仅按行进行整洁的随机多维数组，保持列顺序不变 [英] Numpy shuffle multidimensional array by row only, keep column order unchanged

问题描述

如何仅在Python中按行对多维数组进行混排(因此，请勿对列进行混排).

How can I shuffle a multidimensional array by row only in Python (so do not shuffle the columns).

我正在寻找最有效的解决方案，因为我的矩阵非常庞大.是否还可以在原始阵列上高效执行此操作(以节省内存)?

示例:

import numpy as np
X = np.random.random((6, 2))
print(X)
Y = ???shuffle by row only not colls???
print(Y)

我现在期望的是原始矩阵:

What I expect now is original matrix:

[[ 0.48252164  0.12013048]
 [ 0.77254355  0.74382174]
 [ 0.45174186  0.8782033 ]
 [ 0.75623083  0.71763107]
 [ 0.26809253  0.75144034]
 [ 0.23442518  0.39031414]]

输出会随机洗排行，例如:

Output shuffle the rows not cols e.g.:

[[ 0.45174186  0.8782033 ]
 [ 0.48252164  0.12013048]
 [ 0.77254355  0.74382174]
 [ 0.75623083  0.71763107]
 [ 0.23442518  0.39031414]
 [ 0.26809253  0.75144034]]

推荐答案

这就是numpy.random.shuffle()的作用:

>>> X = np.random.random((6, 2))
>>> X
array([[ 0.9818058 ,  0.67513579],
       [ 0.82312674,  0.82768118],
       [ 0.29468324,  0.59305925],
       [ 0.25731731,  0.16676408],
       [ 0.27402974,  0.55215778],
       [ 0.44323485,  0.78779887]])

>>> np.random.shuffle(X)
>>> X
array([[ 0.9818058 ,  0.67513579],
       [ 0.44323485,  0.78779887],
       [ 0.82312674,  0.82768118],
       [ 0.29468324,  0.59305925],
       [ 0.25731731,  0.16676408],
       [ 0.27402974,  0.55215778]])

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