925200E-04 Av 2018 12 16 9 0 5.2238345E-02 0.000000 1.8164810E-06 0.000000 2.3673405E-03 0.000000 2.1360728E-03 Av 2018 12 16 10 0 6.5125152E-03 0.000000 1.7896851E-06 0.000000 9.4061147E-04 0.000000 3.6432678E-03 @@ -8416,21 +8416,21 @@ Av 2018 12 16 14 0 0.6665281 8.8023025E-06 4.2094448E-06 0.000000 5.1142607E-02 4.9999900E-02 3.6432678E-03 Av 2018 12 16 15 0 0.2780285 1.1576618E-06 4.4591807E-06 0.000000 2.1924589E-02 1.9999960E-02 2.1360728E-03 Av 2018 12 16 16 0 0.1057931 0.000000 4.4297399E-06 2.4673011E-04 4.9605216E-03 0.000000 4.1925200E-04 - Av 2018 12 16 17 0 4.8543744E-02 0.000000 4.3643940E-06 3.3882839E-04 1.6600788E-03 0.000000 0.000000 - Av 2018 12 16 18 0 4.5860093E-02 0.000000 4.3000123E-06 3.3869129E-04 7.1199838E-04 0.000000 0.000000 - Av 2018 12 16 19 0 3.7936613E-02 0.000000 4.2365805E-06 3.3855424E-04 3.6058779E-04 0.000000 0.000000 - Av 2018 12 16 20 0 3.7221350E-02 0.000000 4.1740846E-06 3.3841725E-04 2.0523679E-04 0.000000 0.000000 - Av 2018 12 16 21 0 3.5857491E-02 0.000000 4.1125104E-06 3.3828031E-04 1.2723205E-04 0.000000 0.000000 - Av 2018 12 16 22 0 3.5482027E-02 0.000000 4.0518444E-06 3.3814344E-04 8.4140534E-05 0.000000 0.000000 - Av 2018 12 16 23 0 3.5118897E-02 0.000000 3.9920733E-06 3.3800659E-04 5.8513298E-05 0.000000 0.000000 - Av 2018 12 16 24 0 3.4934599E-02 0.000000 3.9331835E-06 3.3786983E-04 4.2354986E-05 0.000000 0.000000 - Av 2018 12 17 1 0 3.5729259E-02 0.000000 3.8751632E-06 3.3492877E-04 1.9798652E-04 0.000000 0.000000 - Av 2018 12 17 2 0 3.4948386E-02 0.000000 3.8179983E-06 3.3479437E-04 0.000000 0.000000 0.000000 - Av 2018 12 17 3 0 0.2189066 6.0981438E-06 3.9543092E-06 3.3694154E-04 2.6919050E-02 3.9999921E-02 0.000000 - Av 2018 12 17 4 0 0.2524520 4.2656194E-07 4.1011713E-06 3.4122463E-04 1.4078903E-02 9.9999802E-03 0.000000 - Av 2018 12 17 5 0 8.0726549E-02 0.000000 4.0541204E-06 3.4214056E-04 3.6012297E-03 0.000000 0.000000 - Av 2018 12 17 6 0 5.2267149E-02 0.000000 3.9943156E-06 3.4200205E-04 1.3007388E-03 0.000000 0.000000 - Av 2018 12 17 7 0 4.1653357E-02 0.000000 3.9353931E-06 3.4186360E-04 5.8662775E-04 0.000000 0.000000 + Av 2018 12 16 17 0 4.8543744E-02 0.000000 4.3643940E-06 3.3882839E-04 1.6600788E-03 0.000000 0.000000 + Av 2018 12 16 18 0 4.5860093E-02 0.000000 4.3000123E-06 3.3869129E-04 7.1199838E-04 0.000000 0.000000 + Av 2018 12 16 19 0 3.7936613E-02 0.000000 4.2365805E-06 3.3855424E-04 3.6058779E-04 0.000000 0.000000 + Av 2018 12 16 20 0 3.7221350E-02 0.000000 4.1740846E-06 3.3841725E-04 2.0523679E-04 0.000000 0.000000 + Av 2018 12 16 21 0 3.5857491E-02 0.000000 4.1125104E-06 3.3828031E-04 1.2723205E-04 0.000000 0.000000 + Av 2018 12 16 22 0 3.5482027E-02 0.000000 4.0518444E-06 3.3814344E-04 8.4140534E-05 0.000000 0.000000 + Av 2018 12 16 23 0 3.5118897E-02 0.000000 3.9920733E-06 3.3800659E-04 5.8513298E-05 0.000000 0.000000 + Av 2018 12 16 24 0 3.4934599E-02 0.000000 3.9331835E-06 3.3786983E-04 4.2354986E-05 0.000000 0.000000 + Av 2018 12 17 1 0 3.5729259E-02 0.000000 3.8751632E-06 3.3492877E-04 1.9798652E-04 0.000000 0.000000 + Av 2018 12 17 2 0 3.4948386E-02 0.000000 3.8179983E-06 3.3479437E-04 0.000000 0.000000 0.000000 + Av 2018 12 17 3 0 0.2189066 6.0981438E-06 3.9543092E-06 3.3694154E-04 2.6919050E-02 3.9999921E-02 0.000000 + Av 2018 12 17 4 0 0.2524520 4.2656194E-07 4.1011713E-06 3.4122463E-04 1.4078903E-02 9.9999802E-03 0.000000 + Av 2018 12 17 5 0 8.0726549E-02 0.000000 4.0541204E-06 3.4214056E-04 3.6012297E-03 0.000000 0.000000 + Av 2018 12 17 6 0 5.2267149E-02 0.000000 3.9943156E-06 3.4200205E-04 1.3007388E-03 0.000000 0.000000 + Av 2018 12 17 7 0 4.1653357E-02 0.000000 3.9353931E-06 3.4186360E-04 5.8662775E-04 0.000000 0.000000 Av 2018 12 17 8 0 3.2129321E-02 0.000000 3.8773396E-06 2.4721323E-04 3.0760726E-04 0.000000 4.2959992E-04 Av 2018 12 17 9 0 1.2203221E-02 0.000000 3.8201433E-06 0.000000 1.7953453E-04 0.000000 2.2001970E-03 Av 2018 12 17 10 0 1.0262883E-03 0.000000 3.7637901E-06 0.000000 1.1341064E-04 0.000000 3.7559941E-03 @@ -8440,21 +8440,21 @@ Av 2018 12 17 14 0 1.7023662E-03 0.000000 3.5465689E-06 0.000000 1.8873411E-04 0.000000 3.7559941E-03 Av 2018 12 17 15 0 1.3814623E-03 2.2926741E-09 3.4943243E-06 0.000000 0.000000 1.9999960E-02 2.2001970E-03 Av 2018 12 17 16 0 8.6821549E-02 1.4076869E-06 3.4874893E-06 2.4737779E-04 1.0255618E-02 1.9999960E-02 4.2959992E-04 - Av 2018 12 17 17 0 0.4336874 1.5323549E-05 3.9671081E-06 3.4706667E-04 5.1038887E-02 5.9999879E-02 0.000000 - Av 2018 12 17 18 0 0.7263229 2.2039252E-05 5.0958438E-06 3.5692024E-04 6.7915730E-02 6.9999859E-02 0.000000 - Av 2018 12 17 19 0 0.5796669 7.6260144E-06 5.9646586E-06 3.6658748E-04 4.3982398E-02 3.9999921E-02 0.000000 - Av 2018 12 17 20 0 0.4382201 7.7939530E-06 6.3704847E-06 3.7356463E-04 4.0598597E-02 3.9999921E-02 0.000000 - Av 2018 12 17 21 0 0.5192901 1.2446565E-05 6.9272046E-06 3.8120069E-04 4.8482656E-02 4.9999900E-02 0.000000 - Av 2018 12 17 22 0 0.5585381 1.2851903E-05 7.6403257E-06 3.8989095E-04 4.9912039E-02 4.9999900E-02 0.000000 - Av 2018 12 17 23 0 0.5570598 1.3270723E-05 8.3725499E-06 3.9890502E-04 4.9987420E-02 4.9999900E-02 0.000000 - Av 2018 12 17 24 0 0.6799321 2.6853038E-05 9.5532596E-06 4.0962695E-04 6.7094341E-02 6.9999859E-02 0.000000 - Av 2018 12 18 1 0 0.4782701 2.3986133E-06 1.0361850E-05 4.1486148E-04 2.7135663E-02 1.9999960E-02 0.000000 - Av 2018 12 18 2 0 0.2266723 2.3396590E-06 1.0363895E-05 4.1893701E-04 2.1293471E-02 1.9999960E-02 0.000000 - Av 2018 12 18 3 0 0.6182311 3.7695390E-05 1.1525577E-05 4.2699344E-04 7.0590295E-02 7.9999842E-02 0.000000 - Av 2018 12 18 4 0 1.339529 1.4271364E-04 1.7299639E-05 4.4429794E-04 0.1414194 0.1499997 0.000000 - Av 2018 12 18 5 0 1.541091 1.3563439E-04 2.6245725E-05 4.6651132E-04 0.1316054 0.1299997 0.000000 - Av 2018 12 18 6 0 1.466685 1.8718159E-04 3.6618447E-05 4.8961549E-04 0.1391594 0.1399997 0.000000 - Av 2018 12 18 7 0 1.042909 4.1803731E-05 4.3726795E-05 5.0934555E-04 6.8789840E-02 5.9999879E-02 0.000000 + Av 2018 12 17 17 0 0.4336874 1.5323549E-05 3.9671081E-06 3.4706667E-04 5.1038887E-02 5.9999879E-02 0.000000 + Av 2018 12 17 18 0 0.7263229 2.2039252E-05 5.0958438E-06 3.5692024E-04 6.7915730E-02 6.9999859E-02 0.000000 + Av 2018 12 17 19 0 0.5796669 7.6260144E-06 5.9646586E-06 3.6658748E-04 4.3982398E-02 3.9999921E-02 0.000000 + Av 2018 12 17 20 0 0.4382201 7.7939530E-06 6.3704847E-06 3.7356463E-04 4.0598597E-02 3.9999921E-02 0.000000 + Av 2018 12 17 21 0 0.5192901 1.2446565E-05 6.9272046E-06 3.8120069E-04 4.8482656E-02 4.9999900E-02 0.000000 + Av 2018 12 17 22 0 0.5585381 1.2851903E-05 7.6403257E-06 3.8989095E-04 4.9912039E-02 4.9999900E-02 0.000000 + Av 2018 12 17 23 0 0.5570598 1.3270723E-05 8.3725499E-06 3.9890502E-04 4.9987420E-02 4.9999900E-02 0.000000 + Av 2018 12 17 24 0 0.6799321 2.6853038E-05 9.5532596E-06 4.0962695E-04 6.7094341E-02 6.9999859E-02 0.000000 + Av 2018 12 18 1 0 0.4782701 2.3986133E-06 1.0361850E-05 4.1486148E-04 2.7135663E-02 1.9999960E-02 0.000000 + Av 2018 12 18 2 0 0.2266723 2.3396590E-06 1.0363895E-05 4.1893701E-04 2.1293471E-02 1.9999960E-02 0.000000 + Av 2018 12 18 3 0 0.6182311 3.7695390E-05 1.1525577E-05 4.2699344E-04 7.0590295E-02 7.9999842E-02 0.000000 + Av 2018 12 18 4 0 1.339529 1.4271364E-04 1.7299639E-05 4.4429794E-04 0.1414194 0.1499997 0.000000 + Av 2018 12 18 5 0 1.541091 1.3563439E-04 2.6245725E-05 4.6651132E-04 0.1316054 0.1299997 0.000000 + Av 2018 12 18 6 0 1.466685 1.8718159E-04 3.6618447E-05 4.8961549E-04 0.1391594 0.1399997 0.000000 + Av 2018 12 18 7 0 1.042909 4.1803731E-05 4.3726795E-05 5.0934555E-04 6.8789840E-02 5.9999879E-02 0.000000 Av 2018 12 18 8 0 0.4392385 1.0880519E-05 4.4853085E-05 4.1985419E-04 3.5474438E-02 2.9999940E-02 4.5730776E-04 Av 2018 12 18 9 0 0.1917534 0.000000 4.4557986E-05 8.1002945E-06 6.9878111E-03 0.000000 2.3494672E-03 Av 2018 12 18 10 0 1.7576551E-02 0.000000 4.3900687E-05 0.000000 2.1479004E-03 0.000000 4.0129730E-03 @@ -8464,21 +8464,21 @@ Av 2018 12 18 14 0 5.4750657E-03 0.000000 4.1367028E-05 0.000000 1.4316299E-04 0.000000 4.0129730E-03 Av 2018 12 18 15 0 3.2564364E-02 1.3150253E-06 4.0801413E-05 7.7629229E-06 3.9605801E-03 2.9999940E-02 2.3494672E-03 Av 2018 12 18 16 0 0.1495405 4.0479013E-06 4.0381346E-05 4.2753422E-04 1.4279648E-02 1.9999960E-02 4.5730776E-04 - Av 2018 12 18 17 0 0.1437019 0.000000 3.9922405E-05 5.3088734E-04 3.9445246E-03 0.000000 0.000000 - Av 2018 12 18 18 0 6.3818902E-02 0.000000 3.9333489E-05 5.3063215E-04 1.3945810E-03 0.000000 0.000000 - Av 2018 12 18 19 0 6.8893321E-02 0.000000 3.8753256E-05 5.3037715E-04 6.2010909E-04 0.000000 0.000000 - Av 2018 12 18 20 0 5.9728280E-02 0.000000 3.8181584E-05 5.3012226E-04 3.2197963E-04 0.000000 0.000000 - Av 2018 12 18 21 0 5.9857767E-02 0.000000 3.7618345E-05 5.2986742E-04 1.8658716E-04 0.000000 0.000000 - Av 2018 12 18 22 0 5.8311038E-02 0.000000 3.7063415E-05 5.2961276E-04 1.1723607E-04 0.000000 0.000000 - Av 2018 12 18 23 0 5.8003902E-02 0.000000 3.6516671E-05 5.2935816E-04 7.8337107E-05 0.000000 0.000000 - Av 2018 12 18 24 0 5.7578996E-02 0.000000 3.5977995E-05 5.2910374E-04 5.4924967E-05 0.000000 0.000000 - Av 2018 12 19 1 0 5.6937549E-02 0.000000 3.5447261E-05 5.2264403E-04 4.0020881E-05 0.000000 0.000000 - Av 2018 12 19 2 0 5.7560276E-02 0.000000 3.4924360E-05 5.2239577E-04 1.9136733E-04 0.000000 0.000000 - Av 2018 12 19 3 0 5.6967571E-02 0.000000 3.4409171E-05 5.2214763E-04 0.000000 0.000000 0.000000 - Av 2018 12 19 4 0 5.5770226E-02 0.000000 3.3901582E-05 5.2189961E-04 0.000000 0.000000 0.000000 - Av 2018 12 19 5 0 5.6084391E-02 0.000000 3.3401480E-05 5.2165170E-04 0.000000 0.000000 0.000000 - Av 2018 12 19 6 0 5.5874016E-02 0.000000 3.2908756E-05 5.2140391E-04 0.000000 0.000000 0.000000 - Av 2018 12 19 7 0 5.5847041E-02 0.000000 3.2423301E-05 5.2115624E-04 0.000000 0.000000 0.000000 + Av 2018 12 18 17 0 0.1437019 0.000000 3.9922405E-05 5.3088734E-04 3.9445246E-03 0.000000 0.000000 + Av 2018 12 18 18 0 6.3818902E-02 0.000000 3.9333489E-05 5.3063215E-04 1.3945810E-03 0.000000 0.000000 + Av 2018 12 18 19 0 6.8893321E-02 0.000000 3.8753256E-05 5.3037715E-04 6.2010909E-04 0.000000 0.000000 + Av 2018 12 18 20 0 5.9728280E-02 0.000000 3.8181584E-05 5.3012226E-04 3.2197963E-04 0.000000 0.000000 + Av 2018 12 18 21 0 5.9857767E-02 0.000000 3.7618345E-05 5.2986742E-04 1.8658716E-04 0.000000 0.000000 + Av 2018 12 18 22 0 5.8311038E-02 0.000000 3.7063415E-05 5.2961276E-04 1.1723607E-04 0.000000 0.000000 + Av 2018 12 18 23 0 5.8003902E-02 0.000000 3.6516671E-05 5.2935816E-04 7.8337107E-05 0.000000 0.000000 + Av 2018 12 18 24 0 5.7578996E-02 0.000000 3.5977995E-05 5.2910374E-04 5.4924967E-05 0.000000 0.000000 + Av 2018 12 19 1 0 5.6937549E-02 0.000000 3.5447261E-05 5.2264403E-04 4.0020881E-05 0.000000 0.000000 + Av 2018 12 19 2 0 5.7560276E-02 0.000000 3.4924360E-05 5.2239577E-04 1.9136733E-04 0.000000 0.000000 + Av 2018 12 19 3 0 5.6967571E-02 0.000000 3.4409171E-05 5.2214763E-04 0.000000 0.000000 0.000000 + Av 2018 12 19 4 0 5.5770226E-02 0.000000 3.3901582E-05 5.2189961E-04 0.000000 0.000000 0.000000 + Av 2018 12 19 5 0 5.6084391E-02 0.000000 3.3401480E-05 5.2165170E-04 0.000000 0.000000 0.000000 + Av 2018 12 19 6 0 5.5874016E-02 0.000000 3.2908756E-05 5.2140391E-04 0.000000 0.000000 0.000000 + Av 2018 12 19 7 0 5.5847041E-02 0.000000 3.2423301E-05 5.2115624E-04 0.000000 0.000000 0.000000 Av 2018 12 19 8 0 4.9170606E-02 0.000000 3.1945008E-05 4.2429441E-04 0.000000 0.000000 4.3915579E-04 Av 2018 12 19 9 0 2.1278078E-02 0.000000 3.1473766E-05 2.3772882E-05 0.000000 0.000000 2.2585834E-03 Av 2018 12 19 10 0 2.1069166E-03 0.000000 3.1009480E-05 0.000000 0.000000 0.000000 3.8584333E-03 @@ -8488,21 +8488,21 @@ Av 2018 12 19 14 0 2.8687490E-03 0.000000 2.9219816E-05 0.000000 0.000000 0.000000 3.8584333E-03 Av 2018 12 19 15 0 4.3835416E-03 0.000000 2.8788780E-05 2.2290798E-05 0.000000 0.000000 2.2585834E-03 Av 2018 12 19 16 0 3.2532614E-02 0.000000 2.8364098E-05 4.2231832E-04 0.000000 0.000000 4.3915579E-04 - Av 2018 12 19 17 0 5.6442574E-02 0.000000 2.7945684E-05 5.1868608E-04 0.000000 0.000000 0.000000 - Av 2018 12 19 18 0 5.4610662E-02 0.000000 2.7533441E-05 5.1843969E-04 0.000000 0.000000 0.000000 - Av 2018 12 19 19 0 5.5158559E-02 0.000000 2.7127280E-05 5.1819347E-04 0.000000 0.000000 0.000000 - Av 2018 12 19 20 0 5.4879807E-02 0.000000 2.6727108E-05 5.1794731E-04 0.000000 0.000000 0.000000 - Av 2018 12 19 21 0 5.4889314E-02 0.000000 2.6332842E-05 5.1770126E-04 0.000000 0.000000 0.000000 - Av 2018 12 19 22 0 5.4799400E-02 0.000000 2.5944391E-05 5.1745534E-04 0.000000 0.000000 0.000000 - Av 2018 12 19 23 0 5.4744855E-02 0.000000 2.5561671E-05 5.1720953E-04 0.000000 0.000000 0.000000 - Av 2018 12 19 24 0 5.4678805E-02 0.000000 2.5184596E-05 5.1696383E-04 0.000000 0.000000 0.000000 - Av 2018 12 20 1 0 5.4213196E-02 0.000000 2.4813084E-05 5.1076722E-04 0.000000 0.000000 0.000000 - Av 2018 12 20 2 0 5.3887658E-02 0.000000 2.4447052E-05 5.1052740E-04 0.000000 0.000000 0.000000 - Av 2018 12 20 3 0 5.3918894E-02 0.000000 2.4086419E-05 5.1028765E-04 0.000000 0.000000 0.000000 - Av 2018 12 20 4 0 5.3826816E-02 0.000000 2.3731105E-05 5.1004806E-04 0.000000 0.000000 0.000000 - Av 2018 12 20 5 0 5.3778350E-02 0.000000 2.3381033E-05 5.0980854E-04 0.000000 0.000000 0.000000 - Av 2018 12 20 6 0 5.3715445E-02 0.000000 2.3036126E-05 5.0956913E-04 0.000000 0.000000 0.000000 - Av 2018 12 20 7 0 5.3658273E-02 0.000000 2.2696307E-05 5.0932984E-04 0.000000 0.000000 0.000000 + Av 2018 12 19 17 0 5.6442574E-02 0.000000 2.7945684E-05 5.1868608E-04 0.000000 0.000000 0.000000 + Av 2018 12 19 18 0 5.4610662E-02 0.000000 2.7533441E-05 5.1843969E-04 0.000000 0.000000 0.000000 + Av 2018 12 19 19 0 5.5158559E-02 0.000000 2.7127280E-05 5.1819347E-04 0.000000 0.000000 0.000000 + Av 2018 12 19 20 0 5.4879807E-02 0.000000 2.6727108E-05 5.1794731E-04 0.000000 0.000000 0.000000 + Av 2018 12 19 21 0 5.4889314E-02 0.000000 2.6332842E-05 5.1770126E-04 0.000000 0.000000 0.000000 + Av 2018 12 19 22 0 5.4799400E-02 0.000000 2.5944391E-05 5.1745534E-04 0.000000 0.000000 0.000000 + Av 2018 12 19 23 0 5.4744855E-02 0.000000 2.5561671E-05 5.1720953E-04 0.000000 0.000000 0.000000 + Av 2018 12 19 24 0 5.4678805E-02 0.000000 2.5184596E-05 5.1696383E-04 0.000000 0.000000 0.000000 + Av 2018 12 20 1 0 5.4213196E-02 0.000000 2.4813084E-05 5.1076722E-04 0.000000 0.000000 0.000000 + Av 2018 12 20 2 0 5.3887658E-02 0.000000 2.4447052E-05 5.1052740E-04 0.000000 0.000000 0.000000 + Av 2018 12 20 3 0 5.3918894E-02 0.000000 2.4086419E-05 5.1028765E-04 0.000000 0.000000 0.000000 + Av 2018 12 20 4 0 5.3826816E-02 0.000000 2.3731105E-05 5.1004806E-04 0.000000 0.000000 0.000000 + Av 2018 12 20 5 0 5.3778350E-02 0.000000 2.3381033E-05 5.0980854E-04 0.000000 0.000000 0.000000 + Av 2018 12 20 6 0 5.3715445E-02 0.000000 2.3036126E-05 5.0956913E-04 0.000000 0.000000 0.000000 + Av 2018 12 20 7 0 5.3658273E-02 0.000000 2.2696307E-05 5.0932984E-04 0.000000 0.000000 0.000000 Av 2018 12 20 8 0 4.7590904E-02 0.000000 2.2361501E-05 4.1364136E-04 0.000000 9.9999802E-03 4.3386073E-04 Av 2018 12 20 9 0 0.1861317 1.8801433E-05 2.2670747E-05 2.2482709E-05 2.4451897E-02 4.9999900E-02 2.2290160E-03 Av 2018 12 20 10 0 0.3036196 1.0035812E-05 2.3314289E-05 0.000000 2.8002113E-02 2.9999940E-02 3.8072413E-03 @@ -8512,21 +8512,21 @@ Av 2018 12 20 14 0 5.2708737E-03 0.000000 2.2294229E-05 0.000000 3.9248887E-04 0.000000 3.8072413E-03 Av 2018 12 20 15 0 7.7732750E-03 0.000000 2.1965354E-05 3.4500379E-05 2.2034753E-04 9.9999802E-03 2.2290160E-03 Av 2018 12 20 16 0 3.4313254E-02 0.000000 2.1641330E-05 4.2918467E-04 1.3521197E-04 0.000000 4.3386073E-04 - Av 2018 12 20 17 0 5.7290509E-02 0.000000 2.1322085E-05 5.2438432E-04 8.8720277E-05 0.000000 0.000000 - Av 2018 12 20 18 0 5.5215940E-02 0.000000 2.1007552E-05 5.2413472E-04 6.1319093E-05 0.000000 0.000000 - Av 2018 12 20 19 0 5.5558227E-02 0.000000 2.0697658E-05 5.2388525E-04 4.4166492E-05 0.000000 0.000000 - Av 2018 12 20 20 0 5.5170383E-02 0.000000 2.0392334E-05 5.2363583E-04 3.2894361E-05 0.000000 0.000000 - Av 2018 12 20 21 0 5.6086022E-02 0.000000 2.0091515E-05 5.2338658E-04 1.7012922E-04 0.000000 0.000000 - Av 2018 12 20 22 0 5.5469710E-02 0.000000 1.9795134E-05 5.2313745E-04 0.000000 0.000000 0.000000 - Av 2018 12 20 23 0 5.4454252E-02 0.000000 1.9503124E-05 5.2288844E-04 0.000000 0.000000 0.000000 - Av 2018 12 20 24 0 5.4734118E-02 0.000000 1.9215422E-05 5.2263960E-04 0.000000 0.000000 0.000000 - Av 2018 12 21 1 0 5.4154038E-02 0.000000 1.8931963E-05 5.1635428E-04 0.000000 0.000000 0.000000 - Av 2018 12 21 2 0 5.3873952E-02 0.000000 1.8652689E-05 5.1611138E-04 0.000000 0.000000 0.000000 - Av 2018 12 21 3 0 5.3900667E-02 0.000000 1.8377534E-05 5.1586854E-04 0.000000 0.000000 0.000000 - Av 2018 12 21 4 0 5.3821277E-02 0.000000 1.8106435E-05 5.1562587E-04 0.000000 0.000000 0.000000 - Av 2018 12 21 5 0 5.3779341E-02 0.000000 1.7839337E-05 5.1538332E-04 0.000000 0.000000 0.000000 - Av 2018 12 21 6 0 5.3724937E-02 0.000000 1.7576178E-05 5.1514083E-04 0.000000 0.000000 0.000000 - Av 2018 12 21 7 0 5.3675417E-02 0.000000 1.7316903E-05 5.1489845E-04 0.000000 0.000000 0.000000 + Av 2018 12 20 17 0 5.7290509E-02 0.000000 2.1322085E-05 5.2438432E-04 8.8720277E-05 0.000000 0.000000 + Av 2018 12 20 18 0 5.5215940E-02 0.000000 2.1007552E-05 5.2413472E-04 6.1319093E-05 0.000000 0.000000 + Av 2018 12 20 19 0 5.5558227E-02 0.000000 2.0697658E-05 5.2388525E-04 4.4166492E-05 0.000000 0.000000 + Av 2018 12 20 20 0 5.5170383E-02 0.000000 2.0392334E-05 5.2363583E-04 3.2894361E-05 0.000000 0.000000 + Av 2018 12 20 21 0 5.6086022E-02 0.000000 2.0091515E-05 5.2338658E-04 1.7012922E-04 0.000000 0.000000 + Av 2018 12 20 22 0 5.5469710E-02 0.000000 1.9795134E-05 5.2313745E-04 0.000000 0.000000 0.000000 + Av 2018 12 20 23 0 5.4454252E-02 0.000000 1.9503124E-05 5.2288844E-04 0.000000 0.000000 0.000000 + Av 2018 12 20 24 0 5.4734118E-02 0.000000 1.9215422E-05 5.2263960E-04 0.000000 0.000000 0.000000 + Av 2018 12 21 1 0 5.4154038E-02 0.000000 1.8931963E-05 5.1635428E-04 0.000000 0.000000 0.000000 + Av 2018 12 21 2 0 5.3873952E-02 0.000000 1.8652689E-05 5.1611138E-04 0.000000 0.000000 0.000000 + Av 2018 12 21 3 0 5.3900667E-02 0.000000 1.8377534E-05 5.1586854E-04 0.000000 0.000000 0.000000 + Av 2018 12 21 4 0 5.3821277E-02 0.000000 1.8106435E-05 5.1562587E-04 0.000000 0.000000 0.000000 + Av 2018 12 21 5 0 5.3779341E-02 0.000000 1.7839337E-05 5.1538332E-04 0.000000 0.000000 0.000000 + Av 2018 12 21 6 0 5.3724937E-02 0.000000 1.7576178E-05 5.1514083E-04 0.000000 0.000000 0.000000 + Av 2018 12 21 7 0 5.3675417E-02 0.000000 1.7316903E-05 5.1489845E-04 0.000000 0.000000 0.000000 Av 2018 12 21 8 0 4.8062451E-02 0.000000 1.7061451E-05 4.3306267E-04 0.000000 0.000000 3.7087995E-04 Av 2018 12 21 9 0 2.1469533E-02 0.000000 1.6809767E-05 9.6528442E-05 0.000000 0.000000 1.8994804E-03 Av 2018 12 21 10 0 1.2516339E-03 0.000000 1.6561797E-05 0.000000 0.000000 0.000000 3.2426408E-03 @@ -8536,21 +8536,21 @@ Av 2018 12 21 14 0 1.5253080E-03 0.000000 1.5605960E-05 0.000000 0.000000 0.000000 3.2426408E-03 Av 2018 12 21 15 0 7.9840729E-03 0.000000 1.5375748E-05 9.5078023E-05 0.000000 0.000000 1.8994804E-03 Av 2018 12 21 16 0 3.5022303E-02 0.000000 1.5148930E-05 4.3112878E-04 0.000000 0.000000 3.7087995E-04 - Av 2018 12 21 17 0 5.3969122E-02 0.000000 1.4925460E-05 5.1248109E-04 0.000000 0.000000 0.000000 - Av 2018 12 21 18 0 5.2871622E-02 0.000000 1.4705286E-05 5.1223999E-04 0.000000 0.000000 0.000000 - Av 2018 12 21 19 0 5.3190779E-02 0.000000 1.4488361E-05 5.1199895E-04 0.000000 0.000000 0.000000 - Av 2018 12 21 20 0 5.3017803E-02 0.000000 1.4274635E-05 5.1175809E-04 0.000000 0.000000 0.000000 - Av 2018 12 21 21 0 5.3016394E-02 0.000000 1.4064062E-05 5.1151728E-04 0.000000 0.000000 0.000000 - Av 2018 12 21 22 0 5.2955769E-02 0.000000 1.3856595E-05 5.1127665E-04 0.000000 0.000000 0.000000 - Av 2018 12 21 23 0 5.2916169E-02 0.000000 1.3652188E-05 5.1103608E-04 0.000000 0.000000 0.000000 - Av 2018 12 21 24 0 5.2869685E-02 0.000000 1.3450797E-05 5.1079562E-04 0.000000 0.000000 0.000000 - Av 2018 12 22 1 0 5.2432641E-02 0.000000 1.3252376E-05 5.0476560E-04 0.000000 0.000000 0.000000 - Av 2018 12 22 2 0 5.2132182E-02 0.000000 1.3056883E-05 5.0453079E-04 0.000000 0.000000 0.000000 - Av 2018 12 22 3 0 5.2178390E-02 0.000000 1.2864273E-05 5.0429616E-04 0.000000 0.000000 0.000000 - Av 2018 12 22 4 0 5.2104458E-02 0.000000 1.2674505E-05 5.0406158E-04 0.000000 0.000000 0.000000 - Av 2018 12 22 5 0 5.2072700E-02 0.000000 1.2487536E-05 5.0382712E-04 0.000000 0.000000 0.000000 - Av 2018 12 22 6 0 5.2026674E-02 0.000000 1.2303326E-05 5.0359278E-04 0.000000 0.000000 0.000000 - Av 2018 12 22 7 0 5.1985994E-02 0.000000 1.2121832E-05 5.0335855E-04 0.000000 0.000000 0.000000 + Av 2018 12 21 17 0 5.3969122E-02 0.000000 1.4925460E-05 5.1248109E-04 0.000000 0.000000 0.000000 + Av 2018 12 21 18 0 5.2871622E-02 0.000000 1.4705286E-05 5.1223999E-04 0.000000 0.000000 0.000000 + Av 2018 12 21 19 0 5.3190779E-02 0.000000 1.4488361E-05 5.1199895E-04 0.000000 0.000000 0.000000 + Av 2018 12 21 20 0 5.3017803E-02 0.000000 1.4274635E-05 5.1175809E-04 0.000000 0.000000 0.000000 + Av 2018 12 21 21 0 5.3016394E-02 0.000000 1.4064062E-05 5.1151728E-04 0.000000 0.000000 0.000000 + Av 2018 12 21 22 0 5.2955769E-02 0.000000 1.3856595E-05 5.1127665E-04 0.000000 0.000000 0.000000 + Av 2018 12 21 23 0 5.2916169E-02 0.000000 1.3652188E-05 5.1103608E-04 0.000000 0.000000 0.000000 + Av 2018 12 21 24 0 5.2869685E-02 0.000000 1.3450797E-05 5.1079562E-04 0.000000 0.000000 0.000000 + Av 2018 12 22 1 0 5.2432641E-02 0.000000 1.3252376E-05 5.0476560E-04 0.000000 0.000000 0.000000 + Av 2018 12 22 2 0 5.2132182E-02 0.000000 1.3056883E-05 5.0453079E-04 0.000000 0.000000 0.000000 + Av 2018 12 22 3 0 5.2178390E-02 0.000000 1.2864273E-05 5.0429616E-04 0.000000 0.000000 0.000000 + Av 2018 12 22 4 0 5.2104458E-02 0.000000 1.2674505E-05 5.0406158E-04 0.000000 0.000000 0.000000 + Av 2018 12 22 5 0 5.2072700E-02 0.000000 1.2487536E-05 5.0382712E-04 0.000000 0.000000 0.000000 + Av 2018 12 22 6 0 5.2026674E-02 0.000000 1.2303326E-05 5.0359278E-04 0.000000 0.000000 0.000000 + Av 2018 12 22 7 0 5.1985994E-02 0.000000 1.2121832E-05 5.0335855E-04 0.000000 0.000000 0.000000 Av 2018 12 22 8 0 4.6101637E-02 0.000000 1.1943016E-05 4.1742038E-04 0.000000 0.000000 3.8956391E-04 Av 2018 12 22 9 0 2.0119451E-02 0.000000 1.1766839E-05 6.6225388E-05 0.000000 0.000000 1.9848410E-03 Av 2018 12 22 10 0 7.8769552E-04 0.000000 1.1593259E-05 0.000000 0.000000 0.000000 3.3853361E-03 @@ -8560,21 +8560,21 @@ Av 2018 12 22 14 0 1.0536127E-03 0.000000 1.0924171E-05 0.000000 0.000000 0.000000 3.3853361E-03 Av 2018 12 22 15 0 5.4637012E-03 0.000000 1.0763022E-05 6.4823340E-05 0.000000 0.000000 1.9848410E-03 Av 2018 12 22 16 0 3.2164641E-02 0.000000 1.0604252E-05 4.1555104E-04 0.000000 0.000000 3.8956391E-04 - Av 2018 12 22 17 0 0.1239019 9.1573620E-06 1.0760496E-05 5.0385809E-04 9.8668337E-03 6.9999859E-02 0.000000 - Av 2018 12 22 18 0 0.8272701 1.8476983E-04 1.7233217E-05 5.1727169E-04 0.1036130 0.1199998 0.000000 - Av 2018 12 22 19 0 1.356570 4.8296802E-06 3.0617572E-05 5.4080866E-04 0.1191705 0.1199998 0.000000 - Av 2018 12 22 20 0 1.049195 1.1004206E-04 4.1288335E-05 5.6307681E-04 8.4349960E-02 7.9999842E-02 0.000000 - Av 2018 12 22 21 0 0.7010503 4.5684566E-05 4.6057987E-05 5.8064883E-04 5.4371003E-02 4.9999900E-02 0.000000 - Av 2018 12 22 22 0 0.3432652 1.8791554E-06 4.7024529E-05 5.9005839E-04 1.7223904E-02 9.9999802E-03 0.000000 - Av 2018 12 22 23 0 0.1143622 0.000000 4.6396046E-05 5.9165561E-04 4.1688788E-03 0.000000 0.000000 - Av 2018 12 22 24 0 8.5081622E-02 0.000000 4.5711629E-05 5.9136079E-04 1.4546975E-03 0.000000 0.000000 - Av 2018 12 23 1 0 0.2783278 3.0616746E-05 4.6105637E-05 5.8845832E-04 3.0500857E-02 3.9999921E-02 0.000000 - Av 2018 12 23 2 0 0.7207356 1.2284413E-04 5.0785609E-05 6.0364767E-04 7.3295459E-02 7.9999842E-02 0.000000 - Av 2018 12 23 3 0 0.4785660 0.000000 5.4312237E-05 6.1558577E-04 1.1998345E-02 0.000000 0.000000 - Av 2018 12 23 4 0 6.7210689E-02 0.000000 5.3511048E-05 6.1527593E-04 3.2041613E-03 0.000000 0.000000 - Av 2018 12 23 5 0 9.7285733E-02 0.000000 5.2721676E-05 6.1496632E-04 1.1890961E-03 0.000000 0.000000 - Av 2018 12 23 6 0 0.5778505 1.6605259E-04 5.7777368E-05 6.2405708E-04 7.2983257E-02 8.9999817E-02 0.000000 - Av 2018 12 23 7 0 0.8504364 8.0071914E-05 6.5555600E-05 6.4477668E-04 6.2688127E-02 5.9999879E-02 0.000000 + Av 2018 12 22 17 0 0.1239019 9.1573620E-06 1.0760496E-05 5.0385809E-04 9.8668337E-03 6.9999859E-02 0.000000 + Av 2018 12 22 18 0 0.8272701 1.8476983E-04 1.7233217E-05 5.1727169E-04 0.1036130 0.1199998 0.000000 + Av 2018 12 22 19 0 1.356570 4.8296802E-06 3.0617572E-05 5.4080866E-04 0.1191705 0.1199998 0.000000 + Av 2018 12 22 20 0 1.049195 1.1004206E-04 4.1288335E-05 5.6307681E-04 8.4349960E-02 7.9999842E-02 0.000000 + Av 2018 12 22 21 0 0.7010503 4.5684566E-05 4.6057987E-05 5.8064883E-04 5.4371003E-02 4.9999900E-02 0.000000 + Av 2018 12 22 22 0 0.3432652 1.8791554E-06 4.7024529E-05 5.9005839E-04 1.7223904E-02 9.9999802E-03 0.000000 + Av 2018 12 22 23 0 0.1143622 0.000000 4.6396046E-05 5.9165561E-04 4.1688788E-03 0.000000 0.000000 + Av 2018 12 22 24 0 8.5081622E-02 0.000000 4.5711629E-05 5.9136079E-04 1.4546975E-03 0.000000 0.000000 + Av 2018 12 23 1 0 0.2783278 3.0616746E-05 4.6105637E-05 5.8845832E-04 3.0500857E-02 3.9999921E-02 0.000000 + Av 2018 12 23 2 0 0.7207356 1.2284413E-04 5.0785609E-05 6.0364767E-04 7.3295459E-02 7.9999842E-02 0.000000 + Av 2018 12 23 3 0 0.4785660 0.000000 5.4312237E-05 6.1558577E-04 1.1998345E-02 0.000000 0.000000 + Av 2018 12 23 4 0 6.7210689E-02 0.000000 5.3511048E-05 6.1527593E-04 3.2041613E-03 0.000000 0.000000 + Av 2018 12 23 5 0 9.7285733E-02 0.000000 5.2721676E-05 6.1496632E-04 1.1890961E-03 0.000000 0.000000 + Av 2018 12 23 6 0 0.5778505 1.6605259E-04 5.7777368E-05 6.2405708E-04 7.2983257E-02 8.9999817E-02 0.000000 + Av 2018 12 23 7 0 0.8504364 8.0071914E-05 6.5555600E-05 6.4477668E-04 6.2688127E-02 5.9999879E-02 0.000000 Av 2018 12 23 8 0 0.3107639 0.000000 6.7400535E-05 5.6054752E-04 1.0412537E-02 0.000000 4.3028954E-04 Av 2018 12 23 9 0 4.1314777E-02 0.000000 6.6406268E-05 1.7601583E-04 2.8873226E-03 0.000000 2.1766210E-03 Av 2018 12 23 10 0 3.3359505E-02 0.000000 6.5426677E-05 0.000000 1.0973178E-03 0.000000 3.7078077E-03 @@ -8584,21 +8584,21 @@ Av 2018 12 23 14 0 0.2255559 4.8370093E-05 6.3363375E-05 0.000000 3.1521913E-02 5.9999879E-02 3.7078077E-03 Av 2018 12 23 15 0 0.2440067 1.1431304E-06 6.4173473E-05 1.8987199E-04 1.1937585E-02 9.9999802E-03 2.1766210E-03 Av 2018 12 23 16 0 0.1185301 1.6324643E-06 6.3325177E-05 5.7647342E-04 8.7996135E-03 9.9999802E-03 4.3028954E-04 - Av 2018 12 23 17 0 0.5248265 1.1511578E-04 6.6539367E-05 6.8131008E-04 5.8430538E-02 6.9999859E-02 0.000000 - Av 2018 12 23 18 0 1.252090 1.9351563E-05 8.7064320E-05 7.0659874E-04 0.1308801 0.1399997 0.000000 - Av 2018 12 23 19 0 1.785490 1.4136049E-04 1.3440479E-04 7.3897216E-04 0.1667116 0.1699997 0.000000 - Av 2018 12 23 20 0 0.9622669 1.6738786E-05 1.6414591E-04 7.6169660E-04 3.6915626E-02 1.9999960E-02 0.000000 - Av 2018 12 23 21 0 0.1119156 0.000000 1.6232510E-04 7.6613331E-04 7.1870978E-03 0.000000 0.000000 - Av 2018 12 23 22 0 0.1507976 0.000000 1.5993055E-04 7.6571899E-04 2.1934845E-03 0.000000 0.000000 - Av 2018 12 23 23 0 9.4088197E-02 0.000000 1.5757132E-04 7.6530495E-04 8.8626408E-04 0.000000 0.000000 - Av 2018 12 23 24 0 0.1014564 0.000000 1.5524690E-04 7.6489110E-04 4.3091102E-04 0.000000 0.000000 - Av 2018 12 24 1 0 9.3391031E-02 4.0741850E-09 1.5295691E-04 7.5372087E-04 2.3822195E-04 0.000000 0.000000 - Av 2018 12 24 2 0 0.3001772 6.2642241E-05 1.5296225E-04 7.5980159E-04 2.9511871E-02 3.9999921E-02 0.000000 - Av 2018 12 24 3 0 0.2742345 0.000000 1.5295619E-04 7.6812308E-04 6.8584192E-03 0.000000 0.000000 - Av 2018 12 24 4 0 9.0619341E-02 0.000000 1.5069985E-04 7.6771062E-04 2.1181023E-03 0.000000 0.000000 - Av 2018 12 24 5 0 0.1133638 0.000000 1.4847679E-04 7.6729839E-04 8.6235610E-04 0.000000 0.000000 - Av 2018 12 24 6 0 9.3571767E-02 0.000000 1.4628652E-04 7.6688634E-04 4.2146328E-04 0.000000 0.000000 - Av 2018 12 24 7 0 9.5831931E-02 0.000000 1.4412856E-04 7.6647452E-04 2.3385802E-04 0.000000 0.000000 + Av 2018 12 23 17 0 0.5248265 1.1511578E-04 6.6539367E-05 6.8131008E-04 5.8430538E-02 6.9999859E-02 0.000000 + Av 2018 12 23 18 0 1.252090 1.9351563E-05 8.7064320E-05 7.0659874E-04 0.1308801 0.1399997 0.000000 + Av 2018 12 23 19 0 1.785490 1.4136049E-04 1.3440479E-04 7.3897216E-04 0.1667116 0.1699997 0.000000 + Av 2018 12 23 20 0 0.9622669 1.6738786E-05 1.6414591E-04 7.6169660E-04 3.6915626E-02 1.9999960E-02 0.000000 + Av 2018 12 23 21 0 0.1119156 0.000000 1.6232510E-04 7.6613331E-04 7.1870978E-03 0.000000 0.000000 + Av 2018 12 23 22 0 0.1507976 0.000000 1.5993055E-04 7.6571899E-04 2.1934845E-03 0.000000 0.000000 + Av 2018 12 23 23 0 9.4088197E-02 0.000000 1.5757132E-04 7.6530495E-04 8.8626408E-04 0.000000 0.000000 + Av 2018 12 23 24 0 0.1014564 0.000000 1.5524690E-04 7.6489110E-04 4.3091102E-04 0.000000 0.000000 + Av 2018 12 24 1 0 9.3391031E-02 4.0741850E-09 1.5295691E-04 7.5372087E-04 2.3822195E-04 0.000000 0.000000 + Av 2018 12 24 2 0 0.3001772 6.2642241E-05 1.5296225E-04 7.5980159E-04 2.9511871E-02 3.9999921E-02 0.000000 + Av 2018 12 24 3 0 0.2742345 0.000000 1.5295619E-04 7.6812308E-04 6.8584192E-03 0.000000 0.000000 + Av 2018 12 24 4 0 9.0619341E-02 0.000000 1.5069985E-04 7.6771062E-04 2.1181023E-03 0.000000 0.000000 + Av 2018 12 24 5 0 0.1133638 0.000000 1.4847679E-04 7.6729839E-04 8.6235610E-04 0.000000 0.000000 + Av 2018 12 24 6 0 9.3571767E-02 0.000000 1.4628652E-04 7.6688634E-04 4.2146328E-04 0.000000 0.000000 + Av 2018 12 24 7 0 9.5831931E-02 0.000000 1.4412856E-04 7.6647452E-04 2.3385802E-04 0.000000 0.000000 Av 2018 12 24 8 0 8.6544089E-02 0.000000 1.4200243E-04 6.7435956E-04 1.4226281E-04 0.000000 4.1683347E-04 Av 2018 12 24 9 0 5.7112798E-02 0.000000 1.3990767E-04 3.0598551E-04 9.2729882E-05 0.000000 2.0893910E-03 Av 2018 12 24 10 0 2.0598181E-02 0.000000 1.3784382E-04 0.000000 6.3757754E-05 0.000000 3.5535316E-03 @@ -8608,21 +8608,21 @@ Av 2018 12 24 14 0 1.3834139E-02 0.000000 1.2988837E-04 0.000000 0.000000 0.000000 3.5535316E-03 Av 2018 12 24 15 0 3.3187650E-02 0.000000 1.2797231E-04 3.0352169E-04 0.000000 0.000000 2.0893910E-03 Av 2018 12 24 16 0 7.1870133E-02 0.000000 1.2608453E-04 6.7107449E-04 0.000000 0.000000 4.1683347E-04 - Av 2018 12 24 17 0 8.9390516E-02 0.000000 1.2422458E-04 7.6236814E-04 0.000000 0.000000 0.000000 - Av 2018 12 24 18 0 8.9243591E-02 0.000000 1.2239207E-04 7.6195865E-04 0.000000 0.000000 0.000000 - Av 2018 12 24 19 0 8.8991880E-02 0.000000 1.2058661E-04 7.6154945E-04 0.000000 0.000000 0.000000 - Av 2018 12 24 20 0 8.8780269E-02 0.000000 1.1880777E-04 7.6114037E-04 0.000000 0.000000 0.000000 - Av 2018 12 24 21 0 8.8558331E-02 0.000000 1.1705516E-04 7.6073158E-04 0.000000 0.000000 0.000000 - Av 2018 12 24 22 0 8.8343568E-02 0.000000 1.1532842E-04 7.6032302E-04 0.000000 0.000000 0.000000 - Av 2018 12 24 23 0 8.8129818E-02 0.000000 1.1362714E-04 7.5991463E-04 0.000000 0.000000 0.000000 - Av 2018 12 24 24 0 8.7919176E-02 0.000000 1.1195096E-04 7.5950648E-04 0.000000 0.000000 0.000000 - Av 2018 12 25 1 0 8.6985901E-02 0.000000 1.1029951E-04 7.4842828E-04 0.000000 0.000000 0.000000 - Av 2018 12 25 2 0 8.6308032E-02 0.000000 1.0867242E-04 7.4803212E-04 0.000000 0.000000 0.000000 - Av 2018 12 25 3 0 8.6270444E-02 0.000000 1.0706933E-04 7.4763614E-04 0.000000 0.000000 0.000000 - Av 2018 12 25 4 0 8.6013488E-02 0.000000 1.0548989E-04 7.4724044E-04 0.000000 0.000000 0.000000 - Av 2018 12 25 5 0 8.5836023E-02 0.000000 1.0393374E-04 7.4684492E-04 0.000000 0.000000 0.000000 - Av 2018 12 25 6 0 8.5634097E-02 0.000000 1.0240056E-04 7.4644957E-04 0.000000 0.000000 0.000000 - Av 2018 12 25 7 0 8.5443795E-02 0.000000 1.0088999E-04 7.4605440E-04 0.000000 0.000000 0.000000 + Av 2018 12 24 17 0 8.9390516E-02 0.000000 1.2422458E-04 7.6236814E-04 0.000000 0.000000 0.000000 + Av 2018 12 24 18 0 8.9243591E-02 0.000000 1.2239207E-04 7.6195865E-04 0.000000 0.000000 0.000000 + Av 2018 12 24 19 0 8.8991880E-02 0.000000 1.2058661E-04 7.6154945E-04 0.000000 0.000000 0.000000 + Av 2018 12 24 20 0 8.8780269E-02 0.000000 1.1880777E-04 7.6114037E-04 0.000000 0.000000 0.000000 + Av 2018 12 24 21 0 8.8558331E-02 0.000000 1.1705516E-04 7.6073158E-04 0.000000 0.000000 0.000000 + Av 2018 12 24 22 0 8.8343568E-02 0.000000 1.1532842E-04 7.6032302E-04 0.000000 0.000000 0.000000 + Av 2018 12 24 23 0 8.8129818E-02 0.000000 1.1362714E-04 7.5991463E-04 0.000000 0.000000 0.000000 + Av 2018 12 24 24 0 8.7919176E-02 0.000000 1.1195096E-04 7.5950648E-04 0.000000 0.000000 0.000000 + Av 2018 12 25 1 0 8.6985901E-02 0.000000 1.1029951E-04 7.4842828E-04 0.000000 0.000000 0.000000 + Av 2018 12 25 2 0 8.6308032E-02 0.000000 1.0867242E-04 7.4803212E-04 0.000000 0.000000 0.000000 + Av 2018 12 25 3 0 8.6270444E-02 0.000000 1.0706933E-04 7.4763614E-04 0.000000 0.000000 0.000000 + Av 2018 12 25 4 0 8.6013488E-02 0.000000 1.0548989E-04 7.4724044E-04 0.000000 0.000000 0.000000 + Av 2018 12 25 5 0 8.5836023E-02 0.000000 1.0393374E-04 7.4684492E-04 0.000000 0.000000 0.000000 + Av 2018 12 25 6 0 8.5634097E-02 0.000000 1.0240056E-04 7.4644957E-04 0.000000 0.000000 0.000000 + Av 2018 12 25 7 0 8.5443795E-02 0.000000 1.0088999E-04 7.4605440E-04 0.000000 0.000000 0.000000 Av 2018 12 25 8 0 7.9696923E-02 0.000000 9.9401703E-05 6.6423428E-04 0.000000 0.000000 3.7011466E-04 Av 2018 12 25 9 0 5.3904988E-02 0.000000 9.7935364E-05 3.4157376E-04 0.000000 0.000000 1.8349594E-03 Av 2018 12 25 10 0 2.1495271E-02 0.000000 9.6490665E-05 5.9625949E-05 0.000000 0.000000 3.1147469E-03 @@ -8632,21 +8632,21 @@ Av 2018 12 25 14 0 1.5032410E-02 0.000000 9.0921858E-05 5.8049860E-05 0.000000 0.000000 3.1147469E-03 Av 2018 12 25 15 0 3.3897974E-02 0.000000 8.9580615E-05 3.3920960E-04 0.000000 0.000000 1.8349594E-03 Av 2018 12 25 16 0 6.8194434E-02 0.000000 8.8259163E-05 6.6108216E-04 0.000000 0.000000 3.7011466E-04 - Av 2018 12 25 17 0 8.3513975E-02 0.000000 8.6957203E-05 7.4211432E-04 0.000000 0.000000 0.000000 - Av 2018 12 25 18 0 8.3508924E-02 0.000000 8.5674445E-05 7.4172142E-04 0.000000 0.000000 0.000000 - Av 2018 12 25 19 0 8.3284274E-02 0.000000 8.4410618E-05 7.4132869E-04 0.000000 0.000000 0.000000 - Av 2018 12 25 20 0 8.3138570E-02 0.000000 8.3165432E-05 7.4093626E-04 0.000000 0.000000 0.000000 - Av 2018 12 25 21 0 8.2967952E-02 0.000000 8.1938611E-05 7.4054394E-04 0.000000 0.000000 0.000000 - Av 2018 12 25 22 0 8.2808502E-02 0.000000 8.0729893E-05 7.4015185E-04 0.000000 0.000000 0.000000 - Av 2018 12 25 23 0 8.2647637E-02 0.000000 7.9539001E-05 7.3975994E-04 0.000000 0.000000 0.000000 - Av 2018 12 25 24 0 8.2489699E-02 0.000000 7.8365672E-05 7.3936832E-04 0.000000 0.000000 0.000000 - Av 2018 12 26 1 0 8.1638679E-02 0.000000 7.7209654E-05 7.2875578E-04 0.000000 0.000000 0.000000 - Av 2018 12 26 2 0 8.1031755E-02 0.000000 7.6070697E-05 7.2837551E-04 0.000000 0.000000 0.000000 - Av 2018 12 26 3 0 8.1037492E-02 0.000000 7.4948526E-05 7.2799536E-04 0.000000 0.000000 0.000000 - Av 2018 12 26 4 0 8.0832496E-02 0.000000 7.3842915E-05 7.2761544E-04 0.000000 0.000000 0.000000 - Av 2018 12 26 5 0 8.0703020E-02 0.000000 7.2753624E-05 7.2723569E-04 0.000000 0.000000 0.000000 - Av 2018 12 26 6 0 8.0549523E-02 0.000000 7.1680392E-05 7.2685612E-04 0.000000 0.000000 0.000000 - Av 2018 12 26 7 0 8.1625432E-02 0.000000 7.0622998E-05 7.2647672E-04 0.000000 1.9999960E-02 0.000000 + Av 2018 12 25 17 0 8.3513975E-02 0.000000 8.6957203E-05 7.4211432E-04 0.000000 0.000000 0.000000 + Av 2018 12 25 18 0 8.3508924E-02 0.000000 8.5674445E-05 7.4172142E-04 0.000000 0.000000 0.000000 + Av 2018 12 25 19 0 8.3284274E-02 0.000000 8.4410618E-05 7.4132869E-04 0.000000 0.000000 0.000000 + Av 2018 12 25 20 0 8.3138570E-02 0.000000 8.3165432E-05 7.4093626E-04 0.000000 0.000000 0.000000 + Av 2018 12 25 21 0 8.2967952E-02 0.000000 8.1938611E-05 7.4054394E-04 0.000000 0.000000 0.000000 + Av 2018 12 25 22 0 8.2808502E-02 0.000000 8.0729893E-05 7.4015185E-04 0.000000 0.000000 0.000000 + Av 2018 12 25 23 0 8.2647637E-02 0.000000 7.9539001E-05 7.3975994E-04 0.000000 0.000000 0.000000 + Av 2018 12 25 24 0 8.2489699E-02 0.000000 7.8365672E-05 7.3936832E-04 0.000000 0.000000 0.000000 + Av 2018 12 26 1 0 8.1638679E-02 0.000000 7.7209654E-05 7.2875578E-04 0.000000 0.000000 0.000000 + Av 2018 12 26 2 0 8.1031755E-02 0.000000 7.6070697E-05 7.2837551E-04 0.000000 0.000000 0.000000 + Av 2018 12 26 3 0 8.1037492E-02 0.000000 7.4948526E-05 7.2799536E-04 0.000000 0.000000 0.000000 + Av 2018 12 26 4 0 8.0832496E-02 0.000000 7.3842915E-05 7.2761544E-04 0.000000 0.000000 0.000000 + Av 2018 12 26 5 0 8.0703020E-02 0.000000 7.2753624E-05 7.2723569E-04 0.000000 0.000000 0.000000 + Av 2018 12 26 6 0 8.0549523E-02 0.000000 7.1680392E-05 7.2685612E-04 0.000000 0.000000 0.000000 + Av 2018 12 26 7 0 8.1625432E-02 0.000000 7.0622998E-05 7.2647672E-04 0.000000 1.9999960E-02 0.000000 Av 2018 12 26 8 0 0.1035848 1.1739826E-05 7.0005990E-05 6.4654788E-04 3.7199834E-03 2.9999940E-02 3.7483548E-04 Av 2018 12 26 9 0 0.1773564 1.5470909E-05 6.9956332E-05 3.3223353E-04 1.5752696E-02 1.9999960E-02 1.8348733E-03 Av 2018 12 26 10 0 0.3845043 9.4441733E-05 7.2906536E-05 6.3858170E-05 4.2511567E-02 4.9999900E-02 3.1074933E-03 @@ -8656,21 +8656,21 @@ Av 2018 12 26 14 0 0.1869038 4.4313190E-05 7.5750708E-05 8.8698464E-05 2.3169382E-02 3.9999921E-02 3.1074933E-03 Av 2018 12 26 15 0 0.2139961 2.4030762E-06 7.6326396E-05 3.7696501E-04 1.0858682E-02 9.9999802E-03 1.8348733E-03 Av 2018 12 26 16 0 0.1041993 0.000000 7.5287680E-05 6.9959729E-04 2.9778453E-03 0.000000 3.7483548E-04 - Av 2018 12 26 17 0 0.7145652 1.9516227E-05 9.2108217E-05 7.9508830E-04 8.9546308E-02 0.1099998 0.000000 - Av 2018 12 26 18 0 0.6584157 1.0376598E-08 1.0859229E-04 8.1308559E-04 1.4280645E-02 0.000000 0.000000 - Av 2018 12 26 19 0 8.7215491E-02 0.000000 1.0699077E-04 8.1276777E-04 3.6387416E-03 0.000000 0.000000 - Av 2018 12 26 20 0 0.1281535 0.000000 1.0541248E-04 8.1233057E-04 1.3111081E-03 0.000000 0.000000 - Av 2018 12 26 21 0 0.1365720 4.6591108E-06 1.0402827E-04 8.1373326E-04 6.8557071E-03 9.9999802E-03 0.000000 - Av 2018 12 26 22 0 0.1413765 0.000000 1.0266362E-04 8.1575807E-04 2.4422596E-03 0.000000 0.000000 - Av 2018 12 26 23 0 9.8654047E-02 0.000000 1.0114918E-04 8.1531925E-04 9.6370856E-04 0.000000 0.000000 - Av 2018 12 26 24 0 9.9784411E-02 0.000000 9.9657074E-05 8.1488065E-04 4.6112246E-04 0.000000 0.000000 - Av 2018 12 27 1 0 9.3500048E-02 4.8542614E-09 9.8187149E-05 8.0273440E-04 2.5204729E-04 0.000000 0.000000 - Av 2018 12 27 2 0 9.2535794E-02 0.000000 9.6738921E-05 8.0239476E-04 1.5163842E-04 0.000000 0.000000 - Av 2018 12 27 3 0 9.1576830E-02 0.000000 9.5311865E-05 8.0196967E-04 9.8010707E-05 0.000000 0.000000 - Av 2018 12 27 4 0 9.1084592E-02 0.000000 9.3905866E-05 8.0154481E-04 6.6945358E-05 0.000000 0.000000 - Av 2018 12 27 5 0 9.0666987E-02 0.000000 9.2520611E-05 8.0112013E-04 4.7765145E-05 0.000000 0.000000 - Av 2018 12 27 6 0 9.0352640E-02 0.000000 9.1155780E-05 8.0069568E-04 3.5300931E-05 0.000000 0.000000 - Av 2018 12 27 7 0 9.1101587E-02 0.000000 8.9811088E-05 8.0027146E-04 1.7749006E-04 0.000000 0.000000 + Av 2018 12 26 17 0 0.7145652 1.9516227E-05 9.2108217E-05 7.9508830E-04 8.9546308E-02 0.1099998 0.000000 + Av 2018 12 26 18 0 0.6584157 1.0376598E-08 1.0859229E-04 8.1308559E-04 1.4280645E-02 0.000000 0.000000 + Av 2018 12 26 19 0 8.7215491E-02 0.000000 1.0699077E-04 8.1276777E-04 3.6387416E-03 0.000000 0.000000 + Av 2018 12 26 20 0 0.1281535 0.000000 1.0541248E-04 8.1233057E-04 1.3111081E-03 0.000000 0.000000 + Av 2018 12 26 21 0 0.1365720 4.6591108E-06 1.0402827E-04 8.1373326E-04 6.8557071E-03 9.9999802E-03 0.000000 + Av 2018 12 26 22 0 0.1413765 0.000000 1.0266362E-04 8.1575807E-04 2.4422596E-03 0.000000 0.000000 + Av 2018 12 26 23 0 9.8654047E-02 0.000000 1.0114918E-04 8.1531925E-04 9.6370856E-04 0.000000 0.000000 + Av 2018 12 26 24 0 9.9784411E-02 0.000000 9.9657074E-05 8.1488065E-04 4.6112246E-04 0.000000 0.000000 + Av 2018 12 27 1 0 9.3500048E-02 4.8542614E-09 9.8187149E-05 8.0273440E-04 2.5204729E-04 0.000000 0.000000 + Av 2018 12 27 2 0 9.2535794E-02 0.000000 9.6738921E-05 8.0239476E-04 1.5163842E-04 0.000000 0.000000 + Av 2018 12 27 3 0 9.1576830E-02 0.000000 9.5311865E-05 8.0196967E-04 9.8010707E-05 0.000000 0.000000 + Av 2018 12 27 4 0 9.1084592E-02 0.000000 9.3905866E-05 8.0154481E-04 6.6945358E-05 0.000000 0.000000 + Av 2018 12 27 5 0 9.0666987E-02 0.000000 9.2520611E-05 8.0112013E-04 4.7765145E-05 0.000000 0.000000 + Av 2018 12 27 6 0 9.0352640E-02 0.000000 9.1155780E-05 8.0069568E-04 3.5300931E-05 0.000000 0.000000 + Av 2018 12 27 7 0 9.1101587E-02 0.000000 8.9811088E-05 8.0027146E-04 1.7749006E-04 0.000000 0.000000 Av 2018 12 27 8 0 8.4431529E-02 0.000000 8.8486231E-05 7.1293738E-04 0.000000 0.000000 3.9504553E-04 Av 2018 12 27 9 0 5.6700878E-02 0.000000 8.7180917E-05 3.8004911E-04 0.000000 0.000000 1.9062477E-03 Av 2018 12 27 10 0 2.3776833E-02 0.000000 8.5894862E-05 9.0615998E-05 0.000000 0.000000 3.2199272E-03 @@ -8680,21 +8680,21 @@ Av 2018 12 27 14 0 1.7124206E-02 0.000000 8.0937578E-05 8.8923611E-05 0.000000 0.000000 3.2199272E-03 Av 2018 12 27 15 0 3.6507674E-02 0.000000 7.9743622E-05 3.7751044E-04 0.000000 0.000000 1.9062477E-03 Av 2018 12 27 16 0 7.1848698E-02 0.000000 7.8567275E-05 7.0955255E-04 0.000000 0.000000 3.9504553E-04 - Av 2018 12 27 17 0 8.7891504E-02 0.000000 7.7408287E-05 7.9604040E-04 0.000000 0.000000 0.000000 - Av 2018 12 27 18 0 8.8024758E-02 0.000000 7.6266391E-05 7.9561840E-04 0.000000 0.000000 0.000000 - Av 2018 12 27 19 0 8.7767065E-02 0.000000 7.5141339E-05 7.9519663E-04 0.000000 0.000000 0.000000 - Av 2018 12 27 20 0 8.7647617E-02 0.000000 7.4032891E-05 7.9477509E-04 0.000000 0.000000 0.000000 - Av 2018 12 27 21 0 8.7482370E-02 0.000000 7.2940791E-05 7.9435372E-04 0.000000 0.000000 0.000000 - Av 2018 12 27 22 0 8.7335281E-02 0.000000 7.1864801E-05 7.9393259E-04 0.000000 0.000000 0.000000 - Av 2018 12 27 23 0 8.7184072E-02 0.000000 7.0804686E-05 7.9351163E-04 0.000000 0.000000 0.000000 - Av 2018 12 27 24 0 8.7036461E-02 0.000000 6.9760201E-05 7.9309091E-04 0.000000 0.000000 0.000000 - Av 2018 12 28 1 0 8.6756811E-02 0.000000 6.8731126E-05 7.8139058E-04 0.000000 9.9999802E-03 0.000000 - Av 2018 12 28 2 0 8.6637229E-02 8.1040491E-07 6.7746965E-05 7.8180130E-04 0.000000 9.9999802E-03 0.000000 - Av 2018 12 28 3 0 0.1218311 4.6515979E-06 6.6947840E-05 7.8439934E-04 5.1150527E-03 9.9999802E-03 0.000000 - Av 2018 12 28 4 0 0.1720581 4.6590890E-06 6.6301123E-05 7.8846578E-04 9.0705585E-03 9.9999802E-03 0.000000 - Av 2018 12 28 5 0 0.1376396 0.000000 6.5493266E-05 7.9060317E-04 2.7118777E-03 0.000000 0.000000 - Av 2018 12 28 6 0 9.3909502E-02 0.000000 6.4527136E-05 7.9018722E-04 1.0453479E-03 0.000000 0.000000 - Av 2018 12 28 7 0 9.3847692E-02 0.000000 6.3575259E-05 7.8977150E-04 4.9236539E-04 0.000000 0.000000 + Av 2018 12 27 17 0 8.7891504E-02 0.000000 7.7408287E-05 7.9604040E-04 0.000000 0.000000 0.000000 + Av 2018 12 27 18 0 8.8024758E-02 0.000000 7.6266391E-05 7.9561840E-04 0.000000 0.000000 0.000000 + Av 2018 12 27 19 0 8.7767065E-02 0.000000 7.5141339E-05 7.9519663E-04 0.000000 0.000000 0.000000 + Av 2018 12 27 20 0 8.7647617E-02 0.000000 7.4032891E-05 7.9477509E-04 0.000000 0.000000 0.000000 + Av 2018 12 27 21 0 8.7482370E-02 0.000000 7.2940791E-05 7.9435372E-04 0.000000 0.000000 0.000000 + Av 2018 12 27 22 0 8.7335281E-02 0.000000 7.1864801E-05 7.9393259E-04 0.000000 0.000000 0.000000 + Av 2018 12 27 23 0 8.7184072E-02 0.000000 7.0804686E-05 7.9351163E-04 0.000000 0.000000 0.000000 + Av 2018 12 27 24 0 8.7036461E-02 0.000000 6.9760201E-05 7.9309091E-04 0.000000 0.000000 0.000000 + Av 2018 12 28 1 0 8.6756811E-02 0.000000 6.8731126E-05 7.8139058E-04 0.000000 9.9999802E-03 0.000000 + Av 2018 12 28 2 0 8.6637229E-02 8.1040491E-07 6.7746965E-05 7.8180130E-04 0.000000 9.9999802E-03 0.000000 + Av 2018 12 28 3 0 0.1218311 4.6515979E-06 6.6947840E-05 7.8439934E-04 5.1150527E-03 9.9999802E-03 0.000000 + Av 2018 12 28 4 0 0.1720581 4.6590890E-06 6.6301123E-05 7.8846578E-04 9.0705585E-03 9.9999802E-03 0.000000 + Av 2018 12 28 5 0 0.1376396 0.000000 6.5493266E-05 7.9060317E-04 2.7118777E-03 0.000000 0.000000 + Av 2018 12 28 6 0 9.3909502E-02 0.000000 6.4527136E-05 7.9018722E-04 1.0453479E-03 0.000000 0.000000 + Av 2018 12 28 7 0 9.3847692E-02 0.000000 6.3575259E-05 7.8977150E-04 4.9236539E-04 0.000000 0.000000 Av 2018 12 28 8 0 8.2398951E-02 0.000000 6.2637424E-05 7.0155290E-04 2.6614830E-04 0.000000 3.9910484E-04 Av 2018 12 28 9 0 9.4831213E-02 4.3783348E-06 6.1874249E-05 3.7379816E-04 5.7981792E-03 9.9999802E-03 1.8955318E-03 Av 2018 12 28 10 0 0.1539631 1.6024873E-05 6.1710496E-05 9.4040181E-05 1.5347298E-02 1.9999960E-02 3.1924064E-03 @@ -8704,21 +8704,21 @@ Av 2018 12 28 14 0 0.2049071 3.5581037E-05 6.0555951E-05 1.0765763E-04 2.2599177E-02 2.9999940E-02 3.1924064E-03 Av 2018 12 28 15 0 0.2016004 2.6745145E-06 6.1064740E-05 4.0075506E-04 1.0455079E-02 9.9999802E-03 1.8955318E-03 Av 2018 12 28 16 0 0.1068971 0.000000 6.0262057E-05 7.3149649E-04 2.8960041E-03 0.000000 3.9910484E-04 - Av 2018 12 28 17 0 0.1378996 3.1994091E-06 5.9491107E-05 8.2048622E-04 6.0197692E-03 9.9999802E-03 0.000000 - Av 2018 12 28 18 0 0.1278973 0.000000 5.8730951E-05 8.2219398E-04 2.1147302E-03 0.000000 0.000000 - Av 2018 12 28 19 0 9.5367953E-02 0.000000 5.7864578E-05 8.2175137E-04 8.6128165E-04 0.000000 0.000000 - Av 2018 12 28 20 0 9.4994023E-02 0.000000 5.7010984E-05 8.2130893E-04 4.2103720E-04 0.000000 0.000000 - Av 2018 12 28 21 0 9.0684466E-02 0.000000 5.6169985E-05 8.2086679E-04 2.3366077E-04 0.000000 0.000000 - Av 2018 12 28 22 0 9.0114623E-02 0.000000 5.5341388E-05 8.2042493E-04 1.4216041E-04 0.000000 0.000000 - Av 2018 12 28 23 0 8.9183033E-02 0.000000 5.4525019E-05 8.1998319E-04 9.2671886E-05 0.000000 0.000000 - Av 2018 12 28 24 0 8.8803887E-02 0.000000 5.3720691E-05 8.1954175E-04 6.3722604E-05 0.000000 0.000000 - Av 2018 12 29 1 0 8.7650612E-02 4.9405431E-09 5.2928404E-05 8.0735702E-04 4.5709210E-05 0.000000 0.000000 - Av 2018 12 29 2 0 8.6891152E-02 0.000000 5.2147810E-05 8.0701429E-04 3.3928998E-05 0.000000 0.000000 - Av 2018 12 29 3 0 8.7864265E-02 0.000000 5.1378549E-05 8.0658641E-04 1.7331936E-04 0.000000 0.000000 - Av 2018 12 29 4 0 0.1263124 4.7462318E-06 5.0795792E-05 8.0812187E-04 5.6033386E-03 9.9999802E-03 0.000000 - Av 2018 12 29 5 0 0.1761551 4.7538974E-06 5.0396309E-05 8.1223232E-04 9.2542060E-03 9.9999802E-03 0.000000 - Av 2018 12 29 6 0 0.1387104 0.000000 4.9827559E-05 8.1437716E-04 2.7317174E-03 0.000000 0.000000 - Av 2018 12 29 7 0 9.4828457E-02 0.000000 4.9092523E-05 8.1394275E-04 1.0512684E-03 0.000000 0.000000 + Av 2018 12 28 17 0 0.1378996 3.1994091E-06 5.9491107E-05 8.2048622E-04 6.0197692E-03 9.9999802E-03 0.000000 + Av 2018 12 28 18 0 0.1278973 0.000000 5.8730951E-05 8.2219398E-04 2.1147302E-03 0.000000 0.000000 + Av 2018 12 28 19 0 9.5367953E-02 0.000000 5.7864578E-05 8.2175137E-04 8.6128165E-04 0.000000 0.000000 + Av 2018 12 28 20 0 9.4994023E-02 0.000000 5.7010984E-05 8.2130893E-04 4.2103720E-04 0.000000 0.000000 + Av 2018 12 28 21 0 9.0684466E-02 0.000000 5.6169985E-05 8.2086679E-04 2.3366077E-04 0.000000 0.000000 + Av 2018 12 28 22 0 9.0114623E-02 0.000000 5.5341388E-05 8.2042493E-04 1.4216041E-04 0.000000 0.000000 + Av 2018 12 28 23 0 8.9183033E-02 0.000000 5.4525019E-05 8.1998319E-04 9.2671886E-05 0.000000 0.000000 + Av 2018 12 28 24 0 8.8803887E-02 0.000000 5.3720691E-05 8.1954175E-04 6.3722604E-05 0.000000 0.000000 + Av 2018 12 29 1 0 8.7650612E-02 4.9405431E-09 5.2928404E-05 8.0735702E-04 4.5709210E-05 0.000000 0.000000 + Av 2018 12 29 2 0 8.6891152E-02 0.000000 5.2147810E-05 8.0701429E-04 3.3928998E-05 0.000000 0.000000 + Av 2018 12 29 3 0 8.7864265E-02 0.000000 5.1378549E-05 8.0658641E-04 1.7331936E-04 0.000000 0.000000 + Av 2018 12 29 4 0 0.1263124 4.7462318E-06 5.0795792E-05 8.0812187E-04 5.6033386E-03 9.9999802E-03 0.000000 + Av 2018 12 29 5 0 0.1761551 4.7538974E-06 5.0396309E-05 8.1223232E-04 9.2542060E-03 9.9999802E-03 0.000000 + Av 2018 12 29 6 0 0.1387104 0.000000 4.9827559E-05 8.1437716E-04 2.7317174E-03 0.000000 0.000000 + Av 2018 12 29 7 0 9.4828457E-02 0.000000 4.9092523E-05 8.1394275E-04 1.0512684E-03 0.000000 0.000000 Av 2018 12 29 8 0 8.7434143E-02 0.000000 4.8368329E-05 7.0663675E-04 4.9460854E-04 0.000000 4.8578077E-04 Av 2018 12 29 9 0 5.0490201E-02 0.000000 4.7654823E-05 3.1416659E-04 2.6715340E-04 0.000000 2.2677637E-03 Av 2018 12 29 10 0 1.3353200E-02 0.000000 4.6951838E-05 0.000000 1.5932911E-04 0.000000 3.8068565E-03 @@ -8728,21 +8728,21 @@ Av 2018 12 29 14 0 7.5901053E-03 0.000000 4.4321849E-05 0.000000 2.4739851E-04 0.000000 3.8068565E-03 Av 2018 12 29 15 0 2.7238896E-02 0.000000 4.3668031E-05 3.1380757E-04 1.4925454E-04 0.000000 2.2677637E-03 Av 2018 12 29 16 0 6.7751907E-02 0.000000 4.3023858E-05 7.0540950E-04 9.6673291E-05 9.9999802E-03 4.8578077E-04 - 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Av 2018 12 31 4 0 0.1069712 0.000000 1.4417873E-04 9.1630523E-04 0.000000 0.000000 0.000000 - Av 2018 12 31 5 0 0.1067393 0.000000 1.4205187E-04 9.1587851E-04 0.000000 0.000000 0.000000 - Av 2018 12 31 6 0 0.1064751 0.000000 1.3995638E-04 9.1545173E-04 0.000000 0.000000 0.000000 - Av 2018 12 31 7 0 0.1062263 0.000000 1.3789181E-04 9.1502490E-04 0.000000 0.000000 0.000000 + Av 2018 12 30 17 0 0.1112281 0.000000 1.6978446E-04 9.3527511E-04 0.000000 0.000000 0.000000 + Av 2018 12 30 18 0 0.1112898 0.000000 1.6727987E-04 9.3483349E-04 0.000000 0.000000 0.000000 + Av 2018 12 30 19 0 0.1108705 0.000000 1.6481223E-04 9.3439181E-04 0.000000 0.000000 0.000000 + Av 2018 12 30 20 0 0.1106234 0.000000 1.6238098E-04 9.3395007E-04 0.000000 0.000000 0.000000 + Av 2018 12 30 21 0 0.1103213 0.000000 1.5998562E-04 9.3350816E-04 0.000000 0.000000 0.000000 + Av 2018 12 30 22 0 0.1100432 0.000000 1.5762557E-04 9.3306630E-04 0.000000 0.000000 0.000000 + Av 2018 12 30 23 0 0.1097615 0.000000 1.5530035E-04 9.3262427E-04 0.000000 0.000000 0.000000 + Av 2018 12 30 24 0 0.1094858 0.000000 1.5300945E-04 9.3218230E-04 0.000000 0.000000 0.000000 + Av 2018 12 31 1 0 0.1082508 0.000000 1.5075230E-04 9.1758487E-04 0.000000 0.000000 0.000000 + Av 2018 12 31 2 0 0.1073550 0.000000 1.4852847E-04 9.1715838E-04 0.000000 0.000000 0.000000 + Av 2018 12 31 3 0 0.1073085 0.000000 1.4633745E-04 9.1673183E-04 0.000000 0.000000 0.000000 + Av 2018 12 31 4 0 0.1069712 0.000000 1.4417873E-04 9.1630523E-04 0.000000 0.000000 0.000000 + Av 2018 12 31 5 0 0.1067393 0.000000 1.4205187E-04 9.1587851E-04 0.000000 0.000000 0.000000 + Av 2018 12 31 6 0 0.1064751 0.000000 1.3995638E-04 9.1545173E-04 0.000000 0.000000 0.000000 + Av 2018 12 31 7 0 0.1062263 0.000000 1.3789181E-04 9.1502490E-04 0.000000 0.000000 0.000000 Av 2018 12 31 8 0 0.1004303 0.000000 1.3585768E-04 8.3335309E-04 0.000000 0.000000 3.6929536E-04 Av 2018 12 31 9 0 7.7196643E-02 0.000000 1.3385358E-04 5.4906501E-04 0.000000 0.000000 1.6595732E-03 Av 2018 12 31 10 0 4.9014136E-02 0.000000 1.3187903E-04 3.0539936E-04 0.000000 0.000000 2.7652034E-03 @@ -8776,11 +8776,11 @@ Av 2018 12 31 14 0 4.3098982E-02 0.000000 1.2426784E-04 3.0369073E-04 0.000000 0.000000 2.7652034E-03 Av 2018 12 31 15 0 5.9343934E-02 0.000000 1.2243469E-04 5.4650207E-04 0.000000 0.000000 1.6595732E-03 Av 2018 12 31 16 0 8.9305624E-02 0.000000 1.2062860E-04 8.2993583E-04 0.000000 0.000000 3.6929536E-04 - Av 2018 12 31 17 0 0.1034668 0.000000 1.1884913E-04 9.1075338E-04 0.000000 0.000000 0.000000 - Av 2018 12 31 18 0 0.1037867 0.000000 1.1709592E-04 9.1032597E-04 0.000000 0.000000 0.000000 - Av 2018 12 31 19 0 0.1033809 0.000000 1.1536857E-04 9.0989843E-04 0.000000 0.000000 0.000000 - Av 2018 12 31 20 0 0.1032309 0.000000 1.1366671E-04 9.0947084E-04 0.000000 0.000000 0.000000 - Av 2018 12 31 21 0 0.1029954 0.000000 1.1198995E-04 9.0904318E-04 0.000000 0.000000 0.000000 - Av 2018 12 31 22 0 0.1027930 0.000000 1.1033792E-04 9.0861553E-04 0.000000 0.000000 0.000000 - Av 2018 12 31 23 0 0.1025824 0.000000 1.0871026E-04 9.0818782E-04 0.000000 0.000000 0.000000 - Av 2018 12 31 24 0 0.1023780 0.000000 1.0710661E-04 9.0776006E-04 0.000000 0.000000 0.000000 + Av 2018 12 31 17 0 0.1034668 0.000000 1.1884913E-04 9.1075338E-04 0.000000 0.000000 0.000000 + Av 2018 12 31 18 0 0.1037867 0.000000 1.1709592E-04 9.1032597E-04 0.000000 0.000000 0.000000 + Av 2018 12 31 19 0 0.1033809 0.000000 1.1536857E-04 9.0989843E-04 0.000000 0.000000 0.000000 + Av 2018 12 31 20 0 0.1032309 0.000000 1.1366671E-04 9.0947084E-04 0.000000 0.000000 0.000000 + Av 2018 12 31 21 0 0.1029954 0.000000 1.1198995E-04 9.0904318E-04 0.000000 0.000000 0.000000 + Av 2018 12 31 22 0 0.1027930 0.000000 1.1033792E-04 9.0861553E-04 0.000000 0.000000 0.000000 + Av 2018 12 31 23 0 0.1025824 0.000000 1.0871026E-04 9.0818782E-04 0.000000 0.000000 0.000000 + Av 2018 12 31 24 0 0.1023780 0.000000 1.0710661E-04 9.0776006E-04 0.000000 0.000000 0.000000 diff --git a/tests/ipwater/data/HSPF_Test.wdm b/tests/ipwater/data/HSPF_Test.wdm new file mode 100644 index 00000000..dda4a0c5 Binary files /dev/null and b/tests/ipwater/data/HSPF_Test.wdm differ diff --git a/tests/ipwater/data/HSPF_Test240.uci b/tests/ipwater/data/HSPF_Test240.uci index b106e251..8981507a 100644 --- a/tests/ipwater/data/HSPF_Test240.uci +++ b/tests/ipwater/data/HSPF_Test240.uci @@ -13,7 +13,7 @@ WDM1 1 HSPF_Test.wdm MESSU 25 HSPF_Test.ech 26 HSPF_Test220.out 40 Flow_Test.plt - 41 HSPF_Test_Met.SEQ + 41 HSPF_Test_Met.SEQ BINO 27 HSPF_Test220.hbn END FILES @@ -190,7 +190,7 @@ PERLND *** x - x JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 1 0.09 0.10 0.10 0.14 0.17 0.18 0.18 0.18 0.17 0.15 0.12 0.10 END MON-INTERCEP - + END PERLND FTABLES @@ -220,7 +220,7 @@ PLTGEN SCALING <-range><--ymin--><--ymax--><--ivlin-><-thresh-> *** # - # YMIN YMAX IVLIN THRESH *** - 1 7 100 30 -1.0E32 + 1 7 100 30 -1.0E32 END SCALING CURV-DATA @@ -262,14 +262,14 @@ PLTGEN <-range> <-----label----> *** Curve label Line Intg Col Tran *** # - # type eqv code code *** - 1 PREC 0 0 1 + 1 PREC 0 0 1 END CURV-DATA CURV-DATA <-range> <-----label----> *** Curve label Line Intg Col Tran *** # - # type eqv code code *** - 1 PETINP 0 0 1 + 1 PETINP 0 0 1 END CURV-DATA END PLTGEN @@ -298,13 +298,13 @@ END COPY EXT SOURCES <-Volume-> SsysSgap<--Mult-->Tran <-Target vols> <-Grp> <-Member-> *** x x tem strg<-factor->strg x x x x *** -WDM 1 PREC ENGLZERO IMPLND 1 EXTNL PREC +WDM 1 PREC ENGLZERO IMPLND 1 EXTNL PREC WDM 2 HPET ENGL IMPLND 1 EXTNL PETINP -WDM 1 PREC ENGLZERO PERLND 1 EXTNL PREC +WDM 1 PREC ENGLZERO PERLND 1 EXTNL PREC WDM 2 HPET ENGL PERLND 1 EXTNL PETINP -WDM 1 PREC ENGLZERO RCHRES 1 EXTNL PREC -WDM 2 HPET ENGL RCHRES 1 EXTNL POTEV -WDM 1 PREC ENGLZERO COPY 1 INPUT MEAN 1 +WDM 1 PREC ENGLZERO RCHRES 1 EXTNL PREC +WDM 2 HPET ENGL RCHRES 1 EXTNL POTEV +WDM 1 PREC ENGLZERO COPY 1 INPUT MEAN 1 WDM 2 HPET ENGL COPY 1 INPUT MEAN 2 END EXT SOURCES @@ -328,19 +328,19 @@ END SCHEMATIC MASS-LINK 1 <-Volume-> <-Grp> <-Member-><--Mult--> <-Target vols> <-Grp> <-Member-> *** x x<-factor-> x x *** -IMPLND IWATER SURO 0.0833333 RCHRES INFLOW IVOL +IMPLND IWATER SURO 0.0833333 RCHRES INFLOW IVOL END MASS-LINK 1 MASS-LINK 2 <-Volume-> <-Grp> <-Member-><--Mult--> <-Target vols> <-Grp> <-Member-> *** x x<-factor-> x x *** -PERLND PWATER PERO 0.0833333 RCHRES INFLOW IVOL +PERLND PWATER PERO 0.0833333 RCHRES INFLOW IVOL END MASS-LINK 2 MASS-LINK 3 <-Volume-> <-Grp> <-Member-><--Mult--> <-Target vols> <-Grp> <-Member-> *** x x<-factor-> x x *** -RCHRES ROFLOW RCHRES INFLOW +RCHRES ROFLOW RCHRES INFLOW END MASS-LINK 3 - + END RUN diff --git a/tests/ipwater/data/make_uci_data.py b/tests/ipwater/data/make_uci_data.py index 84181cca..0b148c34 100644 --- a/tests/ipwater/data/make_uci_data.py +++ b/tests/ipwater/data/make_uci_data.py @@ -1,10 +1,9 @@ import json import os - from pathlib import Path -from hsp2.hsp2tools import readUCI from hsp2.hsp2io.hdf import HDF5 +from hsp2.hsp2tools import readUCI this_dir = Path(__file__).parent diff --git a/tests/ipwater/data/uci_data.json b/tests/ipwater/data/uci_data.json index 57679de9..0d18f338 100644 --- a/tests/ipwater/data/uci_data.json +++ b/tests/ipwater/data/uci_data.json @@ -217,4 +217,4 @@ "stop": "2019-01-01 00:00:00", "units": 1 } -} \ No newline at end of file +} diff --git a/tests/ipwater/test_ipwater.py b/tests/ipwater/test_ipwater.py index 1df3d497..50e7ebe4 100644 --- a/tests/ipwater/test_ipwater.py +++ b/tests/ipwater/test_ipwater.py @@ -3,13 +3,11 @@ import pandas as pd import pytest - +from hsp2.hsp2.IWATER import iwater +from hsp2.hsp2.PWATER import pwater from numba import types from numba.typed import Dict -from hsp2.hsp2.PWATER import pwater -from hsp2.hsp2.IWATER import iwater - data_path = Path(__file__).parent / "data" diff --git a/tests/land_spec/hwmA51800.uci b/tests/land_spec/HSP2Results/hwmA51800.uci similarity index 81% rename from tests/land_spec/hwmA51800.uci rename to tests/land_spec/HSP2Results/hwmA51800.uci index 5575bcbf..92e30eb4 100644 --- a/tests/land_spec/hwmA51800.uci +++ b/tests/land_spec/HSP2Results/hwmA51800.uci @@ -1,5 +1,5 @@ RUN - + GLOBAL A51800 hwm | P5 | p532cal_06 | VA,SUFFOLK START 1984/ 1/ 1 END 2005/12/31 @@ -55,20 +55,20 @@ SPEC-ACTIONS ***Action Lines for fertilizer IF (prec < 0.1) THEN - PERLND 1 DY 11984 1 1 12 2 3 FNO3 += 0. + PERLND 1 DY 11984 1 1 12 2 3 FNO3 += 0. PERLND 1 DY 11984 2 1 12 2 3 FNO3 += 0.090044 PERLND 1 DY 11984 3 1 12 2 3 FNO3 += 1.917460 PERLND 1 DY 11984 4 1 12 2 3 FNO3 += 2.733176 PERLND 1 DY 11984 5 1 12 2 3 FNO3 += 0.123E-06 PERLND 1 DY 11984 6 1 12 2 3 FNO3 += 6.302083 PERLND 1 DY 11984 7 1 12 2 3 FNO3 += 0.207089 +END IF ***Action Lines for Adjusting Refractory Storage *** commented out for testing -*** PERLND 1 1984 1 1 3 SPRON -= 0. YR 1 22 -*** PERLND 1 1984 1 1 3 UPRON -= 38.97500 YR 1 22 -*** PERLND 1 1984 1 1 3 LPRON -= 10.92700 YR 1 22 -*** PERLND 1 1984 1 1 3 APRON -= 6.131000 YR 1 22 - + PERLND 1 1984 1 1 3 SPRON -= 0. YR 1 22 + PERLND 1 1984 1 1 3 UPRON -= 38.97500 YR 1 22 + PERLND 1 1984 1 1 3 LPRON -= 10.92700 YR 1 22 + PERLND 1 1984 1 1 3 APRON -= 6.131000 YR 1 22 END SPEC-ACTIONS PERLND @@ -89,7 +89,7 @@ PERLND ATEMP-DAT # # ELDAT AIRTMP *** - 1 0. 23.1476 + 1 0. 23.1476 END ATEMP-DAT ICE-FLAG @@ -99,22 +99,22 @@ PERLND SNOW-PARM1 # # LAT ELEV SHADE SNOWCF COVIND *** - 1 36.69108 55.78 0.05 1.3 1.08 + 1 36.69108 55.78 0.05 1.3 1.08 END SNOW-PARM1 SNOW-PARM2 # # RDCSN TSNOW SNOEVP CCFACT MWATER MGMELT *** - 1 0.12 32. 0.13 0.5 0.03 0.03 + 1 0.12 32. 0.13 0.5 0.03 0.03 END SNOW-PARM2 SNOW-INIT1 # # PACK-SNOW PACK-ICE PACK-WATR RDENPF DULL PAKTMP *** - 1 0. 0. 0. 0.15 100. 30. + 1 0. 0. 0. 0.15 100. 30. END SNOW-INIT1 SNOW-INIT2 # # COVINX XLNMLT SKYCLR *** - 1 1.08 0. 0.9 + 1 1.08 0. 0.9 END SNOW-INIT2 PWAT-PARM1 @@ -134,27 +134,27 @@ PERLND PWAT-PARM4 # # CEPSC UZSN NSUR INTFW IRC LZETP *** - 1 0.7 2. 0.435477 + 1 0.7 2. 0.435477 END PWAT-PARM4 MON-INTERCEP # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 .067 .065 .062 .06 .064 .085 .138 .15 .146 .109 .087 .077 + 1 .067 .065 .062 .06 .064 .085 .138 .15 .146 .109 .087 .077 END MON-INTERCEP MON-UZSN # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 .672 .672 .672 .672 .672 .7841.064 1.12 1.12 .896 .784 .728 + 1 .672 .672 .672 .672 .672 .7841.064 1.12 1.12 .896 .784 .728 END MON-UZSN MON-MANNING # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 .2028.2028.1971.2103.2804.3505.3692.3594.3262.2283.2085.2028 + 1 .2028.2028.1971.2103.2804.3505.3692.3594.3262.2283.2085.2028 END MON-MANNING MON-LZETPARM # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 .232 .221 .208 .2 .218 .312 .547 .6 .582 .416 .322 .276 + 1 .232 .221 .208 .2 .218 .312 .547 .6 .582 .416 .322 .276 END MON-LZETPARM PWAT-STATE1 @@ -169,27 +169,27 @@ PERLND SED-PARM2 # - # SMPF KRER JRER AFFIX COVER NVSI *** - 1 1. 1.394872 2. 0.07675 30.57534 + 1 1. 1.394872 2. 0.07675 30.57534 END SED-PARM2 SED-PARM3 # - # KSER JSER KGER JGER *** - 1 6.974359 2. 0. 4. + 1 6.974359 2. 0. 4. END SED-PARM3 MON-COVER # - # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 .0618.0618.0557.1392.2285.3906.6657.7618.8416.7424.6945.0618 + 1 .0618.0618.0557.1392.2285.3906.6657.7618.8416.7424.6945.0618 END MON-COVER MON-NVSI # - # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 + 1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 END MON-NVSI SED-STOR # - # DETS *** - 1 0. + 1 0. END SED-STOR PSTEMP-PARM1 @@ -199,37 +199,37 @@ PERLND PSTEMP-PARM2 # - # ASLT BSLT ULTP1 ULTP2 LGTP1 LGTP2*** - 1 0. 1. 0. 0. 0. 0. + 1 0. 1. 0. 0. 0. 0. END PSTEMP-PARM2 MON-ASLT # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 35.5837.1440.4945.0949.4653.6255.76 54.651.5446.0841.5536.97 + 1 35.5837.1440.4945.0949.4653.6255.76 54.651.5446.0841.5536.97 END MON-ASLT MON-BSLT # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 + 1 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 END MON-BSLT MON-ULTP1 # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 38.4541.2547.2755.5763.4370.9274.7772.6767.1757.3449.1940.94 + 1 38.4541.2547.2755.5763.4370.9274.7772.6767.1757.3449.1940.94 END MON-ULTP1 MON-ULTP2 # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 + 1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 END MON-ULTP2 MON-LGTP1 # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 46.5145.4146.5749.0952.7956.0359.0160.4159.74 57.253.27 49.9 + 1 46.5145.4146.5749.0952.7956.0359.0160.4159.74 57.253.27 49.9 END MON-LGTP1 PSTEMP-TEMPS # # AIRTC SLTMP ULTMP LGTMP *** - 1 32. 32. 32. 50. + 1 32. 32. 32. 50. END PSTEMP-TEMPS PWT-PARM1 @@ -239,37 +239,37 @@ PERLND PWT-PARM2 # # ELEV IDOXP ICO2P ADOXP ACO2P *** - 1 55.78 0. 0. 0. 0. + 1 55.78 0. 0. 0. 0. END PWT-PARM2 MON-IFWDOX # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 12.7 12.7 11.2 9.7 7.4 6.6 6.2 6.2 7.5 8.4 9.4 11.6 + 1 12.7 12.7 11.2 9.7 7.4 6.6 6.2 6.2 7.5 8.4 9.4 11.6 END MON-IFWDOX MON-GRNDDOX # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 10. 10. 10. 10. 7.5 5.5 5. 5. 6.5 7.5 9. 10. + 1 10. 10. 10. 10. 7.5 5.5 5. 5. 6.5 7.5 9. 10. END MON-GRNDDOX PWT-TEMPS # - # SOTMP IOTMP AOTMP*** - 1 33. 40. 55. + 1 33. 40. 55. END PWT-TEMPS PWT-GASES # # SODOX SOCO2 IODOX IOCO2 AODOX AOCO2 *** - 1 14.5 0. 12.7 0. 10. 0. + 1 14.5 0. 12.7 0. 10. 0. END PWT-GASES MST-PARM # # SLMPF ULPF LLPF*** - 1 1. 1. 1. + 1 1. 1. 1. END MST-PARM SOIL-DATA # - # SURFDEP UPDEP LODEP GRNDDEP SURFBD UPBD LOBD GRNDBD *** - 1 0.4 11.5631 93.9878 60. 80.0514 89.2348 80.7519 82.6256 + 1 0.4 11.5631 93.9878 60. 80.0514 89.2348 80.7519 82.6256 END SOIL-DATA NIT-FLAGS @@ -284,7 +284,7 @@ PERLND NIT-FSTGEN # # NO3 NH4 PLN KDSA KADA KIMN KAM KDNI KNI KIMA*** - 1 .8 .2 1.07 1.05 1.05 1.07 1.07 1.07 1.05 1.07 + 1 .8 .2 1.07 1.05 1.05 1.07 1.07 1.07 1.05 1.07 END NIT-FSTGEN NIT-FSTPM @@ -294,32 +294,32 @@ PERLND NIT-ORGPM # - # KLON KRON KONLR THNLR *** - 1 0.20357 1.157812 0.0001 1.07 + 1 0.20357 1.157812 0.0001 1.07 END NIT-ORGPM NIT-AMVOLAT # - # SKVOL UKVOL LKVOL AKVOL THVOL TRFVOL *** - 1 0.5 0.1 0. 0. 1.07 20. + 1 0.5 0.1 0. 0. 1.07 20. END NIT-AMVOLAT NIT-CMAX # # CMAX *** - 1 5000. + 1 5000. END NIT-CMAX NIT-SVALPM # # XFIX K1 N1*** - 1 1. 1. 1.5 + 1 1. 1. 1.5 END NIT-SVALPM MON-NITUPT # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 + 1 END MON-NITUPT SOIL-DATA2 # # SWILTP UWILTP LWILTP AWILTP *** - 1 0.01 0.01 0.01 0.1 + 1 0.01 0.01 0.01 0.1 END SOIL-DATA2 CROP-DATES @@ -329,87 +329,87 @@ PERLND NIT-YIELD # - # NUTTGT NMXRAT *** - 1 105. 1. + 1 105. 1. END NIT-YIELD MON-NUPT-FR1 # - # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 .01 .04 .09 .115 .135 .145 .15 .14 .095 .05 .025 .005 + 1 .01 .04 .09 .115 .135 .145 .15 .14 .095 .05 .025 .005 END MON-NUPT-FR1 MON-NUPT-FR2 # - # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 + 1 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 END MON-NUPT-FR2 NIT-UPIMCSAT # - # CSUNI CSUAM CSINI CSIAM *** - 1 + 1 END NIT-UPIMCSAT MON-NITUPNI # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 + 1 END MON-NITUPNI MON-NITUPAM # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 + 1 END MON-NITUPAM MON-NITIMNI # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 + 1 END MON-NITIMNI MON-NITIMAM # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 + 1 END MON-NITIMAM MON-NITIMAM # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 + 1 END MON-NITIMAM MON-NITIMAM # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 + 1 END MON-NITIMAM MON-NITIMAM # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 + 1 END MON-NITIMAM MON-NPRETBG # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 .01 .01 .005.0005.0001.0001.0001.0001.0005 .01 .02 .02 + 1 .01 .01 .005.0005.0001.0001.0001.0001.0005 .01 .02 .02 END MON-NPRETBG MON-NITAGUTF # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 + 1 END MON-NITAGUTF MON-NPRETAG # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 + 1 END MON-NPRETAG MON-NPRETFLI # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 + 1 END MON-NPRETFLI NIT-STOR1 # # ORGN AMAD AMSU NO3 PLTN RORGN*** - 1 3.1555 1. 0.03 0.3 0. 50. + 1 3.1555 1. 0.03 0.3 0. 50. END NIT-STOR1 NIT-STOR2 # # IAMSU INO3 ISLON ISRON AGPLTN LITTRN*** - 1 0. 0. 0. 0. + 1 0. 0. 0. 0. END NIT-STOR2 PHOS-FLAGS @@ -424,47 +424,47 @@ PERLND PHOS-FSTGEN # # THPLP THKDSP THKADP THKIMP THKMP *** - 1 1.07 1.05 1.05 1.07 1.07 + 1 1.07 1.05 1.05 1.07 1.07 END PHOS-FSTGEN PHOS-FSTPM # # KDSP KADP KIMP KMP *** - 1 0. 0. 0.05 0.005 + 1 0. 0. 0.05 0.005 END PHOS-FSTPM PHOS-CMAX # # CMAX *** - 1 50. + 1 50. END PHOS-CMAX PHOS-SVALPM # # XFIX K1 N1*** - 1 100. 5. 1.5 + 1 100. 5. 1.5 END PHOS-SVALPM MON-PHOSUPT # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 + 1 END MON-PHOSUPT PHOS-YIELD # # PUPTGT PMXRAT *** - 1 25. 1.5 + 1 25. 1.5 END PHOS-YIELD MON-PUPT-FR1 # - # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 .01 .04 .09 .115 .135 .145 .15 .14 .095 .05 .025 .005 + 1 .01 .04 .09 .115 .135 .145 .15 .14 .095 .05 .025 .005 END MON-PUPT-FR1 MON-PUPT-FR2 # - # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** - 1 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 + 1 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 .01 END MON-PUPT-FR2 PHOS-STOR1 # # ORGP P4AD P4SU PLTP *** - 1 15. 1. 0. 0. + 1 15. 1. 0. 0. END PHOS-STOR1 END PERLND diff --git a/tests/land_spec/hwmA51800.wdm b/tests/land_spec/HSP2Results/hwmA51800.wdm similarity index 100% rename from tests/land_spec/hwmA51800.wdm rename to tests/land_spec/HSP2Results/hwmA51800.wdm diff --git a/tests/land_spec/met_A51800.wdm b/tests/land_spec/HSP2Results/met_A51800.wdm similarity index 100% rename from tests/land_spec/met_A51800.wdm rename to tests/land_spec/HSP2Results/met_A51800.wdm diff --git a/tests/land_spec/prad_A51800.wdm b/tests/land_spec/HSP2Results/prad_A51800.wdm similarity index 100% rename from tests/land_spec/prad_A51800.wdm rename to tests/land_spec/HSP2Results/prad_A51800.wdm diff --git a/tests/test05/HSP2compare/CompareHSP2.ipynb b/tests/test05/HSP2compare/CompareHSP2.ipynb index df3903e4..a7a620b5 100644 --- a/tests/test05/HSP2compare/CompareHSP2.ipynb +++ b/tests/test05/HSP2compare/CompareHSP2.ipynb @@ -69,15 +69,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T21:50:25.697609Z", - "iopub.status.busy": "2024-05-21T21:50:25.697517Z", - "iopub.status.idle": "2024-05-21T21:50:26.418254Z", - "shell.execute_reply": "2024-05-21T21:50:26.417827Z", - "shell.execute_reply.started": "2024-05-21T21:50:25.697599Z" - } - }, + "metadata": {}, "outputs": [ { "data": { @@ -110,11 +102,11 @@ " \n", " \n", " Python\n", - " 3.10.14 | packaged by conda-forge | (main, Mar...\n", + " 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11....\n", " \n", " \n", " hsp2\n", - " n/a\n", + " 0.11.0a1\n", " \n", " \n", " numpy\n", @@ -122,27 +114,27 @@ " \n", " \n", " numba\n", - " 0.59.1\n", + " 0.64.0\n", " \n", " \n", " pandas\n", - " 1.5.3\n", + " 2.3.3\n", " \n", " \n", " matplotlib\n", - " 3.8.4\n", + " 3.10.8\n", " \n", " \n", " os\n", - " Linux-5.15.0-91-generic-x86_64-with-glibc2.35\n", + " Linux-6.19.12-200.fc43.x86_64-x86_64-with-glib...\n", " \n", " \n", " processor\n", - " x86_64\n", + " \n", " \n", " \n", " Date/Time\n", - " 2024-05-21T17:50:26.412096\n", + " 2026-05-06T21:46:18.717082\n", " \n", " \n", "\n", @@ -151,15 +143,15 @@ "text/plain": [ " version\n", "name \n", - "Python 3.10.14 | packaged by conda-forge | (main, Mar...\n", - "hsp2 n/a\n", + "Python 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11....\n", + "hsp2 0.11.0a1\n", "numpy 1.26.4\n", - "numba 0.59.1\n", - "pandas 1.5.3\n", - "matplotlib 3.8.4\n", - "os Linux-5.15.0-91-generic-x86_64-with-glibc2.35\n", - "processor x86_64\n", - "Date/Time 2024-05-21T17:50:26.412096" + "numba 0.64.0\n", + "pandas 2.3.3\n", + "matplotlib 3.10.8\n", + "os Linux-6.19.12-200.fc43.x86_64-x86_64-with-glib...\n", + "processor \n", + "Date/Time 2026-05-06T21:46:18.717082" ] }, "execution_count": 1, @@ -198,15 +190,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T21:50:26.419135Z", - "iopub.status.busy": "2024-05-21T21:50:26.418807Z", - "iopub.status.idle": "2024-05-21T21:50:26.421284Z", - "shell.execute_reply": "2024-05-21T21:50:26.420943Z", - "shell.execute_reply.started": "2024-05-21T21:50:26.419119Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "wdmname = \"TEST.WDM\"\n", @@ -231,17 +215,39 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T21:53:55.560529Z", - "iopub.status.busy": "2024-05-21T21:53:55.559951Z", - "iopub.status.idle": "2024-05-21T21:53:59.167584Z", - "shell.execute_reply": "2024-05-21T21:53:59.167200Z", - "shell.execute_reply.started": "2024-05-21T21:53:55.560502Z" - } - }, + "execution_count": 3, + "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_40492/3398803723.py:1: DeprecationWarning: Call to deprecated function readUCI (\n", + "\n", + "readUCI is deprecated and will be removed in a future release.\n", + "Use hsp2.hsp2io.control_file_readers.read_uci_parameters to read the parameters.\n", + "\n", + ").\n", + " readUCI(uciname, hdfname)\n", + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'CURV-DATA1'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though\n", + " check_attribute_name(name)\n", + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'CURV-DATA2'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though\n", + " check_attribute_name(name)\n", + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'CURV-DATA3'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though\n", + " check_attribute_name(name)\n", + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'CURV-DATA4'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though\n", + " check_attribute_name(name)\n", + "/tmp/ipykernel_40492/3398803723.py:2: DeprecationWarning: Call to deprecated function readWDM (\n", + "\n", + "readWDM is deprecated and will be removed in a future release.\n", + "Use hsp2.hsp2io.time_series_readers.read_wdm_ts.read_wdm_ts to read the time\n", + "series data from the WDM file, and then write the data to an HDF file using\n", + "pandas.\n", + "\n", + ").\n", + " readWDM(wdmname, hdfname)\n" + ] + }, { "name": "stdout", "output_type": "stream", @@ -266,360 +272,6 @@ "136 reading from wdm\n", "140 reading from wdm\n" ] - }, - { - "data": { - "text/html": [ - "
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StartStopFreqLengthTSTYPETFILLSTAIDSTNAMSCENARIOLOCATION
TS0391976-01-01 00:00:001977-01-01 00:00:001h8784PREC-999.0000HOURLY PRECPRECIP TRAER IOWATEST02C:1
TS0411976-01-01 00:00:001977-01-01 00:00:001D366EVAP-999.0000DAILY EVAPFARMERS COOP WEATHER STNTEST01M:1
TS0421976-01-01 00:00:001977-01-01 00:00:001D366WIND-999.0000DAILY WINDFARMERS COOP WEATHER STNTEST01M:1
TS0461976-01-01 00:00:001977-01-01 00:00:002h4392SOLR-999.00002 HOUR RADFARMERS WEATHER STNTEST02C:1
TS1131976-01-01 00:00:001977-01-01 00:00:001D366FLOW-999.0000DAILY FLOWIOWA RIVER MARSHALLTOWNTEST01M:1
TS1191976-01-01 00:00:001977-01-01 00:00:001D366FLOW-999.0000DAILY FLOWIOWA RIVER MARENGOTEST01M:1
TS1211976-01-01 00:00:001977-01-01 00:00:002h4392ATMP-999.00002 HOUR AIR TEMPCEDAR RAPIDS IOWATEST02C:1
TS1221976-01-01 00:00:001977-01-01 00:00:002h4392ATMP-999.00002 HOUR AIR TEMPIOWA FALLS IOWATEST02C:1
TS1231976-01-01 00:00:001977-01-01 00:00:002h4392ATMP-999.00002 HOUR AIR TEMPMARSHALLTOWN IOWATEST02C:1
TS1241976-01-01 00:00:001977-01-01 00:00:001D366DEWP-999.0000DAILY DEW PTCEDAR RAPIDS IOWATEST01M:1
TS1251976-01-01 00:00:001977-01-01 00:00:001D366DEWP-999.0000DAILY DEW PTIOWA FALLS IOWATEST01M:1
TS1261976-01-01 00:00:001977-01-01 00:00:001D366DEWP-999.0000DAILY DEW PTMARSHALLTOWN IOWATEST01M:1
TS1271976-01-01 00:00:001977-01-01 00:00:001D366SEDM-999.0000SEDIMENT CONCIOWA RIVER MARENGOTEST01M:1
TS1311976-01-01 00:00:001977-01-01 00:00:001h8784PREC-999.0000HOURLY PRECPRECIP IOWA FALLSTEST02C:1
TS1321976-01-01 00:00:001977-01-01 00:00:001h8784PREC-999.0000HOURLY PRECPRECIP SHEFFIELDTEST02C:1
TS1341976-01-01 00:00:001977-01-01 00:00:001D366WTMP-999.0000WATER TEMPIOWA RIVER (ESTIMATED)TEST01M:1
TS1351976-01-01 00:00:001977-01-01 00:00:001D366CLDC-999.0000CLOUD COVERWATERLOO (TENTHS)TEST03C:1
TS1361976-01-01 00:00:001977-01-01 00:00:001D366FLOW-999.0000DAILY FLOWIOWA RIVER ROWANTEST01M:1
TS1401976-01-01 00:00:001977-01-01 00:00:001D366CLND-999.0000COLINDCOLUMN INDICATOR MEIER POND SUMMER-WINTER OUTLETTEST03C:1
\n", - "
" - ], - "text/plain": [ - " Start Stop Freq Length TSTYPE TFILL \\\n", - "TS039 1976-01-01 00:00:00 1977-01-01 00:00:00 1h 8784 PREC -999.0000 \n", - "TS041 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 EVAP -999.0000 \n", - "TS042 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 WIND -999.0000 \n", - "TS046 1976-01-01 00:00:00 1977-01-01 00:00:00 2h 4392 SOLR -999.0000 \n", - "TS113 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 FLOW -999.0000 \n", - "TS119 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 FLOW -999.0000 \n", - "TS121 1976-01-01 00:00:00 1977-01-01 00:00:00 2h 4392 ATMP -999.0000 \n", - "TS122 1976-01-01 00:00:00 1977-01-01 00:00:00 2h 4392 ATMP -999.0000 \n", - "TS123 1976-01-01 00:00:00 1977-01-01 00:00:00 2h 4392 ATMP -999.0000 \n", - "TS124 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 DEWP -999.0000 \n", - "TS125 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 DEWP -999.0000 \n", - "TS126 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 DEWP -999.0000 \n", - "TS127 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 SEDM -999.0000 \n", - "TS131 1976-01-01 00:00:00 1977-01-01 00:00:00 1h 8784 PREC -999.0000 \n", - "TS132 1976-01-01 00:00:00 1977-01-01 00:00:00 1h 8784 PREC -999.0000 \n", - "TS134 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 WTMP -999.0000 \n", - "TS135 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 CLDC -999.0000 \n", - "TS136 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 FLOW -999.0000 \n", - "TS140 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 CLND -999.0000 \n", - "\n", - " STAID STNAM \\\n", - "TS039 HOURLY PREC PRECIP TRAER IOWA \n", - "TS041 DAILY EVAP FARMERS COOP WEATHER STN \n", - "TS042 DAILY WIND FARMERS COOP WEATHER STN \n", - "TS046 2 HOUR RAD FARMERS WEATHER STN \n", - "TS113 DAILY FLOW IOWA RIVER MARSHALLTOWN \n", - "TS119 DAILY FLOW IOWA RIVER MARENGO \n", - "TS121 2 HOUR AIR TEMP CEDAR RAPIDS IOWA \n", - "TS122 2 HOUR AIR TEMP IOWA FALLS IOWA \n", - "TS123 2 HOUR AIR TEMP MARSHALLTOWN IOWA \n", - "TS124 DAILY DEW PT CEDAR RAPIDS IOWA \n", - "TS125 DAILY DEW PT IOWA FALLS IOWA \n", - "TS126 DAILY DEW PT MARSHALLTOWN IOWA \n", - "TS127 SEDIMENT CONC IOWA RIVER MARENGO \n", - "TS131 HOURLY PREC PRECIP IOWA FALLS \n", - "TS132 HOURLY PREC PRECIP SHEFFIELD \n", - "TS134 WATER TEMP IOWA RIVER (ESTIMATED) \n", - "TS135 CLOUD COVER WATERLOO (TENTHS) \n", - "TS136 DAILY FLOW IOWA RIVER ROWAN \n", - "TS140 COLIND COLUMN INDICATOR MEIER POND SUMMER-WINTER OUTLET \n", - "\n", - " SCENARIO LOCATION \n", - "TS039 TEST02 C:1 \n", - "TS041 TEST01 M:1 \n", - "TS042 TEST01 M:1 \n", - "TS046 TEST02 C:1 \n", - "TS113 TEST01 M:1 \n", - "TS119 TEST01 M:1 \n", - "TS121 TEST02 C:1 \n", - "TS122 TEST02 C:1 \n", - "TS123 TEST02 C:1 \n", - "TS124 TEST01 M:1 \n", - "TS125 TEST01 M:1 \n", - "TS126 TEST01 M:1 \n", - "TS127 TEST01 M:1 \n", - "TS131 TEST02 C:1 \n", - "TS132 TEST02 C:1 \n", - "TS134 TEST01 M:1 \n", - "TS135 TEST03 C:1 \n", - "TS136 TEST01 M:1 \n", - "TS140 TEST03 C:1 " - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" } ], "source": [ @@ -683,39 +335,46 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T21:54:11.910957Z", - "iopub.status.busy": "2024-05-21T21:54:11.910525Z", - "iopub.status.idle": "2024-05-21T21:54:13.201958Z", - "shell.execute_reply": "2024-05-21T21:54:13.201293Z", - "shell.execute_reply.started": "2024-05-21T21:54:11.910941Z" - } - }, + "execution_count": 4, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "2024-05-21 17:54:11.91 Processing started for file hsp2.h5; saveall=True\n", - "STATE initializing contexts.\n", - "Looking for custom om loader in python code hsp2.py\n", - "Looking for custom om json hsp2.json\n" - ] - }, - { - "ename": "KeyError", - "evalue": "'hsp_segments'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[6], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mmain\u001b[49m\u001b[43m(\u001b[49m\u001b[43mhdfname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msaveall\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/anaconda3/envs/hsp2_310/lib/python3.10/site-packages/hsp2/hsp2/main.py:85\u001b[0m, in \u001b[0;36mmain\u001b[0;34m(io_manager, saveall, jupyterlab)\u001b[0m\n\u001b[1;32m 83\u001b[0m state_load_dynamics_om(state, io_manager, siminfo) \u001b[38;5;66;03m# operational model for custom python\u001b[39;00m\n\u001b[1;32m 84\u001b[0m \u001b[38;5;66;03m# finalize all dynamically loaded components and prepare to run the model\u001b[39;00m\n\u001b[0;32m---> 85\u001b[0m \u001b[43mstate_om_model_run_prep\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstate\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mio_manager\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msiminfo\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 86\u001b[0m \u001b[38;5;66;03m#######################################################################################\u001b[39;00m\n\u001b[1;32m 87\u001b[0m \n\u001b[1;32m 88\u001b[0m \u001b[38;5;66;03m# main processing loop\u001b[39;00m\n\u001b[1;32m 89\u001b[0m msg(\u001b[38;5;241m1\u001b[39m, \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mSimulation Start: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mstart\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m, Stop: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mstop\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n", - "File \u001b[0;32m~/anaconda3/envs/hsp2_310/lib/python3.10/site-packages/hsp2/hsp2/om.py:165\u001b[0m, in \u001b[0;36mstate_om_model_run_prep\u001b[0;34m(state, io_manager, siminfo)\u001b[0m\n\u001b[1;32m 163\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mstate_om_model_run_prep\u001b[39m(state, io_manager, siminfo):\n\u001b[1;32m 164\u001b[0m \u001b[38;5;66;03m# insure model base is set\u001b[39;00m\n\u001b[0;32m--> 165\u001b[0m \u001b[43mstate_om_model_root_object\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstate\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msiminfo\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 166\u001b[0m \u001b[38;5;66;03m# now instantiate and link objects\u001b[39;00m\n\u001b[1;32m 167\u001b[0m \u001b[38;5;66;03m# state['model_data'] has alread been prepopulated from json, .py files, hdf5, etc.\u001b[39;00m\n\u001b[1;32m 168\u001b[0m model_root_object \u001b[38;5;241m=\u001b[39m state[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmodel_root_object\u001b[39m\u001b[38;5;124m'\u001b[39m]\n", - "File \u001b[0;32m~/anaconda3/envs/hsp2_310/lib/python3.10/site-packages/hsp2/hsp2/om.py:157\u001b[0m, in \u001b[0;36mstate_om_model_root_object\u001b[0;34m(state, siminfo)\u001b[0m\n\u001b[1;32m 155\u001b[0m timer \u001b[38;5;241m=\u001b[39m SimTimer(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtimer\u001b[39m\u001b[38;5;124m'\u001b[39m, model_root_object, siminfo)\n\u001b[1;32m 156\u001b[0m \u001b[38;5;66;03m# add base object for the HSP2 domains and other things already added to state so they can be influenced\u001b[39;00m\n\u001b[0;32m--> 157\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m (seg_name,seg_path) \u001b[38;5;129;01min\u001b[39;00m \u001b[43mstate\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mhsp_segments\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241m.\u001b[39mitems():\n\u001b[1;32m 158\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (seg_path \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m state[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmodel_object_cache\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39mkeys()):\n\u001b[1;32m 159\u001b[0m \u001b[38;5;66;03m# Create an object shell for this\u001b[39;00m\n\u001b[1;32m 160\u001b[0m ModelObject(seg_name, model_root_object)\n", - "\u001b[0;31mKeyError\u001b[0m: 'hsp_segments'" + "2026-05-06 21:46:22.32 Processing started for file hsp2.h5; saveall=True\n", + "Skipping un-typed siminfo\n", + "op_tokens has 20 elements, with 1 executable elements\n", + "2026-05-06 21:46:25.29 Simulation Start: 1976-01-01 00:00:00, Stop: 1977-01-01 00:00:00\n", + "2026-05-06 21:46:25.29 PERLND P001 DELT(minutes): 30\n", + "2026-05-06 21:46:25.64 SNOW\n", + "2026-05-06 21:46:26.33 PWATER\n", + "2026-05-06 21:46:26.71 PERLND P002 DELT(minutes): 30\n", + "2026-05-06 21:46:26.71 SNOW\n", + "2026-05-06 21:46:26.81 PWATER\n", + "2026-05-06 21:46:26.96 PERLND P003 DELT(minutes): 30\n", + "2026-05-06 21:46:26.98 SNOW\n", + "2026-05-06 21:46:27.08 PWATER\n", + "2026-05-06 21:46:27.24 COPY COPY001 DELT(minutes): 30\n", + "2026-05-06 21:46:27.24 COPY COPY002 DELT(minutes): 30\n", + "2026-05-06 21:46:27.24 COPY COPY003 DELT(minutes): 30\n", + "2026-05-06 21:46:27.24 DISPLY D001 DELT(minutes): 30\n", + "2026-05-06 21:46:27.24 PLTGEN L001 DELT(minutes): 30\n", + "2026-05-06 21:46:27.24 Done; Run time is about 00:04.9 (mm:ss)\n", + "\n", + "\n", + " version\n", + "name \n", + "Python 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11....\n", + "hsp2 0.11.0a1\n", + "numpy 1.26.4\n", + "numba 0.64.0\n", + "pandas 2.3.3\n", + "jupyterlab 4.5.6\n", + "notebook n/a\n", + "os Linux-6.19.12-200.fc43.x86_64-x86_64-with-glib...\n", + "processor \n", + "Date/Time 2026-05-06T21:46:27.390728\n" ] } ], @@ -782,18 +441,22 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.086122Z", - "iopub.status.idle": "2024-05-21T21:50:35.086242Z", - "shell.execute_reply": "2024-05-21T21:50:35.086188Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.086183Z" + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['Monthly', 'Yearly'], dtype=object)" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" } - }, - "outputs": [], + ], "source": [ - "summary = read_hdf(HBN, \"SUMMARY\")\n", + "summary = pd.read_hdf(HBN, \"SUMMARY\")\n", "summary.Frequency.unique()" ] }, @@ -813,41 +476,28 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.086599Z", - "iopub.status.idle": "2024-05-21T21:50:35.086701Z", - "shell.execute_reply": "2024-05-21T21:50:35.086655Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.086650Z" - } - }, + "execution_count": 6, + "metadata": {}, "outputs": [], "source": [ "def hsp2key(hspfkey):\n", " op, activity, segment, _ = hspfkey.split(\"_\")\n", - " return f\"RESULTS/{op}_{op[0]}{segment:0>3s}/{activity}\"" + " return f\"/RESULTS/{op}_{op[0]}{segment:0>3s}/{activity}\"" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.088299Z", - "iopub.status.idle": "2024-05-21T21:50:35.088487Z", - "shell.execute_reply": "2024-05-21T21:50:35.088427Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.088421Z" - } - }, + "execution_count": 18, + "metadata": {}, "outputs": [], "source": [ "def monthlyoutflow(keys, flowname, how=\"sum\"):\n", " concat = []\n", " for key in keys.index:\n", " hsp2 = (\n", - " pd.read_hdf(hdfname, hsp2key(key))[flowname].resample(\"M\").sum().to_numpy()\n", - " )\n", + " pd.read_hdf(hdfname, hsp2key(key))[flowname].resample(\"ME\").sum().to_numpy()\n", + " )[:-1]\n", + " \n", " hspf_flowname = flowname.split(\"_\")[0]\n", " hspf = pd.read_hdf(HBN, key)[hspf_flowname].to_numpy()\n", "\n", @@ -876,15 +526,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.088845Z", - "iopub.status.idle": "2024-05-21T21:50:35.088957Z", - "shell.execute_reply": "2024-05-21T21:50:35.088905Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.088900Z" - } - }, + "execution_count": 27, + "metadata": {}, "outputs": [], "source": [ "def plot(operation, ils, activity, name, how=\"sum\"):\n", @@ -895,18 +538,18 @@ " hsp2 = f\"RESULTS/{operation}_{operation[0]}{ils:0>3s}/{activity}\"\n", " if how == \"sum\":\n", " tshsp2 = (\n", - " pd.read_hdf(hdfname, hsp2)[f\"{name}_{how}\"]\n", - " .resample(\"M\")\n", + " pd.read_hdf(hdfname, hsp2)[f\"{name}\"]\n", + " .resample(\"ME\")\n", " .sum()\n", " .shift(1, \"D\")\n", - " )\n", + " )[:-1]\n", " elif how == \"last\":\n", " tshsp2 = (\n", - " pd.read_hdf(hdfname, hsp2)[f\"{name}_{how}\"]\n", - " .resample(\"M\")\n", + " pd.read_hdf(hdfname, hsp2)[f\"{name}\"]\n", + " .resample(\"ME\")\n", " .last()\n", " .shift(1, \"D\")\n", - " )\n", + " )[:-1]\n", "\n", " plt.figure(figsize=(10, 8))\n", " plt.plot(tshspf.index, tshspf, label=\"HSPF\", color=\"salmon\", lw=4)\n", @@ -917,31 +560,30 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.089360Z", - "iopub.status.idle": "2024-05-21T21:50:35.089467Z", - "shell.execute_reply": "2024-05-21T21:50:35.089417Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.089411Z" - } - }, + "execution_count": 28, + "metadata": {}, "outputs": [], "source": [ "def scatter(operation, ils, activity, name, how=\"sum\"):\n", " hspf = f\"{operation}_{activity}_{ils:0>3s}_4\"\n", - " tshspf = read_hdf(HBN, hspf)[name]\n", + " tshspf = pd.read_hdf(HBN, hspf)[name]\n", "\n", " hsp2 = f\"RESULTS/{operation}_{operation[0]}{ils:0>3s}/{activity}\"\n", " if how == \"sum\":\n", " tshsp2 = (\n", - " read_hdf(hdfname, hsp2)[f\"{name}_{how}\"].resample(\"M\").sum().shift(1, \"D\")\n", - " )\n", + " pd.read_hdf(hdfname, hsp2)[name]\n", + " .resample(\"ME\")\n", + " .sum()\n", + " .shift(1, \"D\")\n", + " )[:-1]\n", " elif how == \"last\":\n", " tshsp2 = (\n", - " read_hdf(hdfname, hsp2)[f\"{name}_{how}\"].resample(\"M\").last().shift(1, \"D\")\n", - " )\n", - "\n", + " pd.read_hdf(hdfname, hsp2)[name]\n", + " .resample(\"ME\")\n", + " .last()\n", + " .shift(1, \"D\")\n", + " )[:-1]\n", + " \n", " plt.scatter(tshspf, tshsp2)" ] }, @@ -949,40 +591,175 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### IMPLND" + "## Automate checking PERLNDs for PERO" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.089746Z", - "iopub.status.idle": "2024-05-21T21:50:35.089865Z", - "shell.execute_reply": "2024-05-21T21:50:35.089801Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.089796Z" + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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OperationActivitysegmentFrequencyShapeStartStop
PERLND_PWATER_001_4PERLNDPWATER1Monthly(12, 29)1976-02-011977-01-01
PERLND_PWATER_002_4PERLNDPWATER2Monthly(12, 29)1976-02-011977-01-01
PERLND_PWATER_003_4PERLNDPWATER3Monthly(12, 29)1976-02-011977-01-01
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" + ], + "text/plain": [ + " Operation Activity segment Frequency Shape Start \\\n", + "PERLND_PWATER_001_4 PERLND PWATER 1 Monthly (12, 29) 1976-02-01 \n", + "PERLND_PWATER_002_4 PERLND PWATER 2 Monthly (12, 29) 1976-02-01 \n", + "PERLND_PWATER_003_4 PERLND PWATER 3 Monthly (12, 29) 1976-02-01 \n", + "\n", + " Stop \n", + "PERLND_PWATER_001_4 1977-01-01 \n", + "PERLND_PWATER_002_4 1977-01-01 \n", + "PERLND_PWATER_003_4 1977-01-01 " + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" } - }, - "outputs": [], + ], "source": [ - "implndkeys = summary[(summary.Frequency == \"Monthly\") & (summary.Operation == \"IMPLND\")]\n", - "summary[(summary.Frequency == \"Monthly\")]" + "perlndkeys = summary[(summary.Frequency == \"Monthly\") & (summary.Operation == \"PERLND\") & (summary.Activity == \"PWATER\")]\n", + "perlndkeys[0:10]" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 30, "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.090352Z", - "iopub.status.idle": "2024-05-21T21:50:35.090499Z", - "shell.execute_reply": "2024-05-21T21:50:35.090434Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.090427Z" - } + "scrolled": true }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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HSP2_SUMHSPF_SUMPercent diffabs(Percent diff)
0034.33644.34110.10970.1097
0024.34144.3356-0.13330.1333
0014.44614.4386-0.16860.1686
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" + ], + "text/plain": [ + " HSP2_SUM HSPF_SUM Percent diff abs(Percent diff)\n", + "003 4.3364 4.3411 0.1097 0.1097\n", + "002 4.3414 4.3356 -0.1333 0.1333\n", + "001 4.4461 4.4386 -0.1686 0.1686" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "delta = monthlyoutflow(implndkeys, \"SURO\")\n", + "delta = monthlyoutflow(perlndkeys, \"PERO\")\n", "delta" ] }, @@ -995,1417 +772,1010 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.091188Z", - "iopub.status.idle": "2024-05-21T21:50:35.091345Z", - "shell.execute_reply": "2024-05-21T21:50:35.091273Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.091267Z" - } - }, - "outputs": [], - "source": [ - "delta.describe()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.092131Z", - "iopub.status.idle": "2024-05-21T21:50:35.092270Z", - "shell.execute_reply": "2024-05-21T21:50:35.092207Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.092201Z" - } - }, - "outputs": [], - "source": [ - "delta[\"Percent diff\"].hist()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.092682Z", - "iopub.status.idle": "2024-05-21T21:50:35.092839Z", - "shell.execute_reply": "2024-05-21T21:50:35.092783Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.092778Z" - } - }, - "outputs": [], - "source": [ - "ils = delta.index[-1]\n", - "print(\"WORST IMPLND SEGMENT IS\", ils)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### IMPLND IWATER SURO, Monthly" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.093111Z", - "iopub.status.idle": "2024-05-21T21:50:35.093213Z", - "shell.execute_reply": "2024-05-21T21:50:35.093166Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.093161Z" - } - }, - "outputs": [], - "source": [ - "plot(\"IMPLND\", ils, \"IWATER\", \"SURO\", \"sum\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.093679Z", - "iopub.status.idle": "2024-05-21T21:50:35.093812Z", - "shell.execute_reply": "2024-05-21T21:50:35.093752Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.093747Z" - } - }, - "outputs": [], - "source": [ - "scatter(\"IMPLND\", ils, \"IWATER\", \"SURO\", \"sum\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### IMPLND IWATER IMPEV, Monthly" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.094334Z", - "iopub.status.idle": "2024-05-21T21:50:35.094494Z", - "shell.execute_reply": "2024-05-21T21:50:35.094426Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.094419Z" - } - }, - "outputs": [], - "source": [ - "plot(\"IMPLND\", ils, \"IWATER\", \"IMPEV\", \"sum\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.094937Z", - "iopub.status.idle": "2024-05-21T21:50:35.095050Z", - "shell.execute_reply": "2024-05-21T21:50:35.094998Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.094993Z" - } - }, - "outputs": [], - "source": [ - "scatter(\"IMPLND\", ils, \"IWATER\", \"IMPEV\", \"sum\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### IMPLND IWATER PET, Monthly" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.095636Z", - "iopub.status.idle": "2024-05-21T21:50:35.095815Z", - "shell.execute_reply": "2024-05-21T21:50:35.095747Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.095740Z" - } - }, - "outputs": [], - "source": [ - "plot(\"IMPLND\", ils, \"IWATER\", \"PET\", \"sum\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.096271Z", - "iopub.status.idle": "2024-05-21T21:50:35.096408Z", - "shell.execute_reply": "2024-05-21T21:50:35.096350Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.096345Z" - } - }, - "outputs": [], - "source": [ - "scatter(\"IMPLND\", ils, \"IWATER\", \"PET\", \"sum\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### IMPLND IWATER RETS, Monthly" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.096897Z", - "iopub.status.idle": "2024-05-21T21:50:35.097037Z", - "shell.execute_reply": "2024-05-21T21:50:35.096983Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.096977Z" - } - }, - "outputs": [], - "source": [ - "plot(\"IMPLND\", ils, \"IWATER\", \"RETS\", \"last\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.097379Z", - "iopub.status.idle": "2024-05-21T21:50:35.097483Z", - "shell.execute_reply": "2024-05-21T21:50:35.097435Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.097430Z" - } - }, - "outputs": [], - "source": [ - "scatter(\"IMPLND\", ils, \"IWATER\", \"RETS\", \"last\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### IMPLND IWATER SUPY, Monthly" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.097732Z", - "iopub.status.idle": "2024-05-21T21:50:35.097827Z", - "shell.execute_reply": "2024-05-21T21:50:35.097783Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.097778Z" - } - }, - "outputs": [], - "source": [ - "plot(\"IMPLND\", ils, \"IWATER\", \"SUPY\", \"sum\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.098200Z", - "iopub.status.idle": "2024-05-21T21:50:35.098298Z", - "shell.execute_reply": "2024-05-21T21:50:35.098252Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.098247Z" - } - }, - "outputs": [], - "source": [ - "scatter(\"IMPLND\", ils, \"IWATER\", \"SUPY\", \"sum\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### IMPLND IWATER SURS, Monthly" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.098559Z", - "iopub.status.idle": "2024-05-21T21:50:35.098658Z", - "shell.execute_reply": "2024-05-21T21:50:35.098612Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.098608Z" - } - }, - "outputs": [], - "source": [ - "plot(\"IMPLND\", ils, \"IWATER\", \"SURS\", \"last\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.099157Z", - "iopub.status.idle": "2024-05-21T21:50:35.099264Z", - "shell.execute_reply": "2024-05-21T21:50:35.099217Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.099212Z" - } - }, - "outputs": [], - "source": [ - "scatter(\"IMPLND\", ils, \"IWATER\", \"SURS\", \"last\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Automate checking PERLNDs for PERO" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.099464Z", - "iopub.status.idle": "2024-05-21T21:50:35.099561Z", - "shell.execute_reply": "2024-05-21T21:50:35.099516Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.099511Z" - } - }, - "outputs": [], - "source": [ - "perlndkeys = summary[(summary.Frequency == \"Monthly\") & (summary.Operation == \"PERLND\")]\n", - "perlndkeys[0:10]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.099955Z", - "iopub.status.idle": "2024-05-21T21:50:35.100061Z", - "shell.execute_reply": "2024-05-21T21:50:35.100013Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.100008Z" - }, - "scrolled": true - }, - "outputs": [], - "source": [ - "delta = monthlyoutflow(perlndkeys, \"PERO\")\n", - "delta" - ] - }, - { - "cell_type": "markdown", + "execution_count": 31, "metadata": {}, - "source": [ - "Look at the statistics for the percent difference column" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.100376Z", - "iopub.status.idle": "2024-05-21T21:50:35.100471Z", - "shell.execute_reply": "2024-05-21T21:50:35.100427Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.100423Z" - } - }, - "outputs": [], - "source": [ - "delta.describe()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.100740Z", - "iopub.status.idle": "2024-05-21T21:50:35.100836Z", - "shell.execute_reply": "2024-05-21T21:50:35.100790Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.100786Z" - } - }, - "outputs": [], - "source": [ - "delta[\"Percent diff\"].hist()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.101196Z", - "iopub.status.idle": "2024-05-21T21:50:35.101300Z", - "shell.execute_reply": "2024-05-21T21:50:35.101251Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.101246Z" - } - }, - "outputs": [], - "source": [ - "pls = delta.index[-1]\n", - "print(\"WORST PERLND SEGMENT IS\", pls)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER AGWLI" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.101621Z", - "iopub.status.idle": "2024-05-21T21:50:35.101765Z", - "shell.execute_reply": "2024-05-21T21:50:35.101699Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.101693Z" - } - }, - "outputs": [], - "source": [ - "plot(\"PERLND\", pls, \"PWATER\", \"AGWLI\", \"sum\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.102124Z", - "iopub.status.idle": "2024-05-21T21:50:35.102223Z", - "shell.execute_reply": "2024-05-21T21:50:35.102178Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.102173Z" - } - }, - "outputs": [], - "source": [ - "scatter(\"PERLND\", pls, \"PWATER\", \"AGWLI\", \"sum\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### PERLND PWATER SURLI" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.102440Z", - "iopub.status.idle": "2024-05-21T21:50:35.102538Z", - "shell.execute_reply": "2024-05-21T21:50:35.102491Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.102487Z" + "outputs": [ + { + "data": { + "text/html": [ + "
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HSP2_SUMHSPF_SUMPercent diffabs(Percent diff)
count3.00003.00003.00003.0000
mean4.37464.3718-0.06410.1372
std0.06190.05790.15160.0296
min4.33644.3356-0.16860.1097
25%4.33894.3384-0.15100.1215
50%4.34144.3411-0.13330.1333
75%4.39374.3898-0.01180.1510
max4.44614.43860.10970.1686
