如果你查看.subset2(GeomViolin, "draw_group")的代码，你会发现分位数路径的linewidth继承自小提琴几何的linewidth美学，你不能（轻易地）改变它。这是有道理的，因为对于小提琴部分，我们在原始数据上操作，而对于分位数，我们实际上需要2位数据（不同维度）：

• 原始数据以确定小提琴轮廓
• 我们要加进去的几个分位数

基本上我有两个选择：

创建您自己的几何图形

诚然，这对我来说似乎有点大材小用，但为了好玩（也为了磨练我的自定义Geom编码技能），我尝试了一下（它远非完美，我需要发明一个新的参数名称linesize，从语义上讲，它就是linewidth，但对于前面提到的我们需要两个不同大小的数据集的问题，我需要一个“新”参数）。
好消息是，你基本上只是复制和粘贴相关的代码，剥离如果从所有不必要的部分有关的小提琴，因此你不必重新发明轮子。唯一真正需要的变化是在draw_group，而对于其他人，我们可以简单地依赖于默认的GeomViolin和StatYdensity（默认的stat的geom_violin）。

## 1. Create your workhorse function for draw_group
## basically a copy paste of .subset2(GeomViolin, "draw_group") 
## where all stuff related to the violin is removed
draw_group_violin_quantiles <- function(self, data, quantiles, ..., linesize = NULL, 
                                        flipped_aes = FALSE) {
  data <- flip_data(data, flipped_aes)
  data <- transform(data, xminv = x - violinwidth * (x - xmin), 
                    xmaxv = x + violinwidth * (xmax - x))
  if (!(all(quantiles >= 0) && all(quantiles <= 1))) {
    cli::cli_abort("{.arg quantiles} must be between 0 and 1")
  }
  quantiles <- ggplot2:::create_quantile_segment_frame(data, quantiles)
  aesthetics <- data[rep(1, nrow(quantiles)), 
                     setdiff(names(data), 
                             c("x", "y", "group")), drop = FALSE]
  aesthetics$alpha <- rep(1, nrow(quantiles))
  if (!is.null(linesize)) {
    aesthetics$linewidth <- rep(linesize, each = 2)
  }
  both <- vctrs::vec_cbind(quantiles, aesthetics)
  both <- both[!is.na(both$group), , drop = FALSE]
  both <- flip_data(both, flipped_aes)
  quantile_grob <- GeomPath$draw_panel(both, ...)
  ggplot2:::ggname("geom_violin_quantiles", quantile_grob)
}

## 2. Create your Geom proto object
## here we just inherit everything from `GeomViolin` and just replace the draw_group
GeomViolinQuantiles <- ggproto(
  "GeomViolinQuantiles",
  GeomViolin,
  draw_group = draw_group_violin_quantiles
)

## 3. Create the user facting geom_violin_qunatiles function
geom_violin_quantiles <- function(mapping = NULL,
                                  data = NULL,
                                  stat = "ydensity",
                                  position = "dodge",
                                  quantiles = NULL,
                                  ...,
                                  linesize = NULL,
                                  trim = TRUE, scale = "area", 
                                  na.rm = FALSE, orientation = NA, 
                                  show.legend = NA, inherit.aes = TRUE) {
  layer(data = data, mapping = mapping, stat = stat, geom = GeomViolinQuantiles, 
        position = position, show.legend = show.legend, inherit.aes = inherit.aes, 
        params = list(trim = trim, scale = scale, quantiles = quantiles, 
                       na.rm = na.rm, orientation = orientation, linesize = linesize, ...))
}

现在你可以像这样使用你的新geom_violin_quantiles了（浅色的问题可以用colorspace::lighten轻松解决）：

library(colorspace)
ggplot(data, aes(Label, n, fill = Label)) +
  geom_violin(trim = FALSE, 
              adjust = 0.6) +
  geom_violin_quantiles(quantiles = c(0.25, 0.5, 0.75), adjust = .6,
                        linesize = c(.5, 1, .5)) +
  scale_fill_manual(values = c(Blue = "#42E894", Red = lighten("#42E894", .5)))

摆弄grob以更改事后宽度

另一种我经常使用的方法是，当我只想更改一个很好的ggplot的一个小方面时，在图表的grob表示中找到相应的插槽并更改图形参数。
这种方法需要在grob维斯str中进行一些搜索，并且不太稳定。也就是说，只要你对原来的绘图做了一点小的改变，你就需要再次搜索grob，因为内部位置可能会改变。
话虽如此，对于给定的示例，您可以简单地运行以下代码行：

library(grid)  
vp <- ggplot(data, aes(Label, n, fill = Label)) +
  geom_violin(trim = FALSE, 
              adjust = 0.6, draw_quantiles = c(0.25, 0.5, 0.75)) +
  scale_fill_manual(values = c(Blue = "#42E894", Red = lighten("#42E894", .5)))

## create the grob from the plot
vp_obj <- ggplotGrob(vp)

## after some searching via `str` find the relavant grob 
## in the whole object which represents the lines for the quantiles
## this position totally depends on the plot and has to be updated in
## case the plot changes

lw <- vp_obj$grobs[[6L]]$children[[3L]]$children[[1L]]$children[[2L]]$gp$lwd
lw[2L] <- 2 * lw[2L]

