implementing ggplot

RBBGCMuso/DESCRIPTION

@@ -16,7 +16,8 @@ Imports:
 	graphics,
 	Rcpp,
 	magrittr,
-	dplyr
+	dplyr,
+	ggplot2
 LinkingTo: Rcpp
 Maintainer: Roland Hollo's <hollorol@gmail.com>
 RoxygenNote: 6.0.1

RBBGCMuso/NAMESPACE

@@ -19,6 +19,7 @@ export(spinupMuso)
 export(supportedMuso)
 export(updateMusoMapping)
 import(dplyr)
+import(ggplot2)
 import(grDevices)
 import(graphics)
 import(magrittr)

RBBGCMuso/R/musoSensi.R

@@ -17,11 +17,13 @@
 #' @import dplyr
 #' @import graphics
 #' @import grDevices
+#' @import ggplot2
 #' @export
 
 musoSensi <- function(monteCarloFile = NULL,
-                     parameters,
+                     parameters=NULL,
                      settings = NULL,
+                     parametersFromFile=FALSE,
                      inputDir = "./",
                      outLoc = "./calib",
                      iterations = 30,
@@ -30,7 +32,19 @@ musoSensi <- function(monteCarloFile = NULL,
                      fun = mean,
                      varIndex = 1,
                      outputFile = "sensitivity.csv",
-                     plotName = "sensitivity.jpg"){
+                     plotName = "sensitivity.png",
+                     plotTitle = "Sensitivity",
+                     dpi=300){
+
+    if(is.null(parameters)){
+        parameters <- read.csv("parameters.csv")
+    } else {
+        if(parametersFromFile){
+            parameters <- read.csv(parameters,stringsAsFactors=FALSE)
+        } else {
+            parameters <- parameters
+        }
+    }
 
     doSensi <- function(M){
         npar <- ncol(M)-1
@@ -47,9 +61,19 @@ musoSensi <- function(monteCarloFile = NULL,
         for(i in 1:npar){
             S[i] <- ((w[i]^2*Sv[i]^2)/overalVar)*100
         }
+        S <- round(S)
         names(S)<-varNames
         write.csv(file = outputFile, x = S)
-        barplot(S,las=2)
+
+        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)
     }
 

RBBGCMuso/man/musoSensi.Rd

@@ -7,7 +7,7 @@
 musoSensi(monteCarloFile = NULL, parameters, settings = NULL,
   inputDir = "./", outLoc = "./calib", iterations = 30,
   preTag = "mont-", outputType = "moreCsv", fun = mean, varIndex = 1,
-  outputFile = "sensitivity.csv", plotName = "sensitivity.jpg")
+  outputFile = "sensitivity.csv", plotName = "sensitivity")
 }
 \arguments{
 \item{monteCarloFile}{If you run musoMonte function previously, you did not have to rerun the monteCarlo, just provide the preservedEpc.csv file with its path. If you do not set this parameter, musoSensi will fun the musoMonte function to get all of the information.}