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Update doc/thirdpartypackages/index.rst #8538

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223 changes: 93 additions & 130 deletions doc/thirdpartypackages/index.rst
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.. _thirdparty-index:

*********************
Third party packages
*********************

Several external packages that extend or build on Matplotlib functionality
exist. Below we list a number of these. Note that they are each
maintained and distributed separately from Matplotlib, and will need
to be installed individually.
********************
Third party packages
********************

Please submit an issue or pull request
on Github if you have created a package that you would like to have included.
We are also happy to host third party packages within the `Matplotlib Github
Organization <https://github.com/matplotlib>`_.
Several external packages that extend or build on Matplotlib functionality are
listed below. They are maintained and distributed separately from Matplotlib
and thus need to be installed individually.

.. _hl_plotting:
Please submit an issue or pull request on Github if you have created
a package that you would like to have included. We are also happy to
host third party packages within the `Matplotlib Github Organization
<https://github.com/matplotlib>`_.

High-Level Plotting
*******************
Mapping toolkits
****************

Several projects provide higher-level interfaces for creating
matplotlib plots.
Basemap
=======
`Basemap <http://matplotlib.org/basemap>`_ plots data on map projections, with
continental and political boundaries.

.. _toolkit_seaborn:
.. image:: /_static/basemap_contour1.png
:height: 400px

seaborn
Cartopy
=======
`Cartopy <http://scitools.org.uk/cartopy/docs/latest>`_ builds on top
of Matplotlib to provide object oriented map projection definitions
and close integration with Shapely for powerful yet easy-to-use vector
data processing tools. An example plot from the `Cartopy gallery
<http://scitools.org.uk/cartopy/docs/latest/gallery.html>`_:

`seaborn <http://seaborn.pydata.org/>`_ is a high level interface for drawing
statistical graphics with matplotlib. It aims to make visualization a central
part of exploring and understanding complex datasets.

.. image:: /_static/seaborn.png
:height: 157px
.. image:: /_static/cartopy_hurricane_katrina_01_00.png
:height: 400px

.. _toolkit_ggplot:
Declarative libraries
*********************

ggplot
======

`ggplot <https://github.com/yhat/ggplot>`_ is a port of the R ggplot2 package
to python based on matplotlib.
to python based on Matplotlib.

.. image:: /_static/ggplot.png
:height: 195px

.. _toolkit_holoviews:

holoviews
=========

`holoviews <http://holoviews.org>`_ makes it easier to visualize data
interactively, especially in a `Jupyter notebook
<http://jupyter.org>`_, by providing a set of declarative
plotting objects that store your data and associated metadata. Your
data is then immediately visualizable alongside or overlaid with other
data, either statically or with automatically provided widgets for
parameter exploration.
interactively, especially in a `Jupyter notebook <http://jupyter.org>`_, by
providing a set of declarative plotting objects that store your data and
associated metadata. Your data is then immediately visualizable alongside or
overlaid with other data, either statically or with automatically provided
widgets for parameter exploration.

.. image:: /_static/holoviews.png
:height: 354px

Specialty plots
***************

.. _toolkits-mapping:
Matplotlib-Venn
===============
`Matplotlib-Venn <https://github.com/konstantint/matplotlib-venn>`_ provides a
set of functions for plotting 2- and 3-set area-weighted (or unweighted) Venn
diagrams.

Mapping Toolkits
****************
mpl-probscale
=============
`mpl-probscale <http://matplotlib.org/mpl-probscale/>`_ is a small extension
that allows Matplotlib users to specify probabilty scales. Simply importing the
``probscale`` module registers the scale with Matplotlib, making it accessible
via e.g., ``ax.set_xscale('prob')`` or ``plt.yscale('prob')``.

Two independent mapping toolkits are available.
.. image:: /_static/probscale_demo.png

.. _toolkit_basemap:
mplstereonet
============
`mplstereonet <https://github.com/joferkington/mplstereonet>`_ provides
stereonets for plotting and analyzing orientation data in Matplotlib.

Basemap
Natgrid
=======
`mpl_toolkits.natgrid <https://github.com/matplotlib/natgrid>`_ is an interface
to the natgrid C library for gridding irregularly spaced data.

Plots data on map projections, with continental and political
boundaries. See `basemap <http://matplotlib.org/basemap>`_
docs.