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" + ], + "text/plain": [ + " HSP2_SUM HSPF_SUM Percent diff abs(Percent diff)\n", + "count 3.0000 3.0000 3.0000 3.0000\n", + "mean 4.3746 4.3718 -0.0641 0.1372\n", + "std 0.0619 0.0579 0.1516 0.0296\n", + "min 4.3364 4.3356 -0.1686 0.1097\n", + "25% 4.3389 4.3384 -0.1510 0.1215\n", + "50% 4.3414 4.3411 -0.1333 0.1333\n", + "75% 4.3937 4.3898 -0.0118 0.1510\n", + "max 4.4461 4.4386 0.1097 0.1686" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" } - }, - "outputs": [], + ], "source": [ - "plot(\"PERLND\", pls, \"PWATER\", \"SURLI\", \"sum\")" + "delta.describe()" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.103025Z", - "iopub.status.idle": "2024-05-21T21:50:35.103125Z", - "shell.execute_reply": "2024-05-21T21:50:35.103080Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.103075Z" - } - }, - "outputs": [], - "source": [ - "scatter(\"PERLND\", pls, \"PWATER\", \"SURLI\", \"sum\")" - ] - }, - { - "cell_type": "markdown", + "execution_count": 32, "metadata": {}, - "source": [ - "#### PERLND PWATER AGWO" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.103454Z", - "iopub.status.idle": "2024-05-21T21:50:35.103568Z", - "shell.execute_reply": "2024-05-21T21:50:35.103514Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.103509Z" + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "plot(\"PERLND\", pls, \"PWATER\", \"AGWO\", \"sum\")" + "delta[\"Percent diff\"].hist()" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.103905Z", - "iopub.status.idle": "2024-05-21T21:50:35.104013Z", - "shell.execute_reply": "2024-05-21T21:50:35.103963Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.103958Z" - } - }, - "outputs": [], - "source": [ - "scatter(\"PERLND\", pls, \"PWATER\", \"AGWO\", \"sum\")" - ] - }, - { - "cell_type": "markdown", + "execution_count": 33, "metadata": {}, - "source": [ - "#### PERLND PWATER BASET" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.104318Z", - "iopub.status.idle": "2024-05-21T21:50:35.104418Z", - "shell.execute_reply": "2024-05-21T21:50:35.104370Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.104366Z" - } - }, - "outputs": [], - "source": [ - "plot(\"PERLND\", pls, \"PWATER\", \"BASET\", \"sum\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.104710Z", - "iopub.status.idle": "2024-05-21T21:50:35.104809Z", - "shell.execute_reply": "2024-05-21T21:50:35.104762Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.104757Z" + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WORST PERLND SEGMENT IS 001\n" + ] } - }, - "outputs": [], + ], "source": [ - "scatter(\"PERLND\", pls, \"PWATER\", \"BASET\", \"sum\")" + "pls = delta.index[-1]\n", + "print(\"WORST PERLND SEGMENT IS\", pls)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "##### PERLND PWATER CEPE" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.105116Z", - "iopub.status.idle": "2024-05-21T21:50:35.105211Z", - "shell.execute_reply": "2024-05-21T21:50:35.105166Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.105161Z" - } - }, - "outputs": [], - "source": [ - "plot(\"PERLND\", pls, \"PWATER\", \"CEPE\", \"sum\")" + "#### PERLND PWATER PERO" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.105566Z", - "iopub.status.idle": "2024-05-21T21:50:35.105659Z", - "shell.execute_reply": "2024-05-21T21:50:35.105615Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.105610Z" - } - }, - "outputs": [], - "source": [ - "scatter(\"PERLND\", pls, \"PWATER\", \"CEPE\", \"sum\")" - ] - }, - { - "cell_type": "markdown", + "execution_count": 34, "metadata": {}, - "source": [ - "#### PERLND PWATER IFWI" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.105929Z", - "iopub.status.idle": "2024-05-21T21:50:35.106018Z", - "shell.execute_reply": "2024-05-21T21:50:35.105975Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.105971Z" + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "plot(\"PERLND\", pls, \"PWATER\", \"IFWI\", \"sum\")" + "plot(\"PERLND\", pls, \"PWATER\", \"PERO\", \"sum\")" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.106398Z", - "iopub.status.idle": "2024-05-21T21:50:35.106499Z", - "shell.execute_reply": "2024-05-21T21:50:35.106452Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.106448Z" - } - }, - "outputs": [], - "source": [ - "scatter(\"PERLND\", pls, \"PWATER\", \"IFWI\", \"sum\")" - ] - }, - { - "cell_type": "markdown", + "execution_count": 35, "metadata": {}, - "source": [ - "#### PERLND PWATER IFWO" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.106842Z", - "iopub.status.idle": "2024-05-21T21:50:35.106950Z", - "shell.execute_reply": "2024-05-21T21:50:35.106904Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.106900Z" - } - }, - "outputs": [], - "source": [ - "plot(\"PERLND\", pls, \"PWATER\", \"IFWO\", \"sum\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.107291Z", - "iopub.status.idle": "2024-05-21T21:50:35.107385Z", - "shell.execute_reply": "2024-05-21T21:50:35.107341Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.107336Z" + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "scatter(\"PERLND\", pls, \"PWATER\", \"IFWO\", \"sum\")" + "scatter(\"PERLND\", pls, \"PWATER\", \"PERO\", \"sum\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### PERLND PWATER IGWI" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.107731Z", - "iopub.status.idle": "2024-05-21T21:50:35.107838Z", - "shell.execute_reply": "2024-05-21T21:50:35.107785Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.107781Z" - } - }, - "outputs": [], - "source": [ - "plot(\"PERLND\", pls, \"PWATER\", \"IGWI\", \"sum\")" + "#### PERLND PWATER AGWO" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.108175Z", - "iopub.status.idle": "2024-05-21T21:50:35.108332Z", - "shell.execute_reply": "2024-05-21T21:50:35.108260Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.108254Z" - } - }, - "outputs": [], - "source": [ - "scatter(\"PERLND\", pls, \"PWATER\", \"IGWI\", \"sum\")" - ] - }, - { - "cell_type": "markdown", + "execution_count": 37, "metadata": {}, - "source": [ - "#### PERLND PWATER INFIL" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.108612Z", - "iopub.status.idle": "2024-05-21T21:50:35.108707Z", - "shell.execute_reply": "2024-05-21T21:50:35.108663Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.108659Z" + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "plot(\"PERLND\", pls, \"PWATER\", \"INFIL\", \"sum\")" + "plot(\"PERLND\", pls, \"PWATER\", \"AGWO\", \"sum\")" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.108925Z", - "iopub.status.idle": "2024-05-21T21:50:35.109012Z", - "shell.execute_reply": "2024-05-21T21:50:35.108971Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.108967Z" - } - }, - "outputs": [], - "source": [ - "scatter(\"PERLND\", pls, \"PWATER\", \"INFIL\", \"sum\")" - ] - }, - { - "cell_type": "markdown", + "execution_count": 38, "metadata": {}, - "source": [ - "#### PERLND PWATER LZET" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.109339Z", - "iopub.status.idle": "2024-05-21T21:50:35.109432Z", - "shell.execute_reply": "2024-05-21T21:50:35.109386Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.109382Z" - } - }, - "outputs": [], - "source": [ - "plot(\"PERLND\", pls, \"PWATER\", \"LZET\", \"sum\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.109761Z", - "iopub.status.idle": "2024-05-21T21:50:35.109858Z", - "shell.execute_reply": "2024-05-21T21:50:35.109814Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.109809Z" + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "scatter(\"PERLND\", pls, \"PWATER\", \"LZET\", \"sum\")" + "scatter(\"PERLND\", pls, \"PWATER\", \"AGWO\", \"sum\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### PERLND PWATER PERC" + "#### PERLND PWATER BASET" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.110376Z", - "iopub.status.idle": "2024-05-21T21:50:35.110470Z", - "shell.execute_reply": "2024-05-21T21:50:35.110426Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.110421Z" + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "plot(\"PERLND\", pls, \"PWATER\", \"PERC\", \"sum\")" + "plot(\"PERLND\", pls, \"PWATER\", \"BASET\", \"sum\")" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.110721Z", - "iopub.status.idle": "2024-05-21T21:50:35.110811Z", - "shell.execute_reply": "2024-05-21T21:50:35.110769Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.110765Z" + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "scatter(\"PERLND\", pls, \"PWATER\", \"PERC\", \"sum\")" + "scatter(\"PERLND\", pls, \"PWATER\", \"BASET\", \"sum\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### PERLND PWATER PERO" + "##### PERLND PWATER CEPE" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.111304Z", - "iopub.status.idle": "2024-05-21T21:50:35.111553Z", - "shell.execute_reply": "2024-05-21T21:50:35.111437Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.111427Z" + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "plot(\"PERLND\", pls, \"PWATER\", \"PERO\", \"sum\")" + "plot(\"PERLND\", pls, \"PWATER\", \"CEPE\", \"sum\")" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.112230Z", - "iopub.status.idle": "2024-05-21T21:50:35.112474Z", - "shell.execute_reply": "2024-05-21T21:50:35.112371Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.112361Z" + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "scatter(\"PERLND\", pls, \"PWATER\", \"PERO\", \"sum\")" + "scatter(\"PERLND\", pls, \"PWATER\", \"CEPE\", \"sum\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### PERLND PWATER PERS" + "#### PERLND PWATER IFWI" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.113020Z", - "iopub.status.idle": "2024-05-21T21:50:35.113204Z", - "shell.execute_reply": "2024-05-21T21:50:35.113117Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.113109Z" + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "plot(\"PERLND\", pls, \"PWATER\", \"PERS\", \"last\")" + "plot(\"PERLND\", pls, \"PWATER\", \"IFWI\", \"sum\")" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.114664Z", - "iopub.status.idle": "2024-05-21T21:50:35.114893Z", - "shell.execute_reply": "2024-05-21T21:50:35.114809Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.114802Z" + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "scatter(\"PERLND\", pls, \"PWATER\", \"PERS\", \"last\")" + "scatter(\"PERLND\", pls, \"PWATER\", \"IFWI\", \"sum\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### PERLND PWATER PET, Monthly" + "#### PERLND PWATER IFWO" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.115354Z", - "iopub.status.idle": "2024-05-21T21:50:35.115499Z", - "shell.execute_reply": "2024-05-21T21:50:35.115442Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.115435Z" + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "plot(\"PERLND\", pls, \"PWATER\", \"PET\", \"sum\")" + "plot(\"PERLND\", pls, \"PWATER\", \"IFWO\", \"sum\")" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.115763Z", - "iopub.status.idle": "2024-05-21T21:50:35.115861Z", - "shell.execute_reply": "2024-05-21T21:50:35.115818Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.115813Z" + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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tdruSk5MDNgAAMDGF9QyLJFVUVKikpER5eXkqKCjQzp071dXVpdLSUkmXrnycOXNGL7/8sn+ftrY2SdLnn3+us2fPqq2tTUlJScrOzpYkrVmzRt/+9rf17LPP6v7779evfvUrvfXWW/rjH/8YhRYBAMB4F3ZgKS4u1rlz57R582Z5PB7l5OSovr5eGRkZki4tFHflmiy33Xab/98tLS169dVXlZGRoc7OTknS/PnztXfvXj311FPasGGDZs+erbq6OuXn519DawAAYKIIex0WU7EOCwAA409M1mEBAAAYCwQWAABgPAILAAAwHoEFAAAYj8ACAACMF/bXmgHceHxDlo50fKqe8xc0fZJDt2dOUXzctf05DgAIB4EFwIgOvOfRpjePy9N3wT+W5nRo49JsLcpJG8OZAbiRcEsIwLAOvOfRylfeCQgrktTdd0ErX3lHB97zjNHMANxoCCwAQvINWdr05nGFWlny8timN4/LNzQh1p4EYDgCC4CQjnR8GnRl5cssSZ6+CzrS8en1mxSAGxaBBUBIPeeHDyuR1AHAtSCwAAhp+iRHVOsA4FoQWACEdHvmFKU5HRruy8s2Xfq20O2ZU67ntADcoAgsAEKKj7Np49JsSQoKLZdfb1yazXosAK4LAguAYS3KSVPNI7lKdQbe9kl1OlTzSC7rsAC4blg4DsCIFuWk6d7sVFa6BTCmCCwArio+zqaC2VPHehoAbmDcEgIAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYL6LAUl1drczMTDkcDrndbjU2No5Yf/jwYbndbjkcDs2aNUs7duwIqtm2bZvmzJmjr3zlK0pPT1d5ebkuXLgQyfQAAMAEE3ZgqaurU1lZmSorK9Xa2qrCwkItXrxYXV1dIes7Ojq0ZMkSFRYWqrW1VU8++aRWr16tffv2+Wt++ctfat26ddq4caPa29u1a9cu1dXVaf369ZF3BgAAJgybZVlWODvk5+crNzdXNTU1/rGsrCwtW7ZMVVVVQfVr167V/v371d7e7h8rLS3VsWPH1NzcLEn68Y9/rPb2dv3Hf/yHv+Yf/uEfdOTIkatevbnM6/XK6XSqr69PycnJ4bQEAADGyGg/v8O6wjIwMKCWlhYVFRUFjBcVFampqSnkPs3NzUH1Cxcu1NGjR3Xx4kVJ0p133qmWlhYdOXJEknTy5EnV19fru9/97rBz6e/vl9frDdgAAMDElBBOcW9vr3w+n1wuV8C4y+VSd3d3yH26u7tD1g8ODqq3t1dpaWl66KGHdPbsWd15552yLEuDg4NauXKl1q1bN+xcqqqqtGnTpnCmDwAAxqmIHrq12WwBry3LChq7Wv2Xxw8dOqRnnnlG1dXVeuedd/T666/r17/+tZ5++ulhj7l+/Xr19fX5t9OnT0fSCgAAGAfCusKSkpKi+Pj4oKspPT09QVdRLktNTQ1Zn5CQoKlTp0qSNmzYoJKSEj322GOSpG9+85v6y1/+oh/+8IeqrKxUXFxwrrLb7bLb7eFMHwAAjFNhXWFJSkqS2+1WQ0NDwHhDQ4Pmz58fcp+CgoKg+oMHDyovL0+JiYmSpC+++CIolMTHx8uyLIX5TDAAAJiAwr4lVFFRoZdeekm7d+9We3u7ysvL1dXVpdLSUkmXbtWsWLHCX19aWqpTp06poqJC7e3t2r17t3bt2qUnnnjCX7N06VLV1NRo79696ujoUENDgzZs2KD77rtP8fHxUWgTAACMZ2HdEpKk4uJinTt3Tps3b5bH41FOTo7q6+uVkZEhSfJ4PAFrsmRmZqq+vl7l5eXavn27ZsyYoRdeeEEPPPCAv+app56SzWbTU089pTNnzmjatGlaunSpnnnmmSi0CAAAxruw12ExFeuwAAAw/sRkHRYAAICxQGABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABgvosBSXV2tzMxMORwOud1uNTY2jlh/+PBhud1uORwOzZo1Szt27Aiq+eyzz7Rq1SqlpaXJ4XAoKytL9fX1kUwPAABMMGEHlrq6OpWVlamyslKtra0qLCzU4sWL1dXVFbK+o6NDS5YsUWFhoVpbW/Xkk09q9erV2rdvn79mYGBA9957rzo7O/Xaa6/pxIkTqq2t1cyZMyPvDAAATBg2y7KscHbIz89Xbm6uampq/GNZWVlatmyZqqqqgurXrl2r/fv3q7293T9WWlqqY8eOqbm5WZK0Y8cObd26VR988IESExMjasTr9crpdKqvr0/JyckRHQMAAFxfo/38DusKy8DAgFpaWlRUVBQwXlRUpKamppD7NDc3B9UvXLhQR48e1cWLFyVJ+/fvV0FBgVatWiWXy6WcnBxt2bJFPp9v2Ln09/fL6/UGbAAAYGIKK7D09vbK5/PJ5XIFjLtcLnV3d4fcp7u7O2T94OCgent7JUknT57Ua6+9Jp/Pp/r6ej311FP6p3/6Jz3zzDPDzqWqqkpOp9O/paenh9MKAAAYRyJ66NZmswW8tiwraOxq9V8eHxoa0vTp07Vz50653W499NBDqqysDLjtdKX169err6/Pv50+fTqSVgAAwDiQEE5xSkqK4uPjg66m9PT0BF1FuSw1NTVkfUJCgqZOnSpJSktLU2JiouLj4/01WVlZ6u7u1sDAgJKSkoKOa7fbZbfbw5k+AAAYp8K6wpKUlCS3262GhoaA8YaGBs2fPz/kPgUFBUH1Bw8eVF5env8B2zvuuEMfffSRhoaG/DUffvih0tLSQoYVAABwYwn7llBFRYVeeukl7d69W+3t7SovL1dXV5dKS0slXbpVs2LFCn99aWmpTp06pYqKCrW3t2v37t3atWuXnnjiCX/NypUrde7cOa1Zs0YffvihfvOb32jLli1atWpVFFoEAADjXVi3hCSpuLhY586d0+bNm+XxeJSTk6P6+nplZGRIkjweT8CaLJmZmaqvr1d5ebm2b9+uGTNm6IUXXtADDzzgr0lPT9fBgwdVXl6uW265RTNnztSaNWu0du3aKLQIAADGu7DXYTEV67AAADD+xGQdFgAAgLFAYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMF5EgaW6ulqZmZlyOBxyu91qbGwcsf7w4cNyu91yOByaNWuWduzYMWzt3r17ZbPZtGzZskimBgAAJqCwA0tdXZ3KyspUWVmp1tZWFRYWavHixerq6gpZ39HRoSVLlqiwsFCtra168skntXr1au3bty+o9tSpU3riiSdUWFgYficAAGDCslmWZYWzQ35+vnJzc1VTU+Mfy8rK0rJly1RVVRVUv3btWu3fv1/t7e3+sdLSUh07dkzNzc3+MZ/Pp7vuuks/+MEP1NjYqM8++0z//u//Pup5eb1eOZ1O9fX1KTk5OZyWAADAGBnt53dYV1gGBgbU0tKioqKigPGioiI1NTWF3Ke5uTmofuHChTp69KguXrzoH9u8ebOmTZumRx99dFRz6e/vl9frDdgAAMDEFFZg6e3tlc/nk8vlChh3uVzq7u4OuU93d3fI+sHBQfX29kqS3n77be3atUu1tbWjnktVVZWcTqd/S09PD6cVAAAwjkT00K3NZgt4bVlW0NjV6i+Pnz9/Xo888ohqa2uVkpIy6jmsX79efX19/u306dNhdAAAAMaThHCKU1JSFB8fH3Q1paenJ+gqymWpqakh6xMSEjR16lS9//776uzs1NKlS/0/HxoaujS5hASdOHFCs2fPDjqu3W6X3W4PZ/oAAGCcCusKS1JSktxutxoaGgLGGxoaNH/+/JD7FBQUBNUfPHhQeXl5SkxM1Ny5c/Xuu++qra3Nv913332655571NbWxq0eAAAQ3hUWSaqoqFBJSYny8vJUUFCgnTt3qqurS6WlpZIu3ao5c+aMXn75ZUmXvhH04osvqqKiQo8//riam5u1a9cu7dmzR5LkcDiUk5MT8B5f+9rXJCloHAAA3JjCDizFxcU6d+6cNm/eLI/Ho5ycHNXX1ysjI0OS5PF4AtZkyczMVH19vcrLy7V9+3bNmDFDL7zwgh544IHodQEAACa0sNdhMRXrsAAAMP7EZB0WAACAsUBgAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8RLGegIwj2/I0pGOT9Vz/oKmT3Lo9swpio+zjfW0AAA3MAILAhx4z6NNbx6Xp++CfyzN6dDGpdlalJM2hjMDANzIuCUEvwPvebTylXcCwookdfdd0MpX3tGB9zxjNDMAwI2OwAJJl24DbXrzuKwQP7s8tunN4/INhaoAACC2Igos1dXVyszMlMPhkNvtVmNj44j1hw8fltvtlsPh0KxZs7Rjx46An9fW1qqwsFCTJ0/W5MmTtWDBAh05ciSSqSFCRzo+Dbqy8mWWJE/fBR3p+PT6TQoAgP8j7MBSV1ensrIyVVZWqrW1VYWFhVq8eLG6urpC1nd0dGjJkiUqLCxUa2urnnzySa1evVr79u3z1xw6dEjf+9739Ic//EHNzc36xje+oaKiIp05cybyzhCWnvPDh5VI6gAAiCabZVlhXePPz89Xbm6uampq/GNZWVlatmyZqqqqgurXrl2r/fv3q7293T9WWlqqY8eOqbm5OeR7+Hw+TZ48WS+++KJWrFgxqnl5vV45nU719fUpOTk5nJYgqfnjc/pe7X9dtW7P499Sweyp12FGAIAbwWg/v8O6wjIwMKCWlhYVFRUFjBcVFampqSnkPs3NzUH1Cxcu1NGjR3Xx4sWQ+3zxxRe6ePGipkyZMuxc+vv75fV6AzZE7vbMKUpzOjTcl5dtuvRtodszh/+dAAAQK2EFlt7eXvl8PrlcroBxl8ul7u7ukPt0d3eHrB8cHFRvb2/IfdatW6eZM2dqwYIFw86lqqpKTqfTv6Wnp4fTCq4QH2fTxqXZkhQUWi6/3rg0m/VYAABjIqKHbm22wA8ty7KCxq5WH2pckp577jnt2bNHr7/+uhwOx7DHXL9+vfr6+vzb6dOnw2kBISzKSVPNI7lKdQb+d091OlTzSC7rsAAAxkxYC8elpKQoPj4+6GpKT09P0FWUy1JTU0PWJyQkaOrUwGchnn/+eW3ZskVvvfWWbrnllhHnYrfbZbfbw5k+RmFRTpruzU5lpVsAgFHCCixJSUlyu91qaGjQ3/zN3/jHGxoadP/994fcp6CgQG+++WbA2MGDB5WXl6fExET/2NatW/Wzn/1Mv/vd75SXlxfOtHCFa11aPz7OxoO1AACjhL00f0VFhUpKSpSXl6eCggLt3LlTXV1dKi0tlXTpVs2ZM2f08ssvS7r0jaAXX3xRFRUVevzxx9Xc3Kxdu3Zpz549/mM+99xz2rBhg1599VXdfPPN/isyN910k2666aZo9HnDYGl9AMBEFPYzLMXFxdq2bZs2b96sefPm6T//8z9VX1+vjIwMSZLH4wlYkyUzM1P19fU6dOiQ5s2bp6efflovvPCCHnjgAX9NdXW1BgYG9Ld/+7dKS0vzb88//3wUWrxxsLQ+AGCiCnsdFlPd6Ouw+IYs3fns74ddrdamSw/P/nHtd3geBQBgjJiswwJzsbQ+AGAiI7BMECytDwCYyAgsE8T0ScOvWRNJHQAAJiGwTBAsrQ8AmMgILBMES+sDACYyAssEwtL6AICJKuyF42A2ltYHAExEBJYJiKX1AQATDbeEAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8/pZQlPmGLP7wIAAAUUZgiaID73m06c3j8vRd8I+lOR3auDRbi3LSxnBmAACMb9wSipID73m08pV3AsKKJHX3XdDKV97Rgfc8YzQzAADGPwJLFPiGLG1687isED+7PLbpzePyDYWqAAAAV0NgiYIjHZ8GXVn5MkuSp++CjnR8ev0mBQDABEJgiYKe88OHlUjqAABAIAJLFEyf5IhqHQAACERgiYLbM6cozenQcF9etunSt4Vuz5xyPacFAMCEQWAJk2/IUvPH5/SrtjNq/vicfEOW4uNs2rg0W5KCQsvl1xuXZrMeCwAAEWIdljBcbZ2Vmkdyg36eyjosAABcM5tlWRPiu7Zer1dOp1N9fX1KTk6O+vEvr7Ny5X+sy9dMah7J1aKcNFa6BQAgDKP9/OYKywg+vzCosr3v6NiZPp07PzDsOis2XVpn5d7sVMXH2VQwe+p1nikAABNbRM+wVFdXKzMzUw6HQ263W42NjSPWHz58WG63Ww6HQ7NmzdKOHTuCavbt26fs7GzZ7XZlZ2frjTfeiGRqUXPfi43K+env9NYHZ3X2/ICGRqhlnRUAAGIr7MBSV1ensrIyVVZWqrW1VYWFhVq8eLG6urpC1nd0dGjJkiUqLCxUa2urnnzySa1evVr79u3z1zQ3N6u4uFglJSU6duyYSkpK9OCDD+pPf/pT5J1dg/tebNT/99/esPdjnRUAAGIj7GdY8vPzlZubq5qaGv9YVlaWli1bpqqqqqD6tWvXav/+/Wpvb/ePlZaW6tixY2pubpYkFRcXy+v16re//a2/ZtGiRZo8ebL27NkzqnlF6xmWzy8MKuenv4to3z2Pf4vbQQAAhGG0n99hXWEZGBhQS0uLioqKAsaLiorU1NQUcp/m5uag+oULF+ro0aO6ePHiiDXDHVOS+vv75fV6A7ZoKK9rDXsf1lkBACC2wgosvb298vl8crlcAeMul0vd3d0h9+nu7g5ZPzg4qN7e3hFrhjumJFVVVcnpdPq39PT0cFoZVtf//P9h1bPOCgAAsRfRQ7c2W+AHs2VZQWNXq79yPNxjrl+/Xn19ff7t9OnTo57/SL4x+Sth1ac6Hf6vNAMAgNgI62vNKSkpio+PD7ry0dPTE3SF5LLU1NSQ9QkJCZo6deqINcMdU5Lsdrvsdns40x+Vfym+bdTPsPyv//d2zf/rFK6sAAAQY2FdYUlKSpLb7VZDQ0PAeENDg+bPnx9yn4KCgqD6gwcPKi8vT4mJiSPWDHfMWLrJkaBbvn71h3Z/9O1MFf4/0wgrAABcB2HfEqqoqNBLL72k3bt3q729XeXl5erq6lJpaamkS7dqVqxY4a8vLS3VqVOnVFFRofb2du3evVu7du3SE0884a9Zs2aNDh48qGeffVYffPCBnn32Wb311lsqKyu79g4jsP/HhSOGlh99O1Prl2RfxxkBAHBjC3ul2+LiYp07d06bN2+Wx+NRTk6O6uvrlZGRIUnyeDwBa7JkZmaqvr5e5eXl2r59u2bMmKEXXnhBDzzwgL9m/vz52rt3r5566ilt2LBBs2fPVl1dnfLz86PQYmT2/7gwYKVbe0Kcvnd7uh4v/GslJfA3IwEAuJ74W0IAAGDMxGQdFgAAgLFAYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjBf20vymurxgr9frHeOZAACA0br8uX21hfcnTGA5f/68JCk9PX2MZwIAAMJ1/vx5OZ3OYX8+Yf6W0NDQkD755BNNmjRJNpstasf1er1KT0/X6dOnJ/TfKLoR+qTHiYEeJ44boU96vDrLsnT+/HnNmDFDcXHDP6kyYa6wxMXF6etf/3rMjp+cnDxh/8f2ZTdCn/Q4MdDjxHEj9EmPIxvpysplPHQLAACMR2ABAADGI7Bchd1u18aNG2W328d6KjF1I/RJjxMDPU4cN0Kf9Bg9E+ahWwAAMHFxhQUAABiPwAIAAIxHYAEAAMYjsAAAAOPdkIGlurpamZmZcjgccrvdamxsHLH+8OHDcrvdcjgcmjVrlnbs2BFUs2/fPmVnZ8tutys7O1tvvPFGrKY/KtHusba2VoWFhZo8ebImT56sBQsW6MiRI7Fs4api8Xu8bO/evbLZbFq2bFmUZx2eWPT42WefadWqVUpLS5PD4VBWVpbq6+tj1cKoxKLPbdu2ac6cOfrKV76i9PR0lZeX68KFC7Fq4arC6dHj8Wj58uWaM2eO4uLiVFZWFrJuPJ93RtPjeD/vjPb3eJkp5x0pNn1e87nHusHs3bvXSkxMtGpra63jx49ba9assb761a9ap06dCll/8uRJ66/+6q+sNWvWWMePH7dqa2utxMRE67XXXvPXNDU1WfHx8daWLVus9vZ2a8uWLVZCQoL1X//1X9errQCx6HH58uXW9u3brdbWVqu9vd36wQ9+YDmdTuu///u/r1dbAWLR42WdnZ3WzJkzrcLCQuv++++PcSfDi0WP/f39Vl5enrVkyRLrj3/8o9XZ2Wk1NjZabW1t16utILHo85VXXrHsdrv1y1/+0uro6LB+97vfWWlpaVZZWdn1aitAuD12dHRYq1evtn7xi19Y8+bNs9asWRNUM97PO6Ppcbyfd0bT42WmnHcsKzZ9RuPcc8MFlttvv90qLS0NGJs7d661bt26kPX/+I//aM2dOzdg7Ec/+pH1rW99y//6wQcftBYtWhRQs3DhQuuhhx6K0qzDE4serzQ4OGhNmjTJ+sUvfnHtE45ArHocHBy07rjjDuull16yvv/974/piSMWPdbU1FizZs2yBgYGoj/hCMWiz1WrVlnf+c53AmoqKiqsO++8M0qzDk+4PX7ZXXfdFfIDYLyfd75suB6vNN7OO182Uo8mnXcsKzZ9RuPcc0PdEhoYGFBLS4uKiooCxouKitTU1BRyn+bm5qD6hQsX6ujRo7p48eKINcMdM5Zi1eOVvvjiC128eFFTpkyJzsTDEMseN2/erGnTpunRRx+N/sTDEKse9+/fr4KCAq1atUoul0s5OTnasmWLfD5fbBq5ilj1eeedd6qlpcV/++DkyZOqr6/Xd7/73Rh0MbJIehyN8X7eicR4O++MlinnHSl2fUbj3DNh/vjhaPT29srn88nlcgWMu1wudXd3h9ynu7s7ZP3g4KB6e3uVlpY2bM1wx4ylWPV4pXXr1mnmzJlasGBB9CY/SrHq8e2339auXbvU1tYWq6mPWqx6PHnypH7/+9/r4YcfVn19vf785z9r1apVGhwc1E9+8pOY9TOcWPX50EMP6ezZs7rzzjtlWZYGBwe1cuVKrVu3Lma9DCeSHkdjvJ93IjHezjujYdJ5R4pdn9E499xQgeUym80W8NqyrKCxq9VfOR7uMWMtFj1e9txzz2nPnj06dOiQHA5HFGYbmWj2eP78eT3yyCOqra1VSkpK9CcboWj/HoeGhjR9+nTt3LlT8fHxcrvd+uSTT7R169YxCSyXRbvPQ4cO6ZlnnlF1dbXy8/P10Ucfac2aNUpLS9OGDRuiPPvRicU5Yryfd8IxXs87IzH1vCNF/3cZjXPPDRVYUlJSFB8fH5QSe3p6gtLkZampqSHrExISNHXq1BFrhjtmLMWqx8uef/55bdmyRW+99ZZuueWW6E5+lGLR4/vvv6/Ozk4tXbrU//OhoSFJUkJCgk6cOKHZs2dHuZPhxer3mJaWpsTERMXHx/trsrKy1N3drYGBASUlJUW5k5HFqs8NGzaopKREjz32mCTpm9/8pv7yl7/ohz/8oSorKxUXd/3uhkfS42iM9/NOOMbreedqPv74Y6POO1LsfpfROPfcUM+wJCUlye12q6GhIWC8oaFB8+fPD7lPQUFBUP3BgweVl5enxMTEEWuGO2YsxapHSdq6dauefvppHThwQHl5edGf/CjFose5c+fq3XffVVtbm3+77777dM8996itrU3p6ekx6yeUWP0e77jjDn300Uf+k6Ikffjhh0pLS7vuYUWKXZ9ffPFFUCiJj4+XdemLBlHs4Ooi6XE0xvt5Z7TG83nnakw770ix+11G5dwT8eO649Tlr2vt2rXLOn78uFVWVmZ99atftTo7Oy3Lsqx169ZZJSUl/vrLX6EsLy+3jh8/bu3atSvoK5Rvv/22FR8fb/385z+32tvbrZ///OdGfL0wmj0+++yzVlJSkvXaa69ZHo/Hv50/f/6692dZsenxSmP9tH4seuzq6rJuuukm68c//rF14sQJ69e//rU1ffp062c/+9l17++yWPS5ceNGa9KkSdaePXuskydPWgcPHrRmz55tPfjgg9e9P8sKv0fLsqzW1lartbXVcrvd1vLly63W1lbr/fff9/98vJ93LOvqPY73845lXb3HK431eceyYtNnNM49N1xgsSzL2r59u5WRkWElJSVZubm51uHDh/0/+/73v2/dddddAfWHDh2ybrvtNispKcm6+eabrZqamqBj/tu//Zs1Z84cKzEx0Zo7d661b9++WLcxomj3mJGRYUkK2jZu3HgdugktFr/HLzPhxBGLHpuamqz8/HzLbrdbs2bNsp555hlrcHAw1q2MKNp9Xrx40frpT39qzZ4923I4HFZ6err193//99b//M//XIduQgu3x1D/f8vIyAioGe/nnav1OBHOO6P5PX6ZCecdy4pNn9d67rH9nzcCAAAw1g31DAsAABifCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMN7/BlBe4rM0qhG9AAAAAElFTkSuQmCC", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "scatter(\"PERLND\", pls, \"PWATER\", \"PET\", \"sum\")" + "scatter(\"PERLND\", pls, \"PWATER\", \"IFWO\", \"sum\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### PERLND PWATER SUPY" + "#### PERLND PWATER IGWI" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.116293Z", - "iopub.status.idle": "2024-05-21T21:50:35.116390Z", - "shell.execute_reply": "2024-05-21T21:50:35.116346Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.116341Z" + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "plot(\"PERLND\", pls, \"PWATER\", \"SUPY\", \"sum\")" + "plot(\"PERLND\", pls, \"PWATER\", \"IGWI\", \"sum\")" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.116727Z", - "iopub.status.idle": "2024-05-21T21:50:35.116824Z", - "shell.execute_reply": "2024-05-21T21:50:35.116779Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.116774Z" + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "scatter(\"PERLND\", pls, \"PWATER\", \"SUPY\", \"sum\")" + "scatter(\"PERLND\", pls, \"PWATER\", \"IGWI\", \"sum\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### PERLND PWATER SURO" + "#### PERLND PWATER INFIL" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.117333Z", - "iopub.status.idle": "2024-05-21T21:50:35.117520Z", - "shell.execute_reply": "2024-05-21T21:50:35.117437Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.117429Z" + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "scatter(\"PERLND\", pls, \"PWATER\", \"SURO\", \"sum\")" + "scatter(\"PERLND\", pls, \"PWATER\", \"INFIL\", \"sum\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### PERLND PWATER TAET" + "#### PERLND PWATER LZET" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.118743Z", - "iopub.status.idle": "2024-05-21T21:50:35.118943Z", - "shell.execute_reply": "2024-05-21T21:50:35.118866Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.118852Z" + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "plot(\"PERLND\", pls, \"PWATER\", \"TAET\", \"sum\")" + "plot(\"PERLND\", pls, \"PWATER\", \"LZET\", \"sum\")" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.119459Z", - "iopub.status.idle": "2024-05-21T21:50:35.119661Z", - "shell.execute_reply": "2024-05-21T21:50:35.119610Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.119605Z" + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "scatter(\"PERLND\", pls, \"PWATER\", \"TAET\", \"sum\")" + "scatter(\"PERLND\", pls, \"PWATER\", \"LZET\", \"sum\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### PERLND PWATER UZET" + "#### PERLND PWATER PERC" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.119967Z", - "iopub.status.idle": "2024-05-21T21:50:35.120090Z", - "shell.execute_reply": "2024-05-21T21:50:35.120043Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.120038Z" + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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fLVu2tMwYfPXVV5LU8n0qKiryWppVVFQkSXI4HN3ymSR3wjNgwICW79WoUaNajlmWpZNOOkkvvviiJO/9Qo899pj69++v//mf//G7n8fzs/Dxxx9r3LhxQcW0evVqv01XR48eHXCGy+MPf/iDFi1apBtvvNHne90VO3bs8Pv3IjU11evP3p9hw4bp8ssv1/z58/Xee+/pa1/7mu655x5t3rxZl1xyid544w195zvfUU5Ojnbt2qXFixfriSee0LPPPkt5bQDdJ2wdjgAgjI7WnLQ1T/PRQI/rr7++5Vx/TVc9/v3vfxtJ5pZbbjHGHGluGejxxBNPGGPcTVfPPvtsn/t9+umnxm63B2y66nkkJCSYAQMGmOnTp5vbb7/dVFdXd+j7E0yzWWOMue+++8zw4cNNQkKCKSgoMDfddJNpbGz0Oa+qqsrMnj3bZGRkmKSkJDNlyhSzePFin/Pafo7Wj4svvtjr3KysLDNlypR2YwzUdDWQ888/30gy5557rs+xe++910gygwcPbhn7+OOPjSRzzTXXBLznxo0bjSRz1VVXeY2rA01XAz1af/+Odp9f/epXRpJZsmRJwPg62gzY816BHlOnTvWJ31/T2B07dpi+ffuaGTNmtIw1Nzebp556ypxyyikmIyPDxMXFmezsbHPWWWeZZ555xqshLwB0lWVMF5oeAAAQRp9++qnGjBmjV155RWeffXa4wwEA9DLsGQIA9FrvvPOOSkpKSIQAAJ3CzBAAAACAmMTMEAAAAICYRDIEAAAAICaRDAEAAACISSRDAAAAAGJS1DRddblc2r59u/r16yfLssIdDgAAAIAwMcZo7969GjRokGy2wPM/UZMMbd++Xfn5+eEOAwAAAECEqKioUF5eXsDjUZMM9evXT5L7A6empoY5GgAAAADhUl9fr/z8/JYcIZCoSYY8S+NSU1NJhgAAAAC0u32GAgoAAAAAYhLJEAAAAICYRDIEAAAAICZFzZ4hAAAAIJI5nU41NTWFO4yoEB8fL7vd3uX7kAwBAAAAPcgYo6qqKtXW1oY7lKiSnp6u3NzcLvUYJRkCAAAAepAnERowYID69OnTpV/e4U4uDxw4oOrqaknSwIEDO30vkiEAAACghzidzpZEKDMzM9zhRI3k5GRJUnV1tQYMGNDpJXMUUAAAAAB6iGePUJ8+fcIcSfTxfE+7sg+LZAgAAADoYSyN637d8T0lGQIAAAAQk0iGAAAAAMQkkiEAAAAAPi655BKdc845PuPvvvuuLMtqKRX+8MMPa9y4cUpJSVF6errGjx+vO++8s+X8m2++WZZlybIs2e125efna+7cudq5c2fLOZ7jrR9f+9rXevojUk0OAAAAQOc89thjuvbaa3X//fdr+vTpamho0CeffKJPP/3U67wxY8borbfektPp1Jo1azRnzhxt27ZNr732Wss5TzzxhM4888yW1wkJCT0eP8kQAAAAECLNLz8n7awKbxDZuYr71vndcqt//etfOv/88zVnzpyWsTFjxvicFxcXp9zcXEnS4MGD9fOf/1y///3vdfDgwZYy2Z4mqqFEMgQAAACEys4qma1bwhpCd9a1y83N1ZIlS7RlyxYVFhZ2+Lrk5GS5XC41Nzd3YzTBY88QAAAAAL9eeeUV9e3b1+tx1llntRy/6aablJ6erqKiIo0YMUKXXHKJnnvuOblcroD33LhxoxYsWKDJkyerX79+LeM/+MEPvN7nn//8Z09+NEnMDAEAAAAIYMaMGVqwYIHX2KpVq3ThhRdKkgYOHKgVK1Zo/fr1WrJkiZYvX66LL75Yjz76qF5//XXZbO65l3Xr1qlv375yOp1qaGjQySefrEceecTrvn/605902mmntbweOHBgD386kiEAAAAAAaSkpOiYY47xGtu6davPeWPHjtXYsWN15ZVX6r333tO0adO0ZMkSzZgxQ5I0YsQIvfzyy7Lb7Ro0aJASExN97pGbm+vzXj2NZAgAAAAIlezcbt2z09kYetLo0aMlSfv3728ZS0hICHmi0xEkQwAAAECIdFcVt0jxk5/8RIMGDdIpp5yivLw8VVZW6rbbblN2drZKSkrCHV67KKAAAAAAoFNOO+00rVy5Uuedd56GDx+u733ve0pKStLbb7+tzMzMcIfXLssYY8IdRHeor69XWlqa6urqlJqaGu5wAAAAAB06dEhlZWUqLi5WUlJSuMOJKkf73nY0N2BmCAAAAEBMIhkCAAAAEJNIhoBusm2btHp1uKMAAABAR5EMAd1kzhxp4kQpOnbhAQAARD+SIaCb/Oxn7ufy8vDGAQAAgI4hGQK6yaRJ7uf33w9vHAAAAOgYkiGgG7hc0pAh7q+XLw9vLAAAAOgYkiGgG+zYIR04II0YIaWkhDsaAAAAdERcuAMAooHD4X5+7jnpuOPCGgoAAAA6iJkhoBt4kqHCQqmuTtq9O6zhAAAAoANIhoBu4HBI/ftLqanS0KHS/PnhjggAAKBrLrnkEp1zzjk+4++++64sy1Jtba0k6eGHH9a4ceOUkpKi9PR0jR8/XnfeeWfL+TfffLMsy5JlWbLb7crPz9fcuXO1c+dOSZLD4dCcOXNUXFys5ORkDR06VDfddJMaGxt7/DOyTA7oBj//uXTeeZJlSZMnU1EOAADEhscee0zXXnut7r//fk2fPl0NDQ365JNP9Omnn3qdN2bMGL311ltyOp1as2aN5syZo23btum1117Txo0b5XK59PDDD+uYY47R+vXrddlll2n//v266667ejR+kiGgG6SkSMcc4/66tFS66y53hTkbc68AACCK/etf/9L555+vOXPmtIyNGTPG57y4uDjl5uZKkgYPHqyf//zn+v3vf6+DBw/qzDPP1Jlnntly7pAhQ7Rp0yYtWLCgx5MhflUDusHcudLf/+7+urTUvW/os8/CGxMAAEBPy83N1cqVK7Vly5agrktOTpbL5VJzc7Pf43V1dcrIyOiOEI+KmSGgi1wu6a9/lcaNc7+ePNk9U/TFF5KffxgBAACQJFVWuh+t9e8vFRdLhw5JbVaaSZJOOMH9vGmTtH+/97GiIikjQ9q5U6qo8D7Wr580bFjwMb7yyivq27ev15jT6Wz5+qabbtJ3v/tdFRUVafjw4SopKdHXv/51nXvuubIFWCKzceNGLViwQJMnT1a/fv18jn/11Vd64IEHdPfddwcfcJBIhoAu2rFDamhw/wdIkvr2lfbskeLjwxoWAACIcA8/LN1yi/fYD3/o/kfWrVulCRN8rzHG/XzJJdLKld7H/vIX6cIL3a0+fvYz72MzZ0pvvBF8jDNmzNCCBQu8xlatWqULL7xQkjRw4ECtWLFC69ev15IlS7R8+XJdfPHFevTRR/X666+3JETr1q1T37595XQ61dDQoJNPPlmPPPKIz/tt375dZ555ps477zzNnTs3+ICDRDIEdJGnrLYnGZLciRB7hgAAwNH8+MfSt77lPda/v/s5L09avTrwtU8+6X9mSJLOP18qKfE+5mcCpkNSUlJ0jGdj9GFbt271OW/s2LEaO3asrrzySr333nuaNm2alixZohkzZkiSRowYoZdffll2u12DBg1SYmKizz22b9+uGTNmqKSkxG+i1BNIhoAuat1jyOM//5HOOUf66ispOzscUQEAgEg3cKD74U9S0pElcf6MGBH4WHZ2eH//GD16tCRpf6tsLSEhwSepam3btm2aMWOGJkyYoCeeeCLgErvuRjIEdNG4cdI997h7DHkMHSrt3SutWOH7Lz4AAADR4ic/+YkGDRqkU045RXl5eaqsrNRtt92m7OxslbSdngpg+/btOvnkk1VQUKC77rqrpf+QpJYKdD2FZAjootGj3Y/WCgqkQYOk5ctJhgAAQPQ67bTT9Pjjj2vBggWqqalRVlaWSkpK9PbbbyszM7ND93jzzTf15Zdf6ssvv1ReXp7XMePZJNVDLNPT7xAi9fX1SktLU11dnVJb/xM90MNeekkaPFiaONF7/Lzz3MUVli4NT1wAACD8Dh06pLKyMhUXFyspKSnc4USVo31vO5obsL0b6KJf/UpauNB3vLRU+uADqakp9DEBAACgfSRDQBe4XNKWLe5+AG1dfLG7uAIltgEAACITe4aALqiqkhobvctqe4SgaTIAAAC6gJkhoAvKytzP/pIhSbr9dumaa0IVDQAAAIJBMgR0gWVJJ53k3WOotfp66fnnj3SLBgAAsSlKapZFlO74npIMAV1QWiotWRK4q3NpqbR9u1ReHtq4AABAZIg/vHn4wIEDYY4k+ni+p/Fd2KDNniGgC3bvdidCgf4OenqNLV8eePYIAABEL7vdrvT0dFVXV0uS+vTpI8uywhxV72aM0YEDB1RdXa309HTZ7fZO34tkCOiCWbOk9HT3Ujh/srOlYcPcydAPfhDS0AAAQITIzc2VpJaECN0jPT295XvbWSRDQBc4HNI55xz9nIcecjdlBQAAscmyLA0cOFADBgxQEw0Iu0V8fHyXZoQ8SIaATvL0GApUSc7jlFNCEg4AAIhwdru9W36BR/ehgALQSZWVUlNT+8nQ/v3Sr38trV4dkrAAAADQQcwMAZ3kqRDXXjKUnCw98oiUliZNmNDjYQEAAKCDSIaATiopkerqpJSUo59ns7nPXb48NHEBAACgY1gmB3RBaqrUkaW/paXSihXufUYAAACIDCRDQCfddJP0i1907NzSUmnPHmnTpp6NCQAAAB3HMjmgk95/X8rI6Ni5kydLv/+91Ldvz8YEAACAjiMZAjrJ4ZBOOKFj5/brJ91yS4+GAwAAgCCxTA7oBKfTXU2uvUpyrX31lfTooz0WEgAAAIJEMgR0Qkd7DLW2apV02WXSrl09FhYAAACCQDIEdEJamrRwoTRxYsevKS11P69c2TMxAQAAIDgkQ0An9Osnff/70oABHb+msFAaONBdeAEAAADhRzIEdMJbb0lPPhncNZblnh2i+SoAAEBkIBkCOmHhQmn+/OCvO+ccafz4bg8HAAAAnUBpbaATHI7giid4XHih+wEAAIDwY2YI6ASHQyou7ty1W7ZImzZ1azgAAADoBGaGgCB1psdQaxde6C6k8Nxz3RoWAAAAgsTMEBCkAwfcleQ6u/entNRdUc6Y7o0LAAAAwelUMjR//nwVFxcrKSlJEyZM0LJlywKe+95772nq1KnKzMxUcnKyRo4cqT/96U8+573wwgsaPXq0EhMTNXr0aL344oudCQ3ocf36SX/5izRlSueuLy2Vtm+XKiq6Ny4AAAAEJ+hkaNGiRbrmmmt0/fXXa82aNZo2bZrOOusslZeX+z0/JSVFP/vZz7R06VJ99tlnuuGGG3TDDTfokUceaTlnxYoVmjVrli666CJ9/PHHuuiii3T++edr1apVnf9kQA/ZscO9Z6izSkrcz5TYBgAACC/LmOAW65x44ok64YQTtGDBgpaxUaNG6ZxzztG8efM6dI/vfve7SklJ0V/+8hdJ0qxZs1RfX6/XXnut5ZwzzzxT/fv318KFCzt0z/r6eqWlpamurk6pqalBfCIgOLfe6i6rXVXV+XuUlkqXXCJdfnm3hQUAAIDDOpobBDUz1NjYqNWrV2vmzJle4zNnztTyDv4z95o1a7R8+XJNnz69ZWzFihU+9zzjjDOOes+GhgbV19d7PYBQ6GxZ7daWLycRAgAACLegkqFdu3bJ6XQqJyfHazwnJ0dV7fwzeV5enhITEzVx4kRdeeWVmjt3bsuxqqqqoO85b948paWltTzy8/OD+ShAp3VHMiRJ+/ZJTU1dvw8AAAA6p1MFFCzL8nptjPEZa2vZsmX68MMP9dBDD+nee+/1Wf4W7D2vu+461dXVtTwq2I2OEOmOZOiLL6T0dHdVOQAAAIRHUH2GsrKyZLfbfWZsqqurfWZ22io+3KHy2GOP1Y4dO3TzzTfrBz/4gSQpNzc36HsmJiYqMTExmPCBLnO5pP37u54MDRkipaS4l8udfHJ3RAYAAIBgBTUzlJCQoAkTJmjx4sVe44sXL1ZpaWmH72OMUUNDQ8vrkpISn3u++eabQd0TCAWbzV1Nrqv7fex2d2luKsoBAACET1AzQ5J07bXX6qKLLtLEiRNVUlKiRx55ROXl5briiiskuZevbdu2TU8//bQk6cEHH1RBQYFGjhwpyd136K677tJVV13Vcs+rr75aJ510ku688059+9vf1ksvvaS33npL7733Xnd8RqDb2bqhXXFpqXT//e7Zpu64HwAAAIITdDI0a9Ys1dTU6NZbb1VlZaXGjh2rV199VYWFhZKkyspKr55DLpdL1113ncrKyhQXF6ehQ4fqjjvu0I9//OOWc0pLS/Xss8/qhhtu0I033qihQ4dq0aJFOvHEE7vhIwLdZ9Eid2nttWul+Piu3au0VLrtNmnLFunwKlIAAACEUNB9hiIVfYYQCrfcIi1Y0LUeQx6NjVJzs9SnT9fvBQAAgCM6mhsEPTMExLLuKqstSQkJ7gcAAADCg50KQBC6MxmSpAcflKZO7b77AQAAoONIhoAgdHcylJbmrihXU9N99wQAAEDHsEwOCMKzz0qZmd13P0/1+JUrpbPP7r77AgAAoH3MDAFBOPFE6Zhjuu9+xcVSbi79hgAAAMKBZAjooA0bpF//Wqqr6757WpZ7dohkCAAAIPRIhoAO+uAD6Y9/7P4KcPPmSX/5S/feEwAAAO1jzxDQQQ6He0lbcnL33nf48O69HwAAADqGmSGgg7q7klxrV14pPfNMz9wbAAAA/pEMAR3kcLgLHvSEjz+WXn65Z+4NAAAA/1gmB3TQt74l5eX1zL1LS91luwEAABA6zAwBHXTttdL55/fMvUtLpYoK9wMAAAChQTIEdEB9vbRkiXTgQM/cv6TE/UyJbQAAgNAhGQI6YPVq6eSTpa1be+b+OTnSo49Kkyf3zP0BAADgiz1DQAc4HO7nwsKee485c3ru3gAAAPDFzBDQAQ6HNGiQlJjYc++xZYt0/fXS/v099x4AAAA4gmQI6ICe7DHkUVcn3X679OGHPfs+AAAAcCMZAjogLk469tiefY8xY6R+/SiiAAAAECrsGQI64LHHev497HZpyhSSIQAAgFBhZghohzHux9HPcclVvlmuzz+VaW7q9HuVlrqTofbeDwAAAF3HzBDQDofDvUTujTekqVN9j5umRjmffUJm8+fugX6pirvkSlkZWUG/19lnS42N0qFDUnJy1+IGAADA0TEzBLTD4XBXeBswwP9x88nqI4mQJO2tl/O1Fzv1XpMmuYsokAgBAAD0PJIhoB1lZe7nggL/x11ffOYzZr7cJLNvb6fe79NPpbff7tSlAAAACALJENCO9noMmZpd/kZlPt/Qqfd74AHpqqs6dSkAAACCQDIEtONoPYaMyyXt8ZcMSa6N6zv1fqWl0mefSbt3d+pyAAAAdBDJENCOu+6SnngiwMH6Wsnp9HvIbP5cpuFQ0O9XWup+Xrky6EsBAAAQBJIhoB0DBkjDh/s/Zmp2Br7Q6ZT5clPQ7zdkiPs96TcEAADQs0iGgKNobJS+/33pv//1f9zs9r9EzsO1cV3Q72lZ7vdMSwv6UgAAAASBPkPAUVRUSIsWSXPnBjjBb/GEI8wXn8k4m2XZg/urdt99QZ0OAACATmBmCDgKh8P9HLCAwu6jLJOTpIZDMo6vOvXe27ZRRAEAAKAnkQwBR+FwuJet5ef7P97eMjlJMp8Fv1SuocG9d+iZZ4K+FAAAAB1EMgQcxdF6DBmXU9pT0+49XJs2yBhXUO+bmChNmCC9/35QlwEAACAI7BkCjuKUU6S8vAAHa/dIrg4kOfvqZbZVyMorDOq9S0ul558P6hIAAAAEgZkh4ChmzJB+/GP/xzqyRK7l3E5UlSstlcrLpa1bg74UAAAAHUAyBBzF889LZWX+jx21x1Abro3rg37v0lIpPV3avDnoSwEAANABJENAAI2N0qxZ0n/+E+CEADND1jEjfQdrdsrs2hHU++fmSjU10kknBXUZAAAAOohkCAigokIy5mhltf0kQ337yXbcBL/nuz4LfnbIZnMnZQAAAOh+JENAAO32GPKzTM7KyJY1bJRks/uevyn4ZOj556WMDOngwaAvBQAAQDtIhoAAjtZjyDid7mpybWVkyUpKllU81PeabeUy9XVBxTBsmLR/v/Thh0FdBgAAgA4gGQICSEyUTjtNSkjwc7B2t+Snd5CVmeV+Hnms33u6gpwdOvZYqW9fafnyoC4DAABAB5AMAQFceKH05pv+jwWqJGdlZEuSbCPG+L8uyKpydrs0ZQrJEAAAQE8gGQIC2LvXXUDBn4DJkGdmqF+arMEFvtc5vpQ5FNwGoNJSadWqwLEAAACgc0iGgABGjZJuvTXAwUANVzOyWr70u1TO5ZL5/NOg4rj6aumLL9z7lwAAANB9SIYAPxoapO3b/RdPkCSz28/MUL80WfFHNhjZRo71e22w+4YyMqR+/YK6BAAAAB1AMgT40W6PoRrfmSHPErmW11kDpKwBvtd+sVGmuSmoeK69Vvrtb4O6BAAAAO0gGQL8KCtzP/tLhkxzk1RX63vgcPGE1mz+lso1Ncps/iKoeA4ckF55JahLAAAA0A6SIcAPh0Oy2aS8PD8H99RI8q1mYGVk+Y4FWiq3cV1Q8ZSWShs2SLW1QV0GAACAoyAZAvz40Y/cS+X89Rjyt0RO8l0mJ0nWoDypX6rvPTZ9KuPy7VMUSGmp+3nFig5fAgAAgHaQDAF+2O3SoEH+j/ktnqAjPYa8xiybbCP8zA4d2CdT4ehwPEOHStnZ9BsCAADoTiRDgB8//rE0f36Ag35nhiwpI9Pv6YGWygXTgNWypOeec8cFAACA7kEyBPjxr39JO3b4P2b89RhKS5cVF+/3fKtoqJSY5DPu2rReJohOqiefHGAPEwAAADqFZAho49AhqbLyKGW1/SyT81c8oeWYPU7W8NG+B/bUSNWVHY5r1y7piiukT4Pr2QoAAIAASIaANsrL3c9+y2o3NUr1dT7jR0uGpKM0YA1iqVxKivT449I773T4EgAAABwFyRDQhsPhfvY7M7S7xv9Fmb7FE1qzjhkp2eN8xoNJhpKTpQkTKKIAAADQXUiGgDZGjZIeesj//pyAleTaS4YSEmUNHe57oGqbTO3uDsdWWiq9/36HTwcAAMBRkAwBbeTnu6u2xfuphxCwx1A7y+Qk+S+xreBmh0pLpS1bpG3bOnwJAAAAAiAZAtp48UVp8WL/x/zODFmW1D+j3ftaI0a7z217zyCSoWnTpLvukhITO3wJAAAAAiAZAtr44x+lv/0twEF/ZbXTM2T52Q/UlpXST1Z+sc+4Kd8sc2Bfh2IbMED65S+lrPYnogAAANAOkiGgDYfjKGW1/SyT68gSuZZz/VWVM0bm847Xy/74Y+nhhzt8OgAAAAIgGQJaOVqPIdPYIO2r9xkPJhnqjhLb770nXXWVdPBghy8BAACAHyRDQCtH6zGkGv+V5Norq92a1T9TyhnoM26+2uROtjqgtFRqapJWr+7w2wIAAMAPkiGgFZdL+uY3pWOO8T1m/O0XUnAzQ1KAqnLNzTJffd6h64891t2AlX5DAAAAXUMyBLQycqT08ssBegwFKqsdxMyQdLSlcus6dH1cnHTiiSRDAAAAXdV+CSwghlRWSsnJUnq67zG/ZbVtNim9f3BvkjtYSusv1e3xvv/nn8o4nbLs9nZvccEFUlVVcG8LAAAAbyRDQCvXXutOiN5918/BQGW1be0nL61ZliXbyLFyrVrmfeDQQZnyzbKKh7V7jzlzgnpLAAAA+MEyOaCVoMtqB7lEruW6AEvlzGcdWyonSevXS5s2dertAQAAIJIhwIvDIRX79kWVOXRQ8tMYNdjiCS3XFRRLyX18xl2b1ssY06F7fP/70j33dOrtAQAAIJIhoMXBg+59OH57DAWoJKfOJkM2u6wRY3wP1NdJlVs7dI/SUoooAAAAdAXJEHDY9u3uSm3B9Bjq7DI5KUCJbXW8AWtpqbRhg1Rb2+kQAAAAYhrJEHDY0KHSoUPS177me6y7egx5XTt0hBSf4DPe0WRo6lTJGGnVqk6HAAAAENNIhoBW7Hb3oy2/yZDd7i6R3UlWfLw7IWprZ5VMgJmo1o45Rpo0Sdq7t9MhAAAAxDSSIeCwO+6QzjsvwEF/yUn/TFm2rv0VCtyAtf3ZIcuS/vtf6dxzuxQCAABAzCIZAg5bu1aqqfF/zN/MUFf2C7XcY/hoyfL9a2g2dWypnCRVV0tOZ5dDAQAAiDkkQ8BhgXoMmYMHpIMHfMa7sl+o5R7JfWQVDfF9z4otMvvq271+1SopJ8fdcwgAAADB6VQyNH/+fBUXFyspKUkTJkzQsmXLAp77j3/8Q6effrqys7OVmpqqkpISvfHGG17nPPnkk7Isy+dx6NChzoQHdErAZCjQ/p2Mrs8MSZLlt6qckdm0od1rjztOio+X3n+/W0IBAACIKUEnQ4sWLdI111yj66+/XmvWrNG0adN01llnqby83O/5S5cu1emnn65XX31Vq1ev1owZM/TNb35Ta9as8TovNTVVlZWVXo+kpKTOfSogSAcPSjt2BCirHaiSXGbXZ4akru0bSk6WTjiBfkMAAACdERfsBffcc4/mzJmjuXPnSpLuvfdevfHGG1qwYIHmzZvnc/69997r9fr222/XSy+9pH/9618aP358y7hlWcrNzQ02HKBb2O3Sa69Jxx7reyzQzFB3LJOTJCutv6yBeTJtmq2asi9kGg7JSjz6PwqUlkr//Ge3hAIAABBTgpoZamxs1OrVqzVz5kyv8ZkzZ2p5B/9p2uVyae/evcrIyPAa37dvnwoLC5WXl6dvfOMbPjNHbTU0NKi+vt7rAXRWQoJ05pnS4MG+x/yW1Y6Lk1LTuu39LX+zQ06nzBeftXttaam0c6e0Z0+3hQMAABATgkqGdu3aJafTqZycHK/xnJwcVVVVdeged999t/bv36/zzz+/ZWzkyJF68skn9fLLL2vhwoVKSkrS1KlT9cUXXwS8z7x585SWltbyyM/PD+ajAF6WLJH+7/8CHPSXDGVkyfJTBa6zbCP9TElJcnWgqty3vuVOhPp3vuURAABATOrUb3OWZXm9Nsb4jPmzcOFC3XzzzVq0aJEGDBjQMj5lyhRdeOGFGjdunKZNm6bnnntOw4cP1wMPPBDwXtddd53q6upaHhUVFZ35KIAk6dVXpYcf9h03xvhdJmd1U/GEFtk5kp9ld+bzz2Sam496aUKCe6LKmO4NCQAAINoFlQxlZWXJbrf7zAJVV1f7zBa1tWjRIs2ZM0fPPfecTjvttKMHZbNp0qRJR50ZSkxMVGpqqtcD6KxAleR0YJ/U4FvVsLv2C7Xcz7Jk81dVrrFBxvFlu9ffcot0yindGhIAAEDUCyoZSkhI0IQJE7R48WKv8cWLF6u0tDTgdQsXLtQll1yiZ555RmeffXa772OM0dq1azVw4MBgwgM6LXBZ7Z6tJOd1z1H+q8qZDlSVy8x0l9emGj0AAEDHBb1M7tprr9Wjjz6qxx9/XJ999pl+8YtfqLy8XFdccYUk9/K12bNnt5y/cOFCzZ49W3fffbemTJmiqqoqVVVVqa6uruWcW265RW+88YY2b96stWvXas6cOVq7dm3LPYGeFnBmaHfP9hhqzRpcKKX08xl3bVovY1xHvba0VGpqklav7vawAAAAolbQydCsWbN077336tZbb9Xxxx+vpUuX6tVXX1VhYaEkqbKy0qvn0MMPP6zm5mZdeeWVGjhwYMvj6quvbjmntrZWl19+uUaNGqWZM2dq27ZtWrp0qSZPntwNHxE4OpdLOu88aepU32MhnRmy2WSNGON7YN9ema3++3h5HHec1KcP/YYAAACCYRkTHduu6+vrlZaWprq6OvYPods0P/+0zKcfew/GJyjuuts7VDQkWK4vPpPzmUd9xm2lM2Q//RtHvfaUU6TUVHoOAQAAdDQ36L7awEAvtWOHtHate4aoLeNvmVxGVo8kQpJkFQ+TEhJ9xl0b16m9f7d45BHpySd7JCwAAICoRDKEmPfCC9KkSb6lqY0xkp9lcj2xRK7l3nFxsoaN9D2we5e0a8dRrz3mGCk9vWfiAgAAiEYkQ4h5DodUUCDZ7W0O7NsrNTX6nN/tPYbaCNiAtZ2qck6nNGuW9OKLPREVAABA9CEZQswLWFY7QCW57u4x5HP/Y0ZKtraZWfsltu12af166Y03eioyAACA6EIyhJjncEjFxX4OBKgkpx5cJidJVlKyrOJjfMbN9gqZ+tqjXltaSkU5AACAjiIZQswzRho61M94wJmhnl0mJ0lWJ5fKlZa6Z4datfECAABAACRDiHkffCBdd53vuNntZ2YoIVFK6dvjMdn89RuSZDa1nwwZI61a1RNRAQAARBeSISAAfw1XrczsHiur7fU+/VJl5RX6xuT4SubggYDXDR8uPfWUNG5cT0YHAAAQHUiGENNee03Ky5N2tlkRZ4zLXc66rR7eL9SaNXKs76DLJfPFZ4GvsaTZs6WcnB4MDAAAIEqQDCGmbd4sVVdLmZltDuytl5qbfM4PxX4hj86W2N6wQfrFL9yltgEAABAYyRBimsMhFRZKtjZ/E/wtkZN6vqy213tlZktZvlM85suNMk2+iZrHrl3Svfe6kyIAAAAERjKEmBaox5ACVJJTZuhmhiTJ5m+pXFOjzObPA14zaZIUF0eJbQAAgPaQDCGmBWy4GgEzQ1KAfUM6+lK5Pn2k8eNJhgAAANoTF+4AgHD6298ku9133G+PoaRkWX1Sej6oVqxBeVK/NGmvd+Mg8/kGGZdTls1P8HKX2P7Xv0IRIQAAQO9FMoSYNny4/3F/PYasEC+RkyTLssk2cqxcH7zvfeDAfpkKh6xCP91iJZ17rpSbK7lcvvuhAAAA4MavSYhZZWXSj38sbdvmPW5cAcpqh3iJnEegpXLmKEvlvvY16be/JRECAAA4Gn5VQsz69FPpkUf8HKiv9VuXOtT7hVret3ColJTsM+7auF7GmIDXrVwpvf12T0YGAADQu5EMIWaVlUnx8dLAgd7jpsZ/JblwLJOTJMtulzV8tO+B2t3SjsqA1913n/T73/dgYAAAAL0cyRBiVsAeQ/6WyElhWyYnSbYRgarKrQt4TWmp9OGHUkNDT0UFAADQu5EMIWYF7DEUqKx2mGaGJMk6ZoRk9613crQS26WlUmOjtHp1T0YGAADQe5EMIWadc450ySW+437LavdJkeVn306oWAmJsob6KX23Y7vMnhq/1xx3nLvnEP2GAAAA/CMZQsy68ELphz/0HfdbVjuMS+Q8bIEasG7a4Hc8Pl66+GIpI6MnowIAAOi9SIYQkw4elF5+Wdq923vcuJySv5mWMC6R87CGj5Esy2fcHGXf0Pz50o9+1JNRAQAA9F4kQ4hJX34pffvb0saNbQ7U7nF3Km0jEmaGrJS+sgqKfcZNeZnM/n1+rzHG/Rlra3s4OAAAgF6IZAgxyeFwP7ctoBCoklwkJEOSZPmrKmeMzOef+j1/zx5p1CjplVd6ODAAAIBeiGQIMcnhkBISpNxc7/FI6zHUVsB9QwGWymVkuJOh99/vyagAAAB6J5IhxKRAPYYUgT2GWrP6Z0o5g3zGzVefyzT6byhUWkpFOQAAAH9IhhCT+vSRSkp8x/0uk+vbT1ZiUs8H1UF+Z4eczTJfbfJ7fmmptG6dVF/fw4EBAAD0MiRDiEl/+IP01FO+4/6WyVkZkbFEziPwUjn/DVhLS6VBg47skwIAAICbb0t7IAY0Nrr3DLVmnE53Nbm2ImSJXIucQVJ6hlTrXRfcfP6pjNMpy273Gh8xQtq6NZQBAgAA9A7MDCHm1NVJSUnSP/7R5kDtbsn4KaudGVnJkGVZsvmrKnfooMyWr/yc734+cKCHAwMAAOhlSIYQc7ZscfffGTjQezxgJbkIWyYnSVaApXImwFK5BQvcS+Wczp6MCgAAoHchGULM8eydKW7TvzRgj6EImxmSJKugSEru4zPu2rhexhif8VGj3DNin/pvRwQAABCTSIYQcxwO9zK5nJw2BwLMDEXcniFJls0ua8QY3wN762S2V/gMT5ok2e2U2AYAAGiNZAgxx9NjyLOXxsPvzFC/NFnxCb7jESBQVTl/S+VSUqTjjycZAgAAaI1kCDHnD3+Q3njDd9xvWe0IXCLnYQ0ZIflJ1Fyb/O8bmjpV+uijno4KAACg9yAZQsxJSXHPDLVmmpukulrfkyOweIKHFR8v65gRvgd27vCb2N1yC8kQAABAayRDiDnf+570+uttBvfUSPItPGBF4H6h1vyW2Jbk2rjOZyw9XYqP7+GAAAAAehGSIcSUujp3f6HaWu9xU9N7Ksm1Zg0fLVm+f40Dldj+4Q+lm2/u4aAAAAB6CZIhxJQtW9zPRUXe42Z37+kx1JqV3EdW0VCfcbN1i8zeep/x5mbprbdCERkAAEDkIxlCTCkrcz+3TYbkd2bIkjIyeziirgvUgNW1aYPPWGmp9OGHUkNDT0cFAAAQ+UiGEFMC9RjyW1Y7LV1WXORvsrH56zckyfipKjd1qjsRWrOmp6MCAACIfCRDiCknnSTdd5+/HkN+ympHePEEDyutv6xB+T7jZvMXMocOeo2NGyclJ9NvCAAAQJLiwh0AEErjx7sfrZmmRqm+zufc3pIMSZI1YqzM9grvQZdT5suNssYe+cDx8dKbb0qjR4c4QAAAgAjEzBBiyjPPSJ980mZwd43/kzMju3hCa7ZA+4b8VJX72tekjIyejggAACDykQwhpvz0p9Jrr3mPBawk14uSIWXnSH5msswXn8k0N3uNbdkiXXDBkcp6AAAAsYpkCDGjttbdZ8inrHagHkO9aZmcZfmfHWpskCn7wmsoJUVauFB6//0QBQcAABChSIYQMxwO93OHegxZltS/d60lC1Riu20D1qwsacQIkiEAAACSIcSMQMmQ/JXVTs+QZe9d9UWsvEIppZ/PuGvTBhmXy2ustJSKcgAAACRDiBnJydKpp0oDBniP+1sm15uWyHlYls1/z6H9e2W2eW8QKi11F5LYuzdEwQEAAEQgkiHEjDPOkN56y7vHkGlskPbV+5zbG5MhqeNL5c44Q1qwwLffEgAAQCwhGULMqK6WmpraDPpbIif1qrLarVnFw6SERJ9x18b1Msa0vM7Ply6/XOrbN5TRAQAARBaSIcSMmTOlq6/2HouGSnKtWXFxsoaN8j2we5e0c4fX0PvvS488EqLAAAAAIhDJEGKGw9HBSnLqZT2G2uhoA9Z335V+/WupTW0FAACAmEEyhJgQsMeQv2VyNpuU3j8UYfUIa9goyWb3GTcb13m9Li11f08+/TRUkQEAAEQWkiHEhIBltWv8zAylZ8jyk0z0FlZikqwhw3zGTeVWmbo9La8nTZLsdkpsAwCA2EUyhJhQUeF+9pkZ8ldWuxcvkfOwRgRYKrdpQ8vXfftK48aRDAEAgNhFMoSY8M1vSvX1UnarPMccOigd2Odzbm8tntCabeQYSb51s9sulbvsMunEE0MUFAAAQISJC3cAQKj06+f92u9+IUmKgmTI6psqK69AZqt3s1Xj2Cxz8ICs5D6SpCuuCEd0AAAAkYGZIcSEq66Sfv/7NoP+9gspOpbJSQEasBqXzOdHKiYY4y6x/fnnIQwMAAAgQpAMISYsXSrtajMRFGhmKBqWyUmSbeSxfsfbltieNUt67LFQRAQAABBZSIYQ9YxxV5MrLm4z7i8ZstultN5bVrs1KzNbys7xGTdfbpRpanSfY7lLbFNEAQAAxCKSIUS92lp38YQOldXunynLFj1/LWz+qso1N8lsPrIurrRU+uADqbExhIEBAABEgOj5rQ8IoKzM/dyRhqvRskTOwxrV/lK50lKpoUFasyZUUQEAAEQGkiFEvcJCaeFCaeTII2Pm4AHp4AGfc62M6Cie4GENzJP6pfmMm00bZFxOSdLxx7sbsO7zrTIOAAAQ1UiGEPUyM6Xvf9+7tLYJUElOUVJJzsOyLNn8VZU7eECm3CFJSkiQ/vtf6dRTQxsbAABAuJEMIer985/Ss8+2GQxUSS4zupbJSQFKbMu7Aasx0ubN7mcAAIBYQTKEqPf449Jf/+o9FmhmKNr2DEmSVThUSkr2GXdtXC9zOPt59VVp6FCpvDzU0QEAAIQPyRCiXllZx4onKC5OSvXdX9PbWXa7rOGjfQ/U7ZF2bJckTZ7sHqLENgAAiCUkQ4hqnh5DPmW1/SVDGVmyrOj8K+F335Ak12fupXLZ2dLw4dL774cyKgAAgPCKzt/8gMN273ZXSWudDBlj/C6Ti7ZKcq1ZQ0e4Z77acG3yLrHNzBAAAIglJEOIao2N0oUXSmPGtBo8sF9qOORzbjTuF/KwEhJlDRnue2BHpcyeGknuZGjHDpqvAgCA2EEyhKg2cKD0l79Io0YdGTO7AxRPiMJKcq3ZRh69Aeull0pbt7pLbQMAAMQCkiFEta1b/VRIq/FfVltRvExOkruIgmX5jJvDyVBcnPuw0xnqyAAAAMKjU8nQ/PnzVVxcrKSkJE2YMEHLli0LeO4//vEPnX766crOzlZqaqpKSkr0xhtv+Jz3wgsvaPTo0UpMTNTo0aP14osvdiY0wMudd0pnn+095reSnKJ/ZshK6SuroNhn3FSUyezfK0n66U+lb3871JEBAACER9DJ0KJFi3TNNdfo+uuv15o1azRt2jSdddZZKg/QoGTp0qU6/fTT9eqrr2r16tWaMWOGvvnNb2rNmjUt56xYsUKzZs3SRRddpI8//lgXXXSRzj//fK1atarznwyQ/0pyfnsMxSdIfVNDEVJYWf6Wyhkjs+lTSe5lhe+/L7lcIQ4MAAAgDCxjgus5f+KJJ+qEE07QggULWsZGjRqlc845R/PmzevQPcaMGaNZs2bp97//vSRp1qxZqq+v12uvvdZyzplnnqn+/ftr4cKFHbpnfX290tLSVFdXp9TU6P+lFh1z7LHSySdLDzxwZKzp4bulqu3eJ+YMUvwVvwxpbOFg9tSo+f7bfcat4aMV94M5+s9/pFNPlTZskEb7aU0EAADQG3Q0NwhqZqixsVGrV6/WzJkzvcZnzpyp5R2syetyubR3715lZGS0jK1YscLnnmeccUaH7wn446/HkDHG756haF8i52H1z5RyBvmMm68+l2ls0OTJks1GiW0AABAbgkqGdu3aJafTqZycHK/xnJwcVVVVdeged999t/bv36/zzz+/ZayqqiroezY0NKi+vt7rAbRWX++ujOa1TG7fXqnJt3Z0NPcYastvA1Zns8yXG9W3rzRuHMkQAACIDZ0qoGC1qUhljPEZ82fhwoW6+eabtWjRIg0YMKBL95w3b57S0tJaHvn5+UF8AsSCtDSppkb67nePjAUsqx3FPYbaaq/E9j/+Ic2fH8qIAAAAwiOoZCgrK0t2u91nxqa6utpnZqetRYsWac6cOXruued02mmneR3Lzc0N+p7XXXed6urqWh4VFRXBfBTEEK+cOlBZ7RhZJidJyhkopWf4DJvPP5VxOlVUJCUlhT4sAACAUAsqGUpISNCECRO0ePFir/HFixertLQ04HULFy7UJZdcomeeeUZnt61zLKmkpMTnnm+++eZR75mYmKjU1FSvB9Dan/8snXii91jgmaHYWSZnWZb/pXINh2QcX2rfPumMM6Q33wx9bAAAAKEU9DK5a6+9Vo8++qgef/xxffbZZ/rFL36h8vJyXXHFFZLcMzazZ89uOX/hwoWaPXu27r77bk2ZMkVVVVWqqqpSXV1dyzlXX3213nzzTd15553auHGj7rzzTr311lu65ppruv4JEbM2bpQOHPAe89tjKCFRSukbmqAihOUvGZK7AWtKirR+vfTOOyEOCgAAIMSCToZmzZqle++9V7feequOP/54LV26VK+++qoKCwslSZWVlV49hx5++GE1Nzfryiuv1MCBA1seV199dcs5paWlevbZZ/XEE0/ouOOO05NPPqlFixbpxLb/rA8EwX+PIT/JUGZ2h/a8RRMrv1jqk+Iz7tq0QZJLpaUUUQAAANEv6D5DkYo+Q2hr7FjplFOk++93vzbGpebbfyc1N3mdZ409XnHfuygMEYZX80uLZNb+12fcPvdq3fdcgX73O6muzl2RDwAAoDfpkT5DQG/hr8eQ9tb7JEJSbO0Xas3vviG5l8qVlkqHDklr14Y2JgAAgFAiGUJUMkZavFg677xWYwEqycVSWe3WrCHDpXjfaR/XxvUaP176+9+lESPCEBgAAECIkAwhKtlsUkmJ5NV+KkAlOWXG5syQFR8v65iRvgd27VB8fbW+9z13ryYAAIBoRTKEqLRihfTrX0tNrVbFMTPkK9BSOdfG9Vq1Svr5z92zbAAAANGIZAhR6b33pIcekuLijoz57TGUlCzLT1W1WGENG+WeRmvDbFynqirpgQck+hkDAIBoRTKEqORwSMXFUuuK2f56DFkxukTOw0ruI6toqM+42VauKcfWS6LENgAAiF4kQ4hKbSvJGeOSdtf4nhjDS+Q8rBH+l8pl7V6vYcOk998PcUAAAAAhQjKEqORTVruuVnI2+5wXy/uFPAKX2F5H81UAABDV4to/Beh9fvADacKEI6/9LZGTWCYnSVZquqxB+TLbvTcHmbIvddH3G/TFlMQwRQYAANCzSIYQlW64wft1oEpyLJNzs0aO9UmG5HJpxuANOvXME8ITFAAAQA9jmRyizs6d0pIlUkNDq8Ea/z2GmBlyO1qJ7TfekP7znxAHBAAAEALMDCHqvPuudP750p49UuLhFV5+y2r3SZGVlBzS2CJWVo67+WybpNF8uVF/etcle5xNp5wSptgAAAB6CDNDiDplZVJampSefmTMb1ltlsi1sCxLNn9V5RobVDKyRitWSC5X6OMCAADoSSRDiDo+ZbVdTmmPn7LaLJHzYgVYKjclc4P27JE2bQpxQAAAAD2MZAhRx6esdu0ev9MazAx5s/IKpL79fMYn2pbLZjOU2AYAAFGHZAhRJzlZGjPmyOuAZbVJhrxYls3vUrlUZ41+NGuvMjLCEBQAAEAPooACos4LL3i/NlSS6zBr5Fhp9Qqf8YcueVf2md8KQ0QAAAA9h5khRBVj3A8vAWaG6DHkyyo+RkpM8hlv2PCpVq0y2rs3DEEBAAD0EJIhRJX//lfq10/67LMjY36XyaX0k+Xnl/5YZ9njZA0b6TO+dYtTU6ZYWrIkDEEBAAD0EJIhRBWHQ9q/Xxo48MiYv2VyLJELzN++oaL03crNaKCIAgAAiCokQ4gqDod3jyHjdLqrybXFErmArGGjJLvde8ySphSWkwwBAICoQjKEqOJbVnu3ZPyU1c4kGQrESkySVTzMZ7w0+1P9979GTU1hCAoAAKAHkAwhqjgcUnHxkdcBK8llsEzuaGx+GrCWFjhUnHtAlZVhCAgAAKAHkAwhqjzxhPSnPx15HbDHEDNDR2WNGCPJ8hqbnFeuj296WgUF4YkJAACgu5EMIark5rZZJhdgZog9Q0dn9U2VlV/oM+5ybNbubfvDEBEAAED3IxlC1Ni5U5o1S/r00yNjfmeG+qXJik8IXWC9lOWnqtz/vnuqxk2ID0M0AAAA3Y9kCFHjq6+k556T1wZ/f8kQS+Q6xt++oWNzKrV1R4IqKsIQEAAAQDcjGULUcDjcz55lcqa5WarzV1ab4gkdYWVmS9m5XmNT8h2SpPeXNochIgAAgO5FMoSo4XBI/fu7+wxJkvbUSMb4nGexX6jD2s4O5fTdp2Mydmr5G7XhCQgAAKAbkQwharTtMWR2ByirzTK5DvO3VG5KvkPr1jjDEA0AAED3igt3AEB3+fa3pa997chregx1g4F5UmqaVF/XMnTf119U3zS7jOtmWTZ7GIMDAADoGpIhRI2zzmozUOOvx5AlZWSGIpyoYFmWbCPGyvXB+y1j/RIbpEOS2VImq/iYMEYHAADQNSyTQ1QwRnr6aWnr1lZj/spqp6XLiqM0dDCsUcf6jJ351I/1f384FIZoAAAAug/JEKLCjh3SxRdLH310ZMzfniGKJwTPKhgiJSV7jdltRstWJcr4KVABAADQW5AMISr4lNVuavTa5+JBMhQ8y26XNXy019iUfIdWlg2Sa/u2MEUFAADQdSRDiAplZe7nwsLDA7tr/J+YSfGEzmhbVa4k36HdB1O08a2yMEUEAADQdSRDiAptewwFLKvNzFCnWENHSHFH6q1MHrxFllxa/tb+MEYFAADQNSRDiAppadLMmUdeG7+V5Ogx1FlWQqI7ITosNalB7829X+cVLPFfqAIAAKAXIBlCVPjpT6Vnnz3y2u/MkGVJ/Smr3Vm2Ed5L5SblVSgloVGujevDFBEAAEDXkAwhKtTWustrt/A3W5GeIctOa63OskaMdieUh22oztE5f5ujXau/DGNUAAAAnUcyhF7P5ZJycqT584+M+Vsmx36hrrH69HWX2T4sOa5Jr34xWitXWjL79oYxMgAAgM4hGUKvV1UlNTZKBQXu16axQdpX73MeyVDXWa2qyhX3362clHqtqCiU+XxDGKMCAADoHJIh9Hptewz5XSInUVa7G7QusW1Zh/sNVRSxbwgAAPRKJEPo9TzJkKfHUMBKcswMdZmVniHlDmp5XZK/RR9sy1fjF1/KNBwKY2QAAADBYzc5ej2HQ8rIkFJT3a8D9hhiZqhb2EaMlatquyTpWyPXaXBqrVzNLpkvN8kaMy7M0QEAAHQcM0Po9X7zG+mzz4689tv3xmaT0vuHLqgoZht1bMvXx2TWaNaxa5UY55Rr07owRgUAABA8ZobQ69nt0oABrQZq/MwMpWfIstlDFlNUGzBQSs+QandLkl77fKS21adrbuJaGWcz5csBAECvwcwQer3zzpP+8pcjr/3NDLFErvtYluVVSOHdsmG6Y9mpUsMhGcdXYYwMAAAgOCRD6NVcLumll6S6Ovdr03BI2r/P5zyKJ3Qva+SRpXIlBWUqr8vQ1ro0GarKAQCAXoRkCL1aZaXU1NSqrLa/JXKSRDLUraz8IqlPiiRpSt4WSdLKrYVybVwvY1xhjAwAAKDjSIbQq3nKahcXu59NgGSIZXLdy7LZZA0fI0nK7bdXQ/rv0sqKImlfvcy2ivAGBwAA0EEkQ+jVfHoMBWi4yjK57te6qtzPpyzV5LxySWKpHAAA6DUo+4RebcoU6bHHpL593a/9JkN2u5RGWe3uZhUPk+ITpKZG/fTE91vGXZvWy37a2WGMDAAAoGOYGUKvNnSo9KMftRrwt0yuf6YsGz/q3c2Kj5d1zEhJUrPTpte/GKmvdmdKu6pl9tWHOToAAID28RsierW//lVauvTIa79ltVki12Nsw9zJkGUZXfj3C7Vo3XhJkil3hDEqAACAjiEZQq92yy3Syy+7vzYHD0gHD/icY2VQPKGnWPnuyhV2m9GUvC1aUVEkSTLlZWGMCgAAoGNIhtBruVzSli3tV5JTJjNDPSYzu6XEdklBmVZWFMnlsmQqSIYAAEDkIxlCr+XTY4hKciFnWZa755Ck0nyH6hqStWFnjkzlNpnGhvAGBwAA0A6SIfRaZYcnHzzJED2GwsMqcE/NTc4r17TCr3SwKUEyLvoNAQCAiEdpbfRaSUnSt77VTo+huDgpNS20gcUYz76hlIRGvX3p/JZxU14mFR8TrrAAAADaxcwQeq2JE6WXXjrSY8jvMrmMLFkWP+Y9yRqY50465S6xvW5HriSxbwgAAEQ8fktEr1VRIdXWur82xvhdJkcluZ5nxcXJGlQgSXpp41hNWPArba9Pldm6RcblCnN0AAAAgZEMode69FLp8ssPvziwX2o45HMOxRNCw7NvqCTfIUlaXlHk/vOorgpfUAAAAO0gGUKvVVbWqnjC7kDFE0iGQsFTUW5Qar2K02u0otydHLlYKgcAACIYyRB6JadTKi9vVVa7xn9ZbbFMLiQ8yZDk7je0nOarAACgFyAZQq+0fbvU3Nx6ZihAjyFmhkLCSu4jZbsLJ0wtKNP+xgQ1O20yFY7wBgYAAHAUJEPolSor3QXMjrpMLj5B6psa0rhime3w7NDcCSv1yc/+qDi7S6rbI1O3J7yBAQAABEAyhF5p8mTp0CFp5Ej3a+NvmVxGlizLCm1gMcxTRMHzLT/U5C63zewQAACIVCRD6LXsdslmc5fV9tdjiCVyoeVJhiRp7j9n6bxFl0hi3xAAAIhcJEPolX71K+myyw6/2L9XamzwOYceQyGWntGyLHFoxi6trCiSy2VRUQ4AAEQskiH0Sh99JNXXu7/212xVosdQqFmWJaugSJJUmu9QXUOyNuzMkXZUyvjpAQUAABBuJEPolRyODpTVZplcyFn57qVykwaXK87m1PLyYskYma1bwhwZAACAL5Ih9DptewwFbLjKMrmQ8+wb6pPQpONzt+nDbQWS2DcEAAAiU1y4AwCC1aEeQwmJUkrfkMYFycoZ5C5p3tSoFy94TFl99kuSDPuGAABABOrUzND8+fNVXFyspKQkTZgwQcuWLQt4bmVlpS644AKNGDFCNptN11xzjc85Tz75pHu/QZvHoUPsM4CvzEzptdfc5bWlAGW1M7Mpqx0Glt0uK889G5TTd5/sNiNJMlvLZZzOcIYGAADgI+hkaNGiRbrmmmt0/fXXa82aNZo2bZrOOusslZeX+z2/oaFB2dnZuv766zVu3LiA901NTVVlZaXXIykpKdjwEAP69JHOPNOdFBnj8l9Wm+IJYePZN3SwKU7THr1K//xsrNTUKLNje5gjAwAA8BZ0MnTPPfdozpw5mjt3rkaNGqV7771X+fn5WrBggd/zi4qKdN9992n27NlKS0sLeF/LspSbm+v1APx55RXp/vsPv9hbLzU3+ZxDMhQ+nn1DyfHN2rm/r5Y6hkpi3xAAAIg8QSVDjY2NWr16tWbOnOk1PnPmTC1fvrxLgezbt0+FhYXKy8vTN77xDa1Zs6ZL90P0+sc/pL/9zf213yVykqxMiieEi5VXKB1eoliS73BXlJNkKhxhjAoAAMBXUMnQrl275HQ6lZOT4zWek5OjqqqqTgcxcuRIPfnkk3r55Ze1cOFCJSUlaerUqfriiy8CXtPQ0KD6+nqvB2KDV1ntAJXkRDIUNlZikpQzUJJUWlCmj6sGaV9Dgkx5mYwxYY4OAADgiE4VUGi7Md0Y06XN6lOmTNGFF16ocePGadq0aXruuec0fPhwPfDAAwGvmTdvntLS0loe+fn5nX5/9C4Oh1TsnmwIPDPEMrmwsh3eN1SS75DT2PXBtgJpX71UuzvMkQEAABwRVDKUlZUlu93uMwtUXV3tM1vUpaBsNk2aNOmoM0PXXXed6urqWh4VFRXd9v6IXM3NHegxlJQsq09KSOOCNyu/SJI0OnuHXr3oYU3OcxdYYd8QAACIJEElQwkJCZowYYIWL17sNb548WKVlpZ2W1DGGK1du1YDBw4MeE5iYqJSU1O9Hoh+hw5JP/mJNGmS+7W/HkPsFwo/TxEFm83otKGfKyWhURL7hgAAQGQJuunqtddeq4suukgTJ05USUmJHnnkEZWXl+uKK66Q5J6x2bZtm55++umWa9auXSvJXSRh586dWrt2rRISEjR69GhJ0i233KIpU6Zo2LBhqq+v1/3336+1a9fqwQcf7IaPiGjSt6/kWT3pLqtd43sSS+TCzkrrL6WmS/W1+u/WAt234iQ9/b2/SeVlsoc7OAAAgMOCToZmzZqlmpoa3XrrraqsrNTYsWP16quvqrCwUJK7yWrbnkPjx49v+Xr16tV65plnVFhYKIfDIUmqra3V5ZdfrqqqKqWlpWn8+PFaunSpJnu6agKHlZdLe/ZI48ZJqquVnM0+57BfKDJYBcUy69eooTlOz28Yr19Pe1vjbJUyBw/ISu4T7vAAAABkmSgp71RfX6+0tDTV1dWxZC6K3XKL9NBDUmWl5Nr8uZx/edjnHPt3fyjbsSeEITq05vzve3K99qIONsUpa97/6u4zX9IVk5fLfsFc2YaNCnd4AAAginU0N+hUNTkgXFqX1Q5USY5lcpHBVjBEkrv56viB27S84nC/IYooAACACEEyhF6lrKz9HkMUUIgQA3KlxCRJ7n5DK8qLJEmmgmQIAABEhqD3DAHh5HBIJSXur/1VklOfFFlJySGNCf5ZNpusvAKZrz7XD479SMflbpfLZcm2rVzG2SzLzn9+AABAeDEzhF7D5ZISEqShQ92vTY3vzBDFEyKLle9eKjd+0DZdOG61bDYjNTfLVG4Lc2QAAADMDKEXsdmkzz93f21cTmnPbt+TWCIXUayCopav/71plA40Jei8sR/LlG+W8grDFxgAAICYGUJvVbtHcjl9hpkZiizW4ALJcv9n5oVPx+mu92dIovkqAACIDCRD6DX+8hcpL09qagqwX0gkQ5HGSkiUNXCwJGlqQZk+qRqkfQ0JMuUORUlVfwAA0IuRDKHX+Oor976h+Hj/+4UkKslFIivfXVK7JN8hp7Hrv9sKpQP7pAAJLQAAQKiQDKHXaN1jKOAv0swMRRzPvqGRWdXqn3RAyz0ltuk3BAAAwoxkCL2GV8NVf8lQSj9Zh/vaIHJ4ZoZsNqNrSt/VqOwdkiQXyRAAAAgzqsmh13A4pNJS99d+y2pnMisUiax+qVL/TGlPja476e2WcZqvAgCAcCMZQq/x+utSSopknE53Nbm2WCIXsaz8Ipk9NWpy2rTUMVQjs3dosHbK7N8nK6VvuMMDAAAximVy6DVGjpTy8yXV7paMy+c4xRMil63AvVSu2WXTt/42Vy99dqwkSmwDAIDwIhlCr7B2rXT55dKePUepJJdBMhSpPPuGkuObNX7gNi2vcL9mqRwAAAgnkiH0CmvWSP/v/0nJyUfpMcSeociVPUBKSpbk7je0gopyAAAgApAMoVdwOKSBA6WkJEkBZobYMxS5LMsmK79IklRSUKaK+v6qqEuX2b5VpqkpvMEBAICYRTKEXqHdstr90mTFJ4QyJATJOrxvqDTfocmDt6jmQB/J5ZTZXhHmyAAAQKyimhx6BYdDKnb/Lu03GWKJXOTz7Bsa0Hef3rvs/pZxU1EmFQ4JV1gAACCGkQyhV7jwQiknRzLNzVKdv7LaFE+IdNagfMlml1xOuVyWvtqTqWGZu9g3BAAAwoZlcugVLrtM+ta3JO2pkYzxOW6xXyjiWfHxsgblSZKeXjtJx/75N9rbkChT4ZDxUyodAACgp5EMIeLt2SO99JK0d69kdgcoq80yuV7Bs1TuxHyHXMamVVsLpUMHpZ3VYY4MAADEIpIhRLw1a6RzzpGqqiRTE6CsNsvkegVPEYURmTuVkbxfyz0ltuk3BAAAwoBkCBHP4ZAsSyookOS3x5AlZWSGOCp0hqe8ts1mNCXfoRWHm6+6KhzhCwoAAMQskiFEPIdDGjRISkwMsEwuLV1WXHzI40LwrJS+UqZ7Fm9qQZmq9vWTMTRfBQAA4UEyhIjn1WPIzzI5iif0Lp59Q9eWvqs1P71LliVpT43M3vrwBgYAAGIOyRAiXv/+0uTJkmlqlOprfY6TDPUutsP7huw2d1XAZqf7P0PsGwIAAKFGnyFEvPvucz+bHTX+T8ikeEJv4imiIEk/fP5CWZb013P/KlPukEaPC19gAAAg5jAzhIjmckmNje6vA5bVZmaod8nIkvr0lSTlp9Vqebk7OWJmCAAAhBrJECKawyElJUlLlx6lrDY9hnoVy7JkFRRJkkryHdpan67y2nSZym0yjQ3hDQ4AAMQUkiFENIdDMkYaPDjAzJBlSf0pq93beEpsl+Q7JEnLK4ol45LZVhG+oAAAQMwhGUJEKytz5zv5+fLfYyitvyw7W996G6tgiCRpQN99OiZjp1ZVFEqixDYAAAgtfotERPP0GEpIkJr8ldWmeEKvZA0cLMXFSc3Nen32QxrUz11Wm31DAAAglJgZQkTz9BgyjQ3SPt8+NBRP6J0se5yswQWSpIL0WsXZXZIkU+GQcbnCGRoAAIghJEOIaA89JC1aJP9L5CTKavdinuaruw8k65THf6p3Nh8jNTZI1VVhjgwAAMQKkiFEtJSUw8UTAlWSY2ao1/IUUeiffFCf7czV0i1DJUmu8s1hjAoAAMQSkiFErIYG6cwzpfffP0qPIWaGei1PMmRZ0pR8h1aUu1+bCkfYYgIAALGFZAgRq6JCeuMN6dAhyfhbJmezSen9Qx8YuoWV3EfKzpUklRaUadXWQjU7bSRDAAAgZEiGELEcDvdzUZGkGj8zQ+kZsmz2EEaE7mYrcO8bKs13aH9Toj7ZMUiq2yNTtyfMkQEAgFhAMoSI5XAc6THkb2aIJXK9n2ep3IRBFXrpgv+n4ZnVklgqBwAAQoNkCBHL4XAXT4g3h6T9+3yOUzyh97MOzwwlxTfrrOEb1TexURLNVwEAQGiQDCFiffOb0h13yP8SOUkiGer90jOkvqmSpOXlRfrJy+fKGMlF81UAABACJEOIWCeeKP3whwGKJ4hlctHAsqyW2aGaAyl67KMSldf1l3ZUyjQcCnN0AAAg2pEMIWI9+qi0cSM9hqKdZ99QSb5DknuGSMbIbN0StpgAAEBsIBlCRGpokC67TFq+PECPIbtdSqOsdjTwzAxlpezX8Mxqrahwv2bfEAAA6GkkQ4hI5eXu56IiSf6WyfXPlGXjxzcaWLmDpPgESe5+Q8tbmq+SDAEAgJ7Fb5OISJ4eQ8XFkvFTQIElctHDstll5RVIki4+/gP9fMoySZLZWi7jdIYzNAAAEOVIhhCRHA7JZpMGZx6QDh7wOW5lUDwhmlj57qVxUwvLNHv8B+7BpkaZHdvDGBUAAIh2JEOISP37S9/9rhRXH6CsdiYzQ9HEs29Ikv69aZRe+3ykJPYNAQCAnkUyhIh07rnS88/L/34hsUwu2lh5hZJlSZIe/2iK7l1xsiT2DQEAgJ5FMoSItH271NTkf7+QRI+haGMlJkk5AyW5iyj8d2uBmpw2mXKHjDFhjg4AAEQrkiFEpEmTpD/8IUDD1bg4KTUt9EGhR9kO7xsqzXdof1OiPqkaJO2rl2p3hzkyAAAQrUiGEHEaGtwzQ8XF8r9MLiNLlsWPbrTx7Bs6YVCFEu1NWk6/IQAA0MP4jRIRx9NjqLDQBCirzRK5aGTlF0mSEuOcuvLE95SftkeSZCoc4QsKAABEtbhwBwC0VXZ4IqAo54DUcMjnOMUTopOV1l9K6y/V7dEdM19pGXeVl8kexrgAAED0YmYIEWfbtsM9hpKr/R63KKsdtTyzQ43Ndi11DNGu/SnSzioZP72mAAAAuopkCBHn0kul+nopvt5/WW2xTC5qefYN1Tck6bQnr9QbX46QxFI5AADQM0iGEJFSUgJUkhMzQ9HMU1EuK2W/RmTt0ApPEQWSIQAA0ANIhhBxLrhAuvtuyez202MoPkHqmxr6oBAaA3KlxCRJ7hLby8uLJFFRDgAA9AySIUScd96R9u6VTE2gstpW6INCSFg2m6y8Qknu5qsbqnNVezBJZnu5jLM5zNEBAIBoQzKEiHLwoFRV5S6r7a/HEEvkop/lab5aUKbjB25T1b5UqblZpnJbmCMDAADRhmQIEcXTY6go94DU2OBznB5D0c9TRGFY5i6t+vG9GpntripoyjeHMywAABCFSIYQURwO93Nhvxq/x+kxFP2swfmS5f5PkzFSRV26+2uKKAAAgG5GMoSIcvzx0rPPSnmJlf5PYJlc1LMSEmUNHCxJ+vOqaRr7wG/U5LTJlDtkjAlzdAAAIJqQDCGi5ORIs2ZJ9roAZbVZJhcTPPuGJg0u18HmBH1cNVg6sM/vPjIAAIDOIhlCRPnrX6V//jNAj6GERCmlb8hjQuh59g2NH7hVSXFNrUpss28IAAB0H5IhRJQHH5ReekkyNX56DGVmU1Y7RlgFRZKkxDinJg4q1/LDzVdd5Y7wBQUAAKIOyRAiisMhFRa6/JfVpnhCzLD6pkr9MyVJJQUObantL0kyFTRfBQAA3YdkCBHD02OoKPeg1Nzkc5xkKLZ4lsrddPIbWn7Zfe7Bmp0y+/eFMSoAABBNSIYQMTw9hgrT9/g9bmVSPCGW2PKLJEkJcU5ZluRyuZdIUmIbAAB0F5IhRAy7XbroIml4/yr/JzAzFFM8M0OS9L2Fl+rqV78jSTLlLJUDAADdg2QIEeOYY6Snn5ZyLf89hpgZijFZA6SkZElSdso+vVc+RBL7hgAAQPchGULE2LxZqqiQzG4/leSSkmX1SQl9UAgby7K1zA6V5jv0aXWOag8myWzfKtPku6cMAAAgWCRDiBi/+500e7b/HkPMCsUm6/C+oZKCMhnZtHJrkeRyymyvCGtcAAAgOpAMIWI4HFJRkZF21/geZL9QTPLMDB2TsUsDUvYeab7KUjkAANANOpUMzZ8/X8XFxUpKStKECRO0bNmygOdWVlbqggsu0IgRI2Sz2XTNNdf4Pe+FF17Q6NGjlZiYqNGjR+vFF1/sTGjoxRwOqWjgQcnZ7HOMstqxyRqUL9ntsizpnR/9WTdMXyyJIgoAAKB7BJ0MLVq0SNdcc42uv/56rVmzRtOmTdNZZ52lck9d5DYaGhqUnZ2t66+/XuPGjfN7zooVKzRr1ixddNFF+vjjj3XRRRfp/PPP16pVq4IND73UwYPSjh1SYUad3+Msk4tNVly8rIF5kqRhmbuUEOeU5C6vbYwrnKEBAIAoEHQydM8992jOnDmaO3euRo0apXvvvVf5+flasGCB3/OLiop03333afbs2UpLS/N7zr333qvTTz9d1113nUaOHKnrrrtOp556qu69995gw0MvVVUlZWRIhf38LJGTWCYXwzxL5bbXp+qMp67QR9vzpEMHpZ3VYY4MAAD0dkElQ42NjVq9erVmzpzpNT5z5kwtX76800GsWLHC555nnHFGl+6J3qW4WKqpkaYVfuX3ODNDscvKdydDWX32a0VFkZZtocQ2AADoHkElQ7t27ZLT6VROTo7XeE5OjqqqAjTK7ICqqqqg79nQ0KD6+nqvB6LAHt9KcuqTIutwvxnEHk9FuYQ4pyYOKtf75e7kyMW+IQAA0EWdKqBgWZbXa2OMz1hP33PevHlKS0treeTn53fp/RFeN90knXmmZGp8ewxRPCG2WSl9pcMzgyUFDq0oL5Ix7n1DAAAAXRFUMpSVlSW73e4zY1NdXe0zsxOM3NzcoO953XXXqa6uruVRUUHfkd5s40apqclIe3b7HmSJXMw70ny1TDv2p2rznkxpT43MXmaEAQBA5wWVDCUkJGjChAlavHix1/jixYtVWlra6SBKSkp87vnmm28e9Z6JiYlKTU31eqD3KiuTCgc2SC6nzzFmhmA7vG/oa4Vl+vv3H1dOyl5J7BsCAABdExfsBddee60uuugiTZw4USUlJXrkkUdUXl6uK664QpJ7xmbbtm16+umnW65Zu3atJGnfvn3auXOn1q5dq4SEBI0ePVqSdPXVV+ukk07SnXfeqW9/+9t66aWX9NZbb+m9997rho+I3sDhkL5RutfvMZIheGaG0pIO6VsjN7SMm3KHNNp/yX4AAID2BJ0MzZo1SzU1Nbr11ltVWVmpsWPH6tVXX1VhYaEkd5PVtj2Hxo8f3/L16tWr9cwzz6iwsFAOh0OSVFpaqmeffVY33HCDbrzxRg0dOlSLFi3SiSee2IWPht5i/35p506pMN3PEjlRSQ5yl1bv01c6sE9LHUP06uejdcfMV5gZAgAAXWIZY0y4g+gO9fX1SktLU11dHUvmepmmJmn1aqmw7FVlff62z/G43/6vrMSkMESGSNK86AmZjev1l7UTNOefF2jHb25Q/z4NivvtbbISEsMdHgAAiCAdzQ06VU0O6E7x8dKUKVK2a5vvwZR+JEKQdKTfUGmBQ5K0sqJQMi6ZbeVHuQoAACAwkiGE3ZtvStdfH6Csdib7heDm2Tc0pH+NclLqW/oNmXJHGKMCAAC9GckQwu6tt6RFi4xUu8f3IMUTcJg1cLAUFyfLOtxvqOJwMlSxOcyRAQCA3iroAgpAd3M4pKLBTZJx+RyzMiieADfLHidrcIHMls2ac8JK7djnXv9rKrbIuFyybPzbDgAACA7JEMLO4ZCOLdzv9xjL5NCalV8ss2Wzzhi26chgY4NUXSXlDgpfYAAAoFfin1IRdg6HVJhR5/cYZbXRmmffkCT9e9MoLXUMkSS5ylkqBwAAgkcyhLByuaQf/1iaPtTh/wT2DKEVK6+w5es/LT9Zf141TZJkKhxhiggAAPRmJEMIK5tN+sMfpKkDN/ke7JcmKz4h9EEhYlnJfaQBuZLcRRSWlxfLGMmU03wVAAAEj2QIYVVRIb37rtS8q8bnGPuF4I/N028ov0zV+/vpq92ZUn2tTJ2faoQAAABHQTKEsHr5ZWnmTCP5+0WWSnLww7NvaEr+FknSck+JbWaHAABAkEiGEFYOh1Qw2Cm75a+sNjND8GXlF0mS+icf1JwTVigz2V2JkH1DAAAgWJTWRlg5HFLRwEN+j7FMDn6lZ0j9UqW99Vrwrb+3DLsqymQPY1gAAKD3YWYIYeVwSEVZ9X6P0XAV/liWJevwvqHGZrtWlBdpb0OitKNSpsF/Yg0AAOAPyRDCKi1NGjVgp58jlpSRGfJ40Dt4lspV1Kdr+uNXufsNGSOzdUt4AwMAAL0KyRDC6q23pKtPWu57IC1dVlx86ANCr2A7XERhSP8a5fatp4gCAADoFJIhhI3LJXePmJpdPsconoCjyh0kxSfIsqSS/DKtKC+SJJkKkiEAANBxJEMIm1dflfr1M6re3uxzjGQIR2PZ7LLyCiVJpQUOfbi9QI3Ndpmt5TJOZ5ijAwAAvQXJEMLG4ZCamqSsPvt9D2ZSPAFH59k39LWCzRqWuVPb96ZKTY0yO7aHNzAAANBrUFobYeNwSIUDG2WzGZ9jzAyhPZ7mqxMGb9Xqn9zdMm7Ky6RB+eEKCwAA9CLMDCFsysqkwgF+ZoVEjyG0z8orlCxLknvv2c79Ke6v2TcEAAA6iGQIYeNwSIX99/gesCypP2W1cXRWYpKUM0iSdMeyU3X8g79yF+Qod8gY39lGAACAtkiGEDb//rd045nLfA+k9ZdlZwUn2mc7vG9o/MBt2nmgn77cnSXtq5dqd4c3MAAA0CuQDCFscnOlQS7fJpkskUNHefYNTclzyJJLK8rpNwQAADqOZAhh8eWX0qzznCrf6vsjaGVQSQ4d40mG0pMPacyAKi2vKJJEMgQAADqGZAhhsXGj9Nzf7Yq3++kJQ1ltdJCVmi6l9Zfk7je0adcASZKrwhG+oAAAQK/BxgyERVmZlJjgUk7KPp9jlNVGMKyCIpl1e/R/M19WcnyTe3BnlczBA7KS+4Q3OAAAENGYGUJYOBxSYc5B/z2GmBlCEKx891K5PglNsix3mW1JMswOAQCAdpAMISwcDqkws973gM0mpfcPeTzovWyH9w1J0rf+Olc3/edMSSRDAACgfSyTQ1hcdJHkfOsj3wPpGbJs9tAHhN4rO1dKTJIaDqlPQqOWbRkqiSIKAACgfcwMISzOOUf6VtF/fcZZIodgWTabrLxCSVJpfpk+3Javhma7zPZymebmMEcHAAAiGckQQu7AAenJRxu1Y4fvMYonoDM8JbanFpSpwRmvNZV5UnOzTOXWMEcGAAAiGckQQu7LL6VLL0tQ2Z5M34MkQ+gETxGF43K3q098g973NF+tYKkcAAAIjD1DCDmHw/1cmL7b5xjL5NAZ1uB8yWZTvFxaNvd+DcvYJenwvqHSGWGODgAARCpmhhByDoeUGO+kxxC6jZWQKCt3sCTp2JwqJcW79wqZii0yxrd8OwAAgEQyhDBwOKTC7P2+PYbsdimNstroHM++obI9GfrmX+fqy5pM6cA+afeuMEcGAAAiFckQQm7AAOmUEQ7fA/0zZdn4kUTnePYNZSQf0JtfjtD75UMkSaZ8czjDAgAAEYzfPBFyv/2tdP+Zz/uMs0QOXWEVFEmS0pIOacyAqpYiCq5yR/iCAgAAEY1kCCG3a+sBmQMHfMatDIonoPOsvqlSf3eFwtICh5ZTUQ4AALSDZAghVVsrZef30fMbjvc9mMnMELrGs2+oJL9Mn9cM0K79KVLNTpn9vsU6AAAASIYQUlu2uJ8L0/yU1WaZHLrIdnjf0GlDP9fC855Sn/hGScwOAQAA/0iGEFKeHkNF/ekxhO7n2TeU03efvjfmE/VJaJIkGfYNAQAAP0iGEFIOh5SU0KwBbXsMxcVJqWlhiQlRJGuAlNxHkvTO5mM0b+mpkpgZAgAA/pEMIaS2bJGKMuplWW0O9M+SZfHjiK6xLJus/CJJ0obqXN2+5HQ1NNtltm+VaWoKb3AAACDi8NsnQuqPfzR6Z+58n3GWyKG7ePoNlRY41OCM10fb8yWXU2Z7RZgjAwAAkYZkCCFlO7RfmXF7fMYpnoDu4tk3dFzOdqXEN7T0GzLlLJUDAADeSIYQUqefYdfLG8f4jFuU1UY3sQblS3a74uwuTc4r1/KKIknsGwIAAL5IhhAytbXS2+8n61BzvO9BGq6im1hx8e6ESNLlE5frnFHrJEmmwiFjXOEMDQAARJi4cAeA2OHpMVSU7q+sNjND6D5WfpFMhUPfG/PJkcFDB6Wd1dKA3PAFBgAAIgozQwiZssOrlArbJkPxCVLf1NAHhKhlFRS3fP3a5yP14Tb3TBFL5QAAQGskQwgZh0NKivfTYygjS5ZPrW2g8zzltSXpxre/rkc+LJEkuSiiAAAAWmGZHEJm5kyjrJV/9+kxxBI5dDerT193A9Zd1SotcOg/m4dJcu8bAgAA8GBmCCEzqmCvZo36wGfcongCeoBndqgkv0yf1wzQzv0p0p4amb314Q0MAABEDJIhhMxD9zfov1sLfMbpMYSeYCs40nxVklZQYhsAALRBMoSQMEb67bz+WuoY6nuQZXLoAVa+OxkqSNuj74z6WIn2Zkk0XwUAAEewZwghUVsr1e+L860kJ5bJoYdkZEl9+so6sE+LZj3dMsy+IQAA4MHMEELC4XA/+/QYSkiUUvqGPB5EP8uyWkpsNzlt+nBbvhqa7TKV22QaG8IcHQAAiAQkQwgJTzJUmL7H+0BmNmW10WM8RRTW7xio0v93jT7cViAZl8y28vAGBgAAIgLJEEIiLc3oO2PWKbtNjyGKJ6AneWaGjs2pVEp8g5Z7iiiUO8IXFAAAiBgkQwiJGRPrtei8J317DJEMoQdZAwdLcXGKs7t0Yt4WLS93J0emYnOYIwMAAJGAZAgh8dXaPao7lOQzbmVSPAE9x7LHyRpcKEkqKXBoZUWRjJFMxRYZlyvM0QEAgHAjGUJIfG9utm58++u+B5gZQg/z7BuaWlCmrJR92rm/r9TYIFVXhjcwAAAQdiRD6HHGSI5tCf7LatNjCD3Ms2/otKGfa93P/k8D+rr3rbnoNwQAQMwjGUKPq62V6g/E+yZDSclSckpYYkLssPIKJR3ZrOZZrmkqSIYAAIh1JEPocZ6y2sVtkiGLstoIASu5jzQgR5J049tnqeSRayRRUQ4AAJAMIQSqqlyKtzf79hhivxBCxJbvXio3ZkCVvtydrep9faX6Wpm6Pe1cCQAAohnJEHrcmSW1qr/+t8rss99rnLLaCBXPvqGpBe6lcSta+g2xVA4AgFhGMoQeZ3bvkt1mfHsMUVYbIeJJhvLTapWfuudIMlThCF9QAAAg7EiG0OPmXJOmX7/xTd8DzAwhVNL6S/1SJbn7DX1SNUgSFeUAAIh1ceEOANFv9bokTc2O9xlnZgihYlmWrIJimQ0f68Fv/F39EhrcB6orZQ4dlJWUHN4AAQBAWDAzhB5ljOTYkayitmW1+6TwCyhCyjpcRCEt6ZBsNuMeNEZm65YwRgUAAMKJZAg9as8eae9B34arFE9AqNnyi1q+PvOpH+tPy6dLYt8QAACxjGQIPWrzV05J8p0ZYokcQi13kBSfIEmyLGmJY6gkmq8CABDLSIbQo4YNqNMrFz6ikdnVXuPMDCHULJtdVl6hJKkkv0wrK4rkclkyW8tlnM4wRwcAAMKBZAg9ql9TtWYes0kpCY1e4yRDCIfW/YZ2H0zRpppsqalRZsf2MEcGAADCgWQIPeqZhZYeW32izziV5BAO1uF9Q5PzymWzXFpe7k6OaL4KAEBs6lQyNH/+fBUXFyspKUkTJkzQsmXLjnr+kiVLNGHCBCUlJWnIkCF66KGHvI4/+eST7tK3bR6HDh3qTHiIIM++kqZ/bRrje4CZIYSBlVcoWZb6JTZo6ZwH9P1j10hi3xAAALEq6GRo0aJFuuaaa3T99ddrzZo1mjZtms466yyVl5f7Pb+srExf//rXNW3aNK1Zs0a/+93v9POf/1wvvPCC13mpqamqrKz0eiQlJXXuUyFiOLYnqCh9j/dgSj9ZifzZIvSsxCQpx91wdXJeecvyTVNeJmNMOEMDAABhEHQydM8992jOnDmaO3euRo0apXvvvVf5+flasGCB3/MfeughFRQU6N5779WoUaM0d+5c/ehHP9Jdd93ldZ5lWcrNzfV6oHczRnJU9/Utq53JrBDCx1Nie+POATrnmR9px76+0r69Uu3uo18IAACiTlDJUGNjo1avXq2ZM2d6jc+cOVPLly/3e82KFSt8zj/jjDP04YcfqqmpqWVs3759KiwsVF5enr7xjW9ozZo1R42loaFB9fX1Xg9Ell3VTu1v9O0xxBI5hJOniEJKQqNe/XwM+4YAAIhhQSVDu3btktPpVE5Ojtd4Tk6Oqqqq/F5TVVXl9/zm5mbt2rVLkjRy5Eg9+eSTevnll7Vw4UIlJSVp6tSp+uKLLwLGMm/ePKWlpbU88vPzg/koCAHXnj366eT3dGxOpde4lUHxBISPJxnKT6tVfuoeragokkQyBABALOpUAQXLsrxeG2N8xto7v/X4lClTdOGFF2rcuHGaNm2annvuOQ0fPlwPPPBAwHted911qqura3lUVFR05qOgB2Xbd+rer7+oYZm7vMZZJodwslLTpbT+kqSSAkfLzJCrwhG+oAAAQFgElQxlZWXJbrf7zAJVV1f7zP545Obm+j0/Li5OmZmZ/oOy2TRp0qSjzgwlJiYqNTXV64HI8sXavVq3w3fvFzNDCDeroEiSVJpfpjWVg3WwKU7aWSVz8EB4AwMAACEVVDKUkJCgCRMmaPHixV7jixcvVmlpqd9rSkpKfM5/8803NXHiRMXHx/u9xhijtWvXauDAgcGEhwhz/1OZuviFH/oeyPCfBAOhYuUPkSSdPeJTPXrOsy3jhtkhAABiSlywF1x77bW66KKLNHHiRJWUlOiRRx5ReXm5rrjiCknu5Wvbtm3T008/LUm64oor9Oc//1nXXnutLrvsMq1YsUKPPfaYFi5c2HLPW265RVOmTNGwYcNUX1+v+++/X2vXrtWDDz7YTR8T4eDYGqfCtmW1+6XJSkgMT0DAYbaCIrkkFabv8foZNeVl0vDR4QsMAACEVNDJ0KxZs1RTU6Nbb71VlZWVGjt2rF599VUVFhZKkiorK716DhUXF+vVV1/VL37xCz344IMaNGiQ7r//fn3ve99rOae2tlaXX365qqqqlJaWpvHjx2vp0qWaPHlyN3xEhItjR7JmFHj3n2K/ECJCdq6UmCQ1HNLbXw3Txl05uvLE95gZAgAgxlgmSjoN1tfXKy0tTXV1dewfigCupmal9nXqppNf1zWlS1vGrROmKO6b54UxMsCt+W//T+bLjbrt3dP1wMqTVPnr38uWYFfcb/5XVlzQ/04EAAAiSEdzg05VkwPas7dit3JS9mpoRo3XuEWPIUQI63Dz1dICh/Yc6qONuwZIzc0ylVvDGxgAAAgZ/vkTPaJfU7U2Xv2EzzjL5BApPP2GJg/eIrvl1PLyYo0esEOmokw6nCgBAIDoxswQeoRr1y6/45TVRqSwBhdINpv6JjbquNztWk7zVQAAYg7JEHrEPY9laOwDv2kzalFWGxHDik+QNTBPkvTTye/r5OIvJbnLa0fJVkoAANAOlsmhR5SV25Rgb/YeTEuXFee/txQQDlZ+kcy2cl08/oMjgwf2SzU7pawB4QsMAACEBDND6BFbtif69BiieAIijWffkDHSG1+M0IbqHPfrCpbKAQAQC0iG0O1MU5Mcu/qpuD+V5BDZrHx3MmRZ0s9eOVdPrXH3NnOxbwgAgJhAMoRuZ3bv0pba/j4zQ8qkeAIii9W3n9TfvY+tpMCh98sPzxTRfBUAgJjAniF0O1OzSysvf1r9kw94jTMzhEhkFRTL7KlRaX6Z/r5hnA40xqtPzU6Z/ftkpfQNd3gAAKAHMTOE7rdnp0ZmVyun7z6vYXoMIRLZDi+VKykoU7PLrg+350ti3xAAALGAZAjdbskSSz95+Vw1NtuPDFpWy3IkIJJ4iiiMHVCl04ZsktPl/s+iKXeEMSoAABAKJEPodv9dm6jnNxyveLvzyGBaf1l2VmUiAmVlS8l9ZLcZvTr7Ec0Y4uk3xMwQAADRjmQI3c6xLV5F6btlWUfGWCKHSGVZNln5RZIkp8vS2spBcrksme1bZZqawhscAADoUSRD6FamsUGO6r5+egxRSQ6Ry1Nie6ljqCY//Et9ujNHcjlltpeHOTIAANCTSIbQvXbXyFGboaL03d7jVJJDBPPsG5qcVy675dSKiiJJ7BsCACDakQyhW5manbpi0nJ9c+R6r3GLHkOIYNagPMluV0pCo8blbtfyln5D7BsCACCasaMd3crs3qkrT3zPZ5xkCJHMiouXNShfpsKh0oIyvfr5aEnu5qvGuGRZ/LsRAADRiP/Do1tt/3KfXt44RgebWuXZNpuU3j98QQEd4Nk3VJLvkCVpX0OCdOigtLM6vIEBAIAeQzKEbvXefxN17rM/UkNzq2QoPUOWzR74IiACWAVFkqRzx3ysz66ep76JjZIkVzlL5QAAiFYkQ+hWZeVxSk86oPTkQy1jLJFDb+Apr+0pCX+gMV4S+4YAAIhmJEPoNqbhkLZUp/gpq00lOUQ+q09fKWuAJOl/Xv+WTnvyp5Ikw8wQAABRi2QI3admp7bU9lchZbXRS3n2DQ3P3Km1VYPds0O1u2X21oc5MgAA0BNIhtBtzO5dyum7VxMGVXiNs0wOvYXt8L6hkoIyNbvs+mBbgSSWygEAEK0orY1uY2p26dFzXvcZZ5kcegvPzNCY7B1KSzyo5RVFml78lXup3OhxYY4OAAB0N2aG0G2adu5SQ3ObqnF2u5RGWW30EhlZUkpf2WxGU/Id+mh7niR3vyEAABB9SIbQbT78yK7U2+7Q+h25Rwb7Z8qy8WOG3sGyrJbZoSe+s1DPnv+0JMlUbpNpbAhnaAAAoAfwWyq6jcMhGdmUl1rbMsYSOfQ2VoE7GcpK2S+7zbgHjUtmW3kYowIAAD2BZAjdwhw8oC3VKb49hjIonoDexdNvyOWydOoTP9WTH02WRIltAACiEckQuoXZvetwWW3vHkPKZGYIvYs1cLAUFy+bzehAU7zedQyVREU5AACiEckQukfNTm2pzVBReo3XMMvk0NtY9jhZg90ltacWlGlFuXvZnKnYIuNyhTM0AADQzUiG0C3M7l1aNOspPfiNF7zG6TGE3sizb6gk36Gy2kxtr0+VGhuk6sowRwYAALoTyRC6hdm9UykJjRrQd9+Rwbg4KTUtfEEBneTZN1Ra4F4at7zC/drFviEAAKIKyRC6xY6yAzr7L5fr46qBRwb7Z8my+BFD7+NOhiwN7LdXb148X2ccs0kS+4YAAIg2/KaKLjPGaPNXRou/GiGr1bhF8QT0UlZSsjTA3S/r5OKv1C/R3WPIlDvCGBUAAOhuJEPouoP75ahOkSQVpe9uGaZ4Anoz2+Glcp9UDdT5iy7WvoYEqb5Wpm7P0S8EAAC9BskQuszU7NSW2v7KSN6v1KSGlnGKJ6A38xRRsCyjf352nD7Y5q4wR78hAACiB8kQuq5mlxx7MlTYalZIkkTDVfRinmRoTPYOpSUebCmiQDIEAED0iAt3AOj9zO5duuC4zTpz2EavcfYMoVdL6y/1S5Ntb51K8h0t/YZcFQ7ZwxwaAADoHswModNcLmnBAmnZ+5amFW3Wt0etP3IwPkHqmxq+4IAusixLVkGRJKmkoEwrtxbK6bKk6kqZQwfDGxwAAOgWJEPolLIy6bTTpJ/+VFryYT/fEzKyZFmW7zjQi1j57tmg74xapz+d9aKcLptkjMzWLWGODAAAdAeSIQTF5ZIefFA69lhp82Zp8WKj3035t895LJFDNLAd3jc0MrtaFx2/WglxTkmSqXCEMSoAANBdSIYQlH37pDvukC6+WFq3Tjp1yl6pscHnPIviCYgGOQPdSz4lLf5yuJ5aM0kSRRQAAIgWJENol8sl/fnP0tatUmqqtH69e3aoXz/J1Ozyew09hhANLJtdVn6hJOnNL0fqtndnSpLMtnIZpzOcoQEAgG5AMoSj+uIL6eSTpauukl591T2WltbqhN07/V/IMjlECc++oZKCMm2py9C2+lSpqVGmaluYIwMAAF1FMgS/nE7p3nulceOkbdukd9+VLr/c97zAM0Msk0N08PQbKs13SJKWHy6xzb4hAAB6P5Ih+FVWJv3ud9Jll0mffCJNn+593DQ2yLnsLbk+XO57cUKilNI3NIECPcwaXCBZlnL77dWQ/ru0wtN8tYJ9QwAA9HY0XUULp1N67DFp9mzpmGOkr76SBg70Psc0Ncn14XK53ntbOrDf/40ysymrjahhJSZJuYOlyq268sT3lJHs/rk35WUyxvCzDgBAL0YyBEnSxo3SpZdKq1ZJgwZJ3/iGdyJkmpvl+milXMvelvbVH/VetkH5PRwtEFq2/CK5KrfqqinLjgzu2yvV7pb6Z4YvMAAA0CUsk4txzc3S//2fdPzxUk2NtGyZOxHyME6nXB+tUvOf75DrtRfbTYSUmCTb5K/1aMxAqFn5RZIkp8vSfzYP0+bdGZIosQ0AQG9HMhTjliyRfvtb6Wc/kz7+WJo61T1uXC65Plmt5gfvlPNfz0l1e9q9l3XMSMXN+bmsAbk9HDUQWp4iCpak7z83WwvXnSCJZAgAgN6OZXIxqLlZevFF6dxzpVNPdS+RGz7cfcwYl8xn6+R85w1p144O3c8qHCrbKWfKVjCkB6MGwsdKTZfS+stWt0cl+Q4tL3f/rLsqymQPb2gAAKALSIZizPr17r1BH30krV7tXh43fLhkjJH5/FM5331dqtreoXtZeYWyzThTVvEwNpEj6lkFxTLr3MnQH987RU6XJfvOHTIHD8hK7hPu8AAAQCeQDMUIz96gW26RhgyRli93J0LGGJnNn8v1zusy28o7drPcwbKfcpasY0aSBCFmWPnFMus+UmlBmfY2Jml9da7G5VbKVDhkDR8d7vAAAEAnkAzFiEcflW68UfrVr6Sbb5aSkiTXlq/cSdCWzR27SXau7DPOlDVyLEkQYo6toFguSRMHVWhKnkP7GpIkHd43RDIEAECvRDIUxZqa3DNA06dLc+ZIJ54ojR8vubZuUfM7r8ts/rxjN8rIkv3kM2SNOV6WjZobiFEDcqTEJPXRIS2d+0DLsKlwhC8mAADQJSRDUeqTT6RLLpE++0xyOKScHOn4gdvUvPB1mc8/7dhN0jNkn366rOMmyLKxTRyxzbJssvKLZL7cKJfL0uc12RqZXS2zrVymuVlWHP85BQCgt+Gf+aNMY6N7X9CECe6ZoffekwbYqtT8/FNqfviejiVC/VJlO/t7ivvZb2Q7fjKJEHCYle8usf3ypjE67sHfaGtdmuRslqncGubIAABAZ/BPmVHmxhulu++Wfvc76Xc/2aW4lW+q+ZWPJJn2L07pK9vXTpVtQoms+PgejxXobayCIklSSb5DkrS8oljnp6117xs63JgVAAD0HiRDUaCxUdq0STr2WOmXv5TO/3qdxtW9LvP/PpQxrvZvkJQs29RTZJs8VVZCYs8HDPRS1uACyWZTTt99Gtp/l1aUF+n8sWtlKsokzQh3eAAAIEgkQ73cRx+5+wbt2iV99XGdMj98W/1Xr5RxOdu/ODFJtiknyTblJFlJyT0fLNDLWfEJsgbmyWwrV0lBmd4vdy+bMxUOGWOosggAQC9DMtRLNTRIt90mzZsnjR3t1MvXL5P94dfkam5u/+L4BNkmf0220pNl9Unp+WCBKGLlF8tsK1dpvkPLy4vV5LQp/sB+qWanlDUg3OEBAIAgkAz1UhdfLP3jH0Y3XPiFfj30KcXvPNT+RfY42SaVyjb1FFl9+/V8kEAUsgqKpJVL9KMTVmnuxJUt46aiTP+/vTuPj+lc+AD+O7NkMrLJvmcSCUGaWhIisYRSQUtK39blpaXo6637Xq3b69bFW3VvP25vvaXaamnRfUdpUUuvpSS1RCghCZFIyEJsCZFlZp73j5GRk5kgRJIxv+/nk0+b85zlOed5ZM5vzjnPkRiGiIiIbArDkA2pqgLOnwcCvSsx89F0/MV3Px72OA3c7rEghRKK7nFQ9B0EydWtWepK9KCqHVFOoTANSlKtV8JBZYAxPxeKbnEtWTUiIiJqJIYhG7FvHzBxghGuynLsHLcQ0ZUVgMdtFpIUkLrEmt4V1PZ2MxPRnZCcXQAPL+BiKab9+CTyLntiw/jlfPkqERGRDeJ7hlq5ykpg5l8MiI8XcCwvxtK+yyFVVtxmKQlSdDeops2EKnk0gxBRE5NuDKOta3sJvxXoYDBKwIXzENfKW7ZiRERE1Ci8MtSKGfV6PBJXgbSMNpg/YCNmJOyASnnre+KkTg9D2T8Jko9fM9WSyP4oQsJgOHwACSG5KK92xJESf3T1L4QoyIPUMbqlq0dERER3iGGoFaq4ZkB1+iE4pf2MVx7yga7PJXT2KbnlMlL7TlAOGALJP6iZaklkv2qfG4oJKIBaoUdqQZgpDOXnAgxDRERENoO3ybUiQhix+/NsdG13GS/+jwG4fBFDO2TeMghJYe2hfO5/oBo7mUGIqLl4+QDaNtCq9egecAb7zoQAAJ8bIiIisjG8MtQKCCFw7VAG5v6lEm//0h09Agswo/f2Wy4jhYRBMWAIFKERzVRLIqolSRKk4FCI7GP45ulP4O10FQAgCs9A1NRAUqtbuIZERER0JxiGWpAQAiInCxVbtiL21adx+rIHFjy6AdPjd0J5Y9je+qSAYCgGDIEUHsm33RO1ICkkDCL7GAJcy25ONBogCvMh6cJbrmJERER0xxiGWogx9ySu/rwVDsU50CgE/tRrF/qF5iDS67z1BXz9Tc8EdYhiCCJqBWqfG6rSK/HYZ89jWtxujOx8BCI/D2AYIiIisgkMQ83MWJAL4/afsWu7Ec+vG43ne6TgpYSdmFLnTfYyXj6m0eE6PwxJ4iNeRK2FFBAEKJXQwIDCcjfszIswhaGC3JauGhEREd0hhqFmIgoLYNixGVczcjBn2zC8t68vEoJz8ViHDOsLuHtCmTgYUnR3SAqGIKLWRlKpIQUEQxTkISEkFyn5oQBMgygIYeSXF0RERDaAYeg+EyVFMOzYDJF5BEXlLhiw8s8oKnfF/w35AS/03G35bJCrG5T9BkPq2gOSUtkylSaiOyIFh5nCUHAePj8ci/IqDVxwHThfAvj4t3T1Gk0YDYBeD+hrbvzX9P/CyjTLMgOgVAIqFSSVGlCp6vzc+F15mzLeAkxERM3srsLQ0qVL8eabb6KoqAhRUVFYvHgx+vbt2+D8O3fuxIwZM5CRkYGAgADMnDkTU6dOlc2zevVqzJ07Fzk5OQgPD8frr7+OkSNH3k31WgVx4bwpBB09hGq9Ag4qwM+5HE9GHcbEbnsR4XlBvoCzCxR9BkIR08t0skBErZ4UEgakbEd8SC6MQoG9Z3QYFJ4NY34elHcRhu4tjMjLRAPzm8osp0GvB8StX+p83ymthCSVCpJS/rs8XNUvM/0u3Si3tpxUbx3mMqWSgYyIyM40Ogx98803ePHFF7F06VL07t0by5Ytw9ChQ3Hs2DGEhIRYzJ+bm4thw4ZhypQp+Pzzz7Fnzx688MIL8Pb2xpNPPgkASE1NxejRo/H3v/8dI0eOxNq1a/H0009j9+7diIuLu/e9bEbi0gUYdm2FOHwAEALbT0Vg6vqn8c7jqzE4IguvD9ooX0DbBoo+j0DRozcktUPLVJqI7ooUHAoA6Oh1DuvGfoiegacBAMb9eyAK820vjNRRY1CgUq9GpV5l/m+I2yVoVAZklXqj4Ir7jTJTeQfP8+gZlI8LFW2Qkh8GjUoPR1UNHFV6tFFX4yHfYgBA6TUnqBQGOKr00Kj0kGUPg970UyWvi/WxNW9fdlcaCFFS/atZSitlShXA25qJiAAAiodjIHl4tXQ1bksSQjTqsyQuLg7du3fH+++/b57WqVMnPPHEE1iwYIHF/H/961+xfv16HD9+3Dxt6tSpOHz4MFJTUwEAo0ePRllZGTZt2mSeZ8iQIXB3d8dXX311R/UqKyuDm5sbrly5AldX18bsUpMQZZdh3LUNxvS9gNGI8ioN/rb1MSw70Bv9dCexLPlbhHvUuRqkcYQioT8UcX0haRybvb5E1DRq3vsXUNrwi5HvhhCAEBIUCoGKajVKK5zMoaNKr4KjugbRvsXQGxRYezwalXoVquoEl6k99sBZU42PD/ZEWmFQnVCjwpiHD2JU5yPYmRuOmVuG43qN2rxsuEcp/v3cUgCA2z8W4Lpe/gXN/qkL0cWvCC/8+B/4KC1eVvbn3v/Ggkc34Ne8dhj48TRZmb/zFZx+eT4AIGLRbORf8TCXOSj12DBuORLDcrAoJREfHog3hyhHVQ2GdTiOl/tsR2GZK2Ztfdw83VGlh1ZdjXmPbAYAfHe0C65UaqExL6tHTEABAlzLUHLVGcVXXaBRGszLOjtUwVlT3aTtRkRENynHPQ9FeGSLbf9Os0GjrgxVV1cjLS0Nr7zyimz64MGDkZKSYnWZ1NRUDB48WDYtKSkJK1asQE1NDdRqNVJTU/HSSy9ZzLN48eIG61JVVYWqqptfH5aVlTU4b3Mw7tkOY5op3B0754vkLyajtMIJS4atxvOxqVDUPhvkoIEiri8U8YmQtG1asMZE1BSk4FCI0hIcLAzC9I0j8ViHY9AbFajUqxDpdQ7ju6bhYoUW0zeOsggt2yYshYPKgHHfj8Ovee1koeX94d/juZi9+PpId0z98WnZNvvpTmLbxPdhFBL+8/tnTPWA0RwC/hB9EM6aahw774u9Z3SyAGEUpksxbbUV6BmYf+MKjakswOXm39Flyd9CKRlly4a7m77QmTfgZ7zSd5u5TKPSw0FpAAD0Cs7DmZdfRZVBZd6X2m0CwAcjvsOVSkdUGVSounEcIjxNrxSI8inGiI5HUaVXmZdv63gdAFBlUOFsmZv5GFUZTB9ftWFoUUp/pBUGQeDmlZmvn/4YozofwReHY/HK1uGyY/h45FGsGbMK5646o92iuab9UOrNV6z2/ddbcNZUY+bm4ThSEgBNnfIJ3fZhQLuTOFgYhB+OP3TjKpgeGqUega5XMLLzERiNEpYdSLDoL+O6HICLpgpbTkYi56L8G9OegacRE3gGeZfcselEZ1mZm+N1jH34IABgZVqcef9rjep8GL7OV/FrXjscPSe/RTPatxB9dLkoueqMNce6yMo0Sj2ei9kLAPjicHeUVWll5cM6HIOu7SUcOBuM/Wfld39EeJzHoxHZKKvU4IvfYy329b9iU6BQCKw9Fo3iq/ITkQFhJ9DR+xyOlvjh19PyoegDXS9jRMcM1BgUFqEbAJ7puh9ODtXYlN0ReZc9ZWW9gvPQzf8sci56YsvJjrIyD+01jI4+BAD48EAv6I3y53KfijoEL6dr2JEbjuPn/WRlXf3OIj4kD4VlrliXGS0ra6OuxrPd9gMAPj0Ui2vVGln545EZCHa7jL0FIThYFCwri/Q6h0fancCl61p8faS7rEyCwNSepnOr7zMexvlrLrLyQeFZaO9ZisPF/kjJbycrC3G7iMcij6OyRoVV6ZZ32EzstheOaj1+yuqMgivusrLeIafwsF8Rsku98Msp+Ymst1M5/iPqdwDAB/sSICC/rXRMdBraaivxS057ZF/wkZXFBBSgZ1A+Cq60xU9ZUbIyZ4dKjO+aBgD4JL0HKmrkX8QkdzyCANcypOSH4nBxoKyss3cxEsNyUHrNCd9ldJWVqRQG82i93xzpiovXnWTlSRHH0c7jItILA/HbmVBZWZj7BQxpn4lr1Q749FAP1Dc5JhVqpRHrM6NwtqytrKxf6ElE+ZTg+Hkf7MhtLyvzcy57oP9GxAbko0dQgcV+tWaNCkOlpaUwGAzw9fWVTff19UVxcbHVZYqLi63Or9frUVpaCn9//wbnaWidALBgwQK89tprjan+faXo8wiMB38D9Hro2l5Cv9AczOm/BWHuF00zqFRQ9OgDRe8BkJycW7ayRNRkFCFhMKTvhUphwIkL3ngrpT/aqGvgqKpBUkSm+QO+5KqLOXi4OV6XBZNHw7PQ0atEFjwSQkxDdA+OyMSGcctkwcPNsRIAoFYacGHW3+CoqoFKYUT9x13+lfRjg/Xu4leEdx5f02D5H6LTGyzzcb7aYJlaabxl+aDw7AbLBkdkYXBEltWyMPeL2DbxfatlAJDy/NsQAqgxKM1hydnB9IXZf3Y5gH6hOTfCqClkebW5BsB0Ivtm0nrZLX9VehU0Kj0AwENbAXdtBSr1KlytdkRphQrlN052T13ywFe/x9QJfmr0CsoznegICX/ZPMKinsM6HIOLpgpfHI7B6nonHXP7b0ZM4BlklvpaLNve87z5ROd//z0UlyvlJyQ9A0/D1/kq1mU+hA/295aV/XePPeijy0XBFXeL9bo7VphPdP61e6DFyVc791Lo2l7CtpwO+MdO+RebT0UdwqMR2bhw3cnqvj4fazqRX7qvD1ILQmVlH4z4Fh29z+G3glCLZQeEncCIjhmoNqisrndkp9/h5FCNTw71tDip/sfADejmfxZHS/wtln3Ip8gchv629XFc18ufz+2jy4GX0zWszuhiESCmx+9EfEgeci95WqzX37nMHIb+uWsQ8uuFi45eJQh2u4yfT3bCm7sfkZWN63IAj7Q7gXPXnC3Wq5SM5jC0JDURB4uCZOWrRn6J9p6l2HO6HWZukS87OCITj0UeR0WN2uox/EP0QTiq9ViR1gtbc+SB582k9XjYrwjpRUEWy8YEFJjD0MwtI2RfdACmgNZWW4lvjnbDl7/HyMpm9vkFPYPyceKCt8V6dW0vmv9Wzt+ehJJ6wa+L31kEuJbhp6woLPmtn6xsUvffkBiWg8JyV4v1tlFXm8PQWyn9kVEvBAS6XkY7j4vYkReBub8Mk5UNjzyKIe0zcaXS0eoxfLbrPqiVRizfn4AdeRGysiXD1iDKpwT7z4ZYLJsQnPtA/434W7+tNheGGnWbXGFhIQIDA5GSkoL4+Jvf1rz++uv47LPPkJmZabFMhw4dMHHiRMyaNcs8bc+ePejTpw+Kiorg5+cHBwcHfPLJJxgzZox5ni+++AKTJk1CZWWl1bpYuzIUHBzcYrfJAYBh83oYf9spn6hUQhETD0WfgZBcWqZeRHT/iKpK6Bf/A6i83tJVuUmhaGDgACuDENx4/kWqP6128AIr024+J1N3HUqg3gAQov4zU4a6gz7UH/jhRplBb/msleEWz1npa0z3FRIRUavyQN4m5+XlBaVSaXHF5ty5cxZXdmr5+flZnV+lUsHT0/OW8zS0TgDQaDTQaDQNlrcERZ8BplvlaqoBSQGpW08o+w2C5OZ++4WJyCZJGkcox06G4afvgXPFAAQgSVaCxY0Aobac3iRhpM4D/pKidQzL31zjst0chc9aiLIMXLJBLAyWwUwYGghqdddRP7QxkBER2aRGhSEHBwfExMRg69atsmGvt27diuTkZKvLxMfH48cf5bdqbNmyBbGxsVCr1eZ5tm7dKntuaMuWLUhIsLyXsjWTnFygiE+EuHzR9MJUGxhBg4junSI4FIr/ftl0sqyQWk0YsReSQgk4KAEHyy/Imj2QMRQREZmobeNVMY0eWnvGjBkYP348YmNjER8fj+XLlyM/P9/83qBZs2bh7Nmz+PTTTwGYRo579913MWPGDEyZMgWpqalYsWKFbJS46dOno1+/fnjjjTeQnJyMdevWYdu2bdi9e3cT7WbzUfRP4nsqiOyUpOJ7rO2VOZAREZFNafQn9+jRo3HhwgXMnz8fRUVFeOihh7Bx40bodDoAQFFREfLz883zh4WFYePGjXjppZfw3nvvISAgAEuWLDG/YwgAEhIS8PXXX2POnDmYO3cuwsPD8c0339jcO4YAMAgREREREdmIRr9nqLVq6fcMERERERFR63Cn2YCvyiYiIiIiIrvEMERERERERHaJYYiIiIiIiOwSwxAREREREdklhiEiIiIiIrJLDENERERERGSXGIaIiIiIiMguMQwREREREZFdYhgiIiIiIiK7xDBERERERER2iWGIiIiIiIjsEsMQERERERHZJYYhIiIiIiKySwxDRERERERklxiGiIiIiIjILjEMERERERGRXWIYIiIiIiIiu8QwREREREREdolhiIiIiIiI7BLDEBERERER2SVVS1egqQghAABlZWUtXBMiIiIiImpJtZmgNiM05IEJQ+Xl5QCA4ODgFq4JERERERG1BuXl5XBzc2uwXBK3i0s2wmg0orCwEC4uLpAkqaWrY3fKysoQHByMgoICuLq6tnR1qJmx/Yl9gAD2A3vH9rdvra39hRAoLy9HQEAAFIqGnwx6YK4MKRQKBAUFtXQ17J6rq2ur+AdALYPtT+wDBLAf2Du2v31rTe1/qytCtTiAAhERERER2SWGISIiIiIisksMQ9QkNBoNXn31VWg0mpauCrUAtj+xDxDAfmDv2P72zVbb/4EZQIGIiIiIiKgxeGWIiIiIiIjsEsMQERERERHZJYYhIiIiIiKySwxDRERERERklxiGHmC7du3C8OHDERAQAEmS8MMPP8jKS0pKMGHCBAQEBKBNmzYYMmQITpw4YS7Py8uDJElWf7777jvZujZs2IC4uDhotVp4eXlh1KhRt63fkSNHkJiYCK1Wi8DAQMyfPx91x/PYvXs3evfuDU9PT2i1WnTs2BGLFi26t4NiZ2y9D+zYscPqtjMzM+/twNgJW2//CRMmWN12VFTUvR0YO2Pr/QAA3nvvPXTq1AlarRaRkZH49NNP7/6A2KHW3AcqKysxYcIEREdHQ6VS4YknnrCYp6ioCGPHjkVkZCQUCgVefPHFuz0Udqk52r+hz2tJkrB///5b1u92fwPud/szDD3Arl27hi5duuDdd9+1KBNC4IknnsCpU6ewbt06pKenQ6fTYdCgQbh27RoAIDg4GEVFRbKf1157DU5OThg6dKh5XatXr8b48eMxceJEHD58GHv27MHYsWNvWbeysjI8+uijCAgIwP79+/HOO+9g4cKFeOutt8zzODk54Y9//CN27dqF48ePY86cOZgzZw6WL1/eREfowWfrfaBWVlaWrA7t27e/xyNjH2y9/d9++23ZtgsKCuDh4YGnnnqqiY6QfbD1fvD+++9j1qxZmDdvHjIyMvDaa69h2rRp+PHHH5voCD34WnMfMBgM0Gq1+NOf/oRBgwZZnaeqqgre3t6YPXs2unTpcg9Hwj41R/snJCRYzDN58mSEhoYiNja2wbrdyd+A+97+guwCALF27Vrz71lZWQKAOHr0qHmaXq8XHh4e4sMPP2xwPV27dhXPPfec+feamhoRGBgoPvroo0bVZ+nSpcLNzU1UVlaapy1YsEAEBAQIo9HY4HIjR44U48aNa9S2yMQW+8D27dsFAHHp0qVGrZss2WL717d27VohSZLIy8tr1LboJlvsB/Hx8eLll1+WLTd9+nTRu3fvRm2LTFpbH6jr2WefFcnJybecJzExUUyfPv2ut2Hv7lf711ddXS18fHzE/Pnzb1mfxn4W3I/255UhO1VVVQUAcHR0NE9TKpVwcHDA7t27rS6TlpaGQ4cOYdKkSeZpBw8exNmzZ6FQKNCtWzf4+/tj6NChyMjIuOX2U1NTkZiYKHsxV1JSEgoLC5GXl2d1mfT0dKSkpCAxMfFOd5NuwZb6QO16Bw4ciO3btzd2V8kKW2r/WitWrMCgQYOg0+nudDfpNmyhH1RVVcnqBwBarRb79u1DTU1No/aXLLV0H6CW1VTtX9/69etRWlqKCRMm3HL7d/NZ0NQYhuxUx44dodPpMGvWLFy6dAnV1dX45z//ieLiYhQVFVldZsWKFejUqRMSEhLM006dOgUAmDdvHubMmYOffvoJ7u7uSExMxMWLFxvcfnFxMXx9fWXTan8vLi6WTQ8KCoJGo0FsbCymTZuGyZMn39U+k5wt9AF/f38sX74cq1evxpo1axAZGYmBAwdi165d97TvZBvtX1dRURE2bdrEf/9NzBb6QVJSEj766COkpaVBCIEDBw5g5cqVqKmpQWlp6T3tP7V8H6CW1VTtb22epKQkBAcH33L7jf0suB8YhuyUWq3G6tWrkZ2dDQ8PD7Rp0wY7duzA0KFDoVQqLea/fv06vvzyS4tvAYxGIwBg9uzZePLJJxETE4NVq1bJHqqLioqCs7MznJ2dZfcWS5IkW5e48bBc/em//vorDhw4gA8++ACLFy/GV199de8HgGyiD0RGRmLKlCno3r074uPjsXTpUjz22GNYuHBh0x0IO2UL7V/Xxx9/jLZt21p9uJruni30g7lz52Lo0KHo1asX1Go1kpOTzd82W6sjNU5r6APUcpqq/es6c+YMNm/ebDFPU3wW3A+qZtkKtUoxMTE4dOgQrly5gurqanh7eyMuLs7qg27ff/89Kioq8Mwzz8im+/v7AwA6d+5snqbRaNCuXTvk5+cDADZu3Gi+lUGr1QIA/Pz8LBL/uXPnAMDiG4KwsDAAQHR0NEpKSjBv3jyMGTPmrvebbrKVPlBXr1698Pnnnzd2V8kKW2l/IQRWrlyJ8ePHw8HB4V52maxo7f1Aq9Vi5cqVWLZsGUpKSsxXjF1cXODl5dUUh8DutWQfoJbXFO1f16pVq+Dp6YkRI0bIpjfluUBT4pUhgpubG7y9vXHixAkcOHAAycnJFvOsWLECI0aMgLe3t2x6TEwMNBoNsrKyzNNqamqQl5dnvq9fp9MhIiICERERCAwMBADEx8dj165dqK6uNi+3ZcsWBAQEIDQ0tMG6CiHM97dS07GlPpCenm7+0KWm0drbf+fOnTh58uQtv4mke9fa+4FarUZQUBCUSiW+/vprPP7441AoeBrTlFqiD1DrcS/tX0sIgVWrVuGZZ56BWq2WlTXluUCTatLhGKhVKS8vF+np6SI9PV0AEG+99ZZIT08Xp0+fFkII8e2334rt27eLnJwc8cMPPwidTidGjRplsZ4TJ04ISZLEpk2brG5n+vTpIjAwUGzevFlkZmaKSZMmCR8fH3Hx4sUG63b58mXh6+srxowZI44cOSLWrFkjXF1dxcKFC83zvPvuu2L9+vUiOztbZGdni5UrVwpXV1cxe/bsezwy9sPW+8CiRYvE2rVrRXZ2tjh69Kh45ZVXBACxevXqezwy9sHW27/WuHHjRFxc3F0eBbL1fpCVlSU+++wzkZ2dLfbu3StGjx4tPDw8RG5u7r0dGDvSmvuAEEJkZGSI9PR0MXz4cNG/f39zXeuqnRYTEyPGjh0r0tPTRUZGxt0dEDvTXO0vhBDbtm0TAMSxY8fuqG53+llwP9ufYegBVjsscf2fZ599VgghxNtvvy2CgoKEWq0WISEhYs6cOaKqqspiPbNmzRJBQUHCYDBY3U51dbX485//LHx8fISLi4sYNGiQbIjGhvz++++ib9++QqPRCD8/PzFv3jzZMIpLliwRUVFRok2bNsLV1VV069ZNLF26tMF6kCVb7wNvvPGGCA8PF46OjsLd3V306dNHbNiw4e4Ohh2y9fYXwvRBqdVqxfLlyxt/AEgIYfv94NixY6Jr165Cq9UKV1dXkZycLDIzM+/uYNip1t4HdDqd1frVZa1cp9M1+ljYo+ZqfyGEGDNmjEhISGhU/e7ks+B+tr90YwNERERERER2hTfbEhERERGRXWIYIiIiIiIiu8QwREREREREdolhiIiIiIiI7BLDEBERERER2SWGISIiIiIisksMQ0REREREZJcYhoiIiIiIyC4xDBERERERkV1iGCIiIiIiIrvEMERERERERHaJYYiIiIiIiOzS/wNv52np1/SskAAAAABJRU5ErkJggg==", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "plot(\"PERLND\", pls, \"PWATER\", \"UZET\", \"sum\")" + "plot(\"PERLND\", pls, \"PWATER\", \"PERC\", \"sum\")" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.120402Z", - "iopub.status.idle": "2024-05-21T21:50:35.120548Z", - "shell.execute_reply": "2024-05-21T21:50:35.120497Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.120492Z" - } - }, - "outputs": [], + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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Z79Kq3AVKTXFM97CAWY3AAgA2nPokqF3vnFcwPBRty/K4tGODVxX5WdM4MmB245EQAEzSqU+Cevr1j2PCiiSFwkN6+vWPdeqT4DSNDJj9CCwAMAkjo5Z2vXNe1hiv3Wjb9c55jYyOVQHgVhFYAGASPrzwZdzKyp+yJAXDQ/rwwpe3b1DAHEJgAYBJ6B8cP6wkUgfAHgILAEzCkvmupNYBsIfAAgCTsCp3gbI8Lo334WWHrn9aaFXugts5LGDOILAAwCSkpji0Y4NXkuJCy42fd2zwsh8LMEUILAAwSRX5WWrcXKBMT+xjn0yPS42bC9iHBZhCbBwHADZU5GdpjTeTnW6B24zAAgA2paY4VLJs4XQPA5hTeCQEAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4CQWWAwcOKDc3Vy6XSz6fT+3t7ePWBoNBPf7447rvvvuUkpKimpqauJqmpiY5HI64Y2iI7+QAAAAJBJaWlhbV1NSovr5egUBAZWVlWrdunXp7e8esHx4e1uLFi1VfX68VK1aM26/b7VYwGIw5XC6+kwMAACQQWP75n/9ZW7du1Q9/+EMtX75cL730krKzs9XY2Dhm/be//W29/PLL2rJlizwez7j9OhwOZWZmxhwAAACSzcBy9epVdXV1qby8PKa9vLxcHR0dtzSQK1euKCcnR0uXLtX69esVCAQmrB8eHlYkEok5AADA7GQrsAwMDGhkZEQZGRkx7RkZGQqFQgkPIi8vT01NTTpx4oSam5vlcrm0evVqffrpp+Oe09DQII/HEz2ys7MT/v0AAMBsCb3p1uGI/c4My7Li2uwoLi7W5s2btWLFCpWVlemNN97Qvffeq3379o17Tl1dncLhcPTo6+tL+PcDAACz2fouoUWLFik1NTVuNaW/vz9u1eVWpKSk6IEHHphwhcXpdMrpdCbtdwIAAHPZWmFJT0+Xz+dTW1tbTHtbW5tKS0uTNijLstTd3a2sLL6qHQAAJPBtzbW1taqsrFRhYaFKSkp06NAh9fb2qqqqStL1RzUXL17U4cOHo+d0d3dLuv7G2j/+8Y/q7u5Wenq6vF6vJGnXrl0qLi7Wd77zHUUiEe3du1fd3d3av39/Ei4RAADMdLYDi9/v16VLl7R7924Fg0Hl5+ertbVVOTk5kq5vFHfzniwrV66M/rurq0tHjhxRTk6OPvvsM0nS5cuX9dRTTykUCsnj8WjlypU6c+aMVq1adQuXBgAAZguHZVnWdA8iGSKRiDwej8LhsNxu93QPBwAATMJk/37zXUIAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8RIKLAcOHFBubq5cLpd8Pp/a29vHrQ0Gg3r88cd13333KSUlRTU1NWPWHTt2TF6vV06nU16vV8ePH09kaAAAYBayHVhaWlpUU1Oj+vp6BQIBlZWVad26dert7R2zfnh4WIsXL1Z9fb1WrFgxZk1nZ6f8fr8qKyt17tw5VVZWatOmTTp79qzd4QEAgFnIYVmWZeeEoqIiFRQUqLGxMdq2fPlybdy4UQ0NDROe+1d/9Ve6//779dJLL8W0+/1+RSIRnTx5MtpWUVGhu+66S83NzZMaVyQSkcfjUTgcltvtnvwFAQCAaTPZv9+2VliuXr2qrq4ulZeXx7SXl5ero6MjsZHq+grLzX2uXbt2wj6Hh4cViURiDgAAMDvZCiwDAwMaGRlRRkZGTHtGRoZCoVDCgwiFQrb7bGhokMfjiR7Z2dkJ/34AAGC2hN5063A4Yn62LCuubar7rKurUzgcjh59fX239PsBAIC50uwUL1q0SKmpqXErH/39/XErJHZkZmba7tPpdMrpdCb8OwEAwMxha4UlPT1dPp9PbW1tMe1tbW0qLS1NeBAlJSVxfZ4+ffqW+gQAALOHrRUWSaqtrVVlZaUKCwtVUlKiQ4cOqbe3V1VVVZKuP6q5ePGiDh8+HD2nu7tbknTlyhX98Y9/VHd3t9LT0+X1eiVJ1dXVevDBB7Vnzx499thjevvtt/Xee+/pgw8+SMIlAgCAmc52YPH7/bp06ZJ2796tYDCo/Px8tba2KicnR9L1jeJu3pNl5cqV0X93dXXpyJEjysnJ0WeffSZJKi0t1dGjR7V9+3Y999xzWrZsmVpaWlRUVHQLlwYAAGYL2/uwmIp9WAAAmHmmZB8WAACA6UBgAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABgvocBy4MAB5ebmyuVyyefzqb29fcL6999/Xz6fTy6XS/fcc48OHjwY83pTU5McDkfcMTQ0lMjwAADALGM7sLS0tKimpkb19fUKBAIqKyvTunXr1NvbO2b9hQsX9Mgjj6isrEyBQEA///nP9eyzz+rYsWMxdW63W8FgMOZwuVyJXRUAAJhVHJZlWXZOKCoqUkFBgRobG6Nty5cv18aNG9XQ0BBX/9Of/lQnTpxQT09PtK2qqkrnzp1TZ2enpOsrLDU1Nbp8+XKClyFFIhF5PB6Fw2G53e6E+wEAALfPZP9+21phuXr1qrq6ulReXh7TXl5ero6OjjHP6ezsjKtfu3atPvroI3399dfRtitXrignJ0dLly7V+vXrFQgEJhzL8PCwIpFIzAEAAGYnW4FlYGBAIyMjysjIiGnPyMhQKBQa85xQKDRm/bVr1zQwMCBJysvLU1NTk06cOKHm5ma5XC6tXr1an3766bhjaWhokMfjiR7Z2dl2LgUAAMwgCb3p1uFwxPxsWVZc2zfV/2l7cXGxNm/erBUrVqisrExvvPGG7r33Xu3bt2/cPuvq6hQOh6NHX19fIpcCAABmgDQ7xYsWLVJqamrcakp/f3/cKsoNmZmZY9anpaVp4cKFY56TkpKiBx54YMIVFqfTKafTaWf4AABghrK1wpKeni6fz6e2traY9ra2NpWWlo55TklJSVz96dOnVVhYqHnz5o15jmVZ6u7uVlZWlp3hAQCAWcr2I6Ha2lr95je/0auvvqqenh5t27ZNvb29qqqqknT9Uc2WLVui9VVVVfr8889VW1urnp4evfrqq3rllVf0k5/8JFqza9cuvfvuu/rDH/6g7u5ubd26Vd3d3dE+AQDA3GbrkZAk+f1+Xbp0Sbt371YwGFR+fr5aW1uVk5MjSQoGgzF7suTm5qq1tVXbtm3T/v37dffdd2vv3r36/ve/H625fPmynnrqKYVCIXk8Hq1cuVJnzpzRqlWrknCJAABgprO9D4up2IcFAICZZ0r2YQEAAJgOBBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA46VN9wAQb2TU0ocXvlT/4JCWzHdpVe4CpaY4pntYAABMGwKLYU59EtSud84rGB6KtmV5XNqxwauK/KxpHBkAANOHR0IGOfVJUE+//nFMWJGkUHhIT7/+sU59EpymkQEAML0ILIYYGbW0653zssZ47UbbrnfOa2R0rAoAAGY3AoshPrzwZdzKyp+yJAXDQ/rwwpe3b1AAABiCwGKI/sHxw0oidQAAzCYEFkMsme9Kah0AALMJgcUQq3IXKMvj0ngfXnbo+qeFVuUuuJ3DAgDACAQWQ6SmOLRjg1eS4kLLjZ93bPCyHwsAYE4isBikIj9LjZsLlOmJfeyT6XGpcXMB+7AAAOYsNo4zTEV+ltZ4M9npFgCAP0FgMVBqikMlyxZO9zAAADAGj4QAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDy+S2gSRkYtvowQAIBpRGCZQOjykNb88rcaHB6Jac/yuLRjg1cV+VnTNDIAAOaWhB4JHThwQLm5uXK5XPL5fGpvb5+w/v3335fP55PL5dI999yjgwcPxtUcO3ZMXq9XTqdTXq9Xx48fT2RoSbP8uZMqfuE/4sKKJIXCQ3r69Y916pPgNIwMAIC5x3ZgaWlpUU1Njerr6xUIBFRWVqZ169apt7d3zPoLFy7okUceUVlZmQKBgH7+85/r2Wef1bFjx6I1nZ2d8vv9qqys1Llz51RZWalNmzbp7NmziV/ZLVj+3En9v69Hx33d+r//7nrnvEZGrXHrAABAcjgsy7L1F7eoqEgFBQVqbGyMti1fvlwbN25UQ0NDXP1Pf/pTnThxQj09PdG2qqoqnTt3Tp2dnZIkv9+vSCSikydPRmsqKip01113qbm5eVLjikQi8ng8CofDcrvddi4pRujykIpf+I9J1zf/XbFKli1M+PcBADCXTfbvt60VlqtXr6qrq0vl5eUx7eXl5ero6BjznM7Ozrj6tWvX6qOPPtLXX389Yc14fUrS8PCwIpFIzJEM6/edsVXfPziUlN8LAADGZyuwDAwMaGRkRBkZGTHtGRkZCoVCY54TCoXGrL927ZoGBgYmrBmvT0lqaGiQx+OJHtnZ2XYuZVyRoWu26pfMdyXl9wIAgPEl9KZbhyP2I72WZcW1fVP9ze12+6yrq1M4HI4efX19kx7/RNyuyX9wKstz/SPOAABgatkKLIsWLVJqamrcykd/f3/cCskNmZmZY9anpaVp4cKFE9aM16ckOZ1Oud3umCMZ/v3HD066dscGL/uxAABwG9gKLOnp6fL5fGpra4tpb2trU2lp6ZjnlJSUxNWfPn1ahYWFmjdv3oQ14/U5lTL/3KU75n3ztBzcXMA+LAAA3Ca2HwnV1tbqN7/5jV599VX19PRo27Zt6u3tVVVVlaTrj2q2bNkSra+qqtLnn3+u2tpa9fT06NVXX9Urr7yin/zkJ9Ga6upqnT59Wnv27NF///d/a8+ePXrvvfdUU1Nz61eYgJ5/XDduaElPc+j3zz9CWAEA4DayvdOt3+/XpUuXtHv3bgWDQeXn56u1tVU5OTmSpGAwGLMnS25urlpbW7Vt2zbt379fd999t/bu3avvf//70ZrS0lIdPXpU27dv13PPPadly5appaVFRUVFSbjExPT84zqFLg9p/b4zigxdk9uVpn//8YPK/HPeZAsAwO1mex8WUyVrHxYAAHD7TMk+LAAAANOBwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGM/21vymurFhbyQSmeaRAACAybrxd/ubNt6fNYFlcHBQkpSdnT3NIwEAAHYNDg7K4/GM+/qs+S6h0dFRffHFF5o/f74cDkfS+o1EIsrOzlZfXx/fUZQA5u/WMH+JY+5uDfN3a5i/ybMsS4ODg7r77ruVkjL+O1VmzQpLSkqKli5dOmX9u91ubrpbwPzdGuYvcczdrWH+bg3zNzkTrazcwJtuAQCA8QgsAADAeASWb+B0OrVjxw45nc7pHsqMxPzdGuYvcczdrWH+bg3zl3yz5k23AABg9mKFBQAAGI/AAgAAjEdgAQAAxiOwAAAA483JwHLgwAHl5ubK5XLJ5/Opvb19wvr3339fPp9PLpdL99xzjw4ePBhXc+zYMXm9XjmdTnm9Xh0/fnyqhj+tkj13TU1NcjgcccfQ0NBUXsa0sTN/wWBQjz/+uO677z6lpKSopqZmzLq5cu9JyZ8/7r/x5++tt97SmjVrtHjxYrndbpWUlOjdd9+Nq5sr91+y526u3XtJYc0xR48etebNm2f9+te/ts6fP29VV1dbd955p/X555+PWf+HP/zB+rM/+zOrurraOn/+vPXrX//amjdvnvVv//Zv0ZqOjg4rNTXVev75562enh7r+eeft9LS0qz//M//vF2XdVtMxdy99tprltvttoLBYMwxG9mdvwsXLljPPvus9S//8i/W/fffb1VXV8fVzJV7z7KmZv64/8afv+rqamvPnj3Whx9+aP3P//yPVVdXZ82bN8/6+OOPozVz5f6birmbS/dessy5wLJq1Sqrqqoqpi0vL8/62c9+Nmb9P/zDP1h5eXkxbT/60Y+s4uLi6M+bNm2yKioqYmrWrl1r/c3f/E2SRm2GqZi71157zfJ4PEkfq4nszt+feuihh8b8gztX7j3Lmpr54/6b3Pzd4PV6rV27dkV/niv331TM3Vy695JlTj0Sunr1qrq6ulReXh7TXl5ero6OjjHP6ezsjKtfu3atPvroI3399dcT1ozX50w0VXMnSVeuXFFOTo6WLl2q9evXKxAIJP8Cplki8zcZc+Hek6Zu/iTuv8nO3+joqAYHB7VgwYJo21y4/6Zq7qS5ce8l05wKLAMDAxoZGVFGRkZMe0ZGhkKh0JjnhEKhMeuvXbumgYGBCWvG63Mmmqq5y8vLU1NTk06cOKHm5ma5XC6tXr1an3766dRcyDRJZP4mYy7ce9LUzR/33+Tn78UXX9RXX32lTZs2Rdvmwv03VXM3V+69ZJo139Zsh8PhiPnZsqy4tm+qv7ndbp8zVbLnrri4WMXFxdHXV69erYKCAu3bt0979+5N1rCNMRX3yVy596TkXyv33+Tmr7m5WTt37tTbb7+tJUuWJKXPmSbZczfX7r1kmFOBZdGiRUpNTY1Lxf39/XHp+YbMzMwx69PS0rRw4cIJa8brcyaaqrm7WUpKih544IFZ938ZiczfZMyFe0+auvm7GfdfvJaWFm3dulVvvvmmHn744ZjX5sL9N1Vzd7PZeu8l05x6JJSeni6fz6e2traY9ra2NpWWlo55TklJSVz96dOnVVhYqHnz5k1YM16fM9FUzd3NLMtSd3e3srKykjNwQyQyf5MxF+49aerm72bcf7Gam5v15JNP6siRI3r00UfjXp8L999Uzd3NZuu9l1TT8U7f6XTj42mvvPKKdf78eaumpsa68847rc8++8yyLMv62c9+ZlVWVkbrb3w0d9u2bdb58+etV155Je6jub/73e+s1NRU64UXXrB6enqsF154YVZ/tC+Zc7dz507r1KlT1u9//3srEAhYP/jBD6y0tDTr7Nmzt/36pprd+bMsywoEAlYgELB8Pp/1+OOPW4FAwPqv//qv6Otz5d6zrKmZP+6/8efvyJEjVlpamrV///6Yj91evnw5WjNX7r+pmLu5dO8ly5wLLJZlWfv377dycnKs9PR0q6CgwHr//fejrz3xxBPWQw89FFP/29/+1lq5cqWVnp5uffvb37YaGxvj+nzzzTet++67z5o3b56Vl5dnHTt2bKovY1oke+5qamqsb33rW1Z6erq1ePFiq7y83Oro6LgdlzIt7M6fpLgjJycnpmau3HuWlfz54/4bf/4eeuihMefviSeeiOlzrtx/yZ67uXbvJYPDsv7vXZAAAACGmlPvYQEAADMTgQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxvv/A7yKa8f88+8AAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "scatter(\"PERLND\", pls, \"PWATER\", \"UZET\", \"sum\")" + "scatter(\"PERLND\", pls, \"PWATER\", \"PERC\", \"sum\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### PERLND PWATER UZI" + "#### PERLND PWATER PERO" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.120802Z", - "iopub.status.idle": "2024-05-21T21:50:35.120894Z", - "shell.execute_reply": "2024-05-21T21:50:35.120850Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.120846Z" + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "plot(\"PERLND\", pls, \"PWATER\", \"UZI\", \"sum\")" + "plot(\"PERLND\", pls, \"PWATER\", \"PERO\", \"sum\")" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.121138Z", - "iopub.status.idle": "2024-05-21T21:50:35.121251Z", - "shell.execute_reply": "2024-05-21T21:50:35.121202Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.121197Z" + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "scatter(\"PERLND\", pls, \"PWATER\", \"UZI\", \"sum\")" + "scatter(\"PERLND\", pls, \"PWATER\", \"PERO\", \"sum\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## RCHRES" + "#### PERLND PWATER PERS" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.121733Z", - "iopub.status.idle": "2024-05-21T21:50:35.121845Z", - "shell.execute_reply": "2024-05-21T21:50:35.121796Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.121790Z" - }, - "scrolled": true - }, - "outputs": [], + "execution_count": 57, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "rchreskeys = summary[(summary.Frequency == \"Monthly\") & (summary.Operation == \"RCHRES\")]\n", - "rchreskeys[0:10]" + "plot(\"PERLND\", pls, \"PWATER\", \"PERS\", \"last\")" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.122060Z", - "iopub.status.idle": "2024-05-21T21:50:35.122153Z", - "shell.execute_reply": "2024-05-21T21:50:35.122109Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.122104Z" + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "delta = monthlyoutflow(rchreskeys, \"ROVOL\")\n", - "delta" + "scatter(\"PERLND\", pls, \"PWATER\", \"PERS\", \"last\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Look at the statistics for the percent difference column" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.122458Z", - "iopub.status.idle": "2024-05-21T21:50:35.122553Z", - "shell.execute_reply": "2024-05-21T21:50:35.122512Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.122507Z" - } - }, - "outputs": [], - "source": [ - "delta.describe()" + "#### PERLND PWATER PET, Monthly" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.122827Z", - "iopub.status.idle": "2024-05-21T21:50:35.122928Z", - "shell.execute_reply": "2024-05-21T21:50:35.122887Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.122882Z" + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "delta[\"Percent diff\"].hist()" + "plot(\"PERLND\", pls, \"PWATER\", \"PET\", \"sum\")" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.123610Z", - "iopub.status.idle": "2024-05-21T21:50:35.123727Z", - "shell.execute_reply": "2024-05-21T21:50:35.123677Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.123672Z" + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "rid = delta.index[-1]\n", - "print(\"WORST RCHRES SEGMENT IS\", rid)" + "scatter(\"PERLND\", pls, \"PWATER\", \"PET\", \"sum\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### RCHRES HYDR IVOL" + "#### PERLND PWATER SUPY" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.123993Z", - "iopub.status.idle": "2024-05-21T21:50:35.124087Z", - "shell.execute_reply": "2024-05-21T21:50:35.124042Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.124038Z" + "execution_count": 61, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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8+PDg52rChAnBx4wxzJw5k+eeew7ovJ/lgQceYMiQIdx444373G/S8b2wYsUKpkyZ0qWali1bts/DJSdOnLjfGaMOt99+O0899RS33HLLXp/r3f3mN7/hvffe48tf/jJTp04lOjqa8vJy/vrXv7J161Z+97vfBa+dPXs255xzDt///vepqKhg1qxZWGuDe2DOOeecg57RExFxjXtHxIiIHNgXHcK4u44D8fZ3+9nPfha8dl+HS3ZYuHChBewvf/lLa+2uwyX3d3vooYestYHDJefNm7fX6xUUFFiv17vfwyU7bhEREXb48OF21qxZ9o477rA1NTUH9fnpyqGa1lr75z//2WZnZ9uIiAg7ZswYe+utt9rW1ta9rquurrZXXHGFTUxMtFFRUfbYY4+1r7/++l7X7flx7H7b/cBCa61NSkqyxx577AFrPNBhiHu6+OKLLWAvvPDCvR7705/+ZAE7evTo4NiKFSssYH/wgx/s9zULCwstYL/73e92GucgDpfc3233z98Xvc5NN91kAbtkyZL91rd06VJ7/fXX2ylTptjExETr9XrtsGHD7Ny5c+1LL7201/Wtra32jjvusLm5uTYyMtJGRkba3Nxce8cdd+z19e/q95S1+//+FxHpLsbaw2hGLyIichAKCgrIzc3lxRdfZN68eW6XIyIifYz2tIiISI976623mDFjhgKLiIgcEs20iIiIiIhISNNMi4iIiIiIhDSFFhERERERCWkKLSIiIiIiEtIUWkREREREJKT1+uGSjuOwYcMG4uLiMMb09tuLiIiIiEiIsNayc+dORo0ahcez//mUXg8tGzZsIDU1tbffVkREREREQlRVVRUpKSn7fbzXQ0tcXBwQKCw+Pr63315EREREREJEXV0dqampwYywP70eWjqWhMXHxyu0iIiIiIjIAbeNaCO+iIiIiIiENIUWEREREREJaQotIiIiIiIS0np9T4uIiIiISCjz+/20tbW5XUa/EB4ejtfrPezXUWgRERERESFwZkh1dTU7duxwu5R+JSEhgeTk5MM6o1GhRUREREQEgoFl+PDhxMTE6CD0w2StpbGxkZqaGgBGjhx5yK+l0CIiIiIiA57f7w8GlqFDh7pdTr8RHR0NQE1NDcOHDz/kpWLaiC8iIiIiA17HHpaYmBiXK+l/Oj6nh7NPSKFFRERERKSdloR1v+74nCq0iIiIiIhISFNoERERERGRkKbQIiIiIiLSh1111VWcd955e40vXrwYY0ywhfN9993HlClTiI2NJSEhgSOOOIK77roreP1tt92GMQZjDF6vl9TUVK699lo2b94cvKbj8d1vJ5xwQk9/iOoeJiIiIiLS3z3wwAPccMMN3HPPPcyaNYuWlhY+//xzCgoKOl2Xm5vLG2+8gd/v57PPPuOaa65h/fr1vPzyy8FrHnroIebOnRu8HxER0eP1K7SIiIiIiOzBt+Bp2FztXgHDkgk75+Jue7kXXniBiy++mGuuuSY4lpubu9d1YWFhJCcnAzB69Gi+973v8Ytf/IKmpqZg++KOwyJ7k0KLiIiIiMieNldj11W69vbd3cMsOTmZJUuWUFlZSVpa2kE/Lzo6Gsdx8Pl83VxR12hPi4iIiIhIH/fiiy8yaNCgTrczzjgj+Pitt95KQkIC6enp5OTkcNVVV/H000/jOM5+X7OwsJD58+dz9NFHExcXFxy/9NJLO73P888/35MfGqCZFhERERGRPm/27NnMnz+/09iHH37IV77yFQBGjhzJBx98wKpVq1iyZAnvv/8+V155Jf/85z955ZVX8HgCcxkrV65k0KBB+P1+WlpaOOmkk7j//vs7ve4f//hHTjnllOD9kSNH9vBHp9AiIiIiItLnxcbGMm7cuE5j69at2+u6vLw88vLyuP7663n33Xc58cQTWbJkCbNnzwYgJyeHBQsW4PV6GTVqFJGRkXu9RnJy8l7v1dMUWkRERERE9jQsudv3lXT1/XvaxIkTAWhoaAiORURE9HogORgKLSIiIiIie+jOzl2h4Fvf+hajRo1izpw5pKSksHHjRn79618zbNgwZsyY4XZ5B6SN+CIiIiIi/dwpp5zC0qVLueiii8jOzuaCCy4gKiqKRYsWMXToULfLOyBjrbW9+YZ1dXUMHjyY2tpa4uPje/OtRURERET2qbm5mfLycjIyMoiKinK7nH7liz63B5sNtDxMZICwvjZs/grwtWHG52Fi4w78JBEREZEQoNAiMgDY5iZ89/8Rtm8NDLz+ImFXfRuTPNrdwkREREQOgva0iAwAzruLdgUWgJZm/G+86F5BIiIiIl2g0CLSz1lrcfJXANDq8/LB2nSsBVu2BtvS7HJ1IiIiIgem0CLS39VshB3baGwN508fzGLWg99lzbYksA62Yo3b1YmIiIgckEKLSD/nFK4C4NU14/n5onkAvFmWBYAtK3GtLhEREZGDpdAi0s85RfkALCjMI2/4Bk4YU8qisuzAYwotIiIi0gcotIj0Y7Z2O2xcR5vfw8LiiZwzfhVzMktYXD4Ov2NgyyZsXa3bZYqIiIh8IYUWkX6sY5blncqx7GiO4dwJqzhlbDFjBm9n487AAU62XLMtIiIiEtp0TotIP2bbQ8u2pmhmpJYzNXk9xsAn3/pD8BqnrBjPlOlulSgiIiJyQJppEemnbHMTtqIUgAtzP2fJNX/FmPbHLKzdkRD4c1kJ1lqXqhQREZHDddVVV3HeeeftNb548WKMMezYsQOA++67jylTphAbG0tCQgJHHHEEd911V/D62267DWMMxhi8Xi+pqalce+21bN68GYCKigquueYaMjIyiI6OZuzYsdx66620trb2+MeomRaRfsquKQTHT/XOOBxrGBVfF3zsn8uO5Ycvf4lN/3cLsfV1sGUTDEt2sVoRERHpSQ888AA33HAD99xzD7NmzaKlpYXPP/+cgoKCTtfl5ubyxhtv4Pf7+eyzz7jmmmtYv349L7/8MoWFhTiOw3333ce4ceNYtWoV1113HQ0NDdx99909Wr9Ci0g/5RQFWh3/7aPj+eeyGVTdeBteT2BG5fgx5bT6w3hvbQanjSvCKSvBq9AiIiLSb73wwgtcfPHFXHPNNcGx3Nzcva4LCwsjOTnwM8Ho0aP53ve+xy9+8QuampqYO3cuc+fODV6bmZlJUVER8+fP7/HQouVhIv2Q9fuwJYUA/K9wEmdkrQ4ElvjBYAwThm1i5KDa3c5rKXazXBEREelhycnJLF26lMrKyi49Lzo6Gsdx8Pl8+3y8traWxMTE7ijxC3V5pmX9+vX83//9Hy+//DJNTU1kZ2fzwAMPcOSRR/ZEfSJyCGxFKbQ0U7wlidWbk/nVnJcB8OROxa4th/VrmZNZEjyvxVaUYv1+jNfrZtkiIiIhaePGwG13Q4ZARgY0N8MeK6wAmDYt8N+iImho6PxYejokJsLmzVBV1fmxkSMDt6568cUXGTRoUKcxv98f/POtt97K+eefT3p6OtnZ2cyYMYMzzzyTCy+8EI9n3/MYhYWFzJ8/n6OPPpq4uLi9Hi8tLeUvf/kLv//977tecBd1KbRs376d448/ntmzZ/Pyyy8zfPhwSktLSUhI6KHyRORQdHQNe6Eoj+iwVk4dWwSAyckDbxh2/VpOHlvM4vJxNLaGE0MLdv1azJgMN8sWEREJSffdB7/8Zeexyy+Hxx6DdetgX7+77+hxc9VVsHRp58cefRS+8hV4+mn4znc6P3brrXDbbV2vcfbs2cyfP7/T2IcffshXvvIVAEaOHMkHH3zAqlWrWLJkCe+//z5XXnkl//znP3nllVeCwWXlypUMGjQIv99PS0sLJ510Evfff/9e77dhwwbmzp3LRRddxLXXXtv1gruoS6HlrrvuIjU1lYceeig4lp6e3t01ichhsNYGz2epb43kSxM/JyaiDWJiManp4Djw7iIuyfuMyycv29VRrKwYFFpERET28o1vwDnndB4bMiTw35QUWLZs/8/917/2PdMCcPHFMGNG58cOZZYFIDY2lnHjxnUaW7du3V7X5eXlkZeXx/XXX8+7777LiSeeyJIlS5g9ezYAOTk5LFiwAK/Xy6hRo4iMjNzrNTZs2MDs2bOZMWPGPgNNT+hSaFmwYAGnn346F110EUuWLGH06NF8+9vf5rrrruup+kSkq6rXQ90OAG6d/Wpw2GRPxHg8kJoGYeGE0QZAc1sYUeG+wCGTJ53uRsUiIiIh7YuWbEVF7VoKti85Oft/bNiwwM0tEydOBKBht1QVERGxV/jZ3fr165k9ezZHHnkkDz300H6XlnW3Lr1LWVkZ8+fPJysri1dffZVvfvObfO973+ORRx7Z73NaWlqoq6vrdBORnuMUBrqGVWwfQkNrRHDckxPoEGLCwjFpgRmV3707myn3/hhrwa6rxLY0937BIiIi0uO+9a1vcfvtt/Pee+9RWVnJ0qVLueKKKxg2bBgz9pzu2Y8NGzZw0kknkZqayt13383mzZuprq6murq6h6vv4kyL4zhMnz6dO+64A4AjjjiC/Px85s+fzxVXXLHP59x55538cs9FgCLSYzqWhn1v4QX4HA8vXXE/hIVhMrOD15iMbGxpMROHVVO+Yyhl24cyNnErtrIMkz3RrdJFRESkh5xyyik8+OCDzJ8/n61bt5KUlMSMGTNYtGgRQ4cOPajXeO2111izZg1r1qwhJSWl02M9fVB1l2ZaRo4cGZxG6jBhwgTWrl273+fcfPPN1NbWBm9Ve7ZIEJFuY3dsg00bqGuO5M3yLM7MDrQzMZnZmIhda1I9mYFWxzPTy/Aa/26tj0t6v2gRERE5LP/61794/vnn9xo/6aSTsNaSkJDABRdcwMKFC9mwYQMtLS2sX7+e//73v0yaNCl4/W233cby5cv3+z5XXXUV1tp93npal0LL8ccfT1FRUaex4uJi0tLS9vucyMhI4uPjO91EpGd0zLK8umY8rf4wzh4fuO/Jyet8YfIoiIklLrKFY1LWBlsfO+U6r0VERERCT5dCyw9/+EOWLl3KHXfcwZo1a3j88ce5//77uf7663uqPhHpAtu+n+V/hZOYmryOtITtgMHkdJ4hNcaDyQjMrszJLOajdWmB1ow11did2ncmIiIioaVLoeWoo47iueee44knniAvL4/bb7+dP/3pT1x++eU9VZ+IHCTb1IitLAOgoTWCL038HACTmoaJ3ftAqI4lYj+YsYTV37tjV+vjci0RExERkdDSpY34AGeddRZnnXVWT9QiIofBlqwG6wDw3GUPBg+1MnsuDWvXsTE/Pqol8HwLxoBTVoxn8j5OyRIRERFxSe80VhaRHucUBZaGlW1LxO+Y4MyJZ/x+QktCIgwJdAv55Vunc/4TXwMCm/F7Y0OdiIhIKNK/gd2vOz6nCi0i/YD1+bBrinAcw0kPfpdb35wbeCBpOGbo/k+t8rTPtgyJauSN0mya2sJgZy1sremNskVEREJGeHg4AI2NjS5X0v90fE47PseHosvLw0Qk9NjyEmht4eP1Y6iuj2duViGw60DJ/TGZWbDsA+ZkltDiD+f9tRmcPLYEp6wEb9KI3ihdREQkJHi9XhISEqipCfziLiYmBtOxbEEOibWWxsZGampqSEhIwOv1HvJrKbSI9AO2vdXx84WTGBazkxmpFcD+97N0MOnjAEPu8GpGxNaxqCybk8eWYMuK4egTerhqERGR0JKcnAwQDC7SPRISEoKf20Ol0CLSx1nr4BTlYy38b/UkzsopwOuxEBuHSRnzhc81MbGYkaNh4zrmZJbsOmSyohTr+DGeQ/+NiIiISF9jjGHkyJEMHz6ctrY2t8vpF8LDww9rhqWDQotIH2c3rIP6OrY3ReP1OJwzfiUAJnsixhx425rJzMJuXMcv57zMoIjWwGBLM3bDOkzK/g+OFRER6a+8Xm+3/KAt3UehRaSP6zhQMjGmiZXf+X/BVsf76xq2J5OZDe+9RfqQ7Z1ft6wYFFpEREQkBKh7mEgf57TvZ1m7IwEInLVCeETwxPsDMWMyICzw+4tfLJrLLxYFOo/ZsuJur1VERETkUCi0iPRhdtsW2FzN+rp4xv3pFp5fHZhdMWNzMAfZVtCEhQeCC1DXEs1/Vh0ReO2qSmxrS88ULiIiItIFCi0ifVjHLMsLhXmEefzMSi8FDtzqeE8mI3Bey5zMYkq3J1G+PREcP7ayrHsLFhERETkECi0ifZgtCuxnWVCYx6z0UoZEN4ExmOwJXXodT2ZgKdms9FI8xtnVRayspHsLFhERETkECi0ifZRtrMeuLWd7UzSLK8ZxbkfXsDEZmJhBXXux5NEQHcPgqGaOGr2WRWWBmRenXPtaRERExH3qHibSR9ni1WAtxVuGMSSqkbNyAkvFDnSg5L4YjweTMQ5b8Dm/n/s/hkQ3Bh7YtBFbvxMzKK47SxcRERHpEs20iPRRHftZjkldS9WNvyRlcC3Q9f0sHTr2tRydspasoVuC47ZcS8RERETEXQotIn2QbWvDlhbR6vOytTEGj6f9cJbhyZjEpEN6zY59LQC3vXk6jy4/EgBH+1pERETEZQotIn2QLSuGtlZeL80m5Xe3UbljCACeQ1ga1sEkJkFCIgDLNqTyxOdHBt/LdpxYKSIiIuIChRaRPsgJdg2bRGbiVsYMDpxmbw5xaVgHk9nR+riEd9dm0twWBnU7YNuWL36iiIiISA9SaBHpY6zjYIsL8DuGF4smcs74VRgDxMVjRqUc1mt3LBE7ObOYZl84H1SlA+CUqYuYiIiIuEehRaSPsesroaGeD6rS2dwYx7njA7MunuxcjDm8v9ImYxwAecOrGR67k0U6r0VERERCgFoei/QxtjDQNaxoy3DSE7Zy9Oi1AJjxh76fpYOJGQTJo/FUr+dPZz7L2CFbA+9ZXoJ1HIxHv+cQERGR3qfQItLHdOxnuebID7ly6seBzmERkZj0cd3y+p7MLJzq9VyY+/muwZZm7MZ1mNFjuuU9RERERLpCvzYV6UPslhrYupm65khafF7CvA4AZtx4TFj3/A6iYzO+3zH87t3ZvFeZEXhv7WsRERERlyi0iPQhHbMsf/nwRCbc81McxwCHfqDkvpgxGeD14vVY/vXZ0Ty58ghA+1pERETEPQotIn2ILQrsZ/nf6kkcN6Y8sDTMeDBZE7rtPUx4BCY1MLtycmYJi8oCMy+2qhzb1tpt7yMiIiJysBRaRPoIW78TW1VJ5Y4hLK9O4Zz2rmEmPRMTHdOt77XrvJZi1mwbFji80u/Hri3v1vcRERERORgKLSJ9hC0uACwvFOYS4fUxd9xqAEzO4XcN25NpP69lVnopHuPwVkfr41LtaxEREZHep+5hIn1Ex36Woi3DOTmzmPioFqB797N0MCNTICqaITTxyzkvM3F4daCG8mK83f5uIiIiIl9MoUWkD7CtLcHuXX8561lafe3RYcQoTEJit7+f8XgwGeOwq1fyfye+ueuB6g3YhnpM7KBuf08RERGR/dHyMJE+wJYVg89HbXMU1kJEmB/omVmWDiYjsK+lqS2Mhz87irJtgXBky9VFTERERHqXQotIH+C0dw275vlLuOipq4LjnvHdv58l+Nrt+1oM8L2F5/O/wkmBWtT6WERERHqZQotIiLOOH1uUT2NrOK+vyeHYlMrAA/EJkDy65944MQkGDyEq3McJaeW82bEZv6wYa23Pva+IiIjIHhRaREKcraqApkZeL82hyRfBuRNWAoGlYcaYHntfYwwmIxBU5mQW805lJi0+L9Ruh+1be+x9RURERPak0CIS4mxhYGnYgsI8JgyrJmvoFgBMDy4N69CxRGxOZgmNbZEsrUoHtERMREREepdCi0gIs9biFK3CWlhVkxw8UJLIKEza2B5//47zWqaM2MDlkz8hOrwtUFe5zmsRERGR3qOWxyKhbPMm2L4VY2Dp1/9Eiy/wV9ZkTcB4e/7EFBMbByNG4dm0gYfOfyI4bstKsI6D8ej3HiIiItLz9BOHSAjrOFCyviUCYyAq3Af0bKvjPXUsEWtqC+Ol4gnUNUdCcxO2en2v1SAiIiIDm0KLSAizRflYC0f87SbuemdOYNDjxWRN6LUaTGbgvJZN9XGc9/i1vFW+q4uYiIiISG9QaBEJUXZnLXb9WpZXj6ayNpHpo6oAMBljMZFRvVaHGZMBHi/pQ7YzdsiW3VofazO+iIiI9A6FFpEQ5RQVAIGuYQlRjcxMLwXA5PR817DdmYhITGo6EGh9vKgsMPNi15Zj29p6tRYREREZmBRaREKUbd/P8r/VeZyZXUC41wF6dz9LB7Nb6+PircOpqk0Avw9bVd7rtYiIiMjAo9AiEoJsSzO2vIQtDbGsrR3Cue2tjs3IFEx8Qq/X07Gv5aSMNZwwppRtTdGBOrWvRURERHqBWh6LhCBbWgR+P0mxDWy46dbgeG8vDQu+76gUiIxiKI28+bW/Bce1r0VERER6g2ZaREKQU5QPBNoMR4T5iQjzA+AZ3/tLwwCMx4tJDxxm6XcMy9anYC3YjeuxjQ2u1CQiIiIDh0KLSIixfj+2uICa+kEk33U7r63JCTyQkAjDR7pWV8cSscXl45jxjx+yqiYZsNjyNa7VJCIiIgODQotIiLFry6G5iYXFE2nxh3HEyHVAYAO+Mca1ujztoeW4MeVEett4s6OLmPa1iIiISA9TaBEJMbu6hk3i+DHlDIsNLL9yaz9L0NBhED+Y6HAfJ6SVB89rccq1r0VERER6lkKLSAix1uIU5bOzJZJFZVmc0941jKhoTFqGq7UZY4JLxOZkFvN2xVhafV7YvhW7faurtYmIiEj/ptAiEkpqNsKObXy6IQWf4wmGFpM9EePxulwceDICsysnZ5YwOr6WdXWDAXURExERkZ6l0CISQpzCQEiZlVFK9f/9gowh2wDwuL00rF3HIZPTRq1j1XfvIjMxUJ9Trn0tIiIi0nMUWkRCiFOUj98x+PweBkc1Bwa9YZhxOe4W1s4MiofhycH71TvjgMBMi7WOW2WJiIhIP6fQIhIibO122LiOt8qzSL37NtbVBpZemcwsTESky9Xt4skI7Gv594ppZPzhFuqaI6GpEao3uFyZiIiI9FcKLSIhouNAyQWFecRFNjM6vhYItDoOJR1LxGakVuC3Xt6uDBw66Whfi4iIiPQQhRaREGGL8nEcw4LCPM4Zv4qOI1lMdoiFlvSx4PGQmbiNjIStwdbHOq9FREREeopCi0gIsM1N2IpSlm1IYcPOwbu6ho0eg4mLd7m6zkxEJCYlHQi0Pl7Uccjk2jKsr83FykRERKS/UmgRCQF2TSE4ft5dm8nQ6AaOS60AQuBAyf3oWCI2J7OEmvo4apujwOfDVlW4W5iIiIj0S2FuFyAi4BQFZlZ+eNwSvjrlE8K8gU5cnvGhtTSsg8nMgsWvct6ElVww8XM8Hgu0n9fSfpaLiIiISHfRTIuIy6zfhy0pxOf3YC0kxTYEHkhMgqQR7ha3H2bUGIiIJNzr4PFYWn2Bgy+1r0VERER6gkKLiMtsRSm0NPPHD2Zx9H034DiBHfienFxMx278EGO83sCGfODeD09gwj03Yy3YDeuwTY0uVyciIiL9jUKLiMvsbq2O0xK2BZdahep+lg4mM7ABP3toDVV1Q1i9eQRgsRVr3C1MRERE+h2FFhEXWWtxivLZuDOOD9elc+74lYEHYmIxqemu1nYgnvbN+MePKSfC69ut9bHOaxEREZHupdAi4qbq9VC3gxeLcvEaP/OyCwAw2RMxnhD/65k0AuLiiYlo47jUct5ob33saF+LiIiIdLMQ/6lIpH9zCgNdwxaXj2NmehmJMU1AYD9LqDPGBJeIzcks4cOqdPyOgW1bsDu2uVydiIiI9CdqeSziIqd9P8ujF/ybLY2xgcGwsGAYCHWejCz8Kz7hW0e/x3ePfQfvbq2PzbRjXK5ORERE+gvNtIi4xO7YBps24DgGj8cyfFA9ENjgbiIiXa7u4HQcMjk4qpnYiNbguFOuJWIiIiLSfRRaRFzSMctyxbOX8+0XLgyOe0K8a9juTNxgGBY4S+bud2dz3r+vAcCWrcFax83SREREpB9RaBFxiS1cRYvPy0vFE0iJ39E+ajA5E90sq8s8GYGlbHGRzbxWmsPOlkhorIdN1S5XJiIiIv2FQouIC2xTI7ayjLfKs6hvjeKc8YEN+SY1DRMb53J1XdOxRGxOZgk+x8s7lZmAuoiJiIhI91FoEXGBLVkN1mFBYR5jh2whd3hgViLUD5TcF5M+FoyHcYlbGDN4267zWsp1XouIiIh0D4UWERc4RauwFhaVZnPuhJUYExj3jO+DoSUyCpMyBmPg5MwSFrWf12Iry7A+n8vViYiISH+glscivcz6fNg1RRgDn377bpp97X8Nk4Zjhg5zt7hDZDKysFUV3DzzdSK8/sBgWyt2XWVgJkZERETkMGimRaSX2fISaG3BWoiNaGVoTCPQNw6U3B8zNjC7kj5kO6Pi64LjVvtaREREpBsotIj0MluUj7Vw9H03cP/HM4LjfXE/SwczOg3az5b57dsn87M3zgQUWkRERKR7KLSI9CJrHZyifAo2j2BF9WhSB28PPBAbh0kZ425xh8F4vZi0QNew7U0xPL7iSKwFu6EK29zkcnUiIiLS1ym0iPQiu2Ed1NexoDCPQRHNzM5YA4DJnogxffuvo8kMLBGbk1nM+p0JFG0ZDtZiK9a4XJmIiIj0dX37pySRPsYWBs5jWVCYx+njCokKD3TX6otdw/bkaT+v5YS0csI9vl2tj8vU+lhEREQOj0KLSC9yivKpqR/EpxtSOHdCIMAQHoHJyHK3sO4wLBli44iNaGVGakWw9bEOmRQREZHDpZbHIr3EbtsCm6sZPggqfvQr4iNbADBjczDh4S5Xd/iMMZjMLOzKT/nNKQuJiWgNPLB1M7Z2O2bwEHcLFBERkT5LMy0ivcQpygfAWhgZt5PY9h/q+3Kr4z11LBE7JnUtk0ZUB8dtuZaIiYiIyKFTaBHpJbZoFdubosn+0894pyLQaQtjMNkT3C2sG3Vsxgf43buzeWT5dAAc7WsRERGRw6DQItILbGM9dm05LxVPoLI2kbGJWwAwYzIwMYNcrq77mPgESBoOwIfr0njks6OAwGZ8a62LlYmIiEhf1qXQcttttwXWre92S05O7qnaRPoNW7warOV/hZM4enRl8NT4vnyg5P542psKnJxZwgdV6TS0RkDDTqipPsAzRURERPatyzMtubm5bNy4MXhbuXJlT9Ql0q84Rfk0tYXx2poczhm/Kjjen/azdNj9vJY2J4x3KzMAdRETERGRQ9fl0BIWFkZycnLwNmzYsJ6oS6TfsG1t2NIi3q4YS2Nb5K7QMjwZk5jkbnE9wKSPBWPIHrqZlPgdvNne+lib8UVERORQdTm0lJSUMGrUKDIyMrjkkksoKyv7wutbWlqoq6vrdBMZSGxZMbS1ctq4IlZcfxfjh9UA4OmHS8MATFQ0ZvQYjIG7TlvAlyZ+DoCtKMX6fS5XJyIiIn1Rl0LLMcccwyOPPMKrr77KP/7xD6qrqznuuOPYunXrfp9z5513Mnjw4OAtNTX1sIsW6UucosDMijEwoT2wAJh+uDSsQ8dhmRflreDY1MrAYFsrdt1aF6sSERGRvqpLoeWMM87gggsuYNKkSZxyyiksXLgQgIcffni/z7n55pupra0N3qqqqg6vYpE+xDoOtriAdyoymT7/BjbujAs8EBePGZXibnE9qGNfi7Xw16Un8HZ7i2erfS0iIiJyCA6r5XFsbCyTJk2ipGT/a9UjIyOJj4/vdBMZKOz6SmioZ0FhHlsaBzEith4AT3YuxvTfjuMmJQ3CIzAGHvj0WB5bETivRftaRERE5FAc1k9NLS0trF69mpEjR3ZXPSL9ii3Mx1pYUJjH2Tmr8HgCZ5WY8f1zP0sHExaGSQvMrpycWcyi0mysBbtuLbal2eXqREREpK/pUmi58cYbWbJkCeXl5Xz44YdceOGF1NXVceWVV/ZUfSJ9mlO0is83jaR8x9BdXcMiIjHp49wtrBfsan1cQlXdEEq2JoF1sBVrXK5MRERE+pouhZZ169Zx6aWXkpOTw/nnn09ERARLly4lLS2tp+oT6bPslhrYupmXiicyOLKJWemlAJhx4zFhYS5X1/M8mYHN+CemlRHm8e9qfVymJWIiIiLSNV36yenJJ5/sqTpE+p2OrmE3Hv8W54xfRUSYH+ifB0ru0/BkiB1EHPX84qRXyR1eDYBTVoLX5dJERESkb+n/v+4VcYktygcg3OuQO3xTYNB4MFkTXKyq9xjjwWRkYVd9xk9mLtr1wJZN2LpaTPxg94oTERGRPqX/ti8ScZGt34mtqmT+R8fzpce/hg3sv8ekZ2KiY9wtrhd1LBFr9Xl5cuURrNk6FFAXMREREekahRaRHmCLCwDLM/mTcazBmMC4yenfXcP21LEZ3xjL9S9cyH/zpwLg6LwWERER6QKFFpEe4BStYktDLO+uzdzVNYwBtJ+lnRk8BBKTCPc6zEwv5c2ywMyLLSvBdkw/iYiIiByAQotIN7OtLdiyYhYWT8RaOCsnsLeFEaMwCYnuFucCT/tsyylji3m/KoPG1nCor4Mtm1yuTERERPoKhRaRbmbLisHn44WiXGakVjJiUD0w8GZZOpj2fS1zMotp9Yfx3toMINBFTERERORgqHuYSDdz2ruG/fPcJ6mujw+Oe8YPrP0sHUz6ODCG8Uk1XDppGdHhbUB7uDvmRJerExERkb5AoUWkG1nHH2x1nBDdTEJ0c+CB+ARIHu1eYS4y0TGYUamwfi0PX/B4cNxWlGL9foxXp7aIiIjIF9PyMJFuZKsqoKmRG14+l1vfnBsc9+TkYjpaiA1AJmNX6+M3y7LY3hQNrS3Y9WtdrkxERET6AoUWkW5kC/Np83v494rpncbNAF0a1qGj9fGWxljmPvJNXi/NAdqXiImIiIgcgEKLSDex1uIUreLdyky2N8dwbker48goTNpYd4tzmUlNg7BwRsXXMWFY9a7WxzpkUkRERA6CQotId9m8CbZv5X+Fk0iN384RI9cBYLImDPh9GyYsHJMW6Bp2cmYxi0qzsRbsukpsS7PL1YmIiEioU2gR6SZO0SqshRcKczln/Co6trAM1FbHezIZgSViczJLqKxNpGz7UHAcbGWZy5WJiIhIqFP3MJFuYovyMQbeuPpveEz7ae8eLyZrgruFhQhPZhYOMDOtlKNHV7KtMYaxiVuxZSWQPdHt8kRERCSEKbSIdAO7szbYCStjyLbguMkYi4mMcqus0JI8CqJjiKeRd6+7JzjslBczsBfPiYiIyIFoeZhIN3CKCgA47/Gv8dTKqcFxkzOwu4btzhgPJrN9A76FlZuS8TsGaqqxO+tcrk5ERERCmUKLSDewRaso2ZrES8W5RIb5guPaz9KZp7318QdV6Rw5/yZWVAcO3FQXMREREfkiCi0ih8m2NGPLS3ihMI+osDZOHRs4e8SMTMHEJ7hbXIjpOK/lqNFrGRTRzKL21seOzmsRERGRL6DQInKYbGkR+P38rzCPU8YWERvRCmhp2L6YhEQYMpRwr8PMtDLeLAuEGFtWgrXW5epEREQkVCm0iBwmpyifTfWDWFqVtutAScAzXkvD9qVjidiczGLercygqS0MdtbC1hqXKxMREZFQpdAichis348tLmBYTAPvXnsP545fGXggIRGGj3S3uBDVsRl/TmYJIwbtpGJHIgBOmfa1iIiIyL6p5bHIYbBry6G5CY8HjkqpCo57cnIxHadLSicmfRxgyB1eTckPfhM8hNOWFcPRJ7ham4iIiIQmzbSIHAZbtIq65kjmPPhtlq1PCY5rP8v+mZhYzMjRGAPGwNbGGABsRSnW8btcnYiIiIQihRaRQ2StxSnK59U143l37ViGxjQEHoiKxqRluFtciOtYIvZswSRG/+6XbGmIhZZm7IZ1LlcmIiIioUihReRQ1WyEHdtYUJjHlOT1pA/ZDoDJnojx6Iz3L7Kr9XEVjvWwuGIsALZUrY9FRERkbwotIofIKVxFq8/LyyUTOGf3rmFaGnZAZkwGhIWROngH2UNrdrU+LldoERERkb0ptIgcIqcon8UV46hrid7VNcwbhhmX425hfYAJCw8EF+DkzGLebD9k0lZVYltb3CxNREREQpBCi8ghsLXbYeM6Tkwr5YXL72fSiI1AYK+GiYh0ubq+wWR0nNdSwuaGQdTUDwLHj60sc7kyERERCTUKLSKHwCnKByA63MfpWUXBtr2eHB0oebA87Zvxz8wuoPr/bmH4oHoArM5rERERkT0otIgcAluUzyfrUzn/iavZ3BAbHDfZCi0HLXk0RMcQ7nUI9zr4/IH/HTna1yIiIiJ7UGgR6SLb3IStKOXZgsksrUonMboRADN6DCYu3uXq+g7j8WAyxgHw0KdHk/Wnn+E4BjZtxNbvdLk6ERERCSUKLSJdZNcUguNnQWEeZ+Xk4/VYQAdKHoqOfS1jE7ewfmcCKzaNAsCWa4mYiIiI7KLQItJFTtEqCjcPp3jr8M6tjsdraVhXdexrOTalkpjwlmAXMUf7WkRERGQ3Ci0iXWD9PmxJIQsK84gNb+HkzPb9F4lJkDTC3eL6oiFDISGRiDA/M9PKdp3XUlaMtdbl4kRERCRUKLSIdIGtKIWWZq6e9iH/veQhosN9QKBrmOloISYHzRiDyexofVzMB1VptPk9ULcDtm1xtzgREREJGQotIl1g21sdD4tt4OSxu5YwaT/LoetYInbVER9R9sPbCfc6ADhl6iImIiIiAQotIgfJWotTlM+/V0zjuy+eT3D1UkwsJjXdzdL6tI4OYgnRzSRENwfHdV6LiIiIdFBoETlY1euhbgf/XjGdkq3DggdKmuyJGI/+Kh0qEzMocGYLcO+HJ3DOY9cCgQ5i1nHcLE1ERERChH7SEjlITuEqdjRFsbhiHOdO2K1rWI66hh2ujiViseGtvLomh+1N0dDSjN24zuXKREREJBQotIgcJKcon5dLJuBzvJyVE9jbQlhYcCO5HLrdN+NbPCwuDywZs9rXIiIiIii0iBwUu2MbbNrAgsI8jhy1ltTBO4DAD9smItLd4voBMyYDvF7GJOxgXOLm4Hkt2tciIiIiAGFuFyDSFzjtXcNunf0q25tiguMedQ3rFiY8ApOaga1Yw8mZxSzqOK+lqhzb1ooJj3C5QhEREXGTQovIQbCFgT0s44fV7DZqMDkT3SmoHzKZWdiKNdxw/GJ+eNziwKDfj60sw4wb72ptIiIi4i4tDxM5ANvUiK0s444lpzD/o+OD4yY1DRMb52Jl/UvHvpaMIdvITNwWHNcSMREREVFoETkAW7Iav9/yt49OoHLHkOC4DpTsXmZkCkRFA3DPByfy09fnAeCUazO+iIjIQKfQInIATtEqPlyXRk1DHOdNWBkc94xXaOlOxuMJHjS5uXEQD392FI5joHoDtqHe5epERETETQotIl/A+nzYNUX8b/UkkgfVcfTotYEHkoZjhg5zt7h+yGQEloidnFnM5sY4VtUkA4GDJkVERGTgUmgR+QK2vATb0sKCwjzOzlmFx2MBHSjZUzoOmTw2pZLosNZgFzFH+1pEREQGNIUWkS9g21sd33fuU3z7mHeD49rP0kMSk2DwEKLCfZyQVr7beS3FWGtdLk5ERETcopbHIvthrYNTlI8xMDO9bNcDsXGYlDHuFdaPGWMwGVnY5R9xy0mvEu7xBx6o3Q7btwZCjYiIiAw4mmkR2Q+7YR3U1/GdFy/gtTU5wXGTPRFj9FenpwSXiKVWcuTodcFxLRETEREZuPSTl8h+2MJVrN2RwP2fHMeO5ujguLqG9SyTkRX8