Hello,
On top of exposing C++ functions (see
http://permalink.gmane.org/gmane.comp.lang.r.rcpp/354), I've added some
code to expose c++ classes to the R level. This is also inspired from
boost.python (although much less comprehensive).
Consider this simple c++ class :
class World {
public:
World() : msg("hello"){}
void set(std::string msg) { this->msg = msg; }
std::string greet() { return msg; }
private:
std::string msg;
};
Using Rcpp modules, you can expose it to R, at the expense of this piece
of code:
RCPP_MODULE(yada){
using namespace Rcpp ;
class_<World>( "World" )
.method( "greet", &World::greet )
.method( "set", &World::set )
;
}
This creates an Rcpp module called "yada" that exposes the "World" class
to R. On the R side, you then grab the module and extract the class :
yada <- Rcpp:::Module( "yada", getDynLib( fx ) )
World <- yada$World
And then you can create instances of World using the new function in R:
w <- new( World )
And then call methods :
> w$greet()
[1] "hello"
> w$set( "hello world" )
> w$greet()
[1] "hello world"
This is probably the craziest c++ code I've ever written, but using it
is easy.
There are many things boost.python does and Rcpp modules does not.
- For now -- until I find a way -- new uses the default constructor.
Boost.Python allows other constructors to be exposed, but I'm not sure
how to achieve this.
- no polymorphism. methods are stored in a map, so if you give the same
name to two c++ functions, the second one will win.
- currently limited to member functions of the target class, e.g. see
the second argument: &World::greet, etc ... I am planning to add the
possibility (should be easy) to attach regular functions which take a
pointer to Foo or a reference to Foo.
- inputs and outputs still need to follow the rules of the last email.
output type can be void or whatever type that Rcpp::wrap is happy with.
input types can be void or whatever sequence of types (up to 65
arguments) Rcpp::as is happy with.
- currently no support for fields or properties.
The most obvious client to this will be the RProtoBuf package, it
already had quiet a diet when we introduced the RCPP_FUNCTION_, etc ..
macros, but with this the code is likely to get more simple and more robust.
Have fun.
Romain
--
Romain Francois
Professional R Enthusiast
+33(0) 6 28 91 30 30
http://romainfrancois.blog.free.fr
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