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- 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 = ...,
- ) -> Any: ... # TODO: np.intp or ndarray[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 = ...,
- ) -> Any: ...
- def array_equal(a1: ArrayLike, a2: ArrayLike) -> bool: ...
- def array_equiv(a1: ArrayLike, a2: ArrayLike) -> bool: ...
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