R/dataInputPrep.R

In tbep-tech/tbepRSparrow: RSPARROW: An R system for SPARROW modeling

#'@title dataInputPrep
#'@description Imports data1.csv and dataDictionary.csv files, checks for duplicate 
#'            `sparrowNames`, replaces `data1UserNames` with `sparrowNames` in the `data1` object, checksreach 
#'            navigation variables for large integers and/or all missing values, creates and/or verifies navigation 
#'            variables and `demtarea`, saves `data1` and `data_names` (dataDictionary.csv import object) 
#'            objects as binary file in top level of results (input_data_fileName)_priorImport, and saves 
#'            `data_names` and `data1` to `.GlobalEnv` \\cr \\cr
#'Executed By: \\itemize\{\\item batchRun.R
#'             \\item executeRSPARROW.R\} \\cr
#'Executes Routines: \\itemize\{\\item checkData1NavigationVars.R
#'             \\item checkDupVarnames.R
#'             \\item checkMissingData1Vars.R
#'             \\item createVerifyReachAttr.R
#'             \\item read_dataDictionary.R
#'             \\item readData.R
#'             \\item replaceData1Names.R
#'             \\item unPackList.R\} \\cr
#'@param file.output.list list of control settings and relative paths used for input and 
#'                        output of external files.  Created by `generateInputList.R`
#'@param input_data_fileName name of users data1 file
#'@param if_reverse_hydseq yes/no indicating whether hydseq in the DATA1 file needs to be 
#'       reversed from sparrow_control
#'@param if_verify_demtarea specify whether or not to verify demtarea
#'@param calculate_reach_attribute_list list of attributes to calculate
#'@param mapping.input.list Named list of sparrow_control settings for mapping: lat_limit, 
#'                          lon_limit, master_map_list, lineShapeName, lineWaterid, 
#'                          polyShapeName, ployWaterid, LineShapeGeo, LineShapeGeo, CRStext, 
#'                          convertShapeToBinary.list, map_siteAttributes.list, 
#'                          residual_map_breakpoints, site_mapPointScale, 
#'                          if_verify_demtarea_maps
#'@param batch_mode yes/no character string indicating whether RSPARROW is being run in batch 
#'       mode



dataInputPrep<-function(#for readData
  file.output.list,input_data_fileName,
  #for checkData1NavigationVars
  if_reverse_hydseq,
  #for createVerifyNavigationVars
  if_verify_demtarea,calculate_reach_attribute_list,
  mapping.input.list,
  #for all
  batch_mode){
  
  
  
  ######################################
  # 2. DATA1 input and data preparation
  ######################################      
  unPackList(lists = list(file.output.list = file.output.list),
             parentObj = list(NA)) 
  
  message("Running Data import and prep...")
  
  # (A) Input DATA1 CSV file
  data1<-readData(file.output.list,input_data_fileName)
  
  
  # (B) input VARNAMES (data dictionary) CSV file
  #     (should contain all required network variables plus any new variables
  #      needed for mapping, plus any variables in SUBDATA used to make calculations)
  data_names <- as.data.frame(read_dataDictionary(file.output.list,batch_mode))
  
  # (B1) check varNames for duplicates
  checkDupVarnames(data_names,batch_mode)
  
  # (C) Replace the column names in DATA1 with the required column names
  #    Set default setting for 'calsites' index if missing or all NAs
  data1 <- replaceData1Names(data_names,data1)
  
  # (C1) Checks for excessively large integer values for navigation variables and 
  #      replacement of values if necessary
  data1 <- checkData1NavigationVars(data1,if_reverse_hydseq,batch_mode)
  
  
  # (D) Optional processing of NETWORK ATTRIBUTES AND VERIFY DRAINAGE AREA
  data1 <-  createVerifyReachAttr(if_verify_demtarea,calculate_reach_attribute_list,data1,
                                  file.output.list,mapping.input.list,
                                  batch_mode)
  
  
  
  # (E) Check for missing required variables in DATA1 as specified in varnames file
  data1 <- checkMissingData1Vars(data1,batch_mode)
  
  
  #save dataInputPrep objects to binary file for future use
  fileList<-c("data1","data_names")
  fileList<-fileList[which(fileList %in% ls())]
  fileName<-strsplit(path_results,.Platform$file.sep)[[1]]
  fileName<-paste(fileName[1:length(fileName)-1],collapse = .Platform$file.sep)
  fileName<-paste(fileName,.Platform$file.sep,gsub(".csv","",input_data_fileName),"_priorImport",sep="")
  save(list=fileList, file=fileName)
  
  
  
  
  assign("data1",data1,envir = .GlobalEnv)
  assign("data_names",data_names,envir = .GlobalEnv)
  
  
}#end function