I would like to draw a surface and some of its iso-z contours, using the plot_surface and contour3D functions of mplot3D. Here is an example (I would like to use it to illustrate Lagrange points in physics) :
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
epsilon, r1 = 0.3, 1
r2 = epsilon*r1
Omega2 = 1/(r1*pow(r1+r2, 2))
u = np.linspace(-2, 2, 100)
x , y = np.meshgrid(u, u)
z = -epsilon/np.sqrt(np.power(x-r1, 2)+ np.power(y, 2)) - 1/np.sqrt(np.power(x+r2, 2)+ np.power(y, 2)) - 0.5*Omega2*(np.power(x, 2) + np.power(y, 2))
z = np.clip(z, -3, 0)
ax.plot_surface(x, y, z, rstride=1, cstride=1, antialiased=True, color="whitesmoke")
ax.contour3D(x, y, z+0.01, levels=np.arange(-2, -1, 0.1))
plt.show()
In the resulting plot, the contours do not show properly :
and as the figure is interactively rotated, they randomly appear and disappear, with a wrong estimation of what part should be hidden by the surface :
Example of figure obtained by interactive rotation
This had been noticed before 4 years ago but no solution had been suggested. Hence my questions : is it still, 4 years after, considered as a limitation of the plotting capabilities of matplolib ? And is there an alternative way, using some other graphical library ?
