def MLdecode(data, hmm): s='' for c in data: emiA = a.getEmissionProbability(0, c, hmm) emiB = a.getEmissionProbability(1, c, hmm) if a.compareProbability(emiA, emiB)==1: s+='A' else: s+='B' return s
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