numpy array operation

[C. Ng]

Is there a numpy operation that does the following to the array?

1 2 ==> 4 3
3 4 2 1

Thanks in advance.

 

[Peter Otten]

Is there a numpy operation that does the following to the array?

1 2 ==> 4 3
3 4 2 1

How about
array([[1, 2],
[3, 4]])

a[::-1].transpose()[::-1].transpose()

array([[4, 3],
[2, 1]])

Or did you mean

a.reshape((4,))[::-1].reshape((2,2))

array([[4, 3],
[2, 1]])

Or even
array([[4, 3],
[2, 1]])

 

[Tim Williams]

Is there a numpy operation that does the following to the array?



1 2 ==> 4 3

3 4 2 1



Thanks in advance.

import numpy as np
a=np.array([[1,2],[3,4]])
a

array([[1, 2],
[3, 4]])array([[4, 3],
[2, 1]])

 

[Terry Reedy]

Is there a numpy operation that does the following to the array?

1 2 ==> 4 3
3 4 2 1

Thanks in advance.

How about:

import numpy as np
a = np.array([[1,2],[3,4]])
a array([[1, 2], [3, 4]])
a[::-1, ::-1]

array([[4, 3], [2, 1]])

Nice. The regular Python equivalent is

a = [[1,2],[3,4]]
print([row[::-1] for row in a[::-1]])[[4, 3], [2, 1]]

The second slice can be replaced with reversed(a), which returns an
iterator, to get
[row[::-1] for row in reversed(a)]
The first slice would have to be list(reversed(a)) to get the same result.