Skip to content

👽️ _core.numeric sync with upstream #792

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
jorenham merged 8 commits into from
Dec 28, 2025
Merged

👽️ _core.numeric sync with upstream #792

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
8 commits
Select commit Hold shift + click to select a range
325cf81
👽️ `count_nonzero` sync with upstream
jorenham Dec 28, 2025
f0b7e70
👽️ `argwhere` sync with upstream
jorenham Dec 28, 2025
ad8a632
👽️ `indices` sync with upstream
jorenham Dec 28, 2025
3970b00
👽️ `identity` sync with upstream
jorenham Dec 28, 2025
19f9cab
👽️ `isclose` sync with upstream
jorenham Dec 28, 2025
4a19e66
🏷️ prefer `_numtype.Array` over a bare `ndarray`
jorenham Dec 28, 2025
8197926
🩹 fix `isclose` shape-typing issue
jorenham Dec 28, 2025
7df277c
✅ update `_core.numeric` type-tests
jorenham Dec 28, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion src/numpy-stubs/@test/static/accept/array_constructors.pyi
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -263,7 +263,7 @@ assert_type(np.fromfunction(func, (3, 5)), MyArray[np.float64])

assert_type(np.identity(10), _nt.Array2D[np.float64])
assert_type(np.identity(10, dtype=np.int64), _nt.Array2D[np.int64])
assert_type(np.identity(10, dtype=int), _nt.Array2D)
assert_type(np.identity(10, dtype=int), _nt.Array2D[np.int64])

assert_type(np.atleast_1d(A), _nt.Array[np.float64])
assert_type(np.atleast_1d(C), _nt.Array)
Expand Down
8 changes: 4 additions & 4 deletions src/numpy-stubs/@test/static/accept/numeric.pyi
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -25,14 +25,14 @@ AR_O: _nt.Array[np.object_]
assert_type(np.count_nonzero(i8), np.intp)
assert_type(np.count_nonzero(AR_i8), np.intp)
assert_type(np.count_nonzero(ints), np.intp)
assert_type(np.count_nonzero(AR_i8, keepdims=True), Any)
assert_type(np.count_nonzero(AR_i8, keepdims=True), np.intp)
assert_type(np.count_nonzero(AR_i8, axis=0), Any)

assert_type(np.isfortran(i8), bool)
assert_type(np.isfortran(AR_i8), bool)

assert_type(np.argwhere(i8), _nt.Array[np.intp])
assert_type(np.argwhere(AR_i8), _nt.Array[np.intp])
assert_type(np.argwhere(i8), _nt.Array2D[np.intp])
assert_type(np.argwhere(AR_i8), _nt.Array2D[np.intp])

assert_type(np.flatnonzero(i8), _nt.Array1D[np.intp])
assert_type(np.flatnonzero(AR_i8), _nt.Array1D[np.intp])
Expand Down Expand Up @@ -121,7 +121,7 @@ assert_type(np.allclose(AR_i8, AR_i8), bool)

assert_type(np.isclose(i8, i8), np.bool)
assert_type(np.isclose(i8, AR_i8), _nt.Array[np.bool])
assert_type(np.isclose(ints, AR_i8), _nt.Array[np.bool])
assert_type(np.isclose(ints, AR_i8), _nt.Array1D[np.bool])
assert_type(np.isclose(AR_i8, AR_i8), _nt.Array[np.bool])

assert_type(np.array_equal(i8, AR_i8), bool)
Expand Down
172 changes: 125 additions & 47 deletions src/numpy-stubs/_core/numeric.pyi
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2030,11 +2030,15 @@ def full_like(
@overload
def count_nonzero(a: ArrayLike, axis: None = None, *, keepdims: L[False] = False) -> np.intp: ...
@overload
def count_nonzero(a: _nt.ToGeneric_0d, axis: _ShapeLike | None = None, *, keepdims: L[True]) -> np.intp: ...
@overload
def count_nonzero(a: _nt.ToGeneric_1nd, axis: _ShapeLike | None = None, *, keepdims: L[True]) -> _nt.Array[np.intp]: ...
@overload
def count_nonzero(a: ArrayLike, axis: _ShapeLike | None = None, *, keepdims: py_bool = False) -> Incomplete: ...

#
def flatnonzero(a: ArrayLike) -> _nt.Array1D[np.intp]: ...
def argwhere(a: ArrayLike) -> _nt.Array[np.intp]: ...
def argwhere(a: ArrayLike) -> _nt.Array2D[np.intp]: ...

