[R-sig-Geo] Faster way to get raster average?

[Robert J. Hijmans]

This suggest that most of the time is spend on reading data from disk.
It could be more efficient to do this in one step.

m <- .colMeans(getValues(cmip), nrow(cmip), ncol(cmip), na.rm=FALSE)

I do not think there is much more you can do beyond that --- although
a solid state hard disk could help.

( I am guessing that na.rm=FALSE is tiny bit faster, and that you do
not need it to be TRUE. )

Robert

On Tue, May 5, 2015 at 6:48 PM, Thiago V. dos Santos
<thi_veloso at yahoo.com.br> wrote:
> Hi all,
> I am working with some terabytes of CMIP5 climate files. Each file is a netcdf with multiple layers (timesteps) representing monthly data.
> For each file, I need to extract the average value of the raster and put all values in a data frame. This is my current approach:---------------
> library(raster)
> # make up some datacmip <- brick(nc=150, nr=114, nl=1872)cmip <- setValues(cmip, matrix(rep(1:17100, 1872), nc=1872))
> # get mean values (area average) as data framescmip.mean <- as.data.frame(cellStats(cmip, mean, na.rm=T))---------------
> which works pretty fast in this example:
>> system.time(as.data.frame(cellStats(cmip, mean, na.rm=T)))
>    user  system elapsed
>   0.069   0.012   0.081
> However, the calculation with my actual data is substantially slower:
>> system.time(as.data.frame(cellStats(cmip, mean, na.rm=T)))
>    user  system elapsed
>   4.600   1.105   5.704
> Since I will have to deal with thousands of files, here comes my question: is there a faster way to get a the average value of a raster ?
> Many thanks,
> --
> Thiago V. dos Santos
> PhD student
> Land and Atmospheric Science
> University of Minnesota
> http://www.laas.umn.edu/CurrentStudents/MeettheStudents/ThiagodosSantos/index.htm
> Phone: (612) 323 9898
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>
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