使用线条/条连接3D点

Question

我目前在3D空间中绘制了一系列点。我想将它们连接在一起形成一个矩形。矩形需要一定的宽度和高度，并且如果遇到框边界，应该以某种方式“包裹”到gthe框的另一边。

我的代码如下：

import matplotlib.pyplot as pyplot
import numpy as np
from mpl_toolkits.mplot3d import Axes3D

x       = [0, 0, 0, 0, 50, 50, 50, 50]
y       = [50,50,50,50,50,50,50,50]
z       = [12.5,37.5,62.5,87.5,25,50,75,0]

fig = pyplot.figure()
ax  = fig.add_subplot(111, projection = '3d')

ax.set_xlim(0,100)
ax.set_ylim(0,100)
ax.set_zlim(0,100)
ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')

#ax.view_init(elev=90, azim=90)
ax.scatter(x, y, z, zdir='z', s=20, c='g')

pyplot.show()

有人有什么想法吗？非常感谢

Answer 1

一种可能的算法是

1. 找到矩形的顶点
2. 重新排序顶点以形成rectagle

这是一个可能的解决方案：

#!/usr/bin/env python3

import matplotlib.pyplot as pyplot
from numpy import *
from numpy import linalg
from mpl_toolkits.mplot3d import Axes3D

x       = array([0, 0, 0, 0, 50, 50, 50, 50])
y       = array([50,50,50,50,50,50,50,50])
z       = array([12.5,37.5,62.5,87.5,25,50,75,0])

data = concatenate((x[:,newaxis],y[:,newaxis],z[:,newaxis]), axis=1)

center = data.mean(axis=0)

distances = empty((0))
for row in data:
    distances = append(distances, linalg.norm(row - center))

vertices = distances.argsort()[-4:]
Vertices_reorder = [vertices[0], vertices[2], vertices[1], vertices[3], vertices[0]]

# plot:
fig = pyplot.figure()
ax  = fig.add_subplot(111, projection = '3d')

ax.set_xlim(0,100)
ax.set_ylim(0,100)
ax.set_zlim(0,100)
ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')

#ax.view_init(elev=90, azim=90)
ax.scatter(x, y, z, zdir='z', s=20, c='g')
ax.plot(x[Vertices_reorder], y[Vertices_reorder], z[Vertices_reorder])

fig.savefig("rect.png")

结果：



我不确定实施的重新排序是否适用于所有情况。