functional programming - higher level functions in R - is there an official compose operator or curry function?

Question

I can create a compose operator in R:

 `%c%` = function(x,y)function(...)x(y(...)) 

To be used like this:

 > numericNull = is.null %c% numeric
 > numericNull(myVec)
 [2] TRUE FALSE

but I would like to know if there is an official set of functions to do this kind of thing and other operations such as currying in R. Largely this is to reduce the number of brackets, function keywords etc in my code.

My curry function:

> curry=function(...){
    z1=z0=substitute(...);z1[1]=call("list");
    function(...){do.call(as.character(z0[[1]]),
                          as.list(c(eval(z1),list(...))))}}
> p = curry(paste(collapse=""))
> p(letters[1:10])
[1] "abcdefghij"

This is especially nice for e.g. aggregate:

> df = data.frame(l=sample(1:3,10,rep=TRUE), t=letters[1:10])
> aggregate(df$t,df["l"],curry(paste(collapse="")) %c% toupper)
  l    x
1 1  ADG
2 2  BCH
3 3 EFIJ

Which I find much more elegant and editable than:

> aggregate(df$t, df["l"], function(x)paste(collapse="",toupper(x)))
  l    x
1 1  ADG
2 2  BCH
3 3 EFIJ

Basically I want to know - has this already been done for R?

Answer 1

Both of these functions actually exist in the roxygen package (see the source code here) from Peter Danenberg (was originally based on Byron Ellis's solution on R-Help):

Curry <- function(FUN,...) {
  .orig = list(...);
  function(...) do.call(FUN,c(.orig,list(...)))
}

Compose <- function(...) {
  fs <- list(...)
  function(...) Reduce(function(x, f) f(x),
                       fs,
                       ...)
}

Note the usage of the Reduce function, which can be very helpful when trying to do functional programming in R. See ?Reduce for more details (which also covers other functions such as Map and Filter).

And your example of Curry (slightly different in this usage):

> library(roxygen)
> p <- Curry(paste, collapse="")
> p(letters[1:10])
[1] "abcdefghij"

Here's an example to show the utility of Compose (applying three different functions to letters):

> Compose(function(x) x[length(x):1], Curry(paste, collapse=""), toupper)(letters)
[1] "ZYXWVUTSRQPONMLKJIHGFEDCBA"

And your final example would work like this:

> aggregate(df[,"t"], df["l"], Compose(Curry(paste, collapse=""), toupper))
  l    x
1 1  ABG
2 2 DEFH
3 3  CIJ

Lastly, here's a way to do the same thing with plyr (could also easily be done with by or aggregate as already shown):

> library(plyr)
> ddply(df, .(l), function(df) paste(toupper(df[,"t"]), collapse=""))
  l   V1
1 1  ABG
2 2 DEFH
3 3  CIJ