diff options
| -rw-r--r-- | .gitignore | 3 | ||||
| -rw-r--r-- | numpy/core/fromnumeric.pyi | 297 | ||||
| -rw-r--r-- | numpy/typing/tests/data/fail/fromnumeric.pyi | 49 | ||||
| -rw-r--r-- | numpy/typing/tests/data/reveal/fromnumeric.pyi | 495 |
4 files changed, 557 insertions, 287 deletions
diff --git a/.gitignore b/.gitignore index 94a2f1753..71629b9f7 100644 --- a/.gitignore +++ b/.gitignore @@ -144,6 +144,7 @@ numpy/core/src/multiarray/lowlevel_strided_loops.c numpy/core/src/multiarray/multiarray_tests.c numpy/core/src/multiarray/nditer_templ.c numpy/core/src/multiarray/scalartypes.c +numpy/core/src/multiarray/textreading/tokenize.c numpy/core/src/npymath/ieee754.c numpy/core/src/npymath/npy_math_complex.c numpy/core/src/npymath/npy_math_internal.h @@ -222,3 +223,5 @@ numpy/core/src/umath/loops_minmax.dispatch.c numpy/core/src/umath/loops_trigonometric.dispatch.c numpy/core/src/umath/loops_exponent_log.dispatch.c numpy/core/src/umath/loops_umath_fp.dispatch.c +# npysort module +numpy/core/src/npysort/x86-qsort.dispatch.c diff --git a/numpy/core/fromnumeric.pyi b/numpy/core/fromnumeric.pyi index 9cb6847d6..9f52ae18d 100644 --- a/numpy/core/fromnumeric.pyi +++ b/numpy/core/fromnumeric.pyi @@ -17,6 +17,7 @@ from numpy import ( ) from numpy.typing import ( DTypeLike, + _DTypeLike, ArrayLike, _ArrayLike, NDArray, @@ -34,13 +35,46 @@ _ArrayType = TypeVar("_ArrayType", bound=NDArray[Any]) __all__: list[str] +@overload +def take( + a: _ArrayLike[_SCT], + indices: _IntLike_co, + axis: None = ..., + out: None = ..., + mode: _ModeKind = ..., +) -> _SCT: ... +@overload def take( a: ArrayLike, - indices: _ArrayLikeInt_co, + indices: _IntLike_co, axis: None | int = ..., - out: None | ndarray = ..., + out: None = ..., mode: _ModeKind = ..., ) -> Any: ... +@overload +def take( + a: _ArrayLike[_SCT], + indices: _ArrayLikeInt_co, + axis: None | int = ..., + out: None = ..., + mode: _ModeKind = ..., +) -> NDArray[_SCT]: ... +@overload +def take( + a: ArrayLike, + indices: _ArrayLikeInt_co, + axis: None | int = ..., + out: None = ..., + mode: _ModeKind = ..., +) -> NDArray[Any]: ... +@overload +def take( + a: ArrayLike, + indices: _ArrayLikeInt_co, + axis: None | int = ..., + out: _ArrayType = ..., + mode: _ModeKind = ..., +) -> _ArrayType: ... @overload def reshape( @@ -179,7 +213,7 @@ def argsort( def argmax( a: ArrayLike, axis: None = ..., - out: None | ndarray = ..., + out: None = ..., *, keepdims: Literal[False] = ..., ) -> intp: ... @@ -187,16 +221,24 @@ def argmax( def argmax( a: ArrayLike, axis: None | int = ..., - out: None | ndarray = ..., + out: None = ..., *, keepdims: bool = ..., ) -> Any: ... +@overload +def argmax( + a: ArrayLike, + axis: None | int = ..., + out: _ArrayType = ..., + *, + keepdims: bool = ..., +) -> _ArrayType: ... @overload def argmin( a: ArrayLike, axis: None = ..., - out: None | ndarray = ..., + out: None = ..., *, keepdims: Literal[False] = ..., ) -> intp: ... @@ -204,10 +246,18 @@ def argmin( def argmin( a: ArrayLike, axis: None | int = ..., - out: None | ndarray = ..., + out: None = ..., *, keepdims: bool = ..., ) -> Any: ... +@overload +def argmin( + a: ArrayLike, + axis: None | int = ..., + out: _ArrayType = ..., + *, + keepdims: bool = ..., +) -> _ArrayType: ... @overload def searchsorted( @@ -266,14 +316,24 @@ def diagonal( axis2: int = ..., # >= 2D array ) -> NDArray[Any]: ... +@overload def trace( a: ArrayLike, # >= 2D array offset: int = ..., axis1: int = ..., axis2: int = ..., dtype: DTypeLike = ..., - out: None | ndarray = ..., + out: None = ..., ) -> Any: ... +@overload +def trace( + a: ArrayLike, # >= 2D array + offset: int = ..., + axis1: int = ..., + axis2: int = ..., + dtype: DTypeLike = ..., + out: _ArrayType = ..., +) -> _ArrayType: ... @overload def ravel(a: _ArrayLike[_SCT], order: _OrderKACF = ...) -> NDArray[_SCT]: ... @@ -308,30 +368,119 @@ def compress( @overload def clip( - a: ArrayLike, - a_min: ArrayLike, + a: _SCT, + a_min: None | ArrayLike, a_max: None | ArrayLike, - out: None | ndarray = ..., - **kwargs: Any, + out: None = ..., + *, + dtype: None = ..., + where: None | _ArrayLikeBool_co = ..., + order: _OrderKACF = ..., + subok: bool = ..., + signature: str | tuple[None | str, ...] = ..., + extobj: list[Any] = ..., +) -> _SCT: ... +@overload +def clip( + a: _ScalarLike_co, + a_min: None | ArrayLike, + a_max: None | ArrayLike, + out: None = ..., + *, + dtype: None = ..., + where: None | _ArrayLikeBool_co = ..., + order: _OrderKACF = ..., + subok: bool = ..., + signature: str | tuple[None | str, ...] = ..., + extobj: list[Any] = ..., ) -> Any: ... @overload def clip( + a: _ArrayLike[_SCT], + a_min: None | ArrayLike, + a_max: None | ArrayLike, + out: None = ..., + *, + dtype: None = ..., + where: None | _ArrayLikeBool_co = ..., + order: _OrderKACF = ..., + subok: bool = ..., + signature: str | tuple[None | str, ...] = ..., + extobj: list[Any] = ..., +) -> NDArray[_SCT]: ... +@overload +def clip( a: ArrayLike, - a_min: None, - a_max: ArrayLike, - out: None | ndarray = ..., - **kwargs: Any, + a_min: None | ArrayLike, + a_max: None | ArrayLike, + out: None = ..., + *, + dtype: None = ..., + where: None | _ArrayLikeBool_co = ..., + order: _OrderKACF = ..., + subok: bool = ..., + signature: str | tuple[None | str, ...] = ..., + extobj: list[Any] = ..., +) -> NDArray[Any]: ... +@overload +def clip( + a: ArrayLike, + a_min: None | ArrayLike, + a_max: None | ArrayLike, + out: _ArrayType = ..., + *, + dtype: DTypeLike, + where: None | _ArrayLikeBool_co = ..., + order: _OrderKACF = ..., + subok: bool = ..., + signature: str | tuple[None | str, ...] = ..., + extobj: list[Any] = ..., ) -> Any: ... +@overload +def clip( + a: ArrayLike, + a_min: None | ArrayLike, + a_max: None | ArrayLike, + out: _ArrayType, + *, + dtype: DTypeLike = ..., + where: None | _ArrayLikeBool_co = ..., + order: _OrderKACF = ..., + subok: bool = ..., + signature: str | tuple[None | str, ...] = ..., + extobj: list[Any] = ..., +) -> _ArrayType: ... +@overload +def sum( + a: _ArrayLike[_SCT], + axis: None = ..., + dtype: None = ..., + out: None = ..., + keepdims: bool = ..., + initial: _NumberLike_co = ..., + where: _ArrayLikeBool_co = ..., +) -> _SCT: ... +@overload def sum( a: ArrayLike, - axis: _ShapeLike = ..., + axis: None | _ShapeLike = ..., dtype: DTypeLike = ..., - out: None | ndarray = ..., + out: None = ..., keepdims: bool = ..., initial: _NumberLike_co = ..., where: _ArrayLikeBool_co = ..., ) -> Any: ... +@overload +def sum( + a: ArrayLike, + axis: None | _ShapeLike = ..., + dtype: DTypeLike = ..., + out: _ArrayType = ..., + keepdims: bool = ..., + initial: _NumberLike_co = ..., + where: _ArrayLikeBool_co = ..., +) -> _ArrayType: ... @overload def all( @@ -346,11 +495,20 @@ def all( def all( a: ArrayLike, axis: None | _ShapeLike = ..., - out: None | ndarray = ..., + out: None = ..., keepdims: bool = ..., *, where: _ArrayLikeBool_co = ..., ) -> Any: ... +@overload +def all( + a: ArrayLike, + axis: None | _ShapeLike = ..., + out: _ArrayType = ..., + keepdims: bool = ..., + *, + where: _ArrayLikeBool_co = ..., +) -> _ArrayType: ... @overload def any( @@ -365,43 +523,134 @@ def any( def any( a: ArrayLike, axis: None | _ShapeLike = ..., - out: None | ndarray = ..., + out: None = ..., keepdims: bool = ..., *, where: _ArrayLikeBool_co = ..., ) -> Any: ... +@overload +def any( + a: ArrayLike, + axis: None | _ShapeLike = ..., + out: _ArrayType = ..., + keepdims: bool = ..., + *, + where: _ArrayLikeBool_co = ..., +) -> _ArrayType: ... +@overload +def cumsum( + a: _ArrayLike[_SCT], + axis: None | int = ..., + dtype: None = ..., + out: None = ..., +) -> NDArray[_SCT]: ... +@overload +def cumsum( + a: ArrayLike, + axis: None | int = ..., + dtype: None = ..., + out: None = ..., +) -> NDArray[Any]: ... +@overload +def cumsum( + a: ArrayLike, + axis: None | int = ..., + dtype: _DTypeLike[_SCT] = ..., + out: None = ..., +) -> NDArray[_SCT]: ... +@overload def cumsum( a: ArrayLike, axis: None | int = ..., dtype: DTypeLike = ..., - out: None | ndarray = ..., -) -> ndarray: ... + out: None = ..., +) -> NDArray[Any]: ... +@overload +def cumsum( + a: ArrayLike, + axis: None | int = ..., + dtype: DTypeLike = ..., + out: _ArrayType = ..., +) -> _ArrayType: ... +@overload +def ptp( + a: _ArrayLike[_SCT], + axis: None = ..., + out: None = ..., + keepdims: Literal[False] = ..., +) -> _SCT: ... +@overload def ptp( a: ArrayLike, axis: None | _ShapeLike = ..., - out: None | ndarray = ..., + out: None = ..., keepdims: bool = ..., ) -> Any: ... +@overload +def ptp( + a: ArrayLike, + axis: None | _ShapeLike = ..., + out: _ArrayType = ..., + keepdims: bool = ..., +) -> _ArrayType: ... +@overload +def amax( + a: _ArrayLike[_SCT], + axis: None = ..., + out: None = ..., + keepdims: Literal[False] = ..., + initial: _NumberLike_co = ..., + where: _ArrayLikeBool_co = ..., +) -> _SCT: ... +@overload def amax( a: ArrayLike, axis: None | _ShapeLike = ..., - out: None | ndarray = ..., + out: None = ..., keepdims: bool = ..., initial: _NumberLike_co = ..., where: _ArrayLikeBool_co = ..., ) -> Any: ... +@overload +def amax( + a: ArrayLike, + axis: None | _ShapeLike = ..., + out: _ArrayType = ..., + keepdims: bool = ..., + initial: _NumberLike_co = ..., + where: _ArrayLikeBool_co = ..., +) -> _ArrayType: ... +@overload +def amin( + a: _ArrayLike[_SCT], + axis: None = ..., + out: None = ..., + keepdims: Literal[False] = ..., + initial: _NumberLike_co = ..., + where: _ArrayLikeBool_co = ..., +) -> _SCT: ... +@overload def amin( a: ArrayLike, axis: None | _ShapeLike = ..., - out: None | ndarray = ..., + out: None = ..., keepdims: bool = ..., initial: _NumberLike_co = ..., where: _ArrayLikeBool_co = ..., ) -> Any: ... +@overload +def amin( + a: ArrayLike, + axis: None | _ShapeLike = ..., + out: _ArrayType = ..., + keepdims: bool = ..., + initial: _NumberLike_co = ..., + where: _ArrayLikeBool_co = ..., +) -> _ArrayType: ... # TODO: `np.prod()``: For object arrays `initial` does not necessarily # have to be a numerical scalar. diff --git a/numpy/typing/tests/data/fail/fromnumeric.pyi b/numpy/typing/tests/data/fail/fromnumeric.pyi index 84c95639d..5f292999a 100644 --- a/numpy/typing/tests/data/fail/fromnumeric.pyi +++ b/numpy/typing/tests/data/fail/fromnumeric.pyi @@ -7,10 +7,10 @@ A.setflags(write=False) a = np.bool_(True) -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.take(a, None) # E: No overload variant +np.take(a, axis=1.0) # E: No overload variant +np.take(A, out=1) # E: No overload variant +np.take(A, mode="bob") # E: No overload variant np.reshape(a, None) # E: No overload variant np.reshape(A, 1, order="bob") # E: No overload variant @@ -80,9 +80,9 @@ np.diagonal(A, offset=None) # E: No overload variant np.diagonal(A, axis1="bob") # E: No overload variant np.diagonal(A, axis2=[]) # E: No overload variant -np.trace(A, offset=None) # E: Argument "offset" to "trace" has incompatible type -np.trace(A, axis1="bob") # E: Argument "axis1" to "trace" has incompatible type -np.trace(A, axis2=[]) # E: Argument "axis2" to "trace" has incompatible type +np.trace(A, offset=None) # E: No overload variant +np.trace(A, axis1="bob") # E: No overload variant +np.trace(A, axis2=[]) # E: No overload variant np.ravel(a, order="bob") # E: No overload variant @@ -91,11 +91,10 @@ np.compress( # E: No overload variant ) 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: incompatible type -np.sum(a, keepdims=1.0) # E: incompatible type -np.sum(a, initial=[1]) # E: incompatible type +np.sum(a, axis=1.0) # E: No overload variant +np.sum(a, keepdims=1.0) # E: No overload variant +np.sum(a, initial=[1]) # E: No overload variant np.all(a, axis=1.0) # E: No overload variant np.all(a, keepdims=1.0) # E: No overload variant @@ -105,24 +104,24 @@ 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: incompatible type -np.cumsum(a, dtype=1.0) # E: incompatible type -np.cumsum(a, out=1.0) # E: incompatible type +np.cumsum(a, axis=1.0) # E: No overload variant +np.cumsum(a, dtype=1.0) # E: No overload variant +np.cumsum(a, out=1.0) # E: No overload variant -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.ptp(a, axis=1.0) # E: No overload variant +np.ptp(a, keepdims=1.0) # E: No overload variant +np.ptp(a, out=1.0) # E: No overload variant -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, axis=1.0) # E: No overload variant +np.amax(a, keepdims=1.0) # E: No overload variant +np.amax(a, out=1.0) # E: No overload variant +np.amax(a, initial=[1.0]) # E: No overload variant np.amax(a, where=[1.0]) # E: incompatible 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, axis=1.0) # E: No overload variant +np.amin(a, keepdims=1.0) # E: No overload variant +np.amin(a, out=1.0) # E: No overload variant +np.amin(a, initial=[1.0]) # E: No overload variant np.amin(a, where=[1.0]) # E: incompatible type np.prod(a, axis=1.0) # E: incompatible type diff --git a/numpy/typing/tests/data/reveal/fromnumeric.pyi b/numpy/typing/tests/data/reveal/fromnumeric.pyi index aba570f1a..f9f0ff625 100644 --- a/numpy/typing/tests/data/reveal/fromnumeric.pyi +++ b/numpy/typing/tests/data/reveal/fromnumeric.pyi @@ -1,268 +1,287 @@ """Tests for :mod:`core.fromnumeric`.""" import numpy as np - -A = np.array(True, ndmin=2, dtype=np.bool_) -B = np.array(1.0, ndmin=2, dtype=np.float32) -A.setflags(write=False) -B.setflags(write=False) - -a = np.bool_(True) -b = np.float32(1.0) -c = 1.0 -d = np.array(1.0, dtype=np.float32) # writeable - -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: ndarray[Any, dtype[bool_]] -reveal_type(np.reshape(b, 1)) # E: ndarray[Any, dtype[{float32}]] -reveal_type(np.reshape(c, 1)) # E: ndarray[Any, dtype[Any]] -reveal_type(np.reshape(A, 1)) # E: ndarray[Any, dtype[bool_]] -reveal_type(np.reshape(B, 1)) # E: ndarray[Any, dtype[{float32}]] +import numpy.typing as npt + +class NDArraySubclass(npt.NDArray[np.complex128]): + ... + +AR_b: npt.NDArray[np.bool_] +AR_f4: npt.NDArray[np.float32] +AR_i8: npt.NDArray[np.int64] +AR_subclass: NDArraySubclass + +b: np.bool_ +f4: np.float32 +f: float + +reveal_type(np.take(b, 0)) # E: bool_ +reveal_type(np.take(f4, 0)) # E: {float32} +reveal_type(np.take(f, 0)) # E: Any +reveal_type(np.take(AR_b, 0)) # E: bool_ +reveal_type(np.take(AR_f4, 0)) # E: {float32} +reveal_type(np.take(AR_b, [0])) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.take(AR_f4, [0])) # E: ndarray[Any, dtype[{float32}]] +reveal_type(np.take([1], [0])) # E: ndarray[Any, dtype[Any]] +reveal_type(np.take(AR_f4, [0], out=AR_subclass)) # E: NDArraySubclass + +reveal_type(np.reshape(b, 1)) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.reshape(f4, 1)) # E: ndarray[Any, dtype[{float32}]] +reveal_type(np.reshape(f, 1)) # E: ndarray[Any, dtype[Any]] +reveal_type(np.reshape(AR_b, 1)) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.reshape(AR_f4, 1)) # E: ndarray[Any, dtype[{float32}]] reveal_type(np.choose(1, [True, True])) # E: Any reveal_type(np.choose([1], [True, True])) # E: ndarray[Any, dtype[Any]] -reveal_type(np.choose([1], A)) # E: ndarray[Any, dtype[bool_]] -reveal_type(np.choose([1], A, out=B)) # E: ndarray[Any, dtype[{float32}]] +reveal_type(np.choose([1], AR_b)) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.choose([1], AR_b, out=AR_f4)) # E: ndarray[Any, dtype[{float32}]] -reveal_type(np.repeat(a, 1)) # E: ndarray[Any, dtype[bool_]] -reveal_type(np.repeat(b, 1)) # E: ndarray[Any, dtype[{float32}]] -reveal_type(np.repeat(c, 1)) # E: ndarray[Any, dtype[Any]] -reveal_type(np.repeat(A, 1)) # E: ndarray[Any, dtype[bool_]] -reveal_type(np.repeat(B, 1)) # E: ndarray[Any, dtype[{float32}]] +reveal_type(np.repeat(b, 1)) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.repeat(f4, 1)) # E: ndarray[Any, dtype[{float32}]] +reveal_type(np.repeat(f, 1)) # E: ndarray[Any, dtype[Any]] +reveal_type(np.repeat(AR_b, 