Fix some link redirects in docs

INSTALL.rst

@@ -108,9 +108,9 @@ Dependencies
 Matplotlib requires the following dependencies:
 
 * `Python <https://www.python.org/downloads/>`_ (>= 3.6)
-* `NumPy <http://www.numpy.org>`_ (>= 1.15)
+* `NumPy <https://numpy.org>`_ (>= 1.15)
 * `setuptools <https://setuptools.readthedocs.io/en/latest/>`_
-* `cycler <http://matplotlib.org/cycler/>`_ (>= 0.10.0)
+* `cycler <https://matplotlib.org/cycler/>`_ (>= 0.10.0)
 * `dateutil <https://pypi.org/project/python-dateutil>`_ (>= 2.1)
 * `kiwisolver <https://github.com/nucleic/kiwi>`_ (>= 1.0.0)
 * `Pillow <https://pillow.readthedocs.io/en/latest/>`_ (>= 6.2)

README.rst

@@ -38,7 +38,7 @@
 .. _Downloads: https://pepy.tech/project/matplotlib/month
 
 .. |NUMFocus| image:: https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A
-.. _NUMFocus: https://www.numfocus.org
+.. _NUMFocus: https://numfocus.org
 
 .. image:: https://matplotlib.org/_static/logo2.svg
 

doc/api/toolkits/mplot3d/faq.rst

@@ -4,12 +4,12 @@
 mplot3d FAQ
 ***********
 
-How is mplot3d different from MayaVi?
+How is mplot3d different from Mayavi?
 =====================================
-`MayaVi2 <http://code.enthought.com/projects/mayavi/documentation.php>`_
+`Mayavi <https://docs.enthought.com/mayavi/mayavi/>`_
 is a very powerful and featureful 3D graphing library. For advanced
 3D scenes and excellent rendering capabilities, it is highly recommended to
-use MayaVi2.
+use Mayavi.
 
 mplot3d was intended to allow users to create simple 3D graphs with the same
 "look-and-feel" as matplotlib's 2D plots. Furthermore, users can use the same
@@ -38,7 +38,7 @@ rendered properly in matplotlib's 2D rendering engine.
 This problem will likely not be solved until OpenGL support is added to all of
 the backends (patches are greatly welcomed). Until then, if you need complex
 3D scenes, we recommend using
-`MayaVi <http://code.enthought.com/projects/mayavi/documentation.php>`_.
+`MayaVi <https://docs.enthought.com/mayavi/mayavi/>`_.
 
 
 I don't like how the 3D plot is laid out, how do I change that?

doc/devel/MEP/MEP11.rst

@@ -117,7 +117,7 @@ Implementation
 For installing from source, and assuming the user has all of the
 C-level compilers and dependencies, this can be accomplished fairly
 easily using distribute_ and following the instructions `here
-<https://pypi.python.org/pypi/distribute>`_.  The only anticipated
+<https://pypi.org/project/distribute>`_.  The only anticipated
 change to the matplotlib library code will be to import pyparsing_
 from the top-level namespace rather than from within matplotlib.  Note
 that distribute_ will also allow us to remove the direct dependency

doc/devel/MEP/MEP12.rst

@@ -105,7 +105,7 @@ sections described above. "Clean-up" should involve:
 
 
 * PEP8_ clean-ups (running `flake8
-  <https://pypi.python.org/pypi/flake8>`_, or a similar checker, is
+  <https://pypi.org/project/flake8>`_, or a similar checker, is
   highly recommended)
 * Commented-out code should be removed.
 * Replace uses of `pylab` interface with `.pyplot` (+ `numpy`,
@@ -141,8 +141,8 @@ page instead of the gallery examples.
 references to that example.  For example, the API documentation for
 :file:`axes.py` and :file:`pyplot.py` may use these examples to generate
 plots. Use your favorite search tool (e.g., grep, ack, `grin
-<https://pypi.python.org/pypi/grin>`_, `pss
-<https://pypi.python.org/pypi/pss>`_) to search the matplotlib
+<https://pypi.org/project/grin>`_, `pss
+<https://pypi.org/project/pss>`_) to search the matplotlib
 package. See `2dc9a46
 <https://github.com/tonysyu/matplotlib/commit/2dc9a4651e5e566afc0866c603aa8d06aaf32b71>`_
 and `aa6b410

doc/devel/release_guide.rst

@@ -362,5 +362,5 @@ numpy/scipy/scikit-image mailing lists.
 
