tacaswell · Aug 28, 2021 · Aug 28, 2021 · Jun 25, 2021 · Jun 25, 2021 · Jun 30, 2021
diff --git a/doc/thirdpartypackages/index.rst b/doc/thirdpartypackages/index.rst
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-.. note:: 
+.. raw:: html
 
-    This page has been moved to <https://matplotlib.org/mpl-third-party/>, 
-    where you will find an up-to-date list of packages.  
-
-
-********************
-Third party packages
-********************
-
-Several external packages that extend or build on Matplotlib functionality are
-listed below. You can find more packages at `PyPI <https://pypi.org/search/?q=&o=&c=Framework+%3A%3A+Matplotlib>`_. 
-They are maintained and distributed separately from Matplotlib, 
-and thus need to be installed individually. 
-
-If you have a created a package that extends or builds on Matplotlib 
-and would like to have your package listed on this page, please submit 
-an issue or pull request on GitHub. The pull request should include a short 
-description of the library and an image demonstrating the functionality. 
-To be included in the PyPI listing, please include ``Framework :: Matplotlib`` 
-in the classifier list in the ``setup.py`` file for your package. We are also 
-happy to host third party packages within the `Matplotlib GitHub Organization
-<https://github.com/matplotlib>`_.
-
-
-Mapping toolkits
-****************
-
-Basemap
-=======
-`Basemap <https://matplotlib.org/basemap/>`_ plots data on map projections,
-with continental and political boundaries.
-
-.. image:: /_static/basemap_contour1.png
-    :height: 400px
-
-Cartopy
-=======
-`Cartopy <https://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
-<https://scitools.org.uk/cartopy/docs/latest/gallery/index.html>`_:
-
-.. image:: /_static/cartopy_hurricane_katrina_01_00.png
-    :height: 400px
-
-Geoplot
-=======
-`Geoplot <https://residentmario.github.io/geoplot/index.html>`_ builds on top
-of Matplotlib and Cartopy to provide a "standard library" of simple, powerful,
-and customizable plot types. An example plot from the `Geoplot gallery
-<https://residentmario.github.io/geoplot/index.html>`_:
-
-.. image:: /_static/geoplot_nyc_traffic_tickets.png
-    :height: 400px
-
-Ridge Map
-=========
-`ridge_map <https://github.com/ColCarroll/ridge_map>`_ uses Matplotlib,
-SRTM.py, NumPy, and scikit-image to make ridge plots of your favorite
-ridges.
-
-.. image:: /_static/ridge_map_white_mountains.png
-    :height: 364px
-
-Declarative libraries
-*********************
-
-ggplot
-======
-`ggplot <https://github.com/yhat/ggplot>`_ is a port of the R ggplot2 package
-to python based on Matplotlib.
-
-.. image:: /_static/ggplot.png
-    :height: 195px
-
-holoviews
-=========
-`holoviews <http://holoviews.org>`_ makes it easier to visualize data
-interactively, especially in a `Jupyter notebook <https://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
-
-plotnine
-========
-
-`plotnine <https://plotnine.readthedocs.io/en/stable/>`_ implements a grammar
-of graphics, similar to R's `ggplot2 <https://ggplot2.tidyverse.org/>`_.
-The grammar allows users to compose plots by explicitly mapping data to the
-visual objects that make up the plot.
-
-.. image:: /_static/plotnine.png
-
-Specialty plots
-***************
-
-Broken Axes
-===========
-`brokenaxes <https://github.com/bendichter/brokenaxes>`_ supplies an axes
-class that can have a visual break to indicate a discontinuous range.
-
-.. image:: /_static/brokenaxes.png
-
-DeCiDa
-======
-
-`DeCiDa <https://pypi.org/project/DeCiDa/>`_ is a library of functions
-and classes for electron device characterization, electronic circuit design and
-general data visualization and analysis.
