def getXi(data, hmm):
alpha = a.forward(data, hmm)
beta = a.backward(data, hmm)
likelihood = beta[0][0]
xi = [[[[0, 0], [0, 0]], [[0, 0], [0, 0]]]]
for t in range(len(data) - 1):
xi.append([[[0, 0], [0, 0]], [[0, 0], [0, 0]]])
data = "#" + data
t = 0
for h in range(len(data) - 1):
for i in range(0, 2):
for j in range(0, 2):
ptrans = a.getTransitionProbability(i, j, hmm)
pemit = a.getEmissionProbability(j, data[t + 1], hmm)
temp = a.multiplyProbability(alpha[t][i], ptrans)
temp = a.multiplyProbability(temp, pemit)
temp = a.multiplyProbability(temp, beta[t + 1][j])
xi[t][i][j] = a.divideProbability(temp, likelihood)
t += 1
return xi
def viterbi(data, hmm): alpha = [[[1,0],[0,0]]] t = 0 track = [[],[]] for c in data: t+=1 alpha.append([[0, 0],[0, 0]]) for j in range(0, 2): cand = [[0.0, 0],[0.0,0]] for i in range(0,2): ptrans = a.getTransitionProbability(i, j, hmm) cand[i]=a.multiplyProbability(alpha[t-1][i], ptrans) if a.compareProbability(cand[0], cand[1])==1: better=cand[0] track[j].append(0) else: better=cand[1] track[j].append(1) pemit = a.getEmissionProbability(j, c, hmm) prob = a.multiplyProbability(better, pemit) # print prob alpha[t][j]=prob # print alpha[t] #print scale[t] if a.compareProbability(alpha[t][0], alpha[t][1])==1: start=0 else: start=1 s = '' # print track[0] for i in range(len(track[0])-1, -1, -1): if start==0: s='A'+s else: s='B'+s start = track[start][i] return s
