How to sort a 3D numpy array according to a column?

Question

For a 2d array, a, we can sort using

a = a[a[:, 0].argsort]

if we want to sort by column 0. How to do a similar thing for a 3d matrix? If we have


a = [[[ 1.,  2., 10.],
         [ 4.,  5.,  6.],
         [ 2.,  3.,  4.]],

        [[ 2.,  3.,  4.],
         [ 4.,  5.,  6.],
         [ 1.,  2.,  3.]],

        [[ 1.,  2.,  3.],
         [ 4.,  5.,  6.],
         [ 2.,  3.,  4.]]]

And we want to sort according to the first column of each element of the 3d matrix?

A (3, 3, 3) sorted array. Sorted by the first column of each element. — Anupam Tripathi
– Anupam Tripathi, Commented Feb 14, 2020 at 21:45
We sort an array by element, but in your case your element is a whole column, we can't make comparisons like [1,2,3] > [1,3,5], what you can do is compare the first element of each column, the l1 or l2 norms, max value, etc. — rrrttt
– rrrttt, Commented Feb 15, 2020 at 14:11

YKang · Accepted Answer · 2020-12-12 08:47:45Z

1

I hope this can help:

COL = 0
DIM0 = 3
a[:, a[:, :, COL].argsort()][np.diag_indices(DIM0)]

answered Dec 12, 2020 at 8:47

YKang

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1 Comment

jeffhale Over a year ago

Thank you for your answer. Explaining what is happening in it would probably make it more helpful to the asker.

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