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Commit2465e60

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Merge pull request#11312 from anntzer/rerefs
Replace :ref:`sphx_glr_...` by :doc:`/...`.
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‎doc/api/api_changes.rst‎

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`kiwisolver<https://github.com/nucleic/kiwi>`__ is now a required
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dependency to support the new constrained_layout, see
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:ref:`sphx_glr_tutorials_intermediate_constrainedlayout_guide.py` for
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:doc:`/tutorials/intermediate/constrainedlayout_guide` for
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more details.
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* The legend handler interface has changed from a callable, to any object
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which implements the ``legend_artists`` method (a deprecation phase will
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see this interface be maintained for v1.4). See
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:ref:`sphx_glr_tutorials_intermediate_legend_guide.py` for further details. Further legend changes
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:doc:`/tutorials/intermediate/legend_guide` for further details. Further legend changes
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include:
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*:func:`matplotlib.axes.Axes._get_legend_handles` now returns a generator

‎doc/api/pyplot_summary.rst‎

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The:mod:`matplotlib.pyplot` module contains functions that allow you to generate
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many kinds of plots quickly. For examples that showcase the use
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of the:mod:`matplotlib.pyplot` module, see the
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:ref:`sphx_glr_tutorials_introductory_pyplot.py`
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:doc:`/tutorials/introductory/pyplot`
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or the:ref:`pyplots_examples`. We also recommend that you look into
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the object-oriented approach to plotting, described below.
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Below we list several ways in which color can be utilized in Matplotlib.
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For a more in-depth look at colormaps, see the
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:ref:`sphx_glr_tutorials_colors_colormaps.py` tutorial.
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:doc:`/tutorials/colors/colormaps` tutorial.
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..autofunction::colormaps

‎doc/api/toolkits/index.rst‎

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plotting (scatter, surf, line, mesh) tools. Not the fastest or most feature
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complete 3D library out there, but it ships with Matplotlib and thus may be a
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lighter weight solution for some use cases. Check out the
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:ref:`mplot3d tutorial<sphx_glr_tutorials_toolkits_mplot3d.py>` for more
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:doc:`mplot3d tutorial</tutorials/toolkits/mplot3d>` for more
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information.
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..figure::../../gallery/mplot3d/images/sphx_glr_contourf3d_2_001.png

‎doc/api/toolkits/mplot3d/index.rst‎

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@@ -11,7 +11,7 @@ The mplot3d toolkit adds simple 3D plotting capabilities to matplotlib by
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supplying an axes object that can create a 2D projection of a 3D scene.
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The resulting graph will have the same look and feel as regular 2D plots.
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See the:ref:`mplot3d tutorial<sphx_glr_tutorials_toolkits_mplot3d.py>` for
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See the:doc:`mplot3d tutorial</tutorials/toolkits/mplot3d>` for
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more information on how to use this toolkit.
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..image::/_static/demo_mplot3d.png

‎doc/devel/contributing.rst‎

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------------------------
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If you are working on a custom backend, the *backend* setting in
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:file:`matplotlibrc` (:ref:`sphx_glr_tutorials_introductory_customizing.py`) supports an
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:file:`matplotlibrc` (:doc:`/tutorials/introductory/customizing`) supports an
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external backend via the ``module`` directive. If
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:file:`my_backend.py` is a Matplotlib backend in your
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:envvar:`PYTHONPATH`, you can set it on one of several ways

