Faster way to get raster average?

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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