dolfin team mailing list archive

[Anders Logg <logg@xxxxxxxxx>]

Would this work? What it does is to define a simple Equation class
that holds a pair of forms (lhs, rhs) but can still be used for
comparisons.

class Equation:

    def __init__(self, lhs, rhs):
        self.lhs = lhs
        self.rhs = rhs

    def __eq__(self, other):
        if isinstance(other, bool):
            return self.__nonzero__() == other
        else:
            return repr(self) == repr(other)

    def __nonzero__(self):
        return repr(self.lhs) == repr(self.rhs)

class Form:

    def __init__(self, a):
        self.a = a

    def __eq__(self, other):
        return Equation(self, other)

    def __repr__(self):
        return str(self.a)

f1 = Form(1)
f2 = Form(2)
f3 = Form(1)

eq = f1 == f2
print eq == False
print eq == True

if f1 == f2:
    print "f1 == f2 is True"

if f1 == f3:
    print "f1 == f3 is True"

--
Anders


On Tue, Jun 14, 2011 at 10:01:47PM +0200, Martin Sandve Alnæs wrote:
> I agree it is pretty in a way, but here comes the showstopper... Sorry! ;)
>
> There can be no ufl.Form.__eq__ implementation
> that does not conform to the Python conventions
> of actually comparing objects and returning
> True or False, because that will break usage
> of Form objects in built in Python data structures.
>
> Martin
>
> On 14 June 2011 21:53, Anders Logg <logg@xxxxxxxxx> wrote:
> > On Tue, Jun 14, 2011 at 09:03:31PM +0200, Marie E. Rognes wrote:
> >> On 06/14/2011 08:35 PM, Garth N. Wells wrote:
> >> >
> >> >
> >> >On 14/06/11 19:24, Anders Logg wrote:
> >> >>On Tue, Jun 14, 2011 at 10:19:20AM -0700, Johan Hake wrote:
> >> >>>On Tuesday June 14 2011 03:33:59 Anders Logg wrote:
> >> >>>>On Tue, Jun 14, 2011 at 09:25:17AM +0100, Garth N. Wells wrote:
> >> >>>>>On 14/06/11 08:53, Anders Logg wrote:
> >> >>>>>>14 jun 2011 kl. 09:18 skrev "Garth N. Wells"<gnw20@xxxxxxxxx>:
> >> >>>>>>>On 14/06/11 08:03, Marie E. Rognes wrote:
> >> >>>>>>>>On 06/13/2011 11:16 PM, Anders Logg wrote:
> >> >>>>>>>>>>>But while we are heading in that direction, how about
> >> >>>>>>>>>>>abolishing the *Problem class(es) altogether, and just use
> >> >>>>>>>>>>>LinearVariationalSolver and
> >> >>>>>>>>>>>NonlinearVariationalSolver/NewtonSolver taking as input (a,
> >> >>>>>>>>>>>L,
> >> >>>>>>>>>>
> >> >>>>>>>>>>bc)
> >> >>>>>>>>>>
> >> >>>>>>>>>>>and (F, dF, bcs), respectively.
> >> >>>>>>>>>
> >> >>>>>>>>>This will be in line with an old blueprint. We noted some time
> >> >>>>>>>>>ago that problems/solvers are designed differently for linear
> >> >>>>>>>>>systems Ax = b than for variational problems a(u, v) = L(v).
> >> >>>>>>>>>For linear systems, we have solvers while for variational
> >> >>>>>>>>>problems we have both problem and solver classes.
> >> >>>>>>>>>
> >> >>>>>>>>>>>I mean, the main difference lies in how to solve the
> >> >>>>>>>>>>>problems, right?
> >> >>>>>>>>>
> >> >>>>>>>>>It looks like the only property a VariationalProblem has in
> >> >>>>>>>>>addition to (forms, bc) + solver parameters is the parameter
> >> >>>>>>>>>symmetric=true/false.
> >> >>>>>>>>>
> >> >>>>>>>>>If we go this route, we could mimic the design of the linear
> >> >>>>>>>>>algebra solvers and provide two different options, one that
> >> >>>>>>>>>offers more control, solver = KrylovSolver() + solver.solve(),
> >> >>>>>>>>>and one quick option that just calls solve:
> >> >>>>>>>>>
> >> >>>>>>>>>1. complex option
> >> >>>>>>>>>
> >> >>>>>>>>>solver = LinearVariationalSolver() # which arguments to
> >> >>>>>>>>>constructor? solver.parameters["foo"] = ... u = solver.solve()
> >> >>>>>>>
> >> >>>>>>>I favour this option, but I think that the name
> >> >>>>>>>'LinearVariationalSolver' is misleading since it's not a
> >> >>>>>>>'variational solver', but solves variational problems, nor should
> >> >>>>>>>it be confused with a LinearSolver that solves Ax = f.
> >> >>>>>>>LinearVariationalProblem is a better name. For total control, we
