how to vectorize nested for loops
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Hello everyone
I want to vectorize the following code to reduce operation time. Can you guys help me out?
thanks
% X is a double matrix
s=size(X);
RepSol=repmat(X,2,2);
% Y is a binary matrix
Y=repmat(Y,2,2);
% Preallocation
p=zeros(s);
for m=1:s(1)
for n=1:s(2)
for i=1:s(1)
for j=1:s(2)
if RepSol(i,j)==RepSol(m+i-1,n+j-1)
p(m,n)=p(m,n)+Y(i,j)*Y(m+i-1,n+j-1);
end
end
end
end
end
Respuestas (2)
darova
el 10 de Sept. de 2019
IS it correct?
for m=1:s(1)
for n=1:s(2)
cond = RepSol(1:s(1),1:s(2)) == RepSol((1:s(1))+m-1,(1:s(2))+n-1);
% cond = X - RepSol((1:s(1))+m-1,(1:s(2))+n-1);
P = Y(1:s(1),1:s(2)) .* Y((1:s(1))+m-1,(1:s(2))+n-1);
res = cond .* P;
p(m,n) = sum(res(:));
end
end
4 comentarios
Bob Thompson
el 10 de Sept. de 2019
cond = RepSol(1:s(1),1:s(2)) == RepSol((1:s(1))+m-1,(1:s(2))+n-1);
A couple of things:
RepSol(1:s(1),1:s(2))
This is just the entirety of RepSol, you shouldn't need to index it
RepSol((1:s(1))+m-1,(1:s(2))+n-1)
Your indexing here doesn't make sense. (1:s(1)) is just calling all rows, but then you're trying to adjust that range to +m-1. So, suppose you have ten rows, and you are looking at m = 5, then you are saying you want to look at rows 5:15, which isn't possible because you only have 10 rows.
Unfortunately, I don't have a way to solve your problem off the top of my head, but it might help us come up with a solution if you explain what you're trying to do with your loops. There might be a command which does it already.
darova
el 10 de Sept. de 2019
s(1) and s(2) are size of RepSol before repmat (two times less)
s=size(X);
RepSol=repmat(X,2,2);
AliHg
el 11 de Sept. de 2019
AliHg
el 17 de Sept. de 2019
0 votos
4 comentarios
darova
el 17 de Sept. de 2019
Can you tell something more about your problem? What are yuo working on now?
Maybe there is some solution
AliHg
el 17 de Sept. de 2019
darova
el 17 de Sept. de 2019
Unfortunately is explains nothing
The script does the follwoing if i understood correctly:
.png)
Rik
el 17 de Sept. de 2019
I agree with darova that your explanation is minimal. Please edit your question, adding what you're trying to achieve. Maybe your problem can be solved with a well-chosen convolution, but with the current level of detail it is impossible to give you a better solution than you already have been given.
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