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TYP: Various typing fixes #29865

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Merged
charris merged 1 commit into from
Oct 2, 2025
Merged

TYP: Various typing fixes #29865

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2 changes: 1 addition & 1 deletion numpy/__init__.pyi
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Original file line number Diff line number Diff line change
Expand Up @@ -3512,7 +3512,7 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeT_co, _DTypeT_co]):
# See https://github.com/numpy/numpy-stubs/pull/80 for more details.
class generic(_ArrayOrScalarCommon, Generic[_ItemT_co]):
@abstractmethod
def __new__(self) -> None: ...
def __new__(cls) -> Self: ...
def __hash__(self) -> int: ...
@overload
def __array__(self, dtype: None = None, /) -> ndarray[tuple[()], dtype[Self]]: ...
Expand Down
16 changes: 8 additions & 8 deletions numpy/lib/_histograms_impl.pyi
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Expand Up @@ -35,16 +35,16 @@ def histogram_bin_edges(

def histogram(
a: ArrayLike,
bins: _BinKind | SupportsIndex | ArrayLike = ...,
range: tuple[float, float] | None = ...,
density: bool = ...,
weights: ArrayLike | None = ...,
bins: _BinKind | SupportsIndex | ArrayLike = 10,
range: tuple[float, float] | None = None,
density: bool | None = None,
weights: ArrayLike | None = None,
) -> tuple[NDArray[Any], NDArray[Any]]: ...

def histogramdd(
sample: ArrayLike,
bins: SupportsIndex | ArrayLike = ...,
range: Sequence[tuple[float, float]] = ...,
density: bool | None = ...,
weights: ArrayLike | None = ...,
bins: SupportsIndex | ArrayLike = 10,
range: Sequence[tuple[float, float]] | None = None,
density: bool | None = None,
weights: ArrayLike | None = None,
) -> tuple[NDArray[Any], tuple[NDArray[Any], ...]]: ...
18 changes: 10 additions & 8 deletions numpy/lib/_polynomial_impl.pyi
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Expand Up @@ -137,20 +137,22 @@ def polyfit(
x: _ArrayLikeFloat_co,
y: _ArrayLikeFloat_co,
deg: SupportsIndex | SupportsInt,
rcond: float | None = ...,
full: L[False] = ...,
w: _ArrayLikeFloat_co | None = ...,
cov: L[True, "unscaled"] = ...,
rcond: float | None = None,
full: L[False] = False,
w: _ArrayLikeFloat_co | None = None,
*,
cov: L[True, "unscaled"],
) -> _2Tup[NDArray[float64]]: ...
@overload
def polyfit(
x: _ArrayLikeComplex_co,
y: _ArrayLikeComplex_co,
deg: SupportsIndex | SupportsInt,
rcond: float | None = ...,
full: L[False] = ...,
w: _ArrayLikeFloat_co | None = ...,
cov: L[True, "unscaled"] = ...,
rcond: float | None = None,
full: L[False] = False,
w: _ArrayLikeFloat_co | None = None,
*,
cov: L[True, "unscaled"],
) -> _2Tup[NDArray[complex128]]: ...
@overload
def polyfit(
Expand Down
71 changes: 32 additions & 39 deletions numpy/linalg/_linalg.pyi
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Expand Up @@ -28,6 +28,7 @@ from numpy import (
)
from numpy._core.fromnumeric import matrix_transpose
from numpy._core.numeric import tensordot
from numpy._globals import _NoValueType
from numpy._typing import (
ArrayLike,
DTypeLike,
Expand Down Expand Up @@ -78,7 +79,7 @@ __all__ = [
"vecdot",
]

_ArrayT = TypeVar("_ArrayT", bound=NDArray[Any])
_NumberT = TypeVar("_NumberT", bound=np.number)

_ModeKind: TypeAlias = L["reduced", "complete", "r", "raw"]

Expand Down Expand Up @@ -182,33 +183,29 @@ def cholesky(a: _ArrayLikeFloat_co, /, *, upper: bool = False) -> NDArray[floati
def cholesky(a: _ArrayLikeComplex_co, /, *, upper: bool = False) -> NDArray[complexfloating]: ...

