[R-sig-Geo] polygonValues (raster): Very slow
alobolistas at gmail.com
Wed Jun 30 19:08:20 CEST 2010
The info looks interesting, as it claims to be a fast algorithm with
support for large files.
Unfortunately, it seems that the package cannot be downloaded any
more. At least the provided
link brings you to an empty space, files seem not to be in the casil.ucdavis.edu
any more and you end up in projects.atlas.ca.gov, where I've not been able
to find the files.
2010/6/30 Nikhil Kaza <nikhil.list at gmail.com>:
> This is not an R solution and I am not even sure if this speeds up your
> process. But in the past I have used starspan for this kind of work. It
> worked fairly well for me for large datasets. But it was a one off process
> that I didn't mind spending couple of hours. I also did a naive
> parallelization by breaking up the polygon files multiple parts and then
> assembling them back, but if you really need the accurate proportion of
> cell area of a cell that falls across two polygons, this strategy wont work.
> Nikhil Kaza
> Asst. Professor,
> City and Regional Planning
> University of North Carolina
> nikhil.list at gmail.com
> On Jun 30, 2010, at 10:12 AM, Agustin Lobo wrote:
>> I'm trying:
>>> eugrd025EFDC <- readOGR(dsn="eugrd025EFDC",layer="eugrd025EFDC")
>> v <- polygonValues(p=eugrd025EFDC, Br, weights=TRUE)
>> Formal class 'SpatialPolygonsDataFrame' [package "sp"] with 5 slots
>> ..@ data :'data.frame': 18000 obs. of 5 variables:
>> ..@ polygons :List of 18000
>> .. .. [list output truncated]
>> ..@ plotOrder : int [1:18000] 17901 17900 17902 17903 17899 17898
>> 17904 17897 17905 17906 ...
>> ..@ bbox : num [1:2, 1:2] 2484331 1314148 6575852 4328780
>> .. ..- attr(*, "dimnames")=List of 2
>> ..@ proj4string:Formal class 'CRS' [package "sp"] with 1 slots
>> Cells: 13967442
>> NAs : 0
>> Min. 0.00
>> 1st Qu. 0.00
>> Median 0.00
>> Mean 48.82
>> 3rd Qu. 0.00
>> Max. 4999.00
>> so quite large objects.
>> The problem is that polygonValues() has been running (and not
>> completed the task) for
>> more than 2 h on a intel core i7 machine with 16 Gb RAM (Dell
>> Precision M6500), so a pretty powerful machine.
>> Is there any way I could speed up this process?
>> Also, is there anything I could do in order to take better advantage
>> of the 8 processing threads?
>> Currently, I see only 1 cpu working for R processes and the rest
>> remain pretty inactive
>> R-sig-Geo mailing list
>> R-sig-Geo at stat.math.ethz.ch
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