Apr 29, 2025 · May 13, 2025 · May 13, 2025 · May 13, 2025 · May 13, 2025 · May 13, 2025
diff --git a/lib/matplotlib/scale.py b/lib/matplotlib/scale.py

 import inspect
 import textwrap
 from functools import wraps

 import numpy as np

        return vmin, vmax


 def _make_axis_parameter_optional(init_func):
    """
    Decorator to allow leaving out the *axis* parameter in scale constructors.

    This decorator ensures backward compatibility for scale classes that
    previously required an *axis* parameter. It allows constructors to be
    callerd with or without the *axis* parameter.

    For simplicity, this does not handle the case when *axis*
    is passed as a keyword. However,
    scanning GitHub, there's no evidence that that is used anywhere.

    Parameters
    ----------
    init_func : callable
        The original __init__ method of a scale class.

    Returns
    -------
    callable
        A wrapped version of *init_func* that handles the optional *axis*.

    Notes
    -----
    If the wrapped constructor defines *axis* as its first argument, the
    parameter is preserved when present. Otherwise, the value `None` is injected
    as the first argument.

    Examples
    --------
    >>> from matplotlib.scale import ScaleBase
    >>> class CustomScale(ScaleBase):
    ...     @_make_axis_parameter_optional
    ...     def __init__(self, axis, custom_param=1):
    ...         self.custom_param = custom_param
    """
    @wraps(init_func)
    def wrapper(self, *args, **kwargs):
        if args and isinstance(args[0], mpl.axis.Axis):
            return init_func(self, *args, **kwargs)
        else:
            # Remove 'axis' from kwargs to avoid double assignment
            kwargs.pop('axis', None)
            return init_func(self, None, *args, **kwargs)
    return wrapper


 class LinearScale(ScaleBase):
    """
    The default linear scale.
    """

    name = 'linear'

    @_make_axis_parameter_optional
    def __init__(self, axis):
        # This method is present only to prevent inheritance of the base class'
        # constructor docstring, which would otherwise end up interpolated into

    name = 'function'

    @_make_axis_parameter_optional
    def __init__(self, axis, functions):
        """
        Parameters
    """
    name = 'log'

    def __init__(self, axis, *, base=10, subs=None, nonpositive="clip"):
    @_make_axis_parameter_optional
    def __init__(self, axis=None, *, base=10, subs=None, nonpositive="clip"):
        """
        Parameters
        ----------

    name = 'functionlog'

    @_make_axis_parameter_optional
    def __init__(self, axis, functions, base=10):
        """
        Parameters
    """
    name = 'symlog'

    def __init__(self, axis, *, base=10, linthresh=2, subs=None, linscale=1):
    @_make_axis_parameter_optional
    def __init__(self, axis=None, *, base=10, linthresh=2, subs=None, linscale=1):
        self._transform = SymmetricalLogTransform(base, linthresh, linscale)
        self.subs = subs

        1024: (256, 512)
    }

    def __init__(self, axis, *, linear_width=1.0,
    @_make_axis_parameter_optional
    def __init__(self, axis=None, *, linear_width=1.0,
                 base=10, subs='auto', **kwargs):
        """
        Parameters
    """
    name = 'logit'

    def __init__(self, axis, nonpositive='mask', *,
    @_make_axis_parameter_optional
    def __init__(self, axis=None, nonpositive='mask', *,
                 one_half=r"\frac{1}{2}", use_overline=False):
        r"""
        Parameters
diff --git a/lib/matplotlib/scale.pyi b/lib/matplotlib/scale.pyi
 from matplotlib.transforms import Transform

 from collections.abc import Callable, Iterable
 from typing import Literal
 from typing import Literal, Union
 from numpy.typing import ArrayLike

 class ScaleBase:

 class LinearScale(ScaleBase):
    name: str
    def __init__(self: ScaleBase, axis: Union[Axis, None] = None) -> None: ...

