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"""A module with private type-check-only `numpy.ufunc` subclasses.
The signatures of the ufuncs are too varied to reasonably type
with a single class. So instead, `ufunc` has been expanded into
four private subclasses, one for each combination of
`~ufunc.nin` and `~ufunc.nout`.
"""
from typing import (
Any,
Generic,
List,
Optional,
overload,
Tuple,
TypeVar,
Union,
)
from numpy import ufunc, _Casting, _OrderKACF
from numpy.typing import NDArray
from ._shape import _ShapeLike
from ._scalars import _ScalarLike_co
from ._array_like import ArrayLike, _ArrayLikeBool_co, _ArrayLikeInt_co
from ._dtype_like import DTypeLike
from typing_extensions import Literal, SupportsIndex
_T = TypeVar("_T")
_2Tuple = Tuple[_T, _T]
_3Tuple = Tuple[_T, _T, _T]
_4Tuple = Tuple[_T, _T, _T, _T]
_NTypes = TypeVar("_NTypes", bound=int)
_IDType = TypeVar("_IDType", bound=Any)
_NameType = TypeVar("_NameType", bound=str)
# NOTE: In reality `extobj` should be a length of list 3 containing an
# int, an int, and a callable, but there's no way to properly express
# non-homogenous lists.
# Use `Any` over `Union` to avoid issues related to lists invariance.
# NOTE: `reduce`, `accumulate`, `reduceat` and `outer` raise a ValueError for
# ufuncs that don't accept two input arguments and return one output argument.
# In such cases the respective methods are simply typed as `None`.
# NOTE: Similarly, `at` won't be defined for ufuncs that return
# multiple outputs; in such cases `at` is typed as `None`
# NOTE: If 2 output types are returned then `out` must be a
# 2-tuple of arrays. Otherwise `None` or a plain array are also acceptable
class _UFunc_Nin1_Nout1(ufunc, Generic[_NameType, _NTypes, _IDType]):
@property
def __name__(self) -> _NameType: ...
@property
def ntypes(self) -> _NTypes: ...
@property
def identity(self) -> _IDType: ...
@property
def nin(self) -> Literal[1]: ...
@property
def nout(self) -> Literal[1]: ...
@property
def nargs(self) -> Literal[2]: ...
@property
def signature(self) -> None: ...
@property
def reduce(self) -> None: ...
@property
def accumulate(self) -> None: ...
@property
def reduceat(self) -> None: ...
@property
def outer(self) -> None: ...
@overload
def __call__(
self,
__x1: _ScalarLike_co,
out: None = ...,
*,
where: Optional[_ArrayLikeBool_co] = ...,
casting: _Casting = ...,
order: _OrderKACF = ...,
dtype: DTypeLike = ...,
subok: bool = ...,
signature: Union[str, _2Tuple[Optional[str]]] = ...,
extobj: List[Any] = ...,
) -> Any: ...
@overload
def __call__(
self,
__x1: ArrayLike,
out: Union[None, NDArray[Any], Tuple[NDArray[Any]]] = ...,
*,
where: Optional[_ArrayLikeBool_co] = ...,
casting: _Casting = ...,
order: _OrderKACF = ...,
dtype: DTypeLike = ...,
subok: bool = ...,
signature: Union[str, _2Tuple[Optional[str]]] = ...,
extobj: List[Any] = ...,
) -> NDArray[Any]: ...
def at(
self,
__a: NDArray[Any],
__indices: _ArrayLikeInt_co,
) -> None: ...
class _UFunc_Nin2_Nout1(ufunc, Generic[_NameType, _NTypes, _IDType]):
@property
def __name__(self) -> _NameType: ...
@property
def ntypes(self) -> _NTypes: ...
@property
def identity(self) -> _IDType: ...
@property
def nin(self) -> Literal[2]: ...
@property
def nout(self) -> Literal[1]: ...
@property
def nargs(self) -> Literal[3]: ...
@property
def signature(self) -> None: ...
