Because R can be interactive, I find that a little exploring through
the use of strategically placed browser() calls (?browser if you are
unfamiliar with this handy debugging tool) is often the fastest way to
solve little R puzzles like this.
For example, try this (in an R GUI):
f2 <- function(y,...){ browser(); list(...) }
f1 <- function(x,...){ browser(); f2(x,...) }
Now at the command line:
## In the f1 browser do ls() to see what's in the f1 environment
## and then do list(...) to see what's in the dots argument
## then issue the browser command c to continue
## and do the same in the f2 browser .
## then try:
f1( x=1, y= 2:4) ## and
f1( 2:4)
f1( y=2:4) ## this will produce an error in f2
I think this help give you a better idea of what's going on (or
totally confuse?!).
-- Bert
On Wed, Jan 30, 2013 at 8:15 AM, Patrick Burns <pburns at pburns.seanet.com> wrote:
Dear users,
I'm trying to learn how to use the "...".
I have written a function (simplified here) that uses doBy::summaryBy():
# 'dat' is a data.frame from which the aggregation is computed
# 'vec_cat' is a integer vector defining which columns of the data.frame
should be use on the right side of the formula
# 'stat_fun' is the function that will be run to aggregate
stat.group <- function(dat, vec_cat, stat_fun){
require(doBy)
df <-
summaryBy(as.formula(paste0(".~",paste0(names(dat)[vec_cat],collapse="+"))),
data=dat, FUN=stat_fun)
return(df)
}
Example, works fine:
my_data <- structure(list(cat = structure(c(1L, 1L, 1L, 1L, 1L, 2L, 2L,
2L, 2L, 2L), .Label = c("A", "B"), class = "factor"), varnum =
c(-0.754816565434373,
-1.94101630973709, -0.102461836059522, -0.519952759645808,
-1.73772800855664,
-1.13939178585609, 0.522356715260142, -0.701428514907824,
1.45197576541159,
0.0844567413828095)), .Names = c("cat", "varnum"), row.names = c(NA,
-10L), class = "data.frame")
stat.group(dat=my_data, vec_cat=1, stat_fun=mean)
Now summaryBy() has an "..." argument and I would like to use it.
For example, I would like to be able to add the trim argument to my call
like this:
stat.group(dat=my_data, vec_cat=1, stat_fun=mean, trim=0.2)
I know I can do it using this "..." but I have no idea how to do it.
I've tried to search for it, but a search with "..." doesn't yield
interesting results!
Thank you in advance for your help!
Ivan