def unexpected_case(cl: Classifier, p0: Perception, p1: Perception,
time: int) -> Optional[Classifier]:
"""
Controls the unexpected case of the classifier.
:param cl:
:param p0:
:param p1:
:param time:
:return: specialized classifier if generation was possible,
None otherwise
"""
cl.decrease_quality()
cl.set_mark(p0)
# Return if the effect is not specializable
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 < 0.5:
child.q = 0.5
return child
def unexpected_case(cl: Classifier, p0: Perception, p1: Perception,
time: int) -> Optional[Classifier]:
"""
Controls the unexpected case of the classifier.
:param cl:
:param p0:
:param p1:
:param time:
:return: specialized classifier if generation was possible,
None otherwise
"""
cl.decrease_quality()
cl.set_mark(p0)
# Return if the effect is not specializable
if not cl.effect.is_specializable(p0, p1):
return None
child = cl.copy_from(cl, time)
if cl.cfg.do_pee:
# Probability-Enhanced attributes cannot appear in the effect part
# if we leave already specialized attributes unchanged.
# Therefore don't leave specialized.
child.specialize(p0, p1, leave_specialized=False)
else:
child.specialize(p0, p1, leave_specialized=True)
if child.q < 0.5:
child.q = 0.5
return child
def test_should_decrease_quality(self, cfg):
# given
cls = Classifier(quality=0.47, cfg=cfg)
# when
cls.decrease_quality()
# then
assert abs(0.45 - cls.q) < 0.01
