三维空间（长方体）中给定边界内均匀分布点的Python随机生成

Question

我试图在python中给定边界内的3D长方体空间中生成2000个随机点。你会怎么做呢

Answer 1

numpy随机生成器类的uniform方法接受数组作为输入，并将广播它们，因此您可以在一次调用中生成值

这里有一个例子。首先，导入numpy并创建随机数生成器的实例。（我正在使用numpy 1.17.0中引入的“新”numpy随机API。）

In [65]: import numpy as np

In [66]: rng = np.random.default_rng()

设置区域的边界

In [67]: x1, x2 = 1, 2
    ...: y1, y2 = 10, 12
    ...: z1, z2 = -5, 0

生成n个样本

In [68]: n = 10

In [69]: sample = rng.uniform([x1, y1, z1], [x2, y2, z2], size=(n, 3))

In [70]: sample
Out[70]: 
array([[ 1.99165561, 10.95293326, -1.44300776],
       [ 1.26473083, 11.46700288, -4.76642593],
       [ 1.50086835, 10.16910997, -4.12962459],
       [ 1.40330536, 10.16069764, -2.32614375],
       [ 1.33484647, 11.12465768, -4.41986844],
       [ 1.51458061, 10.67661873, -1.20121699],
       [ 1.48522136, 10.82256589, -4.76048685],
       [ 1.47682586, 10.94448464, -3.33623395],
       [ 1.30821543, 11.67045336, -3.40941982],
       [ 1.37784727, 11.66706056, -0.09819484]])

---

这也适用于传统的随机API：

In [71]: np.random.uniform([x1, y1, z1], [x2, y2, z2], size=(n, 3))
Out[71]: 
array([[ 1.68445394, 11.59105704, -4.64697128],
       [ 1.61346095, 10.70280999, -2.43062441],
       [ 1.73148392, 11.23600717, -2.66405039],
       [ 1.31235329, 11.23210203, -2.79144212],
       [ 1.07450983, 10.98469372, -4.81962085],
       [ 1.40672198, 11.71311779, -3.52870319],
       [ 1.61392178, 10.5307566 , -2.51603141],
       [ 1.92398626, 10.15939042, -3.11646383],
       [ 1.85797376, 11.88704914, -0.3134136 ],
       [ 1.91229518, 10.23955732, -1.18727606]])

Answer 2

import random

xrange = (-1000.0, 1000.0)
yrange = (-1000.0, 1000.0)
zrange = (-1000.0, 1000.0)

points = []

[ points.append((random.uniform(*xrange), random.uniform(*yrange), random.uniform(*zrange))) for i in range(2000) ]

print(points)

Answer 3

numpy版本，带有“轴系列=比例系数*随机系列+移位位置”

import numpy as np

n = 2000

x1, x2 = 20, 40
y1, y2 = 10, 20
z1, z2 = 25, 50

xs = (x2 - x1)*np.random.rand(n) + x1
ys = (y2 - y1)*np.random.rand(n) + y1
zs = (z2 - z1)*np.random.rand(n) + z1

注：正如文件所指出的，均匀分布用于[0,1]。 我不知道这对你是否重要

如果需要图形：

import matplotlib.pyplot as plt

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

ax.scatter(xs, ys, zs)

ax.set_xlabel('X Label')
ax.set_ylabel('Y Label')
ax.set_zlabel('Z Label')

plt.show()