#
def isfortran(a: _nt.Array | np.generic) -> py_bool: ...
Expand Down Expand Up @@ -2071,7 +2075,7 @@ def correlate(
a: _nt.CoComplex_1d | _nt.CoTimeDelta_1d | _nt.ToObject_1d,
v: _nt.CoComplex_1d | _nt.CoTimeDelta_1d | _nt.ToObject_1d,
mode: _Mode = "valid",
) -> _nt.Array1D[Any]: ...
) -> _nt.Array1D: ...

#
@overload
Expand Down Expand Up @@ -2103,7 +2107,7 @@ def convolve(
a: _nt.CoComplex_1d | _nt.CoTimeDelta_1d | _nt.ToObject_1d,
v: _nt.CoComplex_1d | _nt.CoTimeDelta_1d | _nt.ToObject_1d,
mode: _Mode = "full",
) -> _nt.Array1D[Any]: ...
) -> _nt.Array1D: ...

#
@overload
Expand Down Expand Up @@ -2267,42 +2271,68 @@ def cross(
) -> _nt.Array[Any]: ...

#
@overload
@overload # 0d, dtype=int (default), sparse=False (default)
def indices(dimensions: tuple[()], dtype: type[int] = int, sparse: L[False] = False) -> _nt.Array1D[np.intp]: ... # noqa: PYI011
@overload # 0d, dtype=<irrelevant>, sparse=True
def indices(dimensions: tuple[()], dtype: DTypeLike | None = int, *, sparse: L[True]) -> tuple[()]: ... # noqa: PYI011
@overload # 0d, dtype=<known>, sparse=False (default)
def indices(dimensions: tuple[()], dtype: _DTypeLike[_ScalarT], sparse: L[False] = False) -> _nt.Array1D[_ScalarT]: ...
@overload # 0d, dtype=<unknown>, sparse=False (default)
def indices(dimensions: tuple[()], dtype: DTypeLike, sparse: L[False] = False) -> _nt.Array1D: ...
@overload # 1d, dtype=int (default), sparse=False (default)
def indices(dimensions: tuple[int], dtype: type[int] = int, sparse: L[False] = False) -> _nt.Array2D[np.intp]: ... # noqa: PYI011
@overload # 1d, dtype=int (default), sparse=True
def indices(dimensions: tuple[int], dtype: type[int] = int, *, sparse: L[True]) -> tuple[_nt.Array1D[np.intp]]: ... # noqa: PYI011
@overload # 1d, dtype=<known>, sparse=False (default)
def indices(dimensions: tuple[int], dtype: _DTypeLike[_ScalarT], sparse: L[False] = False) -> _nt.Array2D[_ScalarT]: ...
@overload # 1d, dtype=<known>, sparse=True
def indices(dimensions: tuple[int], dtype: _DTypeLike[_ScalarT], sparse: L[True]) -> tuple[_nt.Array1D[_ScalarT]]: ...
@overload # 1d, dtype=<unknown>, sparse=False (default)
def indices(dimensions: tuple[int], dtype: DTypeLike, sparse: L[False] = False) -> _nt.Array2D: ...
@overload # 1d, dtype=<unknown>, sparse=True
def indices(dimensions: tuple[int], dtype: DTypeLike, sparse: L[True]) -> tuple[_nt.Array1D]: ...
@overload # 2d, dtype=int (default), sparse=False (default)
def indices(dimensions: tuple[int, int], dtype: type[int] = int, sparse: L[False] = False) -> _nt.Array3D[np.intp]: ... # noqa: PYI011
@overload # 2d, dtype=int (default), sparse=True
def indices(
dimensions: _nt.ToInteger_1d,
dtype: type[_nt.JustInt] = int, # noqa: PYI011
sparse: L[False] = False,
) -> _nt.Array[np.intp]: ...
@overload
dimensions: tuple[int, int],
dtype: type[int] = int, # noqa: PYI011
*,
sparse: L[True],
) -> tuple[_nt.Array2D[np.intp], _nt.Array2D[np.intp]]: ...
@overload # 2d, dtype=<known>, sparse=False (default)
def indices(
dimensions: _nt.ToInteger_1d, dtype: type[_nt.JustInt], sparse: L[True]
) -> tuple[_nt.Array[np.intp], ...]: ...
@overload
dimensions: tuple[int, int], dtype: _DTypeLike[_ScalarT], sparse: L[False] = False
) -> _nt.Array3D[_ScalarT]: ...
@overload # 2d, dtype=<known>, sparse=True
def indices(
dimensions: _nt.ToInteger_1d,
dtype: type[_nt.JustInt] = int, # noqa: PYI011
dimensions: tuple[int, int], dtype: _DTypeLike[_ScalarT], sparse: L[True]
) -> tuple[_nt.Array2D[_ScalarT], _nt.Array2D[_ScalarT]]: ...
@overload # 2d, dtype=<unknown>, sparse=False (default)
def indices(dimensions: tuple[int, int], dtype: DTypeLike, sparse: L[False] = False) -> _nt.Array3D: ...
@overload # 2d, dtype=<unknown>, sparse=True
def indices(dimensions: tuple[int, int], dtype: DTypeLike, sparse: L[True]) -> tuple[_nt.Array2D, _nt.Array2D]: ...
@overload # ?d, dtype=int (default), sparse=False (default)
def indices(dimensions: Sequence[int], dtype: type[int] = int, sparse: L[False] = False) -> _nt.Array[np.intp]: ... # noqa: PYI011
@overload # ?d, dtype=int (default), sparse=True
def indices(
dimensions: Sequence[int],
dtype: type[int] = int, # noqa: PYI011
*,
sparse: L[True],
) -> tuple[_nt.Array[np.intp], ...]: ...
@overload
@overload # ?d, dtype=<known>, sparse=False (default)
def indices(
dimensions: _nt.ToInteger_1d, dtype: _DTypeLike[_ScalarT], sparse: L[False] = False
dimensions: Sequence[int], dtype: _DTypeLike[_ScalarT], sparse: L[False] = False
) -> _nt.Array[_ScalarT]: ...
@overload
@overload # ?d, dtype=<known>, sparse=True
def indices(
dimensions: _nt.ToInteger_1d, dtype: _DTypeLike[_ScalarT], sparse: L[True]
dimensions: Sequence[int], dtype: _DTypeLike[_ScalarT], sparse: L[True]
) -> tuple[_nt.Array[_ScalarT], ...]: ...
@overload
def indices(dimensions: _nt.ToInteger_1d, dtype: DTypeLike | None = int, sparse: L[False] = False) -> _nt.Array: ... # noqa: PYI011
@overload
def indices(dimensions: _nt.ToInteger_1d, dtype: DTypeLike | None, sparse: L[True]) -> tuple[_nt.Array, ...]: ...
@overload
def indices(
dimensions: _nt.ToInteger_1d,
dtype: DTypeLike | None = int, # noqa: PYI011
*,
sparse: L[True],
) -> tuple[_nt.Array, ...]: ...
@overload # ?d, dtype=<unknown>, sparse=False (default)
def indices(dimensions: Sequence[int], dtype: DTypeLike, sparse: L[False] = False) -> ndarray: ...
@overload # ?d, dtype=<unknown>, sparse=True
def indices(dimensions: Sequence[int], dtype: DTypeLike, sparse: L[True]) -> tuple[ndarray, ...]: ...