1)) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.repeat(AR_f4, 1)) # E: ndarray[Any, dtype[{float32}]] -# TODO: Add tests for np.put() +# TODO: array_bdd tests for np.put() reveal_type(np.swapaxes([[0, 1]], 0, 0)) # E: ndarray[Any, dtype[Any]] -reveal_type(np.swapaxes(A, 0, 0)) # E: ndarray[Any, dtype[bool_]] -reveal_type(np.swapaxes(B, 0, 0)) # E: ndarray[Any, dtype[{float32}]] - -reveal_type(np.transpose(a)) # E: ndarray[Any, dtype[bool_]] -reveal_type(np.transpose(b)) # E: ndarray[Any, dtype[{float32}]] -reveal_type(np.transpose(c)) # E: ndarray[Any, dtype[Any]] -reveal_type(np.transpose(A)) # E: ndarray[Any, dtype[bool_]] -reveal_type(np.transpose(B)) # E: ndarray[Any, dtype[{float32}]] - -reveal_type(np.partition(a, 0, axis=None)) # E: ndarray[Any, dtype[bool_]] -reveal_type(np.partition(b, 0, axis=None)) # E: ndarray[Any, dtype[{float32}]] -reveal_type(np.partition(c, 0, axis=None)) # E: ndarray[Any, dtype[Any]] -reveal_type(np.partition(A, 0)) # E: ndarray[Any, dtype[bool_]] -reveal_type(np.partition(B, 0)) # E: ndarray[Any, dtype[{float32}]] - -reveal_type(np.argpartition(a, 0)) # E: ndarray[Any, dtype[{intp}]] +reveal_type(np.swapaxes(AR_b, 0, 0)) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.swapaxes(AR_f4, 0, 0)) # E: ndarray[Any, dtype[{float32}]] + +reveal_type(np.transpose(b)) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.transpose(f4)) # E: ndarray[Any, dtype[{float32}]] +reveal_type(np.transpose(f)) # E: ndarray[Any, dtype[Any]] +reveal_type(np.transpose(AR_b)) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.transpose(AR_f4)) # E: ndarray[Any, dtype[{float32}]] + +reveal_type(np.partition(b, 0, axis=None)) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.partition(f4, 0, axis=None)) # E: ndarray[Any, dtype[{float32}]] +reveal_type(np.partition(f, 0, axis=None)) # E: ndarray[Any, dtype[Any]] +reveal_type(np.partition(AR_b, 0)) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.partition(AR_f4, 0)) # E: ndarray[Any, dtype[{float32}]] + reveal_type(np.argpartition(b, 0)) # E: ndarray[Any, dtype[{intp}]] -reveal_type(np.argpartition(c, 0)) # E: ndarray[Any, dtype[{intp}]] -reveal_type(np.argpartition(A, 0)) # E: ndarray[Any, dtype[{intp}]] -reveal_type(np.argpartition(B, 0)) # E: ndarray[Any, dtype[{intp}]] +reveal_type(np.argpartition(f4, 0)) # E: ndarray[Any, dtype[{intp}]] +reveal_type(np.argpartition(f, 0)) # E: ndarray[Any, dtype[{intp}]] +reveal_type(np.argpartition(AR_b, 0)) # E: ndarray[Any, dtype[{intp}]] +reveal_type(np.argpartition(AR_f4, 0)) # E: ndarray[Any, dtype[{intp}]] reveal_type(np.sort([2, 1], 0)) # E: ndarray[Any, dtype[Any]] -reveal_type(np.sort(A, 0)) # E: ndarray[Any, dtype[bool_]] -reveal_type(np.sort(B, 0)) # E: ndarray[Any, dtype[{float32}]] - -reveal_type(np.argsort(A, 0)) # E: ndarray[Any, dtype[{intp}]] -reveal_type(np.argsort(B, 0)) # E: ndarray[Any, dtype[{intp}]] - -reveal_type(np.argmax(A)) # E: {intp} -reveal_type(np.argmax(B)) # E: {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: 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} -reveal_type(np.searchsorted(A[0], [0])) # E: ndarray[Any, dtype[{intp}]] -reveal_type(np.searchsorted(B[0], [0])) # E: ndarray[Any, dtype[{intp}]] - -reveal_type(np.resize(a, (5, 5))) # E: ndarray[Any, dtype[bool_]] -reveal_type(np.resize(b, (5, 5))) # E: ndarray[Any, dtype[{float32}]] -reveal_type(np.resize(c, (5, 5))) # E: ndarray[Any, dtype[Any]] -reveal_type(np.resize(A, (5, 5))) # E: ndarray[Any, dtype[bool_]] -reveal_type(np.resize(B, (5, 5))) # E: ndarray[Any, dtype[{float32}]] - -reveal_type(np.squeeze(a)) # E: bool_ -reveal_type(np.squeeze(b)) # E: {float32} -reveal_type(np.squeeze(c)) # E: ndarray[Any, dtype[Any]] -reveal_type(np.squeeze(A)) # E: ndarray[Any, dtype[bool_]] -reveal_type(np.squeeze(B)) # E: ndarray[Any, dtype[{float32}]] - -reveal_type(np.diagonal(A)) # E: ndarray[Any, dtype[bool_]] -reveal_type(np.diagonal(B)) # E: