如何将geom_segment添加到geom_density_ridges_gradient？

Question

我想在棱线图中添加垂直线段，其直方图显示定制的分位数。

如果我用..x..映射填充颜色，我设法获得了垂直线段，但是我想在密度图中显示分位数。我写了以下代码：

library(datasets)
library(ggplot2)
data("iris")

iris_lines <- data.frame(Species = c("setosa", "versicolor", "virginica"),
                         x0 = c(5, 5.9, 6.5))

Figure1 <- ggplot(iris, aes(x=Sepal.Length, y=Species, fill=(..quantile..))) +
  geom_density_ridges_gradient(jittered_points = FALSE, calc_ecdf = TRUE, quantile_lines = c(TRUE), quantiles =c(0.1,0.25,0.75,0.9),scale=0.9, color='white')+
  geom_segment(data = iris_lines, aes(x = x0, xend = x0, y = as.numeric(Species), yend = as.numeric(Species) + c(.9,.5,.5)), color = "red") + scale_y_discrete(expand = c(0.01, 0))
Figure1

如果我将填充色映射为fill = ..x..，则该代码将起作用，我得到三条垂直线，分别代表每个密度图的平均值；但是，如果将填充颜色映射为fill = ..quantile..，则会出现以下错误：

Error in data.frame(..., check.names = FALSE) : 
  arguments imply differing number of rows: 1, 3

Answer 1

漂亮的图表！

将inherit.aes = F添加到第二个几何中，这样它就不会尝试将您的数据与ggplot(aes()调用中的填充计算进行匹配。

Figure1 <- ggplot(iris, aes(x=Sepal.Length, y=Species, fill=(..quantile..))) +
      geom_density_ridges_gradient(jittered_points = FALSE, 
                                   calc_ecdf = TRUE, 
                                   quantile_lines = c(TRUE), 
                                   quantiles =c(0.1,0.25,0.75,0.9),
                                   scale=0.9, color='white') +
      geom_segment(data = iris_lines, 
                   aes(x = x0, xend = x0, 
                       y = as.numeric(Species), yend = as.numeric(Species) + c(.9,.5,.5)),
                   color = "red", inherit.aes = F) +   #### HERE ####
      scale_y_discrete(expand = c(0.01, 0))
Figure1

---

编辑：

OP在评论中询问有选择地标记一些元素并为中线添加标签。这是一种方法，可能不是最胖的。

Figure1 <- ggplot(iris, aes(x=Sepal.Length, y=Species, 
                            fill = (..quantile..), 
                            color = (..quantile..))) +
  geom_density_ridges_gradient(jittered_points = FALSE, 
                               calc_ecdf = TRUE, 
                               quantile_lines = c(TRUE), 
                               quantiles =c(0.1,0.25,0.75,0.9),
                               scale=0.9, color='white') +
  geom_segment(data = iris_lines, 
               aes(x = x0, xend = x0, fill = "median",
                   y = as.numeric(Species), 
                   yend = as.numeric(Species) + c(.9,.5,.5),
                   color = "median")) +   #### HERE ####
  scale_y_discrete(expand = c(0.01, 0)) +

  scale_color_manual(name = "quantile",
                     limits = c(1:3, "median"),
                     values = alpha("firebrick1", c(0, 0, 0, 1)),
                     labels = c("<10%", "10-25%", "IQR", "median")) +
  scale_fill_manual(name = "quantile",
    limits = c(1:3, "median"),
    values = c("cadetblue", "coral", "orange", "white"), 
    na.value = "gray30",
    labels = c("<10%", "10-25%", "IQR", "median"))
Figure1