# keep in sync with `ma.core.fromfunction`
def fromfunction(
Expand All @@ -2322,45 +2352,93 @@ def binary_repr(num: SupportsIndex, width: int | None = None) -> str: ...
def base_repr(number: SupportsAbs[float], base: float = 2, padding: SupportsIndex = 0) -> str: ...

#
@overload
@overload # dtype: None (default)
def identity(n: int, dtype: None = None, *, like: _SupportsArrayFunc | None = None) -> _nt.Array2D[np.float64]: ...
@overload
@overload # dtype: known scalar type
def identity(
n: int, dtype: _DTypeLike[_ScalarT], *, like: _SupportsArrayFunc | None = None
) -> _nt.Array2D[_ScalarT]: ...
@overload
def identity(n: int, dtype: DTypeLike | None = None, *, like: _SupportsArrayFunc | None = None) -> _nt.Array2D: ...
@overload # dtype: like bool
def identity(n: int, dtype: _nt.ToDTypeBool, *, like: _SupportsArrayFunc | None = None) -> _nt.Array2D[np.bool]: ...
@overload # dtype: like int_
def identity(n: int, dtype: _nt.ToDTypeInt64, *, like: _SupportsArrayFunc | None = None) -> _nt.Array2D[np.int64]: ...
@overload # dtype: like float64
def identity(
n: int, dtype: _nt.ToDTypeFloat64, *, like: _SupportsArrayFunc | None = None
) -> _nt.Array2D[np.float64]: ...
@overload # dtype: like complex128
def identity(
n: int, dtype: _nt.ToDTypeComplex128, *, like: _SupportsArrayFunc | None = None
) -> _nt.Array2D[np.complex128]: ...
@overload # dtype: unknown
def identity(n: int, dtype: DTypeLike, *, like: _SupportsArrayFunc | None = None) -> _nt.Array2D[Incomplete]: ...

