Merge pull request #22 from hollorol/version7

Version7

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/DESCRIPTION

@@ -0,0 +1,18 @@
+Package: RBBGCMuso
+Title: An R package for BiomeBGC-MuSo ecosystem modelling
+Version: 0.7.1
+Authors@R: person("Roland", "Hollo's", , "hollorol@gmail.com", role = c("aut", "cre"))
+Description: What the package does (one paragraph).
+Depends: R (>= 3.3.2)
+License: GPL-2
+NeedsCompilation: no
+Packaged: 2023-02-06 09:42:51 UTC; user
+Author: Roland Hollo's [aut, cre]
+Imports: grDevices, limSolve, stats, utils, graphics, Rcpp, magrittr,
+        dplyr, ggplot2, rmarkdown, tibble, tidyr, glue, scales, tcltk,
+        digest, jsonlite, data.table, gridExtra, lubridate, openxlsx,
+        ncdf4, future, httr, tcltk, Boruta, rpart, rpart.plot
+Maintainer: Roland Hollo's <hollorol@gmail.com>
+Suggests: knitr, rmarkdown,
+VignetteBuilder: knitr
+ByteCompile: true

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/NAMESPACE

@@ -0,0 +1,97 @@
+# Generated by roxygen2: do not edit by hand
+
+export(calibMuso)
+export(calibrateMuso)
+export(changemulline)
+export(checkFileSystem)
+export(checkMeteoBGC)
+export(cleanupMuso)
+export(compareMuso)
+export(copyMusoExampleTo)
+export(corrigMuso)
+export(createSoilFile)
+export(flatMuso)
+export(getAnnualOutputList)
+export(getConstMatrix)
+export(getDailyOutputList)
+export(getFilePath)
+export(getFilesFromIni)
+export(getyearlycum)
+export(getyearlymax)
+export(multiSiteCalib)
+export(musoDate)
+export(musoGlue)
+export(musoMapping)
+export(musoMappingFind)
+export(musoMonte)
+export(musoQuickEffect)
+export(musoRand)
+export(musoSensi)
+export(normalMuso)
+export(optiMuso)
+export(paramSweep)
+export(plotMuso)
+export(plotMusoWithData)
+export(randEpc)
+export(readObservedData)
+export(runMuso)
+export(rungetMuso)
+export(saveAllMusoPlots)
+export(setupMuso)
+export(spinupMuso)
+export(supportedMuso)
+export(updateMusoMapping)
+import(ggplot2)
+import(utils)
+importFrom(data.table,':=')
+importFrom(data.table,data.table)
+importFrom(data.table,fread)
+importFrom(digest,digest)
+importFrom(dplyr,'%>%')
+importFrom(dplyr,filter)
+importFrom(dplyr,group_by)
+importFrom(dplyr,mutate)
+importFrom(dplyr,select)
+importFrom(dplyr,summarize)
+importFrom(dplyr,tbl_df)
+importFrom(future,future)
+importFrom(ggplot2,aes)
+importFrom(ggplot2,aes_string)
+importFrom(ggplot2,element_blank)
+importFrom(ggplot2,element_text)
+importFrom(ggplot2,facet_wrap)
+importFrom(ggplot2,geom_bar)
+importFrom(ggplot2,geom_line)
+importFrom(ggplot2,geom_point)
+importFrom(ggplot2,ggplot)
+importFrom(ggplot2,ggsave)
+importFrom(ggplot2,ggtitle)
+importFrom(ggplot2,labs)
+importFrom(ggplot2,scale_y_continuous)
+importFrom(ggplot2,theme)
+importFrom(ggplot2,theme_classic)
+importFrom(ggplot2,xlab)
+importFrom(ggplot2,ylab)
+importFrom(glue,glue)
+importFrom(gridExtra,grid.arrange)
+importFrom(httr,GET)
+importFrom(httr,config)
+importFrom(httr,content)
+importFrom(httr,with_config)
+importFrom(jsonlite,write_json)
+importFrom(limSolve,xsample)
+importFrom(lubridate,leap_year)
+importFrom(magrittr,'%<>%')
+importFrom(magrittr,'%>%')
+importFrom(openxlsx,read.xlsx)
+importFrom(rmarkdown,pandoc_version)
+importFrom(rmarkdown,render)
+importFrom(rpart,rpart)
+importFrom(rpart,rpart.control)
+importFrom(rpart.plot,rpart.plot)
+importFrom(scales,percent)
+importFrom(stats,approx)
+importFrom(tcltk,tk_choose.files)
+importFrom(tibble,rownames_to_column)
+importFrom(tidyr,gather)
+importFrom(tidyr,separate)

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/assistantFunctions.R

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+#' getLogs
+#'
+#'This function gives us the muso logfiles with their path
+#'
+#'@param outputLoc This is the location of the output files.
+#'@param outputNames These are the prefixes of the logfiles
+#'@return Logfiles with paths
+#'@keywords internal
+
+
+getLogs <- function(outputLoc, outputNames, type = "spinup"){
+    switch(type,
+           "spinup" = return(grep(paste0(outputNames[1], ".log"), list.files(outputLoc), value = TRUE)),
+           "normal" = return(grep(paste0(outputNames[2], ".log"), list.files(outputLoc), value = TRUE)),
+           "both" = return(sapply(1:2, function (x){grep(paste0(outputNames[x], ".log"), list.files(outputLoc), value = TRUE)})))
+}
+
+
+#' readErrors
+#'
+#'This function reads the spinup and the normal logfiles and gives back the last line which indicates weather there are any errors during the model execution or not.
+#'
+#'@param outputLoc This is the location of the output file.
+#'@param logfiles These are the names of the logfiles.
+#'@return vector with 0 and 1 values, 1, if succed, 0 if not. The first is the spinup run, the second is the normal.
+#'@keywords internal
+
+
+readErrors <- function(outputLoc, logfiles, type = "both"){
+
+    if(length(logfiles)==0){
+        if(type=="normal"){
+            return(1)
+        } else {
+            return(c(0,0))
+        }
+    } 
+        
+    
+    switch( type,
+           "both" = return(
+               as.numeric(
+                   as.vector(
+                       lapply(paste(outputLoc,logfiles,sep = "/"),
+                              function(x) {
+                                  tail(readLines(x,-1),1) 
+                              }
+                              )
+                   )
+               )
+           ),
+           "spinup" = print("spinup"),
+           "normal" = return(
+               abs(as.numeric(tail(readLines(file.path(outputLoc,logfiles),-1),1))-1)
+           )
+           )
+}
+
+#' getOutFiles
+#'
+#'This function gives us the muso output files with their paths
+#'
+#'@param outputLoc This is the location of the output files.
+#'@param outputNames These are the prefixes of the logfiles.
+#'@return Output files with their paths.
+#'@keywords internal
+
+
+getOutFiles <- function(outputLoc, outputNames){
+
+    return(grep("out$", grep(paste(paste0(outputNames, "*"), collapse = "|"), list.files(outputLoc), value=TRUE), value = TRUE))
+}
+
+#' stampAndCopy
+#'
+#'This function gives us the model output files with their paths
+#'
+#'@param outputLoc This is the location of the output files.
+#'@param outputNames These are the prefixes of the logfiles
+#'@return Output files with their paths
+#'@keywords internal
+
+stampAndDir <- function(outputLoc,names,stampDir, wrongDir, type="output", errorsign, logfiles){
+
+    switch(type,
+        "output" = (
+           file.copy(file.path(outputLoc,names)
+                            ,file.path(stampDir,paste0((stamp(stampDir)+1),"-",names))) ),
+        "general" = (function (){
+            stampnum <- stamp(stampDir)
+            lapply(names,function (x) file.copy(from = x ,to=paste(stampDir,"/",(stampnum+1),"-", basename(x),sep="")))
+            if(errorsign==1){
+                lapply(names, function (x) file.copy(from = paste(stampDir,"/",(stampnum+1),"-",basename(x),sep=""), to=wrongDir))}})()
+
+    )
+
+}
+
+
+
+compareNA <- function(v,a){
+    compared<- (v==a)
+    compared[is.na(compared)] <- FALSE
+    return(compared)
+}
+
+#' dynRound
+#'
+#'This function rounds a sequence (definded by its endpoints and the length) optimally
+#'
+#'@param  x The lower end of the sequence
+#'@param y The higher end of the sequence
+#' @param seqLen The length of the sequence
+#'@return rounded sequence
+#'@keywords internal
+
+dynRound <- function(x,y,seqLen){
+    digitNum <- 2
+    a <- seq(x,y, length = seqLen)
+    while(length(a) != length(unique(round(a,digitNum)))){
+        digitNum <- digitNum +1
+    }
+    
+    return(round(a,digitNum))
+}
+
+
+readValuesFromFile  <- function(epc, linums){
+	epcFile <- readLines(epc)
+	rows <- numeric(2)
+	values <- sapply(linums, function(x){
+	    rows[1] <- as.integer(x)
+	    rows[2] <- as.integer(round(100*x)) %% 10 + 1 
+	    epcFile <- readLines(epc)
+	    selRow <- unlist(strsplit(epcFile[rows[1]], split= "[\t ]"))
+	    selRow <- selRow[selRow!=""]
+	    return(as.numeric(selRow[rows[2]]))
+
+	})
+
+	return(values)
+}
+#' readMeasuredMuso
+#'
+#' MuSo data reader
+#' @importFrom data.table fread data.table
+#' @export
+
+readObservedData <- function(inFile,
+                             naString = NULL, sep = ",",
+                             leapYearHandling = TRUE,
+                             convert.var = NULL,
+                             convert.scalar = 1,
+                             convert.fun = (function (x) {x * convert.scalar}),
+                             convert.file = NULL,
+                             filterCol = NULL,
+                             filterVal = 1,
+                             selVar = NULL
+                             ){
+
+    if(!is.null(naString)){
+        if(is.numeric(naString)){
+            baseData <- fread(file = inFile, sep=sep)
+            baseData <- as.data.frame(baseData)            
+            baseData[baseData[,selVar] == naString,selVar] <- NA        
+        } else {
+            baseData <- fread(file = inFile, sep=sep, na.strings = naString)
+            baseData <- as.data.frame(baseData)                  
+        }
+        
+    
+    } else {
+        
+            baseData <- fread(file = inFile, sep=sep)
+            baseData <- as.data.frame(baseData)            
+    }
+    
+    if(!is.null(filterCol)){
+        filterVar<- colnames(baseData)[filterCol]
+        baseData[(baseData[,filterVar] == filterVal),selVar] <- NA
+    }
+    head(baseData)
+    if(!is.null(selVar)){
+        baseData[,selVar] <-convert.fun(baseData[,selVar])
+    }
+    
+    return(data.table(baseData))
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/atStart.R

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+.onLoad <- function(libname,pkgname){
+    RMuso_version <- 7
+    cat(sprintf("This is RBBGCMuso version 1.0\nDefault Biome-BGCMuSo version: %d",
+                RMuso_version))
+    RMuso_constMatrix <- list(epc=NULL,soil=NULL) 
+    RMuso_varTable <- list()
+    #___________________________
+    sapply(names(RMuso_constMatrix),function(fType){
+        sapply(list.files(path=system.file("data",package="RBBGCMuso"),
+                          pattern=sprintf("^%sConstMatrix\\d\\.json$",fType), full.names=TRUE),function(fName){
+            constMatrix <- jsonlite::read_json(fName,simplifyVector = TRUE)[,c(1,2,3,4,9,5,6,7,8)]
+            version <- gsub(".*(\\d)\\.json","\\1",fName)
+            RMuso_constMatrix[[fType]][[version]] <<- constMatrix
+        })
+        RMuso_constMatrix
+        # RMuso_constMatrix <<- RMuso_constMatrix 
+    })
+
+
+        sapply(list.files(path=system.file("data",package="RBBGCMuso"),
+                          pattern="^varTable\\d\\.json$", full.names=TRUE),function(fName){
+            varTable <- jsonlite::read_json(fName,simplifyVector = TRUE)
+            version <- gsub(".*(\\d)\\.json","\\1",fName)
+            RMuso_varTable[[version]] <<- varTable
+        })
+
+    RMuso_depTree<- read.csv(file.path(system.file("data",package="RBBGCMuso"),"depTree.csv"), stringsAsFactors=FALSE)
+
+
+    options(RMuso_version=RMuso_version,
+            RMuso_constMatrix=RMuso_constMatrix,
+            RMuso_varTable=RMuso_varTable,
+            RMuso_depTree=RMuso_depTree
+    )
+    # getOption("RMuso_constMatrix")$soil[[as.character(getOption("RMuso_version"))]]
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/calibMuso.R

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+#' calibMuso 
+#'
+#' This function changes the epc file and after that  runs the BBGC-MuSo model and reads in its outputfile in a well-structured way.
+#' 
+#' @author Roland Hollos
+#' @param settings You have to run the setupMuso function before calibMuso. It is its output which contains all of the necessary system variables. It sets the whole running environment
+#' @param timee The required timesteps in the modell output. It can be "d", if it is daily, "m", if it's monthly, "y", it it is yearly. I recommend to use daily data, the yearly and monthly data is not well-tested yet. 
+#' @param debugging If it is TRUE, it copies the log file to a Log directory to store it, if it is stamplog it contatenate a number before the logfile, which is one more than the maximum of the represented ones in the LOG directory. If it is true or stamplog it collects the "wrong" logfiles
+#' @param keepEpc If TRUE, it keeps the epc file and stamp it, after these copies it to the EPCS directory. If debugging True or false, it copies the wrong epc files to the wrong epc directory.
+#' @param export if it is yes or you give a filename here, it converts the ouxtput to the specific extension. For example, if you set export to "example.csv", it converts the output to "csv", if you set it to "example.xls" it converts to example.xls with the xlsx package. If it is not installed it gives back a warning message and converts it to csv.
+#' @param silent If you set it TRUE all off the modells output to the screen will be suppressed. It can be usefull, because it increases the model-speed.
+#' @param aggressive It deletes every possible modell-outputs from the previous modell runs.
+#' @param parameters In the settings variable you have set the row indexes of the variables, you wish to change. In this parameter you can give an exact value for them in a vector like: c(1,2,3,4)
+#' @param logfilename If you want to set a specific name for your logfiles you can set this via logfile parameter
+#' @param leapYear  Should the function do a leapyear correction on the outputdata? If TRUE, then the 31.12 day will be doubled.
+#' @param keepBinary In default RBBGCMuso to keep  working area as clean as possible, deletes all the regular output files. The results are directly printed to the standard output, but you can redirect it, and save it to a variable, or you can export your results to the desired destination in a desired format. Whith this variable you can enable to keep the binary output files. If you want to set the location of the binary output, please take a look at the binaryPlace argument.
+#' @param binaryPlace The place of the binary output files.
+#' @param fileToChange You can change any line of the epc or the ini file, you just have to specify with this variable which file you van a change. Two options possible: "epc", "ini"
+#' @param skipSpinup If TRUE, calibMuso wont do spinup simulation
+#' @param prettyOut date ad Date type, separate year, month, day vectors
+#' @return No return, outputs are written to file 
+#' @usage calibMuso(settings,parameters=NULL, timee="d", debugging=FALSE, logfilename=NULL,
+#' keepEpc=FALSE, export=FALSE, silent=FALSE, aggressive=FALSE, leapYear=FALSE)
+#' @import utils
+#' @export
+
+calibMuso <- function(settings=setupMuso(), calibrationPar=NULL,
+                      parameters=NULL, outVars = NULL, timee="d",
+                      debugging=FALSE, logfilename=NULL,
+                      keepEpc=FALSE, export=FALSE,
+                      silent=FALSE, aggressive=FALSE,
+                      keepBinary=FALSE,
+                      binaryPlace = "./", fileToChange = "epc",
+                      skipSpinup = TRUE, modifyOriginal = FALSE, prettyOut = FALSE,
+                      postProcString = NULL,
+                      doBackup=TRUE
+                      ){ #
+########################################################################
+###########################Set local variables and places###############
+########################################################################
+    if(doBackup){
+        file.copy(eval(parse(text = sprintf("settings$%sInput[2]", fileToChange))),file.path(settings$inputLoc),overwrite=FALSE)
+    }
+
+    bck  <- file.path(settings$inputLoc, "bck",
+                      basename(eval(parse(text = sprintf("settings$%sInput[2]", fileToChange))))) 
+
+    if(!silent){
+        cat("Biome-BGC simulation started\n") # ZOLI
+    }
+    
+    Linuxp <-(Sys.info()[1]=="Linux")
+    ##Copy the variables from settings
+    inputLoc <- settings$inputLoc
+    outputLoc <- settings$outputLoc
+    outputNames <- settings$outputNames
+    executable <- settings$executable
+    iniInput <- settings$iniInput
+    epc <- settings$epcInput
+
+    if(is.null(calibrationPar)){
+        calibrationPar <- settings$calibrationPar
+    }
+    binaryPlace <- normalizePath(binaryPlace)
+    whereAmI<-getwd()
+
+
+    ## Set the working directory to the inputLoc temporarly.
+    setwd(inputLoc)
+
+      
+    if(debugging){#If debugging option turned on
+        #If log or ERROR directory does not exists create it!
+        dirName<-file.path(inputLoc,"LOG")
+        dirERROR<-file.path(inputLoc,"ERROR")
+        
+        if(!dir.exists(dirName)){
+            dir.create(dirName)
+        }
+
+        if(!dir.exists(dirERROR)){
+            dir.create(dirERROR)
+        }
+    }
+    
+    if(keepEpc) {
+        epcdir <- dirname(epc[1])
+        print(epcdir)
+        WRONGEPC<-file.path(inputLoc,"WRONGEPC")
+        EPCS<-file.path(inputLoc,"EPCS")
+        
+        if(!dir.exists(WRONGEPC)){
+            dir.create(WRONGEPC)
+        }
+        
+        if(!dir.exists(EPCS)){
+            dir.create(EPCS)
+        }
+    }   
+
+#############################################################
+############################spinup run############################
+   ########################################################## 
+
+    
+    
+
+     if(aggressive == TRUE){
+         cleanupMuso(location = outputLoc,deep = TRUE)
+     }
+
+    
+    ##change the epc file if and only if there are given parameters
+       
+    if(!is.null(parameters)){
+        changemulline(filePaths = epc[2],
+                      calibrationPar = calibrationPar,
+                      contents = parameters,
+                      src = if(file.exists(bck)){
+                          bck
+                      } else {
+                          NULL
+                      })
+                       # fileToChange = fileToChange,)
+    }
+    
+
+    ##We change the working directory becase of the model, but we want to avoid sideeffects, so we save the current location and after that we will change everything to it.
+    
+   if(!skipSpinup) {
+
+    ##Run the model for the spinup run.
+
+    if(silent){#silenc mode
+        if(Linuxp){
+            #In this case, in linux machines
+            tryCatch(system(paste(executable,iniInput[1],"> /dev/null",sep=" ")),
+                     error= function (e){
+                         setwd((whereAmI))
+                         stop("Cannot run the modell-check the executable!")})
+        } else {
+            #In windows machines there is a show.output.on.console option
+            tryCatch(system(paste(executable,iniInput[1],sep=" "),show.output.on.console = FALSE),
+                     error= function (e){
+                         setwd((whereAmI))
+                         stop("Cannot run the modell-check the executable!")})
+        }
+        
+    } else {
+        system(paste(executable,iniInput[1],sep=" "))
+    }
+
+    
+    logspinup <- getLogs(outputLoc,outputNames,type="spinup")
+    ## logspinup <- grep(paste0(outputNames[1],".log"), list.files(outputLoc),value = TRUE)
+    ## logspinup <- list.files(outputLoc)[grep("log$",list.files(outputLoc))]#load the logfiles
+    
+    if(length(logspinup)==0){
+        if(keepEpc){
+            stampnum<-stamp(EPCS)
+            lapply(epc,function (x) file.copy(from = x ,to=paste(EPCS,"/",(stampnum+1),"-", basename(x),sep="")))
+            lapply(epc, function (x) file.copy(from = paste(EPCS,"/",(stampnum+1),"-",basename(x),sep=""), to=WRONGEPC))
+            setwd(whereAmI)
+            stop("Modell Failure")
+        }
+        setwd(whereAmI)
+        stop("Modell Failure") #in that case the modell did not create even a logfile
+    }
+
+    if(length(logspinup)>1){
+        spincrash<-TRUE
+    } else {
+        if(identical(tail(readLines(paste(outputLoc,logspinup,sep="/"),-1),1),character(0))){
+            spincrash<-TRUE
+        } else {
+            spincrash <- (tail(readLines(paste(outputLoc,logspinup,sep="/"),-1),1)!=1)
+        }
+    }
+    } else {spincrash <- FALSE}
+                                        #If the last line in the logfile is 0 There are mistakes so the spinup crashes
+    
+    if(!spincrash){##If spinup did not crashed, run the normal run.
+        
+       ##################################################################### 
+       ###########################normal run#########################
+      #################################################################
+
+        ##for the sake of safe we set the location again
+        setwd(inputLoc)
+
+        if(silent){
+            if(Linuxp){
+                tryCatch(system(paste(executable,iniInput[2],"> /dev/null",sep=" ")),
+                         error =function (e){
+                             setwd((whereAmI))
+                             stop("Cannot run the modell-check the executable!")})
+            } else {
+                tryCatch(system(paste(executable,iniInput[2],sep=" "),show.output.on.console = FALSE),
+                         error =function (e){
+                             setwd((whereAmI))
+                             stop("Cannot run the modell-check the executable!")} )
+            }
+            
+        } else {
+            tryCatch(system(paste(executable,iniInput[2],sep=" ")),
+                     error =function (e){
+                         setwd((whereAmI))
+                         stop("Cannot run the modell-check the executable!")})
+        }
+
+
+        ##read the output
+         
+        switch(timee,
+               "d"=(Reva <- tryCatch(getdailyout(settings), #(:INSIDE: getOutput.R )
+                                    error = function (e){
+                                        setwd((whereAmI))
+                                        stop("Cannot read binary output, please check if the output type is set 2 in the ini files!")})),
+               "m"=(Reva <- tryCatch(getmonthlyout(settings), #(:INSIDE: getOutput.R )
+                                    error = function (e){
+                                        setwd((whereAmI))
+                                        stop("Cannot read binary output, please check if the output type is set 2 in the ini files!")})),
+               "y"=(Reva <- tryCatch(getyearlyout(settings), #(:INSIDE: getOutput.R )
+                                    error = function (e){
+                                        setwd((whereAmI))
+                                        stop("Cannot read binary output, please check if the output type is set 2 in the ini files!")}))
+               )
+        if(keepBinary){
+            possibleNames <- tryCatch(getOutFiles(outputLoc = outputLoc,outputNames = outputNames),
+                                     error=function (e){
+                                         setwd((whereAmI))
+                                         stop("Cannot find output files")})
+            stampAndDir(outputLoc = outputLoc,names = possibleNames,stampDir=binaryPlace,type="output")
+        }
+    }
+
+    
+    if(skipSpinup){
+       logfiles <- tryCatch(getLogs(outputLoc,outputNames,type="normal"),
+                                error = function (e){
+                                    setwd(whereAmI)
+                                    stop("Cannot find log files, something went wrong")})
+    } else {
+        logfiles <- tryCatch(getLogs(outputLoc,outputNames,type="both"),
+                                error = function (e){
+                                    setwd(whereAmI)
+                                    stop("Cannot find log files, something went wrong")})
+    }
+    ## list.files(outputLoc)[grep("log$",list.files(outputLoc))]#creating a vector for logfilenames
+
+###############################################    
+#############LOG SECTION#######################
+###############################################
+
+    if(skipSpinup){
+        errorsign <- readErrors(outputLoc=outputLoc,logfiles=logfiles,type="normal")
+    } else {
+
+        perror <- readErrors(outputLoc=outputLoc,logfiles=logfiles)                                    #vector of spinup and normalrun error
+        
+        
+        ##if errorsign is 1 there is error, if it is 0 everything ok
+        perror[is.na(perror)]<-0
+        if(length(perror)>sum(perror)){
+        errorsign <- 1
+        } else {
+            if(length(perror)==1){
+                errorsign <- 1
+            } else {
+                if(spincrash){
+                    errorsign <- 1
+                } else {
+                    errorsign <- 0
+                } }
+        }
+        
+        
+        
+    }
+        
+    
+    
+
+    if(keepEpc){#if keepepc option turned on
+
+        if(length(unique(dirname(epc)))>1){
+            stop("Why are you playing with my nervs? Seriously? You hold your epc-s in different folders?")
+        } else {
+            if(skipSpinup){
+                stampAndDir(stampDir=EPCS, wrongDir=WRONGEPC, names=epc[2], type="general", errorsign=errorsign, logfiles=logfiles)
+            }
+            stampAndDir(stampDir=EPCS, wrongDir=WRONGEPC, names=epc, type="general", errorsign=errorsign, logfiles=logfiles)
+
+        }
+    }
+    
+
+
+    if(debugging){ #debugging is boolean
+        logfiles <- file.path(outputLoc,logfiles)
+        
+                       stampAndDir(stampDir=dirName, wrongDir=dirERROR, names=logfiles, type="general",errorsign=errorsign,logfiles=logfiles)}
+  
+    
+    #cleanupMuso(location=outputLoc,deep = FALSE)
+    if(errorsign==1){
+        stop("Modell Failure")
+    }
+
+    
+
+    
+    if(timee=="d"){
+        if(!prettyOut){
+            colnames(Reva) <- unlist(settings$outputVars[[1]])
+        } else{
+            Reva <- cbind.data.frame(
+                musoDate(startYear = settings$startYear,
+                         numYears = settings$numYears,
+                         combined = FALSE, prettyOut = TRUE),
+                Reva)
+            colnames(Reva) <- as.character(c("date","day","month","year",unlist(settings$outputVars[[1]])) )
+            
+        }
+    } else {
+        if(timee=="y")
+            colnames(Reva) <- unlist(settings$outputVars[[2]])
+    }
+
+    if(!is.null(postProcString)){
+        Reva <- postProcMuso(Reva,postProcString)
+    }
+
+    ## if(leapYear){
+    ##     Reva <- corrigMuso(settings,Reva)
+    ##     if(!prettyOut){
+    ##         rownames(Reva) <- musoDate(settings$startYear,settings$numYears)            
+    ##     }
+
+    ## } else {
+    ##     if(!prettyOut){
+    ##         rownames(Reva) <- musoDate(settings$startYear, settings$numYears)    
+    ##     }
+        
+    ## }
+    
+    if(!prettyOut){
+        rownames(Reva) <- musoDate(settings$startYear, numYears = settings$numYears)
+   }
+
+    
+    if(export!=FALSE){
+        setwd(whereAmI)
+
+        ## switch(fextension(export),
+        ##        "csv"=(write.csv(Reva,export)),
+        ##        "xlsx"=(),
+        ##        "odt"=
+                  
+            
+        ## )
+        write.csv(Reva,export)
+        
+    } else{
+        setwd(whereAmI)
+        return(Reva)
+    }
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/calibrateMuso.R

@@ -0,0 +1,396 @@
+#' calibrateMuso
+#'
+#' This funtion uses the Monte Carlo technique to uniformly sample the parameter space from user defined parameters of the Biome-BGCMuSo model. The sampling algorithm ensures that the parameters are constrained by the model logic which means that parameter dependencies are fully taken into account (parameter dependency means that e.g leaf C:N ratio must be smaller than C:N ratio of litter; more complicated rules apply to the allocation parameters where the allocation fractions to different plant compartments must sum up 1). This function implements a mathematically correct solution to provide uniform distriution for all selected parameters. 
+#' @author Roland HOLLOS
+#' @importFrom future future
+#' @export
+calibrateMuso <- function(measuredData, parameters =read.csv("parameters.csv", stringsAsFactor=FALSE), startDate = NULL,
+                     endDate = NULL, formatString = "%Y-%m-%d",
+                     dataVar, outLoc = "./calib",
+                     preTag = "cal-", settings =  setupMuso(),
+                     outVars = NULL, iterations = 100,
+                     skipSpinup = TRUE, plotName = "calib.jpg",
+                     modifyOriginal=TRUE, likelihood, uncertainity = NULL,
+                     naVal = NULL, postProcString = NULL,
+                     thread_prefix="thread", numCores = max(c(parallel::detectCores()-1,1)), pb = txtProgressBar(min=0, max=iterations, style=3),
+                     maxLikelihoodEpc=TRUE,
+                     pbUpdate = setTxtProgressBar, outputLoc="./", method="GLUE",lg = FALSE, w=NULL, ...){
+
+    future::plan(future::multisession)
+    file.remove(list.files(path = settings$inputLoc, pattern="progress.txt", recursive = TRUE, full.names=TRUE))
+    file.remove(list.files(path = settings$inputLoc, pattern="preservedCalib.csv", recursive = TRUE, full.names=TRUE))
+    unlink(file.path(settings$inputLoc,"thread"),recursive=TRUE)
+
+    #   ____                _         _   _                        _     
+    #  / ___|_ __ ___  __ _| |_ ___  | |_| |__  _ __ ___  __ _  __| |___ 
+    # | |   | '__/ _ \/ _` | __/ _ \ | __| '_ \| '__/ _ \/ _` |/ _` / __|
+    # | |___| | |  __/ (_| | ||  __/ | |_| | | | | |  __/ (_| | (_| \__ \
+    #  \____|_|  \___|\__,_|\__\___|  \__|_| |_|_|  \___|\__,_|\__,_|___/
+                                                                       
+    
+
+    copyToThreadDirs(thread_prefix, numcores = numCores, runDir = settings$inputLoc)
+
+    #  ____                _   _                        _     
+    # |  _ \ _   _ _ __   | |_| |__  _ __ ___  __ _  __| |___ 
+    # | |_) | | | | '_ \  | __| '_ \| '__/ _ \/ _` |/ _` / __|
+    # |  _ <| |_| | | | | | |_| | | | | |  __/ (_| | (_| \__ \
+    # |_| \_\\__,_|_| |_|  \__|_| |_|_|  \___|\__,_|\__,_|___/
+                                                            
+    threadCount <- distributeCores(iterations, numCores) 
+
+    fut <- lapply(1:numCores, function(i) {
+                      # browser()
+         future({
+                      tryCatch(
+                               musoSingleThread(measuredData, parameters, startDate,
+                                        endDate, formatString,
+                                        dataVar, outLoc,
+                                        preTag, settings,
+                                        outVars, iterations = threadCount[i],
+                                        skipSpinup, plotName,
+                                        modifyOriginal, likelihood, uncertainity,
+                                        naVal, postProcString, i)
+                      , error = function(e){
+                                            writeLines(as.character(iterations),"progress.txt")
+                                        })
+
+                      # musoSingleThread(measuredData, parameters, startDate,
+                      #                  endDate, formatString,
+                      #                  dataVar, outLoc,
+                      #                  preTag, settings,
+                      #                  outVars, iterations = threadCount[i],
+                      #                  skipSpinup, plotName,
+                      #                  modifyOriginal, likelihood, uncertainity,
+                      #                  naVal, postProcString, i)
+         })
+    })
+
+    # __        ___           _       _                                         
+    # \ \      / / |__   __ _| |_ ___| |__    _ __  _ __ ___   ___ ___  ___ ___ 
+    #  \ \ /\ / /| '_ \ / _` | __/ __| '_ \  | '_ \| '__/ _ \ / __/ _ \/ __/ __|
+    #   \ V  V / | | | | (_| | || (__| | | | | |_) | | | (_) | (_|  __/\__ \__ \
+    #    \_/\_/  |_| |_|\__,_|\__\___|_| |_| | .__/|_|  \___/ \___\___||___/___/
+    #                                        |_|                                
+
+    getProgress <- function(){
+        # threadfiles <- list.files(settings$inputLoc, pattern="progress.txt", recursive = TRUE)
+        threadfiles <- list.files(pattern="progress.txt", recursive = TRUE)
+        if(length(threadfiles)==0){
+            return(0)
+        } else {
+            sum(sapply(threadfiles, function(x){
+                           partRes <- readLines(x)
+                           if(length(partRes)==0){
+                               return(0)
+                           } else {
+                               return(as.numeric(partRes))
+                           }
+
+         }))
+
+        }
+    }
+
+    progress <- 0
+    while(progress < iterations){
+        Sys.sleep(1)
+        progress <- tryCatch(getProgress(), error=function(e){progress})
+        if(is.null(pb)){
+            pbUpdate(as.numeric(progress))
+        } else {
+            pbUpdate(pb,as.numeric(progress))
+        }
+    }
+    if(!is.null(pb)){
+        close(pb)
+    }
+
+    #   ____                _     _            
+    #  / ___|___  _ __ ___ | |__ (_)_ __   ___ 
+    # | |   / _ \| '_ ` _ \| '_ \| | '_ \ / _ \
+    # | |__| (_) | | | | | | |_) | | | | |  __/
+    #  \____\___/|_| |_| |_|_.__/|_|_| |_|\___|
+    resultFiles <- list.files(pattern="preservedCalib.*csv$",recursive=TRUE)
+    res0 <- read.csv(grep("thread_1/",resultFiles, value=TRUE),stringsAsFactors=FALSE)
+    if(numCores==1){
+        results <- res0
+    } else {
+        resultFilesSans0 <- grep("thread_1/", resultFiles, value=TRUE, invert=TRUE)
+        # results <- do.call(rbind,lapply(resultFilesSans0, function(f){read.csv(f, stringsAsFactors=FALSE)}))
+        resultsSans0 <- lapply(resultFilesSans0, function(f){read.csv(f, stringsAsFactors=FALSE, header=FALSE)})
+        resultsSans0 <- do.call(rbind,resultsSans0)
+        colnames(resultsSans0) <- colnames(res0)
+        results <- (rbind(res0,resultsSans0))
+    }
+
+    switch(method,
+           "GLUE"={  
+                musoGlue(results, parameters=parameters,settings=settings, w=w, lg=lg)
+           },
+           "agromo"={
+                liks <- results[,sprintf("%s_likelihood",names(likelihood))]    
+                epcIndexes <- future::value(fut[[1]], stdout = FALSE, signal=FALSE)
+                epcVals <- results[which.max(liks),1:length(epcIndexes)]
+                epcPlace <- file.path(dirname(settings$inputFiles),settings$epc)[2]
+                changemulline(filePaths= epcPlace, epcIndexes,
+                              epcVals, src =epcPlace,# settings$epcInput[2],
+                              outFiles = file.path(outputLoc, "maxLikelihood_epc.epc"))
+                names(epcVals) <- epcIndexes
+                xdate <- as.Date(measuredData$date) 
+                meanM <- measuredData[,sprintf("mean.%s", names(likelihood))]
+                minsd <-  meanM - measuredData[,sprintf("sd.%s", names(likelihood)[1])]
+                maxsd <- meanM + measuredData[,sprintf("sd.%s", names(likelihood)[1])]
+                minM <- measuredData[,sprintf("min.%s", names(likelihood)[1])]
+                maxM <- measuredData[,sprintf("max.%s", names(likelihood)[1])]
+                plot(xdate, minM, type="l", xlab=NA, ylim=c(min(minM)*0.8, max(maxM)*1.1), ylab = names(likelihood)[1])
+                lines(xdate, maxM)
+                polygon(c(xdate,rev(xdate)),c(minM,rev(maxM)), col="gray",border=NA)
+                lines(xdate, minsd)
+                lines(xdate, maxsd)
+                polygon(c(xdate,rev(xdate)),c(minsd,rev(maxsd)), col="gray30",border=NA)
+                points(xdate,meanM)
+
+                varIndex <- match(as.character(dataVar),settings$dailyVarCodes)
+                apriori <- calibMuso(settings)
+                modDates <- as.Date(row.names(apriori), format="%d.%m.%Y")
+                lines(modDates, apriori[,varIndex],col="brown")
+                calibrated <- calibMuso(settings, calibrationPar = as.numeric(names(epcVals)), parameters=epcVals)
+                lines(modDates, calibrated[,varIndex],col="blue")
+
+           },
+           stop(sprintf("method: %s not found, please choose from {GLUE, agromo}. See more about this in the documentation of the function!", method))
+    )
+}
+
+copyToThreadDirs <- function(prefix="thread", numcores=parallel::detectCores()-1, runDir="."){
+    dir.create(file.path(runDir,prefix), showWarnings=TRUE)
+    fileNames <- grep(".*thread$", list.files(runDir,full.names=TRUE), value=TRUE, invert=TRUE)
+    invisible(sapply(1:numcores,function(corenum){
+                threadDir <- file.path(runDir,prefix,paste0(prefix,"_",corenum),"")
+                dir.create(threadDir, showWarnings=FALSE)
+                file.copy(from=fileNames,to=threadDir, overwrite=FALSE, recursive=TRUE)
+    }))
+}
+
+musoSingleThread <- function(measuredData, parameters = NULL, startDate = NULL,
+                     endDate = NULL, formatString = "%Y-%m-%d",
+                     dataVar, outLoc = "./calib",
+                     preTag = "cal-", settings =  setupMuso(),
+                     outVars = NULL, iterations = 300,
+                     skipSpinup = TRUE, plotName = "calib.jpg",
+                     modifyOriginal=TRUE, likelihood, uncertainity = NULL,
+                     naVal = NULL, postProcString = NULL, threadNumber) {
+
+    setwd(paste0(settings$inputLoc, "/thread/thread_", threadNumber))
+
+    iniFiles <- file.path(settings$iniInput) 
+    # iniFiles <- list.files(pattern=".*ini")
+    # if(length(iniFiles)==1){
+    #     iniFiles <- rep(iniFiles, 2)
+    # }
+    settings <- setupMuso(iniInput = iniFiles)
+    # Exanding likelihood
+
+    likelihoodFull <- as.list(rep(NA,length(dataVar)))
+    names(likelihoodFull) <- names(dataVar)
+    if(!missing(likelihood)) {
+        lapply(names(likelihood),function(x){
+                   likelihoodFull[[x]] <<- likelihood[[x]]
+                     })
+    }
+   defaultLikelihood <- which(is.na(likelihood))
+   if(length(defaultLikelihood)>0){
+        likelihoodFull[[defaultLikelihood]] <- (function(x, y){
+                                                       exp(-sqrt(mean((x-y)^2)))
+                                                })
+   }
+
+    mdata <- measuredData
+    if(is.null(parameters)){
+        parameters <- tryCatch(read.csv("parameters.csv", stringsAsFactor=FALSE), error = function (e) {
+            stop("You need to specify a path for the parameters.csv, or a matrix.")
+        })
+    } else {
+        if((!is.list(parameters)) & (!is.matrix(parameters))){
+            parameters <- tryCatch(read.csv(parameters, stringsAsFactor=FALSE), error = function (e){
+                stop("Cannot find neither parameters file neither the parameters matrix")
+            })
+        }}
+
+    outLoc <- normalizePath(outLoc)
+    outLocPlain <- basename(outLoc)
+    currDir <- getwd()
+
+    if(!dir.exists(outLoc)){
+        dir.create(outLoc)
+        warning(paste(outLoc," is not exists, so it was created"))
+    }
+
+    outLoc <- normalizePath(outLoc)
+    parameterNames <- parameters[,1]
+    pretag <- file.path(outLoc,preTag)
+    ##reading the original epc file at the specified
+    ## row numbers
+    print("optiMuso is randomizing the epc parameters now...",quote = FALSE)
+    if(iterations < 3000){
+        randVals <- musoRand(parameters = parameters,constrains = NULL, iterations = 3000)
+        randVals[[2]]<- randVals[[2]][sample(1:3000,iterations),]
+    } else {
+        randVals <- musoRand(parameters = parameters,constrains = NULL, iterations = iterations)
+    }
+
+    origEpc <- readValuesFromFile(settings$epc[2],randVals[[1]])
+    partialResult <- matrix(ncol=length(randVals[[1]])+2*length(dataVar))
+    colN <- randVals[[1]]
+    colN[match(parameters[,2],randVals[[1]])] <- parameters[,1]
+    colN[match(parameters[,2], randVals[[1]])[!is.na(match(parameters[,2],randVals[[1]]))]] <- parameters[,1]
+    colnames(partialResult) <- c(colN,sprintf("%s_likelihood",names(dataVar)),
+                                      sprintf("%s_rmse",names(dataVar)))
+    numParameters <- length(colN)
+    partialResult[1:numParameters] <- origEpc
+    ## Prepare the preservedCalib matrix for the faster
+    ##  run.
+
+    pretag <- file.path(outLoc,preTag)
+
+     musoCodeToIndex  <- sapply(dataVar,function(musoCode){
+           settings$dailyOutputTable[settings$dailyOutputTable$code == musoCode,"index"]
+        })
+    resultRange <- (numParameters + 1):(ncol(partialResult))
+    ## Creating function for generating separate
+    ## csv files for each run
+
+    settings$iniInput[2] %>%
+        (function(x) paste0(dirname(x),"/",tools::file_path_sans_ext(basename(x)),"-tmp.",tools::file_ext(x))) %>%
+        unlink
+    randValues <- randVals[[2]]
+
+    settings$calibrationPar <- randVals[[1]]
+
+    if(!is.null(naVal)){
+        measuredData <- as.data.frame(measuredData)
+        measuredData[measuredData == naVal] <- NA
+    }
+
+    alignIndexes <- alignMuso(settings,measuredData)
+    if(!is.null(uncertainity)){
+        uncert <- measuredData[alignIndexes$meas,uncertainity]
+    } else {
+        uncert <- NULL
+    }
+    # browser()
+    if(threadNumber == 1){
+        origModellOut <- calibMuso(settings=settings, silent=TRUE, skipSpinup = skipSpinup, postProcString=postProcString, modifyOriginal=modifyOriginal)
+        partialResult[,resultRange] <- calcLikelihoodsAndRMSE(dataVar=dataVar, 
+                                                              mod=origModellOut,
+                                                              mes=measuredData,
+                                                              likelihoods=likelihood,
+                                                               alignIndexes=alignIndexes,
+                                                               musoCodeToIndex = musoCodeToIndex,uncert=uncert)
+        write.csv(x=origModellOut, file=paste0(pretag, 1, ".csv"))
+    write.csv(x=partialResult, file="preservedCalib.csv",row.names=FALSE)
+    }
+    print("Running the model with the random epc values...", quote = FALSE)
+
+    # if(!is.null(postProcString)){
+    #     colNumb <- length(settings$dailyVarCodes) + 1
+    # }
+    
+
+    for(i in 2:(iterations+1)){
+
+        tmp <- tryCatch(calibMuso(settings = settings,
+                                  parameters = randValues[(i-1),],
+                                  silent= TRUE,
+                                  skipSpinup = skipSpinup, modifyOriginal=modifyOriginal, postProcString = postProcString), error = function (e) NULL)
+        if(is.null(tmp)){
+           partialResult[,resultRange] <- NA
+        } else {
+            partialResult[,resultRange] <- calcLikelihoodsAndRMSE(dataVar=dataVar, 
+                                                          mod=tmp,
+                                                          mes=measuredData,
+                                                          likelihoods=likelihood,
+                                                           alignIndexes=alignIndexes,
+                                                           musoCodeToIndex = musoCodeToIndex, uncert = uncert)
+        }
+
+        partialResult[1:numParameters] <- randValues[(i-1),]
+        write.table(x=partialResult, file="preservedCalib.csv", append=TRUE, row.names=FALSE,
+                    sep=",", col.names=FALSE)
+        write.csv(x=tmp, file=paste0(pretag, (i+1),".csv"))
+        writeLines(as.character(i-1),"progress.txt")
+    }
+
+    if(threadNumber == 1){
+        return(randVals[[1]])
+    }
+
+}
+
+distributeCores <- function(iterations, numCores){
+    perProcess<- iterations %/% numCores
+    numSimu <- rep(perProcess,numCores)
+    gainers <- sample(1:numCores, iterations %% numCores)
+    numSimu[gainers] <- numSimu[gainers] + 1
+    numSimu
+}
+
+prepareFromAgroMo <- function(fName){
+    obs <- read.table(fName, stringsAsFactors=FALSE, sep = ";", header=T)
+    obs <- reshape(obs, timevar="var_id", idvar = "date", direction = "wide")
+    dateCols <- apply(do.call(rbind,(strsplit(obs$date, split = "-"))),2,as.numeric)
+    colnames(dateCols) <- c("year", "month", "day")
+    cbind.data.frame(dateCols, obs)
+}
+
+
+calcLikelihoodsAndRMSE <- function(dataVar, mod, mes, likelihoods, alignIndexes, musoCodeToIndex, uncert){
+
+     mes <- as.data.frame(mes)
+    # NOT COMPATIBLE WITH OLD  MEASUREMENT DATA, mes have to be a matrix
+    likelihoodRMSE <- sapply(names(dataVar),function(key){
+               modelled <- mod[alignIndexes$mod,musoCodeToIndex[key]]
+               selected <- grep(sprintf("%s$", key), colnames(mes))
+               # browser()
+
+               measured <- mes[alignIndexes$meas,selected]
+
+               if(is.null(dim(measured))){
+                   notNA <- !is.na(measured)             
+                   m <- measured <- measured[notNA]
+                    
+               } else {
+                   notNA <- sapply(1:nrow(measured), function(x){!any(is.na(measured[x,]))})
+                   measured <- measured[notNA,]
+                   m <- measured[,grep("^mean", colnames(measured))]
+               }
+                   modelled <- modelled[notNA] 
+
+               # uncert   <-   uncert[!is.na(measured)]
+
+               # measured <- measured[!is.na(measured)] 
+               res <- c(likelihoods[[key]](modelled, measured),
+                        sqrt(mean((modelled-m)^2))
+               )
+               # browser()
+               res
+        })
+    names(likelihoodRMSE) <- c(sprintf("%s_likelihood",dataVar), sprintf("%s_rmse",dataVar))
+    return(c(likelihoodRMSE[1,],likelihoodRMSE[2,]))
+}
+
+agroLikelihood <- function(modVector,measured){
+    mu <- measured[,grep("mean", colnames(measured))]
+    stdev <- measured[,grep("^sd", colnames(measured))]
+    ndata <- nrow(measured)
+    sum(sapply(1:ndata, function(x){
+                  dnorm(modVector, mu[x], stdev[x], log = TRUE)
+               }), na.rm=TRUE)
+}
+
+
+
+maxLikelihoodAgromo <- function (results, imgPath, varName, ...) {
+    
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/calibration.R

