refactored-sample.R

sample.int <- function(n, size = n, replace = FALSE, prob = NULL,
  prob_method = c("sequential", "marginal", "poisson"),
  useHash = (n > 1e7 && !replace && is.null(prob) && size <= n/2)){
    
    stopifnot(length(n) == 1L)
    replace_or_no_prob <- is.null(prob) || replace
    if (replace_or_no_prob){
      size <- size %||% n
      if (useHash) {
        ## will work with size > n/2 but may be slow.
        stopifnot(is.null(prob), !replace)
        .Internal(sample2(n, size))
      } else {
        .Internal(sample(n, size, replace, prob))
      }
    } else {
      size <- size %||% sum(prob)
      if (length(prob) != n) {
        stop("incorrect number of probabilities")
      }
      prob_method <- match.arg(prob_method)
      switch(
        prob_method,
        sequential = .Internal(sample(n, size, replace, prob)),
        marginal = sample.pps(n, size, prob),
        # using `sample()` to permute selected items 
        poisson = sample(which(runif(n) <= prob * size/sum(prob)))
      )
    }
  }

Potential refactor removing use of else and only using if

sample.int <- function(n, size = n, replace = FALSE, prob = NULL,
                       prob_method = c("sequential", "marginal", "poisson"),
                       useHash = (n > 1e7 && !replace && is.null(prob) && size <= n/2)){
  
  stopifnot(length(n) == 1L)
  if (replace || is.null(prob)) {
    size <- size %||% n
    if (useHash) {
      ## will work with size > n/2 but may be slow.
      stopifnot(is.null(prob), !replace)
      return(.Internal(sample2(n, size)))
    } 
      return(.Internal(sample(n, size, replace, prob)))
  }
    size <- size %||% sum(prob)
    if (length(prob) != n) {
      stop("incorrect number of probabilities")
    }
    prob_method <- match.arg(prob_method)
    switch(
      prob_method,
      sequential = .Internal(sample(n, size, replace, prob)),
      marginal = sample.pps(n, size, prob),
      # using `sample()` to permute selected items 
      poisson = sample(which(runif(n) <= prob * size/sum(prob)))
    )
}