[R] spped up a function

[Jim Holtman]

first thing to do when trying to speed up a function is to see where it is spending its time.  take a subset of the data and use Rprof to profile the code.  my guess is that a lot of time is taken up in the use of dataframes.  see if you can use matrices instead.

Sent from my iPad

On Jul 2, 2013, at 13:47, Santiago Guallar <sguallar at yahoo.com> wrote:

> Hi,
> 
> I have written a function to assign the values of a certain variable 'wd' from a dataset to another dataset. Both contain data from the same time period but differ in the length of their time intervals: 'GPS' has regular 10-minute intervals whereas 'xact' has irregular intervals. I attached simplified text versions from write.table. You can also get a dput of 'xact' in this address: http://www.megafileupload.com/en/file/431569/xact-dput.html).
> The original objects are large and the function takes almost one hour to finish.
> Here's the function:
> 
> fxG= function(xact, GPS){
> l <- rep( 'A', nrow(GPS) )
> v <- unique(GPS$Ring) # the process is carried out for several individuals identified by 'Ring'
> for(k in 1:length(v) ){
> I = v[k]
> df <- xact[xact$Ring == I,]
> for(i in 1:nrow(GPS)){
> if(GPS[i,]$Ring== I){# the code runs along the whole data.frame for each i; it'd save time to make it stop with the last record of each i instead
> u <- df$timepos <= GPS[i,]$timepos
> # fill vector l for each interval t from xact <= each interval from GPS (take the max if there's > 1 interval)
> l[i] <- df[max( which(u == TRUE) ),]$wd
> }
> }
> }
> return(l)}
> 
> vwd <- fxG(xact, GPS)
> 
> 
> My question is: how can I speed up (optimize) this function?
> 
> Thank you for your help
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