>>> import numpy as np
>>> num_dim, num_data = 10, 5
>>> data = np.random.rand(num_data, num_dim)
>>> data
array([[ 0.0498063 , 0.18659463, 0.30563225, 0.99681495, 0.35692358,
0.47759707, 0.85755606, 0.39373145, 0.54677259, 0.5168117 ],
[ 0.18034536, 0.25935541, 0.79718771, 0.28604057, 0.17165293,
0.90277904, 0.94016733, 0.15689765, 0.79758063, 0.41250143],
[ 0.80716045, 0.84998745, 0.17893211, 0.36206016, 0.69604008,
0.27249491, 0.92570247, 0.446499 , 0.34424945, 0.08576628],
[ 0.35311449, 0.67901964, 0.71023927, 0.03120829, 0.72864953,
0.60717032, 0.8020118 , 0.36047207, 0.46362718, 0.12441942],
[ 0.1955419 , 0.02702753, 0.76828842, 0.5438226 , 0.69407709,
0.20865243, 0.12783666, 0.81486189, 0.95583274, 0.30157658]])
从data，我需要随机挑选3个向量，我可以做到这一点：
>>> import random
>>> random.sample(data, 3)
[array([ 0.80716045, 0.84998745, 0.17893211, 0.36206016, 0.69604008,
0.27249491, 0.92570247, 0.446499 , 0.34424945, 0.08576628]), array([ 0.18034536, 0.25935541, 0.79718771, 0.28604057, 0.17165293,
0.90277904, 0.94016733, 0.15689765, 0.79758063, 0.41250143]), array([ 0.35311449, 0.67901964, 0.71023927, 0.03120829, 0.72864953,
0.60717032, 0.8020118 , 0.36047207, 0.46362718, 0.12441942])]
是不是numpy.random.sample()与random.sample()不一样？
请问numpy的random.sample()是否等值？
2016-09-19
alvas
+3
我认为您正在寻找'np.random.choice'。虽然你需要传递'replace = False'，它的行为与'random.sample'类似。 –
+1
你想做什么*做*？什么'numpy.random.sample'做(或不做)，你想(或不想)它做？ –
+0
@brenbarn我需要随机选择n号。来自矢量列表的元素。 –