def computeStartState(self, input: InputStream, p: ATNState):
initialContext = PredictionContext.EMPTY
configs = OrderedATNConfigSet()
for i in range(0, len(p.transitions)):
target = p.transitions[i].target
c = LexerATNConfig(state=target, alt=i + 1, context=initialContext)
self.closure(input, c, configs, False, False, False)
return configs
def computeTargetState(self, input: InputStream, s: DFAState, t: int):
reach = OrderedATNConfigSet()
# if we don't find an existing DFA state
# Fill reach starting from closure, following t transitions
self.getReachableConfigSet(input, s.configs, reach, t)
if len(reach) == 0: # we got nowhere on t from s
if not reach.hasSemanticContext:
# we got nowhere on t, don't throw out this knowledge; it'd
# cause a failover from DFA later.
self.addDFAEdge(s, t, self.ERROR)
# stop when we can't match any more char
return self.ERROR
# Add an edge from s to target DFA found/created for reach
return self.addDFAEdge(s, t, cfgs=reach)