@overload
def outer(x1: _ArrayLike[Never], x2: _ArrayLike[Never]) -> NDArray[Any]: ...
def outer(x1: _ArrayLike[Never], x2: _ArrayLike[Never], /) -> NDArray[Any]: ...
@overload
def outer(x1: _ArrayLikeBool_co, x2: _ArrayLikeBool_co) -> NDArray[np.bool]: ...
def outer(x1: _ArrayLikeBool_co, x2: _ArrayLikeBool_co, /) -> NDArray[np.bool]: ...
@overload
def outer(x1: _ArrayLikeUInt_co, x2: _ArrayLikeUInt_co) -> NDArray[unsignedinteger]: ...
def outer(x1: _ArrayLike[_NumberT], x2: _ArrayLike[_NumberT], /) -> NDArray[_NumberT]: ...
@overload
def outer(x1: _ArrayLikeInt_co, x2: _ArrayLikeInt_co) -> NDArray[signedinteger]: ...
def outer(x1: _ArrayLikeUInt_co, x2: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ...
@overload
def outer(x1: _ArrayLikeFloat_co, x2: _ArrayLikeFloat_co) -> NDArray[floating]: ...
def outer(x1: _ArrayLikeInt_co, x2: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ...
@overload
def outer(
x1: _ArrayLikeComplex_co,
x2: _ArrayLikeComplex_co,
) -> NDArray[complexfloating]: ...
def outer(x1: _ArrayLikeFloat_co, x2: _ArrayLikeFloat_co, /) -> NDArray[floating]: ...
@overload
def outer(
x1: _ArrayLikeTD64_co,
x2: _ArrayLikeTD64_co,
out: None = ...,
) -> NDArray[timedelta64]: ...
def outer(x1: _ArrayLikeComplex_co, x2: _ArrayLikeComplex_co, /) -> NDArray[complexfloating]: ...
@overload
def outer(x1: _ArrayLikeTD64_co, x2: _ArrayLikeTD64_co, /) -> NDArray[timedelta64]: ...
@overload
def outer(x1: _ArrayLikeObject_co, x2: _ArrayLikeObject_co) -> NDArray[object_]: ...
def outer(x1: _ArrayLikeObject_co, x2: _ArrayLikeObject_co, /) -> NDArray[object_]: ...
@overload
def outer(
x1: _ArrayLikeComplex_co | _ArrayLikeTD64_co | _ArrayLikeObject_co,
x2: _ArrayLikeComplex_co | _ArrayLikeTD64_co | _ArrayLikeObject_co,
) -> _ArrayT: ...
/,
) -> NDArray[Any]: ...

@overload
def qr(a: _ArrayLikeInt_co, mode: _ModeKind = ...) -> QRResult: ...
Expand Down Expand Up @@ -308,20 +305,26 @@ def matrix_rank(
@overload
def pinv(
a: _ArrayLikeInt_co,
rcond: _ArrayLikeFloat_co = ...,
hermitian: bool = ...,
rcond: _ArrayLikeFloat_co | None = None,
hermitian: bool = False,
*,
rtol: _ArrayLikeFloat_co | _NoValueType = ...,
) -> NDArray[float64]: ...
@overload
def pinv(
a: _ArrayLikeFloat_co,
rcond: _ArrayLikeFloat_co = ...,
hermitian: bool = ...,
rcond: _ArrayLikeFloat_co | None = None,
hermitian: bool = False,
*,
rtol: _ArrayLikeFloat_co | _NoValueType = ...,
) -> NDArray[floating]: ...
@overload
def pinv(
a: _ArrayLikeComplex_co,
rcond: _ArrayLikeFloat_co = ...,
hermitian: bool = ...,
rcond: _ArrayLikeFloat_co | None = None,
hermitian: bool = False,
*,
rtol: _ArrayLikeFloat_co | _NoValueType = ...,
) -> NDArray[complexfloating]: ...

