R/CompareSim.R

In EcoFoG/vernabota: Association between vernacular and botanical names for Guyafor data

#' Perform simulation and compare them to original species
#'
#' @description This function performs several simulations for trees that have a
#'   complete taxonomic identification and compare the results with the original
#'   species.
#'
#' @param Param a datatable with the parameters for each scenario :
#'  - priors : a vector with the rank of the priors to use in the priors list
#'  - dataAsso : a vector with the rank of the observation data to use in
#'  the DAsso list (if Dasso is not provided, put 1)
#'  - weights : a vector with the weights of the priors
#'  - eps : a vector with the epsilon value for each scenario
#'  - Determ : a vector with the value of Determ (boolean)
#' @param priors a list of datasets containing the priors for each scenario.
#' These datasets must have been prepared using the function PrepPrior.
#' (Default is NULL: no prior information is used).
#' @param D2fill a dataset to fill, this dataset must
#' have been prepared using the function PrepData.
#' @param DAsso a list of datasets of observation used for each scenario, these datasets must have been
#' prepared using the function PrepData (Default is NULL: the dataset Data2fill is used
#' to built the association matrix).
#' @param pc2fill the percentage of data (dataFill) to fill.
#' @param pcFamilyDet the percentage of data determined
#' at the family level (from the subset of dataFill to fill).
#' We recommend using a percentage equivalent than in the data to gapfill.
#' @param pcGenusDet the percentage of data determined at
#'  the genus level (from the subset of dataFill to fill, the rest isn't determined at all).
#'  We recommend using a percentage equivalent than in the data to gapfill.
#' @param NbSim the number of simulations.
#' @param Results_Simulations a boolean specifying if the
#'  user wants to keep the results of the simulations.
#' @param parallel a boolean specifying if the
#'  user wants to speed up the loop by using parallelization.
#'
#' @return This function returns an object of the class VernaBotaSims.
#' The functions summary and plot can be used on this object.
#'
#' @details This function performs the following steps for each scenario:
#'  - Get the data,
#'  - Split between train and test set and remove taxonomic information from the test set (see *SampleTestDataset* function),
#'  - Perform simulations (see *SimFullCom* function),
#'  - Compare simulations with original taxonomic information, with the function
#'  *CompareTaxo*,
#'  - Create and return an object of the class VernaBotaSims.
#'
#' @export
#'
#' @importFrom methods new
#' @importFrom parallel detectCores makeCluster stopCluster
#' @importFrom foreach %dopar% foreach
#' @importFrom doParallel registerDoParallel
#'
#'
CompareSim <- function(Param = NULL,
                       priors = NULL, D2fill, DAsso = NULL,
                       pc2fill = NULL, pcFamilyDet = NULL, pcGenusDet = NULL,
                       NbSim = 1, Results_Simulations = FALSE, parallel = FALSE)

{
  `%dopar%` <- foreach::`%dopar%`
  NScenar <- dim(Param)[1]

  pc_ok_results <- tot_results <- list()

  # creation of the dataset to fill (the same dataset will then be used for all scenarios)
  # Get data and remove duplicated lines corresponding to a single tree
  dat <- D2fill
  dat <- dat[!duplicated(dat$idTree),]

  # creation of the dataset
  tot_test <- SampleTestDataset(dat, pc2fill, pcGenusDet, pcFamilyDet)
  tot <- tot_test[[1]]
  test_taxo <- tot_test[[2]]
  idTest <- tot_test[[3]]

  if (!parallel)
  {
    # loop for each scenario (not parallelized)
    for (s in 1:NScenar){

      # Get DataAsso and remove test trees info from DataAsso (if present in the dataset)
      datAsso <- DAsso[[Param$dataAsso[s]]]
      datAsso <- datAsso[which(!datAsso$idTree%in%idTest),]

      # run the function SimFullCom with parameters from the scenario s
      Results_Sim <- SimFullCom(Data2fill = tot,
                                DataAsso = datAsso,
                                prior = priors[[Param$priors[s]]],
                                wp = Param$weights[s],
                                NSim = NbSim,
                                eps = Param$eps[s],
                                Determ = Param$Determ[s])

      # compare results with data
      pc_ok_results[[s]] <- lapply(Results_Sim, CompareTaxo, test_taxo)

      if (Results_Simulations)
      {
        tot_results[[s]] <- lapply(Results_Sim, ValidTaxo, test_taxo)
        for (i in 1:NbSim) {
          tot_results[[s]][[i]] <- tot_results[[s]][[i]][, c("idTree",
                                                             "Family", "Genus", "Species",
                                                             "BotaSource", "BotaCertainty",
                                                             "VernName", "GenSp",
                                                             "GensSpCor", "BotaCorCode",
                                                             "ValidAsso", "TestData")]
        }
      }
    }
  }

  if(parallel)
  {
    # loop for each scenario (parallelized)

    numCores  <- parallel::detectCores()
    cl <- parallel::makeCluster(numCores-1)
    doParallel::registerDoParallel(cl)

    pc_ok_results <- foreach::foreach (s = 1:NScenar) %dopar% {

      # Get DataAsso and remove test trees info from DataAsso (if present in the dataset)
      datAsso <- DAsso[[Param$dataAsso[s]]]
      datAsso <- datAsso[which(!datAsso$idTree%in%idTest),]

      # run the function SimFullCom with parameters from the scenario s
      Results_Sim <- vernabota::SimFullCom(Data2fill = tot,
                                           DataAsso = datAsso,
                                           prior = priors[[Param$priors[s]]],
                                           wp = Param$weights[s],
                                           NSim = NbSim,
                                           eps = Param$eps[s],
                                           Determ = Param$Determ[s])
      if (Results_Simulations)
      {
        tot_results[[s]] <- lapply(Results_Sim, ValidTaxo, test_taxo)
        for (i in 1:NbSim) {
          tot_results[[s]][[i]] <- tot_results[[s]][[i]][, c("idTree",
                                                             "Family", "Genus", "Species",
                                                             "BotaSource", "BotaCertainty",
                                                             "VernName", "GenSp",
                                                             "GensSpCor", "BotaCorCode",
                                                             "ValidAsso", "TestData")]
        }
      }

      # compare results with data
      lapply(Results_Sim, vernabota::CompareTaxo, test_taxo)}
    parallel::stopCluster(cl)
  }


  # creation of the VernaBotaSims object
  VBS <- new(Class = "VernaBotaSims", NScenar = NScenar, ParamScenar = Param,
             D2fill = D2fill, DAsso = DAsso, priors = priors,
             pc2fill = pc2fill, pcFamilyDet = pcFamilyDet, pcGenusDet=pcGenusDet,
             NbSim = NbSim,
             pc_results = pc_ok_results,
             results = tot_results)
  return(VBS)
}