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Merge pull request #11699 from anntzer/overindentedrst
Dedent overindented rst bullet lists.
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doc/devel/add_new_projection.rst

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@@ -39,24 +39,23 @@ Adding a new scale consists of defining a subclass of
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:class:`matplotlib.scale.ScaleBase`, that includes the following
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elements:
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- A transformation from data coordinates into display coordinates.
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- A transformation from data coordinates into display coordinates.
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- An inverse of that transformation. This is used, for example, to
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convert mouse positions from screen space back into data space.
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- An inverse of that transformation. This is used, for example, to
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convert mouse positions from screen space back into data space.
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- A function to limit the range of the axis to acceptable values
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(``limit_range_for_scale()``). A log scale, for instance, would
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prevent the range from including values less than or equal to
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zero.
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- A function to limit the range of the axis to acceptable values
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(``limit_range_for_scale()``). A log scale, for instance, would
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prevent the range from including values less than or equal to zero.
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- Locators (major and minor) that determine where to place ticks in
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the plot, and optionally, how to adjust the limits of the plot to
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some "good" values. Unlike ``limit_range_for_scale()``, which is
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always enforced, the range setting here is only used when
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automatically setting the range of the plot.
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- Locators (major and minor) that determine where to place ticks in
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the plot, and optionally, how to adjust the limits of the plot to
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some "good" values. Unlike ``limit_range_for_scale()``, which is
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always enforced, the range setting here is only used when
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automatically setting the range of the plot.
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- Formatters (major and minor) that specify how the tick labels
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should be drawn.
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- Formatters (major and minor) that specify how the tick labels
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should be drawn.
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Once the class is defined, it must be registered with matplotlib so
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that the user can select it.
@@ -75,51 +74,48 @@ Adding a new projection consists of defining a projection axes which
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subclasses :class:`matplotlib.axes.Axes` and includes the following
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elements:
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- A transformation from data coordinates into display coordinates.
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- A transformation from data coordinates into display coordinates.
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- An inverse of that transformation. This is used, for example, to
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convert mouse positions from screen space back into data space.
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- An inverse of that transformation. This is used, for example, to
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convert mouse positions from screen space back into data space.
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- Transformations for the gridlines, ticks and ticklabels. Custom
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projections will often need to place these elements in special
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locations, and matplotlib has a facility to help with doing so.
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- Transformations for the gridlines, ticks and ticklabels. Custom
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projections will often need to place these elements in special
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locations, and matplotlib has a facility to help with doing so.
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- Setting up default values (overriding
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:meth:`~matplotlib.axes.Axes.cla`), since the defaults for a
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rectilinear axes may not be appropriate.
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- Setting up default values (overriding :meth:`~matplotlib.axes.Axes.cla`),
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since the defaults for a rectilinear axes may not be appropriate.
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- Defining the shape of the axes, for example, an elliptical axes,
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that will be used to draw the background of the plot and for
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clipping any data elements.
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- Defining the shape of the axes, for example, an elliptical axes, that will be
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used to draw the background of the plot and for clipping any data elements.
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- Defining custom locators and formatters for the projection. For
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example, in a geographic projection, it may be more convenient to
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display the grid in degrees, even if the data is in radians.
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- Defining custom locators and formatters for the projection. For
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example, in a geographic projection, it may be more convenient to
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display the grid in degrees, even if the data is in radians.
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- Set up interactive panning and zooming. This is left as an
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"advanced" feature left to the reader, but there is an example of
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this for polar plots in :mod:`matplotlib.projections.polar`.
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- Set up interactive panning and zooming. This is left as an
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"advanced" feature left to the reader, but there is an example of
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this for polar plots in :mod:`matplotlib.projections.polar`.
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- Any additional methods for additional convenience or features.
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- Any additional methods for additional convenience or features.
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Once the projection axes is defined, it can be used in one of two ways:
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- By defining the class attribute ``name``, the projection axes can be
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registered with :func:`matplotlib.projections.register_projection`
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and subsequently simply invoked by name::
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- By defining the class attribute ``name``, the projection axes can be
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registered with :func:`matplotlib.projections.register_projection`
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and subsequently simply invoked by name::
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plt.axes(projection='my_proj_name')
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plt.axes(projection='my_proj_name')
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- For more complex, parameterisable projections, a generic "projection"
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object may be defined which includes the method ``_as_mpl_axes``.
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``_as_mpl_axes`` should take no arguments and return the projection's
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axes subclass and a dictionary of additional arguments to pass to the
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subclass' ``__init__`` method. Subsequently a parameterised projection
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can be initialised with::
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- For more complex, parameterisable projections, a generic "projection" object
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may be defined which includes the method ``_as_mpl_axes``. ``_as_mpl_axes``
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should take no arguments and return the projection's axes subclass and a
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dictionary of additional arguments to pass to the subclass' ``__init__``
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method. Subsequently a parameterised projection can be initialised with::
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plt.axes(projection=MyProjection(param1=param1_value))
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plt.axes(projection=MyProjection(param1=param1_value))
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where MyProjection is an object which implements a ``_as_mpl_axes`` method.
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where MyProjection is an object which implements a ``_as_mpl_axes`` method.
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A full-fledged and heavily annotated example is in

