[R] Slow computation in for loop

[Peter Dalgaard BSA]

Yves Brostaux <brostaux.y at fsagx.ac.be> writes:

> Dear members,
> 
> I'm using R to do some test computation on a set of parameters of a
> function. This function is included in three for() loops, first one
> for replications, and the remaining two cycling through possible
> parameters values, like this :
> 
> for (k in replicates) {
>    data <- sampling from a population
>    for (i in param1) {
>      for (j in param2) {
>         result <- function(i, j, data)
>      }
>    }
> }
> 
> With the 'hardest' set of parameters, a single computation of the
> function take about 16s on an old Sun Sparc workstation with 64 Mb RAM
> and don't access a single time to disk.
> 
> But when I launch the for() loops (which generate 220 function calls),
> disk gets very sollicitated and the whole process takes as much as 8
> to 10 hours, instead of the expected 1 hour.
> 
> What's wrong here ? Is there a thing I don't know about for() loops,
> and a way to correct it ?

The problem with pseudocode: You didn't really overwrite the "result"
every time did you? I bet you stored it somewhere.

Two common causes of inefficiency are (a) that the stored objects may
be large and (b) some naive ways of storing the results involve
copying all preceding results, e.g.

list.of.results <- list()
for (.....){
     result <- ...
     list.of.results <- c(list.of.results, result)
}

The fix for (a) is to extract what you need and discard the rest
and for (b) to allocate the list up front with the proper length and
assign to list.of.results[[i]].

-- 
   O__  ---- Peter Dalgaard             Blegdamsvej 3  
  c/ /'_ --- Dept. of Biostatistics     2200 Cph. N   
 (*) \(*) -- University of Copenhagen   Denmark      Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk)             FAX: (+45) 35327907