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Commit 45d005a

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timhoffmtimhoffm
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Fix some link redirects in docs
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‎INSTALL.rst

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Matplotlib requires the following dependencies:
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* `Python <https://www.python.org/downloads/>`_ (>= 3.6)
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* `NumPy <http://www.numpy.org>`_ (>= 1.15)
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* `NumPy <https://numpy.org>`_ (>= 1.15)
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* `setuptools <https://setuptools.readthedocs.io/en/latest/>`_
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* `cycler <http://matplotlib.org/cycler/>`_ (>= 0.10.0)
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* `cycler <https://matplotlib.org/cycler/>`_ (>= 0.10.0)
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* `dateutil <https://pypi.org/project/python-dateutil>`_ (>= 2.1)
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* `kiwisolver <https://github.com/nucleic/kiwi>`_ (>= 1.0.0)
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* `Pillow <https://pillow.readthedocs.io/en/latest/>`_ (>= 6.2)

‎README.rst

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.. _Downloads: https://pepy.tech/project/matplotlib/month
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.. |NUMFocus| image:: https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A
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.. _NUMFocus: https://www.numfocus.org
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.. _NUMFocus: https://numfocus.org
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.. image:: https://matplotlib.org/_static/logo2.svg
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‎doc/api/toolkits/mplot3d/faq.rst

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mplot3d FAQ
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***********
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How is mplot3d different from MayaVi?
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How is mplot3d different from Mayavi?
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=====================================
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`MayaVi2 <http://code.enthought.com/projects/mayavi/documentation.php>`_
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`Mayavi <https://docs.enthought.com/mayavi/mayavi/>`_
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is a very powerful and featureful 3D graphing library. For advanced
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3D scenes and excellent rendering capabilities, it is highly recommended to
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use MayaVi2.
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use Mayavi.
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mplot3d was intended to allow users to create simple 3D graphs with the same
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"look-and-feel" as matplotlib's 2D plots. Furthermore, users can use the same
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This problem will likely not be solved until OpenGL support is added to all of
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the backends (patches are greatly welcomed). Until then, if you need complex
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3D scenes, we recommend using
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`MayaVi <http://code.enthought.com/projects/mayavi/documentation.php>`_.
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`MayaVi <https://docs.enthought.com/mayavi/mayavi/>`_.
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I don't like how the 3D plot is laid out, how do I change that?

‎doc/devel/MEP/MEP11.rst

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For installing from source, and assuming the user has all of the
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C-level compilers and dependencies, this can be accomplished fairly
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easily using distribute_ and following the instructions `here
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<https://pypi.python.org/pypi/distribute>`_. The only anticipated
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<https://pypi.org/project/distribute>`_. The only anticipated
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change to the matplotlib library code will be to import pyparsing_
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from the top-level namespace rather than from within matplotlib. Note
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that distribute_ will also allow us to remove the direct dependency

‎doc/devel/MEP/MEP12.rst

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* PEP8_ clean-ups (running `flake8
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<https://pypi.python.org/pypi/flake8>`_, or a similar checker, is
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<https://pypi.org/project/flake8>`_, or a similar checker, is
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highly recommended)
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* Commented-out code should be removed.
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* Replace uses of `pylab` interface with `.pyplot` (+ `numpy`,
@@ -141,8 +141,8 @@ page instead of the gallery examples.
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references to that example. For example, the API documentation for
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:file:`axes.py` and :file:`pyplot.py` may use these examples to generate
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plots. Use your favorite search tool (e.g., grep, ack, `grin
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<https://pypi.python.org/pypi/grin>`_, `pss
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<https://pypi.python.org/pypi/pss>`_) to search the matplotlib
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<https://pypi.org/project/grin>`_, `pss
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<https://pypi.org/project/pss>`_) to search the matplotlib
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package. See `2dc9a46
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<https://github.com/tonysyu/matplotlib/commit/2dc9a4651e5e566afc0866c603aa8d06aaf32b71>`_
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and `aa6b410

‎doc/devel/release_guide.rst

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In addition, announcements should be made on social networks (twitter
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via the ``@matplotlib`` account, any other via personal accounts).
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`NumFOCUS <https://www.numfocus.org/>`__ should be contacted for
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`NumFOCUS <https://numfocus.org/>`__ should be contacted for
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inclusion in their newsletter.

