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Commit d7ad3ad

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Merge branch 'main' into stubtest_script
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‎.pre-commit-config.yaml

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@@ -55,3 +55,4 @@ repos:
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- id: rstcheck
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additional_dependencies:
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- sphinx>=1.8.1
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- tomli

‎ci/mypy-stubtest-allowlist.txt

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@@ -32,18 +32,6 @@ matplotlib.ticker.LogitLocator.nonsingular
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matplotlib.backend_bases._Mode.__new__
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matplotlib.units.Number.__hash__
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# Property read-write vs read-only weirdness, fix if possible
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matplotlib.offsetbox.DraggableBase.canvas
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matplotlib.offsetbox.DraggableBase.cids
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matplotlib.transforms.BboxTransform.is_separable
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matplotlib.transforms.BboxTransformFrom.is_separable
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matplotlib.transforms.BboxTransformTo.is_separable
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matplotlib.transforms.BlendedAffine2D.is_separable
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matplotlib.transforms.CompositeGenericTransform.is_separable
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matplotlib.transforms.TransformWrapper.input_dims
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matplotlib.transforms.TransformWrapper.is_separable
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matplotlib.transforms.TransformWrapper.output_dims
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# 3.6 Pending deprecations
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matplotlib.figure.Figure.set_constrained_layout
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matplotlib.figure.Figure.set_constrained_layout_pads
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# 3.7 deprecations
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matplotlib.cm.register_cmap
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matplotlib.cm.unregister_cmap
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matplotlib.collections.PolyCollection.span_where
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# 3.8 deprecations
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matplotlib.contour.ContourSet.allkinds
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# positional-only argument name lacking leading underscores
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matplotlib.axes._base._AxesBase.axis
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# Other dynamic python behaviors not type hinted
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matplotlib.rcsetup.defaultParams
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# Maybe should be abstractmethods, required for subclasses, stubs define once
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matplotlib.tri.*TriInterpolator.__call__
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matplotlib.tri.*TriInterpolator.gradient
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# Functionally a method call, but actually a class instance, type hinted as former
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matplotlib.rcsetup.validate_fillstyle
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# TypeVar used only in type hints
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matplotlib.backend_bases.FigureCanvasBase._T
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matplotlib.backend_managers.ToolManager._T

