R/perturbate.R

Defines functions grids_perturbate perturbate

Documented in grids_perturbate perturbate

## perturbate grid data


#' Perturbate grid ratings
#'
#' Randomly subtract or add an amount to a proportion of the grid ratings. This
#' emulates randomness during the rating process, producing a grid which might
#' also have resulted.
#' @param x A \code{repgrid} object.
#' @param n Number of perturbated grid to generate.
#' @param prop The proportion of ratings to be perturbated.
#' @param amount The amount set of possible perturbations. Will depend on scale
#'   range. Usually {-1, 1} are reasonable settings
#' @param prob Pobability for each amount to occur.
#' @export
#' @example inst/examples/example-perturbate.R
#' @rdname perturbate
#' 
perturbate <- function(x, prop = .1, amount = c(-1, 1), prob = c(.5, .5)) 
{
  if (!inherits(x, "repgrid")) 
    stop("Object must be of class 'repgrid'")
  
  if (length(amount) != length(prob))
    stop("Length of 'amount' and 'prob' must be the same. ", 
         "Each entry in amount must have a corresponding prob value.", call. = FALSE)
  
  sc <- getScale(x)  # min, max of rating scale
  smin <- sc[1]
  smax <- sc[2]
  r <- ratings(x)
  N <- length(r)
  n_sample <- floor(prop * N)
  ii <- sample(seq_len(N), size = n_sample, replace = FALSE)
  
  # perturbate grid rating by given amounts and probablity for each amount.
  # Values lower or higher thahn scale range are set back to min and max of scale range.
  perturbations <- sample(amount, size = n_sample, replace = TRUE, prob = prob)
  new_values <- r[ii] + perturbations
  new_values <- ifelse(new_values < smin, smin, new_values)
  new_values <- ifelse(new_values > smax, smax, new_values)
  r[ii] <- new_values
  ratings(x) <- r
  x
}


#' @export
#' @rdname perturbate
#' 
grids_perturbate <- function(x, n = 10, prop = .1, amount = c(-1, 1), prob = c(.5, .5))
{
  l <- replicate(n, {
    perturbate(x, prop = prop, amount = amount, prob = prob)
  }, simplify = FALSE)
  as.gridlist(l)
}
markheckmann/OpenRepGrid documentation built on April 30, 2021, 2:33 a.m.