Advice on long for loop

I think something like the following will let you do the thing you want in R:
vec1 <- 1:10
vec2 <- 2:11
vec3 <- 3:12
fun <- function(x){
+ vec1[x] * vec2[x] * vec3[x] #whatever
+ }
tt <- lapply(1:10, fun)

From: Agustin Lobo <alobo at ija.csic.es>
To: r-help <r-help at stat.math.ethz.ch>
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Subject: [R] Advice on long for loop
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X-Original-Date: Fri, 13 Dec 2002 15:22:22 +0100 (MET)
Date: Fri, 13 Dec 2002 15:22:22 +0100 (MET)

I'd appreciate advice on the following:

I've written an R function
that uses 3 vectors (temperature,
precipitation and potential evapotranspiration)
for a given site, calculates a water budget
(which implies few (<4) iterations), and, from
thresults of this water budget, calculates a number of
bioclimatic indices.

Now I want to calculate these indices
for a large number of sites (arranged
as cells in a raster map),  using
monthly raster maps (m rows x n cols)  of temperature,
precipitation and potential evapotranspiration.

I do not see any other way than using
two nested for loops and calling the
aforementioned function for each cell in the
map. But this would be a problem in R
as m and n can be ~ 500.

My question is: would it be any better if
I write a simple python function with the loops
and call the R function for each cell (using
the R-Python interface)? Or, as the calculation
in each cell is independent, should I rather write a
shell script with the loop and submit jobs
with R CMD BATCH?

Thanks

Agus

Dr. Agustin Lobo
Instituto de Ciencias de la Tierra (CSIC)
Lluis Sole Sabaris s/n
08028 Barcelona SPAIN
tel 34 93409 5410
fax 34 93411 0012
alobo at ija.csic.es

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