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|
import datetime as dt
from collections.abc import Sequence
from typing import Union, Any, overload, TypeVar, Literal
from numpy import (
ndarray,
number,
intp,
bool_,
generic,
_OrderKACF,
_OrderACF,
_ModeKind,
_PartitionKind,
_SortKind,
_SortSide,
)
from numpy.typing import (
DTypeLike,
ArrayLike,
_ArrayLike,
NDArray,
_ShapeLike,
_Shape,
_ArrayLikeBool_co,
_ArrayLikeInt_co,
_IntLike_co,
_NumberLike_co,
_ScalarLike_co,
)
_SCT = TypeVar("_SCT", bound=generic)
_ArrayType = TypeVar("_ArrayType", bound=NDArray[Any])
__all__: list[str]
def take(
a: ArrayLike,
indices: _ArrayLikeInt_co,
axis: None | int = ...,
out: None | ndarray = ...,
mode: _ModeKind = ...,
) -> Any: ...
@overload
def reshape(
a: _ArrayLike[_SCT],
newshape: _ShapeLike,
order: _OrderACF = ...,
) -> NDArray[_SCT]: ...
@overload
def reshape(
a: ArrayLike,
newshape: _ShapeLike,
order: _OrderACF = ...,
) -> NDArray[Any]: ...
@overload
def choose(
a: _IntLike_co,
choices: ArrayLike,
out: None = ...,
mode: _ModeKind = ...,
) -> Any: ...
@overload
def choose(
a: _ArrayLikeInt_co,
choices: _ArrayLike[_SCT],
out: None = ...,
mode: _ModeKind = ...,
) -> NDArray[_SCT]: ...
@overload
def choose(
a: _ArrayLikeInt_co,
choices: ArrayLike,
out: None = ...,
mode: _ModeKind = ...,
) -> NDArray[Any]: ...
@overload
def choose(
a: _ArrayLikeInt_co,
choices: ArrayLike,
out: _ArrayType = ...,
mode: _ModeKind = ...,
) -> _ArrayType: ...
@overload
def repeat(
a: _ArrayLike[_SCT],
repeats: _ArrayLikeInt_co,
axis: None | int = ...,
) -> NDArray[_SCT]: ...
@overload
def repeat(
a: ArrayLike,
repeats: _ArrayLikeInt_co,
axis: None | int = ...,
) -> NDArray[Any]: ...
def put(
a: NDArray[Any],
ind: _ArrayLikeInt_co,
v: ArrayLike,
mode: _ModeKind = ...,
) -> None: ...
@overload
def swapaxes(
a: _ArrayLike[_SCT],
axis1: int,
axis2: int,
) -> NDArray[_SCT]: ...
@overload
def swapaxes(
a: ArrayLike,
axis1: int,
axis2: int,
) -> NDArray[Any]: ...
@overload
def transpose(
a: _ArrayLike[_SCT],
axes: None | _ShapeLike = ...
) -> NDArray[_SCT]: ...
@overload
def transpose(
a: ArrayLike,
axes: None | _ShapeLike = ...
) -> NDArray[Any]: ...
@overload
def partition(
a: _ArrayLike[_SCT],
kth: _ArrayLikeInt_co,
axis: None | int = ...,
kind: _PartitionKind = ...,
order: None | str | Sequence[str] = ...,
) -> NDArray[_SCT]: ...
@overload
def partition(
a: ArrayLike,
kth: _ArrayLikeInt_co,
axis: None | int = ...,
kind: _PartitionKind = ...,
order: None | str | Sequence[str] = ...,
) -> NDArray[Any]: ...
def argpartition(
a: ArrayLike,
kth: _ArrayLikeInt_co,
axis: None | int = ...,
kind: _PartitionKind = ...,
order: None | str | Sequence[str] = ...,
) -> NDArray[intp]: ...
@overload
def sort(
a: _ArrayLike[_SCT],
axis: None | int = ...,
kind: None | _SortKind = ...,
order: None | str | Sequence[str] = ...,
) -> NDArray[_SCT]: ...
