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"info": {
"author": "Ryan Abernathey",
"author_email": "rpa@ldeo.columbia.edu",
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"classifiers": [
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"License :: OSI Approved :: Apache Software License",
"Operating System :: OS Independent",
"Programming Language :: Python",
"Programming Language :: Python :: 2",
"Programming Language :: Python :: 2.6",
"Programming Language :: Python :: 2.7",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.3",
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"description": "xmitgcm: Read MITgcm mds binary files into xarray\n=================================================\n\n|pypi| |Build Status| |codecov| |docs| |DOI|\n\nxmitgcm is a python package for reading MITgcm_ binary MDS files into\nxarray_ data structures. By storing data in dask_ arrays, xmitgcm enables\nparallel, out-of-core_ analysis of MITgcm output data.\n\nLinks\n-----\n\n- HTML documentation: https://xmitgcm.readthedocs.org\n- Issue tracker: https://github.com/xgcm/xmitgcm/issues\n- Source code: https://github.com/xgcm/xmitgcm\n\nInstallation\n------------\n\nRequirements\n^^^^^^^^^^^^\n\nxmitgcm is compatible with python 3 and python 2.7. It requires xarray_\n(>= version 0.8.2) and dask_ (>= version 0.11.2).\nThese packages are most reliably installed via the\n`conda `_ environment management\nsystem, which is part of the Anaconda_ python distribution. Assuming you have\nconda available on your system, the dependencies can be installed with the\ncommand::\n\n conda install xarray dask\n\nIf you are using earlier versions of these packages, you should update before\ninstalling xmitgcm.\n\nInstallation via pip\n^^^^^^^^^^^^^^^^^^^^\n\nIf you just want to use xmitgcm, the easiest way is to install via pip::\n\n pip install xmitgcm\n\nThis will automatically install the latest release from\n`pypi `_.\n\nInstallation from github\n^^^^^^^^^^^^^^^^^^^^^^^^\n\nxmitgcm is under active development. To obtain the latest development version,\nyou may clone the `source repository `_\nand install it::\n\n git clone https://github.com/xgcm/xmitgcm.git\n cd xmitgcm\n python setup.py install\n\nUsers are encouraged to `fork `_\nxmitgcm and submit issues_ and `pull requests`_.\n\nQuick Start\n-----------\n\nFirst make sure you understand what an xarray_ Dataset object is. Then find\nsome MITgcm MDS data. If you don't have any data of your own, you can download\nthe xmitgcm\n`test repositories `_\nTo download the some test data, run the shell commands::\n\n $ curl -L -J -O https://ndownloader.figshare.com/files/6494718\n $ tar -xvzf global_oce_latlon.tar.gz\n\nThis will create a directory called ``global_oce_latlon`` which we will use\nfor the rest of these examples. If you have your own data, replace this with\nthe path to your mitgcm files.\n\nTo opean MITgcm MDS data as an xarray.Dataset, do the following in python::\n\n from xmitgcm import open_mdsdataset\n data_dir = './global_oce_latlon'\n ds = open_mdsdataset(data_dir)\n\n``data_dir``, should be the path (absolute or relative) to an\nMITgcm run directory. xmitgcm will automatically scan this directory and\ntry to determine the file prefixes and iteration numbers to read. In some\nconfigurations, the ``open_mdsdataset`` function may work without further\nkeyword arguments. In most cases, you will have to specify further details.\n\nConsult the `online documentation `_ for\nmore details.\n\n.. |DOI| image:: https://zenodo.org/badge/70649781.svg\n :target: https://zenodo.org/badge/latestdoi/70649781\n.. |Build Status| image:: https://travis-ci.org/xgcm/xmitgcm.svg?branch=master\n :target: https://travis-ci.org/xgcm/xmitgcm\n :alt: travis-ci build status\n.. |codecov| image:: https://codecov.io/github/xgcm/xmitgcm/coverage.svg?branch=master\n :target: https://codecov.io/github/xgcm/xmitgcm?branch=master\n :alt: code coverage\n.. |pypi| image:: https://badge.fury.io/py/xmitgcm.svg\n :target: https://badge.fury.io/py/xmitgcm\n :alt: pypi package\n.. |docs| image:: https://readthedocs.org/projects/xmitgcm/badge/?version=stable\n :target: https://xmitgcm.readthedocs.org/en/stable/?badge=stable\n :alt: documentation status\n\n.. _dask: https://dask.pydata.org\n.. _xarray: https://xarray.pydata.org\n.. _Comodo: https://pycomodo.forge.imag.fr/norm.html\n.. _issues: https://github.com/xgcm/xmitgcm/issues\n.. _`pull requests`: https://github.com/xgcm/xmitgcm/pulls\n.. _MITgcm: http://mitgcm.org/public/r2_manual/latest/online_documents/node277.html\n.. _out-of-core: https://en.wikipedia.org/wiki/Out-of-core_algorithm\n.. _Anaconda: https://www.continuum.io/downloads\n\n\n",
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