870fnsDDnx0FBJaIiYiIyMCk0CKyH05RPgsK8wj3+Jg7bnVgMDyi0w/V0v3MoDgYMRKA99Zm8I9PZgDtTREcx83SRERExCUKLSL7YLdtgc3VLCjMY05mCfFRLQCYsTmY8HCXq+v/PJm7Wh9/siGVHU1R0NyErV7vcmUiIiLiBoUWkX1wivLZ2hjDO5WZnDN+VXBcrY57h2kPLXMyS3CshyUVgUMntURMRERkYFJoEdkHW7SKmPBWHr3wMc7tCC3GYLInuFvYAGHGZIDHS8aQbYwdsmW31sfajC8iIjIQqeWxyB5sYz12bTnR4ZYLcz8PjpsxGZiYQS5WNnCYiEhMajq2spRfnvwyI2J3AmDXlmPb2rRET0REZIDRTIvIHmzxahpbwrjq2UtZvXl4cFwHSvYu0976+OK85czKKA0M+n3YqnIXqxIRERE3KLSI7MEpyueNsmwe/3w6YZ5d3aq0n6V3dexrAXhw2TEsKR8LaF+LiIjIQKTQIrIb29aGLS1iQWEeE4ZVkzV0S+CB4ckYncbeq8yoFIiMAuAfy47lwU+PAbSvRUREZCBSaBHZjS0rxtfsY2FR7h5dw7Q0rLcZjxeTHphdmZNZwptlWVgLduN6bGODy9WJiIhIb1JoEdmNU7SK96vS2doUu6trGGC0NMwVJnheSwmbGuLJr0kGLLZ8jbuFiYiISK9SaBFpZx0HW1zA+KQa/nbWf5g2cl3ggbj4wFIl6XUdh0wel1pOVFjbbq2Pta9FRERkIFFoEWln11dCQz3DB9Vz7fSleDwWAE92Lsbor4orhg6D+MFEhfu4eebrTBi2CQCnXPtaREREBhL9JCbSzhbms2pTMje8fC7bm6KD42a89rO4xRgTXCJ288xFnDqufYZl+1bs9q0uViYiIiK9SaFFpJ1TtIpnCqbw6PKjGBTREhiMiMSkj3O3sAHOkxFYEubze3h+dR7FWwJd3NRFTEREZOBQaBEB7JYa2LqZBYV5nJldQLg3cD6LGTceExbmcnUDW8chk8ZYvrngYp5YeSQATrn2tYiIiAwUCi0iBGZZyrYlsnLTqD1aHatrmNvMoHgYnozXYzkpY81um/FLsNY5wLNFRESkP1BoEQFsUT4LCvOI9LZx+rjCwKDxYLImuFuYAODJ6Gh9XMxH68ZQ1xwJTY1QvcHlykRERKQ3KLTIgGfrd2KrKjk9q5D55/yHQZGtAJj0TEx0jMvVCexaIjYnswS/9fJ2ZeDQSUf7WkRERAYEhRYZ8GxxAWCZMKyGr0xZFhw3OeoaFipMWiZ4PGQO2colkz4lKswH6LwWERGRgUKhRQY8p2gVC4sm8P/emYO1u8a1nyV0mMgoTEo6xsAjF/ybU8YGwopdW4b1tblcnYiIiPQ0hRYZ0GxrC7asmH8sm8ErJeMxpv2BEaMwCYmu1iaddSwR8/k9vL82nW2N0eDzYasq3C1MREREepxCiwxotqyY+gYPi0qz1TUsxHWElh3N0Zz04Hd5qWQioPNaREREBgKFFhnQnKJ8XivNocUf3jm0jNd+llBjRo2BiEiSYhuYmryORaWBjmLa1yIiItL/KbTIgGUdP7Yon/+tnsSkERvITNwWeCA+AZJHu1qb7M14vZj0QNewOZklvFmWhbVgN6zDNjW6XJ2IiIj0JIUWGbBsVQU0NXL1tA/55ZyXg+OenFxMcHOLhBKTueu8lo31g1m9eQRgsRVr3C1MREREelSY2wWIuMUW5gNwUkZpp3GjpWEhy5OZhQMcP6acI0ZWsbUxFmjf1zJhsrvFiYiISI9RaJEByVqLU7SKf3xyLInRjVyQ+3nggcgoTNpYd4uT/UsaAYPiiamv48Nv/Ck47JQV43WvKhEREelhWh4mA9PmTThbt3HHklN5f21GcNhkTcB49eNvqDLGBLuIWQslW5No83tg2xbsjm0uVyciIiI95bBCy5133okxhh/84AfdVI5I73CKVvHpxhTW70xQq+M+xtO+r+WzjSnk/uVmPl4/BlDrYxERkf7skEPLxx9/zP3338/kyVpHLn2PLcrnf4V5JEY3cPyY8sCgx4vJmuBuYXJAHTMtU5LXkxDVyKKyQIhxytX6WEREpL86pNBSX1/P5Zdfzj/+8Q+GDBnS3TWJ9Ci7sxa7fi3/W53HvOwCwrwOACZjLCYyyuXq5EBM3GAYNgKvx3JSxhreLGtfLla2Bmsdl6sTERGRnnBIoeX6669n3rx5nHLKKQe8tqWlhbq6uk43ETc5RQU4juHGE97i69PfD46bHHUN6ys8GbtaH3+4Lo2dLZHQWA+bql2uTERERHpCl0PLk08+yaeffsqdd955UNffeeedDB48OHhLTU3tcpEi3ckWrcLjsVwx9ROOSV0bHNd+lr6jY4nYnMwShkY3sGZbEhDoIiYiIiL9T5dCS1VVFd///vd57LHHiIo6uGU0N998M7W1tcFbVVXVIRUq0h1sSzO2vIQ7lpzCx+t2BWgzMgUTn+BeYdIlJn0sGA/jErew9sZfcsTI9QDYcm3GFxER6Y+6FFqWLVtGTU0NRx55JGFhYYSFhbFkyRLuuecewsLC8Pv9ez0nMjKS+Pj4TjcRt9jSIjbuiOG2t86gcMvw4LiWhvUtJjIKkzIGY8AYqG0O/BLFVpZhfT6XqxMREZHu1qXQcvLJJ7Ny5UqWL18evE2fPp3LL7+c5cuX49X5FhLinKJ8XizKxWv8nJm9OjjuGa+lYX2NyQgsEXulZDwj7rqd6p1x0NaKXVfpcmUiIiLS3boUWuLi4sjLy+t0i42NZejQoeTl6TfVEtqs38+6j6v4/XuzmZVeytCYxsADCYkwfKS7xUmXmfbzWqaNXIdjPbxZ3tFFTPtaRERE+pvDOlxSpC+xa8u5+cVTafN7mX/Of4LjnpxcjDEuViaHwqSkQUQkwwfVM3nE+t1aHyu07I/dsgmncCW2drvbpYiIiHRJ2OG+wOLFi7uhDJGeZWu343/5Wf4yr5btTdGkD9n1Q5v2s/RNxuvFpGViS1ZzcmYJ/8mfirXAhipscxMmKtrtEkNG4Pv/OWxRfmAgLAzvuZfgyTvC3cJEREQOkmZapN/buLKa04/eSmmRj8FRzZ0CC1HRmLQM94qTw9KxRGxOZjFbGmNZXzcYrMVWrHG5stBgHQf/h+/g+9vvsEX5tPi85NeMAJ8P/8JnsC3NbpcoIiJyUBRapF/b+FEZs0/2ULAxKfBb+D14Jk3DeNRAoq/y7HZeS83//ZyUwbUA2DK1PrabNuB/8C84rzwPrS28V5nBUX+/gWl/u5HiLUnQ3IQtLXK7TBERkYNy2MvDRELVxsUrOfniYexsjuT1q/7GuKFbO18weAieOWe4U5x0j2HJEBtHeMNOwr0OjmPweCxOWTEDNYratjacJa/hfLAYHIemtjBufOVc/rHsOI4eXcmJaWXsaI4BAt30PBOnuFuwiIjIQVBokX7HWovvvSXMu2wsO5qief2qv5E1dEvni0aMJOyy67TvoY8zxmAys7ArP+XJlUfwk9fOZs0Pfk3Y1s3Y2u2YwUPcLrFXOWXF+F/8L2zfFdAjvX7W1SXw5zOf5evT38fr2TXlaEtWYx2/ZhtFRCTkKbRIv2Ktg/PqC/Dh29x+cg5pCdvITuocWEz6OLxfvkqBpZ/wZGbhX/kpGQlb2bBzMMs2pHBM6lpseQlm6tFul9crbGM9/tdewK74BICq2gR+8NKX+P6MJcxML+P5yx6go0Ge4xiWbUghO2kzg2nEVlVi0jJdrF5EROTAtKdF+g3ra6P6wf/wm9+F4ziG08YVkZO0udM1Ju8IvJdrhqU/6Thk8shR64iPbGJRWWBzvjMA9rVYa3FWfILvr3dhV3yC3zH8dekJTLn3Jj5Zn0qLL/B7KWOAmFgANjUM4vh//oAXigIHqtrifLfKFxEROWgKLdIv2OYmNs1/lNN/diL3fngiG3bG73WN57iT8J5/GSZME4z9iRk8BIYOI8zrMCu9NBhabFkJdl/dF/oJu20L/sfuw//8E9DUSPn2RE785/e44ZUvcfnkZXz+nf/HqeOKwePBc+IphH3vpxAZxci4nRw1upKFRROBwL4WERGRUKef3qTPs7Xb2XTfY5z+h/Op3hnHa1fND3aRCjB4Tj8H77EzXatRepYnMxtn62ZOzizmx6+dQ1NbGNENO6GmGkaMdLu8bmX9fpwPluAseRV8PqwNzKQMjW5gSHQTi7/2F44bUwEEDuD0nn0RZnjgc2DG5WDzVzAvu4DfvzebFp+XyK2bsVs3Y4YOc/GjEhER+WKaaZE+zW7ayNa/3s8Zf/wSG3YO5tUr/07u8E27LvB68V74VQWWfq7jvJbLJi+j7Ie3Ex3uAwIb0/sTZ/1afP/4I86iheDz8UZpNkf9/QaqahOIj2ph4VfvDwSWiEg8Z3wJ79XfCQYWAE92YEnYWTn57GyN4u2KsYHX1WyLiIiEOM20SJ/lVKzB/+RDxLa0cmxqJddNf4K8EdW7LoiMwnvJ1/Ckj3WvSOkVJn0sGENCdOfDEm15CcyY5VJV3ce2NOO8+QrOR+8Cli0Nsdz06jn8+/PpzExbg8/Z9fsnMz4P7xlfwsQn7PU6JmsCGA+TRmzkpPQS6lsjA69fnA/HndQ7H4yIiMghUGiRPsnJX87Wx5+luGY4R6es5Z55z3a+IH4wYZdf1+m3zNJ/mahozOgx2HWVPPTp0TxXMJkFX/kntqIU6/dhvH33f3VOUT7+l56BusCSx9fW5HDlM5fjWMP95zzFlUd8FNhoHxeP94zz8UyYtN/XMtExmDEZUFnKa1f9PThu11ZgGxsw7Zv1RUREQk3f/ZdcBiz/0rfZ9vyrnPHoN9jcMIiC7/6WiDD/rguGJwcCyz5+0yz9l8nIwq6rJDLMxytrJrCpfhAjBtVj163tky197c46/K88jy1YAYDfMXg9ljGDtzM3azV3nfYCwwfVAwbP9Bl4Tj7zoLrimeyJ2MpSAMq3JxIT3hr4PK0pxEw+sic/JBERkUOmPS3SZ1jr4H9tAdv/9ypnPvoNyrYl8d9LHuoUWEz6WMKu/o4CywDUsa9lTkag1fFb5YFWyLaP7Wux1sFZ9gG+e+/CFqygze/hd+/O5pj7fkhzWxjjh9Xw0PlPBALLsGS8X7se77wLDrqNtycnsK+lze9h+vwf8cCyYwHtaxERkdCm0CJ9gvX58D/7b7a/9SHzHv06pduSeOWKvzN15IbgNSZ3Ct7Lv64zWAYok5IG4REkx+0kd/hG3ixrDy3lfee8Frt5E/5//S1wqn1LMx+vS+XY+3/ILYvO5OTMEhzbfkKkNwzP7DMI+8YP8aRmdOk9zNBhkDSccK/DaeMKebHjvJY1hVi/r7s/JBERkW6h5WES8mxzE/6n/oWtWEN1/TBqW6J4+Yr7OGLU+uA1nmNn4jntbIxRDh+oTFgYJi0Tu6aQkzOLea5gMtYC69ZiW5oxkVFul7hf1ufDeXcRzjuLwAnMHN759snc9uZcpo5czwfX/Sn4/W7Sx+I966LDalHsyZ6Is6WGeTkFfO25y9hQF8+o+DpsRSlmbE63fEwiIiLdSaFFQpqtq8X373+ws2obHhNBTtJmln/7d3g9uw4N9Jx2Dt5+0CFKDp/JyMKuKeTbR7/L16Z9GBi0DrZiDSYnz93i9sOpLMX/wn9g62YAmtvCiAr3MXnEBu467QW+c8y7hHkdiIrGe9o5mKlHYYw5rPc0Obnw/mLOyFqNxzi8XDKBa478EFtcAAotIiISghRaJGTZmupAYNncxNmPXcfQmAaeufShXYHF68V73qV48o5wt1AJGZ7MbBwgM3Fbp3FbVgIhFlpsUyP+NxZiP10KwMadcfzw5S/R4gvj2UsfZF7OamA1AGbSEXhPPxcTG9ct721S0iE6hqE0Bs5saQm0PnaK8vHMPe+wQ5GIiEh3U2iRkORUluF/8kHqa/2c8+/rWFWTzEtfvX/XBZFReL98NZ6Mce4VKaFnRDLEDoKGev7xybGUbkvit6e9iFNWgtft2tpZa7EFK/C//Dw07MRxDA98egw/ff0sIsN8/H7u87suTkjEO+8CPOPGd2sNxuMJdBFb8Qn/veRfux6o3Q411TBCrcJFRCS0KLRIyHEKVuB/9nHqGz2c8+9r+bx6FC999T6OTlkbuCCu/QwW/WAlezDGE1gituozquvjeWDZsfzmlIV4t2zC1tVi4ge7Wp+t3Y5/4TPYksAMirUw77Gvs6gsm6uP+JA7T32BxJgmMAbPsbPwnHQaJiKyR2rxZOfiX/EJALXNUdS3RjA6vg6nKB+v/m6JiEiI0a5lCSn+D9/B/59Hwe/judWTWF49moVfvZ9jUtsDy7ARhF3zXQUW2S9PZqBr2MmZxdS2RPPphhTA3S5i1nHwL30b373/D1uymhafl+a2MIyBC3OX8/qVf+O+c58OBJaRKYRd9wO8p53dY4EFwIzNBm9g/mnWA9/h9sWnB2otVutjEREJPZppkZBgrYPzxkKc9xfjOAaPB746dRmzM9aQMjhwErgZk4n3kqsx0TEuVyuhrOO8lqNGryUuoplFZdkclVKFU1aMZ8r0Xq/HVq/H/8J/sBuqAHinIpNvvXARX5r4Obef/DLXHNneMCA8As/suXiOOQHj6fnFbCYyCpM+DltaxNysQv694sjA3731a7H1dZhB8T1eg4iIyMHSTIu4zvp9+J97Auf9xTS2hjPvsa/zyGdHAewKLBMn4/3q1xVY5IDM4CGQmES412Fmeumu81rKSrDWHuDZ3ce2teJ//UV89/8Ju6GK7U3RfHPBRZz8r+sZGtPAJZM+3VXzuPGEffsmvDNm9UpgCb5v9kQA5mUXsKkhnmUds1LFBb1Wg4iIyMHQTIu4yrY0B85gKS+hsTWc85/4Gh+uS+Nns14LXuM5+kQ8c8/RGSxy0DyZ2TjbtvB/Jy7C57R/39TXwZZNMCy5x9/fKS0KHBC5I9DFbFP9IKbP/xFNvnD+Ou+/XHvkUjweC7GD8M49D5M71ZWOXZ6cXJyXn2NGagWJ0Q28UJQbmJUqLsAz7dher0dERGR/FFrENXZnLb5//xM2baCpLYwLnvwaS9elseDyf3JCWjkAnlPPwjPjJLVglS4xmVnwyfscm1rZadwpK8Hbg6HFNtTjf20B9vNlAFTvjGPEoJ2MGFTPjSe8xUW5yxkVXxeo8Yij8Z56tquzh2bwEBgxirBNGzh3/Cq2NwVqsaXF2LZWTHiEa7WJiIjsTqFFXGE3b8L3738EWqwCP339LD6oSuN/lz3AzPQy8HjxnncJnknTXK5U+iKTPg4wgOWhT4/GAFdN+whbVgzHnNjt72etxa74BP9rC6CpEb9juPfDE7j1zTP453lPckHu53x/xtuBi4cOw3vWhXjSQ6NdtycnF2fTBv5+ztMEfzfga8OWlQQOoRQREQkBCi3S65y15fifeACam4JjP5v1OhfnLWfGmAqIiMT75avwtG+oFukqEx2DGZWC3VDFO5WZrNo0MhBaKkqxfj/G2337Ruy2Lfhf/A+2fA0An20czbcWXMRnG0fz7aPf49SxRYELPV48J8zBc+LJmLDwbnv/w2VycuHt1zEG2vweNjcMYlR8XWCJmEKLiIiECIUW6VXO6pX4n30MfD5afF5ufOVc/u/ERaQMriUptgEGxQfOYEke5Xap0seZzGzshirmZJbw2Iqj2NIQSxIN2PVrMWMyDvv1rd8f6Hb39mvg8wHwZlkW8x69jgnDNvHOtX8Jni1kUtPxnnURZnjP76fpKjNyNAyKh/o6Lv3PFTS2RvDSFfdji/Ox9gLtJRMRkZCgf42k1/g/ehf/0w8HA8uXn7qKh5cfTem2pMAFSe1nsCiwSDfoaH08JyNwPstb5YHlWLas+LBf21lXie/+P+C8+RL4fJRuGwrACWPK+NOZz/HhN/4YCCyRUXjmXYD36utDMrBA4EBOT3sXsTkZJSypGEttcxTU78RuWOdydSIiIgEKLdLjrLX4F72E8/JzgA0ElqevZFFZFs9e+iCzMkoxqemEfe07mIREt8uVfsKkpkFYOKPi65gwrHpX6+PDOGTStjTjf+lZ/A/8BWqqqakfxJXPXMakv/4fxVuSiAjz842jPiDc62AmTCbs+h/jnX5cyM9WdOxdmZdTQJsTxmtrcgCwRTpoUkREQoOWh0mPsn5f4GC9FZ8E7lv46jNfYVFpNs9c+hCnjC3GTJiE90uXY8JDZ52/9H0mLByTloEtLeZns15ncGRgD5VdV4ltacZERnXp9ZzCVfhfehZ21mItPLr8KH782tkA/P2cp8kauiVwYdxgvGeej2d8Xrd+PD3JZGRBWDhpCduZPGI9C4snclHeCpzifLxzznC7PBEREYUW6Tm2pRn/fx7Glu5ajmMMXDLpU66ZtpTTxhXhOep4PHPPw3hC+zfR0jeZjGxsaTEX5y3fNeg42Mqy4MGKB2J31uJ/+Tns6pXBsd++czK3vnkml03+hN+dvoBhsQ2AwXP08XjmnNHlQOQ2Ex6OGZuNLcrnrJx83l/bvudn00bsjm2aARUREdcptEiPsPV1gTNYqtcDga5ET6ycxlenfML5EwM//HlOnofn+Nk6g0V6jCczC6f9z49/Po2Rg+qYnbkGW1YCBwgt1jo4nyzFWbQQWppp9Xkp3jqMvBHVXH3ER0wfVcWp49oD+fCReM++CE9KWs9+QD3Ik52LvyifW056Da/HBsed4gK8R5/gYmUiIiIKLdID7JaawBks7aeBt/k9XP7fr7KwaCLTRq4jb2QN3nO+jGfKdJcrlX4veRREx0BTI/d9fBwj4wKhxSkv5ouaHtua6kAb46oKAJZWpfGtFy5ie1MMxd//DclxO0mO2wlhYXhmnRY4ALUb2yi7ITDzZPB6LNbC1sZYkmIbsMX5oNAiIiIu05oc6VZOVQW+B//SKbB85b9fYWHRRJ768sPkpW7He9m1CizSK4zxYDIDG/DnZJawuHwcfsdATTV2Z91e11tfG/43X8Z33x+wVRXUNkfxvYXnM+uB7xAV1sbzl/2TiDB/4LUzsgj71k14Tzi5zwcWADMoDjM6FYCfvTGPmQ98FwBbXoptaXazNBEREYUW6T5O4Sr8j8yHpkYAfH4PVzxzOS8W5fLkxY9w1pFVhF31bTxjc1yuVAYST0ag9fHJmcVsa4plRfVoYO8uYk7FGnx//z3OO2+AEwgmX/nvV3h0+XTunruAd6+9h6kjN0B0DN7zLsX71W9gEpN694PpYR1dxI4bU86abcMo2jIMHD92TZHLlYmIyECn5WHSLfyffIDz0jOB9mDtHGuwGB6/6FHOPr6GsK98Txt6pdeZsYHQcvTotcSGt/BGaTbTRq3DKSvGM/lIbFMj/tdfwH72EQDr6+Kpb40kJ2kzd576IvGRzYxJ2BF4rclH4j3tHEzsILc+nB7lycnFefNl5mSUEB3WysKiXHKSFuMU5+PJneJ2eSIiMoAptMhhsdbivPVK4LfT7Xx+D2XbE8lO2sKTFz+CSUnDe+l3MTGxLlYqA5VJSIQhQ4nYvpWbTniTCcM2AWDLSnBWfYb/leehoR7HMdz/yQx+9sY8Tkwr4/nLHyBvRHXgRRIS8Z51Yf+fJRyWDAmJxOzYxpzMEl4smsgNxy/GlqzGOn6Mp+8vgxMRkb5Jy8PkkFm/H/+CpzoFFr9j+Nrzl3LSg9+lrjkSk5OL94pvKbCIqzyZgdmWn856g7PHtx+YuLMW/zOPQUM9qzYlc9KD3+F7L13Alyd9xkPnPx64xnjwHDebsG/f1P8DC2CMwZMdWCJ2dk4+lTsSaW4Lg6ZGbFWly9WJiMhAppkWOSS2tQX/0w9jS3etdfc7hmuev4T/rJrCYxc+RsIJR+I540s6g0VcZzKzYNkHOI7h9dJs0odsIydpMwDNbWHMfeSbDIlu5M2r/8oJaeWB54xKxXv2RZjk0W6W3utMzkT46B2+OvVjrjriIzzt7Y9tUT6kZbpcnYiIDFQKLdJltn4n/sf/id24LjjmdwzXPn8JT608gkcu+DcXfXc0nhNO1hksEhJM+jjAYIzl2ucv4atTP+H0cYXkjdjI0JhGXrj8H0wcXk1kmB/CI/DMOQPP0ScMyMBt0jIhMorw9o5hO1siiYtswSnOx3va2S5XJyIiA9XA+xdZDovduhnfA/d0CiwAFTsSeXXNeP514RNc8rMJeE88RYFFQoaJicWMHI0xgdbH8z86nlMf/jb/+GQGAEeMWk9kmB+TNYGw63+M99iZAzKwABhvGGbceAAe+vRoMv9wCy0+L2zdjN1S43J1IiIyUA3Mf5XlkDjrKjudwQLgOIYWn5exiVsp/NHdXHbHdDxTj3KxSpF96ziv5aK85cRGtDL/7Kf58QlvBh6MjcN74RV4L70GM3iIi1WGBk/2RACOHFVFbUs0b1eMBcApznezLBERGcC0PEwOilNcgP8/j4CvbdeYY/jmCxexuWEQz177NImXX4MZlepilSL755l6FM77izkrp4B1N922a3zasXhOmYeJjnGvuBBjsiaA8TBpxEbSBm/jxaJcTh1XjC0ugONmu12eiIgMQJppkQNyli3F/+SDewWWb794IQ9/dhQXHF1G+LXfU2CRkGaSRuA971KIig7cT0nDe9X1gc32CiydmOgYzJgMjIGzcvJZWDwRa8GuLcc2NrhdnoiIDECaaZH9stbiLH4V5+3XO407juH6Fy/goU+P5p9Xv8FVf52Niemfh+1J/+KZfCRm0jRobcFERrldTkgzObnYylLm5RTw0GdHs7Z2CGkJ27FrCjGTj3S7PBERGWA00yL7ZB0//hee3iuwACwoyuXBT4/hH994l6vvO0mBRfoUY4wCy0Ho2NdyUvoaqn/8C9IStgPgFGlfi4iI9D7NtMhebGsL/v8+ii1Zvc/Hzx2/ivd//ybH/GC2TsgW6afM0GGQNJywLTWEeR1afF4iw/zYNYVYvw/j1T8fIiLSezTTIp3Yhp34H56/V2CxFn708rk8vWoq3tlzOeaHJyuwiPRznuxcABaXj2XEXbezoS4eWluwFaUuVyYiIgONQosE2W1b8D3wF+yGqs7jFm54+Tz+8uFMGiYcj3fWqTqDRWQAMDmBJWKTRmyk2RfOS8WB+1ZLxEREpJcptAgAzvq1+B74C2zf2mncWrjxlXO596MTmf+rjXz9V5kuVSgivc2kpEN0DENjGjl+TDkvtocWp7gAa627xYmIyICi0CI4JavxPzwfGuv3euzu92bzlw9ncu+d2/jmLSNdqE5E3GI8Hkz7hvx52QW8WZZNQ2sE1G6Hmo0uVyciIgOJQssA53z2If4nHoS21n0+fvmsch6Zv5Nv/ySxlysTkVDQsa/lrJxVtPi8LNuQAqiLmIiI9C6FlgHKWot/yWv4FzwN1tnjMfjzBzPZPCibMT+8iq9+M86lKkXEbWZsNni9ZCdtYcOPb2VmehkAtrjA5cpERGQgUWgZgKzjx//if3EWv7r3YxZ++sY8bnr1XF4f8jVMrAKLyEBmIqMw6eMAGBrTiOMYrAW7fi12Z53L1YmIyECh0DLA2NYW/E/9C/vp0r0fs/DzRWfy+/fm8Ic/OFz5tXAXKhSRUGNyAkvE1mwdStrvf8HH68cAYEs02yIiIr1DoWUAsQ31+B/5+36Xddz21lx+9+7J/P73lh/+UN8aIhLgad+Mn56wnTbHywtFgRCjfS0iItJb9JPpAGEbduJ78C/Y9Wv3fYHxkH1yBnffDTfcoDNYRGQXM3gIJI8izOtwRtZqFha1n9dSVozdTxMPERGR7qTQMkD4X34etm3Z52NL1ubg+fLVXPWLcfzoR71bl4j0Dbu6iOWzqmYUFduHgM+HLStxuTIRERkIFFoGALuzDpu/Yp+P3f7ePE598Ou8XzOxl6sSkb6kY1/LqWOLCPf4WFyeBWiJmIiI9I4wtwuQnufkLwf2Pr36Nx+dw+2vz+KOO+DEE3u9LBHpQ8zI0RAXTzx1FH3/DlIG1wKBzfjWOhij34GJiEjP0b8yA4Bd9dleY3e+fTK/fGkWv/413HyzC0WJSJ9ijAdPVmBGNhhYLFC/E7thnYuViYjIQKDQ0s/Z7Vv32nzv83t4u3oSv/oV/OxnLhUmIn1OxxKxhtYIpt57I//NnwKA1RIxERHpYQot/Zyzanmn+9ZCmNdh4T+ruOUWd2oSkb7JZGRBeASxEa2EeRxe7Gh9XKzQIiIiPUuhpZ9zdlsatqMpion33Mw7lWOJmDzZxapEpC8y4eGYzMAG/LNy8nmlZAI+vwc2bcTu2OZydSIi0p8ptPRjtqYaajYG7z+3ejJl2xMZN20wJnaQi5WJSF/lyelofVzA9uYY3q9KB8DZz6G1IiIi3UGhpR9z9tiA/8Tn05idsYaUE7JdqkhE+jqTNREwTBu5jpGDanl1zXhA+1pERKRnqeVxP2Wt7RRa1tfFs6RiLPd/6RnMhLNdrExE+jIzKA6TMgbPukoWXX0v6QnbAbAVpdiWZkxklMsViohIf6SZln7KbqiC7VuD9xcW5RLh9fOlc1r1Q4WIHBaTHWh9PG7oVsK8TmDQ8WPXFLlYlYiI9GcKLf3UnmezXDf9A1Zc//8YcnSeSxWJSH/Rsa/FWjjv8a/x5w9mAuoiJiIiPUehpR+yjoOTvzx43+8YjIHM5Ib29egiIodhWDIkJGIMeIzl+dWTALAlq7GO3+XiRESkP1Jo6Yfs2nLYWRe8f+ubcznzka9jxudhwsNdrExE+gNjDJ7swGzL2Tn5fFCVzpaGWGhqxFZVuFuciIj0Swot/dDuS8Mcx/DUymmkD9mGJ+8IF6sSkf7E5ARmbc/IWo1jPbxc0tFFTK2PRUSk+ym09DPW78cpWBG8/0FVOpW1iVw6PR+TqVbHItI9TFomREaRHLeTo0ZX8lJxIMRoX4uIiPQEtTzuZ2xZMTQ1Bu8/sXIaqfHbOfHMBIzX62JlItKfGG8YZtx4bP5yHvzSE4yKa1+SunUzdksNJmm4uwWKiEi/opmWfmb3s1mshTfLsvjypM/wTp7qXlEi0i91dBHLSdpMXGRLcFyzLSIi0t0009KP2LY2bOGq4H1jYPm3f0dTVCJmzEnuFSYi/ZIZNx6MB6zDTa+cQ0SYj9+c8lJgX8txs90uT0RE+hHNtPQjtqQAWnf9trOpLYyIMD9Dpk/AePSlFpHuZaJjMGkZAPgcD09+Pg1rwVaVYxsbXK5ORET6E/0k24/svjSsrjmS1Ltv45n8yRh1DRORHmLaWx+flZNPVd0QPt80EqzFlqx2uTIREelPFFr6CdvchC3e9UPC84WTqGuJ5ujcOsyoVBcrE5H+zJMd6Bp2YloZ8ZFNvFgUCDHa1yIiIt1JoaWfsEX54PcF7z/5+TRmpq0h7cRxGGNcrExE+jMzdBgkjSAizM9p44qCocWuKcL6fAd4toiIyMHpUmiZP38+kydPJj4+nvj4eGbMmMHLL7/cU7VJF+y+NKx6Zxxvlmdx6eRPdaCkiPS4jtmW22a/zNNffjgw2NqCrSx1sSoREelPuhRaUlJS+O1vf8snn3zCJ598wpw5czj33HPJz9cyADfZhnpsaXHw/ofr0ogOa+P8WZsww5NdrExEBgLT3vo4O2kLqYN3BMdtkf5tEBGR7tGl0HL22Wdz5plnkp2dTXZ2Nr/5zW8YNGgQS5cu7an65CA4BZ+DdYL3z52winU33cbQoye6WJWIDBQmJQ1iYgGY/9HxXP/CBQA4xQVYa90sTURE+olD3tPi9/t58sknaWhoYMaMGfu9rqWlhbq6uk436V52t6VhO1siafV5iY1oxZM31b2iRGTAMB4PJmsCAM2+MB5dcRQNrRFQux02bXS5OhER6Q+6HFpWrlzJoEGDiIyM5Jvf/CbPPfccEyfu/zf6d955J4MHDw7eUlPVyao72bod2LVlwfu/f+8kJv31/7Ajx2CGDHWxMhEZSDw5u1ofN/vCWVSWBaiLmIiIdI8uh5acnByWL1/O0qVL+da3vsWVV15JQUHBfq+/+eabqa2tDd6qqqoOq2DpzFm1PPhna+HJldOYlbEG72RtwBeR3mPG5oDXS9bQLWQPrWFhRxcx7WsREZFu0OXQEhERwbhx45g+fTp33nknU6ZM4c9//vN+r4+MjAx2G+u4SffZfWnYR+vGULY9iUsnf4Ynd6p7RYnIgGMiIjEZgdmVs3LyWVg8Eccx2A1V2J1aFiwiIofnsM9psdbS0tLSHbVIF9mtm7Eb1wXvP7HySEbF1TLrJDBxCoci0rtMe+vjbxz1Pi9c/g+MCWzCt8X7n40XERE5GGFdufinP/0pZ5xxBqmpqezcuZMnn3ySxYsX88orr/RUffIFdl8aBlC2bShfzvuM8ElTXalHRAY2T/ZEnJeeJWPINhiya9wpzsdz5LHuFSYiIn1el0LLpk2b+OpXv8rGjRsZPHgwkydP5pVXXuHUU0/tqfpkP6y1nQ6UBFjwlX/is+GYib9wqSoRGcjM4CGQPAqqN/BCYS7/yZ/KIxf8G1tWjG1rxYRHuF2iiIj0UV0KLQ888EBP1SFdtWkjbNkUvFuxfQhpCdsJz8nCRMe4WJiIDGSe7Fyc6g20+r08uXIav5zzMhlDtmHLijE5eW6XJyIifdRh72kRdzirPg3+ub4lgql/u4n5Hx2PJ09dw0TEPR2tj08bV0SE18fCosA+F6dI+1pEROTQKbT0QYGlYcuD9xcU5dHYFsmZE0sw7T8wiIi4YmQKxMUTF9nCrPRSFha3tz4uLsBax+XiRESkr1Jo6YPsusrASdPtnvx8GsellpNx7EhMRKSLlYnIQGeMwZO966DJJRVjqW2Ogoad2A3rDvBsERGRfVNo6YN2P5ulpn4Qr5dmc9nkZVoaJiIhoaP18fkTV/DcpQ8QE94K6KBJERE5dAotfYx1/Dj5K4L312xLYszgHVxwRCFm3AQXKxMRCTAZWRAewYhB9ZyeVUS4N7AszFFoERGRQ6TQ0sfYilJo2Bm8f9yYCgq/fwdJ08dhwrrUDE5EpEeY8HDM2GwAlq1P4dKnv4rP74Gajdgd21yuTkRE+iKFlj5m97NZNjfEsq52MMagpWEiElI87UvELIZnCqbyflU6oNkWERE5NAotfYj1+bCrVwbv3/fxcUz92020Rg7GZIxzsTIRkc5M1kTAMG3kOkYOquXFol1dxERERLpKoaUPsaWF0NwU+LOFJ1ZO45zxq4ianIfxeF2uTkRkFzMoDpMyBo/HMi+ngBeLcrE2sMTVtv9/TERE5GAptPQhuy8NW7YhlZKtw7l00qcYLQ0TkRBk2lsfz8vOZ822YRRtGQ6OH1ta5HJlIiLS1yi09BG2tQW724nST3w+jRGxdcyeshmTmuZiZSIi++ZpP+x2TmYJD5z3OKPiagFwtERMRES6SKGlj7DFBdDWGrxvjOWqaR8RMWUKxujLKCIhaNgISEgkOtzHV6cuIz6qBQj8/8w6fpeLExGRvkQ/7fYRuy8NA7h77gJuP/lldQ0TkZBljAnOtlRsH8J1z3+ZzQ2x0NyErapwtzgREelTFFr6ANvUiC0pDN7/YG06Da0RMHQYJI92sTIRkS9m2lsfR4e38cjy6bxcEjgE16r1sYiIdIFCSx9gV6+E9qUUja3hzHvsOv70wUw8eUdgjHG5OhGR/TNpYyEyihGD6jlqdBULiwIhRue1iIhIVyi09AG7Lw17sTiX+tYovpz3mZaGiUjIM14vJms8AGfl5PN6aQ4tPi9s24LdUuNydSIi0lcotIQ4W1+HrVgTvP/E59M4JqWCcblRmKThLlYmInJwPB2tj3PyqW+NYklF4DBczbaIiMjBUmgJcU7+isBJksCWhlheXTOeSyd9qlkWEekzzLjxYDzkDa/mnjOfIXf4RqC9K6KIiMhBUGgJcXa3pWGbG2M5Ma2MC3NX4Mmb6l5RIiJdYKJjMGkZGAPfPPp9RsfXAWCryrGNDS5XJyIifYFCSwizO7Zh11UG708YVsOrV/6dEROSMIOHuFiZiEjXmPYlYrXNUdz8+jwKakaAtdiS1S5XJiIifYFCSwhzVi0P/nlDXTyLy8fiOAajpWEi0sd0nNcSHdbGPz6ZwXOrJwHgFGtfi4iIHJhCSwjbvWvYw8uP4rzHr6HRF4knd4qLVYmIdJ1JTIKkEUSE+TltXBEvFgVCjF1ThPX5XK5ORERCnUJLiLKbN8GmDYE/20DXsHPG5xM3YQwmNs7l6kREus6TEzij5aycfJZtGMOGunhobcFWlrpcmYiIhDqFlhC1+yzL8urRFG5J5rLJy9Q1TET6rI59LXPHrcZr/LxUHAgxVq2PRUTkABRaQpC1tlNoefLzaQyL2ckpWaWY8ZNcrExE5NCZlDSIiSUxpok/nfkcx6RWAOAUF2DbW7uLiIjsi0JLKNq4DrZtCd5NH7KNHxy3hPDxOZioaBcLExE5dMbjwWRNAOAbR33ApBHVgQdqt8OmjS5WJiIioU6hJQTtPssC8K2j3+OmE97S0jAR6fM6uoj5HcOf3p/Je5UZADhaIiYiIl9AoSXEWOvg5C8P3v/f6jxKtiZBeAQme6J7hYmIdAMzNge8XrweywOfHsvDy48CwKr1sYiIfAGFlhBj15ZDXS0AzW1hXPP8Jfx7xZGY8bmY8AiXqxMROTwmIhKTkQXAvOwCXiqeiOMY7IYq7M5al6sTEZFQpdASYuxuB0ouLJ5IXUs0l07+FE/eNPeKEhHpRh1dxM7OyaemIY6P16cCYItXu1mWiIiEMIWWEGL9fpyCFcH7T6ycxpGj1pKTUo8Zm+1iZSIi3ceTHdiMf2xqBUOjG3ih/aBJR0vERERkPxRaQogtL4HGBgC2N0XzSskELp30KWbiFIw3zOXqRES6hxk8BJJH4/VYfnPKQuZkrgHAlhVj21pdrk5EREKRQksI2b1rWFNbOFdO/YiL8para5iI9DsdXcS+duSHzMksCQz6fNiyYherEhGRUKXQEiJsWxt29crg/VHxddx79jOMHGkwaZkuViYi0v08u3VDfHrVVF4pGQ+o9bGIiOybQkuIsGtWQ2sLAOtqB3P/xzNoaI3AkzsF49GXSUT6mZEpEBcPwCOfHcWf3p8FBDbjW+u4WZmIiIQg/TQcInZfGvbEymnc+Oq5+B2D0dIwEemHjDF42ruIzcsp4O3KsdQ2R0HDTuz6KperExGRUKPQEgJsSzO2uCB4/4nPp3FWTj7xIwdhRo9xsTIRkZ5j2ve1zMvOx+d4eXVNYImY1RIxERHZg0JLCLCFq8DnA2DlpmRW1Yzi0kmf4smdijHG5epERHqGyRgH4RGMSdjBlOT1vBhsfVxwgGeKiMhAo9ASAjotDfv8SBKjGzh9XKG6holIv2bCwoNnUN1w3FucNq4w8EDNRuyObS5WJiIioUaHf7jMNtZ3avF5Ylop6QnbiBg5DDNipIuViYj0PE92Lv7CVVw6+bNO405RPt5jTnSpKhERCTUKLS5zClaCs6tTzhnZgd80evLOcKskEZFeY7InAAawvFuZweaGQXxp4kpscT4otIiISDstD3OZ3W1p2IPLjuGtsnEAePKmulSRiEjvMbFxmJRAw5HHPz+Sn70xD2vBVpRhm5tcrk5EREKFQouLbF0ttrIMgBafl5+8fhaLyrIwo1IxiUkuVyci0jtMe+vjs3LyWbNtGEVbhoPjx5YWuVyZiIiECoUWFzn5ywELwCslE9jRHMOlkz/V2SwiMqB42lsfz84oITqsdVcXMbU+FhGRdgotLrJ7HCg5ecR6cofXaGmYiAwsw0bAkKFEh/s4ZWxxMLTYktVYx+9ycSIiEgoUWlxit23Bbgic+lzbHMXCoomBWZb0TEzcYJerExHpPcYYPNkTAbh62oecnrUaa4HmJuzaCldrExGR0KDQ4pLdz2YxWH59yktcMulTnc0iIgOSyenY11LAzTMX0XGuri3WEjEREVFocYW1tlNoiY9q4fsz3mZ0Qj1mwmQXKxMRcYcZkwmRUQAUbh7Of1ZNAQL7Wqy1bpYmIiIhQKHFDTXVsHkTABvq4rnxlXOoqR+EGZuDiYl1uTgRkd5nvF5M1ngA/leYx9f/92Wa28Jg2xbYWuNydSIi4jaFFhfsPsvy1Koj+PvHxxPh9WlpmIgMaJ721sfzsgtoaItkScVYAJyiAjfLEhGREKDQ0sv2XBr2xOfTmJedT0KcL7imW0RkIDLjxoPxkDu8moyErSwsbu8ipn0tIiIDnkJLL7Pr18KObQAU1IxgeXVKoGtY9kRM+3puEZGByETHYNIyMQbm5eSzsGgi1oKtqsA21rtdnoiIuEihpZfteTZLQlQjZ2St1tIwERHAtLc+vih3BWePz6epLRysxZYUulyZiIi4KcztAgYS6zg4+cuD97+c9xlTk9cTGRuOyZrgXmEiIiHCk5OL89oCZoypYMaYiuC4U5SPZ8p09woTERFXaaalF9nKUqjfGbyfN6KaC3I/x4zPw4SFu1iZiEhoMIlJMGwEANU744Ktj21pEdbnc7M0ERFxkUJLL3JW7loa9vv3TuKhT48G0NIwEZHdeNqXiL1ZnsXl/72C9XXx0NqCrVjjcmUiIuIWhZZeYv0+7OrPAWjze7j73TkUbx0GMbGYjCyXqxMRCR0dnRTnjluN1/h5qTgQYmyxWh+LiAxUCi29xJYWQ3MTAK+tyWFrUyyXTvoUz8QpGK/X5epEREKHGZ0GMbEkxjRxQlo5C4sCIcYpysda63J1IiLiBoWWXuKs+jT45ydWHknu8I1MTt6I0dIwEZFOjMcT7CI2LzufRWVZNLRGQN0O2LTB3eJERMQVCi29wLa1YgsDh6PtbInkhcJcLp30KcQPxoxJd7c4EZEQ5MkOzK6clZPP2ePz2d4UDYBTpCViIiIDkVoe9wJblA9trQBEh7Xx5MUPMyV5A57cIzBGuVFEZE9mbDZ4vYwbupXHL3o0OG6L82HWqS5WJiIibtBPzL3A2e1AyTCvwxnZhYyKr1PXMBGR/TARkcEmJQ2tEfxvdR6OY7AbqrA7a12uTkREeptCSw+zzU3YNYGTnKt3xnHuv6+hZGsSJCbByBSXqxMRCV2mfYnYiupRXPTU1Xy8PhVQFzERkYFIoaWH2dUrwe8H4OlVU3mjNJuh0Q148o7AGONydSIiocuTE9iMf0xKJUkx9bzQ0UVMoUVEZMBRaOlhuy8Ne2LlNOZmFZIY06SlYSIiB2DiEyB5NF6P5Yys1bzYHlpsWTG2tcXd4kREpFcptPQgW78TW14CQPGWJJZtGMOlk5fBiFGYYSNcrk5EJPR52g+anJeTT8HmkZRtSwSfD1tW4nJlIiLSmxRaepBTsALaD0J7cuU04iKamZddoFkWEZGD1BFaTh1bzJyMYmqb21sfF+e7WZaIiPQytTzuQXa3pWHfPfYdTspYQ3S4D0/eVPeKEhHpS5JHQ9xg4qjllSvvCw7b4tVY66htvIjIAKH/2/cQW7sdW1URvD8kuomZ6WWY1HRMQqJ7hYmI9CHGGDzZgQ35Pr+HdyszqGuOhIad2PVVLlcnIiK9RaGlh+y+Af/WN+fy8zfOAMBoaZiISJeY9iViG3bGM+eh7/ByyQSg/eBeEREZEBRaekhHaGnze/jnJ8fS6g8DY/BMnOJyZSIifYvJGAfhEYxJ2MGU5PUsLO5ofazQIiIyUCi09AC7ZRNUbwBgUVk2mxvjuHTSp5iMcZhBcS5XJyLSt5iwcMzYHADOysnnlZLxtPk9UFON3b7V5epERKQ3KLT0AGfV8uCfn/h8GjlJm5g6cr26homIHKKOfS1n5+SzozmG99dmADpoUkRkoFBo6WbW2uDSsOa2MBYU5gVmWbxezITJLlcnItI3mewJgOGIkeuYnVFCQ1sEAFZLxEREBgS1PO5u1eth62YAosJ9fPzN3xMf2YLJGo+Jina5OBGRvsnExmFSxsC6Sl698u/BcVtRim1u0v9fRUT6Oc20dLPdu4YBjBu6leGD6rU0TETkMHV0EQMo3pLEpvpB4DjYNYUuViUiIr1BoaUbWesE97Nsbohl0l9/zMfrUiE8AtO+HltERA6Npz20NLeFcfR9N/Do8qMA7WsRERkIFFq6ka2qgLodAPw3fyql25LIGLINk5OLiYh0tTYRkT4vaQQMGUpUuI9TxhbzYlEgxNiS1VjH73JxIiLSkxRaupFduWtp2BOfT+O0sUUkxTZoaZiISDcwxuDJDgSVs7IL+KAqjc0NsdDchF1b4W5xIiLSo7oUWu68806OOuoo4uLiGD58OOeddx5FRUU9VVufYh0/TsHnAJRtS2TpunQumfwpREUHzxcQEZHDY3ICS23PyA4sCXu5ZAIAtkhdxERE+rMuhZYlS5Zw/fXXs3TpUl5//XV8Ph+nnXYaDQ0NPVVfn2HL10BjPQD/K5xEbHgLZ+fkYyZMwoSpSZuISHcwYzIhMooRg+o5K6eAxtZA62OnOB9rrcvViYhIT+nST9OvvPJKp/sPPfQQw4cPZ9myZcycObNbC+trdu8a9v1j32Zedj6xEa1aGiYi0o2M14vJmoBd9RnPXPrQrge2bYGtNYF9LyIi0u8c1p6W2tpaABITE7ulmL7K+tqwq1cC4DgGj8eSnbQFYuMw6eNcrk5EpH/x7NaNcUtDLOvr4gFwtERMRKTfOuTQYq3lhhtu4IQTTiAvL2+/17W0tFBXV9fp1t/YkkJoaQbgJ6+fxcVPXQmAJ3cKxqNeByIi3cmMGw/t/2+d+cB3+e3bpwBg1fpYRKTfOuSfqL/zne/w+eef88QTT3zhdXfeeSeDBw8O3lJTUw/1LUNWx9Iwv2N4auURpMTvAMBoaZiISLcz0TGBvS3AGVmrWVici7WBtvO2fW+hiIj0L4cUWr773e+yYMEC3nrrLVJSUr7w2ptvvpna2trgraqq6pAKDVW2pTn4273F5ePYWD+YSyd9CgmJmJQ0l6sTEemfTPtBk/NyClhXl8Dy6tFgbWDmW0RE+p0uhRZrLd/5znd49tlnefPNN8nIyDjgcyIjI4mPj+90609sUT742gB4/PMjGZe4memjq/DkTsUY43J1IiL9U8e+lhPTShkc2RQ8aFL7WkRE+qcuhZbrr7+exx57jMcff5y4uDiqq6uprq6mqampp+oLebsvDXuzLItLJn2KMeCZpKVhIiI9xSQmwbARhHsdzp2wkp0tkQDY0iKsz+dydSIi0t2M7UJj+/3NHDz00ENcddVVB/UadXV1DB48mNra2j4/62IbG/D9/jZwHACa2sJo9YcxOGUwYd++STMtIiI9yP/GQpz33sRa2P1/t97Lr8Mzbrx7hYmIyEE72GzQpXNadHBXZ3b1ymBgafF5iQ73ER3uw5N3kgKLiEgPMzkT4b03MSbw/+AtjbGMjq8LLNtVaBER6VfUj/cwdCwN29YYzejf/ZKXiwP/SGppmIhIzzOj0yBmEAAXPnk1337hIgCc4gL9kk1EpJ9RaDlEdmcttqIUgGcKptDQGsG0Ueswo1IDa61FRKRHGY8Hkz0BgFPGFvNmWRYNrRFQtwM2bXC3OBER6VYKLYfIyV8BBH6T98Tn0zg5s4QRg+oxuVNdrUtEZCDxZLe3Ps7Op8Ufzhul2YC6iImI9DcKLYfIti8Nq9wxhHfXjuWSyZ8CBk/eVFfrEhEZSMzYbPCGMW7oVsYnVQdbH3ecnyUiIv2DQsshsNu3YtevBeD9tekMimjm3PGrMGkZmPgEd4sTERlATEQkJmMcAGePz2dzQ2CPi91Qhd1Z62ZpIiLSjbrUPUwCOjbgA1w6+TPmZRcQF9mCydMGfBGR3mZycrFrCrl9zst4PLs24NviAsyRM1ysTEREuotmWg5BR2jZ2RKJz+8hPqoFjAfPxMkuVyYiMvB4sicG/uuxWAub6gOzLdrXIiLSfyi0dJGt2Qg11QD8ZsmpHH3fDwMHm43NxrS33hQRkd5j4hNgZAoAN7x8Hqc//E0AbFkJtrXFxcpERKS7KLR0kbNqOQB+x/DUyiM4Ia0cY8CjpWEiIq7pmG2ZmV5KweaRlG1LBL8PW1bicmUiItIdFFq6wFobXBr2TmUm63cmcNnkZRAWhhmf53J1IiIDlycn0DXs1LFFRHh9LCwO3NcSMRGR/kGhpQv+f3v3HR5Hdb59/HtmJatYxZaLLDe59yJZNu4F27hibHoJLZSQQBIIpEAgBEjyI4VACAQIHZIXQgeDu417tyy5W+5d7kWSrbY75/1jZYHBGBdJs5Luz3Xpuqzd2Z17d0aWnp3znGP37IQjhwB4d2UaLWofpGfj7ZjWHTARkR6nExGpxho0gth4YiKKuLj5xq+mPt64Fmtdj8OJiMiFUtFyDuyq4FUWa2H9wfpc2zmjZGhYirfBRESqOWNM6RCx0W3WsvNYLYoDDhzPw+7e6XE6ERG5UJry+CxZ18VdkwmAMTDrtucpDvigRgSmdQdvw4mICKZtR0hfyB1pi7irxwKMCd5us9ZA42Rvw4mIyAXRlZazZHdsgbwcAHbnxGEM1AgLYNp1woSHe5xORERM81YQXoMwn4sxcDQ/OGzX3aC+FhGRyk5Fy1k6OTTsaH4kbZ99mLcyegCaNUxEJFSYsHBMy7YAvLikL22efTg4RGz/XmxJP6KIiFROKlrOgg34cdetBOCTdV0oDjhc0jILoqIxLdp4nE5ERE5y2gaH6/ZsvJ2jBdHM39EcAHfDWi9jiYQMm38Cd2U6gaULsMfzvI4jctZUtJwFu3kD5J8A4J2VaQxusYmGcTk4HbpifD6P04mIyEmmdXvAkJq0i4axx76aRUxTH4tgjx3B/9o/CXzyDu7Ej/D/8/+wB/d5HUvkrKhoOQsn12bZdSyeOdtacH3n5QAYDQ0TEQkppmYspkkyxsDoNmuYkNURa8Fu34wtyPc6nohnrLUEPnsPDh1g25HarNibBEWFBD7/0OtoImdFRcv3sMVFpZ/QZR2sT5P4o4xrvxJi4zHJzT1OJyIi32TaBK+uXNp2DQdO1CQ7Nw5cF7tpvcfJRLxjVyzFbt3IiaJwRrz9Yy79z48oDjjYHVuw+/d6HU/ke6lo+R52wzooKgRgSMuNbLzvT8RFFuJ0TMEYvX0iIqHmZF/LJS03sOdXv6dhXHDmR80iJtWVzcslMGU8AH+cPYydx2qx73gc49d3AsBNX+hlPJGzor+6v8fJoWH782LYnxdTOu+/6ayhYSIiIaluItSuQ5jPpUZYgPzi4JJkduN6bCDgcTiRiheY/CmUDI+8I20hb135/xjYbBNbjtQBwF2xDFtc5GFCke+nouUMbEE+duM6AJ5dNIBuL/6SgGugdh1MUmOP04mIyOkYY3BKhohN2diWxL/8kQPHa0JBPnbnVo/TiVQsN2sNdk0mxQGH40U1aJFwmKs6rmTKzS/xq34zgxsVFmBLFtAWCVUqWs7Arl8NAT+ua3hvVSpj263C51icTqmYk5dcREQk5Ji2waIlNWk3hX4fkzYEh4zZLE19LNWHLSwgMOEjAJ5ZMIgeL91feuXRcSwFxWFkZjcEwE1f5FlOkbOhouUMTg4NW7CzGTuOJXB9l+CsYY6GhomIhDTTtDlERFI/Jo+ejXfwRUnR4matxlrrcTqRiuFOnwC5x9h4qC5/mDWMy9qtJircX3r/YzNHcOl/f0SR34fdtR27b4+HaUXOTEXLd7DH87BbNgLw7spuNI0/TJ8m2yAxCVOvgbfhRETkjIzPV7JmS3AWsWmb2lJQHAZHDsHB/R6nEyl/7o6tuMsW4LqGn4y/mkZxx3h00BQATLNWANyUspT9x2P57GRD/jI15EvoUtHyHdy1K8C6AASswy2pS3Eci9NRV1lERCoDp2SI2Oi2ayjwh7Fib8kwGM0iJlWc9fsJfP4+AG9mXMSc7a14YcyHRNcoxjRvje/aWyG8Bh3r76NPk628lt4LAHfVcmzJjKkioUZFy3ewJUPDAF667AN+N2gqAE6nFI8SiYjIuTCt2oHj0KHePrJ//Sg9m+wAKF17S6SqcudOL72i2Kz2YR7sP43BLTZCWDi+S6/CREaVLpB9R/eFfLm1DZsO1VFDvoQ0FS2nYY8dwe4IzjCzZFfT4JACwDROxtSu42U0ERE5SyYyCpPcAmOgVlQB/oCDtQTH7h/P8zqeSLmw+7Jx580I/tvC4BYbeWLIZACci4djEuoG/929NwBXdljBJS2zOFoQDaghX0KXipbTcEs+ZcgpiGDom3fz4tK+AKWfSoiISOVgSqY+XnegPo3+9jiZ2Y3A2tLp7EWqEuu6wWFhrsun6zox8u27yCusEbwzqTFOrwGl2zoNm0BSY6LC/Uy46WW6N9oZfI7dO7B7d3sRX+SMVLSchrs6E4BP13Wh0O/j6o6ZYAxOx66e5hIRkXPjtAnOGtYq4SCuNXyxIVjEqK9FqiJ36Xzs7h0czY/k3glXEBVeTM0aRWAcwi67BuP4Ttnel9ar9N8LdjRj0c7k4POoIV9CkIqWb7CHDkD2LgDeXdWNAc220Dj+GKZZS0xMnMfpRETkXJiEulCvAeE+l+Gt1/NFVsl6LZuysP5ij9OJlB179DDujIkA/Hb6peQVRfDc6I8wBpw+gzANGn3rMaZTKtSIAOB3M0bxuxmjADXkS2hS0fINJ9dm2ZMTx8ytrbi+c8naLBoaJiJSKZ282jK6zRoyspuw61g8FBdht232OJlI2bDWBheRLC5izrYWvJrem/+75Asaxx+DhLo4A4ed9nEmIrL075vb0xYxe1srsg7Wg6JC7KqM0z5GxCsqWr7GWltatOw/HkOfJlu5vMNKcHyY9l08TiciIufDlEx9PKL1enwmwJztLQHNIiZVh121HLtpPQDbj9bmkpZZ3JkWbKj3XXo1Jjz8Ox97siH/ivYrqRN1/Kvpj5erIV9Ci4qWr9u3p3SKwJSkPXx52wvUjsrHtGqLiYr2OJyIiJwP06gpRMdQOyqfrff/gRu6BK+guxvWYK31OJ3IhbHH8whM/rT0+5tS0vnixpdxHItJ7YnTvNUZH2+SGmMaNiEy3M9NKUt5O7MHBcVh2D07sSXD5UVCgYqWr3FLLoXuOhbP4p1NOfm7TEPDREQqL+M4mDbtAWgQm4u14LoGco5hd23zNpzIBQpMHQ/5J1ixN4lfTb6M/OIwjAFiYvFdculZPYdT0pB/R9pCftxjPkWBYMO+GvIllKhoKWGtWzrV8Svpvbn0vz+i0B8GYeGlQwtERKRyckr+Hz9WEEmn53/D25k9AHBnTvEylsgFcTetx65Mxx9w+PH4a5i2uQ0+E/zE1TfyirMeJXKyIb9N3YM8NngKcZHBJnx3dQa2sKDc8oucCxUtJeyu7XDsCNbCe6tSuaLDSiLD/Zi2HTElM2uIiEjlZFq0gYhI4iML6JyYzR9nXxIcArN1I+7mLK/jiZwzW1RI4IsPAXh+cT+W72nMvy97nxphAUy7zjgdzr4X19SIwOmSBkBuYQRPzBzG+gP1oaiwdBSKiNdUtJQ4OUvG4l3JbDlSl+u7pAMaGiYiUhWYGhE4vQcC8PjgSezOieflZcEGZHfGRKx1vYwncs7cLyfBsSNsOZzA778cyU97zqNnkx0QEYlv1OXn/HxOWvDnoYbPz0tL+/LqyYb89IXq/ZKQoKIFsG4Ad+0KAN5d2Y1GsUcZkLwFIiIxrdp5nE5ERMqC02sARMfQtu4Bbk1dwp/nDiWnIAKbvQu7dpXX8UTOmrtrO+7ieQB8ntWJ+jXzeHzwJAB8l1yKiY0/5+c0DRpiGjUlIizAzSlL+U9mD/KLw2DvbuyenWWaX+R8qGgB7NZNcDwPgCbxR/lZr7nBWTfad8aEhXmcTkREyoKJiMQZMBSARwZNpV7NPLYcqQNA4MuJ2EDAy3giZ8UG/AQ+fx8IXv24t/cclv7478REFGGSW2C69Tzv5/56Q/6Rgmg+XhscYuamqyFfvKeiha8WlAT4Zb+Z3N93FqChYSIiVY2T1hvia9MoLofMu/9GStKe4B2HD2Izl3obTuQsuPNnwv697MuL4e3M7lgLtaIKwBeGb8w1GHP+f9qZjikQEUmrOocY3HwDr6YHh4zZ1ZlqyBfPVfuixfr92HXBYQGfrevE9qO1g3fUjMF8z9zmIiJSuZiwMHwXjwj+28DGQ3X5T2awATkwewq2uMjLeCJnZA/uw50zDYAHJo/jwaljOFoQBYAzcBimTr0Lev6vN+Q/MWQSfxwyMXhHcRHuyuUX9NwiF0pFy6b1UFhAXmENbvn4Bv63Knh1xenQFeP4PE4nIiJlzXTuBvUbAPDx2i78ePw1bD2SALk5uEvmeZxO5PSsdQl8/gEEAkzIas/7q1N5asRn1I7Kh8QknD6DymQ/JxvyL2q8g77JW0tvV0O+eK3aFy0nh4Z9tr4TJ4ojuK5z8HujoWEiIlWScRx8g0cB8NOe86gTfYInZg4HwJ33JTb/hJfxRE7LXbYIu2MruYUR/GzCVQxvtY7rOy8HY4LDwnxl80GrSUzCNE4GYPmexoz+z484URQO+/Zgd+8ok32InI9qXbTYokJs1hoA/reqG32bbiG51hGIr41pkuxxOhERKS+mTQdMk2bUrFHEwwOn8s7Kbqza1wAK8nEXzPI6nsgpbM5R3OlfAPDS0j4cyY/i+Us/whhweg7AadS0TPd38mpLfGQ+0za35cO1XQE15Iu3qnfRkrUG/MXsz4th+uY2wU8sAKdjygU1somISGgzxuAMGQ3Abd0W06L2YR6fGex1cRfNweYe8zKeSClrLYEJH0FRcJX6X/SezZc//FfwQ9ZaCTgXDy/zfZqOKRAZRcuEQwxtkcWry77WkF+QX+b7Ezkb1fov85NDw/L94fygazpXdgyu1eJ01tAwEZGqzklugWndnnCfy+uXv8tfh40P3uEvxp09zdtwIiXs2pXYDWsp9PvI2NOIMJ9LasPdAPguvQpTI6LM92nCw0sb8u/ovpBFu5oFr0T6i3FXppf5/kTORrUtWmz+CeymLACSax3h1XHvUSf6BNStD4kNPU4nIiIVwTdkFGDo3XQbLRIOU+j3YS24yxdjDx3wOp5Uczb/BIFJHwPwl7lDGPDaz9ifFwOA6dodp2Xbctv3ySFiY9quIbFmDm9nXASAm75IDfniiepbtKxbCW6AbUdq83ZGDwqKg4tIBoeGGY/TiYhIRTCJDTElV9f35sbS4Z8PMWlje7AugVmTPU4n1V1g6ng4nsea/Yn8Ze4QHug7k/oxeRAdg2/YZeW6b1O/AaZJM8J9Lp/f+ApPnJz+eH82dtf2ct23yOlU26Ll5NCw/6zowS8mjePkZwZO527ehRIRkQrnu3gEOA6JMbk0r32IR6aPwnVNcPx+9i6v40k15W7ZgM1cSsA1/Hj8NbRIOMRDA6YD4Bs5DhNds9wznLzakpK0h6hwP64b/FBXDfnihWpZtNjcHOzWzVgL767sxrj2q4gK90NS4wtemElERCoXU7sOTlpvjIE/DZ3A6v0Nebdkza7AjIkep5PqyBYXEfjiQwBeS+/F4l3NeGnMB0SEBTCt2wcb5SuA6dAVIoOLVz49fxDD3vpxMN+aTE0NLhWuWhYt7toVgCV9TxM2Ha7H9V1KZg3rlOJpLhER8YYz4BIIr0HPJju4rN0qHp85giK/D7s5C3frJq/jSTXjzpoCRw4BcGXHFbx++TvBhR5rROAbfWWFDWM34eE4XXsA0CLhIHO2t2LF3iTw+9WQLxWuWhYttmRo2Lsru9EgJoeLm28Egv0sIiJS/ZiYWJxeAwB4fPAkatYoYmdOLQDcGRPUeCwVxmbvwl04G2vh8Iko6kSf4MauwQLBGTIKE1+7QvM4ab0AGN1mLUkxx0qnP3bTF+rnQipUtSta7JFDpQ1k/ZK38OigKfgci2navML/IxARkdDh9BkEUdF0rL+P5T95ipYJwU+67e4d2KzV3oaTasEGAvjHvwfW8r9VqbT/52/ZkxMHgGmcjNOjT4VnMvUSMcktCPe53NptCe+sTCOvsAYc2IfdubXC80j1Ve2KFndNZum/L++wiju6LwLAdNLaLCIi1ZmJjMLpNyT4bwMr9ybx4ZouAARmTMK6rpfxpBpwF86GvXs4eLwmD0wex5CWG2gYlwOOD99l13i28LXTLXi15bZuiynwh7FgZ/Ng3vRFnuSR6qnaFS0muQUmpQdERH7tRgenQ1fvQomISEhwLuoLcfEAvJ3Zgx+Pv4aDx2vCwX3YFcs8TidVmT10AHf2FAB+NeUyAq7DMyM/AcDpPwRTr4Fn2UyHLhAVTXKtI+z85WMMaxVc586uWaGGfKkw1a5ocZo0J2zsdYT98jF819yK6dAV07YDpmaM19FERMRjJiwc36DhAPym/wysNfxt3mAAArOmYP3FXsaTKspaS+CLD8DvZ+qmtvy/ld356/DxJMbkQb3E0iuAXjFhXzXkJ0TnUxxwOJIfBQE/rop5qSDVrmg5yYSF47TvTNjVN+O75lav44iISIgwXbtD3frUq3mcX/SZxQtL+rLjaC3IOYq7dIHX8aQKshlLsNs2A9AgJoef9ZzDzSlLAYNvzDWYsDBvA/JVQz7AwNd+xiPTRwFqyJeKU22Llq+rqKkDRUQk9BnHh2/wSADu7T2HuIgCnpwzFAB37nRsYYGX8aSKsbk5wZXvAWuhS4Ns/j7yM4wJDld0mjTzNmAJU7c+pllLAIa3Xs+7q7qRWxgBB/djd2zxOJ1UBypaREREvsG064xp1JTYiEL+39X/4dGLg70G5J/AXTDL02xStQQmfQKFBSzd1YSe//4Fu0tmCyOuFk5J8RwqnLTgdMe3dVvMieIavFeyCKubvtDLWFJNqGgRERH5BmMMzpDRAAxqvpmk2FwKioNDdNyFs7F5uV7GkyrCXbcKu24lRX4fd42/BsdYEmvmAQQXkfz6pEEhwLTrDNE1aRJ/lBGt1/FKenDImF27Ensiz+N0UtWpaBERETkNp3krTMs2AGQdrEerfzzC0l1NoLgId+50j9NJZWcL8glM/BiAvy8YxLoDibx02fuE+VxMp1ScNh08TvhtJiystCH/zrSFFAd8JQ35AdxMNeRL+VLRIiIi8h18g4PNxq0SDlKvZh4PTx+NteAuW4g9csjjdFKZudMnQF4O6w/U50+zh3F/31mkJO2BqGh8I8Z6He87nWzIH9VmHek/+Tu1o/IBcJcvUkO+lCsVLSIiIt/BNGyC6dgVn2P5w5CJzNrWmumb24AbIDBritfxpJJyt28u7QPZnRNP94Y7eWTgVAB8w8diasZ6Ge+MTJ16mOatMCa4CGtGdqNgQ/6hA9jtm72OJ1WYihYREZEz8F08EozD6DZr6d1kK4/MGIXrGuzK5dh9e7yOJ5WM9RcT+PyD0u+HtNzIzNueJyrcj2nZBtMlzcN0Z+dkQ/7+vBj6vHwv767sBqghX8qXihYREZEzMHXq4XTriTHwp6ETMMCBEzUBS+DLSV7Hk0rGnT0NDh1gd04ct39yHQeP18QYILwGvtFXVYplGEy7TlAzhvoxeYxqs45X0ntjLdi1q7DH1ZAv5UNFi4iIyPdwBl4CYWH0S97Kwh/9I7hSOWA3rMXVGhVyluzePbgLZmIt/HzClUzb3Baf4wLgXDwCU7uOxwnPjvGF4aQEG/LvSFvIir2NWLa7CbgB3MylHqeTqkpFi4iIyPcwsfE4PfsH/21g8c6mTMhqDwQbqtWALN/Hui6Bz98H1+XjtV34PKsT/xj1MbWj8jENm5SeX5WF0y3YkD+sVRZN4w/zSnpwyFiwId/1MppUUSpaREREzoLTdzBERgHw4tK+3P351ZwoCsfu3IbduM7jdBLq3MVzsXt2ciQ/ivsmXs7Ydiu5osMqcBx8l12DcSrXn2QmoS6mRRt8juUXfWaTFJsTvOPwQezWTd6Gkyqpcv2EiIiIeMREReP0vRiARwdN4eCJmvxrST8AAjMmYl19uiynZ48cwp05GYDZ21rid308O+oTIFgMm8SGXsY7byenP76n5zweHzy59HY3fZFXkaQKU9EiIiJylpye/SEmjhYJh7mz+yL+Nm9wcHG9/dnY1Rlex5MQZK0l8MWHUFwEwLj2q8m69080jMuBOvVwBgz1OOH5M207Qcn0zAeO1+TVZb2CDfnrV2Hzcj1OJ1WNihYREZGzZMJr4AwcBsBDA6ZRHPDxzIKBAARmTsYG/F7GkxBkV6Zjt2zgRFE4zy3qT5HfR1xkIQC+MVdjwsI9Tnj+jM+Hk3oRABnZjbn7i6tZvCsZXFcN+VLmVLSIiIicAyf1IkioS2JMHu9d+xb39Z4dvOPoYQ2LkVPY47kEpnwGwB9mD+O300az41gtILjWiZPc0sN0ZcPp1hMwDG2xgWa1DvHKMjXkS/lQ0SIiInIOjM+H7+IRQHDmpITofAqKwwBw50zDFhV6GU9CSGDyZ5B/gow9jfjHgoE8Mmgqreocgtg4nKGjvY5XJkztOpiWbXAcy23dFvPBmpTgkMkjh7BbNnodT6oQFS0iIiLnyHTsCkmNAVi6qwnNn36UDQfrwvE83IVzPE4nocDdsBa7OoPigMOPxl9Lh/r7uL/PLAB8o67ElMxEVxU4acGrK7emLsHvOryzMg1QQ76ULRUtIiIi58gYB9+QUQB0TswmKryYx2aOBAguHnhCq4JXZ7awgMCEDwH4dF1nVu1L4t+XvU+4z8V06ILTrpPHCcuWadMBYuJoEJvLn4ZOIDVpFwA2azU2L8fjdFJVqGgRERE5D6ZFG0yzVkSG+3l00BQ+XJPC8j2NoagQd+6XXscTD7kzJkLOMQCu6riChT/6B90b7YTIKHwjL/c4Xdn7ekP+L/rMpk/TbcE7XBc3Y4l3waRKUdEiIiJyHowxOCVXW27suoy2dffxuxnB792l87HHjngZTzzi7tyKu3QB1sK87c0xBlKTdgPgu2QMJibO44Tl42RDPsDUTW15ev4gANzli9WQL2VCRYuIiMh5chonY9p1Jszn8ochEynwh5FXWAMCfgKzpngdTyqY9fsJjP8AsLyVcRGD3/gpK/YmAWCatcKUXI2oikytBEyrtgCs2NuQ3385gsMnouDoYezmDR6nk6pARYuIiMgF8A0eCcYwtt1qpt/6AjERwUUE7Ypl2AN7PU4nFcmdNwMO7mNvbiy/njqGm7oupWuDbAgLC67JYozXEcvVyYb8W1KW4lrDf1d0B9SQL2XjnIuWOXPmMGbMGBo2bIgxhk8//bQcYomIiFQOpl4ipmsPjAFjYMbm1szc0gqsJfDlZK/jSQWx+/fizp0BwC8mjSPcCfDX4eMBcAYNxyTU9TJehTBt2kNsPPVj8ris3WpeTe+FtWCz1mBzj3kdTyq5cy5ajh8/TteuXXn++efLI4+IiEil4xs0DHzBtVqeXnAxP594Bf6Ag12/CnfXdo/TSXmzrkvg8/fBDTB5Yzs+WpvC0yM/pU70CWjQCKf3QK8jVgjjfNWQf2f3Raw/2ID5O5qDVUO+XLhzLlpGjhzJH//4R6644oryyCMiIlLpmPjaOD36AvDHIRPIOpj41dCYGROw1noZT8qZu2wBtqQ4HdhsE6+M/R/XdMoE4xB22TUYx+dtwArkdOsJxjCo2SZeHfcuXRvsAUoa8l015Mv5U0+LiIhIGXD6D4aISFIb7ubqjhk8MWs4+cVh2G2bsZuzvI4n5cQeOxKc4hg4cLwmUeF+bkldijHg9B6AKVmEtLow8bUxrdvjOJabU5YRG1EYvOPYEf0cyAUp96KlsLCQnJycU75ERESqGhMdg9NnEACPDZ5Mdm4sr6YHG5MDMyZq2tcqyFpLYMJHUFTIvO3NafnM74Jr9QDUroMzaLi3AT3idOsFgLVw74TLeXlp8OfATV/oZSyp5Mq9aHnyySeJj48v/WrSpEl571JERMQTTq8BUDOG1nUO8tH1b3Brask4/r27sWtWeBtOypxdnYHduI6C4jDuGn8NKQ12k9KgZE2WMVdjwmt4nNAbpnU7iIvHGDh4oib/XDQg2JC/YS02Rw35cn7KvWh56KGHOHbsWOnXzp07y3uXIiIinjA1InAGXALAqDbriI0opKA42KAfmDkZGwh4GU/KkD2RR2DypwD835yhbDuSwEuXvY/jWEzKRTjNW3sb0EPBhvyeANzZfSEbDtVn7vYWYC1uxmKP00llVe5FS0REBHFxcad8iYiIVFVOWi+olQAEVwZv+cwj7MuLgcMH9QdbFRKY+jmcOM7KvUk8NX8wDw6YQYf6+6BmLL5hY7yO57mTDfkDm22mdZ39vLKsZIiYGvLlPJ1z0ZKXl0dmZiaZmZkAbN26lczMTHbs2FHW2URERCod4wvDd/EIAHo02kGx6+PJOcGrL+7sqdjiIi/jSRlwN2dhVywDoHZUPj/qvpBf9wuu0eIbeTkmKtrLeCHBxNXCtOmAMXBH2iI+XdeZnIIIyDmK3bTe63hSCZ1z0bJs2TJSU1NJTU0F4P777yc1NZVHH320zMOJiIhURqZzKiQmUTsqn1/2nckry3qx5XAC5OXiLp7rdTy5ALaokMAXHwLguoYm8Uf5x6hPiAgLYNp2xHTo4nHC0OGkBa+u/DB1MRl3/424yOBMYmrIl/NxzkXLoEGDsNZ+6+vNN98sh3giIiKVjzEOvsGjAPhpz7nUjT7O4zODV1/c+TOx+Se8jCcXwJ05GY4eZuuRBLr869dkZjcM3hERiW/UlRhjvA0YQkzLthBfm1pRBbSqcwjXNcGG/I3rsMeOeB1PKhmt0yIiIlIOTOv2mKbNia5RzCODppJTGIk/4EBBPu78L72OJ+fB3b0Dd/FcrIWffnEV+cXhtEw4BIAzdDQmLt7jhKHFOE6wtwXYkxNHu38+xKytrYIN+cvV3yXnRkWLiIhIOTDG4AwZDQTH9H9yw+uE+YINyO7iuZr6tZKxgQCB8e+Dtfy/lWlM29yW5y/9kNiIQkzT5sEJGORbnNSLwDgkxeYQEebnlZK1i9yMJVhXs+nJ2VPRIiIiUk6cps1Lm5GthU/XdWLpribg9+POnup1PDkH7oKZsD+b/Xkx/HLyWK7rvJyRbdaDzxdck8XoT6rTMbHxmLZfNeR/tq4T+/NiIPcYduM6r+NJJaKfMBERkXIU7G0xWGt4cs5QfjllLNaWfNJ86IDX8eQs2IP7cWdPA2BvXixt6hzg7yM+BcAZcAmmbqKH6ULfyYb8m7ouxTGWtzN7AOCmL/IyllQyKlpERETKkUlMwnTphuNY/jhkIgt3NmfChg5gXQIzJ3kdT76HtS6Bzz+AgB+ALg2ymXPHc9SreRzqJ+H0vdjjhKHPtGwDtRJIiM7nyo4rgn0tgN24Hnv0sMfppLJQ0SIiIlLOfIOGg+NjaMsNDGq2kd/NGEXANdg1K7B7dnodT87ATV+M3bGF3MIIbvzwxuDU1QAYfJddg/GFeZqvMjDmq4b8f476mPE/eLXkHjXky9lT0SIiIlLOTO06ON17Ywz8cehE1uxP4oM1KQAEZkz0Npx8J5tzDHf6FwA8OmMkX2R1wDEWAKdnf5xGTb2MV6k4qReB4xAXWYjjWPbmxgIlwyQDasiX76eiRUREpAI4A4ZCeA0uaryDD659g3HtVgFgt2zA3bLB43TyTdZaAhM/gsICFu1M5oUlfXli8CSa1T4C8bVxBo/wOmKlYmLiMG07AfDhmi60fOaRYOGSl4PdsNbjdFIZqGgRERGpAKZmLE7vgQCMbb+ayHA/BcXBoUXujIlYa72MJ99g163CZq2hyO/jrvHXkNZwF/f0nAeA79KrMDUiPE5Y+ZycFnpIi434HMtbpQ35C72MJZWEihYREZEK4vQZBFHRALy3KoUOzz1EbmEEds9O7PpV3oaTUjb/BIFJHwOwYm9D9ubG8dJl7+NzLKZLGk6rdh4nrJxMi9ZQuw61o/K5umMmr6f3wnUNdvMG7JFDXseTEKeiRUREpIKYiEic/kMB6NN0GweO1+TZhQOAYG+LFtsLDYFpn0NeLgA9Gu9k8y/+QJcG2RBdE9/wyzxOV3l9vSH/zu4L2Xq0DtO3tEEN+XI2VLSIiIhUIKdHH4ivTZP4o9x90XyeWTCIA8drwqED2MxlXser9tytG7EZS3Bdw9PzB5FTEEFMRBEAvhHjMNExHies3JyUYEN+z8bb6dNkKzuP1QLAzVRDvpyZihYREZEKZMLC8Q0aBsCv+8/AGMtf5w4BIDB7Cra42Mt41ZotLg6uyQL8e1kfHpw2hpX7GgJgWrXDdEr1Ml6VYGJiMe06YwzMvO15bk8rucKSl4vNWuNtOAlpKlpEREQqmOnSHeolUif6BA/0ncnh/GisBXKO4S6d73W8asudPQWOHGLnsVo8PH0Ud6YtoF/yVgivgW/0lRhjvI5YJZxsyDcGjuZHkr67MaCGfDkzFS0iIiIVzDgOvsEjAXiw/wxeu/x/nPx72J03A1uQ72G66slm78JdMBtr4WdfXElcRCH/d8kEAJwhozC1Er7nGeRsmeatIKEuAA9OG8N1798SXGx1ywbs4YMep5NQpaJFRETEA6ZtJ0zjZIyBgGv474o01u5PhPwTuAtmeR2vWrFuAP/nH4B1Wba7CRM3duCfoz8iPrIA0zgZp0dfryNWKcGG/ODVltu6LWb7sQSmbW4LgLt8kZfRJISpaBEREfGAMQZnyGgAAq7DH2YO53czRgHgLpqDzcvxMl614i6cA9m7gOBsYct/8jcua7cGHB++MddgHP25VNaclO7g+OjRaAddEnfzyrLeALiZS7EBv8fpJBTpp1BERMQjTrOWmFbtqBEW4PeDJ/N5VicW7UyG4iLcOdO9jlct2MMHcWdNBmDW1pa4rqFT4l4AnH6DMfUbeBmvyjI1YzHtgw35d3ZfyMQN7dmdEwfH87Dr1ZAv36aiRURExEMne1uu65RB58Q9PDx9NNYGm5K14F75stYS+OID8PuZvrkNw966m8+zOgbvrFu/dE0dKR9OWvDqyvWdlzOyzTqOFUQBasiX01PRIiIi4iGT1BjTKQXHsfxxyATmbm/Jl1tag+sSmDnJ63hVms1cit26ieNFNbjn86sY1Gwjl7VbDZjgsLCwMK8jVmmmWUuoU4+4yEI+vv4NOtTfB4DdulEN+fItKlpEREQ85rt4JDgOI1qv571r3mRAs80A2FUZ2L27PU5XNdm8HAJTxwPw+MzhZOfF8cKYDzAmuACo07S5xwmrPmNMaUO+tTBxQ3uW7moC6GqLfJuKFhEREY+ZhLo43XphDFzeYRXhPpf84uCn/IEvdbWlPAQmfQoF+aza14B/LhrAo4Om0KrOIYiLxxkyyut41YaT0h18PgAe+3IE/zfnEqCkId+vhnz5iooWERGREOAMuATCwgF4YXFfur/0AEV+H3bjOtztmz1OV7W461dj164AoEO9fbw27l3u6z0bAN/oqzARkV7Gq1ZMdAymQ5fShvxJG9uz81gtOHEcu36V1/EkhKhoERERCQEmNg6n1wAA+jfbzKZDdXkj4yIA3BkTsdZ6Ga/KsAX5BCZ+BMDe3Fh8juUHXZcT5nMxHVNw2nTwOGH1c7Ih/7rOGUSFFfPG8pLzXkPE5GtUtIiIiIQIp+/FEBlF58S9/KBrOn+aPYzjRTWwO7dhN2ga2LLgzpgIuTlsOFiXts/+ls/WdQreERmFb8Q4T7NVV6ZpC6hbn9iIQq7rvJw3M3riDzjYbZuxhw54HU9ChIoWERGREGEio3D6DQHg0UFTOHQimucW9QcgMGMS1nW9jFfpuTu24C5bgOsa7v78ahrG5nBJyywAfMPHYmJiPU5YPX29If8nF83n571m43eDf6LqaoucpKJFREQkhDgX9YPYOJrVPsLdF83ncH508I4De7GrlnsbrhKzxUUExr8PwOvLezJneyteGPMB0TWKMS1aY7p29zhh9eak9ABfGF0aZHNfnzlEhgeb8IMN+cUep5NQoKJFREQkhJjwcHwDhwPw1+Hj+evwz0vvC8ycrBmVzoO7cR3+F5+CQwfYkxPHg9Mu5dbUxVzcYhOEheO79GqMMV7HrNZMVDSmY1cADh6vyQOTxrLjaC3IP4Fdp4Z8UdEiIiISckxqD6hTD2OgOODw8tLe7DoWD8eO4C5b4HW8SsMePYz/f68TeOdVOHIIgOjwIm7rtpi/DAsWg87FIzC163gZU0o4acEhYpFhxbyZcRGvL+8JaIiYBKloERERCTHG8QUXnATyi8P5/Zcj+dPskvUr5k7HFhZ4GS/kWb+fwJzp+P/1V2zWGor8Pp6adzGfrO1MragC/jr8c2pH5WOSGuP06u91XClhmjSHeonERBRxfZevNeRv34I9sM/reOIxFS0iIiIhyHTogklqTFxkIQ8OmM6bGReRdbAenDiOu3C21/FClrs5C/9LT+HOnAT+YmZtbUn3l+7ndzNGsv5g/a82jIzCN+46jOPzLqycwhhTOv3xHWkL2ZMbz4QNwSmo3fRFXkaTEKCiRUREJAQZY3CGjgbgru4LaBR3jN9/Gbz64i6cjT2e52W8kGNzjuL/4G0C/30ZDh3gaH4kN334A4a9dTcJUfksvusZHhowAwDTOJmwH/4UUz/J49TyTU6XNAgLIyVpDz0abefV9OCQMXeFGvKruzCvA4iIiMjpOS3a4DZvTeTWjTw6aCp3fHYdmdkNSUnagzt3Br4RY72O6Dkb8OMumos7eyoUF2EtGAPR4cVk58bx6tj/cWPXZTiOhahofEMvxaT2wBh9bhuKgg35KdgVy/j7iM+oWaMweEdBPnbtSkyXNG8DimdUtIiIiIQwZ8goAq8+yw+6LiM+Mp8uidkAuMvm4/Tqj6mV4HFC77jbNhGY8DEcDPY7zNvenPsnjeP1y9+lU+Jept36IsFJwYLrgDhDRmGia3qaWb6fk9aLwIpl9Gqy/ZTb3fSFwSsxUi3pYwYREZEQ5jRqimnfBZ9jGdt+NY5jyS8Og0CAwKwpXsfzhM3Nwf/xfwm89SIc3Me+vBhu++Q6Br/xU8J9gdLtjAGT1BjfHT/HN+ZqFSyVhGncDOo3AGDW1pYMe/PHFAcc7I6t2P17vQ0nnlHRIiIiEuJ8g0dCyXCmJ2YOY8gb92At2BXp2P3ZHqerONYNEFg0B//zf8auygBg+uY2dHruQSZu6MCLY95n7u3P0SlxL0RG4Yy+Et8d9+I0aupxcjkXX2/IT4g6waxtrfkiqyOghvzqTEWLiIhIiDN162NSegAwqPkmlu1pysdruwCWwJeTvA1XQdwdW/D/+xncKZ9BUSHHCiIB6Fg/mxu6pLPmZ3/m9rTFOI7FpPQg7KcP4uveB+PoT53KKNiQH06XBtn0bLyNV9ODRYy7chm2WA351ZF+kkVERCoB36Bh4AtjQLMtDG+1jke/HBlcwyJrDe7ObV7HKzc2Lxf/p+8SeONfsD+bg8drctdn19Dpud9wND+SpNhcnh39CXWiT0BiQ3w//ClhY6/D1IzxOrpcABMZhemUAsCdaYuYtrktWw4nBBvy12R6mk28oaJFRESkEjBxtXAu6gfAE0MmsfFQfd7ODF59cWdMwFrrZbwyZ12XwJJ5waFgK5bhuoZXl/Wi0/O/4ZN1nXl44DRiI0pmloqIxBkxjrAf3YfTtLm3waXMnBwidlXHTOIj8nl3VTcg2JAv1Y9mDxMREakknP5DcJcvIjVpNzd1Xcr+48GrCXb7Fuym9ZjW7T1OWDbcXdsJTPwYsneV3nbX+Gt4K/Mibk5Zwv8NnUD9mOA6NaZLGr5LLsXExHkVV8qJadQUEpOI3pfNzNuep13d/QDYXdux+7IxiVpnpzoxtoI/msnJySE+Pp5jx44RF6f/YERERM5FYO503C8nla5HUiqxIWF3/aJSrz9iT+QRmD4Rm7EYgMMnojhSEE3LhEOk725MgT+cvslbgxvXa4Bv1BU4zVp6mFjKW2DpfNyJH5d+7w84hPlcnB598Y26wsNkUlbOtjaovP+ziYiIVENOz/5QMxZjIL84jH8sGMDR/EjYtwe7OtPreOfFWhc3fSH+5/+CzViM6xreyuhBp+cf5GdfXAlAWqNdwYKlRgTOJWMIu+t+FSzVgNO5G4TXAODh6aMY+84dALgr07HFRV5GkwqmokVERKQSMTUicAZeAsDRgih+/+VI/r7gYgACMydjA34v450zu2cngdeeI/DFh5B/gszshlz8xj3c+dl1DG25gdcuf7d0W9OxK2H3/AZfn0EYn8/D1FJRvt6Q377ePqZtbsumQ3WgsKDSFulyflS0iIiIVDJOt55Quw5Jsbn8rNccnlvUn+zcWDhyCHf5Yq/jnRWbf4LAhI/wv/IsdvcOIHjlaNR/7uJoQRTTbnmBt6/8fyTF5kKdevhuuouwq27GxMV7nFwq2smG/Cs7rKB25AleW94LUEN+daOiRUREpJIxvjB8F48A4Jd9ZxLhC/DknODVF3f2NGxRoZfxzshaFzdzCf7n/4K7bAHWWt5dmcrB4zWJCvcz8aZ/s+zHf2dg880QFo4zeBRhP/4lTos2XkcXj5iGTaBBI6LC/dzYdRlvZ/SgyO/D7t6B3bvH63hSQVS0iIiIVEKmUwokNqRWVAG/6vclr6b3YsfRWnA8F3fxXK/jnZbdu4fAG/8i8Nl7cCKPNfsTueTNn3DLxzfy6brOAKQk7SHc52LadSbsp7/B138IJkyTnVZnxpjSqy13dF9IblEkmXsbAbraUp1o9jAREZFKyt24jsA7r5JfHMbMra0Z2XpdcEaxiEjCfv5bTHRNryMCYAvycWdNwV0yD6wltzCCP84axnOL+9O89iGeHfUJQ1tuCG5cuw6+kZfjVJHpm6Vs2MIC/H9/HIqLyC2M+GqNnhoRhD3we0yNCG8Dynk729pAH12IiIhUUqZVO0xyC6K2b2FUm3UAnCgKJ5oC3Hlf4hs2xtN81lrsquUEpn0Oebmlt284WI+Xl/Xm0UFT+EWfWUSEBSAsDKffEJy+F2PCwj1MLaHIRERiOnfDLl9EbEQhx4tqUOj3kUA+dnUmpltPryNWKu7uHdiN6/ANGu51lLOm4WEiIiKVlDEGZ8jo0u9/PuEKrn3/FgDcJfOwOUc9SgZ2/14Cb71I4JN3IC+X9Qfqc++Eywm4hrRGu9h6/xM8OGAGEWEBTOv2hN39a3wDh6lgke/kSytpwHcNaS8+wF/mDg1+ryFiZ81m78L/7msEXn0Wd/ZU3J3bvI501lS0iIiIVGJOk2aYth0BGNhsE1M2tWf21pYQ8BOYNbXC89jCAgJTP8f/779jt2/meFENHp4+irQXH2DKpnbsPFYLgFpRBRBfG991PyTshjswtetUeFapXEzDJpikxjiOZUzbNbyd2YOC4jDsnp3Y7F1exwtpdl82/vfexP/yM9gNa0tvd2dN9jDVuVHRIiIiUsn5Bo8CDFd0WElawx08MmMU1oLNXII9uK9CMlhrcddk4v/XX3EXzgLXZdKGdnT916/458IBPDhgBhl3/41mtY+Az4fTfyhh9/wap22nCsknVcPJhvzb0xZxKL8mn64PTuDgpi/yMlbIsgf34f/wP/hf+jt2/apv379lI+72zR4kO3cqWkRERCo5U78BpmsaxsCfhk5k8a5mjF/fCawlMLP8P0m1B/cT+O/LBD78D+QeK719//FYOtbfS+Y9f+N3g6YSFe7HtGxD2E9+hW/wSEzJSuciZ8t0ToUaEbSrt58ByZt4dVnJkLFVy7GFBR6nCx328EH8n7yD/4W/YddkAt8975Y7czIVPC/XeVEjvoiISBXgGzQc/+oMBrfYyJi2q9mbFwuAXbsSd/cOnEZNy3yftqgQd+4M3AWzwA2QXxzGX+cNYV9eLC+M+ZCbU5Zyc8rS4IxmcfH4ho/DtO+MMabMs0j1YGpE4HTuhpu+kDu7L+TlZX3ILw4jikLs6gxMyZWY6soePUxg9jTsimVg3e9/QEQkplmr4LbGV/4BL4CKFhERkSrA1ErA6d4Xd/EcPrzuDb5eF7gzJuLc/OMy25e1Fpu1msDkz+DYEQAmZLXn/kmXszs3nvv7zMRaghkcB6fXQJyBl2haWikTTvfeuOkLuaZTJtd2ziy9PZC+qHT4WHVjjx0JfoCQsRjcMxcr1oIbFkF47344fQZhoqIrKOWFUdEiIiJSRTj9h+BmLMYUFZJTEMG/l/XhZz3nErl1I+6WDWWyqrw9fJDApE+wm9YDwZmcrvvgZj5d14WhLbL4/MaXaVP3IACmWSt8o67A1Eu84P2KnGQaNMI0bAJ7dmItzNnWkp6NtxOZvQu7Z2fwvmrC5ubgzpsRnEEtEDjzthZMeDhH2w5ivn8glw+JqqCUZUNFi4iISBVhasbg9B6IO3sq2XlxPDpjJBE+Pz/vPRd3+gTMna3Pe2iWLS7Gnf8l7rwvIeCn0O/DMZZwn0u3pF1c2ymDKzqsDF5diYnDN2wMplOqhoJJuXDSehPYs5MtR+pwyVt388bl/48fdF1OIH0RYdWgaLHHc3Hnz8RdOh/8/jNuezQ/kpeX9+OdrL4sXAT1k+LolV1BQcuQihYREZEqxOk9EHfpfNrWPcAtqUv589yh3Jq6hLjsXdi1KzEdu57zc7ob1hKY/CkcOQTA1E1tuW/i5dzZfSG/6DObBwfMCG5oHJye/XAGDcdERJbhqxI5lemUAlPH0zLhEIOabeS19F78oOty7Krl2GFjquz5Z08cx10wC3fJPCguOuO2O47W4rnFA3ktszdFgTBuuslQ4IM4ICmpYvKWJc0eJiIiUoWYiEic/sFF9x4ZOJW8ogieWTgIgMCXE7HfM4Tk6+zRw/j/9zqBd1+DI4fYeawW1753M5f+90c0ijvGsFbrv9pv0+aE3fULfMPHVtk/GCV0nGzIB7ij+yLm7WjJ2v2JUFyEu2q5x+nKni3IJzBzMv5n/4Q7/8vvLVgwDrdPv4u31vbjZ/eFs22b4dVXoX79islbHnSlRUREpIpxuvfBXTSHxhzh7ovm8Y8FA/l5rznUPnwQm7kUU7Ky+Hexfn/w09y508FfDMD6A/Xp/fJ9xEYU8tYV/+W6zhnBoWA1Y/BdMgbTJU1DwaRCOd174y5bwLh2q6gXnctr6b34+8jPcNMX4qT1rhLnoy0swF08F3fhbCjI/+7tLMzY0oanFwziN7fsYsg9XXntB3VJTISYmAoMXI5UtIiIiFQxJiwM38UjCHz6Lr/uN4MRrddROyr4B09g9pRggREeftrHupuzCEz8GA4Hm+lX72tAp8S9tK27nz8OnchNXZcSF1kIxuB074MzeCQmsnI19ErVYBIbYhonU2PXdn7V70t8TslaI3v3BBvyy2Ga74piiwpxl87HnT8T8k9853bFAYcP1qTw9PxBrNzXiNTOxYT1b4tJgJYJFRi4AqhoERERqYJM524wfyYJB/YyqPlmrIUCfxhRuTm4S+bh63vxKdvbnKMEpnyGXbsSgD05cfxm6hjeW92Nubc/S88mO7in57zgczdqim/0lZikxhX+ukS+zknrRWDXdu7rM+eU291lC8tlbaLyZouLcZctCA4BO573vdv/a3E/fj11LCOHFPDMO3DxxeFUgQtMp6WiRUREpAoyjoNvyEgC/3sDgOs/uJno8CJev/x/uPNm4KT1wkRGYQN+3EVzcGdPg+IiigMOLyzpxxMzhxMZVsyr497losY7gk8aFY1v6KWY1B4Yo7ZY8Z7pmAKTP4PCAnYcrcWkje25q8dC7JpM7PDLKs1VQOv34y5fhDtvBuTmfOd2e3LieH5xf2IjCvjtnXu5/doejCiGzp2rfh+ZihYREZEqyrTpiGnSDLtzG4OabeLeiZdzf59ZdErcizt/JqZFm+BQsIP7Sh/z3KIB/Hb6aO7qvoDHB0+iVlQBYHC69cQZMgoTXdO7FyTyDSa8Bk6XNNyl81m6uyk/m3AV/ZK30LH+PtxVy/H16Ot1xDOygQA2cwmBOdMh5+h3brdmfyLPLBjEuyu7ERXh8sA9Jwi7rhYJQBUbBfadjLXWVuQOc3JyiI+P59ixY8TFxVXkrkVERKodd/sWAm/+i+KAQ5fnf0O7evv45IbXwThggytn78uLYdnuJoxuu468whpsPFSP1Ia7ATBJjXFGX1kph9pI9WD3Z+N/8SmKAw4tnv4dV3VcwTOjPoXEJMLueiAkG/KtG8CuTCcwexocPXzGbTccrEun5x+icUIe995dyI9+VYeq9Cf02dYGurYrIiJShTnJLTCt2xPuc/n94MlM2NCRBTuagXUJuIYXFvel03MP8vMJV1Lk9xETURQsWCKjcEZdie+Oe1WwSEgz9ZMwTZoR7nO5JXUJ/13RnRNF4bAvG7t7h9fxTmFdF3dlOv5//ZXAZ++dtmDxBxzeX53CbZ9ch7XQtlscX7yRzebsGH75h6pVsJwLDQ8TERGp4nyDR+HfuI5rOmbyenpPduXUYvHOpvxswpWs2NuQ27ot5o9DJ1IjLLiGi0npEexdqVlF5kqVKs9J601g5zZu67aYv84byodrUrg5dWlw+uPGyV7Hw1oXu3YVgdlT4MC+025zvKgGbyy/iH8uGsC2o3UY0n4HuWN/QkJKS0aH4NWiiqaiRUREpIozDRpiOqfirMpgyi0vYQyM+e8dGGOZe8dzXzXaJybhG3UlTtPm3gYWOUemQ1eY/CktEg7zl2HjSUnaBYBdnYkdPtazhnxrLTZrNYFZU2Bf9hm2g76v/Jysg/W5uscGPvztMbpd1jwkh7Z5RT0tIiIi1YA9cgj/838GN9jHcvhEFPGRBcG1LSIicS4egdOjD8bxeZxU5PwEJn+Ku3jut253RozD17N/hWax1mI3rcedORmbveu026w/UJ9nFw7gtwOn0yT+KF8e6UmbMV1pNrhNtSpWzrY20JUWERGRasDUroMzYBjurMkAJEQHF5s0XdKCQ8Fi9UGiVG5OWq/SouX91SnsyYnjvj5zcNMX4VzUr0IKAWstdssG3FlTsLu2n+Z+WLCjOX9fMIgvsjrRICaHa/pup9lV7RnWobOmEj8DFS0iIiLVhDNgKNSMwa5fBbHxOCndcZJbeh1LpEyYeg0wTZtjd2xl1b4kXlzSlzu7L6Lmgb3YXdswTcp32KO7bXPwysqOLd+5zeMzh/N/c4bRru5eXr5+Ajc+0JDI1GswjoqV76OiRUREpJowxuDr3hu69/Y6iki5cNJ6E9ixldu7LeKvcwfz/uoUfthtSfBqSzkVLe7OrcFiZeumb92XXxzG25k9aBibw5h2a7imUyYXtT3C6B83x5cyQsMxz4GKFhERERGpEkyHLjD5U5pxhOGtsnhlWW9+2G0Jdk1JQ35UdJnty929IzgMbNP6b9134HhNXlralxeX9OVwfjS/6vclYy7aTedLB9AlpQfGp2LlXKloEREREZEqwYSF43TtjrtoDnd0X8hV/7uNjOxGpCbtxl2xDF+vARe8D7t3N4GZk7Eb1p72/sU7m3LJW3fjGJcfpi7hZ0OW02pcGk63hzBh+tP7fOmdExEREZEqw0nrhbtoDqNar+Pdq9+iQ729AMEhYj37n3dDvt2fTWDWVOy6ld+6b/HOpizd3ZSf9ppHatJufn/xZG7tu4Z6w/vgpN2NCQ+/oNckKlpEREREpAoxdRMxyS0J276ZKzt+rcA4uA+7YysmucU5PZ89uJ/A7CnY1SuAr1YKcV3DhA0deHrBIObvaEH7env5UfeF1IiN4Fe/r4nT4xeYGhFl9KpERYuIiIiIVClOWi8C2zcTcA23fPwDhrXM4ubUpbjpC3HOsmixhw8SmDMNuzI9OFfx1xT5ffR8+Res2Z9EnyZb+fC617m0y1bC+g7D6dkPExFZHi+rWlPRIiIiIiJVimnfBaI+wZd/grzCCF5Y0pebU5di167EjhiHia75nY+1Rw8Hi5XMZWDd0tsPn4jizYye3NNzLhFhAe5IW0Raw530arkXp9cAnN7XYyKjKuLlVUsqWkRERESkSjFhYTgpPXAXzuaO7gu54t3bWb6nMd0a7go25Pce+K3H2JyjuHNn4C5fDG6g9PatRxL458IBvJFxEQHXoXeTbfRuuo17+i3B6dkfp88dZTormZyeihYRERERqXKctN64C2czotV6Gscd5ZVlvXjxsg+DQ8R6DShtyLd5Obhzv8RNXwgB/ynP8fsvR/CXuUOoFZnPfb1nc/dF86lfqwCnx0CcvhdjasZ68dKqJRUtIiIiIlLlmDr1MM1aEbZtE7emLuZfi/vzj1GfEHHoAHb7FqiXiDt/Ju7S+eAvBoKtK5M3tqNprSN0rL+P7g138szIT7k5ZSk1owI4aX1w+g3GxMZ5/OqqH2PtNzqLzsILL7zA3/72N7Kzs+nYsSP/+Mc/6N+//1k9Nicnh/j4eI4dO0ZcnA64iIiIiJQPd3UGgY/+y6ET0RQHfDSIzQ3eUace5ByD4iIACv0+3lvVjacXDGTtgSR+0386fxgyKbit48NJvQhnwFBMXC1vXkgVdra1wTlfaXnvvfe47777eOGFF+jbty///ve/GTlyJGvXrqVp06YXFFpEREREpKyY9p0hOoY65AHBWb/CfQHMoQOl28ze2pKbP/oB2XnxjGqzhudGf0y/5C1gHExKd3wDLsHUSvDqJUiJc77S0rNnT7p168aLL75Yelv79u0ZN24cTz755Pc+XldaRERERKSiBKZ9gbtgJlkH63Hx6z9l/A9eJTEml42H6jG4xUZ2HYvnD7OGc2/v2XSovw+MwXRJCxYrCXW9jl/llcuVlqKiItLT03nwwQdPuX3YsGEsWLDgtI8pLCyksLDwlGAiIiIiIhXBSeuFu2AmrRIOEhVWzA0f3MSunFq0SjjAinv+RuP4Y/x77PuAwXRKwTdwGKZuotex5Rucc9n44MGDBAIBEhNPPZCJiYns3bv3tI958skniY+PL/1q0qTJ+acVERERETkHJqEupnlrfI7lgb4zCfcF+Muwz1lw57OUTCCGad+ZsJ88QNiVN6lgCVHnNXvYySniTrLWfuu2kx566CHuv//+0u9zcnJUuIiIiIhIhXH6DyWwdRN395zP3T3nl95u2nTAN2g4Jqmxh+nkbJxT0VK3bl18Pt+3rqrs37//W1dfToqIiCAiIuL8E4qIiIiIXACneSsYcxWBOdOhsACT3AKn/1CcRppEqrI4p6KlRo0apKWlMW3aNC6//PLS26dNm8bYsWPLPJyIiIiISFlwuvXCpF4EmO8cISSh65yHh91///3cdNNNdO/end69e/Pyyy+zY8cOfvzjH5dHPhERERGRMmHMObVzSwg556Ll2muv5dChQzzxxBNkZ2fTqVMnJk6cSHJycnnkExERERGRau6c12m5UFqnRURERERE4OxrA10jExERERGRkKaiRUREREREQpqKFhERERERCWkqWkREREREJKSpaBERERERkZCmokVEREREREKaihYREREREQlpKlpERERERCSkqWgREREREZGQpqJFRERERERCmooWEREREREJaSpaREREREQkpKloERERERGRkKaiRUREREREQpqKFhERERERCWkqWkREREREJKSpaBERERERkZCmokVEREREREKaihYREREREQlpKlpERERERCSkhVX0Dq21AOTk5FT0rkVEREREJIScrAlO1gjfpcKLltzcXACaNGlS0bsWEREREZEQlJubS3x8/Hfeb+z3lTVlzHVd9uzZQ2xsLMaYity1EKxmmzRpws6dO4mLi/M6jlQwHf/qTcdfTtK5UL3p+FdvoXb8rbXk5ubSsGFDHOe7O1cq/EqL4zg0bty4oncr3xAXFxcSJ6p4Q8e/etPxl5N0LlRvOv7VWygd/zNdYTlJjfgiIiIiIhLSVLSIiIiIiEhIU9FSzURERPD73/+eiIgIr6OIB3T8qzcdfzlJ50L1puNfvVXW41/hjfgiIiIiIiLnQldaREREREQkpKloERERERGRkKaiRUREREREQpqKFhERERERCWkqWkLAnDlzGDNmDA0bNsQYw6effnrK/fv27ePWW2+lYcOGREdHM2LECDZu3Fh6/7Zt2zDGnPbrgw8+OOW5JkyYQM+ePYmKiqJu3bpcccUV35tv1apVDBw4kKioKBo1asQTTzzB1+dvmDdvHn379qVOnTpERUXRrl07nnnmmQt7U6qZyn4OzJo167T7Xr9+/YW9MdVEZT/+t95662n33bFjxwt7Y6qZyn4eAPzrX/+iffv2REVF0bZtW95+++3zf0OqoVA+BwoKCrj11lvp3LkzYWFhjBs37lvbZGdnc8MNN9C2bVscx+G+++4737eiWqqI4/9dv6+NMSxduvSM+b7v/4DyPv4qWkLA8ePH6dq1K88///y37rPWMm7cOLZs2cJnn31GRkYGycnJDB06lOPHjwPQpEkTsrOzT/l6/PHHqVmzJiNHjix9ro8++oibbrqJH/7wh6xYsYL58+dzww03nDFbTk4Ol1xyCQ0bNmTp0qU899xzPPXUUzz99NOl29SsWZOf/vSnzJkzh3Xr1vHII4/wyCOP8PLLL5fRO1T1VfZz4KSsrKxTMrRu3foC35nqobIf/2efffaUfe/cuZOEhASuvvrqMnqHqofKfh68+OKLPPTQQzz22GOsWbOGxx9/nHvuuYfPP/+8jN6hqi+Uz4FAIEBUVBQ///nPGTp06Gm3KSwspF69ejz88MN07dr1At6J6qkijn+fPn2+tc0dd9xBs2bN6N69+3dmO5v/A8r9+FsJKYD95JNPSr/PysqygF29enXpbX6/3yYkJNhXXnnlO58nJSXF3nbbbaXfFxcX20aNGtlXX331nPK88MILNj4+3hYUFJTe9uSTT9qGDRta13W/83GXX365vfHGG89pXxJUGc+BmTNnWsAeOXLknJ5bvq0yHv9v+uSTT6wxxm7btu2c9iVfqYznQe/eve0vf/nLUx5377332r59+57TviQo1M6Br7vlllvs2LFjz7jNwIED7b333nve+6juyuv4f1NRUZGtX7++feKJJ86Y51x/F5TH8deVlhBXWFgIQGRkZOltPp+PGjVqMG/evNM+Jj09nczMTG6//fbS25YvX87u3btxHIfU1FSSkpIYOXIka9asOeP+Fy5cyMCBA09ZgGj48OHs2bOHbdu2nfYxGRkZLFiwgIEDB57ty5QzqEznwMnnHTJkCDNnzjzXlyqnUZmO/0mvvfYaQ4cOJTk5+WxfpnyPynAeFBYWnpIPICoqiiVLllBcXHxOr1e+zetzQLxVVsf/m8aPH8/Bgwe59dZbz7j/8/ldUNZUtIS4du3akZyczEMPPcSRI0coKiriz3/+M3v37iU7O/u0j3nttddo3749ffr0Kb1ty5YtADz22GM88sgjfPHFF9SuXZuBAwdy+PDh79z/3r17SUxMPOW2k9/v3bv3lNsbN25MREQE3bt355577uGOO+44r9csp6oM50BSUhIvv/wyH330ER9//DFt27ZlyJAhzJkz54Jeu1SO4/912dnZTJo0ST//ZawynAfDhw/n1VdfJT09HWsty5Yt4/XXX6e4uJiDBw9e0OsX788B8VZZHf/TbTN8+HCaNGlyxv2f6++C8qCiJcSFh4fz0UcfsWHDBhISEoiOjmbWrFmMHDkSn8/3re3z8/N55513vlVVu64LwMMPP8yVV15JWloab7zxxinNWR07diQmJoaYmJhTxr4aY055LlvSdPXN2+fOncuyZct46aWX+Mc//sG777574W+AVIpzoG3bttx5551069aN3r1788ILLzB69GieeuqpsnsjqqnKcPy/7s0336RWrVqnbdKV81cZzoPf/e53jBw5kl69ehEeHs7YsWNLP709XUY5N6FwDoh3yur4f92uXbuYMmXKt7Ypi98F5SGsQvYiFyQtLY3MzEyOHTtGUVER9erVo2fPnqdtmPrwww85ceIEN9988ym3JyUlAdChQ4fS2yIiImjRogU7duwAYOLEiaWX8KOiogBo0KDBtyro/fv3A3yr4m7evDkAnTt3Zt++fTz22GNcf/315/265SuV5Rz4ul69evHf//73XF+qnEZlOf7WWl5//XVuuukmatSocSEvWU4j1M+DqKgoXn/9df7973+zb9++0iuwsbGx1K1btyzegmrPy3NAvFcWx//r3njjDerUqcNll112yu1l+bdAWdKVlkokPj6eevXqsXHjRpYtW8bYsWO/tc1rr73GZZddRr169U65PS0tjYiICLKyskpvKy4uZtu2baXjzpOTk2nVqhWtWrWiUaNGAPTu3Zs5c+ZQVFRU+ripU6fSsGFDmjVr9p1ZrbWl4y+l7FSmcyAjI6P0l6OUjVA//rNnz2bTpk1n/GRPLlyonwfh4eE0btwYn8/H//73Py699FIcR39ulCUvzgEJHRdy/E+y1vLGG29w8803Ex4efsp9Zfm3QJkq07Z+OS+5ubk2IyPDZmRkWMA+/fTTNiMjw27fvt1aa+37779vZ86caTdv3mw//fRTm5ycbK+44opvPc/GjRutMcZOmjTptPu59957baNGjeyUKVPs+vXr7e23327r169vDx8+/J3Zjh49ahMTE+31119vV61aZT/++GMbFxdnn3rqqdJtnn/+eTt+/Hi7YcMGu2HDBvv666/buLg4+/DDD1/gO1N9VPZz4JlnnrGffPKJ3bBhg129erV98MEHLWA/+uijC3xnqofKfvxPuvHGG23Pnj3P812Qyn4eZGVl2f/85z92w4YNdvHixfbaa6+1CQkJduvWrRf2xlQjoXwOWGvtmjVrbEZGhh0zZowdNGhQadavO3lbWlqaveGGG2xGRoZds2bN+b0h1UxFHX9rrZ0+fboF7Nq1a88q29n+LijP46+iJQScnC72m1+33HKLtdbaZ5991jZu3NiGh4fbpk2b2kceecQWFhZ+63keeugh27hxYxsIBE67n6KiIvvAAw/Y+vXr29jYWDt06NBTps77LitXrrT9+/e3ERERtkGDBvaxxx47ZXq7f/7zn7Zjx442OjraxsXF2dTUVPvCCy98Zw75tsp+DvzlL3+xLVu2tJGRkbZ27dq2X79+dsKECef3ZlRDlf34Wxv8hRYVFWVffvnlc38DxFpb+c+DtWvX2pSUFBsVFWXj4uLs2LFj7fr168/vzaimQv0cSE5OPm2+rzvd/cnJyef8XlRHFXX8rbX2+uuvt3369DmnfGfzu6A8j78p2YGIiIiIiEhI0iBTEREREREJaSpaREREREQkpKloERERERGRkKaiRUREREREQpqKFhERERERCWkqWkREREREJKSpaBERERERkZCmokVEREREREKaihYREREREQlpKlpERERERCSkqWgREREREZGQpqJFRERERERC2v8HqkzHGz1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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "scatter(\"RCHRES\", rid, \"HYDR\", \"IVOL\", \"sum\")" + "scatter(\"PERLND\", pls, \"PWATER\", \"SUPY\", \"sum\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### RCHRES HYDR PRSUPY" + "#### PERLND PWATER SURO" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.124875Z", - "iopub.status.idle": "2024-05-21T21:50:35.125084Z", - "shell.execute_reply": "2024-05-21T21:50:35.125036Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.125031Z" + "execution_count": 63, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "plot(\"RCHRES\", rid, \"HYDR\", \"PRSUPY\", \"sum\")" + "plot(\"PERLND\", pls, \"PWATER\", \"SURO\", \"sum\")" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.125315Z", - "iopub.status.idle": "2024-05-21T21:50:35.125413Z", - "shell.execute_reply": "2024-05-21T21:50:35.125368Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.125363Z" + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "scatter(\"RCHRES\", rid, \"HYDR\", \"PRSUPY\", \"sum\")" + "scatter(\"PERLND\", pls, \"PWATER\", \"SURO\", \"sum\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### RCHRES HYDR ROVOL" + "#### PERLND PWATER TAET" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.125653Z", - "iopub.status.idle": "2024-05-21T21:50:35.125743Z", - "shell.execute_reply": "2024-05-21T21:50:35.125700Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.125695Z" + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "scatter(\"RCHRES\", rid, \"HYDR\", \"ROVOL\", \"sum\")" + "scatter(\"PERLND\", pls, \"PWATER\", \"TAET\", \"sum\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### RCHRES HYDR VOL" + "#### PERLND PWATER UZET" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.126485Z", - "iopub.status.idle": "2024-05-21T21:50:35.126575Z", - "shell.execute_reply": "2024-05-21T21:50:35.126534Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.126530Z" + "execution_count": 67, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "scatter(\"RCHRES\", rid, \"HYDR\", \"VOL\", \"last\")" + "scatter(\"PERLND\", pls, \"PWATER\", \"UZET\", \"sum\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### RCHRES HYDR VOLEV" + "#### PERLND PWATER UZI" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.127233Z", - "iopub.status.idle": "2024-05-21T21:50:35.127325Z", - "shell.execute_reply": "2024-05-21T21:50:35.127282Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.127278Z" + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "plot(\"RCHRES\", rid, \"HYDR\", \"VOLEV\", \"sum\")" + "plot(\"PERLND\", pls, \"PWATER\", \"UZI\", \"sum\")" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T21:50:35.127888Z", - "iopub.status.idle": "2024-05-21T21:50:35.128084Z", - "shell.execute_reply": "2024-05-21T21:50:35.128024Z", - "shell.execute_reply.started": "2024-05-21T21:50:35.128019Z" + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "scatter(\"RCHRES\", rid, \"HYDR\", \"VOLEV\", \"sum\")" + "scatter(\"PERLND\", pls, \"PWATER\", \"UZI\", \"sum\")" ] } ], @@ -2425,7 +1795,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.14" + "version": "3.11.11" } }, "nbformat": 4, diff --git a/tests/test05/HSP2compare/TEST05.UCI b/tests/test05/HSP2compare/TEST05.UCI index 3ddfb1ae..79508b5d 100644 --- a/tests/test05/HSP2compare/TEST05.UCI +++ b/tests/test05/HSP2compare/TEST05.UCI @@ -7,7 +7,7 @@ GLOBAL RESUME 0 RUN 1 UNIT SYSTEM 1 END GLOBAL -FILES +FILES ***<----FILE NAME-------------------------------------------------> WDM 21 test.wdm MESSU 22 test05.ech diff --git a/tests/test05/HSP2compare/TEST05bin.UCI b/tests/test05/HSP2compare/TEST05bin.UCI index 612405ea..880c8f9d 100644 --- a/tests/test05/HSP2compare/TEST05bin.UCI +++ b/tests/test05/HSP2compare/TEST05bin.UCI @@ -200,19 +200,19 @@ EXT SOURCES <-Volume-> SsysSgap<--Mult-->Tran <-Target vols> <-Grp> <-Member-> *** x x tem strg<-factor->strg x x x x *** *** Met Seg C:1,PI:PETINP=0.7 -WDM 39 PREC ENGLZERO PERLND 1 2 EXTNL PREC +WDM 39 PREC ENGLZERO PERLND 1 2 EXTNL PREC WDM 123 ATMP ENGL SAME PERLND 1 2 ATEMP AIRTMP WDM 41 EVAP ENGL 0.7DIV PERLND 1 2 EXTNL PETINP WDM 42 WIND ENGL DIV PERLND 1 2 EXTNL WINMOV WDM 46 SOLR ENGL DIV PERLND 1 2 EXTNL SOLRAD -WDM 126 DEWP ENGL SAME PERLND 1 2 EXTNL DTMPG +WDM 126 DEWP ENGL SAME PERLND 1 2 EXTNL DTMPG *** Met Seg C:1,PI:PETINP=0.7 -WDM 131 PREC ENGLZERO PERLND 3 EXTNL PREC +WDM 131 PREC ENGLZERO PERLND 3 EXTNL PREC WDM 122 ATMP ENGL SAME PERLND 3 ATEMP AIRTMP WDM 41 EVAP ENGL 0.7DIV PERLND 3 EXTNL PETINP WDM 42 WIND ENGL DIV PERLND 3 EXTNL WINMOV WDM 46 SOLR ENGL DIV PERLND 3 EXTNL SOLRAD -WDM 125 DEWP ENGL SAME PERLND 3 EXTNL DTMPG +WDM 125 DEWP ENGL SAME PERLND 3 EXTNL DTMPG WDM 136 FLOW ENGL SAME PLTGEN 1 INPUT MEAN 4 END EXT SOURCES @@ -229,7 +229,7 @@ COPY 1 OUTPUT MEAN 1 1. COPY 2 INPUT MEAN 1 PERLND 1 PWATER PERO 122000. COPY 3 INPUT MEAN 1 PERLND 2 PWATER PERO 176200. COPY 3 INPUT MEAN 1 PERLND 3 PWATER PERO 75500. COPY 3 INPUT MEAN 1 -COPY 3 OUTPUT MEAN 1 1. DISPLY 1 INPUT TIMSER +COPY 3 OUTPUT MEAN 1 1. DISPLY 1 INPUT TIMSER COPY 1 OUTPUT MEAN 1 1. PLTGEN 1 INPUT MEAN 1 COPY 2 OUTPUT MEAN 1 1. PLTGEN 1 INPUT MEAN 2 COPY 3 OUTPUT MEAN 1 1. PLTGEN 1 INPUT MEAN 3 diff --git a/tests/test05/HSPFresults/TEST05.UCI b/tests/test05/HSPFresults/TEST05.UCI index 3ddfb1ae..79508b5d 100644 --- a/tests/test05/HSPFresults/TEST05.UCI +++ b/tests/test05/HSPFresults/TEST05.UCI @@ -7,7 +7,7 @@ GLOBAL RESUME 0 RUN 1 UNIT SYSTEM 1 END GLOBAL -FILES +FILES ***<----FILE NAME-------------------------------------------------> WDM 21 test.wdm MESSU 22 test05.ech diff --git a/tests/test05/HSPFresults/TEST05bin.UCI b/tests/test05/HSPFresults/TEST05bin.UCI index 612405ea..880c8f9d 100644 --- a/tests/test05/HSPFresults/TEST05bin.UCI +++ b/tests/test05/HSPFresults/TEST05bin.UCI @@ -200,19 +200,19 @@ EXT SOURCES <-Volume-> SsysSgap<--Mult-->Tran <-Target vols> <-Grp> <-Member-> *** x x tem strg<-factor->strg x x x x *** *** Met Seg C:1,PI:PETINP=0.7 -WDM 39 PREC ENGLZERO PERLND 1 2 EXTNL PREC +WDM 39 PREC ENGLZERO PERLND 1 2 EXTNL PREC WDM 123 ATMP ENGL SAME PERLND 1 2 ATEMP AIRTMP WDM 41 EVAP ENGL 0.7DIV PERLND 1 2 EXTNL PETINP WDM 42 WIND ENGL DIV PERLND 1 2 EXTNL WINMOV WDM 46 SOLR ENGL DIV PERLND 1 2 EXTNL SOLRAD -WDM 126 DEWP ENGL SAME PERLND 1 2 EXTNL DTMPG +WDM 126 DEWP ENGL SAME PERLND 1 2 EXTNL DTMPG *** Met Seg C:1,PI:PETINP=0.7 -WDM 131 PREC ENGLZERO PERLND 3 EXTNL PREC +WDM 131 PREC ENGLZERO PERLND 3 EXTNL PREC WDM 122 ATMP ENGL SAME PERLND 3 ATEMP AIRTMP WDM 41 EVAP ENGL 0.7DIV PERLND 3 EXTNL PETINP WDM 42 WIND ENGL DIV PERLND 3 EXTNL WINMOV WDM 46 SOLR ENGL DIV PERLND 3 EXTNL SOLRAD -WDM 125 DEWP ENGL SAME PERLND 3 EXTNL DTMPG +WDM 125 DEWP ENGL SAME PERLND 3 EXTNL DTMPG WDM 136 FLOW ENGL SAME PLTGEN 1 INPUT MEAN 4 END EXT SOURCES @@ -229,7 +229,7 @@ COPY 1 OUTPUT MEAN 1 1. COPY 2 INPUT MEAN 1 PERLND 1 PWATER PERO 122000. COPY 3 INPUT MEAN 1 PERLND 2 PWATER PERO 176200. COPY 3 INPUT MEAN 1 PERLND 3 PWATER PERO 75500. COPY 3 INPUT MEAN 1 -COPY 3 OUTPUT MEAN 1 1. DISPLY 1 INPUT TIMSER +COPY 3 OUTPUT MEAN 1 1. DISPLY 1 INPUT TIMSER COPY 1 OUTPUT MEAN 1 1. PLTGEN 1 INPUT MEAN 1 COPY 2 OUTPUT MEAN 1 1. PLTGEN 1 INPUT MEAN 2 COPY 3 OUTPUT MEAN 1 1. PLTGEN 1 INPUT MEAN 3 diff --git a/tests/test05/HSPFresults/test05.d62 b/tests/test05/HSPFresults/test05.d62 index b3ec0545..1764f321 100644 --- a/tests/test05/HSPFresults/test05.d62 +++ b/tests/test05/HSPFresults/test05.d62 @@ -3,42 +3,42 @@ - SIMULATED FLOW (CFS) + SIMULATED FLOW (CFS) Annual data display: Summary for period ending 1976/12 Day JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC - + 1 11.35 28.76 112.01 328.69 386.18 215.49 113.29 12.92 0.26 0.02 1.41 0.20 2 11.10 28.13 108.22 303.71 417.19 203.30 107.10 10.25 0.21 0.01 1.35 0.19 3 10.86 27.38 104.74 283.23 398.27 191.25 100.70 7.80 0.17 0.01 1.25 0.19 4 10.63 26.70 101.50 266.45 374.22 179.40 93.97 5.34 0.13 0.47 1.17 0.19 5 10.40 26.07 98.44 251.78 351.72 168.07 88.24 3.00 0.11 0.58 1.09 0.18 - + 6 10.17 25.45 96.39 238.38 330.44 157.49 82.11 1.46 0.08 0.45 1.00 0.18 7 9.96 25.88 98.07 225.75 311.65 147.79 76.37 0.63 0.07 0.27 0.96 0.17 8 9.74 28.85 98.76 214.28 294.66 138.59 70.48 0.28 0.05 0.01 0.92 0.17 9 9.54 31.40 102.96 203.59 277.39 129.15 64.65 0.20 0.04 0.01 0.86 0.17 10 9.33 32.42 106.94 192.06 260.89 151.26 58.85 0.16 0.03 0.00 0.83 0.16 - + 11 9.19 32.04 129.42 181.82 245.62 147.62 53.20 0.13 0.03 0.00 0.80 0.16 12 9.30 31.52 230.22 173.01 231.43 140.46 48.18 0.10 0.02 0.00 0.79 0.16 13 10.18 30.91 266.62 163.33 259.65 164.18 43.20 0.08 0.02 0.00 0.77 0.15 14 11.52 30.65 287.19 158.00 252.79 203.47 38.23 0.30 0.01 0.00 0.74 0.15 15 12.70 36.81 294.23 186.18 244.51 187.40 34.57 0.11 0.01 0.00 0.68 0.15 - + 16 12.70 48.50 308.34 175.28 299.64 172.57 32.18 0.05 0.01 0.00 0.59 0.14 17 12.42 51.32 327.43 221.35 314.85 160.19 28.18 1.92 0.00 0.00 0.48 0.14 18 12.25 48.84 337.45 474.16 295.31 149.72 24.38 1.59 0.00 0.01 0.41 0.30 19 12.09 47.10 324.06 421.73 276.91 140.57 21.59 1.01 1.08 0.24 0.37 0.52 20 12.01 53.15 308.28 439.27 259.16 131.60 20.67 0.49 1.12 0.22 0.34 0.54 - + 21 11.85 59.64 293.69 561.71 243.04 123.11 20.25 0.29 0.67 0.19 0.33 0.53 22 13.11 57.39 280.72 509.54 246.60 115.25 19.48 0.24 0.37 0.12 0.33 0.52 23 16.33 56.56 268.81 623.06 269.43 107.56 17.69 0.19 0.12 0.87 0.31 0.51 24 17.41 66.28 257.65 680.63 259.20 119.09 14.64 0.15 0.08 1.29 0.27 0.50 25 17.35 71.49 247.03 646.42 245.70 120.11 11.23 1.36 0.07 1.19 0.23 0.49 - + 26 19.01 87.88 239.40 578.49 231.72 112.40 9.81 2.56 0.05 1.15 0.22 0.48 27 20.25 109.63 232.61 521.63 218.35 116.93 8.59 1.98 0.06 1.12 0.21 0.56 28 24.36 117.97 223.55 477.89 208.42 135.45 22.71 1.26 0.05 1.08 0.21 0.58 diff --git a/tests/test05/HSPFresults/test05.ech b/tests/test05/HSPFresults/test05.ech index 05a1c74c..a673c51f 100644 --- a/tests/test05/HSPFresults/test05.ech +++ b/tests/test05/HSPFresults/test05.ech @@ -1,13 +1,13 @@ - FOUND RUN - FOUND END RUN + FOUND RUN + FOUND END RUN ************************************************************ * * * Hydrological Simulation Program - FORTRAN * * * ************************************************************ - + Developed for: Modified and Maintained by - + U.S. Environmental RESPEC, Inc. Protection Agency (605)394-6512 Office of Research email: hspf@respec.com @@ -17,47 +17,47 @@ Athens, Georgia (706)355-8400 email: ceam@epamail.epa.gov - + In cooperation with: - + U.S. Geological Survey Release 12.5 Water Resources Discipline September 2018 Office of Surface Water Reston, Virginia email: h2osoft@usgs.gov - - + + Start of Job - + PREPROCESSING USERS CONTROL INPUT. - + SEARCHING FOR BOUNDARIES OF NEXT DATA SET IN USERS CONTROL INPUT. - - FOUND RUN - FOUND END RUN - + + FOUND RUN + FOUND END RUN + INTERPRETING RUN DATA SET IN USERS CONTROL INPUT - - FOUND GLOBAL - FOUND END GLOBAL - FOUND FILES - FOUND END FILES + + FOUND GLOBAL + FOUND END GLOBAL + FOUND FILES + FOUND END FILES FOUND OPN SEQUENCE FOUND END OPN SEQUENCE - FOUND PERLND - FOUND END PERLND - FOUND DISPLY - FOUND END DISPLY - FOUND COPY - FOUND END COPY - FOUND PLTGEN - FOUND END PLTGEN - FOUND EXT SOURCES - FOUND END EXT SOURCES - FOUND NETWORK - FOUND END NETWORK - - + FOUND PERLND + FOUND END PERLND + FOUND DISPLY + FOUND END DISPLY + FOUND COPY + FOUND END COPY + FOUND PLTGEN + FOUND END PLTGEN + FOUND EXT SOURCES + FOUND END EXT SOURCES + FOUND NETWORK + FOUND END NETWORK + + ==================================================================================================================================== PROCESSING GLOBAL BLOCK @@ -69,36 +69,36 @@ RUN INTERPRETER OUTPUT LEVEL HAS BEEN SET TO: 3 RUNTIME SPECIAL ACTION OUTPUT LEVEL HAS BEEN SET TO: 2 - + SYSTEM HAS BEEN ASKED TO INTERPRET AND EXECUTE THE RUN. RUNFG = 1 THE UNIT SYSTEM OF THE RUN WILL BE ENGLISH. EMFG = 1 - + FINISHED PROCESSING GLOBAL BLOCK ==================================================================================================================================== - + ==================================================================================================================================== CATEGORY BLOCK NOT FOUND - + FINISHED PROCESSING CATEGORY BLOCK ==================================================================================================================================== - + ==================================================================================================================================== PROCESSING OPN SEQUENCE BLOCK - - + + USERS CONTROL INPUT IS: - OPN SEQUENCE - INGRP INDELT 00:30 - PERLND 1 - PERLND 2 - PERLND 3 - COPY 1 - COPY 2 - COPY 3 - DISPLY 1 - PLTGEN 1 - END INGRP - END OPN SEQUENCE + OPN SEQUENCE + INGRP INDELT 00:30 + PERLND 1 + PERLND 2 + PERLND 3 + COPY 1 + COPY 2 + COPY 3 + DISPLY 1 + PLTGEN 1 + END INGRP + END OPN SEQUENCE FINISHED PROCESSING OPN SEQUENCE BLOCK ==================================================================================================================================== @@ -110,18 +110,18 @@ PROCESSING PERVIOUS LAND-SEGMENT NO: 1 TIME STEP(DELT): 30 MINS PROCESSING GENERAL INPUT - + AIRTFG SNOWFG PWATFG SEDFG PSTFG PWGFG PQALFG MSTLFG PESTFG NITRFG PHOSFG TRACFG 0 1 1 0 0 0 0 0 0 0 0 0 - + Printout level flags Print-ivl Print-yrend ATEMP SNOW PWAT SED PSTMP PWTG RQAL MSTL PEST NITR PHOS TRAC PIVL PYREND 4 4 4 4 4 4 4 4 4 4 4 4 1 12 - + Binary Output level flags Print-ivl Print-yrend ATEMP SNOW PWAT SED PSTMP PWTG RQAL MSTL PEST NITR PHOS TRAC PIVL PYREND 4 4 4 4 4 4 4 4 4 4 4 4 1 12 - + Perv Land-segment id Unit systems Print-file nos BinaryOutfileNos IUNITS OUNITS English Metric English Metric BEANS 1 1 1 0 93 0 @@ -130,25 +130,25 @@ ------------------------------------------------------------------------------------------------------------------------------------ PROCESSING INPUT FOR SECTION SNOW - + ICEFG 1 - + SNOPFG VMKFG 0 0 - + LAT MELEV SHADE SNOWCF COVIND KMELT TBASE degrees (ft) (in) (in/d.F) (F) 43. 1225. 0.0 1.45 0.5 0.00 32.0 - + RDCSN TSNOW SNOEVP CCFACT MWATER MGMELT (deg F) (in/day) 0.12 32. 0.05 0.5 0.08 0.0001 - + Pack-snow Pack-ice Pack-watr RDENPF DULL PAKTMP (in) (in) (in) (deg F) 1.4 0.2 0.1 0.2 375. 27.5 - + COVINX XLNMLT SKYCLR (in) (in) 0.50 0.0 1.0 @@ -157,42 +157,42 @@ ------------------------------------------------------------------------------------------------------------------------------------ PROCESSING INPUT FOR SECTION PWATER - + CSNOFG RTOPFG UZFG VCSFG VUZFG VNNFG VIFWFG VIRCFG VLEFG IFFCFG HWTFG IRRGFG IFRDFG NCANPY 1 0 0 1 1 1 0 0 1 1 0 0 0 0 - + FOREST LZSN INFILT LSUR SLSUR KVARY AGWRC (inches) (in/hr) (feet) (1/inches) (1/day) 0.000 8.0 0.100 350. 0.010 0.5 0.98 - + PETMAX PETMIN INFEXP INFILD DEEPFR BASETP AGWETP (degF) (degF) 40. 35. 2.0 2.0 0.10 0.0 0.08 - + CEPSC UZSN NSUR INTFW IRC LZETP (inches) (inches)(nManning) (1/day) 0.00 0.01 0.1 1.0 0.60 0.00 - + FZG FZGL (/in) 1.00 0.100 - + Values of Interception Storage at start of each calendar month (inches): JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 0.04 0.04 0.03 0.03 0.03 0.03 0.10 0.17 0.19 0.14 0.05 0.04 - + Values of Upper Zone Storage at start of each calendar month (inches): JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 0.4 0.4 0.4 0.4 1.6 1.1 1.1 1.3 1.3 1.3 1.1 0.9 - + Values of Manning's N at start of each calendar month: JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 0.30 0.30 0.30 0.30 0.27 0.25 0.25 0.25 0.25 0.25 0.35 0.33 - + Values of Lower Zone ET at start of each calendar month: JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 0.20 0.20 0.20 0.23 0.23 0.25 0.60 0.80 0.75 0.50 0.30 0.20 - + Segment-wide storages (inches): CEPS SURS UZS IFWS LZS AGWS GWVS 0.05 0.0 0.15 0.0 4.0 0.05 0.05 @@ -207,18 +207,18 @@ PROCESSING PERVIOUS LAND-SEGMENT NO: 2 TIME STEP(DELT): 30 MINS PROCESSING GENERAL INPUT - + AIRTFG SNOWFG PWATFG SEDFG PSTFG PWGFG PQALFG MSTLFG PESTFG NITRFG PHOSFG TRACFG 0 1 1 0 0 0 0 0 0 0 0 0 - + Printout level flags Print-ivl Print-yrend ATEMP SNOW PWAT SED PSTMP PWTG RQAL MSTL PEST NITR PHOS TRAC PIVL PYREND 4 4 4 4 4 4 4 4 4 4 4 4 1 12 - + Binary Output level flags Print-ivl Print-yrend ATEMP SNOW PWAT SED PSTMP PWTG RQAL MSTL PEST NITR PHOS TRAC PIVL PYREND 4 4 4 4 4 4 4 4 4 4 4 4 1 12 - + Perv Land-segment id Unit systems Print-file nos BinaryOutfileNos IUNITS OUNITS English Metric English Metric CORN 1 1 1 0 93 0 @@ -227,25 +227,25 @@ ------------------------------------------------------------------------------------------------------------------------------------ PROCESSING INPUT FOR SECTION SNOW - + ICEFG 1 - + SNOPFG VMKFG 0 0 - + LAT MELEV SHADE SNOWCF COVIND KMELT TBASE degrees (ft) (in) (in/d.F) (F) 43. 1225. 0.0 1.45 0.5 0.00 32.0 - + RDCSN TSNOW SNOEVP CCFACT MWATER MGMELT (deg F) (in/day) 0.12 32. 0.05 0.5 0.08 0.0001 - + Pack-snow Pack-ice Pack-watr RDENPF DULL PAKTMP (in) (in) (in) (deg F) 1.4 0.2 0.1 0.2 375. 27.5 - + COVINX XLNMLT SKYCLR (in) (in) 0.50 0.0 1.0 @@ -254,42 +254,42 @@ ------------------------------------------------------------------------------------------------------------------------------------ PROCESSING INPUT FOR SECTION PWATER - + CSNOFG RTOPFG UZFG VCSFG VUZFG VNNFG VIFWFG VIRCFG VLEFG IFFCFG HWTFG IRRGFG IFRDFG NCANPY 1 0 0 1 1 1 0 0 1 1 0 0 0 0 - + FOREST LZSN INFILT LSUR SLSUR KVARY AGWRC (inches) (in/hr) (feet) (1/inches) (1/day) 0.000 8.0 0.100 350. 0.010 0.5 0.98 - + PETMAX PETMIN INFEXP INFILD DEEPFR BASETP AGWETP (degF) (degF) 40. 35. 2.0 2.0 0.10 0.0 0.08 - + CEPSC UZSN NSUR INTFW IRC LZETP (inches) (inches)(nManning) (1/day) 0.00 0.01 0.1 1.0 0.60 0.00 - + FZG FZGL (/in) 1.00 0.100 - + Values of Interception Storage at start of each calendar month (inches): JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 0.12 0.12 0.12 0.12 0.05 0.08 0.14 0.19 0.20 0.15 0.13 0.13 - + Values of Upper Zone Storage at start of each calendar month (inches): JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 0.4 0.4 0.4 0.4 1.4 1.0 1.0 1.2 1.2 1.2 1.0 0.9 - + Values of Manning's N at start of each calendar month: JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 0.30 0.30 0.30 0.30 0.27 0.25 0.25 0.25 0.25 0.25 0.35 0.33 - + Values of Lower Zone ET at start of each calendar month: JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 0.20 0.20 0.20 0.23 0.23 0.25 0.60 0.80 0.75 0.50 0.30 0.20 - + Segment-wide storages (inches): CEPS SURS UZS IFWS LZS AGWS GWVS 0.10 0.0 0.10 0.0 4.0 0.05 0.05 @@ -304,18 +304,18 @@ PROCESSING PERVIOUS LAND-SEGMENT NO: 3 TIME STEP(DELT): 30 MINS PROCESSING GENERAL INPUT - + AIRTFG SNOWFG PWATFG SEDFG PSTFG PWGFG PQALFG MSTLFG PESTFG NITRFG PHOSFG TRACFG 0 1 1 0 0 0 0 0 0 0 0 0 - + Printout level flags Print-ivl Print-yrend ATEMP SNOW PWAT SED PSTMP PWTG RQAL MSTL PEST NITR PHOS TRAC PIVL PYREND 4 4 4 4 4 4 4 4 4 4 4 4 1 12 - + Binary Output level flags Print-ivl Print-yrend ATEMP SNOW PWAT SED PSTMP PWTG RQAL MSTL PEST NITR PHOS TRAC PIVL PYREND 4 4 4 4 4 4 4 4 4 4 4 4 1 12 - + Perv Land-segment id Unit systems Print-file nos BinaryOutfileNos IUNITS OUNITS English Metric English Metric OTHER 1 1 1 0 93 0 @@ -324,25 +324,25 @@ ------------------------------------------------------------------------------------------------------------------------------------ PROCESSING INPUT FOR SECTION SNOW - + ICEFG 1 - + SNOPFG VMKFG 0 0 - + LAT MELEV SHADE SNOWCF COVIND KMELT TBASE degrees (ft) (in) (in/d.F) (F) 43. 1225. 0.0 1.45 0.5 0.00 32.0 - + RDCSN TSNOW SNOEVP CCFACT MWATER MGMELT (deg F) (in/day) 0.12 32. 0.05 0.5 0.08 0.0001 - + Pack-snow Pack-ice Pack-watr RDENPF DULL PAKTMP (in) (in) (in) (deg F) 1.4 0.2 0.1 0.2 375. 27.5 - + COVINX XLNMLT SKYCLR (in) (in) 0.50 0.0 1.0 @@ -351,42 +351,42 @@ ------------------------------------------------------------------------------------------------------------------------------------ PROCESSING INPUT FOR SECTION PWATER - + CSNOFG RTOPFG UZFG VCSFG VUZFG VNNFG VIFWFG VIRCFG VLEFG IFFCFG HWTFG IRRGFG IFRDFG NCANPY 1 0 0 1 1 1 0 0 1 1 0 0 0 0 - + FOREST LZSN INFILT LSUR SLSUR KVARY AGWRC (inches) (in/hr) (feet) (1/inches) (1/day) 0.010 9.0 0.150 350. 0.010 0.5 0.98 - + PETMAX PETMIN INFEXP INFILD DEEPFR BASETP AGWETP (degF) (degF) 40. 35. 2.0 2.0 0.10 0.0 0.08 - + CEPSC UZSN NSUR INTFW IRC LZETP (inches) (inches)(nManning) (1/day) 0.00 0.01 0.1 1.2 0.80 0.00 - + FZG FZGL (/in) 1.00 0.100 - + Values of Interception Storage at start of each calendar month (inches): JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 0.06 0.06 0.06 0.07 0.07 0.08 0.10 0.10 0.10 0.10 0.07 0.06 - + Values of Upper Zone Storage at start of each calendar month (inches): JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 0.8 0.8 0.8 0.8 1.4 1.6 1.6 1.6 1.6 1.6 1.3 1.1 - + Values of Manning's N at start of each calendar month: JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 - + Values of Lower Zone ET at start of each calendar month: JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 0.25 0.25 0.25 0.25 0.30 0.35 0.40 0.40 0.45 0.35 0.30 0.25 - + Segment-wide storages (inches): CEPS SURS UZS IFWS LZS AGWS GWVS 0.05 0.0 0.30 0.0 6.5 0.15 0.10 @@ -405,11 +405,11 @@ ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ PROCESSING DISPLY OPERATION NO. 1 TIME INTERVAL 30 MINS - + Title of display Transform Data for short-span display Data for long-span display code PIVL Digits File-no. PYRFG Digits File-no. PYREND SIMULATED FLOW (CFS) AVER 0 4 1 2 62 12 - + Convert DegC to F Display negative data A B THRSH1 THRSH2 1.00 0.00 0.00 0.00 @@ -425,7 +425,7 @@ ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ PROCESSING COPY OPERATION NO. 1 - + NPT NMN 0 1 @@ -434,7 +434,7 @@ ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ PROCESSING COPY OPERATION NO. 2 - + NPT NMN 0 1 @@ -443,7 +443,7 @@ ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ PROCESSING COPY OPERATION NO. 3 - + NPT NMN 0 1 @@ -458,28 +458,28 @@ ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ PROCESSING PLTGEN OPERATION NO. 1 - + PLOTFL NPT NMN LABLFG PYREND PIVL TYPEFG 92 0 4 0 9 24 1 - + General plot title: Y-axis label: - SIMULATED FLOW CFS - + SIMULATED FLOW CFS + YMIN YMAX IVLIN THRESH (ivl/in) 0. 1500. 20.-1.000E+30 - + Curve label: LINTYP INTEQ COLCOD TRAN - 0 0 0 - + 0 0 0 + Curve label: LINTYP INTEQ COLCOD TRAN - 0 0 0 - + 0 0 0 + Curve label: LINTYP INTEQ COLCOD TRAN - 0 0 0 - + 0 0 0 + Curve label: LINTYP INTEQ COLCOD TRAN - 0 0 0 + 0 0 0 FINISHED PROCESSING PLTGEN OPERATION NO. 1 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ @@ -506,7 +506,7 @@ INPUT TIMESERIES FROM EXTERNAL SOURCES - TYPE # INTERVAL TRN STR MFACT GROUP MEMBER S1 S2 + TYPE # INTERVAL TRN STR MFACT GROUP MEMBER S1 S2 WDM1 39 60 DIV 1.000E+00 EXTNL PREC 1 1 WDM1 123 120 SAME 1.000E+00 ATEMP AIRTMP 1 1 @@ -518,7 +518,7 @@ OUTPUT TIMESERIES TO OTHER OPERATIONS(NETWORK) - GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 + GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 PWATER AGWO 1 1 1.220E+05 COPY 1 INPUT MEAN 1 1 PWATER IFWO 1 1 1.220E+05 COPY 2 INPUT MEAN 1 1 @@ -532,7 +532,7 @@ INPUT TIMESERIES FROM EXTERNAL SOURCES - TYPE # INTERVAL TRN STR MFACT GROUP MEMBER S1 S2 + TYPE # INTERVAL TRN STR MFACT GROUP MEMBER S1 S2 WDM1 39 60 DIV 1.000E+00 EXTNL PREC 1 1 WDM1 123 120 SAME 1.000E+00 ATEMP AIRTMP 1 1 @@ -544,7 +544,7 @@ OUTPUT TIMESERIES TO OTHER OPERATIONS(NETWORK) - GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 + GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 PWATER AGWO 1 1 1.762E+05 COPY 1 INPUT MEAN 1 1 PWATER IFWO 1 1 1.762E+05 COPY 2 INPUT MEAN 1 1 @@ -558,7 +558,7 @@ INPUT TIMESERIES FROM EXTERNAL SOURCES - TYPE # INTERVAL TRN STR MFACT GROUP MEMBER S1 S2 + TYPE # INTERVAL TRN STR MFACT GROUP MEMBER S1 S2 WDM1 131 60 DIV 1.000E+00 EXTNL PREC 1 1 WDM1 122 120 SAME 1.000E+00 ATEMP AIRTMP 1 1 @@ -570,7 +570,7 @@ OUTPUT TIMESERIES TO OTHER OPERATIONS(NETWORK) - GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 + GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 PWATER AGWO 1 1 7.550E+04 COPY 1 INPUT MEAN 1 1 PWATER IFWO 1 1 7.550E+04 COPY 2 INPUT MEAN 1 1 @@ -584,7 +584,7 @@ INPUT TIMESERIES FROM OTHER OPERATIONS(NETWORK) - TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 + TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 PERLND 1 PWATER AGWO 1 1 1.220E+05 INPUT MEAN 1 1 PERLND 2 PWATER AGWO 1 1 1.762E+05 INPUT MEAN 1 1 @@ -593,7 +593,7 @@ OUTPUT TIMESERIES TO OTHER OPERATIONS(NETWORK) - GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 + GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 OUTPUT MEAN 1 1 1.000E+00 COPY 2 INPUT MEAN 1 1 OUTPUT MEAN 1 1 1.000E+00 PLTGEN 1 INPUT MEAN 1 1 @@ -606,7 +606,7 @@ INPUT TIMESERIES FROM OTHER OPERATIONS(NETWORK) - TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 + TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 PERLND 1 PWATER IFWO 1 1 1.220E+05 INPUT MEAN 1 1 PERLND 2 PWATER IFWO 1 1 1.762E+05 INPUT MEAN 1 1 @@ -616,7 +616,7 @@ OUTPUT TIMESERIES TO OTHER OPERATIONS(NETWORK) - GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 + GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 OUTPUT MEAN 1 1 1.000E+00 PLTGEN 1 INPUT MEAN 2 1 @@ -628,7 +628,7 @@ INPUT TIMESERIES FROM OTHER OPERATIONS(NETWORK) - TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 + TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 PERLND 1 PWATER PERO 1 1 1.220E+05 INPUT MEAN 1 1 PERLND 2 PWATER PERO 1 1 1.762E+05 INPUT MEAN 1 1 @@ -637,7 +637,7 @@ OUTPUT TIMESERIES TO OTHER OPERATIONS(NETWORK) - GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 + GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 OUTPUT MEAN 1 1 1.000E+00 DISPLY 1 INPUT TIMSER 1 1 OUTPUT MEAN 1 1 1.000E+00 PLTGEN 1 INPUT MEAN 3 1 @@ -650,7 +650,7 @@ INPUT TIMESERIES FROM OTHER OPERATIONS(NETWORK) - TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 + TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 COPY 3 OUTPUT MEAN 1 1 1.000E+00 INPUT TIMSER 1 1 @@ -662,12 +662,12 @@ INPUT TIMESERIES FROM EXTERNAL SOURCES - TYPE # INTERVAL TRN STR MFACT GROUP MEMBER S1 S2 + TYPE # INTERVAL TRN STR MFACT GROUP MEMBER S1 S2 WDM1 136 1440 SAME 1.000E+00 INPUT MEAN 4 1 FROM OTHER OPERATIONS(NETWORK) - TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 + TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 COPY 1 OUTPUT MEAN 1 1 1.000E+00 INPUT MEAN 1 1 COPY 2 OUTPUT MEAN 1 1 1.000E+00 INPUT MEAN 2 1 @@ -675,10 +675,10 @@ FINISHED PROCESSING BLOCKS CONTAINING TIME SERIES LINKAGES ==================================================================================================================================== - + INTERPRETATION OF RUN DATA SET COMPLETE - + COMMENCING EXECUTION - + End of Job diff --git a/tests/test05/HSPFresults/test05.p92 b/tests/test05/HSPFresults/test05.p92 index 9d63ad81..754ccbfc 100644 --- a/tests/test05/HSPFresults/test05.p92 +++ b/tests/test05/HSPFresults/test05.p92 @@ -2,10 +2,10 @@ SIMU HSPF FILE FOR DRIVING SEPARATE PLOT PROGRAM SIMU Time interval: 720 mins Last month in printout year: 9 SIMU No. of curves plotted: Point-valued: 0 Mean-valued: 4 Total 4 SIMU Label flag: 0 Pivl: 24 Idelt: 30 -SIMU Plot title: SIMULATED FLOW -SIMU Y-axis label: CFS +SIMU Plot title: SIMULATED FLOW +SIMU Y-axis label: CFS SIMU Scale info: Ymin: 0.0000 Threshold:-0.10000E+31 -SIMU Ymax: 1500.0 +SIMU Ymax: 1500.0 SIMU Time: 20.000 intervals/inch SIMU Data for each curve (Point-valued first, then mean-valued): SIMU Label LINTYP INTEQ COLCOD TRAN TRANCOD @@ -24,735 +24,735 @@ SIMU SIMU Date/time Values SIMU SIMU 1975 12 31 24 0-1.0000000E+30-1.0000000E+30-1.0000000E+30-1.0000000E+30 -SIMU 1976 1 1 12 0 273.7137 273.7137 274.1314 360.0000 -SIMU 1976 1 1 24 0 270.9065 270.9065 270.9065 360.0000 -SIMU 1976 1 2 12 0 267.8203 267.8203 267.8203 360.0000 -SIMU 1976 1 2 24 0 265.0379 265.0379 265.0379 360.0000 -SIMU 1976 1 3 12 0 262.0291 262.0291 262.0291 360.0000 -SIMU 1976 1 3 24 0 259.3096 259.3096 259.3096 360.0000 -SIMU 1976 1 4 12 0 256.3756 256.3756 256.3756 384.0000 -SIMU 1976 1 4 24 0 253.7173 253.7173 253.7173 384.0000 -SIMU 1976 1 5 12 0 250.8562 250.8562 250.8562 384.0000 -SIMU 1976 1 5 24 0 248.2574 248.2574 248.2574 384.0000 -SIMU 1976 1 6 12 0 245.4668 245.4668 245.4668 408.0000 -SIMU 1976 1 6 24 0 242.9262 242.9262 242.9262 408.0000 -SIMU 1976 1 7 12 0 240.2040 240.2040 240.2040 432.0000 -SIMU 1976 1 7 24 0 237.7201 237.7201 237.7201 432.0000 -SIMU 1976 1 8 12 0 235.0643 235.0643 235.0643 432.0000 -SIMU 1976 1 8 24 0 232.6355 232.6355 232.6355 432.0000 -SIMU 1976 1 9 12 0 230.0442 230.0442 230.0442 456.0000 -SIMU 1976 1 9 24 0 227.6693 227.6693 227.6693 456.0000 -SIMU 1976 1 10 12 0 225.1406 225.1406 225.1406 456.0000 -SIMU 1976 1 10 24 0 222.8182 222.8182 222.8182 456.0000 -SIMU 1976 1 11 12 0 220.3504 220.3504 220.3504 480.0000 -SIMU 1976 1 11 24 0 220.3348 220.3348 220.6296 480.0000 -SIMU 1976 1 12 12 0 218.7653 218.7653 218.7653 480.0000 -SIMU 1976 1 12 24 0 223.9155 223.9155 227.5199 480.0000 -SIMU 1976 1 13 12 0 224.2073 224.2073 229.0978 480.0000 -SIMU 1976 1 13 24 0 250.5231 250.5231 259.6499 480.0000 -SIMU 1976 1 14 12 0 250.1501 250.1501 251.4268 504.0000 -SIMU 1976 1 14 24 0 282.6879 283.4876 301.6508 504.0000 -SIMU 1976 1 15 12 0 285.4275 286.2410 286.2409 504.0000 -SIMU 1976 1 15 24 0 303.7103 304.4379 323.1508 504.0000 -SIMU 1976 1 16 12 0 305.7707 306.4214 306.4214 504.0000 -SIMU 1976 1 16 24 0 302.5865 303.1686 303.1686 504.0000 -SIMU 1976 1 17 12 0 299.1237 299.6443 299.6443 504.0000 -SIMU 1976 1 17 24 0 296.0120 296.4777 296.4777 504.0000 -SIMU 1976 1 18 12 0 292.6365 293.0529 293.0529 504.0000 -SIMU 1976 1 18 24 0 293.6567 294.1086 294.9831 504.0000 -SIMU 1976 1 19 12 0 291.2049 291.6229 291.6229 504.0000 -SIMU 1976 1 19 24 0 288.1777 288.5516 288.5516 504.0000 -SIMU 1976 1 20 12 0 284.8995 285.2339 285.2339 480.0000 -SIMU 1976 1 20 24 0 287.3622 287.6613 291.0746 480.0000 -SIMU 1976 1 21 12 0 285.6196 285.8871 285.8871 480.0000 -SIMU 1976 1 21 24 0 282.6551 282.8944 282.8944 480.0000 -SIMU 1976 1 22 12 0 279.8778 280.1126 285.2809 480.0000 -SIMU 1976 1 22 24 0 323.7802 324.8535 344.2205 480.0000 -SIMU 1976 1 23 12 0 326.0203 327.0487 340.6180 480.0000 -SIMU 1976 1 23 24 0 395.8738 397.3109 443.0800 480.0000 -SIMU 1976 1 24 12 0 401.3105 402.6367 402.6367 480.0000 -SIMU 1976 1 24 24 0 418.1101 419.2964 433.0610 480.0000 -SIMU 1976 1 25 12 0 416.4763 417.5373 417.5374 480.0000 -SIMU 1976 1 25 24 0 413.9085 414.8574 415.4517 480.0000 -SIMU 1976 1 26 12 0 410.0617 410.9106 426.1584 480.0000 -SIMU 1976 1 26 24 0 458.6590 459.5100 486.1920 480.0000 -SIMU 1976 1 27 12 0 458.6625 459.4549 463.1353 480.0000 -SIMU 1976 1 27 24 0 492.3941 494.8919 509.0454 480.0000 -SIMU 1976 1 28 12 0 492.6601 495.1029 497.4737 480.0000 -SIMU 1976 1 28 24 0 579.1383 589.1035 671.5825 480.0000 -SIMU 1976 1 29 12 0 594.1650 603.9413 634.2453 480.0000 -SIMU 1976 1 29 24 0 713.1340 729.8587 779.6940 480.0000 -SIMU 1976 1 30 12 0 716.6623 730.6788 730.6788 480.0000 -SIMU 1976 1 30 24 0 708.8400 720.0978 720.0978 480.0000 -SIMU 1976 1 31 12 0 699.4521 708.5308 708.5308 456.0000 -SIMU 1976 1 31 24 0 691.8361 699.1887 699.1887 456.0000 -SIMU 1976 2 1 12 0 682.7362 688.7186 688.7186 456.0000 -SIMU 1976 2 1 24 0 682.3723 687.6998 691.6342 456.0000 -SIMU 1976 2 2 12 0 674.7304 679.1472 679.1481 456.0000 -SIMU 1976 2 2 24 0 667.4161 671.0426 671.0426 456.0000 -SIMU 1976 2 3 12 0 658.8010 661.4517 661.4517 432.0000 -SIMU 1976 2 3 24 0 651.6752 652.9003 652.9003 432.0000 -SIMU 1976 2 4 12 0 643.2598 644.3555 644.3555 432.0000 -SIMU 1976 2 4 24 0 636.3148 637.2950 637.2950 432.0000 -SIMU 1976 2 5 12 0 628.1501 629.0268 629.0268 432.0000 -SIMU 1976 2 5 24 0 621.3827 622.1666 622.1666 432.0000 -SIMU 1976 2 6 12 0 613.5100 614.2114 614.2122 432.0000 -SIMU 1976 2 6 24 0 606.9158 607.5430 607.5430 432.0000 -SIMU 1976 2 7 12 0 599.2827 599.8436 599.8453 432.0000 -SIMU 1976 2 7 24 0 621.5203 622.4725 642.5262 432.0000 -SIMU 1976 2 8 12 0 625.0670 626.0715 629.5871 456.0000 -SIMU 1976 2 8 24 0 701.7318 707.7177 755.4160 456.0000 -SIMU 1976 2 9 12 0 707.7151 713.3344 723.4707 480.0000 -SIMU 1976 2 9 24 0 763.7617 770.9675 783.5859 480.0000 -SIMU 1976 2 10 12 0 763.2811 769.2648 771.3387 480.0000 -SIMU 1976 2 10 24 0 777.2682 782.5706 784.9334 480.0000 -SIMU 1976 2 11 12 0 769.1977 773.4739 773.4739 504.0000 -SIMU 1976 2 11 24 0 760.8099 764.2403 764.2402 504.0000 -SIMU 1976 2 12 12 0 751.8317 754.6130 755.4594 528.0000 -SIMU 1976 2 12 24 0 754.6191 757.0453 757.6956 528.0000 -SIMU 1976 2 13 12 0 745.3438 746.0004 746.0004 576.0000 -SIMU 1976 2 13 24 0 737.2469 737.8109 737.8109 576.0000 -SIMU 1976 2 14 12 0 727.6096 728.1143 728.1143 600.0000 -SIMU 1976 2 14 24 0 722.0472 722.6774 743.1882 600.0000 -SIMU 1976 2 15 12 0 788.0955 794.2668 858.8982 648.0000 -SIMU 1976 2 15 24 0 885.9044 897.9026 907.8766 648.0000 -SIMU 1976 2 16 12 0 890.0539 900.4751 934.2605 696.0000 -SIMU 1976 2 16 24 0 1147.188 1252.002 1393.779 696.0000 -SIMU 1976 2 17 12 0 1160.643 1247.780 1247.780 744.0000 -SIMU 1976 2 17 24 0 1147.576 1215.721 1215.721 744.0000 -SIMU 1976 2 18 12 0 1130.966 1184.332 1184.332 840.0000 -SIMU 1976 2 18 24 0 1118.276 1160.133 1160.133 840.0000 -SIMU 1976 2 19 12 0 1102.644 1135.538 1135.871 768.0000 -SIMU 1976 2 19 24 0 1098.210 1124.220 1124.789 768.0000 -SIMU 1976 2 20 12 0 1083.811 1104.346 1104.346 744.0000 -SIMU 1976 2 20 24 0 1159.870 1188.142 1446.803 744.0000 -SIMU 1976 2 21 12 0 1393.915 1445.009 1445.009 672.0000 -SIMU 1976 2 21 24 0 1378.056 1417.898 1417.898 672.0000 -SIMU 1976 2 22 12 0 1357.451 1388.551 1388.552 600.0000 -SIMU 1976 2 22 24 0 1342.063 1366.365 1366.365 600.0000 -SIMU 1976 2 23 12 0 1322.182 1341.198 1341.199 768.0000 -SIMU 1976 2 23 24 0 1344.435 1360.949 1373.761 768.0000 -SIMU 1976 2 24 12 0 1352.014 1366.486 1420.828 840.0000 -SIMU 1976 2 24 24 0 1631.467 1664.786 1760.583 840.0000 -SIMU 1976 2 25 12 0 1645.186 1673.444 1679.449 672.0000 -SIMU 1976 2 25 24 0 1719.133 1743.396 1751.933 672.0000 -SIMU 1976 2 26 12 0 1729.574 1751.620 1863.471 576.0000 -SIMU 1976 2 26 24 0 2145.076 2203.090 2354.557 576.0000 -SIMU 1976 2 27 12 0 2196.134 2248.779 2387.094 624.0000 -SIMU 1976 2 27 24 0 2647.731 2741.445 2875.384 624.0000 -SIMU 1976 2 28 12 0 2666.097 2744.970 2776.679 648.0000 -SIMU 1976 2 28 24 0 2796.178 2866.075 2885.736 648.0000 -SIMU 1976 2 29 12 0 2757.730 2812.425 2812.425 696.0000 -SIMU 1976 2 29 24 0 2724.651 2767.139 2767.139 696.0000 -SIMU 1976 3 1 12 0 2674.779 2707.797 2707.797 600.0000 -SIMU 1976 3 1 24 0 2642.787 2668.460 2668.460 600.0000 -SIMU 1976 3 2 12 0 2594.898 2614.871 2614.871 576.0000 -SIMU 1976 3 2 24 0 2563.970 2579.518 2579.518 576.0000 -SIMU 1976 3 3 12 0 2517.981 2530.094 2530.094 696.0000 -SIMU 1976 3 3 24 0 2488.078 2497.523 2497.523 696.0000 -SIMU 1976 3 4 12 0 2443.906 2451.277 2451.277 840.0000 -SIMU 1976 3 4 24 0 2414.992 2420.751 2420.751 840.0000 -SIMU 1976 3 5 12 0 2372.557 2377.063 2377.063 840.0000 -SIMU 1976 3 5 24 0 2344.595 2348.125 2348.125 840.0000 -SIMU 1976 3 6 12 0 2304.067 2306.842 2307.754 816.0000 -SIMU 1976 3 6 24 0 2312.121 2314.444 2319.128 816.0000 -SIMU 1976 3 7 12 0 2282.915 2284.728 2290.749 768.0000 -SIMU 1976 3 7 24 0 2389.728 2393.710 2416.441 768.0000 -SIMU 1976 3 8 12 0 2375.829 2379.557 2379.557 744.0000 -SIMU 1976 3 8 24 0 2356.251 2359.478 2361.091 744.0000 -SIMU 1976 3 9 12 0 2324.133 2326.993 2343.137 720.0000 -SIMU 1976 3 9 24 0 2533.496 2546.324 2598.988 720.0000 -SIMU 1976 3 10 12 0 2527.951 2539.621 2544.238 720.0000 -SIMU 1976 3 10 24 0 2575.119 2585.723 2589.015 720.0000 -SIMU 1976 3 11 12 0 2542.523 2551.394 2573.140 744.0000 -SIMU 1976 3 11 24 0 3130.838 3325.532 3639.246 744.0000 -SIMU 1976 3 12 12 0 3977.998 4697.345 4755.904 2400.000 -SIMU 1976 3 12 24 0 4568.944 6110.023 6294.532 2400.000 -SIMU 1976 3 13 12 0 4675.457 5991.283 6018.238 9600.000 -SIMU 1976 3 13 24 0 5412.477 6752.256 6779.295 9600.000 -SIMU 1976 3 14 12 0 5441.626 6522.768 6578.951 11520.00 -SIMU 1976 3 14 24 0 6084.311 7198.646 7206.401 11520.00 -SIMU 1976 3 15 12 0 6067.787 6967.828 7024.758 7200.000 -SIMU 1976 3 15 24 0 6255.849 6990.056 7098.378 7200.000 -SIMU 1976 3 16 12 0 6220.770 6828.191 6856.617 5520.000 -SIMU 1976 3 16 24 0 7004.281 7778.937 7943.517 5520.000 -SIMU 1976 3 17 12 0 6931.859 7551.336 7641.298 4512.000 -SIMU 1976 3 17 24 0 7275.872 7853.927 8075.415 4512.000 -SIMU 1976 3 18 12 0 7215.516 7689.605 7997.244 4464.000 -SIMU 1976 3 18 24 0 7592.294 8056.001 8200.375 4464.000 -SIMU 1976 3 19 12 0 7459.372 7824.978 7833.936 4920.000 -SIMU 1976 3 19 24 0 7421.499 7710.471 7721.106 4920.000 -SIMU 1976 3 20 12 0 7246.257 7471.947 7471.947 5472.000 -SIMU 1976 3 20 24 0 7149.289 7325.435 7325.435 5472.000 -SIMU 1976 3 21 12 0 6973.513 7111.144 7111.143 5016.000 -SIMU 1976 3 21 24 0 6878.085 6985.757 6985.757 5016.000 -SIMU 1976 3 22 12 0 6709.121 6793.473 6793.473 3768.000 -SIMU 1976 3 22 24 0 6614.783 6680.972 6680.972 3768.000 -SIMU 1976 3 23 12 0 6451.173 6503.203 6503.203 3000.000 -SIMU 1976 3 23 24 0 6358.853 6399.835 6399.835 3000.000 -SIMU 1976 3 24 12 0 6200.556 6232.910 6232.910 2592.000 -SIMU 1976 3 24 24 0 6108.588 6134.192 6134.193 2592.000 -SIMU 1976 3 25 12 0 5955.584 5975.905 5975.905 2496.000 -SIMU 1976 3 25 24 0 5865.451 5881.626 5881.626 2496.000 -SIMU 1976 3 26 12 0 5724.800 5737.979 5741.190 2280.000 -SIMU 1976 3 26 24 0 5715.033 5728.673 5749.997 2280.000 -SIMU 1976 3 27 12 0 5612.880 5625.292 5625.292 4008.000 -SIMU 1976 3 27 24 0 5530.031 5540.180 5540.180 4008.000 -SIMU 1976 3 28 12 0 5394.651 5402.991 5402.991 4152.000 -SIMU 1976 3 28 24 0 5317.143 5324.122 5327.223 4152.000 -SIMU 1976 3 29 12 0 5324.132 5335.811 5367.000 3336.000 -SIMU 1976 3 29 24 0 5782.515 6035.415 6549.230 3336.000 -SIMU 1976 3 30 12 0 7224.028 9555.914 9767.674 5976.000 -SIMU 1976 3 30 24 0 7472.900 9480.323 9480.323 5976.000 -SIMU 1976 3 31 12 0 7316.518 8884.538 8884.539 15264.00 -SIMU 1976 3 31 24 0 7238.360 8464.639 8464.639 15264.00 -SIMU 1976 4 1 12 0 7075.693 8036.026 8036.025 19440.00 -SIMU 1976 4 1 24 0 6987.918 7741.145 7741.146 19440.00 -SIMU 1976 4 2 12 0 6814.303 7406.119 7406.119 15384.00 -SIMU 1976 4 2 24 0 6706.199 7172.103 7172.103 15384.00 -SIMU 1976 4 3 12 0 6523.954 6891.536 6891.536 9432.000 -SIMU 1976 4 3 24 0 6412.716 6703.433 6703.432 9432.000 -SIMU 1976 4 4 12 0 6241.489 6472.034 6472.034 7104.000 -SIMU 1976 4 4 24 0 6134.128 6317.496 6317.497 7104.000 -SIMU 1976 4 5 12 0 5965.509 6111.832 6111.831 5928.000 -SIMU 1976 4 5 24 0 5856.542 5973.715 5973.715 5928.000 -SIMU 1976 4 6 12 0 5690.369 5784.559 5784.559 5280.000 -SIMU 1976 4 6 24 0 5581.546 5657.571 5657.572 5280.000 -SIMU 1976 4 7 12 0 5417.036 5478.667 5478.667 4680.000 -SIMU 1976 4 7 24 0 5307.307 5357.499 5357.499 4680.000 -SIMU 1976 4 8 12 0 5159.871 5200.943 5200.944 4152.000 -SIMU 1976 4 8 24 0 5050.623 5084.400 5084.399 4152.000 -SIMU 1976 4 9 12 0 4908.787 4936.705 4936.705 3816.000 -SIMU 1976 4 9 24 0 4812.399 4835.593 4835.593 3816.000 -SIMU 1976 4 10 12 0 4655.151 4674.522 4674.522 3528.000 -SIMU 1976 4 10 24 0 4527.910 4544.170 4544.170 3528.000 -SIMU 1976 4 11 12 0 4396.500 4410.582 4413.267 3408.000 -SIMU 1976 4 11 24 0 4302.192 4314.207 4314.207 3408.000 -SIMU 1976 4 12 12 0 4188.302 4198.553 4198.553 3072.000 -SIMU 1976 4 12 24 0 4096.929 4105.714 4105.714 3072.000 -SIMU 1976 4 13 12 0 3968.454 3975.816 3975.816 2832.000 -SIMU 1976 4 13 24 0 3858.228 3864.146 3864.147 2832.000 -SIMU 1976 4 14 12 0 3732.158 3736.671 3736.671 2760.000 -SIMU 1976 4 14 24 0 3713.524 3763.240 3847.532 2760.000 -SIMU 1976 4 15 12 0 4213.024 4442.344 4496.130 2736.000 -SIMU 1976 4 15 24 0 4250.309 4440.435 4440.435 2736.000 -SIMU 1976 4 16 12 0 4128.880 4279.158 4279.159 2640.000 -SIMU 1976 4 16 24 0 4015.025 4134.121 4134.122 2640.000 -SIMU 1976 4 17 12 0 4162.041 4388.927 4478.631 2712.000 -SIMU 1976 4 17 24 0 5332.612 6024.311 6146.051 2712.000 -SIMU 1976 4 18 12 0 7164.555 10746.90 11595.92 3960.000 -SIMU 1976 4 18 24 0 7628.225 11163.71 11163.71 3960.000 -SIMU 1976 4 19 12 0 7486.661 10410.07 10410.07 5832.000 -SIMU 1976 4 19 24 0 7403.147 9832.930 9832.930 5832.000 -SIMU 1976 4 20 12 0 7221.528 9252.327 9256.658 6192.000 -SIMU 1976 4 20 24 0 8600.985 11659.31 11828.30 6192.000 -SIMU 1976 4 21 12 0 9639.791 13331.55 13402.07 6000.000 -SIMU 1976 4 21 24 0 9924.361 13559.89 13559.89 6000.000 -SIMU 1976 4 22 12 0 9659.603 12586.00 12586.00 6192.000 -SIMU 1976 4 22 24 0 9506.230 11871.69 11871.69 6192.000 -SIMU 1976 4 23 12 0 9431.766 12162.72 13825.13 6120.000 -SIMU 1976 4 23 24 0 10365.31 15744.01 16081.51 6120.000 -SIMU 1976 4 24 12 0 10826.79 16290.42 16611.88 6768.000 -SIMU 1976 4 24 24 0 11493.72 16030.07 16058.38 6768.000 -SIMU 1976 4 25 12 0 11736.68 15501.91 15801.95 8952.000 -SIMU 1976 4 25 24 0 12024.70 15226.28 15226.28 8952.000 -SIMU 1976 4 26 12 0 11697.15 14233.31 14233.31 11664.00 -SIMU 1976 4 26 24 0 11519.66 13534.45 13534.45 11664.00 -SIMU 1976 4 27 12 0 11173.10 12778.73 12778.73 10896.00 -SIMU 1976 4 27 24 0 10975.75 12259.70 12259.70 10896.00 -SIMU 1976 4 28 12 0 10633.20 11663.72 11663.72 8832.000 -SIMU 1976 4 28 24 0 10444.50 11274.92 11274.92 8832.000 -SIMU 1976 4 29 12 0 10113.05 10785.08 10785.08 7512.000 -SIMU 1976 4 29 24 0 9910.364 10456.66 10456.66 7512.000 -SIMU 1976 4 30 12 0 9582.726 10028.91 10028.91 6864.000 -SIMU 1976 4 30 24 0 9389.166 9755.379 9755.379 6864.000 -SIMU 1976 5 1 12 0 9082.641 9384.731 9384.731 6432.000 -SIMU 1976 5 1 24 0 8901.657 9152.135 9152.135 6432.000 -SIMU 1976 5 2 12 0 9503.853 9853.097 9976.797 5928.000 -SIMU 1976 5 2 24 0 9716.493 10048.33 10048.33 5928.000 -SIMU 1976 5 3 12 0 9411.116 9680.611 9680.612 5400.000 -SIMU 1976 5 3 24 0 9216.255 9436.145 9436.145 5400.000 -SIMU 1976 5 4 12 0 8910.540 9090.828 9090.829 4944.000 -SIMU 1976 5 4 24 0 8723.168 8871.730 8871.730 4944.000 -SIMU 1976 5 5 12 0 8424.436 8547.482 8547.482 4536.000 -SIMU 1976 5 5 24 0 8232.727 8335.167 8335.166 4536.000 -SIMU 1976 5 6 12 0 7944.313 8030.040 8030.040 4344.000 -SIMU 1976 5 6 24 0 7758.746 7830.853 7830.853 4344.000 -SIMU 1976 5 7 12 0 7502.618 7563.573 7563.572 3912.000 -SIMU 1976 5 7 24 0 7343.863 7395.641 7395.641 3912.000 -SIMU 1976 5 8 12 0 7109.180 7153.368 7153.368 3720.000 -SIMU 1976 5 8 24 0 6952.368 6990.245 6990.245 3720.000 -SIMU 1976 5 9 12 0 6709.893 6742.497 6742.497 3576.000 -SIMU 1976 5 9 24 0 6544.151 6572.327 6572.327 3576.000 -SIMU 1976 5 10 12 0 6313.746 6338.182 6338.182 3456.000 -SIMU 1976 5 10 24 0 6163.176 6184.440 6184.440 3456.000 -SIMU 1976 5 11 12 0 5949.690 5968.250 5968.250 3360.000 -SIMU 1976 5 11 24 0 5805.403 5821.648 5821.648 3360.000 -SIMU 1976 5 12 12 0 5606.486 5620.741 5620.741 3192.000 -SIMU 1976 5 12 24 0 5475.732 5487.095 5488.084 3192.000 -SIMU 1976 5 13 12 0 5921.376 5965.900 6166.316 3312.000 -SIMU 1976 5 13 24 0 6240.886 6296.999 6297.000 3312.000 -SIMU 1976 5 14 12 0 6074.830 6120.905 6120.905 3336.000 -SIMU 1976 5 14 24 0 5974.801 6012.826 6012.826 3336.000 -SIMU 1976 5 15 12 0 5821.232 5853.288 5861.953 3192.000 -SIMU 1976 5 15 24 0 5841.707 5870.807 5874.759 3192.000 -SIMU 1976 5 16 12 0 6133.264 6211.042 6540.570 3888.000 -SIMU 1976 5 16 24 0 7443.866 7770.854 7841.980 3888.000 -SIMU 1976 5 17 12 0 7393.988 7657.070 7657.070 6312.000 -SIMU 1976 5 17 24 0 7248.306 7455.735 7455.735 6312.000 -SIMU 1976 5 18 12 0 7016.071 7180.006 7180.006 8064.000 -SIMU 1976 5 18 24 0 6864.927 6994.829 6994.828 8064.000 -SIMU 1976 5 19 12 0 6632.440 6735.670 6735.670 7296.000 -SIMU 1976 5 19 24 0 6473.555 6555.850 6555.850 7296.000 -SIMU 1976 5 20 12 0 6242.143 6307.977 6307.977 6264.000 -SIMU 1976 5 20 24 0 6078.955 6131.816 6131.816 6264.000 -SIMU 1976 5 21 12 0 5863.405 5906.022 5906.022 5592.000 -SIMU 1976 5 21 24 0 5725.353 5759.856 5759.856 5592.000 -SIMU 1976 5 22 12 0 5548.791 5578.020 5627.149 5208.000 -SIMU 1976 5 22 24 0 6055.835 6113.732 6209.580 5208.000 -SIMU 1976 5 23 12 0 6378.099 6441.832 6473.352 5976.000 -SIMU 1976 5 23 24 0 6387.691 6444.794 6459.470 5976.000 -SIMU 1976 5 24 12 0 6229.678 6278.872 6278.872 6672.000 -SIMU 1976 5 24 24 0 6120.713 6162.870 6162.870 6672.000 -SIMU 1976 5 25 12 0 5929.489 5965.768 5965.768 6312.000 -SIMU 1976 5 25 24 0 5796.314 5827.657 5827.657 6312.000 -SIMU 1976 5 26 12 0 5602.609 5629.787 5629.786 5640.000 -SIMU 1976 5 26 24 0 5469.314 5492.957 5492.957 5640.000 -SIMU 1976 5 27 12 0 5284.036 5304.670 5304.670 5088.000 -SIMU 1976 5 27 24 0 5158.005 5176.063 5176.063 5088.000 -SIMU 1976 5 28 12 0 4983.002 4998.846 4998.846 4728.000 -SIMU 1976 5 28 24 0 4909.798 4945.371 5005.282 4728.000 -SIMU 1976 5 29 12 0 5589.246 5941.422 6028.131 4704.000 -SIMU 1976 5 29 24 0 5797.516 6205.313 6205.313 4704.000 -SIMU 1976 5 30 12 0 5633.561 5950.626 5950.626 6552.000 -SIMU 1976 5 30 24 0 5528.438 5775.097 5775.097 6552.000 -SIMU 1976 5 31 12 0 5369.578 5561.591 5561.591 7776.000 -SIMU 1976 5 31 24 0 5268.968 5418.550 5418.550 7776.000 -SIMU 1976 6 1 12 0 5117.311 5233.938 5233.937 6648.000 -SIMU 1976 6 1 24 0 5018.680 5109.698 5109.698 6648.000 -SIMU 1976 6 2 12 0 4868.513 4939.623 4939.624 5496.000 -SIMU 1976 6 2 24 0 4762.963 4818.588 4818.588 5496.000 -SIMU 1976 6 3 12 0 4608.494 4652.067 4652.067 4728.000 -SIMU 1976 6 3 24 0 4493.570 4527.758 4527.758 4728.000 -SIMU 1976 6 4 12 0 4338.532 4365.403 4365.403 4200.000 -SIMU 1976 6 4 24 0 4224.821 4245.983 4245.983 4200.000 -SIMU 1976 6 5 12 0 4074.822 4091.525 4091.525 3864.000 -SIMU 1976 6 5 24 0 3962.500 3975.717 3975.717 3864.000 -SIMU 1976 6 6 12 0 3821.470 3831.957 3831.957 3600.000 -SIMU 1976 6 6 24 0 3719.002 3727.348 3727.348 3600.000 -SIMU 1976 6 7 12 0 3589.172 3595.836 3595.836 3408.000 -SIMU 1976 6 7 24 0 3492.674 3498.013 3498.013 3408.000 -SIMU 1976 6 8 12 0 3369.697 3373.993 3373.993 3216.000 -SIMU 1976 6 8 24 0 3274.981 3278.451 3278.451 3216.000 -SIMU 1976 6 9 12 0 3150.390 3153.204 3153.204 3048.000 -SIMU 1976 6 9 24 0 3044.716 3046.042 3046.042 3048.000 -SIMU 1976 6 10 12 0 3291.709 3459.219 3513.617 3024.000 -SIMU 1976 6 10 24 0 3518.919 3747.066 3747.066 3024.000 -SIMU 1976 6 11 12 0 3413.929 3595.808 3595.808 3048.000 -SIMU 1976 6 11 24 0 3344.455 3489.951 3489.951 3048.000 -SIMU 1976 6 12 12 0 3228.865 3345.692 3345.692 3024.000 -SIMU 1976 6 12 24 0 3221.686 3381.008 3396.237 3024.000 -SIMU 1976 6 13 12 0 3343.770 3607.325 3607.325 2808.000 -SIMU 1976 6 13 24 0 3731.925 4195.831 4273.231 2808.000 -SIMU 1976 6 14 12 0 4313.558 4992.616 4992.689 3264.000 -SIMU 1976 6 14 24 0 4236.824 4773.909 4773.984 3264.000 -SIMU 1976 6 15 12 0 4153.155 4580.737 4592.651 3120.000 -SIMU 1976 6 15 24 0 4062.318 4402.652 4402.652 3120.000 -SIMU 1976 6 16 12 0 3938.319 4210.056 4210.056 3408.000 -SIMU 1976 6 16 24 0 3855.712 4073.456 4073.456 3408.000 -SIMU 1976 6 17 12 0 3734.820 3909.976 3909.976 3192.000 -SIMU 1976 6 17 24 0 3637.509 3778.990 3778.990 3192.000 -SIMU 1976 6 18 12 0 3526.016 3640.807 3640.861 2664.000 -SIMU 1976 6 18 24 0 3452.074 3545.638 3545.638 2664.000 -SIMU 1976 6 19 12 0 3343.906 3420.537 3420.537 2424.000 -SIMU 1976 6 19 24 0 3263.694 3326.768 3326.768 2424.000 -SIMU 1976 6 20 12 0 3155.298 3207.479 3207.478 2208.000 -SIMU 1976 6 20 24 0 3066.159 3109.553 3109.553 2208.000 -SIMU 1976 6 21 12 0 2960.541 2996.813 2996.812 2040.000 -SIMU 1976 6 21 24 0 2882.089 2912.564 2912.564 2040.000 -SIMU 1976 6 22 12 0 2782.793 2808.525 2808.525 1896.000 -SIMU 1976 6 22 24 0 2701.439 2723.275 2723.275 1896.000 -SIMU 1976 6 23 12 0 2603.720 2622.335 2622.335 1752.000 -SIMU 1976 6 23 24 0 2524.560 2540.502 2540.502 1752.000 -SIMU 1976 6 24 12 0 2506.310 2572.711 2636.606 1704.000 -SIMU 1976 6 24 24 0 2803.375 3035.986 3079.804 1704.000 -SIMU 1976 6 25 12 0 2754.266 2936.758 2936.758 1632.000 -SIMU 1976 6 25 24 0 2686.124 2828.623 2828.623 1632.000 -SIMU 1976 6 26 12 0 2606.177 2717.578 2717.578 1560.000 -SIMU 1976 6 26 24 0 2561.369 2656.339 2677.624 1560.000 -SIMU 1976 6 27 12 0 2647.217 2752.256 2752.709 1512.000 -SIMU 1976 6 27 24 0 2713.907 2819.464 2860.134 1512.000 -SIMU 1976 6 28 12 0 3036.492 3202.362 3233.577 1416.000 -SIMU 1976 6 28 24 0 3110.139 3268.096 3268.096 1416.000 -SIMU 1976 6 29 12 0 3023.118 3145.993 3145.993 1368.000 -SIMU 1976 6 29 24 0 2956.332 3051.979 3051.979 1368.000 -SIMU 1976 6 30 12 0 2866.452 2940.957 2940.958 1416.000 -SIMU 1976 6 30 24 0 2798.310 2856.396 2856.396 1416.000 -SIMU 1976 7 1 12 0 2712.273 2757.601 2757.601 1368.000 -SIMU 1976 7 1 24 0 2644.846 2680.256 2680.256 1368.000 -SIMU 1976 7 2 12 0 2569.992 2597.689 2597.689 1248.000 -SIMU 1976 7 2 24 0 2521.579 2543.271 2543.271 1248.000 -SIMU 1976 7 3 12 0 2442.126 2459.143 2459.143 1200.000 -SIMU 1976 7 3 24 0 2360.918 2374.291 2374.291 1200.000 -SIMU 1976 7 4 12 0 2276.082 2286.612 2286.612 1128.000 -SIMU 1976 7 4 24 0 2215.493 2223.803 2223.803 1128.000 -SIMU 1976 7 5 12 0 2142.424 2148.998 2148.998 1056.000 -SIMU 1976 7 5 24 0 2081.151 2086.365 2086.365 1056.000 -SIMU 1976 7 6 12 0 2003.279 2007.428 2007.429 1008.000 -SIMU 1976 7 6 24 0 1930.496 1933.807 1933.807 1008.000 -SIMU 1976 7 7 12 0 1860.211 1862.865 1862.865 1008.000 -SIMU 1976 7 7 24 0 1801.562 1803.067 1803.067 1008.000 -SIMU 1976 7 8 12 0 1727.611 1728.135 1728.135 1008.000 -SIMU 1976 7 8 24 0 1654.591 1655.059 1655.059 1008.000 -SIMU 1976 7 9 12 0 1580.965 1581.384 1581.384 960.0000 -SIMU 1976 7 9 24 0 1521.349 1521.723 1521.723 960.0000 -SIMU 1976 7 10 12 0 1448.820 1449.155 1449.155 912.0000 -SIMU 1976 7 10 24 0 1375.131 1375.431 1375.431 912.0000 -SIMU 1976 7 11 12 0 1304.743 1305.011 1305.011 888.0000 -SIMU 1976 7 11 24 0 1248.129 1248.368 1248.368 888.0000 -SIMU 1976 7 12 12 0 1185.909 1186.123 1186.123 816.0000 -SIMU 1976 7 12 24 0 1126.353 1126.545 1126.545 816.0000 -SIMU 1976 7 13 12 0 1064.962 1065.078 1065.078 792.0000 -SIMU 1976 7 13 24 0 1008.634 1008.634 1008.634 792.0000 -SIMU 1976 7 14 12 0 947.6622 947.6622 947.6622 768.0000 -SIMU 1976 7 14 24 0 887.4125 887.4125 887.4125 768.0000 -SIMU 1976 7 15 12 0 835.6957 835.6957 835.6957 792.0000 -SIMU 1976 7 15 24 0 817.9781 823.5078 823.8835 792.0000 -SIMU 1976 7 16 12 0 788.2032 796.4568 796.4568 816.0000 -SIMU 1976 7 16 24 0 740.7318 748.1143 748.1143 816.0000 -SIMU 1976 7 17 12 0 692.7055 699.3084 699.3083 840.0000 -SIMU 1976 7 17 24 0 647.5076 653.4134 653.4134 840.0000 -SIMU 1976 7 18 12 0 602.0175 607.2998 607.2998 816.0000 -SIMU 1976 7 18 24 0 558.3641 563.0889 563.0889 816.0000 -SIMU 1976 7 19 12 0 524.3542 528.5801 528.5801 792.0000 -SIMU 1976 7 19 24 0 504.0474 507.8271 507.8271 792.0000 -SIMU 1976 7 20 12 0 479.9358 483.4558 488.4977 816.0000 -SIMU 1976 7 20 24 0 480.9326 484.4180 503.8568 816.0000 -SIMU 1976 7 21 12 0 486.5504 489.6679 489.6679 792.0000 -SIMU 1976 7 21 24 0 479.3178 482.1062 482.1063 792.0000 -SIMU 1976 7 22 12 0 471.2202 473.7142 473.7142 792.0000 -SIMU 1976 7 22 24 0 459.2761 461.5067 461.5067 792.0000 -SIMU 1976 7 23 12 0 436.4136 438.4089 438.4089 816.0000 -SIMU 1976 7 23 24 0 408.7779 410.5625 410.5625 816.0000 -SIMU 1976 7 24 12 0 372.2911 373.8872 373.8872 768.0000 -SIMU 1976 7 24 24 0 327.2109 328.6385 328.6385 768.0000 -SIMU 1976 7 25 