InitModel <- function(reg, model, dim, NAOK=FALSE){
  for (y in list(double(0), matrix(nrow=dim, ncol=3, as.double(1:3)))) {
    vdim <- try(.Call("Init",
                      MODEL.USER,
                      model,
                      matrix(nrow=dim, ncol=3, as.double(1:3)), ## nur dummies
                      y, #y
                      as.double(0), #T
                      as.integer(dim), #spatdim
                      FALSE, # grid
                      FALSE, # distances
                      FALSE, # Time
                      NAOK=NAOK,
                      PACKAGE="RandomFields"), silent=TRUE)
    
    if (is.numeric(vdim)) return(vdim)
    msg <- strsplit(vdim[[1]], "\n")[[1]][2]
    if (RFoptions()$general$printlevel >= PL.FCTN.ERRORS) cat(msg, "\n")
  }
  stop(msg)
  ##  stop("model could not be initialized")
}

rfSplitTrendAndCov <-
  function(model, spatialdim, xdimOZ, Time,  forcedplus=FALSE,
           cathegories=list(trend=DetTrendEffect : SpVarEffect),
           remaining.name="cov") {
  ## splittet additives modell in trend-Teil und cov-Teil auf

  
   info <- .Call("SetAndGetModelInfo",
                 GetModelRegister("split"), list("Dummy", model),
                 as.integer(spatialdim),
                 FALSE,
                 TRUE, ## in case it is a non-domain model
                 as.logical(Time), 
                 as.integer(xdimOZ), 
                 MaxNameCharacter, FALSE, TRUE,
                 PACKAGE="RandomFields")

    
  effect <- info$effect
  
  submodels <- list()
  for (j in 1:(length(cathegories)+1)) submodels[[j]]<-list()
  names(submodels) <- c(names(cathegories), remaining.name)

  if ( !(model[[1]] %in% ZF_PLUS)) model<- list(ZF_SYMBOLS_PLUS, model)        

  for (i in 2:length(model)) {
    j<-1
    while(j<=length(cathegories) && !(effect[i-1] %in% cathegories[[j]])) {
      j <- j+1
    }
    submodels[[j]][[length(submodels[[j]])+1]] <- model[[i]]
  }

  for (j in 1:(length(cathegories)+1)) {
    if (length(submodels[[j]]) > 1 ||
        (forcedplus && length(submodels[[j]])>0)) { # geaendert 2.11.11
      submodels[[j]] <- c(ZF_SYMBOLS_PLUS,  submodels[[j]])
    } else if (length(submodels[[j]])==1) {
      submodels[[j]] <- submodels[[j]][[1]]
    }
  }
  submodels[sapply(submodels, length)==0] <- NULL
  return(submodels)
}


StandardSimpleModel <- function(model, tsdim, aniso=TRUE, addnugget=TRUE, ...) {    ## bei mixed model ist eine zweite Ebene von '+' vorhanden
  ## einfache mixed model koennen aber wie Simple behandelt werden
  ## die zweite '+'-Ebene wird hier aufgeloest:
  ##
  ## Nun koennten noch Namen fuer die Untermodelle vergeben worden sein.
  ## Wenn dann "unlist" aufgerufen wird, werden die namen der Ober- und
  ## Untermodelle zu einem gemeinsamen Namen verbunden, der dann nicht
  ## mehr als als submodel-Name erkannt wird. Also hilft nur alle
  ## (potentiellen) Namen zu loeschen:
  if (model[[1]] %in% ZF_PLUS) {
    submodels <- sapply(model[-1], function(x) x[[1]])
    plus <- submodels %in% ZF_PLUS
    if (any(plus)) {
      plus <- which(plus) + 1
      subs <- lapply(model[plus], function(x) x[-1])
      names(subs) <- NULL
      subs <- unlist(subs, recursive=FALSE)
      names(subs) <- NULL
      trend <- model[-plus]
      names(trend) <- NULL      
      model <- c(trend, subs)
      ## Print(model,trend,subs); xxx
    }
  } 

