def test_spatio_temporal_src_connectivity(): """Test spatio-temporal connectivity from source spaces""" tris = np.array([[0, 1, 2], [3, 4, 5]]) src = [dict(), dict()] connectivity = spatio_temporal_tris_connectivity(tris, 2) src[0]['use_tris'] = np.array([[0, 1, 2]]) src[1]['use_tris'] = np.array([[0, 1, 2]]) src[0]['vertno'] = np.array([0, 1, 2]) src[1]['vertno'] = np.array([0, 1, 2]) connectivity2 = spatio_temporal_src_connectivity(src, 2) assert_array_equal(connectivity.todense(), connectivity2.todense()) # add test for dist connectivity src[0]['dist'] = np.ones((3, 3)) - np.eye(3) src[1]['dist'] = np.ones((3, 3)) - np.eye(3) src[0]['vertno'] = [0, 1, 2] src[1]['vertno'] = [0, 1, 2] connectivity3 = spatio_temporal_src_connectivity(src, 2, dist=2) assert_array_equal(connectivity.todense(), connectivity3.todense()) # add test for source space connectivity with omitted vertices inverse_operator = read_inverse_operator(fname_inv) with warnings.catch_warnings(record=True) as w: warnings.simplefilter('always') src_ = inverse_operator['src'] connectivity = spatio_temporal_src_connectivity(src_, n_times=2) assert len(w) == 1 a = connectivity.shape[0] / 2 b = sum([s['nuse'] for s in inverse_operator['src']]) assert_true(a == b)
def test_spatio_temporal_src_connectivity(): """Test spatio-temporal connectivity from source spaces""" tris = np.array([[0, 1, 2], [3, 4, 5]]) src = [dict(), dict()] connectivity = spatio_temporal_tris_connectivity(tris, 2) src[0]['use_tris'] = np.array([[0, 1, 2]]) src[1]['use_tris'] = np.array([[0, 1, 2]]) src[0]['vertno'] = np.array([0, 1, 2]) src[1]['vertno'] = np.array([0, 1, 2]) connectivity2 = spatio_temporal_src_connectivity(src, 2) assert_array_equal(connectivity.todense(), connectivity2.todense()) # add test for dist connectivity src[0]['dist'] = np.ones((3, 3)) - np.eye(3) src[1]['dist'] = np.ones((3, 3)) - np.eye(3) src[0]['vertno'] = [0, 1, 2] src[1]['vertno'] = [0, 1, 2] connectivity3 = spatio_temporal_src_connectivity(src, 2, dist=2) assert_array_equal(connectivity.todense(), connectivity3.todense()) # add test for source space connectivity with omitted vertices inverse_operator = read_inverse_operator(fname_inv) with warnings.catch_warnings(record=True) as w: connectivity = spatio_temporal_src_connectivity( inverse_operator['src'], n_times=2) assert len(w) == 1 a = connectivity.shape[0] / 2 b = sum([s['nuse'] for s in inverse_operator['src']]) assert_true(a == b)
def test_spatio_temporal_tris_connectivity(): """Test spatio-temporal connectivity from triangles""" tris = np.array([[0, 1, 2], [3, 4, 5]]) connectivity = spatio_temporal_tris_connectivity(tris, 2) x = [1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1] components = stats.cluster_level._get_components(np.array(x), connectivity) assert_array_equal(components, [0, 0, -2, -2, -2, -2, 0, -2, -2, -2, -2, 1])
def test_spatio_temporal_src_connectivity(): """Test spatio-temporal connectivity from source spaaces""" tris = np.array([[0, 1, 2], [3, 4, 5]]) src = [dict(), dict()] connectivity = spatio_temporal_tris_connectivity(tris, 2) src[0]['use_tris'] = np.array([[0, 1, 2]]) src[1]['use_tris'] = np.array([[0, 1, 2]]) connectivity2 = spatio_temporal_src_connectivity(src, 2) assert_array_equal(connectivity.todense(), connectivity2.todense())
def test_spatio_temporal_tris_connectivity(): """Test spatio-temporal connectivity from triangles""" tris = np.array([[0, 1, 2], [3, 4, 5]]) connectivity = spatio_temporal_tris_connectivity(tris, 2) x = [1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1] components = stats.cluster_level._get_components(np.array(x), connectivity) # _get_components works differently now... old_fmt = [0, 0, -2, -2, -2, -2, 0, -2, -2, -2, -2, 1] new_fmt = np.array(old_fmt) new_fmt = [np.nonzero(new_fmt == v)[0] for v in np.unique(new_fmt[new_fmt >= 0])] assert_true(len(new_fmt), len(components)) for c, n in zip(components, new_fmt): assert_array_equal(c, n)