verbose=args.verbose, mcmc_equilibrate_args={ 'verbose': args.verbose, 'epsilon': 1e-4 }) t_partition = timeit.default_timer() t_end = timeit.default_timer() print('\nGraph partition took {} seconds'.format(t_end - t_start)) evaluation.total_runtime(t_start, t_end) if args.sample_type != "none": print("===== Evaluating graph sampling =====") evaluation.evaluate_sampling(full_graph, sampled_graph, full_graph_partition, sampled_graph_partition, block_mapping, vertex_mapping, samplestack.true_block_assignment) evaluation.num_nodes = full_graph.num_vertices() evaluation.num_edges = full_graph.num_edges() # evaluate output partition against the true partition print("===== Evaluating sampled graph partition =====") evaluate_sampled_graph_partition( sampled_graph, samplestack.true_block_assignment[np.fromiter( vertex_mapping.keys(), dtype=np.int32)], sampled_graph_partition, evaluation, block_mapping) print("===== Evaluating full graph partition =====") evaluate_partition(full_graph, samplestack.true_block_assignment, full_graph_partition, evaluation) else: evaluation.loading = t_load - t_start