Merge pull request #20 from hollorol/feature/convex-dependency-refinement
solving the old dependency group problem
This commit is contained in:
Roland Hollós
GitHub
commit
12b6d580de
@ -150,6 +150,7 @@ readValuesFromFile <- function(filename, linums){
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return(values)
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}
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#' readMeasuredMuso
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#'
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#' MuSo data reader
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@ -12,6 +12,7 @@ calibrateMuso <- function(measuredData, parameters =read.csv("parameters.csv", s
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skipSpinup = TRUE, plotName = "calib.jpg",
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modifyOriginal=TRUE, likelihood, uncertainity = NULL,
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naVal = NULL, postProcString = NULL,
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sourceFile=NULL, # bases for musoRand if dependecy group is not fully defined by parameters.csv
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thread_prefix="thread", numCores = max(c(parallel::detectCores()-1,1)), pb = txtProgressBar(min=0, max=iterations, style=3),
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maxLikelihoodEpc=TRUE,
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pbUpdate = setTxtProgressBar, outputLoc="./", method="GLUE",lg = FALSE, w=NULL, ...){
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@ -44,6 +45,7 @@ calibrateMuso <- function(measuredData, parameters =read.csv("parameters.csv", s
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future({
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tryCatch(
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musoSingleThread(measuredData, parameters, startDate,
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sourceFile=settings$epc[2], # EPC SPECIFIC
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endDate, formatString,
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dataVar, outLoc,
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preTag, settings,
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@ -52,6 +54,7 @@ calibrateMuso <- function(measuredData, parameters =read.csv("parameters.csv", s
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modifyOriginal, likelihood, uncertainity,
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naVal, postProcString, i)
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, error = function(e){
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# browser()
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writeLines(as.character(iterations),"progress.txt")
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})
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@ -127,6 +130,19 @@ calibrateMuso <- function(measuredData, parameters =read.csv("parameters.csv", s
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switch(method,
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"GLUE"={
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musoGlue(results, parameters=parameters,settings=settings, w=w, lg=lg)
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liks <- results[,sprintf("%s_likelihood",names(likelihood))]
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epcIndexes <- future::value(fut[[1]], stdout = FALSE, signal=FALSE)
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if(ncol(liks) == 1){
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ml_place <- which.max(liks)
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} else {
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ml_place <- which.max(as.matrix(liks) %*% as.matrix(w))
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}
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epcVals <- results[ml_place,1:length(epcIndexes)]
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epcPlace <- file.path(dirname(settings$inputFiles),settings$epc)[2]
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changemulline(filePaths= epcPlace, epcIndexes,
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epcVals, src =epcPlace,# settings$epcInput[2],
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outFiles = file.path(outputLoc, "maxLikelihood_epc.epc"))
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names(epcVals) <- epcIndexes
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},
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"agromo"={
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liks <- results[,sprintf("%s_likelihood",names(likelihood))]
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@ -174,6 +190,7 @@ copyToThreadDirs <- function(prefix="thread", numcores=parallel::detectCores()-1
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}
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musoSingleThread <- function(measuredData, parameters = NULL, startDate = NULL,
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sourceFile=NULL,
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endDate = NULL, formatString = "%Y-%m-%d",
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dataVar, outLoc = "./calib",
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preTag = "cal-", settings = setupMuso(),
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@ -234,10 +251,10 @@ musoSingleThread <- function(measuredData, parameters = NULL, startDate = NULL,
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## row numbers
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print("optiMuso is randomizing the epc parameters now...",quote = FALSE)
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if(iterations < 3000){
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randVals <- musoRand(parameters = parameters,constrains = NULL, iterations = 3000)
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randVals[[2]]<- randVals[[2]][sample(1:3000,iterations),]
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randVals <- musoRand(parameters = parameters,constrains = NULL, iterations = 3000,sourceFile=sourceFile)
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randVals[[2]]<- randVals[[2]][sample(1:3000,iterations),] # TODO: last not random
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} else {
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randVals <- musoRand(parameters = parameters,constrains = NULL, iterations = iterations)
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randVals <- musoRand(parameters = parameters,constrains = NULL, iterations = iterations,sourceFile=sourceFile)
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}
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origEpc <- readValuesFromFile(settings$epc[2],randVals[[1]])
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@ -18,6 +18,7 @@
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musoMonte <- function(settings=NULL,
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parameters=NULL,
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sourceFile=NULL,
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inputDir = "./",
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outLoc = "./calib",
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iterations = 10,
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@ -100,7 +101,7 @@ musoMonte <- function(settings=NULL,
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##reading the original epc file at the specified
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## row numbers
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if(iterations < 3000){
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randVals <- musoRand(parameters = parameters,fileType="epc", iterations = 3000)
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randVals <- musoRand(parameters = parameters,fileType="epc", iterations = 3000,sourceFile=sourceFile)
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randVals[[2]]<- randVals[[2]][sample(1:3000,iterations),]
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} else {
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randVals <- musoRand(parameters = parameters,fileType="epc", iterations = iterations)
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@ -8,147 +8,182 @@
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#' @importFrom limSolve xsample
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#' @export
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musoRand <- function(parameters, iterations=3000, fileType="epc", constrains = NULL, burnin = NULL){
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musoRand <- function(parameters, iterations=3000, fileType="epc", sourceFile=NULL, constrains = NULL, burnin = NULL){
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if(is.null(constrains)){
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constMatrix <- constrains
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constMatrix <- getOption("RMuso_constMatrix")[[fileType]][[as.character(getOption("RMuso_version"))]]
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} else {
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constMatrix <- constrains
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}
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parameters <- parameters[,-1]
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constMatrix <- constMatrix[,-1]
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depTableMaker <- function(constMatrix,parameters){
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# browser()
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parameters <- parameters[order(parameters[,1]),] ## BUG!!!
