[R-pkg-devel] How to obtain intercept of intercept-only glm in Fortran?

[Ivan Krylov]

On Fri, 10 May 2019 16:17:42 +0000
"Wang, Zhu" <wangz1 using uthscsa.edu> wrote:

> Are there any examples or links for me to follow through more closely?

Calling R functions from C++ is described at
<http://dirk.eddelbuettel.com/code/rcpp/Rcpp-quickref.pdf> and
elsewhere in Rcpp documentation. An example follows:

--------------8<--------------glmfit.cpp--------------8<--------------
#include <algorithm>
#include <Rcpp.h>
using namespace Rcpp;

extern "C" double intercept_glm(size_t n, const double * response) {
	// access functions from default environment
	Function glm_fit("glm.fit"), coef("coef");

	// intercept-only model: response ~ 1
	NumericVector x(n);
	x.fill(1);

	// I couldn't find a way to wrap a double* into a NumericVector
	// without copying anything, sorry; perhaps someone else
	// can offer a solution
	NumericVector y(n);
	std::copy_n(response, n, y.begin());

	// call the R function, convert the result back
	return as<double>(coef(glm_fit(x, y)));
}
--------------8<--------------glmfit.cpp--------------8<--------------

Since this function is extern "C" and uses only primitive C types, it
should be fairly easy to call from Fortran. (C is the lingua franca of
programming languages). Fortran-C interoperability is well described in
"Modern Fortran Explained" by Metcalf et al. Here is the Fortran side
of the code:

--------------8<--------------callglm.f90--------------8<--------------
subroutine callglm(ret)
use, intrinsic :: iso_c_binding, only: c_size_t, c_double
! using iso_c_binding here
! - to get correct type of ret when R calls the function
! - to convert variables before calling C function
implicit none
! using F77-style arguments to match expectations of .Fortran()
real(c_double), intent(out) :: ret
! toy data to compare against R code later
real :: y(10) = [10, 11, 20, 9, 10, 8, 11, 45, 2, 3]
 ! the interface block declares an extern "C" function
 interface
  ! double intercept_glm(size_t n, const double * response)
  function intercept_glm(n, response) bind(c)
   use, intrinsic :: iso_c_binding
   real(c_double) :: intercept_glm
   integer(c_size_t), value :: n
   real(c_double) :: response(*)
  end function
 end interface

 ! call the function as you would call any other function
 ret = intercept_glm(int(size(y), c_size_t), real(y, c_double))
end subroutine
--------------8<--------------callglm.f90--------------8<--------------

For a quick test, make sure that you have Rcpp installed and run:

# adjust R version and path if your library is elsewhere
PKG_CPPFLAGS='-g -I ~/R/x86_64-pc-linux-gnu-library/3.3/Rcpp/include' \
	R CMD SHLIB callglm.f90 glmfit.cpp
R
library(Rcpp)
dyn.load('callglm.so') # change extension if needed
.Fortran('callglm', ret=numeric(1))
# $ret
# [1] 12.9
coef(glm.fit(rep(1, 10), c(10, 11, 20, 9, 10, 8, 11, 45, 2, 3)))
# [1] 12.9

To use this in a package, place both files in the src/ subdirectory of
your package and add LinkingTo: Rcpp in the DESCRIPTION.

-- 
Best regards,
Ivan