波浪号运算符可以用于构建匿名函数的通用性是什么? [英] With which generality can tilde operator be used to build anonymous functions?

问题描述

在诸如 dplyr::mutate_at 或 purrr::map 的一些函数中，它似乎可以使用波浪号运算符~来构建匿名函数.

Inside some functions as dplyr::mutate_at or purrr::map, it seems that one can use tilde operator ~ to build anonymous functions.

例如，您可以按照链接的问题进行操作:map(iris, ~length(unique(.)))

For example, one can do as in the linked question: map(iris, ~length(unique(.)))

或者:mtcars %>% mutate_all(~.*2)

我试图在 sapply 中模仿这个，以避免 sapply(list, function(item) {something_with_item}).我正在编写 sapply(list, ~ something_with_.) 但我收到一个错误

I tried to imitate this inside sapply, to avoid sapply(list, function(item) {something_with_item}). I was writing sapply(list, ~ something_with_.) but I get an error

Error in match.fun(FUN) : 
  '~ something_with_.' is not a function, character or symbol

一个可重现的例子:

> sapply(names(mtcars),function(item) mean(mtcars[[item]]))
       mpg        cyl       disp         hp       drat         wt       qsec 
 20.090625   6.187500 230.721875 146.687500   3.596563   3.217250  17.848750 
        vs         am       gear       carb 
  0.437500   0.406250   3.687500   2.812500 
> sapply(names(mtcars),~mean(mtcars[[.]]))
Error in match.fun(FUN) : 
  '~mean(mtcars[[.]])' is not a function, character or symbol

为什么?将此语法理解为函数只是某些包的行为，例如dplyr 和purrr?对于某些特殊情况，它是否可以被基本的 R 理解?

Why? Understanding this syntaxis as a function is just a behaviour of some packages as dplyr and purrr? Is it understood by base R for some special cases?

谢谢！

推荐答案

正如上面 caldwellst 所说的，tilda ~ 用于创建一个公式对象，这是一个有点未评估的代码，可以以后用.公式与函数不同，purrr 函数与公式一起工作，因为它们调用 rlang::as_function(通过 purrr::as_mapper代码>)在后台.*apply 函数显然不会这样做，尽管您可以通过在自己修改的 *apply 函数中调用上述函数之一来模仿这种行为(最好只是使用map函数，以下只是为了说明问题):

As caldwellst says above, the tilda ~ is used to create a formula object, which is a bit of unevaluated code that can be used later. Formulae are not the same as functions, and the purrr functions work with formulae because they make a call to rlang::as_function (via purrr::as_mapper) in the background. The *apply functions obviously don't do this, though you can imitate this behavior by calling one of the above functions in your own modified *apply function (it's better to just use the map functions, the following is just to illustrate the point):

# Write function with `as_mapper()`.
fapply <- function(x, func) {
    sapply(x, purrr::as_mapper(func))
}

# Now we can use formulae.
fapply(names(mtcars), ~ mean(mtcars[[.]]))

#### OUTPUT ####

       mpg        cyl       disp         hp       drat         wt       qsec         vs         am       gear       carb 
 20.090625   6.187500 230.721875 146.687500   3.596563   3.217250  17.848750   0.437500   0.406250   3.687500   2.812500 

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