Split up `...` arguments and distribute to multiple functions - r

Question

Using the following function foo() as a simple example, I'd like to distribute the values given in ... two different functions, if possible.
foo <- function(x, y, ...) {
list(sum = sum(x, ...), grep = grep("abc", y, ...))
}
In the following example, I would like na.rm to be passed to sum(), and value to be passed to grep(). But I get an error for an unused argument in grep().
X <- c(1:5, NA, 6:10)
Y <- "xyzabcxyz"
foo(X, Y, na.rm = TRUE, value = TRUE)
# Error in grep("abc", y, ...) : unused argument (na.rm = TRUE)
It seems like the arguments were sent to grep() first. Is that correct? I would think R would see and evaluate sum() first, and return an error for that case.
Furthermore, when trying to split up the arguments in ..., I ran into trouble. sum()'s formal arguments are NULL because it is a .Primitive, and therefore I cannot use
names(formals(sum)) %in% names(list(...))
I also don't want to assume that the leftover arguments from
names(formals(grep)) %in% names(list(...))
are to automatically be passed to sum().
How can I safely and efficiently distribute ... arguments to multiple functions so that no unnecessary evaluations are made?
In the long-run, I'd like to be able to apply this to functions with a long list of ... arguments, similar to those of download.file() and scan().

Answer 1

Separate Lists If you really want to pass different sets of parameters to different functions then it's probably cleaner to specify separate lists:
foo <- function(x, y, sum = list(), grep = list()) {
list(sum = do.call("sum", c(x, sum)), grep = do.call("grep", c("abc", y, grep)))
}
# test
X <- c(1:5, NA, 6:10)
Y <- "xyzabcxyz"
foo(X, Y, sum = list(na.rm = TRUE), grep = list(value = TRUE))
## $sum
## [1] 55
##
## $grep
## [1] "xyzabcxyz"
Hybrid list / ... An alternative is that we could use ... for one of these and then specify the other as a list, particularly in the case that one of them is frequently used and the other is infrequently used. The frequently used one would be passed via ... and the infrequently used via a list. e.g.
foo <- function(x, y, sum = list(), ...) {
list(sum = do.call("sum", c(x, sum)), grep = grep("abc", y, ...))
}
foo(X, Y, sum = list(na.rm = TRUE), value = TRUE)
Here are a couple of examples of the hybrid approach from R itself:
i) The mapply function takes that approach using both ... and a MoreArgs list:
> args(mapply)
function (FUN, ..., MoreArgs = NULL, SIMPLIFY = TRUE, USE.NAMES = TRUE)
NULL
ii) nls also takes this approach using both ... and the control list:
> args(nls)
function (formula, data = parent.frame(), start, control = nls.control(),
algorithm = c("default", "plinear", "port"), trace = FALSE,
subset, weights, na.action, model = FALSE, lower = -Inf,
upper = Inf, ...)
NULL

Answer 2

Why does grep error before sum?
See that sum is a lot more accommodating with its arguments:
X <- c(1:5, NA, 6:10)
sum(X, na.rm = TRUE, value = TRUE)
## [1] 56
It doesn't failed because it doesn't care about other named arguments, so the value = TRUE simplifies to just TRUE which sums to 1. Incidentally:
sum(X, na.rm = TRUE)
## [1] 55
How to split ... to different functions?
One method (that is very prone to error) is to look for the args for the target functions. For instance:
foo <- function(x, y, ...){
argnames <- names(list(...))
sumargs <- intersect(argnames, names(as.list(args(sum))))
grepargs <- intersect(argnames, names(as.list(args(grep))))
list(sum = do.call(sum, c(list(x), list(...)[sumargs])),
grep = do.call(grep, c(list("abc", y), list(...)[grepargs])))
}
This is prone to error anytime the arguments a function uses are not properly reported by args, such as S3 objects. As an example:
names(as.list(args(plot)))
## [1] "x" "y" "..." ""
names(as.list(args(plot.default)))
## [1] "x" "y" "type" "xlim" "ylim"
## [6] "log" "main" "sub" "xlab" "ylab"
## [11] "ann" "axes" "frame.plot" "panel.first" "panel.last"
## [16] "asp" "..." ""
In this case, you could substitute the appropriate S3 function. Because of this, I don't have a generalized solution for this (though I don't know that it does or does not exist).

Answer 3

You can only pass the ... argument to another function, if that other function includes all named arguments that you pass to ... or if it has a ... argument itself. So for sum, this is no problem (args(sum) returns function (..., na.rm = FALSE)). On the other hand grep has neither na.rm nor ... as an argument.
args(grep)
# function (pattern, x, ignore.case = FALSE, perl = FALSE, value = FALSE,
# fixed = FALSE, useBytes = FALSE, invert = FALSE)
This does not include ... and also does not include a named argument na.rm either. A simple solution is to just define your own function mygrep as follows:
mygrep <- function (pattern, x, ignore.case = FALSE, perl = FALSE, value = FALSE,
fixed = FALSE, useBytes = FALSE, invert = FALSE, ...)
grep(pattern, x, ignore.case, perl, value, fixed, useBytes, invert)
Then it seems to work:
foo <- function(x, y, ...){
list(sum = sum(x, ...), grep = mygrep("abc", y, ...))
}
X <- c(1:5, NA, 6:10)
Y <- "xyzabcxyz"
foo(X, Y, na.rm = TRUE, value = TRUE)
# $sum
# [1] 56
#
# $grep
# [1] "xyzabcxyz"

Answer 4

This answer does not directly the original question but could be helpful to others who experience a similar problem with their own functions (as opposed to existing functions like sum and grep).
#shadow's answer contains an insight that points to a very simple solution in such cases: just make sure your nested functions have ... as an argument and you won't get the unused argument error.
For example:
nested1 <- function(x, a) {
x + a
}
nested2 <- function(x, b) {
x - b
}
f <- function(x, ...) {
if (x >= 0) {
nested1(x, ...)
} else {
nested2(x, ...)
}
}
If we call f(x = 2, a = 3, b = 4) we get an error: Error in nested1(x, ...) : unused argument (b = 4).
But just add a ... to the formals of nested1 and nested2 and run again:
nested1 <- function(x, a, ...) {
x + a
}
nested2 <- function(x, b, ...) {
x - b
}
Now, f(x = 2, a = 3, b = 4) yields the desired result: 5. Problem solved.