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selectedRows <- constMatrix[,"INDEX"] %in% parameters[,1]
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# constMatrix[constMatrix[,"INDEX"] %in% parameters[,1],]
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rankList <- rank(constMatrix[selectedRows,2])
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constMatrix[selectedRows,c(5,6)] <- parameters[rankList,c(2,3)]
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logiConstrain <- (constMatrix[,"GROUP"] %in% constMatrix[constMatrix[,"INDEX"] %in% parameters[,1],"GROUP"] &
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(constMatrix[,"GROUP"]!=0)) | ((constMatrix[,"INDEX"] %in% parameters[,1]) & (constMatrix[,"GROUP"] == 0))
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constMatrix <- constMatrix[logiConstrain,]
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constMatrix <- constMatrix[order(apply(constMatrix[,7:8],1,function(x){x[1]/10+abs(x[2])})),]
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constMatrix
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logiConstrain <- (constMatrix[,"GROUP"] %in% constMatrix[constMatrix[,"INDEX"] %in% parameters[,1],"GROUP"] &
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(constMatrix[,"GROUP"]!=0)) | ((constMatrix[,"INDEX"] %in% parameters[,1]) & (constMatrix[,"GROUP"] == 0))
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constMatrix <- constMatrix[logiConstrain,]
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constMatrix <- constMatrix[order(apply(constMatrix[,7:8],1,function(x){x[1]/10+abs(x[2])})),]
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paragroups <- unique(constMatrix[constMatrix[,"GROUP"] != 0,"GROUP"])
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missingMembers <- list()
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for(group in paragroups){
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groupMembers <- constMatrix[constMatrix[,"GROUP"] == group,"INDEX"]
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missingMemberElems <- groupMembers[is.na(match(groupMembers,parameters[,1]))]
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if(length(missingMemberElems) > 0){
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missingMembers$indices <- c(missingMembers$indices,
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match(missingMemberElems,constMatrix[,"INDEX"]))
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if(is.null(sourceFile)){
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stop(sprintf("All group members of the group (%s) have to be in parameters if sourceFile not(epc file)",group))
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}
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missingMembers$values <- c(missingMembers$values,
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suppressWarnings(readValuesFromFile(sourceFile,missingMemberElems)))
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}
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}
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list(depTable=constMatrix,missingMembers=missingMembers)
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}
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# browser()
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genMat0 <- function(dep){
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numberOfVariable <- nrow(dep)
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G <- rbind(diag(numberOfVariable), -1*diag(numberOfVariable))
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h <- c(dependences[,5], -1*dependences[,6])
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return(list(G=G,h=h))
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genMat0 <- function(dep, missingIndices){
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numberOfVariable <- nrow(dep)
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if(length(missingMembers) != 0){
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dep <- dep[-missingIndices,]
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}
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G <- rbind(diag(numberOfVariable), -1*diag(numberOfVariable))
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h <- c(dependences[,5], -1*dependences[,6])
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return(list(G=G,h=h))
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}
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genMat1 <- function(dep, N){
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## Range <- sapply(list(min,max),function(x){
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## x(as.numeric(rownames(dep)))
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## }) It is more elegant, more general, but slower
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Range <- (function(x){
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c(min(x), max(x))
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})(as.numeric(dep[,"rowIndex"]))
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## Range <- sapply(list(min,max),function(x){
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## x(as.numeric(rownames(dep)))
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## }) It is more elegant, more general, but slower
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Range <- (function(x){
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c(min(x), max(x))
