sparseLRMatrix

sparseLRMatrix provides a single matrix S4 class called sparseLRMatrix which represents matrices that can be expressed as the sum of sparse matrix and a low rank matrix. We also provide an efficient SVD method for these matrices by wrapping the RSpectra SVD implementation.

Eventually, we will fully subclass Matrix::Matrix objects, but the current implementation is extremely minimal.

Installation

You can install the released version of sparseLRMatrix from CRAN with:

install.packages("sparseLRMatrix")

You can install the development version with:

# install.packages("remotes")remotes::install_github("RoheLab/sparseLRMatrix")

Usage

library(sparseLRMatrix)
#> Loading required package: Matrix
library(RSpectra)
set.seed(528491)
n<-50m<-40k<-3A<- rsparsematrix(n, m, 0.1)
U<- Matrix(rnorm(n*k), nrow=n, ncol=k)
V<- Matrix(rnorm(m*k), nrow=m, ncol=k)
# construct the matrix, which represents A + U %*% t(V)X<- sparseLRMatrix(sparse=A, U=U, V=V)
s<- svds(X, 5) # efficient

And a quick sanity check

Y<-A+ tcrossprod(U, V)
s2<- svds(Y, 5) # inefficient, but same calculation# singular values match up, you can check for yourself# that the singular vectors do as well!
all.equal(s$d, s2$d)
#> [1] TRUE