@@ -0,0 +1,311 @@
+#' optiMuso
+#'
+#' This function calculates the -users specified- likelihood for random model input.
+#'
+#' @author Roland HOLLOS
+#' @param measuredDataFile a
+#' @param parameters b
+#' @param sep c
+#' @param startDate d
+#' @param endDate e
+#' @param formatString a
+#' @param filterCol a
+#' @param filterVal b
+#' @param selVar c
+#' @param outLoc c
+#' @param pretag a
+#' @param calPar a
+#' @param skipSpinup a
+#' @param iterations c
+#' @param constrains d
+#' @param likelihood d
+#' @param settings e
+#' @param leapYear b
+#' @param plotName u
+#' @importFrom ggplot2 ggplot aes_string geom_point ggsave
+#' @importFrom magrittr '%>%'
+#' @importFrom gridExtra grid.arrange
+#' @export
+optiMuso <- function(measuredData, parameters = NULL, startDate = NULL,
+                     endDate = NULL, formatString = "%Y-%m-%d",
+                     dataVar, outLoc = "./calib",
+                     preTag = "cal-", settings =  setupMuso(),
+                     outVars = NULL, iterations = 30,
+                     skipSpinup = TRUE, plotName = "calib.jpg",
+                     modifyOriginal=TRUE, likelihood, uncertainity = NULL,
+                     naVal = NULL, postProcString = NULL, w=NULL, lg=FALSE, parallel = TRUE) {
+    # Exanding likelihood
+    likelihoodFull <- as.list(rep(NA,length(dataVar)))
+    names(likelihoodFull) <- names(dataVar)
+    if(!missing(likelihood)) {
+        lapply(names(likelihood),function(x){
+                   likelihoodFull[[x]] <<- likelihood[[x]]
+                     })
+    }
+   defaultLikelihood <- which(is.na(likelihood))
+   if(length(defaultLikelihood)>0){
+        likelihoodFull[[defaultLikelihood]] <- (function(x, y){
+                                                       exp(-sqrt(mean((x-y)^2)))
+                                                })
+   }
+
+    mdata <- measuredData
+    if(is.null(parameters)){
+        parameters <- tryCatch(read.csv("parameters.csv", stringsAsFactor=FALSE), error = function (e) {
+            stop("You need to specify a path for the parameters.csv, or a matrix.")
+        })
+    } else {
+        if((!is.list(parameters)) & (!is.matrix(parameters))){
+            parameters <- tryCatch(read.csv(parameters, stringsAsFactor=FALSE), error = function (e){
+                stop("Cannot find neither parameters file neither the parameters matrix")
+            })
+        }}
+
+    outLoc <- normalizePath(outLoc)
+    outLocPlain <- basename(outLoc)
+    currDir <- getwd()
+
+    if(!dir.exists(outLoc)){
+        dir.create(outLoc)
+        warning(paste(outLoc," is not exists, so it was created"))
+    }
+
+    outLoc <- normalizePath(outLoc)
+    parameterNames <- parameters[,1]
+    pretag <- file.path(outLoc,preTag)
+    ##reading the original epc file at the specified
+    ## row numbers
+    print("optiMuso is randomizing the epc parameters now...",quote = FALSE)
+    if(iterations < 3000){
+        randVals <- musoRand(parameters = parameters,constrains = NULL, iterations = 3000)
+        randVals[[2]]<- randVals[[2]][sample(1:3000,iterations),]
+    } else {
+        randVals <- musoRand(parameters = parameters,constrains = NULL, iterations = iterations)
+    }
+
+    origEpc <- readValuesFromFile(settings$epc[2],randVals[[1]])
+    partialResult <- matrix(ncol=length(randVals[[1]])+2*length(dataVar))
+    colN <- randVals[[1]]
+    colN[match(parameters[,2],randVals[[1]])] <- parameters[,1]
+    colnames(partialResult) <- c(colN,sprintf("%s_likelihood",names(dataVar)),
+                                      sprintf("%s_rmse",names(dataVar)))
+    numParameters <- length(colN)
+    partialResult[1:numParameters] <- origEpc
+    ## Prepare the preservedCalib matrix for the faster
+    ##  run.
+
+    pretag <- file.path(outLoc,preTag)
+
+     musoCodeToIndex  <- sapply(dataVar,function(musoCode){
+           settings$dailyOutputTable[settings$dailyOutputTable$code == musoCode,"index"]
+        })
+    resultRange <- (numParameters + 1):(ncol(partialResult))
+    ## Creating function for generating separate
+    ## csv files for each run
+
+    progBar <- txtProgressBar(1,iterations,style=3)
+    settings$iniInput[2] %>%
+        (function(x) paste0(dirname(x),"/",tools::file_path_sans_ext(basename(x)),"-tmp.",tools::file_ext(x))) %>%
+        unlink
+    randValues <- randVals[[2]]
+
+    settings$calibrationPar <- randVals[[1]]
+
+    if(!is.null(naVal)){
+        measuredData <- as.data.frame(measuredData)
+        measuredData[measuredData == naVal] <- NA
+    }
+
+    alignIndexes <- alignMuso(settings,measuredData)
+    if(!is.null(uncertainity)){
+        uncert <- measuredData[alignIndexes$meas,uncertainity]
+    } else {
+        uncert <- NULL
+    }
+    # browser()
+    # browser()
+    origModellOut <- calibMuso(settings=settings, silent=TRUE, skipSpinup = skipSpinup, postProcString=postProcString, modifyOriginal=modifyOriginal)
+    partialResult[,resultRange] <- calcLikelihoodsAndRMSE(dataVar=dataVar, 
+                                                          mod=origModellOut,
+                                                          mes=measuredData,
+                                                          likelihoods=likelihood,
+                                                           alignIndexes=alignIndexes,
+                                                           musoCodeToIndex = musoCodeToIndex,uncert=uncert)
+    write.csv(x=origModellOut, file=paste0(pretag, 1, ".csv"))
+    print("Running the model with the random epc values...", quote = FALSE)
+
+    # if(!is.null(postProcString)){
+    #     colNumb <- length(settings$dailyVarCodes) + 1
+    # }
+    
+    write.csv(x=partialResult, file="preservedCalib.csv",row.names=FALSE)
+    for(i in 2:(iterations+1)){
+        # browser()
+        tmp <- tryCatch(calibMuso(settings = settings,
+                                  parameters = randValues[(i-1),],
+                                  silent= TRUE,
+                                  skipSpinup = skipSpinup, modifyOriginal=modifyOriginal, postProcString = postProcString), error = function (e) NULL)
+        if(is.null(tmp)){
+           partialResult[,resultRange] <- NA
+        } else {
+            partialResult[,resultRange] <- calcLikelihoodsAndRMSE(dataVar=dataVar, 
+                                                          mod=tmp,
+                                                          mes=measuredData,
+                                                          likelihoods=likelihood,
+                                                           alignIndexes=alignIndexes,
+                                                           musoCodeToIndex = musoCodeToIndex, uncert = uncert)
+        }
+
+
+        partialResult[1:numParameters] <- randValues[(i-1),]
+        write.table(x=partialResult, file="preservedCalib.csv", append=TRUE, row.names=FALSE,
+                    sep=",", col.names=FALSE)
+        write.csv(x=tmp, file=paste0(pretag, (i+1),".csv"))
+        setTxtProgressBar(progBar,i)
+    }
+    
+    musoGlue("preservedCalib.csv",w=w, lg = lg)
+
+}
+
+
+
+
+alignMuso <- function (settings,measuredData) {
+        # Have to fix for other starting points also
+        modelDates <- seq(from= as.Date(sprintf("%s-01-01",settings$startYear)), 
+            by="days",
+            to=as.Date(sprintf("%s-12-31",settings$startYear+settings$numYears-1)))
+        modelDates <- grep("-02-29",modelDates,invert=TRUE, value=TRUE)
+
+        measuredDates <- apply(measuredData,1,function(xrow){
+                                   sprintf("%s-%s-%s",xrow[1],xrow[2],xrow[3])
+        })
+
+        modIndex <- match(as.Date(measuredDates), as.Date(modelDates))
+        measIndex <- which(!is.na(modIndex))
+        modIndex <- modIndex[!is.na(modIndex)]
+        cbind.data.frame(model=modIndex,meas=measIndex)
+} 
+
+# calcLikelihoodsAndRMSE <- function(dataVar, mod, mes, likelihoods, alignIndexes, musoCodeToIndex, uncert){
+#
+#     likelihoodRMSE <- sapply(names(dataVar),function(key){
+#                # browser()
+#                modelled <- mod[alignIndexes$mod,musoCodeToIndex[key]]
+#                measured <- mes[alignIndexes$meas,key]
+#                modelled <- modelled[!is.na(measured)] 
+#                # uncert   <-   uncert[!is.na(measured)]
+#                measured <- measured[!is.na(measured)] 
+#                res <- c(likelihoods[[key]](modelled, measured, uncert),
+#                         sqrt(mean((modelled-measured)^2))
+#                )
+#                res
+#         })
+#     names(likelihoodRMSE) <- c(sprintf("%s_likelihood",dataVar), sprintf("%s_rmse",dataVar))
+#
+#     return(c(likelihoodRMSE[1,],likelihoodRMSE[2,]))
+# }
+
+#' musoGlue
+#'
+#' This function calculates the -users specified- likelihood for random model input.
+#'
+#' @author Roland HOLLOS
+#' @param plotName u
+#' @export
+musoGlue <- function(presCalFile, w, delta = 0.17, settings=setupMuso(), parameters=read.csv("parameters.csv",
+                                                                        stringsAsFactors=FALSE), lg=FALSE){
+    if(is.data.frame(presCalFile)){
+        preservedCalib <- presCalFile
+    } else {
+        preservedCalib <- read.csv(presCalFile)
+    }
+    paramIndex <- parameters[(match(colnames(preservedCalib),parameters[,1])),2]
+    paramIndex <- paramIndex[!is.na(paramIndex)]
+    paramIndex <- c(paramIndex,
+                        as.numeric(gsub("X","",
+                                          grep("X[0-9]{1,}",
+                                               colnames(preservedCalib),value=TRUE))))
+    preservedCalib <- preservedCalib[-1,] #original
+
+    likeIndexes <- grep("likelihood",colnames(preservedCalib))
+    if(!is.null(w)){
+        forCombine<- sapply(names(w),function(n){
+                                grep(sprintf("%s_likelihood",n),colnames(preservedCalib))
+        })
+        preservedCalib[["combined"]] <- apply(as.data.frame(Map(function(x,y){
+                                                           toNormalize  <- preservedCalib[,y]
+                                                           toNormalize <- toNormalize / sqrt(sum(x^2))
+                                                           toNormalize * x
+
+                                            },w,forCombine)), 1, sum)
+    } else {
+        preservedCalib[["combined"]] <- preservedCalib[,grep("likelihood",colnames(preservedCalib),value=TRUE)]
+    }
+
+    parameterIndexes <- 1:(min(likeIndexes)-1)
+    preservedCalib <- preservedCalib[!is.na(preservedCalib$combined),]
+    unfilteredLikelihood <-  preservedCalib$combined
+    top5points <- preservedCalib$combined>quantile(preservedCalib$combined,0.95)
+    preservedCalibtop5 <- preservedCalib[,]
+    optRanges <-t(apply(preservedCalibtop5,2,function(x) quantile(x,c(0.05,0.5,0.95))))  
+    pdf("dotplot.pdf")
+    if(lg){
+        plot(Reduce(min, -(unfilteredLikelihood), accumulate=TRUE),type="l", ylab="-log(likelihood)",xlab="iterations")
+    } else {
+        plot(Reduce(min, -log(unfilteredLikelihood), accumulate=TRUE),type="l", ylab="-log(likelihood)",xlab="iterations")
+    }
+    pari <- par(mfrow=c(1,2)) 
+    for(i in seq_along(colnames(preservedCalib)[parameterIndexes])){
+        plot(preservedCalib[,i],preservedCalib[,"combined"],pch=19,cex=.1, ylab="likelihood",
+             main = colnames(preservedCalib)[i], xlab="")
+        plot(preservedCalibtop5[,i],preservedCalibtop5[,"combined"],pch=19,cex=.1, ylab="likelihood",
+             main = paste0(colnames(preservedCalibtop5)[i]," (behav.)"), xlab="")
+        abline(v=optRanges[i,1],col="blue")
+        abline(v=optRanges[i,2],col="green")
+        abline(v=optRanges[i,3],col="red")
+        
+    }
+
+    par(pari)
+    dev.off()
+    maxParValues <- preservedCalibtop5[which.max(preservedCalibtop5$combined),]
+    maxParIndexes <- paramIndex
+    write.csv(cbind.data.frame(calibrationPar=maxParValues,parameters=maxParIndexes),"maxLikelihood.csv")
+    write.csv(optRanges,"optRanges.csv")
+    # browser()
+    # There are some serious problems with this implementation. The uncertainity bouns are not for the parameters, but for the output values. The median is pointwise median for all simulation.
+    # And the 95 and 5 percentile also.
+    # dataVec <- preservedCalibtop5$combined
+    # closestToMedian <- function (dataVec) {
+    #     match(sort(dataVec)[min(which(sort(dataVec)>=median(dataVec)))], dataVec)
+    # }
+    #
+    # while(is.null(optimalEpc)){
+    #     match(quantile(preservedCalibtop5$combined,0.5), preservedCalibtop5$combined)
+    #     optInterval <-t(apply(preservedCalibtop5,2,function(x) quantile(x,c(0.5-delta,0.5+delta))))  
+    #     optParamRange <- cbind.data.frame(rownames(optInterval)[parameterIndexes],as.numeric(paramIndex),optInterval[parameterIndexes,])
+    #     optimalEpc <- tryCatch(musoRand(optParamRange,iterations = 2), error=function(e){NULL})
+    #     delta <- delta*1.05
+    #     if(delta > 0.5){
+    #         delta <- 0.5
+    #     }
+    #     if((delta == 0.5) && is.null(optimalEpc)){
+    #         stop("cannot find optimal value in the given range")
+    #     }
+    # }
+    # print("getOptim")
+    # optimalEpc[[2]] <- optimalEpc[[2]][1,]
+    # write.csv(as.data.frame(optimalEpc),"epcOptim.csv")
+    # print(head(optRanges,n=-2))
+    # calibMuso(calibrationPar=optimalEpc[[1]],parameters=optimalEpc[[2]])
+    # file.copy(settings$epcInput[2],"epcOptim.epc")
+}
+
+generateOptEpc <- function(optRanges,delta, maxLikelihood=FALSE){
+    if(missing(delta)){
+
+    }
+    
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/changeMuso.R

@@ -0,0 +1,33 @@
+#' changemulline 
+#'
+#' The function uses the previous changspecline function to operate.
+#' 
+#' @author Roland Hollos
+#' @export
+
+changemulline <- function(filePaths, calibrationPar, contents, src, outFiles=filePaths){
+    # browser()
+    if(is.null(src)){
+        src <- filePaths
+    }
+    
+    fileStringVector <- readLines(src)
+    Map(function(index, content){
+           fileStringVector <<- changeByIndex(index, content, fileStringVector)
+
+    }, calibrationPar, contents)
+    writeLines(fileStringVector, outFiles)
+    
+}
+
+changeNth <- function (string,place,replacement) {
+    trimws(gsub(sprintf("^((.*?\\s+){%s})(.*?\\s+)", place), sprintf("\\1%s ", replacement), paste0(string," "), perl=TRUE),
+           which="right")
+}
+
+changeByIndex <- function (rowIndex, parameter, fileStringVector){
+    h <- round((rowIndex*100) %% 10)
+    i <- as.integer(rowIndex)
+    fileStringVector[i] <- changeNth(fileStringVector[i], h, parameter)        
+    fileStringVector
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/checkMeteoBGC.R

@@ -0,0 +1,103 @@
+#' checkMeteoBGC
+#'
+#' This function calculates the daily and yearly statistics for a given meteorology file (mtc43).
+#'
+#' @author Erzsebet Kristof 
+#' @param settings The output of setupMuso
+#' @param metFileName The name of the meteorology file (mtc43).
+#' @param skip Number of header lines in meteorology file.
+#' @param numericReport If numericReport is set to FALSE, the function returns with a text report. If numericReport is set to TRUE, the function returns with a numeric report.
+#' @param type meteorology for spinup or normal run 
+#' @return It depends on the numericReport parameter. The function returns with a text report, or with a numeric report.
+#' @export 
+
+checkMeteoBGC <- function(settings=NULL, skip = 4, numericReport = FALSE,type="normal"){
+  
+  if(is.null(settings)){
+    settings <- setupMuso()
+  }
+
+  metFileName <- settings$metInput[type]
+
+  intMin <- function(x){
+    round(min(x,na.rm = TRUE), digits = 1)
+  }
+
+  intMax <- function(x){
+    round(max(x,na.rm = TRUE), digits = 1)
+  }
+
+  sradAvgShortestDay <- function(x,y){
+    round(mean(x[na.omit(y) == min(y, na.rm=TRUE)]), digits=1)
+    
+  }
+  sradAvgLongestDay <- function(x,y){
+    round(mean(x[na.omit(y) == max(y, na.rm=TRUE)]), digits=1)
+    
+  }
+  metTable <- tryCatch(read.table(metFileName, skip = skip), error = function(e){
+    stop(sprintf("Cannot read or find meteorology file: %s", metFileName))
+  })
+
+  yearlyPrcpSum <- tapply(metTable$V6,list(metTable$V1), sum)
+  yearlyTempAvg <- tapply(metTable$V5,list(metTable$V1), mean)
+  yearlyVpdAvg <- tapply(metTable$V7,list(metTable$V1), mean)
+
+
+  timeFrame <- range(metTable[,1])
+ if(!numericReport){
+   cat("Daily and yearly statistics of meteorological data for the time period of",
+      timeFrame[1], "-", timeFrame[2], ":\n
+      
+      Precipitation data:
+      Minimum and maximum of daily sums:",
+      intMin(metTable$V6), "cm and", intMax(metTable$V6), "cm.
+      Minimum and maximum of yearly sums:",
+      intMin(yearlyPrcpSum), "cm and", intMax(yearlyPrcpSum), "cm.\n
+       
+      Temperature data:
+      Lowest and highest daily temperatures (Tmin and Tmax):",
+      intMin(metTable$V4), "deg C and", intMax(metTable$V3), "deg C.
+      Minimum and maximum of yearly averages (based on Tday):",
+      intMin(yearlyTempAvg), "deg C and", intMax(yearlyTempAvg), "deg C.\n
+
+      Solar radiation data:
+      Minimum and maximum of daily values:",
+      intMin(metTable$V8), "W m-2 and", intMax(metTable$V8), "W m-2.     
+      Averages of the shortest and longest days:",
+      sradAvgShortestDay(metTable$V8, metTable$V9),"W m-2 and",
+      sradAvgLongestDay(metTable$V8, metTable$V9), "W m-2.\n
+       
+      Vapour pressure deficit data:
+      Minimum and maximum of daily values:",
+      intMin(metTable$V7), "Pa and", intMax(metTable$V7), "Pa.
+      Minimum and maximum of yearly averages:",
+      intMin(yearlyVpdAvg), "Pa and", intMax(yearlyVpdAvg), "Pa.\n")
+   
+ } else {
+   report <- list()
+   cat("Numeric report:\n")
+   report["Precipitation"] <- list(data.frame(minimum = c(daily = intMin(metTable$V6),
+                                                     yearly = intMin(yearlyPrcpSum)),
+                                         maximum = c(daily = intMax(metTable$V6),
+                                                     yearly = intMax(yearlyPrcpSum))))
+
+   report["Temperature"] <- list(data.frame(minimum = c(daily = intMin(metTable$V4),
+                                                     yearly = intMin(yearlyTempAvg)),
+                                         maximum = c(daily = intMax(metTable$V3),
+                                                     yearly = intMax(yearlyTempAvg))))
+   
+   report["Solar radiation"] <- list(data.frame(minimum = c(daily = intMin(metTable$V8),
+                                                     shortest_longest_day = sradAvgShortestDay(metTable$V8, metTable$V9)),
+                                         maximum = c(daily = intMax(metTable$V8),
+                                                     shortest_longest_day = sradAvgLongestDay(metTable$V8, metTable$V9))))
+
+   report["Vapour pressure deficit"] <- list(data.frame(minimum = c(daily = intMin(metTable$V7),
+                                                        yearly = intMin(yearlyVpdAvg)),
+                                            maximum = c(daily = intMax(metTable$V7),
+                                                        yearly = intMax(yearlyVpdAvg))))
+   
+   return(report)
+ }
+
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/cleanup.R

@@ -0,0 +1,55 @@
+#'cleanupMuso
+#'
+#' cleanupMuso can erase all of the unnecessary log and output files.
+#' 
+#' @author Roland HOLLOS
+#' @param location This is the place (directory) where your output files are located.
+#' @param simplicity TRUE or FALSE. If TRUE cleanupMuso will erase only the log files from the location
+#' @param deep If it is TRUE, it will delete every files from the subdirectories also
+#' @usage cleanupMuso(location=NULL, simplicity=TRUE,deep=FALSE)
+#' @export
+
+
+cleanupMuso <- function(location=NULL, simplicity=TRUE,deep=FALSE){
+    
+    if(is.null(location)){
+        location<-"./"
+    }
+
+    logDir<-file.path(location,"LOG")
+    errDir<-file.path(location,"ERROR")
+    epcDir<-file.path(location,"EPCS")
+    wroDir<-file.path(location,"WRONGEPC")
+
+    if(deep){
+
+        if(dir.exists(logDir)){
+            file.remove(
+                list.files(logDir,pattern="(out$)|(endpoint$)|(log$)", full.names=TRUE)
+         )
+        }
+        
+        if(dir.exists(errDir)){
+            file.remove(
+                list.files(errDir,pattern="(out$)|(endpoint$)|(log$)", full.names=TRUE))
+        }
+
+        if(dir.exists(epcDir)){
+            file.remove(
+                list.files(epcDir,pattern="(out$)|(endpoint$)|(log$)", full.names=TRUE))
+        }
+
+        if(dir.exists(wroDir)){
+            file.remove(
+                list.files(wroDir,pattern="(out$)|(endpoint$)|(log$)", full.names=TRUE))
+        }
+
+       file.remove(list.files(location, pattern="(out$)|(endpoint$)|(log$)",full.names=TRUE))}
+    
+    
+    if(!simplicity){    
+        file.remove(list.files(location, pattern="(out$)|(endpoint$)|(log$)",full.names=TRUE))
+    } else {
+             file.remove(list.files(location, pattern="log$",full.names=TRUE))}
+         
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/debugMuso.R

@@ -0,0 +1,68 @@
+#'rungetMuso
+#'
+#' This function runs the Biome-BGCMuSo model and reads its outputfile in a well structured way.
+#' 
+#' @author Roland Hollos
+#' @keywords internal
+#'
+## degubMuso <- function(inputloc,outputloc,debugging,errorsign,){
+
+    
+##     if((debugging=="stamplog")|(debugging==TRUE)){#If debugging option turned on
+##                                         ##If log or ERROR directory does not exists create it!
+##         dirName<-paste(inputloc,"LOG",sep="") 
+##         dirERROR<-paste(inputloc,"ERROR",sep="")
+        
+##         if(!dir.exists(dirName)){
+##             dir.create(dirName)
+##         }
+
+##         if(!dir.exists(dirERROR)){
+##             dir.create(dirERROR)
+##         }
+##     }
+
+##  if(debugging=="stamplog"){
+##         stampnum<-stamp(dirName)
+##         if(inputloc==outputloc){
+##             lapply( logfiles, function (x) file.rename(from=paste(outputloc,x, sep=""), to=paste(dirName, "/",(stampnum+1),"-",x,sep="")))
+            
+##         } else {
+##             lapply( logfiles, function (x) file.rename(from=paste(outputloc,x, sep="/"), to=paste(dirName, "/",(stampnum+1),"-",x,sep="")))
+##         }
+        
+##         if(errorsign==1){
+##             lapply( logfiles, function (x) file.copy(from=paste(dirName, "/",(stampnum+1),"-",x,sep=""), to=dirERROR  ))}
+
+##     } else { if(debugging){
+##                  if(is.null(logfilename)){
+
+##                      if(inputloc==outputloc){
+##                           lapply( logfiles, function (x) file.rename(from=paste(outputloc,x, sep=""), to=paste(dirName,"/", x, sep="")))
+##                      } else {
+##                          lapply( logfiles, function (x) file.rename(from=paste(outputloc,x, sep="/"), to=paste(dirName,"/", x, sep="")))     
+##                      }
+
+##                      if(errorsign==1){
+##                          lapply( logfiles, function (x) file.rename(from=paste(dirName,"/", x, sep=""), to=dirERROR))
+##                      }
+
+##                  } else {
+
+##                      if(inputloc==outputloc){#These are very ugly solutions for a string problem: inputloc: "./", if outputloc equalent of inputloc, it ends with "/", the string manipulation can not handle this. The better solution is easy, but I dont have enough time(Roland Hollo's) 
+##                          lapply( logfiles, function (x) file.rename(from=paste(outputloc,x, sep=""), to=paste(dirName, "/",logfilename,"-",x,sep="")))                        
+##                      } else {
+##                          lapply( logfiles, function (x) file.rename(from=paste(outputloc,x, sep="/"), to=paste(dirName, "/",logfilename,"-",x,sep="")))    
+##                      }
+                     
+##                      if(errorsign==1){
+##                          lapply( logfiles, function (x) file.rename(from=paste(dirName, "/",logfilename,"-",x,sep=""), to=dirERROR))
+##                      }
+##                  }    
+                 
+##              }}
+    
+
+## return(errorsign)
+
+## }

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/flat.R

@@ -0,0 +1,267 @@
+getQueue <- function(depTree=options("RMuso_depTree")[[1]], startPoint){
+    
+    if(length(startPoint) == 0){
+        return(c())
+    }
+    parent <- depTree[depTree[,"name"] == startPoint,"parent"]
+    c(getQueue(depTree, depTree[depTree[,"child"] == depTree[depTree[,"name"] == startPoint,"parent"],"name"]),parent)
+}
+
+isRelative <- function(path){
+   substr(path,1,1) != '/'
+}
+
+#' getFilePath
+#'
+#' This function reads the ini file and for a chosen fileType it gives you the filePath
+#' @param iniName The name of the ini file
+#' @param filetype The type of the choosen file. For options see options("RMuso_depTree")[[1]]$name
+#' @param depTree The file dependency defining dataframe. At default it is:  options("RMuso_depTree")[[1]]
+#' @export
+
+getFilePath <- function(iniName, fileType, execPath = "./", depTree=options("RMuso_depTree")[[1]]){
+    if(!file.exists(iniName) || dir.exists(iniName)){
+        stop(sprintf("Cannot find iniFile: %s", iniName))
+    }
+
+    startPoint <- fileType
+    startRow <- depTree[depTree[,"name"] == startPoint,]
+    startExt <- startRow$child
+
+    parentFile <- Reduce(function(x,y){
+                             tryCatch(file.path(execPath,gsub(sprintf("\\.%s.*",y),
+                                            sprintf("\\.%s",y),
+                                            grep(sprintf("\\.%s",y),readLines(x),value=TRUE,perl=TRUE))), error = function(e){
+                                        stop(sprintf("Cannot find %s",x))
+                             })
+                        },
+                        getQueue(depTree,startPoint)[-1],
+                        init=iniName)
+    if(startRow$mod > 0){
+        tryCatch(
+         gsub(sprintf("\\.%s.*", startExt),
+              sprintf("\\.%s", startExt),
+              grep(sprintf("\\.%s",startExt),readLines(parentFile),value=TRUE,perl=TRUE))[startRow$mod]
+        ,error = function(e){stop(sprintf("Cannot read %s",parentFile))})
+    } else {
+        res <- tryCatch(
+         gsub(sprintf("\\.%s.*", startExt),
+                     sprintf("\\.%s",startExt),
+                     grep(sprintf("\\.%s",startExt),readLines(parentFile),value=TRUE, perl=TRUE))
+        ,error = function(e){stop(sprintf("Cannot read %s", parentFile))})
+        unique(gsub(".*\\t","",res))
+    }
+}
+
+
+
+#' getFilesFromIni
+#'
+#' This function reads the ini file and gives yout back the path of all file involved in model run
+#' @param iniName The name of the ini file
+#' @param depTree The file dependency defining dataframe. At default it is:  options("RMuso_depTree")[[1]]
+#' @export
+
+getFilesFromIni <- function(iniName, execPath = "./", depTree=options("RMuso_depTree")[[1]]){
+    res <- lapply(depTree$name,function(x){
+                      tryCatch(getFilePath(iniName,x,execPath,depTree), error = function(e){
+                            return(NA);
+                     })
+        })
+    names(res) <- depTree$name
+    res
+}
+
+#' flatMuso
+#'
+#' This function reads the ini file and creates a directory (named after the directory argument) with all the files the modell uses with this file. the directory will be flat.
+#' @param iniName The name of the ini file
+#' @param depTree The file dependency defining dataframe. At default it is:  options("RMuso_depTree")[[1]]
+#' @param directory The destination directory for flattening. At default it will be flatdir 
+#' @export
+
+flatMuso <- function(iniName, execPath="./", depTree=options("RMuso_depTree")[[1]], directory="flatdir", d=TRUE,outE=TRUE){
+    dir.create(directory, showWarnings=FALSE, recursive = TRUE)
+    files <- getFilesFromIni(iniName,execPath,depTree)
+    files <- sapply(unlist(files)[!is.na(files)], function(x){ifelse(isRelative(x),file.path(execPath,x),x)})
+    file.copy(unlist(files), directory, overwrite=TRUE)
+    file.copy(iniName, directory, overwrite=TRUE)
+
+    filesByName <- getFilesFromIni(iniName, execPath, depTree)
+    for(i in seq_along(filesByName)){
+        fileLines <- readLines(file.path(directory,list.files(directory, pattern = sprintf("*\\.%s", depTree$parent[i])))[1])
+
+        sapply(filesByName[[i]],function(origname){
+            if(!is.na(origname)){
+                fileLines <<- gsub(origname, basename(origname), fileLines, fixed=TRUE)
+            }
+        })
+
+        if(!is.na(filesByName[[i]][1])){
+            writeLines(fileLines, file.path(directory,list.files(directory, pattern = sprintf("*\\.%s", depTree$parent[i])))[1])
+        }
+
+    }
+
+    iniLines <- readLines(file.path(directory, basename(iniName)))
+    outPlace <- grep("OUTPUT_CONTROL", iniLines, perl=TRUE)+1
+    if(outE){
+        iniLines[outPlace] <- tools::file_path_sans_ext(basename(iniName))
+    } else {
+        iniLines[outPlace] <-  basename(strsplit(iniLines[outPlace], split = "\\s+")[[1]][1])
+    }
+    if(d){
+        iniLines[outPlace + 1] <- 1
+    }
+    writeLines(iniLines, file.path(directory, basename(iniName)))    
+}
+
+#' checkFileSystem
+#'
+#' This function checks the MuSo file system, if it is correct
+#' @param iniName The name of the ini file
+#' @param depTree The file dependency defining dataframe. At default it is:  options("RMuso_depTree")[[1]]
+#' @export
+
+checkFileSystem <- function(iniName,root = ".", depTree = options("RMuso_depTree")[[1]]){
+    recoverAfterEval({
+        setwd(root)
+        fileNames <- getFilesFromIni(iniName, depTree)
+        if(is.na(fileNames$management)){
+            fileNames[getLeafs("management")] <- NA
+        }
+        fileNames <- fileNames[!is.na(fileNames)]
+        errorFiles <- fileNames[!file.exists(unlist(fileNames))]
+    })
+    return(errorFiles)
+}
+
+recoverAfterEval <- function(expr){
+    wd <- getwd()
+    tryCatch({
+        eval(expr)
+        setwd(wd) 
+    }, error=function(e){
+            setwd(wd)
+            stop(e)
+    })
+}
+
+getLeafs <- function(name, depTree=options("RMuso_depTree")[[1]]){
+
+    if(length(name) == 0){
+        return(NULL)
+    }
+
+    if(name[1] == "ini"){
+        return(getLeafs(depTree$name))
+    }
+
+    pname <- depTree[ depTree[,"name"] == name[1] , "child"]
+    children <- depTree[depTree[,"parent"] == pname,"child"]  
+
+    if(length(children)==0){
+        if(length(name) == 1){
+            return(NULL)
+        } else{
+            apname <- depTree[ depTree[,"name"] == name[2] , "child"]
+            achildren <- depTree[depTree[,"parent"] == apname,"child"]  
+            if(length(achildren)!=0){
+                return(c(name[1],name[2],getLeafs(name[-1])))
+            } else{
+                return(c(name[1], getLeafs(name[-1])))
+            }
+
+        }
+    }
+    
+    childrenLogic <-depTree[,"child"] %in% children 
+    parentLogic <- depTree[,"parent"] ==pname
+    res <- depTree[childrenLogic & parentLogic, "name"]
+    getChildelem <- depTree[depTree[,"child"] == intersect(depTree[,"parent"], children), "name"]
+    unique(c(res,getLeafs(getChildelem)))
+}
+
+getParent <- function (name, depTree=options("RMuso_depTree")[[1]]) {
+    parentExt <- depTree[depTree$name == name,"parent"]
+    # if(length(parentExt) == 0){
+    #     browser()
+    # }
+    if(parentExt == "ini"){
+        return("iniFile")
+    }
+
+    depTree[depTree[,"child"] == parentExt,"name"]
+}
+
+
+
+getFilePath2 <- function(iniName, fileType, depTree=options("RMuso_depTree")[[1]]){
+    if(!file.exists(iniName) || dir.exists(iniName)){
+        stop(sprintf("Cannot find iniFile: %s", iniName))
+    }
+
+    startPoint <- fileType
+    startRow <- depTree[depTree[,"name"] == startPoint,]
+    startExt <- startRow$child
+
+    parentFile <- Reduce(function(x,y){
+                             tryCatch(gsub(sprintf("\\.%s.*",y),
+                                   sprintf("\\.%s",y),
+                                   grep(sprintf("\\.%s",y),readLines(x),value=TRUE,perl=TRUE)), error = function(e){
+                                        stop(sprintf("Cannot find %s",x))
+                             })
+                        },
+                        getQueue(depTree,startPoint)[-1],
+                        init=iniName)
+    res <- list()
+    res["parent"] <- parentFile
+    if(startRow$mod > 0){
+    res["children"] <-    tryCatch(
+         gsub(sprintf("\\.%s.*", startExt),
+              sprintf("\\.%s", startExt),
+              grep(sprintf("\\.%s",startExt),readLines(parentFile),value=TRUE,perl=TRUE))[startRow$mod]
+        ,error = function(e){stop(sprintf("Cannot read %s",parentFile))})
+
+    } else {
+         rows <- tryCatch(
+        gsub(sprintf("\\.%s.*", startExt),
+                     sprintf("\\.%s",startExt),
+                     grep(sprintf("\\.%s",startExt),readLines(parentFile),value=TRUE, perl=TRUE))
+         
+        ,error = function(e){stop(sprintf("Cannot read %s", parentFile))})
+        unique(gsub(".*\\t","",res))
+        res["children"] <- unique(gsub(".*\\s+(.*\\.epc)","\\1",rows))
+    }
+    res
+}
+
+getFilesFromIni2 <- function(iniName, depTree=options("RMuso_depTree")[[1]]){
+    res <- lapply(depTree$name,function(x){
+                      tryCatch(getFilePath2(iniName,x,depTree), error = function(e){
+                            return(NA);
+                     })
+        })
+    names(res) <- depTree$name
+    res
+}
+
+checkFileSystemForNotif <- function(iniName,root = ".", depTree = options("RMuso_depTree")[[1]]){
+    recoverAfterEval({
+        setwd(root)
+        fileNames <- suppressWarnings(getFilesFromIni2(iniName, depTree))
+        if(is.atomic(fileNames$management)){
+            fileNames[getLeafs("management")] <- NA
+        }
+
+        hasparent   <- sapply(fileNames, function(x){
+                                  !is.atomic(x)
+                     })
+        notNA <- ! sapply(fileNames[hasparent], function(x) {is.na(x$children)})
+        errorIndex <- ! sapply(fileNames[hasparent & notNA], function(x) file.exists(x$children))
+
+    })
+    return(fileNames[hasparent & notNA][errorIndex])
+}
+
+

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/genEpc.R

@@ -0,0 +1,35 @@
+#' randEpc
+#'
+#' randEpc is a random epc creator based on musoMonte
+#' @author Roland HOLLOS
+#' @param parameterFile parameters.csv file location
+#' @param location output location directory
+#' @param sourceEpc the original epc file-the template
+#' @param iteration the number of iterations
+#' @export
+
+randEpc <- function(parameterFile = "parameters.csv", location = "./epcDir",
+                    sourceEpc = "maize.epc", iterations = 1000, constrains = NULL){
+    
+    if(!dir.exists(location)){
+        dir.create(location)
+    }
+    sourceEpc <- normalizePath(sourceEpc)
+    currDir <- getwd()
+    parameters <- read.csv(parameterFile)
+
+    if(iterations < 3000){
+        randVals <- musoRand(parameters = parameters,constrains = constrains, iterations = 3000)
+        randVals[[2]]<- randVals[[2]][sample(1:3000,iterations),]
+    } else {
+        randVals <- musoRand(parameters = parameters,constrains = constrains, iterations = iterations)
+    }
+    file.copy(sourceEpc,location,overwrite = TRUE)
+    setwd(location)
+    for(i in seq(iterations)){
+        epcOut <- gsub("\\.",paste0("-",i,"."),basename(sourceEpc))
+        changemulline(filePaths = basename(sourceEpc), calibrationPar = randVals[[1]],
+                      contents = randVals[[2]][i,],fileOut = epcOut, fileToChange = "epc")        
+    }
+   setwd(currDir)
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/getOutPutList.R

@@ -0,0 +1,33 @@
+#' getDailyOutputList
+#'
+#' bla bla
+#' @param settings bla
+#' @export
+
+
+getDailyOutputList <- function(settings=NULL){
+    if(is.null(settings)){
+        settings <- setupMuso()
+    }
+    varTable <- getOption("RMuso_varTable")$'6'
+    toPrint <- varTable[match(as.numeric(settings$dailyVarCodes),varTable[,1]),]
+    toPrint <- cbind.data.frame(index=1:nrow(toPrint),toPrint)
+    print(toPrint, row.names=FALSE)
+}
+
+#' getAnnualOutputList
+#'
+#' bla bla
+#' @param settings bla
+#' @export
+
+
+getAnnualOutputList <- function(settings=NULL){
+    if(is.null(settings)){
+        settings<- setupMuso()
+    }
+    varTable <- getOption("RMuso_varTable")$'6'
+    toPrint <- varTable[which(varTable$codes %in% as.numeric(settings$annualVarCodes)),]
+    toPrint <- cbind.data.frame(index=1:nrow(toPrint),toPrint)
+    print(toPrint, row.names=FALSE)
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/getOutput.R

@@ -0,0 +1,44 @@
+getthewholedata<-function(settings){
+  f1<-settings$ininput[2]
+  filename = paste(settings$inputloc,settings$outputname,"_ann.txt",sep="")
+  alloutput<-read.table(filename,skip=22, header = FALSE)
+  return(alloutput)
+}
+
+getthespecdata<-function(settings,colnumbers){
+  filename<-paste(settings$inputloc,settings$outputname,"_ann.txt",sep="")
+  specoutput<-read.table(filename,skip=22, header = FALSE)[,colnumbers]
+  return(specoutput)
+}
+
+getdailyout<-function(settings){
+  binaryname<-paste0(settings$outputLoc,"/",settings$outputNames[2],".dayout")
+  d<-file(binaryname,"rb")
+  ##leapyear is not implemented yet in this function
+  dayoutput<-matrix(readBin(d,"double",size=8,n=(settings$numData[1])),(settings$numYears*365),byrow=TRUE)
+  close(d) 
+  return(dayoutput)
+}
+
+getmonthlyout<-function(settings){
+  binaryname<-paste(settings$inputloc,settings$outputname,".monavgout",sep="")
+  d<-file(binaryname,"rb")
+  monoutput<-matrix(readBin(d,"double",size=4,n=(settings$numdata[2])),(settings$numyears*12),byrow=TRUE)
+  close(d)
+  return(monoutput)
+}
+
+getyearlyout<-function(settings){
+  binaryname<-paste0(settings$inputLoc,"/",settings$outputName[2],".annout")
+  ## d<-file(binaryname,"rb")
+  ## yearoutput<-matrix(readBin(d,"double",size=4,n=(settings$numData[3])),(settings$numYears),byrow=TRUE)
+  ## close(d)
+  ## return(yearoutput)
+  outPut <- read.table(binaryname,skip = 1)
+  colnames(outPut) <- c("year", paste0("var_",settings$annualVarCodes))
+  outPut
+}
+
+
+
+

