def test_spectral_embedding_amg_solver(seed=36):
# Test spectral embedding with amg solver
pytest.importorskip('pyamg')
se_amg = SpectralEmbedding(n_components=2,
affinity="nearest_neighbors",
eigen_solver="amg",
n_neighbors=5,
random_state=np.random.RandomState(seed))
se_arpack = SpectralEmbedding(n_components=2,
affinity="nearest_neighbors",
eigen_solver="arpack",
n_neighbors=5,
random_state=np.random.RandomState(seed))
embed_amg = se_amg.fit_transform(S)
embed_arpack = se_arpack.fit_transform(S)
assert _check_with_col_sign_flipping(embed_amg, embed_arpack, 1e-5)
# same with special case in which amg is not actually used
# regression test for #10715
# affinity between nodes
row = [0, 0, 1, 2, 3, 3, 4]
col = [1, 2, 2, 3, 4, 5, 5]
val = [100, 100, 100, 1, 100, 100, 100]
affinity = sparse.coo_matrix((val + val, (row + col, col + row)),
shape=(6, 6)).toarray()
se_amg.affinity = "precomputed"
se_arpack.affinity = "precomputed"
embed_amg = se_amg.fit_transform(affinity)
embed_arpack = se_arpack.fit_transform(affinity)
assert _check_with_col_sign_flipping(embed_amg, embed_arpack, 1e-5)
