Using GSL functions from R

Dirk Eddelbuettel — written Dec 22, 2012 — updated Nov 21, 2015 — source

The GNU GSL is a very popular–and versatile–library convering many, many scientific computing topics. It provides a standard C API. This API is somewhat restrictive for C++ programmer. However, RcppGSL makes it very easy to pass matrices and vectors in and out.

The following example, based on the code used in the complete (!!) example package included within RcppGSL, which itself in based on an example from the GSL documentation, illustrates this by computing simple vector norm given matrix.

As explained in the package documentation, the RcppGSL clue code instantiates C language pointers suitable for GSL (here the matrix M). In versions prior to RcppGSL 0.3.0, those had to be freed manually. Since release 0.3.0, an simple internal mechanism takes care of this automatically at the end of the score. This form is more common to C++, and now shown below. Other aspects of the the example are straighforward: take a matrix, create a return vector and compute the chosen norm for each column of the matrix.

This example is also shorter and simpler thanks to Rcpp Attributes. For illustration, several older approaches are still contained in the source file.

// [[Rcpp::depends(RcppGSL)]]

#include <RcppGSL.h>
#include <gsl/gsl_matrix.h>
#include <gsl/gsl_blas.h>

// [[Rcpp::export]]
Rcpp::NumericVector colNorm(const RcppGSL::Matrix & M) {

int k = M.ncol();
Rcpp::NumericVector n(k); // to store results

for (int j = 0; j < k; j++) {
RcppGSL::VectorView colview = gsl_matrix_const_column (M, j);
n[j] = gsl_blas_dnrm2(colview);

return n; // return vector

The example function computes a column norm, and returns a (standard) Rcpp vector of type NumericVector. On input, it takes a matrix from R which is already instantiated to a proxy object which maps between R GSL matrices (without making copies). Here RcppGSL::Matrix is a convenient typedef shorthand for RcppGSL::matrix<double>. All the standard GSL types are available via templating. However, double and int are the most sensible in out context as they correspond to R types. Lastly, also note that the GSL vector view types explicitly references a const column, this matches the const & declaration of the matrix M.

A quick illustration, based on Section 8.4.13 of the GSL manual (and thanks to R reduced to a one-liner for the data generation) follows.

## create M as a sum of two outer products
M <- outer(sin(0:9), rep(1,10), "*") + outer(rep(1, 10), cos(0:9), "*")
 [1] 4.31461 3.12050 2.19316 3.26114 2.53416 2.57281 4.20469 3.65202
 [9] 2.08524 3.07313
## same result using just R
apply(M, 2, function(x) sqrt(sum(x^2)))
 [1] 4.31461 3.12050 2.19316 3.26114 2.53416 2.57281 4.20469 3.65202
 [9] 2.08524 3.07313

tags: modeling  gsl 

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