‎doc/index.rst

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.. raw:: html
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<a href="https://www.numfocus.org/">
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<a href="https://numfocus.org/">
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<img src="_static/numfocus_badge.png"
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alt="A Fiscally Sponsored Project of NUMFocus"
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style="float:right; margin-left:20px" />
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<jdh-fellowship_>`_.
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.. _donating: https://numfocus.org/donate-to-matplotlib
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.. _jdh-fellowship: https://www.numfocus.org/programs/john-hunter-technology-fellowship/
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.. _jdh-fellowship: https://numfocus.org/programs/john-hunter-technology-fellowship/
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.. _nf: https://numfocus.org
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The :doc:`Matplotlib license <users/license>` is based on the `Python Software

‎doc/thirdpartypackages/index.rst

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Basemap
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=======
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`Basemap <http://matplotlib.org/basemap>`_ plots data on map projections, with
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continental and political boundaries.
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`Basemap <https://matplotlib.org/basemap/>`_ plots data on map projections,
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with continental and political boundaries.
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.. image:: /_static/basemap_contour1.png
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:height: 400px
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Cartopy
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=======
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`Cartopy <http://scitools.org.uk/cartopy/docs/latest>`_ builds on top
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`Cartopy <https://scitools.org.uk/cartopy/docs/latest>`_ builds on top
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of Matplotlib to provide object oriented map projection definitions
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and close integration with Shapely for powerful yet easy-to-use vector
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data processing tools. An example plot from the `Cartopy gallery
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<http://scitools.org.uk/cartopy/docs/latest/gallery.html>`_:
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<https://scitools.org.uk/cartopy/docs/latest/gallery.html>`_:
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.. image:: /_static/cartopy_hurricane_katrina_01_00.png
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:height: 400px
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holoviews
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=========
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`holoviews <http://holoviews.org>`_ makes it easier to visualize data
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interactively, especially in a `Jupyter notebook <http://jupyter.org>`_, by
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interactively, especially in a `Jupyter notebook <https://jupyter.org>`_, by
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providing a set of declarative plotting objects that store your data and
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associated metadata. Your data is then immediately visualizable alongside or
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overlaid with other data, either statically or with automatically provided
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mpl-probscale
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=============
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`mpl-probscale <http://matplotlib.org/mpl-probscale/>`_ is a small extension
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`mpl-probscale <https://matplotlib.org/mpl-probscale/>`_ is a small extension
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that allows Matplotlib users to specify probabilty scales. Simply importing the
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``probscale`` module registers the scale with Matplotlib, making it accessible
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via e.g., ``ax.set_xscale('prob')`` or ``plt.yscale('prob')``.

‎doc/users/history.rst

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the MATLAB graphics commands, it is
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independent of MATLAB, and can be used in a Pythonic, object oriented
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way. Although Matplotlib is written primarily in pure Python, it
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makes heavy use of `NumPy <http://www.numpy.org>`_ and other extension
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makes heavy use of `NumPy <https://numpy.org>`_ and other extension
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code to provide good performance even for large arrays.
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Matplotlib is designed with the philosophy that you should be able to

‎doc/users/prev_whats_new/whats_new_1.0.rst

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The matplotlib trunk is probably in as good a shape as it has ever
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been, thanks to improved `software carpentry
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<http://software-carpentry.org/>`__. We now have a `buildbot
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<https://software-carpentry.org/>`__. We now have a `buildbot
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<https://buildbot.net>`__ which runs a suite of `nose
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<http://code.google.com/p/python-nose/>`__ regression tests on every
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svn commit, auto-generating a set of images and comparing them against