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})(as.numeric(dep[,"rowIndex"]))
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numberOfVariables <- nrow(dep)
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G<- -1*diag(numberOfVariables)
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numberOfVariables <- nrow(dep)
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G<- -1*diag(numberOfVariables)
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for(i in 1:numberOfVariables){
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if(dep[i,4]!=0){
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G[i,dep[i,4]] <- 1
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}
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for(i in 1:numberOfVariables){
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if(dep[i,4]!=0){
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G[i,dep[i,4]] <- 1
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}
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}
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# browser()
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G<-G[dep[,4]!=0,]
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}
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# browser()
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G<-G[dep[,4]!=0,]
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if(is.null(nrow(G))){
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G<-t(as.matrix(G))
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}
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numRowsInG <- nrow(G)
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if(Range[1]==1){
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G<-cbind(G,matrix(ncol=(N-Range[2]),nrow=numRowsInG,data=0))
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} else{
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if(Range[2]==N){
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G<-cbind(matrix(ncol=(Range[1]-1),nrow=numRowsInG,data=0),G)
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} else {
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G <- cbind(matrix(ncol=(Range[1]-1),nrow=numRowsInG,data=0),G,matrix(ncol=(N-Range[2]),nrow=numRowsInG,data=0))
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}
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}
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return(list(G=-1*G,h=-1*rep(0,nrow(G))))
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if(Range[1]==1){
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G<-cbind(G,matrix(ncol=(N-Range[2]),nrow=numRowsInG,data=0))
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} else{
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if(Range[2]==N){
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G<-cbind(matrix(ncol=(Range[1]-1),nrow=numRowsInG,data=0),G)
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} else {
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G <- cbind(matrix(ncol=(Range[1]-1),
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nrow=numRowsInG,data=0),
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G,
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matrix(ncol=(N-Range[2]),
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nrow=numRowsInG,data=0))
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}
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}
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return(list(G=-1*G,h=-1*rep(0,nrow(G))))
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}
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genMat2 <- function(dep, N){
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G <- rep(1,nrow(dep))
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G <- rep(1,nrow(dep))
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Range <- (function(x){
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c(min(x), max(x))
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})(as.numeric(dep[,"rowIndex"]))
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Range <- (function(x){
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c(min(x), max(x))
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})(as.numeric(dep[,"rowIndex"]))
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if(Range[1]==1){
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G<-c(G, numeric(N-Range[2]))
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} else{
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if(Range[2]==N){
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G<-c(numeric(Range[1]-1), G)
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} else {
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G <- c(numeric(Range[1]-1), G, numeric(N-Range[2]))
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}
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}
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if(Range[1]==1){
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G<-c(G, numeric(N-Range[2]))
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} else{
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if(Range[2]==N){
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G<-c(numeric(Range[1]-1), G)
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} else {
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G <- c(numeric(Range[1]-1), G, numeric(N-Range[2]))