 In addition, announcements should be made on social networks (twitter
 via the ``@matplotlib`` account, any other via personal accounts).
-`NumFOCUS <https://www.numfocus.org/>`__ should be contacted for
+`NumFOCUS <https://numfocus.org/>`__ should be contacted for
 inclusion in their newsletter.

doc/index.rst

@@ -187,7 +187,7 @@ Open source
 
 .. raw:: html
 
-   <a href="https://www.numfocus.org/">
+   <a href="https://numfocus.org/">
    <img src="_static/numfocus_badge.png"
     alt="A Fiscally Sponsored Project of NUMFocus"
     style="float:right; margin-left:20px" />
@@ -210,7 +210,7 @@ the NumFOCUS organization or to the `John Hunter Technology Fellowship
 <jdh-fellowship_>`_.
 
 .. _donating: https://numfocus.org/donate-to-matplotlib
-.. _jdh-fellowship: https://www.numfocus.org/programs/john-hunter-technology-fellowship/
+.. _jdh-fellowship: https://numfocus.org/programs/john-hunter-technology-fellowship/
 .. _nf: https://numfocus.org
 
 The :doc:`Matplotlib license <users/license>` is based on the `Python Software

doc/thirdpartypackages/index.rst

@@ -18,19 +18,19 @@ Mapping toolkits
 
 Basemap
 =======
-`Basemap <http://matplotlib.org/basemap>`_ plots data on map projections, with
-continental and political boundaries.
+`Basemap <https://matplotlib.org/basemap/>`_ plots data on map projections,
+with continental and political boundaries.
 
 .. image:: /_static/basemap_contour1.png
     :height: 400px
 
 Cartopy
 =======
-`Cartopy <http://scitools.org.uk/cartopy/docs/latest>`_ builds on top
+`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
-<http://scitools.org.uk/cartopy/docs/latest/gallery.html>`_:
+<https://scitools.org.uk/cartopy/docs/latest/gallery.html>`_:
 
 .. image:: /_static/cartopy_hurricane_katrina_01_00.png
     :height: 400px
@@ -68,7 +68,7 @@ to python based on Matplotlib.
 holoviews
 =========
 `holoviews <http://holoviews.org>`_ makes it easier to visualize data
-interactively, especially in a `Jupyter notebook <http://jupyter.org>`_, by
+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
@@ -120,7 +120,7 @@ diagrams.
 
 mpl-probscale
 =============
-`mpl-probscale <http://matplotlib.org/mpl-probscale/>`_ is a small extension
+`mpl-probscale <https://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')``.

doc/users/history.rst

@@ -11,7 +11,7 @@ Matplotlib is a library for making 2D plots of arrays in `Python
 the MATLAB graphics commands, it is
 independent of MATLAB, and can be used in a Pythonic, object oriented
 way.  Although Matplotlib is written primarily in pure Python, it
-makes heavy use of `NumPy <http://www.numpy.org>`_ and other extension
+makes heavy use of `NumPy <https://numpy.org>`_ and other extension
 code to provide good performance even for large arrays.
 
 Matplotlib is designed with the philosophy that you should be able to

doc/users/prev_whats_new/whats_new_1.0.rst

@@ -128,7 +128,7 @@ Much improved software carpentry
 
 The matplotlib trunk is probably in as good a shape as it has ever
 been, thanks to improved `software carpentry
-<http://software-carpentry.org/>`__.  We now have a `buildbot
+<https://software-carpentry.org/>`__.  We now have a `buildbot
 <https://buildbot.net>`__ which runs a suite of `nose
 <http://code.google.com/p/python-nose/>`__ regression tests on every
 svn commit, auto-generating a set of images and comparing them against

doc/users/prev_whats_new/whats_new_1.3.rst

@@ -85,7 +85,7 @@ New plotting features
 ``````````````````````````````
 To give your plots a sense of authority that they may be missing,
 Michael Droettboom (inspired by the work of many others in
-:ghpull:`1329`) has added an `xkcd-style <http://xkcd.com/>`__ sketch
+:ghpull:`1329`) has added an `xkcd-style <https://xkcd.com/>`__ sketch
 plotting mode.  To use it, simply call `matplotlib.pyplot.xkcd`
 before creating your plot. For really fine control, it is also possible
 to modify each artist's sketch parameters individually with

doc/users/prev_whats_new/whats_new_1.4.rst

@@ -46,7 +46,7 @@ same way as any other matplotlib backend. Because figures require a connection
 to the IPython notebook server for their interactivity, once the notebook is
 saved, each figure will be rendered as a static image - thus allowing
 non-interactive viewing of figures on services such as
-`nbviewer <http://nbviewer.ipython.org/>`__.
+`nbviewer <https://nbviewer.ipython.org/>`__.
 
 
 

doc/users/prev_whats_new/whats_new_1.5.rst

@@ -174,7 +174,7 @@ wx backend has been updated
 ```````````````````````````
 
