R/easySdcTableGauss.R

In statisticsnorway/Kostra: Functions for Kostra

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#                                          #
#  This file is generated by a r program   #
#  Do not edit by hand                     #
#                                          #
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##### --- EasyData.R ---
#####################################
#' Function that returns a dataset 
#'
#' @encoding UTF8
#'
#' @param dataset Name of data set within the easySdcTable  package  
#' @param path When non-NULL the data set is read from "path/dataset.RData"
#'
#' @return The dataset
#' @export
#' @importFrom utils data
#' @importFrom SSBtools Hrc2DimList SSBtoolsData
#' 
#' @note The function returns the same datasets as \code{\link{SSBtoolsData}}.
#'
#' @examples
#'  z  <- EasyData("sosialFiktiv")
#'
EasyData <- function(dataset, path = NULL) {
  if (!is.null(path)) {
    filename <- paste(path, dataset, ".RData", sep = "")
    return(get(load(filename, envir = environment())))
  }
  SSBtoolsData(dataset)
}
 
##### --- IncProgress.R ---
#####################################
#' Default IncProgress function
#' @export
#' 
#' @note 
#' Instead of using \code{IncProgress = IncDefault} in ProtectTable1/ProtectTable one could use \cr
#' \code{IncProgress = function(){cat("."); flush.console()}} \cr
#' but this results in wrong 
#' "usage line" in the documentation since ";" is not included.
#' 
#' @keywords internal
#'
#' @examples
#'  IncDefault() 
IncDefault =  function(){
  cat(".")
  flush.console()}
 
