对于Python项目，我需要实现Viterbi算法。 无论我输入哪个序列，它都返回0（=第一个状态）的列表，我无法理解为什么。 也许某人有使用此算法的经验
class HMM_model:
def __init__(self, transition_matrix, emission_matrix, initial_state, obs_names, hidden_names):
""" transition_matrix is of shape : len(hidden_names) * len(hidden_names)
emission_matrix is of shape: len(hidden_names) * len(obs_names)
initial_state is a vector of size len(hidden_names)
"""
self.transition_matrix = transition_matrix
self.emission_matrix = emission_matrix
self.initial_state = initial_state
self.obs_names = obs_names
self.hidden_names = hidden_names
def viterbi(self, observations):
# initialize
len_seq = len(observations)
n_diff_states = len(self.hidden_names)
prior = self.initial_state
viterbi = np.zeros((len_seq, n_diff_states))
backpointer = np.zeros((len_seq, n_diff_states))
best_path = np.empty(len_seq, 'B')
# B. appoint initial values for viterbi
viterbi[0,:] = prior * self.emission_matrix[:, observations[0]]
backpointer[0,:] = 0
for i in range(1,len_seq):
viterbi[i, :] = np.max(viterbi[i-1, :, np.newaxis] * self.transition_matrix * self.emission_matrix[:, observations[i-1]], axis=0)
backpointer[i,:] = np.argmax(viterbi[i-1, :, np.newaxis] * self.transition_matrix , axis = 0)
best_path[-1] = np.argmax(viterbi[len_seq -1 ,:])
for i in reversed(range(0, len_seq -1)):
best_path[i-1] = backpointer[i, best_path[i]]
return best_path