GetPracticalRange <- function(model,kappas=NULL) {
  covnr <-
    as.integer(.C("GetModelNr", as.character(model), as.integer(1),
                  nr = integer(1), PACKAGE="RandomFields")$nr)
  if (covnr < 0) {
    .C("PrintModelList", PACKAGE="RandomFields")
    stop("given model cannot be (uniquely) identified from the above list")
  }
  if (length(kappas)!=.C("GetNrParameters", covnr, as.integer(1),
              k = integer(1), PACKAGE="RandomFields", DUP=FALSE)$k)
    stop("incorrect number of parameters!")
  nat.scl <- double(1)
  error <- integer(1)
  .C("GetNaturalScaling",
     as.integer(covnr),
     as.double(kappas),         ## not stable w.r.t. to changings !!
     as.integer(11),
     nat.scl,
     error,
     PACKAGE="RandomFields", DUP=FALSE)
  if (error) stop("natural scaling could not be obtained")
  return(1.0 / nat.scl)
}

GetMethodNames <- function() {
  assign(".p",
       .C("GetrfParameters", covmaxchar=integer(1), methodmaxchar=integer(1),
          distrmaxchar=integer(1),
          covnr=integer(1), methodnr=integer(1), distrnr=integer(1),
          maxdim=integer(1), maxmodels=integer(1),
          PACKAGE="RandomFields"))
  l <- character(.p$methodnr)
  for (i in 1:.p$methodnr) {
    l[i] <- .C("GetMethodName", as.integer(i-1),
               n=paste(rep(" ", .p$methodmaxchar), collapse=""),
               PACKAGE="RandomFields")$n
  }
  return(l)
}

GetDistributionNames <- function() {
  assign(".p",
       .C("GetrfParameters", covmaxchar=integer(1), methodmaxchar=integer(1),
          distrmaxchar=integer(1),
          covnr=integer(1), methodnr=integer(1), distrnr=integer(1),
          maxdim=integer(1), maxmodels=integer(1),
          PACKAGE="RandomFields"))
  l <- character(.p$distrnr)
  for (i in 1:.p$distrnr) {
    l[i] <- .C("GetDistrName", as.integer(i-1),
               n=paste(rep(" ",.p$distrmaxchar), collapse=""),
               PACKAGE="RandomFields")$n
  }
  return(l)
}


GetModelNames <- function() {
  assign(".p",
       .C("GetrfParameters", covmaxchar=integer(1), methodmaxchar=integer(1),
          distrmaxchar=integer(1),
          covnr=integer(1), methodnr=integer(1), distrnr=integer(1),
          maxdim=integer(1), maxmodels=integer(1),
          PACKAGE="RandomFields"))
  l <- character(.p$covnr)
  for (i in 1:.p$covnr) {
    l[i] <- .C("GetModelName",as.integer(i-1),
               n=paste(rep(" ",.p$covmaxchar), collapse=""),
               PACKAGE="RandomFields")$n
  }
  return(l)
}


GetModelList <- function(abbr=TRUE) {
  assign(".methods", GetMethodNames())
  names <- GetModelNames()
  methods <- .methods[.methods!="nugget"]
  if (abbr) methods <- substr(methods, 1, if (is.logical(abbr)) 5 else abbr)
  idx <- integer(length(names) * length(methods))
  .C("GetModelList", idx, PACKAGE="RandomFields", DUP=FALSE)
  t(matrix(as.logical(idx), ncol=length(names), dimnames=list(methods, names)))
}

parampositions <- function(model, param, print=TRUE) {
  type <- if (!missing(param) && !is.null(param))
    if (is.matrix(param)) "n" else "s" else "l"
  old.model <- PrepareModel(model, param)
  model <- PrepareModel(convert.to.readable(old.model))
  if (length(old.model$param) != length(model$param))
    stop("The model should be simplified beforehand") 
  model$param <- 1:length(model$param)
  model$mean <- NA
  model <- convert.to.readable(model, allowed=type)
  model$method <-  model$trend <- NULL
  if (type=="l") {
    if (print) str(model)
  } else {
    if (print) cat("model:", model$model, "\nparam: ")
    if (type=="s") { # standard
      NUGGET <- 3
      if (is.finite(param[NUGGET]) && param[NUGGET]==0)
        model$param[NUGGET] <- NA
      if (print) cat(model$param, "\n")
    } else { # nested
      model$param[model$param==0] <- NA
      if (length(model$param) !=
          length(convert.to.readable(old.model, allow="n")$param))
        stop("Model is too complex to be identified")
      if (print) {
        cat("\n")
        print(model$param)
      }
    }
  }
  invisible(model)
}

