I'm not sure why either, but here's a simpler (and much faster)
illustration of the problem:
library(microbenchmark)
A <- matrix(1:9,3)
replicate(10, microbenchmark(colMeans(A), times = 4)$time)
replicate(10, microbenchmark(A, times = 4)$time)
Hadley
On Mon, Sep 16, 2013 at 8:11 AM, Christophe Genolini
<cgeno...@u-paris10.fr> wrote:
> Hi the list,
>
> I am using the function microbenchmark to measure the performance of some
> code. But I notice that the first execution of the code takes much longueur
> than the next executions.
> I compare it to several executions of the code :
>
> --- 8< ----------
> A <- matrix(1:9,3)
> nbReroll <- 1000
> temps <- matrix(NA,1000,2)
> temps[,1] <- microbenchmark(colMeans(A),times=nbReroll)$time
>
> for(j in 1:nbReroll){
> temps[j,2] <- microbenchmark(colMeans(A),times=1)$time
> }
>
> --- 8< -----------
> Here is a plot of the result I get.
> - In red, temps[,1], that is microbenchmarck(...,times=1000)
> - In blue temps[,2], that is for(i in 1:1000)microbenchmark(...times=1)
>
>
> So why is there such a bid difference? What is the correct execution time
> for my instruction?
>
> Christophe
>
> --
> Christophe Genolini
> Maître de conférences en bio-statistique
> Vice président Communication interne et animation du campus
> Université Paris Ouest Nanterre La Défense
>
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--
Chief Scientist, RStudio
http://had.co.nz/
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