…ythonOT#833)
* fix label-aware cost correction in ot.da
the cost correction that pushes apart differently-labeled samples was
computed backwards. it used missing_ys = (ys == -1) and the product of
the two missing masks, so the large cost was applied only where both
labels are missing, and never where two labeled samples have different
labels. with all labels known the correction was a no-op, so ys/yt had
no effect on the transport (see PythonOT#664).
switched to present masks (ys != -1) so the correction applies exactly
to labeled source/target pairs whose labels differ, matching the
original pre-vectorized loop. restored the semisupervised tests that had
been flipped to assert the buggy no-op (n_unsup == n_semisup) back to
asserting the cost actually changes, and added a regression test.
closes PythonOT#664
* add PR number to releases entry
* Apply suggestion from @rflamary
* use MISSING_LABEL constant instead of bare -1
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Co-authored-by: Rémi Flamary <remi.flamary@gmail.com>