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}
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}
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G <- t(matrix(sign(dep[2,4])*G))
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h <- abs(dep[1,4])
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G <- t(matrix(sign(dep[2,4])*G))
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h <- abs(dep[1,4])
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if(dep[1,"TYPE"]==2){ # This is not needed, I'll have to remove the if part, and keep the content
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G <- G*(-1)
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h <- h*(-1)
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}
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return(list(G=G,h=h))
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return(list(G=G,h=h))
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}
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genMat3 <- function(dep, N){
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Range <- (function(x){
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c(min(x), max(x))
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})(as.numeric(dep[,"rowIndex"]))
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Range <- (function(x){
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c(min(x), max(x))
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})(as.numeric(dep[,"rowIndex"]))
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E <- rep(1,nrow(dep))
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E <- rep(1,nrow(dep))
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if(Range[1]==1){
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E<-c(E, numeric(N-Range[2]))
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} else{
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if(Range[2]==N){
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E<-c(numeric(Range[1]-1), E)
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} else {
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E <- c(numeric(Range[1]-1), E, numeric(N-Range[2]))
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}
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}
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if(Range[1]==1){
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E<-c(E, numeric(N-Range[2]))
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} else{
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if(Range[2]==N){
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E<-c(numeric(Range[1]-1), E)
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} else {
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E <- c(numeric(Range[1]-1), E, numeric(N-Range[2]))
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}
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}
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E <- t(matrix(E))
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f <- dep[1,4]
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return(list(E=E,f=f))
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E <- t(matrix(E))
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f <- dep[1,4]
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return(list(E=E,f=f))
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}
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applyRandTypeG <- function(dep,N){
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type <- unique(dep[,"TYPE"])
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minR <- min(dep[,"rowIndex"])
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maxR <- max(dep[,"rowIndex"])
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switch(type,
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invisible(Gh <- genMat1(dep, N)),
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invisible(Gh <- genMat2(dep, N)))
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return(Gh)
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type <- unique(dep[,"TYPE"])
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minR <- min(dep[,"rowIndex"])
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maxR <- max(dep[,"rowIndex"])
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switch(type,
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invisible(Gh <- genMat1(dep, N)),
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invisible(Gh <- genMat2(dep, N)))
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return(Gh)
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}
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applyRandTypeE <- function(dep,N){
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type <- unique(dep[,"TYPE"])
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minR <- min(dep[,"rowIndex"])
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maxR <- max(dep[,"rowIndex"])
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switch(-type,
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stop("Not implemented yet"),
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stop("Not implemented yet"),
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invisible(Ef <- genMat3(dep, N)))
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return(Ef)
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type <- unique(dep[,"TYPE"])
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minR <- min(dep[,"rowIndex"])
