R/ClassBarPlot.R

In DataVisualizations: Visualizations of High-Dimensional Data

ClassBarPlot = function(Values, Cls, Deviation, Names, ClassColors,
                        ylab = "Values", xlab = "Instances", PlotIt = TRUE){
  # Classbarplot(Values, Class)
  # Classbarplot(Values, Class, Deviation, Names)
  # 
  # DESCRIPTION
  # Represent values for each class and instance as bar plot with optional
  # error deviation, e.g., mean values of features depending on class with
  # standard deviation.
  # 
  # INPUT
  # Values[1:n]        Numeric vector with values (y-axis) in matching order to 
  #                    Class, Deviation and Names
  # Cls[1:n]           Numeric vector of classes in matching order to Values
  #                    and Deviation and Names
  # 
  # OPTIONAL
  # Deviation[1:n]     Numeric vector with deviation in matching order to Values
  #                    and Class and Names
  # Names[1:n]         Character or numeric vector of instances (x-axis) in
  #                    matching order to Values and Class and Deviation
  # ylab               Character stating y label.
  # xlab               Character stating x label.
  # PlotIt             Logical value indicating visual output
  #                    TRUE => create visual output
  #                    FALSE => do not create visual output
  #                    (Default: Boolean=TRUE)
  # OUTPUT
  # ggplot2 object for saving or further manipulation.
  # 
  # Author: QMS October 2024
  # 
  

  if(length(Values) != length(Cls)){
    stop("Classbarplot.R: Length of vectors Values and Cls must equal.")
  }
  Class=sort(unique(Cls))
  
  # Combine Values and Cls into a data frame
  tmpDF <- data.frame(Values, Cls)
  
  # Group by Cls and calculate total count
  tmpVar1 <- aggregate(. ~ Cls, data = tmpDF, FUN = function(x) length(x))
  
  # Extract total counts
  tmpVar2 <- tmpVar1$Values
  if(!all(tmpVar2 == tmpVar2[1])){
    stop("Classbarplot.R: Provide values for each class and each instance on the x-axis.")
  }
  
  UCls      = unique(Cls)
  NumCls    = length(UCls)
  ColNaming = c("Values", "NamesX", "Names", "Class", "ClassColors")
  
  if(!missing(Names)){
    if(length(Names) != table(Cls)[1]){
      stop("Classbarplot.R: Length of vectors Values and Names must equal.")
    }
    NamesX = rep(1:tmpVar2[1], NumCls)
    tmpM = max(nchar(NamesX))
    
    NamesX = as.numeric(sapply(NamesX, function(x, tmpM){
      if(nchar(x) < tmpM){
        x = paste0(rep("0", tmpM - nchar(x)), x)
      }
      x = paste0("1", x)
    }, tmpM))
    
  }else{
    Names  = rep(1:tmpVar2[1], NumCls)
    NamesX = Names
  }
  
  if(!missing(ClassColors)){
    if((length(ClassColors) != length(Cls)) & (length(ClassColors) != NumCls)){
      stop("asdf: Parameter ClassColors must either define the colors for each
           class or match the colors for each class in the Cls vector.")
    }
    if(length(ClassColors) == NumCls){
      ClassColors = ClassColors[Cls]
    }
  }else{
    Colors      = DataVisualizations::DefaultColorSequence[1:NumCls]
    ClassColors = Colors[Cls]
  }
  
  MatCBP = cbind(Values, NamesX, Names, Cls, ClassColors)
  
  if(!missing(Deviation)){
    MatCBP    = cbind(MatCBP, Deviation)
    ColNaming = c(ColNaming, "Deviation")
  }
  
  # DataFrame:
  # as.data.frame(cbind(Values, Class))
  dfCBP            = as.data.frame(MatCBP)

  colnames(dfCBP)  = ColNaming
  row.names(dfCBP) = NULL
  XTicks           = Names[1:tmpVar2[1]]
  XAxis            = NamesX[1:tmpVar2[1]] # 1:tmpVar2[1]
  
  dfCBP$Values = as.numeric(dfCBP$Values)
  if(!is.null(dfCBP$Deviation)){
    dfCBP$Deviation = as.numeric(dfCBP$Values)
  }
  
  #print(colnames(dfCBP))
  
  p = ggplot(dfCBP, aes(x = NamesX, y = Values, group = Class, fill = ClassColors)) +
    geom_bar(stat = 'identity', position = 'dodge', alpha = 0.5)
  
  if(!missing(Deviation)){
    p = p + geom_errorbar(aes(ymin = Values - Deviation, ymax = Values + Deviation),
                          position=position_dodge(0.9), color = "black", width=.2)
  }
  
  p = p + theme_bw() +
    theme(legend.position = "none", axis.text.y = element_blank(), axis.ticks.y = element_blank()) + 
    theme(axis.text.x = element_text(face = "bold", color = "black", 
                                     size = 8, angle = 0),
          axis.text.y = element_text(face = "bold", color = "black", 
                                     size = 14, angle = 0)) +
    scale_x_discrete(breaks = XAxis, labels = XTicks) +
    ylab(ylab) + xlab(xlab)
  
  if(isTRUE(PlotIt)){
    print(p)
  }
  
  return(list("ggplot2Object" = p))
}