-
-matplotlib-scalebar
-===================
-
-`matplotlib-scalebar <https://github.com/ppinard/matplotlib-scalebar>`_ provides a new artist to display a scale bar, aka micron bar.
-It is particularly useful when displaying calibrated images plotted using ``plt.imshow(...)``.
-
-.. image:: /_static/gold_on_carbon.jpg
-
-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.
-
-mpl-probscale
-=============
-`mpl-probscale <https://matplotlib.org/mpl-probscale/>`_ is a small extension
-that allows Matplotlib users to specify probability 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')``.
-
-.. image:: /_static/probscale_demo.png
-
-mpl-scatter-density
-===================
-
-`mpl-scatter-density <https://github.com/astrofrog/mpl-scatter-density>`_ is a
-small package that makes it easy to make scatter plots of large numbers
-of points using a density map. The following example contains around 13 million
-points and the plotting (excluding reading in the data) took less than a
-second on an average laptop:
-
-.. image:: /_static/mpl-scatter-density.png
-    :height: 400px
-
-When used in interactive mode, the density map is downsampled on-the-fly while
-panning/zooming in order to provide a smooth interactive experience.
-
-mplstereonet
-============
-`mplstereonet <https://github.com/joferkington/mplstereonet>`_ provides
-stereonets for plotting and analyzing orientation data in Matplotlib.
-
-Natgrid
-=======
-`mpl_toolkits.natgrid <https://github.com/matplotlib/natgrid>`_ is an interface
-to the natgrid C library for gridding irregularly spaced data.
-
-pyUpSet
-=======
-`pyUpSet <https://github.com/ImSoErgodic/py-upset>`_ is a
-static Python implementation of the `UpSet suite by Lex et al.
-<http://caleydo.org/tools/upset/>`_ to explore complex intersections of
-sets and data frames.
-
-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
-
-WCSAxes
-=======
-
-The `Astropy <https://www.astropy.org/>`_ core package includes a submodule
-called WCSAxes (available at `astropy.visualization.wcsaxes
-<http://docs.astropy.org/en/stable/visualization/wcsaxes/index.html>`_) which
-adds Matplotlib projections for Astronomical image data. The following is an
-example of a plot made with WCSAxes which includes the original coordinate
-system of the image and an overlay of a different coordinate system:
-
-.. image:: /_static/wcsaxes.jpg
-    :height: 400px
-
-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.
-
-Yellowbrick
-===========
-`Yellowbrick <https://www.scikit-yb.org/>`_ is a suite of visual diagnostic tools for machine learning that enables human steering of the model selection process. Yellowbrick combines scikit-learn with matplotlib using an estimator-based API called the ``Visualizer``, which wraps both sklearn models and matplotlib Axes. ``Visualizer`` objects fit neatly into the machine learning workflow allowing data scientists to integrate visual diagnostic and model interpretation tools into experimentation without extra steps.
-
-.. image:: /_static/yellowbrick.png
-    :height: 400px
-
-Animations
-**********
-
-animatplot
-==========
-`animatplot <https://animatplot.readthedocs.io/>`_ is a library for
-producing interactive animated plots with the goal of making production of
-animated plots almost as easy as static ones.
-
-.. image:: /_static/animatplot.png
-
-For an animated version of the above picture and more examples, see the
-`animatplot gallery. <https://animatplot.readthedocs.io/en/stable/gallery.html>`_
-
-gif
-===
-`gif <https://github.com/maxhumber/gif/>`_ is an ultra lightweight animated gif API.
-
-.. image:: /_static/gif_attachment_example.png
-
-numpngw
-=======
-
-`numpngw <https://pypi.org/project/numpngw/>`_  provides functions for writing
-NumPy arrays to PNG and animated PNG files.  It also includes the class
-``AnimatedPNGWriter`` that can be used to save a Matplotlib animation as an
-animated PNG file.  See the example on the PyPI page or at the ``numpngw``
-`github repository <https://github.com/WarrenWeckesser/numpngw>`_.
