test_k_means.py 文件源码

def test_sparse_mb_k_means_callable_init():

    def test_init(X, k, random_state):
        return centers

    # Small test to check that giving the wrong number of centers
    # raises a meaningful error
    msg = "does not match the number of clusters"
    assert_raises_regex(ValueError, msg, MiniBatchKMeans(init=test_init,
                                                         random_state=42).fit,
                        X_csr)

    # Now check that the fit actually works
    mb_k_means = MiniBatchKMeans(n_clusters=3, init=test_init,
                                 random_state=42).fit(X_csr)
    _check_fitted_model(mb_k_means)