def reproduceAsexual(ga, index, child, mom, dad):
if index > len(ga.population) * 0.9:
geneticAlgorithm.randomizeIndividual(child)
else:
geneticAlgorithm.copyIndividual(mom, child)
if random.random() < 0.8:
mutate(child, ga, 0.5)
def reproduce(ga, index, child, mom, dad):
if index == 0:
geneticAlgorithm.copyIndividual(ga.mostfit, child)
elif index < len(ga.population) / 2:
for i in range(len(dad)):
for j in range(len(dad[i])):
child[i][j] = dad[i][j] if random.random() < 0.5 else mom[i][j]
if random.random() < 0.01:
mutate(child, ga)
elif ga.newbest:
geneticAlgorithm.copyIndividual(ga.mostfit, child)
mutate(child, ga)
elif index < len(ga.population) * 0.75:
reproduceAsexual(ga, index, child, mom, dad)
else:
geneticAlgorithm.randomizeIndividual(child)
def reproduceSexualMergeElitist(ga, index, child, mom, dad):
if index == 0:
geneticAlgorithm.copyIndividual(ga.mostfit, child)
else:
reproduceSexualMerge(ga, index, child, mom, dad)