写一个维特比算法用python

好的，以下是一个简单的维特比算法的 Python 代码：

def viterbi(obs, states, start_p, trans_p, emit_p):
    V = [{}]
    path = {}

    # Initialize base cases (t == 0)
    for y in states:
        V[0][y] = start_p[y] * emit_p[y][obs[0]]
        path[y] = [y]

    # Run Viterbi for t > 0
    for t in range(1, len(obs)):
        V.append({})
        newpath = {}

        for y in states:
            (prob, state) = max((V[t-1][y0] * trans_p[y0][y] * emit_p[y][obs[t]], y0) for y0 in states)
            V[t][y] = prob
            newpath[y] = path[state] + [y]

        # Don't need to remember the old paths
        path = newpath

    (prob, state) = max((V[len(obs) - 1][y], y) for y in states)
    return (prob, path[state])

这个算法用于在隐马尔可夫模型中找到最可能的状态序列，其中 `obs` 是观测序列，`states` 是可能的状态集合，`start_p` 是每个状态的初始概率，`trans_p` 是状态之间的转移概率，`emit_p` 是状态生成观测的概率。