On May 19, 2013, at 4:20 AM, Jess Baker wrote:
> Dear list,
>
> I am very new to R and have been struggling with extracting data from a
> netcdf file. Basically I have read in a file containing vegetation height
> data organised in 0.5 degree grid cells spanning the whole globe. Each cell
> contains a histogram representing the height distribution and I need to
> extract a single value (the mean) from each cell. My data has 720 rows and
> 240 columns so is pretty large and I’ve been told for loops should be the
> most straightforward way to do this. Sorry the code below is not reproducible
> but hopefully it illustrates where I am going wrong.
>
> ##The following returns the mean value of a single cell (260,90)
>
>> sum(ht.center.vals*(ht.hist[260,90,]))/sum(ht.hist[260,90,])
>
> ##but when I try to translate this to a for loop I get NaN
>
>> mean.height<-NULL
>> for(i in 1:nrow(ht.hist)){
> + for(j in 1:ncol(ht.hist)){
> + mean.height<-sum(ht.center.vals*(ht.hist[i,j,]))/sum(ht.hist[i,j,])
> + }
> + }
>> mean.height
> [1] NaN
You appear to be committing a common programming mistake. Assignment on the LHS
to a non-indexed variable will overwrite all of the previous values. The NaN is
now simply the last value calculated.
> Can anyone tell me how I tell R to look at each cell in turn, extract the
> mean value and save it in a new array? Clearly I am not doing it correctly!
I would imagine making mean.height be an matrix/array of the desired dimensions
and then assign to the proper values inside that object using the loop indices.
mean.height <- matrix(NA, nrow(ht.hist), ncol(ht.hist) )
# then the loop would do the assignment:
mean.height[,i,j] <- …
--
David Winsemius
Alameda, CA, USA
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