> >> >>>>>>>could have a LinearVariationalProblem constructor that accepts a
> >> >>>>>>>GenericLinearSolver as an argument (as the NewtonSolver does).
> >> >>>>>>>
> >> >>>>>>>>For the eigensolvers, all arguments go in the call to solve.
> >> >>>>>>>>
> >> >>>>>>>>>2. simple option
> >> >>>>>>>>>
> >> >>>>>>>>>u = solve(a, L, bc)
> >> >>>>>>>
> >> >>>>>>>I think that saving one line of code and making the code less
> >> >>>>>>>explicit isn't worthwhile. I can foresee users trying to solve
> >> >>>>>>>nonlinear problems with this.
> >> >>>>>>
> >> >>>>>>With the syntax suggested below it would be easy to check for errors.
> >> >>>>>>
> >> >>>>>>>>Just for linears?
> >> >>>>>>>>
> >> >>>>>>>>>3. very tempting option (simple to implement in both C++ and
> >> >>>>>>>>>Python)
> >> >>>>>>>>>
> >> >>>>>>>>>u = solve(a == L, bc)    # linear u = solve(F == 0, J, bc) #
> >> >>>>>>>>>nonlinear
> >> >>>>>>>
> >> >>>>>>>I don't like this on the same grounds that I don't like the
> >> >>>>>>>present design. Also, I don't follow the above syntax
> >> >>>>>>
> >> >>>>>>I'm not surprised you don't like it. But don't understand why. It's
> >> >>>>>>very clear which is linear and which is nonlinear. And it would be
> >> >>>>>>easy to check for errors. And it would just be a thin layer on top of
> >> >>>>>>the very explicit linear/nonlinear solver classes. And it would
> >> >>>>>>follow the exact same design as for la with solver classes plus a
> >> >>>>>>quick access solve function.
> >> >>>>>
> >> >>>>>Is not clear to me - possibly because, as I wrote above, I don't
> >> >>>>>understand the syntax. What does the '==' mean?
> >> >>>>
> >> >>>>Here's how I see it:
> >> >>>>
> >> >>>>1. Linear problems
> >> >>>>
> >> >>>>   solve(a == L, bc)
> >> >>>>
> >> >>>>   solve the linear variational problem a = L subject to bc
> >> >>>>
> >> >>>>2. Nonlinear problems
> >> >>>>
> >> >>>>   solve(F == 0, bc)
> >> >>>>
> >> >>>>   solve the nonlinear variational problem F = 0 subject to bc
> >> >>>>
> >> >>>>It would be easy to in the first case check that the first operand (a)
> >> >>>>is a bilinear form and the second (L) is a linear form.
> >> >>>>
> >> >>>>And it would be easy to check in the second case that the first
> >> >>>>operand (F) is a linear form and the second is an integer that must be
> >> >>>>zero.
> >> >>>>
> >> >>>>In both cases one can print an informative error message and catch any
> >> >>>>pitfalls.
> >> >>>>
> >> >>>>The nonlinear case would in C++ accept an additional argument J for
> >> >>>>the Jacobian (and in Python an optional additional argument):
> >> >>>>
> >> >>>>   solve(F == 0, J, bc);
> >> >>>>
> >> >>>>The comparison operator == would for a == L return an object of class
> >> >>>>LinearVariationalProblem and in the second case
> >> >>>>NonlinearVariationalProblem. These two would just be simple classes
> >> >>>>holding shared pointers to the forms. Then we can overload solve() to
> >> >>>>take either of the two and pass the call on to either
> >> >>>>LinearVariationalSolver or NonlinearVariationalSolver.
> >> >>>>
> >> >>>>I'm starting to think this would be an ideal solution. It's compact,
> >> >>>>fairly intuitive, and it's possible to catch errors.
> >> >>>>
> >> >>>>The only problem I see is overloading operator== in Python if that
> >> >>>>has implications for UFL that Martin objects to... :-)
> >> >>>
> >> >>>Wow, you really like magical syntaxes ;)
> >> >>
> >> >>Yes, a pretty syntax has been a priority for me ever since we
> >> >>started. I think it is worth a lot.
> >> >>
> >> >
> >> >Magic and pretty are not the same thing.
> >
> > That's true, but some magic is usually required to make pretty.
> >
> > Being able to write dot(grad(u), grad(v))*dx is also a bit magic.
> > The step from there to solve(a == L) is short.
> >
> >> >>>The problem with this syntax is that who on earth would expect a
> >> >>>VariationalProblem to be the result of an == operator...
> >> >>
> >> >>I don't think that's an issue. Figuring out how to solve variational
