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