diff --git a/evalNE_script.py b/evalNE_script.py index dc792636d367b92d54083bc4daddd5bad7d4f0b6..7c1ceeff24d0dd3b4f329c684e2e2f38a3ba4270 100644 --- a/evalNE_script.py +++ b/evalNE_script.py @@ -64,7 +64,7 @@ methods = ['random_prediction', pbar = tqdm(methods,disable= (not args.verbose)) for method in pbar: pbar.set_description("Evaluate "+method) - result = nee.evaluate_baseline(method=method, ) + result = nee.evaluate_baseline(method=method,) scoresheet.log_results(result) if args.network_embedding: @@ -91,7 +91,7 @@ if args.network_embedding: pbar.set_description("Evaluate "+method) command = commands[i] + " --input {} --output {} --representation-size {}" results = nee.evaluate_cmd(method_name=methods[i], method_type='ne', command=command, - edge_embedding_methods=edge_emb, input_delim=' ', output_delim=' ', verbose=args.verbose) + edge_embedding_methods=edge_emb, input_delim=' ', output_delim=' ', verbose=args.verbose,write_weights=nx.is_weighted(G)) scoresheet.log_results(results) except ImportError: diff --git a/lib/random.py b/lib/random.py index 58dd6c61d95e2a419e0ee253dae0c6ad8578cf39..c57df3406a378bdb05d92fe3af86d0194e6f5911 100644 --- a/lib/random.py +++ b/lib/random.py @@ -103,7 +103,8 @@ def _conf_model(degree_seq): def powerlaw_graph(nb_nodes, nb_edges, exponent=2, tries=1000, min_deg=1): """ - Generate a graph with a definied number of vertices, edges, and a degree distribution that fit the power law. + Generate a graph with a defined number of vertices, edges, and a degree distribution that fit the power law. + Using the Molloy-Reed algorithm to Parameters ---------- nb_nodes : int