def start(bot, update, user_data): G = d.Graph() user_data['graph'] = G username = update.message.chat.first_name bot.send_message( chat_id=update.message.chat_id, text= "Hi, %s.\nMy mission is to help you to move throughout Barcelona by bicing. Remember, if you're lost just ask for -> /help.😄😄\n" % username)
def graph(bot, update, args, user_data): if len(args) == 1: if int(args[0]) < 0: bot.send_message(chat_id=update.message.chat_id, text="Please, enter a positive distance") else: G = d.Graph(int(args[0])) user_data['graph'] = G bot.send_message(chat_id=update.message.chat_id, text="Graph created with distance: %s" % args[0]) elif len( args ) == 0: # if no distance is provided, it creates a graph with distance 1000. G = d.Graph() user_data['graph'] = G bot.send_message(chat_id=update.message.chat_id, text="Graph created with distance: 1000") else: bot.send_message(chat_id=update.message.chat_id, text="You should only introduce one distance")
def graph(bot, update, user_data, args): if (args): try: dist = int(args[0]) except ValueError: message = "Please enter an integer" bot.send_message(chat_id=update.message.chat_id, text=message) return # we check if the arguments are correctly given if len(args) > 1: bot.send_message( chat_id=update.message.chat_id, text="It seems you have introduced more than one value, " + "so I'll just consider the first one.") if int(args[0]) >= 0: # we have concluded that the quadratic algorithm works better for # a distance 250 or less if int(args[0]) >= 250: G = d.CreateGraph(dist) else: G = d.Graph(dist) bot.send_message(chat_id=update.message.chat_id, text="Graph created with distance " + str(dist) + "!") # in case no arguments are given, the default distance is 1000 else: bot.send_message(chat_id=update.message.chat_id, text="Really? Negative distance?") # in case no arguments are given, the default distance is 1000 else: G = d.CreateGraph() bot.send_message( chat_id=update.message.chat_id, text="Since no distance was received, the graph by default, " + "which has been created, has distance 1000.") user_data['graph'] = G
rc.RumorCenter(), dc.DistanceCenter(), jc.JordanCenter(), ri.ReverseInfection(), di.DynamicImportance(), prior_detector8, gsba.GSBA(prior_detector1), gsba_bao7.GSBA_coverage_7(prior_detector1), gsba_bao9.GSBA_coverage_9(prior_detector1) ] logger = log.Logger(logname='../data/main_5regular_tree1229.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." d = data.Graph("../data/5regular_tree_2000.txt", weighted=0) d.debug = False test_num = 10 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 20, 350, 40) # test_category = experiment.FULL_TEST # experiment.start(d, test_category, test_num, 200, 400,100) end_time = clock() print "Running time:", end_time - start_time
# ] # methods = [dc.DistanceCenter()] # methods = [bfsa_p.BFSA(prior_detector1)] # methods = [ # # prior_detector1, # gsba_bao7.GSBA_coverage_7(prior_detector1), # gsba_bao10.GSBA_coverage_10(prior_detector1) # ] logger = log.Logger(logname='../data/main_ga_grqc_20191221.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." # d = data.Graph("../data/power-grid.txt") d = data.Graph("../data/CA-GrQc.txt", weighted=0) d.debug = False test_num = 5 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 20, 350, 40) # test_category = experiment.FULL_TEST # experiment.start(d, test_category, test_num, 10, 46, 5) end_time = clock() print "Running time:", end_time - start_time
rc.RumorCenter(), dc.DistanceCenter(), jc.JordanCenter(), ri.ReverseInfection(), di.DynamicImportance(), prior_detector8, gsba.GSBA(prior_detector1), # gsba_bao7.GSBA_coverage_7(prior_detector1), gsba_bao9.GSBA_coverage_9(prior_detector1) ] logger = log.Logger(logname='../data/main_ncstrlwg2_submatrix0104.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." d = data.Graph("../data/wugulidata/ncstrlwg2_submatrix.txt", weighted=0) d.debug = False test_num = 100 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 20, 350, 40) # test_category = experiment.FULL_TEST # experiment.start(d, test_category, test_num, 200, 400,100) end_time = clock() print "Running time:", end_time - start_time
experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() # print "Starting..." # data就是我们的图,我们可以做一些操作。 创建一个简单的图。试试看结果。 ''' 1 创建例子的图 2 给定传播点子图 ''' # infected = set() # infected.add(1) # infected.add(2) # infected.add(4) d = data.Graph("../data/epaAndcoveage_test.txt", weighted=0) # print(d.graph.number_of_edges()) # print(d) d.debug = False test_num = 3 # print(d.subgraph) # #print(infected) # d.subgraph= d.graph d.subgraph = nx.Graph() d.subgraph = nx.subgraph(d.graph, ['0', '1', '6', '7', '8', '9', '10', '11']) # print('子图节点个数') # print(d.subgraph.nodes()) # print(d.graph.nodes())
di.DynamicImportance(), prior_detector8, gsba.GSBA(prior_detector1), gsba_bao7.GSBA_coverage_7(prior_detector1), # gsba_bao7_.GSBA_coverage_7_(prior_detector1), # gsba_bap8.GSBA_coverage_8(prior_detector1), gsba_bao9.GSBA_coverage_9(prior_detector1), # gsba_bao10.GSBA_coverage_10(prior_detector1) ] logger = log.Logger(logname='../data/main_5000scale_free3.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." d = data.Graph("../data/scale_network/5000/5000scale_free3.txt", weighted=0) d.debug = False test_num = 10 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 20, 350, 40) # test_category = experiment.FULL_TEST # experiment.start(d, test_category, test_num, 200, 400,100) end_time = clock() print "Running time:", end_time - start_time
methods = [ rc.RumorCenter(), dc.DistanceCenter(), jc.JordanCenter(), ri.ReverseInfection(), di.DynamicImportance(), prior_detector8, gsba.GSBA(prior_detector1), gsba_bao7.GSBA_coverage_7(prior_detector1), gsba_bao9.GSBA_coverage_9(prior_detector1) ] logger = log.Logger(logname='../data/main_1000random_graph0005.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." d = data.Graph("../data/random_graph/1000/1000random_graph0005.txt", weighted=0) d.debug = False test_num = 100 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 20, 350, 40) # test_category = experiment.FULL_TEST # experiment.start(d, test_category, test_num, 200, 400,100) end_time = clock() print "Running time:", end_time - start_time
methods = [ rc.RumorCenter(), dc.DistanceCenter(), jc.JordanCenter(), ri.ReverseInfection(), di.DynamicImportance(), prior_detector8, gsba.GSBA(prior_detector1), # gsba_bao7.GSBA_coverage_7(prior_detector1), gsba_bao9.GSBA_coverage_9(prior_detector1), gsba_bao15.GSBA_coverage_15(prior_detector1) ] logger = log.Logger(logname='../data/main_graph_CA-GrQc0104.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." d = data.Graph("../data/wugulidata/graph_CA-GrQc.txt", weighted=0) d.debug = False test_num = 100 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 20, 350, 40) # test_category = experiment.FULL_TEST # experiment.start(d, test_category, test_num, 200, 400,100) end_time = clock() print "Running time:", end_time - start_time
rc.RumorCenter(), dc.DistanceCenter(), jc.JordanCenter(), ri.ReverseInfection(), di.DynamicImportance(), prior_detector8, gsba.GSBA(prior_detector1), gsba_bao7.GSBA_coverage_7(prior_detector1), gsba_bao9.GSBA_coverage_9(prior_detector1) ] logger = log.Logger(logname='../data/main_1000scale_free1.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." d = data.Graph("../data/scale_network/1000/1000scale_free1.txt", weighted=0) d.debug = False test_num = 100 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 20, 350, 40) # test_category = experiment.FULL_TEST # experiment.start(d, test_category, test_num, 200, 400,100) end_time = clock() print "Running time:", end_time - start_time
