diff options
| -rw-r--r-- | numpy/core/numeric.pyi | 532 | ||||
| -rw-r--r-- | numpy/typing/tests/data/fail/array_constructors.pyi | 2 | ||||
| -rw-r--r-- | numpy/typing/tests/data/reveal/array_constructors.pyi | 39 | ||||
| -rw-r--r-- | numpy/typing/tests/data/reveal/numeric.pyi | 149 | ||||
| -rw-r--r-- | numpy/typing/tests/test_typing.py | 12 |
5 files changed, 598 insertions, 136 deletions
diff --git a/numpy/core/numeric.pyi b/numpy/core/numeric.pyi index 54ab4b7c8..d7ec30351 100644 --- a/numpy/core/numeric.pyi +++ b/numpy/core/numeric.pyi @@ -1,6 +1,5 @@ from typing import ( Any, - Optional, Union, Sequence, Tuple, @@ -8,18 +7,64 @@ from typing import ( List, overload, TypeVar, - Iterable, Literal, + Type, + SupportsAbs, + SupportsIndex, + NoReturn, ) +from typing_extensions import TypeGuard -from numpy import ndarray, generic, dtype, bool_, signedinteger, _OrderKACF, _OrderCF -from numpy.typing import ArrayLike, DTypeLike, _ShapeLike +from numpy import ( + ComplexWarning as ComplexWarning, + dtype, + generic, + unsignedinteger, + signedinteger, + floating, + complexfloating, + bool_, + int_, + intp, + float64, + timedelta64, + object_, + _OrderKACF, + _OrderCF, +) + +from numpy.typing import ( + ArrayLike, + NDArray, + DTypeLike, + _ShapeLike, + _SupportsDType, + _FiniteNestedSequence, + _SupportsArray, + _ScalarLike_co, + _ArrayLikeBool_co, + _ArrayLikeUInt_co, + _ArrayLikeInt_co, + _ArrayLikeFloat_co, + _ArrayLikeComplex_co, + _ArrayLikeTD64_co, + _ArrayLikeObject_co, +) _T = TypeVar("_T") -_ArrayType = TypeVar("_ArrayType", bound=ndarray) +_SCT = TypeVar("_SCT", bound=generic) +_ArrayType = TypeVar("_ArrayType", bound=NDArray[Any]) +_DTypeLike = Union[ + dtype[_SCT], + Type[_SCT], + _SupportsDType[dtype[_SCT]], +] +_ArrayLike = _FiniteNestedSequence[_SupportsArray[dtype[_SCT]]] _CorrelateMode = Literal["valid", "same", "full"] +__all__: List[str] + @overload def zeros_like( a: _ArrayType, @@ -30,20 +75,61 @@ def zeros_like( ) -> _ArrayType: ... @overload def zeros_like( - a: ArrayLike, - dtype: DTypeLike = ..., + a: _ArrayLike[_SCT], + dtype: None = ..., order: _OrderKACF = ..., subok: bool = ..., - shape: Optional[_ShapeLike] = ..., -) -> ndarray: ... + shape: None | _ShapeLike = ..., +) -> NDArray[_SCT]: ... +@overload +def zeros_like( + a: object, + dtype: None = ..., + order: _OrderKACF = ..., + subok: bool = ..., + shape: None | _ShapeLike= ..., +) -> NDArray[Any]: ... +@overload +def zeros_like( + a: Any, + dtype: _DTypeLike[_SCT], + order: _OrderKACF = ..., + subok: bool = ..., + shape: None | _ShapeLike= ..., +) -> NDArray[_SCT]: ... +@overload +def zeros_like( + a: Any, + dtype: DTypeLike, + order: _OrderKACF = ..., + subok: bool = ..., + shape: None | _ShapeLike= ..., +) -> NDArray[Any]: ... +@overload def ones( shape: _ShapeLike, - dtype: DTypeLike = ..., + dtype: None = ..., + order: _OrderCF = ..., + *, + like: ArrayLike = ..., +) -> NDArray[float64]: ... +@overload +def ones( + shape: _ShapeLike, + dtype: _DTypeLike[_SCT], order: _OrderCF = ..., *, like: ArrayLike = ..., -) -> ndarray: ... +) -> NDArray[_SCT]: ... +@overload +def ones( + shape: _ShapeLike, + dtype: DTypeLike, + order: _OrderCF = ..., + *, + like: ArrayLike = ..., +) -> NDArray[Any]: ... @overload def ones_like( @@ -55,21 +141,64 @@ def ones_like( ) -> _ArrayType: ... @overload def ones_like( - a: ArrayLike, - dtype: DTypeLike = ..., + a: _ArrayLike[_SCT], + dtype: None = ..., order: _OrderKACF = ..., subok: bool = ..., - shape: Optional[_ShapeLike] = ..., -) -> ndarray: ... + shape: None | _ShapeLike = ..., +) -> NDArray[_SCT]: ... +@overload +def ones_like( + a: object, + dtype: None = ..., + order: _OrderKACF = ..., + subok: bool = ..., + shape: None | _ShapeLike= ..., +) -> NDArray[Any]: ... +@overload +def ones_like( + a: Any, + dtype: _DTypeLike[_SCT], + order: _OrderKACF = ..., + subok: bool = ..., + shape: None | _ShapeLike= ..., +) -> NDArray[_SCT]: ... +@overload +def ones_like( + a: Any, + dtype: DTypeLike, + order: _OrderKACF = ..., + subok: bool = ..., + shape: None | _ShapeLike= ..., +) -> NDArray[Any]: ... +@overload def full( shape: _ShapeLike, fill_value: Any, - dtype: DTypeLike = ..., + dtype: None = ..., + order: _OrderCF = ..., + *, + like: ArrayLike = ..., +) -> NDArray[Any]: ... +@overload +def full( + shape: _ShapeLike, + fill_value: Any, + dtype: _DTypeLike[_SCT], order: _OrderCF = ..., *, like: ArrayLike = ..., -) -> ndarray: ... +) -> NDArray[_SCT]: ... +@overload +def full( + shape: _ShapeLike, + fill_value: Any, + dtype: DTypeLike, + order: _OrderCF = ..., + *, + like: ArrayLike = ..., +) -> NDArray[Any]: ... @overload def full_like( @@ -82,13 +211,40 @@ def full_like( ) -> _ArrayType: ... @overload def full_like( - a: ArrayLike, + a: _ArrayLike[_SCT], fill_value: Any, - dtype: DTypeLike = ..., + dtype: None = ..., + order: _OrderKACF = ..., + subok: bool = ..., + shape: None | _ShapeLike = ..., +) -> NDArray[_SCT]: ... +@overload +def full_like( + a: object, + fill_value: Any, + dtype: None = ..., + order: _OrderKACF = ..., + subok: bool = ..., + shape: None | _ShapeLike= ..., +) -> NDArray[Any]: ... +@overload +def full_like( + a: Any, + fill_value: Any, + dtype: _DTypeLike[_SCT], + order: _OrderKACF = ..., + subok: bool = ..., + shape: None | _ShapeLike= ..., +) -> NDArray[_SCT]: ... +@overload +def full_like( + a: Any, + fill_value: Any, + dtype: DTypeLike, order: _OrderKACF = ..., subok: bool = ..., - shape: Optional[_ShapeLike] = ..., -) -> ndarray: ... + shape: None | _ShapeLike= ..., +) -> NDArray[Any]: ... @overload def count_nonzero( @@ -105,78 +261,306 @@ def count_nonzero( keepdims: bool = ..., ) -> Any: ... # TODO: np.intp or ndarray[np.intp] -def isfortran(a: Union[ndarray, generic]) -> bool: ... +def isfortran(a: NDArray[Any] | generic) -> bool: ... -def argwhere(a: ArrayLike) -> ndarray: ... +def argwhere(a: ArrayLike) -> NDArray[intp]: ... -def flatnonzero(a: ArrayLike) -> ndarray: ... +def flatnonzero(a: ArrayLike) -> NDArray[intp]: ... +@overload def correlate( - a: ArrayLike, - v: ArrayLike, + a: _ArrayLikeBool_co, + v: _ArrayLikeBool_co, + mode: _CorrelateMode = ..., +) -> NDArray[bool_]: ... +@overload +def correlate( + a: _ArrayLikeUInt_co, + v: _ArrayLikeUInt_co, + mode: _CorrelateMode = ..., +) -> NDArray[unsignedinteger[Any]]: ... +@overload +def correlate( + a: _ArrayLikeInt_co, + v: _ArrayLikeInt_co, mode: _CorrelateMode = ..., -) -> ndarray: ... +) -> NDArray[signedinteger[Any]]: ... +@overload +def correlate( + a: _ArrayLikeFloat_co, + v: _ArrayLikeFloat_co, + mode: _CorrelateMode = ..., +) -> NDArray[floating[Any]]: ... +@overload +def correlate( + a: _ArrayLikeComplex_co, + v: _ArrayLikeComplex_co, + mode: _CorrelateMode = ..., +) -> NDArray[complexfloating[Any, Any]]: ... +@overload +def correlate( + a: _ArrayLikeTD64_co, + v: _ArrayLikeTD64_co, + mode: _CorrelateMode = ..., +) -> NDArray[timedelta64]: ... +@overload +def correlate( + a: _ArrayLikeObject_co, + v: _ArrayLikeObject_co, + mode: _CorrelateMode = ..., +) -> NDArray[object_]: ... +@overload def convolve( - a: ArrayLike, - v: ArrayLike, + a: _ArrayLikeBool_co, + v: _ArrayLikeBool_co, mode: _CorrelateMode = ..., -) -> ndarray: ... +) -> NDArray[bool_]: ... +@overload +def convolve( + a: _ArrayLikeUInt_co, + v: _ArrayLikeUInt_co, + mode: _CorrelateMode = ..., +) -> NDArray[unsignedinteger[Any]]: ... +@overload +def convolve( + a: _ArrayLikeInt_co, + v: _ArrayLikeInt_co, + mode: _CorrelateMode = ..., +) -> NDArray[signedinteger[Any]]: ... +@overload +def convolve( + a: _ArrayLikeFloat_co, + v: _ArrayLikeFloat_co, + mode: _CorrelateMode = ..., +) -> NDArray[floating[Any]]: ... +@overload +def convolve( + a: _ArrayLikeComplex_co, + v: _ArrayLikeComplex_co, + mode: _CorrelateMode = ..., +) -> NDArray[complexfloating[Any, Any]]: ... +@overload +def convolve( + a: _ArrayLikeTD64_co, + v: _ArrayLikeTD64_co, + mode: _CorrelateMode = ..., +) -> NDArray[timedelta64]: ... +@overload +def convolve( + a: _ArrayLikeObject_co, + v: _ArrayLikeObject_co, + mode: _CorrelateMode = ..., +) -> NDArray[object_]: ... @overload def outer( - a: ArrayLike, - b: ArrayLike, + a: _ArrayLikeBool_co, + b: _ArrayLikeBool_co, out: None = ..., -) -> ndarray: ... +) -> NDArray[bool_]: ... @overload def outer( - a: ArrayLike, - b: ArrayLike, - out: _ArrayType = ..., + a: _ArrayLikeUInt_co, + b: _ArrayLikeUInt_co, + out: None = ..., +) -> NDArray[unsignedinteger[Any]]: ... +@overload +def outer( + a: _ArrayLikeInt_co, + b: _ArrayLikeInt_co, + out: None = ..., +) -> NDArray[signedinteger[Any]]: ... +@overload +def outer( + a: _ArrayLikeFloat_co, + b: _ArrayLikeFloat_co, + out: None = ..., +) -> NDArray[floating[Any]]: ... +@overload +def outer( + a: _ArrayLikeComplex_co, + b: _ArrayLikeComplex_co, + out: None = ..., +) -> NDArray[complexfloating[Any, Any]]: ... +@overload +def outer( + a: _ArrayLikeTD64_co, + b: _ArrayLikeTD64_co, + out: None = ..., +) -> NDArray[timedelta64]: ... +@overload +def outer( + a: _ArrayLikeObject_co, + b: _ArrayLikeObject_co, + out: None = ..., +) -> NDArray[object_]: ... +@overload +def outer( + a: _ArrayLikeComplex_co | _ArrayLikeTD64_co | _ArrayLikeObject_co, + b: _ArrayLikeComplex_co | _ArrayLikeTD64_co | _ArrayLikeObject_co, + out: _ArrayType, ) -> _ArrayType: ... +@overload def tensordot( - a: ArrayLike, - b: ArrayLike, - axes: Union[int, Tuple[_ShapeLike, _ShapeLike]] = ..., -) -> ndarray: ... + a: _ArrayLikeBool_co, + b: _ArrayLikeBool_co, + axes: int | Tuple[_ShapeLike, _ShapeLike] = ..., +) -> NDArray[bool_]: ... +@overload +def tensordot( + a: _ArrayLikeUInt_co, + b: _ArrayLikeUInt_co, + axes: int | Tuple[_ShapeLike, _ShapeLike] = ..., +) -> NDArray[unsignedinteger[Any]]: ... +@overload +def tensordot( + a: _ArrayLikeInt_co, + b: _ArrayLikeInt_co, + axes: int | Tuple[_ShapeLike, _ShapeLike] = ..., +) -> NDArray[signedinteger[Any]]: ... +@overload +def tensordot( + a: _ArrayLikeFloat_co, + b: _ArrayLikeFloat_co, + axes: int | Tuple[_ShapeLike, _ShapeLike] = ..., +) -> NDArray[floating[Any]]: ... +@overload +def tensordot( + a: _ArrayLikeComplex_co, + b: _ArrayLikeComplex_co, + axes: int | Tuple[_ShapeLike, _ShapeLike] = ..., +) -> NDArray[complexfloating[Any, Any]]: ... +@overload +def tensordot( + a: _ArrayLikeTD64_co, + b: _ArrayLikeTD64_co, + axes: int | Tuple[_ShapeLike, _ShapeLike] = ..., +) -> NDArray[timedelta64]: ... +@overload +def tensordot( + a: _ArrayLikeObject_co, + b: _ArrayLikeObject_co, + axes: int | Tuple[_ShapeLike, _ShapeLike] = ..., +) -> NDArray[object_]: ... +@overload +def roll( + a: _ArrayLike[_SCT], + shift: _ShapeLike, + axis: None | _ShapeLike = ..., +) -> NDArray[_SCT]: ... +@overload def roll( a: ArrayLike, shift: _ShapeLike, - axis: Optional[_ShapeLike] = ..., -) -> ndarray: ... + axis: None | _ShapeLike = ..., +) -> NDArray[Any]: ... -def rollaxis(a: ndarray, axis: int, start: int = ...) -> ndarray: ... +def rollaxis( + a: NDArray[_SCT], + axis: int, + start: int = ..., +) -> NDArray[_SCT]: ... def moveaxis( - a: ndarray, + a: NDArray[_SCT], source: _ShapeLike, destination: _ShapeLike, -) -> ndarray: ... +) -> NDArray[_SCT]: ... +@overload def cross( - a: ArrayLike, - b: ArrayLike, + a: _ArrayLikeBool_co, + b: _ArrayLikeBool_co, axisa: int = ..., axisb: int = ..., axisc: int = ..., - axis: Optional[int] = ..., -) -> ndarray: ... + axis: None | int = ..., +) -> NoReturn: ... +@overload +def cross( + a: _ArrayLikeUInt_co, + b: _ArrayLikeUInt_co, + axisa: int = ..., + axisb: int = ..., + axisc: int = ..., + axis: None | int = ..., +) -> NDArray[unsignedinteger[Any]]: ... +@overload +def cross( + a: _ArrayLikeInt_co, + b: _ArrayLikeInt_co, + axisa: int = ..., + axisb: int = ..., + axisc: int = ..., + axis: None | int = ..., +) -> NDArray[signedinteger[Any]]: ... +@overload +def cross( + a: _ArrayLikeFloat_co, + b: _ArrayLikeFloat_co, + axisa: int = ..., + axisb: int = ..., + axisc: int = ..., + axis: None | int = ..., +) -> NDArray[floating[Any]]: ... +@overload +def cross( + a: _ArrayLikeComplex_co, + b: _ArrayLikeComplex_co, + axisa: int = ..., + axisb: int = ..., + axisc: int = ..., + axis: None | int = ..., +) -> NDArray[complexfloating[Any, Any]]: ... +@overload +def cross( + a: _ArrayLikeObject_co, + b: _ArrayLikeObject_co, + axisa: int = ..., + axisb: int = ..., + axisc: int = ..., + axis: None | int = ..., +) -> NDArray[object_]: ... @overload def indices( dimensions: Sequence[int], - dtype: DTypeLike = ..., + dtype: Type[int] = ..., sparse: Literal[False] = ..., -) -> ndarray: ... +) -> NDArray[int_]: ... @overload def indices( dimensions: Sequence[int], - dtype: DTypeLike = ..., + dtype: Type[int] = ..., sparse: Literal[True] = ..., -) -> Tuple[ndarray, ...]: ... +) -> Tuple[NDArray[int_], ...]: ... +@overload +def indices( + dimensions: Sequence[int], + dtype: _DTypeLike[_SCT], + sparse: Literal[False] = ..., +) -> NDArray[_SCT]: ... +@overload +def indices( + dimensions: Sequence[int], + dtype: _DTypeLike[_SCT], + sparse: Literal[True], +) -> Tuple[NDArray[_SCT], ...]: ... +@overload +def indices( + dimensions: Sequence[int], + dtype: DTypeLike, + sparse: Literal[False] = ..., +) -> NDArray[Any]: ... +@overload +def indices( + dimensions: Sequence[int], + dtype: DTypeLike, + sparse: Literal[True], +) -> Tuple[NDArray[Any], ...]: ... def fromfunction( function: Callable[..., _T], @@ -187,18 +571,39 @@ def fromfunction( **kwargs: Any, ) -> _T: ... -def isscalar(element: Any) -> bool: ... +def isscalar(element: object) -> TypeGuard[ + generic | bool | int | float | complex | str | bytes | memoryview +]: ... -def binary_repr(num: int, width: Optional[int] = ...) -> str: ... +def binary_repr(num: int, width: None | int = ...) -> str: ... -def base_repr(number: int, base: int = ..., padding: int = ...) -> str: ... +def base_repr( + number: SupportsAbs[float], + base: float = ..., + padding: SupportsIndex = ..., +) -> str: ... +@overload def identity( n: int, - dtype: DTypeLike = ..., + dtype: None = ..., + *, + like: ArrayLike = ..., +) -> NDArray[float64]: ... +@overload +def identity( + n: int, + dtype: _DTypeLike[_SCT], + *, + like: ArrayLike = ..., +) -> NDArray[_SCT]: ... +@overload +def identity( + n: int, + dtype: DTypeLike, *, like: ArrayLike = ..., -) -> ndarray: ... +) -> NDArray[Any]: ... def allclose( a: ArrayLike, @@ -208,13 +613,22 @@ def allclose( equal_nan: bool = ..., ) -> bool: ... +@overload +def isclose( + a: _ScalarLike_co, + b: _ScalarLike_co, + rtol: float = ..., + atol: float = ..., + equal_nan: bool = ..., +) -> bool_: ... +@overload def isclose( a: ArrayLike, b: ArrayLike, rtol: float = ..., atol: float = ..., equal_nan: bool = ..., -) -> Any: ... +) -> NDArray[bool_]: ... def array_equal(a1: ArrayLike, a2: ArrayLike, equal_nan: bool = ...) -> bool: ... diff --git a/numpy/typing/tests/data/fail/array_constructors.pyi b/numpy/typing/tests/data/fail/array_constructors.pyi index 0e2250513..4f0a60b5b 100644 --- a/numpy/typing/tests/data/fail/array_constructors.pyi +++ b/numpy/typing/tests/data/fail/array_constructors.pyi @@ -10,7 +10,7 @@ np.zeros("test") # E: incompatible type np.zeros() # E: require at least one argument np.ones("test") # E: incompatible type -np.ones() # E: Missing positional argument +np.ones() # E: require at least one argument np.array(0, float, True) # E: No overload variant diff --git a/numpy/typing/tests/data/reveal/array_constructors.pyi b/numpy/typing/tests/data/reveal/array_constructors.pyi index 44c85e988..0aea4ea96 100644 --- a/numpy/typing/tests/data/reveal/array_constructors.pyi +++ b/numpy/typing/tests/data/reveal/array_constructors.pyi @@ -120,32 +120,41 @@ reveal_type(np.logspace(0, 10)) # E: numpy.ndarray[Any, Any] reveal_type(np.geomspace(1, 10)) # E: numpy.ndarray[Any, Any] reveal_type(np.zeros_like(A)) # E: numpy.ndarray[Any, numpy.dtype[{float64}]] -reveal_type(np.zeros_like(C)) # E: numpy.ndarray[Any, Any] -reveal_type(np.zeros_like(B)) # E: SubClass -reveal_type(np.zeros_like(B, dtype=np.int64)) # E: numpy.ndarray[Any, Any] +reveal_type(np.zeros_like(C)) # E: numpy.ndarray[Any, numpy.dtype[Any]] +reveal_type(np.zeros_like(A, dtype=float)) # E: numpy.ndarray[Any, numpy.dtype[Any]] +reveal_type(np.zeros_like(B)) # E: SubClass[{float64}] +reveal_type(np.zeros_like(B, dtype=np.int64)) # E: numpy.ndarray[Any, numpy.dtype[{int64}]] reveal_type(np.ones_like(A)) # E: numpy.ndarray[Any, numpy.dtype[{float64}]] -reveal_type(np.ones_like(C)) # E: numpy.ndarray[Any, Any] -reveal_type(np.ones_like(B)) # E: SubClass -reveal_type(np.ones_like(B, dtype=np.int64)) # E: numpy.ndarray[Any, Any] +reveal_type(np.ones_like(C)) # E: numpy.ndarray[Any, numpy.dtype[Any]] +reveal_type(np.ones_like(A, dtype=float)) # E: numpy.ndarray[Any, numpy.dtype[Any]] +reveal_type(np.ones_like(B)) # E: SubClass[{float64}] +reveal_type(np.ones_like(B, dtype=np.int64)) # E: numpy.ndarray[Any, numpy.dtype[{int64}]] reveal_type(np.full_like(A, i8)) # E: numpy.ndarray[Any, numpy.dtype[{float64}]] -reveal_type(np.full_like(C, i8)) # E: numpy.ndarray[Any, Any] +reveal_type(np.full_like(C, i8)) # E: numpy.ndarray[Any, numpy.dtype[Any]] +reveal_type(np.full_like(A, i8, dtype=int)) # E: numpy.ndarray[Any, numpy.dtype[Any]] reveal_type(np.full_like(B, i8)) # E: SubClass[{float64}] -reveal_type(np.full_like(B, i8, dtype=np.int64)) # E: numpy.ndarray[Any, Any] +reveal_type(np.full_like(B, i8, dtype=np.int64)) # E: numpy.ndarray[Any, numpy.dtype[{int64}]] -reveal_type(np.ones(1)) # E: numpy.ndarray[Any, Any] -reveal_type(np.ones([1, 1, 1])) # E: numpy.ndarray[Any, Any] +reveal_type(np.ones(1)) # E: numpy.ndarray[Any, numpy.dtype[{float64}]] +reveal_type(np.ones([1, 1, 1])) # E: numpy.ndarray[Any, numpy.dtype[{float64}]] +reveal_type(np.ones(5, dtype=np.int64)) # E: numpy.ndarray[Any, numpy.dtype[{int64}]] +reveal_type(np.ones(5, dtype=int)) # E: numpy.ndarray[Any, numpy.dtype[Any]] -reveal_type(np.full(1, i8)) # E: numpy.ndarray[Any, Any] -reveal_type(np.full([1, 1, 1], i8)) # E: numpy.ndarray[Any, Any] +reveal_type(np.full(1, i8)) # E: numpy.ndarray[Any, numpy.dtype[Any]] +reveal_type(np.full([1, 1, 1], i8)) # E: numpy.ndarray[Any, numpy.dtype[Any]] +reveal_type(np.full(1, i8, dtype=np.float64)) # E: numpy.ndarray[Any, numpy.dtype[{float64}]] +reveal_type(np.full(1, i8, dtype=float)) # E: numpy.ndarray[Any, numpy.dtype[Any]] -reveal_type(np.indices([1, 2, 3])) # E: numpy.ndarray[Any, Any] -reveal_type(np.indices([1, 2, 3], sparse=True)) # E: tuple[numpy.ndarray[Any, Any]] +reveal_type(np.indices([1, 2, 3])) # E: numpy.ndarray[Any, numpy.dtype[{int_}]] +reveal_type(np.indices([1, 2, 3], sparse=True)) # E: tuple[numpy.ndarray[Any, numpy.dtype[{int_}]]] reveal_type(np.fromfunction(func, (3, 