尝试绘制连接3D子图上的点到另一个3D子图的线。在2D中，使用ConnectionPatch很容易。我试图从here模仿Arrow3D类没有运气。
我很高兴在这一点上进行解决方案。作为一个例子，在下面的代码生成的图中，我想要连接两个绿点。
def cylinder(r, n):
'''
Returns the unit cylinder that corresponds to the curve r.
INPUTS: r - a vector of radii
n - number of coordinates to return for each element in r
OUTPUTS: x,y,z - coordinates of points
'''
# ensure that r is a column vector
r = np.atleast_2d(r)
r_rows, r_cols = r.shape
if r_cols > r_rows:
r = r.T
# find points along x and y axes
points = np.linspace(0, 2*np.pi, n+1)
x = np.cos(points)*r
y = np.sin(points)*r
# find points along z axis
rpoints = np.atleast_2d(np.linspace(0, 1, len(r)))
z = np.ones((1, n+1))*rpoints.T
return x, y, z
#---------------------------------------
# 3D example
#---------------------------------------
fig = plt.figure()
# top figure
ax = fig.add_subplot(2,1,1, projection='3d')
x,y,z = cylinder(np.linspace(2,1,num=10), 40)
for i in range(len(z)):
ax.plot(x[i], y[i], z[i], 'c')
ax.plot([2], [0], [0],'go')
# bottom figure
ax2 = fig.add_subplot(2,1,2, projection='3d')
x,y,z = cylinder(np.linspace(0,1,num=10), 40)
for i in range(len(z)):
ax2.plot(x[i], y[i], z[i], 'r')
ax2.plot([1], [0], [1],'go')
plt.show()
答案 0 :(得分：4)
我正试图在今晚解决一个非常类似的问题！有些代码可能是不必要的，但它会给你一个主要的想法......我希望
灵感来自：http://hackmap.blogspot.com.au/2008/06/pylab-matplotlib-imagemap.html 过去两个小时内有很多不同来源...
#! /usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d import proj3d
import matplotlib
N = 50
x = np.random.rand(N)
y = np.random.rand(N)
z = np.random.rand(N)
# point's to join
p1 = 10
p2 = 20
fig = plt.figure()
# a background axis to draw lines on
ax0 = plt.axes([0.,0.,1.,1.])
ax0.set_xlim(0,1)
ax0.set_ylim(0,1)
# use these to know how to transform the screen coords
dpi = ax0.figure.get_dpi()
height = ax0.figure.get_figheight() * dpi
width = ax0.figure.get_figwidth() * dpi
# first scatter plot
ax1 = plt.axes([0.05,0.05,0.9,0.425], projection='3d')
ax1.scatter(x, y, z)
# one point of interest
ax1.scatter(x[p1], y[p1], z[p1], s=100.)
x1, y1, _ = proj3d.proj_transform(x[p1], y[p1], z[p1], ax1.get_proj())
[x1,y1] = ax1.transData.transform((x1, y1)) # convert 2d space to screen space
# put them in screen space relative to ax0
x1 = x1/width
y1 = y1/height
# second scatter plot (same data)
ax2 = plt.axes([0.05,0.475,0.9,0.425], projection='3d')
ax2.scatter(x, y, z)
# another point of interest
ax2.scatter(x[p2], y[p2], z[p2], s=100.)
x2, y2, _ = proj3d.proj_transform(x[p2], y[p2], z[p2], ax2.get_proj())
[x2,y2] = ax2.transData.transform((x2, y2)) # convert 2d space to screen space
x2 = x2/width
y2 = y2/height
# set all these guys to invisible (needed?, smartest way?)
for item in [fig, ax1, ax2]:
item.patch.set_visible(False)
# draw a line between the transformed points
# again, needed? I know it works...
transFigure = fig.transFigure.inverted()
coord1 = transFigure.transform(ax0.transData.transform([x1,y1]))
coord2 = transFigure.transform(ax0.transData.transform([x2,y2]))
line = matplotlib.lines.Line2D((coord1[0],coord2[0]),(coord1[1],coord2[1]),
transform=fig.transFigure)
fig.lines = line,
plt.show()
答案 1 :(得分：0)
我的最终代码，只是为了得到一个可行的例子：
#! /usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
import mpl_toolkits.mplot3d.axes3d as p3
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d import proj3d
import matplotlib
def cylinder(r, n):
'''
Returns the unit cylinder that corresponds to the curve r.
INPUTS: r - a vector of radii
n - number of coordinates to return for each element in r
OUTPUTS: x,y,z - coordinates of points
'''
# ensure that r is a column vector
r = np.atleast_2d(r)
r_rows, r_cols = r.shape
if r_cols > r_rows:
r = r.T
# find points along x and y axes
points = np.linspace(0, 2*np.pi, n+1)
x = np.cos(points)*r
y = np.sin(points)*r
# find points along z axis
rpoints = np.atleast_2d(np.linspace(0, 1, len(r)))
z = np.ones((1, n+1))*rpoints.T
return x, y, z
#---------------------------------------
# 3D example
#---------------------------------------
fig = plt.figure()
# a background axis to draw lines on
ax0 = plt.axes([0.,0.,1.,1.])
ax0.set_xlim(0,1)
ax0.set_ylim(0,1)
# use these to know how to transform the screen coords
dpi = ax0.figure.get_dpi()
height = ax0.figure.get_figheight() * dpi
width = ax0.figure.get_figwidth() * dpi
# top figure
ax1 = fig.add_subplot(2,1,1, projection='3d')
x,y,z = cylinder(np.linspace(2,1,num=10), 40)
for i in range(len(z)):
ax1.plot(x[i], y[i], z[i], 'c')
# bottom figure
ax2 = fig.add_subplot(2,1,2, projection='3d')
x,y,z = cylinder(np.linspace(0,1,num=10), 40)
for i in range(len(z)):
ax2.plot(x[i], y[i], z[i], 'r')
# first point of interest
p1 = ([2],[0],[0])
ax1.plot(p1[0], p1[1], p1[2],'go')
x1, y1, _ = proj3d.proj_transform(p1[0], p1[1], p1[2], ax1.get_proj())
[x1,y1] = ax1.transData.transform((x1[0], y1[0])) # convert 2d space to screen space
# put them in screen space relative to ax0
x1 = x1/width
y1 = y1/height
# another point of interest
p2 = ([1], [0], [1])
ax2.plot(p2[0], p2[1], p2[2],'go')
x2, y2, _ = proj3d.proj_transform(p2[0], p2[1], p2[2], ax2.get_proj())
[x2,y2] = ax2.transData.transform((x2[0], y2[0])) # convert 2d space to screen space
x2 = x2/width
y2 = y2/height
# plot line between subplots
transFigure = fig.transFigure.inverted()
coord1 = transFigure.transform(ax0.transData.transform([x1,y1]))
coord2 = transFigure.transform(ax0.transData.transform([x2,y2]))
fig.lines = ax0.plot((coord1[0],coord2[0]),(coord1[1],coord2[1]), transform=fig.transFigure, linestyle='dashed' )
plt.show()