python-3D子图的ConnectionPatch

尝试画一条将3D子图上的点连接到另一个3D子图上的线.在2D模式下,使用ConnectionPatch很容易做到.我试图从here开始模仿Arrow3D类,但没有运气.

我为此很高兴,即使只是解决方法.例如,在下面的代码生成的图中,我想连接两个绿色的点.

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()

解决方法:

我只是想今晚解决一个非常相似的问题!某些代码可能是不必要的,但是它将为您提供主要思想……我希望

灵感来自:http://hackmap.blogspot.com.au/2008/06/pylab-matplotlib-imagemap.html
以及过去两个小时内的其他各种来源…

#! /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()

success http://i42.tinypic.com/5bpxyo.jpg

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