def main():
start_time = time.time()
args = utils.create_argument_parser()
graph = utils.load_graph(args.dataset, args.w)
graph_copy = deepcopy(graph)
communities = community_search(graph)
com_dict = {}
for i in range(len(communities)):
com_dict[i] = communities[i]
utils.print_comm_info_to_display(com_dict)
print('modularity_value =', modularity(graph, com_dict))
com_dict2 = {}
for k, v in com_dict.items():
for node in v:
com_dict2[node] = k
print('NMI =', NMI(args.output, com_dict2))
finish_time = time.time()
print('\nDone in %.4f seconds.' % (finish_time - start_time))
def _main():
start_time = time.time()
args = utils.create_argument_parser()
graph = utils.load_graph(args.dataset, False)
graph_copy = deepcopy(graph)
communities = community_detect(graph)
number_of_nodes = 0
com_dict = {}
for i in range(len(communities)):
com_dict[i] = communities[i]
number_of_nodes += len(communities[i])
print(number_of_nodes, ' nodes has been analyzed.')
utils.print_comm_info_to_display(com_dict)
print('modularity_value =', modularity(graph_copy, com_dict))
com_dict2 = {}
for k, v in com_dict.items():
for node in v:
com_dict2[node] = k
print('NMI =', NMI(args.output, com_dict2))
finish_time = time.time()
print('\nDone in %.4f seconds.' % (finish_time - start_time))
def main():
start_time = time.time()
args = utils.create_argument_parser()
graph = utils.load_graph(args.dataset, args.w)
graph_copy = deepcopy(graph)
preprocess(graph)
c = greedy_modularity_communities(graph)
finish_time = time.time()
print('\nDone in %.4f seconds.' % (finish_time - start_time))
communities = dict()
for i in range(len(c)):
communities[i] = list(c[i])
partition = create_partition(communities)
utils.print_comm_info_to_display(communities)
# utils.write_comm_info_to_file(partition)
print('modularity_value =', modularity(graph_copy, communities))
print('NMI =', NMI(args.output, partition))
finish_time = time.time()
print('\nDone in %.4f seconds.' % (finish_time - start_time))
def main():
start_time = time.time()
args = utils.create_argument_parser()
graph = load_graph(args.dataset, args.w)
partition = find_comms(graph)
finish_time = time.time()
print('\nDone in %.4f seconds.' % (finish_time - start_time))
def main():
start_time = time.time()
args = utils.create_argument_parser()
graph = utils.load_graph(args.dataset, args.w)
intended_node = int(args.output)
community = community_search(graph, intended_node)
print('community =', community, len(community))
finish_time = time.time()
print('\nDone in %.4f seconds.' %(finish_time - start_time))
def _main():
args = utils.create_argument_parser()
graph = utils.load_graph(args.dataset, args.w)
communities = read_communities(args.output)
num_of_disconnected_coms = 0
for com_index, nodes in communities.items():
small_graph = graph.subgraph(nodes)
if not nx.is_connected(small_graph):
num_of_disconnected_coms += 1
print('\nPercent of disconnected communities = %.3f' %(num_of_disconnected_coms / len(communities)))
print(num_of_disconnected_coms, '\t', len(communities))
def main():
start_time = time.time()
args = utils.create_argument_parser()
graph = utils.load_graph(args.dataset, args.w)
partition = best_partition(graph)
finish_time = time.time()
print('\nDone in %.4f seconds.' % (finish_time - start_time))
communities = utils.extract_communities(partition)
utils.print_comm_info_to_display(communities)
# utils.write_comm_info_to_file(args.output, partition)
# print('modularity_value =', modularity(graph, communities))
# print('NMI =', NMI(args.output, partition))
finish_time = time.time()
print('\nDone in %.4f seconds.' % (finish_time - start_time))
def _main():
args = utils.create_argument_parser()
graph = utils.load_graph(args.dataset, args.w, self_loop=True)
nodes = list(graph.nodes())
print('num of nodes =', len(nodes))
print('num of edges =', graph.number_of_edges())
communities = dict()
communities_file = args.output
with open(communities_file, 'r') as file:
lines = file.readlines()
for line in lines:
line = line.split()
if not int(line[0]) in nodes:
continue
if not int(line[1]) in communities:
communities[int(line[1])] = list()
communities[int(line[1])].append(int(line[0]))
print('modularity_value =', modularity(graph, communities))
def _main():
start_time = time.time()
args = utils.create_argument_parser()
graph = utils.load_graph(args.dataset, args.w)
communities = dict()
for e, node in enumerate(graph.nodes()):
community = community_search(graph, node)
community = amend_by_dangles(graph, community)
communities[node] = community
ground_truth = read_ground_truth(args.output)
precision, recall, f1_score = calc_accuracy(communities, ground_truth)
print('precision =', precision, '\trecall =', recall, '\tf1-score =',
f1_score)
finish_time = time.time()
print('\nDone in %.4f seconds.' % (finish_time - start_time))
def _main():
start_time = time.time()
args = utils.create_argument_parser()
graph = utils.load_graph(args.dataset, args.w)
communities = dict()
print('\n\n')
for e, node in enumerate(sorted(graph.nodes())):
community = community_search(graph, node)
communities[node] = community
# print(' Node =', node, ' : degree =', graph.degree[node], '->\t', community, '\t', len(community))
ground_truth = read_ground_truth(args.output)
precision, recall, f1_score = calc_accuracy(communities, ground_truth)
print('precision =', precision, '\trecall =', recall, '\tf1-score =',
f1_score)
finish_time = time.time()
print('\nDone in %.4f seconds.' % (finish_time - start_time))
def main():
start_time = time.time()
args = utils.create_argument_parser()
graph = utils.load_graph(args.dataset, args.w)
graph_copy = deepcopy(graph)
communities = community_detection(graph)
com_dict = {}
for i in range(len(communities)):
com_dict[i] = communities[i]
utils.print_comm_info_to_display(com_dict)
# output_name = args.dataset[args.dataset.rindex('/'):]
# utils.write_comm_info_to_file(output_name, com_dict)
print('modularity_value =', modularity(graph_copy, com_dict))
print('NMI =', NMI(args.output, com_dict))
finish_time = time.time()
print('\nDone in %.4f seconds.' % (finish_time - start_time))
try:
logger.info("New bot instance started")
bot.polling(none_stop=True,
interval=BOT_INTERVAL,
timeout=BOT_TIMEOUT)
except Exception as ex: #Error in polling
logger.warning(
f"Bot polling failed, restarting in {BOT_TIMEOUT} sec. Error:\n{ex}"
)
bot.stop_polling()
sleep(BOT_TIMEOUT)
else: #Clean exit
bot.stop_polling()
logger.error("Bot polling loop finished")
break
if __name__ == "__main__":
arg_parser = create_argument_parser()
cmdline_arguments = arg_parser.parse_args()
log_level = cmdline_arguments.loglevel if hasattr(cmdline_arguments,
"loglevel") else None
if not log_level:
log_level = DEFAULT_LOG_LEVEL
logging.getLogger("main").setLevel(log_level)
configure_colored_logging(log_level)
bot_polling()
