1

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?

Improve this question
1
  • 2
    Isn't it m[::-1,] Commented Mar 8, 2021 at 18:35

3 Answers 3

Reset to default
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]])
Improve this answer
Sign up to request clarification or add additional context in comments.

Comments

1

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

np.flipud(m)
Improve this answer

Comments

0

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]))
Improve this answer

Comments

Start asking to get answers

Find the answer to your question by asking.

Ask question

Explore related questions

See similar questions with these tags.