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