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/multiSite.R

@@ -0,0 +1,640 @@
+`%between%` <- function(x, y){
+    (x <= y[2]) & (x >= y[1])
+}
+
+annualAggregate <- function(x, aggFun){
+    tapply(x, rep(1:(length(x)/365), each=365), aggFun)
+}
+
+SELECT <- function(x, selectPart){
+    if(!is.function(selectPart)){
+        index <- as.numeric(selectPart)
+        tapply(x,rep(1:(length(x)/365),each=365), function(y){
+            y[index]
+        })
+    } else {
+        tapply(x,rep(1:(length(x)/365),each=365), selectPart)
+    }
+}
+    
+bVectToInt<- function(bin_vector){
+    bin_vector <- rev(as.integer(bin_vector))
+    packBits(as.raw(c(bin_vector,numeric(32-length(bin_vector)))),"integer")
+}
+
+constMatToDec <- function(constRes){
+    tab <- table(apply(constRes,2,function(x){paste(x,collapse=" ")}))
+    bitvect <- strsplit(names(tab[which.max(tab)]),split=" ")[[1]]
+    bVectToInt(bitvect)
+}
+
+compose <- function(expr){
+   splt <- strsplit(expr,split="\\|")[[1]]
+   lhs <- splt[1]
+   rhs <- splt[2]
+   penv <- parent.frame()
+   lhsv <- eval(parse(text=lhs),envir=penv)
+   penv[["lhsv"]] <- lhsv
+   place <- regexpr("\\.[^0-9a-zA-Z]",rhs)
+
+   if(place != -1){
+       finalExpression <- paste0(substr(rhs, 1, place -1),"lhsv",
+                                 substr(rhs, place + 1, nchar(rhs)))
+   } else {
+        finalExpression <- paste0(rhs,"(lhsv)")
+   }
+   eval(parse(text=finalExpression),envir=penv)
+}
+
+compoVect <- function(mod, constrTable, fileToWrite = "const_results.data"){
+    with(as.data.frame(mod), {
+             nexpr  <- nrow(constrTable)
+             filtered  <- numeric(nexpr)
+             vali <- numeric(nexpr) 
+             for(i in 1:nexpr){
+                 val <- compose(constrTable[i,1])
+                 filtered[i] <- (val <= constrTable[i,3]) &&
+                             (val >= constrTable[i,2])
+                 vali[i] <- val
+             }
+
+             write(paste(vali,collapse=","), fileToWrite, append=TRUE)
+             filtered
+    })
+}
+
+modCont <- function(expr, datf, interval, dumping_factor){
+    tryCatch({
+        if((with(datf,eval(parse(text=expr))) %between% interval)){
+            return(NA)
+        } else{
+            return(dumping_factor)
+        }
+    },
+        error = function(e){
+            stop(sprintf("Cannot find the variable names in the dataframe, detail:\n%s",
+                         e))
+        })
+}
+
+copyToThreadDirs2 <- function(iniSource, thread_prefix = "thread", numCores, execPath="./",
+
+                              executable = ifelse(Sys.info()[1]=="Linux", file.path(execPath, "muso"),
+                                                                            file.path(execPath,"muso.exe"))){
+    sapply(iniSource, function(x){
+        flatMuso(x, execPath,
+                 directory=file.path("tmp", paste0(thread_prefix,"_1"),tools::file_path_sans_ext(basename(x)),""), d =TRUE)
+        file.copy(executable,
+                  file.path("tmp", paste0(thread_prefix,"_1"),tools::file_path_sans_ext(basename(x))))
+        tryCatch(file.copy(file.path(execPath,"cygwin1.dll"),
+                   file.path("tmp", paste0(thread_prefix,"_1"),tools::file_path_sans_ext(basename(x)))),
+                 error = function(e){"If you are in Windows..."})
+    })
+    sapply(2:numCores,function(thread){
+               dir.create(sprintf("tmp/%s_%s",thread_prefix,thread), showWarnings=FALSE)
+               file.copy(list.files(sprintf("tmp/%s_1",thread_prefix),full.names = TRUE),sprintf("tmp/%s_%s/",thread_prefix,thread),
+                         recursive=TRUE, overwrite = TRUE)
+    })
+
+}
+
+
+#' multiSiteCalib
+#'
+#' This funtion uses the Monte Carlo technique to uniformly sample the parameter space from user defined parameters of the Biome-BGCMuSo model. The sampling algorithm ensures that the parameters are constrained by the model logic which means that parameter dependencies are fully taken into account (parameter dependency means that e.g leaf C:N ratio must be smaller than C:N ratio of litter; more complicated rules apply to the allocation parameters where the allocation fractions to different plant compartments must sum up 1). This function implements a mathematically correct solution to provide uniform distriution of the random parameters on convex polytopes. 
+#' @author Roland HOLLOS
+#' @importFrom future future
+#' @importFrom rpart rpart rpart.control
+#' @importFrom rpart.plot rpart.plot
+#' @param measuremets The table which contains the measurements
+#' @param calTable A dataframe which contantains the ini file locations and the domains they belongs to
+#' @param parameters A dataframe with the name, the minimum, and the maximum value for the parameters used in MonteCarlo experiment 
+#' @param dataVar A named vector where the elements are the MuSo variable codes and the names are the same as provided in measurements and likelihood
+#' @param iterations The number of MonteCarlo experiments to be executed
+#' @param burnin Currently not used, altought it is the length of burnin period of the MCMC sampling used to generate random parameters
+#' @param likelihood A list of likelihood functions which names are linked to dataVar
+#' @param execPath If you are running the calibration from different location than the MuSo executable, you have to provide the path
+#' @param thread_prefix The prefix of thread directory names in the tmp directory created during the calibrational process
+#' @param numCores The number of processes used during the calibration. At default it uses one less than the number of threads available
+#' @param pb The progress bar function. If you use (web-)GUI you can provide a different function
+#' @param pbUpdate The update function for pb (progress bar)
+#' @param copyThread A boolean, recreate tmp directory for calibration or not (case of repeating the calibration)
+#' @param contsraints A dataframe containing the constraints logic the minimum and a maximum value for the calibration.
+#' @param th A trashold value for multisite calibration. What percentage of the site should satisfy the constraints. 
+#' @param treeControl A list which controls (maximal complexity, maximal depth) the details of the decession tree making.
+#' @export
+multiSiteCalib <- function(measurements,
+                           calTable,
+                           parameters,
+                           dataVar, 
+                           iterations = 100,
+                           burnin =ifelse(iterations < 3000, 3000, NULL),
+                           likelihood,
+                           execPath,
+                           thread_prefix="thread",
+                           numCores = (parallel::detectCores()-1),
+                           pb = txtProgressBar(min=0, max=iterations, style=3),
+                           pbUpdate = setTxtProgressBar,
+                           copyThread = TRUE,
+                           constraints=NULL, th = 10, treeControl=rpart.control()
+                           ){
+    future::plan(future::multisession)
+    # file.remove(list.files(path = "tmp", pattern="progress.txt", recursive = TRUE, full.names=TRUE))
+    # file.remove(list.files(path = "tmp", pattern="preservedCalib.csv", recursive = TRUE, full.names=TRUE))
+
+    #   ____                _         _   _                        _     
+    #  / ___|_ __ ___  __ _| |_ ___  | |_| |__  _ __ ___  __ _  __| |___ 
+    # | |   | '__/ _ \/ _` | __/ _ \ | __| '_ \| '__/ _ \/ _` |/ _` / __|
+    # | |___| | |  __/ (_| | ||  __/ | |_| | | | | |  __/ (_| | (_| \__ \
+    #  \____|_|  \___|\__,_|\__\___|  \__|_| |_|_|  \___|\__,_|\__,_|___/
+    if(copyThread){
+        unlink("tmp",recursive=TRUE)
+        copyToThreadDirs2(iniSource=calTable$site_id, numCores=numCores, execPath=execPath)
+    } else {
+        print("copy skipped")
+        file.remove(file.path(list.dirs("tmp",recursive=FALSE),"progress.txt"))
+        file.remove(file.path(list.dirs("tmp", recursive=FALSE), "const_results.data"))
+    }
+
+    #  ____                _   _                        _     
+    # |  _ \ _   _ _ __   | |_| |__  _ __ ___  __ _  __| |___ 
+    # | |_) | | | | '_ \  | __| '_ \| '__/ _ \/ _` |/ _` / __|
+    # |  _ <| |_| | | | | | |_| | | | | |  __/ (_| | (_| \__ \
+    # |_| \_\\__,_|_| |_|  \__|_| |_|_|  \___|\__,_|\__,_|___/
+                                                            
+    threadCount <- distributeCores(iterations, numCores) 
+    fut <- lapply(1:numCores, function(i) {
+         future({
+                      tryCatch(
+
+                               {
+                                  result <- multiSiteThread(measuredData = measurements, parameters = parameters, calTable=calTable, 
+                                                   dataVar = dataVar, iterations = threadCount[i],
+                                                   likelihood = likelihood, threadNumber= i, constraints=constraints, th=th)
+                                   # setwd("../../")
+                                   # return(result)
+                               }
+
+                      , error = function(e){
+                          # browser()
+                                            sink("error.txt")
+                                            print(e)
+                                            sink()
+                                            saveRDS(e,"error.RDS")
+                                            writeLines(as.character(iterations),"progress.txt")
+                                        })
+        })
+    })
+
+    #                _       _                                               
+    # __      ____ _| |_ ___| |__    _ __  _ __ ___   __ _ _ __ ___  ___ ___ 
+    # \ \ /\ / / _` | __/ __| '_ \  | '_ \| '__/ _ \ / _` | '__/ _ \/ __/ __|
+    #  \ V  V / (_| | || (__| | | | | |_) | | | (_) | (_| | | |  __/\__ \__ \
+    #   \_/\_/ \__,_|\__\___|_| |_| | .__/|_|  \___/ \__, |_|  \___||___/___/
+    #                               |_|              |___/                   
+
+    getProgress <- function(){
+        # threadfiles <- list.files(settings$inputLoc, pattern="progress.txt", recursive = TRUE)
+        threadfiles <- list.files(pattern="progress.txt", recursive = TRUE)
+        if(length(threadfiles)==0){
+            return(0)
+        } else {
+            sum(sapply(threadfiles, function(x){
+                           partRes <- readLines(x)
+                           if(length(partRes)==0){
+                               return(0)
+                           } else {
+                               return(as.numeric(partRes))
+                           }
+
+         }))
+
+        }
+    }
+
+    progress <- 0
+    while(progress < iterations){
+        Sys.sleep(1)
+        progress <- tryCatch(getProgress(), error=function(e){progress})
+        if(is.null(pb)){
+            pbUpdate(as.numeric(progress))
+        } else {
+            pbUpdate(pb,as.numeric(progress))
+        }
+    }
+    if(!is.null(pb)){
+        close(pb)
+    }
+
+    #   ____                _     _            
+    #  / ___|___  _ __ ___ | |__ (_)_ __   ___ 
+    # | |   / _ \| '_ ` _ \| '_ \| | '_ \ / _ \
+    # | |__| (_) | | | | | | |_) | | | | |  __/
+    #  \____\___/|_| |_| |_|_.__/|_|_| |_|\___|
+    
+    if(!is.null(constraints)){
+        constRes <- file.path(list.dirs("tmp", recursive=FALSE), "const_results.data")
+        constRes <- lapply(constRes, function(f){read.csv(f, stringsAsFactors=FALSE, header=FALSE)})
+        constRes <- do.call(rbind,constRes)
+        write.csv(constRes, "constRes.csv")
+    }
+    resultFiles <- list.files(pattern="preservedCalib.*csv$",recursive=TRUE)
+    res0 <- read.csv(grep("thread_1/",resultFiles, value=TRUE),stringsAsFactors=FALSE)
+    resultFilesSans0 <- grep("thread_1/", resultFiles, value=TRUE, invert=TRUE)
+    # results <- do.call(rbind,lapply(resultFilesSans0, function(f){read.csv(f, stringsAsFactors=FALSE)}))
+    resultsSans0 <- lapply(resultFilesSans0, function(f){read.csv(f, stringsAsFactors=FALSE, header=FALSE)})
+    resultsSans0 <- do.call(rbind,resultsSans0)
+    colnames(resultsSans0) <- colnames(res0)
+    results <- (rbind(res0,resultsSans0))
+    write.csv(results,"result.csv")
+    calibrationPar <- future::value(fut[[1]], stdout = FALSE, signal=FALSE)[["calibrationPar"]]
+    if(!is.null(constraints)){
+        tryCatch({
+            notForTree <- c(seq(from = (length(calibrationPar)+1), length.out=3))
+            notForTree <- c(notForTree,which(sapply(seq_along(calibrationPar),function(i){sd(results[,i])==0})))
+            treeData <- results[,-notForTree]
+            treeData["failType"] <- as.factor(results$failType)
+            if(ncol(treeData) > 4){
+                rp <- rpart(failType ~ .,data=treeData,control=treeControl)
+                svg("treeplot.svg")
+                rpart.plot(rp)
+                dev.off()
+            }
+        }, error = function(e){
+            print(e)
+        })
+    }
+   origModOut <- future::value(fut[[1]], stdout = FALSE, signal=FALSE)[["origModOut"]]
+    # Just single objective version TODO:Multiobjective
+    results <- results[results[,"Const"] == 1,]
+    if(nrow(results)==0){
+        stop("No simulation suitable for constraints\n Please see treeplot.png for explanation, if you have more than four parameters.")
+    }
+    bestCase <- which.max(results[,length(calibrationPar) + 1])
+    parameters <- results[bestCase,1:length(calibrationPar)] # the last two column is the (log) likelihood and the rmse
+    #TODO: Have to put that before multiSiteThread, we should not have to calculate it at every iterations 
+
+    firstDir <- list.dirs("tmp/thread_1",full.names=TRUE,recursive =FALSE)[1]
+    epcFile <- list.files(firstDir, pattern = "\\.epc",full.names=TRUE)
+    settingsProto <- setupMuso(inputLoc = firstDir,
+                               iniInput =rep(list.files(firstDir, pattern = "\\.ini",full.names=TRUE),2))
+    alignIndexes <- commonIndexes(settingsProto, measurements)
+    musoCodeToIndex  <- sapply(dataVar,function(musoCode){
+      settingsProto$dailyOutputTable[settingsProto$dailyOutputTable$code == musoCode,"index"]
+    })
+
+
+    setwd("tmp/thread_1")
+    aposteriori<- spatialRun(settingsProto, calibrationPar, parameters, calTable)
+    file.copy(list.files(list.dirs(full.names=TRUE, recursive=FALSE)[1], pattern=".*\\.epc", full.names=TRUE),
+              "../../multiSiteOptim.epc", overwrite=TRUE)
+    setwd("../../")
+    #TODO: Have to put that before multiSiteThread, we should not have to calculate it at every iterations 
+    nameGroupTable <- calTable 
+    nameGroupTable[,1] <- tools::file_path_sans_ext(basename(nameGroupTable[,1]))
+    res <- list()
+    
+    res[["calibrationPar"]] <- calibrationPar
+    res[["parameters"]] <- parameters
+    # browser()
+    res[["comparison"]] <- compareCalibratedWithOriginal(key = names(dataVar)[1], modOld=origModOut, modNew=aposteriori, mes=measurements,
+
+                                                                 likelihoods = likelihood,
+                                                                 alignIndexes = alignIndexes,
+                                                                 musoCodeToIndex = musoCodeToIndex,
+                                                                 nameGroupTable = nameGroupTable, mean)
+    res[["likelihood"]] <- results[bestCase,ncol(results)-2]
+    comp <- res$comparison
+    res[["originalMAE"]] <- mean(abs((comp[,1]-comp[,3])))
+    res[["MAE"]] <- mean(abs((comp[,2]-comp[,3])))
+    res[["RMSE"]] <- results[bestCase,ncol(results)-2]
+    res[["originalRMSE"]] <- sqrt(mean((comp[,1]-comp[,3])^2))
+    res[["originalR2"]] <- summary(lm(measured ~ original,data=res$comparison))$r.squared
+    res[["R2"]] <- summary(lm(measured ~ calibrated, data=res$comparison))$r.squared
+    saveRDS(res,"results.RDS")
+    png("calibRes.png")
+    opar <- par(mar=c(5,5,4,2)+0.1, xpd=FALSE)
+        with(data=res$comparison, {
+             plot(measured,original,
+                  ylim=c(min(c(measured,original,calibrated)),
+                         max(c(measured,original,calibrated))),
+                  xlim=c(min(c(measured,original,calibrated)),
+                         max(c(measured,original,calibrated))),
+                  xlab=expression("measured "~(kg[DM]~m^-2)),
+                  ylab=expression("simulated "~(kg[DM]~m^-2)),
+                  cex.lab=1.3,
+                  col="red",
+                  pch=19,
+                  pty="s"
+             )
+             points(measured,calibrated, pch=19, col="blue")
+             abline(0,1)
+             legend(x="top",
+                    pch=c(19,19),
+                    col=c("red","blue"),
+                    inset=c(0,-0.1),
+                    legend=c("original","calibrated"),
+                    ncol=2,
+                    box.lty=0,
+                    xpd=TRUE
+             )
+        })
+    dev.off()
+    return(res)
+}
+
+#' multiSiteThread
+#'
+#' This is an 
+#' @author Roland HOLLOS
+
+
+multiSiteThread <- function(measuredData, parameters = NULL, startDate = NULL,
+                     endDate = NULL, formatString = "%Y-%m-%d", calTable,
+                     dataVar, outLoc = "./calib",
+                     outVars = NULL, iterations = 300,
+                     skipSpinup = TRUE, plotName = "calib.jpg",
+                     modifyOriginal=TRUE, likelihood, uncertainity = NULL, burnin=NULL,
+                     naVal = NULL, postProcString = NULL, threadNumber, constraints=NULL,th=10) {
+
+    originalRun <- list()
+    nameGroupTable <- calTable 
+    nameGroupTable[,1] <- tools::file_path_sans_ext(basename(nameGroupTable[,1]))
+    setwd(paste0("tmp/thread_",threadNumber))
+    firstDir <- list.dirs(full.names=FALSE,recursive =FALSE)[1]
+    epcFile <- list.files(firstDir, pattern = "\\.epc",full.names=TRUE)
+    settingsProto <- setupMuso(inputLoc = firstDir,
+                               iniInput =rep(list.files(firstDir, pattern = "\\.ini",full.names=TRUE),2))
+
+    # Exanding likelihood
+    likelihoodFull <- as.list(rep(NA,length(dataVar)))
+    names(likelihoodFull) <- names(dataVar)
+    if(!missing(likelihood)) {
+        lapply(names(likelihood),function(x){
+                   likelihoodFull[[x]] <<- likelihood[[x]]
+                     })
+    }
+
+   defaultLikelihood <- which(is.na(likelihood))
+   if(length(defaultLikelihood)>0){
+        likelihoodFull[[defaultLikelihood]] <- (function(x, y){
+                                                       exp(-sqrt(mean((x-y)^2)))
+                                                })
+   }
+
+    mdata <- measuredData
+    if(is.null(parameters)){
+        parameters <- tryCatch(read.csv("parameters.csv", stringsAsFactor=FALSE), error = function (e) {
+            stop("You need to specify a path for the parameters.csv, or a matrix.")
+        })
+    } else {
+        if((!is.list(parameters)) & (!is.matrix(parameters))){
+            parameters <- tryCatch(read.csv(parameters, stringsAsFactor=FALSE), error = function (e){
+                stop("Cannot find neither parameters file neither the parameters matrix")
+            })
+        }}
+
+    print("optiMuso is randomizing the epc parameters now...",quote = FALSE)
+    randVals <- musoRand(parameters = parameters,constrains = NULL, iterations = iterations)
+
+    origEpc <- readValuesFromFile(epcFile, randVals[[1]])
+    partialResult <- matrix(ncol=length(randVals[[1]])+2*length(dataVar) + 2)
+    colN <- randVals[[1]]
+    colN[match(parameters[,2],randVals[[1]])] <- parameters[,1]
+    colN[match(parameters[,2], randVals[[1]])[!is.na(match(parameters[,2],randVals[[1]]))]] <- parameters[,1]
+    colnames(partialResult) <- c(colN,sprintf("%s_likelihood",names(dataVar)),
+                                      sprintf("%s_rmse",names(dataVar)),"Const", "failType")
+    numParameters <- length(colN)
+    partialResult[1:numParameters] <- origEpc
+    ## Prepare the preservedCalib matrix for the faster
+    ##  run.
+    musoCodeToIndex  <- sapply(dataVar,function(musoCode){
+      settingsProto$dailyOutputTable[settingsProto$dailyOutputTable$code == musoCode,"index"]
+    })
+
+    resultRange <- (numParameters + 1):(ncol(partialResult))
+    randValues <- randVals[[2]]
+
+    settingsProto$calibrationPar <- randVals[[1]]
+
+    if(!is.null(naVal)){
+        measuredData <- as.data.frame(measuredData)
+        measuredData[measuredData == naVal] <- NA
+    }
+    resIterate <- 1:nrow(calTable)
+    names(resIterate) <- tools::file_path_sans_ext(basename(calTable[,1]))
+    alignIndexes <- commonIndexes(settingsProto, measuredData)
+    if(threadNumber == 1){
+        originalRun[["calibrationPar"]] <- randVals[[1]]
+
+        origModOut <- lapply(resIterate, function(i){
+            dirName <- tools::file_path_sans_ext(basename(calTable[i,1]))
+            setwd(dirName)
+            settings <- settingsProto 
+            settings$outputLoc <- settings$inputLoc <- "./"
+            settings$iniInput <- settings$inputFiles <- rep(paste0(dirName,".ini"),2)
+            settings$outputNames <- rep(dirName,2)
+            settings$executable <- ifelse(Sys.info()[1]=="Linux","./muso","./muso.exe") # set default exe option at start wold be better
+            res <- tryCatch(calibMuso(settings=settings,parameters =origEpc, silent = TRUE, skipSpinup = TRUE), error=function(e){NA})
+            setwd("../")
+            res
+        })
+        originalRun[["origModOut"]] <- origModOut
+
+        partialResult[,resultRange] <- calcLikelihoodsForGroups(dataVar=dataVar, 
+                                                                mod=origModOut,
+                                                                mes=measuredData,
+                                                                likelihoods=likelihood,
+                                                                alignIndexes=alignIndexes,
+                                                                musoCodeToIndex = musoCodeToIndex,nameGroupTable = nameGroupTable, groupFun=mean, constraints=constraints,th=th)
+
+        write.csv(x=randVals[[1]],"../randIndexes.csv")
+        write.csv(x=partialResult, file="preservedCalib.csv",row.names=FALSE)
+    }
+
+    print("Running the model with the random epc values...", quote = FALSE)
+    for(i in 2:(iterations+1)){
+        tmp <- lapply(resIterate, function(siteI){
+            dirName <- tools::file_path_sans_ext(basename(calTable[siteI,1]))
+            setwd(dirName)
+            settings <- settingsProto 
+            settings$outputLoc <- settings$inputLoc <- "./"
+            settings$iniInput <- settings$inputFiles <- rep(paste0(dirName,".ini"),2)
+            settings$outputNames <- rep(dirName,2)
+            settings$executable <- ifelse(Sys.info()[1]=="Linux","./muso","./muso.exe") # set default exe option at start wold be better
+
+            res <- tryCatch(calibMuso(settings=settings,parameters=randValues[(i-1),], silent = TRUE, skipSpinup = TRUE), error=function(e){NA})
+            setwd("../")
+            res
+        })
+
+        if(is.null(tmp)){
+           partialResult[,resultRange] <- NA
+        } else {
+            partialResult[,resultRange] <- calcLikelihoodsForGroups(dataVar=dataVar, 
+                                                                mod=tmp,
+                                                                mes=measuredData,
+                                                                likelihoods=likelihood,
+                                                                alignIndexes=alignIndexes,
+                                                                musoCodeToIndex = musoCodeToIndex,nameGroupTable = nameGroupTable, groupFun=mean, constraints = constraints, th=th)
+
+                
+                
+                
+                
+
+        partialResult[1:numParameters] <- randValues[(i-1),]
+        write.table(x=partialResult, file="preservedCalib.csv", append=TRUE, row.names=FALSE,
+                    sep=",", col.names=FALSE)
+        # write.csv(x=tmp, file=paste0(pretag, (i+1),".csv"))
+        writeLines(as.character(i-1),"progress.txt") #UNCOMMENT IMPORTANT
+    }
+    }
+
+    if(threadNumber == 1){
+        return(originalRun)
+    }
+
+    return(0)
+}
+distributeCores <- function(iterations, numCores){
+    perProcess<- iterations %/% numCores
+    numSimu <- rep(perProcess,numCores)
+    gainers <- sample(1:numCores, iterations %% numCores)
+    numSimu[gainers] <- numSimu[gainers] + 1
+    numSimu
+}
+
+prepareFromAgroMo <- function(fName){
+    obs <- read.table(fName, stringsAsFactors=FALSE, sep = ";", header=T)
+    obs <- reshape(obs, timevar="var_id", idvar = "date", direction = "wide")
+    dateCols <- apply(do.call(rbind,(strsplit(obs$date, split = "-"))),2,as.numeric)
+    colnames(dateCols) <- c("year", "month", "day")
+    cbind.data.frame(dateCols, obs)
+}
+
+calcLikelihoodsForGroups <- function(dataVar, mod, mes,
+                                     likelihoods, alignIndexes, musoCodeToIndex,
+                                     nameGroupTable, groupFun, constraints,
+                                     th = 10){
+
+    if(!is.null(constraints)){
+                         constRes<- sapply(mod,function(m){
+                            compoVect(m,constraints)
+                         })
+
+                        failType <- constMatToDec(constRes)
+    }
+
+    likelihoodRMSE <- sapply(names(dataVar),function(key){
+              modelled <- as.vector(unlist(sapply(sort(names(alignIndexes)),
+                                           function(domain_id){
+                                            apply(do.call(cbind,
+                                                          lapply(nameGroupTable[,1][nameGroupTable[,2] == domain_id],
+                                                                 function(site){mod[[site]][alignIndexes[[domain_id]]$model,musoCodeToIndex[key]]
+                                        })),1,groupFun)
+
+
+
+
+                                        })))
+
+
+               measuredGroups <- split(mes,mes$domain_id)
+               measured <- do.call(rbind.data.frame, lapply(names(measuredGroups), function(domain_id){
+                                                    measuredGroups[[domain_id]][alignIndexes[[domain_id]]$meas,]
+                                        }))
+               measured <- measured[measured$var_id == key,]
+               res <- c(likelihoods[[key]](modelled, measured),
+                        sqrt(mean((modelled-measured$mean)^2))
+               )
+
+
+               print(abs(mean(modelled)-mean(measured$mean)))
+               res
+        })
+
+    likelihoodRMSE <- c(likelihoodRMSE[1,], likelihoodRMSE[2,],
+             ifelse((100 * sum(apply(constRes, 2, prod)) / ncol(constRes)) >= th,
+                    1,0), failType)
+    names(likelihoodRMSE) <- c(sprintf("%s_likelihood",dataVar), sprintf("%s_rmse",dataVar), "Const", "failType")
+    return(likelihoodRMSE)
+}
+
+commonIndexes <- function (settings,measuredData) {
+        # Have to fix for other starting points also
+        modelDates <- seq(from= as.Date(sprintf("%s-01-01",settings$startYear)), 
+            by="days",
+            to=as.Date(sprintf("%s-12-31",settings$startYear+settings$numYears-1)))
+        modelDates <- grep("-02-29",modelDates,invert=TRUE, value=TRUE)
+
+        lapply(split(measuredData,measuredData$domain_id),function(x){
+            measuredDates <- x$date
+            modIndex <- match(as.Date(measuredDates), as.Date(modelDates))
+            measIndex <- which(!is.na(modIndex))
+            modIndex <- modIndex[!is.na(modIndex)]
+            cbind.data.frame(model=modIndex,meas=measIndex)
+        })
+} 
+
+agroLikelihood <- function(modVector,measured){
+    mu <- measured[,grep("mean", colnames(measured))]
+    stdev <- measured[,grep("^sd", colnames(measured))]
+    ndata <- nrow(measured)
+    sum(sapply(1:ndata, function(x){
+                  dnorm(modVector, mu[x], stdev[x], log = TRUE)
+               }), na.rm=TRUE)
+}
+
+
+#' compareCalibratedWithOriginal
+#'
+#' This functions compareses the likelihood and the RMSE values of the simulations and the measurements
+#' @param key
+compareCalibratedWithOriginal <- function(key, modOld, modNew, mes,
+                             likelihoods, alignIndexes, musoCodeToIndex, nameGroupTable,
+                             groupFun){
+
+    original <- as.vector(unlist(sapply(sort(names(alignIndexes)),
+                    function(domain_id){
+                        apply(do.call(cbind,
+                            lapply(nameGroupTable$site_id[nameGroupTable$domain_id == domain_id],
+                                   function(site){
+                                       modOld[[site]][alignIndexes[[domain_id]]$model,musoCodeToIndex[key]]
+                            })),1,groupFun)
+                    })))
+    calibrated <- as.vector(unlist(sapply(sort(names(alignIndexes)),
+                    function(domain_id){
+                        apply(do.call(cbind,
+                            lapply(nameGroupTable$site_id[nameGroupTable$domain_id == domain_id],
+                                   function(site){
+                                       modNew[[site]][alignIndexes[[domain_id]]$model,musoCodeToIndex[key]]
+                            })),1,groupFun)
+                    })))
+    measuredGroups <- split(mes,mes$domain_id)
+    measured <- do.call(rbind.data.frame, lapply(names(measuredGroups), function(domain_id){
+                                                    measuredGroups[[domain_id]][alignIndexes[[domain_id]]$meas,]
+                                        }))
+    measured <- measured[measured$var_id == key,]
+    return(data.frame(original = original, calibrated = calibrated,measured=measured$mean))
+}
+
+
+spatialRun <- function(settingsProto,calibrationPar, parameters, calTable){
+    resIterate <- 1:nrow(calTable)
+    names(resIterate) <- tools::file_path_sans_ext(basename(calTable[,1]))
+    modOut <- lapply(resIterate, function(i){
+            dirName <- tools::file_path_sans_ext(basename(calTable[i,1]))
+            setwd(dirName)
+            settings <- settingsProto 
+            settings$outputLoc <- settings$inputLoc <- "./"
+            settings$iniInput <- settings$inputFiles <- rep(paste0(dirName,".ini"),2)
+            settings$outputNames <- rep(dirName,2)
+            settings$calibrationPar <- calibrationPar
+            settings$executable <- ifelse(Sys.info()[1]=="Linux","./muso","./muso.exe") # set default exe option at start wold be better
+            res <- tryCatch(calibMuso(settings=settings,parameters =parameters, silent = TRUE, skipSpinup = TRUE), error=function(e){NA})
+            setwd("../")
+            res
+        })
+    modOut
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/musoExample.R

@@ -0,0 +1,56 @@
+#'copyMusoExampleTo
+#'
+#'This function enables the user to download a complete, working file set to quickly start using Biome-BGCMuSo through RBBGCMuso (or in standalone mode). The user has to specify the target directory for the files. The file set contains the model executable (muso.exe in Windows), the INI files that drive the model, and other files like meteorology input, ecophysiological constants file (EPC), and other ancillary files (CO2 concentration, parameter range definition file called parameters.csv). Note that we strongly recommend to read the User's Guide of Biome-BGCMuSo to clarify the meaning of the input files. The input files (s.ini, n.ini, maize.epc, meteorology files) are simple text files, so the user can read (and modify) them with his/her favourite text editor (like Editpad Lite, vim, emacs). Note that some files use UNIX/Linux style text which means that the text will not be readable using the Windows Notepad. 
+#'
+#'@param example This is the name of the example file. If it is not set then a simple graphical user interface (tcl/tk menu) will open to select the target dataset (which is typically an experimental site). In the list hhs means the Hegyhatsal eddy covariance site in Hungary. 
+#'@param destination The destination where the example files will be copied.
+#'@export
+
+copyMusoExampleTo <- function(example = NULL, destination = NULL){
+  WindowsP <- Sys.info()[1] == "Windows"
+  
+  chooseExample <- function(){
+    choiceWin <- tcltk::tktoplevel()
+    tcltk::tclRequire("BWidget")
+    tcltk::tktitle(choiceWin) <- "Choose an example!"
+    tcltk::tcl("wm","geometry",choiceWin,"200x50")
+    tcltk::tcl("wm", "attributes", choiceWin, topmost=TRUE)
+    choiceValues <-  basename(list.dirs(system.file("examples","",package = "RBBGCMuso"),recursive = FALSE))
+    choices <- tcltk::tkwidget(choiceWin,"ComboBox",
+                               editable = FALSE, values = choiceValues,
+                               textvariable = tcltk::tclVar(choiceValues[1]))
+    tcltk::tkpack(choices)
+    choiceValue <- NA
+    closeSelection <- tcltk::tkwidget(choiceWin,"button",text ="Select", command =function (){
+      choiceValue <<- tcltk::tclvalue(tcltk::tcl(choices,"get"))
+      tcltk::tkdestroy(choiceWin)
+    })
+    
+    tcltk::tkpack(closeSelection)
+    while(as.numeric(tcltk::tclvalue(tcltk::tcl("winfo","exists",choiceWin)))){
+      
+    }
+    return(choiceValue)
+  }
+  
+  
+  
+  if(is.null(example)){
+    cExample<-paste0(system.file("examples","",package = "RBBGCMuso"),"/",chooseExample())       
+  } else {
+    cExample <- paste0(system.file("examples","",package = "RBBGCMuso"),"/","hhs") 
+  }
+  
+  if(is.null(destination)){
+    destination<-tcltk::tk_choose.dir(getwd(), "Choose folder to copy the examples!")
+  }
+  
+  currDir <- getwd()
+  setwd(cExample)
+  if(!WindowsP){
+      file.copy(grep("(exe|dll)$", list.files(), value = TRUE, invert = TRUE),destination)
+  } else {
+      file.copy(grep("^muso$", list.files(), value = TRUE, invert = TRUE),destination)    
+  }
+  setwd(destination)
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/musoMethChanger.R

@@ -0,0 +1,49 @@
+## library(RBBGCMuso)
+## library(BayesianTools)
+## library(sensitivity)
+
+metMusoGet <- function(metFile,skip=4,namerow=3,saveBackup=TRUE, revert=FALSE){
+
+    
+    
+    metData<-read.table(file = metFile,skip=skip)
+    namesMet <- unlist(read.table(file=metFile,skip = namerow-1,nrows = 1))
+    colnames(metData)<-namesMet
+
+    if(revert){
+        file.copy(grep(basename(metFile),grep("mbck$",list.files(dirname(metFile)),value=TRUE),value = TRUE), metFile,overwrite = TRUE)
+        return(cat("Meteorological data is succesfully reverted to backup data"))
+    }
+
+    if(saveBackup){
+        file.copy(metFile,paste(metFile,"mbck",sep = "-"))
+    }    
+return(metData)
+}
+
+metMusoSet <- function(metFile,skip=4,namerow=3,saveBackup=TRUE, revert=FALSE,index, changedData){
+
+    
+    
+    metData<-read.table(file = metFile,skip=skip)
+    namesMet <- unlist(read.table(file=metFile,skip = namerow-1,nrows = 1))
+    colnames(metData)<-namesMet
+
+    if(revert){
+        file.copy(grep("mbck$",list.files(),value=TRUE), metFile)    
+    }
+
+    if(saveBackup){
+        file.copy(metFile,paste(metFile,"mbck",sep = "-"))
+    }
+
+    if(is.vector(changedData)&(length(metData[,index])==length(changedData))){
+        metData[,index]<-changedData
+
+        changedMet<- c(readLines(metFile,-1)[1:skip],apply(metData,1, function (x) paste(x,collapse = " ")))
+        return(writeLines(changedMet,metFile))
+    
+    }else {
+        return(cat("\n\tThe changedData is not a vector or not in a same length"))
+    }
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/musoMonte.R

@@ -0,0 +1,278 @@
+#' musoMonte
+#'
+#' This function executes the Monte Carlo experiment with Biome-BGCMuSo (musoRand is called by this function). It samples the selected  model parameters within user defined ranges from conditional multivariate uniform distribution, and then runs the model for each run.
+#' @author Roland HOLLOS
+#' @param settings A list of environmental variables for the Monte Carlo experiment. These settings are generated by the setupMuso function. By default the settings parameter is generated automatically. 
+#' @param parameters This is a dataframe (heterogeneous data-matrix), where the first column is the name of the parameter, the second is a numeric vector of the rownumbers of the given variable in the input EPC file, and the last two columns describe the minimum and the maximum of the parameter (i.e. the parameter ranges), defining the interval for the randomization.
+#' @param calibrationPar You might want to change some parameters in your EPC file before you run the modell. You have to select the appropirate model parameters here. You can refer to the parameters by the number of the line in the EPC file where the variables are defined. The indexing of the lines starts at 1, and each line matters (like in any simple text file). You should use a vector for this selection like c(1,5,8)
+#' @param inputDir The location of the input directory for the Biome-BGCMuSo model. This directory must contain a viable pack of all input files and the model executable file.  
+#' @param iterations Number of the Monte Carlo simulations.
+#' @param preTag This defines the name of the output files. This tag will be re-used so that the results will be like preTag-1.csv, preTag-2csv...
+#' @param outputType  This parameter can be "oneCsv", "moreCsv", and "netCDF". If "oneCsv" is chosen the function creates one large csv file for all of the runs. If "moreCsv" is chosen, every model output goes to separate files. If netCDF is selected the output will be stored in a netCDF file. The default value of the outputTypes is "moreCsv". Note that netCDF is not implemented yet. 
+#' @param fun If you select a variable from the possible outputs (by using the varIndex parameter), you have to provide a function which maps to a subset of real numbers. The most frequent possibilities are: mean, min, max, var, but you can define any function for your needs.
+#' @param varIndex This parameter specifies which parameter will be used for the Monte Carlo experiment from the output list of Biome-BGCMuSo (defined by the INI file). You can extract this information from the INI files. At the output parameter specifications, the parameter order will determine this number. For example, if you have set these output parameters: 412, 874, 926, 888, and you want to use 926 for the experiment, you should specify varIndex as 3. 
+#' @param debugging If you set this parameter, you can save every logfile, and RBBGCMuso will select those which contains errors. This is useful to study why the model crashes with a given parameter set. 
+#' @param keepEpc If you set keepEpc as TRUE, it will save every selected EPC file, and move the wrong ones into the WRONGEPC directory.
+#' @importFrom magrittr '%>%'
+#' @export
+
+musoMonte <- function(settings=NULL,
+                     parameters=NULL,
+                     inputDir = "./",
+                     outLoc = "./calib",
+                     iterations = 10,
+                     preTag = "mont-",
+                     outputType = "moreCsv",
+                     fun=mean,
+                     varIndex = 1,
+                     outVars = NULL,
+                     silent = TRUE,
+                     skipSpinup = TRUE,
+                     debugging = FALSE,
+                     keepEpc = FALSE,
+                     constrains = NULL,
+                     skipZero = TRUE,
+                     postProcString=NULL,
+                     modifyOut=TRUE,
+                     ...){
+
+
+    readValuesFromEpc  <- function(epc, linums){
+        epcFile <- readLines(epc)
+        rows <- numeric(2)
+        values <- sapply(linums, function(x){
+            rows[1] <- as.integer(x)
+            rows[2] <- as.integer(round(100*x)) %% 10 + 1 
+            epcFile <- readLines(epc)
+            selRow <- unlist(strsplit(epcFile[rows[1]], split= "[\t ]"))
+            selRow <- selRow[selRow!=""]
+            return(as.numeric(selRow[rows[2]]))
+            
+        })
+        
+        return(values)
+    } 
+    
+    if(is.null(parameters)){
+        parameters <- tryCatch(read.csv("parameters.csv", stringsAsFactor=FALSE), error = function (e) {
+            stop("You need to specify a path for the parameters.csv, or a matrix.")
+        })
+    } else {
+        if((!is.list(parameters)) & (!is.matrix(parameters))){
+             parameters <- tryCatch(read.csv(parameters, stringsAsFactor=FALSE), error = function (e){
+                                         stop("Cannot find neither parameters file neither the parameters matrix")
+                                     })
+        }}
+    
+    outLocPlain <- basename(outLoc)
+    currDir <- getwd()
+
+    if(!dir.exists(outLoc)){
+        dir.create(outLoc)
+        warning(paste(outLoc," is not exists, so it was created"))
+    }
+
+    outLoc <- normalizePath(outLoc)
+
+    if(is.null(settings)){
+        settings <- setupMuso()
+    }
+    
+    
+
+    if(is.null(outVars)){
+        numVars <- length(settings$outputVars[[1]])
+        outVarNames <- settings$outputVars[[1]]
+    } else {
+        numVars <- length(outVars)
+        outVarNames <- sapply(outVars, musoMapping)
+    }
+    
+    if(!is.null(postProcString)){
+        outVarNames <- c(outVarNames,gsub("\\s","",unlist(strsplit(procString,"<-"))[1]))
+    }
+
+    parameterNames <- gsub("([\\s]|\\-epc)","",parameters[,1],perl=TRUE)
+    # settings$calibrationPar <- A[,1] #:LATER:
+    pretag <- file.path(outLoc,preTag)
+    npar <- length(settings$calibrationPar)
+    
+    ##reading the original epc file at the specified
+    ## row numbers
+    if(iterations < 3000){
+        randVals <- musoRand(parameters = parameters,fileType="epc", iterations = 3000)
+        randVals[[2]]<- randVals[[2]][sample(1:3000,iterations),]
+    } else {
+        randVals <- musoRand(parameters = parameters,fileType="epc", iterations = iterations)
+    }
+    
+    origEpc <- readValuesFromEpc(settings$epc[2],parameters[,2])
+    
+    ## Prepare the preservedEpc matrix for the faster
+    ##  run.
+
+    pretag <- file.path(outLoc,preTag)
+    
+    ## Creating function for generating separate
+    ## csv files for each run
+
+    progBar <- txtProgressBar(1,iterations,style=3)
+
+    
+    moreCsv <- function(){
+        settings$iniInput[2] %>%
+            (function(x) paste0(dirname(x),"/",tools::file_path_sans_ext(basename(x)),"-tmp.",tools::file_ext(x))) %>%
+            unlink
+        randValues <- randVals[[2]]
+        settings$calibrationPar <- randVals[[1]]
+        ## randValues <- randValues[,randVals[[1]] %in% parameters[,2]][,rank(parameters[,2])]
+        modellOut <- matrix(ncol = numVars, nrow = iterations + 1)
+
+
+        origModellOut <- calibMuso(settings=settings,silent=TRUE)
+        write.csv(x=origModellOut, file=paste0(pretag,1,".csv"))
+
+        if(!is.list(fun)){
+            funct <- rep(list(fun), numVars)
+        }
+            
+        tmp2 <- numeric(numVars)
+# browser()
+        for(j in 1:numVars){
+            tmp2[j]<-funct[[j]](origModellOut[,j])
+        }
+        modellOut[1,]<- tmp2
+        
+        for(i in 2:(iterations+1)){
+            tmp <- tryCatch(calibMuso(settings = settings,
+                             parameters = randValues[(i-1),],
+                             silent= TRUE,
+                             skipSpinup = skipSpinup,
+                             keepEpc = keepEpc,
+                             debugging = debugging,
+                             modifyOriginal = modifyOut,
+                             outVars = outVars,postProcString=postProcString), error = function (e) NA)
+            
+            if(length(dim(tmp))>=1){
+                for(j in 1:numVars){
+                    tmp2[j]<-funct[[j]](tmp[,j])
+                }
+                if(skipZero){
+                    if(tmp2[j]==0){
+                        tmp2[j] <- NA
+                    }
+                }
+            } else {
+                for(j in 1:numVars){
+                    tmp2[j]<-NA
+                }
+            }
+
+            
+            
+            modellOut[i,]<- tmp2
+            write.csv(x=tmp, file=paste0(pretag,(i+1),".csv"))
+            setTxtProgressBar(progBar,i)
+        }
+
+        paramLines <- parameters[,2]
+        paramLines <- order(paramLines)
+        randInd <- randVals[[1]][(randVals[[1]] %in% parameters[,2])]
+        randInd <- order(randInd)
+    
+
+       
+        # browser()
+        epcStrip <- rbind(origEpc[order(parameters[,2])],
+                          randValues[,randVals[[1]] %in% parameters[,2]][,randInd])
+        
+        
+            preservedEpc <- cbind(epcStrip,
+                                  modellOut)
+        colnames(preservedEpc) <- c(parameterNames[paramLines], sapply(outVarNames, function (x) paste0("mod.", x)))
+        return(preservedEpc)
+    }
+    
+    ## Creating function for generating one
+    ## csv files for each run
+    
+    oneCsv <- function () {
+      #  stop("This function is not implemented yet")
+         settings$iniInput[2] %>%
+            (function(x) paste0(dirname(x),"/",tools::file_path_sans_ext(basename(x)),"-tmp.",tools::file_ext(x))) %>%
+            unlink
+        randValues <- randVals[[2]]
+        settings$calibrationPar <- randVals[[1]]
+        ## randValues <- randValues[,randVals[[1]] %in% parameters[,2]][,rank(parameters[,2])]
+        modellOut <- matrix(ncol = numVars, nrow = iterations + 1)
+
+        origModellOut <- calibMuso(settings=settings,silent=TRUE)
+        write.csv(x=origModellOut, file=paste0(pretag,".csv"))
+
+        if(!is.list(fun)){
+            funct <- rep(list(fun), numVars)
+        }
+            
+        tmp2 <- numeric(numVars)
+
+        for(j in 1:numVars){
+            tmp2[j]<-funct[[j]](origModellOut[,j])
+        }
+        modellOut[1,]<- tmp2
+        
+        for(i in 2:(iterations+1)){
+            tmp <- tryCatch(calibMuso(settings = settings,
+                             parameters = randValues[(i-1),],
+                             silent= TRUE,
+                             skipSpinup = skipSpinup,
+                             keepEpc = keepEpc,
+                             debugging = debugging,
+                             outVars = outVars), error = function (e) NA)
+            
+            if(!is.na(tmp)){
+                for(j in 1:numVars){
+                    tmp2[j]<-funct[[j]](tmp[,j])
+                }
+            } else {
+                for(j in 1:numVars){
+                    tmp2[j]<-rep(NA,length(settings$outputVars[[1]]))
+                }
+            }
+
+            
+            
+            modellOut[i,]<- tmp2
+            write.table(x=tmp, file=paste0(pretag,".csv"), append = TRUE,col.names = FALSE, sep = ",")
+            setTxtProgressBar(progBar,i)
+        }
+
+        paramLines <- parameters[,2]
+        paramLines <- order(paramLines)
+        randInd <- randVals[[1]][(randVals[[1]] %in% parameters[,2])]
+        randInd <- order(randInd)
+        
+       
+        epcStrip <- rbind(origEpc[order(parameters[,2])],
+                          randValues[,randVals[[1]] %in% parameters[,2]][,randInd])
+        
+        
+            preservedEpc <- cbind(epcStrip,
+                                  modellOut)
+        colnames(preservedEpc) <- c(parameterNames[paramLines], sapply(outVarNames, function (x) paste0("mod.", x)))
+        return(preservedEpc)
+    }
+    
+    netCDF <- function () {
+        stop("This function is not inplemented yet")
+    }
+    
+    ## Call one function according to the outputType
+    switch(outputType,
+           "oneCsv" = (a <- oneCsv()),
+           "moreCsv" = (a <- moreCsv()),
+           "netCDF" = (a <- netCDF()))
+    write.csv(a,"preservedEpc.csv")
+   
+    setwd(currDir)
+    return(a)
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/musoRand.R

@@ -0,0 +1,187 @@
+#' musoRand
+#'
+#' This funtion uses the Monte Carlo technique to uniformly sample the parameter space from user defined parameters of the Biome-BGCMuSo model. The sampling algorithm ensures that the parameters are constrained by the model logic which means that parameter dependencies are fully taken into account (parameter dependency means that e.g leaf C:N ratio must be smaller than C:N ratio of litter; more complicated rules apply to the allocation parameters where the allocation fractions to different plant compartments must sum up 1). This function implements a mathematically correct solution to provide uniform distriution for all selected parameters. 
+#' @author Roland HOLLOS
+#' @param parameters This is a dataframe (heterogeneous data-matrix), where the first column is the name of the parameter, the second is a numeric vector of the rownumbers of the given variable in the input EPC file, and the last two columns describe the minimum and the maximum of the parameter (i.e. the parameter ranges), defining the interval for the randomization.
+#' @param constrains This is a matrix wich specify the constrain rules for the sampling. Parameter dependencies are described in the Biome-BGCMuSo User's Guide. Further informations is coming soon.
+#' @param iteration The number of samples for the Monte-Carlo experiment. We propose to use at least 3000 iteration because it is generally fast and it can be subsampled later at any time. 
+#' @importFrom limSolve xsample
+#' @export
+
+musoRand <- function(parameters, iterations=3000, fileType="epc", constrains = NULL, burnin = NULL){
+    if(is.null(constrains)){
+        constMatrix <- constrains
+        constMatrix <- getOption("RMuso_constMatrix")[[fileType]][[as.character(getOption("RMuso_version"))]]
+    } else {
+        constMatrix <- constrains
+    }
+    
+    parameters <- parameters[,-1]
+    constMatrix <- constMatrix[,-1]
+    
+    depTableMaker <- function(constMatrix,parameters){
+        # browser()
+        parameters <- parameters[order(parameters[,1]),] ## BUG!!!
+        selectedRows <- constMatrix[,"INDEX"] %in% parameters[,1]
+        rankList <- rank(constMatrix[selectedRows,2])
+        constMatrix[selectedRows,c(5,6)] <- parameters[rankList,c(2,3)]
+	logiConstrain <- (constMatrix[,"GROUP"] %in% constMatrix[constMatrix[,"INDEX"] %in% parameters[,1],"GROUP"] &
+			  (constMatrix[,"GROUP"]!=0)) | ((constMatrix[,"INDEX"] %in% parameters[,1]) & (constMatrix[,"GROUP"] == 0))
+	constMatrix <- constMatrix[logiConstrain,]
+	constMatrix <- constMatrix[order(apply(constMatrix[,7:8],1,function(x){x[1]/10+abs(x[2])})),]
+	constMatrix
+    }
+    # browser()
+    genMat0 <- function(dep){
+	numberOfVariable <- nrow(dep)
+	G <- rbind(diag(numberOfVariable), -1*diag(numberOfVariable))
+	h <- c(dependences[,5], -1*dependences[,6])
+	return(list(G=G,h=h))
+    }
+
+    genMat1 <- function(dep, N){
+
+	## Range <- sapply(list(min,max),function(x){
+	##   x(as.numeric(rownames(dep)))
+	## }) It is more elegant, more general, but slower
+	Range <- (function(x){
+	    c(min(x), max(x))
+	})(as.numeric(dep[,"rowIndex"]))
+
+	numberOfVariables <- nrow(dep)
+	G<- -1*diag(numberOfVariables)
+
+	for(i in 1:numberOfVariables){
+	    if(dep[i,4]!=0){
+		G[i,dep[i,4]] <- 1
+	    }
+
+	}
+# browser()
+	G<-G[dep[,4]!=0,]
+        
+        if(is.null(nrow(G))){
+            G<-t(as.matrix(G))
+        }
+        numRowsInG <- nrow(G)
+	if(Range[1]==1){
+	    G<-cbind(G,matrix(ncol=(N-Range[2]),nrow=numRowsInG,data=0))
+	} else{
+	    if(Range[2]==N){
+		G<-cbind(matrix(ncol=(Range[1]-1),nrow=numRowsInG,data=0),G)
+	    } else {
+		G <- cbind(matrix(ncol=(Range[1]-1),nrow=numRowsInG,data=0),G,matrix(ncol=(N-Range[2]),nrow=numRowsInG,data=0))
+	    }
+	}
+	return(list(G=-1*G,h=-1*rep(0,nrow(G))))
+    }
+
+    genMat2 <- function(dep, N){
+	G <- rep(1,nrow(dep))
+
+	Range <- (function(x){
+	    c(min(x), max(x))
+	})(as.numeric(dep[,"rowIndex"]))
+
+	if(Range[1]==1){
+	    G<-c(G, numeric(N-Range[2]))
+	} else{
+	    if(Range[2]==N){
+		G<-c(numeric(Range[1]-1), G)
+	    } else {
+		G <- c(numeric(Range[1]-1), G, numeric(N-Range[2]))
+	    }
+	}
+
+	G <- t(matrix(sign(dep[2,4])*G))
+	h <- abs(dep[1,4])
+        if(dep[1,"TYPE"]==2){ # This is not needed, I'll have to remove the if part, and keep the content
+            G <- G*(-1)
+            h <- h*(-1)
+        }
+
+	return(list(G=G,h=h))
+    }
+
+    genMat3 <- function(dep, N){
+	Range <- (function(x){
+	    c(min(x), max(x))
+	})(as.numeric(dep[,"rowIndex"]))
+
+	E <- rep(1,nrow(dep))
+
+	if(Range[1]==1){
+	    E<-c(E, numeric(N-Range[2]))
+	} else{
+	    if(Range[2]==N){
+		E<-c(numeric(Range[1]-1), E)
+	    } else {
+		E <- c(numeric(Range[1]-1), E, numeric(N-Range[2]))
+	    }
+	}
+
+
+	E <- t(matrix(E))
+	f <- dep[1,4]
+	return(list(E=E,f=f))
+    }
+
+
+    applyRandTypeG <- function(dep,N){
+	type <- unique(dep[,"TYPE"])
+	minR <- min(dep[,"rowIndex"])
+	maxR <- max(dep[,"rowIndex"])
+	switch(type,
+	       invisible(Gh <- genMat1(dep, N)),
+	       invisible(Gh <- genMat2(dep, N)))
+	return(Gh)
+    }
+
+    applyRandTypeE <- function(dep,N){
+	type <- unique(dep[,"TYPE"])
+	minR <- min(dep[,"rowIndex"])
+	maxR <- max(dep[,"rowIndex"])
+	switch(-type,
+	       stop("Not implemented yet"),
+	       stop("Not implemented yet"),
+	       invisible(Ef <- genMat3(dep, N)))
+	return(Ef)
+    }
+
+    dependences <- depTableMaker(constMatrix, parameters)
+    dependences <- cbind(dependences,1:nrow(dependences))
+    colnames(dependences)[ncol(dependences)] <- "rowIndex"
+    # browser()
+    numberOfVariable <- nrow(dependences)
+    nonZeroDeps<-dependences[dependences[,"TYPE"]!=0,]
+    if(nrow(nonZeroDeps)!=0){
+        splitedDeps<- split(nonZeroDeps,nonZeroDeps[,"GROUP"])
+        Gh <- list()
+        Ef <- list()
+
+        for(i in 1:length(splitedDeps)){
+            print(splitedDeps[[i]][1,"TYPE"])
+            if(splitedDeps[[i]][1,"TYPE"]>0){
+                Gh[[i]]<-applyRandTypeG(splitedDeps[[i]],nrow(dependences))
+            } else {
+                Ef[[i]] <- applyRandTypeE(splitedDeps[[i]],nrow(dependences))
+            }
+        }
+        
+        Gh0<- genMat0(dependences)
+        G <- do.call(rbind,lapply(Gh,function(x){x$G}))
+        G<- rbind(Gh0$G,G)
+        h <- do.call(c,lapply(Gh,function(x){x$h}))
+        h <- c(Gh0$h,h)
+        E <- do.call(rbind,lapply(Ef,function(x){x$E}))
+        f <- do.call(c,lapply(Ef,function(x){x$f}))
+         # browser()
+        randVal <- suppressWarnings(limSolve::xsample(G=G,H=h,E=E,F=f,burninlength=burnin, iter = iterations))$X
+    } else{
+        Gh0<-genMat0(dependences)
+        randVal <- suppressWarnings(xsample(G=Gh0$G,H=Gh0$h, iter = iterations))$X
+    }
+    
+    results <- list(INDEX =dependences$INDEX, randVal=randVal)
+    return(results)
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/musoSensi.R

@@ -0,0 +1,121 @@
+#' musoSensi
+#'
+#' This function does regression based sensitivity analysis based on the output of musoMonte. 
+#' @param settings A list of montecarlos environmental variables. It is generated by the setupMuso() function. In default the settings parameter is generated automatically. 
+#' @param parameters This is a dataframe (heterogen data-matrix), which first column is the name of the parameters, the second is a numeric vector of the rownumbers of the given variable in the epc-fie, the last two column consist the endpont of the parameter-ranges, where the parameters will be randomized.
+#' @param calibrationPar You may want to change some parameters in your epc file, before you run the modell. You have to select the appropirate modell parameters. You can refence to these with the number of the line in the epc file where the variables are. It indexes from one. You should use a vector for this, like: c(1,5,8)
+#' @param inputDir The location of the input directory, this directory must content a viable pack of all inputfiles and the executable file. 
+#' @param iterations number of the monteCarlo run.
+#' @param preTag It will be the name of the output files. For example preTag-1.csv, pretag-2csv...
+#' @param outputType This parameter can be "oneCsv", "moreCsv", and "netCDF". If "oneCsv" is choosen the function create 1 big csv file for all of the runs, if "moreCsv" is choosen, every modell output goes to separate files, if netCDF is selected the outputs will be put in a netCDF file. The default value of the outputTypes is "moreCsv". netCDF is not implemented yet. 
+#' @param fun If you select a variable from the possible outputs (with specify the varIndex parameter), you have to provide a function which maps to a subset of real numbers. The most frequent possibilities are: mean, min, max, var, but you can define any function for your need.
+#' @param varIndex This parameter specify which parameter of the output will be used. You can extract this information from the ini-files. At the output parameter specifications, the parameters order will determine this number. For example, if you have set these output parameters: 412, 874, 926, 888, and you want to use 926, you should address varIndex with 3.
+#' @param skipSpinup With this parameter, you can turn of the spinup phase after the first spinup. I will decrease the time significantly.
+#' @importFrom ggplot2 geom_bar ggplot aes theme element_text xlab ylab ggtitle ggsave scale_y_continuous
+#' @importFrom scales percent
+#' @export
+
+musoSensi <- function(monteCarloFile = NULL,
+                     parameters = NULL,
+                     settings = NULL,
+                     inputDir = "./",
+                     outLoc = "./calib",
+                     outVars = NULL,
+                     iterations = 30,
+                     preTag = "mont-",
+                     outputType = "moreCsv",
+                     fun = mean,
+                     varIndex = 1,
+                     outputFile = "sensitivity.csv",
+                     plotName = "sensitivity.png",
+                     plotTitle = "Sensitivity",
+                     skipSpinup = TRUE,
+                     skipZero = TRUE,
+                     postProcString=NULL,
+                     modifyOut=TRUE,
+                     dpi=300){
+
+    if(is.null(parameters)){
+        parameters <- tryCatch(read.csv("parameters.csv",stringsAsFactor=FALSE), error = function (e) {
+            stop("You need to specify a path for the parameters.csv, or a matrix.")
+        })
+    } else {
+        if((!is.list(parameters)) & (!is.matrix(parameters))){
+             parameters <- tryCatch(read.csv(parameters,stringsAsFactor=FALSE), error = function (e){
+                                         stop("Cannot find neither parameters file neither the parameters matrix")
+                                     })
+        }}
+    parameters[,1] <- gsub("([\\s]|\\-epc)","",parameters[,1],perl=TRUE)
+    doSensi <- function(M){
+        # browser()
+        npar <- ncol(M)-1
+        M <- M[which(!is.na(M[,ncol(M)])),]
+        M <- M[-1,]
+        y <- M[,(npar+1)]
+        colnames(M) <- gsub("\\.epc","-epc",colnames(M))
+        M <- M[,colnames(M) %in% parameters[,1]]
+        npar <- ncol(M)
+        M <- apply(M[,1:npar],2,function(x){x-mean(x)})
+        varNames<- colnames(M)[1:npar]
+        w <- lm(y~M)$coefficients[-1]
+        Sv <- apply(M,2,var)
+        overalVar <- sum(Sv*w^2,na.rm = TRUE)
+        S=numeric(npar)
+        
+        for(i in 1:npar){
+            S[i] <- ((w[i]^2*Sv[i])/(overalVar))*100
+        }
+        
+        S <- round(S,digits=2)
+        names(S)<-varNames
+        write.csv(file = outputFile, x = S)
+
+        sensiPlot <- ggplot(data.frame(name=varNames,y=S/100),aes(x=name,y=y))+
+            geom_bar(stat = 'identity')+
+            theme(axis.text.x = element_text(angle = 45, hjust = 1))+
+            xlab(NULL)+
+            ylab(NULL)+
+            ggtitle("Sensitivity")+
+            scale_y_continuous(labels = scales::percent,limits=c(0,1))
+        print(sensiPlot)
+        ggsave(plotName,dpi=dpi)
+        return(S)
+    }
+
+    
+
+    if(is.null(monteCarloFile)){
+        M <- musoMonte(parameters = parameters,
+                      settings = settings,
+                      inputDir = inputDir,
+                      outLoc = outLoc,
+                      iterations = iterations,
+                      preTag = preTag,
+                      outputType = outputType,
+                      outVars = outVars,
+                      fun = fun,
+                      varIndex = varIndex,
+                      skipSpinup = skipSpinup,
+                      skipZero=skipZero,
+                      postProcString=postProcString,
+                      modifyOut=modifyOut
+                      )
+        M <- cbind(seq_along(M[,1]),M)
+        yInd <-  grep("mod.", colnames(M))[varIndex]
+        parNames <- grep("mod.",colnames(M), invert=TRUE, value = TRUE)
+        M <- M[,c(grep("mod.", colnames(M),invert=TRUE),yInd)]
+        
+        return(doSensi(M))
+        
+    } else {
+        M <- read.csv(monteCarloFile)
+        yInd <-  grep("mod.", colnames(M))[varIndex]
+        parNames <- grep("mod.",colnames(M), invert=TRUE, value = TRUE)
+        M <- M[,c(grep("mod.", colnames(M),invert=TRUE),yInd)]
+        # browser()
+        return(doSensi(M))        
+    }
+}
+
+
+

