[R] “For” calculation is so slow

[Petr PIKAL]

Hi

> 
> For loops are really, really slow in R. In general, you want to avoid 
them

I strongly disagree. ***Proper*** use of looping is quite convenient and 
reasonably fast.

Consider

> system.time( {
+ a=0
+ for (i in 1:10000000) {
+ a <-a+i
+ }
+ a
+ })
   user  system elapsed 
  10.22    0.02   10.28 
> 
> system.time(b<-sum(as.numeric(1:10000000)))
   user  system elapsed 
   0.09    0.01    0.11 
> identical(a,b)
[1] TRUE

It is usually implementing C habits into R code what makes looping slow. 
The slowest part of a program is usually programming and it is influenced 
mainly by programmer.

Regards
Petr

> like the plague. If you absolutely must insist on using them in large,
> computationally intense and complex code, consider implementing the 
relevant
> parts in C, say, and calling that from R.
> 
> Staying within R, you can probably considerably speed up that code by
> storing gx and gy as a multi-dimensional arrays. (e.g. for sample data,
> something like
> 
> rawGy = sample( 1:240, 240^2* 241, replace = T)
> rawGx = sample( 1:240, 240^2 *241, replace = T)
> gx = array(rawGx, dim = c(length(s) - 1, 240,  max(rawGx)+1  ) )
> gy = array(rawGy, dim = c(length(s) - 1, 240,  max(rawGy)+1 ) )
> 
>  ), in which case, you can easily do the computation without loops by
> 
> gxa = (gx[ ,a,1]+ 1)
> gya =(gy[ ,a, 1] +1)
> uv = gx[cbind(1:(length(s) - 1) , b, gxa)] / gx[cbind(1:(length(s) - 1) 
, a,
> gxa)]  - gy[cbind(1:(length(s) - 1) ,b, gya)]/gy[cbind(1:(length(s) - 1) 
,a,
> gya)]
> 
> or similar, which will be enormously faster (on my computer, there's an 
over
> 30x speed up). With a bit of thought, I'm sure you can also figure out 
how
> to let it vectorise in a, as well...
> 
> Zhou
> 
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> calculation-is-so-slow-tp4630830p4630855.html
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