test_spectral.py 文件源码

def test_spectral_clustering_sparse():
    X, y = make_blobs(n_samples=20, random_state=0,
                      centers=[[1, 1], [-1, -1]], cluster_std=0.01)

    S = rbf_kernel(X, gamma=1)
    S = np.maximum(S - 1e-4, 0)
    S = sparse.coo_matrix(S)

    labels = SpectralClustering(random_state=0, n_clusters=2,
                                affinity='precomputed').fit(S).labels_
    assert_equal(adjusted_rand_score(y, labels), 1)