12 0 286.3557 287.6327 287.6327 720.0000 -SIMU 1976 7 25 24 0 250.3043 251.4465 251.4465 720.0000 -SIMU 1976 7 26 12 0 229.2224 231.0525 237.9428 720.0000 -SIMU 1976 7 26 24 0 230.0116 232.8386 232.8386 720.0000 -SIMU 1976 7 27 12 0 210.4846 213.0132 213.0132 648.0000 -SIMU 1976 7 27 24 0 185.2401 189.8054 199.3956 648.0000 -SIMU 1976 7 28 12 0 355.7942 502.2871 564.0080 1272.000 -SIMU 1976 7 28 24 0 389.4540 525.8757 525.8757 1272.000 -SIMU 1976 7 29 12 0 379.2825 492.8959 492.8959 1896.000 -SIMU 1976 7 29 24 0 359.0034 454.1112 454.1112 1896.000 -SIMU 1976 7 30 12 0 331.6174 411.6410 411.6410 1296.000 -SIMU 1976 7 30 24 0 304.1752 371.9807 375.6659 1296.000 -SIMU 1976 7 31 12 0 299.1547 356.9792 356.9792 984.0000 -SIMU 1976 7 31 24 0 294.6993 344.0361 344.0361 984.0000 -SIMU 1976 8 1 12 0 284.0786 326.3608 326.3608 864.0000 -SIMU 1976 8 1 24 0 257.2543 293.6428 293.6428 864.0000 -SIMU 1976 8 2 12 0 229.6317 261.0710 261.0710 744.0000 -SIMU 1976 8 2 24 0 203.5243 230.7866 230.7866 744.0000 -SIMU 1976 8 3 12 0 177.7175 201.4372 201.4372 672.0000 -SIMU 1976 8 3 24 0 152.2990 172.9997 172.9998 672.0000 -SIMU 1976 8 4 12 0 125.5375 143.6541 143.6541 624.0000 -SIMU 1976 8 4 24 0 96.83620 112.7313 112.7313 624.0000 -SIMU 1976 8 5 12 0 70.62148 83.98846 83.98846 552.0000 -SIMU 1976 8 5 24 0 48.83453 59.95349 59.95348 552.0000 -SIMU 1976 8 6 12 0 33.63858 43.58369 43.58369 552.0000 -SIMU 1976 8 6 24 0 17.44626 26.34144 26.34144 552.0000 -SIMU 1976 8 7 12 0 9.618545 17.57463 17.57463 528.0000 -SIMU 1976 8 7 24 0 5.715816 12.83196 12.83196 528.0000 -SIMU 1976 8 8 12 0 1.375276 7.740143 7.740143 504.0000 -SIMU 1976 8 8 24 0 0.000000 5.692911 5.692911 504.0000 -SIMU 1976 8 9 12 0 0.000000 5.091894 5.091894 480.0000 -SIMU 1976 8 9 24 0 0.000000 4.554329 4.554329 480.0000 -SIMU 1976 8 10 12 0 0.000000 4.073516 4.073516 456.0000 -SIMU 1976 8 10 24 0 0.000000 3.643464 3.643464 456.0000 -SIMU 1976 8 11 12 0 0.000000 3.258813 3.258813 504.0000 -SIMU 1976 8 11 24 0 0.000000 2.914772 2.914772 504.0000 -SIMU 1976 8 12 12 0 0.000000 2.607051 2.607051 528.0000 -SIMU 1976 8 12 24 0 0.000000 2.331817 2.331817 528.0000 -SIMU 1976 8 13 12 0 0.000000 2.085641 2.085641 480.0000 -SIMU 1976 8 13 24 0 0.000000 1.865454 1.865454 480.0000 -SIMU 1976 8 14 12 0 3.306299 5.189642 8.569720 504.0000 -SIMU 1976 8 14 24 0 4.317553 6.061530 6.061530 504.0000 -SIMU 1976 8 15 12 0 2.381328 3.941188 3.941188 528.0000 -SIMU 1976 8 15 24 0 0.000000 1.395181 1.395181 528.0000 -SIMU 1976 8 16 12 0 0.000000 1.247888 1.247888 504.0000 -SIMU 1976 8 16 24 0 0.000000 1.116145 1.116145 504.0000 -SIMU 1976 8 17 12 0 27.85040 45.21229 46.50558 480.0000 -SIMU 1976 8 17 24 0 29.45068 45.73265 45.73265 480.0000 -SIMU 1976 8 18 12 0 27.14911 41.71215 41.71215 456.0000 -SIMU 1976 8 18 24 0 21.66637 34.69194 34.69194 456.0000 -SIMU 1976 8 19 12 0 16.10777 27.75819 27.75819 432.0000 -SIMU 1976 8 19 24 0 10.52678 20.94723 20.94723 432.0000 -SIMU 1976 8 20 12 0 5.192156 14.51250 14.51250 408.0000 -SIMU 1976 8 20 24 0 0.6898000 9.026163 9.026163 408.0000 -SIMU 1976 8 21 12 0 0.000000 7.456270 7.456270 408.0000 -SIMU 1976 8 21 24 0 0.000000 6.669090 6.669090 408.0000 -SIMU 1976 8 22 12 0 0.000000 5.965015 5.965015 384.0000 -SIMU 1976 8 22 24 0 0.000000 5.335272 5.335272 384.0000 -SIMU 1976 8 23 12 0 0.000000 4.772013 4.772013 360.0000 -SIMU 1976 8 23 24 0 0.000000 4.268219 4.268219 360.0000 -SIMU 1976 8 24 12 0 0.000000 3.817610 3.817610 336.0000 -SIMU 1976 8 24 24 0 0.000000 3.414574 3.414574 336.0000 -SIMU 1976 8 25 12 0 0.000000 3.054089 3.054089 360.0000 -SIMU 1976 8 25 24 0 30.53471 54.81184 62.28218 360.0000 -SIMU 1976 8 26 12 0 37.82723 62.75433 62.99365 408.0000 -SIMU 1976 8 26 24 0 37.40852 59.71318 59.71318 408.0000 -SIMU 1976 8 27 12 0 32.02015 51.97005 51.97005 360.0000 -SIMU 1976 8 27 24 0 25.22998 43.07370 43.07370 360.0000 -SIMU 1976 8 28 12 0 18.50882 34.46874 34.46874 336.0000 -SIMU 1976 8 28 24 0 11.87564 26.15062 26.15062 336.0000 -SIMU 1976 8 29 12 0 6.554318 19.32225 19.32225 336.0000 -SIMU 1976 8 29 24 0 2.632745 14.05273 14.05273 336.0000 -SIMU 1976 8 30 12 0 4.2170662E-02 10.25652 10.25652 312.0000 -SIMU 1976 8 30 24 0 0.000000 9.135987 9.135987 312.0000 -SIMU 1976 8 31 12 0 0.000000 8.171477 8.171477 360.0000 -SIMU 1976 8 31 24 0 0.000000 7.308790 7.308790 360.0000 -SIMU 1976 9 1 12 0 0.000000 6.537181 6.537181 336.0000 -SIMU 1976 9 1 24 0 0.000000 5.847033 5.847033 336.0000 -SIMU 1976 9 2 12 0 0.000000 5.229745 5.229745 360.0000 -SIMU 1976 9 2 24 0 0.000000 4.677627 4.677627 360.0000 -SIMU 1976 9 3 12 0 0.000000 4.183796 4.183796 336.0000 -SIMU 1976 9 3 24 0 0.000000 3.742100 3.742100 336.0000 -SIMU 1976 9 4 12 0 0.000000 3.347037 3.347037 336.0000 -SIMU 1976 9 4 24 0 0.000000 2.993680 2.993680 336.0000 -SIMU 1976 9 5 12 0 0.000000 2.677629 2.677629 312.0000 -SIMU 1976 9 5 24 0 0.000000 2.394944 2.394944 312.0000 -SIMU 1976 9 6 12 0 0.000000 2.142103 2.142103 312.0000 -SIMU 1976 9 6 24 0 0.000000 1.915955 1.915955 312.0000 -SIMU 1976 9 7 12 0 0.000000 1.713682 1.713682 288.0000 -SIMU 1976 9 7 24 0 0.000000 1.532764 1.532764 288.0000 -SIMU 1976 9 8 12 0 0.000000 1.370945 1.370945 288.0000 -SIMU 1976 9 8 24 0 0.000000 1.226211 1.226211 288.0000 -SIMU 1976 9 9 12 0 0.000000 1.096756 1.096756 288.0000 -SIMU 1976 9 9 24 0 0.000000 0.9809685 0.9809685 288.0000 -SIMU 1976 9 10 12 0 0.000000 0.8774048 0.8774048 312.0000 -SIMU 1976 9 10 24 0 0.000000 0.7847747 0.7847747 312.0000 -SIMU 1976 9 11 12 0 0.000000 0.7019238 0.7019238 336.0000 -SIMU 1976 9 11 24 0 0.000000 0.6278196 0.6278196 336.0000 -SIMU 1976 9 12 12 0 0.000000 0.5615390 0.5615390 312.0000 -SIMU 1976 9 12 24 0 0.000000 0.5022559 0.5022559 312.0000 -SIMU 1976 9 13 12 0 0.000000 0.4492313 0.4492313 288.0000 -SIMU 1976 9 13 24 0 0.000000 0.4018047 0.4018047 288.0000 -SIMU 1976 9 14 12 0 0.000000 0.3593851 0.3593851 288.0000 -SIMU 1976 9 14 24 0 0.000000 0.3214438 0.3214438 288.0000 -SIMU 1976 9 15 12 0 0.000000 0.2875081 0.2875081 288.0000 -SIMU 1976 9 15 24 0 0.000000 0.2571551 0.2571551 288.0000 -SIMU 1976 9 16 12 0 0.000000 0.2300065 0.2300065 288.0000 -SIMU 1976 9 16 24 0 0.000000 0.2057241 0.2057241 288.0000 -SIMU 1976 9 17 12 0 0.000000 0.1840052 0.1840052 288.0000 -SIMU 1976 9 17 24 0 0.000000 4.9913384E-02 4.9913384E-02 288.0000 -SIMU 1976 9 18 12 0 0.000000 0.000000 0.000000 288.0000 -SIMU 1976 9 18 24 0 0.000000 0.000000 0.000000 288.0000 -SIMU 1976 9 19 12 0 11.82189 14.95630 20.28834 336.0000 -SIMU 1976 9 19 24 0 25.88178 31.69412 31.69412 336.0000 -SIMU 1976 9 20 12 0 24.66236 29.86107 29.86107 384.0000 -SIMU 1976 9 20 24 0 19.24643 23.89630 23.89630 384.0000 -SIMU 1976 9 21 12 0 14.29944 18.45841 18.45841 408.0000 -SIMU 1976 9 21 24 0 10.10197 13.82186 13.82186 408.0000 -SIMU 1976 9 22 12 0 7.246496 10.57367 10.57367 384.0000 -SIMU 1976 9 22 24 0 4.182612 7.158529 7.158529 384.0000 -SIMU 1976 9 23 12 0 0.8932837 3.555027 3.555026 336.0000 -SIMU 1976 9 23 24 0 0.000000 2.380735 2.380735 336.0000 -SIMU 1976 9 24 12 0 0.000000 2.129394 2.129394 312.0000 -SIMU 1976 9 24 24 0 0.000000 1.904588 1.904588 312.0000 -SIMU 1976 9 25 12 0 0.000000 1.703515 1.703515 312.0000 -SIMU 1976 9 25 24 0 0.000000 1.523670 1.523670 312.0000 -SIMU 1976 9 26 12 0 0.000000 1.362812 1.362812 288.0000 -SIMU 1976 9 26 24 0 0.000000 1.218936 1.218936 288.0000 -SIMU 1976 9 27 12 0 0.1548235 1.245073 1.393924 288.0000 -SIMU 1976 9 27 24 0 0.4264256 1.401574 1.401574 288.0000 -SIMU 1976 9 28 12 0 0.4221386 1.294338 1.294338 288.0000 -SIMU 1976 9 28 24 0 0.4178956 1.198015 1.198015 288.0000 -SIMU 1976 9 29 12 0 0.4136944 1.111454 1.111454 312.0000 -SIMU 1976 9 29 24 0 0.2518055 0.8759007 0.8759007 312.0000 -SIMU 1976 9 30 12 0 0.000000 0.5582076 0.5582076 288.0000 -SIMU 1976 9 30 24 0 0.000000 0.4992760 0.4992760 288.0000 -SIMU 1976 10 1 12 0 0.000000 0.4465660 0.4465660 288.0000 -SIMU 1976 10 1 24 0 0.000000 0.3994207 0.3994207 288.0000 -SIMU 1976 10 2 12 0 0.000000 0.3572528 0.3572528 0.000000 -SIMU 1976 10 2 24 0 0.000000 0.3195366 0.3195366 0.000000 -SIMU 1976 10 3 12 0 0.000000 0.2858022 0.2858022 0.000000 -SIMU 1976 10 3 24 0 0.000000 0.2556292 0.2556292 0.000000 -SIMU 1976 10 4 12 0 1.616946 1.943475 5.741490 0.000000 -SIMU 1976 10 4 24 0 8.951859 9.516360 16.73438 0.000000 -SIMU 1976 10 5 12 0 13.37803 13.92399 15.55124 0.000000 -SIMU 1976 10 5 24 0 12.00275 12.49107 12.49107 0.000000 -SIMU 1976 10 6 12 0 10.52446 10.96123 10.96123 0.000000 -SIMU 1976 10 6 24 0 10.28052 10.67118 10.67118 0.000000 -SIMU 1976 10 7 12 0 9.744522 10.09394 10.09394 0.000000 -SIMU 1976 10 7 24 0 2.493862 2.806388 2.806388 0.000000 -SIMU 1976 10 8 12 0 0.000000 0.2795316 0.2795316 0.000000 -SIMU 1976 10 8 24 0 0.000000 0.2500207 0.2500207 0.000000 -SIMU 1976 10 9 12 0 0.000000 0.2236253 0.2236253 0.000000 -SIMU 1976 10 9 24 0 0.000000 0.2000165 0.2000165 0.000000 -SIMU 1976 10 10 12 0 0.000000 0.1789002 0.1789002 0.000000 -SIMU 1976 10 10 24 0 0.000000 7.0297145E-03 7.0297145E-03 0.000000 -SIMU 1976 10 11 12 0 0.000000 0.000000 0.000000 0.000000 -SIMU 1976 10 11 24 0 0.000000 0.000000 0.000000 0.000000 -SIMU 1976 10 12 12 0 0.000000 0.000000 0.000000 0.000000 -SIMU 1976 10 12 24 0 0.000000 0.000000 0.000000 0.000000 -SIMU 1976 10 13 12 0 0.000000 0.000000 0.000000 0.000000 -SIMU 1976 10 13 24 0 0.000000 0.000000 0.000000 0.000000 -SIMU 1976 10 14 12 0 0.000000 0.000000 0.000000 0.000000 -SIMU 1976 10 14 24 0 0.000000 0.000000 0.000000 0.000000 -SIMU 1976 10 15 12 0 0.000000 0.000000 0.000000 0.000000 -SIMU 1976 10 15 24 0 0.000000 0.000000 0.000000 0.000000 -SIMU 1976 10 16 12 0 0.000000 0.000000 0.000000 0.000000 -SIMU 1976 10 16 24 0 0.000000 0.000000 0.000000 0.000000 -SIMU 1976 10 17 12 0 0.000000 0.000000 0.000000 0.000000 -SIMU 1976 10 17 24 0 0.000000 0.000000 0.000000 0.000000 -SIMU 1976 10 18 12 0 0.000000 0.000000 0.000000 0.000000 -SIMU 1976 10 18 24 0 0.1295344 0.1295344 0.3030436 0.000000 -SIMU 1976 10 19 12 0 1.904068 1.904068 6.377760 0.000000 -SIMU 1976 10 19 24 0 5.304407 5.304407 5.304407 0.000000 -SIMU 1976 10 20 12 0 5.250734 5.250734 5.250734 0.000000 -SIMU 1976 10 20 24 0 5.197873 5.197873 5.197873 0.000000 -SIMU 1976 10 21 12 0 5.145288 5.145288 5.145288 0.000000 -SIMU 1976 10 21 24 0 4.193458 4.193458 4.193458 0.000000 -SIMU 1976 10 22 12 0 3.716582 3.716582 3.716582 0.000000 -SIMU 1976 10 22 24 0 2.110835 2.110835 2.110835 0.000000 -SIMU 1976 10 23 12 0 1.469405 1.469405 1.469405 0.000000 -SIMU 1976 10 23 24 0 7.433715 7.835683 40.46391 0.000000 -SIMU 1976 10 24 12 0 26.29626 27.88728 32.70226 0.000000 -SIMU 1976 10 24 24 0 27.61778 29.14638 29.14638 0.000000 -SIMU 1976 10 25 12 0 27.32807 28.69529 28.69533 0.000000 -SIMU 1976 10 25 24 0 27.04974 28.27263 28.27262 0.000000 -SIMU 1976 10 26 12 0 26.76316 27.85693 27.85693 0.000000 -SIMU 1976 10 26 24 0 26.49056 27.46886 27.46886 0.000000 -SIMU 1976 10 27 12 0 26.21033 27.08535 27.08535 0.000000 -SIMU 1976 10 27 24 0 25.94347 26.72611 26.72611 0.000000 -SIMU 1976 10 28 12 0 25.66943 26.36945 26.36945 0.000000 -SIMU 1976 10 28 24 0 24.99927 25.62538 25.62538 0.000000 -SIMU 1976 10 29 12 0 23.76388 24.32389 24.32389 0.000000 -SIMU 1976 10 29 24 0 22.16269 22.66358 22.66358 0.000000 -SIMU 1976 10 30 12 0 23.46229 23.94492 29.29656 0.000000 -SIMU 1976 10 30 24 0 33.60037 34.24939 39.01993 0.000000 -SIMU 1976 10 31 12 0 34.18276 34.77349 34.77349 0.000000 -SIMU 1976 10 31 24 0 33.83573 34.36410 34.36410 0.000000 -SIMU 1976 11 1 12 0 33.48219 33.95477 33.95477 0.000000 -SIMU 1976 11 1 24 0 33.14237 33.56507 33.56507 0.000000 -SIMU 1976 11 2 12 0 32.79008 33.16815 33.16815 0.000000 -SIMU 1976 11 2 24 0 31.39140 31.72956 31.72956 0.000000 -SIMU 1976 11 3 12 0 30.21948 30.52194 30.52194 0.000000 -SIMU 1976 11 3 24 0 29.01873 29.28926 29.28926 0.000000 -SIMU 1976 11 4 12 0 28.42418 28.66615 28.66615 0.000000 -SIMU 1976 11 4 24 0 27.26430 27.48071 27.48071 0.000000 -SIMU 1976 11 5 12 0 26.70259 26.89616 26.89616 0.000000 -SIMU 1976 11 5 24 0 25.22231 25.35395 25.35396 0.000000 -SIMU 1976 11 6 12 0 24.41317 24.41317 24.41317 0.000000 -SIMU 1976 11 6 24 0 23.63493 23.63493 23.63493 0.000000 -SIMU 1976 11 7 12 0 23.32906 23.32906 23.32906 0.000000 -SIMU 1976 11 7 24 0 22.76479 22.76479 22.76479 0.000000 -SIMU 1976 11 8 12 0 22.43890 22.43890 22.43890 0.000000 -SIMU 1976 11 8 24 0 21.68569 21.68569 21.68569 0.000000 -SIMU 1976 11 9 12 0 20.83400 20.83400 20.83400 0.000000 -SIMU 1976 11 9 24 0 20.29675 20.29675 20.29675 0.000000 -SIMU 1976 11 10 12 0 20.06202 20.06202 20.06202 0.000000 -SIMU 1976 11 10 24 0 19.63494 19.63494 19.63494 0.000000 -SIMU 1976 11 11 12 0 19.37324 19.37324 19.37324 0.000000 -SIMU 1976 11 11 24 0 19.17737 19.17737 19.17737 0.000000 -SIMU 1976 11 12 12 0 18.98011 18.98011 18.98011 0.000000 -SIMU 1976 11 12 24 0 18.78824 18.78824 18.78824 0.000000 -SIMU 1976 11 13 12 0 18.59512 18.59512 18.59512 0.000000 -SIMU 1976 11 13 24 0 18.29562 18.29562 18.29562 0.000000 -SIMU 1976 11 14 12 0 18.08212 18.08212 18.08212 0.000000 -SIMU 1976 11 14 24 0 17.33713 17.33713 17.33713 0.000000 -SIMU 1976 11 15 12 0 16.93672 16.93672 16.93672 0.000000 -SIMU 1976 11 15 24 0 15.58869 15.58869 15.58869 0.000000 -SIMU 1976 11 16 12 0 15.04656 15.04656 15.04656 0.000000 -SIMU 1976 11 16 24 0 13.40035 13.40035 13.40035 0.000000 -SIMU 1976 11 17 12 0 12.55171 12.55171 12.55171 0.000000 -SIMU 1976 11 17 24 0 10.70698 10.70698 10.70698 0.000000 -SIMU 1976 11 18 12 0 10.10353 10.10353 10.10353 0.000000 -SIMU 1976 11 18 24 0 9.495403 9.495403 9.495403 0.000000 -SIMU 1976 11 19 12 0 9.222705 9.222705 9.222705 0.000000 -SIMU 1976 11 19 24 0 8.624109 8.624109 8.624109 0.000000 -SIMU 1976 11 20 12 0 8.384901 8.384901 8.384901 0.000000 -SIMU 1976 11 20 24 0 8.151299 8.151299 8.151299 0.000000 -SIMU 1976 11 21 12 0 8.013232 8.013232 8.013232 0.000000 -SIMU 1976 11 21 24 0 7.932450 7.932450 7.932450 0.000000 -SIMU 1976 11 22 12 0 7.851743 7.851743 7.851743 0.000000 -SIMU 1976 11 22 24 0 7.772588 7.772588 7.772588 0.000000 -SIMU 1976 11 23 12 0 7.685007 7.685007 7.685007 0.000000 -SIMU 1976 11 23 24 0 7.128718 7.128718 7.128718 0.000000 -SIMU 1976 11 24 12 0 6.824726 6.824726 6.824726 0.000000 -SIMU 1976 11 24 24 0 6.137748 6.137748 6.137748 0.000000 -SIMU 1976 11 25 12 0 5.650980 5.650980 5.650980 0.000000 -SIMU 1976 11 25 24 0 5.375116 5.375116 5.375116 0.000000 -SIMU 1976 11 26 12 0 5.265902 5.265902 5.265902 0.000000 -SIMU 1976 11 26 24 0 5.212901 5.212901 5.212901 0.000000 -SIMU 1976 11 27 12 0 5.160210 5.160210 5.160210 0.000000 -SIMU 1976 11 27 24 0 5.108275 5.108275 5.108275 0.000000 -SIMU 1976 11 28 12 0 5.056653 5.056653 5.056653 0.000000 -SIMU 1976 11 28 24 0 5.005761 5.005761 5.005761 0.000000 -SIMU 1976 11 29 12 0 4.955183 4.955183 4.955183 0.000000 -SIMU 1976 11 29 24 0 4.905315 4.905315 4.905315 0.000000 -SIMU 1976 11 30 12 0 4.855760 4.855760 4.855760 0.000000 -SIMU 1976 11 30 24 0 4.806894 4.806894 4.806894 0.000000 -SIMU 1976 12 1 12 0 4.758340 4.758340 4.758340 0.000000 -SIMU 1976 12 1 24 0 4.710457 4.710457 4.710457 0.000000 -SIMU 1976 12 2 12 0 4.662884 4.662884 4.662884 0.000000 -SIMU 1976 12 2 24 0 4.615964 4.615964 4.615964 0.000000 -SIMU 1976 12 3 12 0 4.569351 4.569351 4.569351 0.000000 -SIMU 1976 12 3 24 0 4.523374 4.523374 4.523374 0.000000 -SIMU 1976 12 4 12 0 4.477704 4.477704 4.477704 0.000000 -SIMU 1976 12 4 24 0 4.432649 4.432649 4.432649 0.000000 -SIMU 1976 12 5 12 0 4.387900 4.387900 4.387900 0.000000 -SIMU 1976 12 5 24 0 4.343751 4.343751 4.343751 0.000000 -SIMU 1976 12 6 12 0 4.299906 4.299906 4.299906 0.000000 -SIMU 1976 12 6 24 0 4.256644 4.256644 4.256644 0.000000 -SIMU 1976 12 7 12 0 4.213683 4.213683 4.213683 0.000000 -SIMU 1976 12 7 24 0 4.171290 4.171290 4.171290 0.000000 -SIMU 1976 12 8 12 0 4.129197 4.129197 4.129197 0.000000 -SIMU 1976 12 8 24 0 4.087655 4.087655 4.087655 0.000000 -SIMU 1976 12 9 12 0 4.046409 4.046409 4.046409 0.000000 -SIMU 1976 12 9 24 0 4.005703 4.005703 4.005703 0.000000 -SIMU 1976 12 10 12 0 3.965293 3.965293 3.965293 0.000000 -SIMU 1976 12 10 24 0 3.925402 3.925402 3.925402 0.000000 -SIMU 1976 12 11 12 0 3.885803 3.885803 3.885803 0.000000 -SIMU 1976 12 11 24 0 3.846713 3.846713 3.846713 0.000000 -SIMU 1976 12 12 12 0 3.807913 3.807913 3.807913 0.000000 -SIMU 1976 12 12 24 0 3.769608 3.769608 3.769608 0.000000 -SIMU 1976 12 13 12 0 3.731589 3.731589 3.731589 0.000000 -SIMU 1976 12 13 24 0 3.686623 3.686623 3.686623 0.000000 -SIMU 1976 12 14 12 0 3.646369 3.646369 3.646369 0.000000 -SIMU 1976 12 14 24 0 3.591136 3.591136 3.591136 0.000000 -SIMU 1976 12 15 12 0 3.549513 3.549513 3.549513 0.000000 -SIMU 1976 12 15 24 0 3.498237 3.498237 3.498237 0.000000 -SIMU 1976 12 16 12 0 3.455036 3.455036 3.455036 0.000000 -SIMU 1976 12 16 24 0 3.384976 3.384976 3.384976 0.000000 -SIMU 1976 12 17 12 0 3.311943 3.311943 3.311943 0.000000 -SIMU 1976 12 17 24 0 3.252935 3.252935 3.252935 0.000000 -SIMU 1976 12 18 12 0 3.257537 3.257537 3.485761 0.000000 -SIMU 1976 12 18 24 0 7.765163 7.765163 10.72768 0.000000 -SIMU 1976 12 19 12 0 8.991038 8.991038 10.32934 0.000000 -SIMU 1976 12 19 24 0 12.84119 12.84119 14.44906 0.000000 -SIMU 1976 12 20 12 0 12.99357 12.99357 12.99357 0.000000 -SIMU 1976 12 20 24 0 12.86289 12.86289 12.86289 0.000000 -SIMU 1976 12 21 12 0 12.73894 12.73894 12.73908 0.000000 -SIMU 1976 12 21 24 0 12.61096 12.61096 12.61096 0.000000 -SIMU 1976 12 22 12 0 12.48959 12.48959 12.48972 0.000000 -SIMU 1976 12 22 24 0 12.36413 12.36413 12.36413 0.000000 -SIMU 1976 12 23 12 0 12.24528 12.24528 12.24541 0.000000 -SIMU 1976 12 23 24 0 12.12229 12.12229 12.12229 0.000000 -SIMU 1976 12 24 12 0 12.00591 12.00591 12.00600 0.000000 -SIMU 1976 12 24 24 0 11.88532 11.88532 11.88532 0.000000 -SIMU 1976 12 25 12 0 11.76515 11.76515 11.76515 0.000000 -SIMU 1976 12 25 24 0 11.64672 11.64672 11.64672 0.000000 -SIMU 1976 12 26 12 0 11.52898 11.52898 11.52898 0.000000 -SIMU 1976 12 26 24 0 11.41294 11.41294 11.41294 0.000000 -SIMU 1976 12 27 12 0 11.30274 11.30274 11.30286 0.000000 -SIMU 1976 12 27 24 0 13.30873 13.30873 15.44544 0.000000 -SIMU 1976 12 28 12 0 13.87782 13.87782 13.87782 0.000000 -SIMU 1976 12 28 24 0 13.73811 13.73811 13.73811 0.000000 -SIMU 1976 12 29 12 0 13.60452 13.60452 13.60468 0.000000 -SIMU 1976 12 29 24 0 13.46780 13.46780 13.46780 0.000000 -SIMU 1976 12 30 12 0 13.33780 13.33780 13.33792 0.000000 -SIMU 1976 12 30 24 0 13.20381 13.20381 13.20381 0.000000 -SIMU 1976 12 31 12 0 13.07650 13.07650 13.07667 0.000000 -SIMU 1976 12 31 24 0 12.94514 12.94514 12.94514 0.000000 +SIMU 1976 1 1 12 0 273.7137 273.7137 274.1314 360.0000 +SIMU 1976 1 1 24 0 270.9065 270.9065 270.9065 360.0000 +SIMU 1976 1 2 12 0 267.8203 267.8203 267.8203 360.0000 +SIMU 1976 1 2 24 0 265.0379 265.0379 265.0379 360.0000 +SIMU 1976 1 3 12 0 262.0291 262.0291 262.0291 360.0000 +SIMU 1976 1 3 24 0 259.3096 259.3096 259.3096 360.0000 +SIMU 1976 1 4 12 0 256.3756 256.3756 256.3756 384.0000 +SIMU 1976 1 4 24 0 253.7173 253.7173 253.7173 384.0000 +SIMU 1976 1 5 12 0 250.8562 250.8562 250.8562 384.0000 +SIMU 1976 1 5 24 0 248.2574 248.2574 248.2574 384.0000 +SIMU 1976 1 6 12 0 245.4668 245.4668 245.4668 408.0000 +SIMU 1976 1 6 24 0 242.9262 242.9262 242.9262 408.0000 +SIMU 1976 1 7 12 0 240.2040 240.2040 240.2040 432.0000 +SIMU 1976 1 7 24 0 237.7201 237.7201 237.7201 432.0000 +SIMU 1976 1 8 12 0 235.0643 235.0643 235.0643 432.0000 +SIMU 1976 1 8 24 0 232.6355 232.6355 232.6355 432.0000 +SIMU 1976 1 9 12 0 230.0442 230.0442 230.0442 456.0000 +SIMU 1976 1 9 24 0 227.6693 227.6693 227.6693 456.0000 +SIMU 1976 1 10 12 0 225.1406 225.1406 225.1406 456.0000 +SIMU 1976 1 10 24 0 222.8182 222.8182 222.8182 456.0000 +SIMU 1976 1 11 12 0 220.3504 220.3504 220.3504 480.0000 +SIMU 1976 1 11 24 0 220.3348 220.3348 220.6296 480.0000 +SIMU 1976 1 12 12 0 218.7653 218.7653 218.7653 480.0000 +SIMU 1976 1 12 24 0 223.9155 223.9155 227.5199 480.0000 +SIMU 1976 1 13 12 0 224.2073 224.2073 229.0978 480.0000 +SIMU 1976 1 13 24 0 250.5231 250.5231 259.6499 480.0000 +SIMU 1976 1 14 12 0 250.1501 250.1501 251.4268 504.0000 +SIMU 1976 1 14 24 0 282.6879 283.4876 301.6508 504.0000 +SIMU 1976 1 15 12 0 285.4275 286.2410 286.2409 504.0000 +SIMU 1976 1 15 24 0 303.7103 304.4379 323.1508 504.0000 +SIMU 1976 1 16 12 0 305.7707 306.4214 306.4214 504.0000 +SIMU 1976 1 16 24 0 302.5865 303.1686 303.1686 504.0000 +SIMU 1976 1 17 12 0 299.1237 299.6443 299.6443 504.0000 +SIMU 1976 1 17 24 0 296.0120 296.4777 296.4777 504.0000 +SIMU 1976 1 18 12 0 292.6365 293.0529 293.0529 504.0000 +SIMU 1976 1 18 24 0 293.6567 294.1086 294.9831 504.0000 +SIMU 1976 1 19 12 0 291.2049 291.6229 291.6229 504.0000 +SIMU 1976 1 19 24 0 288.1777 288.5516 288.5516 504.0000 +SIMU 1976 1 20 12 0 284.8995 285.2339 285.2339 480.0000 +SIMU 1976 1 20 24 0 287.3622 287.6613 291.0746 480.0000 +SIMU 1976 1 21 12 0 285.6196 285.8871 285.8871 480.0000 +SIMU 1976 1 21 24 0 282.6551 282.8944 282.8944 480.0000 +SIMU 1976 1 22 12 0 279.8778 280.1126 285.2809 480.0000 +SIMU 1976 1 22 24 0 323.7802 324.8535 344.2205 480.0000 +SIMU 1976 1 23 12 0 326.0203 327.0487 340.6180 480.0000 +SIMU 1976 1 23 24 0 395.8738 397.3109 443.0800 480.0000 +SIMU 1976 1 24 12 0 401.3105 402.6367 402.6367 480.0000 +SIMU 1976 1 24 24 0 418.1101 419.2964 433.0610 480.0000 +SIMU 1976 1 25 12 0 416.4763 417.5373 417.5374 480.0000 +SIMU 1976 1 25 24 0 413.9085 414.8574 415.4517 480.0000 +SIMU 1976 1 26 12 0 410.0617 410.9106 426.1584 480.0000 +SIMU 1976 1 26 24 0 458.6590 459.5100 486.1920 480.0000 +SIMU 1976 1 27 12 0 458.6625 459.4549 463.1353 480.0000 +SIMU 1976 1 27 24 0 492.3941 494.8919 509.0454 480.0000 +SIMU 1976 1 28 12 0 492.6601 495.1029 497.4737 480.0000 +SIMU 1976 1 28 24 0 579.1383 589.1035 671.5825 480.0000 +SIMU 1976 1 29 12 0 594.1650 603.9413 634.2453 480.0000 +SIMU 1976 1 29 24 0 713.1340 729.8587 779.6940 480.0000 +SIMU 1976 1 30 12 0 716.6623 730.6788 730.6788 480.0000 +SIMU 1976 1 30 24 0 708.8400 720.0978 720.0978 480.0000 +SIMU 1976 1 31 12 0 699.4521 708.5308 708.5308 456.0000 +SIMU 1976 1 31 24 0 691.8361 699.1887 699.1887 456.0000 +SIMU 1976 2 1 12 0 682.7362 688.7186 688.7186 456.0000 +SIMU 1976 2 1 24 0 682.3723 687.6998 691.6342 456.0000 +SIMU 1976 2 2 12 0 674.7304 679.1472 679.1481 456.0000 +SIMU 1976 2 2 24 0 667.4161 671.0426 671.0426 456.0000 +SIMU 1976 2 3 12 0 658.8010 661.4517 661.4517 432.0000 +SIMU 1976 2 3 24 0 651.6752 652.9003 652.9003 432.0000 +SIMU 1976 2 4 12 0 643.2598 644.3555 644.3555 432.0000 +SIMU 1976 2 4 24 0 636.3148 637.2950 637.2950 432.0000 +SIMU 1976 2 5 12 0 628.1501 629.0268 629.0268 432.0000 +SIMU 1976 2 5 24 0 621.3827 622.1666 622.1666 432.0000 +SIMU 1976 2 6 12 0 613.5100 614.2114 614.2122 432.0000 +SIMU 1976 2 6 24 0 606.9158 607.5430 607.5430 432.0000 +SIMU 1976 2 7 12 0 599.2827 599.8436 599.8453 432.0000 +SIMU 1976 2 7 24 0 621.5203 622.4725 642.5262 432.0000 +SIMU 1976 2 8 12 0 625.0670 626.0715 629.5871 456.0000 +SIMU 1976 2 8 24 0 701.7318 707.7177 755.4160 456.0000 +SIMU 1976 2 9 12 0 707.7151 713.3344 723.4707 480.0000 +SIMU 1976 2 9 24 0 763.7617 770.9675 783.5859 480.0000 +SIMU 1976 2 10 12 0 763.2811 769.2648 771.3387 480.0000 +SIMU 1976 2 10 24 0 777.2682 782.5706 784.9334 480.0000 +SIMU 1976 2 11 12 0 769.1977 773.4739 773.4739 504.0000 +SIMU 1976 2 11 24 0 760.8099 764.2403 764.2402 504.0000 +SIMU 1976 2 12 12 0 751.8317 754.6130 755.4594 528.0000 +SIMU 1976 2 12 24 0 754.6191 757.0453 757.6956 528.0000 +SIMU 1976 2 13 12 0 745.3438 746.0004 746.0004 576.0000 +SIMU 1976 2 13 24 0 737.2469 737.8109 737.8109 576.0000 +SIMU 1976 2 14 12 0 727.6096 728.1143 728.1143 600.0000 +SIMU 1976 2 14 24 0 722.0472 722.6774 743.1882 600.0000 +SIMU 1976 2 15 12 0 788.0955 794.2668 858.8982 648.0000 +SIMU 1976 2 15 24 0 885.9044 897.9026 907.8766 648.0000 +SIMU 1976 2 16 12 0 890.0539 900.4751 934.2605 696.0000 +SIMU 1976 2 16 24 0 1147.188 1252.002 1393.779 696.0000 +SIMU 1976 2 17 12 0 1160.643 1247.780 1247.780 744.0000 +SIMU 1976 2 17 24 0 1147.576 1215.721 1215.721 744.0000 +SIMU 1976 2 18 12 0 1130.966 1184.332 1184.332 840.0000 +SIMU 1976 2 18 24 0 1118.276 1160.133 1160.133 840.0000 +SIMU 1976 2 19 12 0 1102.644 1135.538 1135.871 768.0000 +SIMU 1976 2 19 24 0 1098.210 1124.220 1124.789 768.0000 +SIMU 1976 2 20 12 0 1083.811 1104.346 1104.346 744.0000 +SIMU 1976 2 20 24 0 1159.870 1188.142 1446.803 744.0000 +SIMU 1976 2 21 12 0 1393.915 1445.009 1445.009 672.0000 +SIMU 1976 2 21 24 0 1378.056 1417.898 1417.898 672.0000 +SIMU 1976 2 22 12 0 1357.451 1388.551 1388.552 600.0000 +SIMU 1976 2 22 24 0 1342.063 1366.365 1366.365 600.0000 +SIMU 1976 2 23 12 0 1322.182 1341.198 1341.199 768.0000 +SIMU 1976 2 23 24 0 1344.435 1360.949 1373.761 768.0000 +SIMU 1976 2 24 12 0 1352.014 1366.486 1420.828 840.0000 +SIMU 1976 2 24 24 0 1631.467 1664.786 1760.583 840.0000 +SIMU 1976 2 25 12 0 1645.186 1673.444 1679.449 672.0000 +SIMU 1976 2 25 24 0 1719.133 1743.396 1751.933 672.0000 +SIMU 1976 2 26 12 0 1729.574 1751.620 1863.471 576.0000 +SIMU 1976 2 26 24 0 2145.076 2203.090 2354.557 576.0000 +SIMU 1976 2 27 12 0 2196.134 2248.779 2387.094 624.0000 +SIMU 1976 2 27 24 0 2647.731 2741.445 2875.384 624.0000 +SIMU 1976 2 28 12 0 2666.097 2744.970 2776.679 648.0000 +SIMU 1976 2 28 24 0 2796.178 2866.075 2885.736 648.0000 +SIMU 1976 2 29 12 0 2757.730 2812.425 2812.425 696.0000 +SIMU 1976 2 29 24 0 2724.651 2767.139 2767.139 696.0000 +SIMU 1976 3 1 12 0 2674.779 2707.797 2707.797 600.0000 +SIMU 1976 3 1 24 0 2642.787 2668.460 2668.460 600.0000 +SIMU 1976 3 2 12 0 2594.898 2614.871 2614.871 576.0000 +SIMU 1976 3 2 24 0 2563.970 2579.518 2579.518 576.0000 +SIMU 1976 3 3 12 0 2517.981 2530.094 2530.094 696.0000 +SIMU 1976 3 3 24 0 2488.078 2497.523 2497.523 696.0000 +SIMU 1976 3 4 12 0 2443.906 2451.277 2451.277 840.0000 +SIMU 1976 3 4 24 0 2414.992 2420.751 2420.751 840.0000 +SIMU 1976 3 5 12 0 2372.557 2377.063 2377.063 840.0000 +SIMU 1976 3 5 24 0 2344.595 2348.125 2348.125 840.0000 +SIMU 1976 3 6 12 0 2304.067 2306.842 2307.754 816.0000 +SIMU 1976 3 6 24 0 2312.121 2314.444 2319.128 816.0000 +SIMU 1976 3 7 12 0 2282.915 2284.728 2290.749 768.0000 +SIMU 1976 3 7 24 0 2389.728 2393.710 2416.441 768.0000 +SIMU 1976 3 8 12 0 2375.829 2379.557 2379.557 744.0000 +SIMU 1976 3 8 24 0 2356.251 2359.478 2361.091 744.0000 +SIMU 1976 3 9 12 0 2324.133 2326.993 2343.137 720.0000 +SIMU 1976 3 9 24 0 2533.496 2546.324 2598.988 720.0000 +SIMU 1976 3 10 12 0 2527.951 2539.621 2544.238 720.0000 +SIMU 1976 3 10 24 0 2575.119 2585.723 2589.015 720.0000 +SIMU 1976 3 11 12 0 2542.523 2551.394 2573.140 744.0000 +SIMU 1976 3 11 24 0 3130.838 3325.532 3639.246 744.0000 +SIMU 1976 3 12 12 0 3977.998 4697.345 4755.904 2400.000 +SIMU 1976 3 12 24 0 4568.944 6110.023 6294.532 2400.000 +SIMU 1976 3 13 12 0 4675.457 5991.283 6018.238 9600.000 +SIMU 1976 3 13 24 0 5412.477 6752.256 6779.295 9600.000 +SIMU 1976 3 14 12 0 5441.626 6522.768 6578.951 11520.00 +SIMU 1976 3 14 24 0 6084.311 7198.646 7206.401 11520.00 +SIMU 1976 3 15 12 0 6067.787 6967.828 7024.758 7200.000 +SIMU 1976 3 15 24 0 6255.849 6990.056 7098.378 7200.000 +SIMU 1976 3 16 12 0 6220.770 6828.191 6856.617 5520.000 +SIMU 1976 3 16 24 0 7004.281 7778.937 7943.517 5520.000 +SIMU 1976 3 17 12 0 6931.859 7551.336 7641.298 4512.000 +SIMU 1976 3 17 24 0 7275.872 7853.927 8075.415 4512.000 +SIMU 1976 3 18 12 0 7215.516 7689.605 7997.244 4464.000 +SIMU 1976 3 18 24 0 7592.294 8056.001 8200.375 4464.000 +SIMU 1976 3 19 12 0 7459.372 7824.978 7833.936 4920.000 +SIMU 1976 3 19 24 0 7421.499 7710.471 7721.106 4920.000 +SIMU 1976 3 20 12 0 7246.257 7471.947 7471.947 5472.000 +SIMU 1976 3 20 24 0 7149.289 7325.435 7325.435 5472.000 +SIMU 1976 3 21 12 0 6973.513 7111.144 7111.143 5016.000 +SIMU 1976 3 21 24 0 6878.085 6985.757 6985.757 5016.000 +SIMU 1976 3 22 12 0 6709.121 6793.473 6793.473 3768.000 +SIMU 1976 3 22 24 0 6614.783 6680.972 6680.972 3768.000 +SIMU 1976 3 23 12 0 6451.173 6503.203 6503.203 3000.000 +SIMU 1976 3 23 24 0 6358.853 6399.835 6399.835 3000.000 +SIMU 1976 3 24 12 0 6200.556 6232.910 6232.910 2592.000 +SIMU 1976 3 24 24 0 6108.588 6134.192 6134.193 2592.000 +SIMU 1976 3 25 12 0 5955.584 5975.905 5975.905 2496.000 +SIMU 1976 3 25 24 0 5865.451 5881.626 5881.626 2496.000 +SIMU 1976 3 26 12 0 5724.800 5737.979 5741.190 2280.000 +SIMU 1976 3 26 24 0 5715.033 5728.673 5749.997 2280.000 +SIMU 1976 3 27 12 0 5612.880 5625.292 5625.292 4008.000 +SIMU 1976 3 27 24 0 5530.031 5540.180 5540.180 4008.000 +SIMU 1976 3 28 12 0 5394.651 5402.991 5402.991 4152.000 +SIMU 1976 3 28 24 0 5317.143 5324.122 5327.223 4152.000 +SIMU 1976 3 29 12 0 5324.132 5335.811 5367.000 3336.000 +SIMU 1976 3 29 24 0 5782.515 6035.415 6549.230 3336.000 +SIMU 1976 3 30 12 0 7224.028 9555.914 9767.674 5976.000 +SIMU 1976 3 30 24 0 7472.900 9480.323 9480.323 5976.000 +SIMU 1976 3 31 12 0 7316.518 8884.538 8884.539 15264.00 +SIMU 1976 3 31 24 0 7238.360 8464.639 8464.639 15264.00 +SIMU 1976 4 1 12 0 7075.693 8036.026 8036.025 19440.00 +SIMU 1976 4 1 24 0 6987.918 7741.145 7741.146 19440.00 +SIMU 1976 4 2 12 0 6814.303 7406.119 7406.119 15384.00 +SIMU 1976 4 2 24 0 6706.199 7172.103 7172.103 15384.00 +SIMU 1976 4 3 12 0 6523.954 6891.536 6891.536 9432.000 +SIMU 1976 4 3 24 0 6412.716 6703.433 6703.432 9432.000 +SIMU 1976 4 4 12 0 6241.489 6472.034 6472.034 7104.000 +SIMU 1976 4 4 24 0 6134.128 6317.496 6317.497 7104.000 +SIMU 1976 4 5 12 0 5965.509 6111.832 6111.831 5928.000 +SIMU 1976 4 5 24 0 5856.542 5973.715 5973.715 5928.000 +SIMU 1976 4 6 12 0 5690.369 5784.559 5784.559 5280.000 +SIMU 1976 4 6 24 0 5581.546 5657.571 5657.572 5280.000 +SIMU 1976 4 7 12 0 5417.036 5478.667 5478.667 4680.000 +SIMU 1976 4 7 24 0 5307.307 5357.499 5357.499 4680.000 +SIMU 1976 4 8 12 0 5159.871 5200.943 5200.944 4152.000 +SIMU 1976 4 8 24 0 5050.623 5084.400 5084.399 4152.000 +SIMU 1976 4 9 12 0 4908.787 4936.705 4936.705 3816.000 +SIMU 1976 4 9 24 0 4812.399 4835.593 4835.593 3816.000 +SIMU 1976 4 10 12 0 4655.151 4674.522 4674.522 3528.000 +SIMU 1976 4 10 24 0 4527.910 4544.170 4544.170 3528.000 +SIMU 1976 4 11 12 0 4396.500 4410.582 4413.267 3408.000 +SIMU 1976 4 11 24 0 4302.192 4314.207 4314.207 3408.000 +SIMU 1976 4 12 12 0 4188.302 4198.553 4198.553 3072.000 +SIMU 1976 4 12 24 0 4096.929 4105.714 4105.714 3072.000 +SIMU 1976 4 13 12 0 3968.454 3975.816 3975.816 2832.000 +SIMU 1976 4 13 24 0 3858.228 3864.146 3864.147 2832.000 +SIMU 1976 4 14 12 0 3732.158 3736.671 3736.671 2760.000 +SIMU 1976 4 14 24 0 3713.524 3763.240 3847.532 2760.000 +SIMU 1976 4 15 12 0 4213.024 4442.344 4496.130 2736.000 +SIMU 1976 4 15 24 0 4250.309 4440.435 4440.435 2736.000 +SIMU 1976 4 16 12 0 4128.880 4279.158 4279.159 2640.000 +SIMU 1976 4 16 24 0 4015.025 4134.121 4134.122 2640.000 +SIMU 1976 4 17 12 0 4162.041 4388.927 4478.631 2712.000 +SIMU 1976 4 17 24 0 5332.612 6024.311 6146.051 2712.000 +SIMU 1976 4 18 12 0 7164.555 10746.90 11595.92 3960.000 +SIMU 1976 4 18 24 0 7628.225 11163.71 11163.71 3960.000 +SIMU 1976 4 19 12 0 7486.661 10410.07 10410.07 5832.000 +SIMU 1976 4 19 24 0 7403.147 9832.930 9832.930 5832.000 +SIMU 1976 4 20 12 0 7221.528 9252.327 9256.658 6192.000 +SIMU 1976 4 20 24 0 8600.985 11659.31 11828.30 6192.000 +SIMU 1976 4 21 12 0 9639.791 13331.55 13402.07 6000.000 +SIMU 1976 4 21 24 0 9924.361 13559.89 13559.89 6000.000 +SIMU 1976 4 22 12 0 9659.603 12586.00 12586.00 6192.000 +SIMU 1976 4 22 24 0 9506.230 11871.69 11871.69 6192.000 +SIMU 1976 4 23 12 0 9431.766 12162.72 13825.13 6120.000 +SIMU 1976 4 23 24 0 10365.31 15744.01 16081.51 6120.000 +SIMU 1976 4 24 12 0 10826.79 16290.42 16611.88 6768.000 +SIMU 1976 4 24 24 0 11493.72 16030.07 16058.38 6768.000 +SIMU 1976 4 25 12 0 11736.68 15501.91 15801.95 8952.000 +SIMU 1976 4 25 24 0 12024.70 15226.28 15226.28 8952.000 +SIMU 1976 4 26 12 0 11697.15 14233.31 14233.31 11664.00 +SIMU 1976 4 26 24 0 11519.66 13534.45 13534.45 11664.00 +SIMU 1976 4 27 12 0 11173.10 12778.73 12778.73 10896.00 +SIMU 1976 4 27 24 0 10975.75 12259.70 12259.70 10896.00 +SIMU 1976 4 28 12 0 10633.20 11663.72 11663.72 8832.000 +SIMU 1976 4 28 24 0 10444.50 11274.92 11274.92 8832.000 +SIMU 1976 4 29 12 0 10113.05 10785.08 10785.08 7512.000 +SIMU 1976 4 29 24 0 9910.364 10456.66 10456.66 7512.000 +SIMU 1976 4 30 12 0 9582.726 10028.91 10028.91 6864.000 +SIMU 1976 4 30 24 0 9389.166 9755.379 9755.379 6864.000 +SIMU 1976 5 1 12 0 9082.641 9384.731 9384.731 6432.000 +SIMU 1976 5 1 24 0 8901.657 9152.135 9152.135 6432.000 +SIMU 1976 5 2 12 0 9503.853 9853.097 9976.797 5928.000 +SIMU 1976 5 2 24 0 9716.493 10048.33 10048.33 5928.000 +SIMU 1976 5 3 12 0 9411.116 9680.611 9680.612 5400.000 +SIMU 1976 5 3 24 0 9216.255 9436.145 9436.145 5400.000 +SIMU 1976 5 4 12 0 8910.540 9090.828 9090.829 4944.000 +SIMU 1976 5 4 24 0 8723.168 8871.730 8871.730 4944.000 +SIMU 1976 5 5 12 0 8424.436 8547.482 8547.482 4536.000 +SIMU 1976 5 5 24 0 8232.727 8335.167 8335.166 4536.000 +SIMU 1976 5 6 12 0 7944.313 8030.040 8030.040 4344.000 +SIMU 1976 5 6 24 0 7758.746 7830.853 7830.853 4344.000 +SIMU 1976 5 7 12 0 7502.618 7563.573 7563.572 3912.000 +SIMU 1976 5 7 24 0 7343.863 7395.641 7395.641 3912.000 +SIMU 1976 5 8 12 0 7109.180 7153.368 7153.368 3720.000 +SIMU 1976 5 8 24 0 6952.368 6990.245 6990.245 3720.000 +SIMU 1976 5 9 12 0 6709.893 6742.497 6742.497 3576.000 +SIMU 1976 5 9 24 0 6544.151 6572.327 6572.327 3576.000 +SIMU 1976 5 10 12 0 6313.746 6338.182 6338.182 3456.000 +SIMU 1976 5 10 24 0 6163.176 6184.440 6184.440 3456.000 +SIMU 1976 5 11 12 0 5949.690 5968.250 5968.250 3360.000 +SIMU 1976 5 11 24 0 5805.403 5821.648 5821.648 3360.000 +SIMU 1976 5 12 12 0 5606.486 5620.741 5620.741 3192.000 +SIMU 1976 5 12 24 0 5475.732 5487.095 5488.084 3192.000 +SIMU 1976 5 13 12 0 5921.376 5965.900 6166.316 3312.000 +SIMU 1976 5 13 24 0 6240.886 6296.999 6297.000 3312.000 +SIMU 1976 5 14 12 0 6074.830 6120.905 6120.905 3336.000 +SIMU 1976 5 14 24 0 5974.801 6012.826 6012.826 3336.000 +SIMU 1976 5 15 12 0 5821.232 5853.288 5861.953 3192.000 +SIMU 1976 5 15 24 0 5841.707 5870.807 5874.759 3192.000 +SIMU 1976 5 16 12 0 6133.264 6211.042 6540.570 3888.000 +SIMU 1976 5 16 24 0 7443.866 7770.854 7841.980 3888.000 +SIMU 1976 5 17 12 0 7393.988 7657.070 7657.070 6312.000 +SIMU 1976 5 17 24 0 7248.306 7455.735 7455.735 6312.000 +SIMU 1976 5 18 12 0 7016.071 7180.006 7180.006 8064.000 +SIMU 1976 5 18 24 0 6864.927 6994.829 6994.828 8064.000 +SIMU 1976 5 19 12 0 6632.440 6735.670 6735.670 7296.000 +SIMU 1976 5 19 24 0 6473.555 6555.850 6555.850 7296.000 +SIMU 1976 5 20 12 0 6242.143 6307.977 6307.977 6264.000 +SIMU 1976 5 20 24 0 6078.955 6131.816 6131.816 6264.000 +SIMU 1976 5 21 12 0 5863.405 5906.022 5906.022 5592.000 +SIMU 1976 5 21 24 0 5725.353 5759.856 5759.856 5592.000 +SIMU 1976 5 22 12 0 5548.791 5578.020 5627.149 5208.000 +SIMU 1976 5 22 24 0 6055.835 6113.732 6209.580 5208.000 +SIMU 1976 5 23 12 0 6378.099 6441.832 6473.352 5976.000 +SIMU 1976 5 23 24 0 6387.691 6444.794 6459.470 5976.000 +SIMU 1976 5 24 12 0 6229.678 6278.872 6278.872 6672.000 +SIMU 1976 5 24 24 0 6120.713 6162.870 6162.870 6672.000 +SIMU 1976 5 25 12 0 5929.489 5965.768 5965.768 6312.000 +SIMU 1976 5 25 24 0 5796.314 5827.657 5827.657 6312.000 +SIMU 1976 5 26 12 0 5602.609 5629.787 5629.786 5640.000 +SIMU 1976 5 26 24 0 5469.314 5492.957 5492.957 5640.000 +SIMU 1976 5 27 12 0 5284.036 5304.670 5304.670 5088.000 +SIMU 1976 5 27 24 0 5158.005 5176.063 5176.063 5088.000 +SIMU 1976 5 28 12 0 4983.002 4998.846 4998.846 4728.000 +SIMU 1976 5 28 24 0 4909.798 4945.371 5005.282 4728.000 +SIMU 1976 5 29 12 0 5589.246 5941.422 6028.131 4704.000 +SIMU 1976 5 29 24 0 5797.516 6205.313 6205.313 4704.000 +SIMU 1976 5 30 12 0 5633.561 5950.626 5950.626 6552.000 +SIMU 1976 5 30 24 0 5528.438 5775.097 5775.097 6552.000 +SIMU 1976 5 31 12 0 5369.578 5561.591 5561.591 7776.000 +SIMU 1976 5 31 24 0 5268.968 5418.550 5418.550 7776.000 +SIMU 1976 6 1 12 0 5117.311 5233.938 5233.937 6648.000 +SIMU 1976 6 1 24 0 5018.680 5109.698 5109.698 6648.000 +SIMU 1976 6 2 12 0 4868.513 4939.623 4939.624 5496.000 +SIMU 1976 6 2 24 0 4762.963 4818.588 4818.588 5496.000 +SIMU 1976 6 3 12 0 4608.494 4652.067 4652.067 4728.000 +SIMU 1976 6 3 24 0 4493.570 4527.758 4527.758 4728.000 +SIMU 1976 6 4 12 0 4338.532 4365.403 4365.403 4200.000 +SIMU 1976 6 4 24 0 4224.821 4245.983 4245.983 4200.000 +SIMU 1976 6 5 12 0 4074.822 4091.525 4091.525 3864.000 +SIMU 1976 6 5 24 0 3962.500 3975.717 3975.717 3864.000 +SIMU 1976 6 6 12 0 3821.470 3831.957 3831.957 3600.000 +SIMU 1976 6 6 24 0 3719.002 3727.348 3727.348 3600.000 +SIMU 1976 6 7 12 0 3589.172 3595.836 3595.836 3408.000 +SIMU 1976 6 7 24 0 3492.674 3498.013 3498.013 3408.000 +SIMU 1976 6 8 12 0 3369.697 3373.993 3373.993 3216.000 +SIMU 1976 6 8 24 0 3274.981 3278.451 3278.451 3216.000 +SIMU 1976 6 9 12 0 3150.390 3153.204 3153.204 3048.000 +SIMU 1976 6 9 24 0 3044.716 3046.042 3046.042 3048.000 +SIMU 1976 6 10 12 0 3291.709 3459.219 3513.617 3024.000 +SIMU 1976 6 10 24 0 3518.919 3747.066 3747.066 3024.000 +SIMU 1976 6 11 12 0 3413.929 3595.808 3595.808 3048.000 +SIMU 1976 6 11 24 0 3344.455 3489.951 3489.951 3048.000 +SIMU 1976 6 12 12 0 3228.865 3345.692 3345.692 3024.000 +SIMU 1976 6 12 24 0 3221.686 3381.008 3396.237 3024.000 +SIMU 1976 6 13 12 0 3343.770 3607.325 3607.325 2808.000 +SIMU 1976 6 13 24 0 3731.925 4195.831 4273.231 2808.000 +SIMU 1976 6 14 12 0 4313.558 4992.616 4992.689 3264.000 +SIMU 1976 6 14 24 0 4236.824 4773.909 4773.984 3264.000 +SIMU 1976 6 15 12 0 4153.155 4580.737 4592.651 3120.000 +SIMU 1976 6 15 24 0 4062.318 4402.652 4402.652 3120.000 +SIMU 1976 6 16 12 0 3938.319 4210.056 4210.056 3408.000 +SIMU 1976 6 16 24 0 3855.712 4073.456 4073.456 3408.000 +SIMU 1976 6 17 12 0 3734.820 3909.976 3909.976 3192.000 +SIMU 1976 6 17 24 0 3637.509 3778.990 3778.990 3192.000 +SIMU 1976 6 18 12 0 3526.016 3640.807 3640.861 2664.000 +SIMU 1976 6 18 24 0 3452.074 3545.638 3545.638 2664.000 +SIMU 1976 6 19 12 0 3343.906 3420.537 3420.537 2424.000 +SIMU 1976 6 19 24 0 3263.694 3326.768 3326.768 2424.000 +SIMU 1976 6 20 12 0 3155.298 3207.479 3207.478 2208.000 +SIMU 1976 6 20 24 0 3066.159 3109.553 3109.553 2208.000 +SIMU 1976 6 21 12 0 2960.541 2996.813 2996.812 2040.000 +SIMU 1976 6 21 24 0 2882.089 2912.564 2912.564 2040.000 +SIMU 1976 6 22 12 0 2782.793 2808.525 2808.525 1896.000 +SIMU 1976 6 22 24 0 2701.439 2723.275 2723.275 1896.000 +SIMU 1976 6 23 12 0 2603.720 2622.335 2622.335 1752.000 +SIMU 1976 6 23 24 0 2524.560 2540.502 2540.502 1752.000 +SIMU 1976 6 24 12 0 2506.310 2572.711 2636.606 1704.000 +SIMU 1976 6 24 24 0 2803.375 3035.986 3079.804 1704.000 +SIMU 1976 6 25 12 0 2754.266 2936.758 2936.758 1632.000 +SIMU 1976 6 25 24 0 2686.124 2828.623 2828.623 1632.000 +SIMU 1976 6 26 12 0 2606.177 2717.578 2717.578 1560.000 +SIMU 1976 6 26 24 0 2561.369 2656.339 2677.624 1560.000 +SIMU 1976 6 27 12 0 2647.217 2752.256 2752.709 1512.000 +SIMU 1976 6 27 24 0 2713.907 2819.464 2860.134 1512.000 +SIMU 1976 6 28 12 0 3036.492 3202.362 3233.577 1416.000 +SIMU 1976 6 28 24 0 3110.139 3268.096 3268.096 1416.000 +SIMU 1976 6 29 12 0 3023.118 3145.993 3145.993 1368.000 +SIMU 1976 6 29 24 0 2956.332 3051.979 3051.979 1368.000 +SIMU 1976 6 30 12 0 2866.452 2940.957 2940.958 1416.000 +SIMU 1976 6 30 24 0 2798.310 2856.396 2856.396 1416.000 +SIMU 1976 7 1 12 0 2712.273 2757.601 2757.601 1368.000 +SIMU 1976 7 1 24 0 2644.846 2680.256 2680.256 1368.000 +SIMU 1976 7 2 12 0 2569.992 2597.689 2597.689 1248.000 +SIMU 1976 7 2 24 0 2521.579 2543.271 2543.271 1248.000 +SIMU 1976 7 3 12 0 2442.126 2459.143 2459.143 1200.000 +SIMU 1976 7 3 24 0 2360.918 2374.291 2374.291 1200.000 +SIMU 1976 7 4 12 0 2276.082 2286.612 2286.612 1128.000 +SIMU 1976 7 4 24 0 2215.493 2223.803 2223.803 1128.000 +SIMU 1976 7 5 12 0 2142.424 2148.998 2148.998 1056.000 +SIMU 1976 7 5 24 0 2081.151 2086.365 2086.365 1056.000 +SIMU 1976 7 6 12 0 2003.279 2007.428 2007.429 1008.000 +SIMU 1976 7 6 24 0 1930.496 1933.807 1933.807 1008.000 +SIMU 1976 7 7 12 0 1860.211 1862.865 1862.865 1008.000 +SIMU 1976 7 7 24 0 1801.562 1803.067 1803.067 1008.000 +SIMU 1976 7 8 12 0 1727.611 1728.135 1728.135 1008.000 +SIMU 1976 7 8 24 0 1654.591 1655.059 1655.059 1008.000 +SIMU 1976 7 9 12 0 1580.965 1581.384 1581.384 960.0000 +SIMU 1976 7 9 24 0 1521.349 1521.723 1521.723 960.0000 +SIMU 1976 7 10 12 0 1448.820 1449.155 1449.155 912.0000 +SIMU 1976 7 10 24 0 1375.131 1375.431 1375.431 912.0000 +SIMU 1976 7 11 12 0 1304.743 1305.011 1305.011 888.0000 +SIMU 1976 7 11 24 0 1248.129 1248.368 1248.368 888.0000 +SIMU 1976 7 12 12 0 1185.909 1186.123 1186.123 816.0000 +SIMU 1976 7 12 24 0 1126.353 1126.545 1126.545 816.0000 +SIMU 1976 7 13 12 0 1064.962 1065.078 1065.078 792.0000 +SIMU 1976 7 13 24 0 1008.634 1008.634 1008.634 792.0000 +SIMU 1976 7 14 12 0 947.6622 947.6622 947.6622 768.0000 +SIMU 1976 7 14 24 0 887.4125 887.4125 887.4125 768.0000 +SIMU 1976 7 15 12 0 835.6957 835.6957 835.6957 792.0000 +SIMU 1976 7 15 24 0 817.9781 823.5078 823.8835 792.0000 +SIMU 1976 7 16 12 0 788.2032 796.4568 796.4568 816.0000 +SIMU 1976 7 16 24 0 740.7318 748.1143 748.1143 816.0000 +SIMU 1976 7 17 12 0 692.7055 699.3084 699.3083 840.0000 +SIMU 1976 7 17 24 0 647.5076 653.4134 653.4134 840.0000 +SIMU 1976 7 18 12 0 602.0175 607.2998 607.2998 816.0000 +SIMU 1976 7 18 24 0 558.3641 563.0889 563.0889 816.0000 +SIMU 1976 7 19 12 0 524.3542 528.5801 528.5801 792.0000 +SIMU 1976 7 19 24 0 504.0474 507.8271 507.8271 792.0000 +SIMU 1976 7 20 12 0 479.9358 483.4558 488.4977 816.0000 +SIMU 1976 7 20 24 0 480.9326 484.4180 503.8568 816.0000 +SIMU 1976 7 21 12 0 486.5504 489.6679 489.6679 792.0000 +SIMU 1976 7 21 24 0 479.3178 482.1062 482.1063 792.0000 +SIMU 1976 7 22 12 0 471.2202 473.7142 473.7142 792.0000 +SIMU 1976 7 22 24 0 459.2761 461.5067 461.5067 792.0000 +SIMU 1976 7 23 12 0 436.4136 438.4089 438.4089 816.0000 +SIMU 1976 7 23 24 0 408.7779 410.5625 410.5625 816.0000 +SIMU 1976 7 24 12 0 372.2911 373.8872 373.8872 768.0000 +SIMU 1976 7 24 24 0 327.2109 328.6385 328.6385 768.0000 +SIMU 1976 7 25 12 0 286.3557 287.6327 287.6327 720.0000 +SIMU 1976 7 25 24 0 250.3043 251.4465 251.4465 720.0000 +SIMU 1976 7 26 12 0 229.2224 231.0525 237.9428 720.0000 +SIMU 1976 7 26 24 0 230.0116 232.8386 232.8386 720.0000 +SIMU 1976 7 27 12 0 210.4846 213.0132 213.0132 648.0000 +SIMU 1976 7 27 24 0 185.2401 189.8054 199.3956 648.0000 +SIMU 1976 7 28 12 0 355.7942 502.2871 564.0080 1272.000 +SIMU 1976 7 28 24 0 389.4540 525.8757 525.8757 1272.000 +SIMU 1976 7 29 12 0 379.2825 492.8959 492.8959 1896.000 +SIMU 1976 7 29 24 0 359.0034 454.1112 454.1112 1896.000 +SIMU 1976 7 30 12 0 331.6174 411.6410 411.6410 1296.000 +SIMU 1976 7 30 24 0 304.1752 371.9807 375.6659 1296.000 +SIMU 1976 7 31 12 0 299.1547 356.9792 356.9792 984.0000 +SIMU 1976 7 31 24 0 294.6993 344.0361 344.0361 984.0000 +SIMU 1976 8 1 12 0 284.0786 326.3608 326.3608 864.0000 +SIMU 1976 8 1 24 0 257.2543 293.6428 293.6428 864.0000 +SIMU 1976 8 2 12 0 229.6317 261.0710 261.0710 744.0000 +SIMU 1976 8 2 24 0 203.5243 230.7866 230.7866 744.0000 +SIMU 1976 8 3 12 0 177.7175 201.4372 201.4372 672.0000 +SIMU 1976 8 3 24 0 152.2990 172.9997 172.9998 672.0000 +SIMU 1976 8 4 12 0 125.5375 143.6541 143.6541 624.0000 +SIMU 1976 8 4 24 0 96.83620 112.7313 112.7313 624.0000 +SIMU 1976 8 5 12 0 70.62148 83.98846 83.98846 552.0000 +SIMU 1976 8 5 24 0 48.83453 59.95349 59.95348 552.0000 +SIMU 1976 8 6 12 0 33.63858 43.58369 43.58369 552.0000 +SIMU 1976 8 6 24 0 17.44626 26.34144 26.34144 552.0000 +SIMU 1976 8 7 12 0 9.618545 17.57463 17.57463 528.0000 +SIMU 1976 8 7 24 0 5.715816 12.83196 12.83196 528.0000 +SIMU 1976 8 8 12 0 1.375276 7.740143 7.740143 504.0000 +SIMU 1976 8 8 24 0 0.000000 5.692911 5.692911 504.0000 +SIMU 1976 8 9 12 0 0.000000 5.091894 5.091894 480.0000 +SIMU 1976 8 9 24 0 0.000000 4.554329 4.554329 480.0000 +SIMU 1976 8 10 12 0 0.000000 4.073516 4.073516 456.0000 +SIMU 1976 8 10 24 0 0.000000 3.643464 3.643464 456.0000 +SIMU 1976 8 11 12 0 0.000000 3.258813 3.258813 504.0000 +SIMU 1976 8 11 24 0 0.000000 2.914772 2.914772 504.0000 +SIMU 1976 8 12 12 0 0.000000 2.607051 2.607051 528.0000 +SIMU 1976 8 12 24 0 0.000000 2.331817 2.331817 528.0000 +SIMU 1976 8 13 12 0 0.000000 2.085641 2.085641 480.0000 +SIMU 1976 8 13 24 0 0.000000 1.865454 1.865454 480.0000 +SIMU 1976 8 14 12 0 3.306299 5.189642 8.569720 504.0000 +SIMU 1976 8 14 24 0 4.317553 6.061530 6.061530 504.0000 +SIMU 1976 8 15 12 0 2.381328 3.941188 3.941188 528.0000 +SIMU 1976 8 15 24 0 0.000000 1.395181 1.395181 528.0000 +SIMU 1976 8 16 12 0 0.000000 1.247888 1.247888 504.0000 +SIMU 1976 8 16 24 0 0.000000 1.116145 1.116145 504.0000 +SIMU 1976 8 17 12 0 27.85040 45.21229 46.50558 480.0000 +SIMU 1976 8 17 24 0 29.45068 45.73265 45.73265 480.0000 +SIMU 1976 8 18 12 0 27.14911 41.71215 41.71215 456.0000 +SIMU 1976 8 18 24 0 21.66637 34.69194 34.69194 456.0000 +SIMU 1976 8 19 12 0 16.10777 27.75819 27.75819 432.0000 +SIMU 1976 8 19 24 0 10.52678 20.94723 20.94723 432.0000 +SIMU 1976 8 20 12 0 5.192156 14.51250 14.51250 408.0000 +SIMU 1976 8 20 24 0 0.6898000 9.026163 9.026163 408.0000 +SIMU 1976 8 21 12 0 0.000000 7.456270 7.456270 408.0000 +SIMU 1976 8 21 24 0 0.000000 6.669090 6.669090 408.0000 +SIMU 1976 8 22 12 0 0.000000 5.965015 5.965015 384.0000 +SIMU 1976 8 22 24 0 0.000000 5.335272 5.335272 384.0000 +SIMU 1976 8 23 12 0 0.000000 4.772013 4.772013 360.0000 +SIMU 1976 8 23 24 0 0.000000 4.268219 4.268219 360.0000 +SIMU 1976 8 24 12 0 0.000000 3.817610 3.817610 336.0000 +SIMU 1976 8 24 24 0 0.000000 3.414574 3.414574 336.0000 +SIMU 1976 8 25 12 0 0.000000 3.054089 3.054089 360.0000 +SIMU 1976 8 25 24 0 30.53471 54.81184 62.28218 360.0000 +SIMU 1976 8 26 12 0 37.82723 62.75433 62.99365 408.0000 +SIMU 1976 8 26 24 0 37.40852 59.71318 59.71318 408.0000 +SIMU 1976 8 27 12 0 32.02015 51.97005 51.97005 360.0000 +SIMU 1976 8 27 24 0 25.22998 43.07370 43.07370 360.0000 +SIMU 1976 8 28 12 0 18.50882 34.46874 34.46874 336.0000 +SIMU 1976 8 28 24 0 11.87564 26.15062 26.15062 336.0000 +SIMU 1976 8 29 12 0 6.554318 19.32225 19.32225 336.0000 +SIMU 1976 8 29 24 0 2.632745 14.05273 14.05273 336.0000 +SIMU 1976 8 30 12 0 4.2170662E-02 10.25652 10.25652 312.0000 +SIMU 1976 8 30 24 0 0.000000 9.135987 9.135987 312.0000 +SIMU 1976 8 31 12 0 0.000000 8.171477 8.171477 360.0000 +SIMU 1976 8 31 24 0 0.000000 7.308790 7.308790 360.0000 +SIMU 1976 9 1 12 0 0.000000 6.537181 6.537181 336.0000 +SIMU 1976 9 1 24 0 0.000000 5.847033 5.847033 336.0000 +SIMU 1976 9 2 12 0 0.000000 5.229745 5.229745 360.0000 +SIMU 1976 9 2 24 0 0.000000 4.677627 4.677627 360.0000 +SIMU 1976 9 3 12 0 0.000000 4.183796 4.183796 336.0000 +SIMU 1976 9 3 24 0 0.000000 3.742100 3.742100 336.0000 +SIMU 1976 9 4 12 0 0.000000 3.347037 3.347037 336.0000 +SIMU 1976 9 4 24 0 0.000000 2.993680 2.993680 336.0000 +SIMU 1976 9 5 12 0 0.000000 2.677629 2.677629 312.0000 +SIMU 1976 9 5 24 0 0.000000 2.394944 2.394944 312.0000 +SIMU 1976 9 6 12 0 0.000000 2.142103 2.142103 312.0000 +SIMU 1976 9 6 24 0 0.000000 1.915955 1.915955 312.0000 +SIMU 1976 9 7 12 0 0.000000 1.713682 1.713682 288.0000 +SIMU 1976 9 7 24 0 0.000000 1.532764 1.532764 288.0000 +SIMU 1976 9 8 12 0 0.000000 1.370945 1.370945 288.0000 +SIMU 1976 9 8 24 0 0.000000 1.226211 1.226211 288.0000 +SIMU 1976 9 9 12 0 0.000000 1.096756 1.096756 288.0000 +SIMU 1976 9 9 24 0 0.000000 0.9809685 0.9809685 288.0000 +SIMU 1976 9 10 12 0 0.000000 0.8774048 0.8774048 312.0000 +SIMU 1976 9 10 24 0 0.000000 0.7847747 0.7847747 312.0000 +SIMU 1976 9 11 12 0 0.000000 0.7019238 0.7019238 336.0000 +SIMU 1976 9 11 24 0 0.000000 0.6278196 0.6278196 336.0000 +SIMU 1976 9 12 12 0 0.000000 0.5615390 0.5615390 312.0000 +SIMU 1976 9 12 24 0 0.000000 0.5022559 0.5022559 312.0000 +SIMU 1976 9 13 12 0 0.000000 0.4492313 0.4492313 288.0000 +SIMU 1976 9 13 24 0 0.000000 0.4018047 0.4018047 288.0000 +SIMU 1976 9 14 12 0 0.000000 0.3593851 0.3593851 288.0000 +SIMU 1976 9 14 24 0 0.000000 0.3214438 0.3214438 288.0000 +SIMU 1976 9 15 12 0 0.000000 0.2875081 0.2875081 288.0000 +SIMU 1976 9 15 24 0 0.000000 0.2571551 0.2571551 288.0000 +SIMU 1976 9 16 12 0 0.000000 0.2300065 0.2300065 288.0000 +SIMU 1976 9 16 24 0 0.000000 0.2057241 0.2057241 288.0000 +SIMU 1976 9 17 12 0 0.000000 0.1840052 0.1840052 288.0000 +SIMU 1976 9 17 24 0 0.000000 4.9913384E-02 4.9913384E-02 288.0000 +SIMU 1976 9 18 12 0 0.000000 0.000000 0.000000 288.0000 +SIMU 1976 9 18 24 0 0.000000 0.000000 0.000000 288.0000 +SIMU 1976 9 19 12 0 11.82189 14.95630 20.28834 336.0000 +SIMU 1976 9 19 24 0 25.88178 31.69412 31.69412 336.0000 +SIMU 1976 9 20 12 0 24.66236 29.86107 29.86107 384.0000 +SIMU 1976 9 20 24 0 19.24643 23.89630 23.89630 384.0000 +SIMU 1976 9 21 12 0 14.29944 18.45841 18.45841 408.0000 +SIMU 1976 9 21 24 0 10.10197 13.82186 13.82186 408.0000 +SIMU 1976 9 22 12 0 7.246496 10.57367 10.57367 384.0000 +SIMU 1976 9 22 24 0 4.182612 7.158529 7.158529 384.0000 +SIMU 1976 9 23 12 0 0.8932837 3.555027 3.555026 336.0000 +SIMU 1976 9 23 24 0 0.000000 2.380735 2.380735 336.0000 +SIMU 1976 9 24 12 0 0.000000 2.129394 2.129394 312.0000 +SIMU 1976 9 24 24 0 0.000000 1.904588 1.904588 312.0000 +SIMU 1976 9 25 12 0 0.000000 1.703515 1.703515 312.0000 +SIMU 1976 9 25 24 0 0.000000 1.523670 1.523670 312.0000 +SIMU 1976 9 26 12 0 0.000000 1.362812 1.362812 288.0000 +SIMU 1976 9 26 24 0 0.000000 1.218936 1.218936 288.0000 +SIMU 1976 9 27 12 0 0.1548235 1.245073 1.393924 288.0000 +SIMU 1976 9 27 24 0 0.4264256 1.401574 1.401574 288.0000 +SIMU 1976 9 28 12 0 0.4221386 1.294338 1.294338 288.0000 +SIMU 1976 9 28 24 0 0.4178956 1.198015 1.198015 288.0000 +SIMU 1976 9 29 12 0 0.4136944 1.111454 1.111454 312.0000 +SIMU 1976 9 29 24 0 0.2518055 0.8759007 0.8759007 312.0000 +SIMU 1976 9 30 12 0 0.000000 0.5582076 0.5582076 288.0000 +SIMU 1976 9 30 24 0 0.000000 0.4992760 0.4992760 288.0000 +SIMU 1976 10 1 12 0 0.000000 0.4465660 0.4465660 288.0000 +SIMU 1976 10 1 24 0 0.000000 0.3994207 0.3994207 288.0000 +SIMU 1976 10 2 12 0 0.000000 0.3572528 0.3572528 0.000000 +SIMU 1976 10 2 24 0 0.000000 0.3195366 0.3195366 0.000000 +SIMU 1976 10 3 12 0 0.000000 0.2858022 0.2858022 0.000000 +SIMU 1976 10 3 24 0 0.000000 0.2556292 0.2556292 0.000000 +SIMU 1976 10 4 12 0 1.616946 1.943475 5.741490 0.000000 +SIMU 1976 10 4 24 0 8.951859 9.516360 16.73438 0.000000 +SIMU 1976 10 5 12 0 13.37803 13.92399 15.55124 0.000000 +SIMU 1976 10 5 24 0 12.00275 12.49107 12.49107 0.000000 +SIMU 1976 10 6 12 0 10.52446 10.96123 10.96123 0.000000 +SIMU 1976 10 6 24 0 10.28052 10.67118 10.67118 0.000000 +SIMU 1976 10 7 12 0 9.744522 10.09394 10.09394 0.000000 +SIMU 1976 10 7 24 0 2.493862 2.806388 2.806388 0.000000 +SIMU 1976 10 8 12 0 0.000000 0.2795316 0.2795316 0.000000 +SIMU 1976 10 8 24 0 0.000000 0.2500207 0.2500207 0.000000 +SIMU 1976 10 9 12 0 0.000000 0.2236253 0.2236253 0.000000 +SIMU 1976 10 9 24 0 0.000000 0.2000165 0.2000165 0.000000 +SIMU 1976 10 10 12 0 0.000000 0.1789002 0.1789002 0.000000 +SIMU 1976 10 10 24 0 0.000000 7.0297145E-03 7.0297145E-03 0.000000 +SIMU 1976 10 11 12 0 0.000000 0.000000 0.000000 0.000000 +SIMU 1976 10 11 24 0 0.000000 0.000000 0.000000 0.000000 +SIMU 1976 10 12 12 0 0.000000 0.000000 0.000000 0.000000 +SIMU 1976 10 12 24 0 0.000000 0.000000 0.000000 0.000000 +SIMU 1976 10 13 12 0 0.000000 0.000000 0.000000 0.000000 +SIMU 1976 10 13 24 0 0.000000 0.000000 0.000000 0.000000 +SIMU 1976 10 14 12 0 0.000000 0.000000 0.000000 0.000000 +SIMU 1976 10 14 24 0 0.000000 0.000000 0.000000 0.000000 +SIMU 1976 10 15 12 0 0.000000 0.000000 0.000000 0.000000 +SIMU 1976 10 15 24 0 0.000000 0.000000 0.000000 0.000000 +SIMU 1976 10 16 12 0 0.000000 0.000000 0.000000 0.000000 +SIMU 1976 10 16 24 0 0.000000 0.000000 0.000000 0.000000 +SIMU 1976 10 17 12 0 0.000000 0.000000 0.000000 0.000000 +SIMU 1976 10 17 24 0 0.000000 0.000000 0.000000 0.000000 +SIMU 1976 10 18 12 0 0.000000 0.000000 0.000000 0.000000 +SIMU 1976 10 18 24 0 0.1295344 0.1295344 0.3030436 0.000000 +SIMU 1976 10 19 12 0 1.904068 1.904068 6.377760 0.000000 +SIMU 1976 10 19 24 0 5.304407 5.304407 5.304407 0.000000 +SIMU 1976 10 20 12 0 5.250734 5.250734 5.250734 0.000000 +SIMU 1976 10 20 24 0 5.197873 5.197873 5.197873 0.000000 +SIMU 1976 10 21 12 0 5.145288 5.145288 5.145288 0.000000 +SIMU 1976 10 21 24 0 4.193458 4.193458 4.193458 0.000000 +SIMU 1976 10 22 12 0 3.716582 3.716582 3.716582 0.000000 +SIMU 1976 10 22 24 0 2.110835 2.110835 2.110835 0.000000 +SIMU 1976 10 23 12 0 1.469405 1.469405 1.469405 0.000000 +SIMU 1976 10 23 24 0 7.433715 7.835683 40.46391 0.000000 +SIMU 1976 10 24 12 0 26.29626 27.88728 32.70226 0.000000 +SIMU 1976 10 24 24 0 27.61778 29.14638 29.14638 0.000000 +SIMU 1976 10 25 12 0 27.32807 28.69529 28.69533 0.000000 +SIMU 1976 10 25 24 0 27.04974 28.27263 28.27262 0.000000 +SIMU 1976 10 26 12 0 26.76316 27.85693 27.85693 0.000000 +SIMU 1976 10 26 24 0 26.49056 27.46886 27.46886 0.000000 +SIMU 1976 10 27 12 0 26.21033 27.08535 27.08535 0.000000 +SIMU 1976 10 27 24 0 25.94347 26.72611 26.72611 0.000000 +SIMU 1976 10 28 12 0 25.66943 26.36945 26.36945 0.000000 +SIMU 1976 10 28 24 0 24.99927 25.62538 25.62538 0.000000 +SIMU 1976 10 29 12 0 23.76388 24.32389 24.32389 0.000000 +SIMU 1976 10 29 24 0 22.16269 22.66358 22.66358 0.000000 +SIMU 1976 10 30 12 0 23.46229 23.94492 29.29656 0.000000 +SIMU 1976 10 30 24 0 33.60037 34.24939 39.01993 0.000000 +SIMU 1976 10 31 12 0 34.18276 34.77349 34.77349 0.000000 +SIMU 1976 10 31 24 0 33.83573 34.36410 34.36410 0.000000 +SIMU 1976 11 1 12 0 33.48219 33.95477 33.95477 0.000000 +SIMU 1976 11 1 24 0 33.14237 33.56507 33.56507 0.000000 +SIMU 1976 11 2 12 0 32.79008 33.16815 33.16815 0.000000 +SIMU 1976 11 2 24 0 31.39140 31.72956 31.72956 0.000000 +SIMU 1976 11 3 12 0 30.21948 30.52194 30.52194 0.000000 +SIMU 1976 11 3 24 0 29.01873 29.28926 29.28926 0.000000 +SIMU 1976 11 4 12 0 28.42418 28.66615 28.66615 0.000000 +SIMU 1976 11 4 24 0 27.26430 27.48071 27.48071 0.000000 +SIMU 1976 11 5 12 0 26.70259 26.89616 26.89616 0.000000 +SIMU 1976 11 5 24 0 25.22231 25.35395 25.35396 0.000000 +SIMU 1976 11 6 12 0 24.41317 24.41317 24.41317 0.000000 +SIMU 1976 11 6 24 0 23.63493 23.63493 23.63493 0.000000 +SIMU 1976 11 7 12 0 23.32906 23.32906 23.32906 0.000000 +SIMU 1976 11 7 24 0 22.76479 22.76479 22.76479 0.000000 +SIMU 1976 11 8 12 0 22.43890 22.43890 22.43890 0.000000 +SIMU 1976 11 8 24 0 21.68569 21.68569 21.68569 0.000000 +SIMU 1976 11 9 12 0 20.83400 20.83400 20.83400 0.000000 +SIMU 1976 11 9 24 0 20.29675 20.29675 20.29675 0.000000 +SIMU 1976 11 10 12 0 20.06202 20.06202 20.06202 0.000000 +SIMU 1976 11 10 24 0 19.63494 19.63494 19.63494 0.000000 +SIMU 1976 11 11 12 0 19.37324 19.37324 19.37324 0.000000 +SIMU 1976 11 11 24 0 19.17737 19.17737 19.17737 0.000000 +SIMU 1976 11 12 12 0 18.98011 18.98011 18.98011 0.000000 +SIMU 1976 11 12 24 0 18.78824 18.78824 18.78824 0.000000 +SIMU 1976 11 13 12 0 18.59512 18.59512 18.59512 0.000000 +SIMU 1976 11 13 24 0 18.29562 18.29562 18.29562 0.000000 +SIMU 1976 11 14 12 0 18.08212 18.08212 18.08212 0.000000 +SIMU 1976 11 14 24 0 17.33713 17.33713 17.33713 0.000000 +SIMU 1976 11 15 12 0 16.93672 16.93672 16.93672 0.000000 +SIMU 1976 11 15 24 0 15.58869 15.58869 15.58869 0.000000 +SIMU 1976 11 16 12 0 15.04656 15.04656 15.04656 0.000000 +SIMU 1976 11 16 24 0 13.40035 13.40035 13.40035 0.000000 +SIMU 1976 11 17 12 0 12.55171 12.55171 12.55171 0.000000 +SIMU 1976 11 17 24 0 10.70698 10.70698 10.70698 0.000000 +SIMU 1976 11 18 12 0 10.10353 10.10353 10.10353 0.000000 +SIMU 1976 11 18 24 0 9.495403 9.495403 9.495403 0.000000 +SIMU 1976 11 19 12 0 9.222705 9.222705 9.222705 0.000000 +SIMU 1976 11 19 24 0 8.624109 8.624109 8.624109 0.000000 +SIMU 1976 11 20 12 0 8.384901 8.384901 8.384901 0.000000 +SIMU 1976 11 20 24 0 8.151299 8.151299 8.151299 0.000000 +SIMU 1976 11 21 12 0 8.013232 8.013232 8.013232 0.000000 +SIMU 1976 11 21 24 0 7.932450 7.932450 7.932450 0.000000 +SIMU 1976 11 22 12 0 7.851743 7.851743 7.851743 0.000000 +SIMU 1976 11 22 24 0 7.772588 7.772588 7.772588 0.000000 +SIMU 1976 11 23 12 0 7.685007 7.685007 7.685007 0.000000 +SIMU 1976 11 23 24 0 7.128718 7.128718 7.128718 0.000000 +SIMU 1976 11 24 12 0 6.824726 6.824726 6.824726 0.000000 +SIMU 1976 11 24 24 0 6.137748 6.137748 6.137748 0.000000 +SIMU 1976 11 25 12 0 5.650980 5.650980 5.650980 0.000000 +SIMU 1976 11 25 24 0 5.375116 5.375116 5.375116 0.000000 +SIMU 1976 11 26 12 0 5.265902 5.265902 5.265902 0.000000 +SIMU 1976 11 26 24 0 5.212901 5.212901 5.212901 0.000000 +SIMU 1976 11 27 12 0 5.160210 5.160210 5.160210 0.000000 +SIMU 1976 11 27 24 0 5.108275 5.108275 5.108275 0.000000 +SIMU 1976 11 28 12 0 5.056653 5.056653 5.056653 0.000000 +SIMU 1976 11 28 24 0 5.005761 5.005761 5.005761 0.000000 +SIMU 1976 11 29 12 0 4.955183 4.955183 4.955183 0.000000 +SIMU 1976 11 29 24 0 4.905315 4.905315 4.905315 0.000000 +SIMU 1976 11 30 12 0 4.855760 4.855760 4.855760 0.000000 +SIMU 1976 11 30 24 0 4.806894 4.806894 4.806894 0.000000 +SIMU 1976 12 1 12 0 4.758340 4.758340 4.758340 0.000000 +SIMU 1976 12 1 24 0 4.710457 4.710457 4.710457 0.000000 +SIMU 1976 12 2 12 0 4.662884 4.662884 4.662884 0.000000 +SIMU 1976 12 2 24 0 4.615964 4.615964 4.615964 0.000000 +SIMU 1976 12 3 12 0 4.569351 4.569351 4.569351 0.000000 +SIMU 1976 12 3 24 0 4.523374 4.523374 4.523374 0.000000 +SIMU 1976 12 4 12 0 4.477704 4.477704 4.477704 0.000000 +SIMU 1976 12 4 24 0 4.432649 4.432649 4.432649 0.000000 +SIMU 1976 12 5 12 0 4.387900 4.387900 4.387900 0.000000 +SIMU 1976 12 5 24 0 4.343751 4.343751 4.343751 0.000000 +SIMU 1976 12 6 12 0 4.299906 4.299906 4.299906 0.000000 +SIMU 1976 12 6 24 0 4.256644 4.256644 4.256644 0.000000 +SIMU 1976 12 7 12 0 4.213683 4.213683 4.213683 0.000000 +SIMU 1976 12 7 24 0 4.171290 4.171290 4.171290 0.000000 +SIMU 1976 12 8 12 0 4.129197 4.129197 4.129197 0.000000 +SIMU 1976 12 8 24 0 4.087655 4.087655 4.087655 0.000000 +SIMU 1976 12 9 12 0 4.046409 4.046409 4.046409 0.000000 +SIMU 1976 12 9 24 0 4.005703 4.005703 4.005703 0.000000 +SIMU 1976 12 10 12 0 3.965293 3.965293 3.965293 0.000000 +SIMU 1976 12 10 24 0 3.925402 3.925402 3.925402 0.000000 +SIMU 1976 12 11 12 0 3.885803 3.885803 3.885803 0.000000 +SIMU 1976 12 11 24 0 3.846713 3.846713 3.846713 0.000000 +SIMU 1976 12 12 12 0 3.807913 3.807913 3.807913 0.000000 +SIMU 1976 12 12 24 0 3.769608 3.769608 3.769608 0.000000 +SIMU 1976 12 13 12 0 3.731589 3.731589 3.731589 0.000000 +SIMU 1976 12 13 24 0 3.686623 3.686623 3.686623 0.000000 +SIMU 1976 12 14 12 0 3.646369 3.646369 3.646369 0.000000 +SIMU 1976 12 14 24 0 3.591136 3.591136 3.591136 0.000000 +SIMU 1976 12 15 12 0 3.549513 3.549513 3.549513 0.000000 +SIMU 1976 12 15 24 0 3.498237 3.498237 3.498237 0.000000 +SIMU 1976 12 16 12 0 3.455036 3.455036 3.455036 0.000000 +SIMU 1976 12 16 24 0 3.384976 3.384976 3.384976 0.000000 +SIMU 1976 12 17 12 0 3.311943 3.311943 3.311943 0.000000 +SIMU 1976 12 17 24 0 3.252935 3.252935 3.252935 0.000000 +SIMU 1976 12 18 12 0 3.257537 3.257537 3.485761 0.000000 +SIMU 1976 12 18 24 0 7.765163 7.765163 10.72768 0.000000 +SIMU 1976 12 19 12 0 8.991038 8.991038 10.32934 0.000000 +SIMU 1976 12 19 24 0 12.84119 12.84119 14.44906 0.000000 +SIMU 1976 12 20 12 0 12.99357 12.99357 12.99357 0.000000 +SIMU 1976 12 20 24 0 12.86289 12.86289 12.86289 0.000000 +SIMU 1976 12 21 12 0 12.73894 12.73894 12.73908 0.000000 +SIMU 1976 12 21 24 0 12.61096 12.61096 12.61096 0.000000 +SIMU 1976 12 22 12 0 12.48959 12.48959 12.48972 0.000000 +SIMU 1976 12 22 24 0 12.36413 12.36413 12.36413 0.000000 +SIMU 1976 12 23 12 0 12.24528 12.24528 12.24541 0.000000 +SIMU 1976 12 23 24 0 12.12229 12.12229 12.12229 0.000000 +SIMU 1976 12 24 12 0 12.00591 12.00591 12.00600 0.000000 +SIMU 1976 12 24 24 0 11.88532 11.88532 11.88532 0.000000 +SIMU 1976 12 25 12 0 11.76515 11.76515 11.76515 0.000000 +SIMU 1976 12 25 24 0 11.64672 11.64672 11.64672 0.000000 +SIMU 1976 12 26 12 0 11.52898 11.52898 11.52898 0.000000 +SIMU 1976 12 26 24 0 11.41294 11.41294 11.41294 0.000000 +SIMU 1976 12 27 12 0 11.30274 11.30274 11.30286 0.000000 +SIMU 1976 12 27 24 0 13.30873 13.30873 15.44544 0.000000 +SIMU 1976 12 28 12 0 13.87782 13.87782 13.87782 0.000000 +SIMU 1976 12 28 24 0 13.73811 13.73811 13.73811 0.000000 +SIMU 1976 12 29 12 0 13.60452 13.60452 13.60468 0.000000 +SIMU 1976 12 29 24 0 13.46780 13.46780 13.46780 0.000000 +SIMU 1976 12 30 12 0 13.33780 13.33780 13.33792 0.000000 +SIMU 1976 12 30 24 0 13.20381 13.20381 13.20381 0.000000 +SIMU 1976 12 31 12 0 13.07650 13.07650 13.07667 0.000000 +SIMU 1976 12 31 24 0 12.94514 12.94514 12.94514 0.000000 diff --git a/tests/test09/HSP2compare/TEST09.UCI b/tests/test09/HSP2compare/TEST09.UCI index 84a16e97..b088cdd8 100644 --- a/tests/test09/HSP2compare/TEST09.UCI +++ b/tests/test09/HSP2compare/TEST09.UCI @@ -7,7 +7,7 @@ GLOBAL RESUME 0 RUN 1 UNIT SYSTEM 1 END GLOBAL -FILES +FILES ***<----FILE NAME-------------------------------------------------> WDM 21 TEST.WDM MESSU 22 test09.ech @@ -358,4 +358,3 @@ RCHRES 4 HYDR ROVOL 12.1 PLTGEN 1 INPUT MEAN 3 END NETWORK END RUN - diff --git a/tests/test09/HSP2compare/TEST09bin.UCI b/tests/test09/HSP2compare/TEST09bin.UCI index a879f1f1..d59f8f28 100644 --- a/tests/test09/HSP2compare/TEST09bin.UCI +++ b/tests/test09/HSP2compare/TEST09bin.UCI @@ -7,7 +7,7 @@ GLOBAL RESUME 0 RUN 1 UNIT SYSTEM 1 END GLOBAL -FILES +FILES ***<----FILE NAME-------------------------------------------------> WDM 21 TEST.WDM MESSU 22 test09.ech @@ -43,7 +43,7 @@ PERLND # - # ATMP SNOW PWAT SED PST PWG PQAL MSTL PEST NITR PHOS TRAC *** 1 4 4 12 END PRINT-INFO - + BINARY-INFO Print-flags *** PIVL PYR # - # ATMP SNOW PWAT SED PST PWG PQAL MSTL PEST NITR PHOS TRAC *** @@ -371,4 +371,3 @@ RCHRES 4 HYDR ROVOL 12.1 PLTGEN 1 INPUT MEAN 3 END NETWORK END RUN - diff --git a/tests/test09/HSPFresults/TEST09.UCI b/tests/test09/HSPFresults/TEST09.UCI index 68fcc5a4..3d26a9db 100644 --- a/tests/test09/HSPFresults/TEST09.UCI +++ b/tests/test09/HSPFresults/TEST09.UCI @@ -7,7 +7,7 @@ GLOBAL RESUME 0 RUN 1 UNIT SYSTEM 1 END GLOBAL -FILES +FILES ***<----FILE NAME-------------------------------------------------> WDM 21 test.wdm MESSU 22 test09.ech @@ -358,4 +358,3 @@ RCHRES 4 HYDR ROVOL 12.1 PLTGEN 1 INPUT MEAN 3 END NETWORK END RUN - diff --git a/tests/test09/HSPFresults/TEST09bin.UCI b/tests/test09/HSPFresults/TEST09bin.UCI index 4400d604..f7471913 100644 --- a/tests/test09/HSPFresults/TEST09bin.UCI +++ b/tests/test09/HSPFresults/TEST09bin.UCI @@ -7,7 +7,7 @@ GLOBAL RESUME 0 RUN 1 UNIT SYSTEM 1 END GLOBAL -FILES +FILES ***<----FILE NAME-------------------------------------------------> WDM 21 test.wdm MESSU 22 test09.ech @@ -43,7 +43,7 @@ PERLND # - # ATMP SNOW PWAT SED PST PWG PQAL MSTL PEST NITR PHOS TRAC *** 1 4 4 12 END PRINT-INFO - + BINARY-INFO Print-flags *** PIVL PYR # - # ATMP SNOW PWAT SED PST PWG PQAL MSTL PEST NITR PHOS TRAC *** @@ -371,4 +371,3 @@ RCHRES 4 HYDR ROVOL 12.1 PLTGEN 1 INPUT MEAN 3 END NETWORK END RUN - diff --git a/tests/test09/HSPFresults/test09.d65 b/tests/test09/HSPFresults/test09.d65 index e8a158b7..85bf181a 100644 --- a/tests/test09/HSPFresults/test09.d65 +++ b/tests/test09/HSPFresults/test09.d65 @@ -3,42 +3,42 @@ - OUTLET INFLOW (CFS) + OUTLET INFLOW (CFS) Annual data display: Summary for period ending 1976/12 Day JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC - + 1 0.01 0.76 4.24 9.57 10.05 7.01 5.83 0.79 0.00 0.00 0.00 0.00 2 0.12 0.76 4.22 9.65 10.07 7.01 5.77 0.72 0.00 0.00 0.00 0.00 3 0.19 0.75 4.12 9.66 10.06 7.00 5.68 0.64 0.00 0.00 0.00 0.00 4 0.22 0.73 4.14 9.61 10.05 7.00 5.58 0.56 0.00 0.00 0.00 0.00 5 0.23 0.72 4.02 9.52 10.04 6.97 5.47 0.47 0.00 0.00 0.00 0.00 - + 6 0.23 0.70 3.83 9.40 10.03 6.91 5.34 0.39 0.00 0.00 0.00 0.00 7 0.23 0.69 3.69 9.24 10.02 6.83 5.20 0.30 0.00 0.00 0.00 0.00 8 0.23 0.71 3.63 9.05 10.01 6.73 5.03 0.22 0.00 0.00 0.00 0.00 9 0.22 0.76 3.61 8.85 10.00 6.60 4.86 0.14 0.00 0.00 0.00 0.00 10 0.22 0.82 3.76 8.61 9.98 6.52 4.68 0.06 0.00 0.00 0.00 0.00 - + 11 0.21 0.86 3.94 8.34 9.91 6.48 4.50 0.02 0.00 0.00 0.00 0.00 12 0.21 0.87 4.95 8.07 9.79 6.41 4.30 0.01 0.00 0.00 0.00 0.00 13 0.22 0.87 5.51 7.79 9.72 6.39 4.08 0.00 0.00 0.00 0.00 0.00 14 0.24 0.86 6.05 7.51 9.70 6.54 3.87 0.00 0.00 0.00 0.00 0.00 15 0.27 0.91 6.59 7.38 9.64 6.65 3.66 0.00 0.00 0.00 0.00 0.00 - + 16 0.29 1.08 7.07 7.26 6.93 6.70 3.28 0.00 0.00 0.00 0.00 0.00 17 0.30 1.36 7.59 7.22 7.04 6.71 2.59 0.00 0.00 0.00 0.00 0.00 18 0.31 1.45 8.04 7.69 7.03 6.68 2.10 0.00 0.00 0.00 0.00 0.00 19 0.30 1.46 8.46 8.19 7.03 6.62 1.77 0.00 0.00 0.00 0.00 0.00 20 0.30 1.48 8.77 8.57 7.02 6.54 1.54 0.00 0.00 0.00 0.00 0.00 - + 21 0.30 1.91 8.98 9.24 7.02 6.44 1.41 0.00 0.00 0.00 0.00 0.00 22 0.30 1.98 9.11 9.88 7.02 6.33 1.31 0.00 0.00 0.00 0.00 0.00 23 0.33 1.95 9.19 10.11 7.02 6.20 1.22 0.00 0.00 0.00 0.00 0.00 24 0.39 2.01 9.21 10.14 7.02 6.09 1.11 0.00 0.00 0.00 0.00 0.00 25 0.43 2.25 9.19 10.14 7.01 6.03 1.00 0.00 0.00 0.00 0.00 0.00 - + 26 0.46 2.51 9.14 10.12 7.01 5.95 0.89 0.00 0.00 0.00 0.00 0.00 27 0.50 3.08 9.07 10.10 7.00 5.88 0.80 0.00 0.00 0.00 0.00 0.00 28 0.53 3.75 8.99 10.09 7.00 5.88 0.90 0.00 0.00 0.00 0.00 0.00 @@ -54,42 +54,42 @@ - SPILLWAY INFLOW (CFS) + SPILLWAY INFLOW (CFS) Annual data display: Summary for period ending 1976/12 Day JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC - + 1 0.00 0.00 0.00 0.00 3.96 1.38 0.00 0.00 0.00 0.00 0.00 0.00 2 0.00 0.00 0.00 0.00 5.41 0.86 0.00 0.00 0.00 0.00 0.00 0.00 3 0.00 0.00 0.00 0.00 4.87 0.34 0.00 0.00 0.00 0.00 0.00 0.00 4 0.00 0.00 0.00 0.00 3.98 0.01 0.00 0.00 0.00 0.00 0.00 0.00 5 0.00 0.00 0.00 0.00 3.11 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - + 6 0.00 0.00 0.00 0.00 2.30 0.00 0.00 0.00 0.00 0.00 0.00 0.00 7 0.00 0.00 0.00 0.00 1.61 0.00 0.00 0.00 0.00 0.00 0.00 0.00 8 0.00 0.00 0.00 0.00 0.95 0.00 0.00 0.00 0.00 0.00 0.00 0.00 9 0.00 0.00 0.00 0.00 0.28 0.00 0.00 0.00 0.00 0.00 0.00 0.00 10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - + 11 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 12 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 13 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 14 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - + 16 0.00 0.00 0.00 0.00 0.37 0.00 0.00 0.00 0.00 0.00 0.00 0.00 17 0.00 0.00 0.00 0.00 4.52 0.00 0.00 0.00 0.00 0.00 0.00 0.00 18 0.00 0.00 0.00 0.00 3.90 0.00 0.00 0.00 0.00 0.00 0.00 0.00 19 0.00 0.00 0.00 0.00 3.16 0.00 0.00 0.00 0.00 0.00 0.00 0.00 20 0.00 0.00 0.00 0.00 2.46 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - + 21 0.00 0.00 0.00 0.00 1.88 0.00 0.00 0.00 0.00 0.00 0.00 0.00 22 0.00 0.00 0.00 1.06 1.76 0.00 0.00 0.00 0.00 0.00 0.00 0.00 23 0.00 0.00 0.00 8.50 2.20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 24 0.00 0.00 0.00 11.04 1.79 0.00 0.00 0.00 0.00 0.00 0.00 0.00 25 0.00 0.00 0.00 11.06 1.28 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - + 26 0.00 0.00 0.00 9.68 0.79 0.00 0.00 0.00 0.00 0.00 0.00 0.00 27 0.00 0.00 0.00 8.15 0.33 0.00 0.00 0.00 0.00 0.00 0.00 0.00 28 0.00 0.00 0.00 6.93 0.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 @@ -105,42 +105,42 @@ - KITTLE CREEK FLOW (CFS) + KITTLE CREEK FLOW (CFS) Annual data display: Summary for period ending 1976/12 Day JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC - + 1 0.01 0.76 4.23 9.57 14.03 8.41 5.83 0.79 0.00 0.00 0.00 0.00 2 0.11 0.76 4.22 9.65 15.41 7.89 5.77 0.73 0.00 0.00 0.00 0.00 3 0.19 0.75 4.13 9.66 14.97 7.37 5.69 0.65 0.00 0.00 0.00 0.00 4 0.22 0.74 4.13 9.61 14.06 7.01 5.59 0.57 0.00 0.00 0.00 0.00 5 0.23 0.72 4.04 9.53 13.18 6.97 5.47 0.48 0.00 0.00 0.00 0.00 - + 6 0.23 0.71 3.84 9.40 12.36 6.91 5.35 0.40 0.00 0.00 0.00 0.00 7 0.23 0.69 3.69 9.24 11.65 6.83 5.21 0.31 0.00 0.00 0.00 0.00 8 0.23 0.70 3.63 9.06 10.99 6.73 5.04 0.23 0.00 0.00 0.00 0.00 9 0.22 0.75 3.61 8.86 10.31 6.61 4.87 0.15 0.00 0.00 0.00 0.00 10 0.22 0.82 3.76 8.62 9.99 6.52 4.69 0.07 0.00 0.00 0.00 0.00 - + 11 0.22 0.86 3.92 8.35 9.92 6.48 4.50 0.02 0.00 0.00 0.00 0.00 12 0.21 0.87 4.91 8.08 9.80 6.41 4.31 0.01 0.00 0.00 0.00 0.00 13 0.22 0.87 5.49 7.80 9.72 6.39 4.09 0.00 0.00 0.00 0.00 0.00 14 0.24 0.87 6.03 7.52 9.70 6.53 3.88 0.00 0.00 0.00 0.00 0.00 15 0.26 0.90 6.57 7.38 9.65 6.65 3.67 0.00 0.00 0.00 0.00 0.00 - + 16 0.29 1.06 7.05 7.26 7.27 6.70 3.31 0.00 0.00 0.00 0.00 0.00 17 0.30 1.35 7.57 7.21 11.52 6.71 2.63 0.00 0.00 0.00 0.00 0.00 18 0.31 1.45 8.02 7.66 10.96 6.68 2.13 0.00 0.00 0.00 0.00 0.00 19 0.30 1.46 8.44 8.17 10.21 6.63 1.78 0.00 0.00 0.00 0.00 0.00 20 0.30 1.47 8.76 8.55 9.50 6.55 1.55 0.00 0.00 0.00 0.00 0.00 - + 21 0.30 1.88 8.97 9.21 8.92 6.45 1.42 0.00 0.00 0.00 0.00 0.00 22 0.30 1.99 9.11 10.77 8.76 6.33 1.31 0.00 0.00 0.00 0.00 0.00 23 0.32 1.95 9.19 18.39 9.22 6.20 1.22 0.00 0.00 0.00 0.00 0.00 24 0.38 2.00 9.21 21.18 8.82 6.09 1.12 0.00 0.00 0.00 0.00 0.00 25 0.43 2.23 9.19 21.21 8.31 6.03 1.00 0.00 0.00 0.00 0.00 0.00 - + 26 0.46 2.49 9.14 19.86 7.82 5.95 0.90 0.00 0.00 0.00 0.00 0.00 27 0.50 3.05 9.08 18.29 7.35 5.88 0.81 0.00 0.00 0.00 0.00 0.00 28 0.53 3.72 8.99 17.05 7.04 5.88 0.88 0.00 0.00 0.00 0.00 0.00 diff --git a/tests/test09/HSPFresults/test09.ech b/tests/test09/HSPFresults/test09.ech index c321d056..ff748e5e 100644 --- a/tests/test09/HSPFresults/test09.ech +++ b/tests/test09/HSPFresults/test09.ech @@ -1,13 +1,13 @@ - FOUND RUN - FOUND END RUN + FOUND RUN + FOUND END RUN ************************************************************ * * * Hydrological Simulation Program - FORTRAN * * * ************************************************************ - + Developed for: Modified and Maintained by - + U.S. Environmental RESPEC, Inc. Protection Agency (605)394-6512 Office of Research email: hspf@respec.com @@ -17,49 +17,49 @@ Athens, Georgia (706)355-8400 email: ceam@epamail.epa.gov - + In cooperation with: - + U.S. Geological Survey Release 12.5 Water Resources Discipline September 2018 Office of Surface Water Reston, Virginia email: h2osoft@usgs.gov - - + + Start of Job - + PREPROCESSING USERS CONTROL INPUT. - + SEARCHING FOR BOUNDARIES OF NEXT DATA SET IN USERS CONTROL INPUT. - - FOUND RUN - FOUND END RUN - + + FOUND RUN + FOUND END RUN + INTERPRETING RUN DATA SET IN USERS CONTROL INPUT - - FOUND GLOBAL - FOUND END GLOBAL - FOUND FILES - FOUND END FILES + + FOUND GLOBAL + FOUND END GLOBAL + FOUND FILES + FOUND END FILES FOUND OPN SEQUENCE FOUND END OPN SEQUENCE - FOUND PERLND - FOUND END PERLND - FOUND RCHRES - FOUND END RCHRES - FOUND FTABLES - FOUND END FTABLES - FOUND DISPLY - FOUND END DISPLY - FOUND PLTGEN - FOUND END PLTGEN - FOUND EXT SOURCES - FOUND END EXT SOURCES - FOUND NETWORK - FOUND END NETWORK - - + FOUND PERLND + FOUND END PERLND + FOUND RCHRES + FOUND END RCHRES + FOUND FTABLES + FOUND END FTABLES + FOUND DISPLY + FOUND END DISPLY + FOUND PLTGEN + FOUND END PLTGEN + FOUND EXT SOURCES + FOUND END EXT SOURCES + FOUND NETWORK + FOUND END NETWORK + + ==================================================================================================================================== PROCESSING GLOBAL BLOCK @@ -71,130 +71,130 @@ RUN INTERPRETER OUTPUT LEVEL HAS BEEN SET TO: 3 RUNTIME SPECIAL ACTION OUTPUT LEVEL HAS BEEN SET TO: 2 - + SYSTEM HAS BEEN ASKED TO INTERPRET AND EXECUTE THE RUN. RUNFG = 1 THE UNIT SYSTEM OF THE RUN WILL BE ENGLISH. EMFG = 1 - + FINISHED PROCESSING GLOBAL BLOCK ==================================================================================================================================== - + ==================================================================================================================================== CATEGORY BLOCK NOT FOUND - + FINISHED PROCESSING CATEGORY BLOCK ==================================================================================================================================== - + ==================================================================================================================================== PROCESSING OPN SEQUENCE BLOCK - - + + USERS CONTROL INPUT IS: - OPN SEQUENCE - INGRP INDELT 01:00 - PERLND 1 - RCHRES 1 - RCHRES 2 - RCHRES 3 - RCHRES 4 - DISPLY 1 - DISPLY 2 - DISPLY 3 - PLTGEN 1 - END INGRP - END OPN SEQUENCE + OPN SEQUENCE + INGRP INDELT 01:00 + PERLND 1 + RCHRES 1 + RCHRES 2 + RCHRES 3 + RCHRES 4 + DISPLY 1 + DISPLY 2 + DISPLY 3 + PLTGEN 1 + END INGRP + END OPN SEQUENCE FINISHED PROCESSING OPN SEQUENCE BLOCK ==================================================================================================================================== ==================================================================================================================================== PROCESSING FTABLES BLOCK - + USERS CONTROL INPUT IS: - FTABLES - FTABLE 1 - ROWS COLS *** - 14 6 - WINTER SUMMER SPLWAY *** - DEPTH AREA VOLUME OUTLET OUTLET DISCH *** - (FT) (ACRES) (AC-FT) DISCH DISCH (CFS) *** - (CFS) (CFS) *** - .000 .000 .0000 .0000 .0000 .0000 - 2.000 1.212 1.2120 0.0000 .0000 .0000 - 4.000 2.424 4.8480 0.0000 .0000 .0000 - 6.000 3.636 10.9080 0.0000 .0000 .0000 - 8.000 4.848 19.3920 0.0000 .0000 .0000 - 10.000 6.061 30.3050 0.0000 .0000 .0000 - 12.000 7.273 43.6380 5.0000 3.5000 .0000 - 14.000 8.485 59.3950 6.2500 4.3750 .0000 - 16.000 9.697 77.5760 7.5000 5.2500 .0000 - 18.000 10.909 98.1810 8.7500 6.1250 .0000 - 20.000 12.121 121.2100 10.0000 7.0000 .0000 - 21.000 12.727 133.6360 10.6250 7.4375 50.0000 - 22.000 13.333 146.6630 11.2500 7.8750 100.0000 - 23.000 13.939 160.3030 11.8750 8.3125 500.0000 - END FTABLE 1 - - FTABLE 2 - ROWS COLS *** - 13 4 - DEPTH AREA VOLUME DISCH FLO-THRU *** - (FT) (ACRES) (AC-FT) (CFS) (MIN) *** - .000 .000 .0000 .000 0.0 - .167 .071 .0109 1.2241 6.5 - .333 .081 .0236 3.9148 4.4 - .500 .091 .0379 7.8193 3.5 - .667 .101 .0539 12.9032 3.0 - .833 .111 .0715 19.1853 2.7 - 1.000 .121 .0909 26.7046 2.5 - 1.333 .141 .1347 45.6529 2.1 - 1.667 .162 .1852 70.1757 1.9 - 2.000 .182 .2424 100.7192 1.7 - 2.667 .586 .4983 201.9005 1.8 - 3.333 .990 1.0236 344.6344 2.2 - 4.000 1.394 1.8182 537.0775 2.5 - END FTABLE 2 - - FTABLE 3 - ROWS COLS *** - 13 4 - DEPTH AREA VOLUME DISCH FLO-THRU *** - (FT) (ACRES) (AC-FT) (CFS) (MIN) *** - .000 .000 .0000 .000 0.0 - .167 .071 .0109 1.4992 5.3 - .333 .081 .0236 4.7947 3.6 - .500 .091 .0379 9.5766 2.9 - .667 .101 .0539 15.8032 2.5 - .833 .111 .0715 23.4971 2.2 - 1.000 .121 .0909 32.7063 2.0 - 1.333 .141 .1347 55.9132 1.7 - 1.667 .162 .1852 85.9474 1.6 - 2.000 .182 .2424 123.3553 1.4 - 2.667 .586 .4983 247.2766 1.5 - 3.333 .990 1.0236 422.0892 1.8 - 4.000 1.394 1.8182 657.7828 2.0 - END FTABLE 3 - - FTABLE 4 - ROWS COLS *** - 13 4 - DEPTH AREA VOLUME DISCH FLO-THRU *** - (FT) (ACRES) (AC-FT) (CFS) (MIN) *** - .000 .000 .0000 .000 0.0 - .250 .848 .1970 .9024 158.5 - .500 .970 .4242 2.8860 106.7 - .750 1.091 .6818 5.7642 85.9 - 1.000 1.212 .9697 9.5120 74.0 - 1.250 1.333 1.2879 14.1431 66.1 - 1.500 1.455 1.6364 19.6862 60.3 - 2.000 1.697 2.4242 33.6545 52.3 - 2.500 1.939 3.3333 51.7323 46.8 - 3.000 2.182 4.3636 74.2486 42.7 - 4.000 11.879 11.3939 155.5774 53.2 - 5.000 21.576 28.1212 296.8633 68.8 - 6.000 31.273 54.5454 522.1440 75.8 - END FTABLE 4 - - END FTABLES + FTABLES + FTABLE 1 + ROWS COLS *** + 14 6 + WINTER SUMMER SPLWAY *** + DEPTH AREA VOLUME OUTLET OUTLET DISCH *** + (FT) (ACRES) (AC-FT) DISCH DISCH (CFS) *** + (CFS) (CFS) *** + .000 .000 .0000 .0000 .0000 .0000 + 2.000 1.212 1.2120 0.0000 .0000 .0000 + 4.000 2.424 4.8480 0.0000 .0000 .0000 + 6.000 3.636 10.9080 0.0000 .0000 .0000 + 8.000 4.848 19.3920 0.0000 .0000 .0000 + 10.000 6.061 30.3050 0.0000 .0000 .0000 + 12.000 7.273 43.6380 5.0000 3.5000 .0000 + 14.000 8.485 59.3950 6.2500 4.3750 .0000 + 16.000 9.697 77.5760 7.5000 5.2500 .0000 + 18.000 10.909 98.1810 8.7500 6.1250 .0000 + 20.000 12.121 121.2100 10.0000 7.0000 .0000 + 21.000 12.727 133.6360 10.6250 7.4375 50.0000 + 22.000 13.333 146.6630 11.2500 7.8750 100.0000 + 23.000 13.939 160.3030 11.8750 8.3125 500.0000 + END FTABLE 1 + + FTABLE 2 + ROWS COLS *** + 13 4 + DEPTH AREA VOLUME DISCH FLO-THRU *** + (FT) (ACRES) (AC-FT) (CFS) (MIN) *** + .000 .000 .0000 .000 0.0 + .167 .071 .0109 1.2241 6.5 + .333 .081 .0236 3.9148 4.4 + .500 .091 .0379 7.8193 3.5 + .667 .101 .0539 12.9032 3.0 + .833 .111 .0715 19.1853 2.7 + 1.000 .121 .0909 26.7046 2.5 + 1.333 .141 .1347 45.6529 2.1 + 1.667 .162 .1852 70.1757 1.9 + 2.000 .182 .2424 100.7192 1.7 + 2.667 .586 .4983 201.9005 1.8 + 3.333 .990 1.0236 344.6344 2.2 + 4.000 1.394 1.8182 537.0775 2.5 + END FTABLE 2 + + FTABLE 3 + ROWS COLS *** + 13 4 + DEPTH AREA VOLUME DISCH FLO-THRU *** + (FT) (ACRES) (AC-FT) (CFS) (MIN) *** + .000 .000 .0000 .000 0.0 + .167 .071 .0109 1.4992 5.3 + .333 .081 .0236 4.7947 3.6 + .500 .091 .0379 9.5766 2.9 + .667 .101 .0539 15.8032 2.5 + .833 .111 .0715 23.4971 2.2 + 1.000 .121 .0909 32.7063 2.0 + 1.333 .141 .1347 55.9132 1.7 + 1.667 .162 .1852 85.9474 1.6 + 2.000 .182 .2424 123.3553 1.4 + 2.667 .586 .4983 247.2766 1.5 + 3.333 .990 1.0236 422.0892 1.8 + 4.000 1.394 1.8182 657.7828 2.0 + END FTABLE 3 + + FTABLE 4 + ROWS COLS *** + 13 4 + DEPTH AREA VOLUME DISCH FLO-THRU *** + (FT) (ACRES) (AC-FT) (CFS) (MIN) *** + .000 .000 .0000 .000 0.0 + .250 .848 .1970 .9024 158.5 + .500 .970 .4242 2.8860 106.7 + .750 1.091 .6818 5.7642 85.9 + 1.000 1.212 .9697 9.5120 74.0 + 1.250 1.333 1.2879 14.1431 66.1 + 1.500 1.455 1.6364 19.6862 60.3 + 2.000 1.697 2.4242 33.6545 52.3 + 2.500 1.939 3.3333 51.7323 46.8 + 3.000 2.182 4.3636 74.2486 42.7 + 4.000 11.879 11.3939 155.5774 53.2 + 5.000 21.576 28.1212 296.8633 68.8 + 6.000 31.273 54.5454 522.1440 75.8 + END FTABLE 4 + + END FTABLES FINISHED PROCESSING FTABLES BLOCK ==================================================================================================================================== @@ -206,18 +206,18 @@ PROCESSING PERVIOUS LAND-SEGMENT NO: 1 TIME STEP(DELT): 60 MINS PROCESSING GENERAL INPUT - + AIRTFG SNOWFG PWATFG SEDFG PSTFG PWGFG PQALFG MSTLFG PESTFG NITRFG PHOSFG TRACFG 0 1 1 0 0 0 0 0 0 0 0 0 - + Printout level flags Print-ivl Print-yrend ATEMP SNOW PWAT SED PSTMP PWTG RQAL MSTL PEST NITR PHOS TRAC PIVL PYREND 4 4 4 4 4 4 4 4 4 4 4 4 1 12 - + Binary Output level flags Print-ivl Print-yrend ATEMP SNOW PWAT SED PSTMP PWTG RQAL MSTL PEST NITR PHOS TRAC PIVL PYREND 4 4 4 4 4 4 4 4 4 4 4 4 1 12 - + Perv Land-segment id Unit systems Print-file nos BinaryOutfileNos IUNITS OUNITS English Metric English Metric BICKNELL FARM 1 1 1 0 92 0 @@ -226,25 +226,25 @@ ------------------------------------------------------------------------------------------------------------------------------------ PROCESSING INPUT FOR SECTION SNOW - + ICEFG 1 - + SNOPFG VMKFG 0 0 - + LAT MELEV SHADE SNOWCF COVIND KMELT TBASE degrees (ft) (in) (in/d.F) (F) 42. 520. 0.0 1.45 0.5 0.00 32.0 - + RDCSN TSNOW SNOEVP CCFACT MWATER MGMELT (deg F) (in/day) 0.12 32. 0.05 0.5 0.08 0.0001 - + Pack-snow Pack-ice Pack-watr RDENPF DULL PAKTMP (in) (in) (in) (deg F) 1.4 0.2 0.1 0.2 375. 27.5 - + COVINX XLNMLT SKYCLR (in) (in) 0.50 0.0 1.0 @@ -253,42 +253,42 @@ ------------------------------------------------------------------------------------------------------------------------------------ PROCESSING INPUT FOR SECTION PWATER - + CSNOFG RTOPFG UZFG VCSFG VUZFG VNNFG VIFWFG VIRCFG VLEFG IFFCFG HWTFG IRRGFG IFRDFG NCANPY 1 0 0 1 1 1 0 0 1 1 0 0 0 0 - + FOREST LZSN INFILT LSUR SLSUR KVARY AGWRC (inches) (in/hr) (feet) (1/inches) (1/day) 0.010 8.0 0.150 250. 0.050 0.5 0.98 - + PETMAX PETMIN INFEXP INFILD DEEPFR BASETP AGWETP (degF) (degF) 40. 35. 2.0 2.0 0.10 0.0 0.08 - + CEPSC UZSN NSUR INTFW IRC LZETP (inches) (inches)(nManning) (1/day) 0.00 0.01 0.1 1.0 0.60 0.00 - + FZG FZGL (/in) 1.00 0.100 - + Values of Interception Storage at start of each calendar month (inches): JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 0.04 0.04 0.03 0.03 0.03 0.03 0.10 0.17 0.19 0.14 0.05 0.04 - + Values of Upper Zone Storage at start of each calendar month (inches): JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 0.4 0.4 0.4 0.4 1.6 1.1 1.1 1.3 1.3 1.3 1.1 0.9 - + Values of Manning's N at start of each calendar month: JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 0.30 0.30 0.30 0.30 0.27 0.25 0.25 0.25 0.25 0.25 0.35 0.33 - + Values of Lower Zone ET at start of each calendar month: JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 0.20 0.20 0.20 0.23 0.23 0.25 0.60 0.80 0.75 0.50 0.30 0.20 - + Segment-wide storages (inches): CEPS SURS UZS IFWS LZS AGWS GWVS 0.05 0.0 0.15 0.0 4.0 0.05 0.05 @@ -309,18 +309,18 @@ PROCESSING RCHRES NO: 1 TIME STEP(DELT): 60 MINS PROCESSING GENERAL INPUT - + HYDRFG ADFG CONSFG HTFG SEDFG GQUALFG OXFG NUTFG PLKFG PHFG 1 0 0 0 0 0 0 0 0 0 - + Printout level flags Print-ivl Print-yrend HYDR ADCA CONS HEAT SED GQL OXRX NUTR PLNK PHCB PIVL PYREND 4 4 4 4 4 4 4 4 4 4 1 12 - + Binary Output level flags Print-ivl Print-yrend HYDR ADCA CONS HEAT SED GQL OXRX NUTR PLNK PHCB PIVL PYREND 4 4 4 4 4 4 4 4 4 4 1 12 - + Reach/reservoir-id NEXITS Unit systems Print-file nos Lake- BinaryOutfileNos IUNITS OUNITS English Metric flag English Metric MEIER POND 2 1 1 1 0 1 92 0 @@ -329,19 +329,19 @@ ------------------------------------------------------------------------------------------------------------------------------------ PROCESSING INPUT FOR SECTION HYDR - + VCONFG AUX1FG AUX2FG AUX3FG ODFV-flags for ODGT-flags for FUNCT-flags for each poss. exit poss. exit each poss. exit 0 1 1 0 -1 6 0 0 0 0 0 0 0 0 1 1 1 1 1 - + MILES FT FT IN DSN FTBN LEN DELTH STCOR KS DB50 0.00 1 0.5 1. 0.00 .5 1.000E-02 - + Values of irrigation withdrawal parameters IREXIT IRMINV (ac.ft) 0.00 0.00 - + (acre-ft) CAT Init value of COLIND for each poss exit Init value of OUTDGT for each poss exit (ft3/s) VOL 1 2 3 4 5 1 2 3 4 5 @@ -373,18 +373,18 @@ PROCESSING RCHRES NO: 2 TIME STEP(DELT): 60 MINS PROCESSING GENERAL INPUT - + HYDRFG ADFG CONSFG HTFG SEDFG GQUALFG OXFG NUTFG PLKFG PHFG 1 0 0 0 0 0 0 0 0 0 - + Printout level flags Print-ivl Print-yrend HYDR ADCA CONS HEAT SED GQL OXRX NUTR PLNK PHCB PIVL PYREND 4 4 4 4 4 4 4 4 4 4 1 12 - + Binary Output level flags Print-ivl Print-yrend HYDR ADCA CONS HEAT SED GQL OXRX NUTR PLNK PHCB PIVL PYREND 4 4 4 4 4 4 4 4 4 4 1 12 - + Reach/reservoir-id NEXITS Unit systems Print-file nos Lake- BinaryOutfileNos IUNITS OUNITS English Metric flag English Metric OUTLET 1 1 1 1 0 0 92 0 @@ -393,19 +393,19 @@ ------------------------------------------------------------------------------------------------------------------------------------ PROCESSING INPUT FOR SECTION HYDR - + VCONFG AUX1FG AUX2FG AUX3FG ODFV-flags for ODGT-flags for FUNCT-flags for each poss. exit poss. exit each poss. exit 0 1 1 0 4 0 0 0 0 0 0 0 0 0 1 1 1 1 1 - + MILES FT FT IN DSN FTBN LEN DELTH STCOR KS DB50 00 2 0.25 20. 0.00 .5 1.000E-02 - + Values of irrigation withdrawal parameters IREXIT IRMINV (ac.ft) 0.00 0.00 - + (acre-ft) CAT Init value of COLIND for each poss exit Init value of OUTDGT for each poss exit (ft3/s) VOL 1 2 3 4 5 1 2 3 4 5 @@ -433,18 +433,18 @@ PROCESSING RCHRES NO: 3 TIME STEP(DELT): 60 MINS PROCESSING GENERAL INPUT - + HYDRFG ADFG CONSFG HTFG SEDFG GQUALFG OXFG NUTFG PLKFG PHFG 1 0 0 0 0 0 0 0 0 0 - + Printout level flags Print-ivl Print-yrend HYDR ADCA CONS HEAT SED GQL OXRX NUTR PLNK PHCB PIVL PYREND 4 4 4 4 4 4 4 4 4 4 1 12 - + Binary Output level flags Print-ivl Print-yrend HYDR ADCA CONS HEAT SED GQL OXRX NUTR PLNK PHCB PIVL PYREND 4 4 4 4 4 4 4 4 4 4 1 12 - + Reach/reservoir-id NEXITS Unit systems Print-file nos Lake- BinaryOutfileNos IUNITS OUNITS English Metric flag English Metric SPILLWAY 1 1 1 1 0 0 92 0 @@ -453,19 +453,19 @@ ------------------------------------------------------------------------------------------------------------------------------------ PROCESSING INPUT FOR SECTION HYDR - + VCONFG AUX1FG AUX2FG AUX3FG ODFV-flags for ODGT-flags for FUNCT-flags for each poss. exit poss. exit each poss. exit 0 1 1 0 4 0 0 0 0 0 0 0 0 0 1 1 1 1 1 - + MILES FT FT IN DSN FTBN LEN DELTH STCOR KS DB50 00 3 0.25 30. 0.00 .5 1.000E-02 - + Values of irrigation withdrawal parameters IREXIT IRMINV (ac.ft) 0.00 0.00 - + (acre-ft) CAT Init value of COLIND for each poss exit Init value of OUTDGT for each poss exit (ft3/s) VOL 1 2 3 4 5 1 2 3 4 5 @@ -493,18 +493,18 @@ PROCESSING RCHRES NO: 4 TIME STEP(DELT): 60 MINS PROCESSING GENERAL INPUT - + HYDRFG ADFG CONSFG HTFG SEDFG GQUALFG OXFG NUTFG PLKFG PHFG 1 0 0 0 0 0 0 0 0 0 - + Printout level flags Print-ivl Print-yrend HYDR ADCA CONS HEAT SED GQL OXRX NUTR PLNK PHCB PIVL PYREND 4 4 4 4 4 4 4 4 4 4 1 12 - + Binary Output level flags Print-ivl Print-yrend HYDR ADCA CONS HEAT SED GQL OXRX NUTR PLNK PHCB PIVL PYREND 4 4 4 4 4 4 4 4 4 4 1 12 - + Reach/reservoir-id NEXITS Unit systems Print-file nos Lake- BinaryOutfileNos IUNITS OUNITS English Metric flag English Metric KITTLE CREEK 1 1 1 1 0 0 92 0 @@ -513,19 +513,19 @@ ------------------------------------------------------------------------------------------------------------------------------------ PROCESSING INPUT FOR SECTION HYDR - + VCONFG AUX1FG AUX2FG AUX3FG ODFV-flags for ODGT-flags for FUNCT-flags for each poss. exit poss. exit each poss. exit 0 1 1 0 4 0 0 0 0 0 0 0 0 0 1 1 1 1 1 - + MILES FT FT IN DSN FTBN LEN DELTH STCOR KS DB50 00 4 2.0 40. 0.00 .5 1.000E-02 - + Values of irrigation withdrawal parameters IREXIT IRMINV (ac.ft) 0.00 0.00 - + (acre-ft) CAT Init value of COLIND for each poss exit Init value of OUTDGT for each poss exit (ft3/s) VOL 1 2 3 4 5 1 2 3 4 5 @@ -557,11 +557,11 @@ ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ PROCESSING DISPLY OPERATION NO. 1 TIME INTERVAL 60 MINS - + Title of display Transform Data for short-span display Data for long-span display code PIVL Digits File-no. PYRFG Digits File-no. PYREND OUTLET INFLOW (CFS) AVER 0 4 1 2 65 12 - + Convert DegC to F Display negative data A B THRSH1 THRSH2 1.00 0.00 0.00 0.00 @@ -571,11 +571,11 @@ ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ PROCESSING DISPLY OPERATION NO. 2 TIME INTERVAL 60 MINS - + Title of display Transform Data for short-span display Data for long-span display code PIVL Digits File-no. PYRFG Digits File-no. PYREND SPILLWAY INFLOW (CFS) AVER 0 4 1 2 65 12 - + Convert DegC to F Display negative data A B THRSH1 THRSH2 1.00 0.00 0.00 0.00 @@ -585,11 +585,11 @@ ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ PROCESSING DISPLY OPERATION NO. 3 TIME INTERVAL 60 MINS - + Title of display Transform Data for short-span display Data for long-span display code PIVL Digits File-no. PYRFG Digits File-no. PYREND KITTLE CREEK FLOW (CFS) AVER 0 4 1 2 65 12 - + Convert DegC to F Display negative data A B THRSH1 THRSH2 1.00 0.00 0.00 0.00 @@ -605,23 +605,23 @@ ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ PROCESSING PLTGEN OPERATION NO. 1 - + PLOTFL NPT NMN LABLFG PYREND PIVL TYPEFG 93 0 3 0 9 24 1 - + General plot title: Y-axis label: - SIMULATED FLOWS (CFS) CFS - + SIMULATED FLOWS (CFS) CFS + YMIN YMAX IVLIN THRESH (ivl/in) 0. 25. 20.-1.000E+30 - + Curve label: LINTYP INTEQ COLCOD TRAN SPILLWAY INFLOW 0 1 1 AVER - + Curve label: LINTYP INTEQ COLCOD TRAN OUTLET INFLOW 1 3 1 AVER - + Curve label: LINTYP INTEQ COLCOD TRAN KITTLE CREEK 2 8 2 AVER @@ -650,7 +650,7 @@ INPUT TIMESERIES FROM EXTERNAL SOURCES - TYPE # INTERVAL TRN STR MFACT GROUP MEMBER S1 S2 + TYPE # INTERVAL TRN STR MFACT GROUP MEMBER S1 S2 WDM1 39 60 SAME 1.000E+00 EXTNL PREC 1 1 WDM1 123 120 SAME 1.000E+00 ATEMP AIRTMP 1 1 @@ -662,7 +662,7 @@ OUTPUT TIMESERIES TO OTHER OPERATIONS(NETWORK) - GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 + GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 PWATER PERO 1 1 5.000E+02 RCHRES 1 EXTNL IVOL 1 1 @@ -674,21 +674,21 @@ INPUT TIMESERIES FROM EXTERNAL SOURCES - TYPE # INTERVAL TRN STR MFACT GROUP MEMBER S1 S2 + TYPE # INTERVAL TRN STR MFACT GROUP MEMBER S1 S2 WDM1 39 60 SAME 1.000E+00 EXTNL PREC 1 1 WDM1 41 1440 DIV 7.000E-01 EXTNL POTEV 1 1 WDM1 140 1440 SAME 1.000E+00 EXTNL COLIND 1 1 FROM OTHER OPERATIONS(NETWORK) - TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 + TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 PERLND 1 PWATER PERO 1 1 5.000E+02 EXTNL IVOL 1 1 OUTPUT TIMESERIES TO OTHER OPERATIONS(NETWORK) - GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 + GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 HYDR OVOL 1 1 1.000E+00 RCHRES 2 EXTNL IVOL 1 1 HYDR OVOL 1 1 1.210E+01 DISPLY 1 INPUT TIMSER 1 1 @@ -705,14 +705,14 @@ INPUT TIMESERIES FROM OTHER OPERATIONS(NETWORK) - TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 + TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 RCHRES 1 HYDR OVOL 1 1 1.000E+00 EXTNL IVOL 1 1 OUTPUT TIMESERIES TO OTHER OPERATIONS(NETWORK) - GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 + GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 HYDR ROVOL 1 1 1.000E+00 RCHRES 4 EXTNL IVOL 1 1 @@ -724,14 +724,14 @@ INPUT TIMESERIES FROM OTHER OPERATIONS(NETWORK) - TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 + TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 RCHRES 1 HYDR OVOL 2 1 1.000E+00 EXTNL IVOL 1 1 OUTPUT TIMESERIES TO OTHER OPERATIONS(NETWORK) - GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 + GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 HYDR ROVOL 1 1 1.000E+00 RCHRES 4 EXTNL IVOL 1 1 @@ -743,7 +743,7 @@ INPUT TIMESERIES FROM OTHER OPERATIONS(NETWORK) - TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 + TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 RCHRES 2 HYDR ROVOL 1 1 1.000E+00 EXTNL IVOL 1 1 RCHRES 3 HYDR ROVOL 1 1 1.000E+00 EXTNL IVOL 1 1 @@ -751,7 +751,7 @@ OUTPUT TIMESERIES TO OTHER OPERATIONS(NETWORK) - GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 + GROUP MEMBER S1 S2 MFACT TYPE # GROUP MEMBER S1 S2 HYDR ROVOL 1 1 1.210E+01 DISPLY 3 INPUT TIMSER 1 1 HYDR ROVOL 1 1 1.210E+01 PLTGEN 1 INPUT MEAN 3 1 @@ -764,7 +764,7 @@ INPUT TIMESERIES FROM OTHER OPERATIONS(NETWORK) - TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 + TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 RCHRES 1 HYDR OVOL 1 1 1.210E+01 INPUT TIMSER 1 1 @@ -776,7 +776,7 @@ INPUT TIMESERIES FROM OTHER OPERATIONS(NETWORK) - TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 + TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 RCHRES 1 HYDR OVOL 2 1 1.210E+01 INPUT TIMSER 1 1 @@ -788,7 +788,7 @@ INPUT TIMESERIES FROM OTHER OPERATIONS(NETWORK) - TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 + TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 RCHRES 4 HYDR ROVOL 1 1 1.210E+01 INPUT TIMSER 1 1 @@ -800,7 +800,7 @@ INPUT TIMESERIES FROM OTHER OPERATIONS(NETWORK) - TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 + TYPE # GROUP MEMBER S1 S2 MFACT GROUP MEMBER S1 S2 RCHRES 1 HYDR OVOL 1 1 1.210E+01 INPUT MEAN 2 1 RCHRES 1 HYDR OVOL 2 1 1.210E+01 INPUT MEAN 1 1 @@ -808,10 +808,10 @@ FINISHED PROCESSING BLOCKS CONTAINING TIME SERIES LINKAGES ==================================================================================================================================== - + INTERPRETATION OF RUN DATA SET COMPLETE - + COMMENCING EXECUTION - + End of Job diff --git a/tests/test09/HSPFresults/test09.p93 b/tests/test09/HSPFresults/test09.p93 index c813bdfa..1acea649 100644 --- a/tests/test09/HSPFresults/test09.p93 +++ b/tests/test09/HSPFresults/test09.p93 @@ -2,10 +2,10 @@ SIMU HSPF FILE FOR DRIVING SEPARATE PLOT PROGRAM SIMU Time interval: 1440 mins Last month in printout year: 9 SIMU No. of curves plotted: Point-valued: 0 Mean-valued: 3 Total 3 SIMU Label flag: 0 Pivl: 24 Idelt: 60 -SIMU Plot title: SIMULATED FLOWS (CFS) -SIMU Y-axis label: CFS +SIMU Plot title: SIMULATED FLOWS (CFS) +SIMU Y-axis label: CFS SIMU Scale info: Ymin: 0.0000 Threshold:-0.10000E+31 -SIMU Ymax: 25.000 +SIMU Ymax: 25.000 SIMU Time: 20.000 intervals/inch SIMU Data for each curve (Point-valued first, then mean-valued): SIMU Label LINTYP INTEQ COLCOD TRAN TRANCOD @@ -25,368 +25,368 @@ SIMU Date/time Values SIMU SIMU 1975 12 31 24 0-1.0000000E+30-1.0000000E+30-1.0000000E+30 SIMU 1976 1 1 24 0 0.000000 1.4474314E-02 8.6380793E-03 -SIMU 1976 1 2 24 0 0.000000 0.1248720 0.1125099 -SIMU 1976 1 3 24 0 0.000000 0.1905476 0.1851986 -SIMU 1976 1 4 24 0 0.000000 0.2189076 0.2166849 -SIMU 1976 1 5 24 0 0.000000 0.2296369 0.2288925 -SIMU 1976 1 6 24 0 0.000000 0.2335850 0.2330104 -SIMU 1976 1 7 24 0 0.000000 0.2338135 0.2343417 -SIMU 1976 1 8 24 0 0.000000 0.2288434 0.2294084 -SIMU 1976 1 9 24 0 0.000000 0.2239729 0.2245262 -SIMU 1976 1 10 24 0 0.000000 0.2192056 0.2197471 -SIMU 1976 1 11 24 0 0.000000 0.2145421 0.2150717 -SIMU 1976 1 12 24 0 0.000000 0.2119149 0.2117690 -SIMU 1976 1 13 24 0 0.000000 0.2217572 0.2198658 -SIMU 1976 1 14 24 0 0.000000 0.2424261 0.2399701 -SIMU 1976 1 15 24 0 0.000000 0.2671344 0.2637548 -SIMU 1976 1 16 24 0 0.000000 0.2947665 0.2925780 -SIMU 1976 1 17 24 0 0.000000 0.3046337 0.3040124 -SIMU 1976 1 18 24 0 0.000000 0.3057772 0.3058844 -SIMU 1976 1 19 24 0 0.000000 0.3028567 0.3033009 -SIMU 1976 1 20 24 0 0.000000 0.2990208 0.2992778 -SIMU 1976 1 21 24 0 0.000000 0.2986757 0.2987883 -SIMU 1976 1 22 24 0 0.000000 0.3007911 0.2997144 -SIMU 1976 1 23 24 0 0.000000 0.3295574 0.3238677 -SIMU 1976 1 24 24 0 0.000000 0.3869472 0.3812667 -SIMU 1976 1 25 24 0 0.000000 0.4336508 0.4285055 -SIMU 1976 1 26 24 0 0.000000 0.4649239 0.4612200 -SIMU 1976 1 27 24 0 0.000000 0.5011643 0.4983417 -SIMU 1976 1 28 24 0 0.000000 0.5325606 0.5258945 -SIMU 1976 1 29 24 0 0.000000 0.6205746 0.6085952 -SIMU 1976 1 30 24 0 0.000000 0.7192406 0.7113194 -SIMU 1976 1 31 24 0 0.000000 0.7556167 0.7532462 -SIMU 1976 2 1 24 0 0.000000 0.7623713 0.7621542 -SIMU 1976 2 2 24 0 0.000000 0.7600473 0.7607731 -SIMU 1976 2 3 24 0 0.000000 0.7489523 0.7504413 -SIMU 1976 2 4 24 0 0.000000 0.7345909 0.7363094 -SIMU 1976 2 5 24 0 0.000000 0.7190740 0.7208760 -SIMU 1976 2 6 24 0 0.000000 0.7032824 0.7050893 -SIMU 1976 2 7 24 0 0.000000 0.6916801 0.6920239 -SIMU 1976 2 8 24 0 0.000000 0.7083429 0.7042727 -SIMU 1976 2 9 24 0 0.000000 0.7615871 0.7546917 -SIMU 1976 2 10 24 0 0.000000 0.8247172 0.8184053 -SIMU 1976 2 11 24 0 0.000000 0.8625719 0.8598288 -SIMU 1976 2 12 24 0 0.000000 0.8718647 0.8712609 -SIMU 1976 2 13 24 0 0.000000 0.8734022 0.8737460 -SIMU 1976 2 14 24 0 0.000000 0.8642851 0.8656677 -SIMU 1976 2 15 24 0 0.000000 0.9129595 0.9049062 -SIMU 1976 2 16 24 0 0.000000 1.078044 1.059682 -SIMU 1976 2 17 24 0 0.000000 1.359820 1.349433 -SIMU 1976 2 18 24 0 0.000000 1.452251 1.449551 -SIMU 1976 2 19 24 0 0.000000 1.464540 1.464820 -SIMU 1976 2 20 24 0 0.000000 1.481434 1.471503 -SIMU 1976 2 21 24 0 0.000000 1.906745 1.884500 -SIMU 1976 2 22 24 0 0.000000 1.984607 1.986099 -SIMU 1976 2 23 24 0 0.000000 1.953152 1.954437 -SIMU 1976 2 24 24 0 0.000000 2.010689 1.999853 -SIMU 1976 2 25 24 0 0.000000 2.245111 2.232913 -SIMU 1976 2 26 24 0 0.000000 2.511892 2.486479 -SIMU 1976 2 27 24 0 0.000000 3.084428 3.050205 -SIMU 1976 2 28 24 0 0.000000 3.745470 3.720134 -SIMU 1976 2 29 24 0 0.000000 4.127980 4.116868 -SIMU 1976 3 1 24 0 0.000000 4.235329 4.234165 -SIMU 1976 3 2 24 0 0.000000 4.215328 4.217963 -SIMU 1976 3 3 24 0 0.000000 4.121662 4.126784 -SIMU 1976 3 4 24 0 0.000000 4.138225 4.134162 -SIMU 1976 3 5 24 0 0.000000 4.024909 4.035726 -SIMU 1976 3 6 24 0 0.000000 3.829541 3.837712 -SIMU 1976 3 7 24 0 0.000000 3.687015 3.691668 -SIMU 1976 3 8 24 0 0.000000 3.629119 3.631645 -SIMU 1976 3 9 24 0 0.000000 3.611779 3.607877 -SIMU 1976 3 10 24 0 0.000000 3.763959 3.757464 -SIMU 1976 3 11 24 0 0.000000 3.943267 3.921299 -SIMU 1976 3 12 24 0 0.000000 4.953779 4.908589 -SIMU 1976 3 13 24 0 0.000000 5.509392 5.485821 -SIMU 1976 3 14 24 0 0.000000 6.053998 6.030756 -SIMU 1976 3 15 24 0 0.000000 6.591527 6.571682 -SIMU 1976 3 16 24 0 0.000000 7.068567 7.047995 -SIMU 1976 3 17 24 0 0.000000 7.586174 7.566631 -SIMU 1976 3 18 24 0 0.000000 8.037082 8.019219 -SIMU 1976 3 19 24 0 0.000000 8.455155 8.440041 -SIMU 1976 3 20 24 0 0.000000 8.771515 8.760997 -SIMU 1976 3 21 24 0 0.000000 8.978786 8.971905 -SIMU 1976 3 22 24 0 0.000000 9.113884 9.109606 -SIMU 1976 3 23 24 0 0.000000 9.189359 9.187323 -SIMU 1976 3 24 24 0 0.000000 9.213420 9.213323 -SIMU 1976 3 25 24 0 0.000000 9.193388 9.194930 -SIMU 1976 3 26 24 0 0.000000 9.138386 9.140846 -SIMU 1976 3 27 24 0 0.000000 9.074394 9.077370 -SIMU 1976 3 28 24 0 0.000000 8.985065 8.989177 -SIMU 1976 3 29 24 0 0.000000 8.907846 8.907939 -SIMU 1976 3 30 24 0 0.000000 9.129716 9.115706 -SIMU 1976 3 31 24 0 0.000000 9.409184 9.400278 -SIMU 1976 4 1 24 0 0.000000 9.573208 9.568831 -SIMU 1976 4 2 24 0 0.000000 9.649462 9.647945 -SIMU 1976 4 3 24 0 0.000000 9.657434 9.658134 -SIMU 1976 4 4 24 0 0.000000 9.611531 9.613969 -SIMU 1976 4 5 24 0 0.000000 9.521956 9.526024 -SIMU 1976 4 6 24 0 0.000000 9.395257 9.400982 -SIMU 1976 4 7 24 0 0.000000 9.237177 9.244081 -SIMU 1976 4 8 24 0 0.000000 9.052279 9.060176 -SIMU 1976 4 9 24 0 0.000000 8.847823 8.856330 -SIMU 1976 4 10 24 0 0.000000 8.610672 8.621189 -SIMU 1976 4 11 24 0 0.000000 8.342372 8.353351 -SIMU 1976 4 12 24 0 0.000000 8.068358 8.079432 -SIMU 1976 4 13 24 0 0.000000 7.788944 7.800454 -SIMU 1976 4 14 24 0 0.000000 7.506726 7.516598 -SIMU 1976 4 15 24 0 0.000000 7.377091 7.380398 -SIMU 1976 4 16 24 0 0.000000 7.255644 7.261735 -SIMU 1976 4 17 24 0 0.000000 7.220002 7.214374 -SIMU 1976 4 18 24 0 0.000000 7.688132 7.662509 -SIMU 1976 4 19 24 0 0.000000 8.188305 8.171724 -SIMU 1976 4 20 24 0 0.000000 8.572078 8.552597 -SIMU 1976 4 21 24 0 0.000000 9.236757 9.207616 -SIMU 1976 4 22 24 0 1.064394 9.884415 10.76901 -SIMU 1976 4 23 24 0 8.498691 10.10623 18.38935 -SIMU 1976 4 24 24 0 11.04347 10.13804 21.17851 -SIMU 1976 4 25 24 0 11.05965 10.13825 21.20769 -SIMU 1976 4 26 24 0 9.681353 10.12102 19.85613 -SIMU 1976 4 27 24 0 8.145959 10.10183 18.29488 -SIMU 1976 4 28 24 0 6.926775 10.08658 17.05055 -SIMU 1976 4 29 24 0 5.795807 10.07245 15.90559 -SIMU 1976 4 30 24 0 4.818775 10.06023 14.91012 -SIMU 1976 5 1 24 0 3.955667 10.04945 14.03450 -SIMU 1976 5 2 24 0 5.405225 10.06756 15.40930 -SIMU 1976 5 3 24 0 4.873699 10.06092 14.96735 -SIMU 1976 5 4 24 0 3.979357 10.04974 14.05960 -SIMU 1976 5 5 24 0 3.111852 10.03890 13.18273 -SIMU 1976 5 6 24 0 2.299815 10.02875 12.35783 -SIMU 1976 5 7 24 0 1.608672 10.02011 11.65280 -SIMU 1976 5 8 24 0 0.9515235 10.01189 10.98877 -SIMU 1976 5 9 24 0 0.2810584 10.00351 10.31089 -SIMU 1976 5 10 24 0 1.1198178E-05 9.982972 9.985147 -SIMU 1976 5 11 24 0 0.000000 9.912993 9.916433 -SIMU 1976 5 12 24 0 0.000000 9.793891 9.798832 -SIMU 1976 5 13 24 0 0.000000 9.716702 9.717129 -SIMU 1976 5 14 24 0 0.000000 9.698365 9.699844 -SIMU 1976 5 15 24 0 0.000000 9.643738 9.645794 -SIMU 1976 5 16 24 0 0.3679665 6.930306 7.272403 -SIMU 1976 5 17 24 0 4.521122 7.039560 11.51796 -SIMU 1976 5 18 24 0 3.897263 7.034101 10.95958 -SIMU 1976 5 19 24 0 3.155860 7.027614 10.21031 -SIMU 1976 5 20 24 0 2.456451 7.021493 9.504502 -SIMU 1976 5 21 24 0 1.877169 7.016425 8.915241 -SIMU 1976 5 22 24 0 1.756312 7.015368 8.755388 -SIMU 1976 5 23 24 0 2.202089 7.019268 9.220018 -SIMU 1976 5 24 24 0 1.787248 7.015639 8.822639 -SIMU 1976 5 25 24 0 1.280952 7.011209 8.314347 -SIMU 1976 5 26 24 0 0.7877756 7.006894 7.815502 -SIMU 1976 5 27 24 0 0.3316932 7.002902 7.353515 -SIMU 1976 5 28 24 0 6.7844316E-02 6.998137 7.041820 -SIMU 1976 5 29 24 0 3.333377 7.029168 10.26768 -SIMU 1976 5 30 24 0 2.597399 7.022727 9.648638 -SIMU 1976 5 31 24 0 1.938582 7.016963 8.980260 -SIMU 1976 6 1 24 0 1.380618 7.012081 8.414832 -SIMU 1976 6 2 24 0 0.8569149 7.007498 7.886508 -SIMU 1976 6 3 24 0 0.3449340 7.003019 7.369867 -SIMU 1976 6 4 24 0 1.1105535E-02 6.995922 7.013830 -SIMU 1976 6 5 24 0 0.000000 6.966249 6.968029 -SIMU 1976 6 6 24 0 0.000000 6.908278 6.911087 -SIMU 1976 6 7 24 0 0.000000 6.827023 6.830715 -SIMU 1976 6 8 24 0 0.000000 6.725461 6.729936 -SIMU 1976 6 9 24 0 0.000000 6.604326 6.609624 -SIMU 1976 6 10 24 0 0.000000 6.522068 6.523443 -SIMU 1976 6 11 24 0 0.000000 6.480482 6.482765 -SIMU 1976 6 12 24 0 0.000000 6.409979 6.412432 -SIMU 1976 6 13 24 0 0.000000 6.394574 6.392076 -SIMU 1976 6 14 24 0 0.000000 6.540310 6.534281 -SIMU 1976 6 15 24 0 0.000000 6.649074 6.645895 -SIMU 1976 6 16 24 0 0.000000 6.700322 6.699082 -SIMU 1976 6 17 24 0 0.000000 6.707293 6.707804 -SIMU 1976 6 18 24 0 0.000000 6.678737 6.680389 -SIMU 1976 6 19 24 0 0.000000 6.623828 6.626516 -SIMU 1976 6 20 24 0 0.000000 6.544623 6.548285 -SIMU 1976 6 21 24 0 0.000000 6.444735 6.449089 -SIMU 1976 6 22 24 0 0.000000 6.328608 6.333622 -SIMU 1976 6 23 24 0 0.000000 6.197574 6.203137 -SIMU 1976 6 24 24 0 0.000000 6.086979 6.089646 -SIMU 1976 6 25 24 0 0.000000 6.030831 6.033754 -SIMU 1976 6 26 24 0 0.000000 5.945920 5.949395 -SIMU 1976 6 27 24 0 0.000000 5.878276 5.880149 -SIMU 1976 6 28 24 0 0.000000 5.878632 5.877500 -SIMU 1976 6 29 24 0 0.000000 5.893168 5.893247 -SIMU 1976 6 30 24 0 0.000000 5.875127 5.876381 -SIMU 1976 7 1 24 0 0.000000 5.830767 5.833010 -SIMU 1976 7 2 24 0 0.000000 5.766719 5.769744 -SIMU 1976 7 3 24 0 0.000000 5.684404 5.688806 -SIMU 1976 7 4 24 0 0.000000 5.582630 5.587656 -SIMU 1976 7 5 24 0 0.000000 5.468915 5.474516 -SIMU 1976 7 6 24 0 0.000000 5.342124 5.348369 -SIMU 1976 7 7 24 0 0.000000 5.198686 5.205951 -SIMU 1976 7 8 24 0 0.000000 5.034304 5.042291 -SIMU 1976 7 9 24 0 0.000000 4.861050 4.869270 -SIMU 1976 7 10 24 0 0.000000 4.681617 4.690247 -SIMU 1976 7 11 24 0 0.000000 4.496208 4.504934 -SIMU 1976 7 12 24 0 0.000000 4.298974 4.308869 -SIMU 1976 7 13 24 0 0.000000 4.083657 4.093746 -SIMU 1976 7 14 24 0 0.000000 3.869218 3.879362 -SIMU 1976 7 15 24 0 0.000000 3.658866 3.668646 -SIMU 1976 7 16 24 0 0.000000 3.282700 3.312535 -SIMU 1976 7 17 24 0 0.000000 2.593732 2.628525 -SIMU 1976 7 18 24 0 0.000000 2.104317 2.129354 -SIMU 1976 7 19 24 0 0.000000 1.765723 1.782676 -SIMU 1976 7 20 24 0 0.000000 1.541887 1.551700 -SIMU 1976 7 21 24 0 0.000000 1.412265 1.419812 -SIMU 1976 7 22 24 0 0.000000 1.308958 1.314430 -SIMU 1976 7 23 24 0 0.000000 1.218832 1.224497 -SIMU 1976 7 24 24 0 0.000000 1.114509 1.121729 -SIMU 1976 7 25 24 0 0.000000 0.9957278 1.003061 -SIMU 1976 7 26 24 0 0.000000 0.8912926 0.8990182 -SIMU 1976 7 27 24 0 0.000000 0.8027412 0.8130304 -SIMU 1976 7 28 24 0 0.000000 0.8977730 0.8814639 -SIMU 1976 7 29 24 0 0.000000 0.9119665 0.9128415 -SIMU 1976 7 30 24 0 0.000000 0.8776549 0.8812769 -SIMU 1976 7 31 24 0 0.000000 0.8408716 0.8465602 -SIMU 1976 8 1 24 0 0.000000 0.7861381 0.7930158 -SIMU 1976 8 2 24 0 0.000000 0.7172629 0.7256063 -SIMU 1976 8 3 24 0 0.000000 0.6406082 0.6496004 -SIMU 1976 8 4 24 0 0.000000 0.5580251 0.5678375 -SIMU 1976 8 5 24 0 0.000000 0.4727765 0.4823331 -SIMU 1976 8 6 24 0 0.000000 0.3866437 0.3968916 -SIMU 1976 8 7 24 0 0.000000 0.3015579 0.3106800 -SIMU 1976 8 8 24 0 0.000000 0.2223694 0.2316677 -SIMU 1976 8 9 24 0 0.000000 0.1386606 0.1484068 +SIMU 1976 1 2 24 0 0.000000 0.1248720 0.1125099 +SIMU 1976 1 3 24 0 0.000000 0.1905476 0.1851986 +SIMU 1976 1 4 24 0 0.000000 0.2189076 0.2166849 +SIMU 1976 1 5 24 0 0.000000 0.2296369 0.2288925 +SIMU 1976 1 6 24 0 0.000000 0.2335850 0.2330104 +SIMU 1976 1 7 24 0 0.000000 0.2338135 0.2343417 +SIMU 1976 1 8 24 0 0.000000 0.2288434 0.2294084 +SIMU 1976 1 9 24 0 0.000000 0.2239729 0.2245262 +SIMU 1976 1 10 24 0 0.000000 0.2192056 0.2197471 +SIMU 1976 1 11 24 0 0.000000 0.2145421 0.2150717 +SIMU 1976 1 12 24 0 0.000000 0.2119149 0.2117690 +SIMU 1976 1 13 24 0 0.000000 0.2217572 0.2198658 +SIMU 1976 1 14 24 0 0.000000 0.2424261 0.2399701 +SIMU 1976 1 15 24 0 0.000000 0.2671344 0.2637548 +SIMU 1976 1 16 24 0 0.000000 0.2947665 0.2925780 +SIMU 1976 1 17 24 0 0.000000 0.3046337 0.3040124 +SIMU 1976 1 18 24 0 0.000000 0.3057772 0.3058844 +SIMU 1976 1 19 24 0 0.000000 0.3028567 0.3033009 +SIMU 1976 1 20 24 0 0.000000 0.2990208 0.2992778 +SIMU 1976 1 21 24 0 0.000000 0.2986757 0.2987883 +SIMU 1976 1 22 24 0 0.000000 0.3007911 0.2997144 +SIMU 1976 1 23 24 0 0.000000 0.3295574 0.3238677 +SIMU 1976 1 24 24 0 0.000000 0.3869472 0.3812667 +SIMU 1976 1 25 24 0 0.000000 0.4336508 0.4285055 +SIMU 1976 1 26 24 0 0.000000 0.4649239 0.4612200 +SIMU 1976 1 27 24 0 0.000000 0.5011643 0.4983417 +SIMU 1976 1 28 24 0 0.000000 0.5325606 0.5258945 +SIMU 1976 1 29 24 0 0.000000 0.6205746 0.6085952 +SIMU 1976 1 30 24 0 0.000000 0.7192406 0.7113194 +SIMU 1976 1 31 24 0 0.000000 0.7556167 0.7532462 +SIMU 1976 2 1 24 0 0.000000 0.7623713 0.7621542 +SIMU 1976 2 2 24 0 0.000000 0.7600473 0.7607731 +SIMU 1976 2 3 24 0 0.000000 0.7489523 0.7504413 +SIMU 1976 2 4 24 0 0.000000 0.7345909 0.7363094 +SIMU 1976 2 5 24 0 0.000000 0.7190740 0.7208760 +SIMU 1976 2 6 24 0 0.000000 0.7032824 0.7050893 +SIMU 1976 2 7 24 0 0.000000 0.6916801 0.6920239 +SIMU 1976 2 8 24 0 0.000000 0.7083429 0.7042727 +SIMU 1976 2 9 24 0 0.000000 0.7615871 0.7546917 +SIMU 1976 2 10 24 0 0.000000 0.8247172 0.8184053 +SIMU 1976 2 11 24 0 0.000000 0.8625719 0.8598288 +SIMU 1976 2 12 24 0 0.000000 0.8718647 0.8712609 +SIMU 1976 2 13 24 0 0.000000 0.8734022 0.8737460 +SIMU 1976 2 14 24 0 0.000000 0.8642851 0.8656677 +SIMU 1976 2 15 24 0 0.000000 0.9129595 0.9049062 +SIMU 1976 2 16 24 0 0.000000 1.078044 1.059682 +SIMU 1976 2 17 24 0 0.000000 1.359820 1.349433 +SIMU 1976 2 18 24 0 0.000000 1.452251 1.449551 +SIMU 1976 2 19 24 0 0.000000 1.464540 1.464820 +SIMU 1976 2 20 24 0 0.000000 1.481434 1.471503 +SIMU 1976 2 21 24 0 0.000000 1.906745 1.884500 +SIMU 1976 2 22 24 0 0.000000 1.984607 1.986099 +SIMU 1976 2 23 24 0 0.000000 1.953152 1.954437 +SIMU 1976 2 24 24 0 0.000000 2.010689 1.999853 +SIMU 1976 2 25 24 0 0.000000 2.245111 2.232913 +SIMU 1976 2 26 24 0 0.000000 2.511892 2.486479 +SIMU 1976 2 27 24 0 0.000000 3.084428 3.050205 +SIMU 1976 2 28 24 0 0.000000 3.745470 3.720134 +SIMU 1976 2 29 24 0 0.000000 4.127980 4.116868 +SIMU 1976 3 1 24 0 0.000000 4.235329 4.234165 +SIMU 1976 3 2 24 0 0.000000 4.215328 4.217963 +SIMU 1976 3 3 24 0 0.000000 4.121662 4.126784 +SIMU 1976 3 4 24 0 0.000000 4.138225 4.134162 +SIMU 1976 3 5 24 0 0.000000 4.024909 4.035726 +SIMU 1976 3 6 24 0 0.000000 3.829541 3.837712 +SIMU 1976 3 7 24 0 0.000000 3.687015 3.691668 +SIMU 1976 3 8 24 0 0.000000 3.629119 3.631645 +SIMU 1976 3 9 24 0 0.000000 3.611779 3.607877 +SIMU 1976 3 10 24 0 0.000000 3.763959 3.757464 +SIMU 1976 3 11 24 0 0.000000 3.943267 3.921299 +SIMU 1976 3 12 24 0 0.000000 4.953779 4.908589 +SIMU 1976 3 13 24 0 0.000000 5.509392 5.485821 +SIMU 1976 3 14 24 0 0.000000 6.053998 6.030756 +SIMU 1976 3 15 24 0 0.000000 6.591527 6.571682 +SIMU 1976 3 16 24 0 0.000000 7.068567 7.047995 +SIMU 1976 3 17 24 0 0.000000 7.586174 7.566631 +SIMU 1976 3 18 24 0 0.000000 8.037082 8.019219 +SIMU 1976 3 19 24 0 0.000000 8.455155 8.440041 +SIMU 1976 3 20 24 0 0.000000 8.771515 8.760997 +SIMU 1976 3 21 24 0 0.000000 8.978786 8.971905 +SIMU 1976 3 22 24 0 0.000000 9.113884 9.109606 +SIMU 1976 3 23 24 0 0.000000 9.189359 9.187323 +SIMU 1976 3 24 24 0 0.000000 9.213420 9.213323 +SIMU 1976 3 25 24 0 0.000000 9.193388 9.194930 +SIMU 1976 3 26 24 0 0.000000 9.138386 9.140846 +SIMU 1976 3 27 24 0 0.000000 9.074394 9.077370 +SIMU 1976 3 28 24 0 0.000000 8.985065 8.989177 +SIMU 1976 3 29 24 0 0.000000 8.907846 8.907939 +SIMU 1976 3 30 24 0 0.000000 9.129716 9.115706 +SIMU 1976 3 31 24 0 0.000000 9.409184 9.400278 +SIMU 1976 4 1 24 0 0.000000 9.573208 9.568831 +SIMU 1976 4 2 24 0 0.000000 9.649462 9.647945 +SIMU 1976 4 3 24 0 0.000000 9.657434 9.658134 +SIMU 1976 4 4 24 0 0.000000 9.611531 9.613969 +SIMU 1976 4 5 24 0 0.000000 9.521956 9.526024 +SIMU 1976 4 6 24 0 0.000000 9.395257 9.400982 +SIMU 1976 4 7 24 0 0.000000 9.237177 9.244081 +SIMU 1976 4 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0 0.000000 0.000000 0.000000 +SIMU 1976 12 18 24 0 0.000000 0.000000 0.000000 +SIMU 1976 12 19 24 0 0.000000 0.000000 0.000000 +SIMU 1976 12 20 24 0 0.000000 0.000000 0.000000 +SIMU 1976 12 21 24 0 0.000000 0.000000 0.000000 +SIMU 1976 12 22 24 0 0.000000 0.000000 0.000000 +SIMU 1976 12 23 24 0 0.000000 0.000000 0.000000 +SIMU 1976 12 24 24 0 0.000000 0.000000 0.000000 +SIMU 1976 12 25 24 0 0.000000 0.000000 0.000000 +SIMU 1976 12 26 24 0 0.000000 0.000000 0.000000 +SIMU 1976 12 27 24 0 0.000000 0.000000 0.000000 +SIMU 1976 12 28 24 0 0.000000 0.000000 0.000000 +SIMU 1976 12 29 24 0 0.000000 0.000000 0.000000 +SIMU 1976 12 30 24 0 0.000000 0.000000 0.000000 +SIMU 1976 12 31 24 0 0.000000 0.000000 0.000000 diff --git a/tests/test10/HSP2results/TEST10_hsp2_compare.ipynb b/tests/test10/HSP2results/TEST10_hsp2_compare.ipynb index 6aa05630..2d0c6577 100644 --- a/tests/test10/HSP2results/TEST10_hsp2_compare.ipynb +++ b/tests/test10/HSP2results/TEST10_hsp2_compare.ipynb @@ -54,13 +54,6 @@ "cell_type": "code", "execution_count": 1, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T21:56:45.799145Z", - "iopub.status.busy": "2024-05-21T21:56:45.798755Z", - "iopub.status.idle": "2024-05-21T21:56:46.397347Z", - "shell.execute_reply": "2024-05-21T21:56:46.396929Z", - "shell.execute_reply.started": "2024-05-21T21:56:45.799127Z" - }, "vscode": { "languageId": "python" } @@ -97,11 +90,11 @@ " \n", " \n", " Python\n", - " 3.10.14 | packaged by conda-forge | (main, Mar...\n", + " 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11....\n", " \n", " \n", " hsp2\n", - " n/a\n", + " 0.11.0a1\n", " \n", " \n", " numpy\n", @@ -109,27 +102,27 @@ " \n", " \n", " numba\n", - " 0.59.1\n", + " 0.64.0\n", " \n", " \n", " pandas\n", - " 1.5.3\n", + " 2.3.3\n", " \n", " \n", " matplotlib\n", - " 3.8.4\n", + " 3.10.8\n", " \n", " \n", " os\n", - " Linux-5.15.0-91-generic-x86_64-with-glibc2.35\n", + " Linux-6.19.12-200.fc43.x86_64-x86_64-with-glib...\n", " \n", " \n", " processor\n", - " x86_64\n", + " \n", " \n", " \n", " Date/Time\n", - " 2024-05-21T17:56:46.390922\n", + " 2026-05-06T21:54:58.520601\n", " \n", " \n", "\n", @@ -138,15 +131,15 @@ "text/plain": [ " version\n", "name \n", - "Python 3.10.14 | packaged by conda-forge | (main, Mar...\n", - "hsp2 n/a\n", + "Python 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11....\n", + "hsp2 0.11.0a1\n", "numpy 1.26.4\n", - "numba 0.59.1\n", - "pandas 1.5.3\n", - "matplotlib 3.8.4\n", - "os Linux-5.15.0-91-generic-x86_64-with-glibc2.35\n", - "processor x86_64\n", - "Date/Time 2024-05-21T17:56:46.390922" + "numba 0.64.0\n", + "pandas 2.3.3\n", + "matplotlib 3.10.8\n", + "os Linux-6.19.12-200.fc43.x86_64-x86_64-with-glib...\n", + "processor \n", + "Date/Time 2026-05-06T21:54:58.520601" ] }, "execution_count": 1, @@ -191,13 +184,6 @@ "cell_type": "code", "execution_count": 2, "metadata": { - "execution": { - "iopub.execute_input": "2024-04-28T16:45:34.246207Z", - "iopub.status.busy": "2024-04-28T16:45:34.245792Z", - "iopub.status.idle": "2024-04-28T16:45:34.364011Z", - "shell.execute_reply": "2024-04-28T16:45:34.363366Z", - "shell.execute_reply.started": "2024-04-28T16:45:34.246190Z" - }, "vscode": { "languageId": "python" } @@ -224,15 +210,8 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T21:56:53.062666Z", - "iopub.status.busy": "2024-05-21T21:56:53.062200Z", - "iopub.status.idle": "2024-05-21T21:56:53.065840Z", - "shell.execute_reply": "2024-05-21T21:56:53.065515Z", - "shell.execute_reply.started": "2024-05-21T21:56:53.062649Z" - }, "vscode": { "languageId": "python" } @@ -241,10 +220,10 @@ { "data": { "text/plain": [ - "'hsp2_310'" + "'default311'" ] }, - "execution_count": 2, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -256,15 +235,8 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T21:56:54.465894Z", - "iopub.status.busy": "2024-05-21T21:56:54.465712Z", - "iopub.status.idle": "2024-05-21T21:56:54.469602Z", - "shell.execute_reply": "2024-05-21T21:56:54.469136Z", - "shell.execute_reply.started": "2024-05-21T21:56:54.465880Z" - }, "vscode": { "languageId": "python" } @@ -273,10 +245,10 @@ { "data": { "text/plain": [ - "PosixPath('/home/tim/programming/HSPsquared/tests/test10/HSP2results')" + "PosixPath('/var/home/timcera/programming/HSP_old/HSPsquared/tests/test10/HSP2results')" ] }, - "execution_count": 3, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -290,15 +262,8 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T21:56:56.149119Z", - "iopub.status.busy": "2024-05-21T21:56:56.148907Z", - "iopub.status.idle": "2024-05-21T21:56:56.151201Z", - "shell.execute_reply": "2024-05-21T21:56:56.150872Z", - "shell.execute_reply.started": "2024-05-21T21:56:56.149107Z" - }, "vscode": { "languageId": "python" } @@ -320,15 +285,8 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T21:57:02.704747Z", - "iopub.status.busy": "2024-05-21T21:57:02.704526Z", - "iopub.status.idle": "2024-05-21T21:57:02.707412Z", - "shell.execute_reply": "2024-05-21T21:57:02.706838Z", - "shell.execute_reply.started": "2024-05-21T21:57:02.704736Z" - }, "vscode": { "languageId": "python" } @@ -348,15 +306,8 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T21:57:05.825624Z", - "iopub.status.busy": "2024-05-21T21:57:05.825441Z", - "iopub.status.idle": "2024-05-21T21:57:17.090702Z", - "shell.execute_reply": "2024-05-21T21:57:17.090235Z", - "shell.execute_reply.started": "2024-05-21T21:57:05.825610Z" - }, "vscode": { "languageId": "python" } @@ -367,7 +318,28 @@ "output_type": "stream", "text": [ "CPU times: user 2 µs, sys: 0 ns, total: 2 µs\n", - "Wall time: 3.34 µs\n" + "Wall time: 6.2 µs\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_40924/1322036604.py:2: DeprecationWarning: Call to deprecated function readUCI (\n", + "\n", + "readUCI is deprecated and will be removed in a future release.\n", + "Use hsp2.hsp2io.control_file_readers.read_uci_parameters to read the parameters.\n", + "\n", + ").\n", + " readUCI(uciname, hdfname)\n", + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'CURV-DATA1'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though\n", + " check_attribute_name(name)\n", + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'CURV-DATA2'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though\n", + " check_attribute_name(name)\n", + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'CURV-DATA3'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though\n", + " check_attribute_name(name)\n", + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'CURV-DATA4'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though\n", + " check_attribute_name(name)\n" ] } ], @@ -378,15 +350,8 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T21:57:17.091594Z", - "iopub.status.busy": "2024-05-21T21:57:17.091478Z", - "iopub.status.idle": "2024-05-21T21:57:18.811240Z", - "shell.execute_reply": "2024-05-21T21:57:18.810545Z", - "shell.execute_reply.started": "2024-05-21T21:57:17.091585Z" - }, "vscode": { "languageId": "python" } @@ -396,8 +361,29 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 1 µs, sys: 0 ns, total: 1 µs\n", - "Wall time: 2.38 µs\n", + "CPU times: user 2 µs, sys: 0 ns, total: 2 µs\n", + "Wall time: 4.05 µs\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_40924/1296374569.py:2: DeprecationWarning: Call to deprecated function readWDM (\n", + "\n", + "readWDM is deprecated and will be removed in a future release.\n", + "Use hsp2.hsp2io.time_series_readers.read_wdm_ts.read_wdm_ts to read the time\n", + "series data from the WDM file, and then write the data to an HDF file using\n", + "pandas.\n", + "\n", + ").\n", + " readWDM(wdmname, hdfname)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "39 reading from wdm\n", "41 reading from wdm\n", "42 reading from wdm\n", @@ -418,299 +404,6 @@ "136 reading from wdm\n", "140 reading from wdm\n" ] - }, - { - "data": { - "text/html": [ - "
