How to use the dgl.graph_index.create_graph_index function in dgl

def test_create_from_elist():
    elist = [(2, 1), (1, 0), (2, 0), (3, 0), (0, 2)]
    g = create_graph_index(elist)
    for i, (u, v) in enumerate(elist):
        assert g.edge_id(u, v)[0] == i
    # immutable graph

def generate_from_edgelist():
    edges = [[2, 3], [2, 5], [3, 0], [6, 10], [10, 3], [10, 15]]
    g = create_graph_index(edges, multigraph=False, readonly=False)
    ig = create_graph_index(edges, multigraph=False, readonly=True)
    return g, ig

def generate_from_networkx():
    edges = [[2, 3], [2, 5], [3, 0], [1, 0], [4, 3], [4, 5]]
    nx_graph = nx.DiGraph()
    nx_graph.add_edges_from(edges)
    g = create_graph_index(nx_graph, multigraph=False, readonly=False)
    ig = create_graph_index(nx_graph, multigraph=False, readonly=True)
    return g, ig

def test_nx():
    gi = create_graph_index(multigraph=True)

    gi.add_nodes(2)
    gi.add_edge(0, 1)
    nxg = gi.to_networkx()
    assert len(nxg.nodes) == 2
    assert len(nxg.edges(0, 1)) == 1
    gi.add_edge(0, 1)
    nxg = gi.to_networkx()
    assert len(nxg.edges(0, 1)) == 2

    nxg = nx.DiGraph()
    nxg.add_edge(0, 1)
    gi = create_graph_index(nxg)
    assert not gi.is_multigraph()
    assert gi.number_of_nodes() == 2
    assert gi.number_of_edges() == 1

def test_pickling_graph_index():
    gi = create_graph_index(None, False, False)
    gi.add_nodes(3)
    src_idx = toindex([0, 0])
    dst_idx = toindex([1, 2])
    gi.add_edges(src_idx, dst_idx)

    gi2 = _reconstruct_pickle(gi)

    assert gi2.number_of_nodes() == gi.number_of_nodes()
    src_idx2, dst_idx2, _ = gi2.edges()
    assert F.array_equal(src_idx.tousertensor(), src_idx2.tousertensor())
    assert F.array_equal(dst_idx.tousertensor(), dst_idx2.tousertensor())

def generate_from_networkx():
    edges = [[2, 3], [2, 5], [3, 0], [1, 0], [4, 3], [4, 5]]
    nx_graph = nx.DiGraph()
    nx_graph.add_edges_from(edges)
    g = create_graph_index(nx_graph, multigraph=False, readonly=False)
    ig = create_graph_index(nx_graph, multigraph=False, readonly=True)
    return g, ig

def generate_rand_graph(n):
    arr = (sp.sparse.random(n, n, density=0.1, format='coo') != 0).astype(np.int64)
    g = create_graph_index(arr)
    ig = create_graph_index(arr, readonly=True)
    return g, ig

def test_predsucc():
    gi = create_graph_index(multigraph=True)

    gi.add_nodes(4)
    gi.add_edge(0, 1)
    gi.add_edge(0, 1)
    gi.add_edge(0, 2)
    gi.add_edge(2, 0)
    gi.add_edge(3, 0)
    gi.add_edge(0, 0)
    gi.add_edge(0, 0)

    pred = gi.predecessors(0)
    assert len(pred) == 3
    assert 2 in pred
    assert 3 in pred
    assert 0 in pred

assert gi.number_of_edges() == 1
    assert gi.edge_id(0, 1)[0] == 0

    nxg = nx.MultiDiGraph()
    nxg.add_edge(0, 1)
    nxg.add_edge(0, 1)
    gi = create_graph_index(nxg, True)
    assert gi.is_multigraph()
    assert gi.number_of_nodes() == 2
    assert gi.number_of_edges() == 2
    assert 0 in gi.edge_id(0, 1)
    assert 1 in gi.edge_id(0, 1)

    nxg = nx.DiGraph()
    nxg.add_nodes_from(range(3))
    gi = create_graph_index(nxg)
    assert gi.number_of_nodes() == 3
    assert gi.number_of_edges() == 0

    gi = create_graph_index()
    gi.add_nodes(3)
    nxg = gi.to_networkx()
    assert len(nxg.nodes) == 3
    assert len(nxg.edges) == 0

    nxg = nx.DiGraph()
    nxg.add_edge(0, 1, id=0)
    nxg.add_edge(1, 2, id=1)
    gi = create_graph_index(nxg)
    assert 0 in gi.edge_id(0, 1)
    assert 1 in gi.edge_id(1, 2)
    assert gi.number_of_edges() == 2

def test_edges():
    gi = create_graph_index()
    gi.add_nodes(10)
    gi.add_edges(toindex([5,5,5,5]), toindex([6,7,8,9]))
    gi.add_edges(toindex([0,0,0,0]), toindex([1,2,3,4]))
    gi.add_edges(toindex([1,1,1,1]), toindex([2,3,4,5]))
    src, dst, eid = gi.edges()
    src0, dst0, eid0 = src.tonumpy(), dst.tonumpy(), eid.tonumpy()
    gi.readonly()
    src, dst, eid = gi.edges()
    src, dst, eid = src.tonumpy(), dst.tonumpy(), eid.tonumpy()
    import numpy as np
    assert np.array_equal(src, src0)
    assert np.array_equal(dst, dst0)
    assert np.array_equal(eid, eid0)