## violin for "Blue"
vp_obj$grobs[[6L]]$children[[3L]]$children[[1L]]$children[[2L]]$gp$lwd <- lw

## Violin for "Red"
vp_obj$grobs[[6L]]$children[[3L]]$children[[2L]]$children[[2L]]$gp$lwd <- lw

## Plot the whole thing
grid.draw(vp_obj)

我发现了另一个需要更少代码的解决方案：manual specification of draw_quantile argument in violin plot call in R
首先绘制小提琴图，其中0.25和0.75分位数显示为虚线，然后绘制另一个小提琴图，其中0.5分位数显示为实线，并添加透明背景。

ggplot(data, aes(Label, n)) +
  geom_violin(legend = FALSE, trim = FALSE, adjust = 0.6, draw_quantiles = c(0.25, 0.75), linetype = "dashed") +
  geom_violin(legend = FALSE, trim = FALSE, adjust = 0.6, draw_quantiles = 0.5, fill="transparent")

Violin Plot
我不知道如何在不更改小提琴图轮廓外观的情况下使0.5线更粗（可以通过向透明小提琴图添加参数size来实现）。
colorspace Package中的lighten函数是查找某个颜色的较浅版本的最简单方法。

ggplot(data, aes(Label, n, fill=Label)) +
  geom_violin(legend = FALSE, trim = FALSE, adjust = 0.6, draw_quantiles = c(0.25, 0.75), linetype = "dashed") +
  geom_violin(legend = FALSE, trim = FALSE, adjust = 0.6, draw_quantiles = 0.5, fill="transparent", size=0.75) +
  scale_fill_manual(values=c(Blue = "#42E894", Red = lighten("#42E894", 0.6)))

Violin Plot colored

为了完整和帮助其他人，我实际上结合了@Maria-Christina Weber和@thothal的答案，用粗中线和虚线分位数绘制了一个小提琴图。

从@thothal复制并粘贴代码

## 1. Create your workhorse function for draw_group
## basically a copy paste of .subset2(GeomViolin, "draw_group") 
## where all stuff related to the violin is removed
draw_group_violin_quantiles <- function(self, data, quantiles, ..., linesize = NULL, 
                                        flipped_aes = FALSE) {
  data <- flip_data(data, flipped_aes)
  data <- transform(data, xminv = x - violinwidth * (x - xmin), 
                    xmaxv = x + violinwidth * (xmax - x))
  if (!(all(quantiles >= 0) && all(quantiles <= 1))) {
    cli::cli_abort("{.arg quantiles} must be between 0 and 1")
  }
  quantiles <- ggplot2:::create_quantile_segment_frame(data, quantiles)
  aesthetics <- data[rep(1, nrow(quantiles)), 
                     setdiff(names(data), 
                             c("x", "y", "group")), drop = FALSE]
  aesthetics$alpha <- rep(1, nrow(quantiles))
  if (!is.null(linesize)) {
    aesthetics$linewidth <- rep(linesize, each = 2)
  }
  both <- vctrs::vec_cbind(quantiles, aesthetics)
  both <- both[!is.na(both$group), , drop = FALSE]
  both <- flip_data(both, flipped_aes)
  quantile_grob <- GeomPath$draw_panel(both, ...)
  ggplot2:::ggname("geom_violin_quantiles", quantile_grob)
}

## 2. Create your Geom proto object
## here we just inherit everything from `GeomViolin` and just replace the draw_group
GeomViolinQuantiles <- ggproto(
  "GeomViolinQuantiles",
  GeomViolin,
  draw_group = draw_group_violin_quantiles
)

## 3. Create the user facting geom_violin_qunatiles function
geom_violin_quantiles <- function(mapping = NULL,
                                  data = NULL,
                                  stat = "ydensity",
                                  position = "dodge",
                                  quantiles = NULL,
                                  ...,
                                  linesize = NULL,
                                  trim = TRUE, scale = "area", 
                                  na.rm = FALSE, orientation = NA, 
                                  show.legend = NA, inherit.aes = TRUE) {
  layer(data = data, mapping = mapping, stat = stat, geom = GeomViolinQuantiles, 
        position = position, show.legend = show.legend, inherit.aes = inherit.aes, 
        params = list(trim = trim, scale = scale, quantiles = quantiles, 
                       na.rm = na.rm, orientation = orientation, linesize = linesize, ...))
}

使用透明度和@thotal的新geom函数生成GGplot

library(colorspace)
ggplot(data, aes(Label, n, fill=Label)) +
  geom_violin(show.legend = FALSE, trim = FALSE, adjust = 0.6, draw_quantiles = c(0.25, 0.75), linetype = "dashed") +
  geom_violin(show.legend = FALSE, trim = FALSE, adjust = 0.6, fill= "transparent") +
  geom_violin_quantiles(quantiles = 0.5, adjust = .6,
                        linesize = 1) +
  theme(axis.title.x = element_blank()) +
  scale_fill_manual(values = c(Blue = "#42E894", Red = lighten("#42E894", .5)))

结果图：）x1c 0d1x
谢谢你们两个，太棒了！