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
