similar to: Converting sparse matrix to data.frame in Matrix package

>>>>> Henrik Bengtsson <henrik.bengtsson at gmail.com> >>>>> on Tue, 19 Apr 2016 14:04:11 -0700 writes: > Using the Matrix package, how can I create a row-oriented sparse > Matrix from scratch populated with some data? By default a > column-oriented one is created and I'm aware of the note that the > package is optimized for

Using the Matrix package, how can I create a row-oriented sparse Matrix from scratch populated with some data? By default a column-oriented one is created and I'm aware of the note that the package is optimized for column-oriented ones, but I'm only interested in using it for holding my sparse row-oriented data and doing basic subsetting by rows (even using drop=FALSE). Here is what I

Hello. I am trying to optimize a set of parameters using /optim/ in which the actual function to be minimized contains matrix multiplication and is of the form: SUM ((A%*%X - B)^2) where A is a matrix and X and B are vectors, with X as parameter vector. This has worked well so far. Recently, I was given a data set A of size 360440 x 1173, which could not be handled as a normal matrix. I

>>>>> C W <tmrsg11 at gmail.com> >>>>> on Fri, 20 Oct 2017 15:51:16 -0400 writes: > Thank you for your responses. I guess I don't feel > alone. I don't find the documentation go into any detail. > I also find it surprising that, >> object.size(train$data) > 1730904 bytes >>

> On Oct 21, 2017, at 7:50 AM, Martin Maechler <maechler at stat.math.ethz.ch> wrote: > >>>>>> C W <tmrsg11 at gmail.com> >>>>>> on Fri, 20 Oct 2017 15:51:16 -0400 writes: > >> Thank you for your responses. I guess I don't feel >> alone. I don't find the documentation go into any detail. > >> I also find

Hello, I am working with a sparse matrix that is approx. 13,900 by 14,100. My goal is to select a row out of the matrix and create a new matrix with that row repeated 13,900 times without having to do any looping. Example: Starting Matrix: exampleMatrix 3 x 4 sparse Matrix of class "dgCMatrix" [1,] 1 . . . [2,] . 1 . 0.5 [3,] . . 1 .. New Matrix:.. newExampleMatrix 3 x 4 sparse

Hi, I'm trying to create a new S4 class (myMatrix) which for now just extends dgCMatrix (from package Matrix). Then I want to use "[" which is defined in Matrix. Out of the box with "[" (defined in Matrix) I lose the class information and the result is an object of class dgCMatrix. If I specify a "["-method for myMatrix, it is not used because a signature

Hi,all! I encountered a problem "not-yet-implemented method for <list> %*% <dgCMatrix>" when I tried "diagr %*% design_mat", where "diagr<-diag(vr,100)", vr is a vector with 100 elements, and design_mat is a sparse matrix with dimension 100*677000 constructed by calling sparseMatrix(). I am new to the Matrix package, so I am confused with this, and I

Hi, I just tried to upgrade Nixpkgs to R 3.5.0, but unfortunately the new version fails its regression test suite. We configure the build using the flags "--without-recommended-packages", in case that's relevant. You can see a complete build log with all relevant information at [1]. Anyway, the test failures look like this: | make[3]: Entering directory

Thank you for your responses. I guess I don't feel alone. I don't find the documentation go into any detail. I also find it surprising that, > object.size(train$data) 1730904 bytes > object.size(as.matrix(train$data)) 6575016 bytes the dgCMatrix actually takes less memory, though it *looks* like the opposite. Cheers! On Fri, Oct 20, 2017 at 3:22 PM, David Winsemius

Hi Martin I got stung by this last week. glmnet produces a coefficient matrix of class ?dgCMatrix? If a predictor matrix was created using sparseMatrix as follows, one gets unexpected results, as this simple example shows. My fix was easy (I always convert the predictor matrix to class ?dgCMatrix? now) Trevor > y=Matrix(diag(4)) > y 4 x 4 diagonal matrix of class "ddiMatrix"

Hi all, I am wondering if this is a bug in the Matrix package or if it something that I am just getting wrong...here is an example: > m = matrix(0,4,4) > dimnames(m) = list(letters[1:4], letters[5:8]) > r = c("a","b","a","d") > m[r,2] = 1 > m e f g h a 0 1 0 0 b 0 1 0 0 c 0 0 0 0 d 0 1 0 0 > M = Matrix(0,4,4) > dimnames(M) =

I've been trying to get some linear classifiers (LiblineaR, kernlab, e1071) to work with a sparse matrix of feature data. In the case of LiblineaR and kernlab, it seems I have to coerce my data into a dense matrix in order to train a model. I've done a number of searches, read through the manuals and vignettes, but I can't seem to see how to use either of these packages with sparse

Hi, I have sparse (tridiagonal) matrices, and I use the Matrix package for handling them. For certain computations, I need to either set the first row to zero, or double the last row. I find that neither operation preserves sparsity, eg > m <- Diagonal(5) > m 5 x 5 diagonal matrix of class "ddiMatrix" [,1] [,2] [,3] [,4] [,5] [1,] 1 . . . . [2,] . 1

I want to create a sparse matrix of type "dgCMatrix" using the Matrix package (and the matrix must be of this type even if other more compact representations may exist). I do > library(Matrix) > m1<-Matrix(rep(1,4),nrow=2,ncol=2,sparse=T) > m1 2 x 2 sparse Matrix of class "dsCMatrix" [1,] 1 1 [2,] 1 1 To convert m1, I do > as(m1, "dgCMatrix")

Hi there, Is that change in R-devel intentional? library(Matrix) m <- as(matrix(c(0, 1)), "sparseMatrix") isS4(m) # [1] TRUE x <- I(m) # Warning message: # In `class<-`(x, unique.default(c("AsIs", oldClass(x)))) : # Setting class(x) to multiple strings ("AsIs", "dgCMatrix", ...); result will no longer be an S4 object

This is a Request For Comment, also BCCed to 390 package maintainers of reverse dependencies of the Matrix package. Most users and package authors working with our 'Matrix' package will be using it for numerical computations, and so will be using "dMatrix" (d : double precision) matrix objects M, and indirectly, e.g., for M >= c will also use "lMatrix" (l:

Hi: I was trying to use apply on a sparse matrix from package Matrix, and I get the error: Error in asMethod(object) : Cholmod error 'problem too large' at file ../Core/cholmod_dense.c, line 106 Is there a way to apply a function to all the rows without bumping into this problem? Here is a simplified example: > dim(sm) [1] 72913 43052 > class(sm) [1] "dgCMatrix"

Dear All, in some functions of my package, I use the Matrix S4 class, as defined in the Matrix package. I don't want to depend on Matrix, however, because my package is perfectly fine without Matrix, most of the functionality does not need Matrix. Matrix is so included in the 'Suggests' line. I load Matrix via require(), from the functions that really need it. This mostly works

> sessionInfo() R version 2.13.1 (2011-07-08) Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit) locale: [1] en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8 attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] Matrix_0.999375-50 lattice_0.19-30 loaded via a namespace (and not attached): [1] grid_2.13.1