def rpni(self, pos_examples, neg_examples):
dfa = DFA.from_word_list(pos_examples, self.alphabet)
self.reds = {dfa.start}
self.blues = {
next_state
for token, next_state in dfa.transitions[dfa.start].items()
}
self.draw(dfa=dfa, operation='pta')
while len(self.blues) > 0:
temp_dfa = 0
blue = choose(dfa, self.blues)
for red in list(self.reds):
temp_dfa = self.rpni_merge(deepcopy(dfa), red, blue)
if rpni_compatible(temp_dfa, neg_examples):
# print('compatible')
break
temp_dfa = 0
if temp_dfa != 0:
if blue in self.blues:
self.blues.remove(blue)
dfa = temp_dfa
for r_state in self.reds:
for token, next_state in dfa.transitions[r_state].items():
if next_state not in self.reds:
self.blues.add(next_state)
self.draw(dfa=dfa, operation='merge')
else:
self.rpni_promote(dfa, blue)
self.draw(dfa=dfa, operation='promoted')
return dfa
def learn_dfa(teacher, num_examples):
for i in range(num_examples):
teacher.example()
examples = teacher.used_examples
pos_examples = [ex[0] for ex in examples if ex[1] == '+']
neg_examples = [ex[0] for ex in examples if ex[1] == '-']
pta = DFA.from_word_list(pos_examples, alphabet)
return pta