 # Print("SSM X", model)

  model <- PrepareModel2(model, ...)
  storage.mode(tsdim) <- "integer"
 # userdefined <- GetParameterModelUser(model)
  
  vdim <- InitModel(MODEL.USER, list("Dummy", model), tsdim, NAOK=TRUE)
  if (!is.numeric(vdim) || vdim > 1) return("model not univariate")
  model <- GetModel(register=MODEL.USER) # , do.notreturnparam=TRUE)
  .C("DeleteKey", MODEL.USER)

  s <- rfSplitTrendAndCov(model=model, spatialdim=tsdim, xdimOZ=tsdim,
                          Time=FALSE, forcedplus=TRUE,
                          cathegories=list(simple=c(Primitive:Simple),
                            trend=DetTrendEffect:FixedTrendEffect),
                          remaining.name="cov")
  
  ##  Print(model, s, s$cov, s$simple)
  
  ## Print(model, s); #hhhh
  
  if (!is.null(s$cov) || length(s$simple)>3)
    return("model is too complex to be simple")
  if (length(s$simple) <= 1) return("model is too primitive")
  s <- s$simple

  for (i in 2:length(s)) {
    if (! (s[[i]][[1]] %in% DOLLAR)) s[[i]] <- list(DOLLAR[1], var=1, s[[i]])
  }
  if (length(s)==2 && !(s[[2]][[length(s[[2]])]][[1]] %in% ZF_NUGGET)
              && addnugget){
    ## assuming nugget is missing
    s[[3]] <- list(DOLLAR[1], var=0, list(ZF_NUGGET[2]))
  }

  if (length(s) == 3) {  ## [[1]] is '+'
    if (s[[2]][[length(s[[2]])]][[1]] %in% ZF_NUGGET) {
      s[2:3] <- s[3:2] ## [[1]] is '+'
    }
    if (s[[2]][[length(s[[2]])]][[1]] %in% ZF_NUGGET)
      return("nugget model given twice")
    if (!(s[[3]][[length(s[[3]])]][[1]] %in% ZF_NUGGET))
      return("simple model must the sum of some domain and isotropic model and a nugget effect")
     if (length(c(s[[3]]$scale, s[[3]]$Aniso, s[[3]]$aniso, s[[3]]$proj)) > 0)
       return("nugget contains scale and/or anisotropic elements")
  }
  if (length(c(if (!aniso) s[[2]]$aniso, s[[2]]$Aniso, s[[2]]$proj)) > 0)
    return("model is a complicated scale structure")
       
  return(s)
}


PrepareModel2 <- function(model, ...) {
  if (missing(model) || is.null(model)) stop("'model' must be given.")
  m <- parseModel(model, ...)
  
  #if (!is.list(model))
      
#  if (class(try(all.equal(parseModel(list2RMmodel(m)), m, check.attr=FALSE)))=="try-error"){
#    print("AlexWarning in PrepareModel2: ruecktrafo via list2RMmodel waere falsch oder nich dasselbe ... bitte model mir zuschicken")
#    print("doppelt hin und zurueck:")
#    print(try(all.equal(parseModel(list2RMmodel(parseModel(list2RMmodel(m)))), parseModel(list2RMmodel(m)), check.attr=FALSE)))
#  }

  if (notplus <- !(m[[1]] %in% ZF_PLUS)) m <- list(ZF_SYMBOLS_PLUS, m)
     
  for (i in 2:length(m)) {
    if ((m[[i]][[1]] %in% ZF_MIXED) && length(m[[i]]$X)==1 &&
        is.numeric(m[[i]]$X) && m[[i]]$X==1 && !is.null(m[[i]]$b)) {        
      m[[i]] <- list(ZF_TREND[2], mean=m[[i]]$b)
      if (RFoptions()$general$printlevel > PL.IMPORPANT)
        message(paste("The '1' in the mixed model definition has been replaced by '", ZF_TREND[1], "(mean=", m[[i]]$mean, ")'.", sep=""))
      }
  }
    
  return(if (notplus) m[[2]] else m)

#  if (class(model) != "formula") {
#    if (is.list(model)) return(model)
#    else stop("model of unknown form -- maybe you have used an obsolete definition. See ?RMmodel for the model definition")
#  }
#  return(listmodel)
}


PrepareModel <-  function(model, param, trend=NULL, 
                          nugget.remove=TRUE, method=NULL) {
  ## any of the users model definition (standard, nested, list) for the
  ## covariance function is transformed into a standard format, used
  ## especially in the c programs
  ##
  ## overwrites in some situation the simulation method for nugget.
  ## allows trend to be NA (or any other non finite value  -- is not checked!)
  ## trend has not been implemented yet!

