Metadata-Version: 2.1
Name: xgcm
Version: 0.5.0
Summary: General Circulation Model Postprocessing with xarray
Home-page: https://github.com/xgcm/xgcm
Author: xgcm Developers
Author-email: rpa@ldeo.columbia.edu
License: MIT
Description: xgcm: General Circulation Model Postprocessing with xarray
        ==========================================================
        
        |pypi| |conda forge| |conda-forge| |Build Status| |codecov| |docs| |DOI| |license| |Code style|
        
        Binder Examples
        ---------------
        
        ========= ============== ============================================================================
        Link      Provider       Description
        ========= ============== ============================================================================
        |Binder|  mybinder.org   Basic self-contained example
        |PBinder| Pangeo Binder  More complex examples integrated with other Pangeo tools (dask, zarr, etc.)
        ========= ============== ============================================================================
        
        Description
        -----------
        
        **xgcm** is a python package for working with the datasets produced by numerical
        `General Circulation Models <https://en.wikipedia.org/wiki/General_circulation_model>`_
        (GCMs) and similar gridded datasets that are amenable to
        `finite volume <https://en.wikipedia.org/wiki/Finite_volume_method>`_ analysis.
        In these datasets, different variables are located at different positions with
        respect to a volume or area element (e.g. cell center, cell face, etc.)
        xgcm solves the problem of how to interpolate and difference these variables
        from one position to another.
        
        xgcm consumes and produces xarray_ data structures, which are coordinate and
        metadata-rich representations of multidimensional array data. xarray is ideal
        for analyzing GCM data in many ways, providing convenient indexing and grouping,
        coordinate-aware data transformations, and (via dask_) parallel,
        out-of-core array computation. On top of this, xgcm adds an understanding of
        the finite volume `Arakawa Grids`_ commonly used in ocean and atmospheric
        models and differential and integral operators suited to these grids.
        
        xgcm was motivated by the rapid growth in the numerical resolution of
        ocean, atmosphere, and climate models. While highly parallel supercomputers can
        now easily generate tera- and petascale datasets, common post-processing
        workflows struggle with these volumes. Furthermore, we believe that a flexible,
        evolving, open-source, python-based framework for GCM analysis will enhance
        the productivity of the field as a whole, accelerating the rate of discovery in
        climate science. xgcm is part of the Pangeo_ initiative.
        
        For more information, including installation instructions, read the full
        `xgcm documentation`_.
        
        .. _Pangeo: http://pangeo-data.github.io
        .. _dask: http://dask.pydata.org
        .. _xarray: http://xarray.pydata.org
        .. _Arakawa Grids: https://en.wikipedia.org/wiki/Arakawa_grid
        .. _xgcm documentation: https://xgcm.readthedocs.io/
        
        .. |conda forge| image:: https://img.shields.io/conda/vn/conda-forge/xgcm
           :target: https://anaconda.org/conda-forge/xgcm
        .. |DOI| image:: https://zenodo.org/badge/41581350.svg
           :target: https://zenodo.org/badge/latestdoi/41581350
        .. |Build Status| image:: https://img.shields.io/github/workflow/status/xgcm/xgcm/CI?logo=github
           :target: https://github.com/xgcm/xgcm/actions
           :alt: GitHub Workflow CI Status
        .. |codecov| image:: https://codecov.io/github/xgcm/xgcm/coverage.svg?branch=master
           :target: https://codecov.io/github/xgcm/xgcm?branch=master
           :alt: code coverage
        .. |pypi| image:: https://badge.fury.io/py/xgcm.svg
           :target: https://badge.fury.io/py/xgcm
           :alt: pypi package
        .. |docs| image:: http://readthedocs.org/projects/xgcm/badge/?version=latest
           :target: http://xgcm.readthedocs.org/en/stable/?badge=latest
           :alt: documentation status
        .. |license| image:: https://img.shields.io/github/license/mashape/apistatus.svg
           :target: https://github.com/xgcm/xgcm
           :alt: license
        .. |Code style| image:: https://img.shields.io/badge/code%20style-black-000000.svg
           :target: https://github.com/python/black
           :alt: Code style
        .. |Binder| image:: https://mybinder.org/badge_logo.svg
           :target: https://mybinder.org/v2/gh/xgcm/xgcm/master?filepath=doc%2Fexample_mitgcm.ipynb
        .. |PBinder| image:: https://binder.pangeo.io/badge_logo.svg
           :target: https://binder.pangeo.io/v2/gh/pangeo-data/pangeo-ocean-examples/master
        .. |conda-forge| image:: https://img.shields.io/conda/dn/conda-forge/xgcm?label=conda-forge
           :target: https://anaconda.org/conda-forge/xgcm
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
Provides-Extra: complete
Provides-Extra: docs
Provides-Extra: dev
