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[readme] added stub rst readme, so that pypi shows a link to the github page
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Max Zwiessele
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README.rst
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README.rst
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GPy
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===
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The Gaussian processes framework in Python.
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- GPy `homepage <http://sheffieldml.github.io/GPy/>`__
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- Tutorial
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`notebooks <http://nbviewer.ipython.org/github/SheffieldML/notebook/blob/master/GPy/index.ipynb>`__
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- User
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`mailing-list <https://lists.shef.ac.uk/sympa/subscribe/gpy-users>`__
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- Developer `documentation <http://gpy.readthedocs.org/en/devel/>`__
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- Travis-CI `unit-tests <https://travis-ci.org/SheffieldML/GPy>`__
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- |licence|
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Updated Structure
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-----------------
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We have pulled the core parameterization out of GPy. It is a package
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called `paramz <https://github.com/sods/paramz>`__ and is the pure
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gradient based model optimization.
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If you installed GPy with pip, just upgrade the package using:
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::
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$ pip install --upgrade GPy
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If you have the developmental version of GPy (using the develop or -e
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option) just install the dependencies by running
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::
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$ python setup.py develop
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again, in the GPy installation folder.
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A warning: This usually works, but sometimes ``distutils/setuptools``
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opens a whole can of worms here, specially when compiled extensions are
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involved. If that is the case, it is best to clean the repo and
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reinstall.
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Continuous integration
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----------------------
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+---------------+----------------+---------------+---------------+
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| | Travis-CI | Codecov | RTFD |
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+===============+================+===============+===============+
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| **master:** | |masterstat| | |covmaster| | |docmaster| |
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+---------------+----------------+---------------+---------------+
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| **devel:** | |develstat| | |covdevel| | |docdevel| |
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+---------------+----------------+---------------+---------------+
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Supported Platforms:
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--------------------
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` <https://www.python.org/>`__
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` <http://www.microsoft.com/en-gb/windows>`__
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` <http://www.apple.com/osx/>`__
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` <https://en.wikipedia.org/wiki/List_of_Linux_distributions>`__
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Python 2.7, 3.3 and higher
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Citation
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--------
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::
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@Misc{gpy2014,
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author = {{The GPy authors}},
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title = {{GPy}: A Gaussian process framework in python},
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howpublished = {\url{http://github.com/SheffieldML/GPy}},
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year = {2012--2015}
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}
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Pronounciation:
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~~~~~~~~~~~~~~~
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We like to pronounce it 'g-pie'.
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Getting started: installing with pip
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------------------------------------
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We are now requiring the newest version (0.16) of
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`scipy <http://www.scipy.org/>`__ and thus, we strongly recommend using
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the `anaconda python distribution <http://continuum.io/downloads>`__.
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With anaconda you can install GPy by the following:
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::
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conda update scipy
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pip install gpy
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We've also had luck with `enthought <http://www.enthought.com>`__.
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Install scipy 0.16 (or later) and then pip install GPy:
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::
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pip install gpy
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If you'd like to install from source, or want to contribute to the
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project (i.e. by sending pull requests via github), read on.
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Troubleshooting installation problems
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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If you're having trouble installing GPy via ``pip install GPy`` here is
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a probable solution:
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::
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git clone https://github.com/SheffieldML/GPy.git
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cd GPy
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git checkout devel
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python setup.py build_ext --inplace
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nosetests GPy/testing
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Direct downloads
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~~~~~~~~~~~~~~~~
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|PyPI version| |source| |Windows| |MacOSX|
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Running unit tests:
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-------------------
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Ensure nose is installed via pip:
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::
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pip install nose
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Run nosetests from the root directory of the repository:
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::
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nosetests -v GPy/testing
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or from within IPython
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::
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import GPy; GPy.tests()
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or using setuptools
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::
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python setup.py test
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Ubuntu hackers
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--------------
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Note: Right now the Ubuntu package index does not include scipy
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0.16.0, and thus, cannot be used for GPy. We hope this gets fixed
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soon.