 class FuncTransform(Transform):
    input_dims: int
    name: str
    subs: Iterable[int] | None
    def __init__(
        self,
        axis: Axis | None,
        self: LogScale,
        axis: Axis | None = ...,
        *,
        base: float =...,
        subs: Iterable[int] |None =...,
        nonpositive: Literal["clip", "mask"] =...
        base: float =10,
        subs:Union[Iterable[int],None] =None,
        nonpositive:Union[Literal['clip'], Literal['mask']] ='clip'
    ) -> None: ...
    @property
    def base(self) -> float: ...
    subs: Iterable[int] | None
    def __init__(
        self,
        axis: Axis | None,
        axis: Axis | None = ...,
        *,
        base: float =...,
        linthresh: float =...,
        subs: Iterable[int] |None =...,
        linscale: float =...
        base: float =10,
        linthresh: float =2,
        subs:Union[Iterable[int],None] =None,
        linscale: float =1
    ) -> None: ...
    @property
    def base(self) -> float: ...
    auto_tick_multipliers: dict[int, tuple[int, ...]]
    def __init__(
        self,
        axis: Axis | None,
        axis: Axis | None = ...,
        *,
        linear_width: float = ...,
        base: float = ...,
    name: str
    def __init__(
        self,
        axis: Axis | None,
        nonpositive: Literal["mask", "clip"] =...,
        axis: Axis | None = ...,
        nonpositive:Union[Literal['mask'], Literal['clip']] ='mask',
        *,
        one_half: str =...,
        use_overline: bool =...
        one_half: str ='\\frac{1}{2}',
        use_overline: bool =False
    ) -> None: ...
    def get_transform(self) -> LogitTransform: ...

 def get_scale_names() -> list[str]: ...
 def scale_factory(scale: str, axis: Axis, **kwargs) -> ScaleBase: ...
 def register_scale(scale_class: type[ScaleBase]) -> None: ...
 def handle_axis_parameter(init_func: Callable[..., None]) -> Callable[..., None]: ...
Original file line number	Diff line number	Diff line change
Expand Up		@@ -31,6 +31,7 @@

		import inspect
		import textwrap
		from functools import wraps

		import numpy as np

Expand DownExpand Up		@@ -103,13 +104,61 @@ def limit_range_for_scale(self, vmin, vmax, minpos):
		return vmin, vmax


		def _make_axis_parameter_optional(init_func):
		"""
		Decorator to allow leaving out the axis parameter in scale constructors.

		This decorator ensures backward compatibility for scale classes that
		previously required an axis parameter. It allows constructors to be
		callerd with or without the axis parameter.

		For simplicity, this does not handle the case when axis
		is passed as a keyword. However,
		scanning GitHub, there's no evidence that that is used anywhere.

		Parameters
		----------
		init_func : callable
		The original __init__ method of a scale class.

		Returns
		-------
		callable
		A wrapped version of init_func that handles the optional axis.

		Notes
		-----
		If the wrapped constructor defines axis as its first argument, the
		parameter is preserved when present. Otherwise, the value `None` is injected
		as the first argument.

		Examples
		--------
		>>> from matplotlib.scale import ScaleBase
		>>> class CustomScale(ScaleBase):
		... @_make_axis_parameter_optional
		... def __init__(self, axis, custom_param=1):
		... self.custom_param = custom_param
		"""
		@wraps(init_func)
		def wrapper(self, args, *kwargs):
		if args and isinstance(args[0], mpl.axis.Axis):
		return init_func(self, args, *kwargs)
		else:
		# Remove 'axis' from kwargs to avoid double assignment
		kwargs.pop('axis', None)
		return init_func(self, None, args, *kwargs)
		return wrapper


		class LinearScale(ScaleBase):
		"""
		The default linear scale.
		"""

		name = 'linear'

		@_make_axis_parameter_optional
		def __init__(self, axis):
		# This method is present only to prevent inheritance of the base class'
		# constructor docstring, which would otherwise end up interpolated into
Expand DownExpand Up		@@ -180,6 +229,7 @@ class FuncScale(ScaleBase):

		name = 'function'

		@_make_axis_parameter_optional
		def __init__(self, axis, functions):
		"""
		Parameters
Expand DownExpand Up		@@ -279,7 +329,8 @@ class LogScale(ScaleBase):
		"""
		name = 'log'

		def __init__(self, axis, *, base=10, subs=None, nonpositive="clip"):
		@_make_axis_parameter_optional
		def __init__(self, axis=None, *, base=10, subs=None, nonpositive="clip"):
		"""
		Parameters
		----------
Expand DownExpand Up		@@ -330,6 +381,7 @@ class FuncScaleLog(LogScale):

		name = 'functionlog'

