how to swap all rows in an array

Question

I try to rotate the matrix so that the first line is the last and the last is the first. And proceed in this way with the other lines in array

import numpy as np
m = np.array([[11, 12, 13, 14, 15],
              [21, 22, 23, 24, 25],
              [31, 32, 33, 34, 35],
              [41, 42, 43, 44, 45]])

My attempt:

p = np.rot90(m, 2)
array([[45, 44, 43, 42, 41],
       [35, 34, 33, 32, 31],
       [25, 24, 23, 22, 21],
       [15, 14, 13, 12, 11]])

I need

array([[41, 42, 43, 44, 45],
       [31, 32, 33, 34, 35],
       [21, 22, 23, 24, 25],
       [11, 12, 13, 14, 15]])

Do you have any advice?

2

Isn't it ```m[::-1,]``` – StupidWolf Mar 08 '21 at 18:35

score 1 · Answer 1 · answered Mar 08 '21 at 18:40

1

np.flip(m,axis=0)

output

array([[41, 42, 43, 44, 45],
       [31, 32, 33, 34, 35],
       [21, 22, 23, 24, 25],
       [11, 12, 13, 14, 15]])

answered Mar 08 '21 at 18:40

Rob Raymond

29,118
3
14
30

score 1 · Answer 2 · answered Mar 09 '21 at 05:17

1

You're essentially trying to flip the matrix vertically and the function is literally flipud:

np.flipud(m)

answered Mar 09 '21 at 05:17

Pacific Stickler

1,078
8
20

score 0 · Answer 3 · answered Mar 11 '21 at 21:18

Aside from flipud(m) and flip(m, axis=0), you can use simple indexing to reverse the first dimension:

m[::-1, :]

or even just

m[::-1]

If you really wanted arcane overkill, you could do something with np.lib.stride_tricks.as_strided:

np.lib.stride_tricks.as_strided(m[-1], shape=m.shape, strides=(-m.strides[0], m.strides[1]))

how to swap all rows in an array

3 Answers3

output