I would like to slide a ND numpy array. Currently, the code below do the work.
import numpy as np
arr = np.array([np.arange(0,16), np.arange(17,33),np.arange(33,49)])
window_size=4
expected_opt=[arr [:, i:i+window_size]for i in range(0,16,window_size)]
But I curious whether there is more efficient way to achieve similar objective.
one might suggest 1 , but the solution gives different output.
You are looking at a reshape, not rolling:
arr.reshape(arr.shape[0],-1,window_size).transpose(1,0,2)
Output:
array([[[ 0, 1, 2, 3],
[17, 18, 19, 20],
[33, 34, 35, 36]],
[[ 4, 5, 6, 7],
[21, 22, 23, 24],
[37, 38, 39, 40]],
[[ 8, 9, 10, 11],
[25, 26, 27, 28],
[41, 42, 43, 44]],
[[12, 13, 14, 15],
[29, 30, 31, 32],
[45, 46, 47, 48]]])
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