Sparse Matrix Format with Data on Disk

Provide a sparse matrix format with data stored on disk, to be used in both R and C++. This is intended for more efficient use of sparse data in C++ and also when parallelizing, since data on disk does not need copying. Only a limited number of features will be implemented. For now, conversion can be performed from a 'dgCMatrix' or a 'dsCMatrix' from R package 'Matrix'. A new compact format is also now available.

bigsparser: sparse matrix format with data on disk

Features

For now, only a few features are implemented:

• convert a dgCMatrix or a dsCMatrix to an SFBM, a Sparse Filebacked Big Matrix

• grow an SFBM using $add_columns() (similar to 'cbind' or 'bdiag')

• compute the product and crossproduct of an SFBM with a vector

• solve Ax=b, where A is a symmetric SFBM and b is a vector

• access the subset of an SFBM as a dgCMatrix (matrix accessor, since v0.6.1)

A new compact format is available (since v0.5), which is useful when non-zero values in columns are contiguous (or almost).

Installation

# CRAN
install.packages("bigsparser")

# latest GitHub version
remotes::install_github("privefl/bigsparser")