def test_borderline_smote_no_in_danger_samples(kind):
    """Check that the algorithm behave properly even on a dataset without any sample
    in danger.
    """
    X, y = make_classification(
        n_samples=500,
        n_features=2,
        n_informative=2,
        n_redundant=0,
        n_repeated=0,
        n_clusters_per_class=1,
        n_classes=3,
        weights=[0.1, 0.2, 0.7],
        class_sep=1.5,
        random_state=1,
    )
    smote = BorderlineSMOTE(kind=kind, m_neighbors=3, k_neighbors=5, random_state=0)
    X_res, y_res = smote.fit_resample(X, y)

    assert_allclose(X, X_res)
    assert_allclose(y, y_res)
    assert not smote.in_danger_indices
Check that the algorithm behave properly even on a dataset without any sample
    in danger.
    
imblearn/over_sampling/_smote/tests/test_borderline_smote.py