Douglas Bates <ba...@stat.wisc.edu> writes: > On Tue, Dec 20, 2011 at 8:20 AM, Jean V Adams <jvad...@usgs.gov> wrote: > > Hi Jean, > >> khai wrote on 12/19/2011 11:26:55 PM: >> >>> Hi, >>> >>> I'm very new to working with sparse matrices and would like to know how >> I >>> can column permute a sparse matrix. Here is a small example: >>> >>> > M1 <- >>> > spMatrix(nrow=5,ncol=6,i=sample(5,15,replace=TRUE),j=sample(6, >>> 15,replace=TRUE),x=round_any(rnorm(15,2),0.001)) >>> > M1 >>> 5 x 6 sparse Matrix of class "dgTMatrix" >>> >>> [1,] 2.983 . 1.656 5.003 . . >>> [2,] . . 2.990 . . . >>> [3,] . 0.592 5.349 1.115 . . >>> [4,] 1.836 . 2.804 . . . >>> [5,] . 6.961 . . . 1.077 >>> >>> I know I can permute entire columns this way >>> >>> > M1[,sample(6,6)] >>> 5 x 6 sparse Matrix of class "dgTMatrix" >>> >>> [1,] 5.003 . . . 1.656 2.983 >>> [2,] . . . . 2.990 . >>> [3,] 1.115 0.592 . . 5.349 . >>> [4,] . . . . 2.804 1.836 >>> [5,] . 6.961 1.077 . . . >>> >>> But I would like the new sparse matrix to look like this...where only >> the >>> nonzero elements are permuted. >>> >>> [1,] 1.656 . 5.003 2.983 . . >>> [2,] . . 2.990 . . . >>> [3,] . 5.349 1.115 0.592 . . >>> [4,] 2.804 . 1.836 . . . >>> [5,] . 1.077 . . . 6.961 >>> >>> Thanks in advance for any advice! > > A peculiar request but you can do that by permuting the 'x' slot in > your original matrix. > >> set.seed(1) >> (M1 <- spMatrix(nrow=5,ncol=6,i=sample(5,15,replace=TRUE),j=sample(6, >> 15,replace=TRUE),x=round(rnorm(15,2),3))) > 5 x 6 sparse Matrix of class "dgTMatrix" > > [1,] . . 2.738 . 3.595 . > [2,] . . . . . . > [3,] 3.879 . 4.289 -0.215 1.374 . > [4,] . 4.966 1.180 1.379 . 2.487 > [5,] 3.512 . . . 2.330 . >> (nnz <- nnzero(M1)) > [1] 15 >> M2 <- M1 >> M2@x <- M2@x[sample(nnz, nnz)] >> M2 > 5 x 6 sparse Matrix of class "dgTMatrix" > > [1,] . . 2.487 . 3.595 . > [2,] . . . . . . > [3,] 3.709 . 2.875 3.512 -0.215 . > [4,] . 3.764 1.164 2.576 . 3.125 > [5,] 2.184 . . . 2.738 . >
I do not think this is what was wanted. M1 and M2 are matrices with 12 non-zero elements, not 15 as nnzero() reports. The dgTMatrix representation effectively treats the slots of M1 like this: res <- tapply(M1@x, list(M1@i,M1@j), sum) res[is.na(res)] <- 0 res So permuting 'x' will return a different dgTMatrix with the same number of non-zero elements in place of the existing non-zero elements, but not necessarily having the same values when the (i,j) pairs are not unique. (e.g. 3.709 is seen in M2, but not M1) I think the OP was asking for permutations of the non-zero values in 'res', rather than permutations of M1@x. HTH, Chuck >> >> I don't have experience with sparse matrices, but I was able to get this >> to work by converting the sparse matrix to a "base" matrix and back again. >> >> >> library(Matrix) >> >> nonzero.cols <- !apply(M1==0, 2, all) >> M2 <- as.matrix(M1) >> reord <- sample(seq(dim(M1)[2])[nonzero.cols]) >> M2[, nonzero.cols] <- as.matrix(M1[, reord]) >> Matrix(M2, sparse=TRUE) > > This solution has the disadvantage of converting the sparse matrix to > a dense matrix, which may end up producing a much larger object. > -- Charles C. Berry Dept of Family/Preventive Medicine cberry at ucsd edu UC San Diego http://famprevmed.ucsd.edu/faculty/cberry/ La Jolla, San Diego 92093-0901 ______________________________________________ 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.