prior_detector3 = dc.DistanceCenter() prior_detector4 = jc.JordanCenter() prior_detector5 = ri.ReverseInfection() # methods = [rc.RumorCenter(), dc.DistanceCenter(), jc.JordanCenter(),ri.ReverseInfection(),prior_detector2, # gsba.GSBA( prior_detector1),gsba.GSBA(prior_detector2), gsba.GSBA( prior_detector3), # gsba.GSBA(prior_detector4), gsba.GSBA( prior_detector5)] # methods = [rc.RumorCenter(), dc.DistanceCenter(), jc.JordanCenter(), ri.ReverseInfection(), di.DynamicImportance(), # gsba.GSBA(prior_detector1),gsba.GSBA(prior_detector3),gsba.GSBA(prior_detector4),] methods = [rc.RumorCenter(), dc.DistanceCenter(), jc.JordanCenter(), gsba.GSBA(prior_detector1),gsba.GSBA(prior_detector3),gsba.GSBA(prior_detector4)] logger = log.Logger(logname='../data/main_ca_astroph1203.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." d = data.Graph("../data/CA-AstroPh.gml", weighted=1) d.debug = False test_num = 100 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 10, 200, 10) # test_category = experiment.RANDOM_TEST # experiment.start(d, test_category, 2000, 10, 46, 5) end_time = clock() print "Running time:", end_time-start_time
dc.DistanceCenter(), jc.JordanCenter(), ri.ReverseInfection(), di.DynamicImportance(), prior_detector8, gsba.GSBA(prior_detector1), # gsba_bao7.GSBA_coverage_7(prior_detector1), gsba_bao9.GSBA_coverage_9(prior_detector1), gsba_bao15.GSBA_coverage_15(prior_detector1) ] logger = log.Logger(logname='../data/main_small_world3000.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." d = data.Graph("../data/small_world/swall-world-graph3000.txt", weighted=0) d.debug = False test_num = 100 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 20, 350, 40) # test_category = experiment.FULL_TEST # experiment.start(d, test_category, test_num, 200, 400,100) end_time = clock() print "Running time:", end_time - start_time
methods = [ rc.RumorCenter(), dc.DistanceCenter(), jc.JordanCenter(), ri.ReverseInfection(), di.DynamicImportance(), prior_detector8, gsba.GSBA(prior_detector1), gsba_bao7.GSBA_coverage_7(prior_detector1), gsba_bao9.GSBA_coverage_9(prior_detector1) ] logger = log.Logger(logname='../data/main_random_tree3000.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." d = data.Graph("../data/random_tree/random_tree3000.txt", weighted=0) d.debug = False test_num = 10 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 20, 350, 40) # test_category = experiment.FULL_TEST # experiment.start(d, test_category, test_num, 200, 400,100) end_time = clock() print "Running time:", end_time - start_time
rc.RumorCenter(), dc.DistanceCenter(), jc.JordanCenter(), ri.ReverseInfection(), di.DynamicImportance(), prior_detector8, gsba.GSBA(prior_detector1), gsba_bao7.GSBA_coverage_7(prior_detector1), gsba_bao9.GSBA_coverage_9(prior_detector1) ] logger = log.Logger(logname='../data/main_6regular_tree1229.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." d = data.Graph("../data/6regular_tree_5000.txt", weighted=0) d.debug = False test_num = 10 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 20, 350, 40) # test_category = experiment.FULL_TEST # experiment.start(d, test_category, test_num, 200, 400,100) end_time = clock() print "Running time:", end_time - start_time
jc.JordanCenter(), ri.ReverseInfection(), di.DynamicImportance(), prior_detector8, gsba.GSBA(prior_detector1), gsba_bao7.GSBA_coverage_7(prior_detector1), gsba_bao9.GSBA_coverage_9(prior_detector1) ] logger = log.Logger(logname='../data/main_500random_graph001.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." d = data.Graph("../data/random_graph/500/500random_graph001.txt", weighted=0) d.debug = False test_num = 100 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 20, 350, 40) # test_category = experiment.FULL_TEST # experiment.start(d, test_category, test_num, 200, 400,100) end_time = clock() print "Running time:", end_time - start_time print()
jc.JordanCenter(), ri.ReverseInfection(), di.DynamicImportance(), gsba.GSBA(prior_detector1), gsba.GSBA(prior_detector3), gsba.GSBA(prior_detector4) ] logger = log.Logger(logname='../data/main_IC.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'IC' start_time = clock() print "Starting..." # d = data.Graph("../data/scale-free.ba.v500.e996.gml", weighted=1) # d = data.Graph("../data/power-grid.gml", weighted=1) d = data.Graph("../data/Wiki-Vote.gml", weighted=1) d.debug = False test_num = 100 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 10, 46, 5) test_category = experiment.FULL_TEST # experiment.start(d, test_category, test_num, 10, 46, 5) end_time = clock() print "Running time:", end_time - start_time
