matlab - 在 matplotlib 中显示最大表面？

Question

我正在使用 matplotlib 在同一个图形上绘制多个表面，我只想看到最上面的表面，如 matlab 所示。

Matlab 3D View :

Matlab 俯 View :

Matplotlib 3D View :

Matplotlib 顶 View :

如何让 Matplotlib 显示类似于 Matlab 的结果，其中最顶层的类显示在顶部，而不是一个类优先于另一个类？

Answer 1

我本来想考虑一些肮脏的黑客攻击，比如 mgab 在他们的回答中提到的，但后来决定走一条相当简单的路线:

你可以纯粹通过使用透明度来获得类似的效果，你只需要确保透明度足够低，否则你仍然会发生明显的重叠事情:

from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
import matplotlib.pyplot as plt
import numpy as np
from scipy.special import erf

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

X = np.arange(0, 6, 0.25)
Y = np.arange(0, 6, 0.25)
X, Y = np.meshgrid(X, Y)

Z1 = np.zeros_like(X)
Z2 = np.ones_like(X)

for i in range(len(X)):
  for j in range(len(X[0])):
    Z1[i,j] = 0.5*(erf((X[i,j]+Y[i,j]-4.5)*0.5)+1)
    Z2[i,j] = 0.5*(erf((-X[i,j]-Y[i,j]+4.5)*0.5)+1)


alpha = 0.25

surf1 = ax.plot_surface(X, Y, Z1, cstride=2, rstride=1, cmap=cm.Oranges, linewidth=0, antialiased=False, alpha=alpha)

surf2 = ax.plot_surface(X, Y, Z2, cstride=2, rstride=1, cmap=cm.Blues, linewidth=0, antialiased=False, alpha=alpha)

ax.zaxis.set_major_locator(LinearLocator(10))
ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))

fig.colorbar(surf1, shrink=0.5, aspect=5)
fig.colorbar(surf2, shrink=0.5, aspect=5)

plt.show()

添加交叉线会是一个很好的添加，但我目前没有简单的方法来添加它。

编辑:从 mgab 的答案中大量窃取，使用他的“桥梁”解决方案，然后还对表面使用颜色贴图，并使用 RGBA 元组将桥面设置为透明，您可以几乎完全得到你想要的:

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
from scipy.special import erf

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

X = np.arange(0, 6, 0.25)
Y = np.arange(0, 6, 0.25)
X, Y = np.meshgrid(X, Y)

Z1 = np.empty_like(X)
Z2 = np.empty_like(X)
C1 = np.empty_like(X, dtype=object)
C2 = np.empty_like(X, dtype=object)

for i in range(len(X)):
  for j in range(len(X[0])):
    z1 = 0.5*(erf((X[i,j]+Y[i,j]-4.5)*0.5)+1)
    z2 = 0.5*(erf((-X[i,j]-Y[i,j]+4.5)*0.5)+1)
    Z1[i,j] = z1
    Z2[i,j] = z2

    # If you want to grab a colour from a matplotlib cmap function, 
    # you need to give it a number between 0 and 1. z1 and z2 are 
    # already in this range, so it just works.
    C1[i,j] = plt.get_cmap("Oranges")(z1)
    C2[i,j] = plt.get_cmap("Blues")(z2)


# Create a transparent bridge region
X_bridge = np.vstack([X[-1,:],X[-1,:]])
Y_bridge = np.vstack([Y[-1,:],Y[-1,:]])
Z_bridge = np.vstack([Z1[-1,:],Z2[-1,:]])
color_bridge = np.empty_like(Z_bridge, dtype=object)

color_bridge.fill((1,1,1,0)) # RGBA colour, onlt the last component matters.

# Join the two surfaces flipping one of them (using also the bridge)
X_full = np.vstack([X, X_bridge, np.flipud(X)])
Y_full = np.vstack([Y, Y_bridge, np.flipud(Y)])
Z_full = np.vstack([Z1, Z_bridge, np.flipud(Z2)])
color_full = np.vstack([C1, color_bridge, np.flipud(C2)])

surf_full = ax.plot_surface(X_full, Y_full, Z_full, rstride=1, cstride=1,
                            facecolors=color_full, linewidth=0,
                            antialiased=False)


plt.show()