-
-.. image:: /_static/numpngw_animated_example.png
-
-Interactivity
-*************
-
-mplcursors
-==========
-`mplcursors <https://mplcursors.readthedocs.io>`_ provides interactive data
-cursors for Matplotlib.
-
-MplDataCursor
-=============
-`MplDataCursor <https://github.com/joferkington/mpldatacursor>`_ is a toolkit
-written by Joe Kington to provide interactive "data cursors" (clickable
-annotation boxes) for Matplotlib.
-
-mpl_interactions
-================
-`mpl_interactions <https://mpl-interactions.readthedocs.io/en/latest/>`_
-makes it easy to create interactive plots controlled by sliders and other
-widgets. It also provides several handy capabilities such as manual
-image segmentation, comparing cross-sections of arrays, and using the
-scroll wheel to zoom.
-
-.. image:: /_static/mpl-interactions-slider-animated.png
-
-Rendering backends
-******************
-
-mplcairo
-========
-`mplcairo <https://github.com/anntzer/mplcairo>`_ is a cairo backend for
-Matplotlib, with faster and more accurate marker drawing, support for a wider
-selection of font formats and complex text layout, and various other features.
-
-gr
-==
-`gr <https://gr-framework.org/>`_ is a framework for cross-platform
-visualisation applications, which can be used as a high-performance Matplotlib
-backend.
-
-GUI integration
-***************
-
-wxmplot
-=======
-`WXMPlot <https://pypi.org/project/wxmplot/>`_ provides advanced wxPython
-widgets for plotting and image display of numerical data based on Matplotlib.
-
-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 the iTerm2 nightly build inline image display
-feature.
-
-.. image:: /_static/matplotlib_iterm2_demo.png
-
-mpl-template
-============
-`mpl-template <https://austinorr.github.io/mpl-template/index.html>`_ provides
-a customizable way to add engineering figure elements such as a title block,
-border, and logo.
-
-.. image:: /_static/mpl_template_example.png
-    :height: 330px
-
-figpager
-========
-`figpager <https://pypi.org/project/figpager/>`_ provides customizable figure
-elements such as text, lines and images and subplot layout control for single
-or multi page output.
-
- .. image:: /_static/figpager.png
-
-blume
-=====
-
-`blume <https://pypi.org/project/blume/>`_ provides a replacement for
-the Matplotlib ``table`` module.  It fixes a number of issues with the
-existing table. See the `blume github repository
-<https://github.com/swfiua/blume>`_ for more details.
-
-.. image:: /_static/blume_table_example.png
-
-highlight-text
-==============
-
-`highlight-text <https://pypi.org/project/highlight-text/>`_ is a small library
-that provides an easy way to effectively annotate plots by highlighting
-substrings with the font properties of your choice.
-See the `highlight-text github repository
-<https://github.com/znstrider/highlight_text>`_ for more details and examples.
-
-.. image:: /_static/highlight_text_examples.png
-
-DNA Features Viewer
-===================
-
-`DNA Features Viewer <https://github.com/Edinburgh-Genome-Foundry/DnaFeaturesViewer>`_
-provides methods to plot annotated DNA sequence maps (possibly along other Matplotlib
-plots) for Bioinformatics and Synthetic Biology applications.
-
-.. image:: /_static/dna_features_viewer_screenshot.png
-
-GUI applications
-****************
-
-sviewgui
-========
-
-`sviewgui <https://pypi.org/project/sviewgui/>`_ is a PyQt-based GUI for
-visualisation of data from csv files or `pandas.DataFrame`\s. Main features:
-
-- Scatter, line, density, histogram, and box plot types
-- Settings for the marker size, line width, number of bins of histogram,
-  colormap (from cmocean)
-- Save figure as editable PDF
-- Code of the plotted graph is available so that it can be reused and modified
-  outside of sviewgui
-
-.. image:: /_static/sviewgui_sample.png
+  <meta http-equiv="refresh" content="0; url=https://matplotlib.org/mpl-third-party/">