如何在MatPlotLib中注释/突出显示三维图

Question

我想在3d空间中执行以下操作：http://matplotlib.sourceforge.net/_images/86cbd17f31.png。基本上我想要突出表面图的一部分。有什么建议吗？

Answer 1

edit3 （这取代了之前错误引导的答案）

再次更新。见评论

如果向下钻取到绘图生成的多边形集合，则可以修改曲面图的面颜色。它会进行一些魔术着色并根据zorder对颜色列表进行重新排序，因此我在确定如何在未突出显示的区域中保留指定的阴影但仍然能够索引感兴趣的区域时遇到了一些麻烦。这是一种有效的方法。我希望你想要阴影面，而不是某种3D半透明柱。这也可以做到，但我认为很难说出突出显示的内容，并且定义zorder非常棘手。

import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
import mpl_toolkits.mplot3d.art3d as art3d
from matplotlib.patches import Rectangle, PathPatch

fig = plt.figure()
ax = fig.gca(projection='3d')
X = np.arange(-5, 5, 0.25)
Y = np.arange(-5, 5, 0.25)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X**2 + Y**2)
Z = np.sin(R)

xlo = X.min()
xhi = X.max()
ylo = Y.min()
yhi = Y.max()
zlo = -2
zhi = 2

surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, linewidth=1, zorder=100)
cset = ax.contour(X, Y, Z, zdir='z', offset=zlo, alpha=0.0)

def highlight((xmin, xmax),(ymin, ymax)):
    # draw highlight on xz plane
    p1 = Rectangle((ymin,zlo),(ymax-ymin),(zhi-zlo), color='y', alpha=0.5, zorder=0)
    ax.add_patch(p1)
    art3d.pathpatch_2d_to_3d(p1, z=xlo, zdir='x')

    # draw highlight on yz plane
    p2 = Rectangle((xmin,zlo),(xmax-xmin),(zhi-zlo), color='y', alpha=0.5, zorder=0)
    ax.add_patch(p2)
    art3d.pathpatch_2d_to_3d(p2, z=yhi, zdir='y')

    # define a region to highlight
    highlight = (X>xmin)&(X<xmax)&(Y>ymin)&(Y<ymax)
    coll = ax.collections[0]
    # get the original color shading (if you want to keep that effect)
    colors = coll._facecolors_original
    #colors = coll.get_facecolors()
    # they are stored as a list for some reason so get the flat indicies
    for idx in np.where(highlight[:-1,:-1].flat)[0]:
        # and modifly one-by-one
        color = colors[idx][:]
        colors[idx][0] = color[2]  # swap red with blue
        colors[idx][3] = color[0]
        colors[idx][4] = .2  #change alpha
    # re-set the face colors
    coll.set_facecolors(colors)

highlight((-3,0),(-3,1))

ax.set_xlim3d(xlo, xhi)
ax.set_ylim3d(ylo, yhi)
ax.set_zlim3d(zlo, zhi)

plt.show()