##### --- ProtectTable.R ---
#####################################
#'  Only-Gauss replacement function for easySdcTable::ProtectTable
#'
#'  \code{{GaussSuppression}}, \code{{protectTable}} or  \code{{protect_linked_tables}} 
#'  is run with a data set as the only required input. One (stacked) or several (unstacked) input variables can hold cell counts.
#'  `ProtectTableData` is a tidy wrapper function, which returns a single data frame instead of a list (`info` omitted). 
#'
#' @encoding UTF8
#' 
#' @param data data frame
#' @param dimVar The main dimensional variables and additional aggregating variables (name or number).
#' @param freqVar Variable(s) holding counts or NULL in the case of micro data (name or number).
#' @param protectZeros When TRUE empty cells (count=0) is considered sensitive (i.e. same as allowZeros in  \code{{primarySuppression}}).
#' @param maxN All cells having counts <= maxN are set as primary suppressed.
#' @param method Parameter `method` in \code{{protectTable}}, \code{{protect_linked_tables}}
#'        or wrapper methods via \code{{PTwrap}}. 
#'        `Gauss` (default) is implemented independently of `sdcTable`. There is also a similar variant implemented in sdcTable as `GAUSS`. 
#'        But this implementation is not as optimal and `Gauss` is recommended instead.
#' * **`"SIMPLEHEURISTIC"`:** This method is default in protectable.
#' * **`"SIMPLEHEURISTIC_OLD"`:** As `"SIMPLEHEURISTIC"` in sdcTable versions prior to 0.32.
#' * **`"OPT"`, `"HITAS"`, `"HYPERCUBE"`, `"GAUSS"`:** Other methods in protectable. `"HYPERCUBE"` is not possible in cases with two linked tables.
#' * **`"SimpleSingle"`:**  `"SIMPLEHEURISTIC_OLD"` with `detectSingletons=TRUE` when `protectZeros=FALSE` and
#'                            `"SIMPLEHEURISTIC_OLD"` with `threshold=1` (can be overridden by input) when `protectZeros=TRUE`. 
#' * **`"SIMPLEHEURISTICSingle"`:** As `"SimpleSingle"` with `"SIMPLEHEURISTIC"` instead of `"SIMPLEHEURISTIC_OLD"`.                          
#' * **`"Simple"`:** `"SIMPLEHEURISTIC_OLD"` with `detectSingletons=FALSE`.  
#' * **`"Gauss"`:** \code{{GaussSuppression}} is called with parameters `x`, `candidates`, `primary` and `singleton` automatically generated.
#'                Other parameters (`singletonMethod`, `printInc`) can be specified. 
#' 
#' Alternatively this parameter can be a named list specifying parameters for running tau-argus (see details).                     
#'        See \code{{PTwrap}} for other (experimental) wrapper methods (see details).
#' @param findLinked When TRUE, the function may find two linked tables and run protect_linked_tables.
#' @param total String used to name totals.
#' @param addName When TRUE the variable name is added to the level names, except for variables with most levels.
#' @param sep A character string to separate when addName apply and when creating variable names.
#' @param removeZeros When TRUE, rows with zero count will be removed from the data within the algorithm.
#' @param dimList By default, hierarchies will be automatically found from data (see \code{{FindDimLists}}). 
#'   With non-NULL dimList, these will be changed. 
#'   In practice this is done by the function \code{{ReplaceDimList}}. 
#' @param groupVarInd Possible manual specification of list defining the hierarchical 
#'         variable groups. When NULL (default) this information will be found automatically 
#'         by \code{{FindTableGroup}}.
#' @param ind1  Coding of table 1 as indices referring to elements of groupVarInd. This information 
#'         will be found automatically 
#'         by \code{{FindTableGroup}} when groupVarInd=NULL. 
#' @param ind2  Coding of table 2 as indices referring to elements of groupVarInd (as ind1 above).
#' @param rowData Input to \code{{Stack}} used to generate extra dimVar variables when stacking in cases with several 
#'        freqvar variables. When NULL rowData will be created automatically by \code{{AutoSplit}} using varNames (see below)
#'        and the the freqvar names as input.
#' @param varNames The names of the extra dimVar variable(s) made when stacking in cases with several 
#'        freqvar variables. When length(varNames)>1 several variables may be found by \code{{AutoSplit}}. 
#' @param split Parameter to \code{{AutoSplit}} - see varNames and rowData above.  
#'        When NULL (default), automatic splitting without needing a split string.
#' @param border Parameter to \code{{AutoSplit}} - see varNames and rowData above.
#' @param revBorder Parameter to \code{{AutoSplit}} - see varNames and rowData above..
#' @param freqName Input to \code{{Stack}}. The name of the new freqvar variable obtained when stacking in cases with several 
#'        input freqvar variables.
#' @param totalFirst Parameter controlling how output is sorted.
#' @param numericOrder Parameter controlling how output is sorted. 
#'        Output is character but sorting can be based on the numeric input variables.
#' @param namesAsInput When TRUE those output variables (created by unstacking) that correspond to input will be named as input. 
#' @param orderAsInput When TRUE output corresponding to input will be ordered as input and kept together as one block. 
#' @param sortByReversedColumns When TRUE output will be sorted by variables in opposite order. 
#' @param doUnstack When FALSE output will not be unstacked (in cases with sever input freqvar variables)
#' @param removeTotal When TRUE the total string (see total above) will be removed from the names of output variables 
#'        created by unstacking (in cases with sever input freqvar variables). 
#' @param singleOutput When TRUE output will be in as single data set. Default is FALSE for unstacked data  
#'        (in cases with sever input freqvar variables) and otherwise TRUE.
#' @param suppression Value used for suppressed elements in suppressed output data. Default is NA.
#' @param outFreq String used to name output variable(s)
#' @param outSdcStatus String used to name output variable(s)
#' @param outSuppressed String used to name output variable(s)
#' @param infoAsFrame When TRUE output element info is a data frame (useful in Shiny).
#' @param IncProgress A function to report progress (incProgress in Shiny). Set equal to NULL to turn it off.
#' @param verbose Parameter sent to \code{{protectTable}}, \code{{protect_linked_tables}} or \code{{runArgusBatchFile}}.  
#' @param ...  Further parameters sent to \code{{protectTable}} (possibly via \code{{protect_linked_tables}})
#'        such as timeLimit. 
#'        Parameters to  \code{{GaussSuppression}}, \code{{createArgusInput}} and \code{{PTwrap}} is also possible (see details).
#' 
#' @details One or two tables are identified automatically and subjected to cell suppression 
#'          by \code{{protectTable}} (single table) or \code{{protect_linked_tables}} (two linked tables).
#'          The tables can alternatively be specified manually by groupVarInd, ind1 and ind2.
#'          The output will be on a form similiar to input depending on whether freqVar is a single variable or not.
#'          The status of the cells are 
#'          coded as  "u" (primary suppressed), "x" (secondary suppression), and "s" (can be published).
#'          This is taken directly from the output from sdcTable. In cases with two linked tables "u" or "x" 
#'          for common cells are based on output from the first table.
#'          
#'  * **To run tau-argus** specify `method` as a named list containing the
#'          parameter `exe` for \code{{runArgusBatchFile}} and other parameters for 
#'          \code{{createArgusInput}}.  
#'    * One may specify:  
#'          \code{method = list(exe="C:/Tau/TauArgus.exe", typ="tabular", path= getwd(),} 
#'          \code{solver= "FREE", method= "OPT")}
#'          However these values of "exe", "path" and "solver" and "method" are set by default so in this case 
#'          using "\code{method = list(typ="tabular", method= "OPT")}" is equivalent.
#'    * If \code{typ="microdata"} is specified. Necessary transformation to microdata will be made. 
#'          
#'  * **Wrapper methods (partly experimental):**
#'          In the function \code{{PTwrap}} several additional methods are defined. 
#'          If input to ProtectTable() is one of these methods ProtectTable() will 
#'          be run via PTwrap(). So making explicit call to PTwrap() is not needed.
#'         
#'  * **Singleton and zeros:** The parameter detectSingletons was included in protecttable to handle the so-called 
#'  singleton problem that appers  when `protectZeros=FALSE`. 
#'  Not all problems were solved and the parameter threshold has been introduced later. The value of threshold 
#'  needed depends on the number of singletons in one group. It seems that `threshold=3` is equivalent to `detectSingletons=TRUE`. 
#'  When `protectZeros=TRUE` the related “zero problem” occurs. This problem is solved by `threshold=1`.  
#'          
#'  * **NOTE:** The use of numVarInd, weightInd and sampWeightInd in sdcTable is not implemented. This also limit possible 
#'          input to  tau-argus.
#'
#' @return When singleOutput=TRUE output is a list of two elements.
#' 
#' * **`info`:** Information as a single column character matrix. This is information about the extra 
#'                     dimVar variables created when stacking, information about the identified (linked) 
#'                     table(s) and summary output from sdcTable.
#'               With `method="Gauss"`, a sdcTable function is run with `maxN=0` to create a template for the real output. 
#'               Some of the summary info is therefore misleading in this case. 
#' * **`data`:** A data frame where variables are named according to outFreq, 
#'                     outSdcStatus and outSuppressed.
#'         When singleOutput=FALSE output element data is replaced by three elements and these are named  
#'         according to outFreq, outSdcStatus and outSuppressed.
#'         
#' @export
#' @importFrom SSBtools AutoSplit Stack SortRows Unstack GaussSuppression Extend0
#' @importFrom utils capture.output flush.console
#' @importFrom methods hasArg
#' @importFrom Matrix colSums
#' @importFrom stats aggregate
#' 
#' @note ProtectTable makes a call to the function \code{{ProtectTable1}}.
#' 
#' @seealso See also the vignettes.
#'
#'
#' @examples
#' \dontrun{
#' 
#'  # ==== Example 1 , 8 regions ====
#'  z1 <- EasyData("z1")        
#'  ProtectTable(z1,1:2, 3)
#'  ProtectTableData(z1,1:2, 3)
#'  ProtectTable(z1, c("region","hovedint"), "ant") # Input by name 
#'  # --- Unstacked input data ---
#'  z1w = EasyData("z1w") 
#'  ProtectTable(z1w, 1, 2:5)
#'  ProtectTableData(z1w, 1, 2:5)
#'  ProtectTable(z1w, 1, 2:5, varName="hovedint") 
#'  ProtectTable(z1w, 1, 2:5, method="HITAS")
#'  ProtectTable(z1w, 1, 2:5, totalFirst = TRUE, method ="Simple")
#'  
#'  # ==== Example 2 , 11 regions ====
#'  z2 <- EasyData("z2") 
#'  ProtectTable(z2,c(1,3,4), 5) # With region-variable kostragr
#'  # --- Unstacked input data ---
#'  z2w <- EasyData("z2w") 
#'  ProtectTable(z2w, 1:2, 4:7) # With region-variable fylke
#'  ProtectTable(z2w, 1:3, 4:7) # Two linked tables
#'  
#'  # ==== Example 3 , 36 regions ====
#'  z3 <- EasyData("z3")   
#'  ProtectTable(z3, c(1,4,5), 7)                               # Three dimensions. No subtotals    
#'  ProtectTable(z3, 1:6, 7)                                    # Two linked tables  
#'  # --- Unstacked input data with coded column names 
#'  z3w <- EasyData("z3w")
#'  ProtectTable(z3w,1:3,4:15, varName="g12")                   # coding not used when single varName
#'  ProtectTable(z3w,1:3,4:15, varName=c("hovedint","mnd"))     # Two variables found automatically 
#'  ProtectTable(z3w,1:3,4:15, varName=c("hovedint","mnd"),
#'                removeTotal=FALSE)                            # Keep "Total" in variable names 
#'  # --- Unstacked input data with three level column name coding
#'  z3wb <- EasyData("z3wb")  
#'  ProtectTable(z3wb,1:3,4:15,varName=c("hovedint","mnd","mnd2")) # Two variables found automatically
#'  ProtectTable(z3wb,1:3,4:15,varName=c("hovedint","mnd","mnd2"), 
#'              split="_")                                         # Three variables when splitting
#'  ProtectTable(z3wb,1:3,4:15,varName=c("hovedint","mnd","mnd2"),
#'                split="_",namesAsInput=FALSE,orderAsInput=FALSE) # Alternative ouput format
#'                
#'  # ====  Examples Tau-Argus ====              
#'  exeArgus <- "C:/TauArgus4.1.4/TauArgus.exe" # Change to TauArgus.exe-path in your computer
#'  pathArgus <- "C:/Users/nnn/Documents"       # Change to an existing folder 
#'  z1 = EasyData("z1") 
#'  ProtectTable(z1,1:2,3,method=list(exe=exeArgus, path=pathArgus, typ="tabular", method="OPT")) 
#'  ProtectTable(z1,1:2,3,method=list(exe=exeArgus, path=pathArgus, typ="tabular", method="MOD")) 
#'  ProtectTable(z1,1:2,3,method=list(exe=exeArgus, path=pathArgus, typ="tabular", method="GH"))
#'   ProtectTable(z1,1:2,3,maxN=-1,
#'    method=list(path=pathArgus, exe=exeArgus, method="OPT",
#'          primSuppRules= list(list(type="freq", n=4, rg=20))))
#'  z3 <- EasyData("z3")
#'  ProtectTable(z3,c(1:2,4,5),7,maxN=-1,
#'    method=list(path=pathArgus, exe=exeArgus, method="OPT",
#'          primSuppRules=list(list(type="freq", n=4, rg=20))))
#'          
#'                
#' # ==== Examples with parameter dimList  ====
#' z2 <- EasyData("z2")
#' dList <- FindDimLists(z2[-5])
#' ProtectTable(z2[, c(1,4,5)], 1:2, 3, dimList = dList[c(1,3)])
#' ProtectTable(z2[, c(1,4,5)], 1:2, 3, dimList = dList[2])
#' ProtectTable(z2[, c(1,4,5)], 1:2, 3, dimList = DimList2Hrc(dList[c(2,3)]))
#' }
#'               
ProtectTable  <-  function(data,
                         dimVar=1:NCOL(data),
                         freqVar=NULL,
                         protectZeros=TRUE,
                         maxN=3,
                         method="Gauss",
                         findLinked=TRUE,
                         total="Total",
                         addName=FALSE,
                         sep="_",
                         removeZeros=FALSE,
                         dimList = NULL,
                         groupVarInd=NULL,
                         ind1=NULL,
                         ind2=NULL, 
                         rowData=NULL,
                         varNames=paste("var",1:100,sep=""),
                         split=NULL,
                         border=sep,
                         revBorder=FALSE, 
                         freqName="values",
                         totalFirst=FALSE,
                         numericOrder=TRUE,
                         namesAsInput=TRUE,
                         orderAsInput=TRUE,
                         sortByReversedColumns=FALSE, 
                         doUnstack=TRUE,
                         removeTotal=TRUE,
                         singleOutput=NULL,   # eller TRUE/FALSE
                         suppression=NA,
                         outFreq="freq",
                         outSdcStatus="sdcStatus",
                         outSuppressed="suppressed",
                         infoAsFrame = FALSE,
                         IncProgress = IncDefault,
                         verbose = FALSE,
                         ...) {
  
  if (hasArg("allowZeros"))
    stop('Use "protectZeros" instead of "allowZeros"')
  
  if (hasArg("protectzeros"))
    stop('Misspelled parameter "protectzeros" found. Use "protectZeros".')
  
  if (hasArg("dimvar"))
    stop('Misspelled parameter "dimvar" found. Use "dimVar".')
  
  if (hasArg("freqvar"))
    stop('Misspelled parameter "freqvar" found. Use "freqVar".')
  
  if (hasArg("maxn"))
    stop('Misspelled parameter "maxn" found. Use "maxN".')
  
