R/SDS100_do_it.R

In emeyers/SDS100: Tools for the class Introductory Statistics

#' Repeats a process many times and returns a vector of results
#'
#'
#'@note 
#' This is a simplified version of the mosiac do() that returns a vector only.
#' The idea and code are based on the mosaic do() function, which can be found
#' on github page at: https://github.com/ProjectMOSAIC/mosaic/blob/master/R/do.R
#' The code uses S4 objects.
#'
#'   
#' @param n The number of times to repeat the process.
#' 
#' @param null_dist A vector of data consistent with a null hypothesis.
#'   
#' @param lower.tail A Boolean indicating whether one should return the
#'   proportion of points less than or equal to the obs_stat value.
#'
#' @examples
#'  many_hellos <- do_it(10) * { "hello" }
#'
#' @export
do_it <- function(n=1L) {
  new('doer', n=n)
}





# S4 class definition for runner so that * is appropriately dispatched
#' @export

setClass('doer',
         representation = representation(n='numeric'),
         prototype = prototype(n=1))




# create the * method
# first argument is a runner, the second is any expression
#' @export

setMethod(
  "*",
  signature(e1 = "doer", e2="ANY"),
  function (e1, e2) {

    # create a formula for the second argument in the multiplication
    e2_lazy <- lazyeval::f_capture(e2)

    # get n from the n argument in the run constructor
    n = e1@n

   # evaluate the formula n times
   sapply(integer(n), function(...) { lazyeval::f_eval(e2_lazy) } )

})