考虑这个例子:
In [59]: crr
Out[59]:
array([[0.83704624, 0.42109715, 0.50779425, 0.93753455, 0.11773652,
0.08751938],
[0.83704624, 0.42109715, 0.50779425, 0.93753455, 0.11773652,
0.08751938],
[0.83704624, 0.42109715, 0.50779425, 0.93753455, 0.11773652,
0.08751938],
[0.83704624, 0.42109715, 0.50779425, 0.93753455, 0.11773652,
0.08751938],
[0.83704624, 0.42109715, 0.50779425, 0.93753455, 0.11773652,
0.08751938]])
In [60]: np.random.shuffle(crr[0])
In [61]: crr
Out[61]:
array([[0.42109715, 0.50779425, 0.93753455, 0.11773652, 0.08751938,
0.83704624],
[0.83704624, 0.42109715, 0.50779425, 0.93753455, 0.11773652,
0.08751938],
[0.83704624, 0.42109715, 0.50779425, 0.93753455, 0.11773652,
0.08751938],
[0.83704624, 0.42109715, 0.50779425, 0.93753455, 0.11773652,
0.08751938],
[0.83704624, 0.42109715, 0.50779425, 0.93753455, 0.11773652,
0.08751938]])
由于随机洗牌是就地的,这里我们可以只指定要洗牌的第一行。因此,如果您使用np.repeat 或np.tile 重复您的A N 次并将结果重新整形为像crr 这样的二维数组,您可以这样做以达到最终目标:
In [69]: for v in crr:
...: np.random.shuffle(v)