  
  # Inspired by
  # https://stackoverflow.com/questions/30528652/r-catch-message-return-result-efficiently
  Sms <- function(expr) {
    foo <- "foo"
    zz <- textConnection("foo", "w", local = TRUE)
    sink(zz, type = "message")
    res <- try(eval(expr))  
    sink(type = "message")
    close(zz)
    c(res,foo)
  }
  
  
  
  is_null_IncProgress <- is.null(IncProgress) 
  if (is_null_IncProgress){
    IncProgress <- function(){NULL}
  }
  IncProgress()
  tauArgus <- is.list(method)
  
  # START: New in easySdcTableGauss
  if(tauArgus)
    method <- '"tauArgus"'
  if(!(method %in% c("Gauss","GaussBasic", "GaussNoSingleton"))){
    warning(paste0('Input method "', method,'" ignored. Method set to "Gauss".'))
    tauArgus <- FALSE
    method = "Gauss"
  }
  # END: New in easySdcTableGauss 
  
  if(!tauArgus) 
    if(method %in% c("Simple","SimpleSingle", "SIMPLEHEURISTICSingle", "TauArgus","TauArgusOPT","TauArgusMOD","TauArgusGH")){
      sysCall <- sys.call()
      sysCall[[1]] <- as.name("PTwrap")
      parentFrame = parent.frame()
      return(eval(sysCall, envir=parentFrame))
    }
  
  if(!tauArgus) 
    doGaussSuppression <- grepl("Gauss",method)
  else
    doGaussSuppression <- FALSE 
    
  if(doGaussSuppression){
    if(!(method %in% c("Gauss","GaussBasic", "GaussNoSingleton")))
      stop(paste(method, "is not a valid method"))
  }
  
  if (is.character(dimVar)) 
    dimVarInd <- match(dimVar, names(data)) else dimVarInd <- dimVar
    if (is.character(freqVar)) 
      freqVarInd <- match(freqVar, names(data)) else freqVarInd <- freqVar
      
      tryAutoSplit <- (length(varNames) > 1)
      
      
      
      stacked <- FALSE
      if (length(freqVarInd) > 1) {
        stacked <- TRUE
        if (orderAsInput & !namesAsInput) 
          stop("orderAsInput=TRUE combined with namesAsInput=FALSE is not implemented")
        if (orderAsInput & !doUnstack) 
          warning("orderAsInput=TRUE ignored when doUnstack=FALSE")
        stackVar <- freqVarInd
        dataOrig <- data
        if (is.null(rowData)) 
          rowData <- AutoSplit(colnames(data)[freqVarInd], split = split, border = border, 
                               revBorder = revBorder, noSplit = !tryAutoSplit, varNames = varNames) else rownames(rowData) <- colnames(data)[freqVarInd]
        
        varNames <- colnames(rowData)
        data <- Stack(dataOrig, stackVar = freqVarInd, blockVar = dimVarInd, rowData = rowData, 
                      valueName = freqName, indName = NULL)
        colnamesOrig <- colnames(dataOrig)
        dimVarNamesOrig <- colnamesOrig[dimVarInd]
        dimVarNames <- c(dimVarNamesOrig, varNames)
        dimVarInd <- match(dimVarNames, colnames(data))  ######### New dimVarInd refer to stacked data
        freqVarInd <- match(freqName, colnames(data))  ######### New freqVarInd refer to stacked data
        
      }
      
      IncProgress()
      
     
      if (doGaussSuppression) {
        ProtectTable1parameterRemove <- function(threshold = NULL, detectSingletons = NULL, ...) {
          ProtectTable1(...)
        }
        
        pt <- ProtectTable1parameterRemove(data = data, dimVarInd = dimVarInd, freqVarInd = freqVarInd, protectZeros = FALSE, maxN = 0, method = "SIMPLEHEURISTIC", 
                                           findLinked = findLinked, total = total, addName = addName, sep = sep, removeZeros = removeZeros, dimList = dimList, groupVarInd = groupVarInd, 
                                           ind1 = ind1, ind2 = ind2, dimDataReturn = TRUE, IncProgress = IncProgress, verbose = verbose, ...)
        
        dimLists <- ProtectTable1dimList(data = data, dimVarInd = dimVarInd, freqVarInd = freqVarInd, protectZeros = FALSE, maxN = 0, method = "SIMPLEHEURISTIC", 
                                         findLinked = findLinked, total = total, addName = addName, sep = sep, removeZeros = removeZeros, dimList = dimList, groupVarInd = groupVarInd, 
                                         ind1 = ind1, ind2 = ind2, dimDataReturn = FALSE, IncProgress = IncProgress, verbose = verbose, ...)
      } else {
        
        pt <- ProtectTable1(data = data, dimVarInd = dimVarInd, freqVarInd = freqVarInd, protectZeros = protectZeros, maxN = maxN, method = method, 
                            findLinked = findLinked, total = total, addName = addName, sep = sep, removeZeros = removeZeros, dimList = dimList, groupVarInd = groupVarInd, 
                            ind1 = ind1, ind2 = ind2, dimDataReturn = TRUE, IncProgress = IncProgress, verbose = verbose, ...)
        
      }
      
      
      if(infoAsFrame){
          i00 <- as.data.frame(rbind(
                 ## c("method",method),
                 c("protectZeros",protectZeros),
                 c("maxN",maxN)
          ),stringsAsFactors=FALSE)
          if(!tauArgus) names(i00) <- c("method",method)   #c("Parameter","Choice")
          else names(i00) <- c("method","TauArgus")
          if (stacked) 
          i0 <- data.frame(InputName=rownames(rowData),as.data.frame(as.matrix(rowData),stringsAsFactors=FALSE),stringsAsFactors=FALSE) else i0 <- NULL
          i1 <- as.data.frame(as.matrix(pt$common$info),stringsAsFactors=FALSE)
          if(!tauArgus){
            i2 <- as.data.frame(Sms(capture.output(summary(pt$table1[[1]]))),stringsAsFactors=FALSE)
            names(i2) = "Summary1sdcTable"            
          } else {
            i2 <- as.data.frame(capture.output(print(method)),stringsAsFactors=FALSE)
            names(i2) = "TauArgus"            
          }   # i2 = NULL  
          if (!is.null(pt$table2[[1]])) {
            i3 <- as.data.frame(Sms(capture.output(summary(pt$table2[[1]]))),stringsAsFactors=FALSE)
            names(i3) = "Summary2sdcTable"
          } else i3 <- NULL
        info <- RbindAllwithNames(i00,i0,i1,i2,i3,toRight=TRUE,extra="= = =")
        colnames(info)[1] <- "Info"
      } else {
        if (stacked) 
          i0 <- capture.output(print(rowData)) else i0 <- NULL
      
        i1 <- capture.output(print(pt$common$info))
        if(!tauArgus){ 
          i2 <- Sms(capture.output(summary(pt$table1[[1]]))) ## Wrong in html Vignette without ""
        } else 
          i2 <- capture.output(print(method)) ## Wrong in html Vignette without ""
          #i2 = NULL  
        if (!is.null(pt$table2[[1]])) 
          i3 <- Sms(capture.output(summary(pt$table2[[1]]))) else i3 <- NULL
      
        info <- c(i0, "==========", i1, "==========", i2, "==========", i3)
        info <- as.matrix(info, ncol = 1)  # One element pr row when printed
      }
      
      gVC <- GroupVarCombined(pt$common$groupVarInd, totalFirst)
      
      nDim <- length(gVC)
      
      try( {    # Include in try as extra safety. Sorting can be omitted"
        sortedLists <- vector("list", nDim)
        names(sortedLists) <- names(gVC)
        for (i in seq_len(nDim)) {
          if(is.null(dimList)){
            if (numericOrder) 
              sortedLists[[i]] <- SortedFromData(pt$common$dimData, ind = gVC[[i]], 
                                                 total = total, xNumeric = data[, dimVarInd, drop = FALSE]) 
            else 
              sortedLists[[i]] <- SortedFromData(pt$common$dimData, ind = gVC[[i]], total = total)
          } else{
            sortedLists[[i]] <- SortedFromDimList(pt$table1$dimList[names(gVC)[i]][[1]],pt$table2$dimList[names(gVC)[i]][[1]])
          }
        }
      }, silent = TRUE)
      
      
      if (is.null(pt[[2]][[1]])) {
        if(!tauArgus){ 
          finalData <- as.data.frame(getInfo(pt[[1]][[1]], type = "finalData"))
        } else{
          finalData <- as.data.frame(pt[[1]][[1]])  ## Start treating tauArgus
          names(finalData)[names(finalData)=="freq"] <- "Freq"
          if(!is.null(finalData$cellvalue)){
            if(is.null(finalData$Freq)) finalData$Freq  <- finalData$cellvalue
            finalData$cellvalue <- NULL
          }
          if(!is.null(finalData$sdcStatus_argus)){
            finalData$sdcStatus  <- finalData$sdcStatus_argus
            finalData$sdcStatus_argus <- NULL
          }
        }                                          ## End treating tauArgus
      } else {
        t1 <- as.data.frame(getInfo(pt[[1]][[1]], type = "finalData"))
        t2 <- as.data.frame(getInfo(pt[[2]][[1]], type = "finalData"))
        if (dim(t1)[2] != dim(t2)[2]) 
          stop("Output from linked tables: Something is wrong!")
        
        b <- merge(t1, t2, all = TRUE, by = seq_len(dim(t1)[2] - 2), suffixes = c("", ".y"))
        
        if (max(abs(b$Freq - b$Freq.y), na.rm = TRUE) > (.Machine$double.eps)^(5/8)*max(abs(b$Freq + b$Freq.y), na.rm = TRUE))  
          stop("Output from protect_linked_tables: Something is wrong!")
        
