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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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@@ -8,7 +8,7 @@ The Pyplot API
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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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@@ -21,7 +21,7 @@ mplot3d
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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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complete example.
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.. _howto-twoscale:
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.. only:: html
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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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‎doc/users/prev_whats_new/whats_new_0.99.rst

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New documentation
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-----------------
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Jae-Joon Lee has written two new guides :ref:`sphx_glr_tutorials_intermediate_legend_guide.py`
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Jae-Joon Lee has written two new guides :doc:`/tutorials/intermediate/legend_guide`
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and :ref:`plotting-guide-annotation`. Michael Sarahan has written
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:ref:`sphx_glr_tutorials_introductory_images.py`. John Hunter has written two new tutorials on
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working with paths and transformations: :ref:`sphx_glr_tutorials_advanced_path_tutorial.py` and
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:ref:`sphx_glr_tutorials_advanced_transforms_tutorial.py`.
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:doc:`/tutorials/introductory/images`. John Hunter has written two new tutorials on
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working with paths and transformations: :doc:`/tutorials/advanced/path_tutorial` and
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:doc:`/tutorials/advanced/transforms_tutorial`.
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.. _whats-new-mplot3d:
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longer are your axis lines constrained to be a simple rectangle around
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the figure -- you can turn on or off left, bottom, right and top, as
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well as "detach" the spine to offset it away from the data. See
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:ref:`sphx_glr_gallery_ticks_and_spines_spine_placement_demo.py` and
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:doc:`/gallery/ticks_and_spines/spine_placement_demo` and
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:class:`matplotlib.spines.Spine`.
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.. figure:: ../../gallery/pyplots/images/sphx_glr_whats_new_99_spines_001.png

‎doc/users/prev_whats_new/whats_new_1.0.rst

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Jae-Joon Lee has written :mod:`~matplotlib.gridspec`, a new module for
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doing complex subplot layouts, featuring row and column spans and
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more. See :ref:`sphx_glr_tutorials_intermediate_gridspec.py` for a tutorial overview.
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more. See :doc:`/tutorials/intermediate/gridspec` for a tutorial overview.
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See :ref:`sphx_glr_gallery_subplots_axes_and_figures_subplot_demo.py` for several code examples.
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See :doc:`/gallery/subplots_axes_and_figures/subplot_demo` for several code examples.
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Contour fixes and and triplot
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---------------------------------

‎doc/users/prev_whats_new/whats_new_1.1.rst

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Kevin Davies has extended Yannick Copin's original Sankey example into a module
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(:ref:`sphx_glr_gallery_api_sankey_basics.py`, :ref:`sphx_glr_gallery_api_sankey_links.py`,
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:ref:`sphx_glr_gallery_api_sankey_rankine.py`).
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(:doc:`/gallery/api/sankey_basics`, :doc:`/gallery/api/sankey_links`,
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:doc:`/gallery/api/sankey_rankine`).
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and it will adjust the spacing between subplots
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:doc:`/tutorials/intermediate/tight_layout_guide` has been created to show how to use
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PyQT4, PySide, and IPython
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See the :doc:`/tutorials/intermediate/legend_guide` for more detailed explanation and
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.. figure:: ../../gallery/text_labels_and_annotations/images/sphx_glr_legend_demo_004.png

‎doc/users/prev_whats_new/whats_new_1.2.rst

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Peter Würtz wrote a backend that allows matplotlib to export figures as
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found in :doc:`/tutorials/text/pgf`.
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‎doc/users/prev_whats_new/whats_new_1.4.rst

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:ref:`sphx_glr_gallery_statistics_boxplot.py` and
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:doc:`/gallery/statistics/boxplot` and
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:doc:`/gallery/statistics/bxp`
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Legend and PathEffects documentation
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‎doc/users/prev_whats_new/whats_new_1.5.rst

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‎doc/users/prev_whats_new/whats_new_2.0.0.rst

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:doc:`marker reference </gallery/lines_bars_and_markers/marker_reference>`
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`rcount` and `ccount` for `plot_surface()`

‎doc/users/prev_whats_new/whats_new_2.1.0.rst

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:doc:`/gallery/widgets/polygon_selector_demo` for details.
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‎doc/users/shell.rst

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``backend : TkAgg`` and ``interactive : True`` in your
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:file:`matplotlibrc` file (see :ref:`sphx_glr_tutorials_introductory_customizing.py`) and fire
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:file:`matplotlibrc` file (see :doc:`/tutorials/introductory/customizing`) and fire
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>>> from pylab import *

‎examples/axes_grid1/simple_anchored_artists.py

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This example illustrates the use of the anchored helper classes found in
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can be found in :doc:`/gallery/misc/anchored_artists`.
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‎examples/color/color_cycle_default.py

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====================================
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Display the colors from the default prop_cycle, which is obtained from the
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:doc:`rc parameters</tutorials/introductory/customizing>`.
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"""
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‎examples/color/color_cycler.py

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This example demonstrates two different APIs:
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1. Setting the default
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:ref:`rc parameter<sphx_glr_tutorials_introductory_customizing.py>`
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specifying the property cycle. This affects all subsequent axes
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(but not axes already created).
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2. Setting the property cycle for a single pair of axes.
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1. Setting the default :doc:`rc parameter</tutorials/introductory/customizing>`
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specifying the property cycle. This affects all subsequent axes (but not
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axes already created).
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2. Setting the property cycle for a single pair of axes.
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"""
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from cycler import cycler
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‎examples/color/color_demo.py

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* the :ref:`sphx_glr_tutorials_colors_colors.py` tutorial;
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* the :doc:`/tutorials/colors/colors` tutorial;
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* the `matplotlib.colors` API;
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* the :ref:`sphx_glr_gallery_color_named_colors.py` example.
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* the :doc:`/gallery/color/named_colors` example.
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"""
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‎examples/color/named_colors.py

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* the :ref:`sphx_glr_tutorials_colors_colors.py` tutorial;
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* the :doc:`/tutorials/colors/colors` tutorial;
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* the :ref:`sphx_glr_gallery_color_color_demo.py`.
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* the :doc:`/gallery/color/color_demo`.
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"""
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‎examples/images_contours_and_fields/contour_demo.py

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Illustrate simple contour plotting, contours on an image with
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See also the
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:ref:`contour image example
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<sphx_glr_gallery_images_contours_and_fields_contour_image.py>`.
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See also the :doc:`contour image example
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</gallery/images_contours_and_fields/contour_image>`.
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"""
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import matplotlib
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import numpy as np

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