> >> >>problems is not something one picks up by reading the Programmer's
> >> >>Reference. It's something that will be stated on the first page of any
> >> >>FEniCS tutorial or user manual.
> >> >>
> >> >>I think the solve(a == L) is the one missing piece to make the form
> >> >>language complete. We have all the nice syntax for expressing forms in
> >> >>a declarative way, but then it ends with
> >> >>
> >> >>problem = VariationalProblem(a, L)
> >> >>problem.solve()
> >> >>
> >> >>which I think looks ugly. It's not as extreme as this example taken
> >> >>from cppunit, but it follows the same "create object, call method on
> >> >>object" paradigm which I think is ugly:
> >> >>
> >> >>   TestResult result;
> >> >>   TestResultCollector collected_results;
> >> >>   result.addListener(&collected_results);
> >> >>   TestRunner runner;
> >> >>   runner.addTest(CppUnit::TestFactoryRegistry::getRegistry().makeTest());
> >> >>   runner.run(result);
> >> >>   CompilerOutputter outputter(&collected_results, std::cerr);
> >> >>   outputter.write ();
> >> >>
> >> >>>I see the distinction between FEniCS developers who have programming versus
> >> >>>math in mind when designing the api ;)
> >> >>
> >> >>It's always been one of the top priorities in our work on FEniCS to
> >> >>build an API with the highest possible level of mathematical
> >> >>expressiveness to the API. That sometimes leads to challenges, like
> >> >>needing to develop a special form language, form compilers, JIT
> >> >>compilation, the Expression class etc, but that's the sort of thing
> >> >>we're pretty good at and one of the main selling points of FEniCS.
> >> >>
> >> >
> >> >This is an exaggeration to me. The code
> >> >
> >> >   problem = [Linear]VariationalProblem(a, L)
> >> >   u = problem.solve()
> >> >
> >> >is compact and explicit. It's a stretch to call it ugly.
> >
> > Yes, of course it's a stretch. It's not very ugly, but enough to
> > bother me.
> >
> >> >>>Also __eq__ is already used in ufl.Form to compare two forms.
> >> >>
> >> >>I think it would be worth replacing the use of form0 == form1 by
> >> >>repr(form0) == repr(form1) in UFL to be able to use __eq__ for this:
> >> >>
> >> >>class Equation:
> >> >>   def __init__(self, lhs, rhs):
> >> >>       self.lhs = lhs
> >> >>       self.rhs = rhs
> >> >>
> >> >>class Form:
> >> >>
> >> >>   def __eq__(self, other):
> >> >>       return Equation(self, other)
> >> >>
> >> >>I understand there are other priorities, and others don't care as much
> >> >>as I do about how fancy we can make the DOLFIN Python and C++ interface,
> >> >>but I think this would make a nice final touch to the interface.
> >> >>
> >> >
> >> >I don't see value in it. In fact the opposite - it introduces complexity
> >> >and a degree of ambiguity.
> >
> > Complexity yes (but not much, it would require say around 50-100
> > additional lines of code that I will gladly contribute), but I don't
> > think it's ambiguous. We could perform very rigorous and helpful
> > checks on the input arguments.
> >
> >> Evidently, we all see things differently. I fully support Anders in
> >> that mathematical expressiveness is one of the key features of
> >> FEniCS, and I think that without pushing these types of boundaries
> >> with regard to the language, it will end up as yet another finite
> >> element library.
> >>
> >> Could we compromise on having the two versions, one explicit (based
> >> on LinearVariational[Problem|Solver] or something of the kind) and
> >> one terse (based on solve(x == y)) ?
> >
> > That's what I'm suggesting. The solve(x == y) would just rely on the
> > more "explicit" version and do
> >
> >  <lots of checks>
> >  LinearVariationalSolver solver(x, y, ...);
> >  solver.solve(u);
> >
> > So in essence what I'm asking for is please let me add that tiny layer
> > on top of what we already have + remove the Problem classes (replaced
> > by the Solver classes).
> >
> >
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