frepeat: Repeat an expression or function call multiple times

In functionals: Functional Programming with Parallelism and Progress Tracking

Repeat an expression or function call multiple times

Description

Repeats an expression or function evaluation 'times' times. If 'expr' is a function, it is invoked with optional input '.x' and additional arguments. If 'expr' is a quoted expression, it is evaluated in the parent environment. Supports parallel processing and optional simplification of results.

Usage

frepeat(
  .x = NULL,
  times,
  expr,
  simplify = FALSE,
  ncores = NULL,
  pb = FALSE,
  ...
)

Arguments

.x	Optional input passed to 'expr' if 'expr' is a function. Default is 'NULL'.
times	Integer. Number of repetitions.
expr	A function or an unevaluated expression to repeat. If a function, it will be called 'times' times.
simplify	Logical. If 'TRUE', attempts to simplify the result using 'simplify2array()'. Default is 'FALSE'.
ncores	Integer. Number of cores to use for parallel execution. Default is 'NULL' (sequential).
pb	Logical. Whether to display a progress bar. Default is 'FALSE'.
...	Additional arguments passed to the function 'expr' if it is callable.

Value

A list of outputs (or a simplified array if 'simplify = TRUE') from evaluating 'expr' multiple times.

Note

If 'expr' is passed as a function call (not a function or quoted expression), it will be evaluated immediately, not repeated. Use function(...) \{ ... \} or quote(...) instead.

Examples

# Repeat a pure function call
frepeat(times = 3, expr = function() rnorm(1))

# Repeat a function with input `.x`
frepeat(.x = 10, times = 3, expr = function(x) rnorm(1, mean = x))

# Repeat an unevaluated expression (evaluated with `eval()`)
frepeat(times = 2, expr = quote(rnorm(1)))

# Simplify the output to an array
frepeat(times = 3, expr = function() rnorm(1), simplify = TRUE)

# Monte Carlo simulation: estimate coverage of a 95% CI for sample mean
mc_result <- frepeat(times = 1000, simplify = TRUE, pb = TRUE, ncores = 1, expr = function() {
  sample <- rnorm(30, mean = 0, sd = 1)
  ci <- t.test(sample)$conf.int
  mean(ci[1] <= 0 & 0 <= ci[2])  # check if true mean is inside the interval
})
mean(mc_result)  # estimated coverage

functionals documentation built on Aug. 8, 2025, 7:32 p.m.