def setUp(self):
s1 = DFAState('s1')
s2 = DFAState('s2')
s3 = DFAState('s3')
s1.add_edge('a', s2)
s1.add_edge('b', s1)
s2.add_edge('a', s2)
s2.add_edge('b', s3)
s3.add_edge('a', s3)
s3.add_edge('b', s3)
self.dfa = DFA(s1, [s3])
def setUp(self):
# Set up an example mealy machine
s1 = DFAState('1')
s2 = DFAState('2')
s3 = DFAState('3')
s1.add_edge('a', s2)
s1.add_edge('b', s1)
s2.add_edge('a', s3)
s2.add_edge('b', s1)
s3.add_edge('a', s3)
s3.add_edge('b', s1)
self.dfa = DFA(s1, [s3])
import tempfile
from stmlearn.equivalencecheckers import BFEquivalenceChecker
from stmlearn.learners import TTTDFALearner
from stmlearn.suls import DFA, DFAState
from stmlearn.teachers import Teacher
# Set up a simple state machine (S1) =a> (S2) =b> ((S3))
s1 = DFAState('s1')
s2 = DFAState('s2')
s3 = DFAState('s3')
s1.add_edge('a', s2)
s2.add_edge('b', s3)
sm = DFA(s1, [s3])
# Since we are learning a DFA, we need edges for the whole alphabet in every state
s1.add_edge('b', s1)
s2.add_edge('a', s2)
s3.add_edge('a', s3)
s3.add_edge('b', s3)
# We are using the brute force equivalence checker
eqc = BFEquivalenceChecker(sm)
# Set up the teacher, with the system under learning and the equivalence checker
teacher = Teacher(sm, eqc)
# Set up the learner who only talks to the teacher
def setUp(self):
# Set up an example mealy machine
s1 = DFAState('1')
s1.add_edge('a', s1)
s1.add_edge('b', s1)
self.dfa = DFA(s1, [])