  if (is(model, ZF_MODEL))
    stop("models of class ZF_MODEL cannot be combined with obsolete RandomFields functions")

  if (!is.null(method)) stop("to give method in PrepareModel is obsolete")
  
  if (!is.null(trend))      
     if (!is.numeric(trend) || length(trend)!=1)
        stop("in the obsolete setting, only constant mean can used")
 
  if (is.list(model) && is.character(model[[1]]) &&
      (is.null(names(model)) || names(model)[[1]]=="")) {
     if (!missing(param) && !is.null(param))
        stop("param cannot be given in the extended definition")
     if (is.null(trend)) return(model)
     trend <- list(ZF_TREND[2], mean=trend)
     if (model[[1]] %in% ZF_PLUS) return(c(model, list(trend)))
     else return(list(ZF_SYMBOLS_PLUS, model, trend))
  }
    
  printlevel <- RFoptions()$general$printlevel
  STOP <- function(txt) {
    if (printlevel>=PL.FCTN.ERRORS) {
      cat("model: ")
      if (!missing.model) Print(model) else cat(" missing.\n") #
      cat("param: ")
      if (!missing.param) Print(param) else cat(" missing.\n") #
      cat("trend: ")
      Print(trend) # 
     }
    stop("(in PrepareModel) ", txt, call.=FALSE)
  }
   
  transform <- function(model) {
    if (!is.list(model)) {
      STOP("some elements of the model definition are not lists")
    }
    m <- list(DOLLAR[1], var=model$v)
    lm <- length(model) - 3 # var, scale/aniso, name
    if (!is.null(model$a)) m$aniso <- model$a else m$scale <- model$scale
##    model <- c(model, if (!is.null(model$a))
##               list(aniso=model$a) else list(scale=model$s)) ## ???

## Print(m, model, lm)
    
    if (!is.na(p <- pmatch("meth", names(model), duplicates.ok=TRUE))) {
      if (printlevel>=PL.FCTN.ERRORS)  Print(p, model)
      stop("method cannot be given with the model anymore. It must be given as a parameter to the function. See RFoptions and RFsimulate")
     }
  
    if (!is.null(model$me))
      stop("'mean' seems to be given within the inner model definitions"); 
    if (!is.character(model$m)) {
       stop("'model' was not given extacly once each odd number of list entries or additional unused list elements are given.")
    }
    m1 <- list(model$m)
    if (!is.null(model$k)) {
      lm <- lm - 1
      if (length(model$k) != 0)
        for (i in 1:length(model$k)) {
          eval(parse(text=paste("m1$k", i, " <- model$k[", i, "]", sep="")))
      }
    }
    if (lm != 0) {
      if (printlevel>=PL.FCTN.ERRORS) Print(lm, model) 
      stop("some parameters do not fit")
    }
    m <- c(m, list(m1))

    ##    Print(m)
    return(m)
    
  } # end transform

  op.list <- c(ZF_SYMBOLS_PLUS, ZF_SYMBOLS_MULT)  ## if others use complex list definition !
  missing.model <- missing(model)
  missing.param <- missing(param) || is.null(param)

  if (full.model <- missing.param && is.null(model$param)) { ## full model
    if (RFoptions()$warn$oldstyle)
      warning("the sequential list format is depreciated.")
    if (missing.model || (length(model)==0)) model <- list()
    else if (!is.list(model))
      STOP("if param is missing, model must be a list of lists (or a list in the extended notation)")
    if (is.null(trend) + is.null(model$mean) + is.null(model$trend)<2)
      STOP("trend/mean is given twice")
    if (!is.null(model$mean)) trend <- model$mean else
    if (!is.null(model$trend)) trend <- model$trend else trend <- NULL

    model$trend <- model$mean <- NULL
    ## the definition might be given at a deeper level as element
    ## $model of the list:
    if (is.list(model$model)) {
      if (!is.list(model$model[[1]]))
        STOP("if param is missing, the model$model must be a list of lists")
      model <- model$model
    }
    if (length(model)==0) { ## deterministic      
      return(if (is.null(trend)) NULL else list(ZF_TREND[2], mean=trend))
    }
    if (length(model) %% 2 !=1) STOP("list for model definition should be odd")
    if (length(model)==1)
      return(if (is.null(trend) ||
                 is.numeric(trend) && length(trend)==1 && !is.na(trend)&&trend==0)
             transform(model[[1]]) 
             else list(ZF_SYMBOLS_PLUS, transform(model[[1]]),
                       list(ZF_TREND[2], mean=trend)));