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maxR <- max(dep[,"rowIndex"])
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switch(-type,
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stop("Not implemented yet"),
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stop("Not implemented yet"),
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invisible(Ef <- genMat3(dep, N)))
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return(Ef)
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}
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dependences <- depTableMaker(constMatrix, parameters)
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missingMembers <- dependences$missingMembers
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dependences <- dependences$depTable
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dependences <- cbind(dependences,1:nrow(dependences))
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colnames(dependences)[ncol(dependences)] <- "rowIndex"
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# browser()
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@ -167,21 +202,31 @@ musoRand <- function(parameters, iterations=3000, fileType="epc", constrains = N
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Ef[[i]] <- applyRandTypeE(splitedDeps[[i]],nrow(dependences))
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}
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}
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Gh0<- genMat0(dependences)
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Gh0<- genMat0(dependences, missingMembers$indices)
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G <- do.call(rbind,lapply(Gh,function(x){x$G}))
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G<- rbind(Gh0$G,G)
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h <- do.call(c,lapply(Gh,function(x){x$h}))
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h <- c(Gh0$h,h)
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E <- do.call(rbind,lapply(Ef,function(x){x$E}))
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f <- do.call(c,lapply(Ef,function(x){x$f}))
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# browser()
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# browser()
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if(length(missingMembers$indices)!=0){
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Ep <- matrix(data=0,ncol=numberOfVariable,nrow=length(missingMembers$indices))
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Ep[1:length(missingMembers$indices),missingMembers$indices] <- 1
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E <- rbind(E,Ep)
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f <- c(f,missingMembers$values)
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}
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randVal <- suppressWarnings(limSolve::xsample(G=G,H=h,E=E,F=f,burninlength=burnin, iter = iterations))$X
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} else{
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Gh0<-genMat0(dependences)
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Gh0<-genMat0(dependences,NULL)
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randVal <- suppressWarnings(xsample(G=Gh0$G,H=Gh0$h, iter = iterations))$X
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}
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if(length(missingMembers$indices)!=0){
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return(list(INDEX = dependences$INDEX[-missingMembers$indices],
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randVal=randVal[,-missingMembers$indices]))
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}
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results <- list(INDEX =dependences$INDEX, randVal=randVal)
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return(results)
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}
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@ -31,6 +31,7 @@ musoSensi <- function(monteCarloFile = NULL,
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plotTitle = "Sensitivity",
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skipSpinup = TRUE,
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skipZero = TRUE,
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sourceFile=NULL,
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postProcString=NULL,
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modifyOut=TRUE,
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dpi=300){
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@ -87,6 +88,7 @@ musoSensi <- function(monteCarloFile = NULL,
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if(is.null(monteCarloFile)){
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M <- musoMonte(parameters = parameters,
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settings = settings,
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sourceFile=NULL,
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inputDir = inputDir,
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outLoc = outLoc,
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iterations = iterations,
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382
test.R
382
test.R
@ -1,382 +0,0 @@
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parameters <-
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getOption("RMuso_constMatrix")[["epc"]][["6"]]
