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Fix NaN-aware reductions and NumPy 2 output units #276

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Merged
apdavison merged 2 commits into from
Oct 14, 2026
Merged

Fix NaN-aware reductions and NumPy 2 output units #276

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113e03c
Fix NaN-aware reductions and NumPy 2 output units
ac1982 Oct 13, 2026
700f856
Reject ufunc output unit changes on Quantity views
ac1982 Oct 14, 2026
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67 changes: 18 additions & 49 deletions quantities/quantity.py
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Original file line number Diff line number Diff line change
Expand Up @@ -311,13 +311,17 @@ def __array_prepare__(self, obj, context=None):
return obj

try:
res._dimensionality = p_dict[uf](*objs)
dimensionality = p_dict[uf](*objs)
except KeyError:
raise ValueError(
"""ufunc %r not supported by quantities
please file a bug report at https://github.com/python-quantities
""" % uf
)
if (isinstance(res.base, Quantity)
and res._dimensionality != dimensionality):
raise ValueError('can not modify units of a view of a Quantity')
res._dimensionality = dimensionality
return res

def __array_wrap__(self, obj, context=None, return_scalar=False):
Expand All @@ -328,12 +332,9 @@ def __array_wrap__(self, obj, context=None, return_scalar=False):
return self.__array_prepare__(obj, context)
else:
return obj
# For NumPy > 2.0 we either do the prepare or the wrap
# NumPy 2 no longer calls __array_prepare__, even for Quantity outputs.
else:
if not isinstance(obj, Quantity):
return self.__array_prepare__(obj, context)
else:
return super().__array_wrap__(obj, context, return_scalar)
return self.__array_prepare__(obj, context)


@with_doc(np.ndarray.__add__)
Expand Down Expand Up @@ -379,22 +380,7 @@ def __imod__(self, other):
@with_doc(np.ndarray.__imul__)
@protected_multiplication
def __imul__(self, other):
# the following is an inelegant fix for the removal of __array_prepare__ in NumPy 2.x
# the longer-term solution is probably to implement __array_ufunc__
# See:
# - https://numpy.org/devdocs/release/2.0.0-notes.html#array-prepare-is-removed
# - https://numpy.org/neps/nep-0013-ufunc-overrides.html
if _np_version < (2, 0, 0):
return super().__imul__(other)
else:
cself = self.copy()
if hasattr(other, "copy"):
cother = other.copy()
else:
cother = other
res = super().__imul__(other)
context = (np.multiply, (cself, cother, cself), 0)
return self.__array_prepare__(res, context=context)
return super().__imul__(other)

@with_doc(np.ndarray.__rmul__)
def __rmul__(self, other):
Expand All @@ -403,18 +389,7 @@ def __rmul__(self, other):
@with_doc(np.ndarray.__itruediv__)
@protected_multiplication
def __itruediv__(self, other):
# see comment above on __imul__
if _np_version < (2, 0, 0):
return super().__itruediv__(other)
else:
cself = self.copy()
if hasattr(other, "copy"):
cother = other.copy()
else:
cother = other
res = super().__itruediv__(other)
context = (np.true_divide, (cself, cother, cself), 0)
return self.__array_prepare__(res, context=context)
return super().__itruediv__(other)

@with_doc(np.ndarray.__rtruediv__)
def __rtruediv__(self, other):
Expand All @@ -429,18 +404,9 @@ def __pow__(self, other):
@check_uniform
@protected_power
def __ipow__(self, other):
# see comment above on __imul__
if _np_version < (2, 0, 0):
return super().__ipow__(other)
else:
cself = self.copy()
if hasattr(other, "copy"):
cother = other.copy()
else:
cother = other
res = super().__ipow__(other)
context = (np.power, (cself, cother, cself), 0)
return self.__array_prepare__(res, context=context)
# The exponent can share our magnitude buffer. Keep its original value
# for the dimensionality calculation performed after the ufunc.
return super().__ipow__(other.copy())

def __round__(self, decimals=0):
return np.around(self, decimals)
Expand Down Expand Up @@ -552,8 +518,11 @@ def _tolist(self, work_list):
# item, itemset, tofile, dump, byteswap

