Hello,
Is there a faster way to do this? Basically, I'd like to NA all values in
all_data if there are no 1's in the same column of the other matrix, iu.
Put another way, I want to replace values in the all_data columns if values
in the same column in iu are all 0. This is pretty slow for me, but works:
all_data = matrix(c(1:9),3,3)
colnames(all_data) = c('a','b','c')
> all_data
a b c
[1,] 1 4 7
[2,] 2 5 8
[3,] 3 6 9
iu = matrix(c(1,0,0,0,1,0,0,0,0),3,3)
colnames(iu) = c('a','b','c')
> iu
a b c
[1,] 1 0 0
[2,] 0 1 0
[3,] 0 0 0
fun = function(x,d){
vals = d[,x]
i = iu[,x]
if(!any(i==1)){
vals = rep(NA,times=length(vals))
}else{
vals
}
vals
}
all_data = sapply(colnames(iu),fun,all_data)
> all_data
a b c
[1,] 1 4 NA
[2,] 2 5 NA
[3,] 3 6 NA
...again, this work, but is slow for a large number of columns. Have
anything faster?
Thanks,
ben
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