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NAME
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yearday to start new growth
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yearday to end new growth
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transfer growth period as fraction of growing season
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litterfall as fraction of growing season
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base temperature
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minimum temperature for growth displayed on current day
|
||||
optimal1 temperature for growth displayed on current day
|
||||
optimal2 temperature for growth displayed on current day
|
||||
maxmimum temperature for growth displayed on current day
|
||||
minimum temperature for carbon assimilation displayed on current day
|
||||
optimal1 temperature for carbon assimilation displayed on current day
|
||||
optimal2 temperature for carbon assimilation displayed on current day
|
||||
maxmimum temperature for carbon assimilation displayed on current day
|
||||
annual leaf and fine root turnover fraction
|
||||
annual live wood turnover fraction
|
||||
annual fire mortality fraction
|
||||
whole-plant mortality paramter for vegetation period
|
||||
C:N of leaves
|
||||
C:N of leaf litter
|
||||
C:N of fine roots
|
||||
C:N of fruit
|
||||
C:N of softstem
|
||||
C:N of live wood
|
||||
C:N of dead wood
|
||||
dry matter content of leaves
|
||||
dry matter content of leaf litter
|
||||
dry matter content of fine roots
|
||||
dry matter content of fruit
|
||||
dry matter content of softstem
|
||||
dry matter content of live wood
|
||||
dry matter content of dead wood
|
||||
leaf litter labile proportion
|
||||
leaf litter cellulose proportion
|
||||
fine root labile proportion
|
||||
fine root cellulose proportion
|
||||
fruit labile proportion
|
||||
fruit cellulose proportion
|
||||
softstem labile proportion
|
||||
softstem cellulose proportion
|
||||
dead wood cellulose proportion
|
||||
canopy water interception coefficient
|
||||
canopy light extinction coefficient
|
||||
potential radiation use efficiency
|
||||
radiation parameter1 (Jiang et al.2015)
|
||||
radiation parameter1 (Jiang et al.2015)
|
||||
all-sided to projected leaf area ratio
|
||||
ratio of shaded SLA:sunlit SLA
|
||||
fraction of leaf N in Rubisco
|
||||
fraction of leaf N in PeP
|
||||
maximum stomatal conductance
|
||||
cuticular conductance
|
||||
boundary layer conductance
|
||||
maximum height of plant
|
||||
stem weight corresponding to maximum height
|
||||
plant height function shape parameter (slope)
|
||||
maximum depth of rooting zone
|
||||
root distribution parameter
|
||||
root weight corresponding to max root depth
|
||||
root depth function shape parameter (slope)
|
||||
root weight to rooth length conversion factor
|
||||
growth resp per unit of C grown
|
||||
maintenance respiration in kgC/day per kg of tissue N
|
||||
theoretical maximum prop. of non-structural and structural carbohydrates
|
||||
prop. of non-structural carbohydrates available for maintanance resp
|
||||
symbiotic+asymbiotic fixation of N
|
||||
time delay for temperature in photosynthesis acclimation
|
||||
critical VWCratio (prop. to FC-WP) in germination
|
||||
critical photoslow daylength
|
||||
slope of relative photoslow development rate
|
||||
critical vernalization temperature 1
|
||||
critical vernalization temperature 2
|
||||
critical vernalization temperature 3
|
||||
critical vernalization temperature 4
|
||||
slope of relative vernalization development rate
|
||||
required vernalization days (in vernalization development rate)
|
||||
critical flowering heat stress temperature 1
|
||||
critical flowering heat stress temperature 2
|
||||
theoretical maximum of flowering thermal stress mortality
|
||||
VWC ratio to calc. soil moisture limit 1 (prop. to FC-WP)
|
||||
VWC ratio to calc. soil moisture limit 2 (prop. to SAT-FC)
|
||||
minimum of soil moisture limit2 multiplicator (full anoxic stress value)
|
||||
vapor pressure deficit: start of conductance reduction
|
||||
vapor pressure deficit: complete conductance reduction
|
||||
maximum senescence mortality coefficient of aboveground plant material
|
||||
maximum senescence mortality coefficient of belowground plant material
|
||||
maximum senescence mortality coefficient of non-structured plant material
|
||||
lower limit extreme high temperature effect on senescence mortality
|
||||
upper limit extreme high temperature effect on senescence mortality
|
||||
turnover rate of wilted standing biomass to litter
|
||||
turnover rate of cut-down non-woody biomass to litter
|
||||
turnover rate of cut-down woody biomass to litter
|
||||
drought tolerance parameter (critical value of day since water stress)
|
||||
effect of soilstress factor on photosynthesis
|
||||
crit. amount of snow limiting photosyn.
|
||||
limit1 (under:full constrained) of HEATSUM index
|
||||
limit2 (above:unconstrained) of HEATSUM index
|
||||
limit1 (under:full constrained) of TMIN index
|
||||
limit2 (above:unconstrained) of TMIN index
|
||||
limit1 (above:full constrained) of VPD index
|
||||
limit2 (under:unconstrained) of VPD index
|
||||
limit1 (under:full constrained) of DAYLENGTH index
|
||||
limit2 (above:unconstrained) of DAYLENGTH index
|
||||
moving average (to avoid the effects of extreme events)
|
||||
GSI limit1 (greater that limit -> start of vegper)
|
||||
GSI limit2 (less that limit -> end of vegper)
