# Row wise indexing of 3d array

3 vues (au cours des 30 derniers jours)
Oscar Frick le 14 Juin 2018
Commenté : Oscar Frick le 15 Juin 2018
I have a 3d array, for example:
(:,:,1)
-0.1468 -0.4846 -0.3310
0.3212 -0.4570 0.1491
(:,:,2)
-0.3110 -0.3165 0.1256
0.1868 -0.1315 0.2802
(:,:,3)
-0.4189 0.2757 -0.0641
0.4294 -0.0132 -0.0532
What I want to do is find all values of the last column (:,3,:) that is less than 0, and then set the corresponding rows to NaN. In the above case, the results should be:
(:,:,1)
NaN NaN NaN
0.3212 -0.4570 0.1491
(:,:,2)
-0.3110 0.3165 0.1256
0.1868 -0.1315 0.2802
(:,:,3)
NaN NaN NaN
NaN NaN NaN
I can achieve it in the 2d case using the following code:
array = rand(5,3)-0.5
array(find(array(:,3)<0),:) = NaN
But I struggle with the 3d case.
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### Réponse acceptée

Guillaume le 14 Juin 2018
Note that in the 2D case you didn't need find (which only slows things done):
array(array(:, 3) < 0, :) = NaN;
For the ND case it's a bit more complicated since the result of the comparison is a matrix not a single dimension vector. One possibility:
array(repmat(array(:, 3, :) < 0, 1, size(array, 2), 1)) = NaN
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James Tursa le 14 Juin 2018
On earlier versions of MATLAB that trailing argument of repmat will not work. So just this:
array(repmat(array(:, 3, :) < 0, 1, size(array, 2))) = NaN
Oscar Frick le 15 Juin 2018
This works perfectly as well as being effective. Some short testing I did seems to indicate that the version without the trailing argument has an extremely slight time advantage when having "small" arrays (on the format (n,3,4), small being size seems to be about n<10000000). For larger arrays the version with the trailing one starts getting ahead, getting a more significant efficiency advantage as the arrays grow bigger.

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### Plus de réponses (1)

Mark Saad le 14 Juin 2018
You could try:
[I,J,K] = ind2sub(size(array), find(array(:,:,:) < 0));
ind = find(J == 3);
I = I(ind);
J = J(ind);
K = K(ind);
array(I,:,K) = NaN;
The first line gets the indices of every value that is less than 0. Lines 2-4 filter out any indices not in the third column. The last line sets the desired values to NaN.
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