Hi Robert, Thank you very much for the code. It works. Thanks and kind regards Barnabas Daru \-/ /\ /--| /---/ 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 11, 2014, at 6:47 PM, Robert J. Hijmans wrote:
Barnabas,
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
#raster
b <- brick(system.file("external/rlogo.grd", package="raster"))
# points
set.seed(0)
p <- xyFromCell(b, sample(ncell(b), 10))
# "years"
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)),
include=as.vector(y), value=as.vector(e))
# select values you want
x[x$include==1, ]
Whether the above works for you really depends on how you need to get
the values for further processing.
Robert
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
available.
Thanks and kind regards
Barnabas
\-/
/\
/--|
/---/ 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")
Robert