|
||||
length of phenophase (GDD)-0
|
||||
leaf ALLOCATION -0
|
||||
fine root ALLOCATION-0
|
||||
fruit ALLOCATION -0
|
||||
soft stem ALLOCATION-0
|
||||
live woody stem ALLOCATION -0
|
||||
dead woody stem ALLOCATION -0
|
||||
live coarse root ALLOCATION-0
|
||||
dead coarse root ALLOCATION -0
|
||||
canopy average specific leaf area-0
|
||||
current growth proportion-0
|
||||
maximal lifetime of plant tissue-0
|
||||
length of phenophase (GDD)-1
|
||||
leaf ALLOCATION -1
|
||||
fine root ALLOCATION-1
|
||||
fruit ALLOCATION -1
|
||||
soft stem ALLOCATION-1
|
||||
live woody stem ALLOCATION -1
|
||||
dead woody stem ALLOCATION -1
|
||||
live coarse root ALLOCATION-1
|
||||
dead coarse root ALLOCATION -1
|
||||
canopy average specific leaf area-1
|
||||
current growth proportion-1
|
||||
maximal lifetime of plant tissue-1
|
||||
length of phenophase (GDD)-2
|
||||
leaf ALLOCATION -2
|
||||
fine root ALLOCATION-2
|
||||
fruit ALLOCATION -2
|
||||
soft stem ALLOCATION-2
|
||||
live woody stem ALLOCATION -2
|
||||
dead woody stem ALLOCATION -2
|
||||
live coarse root ALLOCATION-2
|
||||
dead coarse root ALLOCATION -2
|
||||
canopy average specific leaf area-2
|
||||
current growth proportion-2
|
||||
maximal lifetime of plant tissue-2
|
||||
length of phenophase (GDD)-3
|
||||
leaf ALLOCATION -3
|
||||
fine root ALLOCATION-3
|
||||
fruit ALLOCATION -3
|
||||
soft stem ALLOCATION-3
|
||||
live woody stem ALLOCATION -3
|
||||
dead woody stem ALLOCATION -3
|
||||
live coarse root ALLOCATION-3
|
||||
dead coarse root ALLOCATION -3
|
||||
canopy average specific leaf area-3
|
||||
current growth proportion-3
|
||||
maximal lifetime of plant tissue-3
|
||||
length of phenophase (GDD)-4
|
||||
leaf ALLOCATION -4
|
||||
fine root ALLOCATION-4
|
||||
fruit ALLOCATION -4
|
||||
soft stem ALLOCATION-4
|
||||
live woody stem ALLOCATION -4
|
||||
dead woody stem ALLOCATION -4
|
||||
live coarse root ALLOCATION-4
|
||||
dead coarse root ALLOCATION -4
|
||||
canopy average specific leaf area-4
|
||||
current growth proportion-4
|
||||
maximal lifetime of plant tissue-4
|
||||
length of phenophase (GDD)-5
|
||||
leaf ALLOCATION -5
|
||||
fine root ALLOCATION-5
|
||||
fruit ALLOCATION -5
|
||||
soft stem ALLOCATION-5
|
||||
live woody stem ALLOCATION -5
|
||||
dead woody stem ALLOCATION -5
|
||||
live coarse root ALLOCATION-5
|
||||
dead coarse root ALLOCATION -5
|
||||
canopy average specific leaf area-5
|
||||
current growth proportion-5
|
||||
maximal lifetime of plant tissue-5
|
||||
length of phenophase (GDD)-6
|
||||
leaf ALLOCATION -6
|
||||
fine root ALLOCATION-6
|
||||
fruit ALLOCATION -6
|
||||
soft stem ALLOCATION-6
|
||||
live woody stem ALLOCATION -6
|
||||
dead woody stem ALLOCATION -6
|
||||
live coarse root ALLOCATION-6
|
||||
dead coarse root ALLOCATION -6
|
||||
canopy average specific leaf area-6
|
||||
current growth proportion-6
|
||||
maximal lifetime of plant tissue-6
|
||||
INDEX UNIT DEPENDENCE MIN MAX GROUP TYPE
|
||||
9.00 yday NA 0.00000 364.0000 0 0
|
||||
10.00 yday NA 0.00000 364.0000 0 0
|
||||
11.00 prop NA 0.00000 1.0000 0 0
|
||||
12.00 prop NA 0.00000 1.0000 0 0
|
||||
13.00 Celsius NA 0.00000 12.0000 0 0
|
||||
14.00 Celsius 0 0.00000 10.0000 1 1
|
||||
15.00 Celsius 1 10.00000 20.0000 1 1
|
||||
16.00 Celsius 2 20.00000 40.0000 1 1
|
||||
17.00 Celsius 3 30.00000 50.0000 1 1
|
||||
18.00 Celsius 0 0.00000 10.0000 2 1
|
||||
19.00 Celsius 1 10.00000 20.0000 2 1
|
||||
20.00 Celsius 2 20.00000 40.0000 2 1
|
||||
21.00 Celsius 3 30.00000 50.0000 2 1
|
||||
22.00 1/yr NA 0.10000 0.4000 0 0
|
||||
23.00 1/yr NA 0.50000 1.0000 0 0
|
||||
24.00 1/yr NA 0.00000 1.0000 0 0
|
||||
25.00 1/vegper NA 0.00000 0.5000 0 0
|
||||
26.00 kgC/kgN 0 10.00000 100.0000 3 1
|
||||
27.00 kgC/kgN 1 10.00000 60.0000 3 1
|
||||
28.00 kgC/kgN 1 10.00000 60.0000 3 1
|
||||
29.00 kgC/kgN 1 10.00000 60.0000 3 1
|
||||
30.00 kgC/kgN 1 10.00000 60.0000 3 1
|
||||
31.00 kgC/kgN 0 50.00000 100.0000 4 1
|
||||
32.00 kgC/kgN 1 300.00000 800.0000 4 1
|
||||
33.00 kgC/kgDM NA 0.20000 0.6000 0 0
|
||||
34.00 kgC/kgDM NA 0.20000 0.6000 0 0
|
||||
35.00 kgC/kgDM NA 0.20000 0.6000 0 0
|
||||
36.00 kgC/kgDM NA 0.20000 0.6000 0 0
|
||||
37.00 kgC/kgDM NA 0.20000 0.6000 0 0
|
||||
38.00 kgC/kgDM NA 0.20000 0.6000 0 0
|
||||
39.00 kgC/kgDM NA 0.20000 0.6000 0 0
|
||||
40.00 prop 1 0.10000 0.6000 5 2
|
||||
41.00 prop 1 0.10000 0.6000 5 2
|
||||
42.00 prop 1 0.10000 0.6000 6 2
|
||||
43.00 prop 1 0.10000 0.6000 6 2
|
||||
44.00 prop 1 0.10000 0.6000 7 2
|
||||
45.00 prop 1 0.10000 0.6000 7 2
|
||||
46.00 prop 1 0.10000 0.6000 8 2
|
||||
47.00 prop 1 0.10000 0.6000 8 2
|
||||
48.00 prop NA 0.50000 0.9000 0 0
|
||||
49.00 1/LAI/d NA 0.01000 0.1000 0 0
|
||||
50.00 dimless NA 0.20000 0.8000 0 0
|
||||
51.00 g/MJ NA 2.00000 2.0000 0 0
|
||||
52.00 dimless NA 0.78100 0.7810 0 0
|
||||
53.00 dimless NA -13.59600 -13.5960 0 0
|
||||
54.00 dimless NA 2.00000 2.0000 0 0
|
||||
55.00 dimless NA 2.00000 2.0000 0 0
|
||||
56.00 dimless NA 0.01000 0.2000 0 0
|
||||
57.00 dimless NA 0.04240 0.0424 0 0
|
||||
58.00 m/s NA 0.00100 0.1000 0 0
|
||||
59.00 m/s NA 0.00001 0.0001 0 0
|
||||
60.00 m/s NA 0.01000 0.0900 0 0
|
||||
61.00 m NA 0.10000 10.0000 0 0
|
||||
62.00 kgC NA 0.10000 100.0000 0 0
|
||||
63.00 dimless NA 0.50000 0.5000 0 0
|
||||
64.00 m NA 0.10000 10.0000 0 0
|
||||
65.00 prop NA 3.67000 3.6700 0 0
|
||||
66.00 kgC/m2 NA 0.40000 0.4000 0 0
|
||||
67.00 prop NA 0.50000 0.5000 0 0
|
||||
68.00 m/kg NA 1000.00000 1000.0000 0 0
|
||||
69.00 prop NA 0.10000 0.5000 0 0
