python 中一个 3D 图形中的多个 2D 等高线图

Question

在 python 中是否有任何方法可以在 python 中的一个 3D 图中绘制多个 2D 等高线图。我目前正在使用 matplotlib 进行等高线绘制，但找不到适合我正在搜索的内容的任何选项。我添加的示例图像。但我想在 Z 轴上进行。

Answer 1

你可以试试这个。

from mpl_toolkits.mplot3d import Axes3D
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.path import Path
import matplotlib.patches as patches

fig    = plt.figure()
ax     = fig.gca(projection='3d')

x      = np.linspace(0, 1, 100)
X, Y   = np.meshgrid(x, x)
levels = np.linspace(-0.1, 0.4, 100)  #(z_min,z_max,number of contour),

a=0
b=1
c=2
Z1 = a+.1*np.sin(2*X)*np.sin(4*Y)
Z2 = b+.1*np.sin(3*X)*np.sin(4*Y)
Z3 = c+.1*np.sin(4*X)*np.sin(5*Y)

plt.contourf(X, Y,Z1, levels=a+levels,cmap=plt.get_cmap('rainbow'))
plt.contourf(X, Y,Z2, levels=b+levels,cmap=plt.get_cmap('rainbow'))
plt.contourf(X, Y,Z3, levels=c+levels,cmap=plt.get_cmap('rainbow'))

ax.set_xlim3d(0, 1)
ax.set_ylim3d(0, 1)
ax.set_zlim3d(0, 2)

plt.show()

Answer 2

为了在一个 3D 图中绘制真正的 2-D 等高线图，试试这个：

import numpy as np
import matplotlib.pyplot as plt

fig    = plt.figure()
ax     = fig.gca(projection='3d')

x      = np.linspace(0, 1, 100)
X, Y   = np.meshgrid(x, x)
Z1 = .1*np.sin(2*X)*np.sin(4*Y)
Z2 = .1*np.sin(3*X)*np.sin(4*Y)
Z3 = .1*np.sin(4*X)*np.sin(5*Y)

levels=np.linspace(Z1.min(), Z1.max(), 100)
ax.contourf(X, Y,Z1, levels=levels, zdir='z', offset=0, cmap=plt.get_cmap('rainbow'))

levels=np.linspace(Z2.min(), Z2.max(), 100)
ax.contourf(X, Y,Z2, levels=levels, zdir='z', offset=1, cmap=plt.get_cmap('rainbow'))

levels=np.linspace(Z3.min(), Z3.max(), 100)
ax.contourf(X, Y,Z3, levels=levels, zdir='z', offset=2, cmap=plt.get_cmap('rainbow'))

ax.set_xlim3d(0, 1)
ax.set_ylim3d(0, 1)
ax.set_zlim3d(0, 2)

plt.show()

enter image description here

python 中一个 3D 图形中的多个 2D 等高线图

Multiple 2D contour plots in one 3D figure in python

python

3d

contour