Try this -- use matrices instead of dataframes if you want speed:
> p<-data.frame(a=rnorm(10),b=rnorm(10),c=rnorm(10),d=rnorm(10))
> test<-data.frame(a=rnorm(1),b=rnorm(1),c=rnorm(1),d=rnorm(1))
>
> result<-list()
> for(i in 1:nrow(p)){
+ result[[i]]<-sum((p[i,]-test)^2)
+ }
>
> result_1<-unlist(result)
>
> p_1<-cbind(p,result_1)
>
> # don't use dataframes; use matrices
> pm <- as.matrix(p)
> testm <- unlist(test)
>
> result_2 <- colSums((t(pm) - testm)^2)
> p_2 <- cbind(pm, result_2)
> p_1
a b c d result_1
1 1.4580819 0.03351271 -0.6414914 -0.4448870 2.464525
2 -0.7603889 -0.41833604 -1.3576672 -0.1230215 6.270578
3 1.3343855 -1.35613207 2.0560362 -1.0356030 3.592794
4 0.5974293 0.88175552 -1.4756855 0.1634320 6.707364
5 -0.8008295 0.37385864 -0.7822124 -0.4896094 4.712335
6 -0.5550789 0.07063761 0.9432475 1.0785456 4.868218
7 1.0641638 -1.52241836 0.3912154 0.1071740 2.165140
8 1.5619793 -0.30982169 1.2756762 -0.8522361 1.266879
9 -0.1049558 -1.66660559 0.5425563 0.3232156 3.279428
10 -0.1565198 0.59954267 -1.3878649 1.8615366 12.132722
> p_2
a b c d result_2
[1,] 1.4580819 0.03351271 -0.6414914 -0.4448870 2.464525
[2,] -0.7603889 -0.41833604 -1.3576672 -0.1230215 6.270578
[3,] 1.3343855 -1.35613207 2.0560362 -1.0356030 3.592794
[4,] 0.5974293 0.88175552 -1.4756855 0.1634320 6.707364
[5,] -0.8008295 0.37385864 -0.7822124 -0.4896094 4.712335
[6,] -0.5550789 0.07063761 0.9432475 1.0785456 4.868218
[7,] 1.0641638 -1.52241836 0.3912154 0.1071740 2.165140
[8,] 1.5619793 -0.30982169 1.2756762 -0.8522361 1.266879
[9,] -0.1049558 -1.66660559 0.5425563 0.3232156 3.279428
[10,] -0.1565198 0.59954267 -1.3878649 1.8615366 12.132722
>
On Fri, Mar 16, 2012 at 8:32 AM, mrzung <mrzun...@gmail.com> wrote:
> hi,
>
> i'm really in trouble to simulate some experiment.
> that is, it takes too much time to process the following code.
>
> following is short example,
>
> -------------------------------------------------------------------------------------------------------
>
> p<-data.frame(a=rnorm(10),b=rnorm(10),c=rnorm(10),d=rnorm(10))
> test<-data.frame(a=rnorm(1),b=rnorm(1),c=rnorm(1),d=rnorm(1))
>
> result<-list()
> for(i in 1:nrow(p)){
> result[[i]]<-sum((p[i,]-test)^2)
> }
>
> result_1<-unlist(result)
>
> p_1<-cbind(p,result_1)
>
> -------------------------------------------------------------------------------------------------------
>
> is there any efficient way to shorten the time and make same output?
>
>
> --
> View this message in context:
> http://r.789695.n4.nabble.com/how-to-speed-up-the-inefficient-code-tp4478046p4478046.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help@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.
--
Jim Holtman
Data Munger Guru
What is the problem that you are trying to solve?
Tell me what you want to do, not how you want to do it.
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and provide commented, minimal, self-contained, reproducible code.
