def efficiency_targeted():
targeted_time = []
for num_nodes in range(10, 1000, 10):
ugraph = ugraph_UPA(num_nodes, M)
time1 = time()
targeted_order(ugraph)
time2 = time()
targeted_time.append(time2 - time1)
return targeted_time
def efficiency_targeted():
targeted_time = []
for num_nodes in range(10, 1000, 10):
ugraph = ugraph_UPA(num_nodes, M)
time1 = time()
targeted_order(ugraph)
time2 = time()
targeted_time.append(time2 - time1)
return targeted_time
def attack_ordered(ugraphs):
'''
attack the ugraph with the ordered nodes
'''
result = []
for ugraph in ugraphs:
nodes_ordered = targeted_order(ugraph)
resilience = compute_resilience(ugraph, nodes_ordered)
result.append(resilience)
data_file = open('data_resilience_ordered.p', 'wb')
pickle.dump(result, data_file)
data_file.close()
return 'data_resilience_ordered.p'
def attack_ordered(ugraphs):
'''
attack the ugraph with the ordered nodes
'''
result = []
for ugraph in ugraphs:
nodes_ordered = targeted_order(ugraph)
resilience = compute_resilience(ugraph, nodes_ordered)
result.append(resilience)
data_file = open('data_resilience_ordered.p', 'wb')
pickle.dump(result, data_file)
data_file.close()
return 'data_resilience_ordered.p'