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TS0461976-01-01 00:00:001977-01-01 00:00:002h4392SOLR-999.00002 HOUR RADFARMERS WEATHER STN
TS1131976-01-01 00:00:001977-01-01 00:00:001D366FLOW-999.0000DAILY FLOWIOWA RIVER MARSHALLTOWN
TS1191976-01-01 00:00:001977-01-01 00:00:001D366FLOW-999.0000DAILY FLOWIOWA RIVER MARENGO
TS1211976-01-01 00:00:001977-01-01 00:00:002h4392ATMP-999.00002 HOUR AIR TEMPCEDAR RAPIDS IOWA
TS1221976-01-01 00:00:001977-01-01 00:00:002h4392ATMP-999.00002 HOUR AIR TEMPIOWA FALLS IOWA
TS1231976-01-01 00:00:001977-01-01 00:00:002h4392ATMP-999.00002 HOUR AIR TEMPMARSHALLTOWN IOWA
TS1241976-01-01 00:00:001977-01-01 00:00:001D366DEWP-999.0000DAILY DEW PTCEDAR RAPIDS IOWA
TS1251976-01-01 00:00:001977-01-01 00:00:001D366DEWP-999.0000DAILY DEW PTIOWA FALLS IOWA
TS1261976-01-01 00:00:001977-01-01 00:00:001D366DEWP-999.0000DAILY DEW PTMARSHALLTOWN IOWA
TS1271976-01-01 00:00:001977-01-01 00:00:001D366SEDM-999.0000SEDIMENT CONCIOWA RIVER MARENGO
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CEDAR RAPIDS IOWA \n", - "TS125 DAILY DEW PT IOWA FALLS IOWA \n", - "TS126 DAILY DEW PT MARSHALLTOWN IOWA \n", - "TS127 SEDIMENT CONC IOWA RIVER MARENGO \n", - "TS131 HOURLY PREC PRECIP IOWA FALLS \n", - "TS132 HOURLY PREC PRECIP SHEFFIELD \n", - "TS134 WATER TEMP IOWA RIVER (ESTIMATED) \n", - "TS135 CLOUD COVER WATERLOO (TENTHS) \n", - "TS136 DAILY FLOW IOWA RIVER ROWAN \n", - "TS140 COLIND COLUMN INDICATOR MEIER POND SUMMER-WINTER OUTLET " - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" } ], "source": [ @@ -734,15 +427,8 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T21:57:18.812150Z", - "iopub.status.busy": "2024-05-21T21:57:18.811951Z", - "iopub.status.idle": "2024-05-21T21:59:52.791513Z", - "shell.execute_reply": "2024-05-21T21:59:52.791026Z", - "shell.execute_reply.started": "2024-05-21T21:57:18.812091Z" - }, "vscode": { "languageId": "python" } @@ -752,90 +438,92 @@ "name": "stdout", "output_type": "stream", "text": [ - "2024-05-21 17:57:18.81 Processing started for file test10_hsp2_dev2WDM_6.h5; saveall=True\n", - "STATE initializing contexts.\n", - "Looking for custom om loader in python code test10_hsp2_dev2WDM_6.py\n", - "Looking for custom om json test10_hsp2_dev2WDM_6.json\n", - "Loaded objects & paths: insures all paths are valid, connects models as inputs\n", - "Tokenizing models\n", - "Operational model status: enabled\n", - "op_tokens has 114 elements, with 1 executable elements\n", - "2024-05-21 17:57:26.69 Simulation Start: 1976-01-01 00:00:00, Stop: 1977-01-01 00:00:00\n", - "2024-05-21 17:57:26.69 PERLND P001 DELT(minutes): 60\n", - "2024-05-21 17:57:27.24 SNOW\n", - "2024-05-21 17:57:32.12 PWATER\n", - "2024-05-21 17:57:37.24 PSTEMP\n", - "2024-05-21 17:57:38.16 PWTGAS\n", - "2024-05-21 17:57:40.46 RCHRES R001 DELT(minutes): 60\n", - "2024-05-21 17:57:40.48 HYDR\n", - "2024-05-21 17:57:50.01 ADCALC\n", - "2024-05-21 17:57:50.89 CONS\n", - "2024-05-21 17:57:52.30 HTRCH\n", - "2024-05-21 17:57:54.96 SEDTRN\n", - "2024-05-21 17:58:10.98 RQUAL\n", - "2024-05-21 17:59:25.43 GQUAL\n", - "2024-05-21 17:59:30.78 GENER G001 DELT(minutes): 60\n", - "2024-05-21 17:59:30.79 RCHRES R002 DELT(minutes): 60\n", - "2024-05-21 17:59:30.82 HYDR\n", - "2024-05-21 17:59:38.41 ADCALC\n", - "2024-05-21 17:59:38.41 CONS\n", - "2024-05-21 17:59:38.45 HTRCH\n", - "2024-05-21 17:59:38.45 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2024-05-21 17:59:38.51 SEDTRN\n", - "2024-05-21 17:59:38.52 Error count 3598: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", - "2024-05-21 17:59:38.65 RQUAL\n", - "2024-05-21 17:59:39.54 GQUAL\n", - "2024-05-21 17:59:40.30 RCHRES R003 DELT(minutes): 60\n", - "2024-05-21 17:59:40.32 HYDR\n", - "2024-05-21 17:59:40.40 ADCALC\n", - "2024-05-21 17:59:40.41 CONS\n", - "2024-05-21 17:59:40.44 HTRCH\n", - "2024-05-21 17:59:40.44 Error count 3: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2024-05-21 17:59:40.51 SEDTRN\n", - "2024-05-21 17:59:40.51 Error count 513: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", - "2024-05-21 17:59:40.65 RQUAL\n", - "2024-05-21 17:59:41.50 GQUAL\n", - "2024-05-21 17:59:42.19 RCHRES R004 DELT(minutes): 60\n", - "2024-05-21 17:59:42.24 HYDR\n", - "2024-05-21 17:59:42.32 ADCALC\n", - "2024-05-21 17:59:42.33 CONS\n", - "2024-05-21 17:59:42.37 HTRCH\n", - "2024-05-21 17:59:42.37 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2024-05-21 17:59:42.48 SEDTRN\n", - "2024-05-21 17:59:42.49 Error count 6720: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", - "2024-05-21 17:59:42.74 RQUAL\n", - "2024-05-21 17:59:44.35 GQUAL\n", - "2024-05-21 17:59:45.32 IMPLND I001 DELT(minutes): 60\n", - "2024-05-21 17:59:45.34 SNOW\n", - "2024-05-21 17:59:45.46 IWATER\n", - "2024-05-21 17:59:46.95 SOLIDS\n", - "2024-05-21 17:59:47.97 IWTGAS\n", - "2024-05-21 17:59:48.83 IQUAL\n", - "2024-05-21 17:59:49.97 RCHRES R005 DELT(minutes): 60\n", - "2024-05-21 17:59:50.00 HYDR\n", - "2024-05-21 17:59:50.12 ADCALC\n", - "2024-05-21 17:59:50.12 CONS\n", - "2024-05-21 17:59:50.16 HTRCH\n", - "2024-05-21 17:59:50.16 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2024-05-21 17:59:50.23 SEDTRN\n", - "2024-05-21 17:59:50.37 RQUAL\n", - "2024-05-21 17:59:51.28 GQUAL\n", - "2024-05-21 17:59:52.14 GENER G002 DELT(minutes): 60\n", - "2024-05-21 17:59:52.14 Done; Run time is about 02:33.3 (mm:ss)\n", + "2026-05-06 21:55:06.32 Processing started for file test10_hsp2_dev2WDM_6.h5; saveall=True\n", + "Skipping un-typed siminfo\n", + "op_tokens has 186 elements, with 1 executable elements\n", + "2026-05-06 21:55:14.57 Simulation Start: 1976-01-01 00:00:00, Stop: 1977-01-01 00:00:00\n", + "2026-05-06 21:55:14.57 PERLND P001 DELT(minutes): 60\n", + "2026-05-06 21:55:15.16 SNOW\n", + "2026-05-06 21:55:16.27 PWATER\n", + "2026-05-06 21:55:16.83 PSTEMP\n", + "2026-05-06 21:55:16.87 PWTGAS\n", + "2026-05-06 21:55:16.99 RCHRES R001 DELT(minutes): 60\n", + "2026-05-06 21:55:17.00 HYDR\n", + "2026-05-06 21:55:27.90 ADCALC\n", + "2026-05-06 21:55:27.92 CONS\n", + "2026-05-06 21:55:28.24 HTRCH\n", + "2026-05-06 21:55:28.33 SEDTRN\n", + "2026-05-06 21:55:28.55 RQUAL\n", + "2026-05-06 21:55:29.78 GQUAL\n", + "2026-05-06 21:55:31.12 DISPLY D005 DELT(minutes): 60\n", + "2026-05-06 21:55:31.12 DISPLY D001 DELT(minutes): 60\n", + "2026-05-06 21:55:31.12 GENER G001 DELT(minutes): 60\n", + "2026-05-06 21:55:31.13 DISPLY D002 DELT(minutes): 60\n", + "2026-05-06 21:55:31.13 RCHRES R002 DELT(minutes): 60\n", + "2026-05-06 21:55:31.14 HYDR\n", + "2026-05-06 21:55:36.53 ADCALC\n", + "2026-05-06 21:55:36.53 CONS\n", + "2026-05-06 21:55:36.57 HTRCH\n", + "2026-05-06 21:55:36.57 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 21:55:36.64 SEDTRN\n", + "2026-05-06 21:55:36.65 Error count 3598: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-06 21:55:36.78 RQUAL\n", + "2026-05-06 21:55:37.67 GQUAL\n", + "2026-05-06 21:55:38.54 RCHRES R003 DELT(minutes): 60\n", + "2026-05-06 21:55:38.56 HYDR\n", + "2026-05-06 21:55:38.64 ADCALC\n", + "2026-05-06 21:55:38.65 CONS\n", + "2026-05-06 21:55:38.68 HTRCH\n", + "2026-05-06 21:55:38.68 Error count 3: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 21:55:38.74 SEDTRN\n", + "2026-05-06 21:55:38.75 Error count 513: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-06 21:55:38.88 RQUAL\n", + "2026-05-06 21:55:39.73 GQUAL\n", + "2026-05-06 21:55:40.49 RCHRES R004 DELT(minutes): 60\n", + "2026-05-06 21:55:40.53 HYDR\n", + "2026-05-06 21:55:40.62 ADCALC\n", + "2026-05-06 21:55:40.62 CONS\n", + "2026-05-06 21:55:40.66 HTRCH\n", + "2026-05-06 21:55:40.66 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 21:55:40.73 SEDTRN\n", + "2026-05-06 21:55:40.74 Error count 6720: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-06 21:55:40.88 RQUAL\n", + "2026-05-06 21:55:41.78 GQUAL\n", + "2026-05-06 21:55:42.69 PLTGEN L002 DELT(minutes): 60\n", + "2026-05-06 21:55:42.69 IMPLND I001 DELT(minutes): 60\n", + "2026-05-06 21:55:42.71 SNOW\n", + "2026-05-06 21:55:42.81 IWATER\n", + "2026-05-06 21:55:42.87 SOLIDS\n", + "2026-05-06 21:55:42.90 IWTGAS\n", + "2026-05-06 21:55:42.95 IQUAL\n", + "2026-05-06 21:55:43.01 RCHRES R005 DELT(minutes): 60\n", + "2026-05-06 21:55:43.03 HYDR\n", + "2026-05-06 21:55:43.12 ADCALC\n", + "2026-05-06 21:55:43.13 CONS\n", + "2026-05-06 21:55:43.16 HTRCH\n", + "2026-05-06 21:55:43.17 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 21:55:43.23 SEDTRN\n", + "2026-05-06 21:55:43.38 RQUAL\n", + "2026-05-06 21:55:44.30 GQUAL\n", + "2026-05-06 21:55:45.25 DISPLY D003 DELT(minutes): 60\n", + "2026-05-06 21:55:45.25 GENER G002 DELT(minutes): 60\n", + "2026-05-06 21:55:45.25 DISPLY D004 DELT(minutes): 60\n", + "2026-05-06 21:55:45.25 PLTGEN L001 DELT(minutes): 60\n", + "2026-05-06 21:55:45.25 Done; Run time is about 00:38.9 (mm:ss)\n", "\n", "\n", " version\n", "name \n", - "Python 3.10.14 | packaged by conda-forge | (main, Mar...\n", - "hsp2 n/a\n", + "Python 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11....\n", + "hsp2 0.11.0a1\n", "numpy 1.26.4\n", - "numba 0.59.1\n", - "pandas 1.5.3\n", - "jupyterlab 4.1.6\n", - "notebook 7.1.3\n", - "os Linux-5.15.0-91-generic-x86_64-with-glibc2.35\n", - "processor x86_64\n", - "Date/Time 2024-05-21T17:59:52.361916\n", + "numba 0.64.0\n", + "pandas 2.3.3\n", + "jupyterlab 4.5.6\n", + "notebook n/a\n", + "os Linux-6.19.12-200.fc43.x86_64-x86_64-with-glib...\n", + "processor \n", + "Date/Time 2026-05-06T21:55:45.509638\n", " \n", "*** Profile printout saved to text file 'NumbaProfile.txt'.\n" ] @@ -848,15 +536,8 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T21:59:52.792857Z", - "iopub.status.busy": "2024-05-21T21:59:52.792526Z", - "iopub.status.idle": "2024-05-21T21:59:52.797135Z", - "shell.execute_reply": "2024-05-21T21:59:52.796665Z", - "shell.execute_reply.started": "2024-05-21T21:59:52.792840Z" - }, "vscode": { "languageId": "python" } @@ -866,70 +547,70 @@ "name": "stdout", "output_type": "stream", "text": [ - " 295504886 function calls (280920234 primitive calls) in 153.422 seconds\n", + " 68458975 function calls (65840633 primitive calls) in 39.154 seconds\n", "\n", " ncalls tottime percall cumtime percall filename:lineno(function)\n", - " 327358 39.424 0.000 43.907 0.000 ffi.py:190(__call__)\n", - "6331755/1083466 3.537 0.000 5.573 0.000 ir.py:318(_rec_list_vars)\n", - "53558277/53552444 3.391 0.000 4.557 0.000 {built-in method builtins.isinstance}\n", - " 5 2.248 0.450 6.701 1.340 GQUAL.py:243(_gqual_)\n", - " 672680 2.190 0.000 4.917 0.000 instructions.py:13(__init__)\n", - " 13910 2.101 0.000 2.336 0.000 analysis.py:91(liveness)\n", - "4378747/2157034 2.009 0.000 6.855 0.000 {method 'format' of 'str' objects}\n", - " 7420315 1.853 0.000 2.685 0.000 targetconfig.py:111(getter)\n", - "12294732/12211749 1.640 0.000 7.802 0.000 {built-in method builtins.getattr}\n", - " 17440 1.184 0.000 1.261 0.000 {method '_create_carray' of 'tables.hdf5extension.Array' objects}\n", - "1739463/875247 1.036 0.000 2.484 0.000 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0.129 0.000 0.144 0.000 controlflow.py:586(_find_back_edges)\n", + " 162059 0.128 0.000 0.181 0.000 typeddict.py:37(_getitem)\n", + " 1976 0.126 0.000 0.735 0.000 analysis.py:23(compute_use_defs)\n", + " 158414 0.123 0.000 0.826 0.000 event.py:404(end_event)\n", + " 3778 0.122 0.000 0.130 0.000 analysis.py:81(def_reach)\n", + " 708915 0.116 0.000 0.116 0.000 serialize.py:30(_numba_unpickle)\n", + " 158414 0.115 0.000 0.649 0.000 event.py:390(start_event)\n", + " 34115 0.114 0.000 1.434 0.000 attributeset.py:379(_g__setattr)\n", + " 16056 0.113 0.000 0.117 0.000 :405(parent)\n", + "1246240/1121746 0.111 0.000 0.453 0.000 {built-in method builtins.len}\n", + " 15058 0.111 0.000 1.389 0.000 attributeset.py:188(__init__)\n", + " 316828 0.110 0.000 0.231 0.000 event.py:100(__init__)\n", + " 190577 0.110 0.000 1.735 0.000 file.py:370(cache_node)\n", + " 916493 0.109 0.000 0.109 0.000 {method 'startswith' of 'str' objects}\n", + " 251397 0.107 0.000 0.231 0.000 group.py:800(__setattr__)\n", + "167202/89185 0.104 0.000 3.297 0.000 file.py:383(get_node)\n", + "Cum Sum 55.13%\n" ] } ], @@ -971,15 +652,8 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T21:59:52.797948Z", - "iopub.status.busy": "2024-05-21T21:59:52.797734Z", - "iopub.status.idle": "2024-05-21T22:00:10.188996Z", - "shell.execute_reply": "2024-05-21T22:00:10.188715Z", - "shell.execute_reply.started": "2024-05-21T21:59:52.797931Z" - }, "vscode": { "languageId": "python" } @@ -989,90 +663,92 @@ "name": "stdout", "output_type": "stream", "text": [ - "2024-05-21 17:59:52.80 Processing started for file test10_hsp2_dev2WDM_6.h5; saveall=True\n", - "STATE initializing contexts.\n", - "Looking for custom om loader in python code test10_hsp2_dev2WDM_6.py\n", - "Looking for custom om json test10_hsp2_dev2WDM_6.json\n", - "Loaded objects & paths: insures all paths are valid, connects models as inputs\n", - "Tokenizing models\n", - "Operational model status: enabled\n", - "op_tokens has 114 elements, with 1 executable elements\n", - "2024-05-21 17:59:55.48 Simulation Start: 1976-01-01 00:00:00, Stop: 1977-01-01 00:00:00\n", - "2024-05-21 17:59:55.49 PERLND P001 DELT(minutes): 60\n", - "2024-05-21 17:59:55.55 SNOW\n", - "2024-05-21 17:59:55.70 PWATER\n", - "2024-05-21 17:59:55.96 PSTEMP\n", - "2024-05-21 17:59:56.00 PWTGAS\n", - "2024-05-21 17:59:56.14 RCHRES R001 DELT(minutes): 60\n", - "2024-05-21 17:59:56.16 HYDR\n", - "2024-05-21 17:59:56.31 ADCALC\n", - "2024-05-21 17:59:56.32 CONS\n", - "2024-05-21 17:59:56.38 HTRCH\n", - "2024-05-21 17:59:56.50 SEDTRN\n", - "2024-05-21 17:59:56.76 RQUAL\n", - "2024-05-21 17:59:58.62 GQUAL\n", - "2024-05-21 18:00:00.10 GENER G001 DELT(minutes): 60\n", - "2024-05-21 18:00:00.11 RCHRES R002 DELT(minutes): 60\n", - "2024-05-21 18:00:00.12 HYDR\n", - "2024-05-21 18:00:00.19 ADCALC\n", - "2024-05-21 18:00:00.19 CONS\n", - "2024-05-21 18:00:00.22 HTRCH\n", - "2024-05-21 18:00:00.22 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2024-05-21 18:00:00.27 SEDTRN\n", - "2024-05-21 18:00:00.28 Error count 3598: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", - "2024-05-21 18:00:00.38 RQUAL\n", - "2024-05-21 18:00:01.12 GQUAL\n", - "2024-05-21 18:00:02.26 RCHRES R003 DELT(minutes): 60\n", - "2024-05-21 18:00:02.28 HYDR\n", - "2024-05-21 18:00:02.40 ADCALC\n", - "2024-05-21 18:00:02.40 CONS\n", - "2024-05-21 18:00:02.45 HTRCH\n", - "2024-05-21 18:00:02.45 Error count 3: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2024-05-21 18:00:02.55 SEDTRN\n", - "2024-05-21 18:00:02.55 Error count 513: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", - "2024-05-21 18:00:02.76 RQUAL\n", - "2024-05-21 18:00:04.06 GQUAL\n", - "2024-05-21 18:00:05.05 RCHRES R004 DELT(minutes): 60\n", - "2024-05-21 18:00:05.10 HYDR\n", - "2024-05-21 18:00:05.22 ADCALC\n", - "2024-05-21 18:00:05.22 CONS\n", - "2024-05-21 18:00:05.28 HTRCH\n", - "2024-05-21 18:00:05.28 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2024-05-21 18:00:05.37 SEDTRN\n", - "2024-05-21 18:00:05.38 Error count 6720: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", - "2024-05-21 18:00:05.58 RQUAL\n", - "2024-05-21 18:00:06.95 GQUAL\n", - "2024-05-21 18:00:08.14 IMPLND I001 DELT(minutes): 60\n", - "2024-05-21 18:00:08.15 SNOW\n", - "2024-05-21 18:00:08.31 IWATER\n", - "2024-05-21 18:00:08.38 SOLIDS\n", - "2024-05-21 18:00:08.40 IWTGAS\n", - "2024-05-21 18:00:08.46 IQUAL\n", - "2024-05-21 18:00:08.53 RCHRES R005 DELT(minutes): 60\n", - "2024-05-21 18:00:08.56 HYDR\n", - "2024-05-21 18:00:08.64 ADCALC\n", - "2024-05-21 18:00:08.65 CONS\n", - "2024-05-21 18:00:08.67 HTRCH\n", - "2024-05-21 18:00:08.68 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2024-05-21 18:00:08.73 SEDTRN\n", - "2024-05-21 18:00:08.84 RQUAL\n", - "2024-05-21 18:00:09.58 GQUAL\n", - "2024-05-21 18:00:10.15 GENER G002 DELT(minutes): 60\n", - "2024-05-21 18:00:10.15 Done; Run time is about 00:17.3 (mm:ss)\n", + "2026-05-06 21:55:45.61 Processing started for file test10_hsp2_dev2WDM_6.h5; saveall=True\n", + "Skipping un-typed siminfo\n", + "op_tokens has 186 elements, with 1 executable elements\n", + "2026-05-06 21:55:48.33 Simulation Start: 1976-01-01 00:00:00, Stop: 1977-01-01 00:00:00\n", + "2026-05-06 21:55:48.33 PERLND P001 DELT(minutes): 60\n", + "2026-05-06 21:55:48.36 SNOW\n", + "2026-05-06 21:55:48.44 PWATER\n", + "2026-05-06 21:55:48.58 PSTEMP\n", + "2026-05-06 21:55:48.60 PWTGAS\n", + "2026-05-06 21:55:48.68 RCHRES R001 DELT(minutes): 60\n", + "2026-05-06 21:55:48.69 HYDR\n", + "2026-05-06 21:55:48.78 ADCALC\n", + "2026-05-06 21:55:48.78 CONS\n", + "2026-05-06 21:55:48.82 HTRCH\n", + "2026-05-06 21:55:48.88 SEDTRN\n", + "2026-05-06 21:55:49.02 RQUAL\n", + "2026-05-06 21:55:49.97 GQUAL\n", + "2026-05-06 21:55:50.78 DISPLY D005 DELT(minutes): 60\n", + "2026-05-06 21:55:50.78 DISPLY D001 DELT(minutes): 60\n", + "2026-05-06 21:55:50.78 GENER G001 DELT(minutes): 60\n", + "2026-05-06 21:55:50.78 DISPLY D002 DELT(minutes): 60\n", + "2026-05-06 21:55:50.78 RCHRES R002 DELT(minutes): 60\n", + "2026-05-06 21:55:50.79 HYDR\n", + "2026-05-06 21:55:50.86 ADCALC\n", + "2026-05-06 21:55:50.86 CONS\n", + "2026-05-06 21:55:50.89 HTRCH\n", + "2026-05-06 21:55:50.89 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 21:55:50.94 SEDTRN\n", + "2026-05-06 21:55:50.95 Error count 3598: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-06 21:55:51.05 RQUAL\n", + "2026-05-06 21:55:51.76 GQUAL\n", + "2026-05-06 21:55:52.35 RCHRES R003 DELT(minutes): 60\n", + "2026-05-06 21:55:52.36 HYDR\n", + "2026-05-06 21:55:52.42 ADCALC\n", + "2026-05-06 21:55:52.42 CONS\n", + "2026-05-06 21:55:52.45 HTRCH\n", + "2026-05-06 21:55:52.45 Error count 3: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 21:55:52.50 SEDTRN\n", + "2026-05-06 21:55:52.50 Error count 513: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-06 21:55:52.60 RQUAL\n", + "2026-05-06 21:55:53.28 GQUAL\n", + "2026-05-06 21:55:53.78 RCHRES R004 DELT(minutes): 60\n", + "2026-05-06 21:55:53.80 HYDR\n", + "2026-05-06 21:55:53.87 ADCALC\n", + "2026-05-06 21:55:53.87 CONS\n", + "2026-05-06 21:55:53.90 HTRCH\n", + "2026-05-06 21:55:53.90 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 21:55:53.95 SEDTRN\n", + "2026-05-06 21:55:53.96 Error count 6720: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-06 21:55:54.07 RQUAL\n", + "2026-05-06 21:55:54.79 GQUAL\n", + "2026-05-06 21:55:55.42 PLTGEN L002 DELT(minutes): 60\n", + "2026-05-06 21:55:55.42 IMPLND I001 DELT(minutes): 60\n", + "2026-05-06 21:55:55.43 SNOW\n", + "2026-05-06 21:55:55.51 IWATER\n", + "2026-05-06 21:55:55.54 SOLIDS\n", + "2026-05-06 21:55:55.56 IWTGAS\n", + "2026-05-06 21:55:55.59 IQUAL\n", + "2026-05-06 21:55:55.63 RCHRES R005 DELT(minutes): 60\n", + "2026-05-06 21:55:55.64 HYDR\n", + "2026-05-06 21:55:55.71 ADCALC\n", + "2026-05-06 21:55:55.71 CONS\n", + "2026-05-06 21:55:55.74 HTRCH\n", + "2026-05-06 21:55:55.74 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 21:55:55.79 SEDTRN\n", + "2026-05-06 21:55:55.90 RQUAL\n", + "2026-05-06 21:55:56.66 GQUAL\n", + "2026-05-06 21:55:57.29 DISPLY D003 DELT(minutes): 60\n", + "2026-05-06 21:55:57.29 GENER G002 DELT(minutes): 60\n", + "2026-05-06 21:55:57.29 DISPLY D004 DELT(minutes): 60\n", + "2026-05-06 21:55:57.29 PLTGEN L001 DELT(minutes): 60\n", + "2026-05-06 21:55:57.29 Done; Run time is about 00:11.6 (mm:ss)\n", "\n", "\n", " version\n", "name \n", - "Python 3.10.14 | packaged by conda-forge | (main, Mar...\n", - "hsp2 n/a\n", + "Python 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11....\n", + "hsp2 0.11.0a1\n", "numpy 1.26.4\n", - "numba 0.59.1\n", - "pandas 1.5.3\n", - "jupyterlab 4.1.6\n", - "notebook 7.1.3\n", - "os Linux-5.15.0-91-generic-x86_64-with-glibc2.35\n", - "processor x86_64\n", - "Date/Time 2024-05-21T18:00:10.163436\n" + "numba 0.64.0\n", + "pandas 2.3.3\n", + "jupyterlab 4.5.6\n", + "notebook n/a\n", + "os Linux-6.19.12-200.fc43.x86_64-x86_64-with-glib...\n", + "processor \n", + "Date/Time 2026-05-06T21:55:57.308367\n" ] } ], @@ -1141,13 +817,6 @@ "cell_type": "code", "execution_count": 12, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T22:00:24.862923Z", - "iopub.status.busy": "2024-05-21T22:00:24.862655Z", - "iopub.status.idle": "2024-05-21T22:00:25.062623Z", - "shell.execute_reply": "2024-05-21T22:00:25.058794Z", - "shell.execute_reply.started": "2024-05-21T22:00:24.862906Z" - }, "vscode": { "languageId": "python" } @@ -1161,7 +830,7 @@ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", "Cell \u001b[0;32mIn[12], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m summary \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_hdf\u001b[49m\u001b[43m(\u001b[49m\u001b[43mHBN\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mSUMMARY\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2\u001b[0m summary\u001b[38;5;241m.\u001b[39mFrequency\u001b[38;5;241m.\u001b[39munique()\n", - "File \u001b[0;32m~/anaconda3/envs/hsp2_310/lib/python3.10/site-packages/pandas/io/pytables.py:414\u001b[0m, in \u001b[0;36mread_hdf\u001b[0;34m(path_or_buf, key, mode, errors, where, start, stop, columns, iterator, chunksize, **kwargs)\u001b[0m\n\u001b[1;32m 411\u001b[0m exists \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 413\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m exists:\n\u001b[0;32m--> 414\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFile \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpath_or_buf\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m does not exist\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 416\u001b[0m store \u001b[38;5;241m=\u001b[39m HDFStore(path_or_buf, mode\u001b[38;5;241m=\u001b[39mmode, errors\u001b[38;5;241m=\u001b[39merrors, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 417\u001b[0m \u001b[38;5;66;03m# can't auto open/close if we are using an iterator\u001b[39;00m\n\u001b[1;32m 418\u001b[0m \u001b[38;5;66;03m# so delegate to the iterator\u001b[39;00m\n", + "File \u001b[0;32m~/miniconda3/envs/default311/lib/python3.11/site-packages/pandas/io/pytables.py:437\u001b[0m, in \u001b[0;36mread_hdf\u001b[0;34m(path_or_buf, key, mode, errors, where, start, stop, columns, iterator, chunksize, **kwargs)\u001b[0m\n\u001b[1;32m 434\u001b[0m exists \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 436\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m exists:\n\u001b[0;32m--> 437\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFile \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpath_or_buf\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m does not exist\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 439\u001b[0m store \u001b[38;5;241m=\u001b[39m HDFStore(path_or_buf, mode\u001b[38;5;241m=\u001b[39mmode, errors\u001b[38;5;241m=\u001b[39merrors, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 440\u001b[0m \u001b[38;5;66;03m# can't auto open/close if we are using an iterator\u001b[39;00m\n\u001b[1;32m 441\u001b[0m \u001b[38;5;66;03m# so delegate to the iterator\u001b[39;00m\n", "\u001b[0;31mFileNotFoundError\u001b[0m: File test10_hspf.h5 does not exist" ] } @@ -1189,12 +858,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-05-21T22:00:10.313309Z", - "iopub.status.idle": "2024-05-21T22:00:10.313414Z", - "shell.execute_reply": "2024-05-21T22:00:10.313365Z", - "shell.execute_reply.started": "2024-05-21T22:00:10.313360Z" - }, "vscode": { "languageId": "python" } @@ -1210,12 +873,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.793367Z", - "iopub.status.idle": "2024-04-28T16:47:35.793534Z", - "shell.execute_reply": "2024-04-28T16:47:35.793455Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.793447Z" - }, "vscode": { "languageId": "python" } @@ -1257,12 +914,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.793994Z", - "iopub.status.idle": "2024-04-28T16:47:35.794166Z", - "shell.execute_reply": "2024-04-28T16:47:35.794086Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.794078Z" - }, "vscode": { "languageId": "python" } @@ -1294,12 +945,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.794953Z", - "iopub.status.idle": "2024-04-28T16:47:35.795205Z", - "shell.execute_reply": "2024-04-28T16:47:35.795114Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.795106Z" - }, "vscode": { "languageId": "python" } @@ -1334,12 +979,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.795724Z", - "iopub.status.idle": "2024-04-28T16:47:35.795951Z", - "shell.execute_reply": "2024-04-28T16:47:35.795866Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.795858Z" - }, "vscode": { "languageId": "python" } @@ -1354,12 +993,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.796421Z", - "iopub.status.idle": "2024-04-28T16:47:35.796643Z", - "shell.execute_reply": "2024-04-28T16:47:35.796560Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.796552Z" - }, "vscode": { "languageId": "python" } @@ -1381,12 +1014,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.797125Z", - "iopub.status.idle": "2024-04-28T16:47:35.797416Z", - "shell.execute_reply": "2024-04-28T16:47:35.797332Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.797324Z" - }, "vscode": { "languageId": "python" } @@ -1400,12 +1027,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.797835Z", - "iopub.status.idle": "2024-04-28T16:47:35.798053Z", - "shell.execute_reply": "2024-04-28T16:47:35.797969Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.797961Z" - }, "vscode": { "languageId": "python" } @@ -1419,12 +1040,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.798483Z", - "iopub.status.idle": "2024-04-28T16:47:35.798717Z", - "shell.execute_reply": "2024-04-28T16:47:35.798637Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.798629Z" - }, "vscode": { "languageId": "python" } @@ -1446,12 +1061,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.799127Z", - "iopub.status.idle": "2024-04-28T16:47:35.799401Z", - "shell.execute_reply": "2024-04-28T16:47:35.799320Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.799312Z" - }, "vscode": { "languageId": "python" } @@ -1465,12 +1074,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.799811Z", - "iopub.status.idle": "2024-04-28T16:47:35.799997Z", - "shell.execute_reply": "2024-04-28T16:47:35.799937Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.799931Z" - }, "vscode": { "languageId": "python" } @@ -1491,12 +1094,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.800364Z", - "iopub.status.idle": "2024-04-28T16:47:35.800525Z", - "shell.execute_reply": "2024-04-28T16:47:35.800472Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.800466Z" - }, "vscode": { "languageId": "python" } @@ -1510,12 +1107,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.800820Z", - "iopub.status.idle": "2024-04-28T16:47:35.800925Z", - "shell.execute_reply": "2024-04-28T16:47:35.800875Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.800870Z" - }, "vscode": { "languageId": "python" } @@ -1536,12 +1127,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.801179Z", - "iopub.status.idle": "2024-04-28T16:47:35.801281Z", - "shell.execute_reply": "2024-04-28T16:47:35.801232Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.801227Z" - }, "vscode": { "languageId": "python" } @@ -1555,12 +1140,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.801629Z", - "iopub.status.idle": "2024-04-28T16:47:35.801742Z", - "shell.execute_reply": "2024-04-28T16:47:35.801689Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.801684Z" - }, "vscode": { "languageId": "python" } @@ -1581,12 +1160,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.802034Z", - "iopub.status.idle": "2024-04-28T16:47:35.802140Z", - "shell.execute_reply": "2024-04-28T16:47:35.802088Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.802084Z" - }, "vscode": { "languageId": "python" } @@ -1600,12 +1173,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.802456Z", - "iopub.status.idle": "2024-04-28T16:47:35.802559Z", - "shell.execute_reply": "2024-04-28T16:47:35.802511Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.802506Z" - }, "vscode": { "languageId": "python" } @@ -1626,12 +1193,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.802805Z", - "iopub.status.idle": "2024-04-28T16:47:35.802909Z", - "shell.execute_reply": "2024-04-28T16:47:35.802861Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.802853Z" - }, "vscode": { "languageId": "python" } @@ -1645,12 +1206,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.803196Z", - "iopub.status.idle": "2024-04-28T16:47:35.803295Z", - "shell.execute_reply": "2024-04-28T16:47:35.803248Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.803243Z" - }, "vscode": { "languageId": "python" } @@ -1671,12 +1226,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.803608Z", - "iopub.status.idle": "2024-04-28T16:47:35.803715Z", - "shell.execute_reply": "2024-04-28T16:47:35.803666Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.803661Z" - }, "vscode": { "languageId": "python" } @@ -1690,12 +1239,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.804024Z", - "iopub.status.idle": "2024-04-28T16:47:35.804126Z", - "shell.execute_reply": "2024-04-28T16:47:35.804078Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.804073Z" - }, "vscode": { "languageId": "python" } @@ -1716,12 +1259,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.804408Z", - "iopub.status.idle": "2024-04-28T16:47:35.804507Z", - "shell.execute_reply": "2024-04-28T16:47:35.804459Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.804455Z" - }, "vscode": { "languageId": "python" } @@ -1736,12 +1273,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.804766Z", - "iopub.status.idle": "2024-04-28T16:47:35.804863Z", - "shell.execute_reply": "2024-04-28T16:47:35.804817Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.804812Z" - }, "scrolled": true, "vscode": { "languageId": "python" @@ -1764,12 +1295,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.805199Z", - "iopub.status.idle": "2024-04-28T16:47:35.805309Z", - "shell.execute_reply": "2024-04-28T16:47:35.805260Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.805254Z" - }, "vscode": { "languageId": "python" } @@ -1783,12 +1308,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.805681Z", - "iopub.status.idle": "2024-04-28T16:47:35.805793Z", - "shell.execute_reply": "2024-04-28T16:47:35.805743Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.805737Z" - }, "vscode": { "languageId": "python" } @@ -1802,12 +1321,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.806219Z", - "iopub.status.idle": "2024-04-28T16:47:35.806350Z", - "shell.execute_reply": "2024-04-28T16:47:35.806289Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.806283Z" - }, "vscode": { "languageId": "python" } @@ -1829,12 +1342,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.806740Z", - "iopub.status.idle": "2024-04-28T16:47:35.806886Z", - "shell.execute_reply": "2024-04-28T16:47:35.806814Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.806808Z" - }, "vscode": { "languageId": "python" } @@ -1848,12 +1355,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.807172Z", - "iopub.status.idle": "2024-04-28T16:47:35.807318Z", - "shell.execute_reply": "2024-04-28T16:47:35.807251Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.807244Z" - }, "vscode": { "languageId": "python" } @@ -1874,12 +1375,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.807945Z", - "iopub.status.idle": "2024-04-28T16:47:35.808090Z", - "shell.execute_reply": "2024-04-28T16:47:35.808026Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.808020Z" - }, "vscode": { "languageId": "python" } @@ -1893,12 +1388,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.808424Z", - "iopub.status.idle": "2024-04-28T16:47:35.808562Z", - "shell.execute_reply": "2024-04-28T16:47:35.808497Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.808491Z" - }, "vscode": { "languageId": "python" } @@ -1919,12 +1408,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.809143Z", - "iopub.status.idle": "2024-04-28T16:47:35.809260Z", - "shell.execute_reply": "2024-04-28T16:47:35.809207Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.809202Z" - }, "vscode": { "languageId": "python" } @@ -1938,12 +1421,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.809599Z", - "iopub.status.idle": "2024-04-28T16:47:35.809703Z", - "shell.execute_reply": "2024-04-28T16:47:35.809653Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.809648Z" - }, "vscode": { "languageId": "python" } @@ -1964,12 +1441,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.810200Z", - "iopub.status.idle": "2024-04-28T16:47:35.810358Z", - "shell.execute_reply": "2024-04-28T16:47:35.810277Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.810270Z" - }, "vscode": { "languageId": "python" } @@ -1983,12 +1454,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.810827Z", - "iopub.status.idle": "2024-04-28T16:47:35.810995Z", - "shell.execute_reply": "2024-04-28T16:47:35.810926Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.810920Z" - }, "vscode": { "languageId": "python" } @@ -2009,12 +1474,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.811302Z", - "iopub.status.idle": "2024-04-28T16:47:35.811424Z", - "shell.execute_reply": "2024-04-28T16:47:35.811366Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.811361Z" - }, "vscode": { "languageId": "python" } @@ -2028,12 +1487,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.811817Z", - "iopub.status.idle": "2024-04-28T16:47:35.811925Z", - "shell.execute_reply": "2024-04-28T16:47:35.811875Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.811870Z" - }, "vscode": { "languageId": "python" } @@ -2054,12 +1507,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.812350Z", - "iopub.status.idle": "2024-04-28T16:47:35.812455Z", - "shell.execute_reply": "2024-04-28T16:47:35.812403Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.812398Z" - }, "vscode": { "languageId": "python" } @@ -2073,12 +1520,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.812816Z", - "iopub.status.idle": "2024-04-28T16:47:35.812974Z", - "shell.execute_reply": "2024-04-28T16:47:35.812909Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.812901Z" - }, "vscode": { "languageId": "python" } @@ -2099,12 +1540,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.813322Z", - "iopub.status.idle": "2024-04-28T16:47:35.813469Z", - "shell.execute_reply": "2024-04-28T16:47:35.813409Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.813403Z" - }, "vscode": { "languageId": "python" } @@ -2118,12 +1553,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.814100Z", - "iopub.status.idle": "2024-04-28T16:47:35.814241Z", - "shell.execute_reply": "2024-04-28T16:47:35.814178Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.814171Z" - }, "vscode": { "languageId": "python" } @@ -2144,12 +1573,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.814642Z", - "iopub.status.idle": "2024-04-28T16:47:35.814781Z", - "shell.execute_reply": "2024-04-28T16:47:35.814719Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.814713Z" - }, "vscode": { "languageId": "python" } @@ -2163,12 +1586,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.815196Z", - "iopub.status.idle": "2024-04-28T16:47:35.815325Z", - "shell.execute_reply": "2024-04-28T16:47:35.815265Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.815259Z" - }, "vscode": { "languageId": "python" } @@ -2189,12 +1606,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.815862Z", - "iopub.status.idle": "2024-04-28T16:47:35.815972Z", - "shell.execute_reply": "2024-04-28T16:47:35.815920Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.815915Z" - }, "vscode": { "languageId": "python" } @@ -2208,12 +1619,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.816307Z", - "iopub.status.idle": "2024-04-28T16:47:35.816446Z", - "shell.execute_reply": "2024-04-28T16:47:35.816359Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.816354Z" - }, "vscode": { "languageId": "python" } @@ -2234,12 +1639,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.816833Z", - "iopub.status.idle": "2024-04-28T16:47:35.816974Z", - "shell.execute_reply": "2024-04-28T16:47:35.816908Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.816901Z" - }, "vscode": { "languageId": "python" } @@ -2253,12 +1652,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.817354Z", - "iopub.status.idle": "2024-04-28T16:47:35.817492Z", - "shell.execute_reply": "2024-04-28T16:47:35.817427Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.817420Z" - }, "vscode": { "languageId": "python" } @@ -2279,12 +1672,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.817940Z", - "iopub.status.idle": "2024-04-28T16:47:35.818074Z", - "shell.execute_reply": "2024-04-28T16:47:35.818011Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.818005Z" - }, "vscode": { "languageId": "python" } @@ -2298,12 +1685,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.818461Z", - "iopub.status.idle": "2024-04-28T16:47:35.818570Z", - "shell.execute_reply": "2024-04-28T16:47:35.818520Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.818515Z" - }, "vscode": { "languageId": "python" } @@ -2324,12 +1705,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.819065Z", - "iopub.status.idle": "2024-04-28T16:47:35.819219Z", - "shell.execute_reply": "2024-04-28T16:47:35.819143Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.819136Z" - }, "vscode": { "languageId": "python" } @@ -2343,12 +1718,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.819926Z", - "iopub.status.idle": "2024-04-28T16:47:35.820060Z", - "shell.execute_reply": "2024-04-28T16:47:35.819999Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.819993Z" - }, "vscode": { "languageId": "python" } @@ -2369,12 +1738,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.820477Z", - "iopub.status.idle": "2024-04-28T16:47:35.820590Z", - "shell.execute_reply": "2024-04-28T16:47:35.820538Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.820533Z" - }, "vscode": { "languageId": "python" } @@ -2388,12 +1751,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.821046Z", - "iopub.status.idle": "2024-04-28T16:47:35.821151Z", - "shell.execute_reply": "2024-04-28T16:47:35.821101Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.821096Z" - }, "vscode": { "languageId": "python" } @@ -2414,12 +1771,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.821568Z", - "iopub.status.idle": "2024-04-28T16:47:35.821733Z", - "shell.execute_reply": "2024-04-28T16:47:35.821667Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.821660Z" - }, "vscode": { "languageId": "python" } @@ -2433,12 +1784,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.822186Z", - "iopub.status.idle": "2024-04-28T16:47:35.822327Z", - "shell.execute_reply": "2024-04-28T16:47:35.822262Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.822256Z" - }, "vscode": { "languageId": "python" } @@ -2459,12 +1804,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.822942Z", - "iopub.status.idle": "2024-04-28T16:47:35.823084Z", - "shell.execute_reply": "2024-04-28T16:47:35.823020Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.823014Z" - }, "vscode": { "languageId": "python" } @@ -2478,12 +1817,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.823410Z", - "iopub.status.idle": "2024-04-28T16:47:35.823541Z", - "shell.execute_reply": "2024-04-28T16:47:35.823481Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.823475Z" - }, "vscode": { "languageId": "python" } @@ -2504,12 +1837,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.823928Z", - "iopub.status.idle": "2024-04-28T16:47:35.824052Z", - "shell.execute_reply": "2024-04-28T16:47:35.823994Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.823988Z" - }, "vscode": { "languageId": "python" } @@ -2523,12 +1850,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.824587Z", - "iopub.status.idle": "2024-04-28T16:47:35.824696Z", - "shell.execute_reply": "2024-04-28T16:47:35.824646Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.824641Z" - }, "vscode": { "languageId": "python" } @@ -2549,12 +1870,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.824966Z", - "iopub.status.idle": "2024-04-28T16:47:35.825072Z", - "shell.execute_reply": "2024-04-28T16:47:35.825022Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.825017Z" - }, "vscode": { "languageId": "python" } @@ -2568,12 +1883,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.825613Z", - "iopub.status.idle": "2024-04-28T16:47:35.825757Z", - "shell.execute_reply": "2024-04-28T16:47:35.825690Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.825683Z" - }, "vscode": { "languageId": "python" } @@ -2594,12 +1903,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.826143Z", - "iopub.status.idle": "2024-04-28T16:47:35.826253Z", - "shell.execute_reply": "2024-04-28T16:47:35.826203Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.826198Z" - }, "vscode": { "languageId": "python" } @@ -2613,12 +1916,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.826578Z", - "iopub.status.idle": "2024-04-28T16:47:35.826714Z", - "shell.execute_reply": "2024-04-28T16:47:35.826648Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.826642Z" - }, "vscode": { "languageId": "python" } @@ -2639,12 +1936,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.827027Z", - "iopub.status.idle": "2024-04-28T16:47:35.827177Z", - "shell.execute_reply": "2024-04-28T16:47:35.827115Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.827109Z" - }, "vscode": { "languageId": "python" } @@ -2658,12 +1949,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.827817Z", - "iopub.status.idle": "2024-04-28T16:47:35.827945Z", - "shell.execute_reply": "2024-04-28T16:47:35.827887Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.827881Z" - }, "vscode": { "languageId": "python" } @@ -2684,12 +1969,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.828529Z", - "iopub.status.idle": "2024-04-28T16:47:35.828662Z", - "shell.execute_reply": "2024-04-28T16:47:35.828598Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.828592Z" - }, "scrolled": true, "vscode": { "languageId": "python" @@ -2705,12 +1984,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.829109Z", - "iopub.status.idle": "2024-04-28T16:47:35.829220Z", - "shell.execute_reply": "2024-04-28T16:47:35.829168Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.829163Z" - }, "vscode": { "languageId": "python" } @@ -2732,12 +2005,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.829520Z", - "iopub.status.idle": "2024-04-28T16:47:35.829624Z", - "shell.execute_reply": "2024-04-28T16:47:35.829575Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.829570Z" - }, "vscode": { "languageId": "python" } @@ -2751,12 +2018,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.829967Z", - "iopub.status.idle": "2024-04-28T16:47:35.830075Z", - "shell.execute_reply": "2024-04-28T16:47:35.830022Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.830017Z" - }, "vscode": { "languageId": "python" } @@ -2770,12 +2031,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.830423Z", - "iopub.status.idle": "2024-04-28T16:47:35.830530Z", - "shell.execute_reply": "2024-04-28T16:47:35.830480Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.830475Z" - }, "vscode": { "languageId": "python" } @@ -2797,12 +2052,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.830926Z", - "iopub.status.idle": "2024-04-28T16:47:35.831031Z", - "shell.execute_reply": "2024-04-28T16:47:35.830981Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.830976Z" - }, "vscode": { "languageId": "python" } @@ -2816,12 +2065,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.831391Z", - "iopub.status.idle": "2024-04-28T16:47:35.831494Z", - "shell.execute_reply": "2024-04-28T16:47:35.831445Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.831440Z" - }, "vscode": { "languageId": "python" } @@ -2842,12 +2085,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.831747Z", - "iopub.status.idle": "2024-04-28T16:47:35.831846Z", - "shell.execute_reply": "2024-04-28T16:47:35.831799Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.831794Z" - }, "vscode": { "languageId": "python" } @@ -2861,12 +2098,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.832177Z", - "iopub.status.idle": "2024-04-28T16:47:35.832284Z", - "shell.execute_reply": "2024-04-28T16:47:35.832233Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.832227Z" - }, "vscode": { "languageId": "python" } @@ -2887,12 +2118,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.832846Z", - "iopub.status.idle": "2024-04-28T16:47:35.832948Z", - "shell.execute_reply": "2024-04-28T16:47:35.832899Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.832894Z" - }, "vscode": { "languageId": "python" } @@ -2906,12 +2131,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.833229Z", - "iopub.status.idle": "2024-04-28T16:47:35.833331Z", - "shell.execute_reply": "2024-04-28T16:47:35.833282Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.833277Z" - }, "vscode": { "languageId": "python" } @@ -2932,12 +2151,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.833627Z", - "iopub.status.idle": "2024-04-28T16:47:35.833835Z", - "shell.execute_reply": "2024-04-28T16:47:35.833733Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.833723Z" - }, "vscode": { "languageId": "python" } @@ -2951,12 +2164,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.834395Z", - "iopub.status.idle": "2024-04-28T16:47:35.834543Z", - "shell.execute_reply": "2024-04-28T16:47:35.834472Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.834467Z" - }, "vscode": { "languageId": "python" } @@ -2977,12 +2184,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.835103Z", - "iopub.status.idle": "2024-04-28T16:47:35.835259Z", - "shell.execute_reply": "2024-04-28T16:47:35.835191Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.835185Z" - }, "vscode": { "languageId": "python" } @@ -2996,12 +2197,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.835678Z", - "iopub.status.idle": "2024-04-28T16:47:35.835800Z", - "shell.execute_reply": "2024-04-28T16:47:35.835747Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.835742Z" - }, "vscode": { "languageId": "python" } @@ -3028,7 +2223,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.14" + "version": "3.11.11" }, "toc-showmarkdowntxt": false }, diff --git a/tests/test10/HSP2results/test10.example.py b/tests/test10/HSP2results/test10.example.py index 47d10924..6c0ebb90 100644 --- a/tests/test10/HSP2results/test10.example.py +++ b/tests/test10/HSP2results/test10.example.py @@ -1,25 +1,28 @@ import sys -from numba import int8, float32, njit, types, typed # import the types + +from numba import float32, int8, njit, typed, types # import the types print("Loaded a set of HSP2 code!") + @njit def state_step_hydr(state_info, state_paths, state_ix, dict_ix, ts_ix, hydr_ix, step): - if (step <= 1): - print("Custom state_step_hydr() called for ", state_info['segment']) - print("operation", state_info['operation']) + if step <= 1: + print("Custom state_step_hydr() called for ", state_info["segment"]) + print("operation", state_info["operation"]) print("state at start", state_ix) print("domain info", state_info) print("state_paths", state_paths) # Do a simple withdrawal of 10 MGGD from R001 - if (state_info['segment'] == 'R001') and (state_info['activity'] == 'HYDR'): - state_ix[hydr_ix['O1']] = 10.0 * 1.547 + if (state_info["segment"] == "R001") and (state_info["activity"] == "HYDR"): + state_ix[hydr_ix["O1"]] = 10.0 * 1.547 # Route point source return from segment R001 demand to R005 inflow (IVOL) # For demo purposes this will only use the last state_ix value for R001 demand # Realistic approach would run all segments simultaneously or use value from ts_ix (ts_ix loading TBD) - if (state_info['segment'] == 'R005') and (state_info['activity'] == 'HYDR'): - state_ix[hydr_ix['IVOL']] += 0.85 * state_ix[state_paths['/STATE/RCHRES_R001/HYDR/O1']] - if (step <= 1): - print("IVOL after", state_ix[hydr_ix['IVOL']]) + if (state_info["segment"] == "R005") and (state_info["activity"] == "HYDR"): + state_ix[hydr_ix["IVOL"]] += ( + 0.85 * state_ix[state_paths["/STATE/RCHRES_R001/HYDR/O1"]] + ) + if step <= 1: + print("IVOL after", state_ix[hydr_ix["IVOL"]]) return - diff --git a/tests/test10/HSP2results/test10.uci b/tests/test10/HSP2results/test10.uci index 5ec4f0f2..624b8e0f 100644 --- a/tests/test10/HSP2results/test10.uci +++ b/tests/test10/HSP2results/test10.uci @@ -9,7 +9,7 @@ END GLOBAL *** This test run uses MASS-LINK and SCHEMATIC blocks *** -FILES +FILES ***<----FILE NAME-------------------------------------------------> WDM 21 test10.wdm MESSU 22 test10.ech @@ -294,7 +294,7 @@ RCHRES ACTIVITY RCHRES Active Sections (1=Active, 0=Inactive) *** # - # HYFG ADFG CNFG HTFG SDFG GQFG OXFG NUFG PKFG PHFG *** - 1 5 1 1 1 1 1 1 1 1 1 1 + 1 5 1 1 1 1 1 1 1 1 1 1 END ACTIVITY PRINT-INFO @@ -597,8 +597,8 @@ RCHRES OX-BENPARM RCHRES BENOD TCBEN EXPOD BRBOD(1) BRBOD(2) EXPREL *** - # - # mg/m2.hr mg/m2.hr mg/m2.hr *** - 1 5 10. 1.1 1.2 20. 25. 1.3 + # - # mg/m2.hr mg/m2.hr mg/m2.hr *** + 1 5 10. 1.1 1.2 20. 25. 1.3 END OX-BENPARM OX-CFOREA @@ -628,46 +628,46 @@ RCHRES END NUT-FLAGS NUT-BENPARM - RCHRES BRTAM(1) BRTAM(2) BRPO4(1) BRPO4(2) ANAER *** - # - # mg/m2.hr mg/m2.hr mg/m2.hr mg/m2.hr mg/l *** + RCHRES BRTAM(1) BRTAM(2) BRPO4(1) BRPO4(2) ANAER *** + # - # mg/m2.hr mg/m2.hr mg/m2.hr mg/m2.hr mg/l *** 1 5 11.0 33.0 1.1 2.2 0.0005 - END NUT-BENPARM - + END NUT-BENPARM + NUT-NITDENIT - RCHRES KTAM20 KNO220 TCNIT KNO320 TCDEN DENOXT *** - # - # /hr /hr /hr mg/l *** + RCHRES KTAM20 KNO220 TCNIT KNO320 TCDEN DENOXT *** + # - # /hr /hr /hr mg/l *** 1 5 .002 .004 1.07 .001 1.04 0.2 END NUT-NITDENIT - + NUT-NH3VOLAT - RCHRES EXPNVG EXPNVL *** - # - # *** + RCHRES EXPNVG EXPNVL *** + # - # *** 1 5 .50 0.6667 - END NUT-NH3VOLAT - - NUT-BEDCONC + END NUT-NH3VOLAT + + NUT-BEDCONC RCHRES Bed concentrations of NH4 & PO4 (mg/mg) *** # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** 1 5 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 - END NUT-BEDCONC - - NUT-ADSPARM + END NUT-BEDCONC + + NUT-ADSPARM RCHRES Partition coefficients for NH4 AND PO4 (l/mg) *** # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** 1 5 0.0001 0.0001 0.0001 10. 10. 10. END NUT-ADSPARM - - NUT-DINIT + + NUT-DINIT RCHRES NO3 TAM NO2 PO4 PHVAL *** - # - # mg/l mg/l mg/l mg/l ph units *** + # - # mg/l mg/l mg/l mg/l ph units *** 1 5 40. 10. 1. 50. 7.0 END NUT-DINIT - - NUT-ADSINIT + + NUT-ADSINIT RCHRES Initial suspended NH4 and PO4 concentrations (mg/mg) *** # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** 1 5 0. 0. 0. 0. 0. 0. - END NUT-ADSINIT + END NUT-ADSINIT *** Section PLANK *** @@ -920,11 +920,11 @@ SCHEMATIC # <-factor-> # # *** PERLND 1 6000. RCHRES 1 1 IMPLND 1 3000. RCHRES 5 2 -RCHRES 1 RCHRES 2 3 -RCHRES 1 RCHRES 3 4 -RCHRES 2 RCHRES 4 5 -RCHRES 3 RCHRES 4 5 -RCHRES 4 RCHRES 5 5 +RCHRES 1 RCHRES 2 3 +RCHRES 1 RCHRES 3 4 +RCHRES 2 RCHRES 4 5 +RCHRES 3 RCHRES 4 5 +RCHRES 4 RCHRES 5 5 END SCHEMATIC MASS-LINK diff --git a/tests/test10/HSPFresults/HSPF.log b/tests/test10/HSPFresults/HSPF.log index 369c42ed..1b359a51 100644 --- a/tests/test10/HSPFresults/HSPF.log +++ b/tests/test10/HSPFresults/HSPF.log @@ -62,7 +62,7 @@ 00:00:01.366 WriteStatus:(MSG7 unit 99 file ERROR.FIL is open, access:SEQUENTIAL form:FORMATTED r/w:YES recl: 80) 00:00:01.366 Main:Token:MSG7 unit 100 file c:\basins45\models\winhspf31\bin\hspfmsg.wdm is open, access:DIRECT form:UNFORMATTED r/w:NO recl: 2048 00:00:01.366 WriteStatus:(MSG7 unit 100 file c:\basins45\models\winhspf31\bin\hspfmsg.wdm is open, access:DIRECT form:UNFORMATTED r/w:NO recl: 2048) -00:00:01.366 Main:Token:MSG99 +00:00:01.366 Main:Token:MSG99 00:00:01.366 WriteStatus:(MSG99 ) 00:00:01.367 Main:Token:MSG7 File Status at before WDM closing in M_ACTSCN 00:00:01.367 WriteStatus:(MSG7 File Status at before WDM closing in M_ACTSCN) @@ -147,9 +147,9 @@ 00:00:03.480 WriteStatus:(MSG2 FTABLES) 00:00:03.480 Main:Token:MSG2 MASS-LINK 00:00:03.480 WriteStatus:(MSG2 MASS-LINK) -00:00:03.480 Main:Token:MSG3 +00:00:03.480 Main:Token:MSG3 00:00:03.480 WriteStatus:(MSG3 ) -00:00:03.480 Main:Token:MSG4 +00:00:03.480 Main:Token:MSG4 00:00:03.480 WriteStatus:(MSG4 ) 00:00:03.480 Main:Token:MSG2 PERLND 00:00:03.481 WriteStatus:(MSG2 PERLND) @@ -211,9 +211,9 @@ 00:00:03.489 WriteStatus:(MSG4 PWT-TEMPS) 00:00:03.489 Main:Token:MSG4 PWT-GASES 00:00:03.490 WriteStatus:(MSG4 PWT-GASES) -00:00:03.490 Main:Token:MSG3 +00:00:03.490 Main:Token:MSG3 00:00:03.490 WriteStatus:(MSG3 ) -00:00:03.490 Main:Token:MSG4 +00:00:03.490 Main:Token:MSG4 00:00:03.490 WriteStatus:(MSG4 ) 00:00:03.490 Main:Token:MSG2 IMPLND 00:00:03.490 WriteStatus:(MSG2 IMPLND) @@ -269,9 +269,9 @@ 00:00:03.498 WriteStatus:(MSG4 QUAL-PROPS) 00:00:03.498 Main:Token:MSG4 QUAL-INPUT 00:00:03.498 WriteStatus:(MSG4 QUAL-INPUT) -00:00:03.498 Main:Token:MSG3 +00:00:03.498 Main:Token:MSG3 00:00:03.498 WriteStatus:(MSG3 ) -00:00:03.499 Main:Token:MSG4 +00:00:03.499 Main:Token:MSG4 00:00:03.499 WriteStatus:(MSG4 ) 00:00:03.499 Main:Token:MSG2 RCHRES 00:00:03.499 WriteStatus:(MSG2 RCHRES) @@ -1021,9 +1021,9 @@ 00:00:03.624 WriteStatus:(MSG4 PH-PARM2) 00:00:03.624 Main:Token:MSG4 PH-INIT 00:00:03.624 WriteStatus:(MSG4 PH-INIT) -00:00:03.624 Main:Token:MSG3 +00:00:03.624 Main:Token:MSG3 00:00:03.624 WriteStatus:(MSG3 ) -00:00:03.624 Main:Token:MSG4 +00:00:03.624 Main:Token:MSG4 00:00:03.624 WriteStatus:(MSG4 ) 00:00:03.625 Main:Token:MSG2 DISPLY 00:00:03.625 WriteStatus:(MSG2 DISPLY) @@ -1057,9 +1057,9 @@ 00:00:03.629 WriteStatus:(MSG4 DISPLY-INFO1) 00:00:03.629 Main:Token:MSG4 DISPLY-INFO2 00:00:03.629 WriteStatus:(MSG4 DISPLY-INFO2) -00:00:03.629 Main:Token:MSG3 +00:00:03.629 Main:Token:MSG3 00:00:03.629 WriteStatus:(MSG3 ) -00:00:03.629 Main:Token:MSG4 +00:00:03.629 Main:Token:MSG4 00:00:03.630 WriteStatus:(MSG4 ) 00:00:03.630 Main:Token:MSG2 GENER 00:00:03.630 WriteStatus:(MSG2 GENER) @@ -1071,9 +1071,9 @@ 00:00:03.631 WriteStatus:(MSG3 2) 00:00:03.631 Main:Token:MSG4 OPCODE 00:00:03.631 WriteStatus:(MSG4 OPCODE) -00:00:03.631 Main:Token:MSG3 +00:00:03.631 Main:Token:MSG3 00:00:03.631 WriteStatus:(MSG3 ) -00:00:03.631 Main:Token:MSG4 +00:00:03.631 Main:Token:MSG4 00:00:03.631 WriteStatus:(MSG4 ) 00:00:03.632 Main:Token:MSG2 PLTGEN 00:00:03.632 WriteStatus:(MSG2 PLTGEN) @@ -1105,15 +1105,15 @@ 00:00:03.635 WriteStatus:(MSG4 CURV-DATA) 00:00:03.635 Main:Token:MSG4 CURV-DATA 00:00:03.635 WriteStatus:(MSG4 CURV-DATA) -00:00:03.635 Main:Token:MSG3 +00:00:03.635 Main:Token:MSG3 00:00:03.635 WriteStatus:(MSG3 ) -00:00:03.636 Main:Token:MSG4 +00:00:03.636 Main:Token:MSG4 00:00:03.636 WriteStatus:(MSG4 ) -00:00:03.636 Main:Token:MSG3 +00:00:03.636 Main:Token:MSG3 00:00:03.636 WriteStatus:(MSG3 ) -00:00:03.636 Main:Token:MSG3 +00:00:03.636 Main:Token:MSG3 00:00:03.636 WriteStatus:(MSG3 ) -00:00:03.636 Main:Token:MSG4 +00:00:03.636 Main:Token:MSG4 00:00:03.636 WriteStatus:(MSG4 ) 00:00:03.637 Main:Token:MSG2 EXT SOURCES 00:00:03.637 WriteStatus:(MSG2 EXT SOURCES) diff --git a/tests/test10/HSPFresults/test10.d66 b/tests/test10/HSPFresults/test10.d66 index da8b30be..f7be4e8c 100644 --- a/tests/test10/HSPFresults/test10.d66 +++ b/tests/test10/HSPFresults/test10.d66 @@ -8,37 +8,37 @@ Annual data display: Summary for period ending 1976/12 Day JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC - + 1 52.53 32.21 38.94 46.64 56.64 68.84 76.16 82.48 77.61 62.65 40.97 32.07 2 40.78 32.07 35.58 48.59 54.84 68.61 76.59 83.37 76.43 64.77 41.81 32.07 3 32.49 32.28 32.89 49.93 52.23 67.47 77.79 82.51 75.67 66.03 40.57 32.08 4 32.08 32.07 32.07 49.36 52.73 66.62 78.40 79.58 75.01 66.46 37.47 32.07 5 32.10 32.07 32.41 50.83 55.15 67.65 79.90 78.59 74.71 64.44 34.87 32.12 - + 6 32.07 32.19 32.99 53.18 56.59 69.06 81.09 78.26 73.39 61.87 34.11 32.07 7 32.07 32.43 33.25 54.33 56.90 69.61 81.73 78.10 73.04 60.61 33.05 32.07 8 32.07 33.06 32.97 54.07 57.25 71.48 81.80 79.03 73.21 58.42 32.35 32.07 9 32.08 33.34 33.84 53.82 58.36 73.89 82.47 78.81 71.94 56.58 32.93 32.07 10 32.07 34.75 36.13 54.77 60.92 74.46 84.17 78.07 70.29 56.73 32.36 32.07 - + 11 32.12 35.27 36.31 54.15 63.11 74.32 85.27 78.08 70.95 56.83 32.11 32.08 12 32.50 35.95 37.14 52.13 63.23 75.73 85.61 79.46 70.80 56.92 32.10 32.07 13 32.44 36.75 36.49 52.70 61.75 75.41 86.68 80.29 70.65 57.76 32.15 32.09 14 32.36 35.11 35.80 55.39 61.04 74.65 87.37 79.22 72.04 57.30 32.27 32.14 15 32.26 35.86 36.25 60.32 60.75 73.88 86.54 79.02 71.79 55.54 32.39 32.22 - + 16 32.07 36.49 35.80 65.52 59.20 71.50 82.67 76.22 72.01 51.68 32.44 32.24 17 32.12 35.17 35.39 65.42 58.58 70.22 81.09 73.95 73.64 49.57 32.82 32.36 18 32.10 35.05 37.89 64.71 59.49 69.79 82.41 75.71 75.14 47.05 33.49 33.01 19 32.07 36.08 43.83 63.35 61.48 67.60 80.37 77.67 75.17 43.66 34.62 33.74 20 32.13 36.15 48.77 60.43 64.78 66.39 79.17 79.01 73.65 42.20 34.61 32.11 - + 21 32.07 34.11 47.13 57.85 68.04 66.56 79.59 80.08 72.07 41.33 33.31 32.07 22 32.36 32.44 44.49 58.48 67.05 67.00 78.87 81.91 70.93 40.49 32.15 32.07 23 32.70 33.36 44.45 58.38 63.56 67.67 80.96 83.60 69.79 39.67 32.17 32.07 24 32.49 35.07 46.87 55.63 62.41 69.08 82.87 84.68 68.20 39.39 32.82 32.20 25 32.08 37.01 47.81 52.29 63.58 70.45 82.98 85.74 66.33 39.62 33.76 32.39 - + 26 32.09 38.36 48.94 51.45 64.95 73.10 82.80 85.13 64.29 39.59 34.77 32.17 27 32.26 40.84 48.75 52.46 66.43 74.58 82.62 83.20 62.36 39.58 32.18 32.61 28 32.41 42.14 48.80 53.68 67.49 74.63 82.57 81.04 60.49 39.22 32.07 32.07 @@ -54,42 +54,42 @@ - O2 CONC, MEIER POND (mg/l) + O2 CONC, MEIER POND (mg/l) Annual data display: Summary for period ending 1976/12 Day JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC - + 1 8.28 13.96 11.61 10.38 9.00 8.07 7.50 7.01 7.35 9.13 12.30 14.12 2 10.68 13.98 12.18 10.31 8.97 8.07 7.49 6.99 7.45 8.88 12.23 14.11 3 13.10 13.95 12.76 10.13 9.18 8.13 7.42 6.98 7.57 8.67 12.23 14.11 4 13.91 13.95 13.05 10.14 9.33 8.24 7.36 7.17 7.63 8.52 12.69 14.11 5 13.99 13.97 13.18 10.09 9.28 8.28 7.29 7.38 7.69 8.60 13.27 14.08 - + 6 13.99 13.97 13.17 9.93 9.16 8.22 7.18 7.43 7.75 8.94 13.62 14.07 7 14.04 13.95 12.96 9.72 9.11 8.16 7.10 7.48 7.88 9.16 13.79 14.10 8 14.02 13.88 12.83 9.69 9.09 8.08 7.06 7.43 7.85 9.38 14.04 14.10 9 13.97 13.78 12.77 9.69 9.05 7.91 7.04 7.39 7.91 9.69 14.05 14.10 10 13.96 13.58 12.26 9.68 8.95 7.74 6.95 7.44 8.09 9.79 14.02 14.10 - + 11 13.95 13.39 11.98 9.66 8.76 7.67 6.83 7.45 8.13 9.77 14.12 14.09 12 13.89 13.29 11.76 9.83 8.63 7.62 6.78 7.39 8.09 9.76 14.15 14.09 13 13.80 13.06 11.55 9.94 8.62 7.53 6.71 7.24 8.12 9.69 14.15 14.09 14 13.77 13.23 11.54 9.80 8.70 7.49 6.63 7.25 8.03 9.66 14.13 14.08 15 13.78 13.27 11.59 9.34 8.73 7.53 6.63 7.33 7.95 9.79 14.10 14.06 - + 16 13.82 13.00 11.69 8.81 8.78 7.66 6.82 7.42 7.98 10.22 14.08 14.05 17 13.85 13.05 11.83 8.44 8.85 7.84 7.11 7.74 7.84 10.68 14.04 14.03 18 13.87 13.20 11.81 8.23 8.86 7.95 7.10 7.74 7.68 10.99 13.93 13.96 19 13.88 13.12 11.34 8.23 8.79 8.09 7.14 7.54 7.54 11.53 13.67 13.74 20 13.89 12.98 10.72 8.39 8.62 8.27 7.32 7.37 7.66 12.00 13.59 14.01 - + 21 13.91 13.20 10.43 8.54 8.36 8.37 7.33 7.23 7.83 12.15 13.69 14.10 22 13.89 13.62 10.57 8.64 8.21 8.40 7.35 7.08 7.98 12.39 13.99 14.07 23 13.85 13.56 10.95 8.67 8.32 8.38 7.33 6.85 8.10 12.46 14.10 14.06 24 13.82 13.18 10.88 8.67 8.51 8.28 7.11 6.73 8.27 12.63 14.06 14.04 25 13.87 12.61 10.62 8.85 8.57 8.14 7.05 6.59 8.44 12.61 13.88 14.01 - + 26 13.93 12.30 10.40 9.05 8.52 7.97 7.00 6.56 8.71 12.60 13.59 14.01 27 13.93 11.81 10.34 9.13 8.44 7.76 7.05 6.70 8.91 12.60 13.86 13.99 28 13.92 11.45 10.31 9.13 8.34 7.63 6.98 6.92 9.19 12.64 14.09 13.99 @@ -105,42 +105,42 @@ - PEST SED CONC, POND (mg/kg) + PEST SED CONC, POND (mg/kg) Annual data display: Summary for period ending 1976/12 Day JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC - + 1 0.10 0.03 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2 0.09 0.03 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3 0.09 0.03 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4 0.09 0.03 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5 0.08 0.03 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - + 6 0.08 0.03 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 7 0.08 0.03 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 8 0.07 0.02 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 9 0.07 0.02 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 10 0.07 0.02 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - + 11 0.07 0.02 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 12 0.06 0.02 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 13 0.06 0.02 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 14 0.06 0.02 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 15 0.06 0.02 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - + 16 0.06 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 17 0.05 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 18 0.05 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 19 0.05 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 20 0.05 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - + 21 0.05 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 22 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 23 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 24 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 25 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - + 26 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 27 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 28 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 @@ -161,37 +161,37 @@ Annual data display: Summary for period ending 1976/12 Day JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC - + 1 12.34 14.37 14.07 11.29 10.15 8.95 8.10 7.75******************************** 2 10.05 14.12 14.38 11.17 10.54 8.97 7.74 7.17******************************** 3 12.63 14.31 14.38 11.40 10.70 9.18 7.80 8.19******************************** 4 12.23 14.37 14.38 11.00 10.61 9.18 7.85 8.43******************************** 5 12.97 14.37 14.07 10.83 10.01 8.98 7.41 7.76******** 10.70**************** - + 6 12.61 13.75 14.08 10.51 10.13 8.81 7.63 7.65******** 6.80**************** 7 12.80 13.75 14.05 10.89 9.94 8.73 7.60 7.69******************************** 8 14.01 13.82 14.05 10.36 9.97 8.42 7.62 7.74******************************** 9 14.14 13.38 13.98 10.62 9.79 8.29 7.45 7.81******************************** 10 14.33 13.25 14.14 10.38 9.61 8.83 7.31 7.86******************************** - + 11 14.18 12.80 14.17 10.71 9.16 8.31 7.51 7.84******************************** 12 14.28 12.67 13.69 10.77 9.73 8.12 7.20 7.85******************************** 13 14.25 13.66 13.97 10.49 9.81 8.54 7.16 8.22******************************** 14 13.91 13.10 14.09 9.93 9.63 8.85 7.41 8.75 8.99************************ 15 14.36 11.82 13.98 9.46 9.99 8.77 7.98******************************** 10.67 - + 16 14.36 13.40 13.98 8.73 9.96 8.95 8.33******************************** 10.08 17 13.99 14.31 13.64 9.40 9.93 8.69 7.21 8.35************************ 13.68 18 14.22 13.37 12.51 9.59 9.56 9.04 7.66******************************** 13.35 19 14.37 13.14 11.83 9.43 9.42 9.27 8.71**************** 13.20******** 10.35 20 14.28 14.04 12.14 9.99 8.98 9.12 8.39******** 9.22 9.60******** 5.46 - + 21 14.23 14.34 12.10 10.11 8.78 9.06 8.03**************************************** 22 13.73 13.90 12.09 9.84 9.61 8.98 7.90**************************************** 23 13.81 13.83 11.88 10.30 9.62 9.01 6.37**************************************** 24 14.09 14.09 10.87 10.34 9.29 8.68 7.75**************** 10.98**************** 25 14.37 13.61 11.59 10.73 9.08 8.39 7.56**************** 6.22**************** - + 26 14.32 13.20 11.15 10.76 9.00 8.35 8.86 8.81******************************** 27 13.35 12.68 11.13 10.64 8.99 8.45 7.56**************************************** 28 13.99 12.82 11.29 10.41 8.92 8.26 8.94**************************************** @@ -212,37 +212,37 @@ Annual data display: Summary for period ending 1976/12 Day JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC - + 1 0.10 0.06 0.03 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2 0.10 0.06 0.03 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3 0.10 0.06 0.03 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4 0.10 0.05 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5 0.10 0.05 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - + 6 0.09 0.05 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 7 0.09 0.05 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 8 0.09 0.05 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 9 0.09 0.05 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 10 0.09 0.05 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - + 11 0.08 0.05 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 12 0.08 0.05 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 13 0.08 0.05 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 14 0.08 0.05 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 15 0.07 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - + 16 0.07 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 17 0.07 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 18 0.07 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 19 0.07 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 20 0.07 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - + 21 0.07 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 22 0.07 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 23 0.07 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 24 0.06 0.03 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 25 0.06 0.03 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - + 26 0.06 0.03 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 27 0.06 0.03 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 28 0.06 0.03 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 diff --git a/tests/test10/HSPFresults/test10.mwprj b/tests/test10/HSPFresults/test10.mwprj index 0651a35b..35c3921b 100644 --- a/tests/test10/HSPFresults/test10.mwprj +++ b/tests/test10/HSPFresults/test10.mwprj @@ -64,4 +64,4 @@ - \ No newline at end of file + diff --git a/tests/test10/HSPFresults/test10.p94 b/tests/test10/HSPFresults/test10.p94 index cec91099..8cb01406 100644 --- a/tests/test10/HSPFresults/test10.p94 +++ b/tests/test10/HSPFresults/test10.p94 @@ -2,10 +2,10 @@ SIMU HSPF FILE FOR DRIVING SEPARATE PLOT PROGRAM SIMU Time interval: 1440 mins Last month in printout year: 9 SIMU No. of curves plotted: Point-valued: 0 Mean-valued: 2 Total 2 SIMU Label flag: 0 Pivl: 24 Idelt: 60 -SIMU Plot title: SIMULATED FLOWS (CFS) -SIMU Y-axis label: CFS +SIMU Plot title: SIMULATED FLOWS (CFS) +SIMU Y-axis label: CFS SIMU Scale info: Ymin: 0.0000 Threshold:-0.10000E+31 -SIMU Ymax: 150.00 +SIMU Ymax: 150.00 SIMU Time: 20.000 intervals/inch SIMU Data for each curve (Point-valued first, then mean-valued): SIMU Label LINTYP INTEQ COLCOD TRAN TRANCOD @@ -24,369 +24,369 @@ SIMU SIMU Date/time Values SIMU SIMU 1975 12 31 24 0-1.0000000E+30-1.0000000E+30 -SIMU 1976 1 1 24 0 1.4474289E-02 1.260718 +SIMU 1976 1 1 24 0 1.4474289E-02 1.260718 SIMU 1976 1 2 24 0 0.1248719 9.5694907E-02 -SIMU 1976 1 3 24 0 0.1909118 1.438969 -SIMU 1976 1 4 24 0 0.2214593 0.3149185 -SIMU 1976 1 5 24 0 0.2445364 26.38584 -SIMU 1976 1 6 24 0 0.2830130 0.4501142 -SIMU 1976 1 7 24 0 0.3058431 17.70815 -SIMU 1976 1 8 24 0 0.3417993 23.47737 -SIMU 1976 1 9 24 0 0.3868528 20.78489 -SIMU 1976 1 10 24 0 0.4243174 9.438145 -SIMU 1976 1 11 24 0 0.4571089 36.51984 -SIMU 1976 1 12 24 0 0.5390512 31.99113 -SIMU 1976 1 13 24 0 0.6745985 11.18829 -SIMU 1976 1 14 24 0 0.7997810 5.255074 -SIMU 1976 1 15 24 0 0.8668398 0.9759123 -SIMU 1976 1 16 24 0 0.8930736 0.8872543 -SIMU 1976 1 17 24 0 0.8937428 0.8937156 -SIMU 1976 1 18 24 0 0.8816622 0.8843302 -SIMU 1976 1 19 24 0 0.8650545 0.8686689 -SIMU 1976 1 20 24 0 0.8467069 0.8506928 -SIMU 1976 1 21 24 0 0.8278188 0.8319094 -SIMU 1976 1 22 24 0 0.8089502 0.8130208 -SIMU 1976 1 23 24 0 0.7940420 1.102890 -SIMU 1976 1 24 24 0 0.7959095 0.8527839 -SIMU 1976 1 25 24 0 0.7976615 0.7947715 -SIMU 1976 1 26 24 0 0.7891020 0.7936022 -SIMU 1976 1 27 24 0 0.7674562 0.7721074 -SIMU 1976 1 28 24 0 0.7492455 0.9383754 -SIMU 1976 1 29 24 0 0.7572476 4.939040 -SIMU 1976 1 30 24 0 0.8015971 0.9141596 -SIMU 1976 1 31 24 0 0.8147146 0.8119590 -SIMU 1976 2 1 24 0 0.8136443 0.8118444 -SIMU 1976 2 2 24 0 0.8198046 0.8167373 -SIMU 1976 2 3 24 0 0.8151059 0.8153910 -SIMU 1976 2 4 24 0 0.8031108 0.8050318 -SIMU 1976 2 5 24 0 0.7878329 0.7904783 -SIMU 1976 2 6 24 0 0.7712485 0.7741784 -SIMU 1976 2 7 24 0 0.7542881 0.7572957 -SIMU 1976 2 8 24 0 0.7379165 11.98187 -SIMU 1976 2 9 24 0 0.7289269 2.172925 -SIMU 1976 2 10 24 0 0.7348322 0.8702201 -SIMU 1976 2 11 24 0 0.7378606 1.010215 -SIMU 1976 2 12 24 0 0.7313829 0.7404312 -SIMU 1976 2 13 24 0 0.7196591 0.7215089 -SIMU 1976 2 14 24 0 0.7056407 10.74174 -SIMU 1976 2 15 24 0 0.7427791 27.17800 -SIMU 1976 2 16 24 0 0.8933365 24.57355 -SIMU 1976 2 17 24 0 1.170159 1.243186 -SIMU 1976 2 18 24 0 1.265975 1.249576 -SIMU 1976 2 19 24 0 1.290379 1.285805 -SIMU 1976 2 20 24 0 1.315735 1.297269 -SIMU 1976 2 21 24 0 1.744743 1.680262 -SIMU 1976 2 22 24 0 1.828289 1.838541 -SIMU 1976 2 23 24 0 1.876627 21.52497 -SIMU 1976 2 24 24 0 2.222392 22.60762 -SIMU 1976 2 25 24 0 2.781559 4.881145 -SIMU 1976 2 26 24 0 3.252400 8.318310 -SIMU 1976 2 27 24 0 3.815419 4.403160 -SIMU 1976 2 28 24 0 4.162813 4.133219 -SIMU 1976 2 29 24 0 4.275207 4.266679 -SIMU 1976 3 1 24 0 4.249340 4.252468 -SIMU 1976 3 2 24 0 4.171464 4.178832 -SIMU 1976 3 3 24 0 4.054302 4.065627 -SIMU 1976 3 4 24 0 4.062371 4.110520 -SIMU 1976 3 5 24 0 3.950461 25.12659 -SIMU 1976 3 6 24 0 3.883912 22.85689 -SIMU 1976 3 7 24 0 4.228174 17.44470 -SIMU 1976 3 8 24 0 4.652520 4.648649 -SIMU 1976 3 9 24 0 4.921869 16.56644 -SIMU 1976 3 10 24 0 5.185582 17.49589 -SIMU 1976 3 11 24 0 5.481184 92.66568 -SIMU 1976 3 12 24 0 6.213936 39.19748 -SIMU 1976 3 13 24 0 7.056890 42.41711 -SIMU 1976 3 14 24 0 7.707804 33.54050 -SIMU 1976 3 15 24 0 8.199834 18.62578 -SIMU 1976 3 16 24 0 8.588259 34.20103 -SIMU 1976 3 17 24 0 8.884975 16.20712 -SIMU 1976 3 18 24 0 9.087730 9.808556 -SIMU 1976 3 19 24 0 9.234199 9.216591 -SIMU 1976 3 20 24 0 9.320614 9.307731 -SIMU 1976 3 21 24 0 9.353298 9.345859 -SIMU 1976 3 22 24 0 9.340808 9.337936 -SIMU 1976 3 23 24 0 9.289924 9.290966 -SIMU 1976 3 24 24 0 9.206184 9.210584 -SIMU 1976 3 25 24 0 9.094670 9.101867 -SIMU 1976 3 26 24 0 8.962339 31.67052 -SIMU 1976 3 27 24 0 8.832859 8.855320 -SIMU 1976 3 28 24 0 8.681973 18.34608 -SIMU 1976 3 29 24 0 8.545852 80.87876 -SIMU 1976 3 30 24 0 8.726319 124.2728 -SIMU 1976 3 31 24 0 8.954383 8.929785 -SIMU 1976 4 1 24 0 9.077915 9.055797 -SIMU 1976 4 2 24 0 9.125760 9.110368 -SIMU 1976 4 3 24 0 9.114639 9.105069 -SIMU 1976 4 4 24 0 9.056883 9.050970 -SIMU 1976 4 5 24 0 8.961176 8.955414 -SIMU 1976 4 6 24 0 8.832960 8.828364 -SIMU 1976 4 7 24 0 8.668804 8.666864 -SIMU 1976 4 8 24 0 8.470273 8.464606 -SIMU 1976 4 9 24 0 8.254838 8.257338 -SIMU 1976 4 10 24 0 8.023149 8.011706 -SIMU 1976 4 11 24 0 7.773345 19.12269 -SIMU 1976 4 12 24 0 7.515244 7.518793 -SIMU 1976 4 13 24 0 7.228179 7.223881 -SIMU 1976 4 14 24 0 6.940435 6.952693 -SIMU 1976 4 15 24 0 6.831132 55.63663 -SIMU 1976 4 16 24 0 6.734480 6.711138 -SIMU 1976 4 17 24 0 6.720130 325.9186 -SIMU 1976 4 18 24 0 7.225083 180.9549 -SIMU 1976 4 19 24 0 7.760850 7.699038 -SIMU 1976 4 20 24 0 8.150599 81.69958 -SIMU 1976 4 21 24 0 8.849834 18.02646 -SIMU 1976 4 22 24 0 9.515776 9.436546 -SIMU 1976 4 23 24 0 15.74128 74.15636 -SIMU 1976 4 24 24 0 20.78117 42.95824 -SIMU 1976 4 25 24 0 20.80364 21.50803 -SIMU 1976 4 26 24 0 19.42171 19.54881 -SIMU 1976 4 27 24 0 17.89425 17.99521 -SIMU 1976 4 28 24 0 16.68517 16.77532 -SIMU 1976 4 29 24 0 15.56366 15.63566 -SIMU 1976 4 30 24 0 14.59663 14.65335 -SIMU 1976 5 1 24 0 13.74321 13.79692 -SIMU 1976 5 2 24 0 15.23163 49.63367 -SIMU 1976 5 3 24 0 14.71212 14.76457 -SIMU 1976 5 4 24 0 13.82337 13.86915 -SIMU 1976 5 5 24 0 12.96066 13.00000 -SIMU 1976 5 6 24 0 12.15303 12.18444 -SIMU 1976 5 7 24 0 11.46644 11.49579 -SIMU 1976 5 8 24 0 10.81301 10.84046 -SIMU 1976 5 9 24 0 10.16247 10.17847 -SIMU 1976 5 10 24 0 9.972857 9.941750 -SIMU 1976 5 11 24 0 9.891415 9.866317 -SIMU 1976 5 12 24 0 9.762955 9.746064 -SIMU 1976 5 13 24 0 9.677894 70.44886 -SIMU 1976 5 14 24 0 9.652745 9.649599 -SIMU 1976 5 15 24 0 9.592699 20.91854 -SIMU 1976 5 16 24 0 6.950239 115.2386 -SIMU 1976 5 17 24 0 11.23013 10.83308 -SIMU 1976 5 18 24 0 10.84201 10.88450 -SIMU 1976 5 19 24 0 10.10124 10.13407 -SIMU 1976 5 20 24 0 9.402377 9.429980 -SIMU 1976 5 21 24 0 8.824148 8.848166 -SIMU 1976 5 22 24 0 8.706899 127.9437 -SIMU 1976 5 23 24 0 9.158713 41.48767 -SIMU 1976 5 24 24 0 8.744525 8.809204 -SIMU 1976 5 25 24 0 8.238327 8.269934 -SIMU 1976 5 26 24 0 7.745165 7.768769 -SIMU 1976 5 27 24 0 7.289109 7.308912 -SIMU 1976 5 28 24 0 7.042790 6.993178 -SIMU 1976 5 29 24 0 10.29947 9.986157 -SIMU 1976 5 30 24 0 9.576910 9.640110 -SIMU 1976 5 31 24 0 8.915795 8.963757 -SIMU 1976 6 1 24 0 8.356166 8.394520 -SIMU 1976 6 2 24 0 7.830907 7.860313 -SIMU 1976 6 3 24 0 7.317341 7.337018 -SIMU 1976 6 4 24 0 7.001420 6.979714 -SIMU 1976 6 5 24 0 6.963465 6.929173 -SIMU 1976 6 6 24 0 6.903966 6.876798 -SIMU 1976 6 7 24 0 6.821457 6.798852 -SIMU 1976 6 8 24 0 6.718878 6.697733 -SIMU 1976 6 9 24 0 6.596936 6.569315 -SIMU 1976 6 10 24 0 6.514006 104.2585 -SIMU 1976 6 11 24 0 6.471813 6.460088 -SIMU 1976 6 12 24 0 6.400855 29.84579 -SIMU 1976 6 13 24 0 6.385061 160.3763 -SIMU 1976 6 14 24 0 6.530354 26.87983 -SIMU 1976 6 15 24 0 6.638758 26.39072 -SIMU 1976 6 16 24 0 6.689775 6.659705 -SIMU 1976 6 17 24 0 6.696630 6.659134 -SIMU 1976 6 18 24 0 6.668063 17.99355 -SIMU 1976 6 19 24 0 6.613228 6.591832 -SIMU 1976 6 20 24 0 6.534174 6.507708 -SIMU 1976 6 21 24 0 6.434502 6.415373 -SIMU 1976 6 22 24 0 6.318646 6.298468 -SIMU 1976 6 23 24 0 6.187909 6.169038 -SIMU 1976 6 24 24 0 6.076590 29.41311 -SIMU 1976 6 25 24 0 6.020736 13.44458 -SIMU 1976 6 26 24 0 5.936152 20.28425 -SIMU 1976 6 27 24 0 5.868853 6.753101 -SIMU 1976 6 28 24 0 5.869579 5.839720 -SIMU 1976 6 29 24 0 5.884537 17.20980 -SIMU 1976 6 30 24 0 5.866933 5.845886 -SIMU 1976 7 1 24 0 5.823020 5.803921 -SIMU 1976 7 2 24 0 5.759427 5.754079 -SIMU 1976 7 3 24 0 5.677569 5.652538 -SIMU 1976 7 4 24 0 5.576257 5.563374 -SIMU 1976 7 5 24 0 5.463000 5.451096 -SIMU 1976 7 6 24 0 5.336662 5.317111 -SIMU 1976 7 7 24 0 5.193134 5.183722 -SIMU 1976 7 8 24 0 5.029192 5.014221 -SIMU 1976 7 9 24 0 4.856469 4.849349 -SIMU 1976 7 10 24 0 4.677545 4.662172 -SIMU 1976 7 11 24 0 4.492623 4.486209 -SIMU 1976 7 12 24 0 4.295463 4.290396 -SIMU 1976 7 13 24 0 4.080621 4.076970 -SIMU 1976 7 14 24 0 3.866693 3.859507 -SIMU 1976 7 15 24 0 3.656816 52.47431 -SIMU 1976 7 16 24 0 3.277588 3.677223 -SIMU 1976 7 17 24 0 2.590467 2.651126 -SIMU 1976 7 18 24 0 2.103326 2.139087 -SIMU 1976 7 19 24 0 1.766113 13.14555 -SIMU 1976 7 20 24 0 1.543120 24.25051 -SIMU 1976 7 21 24 0 1.414031 1.442276 -SIMU 1976 7 22 24 0 1.311040 1.323735 -SIMU 1976 7 23 24 0 1.221105 1.228090 -SIMU 1976 7 24 24 0 1.116907 1.118449 -SIMU 1976 7 25 24 0 0.9982151 1.003585 -SIMU 1976 7 26 24 0 0.8938456 36.33788 -SIMU 1976 7 27 24 0 0.8053325 21.40343 -SIMU 1976 7 28 24 0 0.9005256 167.9773 -SIMU 1976 7 29 24 0 0.9148608 0.9146647 -SIMU 1976 7 30 24 0 0.8806022 11.76961 -SIMU 1976 7 31 24 0 0.8438397 1.295588 -SIMU 1976 8 1 24 0 0.7890943 0.7919273 -SIMU 1976 8 2 24 0 0.7201992 0.7262144 -SIMU 1976 8 3 24 0 0.6435233 0.6522192 -SIMU 1976 8 4 24 0 0.5609179 0.5707234 -SIMU 1976 8 5 24 0 0.4756463 0.4873315 -SIMU 1976 8 6 24 0 0.3894908 0.4011723 -SIMU 1976 8 7 24 0 0.3043831 0.3180695 -SIMU 1976 8 8 24 0 0.2251702 0.2385858 -SIMU 1976 8 9 24 0 0.1414345 0.1565371 +SIMU 1976 1 3 24 0 0.1909118 1.438969 +SIMU 1976 1 4 24 0 0.2214593 0.3149185 +SIMU 1976 1 5 24 0 0.2445364 26.38584 +SIMU 1976 1 6 24 0 0.2830130 0.4501142 +SIMU 1976 1 7 24 0 0.3058431 17.70815 +SIMU 1976 1 8 24 0 0.3417993 23.47737 +SIMU 1976 1 9 24 0 0.3868528 20.78489 +SIMU 1976 1 10 24 0 0.4243174 9.438145 +SIMU 1976 1 11 24 0 0.4571089 36.51984 +SIMU 1976 1 12 24 0 0.5390512 31.99113 +SIMU 1976 1 13 24 0 0.6745985 11.18829 +SIMU 1976 1 14 24 0 0.7997810 5.255074 +SIMU 1976 1 15 24 0 0.8668398 0.9759123 +SIMU 1976 1 16 24 0 0.8930736 0.8872543 +SIMU 1976 1 17 24 0 0.8937428 0.8937156 +SIMU 1976 1 18 24 0 0.8816622 0.8843302 +SIMU 1976 1 19 24 0 0.8650545 0.8686689 +SIMU 1976 1 20 24 0 0.8467069 0.8506928 +SIMU 1976 1 21 24 0 0.8278188 0.8319094 +SIMU 1976 1 22 24 0 0.8089502 0.8130208 +SIMU 1976 1 23 24 0 0.7940420 1.102890 +SIMU 1976 1 24 24 0 0.7959095 0.8527839 +SIMU 1976 1 25 24 0 0.7976615 0.7947715 +SIMU 1976 1 26 24 0 0.7891020 0.7936022 +SIMU 1976 1 27 24 0 0.7674562 0.7721074 +SIMU 1976 1 28 24 0 0.7492455 0.9383754 +SIMU 1976 1 29 24 0 0.7572476 4.939040 +SIMU 1976 1 30 24 0 0.8015971 0.9141596 +SIMU 1976 1 31 24 0 0.8147146 0.8119590 +SIMU 1976 2 1 24 0 0.8136443 0.8118444 +SIMU 1976 2 2 24 0 0.8198046 0.8167373 +SIMU 1976 2 3 24 0 0.8151059 0.8153910 +SIMU 1976 2 4 24 0 0.8031108 0.8050318 +SIMU 1976 2 5 24 0 0.7878329 0.7904783 +SIMU 1976 2 6 24 0 0.7712485 0.7741784 +SIMU 1976 2 7 24 0 0.7542881 0.7572957 +SIMU 1976 2 8 24 0 0.7379165 11.98187 +SIMU 1976 2 9 24 0 0.7289269 2.172925 +SIMU 1976 2 10 24 0 0.7348322 0.8702201 +SIMU 1976 2 11 24 0 0.7378606 1.010215 +SIMU 1976 2 12 24 0 0.7313829 0.7404312 +SIMU 1976 2 13 24 0 0.7196591 0.7215089 +SIMU 1976 2 14 24 0 0.7056407 10.74174 +SIMU 1976 2 15 24 0 0.7427791 27.17800 +SIMU 1976 2 16 24 0 0.8933365 24.57355 +SIMU 1976 2 17 24 0 1.170159 1.243186 +SIMU 1976 2 18 24 0 1.265975 1.249576 +SIMU 1976 2 19 24 0 1.290379 1.285805 +SIMU 1976 2 20 24 0 1.315735 1.297269 +SIMU 1976 2 21 24 0 1.744743 1.680262 +SIMU 1976 2 22 24 0 1.828289 1.838541 +SIMU 1976 2 23 24 0 1.876627 21.52497 +SIMU 1976 2 24 24 0 2.222392 22.60762 +SIMU 1976 2 25 24 0 2.781559 4.881145 +SIMU 1976 2 26 24 0 3.252400 8.318310 +SIMU 1976 2 27 24 0 3.815419 4.403160 +SIMU 1976 2 28 24 0 4.162813 4.133219 +SIMU 1976 2 29 24 0 4.275207 4.266679 +SIMU 1976 3 1 24 0 4.249340 4.252468 +SIMU 1976 3 2 24 0 4.171464 4.178832 +SIMU 1976 3 3 24 0 4.054302 4.065627 +SIMU 1976 3 4 24 0 4.062371 4.110520 +SIMU 1976 3 5 24 0 3.950461 25.12659 +SIMU 1976 3 6 24 0 3.883912 22.85689 +SIMU 1976 3 7 24 0 4.228174 17.44470 +SIMU 1976 3 8 24 0 4.652520 4.648649 +SIMU 1976 3 9 24 0 4.921869 16.56644 +SIMU 1976 3 10 24 0 5.185582 17.49589 +SIMU 1976 3 11 24 0 5.481184 92.66568 +SIMU 1976 3 12 24 0 6.213936 39.19748 +SIMU 1976 3 13 24 0 7.056890 42.41711 +SIMU 1976 3 14 24 0 7.707804 33.54050 +SIMU 1976 3 15 24 0 8.199834 18.62578 +SIMU 1976 3 16 24 0 8.588259 34.20103 +SIMU 1976 3 17 24 0 8.884975 16.20712 +SIMU 1976 3 18 24 0 9.087730 9.808556 +SIMU 1976 3 19 24 0 9.234199 9.216591 +SIMU 1976 3 20 24 0 9.320614 9.307731 +SIMU 1976 3 21 24 0 9.353298 9.345859 +SIMU 1976 3 22 24 0 9.340808 9.337936 +SIMU 1976 3 23 24 0 9.289924 9.290966 +SIMU 1976 3 24 24 0 9.206184 9.210584 +SIMU 1976 3 25 24 0 9.094670 9.101867 +SIMU 1976 3 26 24 0 8.962339 31.67052 +SIMU 1976 3 27 24 0 8.832859 8.855320 +SIMU 1976 3 28 24 0 8.681973 18.34608 +SIMU 1976 3 29 24 0 8.545852 80.87876 +SIMU 1976 3 30 24 0 8.726319 124.2728 +SIMU 1976 3 31 24 0 8.954383 8.929785 +SIMU 1976 4 1 24 0 9.077915 9.055797 +SIMU 1976 4 2 24 0 9.125760 9.110368 +SIMU 1976 4 3 24 0 9.114639 9.105069 +SIMU 1976 4 4 24 0 9.056883 9.050970 +SIMU 1976 4 5 24 0 8.961176 8.955414 +SIMU 1976 4 6 24 0 8.832960 8.828364 +SIMU 1976 4 7 24 0 8.668804 8.666864 +SIMU 1976 4 8 24 0 8.470273 8.464606 +SIMU 1976 4 9 24 0 8.254838 8.257338 +SIMU 1976 4 10 24 0 8.023149 8.011706 +SIMU 1976 4 11 24 0 7.773345 19.12269 +SIMU 1976 4 12 24 0 7.515244 7.518793 +SIMU 1976 4 13 24 0 7.228179 7.223881 +SIMU 1976 4 14 24 0 6.940435 6.952693 +SIMU 1976 4 15 24 0 6.831132 55.63663 +SIMU 1976 4 16 24 0 6.734480 6.711138 +SIMU 1976 4 17 24 0 6.720130 325.9186 +SIMU 1976 4 18 24 0 7.225083 180.9549 +SIMU 1976 4 19 24 0 7.760850 7.699038 +SIMU 1976 4 20 24 0 8.150599 81.69958 +SIMU 1976 4 21 24 0 8.849834 18.02646 +SIMU 1976 4 22 24 0 9.515776 9.436546 +SIMU 1976 4 23 24 0 15.74128 74.15636 +SIMU 1976 4 24 24 0 20.78117 42.95824 +SIMU 1976 4 25 24 0 20.80364 21.50803 +SIMU 1976 4 26 24 0 19.42171 19.54881 +SIMU 1976 4 27 24 0 17.89425 17.99521 +SIMU 1976 4 28 24 0 16.68517 16.77532 +SIMU 1976 4 29 24 0 15.56366 15.63566 +SIMU 1976 4 30 24 0 14.59663 14.65335 +SIMU 1976 5 1 24 0 13.74321 13.79692 +SIMU 1976 5 2 24 0 15.23163 49.63367 +SIMU 1976 5 3 24 0 14.71212 14.76457 +SIMU 1976 5 4 24 0 13.82337 13.86915 +SIMU 1976 5 5 24 0 12.96066 13.00000 +SIMU 1976 5 6 24 0 12.15303 12.18444 +SIMU 1976 5 7 24 0 11.46644 11.49579 +SIMU 1976 5 8 24 0 10.81301 10.84046 +SIMU 1976 5 9 24 0 10.16247 10.17847 +SIMU 1976 5 10 24 0 9.972857 9.941750 +SIMU 1976 5 11 24 0 9.891415 9.866317 +SIMU 1976 5 12 24 0 9.762955 9.746064 +SIMU 1976 5 13 24 0 9.677894 70.44886 +SIMU 1976 5 14 24 0 9.652745 9.649599 +SIMU 1976 5 15 24 0 9.592699 20.91854 +SIMU 1976 5 16 24 0 6.950239 115.2386 +SIMU 1976 5 17 24 0 11.23013 10.83308 +SIMU 1976 5 18 24 0 10.84201 10.88450 +SIMU 1976 5 19 24 0 10.10124 10.13407 +SIMU 1976 5 20 24 0 9.402377 9.429980 +SIMU 1976 5 21 24 0 8.824148 8.848166 +SIMU 1976 5 22 24 0 8.706899 127.9437 +SIMU 1976 5 23 24 0 9.158713 41.48767 +SIMU 1976 5 24 24 0 8.744525 8.809204 +SIMU 1976 5 25 24 0 8.238327 8.269934 +SIMU 1976 5 26 24 0 7.745165 7.768769 +SIMU 1976 5 27 24 0 7.289109 7.308912 +SIMU 1976 5 28 24 0 7.042790 6.993178 +SIMU 1976 5 29 24 0 10.29947 9.986157 +SIMU 1976 5 30 24 0 9.576910 9.640110 +SIMU 1976 5 31 24 0 8.915795 8.963757 +SIMU 1976 6 1 24 0 8.356166 8.394520 +SIMU 1976 6 2 24 0 7.830907 7.860313 +SIMU 1976 6 3 24 0 7.317341 7.337018 +SIMU 1976 6 4 24 0 7.001420 6.979714 +SIMU 1976 6 5 24 0 6.963465 6.929173 +SIMU 1976 6 6 24 0 6.903966 6.876798 +SIMU 1976 6 7 24 0 6.821457 6.798852 +SIMU 1976 6 8 24 0 6.718878 6.697733 +SIMU 1976 6 9 24 0 6.596936 6.569315 +SIMU 1976 6 10 24 0 6.514006 104.2585 +SIMU 1976 6 11 24 0 6.471813 6.460088 +SIMU 1976 6 12 24 0 6.400855 29.84579 +SIMU 1976 6 13 24 0 6.385061 160.3763 +SIMU 1976 6 14 24 0 6.530354 26.87983 +SIMU 1976 6 15 24 0 6.638758 26.39072 +SIMU 1976 6 16 24 0 6.689775 6.659705 +SIMU 1976 6 17 24 0 6.696630 6.659134 +SIMU 1976 6 18 24 0 6.668063 17.99355 +SIMU 1976 6 19 24 0 6.613228 6.591832 +SIMU 1976 6 20 24 0 6.534174 6.507708 +SIMU 1976 6 21 24 0 6.434502 6.415373 +SIMU 1976 6 22 24 0 6.318646 6.298468 +SIMU 1976 6 23 24 0 6.187909 6.169038 +SIMU 1976 6 24 24 0 6.076590 29.41311 +SIMU 1976 6 25 24 0 6.020736 13.44458 +SIMU 1976 6 26 24 0 5.936152 20.28425 +SIMU 1976 6 27 24 0 5.868853 6.753101 +SIMU 1976 6 28 24 0 5.869579 5.839720 +SIMU 1976 6 29 24 0 5.884537 17.20980 +SIMU 1976 6 30 24 0 5.866933 5.845886 +SIMU 1976 7 1 24 0 5.823020 5.803921 +SIMU 1976 7 2 24 0 5.759427 5.754079 +SIMU 1976 7 3 24 0 5.677569 5.652538 +SIMU 1976 7 4 24 0 5.576257 5.563374 +SIMU 1976 7 5 24 0 5.463000 5.451096 +SIMU 1976 7 6 24 0 5.336662 5.317111 +SIMU 1976 7 7 24 0 5.193134 5.183722 +SIMU 1976 7 8 24 0 5.029192 5.014221 +SIMU 1976 7 9 24 0 4.856469 4.849349 +SIMU 1976 7 10 24 0 4.677545 4.662172 +SIMU 1976 7 11 24 0 4.492623 4.486209 +SIMU 1976 7 12 24 0 4.295463 4.290396 +SIMU 1976 7 13 24 0 4.080621 4.076970 +SIMU 1976 7 14 24 0 3.866693 3.859507 +SIMU 1976 7 15 24 0 3.656816 52.47431 +SIMU 1976 7 16 24 0 3.277588 3.677223 +SIMU 1976 7 17 24 0 2.590467 2.651126 +SIMU 1976 7 18 24 0 2.103326 2.139087 +SIMU 1976 7 19 24 0 1.766113 13.14555 +SIMU 1976 7 20 24 0 1.543120 24.25051 +SIMU 1976 7 21 24 0 1.414031 1.442276 +SIMU 1976 7 22 24 0 1.311040 1.323735 +SIMU 1976 7 23 24 0 1.221105 1.228090 +SIMU 1976 7 24 24 0 1.116907 1.118449 +SIMU 1976 7 25 24 0 0.9982151 1.003585 +SIMU 1976 7 26 24 0 0.8938456 36.33788 +SIMU 1976 7 27 24 0 0.8053325 21.40343 +SIMU 1976 7 28 24 0 0.9005256 167.9773 +SIMU 1976 7 29 24 0 0.9148608 0.9146647 +SIMU 1976 7 30 24 0 0.8806022 11.76961 +SIMU 1976 7 31 24 0 0.8438397 1.295588 +SIMU 1976 8 1 24 0 0.7890943 0.7919273 +SIMU 1976 8 2 24 0 0.7201992 0.7262144 +SIMU 1976 8 3 24 0 0.6435233 0.6522192 +SIMU 1976 8 4 24 0 0.5609179 0.5707234 +SIMU 1976 8 5 24 0 0.4756463 0.4873315 +SIMU 1976 8 6 24 0 0.3894908 0.4011723 +SIMU 1976 8 7 24 0 0.3043831 0.3180695 +SIMU 1976 8 8 24 0 0.2251702 0.2385858 +SIMU 1976 8 9 24 0 0.1414345 0.1565371 SIMU 1976 8 10 24 0 6.5113761E-02 7.8283310E-02 SIMU 1976 8 11 24 0 2.0805009E-02 2.5694320E-02 SIMU 1976 8 12 24 0 7.8668827E-03 1.0234714E-02 -SIMU 1976 8 13 24 0 2.5993612E-04 10.95018 -SIMU 1976 8 14 24 0 0.000000 11.72483 +SIMU 1976 8 13 24 0 2.5993612E-04 10.95018 +SIMU 1976 8 14 24 0 0.000000 11.72483 SIMU 1976 8 15 24 0 0.000000 7.8889243E-03 -SIMU 1976 8 16 24 0 0.000000 11.22915 -SIMU 1976 8 17 24 0 0.000000 74.45544 +SIMU 1976 8 16 24 0 0.000000 11.22915 +SIMU 1976 8 17 24 0 0.000000 74.45544 SIMU 1976 8 18 24 0 0.000000 9.3556540E-03 -SIMU 1976 8 19 24 0 0.000000 0.000000 -SIMU 1976 8 20 24 0 0.000000 0.000000 -SIMU 1976 8 21 24 0 0.000000 0.000000 -SIMU 1976 8 22 24 0 0.000000 0.000000 -SIMU 1976 8 23 24 0 0.000000 0.000000 -SIMU 1976 