@with_doc(np.ndarray.sum)
def sum(self, axis=None, dtype=None, out=None):
ret = self.magnitude.sum(axis, dtype, None if out is None else out.magnitude)
def sum(self, axis=None, dtype=None, out=None, keepdims=False):
ret = self.magnitude.sum(
axis, dtype, None if out is None else out.magnitude,
keepdims=keepdims
)
dim = self.dimensionality
if out is None:
return Quantity(ret, dim)
Expand Down Expand Up @@ -692,7 +661,7 @@ def clip(self, min=None, max=None, out=None):
clipped = self.magnitude.clip(
min.rescale(self._dimensionality).magnitude,
max.rescale(self._dimensionality).magnitude,
out
None if out is None else out.magnitude
)
dim = self.dimensionality
if out is None:
Expand Down
1 change: 1 addition & 0 deletions quantities/tests/test_methods.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,7 @@ def test_sum(self):
self.assertQuantityEqual(self.q.sum(), 10*pq.m)
self.assertQuantityEqual(self.q.sum(0), [4, 6]*pq.m)
self.assertQuantityEqual(self.q.sum(1), [3, 7]*pq.m)
self.assertQuantityEqual(self.q.sum(1, keepdims=True), [[3], [7]]*pq.m)

def test_nansum(self):
import numpy as np
Expand Down
68 changes: 68 additions & 0 deletions quantities/tests/test_umath.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,74 @@ def test_nansum(self):
c = [1,2,3, np.nan] * pq.m
self.assertQuantityEqual(np.nansum(c), 6 * pq.m)

def test_nan_variance_and_standard_deviation(self):
values = np.array([[1., np.nan, 5.], [2., 4., 8.]])
for data in (values, values + 1j * values):
q = data * pq.ms
for func, units in ((np.nanvar, pq.ms**2), (np.nanstd, pq.ms)):
for axis in (None, 0, 1):
for keepdims in (False, True):
with self.subTest(func=func, axis=axis, keepdims=keepdims,
dtype=data.dtype):
expected = func(data, axis=axis, keepdims=keepdims)
result = func(q, axis=axis, keepdims=keepdims)
self.assertQuantityEqual(result, expected * units)
out = np.zeros_like(expected) * pq.kg
self.assertIs(func(q, axis=axis, keepdims=keepdims,
out=out), out)
self.assertQuantityEqual(out, expected * units)
self.assertQuantityEqual(np.nanstd(q, ddof=1),
np.nanstd(data, ddof=1) * pq.ms)
np.testing.assert_array_equal(q.magnitude, data)
self.assertEqual(q.units, pq.ms)

def test_ufunc_output_units(self):
q = [2., 4.] * pq.m
out = [0., 0.] * pq.s
self.assertIs(np.multiply(q, q, out=out), out)
self.assertQuantityEqual(out, [4., 16.] * pq.m**2)
self.assertIs(np.sqrt(out, out=out), out)
self.assertQuantityEqual(out, q)
self.assertIs(np.divide(out, q, out=out), out)
self.assertQuantityEqual(out, [1., 1.] * pq.dimensionless)
q **= 2
self.assertQuantityEqual(q, [4., 16.] * pq.m**2)
scalar = 2. * pq.m
scalar **= scalar.magnitude
self.assertQuantityEqual(scalar, 4. * pq.m**2)

def test_ufunc_output_view_units(self):
for operation in (
lambda v: np.multiply(v, v, out=v),
lambda v: np.divide(v, v, out=v),
lambda v: np.square(v, out=v),
lambda v: np.sqrt(v, out=v)):
with self.subTest(operation=operation):
q = [1., 4., 9.] * pq.m
view = q[:2]
with self.assertRaisesRegex(ValueError, 'modify units of a view'):
operation(view)
self.assertEqual(view.units, pq.m)
self.assertEqual(q.units, pq.m)

q = [1., 4., 9.] * pq.m
view = q[:2]
self.assertIs(np.multiply(view, 2, out=view), view)
self.assertQuantityEqual(q, [2., 8., 9.] * pq.m)
self.assertIs(np.add(view, view, out=view), view)
self.assertQuantityEqual(q, [4., 16., 9.] * pq.m)
self.assertQuantityEqual(np.square(view), [16., 256.] * pq.m**2)

source = [2., 3.] * pq.m
destination = [0., 0., 0.] * pq.m**2
output = destination[:2]
self.assertIs(np.multiply(source, source, out=output), output)
self.assertQuantityEqual(destination, [4., 9., 0.] * pq.m**2)
with self.assertRaisesRegex(ValueError, 'modify units of a view'):
np.sqrt(source, out=output)
self.assertEqual(destination.units, pq.m**2)
self.assertEqual(output.units, pq.m**2)

def test_cumprod(self):
self.assertRaises(ValueError, np.cumprod, self.q)

Expand Down
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