        if (sum(abs(as.integer(b$sdcStatus == "s") - as.integer(b$sdcStatus.y == 
                                                                "s")), na.rm = TRUE) > 0) {
          b$sdcStatus[!is.na(b$sdcStatus) & b$sdcStatus.y == "s"] <- "s"
          warning("Non-unique suppression-output form protect_linked_tables")
        }
        
        if (sum(!(is.na(b$Freq) == is.na(b$sdcStatus))) > 0) 
          stop("Output from protect_linked_tables: Something is wrong!")
        
        nat1 <- is.na(b$Freq)
        b$sdcStatus[nat1] <- b$sdcStatus.y[nat1]
        b$Freq[nat1] <- b$Freq.y[nat1]
        
        finalData <- b[, !(colnames(b) %in% c("Freq.y", "sdcStatus.y")), drop = FALSE]
        
      }
      
      
      okSortTry = FALSE
      try( {    # Include in try as extra safety. Sorting can be omitted"
        
        if (sortByReversedColumns) 
          fd <- finalData[, rev(seq_len(nDim)), drop = FALSE] else fd <- finalData[, seq_len(nDim), drop = FALSE]
        for (i in seq_len(nDim)) {
          fd[, names(sortedLists)[i]] <- as.integer(factor(fd[, names(sortedLists)[i]], 
                                                         levels = sortedLists[[i]]))
        }
      
        if (sum(is.na(fd))) 
          stop("Something went wrong when sorting output")
      
      
        finalData <- finalData[SortRows(fd, index.return = TRUE), , drop = FALSE]
        okSortTry = TRUE
      }, silent = TRUE)
      
      if(!okSortTry)
        warning("Something went wrong when sorting output. Output is not sorted.")
      
      rownames(finalData) <- NULL
      
      suppressed <- finalData$Freq
      
      if(protectZeros)
        suppressed[!finalData$sdcStatus == "s"] <- suppression
      else
        suppressed[!(finalData$sdcStatus == "s" | finalData$sdcStatus == "z") ] <- suppression
      
      
      finalData$supp6547524 <- suppressed
      
      IncProgress()
      if (!is_null_IncProgress)
        cat("\n")
      
      attributes(finalData)$index <- NULL  # avoid attribute
      
  
      if (doGaussSuppression) {
        
        #  Code copied from PTxyz
        ptA <- finalData[, !(names(finalData) %in% c("Freq", "sdcStatus", "supp6547524")), drop = FALSE]
        
        
        if (is.null(freqVarInd)) {
          GetPrintInc <- function(printInc = TRUE, ...) {
            printInc
          }
          printInc <- GetPrintInc(...)
          if (printInc) {
            cat("[preAggregate ", dim(data)[1], "*", dim(data)[2], "->", sep = "")
            flush.console()
          }
          
          # These four lines is about aggregate. Other lines is about printing. 
          dVar <- names(dimLists)
          freqVar_ <- "f_Re_qVa_r"
          data <- aggregate(list(f_Re_qVa_r = data[[dVar[1]]]), data[, dVar, drop = FALSE], length)
          freqVarInd <- ncol(data)
          
          if (printInc) {
            cat(dim(data)[1], "*", dim(data)[2], "]\n", sep = "")
            flush.console()
          }
        }
        
        #xxx <- CrossTable2ModelMatrix(data[, c(freqVarInd, dimVarInd), drop = FALSE], ptA, dimLists)
        #xxx <- CrossTable2ModelMatrix(data[, dimVarInd, drop = FALSE], ptA, dimLists)
        xxx <- CrossTable2ModelMatrix(data, ptA, dimLists)
        
        rownames(xxx) <- apply(data[, names(data) %in% names(ptA), drop = FALSE], 1, paste, collapse = "_")
        colnames(xxx) <- apply(ptA, 1, paste, collapse = ":")
        
        yyy <- as.matrix(data[, freqVarInd, drop = FALSE])
        
        zzz <- as.matrix(Matrix::crossprod(xxx, yyy))
        
        GetCandidates <- function(candidates = NULL, ...) {
          candidates
        }
        
        candidates <- GetCandidates(...)
        
        primary <- (zzz <= maxN)[, 1, drop = TRUE]
        
        if (!protectZeros) 
          primary[zzz == 0] <- FALSE
        
        # Avoid warning in GaussSuppression: warning("Suppressed cells with empty input will not be protected. Extend input data with zeros?")
        if(any(primary))
        if(min(colSums(xxx[, primary, drop = FALSE])) == 0){
          colnames_xxx <- colnames(xxx)
          xxx <- CrossTable2ModelMatrix(Extend0(data[, (names(data) %in% names(dimLists))], hierarchical = FALSE), ptA, dimLists)
          colnames(xxx) <- colnames_xxx
          rownames(xxx) <- NULL
          yyy <- rbind(yyy, matrix(0, nrow(xxx) - nrow(yyy), ncol = 1))
        }
        
        if(is.null(candidates)){
          
          tie <- as.matrix(Matrix::crossprod(xxx, xxx %*% zzz))
          tie <- tie/max(tie)
          
          zzzOrd <- (zzz + 0.99 * tie)[, 1, drop = TRUE]
          if (!protectZeros) {
            zzzOrd[zzz == 0] <- 0.01 + max(zzzOrd) + zzzOrd[zzz == 0]
          }
          
          candidates <- order(zzzOrd, decreasing = TRUE)
          candidatesManually <- FALSE
        } else {
          warning('candidates specified manually. You may try: hidden="output" ')
          candidatesManually <- TRUE
        }
        
        
        if (protectZeros) {
          singleton <- (yyy == 0)[, 1, drop = TRUE]
        } else {
          singleton <- (yyy == 1)[, 1, drop = TRUE]
        }
        
        GetHidden <- function(hidden = NULL, ...) {
          hidden
        }
        
        hidden <- GetHidden(...)
        
        
        GetForced <- function(forced = NULL, ...) {
          forced
        }
        
        forced <- GetForced(...)
        
        if (is.character(hidden)) {
          input <- data[, c(dimVarInd, freqVarInd), drop = FALSE]
          if (hidden == "input") 
            return(input)
          output <- finalData[, !(names(finalData) %in% c("sdcStatus", "supp6547524")), drop = FALSE]
          if (hidden == "output") 
            return(output)
          if (hidden == "inputoutput") 
            return(list(input = input, output = output))
          stop(paste(hidden, "is not a valid as hidden"))
        }
        if(candidatesManually){
          if (method == "Gauss") 
            secondary <- GaussSuppression(x = xxx, primary = primary, singleton = singleton, ...)
          
          if (method == "GaussNoSingleton") 
            secondary <- GaussSuppression(x = xxx, primary = primary, ...)
        } else {
          if (method == "Gauss") 
            secondary <- GaussSuppression(x = xxx, candidates = candidates, primary = primary, singleton = singleton, ...)
          
          if (method == "GaussNoSingleton") 
            secondary <- GaussSuppression(x = xxx, candidates = candidates, primary = primary, ...)
        }
        
        
        if (method == "GaussBasic") {
          GetPrimary <- function(primary = integer(0), ...) {
            primary
          }
          primary <- GetPrimary(...)
          secondary <- GaussSuppression(x = xxx, ...)
        }
        
        
        if (length(hidden)) {
          finalData$sdcStatus[hidden] <- "h"
          finalData$supp6547524[hidden] <- suppression
        }
        
        finalData$sdcStatus[primary] <- "u"
        finalData$sdcStatus[secondary] <- "x"
        finalData$sdcStatus[forced] <- "z"
        
        
        if (length(forced)) {
          finalData$sdcStatus[forced] <- "z"
        }
        
        
        finalData$supp6547524[primary] <- suppression
        finalData$supp6547524[secondary] <- suppression
        
      }
      
      
      if(get0("doReturnExtraFinalData",ifnotfound = FALSE))
        extraFinalData <- list(inputData=data[,c(freqVarInd, dimVarInd),drop=FALSE],finalData=finalData)
      
      
      
      if (stacked & doUnstack) {
        if (is.null(singleOutput)) 
          singleOutput <- FALSE
        
        mainVar1 <- match("Freq", names(finalData))
        mainVar2 <- match("sdcStatus", names(finalData))
        mainVar3 <- match("supp6547524", names(finalData))
        
        stackVar <- match(varNames, names(finalData))
        stackVar <- stackVar[!is.na(stackVar)]
        
        stackVarNames <- names(finalData)[stackVar]
        
        blockVar <- match(dimVarNamesOrig, names(finalData))
        blockVar <- blockVar[!is.na(blockVar)]
        
        
        
        x1 <- Unstack(finalData, mainVar = mainVar1, stackVar = stackVar, blockVar = blockVar, 
                      sep = sep)
        
