补全代码 sigma = 1; x = -2:0.01:2; y = -2:0.01:1.5; [X, Y] = meshgrid(x, y); %X = X; %Y = Y; P_E = X + sqrt(3) * Y + sigma/2 * (X.^2+Y.^2-1).^2; figure subplot(121) contour(X, Y, P_E, 80) sigma = 8; x = -2:0.01:2; y = -2:0.01:1.5; [X, Y] = meshgrid(x

以下是代码的完整版：

sigma = 1;
x = -2:0.01:2;
y = -2:0.01:1.5;
[X, Y] = meshgrid(x, y);
P_E = X + sqrt(3) * Y + sigma/2 * (X.^2+Y.^2-1).^2;

figure
subplot(121)
contour(X, Y, P_E, 80)

sigma = 8;
x = -2:0.01:2;
y = -2:0.01:1.5;
[X, Y] = meshgrid(x, y);
P_E = X + sqrt(3) * Y + sigma/2 * (X.^2+Y.^2-1).^2;

subplot(122)
contour(X, Y, P_E, 80)

这段代码是用MATLAB实现的，其中包含两个子图，分别对应着不同的惩罚系数sigma。首先，我们在一个二维网格上计算出函数P_E的值，然后通过contour函数绘制出等高线图。其中，sigma=1和sigma=8分别对应着左右两张子图。可以看到，当sigma变大时，等高线图变得更加陡峭，目标函数的极小值也变得更加明显。

相关问题

补全代码，让他生成图片 sigma = 1; x = -2:0.01:2; y = -2:0.01:1.5; [X, Y] = meshgrid(x, y); %X = X; %Y = Y; P_E = X + sqrt(3) * Y + sigma/2 * (X.^2+Y.^2-1).^2; figure subplot(121) contour(X, Y, P_E, 80) sigma = 8; x = -2:0.01:2; y = -2:0.01:1.5; [X, Y] = meshg

以下是补全后的代码，使用 MATLAB 可以生成对应的图片：

sigma = 1;
x = -2:0.01:2;
y = -2:0.01:1.5;
[X, Y] = meshgrid(x, y);
P_E = X + sqrt(3) * Y + sigma/2 * (X.^2+Y.^2-1).^2;

figure 
subplot(121)
contour(X, Y, P_E, 80)
title('\sigma = 1')

sigma = 8;
x = -2:0.01:2;
y = -2:0.01:1.5;
[X, Y] = meshgrid(x, y);
P_E = X + sqrt(3) * Y + sigma/2 * (X.^2+Y.^2-1).^2;

subplot(122)
contour(X, Y, P_E, 80)
title('\sigma = 8')

这段代码先设置了两个不同的惩罚系数sigma，然后通过meshgrid函数生成了一个2D网格，用于绘制函数的等高线图。接着，利用contour函数画出了两个子图，分别对应着不同的惩罚系数sigma。最后，通过title函数给每个子图加上标题，方便了解图像的含义。

sigma = 1; x = -2:0.01:2; y = -2:0.01:1.5; [X, Y] = meshgrid(x, y); %X = X; %Y = Y; P_E = X + sqrt(3) * Y + sigma/2 * (X.^2+Y.^2-1).^2; figure subplot(121) contour(X, Y, P_E, 80) sigma = 8; x = -2:0.01:2; y = -2:0.01:1.5; [X, Y] = meshgrid(x, y); %X = X; %Y = Y; P_E = X + sqrt(3) * Y + sigma/2 * (X.^2+Y.^2-1).^2; subplot(122) contour(X, Y, P_E, 180) 将matlib转换成python

import numpy as np
import matplotlib.pyplot as plt

sigma = 1
x = np.arange(-2, 2.01, 0.01)
y = np.arange(-2, 1.51, 0.01)
X, Y = np.meshgrid(x, y)
P_E = X + np.sqrt(3) * Y + sigma/2 * (X**2 + Y**2 - 1)**2

fig, ax = plt.subplots(1, 2, figsize=(10, 5))
ax[0].contour(X, Y, P_E, 80)
ax[0].set_title("sigma = 1")
sigma = 8
X, Y = np.meshgrid(x, y)
P_E = X + np.sqrt(3) * Y + sigma/2 * (X**2 + Y**2 - 1)**2
ax[1].contour(X, Y, P_E, 180)
ax[1].set_title("sigma = 8")

plt.show()