def test_should_create_generic_condition(self, cfg):
# when
cond = Condition.generic(cfg)
# then
assert len(cond) == cfg.classifier_length
for allele in cond:
assert allele == cfg.classifier_wildcard
def get_differences(self, p0: Perception) -> Condition:
"""
Difference determination is run when the classifier anticipated the
change correctly.
If it's marked we want to find if we can propose differences that
will be applied to new condition part (specialization).
There can be two types of differences:
1) unique - one or more attributes in mark does not contain given
perception attribute
2) fuzzy - there is no unique difference - one or more attributes in
the mark specify more than one value in perception attribute.
If only unique differences are present - one random one get specified.
If there are fuzzy differences everyone is specified.
Parameters
----------
p0: Perception
Returns
-------
Condition
differences between mark and perception that can form
a new classifier
"""
diff = Condition.generic(self.cfg)
if self.is_marked():
enc_p0 = list(map(self.cfg.encoder.encode, p0))
# Unique and fuzzy difference counts
nr1, nr2 = 0, 0
# Count difference types
for idx, item in enumerate(self):
if len(item) > 0 and enc_p0[idx] not in item:
nr1 += 1
elif len(item) > 1:
nr2 += 1
if nr1 > 0:
possible_idx = [
pi for pi, p in enumerate(enc_p0)
if p not in self[pi] and len(self[pi]) > 0
]
rand_idx = random.choice(possible_idx)
p = enc_p0[rand_idx]
diff[rand_idx] = UBR(p, p)
elif nr2 > 0:
for pi, p in enumerate(enc_p0):
if len(self[pi]) > 1:
diff[pi] = UBR(p, p)
return diff
def test_should_get_no_differences(self, cfg):
# given
p0 = Perception([.5, .5], oktypes=(float, ))
mark = self._init_mark([], cfg)
# when
diff = mark.get_differences(p0)
# then
assert diff == Condition.generic(cfg)
def test_should_initialize_without_arguments(self, cfg):
# when
c = Classifier(cfg=cfg)
# then
assert c.condition == Condition.generic(cfg=cfg)
assert c.action is None
assert c.effect == Effect.pass_through(cfg=cfg)
assert c.exp == 1
assert c.talp is None
assert c.tav == 0.0
def _init_condition(vals, cfg):
if len(vals) == 0:
return Condition.generic(cfg)
return Condition(vals, cfg)