关键词查询爱站网,wordpress下载的主题怎么用,公司网站设计广州,即墨网站设计举例如下#xff1a;求函数的在x[-3,3],y[-3,3]上的最大值#xff1a;【思路】1. 把DNA设为#xff1a;48个bit的数组。 奇数为x, 偶数为y#xff1b;就是说24个位组成x#xff0c;24个位组成y。如何得到x#xff0c;y#xff1a; 24个奇数位转换成数值比如b, 则 x …举例如下求函数的在x[-3,3],y[-3,3]上的最大值【思路】1. 把DNA设为48个bit的数组。 奇数为x, 偶数为y就是说24个位组成x24个位组成y。如何得到xy 24个奇数位转换成数值比如b, 则 x b/(2^24-1)* (3 - (-3)) -3 2.交叉因子 就是父的前一部分母DNA的后一部分3. 变异因子 就是某个位取反。【代码】代码如下使用200条DNA迭代100次得到结果 (x,y)(0,1.582), z8.1. 结果比较稳定。import numpy as np
import matplotlib.pyplot as plt
from jmespath.ast import projection
from matplotlib import cm
from mpl_toolkits.mplot3d import Axes3DDNA_SIZE24
POP_SIZE200
N_GENERATIONS100
CROSSOVER_RATE0.8
MUTATION_RATE0.005X_BOUND [-3,3]
Y_BOUND [-3,3]
def F(x,y):# 23-x)^2 e( -x^2 - (y1)^2) - 4 e(-(x2)^2-y^2) - 6 e(-(x-2)^2-y(y-2)^2)#return 2*(3-x)**2* np.exp(-x**2-(y1)**2)-4*np.exp(-(x2)**2-y**2)-6*np.exp(-(x-2)**2-(y-2)**2)return 3*(1-x)**2*np.exp(-(x**2)-(y1)**2)-10*(x/5-x**3-y**5)*np.exp(-x**2-y**2)-1/2*np.exp(-(x1)**2-y**2)#return 10-x**2-y**2
def plot_3d(ax):x np.linspace(*X_BOUND, 100)y np.linspace(*Y_BOUND, 100)X, Y np.meshgrid(x, y)Z F(X, Y)surf ax.plot_surface(X,Y,Z,rstride1,cstride1,cmap cm.coolwarm)# 添加颜色条fig.colorbar(surf, axax, shrink0.5, aspect10)# 设置坐标轴标签ax.set_zlim((-20,20))ax.set_xlabel(X轴)ax.set_ylabel(Y轴)ax.set_zlabel(Z轴)# 设置标题ax.set_title(:zf(x,y))plt.pause(3)plt.show()def translateDNA(pop):x_pop pop[:,1::2] #奇数列表示xy_pop pop[:,::2] #偶数列表示yx x_pop.dot( 2** np.arange(DNA_SIZE) [::-1] )/float(2**DNA_SIZE-1)*(X_BOUND[1]-X_BOUND[0]) X_BOUND[0]y y_pop.dot( 2** np.arange(DNA_SIZE) [::-1] )/float(2**DNA_SIZE-1)*(Y_BOUND[1]-Y_BOUND[0]) Y_BOUND[0]return x,ydef crossover_and_mutaion(pop,Crossover_rateCROSSOVER_RATE):halfpop int(POP_SIZE/2)fitness get_fitness(pop)indices np.argpartition(fitness, -halfpop)[-halfpop:] #得到前50%最好的样本进行保留new_pop[]#保留原来比较好的50%.for pepole in pop[indices]:new_pop.append(pepole)#其他的进行交叉以及变异for father in pop:child fatherif(np.random.rand()Crossover_rate):mother pop[np.random.randint(POP_SIZE)]cross_pointnp.random.randint(0,DNA_SIZE*2)child[cross_point:]mother[cross_point:]mutation(child) #变异new_pop.append(child)return new_pop#编译
def mutation(child,mutation_rateMUTATION_RATE):if np.random.rand()mutation_rate:mutation_point np.random.randint(0,DNA_SIZE*2)child[mutation_point] child[mutation_point]^1#选择
def select(pop,fitness):idx np.random.choice(np.arange(fitness.size),sizePOP_SIZE,replaceTrue,p(fitness)/fitness.sum())return pop[idx]def get_fitness(pop):x,ytranslateDNA(pop)predF(x,y)return (pred- np.min(pred))1e-3def print_info(pop):fitness get_fitness(pop)max_fitness_index np.argmax(fitness)x,ytranslateDNA(pop)print(最优基因:,pop[max_fitness_index])print((x,y):,(x[max_fitness_index],y[max_fitness_index]))if __name__ __main__:# main函数程序入口# 创建数据fig plt.figure(figsize(12,9))axfig.add_subplot(111,projection3d)plt.ion()plot_3d(ax)population np.random.randint(2,size(POP_SIZE,DNA_SIZE*2))for i in range(N_GENERATIONS):x,ytranslateDNA(population)population np.array( crossover_and_mutaion(population,Crossover_rate0.8))fitnessget_fitness(population)pop select(population,fitness)if i N_GENERATIONS - 1:x1, y1 translateDNA(pop)sca ax.scatter(x1, y1, F(x1, y1), cgreen, marker*,linewidths5)plt.show()plt.pause(0.1)print(迭代:,i)print(population)print_info(population)plt.ioff()plot_3d(ax)【附录】1.np.argpartition可以取数组中最大的k个值的序号或者最小k个值的序号最小3个值的序号 np.argpartition(arr, 3)[:3]最大3个值的序号 np.argpartition(arr, -3)[-3:]最小值序号举例如下arr np.array([3, 1, 4, 1, 5, 9, 2, 6]) --- [3, 1, 4, 1, 5, 9, 2, 6]
indices np.argpartition(arr, 3) --- [1 3 6 0 2 4 7 5]np.argpartition(arr, 3)[:3] ----- array([1, 3, 6])
最大值序号举例如下np.argpartition(arr, -3)[-3:] ---- array([4, 7, 5])2.np.random.choice(a)从数组中选择可指定概率可放回/不放回
np.random.choice(a, sizeNone, replaceTrue, pNone)参数说明默认值a输入数组或整数必需size输出形状Nonereplace是否允许重复抽样Truep每个元素的概率分布Nonenp.random.choice(data,7,replaceFalse) --》 array([5, 6, 3, 2, 9, 0, 4])np.random.choice(data,7,replaceTrue) -》array([6, 4, 6, 9, 1, 7, 6])data np.arange(5) ---》 array([0, 1, 2, 3, 4])
p[0.1,0.1,0.2,0.3,0.3]np.random.choice(data, size8, pp) ----》 array([3, 1, 4, 4, 2, 1, 4, 3])