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/musoTime.R

@@ -0,0 +1,116 @@
+#' musoDate
+#'
+#' This function generates MuSo compatibla dates for the data
+#' @author Roland HOLLOS
+#' @param startYear
+#' @param numYears
+#' @param timestep
+#' @param combined
+#' @param corrigated
+#' @param format
+#' @importFrom lubridate leap_year
+#' @export
+
+musoDate <- function(startYear, endYears = NULL, numYears, combined = TRUE, leapYearHandling = FALSE, prettyOut = FALSE){
+
+    if(is.null(endYears) & is.null(numYears)){
+        stop("You should provide endYears or numYears")
+    }
+    
+    if(is.null(endYears)){
+        endYear <- startYear + numYears -1
+    }
+    
+    dates <- seq(from = as.Date(paste0(startYear,"01","01"),format = "%Y%m%d"), to =  as.Date(paste0(endYear,"12","31"),format = "%Y%m%d"), by = "day")
+    if(leapYearHandling){
+        if(prettyOut){
+            return(cbind(format(dates,"%d.%m.%Y"),
+                         as.numeric(format(dates,"%d")),
+                         as.numeric(format(dates,"%m")),
+                         as.numeric(format(dates,"%Y")))   )
+        }
+        
+        if(combined == FALSE){
+            return(cbind(format(dates,"%d"),format(dates,"%m"),format(dates,"%Y")))
+        } else {
+            return(format(dates,"%d.%m.%Y"))            
+        }
+
+    } else {
+         dates <- dates[format(dates,"%m%d")!="0229"]
+        if(prettyOut){
+            return(data.frame(date = format(dates,"%d.%m.%Y"),
+                              day = as.numeric(format(dates,"%d")),
+                              month = as.numeric(format(dates,"%m")),
+                              year = as.numeric(format(dates,"%Y"))))
+        }
+       
+
+        if(combined == FALSE){
+            return(cbind(format(dates,"%d"),format(dates,"%m"),format(dates,"%Y")))
+        } else {
+            return(format(dates,"%d.%m.%Y"))            
+        }
+    }
+    
+}
+#' alignData
+#'
+#' This function align the data to the model and the model to the data
+#' @importFrom lubridate leap_year
+#' @keywords internal
+alignData  <- function(mdata, dataCol, modellSettings = NULL, startDate=NULL, endDate=NULL, formatString = "%Y-%m-%d", leapYear = TRUE, continious = FALSE){
+
+    if(continious){
+        if((is.null(startDate) | is.null(endDate))){
+            stop("If your date is continuous, you have to provide both startDate and endDate. ")
+        }
+        startDate <- as.Date(startDate, format = formatString)
+        endDate <- as.Date(endDate, format = formatString)
+    }
+
+    if(is.null(modellSettings)){
+        modellSettings <- setupMuso()
+    }
+
+    mdata <- as.data.frame(mdata)
+
+    if(continious){
+        dates <- seq(startDate, to = endDate, by= "day")
+    } else{
+        dates <- do.call(c,lapply(seq(nrow(mdata)), function(i){ as.Date(paste0(mdata[i,1],sprintf("%02d",mdata[i,2]),mdata[i,3]),format = "%Y%m%d")}))
+    }
+
+    ## if(!leapYear){
+    ##     casualDays <- which(format(dates,"%m%d") != "0229")
+    ##     #mdata <- mdata[casualDays,]
+    ##     dates <- dates[casualDays]
+    ## }
+    
+    mdata <- mdata[dates >= as.Date(paste0(modellSettings$startYear,"01","01"),format = "%Y%m%d"),]
+    dates <- dates[dates >= as.Date(paste0(modellSettings$startYear,"01","01"),format = "%Y%m%d")]
+    ## goodInd <- which(!(leap_year(dates)&
+    ##                    (format(dates,"%m") == "12")&
+    ##                    (format(dates,"%d") == "31")))
+    
+    if(leapYear){
+        goodInd <- which(!(leap_year(dates)&
+                       (format(dates,"%m") == "12")&
+                       (format(dates,"%d") == "31")))
+    } else {
+        goodInd <-seq_along(dates)
+    }
+    realDate <- dates[which(format(dates,"%m%d") != "0229")]
+    if(leapYear){
+        mdata <- cbind.data.frame(realDate,mdata[goodInd,])        
+    } else {
+        mdata <- cbind.data.frame(dates,mdata)
+    }
+    modellDates <- as.Date(musoDate(startYear = modellSettings$startYear,numYears = modellSettings$numYears), format = "%d.%m.%Y")
+    mdata <- mdata[mdata[,1] %in% modellDates,]
+    nonEmpty <- which(!is.na(mdata[,dataCol+1]))
+    mdata <- mdata[nonEmpty,]
+    modIndex <- which(modellDates %in% mdata[,1])
+
+    list(measuredData = mdata[,dataCol +1], modIndex = modIndex)
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/normalMuso.R

@@ -0,0 +1,201 @@
+#' normalMuso
+#'
+#' This function optionally changes the EPC file and runs the Biome-BGCMuSo model in normal phase and reads its output file in a well-structured way with debugging features. (Execution of spinup phase is possible with spinupMuso.) Prerequisite of normalMuso is the existence of the endpoint file (which is the result of the spinup phase and contains initial conditions for the simulation). 
+#' 
+#' @author Roland HOLLOS
+#' @param settings RBBGCMuso uses variables that define the entire simulation environment. Those environment variables include the name of the INI files, the name of the meteorology files, the path to the model executable and its file name, the entire output list, the entire output variable matrix, the dependency rules for the EPC parameters etc. Using the runMuso function RBBGCMuso can automatically create those environment variables by inspecting the files in the working directory (this happens through the setupMuso function). It means that by default model setup is performed automatically in the background and the user has nothing to do. With this settings parameter we can force runMuso to skip automatic environment setup as we provide the environment settings to runMuso. In a typical situation the user can skip this option.
+#' @param timee The required timesteps in the model output. It can be "d", if it is daily, "m", if it is monthly, "y" if it is yearly. It is recommended to use daily data, as the yearly and monthly data is not well-tested yet. 
+#' @param debugging If debugging is set to TRUE, after model execution the function copies the Biome-BGCMuSo log file into a LOG directory and stores it for further processing. If debugging is set to STAMPLOG instead of TRUE, it concatenates a number before the logfile, which is one plus the maximum of those present in the LOG directory. In each case the log files will be saved. 
+#' @param keepEpc If keepEpc is set to TRUE, the function keeps the EPC file and stamps it, and then copies it to the EPCS directory. If debugging is set to TRUE, it copies the wrong EPC files to the wrong epc directory.
+#' @param export If it is set to YES or you define a filename here, the function converts the output to the specific file format. For example, if you set export to "example.csv", it converts the output to "csv". If you set it to "example.xls" it converts the output to example.xls with the xlsx package. If the Excel converter package is not installed it gives back a warning message and converts the results to csv.
+#' @param silent If you set the silent parameter to TRUE, all of the model's output normally written to the screen will be suppressed. This option can be useful to increase the speed of the model execution.
+#' @param aggressive It deletes all previous model-outputs from previous model runs.
+#' @param parameters Using normalMuso it is possible to change some of the EPC parameters prior to model execution. This can be achieved with this option. In the parameters variable you have set the row indices of the variables that you wish to change. In this parameters you can give an exact value for them in a vector form like c(1,2,3,4).
+#' @param logfilename If you would like to set a specific name for your logfiles you can set this via the logfile parameter.
+#' @param leapYear Should the function do a leapyear correction on the output data? If TRUE, then the result for 31 December will be doubled in leap years which means that the results for the leap year will cover all 366 days. See the model's User's Guide for notes on leap years. 
+#' @param keepBinary By default RBBGCMuso keeps the working environment as clean as possible, thus deletes all the regular output files. The results are directly written to the standard output (e.g. to the screen), but you can redirect it and save them to a variable. Alternatively, you can export your results to the desired destination in a desired format. Through the keepBinary parameter you can set RBBGCMuso to keep the binary output files. If you would like to set the location of the binary output, please take a look at the binaryPlace argument.
+#' @param binaryPlace The directory for the binary output files (see the keepBinary parameter).
+#' @param fileToChange You can change any line of the EPC or the INI file prior to model execution. All you need to do is to specify with this variable which file you want to change. Two options possible: "EPC" or "INI" 
+#' @return The simulation output matrix, where the columns are the chosen variables and each row is a daily/monthly/annual data. 
+#' @usage normalMuso(settings,parameters=NULL, timee="d", debugging=FALSE, logfilename=NULL,
+#' keepEpc=FALSE, export=FALSE, silent=FALSE, aggressive=FALSE, leapYear=FALSE)
+#' @import utils
+#' @export
+
+normalMuso<- function(settings=NULL,parameters=NULL,timee="d",debugging=FALSE,logfilename=NULL,keepEpc=FALSE, export=FALSE,silent=FALSE,aggressive=FALSE,leapYear=FALSE, binaryPlace=NULL,fileToChange="epc", keepBinary=FALSE){
+
+
+##########################################################################
+###########################Set local variables########################
+########################################################################
+
+    if(is.null(settings)){
+        settings <- setupMuso() #( :INSIDE: setupMuso.R)
+    }
+        # The software works on Linux or Windows, Mac is not implemented yet, so with this simple dichotomy we can determine wich syste is running
+    Linuxp <-(Sys.info()[1]=="Linux")
+    ##Copy the variables from settings
+    inputLoc <- settings$inputLoc
+    outputLoc <- settings$outputLoc
+    outputNames <- settings$outputNames
+    executable <- settings$executable
+    iniInput <- settings$iniInput
+    epc <- settings$epcInput
+    calibrationPar <- settings$calibrationPar
+    
+    ## We want to minimize the number of sideeffects so we store the state to restore in the end.
+    whereAmI<-getwd()
+
+    
+    ## Optionally the user may want to store the original binary file. At default we set it to the output location. 
+    
+    if(is.null(binaryPlace)){
+        binaryPlace <- outputLoc
+    }
+
+    ## Now we create a directories for the debugging files if these are not exists, and if debugging or keepEpc options are set to true. 
+
+        if(debugging){ #debugging is boolean, so we dont write debugging == TRUE for the sake of faster model run
+        #If log or ERROR directory does not exists create it!
+        dirName<-file.path(inputLoc,"LOG")
+        dirERROR<-file.path(inputLoc,"ERROR")
+        
+        if(!dir.exists(dirName)){
+            dir.create(dirName)
+        }
+
+        if(!dir.exists(dirERROR)){
+            dir.create(dirERROR)
+        }
+    }
+    
+    if(keepEpc) {#keepEpc is boolean
+        epcdir <- dirname(epc[1])
+        print(epcdir)
+        WRONGEPC<-file.path(inputLoc,"WRONGEPC")
+        EPCS<-file.path(inputLoc,"EPCS")
+        
+        if(!dir.exists(WRONGEPC)){
+            dir.create(WRONGEPC)
+        }
+        
+        if(!dir.exists(EPCS)){
+            dir.create(EPCS)
+        }
+    }
+    
+
+
+    
+    
+    if(!is.null(parameters)){
+        switch(fileToChange,
+               "epc" = tryCatch(changemulline(filename = epc[1],calibrationPar,parameters), #(:DONE: trycatch :INSIDE: changeMuso.R)
+                                error = function (e) {stop("Cannot change the epc file")}),
+               "ini" = tryCatch(changemulline(filename = iniInput[1],calibrationPar,parameters), #(:DONE: trycatch :INSIDE: changeMuso.R)
+                                error = function (e) {stop("Cannot change the ini file")}),
+               "both" = (stop("This option is not implemented yet, please choose epc or ini"))
+               )
+    }
+
+
+
+   
+                                        #normal run
+
+    ## if(silent){
+    ##     if(Linuxp){
+    ##         system(paste(executable,iniInput[2],"> /dev/null",sep=" "))
+    ##     } else {
+    ##         system(paste(executable,iniInput[2],sep=" "),show.output.on.console = FALSE)
+    ##     }
+        
+    ## } else {
+    ##     system(paste(executable,iniInput[2],sep=" "))
+    ## }
+
+
+    
+    ## system(paste(executable,iniInput[2],sep=" "))
+    
+    ## switch(timee,
+    ##        "d"=(Reva<-getdailyout(settings)),
+    ##        "m"=(Reva<-getmonthlyout(settings)),
+    ##        "y"=(Reva<-getyearlyout(settings))
+    ##        )
+
+    
+        if(silent){
+            if(Linuxp){
+                tryCatch(system(paste(executable,iniInput[2],"> /dev/null",sep=" ")), 
+                         error =function (e) {stop("Cannot run the modell-check the executable!")})
+            } else {
+                tryCatch(system(paste(executable,iniInput[2],sep=" "),show.output.on.console = FALSE),
+                        error =function (e) {stop("Cannot run the modell-check the executable!")} )
+            }
+            
+        } else {
+            tryCatch(system(paste(executable,iniInput[2],sep=" ")),
+                     error =function (e) {stop("Cannot run the modell-check the executable!")})
+        }
+
+
+        ##read the output
+
+            switch(timee,
+               "d"=(Reva <- tryCatch(getdailyout(settings), #(:INSIDE: getOutput.R ) 
+                                    error = function (e){
+                                        setwd((whereAmI))
+                                        stop("Cannot read binary output, please check if the output type is set 2 in the ini files!")})),
+               "m"=(Reva <- tryCatch(getmonthlyout(settings), #(:INSIDE: getOutput.R )
+                                    error = function (e){
+                                        setwd((whereAmI))
+                                        stop("Cannot read binary output, please check if the output type is set 2 in the ini files!")})),
+               "y"=(Reva <- tryCatch(getyearlyout(settings), #(:INSIDE: getOutput.R )
+                                    error = function (e){
+                                        setwd((whereAmI))
+                                        stop("Cannot read binary output, please check if the output type is set 2 in the ini files!")}))
+               )
+
+
+
+        if(keepBinary){
+            possibleNames <- getOutFiles(outputLoc = outputLoc,outputNames = outputNames) #(:INSIDE: assistantFunctions.R)
+            stampAndDir(outputLoc = outputLoc,names = possibleNames,stampDir=binaryPlace,type="output") #(:INSIDE: assistantFunctions.R)
+        }
+    
+
+
+    logfiles <- getLogs(outputLoc,outputNames,type = "normal") #(:INSIDE: assistantFunctions.R)
+    
+
+#############LOG SECTION#######################
+    errorsign <- readErrors(outputLoc = outputLoc,logfiles = logfiles,type="normal") #(:INSIDE: assistantFunctions.R)
+
+    if(keepEpc){#if keepepc option turned on
+
+        if(length(unique(dirname(epc)))>1){
+            stop("Why are you playing with my nervs? Seriously? You hold your epc-s in different folders?")
+        } else {
+
+            stampAndDir(stampDir=EPCS, wrongDir=WRONGEPC, names=epc[2], type="general", errorsign=errorsign, logfiles=logfiles)
+
+        }
+    }
+        
+
+    
+        if(debugging){ #debugging is boolean
+                       logfiles <- file.path(outputLoc,logfiles)
+                       stampAndDir(stampDir=dirName, wrongDir=dirERROR, names=logfiles, type="general",errorsign=errorsign,logfiles=logfiles)}
+    cleanupMuso()
+    if(errorsign==1){
+        return("Modell Failure")
+    }
+
+    
+
+    
+    return(Reva)
+
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/otherUsefullFunctions.R

@@ -0,0 +1,185 @@
+#' getyearlycum
+#'
+#' Funtion for getting cumulative yearly data from observations
+#' @author Roland Hollos
+#' @param daily_observations vector of the daily observations.
+#' @return A vector of yearly data
+#' @export
+
+
+getyearlycum<-function(daily_observations){
+  number_of_years<-length(daily_observations)/365
+  # daily_observations[is.na(daily_observations)]<-0 # 3+NA=NA
+  fr<-1
+  yearlycum<-rep(NA,number_of_years)
+  for(i in 1:number_of_years){
+    to<-i*365
+    yearlycum[i]<-sum(daily_observations[fr:to],na.rm = TRUE)
+    fr<-i*365+1
+  }
+  return(yearlycum)
+}
+
+#' getyearlymax
+#'
+#' Function for getting the maximum values of the years, from daily data
+#' @author Roland Hollos
+#' @param daily_observations vector of the daily observations
+#' @return A vector of yearly data
+#' @usage getyearlymax(daily_observations)
+#' @export
+
+getyearlymax<-function(daily_observations){
+  number_of_years<-length(daily_observations)/365
+  # daily_observations[is.na(daily_observations)]<-0 # 3+NA=NA
+  fr<-1
+  yearlycum<-rep(NA,number_of_years)
+  for(i in 1:number_of_years){
+    to<-i*365
+    yearlymax[i]<-max(daily_observations[fr:to],na.rm=TRUE)
+    fr<-i*365+1
+  }
+  return(yearlymax)
+}
+
+#' fextension
+#'
+#' A function for extracting the extension name from the filename string
+#' @author Roland Hollos
+#' @param filename The string of the filenam
+#' @return the extension of the given file
+#' @usage fextension(filename)
+
+fextension <- function(filename){
+    #this function gives back the given filenames extension
+    fextension <- tail(unlist(strsplit(filename,"\\.")),1)
+    return(fextension)
+}
+
+#'supportedMuso
+#'
+#' A function for getting the list of the output formats which is supported by RBBGCMuso
+#' @author Roland Hollos
+#' @param type "outputs" or "message", if you choose "outputs", it gives you a simple vector of the formats, if you choose "message", it gives you a full sentence which contains the same information. 
+#' @return if you choose "outputs", it gives you a simple vector of the formats, if you choose "message", it gives you a full sentence which contains the same information.
+#' @usage supportedMuso(type="outputs")
+#' @export
+
+supportedMuso <- function(type="outputs"){
+    supportedFormats <- c("xls","xlsx","odt","csv","txt")
+    
+    if(type=="outputs"){
+        #If you add new format supports, please expand the lists
+        return(supportedFormats)
+    }
+    if(type=="message"){
+        return(cat("Supported formats are ",supportedFormats,"If your fileformat is something else, we automaticle coerced it to csv.\n"))
+    }
+}
+
+#' corrigMuso
+#'
+#' This function leapyear-corrigate the output of the modell
+#' @author Roland Hollos
+#' @param settings This is the output of the setupMuso() function. It contains all of the RBBGCMuso settings
+#' @param data the models outputdata
+#' @return It returns the modells leapyear-corrigated output data.
+#' @export
+#' @usage corrigMuso(settings, data)
+
+corrigMuso <- function(settings, data){
+
+    insertRow <- function(existingDF, newrow, r){
+        nr <- nrow(existingDF)
+        existingDF <- rbind(existingDF,rep(NA,ncol(existingDF)))
+        existingDF[seq(r+1,nr+1),] <- existingDF[seq(r,nr),]
+        existingDF[r,] <- newrow
+        existingDF
+    }
+
+
+    numdays <- nrow(data)
+    data <- data
+    numyears <- settings$numyears
+    leapyears <- musoLeapYears(settings)
+    sylvesters <- data[seq(from=365, to=numdays, by=365),]
+    ind <- 0
+    for(i in 1:numyears){
+        
+        if(leapyears[i]){
+            data <- insertRow(data,sylvesters[i],i*360+ind)
+            ind <- ind+1
+        }
+    }
+    return(data)
+}
+
+## #' file.path2
+## #'
+## #' It is an extended file.path function, it can concatenate path where the first ends and the second begins with "/", so
+## #' there wont be two  slash nearby eachother
+## #' @author Roland Hollos
+## #' @param str1 This is the first path string
+## #' @param str2 This is the second path string
+## #' @return A concatenated path
+## #' @export
+## #' @usage file.path2(str1, str2)
+
+## file.path2<-function(str1, str2){
+##     if(str1==""|str1=="./"){
+##         return(str2)
+##     }
+##     str1<-file.path(dirname(str1),basename(str1))
+##     if(substring(str2,1,1)=="/"){
+##         return(paste(str1,str2,sep=""))
+##     } else{
+##         return(file.path(str1,str2))
+##     }
+## } 
+
+numFactors <- function(x,type="pos"){
+    x <- as.integer(abs(x))
+    div <- seq_len(x)
+    posdiv <- div[x%%div==0L]
+    negdiv <- posdiv*-1
+    alldiv <- c(negdiv,posdiv)
+    switch(type,"pos"=return(posdiv),"neg"=return(negdiv),"all"=return(alldiv))
+}
+
+niceMatrixLayoutForPlots <- function(n){
+    if(n==0){
+        return(cat("Ther is nothing to do with 0 graph"))
+    }
+    n <- as.integer(n)
+    factors <- numFactors(n)
+    if(length(factors)==2){
+        return(n)}
+    sqrtn <- round(sqrt(n))
+    num1 <- factors[which(min(abs(factors-sqrtn))==abs(factors-sqrtn))[1]]
+    num2 <- n/num1
+    return(c(num1,num2))
+}
+
+truncNorm<-function(N,mean, sd, min, max){
+n=0
+randomNorm<-rep(NA,N)
+while(n<=N){
+  transNorm<-rnorm(1,mean,sd)
+  if((transNorm>min)&(transNorm<max)){
+    randomNorm[n]<-transNorm
+    n<-n+1
+  }
+}
+return(randomNorm)
+}
+
+#' getConstMatrix
+#'
+#' getConstMatrix is a function whith wich you can get the default constrain matrix for your choosen type and version. 
+#' @param filetype It can be "epc" or "soil".
+#' @param version The version of the MuSo environment
+#' @export 
+
+getConstMatrix <- function (filetype="epc", version = as.character(getOption("RMuso_version"))) {
+    getOption("RMuso_constMatrix")[[filetype]][[version]]
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/outputMapping.R

@@ -0,0 +1,89 @@
+#' updateMusoMapping
+#'
+#' This function updates the Biome-BGCMuSo output code-variable matrix (creates a json file that is used internally by RBBGCMuso). Within Biome-BGCMuSo the output state variablesare marked by integer numbers (see the User's Guide). In order to provide meaningful variable names (e.g. 3009 means Gross Primary Production) a conversion table is needed which is handled by this function. The input Excel file must have the following column order: name, index, units, description (plus other optional columns line group). name refers to the abbreviation of the variable; index is the integer number of the output variable; unit is the unit of the variable; description is a meaningful text to explain the variable. The script will NOT work with other column order!
+#' @author Roland HOLLOS
+#' @param excelName Name of the excelfile which contains the parameters 
+#' @importFrom openxlsx read.xlsx
+#' @importFrom jsonlite write_json
+#' @return The output code-variable matrix, and also the function changes the global variable
+#' @export
+
+updateMusoMapping <- function(excelName, dest="./", version=getOption("RMuso_version")){
+
+    expandRangeRows <- function (ind) {
+        toExpand <- excelDF[ind,]
+        rangeString <- gsub(".*?(\\d*\\-\\d*).*","\\1",toExpand[2])
+        interval <- as.numeric(strsplit(rangeString,split="-")[[1]])
+        result <- do.call(rbind,lapply(interval[1]:interval[2],function(x){
+            toExpand[2] <- x
+            toExpand[1] <- gsub("\\[.*?\\]",sprintf("_%s",(x-interval[1])),toExpand[1])
+            toExpand
+        }))
+        result <- as.data.frame(result,stringsAsFactors = FALSE)
+        result[,2] <- as.numeric(result[,2])
+        colnames(result) <- c("names","codes","units","descriptions")
+        result[,c(2,1,3,4)]
+    }
+
+    excelDF <- read.xlsx(excelName)
+    excelDF <- excelDF[!is.na(excelDF[,2]),]
+    excelDF[,1] <- trimws(excelDF[,1])
+    excelDF[,2] <- trimws(excelDF[,2])
+    excelDF[,3] <- trimws(excelDF[,3])
+    excelDF[,4] <- trimws(excelDF[,4])
+    rangeRows <- grep("-",excelDF[,2])
+    nonRangeMatrix <- excelDF[setdiff(1:nrow(excelDF),rangeRows),]
+    nonRangeMatrix[,2] <- as.numeric(nonRangeMatrix[,2])
+    nonRangeMatrix[,1] <- trimws(nonRangeMatrix[,1])
+    names(nonRangeMatrix) <- c("names","codes","units","descriptions")
+    outMatrix <- rbind.data.frame(do.call(rbind.data.frame,lapply(rangeRows,expandRangeRows)),
+                                  nonRangeMatrix[,c(2,1,3,4)])
+    outMatrix <- outMatrix[order(outMatrix[,1]),]
+    rownames(outMatrix)<- NULL
+    write_json(outMatrix, file.path(dest,sprintf("varTable%s.json",version)), pretty=TRUE)
+}
+
+#' musoMapping
+#'
+#' musoMapping can provide the user the name of a Biome-BGCMuSo output code. Within Biome-BGCMuSo the state variables and fluxes are marked by integer numbers. In order to provide meaningful variable names (e.g. 3009 means Gross Primary Production) a conversion table is needed which is utilized by this function. This function converts variable codes into names musoMappingFind does the opposite.
+#' @author Roland HOLLOS
+#' @param code the MuSo outputcode
+#' @param mapData updateMusomapping generated matrix
+#' @return The name of the Biome-BGCMuSo output code (e.g. if code is 3009 this function should return GPP to the user)
+#' @export
+#' @usage musoMapping(code, mapData=NULL)
+
+
+musoMapping <- function(code,
+                        mapData=getOption("RMuso_varTable")[[as.character(getOption("RMuso_version"))]]){
+    if(is.null(mapData)){
+        return(unlist(tryCatch(mMapping[which(mMapping[,1]==code),2],error = function(e){
+                                   
+        stop(sprintf("The code %s in inifile is not valid muso output variable code",code))                                   
+                                   
+}))) #mMapping is package-scoped system variable generated by udateMusoMapping
+    } else {
+        return(unlist(mapData[which(mapData[,1]==code),2]))
+    }
+}
+
+
+#' musoMappingFind
+#'
+#' musoMappingFind can provide us the code of the Biome-BGCMuSo output variable name. Within Biome-BGCMuSo the state variables and fluxes are marked by integer numbers. In order to provide meaningful variable names (e.g. 3009 means Gross Primary Production) a conversion table is needed which is utilized by this function. This function converts variable names into codes. musoMapping does the opposite.
+#' @author Roland HOLLOS
+#' @param variable If this is null, return the whole mapping table. In other cases search for the variable code
+#' @return The code of the specific output variable name
+#' @export
+#' @usage musoMapping(code, mapData=NULL)
+
+
+musoMappingFind <- function(variable=NULL,
+                            mMapping=getOption("RMuso_varTable")[[as.character(getOption("RMuso_version"))]]){
+    if(is.null(variable)){
+        return(mMapping)
+    } else {
+                            mMapping[grep(variable,mMapping[,2]),]
+                    }
+}
+

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/parametersweep.R

@@ -0,0 +1,78 @@
+#' paramSweep
+#' 
+#' This function is for testing the modell response to change a set of input variables. It generates an html file which contains a set of graphics of the ...
+#' @author Roland Hollos
+#' @param inputDir  The directory which contains the MuSo model's ini files
+#' @param parameters  A csv file's path which contains the input parameters. The first row must be the name of the parameters, the second is the index of the parameters(row index in the input file), the third is the minimum value of the parameters, the forth is the maximum value of the parameters. If it is not privided, a filebrowser will pop up.
+#' @param outputDir The path of the directory where the html file will be generated. 
+#' @param iterations The number of changes in the parameter
+#' @param outVar The name of the output variable to plot, of the MuSo code of it.
+#' @param htmlOutName The name of the rendered html file 
+#' @importFrom rmarkdown render pandoc_version
+#' @importFrom digest digest
+#' @importFrom tcltk tk_choose.files 
+#' @export
+
+paramSweep <- function(inputDir="./",
+                       parameters=NULL,
+                       outputDir=NULL,
+                       iterations=10,
+                       outVar="daily_gpp",
+                       htmlOutName = "paramsweep.html"){
+    
+    if(is.null(pandoc_version())){
+        stop("In order to use parameterSweep you have to have\n pandoc (1.12.3+) installed or run this function from Rstudio\n
+You can download pandoc from here: 'https://pandoc.org/',\n or Rstudio from here: 'https://www.rstudio.com/'")
+    }
+    currDir <- getwd()
+    opSystem <- Sys.info()[[1]]
+    if(is.character(outVar)){
+        varNames <- as.data.frame(musoMappingFind(outVar))
+        if(nrow(varNames)!=1){
+            warning("There are more than one output variable in conection with ", outVar, ". The first possibility were choosen.")
+            print(varNames)
+            outVarIndex <- unlist(varNames[1,1])
+            varNames <- as.character(unlist(varNames[1,2]))
+        } else {
+            outVarIndex <- unlist(varNames[1,1])
+            varNames <- as.character(unlist(varNames[1,2]))
+        }
+    } else {
+        varNames <- musoMapping(outVar)
+        outVarIndex<-outVar
+    }
+    
+    
+    if(is.null(parameters)){
+        parameters <- tcltk::tk_choose.files(caption = "Please select a file with the parameters and the ranges")
+    }
+    
+    rmdFile <- "---\ntitle: \"ParameterSweep basic\"\n---\n```{r setup, include=FALSE}\nknitr::opts_chunk$set(echo = TRUE)\n```\n```{r, echo=FALSE}\nsuppressWarnings(library(RBBGCMuso))\n```\n```{r, echo=FALSE}\nparameters <- read.csv(\"parameters.csv\")\n```\n```{r,fig.width=10, fig.height=3, echo=FALSE}\nnumPar\nfor(i in 1:numPar){\n  suppressWarnings(musoQuickEffect(calibrationPar=parameters[i,2],startVal = parameters[i,3], endVal = parameters[i,4],\nnSteps = 9,\noutVar = \"daily_gpp\",\nparName = parameters[i,1]))\n}\n```"
+    rmdVec <- unlist(strsplit(rmdFile,"\n"))
+    rmdVec[11] <- paste0("parameters <- read.csv(\"",parameters,"\", stringsAsFactor = FALSE)")
+    rmdVec[14] <- "numPar <- nrow(parameters)"
+    rmdVec[17] <- paste0("nSteps = ", iterations - 1,",")
+    rmdVec[18] <- paste0("outVar = \"",varNames,"\",")
+
+    if(!is.null(outputDir)){
+        setwd(outputDir)
+    }
+    
+    randName <- paste0(digest(date(),"md5"),"-paramsweep.rmd")
+    writeLines(rmdVec,randName)
+    render(randName,output_file = htmlOutName)
+    unlink(randName)
+
+    if(opSystem == "Linux"){
+        system(paste0("xdg-open ",htmlOutName))
+    } else {
+        if(opSystem == "Windows"){
+            shell(paste0("start ",htmlOutName))
+        } else {
+            system(paste0("open ",htmlOutName))
+        }
+    }
+    setwd(currDir)
+    
+}
+

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/plotMuso.R

@@ -0,0 +1,389 @@
+#'plot the Biome-BGCMuSo output 
+#'
+#' This function runs the Biome-BGCMuSo model and reads its output file in a well structured way, and after that it plots the results automatically. plotMuso is a convenient and quick method to create nice graphs from Biome-BGCMuSo output which is quite painful in other environments. 
+#' 
+#' @author Roland HOLLOS, Dora HIDY
+#' @param settings RBBGCMuso uses variables that define the entire simulation environment. Those environment variables include the name of the INI files, the name of the meteorology files, the path to the model executable and its file name, the entire output list, the entire output variable matrix, the dependency rules for the EPC parameters etc. Using the runMuso function RBBGCMuso can automatically create those environment variables by inspecting the files in the working directory (this happens through the setupMuso function). It means that by default model setup is performed automatically in the background and the user has nothing to do. With this settings parameter we can force runMuso to skip automatic environment setup as we provide the environment settings to runMuso. In a typical situation the user can skip this option.
+#' @param timee The required timesteps in the model output. It can be "d", if it is daily, "m", if it is monthly, "y" if it is yearly. It is recommended to use daily data, as the yearly and monthly data is not well-tested yet.
+#' @param debugging If debugging is set to TRUE, after model execution the function copies the Biome-BGCMuSo log file into a LOG directory and stores it for further processing. If debugging is set to STAMPLOG instead of TRUE, it concatenates a number before the logfile, which is one plus the maximum of those present in the LOG directory. In each case the log files will be saved. 
+#' @param keepEpc If keepEpc is set to TRUE, the function keeps the EPC file and stamps it, and then copies it to the EPCS directory. If debugging is set to TRUE, it copies the wrong EPC files to the wrong epc directory.
+#' @param export If it is set to YES or you define a filename here, the function converts the output to the specific file format. For example, if you set export to "example.csv", it converts the output to "csv". If you set it to "example.xls" it converts the output to example.xls with the xlsx package. If the Excel converter package is not installed it gives back a warning message and converts the results to csv.
+#' @param silent If you set the silent parameter to TRUE, all of the model's output normally written to the screen will be suppressed. This option can be useful to increase the speed of the model execution.
+#' @param aggressive It deletes all previous model-outputs from previous model runs.
+#' @param variable Column number of the output variable which should be plotted, or "all" if you have less than 10 variables. In this case the function will plot everything in a matrix layout. 
+#' @param leapYear Should the function do a leapyear correction on the output data? If TRUE, then the result for 31 December will be doubled in leap years which means that the results for the leap year will cover all 366 days. See the model's User's Guide for notes on leap years. 
+#' @param logfilename If you would like to set a specific name for your logfiles you can set this via the logfile parameter.
+#' @param plotType There are two options implemented by now: continuous time series ("cts") or disctrete time series ("dts")
+#' @param skipSpinup If TRUE, the function won't perform the spinup simulation. In this case the endpoint file must exist that provides initial conditions for the run. 
+#' @return It depends on the export parameter. The function returns with a matrix with the model output, or writes this into a file, which is defined previously
+#' @usage plotMuso(settings, variable,
+#' timee="d", silent=TRUE,
+#' debugging=FALSE, keepEpc=FALSE,
+#' logfilename=NULL, aggressive=FALSE,
+#' leapYear=FALSE, export=FALSE)
+#' @importFrom ggplot2 ggplot aes_string geom_line geom_point aes labs theme ggsave element_blank facet_wrap
+#' @importFrom dplyr filter group_by summarize mutate '%>%'
+#' @importFrom tibble rownames_to_column
+#' @importFrom tidyr separate gather
+#' @importFrom data.table ':=' data.table
+#' @export
+
+plotMuso <- function(settings = NULL, variable = "all",
+                     ##compare, ##plotname,
+                     timee = "d", silent = TRUE,
+                     calibrationPar = NULL, parameters = NULL,
+                     debugging = FALSE, keepEpc = FALSE,
+                     fileToChange = "epc", logfilename = NULL,
+                     aggressive = FALSE, leapYear = FALSE,
+                     plotName = NULL, plotType = "cts",
+                     layerPlot = FALSE, colour = "blue",
+                     skipSpinup = TRUE, fromData = FALSE,
+                    timeFrame = "day", selectYear = NULL,
+                    groupFun = mean, separateFile = FALSE, dpi=300, postProcString = NULL){
+
+    if( plotType!="cts" && plotType != "dts"){
+        warning(paste0("The plotType ", plotType," is not implemented, plotType is set to cts"))
+        plotType <- "cts"
+    }
+    
+    if(is.null(settings)){
+        settings <- setupMuso()
+    }
+    
+    numberOfYears <- settings$numYears
+    startYear <- settings$startYear
+    dailyVarCodes <- settings$dailyVarCodes
+    groupByTimeFrame <- function(Data, timeFrame, groupFun){
+        Data <- data.table(Data)
+        Data[,c(variable):=groupFun(get(variable)),get(timeFrame)]
+        Data <- as.data.frame(Data) 
+        Data[,1] <- as.Date(Data[,1],"%d.%m.%Y")
+        Data
+    }
+    
+    if(fromData){
+        Reva <- tryCatch(getdailyout(settings), #(:INSIDE: getOutput.R )
+                                    error = function (e){
+                                        setwd((whereAmI))
+                                        stop("Cannot read binary output, please check if the output type is set 2 in the ini files!")})
+        colnames(Reva) <- unlist(settings$outputVars[[1]])
+        rownames(Reva) <- NULL
+        musoData <- cbind(musoDate(startYear = startYear,numYears = numberOfYears,combined = TRUE,corrigated=FALSE),
+              rep(1:365,numberOfYears),
+              musoDate(startYear = startYear,numYears = numberOfYears,combined = FALSE,corrigated=FALSE),as.data.frame(Reva))
+        colnames(musoData)[1:5]<-c("date","yearDay","year","day","month")
+        musoData <-musoData %>%
+            mutate(date=as.Date(as.character(date),"%d.%m.%Y"))
+    } else {
+        if(!is.element("cum_yieldC_HRV",unlist(settings$outputVars[[1]]))){
+            musoData <- calibMuso(postProcString = postProcString,settings,
+                                  calibrationPar=calibrationPar,
+                                  parameters = parameters,
+                                  silent = TRUE,skipSpinup=skipSpinup,prettyOut = TRUE)
+            if(!is.null(selectYear)){
+            musoData <- musoData %>% filter(year == get("selectYear"))    
+            }
+            
+            if(timeFrame!="day"){
+                musoData <- tryCatch(groupByTimeFrame(Data=musoData, timeFrame = timeFrame, groupFun = groupFun),
+                                     error=function(e){stop("The timeFrame or the groupFun is not found")})
+            }} else {
+                 musoData <- calibMuso(postProcString = postProcString,settings,silent = TRUE,skipSpinup=skipSpinup,parameters = parameters, calibrationPar = calibrationPar,fileToChange = fileToChange) %>%
+                     as.data.frame() %>%
+                     rownames_to_column("date") %>%
+                     mutate(date2=date,date=as.Date(date,"%d.%m.%Y"),
+                            yearDay=rep(1:365,numberOfYears), cum_yieldC_HRV=cum_yieldC_HRV*22.22) %>%
+                     separate(date2,c("day","month","year"),sep="\\.")
+                 if(!is.null(selectYear)){
+                     musoData <- musoData %>% filter(year == get("selectYear"))    
+                 }
+                 
+                 
+                 if(timeFrame!="day"){
+                     musoData <- tryCatch(groupByTimeFrame(data=musoData, timeFrame = timeFrame, groupFun = groupFun),
+                                          error=function(e){stop("The timeframe or the gropFun is not found")})
+                 }
+                 
+             }
+    }
+
+    ## numVari <- ncol(musoData)
+     # numVari <- ncol(musoData)-5
+     numVari <- length(settings$dailyVarCodes)
+
+    pointOrLineOrPlot <- function(musoData, variableName, plotType="cts", expandPlot=FALSE, plotName=NULL){
+        if(!inherits(musoData$date[1], "Date")){
+            musoData$date<- as.Date(as.character(musoData$date),"%d.%m.%Y")
+        }
+        if(!expandPlot){
+            if(plotType=="cts"){
+                if(length(variableName)==1){
+                   p <- ggplot(musoData,aes_string("date",variableName,group=1))+geom_line(colour=colour)+theme(axis.title.x=element_blank())
+                   if(!is.null(plotName)){
+                       ggsave(as.character(plotName), plot = p)
+                    p
+                   }
+                   p
+                } else {
+                    p <- musoData %>%
+                        select(c("date", variableName))%>%
+                        gather(., key= outputs, value = bla, variableName) %>%
+                                        # head  %>%
+                        ggplot(aes(x=date,y=bla))+
+                        facet_wrap(~ outputs, scales = "free_y",ncol=1) +
+                        geom_line(colour=colour)+
+                        theme(
+                            axis.title.y = element_blank()
+                        )
+                    if(!is.null(plotName)){
+                        ggsave(as.character(plotName), plot = p)
+                    }
+                    p
+                }
+            } else {
+                if(length(variableName)==1){
+                    p <- ggplot(musoData,aes_string("date",variableName))+geom_point(colour=colour)+theme(axis.title.x=element_blank())
+                    if(!is.null(plotName)){
+                        ggsave(as.character(plotName),p)
+                    }
+                    p
+                } else{
+                        p <- musoData %>%
+                            select(c("date",variableName))%>%
+                            gather(., key= outputs, value = bla,variableName) %>%
+                                        # head  %>%
+                            ggplot(aes(x=date,y=bla))+
+                            facet_wrap(~ outputs, scales = "free_y",ncol=1) +
+                            geom_line(colour=colour)+
+                            theme(
+                                axis.title.y = element_blank()
+                            )
+                        if(!is.null(plotName)){
+                            ggsave(as.character(plotName),p)
+                        }
+                        p
+                    
+                }
+            }
+        } else {
+            if(!is.null(plotName)){
+                stop("Cannot save a single plot layer to a graphics device")
+            }
+            
+            if(plotType=="cts"){
+                if(length(variableName)==1){
+                    geom_line(data=musoData, colour=colour, aes_string("date",variableName))
+                    
+                } else {
+                    stop("you cannot add layers for multiple plots")
+                }
+            } else {
+                if(length(variableName)==1){
+                    geom_point(data=musoData, colour=colour, aes_string("date",variableName))
+                } else{
+                    stop("you cannot add layers for multiple plots")
+                }
+            }
+            
+        }
+        
+    }
+    
+
+    variableName <-  as.character(settings$outputVars[[1]])[variable]
+    if(variable == "all"){
+        variableName <-  as.character(settings$outputVars[[1]])
+    }
+    if(is.character(variable)){
+
+
+        if(identical(variable,"all")){
+            variable <- as.character(settings$outputVars[[1]])
+            
+        } else {
+
+            if(is.element(variable, settings$dailyVarCodes)){
+                variable <- settings$outputVars[[1]][match(variable,settings$dailyVarCodes)]
+            }
+
+            if(identical(character(0),setdiff(variable,as.character(settings$outputVars[[1]])))){
+                variableName <- variable
+            } else {
+                if(!is.null(postProcString)){
+                 variableName <- variable     
+                } else {
+                    stop("The symmetric difference of the set of the output variables specified in the ini files and the set specified with your variable parameter is not the empty set.")                    
+                }
+
+            }   
+        }
+        
+        if(length(variableName)>8){
+            warning("Too many variables to plot, the output quality can be poor")
+        }
+        
+     } else {
+         
+         if(prod(sapply(variable,function(x){
+             return(x >= 0 && x <= numVari)
+         }))){
+             variableName <-  as.character(settings$outputVars[[1]])[variable]
+         } else {
+             print(numVari)
+             stop("Not all members of the variable parameter are among the output variables")
+         }}
+     
+    pointOrLineOrPlot(musoData = musoData,
+                      variableName = variableName,
+                      plotType = plotType,
+                      expandPlot = layerPlot,
+                      plotName = plotName)
+     }
+
+#'plot the Biome-BGCMuSo model output with observation data 
+#'
+#' This function runs the Biome-BGCMuSo model and reads its output file in a well structured way, and after that it plots the results automatically along with a given measurement dataset provided by the user. plotMusoWithData is a convenient and quick method to create nice graphs from Biome-BGCMuSo output which is quite painful in other environments.  
+#' 
+#' @author Roland HOLLOS, Dora HIDY
+#' @param settings RBBGCMuso uses variables that define the entire simulation environment. Those environment variables include the name of the INI files, the name of the meteorology files, the path to the model executable and its file name, the entire output list, the entire output variable matrix, the dependency rules for the EPC parameters etc. Using the runMuso function RBBGCMuso can automatically create those environment variables by inspecting the files in the working directory (this happens through the setupMuso function). It means that by default model setup is performed automatically in the background and the user has nothing to do. With this settings parameter we can force runMuso to skip automatic environment setup as we provide the environment settings to runMuso. In a typical situation the user can skip this option.
+#' @param sep This is the separator symbol used in the measurement file (that is supposed to be a delimited text file)
+#' @param savePlot It it is specified, the plot will be saved in a graphical format specified by the immanent extension. For example, it the savePlot is set to image01.png then a PNG graphics file will be created. 
+#' @param variable The name of the output variable to plot
+#' @param NACHAR This is not implemented yet
+#' @param csvFile This specifies the filename of the measurements. It must contain a header. Typically this is a CSV file.
+#' @param calibrationPar You might want to change some parameters in your EPC file before running the model. The function offers possibility for this without editing the EPC file. In this situation you have to select the appropirate model parameters first. You can refer to these parameters with the number of the line in the EPC file. Indexing of lines start from one. You should use a vector for this referencing like c(1,5,8)
+#' @param parameters Using the function it is possible to change some of the EPC parameters prior to model execution. This can be achieved with this option. In the parameters variable you have set the row indices of the variables that you wish to change. In this parameters you can give an exact value for them in a vector form like c(1,2,3,4).
+#' @usage plotMuso(settings, variable,
+#' timee="d", silent=TRUE,
+#' debugging=FALSE, keepEpc=FALSE,
+#' logfilename=NULL, aggressive=FALSE,
+#' leapYear=FALSE, export=FALSE)
+#' @importFrom ggplot2 ggplot geom_line geom_point aes aes_string labs theme element_blank 
+#' @export
+plotMusoWithData <- function(mdata, plotName=NULL,
+                             startDate = NULL, endDate = NULL,
+                             colour=c("black","blue"), dataVar, modelVar, settings = setupMuso(), silent = TRUE, continious = FALSE, leapYearHandling = FALSE){
+
+    if(continious  & (is.null(startDate) | is.null(endDate))){
+        stop("If your date is continuous, you have to provide both startDate and endDate. ")
+    }
+
+    dataCol<- grep(paste0("^",dataVar,"$"), colnames(mdata))
+    selVar <- grep(modelVar,(settings$dailyVarCodes))+4
+
+    list2env(alignData(mdata, dataCol = dataCol,
+                       modellSettings = settings,
+                       startDate = startDate,
+                       endDate = endDate, leapYear = leapYearHandling, continious = continious),envir=environment())
+    mesData <- numeric(settings$numYears*365)
+    k <- 1
+    for(i in seq(mesData)){
+        if(i %in% modIndex){
+            mesData[i] <- measuredData[k]
+            k <- k + 1
+        } else {
+            mesData[i] <- NA
+        }
+    }
+    rm(k)
+    # modIndex and measuredData are created.
+    ## measuredData is created
+    ## baseData <- calibMuso(settings = settings, silent = silent, prettyOut = TRUE)[modIndex,]
+    baseData <- calibMuso(settings = settings, silent = silent, prettyOut = TRUE)
+    baseData[,1] <- as.Date(baseData[,1],format = "%d.%m.%Y")
+    selVarName <- colnames(baseData)[selVar]
+    if(!all.equal(colnames(baseData),unique(colnames(baseData)))){
+        notUnique <- setdiff((unlist(settings$dailyVarCodes)),unique(unlist(settings$dailyVarCodes)))
+        stop(paste0("Error: daily output variable list in the ini file must contain unique numbers. Check your ini files! Not unique codes: ",notUnique))
+    }
+    mesData<-cbind.data.frame(baseData[,1],mesData)
+    colnames(mesData) <- c("date", "measured")
+    p <- baseData  %>%
+        ggplot(aes_string("date",selVarName)) +
+        geom_line(colour=colour[1]) +
+        geom_point(data = mesData, colour=colour[2], aes(date,measured)) +
+        labs(y = paste0(selVarName,"_measured"))+
+        theme(axis.title.x = element_blank())
+    if(!is.null(plotName)){ 
+        ggsave(plotName,p)
+        return(p)
+    } else {
+        return(p)
+    }
+    
+}
+
+#' compareMuso 
+#'
+#' This function runs the model, then changes one of its input data, runs it again, and plots both results in one graph. 
+#' 
+#' @author Roland HOLLOS
+#' @param settings RBBGCMuso uses variables that define the entire simulation environment. Those environment variables include the name of the INI files, the name of the meteorology files, the path to the model executable and its file name, the entire output list, the entire output variable matrix, the dependency rules for the EPC parameters etc. Using the runMuso function RBBGCMuso can automatically create those environment variables by inspecting the files in the working directory (this happens through the setupMuso function). It means that by default model setup is performed automatically in the background and the user has nothing to do. With this settings parameter we can force runMuso to skip automatic environment setup as we provide the environment settings to runMuso. In a typical situation the user can skip this option.
+#' @param parameters Using this function it is possible to change some of the EPC parameters prior to model execution. This can be achieved with this option. In the parameters variable you have set the row indices of the variables that you wish to change. In this parameters you can give an exact value for them in a vector form like c(1,2,3,4).
+#' @param variable The name of the output variable to plot
+#' @param calibrationPar You might want to change some parameters in your EPC file before running the model. This function offers possibility for this without editing the EPC file. In this situation you have to select the appropirate model parameters first. You can refer to these parameters with the number of the line in the EPC file. Indexing of lines start from one. You should use a vector for this referencing like c(1,5,8)
+#' @param fileToChange You can change any line of the EPC or the INI file. Please choose "EPC", "INI" or "BOTH". This file will be used for the analysis, and the original parameter values will be changed according to the choice of the user. 
+#' @import ggplot2
+#' @export
+compareMuso <- function(settings=NULL,parameters, variable=1, calibrationPar=NULL, fileToChange="epc", skipSpinup=TRUE, timeFrame="day"){
+
+    if(is.null(settings)){
+        settings <- setupMuso()
+    }
+    
+
+    p1 <- plotMuso(settings = settings,variable = variable,timeFrame = timeFrame)
+    p2 <- p1+plotMuso(settings = settings,variable = variable, timeFrame = timeFrame,fileToChange=fileToChange,layerPlot=TRUE)
+    p2
+    
+}
+
+#' saveAllMusoPlots 
+#'
+#' This simple function takes the parameters from the ini files and generates graphics for all output variable. 
+#' 
+#' @author Roland HOLLOS
+#' @param settings RBBGCMuso uses variables that define the entire simulation environment. Those environment variables include the name of the INI files, the name of the meteorology files, the path to the model executable and its file name, the entire output list, the entire output variable matrix, the dependency rules for the EPC parameters etc. Using the runMuso function RBBGCMuso can automatically create those environment variables by inspecting the files in the working directory (this happens through the setupMuso function). It means that by default model setup is performed automatically in the background and the user has nothing to do. With this settings parameter we can force runMuso to skip automatic environment setup as we provide the environment settings to runMuso. In a typical situation the user can skip this option.
+#' @param plotName The basename for the output plots
+#' @param destination The destination for the output plots, it not exits the  function will create it.
+#' @param silent if true do not suspect for printfs... 
+#' @importFrom ggplot2 theme_classic ggplot geom_line geom_point theme element_blank geom_bar labs aes_string aes ggsave 
+#' @export
+
+
+saveAllMusoPlots <- function(settings=NULL, plotName = ".png",
+                             silent = TRUE, type = "line", outFile = "annual.csv",
+                             colour = "blue", skipSpinup = FALSE){
+
+    if(is.null(settings)){
+        settings <- setupMuso()
+    }
+
+    dailyVarCodes <- settings$dailyVarCodes
+    annualVarCodes <-settings$annualVarCodes
+    outputVars <- unlist(settings$outputVars[[1]])
+    musoData <- calibMuso(settings = settings, prettyOut = TRUE, silent = silent, skipSpinup = skipSpinup)
+    musoData$date<- as.Date(musoData$date,"%d.%m.%Y")
+    for(i in seq_along(dailyVarCodes)){
+        bases <- ggplot(data = musoData, mapping = aes_string(x = "date", y = outputVars[i]))
+        object <-ifelse(type == "line",paste0("geom_line(colour = '",colour,"')"),
+                                  ifelse(type == "point",paste0("geom_line(colour = ",colour,")"),
+                                         stop("The")))
+        outPlot <- bases + eval(parse(text = object)) + theme_classic() + theme(axis.title.x=element_blank())
+        imName <- paste0("daily-",dailyVarCodes[i],plotName)
+        cat(sprintf("Saving daily output image of %s as %s\n",outputVars[i],imName))
+        suppressMessages(ggsave(imName, outPlot))
+    }
+    if(settings$normOutputFlags["annual"]!=2){
+        return("Annual output graphs was not saved (no annual output from the model)")
+    }
+    musoYData <- getyearlyout(settings)
+    write.csv(musoYData,paste0(settings$outputNames[[2]],outFile))
+     for(i in seq_along(annualVarCodes)){
+        outPlot <- ggplot(data = musoYData, mapping = aes_string(x = "year", y = paste0("var_",annualVarCodes[i])))+
+            geom_bar(stat = "identity")+ labs(y = musoMapping(annualVarCodes[i])) + theme_classic() +
+            theme(axis.title.x=element_blank())
+        ggsave(paste0("annual-",annualVarCodes[i],plotName),outPlot)
+     }   
+    
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/postProc.R