8 24 24 0 0.000000 0.000000 -SIMU 1976 8 25 24 0 0.000000 110.5957 -SIMU 1976 8 26 24 0 0.000000 11.77875 +SIMU 1976 8 19 24 0 0.000000 0.000000 +SIMU 1976 8 20 24 0 0.000000 0.000000 +SIMU 1976 8 21 24 0 0.000000 0.000000 +SIMU 1976 8 22 24 0 0.000000 0.000000 +SIMU 1976 8 23 24 0 0.000000 0.000000 +SIMU 1976 8 24 24 0 0.000000 0.000000 +SIMU 1976 8 25 24 0 0.000000 110.5957 +SIMU 1976 8 26 24 0 0.000000 11.77875 SIMU 1976 8 27 24 0 0.000000 1.6596535E-02 -SIMU 1976 8 28 24 0 0.000000 0.000000 -SIMU 1976 8 29 24 0 0.000000 0.000000 -SIMU 1976 8 30 24 0 0.000000 0.000000 -SIMU 1976 8 31 24 0 0.000000 0.000000 -SIMU 1976 9 1 24 0 0.000000 0.000000 -SIMU 1976 9 2 24 0 0.000000 0.000000 -SIMU 1976 9 3 24 0 0.000000 0.000000 -SIMU 1976 9 4 24 0 0.000000 0.000000 -SIMU 1976 9 5 24 0 0.000000 0.000000 -SIMU 1976 9 6 24 0 0.000000 0.000000 -SIMU 1976 9 7 24 0 0.000000 0.000000 -SIMU 1976 9 8 24 0 0.000000 0.000000 -SIMU 1976 9 9 24 0 0.000000 0.000000 -SIMU 1976 9 10 24 0 0.000000 0.000000 -SIMU 1976 9 11 24 0 0.000000 0.000000 -SIMU 1976 9 12 24 0 0.000000 0.000000 -SIMU 1976 9 13 24 0 0.000000 10.56202 -SIMU 1976 9 14 24 0 0.000000 0.7687209 +SIMU 1976 8 28 24 0 0.000000 0.000000 +SIMU 1976 8 29 24 0 0.000000 0.000000 +SIMU 1976 8 30 24 0 0.000000 0.000000 +SIMU 1976 8 31 24 0 0.000000 0.000000 +SIMU 1976 9 1 24 0 0.000000 0.000000 +SIMU 1976 9 2 24 0 0.000000 0.000000 +SIMU 1976 9 3 24 0 0.000000 0.000000 +SIMU 1976 9 4 24 0 0.000000 0.000000 +SIMU 1976 9 5 24 0 0.000000 0.000000 +SIMU 1976 9 6 24 0 0.000000 0.000000 +SIMU 1976 9 7 24 0 0.000000 0.000000 +SIMU 1976 9 8 24 0 0.000000 0.000000 +SIMU 1976 9 9 24 0 0.000000 0.000000 +SIMU 1976 9 10 24 0 0.000000 0.000000 +SIMU 1976 9 11 24 0 0.000000 0.000000 +SIMU 1976 9 12 24 0 0.000000 0.000000 +SIMU 1976 9 13 24 0 0.000000 10.56202 +SIMU 1976 9 14 24 0 0.000000 0.7687209 SIMU 1976 9 15 24 0 0.000000 1.1696724E-03 -SIMU 1976 9 16 24 0 0.000000 0.000000 -SIMU 1976 9 17 24 0 0.000000 0.000000 -SIMU 1976 9 18 24 0 0.000000 0.000000 -SIMU 1976 9 19 24 0 0.000000 112.1296 +SIMU 1976 9 16 24 0 0.000000 0.000000 +SIMU 1976 9 17 24 0 0.000000 0.000000 +SIMU 1976 9 18 24 0 0.000000 0.000000 +SIMU 1976 9 19 24 0 0.000000 112.1296 SIMU 1976 9 20 24 0 0.000000 5.3940173E-02 SIMU 1976 9 21 24 0 0.000000 3.0998995E-05 -SIMU 1976 9 22 24 0 0.000000 0.000000 -SIMU 1976 9 23 24 0 0.000000 0.000000 -SIMU 1976 9 24 24 0 0.000000 0.000000 -SIMU 1976 9 25 24 0 0.000000 0.000000 -SIMU 1976 9 26 24 0 0.000000 0.000000 -SIMU 1976 9 27 24 0 0.000000 0.000000 -SIMU 1976 9 28 24 0 0.000000 0.000000 -SIMU 1976 9 29 24 0 0.000000 0.000000 -SIMU 1976 9 30 24 0 0.000000 0.000000 -SIMU 1976 10 1 24 0 0.000000 0.000000 -SIMU 1976 10 2 24 0 0.000000 0.000000 -SIMU 1976 10 3 24 0 0.000000 0.000000 -SIMU 1976 10 4 24 0 0.000000 35.75327 -SIMU 1976 10 5 24 0 0.000000 0.1814079 +SIMU 1976 9 22 24 0 0.000000 0.000000 +SIMU 1976 9 23 24 0 0.000000 0.000000 +SIMU 1976 9 24 24 0 0.000000 0.000000 +SIMU 1976 9 25 24 0 0.000000 0.000000 +SIMU 1976 9 26 24 0 0.000000 0.000000 +SIMU 1976 9 27 24 0 0.000000 0.000000 +SIMU 1976 9 28 24 0 0.000000 0.000000 +SIMU 1976 9 29 24 0 0.000000 0.000000 +SIMU 1976 9 30 24 0 0.000000 0.000000 +SIMU 1976 10 1 24 0 0.000000 0.000000 +SIMU 1976 10 2 24 0 0.000000 0.000000 +SIMU 1976 10 3 24 0 0.000000 0.000000 +SIMU 1976 10 4 24 0 0.000000 35.75327 +SIMU 1976 10 5 24 0 0.000000 0.1814079 SIMU 1976 10 6 24 0 0.000000 2.9523854E-04 -SIMU 1976 10 7 24 0 0.000000 0.000000 -SIMU 1976 10 8 24 0 0.000000 0.000000 -SIMU 1976 10 9 24 0 0.000000 0.000000 -SIMU 1976 10 10 24 0 0.000000 0.000000 -SIMU 1976 10 11 24 0 0.000000 0.000000 -SIMU 1976 10 12 24 0 0.000000 0.000000 -SIMU 1976 10 13 24 0 0.000000 0.000000 -SIMU 1976 10 14 24 0 0.000000 0.000000 -SIMU 1976 10 15 24 0 0.000000 0.000000 -SIMU 1976 10 16 24 0 0.000000 0.000000 -SIMU 1976 10 17 24 0 0.000000 0.000000 -SIMU 1976 10 18 24 0 0.000000 10.13720 -SIMU 1976 10 19 24 0 0.000000 13.77539 +SIMU 1976 10 7 24 0 0.000000 0.000000 +SIMU 1976 10 8 24 0 0.000000 0.000000 +SIMU 1976 10 9 24 0 0.000000 0.000000 +SIMU 1976 10 10 24 0 0.000000 0.000000 +SIMU 1976 10 11 24 0 0.000000 0.000000 +SIMU 1976 10 12 24 0 0.000000 0.000000 +SIMU 1976 10 13 24 0 0.000000 0.000000 +SIMU 1976 10 14 24 0 0.000000 0.000000 +SIMU 1976 10 15 24 0 0.000000 0.000000 +SIMU 1976 10 16 24 0 0.000000 0.000000 +SIMU 1976 10 17 24 0 0.000000 0.000000 +SIMU 1976 10 18 24 0 0.000000 10.13720 +SIMU 1976 10 19 24 0 0.000000 13.77539 SIMU 1976 10 20 24 0 0.000000 3.0880500E-02 SIMU 1976 10 21 24 0 0.000000 2.7460439E-05 -SIMU 1976 10 22 24 0 0.000000 0.000000 -SIMU 1976 10 23 24 0 0.000000 69.60589 -SIMU 1976 10 24 24 0 0.000000 29.86705 +SIMU 1976 10 22 24 0 0.000000 0.000000 +SIMU 1976 10 23 24 0 0.000000 69.60589 +SIMU 1976 10 24 24 0 0.000000 29.86705 SIMU 1976 10 25 24 0 0.000000 1.5093456E-02 SIMU 1976 10 26 24 0 0.000000 2.0583424E-05 -SIMU 1976 10 27 24 0 0.000000 0.000000 -SIMU 1976 10 28 24 0 0.000000 0.000000 -SIMU 1976 10 29 24 0 0.000000 0.000000 -SIMU 1976 10 30 24 0 0.000000 22.57912 -SIMU 1976 10 31 24 0 0.000000 0.1091672 +SIMU 1976 10 27 24 0 0.000000 0.000000 +SIMU 1976 10 28 24 0 0.000000 0.000000 +SIMU 1976 10 29 24 0 0.000000 0.000000 +SIMU 1976 10 30 24 0 0.000000 22.57912 +SIMU 1976 10 31 24 0 0.000000 0.1091672 SIMU 1976 11 1 24 0 0.000000 2.2634648E-04 -SIMU 1976 11 2 24 0 0.000000 0.000000 -SIMU 1976 11 3 24 0 0.000000 0.000000 -SIMU 1976 11 4 24 0 0.000000 0.000000 -SIMU 1976 11 5 24 0 0.000000 0.000000 -SIMU 1976 11 6 24 0 0.000000 0.000000 -SIMU 1976 11 7 24 0 0.000000 0.000000 -SIMU 1976 11 8 24 0 0.000000 0.000000 -SIMU 1976 11 9 24 0 0.000000 0.000000 -SIMU 1976 11 10 24 0 0.000000 0.000000 -SIMU 1976 11 11 24 0 0.000000 0.000000 -SIMU 1976 11 12 24 0 0.000000 0.000000 -SIMU 1976 11 13 24 0 0.000000 0.000000 -SIMU 1976 11 14 24 0 0.000000 0.000000 -SIMU 1976 11 15 24 0 0.000000 0.000000 -SIMU 1976 11 16 24 0 0.000000 0.000000 -SIMU 1976 11 17 24 0 0.000000 0.000000 -SIMU 1976 11 18 24 0 0.000000 0.000000 -SIMU 1976 11 19 24 0 0.000000 0.000000 -SIMU 1976 11 20 24 0 0.000000 0.000000 -SIMU 1976 11 21 24 0 0.000000 0.000000 -SIMU 1976 11 22 24 0 0.000000 0.000000 -SIMU 1976 11 23 24 0 0.000000 0.000000 -SIMU 1976 11 24 24 0 0.000000 0.000000 -SIMU 1976 11 25 24 0 0.000000 0.000000 -SIMU 1976 11 26 24 0 0.000000 0.000000 -SIMU 1976 11 27 24 0 0.000000 0.000000 -SIMU 1976 11 28 24 0 0.000000 0.000000 -SIMU 1976 11 29 24 0 0.000000 0.000000 -SIMU 1976 11 30 24 0 0.000000 0.000000 -SIMU 1976 12 1 24 0 0.000000 0.000000 -SIMU 1976 12 2 24 0 0.000000 0.000000 -SIMU 1976 12 3 24 0 0.000000 0.000000 -SIMU 1976 12 4 24 0 0.000000 0.000000 -SIMU 1976 12 5 24 0 0.000000 0.000000 -SIMU 1976 12 6 24 0 0.000000 0.000000 -SIMU 1976 12 7 24 0 0.000000 0.000000 -SIMU 1976 12 8 24 0 0.000000 0.000000 -SIMU 1976 12 9 24 0 0.000000 0.000000 -SIMU 1976 12 10 24 0 0.000000 0.000000 -SIMU 1976 12 11 24 0 0.000000 0.000000 -SIMU 1976 12 12 24 0 0.000000 0.000000 -SIMU 1976 12 13 24 0 0.000000 0.000000 -SIMU 1976 12 14 24 0 0.000000 8.038989 -SIMU 1976 12 15 24 0 0.000000 0.1836836 -SIMU 1976 12 16 24 0 0.000000 15.20456 -SIMU 1976 12 17 24 0 0.000000 11.50979 -SIMU 1976 12 18 24 0 0.000000 4.362786 -SIMU 1976 12 19 24 0 0.000000 0.1516617 +SIMU 1976 11 2 24 0 0.000000 0.000000 +SIMU 1976 11 3 24 0 0.000000 0.000000 +SIMU 1976 11 4 24 0 0.000000 0.000000 +SIMU 1976 11 5 24 0 0.000000 0.000000 +SIMU 1976 11 6 24 0 0.000000 0.000000 +SIMU 1976 11 7 24 0 0.000000 0.000000 +SIMU 1976 11 8 24 0 0.000000 0.000000 +SIMU 1976 11 9 24 0 0.000000 0.000000 +SIMU 1976 11 10 24 0 0.000000 0.000000 +SIMU 1976 11 11 24 0 0.000000 0.000000 +SIMU 1976 11 12 24 0 0.000000 0.000000 +SIMU 1976 11 13 24 0 0.000000 0.000000 +SIMU 1976 11 14 24 0 0.000000 0.000000 +SIMU 1976 11 15 24 0 0.000000 0.000000 +SIMU 1976 11 16 24 0 0.000000 0.000000 +SIMU 1976 11 17 24 0 0.000000 0.000000 +SIMU 1976 11 18 24 0 0.000000 0.000000 +SIMU 1976 11 19 24 0 0.000000 0.000000 +SIMU 1976 11 20 24 0 0.000000 0.000000 +SIMU 1976 11 21 24 0 0.000000 0.000000 +SIMU 1976 11 22 24 0 0.000000 0.000000 +SIMU 1976 11 23 24 0 0.000000 0.000000 +SIMU 1976 11 24 24 0 0.000000 0.000000 +SIMU 1976 11 25 24 0 0.000000 0.000000 +SIMU 1976 11 26 24 0 0.000000 0.000000 +SIMU 1976 11 27 24 0 0.000000 0.000000 +SIMU 1976 11 28 24 0 0.000000 0.000000 +SIMU 1976 11 29 24 0 0.000000 0.000000 +SIMU 1976 11 30 24 0 0.000000 0.000000 +SIMU 1976 12 1 24 0 0.000000 0.000000 +SIMU 1976 12 2 24 0 0.000000 0.000000 +SIMU 1976 12 3 24 0 0.000000 0.000000 +SIMU 1976 12 4 24 0 0.000000 0.000000 +SIMU 1976 12 5 24 0 0.000000 0.000000 +SIMU 1976 12 6 24 0 0.000000 0.000000 +SIMU 1976 12 7 24 0 0.000000 0.000000 +SIMU 1976 12 8 24 0 0.000000 0.000000 +SIMU 1976 12 9 24 0 0.000000 0.000000 +SIMU 1976 12 10 24 0 0.000000 0.000000 +SIMU 1976 12 11 24 0 0.000000 0.000000 +SIMU 1976 12 12 24 0 0.000000 0.000000 +SIMU 1976 12 13 24 0 0.000000 0.000000 +SIMU 1976 12 14 24 0 0.000000 8.038989 +SIMU 1976 12 15 24 0 0.000000 0.1836836 +SIMU 1976 12 16 24 0 0.000000 15.20456 +SIMU 1976 12 17 24 0 0.000000 11.50979 +SIMU 1976 12 18 24 0 0.000000 4.362786 +SIMU 1976 12 19 24 0 0.000000 0.1516617 SIMU 1976 12 20 24 0 0.000000 3.4400655E-04 SIMU 1976 12 21 24 0 0.000000 1.4007871E-07 -SIMU 1976 12 22 24 0 0.000000 0.000000 -SIMU 1976 12 23 24 0 0.000000 0.000000 -SIMU 1976 12 24 24 0 0.000000 0.000000 -SIMU 1976 12 25 24 0 0.000000 0.000000 -SIMU 1976 12 26 24 0 0.000000 0.000000 -SIMU 1976 12 27 24 0 0.000000 0.000000 -SIMU 1976 12 28 24 0 0.000000 0.000000 -SIMU 1976 12 29 24 0 0.000000 0.000000 -SIMU 1976 12 30 24 0 0.000000 0.000000 -SIMU 1976 12 31 24 0 0.000000 0.000000 +SIMU 1976 12 22 24 0 0.000000 0.000000 +SIMU 1976 12 23 24 0 0.000000 0.000000 +SIMU 1976 12 24 24 0 0.000000 0.000000 +SIMU 1976 12 25 24 0 0.000000 0.000000 +SIMU 1976 12 26 24 0 0.000000 0.000000 +SIMU 1976 12 27 24 0 0.000000 0.000000 +SIMU 1976 12 28 24 0 0.000000 0.000000 +SIMU 1976 12 29 24 0 0.000000 0.000000 +SIMU 1976 12 30 24 0 0.000000 0.000000 +SIMU 1976 12 31 24 0 0.000000 0.000000 diff --git a/tests/test10/HSPFresults/test10.p95 b/tests/test10/HSPFresults/test10.p95 index 937eaf10..b1381e41 100644 --- a/tests/test10/HSPFresults/test10.p95 +++ b/tests/test10/HSPFresults/test10.p95 @@ -2,10 +2,10 @@ SIMU HSPF FILE FOR DRIVING SEPARATE PLOT PROGRAM SIMU Time interval: 360 mins Last month in printout year: 9 SIMU No. of curves plotted: Point-valued: 3 Mean-valued: 1 Total 4 SIMU Label flag: 0 Pivl: 6 Idelt: 60 -SIMU Plot title: SIMULATED VALS RELATED TO TEMP&PH,RCH 4 -SIMU Y-axis label: +SIMU Plot title: SIMULATED VALS RELATED TO TEMP&PH,RCH 4 +SIMU Y-axis label: SIMU Scale info: Ymin: 0.0000 Threshold:-0.10000E+31 -SIMU Ymax: 150.00 +SIMU Ymax: 150.00 SIMU Time: 20.000 intervals/inch SIMU Data for each curve (Point-valued first, then mean-valued): SIMU Label LINTYP INTEQ COLCOD TRAN TRANCOD @@ -24,245 +24,245 @@ SIMU SIMU Date/time Values SIMU SIMU 1975 12 31 24 0 0.000000 60.00000 8.500000 -1.0000000E+30 -SIMU 1976 1 1 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 1 1 12 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 1 1 18 0 2.7871249E-02 32.07207 13.12421 -168542.4 -SIMU 1976 1 1 24 0 5.4797929E-02 32.07207 13.14930 -866463.3 -SIMU 1976 1 2 6 0 7.2372779E-02 32.07207 13.14771 -1298815. -SIMU 1976 1 2 12 0 8.3345100E-02 32.07207 13.14380 -1348846. -SIMU 1976 1 2 18 0 9.1288775E-02 32.07207 13.14029 -1273172. -SIMU 1976 1 2 24 0 9.7315378E-02 32.07207 13.13692 -978386.6 -SIMU 1976 1 3 6 0 0.1019777 32.07207 13.13352 -406549.0 -SIMU 1976 1 3 12 0 0.1056267 32.07207 13.13008 -50.58556 -SIMU 1976 1 3 18 0 0.1086149 32.07207 13.12659 -44.74771 -SIMU 1976 1 3 24 0 0.1110907 32.07207 13.12318 -43.72315 -SIMU 1976 1 4 6 0 0.1130495 32.07207 13.11980 -41.17428 -SIMU 1976 1 4 12 0 0.1145906 32.07207 13.11646 -164.0769 -SIMU 1976 1 4 18 0 0.1157974 32.07207 13.11312 218310.1 -SIMU 1976 1 4 24 0 0.1167338 32.07207 13.10978 -34.20255 -SIMU 1976 1 5 6 0 0.1174458 32.07207 13.10645 -32.68895 -SIMU 1976 1 5 12 0 0.1180093 32.07207 13.10286 -512.9301 -SIMU 1976 1 5 18 0 0.1226091 32.07207 13.09929 -94580.67 -SIMU 1976 1 5 24 0 0.1256065 32.07207 13.09536 -4049.124 -SIMU 1976 1 6 6 0 0.1276617 32.07207 13.09135 -48.71730 -SIMU 1976 1 6 12 0 0.1292443 32.07207 13.08745 -43.89406 -SIMU 1976 1 6 18 0 0.1309368 32.07207 13.08241 -4313.043 -SIMU 1976 1 6 24 0 0.1324759 32.07207 13.07966 -65.71773 -SIMU 1976 1 7 6 0 0.1330767 32.07207 13.07556 -38.41756 -SIMU 1976 1 7 12 0 0.1334491 32.07207 13.07152 -34.44584 -SIMU 1976 1 7 18 0 0.1362029 32.07207 13.06711 -18.58733 -SIMU 1976 1 7 24 0 0.1381927 32.07207 13.06270 -55.87582 -SIMU 1976 1 8 6 0 0.1395876 32.07207 13.05830 -46.68633 -SIMU 1976 1 8 12 0 0.1406472 32.07207 13.05400 -42.13677 -SIMU 1976 1 8 18 0 0.1444847 32.07207 13.04926 -24.82368 -SIMU 1976 1 8 24 0 0.1471318 32.07207 13.04446 -69.31850 -SIMU 1976 1 9 6 0 0.1490162 32.07207 13.03963 -55.33128 -SIMU 1976 1 9 12 0 0.1504642 32.07207 13.03486 -50.43088 -SIMU 1976 1 9 18 0 0.1532875 32.07207 13.02972 -6713.310 -SIMU 1976 1 9 24 0 0.1556391 32.07207 13.02467 -64.31012 -SIMU 1976 1 10 6 0 0.1574081 32.07207 13.01952 -56.37457 -SIMU 1976 1 10 12 0 0.1587713 32.07207 13.01439 -51.93793 -SIMU 1976 1 10 18 0 0.1599186 32.07207 13.00919 -45.04348 -SIMU 1976 1 10 24 0 0.1609593 32.07207 13.00405 -48.42181 -SIMU 1976 1 11 6 0 0.1617409 32.07207 12.99886 -46.07314 -SIMU 1976 1 11 12 0 0.1628120 36.08153 12.89848 1445355. -SIMU 1976 1 11 18 0 0.1669627 38.73153 12.83231 5886758. -SIMU 1976 1 11 24 0 0.1698543 32.07207 12.98162 -1047912. -SIMU 1976 1 12 6 0 0.1720083 32.07207 12.96951 -66.62341 -SIMU 1976 1 12 12 0 0.1747179 36.53827 12.85713 1896662. -SIMU 1976 1 12 18 0 0.1829739 32.07207 12.95561 36683.13 -SIMU 1976 1 12 24 0 0.1886343 32.07207 12.94796 -823506.1 -SIMU 1976 1 13 6 0 0.1927597 32.07207 12.94042 -79006.93 -SIMU 1976 1 13 12 0 0.1969348 36.48017 12.82878 2593923. -SIMU 1976 1 13 18 0 0.2041864 32.07207 12.92422 186116.2 -SIMU 1976 1 13 24 0 0.2097269 32.07207 12.91546 -355832.4 -SIMU 1976 1 14 6 0 0.2139658 32.07207 12.90677 -115.5082 -SIMU 1976 1 14 12 0 0.2172513 39.38366 12.72847 5287844. -SIMU 1976 1 14 18 0 0.2203937 32.07207 12.88952 2920086. -SIMU 1976 1 14 24 0 0.2232637 32.07207 12.88039 -288367.6 -SIMU 1976 1 15 6 0 0.2254567 32.07207 12.87142 -89.16023 -SIMU 1976 1 15 12 0 0.2271104 32.07207 12.86245 -126683.8 -SIMU 1976 1 15 18 0 0.2284456 32.07207 12.85343 -1664198. -SIMU 1976 1 15 24 0 0.2296095 32.07207 12.84438 -487631.0 -SIMU 1976 1 16 6 0 0.2304322 32.07207 12.83529 -68.80440 -SIMU 1976 1 16 12 0 0.2309750 32.07207 12.82617 -63.18703 -SIMU 1976 1 16 18 0 0.2313024 32.07207 12.81703 -59.65810 -SIMU 1976 1 16 24 0 0.2314551 32.07207 12.80786 -56.80843 -SIMU 1976 1 17 6 0 0.2314396 32.07207 12.79866 -54.78199 -SIMU 1976 1 17 12 0 0.2312956 36.13836 12.69435 3158352. -SIMU 1976 1 17 18 0 0.2310240 32.07207 12.78038 2022261. -SIMU 1976 1 17 24 0 0.2306781 32.07207 12.77090 -48.12863 -SIMU 1976 1 18 6 0 0.2302599 32.07207 12.76156 -47.74211 -SIMU 1976 1 18 12 0 0.2297932 33.92912 12.70849 1226811. -SIMU 1976 1 18 18 0 0.2292996 32.07207 12.74285 811783.7 -SIMU 1976 1 18 24 0 0.2287853 32.07207 12.73329 -45.35953 -SIMU 1976 1 19 6 0 0.2282310 32.07207 12.72377 -45.37050 -SIMU 1976 1 19 12 0 0.2276534 32.07207 12.71419 -43.59500 -SIMU 1976 1 19 18 0 0.2270690 32.07207 12.70455 -329113.2 -SIMU 1976 1 19 24 0 0.2264805 32.07207 12.69486 -44.02403 -SIMU 1976 1 20 6 0 0.2258669 32.07207 12.68510 -44.22742 -SIMU 1976 1 20 12 0 0.2252418 32.85717 12.65678 490087.2 -SIMU 1976 1 20 18 0 0.2246194 32.07207 12.66546 282703.3 -SIMU 1976 1 20 24 0 0.2240007 32.07207 12.65544 -42.21475 -SIMU 1976 1 21 6 0 0.2233642 32.07207 12.64540 -42.72580 -SIMU 1976 1 21 12 0 0.2227219 34.02740 12.58944 1458747. -SIMU 1976 1 21 18 0 0.2220865 32.07207 12.62516 439675.1 -SIMU 1976 1 21 24 0 0.2214584 32.07207 12.61481 -41.47422 -SIMU 1976 1 22 6 0 0.2208163 32.07207 12.60444 -42.27903 -SIMU 1976 1 22 12 0 0.2201712 39.51364 12.42243 5757780. -SIMU 1976 1 22 18 0 0.2195348 32.07207 12.58398 2397629. -SIMU 1976 1 22 24 0 0.2189073 32.07207 12.57282 -238416.0 -SIMU 1976 1 23 6 0 0.2182677 32.07207 12.56203 -41.71608 -SIMU 1976 1 23 12 0 0.2176265 38.66016 12.39909 4659965. -SIMU 1976 1 23 18 0 0.2176039 32.07207 12.54058 872292.1 -SIMU 1976 1 23 24 0 0.2179499 32.07207 12.52875 -1382043. -SIMU 1976 1 24 6 0 0.2181354 32.07207 12.51719 -138291.3 -SIMU 1976 1 24 12 0 0.2181784 35.62005 12.42304 2422957. -SIMU 1976 1 24 18 0 0.2181131 32.07207 12.49404 186504.8 -SIMU 1976 1 24 24 0 0.2179593 32.07207 12.48181 -750856.4 -SIMU 1976 1 25 6 0 0.2177125 32.07207 12.46969 -39238.22 -SIMU 1976 1 25 12 0 0.2178078 32.07207 12.45734 -31.30094 -SIMU 1976 1 25 18 0 0.2189079 32.07207 12.44379 65.19908 -SIMU 1976 1 25 24 0 0.2191160 32.07207 12.43171 -101.9599 -SIMU 1976 1 26 6 0 0.2183461 32.07207 12.41873 -44.22515 -SIMU 1976 1 26 12 0 0.2175145 32.96391 12.38487 523991.5 -SIMU 1976 1 26 18 0 0.2167164 32.07207 12.39252 240245.0 -SIMU 1976 1 26 24 0 0.2159552 32.07207 12.37903 -38.06538 -SIMU 1976 1 27 6 0 0.2152075 32.07207 12.36536 -39.18702 -SIMU 1976 1 27 12 0 0.2144789 42.41420 12.11780 7584524. -SIMU 1976 1 27 18 0 0.2137764 33.09472 12.31527 5716212. -SIMU 1976 1 27 24 0 0.2130969 32.07207 12.32302 -347743.6 -SIMU 1976 1 28 6 0 0.2124194 32.07207 12.30821 -39.51871 -SIMU 1976 1 28 12 0 0.2117509 36.80027 12.18505 3034941. -SIMU 1976 1 28 18 0 0.2111823 32.07207 12.27864 526633.1 -SIMU 1976 1 28 24 0 0.2110445 32.07207 12.26224 -836923.7 -SIMU 1976 1 29 6 0 0.2108856 32.07207 12.24608 -46.83461 -SIMU 1976 1 29 12 0 0.2107723 39.45267 12.06288 5128743. -SIMU 1976 1 29 18 0 0.2136457 32.07207 12.21344 1625268. -SIMU 1976 1 29 24 0 0.2158277 32.07207 12.19417 -980804.1 -SIMU 1976 1 30 6 0 0.2174203 32.07207 12.17550 -40169.84 -SIMU 1976 1 30 12 0 0.2186069 32.75619 12.14079 410363.7 -SIMU 1976 1 30 18 0 0.2194803 32.07207 12.13709 887871.6 -SIMU 1976 1 30 24 0 0.2200985 32.07207 12.11667 -60.85453 -SIMU 1976 1 31 6 0 0.2204858 32.07207 12.09592 -58.12335 -SIMU 1976 1 31 12 0 0.2206918 34.79879 12.01346 1574497. -SIMU 1976 1 31 18 0 0.2207596 32.07207 12.05349 279186.7 -SIMU 1976 1 31 24 0 0.2207145 32.07207 12.02994 -884878.3 -SIMU 1976 2 1 6 0 0.2204997 32.07207 12.00572 -27682.40 -SIMU 1976 2 1 12 0 0.2202164 32.07207 11.97993 -80468.14 -SIMU 1976 2 1 18 0 0.2204060 32.07207 11.95304 -362490.6 -SIMU 1976 2 1 24 0 0.2208953 32.07207 11.92501 -81.96701 -SIMU 1976 2 2 6 0 0.2212104 32.07207 11.89670 -81.21722 -SIMU 1976 2 2 12 0 0.2213626 34.33297 11.81999 1372341. -SIMU 1976 2 2 18 0 0.2213862 32.07207 11.83941 1860878. -SIMU 1976 2 2 24 0 0.2213043 32.07207 11.80733 -74.82951 -SIMU 1976 2 3 6 0 0.2211185 32.07207 11.77509 -73.58753 -SIMU 1976 2 3 12 0 0.2208547 32.79903 11.72706 422251.6 -SIMU 1976 2 3 18 0 0.2205347 32.07207 11.70737 -797257.6 -SIMU 1976 2 3 24 0 0.2201690 32.07207 11.67122 -248466.2 -SIMU 1976 2 4 6 0 0.2197463 32.07207 11.63404 -69.44428 -SIMU 1976 2 4 12 0 0.2192844 32.07207 11.59572 -68.34030 -SIMU 1976 2 4 18 0 0.2188009 32.07207 11.55636 -67.63618 -SIMU 1976 2 4 24 0 0.2183005 32.07207 11.51609 -67.33067 -SIMU 1976 2 5 6 0 0.2177679 32.07207 11.47510 -67.21605 -SIMU 1976 2 5 12 0 0.2172165 32.07207 11.43361 -66.27481 -SIMU 1976 2 5 18 0 0.2166597 32.07207 11.39185 -65.93702 -SIMU 1976 2 5 24 0 0.2160998 32.07207 11.35006 -65.59772 -SIMU 1976 2 6 6 0 0.2155196 32.07207 11.30845 -66.44243 -SIMU 1976 2 6 12 0 0.2149303 39.42032 11.17035 5221518. -SIMU 1976 2 6 18 0 0.2143433 32.07207 11.23109 3387926. -SIMU 1976 2 6 24 0 0.2137594 32.07207 11.18698 -64.19181 -SIMU 1976 2 7 6 0 0.2131614 32.07207 11.14757 -65.00223 -SIMU 1976 2 7 12 0 0.2125588 39.36724 11.02642 5056998. -SIMU 1976 2 7 18 0 0.2119620 32.07207 11.07650 2668830. -SIMU 1976 2 7 24 0 0.2113712 32.07207 11.03579 -467643.1 -SIMU 1976 2 8 6 0 0.2107693 32.07207 10.99985 -63.93411 +SIMU 1976 1 1 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 +SIMU 1976 1 1 12 0 0.000000 32.07207 -1.0000000E+30 0.000000 +SIMU 1976 1 1 18 0 2.7871249E-02 32.07207 13.12421 -168542.4 +SIMU 1976 1 1 24 0 5.4797929E-02 32.07207 13.14930 -866463.3 +SIMU 1976 1 2 6 0 7.2372779E-02 32.07207 13.14771 -1298815. +SIMU 1976 1 2 12 0 8.3345100E-02 32.07207 13.14380 -1348846. +SIMU 1976 1 2 18 0 9.1288775E-02 32.07207 13.14029 -1273172. +SIMU 1976 1 2 24 0 9.7315378E-02 32.07207 13.13692 -978386.6 +SIMU 1976 1 3 6 0 0.1019777 32.07207 13.13352 -406549.0 +SIMU 1976 1 3 12 0 0.1056267 32.07207 13.13008 -50.58556 +SIMU 1976 1 3 18 0 0.1086149 32.07207 13.12659 -44.74771 +SIMU 1976 1 3 24 0 0.1110907 32.07207 13.12318 -43.72315 +SIMU 1976 1 4 6 0 0.1130495 32.07207 13.11980 -41.17428 +SIMU 1976 1 4 12 0 0.1145906 32.07207 13.11646 -164.0769 +SIMU 1976 1 4 18 0 0.1157974 32.07207 13.11312 218310.1 +SIMU 1976 1 4 24 0 0.1167338 32.07207 13.10978 -34.20255 +SIMU 1976 1 5 6 0 0.1174458 32.07207 13.10645 -32.68895 +SIMU 1976 1 5 12 0 0.1180093 32.07207 13.10286 -512.9301 +SIMU 1976 1 5 18 0 0.1226091 32.07207 13.09929 -94580.67 +SIMU 1976 1 5 24 0 0.1256065 32.07207 13.09536 -4049.124 +SIMU 1976 1 6 6 0 0.1276617 32.07207 13.09135 -48.71730 +SIMU 1976 1 6 12 0 0.1292443 32.07207 13.08745 -43.89406 +SIMU 1976 1 6 18 0 0.1309368 32.07207 13.08241 -4313.043 +SIMU 1976 1 6 24 0 0.1324759 32.07207 13.07966 -65.71773 +SIMU 1976 1 7 6 0 0.1330767 32.07207 13.07556 -38.41756 +SIMU 1976 1 7 12 0 0.1334491 32.07207 13.07152 -34.44584 +SIMU 1976 1 7 18 0 0.1362029 32.07207 13.06711 -18.58733 +SIMU 1976 1 7 24 0 0.1381927 32.07207 13.06270 -55.87582 +SIMU 1976 1 8 6 0 0.1395876 32.07207 13.05830 -46.68633 +SIMU 1976 1 8 12 0 0.1406472 32.07207 13.05400 -42.13677 +SIMU 1976 1 8 18 0 0.1444847 32.07207 13.04926 -24.82368 +SIMU 1976 1 8 24 0 0.1471318 32.07207 13.04446 -69.31850 +SIMU 1976 1 9 6 0 0.1490162 32.07207 13.03963 -55.33128 +SIMU 1976 1 9 12 0 0.1504642 32.07207 13.03486 -50.43088 +SIMU 1976 1 9 18 0 0.1532875 32.07207 13.02972 -6713.310 +SIMU 1976 1 9 24 0 0.1556391 32.07207 13.02467 -64.31012 +SIMU 1976 1 10 6 0 0.1574081 32.07207 13.01952 -56.37457 +SIMU 1976 1 10 12 0 0.1587713 32.07207 13.01439 -51.93793 +SIMU 1976 1 10 18 0 0.1599186 32.07207 13.00919 -45.04348 +SIMU 1976 1 10 24 0 0.1609593 32.07207 13.00405 -48.42181 +SIMU 1976 1 11 6 0 0.1617409 32.07207 12.99886 -46.07314 +SIMU 1976 1 11 12 0 0.1628120 36.08153 12.89848 1445355. +SIMU 1976 1 11 18 0 0.1669627 38.73153 12.83231 5886758. +SIMU 1976 1 11 24 0 0.1698543 32.07207 12.98162 -1047912. +SIMU 1976 1 12 6 0 0.1720083 32.07207 12.96951 -66.62341 +SIMU 1976 1 12 12 0 0.1747179 36.53827 12.85713 1896662. +SIMU 1976 1 12 18 0 0.1829739 32.07207 12.95561 36683.13 +SIMU 1976 1 12 24 0 0.1886343 32.07207 12.94796 -823506.1 +SIMU 1976 1 13 6 0 0.1927597 32.07207 12.94042 -79006.93 +SIMU 1976 1 13 12 0 0.1969348 36.48017 12.82878 2593923. +SIMU 1976 1 13 18 0 0.2041864 32.07207 12.92422 186116.2 +SIMU 1976 1 13 24 0 0.2097269 32.07207 12.91546 -355832.4 +SIMU 1976 1 14 6 0 0.2139658 32.07207 12.90677 -115.5082 +SIMU 1976 1 14 12 0 0.2172513 39.38366 12.72847 5287844. +SIMU 1976 1 14 18 0 0.2203937 32.07207 12.88952 2920086. +SIMU 1976 1 14 24 0 0.2232637 32.07207 12.88039 -288367.6 +SIMU 1976 1 15 6 0 0.2254567 32.07207 12.87142 -89.16023 +SIMU 1976 1 15 12 0 0.2271104 32.07207 12.86245 -126683.8 +SIMU 1976 1 15 18 0 0.2284456 32.07207 12.85343 -1664198. +SIMU 1976 1 15 24 0 0.2296095 32.07207 12.84438 -487631.0 +SIMU 1976 1 16 6 0 0.2304322 32.07207 12.83529 -68.80440 +SIMU 1976 1 16 12 0 0.2309750 32.07207 12.82617 -63.18703 +SIMU 1976 1 16 18 0 0.2313024 32.07207 12.81703 -59.65810 +SIMU 1976 1 16 24 0 0.2314551 32.07207 12.80786 -56.80843 +SIMU 1976 1 17 6 0 0.2314396 32.07207 12.79866 -54.78199 +SIMU 1976 1 17 12 0 0.2312956 36.13836 12.69435 3158352. +SIMU 1976 1 17 18 0 0.2310240 32.07207 12.78038 2022261. +SIMU 1976 1 17 24 0 0.2306781 32.07207 12.77090 -48.12863 +SIMU 1976 1 18 6 0 0.2302599 32.07207 12.76156 -47.74211 +SIMU 1976 1 18 12 0 0.2297932 33.92912 12.70849 1226811. +SIMU 1976 1 18 18 0 0.2292996 32.07207 12.74285 811783.7 +SIMU 1976 1 18 24 0 0.2287853 32.07207 12.73329 -45.35953 +SIMU 1976 1 19 6 0 0.2282310 32.07207 12.72377 -45.37050 +SIMU 1976 1 19 12 0 0.2276534 32.07207 12.71419 -43.59500 +SIMU 1976 1 19 18 0 0.2270690 32.07207 12.70455 -329113.2 +SIMU 1976 1 19 24 0 0.2264805 32.07207 12.69486 -44.02403 +SIMU 1976 1 20 6 0 0.2258669 32.07207 12.68510 -44.22742 +SIMU 1976 1 20 12 0 0.2252418 32.85717 12.65678 490087.2 +SIMU 1976 1 20 18 0 0.2246194 32.07207 12.66546 282703.3 +SIMU 1976 1 20 24 0 0.2240007 32.07207 12.65544 -42.21475 +SIMU 1976 1 21 6 0 0.2233642 32.07207 12.64540 -42.72580 +SIMU 1976 1 21 12 0 0.2227219 34.02740 12.58944 1458747. +SIMU 1976 1 21 18 0 0.2220865 32.07207 12.62516 439675.1 +SIMU 1976 1 21 24 0 0.2214584 32.07207 12.61481 -41.47422 +SIMU 1976 1 22 6 0 0.2208163 32.07207 12.60444 -42.27903 +SIMU 1976 1 22 12 0 0.2201712 39.51364 12.42243 5757780. +SIMU 1976 1 22 18 0 0.2195348 32.07207 12.58398 2397629. +SIMU 1976 1 22 24 0 0.2189073 32.07207 12.57282 -238416.0 +SIMU 1976 1 23 6 0 0.2182677 32.07207 12.56203 -41.71608 +SIMU 1976 1 23 12 0 0.2176265 38.66016 12.39909 4659965. +SIMU 1976 1 23 18 0 0.2176039 32.07207 12.54058 872292.1 +SIMU 1976 1 23 24 0 0.2179499 32.07207 12.52875 -1382043. +SIMU 1976 1 24 6 0 0.2181354 32.07207 12.51719 -138291.3 +SIMU 1976 1 24 12 0 0.2181784 35.62005 12.42304 2422957. +SIMU 1976 1 24 18 0 0.2181131 32.07207 12.49404 186504.8 +SIMU 1976 1 24 24 0 0.2179593 32.07207 12.48181 -750856.4 +SIMU 1976 1 25 6 0 0.2177125 32.07207 12.46969 -39238.22 +SIMU 1976 1 25 12 0 0.2178078 32.07207 12.45734 -31.30094 +SIMU 1976 1 25 18 0 0.2189079 32.07207 12.44379 65.19908 +SIMU 1976 1 25 24 0 0.2191160 32.07207 12.43171 -101.9599 +SIMU 1976 1 26 6 0 0.2183461 32.07207 12.41873 -44.22515 +SIMU 1976 1 26 12 0 0.2175145 32.96391 12.38487 523991.5 +SIMU 1976 1 26 18 0 0.2167164 32.07207 12.39252 240245.0 +SIMU 1976 1 26 24 0 0.2159552 32.07207 12.37903 -38.06538 +SIMU 1976 1 27 6 0 0.2152075 32.07207 12.36536 -39.18702 +SIMU 1976 1 27 12 0 0.2144789 42.41420 12.11780 7584524. +SIMU 1976 1 27 18 0 0.2137764 33.09472 12.31527 5716212. +SIMU 1976 1 27 24 0 0.2130969 32.07207 12.32302 -347743.6 +SIMU 1976 1 28 6 0 0.2124194 32.07207 12.30821 -39.51871 +SIMU 1976 1 28 12 0 0.2117509 36.80027 12.18505 3034941. +SIMU 1976 1 28 18 0 0.2111823 32.07207 12.27864 526633.1 +SIMU 1976 1 28 24 0 0.2110445 32.07207 12.26224 -836923.7 +SIMU 1976 1 29 6 0 0.2108856 32.07207 12.24608 -46.83461 +SIMU 1976 1 29 12 0 0.2107723 39.45267 12.06288 5128743. +SIMU 1976 1 29 18 0 0.2136457 32.07207 12.21344 1625268. +SIMU 1976 1 29 24 0 0.2158277 32.07207 12.19417 -980804.1 +SIMU 1976 1 30 6 0 0.2174203 32.07207 12.17550 -40169.84 +SIMU 1976 1 30 12 0 0.2186069 32.75619 12.14079 410363.7 +SIMU 1976 1 30 18 0 0.2194803 32.07207 12.13709 887871.6 +SIMU 1976 1 30 24 0 0.2200985 32.07207 12.11667 -60.85453 +SIMU 1976 1 31 6 0 0.2204858 32.07207 12.09592 -58.12335 +SIMU 1976 1 31 12 0 0.2206918 34.79879 12.01346 1574497. +SIMU 1976 1 31 18 0 0.2207596 32.07207 12.05349 279186.7 +SIMU 1976 1 31 24 0 0.2207145 32.07207 12.02994 -884878.3 +SIMU 1976 2 1 6 0 0.2204997 32.07207 12.00572 -27682.40 +SIMU 1976 2 1 12 0 0.2202164 32.07207 11.97993 -80468.14 +SIMU 1976 2 1 18 0 0.2204060 32.07207 11.95304 -362490.6 +SIMU 1976 2 1 24 0 0.2208953 32.07207 11.92501 -81.96701 +SIMU 1976 2 2 6 0 0.2212104 32.07207 11.89670 -81.21722 +SIMU 1976 2 2 12 0 0.2213626 34.33297 11.81999 1372341. +SIMU 1976 2 2 18 0 0.2213862 32.07207 11.83941 1860878. +SIMU 1976 2 2 24 0 0.2213043 32.07207 11.80733 -74.82951 +SIMU 1976 2 3 6 0 0.2211185 32.07207 11.77509 -73.58753 +SIMU 1976 2 3 12 0 0.2208547 32.79903 11.72706 422251.6 +SIMU 1976 2 3 18 0 0.2205347 32.07207 11.70737 -797257.6 +SIMU 1976 2 3 24 0 0.2201690 32.07207 11.67122 -248466.2 +SIMU 1976 2 4 6 0 0.2197463 32.07207 11.63404 -69.44428 +SIMU 1976 2 4 12 0 0.2192844 32.07207 11.59572 -68.34030 +SIMU 1976 2 4 18 0 0.2188009 32.07207 11.55636 -67.63618 +SIMU 1976 2 4 24 0 0.2183005 32.07207 11.51609 -67.33067 +SIMU 1976 2 5 6 0 0.2177679 32.07207 11.47510 -67.21605 +SIMU 1976 2 5 12 0 0.2172165 32.07207 11.43361 -66.27481 +SIMU 1976 2 5 18 0 0.2166597 32.07207 11.39185 -65.93702 +SIMU 1976 2 5 24 0 0.2160998 32.07207 11.35006 -65.59772 +SIMU 1976 2 6 6 0 0.2155196 32.07207 11.30845 -66.44243 +SIMU 1976 2 6 12 0 0.2149303 39.42032 11.17035 5221518. +SIMU 1976 2 6 18 0 0.2143433 32.07207 11.23109 3387926. +SIMU 1976 2 6 24 0 0.2137594 32.07207 11.18698 -64.19181 +SIMU 1976 2 7 6 0 0.2131614 32.07207 11.14757 -65.00223 +SIMU 1976 2 7 12 0 0.2125588 39.36724 11.02642 5056998. +SIMU 1976 2 7 18 0 0.2119620 32.07207 11.07650 2668830. +SIMU 1976 2 7 24 0 0.2113712 32.07207 11.03579 -467643.1 +SIMU 1976 2 8 6 0 0.2107693 32.07207 10.99985 -63.93411 SIMU 1976 2 8 12 0 0.2101651 46.87627 10.81555 1.0954785E+07 -SIMU 1976 2 8 18 0 0.2096280 38.44360 10.87403 8288330. -SIMU 1976 2 8 24 0 0.2092517 32.07207 10.89960 -2332270. -SIMU 1976 2 9 6 0 0.2088523 32.07207 10.86599 -646623.4 -SIMU 1976 2 9 12 0 0.2084345 42.33037 10.73812 6769364. -SIMU 1976 2 9 18 0 0.2085466 37.16319 10.76024 4051294. -SIMU 1976 2 9 24 0 0.2089582 32.07207 10.77360 -3627167. -SIMU 1976 2 10 6 0 0.2092344 32.07207 10.74258 -1806130. -SIMU 1976 2 10 12 0 0.2093845 44.01875 10.60772 7170272. -SIMU 1976 2 10 18 0 0.2096327 37.28570 10.64219 3960276. -SIMU 1976 2 10 24 0 0.2099025 32.07207 10.65586 -4350830. -SIMU 1976 2 11 6 0 0.2100368 32.07207 10.62652 -2453620. +SIMU 1976 2 8 18 0 0.2096280 38.44360 10.87403 8288330. +SIMU 1976 2 8 24 0 0.2092517 32.07207 10.89960 -2332270. +SIMU 1976 2 9 6 0 0.2088523 32.07207 10.86599 -646623.4 +SIMU 1976 2 9 12 0 0.2084345 42.33037 10.73812 6769364. +SIMU 1976 2 9 18 0 0.2085466 37.16319 10.76024 4051294. +SIMU 1976 2 9 24 0 0.2089582 32.07207 10.77360 -3627167. +SIMU 1976 2 10 6 0 0.2092344 32.07207 10.74258 -1806130. +SIMU 1976 2 10 12 0 0.2093845 44.01875 10.60772 7170272. +SIMU 1976 2 10 18 0 0.2096327 37.28570 10.64219 3960276. +SIMU 1976 2 10 24 0 0.2099025 32.07207 10.65586 -4350830. +SIMU 1976 2 11 6 0 0.2100368 32.07207 10.62652 -2453620. SIMU 1976 2 11 12 0 0.2100444 48.16666 10.46241 1.0019872E+07 -SIMU 1976 2 11 18 0 0.2099543 40.59977 10.50277 8118231. -SIMU 1976 2 11 24 0 0.2097845 32.70205 10.53878 -3130689. -SIMU 1976 2 12 6 0 0.2095322 32.07207 10.51429 -2270578. +SIMU 1976 2 11 18 0 0.2099543 40.59977 10.50277 8118231. +SIMU 1976 2 11 24 0 0.2097845 32.70205 10.53878 -3130689. +SIMU 1976 2 12 6 0 0.2095322 32.07207 10.51429 -2270578. SIMU 1976 2 12 12 0 0.2092186 50.12237 10.34031 1.2878506E+07 -SIMU 1976 2 12 18 0 0.2088632 41.19772 10.38834 6405704. -SIMU 1976 2 12 24 0 0.2084743 33.80486 10.41830 -4300553. -SIMU 1976 2 13 6 0 0.2080420 32.07207 10.40249 -4983673. -SIMU 1976 2 13 12 0 0.2075804 40.06659 10.30964 2075624. -SIMU 1976 2 13 18 0 0.2071033 36.24183 10.31531 1613412. -SIMU 1976 2 13 24 0 0.2066143 32.07207 10.31768 -4338753. -SIMU 1976 2 14 6 0 0.2061006 32.07207 10.28791 -2725556. -SIMU 1976 2 14 12 0 0.2055729 42.39481 10.17666 5236389. -SIMU 1976 2 14 18 0 0.2050417 38.05507 10.18507 4191280. -SIMU 1976 2 14 24 0 0.2103604 33.34616 10.18576 -2299581. -SIMU 1976 2 15 6 0 0.2091928 35.85183 10.13653 2183619. +SIMU 1976 2 12 18 0 0.2088632 41.19772 10.38834 6405704. +SIMU 1976 2 12 24 0 0.2084743 33.80486 10.41830 -4300553. +SIMU 1976 2 13 6 0 0.2080420 32.07207 10.40249 -4983673. +SIMU 1976 2 13 12 0 0.2075804 40.06659 10.30964 2075624. +SIMU 1976 2 13 18 0 0.2071033 36.24183 10.31531 1613412. +SIMU 1976 2 13 24 0 0.2066143 32.07207 10.31768 -4338753. +SIMU 1976 2 14 6 0 0.2061006 32.07207 10.28791 -2725556. +SIMU 1976 2 14 12 0 0.2055729 42.39481 10.17666 5236389. +SIMU 1976 2 14 18 0 0.2050417 38.05507 10.18507 4191280. +SIMU 1976 2 14 24 0 0.2103604 33.34616 10.18576 -2299581. +SIMU 1976 2 15 6 0 0.2091928 35.85183 10.13653 2183619. SIMU 1976 2 15 12 0 0.2089722 50.39380 9.998320 1.3899595E+07 -SIMU 1976 2 15 18 0 0.2117340 40.29866 10.04488 5944207. -SIMU 1976 2 15 24 0 0.2143464 35.73599 10.04247 -2436472. -SIMU 1976 2 16 6 0 0.2164830 32.31719 10.03201 -4864539. -SIMU 1976 2 16 12 0 0.2200372 34.35915 9.979403 -2477170. -SIMU 1976 2 16 18 0 0.2409212 33.80207 9.948843 -2638328. -SIMU 1976 2 16 24 0 0.2502449 32.31387 9.922947 -4825992. -SIMU 1976 2 17 6 0 0.2572343 32.07207 9.883525 -4818313. -SIMU 1976 2 17 12 0 0.2626019 33.98175 9.825178 -2313448. -SIMU 1976 2 17 18 0 0.2666907 32.92642 9.786402 -2553175. -SIMU 1976 2 17 24 0 0.2697741 32.07207 9.738860 -4649499. -SIMU 1976 2 18 6 0 0.2719623 32.07207 9.680928 -3659140. -SIMU 1976 2 18 12 0 0.2735655 41.37241 9.555961 8389743. -SIMU 1976 2 18 18 0 0.2748697 36.90797 9.521747 6349274. -SIMU 1976 2 18 24 0 0.2757961 32.10673 9.465677 -5079268. -SIMU 1976 2 19 6 0 0.2762872 32.07207 9.367689 -4603966. +SIMU 1976 2 15 18 0 0.2117340 40.29866 10.04488 5944207. +SIMU 1976 2 15 24 0 0.2143464 35.73599 10.04247 -2436472. +SIMU 1976 2 16 6 0 0.2164830 32.31719 10.03201 -4864539. +SIMU 1976 2 16 12 0 0.2200372 34.35915 9.979403 -2477170. +SIMU 1976 2 16 18 0 0.2409212 33.80207 9.948843 -2638328. +SIMU 1976 2 16 24 0 0.2502449 32.31387 9.922947 -4825992. +SIMU 1976 2 17 6 0 0.2572343 32.07207 9.883525 -4818313. +SIMU 1976 2 17 12 0 0.2626019 33.98175 9.825178 -2313448. +SIMU 1976 2 17 18 0 0.2666907 32.92642 9.786402 -2553175. +SIMU 1976 2 17 24 0 0.2697741 32.07207 9.738860 -4649499. +SIMU 1976 2 18 6 0 0.2719623 32.07207 9.680928 -3659140. +SIMU 1976 2 18 12 0 0.2735655 41.37241 9.555961 8389743. +SIMU 1976 2 18 18 0 0.2748697 36.90797 9.521747 6349274. +SIMU 1976 2 18 24 0 0.2757961 32.10673 9.465677 -5079268. +SIMU 1976 2 19 6 0 0.2762872 32.07207 9.367689 -4603966. SIMU 1976 2 19 12 0 0.2764649 45.38754 9.189213 1.2301272E+07 -SIMU 1976 2 19 18 0 0.2765108 37.04338 9.117183 6252197. -SIMU 1976 2 19 24 0 0.2764716 32.07207 8.952880 -8949882. -SIMU 1976 2 20 6 0 0.2762046 32.07207 8.763246 -6734484. -SIMU 1976 2 20 12 0 0.2757882 37.17998 8.587992 31352.06 -SIMU 1976 2 20 18 0 0.2761855 33.97680 8.471845 -2593049. -SIMU 1976 2 20 24 0 0.2962097 32.07207 8.398589 -8793852. -SIMU 1976 2 21 6 0 0.3142229 32.07207 8.361709 -6400457. -SIMU 1976 2 21 12 0 0.3274650 33.43695 8.336599 -2807963. -SIMU 1976 2 21 18 0 0.3344572 32.07207 8.321568 -3349036. -SIMU 1976 2 21 24 0 0.3347758 32.07207 8.306821 -2086247. -SIMU 1976 2 22 6 0 0.3345499 32.07207 8.290276 -4241.379 -SIMU 1976 2 22 12 0 0.3351886 36.44737 8.265258 6105793. -SIMU 1976 2 22 18 0 0.3337077 32.07207 8.263033 4028345. -SIMU 1976 2 22 24 0 0.3334940 32.07207 8.249536 -991909.1 -SIMU 1976 2 23 6 0 0.3330114 32.07207 8.237956 -81.09390 +SIMU 1976 2 19 18 0 0.2765108 37.04338 9.117183 6252197. +SIMU 1976 2 19 24 0 0.2764716 32.07207 8.952880 -8949882. +SIMU 1976 2 20 6 0 0.2762046 32.07207 8.763246 -6734484. +SIMU 1976 2 20 12 0 0.2757882 37.17998 8.587992 31352.06 +SIMU 1976 2 20 18 0 0.2761855 33.97680 8.471845 -2593049. +SIMU 1976 2 20 24 0 0.2962097 32.07207 8.398589 -8793852. +SIMU 1976 2 21 6 0 0.3142229 32.07207 8.361709 -6400457. +SIMU 1976 2 21 12 0 0.3274650 33.43695 8.336599 -2807963. +SIMU 1976 2 21 18 0 0.3344572 32.07207 8.321568 -3349036. +SIMU 1976 2 21 24 0 0.3347758 32.07207 8.306821 -2086247. +SIMU 1976 2 22 6 0 0.3345499 32.07207 8.290276 -4241.379 +SIMU 1976 2 22 12 0 0.3351886 36.44737 8.265258 6105793. +SIMU 1976 2 22 18 0 0.3337077 32.07207 8.263033 4028345. +SIMU 1976 2 22 24 0 0.3334940 32.07207 8.249536 -991909.1 +SIMU 1976 2 23 6 0 0.3330114 32.07207 8.237956 -81.09390 SIMU 1976 2 23 12 0 0.3335750 41.74127 8.211655 1.4134156E+07 SIMU 1976 2 23 18 0 0.3434458 34.86575 8.213209 1.1000747E+07 -SIMU 1976 2 23 24 0 0.3508878 32.07207 8.202178 -6638734. -SIMU 1976 2 24 6 0 0.3564769 32.07207 8.189588 -3840848. +SIMU 1976 2 23 24 0 0.3508878 32.07207 8.202178 -6638734. +SIMU 1976 2 24 6 0 0.3564769 32.07207 8.189588 -3840848. SIMU 1976 2 24 12 0 0.3647994 43.56174 8.161217 1.9013062E+07 SIMU 1976 2 24 18 0 0.3857886 37.13430 8.157070 1.3301175E+07 -SIMU 1976 2 24 24 0 0.4018544 34.18435 8.142818 -8225145. +SIMU 1976 2 24 24 0 0.4018544 34.18435 8.142818 -8225145. SIMU 1976 2 25 6 0 0.4144150 33.16384 8.127437 -1.0726974E+07 -SIMU 1976 2 25 12 0 0.4246872 40.10310 8.103894 7287192. -SIMU 1976 2 25 18 0 0.4359689 37.15875 8.090714 5897259. -SIMU 1976 2 25 24 0 0.4443449 34.76394 8.074371 -9063324. +SIMU 1976 2 25 12 0 0.4246872 40.10310 8.103894 7287192. +SIMU 1976 2 25 18 0 0.4359689 37.15875 8.090714 5897259. +SIMU 1976 2 25 24 0 0.4443449 34.76394 8.074371 -9063324. SIMU 1976 2 26 6 0 0.4501042 33.47823 8.057149 -1.1446275E+07 SIMU 1976 2 26 12 0 0.4588588 45.20944 8.028823 2.2433202E+07 SIMU 1976 2 26 18 0 0.4727022 41.14432 8.012241 1.9870178E+07 -SIMU 1976 2 26 24 0 0.4839956 38.16505 7.992144 -7784013. +SIMU 1976 2 26 24 0 0.4839956 38.16505 7.992144 -7784013. SIMU 1976 2 27 6 0 0.4925610 36.35349 7.971609 -1.2485239E+07 SIMU 1976 2 27 12 0 0.5002555 44.81229 7.945271 1.6489419E+07 SIMU 1976 2 27 18 0 0.5086975 42.23417 7.925373 1.2666438E+07 SIMU 1976 2 27 24 0 0.5158166 39.84422 7.903874 -1.2583510E+07 SIMU 1976 2 28 6 0 0.5209914 37.61700 7.882366 -1.8929180E+07 -SIMU 1976 2 28 12 0 0.5248883 44.67606 7.857496 9656575. -SIMU 1976 2 28 18 0 0.5280542 41.54293 7.836951 5137571. +SIMU 1976 2 28 12 0 0.5248883 44.67606 7.857496 9656575. +SIMU 1976 2 28 18 0 0.5280542 41.54293 7.836951 5137571. SIMU 1976 2 28 24 0 0.5304815 39.12517 7.815287 -1.8693700E+07 SIMU 1976 2 29 6 0 0.5318709 39.81722 7.792977 -1.1289198E+07 -SIMU 1976 2 29 12 0 0.5326132 44.82871 7.769802 9777442. -SIMU 1976 2 29 18 0 0.5328862 41.44191 7.749051 5736009. +SIMU 1976 2 29 12 0 0.5326132 44.82871 7.769802 9777442. +SIMU 1976 2 29 18 0 0.5328862 41.44191 7.749051 5736009. SIMU 1976 2 29 24 0 0.5327758 39.60921 7.727418 -1.0832879E+07 SIMU 1976 3 1 6 0 0.5319649 35.50149 7.706499 -2.5365518E+07 SIMU 1976 3 1 12 0 0.5309512 37.45776 7.684379 -1.1554476E+07 @@ -272,41 +272,41 @@ SIMU 1976 3 2 6 0 0.5275885 33.61880 7.620162 -1.4729609E+07 SIMU 1976 3 2 12 0 0.5261047 33.38949 7.598791 -1.2538904E+07 SIMU 1976 3 2 18 0 0.5242208 32.81159 7.577714 -1.1743373E+07 SIMU 1976 3 2 24 0 0.5223529 32.07207 7.556701 -1.3251609E+07 -SIMU 1976 3 3 6 0 0.5202616 32.07207 7.535759 -8814622. -SIMU 1976 3 3 12 0 0.5181792 32.50168 7.514884 -3298728. -SIMU 1976 3 3 18 0 0.5161582 32.07207 7.494278 -2382421. -SIMU 1976 3 3 24 0 0.5141906 32.07207 7.473728 -775056.4 -SIMU 1976 3 4 6 0 0.5122597 32.07207 7.453179 -102.4910 -SIMU 1976 3 4 12 0 0.5226405 32.07207 7.424417 7103.603 -SIMU 1976 3 4 18 0 0.5233483 32.07207 7.406805 2190.109 -SIMU 1976 3 4 24 0 0.5196164 32.07207 7.386524 -83.57268 -SIMU 1976 3 5 6 0 0.5151673 32.07207 7.366695 -109.9247 +SIMU 1976 3 3 6 0 0.5202616 32.07207 7.535759 -8814622. +SIMU 1976 3 3 12 0 0.5181792 32.50168 7.514884 -3298728. +SIMU 1976 3 3 18 0 0.5161582 32.07207 7.494278 -2382421. +SIMU 1976 3 3 24 0 0.5141906 32.07207 7.473728 -775056.4 +SIMU 1976 3 4 6 0 0.5122597 32.07207 7.453179 -102.4910 +SIMU 1976 3 4 12 0 0.5226405 32.07207 7.424417 7103.603 +SIMU 1976 3 4 18 0 0.5233483 32.07207 7.406805 2190.109 +SIMU 1976 3 4 24 0 0.5196164 32.07207 7.386524 -83.57268 +SIMU 1976 3 5 6 0 0.5151673 32.07207 7.366695 -109.9247 SIMU 1976 3 5 12 0 0.5111483 36.20940 7.346437 1.1862827E+07 -SIMU 1976 3 5 18 0 0.5078666 32.07207 7.327579 8570639. -SIMU 1976 3 5 24 0 0.5053058 32.07207 7.307754 -1082994. -SIMU 1976 3 6 6 0 0.5026944 32.07207 7.288142 -145.1788 +SIMU 1976 3 5 18 0 0.5078666 32.07207 7.327579 8570639. +SIMU 1976 3 5 24 0 0.5053058 32.07207 7.307754 -1082994. +SIMU 1976 3 6 6 0 0.5026944 32.07207 7.288142 -145.1788 SIMU 1976 3 6 12 0 0.5014628 36.90552 7.267545 1.2822030E+07 -SIMU 1976 3 6 18 0 0.5096776 32.70774 7.245605 8462882. -SIMU 1976 3 6 24 0 0.5161158 32.07207 7.222585 -8228211. -SIMU 1976 3 7 6 0 0.5207718 32.07207 7.199605 -1693351. +SIMU 1976 3 6 18 0 0.5096776 32.70774 7.245605 8462882. +SIMU 1976 3 6 24 0 0.5161158 32.07207 7.222585 -8228211. +SIMU 1976 3 7 6 0 0.5207718 32.07207 7.199605 -1693351. SIMU 1976 3 7 12 0 0.5251031 38.22975 7.175890 1.9904244E+07 SIMU 1976 3 7 18 0 0.5354815 33.50332 7.151482 1.2612916E+07 SIMU 1976 3 7 24 0 0.5445520 32.07207 7.125658 -1.1644709E+07 -SIMU 1976 3 8 6 0 0.5512207 32.07207 7.100150 -4407397. -SIMU 1976 3 8 12 0 0.5562255 34.63431 7.074668 7408639. -SIMU 1976 3 8 18 0 0.5604930 32.76693 7.049715 5476698. -SIMU 1976 3 8 24 0 0.5642508 32.07207 7.024395 -8607397. -SIMU 1976 3 9 6 0 0.5666265 32.07207 6.999362 -3368590. +SIMU 1976 3 8 6 0 0.5512207 32.07207 7.100150 -4407397. +SIMU 1976 3 8 12 0 0.5562255 34.63431 7.074668 7408639. +SIMU 1976 3 8 18 0 0.5604930 32.76693 7.049715 5476698. +SIMU 1976 3 8 24 0 0.5642508 32.07207 7.024395 -8607397. +SIMU 1976 3 9 6 0 0.5666265 32.07207 6.999362 -3368590. SIMU 1976 3 9 12 0 0.5705411 36.38352 6.973592 1.6083196E+07 SIMU 1976 3 9 18 0 0.5796779 35.01041 6.945069 1.1178901E+07 -SIMU 1976 3 9 24 0 0.5828460 34.29165 6.914813 -8566895. +SIMU 1976 3 9 24 0 0.5828460 34.29165 6.914813 -8566895. SIMU 1976 3 10 6 0 0.5855899 33.61038 6.885360 -1.2362942E+07 -SIMU 1976 3 10 12 0 0.5885710 37.53434 6.855735 5893139. -SIMU 1976 3 10 18 0 0.5928271 36.04980 6.824169 4036707. +SIMU 1976 3 10 12 0 0.5885710 37.53434 6.855735 5893139. +SIMU 1976 3 10 18 0 0.5928271 36.04980 6.824169 4036707. SIMU 1976 3 10 24 0 0.5971430 34.23497 6.792311 -1.3016329E+07 SIMU 1976 3 11 6 0 0.6010177 32.11636 6.761280 -2.1054970E+07 -SIMU 1976 3 11 12 0 0.6052453 36.95206 6.730188 3563172. -SIMU 1976 3 11 18 0 0.6123173 36.72479 6.695086 5681555. +SIMU 1976 3 11 12 0 0.6052453 36.95206 6.730188 3563172. +SIMU 1976 3 11 18 0 0.6123173 36.72479 6.695086 5681555. SIMU 1976 3 11 24 0 0.6292620 35.43702 6.648464 -1.3188663E+07 SIMU 1976 3 12 6 0 0.6353333 33.76544 6.612983 -2.0640210E+07 SIMU 1976 3 12 12 0 0.6485788 34.46986 6.573839 -1.5982963E+07 @@ -322,7 +322,7 @@ SIMU 1976 3 14 18 0 0.7247114 35.83909 6.240804 1.0248002E+07 SIMU 1976 3 14 24 0 0.7307206 34.30053 6.211236 -1.9538420E+07 SIMU 1976 3 15 6 0 0.7361367 33.99430 6.183646 -1.6842700E+07 SIMU 1976 3 15 12 0 0.7411379 37.74323 6.157748 1.0608117E+07 -SIMU 1976 3 15 18 0 0.7461157 35.96395 6.131981 6028013. +SIMU 1976 3 15 18 0 0.7461157 35.96395 6.131981 6028013. SIMU 1976 3 15 24 0 0.7507403 34.61610 6.107511 -1.6662134E+07 SIMU 1976 3 16 6 0 0.7548830 32.54399 6.084393 -2.7821076E+07 SIMU 1976 3 16 12 0 0.7587151 39.18489 6.062830 2.3323548E+07 @@ -331,22 +331,22 @@ SIMU 1976 3 16 24 0 0.7664981 33.18064 6.020073 -2.1241776E+07 SIMU 1976 3 17 6 0 0.7695327 32.27652 6.000479 -2.2427204E+07 SIMU 1976 3 17 12 0 0.7723013 38.37402 5.981895 2.3561984E+07 SIMU 1976 3 17 18 0 0.7748684 37.38544 5.963665 2.9845928E+07 -SIMU 1976 3 17 24 0 0.7772442 35.40250 5.946412 -4567353. -SIMU 1976 3 18 6 0 0.7793149 35.22361 5.930238 -2643025. +SIMU 1976 3 17 24 0 0.7772442 35.40250 5.946412 -4567353. +SIMU 1976 3 18 6 0 0.7793149 35.22361 5.930238 -2643025. SIMU 1976 3 18 12 0 0.7812493 41.76333 5.914763 4.1540804E+07 SIMU 1976 3 18 18 0 0.7831664 41.82815 5.899279 4.2137468E+07 -SIMU 1976 3 18 24 0 0.7849525 40.72164 5.884746 1653480. +SIMU 1976 3 18 24 0 0.7849525 40.72164 5.884746 1653480. SIMU 1976 3 19 6 0 0.7864670 40.00698 5.871230 -1.0294846E+07 SIMU 1976 3 19 12 0 0.7878175 47.32368 5.858557 3.6582808E+07 SIMU 1976 3 19 18 0 0.7890334 47.04634 5.845696 3.3987552E+07 SIMU 1976 3 19 24 0 0.7901185 44.97976 5.833654 -1.8227538E+07 SIMU 1976 3 20 6 0 0.7909642 42.28366 5.824393 -5.3539456E+07 -SIMU 1976 3 20 12 0 0.7916692 49.43140 5.816275 -3664713. -SIMU 1976 3 20 18 0 0.7922592 47.57625 5.807091 -5294365. +SIMU 1976 3 20 12 0 0.7916692 49.43140 5.816275 -3664713. +SIMU 1976 3 20 18 0 0.7922592 47.57625 5.807091 -5294365. SIMU 1976 3 20 24 0 0.7927378 44.35085 5.798018 -5.2213004E+07 SIMU 1976 3 21 6 0 0.7930068 42.81991 5.787798 -5.1516704E+07 -SIMU 1976 3 21 12 0 0.7931603 49.03122 5.778574 7187051. -SIMU 1976 3 21 18 0 0.7932222 45.80598 5.768614 9883458. +SIMU 1976 3 21 12 0 0.7931603 49.03122 5.778574 7187051. +SIMU 1976 3 21 18 0 0.7932222 45.80598 5.768614 9883458. SIMU 1976 3 21 24 0 0.7931955 41.97038 5.759464 -3.5493124E+07 SIMU 1976 3 22 6 0 0.7929860 41.18497 5.751154 -3.0465614E+07 SIMU 1976 3 22 12 0 0.7926807 46.73924 5.743453 1.7047364E+07 @@ -355,18 +355,18 @@ SIMU 1976 3 22 24 0 0.7918422 42.95885 5.728131 -1.4853230E+07 SIMU 1976 3 23 6 0 0.7912228 40.58896 5.724424 -2.5537290E+07 SIMU 1976 3 23 12 0 0.7905225 47.25793 5.721269 2.8668960E+07 SIMU 1976 3 23 18 0 0.7897589 46.42865 5.716682 2.8338244E+07 -SIMU 1976 3 23 24 0 0.7889336 44.92815 5.712003 -9747096. -SIMU 1976 3 24 6 0 0.7879614 46.01321 5.705715 6820741. +SIMU 1976 3 23 24 0 0.7889336 44.92815 5.712003 -9747096. +SIMU 1976 3 24 6 0 0.7879614 46.01321 5.705715 6820741. SIMU 1976 3 24 12 0 0.7869193 52.53497 5.700133 5.5909400E+07 SIMU 1976 3 24 18 0 0.7858253 50.68077 5.693494 5.0280552E+07 -SIMU 1976 3 24 24 0 0.7846809 47.08441 5.687445 -3315738. +SIMU 1976 3 24 24 0 0.7846809 47.08441 5.687445 -3315738. SIMU 1976 3 25 6 0 0.7834077 44.12849 5.681393 -2.7348052E+07 -SIMU 1976 3 25 12 0 0.7820784 48.75908 5.676113 9584211. +SIMU 1976 3 25 12 0 0.7820784 48.75908 5.676113 9584211. SIMU 1976 3 25 18 0 0.7807078 48.63884 5.670557 1.2696018E+07 SIMU 1976 3 25 24 0 0.7792971 47.46568 5.665522 -1.5880412E+07 SIMU 1976 3 26 6 0 0.7814740 47.56243 5.661014 -1.4647850E+07 -SIMU 1976 3 26 12 0 0.7761917 48.35303 5.656819 -7751081. -SIMU 1976 3 26 18 0 0.7748151 47.92815 5.652716 -6784824. +SIMU 1976 3 26 12 0 0.7761917 48.35303 5.656819 -7751081. +SIMU 1976 3 26 18 0 0.7748151 47.92815 5.652716 -6784824. SIMU 1976 3 26 24 0 0.7734550 46.65198 5.648812 -1.8016930E+07 SIMU 1976 3 27 6 0 0.7720282 45.42798 5.645170 -2.3694500E+07 SIMU 1976 3 27 12 0 0.7705547 52.93659 5.641841 3.4148188E+07 @@ -374,15 +374,15 @@ SIMU 1976 3 27 18 0 0.7690504 50.72863 5.638113 3.2991048E+07 SIMU 1976 3 27 24 0 0.7675132 47.47163 5.634801 -1.5712502E+07 SIMU 1976 3 28 6 0 0.7657845 45.20079 5.631865 -2.6802896E+07 SIMU 1976 3 28 12 0 0.7639116 49.88422 5.628957 1.1473984E+07 -SIMU 1976 3 28 18 0 0.7620121 48.97796 5.625787 7406810. +SIMU 1976 3 28 18 0 0.7620121 48.97796 5.625787 7406810. SIMU 1976 3 28 24 0 0.7604238 47.49491 5.623000 -2.0615648E+07 SIMU 1976 3 29 6 0 0.7587393 47.51015 5.620539 -1.0259896E+07 -SIMU 1976 3 29 12 0 0.7572042 47.16862 5.618056 -6762335. -SIMU 1976 3 29 18 0 0.7605649 46.80320 5.615767 -4887181. +SIMU 1976 3 29 12 0 0.7572042 47.16862 5.618056 -6762335. +SIMU 1976 3 29 18 0 0.7605649 46.80320 5.615767 -4887181. SIMU 1976 3 29 24 0 0.7670414 45.64550 5.613661 -1.1601967E+07 SIMU 1976 3 30 6 0 0.7631183 42.82633 5.610643 -2.8972162E+07 -SIMU 1976 3 30 12 0 0.7655277 47.14031 5.608181 6218639. -SIMU 1976 3 30 18 0 0.7685419 45.63046 5.605515 4351788. +SIMU 1976 3 30 12 0 0.7655277 47.14031 5.608181 6218639. +SIMU 1976 3 30 18 0 0.7685419 45.63046 5.605515 4351788. SIMU 1976 3 30 24 0 0.7712246 43.53838 5.603056 -2.5440546E+07 SIMU 1976 3 31 6 0 0.7735100 43.39014 5.600821 -2.1478078E+07 SIMU 1976 3 31 12 0 0.7755176 48.21188 5.598784 1.6549398E+07 @@ -397,8 +397,8 @@ SIMU 1976 4 2 12 0 0.7831374 51.85329 5.584793 3.2974238E+07 SIMU 1976 4 2 18 0 0.7832654 51.30020 5.583063 3.2635470E+07 SIMU 1976 4 2 24 0 0.7832673 48.78926 5.581633 -1.7139088E+07 SIMU 1976 4 3 6 0 0.7830568 46.88587 5.580532 -3.1565966E+07 -SIMU 1976 4 3 12 0 0.7827227 51.25857 5.579642 7403646. -SIMU 1976 4 3 18 0 0.7822867 49.46279 5.578411 7303251. +SIMU 1976 4 3 12 0 0.7827227 51.25857 5.579642 7403646. +SIMU 1976 4 3 18 0 0.7822867 49.46279 5.578411 7303251. SIMU 1976 4 3 24 0 0.7817546 46.43712 5.577346 -2.7885886E+07 SIMU 1976 4 4 6 0 0.7810297 46.03103 5.576464 -2.3455352E+07 SIMU 1976 4 4 12 0 0.7802300 53.66370 5.575768 3.7984632E+07 @@ -413,8 +413,8 @@ SIMU 1976 4 6 12 0 0.7703534 56.76424 5.569218 3.3368230E+07 SIMU 1976 4 6 18 0 0.7687535 55.49616 5.568240 3.0022072E+07 SIMU 1976 4 6 24 0 0.7671001 53.03038 5.567496 -1.7090310E+07 SIMU 1976 4 7 6 0 0.7651578 51.54382 5.566976 -2.6972580E+07 -SIMU 1976 4 7 12 0 0.7630987 53.87653 5.566539 -7122782. -SIMU 1976 4 7 18 0 0.7609931 53.63435 5.565902 -3373325. +SIMU 1976 4 7 12 0 0.7630987 53.87653 5.566539 -7122782. +SIMU 1976 4 7 18 0 0.7609931 53.63435 5.565902 -3373325. SIMU 1976 4 7 24 0 0.7588431 51.34180 5.565342 -2.5201774E+07 SIMU 1976 4 8 6 0 0.7564426 50.70215 5.564920 -2.3961338E+07 SIMU 1976 4 8 12 0 0.7541230 58.35337 5.564703 3.5715668E+07 @@ -439,26 +439,26 @@ SIMU 1976 4 12 24 0 0.7039658 49.91594 5.556997 -1.9427582E+07 SIMU 1976 4 13 6 0 0.7002482 48.69578 5.556784 -2.1393460E+07 SIMU 1976 4 13 12 0 0.6967469 56.77123 5.556432 3.2731292E+07 SIMU 1976 4 13 18 0 0.6932292 56.31489 5.555770 3.5519984E+07 -SIMU 1976 4 13 24 0 0.6896931 53.02139 5.555402 -9700104. -SIMU 1976 4 14 6 0 0.6866010 53.42394 5.555341 -3111273. +SIMU 1976 4 13 24 0 0.6896931 53.02139 5.555402 -9700104. +SIMU 1976 4 14 6 0 0.6866010 53.42394 5.555341 -3111273. SIMU 1976 4 14 12 0 0.6831267 59.33836 5.555136 3.2929436E+07 SIMU 1976 4 14 18 0 0.6796775 59.22460 5.554647 3.3426392E+07 -SIMU 1976 4 14 24 0 0.6789448 56.87212 5.554926 -421275.2 -SIMU 1976 4 15 6 0 0.6822549 57.52593 5.556242 439774.0 +SIMU 1976 4 14 24 0 0.6789448 56.87212 5.554926 -421275.2 +SIMU 1976 4 15 6 0 0.6822549 57.52593 5.556242 439774.0 SIMU 1976 4 15 12 0 0.6778098 63.90020 5.555517 2.8981788E+07 SIMU 1976 4 15 18 0 0.6769684 64.13007 5.555364 2.6612574E+07 -SIMU 1976 4 15 24 0 0.6759933 62.67886 5.555246 -2689431. -SIMU 1976 4 16 6 0 0.6742433 64.46558 5.555977 8622426. +SIMU 1976 4 15 24 0 0.6759933 62.67886 5.555246 -2689431. +SIMU 1976 4 16 6 0 0.6742433 64.46558 5.555977 8622426. SIMU 1976 4 16 12 0 0.6727788 70.76259 5.557030 4.3421368E+07 SIMU 1976 4 16 18 0 0.6711766 69.35081 5.557050 3.1223146E+07 -SIMU 1976 4 16 24 0 0.6694479 66.09668 5.557009 -9094623. +SIMU 1976 4 16 24 0 0.6694479 66.09668 5.557009 -9094623. SIMU 1976 4 17 6 0 0.6682080 62.76033 5.556440 -2.6221836E+07 SIMU 1976 4 17 12 0 0.6791754 63.18653 5.558922 -1.0111928E+07 -SIMU 1976 4 17 18 0 0.6828505 62.89878 5.559621 -4338544. +SIMU 1976 4 17 18 0 0.6828505 62.89878 5.559621 -4338544. SIMU 1976 4 17 24 0 0.6870024 62.35497 5.559551 -1.3619106E+07 -SIMU 1976 4 18 6 0 0.6873006 61.79854 5.559105 -9545677. +SIMU 1976 4 18 6 0 0.6873006 61.79854 5.559105 -9545677. SIMU 1976 4 18 12 0 0.6954516 67.10356 5.560534 1.9261120E+07 -SIMU 1976 4 18 18 0 0.7033113 65.22858 5.560676 9894324. +SIMU 1976 4 18 18 0 0.7033113 65.22858 5.560676 9894324. SIMU 1976 4 18 24 0 0.7102587 61.24307 5.560524 -3.0891156E+07 SIMU 1976 4 19 6 0 0.7160481 60.23217 5.560700 -2.6796902E+07 SIMU 1976 4 19 12 0 0.7210870 66.20204 5.561491 2.3194568E+07 @@ -513,8 +513,8 @@ SIMU 1976 5 1 12 0 0.9524922 59.56753 5.563526 3.9341084E+07 SIMU 1976 5 1 18 0 0.9470614 58.51807 5.562836 3.2861380E+07 SIMU 1976 5 1 24 0 0.9418136 54.77714 5.562046 -3.4277892E+07 SIMU 1976 5 2 6 0 1.001964 53.10336 5.562638 -4.0345032E+07 -SIMU 1976 5 2 12 0 1.010521 55.19504 5.563679 -495944.0 -SIMU 1976 5 2 18 0 1.006356 53.83526 5.563547 2854112. +SIMU 1976 5 2 12 0 1.010521 55.19504 5.563679 -495944.0 +SIMU 1976 5 2 18 0 1.006356 53.83526 5.563547 2854112. SIMU 1976 5 2 24 0 1.000937 50.69932 5.563179 -3.4910796E+07 SIMU 1976 5 3 6 0 0.9893308 49.04585 5.562936 -4.1360212E+07 SIMU 1976 5 3 12 0 0.9830669 55.43445 5.563736 4.1949616E+07 @@ -527,7 +527,7 @@ SIMU 1976 5 4 24 0 0.9437851 53.19838 5.561618 -1.5035075E+07 SIMU 1976 5 5 6 0 0.9322252 54.63073 5.561630 1.2011198E+07 SIMU 1976 5 5 12 0 0.9254209 58.03807 5.561834 4.7653484E+07 SIMU 1976 5 5 18 0 0.9196413 58.08668 5.561321 3.6419664E+07 -SIMU 1976 5 5 24 0 0.9140282 55.83415 5.560778 -7916611. +SIMU 1976 5 5 24 0 0.9140282 55.83415 5.560778 -7916611. SIMU 1976 5 6 6 0 0.9036369 53.96976 5.560407 -2.5934058E+07 SIMU 1976 5 6 12 0 0.8972145 59.32893 5.560900 3.3840488E+07 SIMU 1976 5 6 18 0 0.8916543 58.34956 5.560302 2.7823440E+07 @@ -553,12 +553,12 @@ SIMU 1976 5 11 12 0 0.8143151 67.33586 5.557020 4.5182748E+07 SIMU 1976 5 11 18 0 0.8132621 66.41695 5.556553 4.1538040E+07 SIMU 1976 5 11 24 0 0.8121226 62.62136 5.555984 -1.7003264E+07 SIMU 1976 5 12 6 0 0.8108869 60.40092 5.555800 -3.2888774E+07 -SIMU 1976 5 12 12 0 0.8095080 62.56414 5.555961 -6815269. -SIMU 1976 5 12 18 0 0.8080602 62.19374 5.555703 -7091707. +SIMU 1976 5 12 12 0 0.8095080 62.56414 5.555961 -6815269. +SIMU 1976 5 12 18 0 0.8080602 62.19374 5.555703 -7091707. SIMU 1976 5 12 24 0 0.8067305 60.29037 5.555460 -3.0691622E+07 SIMU 1976 5 13 6 0 0.8064491 60.11403 5.555715 -2.2155780E+07 -SIMU 1976 5 13 12 0 0.8064509 61.49439 5.556119 -6594414. -SIMU 1976 5 13 18 0 0.8063965 60.78276 5.556213 -2177317. +SIMU 1976 5 13 12 0 0.8064509 61.49439 5.556119 -6594414. +SIMU 1976 5 13 18 0 0.8063965 60.78276 5.556213 -2177317. SIMU 1976 5 13 24 0 0.8062637 58.64697 5.556134 -2.0123418E+07 SIMU 1976 5 14 6 0 0.8059162 58.70740 5.556206 -1.8928820E+07 SIMU 1976 5 14 12 0 0.8054999 63.01476 5.556598 1.9894236E+07 @@ -569,8 +569,8 @@ SIMU 1976 5 15 12 0 0.8030831 59.11757 5.556012 -1.8401204E+07 SIMU 1976 5 15 18 0 0.8026431 59.07173 5.555992 -1.3636082E+07 SIMU 1976 5 15 24 0 0.8019890 58.13171 5.555873 -2.2665594E+07 SIMU 1976 5 16 6 0 0.6747134 56.52880 5.553444 -2.3999476E+07 -SIMU 1976 5 16 12 0 0.6824770 58.22295 5.554802 -9159020. -SIMU 1976 5 16 18 0 0.6815952 57.47319 5.554062 -8074471. +SIMU 1976 5 16 12 0 0.6824770 58.22295 5.554802 -9159020. +SIMU 1976 5 16 18 0 0.6815952 57.47319 5.554062 -8074471. SIMU 1976 5 16 24 0 0.7224519 54.67968 5.557324 -2.3608878E+07 SIMU 1976 5 17 6 0 0.8644086 55.50840 5.558327 -2.8581012E+07 SIMU 1976 5 17 12 0 0.8763982 62.01012 5.559523 3.7172252E+07 @@ -597,8 +597,8 @@ SIMU 1976 5 22 12 0 0.7683466 64.32526 5.556421 -2.6332306E+07 SIMU 1976 5 22 18 0 0.7755263 63.67011 5.556025 -2.0044834E+07 SIMU 1976 5 22 24 0 0.7816272 62.17667 5.556095 -2.6954682E+07 SIMU 1976 5 23 6 0 0.7892515 61.89210 5.555958 -2.3207778E+07 -SIMU 1976 5 23 12 0 0.7866829 64.01818 5.556340 918958.4 -SIMU 1976 5 23 18 0 0.7833583 63.08671 5.556155 4773093. +SIMU 1976 5 23 12 0 0.7866829 64.01818 5.556340 918958.4 +SIMU 1976 5 23 18 0 0.7833583 63.08671 5.556155 4773093. SIMU 1976 5 23 24 0 0.7798313 60.29329 5.555777 -2.0020424E+07 SIMU 1976 5 24 6 0 0.7711717 59.85672 5.555051 -1.9820136E+07 SIMU 1976 5 24 12 0 0.7663074 66.51103 5.555388 3.9326384E+07 @@ -681,31 +681,31 @@ SIMU 1976 6 12 12 0 0.6559227 79.17432 5.549924 2.4577934E+07 SIMU 1976 6 12 18 0 0.6547403 78.17436 5.549547 2.0633438E+07 SIMU 1976 6 12 24 0 0.6551464 73.35950 5.549522 -2.0871880E+07 SIMU 1976 6 13 6 0 0.6549066 71.28883 5.549638 -3.5896348E+07 -SIMU 1976 6 13 12 0 0.6545321 76.72098 5.550215 7912949. +SIMU 1976 6 13 12 0 0.6545321 76.72098 5.550215 7912949. SIMU 1976 6 13 18 0 0.6685426 75.73503 5.554291 1.6031168E+07 SIMU 1976 6 13 24 0 0.6582643 70.78479 5.550980 -2.7711694E+07 SIMU 1976 6 14 6 0 0.6603191 70.93432 5.551619 -3.0584748E+07 SIMU 1976 6 14 12 0 0.6624450 76.20059 5.552615 1.1782593E+07 -SIMU 1976 6 14 18 0 0.6639959 75.06334 5.552543 7601471. +SIMU 1976 6 14 18 0 0.6639959 75.06334 5.552543 7601471. SIMU 1976 6 14 24 0 0.6692956 70.89763 5.553131 -3.1256988E+07 SIMU 1976 6 15 6 0 0.6667573 70.15511 5.552403 -3.1890798E+07 -SIMU 1976 6 15 12 0 0.6677718 75.27338 5.552957 9169851. -SIMU 1976 6 15 18 0 0.6686350 73.86320 5.552619 5911406. +SIMU 1976 6 15 12 0 0.6677718 75.27338 5.552957 9169851. +SIMU 1976 6 15 18 0 0.6686350 73.86320 5.552619 5911406. SIMU 1976 6 15 24 0 0.6693462 68.64345 5.552065 -3.8486908E+07 SIMU 1976 6 16 6 0 0.6701037 66.27302 5.552003 -4.9980652E+07 -SIMU 1976 6 16 12 0 0.6705265 72.36515 5.552522 1966306. -SIMU 1976 6 16 18 0 0.6708350 71.32629 5.552179 7812066. +SIMU 1976 6 16 12 0 0.6705265 72.36515 5.552522 1966306. +SIMU 1976 6 16 18 0 0.6708350 71.32629 5.552179 7812066. SIMU 1976 6 16 24 0 0.6710367 66.41796 5.551637 -3.3720020E+07 SIMU 1976 6 17 6 0 0.6707861 67.59657 5.551633 -2.1043544E+07 SIMU 1976 6 17 12 0 0.6706750 73.11227 5.551957 2.2154544E+07 SIMU 1976 6 17 18 0 0.6704656 72.01077 5.551499 1.9730552E+07 SIMU 1976 6 17 24 0 0.6701627 67.15015 5.550919 -2.5465554E+07 SIMU 1976 6 18 6 0 0.6699793 65.95064 5.550844 -3.4136544E+07 -SIMU 1976 6 18 12 0 0.6695296 71.56123 5.551157 9476311. -SIMU 1976 6 18 18 0 0.6689845 70.04117 5.550782 9446207. +SIMU 1976 6 18 12 0 0.6695296 71.56123 5.551157 9476311. +SIMU 1976 6 18 18 0 0.6689845 70.04117 5.550782 9446207. SIMU 1976 6 18 24 0 0.6683736 64.66694 5.550305 -3.5307056E+07 SIMU 1976 6 19 6 0 0.6676772 62.86765 5.550232 -4.4124628E+07 -SIMU 1976 6 19 12 0 0.6668960 69.20610 5.550536 7414375. +SIMU 1976 6 19 12 0 0.6668960 69.20610 5.550536 7414375. SIMU 1976 6 19 18 0 0.6660573 68.07554 5.550189 1.2725847E+07 SIMU 1976 6 19 24 0 0.6651635 62.66450 5.549766 -3.2203818E+07 SIMU 1976 6 20 6 0 0.6639969 62.92485 5.549724 -2.7279914E+07 @@ -724,7 +724,7 @@ SIMU 1976 6 23 6 0 0.6476260 63.91222 5.548015 -2.6766426E+07 SIMU 1976 6 23 12 0 0.6459371 70.24121 5.548166 1.7360068E+07 SIMU 1976 6 23 18 0 0.6442152 69.56856 5.547836 1.7098036E+07 SIMU 1976 6 23 24 0 0.6424475 65.51522 5.547534 -2.1580800E+07 -SIMU 1976 6 24 6 0 0.6408063 68.00972 5.547707 -4977088. +SIMU 1976 6 24 6 0 0.6408063 68.00972 5.547707 -4977088. SIMU 1976 6 24 12 0 0.6420285 74.04981 5.549039 3.7611248E+07 SIMU 1976 6 24 18 0 0.6400416 72.75575 5.548448 3.2294482E+07 SIMU 1976 6 24 24 0 0.6394262 67.37583 5.548304 -1.3965116E+07 @@ -806,15 +806,15 @@ SIMU 1976 7 13 18 0 0.5160317 90.26653 5.542402 2.2437564E+07 SIMU 1976 7 13 24 0 0.5124956 83.41279 5.542144 -2.1427250E+07 SIMU 1976 7 14 6 0 0.5088194 82.04773 5.542037 -2.7924944E+07 SIMU 1976 7 14 12 0 0.5052453 90.66805 5.541983 1.3399472E+07 -SIMU 1976 7 14 18 0 0.5016587 88.38408 5.541710 9165788. +SIMU 1976 7 14 18 0 0.5016587 88.38408 5.541710 9165788. SIMU 1976 7 14 24 0 0.4980675 81.48021 5.541531 -2.9526940E+07 SIMU 1976 7 15 6 0 0.4948420 81.76094 5.541629 -2.4695306E+07 SIMU 1976 7 15 12 0 0.4913791 89.64969 5.541574 1.2385180E+07 SIMU 1976 7 15 18 0 0.4942828 86.78952 5.543625 1.2558482E+07 SIMU 1976 7 15 24 0 0.4844375 79.67560 5.541285 -2.9344150E+07 SIMU 1976 7 16 6 0 0.4807860 75.36061 5.541280 -4.1781824E+07 -SIMU 1976 7 16 12 0 0.4682733 85.32158 5.541031 6931759. -SIMU 1976 7 16 18 0 0.4535405 81.72481 5.540548 5624611. +SIMU 1976 7 16 12 0 0.4682733 85.32158 5.541031 6931759. +SIMU 1976 7 16 18 0 0.4535405 81.72481 5.540548 5624611. SIMU 1976 7 16 24 0 0.4400584 71.42564 5.540371 -3.4860364E+07 SIMU 1976 7 17 6 0 0.4257936 76.62756 5.539500 -1.3312731E+07 SIMU 1976 7 17 12 0 0.4112094 92.31277 5.537364 3.5068344E+07 @@ -825,28 +825,28 @@ SIMU 1976 7 18 12 0 0.3630886 89.56706 5.532371 1.8171452E+07 SIMU 1976 7 18 18 0 0.3531412 85.87677 5.531630 1.3306100E+07 SIMU 1976 7 18 24 0 0.3438720 75.27139 5.531883 -1.9959052E+07 SIMU 1976 7 19 6 0 0.3410550 75.02731 5.533341 -1.5526757E+07 -SIMU 1976 7 19 12 0 0.3285465 78.44379 5.529972 -5864442. -SIMU 1976 7 19 18 0 0.3215367 77.83275 5.529193 -3167155. +SIMU 1976 7 19 12 0 0.3285465 78.44379 5.529972 -5864442. +SIMU 1976 7 19 18 0 0.3215367 77.83275 5.529193 -3167155. SIMU 1976 7 19 24 0 0.3151200 73.82050 5.529002 -1.0866285E+07 -SIMU 1976 7 20 6 0 0.3136511 75.22862 5.530096 -7581807. +SIMU 1976 7 20 6 0 0.3136511 75.22862 5.530096 -7581807. SIMU 1976 7 20 12 0 0.3032159 85.31454 5.525273 1.3128913E+07 -SIMU 1976 7 20 18 0 0.3002526 82.51840 5.522258 8119951. +SIMU 1976 7 20 18 0 0.3002526 82.51840 5.522258 8119951. SIMU 1976 7 20 24 0 0.2973849 74.02446 5.523481 -1.1796409E+07 SIMU 1976 7 21 6 0 0.2939107 72.78670 5.523462 -1.2146674E+07 -SIMU 1976 7 21 12 0 0.2903775 84.24156 5.520190 9625373. -SIMU 1976 7 21 18 0 0.2871701 81.28770 5.520396 6181790. +SIMU 1976 7 21 12 0 0.2903775 84.24156 5.520190 9625373. +SIMU 1976 7 21 18 0 0.2871701 81.28770 5.520396 6181790. SIMU 1976 7 21 24 0 0.2842555 72.42857 5.522109 -1.2715252E+07 -SIMU 1976 7 22 6 0 0.2814678 73.59084 5.521461 -7673781. -SIMU 1976 7 22 12 0 0.2789392 83.35275 5.518492 8098461. -SIMU 1976 7 22 18 0 0.2765144 82.31496 5.518360 8836860. -SIMU 1976 7 22 24 0 0.2741598 74.04549 5.520161 -6273920. -SIMU 1976 7 23 6 0 0.2713564 76.40481 5.518964 -3235091. +SIMU 1976 7 22 6 0 0.2814678 73.59084 5.521461 -7673781. +SIMU 1976 7 22 12 0 0.2789392 83.35275 5.518492 8098461. +SIMU 1976 7 22 18 0 0.2765144 82.31496 5.518360 8836860. +SIMU 1976 7 22 24 0 0.2741598 74.04549 5.520161 -6273920. +SIMU 1976 7 23 6 0 0.2713564 76.40481 5.518964 -3235091. SIMU 1976 7 23 12 0 0.2687623 100.0706 5.509834 3.1877472E+07 SIMU 1976 7 23 18 0 0.2661704 96.21616 5.510904 2.7687080E+07 -SIMU 1976 7 23 24 0 0.2635612 78.38527 5.516870 -6799029. +SIMU 1976 7 23 24 0 0.2635612 78.38527 5.516870 -6799029. SIMU 1976 7 24 6 0 0.2600144 70.59380 5.518258 -1.8646426E+07 SIMU 1976 7 24 12 0 0.2567437 93.11257 5.510090 1.7916570E+07 -SIMU 1976 7 24 18 0 0.2533669 86.50562 5.511864 9921222. +SIMU 1976 7 24 18 0 0.2533669 86.50562 5.511864 9921222. SIMU 1976 7 24 24 0 0.2498952 69.37649 5.516726 -1.9914228E+07 SIMU 1976 7 25 6 0 0.2467015 72.09325 5.515405 -1.2179524E+07 SIMU 1976 7 25 12 0 0.2433193 95.88295 5.505455 1.9558756E+07 @@ -854,637 +854,637 @@ SIMU 1976 7 25 18 0 0.2399269 90.42314 5.507075 1.3259374E+07 SIMU 1976 7 25 24 0 0.2365287 73.76167 5.512652 -1.3943921E+07 SIMU 1976 7 26 6 0 0.2339273 72.73948 5.512640 -1.1743703E+07 SIMU 1976 7 26 12 0 0.2323063 87.95718 5.506826 1.0864084E+07 -SIMU 1976 7 26 18 0 0.2291673 84.31586 5.507048 4789379. +SIMU 1976 7 26 18 0 0.2291673 84.31586 5.507048 4789379. SIMU 1976 7 26 24 0 0.2262969 72.01053 5.510726 -1.2059526E+07 -SIMU 1976 7 27 6 0 0.2231293 72.85818 5.509269 -9364752. +SIMU 1976 7 27 6 0 0.2231293 72.85818 5.509269 -9364752. SIMU 1976 7 27 12 0 0.2200620 94.94079 5.498075 1.5248659E+07 -SIMU 1976 7 27 18 0 0.2169854 89.32647 5.499745 9731594. -SIMU 1976 7 27 24 0 0.2541680 75.59334 5.529692 -4152810. -SIMU 1976 7 28 6 0 0.2321609 72.61652 5.512686 -6277631. -SIMU 1976 7 28 12 0 0.2330156 87.72038 5.506943 7517622. -SIMU 1976 7 28 18 0 0.2333543 83.82273 5.508618 4186112. +SIMU 1976 7 27 18 0 0.2169854 89.32647 5.499745 9731594. +SIMU 1976 7 27 24 0 0.2541680 75.59334 5.529692 -4152810. +SIMU 1976 7 28 6 0 0.2321609 72.61652 5.512686 -6277631. +SIMU 1976 7 28 12 0 0.2330156 87.72038 5.506943 7517622. +SIMU 1976 7 28 18 0 0.2333543 83.82273 5.508618 4186112. SIMU 1976 7 28 24 0 0.2334413 71.60152 5.513045 -1.2925079E+07 SIMU 1976 7 29 6 0 0.2337176 71.75081 5.513131 -1.0698692E+07 SIMU 1976 7 29 12 0 0.2334927 94.11360 5.504048 1.6202200E+07 SIMU 1976 7 29 18 0 0.2329272 90.05401 5.505782 1.2901289E+07 SIMU 1976 7 29 24 0 0.2321440 74.57462 5.511726 -1.0474236E+07 -SIMU 1976 7 30 6 0 0.2306184 73.89405 5.511390 -9796140. +SIMU 1976 7 30 6 0 0.2306184 73.89405 5.511390 -9796140. SIMU 1976 7 30 12 0 0.2288487 96.93640 5.500557 1.8459814E+07 SIMU 1976 7 30 18 0 0.2268155 89.83000 5.503429 1.0533004E+07 SIMU 1976 7 30 24 0 0.2282496 73.22743 5.510817 -1.2838254E+07 SIMU 1976 7 31 6 0 0.2266619 71.02461 5.511228 -1.3489504E+07 SIMU 1976 7 31 12 0 0.2248638 91.92079 5.501945 1.2903436E+07 -SIMU 1976 7 31 18 0 0.2231397 84.14101 5.504905 5494085. +SIMU 1976 7 31 18 0 0.2231397 84.14101 5.504905 5494085. SIMU 1976 7 31 24 0 0.2215113 67.90843 5.510698 -1.6468540E+07 SIMU 1976 8 1 6 0 0.2194079 69.37971 5.509344 -1.1774388E+07 SIMU 1976 8 1 12 0 0.2174039 96.84788 5.495796 1.8623584E+07 SIMU 1976 8 1 18 0 0.2152387 88.41951 5.499516 1.0998954E+07 SIMU 1976 8 1 24 0 0.2129028 69.01788 5.507183 -1.4487018E+07 -SIMU 1976 8 2 6 0 0.2105080 70.83167 5.505612 -9831204. +SIMU 1976 8 2 6 0 0.2105080 70.83167 5.505612 -9831204. SIMU 1976 8 2 12 0 0.2079544 102.7418 5.486952 2.1691818E+07 SIMU 1976 8 2 18 0 0.2052906 94.18774 5.491586 1.5074082E+07 SIMU 1976 8 2 24 0 0.2025303 71.69342 5.502183 -1.1741261E+07 SIMU 1976 8 3 6 0 0.1996751 66.21689 5.503494 -1.4052479E+07 SIMU 1976 8 3 12 0 0.1967356 91.53456 5.489434 1.0329477E+07 -SIMU 1976 8 3 18 0 0.1937216 83.95465 5.492301 4716942. +SIMU 1976 8 3 18 0 0.1937216 83.95465 5.492301 4716942. SIMU 1976 8 3 24 0 0.1906380 67.34616 5.499314 -1.2743731E+07 -SIMU 1976 8 4 6 0 0.1872628 67.31355 5.497911 -9441671. -SIMU 1976 8 4 12 0 0.1838268 84.58102 5.487099 5192869. -SIMU 1976 8 4 18 0 0.1802697 78.55933 5.488691 1061794. -SIMU 1976 8 4 24 0 0.1766189 67.00521 5.493221 -9246339. -SIMU 1976 8 5 6 0 0.1731032 69.13235 5.490435 -5697992. -SIMU 1976 8 5 12 0 0.1694835 70.88154 5.389438 4080216. -SIMU 1976 8 5 18 0 0.1658137 71.03152 5.285555 -4773181. -SIMU 1976 8 5 24 0 0.1620956 62.43964 5.296597 -9866971. +SIMU 1976 8 4 6 0 0.1872628 67.31355 5.497911 -9441671. +SIMU 1976 8 4 12 0 0.1838268 84.58102 5.487099 5192869. +SIMU 1976 8 4 18 0 0.1802697 78.55933 5.488691 1061794. +SIMU 1976 8 4 24 0 0.1766189 67.00521 5.493221 -9246339. +SIMU 1976 8 5 6 0 0.1731032 69.13235 5.490435 -5697992. +SIMU 1976 8 5 12 0 0.1694835 70.88154 5.389438 4080216. +SIMU 1976 8 5 18 0 0.1658137 71.03152 5.285555 -4773181. +SIMU 1976 8 5 24 0 0.1620956 62.43964 5.296597 -9866971. SIMU 1976 8 6 6 0 0.1578494 58.70766 5.303165 -1.0326364E+07 -SIMU 1976 8 6 12 0 0.1535523 71.48152 5.277750 -3166715. -SIMU 1976 8 6 18 0 0.1490997 70.28153 5.279510 -3110619. +SIMU 1976 8 6 12 0 0.1535523 71.48152 5.277750 -3166715. +SIMU 1976 8 6 18 0 0.1490997 70.28153 5.279510 -3110619. SIMU 1976 8 6 24 0 0.1444768 51.78964 5.318360 -1.1948763E+07 SIMU 1976 8 7 6 0 0.1403652 43.80766 5.340560 -1.3791032E+07 -SIMU 1976 8 7 12 0 0.1360981 70.08153 5.279929 -2701610. -SIMU 1976 8 7 18 0 0.1317904 72.93153 5.275013 -944805.1 -SIMU 1976 8 7 24 0 0.1274415 53.33964 5.314708 -8944285. +SIMU 1976 8 7 12 0 0.1360981 70.08153 5.279929 -2701610. +SIMU 1976 8 7 18 0 0.1317904 72.93153 5.275013 -944805.1 +SIMU 1976 8 7 24 0 0.1274415 53.33964 5.314708 -8944285. SIMU 1976 8 8 6 0 0.1225022 44.80766 5.335962 -1.0679479E+07 -SIMU 1976 8 8 12 0 0.1174326 71.08153 5.276250 -2112798. -SIMU 1976 8 8 18 0 0.1121323 75.58154 5.268746 -584766.3 -SIMU 1976 8 8 24 0 0.1065658 61.78964 5.293362 -4617329. -SIMU 1976 8 9 6 0 0.1004819 55.75766 5.305761 -5044592. -SIMU 1976 8 9 12 0 9.3992010E-02 83.68153 5.255707 978643.4 -SIMU 1976 8 9 18 0 8.6985096E-02 87.58154 5.250594 1797106. -SIMU 1976 8 9 24 0 7.9364382E-02 70.28963 5.274197 -1340803. -SIMU 1976 8 10 6 0 7.1696661E-02 62.80766 5.287869 -1736128. -SIMU 1976 8 10 12 0 6.4173289E-02 80.73152 5.256701 246334.0 -SIMU 1976 8 10 18 0 5.6763306E-02 81.88154 5.254156 264438.2 -SIMU 1976 8 10 24 0 4.9369376E-02 65.78963 5.278628 -851358.9 -SIMU 1976 8 11 6 0 4.1590787E-02 58.80766 5.290253 -842845.9 -SIMU 1976 8 11 12 0 3.3281635E-02 80.58154 5.248286 18434.91 -SIMU 1976 8 11 18 0 2.9916262E-02 82.88154 5.261706 101349.7 -SIMU 1976 8 11 24 0 3.0534286E-02 66.78963 5.268066 -336127.8 -SIMU 1976 8 12 6 0 2.7719308E-02 59.80766 5.291016 -334808.8 -SIMU 1976 8 12 12 0 2.2797752E-02 81.58154 5.253386 26055.64 -SIMU 1976 8 12 18 0 1.7042840E-02 83.43153 5.248032 33536.88 -SIMU 1976 8 12 24 0 1.4057538E-02 65.53964 5.270841 -77433.45 -SIMU 1976 8 13 6 0 6.5504415E-03 57.80766 5.272329 -44380.07 -SIMU 1976 8 13 12 0 1.3624813E-03 77.33153 5.168148 2390.271 -SIMU 1976 8 13 18 0 0.000000 79.35045 -1.0000000E+30 -266.9664 -SIMU 1976 8 13 24 0 0.000000 64.23964 -1.0000000E+30 0.000000 -SIMU 1976 8 14 6 0 0.000000 57.80766 -1.0000000E+30 0.000000 -SIMU 1976 8 14 12 0 0.000000 72.73153 -1.0000000E+30 0.000000 -SIMU 1976 8 14 18 0 0.000000 72.58153 -1.0000000E+30 0.000000 -SIMU 1976 8 14 24 0 0.000000 55.28964 -1.0000000E+30 0.000000 -SIMU 1976 8 15 6 0 0.000000 47.80766 -1.0000000E+30 0.000000 -SIMU 1976 8 15 12 0 0.000000 65.73152 -1.0000000E+30 0.000000 -SIMU 1976 8 15 18 0 0.000000 67.38153 -1.0000000E+30 0.000000 -SIMU 1976 8 15 24 0 0.000000 53.03964 -1.0000000E+30 0.000000 -SIMU 1976 8 16 6 0 0.000000 46.80766 -1.0000000E+30 0.000000 -SIMU 1976 8 16 12 0 0.000000 73.08153 -1.0000000E+30 0.000000 -SIMU 1976 8 16 18 0 0.000000 77.73152 -1.0000000E+30 0.000000 -SIMU 1976 8 16 24 0 0.000000 64.53963 -1.0000000E+30 0.000000 -SIMU 1976 8 17 6 0 0.000000 58.75766 -1.0000000E+30 0.000000 -SIMU 1976 8 17 12 0 0.000000 81.33154 -1.0000000E+30 0.000000 -SIMU 1976 8 17 18 0 0.000000 84.58153 -1.0000000E+30 0.000000 -SIMU 1976 8 17 24 0 0.000000 70.78964 -1.0000000E+30 0.000000 -SIMU 1976 8 18 6 0 0.000000 64.75766 -1.0000000E+30 0.000000 -SIMU 1976 8 18 12 0 0.000000 81.98154 -1.0000000E+30 0.000000 -SIMU 1976 8 18 18 0 0.000000 84.23153 -1.0000000E+30 0.000000 -SIMU 1976 8 18 24 0 0.000000 72.73964 -1.0000000E+30 0.000000 -SIMU 1976 8 19 6 0 0.000000 67.75765 -1.0000000E+30 0.000000 -SIMU 1976 8 19 12 0 0.000000 80.48153 -1.0000000E+30 0.000000 -SIMU 1976 8 19 18 0 0.000000 80.23152 -1.0000000E+30 0.000000 -SIMU 1976 8 19 24 0 0.000000 65.23964 -1.0000000E+30 0.000000 -SIMU 1976 8 20 6 0 0.000000 58.80766 -1.0000000E+30 0.000000 -SIMU 1976 8 20 12 0 0.000000 80.58154 -1.0000000E+30 0.000000 -SIMU 1976 8 20 18 0 0.000000 82.58153 -1.0000000E+30 0.000000 -SIMU 1976 8 20 24 0 0.000000 65.28963 -1.0000000E+30 0.000000 -SIMU 1976 8 21 6 0 0.000000 57.80766 -1.0000000E+30 0.000000 -SIMU 1976 8 21 12 0 0.000000 82.58153 -1.0000000E+30 0.000000 -SIMU 1976 8 21 18 0 0.000000 85.73153 -1.0000000E+30 0.000000 -SIMU 1976 8 21 24 0 0.000000 69.03964 -1.0000000E+30 0.000000 -SIMU 1976 8 22 6 0 0.000000 61.80766 -1.0000000E+30 0.000000 -SIMU 1976 8 22 12 0 0.000000 80.53153 -1.0000000E+30 0.000000 -SIMU 1976 8 22 18 0 0.000000 82.73153 -1.0000000E+30 0.000000 -SIMU 1976 8 22 24 0 0.000000 69.53963 -1.0000000E+30 0.000000 -SIMU 1976 8 23 6 0 0.000000 63.75766 -1.0000000E+30 0.000000 -SIMU 1976 8 23 12 0 0.000000 77.98153 -1.0000000E+30 0.000000 -SIMU 1976 8 23 18 0 0.000000 78.93153 -1.0000000E+30 0.000000 -SIMU 1976 8 23 24 0 0.000000 66.23965 -1.0000000E+30 0.000000 -SIMU 1976 8 24 6 0 0.000000 60.75766 -1.0000000E+30 0.000000 -SIMU 1976 8 24 12 0 0.000000 76.48153 -1.0000000E+30 0.000000 -SIMU 1976 8 24 18 0 0.000000 77.73152 -1.0000000E+30 0.000000 -SIMU 1976 8 24 24 0 0.000000 64.53963 -1.0000000E+30 0.000000 -SIMU 1976 8 25 6 0 0.000000 58.75766 -1.0000000E+30 0.000000 -SIMU 1976 8 25 12 0 0.000000 80.58154 -1.0000000E+30 0.000000 -SIMU 1976 8 25 18 0 0.000000 83.08153 -1.0000000E+30 0.000000 -SIMU 1976 8 25 24 0 0.000000 67.48964 -1.0000000E+30 0.000000 -SIMU 1976 8 26 6 0 0.000000 60.80045 -1.0000000E+30 0.000000 -SIMU 1976 8 26 12 0 0.000000 78.73152 -1.0000000E+30 0.000000 -SIMU 1976 8 26 18 0 0.000000 81.38154 -1.0000000E+30 0.000000 -SIMU 1976 8 26 24 0 0.000000 70.48964 -1.0000000E+30 0.000000 -SIMU 1976 8 27 6 0 0.000000 65.75766 -1.0000000E+30 0.000000 -SIMU 1976 8 27 12 0 0.000000 74.63153 -1.0000000E+30 0.000000 -SIMU 1976 8 27 18 0 0.000000 72.58153 -1.0000000E+30 0.000000 -SIMU 1976 8 27 24 0 0.000000 55.28964 -1.0000000E+30 0.000000 -SIMU 1976 8 28 6 0 0.000000 47.80766 -1.0000000E+30 0.000000 -SIMU 1976 8 28 12 0 0.000000 70.33154 -1.0000000E+30 0.000000 -SIMU 1976 8 28 18 0 0.000000 71.43153 -1.0000000E+30 0.000000 -SIMU 1976 8 28 24 0 0.000000 50.03964 -1.0000000E+30 0.000000 -SIMU 1976 8 29 6 0 0.000000 40.85766 -1.0000000E+30 0.000000 -SIMU 1976 8 29 12 0 0.000000 77.78152 -1.0000000E+30 0.000000 -SIMU 1976 8 29 18 0 0.000000 83.23153 -1.0000000E+30 0.000000 -SIMU 1976 8 29 24 0 0.000000 61.33964 -1.0000000E+30 0.000000 -SIMU 1976 8 30 6 0 0.000000 51.85766 -1.0000000E+30 0.000000 -SIMU 1976 8 30 12 0 0.000000 77.33153 -1.0000000E+30 0.000000 -SIMU 1976 8 30 18 0 0.000000 80.43153 -1.0000000E+30 0.000000 -SIMU 1976 8 30 24 0 0.000000 62.53964 -1.0000000E+30 0.000000 -SIMU 1976 8 31 6 0 0.000000 54.80766 -1.0000000E+30 0.000000 -SIMU 1976 8 31 12 0 0.000000 73.53152 -1.0000000E+30 0.000000 -SIMU 1976 8 31 18 0 0.000000 75.73154 -1.0000000E+30 0.000000 -SIMU 1976 8 31 24 0 0.000000 62.53964 -1.0000000E+30 0.000000 -SIMU 1976 9 1 6 0 0.000000 56.75766 -1.0000000E+30 0.000000 -SIMU 1976 9 1 12 0 0.000000 74.73153 -1.0000000E+30 0.000000 -SIMU 1976 9 1 18 0 0.000000 75.28154 -1.0000000E+30 0.000000 -SIMU 1976 9 1 24 0 0.000000 56.78964 -1.0000000E+30 0.000000 -SIMU 1976 9 2 6 0 0.000000 48.80766 -1.0000000E+30 0.000000 -SIMU 1976 9 2 12 0 0.000000 79.68152 -1.0000000E+30 0.000000 -SIMU 1976 9 2 18 0 0.000000 85.08153 -1.0000000E+30 0.000000 -SIMU 1976 9 2 24 0 0.000000 69.48965 -1.0000000E+30 0.000000 -SIMU 1976 9 3 6 0 0.000000 62.80766 -1.0000000E+30 0.000000 -SIMU 1976 9 3 12 0 0.000000 76.98153 -1.0000000E+30 0.000000 -SIMU 1976 9 3 18 0 0.000000 75.73154 -1.0000000E+30 0.000000 -SIMU 1976 9 3 24 0 0.000000 55.53964 -1.0000000E+30 0.000000 -SIMU 1976 9 4 6 0 0.000000 46.80766 -1.0000000E+30 0.000000 -SIMU 1976 9 4 12 0 0.000000 77.68153 -1.0000000E+30 0.000000 -SIMU 1976 9 4 18 0 0.000000 80.93153 -1.0000000E+30 0.000000 -SIMU 1976 9 4 24 0 0.000000 57.83964 -1.0000000E+30 0.000000 -SIMU 1976 9 5 6 0 0.000000 47.85766 -1.0000000E+30 0.000000 -SIMU 1976 9 5 12 0 0.000000 79.43153 -1.0000000E+30 0.000000 -SIMU 1976 9 5 18 0 0.000000 84.43152 -1.0000000E+30 0.000000 -SIMU 1976 9 5 24 0 0.000000 66.53964 -1.0000000E+30 0.000000 -SIMU 1976 9 6 6 0 0.000000 58.80766 -1.0000000E+30 0.000000 -SIMU 1976 9 6 12 0 0.000000 82.83154 -1.0000000E+30 0.000000 -SIMU 1976 9 6 18 0 0.000000 85.28153 -1.0000000E+30 0.000000 -SIMU 1976 9 6 24 0 0.000000 66.78964 -1.0000000E+30 0.000000 -SIMU 1976 9 7 6 0 0.000000 58.80766 -1.0000000E+30 0.000000 -SIMU 1976 9 7 12 0 0.000000 76.73154 -1.0000000E+30 0.000000 -SIMU 1976 9 7 18 0 0.000000 77.58154 -1.0000000E+30 0.000000 -SIMU 1976 9 7 24 0 0.000000 60.28964 -1.0000000E+30 0.000000 -SIMU 1976 9 8 6 0 0.000000 52.80766 -1.0000000E+30 0.000000 -SIMU 1976 9 8 12 0 0.000000 63.13153 -1.0000000E+30 0.000000 -SIMU 1976 9 8 18 0 0.000000 62.58154 -1.0000000E+30 0.000000 -SIMU 1976 9 8 24 0 0.000000 48.78964 -1.0000000E+30 0.000000 -SIMU 1976 9 9 6 0 0.000000 42.75766 -1.0000000E+30 0.000000 -SIMU 1976 9 9 12 0 0.000000 70.68153 -1.0000000E+30 0.000000 -SIMU 1976 9 9 18 0 0.000000 71.58153 -1.0000000E+30 0.000000 -SIMU 1976 9 9 24 0 0.000000 43.88964 -1.0000000E+30 0.000000 -SIMU 1976 9 10 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 9 10 12 0 0.000000 71.78153 -1.0000000E+30 0.000000 -SIMU 1976 9 10 18 0 0.000000 77.43153 -1.0000000E+30 0.000000 -SIMU 1976 9 10 24 0 0.000000 52.63964 -1.0000000E+30 0.000000 -SIMU 1976 9 11 6 0 0.000000 41.85766 -1.0000000E+30 0.000000 -SIMU 1976 9 11 12 0 0.000000 75.68153 -1.0000000E+30 0.000000 -SIMU 1976 9 11 18 0 0.000000 80.93153 -1.0000000E+30 0.000000 -SIMU 1976 9 11 24 0 0.000000 61.33964 -1.0000000E+30 0.000000 -SIMU 1976 9 12 6 0 0.000000 52.80766 -1.0000000E+30 0.000000 -SIMU 1976 9 12 12 0 0.000000 72.33154 -1.0000000E+30 0.000000 -SIMU 1976 9 12 18 0 0.000000 75.23153 -1.0000000E+30 0.000000 -SIMU 1976 9 12 24 0 0.000000 63.73965 -1.0000000E+30 0.000000 -SIMU 1976 9 13 6 0 0.000000 58.75766 -1.0000000E+30 0.000000 -SIMU 1976 9 13 12 0 0.000000 72.23153 -1.0000000E+30 0.000000 -SIMU 1976 9 13 18 0 0.000000 73.23153 -1.0000000E+30 0.000000 -SIMU 1976 9 13 24 0 0.000000 61.73964 -1.0000000E+30 0.000000 -SIMU 1976 9 14 6 0 0.000000 56.75766 -1.0000000E+30 0.000000 -SIMU 1976 9 14 12 0 0.000000 67.88153 -1.0000000E+30 0.000000 -SIMU 1976 9 14 18 0 0.000000 66.43153 -1.0000000E+30 0.000000 -SIMU 1976 9 14 24 0 0.000000 48.53964 -1.0000000E+30 0.000000 -SIMU 1976 9 15 6 0 0.000000 40.80766 -1.0000000E+30 0.000000 -SIMU 1976 9 15 12 0 0.000000 64.08154 -1.0000000E+30 0.000000 -SIMU 1976 9 15 18 0 0.000000 65.23152 -1.0000000E+30 0.000000 -SIMU 1976 9 15 24 0 0.000000 43.33964 -1.0000000E+30 0.000000 -SIMU 1976 9 16 6 0 0.000000 33.85766 -1.0000000E+30 0.000000 -SIMU 1976 9 16 12 0 0.000000 64.68153 -1.0000000E+30 0.000000 -SIMU 1976 9 16 18 0 0.000000 68.08154 -1.0000000E+30 0.000000 -SIMU 1976 9 16 24 0 0.000000 45.58964 -1.0000000E+30 0.000000 -SIMU 1976 9 17 6 0 0.000000 35.85766 -1.0000000E+30 0.000000 -SIMU 1976 9 17 12 0 0.000000 69.68153 -1.0000000E+30 0.000000 -SIMU 1976 9 17 18 0 0.000000 73.93152 -1.0000000E+30 0.000000 -SIMU 1976 9 17 24 0 0.000000 50.83964 -1.0000000E+30 0.000000 -SIMU 1976 9 18 6 0 0.000000 40.85766 -1.0000000E+30 0.000000 -SIMU 1976 9 18 12 0 0.000000 64.83153 -1.0000000E+30 0.000000 -SIMU 1976 9 18 18 0 0.000000 69.53154 -1.0000000E+30 0.000000 -SIMU 1976 9 18 24 0 0.000000 59.23964 -1.0000000E+30 0.000000 -SIMU 1976 9 19 6 0 0.000000 54.75045 -1.0000000E+30 0.000000 -SIMU 1976 9 19 12 0 0.000000 62.13153 -1.0000000E+30 0.000000 -SIMU 1976 9 19 18 0 0.000000 61.88153 -1.0000000E+30 0.000000 -SIMU 1976 9 19 24 0 0.000000 52.68964 -1.0000000E+30 0.000000 -SIMU 1976 9 20 6 0 0.000000 48.75766 -1.0000000E+30 0.000000 -SIMU 1976 9 20 12 0 0.000000 61.48153 -1.0000000E+30 0.000000 -SIMU 1976 9 20 18 0 0.000000 61.58154 -1.0000000E+30 0.000000 -SIMU 1976 9 20 24 0 0.000000 47.78964 -1.0000000E+30 0.000000 -SIMU 1976 9 21 6 0 0.000000 41.75766 -1.0000000E+30 0.000000 -SIMU 1976 9 21 12 0 0.000000 73.43153 -1.0000000E+30 0.000000 -SIMU 1976 9 21 18 0 0.000000 74.78154 -1.0000000E+30 0.000000 -SIMU 1976 9 21 24 0 0.000000 44.18964 -1.0000000E+30 0.000000 -SIMU 1976 9 22 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 9 22 12 0 0.000000 63.93153 -1.0000000E+30 0.000000 -SIMU 1976 9 22 18 0 0.000000 68.23152 -1.0000000E+30 0.000000 -SIMU 1976 9 22 24 0 0.000000 46.33964 -1.0000000E+30 0.000000 -SIMU 1976 9 23 6 0 0.000000 36.85766 -1.0000000E+30 0.000000 -SIMU 1976 9 23 12 0 0.000000 61.58154 -1.0000000E+30 0.000000 -SIMU 1976 9 23 18 0 0.000000 63.43153 -1.0000000E+30 0.000000 -SIMU 1976 9 23 24 0 0.000000 42.03964 -1.0000000E+30 0.000000 -SIMU 1976 9 24 6 0 0.000000 32.85766 -1.0000000E+30 0.000000 -SIMU 1976 9 24 12 0 0.000000 58.33153 -1.0000000E+30 0.000000 -SIMU 1976 9 24 18 0 0.000000 63.23153 -1.0000000E+30 0.000000 -SIMU 1976 9 24 24 0 0.000000 51.73964 -1.0000000E+30 0.000000 -SIMU 1976 9 25 6 0 0.000000 46.75766 -1.0000000E+30 0.000000 -SIMU 1976 9 25 12 0 0.000000 62.48154 -1.0000000E+30 0.000000 -SIMU 1976 9 25 18 0 0.000000 64.38153 -1.0000000E+30 0.000000 -SIMU 1976 9 25 24 0 0.000000 53.48964 -1.0000000E+30 0.000000 -SIMU 1976 9 26 6 0 0.000000 48.75766 -1.0000000E+30 0.000000 -SIMU 1976 9 26 12 0 0.000000 55.38153 -1.0000000E+30 0.000000 -SIMU 1976 9 26 18 0 0.000000 55.73153 -1.0000000E+30 0.000000 -SIMU 1976 9 26 24 0 0.000000 49.43964 -1.0000000E+30 0.000000 -SIMU 1976 9 27 6 0 0.000000 46.70766 -1.0000000E+30 0.000000 -SIMU 1976 9 27 12 0 0.000000 59.48153 -1.0000000E+30 0.000000 -SIMU 1976 9 27 18 0 0.000000 59.23153 -1.0000000E+30 0.000000 -SIMU 1976 9 27 24 0 0.000000 44.23964 -1.0000000E+30 0.000000 -SIMU 1976 9 28 6 0 0.000000 37.80766 -1.0000000E+30 0.000000 -SIMU 1976 9 28 12 0 0.000000 60.33153 -1.0000000E+30 0.000000 -SIMU 1976 9 28 18 0 0.000000 62.58153 -1.0000000E+30 0.000000 -SIMU 1976 9 28 24 0 0.000000 45.28964 -1.0000000E+30 0.000000 -SIMU 1976 9 29 6 0 0.000000 37.80766 -1.0000000E+30 0.000000 -SIMU 1976 9 29 12 0 0.000000 71.68153 -1.0000000E+30 0.000000 -SIMU 1976 9 29 18 0 0.000000 74.43152 -1.0000000E+30 0.000000 -SIMU 1976 9 29 24 0 0.000000 46.13964 -1.0000000E+30 0.000000 -SIMU 1976 9 30 6 0 0.000000 33.90766 -1.0000000E+30 0.000000 -SIMU 1976 9 30 12 0 0.000000 77.63153 -1.0000000E+30 0.000000 -SIMU 1976 9 30 18 0 0.000000 83.13153 -1.0000000E+30 0.000000 -SIMU 1976 9 30 24 0 0.000000 53.63964 -1.0000000E+30 0.000000 -SIMU 1976 10 1 6 0 0.000000 40.90766 -1.0000000E+30 0.000000 -SIMU 1976 10 1 12 0 0.000000 71.68153 -1.0000000E+30 0.000000 -SIMU 1976 10 1 18 0 0.000000 76.28154 -1.0000000E+30 0.000000 -SIMU 1976 10 1 24 0 0.000000 57.78964 -1.0000000E+30 0.000000 -SIMU 1976 10 2 6 0 0.000000 49.80766 -1.0000000E+30 0.000000 -SIMU 1976 10 2 12 0 0.000000 76.93153 -1.0000000E+30 0.000000 -SIMU 1976 10 2 18 0 0.000000 80.88154 -1.0000000E+30 0.000000 -SIMU 1976 10 2 24 0 0.000000 64.78963 -1.0000000E+30 0.000000 -SIMU 1976 10 3 6 0 0.000000 57.80766 -1.0000000E+30 0.000000 -SIMU 1976 10 3 12 0 0.000000 73.48152 -1.0000000E+30 0.000000 -SIMU 1976 10 3 18 0 0.000000 74.08154 -1.0000000E+30 0.000000 -SIMU 1976 10 3 24 0 0.000000 58.48964 -1.0000000E+30 0.000000 -SIMU 1976 10 4 6 0 0.000000 51.80045 -1.0000000E+30 0.000000 -SIMU 1976 10 4 12 0 0.000000 53.78153 -1.0000000E+30 0.000000 -SIMU 1976 10 4 18 0 0.000000 52.88153 -1.0000000E+30 0.000000 -SIMU 1976 10 4 24 0 0.000000 47.18964 -1.0000000E+30 0.000000 -SIMU 1976 10 5 6 0 0.000000 44.70766 -1.0000000E+30 0.000000 -SIMU 1976 10 5 12 0 0.000000 49.88153 -1.0000000E+30 0.000000 -SIMU 1976 10 5 18 0 0.000000 47.08153 -1.0000000E+30 0.000000 -SIMU 1976 10 5 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 6 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 6 12 0 0.000000 45.08154 -1.0000000E+30 0.000000 -SIMU 1976 10 6 18 0 0.000000 47.93153 -1.0000000E+30 0.000000 -SIMU 1976 10 6 24 0 0.000000 35.23964 -1.0000000E+30 0.000000 -SIMU 1976 10 7 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 7 12 0 0.000000 50.83154 -1.0000000E+30 0.000000 -SIMU 1976 10 7 18 0 0.000000 51.58153 -1.0000000E+30 0.000000 -SIMU 1976 10 7 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 8 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 8 12 0 0.000000 51.18153 -1.0000000E+30 0.000000 -SIMU 1976 10 8 18 0 0.000000 56.23153 -1.0000000E+30 0.000000 -SIMU 1976 10 8 24 0 0.000000 41.23964 -1.0000000E+30 0.000000 -SIMU 1976 10 9 6 0 0.000000 34.80766 -1.0000000E+30 0.000000 -SIMU 1976 10 9 12 0 0.000000 62.68153 -1.0000000E+30 0.000000 -SIMU 1976 10 9 18 0 0.000000 64.28152 -1.0000000E+30 0.000000 -SIMU 1976 10 9 24 0 0.000000 38.88964 -1.0000000E+30 0.000000 -SIMU 1976 10 10 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 10 12 0 0.000000 65.53153 -1.0000000E+30 0.000000 -SIMU 1976 10 10 18 0 0.000000 71.93153 -1.0000000E+30 0.000000 -SIMU 1976 10 10 24 0 0.000000 52.33964 -1.0000000E+30 0.000000 -SIMU 1976 10 11 6 0 0.000000 43.80766 -1.0000000E+30 0.000000 -SIMU 1976 10 11 12 0 0.000000 67.08154 -1.0000000E+30 0.000000 -SIMU 1976 10 11 18 0 0.000000 70.38153 -1.0000000E+30 0.000000 -SIMU 1976 10 11 24 0 0.000000 56.03964 -1.0000000E+30 0.000000 -SIMU 1976 10 12 6 0 0.000000 49.80766 -1.0000000E+30 0.000000 -SIMU 1976 10 12 12 0 0.000000 63.23153 -1.0000000E+30 0.000000 -SIMU 1976 10 12 18 0 0.000000 63.73153 -1.0000000E+30 0.000000 -SIMU 1976 10 12 24 0 0.000000 50.53964 -1.0000000E+30 0.000000 -SIMU 1976 10 13 6 0 0.000000 44.75766 -1.0000000E+30 0.000000 -SIMU 1976 10 13 12 0 0.000000 71.08153 -1.0000000E+30 0.000000 -SIMU 1976 10 13 18 0 0.000000 72.63154 -1.0000000E+30 0.000000 -SIMU 1976 10 13 24 0 0.000000 48.33964 -1.0000000E+30 0.000000 -SIMU 1976 10 14 6 0 0.000000 37.85766 -1.0000000E+30 0.000000 -SIMU 1976 10 14 12 0 0.000000 63.33153 -1.0000000E+30 0.000000 -SIMU 1976 10 14 18 0 0.000000 66.43153 -1.0000000E+30 0.000000 -SIMU 1976 10 14 24 0 0.000000 48.53964 -1.0000000E+30 0.000000 -SIMU 1976 10 15 6 0 0.000000 40.80766 -1.0000000E+30 0.000000 -SIMU 1976 10 15 12 0 0.000000 41.28153 -1.0000000E+30 0.000000 -SIMU 1976 10 15 18 0 0.000000 39.23153 -1.0000000E+30 0.000000 -SIMU 1976 10 15 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 16 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 16 12 0 0.000000 41.23153 -1.0000000E+30 0.000000 -SIMU 1976 10 16 18 0 0.000000 41.38153 -1.0000000E+30 0.000000 -SIMU 1976 10 16 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 17 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 17 12 0 0.000000 37.98153 -1.0000000E+30 0.000000 -SIMU 1976 10 17 18 0 0.000000 40.23153 -1.0000000E+30 0.000000 -SIMU 1976 10 17 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 18 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 18 12 0 0.000000 35.73153 -1.0000000E+30 0.000000 -SIMU 1976 10 18 18 0 0.000000 38.03153 -1.0000000E+30 0.000000 -SIMU 1976 10 18 24 0 0.000000 32.93964 -1.0000000E+30 0.000000 -SIMU 1976 10 19 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 19 12 0 0.000000 42.73153 -1.0000000E+30 0.000000 -SIMU 1976 10 19 18 0 0.000000 42.93153 -1.0000000E+30 0.000000 -SIMU 1976 10 19 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 20 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 20 12 0 0.000000 39.73153 -1.0000000E+30 0.000000 -SIMU 1976 10 20 18 0 0.000000 41.38153 -1.0000000E+30 0.000000 -SIMU 1976 10 20 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 21 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 21 12 0 0.000000 42.98153 -1.0000000E+30 0.000000 -SIMU 1976 10 21 18 0 0.000000 42.93153 -1.0000000E+30 0.000000 -SIMU 1976 10 21 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 22 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 22 12 0 0.000000 39.58154 -1.0000000E+30 0.000000 -SIMU 1976 10 22 18 0 0.000000 44.08154 -1.0000000E+30 0.000000 -SIMU 1976 10 22 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 23 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 23 12 0 0.000000 37.13153 -1.0000000E+30 0.000000 -SIMU 1976 10 23 18 0 0.000000 39.15045 -1.0000000E+30 0.000000 -SIMU 1976 10 23 24 0 0.000000 33.95045 -1.0000000E+30 0.000000 -SIMU 1976 10 24 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 24 12 0 0.000000 39.88153 -1.0000000E+30 0.000000 -SIMU 1976 10 24 18 0 0.000000 40.03153 -1.0000000E+30 0.000000 -SIMU 1976 10 24 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 25 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 25 12 0 0.000000 36.63153 -1.0000000E+30 0.000000 -SIMU 1976 10 25 18 0 0.000000 37.23153 -1.0000000E+30 0.000000 -SIMU 1976 10 25 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 26 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 26 12 0 0.000000 38.48153 -1.0000000E+30 0.000000 -SIMU 1976 10 26 18 0 0.000000 38.58154 -1.0000000E+30 0.000000 -SIMU 1976 10 26 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 27 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 27 12 0 0.000000 42.08153 -1.0000000E+30 0.000000 -SIMU 1976 10 27 18 0 0.000000 45.58154 -1.0000000E+30 0.000000 -SIMU 1976 10 27 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 28 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 28 12 0 0.000000 46.08154 -1.0000000E+30 0.000000 -SIMU 1976 10 28 18 0 0.000000 48.93153 -1.0000000E+30 0.000000 -SIMU 1976 10 28 24 0 0.000000 36.23964 -1.0000000E+30 0.000000 -SIMU 1976 10 29 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 29 12 0 0.000000 44.98153 -1.0000000E+30 0.000000 -SIMU 1976 10 29 18 0 0.000000 48.03153 -1.0000000E+30 0.000000 -SIMU 1976 10 29 24 0 0.000000 42.93964 -1.0000000E+30 0.000000 -SIMU 1976 10 30 6 0 0.000000 40.70766 -1.0000000E+30 0.000000 -SIMU 1976 10 30 12 0 0.000000 48.88153 -1.0000000E+30 0.000000 -SIMU 1976 10 30 18 0 0.000000 47.93153 -1.0000000E+30 0.000000 -SIMU 1976 10 30 24 0 0.000000 35.23964 -1.0000000E+30 0.000000 -SIMU 1976 10 31 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 10 31 12 0 0.000000 53.08153 -1.0000000E+30 0.000000 -SIMU 1976 10 31 18 0 0.000000 55.73153 -1.0000000E+30 0.000000 -SIMU 1976 10 31 24 0 0.000000 39.03964 -1.0000000E+30 0.000000 -SIMU 1976 11 1 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 1 12 0 0.000000 51.33153 -1.0000000E+30 0.000000 -SIMU 1976 11 1 18 0 0.000000 54.53153 -1.0000000E+30 0.000000 -SIMU 1976 11 1 24 0 0.000000 44.23964 -1.0000000E+30 0.000000 -SIMU 1976 11 2 6 0 0.000000 39.75766 -1.0000000E+30 0.000000 -SIMU 1976 11 2 12 0 0.000000 44.13153 -1.0000000E+30 0.000000 -SIMU 1976 11 2 18 0 0.000000 42.53153 -1.0000000E+30 0.000000 -SIMU 1976 11 2 24 0 0.000000 32.23964 -1.0000000E+30 0.000000 -SIMU 1976 11 3 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 3 12 0 0.000000 36.63153 -1.0000000E+30 0.000000 -SIMU 1976 11 3 18 0 0.000000 37.03153 -1.0000000E+30 0.000000 -SIMU 1976 11 3 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 4 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 4 12 0 0.000000 41.23153 -1.0000000E+30 0.000000 -SIMU 1976 11 4 18 0 0.000000 41.73153 -1.0000000E+30 0.000000 -SIMU 1976 11 4 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 5 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 5 12 0 0.000000 42.58154 -1.0000000E+30 0.000000 -SIMU 1976 11 5 18 0 0.000000 46.38153 -1.0000000E+30 0.000000 -SIMU 1976 11 5 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 6 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 6 12 0 0.000000 35.38153 -1.0000000E+30 0.000000 -SIMU 1976 11 6 18 0 0.000000 35.53153 -1.0000000E+30 0.000000 -SIMU 1976 11 6 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 7 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 7 12 0 0.000000 37.23153 -1.0000000E+30 0.000000 -SIMU 1976 11 7 18 0 0.000000 36.93153 -1.0000000E+30 0.000000 -SIMU 1976 11 7 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 8 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 8 12 0 0.000000 41.18153 -1.0000000E+30 0.000000 -SIMU 1976 11 8 18 0 0.000000 49.23153 -1.0000000E+30 0.000000 -SIMU 1976 11 8 24 0 0.000000 41.23964 -1.0000000E+30 0.000000 -SIMU 1976 11 9 6 0 0.000000 37.70766 -1.0000000E+30 0.000000 -SIMU 1976 11 9 12 0 0.000000 37.53153 -1.0000000E+30 0.000000 -SIMU 1976 11 9 18 0 0.000000 34.38153 -1.0000000E+30 0.000000 -SIMU 1976 11 9 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 10 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 10 12 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 10 18 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 10 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 11 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 11 12 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 11 18 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 11 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 12 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 12 12 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 12 18 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 12 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 13 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 13 12 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 13 18 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 13 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 14 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 14 12 0 0.000000 33.08153 -1.0000000E+30 0.000000 -SIMU 1976 11 14 18 0 0.000000 36.88153 -1.0000000E+30 0.000000 -SIMU 1976 11 14 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 15 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 15 12 0 0.000000 39.33153 -1.0000000E+30 0.000000 -SIMU 1976 11 15 18 0 0.000000 41.93153 -1.0000000E+30 0.000000 -SIMU 1976 11 15 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 16 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 16 12 0 0.000000 44.68153 -1.0000000E+30 0.000000 -SIMU 1976 11 16 18 0 0.000000 49.58154 -1.0000000E+30 0.000000 -SIMU 1976 11 16 24 0 0.000000 32.28964 -1.0000000E+30 0.000000 -SIMU 1976 11 17 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 17 12 0 0.000000 53.43153 -1.0000000E+30 0.000000 -SIMU 1976 11 17 18 0 0.000000 55.78153 -1.0000000E+30 0.000000 -SIMU 1976 11 17 24 0 0.000000 32.08964 -1.0000000E+30 0.000000 -SIMU 1976 11 18 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 18 12 0 0.000000 42.08154 -1.0000000E+30 0.000000 -SIMU 1976 11 18 18 0 0.000000 44.38153 -1.0000000E+30 0.000000 -SIMU 1976 11 18 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 19 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 19 12 0 0.000000 40.98153 -1.0000000E+30 0.000000 -SIMU 1976 11 19 18 0 0.000000 42.58154 -1.0000000E+30 0.000000 -SIMU 1976 11 19 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 20 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 20 12 0 0.000000 33.88153 -1.0000000E+30 0.000000 -SIMU 1976 11 20 18 0 0.000000 35.03153 -1.0000000E+30 0.000000 -SIMU 1976 11 20 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 21 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 21 12 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 21 18 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 21 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 22 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 22 12 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 22 18 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 22 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 23 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 23 12 0 0.000000 42.18153 -1.0000000E+30 0.000000 -SIMU 1976 11 23 18 0 0.000000 47.08153 -1.0000000E+30 0.000000 -SIMU 1976 11 23 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 24 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 24 12 0 0.000000 49.93153 -1.0000000E+30 0.000000 -SIMU 1976 11 24 18 0 0.000000 54.88153 -1.0000000E+30 0.000000 -SIMU 1976 11 24 24 0 0.000000 38.78964 -1.0000000E+30 0.000000 -SIMU 1976 11 25 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 25 12 0 0.000000 35.28153 -1.0000000E+30 0.000000 -SIMU 1976 11 25 18 0 0.000000 35.38153 -1.0000000E+30 0.000000 -SIMU 1976 11 25 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 26 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 26 12 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 26 18 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 26 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 27 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 27 12 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 27 18 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 27 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 28 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 28 12 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 28 18 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 28 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 29 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 29 12 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 29 18 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 29 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 30 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 30 12 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 30 18 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 11 30 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 12 1 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 12 1 12 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 12 1 18 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 12 1 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 12 2 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 12 2 12 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 12 2 18 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 12 2 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 12 3 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 12 3 12 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 12 3 18 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 12 3 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 12 4 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 12 4 12 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 12 4 18 0 0.000000 32.07207 -1.0000000E+30 0.000000 -SIMU 1976 12 4 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-1.0000000E+30 0.000000 +SIMU 1976 12 29 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 +SIMU 1976 12 29 12 0 0.000000 32.07207 -1.0000000E+30 0.000000 +SIMU 1976 12 29 18 0 0.000000 32.07207 -1.0000000E+30 0.000000 +SIMU 1976 12 29 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 +SIMU 1976 12 30 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 +SIMU 1976 12 30 12 0 0.000000 32.07207 -1.0000000E+30 0.000000 +SIMU 1976 12 30 18 0 0.000000 32.07207 -1.0000000E+30 0.000000 +SIMU 1976 12 30 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 +SIMU 1976 12 31 6 0 0.000000 32.07207 -1.0000000E+30 0.000000 +SIMU 1976 12 31 12 0 0.000000 32.07207 -1.0000000E+30 0.000000 +SIMU 1976 12 31 18 0 0.000000 32.07207 -1.0000000E+30 0.000000 +SIMU 1976 12 31 24 0 0.000000 32.07207 -1.0000000E+30 0.000000 diff --git a/tests/test10/HSPFresults/test10.uci b/tests/test10/HSPFresults/test10.uci index 0ebba1bb..d5a54aeb 100644 --- a/tests/test10/HSPFresults/test10.uci +++ b/tests/test10/HSPFresults/test10.uci @@ -9,7 +9,7 @@ END GLOBAL *** This test run uses MASS-LINK and SCHEMATIC blocks *** -FILES +FILES ***<----FILE NAME-------------------------------------------------> WDM 21 test10.wdm MESSU 22 test10.ech @@ -309,7 +309,7 @@ RCHRES ACTIVITY RCHRES Active Sections (1=Active, 0=Inactive) *** # - # HYFG ADFG CNFG HTFG SDFG GQFG OXFG NUFG PKFG PHFG *** - 1 5 1 1 1 1 1 1 1 1 1 1 + 1 5 1 1 1 1 1 1 1 1 1 1 END ACTIVITY PRINT-INFO @@ -618,8 +618,8 @@ RCHRES OX-BENPARM RCHRES BENOD TCBEN EXPOD BRBOD(1) BRBOD(2) EXPREL *** - # - # mg/m2.hr mg/m2.hr mg/m2.hr *** - 1 5 10. 1.1 1.2 20. 25. 1.3 + # - # mg/m2.hr mg/m2.hr mg/m2.hr *** + 1 5 10. 1.1 1.2 20. 25. 1.3 END OX-BENPARM OX-CFOREA @@ -649,46 +649,46 @@ RCHRES END NUT-FLAGS NUT-BENPARM - RCHRES BRTAM(1) BRTAM(2) BRPO4(1) BRPO4(2) ANAER *** - # - # mg/m2.hr mg/m2.hr mg/m2.hr mg/m2.hr mg/l *** + RCHRES BRTAM(1) BRTAM(2) BRPO4(1) BRPO4(2) ANAER *** + # - # mg/m2.hr mg/m2.hr mg/m2.hr mg/m2.hr mg/l *** 1 5 11.0 33.0 1.1 2.2 0.0005 - END NUT-BENPARM - + END NUT-BENPARM + NUT-NITDENIT - RCHRES KTAM20 KNO220 TCNIT KNO320 TCDEN DENOXT *** - # - # /hr /hr /hr mg/l *** + RCHRES KTAM20 KNO220 TCNIT KNO320 TCDEN DENOXT *** + # - # /hr /hr /hr mg/l *** 1 5 .002 .004 1.07 .001 1.04 0.2 END NUT-NITDENIT - + NUT-NH3VOLAT - RCHRES EXPNVG EXPNVL *** - # - # *** + RCHRES EXPNVG EXPNVL *** + # - # *** 1 5 .50 0.6667 - END NUT-NH3VOLAT - - NUT-BEDCONC + END NUT-NH3VOLAT + + NUT-BEDCONC RCHRES Bed concentrations of NH4 & PO4 (mg/mg) *** # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** 1 5 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 - END NUT-BEDCONC - - NUT-ADSPARM + END NUT-BEDCONC + + NUT-ADSPARM RCHRES Partition coefficients for NH4 AND PO4 (l/mg) *** # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** 1 5 0.0001 0.0001 0.0001 10. 10. 10. END NUT-ADSPARM - - NUT-DINIT + + NUT-DINIT RCHRES NO3 TAM NO2 PO4 PHVAL *** - # - # mg/l mg/l mg/l mg/l ph units *** + # - # mg/l mg/l mg/l mg/l ph units *** 1 5 40. 10. 1. 50. 7.0 END NUT-DINIT - - NUT-ADSINIT + + NUT-ADSINIT RCHRES Initial suspended NH4 and PO4 concentrations (mg/mg) *** # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** 1 5 0. 0. 0. 0. 0. 0. - END NUT-ADSINIT + END NUT-ADSINIT *** Section PLANK *** @@ -941,11 +941,11 @@ SCHEMATIC # <-factor-> # # *** PERLND 1 6000. RCHRES 1 1 IMPLND 1 3000. RCHRES 5 2 -RCHRES 1 RCHRES 2 3 -RCHRES 1 RCHRES 3 4 -RCHRES 2 RCHRES 4 5 -RCHRES 3 RCHRES 4 5 -RCHRES 4 RCHRES 5 5 +RCHRES 1 RCHRES 2 3 +RCHRES 1 RCHRES 3 4 +RCHRES 2 RCHRES 4 5 +RCHRES 3 RCHRES 4 5 +RCHRES 4 RCHRES 5 5 END SCHEMATIC MASS-LINK diff --git a/tests/test10/notebooks-py2/Build_and_Run.ipynb b/tests/test10/notebooks-py2/Build_and_Run.ipynb deleted file mode 100755 index 6894187f..00000000 --- a/tests/test10/notebooks-py2/Build_and_Run.ipynb +++ /dev/null @@ -1,612 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "# TEST10 - HSP2 BUILD and RUN SIMULATION\n", - "\n", - "Place this Jupyter Notebook in a directory with one UCI and one or more WDM files." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "## Required Python Imports" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.execute_input": "2024-04-26T02:14:20.282131Z", - "iopub.status.busy": "2024-04-26T02:14:20.281879Z", - "iopub.status.idle": "2024-04-26T02:14:20.284468Z", - "shell.execute_reply": "2024-04-26T02:14:20.284061Z", - "shell.execute_reply.started": "2024-04-26T02:14:20.282115Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "from glob import glob\n", - "\n", - "import HSP2" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.execute_input": "2024-04-26T02:14:20.286809Z", - "iopub.status.busy": "2024-04-26T02:14:20.286671Z", - "iopub.status.idle": "2024-04-26T02:14:20.290809Z", - "shell.execute_reply": "2024-04-26T02:14:20.290565Z", - "shell.execute_reply.started": "2024-04-26T02:14:20.286797Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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Python3.10.14 | packaged by conda-forge | (main, Mar...