.. image:: /_static/basemap_contour1.png
:height: 400px



Cartopy
pyUpSet
=======
`Cartopy <http://scitools.org.uk/cartopy/docs/latest>`_ builds on top of
matplotlib to provide object oriented map projection definitions and close
integration with Shapely for powerful yet easy-to-use vector data processing
tools. An example plot from the
`Cartopy gallery <http://scitools.org.uk/cartopy/docs/latest/gallery.html>`_:
`pyUpSet <https://github.com/ImSoErgodic/py-upset>`_ is a
static Python implementation of the `UpSet suite by Lex et al.
<http://www.caleydo.org/tools/upset/>`_ to explore complex intersections of
sets and data frames.

.. image:: /_static/cartopy_hurricane_katrina_01_00.png
:height: 400px
seaborn
=======
`seaborn <http://seaborn.pydata.org/>`_ is a high level interface for drawing
statistical graphics with Matplotlib. It aims to make visualization a central
part of exploring and understanding complex datasets.

.. image:: /_static/seaborn.png
:height: 157px

.. _toolkits-misc:
.. _toolkits-general:
Windrose
========
`Windrose <https://github.com/scls19fr/windrose>`_ is a Python Matplotlib,
Numpy library to manage wind data, draw windroses (also known as polar rose
plots), draw probability density functions and fit Weibull distributions.

Miscellaneous Toolkits
**********************
Interactivity
*************

.. _toolkit_probscale:
mplcursors
==========
`mplcursors <https://mplcursors.readthedocs.io>`_ provides interactive data
cursors for Matplotlib.

mpl-probscale
MplDataCursor
=============
`mpl-probscale <http://matplotlib.org/mpl-probscale/>`_
is a small extension that allows matplotlib users to specify probabilty
scales. Simply importing the ``probscale`` module registers the scale
with matplotlib, making it accessible via e.g.,
``ax.set_xscale('prob')`` or ``plt.yscale('prob')``.
`MplDataCursor <https://github.com/joferkington/mpldatacursor>`_ is a toolkit
written by Joe Kington to provide interactive "data cursors" (clickable
annotation boxes) for Matplotlib.

.. image:: /_static/probscale_demo.png
Miscellaneous
*************

adjustText
==========
`adjustText <https://github.com/Phlya/adjustText>`_ is a small library for
automatically adjusting text position in Matplotlib plots to minimize overlaps
between them, specified points and other objects.

.. image:: /_static/adjustText.png

iTerm2 terminal backend
=======================

`matplotlib_iterm2 <https://github.com/oselivanov/matplotlib_iterm2>`_ is an
external matplotlib backend using iTerm2 nightly build inline image display
external Matplotlib backend using the iTerm2 nightly build inline image display
feature.

.. image:: /_static/matplotlib_iterm2_demo.png


.. _toolkit_mpldatacursor:

MplDataCursor
=============

`MplDataCursor <https://github.com/joferkington/mpldatacursor>`_ is a
toolkit written by Joe Kington to provide interactive "data cursors"
(clickable annotation boxes) for matplotlib.


.. _toolkit_mplcursors:

mplcursors
==========

`mplcursors <https://mplcursors.readthedocs.io>`_ provides interactive
data cursors for matplotlib.


.. _toolkit_natgrid:

Natgrid
=======

mpl_toolkits.natgrid is an interface to natgrid C library for gridding
irregularly spaced data. This requires a separate installation of the
`natgrid toolkit <https://github.com/matplotlib/natgrid>`__.


.. _toolkit_matplotlibvenn:

Matplotlib-Venn
===============

`Matplotlib-Venn <https://github.com/konstantint/matplotlib-venn>`_ provides a set of functions for plotting 2- and 3-set area-weighted (or unweighted) Venn diagrams.

mplstereonet
===============

`mplstereonet <https://github.com/joferkington/mplstereonet>`_ provides stereonets for plotting and analyzing orientation data in Matplotlib.

pyupset
===============
`pyUpSet <https://github.com/ImSoErgodic/py-upset>`_ is a static Python implementation of the `UpSet suite by Lex et al. <http://www.caleydo.org/tools/upset/>`_ to explore complex intersections of sets and data frames.

Windrose
===============
`Windrose <https://github.com/scls19fr/windrose>`_ is a Python Matplotlib, Numpy library to manage wind data, draw windrose (also known as a polar rose plot), draw probability density function and fit Weibull distribution

adjustText
===============
`adjustText <https://github.com/Phlya/adjustText>`_ is a small library for automatically adjusting text position in matplotlib plots to minimize overlaps between them, specified points and other objects.

.. image:: /_static/adjustText.png
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