@@ -0,0 +1,10 @@
+postProcMuso  <- function(modelData, procString){
+    cNames <- colnames(modelData)
+    tocalc <- gsub("(@)(\\d)","modelData[,\\2]",procString)
+    newVarName <- gsub("\\s","",unlist(strsplit(procString,"<-"))[1])
+    assign(newVarName,eval(parse(text = unlist(strsplit(tocalc,"<-"))[2])))
+    modelData <- cbind.data.frame(modelData,eval(parse(text = newVarName)))
+    colnames(modelData) <- c(cNames,newVarName)
+    modelData
+}
+

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/postProcString.R

@@ -0,0 +1,15 @@
+#' postProcMuso
+#' 
+#' This is a function wich provides some minimal post processing capabilities
+#' @keywords internal
+postProcMuso  <- function(modelData, procString){
+    modelDat <- modelData[,-(1:4)]
+    cNames <- colnames(modelData)
+    tocalc <- gsub("(@)(\\d)","modelDat[,\\2]",procString)
+    newVarName <- gsub("\\s","",unlist(strsplit(procString,"<-"))[1])
+    assign(newVarName,eval(parse(text = unlist(strsplit(tocalc,"<-"))[2])))
+    modelData <- cbind.data.frame(modelData,eval(parse(text = newVarName)))
+    colnames(modelData) <- c(cNames,newVarName)
+    modelData
+}
+

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/putOutVars.R

@@ -0,0 +1,32 @@
+#' putOutVars
+#'
+#'This function is for adding variables in the inifiles.
+#'
+#' @author Roland Hollos
+#' @param IniFile The name of the normal ini file.
+#' @param outputVars List of the output codes
+#' @keywords internal 
+putOutVars <- function(iniFile,outputVars,modifyOriginal = FALSE){
+    ini <- readLines(iniFile)
+    numVarsOriginal <- as.numeric(unlist(strsplit(ini[grep("DAILY_OUTPUT",ini)+1],"[\ \t]"))[1])
+    if(!modifyOriginal){
+        iniOut <- paste0(tools::file_path_sans_ext(basename(iniFile)),"-tmp.",tools::file_ext(iniFile))
+    } else {
+        iniOut <- iniFile
+    }
+    
+    outNames <- sapply(outputVars,musoMapping)
+    partOne <- ini[1:grep("DAILY_OUTPUT",ini)]
+    partTwo <- ini[grep("ANNUAL_OUTPUT",ini):(length(ini))]
+    numVars <- length(outputVars)
+    fileContent <- c(partOne,
+                     as.character(numVars),
+                     sapply(outputVars,function (x) {
+                         paste(as.character(x),musoMapping(x),sep = " ")
+                     }),
+                     "",
+                     partTwo)
+    writeLines(fileContent,iniOut)
+    return(list(names=outNames,ratio=numVars/numVarsOriginal))
+}
+

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/quickeffect.R

@@ -0,0 +1,86 @@
+#' musoQuickEffect
+#'
+#' This function changes a chosen parameter from the INI or from the ecophysiological constants file (EPC) within a predefined range (defined by the user), and visualizes the effect of the change on the selected output variable. The user has to specify the parameter, the interval for the parameter effect test, and the number of steps. This function focuses only on one parameter. The so-called paramSweep function can manipulate multiple INI/EPC parameters and visualize the results. 
+#' @author Roland HOLLOS
+#' @param settings RBBGCMuso uses variables that define the entire simulation environment. Those environment variables include the name of the INI files, the name of the meteorology files, the path to the model executable and its file name, the entire output list, the entire output variable matrix, the dependency rules for the EPC parameters etc. Using the runMuso function RBBGCMuso can automatically create those environment variables by inspecting the files in the working directory (this happens through the setupMuso function). It means that by default model setup is performed automatically in the background and the user has nothing to do. With this settings parameter we can force runMuso to skip automatic environment setup as we provide the environment settings to runMuso. In a typical situation the user can skip this option.
+#' @param startVal The initial value of the given parameter. 
+#' @param endVal The maximum of the given parameter. 
+#' @param nSteps Number of steps from startVal to endVal. It equals the number of simulations, and number of curves on the final plot. 
+#' @param fileTochange Please choose "EPC", "INI" or "BOTH". This file will be used for the analysis, and the original parameter values will be changed according to the choice of the user. 
+#' @return Graph showing the runs with the selected parameters with color coding. The graph will show data from the last simulation year. 
+#' @importFrom ggplot2 ggplot aes_string geom_line geom_point aes labs theme ggsave element_blank facet_wrap
+#' @importFrom dplyr filter group_by summarize mutate '%>%' tbl_df select
+#' @importFrom tibble rownames_to_column
+#' @importFrom magrittr '%<>%'
+#' @importFrom tidyr separate
+#' @export
+
+musoQuickEffect <- function(settings = setupMuso(), calibrationPar = NULL,  startVal, endVal, nSteps = 1, fileToChange="epc",modifyOriginal=TRUE, outVar, parName = "parVal", yearNum=1, year=(settings$startYear + yearNum -1)){
+
+    if(is.character(outVar)){
+                      varNames <- as.data.frame(musoMappingFind(outVar))
+                      if(nrow(varNames)!=1){
+                          warning("There are more than one output variable in conection with ", outVar, ". The first possibility were choosen.")
+                          print(varNames)
+                          outVarIndex <- unlist(varNames[1,1])
+                          varNames <- as.character(unlist(varNames[1,2]))
+                      } else {
+                          outVarIndex <- unlist(varNames[1,1])
+                          varNames <- as.character(unlist(varNames[1,2]))
+                      }
+                  } else {
+                      varNames <- musoMapping(outVar)
+                      outVarIndex<-outVar
+                  }
+    
+     if(is.null(calibrationPar)){
+         calibrationPar <- settings$calibrationPar
+     }
+    
+    parVals <- seq(startVal, endVal, length = (nSteps + 1))
+    parVals <- dynRound(startVal, endVal, seqLen = (nSteps + 1))
+    a <- do.call(rbind,lapply(parVals, function(parVal){
+        calResult <- tryCatch(calibMuso(settings = settings,calibrationPar = calibrationPar,
+                                        modifyOriginal = modifyOriginal,
+                                        parameters = parVal,
+                                        outVars = outVarIndex,
+                                        silent = TRUE,
+                                        fileToChange = fileToChange), error = function(e){NULL})
+        if(is.null(calResult)){
+            b <- cbind(rep(NA,365),parVal)
+            rownames(b) <- musoDate(startYear = year, numYears = 1)
+            colnames(b)[1] <- varNames
+            return(b)
+        } else {
+            if(yearNum >=0){
+                m <- as.data.frame(calResult[musoDate(startYear = year, numYears = 1),])
+            } else{
+                m <- as.data.frame(calResult)
+            }
+            colnames(m) <- colnames(calResult)
+            return(cbind(m, parVal))
+        }
+        
+    }))
+    a %<>%
+        tbl_df %>%
+        mutate(date=as.Date(rownames(a),"%d.%m.%Y")) %>%
+        select(date,as.character(varNames),parVal)
+    print(suppressWarnings(ggplot(data = a, aes_string(x= "date", y= varNames))+geom_line(aes(alpha = factor(parVal))) + labs(y=varNames, alpha = parName) + scale_alpha_discrete(range=c(0.25,1))))
+}
+# calma <- calibMuso(settings = settings,calibrationPar = calibrationPar,
+#                                          modifyOriginal = modifyOriginal,
+#                                          parameters = parVal,
+#                                          outVars = outVarIndex,
+#                                          silent = TRUE,
+#                                          fileToChange = fileToChange)
+#  plot(calma[,1])
+# calma <- calibMuso(settings = settings,calibrationPar = calibrationPar,
+#                                          modifyOriginal = modifyOriginal,
+#                                          parameters = parVal,
+#                                          silent = TRUE,
+#                                          fileToChange = fileToChange)
+# calm <- calibMuso(calibrationPar=calibrationPar,parameters=parVal,modifyOriginal=TRUE)
+# plot(x=as.Date(musoDate(2015,numYears=1),"%d.%m.%Y"),y=calm[musoDate(2015,numYears=1),"daily_gpp"],type="l")
+# calibrationPar
+# parVal

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/runMuso.R

@@ -0,0 +1,28 @@
+#' runMuso 
+#'
+#' This function runs the Biome-BGCMuSo model (with option to change the EPC file), then it reads its output file in a well-structured way. As the result is passed to R, the results can be easily post-processed in R environment. 
+#' 
+#' @author Roland HOLL\'{O}S
+#' @param settings RBBGCMuso uses variables that define the entire simulation environment. Those environment variables include the name of the INI files, the name of the meteorology files, the path to the model executable and its file name, the entire output list, the entire output variable matrix, the dependency rules for the EPC parameters etc. Using the runMuso function RBBGCMuso can automatically create those environment variables by inspecting the files in the working directory (this happens through the setupMuso function). It means that by default model setup is performed automatically in the background and the user has nothing to do. With this settings parameter we can force runMuso to skip automatic environment setup as we provide the environment settings to runMuso. In a typical situation the user can skip this option.
+#' @param timee The required timesteps in the model output. It can be "d", if it is daily, "m", if it is monthly, "y" if it is yearly. It is recommended to use daily data, as the yearly and monthly data is not well-tested yet. 
+#' @param debugging If debugging is set to TRUE, after model execution the function copies the Biome-BGCMuSo log file into a LOG directory to stores it for further processing. If debugging is set to STAMPLOG instead of TRUE, it concatenates a number before the logfile, which is one plus the maximum of those present in the LOG directory. In each case the log files will be saved. 
+#' @param keepEpc If keepEpc is set to TRUE, the function keeps the EPC file and stamps it, and then copies it to the EPCS directory. If debugging is set to TRUE, it copies the wrong EPC files to the wrong epc directory.
+#' @param export If it is set to YES or you define a filename here, the function converts the output to the specific file format. For example, if you set export to "example.csv", it converts the output to "csv". If you set it to "example.xls" it converts the output to example.xls with the xlsx package. If the Excel converter package is not installed it gives back a warning message and converts the results to csv.
+#' @param silent IIf you set the silent parameter to TRUE, all of the model's output normally written to the screen will be suppressed. This option can be useful to increase the speed of the model execution.
+#' @param aggressive It deletes all previous model-outputs from previous model runs.
+#' @param parameters Using normalMuso it is possible to change some of the EPC parameters prior to model execution. This can be achieved with this option. In the parameters variable you have set the row indices of the variables that you wish to change. In this parameters you can give an exact value for them in a vector form like c(1,2,3,4).
+#' @param logfilename If you would like to set a specific name for your logfiles you can set this via the logfile parameter.
+#' @param leapYear Should the function do a leapyear correction on the output data? If TRUE, then the result for 31 December will be doubled in leap years which means that the results for the leap year will cover all 366 days. See the model's User's Guide for notes on leap years. 
+#' @param keepBinary By default RBBGCMuso keeps the working environment as clean as possible, thus deletes all the regular output files. The results are directly written to the standard output (e.g. to the screen), but you can redirect it and save them to a variable. Alternatively, you can export your results to the desired destination in a desired format. Through the keepBinary parameter you can set RBBGCMuso to keep the binary output files. If you would like to set the location of the binary output, please take a look at the binaryPlace argument.
+#' @param binaryPlace The directory for the binary output files (see the keepBinary parameter).
+#' @param fileToChange You can change any line of the EPC or the INI file prior to model execution. All you need to do is to specify with this variable which file you want to change. Two options possible: "EPC" or "INI" 
+#' @param skipSpinup If this is set to TRUE, runMuso will not perform the spinup simulation. This is of course means that the endpoint file (initial conditions) must be available for the normal INI file. This option might be extremely useful to speed up multiple model execution. In cropland related simulations due to site history the EPC file used in the normal phase might differ from the one used in the spinup phase, which means that the spinup is the same even if we change the parameterization for the normal phase. In this situation skipSpinup is really useful. 
+#' @param prettyOut If this parameter is to TRUE then date will provided as the R-style Date type, and separate year, month and day vectors. In typical cases the user should use this option. 
+#' @return No return, outputs are written to file 
+#' @usage calibMuso(settings,parameters=NULL, timee="d", debugging=FALSE, logfilename=NULL,
+#' keepEpc=FALSE, export=FALSE, silent=FALSE, aggressive=FALSE, leapYear=FALSE)
+#' @import utils
+#' @export
+runMuso <- function(...){
+    calibMuso(...)
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/rungetMuso.R

@@ -0,0 +1,278 @@
+#'rungetMuso
+#'
+#' This function runs the BBGC-MuSo model and reads in its outputfile in a very structured way.
+#' 
+#' @author Roland Hollos
+#' @param settings You have to run the setupMuso function before rungetMuso. It is its output which contains all of the necessary system variables. It sets the whole environment
+#' @param timee The required timesteps in the modell output. It can be "d", if it is daily, "m", if it's monthly, "y", it it is yearly
+#' @param debugging If it is TRUE, it copies the log file to a Log directory to store it, if it is stamplog it contatenate a number before the logfile, which is one more than the maximum of the represented ones in the LOG directory. If it is true or stamplog it collects the "wrong" logfiles
+#' @param keepEpc If TRUE, it keeps the epc file and stamp it, after these copies it to the EPCS directory. If debugging True or false, it copies the wrong epc files to the wrong epc directory.
+#' @param export if it is yes or you give a filename here, it converts the output to the specific extension. For example, if you set export to "example.csv", it converts the output to "csv", if you set it to "example.xls" it converts to example.xls with the xlsx package. If it is not installed it gives back a warning message and converts it to csv.
+#' @param silent If you set it TRUE all off the modells output to the screen will be suppressed. It can be usefull, because it increases the model-speed.
+#' @param aggressive It deletes every possible modell-outputs from the previous modell runs.
+#' @param leapYear Should the function do a leapyear correction on the outputdata? If TRUE, then the 31.12 day will be doubled.
+#' @param logfilename If you want to set a specific name for your logfiles you can set this via logfile parameter
+#' @return It depends on the export parameter. The function returns with a matrix with the modell output, or writes this in a file, which is given previously
+#' @usage rungetMuso(settings, timee="d", debugging=FALSE, logfilename=NULL,
+#' keepEpc=FALSE, export=FALSE, silent=FALSE, aggressive=FALSE, leapYear=FALSE)
+#' @import utils
+#' @export
+
+
+
+rungetMuso <- function(settings, timee="d", debugging=FALSE, logfilename=NULL, keepEpc=FALSE, export=FALSE, silent=FALSE, aggressive=FALSE, leapYear=FALSE){
+    
+
+
+
+##########################################################################
+###########################Set local variables########################
+########################################################################
+    
+    Linuxp <-(Sys.info()[1]=="Linux")
+    ##Copy the variables from settings
+    inputLoc <- settings$inputLoc
+    outputLoc <- settings$outputLoc
+    executable <- settings$executable
+    iniInput <- settings$iniInput
+    epc <- settings$epcInput
+    calibrationPar <- settings$calibrationPar
+    whereAmI<-getwd()
+        
+#############################################################
+############################spinup run############################
+########################################################## 
+
+    
+    ##Sometimes a bug occure due to logfiles and controlfiles in the input loc directory
+    
+
+    if(silent!=TRUE){
+        if(length(grep("(dayout$)|(log$)",list.files(inputLoc)))>0){    
+            cat(" \n \n WARMING: there is a log or dayout file nearby the ini files, that may cause problemes. \n \n If you want to avoid that possible problemes, please copy the log or dayout files into a save place, and after do a cleanupMuso(), or delete these manually, or run the rungetMuso(), with the agressive=TRUE parameter \n \n")
+
+        }
+      
+    }
+    
+    if(aggressive==TRUE){
+        cleanupMuso(location=outputLoc, deep=TRUE)
+    }
+
+    ##We change the working directory becase of the model, but we want to avoid sideeffects, so we save the current location and after that we will change everything to it.
+    
+    ## Set the working directory to the inputLoc temporary.
+    setwd(inputLoc)
+
+
+    ##Run the model for the spinup run.
+
+    if(silent){#silenc mode
+        if(Linuxp){
+                                        #In this case, in linux machines
+            system(paste(executable,iniInput[1],"> /dev/null",sep=" "))
+        } else {
+                                        #In windows machines there is a show.output.on.console option
+            system(paste(executable,iniInput[1],sep=" "),show.output.on.console = FALSE)
+        }
+        
+    } else {
+        system(paste(executable,iniInput[1],sep=" "))
+    }
+
+    
+    
+    logspinup<-list.files(outputLoc)[grep("log$",list.files(outputLoc))]#load the logfiles
+    if(length(logspinup)==0){
+        return("Modell Failure")#in that case the modell did not create even a logfile
+    }
+    
+    
+    if(length(logspinup)>1){
+        spincrash<-TRUE
+    } else {
+        if(identical(tail(readLines(paste(outputLoc,logspinup,sep="/"),-1),1),character(0))){
+            spincrash<-TRUE
+        } else {
+            spincrash<-(tail(readLines(paste(outputLoc,logspinup,sep="/"),-1),1)!=1)
+        }
+    }
+    
+    
+    
+    if(!spincrash){##If spinup did not crashed, run the normal run.
+        
+##################################################################### 
+###########################normal run#########################
+#################################################################
+
+        ##for the sake of safe we set the location again
+        setwd(inputLoc)
+
+        if(silent){
+            if(Linuxp){
+                system(paste(executable,iniInput[2],"> /dev/null",sep=" "))
+            } else {
+                system(paste(executable,iniInput[2],sep=" "),show.output.on.console = FALSE)
+            }
+            
+        } else {
+            system(paste(executable,iniInput[2],sep=" "))
+        }
+
+
+        ##read the output
+        
+        switch(timee,
+               "d"=(Reva<-getdailyout(settings)),
+               "m"=(Reva<-getmonthlyout(settings)),
+               "y"=(Reva<-getyearlyout(settings))
+               )
+    }
+
+    
+    logfiles <- list.files(outputLoc)[grep("log$",list.files(outputLoc))]#creating a vector for logfilenames
+
+###############################################    
+#############LOG SECTION#######################
+###############################################
+    
+    perror<-as.numeric(as.vector(lapply(paste(outputLoc,logfiles,sep="/"),function(x) tail(readLines(x,-1),1)))) #vector of spinup and normalrun error
+    
+    if((debugging=="stamplog")|(debugging==TRUE)){#If debugging option turned on
+                                        ##If log or ERROR directory does not exists create it!
+        dirName<-paste(inputLoc,"LOG",sep="") 
+        dirERROR<-paste(inputLoc,"ERROR",sep="")
+        
+        if(!dir.exists(dirName)){
+            dir.create(dirName)
+        }
+
+        if(!dir.exists(dirERROR)){
+            dir.create(dirERROR)
+        }
+    }
+
+    ##if errorsign is 1 there is error, if it is 0 everything ok
+    if(length(perror)>sum(perror)){
+        errorsign <- 1
+
+    } else {
+        if(spincrash){
+            errorsign <- 1
+        } else {
+            errorsign <- 0
+        } 
+    }
+
+
+    if(keepEpc){#if keepepc option tured on
+        
+        if(length(unique(dirname(epc)))>1){
+            print("Why are you playing with my nervs? Seriously? You hold your epc-s in different folders?")
+        } else {
+            epcdir <- dirname(epc[1])
+            
+            WRONGEPC<-paste(inputLoc,"WRONGEPC",sep="")
+            EPCS<-paste(inputLoc,"EPCS",sep="")
+            
+            if(!dir.exists(WRONGEPC)){
+                dir.create(WRONGEPC)
+            }
+
+            if(!dir.exists(EPCS)){
+                dir.create(EPCS)
+            }
+            
+            epcfiles <- list.files(epcdir)[grep("epc$",list.files(epcdir))]
+            stampnum<-stamp(EPCS)
+            lapply(epcfiles,function (x) file.copy(from = paste(epcdir,"/",x,sep=""),to=paste(EPCS,"/",(stampnum+1),"-",x,sep="")))
+            if(errorsign==1){
+                lapply(epcfiles,function (x) file.copy(from = paste(EPCS,"/",(stampnum+1),"-",x,sep=""), to=WRONGEPC))
+            }
+
+        }
+    }
+    
+
+
+
+
+    if(debugging=="stamplog"){
+        stampnum<-stamp(dirName)
+        if(inputLoc==outputLoc){
+            lapply( logfiles, function (x) file.rename(from=paste(outputLoc,x, sep=""), to=paste(dirName, "/",(stampnum+1),"-",x,sep="")))
+            
+        } else {
+            lapply( logfiles, function (x) file.rename(from=paste(outputLoc,x, sep="/"), to=paste(dirName, "/",(stampnum+1),"-",x,sep="")))
+        }
+        
+        if(errorsign==1){
+            lapply( logfiles, function (x) file.copy(from=paste(dirName, "/",(stampnum+1),"-",x,sep=""), to=dirERROR  ))}
+
+    } else { if(debugging){
+                 if(is.null(logfilename)){
+
+                     if(inputLoc==outputLoc){
+                          lapply( logfiles, function (x) file.rename(from=paste(outputLoc,x, sep=""), to=paste(dirName,"/", x, sep="")))
+                     } else {
+                         lapply( logfiles, function (x) file.rename(from=paste(outputLoc,x, sep="/"), to=paste(dirName,"/", x, sep="")))     
+                     }
+
+                     if(errorsign==1){
+                          lapply( logfiles, function (x) file.copy(from=paste(dirName, "/",logfilename,"-",x,sep=""), to=dirERROR))
+                     }
+
+                 } else {
+
+                     if(inputLoc==outputLoc){#These are very ugly solutions for a string problem: inputLoc: "./", if outputLoc equalent of inputLoc, it ends with "/", the string manipulation can not handle this. The better solution is easy, but I dont have enough time(Roland Hollo's) 
+                         lapply( logfiles, function (x) file.rename(from=paste(outputLoc,x, sep=""), to=paste(dirName, "/",logfilename,"-",x,sep="")))                        
+                     } else {
+                         lapply( logfiles, function (x) file.rename(from=paste(outputLoc,x, sep="/"), to=paste(dirName, "/",logfilename,"-",x,sep="")))    
+                     }
+                     
+                     if(errorsign==1){
+                         lapply( logfiles, function (x) file.copy(from=paste(dirName, "/",logfilename,"-",x,sep=""), to=dirERROR))
+                     }
+                 }    
+                 
+             }}
+    
+    cleanupMuso(location=outputLoc)
+    if(errorsign==1){
+        return("Modell Failure")
+    }
+
+    if(timee=="d"){
+        colnames(Reva) <- unlist(settings$outputVars[[1]])
+    } else {
+        if(timee=="y")
+            colnames(Reva) <- unlist(settings$outputVars[[2]])
+    }
+
+    if(leapYear){
+        Reva <- corrigMuso(settings,Reva)
+        rownames(Reva) <- musoDate(settings$startYear, settings$numYears)
+    } else { 
+        rownames(Reva) <- musoDate(settings$startYear, settings$numYears, corrigated=FALSE)
+    }
+
+    if(export!=FALSE){
+        setwd(whereAmI)
+
+        ## switch(fextension(export),
+        ##        "csv"=(write.csv(Reva,export)),
+        ##        "xlsx"=(),
+        ##        "odt"=
+        
+        
+        ## )
+        write.csv(Reva,export)
+        
+    } else{
+        setwd(whereAmI)
+        return(Reva)}
+}
+
+
+

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/setupMuso.R

@@ -0,0 +1,354 @@
+#' setupMuso
+#'
+#' The setupMuso is fundamental for the Biome-BGCMuSo model related other functions like runMuso, spinupMuso, normalMuso, rungetMuso, as it sets the model's environment. The function reads the INI files from a given directory, analyzes them with error checking, and creates a data structure in R that contains the complete information content for the simulation.  
+#'
+#' @author Roland HOLLOS
+#' @param parallel Set this variable to TRUE if you would like to implement parallel execution of the model 
+#' @param executable This parameter stores the location (directory) of the model-executable file. In normal usage, you don't have to set this parameter, because the RBBGCMuso package always contains the latest model executable. In spite of this, if you would like to use this package for model development or just want to use different model version (for example for comparison), you will find this option useful
+#' @param calibrationPar You might want to change some parameters in your EPC file before running the model. setupMuso offers possibility for this without editing the EPC file. In this situation you have to select the appropirate model parameters first. You can refer to these parameters with the number of the line in the EPC file. Indexing of lines start from one. You should use a vector for this referencing like c(1,5,8)
+#' @param outputLoc With this parameter the user can specify the directory for the model output. The syntax is simple, for example: outputLoc="/place/of/the/outputs/" or outputLoc="C:/my_model_directory/". Note that this output directory is specified by the user within the INI file, which means that the outputLoc parameter overrides the INI settings if specified.
+#' @param inputLoc Usually this is the root (or base) directory where the user stores the INI files for the model. If the working directory is set by the user, this parameter can be skipped. 
+#' @param metInput Via the metInput parameter the user can specify the location of the input meteorological files. By default the package reads this information from the INI files.
+#' @param CO2Input Via the CO2Input parameter the user can specify the location of the CO2 data file. By default the package reads this information from the INI files.
+#' @param plantInput Via the plantInput parameter, the user can specify the location of the the file that contains the planting information. By default the package reads this information from the INI files.
+#' @param thinInput Via the thinInput parameter,the user can specify the location of the file that contains the thinning information. By default the package reads this information from the INI files.
+#' @param mowInput Via the mowInput parameter, the user can specify the location of the file that contains the mowing (i.e. grass cutting) information. By default the package reads this information from the INI files.
+#' @param grazInput Via the grazInput parameter, the user can specify the location of the file that contains the grazing information. By default the package reads this information from the INI files.
+#' @param harvInput Via the harvInput parameter, the user can specify the location of the file that contains the harvesting information. By default the package reads this information from the INI files.
+#' @param plougInput Via the plougInput parameter, the user can specify the location of the file that contains the ploughing information. By default the package reads this information from the INI files.
+#' @param fertInput Via the fertInput parameter, the user can specify the location of the file that contains the fertilizing information. By default the package reads this information from the INI files.
+#' @param irrInput Via the irrInput parameter, the user can specify the location of the file that contains the irrigation information. By default the package reads this information from the INI files.
+#' @param nitInput Via the nitInput parameter, the user can specify the location of the file that contains the nitrogen deposition data. By default the package reads this information from the INI files.
+#' @param iniInput Via the iniInput parameter, the user can specify the location of the INI files. By default the package reads the INI files from the working directory. 
+#' @param epcInput Via the epcInput parameter, the user can specify the location of the EPC data file. By default the package reads this information from the INI files.
+#' @param modelOutputs This parameter contains the list of the codes that defines the required model output variables. Check the Biome-BGCMuS website for the complete list of possible output variables at http://agromo.agrar.mta.hu/bbgc/download.html 
+#' @usage setupMuso(executable=NULL, parallel = F, calibrationPar =c(1),
+#' outputLoc=NULL, inputLoc=NULL,
+#' metInput=NULL, CO2Input=NULL,
+#' plantInput=NULL, thinInput=NULL,
+#' mowInput=NULL, grazInput=NULL,
+#' harvInput=NULL, plougInput=NULL,
+#' fertInput=NULL, irrInput=NULL,
+#' nitInput=NULL, iniInput=NULL, epcInput=NULL)
+#' @return The output is a the model settings list wich contains the following elements:
+#' executable, calibrationPar, outputLoc, outputName, inputLoc, iniInput, metInput, epcInput,thinInput,CO2Input, mowInput, grazInput, harvInput, plougInput, fertInput,rrInput, nitInput, inputFiles, numData, startyear, numYears, outputVars
+#' @export
+
+setupMuso <- function(executable=NULL,
+                      parallel = F,
+                      calibrationPar =c(1),
+                      outputLoc=NULL,
+                      modelOutputs=NULL,
+                      inputLoc=NULL,
+                      metInput=NULL,
+                      CO2Input=NULL,
+                      plantInput=NULL,
+                      thinInput=NULL,
+                      mowInput=NULL,
+                      grazInput=NULL,
+                      harvInput=NULL,
+                      plougInput=NULL,
+                      fertInput=NULL,
+                      irrInput=NULL,
+                      nitInput=NULL,
+                      iniInput=NULL,
+                      epcInput=NULL,
+                      mapData=NULL,
+                      leapYear=FALSE,
+                      version=6,
+                      doCopy=TRUE
+                      ){
+
+    Linuxp <-(Sys.info()[1]=="Linux")
+    writep <- 0
+
+    # if(is.null(mapData)&version==4){
+    #     mData <- mMapping4
+    # }
+    #
+
+    inputParser <- function(string,fileName,counter,value=TRUE){
+        unlist(strsplit(grep(string,fileName,value=TRUE, perl = TRUE),"[\ \t]", useBytes = TRUE))[counter]
+    }
+
+    # outMaker <- function(inputVar,grepString,filep){
+    #     tempVar <- eval(parse(text=inputVar))
+    #     if(is.null(tempVar)){
+    #         writep <<- writep+1
+    #         if(filep)
+    #         {
+    #             tempVar["spinup"] <- file.path(inputLoc,inputParser(string=grepString,fileName=iniFiles$spinup,counter=1,value=TRUE))
+    #             tempVar["normal"] <- file.path(inputLoc,inputParser(string=grepString,fileName=iniFiles$normal,counter=1,value=TRUE))
+    #         } else {
+    #             tempVar["spinup"] <- inputParser(string=grepString,fileName=iniFiles$spinup,counter=1,value=TRUE)
+    #             tempVar["normal"] <- inputParser(string=grepString,fileName=iniFiles$normal,counter=1,value=TRUE)
+    #             
+    #         }
+    #
+    #     } else {
+    #         iniFiles$spinup[grep(grepString,iniFiles$spinup)] <<- paste0(tempVar[1],"\t ",grepString)
+    #         
+    #         if(length(tempVar)==2){
+    #             iniFiles$normal[grep(" grepString",iniFiles$normal)] <<- paste0(tempVar[2],"\t ",grepString)
+    #         }
+    #     }
+    #     return(tempVar)
+    # }
+    
+    if(is.null(inputLoc)){
+        inputLoc<- normalizePath("./")
+    } else{
+        inputLoc <- normalizePath(inputLoc)
+    }
+    
+    #iniChangedp <- FALSE
+
+    if(is.null(iniInput)){
+        spinups<-grep("s.ini$",list.files(inputLoc),value=TRUE, perl = TRUE)
+        normals<-grep("n.ini$",list.files(inputLoc),value=TRUE, perl = TRUE)
+
+        if(length(spinups)==1){
+            iniInput[1] <- file.path(inputLoc,spinups)
+        } else {
+            iniInput[1] <- "no spinup" 
+            # stop("There are multiple or no spinup ini files, please choose")
+        }
+        
+
+        if(length(normals)==1){
+            iniInput[2]<-file.path(inputLoc,normals)
+        } else {stop("There are multiple or no normal ini files, please choose")}
+
+    }
+
+    ##read the ini files for the further changes
+
+    iniFiles<-lapply(iniInput, function (x) readLines(x,-1))
+    iniFiles[[1]] <- gsub("\\\\","/", iniFiles[[1]], perl = TRUE) #replacing \ to /
+    iniFiles[[2]] <- gsub("\\\\","/", iniFiles[[2]], perl = TRUE) #replacing \ to /
+    names(iniFiles) <- c("spinup","normal")
+
+
+    
+    # inputs <- lapply(1:nrow(grepHelper), function (x) {
+    #
+    #     outMaker(grepHelper[x,1],grepHelper[x,2],grepHelper[x,3])
+    #     
+    # })   
+    # names(inputs) <- grepHelper$inputVar   
+    ## grepHelper is in sysdata.rda it is a table like this:
+    ##
+    ## inputVar         string      isFile  
+    ## 1    epcInput  EPC file name TRUE 
+    ## 2    metInput  met file name TRUE
+    ## 3    CO2Input       CO2 file TRUE
+    ## 4    nitInput     N-dep file TRUE
+    ## 5   thinInput    do THINNING FALSE
+    ## 6  plantInput    do PLANTING FALSE
+    ## 7    mowInput      do MOWING FALSE
+    ## 8   grazInput     do GRAZING FALSE
+    ## 9   harvInput  do HARVESTING FALSE
+    ## 10 plougInput   do PLOUGHING FALSE
+    ## 11  fertInput do FERTILIZING FALSE
+    ## 12   irrInput  do IRRIGATION FALSE
+   # return(inputs) debug element 
+
+    
+    # if(is.null(mapData)){
+    #     
+        outIndex<-grep("DAILY_OUTPUT",iniFiles[[2]], perl = TRUE)+1
+        numVar<-as.numeric(unlist(strsplit(iniFiles[[2]][outIndex],"[\ \t]", useBytes = TRUE))[1])
+        dailyVarCodes<-tryCatch(iniFiles[[2]][(outIndex+1):(outIndex+numVar)],
+                                error = function(e){
+        stop("Cannot read indexes of output variables from the normal ini file, please make sure you have not skiped a line after the flag: \"DAILY_OUTPUT\"")    
+        })
+
+        dailyVarCodes<-unlist(lapply(dailyVarCodes, function(x) unlist(strsplit(x,"[\ \t]", useBytes = TRUE))[1]))
+        dailyVarnames<-unlist(lapply(dailyVarCodes, function(x) musoMapping(unlist(strsplit(x,"[\ \t]", useBytes = TRUE))[1])))
+
+        outIndex<-grep("ANNUAL_OUTPUT",iniFiles[[2]], perl = TRUE)+1
+        numVar<-as.numeric(unlist(strsplit(iniFiles[[2]][outIndex],"[\ \t]", useBytes = TRUE))[1])
+        annualVarCodes<-iniFiles[[2]][(outIndex+1):(outIndex+numVar)]
+        annualVarCodes<-unlist(lapply(annualVarCodes, function(x) unlist(strsplit(x,"[\ \t]", useBytes = TRUE))[1]))
+        annualVarnames<-unlist(lapply(annualVarCodes, function(x) musoMapping(unlist(strsplit(x,"[\ \t]", useBytes = TRUE))[1])))
+        outputVars<-list(dailyVarnames,annualVarnames)
+        # browser()
+# } else {
+#
+#                                                           c<-grep("DAILY_OUTPUT",iniFiles[[2]])+1
+#                                                           numVar<-as.numeric(unlist(strsplit(iniFiles[[2]][c],"[\ \t]"))[1])
+#                                                           dailyVarCodes<-iniFiles[[2]][(c+1):(c+numVar)]
+#                                                           dailyVarnames<-lapply(dailyVarCodes, function(x) musoMapping(unlist(strsplit(x,"[\ \t]"))[1],mapData))
+#
+#                                                           c<-grep("ANNUAL_OUTPUT",iniFiles[[2]])+1
+#                                                           numVar<-as.numeric(unlist(strsplit(iniFiles[[2]][c],"[\ \t]"))[1])
+#                                                           annualVarCodes<-iniFiles[[2]][(c+1):(c+numVar)]
+#                                                           annualVarnames<-lapply(annualVarCodes, function(x) musoMapping(unlist(strsplit(x,"[\ \t]"))[1],mapData))
+#                                                           outputVars<-list(dailyVarnames,annualVarnames)
+#
+#
+#                                                           
+#                                                       }
+    
+    
+    
+    if(is.null(executable)){
+        if(Linuxp){
+            executable<-file.path(inputLoc,"muso")
+        } else {
+            executable<-file.path(inputLoc,"muso.exe")
+        }
+    } else {
+        if(doCopy){
+            file.copy(executable,inputLoc)            
+        }
+
+    }
+
+    outputName <- character(2)
+    outputName[1] <- basename(unlist(strsplit(iniFiles[[1]][grep("OUTPUT_CONTROL",iniFiles[[1]], perl = TRUE)+1],"[\ \t]", useBytes = TRUE))[1])
+    outputName[2] <- basename(unlist(strsplit(iniFiles[[2]][grep("OUTPUT_CONTROL",iniFiles[[2]], perl = TRUE)+1],"[\ \t]", useBytes = TRUE))[1])
+    ##  outputName <- unlist(strsplit(grep("output",grep("prefix",iniFiles[[2]],value=TRUE),value=TRUE),"[\ \t]"))[1]
+    ##THIS IS AN UGLY SOLUTION, WHICH NEEDS AN UPGRADE!!! FiXED (2017.09.11)
+    ## outputName <- unlist(strsplit(grep("prefix for output files",iniFiles[[2]],value=TRUE),"[\ \t]"))[1]
+    if(is.null(outputName)){
+        stop("I cannot find outputName in your default ini file \n Please make sure that the line wich contains the name also contains the prefix and the output keywords!")
+        
+    }
+    ##    outputName<-unlist(read.table(iniInput[2],skip=93,nrows = 1))[1]
+
+
+    if(is.null(outputLoc)){
+        ##  outputLoc<-paste((rev(rev(unlist(strsplit(outputName,"/")))[-1])),collapse="/")
+        outputLoc <- dirname(unlist(strsplit(iniFiles[[2]][grep("OUTPUT_CONTROL",iniFiles[[2]], perl = TRUE)+1],"[\ \t]", useBytes = TRUE))[1])
+        if(substr(outputLoc,start = 1,stop = 1)!="/"){
+            ##if the outputName is not absolute path make it absolute
+            outputLoc <- file.path(inputLoc,outputLoc)
+        } 
+    } else {
+        outputLoc <- normalizePath(outputLoc)
+    }
+
+    
+    
+    inputFiles<-c(iniInput,epcInput,metInput)
+    numData<-rep(NA,3)
+    numYears <-  as.numeric(unlist(strsplit(iniFiles[[2]][grep("TIME_DEFINE",iniFiles[[2]], perl = TRUE)+1],"[\ \t]", useBytes = TRUE))[1])
+    ##    numYears<-unlist(read.table(iniInput[2],skip = 14,nrows = 1)[1])
+    numValues <-  as.numeric(unlist(strsplit(iniFiles[[2]][grep("DAILY_OUTPUT",iniFiles[[2]], perl = TRUE)+1],"[\ \t]", useBytes = TRUE))[1])
+    ## numValues will be replaced to numVar
+    ## numValues<-unlist(read.table(iniInput[2],skip=102,nrows = 1)[1])
+    startYear <- as.numeric(unlist(strsplit(iniFiles[[2]][grep("TIME_DEFINE",iniFiles[[2]], perl = TRUE)+2],"[\ \t]", useBytes = TRUE))[1])
+    numData[1] <- numValues * numYears * 365 # Have to corrigate leapyears 
+
+    numData[2] <- numYears * numValues*12
+    numData[3] <- numYears * numValues
+
+    ##Writing out changed ini-file
+
+    writeLines(iniFiles[[1]],iniInput[1])
+    writeLines(iniFiles[[2]],iniInput[2])
+
+    if(!is.null(modelOutputs)){
+        outVarChanges <- putOutVars(iniFile = iniInput[2],outputVars = modelOutputs, modifyOriginal = TRUE)
+        numData <- round(numDate*outVarChanges[[2]])
+        outputVars[[1]] <-outVarChanges[[1]] 
+    }
+    
+
+    suppressWarnings(file.remove(paste0(file.path(outputLoc,outputName[1]),".log")))
+    ## I use file.path additionally because We do not know if outputLoc ends or not to "/"
+    suppressWarnings(file.remove(paste0(file.path(outputLoc,outputName[2]),".log")))
+ 
+    searchBellow <- function(inFile, key, stringP = TRUE,  n=1, management = FALSE){
+        
+            if(stringP){
+                unlist(strsplit(inFile[grep(key,inFile, perl=TRUE)+n],split = "\\s+", useBytes = TRUE))[1]
+            } else {
+                as.numeric(unlist(strsplit(inFile[grep(key,inFile,perl=TRUE)+n],split = "\\s+", useBytes = TRUE))[1])
+            }
+    }
+    
+    normOutputFlags <- c(
+        daily=searchBellow(iniFiles[[2]], "OUTPUT_CONTROL",stringP=FALSE,n=2),
+        annual=searchBellow(iniFiles[[2]], "OUTPUT_CONTROL",stringP=FALSE,n=5))
+    if(normOutputFlags[1]!=1){
+        warning("You should set your daily output flag to 1 (binary) RBBRMuso work only with binary output...")
+    }
+    searchBellow(iniFiles[[2]], "OUTPUT_CONTROL",stringP=FALSE,n=5)
+    soilFile <- NULL
+    if(version >=6){
+        soilFiles <- tryCatch(sapply(iniFiles,function(x){(searchBellow(x,"SOIL_FILE"))}),error = function(e){""})
+    }
+    epcFiles <- tryCatch(sapply(iniFiles,function(x){(searchBellow(x,"EPC_FILE"))}),error = function(e){""}) 
+    metInput <- tryCatch(sapply(iniFiles,function(x){(searchBellow(x,"MET_INPUT"))}),error = function(e){""})
+    dailyOutputTable <- cbind.data.frame(seq_along(dailyVarCodes),dailyVarCodes,outputVars[[1]])
+    colnames(dailyOutputTable) <- c("index","code","name")
+    annualOutputTable <- cbind.data.frame(seq_along(annualVarCodes),annualVarCodes,outputVars[[2]])
+    colnames(annualOutputTable) <- c("index","code","name")
+    
+    settings = list(executable = executable,
+                    calibrationPar = calibrationPar,
+                    outputLoc=outputLoc,
+                    outputNames=outputName,
+                    inputLoc=inputLoc,
+                    iniInput=iniInput,
+                    metInput=metInput,
+                    epcInput=epcFiles,
+                    # thinInput=inputs$thinInput,
+                    # CO2Input=inputs$CO2Input,
+                    # mowInput=inputs$mowInput,
+                    # grazInput=inputs$grazInput,
+                    # harvInput=inputs$harvInput,
+                    # plougInput=inputs$plougInput,
+                    # fertInput=inputs$fertInput,
+                    # irrInput=inputs$irrInput,
+                    # nitInput=inputs$nitInput,
+                    inputFiles=inputFiles,
+                    numData=numData,
+                    startYear=startYear,
+                    numYears=numYears,
+                    outputVars=outputVars,
+                    soilFile=soilFiles,
+                    dailyVarCodes= gsub("\\s.*","",dailyVarCodes),
+                    annualVarCodes = gsub("\\s.*","",annualVarCodes),
+                    dailyOutputTable=dailyOutputTable,
+                    annualOutputTable=annualOutputTable,
+                    normOutputFlags=normOutputFlags 
+                    )
+
+    # if(getOption("RMuso_version")==6){
+    #     manFile <- scan(iniInput[2],what="",n=1,skip=44,sep=" ") # HARDCODED -> UNTIL JSON VERSION
+    #     mgm <- readLines(manFile)
+    #     mgmConn <- file(manFile,open="r")
+    #     manTypes <- c("planting","thinning","mowing","grazing","harvesting","ploughing","fertilizing","irrigating")
+    #     mgmFiles <- rep("none",length(manTypes))
+    #     if(scan(mgmConn,skip=3,n=1,what=integer())==1){
+    #         mgmFiles[1] <- scan(mgmConn,skip=1,n=1,what="", sep = " ")
+    #     }
+    #     for(i in 2:length(mgmFiles)){
+    #        if(scan(mgmConn,skip=2,n=1,what=integer())==1){
+    #            mgmFiles[i] <- scan(mgmConn,skip=1,n=1,what="", sep =" " )
+    #        } else {
+    #            blackhole<-scan(mgmConn,skip =1, n=1,what="")
+    #        }
+    #     }
+    #     names(mgmFiles) <- manTypes
+    #     settings[["management"]] <- mgmFiles
+    #     close(manConn)
+    # }
+
+    
+    # if(writep!=nrow(grepHelper)){
+    #     writeLines(iniFiles[[1]],iniInput[[1]])
+    #     if(inputs$epcInput[1]!=inputs$epc$Input[2]){ #Change need here
+    #         writeLines(iniFiles[[2]],iniInput[[2]])      
+    #     }
+    # }
+
+    suppressWarnings(dir.create(file.path(inputLoc,"bck")))
+    # sapply(iniFiles,epc)
+    return(settings)
+
+}
+

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/setupMuso6.R

@@ -0,0 +1,47 @@
+## #' setupMuso6
+## #'
+## #' This is the setup function for MuSo version: 6
+## #'
+## #' @author Roland HOLLOS
+## #' @param setupFile
+## #' @export
+
+## setupMuso6<- function(setupFile){
+    
+## }
+
+## ini <- readLines("./hhs_apriori_MuSo6_normal.ini")
+## flags <- c("MET_INPUT",
+##            "RESTART",
+##            "TIME_DEFINE",
+##            "CO2_CONTROL",
+##            "NDEP_CONTROL",
+##            "SITE",
+##            "SOILPROP_FILE",
+##            "EPC_FILE",
+##            "MANAGEMENT_FILE",
+##            "SIMULATION_CONTROL",
+##            "W_STATE",
+##            "CN_STATE",
+##            "CLIM_CHANGE",
+##            "CONDITIONAL_MANAGEMENT_STRATEGIES",
+##            "OUTPUT_CONTROL",
+##            "DAILY_OUTPUT",
+##            "ANNUAL_OUTPUT",
+##            "END_INIT")
+## getSegments <- function(ini, flags){
+##     output <- list()
+##     flagIterator <- 1:(length(flags)-1)
+##     for(i in flagIterator){
+##         output[[flags[i]]] <- lapply(ini[(grep(flags[i],ini)+1):(grep(flags[i+1],ini)-2)], function(x){
+##             unlist(strsplit(x,split = "\\["))[1]
+##         })
+##     }
+##     output
+## }
+## getSegments(ini,flags)
+
+## gsub("(.*\\[\\|)([a-zA-Z1-9_]*)","",ini)
+## stringi::stri_trim_right("rexamine.com/", "\\[r\\]")
+## stri_extract("asdfasdf [|Ezat|]",regex = "\\[\\|*\\]")
+## lapply(ini,function(x) gsub("\\s","",(strsplit(x,split= "T]"))[[1]][2]))

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/soilQuery.R

@@ -0,0 +1,73 @@
+#' getSoilDataFull
+#' 
+#' This function collects soil data from a given restapi, de default is soilGrid
+#'
+#' @author Roland HOLLÓS
+#' @name getSoilDataFull
+#' @importFrom glue glue
+#' @importFrom httr  config with_config GET content
+
+getSoilDataFull <- function(lat, lon, apiURL) {
+    if(missing(apiURL)){
+        apiURL <- "https://81.169.232.36"
+    }
+    apiString <- glue("{apiURL}/query?lon={lon}&lat={lat}")
+    soilREST <- #with_config(config(ssl_verifypeer=0L, ssl_verifyhost=0L),
+                            GET(apiString) # ) # This is temporary solution ssl_verification wont bypass
+   content(soilREST) 
+}
+
+#' createSoilFile
+#' 
+#' This function collects soil data from a given restapi, de default is soilGrid
+#'
+#' @author Roland HOLLOS
+#' @name createSoilFile
+#' @importFrom glue glue
+#' @importFrom stats approx 
+#' @importFrom magrittr '%>%'
+#' @export
+
+createSoilFile <- function(lat,lon,
+                            outputFile="recent.soi",
+                            method="constant",apiURL,
+                            template=system.file("examples/hhs/hhs.soi",package="RBBGCMuso")) {
+    if(missing(apiURL)){
+        apiURL <- "https://rest.soilgrids.org/soilgrids/v2.0/properties"
+    }
+    outFile <- suppressWarnings(readLines(template))
+    outFile[1] <- sprintf("SOILPROP FILE - lat: %s, lon: %s, created in: %s",lat,lon,date())
+    musoCenters <- c(1.5,6.5,20.0,45.0,75.0,105.0,135.0,175.0,300.0,700.0)
+    # soilGridDepths  <- c(0,5,15,30,60,100,200)
+    soilGridDepths  <- c(2.5, 10, 22.5, 45, 80, 150)
+    Reduce(function(x,y){(y-x)/2+x},soilGridDepths,accumulate=TRUE)
+    rest<- getSoilDataFull(lat,lon, apiURL)
+
+
+    createMusoLayers <- function(values,depths=soilGridDepths,centers=musoCenters,intMethod=method){
+        approx(x=depths,y=values, xout = centers, method=intMethod,rule=2)$y %>%
+            paste(.,collapse="\t") %>% paste0(.," ")
+    }
+
+    soilDepth <- tryCatch(getMeanSoil(rest,"bdod")/100,error=function(e){stop("There is no data for the given coordinates")})
+    outFile[55] <- sprintf("%s (%%) percentage of sand by volume in rock free soil",
+                           paste(createMusoLayers(getMeanSoil(rest,"sand")/10), collapse="\t"))
+    outFile[56] <- sprintf("%s (%%) percentage of silt by volume in rock free soil",
+                           paste(createMusoLayers(getMeanSoil(rest,"silt")/10), collapse="\t"))
+    outFile[57] <- sprintf("%s (dimless) soil PH",
+                           paste(createMusoLayers(getMeanSoil(rest,"phh2o")/10), collapse="\t"))
+    # outFile[58] <- sprintf("%s (%%) bulk density",paste(createMusoLayers(soilDepth),collapse="\t"))
+    writeLines(outFile,outputFile)
+}
+# createSoilFile(60,50)
+
+getMeanSoil <- function(rest, name){
+    sapply(
+        rest$properties$layers[sapply(rest$properties$layers,function(x){
+                   x$name == name
+                })][[1]]$depths,
+           function(s){
+                s$values$mean
+           }
+    )
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/spinupMuso.R