ndarray[Any, dtype[{float32}]] - -reveal_type(np.trace(A)) # E: Any -reveal_type(np.trace(B)) # E: Any - -reveal_type(np.ravel(a)) # E: ndarray[Any, dtype[bool_]] -reveal_type(np.ravel(b)) # E: ndarray[Any, dtype[{float32}]] -reveal_type(np.ravel(c)) # E: ndarray[Any, dtype[Any]] -reveal_type(np.ravel(A)) # E: ndarray[Any, dtype[bool_]] -reveal_type(np.ravel(B)) # E: ndarray[Any, dtype[{float32}]] - -reveal_type(np.nonzero(a)) # E: tuple[ndarray[Any, dtype[{intp}]]] +reveal_type(np.sort(AR_b, 0)) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.sort(AR_f4, 0)) # E: ndarray[Any, dtype[{float32}]] + +reveal_type(np.argsort(AR_b, 0)) # E: ndarray[Any, dtype[{intp}]] +reveal_type(np.argsort(AR_f4, 0)) # E: ndarray[Any, dtype[{intp}]] + +reveal_type(np.argmax(AR_b)) # E: {intp} +reveal_type(np.argmax(AR_f4)) # E: {intp} +reveal_type(np.argmax(AR_b, axis=0)) # E: Any +reveal_type(np.argmax(AR_f4, axis=0)) # E: Any +reveal_type(np.argmax(AR_f4, out=AR_subclass)) # E: NDArraySubclass + +reveal_type(np.argmin(AR_b)) # E: {intp} +reveal_type(np.argmin(AR_f4)) # E: {intp} +reveal_type(np.argmin(AR_b, axis=0)) # E: Any +reveal_type(np.argmin(AR_f4, axis=0)) # E: Any +reveal_type(np.argmin(AR_f4, out=AR_subclass)) # E: NDArraySubclass + +reveal_type(np.searchsorted(AR_b[0], 0)) # E: {intp} +reveal_type(np.searchsorted(AR_f4[0], 0)) # E: {intp} +reveal_type(np.searchsorted(AR_b[0], [0])) # E: ndarray[Any, dtype[{intp}]] +reveal_type(np.searchsorted(AR_f4[0], [0])) # E: ndarray[Any, dtype[{intp}]] + +reveal_type(np.resize(b, (5, 5))) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.resize(f4, (5, 5))) # E: ndarray[Any, dtype[{float32}]] +reveal_type(np.resize(f, (5, 5))) # E: ndarray[Any, dtype[Any]] +reveal_type(np.resize(AR_b, (5, 5))) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.resize(AR_f4, (5, 5))) # E: ndarray[Any, dtype[{float32}]] + +reveal_type(np.squeeze(b)) # E: bool_ +reveal_type(np.squeeze(f4)) # E: {float32} +reveal_type(np.squeeze(f)) # E: ndarray[Any, dtype[Any]] +reveal_type(np.squeeze(AR_b)) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.squeeze(AR_f4)) # E: ndarray[Any, dtype[{float32}]] + +reveal_type(np.diagonal(AR_b)) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.diagonal(AR_f4)) # E: ndarray[Any, dtype[{float32}]] + +reveal_type(np.trace(AR_b)) # E: Any +reveal_type(np.trace(AR_f4)) # E: Any +reveal_type(np.trace(AR_f4, out=AR_subclass)) # E: NDArraySubclass + +reveal_type(np.ravel(b)) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.ravel(f4)) # E: ndarray[Any, dtype[{float32}]] +reveal_type(np.ravel(f)) # E: ndarray[Any, dtype[Any]] +reveal_type(np.ravel(AR_b)) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.ravel(AR_f4)) # E: ndarray[Any, dtype[{float32}]] + reveal_type(np.nonzero(b)) # E: tuple[ndarray[Any, dtype[{intp}]]] -reveal_type(np.nonzero(c)) # E: tuple[ndarray[Any, dtype[{intp}]]] -reveal_type(np.nonzero(A)) # E: tuple[ndarray[Any, dtype[{intp}]]] -reveal_type(np.nonzero(B)) # E: tuple[ndarray[Any, dtype[{intp}]]] +reveal_type(np.nonzero(f4)) # E: tuple[ndarray[Any, dtype[{intp}]]] +reveal_type(np.nonzero(f)) # E: tuple[ndarray[Any, dtype[{intp}]]] +reveal_type(np.nonzero(AR_b)) # E: tuple[ndarray[Any, dtype[{intp}]]] +reveal_type(np.nonzero(AR_f4)) # E: tuple[ndarray[Any, dtype[{intp}]]] -reveal_type(np.shape(a)) # E: tuple[builtins.int] reveal_type(np.shape(b)) # E: tuple[builtins.int] -reveal_type(np.shape(c)) # E: tuple[builtins.int] -reveal_type(np.shape(A)) # E: tuple[builtins.int] -reveal_type(np.shape(B)) # E: tuple[builtins.int] - -reveal_type(np.compress([True], a)) # E: ndarray[Any, dtype[bool_]] -reveal_type(np.compress([True], b)) # E: ndarray[Any, dtype[{float32}]] -reveal_type(np.compress([True], c)) # E: ndarray[Any, dtype[Any]] -reveal_type(np.compress([True], A)) # E: ndarray[Any, dtype[bool_]] -reveal_type(np.compress([True], B)) # E: ndarray[Any, dtype[{float32}]] - -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: 