diff options
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/core/fromnumeric.pyi | 156 | ||||
| -rw-r--r-- | numpy/typing/tests/data/fail/fromnumeric.pyi | 48 | ||||
| -rw-r--r-- | numpy/typing/tests/data/reveal/fromnumeric.pyi | 126 |
3 files changed, 219 insertions, 111 deletions
diff --git a/numpy/core/fromnumeric.pyi b/numpy/core/fromnumeric.pyi index 472c4ded5..d5ac3db70 100644 --- a/numpy/core/fromnumeric.pyi +++ b/numpy/core/fromnumeric.pyi @@ -19,11 +19,13 @@ from numpy import ( from numpy.typing import ( DTypeLike, ArrayLike, + _ArrayLike, NDArray, _ShapeLike, _Shape, _ArrayLikeBool_co, _ArrayLikeInt_co, + _IntLike_co, _NumberLike_co, ) @@ -36,10 +38,9 @@ _ScalarNumpy = Union[generic, dt.datetime, dt.timedelta] _ScalarBuiltin = Union[str, bytes, dt.date, dt.timedelta, bool, int, float, complex] _Scalar = Union[_ScalarBuiltin, _ScalarNumpy] -# Integers and booleans can generally be used interchangeably -_ScalarGeneric = TypeVar("_ScalarGeneric", bound=generic) - +_SCT = TypeVar("_SCT", bound=generic) _Number = TypeVar("_Number", bound=number) +_ArrayType = TypeVar("_ArrayType", bound=NDArray[Any]) # The signature of take() follows a common theme with its overloads: # 1. A generic comes in; the same generic comes out @@ -54,50 +55,108 @@ def take( mode: _ModeKind = ..., ) -> Any: ... +@overload +def reshape( + a: _ArrayLike[_SCT], + newshape: _ShapeLike, + order: _OrderACF = ..., +) -> NDArray[_SCT]: ... +@overload def reshape( a: ArrayLike, newshape: _ShapeLike, order: _OrderACF = ..., -) -> ndarray: ... +) -> NDArray[Any]: ... +@overload def choose( - a: _ArrayLikeInt_co, + a: _IntLike_co, choices: ArrayLike, - out: None | ndarray = ..., + out: None = ..., mode: _ModeKind = ..., ) -> Any: ... +@overload +def choose( + a: _ArrayLikeInt_co, + choices: _ArrayLike[_SCT], + out: None = ..., + mode: _ModeKind = ..., +) -> NDArray[_SCT]: ... +@overload +def choose( + a: _ArrayLikeInt_co, + choices: ArrayLike, + out: None = ..., + mode: _ModeKind = ..., +) -> NDArray[Any]: ... +@overload +def choose( + a: _ArrayLikeInt_co, + choices: ArrayLike, + out: _ArrayType = ..., + mode: _ModeKind = ..., +) -> _ArrayType: ... +@overload +def repeat( + a: _ArrayLike[_SCT], + repeats: _ArrayLikeInt_co, + axis: None | int = ..., +) -> NDArray[_SCT]: ... +@overload def repeat( a: ArrayLike, repeats: _ArrayLikeInt_co, axis: None | int = ..., -) -> ndarray: ... +) -> NDArray[Any]: ... def put( - a: ndarray, + a: NDArray[Any], ind: _ArrayLikeInt_co, v: ArrayLike, mode: _ModeKind = ..., ) -> None: ... +@overload +def swapaxes( + a: _ArrayLike[_SCT], + axis1: int, + axis2: int, +) -> NDArray[_SCT]: ... +@overload def swapaxes( a: ArrayLike, axis1: int, axis2: int, -) -> ndarray: ... +) -> NDArray[Any]: ... +@overload +def transpose( + a: _ArrayLike[_SCT], + axes: None | _ShapeLike = ... +) -> NDArray[_SCT]: ... +@overload def transpose( a: ArrayLike, - axes: None | Sequence[int] | NDArray[Any] = ... -) -> ndarray: ... + axes: None | _ShapeLike = ... +) -> NDArray[Any]: ... +@overload +def partition( + a: _ArrayLike[_SCT], + kth: _ArrayLikeInt_co, + axis: None | int = ..., + kind: _PartitionKind = ..., + order: None | str | Sequence[str] = ..., +) -> NDArray[_SCT]: ... +@overload def partition( a: ArrayLike, kth: _ArrayLikeInt_co, axis: None | int = ..., kind: _PartitionKind = ..., order: None | str | Sequence[str] = ..., -) -> ndarray: ... +) -> NDArray[Any]: ... def argpartition( a: ArrayLike, @@ -105,21 +164,29 @@ def argpartition( axis: None | int = ..., kind: _PartitionKind = ..., order: None | str | Sequence[str] = ..., -) -> Any: ... +) -> NDArray[intp]: ... +@overload +def sort( + a: _ArrayLike[_SCT], + axis: None | int = ..., + kind: None | _SortKind = ..., + order: None | str | Sequence[str] = ..., +) -> NDArray[_SCT]: ... +@overload def sort( a: ArrayLike, axis: None | int = ..., kind: None | _SortKind = ..., order: None | str | Sequence[str] = ..., -) -> ndarray: ... +) -> NDArray[Any]: ... def argsort( a: ArrayLike, axis: None | int = ..., kind: None | _SortKind = ..., order: None | str | Sequence[str] = ..., -) -> ndarray: ... +) -> NDArray[intp]: ... @overload def argmax( @@ -168,30 +235,49 @@ def searchsorted( v: ArrayLike, side: _SortSide = ..., sorter: None | _ArrayLikeInt_co = ..., # 1D int array -) -> ndarray: ... +) -> NDArray[intp]: ... +@overload +def resize( + a: _ArrayLike[_SCT], + new_shape: _ShapeLike, +) -> NDArray[_SCT]: ... +@overload def resize( a: ArrayLike, new_shape: _ShapeLike, -) -> ndarray: ... +) -> NDArray[Any]: ... @overload def squeeze( - a: _ScalarGeneric, + a: _SCT, + axis: None | _ShapeLike = ..., +) -> _SCT: ... +@overload +def squeeze( + a: _ArrayLike[_SCT], axis: None | _ShapeLike = ..., -) -> _ScalarGeneric: ... +) -> NDArray[_SCT]: ... @overload def squeeze( a: ArrayLike, axis: None | _ShapeLike = ..., -) -> ndarray: ... +) -> NDArray[Any]: ... +@overload +def diagonal( + a: _ArrayLike[_SCT], + offset: int = ..., + axis1: int = ..., + axis2: int = ..., # >= 2D array +) -> NDArray[_SCT]: ... +@overload def diagonal( a: ArrayLike, offset: int = ..., axis1: int = ..., axis2: int = ..., # >= 2D array -) -> ndarray: ... +) -> NDArray[Any]: ... def trace( a: ArrayLike, # >= 2D array @@ -202,18 +288,36 @@ def trace( out: None | ndarray = ..., ) -> Any: ... -def ravel(a: ArrayLike, order: _OrderKACF = ...) -> ndarray: ... +@overload +def ravel(a: _ArrayLike[_SCT], order: _OrderKACF = ...) -> NDArray[_SCT]: ... +@overload +def ravel(a: ArrayLike, order: _OrderKACF = ...) -> NDArray[Any]: ... -def nonzero(a: ArrayLike) -> tuple[ndarray, ...]: ... +def nonzero(a: ArrayLike) -> tuple[NDArray[intp], ...]: ... def shape(a: ArrayLike) -> _Shape: ... +@overload def compress( - condition: ArrayLike, # 1D bool array + condition: _ArrayLikeBool_co, # 1D bool array + a: _ArrayLike[_SCT], + axis: None | int = ..., + out: None = ..., +) -> NDArray[_SCT]: ... +@overload +def compress( + condition: _ArrayLikeBool_co, # 1D bool array a: ArrayLike, axis: None | int = ..., - out: None | ndarray = ..., -) -> ndarray: ... + out: None = ..., +) -> NDArray[Any]: ... +@overload +def compress( + condition: _ArrayLikeBool_co, # 1D bool array + a: ArrayLike, + axis: None | int = ..., + out: _ArrayType = ..., +) -> _ArrayType: ... @overload def clip( diff --git a/numpy/typing/tests/data/fail/fromnumeric.pyi b/numpy/typing/tests/data/fail/fromnumeric.pyi index 8fafed1b7..84c95639d 100644 --- a/numpy/typing/tests/data/fail/fromnumeric.pyi +++ b/numpy/typing/tests/data/fail/fromnumeric.pyi @@ -12,27 +12,27 @@ 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.reshape(a, None) # E: No overload variant +np.reshape(A, 1, order="bob") # E: No overload variant -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.choose(a, None) # E: No overload variant +np.choose(a, out=1.0) # E: No overload variant +np.choose(A, mode="bob") # E: No overload variant -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 +np.repeat(a, None) # E: No overload variant +np.repeat(A, 1, axis=1.0) # E: No overload variant -np.swapaxes(A, None, 1) # E: Argument 2 to "swapaxes" has incompatible type -np.swapaxes(A, 1, [0]) # E: Argument 3 to "swapaxes" has incompatible type +np.swapaxes(A, None, 1) # E: No overload variant +np.swapaxes(A, 1, [0]) # E: No overload variant -np.transpose(A, axes=1.0) # E: Argument "axes" to "transpose" has incompatible type +np.transpose(A, axes=1.0) # E: No overload variant -np.partition(a, None) # E: Argument 2 to "partition" has incompatible type -np.partition( - a, 0, axis="bob" # E: Argument "axis" to "partition" has incompatible type +np.partition(a, None) # E: No overload variant +np.partition( # E: No overload variant + a, 0, axis="bob" ) -np.partition( - A, 0, kind="bob" # E: Argument "kind" to "partition" has incompatible type +np.partition( # E: No overload variant + A, 0, kind="bob" ) np.partition( A, 0, order=range(5) # E: Argument "order" to "partition" has incompatible type @@ -51,8 +51,8 @@ np.argpartition( A, 0, order=range(5) # E: Argument "order" to "argpartition" has incompatible type ) -np.sort(A, axis="bob") # E: Argument "axis" to "sort" has incompatible type -np.sort(A, kind="bob") # E: Argument "kind" to "sort" has incompatible type +np.sort(A, axis="bob") # E: No overload variant +np.sort(A, kind="bob") # E: No overload variant np.sort(A, order=range(5)) # E: Argument "order" to "sort" has incompatible type np.argsort(A, axis="bob") # E: Argument "axis" to "argsort" has incompatible type @@ -72,22 +72,22 @@ np.searchsorted( # E: No overload variant of "searchsorted" matches argument ty A[0], 0, sorter=1.0 ) -np.resize(A, 1.0) # E: Argument 2 to "resize" has incompatible type +np.resize(A, 1.0) # E: No overload variant np.squeeze(A, 1.0) # E: No overload variant of "squeeze" matches argument type -np.diagonal(A, offset=None) # E: Argument "offset" to "diagonal" has incompatible type -np.diagonal(A, axis1="bob") # E: Argument "axis1" to "diagonal" has incompatible type -np.diagonal(A, axis2=[]) # E: Argument "axis2" to "diagonal" has incompatible type +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.ravel(a, order="bob") # E: Argument "order" to "ravel" has incompatible type +np.ravel(a, order="bob") # E: No overload variant -np.compress( - [True], A, axis=1.0 # E: Argument "axis" to "compress" has incompatible type +np.compress( # E: No overload variant + [True], A, axis=1.0 ) np.clip(a, 1, 2, out=1) # E: No overload variant of "clip" matches argument type diff --git a/numpy/typing/tests/data/reveal/fromnumeric.pyi b/numpy/typing/tests/data/reveal/fromnumeric.pyi index 2ee1952cf..aba570f1a 100644 --- a/numpy/typing/tests/data/reveal/fromnumeric.pyi +++ b/numpy/typing/tests/data/reveal/fromnumeric.pyi @@ -2,7 +2,7 @@ import numpy as np -A = np.array(True, ndmin=2, dtype=bool) +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) @@ -20,49 +20,53 @@ 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, Any] -reveal_type(np.reshape(b, 1)) # E: ndarray[Any, Any] -reveal_type(np.reshape(c, 1)) # E: ndarray[Any, Any] -reveal_type(np.reshape(A, 1)) # E: ndarray[Any, Any] -reveal_type(np.reshape(B, 1)) # E: ndarray[Any, 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}]] -reveal_type(np.choose(a, [True, True])) # E: Any -reveal_type(np.choose(A, [True, True])) # E: Any +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.repeat(a, 1)) # E: