bigsparser: Sparse Matrix Format with Data on Disk

Provides 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'.

Version: 0.4.0
Depends: R (≥ 3.1)
Imports: Rcpp, bigassertr, methods
LinkingTo: Rcpp, RcppEigen, rmio (≥ 0.2)
Suggests: Matrix, testthat (≥ 2.1.0)
Published: 2020-08-24
Author: Florian Privé [aut, cre]
Maintainer: Florian Privé <florian.prive.21 at gmail.com>
BugReports: https://github.com/privefl/bigsparser/issues
License: GPL-3
URL: https://github.com/privefl/bigsparser
NeedsCompilation: yes
Materials: README
CRAN checks: bigsparser results

Downloads:

Reference manual: bigsparser.pdf
Package source: bigsparser_0.4.0.tar.gz
Windows binaries: r-devel: bigsparser_0.4.0.zip, r-release: bigsparser_0.4.0.zip, r-oldrel: bigsparser_0.4.0.zip
macOS binaries: r-release: bigsparser_0.4.0.tgz, r-oldrel: bigsparser_0.4.0.tgz
Old sources: bigsparser archive

Reverse dependencies:

Reverse imports: bigsnpr
Reverse linking to: bigsnpr

Linking:

Please use the canonical form https://CRAN.R-project.org/package=bigsparser to link to this page.