R Compiler Tools for Rcpp on macOS

r, rcpp, compilers, os x

Editor’s Note: This is an updated post that covers how to install the macOS toolchain for versions of R starting at 4.y.z.

For R versions between R:

Intro

The objective behind this post is to provide users with information on how to setup the macOS toolchain for compiling used in the 4.y.z series of R. The post is structured primarily for macOS Catalina (10.15.z) users.

Removing Old Installation Files

If you previously used either the clang4, clang6, clang7, clang8, or the macos-rtools installer, please consider deleting the old components that were installed.

Instructions for uninstallation can be found here:

Uninstalling the R development toolchain on macOS

That said, please remove both ~/.R/Makevars and ~/.Renviron files prior to continuing as they were set in a prior iteration. You can achieve this by using:

unlink("~/.R/Makevars")
unlink("~/.Renviron")

Alternatively, if there is contents inside of the ~/.Renviron file that must be retained, please look for where the PATH variable is listed and remove any part with clang.

Open the file in R using:

file.edit("~/.Renviron")

Next, find and remove:

PATH="/usr/local/clang7/bin:${PATH}"

Then, save and close the file. You may need to restart R for the changes to take effect.

Installation Instructions

One of the primary ways to setup the R toolchain for compiled code on macOS is to individually installing each element yourself.

There are two components to the R 4.y.z toolchain based on Section: C.3 macOS of R Installation and Administration. These components are:

  1. Xcode Command Line Tools (“Xcode CLI”)
  2. gfortran
    • gfortran 6.3: Sierra (10.12) and High Sierra (10.13)
    • gfortran 8.2: Mojave (10.14) and Catalina (10.15)

The gfortran component is dependent on the version of macOS being used.

For historical information about the toolchain, please see: R macOS toolchain evolution

Install Guide

This guide provides a step-by-step breakdown of the actions required to setup the toolchain. As a result, this guide will use both installers and script commands ia Terminal.app found in /Applications/Utilities/. Terminal is macOS’ equivalent to Linux’s shell and Window’s command line. From Terminal, we will install only the XCode Command Line Tools (“Xcode CLI”). These provide the system headers used to build the official CRAN binary for R.

XCode Command Line Tools

  1. Open the Terminal from /Applications/Utilities/
  2. Type the following into Terminal
    • Note: Anytime the Xcode CLI toolchain updates, you must re-run this command.
xcode-select --install
  1. Press “Install”
  2. Verify installation by typing into terminal:
gcc --version

Install OS-specific gfortran binary

Determine the version of macOS the computer is being run on.

  1. Click the Apple menu  in the corner of your screen
  2. Choose “About This Mac”
  3. Look for Version 10.1* or the name of the operating system.

For additional help in determining this, please see Apple’s support page on Find out which macOS your Mac is using.

Then, download and install the appropriate gfortran binary from the https://github.com/fxcoudert/gfortran-for-macOS

Both of the installers will place the gfortran binary into /usr/local/gfortran. This will be picked up by the default implicit variable set by R during compilation.

Quick check

To verify that everything is working appropriately, let’s do a quick C++ program using Rcpp and Armadillo.

First, let’s install Rcpp and RcppArmadillo within R.

install.packages(c('Rcpp', 'RcppArmadillo'))

Create a new file, name the follow: helloworld.cpp

By adding the .cpp extension, the file is viewed as being C++ code.

Within the file write:

#include <RcppArmadillo.h>   

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

// [[Rcpp::export]]
void hello_world() {
  Rcpp::Rcout << "Hello World!" << std::endl;  
}

// After compile, this function will be immediately called using
// the below snippet and results will be sent to the R console.

/*** R
hello_world() 
*/

Compile the function using:

Rcpp::sourceCpp('path/to/file/helloworld.cpp')

where 'path/to/file/' is the location containing helloworld.cpp

If everything is installed appropriately, then you should see the following in the console:

> hello_world()

Hello World!

In addition, you should have a new function within the global environment scope called “hello_world”. You can call this function like a normal R function via:

hello_world()

Common Errors

The following are debugged errors that you may run into.

clang: warning: argument unused during compilation: '-fopenmp'
fatal error: 'omp.h' file not found

Unfortunately, with R 4.0.0 the CRAN distributed version of R loses the ability to use OpenMP without a custom setup.

Acknowledgements

Thanks to dr.ing. MPH Verouden for catching a couple of errors in the post and letting me know!

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