diff --git a/doc/thirdpartypackages/index.rst b/doc/thirdpartypackages/index.rst index e6c6aa401526..81dc4d710a52 100644 --- a/doc/thirdpartypackages/index.rst +++ b/doc/thirdpartypackages/index.rst @@ -1,369 +1,5 @@ :orphan: -.. note:: +.. raw:: html - This page has been moved to , - 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 `_. -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 -`_. - - -Mapping toolkits -**************** - -Basemap -======= -`Basemap `_ plots data on map projections, -with continental and political boundaries. - -.. image:: /_static/basemap_contour1.png - :height: 400px - -Cartopy -======= -`Cartopy `_ 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 -`_: - -.. image:: /_static/cartopy_hurricane_katrina_01_00.png - :height: 400px - -Geoplot -======= -`Geoplot `_ 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 -`_: - -.. image:: /_static/geoplot_nyc_traffic_tickets.png - :height: 400px - -Ridge Map -========= -`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 `_ is a port of the R ggplot2 package -to python based on Matplotlib. - -.. image:: /_static/ggplot.png - :height: 195px - -holoviews -========= -`holoviews `_ makes it easier to visualize data -interactively, especially in a `Jupyter notebook `_, 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 `_ implements a grammar -of graphics, similar to R's `ggplot2 `_. -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 `_ supplies an axes -class that can have a visual break to indicate a discontinuous range. - -.. image:: /_static/brokenaxes.png - -DeCiDa -====== - -`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 `_ 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 `_ provides a -set of functions for plotting 2- and 3-set area-weighted (or unweighted) Venn -diagrams. - -mpl-probscale -============= -`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 `_ 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 `_ provides -stereonets for plotting and analyzing orientation data in Matplotlib. - -Natgrid -======= -`mpl_toolkits.natgrid `_ is an interface -to the natgrid C library for gridding irregularly spaced data. - -pyUpSet -======= -`pyUpSet `_ is a -static Python implementation of the `UpSet suite by Lex et al. -`_ to explore complex intersections of -sets and data frames. - -seaborn -======= -`seaborn `_ 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 `_ core package includes a submodule -called WCSAxes (available at `astropy.visualization.wcsaxes -`_) 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 `_ 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 `_ 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 `_ 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. `_ - -gif -=== -`gif `_ is an ultra lightweight animated gif API. - -.. image:: /_static/gif_attachment_example.png - -numpngw -======= - -`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 `_. - -.. image:: /_static/numpngw_animated_example.png - -Interactivity -************* - -mplcursors -========== -`mplcursors `_ provides interactive data -cursors for Matplotlib. - -MplDataCursor -============= -`MplDataCursor `_ is a toolkit -written by Joe Kington to provide interactive "data cursors" (clickable -annotation boxes) for Matplotlib. - -mpl_interactions -================ -`mpl_interactions `_ -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 `_ 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 `_ is a framework for cross-platform -visualisation applications, which can be used as a high-performance Matplotlib -backend. - -GUI integration -*************** - -wxmplot -======= -`WXMPlot `_ provides advanced wxPython -widgets for plotting and image display of numerical data based on Matplotlib. - -Miscellaneous -************* - -adjustText -========== -`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 `_ is an -external Matplotlib backend using the iTerm2 nightly build inline image display -feature. - -.. image:: /_static/matplotlib_iterm2_demo.png - -mpl-template -============ -`mpl-template `_ 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 `_ 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 `_ provides a replacement for -the Matplotlib ``table`` module. It fixes a number of issues with the -existing table. See the `blume github repository -`_ for more details. - -.. image:: /_static/blume_table_example.png - -highlight-text -============== - -`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 -`_ for more details and examples. - -.. image:: /_static/highlight_text_examples.png - -DNA Features Viewer -=================== - -`DNA Features Viewer `_ -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 `_ 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 + pFad - Phonifier reborn

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