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Improve handling of masks in concatenate #6187

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Oct 25, 2024
Merged

Improve handling of masks in concatenate #6187

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1e51588
Improve handling of masks
bouweandela Oct 24, 2024
b79bdde
Add whatsnew
bouweandela Oct 24, 2024
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2 changes: 1 addition & 1 deletion docs/src/whatsnew/latest.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -81,7 +81,7 @@ This document explains the changes made to Iris for this release
may happen when there are very many or large auxiliary coordinates, derived
coordinates, cell measures, or ancillary variables to be checked that span
the concatenation axis. This issue can be avoided by disabling the
problematic check. (:pull:`5926`)
problematic check. (:pull:`5926` and :pull:`6187`)

🔥 Deprecations
===============
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2 changes: 1 addition & 1 deletion lib/iris/_concatenate.py
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Expand Up @@ -310,7 +310,7 @@ def _hash_ndarray(a: np.ndarray) -> np.ndarray:

# Hash the bytes representing the array data.
hash.update(b"data=")
if isinstance(a, np.ma.MaskedArray):
if np.ma.is_masked(a):
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# Hash only the unmasked data
hash.update(a.compressed().tobytes())
# Hash the mask
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17 changes: 17 additions & 0 deletions lib/iris/tests/unit/concatenate/test_hashing.py
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Expand Up @@ -21,6 +21,8 @@
(np.array([np.nan, 1.0]), np.array([np.nan, 1.0]), True),
(np.ma.array([1, 2], mask=[0, 1]), np.ma.array([1, 2], mask=[0, 1]), True),
(np.ma.array([1, 2], mask=[0, 1]), np.ma.array([1, 2], mask=[0, 0]), False),
(np.ma.array([1, 2], mask=[1, 1]), np.ma.array([1, 2], mask=[1, 1]), True),
(np.ma.array([1, 2], mask=[0, 0]), np.ma.array([1, 2], mask=[0, 0]), True),
(da.arange(6).reshape((2, 3)), da.arange(6, chunks=1).reshape((2, 3)), True),
(da.arange(20, chunks=1), da.arange(20, chunks=2), True),
(
Expand All @@ -33,6 +35,21 @@
da.ma.masked_array([1, 3], mask=[0, 1]),
True,
),
(
np.arange(2),
da.ma.masked_array(np.arange(2), mask=[0, 0]),
True,
),
(
np.arange(2),
da.ma.masked_array(np.arange(2), mask=[0, 1]),
False,
),
(
da.ma.masked_array(np.arange(10), mask=np.zeros(10)),
da.ma.masked_array(np.arange(10), mask=np.ma.nomask),
True,
),
(
np.ma.array([1, 2], mask=[0, 1]),
np.ma.array([1, 3], mask=[0, 1], fill_value=10),
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