How to use the dtaidistance.dtw.distance_matrix function in dtaidistance

def test_bug3():
    series = np.array([
        np.array([1, 2, 1]),
        np.array([0., 1, 2, 0, 0, 0, 0, 0, 0]),
        np.array([1., 2, 0, 0, 0, 0, 0, 1, 1, 3, 4, 5]),
        np.array([0., 0, 1, 2, 1, 0, 1]),
        np.array([0., 1, 2, 0, 0, 0, 0, 0]),
        np.array([1., 2, 0, 0, 0, 0, 0, 1, 1])])
    ds = dtw.distance_matrix(series)
    print(ds)

    model = clustering.LinkageTree(dtw.distance_matrix, {})
    cluster_idx = model.fit(series)
    print(cluster_idx)

    if directory:
        fn = directory / "bug3.png"
    else:
        file = tempfile.NamedTemporaryFile()
        fn = Path(file.name + "_bug3.png")

    model.plot(fn, show_ts_label=True)

def test_distance_matrix1_b():
    s = [[0, 0, 1, 2, 1, 0, 1, 0, 0],
         [0, 1, 2, 0, 0, 0, 0, 0, 0]]
    s = [np.array(si) for si in s]
    m2 = dtw.distance_matrix(s, parallel=True, use_c=False)
    assert m2[0, 1] == pytest.approx(math.sqrt(2))

def d():
        return dtw.distance_matrix(s, parallel=False, use_c=True, use_nogil=False, compact=True)

def test_bug1_psi():
    s = [np.array([0., 0, 1, 2, 1, 0, 1, 0, 0]),
         np.array([9., 0, 1, 2, 1, 0, 1, 0, 9])]

    res1 = dtw.distance_matrix(s, compact=True, psi=1)
    res2 = dtw.distance_matrix_fast(s, compact=True, psi=1)
    print(res1)
    print(res2)
    assert res1 == pytest.approx(res2)

def d():
        return dtw.distance_matrix(s, parallel=False, use_c=False, use_nogil=False, compact=True)

def test_distance_matrix2_e():
    n = 1
    nn = 1
    s = [[0., 0, 1, 2, 1, 0, 1, 0, 0] * n,
         [0., 1, 2, 0, 0, 0, 0, 0, 0] * n,
         [1., 2, 0, 0, 0, 0, 0, 1] * n] * nn
    s = [np.array(si) for si in s]
    m1 = dtw_c.distance_matrix_nogil(s, is_parallel=True)
    m1 = dtw.distances_array_to_matrix(m1, len(s))
    m2 = dtw.distance_matrix(s, parallel=True, use_c=True, use_nogil=True)
    assert m1[0, 1] == math.sqrt(2) * n, "m1[0,1]={} != {}".format(m1[0, 1], math.sqrt(2) * n)
    assert m2[0, 1] == math.sqrt(2) * n, "m2[0,1]={} != {}".format(m2[0, 1], math.sqrt(2) * n)

def run_distance_matrix_block(parallel=False, use_c=False, use_nogil=False):
    # print(parallel, use_c, use_nogil)
    s = [[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]]
    s = np.array(s)
    m = dtw.distance_matrix(s, block=((1, 4), (3, 5)), parallel=parallel, use_c=use_c, use_nogil=use_nogil)
    print(m)
    assert m[1, 3] == pytest.approx(math.sqrt(2))
    assert np.isinf(m[1, 2])