Violin plot with list input

Question

I am using the vioplot funciton form the vioplot package, and I would like to feed a list as an input. So this is what I have:

# Violin Plots
library(vioplot)
x1 <- mtcars$mpg[mtcars$cyl==4]
x2 <- mtcars$mpg[mtcars$cyl==6]
x3 <- mtcars$mpg[mtcars$cyl==8]
vioplot(x1, x2, x3, names=c("4 cyl", "6 cyl", "8 cyl"),
   col="gold")
title("Violin Plots of Miles Per Gallon")

And this is what I would like to do:

# Violin Plots
library(vioplot)
x1 <- mtcars$mpg[mtcars$cyl==4]
x2 <- mtcars$mpg[mtcars$cyl==6]
x3 <- mtcars$mpg[mtcars$cyl==8]
l<-list(x1,x2,x3)
vioplot(l, names=c("4 cyl", "6 cyl", "8 cyl"),
   col="gold")
title("Violin Plots of Miles Per Gallon")

But I get this error:

Error in min(data) : invalid 'type' (list) of argument

Can you help? Thanks!

Answer 1

I have modified the vioplot function to accept a list as an input, you can use this vioplot2:

vioplot2<-function (x, ..., range = 1.5, h = NULL, ylim = NULL, names = NULL, 
    horizontal = FALSE, col = "magenta", border = "black", lty = 1, 
    lwd = 1, rectCol = "black", colMed = "white", pchMed = 19, 
    at, add = FALSE, wex = 1, drawRect = TRUE) 
{
    if(!is.list(x)){
        datas <- list(x, ...)
    } else{
        datas<-x
    }
    n <- length(datas)
    if (missing(at)) 
        at <- 1:n
    upper <- vector(mode = "numeric", length = n)
    lower <- vector(mode = "numeric", length = n)
    q1 <- vector(mode = "numeric", length = n)
    q3 <- vector(mode = "numeric", length = n)
    med <- vector(mode = "numeric", length = n)
    base <- vector(mode = "list", length = n)
    height <- vector(mode = "list", length = n)
    baserange <- c(Inf, -Inf)
    args <- list(display = "none")
    if (!(is.null(h))) 
        args <- c(args, h = h)
    for (i in 1:n) {
        data <- datas[[i]]
        data.min <- min(data)
        data.max <- max(data)
        q1[i] <- quantile(data, 0.25)
        q3[i] <- quantile(data, 0.75)
        med[i] <- median(data)
        iqd <- q3[i] - q1[i]
        upper[i] <- min(q3[i] + range * iqd, data.max)
        lower[i] <- max(q1[i] - range * iqd, data.min)
        est.xlim <- c(min(lower[i], data.min), max(upper[i], 
            data.max))
        smout <- do.call("sm.density", c(list(data, xlim = est.xlim), 
            args))
        hscale <- 0.4/max(smout$estimate) * wex
        base[[i]] <- smout$eval.points
        height[[i]] <- smout$estimate * hscale
        t <- range(base[[i]])
        baserange[1] <- min(baserange[1], t[1])
        baserange[2] <- max(baserange[2], t[2])
    }
    if (!add) {
        xlim <- if (n == 1) 
            at + c(-0.5, 0.5)
        else range(at) + min(diff(at))/2 * c(-1, 1)
        if (is.null(ylim)) {
            ylim <- baserange
        }
    }
    if (is.null(names)) {
        label <- 1:n
    }
    else {
        label <- names
    }
    boxwidth <- 0.05 * wex
    if (!add) 
        plot.new()
    if (!horizontal) {
        if (!add) {
            plot.window(xlim = xlim, ylim = ylim)
            axis(2)
            axis(1, at = at, label = label)
        }
        box()
        for (i in 1:n) {
            polygon(c(at[i] - height[[i]], rev(at[i] + height[[i]])), 
                c(base[[i]], rev(base[[i]])), col = col, border = border, 
                lty = lty, lwd = lwd)
            if (drawRect) {
                lines(at[c(i, i)], c(lower[i], upper[i]), lwd = lwd, 
                  lty = lty)
                rect(at[i] - boxwidth/2, q1[i], at[i] + boxwidth/2, 
                  q3[i], col = rectCol)
                points(at[i], med[i], pch = pchMed, col = colMed)
            }
        }
    }
    else {
        if (!add) {
            plot.window(xlim = ylim, ylim = xlim)
            axis(1)
            axis(2, at = at, label = label)
        }
        box()
        for (i in 1:n) {
            polygon(c(base[[i]], rev(base[[i]])), c(at[i] - height[[i]], 
                rev(at[i] + height[[i]])), col = col, border = border, 
                lty = lty, lwd = lwd)
            if (drawRect) {
                lines(c(lower[i], upper[i]), at[c(i, i)], lwd = lwd, 
                  lty = lty)
                rect(q1[i], at[i] - boxwidth/2, q3[i], at[i] + 
                  boxwidth/2, col = rectCol)
                points(med[i], at[i], pch = pchMed, col = colMed)
            }
        }
    }
    invisible(list(upper = upper, lower = lower, median = med, 
        q1 = q1, q3 = q3))
}

What you get with your example is this:

Answer 2

I've included the solution above in an function (R package) on Github. Should work just like input for boxplot (including formula input), includes a range of other custom features such as separate colours for each violin.

Install and load with:

install.packages("devtools")
devtools::install_github("TomKellyGenetics/vioplotx")
library("vioplotx")

So just like you would make a boxplot:

# Set up data
data(mtcars)
x1 <- mtcars$mpg[mtcars$cyl==4]
x2 <- mtcars$mpg[mtcars$cyl==6]
x3 <- mtcars$mpg[mtcars$cyl==8]
l<-list(x1,x2,x3)

# Boxplots
boxplot(l, names=c("4 cyl", "6 cyl", "8 cyl"), col="gold")
title("Boxplots of Miles Per Gallon")

You can use the "vioplotx" do do the same:

So just like you would make a violinplot:

# Violin plots
vioplotx(l, names=c("4 cyl", "6 cyl", "8 cyl"), col="gold")
title("Violin plots of Miles Per Gallon")

This also enables additional customisation with vector inputs:

vioplotx(l, names=c("4 cyl", "6 cyl", "8 cyl"), col=c("cyan", "magenta", "green"))

This is modification of Daniel Adler's "vioplot" package including change based on Federico Giorgi's answer here. This is purely intended to make running such modifications easier.