‎doc/api/artist_api.rst

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Inheritance Diagrams
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====================
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.. inheritance-diagram:: matplotlib.axes._axes.Axes matplotlib.axes._base._AxesBase matplotlib.axis.Axis matplotlib.axis.Tick matplotlib.axis.XAxis matplotlib.axis.XTick matplotlib.axis.YAxis matplotlib.axis.YTick matplotlib.collections.AsteriskPolygonCollection matplotlib.collections.BrokenBarHCollection matplotlib.collections.CircleCollection matplotlib.collections.Collection matplotlib.collections.EllipseCollection matplotlib.collections.EventCollection matplotlib.collections.LineCollection matplotlib.collections.PatchCollection matplotlib.collections.PathCollection matplotlib.collections.PolyCollection matplotlib.collections.QuadMesh matplotlib.collections.RegularPolyCollection matplotlib.collections.StarPolygonCollection matplotlib.collections.TriMesh matplotlib.collections._CollectionWithSizes matplotlib.contour.ClabelText matplotlib.contour.ContourSet matplotlib.contour.QuadContourSet matplotlib.figure.FigureBase matplotlib.figure.Figure matplotlib.figure.SubFigure matplotlib.image.AxesImage matplotlib.image.BboxImage matplotlib.image.FigureImage matplotlib.image.NonUniformImage matplotlib.image.PcolorImage matplotlib.image._ImageBase matplotlib.legend.Legend matplotlib.lines.Line2D matplotlib.offsetbox.AnchoredOffsetbox matplotlib.offsetbox.AnchoredText matplotlib.offsetbox.AnnotationBbox matplotlib.offsetbox.AuxTransformBox matplotlib.offsetbox.DrawingArea matplotlib.offsetbox.HPacker matplotlib.offsetbox.OffsetBox matplotlib.offsetbox.OffsetImage matplotlib.offsetbox.PackerBase matplotlib.offsetbox.PaddedBox matplotlib.offsetbox.TextArea matplotlib.offsetbox.VPacker matplotlib.patches.Annulus matplotlib.patches.Arc matplotlib.patches.Arrow matplotlib.patches.Circle matplotlib.patches.CirclePolygon matplotlib.patches.ConnectionPatch matplotlib.patches.Ellipse matplotlib.patches.FancyArrow matplotlib.patches.FancyArrowPatch matplotlib.patches.FancyBboxPatch matplotlib.patches.Patch matplotlib.patches.PathPatch matplotlib.patches.Polygon matplotlib.patches.Rectangle matplotlib.patches.RegularPolygon matplotlib.patches.Shadow matplotlib.patches.StepPatch matplotlib.patches.Wedge matplotlib.projections.geo.AitoffAxes matplotlib.projections.geo.GeoAxes matplotlib.projections.geo.HammerAxes matplotlib.projections.geo.LambertAxes matplotlib.projections.geo.MollweideAxes matplotlib.projections.polar.PolarAxes matplotlib.projections.polar.RadialAxis matplotlib.projections.polar.RadialTick matplotlib.projections.polar.ThetaAxis matplotlib.projections.polar.ThetaTick matplotlib.quiver.Barbs matplotlib.quiver.Quiver matplotlib.quiver.QuiverKey matplotlib.spines.Spine matplotlib.table.Cell matplotlib.table.Table matplotlib.text.Annotation matplotlib.text.Text matplotlib.tri.TriContourSet
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.. inheritance-diagram:: matplotlib.axes._axes.Axes matplotlib.axes._base._AxesBase matplotlib.axis.Axis matplotlib.axis.Tick matplotlib.axis.XAxis matplotlib.axis.XTick matplotlib.axis.YAxis matplotlib.axis.YTick matplotlib.collections.AsteriskPolygonCollection matplotlib.collections.CircleCollection matplotlib.collections.Collection matplotlib.collections.EllipseCollection matplotlib.collections.EventCollection matplotlib.collections.LineCollection matplotlib.collections.PatchCollection matplotlib.collections.PathCollection matplotlib.collections.PolyCollection matplotlib.collections.QuadMesh matplotlib.collections.RegularPolyCollection matplotlib.collections.StarPolygonCollection matplotlib.collections.TriMesh matplotlib.collections._CollectionWithSizes matplotlib.contour.ClabelText matplotlib.contour.ContourSet matplotlib.contour.QuadContourSet matplotlib.figure.FigureBase matplotlib.figure.Figure matplotlib.figure.SubFigure matplotlib.image.AxesImage matplotlib.image.BboxImage matplotlib.image.FigureImage matplotlib.image.NonUniformImage matplotlib.image.PcolorImage matplotlib.image._ImageBase matplotlib.legend.Legend matplotlib.lines.Line2D matplotlib.offsetbox.AnchoredOffsetbox matplotlib.offsetbox.AnchoredText matplotlib.offsetbox.AnnotationBbox matplotlib.offsetbox.AuxTransformBox matplotlib.offsetbox.DrawingArea matplotlib.offsetbox.HPacker matplotlib.offsetbox.OffsetBox matplotlib.offsetbox.OffsetImage matplotlib.offsetbox.PackerBase matplotlib.offsetbox.PaddedBox matplotlib.offsetbox.TextArea matplotlib.offsetbox.VPacker matplotlib.patches.Annulus matplotlib.patches.Arc matplotlib.patches.Arrow matplotlib.patches.Circle matplotlib.patches.CirclePolygon matplotlib.patches.ConnectionPatch matplotlib.patches.Ellipse matplotlib.patches.FancyArrow matplotlib.patches.FancyArrowPatch matplotlib.patches.FancyBboxPatch matplotlib.patches.Patch matplotlib.patches.PathPatch matplotlib.patches.Polygon matplotlib.patches.Rectangle matplotlib.patches.RegularPolygon matplotlib.patches.Shadow matplotlib.patches.StepPatch matplotlib.patches.Wedge matplotlib.projections.geo.AitoffAxes matplotlib.projections.geo.GeoAxes matplotlib.projections.geo.HammerAxes matplotlib.projections.geo.LambertAxes matplotlib.projections.geo.MollweideAxes matplotlib.projections.polar.PolarAxes matplotlib.projections.polar.RadialAxis matplotlib.projections.polar.RadialTick matplotlib.projections.polar.ThetaAxis matplotlib.projections.polar.ThetaTick matplotlib.quiver.Barbs matplotlib.quiver.Quiver matplotlib.quiver.QuiverKey matplotlib.spines.Spine matplotlib.table.Cell matplotlib.table.Table matplotlib.text.Annotation matplotlib.text.Text matplotlib.tri.TriContourSet
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:parts: 1
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:private-bases:
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‎doc/api/next_api_changes/behavior/26788-AL.rst

