def test_average():
drop_caches()
# Two subtitutions.
q1a = Quote(string="Chase it others is the dogs hound")
q1b = Quote(string="Others is the hound hound")
s1 = Substitution(source=q1a, destination=q1b, start=2, position=3)
q2a = Quote(string="Chase it others is the frisbee hound")
q2b = q1b
s2 = Substitution(source=q2a, destination=q2b, start=2, position=3)
# Our test feature.
values = {"dog": 2, "hound": 3, "frisbee": 4, "chase": 6, "cad": 7, "other": 8}
def feature(word=None):
if word is None:
return set(values.keys())
else:
return values.get(word, np.nan)
# Global average and average of synonyms (computed on lemmas) are well
# retrieved.
assert s1._static_average(feature) == 30 / 6
assert s1._average(feature, False) == 30 / 6
assert s2._static_average(feature) == 30 / 6
assert s2._average(feature, False) == 30 / 6
assert s1._average(feature, True) == np.mean([3, 6, 7])
# 'frisbee' has no synonyms.
assert np.isnan(s2._average(feature, True))
# If we have a lot of NaNs, things still work well.
drop_caches()
values = {"dog": 2, "frisbee": 4, "chase": np.nan, "cad": 7, "other": 8}
assert s1._average(feature, True) == 7
# 'frisbee' has no synonyms.
assert np.isnan(s2._average(feature, True))