        
        
        x2 <- Unstack(finalData, mainVar = mainVar2, stackVar = stackVar, blockVar = blockVar, 
                      sep = sep)
        
        x3 <- Unstack(finalData, mainVar = mainVar3, stackVar = stackVar, blockVar = blockVar, 
                      sep = sep)
        
        
        if (namesAsInput) {
          w <- rbind(cbind(a12345645 = 1, rowData), cbind(a12345645 = 1, rowData))
          ww <- Unstack(w, stackVar = match(stackVarNames, names(w)), sep = sep)$rowData
          w2 <- cbind(outputNames = rownames(ww), ww, stringsAsFactors = FALSE)
          w1 <- cbind(inputNames = rownames(rowData), rowData, stringsAsFactors = FALSE)
          namesFrame <- merge(w1, w2)
          
          indNames <- match(namesFrame$outputNames, colnames(x1$data))
          indNames2 <- match(namesFrame$outputNames, colnames(x2$data))
          indNames3 <- match(namesFrame$outputNames, colnames(x3$data))
          
          
          if (sum(as.integer(indNames != indNames2))) 
            stop("Problems with namesAsInput")
          if (sum(as.integer(indNames != indNames3))) 
            stop("Problems with namesAsInput")
          
          colnames(x1$data)[indNames] <- namesFrame$inputNames
          colnames(x2$data)[indNames] <- namesFrame$inputNames
          colnames(x3$data)[indNames] <- namesFrame$inputNames
        }
        
        if (orderAsInput) {
          
          namesOrig <- dimVarNamesOrig[dimVarNamesOrig %in% names(gVC)]
          
          rInput <- unique(apply(CharacterDataFrame(dataOrig[, namesOrig, drop = FALSE]), 
                                 1, paste, collapse = "_"))
          rOutput <- apply(x1$data[, namesOrig, drop = FALSE], 1, paste, collapse = "_")
          rI <- match(rInput, rOutput)
          rI <- rI[!is.na(rI)]
          rAll <- seq_len(length(rOutput))
          rO <- rAll[!(rAll %in% rI)]
          if (totalFirst) 
            rr <- c(rO, rI) else rr <- c(rI, rO)
          
          cI <- match(colnames(dataOrig), colnames(x1$data))
          cI <- cI[!is.na(cI)]
          cAll <- seq_len(length(colnames(x1$data)))
          cO <- cAll[!(cAll %in% cI)]
          if (totalFirst) 
            cc <- c(cO, cI) else cc <- c(cI, cO)
          
          x1$data <- x1$data[rr, cc, drop = FALSE]
          x2$data <- x2$data[rr, cc, drop = FALSE]
          x3$data <- x3$data[rr, cc, drop = FALSE]
          rownames(x1$data) <- NULL
          rownames(x2$data) <- NULL
          rownames(x3$data) <- NULL
        }
        
        if (removeTotal) {
          colnames(x1$data) <- RemoveTotal(colnames(x1$data), total = total, sep = sep)
          colnames(x2$data) <- RemoveTotal(colnames(x2$data), total = total, sep = sep)
          colnames(x3$data) <- RemoveTotal(colnames(x3$data), total = total, sep = sep)
        }
        
        if (!singleOutput) {
          output <- list(info = info, x1 = x1$data, x2 = x2$data, x3 = x3$data)
          names(output) <- c("info", outFreq, outSdcStatus, outSuppressed)
        } else {
          bv <- seq_len(NCOL(x1$data)) %in% seq_len(length(blockVar))
          block <- x1$data[, bv, drop = FALSE]
          x1 <- x1$data[, !bv, drop = FALSE]
          x2 <- x2$data[, !bv, drop = FALSE]
          x3 <- x3$data[, !bv, drop = FALSE]
          names(x1) <- paste(outFreq, names(x1), sep = sep)
          names(x2) <- paste(outSdcStatus, names(x2), sep = sep)
          names(x3) <- paste(outSuppressed, names(x3), sep = sep)
          output <- list(info = info, data = cbind(block, x1, x2, x3))
        }
        if(get0("doReturnExtraFinalData",ifnotfound = FALSE))
          output <- c(output,extraFinalData)
        return(output)
      }
      if (is.null(singleOutput)) 
        singleOutput <- TRUE
      
      if (!stacked & orderAsInput) {
        # Fungerer ikke å ha denne før unstack
        rInput <- unique(apply(pt$common$dimData[, names(gVC), drop = FALSE], 1, 
                               paste, collapse = "_"))
        rOutput <- apply(finalData[, names(gVC), drop = FALSE], 1, paste, collapse = "_")
        rI <- match(rInput, rOutput)
        rI <- rI[!is.na(rI)]
        rAll <- seq_len(length(rOutput))
        rO <- rAll[!(rAll %in% rI)]
        
        if (totalFirst) 
          finalData <- finalData[c(rO, rI), , drop = FALSE] else finalData <- finalData[c(rI, rO), , drop = FALSE]
        rownames(finalData) <- NULL
      }
      
      names(finalData)[match(c("Freq", "sdcStatus", "supp6547524"), names(finalData))] <- c(outFreq, 
                                                                                            outSdcStatus, outSuppressed)
      
      
      if (singleOutput) 
        output <- list(info = info, data = finalData) else {
          output <- list(info = info, x1 = finalData[, !(names(finalData) %in% c(outSdcStatus, 
                                                                                 outSuppressed))], x2 = finalData[, !(names(finalData) %in% c(outFreq, 
                                                                                                                                              outSuppressed))], x3 = finalData[, !(names(finalData) %in% c(outFreq, 
                                                                                                                                                                                                           outSdcStatus))])
          names(output) <- c("info", outFreq, outSdcStatus, outSuppressed)
        }
      if(get0("doReturnExtraFinalData",ifnotfound = FALSE))
        output <- c(output,extraFinalData) 
      return(output)
}


#' @rdname ProtectTable
#' @export
ProtectTableData <- function(data, ...) {
  ProtectTable(data, ..., singleOutput = TRUE)$data
}



GroupVarCombined <- function(x, reverse = FALSE) {
  l <- sapply(x, length)
  ml <- max(l)
  naml <- rep(NA, ml)
  for (i in 1:length(x)) x[[i]] <- c(x[[i]], naml)[seq_len(ml)]
  un <- unique(names(x))
  z <- vector("list", length(un))
  names(z) <- un
  for (i in seq_len(length(un))) {
    z[[i]] <- unique(as.vector(t(as.matrix(data.frame(x[names(x) == un[i]])))))
    z[[i]] <- c(z[[i]][!is.na(z[[i]])], 0)  # 0 as total code
    if (reverse) 
      z[[i]] <- rev(z[[i]])
  }
  z
}



if (FALSE) {
  # Generering av testdata
  z <- EasyData("sosialFiktiv")
  z8 <- z[z$fylke <= 10 & z$kostragr == 300, ]  # 8 regions
  
  z11 <- z[z$fylke <= 10 & (z$kostragr == 300 | z$kostragr == 400), ]  # 11 regions
  
  z8$kostragr <- "A"
  z8$kostragr[z8$region %in% c(43200, 51400, 62000, 83400)] <- "B"
  z36 <- z[z$fylke >= 11 & z$fylke <= 14 & z$kostragr <= 500, ]  # 36 regions
  
  z1 <- Unstack(z8, mainVar = match("ant", names(z8)), stackVar = match(c("hovedint"), 
                                                                        names(z8)), blockVar = match(c("region"), names(z8)))
  
  z2 <- Unstack(z11, mainVar = match("ant", names(z8)), stackVar = match(c("hovedint"), 
                                                                         names(z8)), blockVar = match(c("region", "fylke", "kostragr"), names(z8)))
  
  
  x1 <- aggregate(z1$data[, 2:5], list(region = z1$data$region), sum)
  x2 <- aggregate(z2$data[, 4:7], list(region = z2$data$region, fylke = z2$data$fylke, 
                                       kostragr = z2$data$kostragr), sum)
  y1 <- aggregate((z8[, 7]), list(region = z8$region, hovedint = z8$hovedint), 
                  sum)
  y2 <- aggregate((z11[, 7]), list(region = z11$region, fylke = z11$fylke, kostragr = z11$kostragr, 
                                   hovedint = z11$hovedint), sum)
  names(y1)[3] <- "ant"
  names(y2)[5] <- "ant"
  
  y3 <- z36
  mnd <- gsub("_", "m", y3$mnd)
  mnd <- gsub("6", "06", mnd)
  mnd <- gsub("9", "09", mnd)
  mnd <- gsub("1m", "01m", mnd)
  mnd <- gsub("5", "05", mnd)
  mnd <- paste("m", mnd, sep = "")
  y3$mnd <- mnd
  mnd <- gsub("-", "M", y3$mnd2)
  mnd <- gsub("6", "06", mnd)
  mnd <- gsub("1M", "01M", mnd)
  mnd <- gsub("5", "05", mnd)
  mnd <- paste("M", mnd, sep = "")
  y3$mnd2 <- mnd
  
  y3Unstack <- Unstack(y3, mainVar = match("ant", names(y3)), stackVar = match(c("hovedint", 
                                                                                 "mnd"), names(y3)), extraVar = match(c("mnd2"), names(y3)), blockVar = match(c("region", 
                                                                                                                                                                "fylke", "kostragr"), names(y3)))
  
  x3 <- y3Unstack$data
  
  
  x3b <- x3
  names(x3b)[4:15] <- paste(names(x3)[4:15], y3Unstack$rowData[, 3], sep = "_")
  
  ind <- NULL
  for (i in 1:NROW(y1)) ind <- c(ind, rep(i, y1$ant[i]))
  y1micro <- y1[ind, ]
  