ndarray[Any, Any] -reveal_type(np.repeat(b, 1)) # E: ndarray[Any, Any] -reveal_type(np.repeat(c, 1)) # E: ndarray[Any, Any] -reveal_type(np.repeat(A, 1)) # E: ndarray[Any, Any] -reveal_type(np.repeat(B, 1)) # E: ndarray[Any, 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(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}]] # TODO: Add tests for np.put() -reveal_type(np.swapaxes(A, 0, 0)) # E: ndarray[Any, Any] -reveal_type(np.swapaxes(B, 0, 0)) # E: ndarray[Any, Any] +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, Any] -reveal_type(np.transpose(b)) # E: ndarray[Any, Any] -reveal_type(np.transpose(c)) # E: ndarray[Any, Any] -reveal_type(np.transpose(A)) # E: ndarray[Any, Any] -reveal_type(np.transpose(B)) # E: ndarray[Any, Any] +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, Any] -reveal_type(np.partition(b, 0, axis=None)) # E: ndarray[Any, Any] -reveal_type(np.partition(c, 0, axis=None)) # E: ndarray[Any, Any] -reveal_type(np.partition(A, 0)) # E: ndarray[Any, Any] -reveal_type(np.partition(B, 0)) # E: ndarray[Any, Any] +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: 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.argpartition(a, 0)) # E: ndarray[Any, dtype[{intp}]] +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.sort(A, 0)) # E: ndarray[Any, Any] -reveal_type(np.sort(B, 0)) # E: ndarray[Any, Any] +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, Any] -reveal_type(np.argsort(B, 0)) # E: ndarray[Any, Any] +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} @@ -76,38 +80,38 @@ 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, Any] -reveal_type(np.searchsorted(B[0], [0])) # E: ndarray[Any, Any] +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, Any] -reveal_type(np.resize(b, (5, 5))) # E: ndarray[Any, Any] -reveal_type(np.resize(c, (5, 5))) # E: ndarray[Any, Any] -reveal_type(np.resize(A, (5, 5))) # E: ndarray[Any, Any] -reveal_type(np.resize(B, (5, 5))) # E: ndarray[Any, 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.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, Any] -reveal_type(np.squeeze(A)) # E: ndarray[Any, Any] -reveal_type(np.squeeze(B)) # E: ndarray[Any, Any] +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, Any] -reveal_type(np.diagonal(B)) # E: ndarray[Any, Any] +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, Any] -reveal_type(np.ravel(b)) # E: ndarray[Any, Any] -reveal_type(np.ravel(c)) # E: ndarray[Any, Any] -reveal_type(np.ravel(A)) # E: ndarray[Any, Any] -reveal_type(np.ravel(B)) # E: ndarray[Any, 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, Any]] -reveal_type(np.nonzero(b)) # E: tuple[ndarray[Any, Any]] -reveal_type(np.nonzero(c)) # E: tuple[ndarray[Any, Any]] -reveal_type(np.nonzero(A)) # E: tuple[ndarray[Any, Any]] -reveal_type(np.nonzero(B)) # E: tuple[ndarray[Any, Any]] +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(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.shape(a)) # E: tuple[builtins.int] reveal_type(np.shape(b)) # E: tuple[builtins.int] @@ -115,11 +119,11 @@ 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, Any] -reveal_type(np.compress([True], b)) # E: ndarray[Any, Any] -reveal_type(np.compress([True], c)) # E: ndarray[Any, Any] -reveal_type(np.compress([True], A)) # E: ndarray[Any, Any] -reveal_type(np.compress([True], B)) # E: ndarray[Any, 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.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 |