[R] Odp: fast way to compare two matrices

peter dalgaard PDalgd at gmail.com
Wed Apr 27 16:21:49 CEST 2011


On Apr 27, 2011, at 13:29 , Alaios wrote:

> That was great :)
> REgards

You may need to turn your sarcasm detector back on. Beware:

> x <- matrix(rnorm(1e6), 1000,1000)
> y <- solve(solve(x))
> identical(x,y)
[1] FALSE
> all.equal(x,y)
[1] TRUE
> summary(c(x-y))
      Min.    1st Qu.     Median       Mean    3rd Qu.       Max. 
-6.442e-11 -6.204e-12  7.550e-15  2.670e-15  6.212e-12  6.722e-11 




> 
> 
> --- On Wed, 4/27/11, Petr PIKAL <petr.pikal at precheza.cz> wrote:
> 
>> From: Petr PIKAL <petr.pikal at precheza.cz>
>> Subject: Odp: [R] fast way to compare two matrices
>> To: "Alaios" <alaios at yahoo.com>
>> Cc: R-help at r-project.org, r-help-bounces at r-project.org
>> Date: Wednesday, April 27, 2011, 12:18 PM
>> Hi
>> 
>> x <- matrix(rnorm(1e6), 1000,1000)
>> y <- matrix(rnorm(1e6), 1000,1000)
>> 
>> identical(x,y)
>> [1] FALSE
>> 
>> The response is almost instant.
>> 
>> In case you are not satisfied with the unspecific answer be
>> more specific 
>> with your question.
>> 
>> Regards
>> Petr
>> 
>> r-help-bounces at r-project.org
>> napsal dne 27.04.2011 13:04:37:
>> 
>>> Dear all,
>>> I am trying to speed up some code and I would like to
>> check fast that it 
>> works
>>> by comparing two different matrices.
>>> 
>>> What is the fastest way to do that in R?
>>> 
>>> Best Regards
>>> Alex
>>> 
>>> ______________________________________________
>>> R-help at r-project.org
>> mailing list
>>> 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 at r-project.org mailing list
> 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.

-- 
Peter Dalgaard
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd.mes at cbs.dk  Priv: PDalgd at gmail.com



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