HSP20.11.0a1
numpy1.26.4
numba0.59.1
pandas2.2.2
osLinux-5.15.0-91-generic-x86_64-with-glibc2.35
processorx86_64
Date/Time2024-04-25 22:14:20
\n", - "
" - ], - "text/plain": [ - " version\n", - "Python 3.10.14 | packaged by conda-forge | (main, Mar...\n", - "HSP2 0.11.0a1\n", - "numpy 1.26.4\n", - "numba 0.59.1\n", - "pandas 2.2.2\n", - "os Linux-5.15.0-91-generic-x86_64-with-glibc2.35\n", - "processor x86_64\n", - "Date/Time 2024-04-25 22:14:20" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import HSP2tools\n", - "\n", - "from HSP2.utilities import versions\n", - "versions()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "## BUILD HDF5 FILE From UCI and WDM files" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Get the name of the UCI file." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.execute_input": "2024-04-26T02:14:20.291927Z", - "iopub.status.busy": "2024-04-26T02:14:20.291683Z", - "iopub.status.idle": "2024-04-26T02:14:20.305323Z", - "shell.execute_reply": "2024-04-26T02:14:20.304239Z", - "shell.execute_reply.started": "2024-04-26T02:14:20.291911Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [ - { - "ename": "IndexError", - "evalue": "list index out of range", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[7], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m uciname \u001b[38;5;241m=\u001b[39m \u001b[43mglob\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m*.uci\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[1;32m 2\u001b[0m uciname\n", - "\u001b[0;31mIndexError\u001b[0m: list index out of range" - ] - } - ], - "source": [ - "uciname = glob(\"*.uci\")[0]\n", - "uciname" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Create the HDF5 file filled with the UCI data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T02:14:20.305886Z", - "iopub.status.idle": "2024-04-26T02:14:20.306086Z", - "shell.execute_reply": "2024-04-26T02:14:20.305997Z", - "shell.execute_reply.started": "2024-04-26T02:14:20.305988Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "HDFname = uciname.split(\".\")[0] + \".h5\"\n", - "HDFname" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T02:14:20.306782Z", - "iopub.status.idle": "2024-04-26T02:14:20.306974Z", - "shell.execute_reply": "2024-04-26T02:14:20.306897Z", - "shell.execute_reply.started": "2024-04-26T02:14:20.306889Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "!del {HDFname}" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T02:14:20.307526Z", - "iopub.status.idle": "2024-04-26T02:14:20.307736Z", - "shell.execute_reply": "2024-04-26T02:14:20.307668Z", - "shell.execute_reply.started": "2024-04-26T02:14:20.307660Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "HSP2tools.readUCI(uciname, HDFname)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T02:14:20.308145Z", - "iopub.status.idle": "2024-04-26T02:14:20.308279Z", - "shell.execute_reply": "2024-04-26T02:14:20.308216Z", - "shell.execute_reply.started": "2024-04-26T02:14:20.308210Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "HSP2tools.cleanup(HDFname)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Add the timeseries data to the HDF5 file." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T02:14:20.308652Z", - "iopub.status.idle": "2024-04-26T02:14:20.308780Z", - "shell.execute_reply": "2024-04-26T02:14:20.308723Z", - "shell.execute_reply.started": "2024-04-26T02:14:20.308717Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "wdmnames = glob(\"*.wdm\")\n", - "wdmnames" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T02:14:20.309124Z", - "iopub.status.idle": "2024-04-26T02:14:20.309227Z", - "shell.execute_reply": "2024-04-26T02:14:20.309177Z", - "shell.execute_reply.started": "2024-04-26T02:14:20.309172Z" - }, - "jupyter": { - "outputs_hidden": false - }, - "scrolled": true - }, - "outputs": [], - "source": [ - "for name in wdmnames:\n", - " HSP2tools.ReadWDM(name, HDFname)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "deletable": true, - "editable": true - }, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T02:14:20.309626Z", - "iopub.status.idle": "2024-04-26T02:14:20.309790Z", - "shell.execute_reply": "2024-04-26T02:14:20.309716Z", - "shell.execute_reply.started": "2024-04-26T02:14:20.309709Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "!rename {HDFname} temp.h5\n", - "!ptrepack temp.h5 {HDFname}\n", - "!del temp.h5" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "## RUN simulation" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Get HDF5 filename (in case you didn't need to run the cells above)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T02:14:20.310167Z", - "iopub.status.idle": "2024-04-26T02:14:20.310278Z", - "shell.execute_reply": "2024-04-26T02:14:20.310227Z", - "shell.execute_reply.started": "2024-04-26T02:14:20.310222Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "hdfname = glob(\"*.h5\")[0]\n", - "hdfname" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T02:14:20.310609Z", - "iopub.status.idle": "2024-04-26T02:14:20.310747Z", - "shell.execute_reply": "2024-04-26T02:14:20.310677Z", - "shell.execute_reply.started": "2024-04-26T02:14:20.310670Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "HSP2.run(hdfname, saveall=True)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "deletable": true, - "editable": true - }, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T02:14:20.311242Z", - "iopub.status.idle": "2024-04-26T02:14:20.311484Z", - "shell.execute_reply": "2024-04-26T02:14:20.311374Z", - "shell.execute_reply.started": "2024-04-26T02:14:20.311364Z" - }, - "jupyter": { - "outputs_hidden": false - }, - "scrolled": true - }, - "outputs": [], - "source": [ - "%timeit HSP2.run(hdfname, saveall=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "For Development, keep record of best run" - ] - }, - { - "cell_type": "raw", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "SAVEALL = FALSE\n", - "\n", - "2017-04-21 22:22:46.40 Run completed\n", - "1 loop, best of 3: 583 ms per loop\n", - "\n", - "SAVEALL = True\n", - "2017-06-21 10:47:49.16 Run completed\n", - "1 loop, best of 3: 602 ms per loop\n", - "\n", - "SAVEALL = True PYTHON 3.5 (Currently need to comment out final write of logfile to HDF5 file at the end of main.)\n", - "2017-06-21 10:39:56.53 Run completed\n", - "1 loop, best of 3: 609 ms per loop" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "## HSPF timing" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "execution": { - "iopub.status.busy": "2024-04-26T02:14:20.311957Z", - "iopub.status.idle": "2024-04-26T02:14:20.312130Z", - "shell.execute_reply": "2024-04-26T02:14:20.312047Z", - "shell.execute_reply.started": "2024-04-26T02:14:20.312039Z" - }, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "!echo %date% - %time%\n", - "\n", - "!C:\\BASINS41\\models\\HSPF\\bin\\WinHspfLt.exe test10.uci\n", - "\n", - "!echo %date% - %time%" - ] - }, - { - "cell_type": "raw", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Development (HSPF timing)\n", - "\n", - "SAVEALL = False\n", - "Tue 04/11/2017 - 17:46:59.22\n", - "Tue 04/11/2017 - 17:47:01.50\n", - "about 0.88 seconds" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "deletable": true, - "editable": true - }, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/tests/test10/notebooks-py2/ViewIMPLND.ipynb b/tests/test10/notebooks-py2/ViewIMPLND.ipynb deleted file mode 100755 index 9e077fa8..00000000 --- a/tests/test10/notebooks-py2/ViewIMPLND.ipynb +++ /dev/null @@ -1,561 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "This Jupyter Notebook Copyright 2016 by RESPEC, INC. All rights reserved.\n", - "\n", - "$\\textbf{HSP}^{\\textbf{2}}\\ \\text{and}\\ \\textbf{HSP2}\\ $ Copyright 2016 by RESPEC INC. and released under this [License](LegalInformation/License.txt)/>" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# View IMPLND data saved in HDF5 " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This notebook displays IMPLND data from the specified HDF5 file.\n", - "\n", - "The Notebook demonstrates how monthly and annual summary results can be calculated via Pandas. It uses aggregation methods 'last' (for the last value at the end of each report interval) and\n", - "'sum (which sums the timeseries within each report interval). There are many other aggregation methods available (such as max, min, and mean). The user can create their own aggragation function as needed.\n", - "\n", - "This Notebook also demonstrates plotting capability in Pandas. These plots can be enhanced with titles, x & y axis labels, legends, line styles, point styles, etc. and saved in various formats (SVG, PDF, etc.). Matplotlib (the basis for these Pandas plots) can be used to make publication quality plots. See Tutorial 5 for more information." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Required Python imports and configuration" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "import shutil\n", - "import numpy as np\n", - "import pandas as pd\n", - "pd.options.display.max_rows = 16\n", - "pd.options.display.max_columns = 20\n", - "pd.options.display.float_format = '{:.2f}'.format # display 2 digits after the decimal point\n", - "\n", - "from matplotlib import pyplot as plt\n", - "\n", - "# replace with \"%matplotlib notebook\" for interactive plots\n", - "%matplotlib inline\n", - "\n", - "import HSP2\n", - "#HSP2.versions()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Set HDF5 filename and paths to the data\n", - "The following cell points to test 10 data to show how this utility works. Modify the cell as needed to point to your data. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "hdfname = 'test10.h5'\n", - "segment = 'I001' # IMPLND id\n", - "\n", - "snow = '/RESULTS/IMPLND_' + segment + '/SNOW'\n", - "water = '/RESULTS/IMPLND_' + segment + '/IWATER'" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### HPERSNO (SNOW) Results, Monthly and Annual reports, and plots" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Names of the possible HYDR timeseries created by HSP$^2$ - user may not save all these during a simulation run." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "state_variables = ['PACKF', 'PACKW', 'PACKI','PDEPTH','COVINX', 'NEGHTS', 'XLNMLT', 'RDENPF', 'SKYCLR', 'SNOCOV', \n", - " 'DULL', 'ALBEDO', 'PAKTMP', 'DEWTMP', 'SNOTMP']\n", - " \n", - "fluxes = ['SNOWF', 'PRAIN', 'SNOWE', 'WYIELD', 'MELT', 'RAINF']" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Read what data is actually in the HDF5 file. Update the lists of column names to reflect only the available data." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "columns = pd.read_hdf(hdfname, snow).columns\n", - "\n", - "state_variables = [v for v in state_variables if v in columns]\n", - "fluxes = [v for v in fluxes if v in columns]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Read Snow State Variables from the HDF5 file\n", - "##### Raw Hourly Data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "sv = pd.read_hdf(hdfname, snow)[state_variables]\n", - "sv.index.names = [segment]\n", - "sv" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Plot the data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - }, - "scrolled": true - }, - "outputs": [], - "source": [ - "_ = sv.plot(subplots=True, figsize=[24,80])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### Monthly Report\n", - "Values are rounded to 2 digits after the decimal place using the round() function." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "sv = sv.resample('M').last()\n", - "sv.index.names = [segment]\n", - "sv" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Read Snow Flux Timeseries from the HDF5 file\n", - "\n", - "##### Raw Hourly Data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "flx = pd.read_hdf(hdfname, snow)[fluxes]\n", - "flx.index.names = [segment]\n", - "flx" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Plot the data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - }, - "scrolled": true - }, - "outputs": [], - "source": [ - "flx.plot(figsize=[24,10])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### Monthly Report\n", - "\n", - "The values are rounded to 2 decimal places for convenience." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "flx = flx.resample('M').sum()\n", - "flx.index.names = [segment]\n", - "flx" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Plot the data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - }, - "scrolled": true - }, - "outputs": [], - "source": [ - "flx.plot(figsize=[24,10])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### Annual Report\n", - "\n", - "Annual reports follow calendar year by default, however you can easily select any month to start. These results are rounded to 2 decimal placed for convenience." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "flx.resample('A').sum() # Annual report, January start month" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### SNOW Water Balance (Monthly)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "HSP2.snow_balance(hdfname, 'IMPLND', segment)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## HIMPWAT IWATER Results, Monthly and Annual reports, and plots" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Names of the possible results - user may not save all these during a simulation run." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "state_variables = ['RETS', 'SURS', 'PETADJ']\n", - "\n", - "fluxes = ['SUPY', 'SURO', 'PET', 'IMPEV', 'SURI']" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The user may not have saved all these desired values, so read what is actually in the HDF5 file. Update the lists of column names to reflect only those available." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "columns = pd.read_hdf(hdfname, water).columns\n", - "\n", - "state_variables = [v for v in state_variables if v in columns]\n", - "fluxes = [v for v in fluxes if v in columns]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Read Water State Variables from the HDF5 file\n", - "##### Raw Hourly Data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "sv = pd.read_hdf(hdfname, water)[state_variables]\n", - "sv.index.names = [segment]\n", - "sv" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "_ = sv.plot(subplots=True, figsize=[18,10])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### Monthly Report\n", - "These values are rounded to 2 decimal places for convenience." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "sv.resample('M').last()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Read Water Flux Timeseries from the HDF5 file\n", - "##### Raw Hourly Data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "flx = pd.read_hdf(hdfname, water)[fluxes]\n", - "flx.index.names = [segment]\n", - "flx" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Plot the results" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "flx.resample('M').sum().plot(figsize=[10,6])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### Monthly Report\n", - "This data is rounded to 2 decimal points for convenience." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "flx.resample('M').sum()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### Annual Report\n", - "\n", - "Annual reports follow calendar year by default, however you can easily select any month to start. These values are rounded to 3 decimal places for convenience." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "flx.resample('A').sum()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### IMPLND Water Balance (Monthly)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "HSP2.iwater_balance(hdfname, segment)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.4" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/tests/test10/notebooks-py2/ViewPERLND.ipynb b/tests/test10/notebooks-py2/ViewPERLND.ipynb deleted file mode 100755 index bc92dfcd..00000000 --- a/tests/test10/notebooks-py2/ViewPERLND.ipynb +++ /dev/null @@ -1,718 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "\n", - "This Jupyter Notebook Copyright 2016 by RESPEC, INC. All rights reserved.\n", - "\n", - "$\\textbf{HSP}^{\\textbf{2}}\\ \\text{and}\\ \\textbf{HSP2}\\ $ Copyright 2016 by RESPEC INC. and released under this [License](LegalInformation/License.txt)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "# View PERLND data saved in HDF5 " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "This notebook displays PERLND data from the specified HDF5 file.\n", - "\n", - "The Notebook demonstrates how monthly and annual summary results can be calculated via Pandas. It uses aggregation methods 'last' (for the last value at the end of each report interval) and\n", - "'sum (which sums the timeseries within each report interval). There are many other aggregation methods available (such as max, min, and mean). The user can create their own aggragation function as needed.\n", - "\n", - "This Notebook also demonstrates plotting capability in Pandas. These plots can be enhanced with titles, x & y axis labels, legends, line styles, point styles, etc. and saved in various formats (SVG, PDF, etc.). Matplotlib (the basis for these Pandas plots) can be used to make publication quality plots. See Tutorial 5 for more information." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "### Required Python imports and configuration" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "import numpy as np\n", - "import pandas as pd\n", - "pd.options.display.max_rows = 16\n", - "pd.options.display.max_columns = 20\n", - "pd.options.display.float_format = '{:.2f}'.format # display 2 digits after the decimal point\n", - "\n", - "from matplotlib import pyplot as plt\n", - "\n", - "# replace with \"%matplotlib notebook\" for interactive plots\n", - "%matplotlib inline\n", - "\n", - "#import HSP2\n", - "#HSP2.versions()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "hdfname = 'test10.h5'\n", - "segment = 'P001' \n", - "\n", - "snow = '/RESULTS/PERLND_' + segment + '/SNOW'\n", - "water = '/RESULTS/PERLND_' + segment + '/PWATER'" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "## HPERSNO (SNOW) Results, Monthly and Annual Reports, and plots" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Names of the possible timeseries created by HSP$^2$ - user may not save all these during a simulation run." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "deletable": true, - "editable": true - }, - "outputs": [], - "source": [ - "state_variables = ['PACKF', 'PACKW', 'PACKI','PDEPTH','COVINX', 'NEGHTS', 'XLNMLT', 'RDENPF', 'SKYCLR', 'SNOCOV', 'DULL',\n", - " 'ALBEDO', 'PAKTMP', 'DEWTMP', 'SNOTMP']\n", - " \n", - "fluxes = ['SNOWF', 'PRAIN', 'SNOWE', 'WYIELD', 'MELT', 'RAINF']" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Read what data is actually in the HDF5 file. Update the lists of column names to reflect only the available data." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "columns = pd.read_hdf(hdfname, snow).columns\n", - "\n", - "state_variables = [v for v in state_variables if v in columns]\n", - "fluxes = [v for v in fluxes if v in columns]" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "### Read Snow State Variables from the HDF5 file\n", - "##### Raw Hourly Data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "sv = pd.read_hdf(hdfname, snow)[state_variables]\n", - "sv.index.names = [segment]\n", - "sv" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Plot these values" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "_ = sv.plot(subplots=True, figsize=[24,80])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "##### Monthly Report \n", - "\n", - "Values below are rounded to 2 digits. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "sv = sv.resample('M').last()\n", - "sv.index.names = [segment]\n", - "sv" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "### Read Snow Flux Timeseries from the HDF5 file\n", - "\n", - "##### Raw Hourly Data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - }, - "scrolled": true - }, - "outputs": [], - "source": [ - "flx = pd.read_hdf(hdfname, snow)[fluxes]\n", - "flx.index.names = [segment]\n", - "flx" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Plot the flux values" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "flx.plot(figsize=[24,10])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "##### Monthly Report\n", - "\n", - "Values are displayed to 2 decimal places for convenience." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "flx = flx.resample('M').sum()\n", - "flx.index.names = [segment]\n", - "flx" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "##### Annual Report\n", - "\n", - "Annual reports follow calendar year by default, however you can easily select any month to start. The data is rounded to 2 decimal places for convenience." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - }, - "scrolled": true - }, - "outputs": [], - "source": [ - "flx.resample('A').sum()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "### SNOW Water Balance (Monthly)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "HSP2.snow_balance(hdfname, 'PERLND', segment)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "## HPERWAT PWATER Results, Monthly and Annual reports, and plots" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Names of the possible results - user may not save all these during a simulation run." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "deletable": true, - "editable": true - }, - "outputs": [], - "source": [ - "state_variables = ['PERS', 'CEPS', 'SURS', 'UZS', 'IFWS', 'LZS', 'AGWS', 'GWVS', 'INFFAC', 'PETADJ', 'TGWS']\n", - "\n", - "fluxes = ['SUPY', 'SURO', 'IFWO', 'AGWO', 'PERO','IGWI','PET', 'CEPE', 'UZET', 'LZET', 'AGWET', 'BASET', \n", - " 'TAET','IFWI', 'UZI', 'INFIL', 'PERC', 'LZI', 'AGWI', 'SURI']" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Read what data is actually in the HDF5 file. Update the lists of column names to reflect only the available data. (User controls which series are stored in the HDF5 file.)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "columns = pd.read_hdf(hdfname, water).columns\n", - "\n", - "state_variables = [v for v in state_variables if v in columns]\n", - "fluxes = [v for v in fluxes if v in columns]" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "### Read Water State Variables from the HDF5 file\n", - "##### Hourly Data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "pd.options.display.float_format = '{:.3f}'.format\n", - "\n", - "sv = pd.read_hdf(hdfname, water)[state_variables]\n", - "sv.index.names = [segment]\n", - "sv" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Plot the data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "_ = sv.plot(subplots=True, figsize=[24,30])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "##### Monthly Report\n", - "Values are displayed to 3 decimal places for convenience." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "pd.options.display.precision = 3\n", - "sv.resample('M').last()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "### Read Water Flux Timeseries from the HDF5 file\n", - "\n", - "##### Raw Hourly Data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "flx = pd.read_hdf(hdfname, water)[fluxes]\n", - "flx.index.names = [segment]\n", - "flx" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Plot this data." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "_ = flx.plot(subplots=True, figsize=(20,100))" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "##### Monthly Report\n", - "\n", - "Values are displayed to 3 decimal places. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "fx = flx.resample('M').sum()\n", - "fx" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "##### Annual Report" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "flx.resample('A').sum()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "### PERLND Water Balance (Monthly)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "HSP2.pwater_balance(hdfname, segment)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "0.165/0.024, 0.525/0.132" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "deletable": true, - "editable": true - }, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.2" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/tests/test10/notebooks-py2/ViewRCHRES.ipynb b/tests/test10/notebooks-py2/ViewRCHRES.ipynb deleted file mode 100755 index c9b78416..00000000 --- a/tests/test10/notebooks-py2/ViewRCHRES.ipynb +++ /dev/null @@ -1,525 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "\n", - "This Jupyter Notebook Copyright 2016 by RESPEC, INC. All rights reserved.\n", - "\n", - "$\\textbf{HSP}^{\\textbf{2}}\\ \\text{and}\\ \\textbf{HSP2}\\ $ Copyright 2016 by RESPEC INC. and released under this [License](LegalInformation/License.txt)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "# View RCHRES Data Saved in HDF5 File" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "This notebook displays RCHRES data from the specified HDF5 file.\n", - "\n", - "The Notebook demonstrates how monthly and annual summary results can be calculated via Pandas. It uses aggregation methods 'last' (for the last value at the end of each report interval) and\n", - "'sum (which sums the timeseries within each report interval). There are many other aggregation methods available (such as max, min, and mean). The user can create their own aggragation function as needed.\n", - "\n", - "This Notebook also demonstrates plotting capability in Pandas. These plots can be enhanced with titles, x & y axis labels, legends, line styles, point styles, etc. and saved in various formats (SVG, PDF, etc.). Matplotlib (the basis for these Pandas plots) can be used to make publication quality plots. See Tutorial 5 for more information." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "### Required Python imports and configurations" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - }, - "scrolled": true - }, - "outputs": [], - "source": [ - "import shutil\n", - "import numpy as np\n", - "import pandas as pd\n", - "pd.options.display.max_rows = 16\n", - "pd.options.display.max_columns = 20\n", - "pd.options.display.float_format = '{:.2f}'.format # display 2 digits after the decimal point\n", - "\n", - "from matplotlib import pyplot as plt\n", - "\n", - "# replace with \"%matplotlib notebook\" for interactive plots\n", - "%matplotlib inline\n", - "\n", - "#import HSP2\n", - "#HSP2.versions()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "### Set HDF5 filename and paths to the data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "hdfname = 'test10.h5'\n", - "segment = 'R001' # Reaches rid \n", - "\n", - "hydr = '/RESULTS/RCHRES_' + segment + '/HYDR'" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Names of the possible HYDR timeseries created by HSP$^2$ - user may not save all these during a simulation run." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "deletable": true, - "editable": true - }, - "outputs": [], - "source": [ - "state_variables = ['VOL', 'DEP', 'SAREA', 'USTAR', 'TAU', 'RO', 'O1', 'O2', 'O3', 'O4', 'O5']\n", - "fluxes = ['IVOL', 'PRSUPY', 'VOLEV', 'ROVOL', 'OVOL1', 'OVOL2', 'OVOL3', 'OVOL4', 'OVOL15']" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Read what data is actually in the HDF5 file. Update the lists of column names to reflect only the available data." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "columns = pd.read_hdf(hdfname, hydr).columns\n", - "\n", - "state_variables = [v for v in state_variables if v in columns]\n", - "fluxes = [v for v in fluxes if v in columns]" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "### Read HYDR State Variables from the HDF5 file\n", - "##### Computed Results, Generally Hourly" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - }, - "scrolled": true - }, - "outputs": [], - "source": [ - "sv = pd.read_hdf(hdfname, hydr)[state_variables]\n", - "sv.index.names = [segment]\n", - "sv" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "##### Monthly Report\n", - "These values are rounded to 3 decimal places for convenience." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - }, - "scrolled": true - }, - "outputs": [], - "source": [ - "pd.options.display.float_format = '{:.3f}'.format \n", - "sv.resample('M').last()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "### Calculated results - not stored in HDF5 since it is simple to post process these results" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "##### Conversion factors (from internal ft$^3$ to acre-ft)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "VFACT = 43560.0 #$162\n", - "AFACT = 43560.0 #$164" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "#### LEN (Length) of Reach (Necessary for the calculations)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "# First - need length of this reach - get it from HDF5 file\n", - "with pd.get_store(hdfname, mode='r') as store:\n", - " x = store['RCHRES/HYDR/PARAMETERS']\n", - " LEN = x.loc[segment, 'LEN'] \n", - "LEN = LEN * 5280.0" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "##### Calculate Additional State Variables from simulation data saved in the HDF5 file\n", - "Note: The calculations are undefined when the flow or volumn is zero, so the fillna() function replaces NaNs with zeros, where needed.\n", - "\n", - "These calculations need the data associated with SAREA, VOL, and RO, so the calculations are conditional." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "if 'SAREA' in sv and 'VOL' in sv and 'RO' in sv:\n", - " sv['TWID'] = AFACT * sv['SAREA']/LEN\n", - " sv['AVDEP'] = (sv['VOL'] / sv['SAREA']).fillna(0.0)\n", - " sv['HRAD'] = (sv['AVDEP'] * sv['TWID']) / (2.0 * sv['AVDEP'] + sv['TWID']).fillna(0.0)\n", - " sv['AVVEL'] = ((LEN * sv['RO'] / sv['VOL']) / AFACT).fillna(0.0)\n", - " sv['AVSECT'] = AFACT * sv['VOL'] / LEN" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Update the state_variables list to reflect the actual available data. The data is also rounded to 2 decimal places for convenience." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - }, - "scrolled": true - }, - "outputs": [], - "source": [ - "pd.options.display.float_format = '{:.2f}'.format # display 2 digits after the decimal point\n", - "\n", - "state_variables = ['VOL', 'DEP', 'AVDEP', 'TWID', 'HRAD', 'SAREA', 'AVVEL', 'AVSECT', 'USTAR', 'TAU', 'RO']\n", - "state_variables = [v for v in state_variables if v in sv]\n", - "\n", - "sv[state_variables].resample('M').last()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Plot this data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "_ = sv.plot(subplots=True, figsize=[20,48])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "### Read HYDR Flux Data from the HDF5 file\n", - "\n", - "##### Raw Hourly Data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "flx = pd.read_hdf(hdfname, hydr)[fluxes]\n", - "flx.index.names = [segment]\n", - "flx" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Plot this data." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "_ = flx.plot(figsize=[20,40], subplots=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "##### Monthly Report\n", - "This data is rounded to s decimal places for convenience." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "pd.options.display.float_format = '{:.3f}'.format\n", - "\n", - "flx.resample('M').sum()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "##### Annual Report\n", - "\n", - "Annual reports follow calendar year by default, however you can easily select any month to start. These values are rounded to 2 decimal places for convenience." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "flx.resample('A').sum() # Annual report, January start month" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "deletable": true, - "editable": true - }, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.2" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/tests/test10/test.ipynb b/tests/test10/test.ipynb index 0aecb234..41f3faed 100644 --- a/tests/test10/test.ipynb +++ b/tests/test10/test.ipynb @@ -13,7 +13,8 @@ "metadata": {}, "outputs": [], "source": [ - "from HSP2 import versions, main as run\n", + "from HSP2 import main as run\n", + "from HSP2 import versions\n", "from HSP2tools import read_UCI, read_WDM\n", "\n", "versions()" @@ -32,7 +33,7 @@ "metadata": {}, "outputs": [], "source": [ - "readUCI('test10.uci', 'test10.h5')" + "readUCI(\"test10.uci\", \"test10.h5\")" ] }, { @@ -41,7 +42,7 @@ "metadata": {}, "outputs": [], "source": [ - "readWDM('test10.wdm', 'test10.h5')" + "readWDM(\"test10.wdm\", \"test10.h5\")" ] }, { @@ -50,7 +51,7 @@ "metadata": {}, "outputs": [], "source": [ - "main('test10.h5')" + "main(\"test10.h5\")" ] }, { diff --git a/tests/test10eq/HSP2results/TEST10_hsp2_compare.ipynb b/tests/test10eq/HSP2results/TEST10_hsp2_compare.ipynb new file mode 100644 index 00000000..bc619887 --- /dev/null +++ b/tests/test10eq/HSP2results/TEST10_hsp2_compare.ipynb @@ -0,0 +1,2232 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# COMPARE HSP2 TO HSPF USING TEST10" + ] + }, + { + "attachments": { + "337b05b8-e081-4c20-b486-27045c75ea6d.png": { + "image/png": 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+ } + }, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![HSP2new.png](attachment:337b05b8-e081-4c20-b486-27045c75ea6d.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Copyright 2020 for this Jupyter Notebook and YouTube Video by RESPEC, INC. All rights reserved.\n", + "\n", + "$\\textbf{HSP}^{\\textbf{2}}\\ \\text{and}\\ \\textbf{HSP2}\\ $ Copyright 2020 by RESPEC INC. and released under the *GNU AFFERO GENERAL PUBLIC LICENSE*" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This Notebook will compare the results of running HSPF and HSP$^2$ for the basic hydrology (PWATER, IWATER, and HYDR) to confirm the proper calculations of HSP$^2$\n", + "\n", + "Calleg is a real watershed and has\n", + "+ 27 IMPLND segments,\n", + "+ 129 PERLND segments,\n", + "+ 119 RCHRES segments,\n", + "+ 9 years of simulation time with hourly time steps (78,888 timesteps) from 1993-10-01 to 2002-10-01\n", + "\n", + "This Notebook assumes HSPF has been run and the HBN data saved to an HDF5 file in the **HSPF RUN** directory." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Required Python imports and setup" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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Python3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11....
hsp20.11.0a1
numpy1.26.4
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pandas2.3.3
matplotlib3.10.8
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\n", + "
" + ], + "text/plain": [ + " version\n", + "name \n", + "Python 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11....\n", + "hsp2 0.11.0a1\n", + "numpy 1.26.4\n", + "numba 0.64.0\n", + "pandas 2.3.3\n", + "matplotlib 3.10.8\n", + "os Linux-6.19.12-200.fc43.x86_64-x86_64-with-glib...\n", + "processor \n", + "Date/Time 2026-05-06T22:15:05.136710" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import os\n", + "\n", + "import pandas as pd\n", + "from matplotlib import pyplot as plt\n", + "\n", + "# Set display options for convenience, does't change the data\n", + "pd.options.display.max_rows = 150\n", + "pd.options.display.max_columns = 20\n", + "pd.options.display.float_format = (\n", + " \"{:.4f}\".format\n", + ") # display 4 digits after the decimal point\n", + "\n", + "%matplotlib inline\n", + "\n", + "from hsp2.hsp2 import main, versions\n", + "from hsp2.hsp2tools import readUCI, readWDM\n", + "\n", + "versions([\"matplotlib\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### If you get the HSP2 Not Found error:\n", + "```python\n", + "ModuleNotFoundError: No module named 'HSP2'\n", + "```\n", + "Then run the following terminal command with your local absolute path to this repo (enabled in this notebook with the `!` magic command), AND restart the kernel.\n", + "See https://github.com/LimnoTech/HSPsquared#4-add-your-hspsquared-path-to-anaconda-sites-packages" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/bin/bash: line 1: conda-develop: command not found\n" + ] + } + ], + "source": [ + "!conda-develop /Users/aaufdenkampe/Documents/Python/limno.HSPsquared/" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Convenient name strings to get to the data" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'default311'" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Confirm your active conda environment for this notebook.\n", + "os.environ[\"CONDA_DEFAULT_ENV\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "PosixPath('/var/home/timcera/programming/HSP_old/HSPsquared/tests/test10eq/HSP2results')" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from pathlib import Path\n", + "\n", + "# get current working directory\n", + "Path.cwd()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "wdmname = \"test10eq.wdm\"\n", + "uciname = \"test10eq.uci\"\n", + "HBN = \"test10_hspf.h5\"\n", + "hdfname = \"test10_hsp2_dev2WDM_6.h5\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Run HSP2 on the calleg" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "# Optional setting to testing Numba\n", + "os.environ[\"NUMBA_DISABLE_JIT\"] = \"0\" # '1' turns off Numba for this session only" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Create HDF5 file" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 4 µs, sys: 0 ns, total: 4 µs\n", + "Wall time: 8.58 µs\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_41909/1322036604.py:2: DeprecationWarning: Call to deprecated function readUCI (\n", + "\n", + "readUCI is deprecated and will be removed in a future release.\n", + "Use hsp2.hsp2io.control_file_readers.read_uci_parameters to read the parameters.\n", + "\n", + ").\n", + " readUCI(uciname, hdfname)\n", + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'CURV-DATA1'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though\n", + " check_attribute_name(name)\n", + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'CURV-DATA2'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though\n", + " check_attribute_name(name)\n", + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'CURV-DATA3'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though\n", + " check_attribute_name(name)\n", + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'CURV-DATA4'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though\n", + " check_attribute_name(name)\n" + ] + } + ], + "source": [ + "%time\n", + "readUCI(uciname, hdfname)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 3 µs, sys: 0 ns, total: 3 µs\n", + "Wall time: 4.53 µs\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_41909/1296374569.py:2: DeprecationWarning: Call to deprecated function readWDM (\n", + "\n", + "readWDM is deprecated and will be removed in a future release.\n", + "Use hsp2.hsp2io.time_series_readers.read_wdm_ts.read_wdm_ts to read the time\n", + "series data from the WDM file, and then write the data to an HDF file using\n", + "pandas.\n", + "\n", + ").\n", + " readWDM(wdmname, hdfname)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "39 reading from wdm\n", + "41 reading from wdm\n", + "42 reading from wdm\n", + "46 reading from wdm\n", + "113 reading from wdm\n", + "119 reading from wdm\n", + "121 reading from wdm\n", + "122 reading from wdm\n", + "123 reading from wdm\n", + "124 reading from wdm\n", + "125 reading from wdm\n", + "126 reading from wdm\n", + "127 reading from wdm\n", + "131 reading from wdm\n", + "132 reading from wdm\n", + "134 reading from wdm\n", + "135 reading from wdm\n", + "136 reading from wdm\n", + "140 reading from wdm\n" + ] + } + ], + "source": [ + "%time\n", + "readWDM(wdmname, hdfname)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Run" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Using profiler" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2026-05-06 22:16:37.19 Processing started for file test10_hsp2_dev2WDM_6.h5; saveall=True\n", + "Skipping un-typed siminfo\n", + "op_tokens has 186 elements, with 1 executable elements\n", + "2026-05-06 22:16:45.58 Simulation Start: 1976-01-01 00:00:00, Stop: 1977-01-01 00:00:00\n", + "2026-05-06 22:16:45.59 PERLND P001 DELT(minutes): 60\n", + "2026-05-06 22:16:46.32 SNOW\n", + "2026-05-06 22:16:47.47 PWATER\n", + "2026-05-06 22:16:48.04 PSTEMP\n", + "2026-05-06 22:16:48.08 PWTGAS\n", + "2026-05-06 22:16:48.19 RCHRES R001 DELT(minutes): 60\n", + "2026-05-06 22:16:48.21 HYDR\n", + "2026-05-06 22:16:59.39 ADCALC\n", + "2026-05-06 22:16:59.41 CONS\n", + "2026-05-06 22:16:59.55 HTRCH\n", + "2026-05-06 22:16:59.65 SEDTRN\n", + "2026-05-06 22:16:59.88 RQUAL\n", + "2026-05-06 22:17:01.15 GQUAL\n", + "2026-05-06 22:17:02.51 DISPLY D005 DELT(minutes): 60\n", + "2026-05-06 22:17:02.51 DISPLY D001 DELT(minutes): 60\n", + "2026-05-06 22:17:02.51 GENER G001 DELT(minutes): 60\n", + "2026-05-06 22:17:02.51 DISPLY D002 DELT(minutes): 60\n", + "2026-05-06 22:17:02.51 RCHRES R002 DELT(minutes): 60\n", + "2026-05-06 22:17:02.53 HYDR\n", + "2026-05-06 22:17:08.05 ADCALC\n", + "2026-05-06 22:17:08.05 CONS\n", + "2026-05-06 22:17:08.08 HTRCH\n", + "2026-05-06 22:17:08.09 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 22:17:08.15 SEDTRN\n", + "2026-05-06 22:17:08.16 Error count 3598: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-06 22:17:08.30 RQUAL\n", + "2026-05-06 22:17:09.21 GQUAL\n", + "2026-05-06 22:17:10.11 RCHRES R003 DELT(minutes): 60\n", + "2026-05-06 22:17:10.12 HYDR\n", + "2026-05-06 22:17:10.21 ADCALC\n", + "2026-05-06 22:17:10.21 CONS\n", + "2026-05-06 22:17:10.24 HTRCH\n", + "2026-05-06 22:17:10.25 Error count 3: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 22:17:10.31 SEDTRN\n", + "2026-05-06 22:17:10.32 Error count 513: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-06 22:17:10.46 RQUAL\n", + "2026-05-06 22:17:11.31 GQUAL\n", + "2026-05-06 22:17:12.10 RCHRES R004 DELT(minutes): 60\n", + "2026-05-06 22:17:12.14 HYDR\n", + "2026-05-06 22:17:12.23 ADCALC\n", + "2026-05-06 22:17:12.24 CONS\n", + "2026-05-06 22:17:12.27 HTRCH\n", + "2026-05-06 22:17:12.28 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 22:17:12.35 SEDTRN\n", + "2026-05-06 22:17:12.36 Error count 6720: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-06 22:17:12.50 RQUAL\n", + "2026-05-06 22:17:13.42 GQUAL\n", + "2026-05-06 22:17:14.39 PLTGEN L002 DELT(minutes): 60\n", + "2026-05-06 22:17:14.39 IMPLND I001 DELT(minutes): 60\n", + "2026-05-06 22:17:14.40 SNOW\n", + "2026-05-06 22:17:14.52 IWATER\n", + "2026-05-06 22:17:14.57 SOLIDS\n", + "2026-05-06 22:17:14.61 IWTGAS\n", + "2026-05-06 22:17:14.66 IQUAL\n", + "2026-05-06 22:17:14.72 RCHRES R005 DELT(minutes): 60\n", + "2026-05-06 22:17:14.74 HYDR\n", + "2026-05-06 22:17:14.84 ADCALC\n", + "2026-05-06 22:17:14.84 CONS\n", + "2026-05-06 22:17:14.87 HTRCH\n", + "2026-05-06 22:17:14.88 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 22:17:14.94 SEDTRN\n", + "2026-05-06 22:17:15.10 RQUAL\n", + "2026-05-06 22:17:16.04 GQUAL\n", + "2026-05-06 22:17:17.03 DISPLY D003 DELT(minutes): 60\n", + "2026-05-06 22:17:17.03 GENER G002 DELT(minutes): 60\n", + "2026-05-06 22:17:17.03 DISPLY D004 DELT(minutes): 60\n", + "2026-05-06 22:17:17.03 PLTGEN L001 DELT(minutes): 60\n", + "2026-05-06 22:17:17.03 Done; Run time is about 00:39.8 (mm:ss)\n", + "\n", + "\n", + " version\n", + "name \n", + "Python 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11....\n", + "hsp2 0.11.0a1\n", + "numpy 1.26.4\n", + "numba 0.64.0\n", + "pandas 2.3.3\n", + "jupyterlab 4.5.6\n", + "notebook n/a\n", + "os Linux-6.19.12-200.fc43.x86_64-x86_64-with-glib...\n", + "processor \n", + "Date/Time 2026-05-06T22:17:17.295665\n", + " \n", + "*** Profile printout saved to text file 'NumbaProfile.txt'.\n" + ] + } + ], + "source": [ + "%%prun -l 60 -T NumbaProfile.txt -q\n", + "main(hdfname, saveall=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 68262652 function calls (65636665 primitive calls) in 40.071 seconds\n", + "\n", + " ncalls tottime percall cumtime percall filename:lineno(function)\n", + "144274/144249 5.760 0.000 7.463 0.000 ffi.py:210(__call__)\n", + " 5 1.882 0.376 3.274 0.655 GQUAL.py:272(_gqual_)\n", + " 17440 1.169 0.000 1.250 0.000 {method '_create_carray' of 'tables.hdf5extension.Array' objects}\n", + " 14262 0.831 0.000 0.831 0.000 {method '_g_close' of 'tables.hdf5extension.Leaf' objects}\n", + "1119581/190161 0.735 0.000 1.000 0.000 ir.py:321(_rec_list_vars)\n", + "9557609/9553366 0.718 0.000 0.946 0.000 {built-in method builtins.isinstance}\n", + " 62933 0.529 0.000 0.529 0.000 {method '_g_get_objinfo' of 'tables.hdf5extension.Group' objects}\n", + " 3244 0.459 0.000 0.507 0.000 analysis.py:91(liveness)\n", + " 34115 0.451 0.000 0.835 0.000 {method '_g_setattr' of 'tables.hdf5extension.AttributeSet' objects}\n", + "2570214/2496161 0.427 0.000 4.038 0.000 {built-in method builtins.getattr}\n", + " 1224418 0.363 0.000 0.521 0.000 targetconfig.py:111(getter)\n", + " 77586 0.354 0.000 0.354 0.000 {method '_g_getattr' of 'tables.hdf5extension.AttributeSet' objects}\n", + " 669874 0.342 0.000 0.778 0.000 event.py:243(notify)\n", + " 7244 0.331 0.000 0.401 0.000 {method '_open_array' of 'tables.hdf5extension.Array' objects}\n", + "895246/458427 0.312 0.000 1.161 0.000 {method 'format' of 'str' objects}\n", + " 170385 0.306 0.000 0.388 0.000 _utils.py:24(deduplicate)\n", + " 130559 0.301 0.000 0.301 0.000 {method 'reduce' of 'numpy.ufunc' objects}\n", + " 1744 0.288 0.000 0.288 0.000 {tables.indexesextension.keysort}\n", + " 162059 0.282 0.000 1.845 0.000 typeddict.py:176(__getitem__)\n", + " 1744 0.266 0.000 0.276 0.000 {method '_fill_col' of 'tables.tableextension.Row' objects}\n", + " 5 0.244 0.049 0.244 0.049 RQUAL.py:331(_rqual_run)\n", + " 30374 0.236 0.000 0.243 0.000 types.py:164(__init__)\n", + " 7364 0.235 0.000 0.235 0.000 {method '_g_get_lchild_attr' of 'tables.hdf5extension.Group' objects}\n", + " 175311 0.232 0.000 0.855 0.000 values.py:557(_set_name)\n", + " 316828 0.230 0.000 1.035 0.000 event.py:209(broadcast)\n", + " 232 0.222 0.001 0.222 0.001 {method '_g_flush' of 'tables.hdf5extension.Leaf' objects}\n", + " 175311 0.219 0.000 0.623 0.000 _utils.py:16(register)\n", + " 98854 0.210 0.000 0.219 0.000 contextlib.py:104(__init__)\n", + " 87026 0.192 0.000 1.137 0.000 attributeset.py:277(__getattr__)\n", + "511884/404080 0.190 0.000 0.314 0.000 abstract.py:121(__hash__)\n", + " 311913 0.172 0.000 0.577 0.000 ssa.py:206(_run_ssa_block_pass)\n", + "486583/201457 0.163 0.000 1.175 0.000 _utils.py:44(__str__)\n", + " 124987 0.161 0.000 0.572 0.000 fromnumeric.py:71(_wrapreduction)\n", + " 53862 0.160 0.000 0.856 0.000 targetconfig.py:200()\n", + " 133115 0.153 0.000 0.925 0.000 values.py:544(_to_string)\n", + "29153/2455 0.152 0.000 8.257 0.003 node.py:182(__init__)\n", + " 17016 0.152 0.000 0.194 0.000 targetconfig.py:57(top_or_none)\n", + " 5232 0.149 0.000 0.149 0.000 {method '_g_write_slice' of 'tables.hdf5extension.Array' objects}\n", + " 1572398 0.140 0.000 0.223 0.000 {method 'get' of 'dict' objects}\n", + "359320/358330 0.138 0.000 0.391 0.000 _utils.py:54(get_reference)\n", + " 200842 0.137 0.000 0.690 0.000 attributeset.py:47(issysattrname)\n", + " 192569 0.137 0.000 0.306 0.000 file.py:356(register_node)\n", + " 334937 0.135 0.000 0.179 0.000 event.py:270(on_end)\n", + " 162059 0.132 0.000 0.186 0.000 typeddict.py:37(_getitem)\n", + " 3778 0.128 0.000 0.137 0.000 analysis.py:81(def_reach)\n", + " 1976 0.127 0.000 0.756 0.000 analysis.py:23(compute_use_defs)\n", + " 158414 0.126 0.000 0.850 0.000 event.py:404(end_event)\n", + " 129269 0.126 0.000 0.974 0.000 instructions.py:13(__init__)\n", + "59102/58508 0.126 0.000 0.155 0.000 values.py:455(_get_reference)\n", + " 34115 0.121 0.000 1.476 0.000 attributeset.py:379(_g__setattr)\n", + " 15258 0.119 0.000 1.441 0.000 attributeset.py:188(__init__)\n", + " 158414 0.117 0.000 0.666 0.000 event.py:390(start_event)\n", + " 708915 0.116 0.000 0.117 0.000 serialize.py:30(_numba_unpickle)\n", + "1250044/1124604 0.114 0.000 0.462 0.000 {built-in method builtins.len}\n", + " 192512 0.113 0.000 1.620 0.000 file.py:370(cache_node)\n", + " 316828 0.113 0.000 0.237 0.000 event.py:100(__init__)\n", + " 919089 0.109 0.000 0.109 0.000 {method 'startswith' of 'str' objects}\n", + " 254027 0.108 0.000 0.237 0.000 group.py:800(__setattr__)\n", + "168937/89283 0.107 0.000 3.463 0.000 file.py:383(get_node)\n", + "6660/4869 0.105 0.000 9.482 0.002 functions.py:284(get_call_type)\n", + "Cum Sum 55.58%\n" + ] + } + ], + "source": [ + "with open(\"NumbaProfile.txt\", \"r\") as f:\n", + " for line in f:\n", + " total = float(line.split()[7])\n", + " print(line)\n", + " f.readline()\n", + " f.readline()\n", + " f.readline()\n", + " f.readline()\n", + " print(f.readline().rstrip())\n", + " break\n", + " sum = 0.0\n", + " for line in f:\n", + " sum += float(line.split()[1])\n", + " print(line.rstrip())\n", + "\n", + " # Pareto rule, look for calls cumsum to 80% time, ignore the rest\n", + " if sum >= 0.8 * total:\n", + " break\n", + "print(f\"Cum Sum {100.0 * sum/total:.2f}%\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## BELOW HERE: Output from Steve's testing" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Normal run" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2026-05-06 22:17:57.04 Processing started for file test10_hsp2_dev2WDM_6.h5; saveall=True\n", + "Skipping un-typed siminfo\n", + "op_tokens has 186 elements, with 1 executable elements\n", + "2026-05-06 22:17:59.72 Simulation Start: 1976-01-01 00:00:00, Stop: 1977-01-01 00:00:00\n", + "2026-05-06 22:17:59.72 PERLND P001 DELT(minutes): 60\n", + "2026-05-06 22:17:59.75 SNOW\n", + "2026-05-06 22:17:59.84 PWATER\n", + "2026-05-06 22:17:59.98 PSTEMP\n", + "2026-05-06 22:18:00.01 PWTGAS\n", + "2026-05-06 22:18:00.10 RCHRES R001 DELT(minutes): 60\n", + "2026-05-06 22:18:00.11 HYDR\n", + "2026-05-06 22:18:00.21 ADCALC\n", + "2026-05-06 22:18:00.21 CONS\n", + "2026-05-06 22:18:00.25 HTRCH\n", + "2026-05-06 22:18:00.31 SEDTRN\n", + "2026-05-06 22:18:00.46 RQUAL\n", + "2026-05-06 22:18:01.46 GQUAL\n", + "2026-05-06 22:18:02.29 DISPLY D005 DELT(minutes): 60\n", + "2026-05-06 22:18:02.29 DISPLY D001 DELT(minutes): 60\n", + "2026-05-06 22:18:02.29 GENER G001 DELT(minutes): 60\n", + "2026-05-06 22:18:02.29 DISPLY D002 DELT(minutes): 60\n", + "2026-05-06 22:18:02.29 RCHRES R002 DELT(minutes): 60\n", + "2026-05-06 22:18:02.30 HYDR\n", + "2026-05-06 22:18:02.37 ADCALC\n", + "2026-05-06 22:18:02.37 CONS\n", + "2026-05-06 22:18:02.40 HTRCH\n", + "2026-05-06 22:18:02.40 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 22:18:02.45 SEDTRN\n", + "2026-05-06 22:18:02.45 Error count 3598: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-06 22:18:02.56 RQUAL\n", + "2026-05-06 22:18:03.28 GQUAL\n", + "2026-05-06 22:18:03.87 RCHRES R003 DELT(minutes): 60\n", + "2026-05-06 22:18:03.88 HYDR\n", + "2026-05-06 22:18:03.94 ADCALC\n", + "2026-05-06 22:18:03.94 CONS\n", + "2026-05-06 22:18:03.97 HTRCH\n", + "2026-05-06 22:18:03.97 Error count 3: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 22:18:04.02 SEDTRN\n", + "2026-05-06 22:18:04.02 Error count 513: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-06 22:18:04.13 RQUAL\n", + "2026-05-06 22:18:04.80 GQUAL\n", + "2026-05-06 22:18:05.31 RCHRES R004 DELT(minutes): 60\n", + "2026-05-06 22:18:05.33 HYDR\n", + "2026-05-06 22:18:05.40 ADCALC\n", + "2026-05-06 22:18:05.41 CONS\n", + "2026-05-06 22:18:05.43 HTRCH\n", + "2026-05-06 22:18:05.44 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 22:18:05.49 SEDTRN\n", + "2026-05-06 22:18:05.49 Error count 6720: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-06 22:18:05.60 RQUAL\n", + "2026-05-06 22:18:06.33 GQUAL\n", + "2026-05-06 22:18:06.94 PLTGEN L002 DELT(minutes): 60\n", + "2026-05-06 22:18:06.94 IMPLND I001 DELT(minutes): 60\n", + "2026-05-06 22:18:06.95 SNOW\n", + "2026-05-06 22:18:07.03 IWATER\n", + "2026-05-06 22:18:07.06 SOLIDS\n", + "2026-05-06 22:18:07.08 IWTGAS\n", + "2026-05-06 22:18:07.10 IQUAL\n", + "2026-05-06 22:18:07.14 RCHRES R005 DELT(minutes): 60\n", + "2026-05-06 22:18:07.15 HYDR\n", + "2026-05-06 22:18:07.23 ADCALC\n", + "2026-05-06 22:18:07.23 CONS\n", + "2026-05-06 22:18:07.25 HTRCH\n", + "2026-05-06 22:18:07.26 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 22:18:07.31 SEDTRN\n", + "2026-05-06 22:18:07.42 RQUAL\n", + "2026-05-06 22:18:08.16 GQUAL\n", + "2026-05-06 22:18:08.78 DISPLY D003 DELT(minutes): 60\n", + "2026-05-06 22:18:08.78 GENER G002 DELT(minutes): 60\n", + "2026-05-06 22:18:08.78 DISPLY D004 DELT(minutes): 60\n", + "2026-05-06 22:18:08.78 PLTGEN L001 DELT(minutes): 60\n", + "2026-05-06 22:18:08.78 Done; Run time is about 00:11.7 (mm:ss)\n", + "\n", + "\n", + " version\n", + "name \n", + "Python 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11....\n", + "hsp2 0.11.0a1\n", + "numpy 1.26.4\n", + "numba 0.64.0\n", + "pandas 2.3.3\n", + "jupyterlab 4.5.6\n", + "notebook n/a\n", + "os Linux-6.19.12-200.fc43.x86_64-x86_64-with-glib...\n", + "processor \n", + "Date/Time 2026-05-06T22:18:08.798107\n" + ] + } + ], + "source": [ + "main(hdfname, saveall=True)" + ] + }, + { + "cell_type": "raw", + "metadata": {}, + "source": [ + "Development note:\n", + "\n", + "SAVEALL = FALSE (new SAVE table for hot restart by default)\n", + "2017-04-16 09:05:26.10 Run completed\n", + "1 loop, best of 3: 32.3 s per loop\n", + "Ratio of HSP2/HSPF 32.3/24.4 = 1.3\n", + "\n", + "SAVEALL = TRUE\n", + "2017-04-11 10:18:22.86 Run completed\n", + "1 loop, best of 3: 38.1 s per loop\n", + "Ratio of HSP2/HSPF 38.1/24.4 = 1.6\n", + "\n", + "04/25/2020 New Python 3 version is about 1.8x slower than HSPF - even when all tricks used.\n", + "However, the new Numba Dict and List implementations are SLOW in the code outside numba - on the order\n", + "of us vs ns which can easily explain a slight difference. Spotted warning messages in HSP2 log file.\n", + "\n", + "05/04/2020 new Calleg testing For reference the run time of HSPF is 32.2 seconds. Using to_hdf()\n", + "With Flush - create test10.h5 Run time is about 01:56.9 size 2,136,787 KB\n", + " existing test10.h5 Run time is about 01:15.2 size 2,136,836 KB\n", + "NO Flush - create test10.h5 Run time is about 01:19.1 size 2,136,787 KB Warning messages seen for closed node\n", + " existing test10.h5 Run time is about 01:14.4 size 2,236,836 KB\n", + "BLOSC - create test10.h5 Run time is about 01:29.0 size 1,156,499 KB No Flush, but no warning messages (Blosc in save_timeseries only)\n", + " existing test10.h5 Run time is about 01:26.2 size 1,156,796 KB\n", + " \n", + "BLOSC (wdm & main)\n", + " - create test10.h5 Run time is about 01:30.8 size 1,050,043 KB No Flush, no warning messages.\n", + " existing test10.h5 Run time is about 01:26.0 size 1,060,340 KB\n", + " existing test10.h5 Run time is about 01:23.6 (5/8/2020)\n", + " existing test10.h5 Run time is about 01:19.7 (5/8/2020) - no kernel restart from last run\n", + " \n", + "NO Numba - existing test10.h5 Run time is about 13:25.1 or x9.4 slower than with Numba.\n", + "\n", + "So current timing results show HSP2 is 2.8x slower than HSPF for this problem.\n", + "\n", + "Also tried return to store.put() with BLOSC (wdm & main) instead of to_hdf()\n", + " - existing test10.h5 Run time is about 01:28.0 but found warning messages for closed node. Speedup not worth it.\n", + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Read Summary from HBN file" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Find the higest frequency data available." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [ + { + "ename": "FileNotFoundError", + "evalue": "File test10_hspf.h5 does not exist", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[19], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m summary \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_hdf\u001b[49m\u001b[43m(\u001b[49m\u001b[43mHBN\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mSUMMARY\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2\u001b[0m summary\u001b[38;5;241m.\u001b[39mFrequency\u001b[38;5;241m.\u001b[39munique()\n", + "File \u001b[0;32m~/miniconda3/envs/default311/lib/python3.11/site-packages/pandas/io/pytables.py:437\u001b[0m, in \u001b[0;36mread_hdf\u001b[0;34m(path_or_buf, key, mode, errors, where, start, stop, columns, iterator, chunksize, **kwargs)\u001b[0m\n\u001b[1;32m 434\u001b[0m exists \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 436\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m exists:\n\u001b[0;32m--> 437\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFile \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpath_or_buf\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m does not exist\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 439\u001b[0m store \u001b[38;5;241m=\u001b[39m HDFStore(path_or_buf, mode\u001b[38;5;241m=\u001b[39mmode, errors\u001b[38;5;241m=\u001b[39merrors, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 440\u001b[0m \u001b[38;5;66;03m# can't auto open/close if we are using an iterator\u001b[39;00m\n\u001b[1;32m 441\u001b[0m \u001b[38;5;66;03m# so delegate to the iterator\u001b[39;00m\n", + "\u001b[0;31mFileNotFoundError\u001b[0m: File test10_hspf.h5 does not exist" + ] + } + ], + "source": [ + "summary = pd.read_hdf(HBN, \"SUMMARY\")\n", + "summary.Frequency.unique()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "So the best available is monthly data." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Automate checking by output flow" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "def hsp2key(hspfkey):\n", + " op, activity, segment, _ = hspfkey.split(\"_\")\n", + " return f\"RESULTS/{op}_{op[0]}{segment:0>3s}/{activity}\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "def monthlyoutflow(keys, flowname, how=\"sum\"):\n", + " concat = []\n", + " for key in keys.index:\n", + " hsp2 = (\n", + " pd.read_hdf(hdfname, hsp2key(key))[flowname].resample(\"M\").sum().to_numpy()\n", + " )\n", + " hspf = pd.read_hdf(HBN, key)[flowname].to_numpy()\n", + "\n", + " hsp2sum = hsp2.sum()\n", + " hspfsum = hspf.sum()\n", + "\n", + " segment = key.split(\"_\")[2]\n", + "\n", + " data = pd.DataFrame(index=[segment])\n", + " data[\"HSP2_SUM\"] = hsp2sum\n", + " data[\"HSPF_SUM\"] = hspfsum\n", + " data[\"Percent diff\"] = 100 * (hspfsum - hsp2sum) / hspfsum\n", + " data[\"abs(Percent diff)\"] = 100 * abs(hspfsum - hsp2sum) / hspfsum\n", + "\n", + " concat.append(data)\n", + "\n", + " return pd.concat(concat).sort_values(by=[\"abs(Percent diff)\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Define a function to plot HSPF and HSP2 data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "def plot(operation, ils, activity, name, how=\"sum\"):\n", + " hspf = f\"{operation}_{activity}_{ils:0>3s}_4\"\n", + " tshspf = read_hdf(HBN, hspf)[name]\n", + "\n", + " hsp2 = f\"RESULTS/{operation}_{operation[0]}{ils:0>3s}/{activity}\"\n", + " if how == \"sum\":\n", + " tshsp2 = (\n", + " read_hdf(hdfname, hsp2)[f\"{name}_{how}\"].resample(\"M\").sum().shift(1, \"D\")\n", + " )\n", + " elif how == \"last\":\n", + " tshsp2 = (\n", + " read_hdf(hdfname, hsp2)[f\"{name}_{how}\"].resample(\"M\").last().shift(1, \"D\")\n", + " )\n", + "\n", + " plt.figure(figsize=(10, 8))\n", + " plt.plot(tshspf.index, tshspf, label=\"HSPF\", color=\"r\")\n", + " plt.plot(tshsp2.index, tshsp2, label=\"HSP2\", color=\"b\")\n", + " plt.legend()\n", + " plt.title(f\"{operation} {operation[0]}{ils:0>3s}, {activity} {name}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "def scatter(operation, ils, activity, name, how=\"sum\"):\n", + " hspf = f\"{operation}_{activity}_{ils:0>3s}_4\"\n", + " tshspf = read_hdf(HBN, hspf)[name]\n", + "\n", + " hsp2 = f\"RESULTS/{operation}_{operation[0]}{ils:0>3s}/{activity}\"\n", + " if how == \"sum\":\n", + " tshsp2 = (\n", + " read_hdf(hdfname, hsp2)[f\"{name}_{how}\"].resample(\"M\").sum().shift(1, \"D\")\n", + " )\n", + " elif how == \"last\":\n", + " tshsp2 = (\n", + " read_hdf(hdfname, hsp2)[f\"{name}_{how}\"].resample(\"M\").last().shift(1, \"D\")\n", + " )\n", + "\n", + " plt.scatter(tshspf, tshsp2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### IMPLND" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "implndkeys = summary[(summary.Frequency == \"Monthly\") & (summary.Operation == \"IMPLND\")]\n", + "implndkeys[0:10]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "delta = monthlyoutflow(implndkeys, \"SURO\")\n", + "delta" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Look at the statistics for the percent difference column" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "delta.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "delta[\"Percent diff\"].hist()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "ils = delta.index[-1]\n", + "print(\"WORST IMPLND SEGMENT IS\", ils)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### IMPLND IWATER SURO, Monthly" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"IMPLND\", ils, \"IWATER\", \"SURO\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"IMPLND\", ils, \"IWATER\", \"SURO\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### IMPLND IWATER IMPEV, Monthly" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"IMPLND\", ils, \"IWATER\", \"IMPEV\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"IMPLND\", ils, \"IWATER\", \"IMPEV\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### IMPLND IWATER PET, Monthly" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"IMPLND\", ils, \"IWATER\", \"PET\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"IMPLND\", ils, \"IWATER\", \"PET\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### IMPLND IWATER RETS, Monthly" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"IMPLND\", ils, \"IWATER\", \"RETS\", \"last\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"IMPLND\", ils, \"IWATER\", \"RETS\", \"last\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### IMPLND IWATER SUPY, Monthly" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"IMPLND\", ils, \"IWATER\", \"SUPY\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"IMPLND\", ils, \"IWATER\", \"SUPY\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### IMPLND IWATER SURS, Monthly" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"IMPLND\", ils, \"IWATER\", \"SURS\", \"last\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"IMPLND\", ils, \"IWATER\", \"SURS\", \"last\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Automate checking PERLNDs for PERO" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "perlndkeys = summary[(summary.Frequency == \"Monthly\") & (summary.Operation == \"PERLND\")]\n", + "perlndkeys[0:10]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true, + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "delta = monthlyoutflow(perlndkeys, \"PERO\")\n", + "delta" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Look at the statistics for the percent difference column" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "delta.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "delta[\"Percent diff\"].hist()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "pls = delta.index[-1]\n", + "print(\"WORST PERLND SEGMENT IS\", pls)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### PERLND PWATER AGWLI" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"PERLND\", pls, \"PWATER\", \"AGWLI\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"PERLND\", pls, \"PWATER\", \"AGWLI\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### PERLND PWATER SURLI" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"PERLND\", pls, \"PWATER\", \"SURLI\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"PERLND\", pls, \"PWATER\", \"SURLI\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### PERLND PWATER AGWO" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"PERLND\", pls, \"PWATER\", \"AGWO\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"PERLND\", pls, \"PWATER\", \"AGWO\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### PERLND PWATER BASET" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"PERLND\", pls, \"PWATER\", \"BASET\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"PERLND\", pls, \"PWATER\", \"BASET\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### PERLND PWATER CEPE" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"PERLND\", pls, \"PWATER\", \"CEPE\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"PERLND\", pls, \"PWATER\", \"CEPE\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### PERLND PWATER IFWI" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"PERLND\", pls, \"PWATER\", \"IFWI\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"PERLND\", pls, \"PWATER\", \"IFWI\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### PERLND PWATER IFWO" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"PERLND\", pls, \"PWATER\", \"IFWO\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"PERLND\", pls, \"PWATER\", \"IFWO\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### PERLND PWATER IGWI" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"PERLND\", pls, \"PWATER\", \"IGWI\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"PERLND\", pls, \"PWATER\", \"IGWI\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### PERLND PWATER INFIL" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"PERLND\", pls, \"PWATER\", \"INFIL\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"PERLND\", pls, \"PWATER\", \"INFIL\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### PERLND PWATER LZET" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"PERLND\", pls, \"PWATER\", \"LZET\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"PERLND\", pls, \"PWATER\", \"LZET\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### PERLND PWATER PERC" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"PERLND\", pls, \"PWATER\", \"PERC\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"PERLND\", pls, \"PWATER\", \"PERC\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### PERLND PWATER PERO" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"PERLND\", pls, \"PWATER\", \"PERO\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"PERLND\", pls, \"PWATER\", \"PERO\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### PERLND PWATER PERS" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"PERLND\", pls, \"PWATER\", \"PERS\", \"last\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"PERLND\", pls, \"PWATER\", \"PERS\", \"last\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### PERLND PWATER PET, Monthly" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"PERLND\", pls, \"PWATER\", \"PET\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"PERLND\", pls, \"PWATER\", \"PET\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### PERLND PWATER SUPY" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"PERLND\", pls, \"PWATER\", \"SUPY\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"PERLND\", pls, \"PWATER\", \"SUPY\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### PERLND PWATER SURO" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"PERLND\", pls, \"PWATER\", \"SURO\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"PERLND\", pls, \"PWATER\", \"SURO\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### PERLND PWATER TAET" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"PERLND\", pls, \"PWATER\", \"TAET\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"PERLND\", pls, \"PWATER\", \"TAET\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### PERLND PWATER UZET" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"PERLND\", pls, \"PWATER\", \"UZET\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"PERLND\", pls, \"PWATER\", \"UZET\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### PERLND PWATER UZI" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"PERLND\", pls, \"PWATER\", \"UZI\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"PERLND\", pls, \"PWATER\", \"UZI\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## RCHRES" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true, + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "rchreskeys = summary[(summary.Frequency == \"Monthly\") & (summary.Operation == \"RCHRES\")]\n", + "rchreskeys[0:10]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "delta = monthlyoutflow(rchreskeys, \"ROVOL\")\n", + "delta" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Look at the statistics for the percent difference column" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "delta.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "delta[\"Percent diff\"].hist()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "rid = delta.index[-1]\n", + "print(\"WORST RCHRES SEGMENT IS\", rid)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### RCHRES HYDR IVOL" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"RCHRES\", rid, \"HYDR\", \"IVOL\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"RCHRES\", rid, \"HYDR\", \"IVOL\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### RCHRES HYDR PRSUPY" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"RCHRES\", rid, \"HYDR\", \"PRSUPY\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"RCHRES\", rid, \"HYDR\", \"PRSUPY\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### RCHRES HYDR ROVOL" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"RCHRES\", rid, \"HYDR\", \"ROVOL\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"RCHRES\", rid, \"HYDR\", \"ROVOL\", \"sum\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### RCHRES HYDR VOL" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"RCHRES\", rid, \"HYDR\", \"VOL\", \"last\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"RCHRES\", rid, \"HYDR\", \"VOL\", \"last\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### RCHRES HYDR VOLEV" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "plot(\"RCHRES\", rid, \"HYDR\", \"VOLEV\", \"sum\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "scatter(\"RCHRES\", rid, \"HYDR\", \"VOLEV\", \"sum\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.11" + }, + "toc-showmarkdowntxt": false + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tests/test10eq/HSP2results/test10eq.json b/tests/test10eq/HSP2results/test10eq.json new file mode 100644 index 00000000..80bae7ed --- /dev/null +++ b/tests/test10eq/HSP2results/test10eq.json @@ -0,0 +1,23 @@ +{ + "RCHRES_R005": { + "name": "RCHRES_R005", + "object_class": "ModelObject", + "value": "0", + "RSED4": { + "name": "RSED4", + "object_class": "Equation", + "equation": "RSED4 + 250000.0" + }, + "RSED5": { + "name": "RSED5", + "object_class": "Equation", + "equation": "RSED5 + 689000.0" + }, + "RSED6": { + "name": "RSED6", + "object_class": "Equation", + "equation": "RSED6 + 401000.0" + } + } +} + diff --git a/tests/test10eq/HSP2results/test10eq.uci b/tests/test10eq/HSP2results/test10eq.uci new file mode 100644 index 00000000..df562c22 --- /dev/null +++ b/tests/test10eq/HSP2results/test10eq.uci @@ -0,0 +1,1015 @@ +RUN + +GLOBAL + Version 11 test run: PERLND and IMPLND w/ RCHRES (sediment, water quality) + START 1976 END 1976 + RUN INTERP OUTPUT LEVEL 3 + RESUME 0 RUN 1 UNIT SYSTEM 1 +END GLOBAL + + *** This test run uses MASS-LINK and SCHEMATIC blocks *** + +FILES + ***<----FILE NAME-------------------------------------------------> +WDM 21 test10eq.wdm +MESSU 22 test10eq.ech + 01 test10eq.out + 66 test10eq.d66 + 94 test10eq.p94 + 95 test10eq.p95 +BINO 81 test10eqP.hbn +BINO 82 test10eqI.hbn +BINO 83 test10eqR.hbn +END FILES + +OPN SEQUENCE + INGRP INDELT 01:00 + PERLND 1 + RCHRES 1 + DISPLY 5 + DISPLY 1 + GENER 1 + DISPLY 2 + RCHRES 2 + RCHRES 3 + RCHRES 4 + PLTGEN 2 + IMPLND 1 + RCHRES 5 + DISPLY 3 + GENER 2 + DISPLY 4 + PLTGEN 1 + END INGRP +END OPN SEQUENCE + +PERLND + ACTIVITY + Active Sections (1=Active, 0=Inactive) *** + # - # ATMP SNOW PWAT SED PST PWG PQAL MSTL PEST NITR PHOS TRAC *** + 1 1 1 1 1 + END ACTIVITY + + PRINT-INFO + Print-flags *** PIVL PYR + # - # ATMP SNOW PWAT SED PST PWG PQAL MSTL PEST NITR PHOS TRAC *** + 1 4 4 4 4 12 + END PRINT-INFO + + BINARY-INFO +*** < PLS> Binary Output Flags PIVL PYR +*** x - x ATMP SNOW PWAT SED PST PWG PQAL MSTL PEST NITR PHOS TRAC + 1 2 2 2 2 2 1 12 + END BINARY-INFO + + GEN-INFO + <-------Name-------> Unit-systems Printer BinaryOut *** + # - # t-series Engl Metr Engl Metr *** + in out *** + 1 BICKNELL FARM 1 1 1 0 81 0 + END GEN-INFO + + *** Section SNOW *** + + ICE-FLAG + 0= Ice formation not simulated, 1= Simulated *** + # - #ICEFG *** + 1 1 + END ICE-FLAG + + SNOW-PARM1 + Snow input info: Part 1 *** + # - # LAT MELEV SHADE SNOWCF COVIND *** + 1 42. 520. 0.0 1.45 0.5 + END SNOW-PARM1 + + SNOW-PARM2 + Snow input info: Part 2 *** + # - # RDCSN TSNOW SNOEVP CCFACT MWATER MGMELT *** + 1 0.12 32. 0.05 0.5 0.08 0.0001 + END SNOW-PARM2 + + SNOW-INIT1 + Initial snow conditions: Part 1 *** + # - # PACKSNOW PACKICE PACKWATER RDENPF DULL PAKTMP *** + 1 1.4 0.2 0.1 0.2 375. 27.5 + END SNOW-INIT1 + + SNOW-INIT2 + Initial snow conditions: Part 2 *** + # - # COVINX XLNMLT SKYCLR *** + 1 0.50 0.0 1.0 + END SNOW-INIT2 + + *** Section PWATER *** + + PWAT-PARM1 + PWATER variable monthly parameter value flags *** + # - # CSNO RTOP UZFG VCS VUZ VNN VIFW VIRC VLE *** + 1 1 0 0 1 1 1 0 0 1 + END PWAT-PARM1 + + PWAT-PARM2 + *** PWATER input info: Part 2 + # - # ***FOREST LZSN INFILT LSUR SLSUR KVARY AGWRC + 1 0.010 8.0 0.150 250. 0.050 0.5 0.98 + END PWAT-PARM2 + + PWAT-PARM3 + *** PWATER input info: Part 3 + # - # ***PETMAX PETMIN INFEXP INFILD DEEPFR BASETP AGWETP + 1 40. 35. 2.0 2.0 0.10 0.0 0.08 + END PWAT-PARM3 + + PWAT-PARM4 + PWATER input info: Part 4 *** + # - # CEPSC UZSN NSUR INTFW IRC LZETP *** + 1 0.01 0.1 1.0 0.60 + END PWAT-PARM4 + + MON-INTERCEP + Only required if VCSFG=1 in PWAT-PARM1 *** + # - # Interception storage capacity at start of each month *** + JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** + 1 0.04 0.04 0.03 0.03 0.03 0.03 0.10 0.17 0.19 0.14 0.05 0.04 + END MON-INTERCEP + + MON-UZSN + Only required if VUZFG=1 in PWAT-PARM1 *** + # - # Upper zone storage at start of each month *** + JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** + 1 0.4 0.4 0.4 0.4 1.6 1.1 1.1 1.3 1.3 1.3 1.1 0.9 + END MON-UZSN + + MON-MANNING + Only required if VNNFG=1 in PWAT-PARM1 *** + # - # Manning's n for overland flow at start of each month *** + JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** + 1 0.30 0.30 0.30 0.30 0.27 0.25 0.25 0.25 0.25 0.25 0.35 0.33 + END MON-MANNING + + MON-LZETPARM + Only required if VLEFG=1 in PWAT-PARM1 *** + # - # Lower zone ET parameter at start of each month *** + JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** + 1 0.20 0.20 0.20 0.23 0.23 0.25 0.60 0.80 0.75 0.50 0.30 0.20 + END MON-LZETPARM + + PWAT-STATE1 + *** Initial conditions at start of simulation + # - # *** CEPS SURS UZS IFWS LZS AGWS GWVS + 1 0.05 0.0 0.15 0.0 4.0 0.05 0.05 + END PWAT-STATE1 + + *** Section PSTEMP *** + + PSTEMP-PARM2 + *** + # - # ASLT BSLT ULTP1 ULTP2 LGTP1 LGTP2 *** + 1 14.5 .365 1.2 4.0 1.2 6.0 + END PSTEMP-PARM2 + + *** Section PWTGAS *** + + PWT-PARM2 + *** + # - # ELEV IDOXP ICO2P ADOXP ACO2P *** + 1 500. 6. .05 5. .05 + END PWT-PARM2 +END PERLND + +IMPLND + ACTIVITY + Active Sections *** + # - # ATMP SNOW IWAT SLD IWG IQAL *** + 1 1 1 1 1 1 + END ACTIVITY + + PRINT-INFO + Print-flags *** + # - # ATMP SNOW IWAT SLD IWG IQAL PIVL PYR *** + 1 4 4 4 4 4 12 + END PRINT-INFO + + BINARY-INFO +*** **** Binary-Output-flags **** PIVL PYR +*** x - x ATMP SNOW IWAT SLD IWG IQAL ********* + 1 2 2 2 2 2 1 12 + END BINARY-INFO + + GEN-INFO + <-------Name-------> Unit-systems Printer BinaryOut *** + # - # t-series Engl Metr Engl Metr *** + in out *** + 1 DONIGIAN INDUSTRY 1 1 1 0 82 0 + END GEN-INFO + + *** Section SNOW *** + + ICE-FLAG + 0= Ice formation not simulated, 1= Simulated *** + # - #ICEFG *** + 1 1 + END ICE-FLAG + + SNOW-PARM1 + Snow input info: Part 1 *** + # - # LAT MELEV SHADE SNOWCF COVIND *** + 1 42. 450. 0.0 1.45 0.5 + END SNOW-PARM1 + + SNOW-PARM2 + Snow input info: Part 2 *** + # - # RDCSN TSNOW SNOEVP CCFACT MWATER MGMELT *** + 1 0.12 32. 0.05 0.5 0.08 0.0001 + END SNOW-PARM2 + + SNOW-INIT1 + Initial snow conditions: Part 1 *** + # - # PACKSNOW PACKICE PACKWATER RDENPF DULL PAKTMP *** + 1 1.4 0.2 0.1 0.2 375. 27.5 + END SNOW-INIT1 + + SNOW-INIT2 + Initial snow conditions: Part 2 *** + # - # COVINX XLNMLT SKYCLR *** + 1 0.50 0.0 1.0 + END SNOW-INIT2 + + *** Section IWATER *** + + IWAT-PARM1 + Flags *** + # - # CSNO RTOP VRS VNN RTLI *** + 1 1 1 + END IWAT-PARM1 + + IWAT-PARM2 + *** + # - # LSUR SLSUR NSUR RETSC *** + 1 200. .010 .010 .01 + END IWAT-PARM2 + + IWAT-PARM3 + *** + # - # PETMAX PETMIN *** + 1 40. 35. + END IWAT-PARM3 + + IWAT-STATE1 + IWATER state variables *** + # - # RETS SURS *** + 1 .01 .01 + END IWAT-STATE1 + + *** Section SOLIDS *** + + SLD-PARM2 + *** + # - # KEIM JEIM ACCSDP REMSDP *** + 1 .08 1.9 .01 .5 + END SLD-PARM2 + + SLD-STOR + Solids storage (tons/acre) *** + # - # *** + 1 0.2 + END SLD-STOR + + *** Section IWTGAS *** + + IWT-PARM2 + *** + # - # ELEV AWTF BWTF *** + 1 410. 40. 0.8 + END IWT-PARM2 + + *** Section IQUAL *** + + NQUALS + *** + # - #NQUAL *** + 1 1 + END NQUALS + + QUAL-PROPS + Identifiers and Flags *** + # - #<--qualid--> QTID QSD VPFW QSO VQO *** + 1 COD LB 1 1 + END QUAL-PROPS + + QUAL-INPUT + Storage on surface and nonseasonal parameters *** + # - # SQO POTFW ACQOP SQOLIM WSQOP *** + 1 1.20 .175 .02 2.0 1.7 + END QUAL-INPUT +END IMPLND + +RCHRES + ACTIVITY + RCHRES Active Sections (1=Active, 0=Inactive) *** + # - # HYFG ADFG CNFG HTFG SDFG GQFG OXFG NUFG PKFG PHFG *** + 1 5 1 1 1 1 1 1 1 1 1 1 + END ACTIVITY + + PRINT-INFO + RCHRES Print-flags *** + # - # HYDR ADCA CONS HEAT SED GQL OXRX NUTR PLNK PHCB PIVL PYR *** + 1 4 5 5 5 5 5 5 5 5 5 5 12 + 5 4 4 4 4 4 4 4 4 4 4 12 + END PRINT-INFO + + BINARY-INFO +*** RCHRES Binary Output level flags +*** x - x HYDR ADCA CONS HEAT SED GQL OXRX NUTR PLNK PHCB PIVL PYR + 1 5 2 2 2 2 2 2 2 2 2 2 1 12 + END BINARY-INFO + + GEN-INFO + RCHRES<-------Name------->Nexit Unit Systems Printer BinaryOut *** + # - # t-series Engl Metr LKFG Engl Metr *** + in out *** + 1 MEIER POND 2 1 1 1 0 1 83 0 + 2 OUTLET 1 1 1 1 0 0 83 0 + 3 SPILLWAY 1 1 1 1 0 0 83 0 + 4 UPPER KITTLE CREEK 1 1 1 1 0 0 83 0 + 5 LOWER KITTLE CREEK 1 1 1 1 0 0 83 0 + END GEN-INFO + + *** Section HYDR *** + + HYDR-PARM1 + RCHRES Flags for HYDR section *** + # - # VC A1 A2 A3 ODFVFG for each ODGTFG for each *** FUNCT for each + FG FG FG FG possible exit possible exit *** possible exit + 1 2 3 4 5 1 2 3 4 5 *** + + 1 1 1 1 -1 6 + 2 5 1 1 1 4 + END HYDR-PARM1 + + HYDR-PARM2 + RCHRES *** + # - # DSN FTBN LEN DELTH STCOR KS DB50 *** + 1 00 1 0.5 1. .5 + 2 00 2 0.25 20. .5 + 3 00 3 0.25 30. .5 + 4 00 4 2.0 40. .5 + 5 00 5 3.0 40. .5 + END HYDR-PARM2 + + HYDR-INIT + RCHRES Initial conditions for HYDR section *** + # - # VOL Initial value of COLIND *** Initial value of OUTDGT + (ac-ft) for each possible exit *** for each possible exit + EX1 EX2 EX3 EX4 EX5 *** EX1 EX2 EX3 EX4 EX5 + 1 30. 4.0 5.0 + 2 5 0.0 4.0 + END HYDR-INIT + + *** Section CONS *** + + NCONS + RCHRES *** + # - #NCONS *** + 1 5 1 + END NCONS + + CONS-DATA + RCHRES Data for conservative constituent No. 3 *** + # - #<---Substance-id---> Conc ID CONV QTYID *** + 1 5 ALKALINITY 1000. MG/L 35.31 KG + END CONS-DATA + + *** Section HTRCH *** + + HEAT-PARM + RCHRES ELEV ELDAT CFSAEX KATRAD KCOND KEVAP *** + # - # *** + 1 5 450. 100. .95 + END HEAT-PARM + + HEAT-INIT + RCHRES TW AIRTMP *** + # - # *** + 1 5 60. 40. + END HEAT-INIT + + *** Section SEDTRN *** + + SANDFG + RCHRES *** + # - # SDFG *** + 1 2 1 + 3 4 2 + 5 3 + END SANDFG + + SED-GENPARM + RCHRES BEDWID BEDWRN POR *** + # - # *** + 1 200. 4. + 2 3 1.33 3. + 4 2.0 2. + 5 2.66 2. + END SED-GENPARM + + SAND-PM + RCHRES D W RHO KSAND EXPSND *** + # - # *** + 1 5 .014 2.5 1.5 1.2 + END SAND-PM + + SILT-CLAY-PM + RCHRES D W RHO TAUCD TAUCS M *** + # - # *** + 1 .00063 .0066 2.2 .2 .4 .5 + 2 3 .00063 .0066 2.2 1.E-10 500. .5 + 4 5 .00063 .0066 2.2 .2 .4 .5 + END SILT-CLAY-PM + + SILT-CLAY-PM + RCHRES D W RHO TAUCD TAUCS M *** + # - # *** + 1 .000055 .000034 2.0 .15 .3 .75 + 2 3 .000055 .000034 2.0 1.E-10 500. .75 + 4 5 .000055 .000034 2.0 .15 .3 .75 + END SILT-CLAY-PM + + SSED-INIT + RCHRES Suspended sed concs (mg/l) *** + # - # Sand Silt Clay *** + 1 5 5. 20. 30. + END SSED-INIT + + BED-INIT + RCHRES BEDDEP Initial bed composition *** + # - # (ft) Sand Silt Clay *** + 1 2. .8 .1 .1 + 2 3 2. .8 .1 .1 + 4 5 1. .8 .1 .1 + END BED-INIT + + *** Section GQUAL *** + + GQ-GENDATA + RCHRES NGQL TPFG PHFG ROFG CDFG SDFG PYFG LAT *** + # - # *** + 1 5 1 1 1 2 1 1 1 42 + END GQ-GENDATA + + GQ-QALDATA + RCHRES<-------GQID-------> DQAL CONCID CONV QTYID *** + # - # *** + 1 5 PESTICIDE B4 10. UG 1.E6 G + END GQ-QALDATA + + GQ-QALFG + RCHRES HDRL OXID PHOT VOLT BIOD GEN SDAS *** + # - # *** + 1 5 1 1 1 1 1 1 1 + END GQ-QALFG + + GQ-HYDPM + RCHRES KA KB KN THHYD *** + # - # *** + 1 5 .001 .01 .001 1.03 + END GQ-HYDPM + + GQ-ROXPM + RCHRES KOX THOX *** + # - # *** + 1 5 .1 1.03 + END GQ-ROXPM + + GQ-PHOTPM + # - #*** K1 K2 K3 K4 K5 K6 K7 + # - #*** K8 K9 K10 K11 K12 K13 K14 + # - #*** K15 K16 K17 K18 PHI THETA + 1 5 848. 544. 330. 195. 120. 68. 41. + 1 5 23. 13. 7. 4. 1. .1 + 1 5 .3 1.1 + END GQ-PHOTPM + + GQ-CFGAS + RCHRES CFGAS *** + # - # *** + 1 5 .001 + END GQ-CFGAS + + GQ-BIOPM + RCHRES BIOCON THBIO BIO *** + # - # *** + 1 5 .01 10. + END GQ-BIOPM + + GQ-GENDECAY + RCHRES FSTDEC THFST *** + # - # *** + 1 5 .2 + END GQ-GENDECAY + + GQ-SEDDECAY + RCHRES KSUSP THSUSP KBED THBED *** + # - # *** + 1 5 .002 + END GQ-SEDDECAY + + GQ-KD + RCHRES Partition coefficients *** + # - # ADPM(1,1) ADPM(2,1) ADPM(3,1) ADPM(4,1) ADPM(5,1) ADPM(6,1) *** + 1 .0001 .001 .001 .0001 .001 .001 + 2 3 .0001 .001 .001 1.E-10 1.E-10 1.E-10 + 4 5 .0001 .001 .001 .0001 .001 .001 + END GQ-KD + + GQ-ADRATE + RCHRES Adsorption/desorption rate parameters *** + # - # ADPM(1,2) ADPM(2,2) ADPM(3,2) ADPM(4,2) ADPM(5,2) ADPM(6,2) *** + 1 150. 150. 150. .25 .25 .25 + 2 3 150. 150. 150. 1000. 1000. 1000. + 4 5 150. 150. 150. .25 .25 .25 + END GQ-ADRATE + + GQ-SEDCONC + RCHRES SQAL1 SQAL2 SQAL3 SQAL4 SQAL5 SQAL6 *** + # - # *** + 1 .001 .01 .01 .001 .01 .01 + 2 3 .001 .01 .01 0. 0. 0. + 4 5 .001 .01 .01 .001 .01 .01 + END GQ-SEDCONC + + GQ-VALUES + RCHRES TWAT PHVAL ROC CLD SDCNC PHY *** + # - # *** + 1 5 1.E-5 + END GQ-VALUES + + GQ-ALPHA + RCHRES*** + # - #*** K1 K2 K3 K4 K5 K6 K7 + # - #*** K8 K9 K10 K11 K12 K13 K14 + # - #*** K15 K16 K17 K18 + 1 5 .008 .009 .010 .011 .011 .011 .012 + 1 5 .013 .015 .016 .017 .018 .019 .020 + 1 5 .021 .022 .024 .024 + END GQ-ALPHA + + GQ-GAMMA + RCHRES*** + # - #*** K1 K2 K3 K4 K5 K6 K7 + # - #*** K8 K9 K10 K11 K12 K13 K14 + # - #*** K15 K16 K17 K18 + 1 5 .001 .001 .001 .001 .001 .001 .001 + 1 5 .001 .002 .002 .002 .002 .002 .002 + 1 5 .002 .002 .002 .002 + END GQ-GAMMA + + GQ-DELTA + RCHRES*** + # - #*** K1 K2 K3 K4 K5 K6 K7 + # - #*** K8 K9 K10 K11 K12 K13 K14 + # - #*** K15 K16 K17 K18 + 1 5 .0007 .0007 .0007 .0007 .0007 .0007 .0007 + 1 5 .0007 .0007 .0007 .0007 .0007 .0007 .0007 + 1 5 .0007 .0007 .0007 .0007 + END GQ-DELTA + + GQ-CLDFACT + RCHRES*** + # - #*** F1 F2 F3 F4 F5 F6 F7 + # - #*** F8 F9 F10 F11 F12 F13 F14 + # - #*** F15 F16 F17 F18 + 1 5 .10 .10 .10 .15 .15 .15 .15 + 1 5 .17 .17 .17 .17 .18 .19 .20 + 1 5 .21 .21 .21 .21 + END GQ-CLDFACT + + *** Section RQUAL *** + + BENTH-FLAG + RCHRES BENF *** + # - # *** + 1 1 + 4 5 1 + END BENTH-FLAG + + SCOUR-PARMS + RCHRES SCRVEL SCRMUL *** + # - # *** + 1 5 3. + END SCOUR-PARMS + + *** Section OXRX *** + + OX-FLAGS + RCHRES REAM *** + # - # *** + 2 3 1 + 4 3 + 5 2 + END OX-FLAGS + + OX-GENPARM + RCHRES KBOD20 TCBOD KODSET SUPSAT *** + # - # /hr *** + 1 5 .1 8. + END OX-GENPARM + + OX-BENPARM + RCHRES BENOD TCBEN EXPOD BRBOD(1) BRBOD(2) EXPREL *** + # - # mg/m2.hr mg/m2.hr mg/m2.hr *** + 1 5 10. 1.1 1.2 20. 25. 1.3 + END OX-BENPARM + + OX-CFOREA + RCHRES CFOREA *** + # - # *** + 1 5. + END OX-CFOREA + + OX-REAPARM + RCHRES TCGINV REAK EXPRED EXPREV *** + # - # /hr *** + 4 2.0 -1.1 1.1 + END OX-REAPARM + + OX-INIT + RCHRES DOX BOD SATDO *** + # - # mg/l mg/l mg/l *** + 1 5 8. 100. + END OX-INIT + + *** Section NUTRX *** + + NUT-FLAGS + RCHRES TAM NO2 PO4 AMV DEN ADNH ADPO PHFL *** + # - # *** + 1 5 1 1 1 1 1 0 0 + END NUT-FLAGS + + NUT-BENPARM + RCHRES BRTAM(1) BRTAM(2) BRPO4(1) BRPO4(2) ANAER *** + # - # mg/m2.hr mg/m2.hr mg/m2.hr mg/m2.hr mg/l *** + 1 5 11.0 33.0 1.1 2.2 0.0005 + END NUT-BENPARM + + NUT-NITDENIT + RCHRES KTAM20 KNO220 TCNIT KNO320 TCDEN DENOXT *** + # - # /hr /hr /hr mg/l *** + 1 5 .002 .004 1.07 .001 1.04 0.2 + END NUT-NITDENIT + + NUT-NH3VOLAT + RCHRES EXPNVG EXPNVL *** + # - # *** + 1 5 .50 0.6667 + END NUT-NH3VOLAT + + NUT-BEDCONC + RCHRES Bed concentrations of NH4 & PO4 (mg/mg) *** + # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** + 1 5 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 + END NUT-BEDCONC + + NUT-ADSPARM + RCHRES Partition coefficients for NH4 AND PO4 (l/mg) *** + # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** + 1 5 0.0001 0.0001 0.0001 10. 10. 10. + END NUT-ADSPARM + + NUT-DINIT + RCHRES NO3 TAM NO2 PO4 PHVAL *** + # - # mg/l mg/l mg/l mg/l ph units *** + 1 5 40. 10. 1. 50. 7.0 + END NUT-DINIT + + NUT-ADSINIT + RCHRES Initial suspended NH4 and PO4 concentrations (mg/mg) *** + # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** + 1 5 0. 0. 0. 0. 0. 0. + END NUT-ADSINIT + + *** Section PLANK *** + + PLNK-FLAGS + RCHRES PHYF ZOOF BALF SDLT AMRF DECF NSFG ZFOO *** + # - # *** + 1 5 1 1 1 1 1 1 + END PLNK-FLAGS + + PLNK-PARM1 + RCHRES RATCLP NONREF LITSED ALNPR EXTB MALGR *** + # - # /ft /hr *** + 1 5 4.5 + END PLNK-PARM1 + + PHYTO-PARM + RCHRES SEED MXSTAY OREF CLALDH PHYSET REFSET *** + # - # mg/l mg/l ug/l *** + 1 5 .1 .1 .5 .5 + END PHYTO-PARM + + ZOO-PARM1 + RCHRES MZOEAT ZFIL20 ZRES20 ZD OXZD *** + # - # mg/l.hr l/mgzoo.hr /hr /hr /hr *** + 1 5 .2 + END ZOO-PARM1 + + PLNK-INIT + RCHRES PHYTO ZOO BENAL ORN ORP ORC *** + # - # mg/l org/l mg/m2 mg/l mg/l mg/l *** + 1 5 40. 200. 5. 20. 20. 20. + END PLNK-INIT + + *** Section PHCARB *** + + PH-PARM1 + RCHRES PHCN ALKC *** + # - # *** + 1 5 50 + END PH-PARM1 + + PH-INIT + RCHRES TIC CO2 PH *** + # - # mg/l mg/l *** + 1 5 20. 5. 8.5 + END PH-INIT +END RCHRES + +FTABLES + FTABLE 1 + ROWS COLS *** + 14 6 + WINTER SUMMER SPLWAY *** + DEPTH AREA VOLUME OUTLET OUTLET DISCH *** + (FT) (ACRES) (AC-FT) DISCH DISCH (CFS) *** + (CFS) (CFS) *** + .000 .000 .0000 .0000 .0000 .0000 + 2.000 1.212 1.2120 0.0000 .0000 .0000 + 4.000 2.424 4.8480 0.0000 .0000 .0000 + 6.000 3.636 10.9080 0.0000 .0000 .0000 + 8.000 4.848 19.3920 0.0000 .0000 .0000 + 10.000 6.061 30.3050 0.0000 .0000 .0000 + 12.000 7.273 43.6380 5.0000 3.5000 .0000 + 14.000 8.485 59.3950 6.2500 4.3750 .0000 + 16.000 9.697 77.5760 7.5000 5.2500 .0000 + 18.000 10.909 98.1810 8.7500 6.1250 .0000 + 20.000 12.121 121.2100 10.0000 7.0000 .0000 + 21.000 12.727 133.6360 10.6250 7.4375 50.0000 + 22.000 13.333 146.6630 11.2500 7.8750 100.0000 + 23.000 13.939 160.3030 11.8750 8.3125 500.0000 + END FTABLE 1 + + FTABLE 2 + ROWS COLS *** + 13 4 + DEPTH AREA VOLUME DISCH FLO-THRU *** + (FT) (ACRES) (AC-FT) (CFS) (MIN) *** + .000 .000 .0000 .000 0.0 + .167 .071 .0109 1.2241 6.5 + .333 .081 .0236 3.9148 4.4 + .500 .091 .0379 7.8193 3.5 + .667 .101 .0539 12.9032 3.0 + .833 .111 .0715 19.1853 2.7 + 1.000 .121 .0909 26.7046 2.5 + 1.333 .141 .1347 45.6529 2.1 + 1.667 .162 .1852 70.1757 1.9 + 2.000 .182 .2424 100.7192 1.7 + 2.667 .586 .4983 201.9005 1.8 + 3.333 .990 1.0236 344.6344 2.2 + 4.000 1.394 1.8182 537.0775 2.5 + END FTABLE 2 + + FTABLE 3 + ROWS COLS *** + 13 4 + DEPTH AREA VOLUME DISCH FLO-THRU *** + (FT) (ACRES) (AC-FT) (CFS) (MIN) *** + .000 .000 .0000 .000 0.0 + .167 .071 .0109 1.4992 5.3 + .333 .081 .0236 4.7947 3.6 + .500 .091 .0379 9.5766 2.9 + .667 .101 .0539 15.8032 2.5 + .833 .111 .0715 23.4971 2.2 + 1.000 .121 .0909 32.7063 2.0 + 1.333 .141 .1347 55.9132 1.7 + 1.667 .162 .1852 85.9474 1.6 + 2.000 .182 .2424 123.3553 1.4 + 2.667 .586 .4983 247.2766 1.5 + 3.333 .990 1.0236 422.0892 1.8 + 4.000 1.394 1.8182 657.7828 2.0 + END FTABLE 3 + + FTABLE 4 + ROWS COLS *** + 13 4 + DEPTH AREA VOLUME DISCH FLO-THRU *** + (FT) (ACRES) (AC-FT) (CFS) (MIN) *** + .000 .000 .0000 .000 0.0 + .250 .848 .1970 .9024 158.5 + .500 .970 .4242 2.8860 106.7 + .750 1.091 .6818 5.7642 85.9 + 1.000 1.212 .9697 9.5120 74.0 + 1.250 1.333 1.2879 14.1431 66.1 + 1.500 1.455 1.6364 19.6862 60.3 + 2.000 1.697 2.4242 33.6545 52.3 + 2.500 1.939 3.3333 51.7323 46.8 + 3.000 2.182 4.3636 74.2486 42.7 + 4.000 11.879 11.3939 155.5774 53.2 + 5.000 21.576 28.1212 296.8633 68.8 + 6.000 31.273 54.5454 522.1440 75.8 + END FTABLE 4 + + FTABLE 5 + ROWS COLS *** + 13 4 + DEPTH AREA VOLUME DISCH FLO-THRU *** + (FT) (ACRES) (AC-FT) (CFS) (MIN) *** + .000 .000 .0000 .000 0.0 + .333 1.697 .5253 1.5869 240.3 + .667 1.939 1.1313 5.0752 161.8 + 1.000 2.182 1.8182 10.1370 130.2 + 1.333 2.424 2.5859 16.7279 112.2 + 1.667 2.667 3.4343 24.8719 100.2 + 2.000 2.909 4.3636 34.6200 91.5 + 2.667 3.394 6.4646 59.1848 79.3 + 3.333 3.879 8.8889 90.9763 70.9 + 4.000 4.364 11.6364 130.5731 64.7 + 5.333 36.687 39.0034 284.8886 99.4 + 6.667 69.010 109.4680 593.7734 133.8 + 8.000 101.333 223.0302 1129.6948 143.3 + END FTABLE 5 +END FTABLES + +DISPLY + DISPLY-INFO1 + # - #<----------Title----------->***TRAN PIVL DIG1 FIL1 PYR DIG2 FIL2 YRND + 1 O2 CONC, MEIER POND (mg/l) AVER 1 2 66 12 + 2 PEST SED CONC, POND (mg/kg) AVER 1 2 66 12 + 3 O2 CONC,LOWER KITTLE C(mg/l) AVER 1 2 66 12 + 4 PEST SED CONC,L KTL C(mg/kg) AVER 1 2 66 12 + 5 WATER TEMP,MEIER POND (DEGF) AVER 1 2 66 12 + END DISPLY-INFO1 +END DISPLY + +GENER + OPCODE + # - # Op- *** + code *** + 1 2 19 + END OPCODE +END GENER + +PLTGEN + PLOTINFO + # - # FILE NPT NMN LABL PYR PIVL *** + 1 94 2 24 + 2 95 3 1 6 + END PLOTINFO + + GEN-LABELS + # - #<----------------Title ----------------> *** <------Y axis------> + 1 SIMULATED FLOWS (CFS) CFS + 2 SIMULATED VALS RELATED TO TEMP&PH,RCH 4 + END GEN-LABELS + + SCALING + # - # YMIN YMAX IVLIN *** + 1 2 0. 150. 20. + END SCALING + + CURV-DATA (first curve) + <-Curve label--> Line Intg Col Tran *** + # - # type eqv code code *** + 1 TOTAL POND OUTFL 7 1 AVER + 2 AVDEP FOR RCH 4 7 1 LAST + END CURV-DATA + + CURV-DATA (second curve) + <-Curve label--> Line Intg Col Tran *** + # - # type eqv code code *** + 1 LOWER KITTLE CR 8 2 AVER + 2 TW FOR RCH 4 8 2 LAST + END CURV-DATA + + CURV-DATA (third curve) + <-Curve label--> Line Intg Col Tran *** + # - # type eqv code code *** + 2 PH FOR RCH 4 9 2 LAST + END CURV-DATA + + CURV-DATA (fourth curve) + <-Curve label--> Line Intg Col Tran *** + # - # type eqv code code *** + 2 HTEXCH FOR RCH 4 10 2 + END CURV-DATA +END PLTGEN + +EXT SOURCES +<-Volume-> SsysSgap<--Mult-->Tran <-Target vols> <-Grp> <-Member-> *** + # # tem strg<-factor->strg # # # # *** +WDM 39 PREC ENGLZERO SAME PERLND 1 EXTNL PREC +WDM 131 PREC ENGLZERO SAME IMPLND 1 EXTNL PREC +WDM 39 PREC ENGLZERO SAME RCHRES 1 3 EXTNL PREC +WDM 131 PREC ENGLZERO SAME RCHRES 4 5 EXTNL PREC +WDM 123 ATMP ENGL SAME PERLND 1 ATEMP AIRTMP +WDM 122 ATMP ENGL SAME IMPLND 1 ATEMP AIRTMP +WDM 123 ATMP ENGL SAME RCHRES 1 3 EXTNL GATMP +WDM 122 ATMP ENGL SAME RCHRES 4 5 EXTNL GATMP +WDM 41 EVAP ENGL .7 DIV PERLND 1 EXTNL PETINP +WDM 41 EVAP ENGL .7 DIV IMPLND 1 EXTNL PETINP +WDM 41 EVAP ENGL .7 DIV RCHRES 1 5 EXTNL POTEV +WDM 42 WIND ENGL DIV PERLND 1 EXTNL WINMOV +WDM 42 WIND ENGL DIV IMPLND 1 EXTNL WINMOV +WDM 42 WIND ENGL DIV RCHRES 1 5 EXTNL WIND +WDM 46 SOLR ENGL DIV PERLND 1 EXTNL SOLRAD +WDM 46 SOLR ENGL DIV IMPLND 1 EXTNL SOLRAD +WDM 46 SOLR ENGL DIV RCHRES 1 5 EXTNL SOLRAD +WDM 126 DEWP ENGL SAME PERLND 1 EXTNL DTMPG +WDM 125 DEWP ENGL SAME IMPLND 1 EXTNL DTMPG +WDM 126 DEWP ENGL SAME RCHRES 1 3 EXTNL DEWTMP +WDM 125 DEWP ENGL SAME RCHRES 4 5 EXTNL DEWTMP +WDM 140 CLND ENGL SAME RCHRES 1 EXTNL COLIND +WDM 135 CLDC ENGL SAME PERLND 1 EXTNL CLOUD +WDM 135 CLDC ENGL SAME IMPLND 1 EXTNL CLOUD +WDM 135 CLDC ENGL SAME RCHRES 1 5 EXTNL CLOUD +END EXT SOURCES + +SCHEMATIC +<-Source-> <--Area--> <-Target-> *** + # <-factor-> # # *** +PERLND 1 6000. RCHRES 1 1 +IMPLND 1 3000. RCHRES 5 2 +RCHRES 1 RCHRES 2 3 +RCHRES 1 RCHRES 3 4 +RCHRES 2 RCHRES 4 5 +RCHRES 3 RCHRES 4 5 +RCHRES 4 RCHRES 5 5 +END SCHEMATIC + +MASS-LINK + + MASS-LINK 1 + <-Grp> <-Member-><--Mult--> <-Grp> <-Member-> *** + # #<-factor-> # # *** +PERLND PWATER PERO 0.0833333 RCHRES INFLOW IVOL +PERLND PWTGAS POHT RCHRES INFLOW IHEAT +PERLND PWTGAS PODOXM RCHRES INFLOW OXIF 1 +PERLND PWTGAS POCO2M RCHRES INFLOW PHIF 2 + END MASS-LINK 1 + + MASS-LINK 2 + <-Grp> <-Member-><--Mult--> <-Grp> <-Member-> *** + # #<-factor-> # # *** +IMPLND IWATER SURO 0.0833333 RCHRES INFLOW IVOL +IMPLND SOLIDS SOSLD 0.10 RCHRES INFLOW ISED 1 +IMPLND SOLIDS SOSLD 0.46 RCHRES INFLOW ISED 2 +IMPLND SOLIDS SOSLD 0.44 RCHRES INFLOW ISED 3 +IMPLND IWTGAS SOHT RCHRES INFLOW IHEAT +IMPLND IWTGAS SODOXM RCHRES INFLOW OXIF 1 +IMPLND IWTGAS SOCO2M RCHRES INFLOW PHIF 2 +IMPLND IQUAL SOQUAL RCHRES INFLOW OXIF 2 + END MASS-LINK 2 + + MASS-LINK 3 + <-Grp> <-Member-><--Mult--> <-Grp> <-Member-> *** + # #<-factor-> # # *** +RCHRES OFLOW 1 RCHRES INFLOW + END MASS-LINK 3 + + MASS-LINK 4 + <-Grp> <-Member-><--Mult--> <-Grp> <-Member-> *** + # #<-factor-> # # *** +RCHRES OFLOW 2 RCHRES INFLOW + END MASS-LINK 4 + + MASS-LINK 5 + <-Grp> <-Member-><--Mult--> <-Grp> <-Member-> *** + # #<-factor-> # # *** +RCHRES ROFLOW RCHRES INFLOW + END MASS-LINK 5 + +END MASS-LINK + +NETWORK +<-Volume-> <-Grp> <-Member-><--Mult-->Tran <-Target vols> <-Grp> <-Member-> *** + # # #<-factor->strg # # # # *** +RCHRES 1 HTRCH TW 1. DISPLY 5 INPUT TIMSER +RCHRES 1 OXRX DOX 1. DISPLY 1 INPUT TIMSER +RCHRES 1 GQUAL RSQAL 12 1. GENER 1 INPUT ONE +RCHRES 1 SEDTRN RSED 10 1. GENER 1 INPUT TWO +GENER 1 OUTPUT TIMSER 1.1 DISPLY 2 INPUT TIMSER +RCHRES 1 HYDR ROVOL 12.1 PLTGEN 1 INPUT MEAN 1 +RCHRES 4 HYDR AVDEP 1. PLTGEN 2 INPUT POINT 1 +RCHRES 4 HTRCH TW 1. PLTGEN 2 INPUT POINT 2 +RCHRES 4 PHCARB PHST 3 1. PLTGEN 2 INPUT POINT 3 +RCHRES 4 HTRCH HTEXCH 1. PLTGEN 2 INPUT MEAN 1 +RCHRES 5 OXRX DOX 1. DISPLY 3 INPUT TIMSER +RCHRES 5 GQUAL RSQAL 12 1. GENER 2 INPUT ONE +RCHRES 5 SEDTRN RSED 10 1. GENER 2 INPUT TWO +GENER 2 OUTPUT TIMSER 1.1 DISPLY 4 INPUT TIMSER +RCHRES 5 HYDR ROVOL 12.1 PLTGEN 1 INPUT MEAN 2 +END NETWORK + +END RUN diff --git a/tests/test10eq/HSP2results/test10eq.wdm b/tests/test10eq/HSP2results/test10eq.wdm new file mode 100644 index 00000000..8d0e2766 Binary files /dev/null and b/tests/test10eq/HSP2results/test10eq.wdm differ diff --git a/tests/test10eq/HSPFresults/test10eq.uci b/tests/test10eq/HSPFresults/test10eq.uci new file mode 100644 index 00000000..690ab448 --- /dev/null +++ b/tests/test10eq/HSPFresults/test10eq.uci @@ -0,0 +1,1023 @@ +RUN + +GLOBAL + Version 11 test run: PERLND and IMPLND w/ RCHRES (sediment, water quality) + START 1976 END 1976 + RUN INTERP OUTPUT LEVEL 3 + RESUME 0 RUN 1 UNIT SYSTEM 1 +END GLOBAL + + *** This test run uses MASS-LINK and SCHEMATIC blocks *** + +FILES + ***<----FILE NAME-------------------------------------------------> +WDM 21 test0eq.wdm +MESSU 22 test0eq.ech + 01 test0eq.out + 66 test0eq.d66 + 94 test0eq.p94 + 95 test0eq.p95 +BINO 81 test0eqP.hbn +BINO 82 test0eqI.hbn +BINO 83 test0eqR.hbn +END FILES + +OPN SEQUENCE + INGRP INDELT 01:00 + PERLND 1 + RCHRES 1 + DISPLY 5 + DISPLY 1 + GENER 1 + DISPLY 2 + RCHRES 2 + RCHRES 3 + RCHRES 4 + PLTGEN 2 + IMPLND 1 + RCHRES 5 + DISPLY 3 + GENER 2 + DISPLY 4 + PLTGEN 1 + END INGRP +END OPN SEQUENCE + +PERLND + ACTIVITY + Active Sections (1=Active, 0=Inactive) *** + # - # ATMP SNOW PWAT SED PST PWG PQAL MSTL PEST NITR PHOS TRAC *** + 1 1 1 1 1 + END ACTIVITY + + PRINT-INFO + Print-flags *** PIVL PYR + # - # ATMP SNOW PWAT SED PST PWG PQAL MSTL PEST NITR PHOS TRAC *** + 1 4 4 4 4 12 + END PRINT-INFO + + BINARY-INFO +*** < PLS> Binary Output Flags PIVL PYR +*** x - x ATMP SNOW PWAT SED PST PWG PQAL MSTL PEST NITR PHOS TRAC + 1 2 2 2 2 2 1 12 + END BINARY-INFO + + GEN-INFO + <-------Name-------> Unit-systems Printer BinaryOut *** + # - # t-series Engl Metr Engl Metr *** + in out *** + 1 BICKNELL FARM 1 1 1 0 81 0 + END GEN-INFO + + *** Section SNOW *** + + ICE-FLAG + 0= Ice formation not simulated, 1= Simulated *** + # - #ICEFG *** + 1 1 + END ICE-FLAG + + SNOW-PARM1 + Snow input info: Part 1 *** + # - # LAT MELEV SHADE SNOWCF COVIND *** + 1 42. 520. 0.0 1.45 0.5 + END SNOW-PARM1 + + SNOW-PARM2 + Snow input info: Part 2 *** + # - # RDCSN TSNOW SNOEVP CCFACT MWATER MGMELT *** + 1 0.12 32. 0.05 0.5 0.08 0.0001 + END SNOW-PARM2 + + SNOW-INIT1 + Initial snow conditions: Part 1 *** + # - # PACKSNOW PACKICE PACKWATER RDENPF DULL PAKTMP *** + 1 1.4 0.2 0.1 0.2 375. 27.5 + END SNOW-INIT1 + + SNOW-INIT2 + Initial snow conditions: Part 2 *** + # - # COVINX XLNMLT SKYCLR *** + 1 0.50 0.0 1.0 + END SNOW-INIT2 + + *** Section PWATER *** + + PWAT-PARM1 + PWATER variable monthly parameter value flags *** + # - # CSNO RTOP UZFG VCS VUZ VNN VIFW VIRC VLE *** + 1 1 0 0 1 1 1 0 0 1 + END PWAT-PARM1 + + PWAT-PARM2 + *** PWATER input info: Part 2 + # - # ***FOREST LZSN INFILT LSUR SLSUR KVARY AGWRC + 1 0.010 8.0 0.150 250. 0.050 0.5 0.98 + END PWAT-PARM2 + + PWAT-PARM3 + *** PWATER input info: Part 3 + # - # ***PETMAX PETMIN INFEXP INFILD DEEPFR BASETP AGWETP + 1 40. 35. 2.0 2.0 0.10 0.0 0.08 + END PWAT-PARM3 + + PWAT-PARM4 + PWATER input info: Part 4 *** + # - # CEPSC UZSN NSUR INTFW IRC LZETP *** + 1 0.01 0.1 1.0 0.60 + END PWAT-PARM4 + + MON-INTERCEP + Only required if VCSFG=1 in PWAT-PARM1 *** + # - # Interception storage capacity at start of each month *** + JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** + 1 0.04 0.04 0.03 0.03 0.03 0.03 0.10 0.17 0.19 0.14 0.05 0.04 + END MON-INTERCEP + + MON-UZSN + Only required if VUZFG=1 in PWAT-PARM1 *** + # - # Upper zone storage at start of each month *** + JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** + 1 0.4 0.4 0.4 0.4 1.6 1.1 1.1 1.3 1.3 1.3 1.1 0.9 + END MON-UZSN + + MON-MANNING + Only required if VNNFG=1 in PWAT-PARM1 *** + # - # Manning's n for overland flow at start of each month *** + JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** + 1 0.30 0.30 0.30 0.30 0.27 0.25 0.25 0.25 0.25 0.25 0.35 0.33 + END MON-MANNING + + MON-LZETPARM + Only required if VLEFG=1 in PWAT-PARM1 *** + # - # Lower zone ET parameter at start of each month *** + JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC *** + 1 0.20 0.20 0.20 0.23 0.23 0.25 0.60 0.80 0.75 0.50 0.30 0.20 + END MON-LZETPARM + + PWAT-STATE1 + *** Initial conditions at start of simulation + # - # *** CEPS SURS UZS IFWS LZS AGWS GWVS + 1 0.05 0.0 0.15 0.0 4.0 0.05 0.05 + END PWAT-STATE1 + + *** Section PSTEMP *** + + PSTEMP-PARM2 + *** + # - # ASLT BSLT ULTP1 ULTP2 LGTP1 LGTP2 *** + 1 14.5 .365 1.2 4.0 1.2 6.0 + END PSTEMP-PARM2 + + *** Section PWTGAS *** + + PWT-PARM2 + *** + # - # ELEV IDOXP ICO2P ADOXP ACO2P *** + 1 500. 6. .05 5. .05 + END PWT-PARM2 +END PERLND + +IMPLND + ACTIVITY + Active Sections *** + # - # ATMP SNOW IWAT SLD IWG IQAL *** + 1 1 1 1 1 1 + END ACTIVITY + + PRINT-INFO + Print-flags *** + # - # ATMP SNOW IWAT SLD IWG IQAL PIVL PYR *** + 1 4 4 4 4 4 12 + END PRINT-INFO + + BINARY-INFO +*** **** Binary-Output-flags **** PIVL PYR +*** x - x ATMP SNOW IWAT SLD IWG IQAL ********* + 1 2 2 2 2 2 1 12 + END BINARY-INFO + + GEN-INFO + <-------Name-------> Unit-systems Printer BinaryOut *** + # - # t-series Engl Metr Engl Metr *** + in out *** + 1 DONIGIAN INDUSTRY 1 1 1 0 82 0 + END GEN-INFO + + *** Section SNOW *** + + ICE-FLAG + 0= Ice formation not simulated, 1= Simulated *** + # - #ICEFG *** + 1 1 + END ICE-FLAG + + SNOW-PARM1 + Snow input info: Part 1 *** + # - # LAT MELEV SHADE SNOWCF COVIND *** + 1 42. 450. 0.0 1.45 0.5 + END SNOW-PARM1 + + SNOW-PARM2 + Snow input info: Part 2 *** + # - # RDCSN TSNOW SNOEVP CCFACT MWATER MGMELT *** + 1 0.12 32. 0.05 0.5 0.08 0.0001 + END SNOW-PARM2 + + SNOW-INIT1 + Initial snow conditions: Part 1 *** + # - # PACKSNOW PACKICE PACKWATER RDENPF DULL PAKTMP *** + 1 1.4 0.2 0.1 0.2 375. 27.5 + END SNOW-INIT1 + + SNOW-INIT2 + Initial snow conditions: Part 2 *** + # - # COVINX XLNMLT SKYCLR *** + 1 0.50 0.0 1.0 + END SNOW-INIT2 + + *** Section IWATER *** + + IWAT-PARM1 + Flags *** + # - # CSNO RTOP VRS VNN RTLI *** + 1 1 1 + END IWAT-PARM1 + + IWAT-PARM2 + *** + # - # LSUR SLSUR NSUR RETSC *** + 1 200. .010 .010 .01 + END IWAT-PARM2 + + IWAT-PARM3 + *** + # - # PETMAX PETMIN *** + 1 40. 35. + END IWAT-PARM3 + + IWAT-STATE1 + IWATER state variables *** + # - # RETS SURS *** + 1 .01 .01 + END IWAT-STATE1 + + *** Section SOLIDS *** + + SLD-PARM2 + *** + # - # KEIM JEIM ACCSDP REMSDP *** + 1 .08 1.9 .01 .5 + END SLD-PARM2 + + SLD-STOR + Solids storage (tons/acre) *** + # - # *** + 1 0.2 + END SLD-STOR + + *** Section IWTGAS *** + + IWT-PARM2 + *** + # - # ELEV AWTF BWTF *** + 1 410. 40. 0.8 + END IWT-PARM2 + + *** Section IQUAL *** + + NQUALS + *** + # - #NQUAL *** + 1 1 + END NQUALS + + QUAL-PROPS + Identifiers and Flags *** + # - #<--qualid--> QTID QSD VPFW QSO VQO *** + 1 COD LB 1 1 + END QUAL-PROPS + + QUAL-INPUT + Storage on surface and nonseasonal parameters *** + # - # SQO POTFW ACQOP SQOLIM WSQOP *** + 1 1.20 .175 .02 2.0 1.7 + END QUAL-INPUT +END IMPLND + +RCHRES + ACTIVITY + RCHRES Active Sections (1=Active, 0=Inactive) *** + # - # HYFG ADFG CNFG HTFG SDFG GQFG OXFG NUFG PKFG PHFG *** + 1 5 1 1 1 1 1 1 1 1 1 1 + END ACTIVITY + + PRINT-INFO + RCHRES Print-flags *** + # - # HYDR ADCA CONS HEAT SED GQL OXRX NUTR PLNK PHCB PIVL PYR *** + 1 4 5 5 5 5 5 5 5 5 5 5 12 + 5 4 4 4 4 4 4 4 4 4 4 12 + END PRINT-INFO + + BINARY-INFO +*** RCHRES Binary Output level flags +*** x - x HYDR ADCA CONS HEAT SED GQL OXRX NUTR PLNK PHCB PIVL PYR + 1 5 2 2 2 2 2 2 2 2 2 2 1 12 + END BINARY-INFO + + GEN-INFO + RCHRES<-------Name------->Nexit Unit Systems Printer BinaryOut *** + # - # t-series Engl Metr LKFG Engl Metr *** + in out *** + 1 MEIER POND 2 1 1 1 0 1 83 0 + 2 OUTLET 1 1 1 1 0 0 83 0 + 3 SPILLWAY 1 1 1 1 0 0 83 0 + 4 UPPER KITTLE CREEK 1 1 1 1 0 0 83 0 + 5 LOWER KITTLE CREEK 1 1 1 1 0 0 83 0 + END GEN-INFO + + *** Section HYDR *** + + HYDR-PARM1 + RCHRES Flags for HYDR section *** + # - # VC A1 A2 A3 ODFVFG for each ODGTFG for each *** FUNCT for each + FG FG FG FG possible exit possible exit *** possible exit + 1 2 3 4 5 1 2 3 4 5 *** + + 1 1 1 1 -1 6 + 2 5 1 1 1 4 + END HYDR-PARM1 + + HYDR-PARM2 + RCHRES *** + # - # DSN FTBN LEN DELTH STCOR KS DB50 *** + 1 00 1 0.5 1. .5 + 2 00 2 0.25 20. .5 + 3 00 3 0.25 30. .5 + 4 00 4 2.0 40. .5 + 5 00 5 3.0 40. .5 + END HYDR-PARM2 + + HYDR-INIT + RCHRES Initial conditions for HYDR section *** + # - # VOL Initial value of COLIND *** Initial value of OUTDGT + (ac-ft) for each possible exit *** for each possible exit + EX1 EX2 EX3 EX4 EX5 *** EX1 EX2 EX3 EX4 EX5 + 1 30. 4.0 5.0 + 2 5 0.0 4.0 + END HYDR-INIT + + *** Section CONS *** + + NCONS + RCHRES *** + # - #NCONS *** + 1 5 1 + END NCONS + + CONS-DATA + RCHRES Data for conservative constituent No. 3 *** + # - #<---Substance-id---> Conc ID CONV QTYID *** + 1 5 ALKALINITY 1000. MG/L 35.31 KG + END CONS-DATA + + *** Section HTRCH *** + + HEAT-PARM + RCHRES ELEV ELDAT CFSAEX KATRAD KCOND KEVAP *** + # - # *** + 1 5 450. 100. .95 + END HEAT-PARM + + HEAT-INIT + RCHRES TW AIRTMP *** + # - # *** + 1 5 60. 40. + END HEAT-INIT + + *** Section SEDTRN *** + + SANDFG + RCHRES *** + # - # SDFG *** + 1 2 1 + 3 4 2 + 5 3 + END SANDFG + + SED-GENPARM + RCHRES BEDWID BEDWRN POR *** + # - # *** + 1 200. 4. + 2 3 1.33 3. + 4 2.0 2. + 5 2.66 2. + END SED-GENPARM + + SAND-PM + RCHRES D W RHO KSAND EXPSND *** + # - # *** + 1 5 .014 2.5 1.5 1.2 + END SAND-PM + + SILT-CLAY-PM + RCHRES D W RHO TAUCD TAUCS M *** + # - # *** + 1 .00063 .0066 2.2 .2 .4 .5 + 2 3 .00063 .0066 2.2 1.E-10 500. .5 + 4 5 .00063 .0066 2.2 .2 .4 .5 + END SILT-CLAY-PM + + SILT-CLAY-PM + RCHRES D W RHO TAUCD TAUCS M *** + # - # *** + 1 .000055 .000034 2.0 .15 .3 .75 + 2 3 .000055 .000034 2.0 1.E-10 500. .75 + 4 5 .000055 .000034 2.0 .15 .3 .75 + END SILT-CLAY-PM + + SSED-INIT + RCHRES Suspended sed concs (mg/l) *** + # - # Sand Silt Clay *** + 1 5 5. 20. 30. + END SSED-INIT + + BED-INIT + RCHRES BEDDEP Initial bed composition *** + # - # (ft) Sand Silt Clay *** + 1 2. .8 .1 .1 + 2 3 2. .8 .1 .1 + 4 5 1. .8 .1 .1 + END BED-INIT + + *** Section GQUAL *** + + GQ-GENDATA + RCHRES NGQL TPFG PHFG ROFG CDFG SDFG PYFG LAT *** + # - # *** + 1 5 1 1 1 2 1 1 1 42 + END GQ-GENDATA + + GQ-QALDATA + RCHRES<-------GQID-------> DQAL CONCID CONV QTYID *** + # - # *** + 1 5 PESTICIDE B4 10. UG 1.E6 G + END GQ-QALDATA + + GQ-QALFG + RCHRES HDRL OXID PHOT VOLT BIOD GEN SDAS *** + # - # *** + 1 5 1 1 1 1 1 1 1 + END GQ-QALFG + + GQ-HYDPM + RCHRES KA KB KN THHYD *** + # - # *** + 1 5 .001 .01 .001 1.03 + END GQ-HYDPM + + GQ-ROXPM + RCHRES KOX THOX *** + # - # *** + 1 5 .1 1.03 + END GQ-ROXPM + + GQ-PHOTPM + # - #*** K1 K2 K3 K4 K5 K6 K7 + # - #*** K8 K9 K10 K11 K12 K13 K14 + # - #*** K15 K16 K17 K18 PHI THETA + 1 5 848. 544. 330. 195. 120. 68. 41. + 1 5 23. 13. 7. 4. 1. .1 + 1 5 .3 1.1 + END GQ-PHOTPM + + GQ-CFGAS + RCHRES CFGAS *** + # - # *** + 1 5 .001 + END GQ-CFGAS + + GQ-BIOPM + RCHRES BIOCON THBIO BIO *** + # - # *** + 1 5 .01 10. + END GQ-BIOPM + + GQ-GENDECAY + RCHRES FSTDEC THFST *** + # - # *** + 1 5 .2 + END GQ-GENDECAY + + GQ-SEDDECAY + RCHRES KSUSP THSUSP KBED THBED *** + # - # *** + 1 5 .002 + END GQ-SEDDECAY + + GQ-KD + RCHRES Partition coefficients *** + # - # ADPM(1,1) ADPM(2,1) ADPM(3,1) ADPM(4,1) ADPM(5,1) ADPM(6,1) *** + 1 .0001 .001 .001 .0001 .001 .001 + 2 3 .0001 .001 .001 1.E-10 1.E-10 1.E-10 + 4 5 .0001 .001 .001 .0001 .001 .001 + END GQ-KD + + GQ-ADRATE + RCHRES Adsorption/desorption rate parameters *** + # - # ADPM(1,2) ADPM(2,2) ADPM(3,2) ADPM(4,2) ADPM(5,2) ADPM(6,2) *** + 1 150. 150. 150. .25 .25 .25 + 2 3 150. 150. 150. 1000. 1000. 1000. + 4 5 150. 150. 150. .25 .25 .25 + END GQ-ADRATE + + GQ-SEDCONC + RCHRES SQAL1 SQAL2 SQAL3 SQAL4 SQAL5 SQAL6 *** + # - # *** + 1 .001 .01 .01 .001 .01 .01 + 2 3 .001 .01 .01 0. 0. 0. + 4 5 .001 .01 .01 .001 .01 .01 + END GQ-SEDCONC + + GQ-VALUES + RCHRES TWAT PHVAL ROC CLD SDCNC PHY *** + # - # *** + 1 5 1.E-5 + END GQ-VALUES + + GQ-ALPHA + RCHRES*** + # - #*** K1 K2 K3 K4 K5 K6 K7 + # - #*** K8 K9 K10 K11 K12 K13 K14 + # - #*** K15 K16 K17 K18 + 1 5 .008 .009 .010 .011 .011 .011 .012 + 1 5 .013 .015 .016 .017 .018 .019 .020 + 1 5 .021 .022 .024 .024 + END GQ-ALPHA + + GQ-GAMMA + RCHRES*** + # - #*** K1 K2 K3 K4 K5 K6 K7 + # - #*** K8 K9 K10 K11 K12 K13 K14 + # - #*** K15 K16 K17 K18 + 1 5 .001 .001 .001 .001 .001 .001 .001 + 1 5 .001 .002 .002 .002 .002 .002 .002 + 1 5 .002 .002 .002 .002 + END GQ-GAMMA + + GQ-DELTA + RCHRES*** + # - #*** K1 K2 K3 K4 K5 K6 K7 + # - #*** K8 K9 K10 K11 K12 K13 K14 + # - #*** K15 K16 K17 K18 + 1 5 .0007 .0007 .0007 .0007 .0007 .0007 .0007 + 1 5 .0007 .0007 .0007 .0007 .0007 .0007 .0007 + 1 5 .0007 .0007 .0007 .0007 + END GQ-DELTA + + GQ-CLDFACT + RCHRES*** + # - #*** F1 F2 F3 F4 F5 F6 F7 + # - #*** F8 F9 F10 F11 F12 F13 F14 + # - #*** F15 F16 F17 F18 + 1 5 .10 .10 .10 .15 .15 .15 .15 + 1 5 .17 .17 .17 .17 .18 .19 .20 + 1 5 .21 .21 .21 .21 + END GQ-CLDFACT + + *** Section RQUAL *** + + BENTH-FLAG + RCHRES BENF *** + # - # *** + 1 1 + 4 5 1 + END BENTH-FLAG + + SCOUR-PARMS + RCHRES SCRVEL SCRMUL *** + # - # *** + 1 5 3. + END SCOUR-PARMS + + *** Section OXRX *** + + OX-FLAGS + RCHRES REAM *** + # - # *** + 2 3 1 + 4 3 + 5 2 + END OX-FLAGS + + OX-GENPARM + RCHRES KBOD20 TCBOD KODSET SUPSAT *** + # - # /hr *** + 1 5 .1 8. + END OX-GENPARM + + OX-BENPARM + RCHRES BENOD TCBEN EXPOD BRBOD(1) BRBOD(2) EXPREL *** + # - # mg/m2.hr mg/m2.hr mg/m2.hr *** + 1 5 10. 1.1 1.2 20. 25. 1.3 + END OX-BENPARM + + OX-CFOREA + RCHRES CFOREA *** + # - # *** + 1 5. + END OX-CFOREA + + OX-REAPARM + RCHRES TCGINV REAK EXPRED EXPREV *** + # - # /hr *** + 4 2.0 -1.1 1.1 + END OX-REAPARM + + OX-INIT + RCHRES DOX BOD SATDO *** + # - # mg/l mg/l mg/l *** + 1 5 8. 