def compare_recusions():
# Compare the two version in terms of efficiency
start_time = time.time()
hmm = Hmm('rescaled')
hmm.compute_proba()
hmm.EM()
print("rescaled version run in %.6s seconds " % (time.time() - start_time))
start_time = time.time()
hmm2 = Hmm('log-scale')
hmm2.compute_proba()
hmm2.EM()
print("log-scale version run in %.6s seconds " %
(time.time() - start_time))
print('difference cond_proba ' % np.min(hmm.cond_proba - hmm2.cond_proba),
np.max(hmm.cond_proba - hmm2.cond_proba))
print(
'difference joined_cond_proba' %
np.min(hmm.joined_cond_proba - hmm2.joined_cond_proba),
np.max(hmm.joined_cond_proba - hmm2.joined_cond_proba))
return
# Q1
print('\n****************** Q1 ******************')
compare_recusions()
# Q2
print('\n****************** Q2 ******************')
hmm = Hmm('rescaled')
hmm2 = Hmm('log-scale')
hmm.compute_proba(hmm.test_data)
hmm.plot_proba(100, 'conditional proba with initial parameters on test', 'q02',
'1')
#Q3 & Q4
print('\n****************** Q4 ******************')
hmm.EM(True)
hmm.print_parameters()
# Q5
print('\n****************** Q5 ******************')
hmm.plot_likelihood('q05', '1')
# Q6
print('\n****************** Q6 ******************')
hmm.print_loglikelihoods_table()
# Q7-Q8
def plot_Viterbi_path(hmm):
hmm.compute_proba()