lsgg_compose_util.py 文件源码

def core_substitution(graph, orig_cip_graph, new_cip_graph):
    """
    graph is the whole graph..
    subgraph is the interfaceregrion in that we will transplant
    new_cip_graph which is the interface and the new core
    """
    graph=_edge_to_vertex(graph)
    assert( set(orig_cip_graph.nodes()) - set(graph.nodes()) == set([]) ), 'orig_cip_graph not in graph'

    # select only the interfaces of the cips
    new_graph_interface_nodes = [n for n, d in new_cip_graph.nodes(data=True) if 'core' not in d]
    new_cip_interface_graph = nx.subgraph(new_cip_graph, new_graph_interface_nodes)

    original_graph_interface_nodes = [n for n, d in orig_cip_graph.nodes(data=True) if 'core' not in d]
    original_interface_graph = nx.subgraph(orig_cip_graph, original_graph_interface_nodes)
    # get isomorphism between interfaces, if none is found we return an empty graph

    iso = get_good_isomorphism(graph,
                               orig_cip_graph,
                               new_cip_graph,
                               original_interface_graph,
                               new_cip_interface_graph)

    if len(iso) != len(original_interface_graph):
        # print iso
        # draw.display(orig_cip_graph)
        # draw.display(new_cip_graph)
        #draw.graphlearn([orig_cip_graph, new_cip_graph],size=10)
        logger.log(5,"grammar hash collision, discovered in 'core_substution' ")
        return None

    # ok we got an isomorphism so lets do the merging
    graph = nx.union(graph, new_cip_graph, rename=('', '-'))

    # removing old core
    # original_graph_core_nodes = [n for n, d in orig_cip_graph.nodes(data=True) if 'core' in d]
    original_graph_core_nodes = [n for n, d in orig_cip_graph.nodes(data=True) if 'core' in d]

    for n in original_graph_core_nodes:
        graph.remove_node(str(n))

    # merge interfaces
    for k, v in iso.iteritems():
        #graph.node[str(k)][
        #    'intgggerface'] = True  # i am marking the interface only for the backflow probability calculation in graphlearn, this is probably deleteable because we also do this in merge, also this line is superlong Ooo
        merge(graph, str(k), '-' + str(v))
    # unionizing killed my labels so we need to relabel

    graph=eg._revert_edge_to_vertex_transform(graph)
    re = nx.convert_node_labels_to_integers(graph)
    graph_clean(re)

    return re