如何从两个范围绘制2D随机均匀样本

Question

我有两个变量的最大值和最小值两对。我想从这两个变量的最小值和最大值之间的均匀分布中提取n个随机样本。例如：

min_x = 0
max_x = 10
min_y = 0
max_y = 20

假设我画了三个样本。这些可能是：

[(4, 15), (8, 9), (0, 19)] # First value is drawn randomly with uniform probability between min_x and max_x, second value is drawn similarly between min_y and max_y

我如何用numpy做到这一点？

我想出了这个：

>>> min_x = 0
>>> max_x = 10
>>> min_y = 0
>>> max_y = 20
>>> sample = np.random.random_sample(2)
>>> sample[0] = (sample[0]) * max_x - min_x
>>> sample[1] = (sample[1]) * max_y - min_y
>>> sample
array([ 1.81221794, 18.0091034 ])

但我觉得应该有一个更简单的解决方案。

编辑：不重复。建议的重复问题的答案涉及整数。

Answer 1

numpy中大多数随机生成函数的参数都在数组上运行。下面的代码产生10个样本，其中第一列从（0，10）均匀分布中绘制，第二列从（0，20）中绘制。

n = 10
xy_min = [0, 0]
xy_max = [10, 20]
data = np.random.uniform(low=xy_min, high=xy_max, size=(n,2))
print(data)

输出是

[[ 5.93168121,  7.36060232],
 [ 6.0681728 ,  8.83458336],
 [ 3.51412518,  7.86395892],
 [ 5.28704184, 11.2423749 ],
 [ 8.14407888,  6.30980757],
 [ 8.93337281, 13.39148231],
 [ 6.94694921, 19.50003171],
 [ 2.52280804, 13.21572422],
 [ 3.41855383,  2.56327567],
 [ 4.06155783,  3.95026796]]