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BUG: allow MaskedArray min/max with dtype=object #29576

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2a97fee
BUG: allow MaskedArray min/max with dtype=object
benburrill Aug 16, 2025
2642203
TST: improve tests of min/max for MAs of objects
benburrill Aug 17, 2025
822ba2d
TST: parametrize test_minmax_object_dtype
benburrill Aug 20, 2025
52d5955
BUG: universal infinity min/max filler for objects
benburrill Aug 31, 2025
fb1604e
TST: test #9103 reproducer specifically
benburrill Aug 31, 2025
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45 changes: 41 additions & 4 deletions numpy/ma/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -191,6 +191,39 @@ class MaskError(MAError):
default_filler["M8[" + v + "]"] = np.datetime64("NaT", v)
default_filler["m8[" + v + "]"] = np.timedelta64("NaT", v)


class _UniversalInfinity:
def __init__(self, neg=False):
self.neg = neg

def __le__(self, other):
return self.neg

def __lt__(self, other):
return self.neg and self != other

def __ge__(self, other):
return not self.neg

def __gt__(self, other):
return not self.neg and self != other

def __eq__(self, other):
return isinstance(other, _UniversalInfinity) and self.neg == other.neg

def __hash__(self):
return hash(self.neg)

def __neg__(self):
return _UniversalInfinity(not self.neg)

def __pos__(self):
return self

def __repr__(self):
return "-uinf" if self.neg else "uinf"


float_types_list = [np.half, np.single, np.double, np.longdouble,
np.csingle, np.cdouble, np.clongdouble]

Expand All @@ -211,6 +244,8 @@ class MaskError(MAError):
min_val, max_val = info.min, info.max
elif scalar_dtype.kind == "b":
min_val, max_val = 0, 1
elif scalar_dtype.kind == "O":
min_val, max_val = -_UniversalInfinity(), _UniversalInfinity()
else:
min_val, max_val = None, None

Expand Down Expand Up @@ -5942,8 +5977,9 @@ def min(self, axis=None, out=None, fill_value=None, keepdims=np._NoValue):
# No explicit output
if out is None:
result = self.filled(fill_value).min(
axis=axis, out=out, **kwargs).view(type(self))
if result.ndim:
axis=axis, out=out, **kwargs)
if isinstance(result, ndarray) and result.ndim:
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@benburrill benburrill Aug 21, 2025 •
edited
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There is an (extreme) edge case I am aware of here that my code fails to address: ideally, I think that

x = np.array([1, 2])
assert np.fromiter([x], dtype=object).view(np.ma.MaskedArray).min() is x

should pass, but with my change, x will get erroneously converted to a masked array when returned by min.

This is identical to the old behavior, so it's not necessarily a problem, but it is a failure of my assumptions: initially when working on this PR, I thought I only needed to worry about arrays containing 0-D array objects, since arrays of higher dimension are not orderable (and so you'd just get an error when calling min(), as you should). But of course I forgot to consider that min() will succeed regardless if there is only one item. Also, as another similar edge case, higher dimensional arrays actually are orderable if they themselves only contain one item (not just if they are 0-D).

I'm not sure if this is actually worth fixing though. Thoughts?

result = result.view(type(self))
# Set the mask
result.__setmask__(newmask)
# Get rid of Infs
Expand Down Expand Up @@ -6047,8 +6083,9 @@ def max(self, axis=None, out=None, fill_value=None, keepdims=np._NoValue):
# No explicit output
if out is None:
result = self.filled(fill_value).max(
axis=axis, out=out, **kwargs).view(type(self))
if result.ndim:
axis=axis, out=out, **kwargs)
if isinstance(result, ndarray) and result.ndim:
result = result.view(type(self))
# Set the mask
result.__setmask__(newmask)
# Get rid of Infs
Expand Down
14 changes: 14 additions & 0 deletions numpy/ma/tests/test_core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1452,6 +1452,20 @@ def test_minmax_dtypes(self):
assert masked_array([-cmax, 0], mask=[0, 1]).max() == -cmax
assert masked_array([cmax, 0], mask=[0, 1]).min() == cmax

@pytest.mark.parametrize("mask", [nomask, [False, True, False]])
@pytest.mark.parametrize("arg1, arg2, arg3", [
(1, 2, 3),
(np.array(1), np.array(2), np.array(3)),
])
def test_minmax_object_dtype(self, arg1, arg2, arg3, mask):
a = masked_array([arg1, arg2, arg3], mask=mask, dtype=object)
assert a.min() is arg1
assert a.max() is arg3

def test_gh_9103(self):
arr = masked_array([1, 2, 3], dtype='object', mask=[True, False, False])
assert arr.min() == 2

@pytest.mark.parametrize("dtype", "bBiIqQ")
@pytest.mark.parametrize("mask", [
[False, False, False, True, True], # masked min/max
Expand Down