@@ -0,0 +1,136 @@
+#' Runs the Biome-BGCMuSo model in spinup phase (execution of normal phase is possible with normalMuso) with debugging features. 
+#'
+#' This function runs the Biome-BGCMuSo model in spinup phase.
+#' 
+#' @author Roland HOLLOS
+#' @param settings RBBGCMuso uses variables that define the entire simulation environment. Those environment variables include the name of the INI files, the name of the meteorology files, the path to the model executable and its file name, the entire output list, the entire output variable matrix, the dependency rules for the EPC parameters etc. Using the runMuso function RBBGCMuso can automatically create those environment variables by inspecting the files in the working directory (this happens through the setupMuso function). It means that by default model setup is performed automatically in the background and the user has nothing to do. With this settings parameter we can force runMuso to skip automatic environment setup as we provide the environment settings to runMuso. In a typical situation the user can skip this option.
+#' @param debugging If debugging is set to TRUE, after model execution the function copies the Biome-BGCMuSo log file into a LOG directory to stores it for further processing. If debugging is set to STAMPLOG instead of TRUE, it concatenates a number before the logfile, which is one plus the maximum of those present in the LOG directory. In each case the log files will be saved.
+#' @param keepEpc If keepEpc is set to TRUE, the function keeps the EPC file and stamps it, and then copies it to the EPCS directory. If debugging is set to TRUE, it copies the wrong EPC files to the wrong epc directory.
+#' @param silent If you set the silent parameter to TRUE, all of the model's output normally written to the screen will be suppressed. This option can be useful to increase the speed of the model execution.
+#' @param aggressive It deletes all previous model-outputs from previous model runs.
+#' @param parameters |||| In the parameters variable you have set the row indices of the variables that you wish to change. In this parameter you can provide an exact value for them in a vector form like c(1,2,3,4)
+#' @param logfilename If you would like to set a specific name for the logfiles you can set this via the logfilename parameter
+#' @return No return, outputs are written to file 
+#' @usage spinupMuso(settings, parameters=NULL, debugging=FALSE,
+#' logfilename=NULL, keepEpc=FALSE, silent=FALSE, aggressive=FALSE)
+#' @export
+
+spinupMuso <- function(settings=NULL, parameters=NULL, debugging=FALSE, logfilename=NULL, keepEpc=FALSE, silent=FALSE, aggressive=FALSE, fileToChange="epc"){
+
+##########################################################################
+###########################Set local variables########################
+########################################################################
+
+    if(is.null(settings)){
+        settings <- setupMuso() #(:INSIDE: setupMuso.R)
+        
+    }
+    # The software works on Linux or Windows, Mac is not implemented yet, so with this simple dichotomy we can determine wich system is running
+    Linuxp <-(Sys.info()[1]=="Linux")
+    ##Copy the variables from settings for the sake of easy
+    inputLoc <- settings$inputLoc
+    outputLoc <- settings$outputLoc
+    outputNames <- settings$outputNames
+    executable <- settings$executable
+    iniInput <- settings$iniInput
+    epc <- settings$epcInput
+    calibrationPar <- settings$calibrationPar
+
+    ## We want to minimize the number of sideeffects so we store the state to restore in the end.
+    whereAmI<-getwd()
+
+
+#############################################################
+############################spinup run############################
+########################################################## 
+
+    ## obsolete feature, but there can be cases in wich this option is helpfull
+    if(aggressive==TRUE){
+        cleanupMuso(location=outputLoc,deep=TRUE)} #(:INSIDE: cleanup.R)
+
+    ## If parameters given, use changemulline, else leave this steps
+    
+     if(!is.null(parameters)){
+        switch(fileToChange,
+               "epc" = tryCatch(changemulline(filename = epc[1],calibrationPar,parameters), #(:INSIDE: changeMuso.R)
+                              error = function (e) {stop("Cannot change the epc file")}),
+               "ini" = tryCatch(changemulline(filename = iniInput[1],calibrationPar,parameters), #(:INSIDE: changeMuso.R)
+                              error = function (e) {stop("Cannot change the ini file")}),
+               "both" = (stop("This option is not implemented yet, please choose epc or ini"))
+               )
+    }
+    
+    ## Set the working directory to the inputLoc temporary.
+    setwd(inputLoc)
+
+    
+    ##Run the spinup modell
+    
+    if(silent){#silenc mode
+        if(Linuxp){
+            #In this case, in linux machines
+            tryCatch(system(paste(executable,iniInput[1],"> /dev/null",sep=" ")),
+                   error= function (e){stop("Cannot run the modell-check the executable!")})
+        } else {
+            #In windows machines there is a show.output.on.console option
+            tryCatch(system(paste(executable,iniInput[1],sep=" "),show.output.on.console = FALSE),
+                     error= function (e){stop("Cannot run the modell-check the executable!")})
+        }} else {
+        system(paste(executable,iniInput[1],sep=" "))
+    }
+###############################################
+#############LOG SECTION#######################
+###############################################
+    
+      logspinup <- getLogs(outputLoc,outputNames,type="spinup") #(:INSIDE: assistantFunctions.R)
+ 
+  if(length(logspinup)==0){
+        if(keepEpc){
+            stampnum<-stamp(EPCS)
+            lapply(epc,function (x) file.copy(from = x ,to=paste(EPCS,"/",(stampnum+1),"-", basename(x),sep="")))
+            lapply(epc, function (x) file.copy(from = paste(EPCS,"/",(stampnum+1),"-",basename(x),sep=""), to=WRONGEPC))
+            setwd(whereAmI)
+            stop("Modell Failure")
+        }
+        setwd(whereAmI)
+        stop("Modell Failure") #in that case the modell did not create even a logfile
+    }
+
+    if(length(logspinup)>1){
+        spincrash<-TRUE
+    } else {
+        if(identical(tail(readLines(paste(outputLoc,logspinup,sep="/"),-1),1),character(0))){
+            spincrash<-TRUE
+        } else {
+            spincrash <- (tail(readLines(paste(outputLoc,logspinup,sep="/"),-1),1)!=1)
+        }
+    }
+
+    dirName<-normalizePath(paste(inputLoc,"/LOG",sep=""))
+    dirERROR<-paste0(inputLoc,"/ERROR")
+    
+    if(!dir.exists(dirName)){
+        dir.create(dirName)}
+
+    if(!dir.exists(dirERROR)){
+        dir.create(dirERROR)}
+
+    if(spincrash){
+        errorsign <- 1
+    } else {
+        errorsign <- 0}
+
+
+
+    if(debugging==TRUE){
+        stampAndDir(outputLoc=outputLoc,stampDir=dirName, names=logspinup, type="output") #(:INSIDE: assistantFunctions.R)
+    }
+
+    
+    
+    if(errorsign==1){
+        stop("Modell Failure")
+    }
+
+    
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/R/stamplog.R

@@ -0,0 +1,33 @@
+#' This function returns only the starting numbers of a string
+#' 
+#' This function returns only the starting numbers of a string
+#' @author Roland Hollos
+#' @keywords internal
+
+numcut<-function(string){
+    #This function returns only the starting numbers of a string
+    unlist(strsplit(grep("^[0-9]",string,value = TRUE),"[aAzZ-]"))[1]
+}
+
+#' numcutall
+#'
+#' apply numcut for all elements of a string vector
+#' @author Roland Hollos
+#' @keywords internal
+numcutall<-function(vector){
+    #numcall apply numcut for all elements of a string vector
+as.numeric(unlist(apply(as.matrix(vector),1,numcut)))
+}
+
+#' It gives back a stamp wich is the maximum number of the output numcall
+#'
+#' It gives back a stamp wich is the maximum number of the output numcall
+#' @author Roland Hollos
+#' @keywords internal
+stamp<-function(path="./"){
+    #It gives back a stamp wich is the maximum number of the output numcall
+    numbers<-numcutall(list.files(path))
+    if(length(numbers)==0){
+        return (0)} else {
+                   return(max(numbers))}
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/inst/data/constMatrix6.json

@@ -0,0 +1,190 @@
+[
+    {"X": "1", "NAME": "yearday to start new growth", "INDEX": "9", "UNIT": "yday", "MIN": "0", "MAX": "364", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "2", "NAME": "yearday to end new growth", "INDEX": "10", "UNIT": "yday", "MIN": "0", "MAX": "364", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "3", "NAME": "transfer growth period as fraction of growing season", "INDEX": "11", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "4", "NAME": "litterfall as fraction of growing season", "INDEX": "12", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "5", "NAME": "base temperature", "INDEX": "13", "UNIT": "Celsius", "MIN": "0", "MAX": "12", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "6", "NAME": "minimum  temperature for growth displayed on current day", "INDEX": "14", "UNIT": "Celsius", "MIN": "0", "MAX": "10", "DEPENDENCE": "0", "GROUP": "1", "TYPE": "1"},
+    {"X": "7", "NAME": "optimal1 temperature for growth displayed on current day", "INDEX": "15", "UNIT": "Celsius", "MIN": "10", "MAX": "20", "DEPENDENCE": "1", "GROUP": "1", "TYPE": "1"},
+    {"X": "8", "NAME": "optimal2 temperature for growth displayed on current day", "INDEX": "16", "UNIT": "Celsius", "MIN": "20", "MAX": "40", "DEPENDENCE": "2", "GROUP": "1", "TYPE": "1"},
+    {"X": "9", "NAME": "maxmimum temperature for growth displayed on current day", "INDEX": "17", "UNIT": "Celsius", "MIN": "30", "MAX": "50", "DEPENDENCE": "3", "GROUP": "1", "TYPE": "1"},
+    {"X": "10", "NAME": "minimum  temperature for carbon assimilation displayed on current day", "INDEX": "18", "UNIT": "Celsius", "MIN": "0", "MAX": "10", "DEPENDENCE": "0", "GROUP": "2", "TYPE": "1"},
+    {"X": "11", "NAME": "optimal1 temperature for carbon assimilation displayed on current day", "INDEX": "19", "UNIT": "Celsius", "MIN": "10", "MAX": "20", "DEPENDENCE": "1", "GROUP": "2", "TYPE": "1"},
+    {"X": "12", "NAME": "optimal2 temperature for carbon assimilation displayed on current day", "INDEX": "20", "UNIT": "Celsius", "MIN": "20", "MAX": "40", "DEPENDENCE": "2", "GROUP": "2", "TYPE": "1"},
+    {"X": "13", "NAME": "maxmimum temperature for carbon assimilation displayed on current day", "INDEX": "21", "UNIT": "Celsius", "MIN": "30", "MAX": "50", "DEPENDENCE": "3", "GROUP": "2", "TYPE": "1"},
+    {"X": "14", "NAME": "annual leaf and fine root turnover fraction", "INDEX": "22", "UNIT": "1/yr", "MIN": "0.1", "MAX": "0.4", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "15", "NAME": "annual live wood turnover fraction", "INDEX": "23", "UNIT": "1/yr", "MIN": "0.5", "MAX": "1", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "16", "NAME": "annual fire mortality fraction", "INDEX": "24", "UNIT": "1/yr", "MIN": "0", "MAX": "1", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "17", "NAME": "whole-plant mortality paramter for vegetation period", "INDEX": "25", "UNIT": "1/vegper", "MIN": "0", "MAX": "0.5", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "18", "NAME": "C:N of leaves", "INDEX": "26", "UNIT": "kgC/kgN", "MIN": "10", "MAX": "100", "DEPENDENCE": "0", "GROUP": "3", "TYPE": "1"},
+    {"X": "19", "NAME": "C:N of leaf litter", "INDEX": "27", "UNIT": "kgC/kgN", "MIN": "10", "MAX": "60", "DEPENDENCE": "1", "GROUP": "3", "TYPE": "1"},
+    {"X": "20", "NAME": "C:N of fine roots", "INDEX": "28", "UNIT": "kgC/kgN", "MIN": "10", "MAX": "60", "DEPENDENCE": "1", "GROUP": "3", "TYPE": "1"},
+    {"X": "21", "NAME": "C:N of fruit", "INDEX": "29", "UNIT": "kgC/kgN", "MIN": "10", "MAX": "60", "DEPENDENCE": "1", "GROUP": "3", "TYPE": "1"},
+    {"X": "22", "NAME": "C:N of softstem", "INDEX": "30", "UNIT": "kgC/kgN", "MIN": "10", "MAX": "60", "DEPENDENCE": "1", "GROUP": "3", "TYPE": "1"},
+    {"X": "23", "NAME": "C:N of live wood", "INDEX": "31", "UNIT": "kgC/kgN", "MIN": "50", "MAX": "100", "DEPENDENCE": "0", "GROUP": "4", "TYPE": "1"},
+    {"X": "24", "NAME": "C:N of dead wood", "INDEX": "32", "UNIT": "kgC/kgN", "MIN": "300", "MAX": "800", "DEPENDENCE": "1", "GROUP": "4", "TYPE": "1"},
+    {"X": "25", "NAME": "dry matter content of leaves", "INDEX": "33", "UNIT": "kgC/kgDM", "MIN": "0.2", "MAX": "0.6", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "26", "NAME": "dry matter content of leaf litter", "INDEX": "34", "UNIT": "kgC/kgDM", "MIN": "0.2", "MAX": "0.6", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "27", "NAME": "dry matter content of fine roots", "INDEX": "35", "UNIT": "kgC/kgDM", "MIN": "0.2", "MAX": "0.6", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "28", "NAME": "dry matter content of fruit", "INDEX": "36", "UNIT": "kgC/kgDM", "MIN": "0.2", "MAX": "0.6", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "29", "NAME": "dry matter content of softstem", "INDEX": "37", "UNIT": "kgC/kgDM", "MIN": "0.2", "MAX": "0.6", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "30", "NAME": "dry matter content of live wood", "INDEX": "38", "UNIT": "kgC/kgDM", "MIN": "0.2", "MAX": "0.6", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "31", "NAME": "dry matter content of dead wood", "INDEX": "39", "UNIT": "kgC/kgDM", "MIN": "0.2", "MAX": "0.6", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "32", "NAME": "leaf litter labile proportion", "INDEX": "40", "UNIT": "prop", "MIN": "0.1", "MAX": "0.6", "DEPENDENCE": "1", "GROUP": "5", "TYPE": "2"},
+    {"X": "33", "NAME": "leaf litter cellulose proportion", "INDEX": "41", "UNIT": "prop", "MIN": "0.1", "MAX": "0.6", "DEPENDENCE": "1", "GROUP": "5", "TYPE": "2"},
+    {"X": "34", "NAME": "fine root labile proportion", "INDEX": "42", "UNIT": "prop", "MIN": "0.1", "MAX": "0.6", "DEPENDENCE": "1", "GROUP": "6", "TYPE": "2"},
+    {"X": "35", "NAME": "fine root cellulose proportion", "INDEX": "43", "UNIT": "prop", "MIN": "0.1", "MAX": "0.6", "DEPENDENCE": "1", "GROUP": "6", "TYPE": "2"},
+    {"X": "36", "NAME": "fruit labile proportion", "INDEX": "44", "UNIT": "prop", "MIN": "0.1", "MAX": "0.6", "DEPENDENCE": "1", "GROUP": "7", "TYPE": "2"},
+    {"X": "37", "NAME": "fruit cellulose proportion", "INDEX": "45", "UNIT": "prop", "MIN": "0.1", "MAX": "0.6", "DEPENDENCE": "1", "GROUP": "7", "TYPE": "2"},
+    {"X": "38", "NAME": "softstem labile proportion", "INDEX": "46", "UNIT": "prop", "MIN": "0.1", "MAX": "0.6", "DEPENDENCE": "1", "GROUP": "8", "TYPE": "2"},
+    {"X": "39", "NAME": "softstem cellulose proportion", "INDEX": "47", "UNIT": "prop", "MIN": "0.1", "MAX": "0.6", "DEPENDENCE": "1", "GROUP": "8", "TYPE": "2"},
+    {"X": "40", "NAME": "dead wood cellulose proportion", "INDEX": "48", "UNIT": "prop", "MIN": "0.5", "MAX": "0.9", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "41", "NAME": "canopy water interception coefficient", "INDEX": "49", "UNIT": "1/LAI/d", "MIN": "0.01", "MAX": "0.1", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "42", "NAME": "canopy light extinction coefficient", "INDEX": "50", "UNIT": "dimless", "MIN": "0.2", "MAX": "0.8", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "43", "NAME": "potential radiation use efficiency", "INDEX": "51", "UNIT": "g/MJ", "MIN": "2", "MAX": "2", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "44", "NAME": "radiation parameter1 (Jiang et al.2015)", "INDEX": "52", "UNIT": "dimless", "MIN": "0.781", "MAX": "0.781", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "45", "NAME": "radiation parameter1 (Jiang et al.2015)", "INDEX": "53", "UNIT": "dimless", "MIN": "-13.596", "MAX": "-13.596", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "46", "NAME": "all-sided to projected leaf area ratio", "INDEX": "54", "UNIT": "dimless", "MIN": "2", "MAX": "2", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "47", "NAME": "ratio of shaded SLA:sunlit SLA", "INDEX": "55", "UNIT": "dimless", "MIN": "2", "MAX": "2", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "48", "NAME": "fraction of leaf N in Rubisco", "INDEX": "56", "UNIT": "dimless", "MIN": "0.01", "MAX": "0.2", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "49", "NAME": "fraction of leaf N in PeP", "INDEX": "57", "UNIT": "dimless", "MIN": "0.0424", "MAX": "0.0424", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "50", "NAME": "maximum stomatal conductance", "INDEX": "58", "UNIT": "m/s", "MIN": "0.001", "MAX": "0.1", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "51", "NAME": "cuticular conductance", "INDEX": "59", "UNIT": "m/s", "MIN": "1E-05", "MAX": "0.0001", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "52", "NAME": "boundary layer conductance", "INDEX": "60", "UNIT": "m/s", "MIN": "0.01", "MAX": "0.09", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "53", "NAME": "maximum height of plant", "INDEX": "61", "UNIT": "m", "MIN": "0.1", "MAX": "10", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "54", "NAME": "stem weight corresponding to maximum height", "INDEX": "62", "UNIT": "kgC", "MIN": "0.1", "MAX": "100", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "55", "NAME": "plant height function shape parameter (slope)", "INDEX": "63", "UNIT": "dimless", "MIN": "0.5", "MAX": "0.5", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "56", "NAME": "maximum depth of rooting zone", "INDEX": "64", "UNIT": "m", "MIN": "0.1", "MAX": "10", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "57", "NAME": "root distribution parameter", "INDEX": "65", "UNIT": "prop", "MIN": "3.67", "MAX": "3.67", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "58", "NAME": "root weight corresponding to max root depth", "INDEX": "66", "UNIT": "kgC/m2", "MIN": "0.4", "MAX": "0.4", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "59", "NAME": "root depth function shape parameter (slope)", "INDEX": "67", "UNIT": "prop", "MIN": "0.5", "MAX": "0.5", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "60", "NAME": "root weight to rooth length conversion factor", "INDEX": "68", "UNIT": "m/kg", "MIN": "1000", "MAX": "1000", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "61", "NAME": "growth resp per unit of C grown", "INDEX": "69", "UNIT": "prop", "MIN": "0.1", "MAX": "0.5", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "62", "NAME": "maintenance respiration in kgC/day per kg of tissue N", "INDEX": "70", "UNIT": "kgC/kgN/d", "MIN": "0.1", "MAX": "0.5", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "63", "NAME": "theoretical maximum prop. of non-structural and structural carbohydrates", "INDEX": "71", "UNIT": "dimless", "MIN": "0", "MAX": "1", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "64", "NAME": "prop. of non-structural carbohydrates available for maintanance resp", "INDEX": "72", "UNIT": "dimless", "MIN": "0", "MAX": "1", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "65", "NAME": "symbiotic+asymbiotic fixation of N", "INDEX": "73", "UNIT": "kgN/m2/yr", "MIN": "0", "MAX": "0.001", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "66", "NAME": "time delay for temperature in photosynthesis acclimation", "INDEX": "74", "UNIT": "day", "MIN": "0", "MAX": "50", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "67", "NAME": "critical VWCratio (prop. to FC-WP) in germination", "INDEX": "79", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "68", "NAME": "critical photoslow daylength", "INDEX": "81", "UNIT": "hour", "MIN": "14", "MAX": "18", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "69", "NAME": "slope of relative photoslow development rate", "INDEX": "82", "UNIT": "dimless", "MIN": "0.005", "MAX": "0.005", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "70", "NAME": "critical vernalization temperature 1", "INDEX": "84", "UNIT": "Celsius", "MIN": "-5", "MAX": "5", "DEPENDENCE": "0", "GROUP": "9", "TYPE": "1"},
+    {"X": "71", "NAME": "critical vernalization temperature 2", "INDEX": "85", "UNIT": "Celsius", "MIN": "0", "MAX": "10", "DEPENDENCE": "1", "GROUP": "9", "TYPE": "1"},
+    {"X": "72", "NAME": "critical vernalization temperature 3", "INDEX": "86", "UNIT": "Celsius", "MIN": "5", "MAX": "15", "DEPENDENCE": "2", "GROUP": "9", "TYPE": "1"},
+    {"X": "73", "NAME": "critical vernalization temperature 4", "INDEX": "87", "UNIT": "Celsius", "MIN": "10", "MAX": "20", "DEPENDENCE": "3", "GROUP": "9", "TYPE": "1"},
+    {"X": "74", "NAME": "slope of relative vernalization development rate", "INDEX": "88", "UNIT": "dimless", "MIN": "0.04", "MAX": "0.04", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "75", "NAME": "required vernalization days (in vernalization development rate)", "INDEX": "89", "UNIT": "dimless", "MIN": "30", "MAX": "70", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "76", "NAME": "critical flowering heat stress temperature 1", "INDEX": "91", "UNIT": "Celsius", "MIN": "30", "MAX": "40", "DEPENDENCE": "0", "GROUP": "10", "TYPE": "1"},
+    {"X": "77", "NAME": "critical flowering heat stress temperature 2", "INDEX": "92", "UNIT": "Celsius", "MIN": "30", "MAX": "50", "DEPENDENCE": "1", "GROUP": "10", "TYPE": "1"},
+    {"X": "78", "NAME": "theoretical maximum of flowering thermal stress mortality", "INDEX": "93", "UNIT": "prop", "MIN": "0", "MAX": "0.4", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "79", "NAME": "VWC ratio to calc. soil moisture limit 1 (prop. to FC-WP)", "INDEX": "96", "UNIT": "prop", "MIN": "0.5", "MAX": "1", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "80", "NAME": "VWC ratio to calc. soil moisture limit 2 (prop. to SAT-FC)", "INDEX": "97", "UNIT": "prop", "MIN": "0.5", "MAX": "1", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "81", "NAME": "minimum of soil moisture limit2 multiplicator (full anoxic stress value)", "INDEX": "98", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "82", "NAME": "vapor pressure deficit: start of conductance reduction", "INDEX": "99", "UNIT": "Pa", "MIN": "500", "MAX": "1500", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "83", "NAME": "vapor pressure deficit: complete conductance reduction", "INDEX": "100", "UNIT": "Pa", "MIN": "1500", "MAX": "3500", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "84", "NAME": "maximum senescence mortality coefficient of aboveground plant material", "INDEX": "101", "UNIT": "prop", "MIN": "0", "MAX": "0.1", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "85", "NAME": "maximum senescence mortality coefficient of belowground plant material", "INDEX": "102", "UNIT": "prop", "MIN": "0", "MAX": "0.1", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "86", "NAME": "maximum senescence mortality coefficient of non-structured plant material", "INDEX": "103", "UNIT": "prop", "MIN": "0", "MAX": "0.1", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "87", "NAME": "lower limit extreme high temperature effect on senescence mortality", "INDEX": "104", "UNIT": "Celsius", "MIN": "30", "MAX": "40", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "88", "NAME": "upper limit extreme high temperature effect on senescence mortality", "INDEX": "105", "UNIT": "Celsius", "MIN": "30", "MAX": "50", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "89", "NAME": "turnover rate of wilted standing biomass to litter", "INDEX": "106", "UNIT": "prop", "MIN": "0", "MAX": "0.1", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "90", "NAME": "turnover rate of cut-down non-woody biomass to litter", "INDEX": "107", "UNIT": "prop", "MIN": "0", "MAX": "0.1", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "91", "NAME": "turnover rate of cut-down woody biomass to litter", "INDEX": "108", "UNIT": "prop", "MIN": "0", "MAX": "0.1", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "92", "NAME": "drought tolerance parameter (critical value of day since water stress)", "INDEX": "109", "UNIT": "n_day", "MIN": "0", "MAX": "100", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "93", "NAME": "crit. amount of snow limiting photosyn.", "INDEX": "112", "UNIT": "kg/m2", "MIN": "0", "MAX": "20", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "94", "NAME": "limit1 (under:full constrained) of HEATSUM index", "INDEX": "113", "UNIT": "Celsius", "MIN": "0", "MAX": "50", "DEPENDENCE": "0", "GROUP": "11", "TYPE": "1"},
+    {"X": "95", "NAME": "limit2 (above:unconstrained) of HEATSUM index", "INDEX": "114", "UNIT": "Celsius", "MIN": "0", "MAX": "100", "DEPENDENCE": "1", "GROUP": "11", "TYPE": "1"},
+    {"X": "96", "NAME": "limit1 (under:full constrained) of TMIN index", "INDEX": "115", "UNIT": "Celsius", "MIN": "-5", "MAX": "5", "DEPENDENCE": "0", "GROUP": "12", "TYPE": "1"},
+    {"X": "97", "NAME": "limit2 (above:unconstrained) of TMIN index", "INDEX": "116", "UNIT": "Celsius", "MIN": "0", "MAX": "10", "DEPENDENCE": "1", "GROUP": "12", "TYPE": "1"},
+    {"X": "98", "NAME": "limit1 (above:full constrained) of VPD index", "INDEX": "117", "UNIT": "Pa", "MIN": "2000", "MAX": "600", "DEPENDENCE": "0", "GROUP": "13", "TYPE": "1"},
+    {"X": "99", "NAME": "limit2 (under:unconstrained) of VPD index", "INDEX": "118", "UNIT": "Pa", "MIN": "500", "MAX": "1500", "DEPENDENCE": "1", "GROUP": "13", "TYPE": "1"},
+    {"X": "100", "NAME": "limit1 (under:full constrained) of DAYLENGTH index", "INDEX": "119", "UNIT": "s", "MIN": "0", "MAX": "0", "DEPENDENCE": "0", "GROUP": "14", "TYPE": "1"},
+    {"X": "101", "NAME": "limit2 (above:unconstrained) of DAYLENGTH index", "INDEX": "120", "UNIT": "s", "MIN": "0", "MAX": "0", "DEPENDENCE": "1", "GROUP": "14", "TYPE": "1"},
+    {"X": "102", "NAME": "moving average (to avoid the effects of extreme events)", "INDEX": "121", "UNIT": "n_day", "MIN": "2", "MAX": "20", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "103", "NAME": "GSI limit1 (greater that limit -> start of vegper)", "INDEX": "122", "UNIT": "dimless", "MIN": "0", "MAX": "0.2", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "104", "NAME": "GSI limit2 (less that limit -> end of vegper)", "INDEX": "123", "UNIT": "dimless", "MIN": "0", "MAX": "0.1", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "105", "NAME": "length of phenophase (GDD)-0", "INDEX": "127.6", "UNIT": "Celsius", "MIN": "0", "MAX": "10000", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "106", "NAME": "leaf ALLOCATION -0", "INDEX": "128.6", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "15", "TYPE": "-3"},
+    {"X": "107", "NAME": "fine root ALLOCATION-0", "INDEX": "129.6", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "15", "TYPE": "-3"},
+    {"X": "108", "NAME": "fruit ALLOCATION -0", "INDEX": "130.6", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "15", "TYPE": "-3"},
+    {"X": "109", "NAME": "soft stem ALLOCATION-0", "INDEX": "131.6", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "15", "TYPE": "-3"},
+    {"X": "110", "NAME": "live woody stem ALLOCATION -0", "INDEX": "132.6", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "15", "TYPE": "-3"},
+    {"X": "111", "NAME": "dead woody stem ALLOCATION -0", "INDEX": "133.6", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "15", "TYPE": "-3"},
+    {"X": "112", "NAME": "live coarse root ALLOCATION-0", "INDEX": "134.6", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "15", "TYPE": "-3"},
+    {"X": "113", "NAME": "dead coarse root ALLOCATION -0", "INDEX": "135.6", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "15", "TYPE": "-3"},
+    {"X": "114", "NAME": "canopy average specific leaf area-0", "INDEX": "136.6", "UNIT": "m2/kg", "MIN": "0", "MAX": "2", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "115", "NAME": "current growth proportion-0", "INDEX": "137.6", "UNIT": "prop", "MIN": "0", "MAX": "0", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "116", "NAME": "maximal lifetime of plant tissue-0", "INDEX": "138.6", "UNIT": "Celsius", "MIN": "1", "MAX": "20000", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "105", "NAME": "length of phenophase (GDD)-1", "INDEX": "127.61", "UNIT": "Celsius", "MIN": "0", "MAX": "10000", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "106", "NAME": "leaf ALLOCATION -1", "INDEX": "128.61", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "16", "TYPE": "-3"},
+    {"X": "107", "NAME": "fine root ALLOCATION-1", "INDEX": "129.61", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "16", "TYPE": "-3"},
+    {"X": "108", "NAME": "fruit ALLOCATION -1", "INDEX": "130.61", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "16", "TYPE": "-3"},
+    {"X": "109", "NAME": "soft stem ALLOCATION-1", "INDEX": "131.61", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "16", "TYPE": "-3"},
+    {"X": "110", "NAME": "live woody stem ALLOCATION -1", "INDEX": "132.61", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "16", "TYPE": "-3"},
+    {"X": "111", "NAME": "dead woody stem ALLOCATION -1", "INDEX": "133.61", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "16", "TYPE": "-3"},
+    {"X": "112", "NAME": "live coarse root ALLOCATION-1", "INDEX": "134.61", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "16", "TYPE": "-3"},
+    {"X": "113", "NAME": "dead coarse root ALLOCATION -1", "INDEX": "135.61", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "16", "TYPE": "-3"},
+    {"X": "114", "NAME": "canopy average specific leaf area-1", "INDEX": "136.61", "UNIT": "m2/kg", "MIN": "0", "MAX": "2", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "115", "NAME": "current growth proportion-1", "INDEX": "137.61", "UNIT": "prop", "MIN": "0", "MAX": "0", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "116", "NAME": "maximal lifetime of plant tissue-1", "INDEX": "138.61", "UNIT": "Celsius", "MIN": "1", "MAX": "20000", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "105", "NAME": "length of phenophase (GDD)-2", "INDEX": "127.62", "UNIT": "Celsius", "MIN": "0", "MAX": "10000", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "106", "NAME": "leaf ALLOCATION -2", "INDEX": "128.62", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "17", "TYPE": "-3"},
+    {"X": "107", "NAME": "fine root ALLOCATION-2", "INDEX": "129.62", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "17", "TYPE": "-3"},
+    {"X": "108", "NAME": "fruit ALLOCATION -2", "INDEX": "130.62", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "17", "TYPE": "-3"},
+    {"X": "109", "NAME": "soft stem ALLOCATION-2", "INDEX": "131.62", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "17", "TYPE": "-3"},
+    {"X": "110", "NAME": "live woody stem ALLOCATION -2", "INDEX": "132.62", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "17", "TYPE": "-3"},
+    {"X": "111", "NAME": "dead woody stem ALLOCATION -2", "INDEX": "133.62", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "17", "TYPE": "-3"},
+    {"X": "112", "NAME": "live coarse root ALLOCATION-2", "INDEX": "134.62", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "17", "TYPE": "-3"},
+    {"X": "113", "NAME": "dead coarse root ALLOCATION -2", "INDEX": "135.62", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "17", "TYPE": "-3"},
+    {"X": "114", "NAME": "canopy average specific leaf area-2", "INDEX": "136.62", "UNIT": "m2/kg", "MIN": "0", "MAX": "2", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "115", "NAME": "current growth proportion-2", "INDEX": "137.62", "UNIT": "prop", "MIN": "0", "MAX": "0", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "116", "NAME": "maximal lifetime of plant tissue-2", "INDEX": "138.62", "UNIT": "Celsius", "MIN": "1", "MAX": "20000", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "105", "NAME": "length of phenophase (GDD)-3", "INDEX": "127.63", "UNIT": "Celsius", "MIN": "0", "MAX": "10000", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "106", "NAME": "leaf ALLOCATION -3", "INDEX": "128.63", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "18", "TYPE": "-3"},
+    {"X": "107", "NAME": "fine root ALLOCATION-3", "INDEX": "129.63", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "18", "TYPE": "-3"},
+    {"X": "108", "NAME": "fruit ALLOCATION -3", "INDEX": "130.63", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "18", "TYPE": "-3"},
+    {"X": "109", "NAME": "soft stem ALLOCATION-3", "INDEX": "131.63", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "18", "TYPE": "-3"},
+    {"X": "110", "NAME": "live woody stem ALLOCATION -3", "INDEX": "132.63", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "18", "TYPE": "-3"},
+    {"X": "111", "NAME": "dead woody stem ALLOCATION -3", "INDEX": "133.63", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "18", "TYPE": "-3"},
+    {"X": "112", "NAME": "live coarse root ALLOCATION-3", "INDEX": "134.63", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "18", "TYPE": "-3"},
+    {"X": "113", "NAME": "dead coarse root ALLOCATION -3", "INDEX": "135.63", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "18", "TYPE": "-3"},
+    {"X": "114", "NAME": "canopy average specific leaf area-3", "INDEX": "136.63", "UNIT": "m2/kg", "MIN": "0", "MAX": "2", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "115", "NAME": "current growth proportion-3", "INDEX": "137.63", "UNIT": "prop", "MIN": "0", "MAX": "0", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "116", "NAME": "maximal lifetime of plant tissue-3", "INDEX": "138.63", "UNIT": "Celsius", "MIN": "1", "MAX": "20000", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "105", "NAME": "length of phenophase (GDD)-4", "INDEX": "127.64", "UNIT": "Celsius", "MIN": "0", "MAX": "10000", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "106", "NAME": "leaf ALLOCATION -4", "INDEX": "128.64", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "19", "TYPE": "-3"},
+    {"X": "107", "NAME": "fine root ALLOCATION-4", "INDEX": "129.64", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "19", "TYPE": "-3"},
+    {"X": "108", "NAME": "fruit ALLOCATION -4", "INDEX": "130.64", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "19", "TYPE": "-3"},
+    {"X": "109", "NAME": "soft stem ALLOCATION-4", "INDEX": "131.64", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "19", "TYPE": "-3"},
+    {"X": "110", "NAME": "live woody stem ALLOCATION -4", "INDEX": "132.64", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "19", "TYPE": "-3"},
+    {"X": "111", "NAME": "dead woody stem ALLOCATION -4", "INDEX": "133.64", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "19", "TYPE": "-3"},
+    {"X": "112", "NAME": "live coarse root ALLOCATION-4", "INDEX": "134.64", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "19", "TYPE": "-3"},
+    {"X": "113", "NAME": "dead coarse root ALLOCATION -4", "INDEX": "135.64", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "19", "TYPE": "-3"},
+    {"X": "114", "NAME": "canopy average specific leaf area-4", "INDEX": "136.64", "UNIT": "m2/kg", "MIN": "0", "MAX": "2", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "115", "NAME": "current growth proportion-4", "INDEX": "137.64", "UNIT": "prop", "MIN": "0", "MAX": "0", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "116", "NAME": "maximal lifetime of plant tissue-4", "INDEX": "138.64", "UNIT": "Celsius", "MIN": "1", "MAX": "20000", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "105", "NAME": "length of phenophase (GDD)-5", "INDEX": "127.65", "UNIT": "Celsius", "MIN": "0", "MAX": "10000", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "106", "NAME": "leaf ALLOCATION -5", "INDEX": "128.65", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "20", "TYPE": "-3"},
+    {"X": "107", "NAME": "fine root ALLOCATION-5", "INDEX": "129.65", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "20", "TYPE": "-3"},
+    {"X": "108", "NAME": "fruit ALLOCATION -5", "INDEX": "130.65", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "20", "TYPE": "-3"},
+    {"X": "109", "NAME": "soft stem ALLOCATION-5", "INDEX": "131.65", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "20", "TYPE": "-3"},
+    {"X": "110", "NAME": "live woody stem ALLOCATION -5", "INDEX": "132.65", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "20", "TYPE": "-3"},
+    {"X": "111", "NAME": "dead woody stem ALLOCATION -5", "INDEX": "133.65", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "20", "TYPE": "-3"},
+    {"X": "112", "NAME": "live coarse root ALLOCATION-5", "INDEX": "134.65", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "20", "TYPE": "-3"},
+    {"X": "113", "NAME": "dead coarse root ALLOCATION -5", "INDEX": "135.65", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "20", "TYPE": "-3"},
+    {"X": "114", "NAME": "canopy average specific leaf area-5", "INDEX": "136.65", "UNIT": "m2/kg", "MIN": "0", "MAX": "2", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "115", "NAME": "current growth proportion-5", "INDEX": "137.65", "UNIT": "prop", "MIN": "0", "MAX": "0", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "116", "NAME": "maximal lifetime of plant tissue-5", "INDEX": "138.65", "UNIT": "Celsius", "MIN": "1", "MAX": "20000", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "105", "NAME": "length of phenophase (GDD)-6", "INDEX": "127.6", "UNIT": "Celsius", "MIN": "0", "MAX": "10000", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "106", "NAME": "leaf ALLOCATION -6", "INDEX": "128.66", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "21", "TYPE": "-3"},
+    {"X": "107", "NAME": "fine root ALLOCATION-6", "INDEX": "129.66", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "21", "TYPE": "-3"},
+    {"X": "108", "NAME": "fruit ALLOCATION -6", "INDEX": "130.66", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "21", "TYPE": "-3"},
+    {"X": "109", "NAME": "soft stem ALLOCATION-6", "INDEX": "131.66", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "21", "TYPE": "-3"},
+    {"X": "110", "NAME": "live woody stem ALLOCATION -6", "INDEX": "132.66", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "21", "TYPE": "-3"},
+    {"X": "111", "NAME": "dead woody stem ALLOCATION -6", "INDEX": "133.66", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "21", "TYPE": "-3"},
+    {"X": "112", "NAME": "live coarse root ALLOCATION-6", "INDEX": "134.66", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "21", "TYPE": "-3"},
+    {"X": "113", "NAME": "dead coarse root ALLOCATION -6", "INDEX": "135.66", "UNIT": "prop", "MIN": "0", "MAX": "1", "DEPENDENCE": "1", "GROUP": "21", "TYPE": "-3"},
+    {"X": "114", "NAME": "canopy average specific leaf area-6", "INDEX": "136.66", "UNIT": "m2/kg", "MIN": "0", "MAX": "2", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "115", "NAME": "current growth proportion-6", "INDEX": "137.66", "UNIT": "prop", "MIN": "0", "MAX": "0", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"},
+    {"X": "116", "NAME": "maximal lifetime of plant tissue-6", "INDEX": "138.66", "UNIT": "Celsius", "MIN": "1", "MAX": "20000", "DEPENDENCE": "NA", "GROUP": "0", "TYPE": "0"}
+]

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/inst/data/depTree.csv

@@ -0,0 +1,18 @@
+"child","parent","mod","name"
+"wth","ini",1,"weather"
+"endpoint","ini",1,"endpointIn"
+"endpoint","ini",2,"endpointOut"
+"txt","ini",1,"co2"
+"txt","ini",2,"nitrogen"
+"soi","ini",1,"soil"
+"epc","ini",1,"startEpc"
+"mgm","ini",1,"management"
+"plt","mgm",1,"planting"
+"thn","mgm",1,"thining"
+"mow","mgm",1,"mowing"
+"grz","mgm",1,"grazing"
+"hrv","mgm",1,"harvest"
+"cul","mgm",1,"cultivation"
+"frz","mgm",1,"fertilization"
+"irr","mgm",1,"irrigation"
+"epc","plt",0,"plantEpc"

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/inst/doc/my-vignette.R

@@ -0,0 +1,7 @@
+## ---- fig.show='hold'---------------------------------------------------------
+plot(1:10)
+plot(10:1)
+
+## ---- echo=FALSE, results='asis'----------------------------------------------
+knitr::kable(head(mtcars, 10))
+

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/inst/doc/my-vignette.Rmd

@@ -0,0 +1,58 @@
+---
+title: "Vignette Title"
+author: "Vignette Author"
+date: "`r Sys.Date()`"
+output: rmarkdown::html_vignette
+vignette: >
+  %\VignetteIndexEntry{Vignette Title}
+  %\VignetteEngine{knitr::rmarkdown}
+  %\VignetteEncoding{UTF-8}
+---
+
+Vignettes are long form documentation commonly included in packages. Because they are part of the distribution of the package, they need to be as compact as possible. The `html_vignette` output type provides a custom style sheet (and tweaks some options) to ensure that the resulting html is as small as possible. The `html_vignette` format:
+
+- Never uses retina figures
+- Has a smaller default figure size
+- Uses a custom CSS stylesheet instead of the default Twitter Bootstrap style
+
+## Vignette Info
+
+Note the various macros within the `vignette` section of the metadata block above. These are required in order to instruct R how to build the vignette. Note that you should change the `title` field and the `\VignetteIndexEntry` to match the title of your vignette.
+
+## Styles
+
+The `html_vignette` template includes a basic CSS theme. To override this theme you can specify your own CSS in the document metadata as follows:
+
+    output: 
+      rmarkdown::html_vignette:
+        css: mystyles.css
+
+## Figures
+
+The figure sizes have been customised so that you can easily put two images side-by-side. 
+
+```{r, fig.show='hold'}
+plot(1:10)
+plot(10:1)
+```
+
+You can enable figure captions by `fig_caption: yes` in YAML:
+
+    output:
+      rmarkdown::html_vignette:
+        fig_caption: yes
+
+Then you can use the chunk option `fig.cap = "Your figure caption."` in **knitr**.
+
+## More Examples
+
+You can write math expressions, e.g. $Y = X\beta + \epsilon$, footnotes^[A footnote here.], and tables, e.g. using `knitr::kable()`.
+
+```{r, echo=FALSE, results='asis'}
+knitr::kable(head(mtcars, 10))
+```
+
+Also a quote using `>`:
+
+> "He who gives up [code] safety for [code] speed deserves neither."
+([via](https://twitter.com/hadleywickham/status/504368538874703872))

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/inst/examples/hhs/CO2.txt

@@ -0,0 +1,119 @@
+ 1900  296.10
+ 1901  296.10
+ 1902  296.50
+ 1903  296.80
+ 1904  297.20
+ 1905  297.60
+ 1906  298.10
+ 1907  298.50
+ 1908  298.90
+ 1909  299.30
+ 1910  299.70
+ 1911  300.10
+ 1912  300.40
+ 1913  300.80
+ 1914  301.10
+ 1915  301.40
+ 1916  301.70
+ 1917  302.10
+ 1918  302.40
+ 1919  302.70
+ 1920  303.00
+ 1921  303.40
+ 1922  303.80
+ 1923  304.10
+ 1924  304.50
+ 1925  305.00
+ 1926  305.40
+ 1927  305.80
+ 1928  306.30
+ 1929  306.80
+ 1930  307.20
+ 1931  307.70
+ 1932  308.20
+ 1933  308.60
+ 1934  309.00
+ 1935  309.40
+ 1936  309.80
+ 1937  310.00
+ 1938  310.20
+ 1939  310.30
+ 1940  310.40
+ 1941  310.40
+ 1942  310.30
+ 1943  310.20
+ 1944  310.10
+ 1945  310.10
+ 1946  310.10
+ 1947  310.20
+ 1948  310.30
+ 1949  310.50
+ 1950  310.70
+ 1951  311.10
+ 1952  311.50
+ 1953  311.90
+ 1954  312.40
+ 1955  313.00
+ 1956  313.60
+ 1957  314.20
+ 1958  314.90
+ 1959  315.79
+ 1960  316.61
+ 1961  317.33
+ 1962  318.08
+ 1963  318.70
+ 1964  319.36
+ 1965  320.02
+ 1966  321.09
+ 1967  321.99
+ 1968  322.93
+ 1969  324.21
+ 1970  325.24
+ 1971  326.06
+ 1972  327.18
+ 1973  328.84
+ 1974  329.73
+ 1975  330.73
+ 1976  331.83
+ 1977  333.25
+ 1978  334.60
+ 1979  336.85
+ 1980  338.69
+ 1981  339.93
+ 1982  341.13
+ 1983  342.78
+ 1984  344.42
+ 1985  345.90
+ 1986  347.15
+ 1987  348.93
+ 1988  351.48
+ 1989  352.91
+ 1990  354.19
+ 1991  355.59
+ 1992  356.37
+ 1993  357.04
+ 1994  358.88
+ 1995  360.88
+ 1996  362.64
+ 1997  363.76
+ 1998  366.63
+ 1999  368.31
+ 2000  369.48
+ 2001  372.59
+ 2002  374.37
+ 2003  378.04
+ 2004  380.88
+ 2005  383.88
+ 2006  385.64
+ 2007  385.76
+ 2008  386.13
+ 2009  387.37
+ 2010  389.85
+ 2011  391.62
+ 2012  393.82
+ 2013  396.48
+ 2014  398.61
+ 2015  400.00
+ 2016  401.00
+ 2017  402.00
+ 2018  404.00

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/inst/examples/hhs/HU-He2_2012_MEASURED.txt

