R/MeasureDebug.R

In mllg/mlr3: Machine Learning in R - Next Generation

#' @title Debug Measure
#'
#' @usage NULL
#' @aliases mlr_measures_debug
#' @format [R6::R6Class()] inheriting from [Measure].
#' @include Measure.R
#'
#' @section Construction:
#' ```
#' MeasureDebug$new(na_ratio = 0)
#' mlr_measures$get("debug")
#' msr("debug")
#' ```
#'
#' * `na_ratio` :: `numeric(1)`\cr
#'   Ratio of scores which should be `NA`.
#'   Default is 0.
#'
#' @description
#' This measure returns the number of observations in the [Prediction] object.
#' Its main purpose is debugging.
#'
#' @section Fields:
#' * `na_ratio` :: `numeric(1)`.
#'
#' @template seealso_measure
#' @export
#' @examples
#' task = tsk("wine")
#' learner = lrn("classif.featureless", predict_sets = "test")
#' measure = msr("debug")
#' rr = resample(task, learner, rsmp("cv", folds = 3))
#' rr$score(measure)
MeasureDebug = R6Class("MeasureDebug",
  inherit = Measure,
  public = list(
    na_ratio = 0,
    initialize = function(na_ratio = 0) {
      super$initialize(
        id = "debug",
        predict_type = "response",
        range = c(0, Inf),
        properties = "na_score"
      )
      self$na_ratio = assert_number(na_ratio, lower = 0, upper = 1)
    },

    score_internal = function(prediction, ...) {
      if (self$na_ratio > runif(1L))
        return(NA_integer_)
      length(prediction$row_ids)
    }
  )
)

#' @include mlr_measures.R
mlr_measures$add("debug", MeasureDebug)