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342 lines
12 KiB
Python
342 lines
12 KiB
Python
from .path import Path
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from .patches import Patch
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from .figure import Figure
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import numpy as np
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from numpy.typing import ArrayLike
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from collections.abc import Iterable, Sequence
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from typing import Literal
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DEBUG: bool
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class TransformNode:
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INVALID_NON_AFFINE: int
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INVALID_AFFINE: int
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INVALID: int
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is_bbox: bool
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# Implemented as a standard attr in base class, but functionally readonly and some subclasses implement as such
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@property
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def is_affine(self) -> bool: ...
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pass_through: bool
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def __init__(self, shorthand_name: str | None = ...) -> None: ...
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def __copy__(self) -> TransformNode: ...
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def invalidate(self) -> None: ...
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def set_children(self, *children: TransformNode) -> None: ...
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def frozen(self) -> TransformNode: ...
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class BboxBase(TransformNode):
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is_bbox: bool
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is_affine: bool
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def frozen(self) -> Bbox: ...
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def __array__(self, *args, **kwargs): ...
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@property
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def x0(self) -> float: ...
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@property
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def y0(self) -> float: ...
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@property
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def x1(self) -> float: ...
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@property
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def y1(self) -> float: ...
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@property
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def p0(self) -> tuple[float, float]: ...
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@property
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def p1(self) -> tuple[float, float]: ...
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@property
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def xmin(self) -> float: ...
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@property
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def ymin(self) -> float: ...
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@property
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def xmax(self) -> float: ...
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@property
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def ymax(self) -> float: ...
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@property
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def min(self) -> tuple[float, float]: ...
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@property
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def max(self) -> tuple[float, float]: ...
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@property
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def intervalx(self) -> tuple[float, float]: ...
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@property
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def intervaly(self) -> tuple[float, float]: ...
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@property
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def width(self) -> float: ...
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@property
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def height(self) -> float: ...
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@property
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def size(self) -> tuple[float, float]: ...
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@property
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def bounds(self) -> tuple[float, float, float, float]: ...
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@property
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def extents(self) -> tuple[float, float, float, float]: ...
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def get_points(self) -> np.ndarray: ...
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def containsx(self, x: float) -> bool: ...
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def containsy(self, y: float) -> bool: ...
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def contains(self, x: float, y: float) -> bool: ...
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def overlaps(self, other: BboxBase) -> bool: ...
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def fully_containsx(self, x: float) -> bool: ...
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def fully_containsy(self, y: float) -> bool: ...
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def fully_contains(self, x: float, y: float) -> bool: ...
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def fully_overlaps(self, other: BboxBase) -> bool: ...
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def transformed(self, transform: Transform) -> Bbox: ...
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coefs: dict[str, tuple[float, float]]
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def anchored(
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self,
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c: tuple[float, float] | Literal['C', 'SW', 'S', 'SE', 'E', 'NE', 'N', 'NW', 'W'],
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container: BboxBase,
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) -> Bbox: ...
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def shrunk(self, mx: float, my: float) -> Bbox: ...
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def shrunk_to_aspect(
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self,
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box_aspect: float,
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container: BboxBase | None = ...,
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fig_aspect: float = ...,
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) -> Bbox: ...
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def splitx(self, *args: float) -> list[Bbox]: ...
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def splity(self, *args: float) -> list[Bbox]: ...
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def count_contains(self, vertices: ArrayLike) -> int: ...
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def count_overlaps(self, bboxes: Iterable[BboxBase]) -> int: ...
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def expanded(self, sw: float, sh: float) -> Bbox: ...
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def padded(self, w_pad: float, h_pad: float | None = ...) -> Bbox: ...
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def translated(self, tx: float, ty: float) -> Bbox: ...
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def corners(self) -> np.ndarray: ...
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def rotated(self, radians: float) -> Bbox: ...
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@staticmethod
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def union(bboxes: Sequence[BboxBase]) -> Bbox: ...
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@staticmethod
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def intersection(bbox1: BboxBase, bbox2: BboxBase) -> Bbox | None: ...
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class Bbox(BboxBase):
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def __init__(self, points: ArrayLike, **kwargs) -> None: ...
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@staticmethod
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def unit() -> Bbox: ...
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@staticmethod
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def null() -> Bbox: ...
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@staticmethod
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def from_bounds(x0: float, y0: float, width: float, height: float) -> Bbox: ...
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@staticmethod
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def from_extents(*args: float, minpos: float | None = ...) -> Bbox: ...