@@ -0,0 +1,367 @@
+  yyyy      mm      dd         NEE         GPP         TER          LE    flag
+  2012       1       1       0.440       0.284       0.724       0.030       0
+  2012       1       2       0.540       0.486       1.026       0.222       0
+  2012       1       3       0.716       0.313       1.030       0.002       0
+  2012       1       4       0.627       0.468       1.095       0.055       0
+  2012       1       5       0.868       0.080       0.948       0.061       0
+  2012       1       6       0.077       0.751       0.828       0.372       0
+  2012       1       7       0.396       0.394       0.791       0.219       0
+  2012       1       8       0.110       0.767       0.877       0.125       0
+  2012       1       9       0.239       0.771       1.010       0.182       0
+  2012       1      10       0.207       0.732       0.938       0.271       0
+  2012       1      11       0.115       1.043       1.158       0.173       0
+  2012       1      12       0.509       0.443       0.952       0.351       0
+  2012       1      13       0.245       0.694       0.940       0.294       0
+  2012       1      14       0.509       0.521       1.030       0.192       0
+  2012       1      15       0.516       0.521       1.037       0.120       0
+  2012       1      16       0.142       0.630       0.772       0.195       0
+  2012       1      17       0.423       0.333       0.756       0.172       0
+  2012       1      18       0.277       0.586       0.863       0.256       0
+  2012       1      19       0.609       0.264       0.873       0.179       0
+  2012       1      20       0.853       0.191       1.043       0.028       0
+  2012       1      21       1.004       0.345       1.349       0.240       0
+  2012       1      22       0.658       0.828       1.486       0.313       0
+  2012       1      23       0.339       0.739       1.078       0.153       0
+  2012       1      24       0.281       0.752       1.032       0.045       0
+  2012       1      25       0.275       0.612       0.886       0.234       0
+  2012       1      26       0.098       0.614       0.712       0.189       0
+  2012       1      27       0.065       0.526       0.591       0.198       0
+  2012       1      28       0.270       0.307       0.577       0.101       0
+  2012       1      29       0.180       0.327       0.507       0.062       0
+  2012       1      30       0.916       0.371       1.287       0.086       0
+  2012       1      31       0.462       0.159       0.621       0.119       0
+  2012       2       1   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       2       2   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       2       3   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       2       4   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       2       5   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       2       6   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       2       7   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       2       8   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       2       9   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       2      10   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       2      11   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       2      12   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       2      13   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       2      14   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       2      15   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       2      16   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       2      17   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       2      18   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       2      19   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       2      20       0.263       0.396       0.660       0.255       0
+  2012       2      21       0.517       0.294       0.811       0.450       0
+  2012       2      22       0.497       0.381       0.878       0.340       0
+  2012       2      23       0.593       0.362       0.955       0.254       0
+  2012       2      24       0.361       0.510       0.872       0.491       0
+  2012       2      25       1.043       0.667       1.710       0.435       0
+  2012       2      26       0.471       0.545       1.016       0.287       0
+  2012       2      27       0.208       0.616       0.825       0.416       0
+  2012       2      28       0.421       0.399       0.820       0.092       0
+  2012       2      29       1.095       0.905       2.000       0.336       0
+  2012       3       1       0.458       1.085       1.542       0.146       0
+  2012       3       2       1.019       1.193       2.212       0.515       0
+  2012       3       3       0.848       1.016       1.865       0.681       0
+  2012       3       4       0.043       1.019       1.063       0.478       0
+  2012       3       5       0.326       0.870       1.196       0.502       0
+  2012       3       6       0.478       0.837       1.315       0.495       0
+  2012       3       7       0.206       0.470       0.675       0.332       0
+  2012       3       8       0.117       0.888       1.005       0.400       0
+  2012       3       9      -0.025       1.098       1.074       0.476       0
+  2012       3      10       0.449       1.011       1.460       0.587       0
+  2012       3      11       1.073       0.594       1.667       0.219       0
+  2012       3      12       1.044       0.590       1.634       0.047       0
+  2012       3      13       0.517       1.387       1.904       0.408       0
+  2012       3      14       0.166       1.769       1.935       0.505       0
+  2012       3      15       0.412       1.703       2.115       0.599       0
+  2012       3      16       0.244       1.535       1.779       0.483       0
+  2012       3      17       0.908       1.756       2.664       0.687       0
+  2012       3      18       0.885       1.659       2.544       0.539       0
+  2012       3      19      -0.386       2.395       2.009       0.502       0
+  2012       3      20      -0.606       2.823       2.217       0.859       0
+  2012       3      21       0.268       2.692       2.960       0.995       0
+  2012       3      22      -0.066       2.926       2.861       0.886       0
+  2012       3      23       0.009       3.536       3.545       0.854       0
+  2012       3      24       0.148       3.509       3.658       0.906       0
+  2012       3      25      -0.373       4.010       3.638       1.150       0
+  2012       3      26      -0.715       3.039       2.325       0.854       0
+  2012       3      27      -1.472       4.040       2.568       1.404       0
+  2012       3      28      -1.693       4.342       2.649       1.060       0
+  2012       3      29       0.028       3.126       3.155       0.736       0
+  2012       3      30       0.353       2.246       2.598       0.348       0
+  2012       3      31      -1.879       5.469       3.589       1.439       0
+  2012       4       1      -2.075       3.925       1.849       0.868       0
+  2012       4       2      -1.823       3.726       1.903       0.912       0
+  2012       4       3      -1.644       4.712       3.068       1.198       0
+  2012       4       4      -1.513       5.074       3.562       1.154       0
+  2012       4       5      -1.560       5.514       3.954       1.246       0
+  2012       4       6       1.817       1.514       3.331       0.048       0
+  2012       4       7       2.102       1.280       3.382       1.149       0
+  2012       4       8      -1.261       4.121       2.861       1.043       0
+  2012       4       9      -0.849       3.436       2.586       1.254       0
+  2012       4      10      -1.403       4.031       2.628       1.119       0
+  2012       4      11      -2.714       5.045       2.331       0.973       0
+  2012       4      12      -0.814       3.435       2.621       0.371       0
+  2012       4      13      -1.430       5.563       4.133       1.196       0
+  2012       4      14       0.886       3.198       4.085       0.124       0
+  2012       4      15      -1.468       5.235       3.767       0.354       0
+  2012       4      16      -0.391       3.663       3.272       0.408       0
+  2012       4      17      -2.404       5.576       3.172       0.967       0
+  2012       4      18      -2.231       5.599       3.368       0.857       0
+  2012       4      19      -4.172       7.629       3.457       1.407       0
+  2012       4      20      -3.302       7.423       4.121       1.344       0
+  2012       4      21      -2.392       6.356       3.965       0.839       0
+  2012       4      22      -1.016       4.731       3.715       0.532       0
+  2012       4      23      -3.809       7.395       3.586       0.974       0
+  2012       4      24      -2.960       6.773       3.813       0.612       0
+  2012       4      25      -4.338       8.789       4.451       2.042       0
+  2012       4      26      -5.087      10.121       5.034       2.478       0
+  2012       4      27      -4.817       8.607       3.790       2.461       0
+  2012       4      28      -4.396       8.659       4.263       2.372       0
+  2012       4      29      -6.780      10.393       3.613       2.607       0
+  2012       4      30      -6.309       9.668       3.358       2.703       0
+  2012       5       1      -3.619       8.815       5.196       2.805       0
+  2012       5       2      -4.568      10.142       5.574       2.899       0
+  2012       5       3      -3.377       7.731       4.355       1.086       0
+  2012       5       4      -0.910       5.555       4.645       0.711       0
+  2012       5       5      -5.536      11.269       5.733       2.516       0
+  2012       5       6      -6.022      11.611       5.589       2.154       0
+  2012       5       7      -1.552       6.454       4.903       0.780       0
+  2012       5       8      -4.539      11.023       6.485       2.654       0
+  2012       5       9      -6.838      12.291       5.453       2.248       0
+  2012       5      10      -6.109      13.095       6.986       2.653       0
+  2012       5      11      -6.404      13.728       7.324       2.453       0
+  2012       5      12      -3.041      11.038       7.998       1.494       0
+  2012       5      13      -2.685       8.466       5.781       1.701       0
+  2012       5      14      -1.911       7.159       5.247       0.614       0
+  2012       5      15      -4.420      10.143       5.723       1.881       0
+  2012       5      16      -2.677       7.455       4.778       0.899       0
+  2012       5      17      -4.086       8.456       4.370       1.535       0
+  2012       5      18      -2.892       8.133       5.241       1.827       0
+  2012       5      19      -3.103       9.789       6.686       2.036       0
+  2012       5      20      -3.446      10.774       7.328       1.722       0
+  2012       5      21      -1.290       8.958       7.668       0.755       0
+  2012       5      22       2.787       3.587       6.373       1.697       0
+  2012       5      23      -0.447       9.872       9.425       1.763       0
+  2012       5      24       0.187      10.434      10.622       2.221       0
+  2012       5      25      -1.949      10.115       8.166       2.603       0
+  2012       5      26       0.660       5.055       5.715       1.618       0
+  2012       5      27       2.652       3.893       6.545       1.588       0
+  2012       5      28       1.376       4.117       5.492       0.978       0
+  2012       5      29       1.416       4.619       6.035       1.400       0
+  2012       5      30       2.294       4.686       6.981       1.480       0
+  2012       5      31       4.244       2.414       6.659       1.549       0
+  2012       6       1       5.654       1.717       7.371       1.859       0
+  2012       6       2      -0.535       6.426       5.891       0.618       0
+  2012       6       3      -2.344      10.030       7.686       2.302       0
+  2012       6       4       1.526       5.390       6.916       1.171       0
+  2012       6       5       3.911       2.762       6.673       1.908       0
+  2012       6       6      -2.767       7.480       4.713       1.747       0
+  2012       6       7      -0.002       5.994       5.993       2.189       0
+  2012       6       8      -1.293       8.200       6.907       2.516       0
+  2012       6       9       2.902       3.437       6.339       0.607       0
+  2012       6      10       1.859       5.307       7.167       1.120       0
+  2012       6      11       2.909       4.120       7.030       0.814       0
+  2012       6      12       1.635       7.776       9.411       0.162       0
+  2012       6      13       3.300       9.112      12.413       1.079       0
+  2012       6      14      -0.500      13.424      12.924       2.230       0
+  2012       6      15      -0.555      13.719      13.164       2.650       0
+  2012       6      16      -2.240      15.315      13.075       2.788       0
+  2012       6      17      -3.710      15.421      11.711       3.815       0
+  2012       6      18      -1.316      13.615      12.299       3.467       0
+  2012       6      19   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       6      20       0.835       9.146       9.981       2.682       0
+  2012       6      21      -3.757      11.764       8.007       2.801       0
+  2012       6      22      -3.178       9.991       6.813       1.756       0
+  2012       6      23      -2.973      11.667       8.695       2.479       0
+  2012       6      24      -1.681       8.276       6.595       2.378       0
+  2012       6      25       1.698       4.862       6.559       0.469       0
+  2012       6      26      -0.333       8.257       7.924       2.947       0
+  2012       6      27      -1.240       9.078       7.839       2.568       0
+  2012       6      28      -2.438       8.591       6.153       2.323       0
+  2012       6      29      -0.041       6.786       6.745       2.320       0
+  2012       6      30   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       7       1   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       7       2   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       7       3   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       7       4      -1.694       7.565       5.871       2.055       0
+  2012       7       5   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       7       6   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       7       7   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       7       8   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       7       9       0.081       8.633       8.714       1.883       0
+  2012       7      10       5.480       4.571      10.050       2.978       0
+  2012       7      11       3.540       6.345       9.885       2.251       0
+  2012       7      12       3.573       6.518      10.092       2.055       0
+  2012       7      13       0.738       6.337       7.074       0.663       0
+  2012       7      14       2.392       5.352       7.744       1.730       0
+  2012       7      15       2.621       3.246       5.867       0.517       0
+  2012       7      16       0.002       5.766       5.768       2.395       0
+  2012       7      17       2.181       4.233       6.414       2.290       0
+  2012       7      18       0.333       5.522       5.855       2.121       0
+  2012       7      19       2.896       4.745       7.641       1.881       0
+  2012       7      20      -4.409      12.188       7.779       2.913       0
+  2012       7      21       2.161       4.473       6.635       0.085       0
+  2012       7      22      -1.966       9.473       7.507       1.158       0
+  2012       7      23      -3.943      12.987       9.044       2.395       0
+  2012       7      24      -1.126      11.111       9.984       1.840       0
+  2012       7      25       0.630       9.271       9.901       1.197       0
+  2012       7      26       0.641      10.025      10.666       2.289       0
+  2012       7      27      -3.677      14.036      10.359       3.401       0
+  2012       7      28       4.881       6.944      11.825       2.951       0
+  2012       7      29      -0.567      10.221       9.654       2.393       0
+  2012       7      30      -5.159      13.376       8.217       2.932       0
+  2012       7      31      -1.854      11.970      10.116       2.514       0
+  2012       8       1      -2.916      12.214       9.298       3.764       0
+  2012       8       2       0.390       8.301       8.691       2.852       0
+  2012       8       3      -3.120      12.612       9.492       2.479       0
+  2012       8       4      -0.243       9.906       9.662       3.369       0
+  2012       8       5       0.921       7.809       8.730       2.621       0
+  2012       8       6       1.958       7.150       9.108       2.832       0
+  2012       8       7      -3.802      12.456       8.654       2.834       0
+  2012       8       8      -3.271      10.859       7.588       1.917       0
+  2012       8       9      -2.539      10.918       8.379       1.708       0
+  2012       8      10      -4.573      13.220       8.647       2.166       0
+  2012       8      11      -1.417       7.881       6.464       0.969       0
+  2012       8      12      -5.064      11.249       6.185       2.064       0
+  2012       8      13      -3.401      10.948       7.547       1.999       0
+  2012       8      14      -4.735      11.421       6.685       2.658       0
+  2012       8      15      -1.630       9.253       7.623       2.609       0
+  2012       8      16      -0.523       9.221       8.698       2.449       0
+  2012       8      17       1.732       5.620       7.352       1.526       0
+  2012       8      18       1.792       5.627       7.419       1.600       0
+  2012       8      19       1.106       5.309       6.415       1.804       0
+  2012       8      20   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       8      21      -1.427       6.966       5.539       1.564       0
+  2012       8      22   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       8      23       1.842       3.369       5.211       1.107       0
+  2012       8      24   -9999.000   -9999.000   -9999.000   -9999.000       1
+  2012       8      25       0.752       4.044       4.796       1.564       0
+  2012       8      26       3.442       2.638       6.080       0.522       0
+  2012       8      27       4.227       2.070       6.297       1.209       0
+  2012       8      28       2.774       2.543       5.317       0.935       0
+  2012       8      29       0.889       6.332       7.221       1.144       0
+  2012       8      30       1.106       5.600       6.705       0.831       0
+  2012       8      31       1.499       4.726       6.225       0.397       0
+  2012       9       1       5.480       0.607       6.087       0.086       0
+  2012       9       2       4.770       3.085       7.854       1.212       0
+  2012       9       3       1.925       4.683       6.608       1.032       0
+  2012       9       4       1.147       4.621       5.768       0.847       0
+  2012       9       5       0.741       4.361       5.102       1.092       0
+  2012       9       6       0.236       3.269       3.505       0.792       0
+  2012       9       7       0.763       2.721       3.484       0.940       0
+  2012       9       8       1.173       3.364       4.537       1.023       0
+  2012       9       9       0.653       4.112       4.765       1.027       0
+  2012       9      10       0.912       4.461       5.373       0.874       0
+  2012       9      11       1.132       4.765       5.898       0.767       0
+  2012       9      12       1.016       5.574       6.589       0.666       0
+  2012       9      13       4.085       0.392       4.477       0.011       0
+  2012       9      14       3.004       2.271       5.276       0.517       0
+  2012       9      15       2.511       3.204       5.715       0.893       0
+  2012       9      16       1.539       4.356       5.896       0.949       0
+  2012       9      17       1.364       4.156       5.520       1.255       0
+  2012       9      18       2.299       4.659       6.957       0.954       0
+  2012       9      19       0.491       5.345       5.836       0.542       0
+  2012       9      20       1.374       4.325       5.699       1.097       0
+  2012       9      21       0.522       3.115       3.637       0.972       0
+  2012       9      22       0.051       3.473       3.524       1.001       0
+  2012       9      23      -0.100       2.702       2.602       0.878       0
+  2012       9      24       0.966       2.419       3.385       0.719       0
+  2012       9      25       1.793       2.237       4.030       1.720       0
+  2012       9      26       1.756       2.586       4.342       1.772       0
+  2012       9      27       0.954       3.168       4.122       0.882       0
+  2012       9      28       0.857       3.393       4.250       1.065       0
+  2012       9      29       1.165       3.372       4.537       0.451       0
+  2012       9      30      -0.759       5.569       4.811       0.830       0
+  2012      10       1       0.207       4.616       4.823       0.919       0
+  2012      10       2       2.516       1.735       4.251       0.041       0
+  2012      10       3      -1.047       4.089       3.042       0.614       0
+  2012      10       4      -1.631       4.975       3.343       0.784       0
+  2012      10       5      -1.277       4.647       3.369       0.901       0
+  2012      10       6      -1.711       5.633       3.922       0.899       0
+  2012      10       7      -1.559       5.570       4.011       0.717       0
+  2012      10       8      -2.029       5.085       3.056       0.904       0
+  2012      10       9      -1.604       5.274       3.671       0.692       0
+  2012      10      10       0.803       1.903       2.705       0.122       0
+  2012      10      11      -2.131       4.498       2.367       0.456       0
+  2012      10      12       0.644       2.323       2.966       0.063       0
+  2012      10      13       0.037       2.745       2.783       0.162       0
+  2012      10      14      -1.170       4.054       2.884       0.115       0
+  2012      10      15      -2.453       5.964       3.511       0.608       0
+  2012      10      16       0.666       1.569       2.235       0.361       0
+  2012      10      17      -2.423       5.213       2.790       0.140       0
+  2012      10      18      -2.999       7.236       4.237       0.575       0
+  2012      10      19      -2.974       6.842       3.869       0.509       0
+  2012      10      20      -0.961       6.009       5.047       0.313       0
+  2012      10      21      -1.929       6.137       4.208       0.308       0
+  2012      10      22      -1.843       7.383       5.540       0.478       0
+  2012      10      23       0.129       4.387       4.516       0.030       0
+  2012      10      24       1.710       3.265       4.975       0.073       0
+  2012      10      25       1.606       3.260       4.866       0.060       0
+  2012      10      26       0.887       2.925       3.811       0.051       0
+  2012      10      27      -1.423       4.769       3.346       0.060       0
+  2012      10      28       0.073       2.014       2.088       0.099       0
+  2012      10      29       0.697       0.838       1.535       0.002       0
+  2012      10      30      -0.362       1.947       1.585       0.214       0
+  2012      10      31      -0.675       2.402       1.727       0.288       0
+  2012      11       1       0.985       0.571       1.556       0.159       0
+  2012      11       2       0.282       1.449       1.731       0.123       0
+  2012      11       3      -1.547       3.771       2.224       0.479       0
+  2012      11       4      -1.364       4.402       3.038       0.569       0
+  2012      11       5       1.604       0.670       2.273       0.159       0
+  2012      11       6       0.679       2.410       3.089       0.170       0
+  2012      11       7      -0.727       2.904       2.176       0.374       0
+  2012      11       8      -0.928       3.313       2.385       0.377       0
+  2012      11       9      -0.790       2.533       1.743       0.293       0
+  2012      11      10      -0.660       2.691       2.031       0.184       0
+  2012      11      11      -0.739       2.588       1.850       0.136       0
+  2012      11      12       2.039       0.224       2.263       0.002       0
+  2012      11      13       1.237       2.104       3.341       0.052       0
+  2012      11      14       0.073       2.379       2.452       0.243       0
+  2012      11      15      -1.381       3.138       1.757       0.207       0
+  2012      11      16       0.103       1.772       1.875       0.067       0
+  2012      11      17      -0.843       2.621       1.778       0.094       0
+  2012      11      18       0.383       1.353       1.736       0.017       0
+  2012      11      19       1.891       0.365       2.256       0.007       0
+  2012      11      20       0.456       1.504       1.960       0.027       0
+  2012      11      21       0.973       1.028       2.002       0.011       0
+  2012      11      22       1.407       0.499       1.905       0.014       0
+  2012      11      23       0.676       1.122       1.798       0.011       0
+  2012      11      24      -0.320       2.203       1.883       0.023       0
+  2012      11      25       0.519       1.067       1.586       0.024       0
+  2012      11      26       0.191       1.449       1.640       0.067       0
+  2012      11      27      -0.142       2.655       2.512       0.536       0
+  2012      11      28      -0.100       2.787       2.686       0.361       0
+  2012      11      29      -0.291       2.827       2.536       0.099       0
+  2012      11      30       1.480       0.791       2.271       0.216       0
+  2012      12       1      -0.573       1.355       0.782       0.104       0
+  2012      12       2       1.006       0.284       1.290       0.009       0
+  2012      12       3       0.518       1.285       1.803       0.211       0
+  2012      12       4       0.150       1.210       1.360       0.035       0
+  2012      12       5       0.435       1.623       2.058       0.033       0
+  2012      12       6       0.319       0.842       1.161       0.022       0
+  2012      12       7       0.430       0.904       1.334       0.080       0
+  2012      12       8       1.286       0.000       1.286       0.012       0
+  2012      12       9       0.610       0.205       0.815       0.104       0
+  2012      12      10       0.676       0.293       0.969       0.087       0
+  2012      12      11       0.656       0.223       0.878       0.034       0
+  2012      12      12       0.418       0.242       0.660       0.101       0
+  2012      12      13       0.494       0.000       0.494       0.042       0
+  2012      12      14       0.662       0.316       0.978       0.005       0
+  2012      12      15       0.458       0.707       1.164       0.006       0
+  2012      12      16       0.185       0.889       1.073       0.005       0
+  2012      12      17       0.743       0.345       1.088       0.044       0
+  2012      12      18       0.764       0.111       0.875       0.009       0
+  2012      12      19       0.554       0.677       1.231       0.044       0
+  2012      12      20       0.308       0.775       1.083       0.028       0
+  2012      12      21       0.439       0.496       0.934       0.044       0
+  2012      12      22       0.141       0.800       0.941       0.005       0
+  2012      12      23       0.146       0.846       0.992       0.044       0
+  2012      12      24      -0.763       1.761       0.999       0.066       0
+  2012      12      25       0.390       1.345       1.735       0.131       0
+  2012      12      26       1.101       0.369       1.470       0.015       0
+  2012      12      27      -0.462       1.742       1.280       0.048       0
+  2012      12      28       0.525       0.520       1.045       0.044       0
+  2012      12      29      -0.086       0.827       0.740       0.060       0
+  2012      12      30      -0.044       0.648       0.604       0.056       0
+  2012      12      31      -0.040       0.731       0.692       0.092       0

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/inst/examples/hhs/Ndep.txt

@@ -0,0 +1,119 @@
+1900    0.0003911
+1901    0.0003922
+1902    0.0003952
+1903    0.0003982
+1904    0.0004012
+1905    0.0004043
+1906    0.0004073
+1907    0.0004103
+1908    0.0004133
+1909    0.0004164
+1910    0.0004224
+1911    0.0004267
+1912    0.0004310
+1913    0.0004353
+1914    0.0004396
+1915    0.0004439
+1916    0.0004482
+1917    0.0004525
+1918    0.0004568
+1919    0.0004611
+1920    0.0004697
+1921    0.0004741
+1922    0.0004786
+1923    0.0004830
+1924    0.0004875
+1925    0.0004919
+1926    0.0004964
+1927    0.0005008
+1928    0.0005053
+1929    0.0005097
+1930    0.0005186
+1931    0.0005214
+1932    0.0005243
+1933    0.0005271
+1934    0.0005299
+1935    0.0005327
+1936    0.0005356
+1937    0.0005384
+1938    0.0005412
+1939    0.0005440
+1940    0.0005497
+1941    0.0005600
+1942    0.0005703
+1943    0.0005806
+1944    0.0005909
+1945    0.0006013
+1946    0.0006116
+1947    0.0006219
+1948    0.0006322
+1949    0.0006425
+1950    0.0006632
+1951    0.0006775
+1952    0.0006919
+1953    0.0007063
+1954    0.0007207
+1955    0.0007350
+1956    0.0007494
+1957    0.0007638
+1958    0.0007782
+1959    0.0007925
+1960    0.0008213
+1961    0.0008407
+1962    0.0008601
+1963    0.0008795
+1964    0.0008989
+1965    0.0009183
+1966    0.0009378
+1967    0.0009572
+1968    0.0009766
+1969    0.0009960
+1970    0.0010348
+1971    0.0010591
+1972    0.0010465
+1973    0.0010524
+1974    0.0010582
+1975    0.0010641
+1976    0.0010699
+1977    0.0010758
+1978    0.0010816
+1979    0.0010875
+1980    0.0010933
+1981    0.0010992
+1982    0.0011050
+1983    0.0011109
+1984    0.0011167
+1985    0.0011226
+1986    0.0011284
+1987    0.0011343
+1988    0.0011401
+1989    0.0011460
+1990    0.0011519
+1991    0.0011577
+1992    0.0011636
+1993    0.0011694
+1994    0.0011753
+1995    0.0011811
+1996    0.0011870
+1997    0.0011928
+1998    0.0011987
+1999    0.0012045
+2000    0.0012104
+2001	0.0012239
+2002	0.0012347
+2003	0.0012654
+2004	0.0012762
+2005	0.0012870
+2006	0.0012977
+2007	0.0013085
+2008	0.0013192
+2009	0.0013200
+2010	0.0013407
+2011	0.0013515
+2012	0.0013722
+2013	0.0013830
+2014	0.0013938
+2015	0.0014010
+2016	0.0014020
+2017	0.0014040
+2018	0.0014050

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/inst/examples/hhs/c3grass_muso6.epc

@@ -1,139 +1,139 @@
-ECOPHYS FILE -    C3 grass muso6 
-----------------------------------------------------------------------------------------
-FLAGS
-0	(flag)		biome type flag (1 = WOODY 0 = NON-WOODY)
-0	(flag)		woody type flag (1 = EVERGREEN 0 = DECIDUOUS)
-1	(flag)		photosyn. type flag (1 = C3 PSN 0 = C4 PSN)
-----------------------------------------------------------------------------------------
-PLANT FUNCTIONING PARAMETERS
-0	(yday)		yearday to start new growth (when phenology flag = 0)
-364	(yday)		yearday to end litterfall (when phenology flag = 0)
-0.5	(prop.)		transfer growth period as fraction of growing season (when transferGDD_flag = 0)
-0.5	(prop.)		litterfall as fraction of growing season (when transferGDD_flag = 0)
-0	(Celsius) 	base temperature
--9999	(Celsius) 	minimum  temperature for growth displayed on current day (-9999: no T-dependence of allocation)
--9999	(Celsius) 	optimal1 temperature for growth displayed on current day (-9999: no T-dependence of allocation) 
--9999	(Celsius) 	optimal2 temperature for growth displayed on current day (-9999: no T-dependence of allocation) 
--9999	(Celsius) 	maxmimum temperature for growth displayed on current day (-9999: no T-dependence of allocation)
--9999	(Celsius) 	minimum  temperature for carbon assimilation displayed on current day (-9999: no limitation)
--9999	(Celsius) 	optimal1 temperature for carbon assimilation displayed on current day (-9999: no limitation) 
--9999	(Celsius) 	optimal2 temperature for carbon assimilation displayed on current day (-9999: no limitation) 
--9999	(Celsius) 	maxmimum temperature for carbon assimilation displayed on current day (-9999: no limitation)
-1.0	(1/yr)		annual leaf and fine root turnover fraction
-0.00	(1/yr)		annual live wood turnover fraction
-0.03	(1/yr)		annual fire mortality fraction
-0.01	(1/vegper)	whole-plant mortality fraction in vegetation period
-36.6	(kgC/kgN)	C:N of leaves
-45.0	(kgC/kgN)	C:N of leaf litter, after retranslocation
-50.0	(kgC/kgN)	C:N of fine roots
-36.6   *(kgC/kgN)       C:N of fruit  
-36.6    (kgC/kgN)  	C:N of soft stem 
-0.0    *(kgC/kgN)	C:N of live wood
-0.0    *(kgC/kgN)	C:N of dead wood
-0.4	(kgC/kgDM)	dry matter carbon content of leaves
-0.4	(kgC/kgDM)	dry matter carbon content of leaf litter
-0.4	(kgC/kgDM)	dry matter carbon content of fine roots
-0.4    *(kgC/kgDM)      dry matter carbon content of fruit  
-0.4     (kgC/kgDM)  	dry matter carbon content of soft stem 
-0.4    *(kgC/kgDM)	dry matter carbon content of live wood
-0.4    *(kgC/kgDM)	dry matter carbon content of dead wood
-0.68	(DIM)		leaf litter labile proportion
-0.23	(DIM)		leaf litter cellulose proportion
-0.34	(DIM)		fine root labile proportion
-0.44	(DIM)		fine root cellulose proportion
-0.68   *(DIM)		fruit litter labile proportion
-0.23   *(DIM)		fruit litter cellulose proportion
-0.68    (DIM)		soft stem litter labile proportion
-0.23    (DIM)		soft stem litter cellulose proportion
-0.00   *(DIM)		dead wood cellulose proportion
-0.01	(1/LAI/d)	canopy water interception coefficient
-0.63	(DIM)		canopy light extinction coefficient
-2.0     (g/MJ)          potential radiation use efficiency
-0.781   (DIM)           radiation parameter1 (Jiang et al.2015)
--13.596 (DIM)           radiation parameter2 (Jiang et al.2015)
-2.0	(DIM)		all-sided to projected leaf area ratio
-2.0	(DIM)		ratio of shaded SLA:sunlit SLA
-0.14	(DIM)		fraction of leaf N in Rubisco
-0.03	(DIM)		fraction of leaf N in PEP Carboxylase 
-0.004	(m/s)		maximum stomatal conductance (projected area basis)
-0.00006	(m/s)		cuticular conductance (projected area basis)
-0.04	(m/s)		boundary layer conductance (projected area basis)
-1.5     (m) 		maximum height of plant
-0.8     (kgC) 	        stem weight corresponding to maximum height
-0.5     (dimless) 	plant height function shape parameter (slope)
-4.0     (m) 		maximum depth of rooting zone
-3.67	(DIM) 		root distribution parameter
-0.4	(kgC)	        root weight corresponding to max root depth
-0.5	(dimless)	root depth function shape parameter (slope)
-1000	(m/kg)		root weight to root length conversion factor
-0.3     (prop.) 	growth resp per unit of C grown
-0.218   (kgC/kgN/d) 	maintenance respiration in kgC/day per kg of tissue N 
-0.1     (DIM)           theoretical maximum prop. of non-structural and structural carbohydrates
-0.24	(DIM)		prop. of non-structural carbohydrates available for maintanance respiration
-0.02  (kgN/m2/yr) 	symbiotic+asymbiotic fixation of N
-0	(day)		time delay for temperature in photosynthesis acclimation
-----------------------------------------------------------------------------------------
-CROP SPECIFIC PARAMETERS
-0   	(DIM)           number of phenophase of germination (from 1 to 7; 0: NO specific)
-0   	(DIM)           number of phenophase of emergence (from 1 to 7; 0: NO specific)
-0.5     (prop.)         critical VWCratio (prop. to FC-WP) in germination
-0       (DIM)           number of phenophase of photoperiodic slowing effect (from 1 to 7; 0: NO effect)
-20      (hour) 	        critical photoslow daylength
-0.005   (DIM) 	        slope of relative photoslow development rate 
-0       (DIM)           number of phenophase of vernalization (from 1 to 7; 0: NO effect)
-0       (Celsius) 	critical vernalization temperature 1
-5       (Celsius) 	critical vernalization temperature 2
-8       (Celsius) 	critical vernalization temperature 3
-15      (Celsius) 	critical vernalization temperature 4
-0.04    (DIM) 	        slope of relative vernalization development rate 
-50      (n)             required vernalization days (in vernalization development rate)
-0	(DIM)           number of flowering phenophase (from 1 to 7;0: NO effect)
-35	(Celsius)       critical flowering heat stress temperature 1
-40	(Celsius)       critical flowering heat stress temperature 2
-0.2	(prop.)         theoretical maximum of flowering thermal stress mortality parameter 
-----------------------------------------------------------------------------------------
-STRESS AND SENESCENCE PARAMETERS
-0.98	(prop)		VWC ratio to calc. soil moisture limit 1 (prop. to FC-WP)
-0.7	(prop)		VWC ratio to calc. soil moisture limit 2 (prop. to SAT-FC)
-0.4     (prop)		minimum of soil moisture limit2 multiplicator (full anoxic stress value)
-1000	(Pa)		vapor pressure deficit: start of conductance reduction
-4000	(Pa)		vapor pressure deficit: complete conductance reduction
-0.003     (prop.) 	maximum senescence mortality coefficient of aboveground plant material
-0.001    (prop.) 	maximum senescence mortality coefficient of belowground plant material
-0.0     (prop.) 	maximum senescence mortality coefficient of non-structured plant material
-35	(Celsius) 	lower limit extreme high temperature effect on senescence mortality
-40	(Celsius) 	upper limit extreme high temperature effect on senescence mortality
-0.01    (prop.) 	turnover rate of wilted standing biomass to litter
-0.047   (prop.) 	turnover rate of non-woody cut-down biomass to litter
-0.01    (prop.) 	turnover rate of woody cut-down biomass to litter
-17	(nday)		drought tolerance parameter (critical value of DSWS)
-0.3    (prop) soil water deficit effect on photosynthesis downregulation
-----------------------------------------------------------------------------------------
-GROWING SEASON PARAMETERS
-5       (kg/m2) 	crit. amount of snow limiting photosyn.
-20      (Celsius) 	limit1 (under:full constrained) of HEATSUM index
-60      (Celsius) 	limit2 (above:unconstrained) of HEATSUM index
-0       (Celsius) 	limit1 (under:full constrained) of TMIN index
-5       (Celsius) 	limit2 (above:unconstrained) of TMIN index
-4000    (Pa) 		limit1 (above:full constrained) of VPD index
-1000    (Pa) 		limit2 (under:unconstrained) of VPD index
-0       (s) 		limit1 (under:full constrained) of DAYLENGTH index
-0       (s) 		limit2 (above:unconstrained) of DAYLENGTH index
-10      (day) 		moving average (to avoid the effects of extreme events)
-0.10    (dimless) 	GSI limit1 (greater that limit -> start of vegper)
-0.01    (dimless) 	GSI limit2 (less that limit -> end of vegper)
-----------------------------------------------------------------------------------------
-PHENOLOGICAL (ALLOCATION) PARAMETERS (7 phenological phases)
-phase1  phase2  phase3  phase4 	phase5 	phase6 	phase7  (text) name of the phenophase
-5000	200	500	200	400	200	100	(Celsius) length of phenophase (GDD)
-0.3	0.4	0.4	0.4	0.4	0.4  	0.4	(ratio) leaf ALLOCATION 	                                                                                                                                                                                                                                                           
-0.5	0.4	0.4	0.4	0.4	0.4  	0.4	(ratio) fine root ALLOCATION
-0.0	0.0	0.0	0.0	0.0	0.0  	0.0	(ratio) fruit ALLOCATION 	                                                                                                                                                                                                                                             
-0.2	0.2	0.2	0.2	0.2	0.2  	0.2	(ratio) soft stem ALLOCATION
-0	0	0	0	0	0	0	(ratio) live woody stem ALLOCATION 
-0	0	0	0	0	0	0	(ratio) dead woody stem ALLOCATION 
-0	0	0	0	0	0	0	(ratio) live coarse root ALLOCATION 
-0	0	0	0	0	0	0	(ratio) dead coarse root ALLOCATION 
-49	49	49	49	49	49	49	(m2/kgC) canopy average specific leaf area (projected area basis)
-0.37	0.37	0.37	0.37	0.37	0.37    0.37	(prop.)	current growth proportion
-10000	10000	10000	10000	10000	10000	10000    (Celsius) maximal lifetime of plant tissue
+ECOPHYS FILE -    C3 grass muso6 
+----------------------------------------------------------------------------------------
+FLAGS
+0	(flag)		biome type flag (1 = WOODY 0 = NON-WOODY)
+0	(flag)		woody type flag (1 = EVERGREEN 0 = DECIDUOUS)
+1	(flag)		photosyn. type flag (1 = C3 PSN 0 = C4 PSN)
+----------------------------------------------------------------------------------------
+PLANT FUNCTIONING PARAMETERS
+0	(yday)		yearday to start new growth (when phenology flag = 0)
+364	(yday)		yearday to end litterfall (when phenology flag = 0)
+0.5	(prop.)		transfer growth period as fraction of growing season (when transferGDD_flag = 0)
+0.5	(prop.)		litterfall as fraction of growing season (when transferGDD_flag = 0)
+0	(Celsius) 	base temperature
+-9999	(Celsius) 	minimum  temperature for growth displayed on current day (-9999: no T-dependence of allocation)
+-9999	(Celsius) 	optimal1 temperature for growth displayed on current day (-9999: no T-dependence of allocation) 
+-9999	(Celsius) 	optimal2 temperature for growth displayed on current day (-9999: no T-dependence of allocation) 
+-9999	(Celsius) 	maxmimum temperature for growth displayed on current day (-9999: no T-dependence of allocation)
+-9999	(Celsius) 	minimum  temperature for carbon assimilation displayed on current day (-9999: no limitation)
+-9999	(Celsius) 	optimal1 temperature for carbon assimilation displayed on current day (-9999: no limitation) 
+-9999	(Celsius) 	optimal2 temperature for carbon assimilation displayed on current day (-9999: no limitation) 
+-9999	(Celsius) 	maxmimum temperature for carbon assimilation displayed on current day (-9999: no limitation)
+1.0	(1/yr)		annual leaf and fine root turnover fraction
+0.00	(1/yr)		annual live wood turnover fraction
+0.03	(1/yr)		annual fire mortality fraction
+0.01	(1/vegper)	whole-plant mortality fraction in vegetation period
+36.6	(kgC/kgN)	C:N of leaves
+45.0	(kgC/kgN)	C:N of leaf litter, after retranslocation
+50.0	(kgC/kgN)	C:N of fine roots
+36.6   *(kgC/kgN)       C:N of fruit  
+36.6    (kgC/kgN)  	C:N of soft stem 
+0.0    *(kgC/kgN)	C:N of live wood
+0.0    *(kgC/kgN)	C:N of dead wood
+0.4	(kgC/kgDM)	dry matter carbon content of leaves
+0.4	(kgC/kgDM)	dry matter carbon content of leaf litter
+0.4	(kgC/kgDM)	dry matter carbon content of fine roots
+0.4    *(kgC/kgDM)      dry matter carbon content of fruit  
+0.4     (kgC/kgDM)  	dry matter carbon content of soft stem 
+0.4    *(kgC/kgDM)	dry matter carbon content of live wood
+0.4    *(kgC/kgDM)	dry matter carbon content of dead wood
+0.68	(DIM)		leaf litter labile proportion
+0.23	(DIM)		leaf litter cellulose proportion
+0.34	(DIM)		fine root labile proportion
+0.44	(DIM)		fine root cellulose proportion
+0.68   *(DIM)		fruit litter labile proportion
+0.23   *(DIM)		fruit litter cellulose proportion
+0.68    (DIM)		soft stem litter labile proportion
+0.23    (DIM)		soft stem litter cellulose proportion
+0.00   *(DIM)		dead wood cellulose proportion
+0.01	(1/LAI/d)	canopy water interception coefficient
+0.63	(DIM)		canopy light extinction coefficient
+2.0     (g/MJ)          potential radiation use efficiency
+0.781   (DIM)           radiation parameter1 (Jiang et al.2015)
+-13.596 (DIM)           radiation parameter2 (Jiang et al.2015)
+2.0	(DIM)		all-sided to projected leaf area ratio
+2.0	(DIM)		ratio of shaded SLA:sunlit SLA
+0.14	(DIM)		fraction of leaf N in Rubisco
+0.03	(DIM)		fraction of leaf N in PEP Carboxylase 
+0.004	(m/s)		maximum stomatal conductance (projected area basis)
+0.00006	(m/s)		cuticular conductance (projected area basis)
+0.04	(m/s)		boundary layer conductance (projected area basis)
+1.5     (m) 		maximum height of plant
+0.8     (kgC) 	        stem weight corresponding to maximum height
+0.5     (dimless) 	plant height function shape parameter (slope)
+4.0     (m) 		maximum depth of rooting zone
+3.67	(DIM) 		root distribution parameter
+0.4	(kgC)	        root weight corresponding to max root depth
+0.5	(dimless)	root depth function shape parameter (slope)
+1000	(m/kg)		root weight to root length conversion factor
+0.3     (prop.) 	growth resp per unit of C grown
+0.218   (kgC/kgN/d) 	maintenance respiration in kgC/day per kg of tissue N 
+0.1     (DIM)           theoretical maximum prop. of non-structural and structural carbohydrates
+0.24	(DIM)		prop. of non-structural carbohydrates available for maintanance respiration
+0.02  (kgN/m2/yr) 	symbiotic+asymbiotic fixation of N
+0	(day)		time delay for temperature in photosynthesis acclimation
+----------------------------------------------------------------------------------------
+CROP SPECIFIC PARAMETERS
+0   	(DIM)           number of phenophase of germination (from 1 to 7; 0: NO specific)
+0   	(DIM)           number of phenophase of emergence (from 1 to 7; 0: NO specific)
+0.5     (prop.)         critical VWCratio (prop. to FC-WP) in germination
+0       (DIM)           number of phenophase of photoperiodic slowing effect (from 1 to 7; 0: NO effect)
+20      (hour) 	        critical photoslow daylength
+0.005   (DIM) 	        slope of relative photoslow development rate 
+0       (DIM)           number of phenophase of vernalization (from 1 to 7; 0: NO effect)
+0       (Celsius) 	critical vernalization temperature 1
+5       (Celsius) 	critical vernalization temperature 2
+8       (Celsius) 	critical vernalization temperature 3
+15      (Celsius) 	critical vernalization temperature 4
+0.04    (DIM) 	        slope of relative vernalization development rate 
+50      (n)             required vernalization days (in vernalization development rate)
+0	(DIM)           number of flowering phenophase (from 1 to 7;0: NO effect)
+35	(Celsius)       critical flowering heat stress temperature 1
+40	(Celsius)       critical flowering heat stress temperature 2
+0.2	(prop.)         theoretical maximum of flowering thermal stress mortality parameter 
+----------------------------------------------------------------------------------------
+STRESS AND SENESCENCE PARAMETERS
+0.98	(prop)		VWC ratio to calc. soil moisture limit 1 (prop. to FC-WP)
+0.7	(prop)		VWC ratio to calc. soil moisture limit 2 (prop. to SAT-FC)
+0.4     (prop)		minimum of soil moisture limit2 multiplicator (full anoxic stress value)
+1000	(Pa)		vapor pressure deficit: start of conductance reduction
+4000	(Pa)		vapor pressure deficit: complete conductance reduction
+0.003     (prop.) 	maximum senescence mortality coefficient of aboveground plant material
+0.001    (prop.) 	maximum senescence mortality coefficient of belowground plant material
+0.0     (prop.) 	maximum senescence mortality coefficient of non-structured plant material
+35	(Celsius) 	lower limit extreme high temperature effect on senescence mortality
+40	(Celsius) 	upper limit extreme high temperature effect on senescence mortality
+0.01    (prop.) 	turnover rate of wilted standing biomass to litter
+0.047   (prop.) 	turnover rate of non-woody cut-down biomass to litter
+0.01    (prop.) 	turnover rate of woody cut-down biomass to litter
+17	(nday)		drought tolerance parameter (critical value of DSWS)
+0.3    (prop) soil water deficit effect on photosynthesis downregulation
+----------------------------------------------------------------------------------------
+GROWING SEASON PARAMETERS
+5       (kg/m2) 	crit. amount of snow limiting photosyn.
+20      (Celsius) 	limit1 (under:full constrained) of HEATSUM index
+60      (Celsius) 	limit2 (above:unconstrained) of HEATSUM index
+0       (Celsius) 	limit1 (under:full constrained) of TMIN index
+5       (Celsius) 	limit2 (above:unconstrained) of TMIN index
+4000    (Pa) 		limit1 (above:full constrained) of VPD index
+1000    (Pa) 		limit2 (under:unconstrained) of VPD index
+0       (s) 		limit1 (under:full constrained) of DAYLENGTH index
+0       (s) 		limit2 (above:unconstrained) of DAYLENGTH index
+10      (day) 		moving average (to avoid the effects of extreme events)
+0.10    (dimless) 	GSI limit1 (greater that limit -> start of vegper)
+0.01    (dimless) 	GSI limit2 (less that limit -> end of vegper)
+----------------------------------------------------------------------------------------
+PHENOLOGICAL (ALLOCATION) PARAMETERS (7 phenological phases)
+phase1  phase2  phase3  phase4 	phase5 	phase6 	phase7  (text) name of the phenophase
+5000	200	500	200	400	200	100	(Celsius) length of phenophase (GDD)
+0.3	0.4	0.4	0.4	0.4	0.4  	0.4	(ratio) leaf ALLOCATION 	                                                                                                                                                                                                                                                           
+0.5	0.4	0.4	0.4	0.4	0.4  	0.4	(ratio) fine root ALLOCATION
+0.0	0.0	0.0	0.0	0.0	0.0  	0.0	(ratio) fruit ALLOCATION 	                                                                                                                                                                                                                                             
+0.2	0.2	0.2	0.2	0.2	0.2  	0.2	(ratio) soft stem ALLOCATION
+0	0	0	0	0	0	0	(ratio) live woody stem ALLOCATION 
+0	0	0	0	0	0	0	(ratio) dead woody stem ALLOCATION 
+0	0	0	0	0	0	0	(ratio) live coarse root ALLOCATION 
+0	0	0	0	0	0	0	(ratio) dead coarse root ALLOCATION 
+49	49	49	49	49	49	49	(m2/kgC) canopy average specific leaf area (projected area basis)
+0.37	0.37	0.37	0.37	0.37	0.37    0.37	(prop.)	current growth proportion
+10000	10000	10000	10000	10000	10000	10000    (Celsius) maximal lifetime of plant tissue

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/inst/examples/hhs/hhs.mgm

@@ -1,33 +1,33 @@
-MANAGEMENT_INFORMATION MuSo6
--------------------------------------------------------------------------------------------------------------------
-PLANTING
-0                                  (flag) flag of management action: 0 - no MGM, 1 - MGM information from file below 
-none
--------------------------------------------------------------------------------------------------------------------
-THINNING
-0                                  (flag) flag of management action: 0 - no MGM, 1 - MGM information from file below 
-none
--------------------------------------------------------------------------------------------------------------------
-MOWING
-1                                  (flag) flag of management action: 0 - no MGM, 1 - MGM information from file below 
-hhs.mow
--------------------------------------------------------------------------------------------------------------------
-GRAZING
-0                                  (flag) flag of management action: 0 - no MGM, 1 - MGM information from file below 
-none
--------------------------------------------------------------------------------------------------------------------
-HARVESTING
-0                                  (flag) flag of management action: 0 - no MGM, 1 - MGM information from file below 
-none
--------------------------------------------------------------------------------------------------------------------
-PLOUGHING
-0                                  (flag) flag of management action: 0 - no MGM, 1 - MGM information from file below 
-none
--------------------------------------------------------------------------------------------------------------------
-FERTILIZING
-0                                  (flag) flag of management action: 0 - no MGM, 1 - MGM information from file below 
-none
--------------------------------------------------------------------------------------------------------------------
-IRRIGATING
-0                                  (flag) flag of management action: 0 - no MGM, 1 - MGM information from file below 
-none
+MANAGEMENT_INFORMATION MuSo6
+-------------------------------------------------------------------------------------------------------------------
+PLANTING
+0                                  (flag) flag of management action: 0 - no MGM, 1 - MGM information from file below 
+none
+-------------------------------------------------------------------------------------------------------------------
+THINNING
+0                                  (flag) flag of management action: 0 - no MGM, 1 - MGM information from file below 
+none
+-------------------------------------------------------------------------------------------------------------------
+MOWING
+1                                  (flag) flag of management action: 0 - no MGM, 1 - MGM information from file below 
+hhs.mow
+-------------------------------------------------------------------------------------------------------------------
+GRAZING
+0                                  (flag) flag of management action: 0 - no MGM, 1 - MGM information from file below 
+none
+-------------------------------------------------------------------------------------------------------------------
+HARVESTING
+0                                  (flag) flag of management action: 0 - no MGM, 1 - MGM information from file below 
+none
+-------------------------------------------------------------------------------------------------------------------
+PLOUGHING
+0                                  (flag) flag of management action: 0 - no MGM, 1 - MGM information from file below 
+none
+-------------------------------------------------------------------------------------------------------------------
+FERTILIZING
+0                                  (flag) flag of management action: 0 - no MGM, 1 - MGM information from file below 
+none
+-------------------------------------------------------------------------------------------------------------------
+IRRIGATING
+0                                  (flag) flag of management action: 0 - no MGM, 1 - MGM information from file below 
+none

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/inst/examples/hhs/hhs.mow

@@ -0,0 +1,23 @@
+DATE		afterLAI(m2/m2)		transPART(%) 
+2006.08.09      1                       90
+2007.06.18	1			90
+2008.05.30	1			90
+2008.08.18	1			90
+2009.06.08	1			90
+2009.08.07	1			90
+2010.06.12	1			90
+2010.09.26	1			90
+2011.06.01	1			90
+2011.08.21	1			90
+2012.05.24	1			90
+2012.08.17	1			90
+2013.06.16	1			90
+2013.09.29	1			90
+2014.06.09	1			90
+2015.06.13	1			90
+2015.09.30	1			90
+2016.06.22	1			90
+2016.08.14	1			90
+2017.06.18	1			90
+2018.06.03	1			90
+2018.07.30	1			90

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/inst/examples/hhs/hhs.soi

@@ -1,64 +1,64 @@
-SOILPROP FILE -    hhs muso6 
-----------------------------------------------------------------------------------------               
-NITROGEN AND DECOMPOSITION PARAMETERS    
-0.1    (prop.) 	denitrification rate per g of CO2 respiration of SOM
-0.2     (prop.) 	nitrification coefficient 1 
-0.1	(prop.) 	nitrification coefficient 2
-0.02    (prop.)		coefficient of N2O emission of nitrification
-0.1     (prop.) 	NH4 mobilen proportion
-1.0     denitrification related N2/N2O ratio multiplier (soil texture effect) 
-10      (m) 		e-folding depth of decomposition rate's depth scalar
-0.002	(prop.) 	fraction of dissolved part of SOIL1 organic matter
-0.002	(prop.) 	fraction of dissolved part of SOIL2 organic matter
-0.002	(prop.) 	fraction of dissolved part of SOIL3 organic matter
-0.002	(prop.) 	fraction of dissolved part of SOIL4 organic matter
-0.1	(prop.)		minimum WFPS for scalar of nitrification calculation
-0.45	(prop.)		lower optimum WFPS for scalar of nitrification calculation
-0.55	(prop.)		higher optimum WFPS for scalar of nitrification calculation
-0.2	(prop.)		minimum value for saturated WFPS scalar of nitrification calculation
-10      (ppm)		C:N ratio of recaltirant SOM (slowest)
-----------------------------------------------------------------------------------------               
-RATE SCALARS  
-0.39 	(DIM) 		respiration fractions for fluxes between compartments (l1s1)
-0.55 	(DIM) 		respiration fractions for fluxes between compartments (l2s2)
-0.29 	(DIM) 		respiration fractions for fluxes between compartments (l4s3)
-0.28 	(DIM) 		respiration fractions for fluxes between compartments (s1s2)
-0.46 	(DIM) 		respiration fractions for fluxes between compartments (s2s3)
-0.55 	(DIM) 		respiration fractions for fluxes between compartments (s3s4)
-0.7     (DIM) 		rate constant scalar of  labile litter pool
-0.07    (DIM) 		rate constant scalar of cellulose litter pool
-0.014   (DIM) 		rate constant scalar of lignin litter pool
-0.07    (DIM) 		rate constant scalar of  fast microbial recycling pool
-0.014   (DIM) 		rate constant scalar of  medium microbial recycling pool 
-0.0014  (DIM) 		rate constant scalar of  slow microbial recycling pool
-0.0001  (DIM) 		rate constant scalar of  recalcitrant SOM (humus) pool
-0.001   (DIM) 		rate constant scalar of  physical fragmentation of coarse woody debris
-----------------------------------------------------------------------------------------
-CH4 PARAMETERS
-212.5	(DIM) 		soil CH4 emission bulk density dependence parameter1
-1.81	(DIM) 		soil CH4 emission bulk density dependence parameter2
--1.353	(DIM) 		soil CH4 emission soil water content dependence parameter1
-0.2	(DIM) 		soil CH4 emission soil water content dependence parameter2
-1.781	(DIM) 		soil CH4 emission soil water content dependence parameter3
-6.786	(DIM) 		soil CH4 emission soil water content dependence parameter4
-0.010	(DIM) 		soil CH4 emission soil temperature dependence parameter1
-----------------------------------------------------------------------------------------
-SOIL PARAMETERS
-2       (m)             depth of soil
-6	(mm)            limit of first stage evaporation
-5.00   (mm) 		maximum height of pond water
-1	(dimless)	curvature of soil stress function
--9999   (dimless) 	runoff curve number (-9999: no , model estimation) 
-107	(s/m)           aerodynamic resistance (Wallace and Holwill, 1997) 
-----------------------------------------------------------------------------------------
-SOIL COMPOSITION AND CHARACTERISTIC VALUES (-9999: no measured data)
-30.0 	30.0 	30.0 	30.0 	30.0 	30.0 	30.0 	30.0 	30.0 	30.0                  (%) sand percentage by volume in rock-free soil
-50.0 	50.0 	50.0 	50.0 	50.0 	50.0 	50.0 	50.0 	50.0 	50.0                  (%) silt percentage by volume in rock-free soil
-7.0 	7.0 	7.0 	7.0 	7.0 	7.0 	7.0 	7.0 	7.0 	7.0                   (dimless) soil pH                                                                           (dimless) measured runoff curve number
--9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999                 (g/cm3) bulk density
--9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999                 (m3/m3) SWC at saturation
--9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999                 (m3/m3) SWC at field capacity
--9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999                 (m3/m3) SWC at wilting point
--9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999                 (m3/m3) SWC at hygroscopic water content
--9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999                 (dimless) drainage coefficient
--9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999                 (cm/day) hydraulic condictivity at saturation
+SOILPROP FILE -    hhs muso6 
+----------------------------------------------------------------------------------------               
+NITROGEN AND DECOMPOSITION PARAMETERS    
+0.1    (prop.) 	denitrification rate per g of CO2 respiration of SOM
+0.2     (prop.) 	nitrification coefficient 1 
+0.1	(prop.) 	nitrification coefficient 2
+0.02    (prop.)		coefficient of N2O emission of nitrification
+0.1     (prop.) 	NH4 mobilen proportion
+1.0     denitrification related N2/N2O ratio multiplier (soil texture effect) 
+10      (m) 		e-folding depth of decomposition rate's depth scalar
+0.002	(prop.) 	fraction of dissolved part of SOIL1 organic matter
+0.002	(prop.) 	fraction of dissolved part of SOIL2 organic matter
+0.002	(prop.) 	fraction of dissolved part of SOIL3 organic matter
+0.002	(prop.) 	fraction of dissolved part of SOIL4 organic matter
+0.1	(prop.)		minimum WFPS for scalar of nitrification calculation
+0.45	(prop.)		lower optimum WFPS for scalar of nitrification calculation
+0.55	(prop.)		higher optimum WFPS for scalar of nitrification calculation
+0.2	(prop.)		minimum value for saturated WFPS scalar of nitrification calculation
+10      (ppm)		C:N ratio of recaltirant SOM (slowest)
+----------------------------------------------------------------------------------------               
+RATE SCALARS  
+0.39 	(DIM) 		respiration fractions for fluxes between compartments (l1s1)
+0.55 	(DIM) 		respiration fractions for fluxes between compartments (l2s2)
+0.29 	(DIM) 		respiration fractions for fluxes between compartments (l4s3)
+0.28 	(DIM) 		respiration fractions for fluxes between compartments (s1s2)
+0.46 	(DIM) 		respiration fractions for fluxes between compartments (s2s3)
+0.55 	(DIM) 		respiration fractions for fluxes between compartments (s3s4)
+0.7     (DIM) 		rate constant scalar of  labile litter pool
+0.07    (DIM) 		rate constant scalar of cellulose litter pool
+0.014   (DIM) 		rate constant scalar of lignin litter pool
+0.07    (DIM) 		rate constant scalar of  fast microbial recycling pool
+0.014   (DIM) 		rate constant scalar of  medium microbial recycling pool 
+0.0014  (DIM) 		rate constant scalar of  slow microbial recycling pool
+0.0001  (DIM) 		rate constant scalar of  recalcitrant SOM (humus) pool
+0.001   (DIM) 		rate constant scalar of  physical fragmentation of coarse woody debris
+----------------------------------------------------------------------------------------
+CH4 PARAMETERS
+212.5	(DIM) 		soil CH4 emission bulk density dependence parameter1
+1.81	(DIM) 		soil CH4 emission bulk density dependence parameter2
+-1.353	(DIM) 		soil CH4 emission soil water content dependence parameter1
+0.2	(DIM) 		soil CH4 emission soil water content dependence parameter2
+1.781	(DIM) 		soil CH4 emission soil water content dependence parameter3
+6.786	(DIM) 		soil CH4 emission soil water content dependence parameter4
+0.010	(DIM) 		soil CH4 emission soil temperature dependence parameter1
+----------------------------------------------------------------------------------------
+SOIL PARAMETERS
+2       (m)             depth of soil
+6	(mm)            limit of first stage evaporation
+5.00   (mm) 		maximum height of pond water
+1	(dimless)	curvature of soil stress function
+-9999   (dimless) 	runoff curve number (-9999: no , model estimation) 
+107	(s/m)           aerodynamic resistance (Wallace and Holwill, 1997) 
+----------------------------------------------------------------------------------------
+SOIL COMPOSITION AND CHARACTERISTIC VALUES (-9999: no measured data)
+30.0 	30.0 	30.0 	30.0 	30.0 	30.0 	30.0 	30.0 	30.0 	30.0                  (%) sand percentage by volume in rock-free soil
+50.0 	50.0 	50.0 	50.0 	50.0 	50.0 	50.0 	50.0 	50.0 	50.0                  (%) silt percentage by volume in rock-free soil
+7.0 	7.0 	7.0 	7.0 	7.0 	7.0 	7.0 	7.0 	7.0 	7.0                   (dimless) soil pH                                                                           (dimless) measured runoff curve number
+-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999                 (g/cm3) bulk density
+-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999                 (m3/m3) SWC at saturation
+-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999                 (m3/m3) SWC at field capacity
+-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999                 (m3/m3) SWC at wilting point
+-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999                 (m3/m3) SWC at hygroscopic water content
+-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999                 (dimless) drainage coefficient
+-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999 	-9999                 (cm/day) hydraulic condictivity at saturation