  
  # rename and save
  if (FALSE) {
    z1 <- y1
    z1micro <- y1micro
    z2 <- y2
    z3 <- y3
    z1w <- x1
    z2w <- x2
    z3w <- x3
    z3wb <- x3b
    save(z1, file = "C:/R/easysdctable/data/z1.RData")
    save(z1micro, file = "C:/R/easysdctable/data/z1micro.RData")
    save(z2, file = "C:/R/easysdctable/data/z2.RData")
    save(z3, file = "C:/R/easysdctable/data/z3.RData")
    save(z1w, file = "C:/R/easysdctable/data/z1w.RData")
    save(z2w, file = "C:/R/easysdctable/data/z2w.RData")
    save(z3w, file = "C:/R/easysdctable/data/z3w.RData")
    save(z3wb, file = "C:/R/easysdctable/data/z3wb.RData")
  }
}




SortedFromDimList <- function(dimList1, dimList2 = NULL) {
  if (!is.null(dimList2)) {
    dimList <- rbind(dimList1, dimList2)
    return(unique(dimList[order(c(-5 * as.integer(factor(dimList1$levels)), -4 * 
                                    as.integer(factor(dimList2$levels))), c(dimList1$codes, dimList2$codes)), ])[, 2])
  }
  return(unique(dimList1[order(c(-5 * as.integer(factor(dimList1$levels))), c(dimList1$codes)), ])[, 2])
}

uniqueIndex <- function(x, ordered = FALSE) {
  ui <- seq_len(length(x))[!duplicated(x)]
  if (!ordered) 
    return(ui)
  ui[order(x[ui])]
}

SortedFromData <- function(xCharacter, ind, total, xNumeric = NULL) {
  z <- NULL
  for (i in ind) {
    if (i == 0) 
      x <- total else {
        if (!is.null(xNumeric)) 
          ui <- uniqueIndex(xNumeric[, i], ordered = TRUE) else ui <- uniqueIndex(xCharacter[, i], ordered = TRUE)
          x <- xCharacter[ui, i]
      }
    z <- c(z, x)
  }
  z
}

CharacterDataFrame <- function(x) {
  for (i in seq_len(NCOL(x))) x[, i] <- as.character(x[, i])
  x
}

RemoveTotal <- function(x, total = "Total", sep = "_") {
  x <- gsub(paste(total, sep, sep = ""), "", x)
  gsub(paste(sep, total, sep = ""), "", x)
}
 
##### --- ProtectTable1.R ---
#####################################
#'  Only-Gauss replacement function for easySdcTable::ProtectTable1
#'
#' protectTable or protect_linked_tables is run with a data set at the only required input.
#'
#' @encoding UTF8
#'
#' @param data Matrix or data frame
#' @param dimVarInd Column-indices of the main dimensional variables and additional aggregating variables.
#' @param freqVarInd Column-indices of a variable holding counts or NULL in the case of micro data.
#' @param protectZeros When TRUE empty cells (count=0) is considered sensitive (i.e. same as allowZeros in primarySuppression).
#' @param maxN All cells having counts <= maxN are set as primary suppressed.
#' @param method Parameter "method" in protectTable or protect_linked_tables.
#'               Alternatively a list defining parameters for running tau-argus (see \code{{ProtectTable}}).
#' @param findLinked When TRUE, the function may find two linked tables and run protect_linked_tables.
#' @param total String used to name totals.
#' @param addName When TRUE the variable name is added to the level names, except for variables with most levels.
#' @param sep A character string to separate when addName apply.
#' @param removeZeros When TRUE, rows with zero count will be removed from the data.
#' @param dimList See \code{{ProtectTable}}.
#' @param groupVarInd Possible manual specification if list defining the hierarchical variable groups
#' @param ind1  Coding of table 1 as indices referring to elements of groupVarInd
#' @param ind2  Coding of table 2 as indices referring to elements of groupVarInd
#' @param dimDataReturn When TRUE a data frame containing the dimVarInd variables is retuned
#' @param IncProgress A function to report progress (incProgress in Shiny).
#' @param verbose Parameter sent to protectTable, protect_linked_tables or runArgusBatchFile. 
#' @param ... Further parameters sent to protectTable, protect_linked_tables or createArgusInput.
#'
#' @details One or two tables are identified automatically and subjected to cell suppression methods in package sdcTable.
#'          The tables can alternatively be specified manually by groupVarInd, ind1 and ind2 (see \code{{FindTableGroup}}).
#'
#' @return Output is a list of three elements.
#'
#'         \strong{table1} consists of the following elements:
#'         \item{secondary}{Output from \code{{protectTable}} or first element of output from \code{{protect_linked_tables}} 
#'         or output from \code{{runArgusBatchFile}}.}
#'         \item{primary}{Output from \code{{primarySuppression}}.}
#'         \item{problem}{Output from \code{{makeProblem}}.}
#'         \item{dimList}{Generated input to makeProblem.}
#'         \item{ind}{Indices referring to elements of groupVarInd in the output element common.}
#'
#'         \strong{table2} consists of elements of the same type as table1 in cases of two linked tables. Otherwise  table2 is NULL.
#'
#'         \strong{common} consists of the following elements:
#'         \item{commonCells}{Input to protect_linked_tables.}
#'         \item{groupVarInd}{List defining the hierarchical variable groups}
#'         \item{info}{A table summarizing the tables using variable names}
#'         \item{nLevels}{The number of levels of each variable (only when groupVarInd input is NULL)}
#'         \item{dimData}{Data frame containing the dimVarInd variables when dimDataReturn=TRUE. Otherwise NULL.}
#'
#' @export
#' @importFrom SSBtools FindTableGroup FindDimLists FindCommonCells FactorLevCorr MakeMicro
#'
#' @seealso \code{{ProtectTable}}, 
#'         \code{{HierarchicalGroups}}, \code{{FactorLevCorr}},
#'         \code{{FindDimLists}}, \code{{FindCommonCells}}
#'         
#' @noMd         
#'
#' @examples
#' \dontrun{
#' z2 <- EasyData("z2")
#' a <- ProtectTable1(z2, c(1, 3, 4), 5)
#' head(as.data.frame(getInfo(a[[1]][[1]], type = "finalData"))) # The table (not linked)
#' 
#' z3 <- EasyData("z3")
#' b <- ProtectTable1(z3, 1:6, 7)
#' head(as.data.frame(getInfo(b[[1]][[1]], type = "finalData"))) # First table
#' head(as.data.frame(getInfo(b[[2]][[1]], type = "finalData"))) # Second table
#' }
ProtectTable1 <- function(data, dimVarInd = 1:NCOL(data), freqVarInd = NULL, protectZeros = TRUE, 
                          maxN = 3, method = "SIMPLEHEURISTIC", findLinked = TRUE, total = "Total", addName = FALSE, 
                          sep = ".", removeZeros = FALSE, 
                          dimList = NULL,
                          groupVarInd = NULL, ind1 = NULL, ind2 = NULL, 
                          dimDataReturn = FALSE, 
                          IncProgress = IncDefault,
                          verbose = FALSE, 
                          ...) {
  tauArgus <- is.list(method)
  makeMicro = FALSE
  
  if(tauArgus){
    exeTauArgus <- method$exe
    method$exe <- NULL
    if(is.null(exeTauArgus)) exeTauArgus  <- formals(runArgusBatchFile)$exe # "C:\\Tau\\TauArgus.exe"
    if(is.null(method$typ))    method$typ <- formals(createArgusInput)$typ  #  "microdata"
    if(!(method$typ %in% c("microdata","tabular")))
      stop('typ must be "microdata" or "tabular"')
    if(method$typ == "microdata") makeMicro = TRUE
  }  
  
  if(maxN>=0) primarySupp <- primarySuppression 
  else primarySupp <- function(...) NULL # Possible to ignore primarySuppression
  
  
  allowZeros <- protectZeros
  methodLinked <- method
  if (removeZeros & !is.null(freqVarInd)) 
    data <- data[data[, freqVarInd] > 0, , drop = FALSE]
  
  if (is.null(groupVarInd)) {
    fCorr <- FactorLevCorr(data[, dimVarInd, drop = FALSE])
    nLevels <- diag(fCorr)
    tableGroup <- FindTableGroup(findLinked = findLinked, fCorr = fCorr, CheckHandling = stop)
    groupVarInd <- tableGroup$groupVarInd
    ind1 <- tableGroup$table$ind1
    if (length(tableGroup$table) > 1) 
      ind2 <- tableGroup$table$ind2 else ind2 <- NULL
  } else {
    if (is.null(ind1)) 
      stop("ind1 is needed when groupVarInd is in input")
    nLevels <- NULL
  }
  
  
  linked <- !is.null(ind2)
  
  dimLists <- FindDimLists(data[, dimVarInd, drop = FALSE], groupVarInd = groupVarInd, 
                           addName = addName, sep = sep, total = total, xReturn = dimDataReturn)
  

  if (dimDataReturn) {
    dimData <- dimLists$x
    dimLists <- dimLists$dimLists
  } else dimData <- NULL
  
  
  if(!is.null(dimList)){
    dimLists <- ReplaceDimList(dimLists, dimList, total = total)
  }
  
  
  dimList1 <- dimLists[ind1]
  
  if(makeMicro){ 
    data <- MakeMicro(data,freqVarInd)
    freqVarInd <- NULL
  }
  
