```
## Measure the time it takes to dispatch a simple function call
## compared to simply evaluating the constant \code{NULL}
f <- function() NULL
res <- microbenchmark(NULL, f(), times=100L)
## Print results:
print(res)
dput(res)
## Plot results:
boxplot(res)
## Pretty plot:
if (requireNamespace("ggplot2")) {
ggplot2::autoplot(res)
}
## Example check usage
my_check <- function(values) {
all(sapply(values[-1], function(x) identical(values[[1]], x)))
}
f <- function(a, b)
2 + 2
a <- 2
## Check passes
microbenchmark(2 + 2, 2 + a, f(2, a), f(2, 2), check=my_check)
if (FALSE) {
a <- 3
## Check fails
microbenchmark(2 + 2, 2 + a, f(2, a), f(2, 2), check=my_check)
}
## Example setup usage
set.seed(21)
x <- rnorm(10)
microbenchmark(x, rnorm(10), check=my_check, setup=set.seed(21))
## Will fail without setup
if (FALSE) {
microbenchmark(x, rnorm(10), check=my_check)
}
## using check
a <- 2
microbenchmark(2 + 2, 2 + a, sum(2, a), sum(2, 2), check='identical')
microbenchmark(2 + 2, 2 + a, sum(2, a), sum(2, 2), check='equal')
attr(a, 'abc') <- 123
microbenchmark(2 + 2, 2 + a, sum(2, a), sum(2, 2), check='equivalent')
## check='equal' will fail due to difference in attribute
if (FALSE) {
microbenchmark(2 + 2, 2 + a, sum(2, a), sum(2, 2), check='equal')
}
```

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