fix: uncap numpy

docs/changelog.md

@@ -2,6 +2,14 @@
 
 ## Version 1.5
 
+### Version 1.5.1
+
+#### Fixes
+
+- fix: uncap numpy [#502][]
+
+[#502]: https://github.com/scikit-hep/vector/pull/502
+
 ### Version 1.5.0
 
 #### Breaking

pyproject.toml

@@ -42,7 +42,7 @@ dynamic = [
   "version",
 ]
 dependencies = [
-  "numpy>=1.13.3,<2.1",
+  "numpy>=1.13.3",
   "packaging>=19",
 ]
 optional-dependencies.awkward = [

src/vector/backends/numpy.py

@@ -215,38 +215,38 @@
             )
         if hasattr(array, "_longitudinal_type"):
             longitudinal = array._longitudinal_type.ObjectClass(
-                *(out[x] for x in _coordinate_class_to_names[_ltype(array)])  # type: ignore[arg-type]
+                *(out[x] for x in _coordinate_class_to_names[_ltype(array)])
             )
         if hasattr(array, "_temporal_type"):
             temporal = array._temporal_type.ObjectClass(
-                *(out[x] for x in _coordinate_class_to_names[_ttype(array)])  # type: ignore[arg-type]
+                *(out[x] for x in _coordinate_class_to_names[_ttype(array)])
             )
         if temporal is not None:
             return array.ObjectClass(
                 azimuthal=azimuthal,
-                longitudinal=longitudinal,  # type: ignore[arg-type, return-value]
+                longitudinal=longitudinal,  # type: ignore[arg-type]
                 temporal=temporal,  # type: ignore[arg-type]
             )
         elif longitudinal is not None:
-            return array.ObjectClass(azimuthal=azimuthal, longitudinal=longitudinal)  # type: ignore[arg-type, return-value]
+            return array.ObjectClass(azimuthal=azimuthal, longitudinal=longitudinal)  # type: ignore[arg-type]
         elif azimuthal is not None:
-            return array.ObjectClass(azimuthal=azimuthal)  # type: ignore[return-value]
+            return array.ObjectClass(azimuthal=azimuthal)
         elif issubclass(array.ObjectClass, vector.backends.object.AzimuthalObject):
-            return array.ObjectClass(*tuple(out)[:2])  # type: ignore[arg-type, return-value]
+            return array.ObjectClass(*tuple(out)[:2])  # type: ignore[arg-type]
         elif issubclass(array.ObjectClass, vector.backends.object.LongitudinalObject):
             coords = (
                 out.view(numpy.ndarray)[0]
                 if len(out) == 1  # type: ignore[arg-type]
                 else out.view(numpy.ndarray)[2]
             )
-            return array.ObjectClass(coords)  # type: ignore[return-value]
+            return array.ObjectClass(coords)
         else:
             coords = (
                 out.view(numpy.ndarray)[0]
                 if len(out) == 1  # type: ignore[arg-type]
                 else out.view(numpy.ndarray)[3]
             )
-            return array.ObjectClass(coords)  # type: ignore[return-value]
+            return array.ObjectClass(coords)
 
 
 def _array_repr(
@@ -871,7 +871,7 @@
         return typing.cast(
             SameVectorNumpyType,
             # pylint: disable-next=unexpected-keyword-arg
             numpy.sum(
                 self,
                 axis=axis,
                 dtype=dtype,
@@ -879,14 +879,14 @@
                 keepdims=keepdims,
                 initial=initial,
                 where=where,
-            ),  # type: ignore[call-overload]
+            ),
         )
 
     def __eq__(self, other: typing.Any) -> typing.Any:
-        return numpy.equal(self, other)  # type: ignore[call-overload]
+        return numpy.equal(self, other)
 
     def __ne__(self, other: typing.Any) -> typing.Any:
-        return numpy.not_equal(self, other)  # type: ignore[call-overload]
+        return numpy.not_equal(self, other)
 
     def __reduce__(self) -> str | tuple[typing.Any, ...]:
         pickled_state = super().__reduce__()
@@ -1197,7 +1197,7 @@
             AzimuthalNumpyXY([(1.1, 2.1), (1.2, 2.2), (1.3, 2.3), (1.4, 2.4),
                               (1.5, 2.5)], dtype=[('x', '<f8'), ('y', '<f8')])
         """
-        return self.view(self._azimuthal_type)  # type: ignore[return-value]
+        return self.view(self._azimuthal_type)
 
     def _wrap_result(
         self,
@@ -1305,7 +1305,7 @@
         return _setitem(self, where, what, False)
 
 
-class MomentumNumpy2D(PlanarMomentum, VectorNumpy2D):  # type: ignore[misc]
+class MomentumNumpy2D(PlanarMomentum, VectorNumpy2D):
     """
     Two dimensional momentum vector class for the NumPy backend. This class can be directly
     used to construct two dimensional NumPy momentum vectors. For two dimensional
@@ -1427,13 +1427,13 @@
     def azimuthal(self) -> AzimuthalNumpy:
         """Returns the azimuthal type class for the given ``VectorNumpy3D`` object."""
         # TODO: Add an example here - see https://github.com/scikit-hep/vector/issues/194
-        return self.view(self._azimuthal_type)  # type: ignore[return-value]
+        return self.view(self._azimuthal_type)
 