"RFparameters" <- function (...) {
  ## do not add any temporary variable til ## **
  ## do not remove leading "." from .maxdim
  
  assign(".methods", GetMethodNames())
  assign(".p",
       .C("GetrfParameters", covmaxchar=integer(1), methodmaxchar=integer(1),
          distrmaxchar=integer(1),
          covnr=integer(1), methodnr=integer(1), distrnr=integer(1),
          maxdim=integer(1), maxmodels=integer(1),
          PACKAGE="RandomFields"))
  Storing <- integer(1)
  PrintLevel <- integer(1)
  PracticalRange <- integer(1)
  ## always logical returned
  ## PracticalRange also allows for being set to
  ##  0 : no practical range
  ##  1,11 : practical range, evaluated exactly (if given in RFCovfct.cc)
  ##  2,12 : approximative value (if given in RFCovfct.cc)
  ##  3,13 : rough guess (good enough for MLE) (if given in RFCovfct.cc)
  ## >10: and if nothing appropriate given in RFCovfct.cc then numerical approx.
  pch <- as.character("  ")
  
  CE.force <- integer(1)
  CE.tolRe <- double(1)
  CE.tolIm <- double(1)
  CE.trials <- integer(1)
  CE.mmin <- integer(.p$maxdim)
  CE.userfft <- integer(1)
  CE.strategy <- integer(1)

  TBMCE.force <- integer(1)
  TBMCE.tolRe <- double(1)
  TBMCE.tolIm <- double(1)
  TBMCE.trials <- integer(1)
  TBMCE.mmin <- integer(.p$maxdim)
  TBMCE.userfft <- integer(1)
  TBMCE.strategy <- integer(1)
  TBM.method <- integer(1)

  TBM2.lines <- integer(1)
  TBM2.linesimufactor <- double(1)
  TBM2.linesimustep <- double(1)
  TBM2.every <- integer(1)
  
  TBM3D2.lines <- integer(1)
  TBM3D2.linesimufactor <- double(1)
  TBM3D2.linesimustep <- double(1)
  TBM3D2.every <- integer(1)
  
  TBM3D3.lines <- integer(1)
  TBM3D3.linesimufactor <- double(1)
  TBM3D3.linesimustep <- double(1)
  TBM3D3.every <- integer(1)

  spectral.lines <- integer(1)
  spectral.grid <- integer(1)

  direct.method <- integer(1)
  direct.checkprecision <- integer(1)
  direct.requiredprecision <- double(1)
  direct.maxvariables <- integer(1)

  MPP.approxzero <- double(1)
  add.MPP.realisations <- double(1)
  MPP.radius <- double(1)
  
  maxstable.maxGauss <- double(1)

