我的带有 in 函数的代码不执行该任务，但在 out 时执行相同的任务？

问题描述

这是我的代码，我稍微翻转一下，跨越两个列表并选择列表的随机元素：

def selRandom(individuals,k):
    return [random.choice(individuals) for i in range(k)]

def cxOnePoint(ind1,ind2):

    size = min(len(ind1),len(ind2))
    cxpoint = random.randint(1,size - 1)
    ind1[cxpoint:],ind2[cxpoint:] = ind2[cxpoint:],ind1[cxpoint:]

    return ind1,ind2

def mutFlipBit(individual,indpb):

    for i in range(len(individual)):
        if random.random() < indpb:
            individual[i] = type(individual[i])(not individual[i])

    return individual,def operators(selection,crossover,mutation,parent,k,indvpb):

    select = ['randomSelection']
    cx = ['OnePoint']
    mutate = ['flipBitMutate']


    if selection not in select:
        return "invalid"

    else:

        if selection == 'randomSelection':
            (parent) = selRandom(parent,k)

    if crossover not in cx:
        return "invalid"

    else:
        if crossover == 'OnePoint':
            ind = cxOnePoint(parent[0],parent[1])

    if mutation not in mutate:
        return "not valid"
    else:
        if mutation == 'flipBitMutate':
            mutatedindvidual = mutFlipBit(ind[0],indvpb)


    return parent,ind,mutatedindvidual

我运行它来执行代码：

indv = ([1,1,1],[0,0],[1,1])
selection = 'randomSelection'
crossover = 'OnePoint'
mutation = 'flipBitMutate'
selected_parent,mutatedindvidual = operators(selection = selection,crossover = crossover,mutation = mutation,parent = indv,k = 3,indvpb = 0.1 )
print("Parents:\n",indv)
print("Selected parent to reproduce:\n",selected_parent)
print("Crossover offsprings:\n",ind)
print("Mutated offsprings",mutatedindvidual)

并得到结果：

Parents:
 ([1,1])
Selected parent to reproduce:
 [[1,0]]
Crossover offsprings:
 ([1,1])
Mutated offsprings ([1,)

所以代码正在执行但没有运行。它从元组中随机选择，然后它不会交叉（混合来自两个列表的位）或翻转位。如果我单独测试运行代码（在操作符方法之外），它可以工作：

a = [1,1]
b = [0,0] 
c = [1,1]
d= (a,b,c)
print("selecting randomely:\n",selRandom(d,1))
print("TESTING CROSSOVER\n",cxOnePoint(a,b))
print("Mutate:\n",mutFlipBit(a,0.4))

并得到正确的结果：

selecting randomely:
 [[0,0]]
TESTING CROSSOVER
 ([1,1])
Mutate:
 ([0,)

我在这里犯的逻辑错误是什么？

谢谢！

解决方法

回答我自己的问题：

我已在 mutFlipBit() 和 cxOnePoint 中分配了原始列表，并将“mutFlipBit()”更改为：

 def mutation(individual,indp):
     return [not ind if random.random() < indp else ind for ind in individual]

这对我有用

genetic-algorithm python