如何在python中随机调整数据和目标？

Question

我有一个4D阵列训练图像,其尺寸对应于(image_number,通道,宽度,高度).我还有一个2D目标标签,其尺寸对应于(image_number,class_number).在训练时,我想通过使用random.shuffle随机地移动数据,但是如何保持标签与我的图像的相同顺序混洗？谢谢!

Answer 1

from sklearn.utils import shuffle
import numpy as np

X = np.array([[0, 0, 0], [1, 1, 1], [2, 2, 2], [3, 3, 3], [4, 4, 4]])
y = np.array([0, 1, 2, 3, 4])
X, y = shuffle(X, y)
print(X)
print(y)



[[1 1 1]
 [3 3 3]
 [0 0 0]
 [2 2 2]
 [4 4 4]] 

[1 3 0 2 4]

Answer 2

如果你想要一个 numpy-only 解决方案，你可以在第一个数组上重新索引第二个数组，假设你在两个数组中都有相同的图像编号：

In [67]: train = np.arange(20).reshape(4,5).T

In [68]: target = np.hstack([np.arange(5).reshape(5,1), np.arange(100, 105).reshape(5,1)])

In [69]: train
Out[69]:
array([[ 0,  5, 10, 15],
       [ 1,  6, 11, 16],
       [ 2,  7, 12, 17],
       [ 3,  8, 13, 18],
       [ 4,  9, 14, 19]])

In [70]: target
Out[70]:
array([[  0, 100],
       [  1, 101],
       [  2, 102],
       [  3, 103],
       [  4, 104]])

In [71]: np.random.shuffle(train)

In [72]: target[train[:,0]]
Out[72]:
array([[  2, 102],
       [  3, 103],
       [  1, 101],
       [  4, 104],
       [  0, 100]])

In [73]: train
Out[73]:
array([[ 2,  7, 12, 17],
       [ 3,  8, 13, 18],
       [ 1,  6, 11, 16],
       [ 4,  9, 14, 19],
       [ 0,  5, 10, 15]])

Answer 3

还有另一种简单的方法可以做到这一点.让我们假设有完整的N图像.然后我们可以做到以下几点:

from random import shuffle

ind_list = [i for i in range(N)]
shuffle(ind_list)
train_new  = train[ind_list, :,:,:]
target_new = target[ind_list,]