# gsba.GSBA(prior_detector4), gsba.GSBA(prior_detector5), gsba.GSBA(prior_detector2), # bfsa_p.BFSA(prior_detector1), # gsba.GSBA(prior_detector7), # gsba_bao.GSBA_coverage(prior_detector1) # # ] # methods = [dc.DistanceCenter()] # methods = [bfsa_p.BFSA(prior_detector1)] # methods = [dmp2.DynamicMessagePassing()] logger = log.Logger(logname='../data/main_email_20191221.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." # d = data.Graph("../data/power-grid.txt") d = data.Graph("../data/email-Eu-core.txt", weighted=0) d.debug = False test_num = 10 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 20, 350, 40) # test_category = experiment.FULL_TEST # experiment.start(d, test_category, test_num, 10, 46, 5) end_time = clock() print "Running time:", end_time - start_time
def detect_loaded(self, network, test_category, infected_size, test_num=1): """ do random (or full) test with loaded simulations about information propagation. Args: data: mydata.Graph test_category: {'full_test', 'random_test'} test_num: int infected_size: int """ """Read the network and generate source nodes according to the test_category category""" d = mydata.Graph("../data/%s" % network, weighted=1) nodes = d.graph.nodes() n = d.graph.number_of_nodes() sources = list() # source nodes' index self.initialize_evaluation_measures(test_category) if test_category is self.RANDOM_TEST: v = 0 while v < test_num: sources.append(random.randint(0, n - 1)) v += 1 else: sources = np.arange(0, n) n = len(sources) """run the test_category""" print test_category, len( nodes), d.graph.number_of_edges(), infected_size, test_num for m in self.methods: print '\t', m.method_name start_time = clock() percentage = 0.2 i = 0 for s in sources: i += 1 if abs(i - n * percentage) < 1: print '\t\t percentage: ', percentage percentage += 0.2 file = "../data/simulation/%s.i%s.s%s.subgraph" % ( network, infected_size, s) reader = open(file, "r") data = pickle.load(reader) """@type data: mydata.Graph""" reader.close() data.weights = d.weights m.set_data(data) result = m.detect() """evaluate the result""" if len(result) > 0: if result[0][0] == nodes[s]: self.precision[test_category][m.method_name].append(1) else: self.precision[test_category][m.method_name].append(0) self.error[test_category][m.method_name].append( nx.dijkstra_path_length(d.subgraph, result[0][0], nodes[s], weight='weight')) self.topological_error[test_category][ m.method_name].append( nx.dijkstra_path_length(d.subgraph, result[0][0], nodes[s], weight=None)) r = 0 for u in result: r += 1 if u[0] == nodes[s]: self.ranking[test_category][m.method_name].append( r * 1.0 / len(result)) break end_time = clock() self.running_time[test_category][ m.method_name] = end_time - start_time
# ] # methods = [dc.DistanceCenter()] # methods = [bfsa_p.BFSA(prior_detector1)] # methods = [ # # prior_detector1, # gsba_bao7.GSBA_coverage_7(prior_detector1), # gsba_bao10.GSBA_coverage_10(prior_detector1) # ] logger = log.Logger(logname='../data/main_facebook_20191212.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." # d = data.Graph("../data/power-grid.txt") d = data.Graph("../data/facebook_combined.txt", weighted=0) d.debug = False test_num = 100 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 30, 500, 50) # test_category = experiment.FULL_TEST # experiment.start(d, test_category, test_num, 10, 46, 5) end_time = clock() print "Running time:", end_time - start_time
prior_detector0 = prior.Uniform() prior_detector1 = rc.RumorCenter() prior_detector2 = dmp2.DynamicMessagePassing() prior_detector3 = dc.DistanceCenter() prior_detector4 = jc.JordanCenter() prior_detector5 = ri.ReverseInfection() methods = [rc.RumorCenter(), dc.DistanceCenter(), jc.JordanCenter(), gsba.GSBA(prior_detector1),gsba.GSBA(prior_detector3),gsba.GSBA(prior_detector4)] # methods = [dc.DistanceCenter()] #methods = [bfsa_p.BFSA(prior_detector1)] # methods = [dmp2.DynamicMessagePassing()] logger = log.Logger(logname='../data/main_power_grid1202.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." # d = data.Graph("../data/power-grid.txt") d = data.Graph("../data/power-grid.gml", weighted=1) d.debug = False test_num = 100 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 10, 200, 10) # test_category = experiment.FULL_TEST # experiment.start(d, test_category, test_num, 10, 46, 5) end_time = clock() print "Running time:", end_time-start_time
