pick elements from a 3d array, based on an indexing matrix

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Bernhard
Bernhard el 26 de En. de 2021
Comentada: Stephen23 el 27 de En. de 2021
I have a 3d array A with nr rows, nc columns, and np pages, and an nr x nc indexing matrix I with integer elements between 1 and np. I want to create a matrix B with elements picked from A, where for each position (r,c) the element is picked from the page of A given by the value of I at that position.
A straightforward way to do this would be the double loop:
B = zeros(nr,nc);
for r = 1:nr
for c = 1:nc
p = I(r,c);
B(r,c) = A(r,c,p);
end
end
Is there a way to accelerate this by vectorization for large arrays?

Respuesta aceptada

Stephen23
Stephen23 el 26 de En. de 2021
Editada: Stephen23 el 26 de En. de 2021
% fake data:
nr = 5;
nc = 7;
np = 3;
A = randi(9,nr,nc,np);
I = randi(np,nr,nc)
I = 5×7
1 1 2 1 2 2 3 1 3 3 2 3 3 1 1 2 3 2 3 1 1 2 2 2 1 3 2 2 1 1 2 3 3 1 1
% your looped approach:
B = zeros(nr,nc);
for r = 1:nr
for c = 1:nc
p = I(r,c);
B(r,c) = A(r,c,p);
end
end
B
B = 5×7
7 1 6 2 3 7 6 6 4 3 1 5 5 4 4 1 3 2 2 2 6 4 3 8 2 1 7 9 9 9 6 2 5 1 6
% SUB2IND approach:
[xr,xc] = ndgrid(1:nr,1:nc);
X = sub2ind(size(A),xr,xc,I);
C = A(X)
C = 5×7
7 1 6 2 3 7 6 6 4 3 1 5 5 4 4 1 3 2 2 2 6 4 3 8 2 1 7 9 9 9 6 2 5 1 6
  2 comentarios
Bernhard
Bernhard el 26 de En. de 2021
Thank you, Stephen, that is a nice gimmick. It took about 60% of the time needed for the looped approach.
Bernhard
Stephen23
Stephen23 el 27 de En. de 2021
@Bernhard: if the speed of this operation is very critical to your algorithm, then take a look inside the sub2ind file. The sub2ind function is generic, for any number of dimensions, but with a little effort you can write your own version that is hardcoded for the number of dimensions of your data and that does not require ndgrid beforehand. Whether it is worth the effort depends on your situation.

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