return False data_path = "../DataSet/Transition/" graph_path = "../DataSet/GraphData/" venue_path = "../DataSet/VenueData/" trsn_list = VH.load_pickle_file(data_path, "sf_trsn_small_new") time_list = VH.load_pickle_file(data_path, "sf_time_small_new") full_venue_dict = VH.GetFullVenueDict(venue_path, "venues-CA-new.json") category_dict = VH.load_json(venue_path, "category_map.json") pcategory_dict = VH.load_json(venue_path, "pcategory_map.json") vid_map = create_vid_map(trsn_list) ts_list = TH.gen_ts_list("201201010000", "201301010000", 30) venue_g = snap.TNEANet.New() for ts_idx, ts in enumerate(ts_list): for trsn_idx, trsn in enumerate(trsn_list): src_ts = time_list[trsn_idx][0] # only need check one ts dst_ts = time_list[trsn_idx][1] if within_ts_range(ts, src_ts): src_nid = vid_map[trsn[0]] dst_nid = vid_map[trsn[1]] GH.add_node(venue_g, src_nid, trsn[0], src_ts) GH.add_node(venue_g, dst_nid, trsn[1], dst_ts) GH.add_edge(venue_g, src_nid, dst_nid, time_list[trsn_idx]) GH.add_category(venue_g, full_venue_dict, category_dict, pcategory_dict) print venue_g.GetNodes() GH.save_graph(venue_g, graph_path, "sf_venue_small_" + str(ts))