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def __format__(self, fmt: str) -> str: ...
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def ignore(self, value: bool) -> None: ...
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def update_from_path(
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self,
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path: Path,
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ignore: bool | None = ...,
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updatex: bool = ...,
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updatey: bool = ...,
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) -> None: ...
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def update_from_data_x(self, x: ArrayLike, ignore: bool | None = ...) -> None: ...
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def update_from_data_y(self, y: ArrayLike, ignore: bool | None = ...) -> None: ...
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def update_from_data_xy(
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self,
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xy: ArrayLike,
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ignore: bool | None = ...,
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updatex: bool = ...,
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updatey: bool = ...,
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) -> None: ...
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@property
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def minpos(self) -> float: ...
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@property
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def minposx(self) -> float: ...
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@property
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def minposy(self) -> float: ...
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def get_points(self) -> np.ndarray: ...
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def set_points(self, points: ArrayLike) -> None: ...
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def set(self, other: Bbox) -> None: ...
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def mutated(self) -> bool: ...
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def mutatedx(self) -> bool: ...
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def mutatedy(self) -> bool: ...
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class TransformedBbox(BboxBase):
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def __init__(self, bbox: Bbox, transform: Transform, **kwargs) -> None: ...
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def get_points(self) -> np.ndarray: ...
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class LockableBbox(BboxBase):
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def __init__(
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self,
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bbox: BboxBase,
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x0: float | None = ...,
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y0: float | None = ...,
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x1: float | None = ...,
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y1: float | None = ...,
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**kwargs
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) -> None: ...
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@property
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def locked_x0(self) -> float | None: ...
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@locked_x0.setter
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def locked_x0(self, x0: float | None) -> None: ...
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@property
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def locked_y0(self) -> float | None: ...
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@locked_y0.setter
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def locked_y0(self, y0: float | None) -> None: ...
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@property
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def locked_x1(self) -> float | None: ...
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@locked_x1.setter
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def locked_x1(self, x1: float | None) -> None: ...
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@property
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def locked_y1(self) -> float | None: ...
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@locked_y1.setter
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def locked_y1(self, y1: float | None) -> None: ...
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class Transform(TransformNode):
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# Implemented as a standard attrs in base class, but functionally readonly and some subclasses implement as such
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@property
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def input_dims(self) -> int | None: ...
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@property
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def output_dims(self) -> int | None: ...
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@property
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def is_separable(self) -> bool: ...
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@property
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def has_inverse(self) -> bool: ...
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def __add__(self, other: Transform) -> Transform: ...
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@property
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def depth(self) -> int: ...
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def contains_branch(self, other: Transform) -> bool: ...
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def contains_branch_seperately(
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self, other_transform: Transform
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) -> Sequence[bool]: ...
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def __sub__(self, other: Transform) -> Transform: ...
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def __array__(self, *args, **kwargs) -> np.ndarray: ...
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def transform(self, values: ArrayLike) -> np.ndarray: ...
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def transform_affine(self, values: ArrayLike) -> np.ndarray: ...
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def transform_non_affine(self, values: ArrayLike) -> ArrayLike: ...
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def transform_bbox(self, bbox: BboxBase) -> Bbox: ...
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def get_affine(self) -> Transform: ...
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def get_matrix(self) -> np.ndarray: ...
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def transform_point(self, point: ArrayLike) -> np.ndarray: ...
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def transform_path(self, path: Path) -> Path: ...
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def transform_path_affine(self, path: Path) -> Path: ...
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def transform_path_non_affine(self, path: Path) -> Path: ...
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def transform_angles(
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self,
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angles: ArrayLike,
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pts: ArrayLike,
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radians: bool = ...,
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pushoff: float = ...,
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) -> np.ndarray: ...
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def inverted(self) -> Transform: ...
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class TransformWrapper(Transform):
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pass_through: bool
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def __init__(self, child: Transform) -> None: ...
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def __eq__(self, other: object) -> bool: ...
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def frozen(self) -> Transform: ...
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def set(self, child: Transform) -> None: ...
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class AffineBase(Transform):
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is_affine: Literal[True]
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def __init__(self, *args, **kwargs) -> None: ...
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def __eq__(self, other: object) -> bool: ...
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class Affine2DBase(AffineBase):
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input_dims: Literal[2]
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output_dims: Literal[2]
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def frozen(self) -> Affine2D: ...
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def to_values(self) -> tuple[float, float, float, float, float, float]: ...
