from typing import Any, Callable, Literal, Sequence from ._typing import * from .axis import Axis from .transforms import Transform class ScaleBase: def __init__(self, axis: Axis) -> None: ... def get_transform(self) -> Transform: ... def set_default_locators_and_formatters(self, axis: Axis): ... def limit_range_for_scale(self, vmin: float, vmax: float, minpos: float): ... class LinearScale(ScaleBase): name = ... def __init__(self, axis: Axis) -> None: ... def set_default_locators_and_formatters(self, axis: Axis): ... def get_transform(self) -> Transform: ... class FuncTransform(Transform): input_dims = ... def __init__(self, forward: Callable, inverse: Callable) -> None: ... def transform_non_affine(self, values: ArrayLike) -> list: ... def inverted(self): ... class FuncScale(ScaleBase): name = ... def __init__(self, axis: Axis, functions: Sequence[Callable]) -> None: ... def get_transform(self) -> FuncTransform: ... def set_default_locators_and_formatters(self, axis): ... class LogTransform(Transform): input_dims = ... def __init__(self, base, nonpositive: Literal["clip", "mask"] = "clip") -> None: ... def __str__(self) -> str: ... def transform_non_affine(self, a) -> list: ... def inverted(self): ... class InvertedLogTransform(Transform): input_dims = ... def __init__(self, base) -> None: ... def __str__(self) -> str: ... def transform_non_affine(self, a) -> list: ... def inverted(self): ... class LogScale(ScaleBase): name = ... def __init__( self, axis: Axis, *, base: float = 10, subs=Sequence[int], nonpositive: Literal["clip", "mask"] = "clip" ) -> None: ... base = ... def set_default_locators_and_formatters(self, axis: Axis): ... def get_transform(self) -> LogTransform: ... def limit_range_for_scale(self, vmin: float, vmax: float, minpos: float): ... class FuncScaleLog(LogScale): name = ... def __init__(self, axis: Axis, functions: Sequence[Callable], base: float = 10) -> None: ... @property def base(self): ... def get_transform(self) -> Transform: ... class SymmetricalLogTransform(Transform): input_dims = ... def __init__(self, base, linthresh, linscale) -> None: ... def transform_non_affine(self, a) -> list: ... def inverted(self): ... class InvertedSymmetricalLogTransform(Transform): input_dims = ... def __init__(self, base, linthresh, linscale) -> None: ... def transform_non_affine(self, a) -> list: ... def inverted(self): ... class SymmetricalLogScale(ScaleBase): name = ... def __init__( self, axis: Axis, *, base: float = 10, linthresh: float = 2, subs: Sequence[int] = ..., linscale: float = ... ) -> None: ... base = ... linthresh = ... linscale = ... def set_default_locators_and_formatters(self, axis: Axis): ... def get_transform(self) -> SymmetricalLogTransform: ... class AsinhTransform(Transform): input_dims = ... def __init__(self, linear_width) -> None: ... def transform_non_affine(self, a) -> list: ... def inverted(self): ... class InvertedAsinhTransform(Transform): input_dims = ... def __init__(self, linear_width) -> None: ... def transform_non_affine(self, a) -> list: ... def inverted(self): ... class AsinhScale(ScaleBase): name = ... auto_tick_multipliers = ... def __init__(self, axis: Axis, *, linear_width: float = 1, base: float = 10, subs: Sequence[int] = ..., **kwargs) -> None: ... linear_width = ... def get_transform(self): ... def set_default_locators_and_formatters(self, axis): ... class LogitTransform(Transform): input_dims = ... def __init__(self, nonpositive: Literal["mask", "clip"] = ...) -> None: ... def transform_non_affine(self, a): ... def inverted(self): ... def __str__(self) -> str: ... class LogisticTransform(Transform): input_dims = ... def __init__(self, nonpositive: Literal["mask", "clip"] = ...) -> None: ... def transform_non_affine(self, a): ... def inverted(self): ... def __str__(self) -> str: ... class LogitScale(ScaleBase): name = ... def __init__( self, axis: Axis, nonpositive: Literal["mask", "clip"] = ..., *, one_half: str = ..., use_overline=... ) -> None: ... def get_transform(self) -> LogitTransform: ... def set_default_locators_and_formatters(self, axis: Axis): ... def limit_range_for_scale(self, vmin: float, vmax: float, minpos: float): ... def get_scale_names(): ... def scale_factory( scale: Literal["asinh", "function", "functionlog", "linear", "log", "logit", "symlog"], axis: Axis, **kwargs ): ... def register_scale(scale_class): ...