Numpy reshape the matrix

Question

Does anyone can tell me how to use Numpy to reshape the Matrix

[1,2,3,4]
[5,6,7,8]
[9,10,11,12]
[13,14,15,16]

to

[16,15,14,13]
[12,11,10,9]
[8,7,6,5]
[4,3,2,1]

Thanks:)

python 3.8 numpy 1.21.5

an example of my matrixs:

[[ 1.92982258e+00  1.96782439e+00  2.00233048e-01  3.95128552e-01
   4.21665915e-01 -1.10885581e-01  3.15967524e-01  1.86851601e-01]
 [ 5.82581567e-01  3.85242821e-01  6.52345512e-01  6.96774921e-01
   4.46925274e-01  1.10208991e-01 -1.78544580e-02  2.63118328e-01]
 [ 1.18591189e-01 -8.87084649e-02  3.35701398e-01  3.81145692e-01
   2.11622312e-02  3.10028567e-01  2.04480529e-01  4.45985566e-01]
 [ 5.59840625e-01  2.01962111e-01  5.34994738e-01  2.48421290e-01
   2.42632687e-01  2.13238611e-01  3.96632085e-01  4.94549692e-01]
 [-7.69809051e-02 -3.00706661e-04  1.44790257e-01  3.49158021e-01
   1.10096226e-01  2.03164938e-01 -3.45361600e-01 -3.33408510e-02]
 [ 2.33273192e-01  4.39144490e-01 -6.11938054e-02 -6.93128853e-02
  -9.55871298e-02 -1.97338746e-02 -6.54788754e-02  2.81574199e-01]
 [ 6.61742595e-01  4.04149752e-01  2.33536310e-01  8.86332882e-02
  -2.21808751e-01 -5.48789656e-03  5.49503834e-01 -1.22011728e-01]
 [-9.58502481e-03  2.36994437e-01 -1.28777627e-01  3.99751917e-01
  -1.92452263e-02 -2.58119080e-01  3.40399940e-01 -2.20455571e-01]]

Answer 1

You can rotate the matrix with numpy.rot90(). To get two rotations as your example, pass in k=2:

import numpy as np

a = np.array([
    [1,2,3,4],
    [5,6,7,8],
    [9,10,11,12],
    [13,14,15,16],
])

np.rot90(a, k=2)

returning:

array([[16, 15, 14, 13],
       [12, 11, 10,  9],
       [ 8,  7,  6,  5],
       [ 4,  3,  2,  1]])

Note the docs that say it returns a view of the original. This means the rotated matrix shares data with the original. Mutating one effects the other.