team-10/env/Lib/site-packages/numpy/lib/_stride_tricks_impl.pyi
2025-08-02 07:34:44 +02:00

74 lines
1.8 KiB
Python

from collections.abc import Iterable
from typing import Any, SupportsIndex, TypeVar, overload
from numpy import generic
from numpy._typing import ArrayLike, NDArray, _AnyShape, _ArrayLike, _ShapeLike
__all__ = ["broadcast_to", "broadcast_arrays", "broadcast_shapes"]
_ScalarT = TypeVar("_ScalarT", bound=generic)
class DummyArray:
__array_interface__: dict[str, Any]
base: NDArray[Any] | None
def __init__(
self,
interface: dict[str, Any],
base: NDArray[Any] | None = ...,
) -> None: ...
@overload
def as_strided(
x: _ArrayLike[_ScalarT],
shape: Iterable[int] | None = ...,
strides: Iterable[int] | None = ...,
subok: bool = ...,
writeable: bool = ...,
) -> NDArray[_ScalarT]: ...
@overload
def as_strided(
x: ArrayLike,
shape: Iterable[int] | None = ...,
strides: Iterable[int] | None = ...,
subok: bool = ...,
writeable: bool = ...,
) -> NDArray[Any]: ...
@overload
def sliding_window_view(
x: _ArrayLike[_ScalarT],
window_shape: int | Iterable[int],
axis: SupportsIndex | None = ...,
*,
subok: bool = ...,
writeable: bool = ...,
) -> NDArray[_ScalarT]: ...
@overload
def sliding_window_view(
x: ArrayLike,
window_shape: int | Iterable[int],
axis: SupportsIndex | None = ...,
*,
subok: bool = ...,
writeable: bool = ...,
) -> NDArray[Any]: ...
@overload
def broadcast_to(
array: _ArrayLike[_ScalarT],
shape: int | Iterable[int],
subok: bool = ...,
) -> NDArray[_ScalarT]: ...
@overload
def broadcast_to(
array: ArrayLike,
shape: int | Iterable[int],
subok: bool = ...,
) -> NDArray[Any]: ...
def broadcast_shapes(*args: _ShapeLike) -> _AnyShape: ...
def broadcast_arrays(
*args: ArrayLike,
subok: bool = ...,
) -> tuple[NDArray[Any], ...]: ...