**dirk.eddelbuettel**, and kindly contributed to R-bloggers)

The following R code defines a character
variable `gslrng`

. This variable contains a short C++ code
segment, which is then transformed by the function `cfunction`

into a function of two arguments assigned to `funx`

:

## now use Rcpp to pass down a parameter for the seed, and a vector size gslrng <- ' int seed = RcppSexp(s).asInt(); int len = RcppSexp(n).asInt(); gsl_rng *r; gsl_rng_env_setup(); std::vector<double> v(len); r = gsl_rng_alloc (gsl_rng_default); gsl_rng_set (r, (unsigned long) seed); for (int i=0; i<len; i++) { v[i] = gsl_rng_get (r); } gsl_rng_free(r); return RcppSexp(v).asSexp(); ' ## turn into a function that R can call ## compileargs redundant on Debian/Ubuntu as gsl headers are found anyway funx <- cfunction(signature(s="numeric", n="numeric"), gslrng, includes="#include <gsl/gsl_rng.h>", Rcpp=TRUE, cppargs="-I/usr/include", libargs="-lgsl -lgslcblas") print(funx(0, 5))

The `signature`

argument to `cfunction`

defines two
variables `s`

and `n`

-- which the C++ function then
reads in from R and converts to two integers `seed`

and `len`

. `seed`

is used to initialize the random-number generator, and `len`

draws are then taken and stored in the STL vector `v`

which returned at the end.

As the R level, we now have a function of two arguments returning a vector of RNG draws of the given lenth and using the given seed.

Also note how we tell `cfunction`

to add the GSL include line,
specify that we want to compile and link against Rcpp and provide `-I`

and `-L`

arguments to compile and link with the
GSL. (The include statement is not needed as the compiler would have found them
in `/usr/include`

anyway, but it shows how to set this if needed.)

Finally, we simply call our freshly compiled, linked and loaded C++ function with arguments zero for the seed and five for the length, and print the results vector returned to R from C++.

**leave a comment**for the author, please follow the link and comment on his blog:

**dirk.eddelbuettel**.

R-bloggers.com offers

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