⬆️ optype 0.14.0 (#899)

Author: jorenham

pyproject.toml

@@ -36,7 +36,7 @@ classifiers = [
   "Typing :: Stubs Only",
 ]
 requires-python = ">=3.11"
-dependencies = ["optype[numpy]>=0.13.4,<0.14"]
+dependencies = ["optype[numpy]>=0.14.0"]
 
 [project.optional-dependencies]
 scipy = ["scipy>=1.16.2,<1.17"]

scipy-stubs/differentiate/_differentiate.pyi

@@ -68,7 +68,7 @@ class _HessianResult(_RichResult, Generic[_FloatT_co, _ShapeT2_co]):
 @overload  # 0-d float64
 def derivative(
     f: _Function00[np.float64],
-    x: float | np.float64 | npc.integer | onp.CanArray0D[np.float64 | npc.integer],
+    x: float | onp.CanArray0[np.float64 | npc.integer],
     *,
     args: tuple[onp.ToScalar, ...] = (),
     tolerances: _Tolerances | None = None,
@@ -83,7 +83,7 @@ def derivative(
 @overload  # 0-d <known>
 def derivative(
     f: _Function00[_FloatT],
-    x: _FloatT | onp.CanArray0D[_FloatT],
+    x: onp.CanArray0[_FloatT],
     *,
     args: tuple[onp.ToScalar, ...] = (),
     tolerances: _Tolerances | None = None,

scipy-stubs/linalg/_special_matrices.pyi

@@ -43,7 +43,7 @@ _Float3ND: TypeAlias = _Array3ND[np.float64]
 _Complex2D: TypeAlias = onp.Array2D[np.complex128]
 _Complex3ND: TypeAlias = _Array3ND[np.complex128]
 
-_To0D: TypeAlias = _SCT | onp.CanArray0D[_SCT]
+_To0D: TypeAlias = onp.CanArray0[_SCT]
 _To1D: TypeAlias = Sequence[_To0D[_SCT]] | onp.CanArrayND[_SCT]
 _ToStrict1D: TypeAlias = Sequence[_To0D[_SCT]] | onp.CanArray1D[_SCT]
 _ToStrict2ND: TypeAlias = onp.SequenceND[_To1D[_SCT]] | onp.CanArrayND[_SCT, onp.AtLeast2D]