On Apr 12, 2011, at 10:33 , Joris Meys wrote:
> Thanks for the explanation, I wasn't fully aware of which optimization
> I was using. I reckon your solution is more R-sound, so no reason to
> keep with my bizarre workaround. It would be nice though if gl() got
> optimized. Thank you for the example too, I'm learning every day.
>
I have now committed a version of the below to r-devel. (A couple of demons
turned out to be lurking in the details, so not exactly the same code.)
-pd
> Cheers
> Joris
>
> On Tue, Apr 12, 2011 at 8:51 AM, peter dalgaard <pda...@gmail.com> wrote:
>>
>> On Apr 11, 2011, at 23:53 , Joris Meys wrote:
>>
>>> Based on a discussion on SO I ran some tests and found that converting
>>> to a factor is best done early in the process. Hence, I propose to
>>> rewrite the gl() function as :
>>>
>>> gl2 <- function(n, k, length = n * k, labels = 1:n, ordered = FALSE){
>>> rep(
>>> rep(
>>> factor(1:n,levels=1:n,labels=labels, ordered=ordered),rep.int(k,n)
>>> ),length.out=length
>>> )
>>> }
>>>
>>
>> That's bizarre! You are relying on an optimization in rep.factor whereby it
>> replicates the internal codes and exploits that the result has the same
>> structure as the input. I.e., it just tacks on class and levels attributes
>> rather than call match() as factor() does internally.
>>
>> However, you can do the same thing straight away:
>>
>>> gl2
>> function (n, k, length = n * k, labels = 1:n, ordered = FALSE)
>> {
>> y <- rep(rep.int(1:n, rep.int(k, n)), length.out = length)
>> structure(y, levels=as.character(labels),
>> class=c(if(ordered)"ordered","factor"))
>> }
>>
>> I get this to be a bit faster than your version, although with a smaller
>> speedup factor, which probably just indicates that match() is faster on this
>> machine.
>>
>>> Some test results :
>>>
>>>> system.time(X1 <- gl(5,1e7))
>>> user system elapsed
>>> 29.21 0.30 29.58
>>>
>>>> system.time(X2 <- gl2(5,1e7))
>>> user system elapsed
>>> 1.87 0.45 2.37
>>>
>>>> all.equal(X1,X2)
>>> [1] TRUE
>>>
>>>> system.time(X1 <- gl(5,100,1e7))
>>> user system elapsed
>>> 5.98 0.05 6.05
>>>
>>>> system.time(X2 <- gl2(5,100,1e7))
>>> user system elapsed
>>> 0.21 0.03 0.25
>>>
>>>> all.equal(X1,X2)
>>> [1] TRUE
>>>
>>>> system.time(X1 <- gl(5,100,1e7,labels=letters[1:5]))
>>> user system elapsed
>>> 5.88 0.02 5.98
>>>
>>>> system.time(X2 <- gl2(5,100,1e7,labels=letters[1:5]))
>>> user system elapsed
>>> 0.20 0.05 0.25
>>>
>>>> all.equal(X1,X2)
>>> [1] TRUE
>>>
>>>> system.time(X1 <- gl(5,100,1e7,labels=letters[1:5],ordered=T))
>>> user system elapsed
>>> 5.82 0.03 5.89
>>>
>>>> system.time(X2 <- gl2(5,100,1e7,labels=letters[1:5],ordered=T))
>>> user system elapsed
>>> 0.22 0.04 0.25
>>>
>>>> all.equal(X1,X2)
>>> [1] TRUE
>>>
>>> reference to SO :
>>> http://stackoverflow.com/questions/5627264/how-can-i-efficiently-construct-a-very-long-factor-with-few-levels
>>>
>>> --
>>> Joris Meys
>>> Statistical consultant
>>>
>>> Ghent University
>>> Faculty of Bioscience Engineering
>>> Department of Applied mathematics, biometrics and process control
>>>
>>> tel : +32 9 264 59 87
>>> joris.m...@ugent.be
>>> -------------------------------
>>> Disclaimer : http://helpdesk.ugent.be/e-maildisclaimer.php
>>>
>>> ______________________________________________
>>> R-devel@r-project.org mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-devel
>>
>> --
>> Peter Dalgaard
>> Center for Statistics, Copenhagen Business School
>> Solbjerg Plads 3, 2000 Frederiksberg, Denmark
>> Phone: (+45)38153501
>> Email: pd....@cbs.dk Priv: pda...@gmail.com
>>
>>
>
>
>
> --
> Joris Meys
> Statistical consultant
>
> Ghent University
> Faculty of Bioscience Engineering
> Department of Applied mathematics, biometrics and process control
>
> tel : +32 9 264 59 87
> joris.m...@ugent.be
> -------------------------------
> Disclaimer : http://helpdesk.ugent.be/e-maildisclaimer.php
--
Peter Dalgaard
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd....@cbs.dk Priv: pda...@gmail.com
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