‎doc/users/prev_whats_new/whats_new_1.3.rst

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``````````````````````````````
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To give your plots a sense of authority that they may be missing,
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Michael Droettboom (inspired by the work of many others in
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:ghpull:`1329`) has added an `xkcd-style <http://xkcd.com/>`__ sketch
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:ghpull:`1329`) has added an `xkcd-style <https://xkcd.com/>`__ sketch
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plotting mode. To use it, simply call `matplotlib.pyplot.xkcd`
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before creating your plot. For really fine control, it is also possible
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to modify each artist's sketch parameters individually with

‎doc/users/prev_whats_new/whats_new_1.4.rst

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to the IPython notebook server for their interactivity, once the notebook is
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saved, each figure will be rendered as a static image - thus allowing
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non-interactive viewing of figures on services such as
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`nbviewer <http://nbviewer.ipython.org/>`__.
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`nbviewer <https://nbviewer.ipython.org/>`__.
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‎doc/users/prev_whats_new/whats_new_1.5.rst

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The wx backend can now be used with both wxPython classic and
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`Phoenix <http://wxpython.org/Phoenix/docs/html/main.html>`__.
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`Phoenix <https://wxpython.org/Phoenix/docs/html/main.html>`__.
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wxPython classic has to be at least version 2.8.12 and works on Python 2.x. As
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of May 2015 no official release of wxPython Phoenix is available but a

‎doc/users/prev_whats_new/whats_new_2.2.rst

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Thus, to force usage of PGI when both bindings are installed, import it first.
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.. _PGI: https://pgi.readthedocs.io/en/latest/
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.. _PyGObject: http://pygobject.readthedocs.io/en/latest/#
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.. _PyGObject: https://pygobject.readthedocs.io/en/latest/
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‎examples/misc/image_thumbnail_sgskip.py

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Matplotlib relies on Pillow_ for reading images, and thus supports all formats
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.. _Pillow: http://python-pillow.org/
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.. _Pillow: https://python-pillow.org/
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"""
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from argparse import ArgumentParser

‎examples/showcase/anatomy.py

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connectionstyle="arc3",
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ax.text(4.0, -0.4, "Made with http://matplotlib.org",
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ax.text(4.0, -0.4, "Made with https://matplotlib.org",
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fontsize=10, ha="right", color='.5')
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plt.show()

‎examples/showcase/mandelbrot.py

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# Some advertisement for matplotlib
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year = time.strftime("%Y")
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text = ("The Mandelbrot fractal set\n"
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"Rendered with matplotlib %s, %s - http://matplotlib.org"
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"Rendered with matplotlib %s, %s - https://matplotlib.org"
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% (matplotlib.__version__, year))
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ax.text(xmin+.025, ymin+.025, text, color="white", fontsize=12, alpha=0.5)
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‎examples/statistics/boxplot_vs_violin.py

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Violin plots require matplotlib >= 1.4.
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For more information on violin plots, the scikit-learn docs have a great
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section: http://scikit-learn.org/stable/modules/density.html
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section: https://scikit-learn.org/stable/modules/density.html
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"""
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import matplotlib.pyplot as plt

‎examples/statistics/customized_violin.py

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of the violins are modified.
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For more information on violin plots, the scikit-learn docs have a great
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section: https://scikit-learn.org/stable/modules/density.html
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"""
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import matplotlib.pyplot as plt

‎examples/statistics/violinplot.py

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and how to modify the band-width of the KDE (``bw_method``).
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For more information on violin plots and KDE, the scikit-learn docs
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have a great section: http://scikit-learn.org/stable/modules/density.html
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have a great section: https://scikit-learn.org/stable/modules/density.html
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"""
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import numpy as np

