On 09/10/2011 08:08 AM, André Rossi wrote:
Hi everybody!
I'm creating an object of a S4 class that has two slots: ListExamples, which
is a list, and idx, which is an integer (as the code below).
Then, I read a data.frame file with 10000 (ten thousands) of lines and 10
columns, do some pre-processing and, basically, I store each line as an
element of a list in the slot ListExamples of the S4 object. However, many
operations after this take a considerable time.
Can anyone explain me why dois it happen? Is it possible to speed up an
script that deals with a big number of data (it might be data.frame or
list)?
Thank you,
André Rossi
setClass("Buffer",
representation=representation(
Listexamples = "list",
idx = "integer"
)
)
Hi André,
Can you provide a simpler and more reproducible example, for instance
> setClass("Buf", representation=representation(lst="list"))
[1] "Buf"
> b=new("Buf", lst=replicate(10000, list(10), simplify=FALSE))
> system.time({ b@lst[[1]][[1]] = 2 })
user system elapsed
0.005 0.000 0.005
Generally it sounds like you're modeling the rows as elements of
Listofelements, but you're better served by modeling the columns (lst =
replicate(10, integer(10000)), if all of your 10 columns were
integer-valued, for instance). Also, S4 is providing some measure of
type safety, and you're undermining that by having your class contain a
'list'. I'd go after
setClass("Buffer",
representation=representation(
col1="integer",
col2="character",
col3="numeric"
## etc.
),
validity=function(object) {
nms <- slotNames(object)
len <- sapply(nms, function(nm) length(slot(object, nm)))
if (1L != length(unique(len)))
"slots must all be of same length"
else TRUE
})
Buffer <-
function(col1, col2, col3, ...)
{
new("Buffer", col1=col1, col2=col2, col3=col3, ...)
}
Let's see where the inefficiencies are before deciding that this is an
S4 issue.
Martin
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
--
Computational Biology
Fred Hutchinson Cancer Research Center
1100 Fairview Ave. N. PO Box 19024 Seattle, WA 98109
Location: M1-B861
Telephone: 206 667-2793
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