5))) # E: SubClass[{float64}] -reveal_type(np.identity(10)) # E: numpy.ndarray[Any, Any] +reveal_type(np.identity(10)) # E: numpy.ndarray[Any, numpy.dtype[{float64}]] +reveal_type(np.identity(10, dtype=np.int64)) # E: numpy.ndarray[Any, numpy.dtype[{int64}]] +reveal_type(np.identity(10, dtype=int)) # E: numpy.ndarray[Any, numpy.dtype[Any]] reveal_type(np.atleast_1d(A)) # E: numpy.ndarray[Any, numpy.dtype[{float64}]] reveal_type(np.atleast_1d(C)) # E: numpy.ndarray[Any, numpy.dtype[Any]] diff --git a/numpy/typing/tests/data/reveal/numeric.pyi b/numpy/typing/tests/data/reveal/numeric.pyi index ec6e47ca0..9b3b1419d 100644 --- a/numpy/typing/tests/data/reveal/numeric.pyi +++ b/numpy/typing/tests/data/reveal/numeric.pyi @@ -7,83 +7,128 @@ Does not include tests which fall under ``array_constructors``. from typing import List import numpy as np +import numpy.typing as npt -class SubClass(np.ndarray): +class SubClass(npt.NDArray[np.int64]): ... i8: np.int64 -A: np.ndarray +AR_b: npt.NDArray[np.bool_] +AR_u8: npt.NDArray[np.uint64] +AR_i8: npt.NDArray[np.int64] +AR_f8: npt.NDArray[np.float64] +AR_c16: npt.NDArray[np.complex128] +AR_m: npt.NDArray[np.timedelta64] +AR_O: npt.NDArray[np.object_] + B: List[int] C: SubClass reveal_type(np.count_nonzero(i8)) # E: int -reveal_type(np.count_nonzero(A)) # E: int +reveal_type(np.count_nonzero(AR_i8)) # E: int reveal_type(np.count_nonzero(B)) # E: int -reveal_type(np.count_nonzero(A, keepdims=True)) # E: Any -reveal_type(np.count_nonzero(A, axis=0)) # E: Any +reveal_type(np.count_nonzero(AR_i8, keepdims=True)) # E: Any +reveal_type(np.count_nonzero(AR_i8, axis=0)) # E: Any reveal_type(np.isfortran(i8)) # E: bool -reveal_type(np.isfortran(A)) # E: bool - -reveal_type(np.argwhere(i8)) # E: numpy.ndarray[Any, Any] -reveal_type(np.argwhere(A)) # E: numpy.ndarray[Any, Any] - -reveal_type(np.flatnonzero(i8)) # E: numpy.ndarray[Any, Any] -reveal_type(np.flatnonzero(A)) # E: numpy.ndarray[Any, Any] - -reveal_type(np.correlate(B, A, mode="valid")) # E: numpy.ndarray[Any, Any] -reveal_type(np.correlate(A, A, mode="same")) # E: numpy.ndarray[Any, Any] - -reveal_type(np.convolve(B, A, mode="valid")) # E: numpy.ndarray[Any, Any] -reveal_type(np.convolve(A, A, mode="same")) # E: numpy.ndarray[Any, Any] - -reveal_type(np.outer(i8, A)) # E: numpy.ndarray[Any, Any] -reveal_type(np.outer(B, A)) # E: numpy.ndarray[Any, Any] -reveal_type(np.outer(A, A)) # E: numpy.ndarray[Any, Any] -reveal_type(np.outer(A, A, out=C)) # E: SubClass - -reveal_type(np.tensordot(B, A)) # E: numpy.ndarray[Any, Any] -reveal_type(np.tensordot(A, A)) # E: numpy.ndarray[Any, Any] -reveal_type(np.tensordot(A, A, axes=0)) # E: numpy.ndarray[Any, Any] -reveal_type(np.tensordot(A, A, axes=(0, 1))) # E: numpy.ndarray[Any, Any] +reveal_type(np.isfortran(AR_i8)) # E: bool + +reveal_type(np.argwhere(i8)) # E: numpy.ndarray[Any, numpy.dtype[{intp}]] +reveal_type(np.argwhere(AR_i8)) # E: numpy.ndarray[Any, numpy.dtype[{intp}]] + +reveal_type(np.flatnonzero(i8)) # E: numpy.ndarray[Any, numpy.dtype[{intp}]] +reveal_type(np.flatnonzero(AR_i8)) # E: numpy.ndarray[Any, numpy.dtype[{intp}]] + +reveal_type(np.correlate(B, AR_i8, mode="valid")) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(np.correlate(AR_i8, AR_i8, mode="same")) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(np.correlate(AR_b, AR_b)) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(np.correlate(AR_b, AR_u8)) # E: numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]] +reveal_type(np.correlate(AR_i8, AR_b)) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(np.correlate(AR_i8, AR_f8)) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(np.correlate(AR_i8, AR_c16)) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(np.correlate(AR_i8, AR_m)) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] +reveal_type(np.correlate(AR_O, AR_O)) # E: numpy.ndarray[Any, numpy.dtype[numpy.object_]] + +reveal_type(np.convolve(B, AR_i8, mode="valid")) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(np.convolve(AR_i8, AR_i8, mode="same")) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(np.convolve(AR_b, AR_b)) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(np.convolve(AR_b, AR_u8)) # E: numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]] +reveal_type(np.convolve(AR_i8, AR_b)) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(np.convolve(AR_i8, AR_f8)) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(np.convolve(AR_i8, AR_c16)) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(np.convolve(AR_i8, AR_m)) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] +reveal_type(np.convolve(AR_O, AR_O)) # E: numpy.ndarray[Any, numpy.dtype[numpy.object_]] + +reveal_type(np.outer(i8, AR_i8)) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(np.outer(B, AR_i8)) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(np.outer(AR_i8, AR_i8)) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(np.outer(AR_i8, AR_i8, out=C)) # E: SubClass +reveal_type(np.outer(AR_b, AR_b)) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(np.outer(AR_b, AR_u8)) # E: numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]] +reveal_type(np.outer(AR_i8, AR_b)) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(np.convolve(AR_i8, AR_f8)) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(np.outer(AR_i8, AR_c16)) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(np.outer(AR_i8, AR_m)) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] +reveal_type(np.outer(AR_O, AR_O)) # E: numpy.ndarray[Any, numpy.dtype[numpy.object_]] + +reveal_type(np.tensordot(B, AR_i8)) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(np.tensordot(AR_i8, AR_i8)) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(np.tensordot(AR_i8, AR_i8, axes=0)) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(np.tensordot(AR_i8, AR_i8, axes=(0, 1))) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(np.tensordot(AR_b, AR_b)) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(np.tensordot(AR_b, AR_u8)) # E: numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]] +reveal_type(np.tensordot(AR_i8, AR_b)) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(np.tensordot(AR_i8, AR_f8)) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(np.tensordot(AR_i8, AR_c16)) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(np.tensordot(AR_i8, AR_m)) # E: numpy.ndarray[Any, numpy.dtype[numpy.timedelta64]] +reveal_type(np.tensordot(AR_O, AR_O)) # E: numpy.ndarray[Any, numpy.dtype[numpy.object_]] reveal_type(np.isscalar(i8)) # E: bool -reveal_type(np.isscalar(A)) # E: bool +reveal_type(np.isscalar(AR_i8)) # E: bool reveal_type(np.isscalar(B)) # E: bool -reveal_type(np.roll(A, 1)) # E: numpy.ndarray[Any, Any] -reveal_type(np.roll(A, (1, 2))) # E: numpy.ndarray[Any, Any] -reveal_type(np.roll(B, 1)) # E: numpy.ndarray[Any, Any] +reveal_type(np.roll(AR_i8, 1)) # E: numpy.ndarray[Any, numpy.dtype[{int64}]] +reveal_type(np.roll(AR_i8, (1, 2))) # E: numpy.ndarray[Any, numpy.dtype[{int64}]] +reveal_type(np.roll(B, 1)) # E: numpy.ndarray[Any, numpy.dtype[Any]] -reveal_type(np.rollaxis(A, 0, 1)) # E: numpy.ndarray[Any, Any] +reveal_type(np.rollaxis(AR_i8, 0, 1)) # E: numpy.ndarray[Any, numpy.dtype[{int64}]] -reveal_type(np.moveaxis(A, 0, 1)) # E: numpy.ndarray[Any, Any] -reveal_type(np.moveaxis(A, (0, 1), (1, 2))) # E: numpy.ndarray[Any, Any] +reveal_type(np.moveaxis(AR_i8, 