    op <- pmatch(c(model[seq(2, length(model), 2)], recursive=TRUE),
                 op.list, duplicates.ok=TRUE) - 1
    if (!all(is.finite(op))) STOP("operators are not all allowed; see the extended list definition for extensions")
    model <- model[seq(1, length(model), 2)]

    plus <- which(op==0)
    if (length(plus) == 0) {
      m <- list("*", lapply(model, transform))
    } else {
      plus <- c(0, plus, length(op)+1)
      m <- list(ZF_SYMBOLS_PLUS)
      for (i in 1:(length(plus) - 1)) {
        m[[i+1]] <-
          if (plus[i] + 1 == plus[i+1]) transform(model[[plus[i] + 1]])
          else list(ZF_SYMBOLS_MULT,
                    lapply(model[(plus[i] + 1) : plus[i+1]], transform))
      }
    }
   model <- m
  } else { ## standard definition or nested model
    if (missing.param) { ## a simple list of the model and the
      ##                    parameters is also possible
      if (is.null(param <- model$p)) STOP("is.null(model$param)")
      stopifnot(is.null(trend) || is.null(model$trend))
      if (is.null(trend)) trend <- model$trend
      if (!is.null(model$mean)) {
        if (!is.null(trend)) STOP("mean and trend given twice")
        trend <- model$mean
      }
      model <- model$model
    }
    stopifnot(is.character(model), length(model)==1)
    if (is.matrix(param)) { ## nested
      if (nrow(param) == 1)
        return(PrepareModel(model=model, param=c(param[1], 0, param[-1]),
                            trend=trend))
      name <- model
      model <- list(ZF_SYMBOLS_PLUS)#, method=method)
      for (i in 1:nrow(param)) {
        model <- c(model,
                   if (is.na(param[i, 2]) || param[i, 2] != 0)
                   list(list(DOLLAR[1], var=param[i, 1], scale=param[i, 2],
                             if (ncol(param) >2) list(name, k=param[i,-1:-2])
                             else list(name)))
                   else list(list(DOLLAR[1], var=param[i,1],
                                  list(ZF_NUGGET[2]))))
      }
    } else if (is.vector(param)) {  ## standard, simple way
      ## falls trend gegeben, dann ist param um 1 Komponente gekuerzt
      if (is.null(trend)) {
        trend <- param[1]
        param <- param[-1]
      } else message("It is assumed that no mean is given so that the first component of param is the variance")
      if (model == ZF_NUGGET[2]) {
        model <- transform(list(model=model, var=sum(param[1:2]), scale=1)) 
      } else {
        if  (length(param) > 3)
          model <- transform(list(model=model, var=param[1], scale=param[3],
                                  k=param[-1:-3]))
        else 
          model <- transform(list(model=model, var=param[1], scale=param[3]))
        if (is.na(param[2]) || param[2] != 0 || !nugget.remove) {# nugget
          model <- list(ZF_SYMBOLS_PLUS,
                        model,
                        transform(list(model=ZF_NUGGET[2], var=param[2], scale=1)))
        }
        ## if (!is.null(method)) model <- c(model, method=method) ## doppelt
      }
    } else stop("unknown format")  # end nested/standard definition
  }

  return(if (is.null(trend) ||
             is.numeric(trend) && length(trend)==1 &&  !is.na(trend) &&trend==0)
         return(model)
         else if (model[[1]] %in% ZF_PLUS)
                 c(model, list(list(ZF_TREND[2], mean=trend)))
         else list(ZF_SYMBOLS_PLUS, model, list(ZF_TREND[2], mean=trend)))
}


seq2grid <- function(x, name, grid, warn.ambiguous, gridtolerance) {
  xx <- matrix(nrow=3, ncol=length(x))
  step0 <- rep(FALSE, length(x))
  
  for (i in 1:length(x)) {
    if (length(x[[i]]) == 1) {
      xx[,i] <- c(x[[i]], 0, 1)
      next
    }
    step <- diff(x[[i]])
    if (step[1] == 0.0) {
      ok <- step0[i] <- all(step == 0.0)
    } else {
      ok <- max(abs(step / step[1] - 1.0)) <= gridtolerance
    }

    if (!ok) {
      if (missing(grid)) return(FALSE)

      stop(paste(sep="", name, "= (",
                 paste(x[[i]][1:min(100, length(x[[i]]))], collapse=", "),
                 ")\ndiff = (",
                 paste(step[1:min(100,length(step))], collapse=", "),
                 ")\nDifferent grid distances detected, but the grid must ",
                 "have equal distances in each direction -- if sure that ",
                 "it is a grid, increase the value of 'gridtolerance'.\n"))
    }

