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| author | Charles Harris <charlesr.harris@gmail.com> | 2021-05-04 11:43:50 -0600 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2021-05-04 11:43:50 -0600 |
| commit | 4d753a0cd67cc381af9d096afdafda674a37c971 (patch) | |
| tree | b3834178d0026c26cfaafeb9196c085033237c9c /numpy | |
| parent | 70dd918b8b531ce7be91bb9e6bb52fdc7c7199b9 (diff) | |
| parent | 6fa34d432722faaaf54f27fb9cb3b1b9e197e9fe (diff) | |
| download | numpy-4d753a0cd67cc381af9d096afdafda674a37c971.tar.gz | |
Merge pull request #18885 from BvB93/unsafe
MAINT: Remove unsafe unions and ABCs from return-annotations
Diffstat (limited to 'numpy')
22 files changed, 980 insertions, 1012 deletions
diff --git a/numpy/__init__.pyi b/numpy/__init__.pyi index 5c7a3c7e4..8824497f0 100644 --- a/numpy/__init__.pyi +++ b/numpy/__init__.pyi @@ -11,7 +11,6 @@ from numpy.typing import ( # Arrays ArrayLike, _ArrayND, - _ArrayOrScalar, _SupportsArray, _NestedSequence, _RecursiveSequence, @@ -1289,14 +1288,21 @@ class _ArrayOrScalarCommon: def __array_wrap__(array, context=...): ... def __setstate__(self, __state): ... # a `bool_` is returned when `keepdims=True` and `self` is a 0d array + @overload def all( - self, axis: None = ..., out: None = ..., keepdims: Literal[False] = ... + self, + axis: None = ..., + out: None = ..., + keepdims: Literal[False] = ..., ) -> bool_: ... @overload def all( - self, axis: Optional[_ShapeLike] = ..., out: None = ..., keepdims: bool = ... - ) -> Union[bool_, ndarray]: ... + self, + axis: Optional[_ShapeLike] = ..., + out: None = ..., + keepdims: bool = ..., + ) -> Any: ... @overload def all( self, @@ -1304,14 +1310,21 @@ class _ArrayOrScalarCommon: out: _NdArraySubClass = ..., keepdims: bool = ..., ) -> _NdArraySubClass: ... + @overload def any( - self, axis: None = ..., out: None = ..., keepdims: Literal[False] = ... + self, + axis: None = ..., + out: None = ..., + keepdims: Literal[False] = ..., ) -> bool_: ... @overload def any( - self, axis: Optional[_ShapeLike] = ..., out: None = ..., keepdims: bool = ... - ) -> Union[bool_, ndarray]: ... + self, + axis: Optional[_ShapeLike] = ..., + out: None = ..., + keepdims: bool = ..., + ) -> Any: ... @overload def any( self, @@ -1319,40 +1332,67 @@ class _ArrayOrScalarCommon: out: _NdArraySubClass = ..., keepdims: bool = ..., ) -> _NdArraySubClass: ... + @overload - def argmax(self, axis: None = ..., out: None = ...) -> intp: ... + def argmax( + self, + axis: None = ..., + out: None = ..., + ) -> intp: ... @overload def argmax( - self, axis: _ShapeLike = ..., out: None = ... - ) -> Union[ndarray, intp]: ... + self, + axis: _ShapeLike = ..., + out: None = ..., + ) -> Any: ... @overload def argmax( - self, axis: Optional[_ShapeLike] = ..., out: _NdArraySubClass = ... + self, + axis: Optional[_ShapeLike] = ..., + out: _NdArraySubClass = ..., ) -> _NdArraySubClass: ... + @overload - def argmin(self, axis: None = ..., out: None = ...) -> intp: ... + def argmin( + self, + axis: None = ..., + out: None = ..., + ) -> intp: ... @overload def argmin( - self, axis: _ShapeLike = ..., out: None = ... - ) -> Union[ndarray, intp]: ... + self, + axis: _ShapeLike = ..., + out: None = ..., + ) -> Any: ... @overload def argmin( - self, axis: Optional[_ShapeLike] = ..., out: _NdArraySubClass = ... + self, + axis: Optional[_ShapeLike] = ..., + out: _NdArraySubClass = ..., ) -> _NdArraySubClass: ... + def argsort( self, axis: Optional[SupportsIndex] = ..., kind: Optional[_SortKind] = ..., order: Union[None, str, Sequence[str]] = ..., ) -> ndarray: ... + @overload def choose( - self, choices: ArrayLike, out: None = ..., mode: _ModeKind = ..., + self, + choices: ArrayLike, + out: None = ..., + mode: _ModeKind = ..., ) -> ndarray: ... @overload def choose( - self, choices: ArrayLike, out: _NdArraySubClass = ..., mode: _ModeKind = ..., + self, + choices: ArrayLike, + out: _NdArraySubClass = ..., + mode: _ModeKind = ..., ) -> _NdArraySubClass: ... + @overload def clip( self, @@ -1360,7 +1400,7 @@ class _ArrayOrScalarCommon: max: Optional[ArrayLike] = ..., out: None = ..., **kwargs: Any, - ) -> Union[number, ndarray]: ... + ) -> ndarray: ... @overload def clip( self, @@ -1368,7 +1408,7 @@ class _ArrayOrScalarCommon: max: ArrayLike = ..., out: None = ..., **kwargs: Any, - ) -> Union[number, ndarray]: ... + ) -> ndarray: ... @overload def clip( self, @@ -1385,6 +1425,7 @@ class _ArrayOrScalarCommon: out: _NdArraySubClass = ..., **kwargs: Any, ) -> _NdArraySubClass: ... + @overload def compress( self, @@ -1399,8 +1440,11 @@ class _ArrayOrScalarCommon: axis: Optional[SupportsIndex] = ..., out: _NdArraySubClass = ..., ) -> _NdArraySubClass: ... + def conj(self: _ArraySelf) -> _ArraySelf: ... + def conjugate(self: _ArraySelf) -> _ArraySelf: ... + @overload def cumprod( self, @@ -1415,6 +1459,7 @@ class _ArrayOrScalarCommon: dtype: DTypeLike = ..., out: _NdArraySubClass = ..., ) -> _NdArraySubClass: ... + @overload def cumsum( self, @@ -1429,15 +1474,7 @@ class _ArrayOrScalarCommon: dtype: DTypeLike = ..., out: _NdArraySubClass = ..., ) -> _NdArraySubClass: ... - @overload - def max( - self, - axis: None = ..., - out: None = ..., - keepdims: Literal[False] = ..., - initial: _NumberLike_co = ..., - where: _ArrayLikeBool = ..., - ) -> number: ... + @overload def max( self, @@ -1446,7 +1483,7 @@ class _ArrayOrScalarCommon: keepdims: bool = ..., initial: _NumberLike_co = ..., where: _ArrayLikeBool = ..., - ) -> Union[number, ndarray]: ... + ) -> Any: ... @overload def max( self, @@ -1456,14 +1493,7 @@ class _ArrayOrScalarCommon: initial: _NumberLike_co = ..., where: _ArrayLikeBool = ..., ) -> _NdArraySubClass: ... - @overload - def mean( - self, - axis: None = ..., - dtype: DTypeLike = ..., - out: None = ..., - keepdims: Literal[False] = ..., - ) -> number: ... + @overload def mean( self, @@ -1471,7 +1501,7 @@ class _ArrayOrScalarCommon: dtype: DTypeLike = ..., out: None = ..., keepdims: bool = ..., - ) -> Union[number, ndarray]: ... + ) -> Any: ... @overload def mean( self, @@ -1480,15 +1510,7 @@ class _ArrayOrScalarCommon: out: _NdArraySubClass = ..., keepdims: bool = ..., ) -> _NdArraySubClass: ... - @overload - def min( - self, - axis: None = ..., - out: None = ..., - keepdims: Literal[False] = ..., - initial: _NumberLike_co = ..., - where: _ArrayLikeBool = ..., - ) -> number: ... + @overload def min( self, @@ -1497,7 +1519,7 @@ class _ArrayOrScalarCommon: keepdims: bool = ..., initial: _NumberLike_co = ..., where: _ArrayLikeBool = ..., - ) -> Union[number, ndarray]: ... + ) -> Any: ... @overload def min( self, @@ -1507,17 +1529,12 @@ class _ArrayOrScalarCommon: initial: _NumberLike_co = ..., where: _ArrayLikeBool = ..., ) -> _NdArraySubClass: ... - def newbyteorder(self: _ArraySelf, __new_order: _ByteOrder = ...) -> _ArraySelf: ... - @overload - def prod( - self, - axis: None = ..., - dtype: DTypeLike = ..., - out: None = ..., - keepdims: Literal[False] = ..., - initial: _NumberLike_co = ..., - where: _ArrayLikeBool = ..., - ) -> number: ... + + def newbyteorder( + self: _ArraySelf, + __new_order: _ByteOrder = ..., + ) -> _ArraySelf: ... + @overload def prod( self, @@ -1527,7 +1544,7 @@ class _ArrayOrScalarCommon: keepdims: bool = ..., initial: _NumberLike_co = ..., where: _ArrayLikeBool = ..., - ) -> Union[number, ndarray]: ... + ) -> Any: ... @overload def prod( self, @@ -1538,14 +1555,14 @@ class _ArrayOrScalarCommon: initial: _NumberLike_co = ..., where: _ArrayLikeBool = ..., ) -> _NdArraySubClass: ... + @overload def ptp( - self, axis: None = ..., out: None = ..., keepdims: Literal[False] = ..., - ) -> number: ... - @overload - def ptp( - self, axis: Optional[_ShapeLike] = ..., out: None = ..., keepdims: bool = ..., - ) -> Union[number, ndarray]: ... + self, + axis: Optional[_ShapeLike] = ..., + out: None = ..., + keepdims: bool = ..., + ) -> Any: ... @overload def ptp( self, @@ -1553,26 +1570,26 @@ class _ArrayOrScalarCommon: out: _NdArraySubClass = ..., keepdims: bool = ..., ) -> _NdArraySubClass: ... + def repeat( - self, repeats: _ArrayLikeIntOrBool, axis: Optional[SupportsIndex] = ... + self, + repeats: _ArrayLikeIntOrBool, + axis: Optional[SupportsIndex] = ..., ) -> ndarray: ... + @overload def round( - self: _ArraySelf, decimals: SupportsIndex = ..., out: None = ... + self: _ArraySelf, + decimals: SupportsIndex = ..., + out: None = ..., ) -> _ArraySelf: ... @overload def round( - self, decimals: SupportsIndex = ..., out: _NdArraySubClass = ... - ) -> _NdArraySubClass: ... - @overload - def std( self, - axis: None = ..., - dtype: DTypeLike = ..., - out: None = ..., - ddof: int = ..., - keepdims: Literal[False] = ..., - ) -> number: ... + decimals: SupportsIndex = ..., + out: _NdArraySubClass = ..., + ) -> _NdArraySubClass: ... + @overload def std( self, @@ -1581,7 +1598,7 @@ class _ArrayOrScalarCommon: out: None = ..., ddof: int = ..., keepdims: bool = ..., - ) -> Union[number, ndarray]: ... + ) -> Any: ... @overload def std( self, @@ -1591,16 +1608,7 @@ class _ArrayOrScalarCommon: ddof: int = ..., keepdims: bool = ..., ) -> _NdArraySubClass: ... - @overload - def sum( - self, - axis: None = ..., - dtype: DTypeLike = ..., - out: None = ..., - keepdims: Literal[False] = ..., - initial: _NumberLike_co = ..., - where: _ArrayLikeBool = ..., - ) -> number: ... + @overload def sum( self, @@ -1610,7 +1618,7 @@ class _ArrayOrScalarCommon: keepdims: bool = ..., initial: _NumberLike_co = ..., where: _ArrayLikeBool = ..., - ) -> Union[number, ndarray]: ... + ) -> Any: ... @overload def sum( self, @@ -1621,6 +1629,7 @@ class _ArrayOrScalarCommon: initial: _NumberLike_co = ..., where: _ArrayLikeBool = ..., ) -> _NdArraySubClass: ... + @overload def take( self, @@ -1628,7 +1637,7 @@ class _ArrayOrScalarCommon: axis: Optional[SupportsIndex] = ..., out: None = ..., mode: _ModeKind = ..., - ) -> generic: ... + ) -> Any: ... @overload def take( self, @@ -1645,15 +1654,7 @@ class _ArrayOrScalarCommon: out: _NdArraySubClass = ..., mode: _ModeKind = ..., ) -> _NdArraySubClass: ... - @overload - def var( - self, - axis: None = ..., - dtype: DTypeLike = ..., - out: None = ..., - ddof: int = ..., - keepdims: Literal[False] = ..., - ) -> number: ... + @overload def var( self, @@ -1662,7 +1663,7 @@ class _ArrayOrScalarCommon: out: None = ..., ddof: int = ..., keepdims: bool = ..., - ) -> Union[number, ndarray]: ... + ) -> Any: ... @overload def var( self, @@ -1772,7 +1773,7 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): axis2: SupportsIndex = ..., ) -> _ArraySelf: ... @overload - def dot(self, b: ArrayLike, out: None = ...) -> Union[number, ndarray]: ... + def dot(self, b: ArrayLike, out: None = ...) -> ndarray: ... @overload def dot(self, b: ArrayLike, out: _NdArraySubClass = ...) -> _NdArraySubClass: ... # `nonzero()` is deprecated for 0d arrays/generics @@ -1812,7 +1813,7 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): axis2: SupportsIndex = ..., dtype: DTypeLike = ..., out: None = ..., - ) -> Union[number, ndarray]: ... + ) -> Any: ... @overload def trace( self, # >= 2D array @@ -1843,105 +1844,105 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __lt__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __lt__(self: _ArrayNumber_co, other: _ArrayLikeNumber_co) -> _ArrayOrScalar[bool_]: ... + def __lt__(self: _ArrayNumber_co, other: _ArrayLikeNumber_co) -> _ArrayND[bool_]: ... @overload - def __lt__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> _ArrayOrScalar[bool_]: ... + def __lt__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> _ArrayND[bool_]: ... @overload - def __lt__(self: _ArrayND[datetime64], other: _ArrayLikeDT64_co) -> _ArrayOrScalar[bool_]: ... + def __lt__(self: _ArrayND[datetime64], other: _ArrayLikeDT64_co) -> _ArrayND[bool_]: ... @overload - def __lt__(self: _ArrayND[object_], other: Any) -> _ArrayOrScalar[bool_]: ... + def __lt__(self: _ArrayND[object_], other: Any) -> _ArrayND[bool_]: ... @overload - def __lt__(self: _ArrayND[Any], other: _ArrayLikeObject_co) -> _ArrayOrScalar[bool_]: ... + def __lt__(self: _ArrayND[Any], other: _ArrayLikeObject_co) -> _ArrayND[bool_]: ... @overload def __lt__( self: _ArrayND[Union[number[Any], datetime64, timedelta64, bool_]], other: _RecursiveSequence, - ) -> _ArrayOrScalar[bool_]: ... + ) -> _ArrayND[bool_]: ... @overload def __le__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __le__(self: _ArrayNumber_co, other: _ArrayLikeNumber_co) -> _ArrayOrScalar[bool_]: ... + def __le__(self: _ArrayNumber_co, other: _ArrayLikeNumber_co) -> _ArrayND[bool_]: ... @overload - def __le__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> _ArrayOrScalar[bool_]: ... + def __le__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> _ArrayND[bool_]: ... @overload - def __le__(self: _ArrayND[datetime64], other: _ArrayLikeDT64_co) -> _ArrayOrScalar[bool_]: ... + def __le__(self: _ArrayND[datetime64], other: _ArrayLikeDT64_co) -> _ArrayND[bool_]: ... @overload - def __le__(self: _ArrayND[object_], other: Any) -> _ArrayOrScalar[bool_]: ... + def __le__(self: _ArrayND[object_], other: Any) -> _ArrayND[bool_]: ... @overload - def __le__(self: _ArrayND[Any], other: _ArrayLikeObject_co) -> _ArrayOrScalar[bool_]: ... + def __le__(self: _ArrayND[Any], other: _ArrayLikeObject_co) -> _ArrayND[bool_]: ... @overload def __le__( self: _ArrayND[Union[number[Any], datetime64, timedelta64, bool_]], other: _RecursiveSequence, - ) -> _ArrayOrScalar[bool_]: ... + ) -> _ArrayND[bool_]: ... @overload def __gt__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __gt__(self: _ArrayNumber_co, other: _ArrayLikeNumber_co) -> _ArrayOrScalar[bool_]: ... + def __gt__(self: _ArrayNumber_co, other: _ArrayLikeNumber_co) -> _ArrayND[bool_]: ... @overload - def __gt__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> _ArrayOrScalar[bool_]: ... + def __gt__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> _ArrayND[bool_]: ... @overload - def __gt__(self: _ArrayND[datetime64], other: _ArrayLikeDT64_co) -> _ArrayOrScalar[bool_]: ... + def __gt__(self: _ArrayND[datetime64], other: _ArrayLikeDT64_co) -> _ArrayND[bool_]: ... @overload - def __gt__(self: _ArrayND[object_], other: Any) -> _ArrayOrScalar[bool_]: ... + def __gt__(self: _ArrayND[object_], other: Any) -> _ArrayND[bool_]: ... @overload - def __gt__(self: _ArrayND[Any], other: _ArrayLikeObject_co) -> _ArrayOrScalar[bool_]: ... + def __gt__(self: _ArrayND[Any], other: _ArrayLikeObject_co) -> _ArrayND[bool_]: ... @overload def __gt__( self: _ArrayND[Union[number[Any], datetime64, timedelta64, bool_]], other: _RecursiveSequence, - ) -> _ArrayOrScalar[bool_]: ... + ) -> _ArrayND[bool_]: ... @overload def __ge__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __ge__(self: _ArrayNumber_co, other: _ArrayLikeNumber_co) -> _ArrayOrScalar[bool_]: ... + def __ge__(self: _ArrayNumber_co, other: _ArrayLikeNumber_co) -> _ArrayND[bool_]: ... @overload - def __ge__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> _ArrayOrScalar[bool_]: ... + def __ge__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> _ArrayND[bool_]: ... @overload - def __ge__(self: _ArrayND[datetime64], other: _ArrayLikeDT64_co) -> _ArrayOrScalar[bool_]: ... + def __ge__(self: _ArrayND[datetime64], other: _ArrayLikeDT64_co) -> _ArrayND[bool_]: ... @overload - def __ge__(self: _ArrayND[object_], other: Any) -> _ArrayOrScalar[bool_]: ... + def __ge__(self: _ArrayND[object_], other: Any) -> _ArrayND[bool_]: ... @overload - def __ge__(self: _ArrayND[Any], other: _ArrayLikeObject_co) -> _ArrayOrScalar[bool_]: ... + def __ge__(self: _ArrayND[Any], other: _ArrayLikeObject_co) -> _ArrayND[bool_]: ... @overload def __ge__( self: _ArrayND[Union[number[Any], datetime64, timedelta64, bool_]], other: _RecursiveSequence, - ) -> _ArrayOrScalar[bool_]: ... + ) -> _ArrayND[bool_]: ... # Unary ops @overload - def __abs__(self: _ArrayND[bool_]) -> _ArrayOrScalar[bool_]: ... + def __abs__(self: _ArrayND[bool_]) -> _ArrayND[bool_]: ... @overload - def __abs__(self: _ArrayND[complexfloating[_NBit1, _NBit1]]) -> _ArrayOrScalar[floating[_NBit1]]: ... + def __abs__(self: _ArrayND[complexfloating[_NBit1, _NBit1]]) -> _ArrayND[floating[_NBit1]]: ... @overload - def __abs__(self: _ArrayND[_NumberType]) -> _ArrayOrScalar[_NumberType]: ... + def __abs__(self: _ArrayND[_NumberType]) -> _ArrayND[_NumberType]: ... @overload - def __abs__(self: _ArrayND[timedelta64]) -> _ArrayOrScalar[timedelta64]: ... + def __abs__(self: _ArrayND[timedelta64]) -> _ArrayND[timedelta64]: ... @overload def __abs__(self: _ArrayND[object_]) -> Any: ... @overload - def __invert__(self: _ArrayND[bool_]) -> _ArrayOrScalar[bool_]: ... + def __invert__(self: _ArrayND[bool_]) -> _ArrayND[bool_]: ... @overload - def __invert__(self: _ArrayND[_IntType]) -> _ArrayOrScalar[_IntType]: ... + def __invert__(self: _ArrayND[_IntType]) -> _ArrayND[_IntType]: ... @overload def __invert__(self: _ArrayND[object_]) -> Any: ... @overload - def __pos__(self: _ArrayND[_NumberType]) -> _ArrayOrScalar[_NumberType]: ... + def __pos__(self: _ArrayND[_NumberType]) -> _ArrayND[_NumberType]: ... @overload - def __pos__(self: _ArrayND[timedelta64]) -> _ArrayOrScalar[timedelta64]: ... + def __pos__(self: _ArrayND[timedelta64]) -> _ArrayND[timedelta64]: ... @overload def __pos__(self: _ArrayND[object_]) -> Any: ... @overload - def __neg__(self: _ArrayND[_NumberType]) -> _ArrayOrScalar[_NumberType]: ... + def __neg__(self: _ArrayND[_NumberType]) -> _ArrayND[_NumberType]: ... @overload - def __neg__(self: _ArrayND[timedelta64]) -> _ArrayOrScalar[timedelta64]: ... + def __neg__(self: _ArrayND[timedelta64]) -> _ArrayND[timedelta64]: ... @overload def __neg__(self: _ArrayND[object_]) -> Any: ... @@ -1950,15 +1951,15 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __matmul__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __matmul__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[bool_]: ... # type: ignore[misc] + def __matmul__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[bool_]: ... # type: ignore[misc] @overload - def __matmul__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __matmul__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __matmul__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... # type: ignore[misc] + def __matmul__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... # type: ignore[misc] @overload - def __matmul__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayOrScalar[floating[Any]]: ... # type: ignore[misc] + def __matmul__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayND[floating[Any]]: ... # type: ignore[misc] @overload - def __matmul__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayOrScalar[complexfloating[Any, Any]]: ... + def __matmul__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayND[complexfloating[Any, Any]]: ... @overload def __matmul__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -1972,15 +1973,15 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __rmatmul__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __rmatmul__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[bool_]: ... # type: ignore[misc] + def __rmatmul__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[bool_]: ... # type: ignore[misc] @overload - def __rmatmul__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __rmatmul__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __rmatmul__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... # type: ignore[misc] + def __rmatmul__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... # type: ignore[misc] @overload - def __rmatmul__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayOrScalar[floating[Any]]: ... # type: ignore[misc] + def __rmatmul__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayND[floating[Any]]: ... # type: ignore[misc] @overload - def __rmatmul__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayOrScalar[complexfloating[Any, Any]]: ... + def __rmatmul__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayND[complexfloating[Any, Any]]: ... @overload def __rmatmul__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -1994,15 +1995,15 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __mod__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __mod__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[int8]: ... # type: ignore[misc] + def __mod__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[int8]: ... # type: ignore[misc] @overload - def __mod__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __mod__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __mod__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... # type: ignore[misc] + def __mod__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... # type: ignore[misc] @overload - def __mod__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayOrScalar[floating[Any]]: ... # type: ignore[misc] + def __mod__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayND[floating[Any]]: ... # type: ignore[misc] @overload - def __mod__(self: _ArrayTD64_co, other: _NestedSequence[_SupportsArray[dtype[timedelta64]]]) -> _ArrayOrScalar[timedelta64]: ... + def __mod__(self: _ArrayTD64_co, other: _NestedSequence[_SupportsArray[dtype[timedelta64]]]) -> _ArrayND[timedelta64]: ... @overload def __mod__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2016,15 +2017,15 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __rmod__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __rmod__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[int8]: ... # type: ignore[misc] + def __rmod__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[int8]: ... # type: ignore[misc] @overload - def __rmod__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __rmod__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __rmod__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... # type: ignore[misc] + def __rmod__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... # type: ignore[misc] @overload - def __rmod__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayOrScalar[floating[Any]]: ... # type: ignore[misc] + def __rmod__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayND[floating[Any]]: ... # type: ignore[misc] @overload - def __rmod__(self: _ArrayTD64_co, other: _NestedSequence[_SupportsArray[dtype[timedelta64]]]) -> _ArrayOrScalar[timedelta64]: ... + def __rmod__(self: _ArrayTD64_co, other: _NestedSequence[_SupportsArray[dtype[timedelta64]]]) -> _ArrayND[timedelta64]: ... @overload def __rmod__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2038,15 +2039,15 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __divmod__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __divmod__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _2Tuple[_ArrayOrScalar[int8]]: ... # type: ignore[misc] + def __divmod__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _2Tuple[_ArrayND[int8]]: ... # type: ignore[misc] @overload - def __divmod__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _2Tuple[_ArrayOrScalar[unsignedinteger[Any]]]: ... # type: ignore[misc] + def __divmod__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _2Tuple[_ArrayND[unsignedinteger[Any]]]: ... # type: ignore[misc] @overload - def __divmod__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _2Tuple[_ArrayOrScalar[signedinteger[Any]]]: ... # type: ignore[misc] + def __divmod__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _2Tuple[_ArrayND[signedinteger[Any]]]: ... # type: ignore[misc] @overload - def __divmod__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _2Tuple[_ArrayOrScalar[floating[Any]]]: ... # type: ignore[misc] + def __divmod__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _2Tuple[_ArrayND[floating[Any]]]: ... # type: ignore[misc] @overload - def __divmod__(self: _ArrayTD64_co, other: _NestedSequence[_SupportsArray[dtype[timedelta64]]]) -> Union[Tuple[int64, timedelta64], Tuple[_ArrayND[int64], _ArrayND[timedelta64]]]: ... + def __divmod__(self: _ArrayTD64_co, other: _NestedSequence[_SupportsArray[dtype[timedelta64]]]) -> Tuple[_ArrayND[int64], _ArrayND[timedelta64]]: ... @overload def __divmod__( self: _ArrayND[Union[bool_, integer[Any], floating[Any], timedelta64]], @@ -2056,15 +2057,15 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __rdivmod__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __rdivmod__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _2Tuple[_ArrayOrScalar[int8]]: ... # type: ignore[misc] + def __rdivmod__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _2Tuple[_ArrayND[int8]]: ... # type: ignore[misc] @overload - def __rdivmod__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _2Tuple[_ArrayOrScalar[unsignedinteger[Any]]]: ... # type: ignore[misc] + def __rdivmod__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _2Tuple[_ArrayND[unsignedinteger[Any]]]: ... # type: ignore[misc] @overload - def __rdivmod__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _2Tuple[_ArrayOrScalar[signedinteger[Any]]]: ... # type: ignore[misc] + def __rdivmod__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _2Tuple[_ArrayND[signedinteger[Any]]]: ... # type: ignore[misc] @overload - def __rdivmod__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _2Tuple[_ArrayOrScalar[floating[Any]]]: ... # type: ignore[misc] + def __rdivmod__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _2Tuple[_ArrayND[floating[Any]]]: ... # type: ignore[misc] @overload - def __rdivmod__(self: _ArrayTD64_co, other: _NestedSequence[_SupportsArray[dtype[timedelta64]]]) -> Union[Tuple[int64, timedelta64], Tuple[_ArrayND[int64], _ArrayND[timedelta64]]]: ... + def __rdivmod__(self: _ArrayTD64_co, other: _NestedSequence[_SupportsArray[dtype[timedelta64]]]) -> Tuple[_ArrayND[int64], _ArrayND[timedelta64]]: ... @overload def __rdivmod__( self: _ArrayND[Union[bool_, integer[Any], floating[Any], timedelta64]], @@ -2074,21 +2075,21 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __add__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __add__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[bool_]: ... # type: ignore[misc] + def __add__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[bool_]: ... # type: ignore[misc] @overload - def __add__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __add__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __add__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... # type: ignore[misc] + def __add__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... # type: ignore[misc] @overload - def __add__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayOrScalar[floating[Any]]: ... # type: ignore[misc] + def __add__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayND[floating[Any]]: ... # type: ignore[misc] @overload - def __add__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayOrScalar[complexfloating[Any, Any]]: ... # type: ignore[misc] + def __add__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayND[complexfloating[Any, Any]]: ... # type: ignore[misc] @overload - def __add__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> _ArrayOrScalar[timedelta64]: ... # type: ignore[misc] + def __add__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> _ArrayND[timedelta64]: ... # type: ignore[misc] @overload - def __add__(self: _ArrayTD64_co, other: _ArrayLikeDT64_co) -> _ArrayOrScalar[datetime64]: ... + def __add__(self: _ArrayTD64_co, other: _ArrayLikeDT64_co) -> _ArrayND[datetime64]: ... @overload - def __add__(self: _ArrayND[datetime64], other: _ArrayLikeTD64_co) -> _ArrayOrScalar[datetime64]: ... + def __add__(self: _ArrayND[datetime64], other: _ArrayLikeTD64_co) -> _ArrayND[datetime64]: ... @overload def __add__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2102,21 +2103,21 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __radd__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __radd__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[bool_]: ... # type: ignore[misc] + def __radd__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[bool_]: ... # type: ignore[misc] @overload - def __radd__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __radd__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __radd__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... # type: ignore[misc] + def __radd__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... # type: ignore[misc] @overload - def __radd__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayOrScalar[floating[Any]]: ... # type: ignore[misc] + def __radd__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayND[floating[Any]]: ... # type: ignore[misc] @overload - def __radd__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayOrScalar[complexfloating[Any, Any]]: ... # type: ignore[misc] + def __radd__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayND[complexfloating[Any, Any]]: ... # type: ignore[misc] @overload - def __radd__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> _ArrayOrScalar[timedelta64]: ... # type: ignore[misc] + def __radd__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> _ArrayND[timedelta64]: ... # type: ignore[misc] @overload - def __radd__(self: _ArrayTD64_co, other: _ArrayLikeDT64_co) -> _ArrayOrScalar[datetime64]: ... + def __radd__(self: _ArrayTD64_co, other: _ArrayLikeDT64_co) -> _ArrayND[datetime64]: ... @overload - def __radd__(self: _ArrayND[datetime64], other: _ArrayLikeTD64_co) -> _ArrayOrScalar[datetime64]: ... + def __radd__(self: _ArrayND[datetime64], other: _ArrayLikeTD64_co) -> _ArrayND[datetime64]: ... @overload def __radd__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2132,19 +2133,19 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __sub__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> NoReturn: ... @overload - def __sub__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __sub__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __sub__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... # type: ignore[misc] + def __sub__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... # type: ignore[misc] @overload - def __sub__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayOrScalar[floating[Any]]: ... # type: ignore[misc] + def __sub__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayND[floating[Any]]: ... # type: ignore[misc] @overload - def __sub__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayOrScalar[complexfloating[Any, Any]]: ... # type: ignore[misc] + def __sub__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayND[complexfloating[Any, Any]]: ... # type: ignore[misc] @overload - def __sub__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> _ArrayOrScalar[timedelta64]: ... # type: ignore[misc] + def __sub__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> _ArrayND[timedelta64]: ... # type: ignore[misc] @overload - def __sub__(self: _ArrayND[datetime64], other: _ArrayLikeTD64_co) -> _ArrayOrScalar[datetime64]: ... + def __sub__(self: _ArrayND[datetime64], other: _ArrayLikeTD64_co) -> _ArrayND[datetime64]: ... @overload - def __sub__(self: _ArrayND[datetime64], other: _ArrayLikeDT64_co) -> _ArrayOrScalar[timedelta64]: ... + def __sub__(self: _ArrayND[datetime64], other: _ArrayLikeDT64_co) -> _ArrayND[timedelta64]: ... @overload def __sub__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2160,19 +2161,19 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __rsub__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> NoReturn: ... @overload - def __rsub__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __rsub__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __rsub__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... # type: ignore[misc] + def __rsub__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... # type: ignore[misc] @overload - def __rsub__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayOrScalar[floating[Any]]: ... # type: ignore[misc] + def __rsub__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayND[floating[Any]]: ... # type: ignore[misc] @overload - def __rsub__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayOrScalar[complexfloating[Any, Any]]: ... # type: ignore[misc] + def __rsub__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayND[complexfloating[Any, Any]]: ... # type: ignore[misc] @overload - def __rsub__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> _ArrayOrScalar[timedelta64]: ... # type: ignore[misc] + def __rsub__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> _ArrayND[timedelta64]: ... # type: ignore[misc] @overload - def __rsub__(self: _ArrayTD64_co, other: _ArrayLikeDT64_co) -> _ArrayOrScalar[datetime64]: ... # type: ignore[misc] + def __rsub__(self: _ArrayTD64_co, other: _ArrayLikeDT64_co) -> _ArrayND[datetime64]: ... # type: ignore[misc] @overload - def __rsub__(self: _ArrayND[datetime64], other: _ArrayLikeDT64_co) -> _ArrayOrScalar[timedelta64]: ... + def __rsub__(self: _ArrayND[datetime64], other: _ArrayLikeDT64_co) -> _ArrayND[timedelta64]: ... @overload def __rsub__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2186,19 +2187,19 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __mul__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __mul__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[bool_]: ... # type: ignore[misc] + def __mul__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[bool_]: ... # type: ignore[misc] @overload - def __mul__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __mul__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __mul__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... # type: ignore[misc] + def __mul__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... # type: ignore[misc] @overload - def __mul__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayOrScalar[floating[Any]]: ... # type: ignore[misc] + def __mul__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayND[floating[Any]]: ... # type: ignore[misc] @overload - def __mul__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayOrScalar[complexfloating[Any, Any]]: ... # type: ignore[misc] + def __mul__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayND[complexfloating[Any, Any]]: ... # type: ignore[misc] @overload - def __mul__(self: _ArrayTD64_co, other: _ArrayLikeFloat_co) -> _ArrayOrScalar[timedelta64]: ... + def __mul__(self: _ArrayTD64_co, other: _ArrayLikeFloat_co) -> _ArrayND[timedelta64]: ... @overload - def __mul__(self: _ArrayFloat_co, other: _ArrayLikeTD64_co) -> _ArrayOrScalar[timedelta64]: ... + def __mul__(self: _ArrayFloat_co, other: _ArrayLikeTD64_co) -> _ArrayND[timedelta64]: ... @overload def __mul__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2212,19 +2213,19 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __rmul__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __rmul__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[bool_]: ... # type: ignore[misc] + def __rmul__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[bool_]: ... # type: ignore[misc] @overload - def __rmul__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __rmul__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __rmul__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... # type: ignore[misc] + def __rmul__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... # type: ignore[misc] @overload - def __rmul__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayOrScalar[floating[Any]]: ... # type: ignore[misc] + def __rmul__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayND[floating[Any]]: ... # type: ignore[misc] @overload - def __rmul__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayOrScalar[complexfloating[Any, Any]]: ... # type: ignore[misc] + def __rmul__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayND[complexfloating[Any, Any]]: ... # type: ignore[misc] @overload - def __rmul__(self: _ArrayTD64_co, other: _ArrayLikeFloat_co) -> _ArrayOrScalar[timedelta64]: ... + def __rmul__(self: _ArrayTD64_co, other: _ArrayLikeFloat_co) -> _ArrayND[timedelta64]: ... @overload - def __rmul__(self: _ArrayFloat_co, other: _ArrayLikeTD64_co) -> _ArrayOrScalar[timedelta64]: ... + def __rmul__(self: _ArrayFloat_co, other: _ArrayLikeTD64_co) -> _ArrayND[timedelta64]: ... @overload def __rmul__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2238,21 +2239,21 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __floordiv__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __floordiv__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[int8]: ... # type: ignore[misc] + def __floordiv__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[int8]: ... # type: ignore[misc] @overload - def __floordiv__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __floordiv__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __floordiv__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... # type: ignore[misc] + def __floordiv__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... # type: ignore[misc] @overload - def __floordiv__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayOrScalar[floating[Any]]: ... # type: ignore[misc] + def __floordiv__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayND[floating[Any]]: ... # type: ignore[misc] @overload - def __floordiv__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayOrScalar[complexfloating[Any, Any]]: ... # type: ignore[misc] + def __floordiv__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayND[complexfloating[Any, Any]]: ... # type: ignore[misc] @overload - def __floordiv__(self: _ArrayND[timedelta64], other: _NestedSequence[_SupportsArray[dtype[timedelta64]]]) -> _ArrayOrScalar[int64]: ... + def __floordiv__(self: _ArrayND[timedelta64], other: _NestedSequence[_SupportsArray[dtype[timedelta64]]]) -> _ArrayND[int64]: ... @overload def __floordiv__(self: _ArrayND[timedelta64], other: _ArrayLikeBool_co) -> NoReturn: ... @overload - def __floordiv__(self: _ArrayND[timedelta64], other: _ArrayLikeFloat_co) -> _ArrayOrScalar[timedelta64]: ... + def __floordiv__(self: _ArrayND[timedelta64], other: _ArrayLikeFloat_co) -> _ArrayND[timedelta64]: ... @overload def __floordiv__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2266,21 +2267,21 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __rfloordiv__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __rfloordiv__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[int8]: ... # type: ignore[misc] + def __rfloordiv__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[int8]: ... # type: ignore[misc] @overload - def __rfloordiv__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __rfloordiv__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __rfloordiv__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... # type: ignore[misc] + def __rfloordiv__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... # type: ignore[misc] @overload - def __rfloordiv__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayOrScalar[floating[Any]]: ... # type: ignore[misc] + def __rfloordiv__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayND[floating[Any]]: ... # type: ignore[misc] @overload - def __rfloordiv__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayOrScalar[complexfloating[Any, Any]]: ... # type: ignore[misc] + def __rfloordiv__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayND[complexfloating[Any, Any]]: ... # type: ignore[misc] @overload - def __rfloordiv__(self: _ArrayND[timedelta64], other: _NestedSequence[_SupportsArray[dtype[timedelta64]]]) -> _ArrayOrScalar[int64]: ... + def __rfloordiv__(self: _ArrayND[timedelta64], other: _NestedSequence[_SupportsArray[dtype[timedelta64]]]) -> _ArrayND[int64]: ... @overload def __rfloordiv__(self: _ArrayND[bool_], other: _ArrayLikeTD64_co) -> NoReturn: ... @overload - def __rfloordiv__(self: _ArrayFloat_co, other: _ArrayLikeTD64_co) -> _ArrayOrScalar[timedelta64]: ... + def __rfloordiv__(self: _ArrayFloat_co, other: _ArrayLikeTD64_co) -> _ArrayND[timedelta64]: ... @overload def __rfloordiv__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2294,15 +2295,15 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __pow__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __pow__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[int8]: ... # type: ignore[misc] + def __pow__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[int8]: ... # type: ignore[misc] @overload - def __pow__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __pow__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __pow__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... # type: ignore[misc] + def __pow__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... # type: ignore[misc] @overload - def __pow__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayOrScalar[floating[Any]]: ... # type: ignore[misc] + def __pow__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayND[floating[Any]]: ... # type: ignore[misc] @overload - def __pow__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayOrScalar[complexfloating[Any, Any]]: ... + def __pow__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayND[complexfloating[Any, Any]]: ... @overload def __pow__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2316,15 +2317,15 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __rpow__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __rpow__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[int8]: ... # type: ignore[misc] + def __rpow__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[int8]: ... # type: ignore[misc] @overload - def __rpow__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __rpow__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __rpow__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... # type: ignore[misc] + def __rpow__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... # type: ignore[misc] @overload - def __rpow__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayOrScalar[floating[Any]]: ... # type: ignore[misc] + def __rpow__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayND[floating[Any]]: ... # type: ignore[misc] @overload - def __rpow__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayOrScalar[complexfloating[Any, Any]]: ... + def __rpow__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayND[complexfloating[Any, Any]]: ... @overload def __rpow__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2338,17 +2339,17 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __truediv__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __truediv__(self: _ArrayInt_co, other: _ArrayInt_co) -> _ArrayOrScalar[float64]: ... # type: ignore[misc] + def __truediv__(self: _ArrayInt_co, other: _ArrayInt_co) -> _ArrayND[float64]: ... # type: ignore[misc] @overload - def __truediv__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayOrScalar[floating[Any]]: ... # type: ignore[misc] + def __truediv__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayND[floating[Any]]: ... # type: ignore[misc] @overload - def __truediv__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayOrScalar[complexfloating[Any, Any]]: ... # type: ignore[misc] + def __truediv__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayND[complexfloating[Any, Any]]: ... # type: ignore[misc] @overload - def __truediv__(self: _ArrayND[timedelta64], other: _NestedSequence[_SupportsArray[dtype[timedelta64]]]) -> _ArrayOrScalar[float64]: ... + def __truediv__(self: _ArrayND[timedelta64], other: _NestedSequence[_SupportsArray[dtype[timedelta64]]]) -> _ArrayND[float64]: ... @overload def __truediv__(self: _ArrayND[timedelta64], other: _ArrayLikeBool_co) -> NoReturn: ... @overload - def __truediv__(self: _ArrayND[timedelta64], other: _ArrayLikeFloat_co) -> _ArrayOrScalar[timedelta64]: ... + def __truediv__(self: _ArrayND[timedelta64], other: _ArrayLikeFloat_co) -> _ArrayND[timedelta64]: ... @overload def __truediv__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2362,17 +2363,17 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __rtruediv__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __rtruediv__(self: _ArrayInt_co, other: _ArrayInt_co) -> _ArrayOrScalar[float64]: ... # type: ignore[misc] + def __rtruediv__(self: _ArrayInt_co, other: _ArrayInt_co) -> _ArrayND[float64]: ... # type: ignore[misc] @overload - def __rtruediv__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayOrScalar[floating[Any]]: ... # type: ignore[misc] + def __rtruediv__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayND[floating[Any]]: ... # type: ignore[misc] @overload - def __rtruediv__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayOrScalar[complexfloating[Any, Any]]: ... # type: ignore[misc] + def __rtruediv__(self: _ArrayComplex_co, other: _ArrayLikeComplex_co) -> _ArrayND[complexfloating[Any, Any]]: ... # type: ignore[misc] @overload - def __rtruediv__(self: _ArrayND[timedelta64], other: _NestedSequence[_SupportsArray[dtype[timedelta64]]]) -> _ArrayOrScalar[float64]: ... + def __rtruediv__(self: _ArrayND[timedelta64], other: _NestedSequence[_SupportsArray[dtype[timedelta64]]]) -> _ArrayND[float64]: ... @overload def __rtruediv__(self: _ArrayND[bool_], other: _ArrayLikeTD64_co) -> NoReturn: ... @overload - def __rtruediv__(self: _ArrayFloat_co, other: _ArrayLikeTD64_co) -> _ArrayOrScalar[timedelta64]: ... + def __rtruediv__(self: _ArrayFloat_co, other: _ArrayLikeTD64_co) -> _ArrayND[timedelta64]: ... @overload def __rtruediv__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2386,11 +2387,11 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __lshift__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __lshift__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[int8]: ... # type: ignore[misc] + def __lshift__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[int8]: ... # type: ignore[misc] @overload - def __lshift__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __lshift__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __lshift__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... + def __lshift__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... @overload def __lshift__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2404,11 +2405,11 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __rlshift__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __rlshift__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[int8]: ... # type: ignore[misc] + def __rlshift__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[int8]: ... # type: ignore[misc] @overload - def __rlshift__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __rlshift__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __rlshift__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... + def __rlshift__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... @overload def __rlshift__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2422,11 +2423,11 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __rshift__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __rshift__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[int8]: ... # type: ignore[misc] + def __rshift__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[int8]: ... # type: ignore[misc] @overload - def __rshift__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __rshift__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __rshift__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... + def __rshift__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... @overload def __rshift__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2440,11 +2441,11 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __rrshift__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __rrshift__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[int8]: ... # type: ignore[misc] + def __rrshift__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[int8]: ... # type: ignore[misc] @overload - def __rrshift__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __rrshift__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __rrshift__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... + def __rrshift__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... @overload def __rrshift__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2458,11 +2459,11 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __and__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __and__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[bool_]: ... # type: ignore[misc] + def __and__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[bool_]: ... # type: ignore[misc] @overload - def __and__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __and__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __and__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... + def __and__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... @overload def __and__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2476,11 +2477,11 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __rand__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __rand__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[bool_]: ... # type: ignore[misc] + def __rand__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[bool_]: ... # type: ignore[misc] @overload - def __rand__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __rand__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __rand__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... + def __rand__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... @overload def __rand__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2494,11 +2495,11 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __xor__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __xor__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[bool_]: ... # type: ignore[misc] + def __xor__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[bool_]: ... # type: ignore[misc] @overload - def __xor__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __xor__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __xor__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... + def __xor__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... @overload def __xor__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2512,11 +2513,11 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __rxor__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __rxor__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[bool_]: ... # type: ignore[misc] + def __rxor__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[bool_]: ... # type: ignore[misc] @overload - def __rxor__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __rxor__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __rxor__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... + def __rxor__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... @overload def __rxor__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2530,11 +2531,11 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __or__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __or__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[bool_]: ... # type: ignore[misc] + def __or__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[bool_]: ... # type: ignore[misc] @overload - def __or__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __or__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __or__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... + def __or__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... @overload def __or__(self: _ArrayND[object_], other: Any) -> Any: ... @overload @@ -2548,11 +2549,11 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]): @overload def __ror__(self: _ArrayND[Any], other: _NestedSequence[Union[str, bytes]]) -> NoReturn: ... @overload - def __ror__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayOrScalar[bool_]: ... # type: ignore[misc] + def __ror__(self: _ArrayND[bool_], other: _ArrayLikeBool_co) -> _ArrayND[bool_]: ... # type: ignore[misc] @overload - def __ror__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayOrScalar[unsignedinteger[Any]]: ... # type: ignore[misc] + def __ror__(self: _ArrayUInt_co, other: _ArrayLikeUInt_co) -> _ArrayND[unsignedinteger[Any]]: ... # type: ignore[misc] @overload - def __ror__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayOrScalar[signedinteger[Any]]: ... + def __ror__(self: _ArrayInt_co, other: _ArrayLikeInt_co) -> _ArrayND[signedinteger[Any]]: ... @overload def __ror__(self: _ArrayND[object_], other: Any) -> Any: ... @overload diff --git a/numpy/core/einsumfunc.pyi b/numpy/core/einsumfunc.pyi index b33aff29f..2457e8719 100644 --- a/numpy/core/einsumfunc.pyi +++ b/numpy/core/einsumfunc.pyi @@ -13,7 +13,6 @@ from numpy import ( _OrderKACF, ) from numpy.typing import ( - _ArrayOrScalar, _ArrayLikeBool_co, _ArrayLikeUInt_co, _ArrayLikeInt_co, @@ -46,6 +45,11 @@ _CastingUnsafe = Literal["unsafe"] __all__: List[str] # TODO: Properly handle the `casting`-based combinatorics +# TODO: We need to evaluate the content `__subscripts` in order +# to identify whether or an array or scalar is returned. At a cursory +# glance this seems like something that can quite easilly be done with +# a mypy plugin. +# Something like `is_scalar = bool(__subscripts.partition("->")[-1])` @overload def einsum( __subscripts: str, @@ -55,7 +59,7 @@ def einsum( order: _OrderKACF = ..., casting: _CastingSafe = ..., optimize: _OptimizeKind = ..., -) -> _ArrayOrScalar[bool_]: ... +) -> Any: ... @overload def einsum( __subscripts: str, @@ -65,7 +69,7 @@ def einsum( order: _OrderKACF = ..., casting: _CastingSafe = ..., optimize: _OptimizeKind = ..., -) -> _ArrayOrScalar[unsignedinteger[Any]]: ... +) -> Any: ... @overload def einsum( __subscripts: str, @@ -75,7 +79,7 @@ def einsum( order: _OrderKACF = ..., casting: _CastingSafe = ..., optimize: _OptimizeKind = ..., -) -> _ArrayOrScalar[signedinteger[Any]]: ... +) -> Any: ... @overload def einsum( __subscripts: str, @@ -85,7 +89,7 @@ def einsum( order: _OrderKACF = ..., casting: _CastingSafe = ..., optimize: _OptimizeKind = ..., -) -> _ArrayOrScalar[floating[Any]]: ... +) -> Any: ... @overload def einsum( __subscripts: str, @@ -95,7 +99,7 @@ def einsum( order: _OrderKACF = ..., casting: _CastingSafe = ..., optimize: _OptimizeKind = ..., -) -> _ArrayOrScalar[complexfloating[Any, Any]]: ... +) -> Any: ... @overload def einsum( __subscripts: str, @@ -105,7 +109,7 @@ def einsum( out: None = ..., order: _OrderKACF = ..., optimize: _OptimizeKind = ..., -) -> _ArrayOrScalar[Any]: ... +) -> Any: ... @overload def einsum( __subscripts: str, diff --git a/numpy/core/fromnumeric.pyi b/numpy/core/fromnumeric.pyi index fc7f28a59..26a43c1a0 100644 --- a/numpy/core/fromnumeric.pyi +++ b/numpy/core/fromnumeric.pyi @@ -23,7 +23,6 @@ from numpy.typing import ( ArrayLike, _ShapeLike, _Shape, - _IntLike_co, _NumberLike_co, ) @@ -42,11 +41,7 @@ _ScalarBuiltin = Union[str, bytes, dt.date, dt.timedelta, bool, int, float, comp _Scalar = Union[_ScalarBuiltin, _ScalarNumpy] # Integers and booleans can generally be used interchangeably -_ScalarIntOrBool = TypeVar("_ScalarIntOrBool", bound=Union[integer, bool_]) _ScalarGeneric = TypeVar("_ScalarGeneric", bound=generic) -_ScalarGenericDT = TypeVar( - "_ScalarGenericDT", bound=Union[dt.datetime, dt.timedelta, generic] -) _Number = TypeVar("_Number", bound=number) @@ -55,67 +50,51 @@ _Number = TypeVar("_Number", bound=number) # 2. A scalar comes in; a generic comes out # 3. An array-like object comes in; some keyword ensures that a generic comes out # 4. An array-like object comes in; an ndarray or generic comes out -@overload -def take( - a: _ScalarGenericDT, - indices: int, - axis: Optional[int] = ..., - out: Optional[ndarray] = ..., - mode: _ModeKind = ..., -) -> _ScalarGenericDT: ... -@overload -def take( - a: _Scalar, - indices: int, - axis: Optional[int] = ..., - out: Optional[ndarray] = ..., - mode: _ModeKind = ..., -) -> _ScalarNumpy: ... -@overload -def take( - a: ArrayLike, - indices: int, - axis: Optional[int] = ..., - out: Optional[ndarray] = ..., - mode: _ModeKind = ..., -) -> _ScalarNumpy: ... -@overload def take( a: ArrayLike, indices: _ArrayLikeIntOrBool, axis: Optional[int] = ..., out: Optional[ndarray] = ..., mode: _ModeKind = ..., -) -> Union[_ScalarNumpy, ndarray]: ... -def reshape(a: ArrayLike, newshape: _ShapeLike, order: _OrderACF = ...) -> ndarray: ... -@overload -def choose( - a: _ScalarIntOrBool, - choices: ArrayLike, - out: Optional[ndarray] = ..., - mode: _ModeKind = ..., -) -> _ScalarIntOrBool: ... -@overload -def choose( - a: _IntLike_co, choices: ArrayLike, out: Optional[ndarray] = ..., mode: _ModeKind = ... -) -> Union[integer, bool_]: ... -@overload +) -> Any: ... + +def reshape( + a: ArrayLike, + newshape: _ShapeLike, + order: _OrderACF = ..., +) -> ndarray: ... + def choose( a: _ArrayLikeIntOrBool, choices: ArrayLike, out: Optional[ndarray] = ..., mode: _ModeKind = ..., -) -> ndarray: ... +) -> Any: ... + def repeat( - a: ArrayLike, repeats: _ArrayLikeIntOrBool, axis: Optional[int] = ... + a: ArrayLike, + repeats: _ArrayLikeIntOrBool, + axis: Optional[int] = ..., ) -> ndarray: ... + def put( - a: ndarray, ind: _ArrayLikeIntOrBool, v: ArrayLike, mode: _ModeKind = ... + a: ndarray, + ind: _ArrayLikeIntOrBool, + v: ArrayLike, + mode: _ModeKind = ..., ) -> None: ... -def swapaxes(a: ArrayLike, axis1: int, axis2: int) -> ndarray: ... + +def swapaxes( + a: ArrayLike, + axis1: int, + axis2: int, +) -> ndarray: ... + def transpose( - a: ArrayLike, axes: Union[None, Sequence[int], ndarray] = ... + a: ArrayLike, + axes: Union[None, Sequence[int], ndarray] = ... ) -> ndarray: ... + def partition( a: ArrayLike, kth: _ArrayLikeIntOrBool, @@ -123,54 +102,55 @@ def partition( kind: _PartitionKind = ..., order: Union[None, str, Sequence[str]] = ..., ) -> ndarray: ... -@overload -def argpartition( - a: generic, - kth: _ArrayLikeIntOrBool, - axis: Optional[int] = ..., - kind: _PartitionKind = ..., - order: Union[None, str, Sequence[str]] = ..., -) -> intp: ... -@overload -def argpartition( - a: _ScalarBuiltin, - kth: _ArrayLikeIntOrBool, - axis: Optional[int] = ..., - kind: _PartitionKind = ..., - order: Union[None, str, Sequence[str]] = ..., -) -> ndarray: ... -@overload + def argpartition( a: ArrayLike, kth: _ArrayLikeIntOrBool, axis: Optional[int] = ..., kind: _PartitionKind = ..., order: Union[None, str, Sequence[str]] = ..., -) -> ndarray: ... +) -> Any: ... + def sort( a: ArrayLike, axis: Optional[int] = ..., kind: Optional[_SortKind] = ..., order: Union[None, str, Sequence[str]] = ..., ) -> ndarray: ... + def argsort( a: ArrayLike, axis: Optional[int] = ..., kind: Optional[_SortKind] = ..., order: Union[None, str, Sequence[str]] = ..., ) -> ndarray: ... + @overload -def argmax(a: ArrayLike, axis: None = ..., out: Optional[ndarray] = ...) -> intp: ... +def argmax( + a: ArrayLike, + axis: None = ..., + out: Optional[ndarray] = ..., +) -> intp: ... @overload def argmax( - a: ArrayLike, axis: int = ..., out: Optional[ndarray] = ... -) -> Union[ndarray, intp]: ... + a: ArrayLike, + axis: Optional[int] = ..., + out: Optional[ndarray] = ..., +) -> Any: ... + @overload -def argmin(a: ArrayLike, axis: None = ..., out: Optional[ndarray] = ...) -> intp: ... +def argmin( + a: ArrayLike, + axis: None = ..., + out: Optional[ndarray] = ..., +) -> intp: ... @overload def argmin( - a: ArrayLike, axis: int = ..., out: Optional[ndarray] = ... -) -> Union[ndarray, intp]: ... + a: ArrayLike, + axis: Optional[int] = ..., + out: Optional[ndarray] = ..., +) -> Any: ... + @overload def searchsorted( a: ArrayLike, @@ -185,14 +165,30 @@ def searchsorted( side: _SortSide = ..., sorter: Optional[_ArrayLikeIntOrBool] = ..., # 1D int array ) -> ndarray: ... -def resize(a: ArrayLike, new_shape: _ShapeLike) -> ndarray: ... + +def resize( + a: ArrayLike, + new_shape: _ShapeLike, +) -> ndarray: ... + @overload -def squeeze(a: _ScalarGeneric, axis: Optional[_ShapeLike] = ...) -> _ScalarGeneric: ... +def squeeze( + a: _ScalarGeneric, + axis: Optional[_ShapeLike] = ..., +) -> _ScalarGeneric: ... @overload -def squeeze(a: ArrayLike, axis: Optional[_ShapeLike] = ...) -> ndarray: ... +def squeeze( + a: ArrayLike, + axis: Optional[_ShapeLike] = ..., +) -> ndarray: ... + def diagonal( - a: ArrayLike, offset: int = ..., axis1: int = ..., axis2: int = ... # >= 2D array + a: ArrayLike, + offset: int = ..., + axis1: int = ..., + axis2: int = ..., # >= 2D array ) -> ndarray: ... + def trace( a: ArrayLike, # >= 2D array offset: int = ..., @@ -200,32 +196,21 @@ def trace( axis2: int = ..., dtype: DTypeLike = ..., out: Optional[ndarray] = ..., -) -> Union[number, ndarray]: ... +) -> Any: ... + def ravel(a: ArrayLike, order: _OrderKACF = ...) -> ndarray: ... + def nonzero(a: ArrayLike) -> Tuple[ndarray, ...]: ... + def shape(a: ArrayLike) -> _Shape: ... + def compress( condition: ArrayLike, # 1D bool array a: ArrayLike, axis: Optional[int] = ..., out: Optional[ndarray] = ..., ) -> ndarray: ... -@overload -def clip( - a: _Number, - a_min: ArrayLike, - a_max: Optional[ArrayLike], - out: Optional[ndarray] = ..., - **kwargs: Any, -) -> _Number: ... -@overload -def clip( - a: _Number, - a_min: None, - a_max: ArrayLike, - out: Optional[ndarray] = ..., - **kwargs: Any, -) -> _Number: ... + @overload def clip( a: ArrayLike, @@ -233,7 +218,7 @@ def clip( a_max: Optional[ArrayLike], out: Optional[ndarray] = ..., **kwargs: Any, -) -> Union[number, ndarray]: ... +) -> Any: ... @overload def clip( a: ArrayLike, @@ -241,18 +226,8 @@ def clip( a_max: ArrayLike, out: Optional[ndarray] = ..., **kwargs: Any, -) -> Union[number, ndarray]: ... -@overload -def sum( - a: _Number, - axis: Optional[_ShapeLike] = ..., - dtype: DTypeLike = ..., - out: Optional[ndarray] = ..., - keepdims: bool = ..., - initial: _NumberLike_co = ..., - where: _ArrayLikeBool = ..., -) -> _Number: ... -@overload +) -> Any: ... + def sum( a: ArrayLike, axis: _ShapeLike = ..., @@ -261,12 +236,13 @@ def sum( keepdims: bool = ..., initial: _NumberLike_co = ..., where: _ArrayLikeBool = ..., -) -> Union[number, ndarray]: ... +) -> Any: ... + @overload def all( a: ArrayLike, axis: None = ..., - out: Optional[ndarray] = ..., + out: None = ..., keepdims: Literal[False] = ..., ) -> bool_: ... @overload @@ -275,12 +251,13 @@ def all( axis: Optional[_ShapeLike] = ..., out: Optional[ndarray] = ..., keepdims: bool = ..., -) -> Union[bool_, ndarray]: ... +) -> Any: ... + @overload def any( a: ArrayLike, axis: None = ..., - out: Optional[ndarray] = ..., + out: None = ..., keepdims: Literal[False] = ..., ) -> bool_: ... @overload @@ -289,53 +266,22 @@ def any( axis: Optional[_ShapeLike] = ..., out: Optional[ndarray] = ..., keepdims: bool = ..., -) -> Union[bool_, ndarray]: ... +) -> Any: ... + def cumsum( a: ArrayLike, axis: Optional[int] = ..., dtype: DTypeLike = ..., out: Optional[ndarray] = ..., ) -> ndarray: ... -@overload -def ptp( - a: _Number, - axis: Optional[_ShapeLike] = ..., - out: Optional[ndarray] = ..., - keepdims: bool = ..., -) -> _Number: ... -@overload -def ptp( - a: ArrayLike, - axis: None = ..., - out: Optional[ndarray] = ..., - keepdims: Literal[False] = ..., -) -> number: ... -@overload + def ptp( a: ArrayLike, axis: Optional[_ShapeLike] = ..., out: Optional[ndarray] = ..., keepdims: bool = ..., -) -> Union[number, ndarray]: ... -@overload -def amax( - a: _Number, - axis: Optional[_ShapeLike] = ..., - out: Optional[ndarray] = ..., - keepdims: bool = ..., - initial: _NumberLike_co = ..., - where: _ArrayLikeBool = ..., -) -> _Number: ... -@overload -def amax( - a: ArrayLike, - axis: None = ..., - out: Optional[ndarray] = ..., - keepdims: Literal[False] = ..., - initial: _NumberLike_co = ..., - where: _ArrayLikeBool = ..., -) -> number: ... -@overload +) -> Any: ... + def amax( a: ArrayLike, axis: Optional[_ShapeLike] = ..., @@ -343,26 +289,8 @@ def amax( keepdims: bool = ..., initial: _NumberLike_co = ..., where: _ArrayLikeBool = ..., -) -> Union[number, ndarray]: ... -@overload -def amin( - a: _Number, - axis: Optional[_ShapeLike] = ..., - out: Optional[ndarray] = ..., - keepdims: bool = ..., - initial: _NumberLike_co = ..., - where: _ArrayLikeBool = ..., -) -> _Number: ... -@overload -def amin( - a: ArrayLike, - axis: None = ..., - out: Optional[ndarray] = ..., - keepdims: Literal[False] = ..., - initial: _NumberLike_co = ..., - where: _ArrayLikeBool = ..., -) -> number: ... -@overload +) -> Any: ... + def amin( a: ArrayLike, axis: Optional[_ShapeLike] = ..., @@ -370,7 +298,7 @@ def amin( keepdims: bool = ..., initial: _NumberLike_co = ..., where: _ArrayLikeBool = ..., -) -> Union[number, ndarray]: ... +) -> Any: ... # TODO: `np.prod()``: For object arrays `initial` does not necessarily # have to be a numerical scalar. @@ -379,27 +307,6 @@ def amin( # Note that the same situation holds for all wrappers around # `np.ufunc.reduce`, e.g. `np.sum()` (`.__add__()`). -@overload -def prod( - a: _Number, - axis: Optional[_ShapeLike] = ..., - dtype: DTypeLike = ..., - out: None = ..., - keepdims: bool = ..., - initial: _NumberLike_co = ..., - where: _ArrayLikeBool = ..., -) -> _Number: ... -@overload -def prod( - a: ArrayLike, - axis: None = ..., - dtype: DTypeLike = ..., - out: None = ..., - keepdims: Literal[False] = ..., - initial: _NumberLike_co = ..., - where: _ArrayLikeBool = ..., -) -> number: ... -@overload def prod( a: ArrayLike, axis: Optional[_ShapeLike] = ..., @@ -408,53 +315,33 @@ def prod( keepdims: bool = ..., initial: _NumberLike_co = ..., where: _ArrayLikeBool = ..., -) -> Union[number, ndarray]: ... +) -> Any: ... + def cumprod( a: ArrayLike, axis: Optional[int] = ..., dtype: DTypeLike = ..., out: Optional[ndarray] = ..., ) -> ndarray: ... + def ndim(a: ArrayLike) -> int: ... + def size(a: ArrayLike, axis: Optional[int] = ...) -> int: ... -@overload -def around( - a: _Number, decimals: int = ..., out: Optional[ndarray] = ... -) -> _Number: ... -@overload -def around( - a: _NumberLike_co, decimals: int = ..., out: Optional[ndarray] = ... -) -> number: ... -@overload + def around( - a: ArrayLike, decimals: int = ..., out: Optional[ndarray] = ... -) -> ndarray: ... -@overload -def mean( a: ArrayLike, - axis: None = ..., - dtype: DTypeLike = ..., - out: None = ..., - keepdims: Literal[False] = ..., -) -> number: ... -@overload + decimals: int = ..., + out: Optional[ndarray] = ..., +) -> Any: ... + def mean( a: ArrayLike, axis: Optional[_ShapeLike] = ..., dtype: DTypeLike = ..., out: Optional[ndarray] = ..., keepdims: bool = ..., -) -> Union[number, ndarray]: ... -@overload -def std( - a: ArrayLike, - axis: None = ..., - dtype: DTypeLike = ..., - out: None = ..., - ddof: int = ..., - keepdims: Literal[False] = ..., -) -> number: ... -@overload +) -> Any: ... + def std( a: ArrayLike, axis: Optional[_ShapeLike] = ..., @@ -462,17 +349,8 @@ def std( out: Optional[ndarray] = ..., ddof: int = ..., keepdims: bool = ..., -) -> Union[number, ndarray]: ... -@overload -def var( - a: ArrayLike, - axis: None = ..., - dtype: DTypeLike = ..., - out: None = ..., - ddof: int = ..., - keepdims: Literal[False] = ..., -) -> number: ... -@overload +) -> Any: ... + def var( a: ArrayLike, axis: Optional[_ShapeLike] = ..., @@ -480,4 +358,4 @@ def var( out: Optional[ndarray] = ..., ddof: int = ..., keepdims: bool = ..., -) -> Union[number, ndarray]: ... +) -> Any: ... diff --git a/numpy/core/function_base.pyi b/numpy/core/function_base.pyi index d4543f281..b5d6ca6ab 100644 --- a/numpy/core/function_base.pyi +++ b/numpy/core/function_base.pyi @@ -1,7 +1,7 @@ import sys from typing import overload, Tuple, Union, Sequence, Any -from numpy import ndarray, inexact +from numpy import ndarray from numpy.typing import ArrayLike, DTypeLike, _SupportsArray, _NumberLike_co if sys.version_info >= (3, 8): @@ -33,7 +33,8 @@ def linspace( retstep: Literal[True] = ..., dtype: DTypeLike = ..., axis: SupportsIndex = ..., -) -> Tuple[ndarray, inexact]: ... +) -> Tuple[ndarray, Any]: ... + def logspace( start: _ArrayLikeNumber, stop: _ArrayLikeNumber, @@ -43,6 +44,7 @@ def logspace( dtype: DTypeLike = ..., axis: SupportsIndex = ..., ) -> ndarray: ... + def geomspace( start: _ArrayLikeNumber, stop: _ArrayLikeNumber, diff --git a/numpy/core/numeric.pyi b/numpy/core/numeric.pyi index d91cb31c2..6b9ef4b20 100644 --- a/numpy/core/numeric.pyi +++ b/numpy/core/numeric.pyi @@ -41,6 +41,7 @@ def zeros_like( subok: bool = ..., shape: Optional[_ShapeLike] = ..., ) -> ndarray: ... + def ones( shape: _ShapeLike, dtype: DTypeLike = ..., @@ -48,6 +49,7 @@ def ones( *, like: ArrayLike = ..., ) -> ndarray: ... + @overload def ones_like( a: _ArrayType, @@ -64,6 +66,7 @@ def ones_like( subok: bool = ..., shape: Optional[_ShapeLike] = ..., ) -> ndarray: ... + @overload def empty_like( a: _ArrayType, @@ -80,6 +83,7 @@ def empty_like( subok: bool = ..., shape: Optional[_ShapeLike] = ..., ) -> ndarray: ... + def full( shape: _ShapeLike, fill_value: Any, @@ -88,6 +92,7 @@ def full( *, like: ArrayLike = ..., ) -> ndarray: ... + @overload def full_like( a: _ArrayType, @@ -106,39 +111,73 @@ def full_like( subok: bool = ..., shape: Optional[_ShapeLike] = ..., ) -> ndarray: ... + @overload def count_nonzero( - a: ArrayLike, axis: None = ..., *, keepdims: Literal[False] = ... + 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 + 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: ... + +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: ... +def outer( + a: ArrayLike, + b: ArrayLike, + out: None = ..., +) -> ndarray: ... @overload -def outer(a: ArrayLike, b: ArrayLike, out: _ArrayType = ...) -> _ArrayType: ... +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, @@ -147,6 +186,7 @@ def cross( axisc: int = ..., axis: Optional[int] = ..., ) -> ndarray: ... + @overload def indices( dimensions: Sequence[int], @@ -159,6 +199,7 @@ def indices( dtype: DTypeLike = ..., sparse: Literal[True] = ..., ) -> Tuple[ndarray, ...]: ... + def fromfunction( function: Callable[..., _T], shape: Sequence[int], @@ -167,10 +208,20 @@ def fromfunction( 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 identity( + n: int, + dtype: DTypeLike = ..., + *, + like: ArrayLike = ..., +) -> ndarray: ... + def allclose( a: ArrayLike, b: ArrayLike, @@ -178,12 +229,15 @@ def allclose( atol: float = ..., equal_nan: bool = ..., ) -> bool: ... + def isclose( a: ArrayLike, b: ArrayLike, rtol: float = ..., atol: float = ..., equal_nan: bool = ..., -) -> Union[bool_, ndarray]: ... +) -> Any: ... + def array_equal(a1: ArrayLike, a2: ArrayLike) -> bool: ... + def array_equiv(a1: ArrayLike, a2: ArrayLike) -> bool: ... diff --git a/numpy/lib/index_tricks.pyi b/numpy/lib/index_tricks.pyi index 3e5bc1adb..e486fe8f2 100644 --- a/numpy/lib/index_tricks.pyi +++ b/numpy/lib/index_tricks.pyi @@ -17,6 +17,7 @@ from numpy import ( ndindex as ndindex, ndarray, dtype, + integer, str_, bytes_, bool_, @@ -33,7 +34,6 @@ from numpy.typing import ( _NestedSequence, _RecursiveSequence, _ArrayND, - _ArrayOrScalar, _ArrayLikeInt, # DTypes @@ -57,18 +57,33 @@ _ArrayType = TypeVar("_ArrayType", bound=ndarray[Any, Any]) __all__: List[str] +@overload +def unravel_index( # type: ignore[misc] + indices: Union[int, integer[Any]], + shape: _ShapeLike, + order: _OrderCF = ... +) -> Tuple[intp, ...]: ... +@overload def unravel_index( indices: _ArrayLikeInt, shape: _ShapeLike, order: _OrderCF = ... -) -> Tuple[_ArrayOrScalar[intp], ...]: ... +) -> Tuple[_ArrayND[intp], ...]: ... +@overload +def ravel_multi_index( # type: ignore[misc] + multi_index: Sequence[Union[int, integer[Any]]], + dims: _ShapeLike, + mode: Union[_ModeKind, Tuple[_ModeKind, ...]] = ..., + order: _OrderCF = ... +) -> intp: ... +@overload def ravel_multi_index( - multi_index: ArrayLike, + multi_index: Sequence[_ArrayLikeInt], dims: _ShapeLike, mode: Union[_ModeKind, Tuple[_ModeKind, ...]] = ..., order: _OrderCF = ... -) -> _ArrayOrScalar[intp]: ... +) -> _ArrayND[intp]: ... @overload def ix_(*args: _NestedSequence[_SupportsDType[_DType]]) -> Tuple[ndarray[Any, _DType], ...]: ... diff --git a/numpy/lib/ufunclike.pyi b/numpy/lib/ufunclike.pyi index 3443fa7ae..e97383af8 100644 --- a/numpy/lib/ufunclike.pyi +++ b/numpy/lib/ufunclike.pyi @@ -1,10 +1,11 @@ from typing import Any, overload, TypeVar, List, Union -from numpy import floating, bool_, ndarray +from numpy import floating, bool_, object_, ndarray from numpy.typing import ( + _ArrayND, + _FloatLike_co, _ArrayLikeFloat_co, _ArrayLikeObject_co, - _ArrayOrScalar, ) _ArrayType = TypeVar("_ArrayType", bound=ndarray[Any, Any]) @@ -12,15 +13,20 @@ _ArrayType = TypeVar("_ArrayType", bound=ndarray[Any, Any]) __all__: List[str] @overload +def fix( # type: ignore[misc] + x: _FloatLike_co, + out: None = ..., +) -> floating[Any]: ... +@overload def fix( x: _ArrayLikeFloat_co, out: None = ..., -) -> _ArrayOrScalar[floating[Any]]: ... +) -> _ArrayND[floating[Any]]: ... @overload def fix( x: _ArrayLikeObject_co, out: None = ..., -) -> Any: ... +) -> _ArrayND[object_]: ... @overload def fix( x: Union[_ArrayLikeFloat_co, _ArrayLikeObject_co], @@ -28,10 +34,15 @@ def fix( ) -> _ArrayType: ... @overload +def isposinf( # type: ignore[misc] + x: _FloatLike_co, + out: None = ..., +) -> bool_: ... +@overload def isposinf( x: _ArrayLikeFloat_co, out: None = ..., -) -> _ArrayOrScalar[bool_]: ... +) -> _ArrayND[bool_]: ... @overload def isposinf( x: _ArrayLikeFloat_co, @@ -39,10 +50,15 @@ def isposinf( ) -> _ArrayType: ... @overload +def isneginf( # type: ignore[misc] + x: _FloatLike_co, + out: None = ..., +) -> bool_: ... +@overload def isneginf( x: _ArrayLikeFloat_co, out: None = ..., -) -> _ArrayOrScalar[bool_]: ... +) -> _ArrayND[bool_]: ... @overload def isneginf( x: _ArrayLikeFloat_co, diff --git a/numpy/typing/__init__.py b/numpy/typing/__init__.py index d71ec0719..a2d4c60fb 100644 --- a/numpy/typing/__init__.py +++ b/numpy/typing/__init__.py @@ -140,6 +140,20 @@ Timedelta64 The `~numpy.timedelta64` class is not considered a subclass of `~numpy.signedinteger`, the former only inheriting from `~numpy.generic` while static type checking. +0D arrays +~~~~~~~~~ + +During runtime numpy aggressively casts any passed 0D arrays into their +corresponding `~numpy.generic` instance. Until the introduction of shape +typing (see :pep:`646`) it is unfortunately not possible to make the +necessary distinction between 0D and >0D arrays. While thus not strictly +correct, all operations are that can potentially perform a 0D-array -> scalar +cast are currently annotated as exclusively returning an `ndarray`. + +If it is known in advance that an operation _will_ perform a +0D-array -> scalar cast, then one can consider manually remedying the +situation with either `typing.cast` or a ``# type: ignore`` comment. + API --- @@ -326,7 +340,6 @@ from ._array_like import ( _RecursiveSequence, _SupportsArray, _ArrayND, - _ArrayOrScalar, _ArrayLikeInt, _ArrayLikeBool_co, _ArrayLikeUInt_co, diff --git a/numpy/typing/_array_like.py b/numpy/typing/_array_like.py index eb8d3f4e1..582d3db9a 100644 --- a/numpy/typing/_array_like.py +++ b/numpy/typing/_array_like.py @@ -132,7 +132,5 @@ _ArrayLikeInt = _ArrayLike[ if TYPE_CHECKING: _ArrayND = ndarray[Any, dtype[_ScalarType]] - _ArrayOrScalar = Union[_ScalarType, _ArrayND[_ScalarType]] else: _ArrayND = Any - _ArrayOrScalar = Any diff --git a/numpy/typing/_callable.py b/numpy/typing/_callable.py index 23cabd47a..30c210b62 100644 --- a/numpy/typing/_callable.py +++ b/numpy/typing/_callable.py @@ -47,7 +47,7 @@ from ._scalars import ( _NumberLike_co, ) from . import NBitBase -from ._array_like import ArrayLike, _ArrayOrScalar +from ._array_like import ArrayLike, _ArrayND if sys.version_info >= (3, 8): from typing import Protocol @@ -168,7 +168,7 @@ if TYPE_CHECKING or HAVE_PROTOCOL: @overload def __call__( self, __other: Union[int, signedinteger[Any]] - ) -> Union[signedinteger[Any], float64]: ... + ) -> Any: ... @overload def __call__(self, __other: float) -> floating[Union[_NBit1, _NBitDouble]]: ... @overload @@ -198,7 +198,7 @@ if TYPE_CHECKING or HAVE_PROTOCOL: @overload def __call__( self, __other: Union[int, signedinteger[Any]] - ) -> Union[signedinteger[Any], float64]: ... + ) -> Any: ... @overload def __call__(self, __other: float) -> floating[Union[_NBit1, _NBitDouble]]: ... @overload @@ -212,7 +212,7 @@ if TYPE_CHECKING or HAVE_PROTOCOL: @overload def __call__( self, __other: Union[int, signedinteger[Any]] - ) -> Union[_2Tuple[signedinteger[Any]], _2Tuple[float64]]: ... + ) -> _2Tuple[Any]: ... @overload def __call__(self, __other: float) -> _2Tuple[floating[Union[_NBit1, _NBitDouble]]]: ... @overload @@ -336,7 +336,7 @@ if TYPE_CHECKING or HAVE_PROTOCOL: @overload def __call__(self, __other: _T1) -> bool_: ... @overload - def __call__(self, __other: _T2) -> _ArrayOrScalar[bool_]: ... + def __call__(self, __other: _T2) -> _ArrayND[bool_]: ... else: _BoolOp = Any diff --git a/numpy/typing/tests/data/fail/fromnumeric.py b/numpy/typing/tests/data/fail/fromnumeric.py index c9156895d..d8f7a5d69 100644 --- a/numpy/typing/tests/data/fail/fromnumeric.py +++ b/numpy/typing/tests/data/fail/fromnumeric.py @@ -7,17 +7,17 @@ A.setflags(write=False) a = np.bool_(True) -np.take(a, None) # E: No overload variant of "take" matches argument type -np.take(a, axis=1.0) # E: No overload variant of "take" matches argument type -np.take(A, out=1) # E: No overload variant of "take" matches argument type -np.take(A, mode="bob") # E: No overload variant of "take" matches argument type +np.take(a, None) # E: incompatible type +np.take(a, axis=1.0) # E: incompatible type +np.take(A, out=1) # E: incompatible type +np.take(A, mode="bob") # E: incompatible type np.reshape(a, None) # E: Argument 2 to "reshape" has incompatible type np.reshape(A, 1, order="bob") # E: Argument "order" to "reshape" has incompatible type -np.choose(a, None) # E: No overload variant of "choose" matches argument type -np.choose(a, out=1.0) # E: No overload variant of "choose" matches argument type -np.choose(A, mode="bob") # E: No overload variant of "choose" matches argument type +np.choose(a, None) # E: incompatible type +np.choose(a, out=1.0) # E: incompatible type +np.choose(A, mode="bob") # E: incompatible type np.repeat(a, None) # E: Argument 2 to "repeat" has incompatible type np.repeat(A, 1, axis=1.0) # E: Argument "axis" to "repeat" has incompatible type @@ -38,14 +38,14 @@ np.partition( A, 0, order=range(5) # E: Argument "order" to "partition" has incompatible type ) -np.argpartition( # E: No overload variant of "argpartition" matches argument type - a, None +np.argpartition( + a, None # E: incompatible type ) -np.argpartition( # E: No overload variant of "argpartition" matches argument type - a, 0, axis="bob" +np.argpartition( + a, 0, axis="bob" # E: incompatible type ) -np.argpartition( # E: No overload variant of "argpartition" matches argument type - A, 0, kind="bob" +np.argpartition( + A, 0, kind="bob" # E: incompatible type ) np.argpartition( A, 0, order=range(5) # E: Argument "order" to "argpartition" has incompatible type @@ -93,62 +93,62 @@ np.compress( np.clip(a, 1, 2, out=1) # E: No overload variant of "clip" matches argument type np.clip(1, None, None) # E: No overload variant of "clip" matches argument type -np.sum(a, axis=1.0) # E: No overload variant of "sum" matches argument type -np.sum(a, keepdims=1.0) # E: No overload variant of "sum" matches argument type -np.sum(a, initial=[1]) # E: No overload variant of "sum" matches argument type +np.sum(a, axis=1.0) # E: incompatible type +np.sum(a, keepdims=1.0) # E: incompatible type +np.sum(a, initial=[1]) # E: incompatible type -np.all(a, axis=1.0) # E: No overload variant of "all" matches argument type -np.all(a, keepdims=1.0) # E: No overload variant of "all" matches argument type -np.all(a, out=1.0) # E: No overload variant of "all" matches argument type +np.all(a, axis=1.0) # E: No overload variant +np.all(a, keepdims=1.0) # E: No overload variant +np.all(a, out=1.0) # E: No overload variant -np.any(a, axis=1.0) # E: No overload variant of "any" matches argument type -np.any(a, keepdims=1.0) # E: No overload variant of "any" matches argument type -np.any(a, out=1.0) # E: No overload variant of "any" matches argument type +np.any(a, axis=1.0) # E: No overload variant +np.any(a, keepdims=1.0) # E: No overload variant +np.any(a, out=1.0) # E: No overload variant -np.cumsum(a, axis=1.0) # E: Argument "axis" to "cumsum" has incompatible type -np.cumsum(a, dtype=1.0) # E: Argument "dtype" to "cumsum" has incompatible type -np.cumsum(a, out=1.0) # E: Argument "out" to "cumsum" has incompatible type +np.cumsum(a, axis=1.0) # E: incompatible type +np.cumsum(a, dtype=1.0) # E: incompatible type +np.cumsum(a, out=1.0) # E: incompatible type -np.ptp(a, axis=1.0) # E: No overload variant of "ptp" matches argument type -np.ptp(a, keepdims=1.0) # E: No overload variant of "ptp" matches argument type -np.ptp(a, out=1.0) # E: No overload variant of "ptp" matches argument type +np.ptp(a, axis=1.0) # E: incompatible type +np.ptp(a, keepdims=1.0) # E: incompatible type +np.ptp(a, out=1.0) # E: incompatible type -np.amax(a, axis=1.0) # E: No overload variant of "amax" matches argument type -np.amax(a, keepdims=1.0) # E: No overload variant of "amax" matches argument type -np.amax(a, out=1.0) # E: No overload variant of "amax" matches argument type -np.amax(a, initial=[1.0]) # E: No overload variant of "amax" matches argument type +np.amax(a, axis=1.0) # E: incompatible type +np.amax(a, keepdims=1.0) # E: incompatible type +np.amax(a, out=1.0) # E: incompatible type +np.amax(a, initial=[1.0]) # E: incompatible type np.amax(a, where=[1.0]) # E: List item 0 has incompatible type -np.amin(a, axis=1.0) # E: No overload variant of "amin" matches argument type -np.amin(a, keepdims=1.0) # E: No overload variant of "amin" matches argument type -np.amin(a, out=1.0) # E: No overload variant of "amin" matches argument type -np.amin(a, initial=[1.0]) # E: No overload variant of "amin" matches argument type +np.amin(a, axis=1.0) # E: incompatible type +np.amin(a, keepdims=1.0) # E: incompatible type +np.amin(a, out=1.0) # E: incompatible type +np.amin(a, initial=[1.0]) # E: incompatible type np.amin(a, where=[1.0]) # E: List item 0 has incompatible type -np.prod(a, axis=1.0) # E: No overload variant of "prod" matches argument type -np.prod(a, out=False) # E: No overload variant of "prod" matches argument type -np.prod(a, keepdims=1.0) # E: No overload variant of "prod" matches argument type -np.prod(a, initial=int) # E: No overload variant of "prod" matches argument type -np.prod(a, where=1.0) # E: No overload variant of "prod" matches argument type +np.prod(a, axis=1.0) # E: incompatible type +np.prod(a, out=False) # E: incompatible type +np.prod(a, keepdims=1.0) # E: incompatible type +np.prod(a, initial=int) # E: incompatible type +np.prod(a, where=1.0) # E: incompatible type np.cumprod(a, axis=1.0) # E: Argument "axis" to "cumprod" has incompatible type np.cumprod(a, out=False) # E: Argument "out" to "cumprod" has incompatible type np.size(a, axis=1.0) # E: Argument "axis" to "size" has incompatible type -np.around(a, decimals=1.0) # E: No overload variant of "around" matches argument type -np.around(a, out=type) # E: No overload variant of "around" matches argument type +np.around(a, decimals=1.0) # E: incompatible type +np.around(a, out=type) # E: incompatible type -np.mean(a, axis=1.0) # E: No overload variant of "mean" matches argument type -np.mean(a, out=False) # E: No overload variant of "mean" matches argument type -np.mean(a, keepdims=1.0) # E: No overload variant of "mean" matches argument type +np.mean(a, axis=1.0) # E: incompatible type +np.mean(a, out=False) # E: incompatible type +np.mean(a, keepdims=1.0) # E: incompatible type -np.std(a, axis=1.0) # E: No overload variant of "std" matches argument type -np.std(a, out=False) # E: No overload variant of "std" matches argument type -np.std(a, ddof='test') # E: No overload variant of "std" matches argument type -np.std(a, keepdims=1.0) # E: No overload variant of "std" matches argument type +np.std(a, axis=1.0) # E: incompatible type +np.std(a, out=False) # E: incompatible type +np.std(a, ddof='test') # E: incompatible type +np.std(a, keepdims=1.0) # E: incompatible type -np.var(a, axis=1.0) # E: No overload variant of "var" matches argument type -np.var(a, out=False) # E: No overload variant of "var" matches argument type -np.var(a, ddof='test') # E: No overload variant of "var" matches argument type -np.var(a, keepdims=1.0) # E: No overload variant of "var" matches argument type +np.var(a, axis=1.0) # E: incompatible type +np.var(a, out=False) # E: incompatible type +np.var(a, ddof='test') # E: incompatible type +np.var(a, keepdims=1.0) # E: incompatible type diff --git a/numpy/typing/tests/data/fail/index_tricks.py b/numpy/typing/tests/data/fail/index_tricks.py index cbc43fd54..c508bf3ae 100644 --- a/numpy/typing/tests/data/fail/index_tricks.py +++ b/numpy/typing/tests/data/fail/index_tricks.py @@ -5,7 +5,7 @@ AR_LIKE_i: List[int] AR_LIKE_f: List[float] np.unravel_index(AR_LIKE_f, (1, 2, 3)) # E: incompatible type -np.ravel_multi_index(AR_LIKE_i, (1, 2, 3), mode="bob") # E: incompatible type +np.ravel_multi_index(AR_LIKE_i, (1, 2, 3), mode="bob") # E: No overload variant np.mgrid[1] # E: Invalid index type np.mgrid[...] # E: Invalid index type np.ogrid[1] # E: Invalid index type diff --git a/numpy/typing/tests/data/reveal/arithmetic.py b/numpy/typing/tests/data/reveal/arithmetic.py index 53a3a846d..f5d185206 100644 --- a/numpy/typing/tests/data/reveal/arithmetic.py +++ b/numpy/typing/tests/data/reveal/arithmetic.py @@ -45,104 +45,104 @@ AR_LIKE_O: List[np.object_] # Array subtraction -reveal_type(AR_b - AR_LIKE_u) # E: Union[numpy.unsignedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]]] -reveal_type(AR_b - AR_LIKE_i) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] -reveal_type(AR_b - AR_LIKE_f) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_b - AR_LIKE_c) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_b - AR_LIKE_m) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] +reveal_type(AR_b - AR_LIKE_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]] +reveal_type(AR_b - AR_LIKE_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(AR_b - AR_LIKE_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_b - AR_LIKE_c) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_b - AR_LIKE_m) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] reveal_type(AR_b - AR_LIKE_O) # E: Any -reveal_type(AR_LIKE_u - AR_b) # E: Union[numpy.unsignedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]]] -reveal_type(AR_LIKE_i - AR_b) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] -reveal_type(AR_LIKE_f - AR_b) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_LIKE_c - AR_b) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_LIKE_m - AR_b) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] -reveal_type(AR_LIKE_M - AR_b) # E: Union[numpy.datetime64, numpy.ndarray[Any, numpy.dtype[numpy.datetime64]]] +reveal_type(AR_LIKE_u - AR_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]] +reveal_type(AR_LIKE_i - AR_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(AR_LIKE_f - AR_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_LIKE_c - AR_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_LIKE_m - AR_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] +reveal_type(AR_LIKE_M - AR_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.datetime64]] reveal_type(AR_LIKE_O - AR_b) # E: Any -reveal_type(AR_u - AR_LIKE_b) # E: Union[numpy.unsignedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]]] -reveal_type(AR_u - AR_LIKE_u) # E: Union[numpy.unsignedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]]] -reveal_type(AR_u - AR_LIKE_i) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] -reveal_type(AR_u - AR_LIKE_f) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_u - AR_LIKE_c) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_u - AR_LIKE_m) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] +reveal_type(AR_u - AR_LIKE_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]] +reveal_type(AR_u - AR_LIKE_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]] +reveal_type(AR_u - AR_LIKE_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(AR_u - AR_LIKE_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_u - AR_LIKE_c) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_u - AR_LIKE_m) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] reveal_type(AR_u - AR_LIKE_O) # E: Any -reveal_type(AR_LIKE_b - AR_u) # E: Union[numpy.unsignedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]]] -reveal_type(AR_LIKE_u - AR_u) # E: Union[numpy.unsignedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]]] -reveal_type(AR_LIKE_i - AR_u) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] -reveal_type(AR_LIKE_f - AR_u) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_LIKE_c - AR_u) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_LIKE_m - AR_u) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] -reveal_type(AR_LIKE_M - AR_u) # E: Union[numpy.datetime64, numpy.ndarray[Any, numpy.dtype[numpy.datetime64]]] +reveal_type(AR_LIKE_b - AR_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]] +reveal_type(AR_LIKE_u - AR_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]] +reveal_type(AR_LIKE_i - AR_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(AR_LIKE_f - AR_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_LIKE_c - AR_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_LIKE_m - AR_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] +reveal_type(AR_LIKE_M - AR_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.datetime64]] reveal_type(AR_LIKE_O - AR_u) # E: Any -reveal_type(AR_i - AR_LIKE_b) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] -reveal_type(AR_i - AR_LIKE_u) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] -reveal_type(AR_i - AR_LIKE_i) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] -reveal_type(AR_i - AR_LIKE_f) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_i - AR_LIKE_c) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_i - AR_LIKE_m) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] +reveal_type(AR_i - AR_LIKE_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(AR_i - AR_LIKE_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(AR_i - AR_LIKE_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(AR_i - AR_LIKE_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_i - AR_LIKE_c) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_i - AR_LIKE_m) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] reveal_type(AR_i - AR_LIKE_O) # E: Any -reveal_type(AR_LIKE_b - AR_i) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] -reveal_type(AR_LIKE_u - AR_i) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] -reveal_type(AR_LIKE_i - AR_i) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] -reveal_type(AR_LIKE_f - AR_i) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_LIKE_c - AR_i) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_LIKE_m - AR_i) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] -reveal_type(AR_LIKE_M - AR_i) # E: Union[numpy.datetime64, numpy.ndarray[Any, numpy.dtype[numpy.datetime64]]] +reveal_type(AR_LIKE_b - AR_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(AR_LIKE_u - AR_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(AR_LIKE_i - AR_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(AR_LIKE_f - AR_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_LIKE_c - AR_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_LIKE_m - AR_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] +reveal_type(AR_LIKE_M - AR_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.datetime64]] reveal_type(AR_LIKE_O - AR_i) # E: Any -reveal_type(AR_f - AR_LIKE_b) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_f - AR_LIKE_u) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_f - AR_LIKE_i) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_f - AR_LIKE_f) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_f - AR_LIKE_c) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] +reveal_type(AR_f - AR_LIKE_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_f - AR_LIKE_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_f - AR_LIKE_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_f - AR_LIKE_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_f - AR_LIKE_c) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] reveal_type(AR_f - AR_LIKE_O) # E: Any -reveal_type(AR_LIKE_b - AR_f) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_LIKE_u - AR_f) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_LIKE_i - AR_f) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_LIKE_f - AR_f) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_LIKE_c - AR_f) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] +reveal_type(AR_LIKE_b - AR_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_LIKE_u - AR_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_LIKE_i - AR_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_LIKE_f - AR_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_LIKE_c - AR_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] reveal_type(AR_LIKE_O - AR_f) # E: Any -reveal_type(AR_c - AR_LIKE_b) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_c - AR_LIKE_u) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_c - AR_LIKE_i) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_c - AR_LIKE_f) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_c - AR_LIKE_c) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] +reveal_type(AR_c - AR_LIKE_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_c - AR_LIKE_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_c - AR_LIKE_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_c - AR_LIKE_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_c - AR_LIKE_c) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] reveal_type(AR_c - AR_LIKE_O) # E: Any -reveal_type(AR_LIKE_b - AR_c) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_LIKE_u - AR_c) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_LIKE_i - AR_c) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_LIKE_f - AR_c) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_LIKE_c - AR_c) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] +reveal_type(AR_LIKE_b - AR_c) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_LIKE_u - AR_c) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_LIKE_i - AR_c) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_LIKE_f - AR_c) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_LIKE_c - AR_c) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] reveal_type(AR_LIKE_O - AR_c) # E: Any -reveal_type(AR_m - AR_LIKE_b) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] -reveal_type(AR_m - AR_LIKE_u) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] -reveal_type(AR_m - AR_LIKE_i) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] -reveal_type(AR_m - AR_LIKE_m) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] +reveal_type(AR_m - AR_LIKE_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] +reveal_type(AR_m - AR_LIKE_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] +reveal_type(AR_m - AR_LIKE_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] +reveal_type(AR_m - AR_LIKE_m) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] reveal_type(AR_m - AR_LIKE_O) # E: Any -reveal_type(AR_LIKE_b - AR_m) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] -reveal_type(AR_LIKE_u - AR_m) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] -reveal_type(AR_LIKE_i - AR_m) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] -reveal_type(AR_LIKE_m - AR_m) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] -reveal_type(AR_LIKE_M - AR_m) # E: Union[numpy.datetime64, numpy.ndarray[Any, numpy.dtype[numpy.datetime64]]] +reveal_type(AR_LIKE_b - AR_m) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] +reveal_type(AR_LIKE_u - AR_m) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] +reveal_type(AR_LIKE_i - AR_m) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] +reveal_type(AR_LIKE_m - AR_m) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] +reveal_type(AR_LIKE_M - AR_m) # E: numpy.ndarray[Any, numpy.dtype[numpy.datetime64]] reveal_type(AR_LIKE_O - AR_m) # E: Any -reveal_type(AR_M - AR_LIKE_b) # E: Union[numpy.datetime64, numpy.ndarray[Any, numpy.dtype[numpy.datetime64]]] -reveal_type(AR_M - AR_LIKE_u) # E: Union[numpy.datetime64, numpy.ndarray[Any, numpy.dtype[numpy.datetime64]]] -reveal_type(AR_M - AR_LIKE_i) # E: Union[numpy.datetime64, numpy.ndarray[Any, numpy.dtype[numpy.datetime64]]] -reveal_type(AR_M - AR_LIKE_m) # E: Union[numpy.datetime64, numpy.ndarray[Any, numpy.dtype[numpy.datetime64]]] -reveal_type(AR_M - AR_LIKE_M) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] +reveal_type(AR_M - AR_LIKE_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.datetime64]] +reveal_type(AR_M - AR_LIKE_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.datetime64]] +reveal_type(AR_M - AR_LIKE_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.datetime64]] +reveal_type(AR_M - AR_LIKE_m) # E: numpy.ndarray[Any, numpy.dtype[numpy.datetime64]] +reveal_type(AR_M - AR_LIKE_M) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] reveal_type(AR_M - AR_LIKE_O) # E: Any -reveal_type(AR_LIKE_M - AR_M) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] +reveal_type(AR_LIKE_M - AR_M) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] reveal_type(AR_LIKE_O - AR_M) # E: Any reveal_type(AR_O - AR_LIKE_b) # E: Any @@ -165,86 +165,86 @@ reveal_type(AR_LIKE_O - AR_O) # E: Any # Array floor division -reveal_type(AR_b // AR_LIKE_b) # E: Union[{int8}, numpy.ndarray[Any, numpy.dtype[{int8}]]] -reveal_type(AR_b // AR_LIKE_u) # E: Union[numpy.unsignedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]]] -reveal_type(AR_b // AR_LIKE_i) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] -reveal_type(AR_b // AR_LIKE_f) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_b // AR_LIKE_c) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] +reveal_type(AR_b // AR_LIKE_b) # E: numpy.ndarray[Any, numpy.dtype[{int8}]] +reveal_type(AR_b // AR_LIKE_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]] +reveal_type(AR_b // AR_LIKE_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(AR_b // AR_LIKE_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_b // AR_LIKE_c) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] reveal_type(AR_b // AR_LIKE_O) # E: Any -reveal_type(AR_LIKE_b // AR_b) # E: Union[{int8}, numpy.ndarray[Any, numpy.dtype[{int8}]]] -reveal_type(AR_LIKE_u // AR_b) # E: Union[numpy.unsignedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]]] -reveal_type(AR_LIKE_i // AR_b) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] -reveal_type(AR_LIKE_f // AR_b) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_LIKE_c // AR_b) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] +reveal_type(AR_LIKE_b // AR_b) # E: numpy.ndarray[Any, numpy.dtype[{int8}]] +reveal_type(AR_LIKE_u // AR_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]] +reveal_type(AR_LIKE_i // AR_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(AR_LIKE_f // AR_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_LIKE_c // AR_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] reveal_type(AR_LIKE_O // AR_b) # E: Any -reveal_type(AR_u // AR_LIKE_b) # E: Union[numpy.unsignedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]]] -reveal_type(AR_u // AR_LIKE_u) # E: Union[numpy.unsignedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]]] -reveal_type(AR_u // AR_LIKE_i) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] -reveal_type(AR_u // AR_LIKE_f) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_u // AR_LIKE_c) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] +reveal_type(AR_u // AR_LIKE_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]] +reveal_type(AR_u // AR_LIKE_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]] +reveal_type(AR_u // AR_LIKE_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(AR_u // AR_LIKE_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_u // AR_LIKE_c) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] reveal_type(AR_u // AR_LIKE_O) # E: Any -reveal_type(AR_LIKE_b // AR_u) # E: Union[numpy.unsignedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]]] -reveal_type(AR_LIKE_u // AR_u) # E: Union[numpy.unsignedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]]] -reveal_type(AR_LIKE_i // AR_u) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] -reveal_type(AR_LIKE_f // AR_u) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_LIKE_c // AR_u) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_LIKE_m // AR_u) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] +reveal_type(AR_LIKE_b // AR_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]] +reveal_type(AR_LIKE_u // AR_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]] +reveal_type(AR_LIKE_i // AR_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(AR_LIKE_f // AR_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_LIKE_c // AR_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_LIKE_m // AR_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] reveal_type(AR_LIKE_O // AR_u) # E: Any -reveal_type(AR_i // AR_LIKE_b) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] -reveal_type(AR_i // AR_LIKE_u) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] -reveal_type(AR_i // AR_LIKE_i) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] -reveal_type(AR_i // AR_LIKE_f) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_i // AR_LIKE_c) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] +reveal_type(AR_i // AR_LIKE_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(AR_i // AR_LIKE_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(AR_i // AR_LIKE_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(AR_i // AR_LIKE_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_i // AR_LIKE_c) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] reveal_type(AR_i // AR_LIKE_O) # E: Any -reveal_type(AR_LIKE_b // AR_i) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] -reveal_type(AR_LIKE_u // AR_i) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] -reveal_type(AR_LIKE_i // AR_i) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] -reveal_type(AR_LIKE_f // AR_i) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_LIKE_c // AR_i) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_LIKE_m // AR_i) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] +reveal_type(AR_LIKE_b // AR_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(AR_LIKE_u // AR_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(AR_LIKE_i // AR_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(AR_LIKE_f // AR_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_LIKE_c // AR_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_LIKE_m // AR_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] reveal_type(AR_LIKE_O // AR_i) # E: Any -reveal_type(AR_f // AR_LIKE_b) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_f // AR_LIKE_u) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_f // AR_LIKE_i) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_f // AR_LIKE_f) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_f // AR_LIKE_c) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] +reveal_type(AR_f // AR_LIKE_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_f // AR_LIKE_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_f // AR_LIKE_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_f // AR_LIKE_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_f // AR_LIKE_c) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] reveal_type(AR_f // AR_LIKE_O) # E: Any -reveal_type(AR_LIKE_b // AR_f) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_LIKE_u // AR_f) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_LIKE_i // AR_f) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_LIKE_f // AR_f) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(AR_LIKE_c // AR_f) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_LIKE_m // AR_f) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] +reveal_type(AR_LIKE_b // AR_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_LIKE_u // AR_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_LIKE_i // AR_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_LIKE_f // AR_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(AR_LIKE_c // AR_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_LIKE_m // AR_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] reveal_type(AR_LIKE_O // AR_f) # E: Any -reveal_type(AR_c // AR_LIKE_b) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_c // AR_LIKE_u) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_c // AR_LIKE_i) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_c // AR_LIKE_f) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_c // AR_LIKE_c) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] +reveal_type(AR_c // AR_LIKE_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_c // AR_LIKE_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_c // AR_LIKE_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_c // AR_LIKE_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_c // AR_LIKE_c) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] reveal_type(AR_c // AR_LIKE_O) # E: Any -reveal_type(AR_LIKE_b // AR_c) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_LIKE_u // AR_c) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_LIKE_i // AR_c) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_LIKE_f // AR_c) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] -reveal_type(AR_LIKE_c // AR_c) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]]] +reveal_type(AR_LIKE_b // AR_c) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_LIKE_u // AR_c) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_LIKE_i // AR_c) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_LIKE_f // AR_c) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(AR_LIKE_c // AR_c) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] reveal_type(AR_LIKE_O // AR_c) # E: Any -reveal_type(AR_m // AR_LIKE_u) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] -reveal_type(AR_m // AR_LIKE_i) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] -reveal_type(AR_m // AR_LIKE_f) # E: Union[numpy.timedelta64, numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] -reveal_type(AR_m // AR_LIKE_m) # E: Union[{int64}, numpy.ndarray[Any, numpy.dtype[{int64}]]] +reveal_type(AR_m // AR_LIKE_u) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] +reveal_type(AR_m // AR_LIKE_i) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] +reveal_type(AR_m // AR_LIKE_f) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] +reveal_type(AR_m // AR_LIKE_m) # E: numpy.ndarray[Any, numpy.dtype[{int64}]] reveal_type(AR_m // AR_LIKE_O) # E: Any -reveal_type(AR_LIKE_m // AR_m) # E: Union[{int64}, numpy.ndarray[Any, numpy.dtype[{int64}]]] +reveal_type(AR_LIKE_m // AR_m) # E: numpy.ndarray[Any, numpy.dtype[{int64}]] reveal_type(AR_LIKE_O // AR_m) # E: Any reveal_type(AR_O // AR_LIKE_b) # E: Any @@ -472,9 +472,9 @@ reveal_type(AR_f + f4) # E: Any # Int reveal_type(i8 + i8) # E: {int64} -reveal_type(i8 + u8) # E: Union[numpy.signedinteger[Any], {float64}] +reveal_type(i8 + u8) # E: Any reveal_type(i8 + i4) # E: {int64} -reveal_type(i8 + u4) # E: Union[numpy.signedinteger[Any], {float64}] +reveal_type(i8 + u4) # E: Any reveal_type(i8 + b_) # E: {int64} reveal_type(i8 + b) # E: {int64} reveal_type(i8 + c) # E: {complex128} @@ -483,19 +483,19 @@ reveal_type(i8 + i) # E: {int64} reveal_type(i8 + AR_f) # E: Any reveal_type(u8 + u8) # E: {uint64} -reveal_type(u8 + i4) # E: Union[numpy.signedinteger[Any], {float64}] +reveal_type(u8 + i4) # E: Any reveal_type(u8 + u4) # E: {uint64} reveal_type(u8 + b_) # E: {uint64} reveal_type(u8 + b) # E: {uint64} reveal_type(u8 + c) # E: {complex128} reveal_type(u8 + f) # E: {float64} -reveal_type(u8 + i) # E: Union[numpy.signedinteger[Any], {float64}] +reveal_type(u8 + i) # E: Any reveal_type(u8 + AR_f) # E: Any reveal_type(i8 + i8) # E: {int64} -reveal_type(u8 + i8) # E: Union[numpy.signedinteger[Any], {float64}] +reveal_type(u8 + i8) # E: Any reveal_type(i4 + i8) # E: {int64} -reveal_type(u4 + i8) # E: Union[numpy.signedinteger[Any], {float64}] +reveal_type(u4 + i8) # E: Any reveal_type(b_ + i8) # E: {int64} reveal_type(b + i8) # E: {int64} reveal_type(c + i8) # E: {complex128} @@ -504,13 +504,13 @@ reveal_type(i + i8) # E: {int64} reveal_type(AR_f + i8) # E: Any reveal_type(u8 + u8) # E: {uint64} -reveal_type(i4 + u8) # E: Union[numpy.signedinteger[Any], {float64}] +reveal_type(i4 + u8) # E: Any reveal_type(u4 + u8) # E: {uint64} reveal_type(b_ + u8) # E: {uint64} reveal_type(b + u8) # E: {uint64} reveal_type(c + u8) # E: {complex128} reveal_type(f + u8) # E: {float64} -reveal_type(i + u8) # E: Union[numpy.signedinteger[Any], {float64}] +reveal_type(i + u8) # E: Any reveal_type(AR_f + u8) # E: Any reveal_type(i4 + i8) # E: {int64} @@ -520,11 +520,11 @@ reveal_type(i4 + b_) # E: {int32} reveal_type(i4 + b) # E: {int32} reveal_type(i4 + AR_f) # E: Any -reveal_type(u4 + i8) # E: Union[numpy.signedinteger[Any], {float64}] -reveal_type(u4 + i4) # E: Union[numpy.signedinteger[Any], {float64}] +reveal_type(u4 + i8) # E: Any +reveal_type(u4 + i4) # E: Any reveal_type(u4 + u8) # E: {uint64} reveal_type(u4 + u4) # E: {uint32} -reveal_type(u4 + i) # E: Union[numpy.signedinteger[Any], {float64}] +reveal_type(u4 + i) # E: Any reveal_type(u4 + b_) # E: {uint32} reveal_type(u4 + b) # E: {uint32} reveal_type(u4 + AR_f) # E: Any @@ -536,11 +536,11 @@ reveal_type(b_ + i4) # E: {int32} reveal_type(b + i4) # E: {int32} reveal_type(AR_f + i4) # E: Any -reveal_type(i8 + u4) # E: Union[numpy.signedinteger[Any], {float64}] -reveal_type(i4 + u4) # E: Union[numpy.signedinteger[Any], {float64}] +reveal_type(i8 + u4) # E: Any +reveal_type(i4 + u4) # E: Any reveal_type(u8 + u4) # E: {uint64} reveal_type(u4 + u4) # E: {uint32} reveal_type(b_ + u4) # E: {uint32} reveal_type(b + u4) # E: {uint32} -reveal_type(i + u4) # E: Union[numpy.signedinteger[Any], {float64}] +reveal_type(i + u4) # E: Any reveal_type(AR_f + u4) # E: Any diff --git a/numpy/typing/tests/data/reveal/array_constructors.py b/numpy/typing/tests/data/reveal/array_constructors.py index 04d5cd229..2e803a365 100644 --- a/numpy/typing/tests/data/reveal/array_constructors.py +++ b/numpy/typing/tests/data/reveal/array_constructors.py @@ -41,7 +41,7 @@ reveal_type(np.require(B, requirements="A")) # E: SubClass reveal_type(np.require(C)) # E: numpy.ndarray[Any, Any] reveal_type(np.linspace(0, 10)) # E: numpy.ndarray[Any, Any] -reveal_type(np.linspace(0, 10, retstep=True)) # E: Tuple[numpy.ndarray[Any, Any], numpy.inexact[Any]] +reveal_type(np.linspace(0, 10, retstep=True)) # E: Tuple[numpy.ndarray[Any, Any], Any] reveal_type(np.logspace(0, 10)) # E: numpy.ndarray[Any, Any] reveal_type(np.geomspace(1, 10)) # E: numpy.ndarray[Any, Any] diff --git a/numpy/typing/tests/data/reveal/comparisons.py b/numpy/typing/tests/data/reveal/comparisons.py index 5053a9e82..16f21cc39 100644 --- a/numpy/typing/tests/data/reveal/comparisons.py +++ b/numpy/typing/tests/data/reveal/comparisons.py @@ -34,12 +34,12 @@ reveal_type(td > i) # E: numpy.bool_ reveal_type(td > i4) # E: numpy.bool_ reveal_type(td > i8) # E: numpy.bool_ -reveal_type(td > AR) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(td > SEQ) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(AR > SEQ) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(AR > td) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(SEQ > td) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(SEQ > AR) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] +reveal_type(td > AR) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(td > SEQ) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(AR > SEQ) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(AR > td) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(SEQ > td) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(SEQ > AR) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] # boolean @@ -56,8 +56,8 @@ reveal_type(b_ > f4) # E: numpy.bool_ reveal_type(b_ > c) # E: numpy.bool_ reveal_type(b_ > c16) # E: numpy.bool_ reveal_type(b_ > c8) # E: numpy.bool_ -reveal_type(b_ > AR) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(b_ > SEQ) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] +reveal_type(b_ > AR) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(b_ > SEQ) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] # Complex @@ -72,8 +72,8 @@ reveal_type(c16 > b) # E: numpy.bool_ reveal_type(c16 > c) # E: numpy.bool_ reveal_type(c16 > f) # E: numpy.bool_ reveal_type(c16 > i) # E: numpy.bool_ -reveal_type(c16 > AR) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(c16 > SEQ) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] +reveal_type(c16 > AR) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(c16 > SEQ) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] reveal_type(c16 > c16) # E: numpy.bool_ reveal_type(f8 > c16) # E: numpy.bool_ @@ -86,8 +86,8 @@ reveal_type(b > c16) # E: numpy.bool_ reveal_type(c > c16) # E: numpy.bool_ reveal_type(f > c16) # E: numpy.bool_ reveal_type(i > c16) # E: numpy.bool_ -reveal_type(AR > c16) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(SEQ > c16) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] +reveal_type(AR > c16) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(SEQ > c16) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] reveal_type(c8 > c16) # E: numpy.bool_ reveal_type(c8 > f8) # E: numpy.bool_ @@ -100,8 +100,8 @@ reveal_type(c8 > b) # E: numpy.bool_ reveal_type(c8 > c) # E: numpy.bool_ reveal_type(c8 > f) # E: numpy.bool_ reveal_type(c8 > i) # E: numpy.bool_ -reveal_type(c8 > AR) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(c8 > SEQ) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] +reveal_type(c8 > AR) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(c8 > SEQ) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] reveal_type(c16 > c8) # E: numpy.bool_ reveal_type(f8 > c8) # E: numpy.bool_ @@ -114,8 +114,8 @@ reveal_type(b > c8) # E: numpy.bool_ reveal_type(c > c8) # E: numpy.bool_ reveal_type(f > c8) # E: numpy.bool_ reveal_type(i > c8) # E: numpy.bool_ -reveal_type(AR > c8) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(SEQ > c8) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] +reveal_type(AR > c8) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(SEQ > c8) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] # Float @@ -128,8 +128,8 @@ reveal_type(f8 > b) # E: numpy.bool_ reveal_type(f8 > c) # E: numpy.bool_ reveal_type(f8 > f) # E: numpy.bool_ reveal_type(f8 > i) # E: numpy.bool_ -reveal_type(f8 > AR) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(f8 > SEQ) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] +reveal_type(f8 > AR) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(f8 > SEQ) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] reveal_type(f8 > f8) # E: numpy.bool_ reveal_type(i8 > f8) # E: numpy.bool_ @@ -140,8 +140,8 @@ reveal_type(b > f8) # E: numpy.bool_ reveal_type(c > f8) # E: numpy.bool_ reveal_type(f > f8) # E: numpy.bool_ reveal_type(i > f8) # E: numpy.bool_ -reveal_type(AR > f8) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(SEQ > f8) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] +reveal_type(AR > f8) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(SEQ > f8) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] reveal_type(f4 > f8) # E: numpy.bool_ reveal_type(f4 > i8) # E: numpy.bool_ @@ -152,8 +152,8 @@ reveal_type(f4 > b) # E: numpy.bool_ reveal_type(f4 > c) # E: numpy.bool_ reveal_type(f4 > f) # E: numpy.bool_ reveal_type(f4 > i) # E: numpy.bool_ -reveal_type(f4 > AR) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(f4 > SEQ) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] +reveal_type(f4 > AR) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(f4 > SEQ) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] reveal_type(f8 > f4) # E: numpy.bool_ reveal_type(i8 > f4) # E: numpy.bool_ @@ -164,8 +164,8 @@ reveal_type(b > f4) # E: numpy.bool_ reveal_type(c > f4) # E: numpy.bool_ reveal_type(f > f4) # E: numpy.bool_ reveal_type(i > f4) # E: numpy.bool_ -reveal_type(AR > f4) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(SEQ > f4) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] +reveal_type(AR > f4) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(SEQ > f4) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] # Int @@ -178,8 +178,8 @@ reveal_type(i8 > b) # E: numpy.bool_ reveal_type(i8 > c) # E: numpy.bool_ reveal_type(i8 > f) # E: numpy.bool_ reveal_type(i8 > i) # E: numpy.bool_ -reveal_type(i8 > AR) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(i8 > SEQ) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] +reveal_type(i8 > AR) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(i8 > SEQ) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] reveal_type(u8 > u8) # E: numpy.bool_ reveal_type(u8 > i4) # E: numpy.bool_ @@ -189,8 +189,8 @@ reveal_type(u8 > b) # E: numpy.bool_ reveal_type(u8 > c) # E: numpy.bool_ reveal_type(u8 > f) # E: numpy.bool_ reveal_type(u8 > i) # E: numpy.bool_ -reveal_type(u8 > AR) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(u8 > SEQ) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] +reveal_type(u8 > AR) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(u8 > SEQ) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] reveal_type(i8 > i8) # E: numpy.bool_ reveal_type(u8 > i8) # E: numpy.bool_ @@ -201,8 +201,8 @@ reveal_type(b > i8) # E: numpy.bool_ reveal_type(c > i8) # E: numpy.bool_ reveal_type(f > i8) # E: numpy.bool_ reveal_type(i > i8) # E: numpy.bool_ -reveal_type(AR > i8) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(SEQ > i8) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] +reveal_type(AR > i8) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(SEQ > i8) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] reveal_type(u8 > u8) # E: numpy.bool_ reveal_type(i4 > u8) # E: numpy.bool_ @@ -212,16 +212,16 @@ reveal_type(b > u8) # E: numpy.bool_ reveal_type(c > u8) # E: numpy.bool_ reveal_type(f > u8) # E: numpy.bool_ reveal_type(i > u8) # E: numpy.bool_ -reveal_type(AR > u8) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(SEQ > u8) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] +reveal_type(AR > u8) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(SEQ > u8) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] reveal_type(i4 > i8) # E: numpy.bool_ reveal_type(i4 > i4) # E: numpy.bool_ reveal_type(i4 > i) # E: numpy.bool_ reveal_type(i4 > b_) # E: numpy.bool_ reveal_type(i4 > b) # E: numpy.bool_ -reveal_type(i4 > AR) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(i4 > SEQ) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] +reveal_type(i4 > AR) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(i4 > SEQ) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] reveal_type(u4 > i8) # E: numpy.bool_ reveal_type(u4 > i4) # E: numpy.bool_ @@ -230,16 +230,16 @@ reveal_type(u4 > u4) # E: numpy.bool_ reveal_type(u4 > i) # E: numpy.bool_ reveal_type(u4 > b_) # E: numpy.bool_ reveal_type(u4 > b) # E: numpy.bool_ -reveal_type(u4 > AR) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(u4 > SEQ) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] +reveal_type(u4 > AR) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(u4 > SEQ) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] reveal_type(i8 > i4) # E: numpy.bool_ reveal_type(i4 > i4) # E: numpy.bool_ reveal_type(i > i4) # E: numpy.bool_ reveal_type(b_ > i4) # E: numpy.bool_ reveal_type(b > i4) # E: numpy.bool_ -reveal_type(AR > i4) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(SEQ > i4) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] +reveal_type(AR > i4) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(SEQ > i4) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] reveal_type(i8 > u4) # E: numpy.bool_ reveal_type(i4 > u4) # E: numpy.bool_ @@ -248,5 +248,5 @@ reveal_type(u4 > u4) # E: numpy.bool_ reveal_type(b_ > u4) # E: numpy.bool_ reveal_type(b > u4) # E: numpy.bool_ reveal_type(i > u4) # E: numpy.bool_ -reveal_type(AR > u4) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(SEQ > u4) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] +reveal_type(AR > u4) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(SEQ > u4) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] diff --git a/numpy/typing/tests/data/reveal/einsumfunc.py b/numpy/typing/tests/data/reveal/einsumfunc.py index 18c192b0b..f1a90428d 100644 --- a/numpy/typing/tests/data/reveal/einsumfunc.py +++ b/numpy/typing/tests/data/reveal/einsumfunc.py @@ -10,17 +10,17 @@ AR_LIKE_U: List[str] OUT_f: np.ndarray[Any, np.dtype[np.float64]] -reveal_type(np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_b)) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]] -reveal_type(np.einsum("i,i->i", AR_LIKE_u, AR_LIKE_u)) # E: Union[numpy.unsignedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]] -reveal_type(np.einsum("i,i->i", AR_LIKE_i, AR_LIKE_i)) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] -reveal_type(np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f)) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] -reveal_type(np.einsum("i,i->i", AR_LIKE_c, AR_LIKE_c)) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] -reveal_type(np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_i)) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] -reveal_type(np.einsum("i,i,i,i->i", AR_LIKE_b, AR_LIKE_u, AR_LIKE_i, AR_LIKE_c)) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_b)) # E: Any +reveal_type(np.einsum("i,i->i", AR_LIKE_u, AR_LIKE_u)) # E: Any +reveal_type(np.einsum("i,i->i", AR_LIKE_i, AR_LIKE_i)) # E: Any +reveal_type(np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f)) # E: Any +reveal_type(np.einsum("i,i->i", AR_LIKE_c, AR_LIKE_c)) # E: Any +reveal_type(np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_i)) # E: Any +reveal_type(np.einsum("i,i,i,i->i", AR_LIKE_b, AR_LIKE_u, AR_LIKE_i, AR_LIKE_c)) # E: Any reveal_type(np.einsum("i,i->i", AR_LIKE_c, AR_LIKE_c, out=OUT_f)) # E: numpy.ndarray[Any, numpy.dtype[{float64}] reveal_type(np.einsum("i,i->i", AR_LIKE_U, AR_LIKE_U, dtype=bool, casting="unsafe", out=OUT_f)) # E: numpy.ndarray[Any, numpy.dtype[{float64}] -reveal_type(np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f, dtype="c16")) # E: Union[numpy.complexfloating[Any, Any], numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f, dtype="c16")) # E: Any reveal_type(np.einsum("i,i->i", AR_LIKE_U, AR_LIKE_U, dtype=bool, casting="unsafe")) # E: Any reveal_type(np.einsum_path("i,i->i", AR_LIKE_b, AR_LIKE_b)) # E: Tuple[builtins.list[Any], builtins.str] diff --git a/numpy/typing/tests/data/reveal/fromnumeric.py b/numpy/typing/tests/data/reveal/fromnumeric.py index 2b58f019f..bbcfbb85a 100644 --- a/numpy/typing/tests/data/reveal/fromnumeric.py +++ b/numpy/typing/tests/data/reveal/fromnumeric.py @@ -12,27 +12,13 @@ b = np.float32(1.0) c = 1.0 d = np.array(1.0, dtype=np.float32) # writeable -reveal_type(np.take(a, 0)) # E: numpy.bool_ -reveal_type(np.take(b, 0)) # E: {float32} -reveal_type( - np.take(c, 0) # E: Union[numpy.generic, datetime.datetime, datetime.timedelta] -) -reveal_type( - np.take(A, 0) # E: Union[numpy.generic, datetime.datetime, datetime.timedelta] -) -reveal_type( - np.take(B, 0) # E: Union[numpy.generic, datetime.datetime, datetime.timedelta] -) -reveal_type( - np.take( # E: Union[Union[numpy.generic, datetime.datetime, datetime.timedelta], numpy.ndarray[Any, Any]] - A, [0] - ) -) -reveal_type( - np.take( # E: Union[Union[numpy.generic, datetime.datetime, datetime.timedelta], numpy.ndarray[Any, Any]] - B, [0] - ) -) +reveal_type(np.take(a, 0)) # E: Any +reveal_type(np.take(b, 0)) # E: Any +reveal_type(np.take(c, 0)) # E: Any +reveal_type(np.take(A, 0)) # E: Any +reveal_type(np.take(B, 0)) # E: Any +reveal_type(np.take(A, [0])) # E: Any +reveal_type(np.take(B, [0])) # E: Any reveal_type(np.reshape(a, 1)) # E: numpy.ndarray[Any, Any] reveal_type(np.reshape(b, 1)) # E: numpy.ndarray[Any, Any] @@ -40,8 +26,8 @@ reveal_type(np.reshape(c, 1)) # E: numpy.ndarray[Any, Any] reveal_type(np.reshape(A, 1)) # E: numpy.ndarray[Any, Any] reveal_type(np.reshape(B, 1)) # E: numpy.ndarray[Any, Any] -reveal_type(np.choose(a, [True, True])) # E: numpy.bool_ -reveal_type(np.choose(A, [True, True])) # E: numpy.ndarray[Any, Any] +reveal_type(np.choose(a, [True, True])) # E: Any +reveal_type(np.choose(A, [True, True])) # E: Any reveal_type(np.repeat(a, 1)) # E: numpy.ndarray[Any, Any] reveal_type(np.repeat(b, 1)) # E: numpy.ndarray[Any, Any] @@ -66,11 +52,11 @@ reveal_type(np.partition(c, 0, axis=None)) # E: numpy.ndarray[Any, Any] reveal_type(np.partition(A, 0)) # E: numpy.ndarray[Any, Any] reveal_type(np.partition(B, 0)) # E: numpy.ndarray[Any, Any] -reveal_type(np.argpartition(a, 0)) # E: {intp} -reveal_type(np.argpartition(b, 0)) # E: {intp} -reveal_type(np.argpartition(c, 0)) # E: numpy.ndarray[Any, Any] -reveal_type(np.argpartition(A, 0)) # E: numpy.ndarray[Any, Any] -reveal_type(np.argpartition(B, 0)) # E: numpy.ndarray[Any, Any] +reveal_type(np.argpartition(a, 0)) # E: Any +reveal_type(np.argpartition(b, 0)) # E: Any +reveal_type(np.argpartition(c, 0)) # E: Any +reveal_type(np.argpartition(A, 0)) # E: Any +reveal_type(np.argpartition(B, 0)) # E: Any reveal_type(np.sort(A, 0)) # E: numpy.ndarray[Any, Any] reveal_type(np.sort(B, 0)) # E: numpy.ndarray[Any, Any] @@ -80,13 +66,13 @@ reveal_type(np.argsort(B, 0)) # E: numpy.ndarray[Any, Any] reveal_type(np.argmax(A)) # E: {intp} reveal_type(np.argmax(B)) # E: {intp} -reveal_type(np.argmax(A, axis=0)) # E: Union[numpy.ndarray[Any, Any], {intp}] -reveal_type(np.argmax(B, axis=0)) # E: Union[numpy.ndarray[Any, Any], {intp}] +reveal_type(np.argmax(A, axis=0)) # E: Any +reveal_type(np.argmax(B, axis=0)) # E: Any reveal_type(np.argmin(A)) # E: {intp} reveal_type(np.argmin(B)) # E: {intp} -reveal_type(np.argmin(A, axis=0)) # E: Union[numpy.ndarray[Any, Any], {intp}] -reveal_type(np.argmin(B, axis=0)) # E: Union[numpy.ndarray[Any, Any], {intp}] +reveal_type(np.argmin(A, axis=0)) # E: Any +reveal_type(np.argmin(B, axis=0)) # E: Any reveal_type(np.searchsorted(A[0], 0)) # E: {intp} reveal_type(np.searchsorted(B[0], 0)) # E: {intp} @@ -108,8 +94,8 @@ reveal_type(np.squeeze(B)) # E: numpy.ndarray[Any, Any] reveal_type(np.diagonal(A)) # E: numpy.ndarray[Any, Any] reveal_type(np.diagonal(B)) # E: numpy.ndarray[Any, Any] -reveal_type(np.trace(A)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.trace(B)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] +reveal_type(np.trace(A)) # E: Any +reveal_type(np.trace(B)) # E: Any reveal_type(np.ravel(a)) # E: numpy.ndarray[Any, Any] reveal_type(np.ravel(b)) # E: numpy.ndarray[Any, Any] @@ -135,39 +121,39 @@ reveal_type(np.compress([True], c)) # E: numpy.ndarray[Any, Any] reveal_type(np.compress([True], A)) # E: numpy.ndarray[Any, Any] reveal_type(np.compress([True], B)) # E: numpy.ndarray[Any, Any] -reveal_type(np.clip(a, 0, 1.0)) # E: numpy.number[Any] -reveal_type(np.clip(b, -1, 1)) # E: {float32} -reveal_type(np.clip(c, 0, 1)) # E: numpy.number[Any] -reveal_type(np.clip(A, 0, 1)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.clip(B, 0, 1)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] +reveal_type(np.clip(a, 0, 1.0)) # E: Any +reveal_type(np.clip(b, -1, 1)) # E: Any +reveal_type(np.clip(c, 0, 1)) # E: Any +reveal_type(np.clip(A, 0, 1)) # E: Any +reveal_type(np.clip(B, 0, 1)) # E: Any -reveal_type(np.sum(a)) # E: numpy.number[Any] -reveal_type(np.sum(b)) # E: {float32} -reveal_type(np.sum(c)) # E: numpy.number[Any] -reveal_type(np.sum(A)) # E: numpy.number[Any] -reveal_type(np.sum(B)) # E: numpy.number[Any] -reveal_type(np.sum(A, axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.sum(B, axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] +reveal_type(np.sum(a)) # E: Any +reveal_type(np.sum(b)) # E: Any +reveal_type(np.sum(c)) # E: Any +reveal_type(np.sum(A)) # E: Any +reveal_type(np.sum(B)) # E: Any +reveal_type(np.sum(A, axis=0)) # E: Any +reveal_type(np.sum(B, axis=0)) # E: Any reveal_type(np.all(a)) # E: numpy.bool_ reveal_type(np.all(b)) # E: numpy.bool_ reveal_type(np.all(c)) # E: numpy.bool_ reveal_type(np.all(A)) # E: numpy.bool_ reveal_type(np.all(B)) # E: numpy.bool_ -reveal_type(np.all(A, axis=0)) # E: Union[numpy.bool_, numpy.ndarray[Any, Any]] -reveal_type(np.all(B, axis=0)) # E: Union[numpy.bool_, numpy.ndarray[Any, Any]] -reveal_type(np.all(A, keepdims=True)) # E: Union[numpy.bool_, numpy.ndarray[Any, Any]] -reveal_type(np.all(B, keepdims=True)) # E: Union[numpy.bool_, numpy.ndarray[Any, Any]] +reveal_type(np.all(A, axis=0)) # E: Any +reveal_type(np.all(B, axis=0)) # E: Any +reveal_type(np.all(A, keepdims=True)) # E: Any +reveal_type(np.all(B, keepdims=True)) # E: Any reveal_type(np.any(a)) # E: numpy.bool_ reveal_type(np.any(b)) # E: numpy.bool_ reveal_type(np.any(c)) # E: numpy.bool_ reveal_type(np.any(A)) # E: numpy.bool_ reveal_type(np.any(B)) # E: numpy.bool_ -reveal_type(np.any(A, axis=0)) # E: Union[numpy.bool_, numpy.ndarray[Any, Any]] -reveal_type(np.any(B, axis=0)) # E: Union[numpy.bool_, numpy.ndarray[Any, Any]] -reveal_type(np.any(A, keepdims=True)) # E: Union[numpy.bool_, numpy.ndarray[Any, Any]] -reveal_type(np.any(B, keepdims=True)) # E: Union[numpy.bool_, numpy.ndarray[Any, Any]] +reveal_type(np.any(A, axis=0)) # E: Any +reveal_type(np.any(B, axis=0)) # E: Any +reveal_type(np.any(A, keepdims=True)) # E: Any +reveal_type(np.any(B, keepdims=True)) # E: Any reveal_type(np.cumsum(a)) # E: numpy.ndarray[Any, Any] reveal_type(np.cumsum(b)) # E: numpy.ndarray[Any, Any] @@ -175,47 +161,47 @@ reveal_type(np.cumsum(c)) # E: numpy.ndarray[Any, Any] reveal_type(np.cumsum(A)) # E: numpy.ndarray[Any, Any] reveal_type(np.cumsum(B)) # E: numpy.ndarray[Any, Any] -reveal_type(np.ptp(a)) # E: numpy.number[Any] -reveal_type(np.ptp(b)) # E: {float32} -reveal_type(np.ptp(c)) # E: numpy.number[Any] -reveal_type(np.ptp(A)) # E: numpy.number[Any] -reveal_type(np.ptp(B)) # E: numpy.number[Any] -reveal_type(np.ptp(A, axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.ptp(B, axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.ptp(A, keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.ptp(B, keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] - -reveal_type(np.amax(a)) # E: numpy.number[Any] -reveal_type(np.amax(b)) # E: {float32} -reveal_type(np.amax(c)) # E: numpy.number[Any] -reveal_type(np.amax(A)) # E: numpy.number[Any] -reveal_type(np.amax(B)) # E: numpy.number[Any] -reveal_type(np.amax(A, axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.amax(B, axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.amax(A, keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.amax(B, keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] - -reveal_type(np.amin(a)) # E: numpy.number[Any] -reveal_type(np.amin(b)) # E: {float32} -reveal_type(np.amin(c)) # E: numpy.number[Any] -reveal_type(np.amin(A)) # E: numpy.number[Any] -reveal_type(np.amin(B)) # E: numpy.number[Any] -reveal_type(np.amin(A, axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.amin(B, axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.amin(A, keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.amin(B, keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] - -reveal_type(np.prod(a)) # E: numpy.number[Any] -reveal_type(np.prod(b)) # E: {float32} -reveal_type(np.prod(c)) # E: numpy.number[Any] -reveal_type(np.prod(A)) # E: numpy.number[Any] -reveal_type(np.prod(B)) # E: numpy.number[Any] -reveal_type(np.prod(A, axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.prod(B, axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.prod(A, keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.prod(B, keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.prod(b, out=d)) # E: numpy.ndarray[Any, Any] -reveal_type(np.prod(B, out=d)) # E: numpy.ndarray[Any, Any] +reveal_type(np.ptp(a)) # E: Any +reveal_type(np.ptp(b)) # E: Any +reveal_type(np.ptp(c)) # E: Any +reveal_type(np.ptp(A)) # E: Any +reveal_type(np.ptp(B)) # E: Any +reveal_type(np.ptp(A, axis=0)) # E: Any +reveal_type(np.ptp(B, axis=0)) # E: Any +reveal_type(np.ptp(A, keepdims=True)) # E: Any +reveal_type(np.ptp(B, keepdims=True)) # E: Any + +reveal_type(np.amax(a)) # E: Any +reveal_type(np.amax(b)) # E: Any +reveal_type(np.amax(c)) # E: Any +reveal_type(np.amax(A)) # E: Any +reveal_type(np.amax(B)) # E: Any +reveal_type(np.amax(A, axis=0)) # E: Any +reveal_type(np.amax(B, axis=0)) # E: Any +reveal_type(np.amax(A, keepdims=True)) # E: Any +reveal_type(np.amax(B, keepdims=True)) # E: Any + +reveal_type(np.amin(a)) # E: Any +reveal_type(np.amin(b)) # E: Any +reveal_type(np.amin(c)) # E: Any +reveal_type(np.amin(A)) # E: Any +reveal_type(np.amin(B)) # E: Any +reveal_type(np.amin(A, axis=0)) # E: Any +reveal_type(np.amin(B, axis=0)) # E: Any +reveal_type(np.amin(A, keepdims=True)) # E: Any +reveal_type(np.amin(B, keepdims=True)) # E: Any + +reveal_type(np.prod(a)) # E: Any +reveal_type(np.prod(b)) # E: Any +reveal_type(np.prod(c)) # E: Any +reveal_type(np.prod(A)) # E: Any +reveal_type(np.prod(B)) # E: Any +reveal_type(np.prod(A, axis=0)) # E: Any +reveal_type(np.prod(B, axis=0)) # E: Any +reveal_type(np.prod(A, keepdims=True)) # E: Any +reveal_type(np.prod(B, keepdims=True)) # E: Any +reveal_type(np.prod(b, out=d)) # E: Any +reveal_type(np.prod(B, out=d)) # E: Any reveal_type(np.cumprod(a)) # E: numpy.ndarray[Any, Any] reveal_type(np.cumprod(b)) # E: numpy.ndarray[Any, Any] @@ -235,44 +221,44 @@ reveal_type(np.size(c)) # E: int reveal_type(np.size(A)) # E: int reveal_type(np.size(B)) # E: int -reveal_type(np.around(a)) # E: numpy.number[Any] -reveal_type(np.around(b)) # E: {float32} -reveal_type(np.around(c)) # E: numpy.number[Any] -reveal_type(np.around(A)) # E: numpy.ndarray[Any, Any] -reveal_type(np.around(B)) # E: numpy.ndarray[Any, Any] - -reveal_type(np.mean(a)) # E: numpy.number[Any] -reveal_type(np.mean(b)) # E: numpy.number[Any] -reveal_type(np.mean(c)) # E: numpy.number[Any] -reveal_type(np.mean(A)) # E: numpy.number[Any] -reveal_type(np.mean(B)) # E: numpy.number[Any] -reveal_type(np.mean(A, axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.mean(B, axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.mean(A, keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.mean(B, keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.mean(b, out=d)) # E: numpy.ndarray[Any, Any] -reveal_type(np.mean(B, out=d)) # E: numpy.ndarray[Any, Any] - -reveal_type(np.std(a)) # E: numpy.number[Any] -reveal_type(np.std(b)) # E: numpy.number[Any] -reveal_type(np.std(c)) # E: numpy.number[Any] -reveal_type(np.std(A)) # E: numpy.number[Any] -reveal_type(np.std(B)) # E: numpy.number[Any] -reveal_type(np.std(A, axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.std(B, axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.std(A, keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.std(B, keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.std(b, out=d)) # E: numpy.ndarray[Any, Any] -reveal_type(np.std(B, out=d)) # E: numpy.ndarray[Any, Any] - -reveal_type(np.var(a)) # E: numpy.number[Any] -reveal_type(np.var(b)) # E: numpy.number[Any] -reveal_type(np.var(c)) # E: numpy.number[Any] -reveal_type(np.var(A)) # E: numpy.number[Any] -reveal_type(np.var(B)) # E: numpy.number[Any] -reveal_type(np.var(A, axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.var(B, axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.var(A, keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.var(B, keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(np.var(b, out=d)) # E: numpy.ndarray[Any, Any] -reveal_type(np.var(B, out=d)) # E: numpy.ndarray[Any, Any] +reveal_type(np.around(a)) # E: Any +reveal_type(np.around(b)) # E: Any +reveal_type(np.around(c)) # E: Any +reveal_type(np.around(A)) # E: Any +reveal_type(np.around(B)) # E: Any + +reveal_type(np.mean(a)) # E: Any +reveal_type(np.mean(b)) # E: Any +reveal_type(np.mean(c)) # E: Any +reveal_type(np.mean(A)) # E: Any +reveal_type(np.mean(B)) # E: Any +reveal_type(np.mean(A, axis=0)) # E: Any +reveal_type(np.mean(B, axis=0)) # E: Any +reveal_type(np.mean(A, keepdims=True)) # E: Any +reveal_type(np.mean(B, keepdims=True)) # E: Any +reveal_type(np.mean(b, out=d)) # E: Any +reveal_type(np.mean(B, out=d)) # E: Any + +reveal_type(np.std(a)) # E: Any +reveal_type(np.std(b)) # E: Any +reveal_type(np.std(c)) # E: Any +reveal_type(np.std(A)) # E: Any +reveal_type(np.std(B)) # E: Any +reveal_type(np.std(A, axis=0)) # E: Any +reveal_type(np.std(B, axis=0)) # E: Any +reveal_type(np.std(A, keepdims=True)) # E: Any +reveal_type(np.std(B, keepdims=True)) # E: Any +reveal_type(np.std(b, out=d)) # E: Any +reveal_type(np.std(B, out=d)) # E: Any + +reveal_type(np.var(a)) # E: Any +reveal_type(np.var(b)) # E: Any +reveal_type(np.var(c)) # E: Any +reveal_type(np.var(A)) # E: Any +reveal_type(np.var(B)) # E: Any +reveal_type(np.var(A, axis=0)) # E: Any +reveal_type(np.var(B, axis=0)) # E: Any +reveal_type(np.var(A, keepdims=True)) # E: Any +reveal_type(np.var(B, keepdims=True)) # E: Any +reveal_type(np.var(b, out=d)) # E: Any +reveal_type(np.var(B, out=d)) # E: Any diff --git a/numpy/typing/tests/data/reveal/index_tricks.py b/numpy/typing/tests/data/reveal/index_tricks.py index ec2013025..863d60220 100644 --- a/numpy/typing/tests/data/reveal/index_tricks.py +++ b/numpy/typing/tests/data/reveal/index_tricks.py @@ -27,15 +27,16 @@ reveal_type(iter(np.ndenumerate(AR_LIKE_U))) # E: Iterator[Tuple[builtins.tuple reveal_type(iter(np.ndindex(1, 2, 3))) # E: Iterator[builtins.tuple[builtins.int]] reveal_type(next(np.ndindex(1, 2, 3))) # E: builtins.tuple[builtins.int] -reveal_type(np.unravel_index([22, 41, 37], (7, 6))) # E: tuple[Union[{intp}, numpy.ndarray[Any, numpy.dtype[{intp}]]]] -reveal_type(np.unravel_index([31, 41, 13], (7, 6), order="F")) # E: