def test_train_segments():
results = np.zeros((6, 12))
for i in range(6):
dat = io.loadmat('testset%02d.mat' % (i + 1))
eog_v = dat['eog_v_seg'][0]
eog_h = dat['eog_h_seg'][0]
fs = float(dat['fs'][0])
fir_len = 150
stop_limit = 500 / fs
wn = stop_limit / (fs / 2)
b = sig.firwin(fir_len, wn)
eog_v_f = sig.filtfilt(b, 1, eog_v)
eog_h_f = sig.filtfilt(b, 1, eog_h)
p = PyGERT()
p.train(eog_h_f, eog_v_f)
results[i, 0] = p.mu_fix
results[i, 1] = p.sigma_fix
results[i, 2] = p.prior_fix
results[i, 3] = p.mu_sac
results[i, 4] = p.sigma_sac
results[i, 5] = p.prior_sac
results[i, 6] = p.mu_bli
results[i, 7] = p.sigma_bli
results[i, 8] = p.prior_bli
results[i, 9] = p.mu_bs
results[i, 10] = p.sigma_bs
results[i, 11] = p.prior_bs
print(results)
np.savetxt('segment_test_python.csv', results, delimiter=',')
def test_train_segments():
results = np.zeros((6, 12))
for i in range(6):
dat = io.loadmat('testset%02d.mat' % (i + 1))
eog_v = dat['eog_v_seg'][0]
eog_h = dat['eog_h_seg'][0]
fs = float(dat['fs'][0])
fir_len = 150
stop_limit = 500 / fs
wn = stop_limit / (fs/2)
b = sig.firwin(fir_len, wn)
eog_v_f = sig.filtfilt(b, 1, eog_v)
eog_h_f = sig.filtfilt(b, 1, eog_h)
p = PyGERT()
p.train(eog_h_f, eog_v_f)
results[i, 0] = p.mu_fix
results[i, 1] = p.sigma_fix
results[i, 2] = p.prior_fix
results[i, 3] = p.mu_sac
results[i, 4] = p.sigma_sac
results[i, 5] = p.prior_sac
results[i, 6] = p.mu_bli
results[i, 7] = p.sigma_bli
results[i, 8] = p.prior_bli
results[i, 9] = p.mu_bs
results[i, 10] = p.sigma_bs
results[i, 11] = p.prior_bs
print(results)
np.savetxt('segment_test_python.csv', results, delimiter=',')
def test_train_fulldata():
eog_h_f, eog_v_f = prepare_data()
p = PyGERT()
p.train(eog_h_f, eog_v_f)
print(' \tmu\tsd\tpri')
print('sac:\t%0.2f\t%0.2f\t%0.2f' % (p.mu_sac, p.sigma_sac, p.prior_sac))
print('bli:\t%0.2f\t%0.2f\t%0.2f' % (p.mu_bli, p.sigma_bli, p.prior_bli))
print('fix:\t%0.2f\t%0.2f\t%0.2f' % (p.mu_fix, p.sigma_fix, p.prior_fix))
print('bs :\t%0.2f\t%0.2f\t%0.2f' % (p.mu_bs, p.sigma_bs, p.prior_bs))
def test_train_fulldata():
eog_h_f, eog_v_f = prepare_data()
p = PyGERT()
p.train(eog_h_f, eog_v_f)
print(' \tmu\tsd\tpri')
print('sac:\t%0.2f\t%0.2f\t%0.2f' % (p.mu_sac, p.sigma_sac, p.prior_sac))
print('bli:\t%0.2f\t%0.2f\t%0.2f' % (p.mu_bli, p.sigma_bli, p.prior_bli))
print('fix:\t%0.2f\t%0.2f\t%0.2f' % (p.mu_fix, p.sigma_fix, p.prior_fix))
print('bs :\t%0.2f\t%0.2f\t%0.2f' % (p.mu_bs, p.sigma_bs, p.prior_bs))
