rd[f] = np.zeros(max_k, dtype=float) for res in results: for f in RES_FIELDS: res_line = np.array(res[f]) rd[f] += res_line for f in RES_FIELDS: rd[f] /= len(SEEDS) rd[f] = rd[f].tolist() return rd if __name__ == "__main__": config = cfg.Configuration(f"./config") # Initialize Evaluation Configuration for k, v in USE_CONFIG.items(): globals()[k] = v # Configurations ds_config = config.ds_config() em_config = config.em_config(DATASET) ev_config = config.ev_config(DATASET) os.makedirs(f"./output/", exist_ok=True) # Runner runner = rs.RunStages(0, DATASET, None, None) graphs = runner.load_graphs(ds_config, NORMALIZATION, HIDE_PERC)
print(f"{ph.INFO} No method specified, skipping") def enlarge_graph(runner: rs.RunStages, config: cfg.Configuration, args): print(f" <<< === ENLARGE === >>> ") if args.add_edges: enlarge_file = f"{args.embed_method}#{TIMESTAMP}.csv" enlarge_dir = f"{args.output}/{args.enlarge_dir}/{args.dataset}" os.makedirs(enlarge_dir, exist_ok=True) runner.enlarge_graph(args.add_edges, f"{enlarge_dir}/{enlarge_file}") else: print(f"{ph.INFO} Not specified, wont add edges") if __name__ == "__main__": args = parse_arguments() # Run Managers runner = rs.RunStages(args.seed, args.dataset, args.embed_method, args.eval_method) config = cfg.Configuration(args.config) # Run Stages load_graphs(runner, config, args) get_embeddings(runner, config, args) run_evaluations(runner, config, args) enlarge_graph(runner, config, args) print(f"{ph.OK} Done.")