  IncProgress()
  
  
  problem1 <- makeProblem(data = data, dimList = dimList1, dimVarInd = match(names(dimList1), 
                                                                               colnames(data)), freqVarInd = freqVarInd)
  

  
  primary1 <- primarySupp(problem1, type = "freq", maxN = maxN, allowZeros = allowZeros)
  if(get0("doPrintDimLists",ifnotfound = FALSE)){
    print(dimList1)
    flush.console()
  }  
  
  
  if (linked) {
    if(tauArgus) stop("tauArgus with linked tables is not implemented")
    dimList2 <- dimLists[ind2]
    problem2 <- makeProblem(data = data, dimList = dimList2, dimVarInd = match(names(dimList2), 
                                                                               colnames(data)), freqVarInd = freqVarInd)
    primary2 <- primarySupp(problem2, type = "freq", maxN = maxN, allowZeros = allowZeros)
    commonCells <- FindCommonCells(dimList1, dimList2)
    IncProgress()
    secondary <- protect_linked_tables(x = primary1, y = primary2, common_cells = commonCells, method = methodLinked, verbose = verbose, ...)
    if(get0("doPrintDimLists",ifnotfound = FALSE)){
      print(dimList2)
      print(commonCells)
      flush.console()
    }
  } else {
    
    
    ind2 <- NULL
    dimList2 <- NULL
    problem2 <- NULL
    primary2 <- NULL
    commonCells <- NULL
    IncProgress()
    if(!tauArgus){
      
      secondary <- list(protectTable(object = primary1, method = method, verbose = verbose, ...), NULL)
      
    } else {  
      ## tauArgus start here
      optionsUseFancyQuotes <- options("useFancyQuotes") 
      options(useFancyQuotes=FALSE)  # In .onAttach() in sdcTable
      if(method$typ == "microdata"){
        batchF <- eval(as.call(c(as.name("createArgusInput"),obj=as.name("problem1"),method, verbose = verbose, ...)))
        if(get0("waitForAKeyPress",ifnotfound = FALSE)) invisible(readline(prompt="Press [enter] to continue"))
        secondary <- list(runArgusBatchFile(obj=problem1, batchF = batchF, exe = exeTauArgus, verbose = verbose), NULL)
      }
      else{  # Same as above with primary1 instead of problem1
        batchF <- eval(as.call(c(as.name("createArgusInput"),obj=as.name("primary1"),method, verbose = verbose, ...)))
        if(get0("waitForAKeyPress",ifnotfound = FALSE)) invisible(readline(prompt="Press [enter] to continue"))
        secondary <- list(runArgusBatchFile(obj=primary1, batchF = batchF, exe = exeTauArgus, verbose = verbose), NULL)
      }
      options(optionsUseFancyQuotes)
    }
  }
  
  
  x <- groupVarInd
  for (i in 1:length(x)) x[[i]] <- paste((colnames(data)[dimVarInd])[x[[i]]], collapse = ", ")
  x <- cbind(as.data.frame(as.character(unlist(x))), 0, 0)
  colnames(x) <- c("Variables", "Table1", "Table2")
  x[ind1, 2] <- 1
  if (linked) 
    x[ind2, 3] <- 1
  
  return(list(table1 = list(secondary = secondary[[1]], primary = primary1, problem = problem1, 
                            dimList = dimList1, ind = ind1), table2 = list(secondary = secondary[[2]], 
                                                                           primary = primary2, problem = problem2, dimList = dimList2, ind = ind2), 
              common = list(commonCells = commonCells, groupVarInd = groupVarInd, info = x, 
                            nLevels = nLevels, dimData = dimData)))
}

 
##### --- PTxyz.R ---
#####################################
#' ProtectTable with output ready for SuppressDec in package RegSDC
#' 
#' Assuming correct suppression, suppressed values become decimal numbers (not whole numbers) instead of missing.
#' 
#' Within this r package this function will be used for testing
#' 
#'
#' @param data data frame
#' @param dimVar The main dimensional variables and additional aggregating variables (name or number).
#' @param freqVar Variable(s) holding counts (name or number).
#' @param ... Further parameters sent to \code{\link{ProtectTable}} 
#'
#' @return List of three matrices ready as input to \code{SuppressDec}
#' \item{x}{Sparse dummy matrix where the dimensions match z and y.}
#' \item{z}{Frequencies to be published with suppressed as NA.}
#' \item{y}{Inner cell frequencies.}
#'  
#' @importFrom SSBtools AutoHierarchies FactorLevCorr FindTableGroup FindDimLists HierarchyComputeDummy
#' @export
#' @author Øyvind Langsrud
#'
#' @examples
#' \dontrun{
#' 
#' # Same examples as in ProtectTable 
#' a1 <- PTxyz(EasyData("z1"), c("region","hovedint") ,"ant")
#' a2 <- PTxyz(EasyData("z2"), c(1,3,4),5) 
#'  
#' if (require(RegSDC)) { # RegSDCdata and SuppressDec
#'   # Same data as in RegSDCdata examples (and in paper)
#'   data7 <- RegSDCdata("sec7data")
#'   data7 <- data7[!is.na(data7$y), 1:3]
#'   data7
#' 
#'   # Generate x, y, z similar to xAll, y, zAllSupp in RegSDCdata examples 
#'   # But different suppressed cells and z ordered differently
#'   a <- PTxyz(data7, 1:2, 3, maxN = 3, method = "HITAS")
#'   a
#' 
#'   # Suppressed inner cells as decimal numbers
#'   yDec <- SuppressDec(a$x, a$z, a$y, rmse = 1)
#'   yDec
#' 
#'   # All cells as decimal numbers
#'   cbind(a$z, t(a$x) %*% cbind(a$y, yDec))
#' 
#'   # As ProtectTable example
#'   z1 <- EasyData("z1")
#'   a <- PTxyz(z1, c("region", "hovedint"), "ant")
#' 
#'   # Inner cells as decimal numbers. 3 replicates.
#'   yDec <- SuppressDec(a$x, a$z, a$y, nRep = 3)
#'   yDec
#' 
#'   # All cells with 3 replicates.
#'   cbind(a$z, t(a$x) %*% cbind(a$y, yDec))
#' }
#' 
#' if (require(RegSDC)) {
#'   # An example involving two linked tables.  
#'   # It is demonstrated that the SIMPLEHEURISTIC approach to suppression is not safe.  
#'   # That is, perfect fit (whole numbers) for some suppressed cells.
#'   a <- PTxyz(EasyData("z3"), 1:5, 7, method = "SIMPLEHEURISTIC", protectZeros= FALSE)
#'   cbind(a$z, t(a$x) %*% cbind(a$y, SuppressDec(a$x, a$z, rmse=pi/3, nRep=3)))[which(is.na(a$z)), ]
#' }}
PTxyz <- function(data, dimVar, freqVar, ...) {
  
  systemTime <- hasArg("systemTime")
  
  if (length(freqVar) != 1)
    stop("Only a single freVar allowed in this implementation")
  
  # Generate dimList as in ProtectTable. So this is done twice in this implementation.
  dimLists <- ProtectTable1dimList(data, dimVar, freqVar, ...)
  
  if (systemTime) {
    system_time <- system.time({
      pt <- ProtectTable(data, dimVar, freqVar, ...)
    })
  } else {
    pt <- ProtectTable(data, dimVar, freqVar, ...)
  }
  
  freqVar <- names(data[1, freqVar, drop = FALSE])
  
  varNames <- unique(names(dimLists))
  ptA <- pt$data[, !(names(pt$data) %in% c("freq", "sdcStatus", "suppressed")), drop = FALSE]
  
  x <- CrossTable2ModelMatrix(data, ptA, dimLists)
  
  rownames(x) <- apply(data[, names(data) %in% names(ptA), drop = FALSE], 1, paste, collapse = "_")
  colnames(x) <- apply(ptA, 1, paste, collapse = ":")
  y <- as.matrix(data[, freqVar, drop = FALSE])
  z <- as.matrix(pt$data[, "suppressed", drop = FALSE])
  rownames(z) <- colnames(x)
  rownames(y) <- rownames(x)
  
  if (systemTime) {
    return(list(x = x, y = y, z = z, system_time = system_time))
  }
  list(x = x, y = y, z = z)
}


