big changes + version upgrade

RBBGCMuso/DESCRIPTION

@@ -1,6 +1,6 @@
 Package: RBBGCMuso
 Title: An R package for BiomeBGC-MuSo ecosystem modelling
-Version: 0.4.0.0-2
+Version: 0.5.0.0-0
 Authors@R: person("Roland", "Hollo's", , "hollorol@gmail.com", role = c("aut", "cre"))
 Description: What the package does (one paragraph).
 Depends: R (>= 2.10)

RBBGCMuso/R/musoMonte.R

@@ -22,6 +22,7 @@ musoMonte <- function(settings=NULL,
                      outputType = "moreCsv",
                      fun=mean,
                      varIndex = 1,
+                     silent = TRUE,
                      ...){
     
     outLocPlain <- basename(outLoc)
@@ -75,8 +76,12 @@ musoMonte <- function(settings=NULL,
     ##  run.
     preservedEpc <- matrix(nrow = (iterations +1 ), ncol = npar)
     preservedEpc[1,] <- origEpc
-    colnames(preservedEpc) <- Otable[[1]][,1]
+    Otable[[1]][,1]  <- (as.character(Otable[[1]][,1]))
+    for(i in parameters[,2]){
+        Otable[[1]][Otable[[1]][,2]==i,1] <- as.character(parameters[parameters[,2]==i,1])
+    }
     
+    colnames(preservedEpc) <- Otable[[1]][,1]
     preservedEpc <- cbind(preservedEpc,rep(NA,(iterations+1)))
     colnames(preservedEpc)[(npar+1)] <- "y"
     ## Save the backupEpc, while change the settings
@@ -86,9 +91,10 @@ musoMonte <- function(settings=NULL,
     
     ## Creating function for generating separate
     ## csv files for each run
+    progBar <- txtProgressBar(1,iterations,style=3)
     moreCsv <- function(){
         a <- numeric(iterations+1)
-        tempData <- calibMuso(settings, debugging = "stamplog", parameters = origEpc,keepEpc = TRUE)
+        tempData <- calibMuso(settings, debugging = "stamplog", parameters = origEpc,keepEpc = TRUE,silent = silent)
         a[1] <- tryCatch(fun(tempData[,varIndex]),error=function(e){return(NA)})
         preservedEpc[1,(npar+1)] <- a[1]
         write.table(t(preservedEpc[1,]),row.names = FALSE,"preservedEpc.csv",sep=",")
@@ -99,12 +105,15 @@ musoMonte <- function(settings=NULL,
             exportName <- paste0(preTag,(i+1),".csv")
             tempData <- calibMuso(settings,debugging = "stamplog",
                                  parameters = parVar,
-                                 keepEpc = TRUE)
+                                 keepEpc = TRUE,
+                                 silent=silent)
             write.csv(x=tempData,file=exportName)
             
             preservedEpc[(i+1),(npar+1)] <- a[i+1]<- tryCatch(fun(tempData[,varIndex]),error=function(e){return(NA)})
             write.table(t(preservedEpc[(i+1),]),file="preservedEpc.csv",row.names=FALSE,col.names=FALSE, append=TRUE,sep=",")
+            setTxtProgressBar(progBar,i)
         }
+        cat("\n")
         return(preservedEpc)
     }
     

RBBGCMuso/R/musoSensi.R

@@ -25,46 +25,19 @@ musoSensi <- function(monteCarloFile = NULL,
                      inputDir = "./",
                      outLoc = "./calib",
                      iterations = 30,
-                     preTag = "mount-",
+                     preTag = "mont-",
                      outputType = "moreCsv",
                      fun = mean,
                      varIndex = 1,
                      outputFile = "sensitivity.csv",
                      plotName = "sensitivity.jpg"){
 
-    if(is.null(monteCarloFile)){
+    doSensi <- function(M){
-        M <- musoMonte(parameters = parameters,
-                      settings = settings,
-                      inputDir = inputDir,
-                      outLoc = outLoc,
-                      iterations = iterations,
-                      preTag = preTag,
-                      outputType = outputType,
-                      fun = fun,
-                      varIndex = varIndex
-                      )
         npar <- ncol(M)-1
-        M <- M[which(!is.na(M$y)),]
+        M <- M[which(!is.na(M[,"y"])),]
-        y <- M[,(npar+1)]
-        M <- apply(M[,1:npar],2,function(x){x-mean(x)})
-        varNames<- colnames(M)[1:npar]
-        w <- lm(y~M)$coefficients[-1]
-        Sv <- apply(M,2,var)
-        overalVar <- sum(Sv^2*w^2)
-        S=numeric(npar)
-        for(i in 1:npar){
-            S[i] <- ((w[i]^2*Sv[i]^2)/overalVar)*100
-        }
-        write.csv(file = outputFile, x = S)
-        names(S)<-varNames
-        barplot(S,las=2)
-        return(S)
-    } else {
-        M <- read.csv(monteCarloFile)
-        
-        npar <- ncol(M)-1
-        M <- M[which(!is.na(M$y)),]
         y <- M[,(npar+1)]
+        M <- M[,colnames(M) %in% parameters[,1]]
+        npar <- ncol(M)
         M <- apply(M[,1:npar],2,function(x){x-mean(x)})
         varNames<- colnames(M)[1:npar]
         w <- lm(y~M)$coefficients[-1]
@@ -79,4 +52,24 @@ musoSensi <- function(monteCarloFile = NULL,
         barplot(S,las=2)
         return(S)
     }
+
+    
+
+    if(is.null(monteCarloFile)){
+        M <- musoMonte(parameters = parameters,
+                      settings = settings,
+                      inputDir = inputDir,
+                      outLoc = outLoc,
+                      iterations = iterations,
+                      preTag = preTag,
+                      outputType = outputType,
+                      fun = fun,
+                      varIndex = varIndex
+                      )
+        return(doSensi(M))
+        
+    } else {
+        M <- read.csv(monteCarloFile)
+        return(doSensi(M))        
+    }
 }

RBBGCMuso/man/musoMonte.Rd

@@ -6,7 +6,7 @@
 \usage{
 musoMonte(settings = NULL, parameters, inputDir = "./",
   outLoc = "./calib", iterations = 10, preTag = "mont-",
-  outputType = "moreCsv", fun = mean, varIndex = 1, ...)
+  outputType = "moreCsv", fun = mean, varIndex = 1, silent = TRUE, ...)
 }
 \arguments{
 \item{settings}{A list of montecarlos environmental variables. It is generated by the setupMuso() function. In default the settings parameter is generated automatically.}

RBBGCMuso/man/musoSensi.Rd

@@ -6,7 +6,7 @@
 \usage{
 musoSensi(monteCarloFile = NULL, parameters, settings = NULL,
   inputDir = "./", outLoc = "./calib", iterations = 30,
-  preTag = "mount-", outputType = "moreCsv", fun = mean, varIndex = 1,
+  preTag = "mont-", outputType = "moreCsv", fun = mean, varIndex = 1,
   outputFile = "sensitivity.csv", plotName = "sensitivity.jpg")
 }
 \arguments{