🚚 port numpy.ma.min

Co-Authored-By: Marco Edward Gorelli <[email protected]>
Co-Authored-By: Joren Hammudoglu <[email protected]>

Author: 3 people

src/numpy-stubs/@test/static/accept/ma.pyi

@@ -1,6 +1,8 @@
+from typing import Any, TypeAlias, TypeVar
 from typing_extensions import assert_type
 
 import numpy as np
+from numpy._typing import _Shape
 
 m: np.ma.MaskedArray[tuple[int], np.dtype[np.float64]]
 
@@ -10,3 +12,14 @@ assert_type(m.dtype, np.dtype[np.float64])
 
 assert_type(int(m), int)
 assert_type(float(m), float)
+
+_ScalarT_co = TypeVar("_ScalarT_co", bound=np.generic, covariant=True)
+MaskedNDArray: TypeAlias = np.ma.MaskedArray[_Shape, np.dtype[_ScalarT_co]]
+
+class MaskedNDArraySubclass(MaskedNDArray[np.complex128]): ...
+
+MAR_b: MaskedNDArray[np.bool]
+MAR_f4: MaskedNDArray[np.float32]
+MAR_i8: MaskedNDArray[np.int64]
+MAR_subclass: MaskedNDArraySubclass
+MAR_1d: np.ma.MaskedArray[tuple[int], np.dtype[Any]]

src/numpy-stubs/@test/static/reject/ma.pyi

@@ -4,3 +4,8 @@ m: np.ma.MaskedArray[tuple[int], np.dtype[np.float64]]
 
 m.shape = (3, 1)  # type: ignore[assignment]
 m.dtype = np.bool  # type: ignore[assignment]  # pyright: ignore[reportAttributeAccessIssue]
+
+np.amin(m, axis=1.0)  # type: ignore[call-overload] # pyright: ignore[reportArgumentType, reportCallIssue]
+np.amin(m, keepdims=1.0)  # type: ignore[call-overload] # pyright: ignore[reportArgumentType, reportCallIssue]
+np.amin(m, out=1.0)  # type: ignore[call-overload] # pyright: ignore[reportArgumentType, reportCallIssue]
+np.amin(m, fill_value=lambda x: 27)  # type: ignore[call-overload] # pyright: ignore[reportCallIssue, reportUnknownLambdaType]

src/numpy-stubs/ma/core.pyi

@@ -5,7 +5,8 @@ from typing_extensions import Never, Self, TypeVar, deprecated, overload, overri
 import numpy as np
 from _numtype import Array, ToGeneric_0d, ToGeneric_1nd, ToGeneric_nd
 from numpy import _OrderACF, _OrderKACF, amax, amin, bool_, expand_dims  # noqa: ICN003
-from numpy._typing import _BoolCodes
+from numpy._globals import _NoValueType
+from numpy._typing import ArrayLike, _ArrayLike, _BoolCodes, _ScalarLike_co, _ShapeLike
 
 __all__ = [
     "MAError",
@@ -188,7 +189,9 @@ __all__ = [
     "zeros_like",
 ]
 
+_ArrayT = TypeVar("_ArrayT", bound=np.ndarray[Any, Any])
 _UFuncT_co = TypeVar("_UFuncT_co", bound=np.ufunc, default=np.ufunc, covariant=True)
+_ScalarT = TypeVar("_ScalarT", bound=np.generic)
 _ShapeT = TypeVar("_ShapeT", bound=tuple[int, ...])
 _ShapeT_co = TypeVar("_ShapeT_co", bound=tuple[int, ...], default=tuple[int, ...], covariant=True)
 _DTypeT = TypeVar("_DTypeT", bound=np.dtype)
@@ -818,13 +821,41 @@ def array(
 ) -> Incomplete: ...
 
 #
+@overload
 def min(
-    obj: Incomplete,
-    axis: Incomplete = ...,
-    out: Incomplete = ...,
-    fill_value: Incomplete = ...,
-    keepdims: Incomplete = ...,
-) -> Incomplete: ...
+    obj: _ArrayLike[_ScalarT],
+    axis: None = None,
+    out: None = None,
+    fill_value: _ScalarLike_co | None = None,
+    keepdims: L[False] | _NoValueType = ...,
+) -> _ScalarT: ...
+@overload
+def min(
+    obj: ArrayLike,
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    fill_value: _ScalarLike_co | None = None,
+    keepdims: bool | _NoValueType = ...,
+) -> Any: ...
+@overload
+def min(
+    obj: ArrayLike,
+    axis: None,
+    out: _ArrayT,
+    fill_value: _ScalarLike_co | None = None,
+    keepdims: bool | _NoValueType = ...,
+) -> _ArrayT: ...
+@overload
+def min(
+    obj: ArrayLike,
+    axis: _ShapeLike | None = None,
+    *,
+    out: _ArrayT,
+    fill_value: _ScalarLike_co | None = None,
+    keepdims: bool | _NoValueType = ...,
+) -> _ArrayT: ...
+
+#
 def max(
     obj: Incomplete,
     axis: Incomplete = ...,