CrossTable2ModelMatrix <- function(data, crossTable, hierarchies = NULL, total = "Total", 
                                   hierarchyVarNames = c(mapsFrom = "mapsFrom", mapsTo = "mapsTo", sign = "sign", level = "level"), 
                                   unionComplement = FALSE) {
  cNames <- colnames(crossTable)
  if (!is.null(hierarchies)) 
    cNames <- cNames[!(cNames %in% names(hierarchies))]
  ncNames <- length(cNames)
  if (ncNames > 0) {
    lNames <- as.list(rep(total, ncNames))
    names(lNames) <- cNames
    hierarchies <- c(hierarchies, lNames)
  }
  
  Hierarchies2ModelMatrixNew(data = data, hierarchies = hierarchies, total = total, hierarchyVarNames = hierarchyVarNames, 
                             unionComplement = unionComplement, inputCrossTable = crossTable)
}

# Copy of part of ProtectTable1 used to generate dimList
ProtectTable1dimList <- function(data, dimVarInd = 1:NCOL(data), freqVarInd = NULL, findLinked = TRUE, total = "Total", 
                                 addName = FALSE, sep = ".", dimList = NULL, groupVarInd = NULL, 
                                 dimDataReturn = FALSE, ...) {
  
  if (is.null(groupVarInd)) {
    fCorr <- FactorLevCorr(data[, dimVarInd, drop = FALSE])
    nLevels <- diag(fCorr)
    tableGroup <- FindTableGroup(findLinked = findLinked, fCorr = fCorr, CheckHandling = stop)
    groupVarInd <- tableGroup$groupVarInd
  }
  
  dimLists <- FindDimLists(data[, dimVarInd, drop = FALSE], groupVarInd = groupVarInd, addName = addName, 
                           sep = sep, total = total, xReturn = dimDataReturn)
  
  if (!is.null(dimList)) {
    dimLists <- ReplaceDimList(dimLists, dimList, total = total)
  }
  dimLists
}


# Hierarchies2ModelMatrix with inputCrossTable as new parameter
Hierarchies2ModelMatrixNew <- function(data, hierarchies, inputInOutput = TRUE, crossTable = FALSE, total = "Total", 
                                       hierarchyVarNames = c(mapsFrom = "mapsFrom", mapsTo = "mapsTo", sign = "sign", level = "level"), 
                                       unionComplement = FALSE, inputCrossTable = NULL) {
  autoHierarchies <- AutoHierarchies(hierarchies = hierarchies, data = data, total = total, hierarchyVarNames = hierarchyVarNames)
  HierarchyComputeDummy(data = data, hierarchies = autoHierarchies, inputInOutput = inputInOutput, crossTable = crossTable, 
                        unionComplement = unionComplement, rowSelect = inputCrossTable)
}







if (FALSE) {
  # To obtain exact same suppression as in paper
  exeArgus <- "C:/TauArgus4.1.4/TauArgus.exe"
  pathArgus <- "C:/Users/oyl/Documents/back/tull"
  a <- PTxyz(data7, 1:2, 3, maxN = -1, 
             method = list(path = pathArgus, exe = exeArgus, method = "OPT", primSuppRules = list(list(type = "freq", n = 4, rg = 20))))
  ma <- match(colnames(RegSDCdata("sec7xAll")), colnames(a$x))
  all.equal(a$y[, 1], RegSDCdata("sec7y")[, 1])  # TRUE
  max(abs(a$x[, ma] - RegSDCdata("sec7xAll")))  # 0
  all.equal(a$z[ma, 1], RegSDCdata("sec7zAllSupp")[, 1])  # TRUE
}





 
##### --- RbindAllwithNames.R ---
#####################################

# Special version of RbindAll in SSBtools used when infoAsFrame = TRUE in protectTable

RbindAllwithNames <- function(...,toRight=FALSE,extra=""){
  x = list(...)
  sap = sapply(x,is.null)
  if(any(sap)) x = x[!sap]
  for(i in seq_len(length(x))){
    c1 = colnames(x[[i]])
    c2 = c1
    c2[] = extra
    a = rbind(c1,x[[i]],c2)
    if(toRight) a = a[rev(seq_len(NCOL(a)))]
    colnames(a) = NULL
    rownames(a) = NULL
    colnames(a) = colnames(a, do.NULL=FALSE) 
    x[[i]] = a
  }
  a = RbindAllnoNA(x)
  if(toRight){
    a = a[rev(seq_len(NCOL(a)))]
  }
  colnames(a)[] =""
  a
}


RbindAllnoNA <- function(...){
  x = list(...)
  if(length(x)==1) # Handle list input
    if(is.list(x[[1]]))
      if(!is.data.frame(x[[1]]))
        x = x[[1]]
      n = length(x)
      allColnames = NULL
      for(i in seq_len(n)) 
        allColnames = unique(c(allColnames,colnames(x[[i]])))
      for(i in seq_len(n))
        x[[i]][, c(as.character(setdiff(allColnames, colnames(x[[i]]))))] <- "" #NA
      eval(parse(text = paste("rbind(",paste("x[[",seq_len(n),"]],",collapse = ""),"deparse.level = 0)")))
}
 
##### --- REPLACE_sdcTable.R ---
#####################################

### @importFrom sdcTable summary getInfo
### @importFrom sdcTable makeProblem primarySuppression protectTable protect_linked_tables createArgusInput runArgusBatchFile


makeProblem <- function(...) {
  list(...)
}

primarySuppression <- function(object, ...) object

getInfo <- function(object, ...) object


#' @importFrom SSBtools ModelMatrix
protectTable <- function(object, ...) {
  mm <- ModelMatrix(object$data, hierarchies = object$dimList, crossTable = TRUE)
  if (is.null(object$freqVarInd)) {
    Freq <- as.vector(Matrix::colSums(mm$modelMatrix))
  } else {
    Freq <- as.vector(Matrix::crossprod(mm$modelMatrix, object$data[[object$freqVarInd]]))
  }
  cbind(mm$crossTable, Freq = Freq, sdcStatus = "s")
}


protect_linked_tables <- function(x, y, ...) {
  list(x = protectTable(x), y = protectTable(y))
}

createArgusInput <- function(...) "createArgusInput"
runArgusBatchFile <- function(...) "runArgusBatchFile"
 
##### --- ReplaceDimList.R ---
#####################################

#' ReplaceDimList
#' 
#' Replace list elements of sdcTable coded hierarchies.
#' Replacement elements can be sdcTable coded or TauArgus coded.
#'
#' @param dimList Named list of data frames (sdcTable coded)
#' @param replaceList Named list where elements are data frames (sdcTable coded) or character vectors (TauArgus coded)
#' @param total String used to name totals when TauArgus coded input
#'
#' @return Updated dimList where some or all elements are replaced 
#' @importFrom SSBtools Hrc2DimList
#' @export
#' @keywords internal
#'
#' @examples
#' # First generate dimLists
#' dimListA <- FindDimLists(SSBtoolsData("sprt_emp_withEU")[, c("geo", "eu", "age")])
#' dimListB <- FindDimLists(SSBtoolsData("sprt_emp_withEU")[, c("geo", "age")])
#' dimListC <- FindDimLists(SSBtoolsData("sprt_emp_withEU")[, c("geo", "eu")])
#' 
#' # dimListA1 and dimListA are identical
#' dimListA1 <- ReplaceDimList(dimListB, dimListC)
#' identical(dimListA, dimListA1)
#' 
#' # replaceList can be TauArgus coded
#' hcrC <- DimList2Hrc(dimListC)
#' 
#' # dimListA2 and dimListA are identical
#' dimListA2 <- ReplaceDimList(dimListB, hcrC)
#' identical(dimListA, dimListA2)
#' 
#' # Also possible when duplicated names
#' ReplaceDimList(FindDimLists(EasyData("z3")[, -7]), 
#'                FindDimLists(EasyData("z2")[, -5]))
ReplaceDimList <- function(dimList, replaceList, total = "Total") {
  for (i in seq_along(replaceList)) {
    if (is.character(replaceList[[i]])) 
      replaceList[[i]] <- Hrc2DimList(replaceList[[i]], total = total)
    else
      replaceList[[i]] <- FixDimListNames(replaceList[[i]])
  }
  names1 <- make.names(names(dimList), unique = TRUE)
  names2 <- make.names(names(replaceList), unique = TRUE)
  matchNames <- match(names1, names2)
  dimList[!is.na(matchNames)] <- replaceList[matchNames[!is.na(matchNames)]]
  dimList
}


# Same as in SSBtools
FixDimListNames <- function(x) {
  if (!any(!(c("levels", "codes") %in% names(x)))) 
    return(x)
  a <- unique(c(pmatch(c("lev", "cod", "nam"), names(x)), 1:2))
  a <- a[!is.na(a)][1:2]
  names(x)[a] <- c("levels", "codes")
  x
}