MNT: Registered 3rd party scales do not need an axis parameter anymore

First step of matplotlib#29349.

Author: timhoffm

doc/api/next_api_changes/deprecations/29358-TH.rst

@@ -0,0 +1,16 @@
+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.
+
+The *axis* parameter is pending-deprecated. It will be deprecated in matplotlib 3.13,
+and removed in matplotlib 3.15.
+
+3rd-party scales are recommended to remove the *axis* parameter now if they can
+afford to restrict compatibility to matplotlib >= 3.11 already. Otherwise, they may
+keep the *axis* parameter and remove it in time for matplotlib 3.13.

lib/matplotlib/scale.py

@@ -77,10 +77,18 @@ def __init__(self, axis):
         For back-compatibility reasons, scales take an `~matplotlib.axis.Axis`
         object as the first argument.
 
-        The current recommendation for `.ScaleBase` subclasses is to have the
-        *axis* parameter for API compatibility, but not make use of it. This is
-        because we plan to remove this argument to make a scale object usable
-        by multiple `~matplotlib.axis.Axis`\es at the same time.
+        .. deprecated:: 3.11
+
+           The *axis* parameter is now optional, i.e. matplotlib is compatible
+           with `.ScaleBase` subclasses that do not take an *axis* parameter.
+
+           The *axis* parameter is pending-deprecated. It will be deprecated
+           in matplotlib 3.13, and removed in matplotlib 3.15.
+
+           3rd-party scales are recommended to remove the *axis* parameter now
+           if they can afford to restrict compatibility to matplotlib >= 3.11
+           already. Otherwise, they may keep the *axis* parameter and remove it
+           in time for matplotlib 3.13.
         """
 
     def get_transform(self):
@@ -801,6 +809,20 @@ def limit_range_for_scale(self, vmin, vmax, minpos):
     'functionlog': FuncScaleLog,
     }
 
+# caching of signature info
+# For backward compatibility, the built-in scales will keep the *axis* parameter
+# in their constructors until matplotlib 3.15, i.e. as long as the *axis* parameter
+# is still supported.
+_scale_has_axis_parameter = {
+    'linear': True,
+    'log': True,
+    'symlog': True,
+    'asinh': True,
+    'logit': True,
+    'function': True,
+    'functionlog': True,
+}
+
 
 def get_scale_names():
     """Return the names of the available scales."""
@@ -817,7 +839,11 @@ def scale_factory(scale, axis, **kwargs):
     axis : `~matplotlib.axis.Axis`
     """
     scale_cls = _api.check_getitem(_scale_mapping, scale=scale)
-    return scale_cls(axis, **kwargs)
+
+    if _scale_has_axis_parameter[scale]:
+        return scale_cls(axis, **kwargs)
+    else:
+        return scale_cls(**kwargs)
 
 
 if scale_factory.__doc__:
@@ -836,6 +862,20 @@ def register_scale(scale_class):
     """
     _scale_mapping[scale_class.name] = scale_class
 
+    # migration code to handle the *axis* parameter
+    has_axis_parameter = "axis" in inspect.signature(scale_class).parameters
+    _scale_has_axis_parameter[scale_class.name] = has_axis_parameter
+    if has_axis_parameter:
+        _api.warn_deprecated(
+            "3.11",
+            message=f"The scale {scale_class.__qualname__!r} uses an 'axis' parameter "
+                    "in the constructors. This parameter is pending-deprecated since "
+                    "matplotlib 3.11. It will be fully deprecated in 3.13 and removed "
+                    "in 3.15. Starting with 3.11, 'register_scale()' accepts scales "
+                    "without the *axis* parameter.",
+            pending=True,
+        )
+
 
 def _get_scale_docs():
     """

lib/matplotlib/tests/test_scale.py

@@ -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
@@ -295,3 +299,35 @@ 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"]