def test_should_not_generalize_unchanging_attribute(
self, _condition, _effect, _sua_before, _sua_after, cfg):
# given
cls = Classifier(condition=_condition, effect=_effect, cfg=cfg)
assert len(cls.specified_unchanging_attributes) == _sua_before
# when
cls.generalize_unchanging_condition_attribute()
# then
assert len(cls.specified_unchanging_attributes) == _sua_after
def expected_case(cl: Classifier, p0: Perception,
time: int) -> Optional[Classifier]:
"""
Controls the expected case of a classifier. If the classifier
is too specific it tries to add some randomness to it by
generalizing some attributes.
:param cl:
:param p0:
:param time:
:return: new classifier or None
"""
if cl.cfg.do_pee:
cl.effect.update_enhanced_effect_probs(p0, cl.cfg.beta)
diff = cl.mark.get_differences(p0)
if diff.specificity == 0:
if cl.cfg.do_pee and cl.is_marked():
cl.ee = True
cl.increase_quality()
return None
no_spec = len(cl.specified_unchanging_attributes)
no_spec_new = diff.specificity
child = cl.copy_from(cl, time)
if no_spec >= cl.cfg.u_max:
while no_spec >= cl.cfg.u_max:
res = cl.generalize_unchanging_condition_attribute()
assert res is True
no_spec -= 1
while no_spec + no_spec_new > cl.cfg.u_max:
if random() < 0.5:
diff.generalize_specific_attribute_randomly()
no_spec_new -= 1
else:
if cl.generalize_unchanging_condition_attribute():
no_spec -= 1
else:
while no_spec + no_spec_new > cl.cfg.u_max:
diff.generalize_specific_attribute_randomly()
no_spec_new -= 1
child.condition.specialize_with_condition(diff)
if child.q < 0.5:
child.q = 0.5
return child
def test_should_generalize_second_unchanging_attribute(self, cfg):
# given
cls = Classifier(condition='#####0#0', effect='########', cfg=cfg)
assert len(cls.specified_unchanging_attributes) == 2
# when
generalized = cls.generalize_unchanging_condition_attribute(
lambda x: 7)
# then
assert generalized is True
assert len(cls.specified_unchanging_attributes) == 1
assert Condition('#####0##') == cls.condition
