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Re: ListTensor

 

On Wed, Mar 4, 2009 at 9:34 AM, Martin Sandve Alnæs <martinal@xxxxxxxxx> wrote:
> On Wed, Mar 4, 2009 at 8:45 AM, Anders Logg <logg@xxxxxxxxx> wrote:
>> On Wed, Mar 04, 2009 at 08:15:53AM +0100, Martin Sandve Alnæs wrote:
>>> On Wed, Mar 4, 2009 at 12:31 AM, Kristian Oelgaard
>>> <k.b.oelgaard@xxxxxxxxxx> wrote:
>>> > Quoting Anders Logg <logg@xxxxxxxxx>:
>>> >
>>> >> On Tue, Mar 03, 2009 at 09:10:50PM +0100, Martin Sandve Alnæs wrote:
>>> >> > On Tue, Mar 3, 2009 at 12:18 AM, Anders Logg <logg@xxxxxxxxx> wrote:
>>> >> > > Is there a way to transform an expression to remove ListTensor from
>>> >> > > the tree? I'm struggling with the monomial transformation.
>>> >> > >
>>> >> > > Take for example the following expression:
>>> >> > >
>>> >> > >  inner(as_tensor([v[0], v[1]]), as_tensor([u[0], u[0].dx(1)]))
>>> >> > >
>>> >> > > This might be rewritten as
>>> >> > >
>>> >> > >  a = v[0]*u[0] + v[1]*u[0].dx(1)
>>> >> > >
>>> >> > > This I can handle, but not the version containing ListTensor.
>>> >> >
>>> >> > You have something similar in FFC, right?
>>> >> > vec and mat or something?
>>> >> > How do you handle those?
>>> >> >
>>> >> > Martin
>>> >>
>>> >> The corresponding thing in FFC is regular Python lists. For example,
>>> >> here's the grad() operator:
>>> >>
>>> >> def grad(v):
>>> >>     "Return gradient of given function."
>>> >>     # Get shape dimension
>>> >>     d = __cell_dimension(v)
>>> >>     # Check if we have a vector
>>> >>     if value_rank(v) == 1:
>>> >>         return [[D(v[i], j) for j in range(d)] for i in range(len(v))]
>>> >>     # Otherwise assume we have a scalar
>>> >>     return [D(v, i) for i in range(d)]
>>> >>
>>> >> At some later point, the list will appear as an argument of a dot
>>> >> product or it might be indexed (with a fixed index). The result of
>>> >> both operations will remove the list and return a scalar expression.
>>> >>
>>> >> So when a form has been defined correctly, the resulting expression is
>>> >> always a scalar which does not contain any lists. What makes this
>>> >> simpler in FFC might be that only fixed indices (ints) are allowed as
>>> >> indices in a list, whereas UFL allows general indices to be used.
>>> >>
>>> >> In particular, the following is not allowed in FFC:
>>> >>
>>> >>   a = grad(v)[i]*grad(u)[i]*dx
>>> >>
>>> >> One must write one of the following:
>>> >>
>>> >>   a = dot(grad(v), grad(u))*dx
>>> >>   a = v.dx(i)*u.dx(i)*dx
>>> >>
>>> >> The important point here is that dot() will pick out the elements in
>>> >> the list one by one and return something that is not a list.
>>> >>
>>> >> I don't know if it would be a too severe restriction to disallow
>>> >> general indices in a ListTensor.
>>> >
>>> > If I understood it correctly, it should be
>>> > 'general indices OF a ListTensor' ??
>>> >
>>> > Kristian
>>>
>>> That's what I think he meant too. And if I understand this
>>> correctly, arbitrary limitations like that is not an option in UFL.
>>> Any tensor _valued_ expression can be indexed, and that's
>>> the way it should be. That's also the whole point of the ListTensor,
>>> to make subexpressions into a tensor valued expression.
>>> The alternative is an inconsistent language and special cases
>>> all over the place. The limitations of the tensor representation
>>> is one of the reasons I got into this in the first place :-P
>>
>> Would it help to expand IndexSum into a sum of terms, adding more Sum
>> nodes to the tree, each one with a fixed index value? This should (at
>> least in some simple cases with limited nesting) result in Indexed
>> nodes with children that are ListTensor and FixedIndex, which would
>> make it possible to just pick out the correct item and remove
>> ListTensor from the tree.
>
> Yes, that's basically what I've been thinking. My thoughts now are:
> 1) Implement a general expand_index_sums, just to get this part right
> 2) Make a specialization of this that only expands the index sums
> where the index ultimately applies to a ListTensor
>
> If you index a ListTensor with a fixed index, the subcomponent is
> already being extracted as a simplification.
>
> Martin

See the latest commit message.

I have to prioritize some other things before improving it further.

Martin


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