 The wx backend can now be used with both wxPython classic and
-`Phoenix <http://wxpython.org/Phoenix/docs/html/main.html>`__.
+`Phoenix <https://wxpython.org/Phoenix/docs/html/main.html>`__.
 
 wxPython classic has to be at least version 2.8.12 and works on Python 2.x. As
 of May 2015 no official release of wxPython Phoenix is available but a

doc/users/prev_whats_new/whats_new_2.2.rst

@@ -284,7 +284,7 @@ The binding selection rules are as follows:
 Thus, to force usage of PGI when both bindings are installed, import it first.
 
 .. _PGI: https://pgi.readthedocs.io/en/latest/
-.. _PyGObject: http://pygobject.readthedocs.io/en/latest/#
+.. _PyGObject: https://pygobject.readthedocs.io/en/latest/
 
 
 

examples/misc/image_thumbnail_sgskip.py

@@ -7,7 +7,7 @@
 Matplotlib relies on Pillow_ for reading images, and thus supports all formats
 supported by Pillow.
 
-.. _Pillow: http://python-pillow.org/
+.. _Pillow: https://python-pillow.org/
 """
 
 from argparse import ArgumentParser

examples/showcase/anatomy.py

@@ -137,7 +137,7 @@ def text(x, y, text):
                             connectionstyle="arc3",
                             color=color))
 
-ax.text(4.0, -0.4, "Made with http://matplotlib.org",
+ax.text(4.0, -0.4, "Made with https://matplotlib.org",
         fontsize=10, ha="right", color='.5')
 
 plt.show()

examples/showcase/mandelbrot.py

@@ -66,7 +66,7 @@ def mandelbrot_set(xmin, xmax, ymin, ymax, xn, yn, maxiter, horizon=2.0):
     # Some advertisement for matplotlib
     year = time.strftime("%Y")
     text = ("The Mandelbrot fractal set\n"
-            "Rendered with matplotlib %s, %s - http://matplotlib.org"
+            "Rendered with matplotlib %s, %s - https://matplotlib.org"
             % (matplotlib.__version__, year))
     ax.text(xmin+.025, ymin+.025, text, color="white", fontsize=12, alpha=0.5)
 

examples/statistics/boxplot_vs_violin.py

@@ -17,7 +17,7 @@
 Violin plots require matplotlib >= 1.4.
 
 For more information on violin plots, the scikit-learn docs have a great
-section: http://scikit-learn.org/stable/modules/density.html
+section: https://scikit-learn.org/stable/modules/density.html
 """
 
 import matplotlib.pyplot as plt

examples/statistics/customized_violin.py

@@ -11,7 +11,7 @@
 of the violins are modified.
 
 For more information on violin plots, the scikit-learn docs have a great
-section: http://scikit-learn.org/stable/modules/density.html
+section: https://scikit-learn.org/stable/modules/density.html
 """
 
 import matplotlib.pyplot as plt

examples/statistics/violinplot.py

@@ -13,7 +13,7 @@
 and how to modify the band-width of the KDE (``bw_method``).
 
 For more information on violin plots and KDE, the scikit-learn docs
-have a great section: http://scikit-learn.org/stable/modules/density.html
+have a great section: https://scikit-learn.org/stable/modules/density.html
 """
 
 import numpy as np

lib/matplotlib/__init__.py

@@ -443,18 +443,19 @@ def _create_tmp_config_or_cache_dir():
 
 def _get_xdg_config_dir():
     """
-    Return the XDG configuration directory, according to the `XDG
-    base directory spec
-    <http://standards.freedesktop.org/basedir-spec/basedir-spec-latest.html>`_.
+    Return the XDG configuration directory, according to the XDG base
+    directory spec:
+
+    https://standards.freedesktop.org/basedir-spec/basedir-spec-latest.html
     """
     return os.environ.get('XDG_CONFIG_HOME') or str(Path.home() / ".config")
 
 
 def _get_xdg_cache_dir():
     """
-    Return the XDG cache directory, according to the `XDG
-    base directory spec
-    <http://standards.freedesktop.org/basedir-spec/basedir-spec-latest.html>`_.
+    Return the XDG cache directory, according to the XDG base directory spec:
+
+    https://standards.freedesktop.org/basedir-spec/basedir-spec-latest.html
     """
     return os.environ.get('XDG_CACHE_HOME') or str(Path.home() / ".cache")
 