    ## return(c(x[1], x[length(x)]+0.001*step[1], step[1]))
    ##       Print(c(x[1], step[1], length(x)))
    xx[,i] <- c(x[[i]][1], step[1], if (step0[i]) 1 else length(x[[i]]))
  }

  if (missing(grid) && warn.ambiguous && length(x) > 1) {
    RFoptions(warn.ambiguous = FALSE)
    message("Ambiguous interpretation of coordinates. Better give 'grid=TRUE' explicitly. (This message appears only once per session.)")
  }

  if (any(step0)) {
    if (all(step0)) {
      if (missing(grid)) return(FALSE)
      else stop("Within a grid, the coordinates must be distinguishable")
    } else {
      if (missing(grid) && warn.ambiguous) {
        RFoptions(warn.ambiguous = FALSE)
        warning("Interpretation as degenerated grid. Better give 'grid' explicitely. (This warning appears only once per session.)")
      }
    }
  }

  return(xx)
}


CheckXT <- function(x, y, z, T, grid, distances, spdim=NULL, length.data,
                    y.ok = FALSE, 
                    printlevel = RFoptions()$general$printlevel){

  ## converts the given coordinates into standard formats
  ## (one for arbitrarily given locations and one for grid points)
  
  if (!missing(distances)) {
    stopifnot(is.matrix(distances) || (!missing(spdim) && !is.null(spdim)),
              missing(grid) || length(grid)==0,
              missing(x) || is.null(x),
              missing(y) || is.null(y),
              missing(z) || is.null(z),
              missing(T) || is.null(T))

    
    if (class(distances) == "dist") {
      x <- as.vector(distances)
      l <- length(x)
    } else if (is.matrix(distances) || is.vector(distances)) {
      if (is.matrix(distances)) {        
        len <- nrow(distances)
        if (is.null(spdim)) spdim = ncol(distances)
        else if (spdim != ncol(distances))
          stop("matrix of distances does not fit the given dimension")
      } else {
        len <- length(distances)
        if (is.null(spdim))
          stop("spdim is not given although 'distances' are used")
      }
      x <- distances
      l <- as.integer(1e-9 + 0.5 * (1 + sqrt(1 + 8 * len)))
      if (l * (l-1) / 2 != len)
        stop("number of given 'distances' is incorrect.")
    } else {
      stop("'distances' not of required format.")
    }

    return(list(x=as.matrix(x),
                T=NULL, 
                Time=FALSE,
                restotal = l,
                l = l,
                spacedim=spdim,
                grid = FALSE,
                distances = TRUE
                )
           )
  }

  stopifnot(!missing(x))
  
  RFopt <- RFoptions()

  if (missing(grid) && !missing(length.data)) {
    new <-  try(CheckXT(x=x, y=y, z=z, T=T, grid=TRUE, distances=distances,
                        spdim=if (!missing(spdim)) spdim,
                        length.data = length.data, y.ok =y.ok,
                        printlevel = printlevel
                        ), silent=TRUE)
    if (grid <- (class(new) != "try-error")) {
      ratio <- length.data / new$restotal

   # Print(new, ratio, length.data, x)
      
      if (grid <- ratio == as.integer(ratio)) {
        if (printlevel>=PL.IMPORPANT && new$spacedim > 1)
          message("Grid detected. If it is not a grid, set grid=FALSE.\n")
      }
    }
    return(if (grid) new else { CheckXT(x, y, z, T, grid=FALSE, distances,
                                        if (!missing(distances)) spdim=1,
                                        length.data = length.data,
                                        printlevel = printlevel) }
           )
  } # if (missing(grid) && !missing(length.data))
  

  if (!missing(spdim) && !is.null(spdim))
    stop("'dim' should be given only when 'distances' are given")
  gridtriple <- FALSE