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``axvspan`` and ``axhspan`` now return ``Rectangle``\s, not ``Polygons``
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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This change allows using `~.Axes.axhspan` to draw an annulus on polar axes.
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This change also affects other elements built via `~.Axes.axvspan` and
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`~.Axes.axhspan`, such as ``Slider.poly``.

‎doc/api/next_api_changes/behavior/26902-RP.rst

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``Line2D``
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~~~~~~~~~~
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When creating a Line2D or using `.Line2D.set_xdata` and `.Line2D.set_ydata`,
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passing x/y data as non sequence is now an error.

‎doc/api/next_api_changes/removals/26852-OG.rst

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33

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... of the `.dates` module are removed without replacements. These were
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undocumented and not exported.
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Julian dates in Matplotlib were calculated from a Julian date epoch: ``jdate =
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(date - np.datetime64(EPOCH)) / np.timedelta64(1, 'D')``. Conversely, a Julian
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date was converted to datetime as ``date = np.timedelta64(int(jdate * 24 *
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3600), 's') + np.datetime64(EPOCH)``. Matplotlib was using
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``EPOCH='-4713-11-24T12:00'`` so that 2000-01-01 at 12:00 is 2_451_545.0 (see
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<https://en.wikipedia.org/wiki/Julian_day>`).

‎doc/api/next_api_changes/removals/26872-AD.rst

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``repeat``
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~~~~~~~~~~
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... of `.TimedAnimation` is removed without replacements.
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``save_count``
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~~~~~~~~~~~~~~
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... of `.FuncAnimation` is removed without replacements.
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``Animation`` attributes
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~~~~~~~~~~~~~~~~~~~~~~~~
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The attributes ``repeat`` of `.TimedAnimation` and subclasses and
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``save_count`` of `.FuncAnimation` are considered private and removed.

‎doc/api/next_api_changes/removals/26874-AG.rst

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``collections.PolyCollection.span_where`` and ``collections.BrokenBarHCollection``
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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... removed as it was deprecated during 3.7. Use ``fill_between`` instead

‎doc/api/next_api_changes/removals/26918-EW.rst

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``Quiver.quiver_doc`` and ``Barbs.barbs_doc``
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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... are removed. These are the doc-string and should not be accessible as a named class member.

‎doc/users/next_whats_new/polar-line-spans.rst

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``axhline`` and ``axhspan`` on polar axes
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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... now draw circles and circular arcs (`~.Axes.axhline`) or annuli and wedges
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(`~.Axes.axhspan`).

‎doc/users/next_whats_new/stdfmt-axisartist.rst

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``axisartist`` can now be used together with standard ``Formatters``
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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... instead of being limited to axisartist-specific ones.

‎doc/users/prev_whats_new/whats_new_1.4.rst

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Added the ``get_size`` and ``set_size`` functions to control the size of
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elements of specialized collections (
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:class:`~matplotlib.collections.AsteriskPolygonCollection`
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:class:`~matplotlib.collections.BrokenBarHCollection`
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``matplotlib.collections.BrokenBarHCollection``
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:class:`~matplotlib.collections.CircleCollection`
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:class:`~matplotlib.collections.PathCollection`
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:class:`~matplotlib.collections.PolyCollection`

