def Gen_Filtering_Graph(relation_count=100, ori_tw_count=30): """ this function aim to generate a graph that was filtered by certain criterion """ import FSDao import igraph g = FSDao.read_pickle_graph(properties["base_dir"] + properties["expr_dir"] + "relation.pickle.old") f = open(properties["base_dir"] + "users_unfilter.csv") uid_list = [] for line in f: t = line.strip().split(",") if int(t[1]) <= relation_count: continue if int(t[2]) <= ori_tw_count: continue uid_list.append(int(t[0])) f.close() sub_vlsit = [v.index for v in g.vs if v["user_id"] in uid_list] g_sub = g.subgraph(sub_vlsit) # FSDao.write_pickle(properties['base_dir']+properties['expr_dir'],'relation.pickle',g_sub) return g_sub pass
def Gen_Filtering_Graph(relation_count=100, ori_tw_count=30): ''' this function aim to generate a graph that was filtered by certain criterion ''' import FSDao import igraph g = FSDao.read_pickle_graph(properties['base_dir'] + properties['expr_dir'] + 'relation.pickle.old') f = open(properties['base_dir'] + 'users_unfilter.csv') uid_list = [] for line in f: t = line.strip().split(',') if int(t[1]) <= relation_count: continue if int(t[2]) <= ori_tw_count: continue uid_list.append(int(t[0])) f.close() sub_vlsit = [v.index for v in g.vs if v['user_id'] in uid_list] g_sub = g.subgraph(sub_vlsit) #FSDao.write_pickle(properties['base_dir']+properties['expr_dir'],'relation.pickle',g_sub) return g_sub pass
def __init__(self, base_dir,expr_dir): self.base_dir=base_dir self.expr_dir=expr_dir self.g=FSDao.read_pickle_graph(self.base_dir+self.expr_dir+SQLDao.ce.properties['relation_graph_file_name']) pass