134 lines
4.5 KiB
Python
134 lines
4.5 KiB
Python
"""
|
|
This type stub file was generated by pyright.
|
|
"""
|
|
|
|
from collections.abc import Callable, Sequence
|
|
from typing import Any, TypeVar, Union, overload
|
|
from numpy import _OrderCF, bool_, complexfloating, datetime64, float64, floating, generic, int_, intp, number, object_, signedinteger, timedelta64
|
|
from numpy._typing import ArrayLike, DTypeLike, NDArray, _ArrayLike, _ArrayLikeComplex_co, _ArrayLikeFloat_co, _ArrayLikeInt_co, _ArrayLikeObject_co, _DTypeLike, _SupportsArrayFunc
|
|
|
|
_T = TypeVar("_T")
|
|
_SCT = TypeVar("_SCT", bound=generic)
|
|
_MaskFunc = Callable[[NDArray[int_], _T], NDArray[Union[number[Any], bool_, timedelta64, datetime64, object_]],]
|
|
__all__: list[str]
|
|
@overload
|
|
def fliplr(m: _ArrayLike[_SCT]) -> NDArray[_SCT]:
|
|
...
|
|
|
|
@overload
|
|
def fliplr(m: ArrayLike) -> NDArray[Any]:
|
|
...
|
|
|
|
@overload
|
|
def flipud(m: _ArrayLike[_SCT]) -> NDArray[_SCT]:
|
|
...
|
|
|
|
@overload
|
|
def flipud(m: ArrayLike) -> NDArray[Any]:
|
|
...
|
|
|
|
@overload
|
|
def eye(N: int, M: None | int = ..., k: int = ..., dtype: None = ..., order: _OrderCF = ..., *, like: None | _SupportsArrayFunc = ...) -> NDArray[float64]:
|
|
...
|
|
|
|
@overload
|
|
def eye(N: int, M: None | int = ..., k: int = ..., dtype: _DTypeLike[_SCT] = ..., order: _OrderCF = ..., *, like: None | _SupportsArrayFunc = ...) -> NDArray[_SCT]:
|
|
...
|
|
|
|
@overload
|
|
def eye(N: int, M: None | int = ..., k: int = ..., dtype: DTypeLike = ..., order: _OrderCF = ..., *, like: None | _SupportsArrayFunc = ...) -> NDArray[Any]:
|
|
...
|
|
|
|
@overload
|
|
def diag(v: _ArrayLike[_SCT], k: int = ...) -> NDArray[_SCT]:
|
|
...
|
|
|
|
@overload
|
|
def diag(v: ArrayLike, k: int = ...) -> NDArray[Any]:
|
|
...
|
|
|
|
@overload
|
|
def diagflat(v: _ArrayLike[_SCT], k: int = ...) -> NDArray[_SCT]:
|
|
...
|
|
|
|
@overload
|
|
def diagflat(v: ArrayLike, k: int = ...) -> NDArray[Any]:
|
|
...
|
|
|
|
@overload
|
|
def tri(N: int, M: None | int = ..., k: int = ..., dtype: None = ..., *, like: None | _SupportsArrayFunc = ...) -> NDArray[float64]:
|
|
...
|
|
|
|
@overload
|
|
def tri(N: int, M: None | int = ..., k: int = ..., dtype: _DTypeLike[_SCT] = ..., *, like: None | _SupportsArrayFunc = ...) -> NDArray[_SCT]:
|
|
...
|
|
|
|
@overload
|
|
def tri(N: int, M: None | int = ..., k: int = ..., dtype: DTypeLike = ..., *, like: None | _SupportsArrayFunc = ...) -> NDArray[Any]:
|
|
...
|
|
|
|
@overload
|
|
def tril(v: _ArrayLike[_SCT], k: int = ...) -> NDArray[_SCT]:
|
|
...
|
|
|
|
@overload
|
|
def tril(v: ArrayLike, k: int = ...) -> NDArray[Any]:
|
|
...
|
|
|
|
@overload
|
|
def triu(v: _ArrayLike[_SCT], k: int = ...) -> NDArray[_SCT]:
|
|
...
|
|
|
|
@overload
|
|
def triu(v: ArrayLike, k: int = ...) -> NDArray[Any]:
|
|
...
|
|
|
|
@overload
|
|
def vander(x: _ArrayLikeInt_co, N: None | int = ..., increasing: bool = ...) -> NDArray[signedinteger[Any]]:
|
|
...
|
|
|
|
@overload
|
|
def vander(x: _ArrayLikeFloat_co, N: None | int = ..., increasing: bool = ...) -> NDArray[floating[Any]]:
|
|
...
|
|
|
|
@overload
|
|
def vander(x: _ArrayLikeComplex_co, N: None | int = ..., increasing: bool = ...) -> NDArray[complexfloating[Any, Any]]:
|
|
...
|
|
|
|
@overload
|
|
def vander(x: _ArrayLikeObject_co, N: None | int = ..., increasing: bool = ...) -> NDArray[object_]:
|
|
...
|
|
|
|
@overload
|
|
def histogram2d(x: _ArrayLikeFloat_co, y: _ArrayLikeFloat_co, bins: int | Sequence[int] = ..., range: None | _ArrayLikeFloat_co = ..., density: None | bool = ..., weights: None | _ArrayLikeFloat_co = ...) -> tuple[NDArray[float64], NDArray[floating[Any]], NDArray[floating[Any]],]:
|
|
...
|
|
|
|
@overload
|
|
def histogram2d(x: _ArrayLikeComplex_co, y: _ArrayLikeComplex_co, bins: int | Sequence[int] = ..., range: None | _ArrayLikeFloat_co = ..., density: None | bool = ..., weights: None | _ArrayLikeFloat_co = ...) -> tuple[NDArray[float64], NDArray[complexfloating[Any, Any]], NDArray[complexfloating[Any, Any]],]:
|
|
...
|
|
|
|
@overload
|
|
def histogram2d(x: _ArrayLikeComplex_co, y: _ArrayLikeComplex_co, bins: Sequence[_ArrayLikeInt_co], range: None | _ArrayLikeFloat_co = ..., density: None | bool = ..., weights: None | _ArrayLikeFloat_co = ...) -> tuple[NDArray[float64], NDArray[Any], NDArray[Any],]:
|
|
...
|
|
|
|
@overload
|
|
def mask_indices(n: int, mask_func: _MaskFunc[int], k: int = ...) -> tuple[NDArray[intp], NDArray[intp]]:
|
|
...
|
|
|
|
@overload
|
|
def mask_indices(n: int, mask_func: _MaskFunc[_T], k: _T) -> tuple[NDArray[intp], NDArray[intp]]:
|
|
...
|
|
|
|
def tril_indices(n: int, k: int = ..., m: None | int = ...) -> tuple[NDArray[int_], NDArray[int_]]:
|
|
...
|
|
|
|
def tril_indices_from(arr: NDArray[Any], k: int = ...) -> tuple[NDArray[int_], NDArray[int_]]:
|
|
...
|
|
|
|
def triu_indices(n: int, k: int = ..., m: None | int = ...) -> tuple[NDArray[int_], NDArray[int_]]:
|
|
...
|
|
|
|
def triu_indices_from(arr: NDArray[Any], k: int = ...) -> tuple[NDArray[int_], NDArray[int_]]:
|
|
...
|
|
|