def apply(p0: Perception, p1: Perception, cl: Classifier,
population: ClassifiersList):
if not _perception_changed(p0, p1):
handle_useless_case(cl)
elif cl.does_anticipate_correctly(p0, p1):
handle_expected_case(cl)
elif not cl.does_anticipate_correctly(p0, p1) and _perception_changed(
p0, p1) and cl.can_be_corrected(p0, p1):
handle_correctable_case(p0, p1, cl, population)
else:
handle_not_correctable_case(cl, p0)
# Remove inadequate classifiers
for cl in population:
if cl.is_inadequate() and not cl.is_general():
population.remove(cl)
def test_distinguish_general_classifier(self, _c, _e, _result, cfg):
cl = Classifier(condition=Condition(_c), effect=Effect(_e), cfg=cfg)
assert cl.is_general() == _result