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BUG: Ensure that same-kind casting works for uints (mostly) #27802

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merged 2 commits into from
Nov 20, 2024
Merged

BUG: Ensure that same-kind casting works for uints (mostly) #27802

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792b7f8
BUG: Ensure that same-kind casting works for uints (mostly)
seberg Nov 20, 2024
236cda1
DOC: Adapt to changes in docs (and fix typo/style nit)
seberg Nov 20, 2024
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14 changes: 12 additions & 2 deletions numpy/ma/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -469,6 +469,16 @@ def _check_fill_value(fill_value, ndtype):
ndtype = np.dtype(ndtype)
if fill_value is None:
fill_value = default_fill_value(ndtype)
# TODO: It seems better to always store a valid fill_value, the oddity
# about is that `_fill_value = None` would behave even more
# different then.
# (e.g. this allows arr_uint8.astype(int64) to have the default
# fill value again...)
# The one thing that changed in 2.0/2.1 around cast safety is that the
# default `int(99...)` is not a same-kind cast anymore, so if we
# have a uint, use the default uint.
if ndtype.kind == "u":
fill_value = np.uint(fill_value)
elif ndtype.names is not None:
if isinstance(fill_value, (ndarray, np.void)):
try:
Expand Down Expand Up @@ -6165,7 +6175,7 @@ def ptp(self, axis=None, out=None, fill_value=None, keepdims=False):
>>> y.ptp(axis=1).view(np.uint8)
masked_array(data=[126, 127, 128, 129],
mask=False,
fill_value=np.int64(999999),
fill_value=np.uint64(999999),
dtype=uint8)
"""
if out is None:
Expand Down Expand Up @@ -7853,7 +7863,7 @@ def diff(a, /, n=1, axis=-1, prepend=np._NoValue, append=np._NoValue):
>>> np.ma.diff(u8_arr)
masked_array(data=[255],
mask=False,
fill_value=np.int64(999999),
fill_value=np.uint64(999999),
dtype=uint8)
>>> u8_arr[1,...] - u8_arr[0,...]
np.uint8(255)
Expand Down
29 changes: 29 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 @@ -1351,6 +1351,23 @@ 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("dtype", "bBiIqQ")
@pytest.mark.parametrize("mask", [
[False, False, False, True, True], # masked min/max
[False, False, False, True, False], # masked max only
[False, False, False, False, True], # masked min only
])
@pytest.mark.parametrize("axis", [None, -1])
def test_minmax_ints(self, dtype, mask, axis):
iinfo = np.iinfo(dtype)
# two dimensional to hit certain filling paths
a = np.array([[0, 10, -10, iinfo.min, iinfo.max]] * 2).astype(dtype)
mask = np.asarray([mask] * 2)

masked_a = masked_array(a, mask=mask)
assert_array_equal(masked_a.min(axis), a[~mask].min(axis))
assert_array_equal(masked_a.max(axis), a[~mask].max(axis))

@pytest.mark.parametrize("time_type", ["M8[s]", "m8[s]"])
def test_minmax_time_dtypes(self, time_type):
def minmax_with_mask(arr, mask):
Expand Down Expand Up @@ -5755,3 +5772,15 @@ def test_deepcopy_0d_obj():
deepcopy[...] = 17
assert_equal(source, 0)
assert_equal(deepcopy, 17)


def test_uint_fill_value_and_filled():
# See also gh-27269
a = np.ma.MaskedArray([1, 1], [True, False], dtype="uint16")
# the fill value should likely not be 99999, but for now guarantee it:
assert a.fill_value == 999999
# However, it's type is uint:
assert a.fill_value.dtype.kind == "u"
# And this ensures things like filled work:
np.testing.assert_array_equal(
a.filled(), np.array([999999, 1]).astype("uint16"), strict=True)
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