'Rcpp' Integration for 'GNU GSL' Vectors and Matrices

'Rcpp' integration for 'GNU GSL' vectors and matrices The 'GNU Scientific Library' (or 'GSL') is a collection of numerical routines for scientific computing. It is particularly useful for C and C++ programs as it provides a standard C interface to a wide range of mathematical routines. There are over 1000 functions in total with an extensive test suite. The 'RcppGSL' package provides an easy-to-use interface between 'GSL' data structures and R using concepts from 'Rcpp' which is itself a package that eases the interfaces between R and C++. This package also serves as a prime example of how to build a package that uses 'Rcpp' to connect to another third-party library. The 'autoconf' script, 'inline' plugin and example package can all be used as a stanza to write a similar package against another library.


This package uses Rcpp to connect the R system to the GNU GSL, a collection of numerical routines for scientific computing, particularly its vector and matrix classes.

The fastLm() function included as file src/fastLm.cpp in the package:

#include <RcppGSL.h>
 
#include <gsl/gsl_multifit.h>
#include <cmath>
 
// [[Rcpp::export]]
Rcpp::List fastLm(const RcppGSL::Matrix &X, const RcppGSL::Vector &y) {
 
    int n = X.nrow(), k = X.ncol();
    double chisq;
 
    RcppGSL::Vector coef(k);                // to hold the coefficient vector 
    RcppGSL::Matrix cov(k,k);               // and the covariance matrix
    
    // the actual fit requires working memory we allocate and free
    gsl_multifit_linear_workspace *work = gsl_multifit_linear_alloc (n, k);
    gsl_multifit_linear (X, y, coef, cov, &chisq, work);
    gsl_multifit_linear_free (work);
 
    // assign diagonal to a vector, then take square roots to get std.error
    Rcpp::NumericVector std_err;
    std_err = gsl_matrix_diagonal(cov);     // need two step decl. and assignment
    std_err = Rcpp::sqrt(std_err);          // sqrt() is an Rcpp sugar function
 
    return Rcpp::List::create(Rcpp::Named("coefficients") = coef, 
                              Rcpp::Named("stderr")       = std_err,
                              Rcpp::Named("df.residual")  = n - k);
    
}
 

This example comes from the complete example package included in RcppGSL and is from the file inst/examples/RcppGSLExample/src/colNorm.cpp

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

On CRAN, here and on its package page.

Dirk Eddelbuettel and Romain Francois

GPL (>= 2)

News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("RcppGSL")

0.3.3 by Dirk Eddelbuettel, 2 months ago


Browse source code at https://github.com/cran/RcppGSL


Authors: Dirk Eddelbuettel and Romain Francois


Documentation:   PDF Manual  


GPL (>= 2) license


Imports Rcpp, stats

Suggests RUnit, inline, knitr, rmarkdown, pinp

Linking to Rcpp

System requirements: GNU GSL


Imported by RGraphM.

Linked to by RcppZiggurat, catSurv, coga, flan, matdist, mixlink, mvabund.


See at CRAN