| title | author | license | tags | summary | layout | src |
|---|---|---|---|---|---|---|
Calling R Functions from C++ |
Dirk Eddelbuettel |
GPL (>= 2) |
basics function featured |
This post discusses calling R functions from C++ |
post |
2013-01-05-r-function-from-c++.cpp |
At its very essence, Rcpp permits easy access to native R objects at the C++ level. R objects can be
- simple vectors, list or matrices;
- compound data structures created from these;
- objects of S3, S4 or Reference Class vintage; or
- language objects as for example environments.
Accessing a function object is no different. And calling a function can be very useful. Maybe to pick up parameter initializations, maybe to access a custom data summary that would be tedious to recode, or maybe even calling a plotting routine. We already have examples for just about all of these use case in the Rcpp examples or unit tests shipping with the package.
So here were a just providing a simple example of calling a summary
function, namely the Tukey fivenum().
But before we proceed, a warning. Calling a function is simple and tempting. It is also slow as there are overheads involved. And calling it repeatedly from inside your C++ code, possibly buried within several loops, is outright silly. This has to be slower than equivalent C++ code, and even slower than just the R code (because of the marshalling of data). Do it when it makes sense, and not simply because it is available.
{% highlight r %} set.seed(42) x <- rnorm(1e5) fivenum(x) {% endhighlight %}
[1] -4.043276 -0.682384 -0.002066 0.673325 4.328091
Now via this C++ code:
{% highlight cpp %} #include <Rcpp.h>
using namespace Rcpp;
// [[Rcpp::export]] NumericVector callFunction(NumericVector x, Function f) { NumericVector res = f(x); return res; } {% endhighlight %}
And unsurprisingly, calling the same function on the same data gets the same result:
{% highlight r %} callFunction(x, fivenum) {% endhighlight %}
[1] -4.043276 -0.682384 -0.002066 0.673325 4.328091