How to modify a 3d array using numpy block without for loop?

I want to modify block elements of 3d array without for loop. Without loop because it is the bottleneck of my code.

To illustrate what I want, I draw a figure:

The code with for loop:

import numpy as np

# Create 3d array with 2x4x4 elements
a = np.arange(2*4*4).reshape(2,4,4)
b = np.zeros(np.shape(a))

# Change Block Elements

for it1 in range(2):
    b[it1]= np.block([[a[it1,0:2,0:2], a[it1,2:4,0:2]],[a[it1,0:2,2:4], a[it1,2:4,2:4]]] )

>Solution :

Will it make it faster?

import numpy as np
a = np.arange(2*4*4).reshape(2,4,4)
b = a.copy()
b[:,0:2,2:4], b[:,2:4,0:2] = b[:,2:4,0:2].copy(), b[:,0:2,2:4].copy()

Comparison with np.block() alternative from another answer.

Option 1:

%timeit b = a.copy(); b[:,0:2,2:4], b[:,2:4,0:2] = b[:,2:4,0:2].copy(), b[:,0:2,2:4].copy()

Output:

5.44 µs ± 134 ns per loop (mean ± std. dev. of 7 runs, 100,000 loops each)

Option 2

%timeit b = np.block([[a[:,0:2,0:2], a[:,2:4,0:2]],[a[:,0:2,2:4], a[:,2:4,2:4]]])

Output:

30.6 µs ± 1.75 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)