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ggplot用水平平均线分割小提琴图

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我使用ggplot创建了这些分裂半小提琴图 . 然而,我不想包括显示中位数的箱线图,而是想包含一个带平均线的水平线 . 这意味着每个有色半部分都有自己的平均线:金半部分的平均线与灰色半部分的平均线不完全对齐 . 重要的是,我希望平均线仅位于密度图内 . 我怎样才能做到这一点?我无法理解,我会感激任何帮助!

这是一些示例数据:

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))
)

这是geom_violin创建split_geom_violin的扩展:

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, ...))
}

这是图表的代码:

library(ggplot2)
ggplot(my_data, aes(x, y, fill=m)) + 
  geom_split_violin(trim = TRUE) + 
  geom_boxplot(width = 0.25, notch = FALSE, notchwidth = .4, outlier.shape = NA, coef=0) +
  labs(x=NULL,y="GM Attitude Score") +
  theme_classic() +
  theme(text = element_text(size = 20)) +
  scale_x_discrete(labels=c("0" = "Control\nCondition", "1" = "GM\nCondition")) +
  scale_fill_manual(values=c("#E69F00", "#999999"), 
                    name="Survey\nPart",
                    breaks=c("1", "2"),
                    labels=c("Time 1", "Time 5"))

enter image description here

1 回答

  • 1

    您可以使用 stat_summarygeom_crossbar 同时将所有 fun.yfun.yminfun.ymax 设置为 mean

    library(ggplot2)
    
    ggplot(my_data, aes(x, y, fill = m)) +
      geom_split_violin(trim = TRUE) +
      stat_summary(fun.y = mean, fun.ymin = mean, fun.ymax = mean,
                   geom = "crossbar", 
                   width = 0.25,
                   position = position_dodge(width = .25),
      ) +
      labs(x = NULL, y = "GM Attitude Score") +
      theme_classic() +
      theme(text = element_text(size = 20)) +
      scale_x_discrete(labels = c("0" = "Control\nCondition", "1" = "GM\nCondition")) +
      scale_fill_manual(
        values = c("#E69F00", "#999999"),
        name = "Survey\nPart",
        breaks = c("1", "2"),
        labels = c("Time 1", "Time 5")
      )
    

    使用的数据和功能:

    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))
    )
    
    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, ...
        )
      )
    }
    

    reprex package(v0.2.0.9000)创建于2018-07-08 .

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