mirror of
https://github.com/SheffieldML/GPy.git
synced 2026-04-25 12:56:22 +02:00
148 lines
6.5 KiB
Markdown
148 lines
6.5 KiB
Markdown
# 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 | RTFD |
|
|
| ---: | :--: | :---: | :---: |
|
|
| **master:** | [](https://travis-ci.org/SheffieldML/GPy) | [](http://codecov.io/github/SheffieldML/GPy?branch=master) | [](http://gpy.readthedocs.org/en/master/) |
|
|
| **devel:** | [](https://travis-ci.org/SheffieldML/GPy) | [](http://codecov.io/github/SheffieldML/GPy?branch=devel) | [](http://gpy.readthedocs.org/en/devel/) |
|
|
|
|
## 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, 3.3 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"
|