我必须为功能绘制轮廓和线框图。这是我到目前为止的代码：
# Number of uniformly ditributed random numbers
n = 2000
def func_vec(x1s, x2s):
return x1s * x1s + 4 * x2s * x2s
np.random.seed()
x1s = np.random.uniform(-1, 1, n)
x2s = np.random.uniform(-1, 1, n)
ys = func_vec(x1s, x2s)
fig = plt.figure()
# Scatter
ax1 = fig.add_subplot(1, 2, 1)
ax1.scatter(x1s, x2s, color = 'g', s = 2, edgecolor = 'none')
ax1.set_ylim([-1,1])
ax1.set_xlim([-1,1])
# Contour
ax1.contour(x2s, x1s, ys[np.newaxis,:].repeat(n, axis = 0))
# 3D visualization
ax2 = fig.add_subplot(1, 2, 2, projection = '3d')
X = x1s
Y = x2s
Z = ys
ax2.plot_wireframe(X, Y, Z, rstride = 1, cstride = 1)
plt.show()
我不了解的是
contour()和plot_firewrame()实际如何工作？有人可以这么友好地向我解释一下吗（在指定功能的背景下）？此外，我应该如何指定X，Y和Z？现在是这样的样子：
这就是它的样子（上面的分散工作正常）：
最佳答案
这是将产生正确绘图的代码。对此进行任何努力的人，应该会发现代码几乎是不言自明的：
# Number of uniformly ditributed random numbers
n = 2000
def func_vec(x1s, x2s):
return x1s * x1s + 4 * x2s * x2s
np.random.seed()
x1s = np.random.uniform(-1, 1, n)
x2s = np.random.uniform(-1, 1, n)
ys = func_vec(x1s, x2s)
fig = plt.figure(22)
# Scatter
ax1 = fig.add_subplot(1, 2, 1)
ax1.scatter(x1s, x2s, color = 'g', s = 2, edgecolor = 'none')
ax1.set_ylim([-1,1])
ax1.set_xlim([-1,1])
# Contour
xi = np.linspace(-1,1,20)
yi = np.linspace(-1,1,20)
zi = griddata((x2s, x1s), ys, (xi[None,:], yi[:,None]), method = 'cubic')
ax1.contour(xi, yi, zi, 6, linewidths = 1, colors = ('#0000ff', '#0099ff', '#009999', '#999900', '#ff9900', '#ff0000'))
# 3D visualization
ax2 = fig.add_subplot(1, 2, 2, projection = '3d')
X, Y = np.meshgrid(xi, yi)
ax2.plot_wireframe(X, Y, zi, rstride = 1, cstride = 1)
ax2.view_init(28, -144)
plt.show()
关于python - 使用Matplotlib绘制轮廓和线框图，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/18923502/