doc/devel/testing.rst

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@@ -25,16 +25,16 @@ local FreeType build
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The following software is required to run the tests:
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- pytest_ (>=3.4)
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- Ghostscript_ (to render PDF files)
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- Inkscape_ (to render SVG files)
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- pytest_ (>=3.4)
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- Ghostscript_ (to render PDF files)
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- Inkscape_ (to render SVG files)
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Optionally you can install:
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- pytest-cov_ (>=2.3.1) to collect coverage information
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- pytest-pep8_ to test coding standards
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- pytest-timeout_ to limit runtime in case of stuck tests
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- pytest-xdist_ to run tests in parallel
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- pytest-cov_ (>=2.3.1) to collect coverage information
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- pytest-pep8_ to test coding standards
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- pytest-timeout_ to limit runtime in case of stuck tests
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- pytest-xdist_ to run tests in parallel
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Running the tests
@@ -188,16 +188,14 @@ a feature dependent on that backend.
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There are two optional keyword arguments to the `image_comparison`
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decorator:
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- `extensions`: If you only wish to test additional image formats
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(rather than just `png`), pass any additional file types in the
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list of the extensions to test. When copying the new
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baseline files be sure to only copy the output files, not their
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conversions to ``png``. For example only copy the files
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ending in ``pdf``, not in ``_pdf.png``.
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- `extensions`: If you only wish to test additional image formats (rather than
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just `png`), pass any additional file types in the list of the extensions to
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test. When copying the new baseline files be sure to only copy the output
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files, not their conversions to ``png``. For example only copy the files
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ending in ``pdf``, not in ``_pdf.png``.
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- `tol`: This is the image matching tolerance, the default `1e-3`.
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If some variation is expected in the image between runs, this
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value may be adjusted.
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- `tol`: This is the image matching tolerance, the default `1e-3`. If some
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variation is expected in the image between runs, this value may be adjusted.
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Known failing tests
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-------------------

doc/users/dflt_style_changes.rst

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@@ -275,12 +275,12 @@ Plotting functions
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The following changes were made to the default behavior of
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`~matplotlib.axes.Axes.scatter`
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- The default size of the elements in a scatter plot is now based on
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the rcParam ``lines.markersize`` so it is consistent with ``plot(X,
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Y, 'o')``. The old value was 20, and the new value is 36 (6^2).
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- scatter markers no longer have a black edge.
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- if the color of the markers is not specified it will follow the
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property cycle, pulling from the 'patches' cycle on the ``Axes``.
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- The default size of the elements in a scatter plot is now based on
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the rcParam ``lines.markersize`` so it is consistent with ``plot(X,
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Y, 'o')``. The old value was 20, and the new value is 36 (6^2).
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- Scatter markers no longer have a black edge.
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- If the color of the markers is not specified it will follow the
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property cycle, pulling from the 'patches' cycle on the ``Axes``.
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.. plot::
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The following changes were made to the default behavior of
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`~matplotlib.axes.Axes.plot`
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- the default linewidth increased from 1 to 1.5
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- the dash patterns associated with ``'--'``, ``':'``, and ``'-.'`` have
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changed
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- the dash patterns now scale with line width
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- the default linewidth increased from 1 to 1.5
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- the dash patterns associated with ``'--'``, ``':'``, and ``'-.'`` have
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changed
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- the dash patterns now scale with line width
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.. plot::
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The color of the lines in the hatch is now determined by
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- If an edge color is explicitly set, use that for the hatch color
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- If the edge color is not explicitly set, use ``rcParam['hatch.color']`` which
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is looked up at artist creation time.
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- If an edge color is explicitly set, use that for the hatch color
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- If the edge color is not explicitly set, use ``rcParam['hatch.color']`` which
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is looked up at artist creation time.
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The width of the lines in a hatch pattern is now configurable by the
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rcParams `hatch.linewidth`, which defaults to 1 point. The old
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behavior for the line width was different depending on backend:
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- PDF: 0.1 pt
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- SVG: 1.0 pt
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- PS: 1 px
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- Agg: 1 px
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- PDF: 0.1 pt
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- SVG: 1.0 pt
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- PS: 1 px
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- Agg: 1 px
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The old line width behavior can not be restored across all backends
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simultaneously, but can be restored for a single backend by setting::

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