|
||||
70.00 kgC/kgN/d NA 0.10000 0.5000 0 0
|
||||
71.00 dimless NA 0.00000 1.0000 0 0
|
||||
72.00 dimless NA 0.00000 1.0000 0 0
|
||||
73.00 kgN/m2/yr NA 0.00000 0.0010 0 0
|
||||
74.00 day NA 0.00000 50.0000 0 0
|
||||
79.00 prop NA 0.00000 1.0000 0 0
|
||||
81.00 hour NA 14.00000 18.0000 0 0
|
||||
82.00 dimless NA 0.00500 0.0050 0 0
|
||||
84.00 Celsius 0 -5.00000 5.0000 9 1
|
||||
85.00 Celsius 1 0.00000 10.0000 9 1
|
||||
86.00 Celsius 2 5.00000 15.0000 9 1
|
||||
87.00 Celsius 3 10.00000 20.0000 9 1
|
||||
88.00 dimless NA 0.04000 0.0400 0 0
|
||||
89.00 dimless NA 30.00000 70.0000 0 0
|
||||
91.00 Celsius 0 30.00000 40.0000 10 1
|
||||
92.00 Celsius 1 30.00000 50.0000 10 1
|
||||
93.00 prop NA 0.00000 0.4000 0 0
|
||||
96.00 prop NA 0.50000 1.0000 0 0
|
||||
97.00 prop NA 0.50000 1.0000 0 0
|
||||
98.00 prop NA 0.00000 1.0000 0 0
|
||||
99.00 Pa NA 500.00000 1500.0000 0 0
|
||||
100.00 Pa NA 1500.00000 3500.0000 0 0
|
||||
101.00 prop 0 0.00000 0.1000 0 0
|
||||
102.00 prop 1 0.00000 0.1000 0 0
|
||||
103.00 prop NA 0.00000 0.1000 0 0
|
||||
104.00 Celsius NA 30.00000 40.0000 0 0
|
||||
105.00 Celsius NA 30.00000 50.0000 0 0
|
||||
106.00 prop NA 0.00000 0.1000 0 0
|
||||
107.00 prop NA 0.00000 0.1000 0 0
|
||||
108.00 prop NA 0.00000 0.1000 0 0
|
||||
109.00 n_day NA 0.00000 100.0000 0 0
|
||||
110.00 dimless NA 0.00000 1.0000 0 0
|
||||
113.00 kg/m2 NA 0.00000 20.0000 0 0
|
||||
114.00 Celsius 0 0.00000 50.0000 11 1
|
||||
115.00 Celsius 1 0.00000 100.0000 11 1
|
||||
116.00 Celsius 0 -5.00000 5.0000 12 1
|
||||
117.00 Celsius 1 0.00000 10.0000 12 1
|
||||
118.00 Pa 0 2000.00000 600.0000 13 1
|
||||
119.00 Pa 1 500.00000 1500.0000 13 1
|
||||
120.00 s 0 0.00000 0.0000 14 1
|
||||
121.00 s 1 0.00000 0.0000 14 1
|
||||
122.00 n_day NA 2.00000 20.0000 0 0
|
||||
123.00 dimless NA 0.00000 0.2000 0 0
|
||||
124.00 dimless NA 0.00000 0.1000 0 0
|
||||
128.60 Celsius NA 0.00000 10000.0000 0 0
|
||||
129.60 prop 1 0.00000 1.0000 15 -3
|
||||
130.60 prop 1 0.00000 1.0000 15 -3
|
||||
131.60 prop 1 0.00000 1.0000 15 -3
|
||||
132.60 prop 1 0.00000 1.0000 15 -3
|
||||
133.60 prop 1 0.00000 1.0000 15 -3
|
||||
134.60 prop 1 0.00000 1.0000 15 -3
|
||||
135.60 prop 1 0.00000 1.0000 15 -3
|
||||
136.60 prop 1 0.00000 1.0000 15 -3
|
||||
137.60 m2/kg NA 0.00000 2.0000 0 0
|
||||
138.60 prop NA 0.00000 0.0000 0 0
|
||||
139.60 Celsius NA 1.00000 20000.0000 0 0
|
||||
128.61 Celsius NA 0.00000 10000.0000 0 0
|
||||
129.61 prop 1 0.00000 1.0000 16 -3
|
||||
130.61 prop 1 0.00000 1.0000 16 -3
|
||||
131.61 prop 1 0.00000 1.0000 16 -3
|
||||
132.61 prop 1 0.00000 1.0000 16 -3
|
||||
133.61 prop 1 0.00000 1.0000 16 -3
|
||||
134.61 prop 1 0.00000 1.0000 16 -3
|
||||
135.61 prop 1 0.00000 1.0000 16 -3
|
||||
136.61 prop 1 0.00000 1.0000 16 -3
|
||||
137.61 m2/kg NA 0.00000 2.0000 0 0
|
||||
138.61 prop NA 0.00000 0.0000 0 0
|
||||
139.61 Celsius NA 1.00000 20000.0000 0 0
|
||||
128.62 Celsius NA 0.00000 10000.0000 0 0
|
||||
129.62 prop 1 0.00000 1.0000 17 -3
|
||||
130.62 prop 1 0.00000 1.0000 17 -3
|
||||
131.62 prop 1 0.00000 1.0000 17 -3
|
||||
132.62 prop 1 0.00000 1.0000 17 -3
|
||||
133.62 prop 1 0.00000 1.0000 17 -3
|
||||
134.62 prop 1 0.00000 1.0000 17 -3
|
||||
135.62 prop 1 0.00000 1.0000 17 -3
|
||||
136.62 prop 1 0.00000 1.0000 17 -3
|
||||
137.62 m2/kg NA 0.00000 2.0000 0 0
|
||||
138.62 prop NA 0.00000 0.0000 0 0
|
||||
139.62 Celsius NA 1.00000 20000.0000 0 0
|
||||
128.63 Celsius NA 0.00000 10000.0000 0 0
|
||||
129.63 prop 1 0.00000 1.0000 18 -3
|
||||
130.63 prop 1 0.00000 1.0000 18 -3
|
||||
131.63 prop 1 0.00000 1.0000 18 -3
|
||||
132.63 prop 1 0.00000 1.0000 18 -3
|
||||
133.63 prop 1 0.00000 1.0000 18 -3
|
||||
134.63 prop 1 0.00000 1.0000 18 -3
|
||||
135.63 prop 1 0.00000 1.0000 18 -3
|
||||
136.63 prop 1 0.00000 1.0000 18 -3
|
||||
137.63 m2/kg NA 0.00000 2.0000 0 0
|
||||
138.63 prop NA 0.00000 0.0000 0 0
|
||||
139.63 Celsius NA 1.00000 20000.0000 0 0
|
||||
128.64 Celsius NA 0.00000 10000.0000 0 0
|
||||
129.64 prop 1 0.00000 1.0000 19 -3
|
||||
130.64 prop 1 0.00000 1.0000 19 -3
|
||||
131.64 prop 1 0.00000 1.0000 19 -3
|
||||
132.64 prop 1 0.00000 1.0000 19 -3
|
||||
133.64 prop 1 0.00000 1.0000 19 -3
|
||||
134.64 prop 1 0.00000 1.0000 19 -3
|
||||
135.64 prop 1 0.00000 1.0000 19 -3
|
||||
136.64 prop 1 0.00000 1.0000 19 -3
|
||||
137.64 m2/kg NA 0.00000 2.0000 0 0
|
||||
138.64 prop NA 0.00000 0.0000 0 0
|
||||
139.64 Celsius NA 1.00000 20000.0000 0 0
|
||||
128.65 Celsius NA 0.00000 10000.0000 0 0
|
||||
129.65 prop 1 0.00000 1.0000 20 -3
|
||||
130.65 prop 1 0.00000 1.0000 20 -3
|
||||
131.65 prop 1 0.00000 1.0000 20 -3
|
||||
132.65 prop 1 0.00000 1.0000 20 -3
|
||||
133.65 prop 1 0.00000 1.0000 20 -3
|
||||
134.65 prop 1 0.00000 1.0000 20 -3
|
||||
135.65 prop 1 0.00000 1.0000 20 -3
|
||||
136.65 prop 1 0.00000 1.0000 20 -3
|
||||
137.65 m2/kg NA 0.00000 2.0000 0 0
|
||||
138.65 prop NA 0.00000 0.0000 0 0
|
||||
139.65 Celsius NA 1.00000 20000.0000 0 0
|
||||
128.66 Celsius NA 0.00000 10000.0000 0 0
|
||||
129.66 prop 1 0.00000 1.0000 21 -3
|
||||
130.66 prop 1 0.00000 1.0000 21 -3
|
||||
131.66 prop 1 0.00000 1.0000 21 -3
|
||||
132.66 prop 1 0.00000 1.0000 21 -3
|
||||
133.66 prop 1 0.00000 1.0000 21 -3
|
||||
134.66 prop 1 0.00000 1.0000 21 -3
|
||||
135.66 prop 1 0.00000 1.0000 21 -3
|
||||
136.66 prop 1 0.00000 1.0000 21 -3
|
||||
137.66 m2/kg NA 0.00000 2.0000 0 0
|
||||
138.66 prop NA 0.00000 0.0000 0 0
|
||||
139.66 Celsius NA 1.00000 20000.0000 0 0
|
||||
Loading…
Reference in New Issue
Block a user