You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
221 lines
5.4 KiB
221 lines
5.4 KiB
import sys
|
|
from collections.abc import Callable, Sequence
|
|
from typing import TypeVar, Any, overload, SupportsIndex, Protocol
|
|
|
|
if sys.version_info >= (3, 10):
|
|
from typing import ParamSpec, Concatenate
|
|
else:
|
|
from typing_extensions import ParamSpec, Concatenate
|
|
|
|
from numpy import (
|
|
generic,
|
|
integer,
|
|
ufunc,
|
|
bool_,
|
|
unsignedinteger,
|
|
signedinteger,
|
|
floating,
|
|
complexfloating,
|
|
object_,
|
|
)
|
|
|
|
from numpy._typing import (
|
|
ArrayLike,
|
|
NDArray,
|
|
_ShapeLike,
|
|
_ArrayLike,
|
|
_ArrayLikeBool_co,
|
|
_ArrayLikeUInt_co,
|
|
_ArrayLikeInt_co,
|
|
_ArrayLikeFloat_co,
|
|
_ArrayLikeComplex_co,
|
|
_ArrayLikeObject_co,
|
|
)
|
|
|
|
from numpy.core.shape_base import vstack
|
|
|
|
_P = ParamSpec("_P")
|
|
_SCT = TypeVar("_SCT", bound=generic)
|
|
|
|
# The signatures of `__array_wrap__` and `__array_prepare__` are the same;
|
|
# give them unique names for the sake of clarity
|
|
class _ArrayWrap(Protocol):
|
|
def __call__(
|
|
self,
|
|
array: NDArray[Any],
|
|
context: None | tuple[ufunc, tuple[Any, ...], int] = ...,
|
|
/,
|
|
) -> Any: ...
|
|
|
|
class _ArrayPrepare(Protocol):
|
|
def __call__(
|
|
self,
|
|
array: NDArray[Any],
|
|
context: None | tuple[ufunc, tuple[Any, ...], int] = ...,
|
|
/,
|
|
) -> Any: ...
|
|
|
|
class _SupportsArrayWrap(Protocol):
|
|
@property
|
|
def __array_wrap__(self) -> _ArrayWrap: ...
|
|
|
|
class _SupportsArrayPrepare(Protocol):
|
|
@property
|
|
def __array_prepare__(self) -> _ArrayPrepare: ...
|
|
|
|
__all__: list[str]
|
|
|
|
row_stack = vstack
|
|
|
|
def take_along_axis(
|
|
arr: _SCT | NDArray[_SCT],
|
|
indices: NDArray[integer[Any]],
|
|
axis: None | int,
|
|
) -> NDArray[_SCT]: ...
|
|
|
|
def put_along_axis(
|
|
arr: NDArray[_SCT],
|
|
indices: NDArray[integer[Any]],
|
|
values: ArrayLike,
|
|
axis: None | int,
|
|
) -> None: ...
|
|
|
|
@overload
|
|
def apply_along_axis(
|
|
func1d: Callable[Concatenate[NDArray[Any], _P], _ArrayLike[_SCT]],
|
|
axis: SupportsIndex,
|
|
arr: ArrayLike,
|
|
*args: _P.args,
|
|
**kwargs: _P.kwargs,
|
|
) -> NDArray[_SCT]: ...
|
|
@overload
|
|
def apply_along_axis(
|
|
func1d: Callable[Concatenate[NDArray[Any], _P], ArrayLike],
|
|
axis: SupportsIndex,
|
|
arr: ArrayLike,
|
|
*args: _P.args,
|
|
**kwargs: _P.kwargs,
|
|
) -> NDArray[Any]: ...
|
|
|
|
def apply_over_axes(
|
|
func: Callable[[NDArray[Any], int], NDArray[_SCT]],
|
|
a: ArrayLike,
|
|
axes: int | Sequence[int],
|
|
) -> NDArray[_SCT]: ...
|
|
|
|
@overload
|
|
def expand_dims(
|
|
a: _ArrayLike[_SCT],
|
|
axis: _ShapeLike,
|
|
) -> NDArray[_SCT]: ...
|
|
@overload
|
|
def expand_dims(
|
|
a: ArrayLike,
|
|
axis: _ShapeLike,
|
|
) -> NDArray[Any]: ...
|
|
|
|
@overload
|
|
def column_stack(tup: Sequence[_ArrayLike[_SCT]]) -> NDArray[_SCT]: ...
|
|
@overload
|
|
def column_stack(tup: Sequence[ArrayLike]) -> NDArray[Any]: ...
