How to assign from a function which returns more than one value?

Question

(1) list[...]<- I had posted this over a decade ago on r-help. Since then it has been added to the gsubfn package. It does not require a special operator but does require that the left hand side be written using list[...] like this:

library(gsubfn)  # need 0.7-0 or later
list[a, b] <- functionReturningTwoValues()

If you only need the first or second component these all work too:

list[a] <- functionReturningTwoValues()
list[a, ] <- functionReturningTwoValues()
list[, b] <- functionReturningTwoValues()

(Of course, if you only needed one value then functionReturningTwoValues()[[1]] or functionReturningTwoValues()[[2]] would be sufficient.)

See the cited r-help thread for more examples.

(2) with If the intent is merely to combine the multiple values subsequently and the return values are named then a simple alternative is to use with :

myfun <- function() list(a = 1, b = 2)

list[a, b] <- myfun()
a + b

# same
with(myfun(), a + b)

(3) attach Another alternative is attach:

attach(myfun())
a + b

ADDED: with and attach

I somehow stumbled on this clever hack on the internet ... I'm not sure if it's nasty or beautiful, but it lets you create a "magical" operator that allows you to unpack multiple return values into their own variable. The := function is defined here, and included below for posterity:

':=' <- function(lhs, rhs) {
  frame <- parent.frame()
  lhs <- as.list(substitute(lhs))
  if (length(lhs) > 1)
    lhs <- lhs[-1]
  if (length(lhs) == 1) {
    do.call(`=`, list(lhs[[1]], rhs), envir=frame)
    return(invisible(NULL)) 
  }
  if (is.function(rhs) || is(rhs, 'formula'))
    rhs <- list(rhs)
  if (length(lhs) > length(rhs))
    rhs <- c(rhs, rep(list(NULL), length(lhs) - length(rhs)))
  for (i in 1:length(lhs))
    do.call(`=`, list(lhs[[i]], rhs[[i]]), envir=frame)
  return(invisible(NULL)) 
}

With that in hand, you can do what you're after:

functionReturningTwoValues <- function() {
  return(list(1, matrix(0, 2, 2)))
}
c(a, b) := functionReturningTwoValues()
a
#[1] 1
b
#     [,1] [,2]
# [1,]    0    0
# [2,]    0    0

I don't know how I feel about that. Perhaps you might find it helpful in your interactive workspace. Using it to build (re-)usable libraries (for mass consumption) might not be the best idea, but I guess that's up to you.

... you know what they say about responsibility and power ...

Usually I wrap the output into a list, which is very flexible (you can have any combination of numbers, strings, vectors, matrices, arrays, lists, objects int he output)

so like:

func2<-function(input) {
   a<-input+1
   b<-input+2
   output<-list(a,b)
   return(output)
}

output<-func2(5)

for (i in output) {
   print(i)
}

[1] 6
[1] 7

I put together an R package zeallot to tackle this problem. zeallot includes a multiple assignment or unpacking assignment operator, %<-%. The LHS of the operator is any number of variables to assign, built using calls to c(). The RHS of the operator is a vector, list, data frame, date object, or any custom object with an implemented destructure method (see ?zeallot::destructure).

Here are a handful of examples based on the original post,

library(zeallot)

functionReturningTwoValues <- function() { 
  return(c(1, 2)) 
}

c(a, b) %<-% functionReturningTwoValues()
a  # 1
b  # 2

functionReturningListOfValues <- function() {
  return(list(1, 2, 3))
}

c(d, e, f) %<-% functionReturningListOfValues()
d  # 1
e  # 2
f  # 3

functionReturningNestedList <- function() {
  return(list(1, list(2, 3)))
}

c(f, c(g, h)) %<-% functionReturningNestedList()
f  # 1
g  # 2
h  # 3

functionReturningTooManyValues <- function() {
  return(as.list(1:20))
}

c(i, j, ...rest) %<-% functionReturningTooManyValues()
i     # 1
j     # 2
rest  # list(3, 4, 5, ..)

Check out the package vignette for more information and examples.

functionReturningTwoValues <- function() { 
  results <- list()
  results$first <- 1
  results$second <-2
  return(results) 
}
a <- functionReturningTwoValues()

I think this works.

There's no right answer to this question. I really depends on what you're doing with the data. In the simple example above, I would strongly suggest:

1. Keep things as simple as possible.
2. Wherever possible, it's a best practice to keep your functions vectorized. That provides the greatest amount of flexibility and speed in the long run.

Is it important that the values 1 and 2 above have names? In other words, why is it important in this example that 1 and 2 be named a and b, rather than just r[1] and r[2]? One important thing to understand in this context is that a and b are also both vectors of length 1. So you're not really changing anything in the process of making that assignment, other than having 2 new vectors that don't need subscripts to be referenced:

> r <- c(1,2)
> a <- r[1]
> b <- r[2]
> class(r)
[1] "numeric"
> class(a)
[1] "numeric"
> a
[1] 1
> a[1]
[1] 1

You can also assign the names to the original vector if you would rather reference the letter than the index:

> names(r) <- c("a","b")
> names(r)
[1] "a" "b"
> r["a"]
a 
1 

[Edit] Given that you will be applying min and max to each vector separately, I would suggest either using a matrix (if a and b will be the same length and the same data type) or data frame (if a and b will be the same length but can be different data types) or else use a list like in your last example (if they can be of differing lengths and data types).

> r <- data.frame(a=1:4, b=5:8)
> r
  a b
1 1 5
2 2 6
3 3 7
4 4 8
> min(r$a)
[1] 1
> max(r$b)
[1] 8

Lists seem perfect for this purpose. For example within the function you would have

x = desired_return_value_1 # (vector, matrix, etc)

y = desired_return_value_2 # (vector, matrix, etc)

returnlist = list(x,y...)

}  # end of function

main program

x = returnlist[[1]]

y = returnlist[[2]]