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Py-ART is used by the\n`Atmospheric Radiation Measurement (ARM) User Facility\n\u003chttp://www.arm.gov\u003e`_ for working with data from a number of precipitation\nand cloud radars, but has been designed so that it can be used by others in\nthe radar and atmospheric communities to examine, processes, and analyze\ndata from many types of weather radars.\n\n\nImportant Links\n===============\n\n- Official source code repository: https://github.com/ARM-DOE/pyart\n- HTML documentation: https://arm-doe.github.io/pyart/\n- Examples: https://arm-doe.github.io/pyart/examples\n- Mailing List: https://openradar.discourse.group/tag/py-art\n- Issue Tracker: https://github.com/ARM-DOE/pyart/issues\n\n\nCiting\n======\n\nIf you use the Python ARM Radar Toolkit (Py-ART) to prepare a publication\nplease cite:\n\n    Helmus, J.J. \u0026 Collis, S.M., (2016). The Python ARM Radar Toolkit\n    (Py-ART), a Library for Working with Weather Radar Data in the Python\n    Programming Language. Journal of Open Research Software. 4(1), p.e25.\n    DOI: http://doi.org/10.5334/jors.119\n\nPy-ART implements many published scientific methods which should *also* be\ncited if you make use of them. Refer to the **References** section in the\ndocumentation of the functions used for information on these citations.\n\n\nInstall\n=======\n\nThe easiest method for installing Py-ART is to use the conda packages from\nthe latest release and use Python 3, as Python 2 support ended January 1st,\n2020 and many packages including Py-ART no longer support Python 2.\nTo do this you must download and install\n`Anaconda \u003chttps://www.anaconda.com/download/#\u003e`_ or\n`Miniconda \u003chttps://conda.io/miniconda.html\u003e`_.\nWith Anaconda or Miniconda install, it is recommended to create a new conda\nenvironment when using Py-ART or even other packages. To create a new\nenvironment based on the `environment.yml \u003chttps://github.com/ARM-DOE/pyart/blob/master/environment.yml\u003e`_::\n\n    conda env create -f environment.yml\n\nOr for a basic environment and downloading optional dependencies as needed::\n\n    conda create -n pyart_env -c conda-forge python=3.9 arm_pyart\n\nBasic command in a terminal or command prompt to install the latest version of\nPy-ART::\n\n    conda install -c conda-forge arm_pyart\n\nTo update an older version of Py-ART to the latest release use::\n\n    conda update -c conda-forge arm_pyart\n\nIf you are using mamba::\n\n    mamba install -c conda-forge arm_pyart\n\nIf you do not wish to use Anaconda or Miniconda as a Python environment or want\nto use the latest, unreleased version of Py-ART see the section below on\n**Installing from source**.\n\n\nConfiguration\n=============\n\nThe configuration file in Py-ART specifies the default metadata, field names,\ncolormaps and plot limits. A custom configuration can be loaded\nautomatically be setting the environmental variable **PYART_CONFIG** to point\nto a custom configuration file. For additional details on this process see the\ndocumentation on the `pyart.load_config` function.\n\n\nExtensions and related software\n===============================\n\nA number of projects are available which extend the functionality of Py-ART.\nThese include:\n\n* `ARTView \u003chttps://github.com/nguy/artview\u003e`_ :\n  Interactive radar viewing browser.\n\n* `pyrad \u003chttps://github.com/MeteoSwiss/pyrad\u003e`_ :\n  A real-time data processing framework developed by MeteoSwiss and MeteoFrance.\n\n* `PyTDA \u003chttps://github.com/nasa/PyTDA\u003e`_ :\n  Python Turbulence Detection Algorithm.\n\n* `SingleDop \u003chttps://github.com/nasa/SingleDop\u003e`_ :\n  Single Doppler Retrieval Toolkit.\n\n* `DualPol \u003chttps://github.com/nasa/DualPol\u003e`_ :\n  Python Interface to Dual-Pol Radar Algorithms.