Alternative to for/while cycle

Hi, I have a question. I'm working at my master thesis and I'm writing a code quite computationally heavy. I'd like to light it and a possible option should be the replacement of the for and while cycles with another option. Do you have idea about any possible replacement?

This is a portion of the code (consider that the table_percentage matrix is already pre-allocated):

for a = ceil((minimum/single_step)+1):(length(steps)-((number_surrogates-1)*(minimum/single_step)))
        for b = ceil((minimum/single_step)+1):(length(steps)-((number_surrogates-1)*(minimum/single_step)))
            for c = ceil((minimum/single_step)+1):(length(steps)-((number_surrogates-1)*(minimum/single_step)))
                for d = ceil((minimum/single_step)+1):(length(steps)-((number_surrogates-1)*(minimum/single_step)))
                    if steps(a)+steps(b)+steps(c)+steps(d)==1
                        table_percentage(index,:) = [steps(a), steps(b), steps(c), steps(d)];        
                        index = index+1;
                    end 
              end
         end
    end
end

Thank you very much for every help.

Luca

Answer 1

[Stephen23]

"a possible option should be the replacement of the for and while cycles with another option"

Why do you think that the loops themselves are the slow part? Have you profiled your code?

A quick look at your code shows that you could easily move the loop iteration vector definition before the loops, as it is indetical for all loops (currently you are pointlessly redefining exactly the same vector multiple times):

V = ceil((minimum/single_step)+1):(length(steps)-((number_surrogates-1)*(minimum/single_step)))
for a = V
    for b = V
        for c = V
            for d = V
                if steps(a)+steps(b)+steps(c)+steps(d)==1
                    table_percentage(index,:) = [steps(a), steps(b), steps(c), steps(d)];        
                    index = index+1;
                end
            end
        end
    end
end

Another option would be to avoid the loops entirely using ndgrid to generate the indices:

[A,B,C,D] = ndgrid(steps(V));
X = [A(:),B(:),C(:),D(:)];
table_percentage = X(sum(X,2)==1,:);

Note that this method will only work for V with a small number of elements, and you will need to adjust the indexing to suit steps and table_percentage (which you have told us nothing about).