  arg.list <- ls()
  ## ** 

  ## first element is the function name
  parameters <- list(...)
  for (m in 1:0) {
    # m = 1 reading parameters
    # m = 0 storing parameters
    storage.mode(m) <- "integer"
    ## "SetParam" more complicated since pch is of character type
    x <- .C("SetParam", m, Storing=Storing, PrintLevel=PrintLevel,
            PracticalRange=PracticalRange, pch=pch, PACKAGE="RandomFields")
    Storing <- x$Storing
    PrintLevel <- x$PrintLevel
    PracticalRange <- x$PracticalRange
    pch <- x$pch
    .C("SetParamCircEmbed", m, CE.force, CE.tolRe, CE.tolIm, CE.trials, 
       CE.mmin, CE.userfft, CE.strategy, PACKAGE="RandomFields", DUP=FALSE)
    .C("SetParamTBMCE", m, TBMCE.force, TBMCE.tolRe, TBMCE.tolIm, TBMCE.trials, 
       TBMCE.mmin, TBMCE.userfft, TBMCE.strategy,
       PACKAGE="RandomFields", DUP=FALSE)
    .C("SetParamTBM2", m, TBM2.lines, TBM2.linesimufactor,
       TBM2.linesimustep, TBM2.every, PACKAGE="RandomFields", DUP=FALSE)
    .C("SetParamTBM3D2", m, TBM3D2.lines, TBM3D2.linesimufactor,
       TBM3D2.linesimustep, TBM3D2.every, PACKAGE="RandomFields", DUP=FALSE)
    .C("SetParamTBM3D3", m, TBM3D3.lines, TBM3D3.linesimufactor,
       TBM3D3.linesimustep, TBM3D3.every, PACKAGE="RandomFields", DUP=FALSE)
    .C("SetParamTBM", m, TBM.method, PACKAGE="RandomFields", DUP=FALSE)
    .C("SetParamSpectral", m, spectral.lines, spectral.grid,
       PACKAGE="RandomFields", DUP=FALSE)
    .C("SetParamDirectGauss", m, direct.method, direct.checkprecision,
       direct.requiredprecision, direct.maxvariables,
       PACKAGE="RandomFields", DUP=FALSE)
    .C("SetMPP", m, MPP.approxzero, add.MPP.realisations, MPP.radius,
       PACKAGE="RandomFields", DUP=FALSE)
    .C("SetExtremes", m, maxstable.maxGauss, PACKAGE="RandomFields", DUP=FALSE)
    
    if (length(parameters)==0)
      return(list(Storing=as.logical(Storing),
                  PrintLevel=PrintLevel,
                  PracticalRange=if (PracticalRange<=1)
                   as.logical(PracticalRange) else PracticalRange, 
                  CE.force=as.logical(CE.force),
                  CE.mmin=CE.mmin,
                  CE.tolRe=CE.tolRe,
                  CE.tolIm=CE.tolIm,
                  CE.trials=CE.trials,
                  CE.userfft=as.logical(CE.userfft),
                  CE.strategy=CE.strategy,
                  direct.checkprecision=as.logical(direct.checkprecision),
                  direct.maxvariables=direct.maxvariables,
                  direct.method=direct.method,
                  direct.requiredprecision=direct.requiredprecision,
                  spectral.lines=spectral.lines,
                  spectral.grid=as.logical(spectral.grid),
                  TBMCE.force=as.logical(TBMCE.force),
                  TBMCE.mmin=TBMCE.mmin,
                  TBMCE.tolRe=TBMCE.tolRe,
                  TBMCE.tolIm=TBMCE.tolIm,
                  TBMCE.trials=TBMCE.trials,
                  TBMCE.userfft=as.logical(TBMCE.userfft),
                  TBMCE.strategy=TBMCE.strategy,
                  TBM2.lines=TBM2.lines,
                  TBM2.linesimufactor=TBM2.linesimufactor,
                  TBM2.linesimustep=TBM2.linesimustep,
                  TBM2.every=TBM2.every,
                  TBM3D2.lines=TBM3D2.lines,
                  TBM3D2.linesimufactor=TBM3D2.linesimufactor,
                  TBM3D2.linesimustep=TBM3D2.linesimustep,
                  TBM3D2.every=TBM3D2.every,
                  TBM3D3.lines=TBM3D3.lines,
                  TBM3D3.linesimufactor=TBM3D3.linesimufactor,
                  TBM3D3.linesimustep=TBM3D3.linesimustep,
                  TBM3D3.every=TBM3D3.every,
                  TBM.method=.methods[TBM.method+1],
                  MPP.approxzero=MPP.approxzero,
                  add.MPP.realisations=add.MPP.realisations,
                  MPP.radius=MPP.radius,
                  maxstable.maxGauss=maxstable.maxGauss,
                  pch=pch,
                  covmaxchar=.p$covmaxchar,
                  methodmaxchar=.p$methodmaxchar,
                  distrmaxchar=.p$distrmaxchar,
                  covnr=.p$covnr,
                  methodnr=.p$methodnr,
                  distrnr=.p$distrnr,
                  maxdim=.p$maxdim,
                  maxmodels=.p$maxmodels,
                  )
             )
    if (m==0) return(invisible(parameters))

