`import numpy as np
import matplotlib.pyplot as plt
from scipy.interpolate import griddata
def f(x, y):
x2 = x2
return (x2 - 2*x) * np.exp(-x2 - y2 - x*y)
x_min, x_max = -3, 3
y_min, y_max = -4, 4
num_points = 1000
x_random = np.random.uniform(x_min, x_max, num_points)
y_random = np.random.uniform(y_min, y_max, num_points)
z_random = f(x_random, y_random)
grid_x, grid_y = np.mgrid[x_min:x_max:100j, y_min:y_max:100j]
grid_z = griddata((x_random, y_random), z_random, (grid_x, grid_y), method='cubic')
fig, ax = plt.subplots(figsize=(10, 8))
contourf = ax.contourf(grid_x, grid_y, grid_z, levels=50, cmap='viridis')
fig.colorbar(contourf, ax=ax, label='f(x, y)')
ax.scatter(x_random, y_random, c='red', s=10, label="随机散乱点")
ax.set_title("函数f(x,y)的插值结果")
ax.set_xlabel('x')
ax.set_ylabel('y')
ax.legend()
ax.grid(True)
plt.show()
print("学号后四位：3005")
`
