python类barabasi_albert_graph()的实例源码

def SF_Generateor(N=1000, m=3):
    G = nx.barabasi_albert_graph(N, m)
    #component of the network
    if nx.is_connected(G) == False:
        # Get the Greatest Component of Networks #####
        components = sorted(nx.connected_components(G), key = len, reverse=True)
        print "Component Number of the Generated Network:", len(components)

        for i in range(1, len(components)):
            for node in components[i]:
                G.remove_node(node)
        #end for
        print nx.is_connected(G)
    #endif

    return G

#************************************************************************

def SF_Generateor(N=1000, m=3):
    G = nx.barabasi_albert_graph(N, m)
    #component of the network
    if nx.is_connected(G) == False:
        # Get the Greatest Component of Networks #####
        components = sorted(nx.connected_components(G), key = len, reverse=True)
        print "Component Number of the Generated Network:", len(components)

        for i in range(1, len(components)):
            for node in components[i]:
                G.remove_node(node)
        #end for
        print nx.is_connected(G)
    #endif

    return G

#************************************************************************

def save_topology(adj, path, graph_name, link_possibility):
    graph = nx.Graph()

    if not os.path.isdir(path):
        os.makedirs(path)
    # 1. transfer adj to nx
    adj_list = list(np.squeeze(adj[0,:,:,:]))

    for src in range(len(adj_list)):
        graph.add_node(src)
        for dst in range(len(adj_list[src])):
            if adj_list[src][dst] >= link_possibility: # ?? sample ?? ?? [0,1]???
                graph.add_edge(src,dst)

    # 2. read position
    pos_file = glob.glob(path+'*.pos')
    if pos_file == []:
        node_size = len(graph.nodes())
        tmp_graph = nx.barabasi_albert_graph(node_size,2)
        pos = nx.spring_layout(tmp_graph)
        pickle.dump(pos, open(path+'graph.pos','wb'))
    else:
        pos = pickle.load(open(pos_file[0],'rb'))

    # 3. draw graph
    nx.draw_networkx_nodes(graph, pos, node_size=300, node_color='b', alpha=0.8)
    nx.draw_networkx_edges(graph, pos, width=1.5, alpha=0.8)
    nx.draw_networkx_labels(graph, pos, font_color='w')

    plt.savefig(path+'/'+graph_name+'.png')
    plt.savefig(path+'/'+graph_name+'.pdf')
    # plt.show()
    plt.clf()

    # 4. store graph
    pickle.dump(graph, open(path+graph_name+'.graph','wb'))

# ------------------------------
# show_all_variables()
# @purpose: ??TF??????
# ------------------------------