Passing multiple arguments to Reduce - r

Question

I have a list of data.frames, and would like to operate on their columns, using various weights.
For example, subtracting the first columns from the second column (solved, see below); or subtracting the first and third from twice the second (unsolved).
Thanks to the generous help obtained in response to this question, I have a solution to the the problem in two dimensions without weights using Reduce.
I would like to have the flexibility to operate with weights - and in higher dimesions.
What I have so far is:
priceList <- data.frame(aaa = rnorm(100, 100, 10), bbb = rnorm(100, 100, 10),
ccc = rnorm(100, 100, 10), ddd = rnorm(100, 100, 10),
eee = rnorm(100, 100, 10), fff = rnorm(100, 100, 10),
ggg = rnorm(100, 100, 10)
)
colDiff <- function(x)
{
Reduce('-', rev(x))
}
tradeLegsList <- combn(names(priceList), 3, function(x) priceList[x], simplify = FALSE)
tradeList <- lapply(tradeLegsList, colDiff)
From what I can tell, Reduce is not designed to take multiple arguments.
I can do this the long way with 2* tradeLegsList[[1]]$bbb - tradeLegsList[[1]]$aaa - tradeLegsList[[1]]$ccc, and some loops, but it doesn't seem like the R way.
Is there a way to pass in a weight vector?
Ideally, I would to pass an argument such as w = c(-1, 2, -1) to the colDiff (or Reduce) function ... or something similar.

Answer 1

True, Reduce is not geared to allow multiple arguments, just two for each reduction. Therefore it is easiest to premultiply the elements in the list you are Reduce-ing.
Below is a solution that does this using mapply within your colDiff function definition.
Change your definifion of colDiff to allow a weight vector, and apply this using mapply
with SIMPLIFY = F.
EDIT
In light of the comments, weighting depends on the number of columns and there being no need for the rev
The weighting by length
length(x) == 1 -> w = 1
length(x) == 2 -> w = c(-1, 1),
length(x) == 3 -> w = c(-1, 2, -1),
length(x) == 4 -> w = c(-1, 1, -1, +1)
weighting <- function(i){
switch(i, 1, c(-1,1), c(-1,2,-1), c(-1,1,-1, 1))
}
colDiff <- function(x)
{
w = weighting(length(x))
Reduce('+', mapply('*', x, e2 = w, SIMPLIFY = F))
}
Then something like this would work
tradeList <- lapply(tradeLegsList, colDiff)
you could also keep with the functional programming theme and use Map which is a simple wrapper for mapply with SIMPLIFY = F
colDiff <- function(x)
{
w = weighting(length(x))
Reduce('+', Map('*', x , e2 = w))
}
you could also prefine the weighting within the function colDiff (which may be easier).
weighting[[2]] is weighting for when there are 2 columns, weighting[[3]] when there are 3.
colDiff <- function(x)
{
weighting <- list(1, c(-1,1), c(-1,2,-1), c(-1,1,-1, 1))
w = weighting[[length(x)]]
Reduce('+', Map('*', x , e2 = w))
}