loop is going to take 26 hours - needs to be quicker!

Jenny Barnes wrote:

Dear R-help,

I have a loop, which is set to take about 26 hours to run at the rate it's going
- this is ridiculous and I really need your help to find a more efficient way of
loading up my array gpcc.array:

#My data is stored in a table format with all the data in one long column
#running though every longitute, for every latitude, for every year. The
#original data is sotred as gpcc.data2 where dim(gpcc.data2) = [476928,5] where
#the 5th column is the data:

#make the array in the format I need [longitude,latitude,years]

gpcc.array <- array(NA, c(144,72,46))

n=0
for(k in 1:46){
for(j in 1:72){
for(i in 1:144){
n <- n+1
gpcc.array[i,j,k] <- gpcc.data2[n,5]
print(j)
}
}
}

I don't know if it is faster - but adding three columns to qpcc.data,
one for longitude, one for lattitude and one for year (using rep() as
they are in sequence) and the using reshape() might be faster?

So it runs through all the longs for every lat for every year - which is the
order the data is running down the column in gpcc.data2 so n increses by 1 each
time and each data point is pulled off....

It needs to be a lot quicker, I'd appreciate any ideas!

Many thanks for taking time to read this,

Jenny Barnes

~~~~~~~~~~~~~~~~~~
Jennifer Barnes
PhD student - long range drought prediction
Climate Extremes
Department of Space and Climate Physics
University College London
Holmbury St Mary, Dorking
Surrey
RH5 6NT
01483 204149
07916 139187
Web: http://climate.mssl.ucl.ac.uk

--
Rainer M. Krug, Dipl. Phys. (Germany), MSc Conservation
Biology (UCT)

Department of Conservation Ecology and Entomology
University of Stellenbosch
Matieland 7602
South Africa

Tel:            +27 - (0)72 808 2975 (w)
Fax:            +27 - (0)86 516 2782
Fax:            +27 - (0)21 808 3304 (w)
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email:  RKrug at sun.ac.za
        Rainer at krugs.de