R/populateShinyApp.R

In ABMI/SevereCovidPrediction: A Package Skeleton for Patient Level Prediction Studies

#' @export
populateShinyApp <- function(shinyDirectory,
                             resultDirectory,
                             minCellCount = 10,
                             databaseName = 'sharable name of development data'){
  
  #check inputs
  if(missing(shinyDirectory)){
    shinyDirectory <- system.file("shiny", "PLPViewer", package = "SevereCovidPrediction")
  }
  if(missing(resultDirectory)){
    stop('Need to enter the resultDirectory')
  }
  if(!dir.exists(resultDirectory)){
    stop('resultDirectory does not exist')
  }
  
  outputDirectory <- file.path(shinyDirectory,'data')
  
  # create the shiny data folder
  if(!dir.exists(outputDirectory)){
    dir.create(outputDirectory, recursive = T)
  }
  
  # copy the settings csv
  file <- utils::read.csv(file.path(resultDirectory,'settings.csv'))
  utils::write.csv(file, file.path(outputDirectory,'settings.csv'), row.names = F)
  
  # copy each analysis as a rds file and copy the log
  files <- dir(resultDirectory, full.names = F)
  files <- files[grep('Analysis', files)]
  for(file in files){
    
    if(!dir.exists(file.path(outputDirectory,file))){
      dir.create(file.path(outputDirectory,file))
    }
    
    if(dir.exists(file.path(resultDirectory,file, 'plpResult'))){
      res <- PatientLevelPrediction::loadPlpResult(file.path(resultDirectory,file, 'plpResult'))
      res <- PatientLevelPrediction::transportPlp(res, n= minCellCount, 
                                                  save = F, dataName = databaseName)
      saveRDS(res, file.path(outputDirectory,file, 'plpResult.rds'))
    }
    if(file.exists(file.path(resultDirectory,file, 'plpLog.txt'))){
      file.copy(from = file.path(resultDirectory,file, 'plpLog.txt'), 
                to = file.path(outputDirectory,file, 'plpLog.txt'))
    }
  }
  
  # copy any validation results
  if(dir.exists(file.path(resultDirectory,'Validation'))){
    valFolders <-  dir(file.path(resultDirectory,'Validation'), full.names = F)
    
    if(length(valFolders)>0){
      # move each of the validation rds
      for(valFolder in valFolders){
        
        # get the analysisIds
        valSubfolders <- dir(file.path(resultDirectory,'Validation',valFolder), full.names = F)
        if(length(valSubfolders)!=0){
          for(valSubfolder in valSubfolders ){
            valOut <- file.path(valFolder,valSubfolder)
            if(!dir.exists(file.path(outputDirectory,'Validation',valOut))){
              dir.create(file.path(outputDirectory,'Validation',valOut), recursive = T)
            }
            
            
            if(file.exists(file.path(resultDirectory,'Validation',valOut, 'validationResult.rds'))){
              res <- readRDS(file.path(resultDirectory,'Validation',valOut, 'validationResult.rds'))
              res <- PatientLevelPrediction::transportPlp(res, n= minCellCount, 
                                                          save = F, dataName = databaseName)
              saveRDS(res, file.path(outputDirectory,'Validation',valOut, 'validationResult.rds'))
            }
          }
        }
        
      }
      
    }
    
  }
  
  return(outputDirectory)
  
}

#' View shiny app 
#' @details
#' This function will open an interactive shiny app for viewing the results
#' @param package The name of the package as a string
#'
#' @examples
#' \dontrun{
#' viewShiny()
#' }
#' @export
viewShiny <- function(package = NULL){
  if(is.null(package)){
    appDir <- system.file("shiny", "PLPViewer", package = "SevereCovidPrediction")
  }
  if(!is.null(package)){
    appDir <- system.file("shiny", "PLPViewer", package = package)
  }
  
  shiny::shinyAppDir(appDir)
}