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GPy

The Gaussian processes framework in Python.

Continuous integration

Travis-CI Codecov RTFD
master: master codecov.io master Documentation Status
devel: devel codecov.io devel Documentation Status

Supported Platforms:

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 and thus, we strongly recommend using the anaconda python distribution. With anaconda you can install GPy by the following:

conda update scipy
pip install gpy

We've also had luck with enthought. 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 source Windows MacOSX

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 [email protected]: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.

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

  • BBSRC Project No BB/K011197/1 "Linking recombinant gene sequence to protein product manufacturability using CHO cell genomic resources"
  • EU FP7-KBBE Project Ref 289434 "From Data to Models: New Bioinformatics Methods and Tools for Data-Driven Predictive Dynamic Modelling in Biotechnological Applications"
  • BBSRC Project No BB/H018123/2 "An iterative pipeline of computational modelling and experimental design for uncovering gene regulatory networks in vertebrates"
  • Erasysbio "SYNERGY: Systems approach to gene regulation biology through nuclear receptors"

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