def iteration(agents, agent_number, iteration_times):
cardinality = []
P_choosing_best = []
#an = agent_number
#sn = proposition_number
N = iteration_times
iteration = 0 # iteration time count
while iteration < N:
reward = bnfc.get_reward(agents, Q)
iteration = iteration + 1
square_rank = bnfc.get_sq_rank(reward)
index1 = bnfc.pick_agent(agents, square_rank)
index2 = bnfc.pick_agent(agents, square_rank)
#t = agents [index1]
#s = agents [index2]
Intersection = agents[index1] & agents[index2]
Union = agents[index1] | agents[index2]
#distance = hammingdis(s,t) # check if overlap exists
if (Intersection == set()):
agents[index1] = Union
agents[index2] = Union
else:
agents[index1] = Intersection #intersect if not
agents[index2] = Intersection
cardinality.append(bnfc.cal_card(agents))
proportion = bnfc.get_proportion(grid, agents)
P_choosing_best.append(proportion[1])
return agents, P_choosing_best, cardinality
Pstore = []
cardstore = []
#correct = 0
while times < N:
agents = bnfc.random_initialise_toss(agent_number, grid)
#plot(agents,get_proportion(grid,agents))
##print (agents)
##print(get_reward(agents,Q))
##reward = get_reward(agents,Q)
##print(pick_agent(agents,reward))
#agents,P1 = iteration(agents,len(agents),500)
#plot(agents,get_proportion(grid,agents))
#agents,P2 = iteration(agents,len(agents),500)
#plot(agents,get_proportion(grid,agents))
agents, P1, cardinality = iteration(agents, len(agents), iter)
proportion = bnfc.get_proportion(grid, agents)
Pstore.append(proportion)
bestPstore.append(P1)
cardstore.append(cardinality)
times = times + 1
#print(Ave_P)
sumcard = np.sum(cardstore, axis=0)
stdcard = np.std(cardstore, axis=0)
ave_card = sumcard / N
sumPbest = np.sum(bestPstore, axis=0)
stdPbest = np.std(bestPstore, axis=0)
#index = list(range(0,3000))
ave_pbest = sumPbest / N
sumP = np.sum(Pstore, axis=0)