How to vectorize a for-loop?

Hello!
I would appreaciate any help vectorizing the for loop below. The problem i cannot solve is how to take out the constants from wdrive and multiply it with the rest, according to the loop below. I want to become better at vectorizing my MATLAB code so I would really appreciate any help! Thanks alot!
%S and R are square matrices (404*404).
%fc is a column vector
wdrive=0:1:800;
a2=zeros(2*dofs,(length(wdrive)));
b2=zeros(2*dofs,(length(wdrive)));
Amp=zeros(1,length(wdrive));
SRS=S*(R\S);
SRfc=S*(R\fc);
for i=1:length(wdrive)
a2(:,i)=(wdrive(i)^2*SRS+R)\(fs-wdrive(i)*SRfc);
b2(:,i)=(R)\(fc+wdrive(i)*S*a2(:,i));
Amp(i)=sqrt(a2(dofs-1,i)^2+b2(dofs-1,i)^2);
end

2 Comments

What is "fs"?
Ops! Forgot to specify that. Fc is a column vector with the same size as Fs.

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 Accepted Answer

Matt J
Matt J on 18 May 2013
Edited: Matt J on 18 May 2013
I don't think you can vectorize everything, but you can cut down on the operations done inside the loop,
Rfc=R\fc;
SRS=S*(R\S);
SRfc=S*(Rfc);
rhs=bsxfun(@minus,fs,SRfc*wdrive);
for i=1:length(wdrive)
a2(:,i)=(wdrive(i)^2*SRS+R)\rhs(:,i);
end
b2=Rfc+R\S*bsxfun(@times, wdrive, a2);
Amp=abs(a2(dofs-1,:)+i*b2(dofs-1,:));

5 Comments

Tank you for answering! I will make sure to try it your way once I get home!
I have now tried and had to change just one little thing. This is what i ended up with, it's not too pretty but atleast it's faster now.
Rfc=R\fc;
SRS=S*(R\S);
SRfc=S*(Rfc);
rhs=bsxfun(@minus,fs,SRfc*wdrive);
for i=1:length(wdrive)
a2(:,i)=(wdrive(i)^2*SRS+R)\(rhs(:,i));
end
b2=R\(bsxfun(@plus,fc,(bsxfun(@times,wdrive,S*a2))));
Amp=abs(a2(dofs-1,:)+i*b2(dofs-1,:));
Samuel Hammarberg commented:
It would still be sweet if you, somehow, could get rid of the for loop altogether. So if some one could crack that, that would be great!
Thank you very much!
The for-loop isn't slowing you down significantly. You just have a lot of matrix inversions
(wdrive(i)^2*SRS+R)
to do. There's no simplification to this that I can see, unless there is some special structure in S and R that you haven't mentioned.
You could also try parfor, if you have the Parallel Computing Toolbox.

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More Answers (1)

Samuel Hammarberg
Samuel Hammarberg on 18 May 2013
Edited: Matt J on 19 May 2013
Relocated to Comment by Matt J

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