tuple[Union[{intp}, numpy.ndarray[Any, numpy.dtype[{intp}]]]] -reveal_type(np.unravel_index(1621, (6, 7, 8, 9))) # E: tuple[Union[{intp}, numpy.ndarray[Any, numpy.dtype[{intp}]]]] - -reveal_type(np.ravel_multi_index(AR_LIKE_i, (7, 6))) # E: Union[{intp}, numpy.ndarray[Any, numpy.dtype[{intp}]]] -reveal_type(np.ravel_multi_index(AR_LIKE_i, (7, 6), order="F")) # E: Union[{intp}, numpy.ndarray[Any, numpy.dtype[{intp}]]] -reveal_type(np.ravel_multi_index(AR_LIKE_i, (4, 6), mode="clip")) # E: Union[{intp}, numpy.ndarray[Any, numpy.dtype[{intp}]]] -reveal_type(np.ravel_multi_index(AR_LIKE_i, (4, 4), mode=("clip", "wrap"))) # E: Union[{intp}, numpy.ndarray[Any, numpy.dtype[{intp}]]] -reveal_type(np.ravel_multi_index((3, 1, 4, 1), (6, 7, 8, 9))) # E: Union[{intp}, numpy.ndarray[Any, numpy.dtype[{intp}]]] +reveal_type(np.unravel_index([22, 41, 37], (7, 6))) # E: tuple[numpy.ndarray[Any, numpy.dtype[{intp}]]] +reveal_type(np.unravel_index([31, 41, 13], (7, 6), order="F")) # E: tuple[numpy.ndarray[Any, numpy.dtype[{intp}]]] +reveal_type(np.unravel_index(1621, (6, 7, 8, 9))) # E: tuple[{intp}] + +reveal_type(np.ravel_multi_index([[1]], (7, 6))) # E: numpy.ndarray[Any, numpy.dtype[{intp}]] +reveal_type(np.ravel_multi_index(AR_LIKE_i, (7, 6))) # E: {intp} +reveal_type(np.ravel_multi_index(AR_LIKE_i, (7, 6), order="F")) # E: {intp} +reveal_type(np.ravel_multi_index(AR_LIKE_i, (4, 6), mode="clip")) # E: {intp} +reveal_type(np.ravel_multi_index(AR_LIKE_i, (4, 4), mode=("clip", "wrap"))) # E: {intp} +reveal_type(np.ravel_multi_index((3, 1, 4, 1), (6, 7, 8, 9))) # E: {intp} reveal_type(np.mgrid[1:1:2]) # E: numpy.ndarray[Any, numpy.dtype[Any]] reveal_type(np.mgrid[1:1:2, None:10]) # E: numpy.ndarray[Any, numpy.dtype[Any]] diff --git a/numpy/typing/tests/data/reveal/mod.py b/numpy/typing/tests/data/reveal/mod.py index 4a913f11a..bf45b8c58 100644 --- a/numpy/typing/tests/data/reveal/mod.py +++ b/numpy/typing/tests/data/reveal/mod.py @@ -26,8 +26,8 @@ reveal_type(AR_m % td) # E: Any reveal_type(td % AR_m) # E: Any reveal_type(divmod(td, td)) # E: Tuple[{int64}, numpy.timedelta64] -reveal_type(divmod(AR_m, td)) # E: Union[Tuple[numpy.signedinteger[numpy.typing._64Bit], numpy.timedelta64], Tuple[numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[numpy.typing._64Bit]]], numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]]] -reveal_type(divmod(td, AR_m)) # E: Union[Tuple[numpy.signedinteger[numpy.typing._64Bit], numpy.timedelta64], Tuple[numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[numpy.typing._64Bit]]], numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]]] +reveal_type(divmod(AR_m, td)) # E: Tuple[numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[numpy.typing._64Bit]]], numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] +reveal_type(divmod(td, AR_m)) # E: Tuple[numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[numpy.typing._64Bit]]], numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]]] # Bool @@ -38,7 +38,7 @@ reveal_type(b_ % b_) # E: {int8} reveal_type(b_ % i8) # E: {int64} reveal_type(b_ % u8) # E: {uint64} reveal_type(b_ % f8) # E: {float64} -reveal_type(b_ % AR_b) # E: Union[{int8}, numpy.ndarray[Any, numpy.dtype[{int8}]]] +reveal_type(b_ % AR_b) # E: numpy.ndarray[Any, numpy.dtype[{int8}]] reveal_type(divmod(b_, b)) # E: Tuple[{int8}, {int8}] reveal_type(divmod(b_, i)) # E: Tuple[{int_}, {int_}] @@ -47,7 +47,7 @@ reveal_type(divmod(b_, b_)) # E: Tuple[{int8}, {int8}] reveal_type(divmod(b_, i8)) # E: Tuple[{int64}, {int64}] reveal_type(divmod(b_, u8)) # E: Tuple[{uint64}, {uint64}] reveal_type(divmod(b_, f8)) # E: Tuple[{float64}, {float64}] -reveal_type(divmod(b_, AR_b)) # E: Tuple[Union[{int8}, numpy.ndarray[Any, numpy.dtype[{int8}]]], Union[{int8}, numpy.ndarray[Any, numpy.dtype[{int8}]]]] +reveal_type(divmod(b_, AR_b)) # E: numpy.ndarray[Any, numpy.dtype[{int8}]], numpy.ndarray[Any, numpy.dtype[{int8}]]] reveal_type(b % b_) # E: {int8} reveal_type(i % b_) # E: {int_} @@ -56,7 +56,7 @@ reveal_type(b_ % b_) # E: {int8} reveal_type(i8 % b_) # E: {int64} reveal_type(u8 % b_) # E: {uint64} reveal_type(f8 % b_) # E: {float64} -reveal_type(AR_b % b_) # E: Union[{int8}, numpy.ndarray[Any, numpy.dtype[{int8}]]] +reveal_type(AR_b % b_) # E: numpy.ndarray[Any, numpy.dtype[{int8}]] reveal_type(divmod(b, b_)) # E: Tuple[{int8}, {int8}] reveal_type(divmod(i, b_)) # E: Tuple[{int_}, {int_}] @@ -65,7 +65,7 @@ reveal_type(divmod(b_, b_)) # E: Tuple[{int8}, {int8}] reveal_type(divmod(i8, b_)) # E: Tuple[{int64}, {int64}] reveal_type(divmod(u8, b_)) # E: Tuple[{uint64}, {uint64}] reveal_type(divmod(f8, b_)) # E: Tuple[{float64}, {float64}] -reveal_type(divmod(AR_b, b_)) # E: Tuple[Union[{int8}, numpy.ndarray[Any, numpy.dtype[{int8}]]], Union[{int8}, numpy.ndarray[Any, numpy.dtype[{int8}]]]] +reveal_type(divmod(AR_b, b_)) # E: numpy.ndarray[Any, numpy.dtype[{int8}]], numpy.ndarray[Any, numpy.dtype[{int8}]]] # int @@ -78,7 +78,7 @@ reveal_type(i4 % i8) # E: {int64} reveal_type(i4 % f8) # E: {float64} reveal_type(i4 % i4) # E: {int32} reveal_type(i4 % f4) # E: {float32} -reveal_type(i8 % AR_b) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] +reveal_type(i8 % AR_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] reveal_type(divmod(i8, b)) # E: Tuple[{int64}, {int64}] reveal_type(divmod(i8, i)) # E: Tuple[{int64}, {int64}] @@ -89,7 +89,7 @@ reveal_type(divmod(i8, i4)) # E: Tuple[{int64}, {int64}] reveal_type(divmod(i8, f4)) # E: Tuple[{float64}, {float64}] reveal_type(divmod(i4, i4)) # E: Tuple[{int32}, {int32}] reveal_type(divmod(i4, f4)) # E: Tuple[{float32}, {float32}] -reveal_type(divmod(i8, AR_b)) # E: Tuple[Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]], Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]]] +reveal_type(divmod(i8, AR_b)) # E: Tuple[numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] reveal_type(b % i8) # E: {int64} reveal_type(i % i8) # E: {int64} @@ -100,7 +100,7 @@ reveal_type(i8 % i4) # E: {int64} reveal_type(f8 % i4) # E: {float64} reveal_type(i4 % i4) # E: {int32} reveal_type(f4 % i4) # E: {float32} -reveal_type(AR_b % i8) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] +reveal_type(AR_b % i8) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] reveal_type(divmod(b, i8)) # E: Tuple[{int64}, {int64}] reveal_type(divmod(i, i8)) # E: Tuple[{int64}, {int64}] @@ -111,7 +111,7 @@ reveal_type(divmod(i4, i8)) # E: Tuple[{int64}, {int64}] reveal_type(divmod(f4, i8)) # E: Tuple[{float64}, {float64}] reveal_type(divmod(i4, i4)) # E: Tuple[{int32}, {int32}] reveal_type(divmod(f4, i4)) # E: Tuple[{float32}, {float32}] -reveal_type(divmod(AR_b, i8)) # E: Tuple[Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]], Union[numpy.signedinteger[Any], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]]] +reveal_type(divmod(AR_b, i8)) # E: Tuple[numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]], numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]]] # float @@ -120,7 +120,7 @@ reveal_type(f8 % i) # E: {float64} reveal_type(f8 % f) # E: {float64} reveal_type(i8 % f4) # E: {float64} reveal_type(f4 % f4) # E: {float32} -reveal_type(f8 % AR_b) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] +reveal_type(f8 % AR_b) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] reveal_type(divmod(f8, b)) # E: Tuple[{float64}, {float64}] reveal_type(divmod(f8, i)) # E: Tuple[{float64}, {float64}] @@ -128,7 +128,7 @@ reveal_type(divmod(f8, f)) # E: Tuple[{float64}, {float64}] reveal_type(divmod(f8, f8)) # E: Tuple[{float64}, {float64}] reveal_type(divmod(f8, f4)) # E: Tuple[{float64}, {float64}] reveal_type(divmod(f4, f4)) # E: Tuple[{float32}, {float32}] -reveal_type(divmod(f8, AR_b)) # E: Tuple[Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]], Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]]] +reveal_type(divmod(f8, AR_b)) # E: Tuple[numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] reveal_type(b % f8) # E: {float64} reveal_type(i % f8) # E: {float64} @@ -136,7 +136,7 @@ reveal_type(f % f8) # E: {float64} reveal_type(f8 % f8) # E: {float64} reveal_type(f8 % f8) # E: {float64} reveal_type(f4 % f4) # E: {float32} -reveal_type(AR_b % f8) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] +reveal_type(AR_b % f8) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] reveal_type(divmod(b, f8)) # E: Tuple[{float64}, {float64}] reveal_type(divmod(i, f8)) # E: Tuple[{float64}, {float64}] @@ -144,4 +144,4 @@ reveal_type(divmod(f, f8)) # E: Tuple[{float64}, {float64}] reveal_type(divmod(f8, f8)) # E: Tuple[{float64}, {float64}] reveal_type(divmod(f4, f8)) # E: Tuple[{float64}, {float64}] reveal_type(divmod(f4, f4)) # E: Tuple[{float32}, {float32}] -reveal_type(divmod(AR_b, f8)) # E: Tuple[Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]], Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]]] +reveal_type(divmod(AR_b, f8)) # E: Tuple[numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] diff --git a/numpy/typing/tests/data/reveal/ndarray_misc.py b/numpy/typing/tests/data/reveal/ndarray_misc.py index 0f7345358..e0f44bcbc 100644 --- a/numpy/typing/tests/data/reveal/ndarray_misc.py +++ b/numpy/typing/tests/data/reveal/ndarray_misc.py @@ -16,24 +16,24 @@ B: SubClass reveal_type(f8.all()) # E: numpy.bool_ reveal_type(A.all()) # E: numpy.bool_ -reveal_type(A.all(axis=0)) # E: Union[numpy.bool_, numpy.ndarray[Any, Any]] -reveal_type(A.all(keepdims=True)) # E: Union[numpy.bool_, numpy.ndarray[Any, Any]] +reveal_type(A.all(axis=0)) # E: Any +reveal_type(A.all(keepdims=True)) # E: Any reveal_type(A.all(out=B)) # E: SubClass reveal_type(f8.any()) # E: numpy.bool_ reveal_type(A.any()) # E: numpy.bool_ -reveal_type(A.any(axis=0)) # E: Union[numpy.bool_, numpy.ndarray[Any, Any]] -reveal_type(A.any(keepdims=True)) # E: Union[numpy.bool_, numpy.ndarray[Any, Any]] +reveal_type(A.any(axis=0)) # E: Any +reveal_type(A.any(keepdims=True)) # E: Any reveal_type(A.any(out=B)) # E: SubClass reveal_type(f8.argmax()) # E: {intp} reveal_type(A.argmax()) # E: {intp} -reveal_type(A.argmax(axis=0)) # E: Union[numpy.ndarray[Any, Any], {intp}] +reveal_type(A.argmax(axis=0)) # E: Any reveal_type(A.argmax(out=B)) # E: SubClass reveal_type(f8.argmin()) # E: {intp} reveal_type(A.argmin()) # E: {intp} -reveal_type(A.argmin(axis=0)) # E: Union[numpy.ndarray[Any, Any], {intp}] +reveal_type(A.argmin(axis=0)) # E: Any reveal_type(A.argmin(out=B)) # E: SubClass reveal_type(f8.argsort()) # E: numpy.ndarray[Any, Any] @@ -43,9 +43,9 @@ reveal_type(f8.astype(np.int64).choose([()])) # E: numpy.ndarray[Any, Any] reveal_type(A.choose([0])) # E: numpy.ndarray[Any, Any] reveal_type(A.choose([0], out=B)) # E: SubClass -reveal_type(f8.clip(1)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(A.clip(1)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(A.clip(None, 1)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] +reveal_type(f8.clip(1)) # E: Any +reveal_type(A.clip(1)) # E: Any +reveal_type(A.clip(None, 1)) # E: Any reveal_type(A.clip(1, out=B)) # E: SubClass reveal_type(A.clip(None, 1, out=B)) # E: SubClass @@ -69,38 +69,38 @@ reveal_type(f8.cumsum()) # E: numpy.ndarray[Any, Any] reveal_type(A.cumsum()) # E: numpy.ndarray[Any, Any] reveal_type(A.cumsum(out=B)) # E: SubClass -reveal_type(f8.max()) # E: numpy.number[Any] -reveal_type(A.max()) # E: numpy.number[Any] -reveal_type(A.max(axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(A.max(keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] +reveal_type(f8.max()) # E: Any +reveal_type(A.max()) # E: Any +reveal_type(A.max(axis=0)) # E: Any +reveal_type(A.max(keepdims=True)) # E: Any reveal_type(A.max(out=B)) # E: SubClass -reveal_type(f8.mean()) # E: numpy.number[Any] -reveal_type(A.mean()) # E: numpy.number[Any] -reveal_type(A.mean(axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(A.mean(keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] +reveal_type(f8.mean()) # E: Any +reveal_type(A.mean()) # E: Any +reveal_type(A.mean(axis=0)) # E: Any +reveal_type(A.mean(keepdims=True)) # E: Any reveal_type(A.mean(out=B)) # E: SubClass -reveal_type(f8.min()) # E: numpy.number[Any] -reveal_type(A.min()) # E: numpy.number[Any] -reveal_type(A.min(axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(A.min(keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] +reveal_type(f8.min()) # E: Any +reveal_type(A.min()) # E: Any +reveal_type(A.min(axis=0)) # E: Any +reveal_type(A.min(keepdims=True)) # E: Any reveal_type(A.min(out=B)) # E: SubClass reveal_type(f8.newbyteorder()) # E: {float64} reveal_type(A.newbyteorder()) # E: numpy.ndarray[Any, Any] reveal_type(B.newbyteorder('|')) # E: SubClass -reveal_type(f8.prod()) # E: numpy.number[Any] -reveal_type(A.prod()) # E: numpy.number[Any] -reveal_type(A.prod(axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(A.prod(keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] +reveal_type(f8.prod()) # E: Any +reveal_type(A.prod()) # E: Any +reveal_type(A.prod(axis=0)) # E: Any +reveal_type(A.prod(keepdims=True)) # E: Any reveal_type(A.prod(out=B)) # E: SubClass -reveal_type(f8.ptp()) # E: numpy.number[Any] -reveal_type(A.ptp()) # E: numpy.number[Any] -reveal_type(A.ptp(axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(A.ptp(keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] +reveal_type(f8.ptp()) # E: Any +reveal_type(A.ptp()) # E: Any +reveal_type(A.ptp(axis=0)) # E: Any +reveal_type(A.ptp(keepdims=True)) # E: Any reveal_type(A.ptp(out=B)) # E: SubClass reveal_type(f8.round()) # E: {float64} @@ -111,40 +111,40 @@ reveal_type(f8.repeat(1)) # E: numpy.ndarray[Any, Any] reveal_type(A.repeat(1)) # E: numpy.ndarray[Any, Any] reveal_type(B.repeat(1)) # E: numpy.ndarray[Any, Any] -reveal_type(f8.std()) # E: numpy.number[Any] -reveal_type(A.std()) # E: numpy.number[Any] -reveal_type(A.std(axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(A.std(keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] +reveal_type(f8.std()) # E: Any +reveal_type(A.std()) # E: Any +reveal_type(A.std(axis=0)) # E: Any +reveal_type(A.std(keepdims=True)) # E: Any reveal_type(A.std(out=B)) # E: SubClass -reveal_type(f8.sum()) # E: numpy.number[Any] -reveal_type(A.sum()) # E: numpy.number[Any] -reveal_type(A.sum(axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(A.sum(keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] +reveal_type(f8.sum()) # E: Any +reveal_type(A.sum()) # E: Any +reveal_type(A.sum(axis=0)) # E: Any +reveal_type(A.sum(keepdims=True)) # E: Any reveal_type(A.sum(out=B)) # E: SubClass -reveal_type(f8.take(0)) # E: numpy.generic -reveal_type(A.take(0)) # E: numpy.generic +reveal_type(f8.take(0)) # E: Any +reveal_type(A.take(0)) # E: Any reveal_type(A.take([0])) # E: numpy.ndarray[Any, Any] reveal_type(A.take(0, out=B)) # E: SubClass reveal_type(A.take([0], out=B)) # E: SubClass -reveal_type(f8.var()) # E: numpy.number[Any] -reveal_type(A.var()) # E: numpy.number[Any] -reveal_type(A.var(axis=0)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] -reveal_type(A.var(keepdims=True)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] +reveal_type(f8.var()) # E: Any +reveal_type(A.var()) # E: Any +reveal_type(A.var(axis=0)) # E: Any +reveal_type(A.var(keepdims=True)) # E: Any reveal_type(A.var(out=B)) # E: SubClass reveal_type(A.argpartition([0])) # E: numpy.ndarray[Any, Any] reveal_type(A.diagonal()) # E: numpy.ndarray[Any, Any] -reveal_type(A.dot(1)) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] +reveal_type(A.dot(1)) # E: Any reveal_type(A.dot(1, out=B)) # E: SubClass reveal_type(A.nonzero()) # E: tuple[numpy.ndarray[Any, Any]] reveal_type(A.searchsorted([1])) # E: numpy.ndarray[Any, Any] -reveal_type(A.trace()) # E: Union[numpy.number[Any], numpy.ndarray[Any, Any]] +reveal_type(A.trace()) # E: Any reveal_type(A.trace(out=B)) # E: SubClass diff --git a/numpy/typing/tests/data/reveal/numeric.py b/numpy/typing/tests/data/reveal/numeric.py index 78e5c1d61..ec6e47ca0 100644 --- a/numpy/typing/tests/data/reveal/numeric.py +++ b/numpy/typing/tests/data/reveal/numeric.py @@ -20,8 +20,8 @@ C: SubClass reveal_type(np.count_nonzero(i8)) # E: int reveal_type(np.count_nonzero(A)) # E: int reveal_type(np.count_nonzero(B)) # E: int -reveal_type(np.count_nonzero(A, keepdims=True)) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, Any]] -reveal_type(np.count_nonzero(A, axis=0)) # E: Union[numpy.signedinteger[Any], numpy.ndarray[Any, Any]] +reveal_type(np.count_nonzero(A, keepdims=True)) # E: Any +reveal_type(np.count_nonzero(A, axis=0)) # E: Any reveal_type(np.isfortran(i8)) # E: bool reveal_type(np.isfortran(A)) # E: bool @@ -76,9 +76,9 @@ reveal_type(np.allclose(i8, A)) # E: bool reveal_type(np.allclose(B, A)) # E: bool reveal_type(np.allclose(A, A)) # E: bool -reveal_type(np.isclose(i8, A)) # E: Union[numpy.bool_, numpy.ndarray[Any, Any]] -reveal_type(np.isclose(B, A)) # E: Union[numpy.bool_, numpy.ndarray[Any, Any]] -reveal_type(np.isclose(A, A)) # E: Union[numpy.bool_, numpy.ndarray[Any, Any]] +reveal_type(np.isclose(i8, A)) # E: Any +reveal_type(np.isclose(B, A)) # E: Any +reveal_type(np.isclose(A, A)) # E: Any reveal_type(np.array_equal(i8, A)) # E: bool reveal_type(np.array_equal(B, A)) # E: bool diff --git a/numpy/typing/tests/data/reveal/ufunclike.py b/numpy/typing/tests/data/reveal/ufunclike.py index 35e45a824..8b3aea7ce 100644 --- a/numpy/typing/tests/data/reveal/ufunclike.py +++ b/numpy/typing/tests/data/reveal/ufunclike.py @@ -9,21 +9,21 @@ AR_LIKE_O: List[np.object_] AR_U: np.ndarray[Any, np.dtype[np.str_]] -reveal_type(np.fix(AR_LIKE_b)) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(np.fix(AR_LIKE_u)) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(np.fix(AR_LIKE_i)) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] -reveal_type(np.fix(AR_LIKE_f)) # E: Union[numpy.floating[Any], numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]]] +reveal_type(np.fix(AR_LIKE_b)) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(np.fix(AR_LIKE_u)) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(np.fix(AR_LIKE_i)) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(np.fix(AR_LIKE_f)) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] reveal_type(np.fix(AR_LIKE_O)) # E: Any reveal_type(np.fix(AR_LIKE_f, out=AR_U)) # E: numpy.ndarray[Any, numpy.dtype[numpy.str_]] -reveal_type(np.isposinf(AR_LIKE_b)) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(np.isposinf(AR_LIKE_u)) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(np.isposinf(AR_LIKE_i)) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(np.isposinf(AR_LIKE_f)) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] +reveal_type(np.isposinf(AR_LIKE_b)) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(np.isposinf(AR_LIKE_u)) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(np.isposinf(AR_LIKE_i)) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(np.isposinf(AR_LIKE_f)) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] reveal_type(np.isposinf(AR_LIKE_f, out=AR_U)) # E: numpy.ndarray[Any, numpy.dtype[numpy.str_]] -reveal_type(np.isneginf(AR_LIKE_b)) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(np.isneginf(AR_LIKE_u)) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(np.isneginf(AR_LIKE_i)) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] -reveal_type(np.isneginf(AR_LIKE_f)) # E: Union[numpy.bool_, numpy.ndarray[Any, numpy.dtype[numpy.bool_]]] +reveal_type(np.isneginf(AR_LIKE_b)) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(np.isneginf(AR_LIKE_u)) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(np.isneginf(AR_LIKE_i)) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(np.isneginf(AR_LIKE_f)) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] reveal_type(np.isneginf(AR_LIKE_f, out=AR_U)) # E: numpy.ndarray[Any, numpy.dtype[numpy.str_]] |