Question

I have an R code with a bunch of user-defined R functions. I'm trying to make the code run faster and of course the best option is to use Rcpp. My code involves functions that call each other. Therefore, If I write some functions in C++, I should be able to call and to run some of my R functions in my c++ code. In a simple example consider the code below in R:

mySum <- function(x, y){
 return(2*x + 3*y)
}
x <<- 1
y <<- 1

Now consider the C++ code in which I'm trying to access the function above:

#include <Rcpp.h>
using namespace Rcpp;

// [[Rcpp::export]]
int mySuminC(){
 Environment myEnv = Environment::global_env();
 Function mySum = myEnv["mySum"];
 int x = myEnv["x"];
 int y = myEnv["y"];
 return wrap(mySum(Rcpp::Named("x", x), Rcpp::Named("y", y)));
 }

When I source the file in R with the inline function sourceCpp(), I get the error:

 "invalid conversion from 'SEXPREC*' to int

Could anyone help me on debugging the code? Is my code efficient? Can it be summarized? Is there any better idea to use mySum function than what I did in my code?

Thanks very much for your help.

Était-ce utile?

La solution

You declare that the function should return an int, but use wrap which indicates the object returned should be a SEXP. Moreover, calling an R function from Rcpp (through Function) also returns a SEXP.

You want something like:

#include <Rcpp.h>
using namespace Rcpp;

// [[Rcpp::export]]
SEXP mySuminC(){
  Environment myEnv = Environment::global_env();
  Function mySum = myEnv["mySum"];
  int x = myEnv["x"];
  int y = myEnv["y"];
  return mySum(Rcpp::Named("x", x), Rcpp::Named("y", y));
}

(or, leave function return as int and use as<int> in place of wrap).

That said, this is kind of non-idiomatic Rcpp code. Remember that calling R functions from C++ is still going to be slow.

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