Hello,
The first is easy.
>
> How can I cut these files and save them automatically (one file for ST001,
> another for ST002, ...) according to these columns names?
>
Similar to the way they were read, using lapply on the results list.
But first make a file names vector.
(I've used the file extension 'dat'.)
test <- process.all(lst, m)
fl.names <- paste(names(test), "dat", sep=".")
lapply(seq_len(length(test)), function(i) write.table(test[[i]],
fl.names[i], ...))
The second is trickier.
>
> And it is possible in your script to take the second best correlated
> station data
> instead of the best one, if there are NAs in this best correlated station
> at the same
> lines with the NA gaps of the station to fill?
>
In the function 'process.all', after the internal function 'f',
include the following.
g <- function(station){
x <- df.list[[station]]
if(any(is.na(x$data))){
mat[row(mat) == col(mat)] <- -Inf
nas <- which(is.na(x$data))
ord <- order(mat[station, ], decreasing = TRUE)[-c(1,
ncol(mat))]
for(i in nas){
for(y in ord){
if(!is.na(df.list[[y]]$data[i])){
x$data[i] <- df.list[[y]]$data[i]
break
}
}
}
}
x
}
Then, change the second pass to
# Note that the two passes are different
df.list <- lapply(seq.int(n), f)
df.list <- lapply(seq.int(n), g)
And I come from Portugal. I'm a mathematician (with 6 semesters of stats).
When I go to France, it's more to Charente-Maritime - Cognac, I have friends
there,
and I'll definitelly have a couple of cognacs on you.
Good luck with your assignment.
Rui Barradas
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