用ggplot2分割小提琴情节

时间:2016-03-01 07:49:38

标签: r ggplot2 violin-plot ggproto

我想用ggplot创建一个分裂小提琴密度图,就像seaborn文档this page上的第四个例子一样。

以下是一些数据:

set.seed(20160229)

my_data = data.frame(
    y=c(rnorm(1000), rnorm(1000, 0.5), rnorm(1000, 1), rnorm(1000, 1.5)),
    x=c(rep('a', 2000), rep('b', 2000)),
    m=c(rep('i', 1000), rep('j', 2000), rep('i', 1000))
)

我可以像这样绘制躲闪的小提琴:

library('ggplot2')

ggplot(my_data, aes(x, y, fill=m)) +
  geom_violin()

enter image description here

但是在视觉上比较并排分布中不同点的宽度很难。我无法在ggplot中找到任何拆分小提琴的例子 - 这可能吗?

我发现了一个base R graphics solution,但功能很长,我想突出显示分布模式,这些模式很容易在ggplot中作为附加图层添加,但如果我需要弄清楚如何编辑将会更难那个功能。

2 个答案:

答案 0 :(得分:41)

注意:我认为jan-glx的答案要好得多,大多数人都应该使用它。

您可以通过事先计算密度,然后绘制多边形来实现此目的。请参阅下面的粗略概念。

获取密度

library(dplyr)
pdat <- my_data %>%
  group_by(x, m) %>%
  do(data.frame(loc = density(.$y)$x,
                dens = density(.$y)$y))

组的翻转和偏移密度

pdat$dens <- ifelse(pdat$m == 'i', pdat$dens * -1, pdat$dens)
pdat$dens <- ifelse(pdat$x == 'b', pdat$dens + 1, pdat$dens)

剧情

ggplot(pdat, aes(dens, loc, fill = m, group = interaction(m, x))) + 
  geom_polygon() +
  scale_x_continuous(breaks = 0:1, labels = c('a', 'b')) +
  ylab('density') +
  theme_minimal() +
  theme(axis.title.x = element_blank())

结果

enter image description here

答案 1 :(得分:33)

或者,为了避免摆弄密度,您可以像这样扩展Concatenating null strings in Java

GeomSplitViolin <- ggproto("GeomSplitViolin", GeomViolin, 
                           draw_group = function(self, data, ..., draw_quantiles = NULL) {
  data <- transform(data, xminv = x - violinwidth * (x - xmin), xmaxv = x + violinwidth * (xmax - x))
  grp <- data[1, "group"]
  newdata <- plyr::arrange(transform(data, x = if (grp %% 2 == 1) xminv else xmaxv), if (grp %% 2 == 1) y else -y)
  newdata <- rbind(newdata[1, ], newdata, newdata[nrow(newdata), ], newdata[1, ])
  newdata[c(1, nrow(newdata) - 1, nrow(newdata)), "x"] <- round(newdata[1, "x"])

  if (length(draw_quantiles) > 0 & !scales::zero_range(range(data$y))) {
    stopifnot(all(draw_quantiles >= 0), all(draw_quantiles <=
      1))
    quantiles <- ggplot2:::create_quantile_segment_frame(data, draw_quantiles)
    aesthetics <- data[rep(1, nrow(quantiles)), setdiff(names(data), c("x", "y")), drop = FALSE]
    aesthetics$alpha <- rep(1, nrow(quantiles))
    both <- cbind(quantiles, aesthetics)
    quantile_grob <- GeomPath$draw_panel(both, ...)
    ggplot2:::ggname("geom_split_violin", grid::grobTree(GeomPolygon$draw_panel(newdata, ...), quantile_grob))
  }
  else {
    ggplot2:::ggname("geom_split_violin", GeomPolygon$draw_panel(newdata, ...))
  }
})

geom_split_violin <- function(mapping = NULL, data = NULL, stat = "ydensity", position = "identity", ..., 
                              draw_quantiles = NULL, trim = TRUE, scale = "area", na.rm = FALSE, 
                              show.legend = NA, inherit.aes = TRUE) {
  layer(data = data, mapping = mapping, stat = stat, geom = GeomSplitViolin, 
        position = position, show.legend = show.legend, inherit.aes = inherit.aes, 
        params = list(trim = trim, scale = scale, draw_quantiles = draw_quantiles, na.rm = na.rm, ...))
}

然后像这样使用新的geom_split_violin

ggplot(my_data, aes(x, y, fill = m)) + geom_split_violin()

ggplot2's GeomViolin