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.")