NFA的确定化完整代码Python

NFA（非确定性有限自动机）是一种理论上的模型，用于表示正则表达式的匹配过程。为了将其转换为DFA（确定性有限自动机），我们通常会通过算法如“ subset construction”（集合构造法）来实现确定化。以下是使用Python的一个简化版DFA确定化的示例代码：

from collections import defaultdict

def nfa_to_dfa(nfa):
    states = set()
    transitions = defaultdict(set)
    
    # 初始化状态和转换函数
    for state, input_char, next_states in nfa.transitions.items():
        states.add(state)
        for next_state in next_states:
            transitions[(state, input_char)].add(next_state)

    start_state = frozenset([nfa.start])
    final_states = {frozenset([s]) for s in nfa.final}

    initial_transitions = {}
    q = [start_state]

    while q:
        current_state = q.pop()
        if current_state not in initial_transitions:
            initial_transitions[current_state] = defaultdict(list)

        for char, next_states in transitions[current_state].items():
            new_state = frozenset.union(current_state, next_states)
            if new_state not in q:
                q.append(new_state)
            initial_transitions[current_state][char].append(new_state)

    dfa_start = frozenset([start_state])
    dfa_final = {final_state for state in initial_transitions for final_state in state if state in final_states}

    return Dfa(dfa_start, initial_transitions, dfa_final)

class Dfa:
    def __init__(self, start, transitions, final):
        self.start = start
        self.transitions = transitions
        self.final = final

# 使用这个类创建DFA实例，需要提供输入的NFA对象
# 其中nfa对象通常包含状态、输入字符到状态的映射以及起始状态和终态信息
nfa_example = ...  # 假设这是一个已有的NFA对象
dfa = nfa_to_dfa(nfa_example)

请注意，这只是一个简化的版本，实际的NFA到DFA转换可能会更复杂，并需要考虑优化，比如处理空字符等。