Dirk Eddelbuettel — Dec 22, 2012 | source

The GNU GSL is very popularâ€“and versatileâ€“library convering many, many scientific computing topics. It provides a standard C API which is somewhat restrictive. However, RcppGSL makes it 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`

). Those *must* be freed manually, as shown before the `return`

statement. Otherwise the example is 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.

```
// [[Rcpp::depends(RcppGSL)]]
#include <RcppGSL.h>
#include <gsl/gsl_matrix.h>
#include <gsl/gsl_blas.h>
// [[Rcpp::export]]
Rcpp::NumericVector colNorm(Rcpp::NumericMatrix sM) {
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() ; // important: GSL wrappers use C structure
return n; // return vector
}
```

A quick illustration, based on Section 8.4.13 of the GSL manual (but 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), "*")
colNorm(M)
```

[1] 4.315 3.121 2.193 3.261 2.534 2.573 4.205 3.652 2.085 3.073

```
## same result using just R
apply(M, 2, function(x) sqrt(sum(x^2)))
```

[1] 4.315 3.121 2.193 3.261 2.534 2.573 4.205 3.652 2.085 3.073Tweet

- Stochastic SIR Epidemiological Compartment Model — Christian Gunning
- Call matplotlib from R — Matti Pastell
- Parsing Dates and Times — Dirk Eddelbuettel