""" This type stub file was generated by pyright. """ from matplotlib.axis import Axis from matplotlib.transforms import Transform from collections.abc import Callable, Iterable from typing import Literal from numpy.typing import ArrayLike class ScaleBase: def __init__(self, axis: Axis | None) -> None: ... def get_transform(self) -> Transform: ... def set_default_locators_and_formatters(self, axis: Axis) -> None: ... def limit_range_for_scale(self, vmin: float, vmax: float, minpos: float) -> tuple[float, float]: ... class LinearScale(ScaleBase): name: str ... class FuncTransform(Transform): input_dims: int output_dims: int def __init__(self, forward: Callable[[ArrayLike], ArrayLike], inverse: Callable[[ArrayLike], ArrayLike]) -> None: ... def inverted(self) -> FuncTransform: ... class FuncScale(ScaleBase): name: str def __init__(self, axis: Axis | None, functions: tuple[Callable[[ArrayLike], ArrayLike], Callable[[ArrayLike], ArrayLike]]) -> None: ... class LogTransform(Transform): input_dims: int output_dims: int base: float def __init__(self, base: float, nonpositive: Literal["clip", "mask"] = ...) -> None: ... def inverted(self) -> InvertedLogTransform: ... class InvertedLogTransform(Transform): input_dims: int output_dims: int base: float def __init__(self, base: float) -> None: ... def inverted(self) -> LogTransform: ... class LogScale(ScaleBase): name: str subs: Iterable[int] | None def __init__(self, axis: Axis | None, *, base: float = ..., subs: Iterable[int] | None = ..., nonpositive: Literal["clip", "mask"] = ...) -> None: ... @property def base(self) -> float: ... def get_transform(self) -> Transform: ... class FuncScaleLog(LogScale): def __init__(self, axis: Axis | None, functions: tuple[Callable[[ArrayLike], ArrayLike], Callable[[ArrayLike], ArrayLike]], base: float = ...) -> None: ... @property def base(self) -> float: ... def get_transform(self) -> Transform: ... class SymmetricalLogTransform(Transform): input_dims: int output_dims: int base: float linthresh: float linscale: float def __init__(self, base: float, linthresh: float, linscale: float) -> None: ... def inverted(self) -> InvertedSymmetricalLogTransform: ... class InvertedSymmetricalLogTransform(Transform): input_dims: int output_dims: int base: float linthresh: float invlinthresh: float linscale: float def __init__(self, base: float, linthresh: float, linscale: float) -> None: ... def inverted(self) -> SymmetricalLogTransform: ... class SymmetricalLogScale(ScaleBase): name: str subs: Iterable[int] | None def __init__(self, axis: Axis | None, *, base: float = ..., linthresh: float = ..., subs: Iterable[int] | None = ..., linscale: float = ...) -> None: ... @property def base(self) -> float: ... @property def linthresh(self) -> float: ... @property def linscale(self) -> float: ... def get_transform(self) -> SymmetricalLogTransform: ... class AsinhTransform(Transform): input_dims: int output_dims: int linear_width: float def __init__(self, linear_width: float) -> None: ... def inverted(self) -> InvertedAsinhTransform: ... class InvertedAsinhTransform(Transform): input_dims: int output_dims: int linear_width: float def __init__(self, linear_width: float) -> None: ... def inverted(self) -> AsinhTransform: ... class AsinhScale(ScaleBase): name: str auto_tick_multipliers: dict[int, tuple[int, ...]] def __init__(self, axis: Axis | None, *, linear_width: float = ..., base: float = ..., subs: Iterable[int] | Literal["auto"] | None = ..., **kwargs) -> None: ... @property def linear_width(self) -> float: ... def get_transform(self) -> AsinhTransform: ... class LogitTransform(Transform): input_dims: int output_dims: int def __init__(self, nonpositive: Literal["mask", "clip"] = ...) -> None: ... def inverted(self) -> LogisticTransform: ... class LogisticTransform(Transform): input_dims: int output_dims: int def __init__(self, nonpositive: Literal["mask", "clip"] = ...) -> None: ... def inverted(self) -> LogitTransform: ... class LogitScale(ScaleBase): name: str def __init__(self, axis: Axis | None, nonpositive: Literal["mask", "clip"] = ..., *, one_half: str = ..., use_overline: bool = ...) -> 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: ...