def algorithm_upa(nodes_n,nodes_m):
#counter=0
graph_V=er.algorithm_er_undirected(nodes_m,1.0)
upa_object=UPATrial(len(graph_V))
for node_i in range(nodes_m,nodes_n):
#in_degree_graph=er.compute_in_degrees(graph_V)
V_=upa_object.run_trial(nodes_m)
graph_V.update({node_i:set([])})
for v in V_:
graph_V[node_i].add(v)
#counter+=1
for node in graph_V[node_i]:
graph_V[node].add(node_i)
#print counter
return graph_V
"""Question 1 Application 2 of Algorthmic Thinking Part 1""" import random_order import at_project2 as at import ugraph_at_app_2 as ug import UPAalgorithm as upa import undirected_er as er import matplotlib.pyplot as plt import numpy as np import at1_app2_q3 as to graph1=ug.loader() graph2=er.algorithm_er_undirected(1239,0.0020) graph3=upa.algorithm_upa(1239,3) attack1=to.fast_targeted_order(graph1) attack2=to.fast_targeted_order(graph2) attack3=to.fast_targeted_order(graph3) res_list1=at.compute_resilience(graph1,attack1) res_list2=at.compute_resilience(graph2,attack2) res_list3=at.compute_resilience(graph3,attack3) #len_list=[len(graph1),len(graph2),len(graph3)] x_axis1=range(len(res_list1)) x_axis2=range(len(res_list2)) x_axis3=range(len(res_list3)) ########################################################################### #xvals = [1, 2, 3, 4, 5] #yvals1 = [1, 2, 3, 4, 5]