lib/matplotlib/axes/_axes.py

@@ -2787,7 +2787,7 @@ def stem(self, *args, linefmt=None, markerfmt=None, basefmt=None, bottom=0,
         -----
         .. seealso::
             The MATLAB function
-            `stem <http://www.mathworks.com/help/techdoc/ref/stem.html>`_
+            `stem <https://www.mathworks.com/help/matlab/ref/stem.html>`_
             which inspired this method.
         """
         if not 1 <= len(args) <= 5:

lib/matplotlib/image.py

@@ -1639,7 +1639,7 @@ def thumbnail(infile, thumbfile, scale=0.1, interpolation='bilinear',
         thus supports a wide range of file formats, including PNG, JPG, TIFF
         and others.
 
-        .. _Pillow: http://python-pillow.org/
+        .. _Pillow: https://python-pillow.org/
 
     thumbfile : str or file-like
         The thumbnail filename.

lib/matplotlib/legend.py

@@ -726,7 +726,7 @@ def _init_legend_box(self, handles, labels, markerfirst=True):
                 cbook._warn_external(
                     "Legend does not support {!r} instances.\nA proxy artist "
                     "may be used instead.\nSee: "
-                    "http://matplotlib.org/users/legend_guide.html"
+                    "https://matplotlib.org/users/legend_guide.html"
                     "#creating-artists-specifically-for-adding-to-the-legend-"
                     "aka-proxy-artists".format(orig_handle))
                 # We don't have a handle for this artist, so we just defer

lib/matplotlib/patches.py

@@ -1621,7 +1621,7 @@ def draw(self, renderer):
           Lancaster, Don.  *Approximating a Circle or an Ellipse Using
           Four Bezier Cubic Splines.*
 
-          http://www.tinaja.com/glib/ellipse4.pdf
+          https://www.tinaja.com/glib/ellipse4.pdf
 
         There is a use case where very large ellipses must be drawn
         with very high accuracy, and it is too expensive to render the

lib/matplotlib/path.py

@@ -733,7 +733,7 @@ def circle(cls, center=(0., 0.), radius=1., readonly=False):
         The circle is approximated using 8 cubic Bezier curves, as described in
 
           Lancaster, Don.  `Approximating a Circle or an Ellipse Using Four
-          Bezier Cubic Splines <http://www.tinaja.com/glib/ellipse4.pdf>`_.
+          Bezier Cubic Splines <https://www.tinaja.com/glib/ellipse4.pdf>`_.
         """
         MAGIC = 0.2652031
         SQRTHALF = np.sqrt(0.5)

lib/matplotlib/projections/geo.py

@@ -393,7 +393,7 @@ def transform_non_affine(self, xy):
             # docstring inherited
             x, y = xy.T
             # from Equations (7, 8) of
-            # http://mathworld.wolfram.com/MollweideProjection.html
+            # https://mathworld.wolfram.com/MollweideProjection.html
             theta = np.arcsin(y / np.sqrt(2))
             longitude = (np.pi / (2 * np.sqrt(2))) * x / np.cos(theta)
             latitude = np.arcsin((2 * theta + np.sin(2 * theta)) / np.pi)

lib/matplotlib/pyplot.py

@@ -1779,7 +1779,7 @@ def colormaps():
       =========   ===================================================
 
     The following colormaps are based on the `ColorBrewer
-    <http://colorbrewer2.org>`_ color specifications and designs developed by
+    <https://colorbrewer2.org>`_ color specifications and designs developed by
     Cynthia Brewer:
 
     ColorBrewer Diverging (luminance is highest at the midpoint, and
@@ -1955,7 +1955,7 @@ def colormaps():
     .. [#] Rainbow colormaps, ``jet`` in particular, are considered a poor
       choice for scientific visualization by many researchers: `Rainbow Color
       Map (Still) Considered Harmful
-      <http://ieeexplore.ieee.org/document/4118486/?arnumber=4118486>`_
+      <https://ieeexplore.ieee.org/document/4118486/?arnumber=4118486>`_
 
     .. [#] Resembles "BkBlAqGrYeOrReViWh200" from NCAR Command
       Language. See `Color Table Gallery

tutorials/intermediate/color_cycle.py

@@ -9,7 +9,7 @@
 .. note::
 
     More complete documentation of the ``cycler`` API can be found
-    `here <http://matplotlib.org/cycler/>`_.
+    `here <https://matplotlib.org/cycler/>`_.
 
 This example demonstrates two different APIs: