使用ggplot stat_function"group"在自定义函数中

问题描述

如果您阅读ggplot的stat_function 帮助，则可以看到:

If you read ggplot's stat_function help, you can see that :

• 组
• y

但是没有如何使用它的示例.

But there is no example on how to use it.

就我而言，我想访问自定义函数中的组" ae.这是我不幸的尝试(只能绘制一条曲线，而不是每组绘制1条曲线):

In my case, I want to access the "group" aes inside a custom function. Here is my unfortunate try (which only plot one curve, not 1 per group):

df = data.frame(A=1:10, B=rep(seq(1,1.8,by=0.2), 2),
                myGroup=c(rep("Group1", 5), rep("Group2", 5)))

log.test = function(x, data, ...) {
  y = log(data$A + x*data$B)
  return(y)
}

ggplot(df) +
  xlim(0,50) + ylim(0,50) +
  labs(x="time", y="Y", color="Group") +
  stat_function(aes(group=myGroup), fun=log.test, args=list(data=df))

奇怪的是，我无法使调试器在log.test中运行，所以我不知道哪个变量可用.

Something odd is that I cannot get the debugger to work inside log.test, so I don't know which variable is available.

请注意，这将与geom_abline(aes(intercept=A,slope=B,color=myGroup))(而不是stat_function(...))完美配合.

Note that this would work perfectly with geom_abline(aes(intercept=A,slope=B,color=myGroup)) instead of stat_function(...).

我在这里可能有一个很大的误解，但我找不到它.

I may have a big misunderstanding here, but I cannot manage to find it.

推荐答案

尝试一下:

df = data.frame(A=1:10, B=rep(seq(1,1.8,by=0.2), 2),
                myGroup=c(rep("Group1", 5), rep("Group2", 5))) #you don't even need to define df here because you're passing all the arguments inside mapply

log.test = function(x,A,B) {
  y = log(A + x*B)
  return(y)
}

ggplot(data.frame(x = c(0, 50)), aes(x)) +
  mapply(function(A, B, myGroup) {
    stat_function(fun = log.test, args = list(A = A, B = B), col = myGroup)
  },
  # enter A, B, and colors here
  A = c(0, 10),
  B=rep(seq(1,1.8,by=0.2), 2),
  myGroup=c(rep("red", 5), rep("green", 5)))

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