Rotate 2D axis around the central x axis

Question

I have a simple 2D array:

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

And would like it to be:

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

How could this be done, and then, in general, how could this be done for an [n,m] sort of array?

Asked By: Miss_Orchid

||

Source

Answer 1

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]])

Answered By: chirag goyal

Answer 2

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]])

Answered By: Sadra TMH

Answer 3

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.flipupd(arr)

Output:

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

Answered By: MagnusO_O

Answer 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]])

Answered By: ninpnin

Answer 5

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]])

Answered By: Mechanic Pig

Rotate 2D axis around the central x axis

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