def test_diff_between_canonical_variables(self):
"""Test if the scaled canonical variables are almost same."""
rho, w_x, w_y = calculate_cca(self.dat_x, self.dat_y)
cv_x = apply_spatial_filter(self.dat_x, w_x)
cv_y = apply_spatial_filter(self.dat_y, w_y)
def scale(x):
tmp = x.data - x.data.mean()
return tmp / tmp[np.argmax(np.abs(tmp))]
diff = scale(cv_x) - scale(cv_y)
diff = np.sum(np.abs(diff)) / self.SAMPLES
self.assertTrue(diff < 0.1)
def test_diff_between_canonical_variables(self):
"""Test if the scaled canonical variables are almost same."""
rho, w_x, w_y = calculate_cca(self.dat_x, self.dat_y)
cv_x = apply_spatial_filter(self.dat_x, w_x)
cv_y = apply_spatial_filter(self.dat_y, w_y)
def scale(x):
tmp = x.data - x.data.mean()
return tmp / tmp[np.argmax(np.abs(tmp))]
diff = scale(cv_x) - scale(cv_y)
diff = np.sum(np.abs(diff)) / self.SAMPLES
self.assertTrue(diff < 0.1)
def test_diagonal(self):
"""The whitened data should have all 1s on the covariance matrix."""
a = calculate_whitening_matrix(self.cnt)
dat2 = apply_spatial_filter(self.cnt, a)
vals = np.diag(np.cov(dat2.data.T))
np.testing.assert_array_almost_equal(vals,
[1. for i in range(len(vals))])
def test_zeros(self):
"""The whitened data should have all 0s on the non-diagonals of the covariance matrix."""
a = calculate_whitening_matrix(self.cnt)
dat2 = apply_spatial_filter(self.cnt, a)
cov = np.cov(dat2.data.T)
# substract the diagonals
cov -= np.diag(np.diag(cov))
self.assertAlmostEqual(np.sum(cov), 0)
def test_zeros(self):
"""The whitened data should have all 0s on the non-diagonals of the covariance matrix."""
a = calculate_whitening_matrix(self.cnt)
dat2 = apply_spatial_filter(self.cnt, a)
cov = np.cov(dat2.data.T)
# substract the diagonals
cov -= np.diag(np.diag(cov))
self.assertAlmostEqual(np.sum(cov), 0)
def test_spatial_filter_cnt(self):
"""Spatial filtering should work with cnt."""
cnt_f = apply_spatial_filter(self.cnt, self.w)
# chan 0
np.testing.assert_array_equal(cnt_f.data[:, 0], self.cnt.data[:, 2] - self.cnt.data[:, 1])
# chan 1
np.testing.assert_array_equal(cnt_f.data[:, 1], 0.5 * np.sum(self.cnt.data, axis=-1))
# chan 2
np.testing.assert_array_equal(cnt_f.data[:, 2], self.cnt.data[:, 0])
def test_spatial_filter_cnt(self):
"""Spatial filtering should work with cnt."""
cnt_f = apply_spatial_filter(self.cnt, self.w)
# chan 0
np.testing.assert_array_equal(
cnt_f.data[:, 0], self.cnt.data[:, 2] - self.cnt.data[:, 1])
# chan 1
np.testing.assert_array_equal(cnt_f.data[:, 1],
0.5 * np.sum(self.cnt.data, axis=-1))
# chan 2
np.testing.assert_array_equal(cnt_f.data[:, 2], self.cnt.data[:, 0])
def apply_csp(data,
return_as='filtered',
time_axis=1,
columns_to_apply=(0, 1, -2, -1)):
"""Calculates and applies CSP"""
w, a, d = calculate_csp(data)
if return_as == 'patterns':
return w, a
w = w[:, list(columns_to_apply)]
filtered = apply_spatial_filter(data, w)
if return_as == 'logvar':
filtered.data = np.log(np.var(filtered.data, axis=time_axis))
filtered.axes[1] = np.arange(filtered.data.shape[0])
return filtered
else:
return filtered
def test_prefix_and_postfix(self):
"""Prefix and Postfix are mutual exclusive."""
with self.assertRaises(ValueError):
apply_spatial_filter(self.cnt, self.w, prefix='foo', postfix='bar')
def test_diagonal(self):
"""The whitened data should have all 1s on the covariance matrix."""
