ggplot2：标准错误色带与绘图线不匹配

Question

我正在尝试向我的 ggplot 添加错误栏色带，但由于某种原因，阴影与绘制的线不匹配。这是我第二次遇到这个问题，我一生都无法弄清楚为什么会发生这种情况。最初，我认为这可能是由于某些变量被定义为因素的方式，但即使我更改了它们的格式，我仍然会遇到这个问题。任何想法或建议将不胜感激！谢谢！

数据框：

    m<- structure(list(sound = structure(c(2L, 2L, 2L, 2L, 1L, 1L, 1L, 
1L), .Label = c("Silence", "English"), class = "factor"), `Reading condition` = structure(c(1L, 
1L, 2L, 2L, 1L, 1L, 2L, 2L), .Label = c("normal", "trailing mask"
), class = "factor"), diff = structure(c(2L, 1L, 2L, 1L, 2L, 
1L, 2L, 1L), .Label = c("Easy questions", "Difficult questions"
), class = "factor"), Mean = c(0.283, 0.36, 0.183, 0.227, 0.19, 
0.347, 0.197, 0.333), SD = c(0.500558971667007, 0.34814947033031, 
0.497195715406262, 0.447163568809774, 0.49804988833968, 0.361515576848703, 
0.498812908487118, 0.373926502247132), SE = c(0.100111794333401, 
0.0696298940660619, 0.0994391430812524, 0.0894327137619548, 0.099609977667936, 
0.0723031153697406, 0.0997625816974236, 0.0747853004494263)), .Names = c("sound", 
"Reading condition", "diff", "Mean", "SD", "SE"), row.names = c(NA, 
8L), idvars = c("sound", "mask", "diff"), rdimnames = list(structure(list(
    sound = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L), .Label = c("English", 
    "Silence"), class = "factor"), mask = structure(c(1L, 1L, 
    2L, 2L, 1L, 1L, 2L, 2L), .Label = c("No", "Yes"), class = "factor"), 
    diff = c("difficult", "easy", "difficult", "easy", "difficult", 
    "easy", "difficult", "easy")), .Names = c("sound", "mask", 
"diff"), row.names = c("English_No_difficult", "English_No_easy", 
"English_Yes_difficult", "English_Yes_easy", "Silence_No_difficult", 
"Silence_No_easy", "Silence_Yes_difficult", "Silence_Yes_easy"
), class = "data.frame"), structure(list(variable = structure(c(1L, 
1L), .Label = "accuracy", class = "factor"), result_variable = structure(1:2, .Label = c("M", 
"SD"), class = "factor")), .Names = c("variable", "result_variable"
), row.names = c("accuracy_M", "accuracy_SD"), class = "data.frame")), class = "data.frame")

图形代码：

library(ggplot2)
limits <- aes(ymax = m$Mean + m$SE, ymin=m$Mean - m$SE)

Dplot<- ggplot(data= m, aes(x=sound, y= Mean, color= `Reading condition`, 
                            fill= `Reading condition`,
                            group=`Reading condition`, shape=`Reading condition`,
                            linetype=`Reading condition`))+ 
  scale_fill_brewer(palette="Dark2")+ scale_colour_brewer(palette="Dark2")+
  theme_bw() + theme(panel.grid.major = element_line(colour = "#E3E5E6", size=0.7), 
                     axis.line = element_line(colour = "black", size=1),
                     panel.border = element_rect(colour = "black", size=1, fill = NA))+
  geom_line(size=2) + ylim(0, 0.5)+
  geom_point(size=7)+ scale_x_discrete(expand=c(0.2,0.2))+
  #scale_y_continuous(limits- c(0,0.50))+
  xlab("\n Background sound")+ ylab("Comprehension above chance level (%)")+ 
  theme(legend.position="bottom", legend.title=element_text(size=20, face="bold", family="serif"), legend.text=element_text(size=20,family="serif"),legend.key.width=unit(2,"cm"),
        legend.key.height=unit(1,"cm"), strip.text=element_text(size=20, family="serif"),
        title=element_text(size=20, family="serif"),
        axis.title.x = element_text(size=20, face="bold", family="serif"), axis.title.y = element_text(size=20, face="bold", family="serif"), 
        axis.text=element_text(size=20, family="serif"), 
        panel.border = element_rect(linetype = "solid", colour = "black"), 
        legend.key = element_rect(colour = "#000000", size=1))+
  geom_ribbon(limits, alpha=0.15, colour=NA) +
  facet_grid(.~ diff) + theme(strip.text.x = element_text(size = 20,  face="bold",family="serif"),
                                 strip.background = element_rect(fill="#F5F7F7", colour="black", size=1.5),
                                 legend.key = element_rect(colour = "#000000", size=1))

Answer 1

指定数据框和变量的子集（例如使用$）可能会导致ggplot中发生奇怪的事情。您永远不需要这样的子集，因为数据框已经在某个时候指定给 data 参数（可能在第一个 ggplot(...) 调用中）。与美学一样，数据也是从ggplot 继承到 geoms 和 stats，因此除非您更改数据，否则无需担心重新指定其来源。 （如果您确实想要更改使用的数据框，请指定相关几何或统计的data 参数。）

删除m$s 将解决问题。重新排列和简化，使逻辑更明显，

library(ggplot2)

m <- data.frame(sound = c("English", "English", "English", "English", "Silence", "Silence", "Silence", "Silence"), 
                `Reading condition` = c("normal", "normal", "trailing mask", "trailing mask", "normal", "normal", "trailing mask", "trailing mask"), 
                diff = c("Difficult questions", "Easy questions", "Difficult questions", "Easy questions", "Difficult questions", "Easy questions", "Difficult questions", "Easy questions"), 
                Mean = c(0.283, 0.36, 0.183, 0.227, 0.19, 0.347, 0.197, 0.333), 
                SD = c(0.500558971667007, 0.34814947033031, 0.497195715406262, 0.447163568809774, 0.49804988833968, 0.361515576848703, 0.498812908487118, 0.373926502247132), 
                SE = c(0.100111794333401, 0.0696298940660619, 0.0994391430812524, 0.0894327137619548, 0.099609977667936, 0.0723031153697406, 0.0997625816974236, 0.0747853004494263), 
                check.names = FALSE)

ggplot(m, aes(x = sound, y = Mean, ymax = Mean + SE, ymin = Mean - SE, 
              color = `Reading condition`, fill = `Reading condition`, 
              group = `Reading condition`)) + 
    geom_line() +
    geom_point() + 
    geom_ribbon(alpha = 0.15, colour = NA) +
    facet_grid(. ~ diff)

Answer 2

这样想 Alistaire 的正确答案：在后台，ggplot 获取您的起始 data.frame(s) 并应用您的 ggplot 代码所需的所有转换、比例和统计信息。然后在结果坐标系中生成图形。

通过使用 m$... 将功能区的 aes 锚定到全局环境 data.frame，您指定了预变换、预统计、预缩放坐标...有时您的原始坐标系可能是令人困惑地接近隐藏的坐标系，以便您的元素出现，但正如您所见，只是有点偏离。