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.github/workflows/sphinx_build_deploy.yml
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.github/workflows/sphinx_build_deploy.yml
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@ -3,7 +3,7 @@ name: Publish Sphinx Built Webpages to Github Pages
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on:
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on:
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push:
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push:
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branches:
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branches:
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- master
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- main
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paths:
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paths:
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- 'docs/**'
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- 'docs/**'
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- 'examples/**'
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- 'examples/**'
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@ -2,24 +2,48 @@
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Python AWIPS Data Access Framework
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Python AWIPS Data Access Framework
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==================================
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==================================
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The python-awips package provides a data access framework for requesting meteorological and geometry datasets from an `EDEX <http://unidata.github.io/awips2/#edex>`_ server.
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The python-awips package provides a data access framework for requesting meteorological and geographic datasets from an `EDEX <http://unidata.github.io/awips2/#edex>`_ server.
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`AWIPS <http://unidata.github.io/awips2>`_ is a weather display and analysis package developed by the National Weather Service for operational forecasting. UCAR's `Unidata Program Center <http://www.unidata.ucar.edu/software/awips2/>`_ supports a non-operational open-source release of the AWIPS software (`EDEX <http://unidata.github.io/awips2/#edex>`_, `CAVE <http://unidata.github.io/awips2/#cave>`_, and `python-awips <https://github.com/Unidata/python-awips>`_).
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`AWIPS <http://unidata.github.io/awips2>`_ is a weather display and analysis package developed by the National Weather Service for operational forecasting. UCAR's `Unidata Program Center <http://www.unidata.ucar.edu/software/awips2/>`_ supports a non-operational open-source release of the AWIPS software (`EDEX <http://unidata.github.io/awips2/#edex>`_, `CAVE <http://unidata.github.io/awips2/#cave>`_, and `python-awips <https://github.com/Unidata/python-awips>`_).
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.. _Jupyter Notebook: http://nbviewer.jupyter.org/github/Unidata/python-awips/tree/master/examples/notebooks
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.. _Jupyter Notebook: http://nbviewer.jupyter.org/github/Unidata/python-awips/tree/master/examples/notebooks
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Pre-requisite Software
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----------------------
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In order to effictively use python-awips you'll need to have these installed already:
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- python3
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- conda
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- git *(for the source code and examples installation)*
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Package-Only Install
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--------------------
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If you already work with Python, you might just be interested in how to install the python-awips pacakge.
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The package can be installed with either of the two well known package managers: **pip** and **conda**.
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Pip Install
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Pip Install
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-----------
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~~~~~~~~~~~
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::
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::
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pip install python-awips
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pip install python-awips
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Conda Environment Install
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Conda Install
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-------------------------
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~~~~~~~~~~~~~
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To install the latest version of python-awips, with all required and optional packages:
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::
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conda install -c conda-forge python-awips
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Source Code with Examples Install
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---------------------------------
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Below are instructions on how to install the source code of python-awips, with all included example notebooks. This will create a new conda environment called ``python3-awips`` and start up a browser for the jupyter notebook examples.
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::
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::
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@ -35,111 +59,14 @@ To install the latest version of python-awips, with all required and optional pa
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conda update --all
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conda update --all
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Requirements
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Questions -- Contact Us!
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------------
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------------------------
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These are specified in the environment.yml file that is used to create the 'python3-awips' conda environment:
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Please feel free to reach out to us at our support email at **support-awips@unidata.ucar.edu**
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- python 3
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- numpy
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- nomkl
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- matplotlib
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- cartopy
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- jupyter
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- netcdf4
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- owslib
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- metpy
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- pint
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- h5py
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- nbconvert 4.1+
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- siphon
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- xarray
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- ffmpeg
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- pytest
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- shapely
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- six
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- pip
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Quick Example
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~~~~~~~~~~~~~
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::
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from awips.dataaccess import DataAccessLayer
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DataAccessLayer.changeEDEXHost("edex-cloud.unidata.ucar.edu")
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dataTypes = DataAccessLayer.getSupportedDatatypes()
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list(dataTypes)
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['acars',
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'binlightning',
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'bufrmosavn',
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'bufrmoseta',
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'bufrmosgfs',
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'bufrmoshpc',
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'bufrmoslamp',
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'bufrmosmrf',
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'bufrua',
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'climate',
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'common_obs_spatial',
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'gfe',
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'gfeeditarea',
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'grid',
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'maps',
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'modelsounding',
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'obs',
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'practicewarning',
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'profiler',
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'radar',
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'radar_spatial',
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'satellite',
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'sfcobs',
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'topo',
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'warning']
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request = DataAccessLayer.newDataRequest()
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request.setDatatype("satellite")
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availableSectors = DataAccessLayer.getAvailableLocationNames(request)
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availableSectors.sort()
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for sector in availableSectors:
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print sector
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request.setLocationNames(sector)
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availableProducts = DataAccessLayer.getAvailableParameters(request)
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availableProducts.sort()
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for product in availableProducts:
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print " - " + product
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ECONUS
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- ACTP
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- ADP
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- AOD
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- CAPE
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- CH-01-0.47um
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- CH-02-0.64um
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- CH-03-0.87um
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- CH-04-1.38um
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...
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EFD
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- ACTP
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- ADP
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- AOD
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- CAPE
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- CH-01-0.47um
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- CH-02-0.64um
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- CH-03-0.87um
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- CH-04-1.38um
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...
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See the `API Documentation <api/DataAccessLayer.html>`_ for more information.
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----------------------
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Read The Docs Contents
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----------------------
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.. toctree::
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.. toctree::
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:maxdepth: 2
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:maxdepth: 2
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:hidden:
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api/index
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api/index
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datatypes
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datatypes
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"cell_type": "markdown",
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"cell_type": "markdown",
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"metadata": {},
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"metadata": {},
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"source": [
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"source": [
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"This example covers the callable methods of the Python AWIPS DAF when working with gridded data. We start with a connection to an EDEX server, then query data types, then grid names, parameters, levels, and other information. Finally the gridded data is plotted for its domain using Matplotlib and Cartopy."
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"This example covers the callable methods of python-awips when working with gridded data. We start with a connection to an EDEX server, then query data types, then grid names, parameters, levels, and other information. Finally the gridded data is plotted for its domain using Matplotlib and Cartopy."
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]
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]
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},
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},
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{
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{
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