The Gaussian Process Toolbox
Project description
# 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://gpy.readthedocs.org/en/devel/)
* 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)
## 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.
## Continuous integration
| | Travis-CI | Codecov | RTFD |
| ---: | :--: | :---: | :---: |
| **master:** | [![masterstat](https://travis-ci.org/SheffieldML/GPy.svg?branch=master)](https://travis-ci.org/SheffieldML/GPy) | [![covmaster](http://codecov.io/github/SheffieldML/GPy/coverage.svg?branch=master)](http://codecov.io/github/SheffieldML/GPy?branch=master) | [![docmaster](https://readthedocs.org/projects/gpy/badge/?version=master)](http://gpy.readthedocs.org/en/master/) |
| **devel:** | [![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) | [![docdevel](https://readthedocs.org/projects/gpy/badge/?version=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
[![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"
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://gpy.readthedocs.org/en/devel/)
* 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)
## 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.
## Continuous integration
| | Travis-CI | Codecov | RTFD |
| ---: | :--: | :---: | :---: |
| **master:** | [![masterstat](https://travis-ci.org/SheffieldML/GPy.svg?branch=master)](https://travis-ci.org/SheffieldML/GPy) | [![covmaster](http://codecov.io/github/SheffieldML/GPy/coverage.svg?branch=master)](http://codecov.io/github/SheffieldML/GPy?branch=master) | [![docmaster](https://readthedocs.org/projects/gpy/badge/?version=master)](http://gpy.readthedocs.org/en/master/) |
| **devel:** | [![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) | [![docdevel](https://readthedocs.org/projects/gpy/badge/?version=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
[![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"
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
GPy-1.0.0.tar.gz
(3.6 MB
view hashes)
Built Distributions
Close
Hashes for GPy-1.0.0-cp35-cp35m-macosx_10_5_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | a0daeaa00beaf9147b0c30035f42754f439dd8a4bb26185aa3ffb968b4b8a467 |
|
MD5 | c2ae951b4a96fe4181358bf406090656 |
|
BLAKE2b-256 | d03781190d5be4605acff045c2758fedfe709fffac29e5cac15ac26e68273504 |
Close
Hashes for GPy-1.0.0-cp34-cp34m-macosx_10_5_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b6a374d98e799b5ca0ce794903bf74d4997e9e722363a1601501fb66a6329a05 |
|
MD5 | 25b87ce0ca65ee9a07afa2a8e96754c8 |
|
BLAKE2b-256 | 9849708e96456d67983ed862daf790a15272b538b7364741744a814361b314a8 |
Close
Hashes for GPy-1.0.0-cp33-cp33m-macosx_10_5_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3064d39c78bfe6e0d9a3d48cae465f739f301b7db600883f5e9ba12e367ee65f |
|
MD5 | 3e836ffcf66720abee12c349f160305e |
|
BLAKE2b-256 | d33e0a922dc72b4e7cd6b6108c39fc9cd389bc58f7cb977910301f02fdeaf693 |
Close
Hashes for GPy-1.0.0-cp27-cp27m-macosx_10_5_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | ed8c6069f04295f81bd5ea9b73ea22880b823ee9014dd09d76ad5fefc060ad6f |
|
MD5 | 5b92a701435cd7843e84592ad2e0ac81 |
|
BLAKE2b-256 | 4bf67103c29c0ec35c334cf2d017e704836abb8af855b0114d465d28b9efc236 |