100. + END OX-INIT + + *** Section NUTRX *** + + NUT-FLAGS + RCHRES TAM NO2 PO4 AMV DEN ADNH ADPO PHFL *** + # - # *** + 1 5 1 1 1 1 1 0 0 + END NUT-FLAGS + + NUT-BENPARM + RCHRES BRTAM(1) BRTAM(2) BRPO4(1) BRPO4(2) ANAER *** + # - # mg/m2.hr mg/m2.hr mg/m2.hr mg/m2.hr mg/l *** + 1 5 11.0 33.0 1.1 2.2 0.0005 + END NUT-BENPARM + + NUT-NITDENIT + RCHRES KTAM20 KNO220 TCNIT KNO320 TCDEN DENOXT *** + # - # /hr /hr /hr mg/l *** + 1 5 .002 .004 1.07 .001 1.04 0.2 + END NUT-NITDENIT + + NUT-NH3VOLAT + RCHRES EXPNVG EXPNVL *** + # - # *** + 1 5 .50 0.6667 + END NUT-NH3VOLAT + + NUT-BEDCONC + RCHRES Bed concentrations of NH4 & PO4 (mg/mg) *** + # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** + 1 5 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 + END NUT-BEDCONC + + NUT-ADSPARM + RCHRES Partition coefficients for NH4 AND PO4 (l/mg) *** + # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** + 1 5 0.0001 0.0001 0.0001 10. 10. 10. + END NUT-ADSPARM + + NUT-DINIT + RCHRES NO3 TAM NO2 PO4 PHVAL *** + # - # mg/l mg/l mg/l mg/l ph units *** + 1 5 40. 10. 1. 50. 7.0 + END NUT-DINIT + + NUT-ADSINIT + RCHRES Initial suspended NH4 and PO4 concentrations (mg/mg) *** + # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** + 1 5 0. 0. 0. 0. 0. 0. + END NUT-ADSINIT + + *** Section PLANK *** + + PLNK-FLAGS + RCHRES PHYF ZOOF BALF SDLT AMRF DECF NSFG ZFOO *** + # - # *** + 1 5 1 1 1 1 1 1 + END PLNK-FLAGS + + PLNK-PARM1 + RCHRES RATCLP NONREF LITSED ALNPR EXTB MALGR *** + # - # /ft /hr *** + 1 5 4.5 + END PLNK-PARM1 + + PHYTO-PARM + RCHRES SEED MXSTAY OREF CLALDH PHYSET REFSET *** + # - # mg/l mg/l ug/l *** + 1 5 .1 .1 .5 .5 + END PHYTO-PARM + + ZOO-PARM1 + RCHRES MZOEAT ZFIL20 ZRES20 ZD OXZD *** + # - # mg/l.hr l/mgzoo.hr /hr /hr /hr *** + 1 5 .2 + END ZOO-PARM1 + + PLNK-INIT + RCHRES PHYTO ZOO BENAL ORN ORP ORC *** + # - # mg/l org/l mg/m2 mg/l mg/l mg/l *** + 1 5 40. 200. 5. 20. 20. 20. + END PLNK-INIT + + *** Section PHCARB *** + + PH-PARM1 + RCHRES PHCN ALKC *** + # - # *** + 1 5 50 + END PH-PARM1 + + PH-INIT + RCHRES TIC CO2 PH *** + # - # mg/l mg/l *** + 1 5 20. 5. 8.5 + END PH-INIT +END RCHRES + +FTABLES + FTABLE 1 + ROWS COLS *** + 14 6 + WINTER SUMMER SPLWAY *** + DEPTH AREA VOLUME OUTLET OUTLET DISCH *** + (FT) (ACRES) (AC-FT) DISCH DISCH (CFS) *** + (CFS) (CFS) *** + .000 .000 .0000 .0000 .0000 .0000 + 2.000 1.212 1.2120 0.0000 .0000 .0000 + 4.000 2.424 4.8480 0.0000 .0000 .0000 + 6.000 3.636 10.9080 0.0000 .0000 .0000 + 8.000 4.848 19.3920 0.0000 .0000 .0000 + 10.000 6.061 30.3050 0.0000 .0000 .0000 + 12.000 7.273 43.6380 5.0000 3.5000 .0000 + 14.000 8.485 59.3950 6.2500 4.3750 .0000 + 16.000 9.697 77.5760 7.5000 5.2500 .0000 + 18.000 10.909 98.1810 8.7500 6.1250 .0000 + 20.000 12.121 121.2100 10.0000 7.0000 .0000 + 21.000 12.727 133.6360 10.6250 7.4375 50.0000 + 22.000 13.333 146.6630 11.2500 7.8750 100.0000 + 23.000 13.939 160.3030 11.8750 8.3125 500.0000 + END FTABLE 1 + + FTABLE 2 + ROWS COLS *** + 13 4 + DEPTH AREA VOLUME DISCH FLO-THRU *** + (FT) (ACRES) (AC-FT) (CFS) (MIN) *** + .000 .000 .0000 .000 0.0 + .167 .071 .0109 1.2241 6.5 + .333 .081 .0236 3.9148 4.4 + .500 .091 .0379 7.8193 3.5 + .667 .101 .0539 12.9032 3.0 + .833 .111 .0715 19.1853 2.7 + 1.000 .121 .0909 26.7046 2.5 + 1.333 .141 .1347 45.6529 2.1 + 1.667 .162 .1852 70.1757 1.9 + 2.000 .182 .2424 100.7192 1.7 + 2.667 .586 .4983 201.9005 1.8 + 3.333 .990 1.0236 344.6344 2.2 + 4.000 1.394 1.8182 537.0775 2.5 + END FTABLE 2 + + FTABLE 3 + ROWS COLS *** + 13 4 + DEPTH AREA VOLUME DISCH FLO-THRU *** + (FT) (ACRES) (AC-FT) (CFS) (MIN) *** + .000 .000 .0000 .000 0.0 + .167 .071 .0109 1.4992 5.3 + .333 .081 .0236 4.7947 3.6 + .500 .091 .0379 9.5766 2.9 + .667 .101 .0539 15.8032 2.5 + .833 .111 .0715 23.4971 2.2 + 1.000 .121 .0909 32.7063 2.0 + 1.333 .141 .1347 55.9132 1.7 + 1.667 .162 .1852 85.9474 1.6 + 2.000 .182 .2424 123.3553 1.4 + 2.667 .586 .4983 247.2766 1.5 + 3.333 .990 1.0236 422.0892 1.8 + 4.000 1.394 1.8182 657.7828 2.0 + END FTABLE 3 + + FTABLE 4 + ROWS COLS *** + 13 4 + DEPTH AREA VOLUME DISCH FLO-THRU *** + (FT) (ACRES) (AC-FT) (CFS) (MIN) *** + .000 .000 .0000 .000 0.0 + .250 .848 .1970 .9024 158.5 + .500 .970 .4242 2.8860 106.7 + .750 1.091 .6818 5.7642 85.9 + 1.000 1.212 .9697 9.5120 74.0 + 1.250 1.333 1.2879 14.1431 66.1 + 1.500 1.455 1.6364 19.6862 60.3 + 2.000 1.697 2.4242 33.6545 52.3 + 2.500 1.939 3.3333 51.7323 46.8 + 3.000 2.182 4.3636 74.2486 42.7 + 4.000 11.879 11.3939 155.5774 53.2 + 5.000 21.576 28.1212 296.8633 68.8 + 6.000 31.273 54.5454 522.1440 75.8 + END FTABLE 4 + + FTABLE 5 + ROWS COLS *** + 13 4 + DEPTH AREA VOLUME DISCH FLO-THRU *** + (FT) (ACRES) (AC-FT) (CFS) (MIN) *** + .000 .000 .0000 .000 0.0 + .333 1.697 .5253 1.5869 240.3 + .667 1.939 1.1313 5.0752 161.8 + 1.000 2.182 1.8182 10.1370 130.2 + 1.333 2.424 2.5859 16.7279 112.2 + 1.667 2.667 3.4343 24.8719 100.2 + 2.000 2.909 4.3636 34.6200 91.5 + 2.667 3.394 6.4646 59.1848 79.3 + 3.333 3.879 8.8889 90.9763 70.9 + 4.000 4.364 11.6364 130.5731 64.7 + 5.333 36.687 39.0034 284.8886 99.4 + 6.667 69.010 109.4680 593.7734 133.8 + 8.000 101.333 223.0302 1129.6948 143.3 + END FTABLE 5 +END FTABLES + +DISPLY + DISPLY-INFO1 + # - #<----------Title----------->***TRAN PIVL DIG1 FIL1 PYR DIG2 FIL2 YRND + 1 O2 CONC, MEIER POND (mg/l) AVER 1 2 66 12 + 2 PEST SED CONC, POND (mg/kg) AVER 1 2 66 12 + 3 O2 CONC,LOWER KITTLE C(mg/l) AVER 1 2 66 12 + 4 PEST SED CONC,L KTL C(mg/kg) AVER 1 2 66 12 + 5 WATER TEMP,MEIER POND (DEGF) AVER 1 2 66 12 + END DISPLY-INFO1 +END DISPLY + +GENER + OPCODE + # - # Op- *** + code *** + 1 2 19 + END OPCODE +END GENER + +PLTGEN + PLOTINFO + # - # FILE NPT NMN LABL PYR PIVL *** + 1 94 2 24 + 2 95 3 1 6 + END PLOTINFO + + GEN-LABELS + # - #<----------------Title ----------------> *** <------Y axis------> + 1 SIMULATED FLOWS (CFS) CFS + 2 SIMULATED VALS RELATED TO TEMP&PH,RCH 4 + END GEN-LABELS + + SCALING + # - # YMIN YMAX IVLIN *** + 1 2 0. 150. 20. + END SCALING + + CURV-DATA (first curve) + <-Curve label--> Line Intg Col Tran *** + # - # type eqv code code *** + 1 TOTAL POND OUTFL 7 1 AVER + 2 AVDEP FOR RCH 4 7 1 LAST + END CURV-DATA + + CURV-DATA (second curve) + <-Curve label--> Line Intg Col Tran *** + # - # type eqv code code *** + 1 LOWER KITTLE CR 8 2 AVER + 2 TW FOR RCH 4 8 2 LAST + END CURV-DATA + + CURV-DATA (third curve) + <-Curve label--> Line Intg Col Tran *** + # - # type eqv code code *** + 2 PH FOR RCH 4 9 2 LAST + END CURV-DATA + + CURV-DATA (fourth curve) + <-Curve label--> Line Intg Col Tran *** + # - # type eqv code code *** + 2 HTEXCH FOR RCH 4 10 2 + END CURV-DATA +END PLTGEN + +EXT SOURCES +<-Volume-> SsysSgap<--Mult-->Tran <-Target vols> <-Grp> <-Member-> *** + # # tem strg<-factor->strg # # # # *** +WDM 39 PREC ENGLZERO SAME PERLND 1 EXTNL PREC +WDM 131 PREC ENGLZERO SAME IMPLND 1 EXTNL PREC +WDM 39 PREC ENGLZERO SAME RCHRES 1 3 EXTNL PREC +WDM 131 PREC ENGLZERO SAME RCHRES 4 5 EXTNL PREC +WDM 123 ATMP ENGL SAME PERLND 1 ATEMP AIRTMP +WDM 122 ATMP ENGL SAME IMPLND 1 ATEMP AIRTMP +WDM 123 ATMP ENGL SAME RCHRES 1 3 EXTNL GATMP +WDM 122 ATMP ENGL SAME RCHRES 4 5 EXTNL GATMP +WDM 41 EVAP ENGL .7 DIV PERLND 1 EXTNL PETINP +WDM 41 EVAP ENGL .7 DIV IMPLND 1 EXTNL PETINP +WDM 41 EVAP ENGL .7 DIV RCHRES 1 5 EXTNL POTEV +WDM 42 WIND ENGL DIV PERLND 1 EXTNL WINMOV +WDM 42 WIND ENGL DIV IMPLND 1 EXTNL WINMOV +WDM 42 WIND ENGL DIV RCHRES 1 5 EXTNL WIND +WDM 46 SOLR ENGL DIV PERLND 1 EXTNL SOLRAD +WDM 46 SOLR ENGL DIV IMPLND 1 EXTNL SOLRAD +WDM 46 SOLR ENGL DIV RCHRES 1 5 EXTNL SOLRAD +WDM 126 DEWP ENGL SAME PERLND 1 EXTNL DTMPG +WDM 125 DEWP ENGL SAME IMPLND 1 EXTNL DTMPG +WDM 126 DEWP ENGL SAME RCHRES 1 3 EXTNL DEWTMP +WDM 125 DEWP ENGL SAME RCHRES 4 5 EXTNL DEWTMP +WDM 140 CLND ENGL SAME RCHRES 1 EXTNL COLIND +WDM 135 CLDC ENGL SAME PERLND 1 EXTNL CLOUD +WDM 135 CLDC ENGL SAME IMPLND 1 EXTNL CLOUD +WDM 135 CLDC ENGL SAME RCHRES 1 5 EXTNL CLOUD +END EXT SOURCES + +SCHEMATIC +<-Source-> <--Area--> <-Target-> *** + # <-factor-> # # *** +PERLND 1 6000. RCHRES 1 1 +IMPLND 1 3000. RCHRES 5 2 +RCHRES 1 RCHRES 2 3 +RCHRES 1 RCHRES 3 4 +RCHRES 2 RCHRES 4 5 +RCHRES 3 RCHRES 4 5 +RCHRES 4 RCHRES 5 5 +END SCHEMATIC + +MASS-LINK + + MASS-LINK 1 + <-Grp> <-Member-><--Mult--> <-Grp> <-Member-> *** + # #<-factor-> # # *** +PERLND PWATER PERO 0.0833333 RCHRES INFLOW IVOL +PERLND PWTGAS POHT RCHRES INFLOW IHEAT +PERLND PWTGAS PODOXM RCHRES INFLOW OXIF 1 +PERLND PWTGAS POCO2M RCHRES INFLOW PHIF 2 + END MASS-LINK 1 + + MASS-LINK 2 + <-Grp> <-Member-><--Mult--> <-Grp> <-Member-> *** + # #<-factor-> # # *** +IMPLND IWATER SURO 0.0833333 RCHRES INFLOW IVOL +IMPLND SOLIDS SOSLD 0.10 RCHRES INFLOW ISED 1 +IMPLND SOLIDS SOSLD 0.46 RCHRES INFLOW ISED 2 +IMPLND SOLIDS SOSLD 0.44 RCHRES INFLOW ISED 3 +IMPLND IWTGAS SOHT RCHRES INFLOW IHEAT +IMPLND IWTGAS SODOXM RCHRES INFLOW OXIF 1 +IMPLND IWTGAS SOCO2M RCHRES INFLOW PHIF 2 +IMPLND IQUAL SOQUAL RCHRES INFLOW OXIF 2 + END MASS-LINK 2 + + MASS-LINK 3 + <-Grp> <-Member-><--Mult--> <-Grp> <-Member-> *** + # #<-factor-> # # *** +RCHRES OFLOW 1 RCHRES INFLOW + END MASS-LINK 3 + + MASS-LINK 4 + <-Grp> <-Member-><--Mult--> <-Grp> <-Member-> *** + # #<-factor-> # # *** +RCHRES OFLOW 2 RCHRES INFLOW + END MASS-LINK 4 + + MASS-LINK 5 + <-Grp> <-Member-><--Mult--> <-Grp> <-Member-> *** + # #<-factor-> # # *** +RCHRES ROFLOW RCHRES INFLOW + END MASS-LINK 5 + +END MASS-LINK + +NETWORK +<-Volume-> <-Grp> <-Member-><--Mult-->Tran <-Target vols> <-Grp> <-Member-> *** + # # #<-factor->strg # # # # *** +RCHRES 1 HTRCH TW 1. DISPLY 5 INPUT TIMSER +RCHRES 1 OXRX DOX 1. DISPLY 1 INPUT TIMSER +RCHRES 1 GQUAL RSQAL 12 1. GENER 1 INPUT ONE +RCHRES 1 SEDTRN RSED 10 1. GENER 1 INPUT TWO +GENER 1 OUTPUT TIMSER 1.1 DISPLY 2 INPUT TIMSER +RCHRES 1 HYDR ROVOL 12.1 PLTGEN 1 INPUT MEAN 1 +RCHRES 4 HYDR AVDEP 1. PLTGEN 2 INPUT POINT 1 +RCHRES 4 HTRCH TW 1. PLTGEN 2 INPUT POINT 2 +RCHRES 4 PHCARB PHST 3 1. PLTGEN 2 INPUT POINT 3 +RCHRES 4 HTRCH HTEXCH 1. PLTGEN 2 INPUT MEAN 1 +RCHRES 5 OXRX DOX 1. DISPLY 3 INPUT TIMSER +RCHRES 5 GQUAL RSQAL 12 1. GENER 2 INPUT ONE +RCHRES 5 SEDTRN RSED 10 1. GENER 2 INPUT TWO +GENER 2 OUTPUT TIMSER 1.1 DISPLY 4 INPUT TIMSER +RCHRES 5 HYDR ROVOL 12.1 PLTGEN 1 INPUT MEAN 2 +END NETWORK + +SPEC-ACTIONS +*** test special actions + RCHRES 5 RSED 4 += 2.50E+05 + RCHRES 5 RSED 5 += 6.89E+05 + RCHRES 5 RSED 6 += 4.01E+05 +END SPEC-ACTIONS + + +END RUN diff --git a/tests/test10eq/HSPFresults/test10eq.wdm b/tests/test10eq/HSPFresults/test10eq.wdm new file mode 100644 index 00000000..8d0e2766 Binary files /dev/null and b/tests/test10eq/HSPFresults/test10eq.wdm differ diff --git a/tests/test10eq/HSPFresults/test10eqI.hbn b/tests/test10eq/HSPFresults/test10eqI.hbn new file mode 100644 index 00000000..a4529a11 Binary files /dev/null and b/tests/test10eq/HSPFresults/test10eqI.hbn differ diff --git a/tests/test10eq/HSPFresults/test10eqP.hbn b/tests/test10eq/HSPFresults/test10eqP.hbn new file mode 100644 index 00000000..bfe0d3b0 Binary files /dev/null and b/tests/test10eq/HSPFresults/test10eqP.hbn differ diff --git a/tests/test10eq/HSPFresults/test10eqR.hbn b/tests/test10eq/HSPFresults/test10eqR.hbn new file mode 100644 index 00000000..45fa25d7 Binary files /dev/null and b/tests/test10eq/HSPFresults/test10eqR.hbn differ diff --git a/tests/test10specl/HSP2results/TEST10_hsp2_compare.ipynb b/tests/test10specl/HSP2results/TEST10_hsp2_compare.ipynb index 165cafb7..e95c7b78 100644 --- a/tests/test10specl/HSP2results/TEST10_hsp2_compare.ipynb +++ b/tests/test10specl/HSP2results/TEST10_hsp2_compare.ipynb @@ -54,13 +54,6 @@ "cell_type": "code", "execution_count": 1, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T22:16:22.070310Z", - "iopub.status.busy": "2024-05-21T22:16:22.070084Z", - "iopub.status.idle": "2024-05-21T22:16:22.793186Z", - "shell.execute_reply": "2024-05-21T22:16:22.792716Z", - "shell.execute_reply.started": "2024-05-21T22:16:22.070294Z" - }, "vscode": { "languageId": "python" } @@ -97,11 +90,11 @@ " \n", " \n", " Python\n", - " 3.10.14 | packaged by conda-forge | (main, Mar...\n", + " 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11....\n", " \n", " \n", " hsp2\n", - " n/a\n", + " 0.11.0a1\n", " \n", " \n", " numpy\n", @@ -109,27 +102,27 @@ " \n", " \n", " numba\n", - " 0.59.1\n", + " 0.64.0\n", " \n", " \n", " pandas\n", - " 1.5.3\n", + " 2.3.3\n", " \n", " \n", " matplotlib\n", - " 3.8.4\n", + " 3.10.8\n", " \n", " \n", " os\n", - " Linux-5.15.0-91-generic-x86_64-with-glibc2.35\n", + " Linux-6.19.12-200.fc43.x86_64-x86_64-with-glib...\n", " \n", " \n", " processor\n", - " x86_64\n", + " \n", " \n", " \n", " Date/Time\n", - " 2024-05-21T18:16:22.786814\n", + " 2026-05-06T22:19:06.813098\n", " \n", " \n", "\n", @@ -138,15 +131,15 @@ "text/plain": [ " version\n", "name \n", - "Python 3.10.14 | packaged by conda-forge | (main, Mar...\n", - "hsp2 n/a\n", + "Python 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11....\n", + "hsp2 0.11.0a1\n", "numpy 1.26.4\n", - "numba 0.59.1\n", - "pandas 1.5.3\n", - "matplotlib 3.8.4\n", - "os Linux-5.15.0-91-generic-x86_64-with-glibc2.35\n", - "processor x86_64\n", - "Date/Time 2024-05-21T18:16:22.786814" + "numba 0.64.0\n", + "pandas 2.3.3\n", + "matplotlib 3.10.8\n", + "os Linux-6.19.12-200.fc43.x86_64-x86_64-with-glib...\n", + "processor \n", + "Date/Time 2026-05-06T22:19:06.813098" ] }, "execution_count": 1, @@ -191,13 +184,6 @@ "cell_type": "code", "execution_count": 2, "metadata": { - "execution": { - "iopub.execute_input": "2024-04-28T16:45:34.246207Z", - "iopub.status.busy": "2024-04-28T16:45:34.245792Z", - "iopub.status.idle": "2024-04-28T16:45:34.364011Z", - "shell.execute_reply": "2024-04-28T16:45:34.363366Z", - "shell.execute_reply.started": "2024-04-28T16:45:34.246190Z" - }, "vscode": { "languageId": "python" } @@ -224,15 +210,8 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T22:16:31.196161Z", - "iopub.status.busy": "2024-05-21T22:16:31.195656Z", - "iopub.status.idle": "2024-05-21T22:16:31.199544Z", - "shell.execute_reply": "2024-05-21T22:16:31.199047Z", - "shell.execute_reply.started": "2024-05-21T22:16:31.196142Z" - }, "vscode": { "languageId": "python" } @@ -241,10 +220,10 @@ { "data": { "text/plain": [ - "'hsp2_310'" + "'default311'" ] }, - "execution_count": 2, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -256,15 +235,8 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T22:16:32.643829Z", - "iopub.status.busy": "2024-05-21T22:16:32.643618Z", - "iopub.status.idle": "2024-05-21T22:16:32.646567Z", - "shell.execute_reply": "2024-05-21T22:16:32.646182Z", - "shell.execute_reply.started": "2024-05-21T22:16:32.643818Z" - }, "vscode": { "languageId": "python" } @@ -273,10 +245,10 @@ { "data": { "text/plain": [ - "PosixPath('/home/tim/programming/HSPsquared/tests/test10specl/HSP2results')" + "PosixPath('/var/home/timcera/programming/HSP_old/HSPsquared/tests/test10specl/HSP2results')" ] }, - "execution_count": 3, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -290,15 +262,8 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 5, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T22:17:23.831107Z", - "iopub.status.busy": "2024-05-21T22:17:23.830606Z", - "iopub.status.idle": "2024-05-21T22:17:23.833610Z", - "shell.execute_reply": "2024-05-21T22:17:23.833193Z", - "shell.execute_reply.started": "2024-05-21T22:17:23.831088Z" - }, "vscode": { "languageId": "python" } @@ -320,15 +285,8 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 6, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T22:17:26.288627Z", - "iopub.status.busy": "2024-05-21T22:17:26.287881Z", - "iopub.status.idle": "2024-05-21T22:17:26.290699Z", - "shell.execute_reply": "2024-05-21T22:17:26.290347Z", - "shell.execute_reply.started": "2024-05-21T22:17:26.288601Z" - }, "vscode": { "languageId": "python" } @@ -348,15 +306,8 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 7, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T22:17:28.137137Z", - "iopub.status.busy": "2024-05-21T22:17:28.136607Z", - "iopub.status.idle": "2024-05-21T22:17:38.473173Z", - "shell.execute_reply": "2024-05-21T22:17:38.472872Z", - "shell.execute_reply.started": "2024-05-21T22:17:28.137119Z" - }, "vscode": { "languageId": "python" } @@ -366,8 +317,31 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 3 µs, sys: 0 ns, total: 3 µs\n", - "Wall time: 5.96 µs\n" + "CPU times: user 2 µs, sys: 0 ns, total: 2 µs\n", + "Wall time: 6.68 µs\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_42144/1322036604.py:2: DeprecationWarning: Call to deprecated function readUCI (\n", + "\n", + "readUCI is deprecated and will be removed in a future release.\n", + "Use hsp2.hsp2io.control_file_readers.read_uci_parameters to read the parameters.\n", + "\n", + ").\n", + " readUCI(uciname, hdfname)\n", + "/var/home/timcera/programming/HSP_old/HSPsquared/src/hsp2/hsp2io/control_file_readers/utils.py:179: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " nparms = nparms.infer_objects(copy=False).fillna(dict(zip(defaults.index, defaults[\"DEFAULT\"].values)))\n", + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'CURV-DATA1'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though\n", + " check_attribute_name(name)\n", + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'CURV-DATA2'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though\n", + " check_attribute_name(name)\n", + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'CURV-DATA3'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though\n", + " check_attribute_name(name)\n", + "/var/home/timcera/miniconda3/envs/default311/lib/python3.11/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'CURV-DATA4'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though\n", + " check_attribute_name(name)\n" ] } ], @@ -378,15 +352,8 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 8, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T22:17:42.981439Z", - "iopub.status.busy": "2024-05-21T22:17:42.981148Z", - "iopub.status.idle": "2024-05-21T22:17:45.893779Z", - "shell.execute_reply": "2024-05-21T22:17:45.893433Z", - "shell.execute_reply.started": "2024-05-21T22:17:42.981422Z" - }, "vscode": { "languageId": "python" } @@ -397,7 +364,28 @@ "output_type": "stream", "text": [ "CPU times: user 2 µs, sys: 0 ns, total: 2 µs\n", - "Wall time: 4.77 µs\n", + "Wall time: 4.05 µs\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_42144/1296374569.py:2: DeprecationWarning: Call to deprecated function readWDM (\n", + "\n", + "readWDM is deprecated and will be removed in a future release.\n", + "Use hsp2.hsp2io.time_series_readers.read_wdm_ts.read_wdm_ts to read the time\n", + "series data from the WDM file, and then write the data to an HDF file using\n", + "pandas.\n", + "\n", + ").\n", + " readWDM(wdmname, hdfname)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "39 reading from wdm\n", "41 reading from wdm\n", "42 reading from wdm\n", @@ -418,299 +406,6 @@ "136 reading from wdm\n", "140 reading from wdm\n" ] - }, - { - "data": { - "text/html": [ - "
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TS0391976-01-01 00:00:001977-01-01 00:00:001h8784PREC-999.0000HOURLY PRECPRECIP TRAER IOWA
TS0411976-01-01 00:00:001977-01-01 00:00:001D366EVAP-999.0000DAILY EVAPFARMERS COOP WEATHER STN
TS0421976-01-01 00:00:001977-01-01 00:00:001D366WIND-999.0000DAILY WINDFARMERS COOP WEATHER STN
TS0461976-01-01 00:00:001977-01-01 00:00:002h4392SOLR-999.00002 HOUR RADFARMERS WEATHER STN
TS1131976-01-01 00:00:001977-01-01 00:00:001D366FLOW-999.0000DAILY FLOWIOWA RIVER MARSHALLTOWN
TS1191976-01-01 00:00:001977-01-01 00:00:001D366FLOW-999.0000DAILY FLOWIOWA RIVER MARENGO
TS1211976-01-01 00:00:001977-01-01 00:00:002h4392ATMP-999.00002 HOUR AIR TEMPCEDAR RAPIDS IOWA
TS1221976-01-01 00:00:001977-01-01 00:00:002h4392ATMP-999.00002 HOUR AIR TEMPIOWA FALLS IOWA
TS1231976-01-01 00:00:001977-01-01 00:00:002h4392ATMP-999.00002 HOUR AIR TEMPMARSHALLTOWN IOWA
TS1241976-01-01 00:00:001977-01-01 00:00:001D366DEWP-999.0000DAILY DEW PTCEDAR RAPIDS IOWA
TS1251976-01-01 00:00:001977-01-01 00:00:001D366DEWP-999.0000DAILY DEW PTIOWA FALLS IOWA
TS1261976-01-01 00:00:001977-01-01 00:00:001D366DEWP-999.0000DAILY DEW PTMARSHALLTOWN IOWA
TS1271976-01-01 00:00:001977-01-01 00:00:001D366SEDM-999.0000SEDIMENT CONCIOWA RIVER MARENGO
TS1311976-01-01 00:00:001977-01-01 00:00:001h8784PREC-999.0000HOURLY PRECPRECIP IOWA FALLS
TS1321976-01-01 00:00:001977-01-01 00:00:001h8784PREC-999.0000HOURLY PRECPRECIP SHEFFIELD
TS1341976-01-01 00:00:001977-01-01 00:00:001D366WTMP-999.0000WATER TEMPIOWA RIVER (ESTIMATED)
TS1351976-01-01 00:00:001977-01-01 00:00:001D366CLDC-999.0000CLOUD COVERWATERLOO (TENTHS)
TS1361976-01-01 00:00:001977-01-01 00:00:001D366FLOW-999.0000DAILY FLOWIOWA RIVER ROWAN
TS1401976-01-01 00:00:001977-01-01 00:00:001D366CLND-999.0000COLINDCOLUMN INDICATOR MEIER POND SUMMER-WINTER OUTLET
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1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 SEDM -999.0000 \n", - "TS131 1976-01-01 00:00:00 1977-01-01 00:00:00 1h 8784 PREC -999.0000 \n", - "TS132 1976-01-01 00:00:00 1977-01-01 00:00:00 1h 8784 PREC -999.0000 \n", - "TS134 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 WTMP -999.0000 \n", - "TS135 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 CLDC -999.0000 \n", - "TS136 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 FLOW -999.0000 \n", - "TS140 1976-01-01 00:00:00 1977-01-01 00:00:00 1D 366 CLND -999.0000 \n", - "\n", - " STAID STNAM \n", - "TS039 HOURLY PREC PRECIP TRAER IOWA \n", - "TS041 DAILY EVAP FARMERS COOP WEATHER STN \n", - "TS042 DAILY WIND FARMERS COOP WEATHER STN \n", - "TS046 2 HOUR RAD FARMERS WEATHER STN \n", - "TS113 DAILY FLOW IOWA RIVER MARSHALLTOWN \n", - "TS119 DAILY FLOW IOWA RIVER MARENGO \n", - "TS121 2 HOUR AIR TEMP CEDAR RAPIDS IOWA \n", - "TS122 2 HOUR AIR TEMP IOWA FALLS IOWA \n", - "TS123 2 HOUR AIR TEMP MARSHALLTOWN IOWA \n", - "TS124 DAILY DEW PT CEDAR RAPIDS IOWA \n", - "TS125 DAILY DEW PT IOWA FALLS IOWA \n", - "TS126 DAILY DEW PT MARSHALLTOWN IOWA \n", - "TS127 SEDIMENT CONC IOWA RIVER MARENGO \n", - "TS131 HOURLY PREC PRECIP IOWA FALLS \n", - "TS132 HOURLY PREC PRECIP SHEFFIELD \n", - "TS134 WATER TEMP IOWA RIVER (ESTIMATED) \n", - "TS135 CLOUD COVER WATERLOO (TENTHS) \n", - "TS136 DAILY FLOW IOWA RIVER ROWAN \n", - "TS140 COLIND COLUMN INDICATOR MEIER POND SUMMER-WINTER OUTLET " - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" } ], "source": [ @@ -734,15 +429,8 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 9, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T22:17:52.790472Z", - "iopub.status.busy": "2024-05-21T22:17:52.790005Z", - "iopub.status.idle": "2024-05-21T22:18:33.763504Z", - "shell.execute_reply": "2024-05-21T22:18:33.762890Z", - "shell.execute_reply.started": "2024-05-21T22:17:52.790454Z" - }, "vscode": { "languageId": "python" } @@ -752,90 +440,92 @@ "name": "stdout", "output_type": "stream", "text": [ - "2024-05-21 18:17:52.79 Processing started for file test10_hsp2_dev2WDM_6.h5; saveall=True\n", - "STATE initializing contexts.\n", - "Looking for custom om loader in python code test10_hsp2_dev2WDM_6.py\n", - "Looking for custom om json test10_hsp2_dev2WDM_6.json\n", - "Loaded objects & paths: insures all paths are valid, connects models as inputs\n", - "Tokenizing models\n", - "Operational model status: enabled\n", - "op_tokens has 123 elements, with 4 executable elements\n", - "2024-05-21 18:18:02.30 Simulation Start: 1976-01-01 00:00:00, Stop: 1977-01-01 00:00:00\n", - "2024-05-21 18:18:02.30 PERLND P001 DELT(minutes): 60\n", - "2024-05-21 18:18:02.86 SNOW\n", - "2024-05-21 18:18:03.96 PWATER\n", - "2024-05-21 18:18:04.47 PSTEMP\n", - "2024-05-21 18:18:04.52 PWTGAS\n", - "2024-05-21 18:18:04.63 RCHRES R001 DELT(minutes): 60\n", - "2024-05-21 18:18:04.65 HYDR\n", - "2024-05-21 18:18:13.19 ADCALC\n", - "2024-05-21 18:18:13.21 CONS\n", - "2024-05-21 18:18:13.34 HTRCH\n", - "2024-05-21 18:18:13.42 SEDTRN\n", - "2024-05-21 18:18:13.62 RQUAL\n", - "2024-05-21 18:18:15.29 GQUAL\n", - "2024-05-21 18:18:17.12 GENER G001 DELT(minutes): 60\n", - "2024-05-21 18:18:17.12 RCHRES R002 DELT(minutes): 60\n", - "2024-05-21 18:18:17.14 HYDR\n", - "2024-05-21 18:18:22.25 ADCALC\n", - "2024-05-21 18:18:22.26 CONS\n", - "2024-05-21 18:18:22.29 HTRCH\n", - "2024-05-21 18:18:22.30 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2024-05-21 18:18:22.36 SEDTRN\n", - "2024-05-21 18:18:22.37 Error count 3598: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", - "2024-05-21 18:18:22.51 RQUAL\n", - "2024-05-21 18:18:23.38 GQUAL\n", - "2024-05-21 18:18:24.14 RCHRES R003 DELT(minutes): 60\n", - "2024-05-21 18:18:24.16 HYDR\n", - "2024-05-21 18:18:24.24 ADCALC\n", - "2024-05-21 18:18:24.24 CONS\n", - "2024-05-21 18:18:24.27 HTRCH\n", - "2024-05-21 18:18:24.28 Error count 3: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2024-05-21 18:18:24.34 SEDTRN\n", - "2024-05-21 18:18:24.34 Error count 513: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", - "2024-05-21 18:18:24.57 RQUAL\n", - "2024-05-21 18:18:25.75 GQUAL\n", - "2024-05-21 18:18:27.09 RCHRES R004 DELT(minutes): 60\n", - "2024-05-21 18:18:27.16 HYDR\n", - "2024-05-21 18:18:27.31 ADCALC\n", - "2024-05-21 18:18:27.31 CONS\n", - "2024-05-21 18:18:27.38 HTRCH\n", - "2024-05-21 18:18:27.38 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2024-05-21 18:18:27.49 SEDTRN\n", - "2024-05-21 18:18:27.50 Error count 6720: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", - "2024-05-21 18:18:27.73 RQUAL\n", - "2024-05-21 18:18:29.05 GQUAL\n", - "2024-05-21 18:18:30.49 IMPLND I001 DELT(minutes): 60\n", - "2024-05-21 18:18:30.50 SNOW\n", - "2024-05-21 18:18:30.61 IWATER\n", - "2024-05-21 18:18:30.66 SOLIDS\n", - "2024-05-21 18:18:30.69 IWTGAS\n", - "2024-05-21 18:18:30.73 IQUAL\n", - "2024-05-21 18:18:30.79 RCHRES R005 DELT(minutes): 60\n", - "2024-05-21 18:18:30.81 HYDR\n", - "2024-05-21 18:18:30.90 ADCALC\n", - "2024-05-21 18:18:30.90 CONS\n", - "2024-05-21 18:18:30.94 HTRCH\n", - "2024-05-21 18:18:30.94 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2024-05-21 18:18:31.02 SEDTRN\n", - "2024-05-21 18:18:31.18 RQUAL\n", - "2024-05-21 18:18:32.08 GQUAL\n", - "2024-05-21 18:18:32.93 GENER G002 DELT(minutes): 60\n", - "2024-05-21 18:18:32.94 Done; Run time is about 00:40.1 (mm:ss)\n", + "2026-05-06 22:19:15.36 Processing started for file test10_hsp2_dev2WDM_6.h5; saveall=True\n", + "Skipping un-typed siminfo\n", + "op_tokens has 195 elements, with 4 executable elements\n", + "2026-05-06 22:19:24.26 Simulation Start: 1976-01-01 00:00:00, Stop: 1977-01-01 00:00:00\n", + "2026-05-06 22:19:24.26 PERLND P001 DELT(minutes): 60\n", + "2026-05-06 22:19:24.87 SNOW\n", + "2026-05-06 22:19:26.06 PWATER\n", + "2026-05-06 22:19:26.67 PSTEMP\n", + "2026-05-06 22:19:26.71 PWTGAS\n", + "2026-05-06 22:19:26.83 RCHRES R001 DELT(minutes): 60\n", + "2026-05-06 22:19:26.85 HYDR\n", + "2026-05-06 22:19:37.90 ADCALC\n", + "2026-05-06 22:19:37.92 CONS\n", + "2026-05-06 22:19:38.06 HTRCH\n", + "2026-05-06 22:19:38.16 SEDTRN\n", + "2026-05-06 22:19:38.40 RQUAL\n", + "2026-05-06 22:19:39.68 GQUAL\n", + "2026-05-06 22:19:41.04 DISPLY D005 DELT(minutes): 60\n", + "2026-05-06 22:19:41.04 DISPLY D001 DELT(minutes): 60\n", + "2026-05-06 22:19:41.04 GENER G001 DELT(minutes): 60\n", + "2026-05-06 22:19:41.04 DISPLY D002 DELT(minutes): 60\n", + "2026-05-06 22:19:41.04 RCHRES R002 DELT(minutes): 60\n", + "2026-05-06 22:19:41.06 HYDR\n", + "2026-05-06 22:19:46.60 ADCALC\n", + "2026-05-06 22:19:46.60 CONS\n", + "2026-05-06 22:19:46.64 HTRCH\n", + "2026-05-06 22:19:46.64 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 22:19:46.70 SEDTRN\n", + "2026-05-06 22:19:46.71 Error count 3598: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-06 22:19:46.86 RQUAL\n", + "2026-05-06 22:19:47.77 GQUAL\n", + "2026-05-06 22:19:48.71 RCHRES R003 DELT(minutes): 60\n", + "2026-05-06 22:19:48.72 HYDR\n", + "2026-05-06 22:19:48.81 ADCALC\n", + "2026-05-06 22:19:48.81 CONS\n", + "2026-05-06 22:19:48.85 HTRCH\n", + "2026-05-06 22:19:48.85 Error count 3: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 22:19:48.93 SEDTRN\n", + "2026-05-06 22:19:48.94 Error count 513: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-06 22:19:49.09 RQUAL\n", + "2026-05-06 22:19:49.99 GQUAL\n", + "2026-05-06 22:19:50.77 RCHRES R004 DELT(minutes): 60\n", + "2026-05-06 22:19:50.81 HYDR\n", + "2026-05-06 22:19:50.90 ADCALC\n", + "2026-05-06 22:19:50.90 CONS\n", + "2026-05-06 22:19:50.94 HTRCH\n", + "2026-05-06 22:19:50.94 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 22:19:51.01 SEDTRN\n", + "2026-05-06 22:19:51.02 Error count 6720: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-06 22:19:51.16 RQUAL\n", + "2026-05-06 22:19:52.08 GQUAL\n", + "2026-05-06 22:19:53.05 PLTGEN L002 DELT(minutes): 60\n", + "2026-05-06 22:19:53.05 IMPLND I001 DELT(minutes): 60\n", + "2026-05-06 22:19:53.06 SNOW\n", + "2026-05-06 22:19:53.17 IWATER\n", + "2026-05-06 22:19:53.23 SOLIDS\n", + "2026-05-06 22:19:53.26 IWTGAS\n", + "2026-05-06 22:19:53.31 IQUAL\n", + "2026-05-06 22:19:53.38 RCHRES R005 DELT(minutes): 60\n", + "2026-05-06 22:19:53.40 HYDR\n", + "2026-05-06 22:19:53.49 ADCALC\n", + "2026-05-06 22:19:53.50 CONS\n", + "2026-05-06 22:19:53.53 HTRCH\n", + "2026-05-06 22:19:53.54 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 22:19:53.60 SEDTRN\n", + "2026-05-06 22:19:53.77 RQUAL\n", + "2026-05-06 22:19:54.74 GQUAL\n", + "2026-05-06 22:19:55.74 DISPLY D003 DELT(minutes): 60\n", + "2026-05-06 22:19:55.74 GENER G002 DELT(minutes): 60\n", + "2026-05-06 22:19:55.74 DISPLY D004 DELT(minutes): 60\n", + "2026-05-06 22:19:55.74 PLTGEN L001 DELT(minutes): 60\n", + "2026-05-06 22:19:55.74 Done; Run time is about 00:40.3 (mm:ss)\n", "\n", "\n", " version\n", "name \n", - "Python 3.10.14 | packaged by conda-forge | (main, Mar...\n", - "hsp2 n/a\n", + "Python 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11....\n", + "hsp2 0.11.0a1\n", "numpy 1.26.4\n", - "numba 0.59.1\n", - "pandas 1.5.3\n", - "jupyterlab 4.1.6\n", - "notebook 7.1.3\n", - "os Linux-5.15.0-91-generic-x86_64-with-glibc2.35\n", - "processor x86_64\n", - "Date/Time 2024-05-21T18:18:33.252471\n", + "numba 0.64.0\n", + "pandas 2.3.3\n", + "jupyterlab 4.5.6\n", + "notebook n/a\n", + "os Linux-6.19.12-200.fc43.x86_64-x86_64-with-glib...\n", + "processor \n", + "Date/Time 2026-05-06T22:19:56.015349\n", " \n", "*** Profile printout saved to text file 'NumbaProfile.txt'.\n" ] @@ -848,15 +538,8 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 10, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T22:18:33.764922Z", - "iopub.status.busy": "2024-05-21T22:18:33.764597Z", - "iopub.status.idle": "2024-05-21T22:18:33.769555Z", - "shell.execute_reply": "2024-05-21T22:18:33.769078Z", - "shell.execute_reply.started": "2024-05-21T22:18:33.764907Z" - }, "vscode": { "languageId": "python" } @@ -866,70 +549,70 @@ "name": "stdout", "output_type": "stream", "text": [ - " 69292273 function calls (66180498 primitive calls) in 40.441 seconds\n", + " 68467163 function calls (65833437 primitive calls) in 40.629 seconds\n", "\n", " ncalls tottime percall cumtime percall filename:lineno(function)\n", - "107310/107286 5.062 0.000 6.031 0.000 ffi.py:190(__call__)\n", - " 5 2.519 0.504 4.409 0.882 GQUAL.py:243(_gqual_)\n", - " 17440 1.281 0.000 1.360 0.000 {method '_create_carray' of 'tables.hdf5extension.Array' objects}\n", - " 13784 0.816 0.000 0.816 0.000 {method '_g_close' of 'tables.hdf5extension.Leaf' objects}\n", - "1099645/185794 0.669 0.000 0.890 0.000 ir.py:318(_rec_list_vars)\n", - "9350662/9344872 0.643 0.000 0.886 0.000 {built-in method builtins.isinstance}\n", - " 69265 0.604 0.000 0.604 0.000 {method '_g_getattr' of 'tables.hdf5extension.AttributeSet' objects}\n", - " 1744 0.559 0.000 0.569 0.000 {method '_fill_col' of 'tables.tableextension.Row' objects}\n", - " 58232 0.551 0.000 0.551 0.000 {method '_g_get_objinfo' of 'tables.hdf5extension.Group' objects}\n", - " 34115 0.543 0.000 0.972 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1.163 0.000 {method 'format' of 'str' objects}\n", + " 170385 0.295 0.000 0.377 0.000 _utils.py:24(deduplicate)\n", + " 79636 0.292 0.000 0.351 0.000 os.py:674(__getitem__)\n", + " 1744 0.290 0.000 0.290 0.000 {tables.indexesextension.keysort}\n", + " 162677 0.283 0.000 1.991 0.000 typeddict.py:176(__getitem__)\n", + " 1744 0.271 0.000 0.281 0.000 {method '_fill_col' of 'tables.tableextension.Row' objects}\n", + " 7457 0.251 0.000 0.251 0.000 {method '_g_get_lchild_attr' of 'tables.hdf5extension.Group' objects}\n", + " 5 0.245 0.049 0.245 0.049 RQUAL.py:331(_rqual_run)\n", + " 233 0.230 0.001 0.230 0.001 {method '_g_flush' of 'tables.hdf5extension.Leaf' objects}\n", + " 316828 0.225 0.000 1.023 0.000 event.py:209(broadcast)\n", + " 87920 0.195 0.000 1.168 0.000 attributeset.py:277(__getattr__)\n", + "512878/404882 0.191 0.000 0.316 0.000 abstract.py:121(__hash__)\n", + " 311913 0.171 0.000 0.570 0.000 ssa.py:206(_run_ssa_block_pass)\n", + "486583/201457 0.164 0.000 1.087 0.000 _utils.py:44(__str__)\n", + " 53796 0.161 0.000 0.861 0.000 targetconfig.py:200()\n", + "51864/51660 0.158 0.000 0.304 0.000 manager.py:29(lookup)\n", + " 125618 0.157 0.000 0.586 0.000 fromnumeric.py:71(_wrapreduction)\n", + " 133115 0.157 0.000 0.931 0.000 values.py:544(_to_string)\n", + " 4500 0.154 0.000 0.277 0.000 numpy_support.py:380(ufunc_find_matching_loop)\n", + "29274/2459 0.154 0.000 8.519 0.003 node.py:182(__init__)\n", + " 5232 0.147 0.000 0.147 0.000 {method '_g_write_slice' of 'tables.hdf5extension.Array' objects}\n", + " 1572980 0.143 0.000 0.228 0.000 {method 'get' of 'dict' objects}\n", + " 31282 0.140 0.000 0.573 0.000 initialise.py:111(wrap_stream)\n", + " 5526 0.139 0.000 0.143 0.000 typeof.py:66(_typeof_buffer)\n", + " 202250 0.138 0.000 0.707 0.000 attributeset.py:47(issysattrname)\n", + " 193732 0.138 0.000 0.311 0.000 file.py:356(register_node)\n", + "359320/358330 0.137 0.000 0.293 0.000 _utils.py:54(get_reference)\n", + " 334937 0.135 0.000 0.178 0.000 event.py:270(on_end)\n", + " 162677 0.131 0.000 0.185 0.000 typeddict.py:37(_getitem)\n", + " 27682 0.131 0.000 0.136 0.000 controlflow.py:390(_dfs)\n", + " 1976 0.126 0.000 0.748 0.000 analysis.py:23(compute_use_defs)\n", + " 3778 0.126 0.000 0.134 0.000 analysis.py:81(def_reach)\n", + " 158414 0.125 0.000 0.840 0.000 event.py:404(end_event)\n", + " 129269 0.124 0.000 0.690 0.000 instructions.py:13(__init__)\n", + " 15379 0.121 0.000 1.480 0.000 attributeset.py:188(__init__)\n", + " 34115 0.121 0.000 1.498 0.000 attributeset.py:379(_g__setattr)\n", + " 709761 0.117 0.000 0.118 0.000 serialize.py:30(_numba_unpickle)\n", + " 158414 0.117 0.000 0.656 0.000 event.py:390(start_event)\n", + " 193675 0.116 0.000 1.690 0.000 file.py:370(cache_node)\n", + "1257638/1130430 0.115 0.000 0.492 0.000 {built-in method builtins.len}\n", + " 255593 0.113 0.000 0.245 0.000 group.py:800(__setattr__)\n", + "169979/89339 0.112 0.000 3.636 0.000 file.py:383(get_node)\n", + " 920654 0.111 0.000 0.111 0.000 {method 'startswith' of 'str' objects}\n", + " 316828 0.109 0.000 0.231 0.000 event.py:100(__init__)\n", + " 669874 0.106 0.000 0.106 0.000 event.py:138(is_start)\n", + "Cum Sum 54.84%\n" ] } ], @@ -971,15 +654,8 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 11, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T22:18:33.770229Z", - "iopub.status.busy": "2024-05-21T22:18:33.770060Z", - "iopub.status.idle": "2024-05-21T22:18:45.602438Z", - "shell.execute_reply": "2024-05-21T22:18:45.601680Z", - "shell.execute_reply.started": "2024-05-21T22:18:33.770211Z" - }, "vscode": { "languageId": "python" } @@ -989,90 +665,92 @@ "name": "stdout", "output_type": "stream", "text": [ - "2024-05-21 18:18:33.77 Processing started for file test10_hsp2_dev2WDM_6.h5; saveall=True\n", - "STATE initializing contexts.\n", - "Looking for custom om loader in python code test10_hsp2_dev2WDM_6.py\n", - "Looking for custom om json test10_hsp2_dev2WDM_6.json\n", - "Loaded objects & paths: insures all paths are valid, connects models as inputs\n", - "Tokenizing models\n", - "Operational model status: enabled\n", - "op_tokens has 123 elements, with 4 executable elements\n", - "2024-05-21 18:18:36.10 Simulation Start: 1976-01-01 00:00:00, Stop: 1977-01-01 00:00:00\n", - "2024-05-21 18:18:36.10 PERLND P001 DELT(minutes): 60\n", - "2024-05-21 18:18:36.13 SNOW\n", - "2024-05-21 18:18:36.21 PWATER\n", - "2024-05-21 18:18:36.35 PSTEMP\n", - "2024-05-21 18:18:36.37 PWTGAS\n", - "2024-05-21 18:18:36.45 RCHRES R001 DELT(minutes): 60\n", - "2024-05-21 18:18:36.46 HYDR\n", - "2024-05-21 18:18:36.55 ADCALC\n", - "2024-05-21 18:18:36.55 CONS\n", - "2024-05-21 18:18:36.59 HTRCH\n", - "2024-05-21 18:18:36.65 SEDTRN\n", - "2024-05-21 18:18:36.79 RQUAL\n", - "2024-05-21 18:18:37.78 GQUAL\n", - "2024-05-21 18:18:38.54 GENER G001 DELT(minutes): 60\n", - "2024-05-21 18:18:38.54 RCHRES R002 DELT(minutes): 60\n", - "2024-05-21 18:18:38.55 HYDR\n", - "2024-05-21 18:18:38.62 ADCALC\n", - "2024-05-21 18:18:38.63 CONS\n", - "2024-05-21 18:18:38.65 HTRCH\n", - "2024-05-21 18:18:38.66 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2024-05-21 18:18:38.70 SEDTRN\n", - "2024-05-21 18:18:38.71 Error count 3598: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", - "2024-05-21 18:18:38.87 RQUAL\n", - "2024-05-21 18:18:40.16 GQUAL\n", - "2024-05-21 18:18:40.79 RCHRES R003 DELT(minutes): 60\n", - "2024-05-21 18:18:40.80 HYDR\n", - "2024-05-21 18:18:40.86 ADCALC\n", - "2024-05-21 18:18:40.86 CONS\n", - "2024-05-21 18:18:40.89 HTRCH\n", - "2024-05-21 18:18:40.89 Error count 3: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2024-05-21 18:18:40.94 SEDTRN\n", - "2024-05-21 18:18:40.95 Error count 513: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", - "2024-05-21 18:18:41.05 RQUAL\n", - "2024-05-21 18:18:41.72 GQUAL\n", - "2024-05-21 18:18:42.17 RCHRES R004 DELT(minutes): 60\n", - "2024-05-21 18:18:42.20 HYDR\n", - "2024-05-21 18:18:42.27 ADCALC\n", - "2024-05-21 18:18:42.27 CONS\n", - "2024-05-21 18:18:42.30 HTRCH\n", - "2024-05-21 18:18:42.31 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2024-05-21 18:18:42.35 SEDTRN\n", - "2024-05-21 18:18:42.36 Error count 6720: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", - "2024-05-21 18:18:42.47 RQUAL\n", - "2024-05-21 18:18:43.19 GQUAL\n", - "2024-05-21 18:18:43.75 IMPLND I001 DELT(minutes): 60\n", - "2024-05-21 18:18:43.75 SNOW\n", - "2024-05-21 18:18:43.83 IWATER\n", - "2024-05-21 18:18:43.87 SOLIDS\n", - "2024-05-21 18:18:43.88 IWTGAS\n", - "2024-05-21 18:18:43.91 IQUAL\n", - "2024-05-21 18:18:43.95 RCHRES R005 DELT(minutes): 60\n", - "2024-05-21 18:18:43.97 HYDR\n", - "2024-05-21 18:18:44.04 ADCALC\n", - "2024-05-21 18:18:44.05 CONS\n", - "2024-05-21 18:18:44.07 HTRCH\n", - "2024-05-21 18:18:44.08 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", - "2024-05-21 18:18:44.12 SEDTRN\n", - "2024-05-21 18:18:44.25 RQUAL\n", - "2024-05-21 18:18:44.99 GQUAL\n", - "2024-05-21 18:18:45.56 GENER G002 DELT(minutes): 60\n", - "2024-05-21 18:18:45.57 Done; Run time is about 00:11.7 (mm:ss)\n", + "2026-05-06 22:19:56.34 Processing started for file test10_hsp2_dev2WDM_6.h5; saveall=True\n", + "Skipping un-typed siminfo\n", + "op_tokens has 195 elements, with 4 executable elements\n", + "2026-05-06 22:19:59.03 Simulation Start: 1976-01-01 00:00:00, Stop: 1977-01-01 00:00:00\n", + "2026-05-06 22:19:59.03 PERLND P001 DELT(minutes): 60\n", + "2026-05-06 22:19:59.07 SNOW\n", + "2026-05-06 22:19:59.15 PWATER\n", + "2026-05-06 22:19:59.29 PSTEMP\n", + "2026-05-06 22:19:59.31 PWTGAS\n", + "2026-05-06 22:19:59.39 RCHRES R001 DELT(minutes): 60\n", + "2026-05-06 22:19:59.40 HYDR\n", + "2026-05-06 22:19:59.49 ADCALC\n", + "2026-05-06 22:19:59.49 CONS\n", + "2026-05-06 22:19:59.53 HTRCH\n", + "2026-05-06 22:19:59.59 SEDTRN\n", + "2026-05-06 22:19:59.73 RQUAL\n", + "2026-05-06 22:20:00.77 GQUAL\n", + "2026-05-06 22:20:01.69 DISPLY D005 DELT(minutes): 60\n", + "2026-05-06 22:20:01.69 DISPLY D001 DELT(minutes): 60\n", + "2026-05-06 22:20:01.69 GENER G001 DELT(minutes): 60\n", + "2026-05-06 22:20:01.69 DISPLY D002 DELT(minutes): 60\n", + "2026-05-06 22:20:01.69 RCHRES R002 DELT(minutes): 60\n", + "2026-05-06 22:20:01.70 HYDR\n", + "2026-05-06 22:20:01.78 ADCALC\n", + "2026-05-06 22:20:01.79 CONS\n", + "2026-05-06 22:20:01.82 HTRCH\n", + "2026-05-06 22:20:01.82 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 22:20:01.88 SEDTRN\n", + "2026-05-06 22:20:01.88 Error count 3598: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-06 22:20:02.00 RQUAL\n", + "2026-05-06 22:20:02.81 GQUAL\n", + "2026-05-06 22:20:03.45 RCHRES R003 DELT(minutes): 60\n", + "2026-05-06 22:20:03.47 HYDR\n", + "2026-05-06 22:20:03.54 ADCALC\n", + "2026-05-06 22:20:03.54 CONS\n", + "2026-05-06 22:20:03.57 HTRCH\n", + "2026-05-06 22:20:03.57 Error count 3: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 22:20:03.63 SEDTRN\n", + "2026-05-06 22:20:03.63 Error count 513: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-06 22:20:03.75 RQUAL\n", + "2026-05-06 22:20:04.65 GQUAL\n", + "2026-05-06 22:20:05.19 RCHRES R004 DELT(minutes): 60\n", + "2026-05-06 22:20:05.23 HYDR\n", + "2026-05-06 22:20:05.31 ADCALC\n", + "2026-05-06 22:20:05.31 CONS\n", + "2026-05-06 22:20:05.34 HTRCH\n", + "2026-05-06 22:20:05.35 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 22:20:05.40 SEDTRN\n", + "2026-05-06 22:20:05.41 Error count 6720: SEDTRN: Warning -- bed storage of sediment size fraction sand is empty\n", + "2026-05-06 22:20:05.53 RQUAL\n", + "2026-05-06 22:20:06.31 GQUAL\n", + "2026-05-06 22:20:06.96 PLTGEN L002 DELT(minutes): 60\n", + "2026-05-06 22:20:06.96 IMPLND I001 DELT(minutes): 60\n", + "2026-05-06 22:20:06.96 SNOW\n", + "2026-05-06 22:20:07.05 IWATER\n", + "2026-05-06 22:20:07.09 SOLIDS\n", + "2026-05-06 22:20:07.10 IWTGAS\n", + "2026-05-06 22:20:07.13 IQUAL\n", + "2026-05-06 22:20:07.18 RCHRES R005 DELT(minutes): 60\n", + "2026-05-06 22:20:07.19 HYDR\n", + "2026-05-06 22:20:07.26 ADCALC\n", + "2026-05-06 22:20:07.27 CONS\n", + "2026-05-06 22:20:07.29 HTRCH\n", + "2026-05-06 22:20:07.30 Error count 1: HTRCH: Water temperature is above 66 C (150 F) -- In most cases, this indicates an instability in advection\n", + "2026-05-06 22:20:07.35 SEDTRN\n", + "2026-05-06 22:20:07.48 RQUAL\n", + "2026-05-06 22:20:08.34 GQUAL\n", + "2026-05-06 22:20:09.03 DISPLY D003 DELT(minutes): 60\n", + "2026-05-06 22:20:09.03 GENER G002 DELT(minutes): 60\n", + "2026-05-06 22:20:09.04 DISPLY D004 DELT(minutes): 60\n", + "2026-05-06 22:20:09.04 PLTGEN L001 DELT(minutes): 60\n", + "2026-05-06 22:20:09.04 Done; Run time is about 00:12.6 (mm:ss)\n", "\n", "\n", " version\n", "name \n", - "Python 3.10.14 | packaged by conda-forge | (main, Mar...\n", - "hsp2 n/a\n", + "Python 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11....\n", + "hsp2 0.11.0a1\n", "numpy 1.26.4\n", - "numba 0.59.1\n", - "pandas 1.5.3\n", - "jupyterlab 4.1.6\n", - "notebook 7.1.3\n", - "os Linux-5.15.0-91-generic-x86_64-with-glibc2.35\n", - "processor x86_64\n", - "Date/Time 2024-05-21T18:18:45.579401\n" + "numba 0.64.0\n", + "pandas 2.3.3\n", + "jupyterlab 4.5.6\n", + "notebook n/a\n", + "os Linux-6.19.12-200.fc43.x86_64-x86_64-with-glib...\n", + "processor \n", + "Date/Time 2026-05-06T22:20:09.051874\n" ] } ], @@ -1139,15 +817,8 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 12, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T22:18:45.604032Z", - "iopub.status.busy": "2024-05-21T22:18:45.603921Z", - "iopub.status.idle": "2024-05-21T22:18:45.838952Z", - "shell.execute_reply": "2024-05-21T22:18:45.838529Z", - "shell.execute_reply.started": "2024-05-21T22:18:45.604023Z" - }, "vscode": { "languageId": "python" } @@ -1160,8 +831,8 @@ "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[14], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m summary \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_hdf\u001b[49m\u001b[43m(\u001b[49m\u001b[43mHBN\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mSUMMARY\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2\u001b[0m summary\u001b[38;5;241m.\u001b[39mFrequency\u001b[38;5;241m.\u001b[39munique()\n", - "File \u001b[0;32m~/anaconda3/envs/hsp2_310/lib/python3.10/site-packages/pandas/io/pytables.py:414\u001b[0m, in \u001b[0;36mread_hdf\u001b[0;34m(path_or_buf, key, mode, errors, where, start, stop, columns, iterator, chunksize, **kwargs)\u001b[0m\n\u001b[1;32m 411\u001b[0m exists \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 413\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m exists:\n\u001b[0;32m--> 414\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFile \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpath_or_buf\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m does not exist\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 416\u001b[0m store \u001b[38;5;241m=\u001b[39m HDFStore(path_or_buf, mode\u001b[38;5;241m=\u001b[39mmode, errors\u001b[38;5;241m=\u001b[39merrors, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 417\u001b[0m \u001b[38;5;66;03m# can't auto open/close if we are using an iterator\u001b[39;00m\n\u001b[1;32m 418\u001b[0m \u001b[38;5;66;03m# so delegate to the iterator\u001b[39;00m\n", + "Cell \u001b[0;32mIn[12], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m summary \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_hdf\u001b[49m\u001b[43m(\u001b[49m\u001b[43mHBN\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mSUMMARY\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2\u001b[0m summary\u001b[38;5;241m.\u001b[39mFrequency\u001b[38;5;241m.\u001b[39munique()\n", + "File \u001b[0;32m~/miniconda3/envs/default311/lib/python3.11/site-packages/pandas/io/pytables.py:437\u001b[0m, in \u001b[0;36mread_hdf\u001b[0;34m(path_or_buf, key, mode, errors, where, start, stop, columns, iterator, chunksize, **kwargs)\u001b[0m\n\u001b[1;32m 434\u001b[0m exists \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 436\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m exists:\n\u001b[0;32m--> 437\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFile \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpath_or_buf\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m does not exist\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 439\u001b[0m store \u001b[38;5;241m=\u001b[39m HDFStore(path_or_buf, mode\u001b[38;5;241m=\u001b[39mmode, errors\u001b[38;5;241m=\u001b[39merrors, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 440\u001b[0m \u001b[38;5;66;03m# can't auto open/close if we are using an iterator\u001b[39;00m\n\u001b[1;32m 441\u001b[0m \u001b[38;5;66;03m# so delegate to the iterator\u001b[39;00m\n", "\u001b[0;31mFileNotFoundError\u001b[0m: File test10_hspf.h5 does not exist" ] } @@ -1189,12 +860,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.792607Z", - "iopub.status.idle": "2024-04-28T16:47:35.792790Z", - "shell.execute_reply": "2024-04-28T16:47:35.792705Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.792697Z" - }, "vscode": { "languageId": "python" } @@ -1208,15 +873,8 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T22:20:52.323144Z", - "iopub.status.busy": "2024-05-21T22:20:52.322635Z", - "iopub.status.idle": "2024-05-21T22:20:52.327715Z", - "shell.execute_reply": "2024-05-21T22:20:52.327288Z", - "shell.execute_reply.started": "2024-05-21T22:20:52.323112Z" - }, "vscode": { "languageId": "python" } @@ -1256,15 +914,8 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "metadata": { - "execution": { - "iopub.execute_input": "2024-05-21T22:21:13.318802Z", - "iopub.status.busy": "2024-05-21T22:21:13.318576Z", - "iopub.status.idle": "2024-05-21T22:21:13.323178Z", - "shell.execute_reply": "2024-05-21T22:21:13.322666Z", - "shell.execute_reply.started": "2024-05-21T22:21:13.318786Z" - }, "vscode": { "languageId": "python" } @@ -1296,12 +947,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.794953Z", - "iopub.status.idle": "2024-04-28T16:47:35.795205Z", - "shell.execute_reply": "2024-04-28T16:47:35.795114Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.795106Z" - }, "vscode": { "languageId": "python" } @@ -1336,12 +981,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.795724Z", - "iopub.status.idle": "2024-04-28T16:47:35.795951Z", - "shell.execute_reply": "2024-04-28T16:47:35.795866Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.795858Z" - }, "vscode": { "languageId": "python" } @@ -1356,12 +995,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.796421Z", - "iopub.status.idle": "2024-04-28T16:47:35.796643Z", - "shell.execute_reply": "2024-04-28T16:47:35.796560Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.796552Z" - }, "vscode": { "languageId": "python" } @@ -1383,12 +1016,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.797125Z", - "iopub.status.idle": "2024-04-28T16:47:35.797416Z", - "shell.execute_reply": "2024-04-28T16:47:35.797332Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.797324Z" - }, "vscode": { "languageId": "python" } @@ -1402,12 +1029,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.797835Z", - "iopub.status.idle": "2024-04-28T16:47:35.798053Z", - "shell.execute_reply": "2024-04-28T16:47:35.797969Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.797961Z" - }, "vscode": { "languageId": "python" } @@ -1421,12 +1042,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.798483Z", - "iopub.status.idle": "2024-04-28T16:47:35.798717Z", - "shell.execute_reply": "2024-04-28T16:47:35.798637Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.798629Z" - }, "vscode": { "languageId": "python" } @@ -1448,12 +1063,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.799127Z", - "iopub.status.idle": "2024-04-28T16:47:35.799401Z", - "shell.execute_reply": "2024-04-28T16:47:35.799320Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.799312Z" - }, "vscode": { "languageId": "python" } @@ -1467,12 +1076,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.799811Z", - "iopub.status.idle": "2024-04-28T16:47:35.799997Z", - "shell.execute_reply": "2024-04-28T16:47:35.799937Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.799931Z" - }, "vscode": { "languageId": "python" } @@ -1493,12 +1096,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.800364Z", - "iopub.status.idle": "2024-04-28T16:47:35.800525Z", - "shell.execute_reply": "2024-04-28T16:47:35.800472Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.800466Z" - }, "vscode": { "languageId": "python" } @@ -1512,12 +1109,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.800820Z", - "iopub.status.idle": "2024-04-28T16:47:35.800925Z", - "shell.execute_reply": "2024-04-28T16:47:35.800875Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.800870Z" - }, "vscode": { "languageId": "python" } @@ -1538,12 +1129,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.801179Z", - "iopub.status.idle": "2024-04-28T16:47:35.801281Z", - "shell.execute_reply": "2024-04-28T16:47:35.801232Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.801227Z" - }, "vscode": { "languageId": "python" } @@ -1557,12 +1142,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.801629Z", - "iopub.status.idle": "2024-04-28T16:47:35.801742Z", - "shell.execute_reply": "2024-04-28T16:47:35.801689Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.801684Z" - }, "vscode": { "languageId": "python" } @@ -1583,12 +1162,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.802034Z", - "iopub.status.idle": "2024-04-28T16:47:35.802140Z", - "shell.execute_reply": "2024-04-28T16:47:35.802088Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.802084Z" - }, "vscode": { "languageId": "python" } @@ -1602,12 +1175,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.802456Z", - "iopub.status.idle": "2024-04-28T16:47:35.802559Z", - "shell.execute_reply": "2024-04-28T16:47:35.802511Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.802506Z" - }, "vscode": { "languageId": "python" } @@ -1628,12 +1195,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.802805Z", - "iopub.status.idle": "2024-04-28T16:47:35.802909Z", - "shell.execute_reply": "2024-04-28T16:47:35.802861Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.802853Z" - }, "vscode": { "languageId": "python" } @@ -1647,12 +1208,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.803196Z", - "iopub.status.idle": "2024-04-28T16:47:35.803295Z", - "shell.execute_reply": "2024-04-28T16:47:35.803248Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.803243Z" - }, "vscode": { "languageId": "python" } @@ -1673,12 +1228,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.803608Z", - "iopub.status.idle": "2024-04-28T16:47:35.803715Z", - "shell.execute_reply": "2024-04-28T16:47:35.803666Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.803661Z" - }, "vscode": { "languageId": "python" } @@ -1692,12 +1241,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.804024Z", - "iopub.status.idle": "2024-04-28T16:47:35.804126Z", - "shell.execute_reply": "2024-04-28T16:47:35.804078Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.804073Z" - }, "vscode": { "languageId": "python" } @@ -1718,12 +1261,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.804408Z", - "iopub.status.idle": "2024-04-28T16:47:35.804507Z", - "shell.execute_reply": "2024-04-28T16:47:35.804459Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.804455Z" - }, "vscode": { "languageId": "python" } @@ -1738,12 +1275,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.804766Z", - "iopub.status.idle": "2024-04-28T16:47:35.804863Z", - "shell.execute_reply": "2024-04-28T16:47:35.804817Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.804812Z" - }, "scrolled": true, "vscode": { "languageId": "python" @@ -1766,12 +1297,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.805199Z", - "iopub.status.idle": "2024-04-28T16:47:35.805309Z", - "shell.execute_reply": "2024-04-28T16:47:35.805260Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.805254Z" - }, "vscode": { "languageId": "python" } @@ -1785,12 +1310,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.805681Z", - "iopub.status.idle": "2024-04-28T16:47:35.805793Z", - "shell.execute_reply": "2024-04-28T16:47:35.805743Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.805737Z" - }, "vscode": { "languageId": "python" } @@ -1804,12 +1323,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.806219Z", - "iopub.status.idle": "2024-04-28T16:47:35.806350Z", - "shell.execute_reply": "2024-04-28T16:47:35.806289Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.806283Z" - }, "vscode": { "languageId": "python" } @@ -1831,12 +1344,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.806740Z", - "iopub.status.idle": "2024-04-28T16:47:35.806886Z", - "shell.execute_reply": "2024-04-28T16:47:35.806814Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.806808Z" - }, "vscode": { "languageId": "python" } @@ -1850,12 +1357,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.807172Z", - "iopub.status.idle": "2024-04-28T16:47:35.807318Z", - "shell.execute_reply": "2024-04-28T16:47:35.807251Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.807244Z" - }, "vscode": { "languageId": "python" } @@ -1876,12 +1377,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.807945Z", - "iopub.status.idle": "2024-04-28T16:47:35.808090Z", - "shell.execute_reply": "2024-04-28T16:47:35.808026Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.808020Z" - }, "vscode": { "languageId": "python" } @@ -1895,12 +1390,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.808424Z", - "iopub.status.idle": "2024-04-28T16:47:35.808562Z", - "shell.execute_reply": "2024-04-28T16:47:35.808497Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.808491Z" - }, "vscode": { "languageId": "python" } @@ -1921,12 +1410,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.809143Z", - "iopub.status.idle": "2024-04-28T16:47:35.809260Z", - "shell.execute_reply": "2024-04-28T16:47:35.809207Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.809202Z" - }, "vscode": { "languageId": "python" } @@ -1940,12 +1423,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.809599Z", - "iopub.status.idle": "2024-04-28T16:47:35.809703Z", - "shell.execute_reply": "2024-04-28T16:47:35.809653Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.809648Z" - }, "vscode": { "languageId": "python" } @@ -1966,12 +1443,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.810200Z", - "iopub.status.idle": "2024-04-28T16:47:35.810358Z", - "shell.execute_reply": "2024-04-28T16:47:35.810277Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.810270Z" - }, "vscode": { "languageId": "python" } @@ -1985,12 +1456,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.810827Z", - "iopub.status.idle": "2024-04-28T16:47:35.810995Z", - "shell.execute_reply": "2024-04-28T16:47:35.810926Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.810920Z" - }, "vscode": { "languageId": "python" } @@ -2011,12 +1476,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.811302Z", - "iopub.status.idle": "2024-04-28T16:47:35.811424Z", - "shell.execute_reply": "2024-04-28T16:47:35.811366Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.811361Z" - }, "vscode": { "languageId": "python" } @@ -2030,12 +1489,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.811817Z", - "iopub.status.idle": "2024-04-28T16:47:35.811925Z", - "shell.execute_reply": "2024-04-28T16:47:35.811875Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.811870Z" - }, "vscode": { "languageId": "python" } @@ -2056,12 +1509,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.812350Z", - "iopub.status.idle": "2024-04-28T16:47:35.812455Z", - "shell.execute_reply": "2024-04-28T16:47:35.812403Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.812398Z" - }, "vscode": { "languageId": "python" } @@ -2075,12 +1522,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.812816Z", - "iopub.status.idle": "2024-04-28T16:47:35.812974Z", - "shell.execute_reply": "2024-04-28T16:47:35.812909Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.812901Z" - }, "vscode": { "languageId": "python" } @@ -2101,12 +1542,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.813322Z", - "iopub.status.idle": "2024-04-28T16:47:35.813469Z", - "shell.execute_reply": "2024-04-28T16:47:35.813409Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.813403Z" - }, "vscode": { "languageId": "python" } @@ -2120,12 +1555,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.814100Z", - "iopub.status.idle": "2024-04-28T16:47:35.814241Z", - "shell.execute_reply": "2024-04-28T16:47:35.814178Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.814171Z" - }, "vscode": { "languageId": "python" } @@ -2146,12 +1575,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.814642Z", - "iopub.status.idle": "2024-04-28T16:47:35.814781Z", - "shell.execute_reply": "2024-04-28T16:47:35.814719Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.814713Z" - }, "vscode": { "languageId": "python" } @@ -2165,12 +1588,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.815196Z", - "iopub.status.idle": "2024-04-28T16:47:35.815325Z", - "shell.execute_reply": "2024-04-28T16:47:35.815265Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.815259Z" - }, "vscode": { "languageId": "python" } @@ -2191,12 +1608,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.815862Z", - "iopub.status.idle": "2024-04-28T16:47:35.815972Z", - "shell.execute_reply": "2024-04-28T16:47:35.815920Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.815915Z" - }, "vscode": { "languageId": "python" } @@ -2210,12 +1621,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.816307Z", - "iopub.status.idle": "2024-04-28T16:47:35.816446Z", - "shell.execute_reply": "2024-04-28T16:47:35.816359Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.816354Z" - }, "vscode": { "languageId": "python" } @@ -2236,12 +1641,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.816833Z", - "iopub.status.idle": "2024-04-28T16:47:35.816974Z", - "shell.execute_reply": "2024-04-28T16:47:35.816908Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.816901Z" - }, "vscode": { "languageId": "python" } @@ -2255,12 +1654,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.817354Z", - "iopub.status.idle": "2024-04-28T16:47:35.817492Z", - "shell.execute_reply": "2024-04-28T16:47:35.817427Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.817420Z" - }, "vscode": { "languageId": "python" } @@ -2281,12 +1674,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.817940Z", - "iopub.status.idle": "2024-04-28T16:47:35.818074Z", - "shell.execute_reply": "2024-04-28T16:47:35.818011Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.818005Z" - }, "vscode": { "languageId": "python" } @@ -2300,12 +1687,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.818461Z", - "iopub.status.idle": "2024-04-28T16:47:35.818570Z", - "shell.execute_reply": "2024-04-28T16:47:35.818520Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.818515Z" - }, "vscode": { "languageId": "python" } @@ -2326,12 +1707,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.819065Z", - "iopub.status.idle": "2024-04-28T16:47:35.819219Z", - "shell.execute_reply": "2024-04-28T16:47:35.819143Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.819136Z" - }, "vscode": { "languageId": "python" } @@ -2345,12 +1720,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.819926Z", - "iopub.status.idle": "2024-04-28T16:47:35.820060Z", - "shell.execute_reply": "2024-04-28T16:47:35.819999Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.819993Z" - }, "vscode": { "languageId": "python" } @@ -2371,12 +1740,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.820477Z", - "iopub.status.idle": "2024-04-28T16:47:35.820590Z", - "shell.execute_reply": "2024-04-28T16:47:35.820538Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.820533Z" - }, "vscode": { "languageId": "python" } @@ -2390,12 +1753,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.821046Z", - "iopub.status.idle": "2024-04-28T16:47:35.821151Z", - "shell.execute_reply": "2024-04-28T16:47:35.821101Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.821096Z" - }, "vscode": { "languageId": "python" } @@ -2416,12 +1773,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.821568Z", - "iopub.status.idle": "2024-04-28T16:47:35.821733Z", - "shell.execute_reply": "2024-04-28T16:47:35.821667Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.821660Z" - }, "vscode": { "languageId": "python" } @@ -2435,12 +1786,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.822186Z", - "iopub.status.idle": "2024-04-28T16:47:35.822327Z", - "shell.execute_reply": "2024-04-28T16:47:35.822262Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.822256Z" - }, "vscode": { "languageId": "python" } @@ -2461,12 +1806,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.822942Z", - "iopub.status.idle": "2024-04-28T16:47:35.823084Z", - "shell.execute_reply": "2024-04-28T16:47:35.823020Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.823014Z" - }, "vscode": { "languageId": "python" } @@ -2480,12 +1819,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.823410Z", - "iopub.status.idle": "2024-04-28T16:47:35.823541Z", - "shell.execute_reply": "2024-04-28T16:47:35.823481Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.823475Z" - }, "vscode": { "languageId": "python" } @@ -2506,12 +1839,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.823928Z", - "iopub.status.idle": "2024-04-28T16:47:35.824052Z", - "shell.execute_reply": "2024-04-28T16:47:35.823994Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.823988Z" - }, "vscode": { "languageId": "python" } @@ -2525,12 +1852,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.824587Z", - "iopub.status.idle": "2024-04-28T16:47:35.824696Z", - "shell.execute_reply": "2024-04-28T16:47:35.824646Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.824641Z" - }, "vscode": { "languageId": "python" } @@ -2551,12 +1872,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.824966Z", - "iopub.status.idle": "2024-04-28T16:47:35.825072Z", - "shell.execute_reply": "2024-04-28T16:47:35.825022Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.825017Z" - }, "vscode": { "languageId": "python" } @@ -2570,12 +1885,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.825613Z", - "iopub.status.idle": "2024-04-28T16:47:35.825757Z", - "shell.execute_reply": "2024-04-28T16:47:35.825690Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.825683Z" - }, "vscode": { "languageId": "python" } @@ -2596,12 +1905,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.826143Z", - "iopub.status.idle": "2024-04-28T16:47:35.826253Z", - "shell.execute_reply": "2024-04-28T16:47:35.826203Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.826198Z" - }, "vscode": { "languageId": "python" } @@ -2615,12 +1918,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.826578Z", - "iopub.status.idle": "2024-04-28T16:47:35.826714Z", - "shell.execute_reply": "2024-04-28T16:47:35.826648Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.826642Z" - }, "vscode": { "languageId": "python" } @@ -2641,12 +1938,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.827027Z", - "iopub.status.idle": "2024-04-28T16:47:35.827177Z", - "shell.execute_reply": "2024-04-28T16:47:35.827115Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.827109Z" - }, "vscode": { "languageId": "python" } @@ -2660,12 +1951,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.827817Z", - "iopub.status.idle": "2024-04-28T16:47:35.827945Z", - "shell.execute_reply": "2024-04-28T16:47:35.827887Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.827881Z" - }, "vscode": { "languageId": "python" } @@ -2686,12 +1971,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.828529Z", - "iopub.status.idle": "2024-04-28T16:47:35.828662Z", - "shell.execute_reply": "2024-04-28T16:47:35.828598Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.828592Z" - }, "scrolled": true, "vscode": { "languageId": "python" @@ -2707,12 +1986,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.829109Z", - "iopub.status.idle": "2024-04-28T16:47:35.829220Z", - "shell.execute_reply": "2024-04-28T16:47:35.829168Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.829163Z" - }, "vscode": { "languageId": "python" } @@ -2734,12 +2007,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.829520Z", - "iopub.status.idle": "2024-04-28T16:47:35.829624Z", - "shell.execute_reply": "2024-04-28T16:47:35.829575Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.829570Z" - }, "vscode": { "languageId": "python" } @@ -2753,12 +2020,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.829967Z", - "iopub.status.idle": "2024-04-28T16:47:35.830075Z", - "shell.execute_reply": "2024-04-28T16:47:35.830022Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.830017Z" - }, "vscode": { "languageId": "python" } @@ -2772,12 +2033,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.830423Z", - "iopub.status.idle": "2024-04-28T16:47:35.830530Z", - "shell.execute_reply": "2024-04-28T16:47:35.830480Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.830475Z" - }, "vscode": { "languageId": "python" } @@ -2799,12 +2054,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.830926Z", - "iopub.status.idle": "2024-04-28T16:47:35.831031Z", - "shell.execute_reply": "2024-04-28T16:47:35.830981Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.830976Z" - }, "vscode": { "languageId": "python" } @@ -2818,12 +2067,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.831391Z", - "iopub.status.idle": "2024-04-28T16:47:35.831494Z", - "shell.execute_reply": "2024-04-28T16:47:35.831445Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.831440Z" - }, "vscode": { "languageId": "python" } @@ -2844,12 +2087,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.831747Z", - "iopub.status.idle": "2024-04-28T16:47:35.831846Z", - "shell.execute_reply": "2024-04-28T16:47:35.831799Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.831794Z" - }, "vscode": { "languageId": "python" } @@ -2863,12 +2100,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.832177Z", - "iopub.status.idle": "2024-04-28T16:47:35.832284Z", - "shell.execute_reply": "2024-04-28T16:47:35.832233Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.832227Z" - }, "vscode": { "languageId": "python" } @@ -2889,12 +2120,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.832846Z", - "iopub.status.idle": "2024-04-28T16:47:35.832948Z", - "shell.execute_reply": "2024-04-28T16:47:35.832899Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.832894Z" - }, "vscode": { "languageId": "python" } @@ -2908,12 +2133,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.833229Z", - "iopub.status.idle": "2024-04-28T16:47:35.833331Z", - "shell.execute_reply": "2024-04-28T16:47:35.833282Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.833277Z" - }, "vscode": { "languageId": "python" } @@ -2934,12 +2153,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.833627Z", - "iopub.status.idle": "2024-04-28T16:47:35.833835Z", - "shell.execute_reply": "2024-04-28T16:47:35.833733Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.833723Z" - }, "vscode": { "languageId": "python" } @@ -2953,12 +2166,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.834395Z", - "iopub.status.idle": "2024-04-28T16:47:35.834543Z", - "shell.execute_reply": "2024-04-28T16:47:35.834472Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.834467Z" - }, "vscode": { "languageId": "python" } @@ -2979,12 +2186,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.835103Z", - "iopub.status.idle": "2024-04-28T16:47:35.835259Z", - "shell.execute_reply": "2024-04-28T16:47:35.835191Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.835185Z" - }, "vscode": { "languageId": "python" } @@ -2998,12 +2199,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "execution": { - "iopub.status.busy": "2024-04-28T16:47:35.835678Z", - "iopub.status.idle": "2024-04-28T16:47:35.835800Z", - "shell.execute_reply": "2024-04-28T16:47:35.835747Z", - "shell.execute_reply.started": "2024-04-28T16:47:35.835742Z" - }, "vscode": { "languageId": "python" } @@ -3030,7 +2225,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.14" + "version": "3.11.11" }, "toc-showmarkdowntxt": false }, diff --git a/tests/test10specl/HSP2results/test10specl.uci b/tests/test10specl/HSP2results/test10specl.uci index 54b48e69..7e07bfc8 100644 --- a/tests/test10specl/HSP2results/test10specl.uci +++ b/tests/test10specl/HSP2results/test10specl.uci @@ -9,7 +9,7 @@ END GLOBAL *** This test run uses MASS-LINK and SCHEMATIC blocks *** -FILES +FILES ***<----FILE NAME-------------------------------------------------> WDM 21 test10.wdm MESSU 22 test10.ech @@ -309,7 +309,7 @@ RCHRES ACTIVITY RCHRES Active Sections (1=Active, 0=Inactive) *** # - # HYFG ADFG CNFG HTFG SDFG GQFG OXFG NUFG PKFG PHFG *** - 1 5 1 1 1 1 1 1 1 1 1 1 + 1 5 1 1 1 1 1 1 1 1 1 1 END ACTIVITY PRINT-INFO @@ -618,8 +618,8 @@ RCHRES OX-BENPARM RCHRES BENOD TCBEN EXPOD BRBOD(1) BRBOD(2) EXPREL *** - # - # mg/m2.hr mg/m2.hr mg/m2.hr *** - 1 5 10. 1.1 1.2 20. 25. 1.3 + # - # mg/m2.hr mg/m2.hr mg/m2.hr *** + 1 5 10. 1.1 1.2 20. 25. 1.3 END OX-BENPARM OX-CFOREA @@ -649,46 +649,46 @@ RCHRES END NUT-FLAGS NUT-BENPARM - RCHRES BRTAM(1) BRTAM(2) BRPO4(1) BRPO4(2) ANAER *** - # - # mg/m2.hr mg/m2.hr mg/m2.hr mg/m2.hr mg/l *** + RCHRES BRTAM(1) BRTAM(2) BRPO4(1) BRPO4(2) ANAER *** + # - # mg/m2.hr mg/m2.hr mg/m2.hr mg/m2.hr mg/l *** 1 5 11.0 33.0 1.1 2.2 0.0005 - END NUT-BENPARM - + END NUT-BENPARM + NUT-NITDENIT - RCHRES KTAM20 KNO220 TCNIT KNO320 TCDEN DENOXT *** - # - # /hr /hr /hr mg/l *** + RCHRES KTAM20 KNO220 TCNIT KNO320 TCDEN DENOXT *** + # - # /hr /hr /hr mg/l *** 1 5 .002 .004 1.07 .001 1.04 0.2 END NUT-NITDENIT - + NUT-NH3VOLAT - RCHRES EXPNVG EXPNVL *** - # - # *** + RCHRES EXPNVG EXPNVL *** + # - # *** 1 5 .50 0.6667 - END NUT-NH3VOLAT - - NUT-BEDCONC + END NUT-NH3VOLAT + + NUT-BEDCONC RCHRES Bed concentrations of NH4 & PO4 (mg/mg) *** # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** 1 5 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 - END NUT-BEDCONC - - NUT-ADSPARM + END NUT-BEDCONC + + NUT-ADSPARM RCHRES Partition coefficients for NH4 AND PO4 (l/mg) *** # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** 1 5 0.0001 0.0001 0.0001 10. 10. 10. END NUT-ADSPARM - - NUT-DINIT + + NUT-DINIT RCHRES NO3 TAM NO2 PO4 PHVAL *** - # - # mg/l mg/l mg/l mg/l ph units *** + # - # mg/l mg/l mg/l mg/l ph units *** 1 5 40. 10. 1. 50. 7.0 END NUT-DINIT - - NUT-ADSINIT + + NUT-ADSINIT RCHRES Initial suspended NH4 and PO4 concentrations (mg/mg) *** # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** 1 5 0. 0. 0. 0. 0. 0. - END NUT-ADSINIT + END NUT-ADSINIT *** Section PLANK *** @@ -941,11 +941,11 @@ SCHEMATIC # <-factor-> # # *** PERLND 1 6000. RCHRES 1 1 IMPLND 1 3000. RCHRES 5 2 -RCHRES 1 RCHRES 2 3 -RCHRES 1 RCHRES 3 4 -RCHRES 2 RCHRES 4 5 -RCHRES 3 RCHRES 4 5 -RCHRES 4 RCHRES 5 5 +RCHRES 1 RCHRES 2 3 +RCHRES 1 RCHRES 3 4 +RCHRES 2 RCHRES 4 5 +RCHRES 3 RCHRES 4 5 +RCHRES 4 RCHRES 5 5 END SCHEMATIC MASS-LINK diff --git a/tests/test10specl/HSPFresults/test10specl.uci b/tests/test10specl/HSPFresults/test10specl.uci index 20e6eaf0..ce4f9621 100644 --- a/tests/test10specl/HSPFresults/test10specl.uci +++ b/tests/test10specl/HSPFresults/test10specl.uci @@ -9,7 +9,7 @@ END GLOBAL *** This test run uses MASS-LINK and SCHEMATIC blocks *** -FILES +FILES ***<----FILE NAME-------------------------------------------------> WDM 21 test10specl.wdm MESSU 22 test10specl.ech @@ -309,7 +309,7 @@ RCHRES ACTIVITY RCHRES Active Sections (1=Active, 0=Inactive) *** # - # HYFG ADFG CNFG HTFG SDFG GQFG OXFG NUFG PKFG PHFG *** - 1 5 1 1 1 1 1 1 1 1 1 1 + 1 5 1 1 1 1 1 1 1 1 1 1 END ACTIVITY PRINT-INFO @@ -618,8 +618,8 @@ RCHRES OX-BENPARM RCHRES BENOD TCBEN EXPOD BRBOD(1) BRBOD(2) EXPREL *** - # - # mg/m2.hr mg/m2.hr mg/m2.hr *** - 1 5 10. 1.1 1.2 20. 25. 1.3 + # - # mg/m2.hr mg/m2.hr mg/m2.hr *** + 1 5 10. 1.1 1.2 20. 25. 1.3 END OX-BENPARM OX-CFOREA @@ -649,46 +649,46 @@ RCHRES END NUT-FLAGS NUT-BENPARM - RCHRES BRTAM(1) BRTAM(2) BRPO4(1) BRPO4(2) ANAER *** - # - # mg/m2.hr mg/m2.hr mg/m2.hr mg/m2.hr mg/l *** + RCHRES BRTAM(1) BRTAM(2) BRPO4(1) BRPO4(2) ANAER *** + # - # mg/m2.hr mg/m2.hr mg/m2.hr mg/m2.hr mg/l *** 1 5 11.0 33.0 1.1 2.2 0.0005 - END NUT-BENPARM - + END NUT-BENPARM + NUT-NITDENIT - RCHRES KTAM20 KNO220 TCNIT KNO320 TCDEN DENOXT *** - # - # /hr /hr /hr mg/l *** + RCHRES KTAM20 KNO220 TCNIT KNO320 TCDEN DENOXT *** + # - # /hr /hr /hr mg/l *** 1 5 .002 .004 1.07 .001 1.04 0.2 END NUT-NITDENIT - + NUT-NH3VOLAT - RCHRES EXPNVG EXPNVL *** - # - # *** + RCHRES EXPNVG EXPNVL *** + # - # *** 1 5 .50 0.6667 - END NUT-NH3VOLAT - - NUT-BEDCONC + END NUT-NH3VOLAT + + NUT-BEDCONC RCHRES Bed concentrations of NH4 & PO4 (mg/mg) *** # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** 1 5 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 - END NUT-BEDCONC - - NUT-ADSPARM + END NUT-BEDCONC + + NUT-ADSPARM RCHRES Partition coefficients for NH4 AND PO4 (l/mg) *** # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** 1 5 0.0001 0.0001 0.0001 10. 10. 10. END NUT-ADSPARM - - NUT-DINIT + + NUT-DINIT RCHRES NO3 TAM NO2 PO4 PHVAL *** - # - # mg/l mg/l mg/l mg/l ph units *** + # - # mg/l mg/l mg/l mg/l ph units *** 1 5 40. 10. 1. 50. 7.0 END NUT-DINIT - - NUT-ADSINIT + + NUT-ADSINIT RCHRES Initial suspended NH4 and PO4 concentrations (mg/mg) *** # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay *** 1 5 0. 0. 0. 0. 0. 0. - END NUT-ADSINIT + END NUT-ADSINIT *** Section PLANK *** @@ -941,11 +941,11 @@ SCHEMATIC # <-factor-> # # *** PERLND 1 6000. RCHRES 1 1 IMPLND 1 3000. RCHRES 5 2 -RCHRES 1 RCHRES 2 3 -RCHRES 1 RCHRES 3 4 -RCHRES 2 RCHRES 4 5 -RCHRES 3 RCHRES 4 5 -RCHRES 4 RCHRES 5 5 +RCHRES 1 RCHRES 2 3 +RCHRES 1 RCHRES 3 4 +RCHRES 2 RCHRES 4 5 +RCHRES 3 RCHRES 4 5 +RCHRES 4 RCHRES 5 5 END SCHEMATIC MASS-LINK diff --git a/tests/test_regression.py b/tests/test_regression.py index 02c0d02b..8123276d 100644 --- a/tests/test_regression.py +++ b/tests/test_regression.py @@ -3,9 +3,9 @@ import pytest from hsp2.hsp2tools.commands import import_uci, run -from hsp2.hsp2tools.HDF5 import HDF5 from .convert.regression_base import RegressTest as RegressTestBase +from .utils.HDF5 import HDF5 class RegressTest(RegressTestBase): diff --git a/tests/testcbp/HSP2results/PL3_5250_0001.json.constant_wd b/tests/testcbp/HSP2results/PL3_5250_0001.json.constant_wd index 8a6d387e..3a4a0439 100644 --- a/tests/testcbp/HSP2results/PL3_5250_0001.json.constant_wd +++ b/tests/testcbp/HSP2results/PL3_5250_0001.json.constant_wd @@ -17,4 +17,3 @@ } } } - diff --git a/tests/testcbp/HSP2results/PL3_5250_0001.uci b/tests/testcbp/HSP2results/PL3_5250_0001.uci index 6c04b569..0f9de5ad 100644 --- a/tests/testcbp/HSP2results/PL3_5250_0001.uci +++ b/tests/testcbp/HSP2results/PL3_5250_0001.uci @@ -1,5 +1,5 @@ RUN - + GLOBAL PL3_5250_0 riv | P5 | hsp2_2022 | Occoquan START 2001/01/01 END 2001/12/31 @@ -54,7 +54,7 @@ RCHRES HYDR-PARM2 RCHRES *** # - # FTABNO LEN DELTH STCOR KS DB50 *** - 1 1. 10. 2. 0.5 + 1 1. 10. 2. 0.5 END HYDR-PARM2 HYDR-INIT @@ -68,7 +68,7 @@ RCHRES ADCALC-DATA RCHRES Data for section ADCALC *** # - # CRRAT VOL *** - 1 1.5 12175. + 1 1.5 12175. END ADCALC-DATA END RCHRES diff --git a/tests/testcbp/HSP2results/PL3_5250_0001eq.uci b/tests/testcbp/HSP2results/PL3_5250_0001eq.uci new file mode 100644 index 00000000..2dd128e8 --- /dev/null +++ b/tests/testcbp/HSP2results/PL3_5250_0001eq.uci @@ -0,0 +1,228 @@ +RUN +*** This UCI will load a companion file with JSON in it + +GLOBAL + PL3_5250_0 riv | P5 | hsp2_2022 | Occoquan + START 2001/01/01 END 2001/12/31 + RUN INTERP OUTPUT LEVEL 1 1 + RESUME 0 RUN 1 UNIT SYSTEM 1 +END GLOBAL + +FILES + ***<----FILE NAME-------------------------------------------------> +WDM1 21 met_A51059.wdm +WDM2 22 prad_A51059.wdm +WDM3 23 ps_sep_div_ams_hsp2_2022_PL3_5250_0001.wdm +WDM4 24 PL3_5250_0001.wdm +MESSU 25 PL3_5250_0001.ech + 26 PL3_5250_0001.out + 31 PL3_5250_0001.tau +END FILES + +OPN SEQUENCE + INGRP INDELT 01:00 + RCHRES 1 + PLTGEN 1 + END INGRP +END OPN SEQUENCE + +RCHRES + ACTIVITY + # - # HYFG ADFG CNFG HTFG SDFG GQFG OXFG NUFG PKFG PHFG *** + 1 1 1 0 0 0 0 0 0 0 0 + END ACTIVITY + + PRINT-INFO + # - # HYFG ADFG CNFG HTFG SDFG GQFG OXFG NUFG PKFG PHFG PIVL***PY + 1 5 5 0 0 0 0 0 0 0 0 0 12 + END PRINT-INFO + + GEN-INFO + RCHRES<-------Name------->Nexit Unit Systems Printer *** + # - # User t-series Engl Metr LKFG *** + 1 PL3_5250_0001 3 1 1 1 26 0 1 + END GEN-INFO + + HYDR-PARM1 + RCHRES Flags for HYDR section *** + # - # VC A1 A2 A3 ODFVFG for each ODGTFG for each *** FUNCT for each + FG FG FG FG possible exit possible exit *** possible exit + 1 2 3 4 5 1 2 3 4 5 *** 1 2 3 4 5 + VC A1 A2 A3 V1 V2 V3 V4 V5 G1 G2 G3 G4 G5 *** F1 F2 F3 F4 F5 + 1 0 1 1 1 0 0 4 0 0 1 2 0 0 0 0 0 0 0 0 + END HYDR-PARM1 + + HYDR-PARM2 + RCHRES *** + # - # FTABNO LEN DELTH STCOR KS DB50 *** + 1 1. 10. 2. 0.5 + END HYDR-PARM2 + + HYDR-INIT + RCHRES Initial conditions for HYDR section *** + # - # VOL Initial value of COLIND *** Initial value of OUTDGT + (ac-ft) for each possible exit *** for each possible exit + VOL CEX1 CEX2 CEX3 CEX4 CEX5 *** DEX1 DEX2 DEX3 DEX4 DEX5 + 1 12175.000 + END HYDR-INIT + + ADCALC-DATA + RCHRES Data for section ADCALC *** + # - # CRRAT VOL *** + 1 1.5 12175. + END ADCALC-DATA + +END RCHRES + +FTABLES + FTABLE 1 + ROWS COLS *** + 20 4 + DEPTH AREA VOLUME DISCH *** + (FT) (ACRES) (AC-FT) (CFS) *** + 0 0 0 0 + 20 124 1007 0 + 30 240 2781 0 + 40 444 6106 0 + 50 804 12175 0 + 52 909 13886 39 + 54 1024 15819 78 + 56 1155 17999 117 + 57 1226 19227 136 + 58 1296 20456 137 + 60 1413 23180 138 + 62 1524 26140 140 + 63 1586 27745 1922 + 64 1647 29351 5179 + 65 1701 31247 9398 + 66 1755 33143 14393 + 67 1803 34984 20645 + 69 1879 38705 36532 + 70 1908 40585 44603 + 76 2100 54000 103071 + END FTABLE 1 +END FTABLES + +EXT SOURCES +<-Volume-> SsysSgap<--Mult-->Tran <-Target vols> <-Grp> <-Member->*** + # # tem strg<-factor->strg # # # #*** +*** METEOROLOGY +WDM1 1000 EVAP ENGLZERO 1.000 SAME RCHRES 1 EXTNL POTEV +WDM1 1001 DEWP ENGLZERO SAME RCHRES 1 EXTNL DEWTMP +WDM1 1002 WNDH ENGLZERO SAME RCHRES 1 EXTNL WIND +WDM1 1003 RADH ENGLZERO SAME RCHRES 1 EXTNL SOLRAD +WDM1 1004 ATMP ENGLZERO SAME RCHRES 1 EXTNL GATMP +WDM1 1005 CLDC ENGLZERO SAME RCHRES 1 EXTNL CLOUD + +*** PRECIPITATION AND ATMOSPHERIC DEPOSITION LOADS +WDM2 2000 HPRC ENGLZERO SAME RCHRES 1 EXTNL PREC +WDM2 2001 NO23 ENGLZERO DIV RCHRES 1 EXTNL NUADFX 1 1 +WDM2 2002 NH4A ENGLZERO DIV RCHRES 1 EXTNL NUADFX 2 1 +WDM2 2003 NO3D ENGLZERO DIV RCHRES 1 EXTNL NUADFX 1 1 +WDM2 2004 NH4D ENGLZERO DIV RCHRES 1 EXTNL NUADFX 2 1 +WDM2 2005 ORGN ENGLZERO DIV RCHRES 1 EXTNL PLADFX 1 1 +WDM2 2006 PO4A ENGLZERO DIV RCHRES 1 EXTNL NUADFX 3 1 +WDM2 2007 ORGP ENGLZERO DIV RCHRES 1 EXTNL PLADFX 2 1 + +*** POINT SOURCE +WDM3 3000 FLOW ENGLZERO DIV RCHRES 1 INFLOW IVOL +WDM3 3001 HEAT ENGLZERO DIV RCHRES 1 INFLOW IHEAT +WDM3 3002 NH3X ENGLZERO DIV RCHRES 1 INFLOW NUIF1 2 +WDM3 3003 NO3X ENGLZERO DIV RCHRES 1 INFLOW NUIF1 1 +WDM3 3004 ORNX ENGLZERO DIV RCHRES 1 INFLOW PKIF 3 +WDM3 3005 PO4X ENGLZERO DIV RCHRES 1 INFLOW NUIF1 4 +WDM3 3006 ORPX ENGLZERO DIV RCHRES 1 INFLOW PKIF 4 +WDM3 3021 BODX ENGLZERO DIV RCHRES 1 INFLOW OXIF 2 +WDM3 3022 TSSX ENGLZERO 0.0005 DIV RCHRES 1 INFLOW ISED 3 +WDM3 3023 DOXX ENGLZERO DIV RCHRES 1 INFLOW OXIF 1 +WDM3 3024 TOCX ENGLZERO DIV RCHRES 1 INFLOW PKIF 5 + +*** DIVERSIONS +WDM3 3007 DIVR ENGLZERO SAME RCHRES 1 EXTNL OUTDGT 1 +WDM3 3008 DIVA ENGLZERO SAME RCHRES 1 EXTNL OUTDGT 2 + +*** SEPTIC +WDM3 3010 SNO3 ENGLZERO 1.0000 DIV RCHRES 1 INFLOW NUIF1 1 + +*** AEOLIAN SEDIMENT +WDM3 3061 SFAS ENGLZERO 7.027e-06DIV RCHRES 1 INFLOW ISED 2 +WDM3 3062 SFAC ENGLZERO 7.027e-06DIV RCHRES 1 INFLOW ISED 3 + +*** UPSTREAM and EOS INPUT *** +WDM4 11 WATR ENGLZERO SAME RCHRES 1 INFLOW IVOL +WDM4 12 HEAT ENGLZERO SAME RCHRES 1 INFLOW IHEAT +WDM4 13 DOXY ENGLZERO SAME RCHRES 1 INFLOW OXIF 1 +WDM4 21 SAND ENGLZERO SAME RCHRES 1 INFLOW ISED 1 +WDM4 22 SILT ENGLZERO SAME RCHRES 1 INFLOW ISED 2 +WDM4 23 CLAY ENGLZERO SAME RCHRES 1 INFLOW ISED 3 +WDM4 31 NO3D ENGLZERO SAME RCHRES 1 INFLOW NUIF1 1 +WDM4 32 NH3D ENGLZERO SAME RCHRES 1 INFLOW NUIF1 2 +WDM4 33 NH3A ENGLZERO SAME RCHRES 1 INFLOW NUIF2 1 1 +WDM4 34 NH3I ENGLZERO SAME RCHRES 1 INFLOW NUIF2 2 1 +WDM4 35 NH3C ENGLZERO SAME RCHRES 1 INFLOW NUIF2 3 1 +WDM4 36 RORN ENGLZERO SAME RCHRES 1 INFLOW PKIF 3 +WDM4 41 PO4D ENGLZERO SAME RCHRES 1 INFLOW NUIF1 4 +WDM4 42 PO4A ENGLZERO SAME RCHRES 1 INFLOW NUIF2 1 2 +WDM4 43 PO4I ENGLZERO SAME RCHRES 1 INFLOW NUIF2 2 2 +WDM4 44 PO4C ENGLZERO SAME RCHRES 1 INFLOW NUIF2 3 2 +WDM4 45 RORP ENGLZERO SAME RCHRES 1 INFLOW PKIF 4 +WDM4 51 BODA ENGLZERO SAME RCHRES 1 INFLOW OXIF 2 +WDM4 52 TORC ENGLZERO SAME RCHRES 1 INFLOW PKIF 5 +WDM4 53 PHYT ENGLZERO SAME RCHRES 1 INFLOW PKIF 1 +END EXT SOURCES + +EXT TARGETS +<-Volume-> <-Grp> <-Member-><--Mult-->Tran <-Volume-> Tsys Tgap Amd *** + # # #<-factor->strg # # tem strg strg*** +RCHRES 1 OFLOW OVOL 3 SAME WDM4 111 WATR ENGL REPL +RCHRES 1 OFLOW OHEAT 3 SAME WDM4 112 HEAT ENGL REPL +RCHRES 1 OFLOW OXCF2 3 1 SAME WDM4 113 DOXY ENGL REPL +RCHRES 1 OFLOW OSED 3 1 SAME WDM4 121 SAND ENGL REPL +RCHRES 1 OFLOW OSED 3 2 SAME WDM4 122 SILT ENGL REPL +RCHRES 1 OFLOW OSED 3 3 SAME WDM4 123 CLAY ENGL REPL +RCHRES 1 OFLOW NUCF9 3 1 SAME WDM4 131 NO3D ENGL REPL +RCHRES 1 OFLOW NUCF9 3 2 SAME WDM4 132 NH3D ENGL REPL +RCHRES 1 OFLOW OSNH4 3 1 SAME WDM4 133 NH3A ENGL REPL +RCHRES 1 OFLOW OSNH4 3 2 SAME WDM4 134 NH3I ENGL REPL +RCHRES 1 OFLOW OSNH4 3 3 SAME WDM4 135 NH3C ENGL REPL +RCHRES 1 OFLOW PKCF2 3 3 SAME WDM4 136 RORN ENGL REPL +RCHRES 1 OFLOW NUCF9 3 4 SAME WDM4 141 PO4D ENGL REPL +RCHRES 1 OFLOW OSPO4 3 1 SAME WDM4 142 PO4A ENGL REPL +RCHRES 1 OFLOW OSPO4 3 2 SAME WDM4 143 PO4I ENGL REPL +RCHRES 1 OFLOW OSPO4 3 3 SAME WDM4 144 PO4C ENGL REPL +RCHRES 1 OFLOW PKCF2 3 4 SAME WDM4 145 RORP ENGL REPL +RCHRES 1 OFLOW OXCF2 3 2 SAME WDM4 151 BODA ENGL REPL +RCHRES 1 OFLOW PKCF2 3 5 SAME WDM4 152 TORC ENGL REPL +RCHRES 1 OFLOW PKCF2 3 1 SAME WDM4 153 PHYT ENGL REPL +END EXT TARGETS + +NETWORK +<-Volume-> <-Grp> <-Member-><--Mult-->Tran <-Target vols> <-Grp> <-Member-> *** + # # #<-factor->strg # # # # *** +RCHRES 1 HYDR TAU AVER PLTGEN 1 INPUT MEAN 1 +END NETWORK + +PLTGEN + PLOTINFO + # - # FILE NPT NMN LABL PYR PIVL *** + 1 31 1 12 24 + END PLOTINFO + + GEN-LABELS + # - #<----------------Title-----------------> *** + 1 PL3_5250_0001 daily_shear_stress_lbsft2 + END GEN-LABELS + + SCALING + #thru# YMIN YMAX IVLIN THRESH *** + 1 99 0. 100000. 20. + END SCALING + + CURV-DATA + <-Curve label--> Line Intg Col Tran *** + # - # type eqv code code *** + 1 daily_shear_stre 1 1 AVER + END CURV-DATA +END PLTGEN + +END RUN diff --git a/tests/testcbp/HSP2results/PL3_5250_0001eqlong.uci b/tests/testcbp/HSP2results/PL3_5250_0001eqlong.uci new file mode 100644 index 00000000..5cc08fab --- /dev/null +++ b/tests/testcbp/HSP2results/PL3_5250_0001eqlong.uci @@ -0,0 +1,228 @@ +RUN +*** This UCI will load a companion file with JSON in it + +GLOBAL + PL3_5250_0 riv | P5 | hsp2_2022 | Occoquan + START 1984/01/01 END 2019/12/31 + RUN INTERP OUTPUT LEVEL 1 1 + RESUME 0 RUN 1 UNIT SYSTEM 1 +END GLOBAL + +FILES + ***<----FILE NAME-------------------------------------------------> +WDM1 21 met_A51059.wdm +WDM2 22 prad_A51059.wdm +WDM3 23 ps_sep_div_ams_hsp2_2022_PL3_5250_0001.wdm +WDM4 24 PL3_5250_0001.wdm +MESSU 25 PL3_5250_0001.ech + 26 PL3_5250_0001.out + 31 PL3_5250_0001.tau +END FILES + +OPN SEQUENCE + INGRP INDELT 01:00 + RCHRES 1 + PLTGEN 1 + END INGRP +END OPN SEQUENCE + +RCHRES + ACTIVITY + # - # HYFG ADFG CNFG HTFG SDFG GQFG OXFG NUFG PKFG PHFG *** + 1 1 1 0 0 0 0 0 0 0 0 + END ACTIVITY + + PRINT-INFO + # - # HYFG ADFG CNFG HTFG SDFG GQFG OXFG NUFG PKFG PHFG PIVL***PY + 1 5 5 0 0 0 0 0 0 0 0 0 12 + END PRINT-INFO + + GEN-INFO + RCHRES<-------Name------->Nexit Unit Systems Printer *** + # - # User t-series Engl Metr LKFG *** + 1 PL3_5250_0001 3 1 1 1 26 0 1 + END GEN-INFO + + HYDR-PARM1 + RCHRES Flags for HYDR section *** + # - # VC A1 A2 A3 ODFVFG for each ODGTFG for each *** FUNCT for each + FG FG FG FG possible exit possible exit *** possible exit + 1 2 3 4 5 1 2 3 4 5 *** 1 2 3 4 5 + VC A1 A2 A3 V1 V2 V3 V4 V5 G1 G2 G3 G4 G5 *** F1 F2 F3 F4 F5 + 1 0 1 1 1 0 0 4 0 0 1 2 0 0 0 0 0 0 0 0 + END HYDR-PARM1 + + HYDR-PARM2 + RCHRES *** + # - # FTABNO LEN DELTH STCOR KS DB50 *** + 1 1. 10. 2. 0.5 + END HYDR-PARM2 + + HYDR-INIT + RCHRES Initial conditions for HYDR section *** + # - # VOL Initial value of COLIND *** Initial value of OUTDGT + (ac-ft) for each possible exit *** for each possible exit + VOL CEX1 CEX2 CEX3 CEX4 CEX5 *** DEX1 DEX2 DEX3 DEX4 DEX5 + 1 12175.000 + END HYDR-INIT + + ADCALC-DATA + RCHRES Data for section ADCALC *** + # - # CRRAT VOL *** + 1 1.5 12175. + END ADCALC-DATA + +END RCHRES + +FTABLES + FTABLE 1 + ROWS COLS *** + 20 4 + DEPTH AREA VOLUME DISCH *** + (FT) (ACRES) (AC-FT) (CFS) *** + 0 0 0 0 + 20 124 1007 0 + 30 240 2781 0 + 40 444 6106 0 + 50 804 12175 0 + 52 909 13886 39 + 54 1024 15819 78 + 56 1155 17999 117 + 57 1226 19227 136 + 58 1296 20456 137 + 60 1413 23180 138 + 62 1524 26140 140 + 63 1586 27745 1922 + 64 1647 29351 5179 + 65 1701 31247 9398 + 66 1755 33143 14393 + 67 1803 34984 20645 + 69 1879 38705 36532 + 70 1908 40585 44603 + 76 2100 54000 103071 + END FTABLE 1 +END FTABLES + +EXT SOURCES +<-Volume-> SsysSgap<--Mult-->Tran <-Target vols> <-Grp> <-Member->*** + # # tem strg<-factor->strg # # # #*** +*** METEOROLOGY +WDM1 1000 EVAP ENGLZERO 1.000 SAME RCHRES 1 EXTNL POTEV +WDM1 1001 DEWP ENGLZERO SAME RCHRES 1 EXTNL DEWTMP +WDM1 1002 WNDH ENGLZERO SAME RCHRES 1 EXTNL WIND +WDM1 1003 RADH ENGLZERO SAME RCHRES 1 EXTNL SOLRAD +WDM1 1004 ATMP ENGLZERO SAME RCHRES 1 EXTNL GATMP +WDM1 1005 CLDC ENGLZERO SAME RCHRES 1 EXTNL CLOUD + +*** PRECIPITATION AND ATMOSPHERIC DEPOSITION LOADS +WDM2 2000 HPRC ENGLZERO SAME RCHRES 1 EXTNL PREC +WDM2 2001 NO23 ENGLZERO DIV RCHRES 1 EXTNL NUADFX 1 1 +WDM2 2002 NH4A ENGLZERO DIV RCHRES 1 EXTNL NUADFX 2 1 +WDM2 2003 NO3D ENGLZERO DIV RCHRES 1 EXTNL NUADFX 1 1 +WDM2 2004 NH4D ENGLZERO DIV RCHRES 1 EXTNL NUADFX 2 1 +WDM2 2005 ORGN ENGLZERO DIV RCHRES 1 EXTNL PLADFX 1 1 +WDM2 2006 PO4A ENGLZERO DIV RCHRES 1 EXTNL NUADFX 3 1 +WDM2 2007 ORGP ENGLZERO DIV RCHRES 1 EXTNL PLADFX 2 1 + +*** POINT SOURCE +WDM3 3000 FLOW ENGLZERO DIV RCHRES 1 INFLOW IVOL +WDM3 3001 HEAT ENGLZERO DIV RCHRES 1 INFLOW IHEAT +WDM3 3002 NH3X ENGLZERO DIV RCHRES 1 INFLOW NUIF1 2 +WDM3 3003 NO3X ENGLZERO DIV RCHRES 1 INFLOW NUIF1 1 +WDM3 3004 ORNX ENGLZERO DIV RCHRES 1 INFLOW PKIF 3 +WDM3 3005 PO4X ENGLZERO DIV RCHRES 1 INFLOW NUIF1 4 +WDM3 3006 ORPX ENGLZERO DIV RCHRES 1 INFLOW PKIF 4 +WDM3 3021 BODX ENGLZERO DIV RCHRES 1 INFLOW OXIF 2 +WDM3 3022 TSSX ENGLZERO 0.0005 DIV RCHRES 1 INFLOW ISED 3 +WDM3 3023 DOXX ENGLZERO DIV RCHRES 1 INFLOW OXIF 1 +WDM3 3024 TOCX ENGLZERO DIV RCHRES 1 INFLOW PKIF 5 + +*** DIVERSIONS +WDM3 3007 DIVR ENGLZERO SAME RCHRES 1 EXTNL OUTDGT 1 +WDM3 3008 DIVA ENGLZERO SAME RCHRES 1 EXTNL OUTDGT 2 + +*** SEPTIC +WDM3 3010 SNO3 ENGLZERO 1.0000 DIV RCHRES 1 INFLOW NUIF1 1 + +*** AEOLIAN SEDIMENT +WDM3 3061 SFAS ENGLZERO 7.027e-06DIV RCHRES 1 INFLOW ISED 2 +WDM3 3062 SFAC ENGLZERO 7.027e-06DIV RCHRES 1 INFLOW ISED 3 + +*** UPSTREAM and EOS INPUT *** +WDM4 11 WATR ENGLZERO SAME RCHRES 1 INFLOW IVOL +WDM4 12 HEAT ENGLZERO SAME RCHRES 1 INFLOW IHEAT +WDM4 13 DOXY ENGLZERO SAME RCHRES 1 INFLOW OXIF 1 +WDM4 21 SAND ENGLZERO SAME RCHRES 1 INFLOW ISED 1 +WDM4 22 SILT ENGLZERO SAME RCHRES 1 INFLOW ISED 2 +WDM4 23 CLAY ENGLZERO SAME RCHRES 1 INFLOW ISED 3 +WDM4 31 NO3D ENGLZERO SAME RCHRES 1 INFLOW NUIF1 1 +WDM4 32 NH3D ENGLZERO SAME RCHRES 1 INFLOW NUIF1 2 +WDM4 33 NH3A ENGLZERO SAME RCHRES 1 INFLOW NUIF2 1 1 +WDM4 34 NH3I ENGLZERO SAME RCHRES 1 INFLOW NUIF2 2 1 +WDM4 35 NH3C ENGLZERO SAME RCHRES 1 INFLOW NUIF2 3 1 +WDM4 36 RORN ENGLZERO SAME RCHRES 1 INFLOW PKIF 3 +WDM4 41 PO4D ENGLZERO SAME RCHRES 1 INFLOW NUIF1 4 +WDM4 42 PO4A ENGLZERO SAME RCHRES 1 INFLOW NUIF2 1 2 +WDM4 43 PO4I ENGLZERO SAME RCHRES 1 INFLOW NUIF2 2 2 +WDM4 44 PO4C ENGLZERO SAME RCHRES 1 INFLOW NUIF2 3 2 +WDM4 45 RORP ENGLZERO SAME RCHRES 1 INFLOW PKIF 4 +WDM4 51 BODA ENGLZERO SAME RCHRES 1 INFLOW OXIF 2 +WDM4 52 TORC ENGLZERO SAME RCHRES 1 INFLOW PKIF 5 +WDM4 53 PHYT ENGLZERO SAME RCHRES 1 INFLOW PKIF 1 +END EXT SOURCES + +EXT TARGETS +<-Volume-> <-Grp> <-Member-><--Mult-->Tran <-Volume-> Tsys Tgap Amd *** + # # #<-factor->strg # # tem strg strg*** +RCHRES 1 OFLOW OVOL 3 SAME WDM4 111 WATR ENGL REPL +RCHRES 1 OFLOW OHEAT 3 SAME WDM4 112 HEAT ENGL REPL +RCHRES 1 OFLOW OXCF2 3 1 SAME WDM4 113 DOXY ENGL REPL +RCHRES 1 OFLOW OSED 3 1 SAME WDM4 121 SAND ENGL REPL +RCHRES 1 OFLOW OSED 3 2 SAME WDM4 122 SILT ENGL REPL +RCHRES 1 OFLOW OSED 3 3 SAME WDM4 123 CLAY ENGL REPL +RCHRES 1 OFLOW NUCF9 3 1 SAME WDM4 131 NO3D ENGL REPL +RCHRES 1 OFLOW NUCF9 3 2 SAME WDM4 132 NH3D ENGL REPL +RCHRES 1 OFLOW OSNH4 3 1 SAME WDM4 133 NH3A ENGL REPL +RCHRES 1 OFLOW OSNH4 3 2 SAME WDM4 134 NH3I ENGL REPL +RCHRES 1 OFLOW OSNH4 3 3 SAME WDM4 135 NH3C ENGL REPL +RCHRES 1 OFLOW PKCF2 3 3 SAME WDM4 136 RORN ENGL REPL +RCHRES 1 OFLOW NUCF9 3 4 SAME WDM4 141 PO4D ENGL REPL +RCHRES 1 OFLOW OSPO4 3 1 SAME WDM4 142 PO4A ENGL REPL +RCHRES 1 OFLOW OSPO4 3 2 SAME WDM4 143 PO4I ENGL REPL +RCHRES 1 OFLOW OSPO4 3 3 SAME WDM4 144 PO4C ENGL REPL +RCHRES 1 OFLOW PKCF2 3 4 SAME WDM4 145 RORP ENGL REPL +RCHRES 1 OFLOW OXCF2 3 2 SAME WDM4 151 BODA ENGL REPL +RCHRES 1 OFLOW PKCF2 3 5 SAME WDM4 152 TORC ENGL REPL +RCHRES 1 OFLOW PKCF2 3 1 SAME WDM4 153 PHYT ENGL REPL +END EXT TARGETS + +NETWORK +<-Volume-> <-Grp> <-Member-><--Mult-->Tran <-Target vols> <-Grp> <-Member-> *** + # # #<-factor->strg # # # # *** +RCHRES 1 HYDR TAU AVER PLTGEN 1 INPUT MEAN 1 +END NETWORK + +PLTGEN + PLOTINFO + # - # FILE NPT NMN LABL PYR PIVL *** + 1 31 1 12 24 + END PLOTINFO + + GEN-LABELS + # - #<----------------Title-----------------> *** + 1 PL3_5250_0001 daily_shear_stress_lbsft2 + END GEN-LABELS + + SCALING + #thru# YMIN YMAX IVLIN THRESH *** + 1 99 0. 100000. 20. + END SCALING + + CURV-DATA + <-Curve label--> Line Intg Col Tran *** + # - # type eqv code code *** + 1 daily_shear_stre 1 1 AVER + END CURV-DATA +END PLTGEN + +END RUN diff --git a/tests/testcbp/HSP2results/check_endpoint_ts.py b/tests/testcbp/HSP2results/check_endpoint_ts.py index 97ee7af5..f42e1d19 100644 --- a/tests/testcbp/HSP2results/check_endpoint_ts.py +++ b/tests/testcbp/HSP2results/check_endpoint_ts.py @@ -1,13 +1,15 @@ # Must be run from the HSPsquared source directory, the h5 file has already been setup with hsp import_uci test10.uci # bare bones tester - must be run from the HSPsquared source directory import os + +import numpy +from hsp2 import hsp2iO from hsp2.hsp2.main import * from hsp2.hsp2.om import * -from hsp2 import hsp2iO -import numpy from hsp2.hsp2io.hdf import HDF5 from hsp2.hsp2io.io import IOManager -fpath = './tests/test10/HSP2results/test10.h5' + +fpath = "./tests/test10/HSP2results/test10.h5" # try also: # fpath = './tests/testcbp/HSP2results/PL3_5250_0001.h5' # sometimes when testing you may need to close the file, so try: @@ -24,7 +26,7 @@ # now load state and the special actions state = init_state_dicts() state_initialize_om(state) -state['specactions'] = uci_obj.specactions # stash the specaction dict in state +state["specactions"] = uci_obj.specactions # stash the specaction dict in state state_siminfo_hsp2(uci_obj, siminfo) # Add support for dynamic functions to operate on STATE @@ -33,14 +35,24 @@ # Iterate through all segments and add crucial paths to state # before loading dynamic components that may reference them state_init_hsp2(state, opseq, activities) -state_load_dynamics_specl(state, io_manager, siminfo) # traditional special actions -state_load_dynamics_om(state, io_manager, siminfo) # operational model for custom python -state_om_model_run_prep(state, io_manager, siminfo) # this creates all objects from the UCI and previous loads +state_load_dynamics_specl(state, io_manager, siminfo) # traditional special actions +state_load_dynamics_om( + state, io_manager, siminfo +) # operational model for custom python +state_om_model_run_prep( + state, io_manager, siminfo +) # this creates all objects from the UCI and previous loads # state['model_root_object'].find_var_path('RCHRES_R001') # Get the timeseries naked, without an object -rchres1 = state['model_object_cache']['/STATE/RCHRES_R001'] -precip_ts = ModelLinkage('PRCP', rchres1, {'right_path':'/TIMESERIES/TS039', 'SVOLNO':'TS039', 'link_type':3}) -ts1 = precip_ts.read_ts() # same as precip_ts.ts_ix[precip_ts.ix], same as state['ts_ix'][precip_ts.ix] +rchres1 = state["model_object_cache"]["/STATE/RCHRES_R001"] +precip_ts = ModelLinkage( + "PRCP", + rchres1, + {"right_path": "/TIMESERIES/TS039", "SVOLNO": "TS039", "link_type": 3}, +) +ts1 = ( + precip_ts.read_ts() +) # same as precip_ts.ts_ix[precip_ts.ix], same as state['ts_ix'][precip_ts.ix] # NOTE: THIS SEEMS TO FAIL RIGHT NOW DUE TO WRITING THE TS VALUES BACK WITH A NAME OF tsvalue_0, and is now embeded @@ -53,15 +65,17 @@ # precip_ts.io_manager._input._store # write it back. We can give an arbitrary name or it will default to write back to the source path in right_path variable # we can specify a custom path to write this TS to -precip_ts.write_path = '/RESULTS/test_TS039' +precip_ts.write_path = "/RESULTS/test_TS039" precip_ts.write_ts() # precip_ts.write_ts is same as: # ts4 = precip_ts.format_ts(ts1, ['tsvalue'], siminfo['tindex']) # ts4.to_hdf(precip_ts.io_manager._output._store, precip_ts.write_path, format='t', data_columns=True, complevel=precip_ts.complevel) -tsdf = pd.DataFrame(data=ts1, index=siminfo['tindex'],columns=None) +tsdf = pd.DataFrame(data=ts1, index=siminfo["tindex"], columns=None) # verify -ts1 = precip_ts.read_ts() # same as precip_ts.ts_ix[precip_ts.ix], same as state['ts_ix'][precip_ts.ix] +ts1 = ( + precip_ts.read_ts() +) # same as precip_ts.ts_ix[precip_ts.ix], same as state['ts_ix'][precip_ts.ix] # Calls: # - ts = precip_ts.io_manager.read_ts(Category.INPUTS, None, precip_ts.ts_name) # - ts = transform(ts, self.ts_name, 'SAME', self.siminfo) @@ -74,36 +88,66 @@ ts4 = precip_ts.io_manager._output._store[precip_ts.write_path] exdd = defaultdict(list) -exdd[(precip_ts.SVOL, precip_ts.SVOLNO)].append(pd.DataFrame({'SVOL':precip_ts.SVOLNO, 'SVOLNO':precip_ts.SVOLNO, 'MFACTOR':precip_ts.MFACTOR, 'TMEMN':precip_ts.TMEMN, 'TMEMSB':precip_ts.TMEMSB})) -exdd[(precip_ts.SVOL, precip_ts.SVOLNO)].append({'SVOL':precip_ts.SVOLNO, 'SVOLNO':precip_ts.SVOLNO, 'MFACTOR':precip_ts.MFACTOR, 'TMEMN':precip_ts.TMEMN, 'TMEMSB':precip_ts.TMEMSB}) +exdd[(precip_ts.SVOL, precip_ts.SVOLNO)].append( + pd.DataFrame( + { + "SVOL": precip_ts.SVOLNO, + "SVOLNO": precip_ts.SVOLNO, + "MFACTOR": precip_ts.MFACTOR, + "TMEMN": precip_ts.TMEMN, + "TMEMSB": precip_ts.TMEMSB, + } + ) +) +exdd[(precip_ts.SVOL, precip_ts.SVOLNO)].append( + { + "SVOL": precip_ts.SVOLNO, + "SVOLNO": precip_ts.SVOLNO, + "MFACTOR": precip_ts.MFACTOR, + "TMEMN": precip_ts.TMEMN, + "TMEMSB": precip_ts.TMEMSB, + } +) exdd = defaultdict(list) -df = pd.DataFrame({'SVOL':[precip_ts.SVOLNO], 'SVOLNO':[precip_ts.SVOLNO], 'MFACTOR':[precip_ts.MFACTOR], 'TMEMN':[precip_ts.TMEMN], 'TMEMSB':[precip_ts.TMEMSB]}) +df = pd.DataFrame( + { + "SVOL": [precip_ts.SVOLNO], + "SVOLNO": [precip_ts.SVOLNO], + "MFACTOR": [precip_ts.MFACTOR], + "TMEMN": [precip_ts.TMEMN], + "TMEMSB": [precip_ts.TMEMSB], + } +) for row in df.itertuples(): exdd[(precip_ts.SVOL, precip_ts.SVOLNO)].append(row) for row in exdd: - data_frame = precip_ts.io_manager.read_ts(category=Category.INPUTS,segment=row.SVOLNO) + data_frame = precip_ts.io_manager.read_ts( + category=Category.INPUTS, segment=row.SVOLNO + ) xdr = list(df.itertuples()) xdr = precip_ts.ext_sourcesdd for row in xdr: - data_frame = precip_ts.io_manager.read_ts(category=Category.INPUTS,segment=row.SVOLNO) - clean_name(row.TMEMN,row.TMEMSB) + data_frame = precip_ts.io_manager.read_ts( + category=Category.INPUTS, segment=row.SVOLNO + ) + clean_name(row.TMEMN, row.TMEMSB) ext_sourcesdd = XDR ts = Dict.empty(key_type=types.unicode_type, value_type=types.float64[:]) -data_frame = precip_ts.io_manager.read_ts(category=Category.INPUTS,segment=row.SVOLNO) +data_frame = precip_ts.io_manager.read_ts(category=Category.INPUTS, segment=row.SVOLNO) if row.MFACTOR != 1.0: data_frame *= row.MFACTOR t = transform(data_frame, row.TMEMN, row.TRAN, siminfo) -tname = clean_name(row.TMEMN,row.TMEMSB) +tname = clean_name(row.TMEMN, row.TMEMSB) if tname in ts: ts[tname] += t else: - ts[tname] = t + ts[tname] = t # Debug: def read_ts(self, category:Category, operation:Union[str,None]=None, segment:Union[str,None]=None, activity:Union[str,None]=None, ...) @@ -111,6 +155,8 @@ for row in precip_ts.ext_sourcesdd[(precip_ts.SVOL, precip_ts.SVOLNO)]: print(str(row.SVOLNO)) precip_ts.io_manager.read_ts(Category.INPUTS, None, precip_ts.ts_name) -precip_ts.io_manager.read_ts(category=Category.INPUTS,segment=row.SVOLNO) -precip_ts.io_manager.read_ts(category=Category.INPUTS,segment=str(row.SVOLNO)) -precip_ts.io_manager.read_ts(category=Category.INPUTS, operation=None,segment=row.SVOLNO) +precip_ts.io_manager.read_ts(category=Category.INPUTS, segment=row.SVOLNO) +precip_ts.io_manager.read_ts(category=Category.INPUTS, segment=str(row.SVOLNO)) +precip_ts.io_manager.read_ts( + category=Category.INPUTS, operation=None, segment=row.SVOLNO +) diff --git a/tests/testcbp/HSP2results/check_equation.py b/tests/testcbp/HSP2results/check_equation.py index 40bb1f23..3a01be47 100644 --- a/tests/testcbp/HSP2results/check_equation.py +++ b/tests/testcbp/HSP2results/check_equation.py @@ -1,12 +1,13 @@ -# Must be run from the HSPsquared source directory, the h5 file has already been setup with hsp import_uci test10.uci -# bare bones tester - must be run from the HSPsquared source directory -import os +# this is a simple tester that should be kept up to date with the code in main.py +# alternative to step debugger +fpath = "./tests/testcbp/HSP2results/JL1_6562_6560.h5" + from hsp2.hsp2.main import * from hsp2.hsp2.om import * -import numpy from hsp2.hsp2io.hdf import HDF5 from hsp2.hsp2io.io import IOManager -fpath = './tests/testcbp/HSP2results/JL1_6562_6560.h5' +from hsp2.state.state import * + # try also: # fpath = './tests/testcbp/HSP2results/JL1_6562_6560.h5' # sometimes when testing you may need to close the file, so try: @@ -14,48 +15,27 @@ # # f.close() hdf5_instance = HDF5(fpath) io_manager = IOManager(hdf5_instance) -uci_obj = io_manager.read_uci() -siminfo = uci_obj.siminfo -opseq = uci_obj.opseq +parameter_obj = io_manager.read_parameters() +siminfo = parameter_obj.siminfo +opseq = parameter_obj.opseq # Note: now that the UCI is read in and hdf5 loaded, you can see things like: # - hdf5_instance._store.keys() - all the paths in the UCI/hdf5 # - finally stash specactions in state, not domain (segment) dependent so do it once # now load state and the special actions state = init_state_dicts() -state_initialize_om(state) -state['specactions'] = uci_obj.specactions # stash the specaction dict in state - -state_siminfo_hsp2(uci_obj, siminfo) +state_siminfo_hsp2(parameter_obj, siminfo, io_manager, state) # Add support for dynamic functions to operate on STATE # - Load any dynamic components if present, and store variables on objects state_load_dynamics_hsp2(state, io_manager, siminfo) # Iterate through all segments and add crucial paths to state # before loading dynamic components that may reference them state_init_hsp2(state, opseq, activities) -state_load_dynamics_specl(state, io_manager, siminfo) # traditional special actions -state_load_dynamics_om(state, io_manager, siminfo) # operational model for custom python -state_om_model_run_prep(state, io_manager, siminfo) # this creates all objects from the UCI and previous loads -# state['model_root_object'].find_var_path('RCHRES_R001') -# Get the timeseries naked, without an object -Rlocal = state['model_object_cache']['/STATE/RCHRES_R001/Rlocal'] -Rlocal_ts = Rlocal.read_ts() -rchres1 = state['model_object_cache']['/STATE/RCHRES_R001'] -Rlocal_check = ModelLinkage('Rlocal1', rchres1, {'right_path':'/TIMESERIES/TS010', 'link_type':3}) -# Calls: -# - ts = Rlocal.io_manager.read_ts(Category.INPUTS, None, Rlocal.ts_name) -# - ts = transform(ts, Rlocal.ts_name, 'SAME', Rlocal.siminfo) -Rlocal.io_manager._output._store.keys() -# write it back. We can give an arbitrary name or it will default to write back to the source path in right_path variable -ts1 = precip_ts.read_ts() # same as precip_ts.ts_ix[precip_ts.ix], same as state['ts_ix'][precip_ts.ix] -# we can specify a custom path to write this TS to -precip_ts.write_path = '/RESULTS/test_TS039' -precip_ts.write_ts() -# precip_ts.write_ts is same as: -# ts4 = precip_ts.format_ts(ts1, ['tsvalue'], siminfo['tindex']) -# ts4.to_hdf(precip_ts.io_manager._output._store, precip_ts.write_path, format='t', data_columns=True, complevel=precip_ts.complevel) - -start = time.time() -iterate_models(model_exec_list, op_tokens, state_ix, dict_ix, ts_ix, siminfo['steps'], -1) -end = time.time() -print(len(model_exec_list), "components iterated over state_ix", siminfo['steps'], "time steps took" , end - start, "seconds") - +# - finally stash specactions in state, not domain (segment) dependent so do it once +state["specactions"] = specactions # stash the specaction dict in state +om_init_state(state) # set up operational model specific state entries +specl_load_state(state, io_manager, siminfo) # traditional special actions +state_load_dynamics_om( + state, io_manager, siminfo +) # operational model for custom python +# finalize all dynamically loaded components and prepare to run the model +state_om_model_run_prep(state, io_manager, siminfo) diff --git a/tests/testcbp/HSP2results/check_h5.R b/tests/testcbp/HSP2results/check_h5.R index 34eba646..14790c1f 100644 --- a/tests/testcbp/HSP2results/check_h5.R +++ b/tests/testcbp/HSP2results/check_h5.R @@ -1,11 +1,10 @@ -#!/usr/bin/R library("rhdf5") #https://bioc.ism.ac.jp/packages/3.4/bioc/vignettes/rhdf5/inst/doc/rhdf5.pdf # Find and load the h5 file # dir() # specify .h5 file -h5_file_name = "PL3_5250_0001.h5" +h5_file_name = "PL3_5250_0001.h5" # open the file in R h5f = H5Fopen(h5_file_name) @@ -45,4 +44,4 @@ tail(TS_table) # HYDR_table[1:10,] # tail(HYDR_table) # length(HYDR_table[,1]) -# write.csv(HYDR_table, "HYDR_table_vsetOUTDGT.csv") \ No newline at end of file +# write.csv(HYDR_table, "HYDR_table_vsetOUTDGT.csv") diff --git a/tests/utils/HDF5.py b/tests/utils/HDF5.py new file mode 100644 index 00000000..66a60f57 --- /dev/null +++ b/tests/utils/HDF5.py @@ -0,0 +1,116 @@ +import os + +# turns out that HDF5 is not threading safe, need to implement manual locking +from threading import Lock +from typing import Dict, Tuple, Union + +import pandas as pd + +import hsp2 + + +class HDF5: + REQUIRES_MAPPING = ["GQUAL", "CONS", "IQUAL", "PQUAL"] + + def __init__(self, file_name: str) -> None: + self.file_name = file_name + self.aliases = self._read_aliases_csv() + self.data = {} + self.lock = Lock() + + self.gqual_prefixes = self._read_gqual_mapping() + self.cons_prefixes = self._read_cons_mapping() + self.iqual_prefixes = self._read_iqual_mapping() + self.pqual_prefixes = self._read_pqual_mapping() + + def _read_nqual_mapping( + self, key: str, target_col: str, nquals: int = 10 + ) -> Dict[str, str]: + """Some modules, like GQUAL, allow for number which corresponds to the consistent + being modeled. However which number is assoicated with which parameter changes + based on the UCI file. Need to read from specification tables + """ + dict_mappings = {} + for i in range(1, nquals): + try: + with pd.HDFStore(self.file_name, "r") as store: + if key.endswith("IQUAL") or key.endswith("PQUAL"): + df = pd.read_hdf(store, f"{key}{i}" + "/FLAGS") + else: + df = pd.read_hdf(store, f"{key}{i}") + row = df.iloc[0] + gqid = row[target_col] + dict_mappings[gqid] = str(i) + except KeyError: + # Mean no nqual number (e.g. GQUAL3) for this run + pass + return dict_mappings + + def _read_gqual_mapping(self) -> Dict[str, str]: + return self._read_nqual_mapping(R"RCHRES/GQUAL/GQUAL", "GQID", 7) + + def _read_cons_mapping(self) -> Dict[str, str]: + return self._read_nqual_mapping(R"RCHRES/CONS/CONS", "CONID", 7) + + def _read_iqual_mapping(self) -> Dict[str, str]: + return self._read_nqual_mapping(R"IMPLND/IQUAL/IQUAL", "QUALID", 10) + + def _read_pqual_mapping(self) -> Dict[str, str]: + return self._read_nqual_mapping(R"PERLND/PQUAL/PQUAL", "QUALID", 10) + + def _read_aliases_csv(self) -> Dict[Tuple[str, str, str], str]: + datapath = os.path.join(hsp2.__path__[0], "data", "HBNAliases.csv") + df = pd.read_csv(datapath) + df = df.set_index(["operation", "activity", "hspf_name"]) + df_dict = df["hsp2_name"].to_dict() + return df_dict + + def get_time_series( + self, operation: str, id: str, constituent: str, activity: str + ) -> Union[pd.Series, None]: + """Reads timeseries from HDF5 are returns the desired.""" + operation = operation.upper() + constituent = constituent.upper() + activity = activity.upper() + + constituent_prefix = "" + if activity in self.REQUIRES_MAPPING: + constituent_prefix = "" + prefix_dict = getattr(self, f"{activity.lower()}_prefixes") + for key, value in prefix_dict.items(): + if activity == "PQUAL" or activity == "IQUAL": + if constituent.endswith(key): + constituent_prefix = f"{activity}{value}_" + constituent = constituent.replace(key, "") + else: + if constituent.startswith(key): + constituent_prefix = f"{activity}{value}_" + constituent = constituent.replace(key, "") + + key = (operation, id, activity) + try: + self.lock.acquire() + if key not in self.data.keys(): + self.data[key] = self._read_table(operation, id, activity) + self.lock.release() + + df = self.data[key] + if constituent_prefix + constituent in df.columns: + return df[constituent_prefix + constituent] + else: + constituent_alias = self.aliases[(operation, activity, constituent)] + return df[constituent_prefix + constituent_alias] + except KeyError: + return None + + def _read_table(self, operation: str, id: str, activity: str) -> pd.DataFrame: + key = f"RESULTS/{operation}_{operation[0]}{id}/{activity}/table" + + try: + with pd.HDFStore(self.file_name, "r") as store: + df = pd.read_hdf(store, key=key) + df["index"] = pd.to_datetime(df["index"], unit="ns") + df = df.set_index("index") + return df + except KeyError: + return pd.DataFrame() diff --git a/tests/utils/__init__.py b/tests/utils/__init__.py new file mode 100644 index 00000000..e69de29b