a = calculate_whitening_matrix(self.cnt)
dat2 = apply_spatial_filter(self.cnt, a)
vals = np.diag(np.cov(dat2.data.T))
np.testing.assert_array_almost_equal(vals, [1. for i in range(len(vals))])
def test_prefix(self):
"""Apply prefix correctly."""
cnt_f = apply_spatial_filter(self.cnt, self.w, prefix='foo')
self.assertEqual(cnt_f.axes[-1], ['foo'+str(i) for i in range(CHANS)])
def test_apply_spatial_filter_copy(self):
"""apply_spatial_filter must not modify arguments."""
cpy = self.cnt.copy()
apply_spatial_filter(self.cnt, self.w)
self.assertEqual(self.cnt, cpy)
def test_postfix_w_wrong_type(self):
"""Raise TypeError if postfix is neither None or str."""
with self.assertRaises(TypeError):
apply_spatial_filter(self.cnt, self.w, postfix=1)
def test_postfix(self):
"""Apply postfix correctly."""
cnt_f = apply_spatial_filter(self.cnt, self.w, postfix='foo')
self.assertEqual(cnt_f.axes[-1],
[c + 'foo' for c in self.cnt.axes[-1]])
def test_apply_spatial_filter_copy(self):
"""apply_spatial_filter must not modify arguments."""
cpy = self.cnt.copy()
apply_spatial_filter(self.cnt, self.w)
self.assertEqual(self.cnt, cpy)
def test_prefix_and_postfix(self):
"""Prefix and Postfix are mutual exclusive."""
with self.assertRaises(ValueError):
apply_spatial_filter(self.cnt, self.w, prefix='foo', postfix='bar')
def test_spatial_filter_epo(self):
"""Spatial filtering should work with epo."""
cnt_f = apply_spatial_filter(self.cnt, self.w)
epo_f = apply_spatial_filter(self.epo, self.w)
for i in range(EPOS):
np.testing.assert_array_equal(epo_f.data[i, ...], cnt_f.data)
def test_shape(self):
"""The spatial filtered data should keep its shape."""
cnt_f = apply_spatial_filter(self.cnt, self.w)
epo_f = apply_spatial_filter(self.epo, self.w)
self.assertEqual(self.cnt.data.shape, cnt_f.data.shape)
self.assertEqual(self.epo.data.shape, epo_f.data.shape)
def test_shape(self):
"""The spatial filtered data should keep its shape."""
cnt_f = apply_spatial_filter(self.cnt, self.w)
epo_f = apply_spatial_filter(self.epo, self.w)
self.assertEqual(self.cnt.data.shape, cnt_f.data.shape)
self.assertEqual(self.epo.data.shape, epo_f.data.shape)
def test_postfix(self):
"""Apply postfix correctly."""
cnt_f = apply_spatial_filter(self.cnt, self.w, postfix='foo')
self.assertEqual(cnt_f.axes[-1], [c+'foo' for c in self.cnt.axes[-1]])
def test_spatial_filter_epo(self):
"""Spatial filtering should work with epo."""
cnt_f = apply_spatial_filter(self.cnt, self.w)
epo_f = apply_spatial_filter(self.epo, self.w)
for i in range(EPOS):
np.testing.assert_array_equal(epo_f.data[i, ...], cnt_f.data)
def test_prefix(self):
"""Apply prefix correctly."""
cnt_f = apply_spatial_filter(self.cnt, self.w, prefix='foo')
self.assertEqual(cnt_f.axes[-1],
['foo' + str(i) for i in range(CHANS)])
def test_apply_spatial_filter_swapaxes(self):
"""apply_spatial_filter must work with nonstandard chanaxis."""
epo_f = apply_spatial_filter(swapaxes(self.epo, 1, -1), self.w, chanaxis=1)
epo_f = swapaxes(epo_f, 1, -1)
epo_f2 = apply_spatial_filter(self.epo, self.w)
self.assertEqual(epo_f, epo_f2)
def test_postfix_w_wrong_type(self):
"""Raise TypeError if postfix is neither None or str."""
with self.assertRaises(TypeError):
apply_spatial_filter(self.cnt, self.w, postfix=1)
