best_costs = []
for iteration in range(n):
pop_size=50
W = initial_population(region, scale , pop_size)
pop = PatternPosePopulation(W, pat)
pop.set_distance_image(imd)
pop.temperature = 5
Lw, Lc = pop.particle_filter_search(int(1000/pop_size),log=True)
best_costs.append(pop.best_cost)#store the best cost for this iteration
#Loop should end here for example run pop 50 x n times and store best_cost, take average of bestcost save to csv file.
plt.plot(Lc)
plt.title('Cost vs generation index')
plt.show()
print(pop.best_w)
print(pop.best_cost)
#write to csv
best_cost_total = min(best_costs)
best_cost_avg = sum(best_costs) / n
results = [str(best_cost_total), str(best_cost_avg)]
with open('results.csv', 'w') as f:
f.write(";".join(results))
这会将最佳成本和平均值写入
results.csv
具有
;
作为分隔符。对于更具体的方法,需要更多信息。。。
编辑:没错,写入csv部分应该在循环之后