prior_detector3 = dc.DistanceCenter() prior_detector4 = jc.JordanCenter() prior_detector5 = ri.ReverseInfection() methods = [rc.RumorCenter(), dc.DistanceCenter(), jc.JordanCenter(),ri.ReverseInfection(),prior_detector2, gsba.GSBA( prior_detector1),gsba.GSBA(prior_detector2), gsba.GSBA( prior_detector3), gsba.GSBA(prior_detector4), gsba.GSBA( prior_detector5)] methods = [rc.RumorCenter(), dc.DistanceCenter(), jc.JordanCenter(), ri.ReverseInfection(), di.DynamicImportance(), prior_detector2, gsba.GSBA(prior_detector0), gsba.GSBA(prior_detector1), gsba.GSBA( prior_detector3), gsba.GSBA(prior_detector4), gsba.GSBA( prior_detector5), gsba.GSBA(prior_detector2), bfsa_p.BFSA(prior_detector1)] methods = [bfsa.BFSA(prior_detector1)] # methods = [dmp2.DynamicMessagePassing()] experiment.methods = methods start_time = clock() print "Starting..." d = data.Graph("../data/test_category.txt", weighted=1) # d = data.Graph("../data/karate_club.gml") # d = data.Graph("../data/small-world.ws.v100.e500.gml", weighted=1) d = data.Graph("../data/scale-free.ba.v500.e996.gml", weighted=1) #d = data.Graph("../data/power-grid.txt") d.debug = False random_num = 100 experiment.propagation_model = 'SI' print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test = "random_test" # 0.016 8 d.ratio_infected = 0.016 for i in np.arange(0,3): experiment.initialize_evaluation_measures() str = 'd.ratio_infected', d.ratio_infected, d.ratio_infected*d.graph.number_of_nodes()
gsba.GSBA(prior_detector0), gsba.GSBA(prior_detector1), gsba.GSBA(prior_detector3), gsba.GSBA(prior_detector4), gsba3.GSBA(prior_detector0), gsba3.GSBA(prior_detector1), gsba3.GSBA(prior_detector3), gsba3.GSBA(prior_detector4) ] logger = log.Logger(logname='../data/main_scale_free3.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." d = data.Graph("../data/scale-free.ba.v500.e996.gml", weighted=1) d.debug = False test_num = 100 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 10, 41, 1) test_category = experiment.FULL_TEST experiment.start(d, test_category, test_num, 10, 41, 1) end_time = clock() print "Running time:", end_time - start_time
rc.RumorCenter(), dc.DistanceCenter(), jc.JordanCenter(), ri.ReverseInfection(), di.DynamicImportance(), prior_detector8, gsba.GSBA(prior_detector1), # gsba_bao7.GSBA_coverage_7(prior_detector1), gsba_bao9.GSBA_coverage_9(prior_detector1) ] logger = log.Logger(logname='../data/main_actors_dat_submatrix0104.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." d = data.Graph("../data/wugulidata/actors_dat_submatrix.txt", weighted=0) d.debug = False test_num = 100 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 20, 350, 40) # test_category = experiment.FULL_TEST # experiment.start(d, test_category, test_num, 200, 400,100) end_time = clock() print "Running time:", end_time - start_time
dc.DistanceCenter(), jc.JordanCenter(), ri.ReverseInfection(), di.DynamicImportance(), prior_detector8, gsba.GSBA(prior_detector1), # gsba_bao7.GSBA_coverage_7(prior_detector1), gsba_bao9.GSBA_coverage_9(prior_detector1), gsba_bao15.GSBA_coverage_15(prior_detector1) ] logger = log.Logger(logname='../data/main_graph_CA-AstroPh0104.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." d = data.Graph("../data/wugulidata/graph_CA-AstroPh.txt", weighted=0) d.debug = False test_num = 100 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 100, 350, 40) # test_category = experiment.FULL_TEST # experiment.start(d, test_category, test_num, 200, 400,100) end_time = clock() print "Running time:", end_time - start_time
