children = POPULATION(c.popSize)
entire_fill_temp = children.Fill_From(parents)
fillTime = time.time() - starttime
# pp.pformat(children.pop[0])
children.Evaluate(envs, pb=True, pp=False)
evaluateTime = time.time() - fillTime
parents = copy.deepcopy(children)
copyTime = time.time() - evaluateTime
if g % 2 == 0:
print(g, end=" ")
children.Print()
else:
print(g)
recorder.record_times(g, evaluateTime, copyTime, fillTime, starttime,
entire_fill_temp)
recorder.add_metrics(parents.pop[0])
recorder.plotTimes()
recorder.plot_evolution()
best = POPULATION(1)
best.pop[0] = parents.Copy_Best_From(parents)
repeat = 'r'
while repeat == 'r':
best.Evaluate_Best(envs, pb=False, pp=True, retain_data=True)
recorder.plot_touch_values(best.pop[0])
repeat = input("Press 'r' to repeat: ")
saveOption = input("Save File? [y/n]")
if (saveOption == 'y'):
saveBot = True
saveLabel = input("file name: ")
entire_fill_temp = children.Fill_From(parents)
fillTime = time.time() - starttime
# pp.pformat(children.pop[0])
children.Evaluate(envs, pb=True, pp=False)
evaluateTime = time.time() - fillTime
parents = copy.deepcopy(children)
copyTime = time.time() - evaluateTime
if g % 2 == 0:
print(g, end=" ")
children.Print()
else:
print(g)
recorder.record_times(g, evaluateTime, copyTime, fillTime, starttime)
if c.evolution_alg == 'apfo':
recorder.add_metrics(
parents.pop[recorder.evolution_data['pop_fitness'][g - 1]
['best_index']], g)
elif c.evolution_alg == 'genetic':
recorder.add_metrics(parents.pop[0], g)
pop_size = len(parents.pop)
# recorder.plotTimes()
recorder.plot_evolution()
best = POPULATION(1)
best.pop[0] = parents.Copy_Best_From(parents)
repeat = 'r'
while repeat == 'r':
best.Evaluate_Best(envs, pb=False, pp=True, retain_data=True)
recorder.plot_touch_values(best.pop[0])
repeat = input("Press 'r' to repeat: ")
