[R] Suitability of R for Algorithm simulations

[François Pinard]

[Ethan B. Fini]

> I would like to be able to instantiate an object for each node in my 
> simulated  (stand alone, one computer) "distributed" environment and 
> then proceed by (a)  adding message exchange functionality and (b) 
> algorithm  behavior to each node.

Not so long ago, I quickly glanced at Eiffel after an enthusiastic 
friend told me about it, and while I do not think I will soon use it for 
myself, Eiffel might be the right choice for you, being strong on 
light-weight processes and message passing, from what I've read...

If I had a simulation problem to tackle nowadays, I'd likely consider 
Python supplemented with greelets from the pylib library, mainly because 
I'm fond on Python legibility, and have a reasonably good confidence in 
people having implemented greenlets.

> The simulation results are represented on a GUI [...]

The GUI aspects of Eiffel are unknown to me, I did not dive deep enough 
to touch them.  For Python, I'd use pygtk, but there are many toolkits 
to choose from.

> Is R suitable for what I am trying to do? I looked around but have not 
> been able to determine if R is the appropriate platform. 

R libraries are especially good at statistics and graphics.  The 
language in itself is much oriented towards vectorisation, among other 
things, and this might be convenient for a speedy implementation of some 
simulation problems.  If vectorisation could not be turned into an 
advantage for you with R, it is likely that R might be slow for such 
problems, and also not so well adapted to quasi-parallelism between 
interacting processes having each their own behaviour.

Of course, seasoned R users might have much more sound opinions than 
mine on this topic! :-)

-- 
François Pinard   http://pinard.progiciels-bpi.ca