Vectorize loop to speed up
2 visualizaciones (últimos 30 días)
Mostrar comentarios más antiguos
Hi,
This segment of code takes 13 seconds to run and as it runs hundreds of times it needs to be drastically speed optimized. Wonder if it can be done. Parallelizing the loop doesn't seem to help much.
Parameters are:
tau is a cell array of 384 each a matrix of 202 x 202 double elements.
FFT is a cell array of 384 each a vector of 5000 double elements.
omega is a vector of doubles of length 5000.
the outer loop 'flow' to 'fhigh' is 1:1:150
Converting cell arrays to arrays helps only slightly.
Thanks in advance.
P=zeros(size(tau{1}));
for k=flow:fhigh
F=zeros(size(tau{1}));
for j=1:nchan
F=F+FFT{j}(k)*exp(i*omega(k)*tau{j});
end
F=F.*conj(F);
P=P+F;
end
5 comentarios
Respuestas (2)
Matt J
el 16 de Mayo de 2022
Editada: Matt J
el 16 de Mayo de 2022
Fcell=cellfun(@(x)x(:),FFT,'uni',0);
Fmat=cell2mat(Fcell(:)');
Tau=cellfun(@(x)x(:)',tau,'uni',0);
Tmat=cell2mat(Tau(:));
P=0;
for k=flow:fhigh
F=abs( Fmat(k,:)*exp((1i*omega(k)).*Taumat) ).^2;
P=P+F;
end
P=reshape(P, size(tau{1}) );
2 comentarios
Matt J
el 16 de Mayo de 2022
Editada: Matt J
el 16 de Mayo de 2022
The operations look like IFFTs, though possibly you have irregular time and frequency sampling. Even so, you should possibly consider a compromise where you take the IFFT with pre- and post-interpolation to get the sampling that you need.
Ver también
Categorías
Más información sobre Logical en Help Center y File Exchange.
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!