[R] python

[Romain Francois]

On 11/21/2009 11:32 PM, Stefan Evert wrote:
>
>> My hunch is that Python and R run at about the same speed, and both
>> use C libraries for speedups (Python primarily via the numpy package).
>
> That's not necessarily true. There can be enormous differences between
> interpreted languages, and R appears to be a particularly slow one
> (which doesn't usually matter, as well-written code will mostly perform
> matrix operations).
>
> I did run some simple benchmarks with "naive" loops such as this one
>
>> for (x in 1:N) {
>> sum <- sum + x
>> }

Sure, badly written R code does not perform as well as well written 
python code or C code. On the other hand badly written python code does 
not perform as well as well written R code.

What happens when you try one of these :

sum <- sum( 1:N )
sum <- sum( seq_len(N) )
sum <- N * (N + 1L) / 2L  # ;-)

A lot can be done by just rewriting some of the R code.


> as well as function calls. I haven't tested Python yet, but in generally
> it is considered to be roughly on par with Perl.
>
> Here are results for the loop above:
>
> R/simple_count.R 0.82 Mops/s (2000000 ops in 2.43 s)
> perl/simple_count.perl 8.32 Mops/s (10000000 ops in 1.20 s)
>
> (where Mops = million operations per second treats one loop iteration as
> a single operation here). As you can see, Perl is about 10 times as fast
> as R. The point is, however, that this difference may not be worth the
> effort you spend re-implementing your algorithms in Python or Perl and
> getting the Python/Perl interface for R up and running (I've just about
> given up on RSPerl, since I simply can't get it to install on my Mac in
> the way I need it).
>
> The difference between R and Perl appears much less important if you
> compare it to compiled C code:
>
> C/simple_count.exe 820.86 Mops/s (500000000 ops in 0.61 s)
>
> If you really need speed from an interpreted language, you could try Lua:
>
> lua/simple_count.lua 65.78 Mops/s (100000000 ops in 1.52 s)
>
> (though you're going to lose much of this advantage as soon as you
> include function calls, which have a lot of overhead in every
> interpreted language.
>
>
> Hope this helps,
> Stefan

-- 
Romain Francois
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http://romainfrancois.blog.free.fr
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