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/inst/examples/hhs/n.ini

@@ -0,0 +1,147 @@
+BBGCMuSo simulation
+
+MET_INPUT
+hhs.mtc43                                                                            (filename) met file name
+4                                                                            (int) number of header lines in met file
+365                                                  (int) number of simdays in last simyear (truncated year: <= 365)
+
+RESTART
+1                                                                      (flag) 1 = read restart; 0 = dont read restart
+0                                                                    (flag) 1 = write restart; 0 = dont write restart
+hhs_MuSo6.endpoint                                          (filename) name of the input restart file
+hhs_MuSo6.endpoint                                         (filename) name of the output restart file
+
+TIME_DEFINE
+9                                                                                   (int) number of simulation years 
+2007                                                                                      (int) first simulation year
+0                                                                               (flag) 1 = spinup run; 0 = normal run
+6000                                                                             (int) maximum number of spinup years
+
+CO2_CONTROL
+1                                                                                 (flag) 0=constant; 1=vary with file
+395.0                                                                    (ppm) constant atmospheric CO2 concentration
+CO2.txt                                                                           (filename) name of the CO2 file
+
+NDEP_CONTROL
+1                                                                                 (flag) 0=constant; 1=vary with file
+0.001400                                                              (kgN/m2/yr) wet+dry atmospheric deposition of N
+Ndep.txt                                                                  (filename)  name of the N-dep file
+
+SITE
+248.0                                                                                             (m)  site elevation
+46.95                                                                          (degrees) site latitude (- for S.Hem.)
+0.20                                                                                      (DIM) site shortwave albedo
+9.00                                                                            (Celsius) mean annual air temperature
+10.15                                                                     (Celsius) mean annual air temperature range
+0.50                                                                  (prop.) proprortion of NH4 flux of N-deposition
+
+SOIL_FILE
+hhs.soi                                                                  (filename) SOIL filename
+
+EPC_FILE
+c3grass_muso6.epc                                                                  (filename) EPC filename
+
+MANAGEMENT_FILE
+hhs.mgm                                                                 (filename) MGM filename (or "none")
+
+SIMULATION_CONTROL
+1                                            (flag) phenology flag (1 = MODEL PHENOLOGY 0 = USER-SPECIFIED PHENOLOGY)
+1                                   (flag) vegper calculation method if MODEL PHENOLOGY is used (0: original, 1: GSI)
+0                                    (flag) transferGDD flag (1= transfer calc. from GDD 0 = transfer calc. from EPC)
+1                                        (flag) q10 flag (1 = temperature dependent q10 value; 0= constans q10 value)
+1                                      (flag) acclimation flag of photosynthesis (1 = acclimation 0 = no acclimation)
+1                                         (flag) acclimation flag of respiration (1 = acclimation 0 = no acclimation)
+1                                                 (flag) CO2 conductance reduction flag (0: no effect, 1: multiplier)
+0                                                     (flag) soil temperature calculation method (0: Zheng, 1: DSSAT)
+1                                         (flag) soil hydrological calculation method (0: Richards, 1: tipping DSSAT)
+0                         (int) discretization level of soil hydr.calc.[Richards-method] (0: low, 1: medium, 2: high)
+0                                                    (flag) photosynthesis calculation method (0: Farquhar, 1: DSSAT)
+0                               (flag) evapotranspiration calculation method (0: Penman-Montieth, 1: Priestly-Taylor)
+0                                                               (flag) radiation calculation method (0: SWabs, 1: Rn)
+0                                  (flag) soilstress calculation method (0: based on VWC, 1: based on transp. demand)
+
+W_STATE
+0.0                                                                                  (kg/m2) water stored in snowpack
+1.0                                                        (DIM) initial soil water as a proportion of field capacity
+
+CN_STATE
+0.001                                                                        (kgC/m2)  first-year maximum leaf carbon
+0.001                                                                   (kgC/m2)  first-year maximum fine root carbon
+0.001                                                                       (kgC/m2)  first-year maximum fruit carbon
+0.001                                                                    (kgC/m2)  first-year maximum softstem carbon
+0.001                                                             (kgC/m2)  first-year maximum live woody stem carbon
+0.001                                                            (kgC/m2)  first-year maximum live coarse root carbon
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0                        (kgC/m2)  coarse woody debris carbon
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0                        (kgC/m2)  litter carbon, labile pool
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0          (kgC/m2)  litter carbon, unshielded cellulose pool
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0            (kgC/m2)  litter carbon, shielded cellulose pool
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0                        (kgC/m2)  litter carbon, lignin pool
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0        (kgC/m2)  soil carbon, fast microbial recycling pool
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0      (kgC/m2)  soil carbon, medium microbial recycling pool
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0        (kgC/m2)  soil carbon, slow microbial recycling pool
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0           (kgC/m2)  soil carbon, recalcitrant SOM (slowest)
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0                      (kgN/m2)  litter nitrogen, labile pool
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0               (kgN/m2)  soil mineralized nitrogen, NH4 pool
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0               (kgN/m2)  soil mineralized nitrogen, NO3 pool
+
+CLIM_CHANGE
+0.0                                                                                          (degC) - offset for Tmax
+0.0                                                                                          (degC) - offset for Tmin
+1.0                                                                                      (degC) - multiplier for PRCP
+1.0                                                                                       (degC) - multiplier for VPD
+1.0                                                                                       (degC) - multiplier for RAD
+
+CONDITIONAL_MANAGEMENT_STRATEGIES
+0                                                                         (flag) conditional mowing ? 0 - no, 1 - yes
+0.0                                                                      (m2/m2) fixed value of the LAI before MOWING
+0.0                                                                       (m2/m2) fixed value of the LAI after MOWING
+0.0                                                               (%) transported part of plant material after MOWING
+0                                                                      (flag) conditional irrigation? 0 - no, 1 - yes
+0.0                                                     (prop) SMSI before cond. IRRIGATION (-9999: SWCratio is used)
+0.0                                         (prop) SWCratio of rootzone before cond. IRRIGATION (-9999: SMSI is used)
+0.0                                                                (prop) SWCratio of rootzone after cond. IRRIGATION
+0.0                                                                      (kgH2O/m2) maximum amount of irrigated water
+
+OUTPUT_CONTROL
+hhs_MuSo6                                                                    (filename) output prefix
+1                                         (flag)  writing daily output (0 = no; 1 = binary; 2 = ascii; 3 = on-screen)
+0                      (flag)  writing monthly average of daily output (0 = no; 1 = binary; 2 = ascii; 3 = on-screen)
+0                       (flag)  writing annual average of daily output (0 = no; 1 = binary; 2 = ascii; 3 = on-screen)
+0                                        (flag)  writing annual output (0 = no; 1 = binary; 2 = ascii; 3 = on-screen)
+1                                                                            (flag)  for on-screen progress indicator
+
+DAILY_OUTPUT
+12                                                                                  number of daily output variables
+2520                                                                                                         proj_lai
+3009                                                                                                        daily_GPP
+3014                                                                                                       daily_Reco
+171                                                                                                       evapotransp
+2502                                                                                                        n_actphen
+2603                                                                                                       vwc00-03cm
+2604                                                                                                       vwc03-10cm
+2605                                                                                                       vwc10-30cm
+75                                                                                                                GDD
+2636                                                                                                    rooting_depth
+2716                                                                                                     m_soilstress
+671                                                                                                    m_vegc_to_SNSC
+
+ANNUAL_OUTPUT
+16                                                                                  number of annual output variables
+3000                                                                                                          annprcp
+3001                                                                                                          anntavg
+3002                                                                                                        annrunoff
+3003                                                                                                       annoutflow
+2734                                                                                                       annmax_lai
+3031                                                                                                    cum_Closs_MGM
+3032                                                                                                    cum_Cplus_MGM
+3045                                                                                                   cum_Closs_SNSC
+3046                                                                                                   cum_Cplus_STDB
+3058                                                                                                             vegc
+3064                                                                                                           totalc
+3066                                                                                                      SOM_C_top30
+3070                                                                                                     SOM_C_30to60
+3071                                                                                                     SOM_C_60to90
+3068                                                                                                        NH4_top30
+3069                                                                                                        NO3_top30
+
+END_INIT

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/inst/examples/hhs/parameters.csv

@@ -0,0 +1,15 @@
+ABREVIATION,INDEX,min,max      MuSo6
+TRANSFERGROWTHP,11,0.1,1
+T_BASE,13,0,8
+WPM,25,0,0.1
+CN_leaf,26,14.3,58.8
+CWIC,49,0.01,0.07
+CLEC,50,0.3,0.8
+FLNR,56,0.1,0.2
+MSTOMACOND,58,0.001,0.007
+ROOTDEPTH,64,0.5,3
+ROOTDISTRIB,65,0.2,5
+RELSWCCRIT1,96,0.97,1
+RELSWCCRIT2,97,0.4,1
+SENESCENCABG,101,0,0.1
+SLA,137.60,10,60

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/inst/examples/hhs/s.ini

@@ -0,0 +1,147 @@
+BBGCMuSo simulation
+
+MET_INPUT
+hhs.mtc43                                                                            (filename) met file name
+4                                                                            (int) number of header lines in met file
+365                                                  (int) number of simdays in last simyear (truncated year: <= 365)
+
+RESTART
+0                                                                      (flag) 1 = read restart; 0 = dont read restart
+1                                                                    (flag) 1 = write restart; 0 = dont write restart
+hhs_MuSo6.endpoint                                          (filename) name of the input restart file
+hhs_MuSo6.endpoint                                         (filename) name of the output restart file
+
+TIME_DEFINE
+54                                                                                  (int) number of simulation years 
+1961                                                                                      (int) first simulation year
+1                                                                               (flag) 1 = spinup run; 0 = normal run
+6000                                                                             (int) maximum number of spinup years
+
+CO2_CONTROL
+1                                                                                 (flag) 0=constant; 1=vary with file
+290.0                                                                    (ppm) constant atmospheric CO2 concentration
+CO2.txt                                                                           (filename) name of the CO2 file
+
+NDEP_CONTROL
+1                                                                                 (flag) 0=constant; 1=vary with file
+0.000200                                                              (kgN/m2/yr) wet+dry atmospheric deposition of N
+Ndep.txt                                                                  (filename)  name of the N-dep file
+
+SITE
+248.0                                                                                             (m)  site elevation
+46.95                                                                          (degrees) site latitude (- for S.Hem.)
+0.20                                                                                      (DIM) site shortwave albedo
+9.00                                                                            (Celsius) mean annual air temperature
+10.15                                                                     (Celsius) mean annual air temperature range
+0.50                                                                  (prop.) proprortion of NH4 flux of N-deposition
+
+SOIL_FILE
+hhs.soi                                                                  (filename) SOIL filename
+
+EPC_FILE
+c3grass_muso6.epc                                                                 (filename) EPC filename
+
+MANAGEMENT_FILE
+none                                                                              (filename) MGM filename (or "none")
+
+SIMULATION_CONTROL
+1                                            (flag) phenology flag (1 = MODEL PHENOLOGY 0 = USER-SPECIFIED PHENOLOGY)
+1                                   (flag) vegper calculation method if MODEL PHENOLOGY is used (0: original, 1: GSI)
+0                                    (flag) transferGDD flag (1= transfer calc. from GDD 0 = transfer calc. from EPC)
+1                                        (flag) q10 flag (1 = temperature dependent q10 value; 0= constans q10 value)
+1                                      (flag) acclimation flag of photosynthesis (1 = acclimation 0 = no acclimation)
+1                                         (flag) acclimation flag of respiration (1 = acclimation 0 = no acclimation)
+1                                                 (flag) CO2 conductance reduction flag (0: no effect, 1: multiplier)
+0                                                     (flag) soil temperature calculation method (0: Zheng, 1: DSSAT)
+1                                         (flag) soil hydrological calculation method (0: Richards, 1: tipping DSSAT)
+0                         (int) discretization level of soil hydr.calc.[Richards-method] (0: low, 1: medium, 2: high)
+0                                                    (flag) photosynthesis calculation method (0: Farquhar, 1: DSSAT)
+0                               (flag) evapotranspiration calculation method (0: Penman-Montieth, 1: Priestly-Taylor)
+0                                                               (flag) radiation calculation method (0: SWabs, 1: Rn)
+0                                  (flag) soilstress calculation method (0: based on VWC, 1: based on transp. demand)
+
+W_STATE
+0.0                                                                                  (kg/m2) water stored in snowpack
+1.0                                                        (DIM) initial soil water as a proportion of field capacity
+
+CN_STATE
+0.001                                                                        (kgC/m2)  first-year maximum leaf carbon
+0.001                                                                   (kgC/m2)  first-year maximum fine root carbon
+0.001                                                                       (kgC/m2)  first-year maximum fruit carbon
+0.001                                                                    (kgC/m2)  first-year maximum softstem carbon
+0.001                                                             (kgC/m2)  first-year maximum live woody stem carbon
+0.001                                                            (kgC/m2)  first-year maximum live coarse root carbon
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0                        (kgC/m2)  coarse woody debris carbon
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0                        (kgC/m2)  litter carbon, labile pool
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0          (kgC/m2)  litter carbon, unshielded cellulose pool
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0            (kgC/m2)  litter carbon, shielded cellulose pool
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0                        (kgC/m2)  litter carbon, lignin pool
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0        (kgC/m2)  soil carbon, fast microbial recycling pool
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0      (kgC/m2)  soil carbon, medium microbial recycling pool
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0        (kgC/m2)  soil carbon, slow microbial recycling pool
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0           (kgC/m2)  soil carbon, recalcitrant SOM (slowest)
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0                      (kgN/m2)  litter nitrogen, labile pool
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0               (kgN/m2)  soil mineralized nitrogen, NH4 pool
+0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0               (kgN/m2)  soil mineralized nitrogen, NO3 pool
+
+CLIM_CHANGE
+0.0                                                                                          (degC) - offset for Tmax
+0.0                                                                                          (degC) - offset for Tmin
+1.0                                                                                      (degC) - multiplier for PRCP
+1.0                                                                                       (degC) - multiplier for VPD
+1.0                                                                                       (degC) - multiplier for RAD
+
+CONDITIONAL_MANAGEMENT_STRATEGIES
+0                                                                         (flag) conditional mowing ? 0 - no, 1 - yes
+0.0                                                                      (m2/m2) fixed value of the LAI before MOWING
+0.0                                                                       (m2/m2) fixed value of the LAI after MOWING
+0.0                                                               (%) transported part of plant material after MOWING
+0                                                                      (flag) conditional irrigation? 0 - no, 1 - yes
+0.0                                                     (prop) SMSI before cond. IRRIGATION (-9999: SWCratio is used)
+0.0                                         (prop) SWCratio of rootzone before cond. IRRIGATION (-9999: SMSI is used)
+0.0                                                                (prop) SWCratio of rootzone after cond. IRRIGATION
+0.0                                                                      (kgH2O/m2) maximum amount of irrigated water
+
+OUTPUT_CONTROL
+hhs_MuSo6_Spinup                                                                                 (filename) output prefix
+0                                         (flag)  writing daily output (0 = no; 1 = binary; 2 = ascii; 3 = on-screen)
+0                      (flag)  writing monthly average of daily output (0 = no; 1 = binary; 2 = ascii; 3 = on-screen)
+0                       (flag)  writing annual average of daily output (0 = no; 1 = binary; 2 = ascii; 3 = on-screen)
+2                                        (flag)  writing annual output (0 = no; 1 = binary; 2 = ascii; 3 = on-screen)
+1                                                                            (flag)  for on-screen progress indicator
+
+DAILY_OUTPUT
+12                                                                                   number of daily output variables
+2502                                                                                                        n_actphen
+2603                                                                                                       vwc00-03cm
+2604                                                                                                       vwc03-10cm
+2605                                                                                                       vwc10-30cm
+75                                                                                                                GDD
+2636                                                                                                    rooting_depth
+2716                                                                                                     m_soilstress
+671                                                                                                    m_vegc_to_SNSC
+171                                                                                                       evapotransp
+3009                                                                                                        daily_gpp
+3014                                                                                                         daily_tr
+2520                                                                                                         proj_lai
+
+ANNUAL_OUTPUT
+16                                                                                  number of annual output variables
+3000                                                                                                          annprcp
+3001                                                                                                          anntavg
+3002                                                                                                        annrunoff
+3003                                                                                                       annoutflow
+2734                                                                                                       annmax_lai
+3031                                                                                                    cum_Closs_MGM
+3032                                                                                                    cum_Cplus_MGM
+3045                                                                                                   cum_Closs_SNSC
+3046                                                                                                   cum_Cplus_STDB
+3058                                                                                                             vegc
+3064                                                                                                           totalc
+3066                                                                                                      SOM_C_top30
+3070                                                                                                     SOM_C_30to60
+3071                                                                                                     SOM_C_60to90
+3068                                                                                                        NH4_top30
+3069                                                                                                        NO3_top30
+
+END_INIT

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/inst/markdowns/parameterSweep.rmd

@@ -0,0 +1,115 @@
+---
+title: "ParameterSweep"
+auth or: ""
+date: "`r format(Sys.time(), '%d %B, %Y')`"
+output: html_document
+---
+
+```{r setup, include=FALSE}
+knitr::opts_chunk$set(echo = TRUE)
+```
+
+```{r,echo=FALSE}
+library("RBBGCMuso")
+
+quickAndDirty <- function(settings, parameters, inputDir= "./", outLoc, iterations=2, outVar=8,){
+
+
+
+    outLocPlain <- basename(outLoc)
+    currDir <- getwd()
+    inputDir <- normalizePath(inputDir)
+    tmp <- file.path(outLoc,"tmp/")
+
+    if(!dir.exists(outLoc)){
+        dir.create(outLoc)
+        warning(paste(outLoc," is not exists, so it was created"))
+    }
+
+    if(dir.exists(tmp)){
+        stop("There is a tmp directory inside the output location, please replace it. tmp is an important temporary directory for the function")
+    }
+    dir.create(tmp)
+    outLoc <- normalizePath(outLoc)
+    tmp <- normalizePath(tmp)
+
+    inputFiles <- file.path(inputDir,grep(basename(outLoc),list.files(inputDir),invert = TRUE,value = TRUE)) 
+
+    
+    for(i in inputFiles){
+        file.copy(i,tmp)
+    }
+    
+    setwd(tmp)
+
+    if(is.null(settings)){
+        settings <- setupMuso()
+    }
+
+
+    
+    file.copy(settings$epcInput[2],"epc-save",overwrite = TRUE)
+    calibrationPar <- matrix[,"INDEX"]
+    npar <- nrow(matrix)
+    paramMatrices <- list()    
+    parameters <- matrix(nrow = npar,ncol = iterations)
+    paramtest <- parameters
+    rownames(paramtest) <- matrix[,1]
+   
+    for(i in 1:npar){
+        parameters[i,] <- seq(from=matrix[i,5],to=matrix[i,6],length=iterations)
+        #print(parameters[i,])
+        settings$calibrationPar <- calibrationPar[i]
+        for(j in 1:iterations){
+            p <- try(calibMuso(settings,parameters =parameters[i,j],silent=TRUE))
+
+            if(length(p)>1){
+                   paramtest[i,j] <- max(p[,outVar])
+                #   print(paramtest)
+            } else {
+                paramtest[i,j] <- NA
+              #  print(paramtest)
+            }                   
+        }
+      file.copy("epc-save",settings$epcInput[2],overwrite = TRUE)    
+    }
+    
+  print("###################################################")
+   paramMatrices <- (function(){
+       for(i in 1:nrow(paramtest)){
+           matrx <- matrix(ncol = 2,nrow=iterations)
+           matrx[,1] <- parameters[i,]
+           matrx[,2] <- paramtest[i,]
+           paramMatrices[[i]] <- matrx
+           names(paramMatrices)[i] <- rownames(paramtest)[i]
+       }
+       return(paramMatrices)
+   })()
+
+    
+    return(list(paramtest,paramMatrices))
+
+
+}
+
+```
+
+
+```{r, echo=FALSE,cache=TRUE}
+parconstrains <- read.csv("parconstrains_extended.csv")
+settings <- setupMuso()
+parSeq<-quickAndDirty(settings = settings,matrix = parconstrains,outVar = 8,iterations = 5)
+```
+
+```{r}
+parSeq
+```
+
+```{r,echo=FALSE}
+ parlist<-parSeq[[2]]
+ lparlist<-length(parlist)
+ for(i in 1:lparlist){
+   title<-names(parlist)[i]
+  plot(x = parlist[[i]][,1], y= parlist[[i]][,2], ylim=c(0,15), main=title,ylab="LAI")  
+ }
+```

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/inst/markdowns/parameters.csv

@@ -0,0 +1,14 @@
+NAME,INDEX,MIN,MAX
+BASETEMP,25,3,9
+WPM,36,0,0.1
+CN_lv,38,10,50
+CN_li,39,32,70
+CN_root,40,20,70
+CN_fruit,41,10.50,70
+CN_stem,42,0,70
+CLEC,55,0.4,0.8
+FLNR,61,0.05,0.8
+STOMA,63,0.003,0.015
+ROOTDEPTH,74,0.3,2.
+SWCGERMIN,87,0.2,0.9
+NH4MOBILEPROP,120,0.05,0.7

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/inst/tests/test_postProcMuso.R

@@ -0,0 +1,21 @@
+context("Post processing")
+library(testthat)
+library(RBBGCMuso)
+setwd(system.file("examples/hhs","",package = "RBBGCMuso"))
+
+test_that("Post processing string",{
+    testMatrix1 <- data.frame(first = rep(1,5), second = rep(2,5), third = rep(3,5))
+    testMatrix1c <- testMatrix1 
+    testMatrix1c[,"newCol"] <- testMatrix1c[,2] + 3 * testMatrix1c[,3] 
+    expect_equal(postProcMuso(testMatrix1,"newCol <- @2 + 3*@3"),testMatrix1c)
+})
+
+test_that("calibMuso with postprocessing",{
+    model <- calibMuso(skipSpinup = FALSE, silent = TRUE)
+    modelc<- model
+    newCol <- modelc[,1]
+    modelc<- cbind.data.frame(modelc,newCol)
+    modelc[,"newCol"]<- model[,5]+3*model[,7]
+    expect_equal(calibMuso(skipSpinup = FALSE,silent = TRUE, postProcString = "newCol <- @5 + 3* @7"), modelc)
+})
+

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/alignData.Rd

@@ -0,0 +1,21 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/musoTime.R
+\name{alignData}
+\alias{alignData}
+\title{alignData}
+\usage{
+alignData(
+  mdata,
+  dataCol,
+  modellSettings = NULL,
+  startDate = NULL,
+  endDate = NULL,
+  formatString = "\%Y-\%m-\%d",
+  leapYear = TRUE,
+  continious = FALSE
+)
+}
+\description{
+This function align the data to the model and the model to the data
+}
+\keyword{internal}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/calibMuso.Rd

@@ -0,0 +1,49 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/calibMuso.R
+\name{calibMuso}
+\alias{calibMuso}
+\title{calibMuso}
+\usage{
+calibMuso(settings,parameters=NULL, timee="d", debugging=FALSE, logfilename=NULL,
+keepEpc=FALSE, export=FALSE, silent=FALSE, aggressive=FALSE, leapYear=FALSE)
+}
+\arguments{
+\item{settings}{You have to run the setupMuso function before calibMuso. It is its output which contains all of the necessary system variables. It sets the whole running environment}
+
+\item{parameters}{In the settings variable you have set the row indexes of the variables, you wish to change. In this parameter you can give an exact value for them in a vector like: c(1,2,3,4)}
+
+\item{timee}{The required timesteps in the modell output. It can be "d", if it is daily, "m", if it's monthly, "y", it it is yearly. I recommend to use daily data, the yearly and monthly data is not well-tested yet.}
+
+\item{debugging}{If it is TRUE, it copies the log file to a Log directory to store it, if it is stamplog it contatenate a number before the logfile, which is one more than the maximum of the represented ones in the LOG directory. If it is true or stamplog it collects the "wrong" logfiles}
+
+\item{logfilename}{If you want to set a specific name for your logfiles you can set this via logfile parameter}
+
+\item{keepEpc}{If TRUE, it keeps the epc file and stamp it, after these copies it to the EPCS directory. If debugging True or false, it copies the wrong epc files to the wrong epc directory.}
+
+\item{export}{if it is yes or you give a filename here, it converts the ouxtput to the specific extension. For example, if you set export to "example.csv", it converts the output to "csv", if you set it to "example.xls" it converts to example.xls with the xlsx package. If it is not installed it gives back a warning message and converts it to csv.}
+
+\item{silent}{If you set it TRUE all off the modells output to the screen will be suppressed. It can be usefull, because it increases the model-speed.}
+
+\item{aggressive}{It deletes every possible modell-outputs from the previous modell runs.}
+
+\item{keepBinary}{In default RBBGCMuso to keep  working area as clean as possible, deletes all the regular output files. The results are directly printed to the standard output, but you can redirect it, and save it to a variable, or you can export your results to the desired destination in a desired format. Whith this variable you can enable to keep the binary output files. If you want to set the location of the binary output, please take a look at the binaryPlace argument.}
+
+\item{binaryPlace}{The place of the binary output files.}
+
+\item{fileToChange}{You can change any line of the epc or the ini file, you just have to specify with this variable which file you van a change. Two options possible: "epc", "ini"}
+
+\item{skipSpinup}{If TRUE, calibMuso wont do spinup simulation}
+
+\item{prettyOut}{date ad Date type, separate year, month, day vectors}
+
+\item{leapYear}{Should the function do a leapyear correction on the outputdata? If TRUE, then the 31.12 day will be doubled.}
+}
+\value{
+No return, outputs are written to file
+}
+\description{
+This function changes the epc file and after that  runs the BBGC-MuSo model and reads in its outputfile in a well-structured way.
+}
+\author{
+Roland Hollos
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/calibrateMuso.Rd

@@ -0,0 +1,43 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/calibrateMuso.R
+\name{calibrateMuso}
+\alias{calibrateMuso}
+\title{calibrateMuso}
+\usage{
+calibrateMuso(
+  measuredData,
+  parameters = read.csv("parameters.csv", stringsAsFactor = FALSE),
+  startDate = NULL,
+  endDate = NULL,
+  formatString = "\%Y-\%m-\%d",
+  dataVar,
+  outLoc = "./calib",
+  preTag = "cal-",
+  settings = setupMuso(),
+  outVars = NULL,
+  iterations = 100,
+  skipSpinup = TRUE,
+  plotName = "calib.jpg",
+  modifyOriginal = TRUE,
+  likelihood,
+  uncertainity = NULL,
+  naVal = NULL,
+  postProcString = NULL,
+  thread_prefix = "thread",
+  numCores = (parallel::detectCores() - 1),
+  pb = txtProgressBar(min = 0, max = iterations, style = 3),
+  maxLikelihoodEpc = TRUE,
+  pbUpdate = setTxtProgressBar,
+  outputLoc = "./",
+  method = "GLUE",
+  lg = FALSE,
+  w = NULL,
+  ...
+)
+}
+\description{
+This funtion uses the Monte Carlo technique to uniformly sample the parameter space from user defined parameters of the Biome-BGCMuSo model. The sampling algorithm ensures that the parameters are constrained by the model logic which means that parameter dependencies are fully taken into account (parameter dependency means that e.g leaf C:N ratio must be smaller than C:N ratio of litter; more complicated rules apply to the allocation parameters where the allocation fractions to different plant compartments must sum up 1). This function implements a mathematically correct solution to provide uniform distriution for all selected parameters.
+}
+\author{
+Roland HOLLOS
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/changemulline.Rd

@@ -0,0 +1,14 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/changeMuso.R
+\name{changemulline}
+\alias{changemulline}
+\title{changemulline}
+\usage{
+changemulline(filePaths, calibrationPar, contents, src, outFiles = filePaths)
+}
+\description{
+The function uses the previous changspecline function to operate.
+}
+\author{
+Roland Hollos
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/checkFileSystem.Rd

@@ -0,0 +1,16 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/flat.R
+\name{checkFileSystem}
+\alias{checkFileSystem}
+\title{checkFileSystem}
+\usage{
+checkFileSystem(iniName, root = ".", depTree = options("RMuso_depTree")[[1]])
+}
+\arguments{
+\item{iniName}{The name of the ini file}
+
+\item{depTree}{The file dependency defining dataframe. At default it is:  options("RMuso_depTree")[[1]]}
+}
+\description{
+This function checks the MuSo file system, if it is correct
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/checkMeteoBGC.Rd

@@ -0,0 +1,33 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/checkMeteoBGC.R
+\name{checkMeteoBGC}
+\alias{checkMeteoBGC}
+\title{checkMeteoBGC}
+\usage{
+checkMeteoBGC(
+  settings = NULL,
+  skip = 4,
+  numericReport = FALSE,
+  type = "normal"
+)
+}
+\arguments{
+\item{settings}{The output of setupMuso}
+
+\item{skip}{Number of header lines in meteorology file.}
+
+\item{numericReport}{If numericReport is set to FALSE, the function returns with a text report. If numericReport is set to TRUE, the function returns with a numeric report.}
+
+\item{type}{meteorology for spinup or normal run}
+
+\item{metFileName}{The name of the meteorology file (mtc43).}
+}
+\value{
+It depends on the numericReport parameter. The function returns with a text report, or with a numeric report.
+}
+\description{
+This function calculates the daily and yearly statistics for a given meteorology file (mtc43).
+}
+\author{
+Erzsebet Kristof
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/cleanupMuso.Rd

@@ -0,0 +1,21 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/cleanup.R
+\name{cleanupMuso}
+\alias{cleanupMuso}
+\title{cleanupMuso}
+\usage{
+cleanupMuso(location=NULL, simplicity=TRUE,deep=FALSE)
+}
+\arguments{
+\item{location}{This is the place (directory) where your output files are located.}
+
+\item{simplicity}{TRUE or FALSE. If TRUE cleanupMuso will erase only the log files from the location}
+
+\item{deep}{If it is TRUE, it will delete every files from the subdirectories also}
+}
+\description{
+cleanupMuso can erase all of the unnecessary log and output files.
+}
+\author{
+Roland HOLLOS
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/compareCalibratedWithOriginal.Rd

@@ -0,0 +1,21 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/multiSite.R
+\name{compareCalibratedWithOriginal}
+\alias{compareCalibratedWithOriginal}
+\title{compareCalibratedWithOriginal}
+\usage{
+compareCalibratedWithOriginal(
+  key,
+  modOld,
+  modNew,
+  mes,
+  likelihoods,
+  alignIndexes,
+  musoCodeToIndex,
+  nameGroupTable,
+  groupFun
+)
+}
+\description{
+This functions compareses the likelihood and the RMSE values of the simulations and the measurements
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/compareMuso.Rd

@@ -0,0 +1,33 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plotMuso.R
+\name{compareMuso}
+\alias{compareMuso}
+\title{compareMuso}
+\usage{
+compareMuso(
+  settings = NULL,
+  parameters,
+  variable = 1,
+  calibrationPar = NULL,
+  fileToChange = "epc",
+  skipSpinup = TRUE,
+  timeFrame = "day"
+)
+}
+\arguments{
+\item{settings}{RBBGCMuso uses variables that define the entire simulation environment. Those environment variables include the name of the INI files, the name of the meteorology files, the path to the model executable and its file name, the entire output list, the entire output variable matrix, the dependency rules for the EPC parameters etc. Using the runMuso function RBBGCMuso can automatically create those environment variables by inspecting the files in the working directory (this happens through the setupMuso function). It means that by default model setup is performed automatically in the background and the user has nothing to do. With this settings parameter we can force runMuso to skip automatic environment setup as we provide the environment settings to runMuso. In a typical situation the user can skip this option.}
+
+\item{parameters}{Using this function it is possible to change some of the EPC parameters prior to model execution. This can be achieved with this option. In the parameters variable you have set the row indices of the variables that you wish to change. In this parameters you can give an exact value for them in a vector form like c(1,2,3,4).}
+
+\item{variable}{The name of the output variable to plot}
+
+\item{calibrationPar}{You might want to change some parameters in your EPC file before running the model. This function offers possibility for this without editing the EPC file. In this situation you have to select the appropirate model parameters first. You can refer to these parameters with the number of the line in the EPC file. Indexing of lines start from one. You should use a vector for this referencing like c(1,5,8)}
+
+\item{fileToChange}{You can change any line of the EPC or the INI file. Please choose "EPC", "INI" or "BOTH". This file will be used for the analysis, and the original parameter values will be changed according to the choice of the user.}
+}
+\description{
+This function runs the model, then changes one of its input data, runs it again, and plots both results in one graph.
+}
+\author{
+Roland HOLLOS
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/copyMusoExampleTo.Rd

@@ -0,0 +1,16 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/musoExample.R
+\name{copyMusoExampleTo}
+\alias{copyMusoExampleTo}
+\title{copyMusoExampleTo}
+\usage{
+copyMusoExampleTo(example = NULL, destination = NULL)
+}
+\arguments{
+\item{example}{This is the name of the example file. If it is not set then a simple graphical user interface (tcl/tk menu) will open to select the target dataset (which is typically an experimental site). In the list hhs means the Hegyhatsal eddy covariance site in Hungary.}
+
+\item{destination}{The destination where the example files will be copied.}
+}
+\description{
+This function enables the user to download a complete, working file set to quickly start using Biome-BGCMuSo through RBBGCMuso (or in standalone mode). The user has to specify the target directory for the files. The file set contains the model executable (muso.exe in Windows), the INI files that drive the model, and other files like meteorology input, ecophysiological constants file (EPC), and other ancillary files (CO2 concentration, parameter range definition file called parameters.csv). Note that we strongly recommend to read the User's Guide of Biome-BGCMuSo to clarify the meaning of the input files. The input files (s.ini, n.ini, maize.epc, meteorology files) are simple text files, so the user can read (and modify) them with his/her favourite text editor (like Editpad Lite, vim, emacs). Note that some files use UNIX/Linux style text which means that the text will not be readable using the Windows Notepad.
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/corrigMuso.Rd

@@ -0,0 +1,22 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/otherUsefullFunctions.R
+\name{corrigMuso}
+\alias{corrigMuso}
+\title{corrigMuso}
+\usage{
+corrigMuso(settings, data)
+}
+\arguments{
+\item{settings}{This is the output of the setupMuso() function. It contains all of the RBBGCMuso settings}
+
+\item{data}{the models outputdata}
+}
+\value{
+It returns the modells leapyear-corrigated output data.
+}
+\description{
+This function leapyear-corrigate the output of the modell
+}
+\author{
+Roland Hollos
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/createSoilFile.Rd

@@ -0,0 +1,11 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/soilQuery.R
+\name{createSoilFile}
+\alias{createSoilFile}
+\title{createSoilFile}
+\description{
+This function collects soil data from a given restapi, de default is soilGrid
+}
+\author{
+Roland HOLLOS
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/dynRound.Rd

@@ -0,0 +1,22 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/assistantFunctions.R
+\name{dynRound}
+\alias{dynRound}
+\title{dynRound}
+\usage{
+dynRound(x, y, seqLen)
+}
+\arguments{
+\item{x}{The lower end of the sequence}
+
+\item{y}{The higher end of the sequence}
+
+\item{seqLen}{The length of the sequence}
+}
+\value{
+rounded sequence
+}
+\description{
+This function rounds a sequence (definded by its endpoints and the length) optimally
+}
+\keyword{internal}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/fextension.Rd

@@ -0,0 +1,20 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/otherUsefullFunctions.R
+\name{fextension}
+\alias{fextension}
+\title{fextension}
+\usage{
+fextension(filename)
+}
+\arguments{
+\item{filename}{The string of the filenam}
+}
+\value{
+the extension of the given file
+}
+\description{
+A function for extracting the extension name from the filename string
+}
+\author{
+Roland Hollos
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/flatMuso.Rd

@@ -0,0 +1,25 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/flat.R
+\name{flatMuso}
+\alias{flatMuso}
+\title{flatMuso}
+\usage{
+flatMuso(
+  iniName,
+  execPath = "./",
+  depTree = options("RMuso_depTree")[[1]],
+  directory = "flatdir",
+  d = TRUE,
+  outE = TRUE
+)
+}
+\arguments{
+\item{iniName}{The name of the ini file}
+
+\item{depTree}{The file dependency defining dataframe. At default it is:  options("RMuso_depTree")[[1]]}
+
+\item{directory}{The destination directory for flattening. At default it will be flatdir}
+}
+\description{
+This function reads the ini file and creates a directory (named after the directory argument) with all the files the modell uses with this file. the directory will be flat.
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/getAnnualOutputList.Rd

@@ -0,0 +1,14 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/getOutPutList.R
+\name{getAnnualOutputList}
+\alias{getAnnualOutputList}
+\title{getAnnualOutputList}
+\usage{
+getAnnualOutputList(settings = NULL)
+}
+\arguments{
+\item{settings}{bla}
+}
+\description{
+bla bla
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/getConstMatrix.Rd

@@ -0,0 +1,19 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/otherUsefullFunctions.R
+\name{getConstMatrix}
+\alias{getConstMatrix}
+\title{getConstMatrix}
+\usage{
+getConstMatrix(
+  filetype = "epc",
+  version = as.character(getOption("RMuso_version"))
+)
+}
+\arguments{
+\item{filetype}{It can be "epc" or "soil".}
+
+\item{version}{The version of the MuSo environment}
+}
+\description{
+getConstMatrix is a function whith wich you can get the default constrain matrix for your choosen type and version.
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/getDailyOutputList.Rd

@@ -0,0 +1,14 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/getOutPutList.R
+\name{getDailyOutputList}
+\alias{getDailyOutputList}
+\title{getDailyOutputList}
+\usage{
+getDailyOutputList(settings = NULL)
+}
+\arguments{
+\item{settings}{bla}
+}
+\description{
+bla bla
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/getFilePath.Rd

@@ -0,0 +1,23 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/flat.R
+\name{getFilePath}
+\alias{getFilePath}
+\title{getFilePath}
+\usage{
+getFilePath(
+  iniName,
+  fileType,
+  execPath = "./",
+  depTree = options("RMuso_depTree")[[1]]
+)
+}
+\arguments{
+\item{iniName}{The name of the ini file}
+
+\item{depTree}{The file dependency defining dataframe. At default it is:  options("RMuso_depTree")[[1]]}
+
+\item{filetype}{The type of the choosen file. For options see options("RMuso_depTree")[[1]]$name}
+}
+\description{
+This function reads the ini file and for a chosen fileType it gives you the filePath
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/getFilesFromIni.Rd

@@ -0,0 +1,20 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/flat.R
+\name{getFilesFromIni}
+\alias{getFilesFromIni}
+\title{getFilesFromIni}
+\usage{
+getFilesFromIni(
+  iniName,
+  execPath = "./",
+  depTree = options("RMuso_depTree")[[1]]
+)
+}
+\arguments{
+\item{iniName}{The name of the ini file}
+
+\item{depTree}{The file dependency defining dataframe. At default it is:  options("RMuso_depTree")[[1]]}
+}
+\description{
+This function reads the ini file and gives yout back the path of all file involved in model run
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/getLogs.Rd

@@ -0,0 +1,20 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/assistantFunctions.R
+\name{getLogs}
+\alias{getLogs}
+\title{getLogs}
+\usage{
+getLogs(outputLoc, outputNames, type = "spinup")
+}
+\arguments{
+\item{outputLoc}{This is the location of the output files.}
+
+\item{outputNames}{These are the prefixes of the logfiles}
+}
+\value{
+Logfiles with paths
+}
+\description{
+This function gives us the muso logfiles with their path
+}
+\keyword{internal}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/getOutFiles.Rd

@@ -0,0 +1,20 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/assistantFunctions.R
+\name{getOutFiles}
+\alias{getOutFiles}
+\title{getOutFiles}
+\usage{
+getOutFiles(outputLoc, outputNames)
+}
+\arguments{
+\item{outputLoc}{This is the location of the output files.}
+
+\item{outputNames}{These are the prefixes of the logfiles.}
+}
+\value{
+Output files with their paths.
+}
+\description{
+This function gives us the muso output files with their paths
+}
+\keyword{internal}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/getSoilDataFull.Rd

@@ -0,0 +1,11 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/soilQuery.R
+\name{getSoilDataFull}
+\alias{getSoilDataFull}
+\title{getSoilDataFull}
+\description{
+This function collects soil data from a given restapi, de default is soilGrid
+}
+\author{
+Roland HOLLÓS
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/getyearlycum.Rd

@@ -0,0 +1,20 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/otherUsefullFunctions.R
+\name{getyearlycum}
+\alias{getyearlycum}
+\title{getyearlycum}
+\usage{
+getyearlycum(daily_observations)
+}
+\arguments{
+\item{daily_observations}{vector of the daily observations.}
+}
+\value{
+A vector of yearly data
+}
+\description{
+Funtion for getting cumulative yearly data from observations
+}
+\author{
+Roland Hollos
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/getyearlymax.Rd

@@ -0,0 +1,20 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/otherUsefullFunctions.R
+\name{getyearlymax}
+\alias{getyearlymax}
+\title{getyearlymax}
+\usage{
+getyearlymax(daily_observations)
+}
+\arguments{
+\item{daily_observations}{vector of the daily observations}
+}
+\value{
+A vector of yearly data
+}
+\description{
+Function for getting the maximum values of the years, from daily data
+}
+\author{
+Roland Hollos
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/multiSiteCalib.Rd

@@ -0,0 +1,64 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/multiSite.R
+\name{multiSiteCalib}
+\alias{multiSiteCalib}
+\title{multiSiteCalib}
+\usage{
+multiSiteCalib(
+  measurements,
+  calTable,
+  parameters,
+  dataVar,
+  iterations = 100,
+  burnin = ifelse(iterations < 3000, 3000, NULL),
+  likelihood,
+  execPath,
+  thread_prefix = "thread",
+  numCores = (parallel::detectCores() - 1),
+  pb = txtProgressBar(min = 0, max = iterations, style = 3),
+  pbUpdate = setTxtProgressBar,
+  copyThread = TRUE,
+  constraints = NULL,
+  th = 10,
+  treeControl = rpart.control()
+)
+}
+\arguments{
+\item{calTable}{A dataframe which contantains the ini file locations and the domains they belongs to}
+
+\item{parameters}{A dataframe with the name, the minimum, and the maximum value for the parameters used in MonteCarlo experiment}
+
+\item{dataVar}{A named vector where the elements are the MuSo variable codes and the names are the same as provided in measurements and likelihood}
+
+\item{iterations}{The number of MonteCarlo experiments to be executed}
+
+\item{burnin}{Currently not used, altought it is the length of burnin period of the MCMC sampling used to generate random parameters}
+
+\item{likelihood}{A list of likelihood functions which names are linked to dataVar}
+
+\item{execPath}{If you are running the calibration from different location than the MuSo executable, you have to provide the path}
+
+\item{thread_prefix}{The prefix of thread directory names in the tmp directory created during the calibrational process}
+
+\item{numCores}{The number of processes used during the calibration. At default it uses one less than the number of threads available}
+
+\item{pb}{The progress bar function. If you use (web-)GUI you can provide a different function}
+
+\item{pbUpdate}{The update function for pb (progress bar)}
+
+\item{copyThread}{A boolean, recreate tmp directory for calibration or not (case of repeating the calibration)}
+
+\item{th}{A trashold value for multisite calibration. What percentage of the site should satisfy the constraints.}
+
+\item{treeControl}{A list which controls (maximal complexity, maximal depth) the details of the decession tree making.}
+
+\item{measuremets}{The table which contains the measurements}
+
+\item{contsraints}{A dataframe containing the constraints logic the minimum and a maximum value for the calibration.}
+}
+\description{
+This funtion uses the Monte Carlo technique to uniformly sample the parameter space from user defined parameters of the Biome-BGCMuSo model. The sampling algorithm ensures that the parameters are constrained by the model logic which means that parameter dependencies are fully taken into account (parameter dependency means that e.g leaf C:N ratio must be smaller than C:N ratio of litter; more complicated rules apply to the allocation parameters where the allocation fractions to different plant compartments must sum up 1). This function implements a mathematically correct solution to provide uniform distriution of the random parameters on convex polytopes.
+}
+\author{
+Roland HOLLOS
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/multiSiteThread.Rd

@@ -0,0 +1,36 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/multiSite.R
+\name{multiSiteThread}
+\alias{multiSiteThread}
+\title{multiSiteThread}
+\usage{
+multiSiteThread(
+  measuredData,
+  parameters = NULL,
+  startDate = NULL,
+  endDate = NULL,
+  formatString = "\%Y-\%m-\%d",
+  calTable,
+  dataVar,
+  outLoc = "./calib",
+  outVars = NULL,
+  iterations = 300,
+  skipSpinup = TRUE,
+  plotName = "calib.jpg",
+  modifyOriginal = TRUE,
+  likelihood,
+  uncertainity = NULL,
+  burnin = NULL,
+  naVal = NULL,
+  postProcString = NULL,
+  threadNumber,
+  constraints = NULL,
+  th = 10
+)
+}
+\description{
+This is an
+}
+\author{
+Roland HOLLOS
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/musoDate.Rd

@@ -0,0 +1,21 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/musoTime.R
+\name{musoDate}
+\alias{musoDate}
+\title{musoDate}
+\usage{
+musoDate(
+  startYear,
+  endYears = NULL,
+  numYears,
+  combined = TRUE,
+  leapYearHandling = FALSE,
+  prettyOut = FALSE
+)
+}
+\description{
+This function generates MuSo compatibla dates for the data
+}
+\author{
+Roland HOLLOS
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/musoGlue.Rd

@@ -0,0 +1,24 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/calibration.R
+\name{musoGlue}
+\alias{musoGlue}
+\title{musoGlue}
+\usage{
+musoGlue(
+  presCalFile,
+  w,
+  delta = 0.17,
+  settings = setupMuso(),
+  parameters = read.csv("parameters.csv", stringsAsFactors = FALSE),
+  lg = FALSE
+)
+}
+\arguments{
+\item{plotName}{u}
+}
+\description{
+This function calculates the -users specified- likelihood for random model input.
+}
+\author{
+Roland HOLLOS
+}

RBBGCMuso.Rcheck/00_pkg_src/RBBGCMuso/man/musoMapping.Rd

@@ -0,0 +1,22 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/outputMapping.R
+\name{musoMapping}
+\alias{musoMapping}
+\title{musoMapping}
+\usage{
+musoMapping(code, mapData=NULL)
+}
+\arguments{
+\item{code}{the MuSo outputcode}
+
+\item{mapData}{updateMusomapping generated matrix}
+}
+\value{
+The name of the Biome-BGCMuSo output code (e.g. if code is 3009 this function should return GPP to the user)
+}
+\description{
+musoMapping can provide the user the name of a Biome-BGCMuSo output code. Within Biome-BGCMuSo the state variables and fluxes are marked by integer numbers. In order to provide meaningful variable names (e.g. 3009 means Gross Primary Production) a conversion table is needed which is utilized by this function. This function converts variable codes into names musoMappingFind does the opposite.
+}
+\author{
+Roland HOLLOS
+}