‎lib/matplotlib/__init__.py

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def _get_xdg_config_dir():
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"""
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Return the XDG configuration directory, according to the `XDG
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base directory spec
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<http://standards.freedesktop.org/basedir-spec/basedir-spec-latest.html>`_.
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Return the XDG configuration directory, according to the XDG base
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directory spec:
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https://standards.freedesktop.org/basedir-spec/basedir-spec-latest.html
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"""
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return os.environ.get('XDG_CONFIG_HOME') or str(Path.home() / ".config")
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def _get_xdg_cache_dir():
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"""
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Return the XDG cache directory, according to the `XDG
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base directory spec
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<http://standards.freedesktop.org/basedir-spec/basedir-spec-latest.html>`_.
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Return the XDG cache directory, according to the XDG base directory spec:
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https://standards.freedesktop.org/basedir-spec/basedir-spec-latest.html
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"""
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return os.environ.get('XDG_CACHE_HOME') or str(Path.home() / ".cache")
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‎lib/matplotlib/axes/_axes.py

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-----
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.. seealso::
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The MATLAB function
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`stem <http://www.mathworks.com/help/techdoc/ref/stem.html>`_
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`stem <https://www.mathworks.com/help/matlab/ref/stem.html>`_
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which inspired this method.
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"""
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if not 1 <= len(args) <= 5:

‎lib/matplotlib/image.py

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thus supports a wide range of file formats, including PNG, JPG, TIFF
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.. _Pillow: http://python-pillow.org/
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.. _Pillow: https://python-pillow.org/
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thumbfile : str or file-like
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The thumbnail filename.

‎lib/matplotlib/legend.py

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"Legend does not support {!r} instances.\nA proxy artist "
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"may be used instead.\nSee: "
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"http://matplotlib.org/users/legend_guide.html"
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"https://matplotlib.org/users/legend_guide.html"
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"#creating-artists-specifically-for-adding-to-the-legend-"
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"aka-proxy-artists".format(orig_handle))
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# We don't have a handle for this artist, so we just defer

‎lib/matplotlib/patches.py

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Lancaster, Don. *Approximating a Circle or an Ellipse Using
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Four Bezier Cubic Splines.*
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http://www.tinaja.com/glib/ellipse4.pdf
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https://www.tinaja.com/glib/ellipse4.pdf
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There is a use case where very large ellipses must be drawn
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with very high accuracy, and it is too expensive to render the

‎lib/matplotlib/path.py

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The circle is approximated using 8 cubic Bezier curves, as described in
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Lancaster, Don. `Approximating a Circle or an Ellipse Using Four
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Bezier Cubic Splines <http://www.tinaja.com/glib/ellipse4.pdf>`_.
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Bezier Cubic Splines <https://www.tinaja.com/glib/ellipse4.pdf>`_.
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"""
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MAGIC = 0.2652031
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SQRTHALF = np.sqrt(0.5)

‎lib/matplotlib/projections/geo.py

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# from Equations (7, 8) of
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# http://mathworld.wolfram.com/MollweideProjection.html
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# https://mathworld.wolfram.com/MollweideProjection.html
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theta = np.arcsin(y / np.sqrt(2))
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longitude = (np.pi / (2 * np.sqrt(2))) * x / np.cos(theta)
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latitude = np.arcsin((2 * theta + np.sin(2 * theta)) / np.pi)

‎lib/matplotlib/pyplot.py

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========= ===================================================
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The following colormaps are based on the `ColorBrewer
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<http://colorbrewer2.org>`_ color specifications and designs developed by
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<https://colorbrewer2.org>`_ color specifications and designs developed by
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Cynthia Brewer:
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ColorBrewer Diverging (luminance is highest at the midpoint, and
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.. [#] Rainbow colormaps, ``jet`` in particular, are considered a poor
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choice for scientific visualization by many researchers: `Rainbow Color
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Map (Still) Considered Harmful
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<http://ieeexplore.ieee.org/document/4118486/?arnumber=4118486>`_
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<https://ieeexplore.ieee.org/document/4118486/?arnumber=4118486>`_
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.. [#] Resembles "BkBlAqGrYeOrReViWh200" from NCAR Command
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Language. See `Color Table Gallery

‎tutorials/intermediate/color_cycle.py

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.. note::
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More complete documentation of the ``cycler`` API can be found
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`here <http://matplotlib.org/cycler/>`_.
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`here <https://matplotlib.org/cycler/>`_.
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This example demonstrates two different APIs:
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