GPy/README.md

# GPy

The Gaussian processes framework in Python.

* GPy [homepage](http://sheffieldml.github.io/GPy/)
* Tutorial [notebooks](http://nbviewer.ipython.org/github/SheffieldML/notebook/blob/master/GPy/index.ipynb)
* User [mailing-list](https://lists.shef.ac.uk/sympa/subscribe/gpy-users)
* Developer [documentation](http://pythonhosted.org/GPy/)
* Travis-CI [unit-tests](https://travis-ci.org/SheffieldML/GPy)
* [![licence](https://img.shields.io/badge/licence-BSD-blue.svg)](http://opensource.org/licenses/BSD-3-Clause)

[![develstat](https://travis-ci.org/SheffieldML/GPy.svg?branch=devel)](https://travis-ci.org/SheffieldML/GPy) [![covdevel](http://codecov.io/github/SheffieldML/GPy/coverage.svg?branch=devel)](http://codecov.io/github/SheffieldML/GPy?branch=devel) [![Research software impact](http://depsy.org/api/package/pypi/GPy/badge.svg)](http://depsy.org/package/python/GPy)

## Updated Structure

We have pulled the core parameterization out of GPy. It is a package called [paramz](https://github.com/sods/paramz) and is the pure gradient based model optimization.

If you installed GPy with pip, just upgrade the package using:

    $ pip install --upgrade GPy

If you have the developmental version of GPy (using the develop or -e option) just install the dependencies by running

    $ python setup.py develop

again, in the GPy installation folder.

A warning: This usually works, but sometimes `distutils/setuptools` opens a
whole can of worms here, specially when compiled extensions are involved.
If that is the case, it is best to clean the repo and reinstall.

## Supported Platforms:

[<img src="https://www.python.org/static/community_logos/python-logo-generic.svg" height=40px>](https://www.python.org/)
[<img src="https://upload.wikimedia.org/wikipedia/commons/5/5f/Windows_logo_-_2012.svg" height=40px>](http://www.microsoft.com/en-gb/windows)
[<img src="https://upload.wikimedia.org/wikipedia/commons/8/8e/OS_X-Logo.svg" height=40px>](http://www.apple.com/osx/)
[<img src="https://upload.wikimedia.org/wikipedia/commons/3/35/Tux.svg" height=40px>](https://en.wikipedia.org/wiki/List_of_Linux_distributions)

Python 2.7, 3.4 and higher

## Citation

    @Misc{gpy2014,
      author =   {{The GPy authors}},
      title =    {{GPy}: A Gaussian process framework in python},
      howpublished = {\url{http://github.com/SheffieldML/GPy}},
      year = {2012--2015}
    }

### Pronounciation:

We like to pronounce it 'g-pie'.

## Getting started: installing with pip

We are now requiring the newest version (0.16) of
[scipy](http://www.scipy.org/) and thus, we strongly recommend using
the  [anaconda python distribution](http://continuum.io/downloads).
With anaconda you can install GPy by the following:

    conda update scipy
    pip install gpy

We've also had luck with [enthought](http://www.enthought.com). Install scipy 0.16 (or later)
 and then pip install GPy:

    pip install gpy

If you'd like to install from source, or want to contribute to the project (i.e. by sending pull requests via github), read on.

### Troubleshooting installation problems

If you're having trouble installing GPy via `pip install GPy` here is a probable solution:

    git clone https://github.com/SheffieldML/GPy.git
    cd GPy
    git checkout devel
    python setup.py build_ext --inplace
    nosetests GPy/testing

### Direct downloads

[![PyPI version](https://badge.fury.io/py/GPy.svg)](https://pypi.python.org/pypi/GPy) [![source](https://img.shields.io/badge/download-source-green.svg)](https://pypi.python.org/pypi/GPy)
[![Windows](https://img.shields.io/badge/download-windows-orange.svg)](https://pypi.python.org/pypi/GPy)
[![MacOSX](https://img.shields.io/badge/download-macosx-blue.svg)](https://pypi.python.org/pypi/GPy)

## Running unit tests:

Ensure nose is installed via pip:

    pip install nose

Run nosetests from the root directory of the repository:

    nosetests -v GPy/testing

or from within IPython

    import GPy; GPy.tests()

or using setuptools

    python setup.py test

## Ubuntu hackers

> Note: Right now the Ubuntu package index does not include scipy 0.16.0, and thus, cannot
> be used for GPy. We hope this gets fixed soon.

For the most part, the developers are using ubuntu. To install the required packages:

    sudo apt-get install python-numpy python-scipy python-matplotlib

clone this git repository and add it to your path:

    git clone git@github.com:SheffieldML/GPy.git ~/SheffieldML
    echo 'PYTHONPATH=$PYTHONPATH:~/SheffieldML' >> ~/.bashrc


## Compiling documentation:

The documentation is stored in doc/ and is compiled with the Sphinx Python documentation generator, and is written in the reStructuredText format.

The Sphinx documentation is available here: http://sphinx-doc.org/latest/contents.html

**Installing dependencies:**

To compile the documentation, first ensure that Sphinx is installed. On Debian-based systems, this can be achieved as follows:

    sudo apt-get install python-pip
    sudo pip install sphinx

**Compiling documentation:**

The documentation can be compiled as follows:

    cd doc
    sphinx-apidoc -o source/ ../GPy/
    make html

The HTML files are then stored in doc/build/html

## Funding Acknowledgements

Current support for the GPy software is coming through the following projects.

* [EU FP7-HEALTH Project Ref 305626](http://radiant-project.eu) "RADIANT: Rapid Development and Distribution of Statistical Tools for High-Throughput Sequencing Data"

* [EU FP7-PEOPLE Project Ref 316861](http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/projects/mlpm/) "MLPM2012: Machine Learning for Personalized Medicine"

* MRC Special Training Fellowship "Bayesian models of expression in the transcriptome for clinical RNA-seq"

*  [EU FP7-ICT Project Ref 612139](http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/projects/wysiwyd/) "WYSIWYD: What You Say is What You Did"

Previous support for the GPy software came from the following projects:

- [BBSRC Project No BB/K011197/1](http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/projects/recombinant/) "Linking recombinant gene sequence to protein product manufacturability using CHO cell genomic resources"
- [EU FP7-KBBE Project Ref 289434](http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/projects/biopredyn/) "From Data to Models: New Bioinformatics Methods and Tools for Data-Driven Predictive Dynamic Modelling in Biotechnological Applications"
- [BBSRC Project No BB/H018123/2](http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/projects/iterative/) "An iterative pipeline of computational modelling and experimental design for uncovering gene regulatory networks in vertebrates"
- [Erasysbio](http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/projects/synergy/) "SYNERGY: Systems approach to gene regulation biology through nuclear receptors"