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rtreeboxplotparty

partykit - Modify the terminal node of a boxplot to display y axis in the log scale


I am trying to plot a regression tree generated with rpart using partykit. The code that generates the tree is this one:

library("rpart")
fit <- rpart(Price ~ Mileage + Type + Country, cu.summary)
library("partykit")
tree.2 <- as.party(fit)

plot(tree.2, type = "simple", terminal_panel = node_boxplot(tree.2,
                                                            col = "black", fill = "lightgray", width = 0.5, yscale = NULL,
                                                            ylines = 3, cex = 0.5, id = TRUE))

I am trying to modify the boxplots on the terminal nodes so that the y axis is on the log scale.

I am aware that when trying to make a boxplot all we have to do is to specify boxplot(data, log="y"). Which is why I tried to modify the function node_boxplot only in the single line where the function boxplot is used. However I keep getting the same graph. Is there something I am missing? Any feedback would be greatly appreciated.

node_boxplot2<-function (obj, col = "black", fill = "lightgray", bg = "white", 
          width = 0.5, yscale = NULL, ylines = 3, cex = 0.5, id = TRUE, 
          mainlab = NULL, gp = gpar()) 
{
  y <- log(obj$fitted[["(response)"]])
  stopifnot(is.numeric(y))
  if (is.null(yscale)) 
    yscale <- range(y) +c(0,0.1)* diff(range(y))
  rval <- function(node) {
    nid <- id_node(node)
    dat <- data_party(obj, nid)
    yn <- dat[["(response)"]]
    wn <- dat[["(weights)"]]
    if (is.null(wn)) 
      wn <- rep(1, length(yn))
    x <- boxplot(rep.int(yn, wn),plot = FALSE)
    top_vp <- viewport(layout = grid.layout(nrow = 2, ncol = 3, 
                                            widths = unit(c(ylines, 1, 1), c("lines", "null", 
                                                                             "lines")), heights = unit(c(1, 1), c("lines", 
                                                                                                                  "null"))), width = unit(1, "npc"), height = unit(1, 
                                                                                                                                                                   "npc") - unit(2, "lines"), name = paste("node_boxplot", 
                                                                                                                                                                                                           nid, sep = ""), gp = gp)
    pushViewport(top_vp)
    grid.rect(gp = gpar(fill = bg, col = 0))
    top <- viewport(layout.pos.col = 2, layout.pos.row = 1)
    pushViewport(top)
    if (is.null(mainlab)) {
      mainlab <- if (id) {
        function(id, nobs) sprintf("Node %s (n = %s)", 
                                   id, nobs)
      }
      else {
        function(id, nobs) sprintf("n = %s", nobs)
      }
    }
    if (is.function(mainlab)) {
      mainlab <- mainlab(names(obj)[nid], sum(wn))
    }
    grid.text(mainlab)
    popViewport()
    plot <- viewport(layout.pos.col = 2, layout.pos.row = 2, 
                     xscale = c(0, 1), yscale = yscale, name = paste0("node_boxplot", 
                                                                      nid, "plot"), clip = FALSE)
    pushViewport(plot)
    grid.yaxis()
    grid.rect(gp = gpar(fill = "transparent"))
    grid.clip()
    xl <- 0.5 - width/4
    xr <- 0.5 + width/4
    grid.lines(unit(c(xl, xr), "npc"), unit(x$stats[1], "native"), 
               gp = gpar(col = col))
    grid.lines(unit(0.5, "npc"), unit(x$stats[1:2], "native"), 
               gp = gpar(col = col, lty = 2))
    grid.rect(unit(0.5, "npc"), unit(x$stats[2], "native"), 
              width = unit(width, "npc"), height = unit(diff(x$stats[c(2, 
                                                                       4)]), "native"), just = c("center", "bottom"), 
              gp = gpar(col = col, fill = fill))
    grid.lines(unit(c(0.5 - width/2, 0.5 + width/2), "npc"), 
               unit(x$stats[3], "native"), gp = gpar(col = col, 
                                                     lwd = 2))
    grid.lines(unit(0.5, "npc"), unit(x$stats[4:5], "native"), 
               gp = gpar(col = col, lty = 2))
    grid.lines(unit(c(xl, xr), "npc"), unit(x$stats[5], "native"), 
               gp = gpar(col = col))
    n <- length(x$out)
    if (n > 0) {
      index <- 1:n
      if (length(index) > 0) 
        grid.points(unit(rep.int(0.5, length(index)), 
                         "npc"), unit(x$out[index], "native"), size = unit(cex, 
                                                                           "char"), gp = gpar(col = col))
    }
    upViewport(2)
  }
  return(rval)
}

Solution

  • (1) If plotting is more appropriate on a log-scale, then I would usually expect that growing the tree is also better done on a log-scale. Here, you could simply use rpart(log(Price) ~ ...).