     @property
     def longitudinal(self) -> LongitudinalNumpy:
         """Returns the longitudinal type class for the given ``VectorNumpy3D`` object."""
         # TODO: Add an example here - see https://github.com/scikit-hep/vector/issues/194
-        return self.view(self._longitudinal_type)  # type: ignore[return-value]
+        return self.view(self._longitudinal_type)
 
     def _wrap_result(
         self,
@@ -1562,7 +1562,7 @@
         return _setitem(self, where, what, False)
 
 
-class MomentumNumpy3D(SpatialMomentum, VectorNumpy3D):  # type: ignore[misc]
+class MomentumNumpy3D(SpatialMomentum, VectorNumpy3D):
     """
     Three dimensional momentum vector class for the NumPy backend. This class can be directly
     used to construct three dimensional NumPy momentum vectors. For three dimensional
@@ -1707,19 +1707,19 @@
     def azimuthal(self) -> AzimuthalNumpy:
         """Returns the azimuthal type class for the given ``VectorNumpy4D`` object."""
         # TODO: Add an example here - see https://github.com/scikit-hep/vector/issues/194
-        return self.view(self._azimuthal_type)  # type: ignore[return-value]
+        return self.view(self._azimuthal_type)
 
     @property
     def longitudinal(self) -> LongitudinalNumpy:
         """Returns the longitudinal type class for the given ``Vectornumpy4D`` object."""
         # TODO: Add an example here - see https://github.com/scikit-hep/vector/issues/194
-        return self.view(self._longitudinal_type)  # type: ignore[return-value]
+        return self.view(self._longitudinal_type)
 
     @property
     def temporal(self) -> TemporalNumpy:
         """Returns the azimuthal type class for the given ``VectorNumpy4D`` object."""
         # TODO: Add an example here - see https://github.com/scikit-hep/vector/issues/194
-        return self.view(self._temporal_type)  # type: ignore[return-value]
+        return self.view(self._temporal_type)
 
     def _wrap_result(
         self,
@@ -1882,7 +1882,7 @@
         return _setitem(self, where, what, False)
 
 
-class MomentumNumpy4D(LorentzMomentum, VectorNumpy4D):  # type: ignore[misc]
+class MomentumNumpy4D(LorentzMomentum, VectorNumpy4D):
     """
     Four dimensional momentum vector class for the NumPy backend. This class can be directly
     used to construct four dimensional NumPy momentum vectors. For three dimensional

src/vector/backends/object.py

@@ -332,61 +332,61 @@ class VectorObject(Vector):
     lib = numpy
 
     def __eq__(self, other: typing.Any) -> typing.Any:
-        return numpy.equal(self, other)  # type: ignore[call-overload]
+        return numpy.equal(self, other)
 
     def __ne__(self, other: typing.Any) -> typing.Any:
-        return numpy.not_equal(self, other)  # type: ignore[call-overload]
+        return numpy.not_equal(self, other)
 
     def __abs__(self) -> float:
         return numpy.absolute(self)
 
     def __add__(self, other: VectorProtocol) -> VectorProtocol:
-        return numpy.add(self, other)  # type: ignore[call-overload]
+        return numpy.add(self, other)
 
     def __radd__(self, other: VectorProtocol) -> VectorProtocol:
-        return numpy.add(other, self)  # type: ignore[call-overload]
+        return numpy.add(other, self)
 
     def __iadd__(self: SameVectorType, other: VectorProtocol) -> SameVectorType:
-        return _replace_data(self, numpy.add(self, other))  # type: ignore[call-overload]
+        return _replace_data(self, numpy.add(self, other))
 
     def __sub__(self, other: VectorProtocol) -> VectorProtocol:
-        return numpy.subtract(self, other)  # type: ignore[call-overload]
+        return numpy.subtract(self, other)
 
     def __rsub__(self, other: VectorProtocol) -> VectorProtocol:
-        return numpy.subtract(other, self)  # type: ignore[call-overload]
+        return numpy.subtract(other, self)
 
     def __isub__(self: SameVectorType, other: VectorProtocol) -> SameVectorType:
-        return _replace_data(self, numpy.subtract(self, other))  # type: ignore[call-overload]
+        return _replace_data(self, numpy.subtract(self, other))
 
     def __mul__(self, other: float) -> VectorProtocol:
-        return numpy.multiply(self, other)  # type: ignore[call-overload]
+        return numpy.multiply(self, other)
 
     def __rmul__(self, other: float) -> VectorProtocol:
-        return numpy.multiply(other, self)  # type: ignore[call-overload]
+        return numpy.multiply(other, self)
 
     def __imul__(self: SameVectorType, other: float) -> SameVectorType:
-        return _replace_data(self, numpy.multiply(self, other))  # type: ignore[call-overload]
+        return _replace_data(self, numpy.multiply(self, other))
 
