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bobturneruk committed Mar 31, 2020
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6 changes: 6 additions & 0 deletions .gitignore
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# pycharm IDE stuff
.idea/

# docs
GPy*.rst

# vscode
settings.json
24 changes: 24 additions & 0 deletions .readthedocs.yml
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# .readthedocs.yml
# Read the Docs configuration file
# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details

# Required
version: 2

# Build documentation in the docs/ directory with Sphinx
sphinx:
configuration: doc/source/conf.py

# Build documentation with MkDocs
#mkdocs:
# configuration: mkdocs.yml

# Optionally build your docs in additional formats such as PDF and ePub
formats:
- htmlzip

# Optionally set the version of Python and requirements required to build your docs
python:
version: 3.7
install:
- requirements: doc/source/requirements.txt
2 changes: 1 addition & 1 deletion doc/source/conf.py
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Expand Up @@ -134,7 +134,7 @@ def __getattr__(cls, name):
project = u'GPy'
#author = u'`Humans <https://github.com/SheffieldML/GPy/graphs/contributors>`_'
author = 'GPy Authors, see https://github.com/SheffieldML/GPy/graphs/contributors'
copyright = u'2015, '+author
copyright = u'2020, '+author

# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
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48 changes: 27 additions & 21 deletions doc/source/index.rst
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.. GPy documentation master file, created by
sphinx-quickstart on Fri Sep 18 18:16:28 2015.
You can adapt this file completely to your liking, but it should at least
contain the root `toctree` directive.
GPy - A Gaussian Process (GP) framework in Python
=================================================

Welcome to GPy's documentation!
===============================
Introduction
------------

`GPy <http://sheffieldml.github.io/GPy/>`_ is a Gaussian Process (GP) framework written in Python, from the Sheffield machine learning group.
`GPy <http://sheffieldml.github.io/GPy/>`_ is a Gaussian Process (GP) framework written in Python, from the Sheffield machine learning group. It includes support for basic GP regression, multiple output GPs (using coregionalization), various noise models, sparse GPs, non-parametric regression and latent variables.

The `GPy homepage <http://sheffieldml.github.io/GPy/>`_ contains tutorials for users and further information on the project, including installation instructions.
This documentation is mostly aimed at developers interacting closely with the code-base.

The documentation hosted here is mostly aimed at developers interacting closely with the code-base.

Source Code
-----------

The code can be found on our `Github project page <https://github.com/SheffieldML/GPy>`_. It is open source and provided under the BSD license.

For developers:
Installation
------------

Installation instructions can currently be found on our `Github project page <https://github.com/SheffieldML/GPy>`_.

Tutorials
---------

- `Writing new models <tuto_creating_new_models.html>`_
- `Writing new kernels <tuto_creating_new_kernels.html>`_
- `Write a new plotting routine using gpy_plot <tuto_plotting.html>`_
- `Parameterization handles <tuto_parameterized.html>`_
Several tutorials have been developed in the form of `Jupyter Notebooks <https://nbviewer.jupyter.org/github/SheffieldML/notebook/blob/master/GPy/index.ipynb>`_.

Contents:
.. toctree::
:maxdepth: 1
:caption: For developers

tuto_creating_new_models
tuto_creating_new_kernels
tuto_plotting
tuto_parameterized

.. toctree::
:maxdepth: 1
:caption: API Documentation

GPy.models
GPy.kern
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GPy.inference.optimization
GPy.inference.latent_function_inference
GPy.inference.mcmc

Indices and tables
==================

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`

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