On 23 May 2010 15:08, Garth N. Wells<gnw20@xxxxxxxxx> wrote:
On 23/05/10 13:58, Kristian Oelgaard wrote:
On 23 May 2010 12:51, Kristian Oelgaard<k.b.oelgaard@xxxxxxxxx> wrote:
On 23 May 2010 12:14, Garth N. Wells<gnw20@xxxxxxxxx> wrote:
Where are we at with attaching data to integrals? The quadrature order
can
be attached, but I's like to do:
dS({"representation": "tensor"})
Is this supported by FFC?
It looks like this is already supported in FFC.
Note that the representation must be the same on each subdomain (this
is also a requirement for quadrature_degree).
dS(0, {"representation": "tensor"}) + dS(0, {"representation":
"quadrature"})
is not possible, but
dS(1, {"representation": "tensor"}) + dS(0, {"representation":
"quadrature"})
OK.
dS(0, {"representation": "tensor"}) \
+ dS(0, {"representation": "tensor"})
works, but
dS({"representation": "tensor"}) \
+ dS({"representation": "tensor"})
doesn't. Seems like a bug.
It's because domain_id is not a keyword argument in the __call__
function of Measure.
I changed this such that you can do:
dS(metadata={"representation": "tensor"}) \
+ dS(metadata={"representation": "tensor"})
Turns out I can't use this anyway because facet normals are not supported by
FFC with the tensor representation,
ffc.tensor.monomialextraction.MonomialException: No handler defined for
terminal FacetNormal
I don't know if this is just because it is not implemented yet, or
because it is not possible to support this with
tensor representation.
