dolfin team mailing list archive

[Johan Hake <hake@xxxxxxxxx>]

On Tuesday 04 November 2008 15:49:37 Martin Sandve Alnæs wrote:
> 2008/11/4 Martin Sandve Alnæs <martinal@xxxxxxxxx>:
> > 2008/11/4 Johan Hake <hake@xxxxxxxxx>:
> >> On Tuesday 04 November 2008 13:59:22 Martin Sandve Alnæs wrote:
> >>> 2008/11/4 Johan Hake <hake@xxxxxxxxx>:
> >>> > On Tuesday 04 November 2008 13:07:07 Martin Sandve Alnæs wrote:
> >>> >> 2008/11/4 Johan Hake <hake@xxxxxxxxx>:
> >>> >> > Hello!
> >>> >> >
> >>> >> > I have started the work on the PyDOLFIN. We can now define the
> >>> >> > forms in the poisson demo, using the syntax previously discussed,
> >>> >> > see python poisson demo.
> >>> >> >
> >>> >> > A FunctionSpace now inherits both dolfin::FunctionSpace and
> >>> >> > ffc.FiniteElement, and it can be used to instantiate user defined
> >>> >> > Functions which can be used to define forms.
> >>> >> >
> >>> >> > We need to discuss how to implement a discrete function. This is a
> >>> >> > bit complicated using the metaclass magic that is implemented now.
> >>> >> > Now we cannot do:
> >>> >> >
> >>> >> >  u = Function(V)
> >>> >> >  x = u.vector()
> >>> >> >
> >>> >> > as Function is just a dummy class for creation of userdefined
> >>> >> > functions.
> >>>
> >>> I don't quite understand the problem here.
> >>> Are you saying that type(u) is not a subclass of cpp_Function or what?
> >>
> >> With the metaclass implementation, Function cannot inherit cpp_Function
> >> or ffc.Function. A derived class of Function will inherit Function,
> >> cpp_Function and ffc.Function though. Function is as it is now, only an
> >> more or less empty class that can be inherited.
> >>
> >> The syntax above can be valid with some __new__ magic in Function,
> >> probably much in line with what you had in mind.
> >>
> >>> >> We don't have to use metaclasses, it would be enough to implement
> >>> >> Function.__new__(cls, *args). This function can return objects of
> >>> >> a different type, e.g. a compiled function that doesn't inherit from
> >>> >> dolfin.Function but directly from dolfin::Function.
> >>> >
> >>> > and from ufl.Function too?
> >>>
> >>> Yes.
> >>>
> >>> >> (I didn't understand this stuff fully until last week...)
> >>> >
> >>> > Yes I have thought about that solution, but then the created class
> >>> > wont be a Function. It can be handy to have a class that all python
> >>> > Function can be checked if isinstance of. With the __new__ function
> >>> > we create different classes.
> >>>
> >>> This is not a problem. On the contrary, you either wish to
> >>> check if a function is a cpp_Function or a ufl.Function.
> >>> I would consider "isinstance(f, dolfin.Function)" a bug in
> >>> most circumstances. That's one of the things I don't
> >>> like about this design...
> >>
> >> Yes, but if you check if u is a Function you allready know it is a
> >> cpp_Function _and_ an ufl.Function. Just one to keep in mind ;)
> >
> > That's the bug right there. You (almost) never want to check for a
> > dolfin.Function, because you're usually _either_ working with
> > ufl.Function functionality _or_ working with cpp_Function functionality.
> > Checking for dolfin.Function is then _wrong_, since a real ufl.Function
> > or cpp_Function won't pass the test.

Ok, you are right.

Then I realise that we do not need the dolfin.Function class, other than to 
produce user defined functors, in python and compiled ones, and for 
instantiate a discrete function, where all of these functions also are 
ufl/ffc.Functions.

We agree on this?

Then we need to deside how we will implement it, through metaclasses or 
__new__.

For functors defined in python the syntax will be the same for both 
alternatives and the same as today, but they are instantiated by a 
FunctionSpace.

For compiled functions this can either be done more or less as it is today:

  function_list = compile_functions(["exp(alpha)",
                     ("sin(x[0])", "cos(x[1])", "0.0"),
                     (("sin(x[0])", "cos(x[1])"), ("0.0", "1.0"))],
                     [V1, V2, V3])

  f1, f2, f3 = tuple(function_list)

or with metafunctions:

  class MyFunction1(Function):
      cppcode = "exp(alpha)"

  class MyFunction2(Function):
      cppcode = ("sin(x[0])", "cos(x[1])", "0.0")

  class MyFunction3(Function):
      cppcode = (("sin(x[0])", "cos(x[1])"), ("0.0", "1.0"))

  f1 = MyFunction1(V1)
  f2 = MyFunction2(V2)
  f3 = MyFunction3(V3)

The syntax for a discrete function would also be looking the same.