     def __neg__(self: SameVectorType) -> SameVectorType:
-        return numpy.negative(self)  # type: ignore[call-overload]
+        return numpy.negative(self)
 
     def __pos__(self: SameVectorType) -> SameVectorType:
-        return numpy.positive(self)  # type: ignore[call-overload]
+        return numpy.positive(self)
 
     def __truediv__(self, other: float) -> VectorProtocol:
-        return numpy.true_divide(self, other)  # type: ignore[call-overload]
+        return numpy.true_divide(self, other)
 
     def __rtruediv__(self, other: float) -> VectorProtocol:
-        return numpy.true_divide(other, self)  # type: ignore[call-overload]
+        return numpy.true_divide(other, self)
 
     def __itruediv__(self: SameVectorType, other: float) -> VectorProtocol:
-        return _replace_data(self, numpy.true_divide(self, other))  # type: ignore[call-overload]
+        return _replace_data(self, numpy.true_divide(self, other))
 
     def __pow__(self, other: float) -> float:
-        return numpy.square(self) if other == 2 else numpy.power(self, other)  # type: ignore[call-overload]
+        return numpy.square(self) if other == 2 else numpy.power(self, other)
 
     def __matmul__(self, other: VectorProtocol) -> float:
-        return numpy.matmul(self, other)  # type: ignore[call-overload]
+        return numpy.matmul(self, other)
 
     def __array_ufunc__(
         self,

src/vector/backends/sympy.py

@@ -345,61 +345,61 @@ class VectorSympy(Vector):
     lib = SympyLib()
 
     def __eq__(self, other: typing.Any) -> typing.Any:
-        return numpy.equal(self, other)  # type: ignore[call-overload]
+        return numpy.equal(self, other)
 
     def __ne__(self, other: typing.Any) -> typing.Any:
-        return numpy.not_equal(self, other)  # type: ignore[call-overload]
+        return numpy.not_equal(self, other)
 
     def __abs__(self) -> float:
         return numpy.absolute(self)
 
     def __add__(self, other: VectorProtocol) -> VectorProtocol:
-        return numpy.add(self, other)  # type: ignore[call-overload]
+        return numpy.add(self, other)
 
     def __radd__(self, other: VectorProtocol) -> VectorProtocol:
-        return numpy.add(other, self)  # type: ignore[call-overload]
+        return numpy.add(other, self)
 
     def __iadd__(self: SameVectorType, other: VectorProtocol) -> SameVectorType:
-        return _replace_data(self, numpy.add(self, other))  # type: ignore[call-overload]
+        return _replace_data(self, numpy.add(self, other))
 
     def __sub__(self, other: VectorProtocol) -> VectorProtocol:
-        return numpy.subtract(self, other)  # type: ignore[call-overload]
+        return numpy.subtract(self, other)
 
     def __rsub__(self, other: VectorProtocol) -> VectorProtocol:
-        return numpy.subtract(other, self)  # type: ignore[call-overload]
+        return numpy.subtract(other, self)
 
     def __isub__(self: SameVectorType, other: VectorProtocol) -> SameVectorType:
-        return _replace_data(self, numpy.subtract(self, other))  # type: ignore[call-overload]
+        return _replace_data(self, numpy.subtract(self, other))
 
     def __mul__(self, other: float) -> VectorProtocol:
-        return numpy.multiply(self, other)  # type: ignore[call-overload]
+        return numpy.multiply(self, other)
 
     def __rmul__(self, other: float) -> VectorProtocol:
-        return numpy.multiply(other, self)  # type: ignore[call-overload]
+        return numpy.multiply(other, self)
 
     def __imul__(self: SameVectorType, other: float) -> SameVectorType:
-        return _replace_data(self, numpy.multiply(self, other))  # type: ignore[call-overload]
+        return _replace_data(self, numpy.multiply(self, other))
 
     def __neg__(self: SameVectorType) -> SameVectorType:
-        return numpy.negative(self)  # type: ignore[call-overload]
+        return numpy.negative(self)
 
     def __pos__(self: SameVectorType) -> SameVectorType:
-        return numpy.positive(self)  # type: ignore[call-overload]
+        return numpy.positive(self)
 
     def __truediv__(self, other: float) -> VectorProtocol:
-        return numpy.true_divide(self, other)  # type: ignore[call-overload]
+        return numpy.true_divide(self, other)
 
     def __rtruediv__(self, other: float) -> VectorProtocol:
-        return numpy.true_divide(other, self)  # type: ignore[call-overload]
+        return numpy.true_divide(other, self)
 
     def __itruediv__(self: SameVectorType, other: float) -> VectorProtocol:
-        return _replace_data(self, numpy.true_divide(self, other))  # type: ignore[call-overload]
+        return _replace_data(self, numpy.true_divide(self, other))
 
     def __pow__(self, other: float) -> float:
-        return numpy.power(self, other)  # type: ignore[call-overload]
+        return numpy.power(self, other)
 
     def __matmul__(self, other: VectorProtocol) -> float:
-        return numpy.matmul(self, other)  # type: ignore[call-overload]
+        return numpy.matmul(self, other)
 
     def __array_ufunc__(
         self,