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Files and Folders in: //opt/cloudlinux/venv/lib64/python3.11///site-packages/numpy/lib

NameTypeSizeLast ModifiedActions
__pycache__ Directory - -
tests Directory - -
__init__.py File 2763 bytes April 17 2025 13:10:58.
__init__.pyi File 5596 bytes April 17 2025 13:10:58.
_datasource.py File 22631 bytes April 17 2025 13:10:58.
_iotools.py File 30868 bytes April 17 2025 13:10:58.
_version.py File 4855 bytes April 17 2025 13:10:58.
_version.pyi File 633 bytes April 17 2025 13:10:58.
arraypad.py File 31803 bytes April 17 2025 13:10:58.
arraypad.pyi File 1728 bytes April 17 2025 13:10:58.
arraysetops.py File 33655 bytes April 17 2025 13:10:58.
arraysetops.pyi File 8337 bytes April 17 2025 13:10:58.
arrayterator.py File 7063 bytes April 17 2025 13:10:58.
arrayterator.pyi File 1537 bytes April 17 2025 13:10:58.
format.py File 34769 bytes April 17 2025 13:10:58.
format.pyi File 748 bytes April 17 2025 13:10:58.
function_base.py File 189103 bytes April 17 2025 13:10:58.
function_base.pyi File 16585 bytes April 17 2025 13:10:58.
histograms.py File 37697 bytes April 17 2025 13:10:58.
histograms.pyi File 995 bytes April 17 2025 13:10:58.
index_tricks.py File 31346 bytes April 17 2025 13:10:58.
index_tricks.pyi File 4251 bytes April 17 2025 13:10:58.
mixins.py File 7071 bytes April 17 2025 13:10:58.
mixins.pyi File 3117 bytes April 17 2025 13:10:58.
nanfunctions.py File 65775 bytes April 17 2025 13:10:58.
nanfunctions.pyi File 606 bytes April 17 2025 13:10:58.
npyio.py File 97316 bytes April 17 2025 13:10:58.
npyio.pyi File 9728 bytes April 17 2025 13:10:58.
polynomial.py File 44133 bytes April 17 2025 13:10:58.
polynomial.pyi File 6958 bytes April 17 2025 13:10:58.
recfunctions.py File 59423 bytes April 17 2025 13:10:58.
scimath.py File 15037 bytes April 17 2025 13:10:58.
scimath.pyi File 2883 bytes April 17 2025 13:10:58.
setup.py File 405 bytes April 17 2025 13:10:58.
shape_base.py File 38947 bytes April 17 2025 13:10:58.
shape_base.pyi File 5184 bytes April 17 2025 13:10:58.
stride_tricks.py File 17911 bytes April 17 2025 13:10:58.
stride_tricks.pyi File 1747 bytes April 17 2025 13:10:58.
twodim_base.py File 32947 bytes April 17 2025 13:10:58.
twodim_base.pyi File 5370 bytes April 17 2025 13:10:58.
type_check.py File 19954 bytes April 17 2025 13:10:58.
type_check.pyi File 5571 bytes April 17 2025 13:10:58.
ufunclike.py File 6325 bytes April 17 2025 13:10:58.
ufunclike.pyi File 1293 bytes April 17 2025 13:10:58.
user_array.py File 7721 bytes April 17 2025 13:10:58.
utils.py File 37804 bytes April 17 2025 13:10:58.
utils.pyi File 2360 bytes April 17 2025 13:10:58.

Reading File: //opt/cloudlinux/venv/lib64/python3.11///site-packages/numpy/lib/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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