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Diffstat (limited to 'numpy/core/numeric.pyi')
| -rw-r--r-- | numpy/core/numeric.pyi | 189 |
1 files changed, 189 insertions, 0 deletions
diff --git a/numpy/core/numeric.pyi b/numpy/core/numeric.pyi new file mode 100644 index 000000000..d91cb31c2 --- /dev/null +++ b/numpy/core/numeric.pyi @@ -0,0 +1,189 @@ +import sys +from typing import ( + Any, + Optional, + Union, + Sequence, + Tuple, + Callable, + List, + overload, + TypeVar, + Iterable, +) + +from numpy import ndarray, generic, dtype, bool_, signedinteger, _OrderKACF, _OrderCF +from numpy.typing import ArrayLike, DTypeLike, _ShapeLike + +if sys.version_info >= (3, 8): + from typing import Literal +else: + from typing_extensions import Literal + +_T = TypeVar("_T") +_ArrayType = TypeVar("_ArrayType", bound=ndarray) + +_CorrelateMode = Literal["valid", "same", "full"] + +@overload +def zeros_like( + a: _ArrayType, + dtype: None = ..., + order: _OrderKACF = ..., + subok: Literal[True] = ..., + shape: None = ..., +) -> _ArrayType: ... +@overload +def zeros_like( + a: ArrayLike, + dtype: DTypeLike = ..., + order: _OrderKACF = ..., + subok: bool = ..., + shape: Optional[_ShapeLike] = ..., +) -> ndarray: ... +def ones( + shape: _ShapeLike, + dtype: DTypeLike = ..., + order: _OrderCF = ..., + *, + like: ArrayLike = ..., +) -> ndarray: ... +@overload +def ones_like( + a: _ArrayType, + dtype: None = ..., + order: _OrderKACF = ..., + subok: Literal[True] = ..., + shape: None = ..., +) -> _ArrayType: ... +@overload +def ones_like( + a: ArrayLike, + dtype: DTypeLike = ..., + order: _OrderKACF = ..., + subok: bool = ..., + shape: Optional[_ShapeLike] = ..., +) -> ndarray: ... +@overload +def empty_like( + a: _ArrayType, + dtype: None = ..., + order: _OrderKACF = ..., + subok: Literal[True] = ..., + shape: None = ..., +) -> _ArrayType: ... +@overload +def empty_like( + a: ArrayLike, + dtype: DTypeLike = ..., + order: _OrderKACF = ..., + subok: bool = ..., + shape: Optional[_ShapeLike] = ..., +) -> ndarray: ... +def full( + shape: _ShapeLike, + fill_value: Any, + dtype: DTypeLike = ..., + order: _OrderCF = ..., + *, + like: ArrayLike = ..., +) -> ndarray: ... +@overload +def full_like( + a: _ArrayType, + fill_value: Any, + dtype: None = ..., + order: _OrderKACF = ..., + subok: Literal[True] = ..., + shape: None = ..., +) -> _ArrayType: ... +@overload +def full_like( + a: ArrayLike, + fill_value: Any, + dtype: DTypeLike = ..., + order: _OrderKACF = ..., + subok: bool = ..., + shape: Optional[_ShapeLike] = ..., +) -> ndarray: ... +@overload +def count_nonzero( + a: ArrayLike, axis: None = ..., *, keepdims: Literal[False] = ... +) -> int: ... +@overload +def count_nonzero( + a: ArrayLike, axis: _ShapeLike = ..., *, keepdims: bool = ... +) -> Union[signedinteger[Any], ndarray]: ... # TODO: np.intp +def isfortran(a: Union[ndarray, generic]) -> bool: ... +def argwhere(a: ArrayLike) -> ndarray: ... +def flatnonzero(a: ArrayLike) -> ndarray: ... +def correlate(a: ArrayLike, v: ArrayLike, mode: _CorrelateMode = ...) -> ndarray: ... +def convolve(a: ArrayLike, v: ArrayLike, mode: _CorrelateMode = ...) -> ndarray: ... +@overload +def outer(a: ArrayLike, b: ArrayLike, out: None = ...) -> ndarray: ... +@overload +def outer(a: ArrayLike, b: ArrayLike, out: _ArrayType = ...) -> _ArrayType: ... +def tensordot( + a: ArrayLike, + b: ArrayLike, + axes: Union[int, Tuple[_ShapeLike, _ShapeLike]] = ..., +) -> ndarray: ... +def roll( + a: ArrayLike, + shift: _ShapeLike, + axis: Optional[_ShapeLike] = ..., +) -> ndarray: ... +def rollaxis(a: ndarray, axis: int, start: int = ...) -> ndarray: ... +def moveaxis( + a: ndarray, + source: _ShapeLike, + destination: _ShapeLike, +) -> ndarray: ... +def cross( + a: ArrayLike, + b: ArrayLike, + axisa: int = ..., + axisb: int = ..., + axisc: int = ..., + axis: Optional[int] = ..., +) -> ndarray: ... +@overload +def indices( + dimensions: Sequence[int], + dtype: DTypeLike = ..., + sparse: Literal[False] = ..., +) -> ndarray: ... +@overload +def indices( + dimensions: Sequence[int], + dtype: DTypeLike = ..., + sparse: Literal[True] = ..., +) -> Tuple[ndarray, ...]: ... +def fromfunction( + function: Callable[..., _T], + shape: Sequence[int], + *, + dtype: DTypeLike = ..., + like: ArrayLike = ..., + **kwargs: Any, +) -> _T: ... +def isscalar(element: Any) -> bool: ... +def binary_repr(num: int, width: Optional[int] = ...) -> str: ... +def base_repr(number: int, base: int = ..., padding: int = ...) -> str: ... +def identity(n: int, dtype: DTypeLike = ..., *, like: ArrayLike = ...) -> ndarray: ... +def allclose( + a: ArrayLike, + b: ArrayLike, + rtol: float = ..., + atol: float = ..., + equal_nan: bool = ..., +) -> bool: ... +def isclose( + a: ArrayLike, + b: ArrayLike, + rtol: float = ..., + atol: float = ..., + equal_nan: bool = ..., +) -> Union[bool_, ndarray]: ... +def array_equal(a1: ArrayLike, a2: ArrayLike) -> bool: ... +def array_equiv(a1: ArrayLike, a2: ArrayLike) -> bool: ... |