Validating function arguments in R

Update: The assert package is now available on CRAN:

install.packages("assert")

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I was programming a Gibbs sampler the other day and all hell broke loose: small errors were hard to trace back to the source of the problem and debugging was a pain.

The bugs could have been caught much more early if I had properly validated the input arguments of my various helper functions. So I decided it was time for me to learn how to do this properly.

Validating function input arguments in R

The easiest way is to manually incorporate checks.

mySum <- function(a, b) {
  if (!is.numeric(a) | !is.numeric(b)) {
    stop("Arguments should be numeric.")
  }
  if (length(a) != length(b)) {
    stop("Arguments should be of the same length.")
  } 
  
  return(a+b)
}

This works well enough, but it takes up a lot of space and you have to manually write up the description of the errors.

A first solution

Let’s use the assertthat package.

mySum <- function(a, b) {
  assert_that(is.numeric(a), is.numeric(b))
    assert_that(length(a) == length(b))
  
  return(a+b)
}

This is neater, but the error messages are not very descriptive.

> mySum(1, "1")
        Error: b is not a numeric or integer vector 

What is b here? What arguments in the function call caused the error? It’s a bit hard to tell, especially if the call to this function is hidden in some large Gibbs sampler.

The assert function

My solution is the assert function which you can find on my Github Gist.

source("assert.R")

Usage is similar to what we did above:

mySum <- function(a, b) {
  assert(is.numeric(a), is.numeric(b))
    assert(length(a) == length(b))
  
  return(a+b)
}

But now we have much more descriptive error messages.

> mySum(1, "1")
        Error: in mySum(a = 1, b = "1")
        Failed checks: 
            is.numeric(b) 

Copyright

Olivier Binette