How to index/slice 3D numpy array

Question

I'm relatively new to python/numpy. I have a 3D numpy array of TxNxN. It contains a sequence of symmetrical NxN matrices. I want convert it to a 2D array of TxM (where M = N(N+1)/2). How can I do that? I can certainly use 3 loops, but I thought there probably better ways to do that in python/numpy.

You need to understand slicing in numpy first, thats the direction to look at, and it can be done on 1 loop, by iterating only on the 3rd dimension. on each iteration you will need to instantiate and create a 2D array that you can store either on a list, a variable, a file (probably as an image, I have no context on your problem). — EnriqueBet
– EnriqueBet, Commented May 25, 2022 at 3:29
Show us the 3 loops first! And as a bonus - your attempt(s) at "better" ways. — hpaulj
– hpaulj, Commented May 25, 2022 at 3:32
Basically: 1. do a for loop across the X dimension (in this case I'll take the 3rd for example), in this case: for k in range(N) 2. do something for each iteration of k. Example: slice = my3dnumpyarray[:, :, k] Note: each : means that you are taking the whole range (domain) of that dimension, if the first dimension goes from 0 to T - 1 then the first : means exactly that — EnriqueBet
– EnriqueBet, Commented May 25, 2022 at 3:32

Mechanic Pig · Accepted Answer · 2022-05-26 06:48:35Z

It seems that you want to get the upper triangle or lower triangle of each symmetric matrix. A simple method is to generate a mask array and apply it to each 2D array:

>>> e
array([[[0, 1, 2, 3],
        [1, 2, 3, 0],
        [2, 3, 0, 1],
        [3, 0, 1, 2]],

       [[1, 2, 3, 4],
        [2, 3, 4, 1],
        [3, 4, 1, 2],
        [4, 1, 2, 3]],

       [[2, 3, 4, 5],
        [3, 4, 5, 2],
        [4, 5, 2, 3],
        [5, 2, 3, 4]]])
>>> ii, jj = np.indices(e.shape[1:])
>>> jj >= ii
array([[ True,  True,  True,  True],
       [False,  True,  True,  True],
       [False, False,  True,  True],
       [False, False, False,  True]])
>>> e[:, jj >= ii]
array([[0, 1, 2, 3, 2, 3, 0, 0, 1, 2],
       [1, 2, 3, 4, 3, 4, 1, 1, 2, 3],
       [2, 3, 4, 5, 4, 5, 2, 2, 3, 4]])

Using the numpy.triu_indices function can do better, but you can't put the obtained indices tuple directly between square brackets. You need to unpack them first:

>>> i, j = np.triu_indices(e.shape[1])
>>> e[:, i, j]
array([[0, 1, 2, 3, 2, 3, 0, 0, 1, 2],
       [1, 2, 3, 4, 3, 4, 1, 1, 2, 3],
       [2, 3, 4, 5, 4, 5, 2, 2, 3, 4]])

Collectives™ on Stack Overflow

How to index/slice 3D numpy array

1 Answer 1

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

Comments

Your Answer

Sign up or log in

Post as a guest

Related