‎galleries/examples/axes_grid1/demo_colorbar_with_axes_divider.py

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"""
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.. _demo-colorbar-with-axes-divider:
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=========================
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Colorbar with AxesDivider
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=========================
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method of the `.AxesDivider` can then be used to create a new axes on a given
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side ("top", "right", "bottom", or "left") of the original axes. This example
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uses `.append_axes` to add colorbars next to axes.
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Users should consider simply passing the main axes to the *ax* keyword argument of
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`~.Figure.colorbar` instead of creating a locatable axes manually like this.
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See :ref:`colorbar_placement`.
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"""
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import matplotlib.pyplot as plt

‎galleries/examples/axes_grid1/demo_colorbar_with_inset_locator.py

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"""
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.. _demo-colorbar-with-inset-locator:
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==============================================================
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Controlling the position and size of colorbars with Inset Axes
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==============================================================
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This example shows how to control the position, height, and width of
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colorbars using `~mpl_toolkits.axes_grid1.inset_locator.inset_axes`.
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This example shows how to control the position, height, and width of colorbars
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using `~mpl_toolkits.axes_grid1.inset_locator.inset_axes`.
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Inset axes placement is controlled as for legends: either by providing a *loc*
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option ("upper right", "best", ...), or by providing a locator with respect to
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the parent bbox. Parameters such as *bbox_to_anchor* and *borderpad* likewise
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work in the same way, and are also demonstrated here.
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Users should consider using `.Axes.inset_axes` instead (see
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:ref:`colorbar_placement`).
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"""
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import matplotlib.pyplot as plt

