Hello Christian:
Yes indeed, my experience is that Raster package operations on very
large datasets take a long time,
on either Linux or Windows desktops.
As an alternative to the Raster package, I have had good experience
using the GDAL raster image utilities,
embedded within shell or Python scripts to perform first-order raster
subsampling and subimage generation.
Check out the gdalinfo, gdal_translate, and gdalwarp utilities. I have
been using these to work with 100 gigabyte-class
raster DEM images, with great success and relatively low execution times
(considering the size of the data sets).
HTH,
Rick Reeves
NCEAS
On 7/1/2011 7:02 AM, Christian Kamenik wrote:
Dear all,
The package 'raster' provides excellent tools to work on geographic
data. Subsetting a RasterBrick object, however, takes ages.
I have the following RasterBrick object:
Temp.CRU.cropped
class: RasterBrick
filename:
dimensions: 43, 99, 1200 (nrow, ncol, nlayers)
ncell: 4257
projection: +proj=longlat +ellps=WGS84
min values: -14.8 -22.1 -15.0 -8.6 -3.8 4.7 8.7
6.0 1.6 -2.4 ...
max values: 2.1 -3.9 -2.1 1.8 6.6 15.7 18.0 14.8 10.7 7.7
...
extent: 15, 31.5, 64, 71.16667 (xmin, xmax, ymin,
ymax)
resolution: 0.1666667, 0.1666667 (x, y)
These are temperature readings from northern Fennoscandia, and each
layer represents a month, thus each grid cell has monthly readings
over the last 100 years.
Now I want to extract the readings for only July:
Months <- rep(month.abb,nlayers(Temp.CRU.cropped)/12)
Temp.CRU.J <- subset(Temp.CRU.cropped,which(Months=='Jul'))
But as I said, this takes ages. It is much faster to do the subsetting
on an array:
CRU.values <- getValues(Temp.CRU.cropped)
Temp.CRU.J <- CRU.values[,which(Months=='Jul')]
Temp.CRU.J <-
array(Temp.CRU.J,dim=c(nrow(Temp.CRU.cropped),ncol(Temp.CRU.cropped),nlayers(Temp.CRU.cropped)/12))
Temp.CRU.J <- brick(Temp.CRU.J)
Temp.CRU.J <- setExtent(Temp.CRU.J,extent(Temp.CRU.cropped))
projection(Temp.CRU.J) <- projection(Temp.CRU.cropped)
It is strange that several lines of code run much faster than the
'subset' command, and I was wondering why 'subset' takes at least a
1000 times longer.
I would be interested in your opinion.
Many thanks, Christian
_______________________________________________
R-sig-Geo mailing list
R-sig-Geo@r-project.org
https://stat.ethz.ch/mailman/listinfo/r-sig-geo