[ Sorry about my last incomplete reply. Here it is in full ]
On Tue, 09 Nov 2004 21:50:57 +0100 Roberto Bagnara bagnara@cs.unipr.it wrote:
By the way, we (the PPL developers) are more and more curious about these Haskell bindings we have read about in some recent messages to the mailing list. It may come as a surprise to you, but we never saw them and we have not the slightest idea about how they look like. Can you give us a pointer?
The bindings are just Haskell library code that calls the PPL C interface functions. It also defines Haskell wrapper types for (pointers to) the PPL data objects. So effectively the Haskell interface in built on top of the C one and you get the same API as with C.
Axel Simon wrote the basic Haskell interface code and I got it from him. He didn't made publicly available because he came across a bug he couldn't resolve. It turned out to be of a memory allocation conflict which I managed to get around it by linking the PPL with a private version of libgmp. This is still a bit of a hack, so I don't know if Axel has made it available yet on his web page. For me, I'd much prefer to use Haskell than C/C++ or Prolog, so that's incentive enough to get it working...
So, let us start with your question. Premise number 1 is that I am not against providing `omega_reduce()' to the user of Polyhedra_Powerset. Premise number 2 is that I prefer to be extra-sure providing `omega_reduce()' to the user of Polyhedra_Powerset is the right thing to do. The obvious question I have to ask you is: why would you want to have access to `omega_reduce()? What is the effect you wish to obtain? Afterall, one may say that a Polyhedra_Powerset and its omega-reduced counterparts have the same semantics.
True, I should be more explict: I only need omega_reduce() before converting constraints to a Haskell representation after a sequence of polyhedral computations. The constraints should be simplified for pretty printing and because they will eventually get replicated. I know I could just leave them in the PPL world, but I prefer to use the PPL as a "black box" solver and get an observable value out (at least for the time being).
To make a parallel with a similar situation with the C_Polyhedron and NNC_Polyhedron classes, we do not provide a method `minimize()' to the user. We rather ask the user to declare what is wanted by calling `miminized_constraints()' or `minimized_generators()' and keep polyhedra minimization as an internal business the user needs not be concerned about. Up to now, this design choice has proved its value without showing any drawback.
Yes, but I could not find an analogous operation for Powersets. I am using minimzed_constraints() for each powerset element, but (of course) that doesn't eliminate redundant elements (for example: bottom elements).
The method `pairwise_reduce()' does a different thing (please consult the documentation and complain if it does not provide enough information). And moreover, it is quite expensive.
Yes, I thought as much!
Thanks for your thorough reply,
Pedro Vasconcelos