How to use the dtaidistance.clustering.LinkageTree function in dtaidistance

def test_linkage_tree():
    s = np.array([
         [0., 0, 1, 2, 1, 0, 1, 0, 0],
         [0., 1, 2, 0, 0, 0, 0, 0, 0],
         [1., 2, 0, 0, 0, 0, 0, 1, 1],
         [0., 0, 1, 2, 1, 0, 1, 0, 0],
         [0., 1, 2, 0, 0, 0, 0, 0, 0],
         [1., 2, 0, 0, 0, 0, 0, 1, 1],
         [1., 2, 0, 0, 0, 0, 0, 1, 1]])

    model = clustering.LinkageTree(dtw.distance_matrix_fast, {})
    cluster_idx = model.fit(s)

    if directory:
        hierarchy_fn = os.path.join(directory, "hierarchy.png")
        graphviz_fn = os.path.join(directory, "hierarchy.dot")
    else:
        file = tempfile.NamedTemporaryFile()
        hierarchy_fn = file.name + "_hierarchy.png"
        graphviz_fn = file.name + "_hierarchy.dot"
    model.plot(hierarchy_fn)
    print("Figure saved to", hierarchy_fn)
    with open(graphviz_fn, "w") as ofile:
        print(model.to_dot(), file=ofile)
    print("Dot saved to", graphviz_fn)