@overload
def __call__(
self,
__x1: _ScalarLike_co,
__x2: _ScalarLike_co,
out: None = ...,
*,
where: Optional[_ArrayLikeBool_co] = ...,
casting: _Casting = ...,
order: _OrderKACF = ...,
dtype: DTypeLike = ...,
subok: bool = ...,
signature: Union[str, _3Tuple[Optional[str]]] = ...,
extobj: List[Any] = ...,
) -> Any: ...
@overload
def __call__(
self,
__x1: ArrayLike,
__x2: ArrayLike,
out: Union[None, NDArray[Any], Tuple[NDArray[Any]]] = ...,
*,
where: Optional[_ArrayLikeBool_co] = ...,
casting: _Casting = ...,
order: _OrderKACF = ...,
dtype: DTypeLike = ...,
subok: bool = ...,
signature: Union[str, _3Tuple[Optional[str]]] = ...,
extobj: List[Any] = ...,
) -> NDArray[Any]: ...
def at(
self,
__a: NDArray[Any],
__indices: _ArrayLikeInt_co,
__b: ArrayLike,
) -> None: ...
def reduce(
self,
array: ArrayLike,
axis: Optional[_ShapeLike] = ...,
dtype: DTypeLike = ...,
out: Optional[NDArray[Any]] = ...,
keepdims: bool = ...,
initial: Any = ...,
where: _ArrayLikeBool_co = ...,
) -> Any: ...
def accumulate(
self,
array: ArrayLike,
axis: SupportsIndex = ...,
dtype: DTypeLike = ...,
out: Optional[NDArray[Any]] = ...,
) -> NDArray[Any]: ...
def reduceat(
self,
array: ArrayLike,
indices: _ArrayLikeInt_co,
axis: SupportsIndex = ...,
dtype: DTypeLike = ...,
out: Optional[NDArray[Any]] = ...,
) -> NDArray[Any]: ...
# Expand `**kwargs` into explicit keyword-only arguments
@overload
def outer(
self,
__A: _ScalarLike_co,
__B: _ScalarLike_co,
*,
out: None = ...,
where: Optional[_ArrayLikeBool_co] = ...,
casting: _Casting = ...,
order: _OrderKACF = ...,
dtype: DTypeLike = ...,
subok: bool = ...,
signature: Union[str, _3Tuple[Optional[str]]] = ...,
extobj: List[Any] = ...,
) -> Any: ...
@overload
def outer( # type: ignore[misc]
self,
__A: ArrayLike,
__B: ArrayLike,
*,
out: Union[None, NDArray[Any], Tuple[NDArray[Any]]] = ...,
where: Optional[_ArrayLikeBool_co] = ...,
casting: _Casting = ...,
order: _OrderKACF = ...,
dtype: DTypeLike = ...,
subok: bool = ...,
signature: Union[str, _3Tuple[Optional[str]]] = ...,
extobj: List[Any] = ...,
) -> NDArray[Any]: ...
class _UFunc_Nin1_Nout2(ufunc, Generic[_NameType, _NTypes, _IDType]):
@property
def __name__(self) -> _NameType: ...
@property
def ntypes(self) -> _NTypes: ...
@property
def identity(self) -> _IDType: ...
@property
def nin(self) -> Literal[1]: ...
@property
def nout(self) -> Literal[2]: ...
@property
def nargs(self) -> Literal[3]: ...
@property
def signature(self) -> None: ...
@property
def at(self) -> None: ...
@property
def reduce(self) -> None: ...
@property
def accumulate(self) -> None: ...
@property
def reduceat(self) -> None: ...
@property
def outer(self) -> None: ...
@overload
def __call__(
self,
__x1: _ScalarLike_co,
__out1: None = ...,
__out2: None = ...,
*,
where: Optional[_ArrayLikeBool_co] = ...,
casting: _Casting = ...,
order: _OrderKACF = ...,
dtype: DTypeLike = ...,
subok: bool = ...,
signature: Union[str, _3Tuple[Optional[str]]] = ...,
extobj: List[Any] = ...,
) -> _2Tuple[Any]: ...
