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File/Folder	Size	Actions
__init__.py	2.7 KB	Del OK
__init__.pyi	5.46 KB	Del OK
__pycache__	-	Del OK
_datasource.py	22.1 KB	Del OK
_iotools.py	30.14 KB	Del OK
_version.py	4.74 KB	Del OK
_version.pyi	633 B	Del OK
arraypad.py	31.06 KB	Del OK
arraypad.pyi	1.69 KB	Del OK
arraysetops.py	32.87 KB	Del OK
arraysetops.pyi	8.14 KB	Del OK
arrayterator.py	6.9 KB	Del OK
arrayterator.pyi	1.5 KB	Del OK
format.py	33.95 KB	Del OK
format.pyi	748 B	Del OK
function_base.py	184.67 KB	Del OK
function_base.pyi	16.2 KB	Del OK
histograms.py	36.81 KB	Del OK
histograms.pyi	995 B	Del OK
index_tricks.py	30.61 KB	Del OK
index_tricks.pyi	4.15 KB	Del OK
mixins.py	6.91 KB	Del OK
mixins.pyi	3.04 KB	Del OK
nanfunctions.py	64.23 KB	Del OK
nanfunctions.pyi	606 B	Del OK
npyio.py	95.04 KB	Del OK
npyio.pyi	9.5 KB	Del OK
polynomial.py	43.1 KB	Del OK
polynomial.pyi	6.79 KB	Del OK
recfunctions.py	58.03 KB	Del OK
scimath.py	14.68 KB	Del OK
scimath.pyi	2.82 KB	Del OK
setup.py	405 B	Del OK
shape_base.py	38.03 KB	Del OK
shape_base.pyi	5.06 KB	Del OK
stride_tricks.py	17.49 KB	Del OK
stride_tricks.pyi	1.71 KB	Del OK
tests	-	Del OK
twodim_base.py	32.17 KB	Del OK
twodim_base.pyi	5.24 KB	Del OK
type_check.py	19.49 KB	Del OK
type_check.pyi	5.44 KB	Del OK
ufunclike.py	6.18 KB	Del OK
ufunclike.pyi	1.26 KB	Del OK
user_array.py	7.54 KB	Del OK
utils.py	36.92 KB	Del OK
utils.pyi	2.3 KB	Del OK

Edit: shape_base.pyi

from collections.abc import Callable, Sequence from typing import TypeVar, Any, overload, SupportsIndex, Protocol 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 _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: ... # TODO: Use PEP 612 `ParamSpec` once mypy supports `Concatenate` # xref python/mypy#8645 @overload def apply_along_axis( func1d: Callable[..., _ArrayLike[_SCT]], axis: SupportsIndex, arr: ArrayLike, *args: Any, **kwargs: Any, ) -> NDArray[_SCT]: ... @overload def apply_along_axis( func1d: Callable[..., ArrayLike], axis: SupportsIndex, arr: ArrayLike, *args: Any, **kwargs: Any, ) -> 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]: ...
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