# TODO: Returns a 2-tuple of scalars for 2D arrays and
Expand Down Expand Up @@ -461,22 +464,12 @@ def cross(
) -> NDArray[complexfloating]: ...

@overload
def matmul(
x1: _ArrayLikeInt_co,
x2: _ArrayLikeInt_co,
) -> NDArray[signedinteger]: ...
def matmul(x1: _ArrayLike[_NumberT], x2: _ArrayLike[_NumberT], /) -> NDArray[_NumberT]: ...
@overload
def matmul(
x1: _ArrayLikeUInt_co,
x2: _ArrayLikeUInt_co,
) -> NDArray[unsignedinteger]: ...
def matmul(x1: _ArrayLikeInt_co, x2: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ...
@overload
def matmul(
x1: _ArrayLikeFloat_co,
x2: _ArrayLikeFloat_co,
) -> NDArray[floating]: ...
def matmul(x1: _ArrayLikeUInt_co, x2: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ...
@overload
def matmul(
x1: _ArrayLikeComplex_co,
x2: _ArrayLikeComplex_co,
) -> NDArray[complexfloating]: ...
def matmul(x1: _ArrayLikeFloat_co, x2: _ArrayLikeFloat_co, /) -> NDArray[floating]: ...
@overload
def matmul(x1: _ArrayLikeComplex_co, x2: _ArrayLikeComplex_co, /) -> NDArray[complexfloating]: ...
12 changes: 6 additions & 6 deletions numpy/typing/tests/data/reveal/linalg.pyi
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Expand Up @@ -43,9 +43,9 @@ assert_type(np.linalg.cholesky(AR_i8), npt.NDArray[np.float64])
assert_type(np.linalg.cholesky(AR_f8), npt.NDArray[np.floating])
assert_type(np.linalg.cholesky(AR_c16), npt.NDArray[np.complexfloating])

assert_type(np.linalg.outer(AR_i8, AR_i8), npt.NDArray[np.signedinteger])
assert_type(np.linalg.outer(AR_f8, AR_f8), npt.NDArray[np.floating])
assert_type(np.linalg.outer(AR_c16, AR_c16), npt.NDArray[np.complexfloating])
assert_type(np.linalg.outer(AR_i8, AR_i8), npt.NDArray[np.int64])
assert_type(np.linalg.outer(AR_f8, AR_f8), npt.NDArray[np.float64])
assert_type(np.linalg.outer(AR_c16, AR_c16), npt.NDArray[np.complex128])
assert_type(np.linalg.outer(AR_b, AR_b), npt.NDArray[np.bool])
assert_type(np.linalg.outer(AR_O, AR_O), npt.NDArray[np.object_])
assert_type(np.linalg.outer(AR_i8, AR_m), npt.NDArray[np.timedelta64])
Expand Down Expand Up @@ -127,6 +127,6 @@ assert_type(np.linalg.cross(AR_i8, AR_i8), npt.NDArray[np.signedinteger])
assert_type(np.linalg.cross(AR_f8, AR_f8), npt.NDArray[np.floating])
assert_type(np.linalg.cross(AR_c16, AR_c16), npt.NDArray[np.complexfloating])

assert_type(np.linalg.matmul(AR_i8, AR_i8), npt.NDArray[np.signedinteger])
assert_type(np.linalg.matmul(AR_f8, AR_f8), npt.NDArray[np.floating])
assert_type(np.linalg.matmul(AR_c16, AR_c16), npt.NDArray[np.complexfloating])
assert_type(np.linalg.matmul(AR_i8, AR_i8), npt.NDArray[np.int64])
assert_type(np.linalg.matmul(AR_f8, AR_f8), npt.NDArray[np.float64])
assert_type(np.linalg.matmul(AR_c16, AR_c16), npt.NDArray[np.complex128])
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