|
|
|
|
@overload
|
|
def dstack(tup: Sequence[_ArrayLike[_SCT]]) -> NDArray[_SCT]: ...
|
|
@overload
|
|
def dstack(tup: Sequence[ArrayLike]) -> NDArray[Any]: ...
|
|
|
|
@overload
|
|
def array_split(
|
|
ary: _ArrayLike[_SCT],
|
|
indices_or_sections: _ShapeLike,
|
|
axis: SupportsIndex = ...,
|
|
) -> list[NDArray[_SCT]]: ...
|
|
@overload
|
|
def array_split(
|
|
ary: ArrayLike,
|
|
indices_or_sections: _ShapeLike,
|
|
axis: SupportsIndex = ...,
|
|
) -> list[NDArray[Any]]: ...
|
|
|
|
@overload
|
|
def split(
|
|
ary: _ArrayLike[_SCT],
|
|
indices_or_sections: _ShapeLike,
|
|
axis: SupportsIndex = ...,
|
|
) -> list[NDArray[_SCT]]: ...
|
|
@overload
|
|
def split(
|
|
ary: ArrayLike,
|
|
indices_or_sections: _ShapeLike,
|
|
axis: SupportsIndex = ...,
|
|
) -> list[NDArray[Any]]: ...
|
|
|
|
@overload
|
|
def hsplit(
|
|
ary: _ArrayLike[_SCT],
|
|
indices_or_sections: _ShapeLike,
|
|
) -> list[NDArray[_SCT]]: ...
|
|
@overload
|
|
def hsplit(
|
|
ary: ArrayLike,
|
|
indices_or_sections: _ShapeLike,
|
|
) -> list[NDArray[Any]]: ...
|
|
|
|
@overload
|
|
def vsplit(
|
|
ary: _ArrayLike[_SCT],
|
|
indices_or_sections: _ShapeLike,
|
|
) -> list[NDArray[_SCT]]: ...
|
|
@overload
|
|
def vsplit(
|
|
ary: ArrayLike,
|
|
indices_or_sections: _ShapeLike,
|
|
) -> list[NDArray[Any]]: ...
|
|
|
|
@overload
|
|
def dsplit(
|
|
ary: _ArrayLike[_SCT],
|
|
indices_or_sections: _ShapeLike,
|
|
) -> list[NDArray[_SCT]]: ...
|
|
@overload
|
|
def dsplit(
|
|
ary: ArrayLike,
|
|
indices_or_sections: _ShapeLike,
|
|
) -> list[NDArray[Any]]: ...
|
|
|
|
@overload
|
|
def get_array_prepare(*args: _SupportsArrayPrepare) -> _ArrayPrepare: ...
|
|
@overload
|
|
def get_array_prepare(*args: object) -> None | _ArrayPrepare: ...
|
|
|
|
@overload
|
|
def get_array_wrap(*args: _SupportsArrayWrap) -> _ArrayWrap: ...
|
|
@overload
|
|
def get_array_wrap(*args: object) -> None | _ArrayWrap: ...
|
|
|
|
@overload
|
|
def kron(a: _ArrayLikeBool_co, b: _ArrayLikeBool_co) -> NDArray[bool_]: ... # type: ignore[misc]
|
|
@overload
|
|
def kron(a: _ArrayLikeUInt_co, b: _ArrayLikeUInt_co) -> NDArray[unsignedinteger[Any]]: ... # type: ignore[misc]
|
|
@overload
|
|
def kron(a: _ArrayLikeInt_co, b: _ArrayLikeInt_co) -> NDArray[signedinteger[Any]]: ... # type: ignore[misc]
|
|
@overload
|
|
def kron(a: _ArrayLikeFloat_co, b: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ... # type: ignore[misc]
|
|
@overload
|
|
def kron(a: _ArrayLikeComplex_co, b: _ArrayLikeComplex_co) -> NDArray[complexfloating[Any, Any]]: ...
|
|
@overload
|
|
def kron(a: _ArrayLikeObject_co, b: Any) -> NDArray[object_]: ...
|
|
@overload
|
|
def kron(a: Any, b: _ArrayLikeObject_co) -> NDArray[object_]: ...
|
|
|
|
@overload
|
|
def tile(
|
|
A: _ArrayLike[_SCT],
|
|
reps: int | Sequence[int],
|
|
) -> NDArray[_SCT]: ...
|
|
@overload
|
|
def tile(
|
|
A: ArrayLike,
|
|
reps: int | Sequence[int],
|
|
) -> NDArray[Any]: ...
|