将 geom_hline 添加到图例

Question

昨天和今天在网上搜索后，我获得图例工作的唯一方法是遵循“Brian Diggs”在这篇文章中的解决方案： 将图例添加到 ggplot2 线图

这给了我以下代码：

library(ggplot2)
ggplot()+
  geom_line(data=myDf, aes(x=count, y=mean, color="TrueMean"))+
  geom_hline(yintercept = myTrueMean, color="SampleMean")+
  scale_colour_manual("",breaks=c("SampleMean", "TrueMean"),values=c("red","blue"))+
  labs(title = "Plot showing convergens of Mean", x="Index", y="Mean")+
  theme_minimal()

如果我删除 的颜色，一切都会正常，但是如果我在不是实际颜色hline的颜色中添加一个值（例如），我会得到一个错误，它不是颜色（仅适用于）。添加一个像传奇这样常见的东西怎么会成为一个大问题呢？还有更简单的方法吗？hline"SampleMean"hline

创建原始数据：

#Initial variables
myAlpha=2
myBeta=2
successes=14
n=20
fails=n-successes

#Posterior values
postAlpha=myAlpha+successes
postBeta=myBeta+fails

#Calculating the mean and SD
myTrueMean=(myAlpha+successes)/(myAlpha+successes+myBeta+fails)
myTrueSD=sqrt(((myAlpha+successes)*(myBeta+fails))/((myAlpha+successes+myBeta+fails)^2*(myAlpha+successes+myBeta+fails+1)))

#Simulate the data
simulateBeta=function(n,tmpAlpha,tmpBeta){
  tmpValues=rbeta(n, tmpAlpha, tmpBeta)
  tmpMean=mean(tmpValues)
  tmpSD=sd(tmpValues)
  returnVector=c(count=n, mean=tmpMean, sd=tmpSD)
  return(returnVector)
}

#Make a df for the data
myDf=data.frame(t(sapply(2:10000, simulateBeta, postAlpha, postBeta)))

Answer 1

给定的解决方案适用于大多数情况，但不适用于geom_hline( vline)。对于它们，您通常不必使用aes，但是当您需要生成图例时，您必须将它们包装在aes：

library(ggplot2)
ggplot() +
  geom_line(aes(count, mean, color = "TrueMean"), myDf) +
  geom_hline(aes(yintercept = myTrueMean, color = "SampleMean")) +
  scale_colour_manual(values = c("red", "blue")) +
  labs(title = "Plot showing convergens of Mean",
       x = "Index",
       y = "Mean",
       color = NULL) +
  theme_minimal()

查看可用于geom_point更好可视化的原始数据（还添加了一些主题更改）：

ggplot() +
  geom_point(aes(count, mean, color = "Observed"), myDf,
             alpha = 0.3, size = 0.7) +
  geom_hline(aes(yintercept = myTrueMean, color = "Expected"),
             linetype = 2, size = 0.5) +
  scale_colour_manual(values = c("blue", "red")) +
  labs(title = "Plot showing convergens of Mean",
       x = "Index",
       y = "Mean",
       color = "Mean type") +
  theme_minimal() +
  guides(color = guide_legend(override.aes = list(
    linetype = 0, size = 4, shape = 15, alpha = 1))
  )