def test_should_decrease_quality(self, cfg):
# given
cl = Classifier(cfg=cfg)
assert cl.q == 0.5
# when
cl.decrease_quality()
# then
assert cl.q == 0.475
def unexpected_case(cl: Classifier,
p0: Perception,
p1: Perception,
time: int) -> Optional[Classifier]:
"""
The classifier does not anticipate the resulting state correctly.
In this case the classifier is marked by the `previous_perception`
and it's quality is decreased.
If it is possible to specialize an offspring (change pass-through
symbols to correct values then new classifier is returned.
Parameters
----------
cl: Classifier
Classifier object
p0: Perception
previous situation
p1: Perception
current situation
time:
current epoch
Returns
-------
Optional[Classifier]
If possible to specialize parent, None otherwise
"""
cl.decrease_quality()
cl.set_mark(p0)
# TODO: think
if not cl.effect.is_specializable(p0, p1):
return None
child = cl.copy_from(cl, time)
child.specialize(p0, p1, leave_specialized=True)
if child.q < .5:
child.q = .5
return child
