> On Dec 9, 2016, at 9:15 AM, Doran, Harold <hdo...@air.org> wrote:
>
> I believe I now see the light vis-à-vis iterators when combined with
> foreach() calls in R. I have now been able to reduce computational workload
> to minutes instead of hours. I want to verify that the way I am using them is
> "safe". By safe I mean does the iterator traverse elements in the same way as
> I have below in my toy example to illustrate what I mean.
>
> In the first "traditional" example, I have only one index variable for the
> loop and so I know that the same list in r1 and r2 are always being grabbed.
> That is, in iteration 1 it is guaranteed to use r1[[1]] + r2[[1]].
>
> In the example that uses the iterators, is this also guaranteed even though I
> now have two iterator objects? That is, will the index for element i always
> be the same as the index for element j when using this across many different
> cores?
>
> It seems to be true and in all my test cases so far I am seeing it to be
> true. But, that could be just luck, so I wonder if there is a condition under
> which that would NOT be true.
>
> Thank you
> Harold
>
>
> library(foreach)
> library(doParallel)
> cl <- makeCluster(2)
> registerDoParallel(cl)
>
> ### Create random data
> r1 <- vector("list", 20)
> for(i in 1:20){
> r1[[i]] <- rnorm(10)
> }
>
> ### Create random data
> r2 <- vector("list", 20)
> for(i in 1:20){
> r2[[i]] <- rnorm(10)
> }
>
> ### Use a for loop traditionally
> result1 <- vector("list", 20)
> for(i in 1:20){
> result1[[i]] <- r1[[i]] + r2[[i]]
> }
>
> ### Use iterators
> itx1 <- iter(r1)
> itx2 <- iter(r2)
>
> result2 <- foreach(i = itx1, j = itx2) %dopar% {
> i + j
> }
>
> all.equal(result1, result2)
I wasn't sure how this would or should behave. I'm not an experienced user,
merely a reader of help pages. Neither the help page, not the vignette
references on the help page answered my questions in this case. I expected that
call would behave analogously to the behavior of mapply when given iterators of
unequal length. (The shorter of the objects is recycled to reach the length of
the longer object.) That expectation was not realized. It appears that the
length of first object of the objects determines computation length, but that
missing values will not be recycled for the shorter iterator. An error is not
reported, but rather numeric(0) is returned. So in one sense the %dopar%
version is "safer" at least to the extent of not failing with an error that
would have occurred when using a for-loop.
This was my test case:
r1 <- vector("list", 10)
for(i in 1:20){
r1[[i]] <-20:29+i*10
# random numbers are not good for determining sequences of operations
}
r2 <- vector("list", 20)
for(i in 1:10){
r2[[i]] <- 1:10 +i
}
itx1 <- iter(r1)
itx2 <- iter(r2)
result2 <- foreach(i = itx1, j = itx2) %dopar% {
i + j
}
result2
--
David Winsemius
Alameda, CA, USA
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