‎galleries/users_explain/axes/colorbar_placement.py

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Colorbars indicate the quantitative extent of image data. Placing in
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a figure is non-trivial because room needs to be made for them.
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The simplest case is just attaching a colorbar to each axes:
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Automatic placement of colorbars
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================================
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The simplest case is just attaching a colorbar to each axes. Note in this
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example that the colorbars steal some space from the parent axes.
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"""
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import matplotlib.pyplot as plt
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import numpy as np
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fig.colorbar(pcm, ax=ax)
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# %%
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# The first column has the same type of data in both rows, so it may
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# be desirable to combine the colorbar which we do by calling
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# `.Figure.colorbar` with a list of axes instead of a single axes.
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# The first column has the same type of data in both rows, so it may be
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# desirable to have just one colorbar. We do this by passing `.Figure.colorbar`
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# a list of axes with the *ax* kwarg.
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fig, axs = plt.subplots(2, 2)
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cmaps = ['RdBu_r', 'viridis']
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cmap=cmaps[col])
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fig.colorbar(pcm, ax=axs[:, col], shrink=0.6)
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# %%
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# The stolen space can lead to axes in the same subplot layout
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# being different sizes, which is often undesired if the the
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# x-axis on each plot is meant to be comparable as in the following:
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fig, axs = plt.subplots(2, 1, figsize=(4, 5), sharex=True)
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X = np.random.randn(20, 20)
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axs[0].plot(np.sum(X, axis=0))
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axs[1].pcolormesh(X)
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fig.colorbar(pcm, ax=axs[1], shrink=0.6)
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# %%
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# This is usually undesired, and can be worked around in various ways, e.g.
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# adding a colorbar to the other axes and then removing it. However, the most
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# straightforward is to use :ref:`constrained layout <constrainedlayout_guide>`:
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fig, axs = plt.subplots(2, 1, figsize=(4, 5), sharex=True, layout='constrained')
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axs[0].plot(np.sum(X, axis=0))
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axs[1].pcolormesh(X)
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fig.colorbar(pcm, ax=axs[1], shrink=0.6)
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# %%
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# Relatively complicated colorbar layouts are possible using this
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# paradigm. Note that this example works far better with
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fig.colorbar(pcm, ax=[axs[2, 1]], location='left')
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# %%
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# Colorbars with fixed-aspect-ratio axes
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# ======================================
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# Adjusting the spacing between colorbars and parent axes
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# =======================================================
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#
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# The distance a colorbar is from the parent axes can be adjusted with the
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# *pad* keyword argument. This is in units of fraction of the parent axes
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# width, and the default for a vertical axes is 0.05 (or 0.15 for a horizontal
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# axes).
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fig, axs = plt.subplots(3, 1, layout='constrained', figsize=(5, 5))
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for ax, pad in zip(axs, [0.025, 0.05, 0.1]):
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pcm = ax.pcolormesh(np.random.randn(20, 20), cmap='viridis')
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fig.colorbar(pcm, ax=ax, pad=pad, label=f'pad: {pad}')
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fig.suptitle("layout='constrained'")
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# %%
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# Note that if you do not use constrained layout, the pad command makes the
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# parent axes shrink:
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fig, axs = plt.subplots(3, 1, figsize=(5, 5))
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for ax, pad in zip(axs, [0.025, 0.05, 0.1]):
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pcm = ax.pcolormesh(np.random.randn(20, 20), cmap='viridis')
105+
fig.colorbar(pcm, ax=ax, pad=pad, label=f'pad: {pad}')
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fig.suptitle("No layout manager")
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# %%
109+
# Manual placement of colorbars
110+
# =============================
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#
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# Sometimes the automatic placement provided by ``colorbar`` does not
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# give the desired effect. We can manually create an axes and tell
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# ``colorbar`` to use that axes by passing the axes to the *cax* keyword
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# argument.
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#
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# Using ``inset_axes``
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# --------------------
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#
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# We can manually create any type of axes for the colorbar to use, but an
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# `.Axes.inset_axes` is useful because it is a child of the parent axes and can
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# be positioned relative to the parent. Here we add a colorbar centered near
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# the bottom of the parent axes.
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fig, ax = plt.subplots(layout='constrained', figsize=(4, 4))
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pcm = ax.pcolormesh(np.random.randn(20, 20), cmap='viridis')
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ax.set_ylim([-4, 20])
128+
cax = ax.inset_axes([0.3, 0.07, 0.4, 0.04])
129+
fig.colorbar(pcm, cax=cax, orientation='horizontal')
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# %%
132+
# `.Axes.inset_axes` can also specify its position in data coordinates
133+
# using the *transform* keyword argument if you want your axes at a
134+
# certain data position on the graph:
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fig, ax = plt.subplots(layout='constrained', figsize=(4, 4))
137+
pcm = ax.pcolormesh(np.random.randn(20, 20), cmap='viridis')
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ax.set_ylim([-4, 20])
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cax = ax.inset_axes([7.5, -1.7, 5, 1.2], transform=ax.transData)
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fig.colorbar(pcm, cax=cax, orientation='horizontal')
141+
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# %%
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# Colorbars attached to fixed-aspect-ratio axes
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# ---------------------------------------------
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#
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# Placing colorbars for axes with a fixed aspect ratio pose a particular
63147
# challenge as the parent axes changes size depending on the data view.
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77161
fig.colorbar(pcm, ax=ax, shrink=0.6)
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# %%
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# One way around this issue is to use an `.Axes.inset_axes` to locate the
81-
# axes in axes coordinates. Note that if you zoom in on the axes, and
82-
# change the shape of the axes, the colorbar will also change position.
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# We solve this problem using `.Axes.inset_axes` to locate the axes in "axes
165+
# coordinates" (see :ref:`transforms_tutorial`). Note that if you zoom in on
166+
# the parent axes, and thus change the shape of it, the colorbar will also
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# change position.
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fig, axs = plt.subplots(2, 2, layout='constrained')
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cmaps = ['RdBu_r', 'viridis']
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ax.set_aspect(1/2)
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if row == 1:
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cax = ax.inset_axes([1.04, 0.2, 0.05, 0.6])
97-
fig.colorbar(pcm, ax=ax, cax=cax)
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fig.colorbar(pcm, cax=cax)
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plt.show()
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# %%
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# .. seealso::
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#
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# :ref:`axes_grid` has methods for manually creating colorbar axes as well:
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#
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# - :ref:`demo-colorbar-with-inset-locator`
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# - :ref:`demo-colorbar-with-axes-divider`

‎galleries/users_explain/axes/constrainedlayout_guide.py

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.. _constrainedlayout_guide:
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7-
================================
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========================
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Constrained Layout Guide
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================================
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========================
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Use *constrained layout* to fit plots within your figure cleanly.
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