nvim_config/typings/matplotlib/scale.pyi

"""
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:
    ...