def test_attack_ordered():
ugraph_network = load_graph('computer_network.txt')
ugraph_ER = ugraph_probability(NODES, P)
attack_ordered((ugraph_network, ugraph_ER))
data_file = open('data_resilience_ordered.p', 'rb')
cc_set = pickle.load(data_file)
data_file.close()
print('test attack:')
print("cc_network length: %d, cc_er length: %d" %(len(cc_set[0]), len(cc_set[1])))
print("cc_network: %s\n%s" %(cc_set[0][-6:], cc_set[0][:6]))
print("cc_er: %s\n%s" %(cc_set[1][-6:], cc_set[1][:6]))
def test_attack_ordered():
ugraph_network = load_graph('computer_network.txt')
ugraph_ER = ugraph_probability(NODES, P)
attack_ordered((ugraph_network, ugraph_ER))
data_file = open('data_resilience_ordered.p', 'rb')
cc_set = pickle.load(data_file)
data_file.close()
print('test attack:')
print("cc_network length: %d, cc_er length: %d" %
(len(cc_set[0]), len(cc_set[1])))
print("cc_network: %s\n%s" % (cc_set[0][-6:], cc_set[0][:6]))
print("cc_er: %s\n%s" % (cc_set[1][-6:], cc_set[1][:6]))
def test_ro():
ugraph = ugraph_probability(10, 0.3)
print random_order(ugraph)
def test_to_ER():
#test targeted_order with ugraph_ER
from ER_ugraph import ugraph_probability
ugraph = ugraph_probability(10, 0.4)
print("test targeted graph: %s" % targeted_order(ugraph))
def test_to_ER():
#test targeted_order with ugraph_ER
from ER_ugraph import ugraph_probability
ugraph = ugraph_probability(10, 0.4)
print("test targeted graph: %s" %targeted_order(ugraph))
def test_ro():
ugraph = ugraph_probability(10, 0.3)
print random_order(ugraph)
