[R] recursive relevel

[baptiste auguie]

Dear list,

I'm having second thoughts after solving a very trivial problem: I  
want to extend the relevel() function to reorder an arbitrary number  
of levels of a factor in one go. I could not find a trivial way of  
using the code obtained by getS3method("relevel","factor"). Instead, I  
thought of solving the problem in a recursive manner (possibly after  
reading Paul Graham essays on Lisp too recently). Here is my attempt :

>
> order.factor <- function (x, ref)
> 	{
> 		
> 	last.index <- length(ref) # convenience for matlab's end keyword
> 	if(last.index == 1) return(relevel(x, ref)) # end case, normal case  
> of relevel
> 	my.new.list <- list(x=relevel(x, ref[last.index]),  # creating a  
> list with updated parameters,
> 														# going through the list in reverse order
> 							ref=ref[-last.index]) # chop the vector from its last level
> 	return(do.call(order.factor, my.new.list)) # recursive call
> }
>
> ff <- factor(c("a", "b", "c", "d"))
> ff
> relevel(ff, levels(ff)[1])
> relevel(ff, levels(ff)[2]) # that's the usual case: you want to put  
> a level first
>
> order.factor(x=ff, ref=c("a", "b"))
> order.factor(x=ff, ref=c("c"))
> order.factor(x=ff, ref=c("c", "d")) # that's my wish: put c and d in  
> that order as the first two levels
>


I'm hoping this can be improved in several aspects:

- there is probably already a better function I missed or overlooked  
(I'd still be curious about the following points, though)

- after reading a few threads, it appears that some recursive  
functions are fragile in some sense, and I'm not sure what this means  
in practice. (Should I use Recall, somehow?)

- it's probably quite slow for large data.frames

- I could not think of a good name, this one might clash with some S3  
method perhaps?

- any other thoughts welcome!


Best wishes,

Baptiste
_____________________________

Baptiste Auguié

School of Physics
University of Exeter
Stocker Road,
Exeter, Devon,
EX4 4QL, UK

Phone: +44 1392 264187

http://newton.ex.ac.uk/research/emag