‎doc/faq/howto_faq.rst‎

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Find all objects in a figure of a certain type
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----------------------------------------------
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Every Matplotlib artist (see:ref:`sphx_glr_tutorials_intermediate_artists.py`) has a method
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Every Matplotlib artist (see:doc:`/tutorials/intermediate/artists`) has a method
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called:meth:`~matplotlib.artist.Artist.findobj` that can be used to
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recursively search the artist for any artists it may contain that meet
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some criteria (e.g., match all:class:`~matplotlib.lines.Line2D`
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ax = fig.add_subplot(111)
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You can control the defaults for these parameters in your
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:file:`matplotlibrc` file; see:ref:`sphx_glr_tutorials_introductory_customizing.py`. For
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:file:`matplotlibrc` file; see:doc:`/tutorials/introductory/customizing`. For
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example, to make the above setting permanent, you would set::
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figure.subplot.bottom : 0.2 # the bottom of the subplots of the figure
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ax = fig.add_axes([left, bottom, width, height])
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where all values are in fractional (0 to 1) coordinates. See
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:ref:`sphx_glr_gallery_subplots_axes_and_figures_axes_demo.py` for an example of placing axes manually.
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:doc:`/gallery/subplots_axes_and_figures/axes_demo` for an example of placing axes manually.
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.. _howto-auto-adjust:
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..note::
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This is now easier to handle than ever before.
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Calling:func:`~matplotlib.pyplot.tight_layout` can fix many common
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layout issues. See the:ref:`sphx_glr_tutorials_intermediate_tight_layout_guide.py`.
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layout issues. See the:doc:`/tutorials/intermediate/tight_layout_guide`.
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The information below is kept here in case it is useful for other
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purposes.
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..only::html
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See:ref:`sphx_glr_gallery_misc_zorder_demo.py` for a complete example.
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See:doc:`/gallery/misc/zorder_demo` for a complete example.
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You can also use the Axes property
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:meth:`~matplotlib.axes.Axes.set_axisbelow` to control whether the grid
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..only::html
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See:ref:`sphx_glr_gallery_subplots_axes_and_figures_axis_equal_demo.py` for a
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See:doc:`/gallery/subplots_axes_and_figures/axis_equal_demo` for a
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.. _howto-twoscale:
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See:ref:`sphx_glr_gallery_api_two_scales.py` for a complete example
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See:doc:`/gallery/api/two_scales` for a complete example
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.. _howto-batch:
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Alternatively, you can avoid pylab/pyplot altogether, which will give
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you a little more control, by calling the API directly as shown in
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:ref:`sphx_glr_gallery_api_agg_oo_sgskip.py`.
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:doc:`/gallery/api/agg_oo_sgskip`.
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You can either generate hardcopy on the filesystem by calling savefig::
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‎doc/faq/installing_faq.rst‎

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This will give you additional information about which backends matplotlib is
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loading, version information, and more. At this point you might want to make
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sure you understand matplotlib's:ref:`configuration<sphx_glr_tutorials_introductory_customizing.py>`
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sure you understand matplotlib's:doc:`configuration</tutorials/introductory/customizing>`
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process, governed by the:file:`matplotlibrc` configuration file which contains
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instructions within and the concept of the matplotlib backend.
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‎doc/faq/troubleshooting_faq.rst‎

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`Enthought Canopy<https://www.enthought.com/products/canopy/>`_).
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* Any customizations to your ``matplotlibrc`` file (see
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:ref:`sphx_glr_tutorials_introductory_customizing.py`).
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:doc:`/tutorials/introductory/customizing`).
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* If the problem is reproducible, please try to provide a *minimal*, standalone
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Python script that demonstrates the problem. This is *the* critical step.

‎doc/users/dflt_style_changes.rst‎

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the property cycling the notation for colors ``'CN'``, where ``N``
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takes values 0-9, was added to
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denote the first 10 colors in ``mpl.rcParams['axes.prop_cycle']`` See
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:ref:`sphx_glr_tutorials_colors_colors.py` for more details.
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:doc:`/tutorials/colors/colors` for more details.
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To restore the old color cycle use
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See `here for many more details<https://bids.github.io/colormap/>`__
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about the other alternatives and the tools used to create the color
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map. For details on all of the color maps available in matplotlib see
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:ref:`sphx_glr_tutorials_colors_colormaps.py`.
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:doc:`/tutorials/colors/colormaps`.
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..raw::html
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‎doc/users/prev_whats_new/whats_new_0.98.4.rst‎

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Ryan May did a lot of work to rationalize the amplitude scaling of
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:func:`~matplotlib.pyplot.psd` and friends. See
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:ref:`sphx_glr_gallery_lines_bars_and_markers_psd_demo.py`.
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:doc:`/gallery/lines_bars_and_markers/psd_demo`.
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The changes should increase MATLAB
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compatibility and increase scaling options.
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