Metadata-Version: 2.0
Name: GPy
Version: 1.0.0
Summary: The Gaussian Process Toolbox
Home-page: http://sheffieldml.github.com/GPy/
Author: `GPy Authors <https://github.com/SheffieldML/GPy/graphs/contributors>`__
Requires-Dist: numpy (>=1.7)
Requires-Dist: paramz
Requires-Dist: scipy (>=0.16)
Requires-Dist: six
Provides-Extra: docs
Requires-Dist: sphinx; extra == 'docs'
Provides-Extra: notebook
Requires-Dist: ipykernel (>=4.1.0); extra == 'notebook'
Requires-Dist: ipywidgets (>=4.0.3); extra == 'notebook'
Requires-Dist: jupyter-client (>=4.0.6); extra == 'notebook'
Requires-Dist: notebook (>=4.0.5); extra == 'notebook'
Provides-Extra: optional
Requires-Dist: ipython (>=4.0.0); extra == 'optional'
Requires-Dist: mpi4py; extra == 'optional'
Provides-Extra: plotting
Requires-Dist: matplotlib (>=1.3); extra == 'plotting'
Requires-Dist: plotly (>=1.8.6); extra == 'plotting'

Author-email: gpy.authors@gmail.com
License: BSD 3-clause
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|
        
        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|   | |covmaster|   | |docmaster|   |
        +---------------+----------------+---------------+---------------+
        | **devel:**    | |develstat|    | |covdevel|    | |docdevel|    |
        +---------------+----------------+---------------+---------------+
        
        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
        ~~~~~~~~~~~~~~~~
        
        |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 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"
        
        .. |licence| image:: https://img.shields.io/badge/licence-BSD-blue.svg
           :target: http://opensource.org/licenses/BSD-3-Clause
        .. |masterstat| image:: https://travis-ci.org/SheffieldML/GPy.svg?branch=master
           :target: https://travis-ci.org/SheffieldML/GPy
        .. |covmaster| image:: http://codecov.io/github/SheffieldML/GPy/coverage.svg?branch=master
           :target: http://codecov.io/github/SheffieldML/GPy?branch=master
        .. |docmaster| image:: https://readthedocs.org/projects/gpy/badge/?version=master
           :target: http://gpy.readthedocs.org/en/master/
        .. |develstat| image:: https://travis-ci.org/SheffieldML/GPy.svg?branch=devel
           :target: https://travis-ci.org/SheffieldML/GPy
        .. |covdevel| image:: http://codecov.io/github/SheffieldML/GPy/coverage.svg?branch=devel
           :target: http://codecov.io/github/SheffieldML/GPy?branch=devel
        .. |docdevel| image:: https://readthedocs.org/projects/gpy/badge/?version=devel
           :target: http://gpy.readthedocs.org/en/devel/
        .. |PyPI version| image:: https://badge.fury.io/py/GPy.svg
           :target: https://pypi.python.org/pypi/GPy
        .. |source| image:: https://img.shields.io/badge/download-source-green.svg
           :target: https://pypi.python.org/pypi/GPy
        .. |Windows| image:: https://img.shields.io/badge/download-windows-orange.svg
           :target: https://pypi.python.org/pypi/GPy
        .. |MacOSX| image:: https://img.shields.io/badge/download-macosx-blue.svg
           :target: https://pypi.python.org/pypi/GPy
        
Keywords: machine-learning gaussian-processes kernels
Platform: UNKNOWN
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