		@_make_axis_parameter_optional
		def __init__(self, axis, functions, base=10):
		"""
		Parameters
Expand DownExpand Up		@@ -455,7 +507,8 @@ class SymmetricalLogScale(ScaleBase):
		"""
		name = 'symlog'

		def __init__(self, axis, *, base=10, linthresh=2, subs=None, linscale=1):
		@_make_axis_parameter_optional
		def __init__(self, axis=None, *, base=10, linthresh=2, subs=None, linscale=1):
		self._transform = SymmetricalLogTransform(base, linthresh, linscale)
		self.subs = subs

Expand DownExpand Up		@@ -547,7 +600,8 @@ class AsinhScale(ScaleBase):
		1024: (256, 512)
		}

		def __init__(self, axis, *, linear_width=1.0,
		@_make_axis_parameter_optional
		def __init__(self, axis=None, *, linear_width=1.0,
		base=10, subs='auto', **kwargs):
		"""
		Parameters
Expand DownExpand Up		@@ -645,7 +699,8 @@ class LogitScale(ScaleBase):
		"""
		name = 'logit'

		def __init__(self, axis, nonpositive='mask', *,
		@_make_axis_parameter_optional
		def __init__(self, axis=None, nonpositive='mask', *,
		one_half=r"\frac{1}{2}", use_overline=False):
		r"""
		Parameters
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -2,7 +2,7 @@ from matplotlib.axis import Axis
		from matplotlib.transforms import Transform

		from collections.abc import Callable, Iterable
		from typing import Literal
		from typing import Literal, Union
		from numpy.typing import ArrayLike

		class ScaleBase:
Expand All		@@ -15,6 +15,7 @@ class ScaleBase:

		class LinearScale(ScaleBase):
		name: str
		def __init__(self: ScaleBase, axis: Union[Axis, None] = None) -> None: ...

		class FuncTransform(Transform):
		input_dims: int
Expand DownExpand Up		@@ -56,12 +57,12 @@ class LogScale(ScaleBase):
		name: str
		subs: Iterable[int] \| None
		def __init__(
		self,
		axis: Axis \| None,
		self: LogScale,
vagnermcj marked this conversation as resolved. Show resolvedHide resolved
		axis: Axis \| None = ...,
		*,
		base: float =...,
		subs: Iterable[int] \|None =...,
		nonpositive: Literal["clip", "mask"] =...
		base: float =10,
		subs:Union[Iterable[int],None] =None,
		nonpositive:Union[Literal['clip'], Literal['mask']] ='clip'
		) -> None: ...
		@property
		def base(self) -> float: ...
Expand DownExpand Up		@@ -104,12 +105,12 @@ class SymmetricalLogScale(ScaleBase):
		subs: Iterable[int] \| None
		def __init__(
		self,
		axis: Axis \| None,
		axis: Axis \| None = ...,
		*,
		base: float =...,
		linthresh: float =...,
		subs: Iterable[int] \|None =...,
		linscale: float =...
		base: float =10,
		linthresh: float =2,
		subs:Union[Iterable[int],None] =None,
		linscale: float =1
		) -> None: ...
		@property
		def base(self) -> float: ...
Expand DownExpand Up		@@ -138,7 +139,7 @@ class AsinhScale(ScaleBase):
		auto_tick_multipliers: dict[int, tuple[int, ...]]
		def __init__(
		self,
		axis: Axis \| None,
		axis: Axis \| None = ...,
		*,
		linear_width: float = ...,
		base: float = ...,
Expand All		@@ -165,14 +166,15 @@ class LogitScale(ScaleBase):
		name: str
		def __init__(
		self,
		axis: Axis \| None,
		nonpositive: Literal["mask", "clip"] =...,
		axis: Axis \| None = ...,
		nonpositive:Union[Literal['mask'], Literal['clip']] ='mask',
		*,
		one_half: str =...,
		use_overline: bool =...
		one_half: str ='\\frac{1}{2}',
		use_overline: bool =False
		) -> None: ...
		def get_transform(self) -> LogitTransform: ...

		def get_scale_names() -> list[str]: ...
		def scale_factory(scale: str, axis: Axis, **kwargs) -> ScaleBase: ...
		def register_scale(scale_class: type[ScaleBase]) -> None: ...
		def handle_axis_parameter(init_func: Callable[..., None]) -> Callable[..., None]: ...