> >>> > The advantage, as I see it with your suggestion would be that we can
> >>> > use the present feature of compiling many functions at a time, but we
> >>> > loose the consistent syntax:
> >>> >
> >>> >  class MyFunction(Function):
> >>> >      def eval(v,x):
> >>> >           do something
> >>> >
> >>> >  class MyCompiledFunction(Function):
> >>> >      cpp_code = do something
> >>> >
> >>> >  f = MyFunction(V)
> >>> >  g = MyCompiledFunction(V)
> >>> >
> >>> > and it could be complicated to pass the right FunctionSpaces to the
> >>> > compile_function function.
> >>>
> >>> I forgot about this syntax. It's nice, but personally I'll be fine
> >>> without it :-)
> >>>
> >>> >> > Is it possible to define a DiscreteFunction class in c++ (or just
> >>> >> > in swig?) that inherits dolfin::Function, and in its constructor
> >>> >> > calls vector()?
> >>> >> >
> >>> >> > Then we can use this class in python to create discrete functions.
> >>> >> > We then avoid the director class that is created by swig for all
> >>> >> > functions that inherits the cpp_Function. The obvious syntax would
> >>> >> > then be
> >>> >> >
> >>> >> >  u = DiscreteFunction(V)
> >>> >> >
> >>> >> > in python. I think with some python magic we still can have the
> >>> >> > syntax
> >>> >> >
> >>> >> >  u = Function(V)
> >>> >> >
> >>> >> > which would imply that a discrete function is created, but I
> >>> >> > haven't implemented it.
> >>> >>
> >>> >> That would basically be duplicating the design that has been
> >>> >> replaced... I think dropping the metaclass is a much easier
> >>> >> solution.
> >>> >
> >>> > No, this is just for the python interface. This could come handy with
> >>> > the __new__ implementation you want too. By this we circumvent the
> >>> > director class that swig creates for dolfin::functions. We dont want
> >>> > to call eval on such a class to often do we? :)
> >>> >
> >>> >> > We also have a problem with MixedElements. Now the FunctionSpace
> >>> >> > inherits ffc.FiniteElement and a MixedElement is not a
> >>> >> > FiniteElement. I suppose we could overload the __add__ operator
> >>> >> > for the FunctionSpace together with a new class
> >>> >> > MixedFunctionSpace, to fix this?
> >>> >> >
> >>> >> > Johan
> >>> >>
> >>> >> We also have (in UFL at least) the classes VectorElement and
> >>> >> TensorElement, so this gets complicated. I think we should just make
> >>> >> FunctionSpace own an element instead.
> >>> >>
> >>> >> element = FiniteElement(...)
> >>> >> V = FunctionSpace(mesh, element)
> >>> >> f = Function(V) # calls FiniteElement.__init__(self, element)
> >>> >
> >>> > Thats looks nice. We could also use the syntax Anders suggested,
> >>> >
> >>> >  V = FunctionSpace(mesh, "Lagrange", 1)
> >>> >
> >>> > and then instantiate the FiniteElement in the __init__ function.
> >>>
> >>> No, we can't, that's exactly the issue you brought up with
> >>> MixedElement. ("Lagrange", 1) doesn't carry all information about an
> >>> element. In UFL we have classes FiniteElement, MixedElement,
> >>> VectorElement, and TensorElement. In addition to
> >>> (family,domain,degree), a
> >>> VectorElement can have a dim, and a TensorElement
> >>> can have a shape and symmetries...
> >>
> >> Of course :P
> >>
> >> But would it be possible to create a MixedFunctionSpace by adding two
> >> other function spaces, with some overloading of __add__? And would it be
> >> possible to extend the initialization of FunctionSpace, with kwargs and
> >> some __new__ magic, to instantiate FunctionSpace of different elements?
> >
> > If you do that, you suddenly get a hierarchy of FunctionSpace classes.
> > My challenge to Anders would then be:
> >
> > V1 = TensorFunctionSpace(mesh, "CG", 2) # , shape=(2,2),
> > symmetry=True) # optional args
> > V2 = VectorFunctionSpace(mesh, "CG", 1) #, dim=2) # optional args
> > V3 = FunctionSpace(mesh, "DG", 0)
> > V = MixedFunctionSpace(V1, V2, V3)
> >
> > Here each of these will be a new cpp_FunctionSpace,
> > calling jit and constructing dofmaps and whatnot.
> > It seems possible, but...
> >
> >> Maybee more relevant do we want it?
> >
> > Anders does.

:)

> >>> > This wont work for the basis functions though, but we could just add
> >>> > a class that inherits the ffc.BasisFunction and which can be
> >>> > instantiated with both a FunctionSpace and a FiniteElement.
> >>>
> >>> We'd need to consider both BasisFunction, and BasisFunctions, which is
> >>> a function and a bit more complicated. Also TestFunction(s) and
> >>> TrialFunction(s), but those are just syntactic sugar.
> >>
> >> Ok.
> >>
> >>> I'd very much prefer letting BasisFunction be and just passing it an
> >>> element.
> >>
> >> I see you point.
> >
> > In particular, what happens with
> >    t, v, s = BasisFunctions(V)
> > with V a mixed function space like above?
> > That's getting quite difficult to follow.
> >
> >
> > But my largest concern is that inheriting from ufl classes and
> > overriding their behaviour may have unanticipated effects inside UFL.
> > For example, operators like +-*/ can't be implemented on a
> > dolfin.Function or cpp_Function.
>
> Speaking of which, does FunctionSpace and Function need to implement
> __repr__? If so, why? It won't work anyway since it just uses the string
> "mesh". In UFL I've used repr for quite a few things, and this would break
> a lot.

Yes I thought that could be problematic, but repr on the resulting form 
produced a "nice" representation, (it is eventually that is used by ffc?) so 
I thought I implemented a more verbal __repr__ and __str__, as the default 
repr was the swig generated one. 

If we need ufl's repr we just change the order of the bases in the bases 
tuple, and _not_ implement a repr.

Johan