我有两个变量的两对最小值和最大值。我想从这两个变量的均匀分布中抽取 n 个随机样本,位于它们的最小值和最大值之间。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
如何使用 numpy 以简单的方式实现这一点?
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:不是重复的。建议的重复问题的答案涉及整数。
最佳答案
numpy 中大多数随机生成函数的参数都在数组上运行。以下代码生成 10 个样本,其中第一列取自 (0, 10) 均匀分布,第二列取自 (0, 20)。
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]]
关于python - 如何从两个范围内抽取二维随机均匀样本,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/49754797/