@overload
def sort(
a: ArrayLike,
axis: None | int = ...,
kind: None | _SortKind = ...,
order: None | str | Sequence[str] = ...,
) -> NDArray[Any]: ...
def argsort(
a: ArrayLike,
axis: None | int = ...,
kind: None | _SortKind = ...,
order: None | str | Sequence[str] = ...,
) -> NDArray[intp]: ...
@overload
def argmax(
a: ArrayLike,
axis: None = ...,
out: None | ndarray = ...,
*,
keepdims: Literal[False] = ...,
) -> intp: ...
@overload
def argmax(
a: ArrayLike,
axis: None | int = ...,
out: None | ndarray = ...,
*,
keepdims: bool = ...,
) -> Any: ...
@overload
def argmin(
a: ArrayLike,
axis: None = ...,
out: None | ndarray = ...,
*,
keepdims: Literal[False] = ...,
) -> intp: ...
@overload
def argmin(
a: ArrayLike,
axis: None | int = ...,
out: None | ndarray = ...,
*,
keepdims: bool = ...,
) -> Any: ...
@overload
def searchsorted(
a: ArrayLike,
v: _ScalarLike_co,
side: _SortSide = ...,
sorter: None | _ArrayLikeInt_co = ..., # 1D int array
) -> intp: ...
@overload
def searchsorted(
a: ArrayLike,
v: ArrayLike,
side: _SortSide = ...,
sorter: None | _ArrayLikeInt_co = ..., # 1D int array
) -> NDArray[intp]: ...
@overload
def resize(
a: _ArrayLike[_SCT],
new_shape: _ShapeLike,
) -> NDArray[_SCT]: ...
@overload
def resize(
a: ArrayLike,
new_shape: _ShapeLike,
) -> NDArray[Any]: ...
@overload
def squeeze(
a: _SCT,
axis: None | _ShapeLike = ...,
) -> _SCT: ...
@overload
def squeeze(
a: _ArrayLike[_SCT],
axis: None | _ShapeLike = ...,
) -> NDArray[_SCT]: ...
@overload
def squeeze(
a: ArrayLike,
axis: None | _ShapeLike = ...,
) -> NDArray[Any]: ...
@overload
def diagonal(
a: _ArrayLike[_SCT],
offset: int = ...,
axis1: int = ...,
axis2: int = ..., # >= 2D array
) -> NDArray[_SCT]: ...
@overload
def diagonal(
a: ArrayLike,
offset: int = ...,
axis1: int = ...,
axis2: int = ..., # >= 2D array
) -> NDArray[Any]: ...
def trace(
a: ArrayLike, # >= 2D array
offset: int = ...,
axis1: int = ...,
axis2: int = ...,
dtype: DTypeLike = ...,
out: None | ndarray = ...,
) -> Any: ...
@overload
def ravel(a: _ArrayLike[_SCT], order: _OrderKACF = ...) -> NDArray[_SCT]: ...
@overload
def ravel(a: ArrayLike, order: _OrderKACF = ...) -> NDArray[Any]: ...
def nonzero(a: ArrayLike) -> tuple[NDArray[intp], ...]: ...
def shape(a: ArrayLike) -> _Shape: ...
@overload
def compress(
condition: _ArrayLikeBool_co, # 1D bool array
a: _ArrayLike[_SCT],
axis: None | int = ...,
out: None = ...,
) -> NDArray[_SCT]: ...
@overload
def compress(
condition: _ArrayLikeBool_co, # 1D bool array
a: ArrayLike,
axis: None | int = ...,
out: None = ...,
) -> NDArray[Any]: ...
@overload
def compress(
condition: _ArrayLikeBool_co, # 1D bool array
a: ArrayLike,
axis: None | int = ...,
out: _ArrayType = ...,
) -> _ArrayType: ...
@overload
def clip(
a: ArrayLike,
a_min: ArrayLike,
a_max: None | ArrayLike,
out: None | ndarray = ...,
**kwargs: Any,
) -> Any: ...
