小提琴图：展示数据密度分布的工具

小提琴图没什么特别的，就是把密度估计放在一根对称轴的两边，然后竖起来就可以了。我们可以把它看做箱线图的同伴；箱线图只是展示了分位数的位置，小提琴图展示了任意位置的密度，通过小提琴图我们可以知道哪些位置的密度较高。另外，我们也可以把多个小提琴放在一起比较。如下图：

所用函数simple.violinplot()来自于UsingR包，不过它没有提供填充不同颜色的功能，上图是我修改了源代码之后作出来的。问题来自于Adelaide大学的Fernando Marmolejo Ramos，他在R-help里面问了没人回答，所以就给我私人Email了。

不多写了，不然到时候书卖不出去了。

library(UsingR)
violin.colors = function(x, ..., orientation = "vertical", 
  bw = "nrd0", names = NULL, from = NULL, to = from, pars = NULL, 
  col = NA) {
  args <- list(x, ...)
  namedargs <- if (!is.null(attributes(args)$names)) 
      attributes(args)$names != ""
  else rep(FALSE, length = length(args))
  pars <- c(args[namedargs], pars)
  groups <- if (is.list(x)) 
    x
  else args[!namedargs]
  if (0 == (n <- length(groups))) 
    stop("invalid first argument")
  if (length(class(groups))) 
    groups <- unclass(groups)
  if (!missing(names)) 
    attr(groups, "names") <- names
  else {
    if (is.null(attr(groups, "names"))) 
      attr(groups, "names") <- 1:n
    names <- attr(groups, "names")
  }
  xvals <- matrix(0, nr = 512, nc = n)
  yvals <- matrix(0, nr = 512, nc = n)
  center <- 1:n
  for (i in 1:n) {
    if (is.null(from)) 
      tmp.dens <- density(groups[[i]], bw = bw)
    else tmp.dens <- density(groups[[i]], bw = bw, from = from, 
      to = to)
    xvals[, i] <- tmp.dens$x
    yvals.needtoscale <- tmp.dens$y
    yvals.scaled <- 7/16 * yvals.needtoscale/max(yvals.needtoscale)
    yvals[, i] <- yvals.scaled
  }
  if (orientation == "vertical") {
    xrange <- c(1/2, n + 1/2)
    yrange <- range(xvals)
  }
  else {
    xrange <- range(xvals)
    yrange <- c(min(yvals), max(yvals))
  }
  plot.new()
  plot.window(xlim = xrange, ylim = yrange)
  for (i in 1:n) vlnplt(xvals[, i], yvals[, i], center[i], 
      bordercolor = rainbow(i), bgcolor = rainbow(n - i), orientation = orientation, 
      col = col[i], ...)
  axis(1, at = 1:n, labels = names)
  axis(2)
}

a = rnorm(25, 100, 50)
b = rnorm(25, 300, 50)

violin.colors(list("Group A" = a, "Group B" = b), col = 1:2)