I\'ve noticed that R
keeps the index from for
loops stored in the global environment, e.g.:
for (ii in 1:5){ }
print(ii)
# [1] 5
<
-
In order to do what you suggest, R would have to change the scoping rules for for
loops. This will likely never happen because i'm sure there is code out there in packages that rely on it. You may not use the index after the for loop, but given that loops can break()
at any time, the final iteration value isn't always known ahead of time. And having this as a global option again would cause problems with existing code in working packages.
As pointed out, it's for more common to use sapply or lapply loops in R. Something like
for(i in 1:4) {
lm(data[, 1] ~ data[, i])
}
becomes
sapply(1:4, function(i) {
lm(data[, 1] ~ data[, i])
})
You shouldn't be afraid of functions in R. After all, R is a functional language.
It's fine to use for
loops for more control, but you will have to take care of removing the indexing variable with rm()
as you've pointed out. Unless you're using a different indexing variable in each loop, i'm surprised that they are piling up. I'm also surprised that in your case, if they are data.tables, they they are adding additional memory since data.tables don't make deep copies by default as far as i know. The only memory "price" you would pay is a simple pointer.
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