nfa确定化python
时间: 2023-07-09 17:49:02 浏览: 53
可以使用Python实现NFA到DFA的确定化过程。以下是一个简单的实现示例:
```python
nfa = {
0: {'a': {1}, 'b': {0}},
1: {'a': {2, 3}, 'b': {1}},
2: {'a': {2}, 'b': {2}},
3: {'a': {3}, 'b': {3}}
}
def e_closure(states):
e_closure_set = set(states)
stack = list(states)
while stack:
state = stack.pop()
if state in nfa:
e_transitions = nfa[state].get('', set())
for e_transition in e_transitions:
if e_transition not in e_closure_set:
e_closure_set.add(e_transition)
stack.append(e_transition)
return frozenset(e_closure_set)
def nfa_to_dfa(nfa, start_state):
dfa = {}
unmarked_states = [e_closure({start_state})]
while unmarked_states:
state_set = unmarked_states.pop()
state_set = frozenset(state_set)
if state_set not in dfa:
dfa[state_set] = {}
for symbol in set().union(*[nfa[state].keys() for state in state_set]):
if symbol == '':
continue
next_state_set = set()
for state in state_set:
next_state_set |= nfa.get(state, {}).get(symbol, set())
next_state_set = e_closure(next_state_set)
dfa[state_set][symbol] = next_state_set
if next_state_set not in dfa:
unmarked_states.append(next_state_set)
return dfa
dfa = nfa_to_dfa(nfa, 0)
print(dfa)
```
在上述示例中,我们首先定义了一个NFA,并实现了一个函数`e_closure`来计算状态集合的e-closure。然后我们实现了`nfa_to_dfa`函数来将NFA转换为DFA。这个函数从起始状态开始,不断地计算每个状态集合的e-closure和转换,并将其添加到DFA中,直到所有状态集合都被标记为已访问。
最后,我们使用这个函数将NFA转换为DFA,并打印出DFA的状态转换表。