    (2) If you only want to draw a different scale in the node boxplots, a little bit more work is needed because the box plots are drawn "by hand" using the grid.*() functions. In the code below, I transform both the overall response and the response in the node to be plotted by taking logs. And then I just modify the grid.yaxis() as needed. The function node_logboxplot() is simply a copy of node_boxplot() with a few simple modifications (marked by #!!#). With this you can do

    plot(tree.2, terminal_panel = node_logboxplot)
    

    node_logboxplot

    compared to

    plot(tree.2, terminal_panel = node_boxplot)
    

    node_boxplot

    Modified panel function:

    node_logboxplot <- function(obj,
                             col = "black",
                     fill = "lightgray",
                 bg = "white",
                     width = 0.5,
                     yscale = NULL,
                     ylines = 3,
                 cex = 0.5,
                     id = TRUE,
                             mainlab = NULL, 
                 gp = gpar())
    {
        y <- log(obj$fitted[["(response)"]]) #!!# log-transform overall response
        stopifnot(is.numeric(y))
    
        if (is.null(yscale)) 
            yscale <- range(y) + c(-0.1, 0.1) * diff(range(y))
    
        #!!# compute yaxis labels on original scale
        yaxis <- pretty(exp(y))
        yaxis <- yaxis[yaxis > 0]
    
        ### panel function for boxplots in nodes
        rval <- function(node) {
    
            ## extract data
        nid <- id_node(node)
        dat <- data_party(obj, nid)
        yn <- log(dat[["(response)"]]) #!!# log-transform response in node
        wn <- dat[["(weights)"]]
        if(is.null(wn)) wn <- rep(1, length(yn))
    
            ## parameter setup
        x <- boxplot(rep.int(yn, wn), plot = FALSE)
    
            top_vp <- viewport(layout = grid.layout(nrow = 2, ncol = 3,
                               widths = unit(c(ylines, 1, 1), 
                                             c("lines", "null", "lines")),  
                               heights = unit(c(1, 1), c("lines", "null"))),
                               width = unit(1, "npc"), 
                               height = unit(1, "npc") - unit(2, "lines"),
                   name = paste("node_boxplot", nid, sep = ""),
                   gp = gp)
    
            pushViewport(top_vp)
            grid.rect(gp = gpar(fill = bg, col = 0))
    
            ## main title
            top <- viewport(layout.pos.col=2, layout.pos.row=1)
            pushViewport(top)
            if (is.null(mainlab)) { 
          mainlab <- if(id) {
            function(id, nobs) sprintf("Node %s (n = %s)", id, nobs)
          } else {
            function(id, nobs) sprintf("n = %s", nobs)
          }
            }
        if (is.function(mainlab)) {
              mainlab <- mainlab(names(obj)[nid], sum(wn))
        }
            grid.text(mainlab)
            popViewport()
    
            plot <- viewport(layout.pos.col = 2, layout.pos.row = 2,
                             xscale = c(0, 1), yscale = yscale,
                 name = paste0("node_boxplot", nid, "plot"),
                 clip = FALSE)
    
            pushViewport(plot)
    
            grid.yaxis(at = log(yaxis), label = yaxis) #!!# use pre-computed axis labels
            grid.rect(gp = gpar(fill = "transparent"))
        grid.clip()
    
        xl <- 0.5 - width/4
        xr <- 0.5 + width/4
    
            ## box & whiskers
            grid.lines(unit(c(xl, xr), "npc"), 
                       unit(x$stats[1], "native"), gp = gpar(col = col))
            grid.lines(unit(0.5, "npc"), 
                       unit(x$stats[1:2], "native"), gp = gpar(col = col, lty = 2))
            grid.rect(unit(0.5, "npc"), unit(x$stats[2], "native"), 
                      width = unit(width, "npc"), height = unit(diff(x$stats[c(2, 4)]), "native"),
                      just = c("center", "bottom"), 
                      gp = gpar(col = col, fill = fill))
            grid.lines(unit(c(0.5 - width/2, 0.5+width/2), "npc"), 
                       unit(x$stats[3], "native"), gp = gpar(col = col, lwd = 2))
            grid.lines(unit(0.5, "npc"), unit(x$stats[4:5], "native"), 
                       gp = gpar(col = col, lty = 2))
            grid.lines(unit(c(xl, xr), "npc"), unit(x$stats[5], "native"), 
                       gp = gpar(col = col))
    
            ## outlier
            n <- length(x$out)
            if (n > 0) {
                index <- 1:n ## which(x$out > yscale[1] & x$out < yscale[2])
                if (length(index) > 0)
                    grid.points(unit(rep.int(0.5, length(index)), "npc"), 
                                unit(x$out[index], "native"),
                                size = unit(cex, "char"), gp = gpar(col = col))
            }
    
            upViewport(2)
        }
    
        return(rval)
    }
    class(node_logboxplot) <- "grapcon_generator"