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__init__.py
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__init__.pyi
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__pycache__
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_datasource.py
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_iotools.py
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_version.py
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_version.pyi
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arraypad.py
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arraypad.pyi
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arraysetops.py
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arraysetops.pyi
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arrayterator.py
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arrayterator.pyi
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format.py
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format.pyi
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function_base.py
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function_base.pyi
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histograms.py
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histograms.pyi
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index_tricks.py
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index_tricks.pyi
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mixins.py
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mixins.pyi
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nanfunctions.py
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nanfunctions.pyi
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npyio.py
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npyio.pyi
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polynomial.py
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polynomial.pyi
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recfunctions.py
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scimath.py
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scimath.pyi
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setup.py
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shape_base.py
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shape_base.pyi
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stride_tricks.py
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stride_tricks.pyi
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tests
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twodim_base.py
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twodim_base.pyi
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type_check.py
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type_check.pyi
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ufunclike.py
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ufunclike.pyi
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user_array.py
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utils.py
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utils.pyi
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Editing: 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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