How to cut a Numpy 2d array and store as a 3d array?

Question

suppose I have the following Numpy 2d array (3*9)

[[-2 -2 -2 -2 -2 -2 -2 -2 -2]
 [-2 -2 -2 -2 -2 -2 -2 -2 -2]
 [-2 -2 71 -1 -1 -1 71 -1 52]]

I would like to equally divide this whole array by 3 and get the target array like this, which means I should get a 3d array of shape(3 by 3 by3):

[[-2 -2 -2] [-2 -2 -2] [-2 -2 -2]
 [-2 -2 -2] [-2 -2 -2] [-2 -2 -2]
 [-2 -2 71] [-1 -1 -1] [71 -1 52]]

Anyone can explain how to do this?

Frederick Zhang · Accepted Answer · 2022-03-21 10:18:28Z

2

If you already know the previous shape and target shape, you can simply use reshape

arr = [[-2, -2, -2, -2, -2, -2, -2, -2, -2],
[-2, -2, -2, -2, -2, -2, -2, -2, -2,],
[-2, -2, 71, -1, -1, -1, 71, -1, 52]]
arr = np.array(arr)
arr.reshape(3,3,3)

answered Mar 21, 2022 at 10:18

Frederick Zhang

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1 Comment

mozway Over a year ago

Note that you could let numpy do the calculation for you: arr.reshape(3,-1,3)

Mahmoud Hefny · Accepted Answer · 2022-03-21 10:30:52Z

1

you can use reshape method like the following

import numpy as np
array = np.array([[-2,-2,-2,-2,-2,-2,-2,-2,-2],
                [-2,-2,-2,-2,-2,-2,-2,-2,-2],
                [-2,-2,71,-1,-1,-1,71,-1,52]])

newarr = array.reshape(3,3,3)
print(newarr)

answered Mar 21, 2022 at 10:30

Mahmoud Hefny

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