Using Rcout for output synchronised with R

[This article was first published on Rcpp Gallery, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

The Writing R Extensions manual, which provides the gold standard of documentation as far as extending R goes, suggests to use Rprintf and REprintf for output (from C/C++ code) as these are matched to the usual output and error streams maintained by R itself.

Also, use of std::cout and std::cerr (as common in standard C++ code) is flagged when running R CMD check and no longer permitted when uploading to CRAN.

Thanks to an initial patch by Jelmer Ypma, which has since been reworked and extended, we have devices Rcout (for standard output) and Rcerr (for standard error) which intercept output and redirect it to R.

To illustrate, we create a simple function which prints a value:

#include <RcppArmadillo.h>   // as we use RcppArmadillo below
                             // this first example use only Rcpp 

using namespace Rcpp;

// [[Rcpp::export]]
void showValue(double x) {
    Rcout << "The value is " << x << std::endl;
}

We can use this from R, and output will be properly synchronised:

cat("Before\n")


Before

showValue(1.23)


The value is 1.23

cat("After\n")


After

As of the 0.10.* releases, Rcpp itself still lacks the converter code to print simple non-scalar data structures—but RcppArmadillo can do so as Conrad permitted a hool for us to supply the Rcout device as the default device

#include <RcppArmadillo.h>

// [[Rcpp::depends(RcppArmadillo)]]

// [[Rcpp::export]]
void showMatrix(arma::mat X) {
    Rcout << "Armadillo matrix is" << std::endl << X << std::endl;
}

M <- matrix(1:9,3,3)
print(M)


     [,1] [,2] [,3]
[1,]    1    4    7
[2,]    2    5    8
[3,]    3    6    9

showMatrix(M)


Armadillo matrix is
   1.0000   4.0000   7.0000
   2.0000   5.0000   8.0000
   3.0000   6.0000   9.0000

Having output from R and C++ mix effortlessly is a very useful feature. We hope to over time add more features to output more of Rcpp basic objects. Patches are of course always welcome.

To leave a comment for the author, please follow the link and comment on their blog: Rcpp Gallery.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)