def test_data(self):
w = BDFWriter(psychic.find_data_path('sine-256Hz-test.bdf'),
header=self.header)
w.write(self.d)
w.close()
d2 = load_bdf(psychic.find_data_path('sine-256Hz-test.bdf'))
np.testing.assert_allclose(self.d.data, d2.data, atol=0.05)
def test_save(self):
d = load_bdf(psychic.find_data_path('sine-256Hz.bdf'))
save_bdf(d, psychic.find_data_path('sine-256Hz-test.bdf'))
d2 = load_bdf(psychic.find_data_path('sine-256Hz-test.bdf'))
self.assertEqual(d.feat_lab, d2.feat_lab)
np.testing.assert_allclose(d.data, d2.data, atol=0.0001)
np.testing.assert_allclose(d.labels, d2.labels)
np.testing.assert_allclose(d.ids, d2.ids)
def test_header(self):
w = BDFWriter(psychic.find_data_path('sine-256Hz-test.bdf'),
header=self.header)
w.write(self.d)
w.close()
with open(psychic.find_data_path('sine-256Hz.bdf'), "rb") as f:
file1 = f.read()
with open(psychic.find_data_path('sine-256Hz-test.bdf'), "rb") as f:
file2 = f.read()
header_length = 4608
self.assertEqual(file1[:header_length], file2[:header_length])
def test_header_types(self):
# Test using a DataSet for header values
w = BDFWriter(psychic.find_data_path('sine-256Hz-test.bdf'),
dataset=self.d)
w.write(self.d)
w.close()
r = BDFReader(psychic.find_data_path('sine-256Hz-test.bdf'))
np.testing.assert_array_equal(r.header['n_samples_per_record'], 256)
# Test specifying a sample_rate and num_samples for header values
w = BDFWriter(psychic.find_data_path('sine-256Hz-test.bdf'),
sample_rate=256, num_channels=self.d.nfeatures)
w.write(self.d)
w.close()
r = BDFReader(psychic.find_data_path('sine-256Hz-test.bdf'))
np.testing.assert_array_equal(r.header['n_samples_per_record'], 256)
def test_load(self):
d = load_bdf(psychic.find_data_path('sine-256Hz.bdf'))
# test labels
targets = [['A%d' % (i + 1) for i in range(16)]]
self.assertEqual(d.feat_lab, targets)
self.assertEqual(d.cl_lab, ['class254', 'class255'])
# test ids ~ time
self.assertAlmostEqual(d.ids[0, 256 + 1], 1, 2)
# test dims
self.assertEqual(d.nfeatures, 16)
self.assertEqual(d.ninstances, 60 * 256)
self.assertEqual(d.extra, {})
def setUp(self):
self.d = load_bdf(psychic.find_data_path('sine-256Hz.bdf'))
r = BDFReader(psychic.find_data_path('sine-256Hz.bdf'))
self.header = r.header
r.close()
def setUp(self):
self.bdf = BDFReader(open(psychic.find_data_path('sine-256Hz.bdf'), 'rb'))
import psychic
import golem
from matplotlib import pyplot as plt
trials = golem.DataSet.load(psychic.find_data_path('priming-trials.dat'))
trials = psychic.nodes.Baseline((-0.2, 0)).train_apply(trials, trials)
psychic.plot_erp(trials.lix[['Fz', 'Cz', 'Pz'], :, :], fwer=None)
plt.savefig('plot_erp.png')
erp = psychic.nodes.ERP().apply(trials)
psychic.plot_erp(erp.lix[['Fz', 'Cz', 'Pz'], :, :])
plt.savefig('plot_erp_erp.png')