dolfin team mailing list archive

[Johan Hake <hake@xxxxxxxxx>]

On Friday 08 May 2009 08:49:59 Garth N. Wells wrote:
> Anders Logg wrote:
> > On Fri, May 08, 2009 at 08:12:35AM +0200, Johan Hake wrote:
> >> On Thursday 07 May 2009 23:16:54 Anders Logg wrote:
> >>> On Thu, May 07, 2009 at 11:05:49PM +0200, Johan Hake wrote:
> >>>> On Thursday 07 May 2009 18:54:04 Anders Logg wrote:
> >>>>> I've added some of the requested features to the parameter system,
> >>>>> some pushed and some sitting here in a local repository. But the
> >>>>> current design makes it a pain to add new features. A single change
> >>>>> will make it necessary to add a function in at least 5 different
> >>>>> classes.
> >>>>>
> >>>>> So I'm thinking of reimplementing and simplifying the parameter
> >>>>> system. I think I know how to make it simpler.
> >>>>>
> >>>>> But before I do that, does anyone have opinions on the
> >>>>> design/implementation? Is there any third-party library that we
> >>>>> could/should use (maybe something in boost)?
> >>>>
> >>>> It would be nice to have something that easely could be transferable
> >>>> to Python.
> >>>>
> >>>> Having a base class let say Parameterized and then let all inherit
> >>>> this to be able to define parameters will not work well for the
> >>>> shared_ptr interface we have. We have problems with the Variable
> >>>> class, which does not work for the derived shared_ptr classes e.g.
> >>>> Function. I would rather have classes that have a parameter rather
> >>>> than beeing.
> >>>
> >>> How would that work? Inheritance now provides get/set functions for
> >>> subclasses making it possible to do
> >>>
> >>>   solver.set("tolerance", 0.1);
> >>
> >> Not sure what you ask for here. I know of Parametrized and I agree that
> >> the above syntax is nice. But I prefer to keep the parameters in its own
> >> object and just operate on that. These can then be collected into one
> >> "dict/map" and then form the parameters of an application. This is also
> >> easier to wrap to python.
> >>
> >> The shared_ptr argument might not be so relevant as the potential
> >> parametrized classes may not be declared as shared_ptr classes in the
> >> swig interface anyway. However if that will be the case we must declare
> >> Parametrized as a shared_ptr class in swig and then we must declare all
> >> Parametrized sub classes as shared_ptr...
> >>
> >>>> Also by defining a parameter(list/dict) class which can be accessed as
> >>>> a dict let us make the transition to python smoother.
> >>>>
> >>>>    ParameterDict p = solver.default_params();
> >>>>    p["abs_tol"] = 1e-9;
> >>>
> >>> It would need to be
> >>>
> >>>     ParameterDict& p = solver.default_params();
> >>
> >> Sure :P
> >>
> >>> and I'd suggest naming it Parameters:
> >>>
> >>>     Parameters& p = solver.parameters();
> >>
> >> Fine.
> >>
> >>>> By defining some templated check classes we could controll the
> >>>> assignment. In the Solver:
> >>>>    ...
> >>>>    ParameterDict& default_params(){
> >>>>       if (!_par)
> >>>>       {
> >>>>          _par = new ParameterDict();
> >>>>          _par->add_param("abs_tol",new RangeCheck<double>(1e-15,0,1));
> >>>>          vector<string> * allowed_prec = new Vector<string>();
> >>>>          allowed_prec->push_back("ilu");
> >>>>          allowed_prec->push_back("amg");
> >>>>          allowed_prec->push_back("jacobi");
> >>>>          _par->add_param("prec",new
> >>>> OptionCheck<string>("ilu"),allowed_prec));
> >>>> _par->add_param("nonsense","jada"); // No checks
> >>>>       }
> >>>>    }
> >>>>
> >>>> Well, I admit that the above code is not beautiful, and others can
> >>>> probably make it cleaner and spot errors. The point is that RangeCheck
> >>>> and OptionCheck can be derived from a ParCheck class that overloads
> >>>> the operator=(). This will just call a private set function which is
> >>>> defined in the derived classes, and which do the check.
> >>>
> >>> I think we can also solve this without excessive templating... ;-)
> >>
> >> Good!
> >>
> >>>> The to and from file can be implemented in the ParameterDict body. The
> >>>> checks do not have to be written or read, as a ParameterDict can only
> >>>> read in allready predefined parameters, and the check will be done
> >>>> when the file is read.
> >>>>
> >>>> The option parser ability can also be implemented in ParameterDict
> >>>> using boost or other libraries, based on the registered parameters.
> >>>>
> >>>> I have implemented something like this in Python, and the above is a
> >>>> try to scetch something similare in c++.
> >>>
> >>> What exactly is needed from the Python side? I think I can make a
> >>> fairly simple implementation of this in C++ using a minimal amount of
> >>> templates with simple syntax.
> >>
> >> Using operator[] to get and set parameters can straightforwardly be
> >> mapped to python, and we can then also implement the map/dict protocol
> >> on top of that. Other get and set methods can also be used, however set
> >> is a built in type in Python and not a good alternative.
> >>
> >>> Is the main difference that instead of inheriting Parametrized, a
> >>> subclass needs to implement a method named parameters() which returns
> >>> the parameter "dictionary"?
> >>
> >> Yes.
> >
> > ok, I'll try this. I'll add a sketch of a new class using as much of
> > po as seems reasonable and then you could have a look before I proceed.
>
> Will there be just one parameter dictionary, or will objects have their
> own? I'm thinking of cases like when a program uses two Krylov solvers
> but may use different tolerances for each one.

You mean one parameter dictionary per class or one per instance? I have the 
same distinction in a Python application. Some places I need one per instance 
and other places it is more convinient to have one per class.

In python I have a way to controll this dynamically. Not sure how this could 
be done in c++. 

Johan

> Garth
>
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