Using Processing and R together (in OS X)

[This article was first published on Quantum Forest » rblogs, 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.

I wanted to develop a small experiment with a front end using the Processing language and the backend calculations in R; the reason why will be another post. This post explained the steps assuming that one already has R and Processing installed:

  1. Install the Rserve package. This has to be done from source (e.g. using R CMD INSTALL packagename).
  2. Download Rserve jar files and include them in the Processing sketch.
  3. Run your code

For example, this generates 100 normal distributed random numbers in R and then sorts them (code copy and pasted from second link):

import org.rosuda.REngine.Rserve.*;
import org.rosuda.REngine.*;
double[] data;
void setup() {
  try {
    RConnection c = new RConnection();  
    // generate 100 normal distributed random numbers and then sort them 
    data= c.eval("sort(rnorm(100))").asDoubles();
  } catch ( REXPMismatchException rme ) {
  } catch ( REngineException ree ) {
void draw() {
  for( int i = 0; i < data.length; i++) {
    line( i * 3.0, height/2, i* 3.0, height/2 - (float)data[i] * 50 );

The problem is that this didn’t work, because my OS X (I use macs) R installation didn’t have shared libraries. My not-so-quick solution was to compile R from source, which involved:

  1. Downloading R source. I went for the latest stable version, but I could have gone for the development one.
  2. Setting up the latest version of C and Fortran compilers. I did have an outdated version of Xcode in my macbook air, but decided to delete it because i- uses many GB of room in a small drive and ii- it’s a monster download. Instead I went for the Apple Command Line Tools, which is a small fraction of size and do the job.
  3. In the case of gfortran, there are many sites pointing to this page that hosts a fairly outdated version, which was giving me all sorts of problems (e.g. “checking for Fortran 77 name-mangling scheme”) because the versions between the C and Fortran compilers were out of whack. Instead, I downloaded the latest version from the GNU site.
  4. Changing the file in a few places, ensuring that I had:
  5. CC="gcc -arch x86_64 -std=gnu99"
    CXX="g++ -arch x86_64"
    F77="gfortran -arch x86_64"
    FC="gfortran -arch x86_64"

Then compiled using (didn’t want X11 and enabling shared library):

./configure --without-x --enable-R-shlib
make check
make pdf # This produces a lot of rubbish on screen and it isn't really needed
make info

And finally installed using:

make prefix=/luis/compiled install

This used a prefix because I didn’t want to replace my fully functioning R installation, but just having another one with shared libraries. If one types R in terminal then it is still calling the old version; the new one is called via /luis/compiled/R.framework/Versions/Current/Resources/bin/R. I then installed Rserve in the new version and was able to call R from processing so I could obtain.

A 'hello world' of the calling R from Processing world.

A ‘hello world’ of the calling R from Processing world.

Now I can move to what I really wanted to do. File under stuff that I may need to remember one day.

To leave a comment for the author, please follow the link and comment on their blog: Quantum Forest » rblogs. 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)