OK, just for fun, I added a couple of *obvious* (or should have been)
approaches and got results that exactly agreed with Peter D's
comments: all O(n^2) results were essentially the same, and my matrix
multiplication O(n^3) solution was **far** worse. So I'm not sure
quite where Jeff's result came from.
microbenchmark( { t( y * t(x) ) }
,{ x %*% diag( y ) }
,{ sweep( x, 2, y, `*` ) }
,{vapply(seq_along(y),function(i)x[,i]*y[i],.1*seq_along(y))}
,{scale(x,center = FALSE,scale = 1/y)}
)
Unit: milliseconds
expr min lq mean
{ t(y *
t(x)) } 8.163510 9.880709 17.29899
{ x %*%
diag(y) } 637.639318 665.391992 686.12427
{ sweep(x, 2, y,
`*`) } 9.383453 10.497793 20.81000
{ vapply(seq_along(y), function(i) x[, i] * y[i], 0.1 *
seq_along(y)) } 9.980690 11.748857 18.05533
{ scale(x, center = FALSE, scale =
1/y) } 10.427894 12.342690 19.57287
median uq max neval
11.72617 13.36316 100.00340 100
679.38066 699.03779 827.17972 100
13.11326 15.18546 95.41382 100
13.47730 14.50548 98.80840 100
14.08266 15.70222 99.52050 100
Note that scale() is basically a wrapper for sweep() with the api the
OP requested, so it would seem to be the "natural" choice. Also, my
matrix solution was an awful suggestion and should be tossed intp the
trash.
Cheers,
Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Fri, Nov 4, 2016 at 1:52 PM, Stefan Evert <stefa...@collocations.de> wrote:
>
>> On 4 Nov 2016, at 17:35, peter dalgaard <pda...@gmail.com> wrote:
>>
>> Notice though, that Bert loses (or _should_ lose) for larger values of N,
>> since that method involves O(N^3) operations whereas the other two are
>> O(N^2). I am a bit surprised that sweep() is so inefficient even at N=1000.
>
> I also got different results on Mac OS X (with R 3.3.1 and vecLib BLAS):
>
> Unit: milliseconds
> expr min lq mean median uq
> max neval
> { t(y * t(x)) } 18.46369 19.61954 25.77548 21.24242 22.72943
> 88.03469 100
> { x %*% diag(y) } 28.12786 29.87109 37.83814 31.59671 32.77839
> 101.68553 100
> { sweep(x, 2, y, `*`) } 11.19871 12.76442 21.48670 14.51618 15.70665
> 100.51444 100
>
> Note that sweep() is considerably _faster_ than the other two methods (which
> I found quite surprising).
>
> Of course, if you care about speed (and memory efficiency), you could also
>
> library(wordspace)
> scaleMargins(x, cols=y)
>
> Best,
> Stefan
>
> ______________________________________________
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