Logical indexing two dimensions. How do I avoid a nested for loop?
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I have a matrix X with doubles of size = 450 8156 and another matrix C with logical values with size = 64 8156 where 400 of the 8156 elements of each of the 64 rows are true. And I also have yet another matrix T of logical values with size = 9 450 where 400 of the 450 elements of each row are true.
I want to extract all the true values of X so that the resulting matrix becomes of size = 400 400 9 64
I can do this easily with a double for loop like this:
for n = 1 : 64
for z = 1 : 9
A(:,:,z,n) = X(T(z,:)',C(n,:));
end
end
but it is very slow. Is there a faster, more reasonable, vectorized way of doing thing? By using repmat, reshape, bsxfun, arrayfun etc.? Anyone good with logical indexing that can help me out?
Thanks.
5 Commenti
Jos (10584)
il 15 Apr 2016
Did you pre-allocate A? Doing so, should make the for-loops pretty fast.
Peta
il 15 Apr 2016
Stephen23
il 15 Apr 2016
Your output array has 92160000 elements (92 million is nearly 1GB of double class) and it takes two seconds to process...
Generating intermediate variables is likely to take just as much time as the loops with a preallocated array, if not longer. Consider your time investment: are these loops really a bottleneck? Will the more complex code maintenance be worth it?
Peta
il 15 Apr 2016
Risposta accettata
Più risposte (2)
Azzi Abdelmalek
il 15 Apr 2016
You can improve your for loop by pre-allocating
A=zeros(400,400,9,64)
Jos (10584)
il 15 Apr 2016
Pre-allocate but also put the transpose out of the loop!
T = T.' ;
A = zeros(400,400,9,64)
for n = 1 : 64
for z = 1 : 9
A(:,:,z,n) = X(T(:,z), C(n,:));
end
end
Damn, this is fast :-)
2 Commenti
Peta
il 15 Apr 2016
Jos (10584)
il 17 Apr 2016
tens of thousands of times x 0.1s per time (which is fast) = thousands of seconds = a few hours. Maybe Matlab is not the right tool for the job?
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