    ## set to 0 since only one part of each pair might be non-zero
    ## this is then checked in RFtbm.cc, SetParamLines
    TBM2.linesimufactor <- as.double(0)
    TBM2.linesimustep <- as.double(0)
    TBM3D2.linesimufactor <- as.double(0)
    TBM3D2.linesimustep <- as.double(0)
    TBM3D3.linesimufactor <- as.double(0)
    TBM3D3.linesimustep <- as.double(0)
    
    orig.name <- names(parameters)
    if (is.null(orig.name) || (orig.name[1]=="")) {
      txt <- "either a single unnamed list must be given or the parameters should be referenced by names"
      if ((length(parameters)!=1)) stop(txt)
      parameters <- parameters[[1]]
      orig.name <- names(parameters)
      if ((length(parameters) != sum(orig.name!="") ||
           (length(parameters)==0))) stop(txt)
    }

    name <- arg.list[pmatch(orig.name, arg.list)]
    if (any(is.na(name)))
      stop("the following parameter(s) could not be matched: ",
           paste(orig.name[is.na(name)], collapse=", "))
    names(parameters) <- name

    for (i in 1:length(parameters)) {
      type <- storage.mode(get(name[i]))
      ## parameters[i] is not sufficient since user give expression,
      ## which have type "language"
      v <- parameters[[i]]
      if (name[i]=="TBM.method") v <- pmatch(v, .methods) - 1
      if (switch(type,
                 character = !is.character(v),
                 integer = !is.finite(v) || (v != as.integer(v)),
                 double = !is.numeric(v)))
        stop(paste("`", orig.name[i], "' is not ", type, sep=""))
      len <- length(get(name[i]))
      if (length(v) > len)
        stop(paste("`", orig.name[i], "' is a too long vector", sep=""))
      assign(name[i], rep(v, length=len))
      eval(parse(text=paste("storage.mode(",name[i],") <- type")))
    }
    stopifnot(PracticalRange %in% c(FALSE, TRUE, 2, 3, 11, 12, 13))
  }
}


"PrintModelList" <-function () {
    .C("PrintModelList", PACKAGE="RandomFields")
    invisible()
}


"PrintMethodList" <-function () {
    .C("PrintMethods", PACKAGE="RandomFields")
    invisible()
}


parameter.range <- function(model, dim){
  if (length(model)==0) stop("model not given")
  stopifnot(is.character(model))
  nr <- .C("GetModelNr", as.character(model), as.integer(1), nr=integer(1),
           PACKAGE="RandomFields")$nr
  if (nr < 0) {
    .C("PrintModelList", PACKAGE="RandomFields")
    stop("given model cannot be (uniquely) identified from the above list")
  }
  storage.mode(nr) = "integer"
  storage.mode(dim) = "integer"
  l <- as.integer(4 * .C("GetNrParameters", nr, as.integer(1), k=integer(1),
                         PACKAGE="RandomFields")$k)
  r <- list()
  r$theoretical <- list()
  r$practical <- list()
  index <- as.integer(1)
  while (index>0) {
    R <- double(l)
    index.orig <- as.integer(index) ## without index.orig points to index,
    ## what is a bug in R -- do report! -- Check if bug is still there
    .C("GetRange", nr, dim, index, R, l, PACKAGE="RandomFields", DUP=FALSE)
    R <- matrix(R, nrow=4)
    r$theoretical[[index.orig]] <- R[1:2, , drop=FALSE]
    r$practical[[index.orig]] <- R[3:4, ,drop=FALSE]
  }
  if (index <= -2) {
    if (index==-2) r <- NaN ##  stop("dimension not correct")
    else stop(paste("error: inform maintainer (error nr.",index,")"))
  }
  return(if (is.list(r) && ncol(r$theoretical[[1]])==0) NULL else r)
}