Yes, sorry, so the distance is colSums((t(x)-y)**2)
(I knew that) :S Tsjerk On Wed, Aug 24, 2011 at 9:19 AM, Enrico Schumann <enricoschum...@yahoo.de> wrote: > R will subtract the vector columnwise from the matrix (so the vectors need > be the columns). > > x <- matrix(0, nrow = 10L, ncol = 5L) > y <- 1:5 > x - y > > [,1] [,2] [,3] [,4] [,5] > [1,] -1 -1 -1 -1 -1 > [2,] -2 -2 -2 -2 -2 > [3,] -3 -3 -3 -3 -3 > [4,] -4 -4 -4 -4 -4 > [5,] -5 -5 -5 -5 -5 > [6,] -1 -1 -1 -1 -1 > [7,] -2 -2 -2 -2 -2 > [8,] -3 -3 -3 -3 -3 > [9,] -4 -4 -4 -4 -4 > [10,] -5 -5 -5 -5 -5 > > > > >> -----Ursprüngliche Nachricht----- >> Von: Tsjerk Wassenaar [mailto:tsje...@gmail.com] >> Gesendet: Mittwoch, 24. August 2011 09:02 >> An: Enrico Schumann >> Cc: Wei Wu; r-help@r-project.org >> Betreff: Re: [R] Efficient way to Calculate the squared >> distances for a set ofvectors to a fixed vector >> >> Hi Wei Wu, >> >> What about: >> >> x <- matrix(rnorm(20000*5),ncol=5) >> y <- rnorm(5) >> distances <- rowSums((x-y)**2) >> >> Cheers, >> >> Tsjerk >> >> On Wed, Aug 24, 2011 at 8:43 AM, Enrico Schumann >> <enricoschum...@yahoo.de> wrote: >> > >> > You could do something like this: >> > >> > # data >> > nrows <- 20000L >> > ncols <- 5L >> > myVec <- array(rnorm(nrows * ncols), dim = c(nrows, ncols)) y <- >> > rnorm(ncols) >> > >> > temp <- t(myVec) - y >> > result <- colSums(temp * temp) >> > >> > # check >> > all.equal(as.numeric(crossprod(myVec[1L, ] - y)), result[1L]) #... >> > >> > (And don't use a data.frame, but a matrix.) >> > >> > regards, >> > Enrico >> >> -----Ursprüngliche Nachricht----- >> >> Von: r-help-boun...@r-project.org >> >> [mailto:r-help-boun...@r-project.org] Im Auftrag von Wei Wu >> >> Gesendet: Mittwoch, 24. August 2011 07:18 >> >> An: r-help@r-project.org >> >> Betreff: [R] Efficient way to Calculate the squared >> distances for a >> >> set ofvectors to a fixed vector >> >> >> >> I am pretty new to R. So this may be an easy question for >> most of you. >> >> >> >> I would like to calculate the squared distances of a large >> set (let's >> >> say 20000) of vectors (let's say dimension of 5) to a fixed vector. >> >> >> >> Say I have a data frame MY_VECTORS with 20000 rows and 5 >> columns, and >> >> one 5x1 vector y. I would like to efficiently calculate >> the squared >> >> distances between each of the 20000 vectors in MY_VECTORS and y. >> >> >> >> The squared distance between two vectors x and y can be calculated: >> >> distance <- crossprod(x-y) >> >> >> >> Without looping, what is the efficient code to achieve this? >> >> >> >> Thanks. >> >> >> >> ______________________________________________ >> >> 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. >> > >> > ______________________________________________ >> > 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. >> > >> >> >> >> -- >> Tsjerk A. Wassenaar, Ph.D. >> >> post-doctoral researcher >> Molecular Dynamics Group >> * Groningen Institute for Biomolecular Research and Biotechnology >> * Zernike Institute for Advanced Materials University of >> Groningen The Netherlands > > -- Tsjerk A. Wassenaar, Ph.D. post-doctoral researcher Molecular Dynamics Group * Groningen Institute for Biomolecular Research and Biotechnology * Zernike Institute for Advanced Materials University of Groningen The Netherlands ______________________________________________ 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.