def test_ltsa_eigendecomps():
N = 10
X, color = datasets.samples_generator.make_s_curve(N, random_state=0)
n_components = 2
G = geom.Geometry(adjacency_method = 'brute', adjacency_kwds = {'radius':2})
G.set_data_matrix(X)
mm_ltsa_ref, err_ref = ltsa.ltsa(G, n_components,
eigen_solver=EIGEN_SOLVERS[0])
for eigen_solver in EIGEN_SOLVERS[1:]:
mm_ltsa, err = ltsa.ltsa(G, n_components, eigen_solver=eigen_solver)
assert(_check_with_col_sign_flipping(mm_ltsa, mm_ltsa_ref, 0.05))
def test_ltsa_with_sklearn():
N = 10
X, color = datasets.samples_generator.make_s_curve(N, random_state=0)
n_components = 2
n_neighbors = 3
knn = NearestNeighbors(n_neighbors + 1).fit(X)
G = geom.Geometry()
G.set_data_matrix(X)
G.set_adjacency_matrix(knn.kneighbors_graph(X, mode = 'distance'))
sk_Y_ltsa = manifold.LocallyLinearEmbedding(n_neighbors, n_components,
method = 'ltsa',
eigen_solver = 'arpack').fit_transform(X)
(mm_Y_ltsa, err) = ltsa.ltsa(G, n_components, eigen_solver = 'arpack')
assert(_check_with_col_sign_flipping(sk_Y_ltsa, mm_Y_ltsa, 0.05))