# 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/)
* [Unit tests (Travis-CI)](https://travis-ci.org/SheffieldML/GPy)
* [](http://opensource.org/licenses/BSD-3-Clause)
## Continuous integration
| | Travis-CI | Codecov |
| ---: | :--: | :---: |
| **master:** | [](https://travis-ci.org/SheffieldML/GPy) | [](http://codecov.io/github/SheffieldML/GPy?branch=master) |
| **devel:** | [](https://travis-ci.org/SheffieldML/GPy) | [](http://codecov.io/github/SheffieldML/GPy?branch=devel) |
## Supported Platforms:
[
](https://www.python.org/)
[
](http://www.microsoft.com/en-gb/windows)
[
](http://www.apple.com/osx/)
[
](https://en.wikipedia.org/wiki/List_of_Linux_distributions)
Python 2.7, 3.3 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
[](https://pypi.python.org/pypi/GPy) [](https://pypi.python.org/pypi/GPy)
[](https://pypi.python.org/pypi/GPy)
[](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"