[R-sig-Geo] Automate the extraction of climate variable at different time depths from netcdf in r
Robert J. Hijmans
r.hijmans at gmail.com
Thu Sep 11 18:47:11 CEST 2014
I doubt you will need to "delete one-by-one, the values for the years
that I do not desire". There surely are basic R tricks for that.
Perhaps the below example can get you there:
## example data
b <- brick(system.file("external/rlogo.grd", package="raster"))
p <- xyFromCell(b, sample(ncell(b), 10))
y <- cbind(y1=sample(0:1, 10, replace=TRUE), y2=sample(0:1, 10,
replace=TRUE), y3=sample(0:1, 10, replace=TRUE))
# extract all
e <- extract(b, p)
# combine data
x <- data.frame(x=p[,1], y=p[,2], year=rep(1:3, each=nrow(p)),
# select values you want
Whether the above works for you really depends on how you need to get
the values for further processing.
On Sun, Sep 7, 2014 at 8:58 AM, Barnabas Daru <darunabas at gmail.com> wrote:
> Hi Robert,
> Thanks very much for your suggestion.
> I tried the code you provided and it work! Many thanks.
> However, it tends to extract the SST values for all the points and for time
> periods including even the years that I don't desire. This means I will have
> to delete one-by-one, the values for the years that I do not desire and keep
> only the ones I want.
> I thought there is a way I could simply ask R to print in one column, the
> extracted values associated with only the years for which point data is
> Thanks and kind regards
> /---/ Barnabas Daru
> |--/ PhD Candidate,
> \-/ African Centre for DNA Barcoding,
> /\ University of Johannesburg,
> /--\ PO Box 524, Auckland Park, 2006,
> |---\ Johannesburg, South Africa.
> \---\ Lab: +27 11 559 3477
> \--| Mobile: +277 3818 9583
> \-/ Website: www.barnabasdaru.com
> #…if you can think it, you can do it.
> On Sep 7, 2014, at 5:23 AM, Robert J. Hijmans wrote:
> Barnabas, ,
> You can try something like this:
> b <- brick("~sst.mnmean.nc", varname="sst")
> # loop over species, or combine all species into one data.frame?
> mydata <- read.csv("~Species one.csv")
> extract.mydata <- extract(b, mydata[,5:6])
> write.csv(extract.mydata, file = "Species_one_extracted.csv")
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