up follow livre

venv/lib/python3.13/site-packages/matplotlib/scale.pyi

@@ -0,0 +1,178 @@
+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: ...