\n\n* `PyBlock \u003chttps://github.com/nasa/PyBlock\u003e`_:\n  Python Polarimetric Radar Beam Blockage Calculation\n\n\nOther related open source software for working with weather radar data:\n\n* `wradlib \u003chttps://wradlib.org\u003e`_ :\n  An open source library for weather radar data processing.\n\n* `BALTRAD \u003chttps://baltrad.eu/\u003e`_ : Community-based weather radar networking.\n\n* `MMM-Py \u003chttps://github.com/nasa/MMM-Py\u003e`_ :\n  Marshall MRMS Mosaic Python Toolkit.\n\n* `CSU_RadarTools \u003chttps://github.com/CSU-Radarmet/CSU_RadarTools\u003e`_ :\n  Colorado State University Radar Tools.\n\n* `TRMM RSL \u003chttps://trmm-fc.gsfc.nasa.gov/trmm_gv/software/rsl/\u003e`_ :\n  TRMM Radar Software Library.\n\n* `RadX \u003chttps://www.ral.ucar.edu/projects/titan/docs/radial_formats/radx.html\u003e`_ :\n  Radx C++ Software Package for Radial Radar Data.\n\n* `PyDDA \u003chttps://openradarscience.org/PyDDA/\u003e`_ :\n  Software designed to retrieve wind kinematics in precipitation storm systems\n  from one or more Doppler weather radars.\n\n\nDependencies\n============\n\nPy-ART is tested to work under Python 3.11, 3.12, and 3.13.\n\nThe required dependencies to install Py-ART in addition to Python are:\n\n* `NumPy \u003chttps://www.numpy.org/\u003e`_\n* `SciPy \u003chttps://www.scipy.org\u003e`_\n* `matplotlib \u003chttps://matplotlib.org/\u003e`_\n* `netCDF4 \u003chttps://github.com/Unidata/netcdf4-python\u003e`_\n* `pooch \u003chttps://pypi.org/project/pooch/\u003e`_\n* `Cython \u003chttps://cython.readthedocs.io/en/latest/\u003e`_\n* `setuptools \u003chttps://setuptools.pypa.io/en/latest/index.html\u003e`_\n* `cartopy \u003chttps://scitools.org.uk/cartopy/docs/latest/\u003e`_\n* `cmweather \u003chttps://cmweather.readthedocs.io/en/latest/\u003e`_\n\nA working C/C++ compiler is required for some optional modules. An easy method\nto install these dependencies is by using a\n`Scientific Python distributions \u003chttp://scipy.org/install.html\u003e`_.\n`Anaconda \u003chttps://www.anaconda.com/distribution/\u003e`_ will install all of\nthe above packages by default on Windows, Linux and Mac computers and is\nprovided free of charge by Anaconda. Anaconda also has their own compilers,\nwhich may be required for optional dependencies such as CyLP. These compilers\ncan be found here:\nhttps://docs.conda.io/projects/conda-build/en/latest/resources/compiler-tools.html\n\n\nOptional Dependences\n====================\n\nThe above Python modules are require before installing Py-ART, additional\nfunctionality is available of the following modules are installed.\n\n* `TRMM Radar Software Library (RSL)\n  \u003chttps://trmm-fc.gsfc.nasa.gov/trmm_gv/software/rsl/\u003e`_.\n  If installed Py-ART will be able to read in radar data in a number of\n  additional formats (Lassen, McGill, Universal Format, and RADTEC) and\n  perform automatic dealiasing of Doppler velocities.  RSL should be\n  install prior to installing Py-ART. The environmental variable `RSL_PATH`\n  should point to the location where RSL was installed if RSL was not\n  installed in the default location (/usr/local/trmm), such as a anaconda path\n  (/usr/anaconda3/envs/pyart_env/.\n\n* In order to read files which are stored in HDF5 files the\n  `h5py \u003chttps://www.h5py.org/\u003e`_ package and related libraries must be\n  installed.\n\n* A linear programming solver and Python wrapper to use the LP phase\n  processing method. `CyLP \u003chttps://github.com/mpy/CyLP\u003e`_ is recommended as\n  it gives the fastest results, but\n  `PyGLPK \u003chttps://tfinley.net/software/pyglpk/\u003e`_ and\n  `CVXOPT \u003chttps://cvxopt.org/\u003e`_ are also supported. The underlying LP\n  solvers `CBC \u003chttps://projects.coin-or.org/Cbc\u003e`_ or\n  `GLPK \u003chttps://www.gnu.org/software/glpk/\u003e`_ will also be required depending\n  on which wrapper is used. When using `CyLP \u003chttps://github.com/mpy/CyLP\u003e`_\n  a path to coincbc is needed by setting the `COIN_INSTALL_DIR` path, such as\n  (/usr/anaconda3/envs/pyart_env/).