My mental model is that the left hand side forms a sort of "virtual vector"
where each element really points to an element in the vector being modified.
Then the right hand side scalar is extended in the usual repetitious way (if
necessary) until it is a vector just as long as the "virtual vector" on the
left. Then the right vector is assigned to the left vector, which leaves the
designated elements in the destination vector changed.
You could work out an equivalent for loop structure, but I think it would be
tricky to keep the behavior for different length source and destination
assignments straight.
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Sent from my phone. Please excuse my brevity.
Al Roark <hrbuil...@hotmail.com> wrote:
Hi All:
I'm looking to find out a bit more about how subassignment actually works and
am hoping someone with knowledge of the details can fill me in (I've looked at
the source code, but my knowledge of C is lacking).
In the case of vectors, my reading of ?"[" would indicate that for a vector,
vec <- 1:25, vec[c(1,5,25)] <- c(101,102,103)is functionally the same as indx
<- c(1,5,25) for (i in 1:length(indx)) vec[indx[i]] <- c(101,102,103)[i]
And in the case of a data frame, df <- data.frame(d1=1:10,d2=11:20,d3=21:30),
df[c(1,5,10),c(1,3)] <- data.frame(a=101:103,b=104:106)is functionally the same
as rowindx <- c(1,5,10) colindx <- c(1,3) for (i in 1:length(rowindx)) { for
(j in 1:length(colindx)) df[rowindx[i],colindx[j]] <-
data.frame(a=101:103,b=104:106)[i,j] } Obviously I've verified
that these examples work and I realize that my loops also contain
subassignments; what I'm really after is to understand the mechanics of
replacing multiple elements. Is a for-loop the proper way to understand the
sequential nature of subassignments here (even if it is not actually
implemented using a loop)?
Cheers,HR
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