How to use the kmapper.cluster function in kmapper

def test_simplices(self):
        mapper = KeplerMapper()

        X = np.random.rand(100, 2)
        lens = mapper.fit_transform(X)
        graph = mapper.map(
            lens,
            X=X,
            cover=Cover(n_cubes=3, perc_overlap=0.75),
            clusterer=cluster.DBSCAN(metric="euclidean", min_samples=3),
        )
        assert max([len(s) for s in graph["simplices"]]) <= 2

        nodes = [n for n in graph["simplices"] if len(n) == 1]
        edges = [n for n in graph["simplices"] if len(n) == 2]
        assert len(nodes) == 3
        assert len(edges) == 3

def test_remove_duplicates_argument(self, capsys):
        mapper = KeplerMapper(verbose=1)
        X = np.random.rand(100, 5)

        lens = mapper.project(X)
        graph = mapper.map(
            lens,
            X=X,
            cover=Cover(n_cubes=2, perc_overlap=1),
            clusterer=cluster.DBSCAN(metric="euclidean", min_samples=3),
            remove_duplicate_nodes=True,
        )

        captured = capsys.readouterr()
        assert "duplicate nodes" in captured[0]