I've found the need to compute a version of order(x,y)
where I want the sort order
for *increasing* x and *decresing* y ...
something we could imagine could be provided in the future as
order(x,y, decreasing = c(FALSE, TRUE))
i.e., using a 'vectorized' decreasing argument.
{No, I'm not volunteering right now!}
I've found the following R-level solution and
like to quiz you for more elegant / faster solutions
{but I am not really interested in replacing
order(x) by sort.list(x, method="quick") and similar things;
one thing to consider *is* using an 'na.last = . ' correctly,
and I haven't had the need for that and so not bothered to "do it"}
## Here's a script with my version and a small example
## (if you want speed comparisons, use larger examples) :
orderXuYd <- function(x,y)
{
## Purpose: order(x,y): x up, y down
## ----------------------------------------------------------------------
## Arguments: x,y: vectors of the same length
## ----------------------------------------------------------------------
## Author: Martin Maechler, Date: 21 Aug 2008
ix <- order(x)
xx <- x[ix]
iy <- tapply(y[ix], xx, order, decreasing = TRUE)
## Note: 'SIMPLIFY', 'USE.NAMES', 'use.names' are just for efficiency:
unlist(mapply(`[`, split(ix,xx), iy,
SIMPLIFY = FALSE, USE.NAMES = FALSE),
use.names = FALSE)
}
x <- c(1, 1, 2, 0, 0, 2, 1, 2, 2, 0, 2)
y <- c(27, 21, 45, 11, 13, 58, 35, 74, 95, 16, 122)
ii <- orderXuYd(x,y)
## yes, this is it :
cbind(ii=ii, x=x[ii],y=y[ii])
------------------
Yes, the real reason this goes to R-devel is that it might be
neat to provide this (well, its generalization) via an enhanced
order() function.
Martin Maechler, ETH Zurich
PS: I will be basically offline all day tomorrow, so don't
expect my reactions to your ideas quickly
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