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class Affine2D(Affine2DBase):
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def __init__(self, matrix: ArrayLike | None = ..., **kwargs) -> None: ...
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@staticmethod
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def from_values(
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a: float, b: float, c: float, d: float, e: float, f: float
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) -> Affine2D: ...
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def set_matrix(self, mtx: ArrayLike) -> None: ...
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def clear(self) -> Affine2D: ...
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def rotate(self, theta: float) -> Affine2D: ...
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def rotate_deg(self, degrees: float) -> Affine2D: ...
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def rotate_around(self, x: float, y: float, theta: float) -> Affine2D: ...
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def rotate_deg_around(self, x: float, y: float, degrees: float) -> Affine2D: ...
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def translate(self, tx: float, ty: float) -> Affine2D: ...
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def scale(self, sx: float, sy: float | None = ...) -> Affine2D: ...
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def skew(self, xShear: float, yShear: float) -> Affine2D: ...
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def skew_deg(self, xShear: float, yShear: float) -> Affine2D: ...
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class IdentityTransform(Affine2DBase): ...
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class _BlendedMixin:
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def __eq__(self, other: object) -> bool: ...
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def contains_branch_seperately(self, transform: Transform) -> Sequence[bool]: ...
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class BlendedGenericTransform(_BlendedMixin, Transform):
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input_dims: Literal[2]
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output_dims: Literal[2]
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pass_through: bool
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def __init__(
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self, x_transform: Transform, y_transform: Transform, **kwargs
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) -> None: ...
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@property
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def depth(self) -> int: ...
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def contains_branch(self, other: Transform) -> Literal[False]: ...
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@property
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def is_affine(self) -> bool: ...
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class BlendedAffine2D(_BlendedMixin, Affine2DBase):
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def __init__(
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self, x_transform: Transform, y_transform: Transform, **kwargs
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) -> None: ...
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def blended_transform_factory(
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x_transform: Transform, y_transform: Transform
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) -> BlendedGenericTransform | BlendedAffine2D: ...
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class CompositeGenericTransform(Transform):
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pass_through: bool
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def __init__(self, a: Transform, b: Transform, **kwargs) -> None: ...
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class CompositeAffine2D(Affine2DBase):
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def __init__(self, a: Affine2DBase, b: Affine2DBase, **kwargs) -> None: ...
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@property
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def depth(self) -> int: ...
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def composite_transform_factory(a: Transform, b: Transform) -> Transform: ...
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class BboxTransform(Affine2DBase):
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def __init__(self, boxin: BboxBase, boxout: BboxBase, **kwargs) -> None: ...
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class BboxTransformTo(Affine2DBase):
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def __init__(self, boxout: BboxBase, **kwargs) -> None: ...
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class BboxTransformToMaxOnly(BboxTransformTo): ...
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class BboxTransformFrom(Affine2DBase):
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def __init__(self, boxin: BboxBase, **kwargs) -> None: ...
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class ScaledTranslation(Affine2DBase):
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def __init__(
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self, xt: float, yt: float, scale_trans: Affine2DBase, **kwargs
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) -> None: ...
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class AffineDeltaTransform(Affine2DBase):
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def __init__(self, transform: Affine2DBase, **kwargs) -> None: ...
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class TransformedPath(TransformNode):
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def __init__(self, path: Path, transform: Transform) -> None: ...
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def get_transformed_points_and_affine(self) -> tuple[Path, Transform]: ...
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def get_transformed_path_and_affine(self) -> tuple[Path, Transform]: ...
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def get_fully_transformed_path(self) -> Path: ...
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def get_affine(self) -> Transform: ...
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class TransformedPatchPath(TransformedPath):
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def __init__(self, patch: Patch) -> None: ...
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def nonsingular(
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vmin: float,
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vmax: float,
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expander: float = ...,
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tiny: float = ...,
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increasing: bool = ...,
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) -> tuple[float, float]: ...
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def interval_contains(interval: tuple[float, float], val: float) -> bool: ...
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def interval_contains_open(interval: tuple[float, float], val: float) -> bool: ...
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def offset_copy(
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trans: Transform,
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fig: Figure | None = ...,
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x: float = ...,
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y: float = ...,
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units: Literal["inches", "points", "dots"] = ...,
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) -> Transform: ...
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class _ScaledRotation(Affine2DBase):
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def __init__(self, theta: float, trans_shift: Transform) -> None: ...
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def get_matrix(self) -> np.ndarray: ...
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