:eyes: assert

assert provides a replacement to stopifnot and assertthat::assert_that which provides more informative error messages.

Installation

You can install the released version of assert from CRAN with:

install.packages("assert")

And the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("OlivierBinette/assert")

Examples

Assertions throughout a data analysis workflow:

library(assert)
attach(ChickWeight)

# Passing assertions
assert(is.numeric(weight),
       all(weight > 0))

# Failing assertions
assert(all(Diet > 0),
       is.numeric(Times))
#> Error in assert(all(Diet > 0), is.numeric(Times)) : 
#> Failed checks: 
#>      all(Diet > 0)   (NA)
#>      is.numeric(Times)   (object 'Times' not found)

Validate function arguments:

# Sample from a multivariate normal distribution
rmultinorm <- function(k, mu, sigma) {
  assert(is.numeric(k),
         length(k) == 1,
         k > 0,
         msg = "Number of samples `k` should be a positive integer")
  assert(is.numeric(mu),
         is.matrix(sigma),
         all(length(mu) == dim(sigma)),
         msg = "Mean vector should match the covariance matrix dimensions.")

  p <- length(mu)
  t(chol(sigma)) %*% matrix(rnorm(p*k, 0, 1), nrow=p) + mu
}

mu <- c(0,10)
sigma <- matrix(c(2,1,1,2), nrow=2)
rmultinorm(3, mu, sigma)
#>           [,1]      [,2]      [,3]
#> [1,]  0.111465 -1.193094 0.4347379
#> [2,] 10.037030  8.237249 8.2379180

rmultinorm(mu, 3, sigma)
#> Error: in rmultinorm(k = mu, mu = 3, sigma = sigma)
#> Failed checks: 
#>      length(k) == 1
#>      k > 0   (c(FALSE, TRUE))
#>
#> Number of samples `k` should be a positive integer