  ## if (!missing(x)) {  ## missing(x) ist hier immer FALSE 
  ##  Print(x)
  if (is.GridTopology <- is(x, "GridTopology")){
    x <- rbind(x@cellcentre.offset,
               x@cellsize,
               x@cells.dim)
    if (missing(grid)) grid <- TRUE else stopifnot(grid)
    gridtriple <- TRUE
  }
  ##else {
  ##  is.GridTopology <- FALSE
  ##}

  
  if (is.data.frame(x)) {
    if (ncol(x)==1) x <- as.vector(x) else x <- as.matrix(x)
  }
  
  stopifnot(all(unlist(lapply(as.list(x), FUN=function(li) is.numeric(li)))))
  stopifnot(length(x) != 0) 
  stopifnot(all(is.finite(x)), all(is.finite(y)), all(is.finite(z)))
            
  
  if (is.matrix(x)) {
    if (!is.numeric(x)) stop("x is not numeric.")
    if (!is.null(z)) stop("If x is a matrix, then z may not be given")
    if (!is.null(y)) {
      if (!y.ok) stop("If x is a matrix, then y may not be given")
      if (!is.null(T))
        stop("If x is a matrix and y is given, then T may not be given")
      if (!is.matrix(y) || ncol(y) != ncol(x) ||
          nrow(x)==3 && nrow(y)!=3 && (missing(grid) || grid))
        stop("y does not match x (it must be a matrix)")
    }
    spacedim <- ncol(x)

    len <- nrow(x)
    if (spacedim==1 && len != 3 && missing(grid)) {
      if (length(x) <= 2) grid <- TRUE
      else {
        dx <- diff(x)
        grid <- max(abs(diff(dx))) < dx[1] * RFopt$general$gridtolerance
      }
    } # else {
    if (missing(grid) && apply(x, 2, function(z) (length(z) <= 2) ||
                               (max(abs(diff(diff(z))))
        > RFopt$general$gridtolerance)))
      grid <- FALSE      
    if (missing(grid) || !is.logical(grid)) {
      grid <- TRUE
      if (spacedim > 1 && RFopt$warn$ambiguous) {
        RFoptions(warn.ambiguous = FALSE)
        warning("Ambiguous interpretation of the coordinates. Better give the logical parameter 'grid=TRUE' explicitely. (This warning appears only once per session.)")
      }
    }
    if (grid && !is.GridTopology) {
      if (gridtriple <- len==3) {
        if (printlevel >= PL.SUBIMPORPANT && RFopt$warn$oldstyle) {
          message("x was interpreted as a gridtriple; the new gridtriple notation is:\n  1st row of x is interpreted as starting values of sequences,\n  2nd row as step,\n 3rd row as number of points (i.e. length),\n  in each of the ", ncol(x), " directions.")
        } 
      } else len <- rep(len, times=spacedim)   # Alex 8.10.2011
    }
    if (grid && !gridtriple) {
      ## list with columns as list elements -- easier way to
      ## do it??
      x <- lapply(apply(x, 2, list), function(r) r[[1]])
      if (!is.null(y)) y <- lapply(apply(y, 2, list), function(r) r[[1]])
    }
  } else { ## x, y, z given separately 
   if (is.null(y) && !is.null(z)) stop("y is not given, but z")
    xyzT <- list(x=if (!missing(x)) x, y=if (!missing(y)) y,
                 z=if (!missing(z)) z, T=if (!missing(T)) T)
    for (i in 1:4) {
      if (!is.null(xyzT[[i]]) && !is.numeric(xyzT[[i]])) {
        if (printlevel>PL.IMPORPANT) 
          message(names(xyzT)[i],
                  " not being numeric it is converted to numeric")
        assign(names(xyzT)[i], as.numeric(xyzT[[i]]))
      }
    }
    remove(xyzT)
    spacedim <- 1 + (!is.null(y)) + (!is.null(z))
    if (spacedim==1 && (missing(grid) || !grid)) {
      ## ueberschreibt Einstellung des Nutzers im Falle d=1
      if (length(x) <= 2) newgrid <- TRUE
      else {
        dx <- diff(x)
        newgrid <- max(abs(diff(dx))) < dx[1] * RFopt$general$gridtolerance
      }
      if (missing(grid)) grid <- newgrid
      else if (xor(newgrid, grid))
        message("coordinates", if (grid) " do not",
                " seem to be on a grid, but grid =", grid)
    }
    len <- c(length(x), length(y), length(z))[1:spacedim]
    
