On Nov 25, 2011, at 12:50 PM, Robin Corrià wrote:
Dear all,
I have a
big data frame:
str(data1)
'data.frame': 18272 obs. of 11 variables:
$ tag :
int 100001 100002 100003 100005 100007
100008 100009 100011 100012 100014 ...
$ sp :
Factor w/ 18 levels "acassp","acocar",..: 13 5 7 14 14 18 3
11 13 10 ...
$ gx :
num 20 10 35 68 88 63 123 115 137 136
...
$ gy :
num 30 25 24 1 10 40 45 25 23 45 ...
$ d0 :
int 0 0 0 0 0 0 0 0 0 0 ...
$ d1 :
int 395 395 395 395 395 395 395 395 395
395 ...
$ d2 :
int 751 751 751 751 751 751 751 751 751
751 ...
$ d3 :
int 1515 1515 1515 1515 1515 1515 1515
1515 1515 1515 ...
$ d4 :
int 2562 2562 2562 2562 2562 2562 2562
2562 2562 2562 ...
$ block: int
1 1 1 1 1 1 1 1 1 1 ...
$ treat: Factor w/ 4 levels
"I","M","N","T": 1 1 1 1 1 1 1 1 1 1
...
And I need to
do multiple selections of gx and gy for all the levels of: sp,
block, treat, and when d0!="NA". Then
calculate some spatial functions with the selected gx and gy
coordinates, and
save the results with a name according to the selection.
One single
selection could be done and named like that:
acocar1I=subset(data1,(treat=="I"
& data1$block==1 & data1$sp=="acocar" & data1$d0!="NA"))
You should watch out since that is not a valid test for NA. If the
values are NA rahter than "NA" you need to use !is.na()
You could set up a condition list which would really be a list of
logical vectors and then loop through it like this:
consList[[1]] <- with(data1, treat=="I"&
block==1 &
sp=="acocar" &
d0!="NA")
(Then add more vectors to the list.)
for (cond in condList) { sel.spp[[i]] <- with(
subset(data1,
condList[[i]]),
spp(x=gx, y=gy,
window=wA) )
acocar1I.dp[[i]] <-dval(sel.spp[[i]],
25,2.5,18,20)
}
(You could then assemble the various calculations in a dataframe. All
of this obviously untested.)
If you really are doing this for "all levels of sp, bloc, treat then
there might be further option in the plyr pkg or with aggregate since
they provide features for running through all existing combinations
using the interaction function. The `expand.grid` function is
sometimes useful for building data.frames as scaffolding to hold
repeated calculations.
--
David.
These are some
of the functions I have to calculate:
acocar1I.spp<-spp(x=acocar1I$gx,
y=acocar1I$gy, window=wA)
acocar1I.dp<-dval(acocar1I.spp,25,2.5,18,20)
And I want
to create a 'results' object to access easily all the results:
acocar1I.res<-alist()
acocar1I.res$data1<-acocar1I
acocar1I.res$spp<-acocar1I.spp
acocar1I.res$dp<-acocar1I.dp
Can I do everything
in a single loop or a single function?
Depends on specifics.
Many
thanks!
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David Winsemius, MD
West Hartford, CT
______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
