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        "description": "eofs - EOF analysis in Python\n=============================\n\n[![Build Status](https://travis-ci.org/ajdawson/eofs.svg?branch=master)](https://travis-ci.org/ajdawson/eofs) [![DOI (paper)](https://img.shields.io/badge/DOI%20%28paper%29-10.5334%2Fjors.122-blue.svg)](http://doi.org/10.5334/jors.122) [![DOI (latest release)](https://zenodo.org/badge/20448/ajdawson/eofs.svg)](https://zenodo.org/badge/latestdoi/20448/ajdawson/eofs)\n\n\nOverview\n--------\n\neofs is a Python package for performing empirical orthogonal function (EOF) analysis on spatial-temporal data sets, licensed under the GNU GPLv3.\n\nThe package was created to simplify the process of EOF analysis in the Python environment.\nSome of the key features are listed below:\n\n* Suitable for large data sets: computationally efficient for the large data sets typical of modern climate model output.\n* Transparent handling of missing values: missing values are removed automatically when computing EOFs and re-inserted into output fields.\n* Meta-data preserving interfaces (optional): works with the iris data analysis package, xarray, or the cdms2 module (from UV-CDAT) to carry meta-data over from input fields to output.\n* No Fortran dependencies: written in Python using the power of NumPy, no compilers required.\n\n\nRequirements\n------------\n\neofs only requires the NumPy package (and setuptools to install).\nIn order to use the meta-data preserving interfaces one (or more) of cdms2 (part of [UV-CDAT](http://uvcdat.llnl.gov/)), [iris](http://scitools.org.uk/iris), or [xarray](http://xarray.pydata.org) is needed.\n\n\nDocumentation\n-------------\n\nDocumentation is available [online](http://ajdawson.github.com/eofs).\nThe package docstrings are also very complete and can be used as a source of reference when working interactively.\n\n\nCitation\n--------\n\nIf you use eofs in published research, please cite it by referencing the [peer-reviewed paper](http://doi.org/10.5334/jors.122).\nYou can additionally cite the [Zenodo DOI](http://dx.doi.org/10.5281/zenodo.46871) if you need to cite a particular version (but please also cite the paper, it helps me justify my time working on this and similar projects).\n\n\nInstallation\n------------\n\neofs works on Python 2 or 3 on Linux, Windows or OSX.\nThe easiest way to install eofs is by using [conda](http://conda.pydata.org/docs/) or pip:\n\n    conda install -c conda-forge eofs\n\nor\n\n    pip install eofs\n\nYou can also install from the source distribution:\n\n    python setup.py install\n\n\nFrequently asked questions\n--------------------------\n\n* **Do I need UV-CDAT/cdms2, iris or xarray to use eofs?**\n  No. All the computation code uses NumPy only.\n  The cdms2 module, iris and xarray are only required for the meta-data preserving interfaces.",
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