what you measures is the "elapsed" time in the default setting. you
might need to take a closer look at the beautiful benchmark() function
and see what time I am talking about.
I just provided tentative solution for the person asking for it and
believe he has enough wisdom to decide what's best. why bother to
judge others subjectively?
On Sun, Sep 23, 2018 at 1:18 PM Ista Zahn <istaz...@gmail.com> wrote:
>
> On Sun, Sep 23, 2018 at 1:46 PM Wensui Liu <liuwen...@gmail.com> wrote:
> >
> > actually, by the parallel pvec, the user time is a lot shorter. or did
> > I somewhere miss your invaluable insight?
> >
> > > c1 <- 1:1000000
> > > len <- length(c1)
> > > rbenchmark::benchmark(log(c1[-1]/c1[-len]), replications = 100)
> > test replications elapsed relative user.self sys.self
> > 1 log(c1[-1]/c1[-len]) 100 4.617 1 4.484 0.133
> > user.child sys.child
> > 1 0 0
> > > rbenchmark::benchmark(pvec(1:(len - 1), mc.cores = 4, function(i)
> > > log(c1[i + 1] / c1[i])), replications = 100)
> > test
> > 1 pvec(1:(len - 1), mc.cores = 4, function(i) log(c1[i + 1]/c1[i]))
> > replications elapsed relative user.self sys.self user.child sys.child
> > 1 100 9.079 1 2.571 4.138 9.736 8.046
>
> Your output is mangled in my email, but on my system your pvec
> approach takes more than twice as long:
>
> c1 <- 1:1000000
> len <- length(c1)
> library(parallel)
> library(rbenchmark)
>
> regular <- function() log(c1[-1]/c1[-len])
> iterate.parallel <- function() {
> pvec(1:(len - 1), mc.cores = 4,
> function(i) log(c1[i + 1] / c1[i]))
> }
>
> benchmark(regular(), iterate.parallel(),
> replications = 100,
> columns = c("test", "elapsed", "relative"))
> ## test elapsed relative
> ## 2 iterate.parallel() 7.517 2.482
> ## 1 regular() 3.028 1.000
>
> Honestly, just use log(c1[-1]/c1[-len]). The code is simple and easy
> to understand and it runs pretty fast. There is usually no reason to
> make it more complicated.
> --Ista
>
> > On Sun, Sep 23, 2018 at 12:33 PM Ista Zahn <istaz...@gmail.com> wrote:
> > >
> > > On Sun, Sep 23, 2018 at 10:09 AM Wensui Liu <liuwen...@gmail.com> wrote:
> > > >
> > > > Why?
> > >
> > > The operations required for this algorithm are vectorized, as are most
> > > operations in R. There is no need to iterate through each element.
> > > Using Vectorize to achieve the iteration is no better than using
> > > *apply or a for-loop, and betrays the same basic lack of insight into
> > > basic principles of programming in R.
> > >
> > > And/or, if you want a more practical reason:
> > >
> > > > c1 <- 1:1000000
> > > > len <- 1000000
> > > > system.time( s1 <- log(c1[-1]/c1[-len]))
> > > user system elapsed
> > > 0.031 0.004 0.035
> > > > system.time(s2 <- Vectorize(function(i) log(c1[i + 1] / c1[i])) (1:len))
> > > user system elapsed
> > > 1.258 0.022 1.282
> > >
> > > Best,
> > > Ista
> > >
> > > >
> > > > On Sun, Sep 23, 2018 at 7:54 AM Ista Zahn <istaz...@gmail.com> wrote:
> > > >>
> > > >> On Sat, Sep 22, 2018 at 9:06 PM Wensui Liu <liuwen...@gmail.com> wrote:
> > > >> >
> > > >> > or this one:
> > > >> >
> > > >> > (Vectorize(function(i) log(c1[i + 1] / c1[i])) (1:len))
> > > >>
> > > >> Oh dear god no.
> > > >>
> > > >> >
> > > >> > On Sat, Sep 22, 2018 at 4:16 PM rsherry8 <rsher...@comcast.net>
> > > >> > wrote:
> > > >> > >
> > > >> > >
> > > >> > > It is my impression that good R programmers make very little use
> > > >> > > of the
> > > >> > > for statement. Please consider the following
> > > >> > > R statement:
> > > >> > > for( i in 1:(len-1) ) s[i] = log(c1[i+1]/c1[i], base =
> > > >> > > exp(1) )
> > > >> > > One problem I have found with this statement is that s must exist
> > > >> > > before
> > > >> > > the statement is run. Can it be written without using a for
> > > >> > > loop? Would that be better?
> > > >> > >
> > > >> > > Thanks,
> > > >> > > Bob
> > > >> > >
> > > >> > > ______________________________________________
> > > >> > > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > > >> > > https://stat.ethz.ch/mailman/listinfo/r-help
> > > >> > > PLEASE do read the posting guide
> > > >> > > http://www.R-project.org/posting-guide.html
> > > >> > > and provide commented, minimal, self-contained, reproducible code.
> > > >> >
> > > >> > ______________________________________________
> > > >> > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > > >> > https://stat.ethz.ch/mailman/listinfo/r-help
> > > >> > PLEASE do read the posting guide
> > > >> > http://www.R-project.org/posting-guide.html
> > > >> > and provide commented, minimal, self-contained, reproducible code.
______________________________________________
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