从使用 stat_summary 生成的图中删除点

Question

有人要求我从使用ggplot2 制作的绘图中删除点。我正在附加一个 MWE：

require(ggplot2)
require(Hmisc)
x = 5
k = 50
kx = k*5
data.A.1 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 0)
data.B.1 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 1)
data.C.1 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 2)
data.A.2 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 3)
data.B.2 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 4)
data.C.2 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 5)
multiple.plot.6x3.interval <- function(D, L) {
    data = data.frame()
    # join all the data in D into 'data'
    e = 0
    NN = ""
    for (i in seq(1, length(D))) {
        lidx = i%%3
        if (lidx == 0) { lidx = 3 }
        if (lidx == 1) {
            e = e + 1
            NN = paste0("10^", e)
        }
        n.obs = length(D[[i]]$n)
        D[[i]]$lang.name = rep(L[lidx], n.obs)
        D[[i]]$N = rep(NN, n.obs)
        data = rbind(data, D[[i]])
    }
    # make the plot
    g <- ggplot(data, aes(x=n, y=v)) +
        stat_summary(  # plot confidence interval
            fun.data = mean_cl_boot, fun.args = (conf.int = 0.99),
            geom = "ribbon", fill = "darkgrey"
        ) +
        stat_summary(  # plot maximum and minimum bars
            fun = mean, fun.min = min, fun.max = max,
            colour = "red", size = 0.15
        ) +
        stat_summary(
            fun = mean,
            geom = "line", linetype = "solid", size = 0.4, color = "black"
        ) +
        coord_cartesian(xlim=c(1, 100)) + 
        scale_x_continuous(breaks=seq(1, 101, 10)-1) +
        facet_grid(
            N ~ lang.name, labeller = "label_parsed"
        ) +
        labs(
            x=bquote("X"),
            y=bquote("Y")
        ) +
        theme(text = element_text(size = 20))
    
    return (g)
}
g <- multiple.plot.6x3.interval(
    list(
        data.A.1, data.B.1, data.C.1,
        data.A.2, data.B.2, data.C.2
    ),
    c("A", "B", "C")
)
plot(g)

这段代码的结果是我想要的，但我被要求删除这个点的例外

        stat_summary(  # plot maximum and minimum bars
            fun = mean, fun.min = min, fun.max = max,
            colour = "red", size = 0.15
        ) +

在保持条形的同时生成。

这是我得到的，我想删除红点（不是红条）。

使用size = 0 将使条形完全不可见。我自己无法做到这一点。我想知道：这可以做到吗？如果是这样，怎么做？任何帮助将不胜感激。

谢谢大家。

Answer 1

尝试将geom = "errorbar" 作为stat_summary 的参数：

require(ggplot2)
require(Hmisc)
x = 5
k = 50
kx = k*5
data.A.1 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 0)
data.B.1 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 1)
data.C.1 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 2)
data.A.2 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 3)
data.B.2 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 4)
data.C.2 = data.frame(n = rep(sample(1:100, k, replace=FALSE), x), v = rnorm(kx, 1, 2) + 5)
multiple.plot.6x3.interval <- function(D, L) {
  data = data.frame()
  # join all the data in D into 'data'
  e = 0
  NN = ""
  for (i in seq(1, length(D))) {
    lidx = i%%3
    if (lidx == 0) { lidx = 3 }
    if (lidx == 1) {
      e = e + 1
      NN = paste0("10^", e)
    }
    n.obs = length(D[[i]]$n)
    D[[i]]$lang.name = rep(L[lidx], n.obs)
    D[[i]]$N = rep(NN, n.obs)
    data = rbind(data, D[[i]])
  }
  # make the plot
  g <- ggplot(data, aes(x=n, y=v)) +
    stat_summary(  # plot confidence interval
      fun.data = mean_cl_boot, fun.args = (conf.int = 0.99),
      geom = "ribbon", fill = "darkgrey"
    ) +
    stat_summary(  # plot maximum and minimum bars
      fun = mean, fun.min = min, fun.max = max,
      geom = "errorbar",     ### HERE
      colour = "red", size = 0.15
    ) +
    stat_summary(
      fun = mean,
      geom = "line", linetype = "solid", size = 0.4, color = "black"
    ) +
    coord_cartesian(xlim=c(1, 100)) + 
    scale_x_continuous(breaks=seq(1, 101, 10)-1) +
    facet_grid(
      N ~ lang.name, labeller = "label_parsed"
    ) +
    labs(
      x=bquote("X"),
      y=bquote("Y")
    ) +
    theme(text = element_text(size = 20))
  
  return (g)
}
g <- multiple.plot.6x3.interval(
  list(
    data.A.1, data.B.1, data.C.1,
    data.A.2, data.B.2, data.C.2
  ),
  c("A", "B", "C")
)
plot(g)