R/ABCbarplot.R

In Mthrun/DataVisualizations: Visualizations of High-Dimensional Data

ABCbarplot=ABC_screeplot=function(Data,Colors=DataVisualizations::DefaultColorSequence[1:3],main,xlab,ylab="Value"){
# V= ABCbarPlot(Data);
# V has the elements Aind,Bind,Cind,ABlimit,BClimit
# barplot of sortdescending(Data) with the sets in different colours
# plot also : two diagonals and  ABC curve for Uniform distibution U[0,max(data) and   Horizintal and Vertical limits for setsABC 
# 
# INPUT
# Data(1:n)         data points, for ABCplots the  CleanedData = ABCcleanData(Data) are used
                                                                       
# OPTIONAL
# Colors             colors for A,B,C ; default:  DefaultColorSequence
  if (!requireNamespace('ABCanalysis',quietly = TRUE)){
    
    message('Subordinate package (ABCanalysis) is missing. No computations are performed.
Please install the package which is defined in "Suggests".')
    
    return('Subordinate package (ABCanalysis) is missing. No computations are performed.
Please install the package which is defined in "Suggests".')
  }
  
  
  if(missing(xlab)) xlab=paste0("Fraction of ",deparse1(substitute(Data))," in %")
  
if(missing(main)) main="Barplot colored by ABCanalysis Indicating Most-Important Values"
Data=Data[is.finite(Data)]
SortedData = sort(Data,decreasing = T,na.last = T)
V = ABCanalysis::ABCanalysis(SortedData)
Aind =V$Aind
Bind =V$Bind
Cind =V$Cind

X = c(1:length(SortedData))
ColorsVec=c(rep(Colors[1],length(Aind)),rep(Colors[2],length(Bind)),rep(Colors[3],length(Cind)))
ABC_classes=c(rep('A',length(Aind)),rep('B',length(Bind)),rep('C',length(Cind)))
DF=data.frame(X=X/length(SortedData)*100,Y=SortedData,ABC_classes=ABC_classes,ColorsVec=ColorsVec)

ggobject=ggplot(data=DF, aes(x=.data$X, y=.data$Y, fill=.data$ABC_classes)) + geom_bar(stat="identity")+ 
  scale_fill_manual(values = Colors, name = "ABC Analysis")+
  ggtitle(main)+xlab(xlab)+ylab(ylab)
print(ggobject)
return(list(ABCanalysis=V,ggobject=ggobject,DF=DF))
}