使用遗传算法实现对三角函数的逼近 点，请给出完整代码

使用遗传算法逼近三角函数的完整代码如下：def genetic_algorithm_approximate_trig_function(target_function, population_size, num_generations, mutation_rate):
# 初始化种群
population = [random.random() * 2 * math.pi for _ in range(population_size)]
# 计算适应度
fitnesses = [abs(target_function(x) - math.sin(x)) for x in population]
# 进行进化
for generation in range(num_generations):
# 选择
weights = normalize(fitnesses)
parents = random.choices(population, weights=weights, k=population_size)
# 交叉
offsprings = [crossover(parents[i], parents[(i + 1) % population_size]) for i in range(population_size)]
# 变异
offsprings = [mutate(offspring, mutation_rate) for offspring in offsprings]
# 更新
population = offsprings
fitnesses = [abs(target_function(x) - math.sin(x)) for x in population]
return population, fitnesses