    if (!missing(grid) && !grid) { ## sicher nicht grid, ansonsten ausprobieren
      if (any(diff(len) != 0)) stop("some of x, y, z differ in length")
      x <- cbind(x, y, z)
      ## make a matrix out of the list
      len <- len[1]
    } else {
      if (missing(grid) && any(len != len[1])) grid <- TRUE
      x <- list(x, y, z)[1:spacedim]
    }
    y <- z <- NULL ## wichtig dass y = NULL ist, da unten die Abfrage
  }  ## end of x, y, z given separately 

  ##Print(grid,  gridtriple, tryCatch(dim(x), error=function(e) "err"), len)
  
  if (!all(is.finite(unlist(x)))) stop("coordinates are not all finite")

  
  if (missing(grid) || grid) {
    if (gridtriple) {
      if (len != 3)
        stop("In case of simulating a grid with option gridtriple, exactly 3 numbers are needed for each direction")
      lr <- x[3,] # apply(x, 2, function(r) length(seq(r[1], r[2], r[3])))
      ##x[2,] <- x[1,] + (lr - 0.999) * x[3,] ## since own algorithm recalculates
      ##                               the sequence, this makes sure that
      ##                               I will certainly get the result of seq
      ##                               altough numerical errors may occurs
      restotal <- prod(x[3, ])
      if (!is.null(y) && !all(y[3,] == x[3,]))
        stop("the grids of x and y do not match ")        
    } else {     
      xx <- seq2grid(x, "x",  grid,
                     RFopt$warn$ambiguous, RFopt$general$gridtolerance)
  #    Print(xx, x, grid); ddd
      if (!is.null(y)) {
        yy <- seq2grid(y, "y", grid,
                       RFopt$warn$ambiguous, RFopt$general$gridtolerance)
        if (xor(is.logical(xx), is.logical(yy)) ||
            (!is.logical(xx) && !all(yy[3,] == xx[3,])))
          stop("the grids for x and y do not match")      
      }
      if (missing(grid)) grid <- !is.logical(xx)       
      if (grid) {
        x <- xx
        if (!is.null(y)) y <- yy
        restotal <- prod(len)
        len <- 3
      } else {
        x <- sapply(x, function(z) z)
        if (!is.null(y)) y <- sapply(y, function(z) z)
      }
    }
    if (grid && any(x[3, ] <= 0))
      stop(paste("step must be postive. Got as steps", x[3,]))
    ##if (len == 1) stop("Use grid=FALSE if only a single point is simulated")
  }

  stopifnot(!missing(grid))
  
  if (!grid) { ## not grid
    restotal <- nrow(x)
    if (is.null(y)) {
      if (restotal < 200 && any(as.double(dist(x)) == 0)) {## 2000
        d <- as.matrix(dist(x))
        diag(d) <- 1
        idx <-  which(as.matrix(d) ==0)
        if (printlevel>PL.FCTN.ERRORS)
          Print(x, dim(d), idx , cbind( 1 + ((idx-1)%% nrow(d)), #
                                       1 + as.integer((idx - 1)  / nrow(d))) )
        stop("locations must be distinguishable")
      }
      ## fuer hoehere Werte con total ist ueberpruefung nicht mehr praktikabel
    }
  }
  
  if (Time <- !is.null(T)) {
    if (length(T)!=3) stop("length(T) == 3 is not TRUE. Note that for the time component R,\nthe gridtriple notation c(start, step, length) must be used.")
    #lT <- length(seq(T[1],T[2],T[3]))
    #T[2] <- T[1] + (lT - 0.999) * T[3]
    restotal <- restotal * T[3]
  }

  storage.mode(x) <- "double"
  if (is.null(y)) {
    return(list(x=x, T=T, Time=Time, restotal=restotal, l=len,
                spacedim=spacedim, grid=grid, distances=FALSE))
  } else {
    storage.mode(y) <- "double"
    return(list(x=x, y=y, T=T, Time=Time, restotal=restotal, l=len,
                spacedim=spacedim, grid=grid, distances=FALSE))
  }
  
}