R/ResamplingRepeatedSpCVCoords.R

In mlr3spatiotempcv: Spatiotemporal Resampling Methods for 'mlr3'

#' @title (sperrorest) Repeated coordinate-based k-means clustering
#'
#' @template rox_spcv_coords
#' @name mlr_resamplings_repeated_spcv_coords
#'
#' @section Parameters:
#'
#' * `repeats` (`integer(1)`)\cr
#'   Number of repeats.
#'
#' @references
#' `r format_bib("brenning2012")`
#'
#' @export
#' @examples
#' library(mlr3)
#' task = tsk("diplodia")
#'
#' # Instantiate Resampling
#' rrcv = rsmp("repeated_spcv_coords", folds = 3, repeats = 5)
#' rrcv$instantiate(task)
#'
#' # Individual sets:
#' rrcv$iters
#' rrcv$folds(1:6)
#' rrcv$repeats(1:6)
#'
#' # Individual sets:
#' rrcv$train_set(1)
#' rrcv$test_set(1)
#' intersect(rrcv$train_set(1), rrcv$test_set(1))
#'
#' # Internal storage:
#' rrcv$instance # table
ResamplingRepeatedSpCVCoords = R6Class("ResamplingRepeatedSpCVCoords",
  inherit = mlr3::Resampling,
  public = list(
    #' @description
    #' Create an "coordinate-based" repeated resampling instance.
    #'
    #' For a list of available arguments, please see [sperrorest::partition_cv].
    #' @param id `character(1)`\cr
    #'   Identifier for the resampling strategy.
    initialize = function(id = "repeated_spcv_coords") {
      ps = ParamSet$new(params = list(
        ParamInt$new("folds", lower = 1L, default = 10L, tags = "required"),
        ParamInt$new("repeats", lower = 1, default = 1L, tags = "required")
      ))
      ps$values = list(folds = 10L, repeats = 1)
      super$initialize(
        id = id,
        param_set = ps,
        label = "Repeated coordinate-based k-means clustering resampling",
        man = "mlr3spatiotempcv::mlr_resamplings_repeated_spcv_coords"
      )
    },

    #' @description Translates iteration numbers to fold number.
    #' @param iters `integer()`\cr
    #'   Iteration number.
    folds = function(iters) {
      iters = assert_integerish(iters, any.missing = FALSE, coerce = TRUE)
      ((iters - 1L) %% as.integer(self$param_set$values$folds)) + 1L
    },

    #' @description Translates iteration numbers to repetition number.
    #' @param iters `integer()`\cr
    #'   Iteration number.
    repeats = function(iters) {
      iters = assert_integerish(iters, any.missing = FALSE, coerce = TRUE)
      ((iters - 1L) %/% as.integer(self$param_set$values$folds)) + 1L
    },

    #' @description
    #'  Materializes fixed training and test splits for a given task.
    #' @param task [Task]\cr
    #'  A task to instantiate.
    instantiate = function(task) {

      mlr3::assert_task(task)
      assert_spatial_task(task)
      groups = task$groups
      if (!is.null(groups)) {
        stopf("Grouping is not supported for spatial resampling methods.") # nocov
      }

      instance = private$.sample(task$row_ids, task$coordinates())

      self$instance = instance
      self$task_hash = task$hash
      self$task_nrow = task$nrow
      invisible(self)
    }
  ),
  active = list(

    #' @field iters `integer(1)`\cr
    #'   Returns the number of resampling iterations, depending on the
    #'   values stored in the `param_set`.
    iters = function() {
      pv = self$param_set$values
      as.integer(pv$repeats) * as.integer(pv$folds)
    }
  ),
  private = list(
    .sample = function(ids, coords) {
      pv = self$param_set$values
      folds = as.integer(pv$folds)

      mlr3misc::map_dtr(seq_len(pv$repeats), function(i) {
        data.table(
          row_id = ids, rep = i,
          fold = kmeans(coords, centers = folds)$cluster
        )
      })
    },
    .get_train = function(i) {
      i = as.integer(i) - 1L
      folds = as.integer(self$param_set$values$folds)
      rep = i %/% folds + 1L
      fold = i %% folds + 1L
      ii = data.table(rep = rep, fold = seq_len(folds)[-fold])
      self$instance[ii, "row_id", on = names(ii), nomatch = 0L][[1L]]
    },
    .get_test = function(i) {
      i = as.integer(i) - 1L
      folds = as.integer(self$param_set$values$folds)
      rep = i %/% folds + 1L
      fold = i %% folds + 1L
      ii = data.table(rep = rep, fold = fold)
      self$instance[ii, "row_id", on = names(ii), nomatch = 0L][[1L]]
    }
  )
)