R/ck_generate_rkeys.R

In sdcTools/cellKey: Consistent Perturbation of Statistical Frequency- And Magnitude Tables

#' Generate random record keys
#'
#' This function allows to create random record keys from a uniform distribution. If no seed is
#' specified, a seed value is computed from the input data set to allow for reproducability depending
#' on the input data set.
#'
#' @param dat microdata used to generated hash for random seed
#' @param nr_digits maximum number of digits in the record keys. The default setting (`8`) corresponds
#' with the default setting of the method in `tau-argus`.
#' @param seed if not `NULL`, a number specifying the initial seed value
#' for the random number generator. If `NULL`, a seed is computed from `dat` itself.
#' @return a numeric vector with `nrow(dat)` record keys
#' @export
#' @md
#' @examples
#' dat <- ck_create_testdata()
#' dat$rkeys <- ck_generate_rkeys(dat = ck_create_testdata(), nr_digits = 8)
ck_generate_rkeys <- function(dat, nr_digits = 8, seed = NULL) {
  if (!inherits(dat, "data.frame")) {
    stop("`dat` is not coercible to a `data.frame`.", call. = FALSE)
  }
  if (!is.null(seed)) {
    stopifnot(is_scalar_integerish(seed))
  } else {
    seed <- ck_create_seed_from_hash(dat)
  }

  if (!rlang::is_scalar_integerish(nr_digits)) {
    stop("`nr_digits` is not an integerish number.", call. = FALSE)
  }
  if (nr_digits < 5) {
    stop("`nr_digits` must be >= 5.", call. = FALSE)
  }
  if (nr_digits > 20) {
    stop("`nr_digits` must be <= 20.", call. = FALSE)
  }
  set.seed(seed)
  return(round(
    x = runif(n = nrow(dat), min = 0, max = 1),
    digits = nr_digits))
}