0, 1)) # E: numpy.ndarray[Any, numpy.dtype[{int64}]] +reveal_type(np.moveaxis(AR_i8, (0, 1), (1, 2))) # E: numpy.ndarray[Any, numpy.dtype[{int64}]] -reveal_type(np.cross(B, A)) # E: numpy.ndarray[Any, Any] -reveal_type(np.cross(A, A)) # E: numpy.ndarray[Any, Any] +reveal_type(np.cross(B, AR_i8)) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(np.cross(AR_i8, AR_i8)) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(np.cross(AR_b, AR_u8)) # E: numpy.ndarray[Any, numpy.dtype[numpy.unsignedinteger[Any]]] +reveal_type(np.cross(AR_i8, AR_b)) # E: numpy.ndarray[Any, numpy.dtype[numpy.signedinteger[Any]]] +reveal_type(np.cross(AR_i8, AR_f8)) # E: numpy.ndarray[Any, numpy.dtype[numpy.floating[Any]]] +reveal_type(np.cross(AR_i8, AR_c16)) # E: numpy.ndarray[Any, numpy.dtype[numpy.complexfloating[Any, Any]]] +reveal_type(np.cross(AR_O, AR_O)) # E: numpy.ndarray[Any, numpy.dtype[numpy.object_]] -reveal_type(np.indices([0, 1, 2])) # E: numpy.ndarray[Any, Any] -reveal_type(np.indices([0, 1, 2], sparse=False)) # E: numpy.ndarray[Any, Any] -reveal_type(np.indices([0, 1, 2], sparse=True)) # E: tuple[numpy.ndarray[Any, Any]] +reveal_type(np.indices([0, 1, 2])) # E: numpy.ndarray[Any, numpy.dtype[{int_}]] +reveal_type(np.indices([0, 1, 2], sparse=True)) # E: tuple[numpy.ndarray[Any, numpy.dtype[{int_}]]] +reveal_type(np.indices([0, 1, 2], dtype=np.float64)) # E: numpy.ndarray[Any, numpy.dtype[{float64}]] +reveal_type(np.indices([0, 1, 2], sparse=True, dtype=np.float64)) # E: tuple[numpy.ndarray[Any, numpy.dtype[{float64}]]] +reveal_type(np.indices([0, 1, 2], dtype=float)) # E: numpy.ndarray[Any, numpy.dtype[Any]] +reveal_type(np.indices([0, 1, 2], sparse=True, dtype=float)) # E: tuple[numpy.ndarray[Any, numpy.dtype[Any]]] reveal_type(np.binary_repr(1)) # E: str reveal_type(np.base_repr(1)) # E: str -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.allclose(i8, AR_i8)) # E: bool +reveal_type(np.allclose(B, AR_i8)) # E: bool +reveal_type(np.allclose(AR_i8, AR_i8)) # E: bool -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.isclose(i8, i8)) # E: numpy.bool_ +reveal_type(np.isclose(i8, AR_i8)) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(np.isclose(B, AR_i8)) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] +reveal_type(np.isclose(AR_i8, AR_i8)) # E: numpy.ndarray[Any, numpy.dtype[numpy.bool_]] -reveal_type(np.array_equal(i8, A)) # E: bool -reveal_type(np.array_equal(B, A)) # E: bool -reveal_type(np.array_equal(A, A)) # E: bool +reveal_type(np.array_equal(i8, AR_i8)) # E: bool +reveal_type(np.array_equal(B, AR_i8)) # E: bool +reveal_type(np.array_equal(AR_i8, AR_i8)) # E: bool -reveal_type(np.array_equiv(i8, A)) # E: bool -reveal_type(np.array_equiv(B, A)) # E: bool -reveal_type(np.array_equiv(A, A)) # E: bool +reveal_type(np.array_equiv(i8, AR_i8)) # E: bool +reveal_type(np.array_equiv(B, AR_i8)) # E: bool +reveal_type(np.array_equiv(AR_i8, AR_i8)) # E: bool diff --git a/numpy/typing/tests/test_typing.py b/numpy/typing/tests/test_typing.py index f303ebea3..4dd6530ff 100644 --- a/numpy/typing/tests/test_typing.py +++ b/numpy/typing/tests/test_typing.py @@ -98,16 +98,10 @@ def run_mypy() -> None: def get_test_cases(directory: str) -> Iterator[ParameterSet]: for root, _, files in os.walk(directory): for fname in files: - if os.path.splitext(fname)[-1] in (".pyi", ".py"): + short_fname, ext = os.path.splitext(fname) + if ext in (".pyi", ".py"): fullpath = os.path.join(root, fname) - # Use relative path for nice py.test name - relpath = os.path.relpath(fullpath, start=directory) - - yield pytest.param( - fullpath, - # Manually specify a name for the test - id=relpath, - ) + yield pytest.param(fullpath, id=short_fname) @pytest.mark.slow |