R/PackageResults.R

In ohdsi-studies/PCE: A Package Skeleton for Replicating Published Prediction Models

# Copyright 2020 Observational Health Data Sciences and Informatics
#
# This file is part of PCE
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

#' Package the results for sharing with OHDSI researchers
#'
#' @details
#' This function packages the results.
#'
#' @param outputFolder        Name of folder containing the study analysis results 
#'                            (/)
#' @param minCellCount        The minimum number of subjects contributing to a count before it can be included in the results.
#'
#' @export
packageResults <- function(outputFolder, 
                           minCellCount = 5) {
  if(missing(outputFolder)){
    stop('Missing outputFolder...')
  }
  
  # for each analysis copy the requested files...
  folders <- list.dirs(path = outputFolder, recursive = F, full.names = F)
  folders <- folders[grep('Analysis_', folders)]
  
  #create export subfolder in workFolder
  exportFolder <- file.path(outputFolder, "export")
  dir.create(exportFolder, recursive = T)
  
  for(folder in folders){
    #copy all plots across
    if (!file.exists(file.path(exportFolder,folder))){
      dir.create(file.path(exportFolder,folder), recursive = T)
    }
    
    # loads analysis results
    if(dir.exists(file.path(outputFolder,folder, 'plpResult'))){
      plpResult <- PatientLevelPrediction::loadPlpResult(file.path(outputFolder,folder, 'plpResult'))
      
      #---- custom
      # loads table1:
      table1 <- NULL
      if(file.exists(file.path(outputFolder,folder, 'plpResult','table1.rds'))){
        table1 <- readRDS(file.path(outputFolder,folder, 'plpResult','table1.rds'))
      }
      #------
      
      plpResult$model$predict <- NULL
      cvst <- plpResult$inputSetting$dataExtrractionSettings$covariateSettings
      
      #---- custom
      # extract the nb 
      nb <- plpResult$performanceEvaluation$nbSummary 
      #------
      
      if(minCellCount!=0){
        plpResult <- PatientLevelPrediction::transportPlp(plpResult,
                                                          dataName = cdmDatabaseName,
                                                          n=minCellCount,
                                                          includeEvaluationStatistics=T,
                                                          includeThresholdSummary=T, 
                                                          includeDemographicSummary=T,
                                                          includeCalibrationSummary =T, 
                                                          includePredictionDistribution=T,
                                                          includeCovariateSummary=T, 
                                                          save = F)
      } else {
        plpResult <- PatientLevelPrediction::transportPlp(plpResult, 
                                                          n=NULL,
                                                          includeEvaluationStatistics=T,
                                                          includeThresholdSummary=T, 
                                                          includeDemographicSummary=T,
                                                          includeCalibrationSummary =T, 
                                                          includePredictionDistribution=T,
                                                          includeCovariateSummary=T, 
                                                          save = F)
      }
      
      plpResult$inputSetting$dataExtrractionSettings$covariateSettings <- cvst
      
      # save as csv
      PatientLevelPrediction::savePlpToCsv(plpResult, file.path(exportFolder,folder))
      
      
      #---- custom
      # save the nb (it has no patient level data)
      if(!is.null(nb)){
        write.csv(nb, file.path(exportFolder,folder, 'performanceEvaluation', 'nbSummary.csv'))
      }
      if(!is.null(table1)){
        write.csv(table1, file.path(exportFolder,folder, 'performanceEvaluation', 'table1.csv'))
      }
      #------
      
    }
  }
  
  
  ### Add all to zip file ###
  zipName <- paste0(outputFolder, '.zip')
  OhdsiSharing::compressFolder(exportFolder, zipName)
  # delete temp folder
  unlink(exportFolder, recursive = T)
  
  writeLines(paste("\nStudy results are compressed and ready for sharing at:", zipName))
  return(zipName)
}