dc.DistanceCenter(), jc.JordanCenter(), ri.ReverseInfection(), di.DynamicImportance(), prior_detector8, gsba.GSBA(prior_detector1), # gsba_bao7.GSBA_coverage_7(prior_detector1), gsba_bao9.GSBA_coverage_9(prior_detector1), gsba_bao15.GSBA_coverage_15(prior_detector1) ] logger = log.Logger(logname='../data/main_graph_CA-CondMat0104.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." d = data.Graph("../data/wugulidata/graph_CA-CondMat.txt", weighted=0) d.debug = False test_num = 100 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 20, 350, 40) # test_category = experiment.FULL_TEST # experiment.start(d, test_category, test_num, 200, 400,100) end_time = clock() print "Running time:", end_time - start_time
# gsba_bao11.GSBA_coverage_11(prior_detector1), # gsba_bao12.GSBA_coverage_12(prior_detector1) # ] # methods = [rc.RumorCenter(), dc.DistanceCenter(), jc.JordanCenter(), # gsba.GSBA(prior_detector1), gsba.GSBA(prior_detector3),gsba.GSBA(prior_detector4), # ulbaa.ULBAA(prior_detector1), ulbaa.ULBAA(prior_detector3), ulbaa.ULBAA(prior_detector4), # gslba.GSLBA(prior_detector1), gslba.GSLBA(prior_detector3), gslba.GSLBA(prior_detector4), # gsba2.GSBA(prior_detector1), gsba2.GSBA( prior_detector3),gsba2.GSBA(prior_detector4),] logger = log.Logger(logname='../data/main_wiki_vote1222.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." d = data.Graph("../data/test.txt", weighted=1) d = data.Graph("../data/Wiki-Vote.gml", weighted=1) d.debug = False test_num = 10 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 300, 500, 50) # test_category = experiment.FULL_TEST # experiment.start(d, test_category, test_num, 10, 31, 5) end_time = clock() print "Running time:", end_time - start_time
# coding=utf-8 """ A part of Source Detection. Author: Biao Chang, [email protected], from University of Science and Technology of China created at 2017/1/9. """ import data if __name__ == '__main__': ratio_infected = 0.3 input_file = "../data/small-world.ws.v100.e500.gml" output_file = "../data/simulation/small-world.ws.v100.e500.gml" ratio_infected = 0.03 input_file = "../data/power-grid.txt" output_file = "../data/simulation/power-grid.gml" ratio_infected = 0.03 # input_file = "../data/Wiki-Vote.gml" output_file = "../data/simulation/Wiki-Vote.gml" d = data.Graph(input_file, weighted=1) d.generate_random_graph(200) d.generate_infected_subgraph(output_file, ratio_infected) # print d.get_diameter_for_subgraphs(35)
experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." # data就是我们的图,我们可以做一些操作。 创建一个简单的图。试试看结果。 ''' 1 创建例子的图 2 给定传播点子图 ''' infected = set() infected.add(1) infected.add(2) infected.add(4) d = data.Graph("../data/test.txt", weighted=1) print(d.graph.number_of_edges()) print(d) d.debug = False test_num = 1 print(d.subgraph) # print(infected) # d.subgraph= d.graph d.subgraph = nx.Graph() d.subgraph = nx.subgraph(d.graph, ['1', '2', '4']) print('子图节点个数') print(d.subgraph.nodes()) print(d.graph.nodes()) print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges()
dc.DistanceCenter(), jc.JordanCenter(), ri.ReverseInfection(), di.DynamicImportance(), prior_detector8, gsba.GSBA(prior_detector1), # gsba_bao7.GSBA_coverage_7(prior_detector1), gsba_bao9.GSBA_coverage_9(prior_detector1), gsba_bao15.GSBA_coverage_15(prior_detector1) ] logger = log.Logger(logname='../data/main_graph_CA-HepTh0104.log', loglevel=logging.INFO, logger="experiment").get_log() experiment = Experiment(methods, logger) experiment.propagation_model = 'SI' start_time = clock() print "Starting..." d = data.Graph("../data/wugulidata/graph_CA-HepTh.txt", weighted=0) d.debug = False test_num = 100 print 'Graph size: ', d.graph.number_of_nodes(), d.graph.number_of_edges() test_category = experiment.RANDOM_TEST experiment.start(d, test_category, test_num, 20, 350, 40) # test_category = experiment.FULL_TEST # experiment.start(d, test_category, test_num, 200, 400,100) end_time = clock() print "Running time:", end_time - start_time