Rotate 2D axis around the central x axis

You can use np.flipud (up/down) or with similar result np.flip on the axis=0:

import numpy as np

arr = np.array([[ 1,  2,  3,  4],
                [ 5,  6,  7,  8],
                [ 9, 10, 11, 12]])

flipud_arr = np.flipud(arr)
print(flipud_arr)    

flip_arr = np.flip(arr, axis=0)
print(flip_arr)

Both have the same output:

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

Both work in general, so also for even rows:

arr = np.array([[ 1,  2,  3,  4],
                [ 5,  6,  7,  8],
                [ 9, 10, 11, 12],
                [ 3,  0,  8,  1]])
np.flipud(arr)  # in place = same memory, for copy see 1st code snippet

Output:

array([[ 3,  0,  8,  1],
       [ 9, 10, 11, 12],
       [ 5,  6,  7,  8],
       [ 1,  2,  3,  4]])

Slicing:

>>> ar = np.array([[ 1,  2,  3,  4],
...                [ 5,  6,  7,  8],
...                [ 9, 10, 11, 12]])
>>> ar[::-1]
array([[ 9, 10, 11, 12],
       [ 5,  6,  7,  8],
       [ 1,  2,  3,  4]])

This returns an array view, which shares memory with the original array. If you do not want to share memory, copy it:

>>> ar[::-1].copy()
array([[ 9, 10, 11, 12],
       [ 5,  6,  7,  8],
       [ 1,  2,  3,  4]])

Code:

a = np.array([[ 1,  2,  3,  4],
              [ 5,  6,  7,  8],
              [ 9, 10, 11, 12]])
         
b = a.copy()

for i in range(len(a)):
    b[i], b[len(a) - i - 1] = a[len(a) - i - 1], a[i]

print(b)

Output:

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

I don't know if there is a method for it in Numpy but one way is to re-index it backwards. This is how it's done:

import numpy as np
a = np.array([[ 1,  2,  3,  4],
              [ 5,  6,  7,  8],
              [ 9, 10, 11, 12]])

a = a[list(range(len(a)-1,-1,-1))] 
a

output:

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

np.flip does the job.

>>>A = np.array([[ 1,  2,  3,  4],
       [ 5,  6,  7,  8],
       [ 9, 10, 11, 12]])
>>>np.flip(A, axis=0)
array([[ 9, 10, 11, 12],
       [ 5,  6,  7,  8],
       [ 1,  2,  3,  4]])