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For the most part, the developers are using ubuntu. To install the
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required packages:
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::
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sudo apt-get install python-numpy python-scipy python-matplotlib
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clone this git repository and add it to your path:
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::
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git clone git@github.com:SheffieldML/GPy.git ~/SheffieldML
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echo 'PYTHONPATH=$PYTHONPATH:~/SheffieldML' >> ~/.bashrc
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Compiling documentation:
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------------------------
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The documentation is stored in doc/ and is compiled with the Sphinx
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Python documentation generator, and is written in the reStructuredText
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format.
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The Sphinx documentation is available here:
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http://sphinx-doc.org/latest/contents.html
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**Installing dependencies:**
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To compile the documentation, first ensure that Sphinx is installed. On
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Debian-based systems, this can be achieved as follows:
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::
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sudo apt-get install python-pip
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sudo pip install sphinx
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**Compiling documentation:**
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The documentation can be compiled as follows:
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::
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cd doc
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sphinx-apidoc -o source/ ../GPy/
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make html
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The HTML files are then stored in doc/build/html
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Funding Acknowledgements
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------------------------
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Current support for the GPy software is coming through the following
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projects.
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- `EU FP7-HEALTH Project Ref 305626 <http://radiant-project.eu>`__
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"RADIANT: Rapid Development and Distribution of Statistical Tools for
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High-Throughput Sequencing Data"
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- `EU FP7-PEOPLE Project Ref
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316861 <http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/projects/mlpm/>`__
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"MLPM2012: Machine Learning for Personalized Medicine"
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- MRC Special Training Fellowship "Bayesian models of expression in the
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transcriptome for clinical RNA-seq"
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- `EU FP7-ICT Project Ref
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612139 <http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/projects/wysiwyd/>`__
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"WYSIWYD: What You Say is What You Did"
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Previous support for the GPy software came from the following projects:
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- `BBSRC Project No
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BB/K011197/1 <http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/projects/recombinant/>`__
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"Linking recombinant gene sequence to protein product
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manufacturability using CHO cell genomic resources"
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- `EU FP7-KBBE Project Ref
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289434 <http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/projects/biopredyn/>`__
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"From Data to Models: New Bioinformatics Methods and Tools for
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Data-Driven Predictive Dynamic Modelling in Biotechnological
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Applications"
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- `BBSRC Project No
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BB/H018123/2 <http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/projects/iterative/>`__
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"An iterative pipeline of computational modelling and experimental
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design for uncovering gene regulatory networks in vertebrates"
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- `Erasysbio <http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/projects/synergy/>`__
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"SYNERGY: Systems approach to gene regulation biology through nuclear
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receptors"
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.. |licence| image:: https://img.shields.io/badge/licence-BSD-blue.svg
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:target: http://opensource.org/licenses/BSD-3-Clause
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.. |masterstat| image:: https://travis-ci.org/SheffieldML/GPy.svg?branch=master
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:target: https://travis-ci.org/SheffieldML/GPy
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.. |covmaster| image:: http://codecov.io/github/SheffieldML/GPy/coverage.svg?branch=master
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:target: http://codecov.io/github/SheffieldML/GPy?branch=master
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.. |docmaster| image:: https://readthedocs.org/projects/gpy/badge/?version=master
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:target: http://gpy.readthedocs.org/en/master/
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.. |develstat| image:: https://travis-ci.org/SheffieldML/GPy.svg?branch=devel
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:target: https://travis-ci.org/SheffieldML/GPy
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.. |covdevel| image:: http://codecov.io/github/SheffieldML/GPy/coverage.svg?branch=devel
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:target: http://codecov.io/github/SheffieldML/GPy?branch=devel
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.. |docdevel| image:: https://readthedocs.org/projects/gpy/badge/?version=devel
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:target: http://gpy.readthedocs.org/en/devel/
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.. |PyPI version| image:: https://badge.fury.io/py/GPy.svg
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:target: https://pypi.python.org/pypi/GPy
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.. |source| image:: https://img.shields.io/badge/download-source-green.svg
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:target: https://pypi.python.org/pypi/GPy
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.. |Windows| image:: https://img.shields.io/badge/download-windows-orange.svg
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:target: https://pypi.python.org/pypi/GPy
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.. |MacOSX| image:: https://img.shields.io/badge/download-macosx-blue.svg
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:target: https://pypi.python.org/pypi/GPy
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