test_affinity_propagation.py 文件源码

def test_affinity_propagation():
    # Affinity Propagation algorithm
    # Compute similarities
    S = -euclidean_distances(X, squared=True)
    preference = np.median(S) * 10
    # Compute Affinity Propagation
    cluster_centers_indices, labels = affinity_propagation(
        S, preference=preference)

    n_clusters_ = len(cluster_centers_indices)

    assert_equal(n_clusters, n_clusters_)

    af = AffinityPropagation(preference=preference, affinity="precomputed")
    labels_precomputed = af.fit(S).labels_

    af = AffinityPropagation(preference=preference, verbose=True)
    labels = af.fit(X).labels_

    assert_array_equal(labels, labels_precomputed)

    cluster_centers_indices = af.cluster_centers_indices_

    n_clusters_ = len(cluster_centers_indices)
    assert_equal(np.unique(labels).size, n_clusters_)
    assert_equal(n_clusters, n_clusters_)

    # Test also with no copy
    _, labels_no_copy = affinity_propagation(S, preference=preference,
                                             copy=False)
    assert_array_equal(labels, labels_no_copy)

    # Test input validation
    assert_raises(ValueError, affinity_propagation, S[:, :-1])
    assert_raises(ValueError, affinity_propagation, S, damping=0)
    af = AffinityPropagation(affinity="unknown")
    assert_raises(ValueError, af.fit, X)