Exemple #1
0
def out_net_commudet(dbname, colname, name):
    # transform the largest component to undirect for community detection
    # G = nt.load_beh_network(dbname, colname)
    G = nt.load_beh_network(dbname, colname)
    nx.write_edgelist(G, "data/net.data")
    # G = nx.read_edgelist("data/net.data")
    GC = nt.get_gaint_comp(G)
    # nt.net_statis(GC)
    # GCG = GC.to_undirected()
    # nt.net_statis(GCG)
    nx.write_edgelist(GC, "data/comp.data")
    print GC.number_of_selfloops()

    out_net(GC, name)
Exemple #2
0
def plot_communty(dbname, colname, name, commline):
    G = nt.load_network(dbname, colname)
    GC = nt.get_gaint_comp(G)

    id_map = pickle.load(open("data/" + name + "-id.pick", "r"))
    nodelist = list()

    fr = open("data/" + name + "-fc_best.groups", "r")
    line = ""
    while commline not in line:
        line = fr.readline()
    print line
    print "----------------------------"
    for line in fr.readlines():
        if "GROUP" in line:
            break
        else:
            nodelist.append(id_map[int(line.strip())])
    print "node size:", str(len(nodelist))
    # plot.network_top(GC.subgraph(nodelist))
    pickle.dump(nodelist, open("data/" + name + "uid.pick", "w"))
    return GC.subgraph(nodelist)