Dec 20, 2024
diff --git a/doc/api/next_api_changes/deprecations/29358-TH.rst b/doc/api/next_api_changes/deprecations/29358-TH.rst
 3rd party scales do not need to have an *axis* parameter anymore
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

 Since matplotlib 3.1 `PR 12831<https://github.com/matplotlib/matplotlib/pull/12831>`_
 scales should be reusable and therefore independent of the Axis. Therefore the use of
 of the *axis* parameter in the ``__init__`` had been discouraged. However, that
 parameter was still necessary for API compatibility. This is no longer the case.

 `.register_scale` now accepts scale classes with and without this parameter.
 3rd party scales can and should remove that parameter.
diff --git a/lib/matplotlib/scale.py b/lib/matplotlib/scale.py
    'functionlog': FuncScaleLog,
    }

 # caching of signature info
 _scale_has_axis_parameter = {}


 def get_scale_names():
    """Return the names of the available scales."""
    axis : `~matplotlib.axis.Axis`
    """
    scale_cls = _api.check_getitem(_scale_mapping, scale=scale)
    return scale_cls(axis, **kwargs)

    # We support scales that may or may not have an initial *axis* parameter.
    # This information is cached, so that we do not need to inspect the signature
    # on every time we create a scale.
    if scale not in _scale_has_axis_parameter:
        _scale_has_axis_parameter[scale] = (
            "axis" in inspect.signature(scale_cls).parameters
        )

    if _scale_has_axis_parameter[scale]:
        return scale_cls(axis, **kwargs)
    else:
        return scale_cls(**kwargs)


 if scale_factory.__doc__:
diff --git a/lib/matplotlib/tests/test_scale.py b/lib/matplotlib/tests/test_scale.py
    LogTransform, InvertedLogTransform,
    SymmetricalLogTransform)
 import matplotlib.scale as mscale
 from matplotlib.ticker import AsinhLocator, LogFormatterSciNotation
 from matplotlib.ticker import (
    AsinhLocator, AutoLocator, LogFormatterSciNotation,
    NullFormatter, NullLocator, ScalarFormatter
 )
 from matplotlib.testing.decorators import check_figures_equal, image_comparison
 from matplotlib.transforms import IdentityTransform

 import numpy as np
 from numpy.testing import assert_allclose
            AsinhScale(axis=None, linear_width=-1)
        s0 = AsinhScale(axis=None, )
        s1 = AsinhScale(axis=None, linear_width=3.0)


 def test_custom_scale_without_axis():
    """
    Test that one can register and use custom scales that don't take an *axis* param.
    """
    class CustomTransform(IdentityTransform):
        pass

    class CustomScale(mscale.ScaleBase):
        name = "custom"

        def __init__(self):
            self._transform = CustomTransform()

        def get_transform(self):
            return self._transform

        def set_default_locators_and_formatters(self, axis):
            axis.set_major_locator(AutoLocator())
            axis.set_major_formatter(ScalarFormatter())
            axis.set_minor_locator(NullLocator())
            axis.set_minor_formatter(NullFormatter())

    try:
        mscale.register_scale(CustomScale)
        fig, ax = plt.subplots()
        ax.set_xscale('custom')
        assert isinstance(ax.xaxis.get_transform(), CustomTransform)
    finally:
        # cleanup - there's no public unregister_scale()
        del mscale._scale_mapping["custom"]
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1,10 @@
		3rd party scales do not need to have an axis parameter anymore
		~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

		Since matplotlib 3.1 `PR 12831<https://github.com/matplotlib/matplotlib/pull/12831>`_
		scales should be reusable and therefore independent of the Axis. Therefore the use of
		of the axis parameter in the ``__init__`` had been discouraged. However, that
		parameter was still necessary for API compatibility. This is no longer the case.

		`.register_scale` now accepts scale classes with and without this parameter.
		3rd party scales can and should remove that parameter.
Original file line number	Diff line number	Diff line change
Expand Up		@@ -690,6 +690,9 @@ def limit_range_for_scale(self, vmin, vmax, minpos):
		'functionlog': FuncScaleLog,
		}

		# caching of signature info
		_scale_has_axis_parameter = {}


		def get_scale_names():
		"""Return the names of the available scales."""
Expand All		@@ -706,7 +709,19 @@ def scale_factory(scale, axis, **kwargs):
		axis : `~matplotlib.axis.Axis`
		"""
		scale_cls = _api.check_getitem(_scale_mapping, scale=scale)
		return scale_cls(axis, **kwargs)

		# We support scales that may or may not have an initial axis parameter.
		# This information is cached, so that we do not need to inspect the signature
		# on every time we create a scale.
		if scale not in _scale_has_axis_parameter:
		_scale_has_axis_parameter[scale] = (
		"axis" in inspect.signature(scale_cls).parameters
		)

		if _scale_has_axis_parameter[scale]:
		return scale_cls(axis, **kwargs)
		else:
		return scale_cls(**kwargs)


		if scale_factory.__doc__:
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -6,8 +6,12 @@
		LogTransform, InvertedLogTransform,
		SymmetricalLogTransform)
		import matplotlib.scale as mscale
		from matplotlib.ticker import AsinhLocator, LogFormatterSciNotation
		from matplotlib.ticker import (
		AsinhLocator, AutoLocator, LogFormatterSciNotation,
		NullFormatter, NullLocator, ScalarFormatter
		)
		from matplotlib.testing.decorators import check_figures_equal, image_comparison
		from matplotlib.transforms import IdentityTransform

		import numpy as np
		from numpy.testing import assert_allclose
Expand DownExpand Up		@@ -293,3 +297,35 @@ def test_bad_scale(self):
		AsinhScale(axis=None, linear_width=-1)
		s0 = AsinhScale(axis=None, )
		s1 = AsinhScale(axis=None, linear_width=3.0)


		def test_custom_scale_without_axis():
		"""
		Test that one can register and use custom scales that don't take an axis param.
		"""
		class CustomTransform(IdentityTransform):
		pass

		class CustomScale(mscale.ScaleBase):
		name = "custom"

		def __init__(self):
		self._transform = CustomTransform()

		def get_transform(self):
		return self._transform

		def set_default_locators_and_formatters(self, axis):
		axis.set_major_locator(AutoLocator())
		axis.set_major_formatter(ScalarFormatter())
		axis.set_minor_locator(NullLocator())
		axis.set_minor_formatter(NullFormatter())

		try:
		mscale.register_scale(CustomScale)
		fig, ax = plt.subplots()
		ax.set_xscale('custom')
		assert isinstance(ax.xaxis.get_transform(), CustomTransform)
		finally:
		# cleanup - there's no public unregister_scale()
		del mscale._scale_mapping["custom"]