@overload
def __call__(
self,
__x1: ArrayLike,
__out1: Optional[NDArray[Any]] = ...,
__out2: Optional[NDArray[Any]] = ...,
*,
out: _2Tuple[NDArray[Any]] = ...,
where: Optional[_ArrayLikeBool_co] = ...,
casting: _Casting = ...,
order: _OrderKACF = ...,
dtype: DTypeLike = ...,
subok: bool = ...,
signature: Union[str, _3Tuple[Optional[str]]] = ...,
extobj: List[Any] = ...,
) -> _2Tuple[NDArray[Any]]: ...
class _UFunc_Nin2_Nout2(ufunc, Generic[_NameType, _NTypes, _IDType]):
@property
def __name__(self) -> _NameType: ...
@property
def ntypes(self) -> _NTypes: ...
@property
def identity(self) -> _IDType: ...
@property
def nin(self) -> Literal[2]: ...
@property
def nout(self) -> Literal[2]: ...
@property
def nargs(self) -> Literal[4]: ...
@property
def signature(self) -> None: ...
@property
def at(self) -> None: ...
@property
def reduce(self) -> None: ...
@property
def accumulate(self) -> None: ...
@property
def reduceat(self) -> None: ...
@property
def outer(self) -> None: ...
@overload
def __call__(
self,
__x1: _ScalarLike_co,
__x2: _ScalarLike_co,
__out1: None = ...,
__out2: None = ...,
*,
where: Optional[_ArrayLikeBool_co] = ...,
casting: _Casting = ...,
order: _OrderKACF = ...,
dtype: DTypeLike = ...,
subok: bool = ...,
signature: Union[str, _4Tuple[Optional[str]]] = ...,
extobj: List[Any] = ...,
) -> _2Tuple[Any]: ...
@overload
def __call__(
self,
__x1: ArrayLike,
__x2: ArrayLike,
__out1: Optional[NDArray[Any]] = ...,
__out2: Optional[NDArray[Any]] = ...,
*,
out: _2Tuple[NDArray[Any]] = ...,
where: Optional[_ArrayLikeBool_co] = ...,
casting: _Casting = ...,
order: _OrderKACF = ...,
dtype: DTypeLike = ...,
subok: bool = ...,
signature: Union[str, _4Tuple[Optional[str]]] = ...,
extobj: List[Any] = ...,
) -> _2Tuple[NDArray[Any]]: ...
class _GUFunc_Nin2_Nout1(ufunc, Generic[_NameType, _NTypes, _IDType]):
@property
def __name__(self) -> _NameType: ...
@property
def ntypes(self) -> _NTypes: ...
@property
def identity(self) -> _IDType: ...
@property
def nin(self) -> Literal[2]: ...
@property
def nout(self) -> Literal[1]: ...
@property
def nargs(self) -> Literal[3]: ...
# NOTE: In practice the only gufunc in the main name is `matmul`,
# so we can use its signature here
@property
def signature(self) -> Literal["(n?,k),(k,m?)->(n?,m?)"]: ...
@property
def reduce(self) -> None: ...
@property
def accumulate(self) -> None: ...
@property
def reduceat(self) -> None: ...
@property
def outer(self) -> None: ...
@property
def at(self) -> None: ...
# Scalar for 1D array-likes; ndarray otherwise
@overload
def __call__(
self,
__x1: ArrayLike,
__x2: ArrayLike,
out: None = ...,
*,
casting: _Casting = ...,
order: _OrderKACF = ...,
dtype: DTypeLike = ...,
subok: bool = ...,
signature: Union[str, _3Tuple[Optional[str]]] = ...,
extobj: List[Any] = ...,
axes: List[_2Tuple[SupportsIndex]] = ...,
) -> Any: ...
@overload
def __call__(
self,
__x1: ArrayLike,
__x2: ArrayLike,
out: Union[NDArray[Any], Tuple[NDArray[Any]]],
*,
casting: _Casting = ...,
order: _OrderKACF = ...,
dtype: DTypeLike = ...,
subok: bool = ...,
signature: Union[str, _3Tuple[Optional[str]]] = ...,
extobj: List[Any] = ...,
axes: List[_2Tuple[SupportsIndex]] = ...,
) -> NDArray[Any]: ...
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