Le 13/11/2019 à 09:31, LEVRA-JUILLET William a écrit :
Thx Sergei,

Yes you're right, I want to use my c++ function as a R function.
Sorry about the Banana function that takes 2 scalars, you’re right again, it 
should take a vector as input.
Please ignore this for now (this is a dummy example)

My c++ "Banana" function is already compiled in my project by the time I start 
he R session (via RInside).
I can pass it to R via a XPtr.
Something like R["myfuncptr"] = Rcpp::XPtr<func_type>(new func_type (Banana));
So, in R I got "myfuncptr" which is an "externalptr".

Now my only problem is to make that "externalptr" seen as a R function in R.
Maybe with something like a ".Call(externalptr, param...)"?
Here (https://stackoverflow.com/questions/13904786/r-pointer-to-c-function), 
Romains says something about wrapping the external pointer into an R function...
But I struggle to find the correct way to achieve this with the function 
parameters...
Well, I won't help you in this fight against XPtrs but I have made my own hack without them and it works on my Linux. May be it will inspire you to smth useful.

8<------file optim2.cpp
#include <RInside.h>
using namespace Rcpp;

double Banana(double x, double y) {return (1-x)*(1-x)+100*(y-x*x)*(y-x*x);};
RcppExport SEXP wrap_banana(SEXP xSEXP, SEXP ySEXP) {
BEGIN_RCPP
    Rcpp::RObject rcpp_result_gen;
    Rcpp::traits::input_parameter< double >::type x(xSEXP);
    Rcpp::traits::input_parameter< double >::type y(ySEXP);
    rcpp_result_gen = Rcpp::wrap(Banana(x, y));
    return rcpp_result_gen;
END_RCPP
}

int main(int argc, char *argv[]) {
   RInside R(argc, argv);
R.parseEval("dyn.load('optim2.so'); fn <- function(v) invisible(.Call('wrap_banana', v[1L], v[2L]))");
   Rcpp::RObject res = R.parseEval("optim(c(-2,-2), fn)");
   Rf_PrintValue(res);
   return 0;
}
8<------end of file optim2.cpp

In classical makefile I had to modify implicit rules to produce and use an intermidiate .so library (which is loaded in R session):
%.so:   %.cpp
        $(CXX) $(CPPFLAGS) $(CXXFLAGS) $(RINSIDELIBS) -fPIC -shared $< -o $@
%:      %.so
        $(CXX) $^ $(LDLIBS) -o $@

Best,
Serguei.


Thank you
William




-----Message d'origine-----
De : Serguei Sokol <serguei.so...@gmail.com>
Envoyé : mardi 12 novembre 2019 17:49
À : LEVRA-JUILLET William <william.levra-juil...@addactis.com>; 
rcpp-devel@lists.r-forge.r-project.org
Objet : Re: [Rcpp-devel] RInside: C/C++ function(s) passed to R?

Le 08/11/2019 à 11:06, LEVRA-JUILLET William a écrit :
Hi all,

I’m evaluating RInside/Rcpp to interact our C++ project with R.

I’ve seen the samples to get/set data (matrix, dataframes, etc)
to/from R and it builds/works fine.

(Using gcc/mingw compiler from RTools on Windows)

My questions is about functions…

My project is C++, and it uses RInside to call R from our code.

Let’s say I have a C++ function implemented in my project, and I want
to pass that c++ function to R so it can be “used” as a R function
(typically passed as argument to optim/optimize)

I couldn’t find a way to do that using RInside.

Ideally, I’d like to achieve something like:

#include <RInside.h>

double Banana(double x, double y)

{

return (1-x)*(1-x)+100*(y-x*x)*(y-x*x);

}

Int main()

{

RInside R(argc,, argv);

R[“fn”] = Banana;

R.parseEval(“optim(c(-2,-2), fn”);

}

I believe it’s similar to
https://stackoverflow.com/questions/53729493/rinside-wrapping-a-c-func
tion-for-use-in-an-r-function

But I can’t really understand the Rcpp::XPtr suggestion from Dirk.

Any help or pointers welcome J
Sorry for a late comment but for what it's worth, XPtr won't help here as 
optim() expects an R function, not C++ pointer to a function.
Moreover, this R function takes only one argument -- a vector, not a couple of 
scalars. So maybe you meant something similar to:
#include <RInside.h>
int main(int argc, char *argv[]) {
     RInside R(argc, argv);
     R.parseEval("Rcpp::cppFunction('double Banana(double x, double y) {return 
(1-x)*(1-x)+100*(y-x*x)*(y-x*x);};', cacheDir='lib')");
     R.parseEval("fn <- function(p, ...) Banana(p[1L], p[2L])");
     Rcpp::RObject res = R.parseEval("optim(c(-2,-2), fn)");
     Rf_PrintValue(res);
     return 0;
}

which prints:

$par
[1] 0.9990277 0.9977136

$value
[1] 1.269722e-05

$counts
function gradient
       157       NA

$convergence
[1] 0

$message
NULL

As already underlined by others this is a sub-optimal way to use C++ functions in R but 
here it is imposed by optim() interface. For better designed interfaces (at least from 
"optimality of R/C++ exchanges" point of view) refer to examples cited by Dirk 
and Inaki.

Best,
Serguei.


Thx a mil

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*   William **LEVRA-JUILLET*
     Senior Software Architect
*   ADDACTIS Software*
     +33 (0)4 81 92 13 00


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