def test_agg_ch(self):
"""Test channels aggregation."""
# build dataset (with aggregation)
d_3d = self._get_data(3)
ds = DatasetEphy(d_3d, roi='roi', agg_ch=True, **kw)
ds_roi2 = ds.get_roi_data("roi_0", copnorm=False)
np.testing.assert_array_equal(ds_roi2['agg_ch'].data, [0] * 30)
# build dataset (without aggregation)
ds = DatasetEphy(d_3d, roi='roi', agg_ch=False, **kw)
ds_roi0 = ds.get_roi_data("roi_0", copnorm=False)
np.testing.assert_array_equal(ds_roi0['agg_ch'].data,
[0] * 10 + [1] * 10 + [6] * 10)
def test_multivariate(self):
"""Test multivariate"""
d_4d = self._get_data(4)
# multivariate = False
ds = DatasetEphy(d_4d, roi='roi', multivariate=False, **kw)
x_roi2 = ds.get_roi_data('roi_2')
assert x_roi2.dims == ('freqs', 'times', 'mv', 'rtr')
assert x_roi2.shape == (4, 100, 1, 20)
# multivariate = True
d_4d = self._get_data(4)
ds = DatasetEphy(d_4d, roi='roi', multivariate=True, **kw)
x_roi2 = ds.get_roi_data('roi_2')
assert x_roi2.dims == ('times', 'mv', 'rtr')
assert x_roi2.shape == (100, 4, 20)
def test_copnorm(self):
"""Test function copnorm."""
# build dataset
d_3d = self._get_data(3)
ds = DatasetEphy(d_3d, y='y', z='z', **kw)
# check copnorm range
ds_roi2 = ds.get_roi_data("roi_2", copnorm=False)
s1_r2, s2_r2 = d_3d[0].sel(roi='roi_2'), d_3d[1].sel(roi='roi_2')
s12 = xr.concat((s1_r2, s2_r2), 'trials').T.expand_dims('mv', axis=-2)
assert 9. < ds_roi2.data.ravel().mean() < 11.
np.testing.assert_array_equal(s12.data, ds_roi2.data)
ds_roi2 = ds.get_roi_data("roi_2", copnorm=True)
assert -1. < ds_roi2.data.ravel().mean() < 1.
# check values (gcrn_per_suj=False)
gc_t = ds.get_roi_data("roi_2", copnorm=True, gcrn_per_suj=False)
np.testing.assert_array_equal(copnorm_nd(s12.data), gc_t.data)
# check values (gcrn_per_suj=True)
gc_t = ds.get_roi_data("roi_2", copnorm=True, gcrn_per_suj=True)
np.testing.assert_array_equal(
copnorm_cat_nd(s12.data, gc_t['subject'].data), gc_t.data)
def test_get_roi_data(self):
"""Test getting the data of a single brain region."""
# build dataset
d_3d = self._get_data(3)
ds = DatasetEphy(d_3d, y='y', z='z', **kw)
# get the data
ds_roi2 = ds.get_roi_data("roi_2", copnorm=False)
np.testing.assert_array_equal(ds_roi2.shape, (100, 1, 20))
# test the data
s1_r2, s2_r2 = d_3d[0].sel(roi='roi_2'), d_3d[1].sel(roi='roi_2')
s12 = xr.concat((s1_r2, s2_r2), 'trials').T.expand_dims('mv', axis=-2)
np.testing.assert_array_equal(ds_roi2.data, s12.data)
# test task-related variables
y_12, z_12 = np.r_[y_int[0], y_int[1]], np.r_[z[0], z[1]]
np.testing.assert_array_equal(y_12, ds_roi2['y'].data)
np.testing.assert_array_equal(z_12, ds_roi2['z'].data)