Maybe one of these will improve: >help.search('kronecker') ... spam::kronecker Kronecker Products on Sparse Matrices spam::spam.class Class "spam" base::kronecker Kronecker Products on Arrays Matrix::kronecker-methods Methods for Function 'kronecker()' in Package 'Matrix'
I doubt it because they will calculate the "full" Kronecker prod and it will be up to you to index the rows, but you never know... system.time(A[, rep(seq(ncol(A)), each = ncol(B))] * B[,rep(seq(ncol(B)),ncol(A))]) user system elapsed 0.016 0.000 0.019 > system.time(kronecker(A,B)[c(1,4),]) user system elapsed 0.008 0.000 0.008 > system.time(spam::kronecker(A,B)[c(1,4),]) user system elapsed 0.008 0.000 0.009 Cheers On Thu, Feb 9, 2012 at 9:38 AM, Ally <a.rushwo...@stats.gla.ac.uk> wrote: > > I'm trying to calculate the row-wise kronecker product A \Box B of two > sparse matrices A and B, and am struggling to find a quick way to do this > that takes advantage of sparseness. I thought a good idea would be to use > "rep" to construct 2 matrices of the same dimension of the end product, and > multiply these two together: > > library(Matrix) > A<-Matrix(c(1,0,0,0,0,1,2,0), 2, 4) > B<-Matrix(c(2,5,0,0,0,1,0,0,0,0), 2, 5) > > A[, rep(seq(ncol(A)), each = ncol(B))] * B[, rep(seq(ncol(B)),ncol(A))] > > This works, but for much larger problems is slow (compared to keeping A and > B dense). I was wondering why this happens, and whether there might be a > way around it? > > Thanks in advance for any advice, > > Alastair > > -- > View this message in context: > http://r.789695.n4.nabble.com/Row-wise-kronecker-product-with-Matrix-package-tp4373437p4373437.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > 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.