dfa最小化代码python

下面是一个简单的 Python 代码示例，用于将 DFA 最小化：

def minimize_dfa(dfa):
    # 初始化分组
    partitions = [dfa.final_states(), dfa.non_final_states()]

    while True:
        new_partitions = []
        # 对于每个分组
        for partition in partitions:
            # 如果分组只有一个状态，则跳过
            if len(partition) == 1:
                new_partitions.append(partition)
                continue
            # 按照状态是否等价进行分组
            equiv_classes = {}
            for state in partition:
                equiv_classes.setdefault(dfa.state_eq_class(state), []).append(state)
            new_partitions.extend(equiv_classes.values())
        # 如果分组不再变化，则退出循环
        if new_partitions == partitions:
            break
        partitions = new_partitions

    # 创建新的 DFA 状态和转移函数
    new_states = []
    new_transitions = {}
    for partition in partitions:
        new_state = dfa.state_eq_class(partition[0])
        new_states.append(new_state)
        for state in partition:
            for symbol in dfa.alphabet():
                next_state = dfa.transition(state, symbol)
                new_next_state = dfa.state_eq_class(next_state)
                new_transitions[(new_state, symbol)] = new_next_state

    # 构建新的 DFA 并返回
    new_start_state = dfa.state_eq_class(dfa.start_state())
    new_final_states = set(dfa.state_eq_class(state) for state in dfa.final_states())
    return DFA(new_states, dfa.alphabet(), new_transitions, new_start_state, new_final_states)

请注意，这里的 `DFA` 类需要根据你的实现进行调整。此代码假定 `DFA` 类具有以下方法：

- `final_states()` 返回 DFA 的终止状态集合。
- `non_final_states()` 返回 DFA 的非终止状态集合。
- `state_eq_class(state)` 返回状态 `state` 所在的等价类。
- `transition(state, symbol)` 返回在状态 `state` 下读取符号 `symbol` 后的下一个状态。
- `alphabet()` 返回 DFA 的字母表。