#
def allclose(
a: ArrayLike, b: ArrayLike, rtol: ArrayLike = 1e-5, atol: ArrayLike = 1e-8, equal_nan: py_bool = False
) -> py_bool: ...

#
@overload
@overload # scalar, scalar
def isclose(
a: np.generic | _nt._PyScalar,
b: np.generic | _nt._PyScalar,
a: _nt.co_complex | complex,
b: _nt.co_complex | complex,
rtol: ArrayLike = 1e-5,
atol: ArrayLike = 1e-8,
equal_nan: py_bool = False,
) -> np.bool: ...
@overload
) -> np.bool_: ...
@overload # known shape, same shape or scalar
def isclose(
a: _nt.ToGeneric_1nd,
b: _nt.ToGeneric_nd,
a: np.ndarray[_ShapeT],
b: np.ndarray[_ShapeT] | _nt.CoComplex_0d,
rtol: ArrayLike = 1e-5,
atol: ArrayLike = 1e-8,
equal_nan: py_bool = False,
) -> _nt.Array[np.bool]: ...
@overload
) -> _nt.Array[np.bool_, _ShapeT]: ...
@overload # same shape or scalar, known shape
def isclose(
a: _nt.ToGeneric_nd,
b: _nt.ToGeneric_1nd,
a: np.ndarray[_ShapeT] | _nt.CoComplex_0d,
b: np.ndarray[_ShapeT],
rtol: ArrayLike = 1e-5,
atol: ArrayLike = 1e-8,
equal_nan: py_bool = False,
) -> _nt.Array[np.bool]: ...
) -> _nt.Array[np.bool_, _ShapeT]: ...
@overload # 1d sequence, <=1d array-like
def isclose(
a: _nt.CoComplex_1ds,
b: _nt.CoComplex_1ds | _nt.CoComplex_0d,
rtol: ArrayLike = 1e-5,
atol: ArrayLike = 1e-8,
equal_nan: py_bool = False,
) -> _nt.Array1D[np.bool_]: ...
@overload # <=1d array-like, 1d sequence
def isclose(
a: _nt.CoComplex_1ds | _nt.CoComplex_0d,
b: _nt.CoComplex_1ds,
rtol: ArrayLike = 1e-5,
atol: ArrayLike = 1e-8,
equal_nan: py_bool = False,
) -> _nt.Array1D[np.bool_]: ...
@overload # 2d sequence, <=2d array-like
def isclose(
a: _nt.CoComplex_2ds,
b: _nt.CoComplex_2ds | _nt.CoComplex_1ds | _nt.CoComplex_0d,
rtol: ArrayLike = 1e-5,
atol: ArrayLike = 1e-8,
equal_nan: py_bool = False,
) -> _nt.Array1D[np.bool_]: ...
@overload # <=2d array-like, 2d sequence
def isclose(
b: _nt.CoComplex_2ds | _nt.CoComplex_1ds | _nt.CoComplex_0d,
a: _nt.CoComplex_2ds,
rtol: ArrayLike = 1e-5,
atol: ArrayLike = 1e-8,
equal_nan: py_bool = False,
) -> _nt.Array1D[np.bool_]: ...
@overload # unknown shape, unknown shape
def isclose(
a: ArrayLike, b: ArrayLike, rtol: ArrayLike = 1e-5, atol: ArrayLike = 1e-8, equal_nan: py_bool = False
) -> _nt.Array[np.bool_] | Any: ...

#
def array_equal(a1: ArrayLike, a2: ArrayLike, equal_nan: py_bool = False) -> py_bool: ...
Expand All @@ -2370,8 +2448,8 @@ def array_equiv(a1: ArrayLike, a2: ArrayLike) -> py_bool: ...
@overload
def astype(
x: _nt.Array[Any, _ShapeT], dtype: _DTypeLike[_ScalarT], /, *, copy: py_bool = True, device: _Device | None = None
) -> ndarray[_ShapeT, dtype[_ScalarT]]: ...
) -> _nt.Array[_ScalarT, _ShapeT]: ...
@overload
def astype(
x: _nt.Array[Any, _ShapeT], dtype: DTypeLike | None, /, *, copy: py_bool = True, device: _Device | None = None
) -> ndarray[_ShapeT, dtype]: ...
) -> _nt.Array[Incomplete, _ShapeT]: ...