R 自定义ggplot2中一个图形内的两个图例

我想就以下疑问发表评论

使用此代码：

Plot<-data.frame(Age=c(0,0,0,0,0),Density=c(0,0,0,0,0),Sensitivity=c(0,0,0,0,0),inf=c(0,0,0,0,0),sup=c(0,0,0,0,0),tde=c(0,0,0,0,0))    
Plot[1,]<-c(1,1,0.857,0.793,0.904,0.00209834)
Plot[2,]<-c(1,2,0.771   ,0.74,0.799,0.00348286)
Plot[3,]<-c(1,3,0.763   ,0.717,0.804,0.00577784) 
Plot[4,]<-c(1,4,0.724   ,0.653,0.785,0.00504161)
Plot[5,]<-c(2,1,0.906,0.866,0.934,0.00365742)
Plot[6,]<-c(2,2,0.785   ,0.754,0.813,0.00440399)
Plot[7,]<-c(2,3,0.660,0.593,0.722,0.00542849)
Plot[8,]<-c(2,4,0.544,0.425,0.658,0.00433052)

     names(Plot)<-c("Age","Mammographyc density","Sensitivity","inf","sup","tde")
    Plot$Age<-c("50-59","50-59","50-59","50-59","60-69","60-69","60-69","60-69")
    Plot$Density<-c("Almost entirely fat","Scattered fibroglandular density","Heterogeneously dense","Extremely dense","Almost entirely fat","Scattered fibroglandular density","Heterogeneously dense","Extremely dense")    
levels(Plot$Age)<-c("50-59","60-69")
levels(Plot$Density)<-c("Almost entirely fat","Scattered fibroglandular density","Heterogeneously dense","Extremely dense")
pd <- position_dodge(0.2) # 
    Plot$Density <- reorder(Plot$Density, 1-Plot$Sensitivity)

ggplot(Plot, aes(x = Density, y = 100*Sensitivity, colour=Age)) + 
  geom_errorbar(aes(ymin = 100*inf, ymax = 100*sup), width = .1, position = pd) +
  geom_line(position = pd, aes(group = Age), linetype = c("dashed")) +
  geom_point(position = pd, size = 4)+
  scale_y_continuous(expand = c(0, 0),name = 'Sensitivity (%)',sec.axis = sec_axis(~./5,   name  = 'Breast cancer detection rate (per 1000 mammograms)', breaks = c(0,5,10,15,20),
                                                              labels = c('0‰',"5‰", '10‰', '15‰', '20‰')), limits = c(0,100)) +
   geom_line(position = pd, aes(x = Density, y = tde * 5000, colour = Age, group = Age), linetype = c("dashed"), data = Plot) +
  geom_point(shape=18,aes(x = Density, y = tde * 5000, colour = Age, group = Age), position = pd, size = 4) +
  theme_light() + 
 scale_color_manual(name="Age (years)",values = c("50-59"= "grey55", "60-69" = "grey15")) +
  theme(legend.position="bottom") + guides(colour = guide_legend(), size = guide_legend(),
                                         shape = guide_legend())

Plot您应该做的是一个面板图，以避免双轴混淆：

library(dplyr)
library(tidyr)
Plot %>% 
  gather(measure, Result, Sensitivity, tde) %>%
  ggplot(aes(x = Density, y = Result, colour=Age)) + 
  geom_errorbar(aes(ymin = inf, ymax = sup), width = .1, position = pd,
                data = . %>% filter(measure == "Sensitivity")) +
  geom_line(aes(group = Age), position = pd, linetype = "dashed") +
  geom_point(position = pd, size = 4)+
  # scale_y_continuous(expand = c(0, 0), limits = c(0, 1)) +
  scale_y_continuous(labels = scales::percent) +
  facet_wrap(~measure, ncol = 1, scales = "free_y") +
  theme_light() + 
  scale_color_manual(name="Age (years)",values = c("50-59"= "grey55", "60-69" = "grey15")) +
  theme(legend.position="bottom")


但按照您的要求，您的问题是您只有一个非位置美学贴图，所以您不能获得多个图例。要强制创建第二个图例，需要添加第二个映射。它可以是一个无效的虚拟映射，如下所示，我们映射
alpha
，然后手动将两个级别缩放到100%。此解决方案不可取，因为正如您在所需图例示例中所做的那样，很容易混淆映射，并通过错误标记哪些点是敏感点，哪些点是检测率来让viz说谎

ggplot(Plot, aes(x = Density, y = 100*Sensitivity, colour=Age, alpha = Age)) + 
  geom_errorbar(aes(ymin = 100*inf, ymax = 100*sup), width = .1, position = pd) +
  geom_line(position = pd, aes(group = Age), linetype = c("dashed")) +
  geom_point(position = pd, size = 4)+
  scale_y_continuous(expand = c(0, 0),name = 'Sensitivity (%)',sec.axis = sec_axis(~./5,   name  = 'Breast cancer detection rate (per 1000 mammograms)', breaks = c(0,5,10,15,20),
                                                                                   labels = c('0‰',"5‰", '10‰', '15‰', '20‰')), limits = c(0,100)) +
  geom_line(position = pd, aes(x = Density, y = tde * 5000, colour = Age, group = Age), linetype = c("dashed"), data = Plot) +
  geom_point(shape=18,aes(x = Density, y = tde * 5000, colour = Age, group = Age), position = pd, size = 4) +
  theme_light() + 
  scale_color_manual(name="Age (years)",values = c("50-59"= "grey55", "60-69" = "grey15")) +
  scale_alpha_manual(values = c(1, 1)) +
  guides(alpha = guide_legend("Sensitivity"),
         color = guide_legend("Detection Rate", override.aes = list(shape = 18))) +
  theme(legend.position="bottom")

我认为您提出的解决方案更好，非常感谢。只有一个问题，我怎样才能更改“tde”的标签？因为我真的很想把“检测率”放进去，我不能这样调用变量。定制刻面标签有点复杂。我最常做的是在将变量传递给ggplot之前重命名数据帧中的变量。要在绘图中执行此操作，您需要将此参数添加到
facet\u wrap
调用中：
labeller=labeller（measure=c（“检测率”=“tde”，“灵敏度”=“灵敏度”））