Dear Patrick, Thank you for the link - I'd advise anyone who's started using R to have a look at these as well - any help is always appreciated. I've downloaded the S Poetry and will hit the books tomorrow and get reading it! Jenny
S Poetry may be of use to you -- especially the chapter on arrays which discusses 3 dimensional arrays in particular. Patrick Burns patrick at burns-stat.com +44 (0)20 8525 0696 http://www.burns-stat.com (home of S Poetry and "A Guide for the Unwilling S User") Jenny Barnes wrote:
Dear R-help, I forgot to mention that I need the array in that format because I am going to do the same thing for another dataset of precipitation (ncep.data2) so they
are
both arrays of dimensions [144,72,46] so that I can correlate them globally
and
plot a visual image of the global correlations between the 2 datasets.... One
of
the datasets has a land mask applied to it already so it should be clear to
see
the land and pick ot the locations (i.e.over Europe) where there is strongest and weakest correlation.....that is the ultimate goal. Following Rainer's response I should also point out that the columns in gpcc.data2 (with dimensions dim(gpcc.data2) = [476928,5]) are: [,1]="Year", [,2]="month" (which is just january so always 1),
[,3]="latitude",
[,4]="longitude" and [,5]="data". All I want in the gpcc.array is the data not the longitudes and latitude values...hope that helps clear it up a bit! I look forward to hearing any more ideas, thanks again for your time in
reading
this, Jenny Barnes
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
______________________________________________ R-help at stat.math.ethz.ch 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.
--
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)
Cell: +27 - (0)83 9479 042
email: RKrug at sun.ac.za
Rainer at krugs.de
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 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
______________________________________________ R-help at stat.math.ethz.ch 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.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 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