test_k_means.py 文件源码

def test_minibatch_sensible_reassign_fit():
    # check if identical initial clusters are reassigned
    # also a regression test for when there are more desired reassignments than
    # samples.
    zeroed_X, true_labels = make_blobs(n_samples=100, centers=5,
                                       cluster_std=1., random_state=42)
    zeroed_X[::2, :] = 0
    mb_k_means = MiniBatchKMeans(n_clusters=20, batch_size=10, random_state=42,
                                 init="random")
    mb_k_means.fit(zeroed_X)
    # there should not be too many exact zero cluster centers
    assert_greater(mb_k_means.cluster_centers_.any(axis=1).sum(), 10)

    # do the same with batch-size > X.shape[0] (regression test)
    mb_k_means = MiniBatchKMeans(n_clusters=20, batch_size=201,
                                 random_state=42, init="random")
    mb_k_means.fit(zeroed_X)
    # there should not be too many exact zero cluster centers
    assert_greater(mb_k_means.cluster_centers_.any(axis=1).sum(), 10)