From: Erik Iverson <iverson_at_biostat.wisc.edu>

Date: Wed, 30 Apr 2008 15:56:37 -0500

}

return(fc_matrix)

}

}

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. Received on Wed 30 Apr 2008 - 21:10:38 GMT

Date: Wed, 30 Apr 2008 15:56:37 -0500

Zhandong Liu wrote:

> I am switching from Matlab to R, but I found that R is 200 times slower than

*> matlab.
**>
**> Since I am newbie to R, I must be missing some important programming tips.
*

The most important tip I would give you is to use the vectorized nature of R whenever possible. This helps avoid messy indexing and 'for' loops.

Look at the following 3 functions. Yours, Gabor's, and my own (which I was about to post when I saw Gabor's nice solution, and is basically the same).

Also see the system timings after the definitions.

grw_permute <- function(input_fc){

fc_vector <- input_fc

index <- 1

k <- length(fc_vector)

fc_matrix <- matrix(0, 2, k^2)

for(i in 1:k){

for(j in 1:k){ fc_matrix[index] <- fc_vector[i] fc_matrix[index+1] <- fc_vector[j] index <- index + 2 }

}

return(fc_matrix)

}

grw.permute2 <- function(v) {

cbind( rep(v, each=length(v)), rep(v, length(v)) ) }

grw_permute3 <- function(input_fc) {

matrix(c(rep(input_fc, each = length(input_fc)),

rep.int(input_fc, times = length(input_fc))), nrow = 2, byrow = TRUE)

}

> system.time(p1 <- grw_permute(1:300))

user system elapsed

1.548 0.064 2.341

> system.time(p2 <- grw_permute2(1:300))

user system elapsed

0.009 0.001 0.010

> system.time(p3 <- grw_permute3(1:300))

user system elapsed

0.008 0.002 0.010

Erik Iverson

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. Received on Wed 30 Apr 2008 - 21:10:38 GMT

Archive maintained by Robert King, hosted by
the discipline of
statistics at the
University of Newcastle,
Australia.

Archive generated by hypermail 2.2.0, at Wed 30 Apr 2008 - 21:30:42 GMT.

*
Mailing list information is available at https://stat.ethz.ch/mailman/listinfo/r-help.
Please read the posting
guide before posting to the list.
*