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: bool_ +reveal_type(np.shape(f4)) # E: tuple[builtins.int] +reveal_type(np.shape(f)) # E: tuple[builtins.int] +reveal_type(np.shape(AR_b)) # E: tuple[builtins.int] +reveal_type(np.shape(AR_f4)) # E: tuple[builtins.int] + +reveal_type(np.compress([True], b)) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.compress([True], f4)) # E: ndarray[Any, dtype[{float32}]] +reveal_type(np.compress([True], f)) # E: ndarray[Any, dtype[Any]] +reveal_type(np.compress([True], AR_b)) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.compress([True], AR_f4)) # E: ndarray[Any, dtype[{float32}]] + +reveal_type(np.clip(b, 0, 1.0)) # E: bool_ +reveal_type(np.clip(f4, -1, 1)) # E: {float32} +reveal_type(np.clip(f, 0, 1)) # E: Any +reveal_type(np.clip(AR_b, 0, 1)) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.clip(AR_f4, 0, 1)) # E: ndarray[Any, dtype[{float32}]] +reveal_type(np.clip([0], 0, 1)) # E: ndarray[Any, dtype[Any]] +reveal_type(np.clip(AR_b, 0, 1, out=AR_subclass)) # E: NDArraySubclass + +reveal_type(np.sum(b)) # E: bool_ +reveal_type(np.sum(f4)) # E: {float32} +reveal_type(np.sum(f)) # E: Any +reveal_type(np.sum(AR_b)) # E: bool_ +reveal_type(np.sum(AR_f4)) # E: {float32} +reveal_type(np.sum(AR_b, axis=0)) # E: Any +reveal_type(np.sum(AR_f4, axis=0)) # E: Any +reveal_type(np.sum(AR_f4, out=AR_subclass)) # E: NDArraySubclass + reveal_type(np.all(b)) # E: bool_ -reveal_type(np.all(c)) # E: bool_ -reveal_type(np.all(A)) # E: bool_ -reveal_type(np.all(B)) # E: bool_ -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: bool_ +reveal_type(np.all(f4)) # E: bool_ +reveal_type(np.all(f)) # E: bool_ +reveal_type(np.all(AR_b)) # E: bool_ +reveal_type(np.all(AR_f4)) # E: bool_ +reveal_type(np.all(AR_b, axis=0)) # E: Any +reveal_type(np.all(AR_f4, axis=0)) # E: Any +reveal_type(np.all(AR_b, keepdims=True)) # E: Any +reveal_type(np.all(AR_f4, keepdims=True)) # E: Any +reveal_type(np.all(AR_f4, out=AR_subclass)) # E: NDArraySubclass + reveal_type(np.any(b)) # E: bool_ -reveal_type(np.any(c)) # E: bool_ -reveal_type(np.any(A)) # E: bool_ -reveal_type(np.any(B)) # E: bool_ -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: ndarray[Any, Any] -reveal_type(np.cumsum(b)) # E: ndarray[Any, Any] -reveal_type(np.cumsum(c)) # E: ndarray[Any, Any] -reveal_type(np.cumsum(A)) # E: ndarray[Any, Any] -reveal_type(np.cumsum(B)) # E: 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.any(f4)) # E: bool_ +reveal_type(np.any(f)) # E: bool_ +reveal_type(np.any(AR_b)) # E: bool_ +reveal_type(np.any(AR_f4)) # E: bool_ +reveal_type(np.any(AR_b, axis=0)) # E: Any +reveal_type(np.any(AR_f4, axis=0)) # E: Any +reveal_type(np.any(AR_b, keepdims=True)) # E: Any +reveal_type(np.any(AR_f4, keepdims=True)) # E: Any +reveal_type(np.any(AR_f4, out=AR_subclass)) # E: NDArraySubclass + +reveal_type(np.cumsum(b)) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.cumsum(f4)) # E: ndarray[Any, dtype[{float32}]] +reveal_type(np.cumsum(f)) # E: ndarray[Any, dtype[Any]] +reveal_type(np.cumsum(AR_b)) # E: ndarray[Any, dtype[bool_]] +reveal_type(np.cumsum(AR_f4)) # E: ndarray[Any, dtype[{float32}]] +reveal_type(np.cumsum(f, dtype=float)) # E: ndarray[Any, dtype[Any]] +reveal_type(np.cumsum(f, dtype=np.float64)) # E: ndarray[Any, dtype[{float64}]] +reveal_type(np.cumsum(AR_f4, out=AR_subclass)) # E: NDArraySubclass + +reveal_type(np.ptp(b)) # E: bool_ +reveal_type(np.ptp(f4)) # E: {float32} +reveal_type(np.ptp(f)) # E: Any +reveal_type(np.ptp(AR_b)) # E: bool_ +reveal_type(np.ptp(AR_f4)) # E: {float32} +reveal_type(np.ptp(AR_b, axis=0)) # E: Any +reveal_type(np.ptp(AR_f4, axis=0)) # E: Any +reveal_type(np.ptp(AR_b, keepdims=True)) # E: Any +reveal_type(np.ptp(AR_f4, keepdims=True)) # E: Any +reveal_type(np.ptp(AR_f4, out=AR_subclass)) # E: NDArraySubclass + +reveal_type(np.amax(b)) # E: bool_ +reveal_type(np.amax(f4)) # E: {float32} +reveal_type(np.amax(f)) # E: Any +reveal_type(np.amax(AR_b)) # E: bool_ +reveal_type(np.amax(AR_f4)) # E: {float32} +reveal_type(np.amax(AR_b, axis=0)) # E: Any +reveal_type(np.amax(AR_f4, axis=0)) # E: Any +reveal_type(np.amax(AR_b, keepdims=True)) # E: Any +reveal_type(np.amax(AR_f4, keepdims=True)) # E: Any +reveal_type(np.amax(AR_f4, out=AR_subclass)) # E: NDArraySubclass + +reveal_type(np.amin(b)) # E: bool_ +reveal_type(np.amin(f4)) # E: {float32} +reveal_type(np.amin(f)) # E: Any +reveal_type(np.amin(AR_b)) # E: bool_ +reveal_type(np.amin(AR_f4)) # E: {float32} +reveal_type(np.amin(AR_b, axis=0)) # E: Any +reveal_type(np.amin(AR_f4, axis=0)) # E: Any +reveal_type(np.amin(AR_b, keepdims=True)) # E: Any +reveal_type(np.amin(AR_f4, keepdims=True)) # E: Any +reveal_type(np.amin(AR_f4, out=AR_subclass)) # E: NDArraySubclass + 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: ndarray[Any, Any] +reveal_type(np.prod(f4)) # E: Any +reveal_type(np.prod(f)) # E: Any +reveal_type(np.prod(AR_b)) # E: Any +reveal_type(np.prod(AR_f4)) # E: Any +reveal_type(np.prod(AR_b, axis=0)) # E: Any +reveal_type(np.prod(AR_f4, axis=0)) # E: Any +reveal_type(np.prod(AR_b, keepdims=True)) # E: Any +reveal_type(np.prod(AR_f4, keepdims=True)) # E: Any +reveal_type(np.prod(f4, out=AR_i8)) # E: Any +reveal_type(np.prod(AR_f4, out=AR_i8)) # E: Any + reveal_type(np.cumprod(b)) # E: ndarray[Any, Any] -reveal_type(np.cumprod(c)) # E: ndarray[Any, Any] -reveal_type(np.cumprod(A)) # E: ndarray[Any, Any] -reveal_type(np.cumprod(B)) # E: ndarray[Any, Any] +reveal_type(np.cumprod(f4)) # E: ndarray[Any, Any] +reveal_type(np.cumprod(f)) # E: ndarray[Any, Any] +reveal_type(np.cumprod(AR_b)) # E: ndarray[Any, Any] +reveal_type(np.cumprod(AR_f4)) # E: ndarray[Any, Any] -reveal_type(np.ndim(a)) # E: int reveal_type(np.ndim(b)) # E: int -reveal_type(np.ndim(c)) # E: int -reveal_type(np.ndim(A)) # E: int -reveal_type(np.ndim(B)) # E: int +reveal_type(np.ndim(f4)) # E: int +reveal_type(np.ndim(f)) # E: int +reveal_type(np.ndim(AR_b)) # E: int +reveal_type(np.ndim(AR_f4)) # E: int -reveal_type(np.size(a)) # E: int reveal_type(np.size(b)) # E: int -reveal_type(np.size(c)) # E: int -reveal_type(np.size(A)) # E: int -reveal_type(np.size(B)) # E: int +reveal_type(np.size(f4)) # E: int +reveal_type(np.size(f)) # E: int +reveal_type(np.size(AR_b)) # E: int +reveal_type(np.size(AR_f4)) # E: int -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.around(f4)) # E: Any +reveal_type(np.around(f)) # E: Any +reveal_type(np.around(AR_b)) # E: Any +reveal_type(np.around(AR_f4)) # 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.mean(f4)) # E: Any +reveal_type(np.mean(f)) # E: Any +reveal_type(np.mean(AR_b)) # E: Any +reveal_type(np.mean(AR_f4)) # E: Any +reveal_type(np.mean(AR_b, axis=0)) # E: Any +reveal_type(np.mean(AR_f4, axis=0)) # E: Any +reveal_type(np.mean(AR_b, keepdims=True)) # E: Any +reveal_type(np.mean(AR_f4, keepdims=True)) # E: Any +reveal_type(np.mean(f4, out=AR_i8)) # E: Any +reveal_type(np.mean(AR_f4, out=AR_i8)) # 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.std(f4)) # E: Any +reveal_type(np.std(f)) # E: Any +reveal_type(np.std(AR_b)) # E: Any +reveal_type(np.std(AR_f4)) # E: Any +reveal_type(np.std(AR_b, axis=0)) # E: Any +reveal_type(np.std(AR_f4, axis=0)) # E: Any +reveal_type(np.std(AR_b, keepdims=True)) # E: Any +reveal_type(np.std(AR_f4, keepdims=True)) # E: Any +reveal_type(np.std(f4, out=AR_i8)) # E: Any +reveal_type(np.std(AR_f4, out=AR_i8)) # 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 +reveal_type(np.var(f4)) # E: Any +reveal_type(np.var(f)) # E: Any +reveal_type(np.var(AR_b)) # E: Any +reveal_type(np.var(AR_f4)) # E: Any +reveal_type(np.var(AR_b, axis=0)) # E: Any +reveal_type(np.var(AR_f4, axis=0)) # E: Any +reveal_type(np.var(AR_b, keepdims=True)) # E: Any +reveal_type(np.var(AR_f4, keepdims=True)) # E: Any +reveal_type(np.var(f4, out=AR_i8)) # E: Any +reveal_type(np.var(AR_f4, out=AR_i8)) # E: Any |