I'm not quite sure of what you mean by not worry if it's 1d R matrices. X1 and X2 are both n by d matrices and W is d by d.
Thanks for the help though. Any other ideas? Thanks Sachin On Friday, November 18, 2011, R. Michael Weylandt < michael.weyla...@gmail.com> wrote: > The fastest is probably to just implement the matrix calculation > directly in R with the %*% operator. > > (X1-X2) %*% W %*% (X1-X2) > > You don't need to worry about the transposing if you are passing R > vectors X1,X2. If they are 1-d matrices, you might need to. > > Michael > > On Thu, Nov 17, 2011 at 1:30 AM, Sachinthaka Abeywardana > <sachin.abeyward...@gmail.com> wrote: >> Hi All, >> >> I am trying to convert the following piece of matlab code to R: >> >> XX1 = sum(w(:,ones(1,N1)).*X1.*X1,1); #square the elements of X1, >> weight it and repeat this vector N1 times >> XX2 = sum(w(:,ones(1,N2)).*X2.*X2,1); #square the elements of X2, >> weigh and repeat this vector N2 times >> X1X2 = (w(:,ones(1,N1)).*X1)'*X2; #get the weighted >> 'covariance' term >> XX1T = XX1'; #transpose >> z = XX1T(:,ones(1,N2)) + XX2(ones(1,N1),:) - 2*X1X2; #get the >> squared weighted distance >> >> which is basically doing: z=(X1-X2)' W (X1-X2) >> >> What would the best way (for SPEED) to do this? or is vectorizing as above >> the best? Any hints, suggestions? >> >> Thanks, >> Sachin >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
