Finding unique slices of a multidimensional array
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I'm trying to find unique slices of a multi-dimensional array. For example, if I have something like
A = repmat(magic(4),1,1,3);
A(:,:,2) = A(:,:,2) - 1
A(:,:,1) =
16 2 3 13
5 11 10 8
9 7 6 12
4 14 15 1
A(:,:,2) =
15 1 2 12
4 10 9 7
8 6 5 11
3 13 14 0
A(:,:,3) =
16 2 3 13
5 11 10 8
9 7 6 12
4 14 15 1
I would like to be able to call something (with the dimension along which I'm slicing specified) and get
[C, ia, ic] = highdim_unique(A, 3)
C(:,:,1) =
16 2 3 13
5 11 10 8
9 7 6 12
4 14 15 1
C(:,:,2) =
15 1 2 12
4 10 9 7
8 6 5 11
3 13 14 0
ia =
1
2
ic =
1
2
1
Any chance that something like this exists or has a straightforward solution? Ideally I would want to do this for arbitrariliy many dimensions, but doing it in 3 would be fine.
Thanks,
Jake
0 Comments
Accepted Answer
the cyclist
on 20 Nov 2020
% Define a 3-d array of pretend data, that has a couple duplicate slices
% (Use your data instead)
rng default
A = rand(2,2,4) > 0.5;
% Find the size of A, for generality
[s1,s2,s3] = size(A);
% Reshape the slices into rows (by working down column-wise, and then across columns)
A_r = reshape(A,s1*s2,s3,1)';
% Find the unique rows (which corresponds to unique slices of original array)
A_ru = unique(A_r,'rows','stable');
% Reshape the rows back to 3-d
A_u = reshape(A_ru',s1,s2,[]);
2 Comments
the cyclist
on 20 Nov 2020
Excellent.
I didn't really think about how to do it for N-dimensional array for N>3, but I see no reason why you could not do the same "reshape into rows" method.
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