\n\n* `Cartopy \u003chttps://scitools.org.uk/cartopy/docs/latest/\u003e`_. If installed,\n  the ability to plot grids on geographic maps is available.\n\n* `xarray \u003chttps://xarray.pydata.org/en/stable/\u003e`_. If installed, gives the\n  ability to work with the grid dataset used in grid plotting.\n\n* `Basemap \u003chttps://matplotlib.org/basemap/\u003e`_. If installed, also gives the\n  ability to plot grids on geographic maps, but Cartopy is recommended over\n  Basemap.\n\n* `wradlib \u003chttps://docs.wradlib.org/en/latest/\u003e`_.  Needed to calculate the texture\n  of a differential phase field.\n\n* `pytest \u003chttps://docs.pytest.org/en/latest/\u003e`_.\n  Required to run the Py-ART unit tests.\n\n* `gdal \u003chttps://pypi.python.org/pypi/GDAL/\u003e`_.\n  Required to output GeoTIFFs from `Grid` objects.\n\nInstalling from source\n======================\n\nInstalling Py-ART from source is the only way to get the latest updates and\nenhancement to the software that have not yet made it into a release.\nThe latest source code for Py-ART can be obtained from the GitHub repository,\nhttps://github.com/ARM-DOE/pyart. Either download and unpack the\n`zip file \u003chttps://github.com/ARM-DOE/pyart/archive/master.zip\u003e`_ of\nthe source code or use git to checkout the repository::\n\n    git clone https://github.com/ARM-DOE/pyart.git\n\nTo install in your home directory, use::\n\n    python setup.py install --user\n\nTo install for all users on Unix/Linux::\n\n    python setup.py build\n    sudo python setup.py install\n\nDevelopment install using pip from within Py-ART directory::\n\n    pip install -e .\n\n\nDevelopment\n===========\n\nPy-ART is an open source, community software project. Contributions to\nthe package are welcomed from all users.\n\nCode\n----\nThe latest source code can be obtained with the command::\n\n    git clone https://github.com/ARM-DOE/pyart.git\n\nIf you are planning on making changes that you would like included in Py-ART,\nforking the repository is highly recommended.\n\nGetting help\n------------\nPy-ART has a `Discussion Forum \u003chttps://github.com/ARM-DOE/pyart/discussions\u003e`_ where you can ask questions and request help.\n\nContributing\n-------------\n\nWe welcome contributions for all uses of Py-ART, provided the code can be\ndistributed under the BSD 3-clause license. A copy of this license is\navailable in the **LICENSE.txt** file in this directory. For more on\ncontributing, see the `contributor's guide. \u003chttps://github.com/ARM-DOE/pyart/blob/main/CONTRIBUTING.rst\u003e`_\n\nTesting\n-------\n\nFor testing, we use pytest for running the unit tests and open-test-data for\ntest files that are used for Py-ART's example gallery. To install pytest::\n\n   $ conda install -c conda-forge pytest\n\nTo install open-radar-data::\n\n   $ conda install -c conda-forge open-radar-data\n\nAfter installation of pytest you can launch the test\nsuite from outside the source directory (you will need to have pytest\ninstalled)::\n\n   $ pytest --pyargs pyart\n\nIn-place installs can be tested using the `pytest` command from within\nthe source directory.\n","funding_links":[],"categories":["Radar","Atmosphere"],"sub_categories":["Meteorological Observation and Forecast"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FARM-DOE%2Fpyart","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FARM-DOE%2Fpyart","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FARM-DOE%2Fpyart/lists"}