@overload
def clip(
a: ArrayLike,
a_min: None,
a_max: ArrayLike,
out: None | ndarray = ...,
**kwargs: Any,
) -> Any: ...
def sum(
a: ArrayLike,
axis: _ShapeLike = ...,
dtype: DTypeLike = ...,
out: None | ndarray = ...,
keepdims: bool = ...,
initial: _NumberLike_co = ...,
where: _ArrayLikeBool_co = ...,
) -> Any: ...
@overload
def all(
a: ArrayLike,
axis: None = ...,
out: None = ...,
keepdims: Literal[False] = ...,
*,
where: _ArrayLikeBool_co = ...,
) -> bool_: ...
@overload
def all(
a: ArrayLike,
axis: None | _ShapeLike = ...,
out: None | ndarray = ...,
keepdims: bool = ...,
*,
where: _ArrayLikeBool_co = ...,
) -> Any: ...
@overload
def any(
a: ArrayLike,
axis: None = ...,
out: None = ...,
keepdims: Literal[False] = ...,
*,
where: _ArrayLikeBool_co = ...,
) -> bool_: ...
@overload
def any(
a: ArrayLike,
axis: None | _ShapeLike = ...,
out: None | ndarray = ...,
keepdims: bool = ...,
*,
where: _ArrayLikeBool_co = ...,
) -> Any: ...
def cumsum(
a: ArrayLike,
axis: None | int = ...,
dtype: DTypeLike = ...,
out: None | ndarray = ...,
) -> ndarray: ...
def ptp(
a: ArrayLike,
axis: None | _ShapeLike = ...,
out: None | ndarray = ...,
keepdims: bool = ...,
) -> Any: ...
def amax(
a: ArrayLike,
axis: None | _ShapeLike = ...,
out: None | ndarray = ...,
keepdims: bool = ...,
initial: _NumberLike_co = ...,
where: _ArrayLikeBool_co = ...,
) -> Any: ...
def amin(
a: ArrayLike,
axis: None | _ShapeLike = ...,
out: None | ndarray = ...,
keepdims: bool = ...,
initial: _NumberLike_co = ...,
where: _ArrayLikeBool_co = ...,
) -> Any: ...
# TODO: `np.prod()``: For object arrays `initial` does not necessarily
# have to be a numerical scalar.
# The only requirement is that it is compatible
# with the `.__mul__()` method(s) of the passed array's elements.
# Note that the same situation holds for all wrappers around
# `np.ufunc.reduce`, e.g. `np.sum()` (`.__add__()`).
def prod(
a: ArrayLike,
axis: None | _ShapeLike = ...,
dtype: DTypeLike = ...,
out: None | ndarray = ...,
keepdims: bool = ...,
initial: _NumberLike_co = ...,
where: _ArrayLikeBool_co = ...,
) -> Any: ...
def cumprod(
a: ArrayLike,
axis: None | int = ...,
dtype: DTypeLike = ...,
out: None | ndarray = ...,
) -> ndarray: ...
def ndim(a: ArrayLike) -> int: ...
def size(a: ArrayLike, axis: None | int = ...) -> int: ...
def around(
a: ArrayLike,
decimals: int = ...,
out: None | ndarray = ...,
) -> Any: ...
def mean(
a: ArrayLike,
axis: None | _ShapeLike = ...,
dtype: DTypeLike = ...,
out: None | ndarray = ...,
keepdims: bool = ...,
*,
where: _ArrayLikeBool_co = ...,
) -> Any: ...
def std(
a: ArrayLike,
axis: None | _ShapeLike = ...,
dtype: DTypeLike = ...,
out: None | ndarray = ...,
ddof: int = ...,
keepdims: bool = ...,
*,
where: _ArrayLikeBool_co = ...,
) -> Any: ...
def var(
a: ArrayLike,
axis: None | _ShapeLike = ...,
dtype: DTypeLike = ...,
out: None | ndarray = ...,
ddof: int = ...,
keepdims: bool = ...,
*,
where: _ArrayLikeBool_co = ...,
) -> Any: ...
|
