RcppGSL 0.3.0

August 30, 2015

(This article was first published on Thinking inside the box , and kindly contributed to R-bloggers)

A new version of RcppGSL just arrived on CRAN. The RcppGSL package provides an interface from R to the GNU GSL using our Rcpp package.

Following on the heels of an update last month we updated the package (and its vignette) further. One of the key additions concern memory management: Given that our proxy classes around the GSL vector and matrix types are real C++ object, we can monitor their scope and automagically call free() on them rather then insisting on the user doing it. This renders code much simpler as illustrated below. Dan Dillon added const correctness over a series on pull request which allows us to write more standard (and simply nicer) function interfaces. Lastly, a few new typedef declaration further simply the use of the (most common) double and int vectors and matrices.

Maybe a code example will help. RcppGSL contains a full and complete example package illustrating how to write a package using the RcppGSL facilities. It contains an example of computing a column norm — which we blogged about before when announcing an much earlier version. In its full glory, it looks like this:


extern "C" SEXP colNorm(SEXP sM) {

  try {

        RcppGSL::matrix<double> M = sM;     // create gsl data structures from SEXP
        int k = M.ncol();
        Rcpp::NumericVector n(k);           // to store results

        for (int j = 0; j < k; j++) {
            RcppGSL::vector_view<double> colview = gsl_matrix_column (M, j);
            n[j] = gsl_blas_dnrm2(colview);
        M.free() ;
        return n;                           // return vector

  } catch( std::exception &ex ) {
        forward_exception_to_r( ex );

  } catch(...) {
        ::Rf_error( "c++ exception (unknown reason)" );
  return R_NilValue; // -Wall

We manually translate the SEXP coming from R, manually cover the try and catch exception handling, manually free the memory etc pp.

Well in the current version, the example is written as follows:


// [[Rcpp::export]]
Rcpp::NumericVector colNorm(const RcppGSL::Matrix & G) {
    int k = G.ncol();
    Rcpp::NumericVector n(k);           // to store results
    for (int j = 0; j < k; j++) {
        RcppGSL::VectorView colview = gsl_matrix_const_column (G, j);
        n[j] = gsl_blas_dnrm2(colview);
    return n;                           // return vector

This takes full advantage of Rcpp Attributes automagically creating the interface and exception handler (as per the previous release), adds a const & interface, does away with the tedious and error-pronce free() and uses the shorter-typedef forms for RcppGSL::Matrix and RcppGSL::VectorViews using double variables. Now the function is short and concise and hence easier to read and maintain. The package vignette has more details on using RcppGSL.

The NEWS file entries follows below:

Changes in version 0.3.0 (2015-08-30)

  • The RcppGSL matrix and vector class now keep track of object allocation and can therefore automatically free allocated object in the destructor. Explicit x.free() use is still supported.

  • The matrix and vector classes now support const reference semantics in the interfaces (thanks to PR #7 by Dan Dillon)

  • The matrix_view and vector_view classes are reorganized to better support const arguments (thanks to PR #8 and #9 by Dan Dillon)

  • Shorthand forms such as Rcpp::Matrix have been added for double and int vectors and matrices including views.

  • Examples such as fastLm can now be written in a much cleaner and shorter way as GSL objects can appear in the function signature and without requiring explicit .free() calls at the end.

  • The included examples, as well as the introductory vignette, have been updated accordingly.

Courtesy of CRANberries, a summary of changes to the most recent release is available.

More information is on the RcppGSL page. Questions, comments etc should go to the rcpp-devel mailing list off the R-Forge page.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.

To leave a comment for the author, please follow the link and comment on their blog: Thinking inside the box .

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.


Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)