Actually, I have a question about this. I may have asked this before, so
forgive me if I repeat.
Suppose my exact solution is sin(2*pi*x). I would like to compute the
exact error against this function. Is this doable? I know you can
resample it with a higher order function, but that is lame! Can't FFC
treat it like a linear form and use quadrature to evaluate it? I know it
isn't really a linear form, but FFC wouldn't know the difference! :)
Maybe I am missing something...
- Shawn
On Wed, 10 Jun 2009, Martin Sandve Alnæs wrote:
The norm definitions should use "inner" instead of "dot" to handle
tensor fields as well.
Martin
On Wed, Jun 10, 2009 at 6:14 PM, Anders Logg<l...@simula.no> wrote:
On Wed, Jun 10, 2009 at 09:58:20AM -0500, Jehanzeb Hameed wrote:
Thanks. So I guess that means no such facility is available in C/C++ ?
No, since the computation depends on the space the functions are in
and so the code needs to be generated. In C++, you need to define a
form file for the norm. Look at
site-packages/dolfin/norm.py
for how to define the norms.
--
Anders
On Wed, Jun 10, 2009 at 2:03 AM, Anders Logg<l...@simula.no> wrote:
On Tue, Jun 09, 2009 at 05:11:48PM -0500, Jehanzeb Hameed wrote:
Hello,
Is there a builtin function in dolfin to compute L^2 or H_1 norms? If
so, can you please point it out. If not, are there support functions
(e.g. a Gauss Quadrature table, computation of Jacobians, etc) which
can help in this?
Yes, this is available in the DOLFIN Python interface:
norm(v)
The default computes the L^2 norm. Several options are available:
L^2: norm(v, 'L2')
H^1: norm(v, 'H1') includes L^2 term
H^1_0: norm(v, 'H10') does not include L^2 term
H(div): norm(v, 'Hdiv') includes L^2 term
H(div): norm(v, 'Hdiv0') does not include L^2 term
H(curl): norm(v, 'Hcurl') includes L^2 term
H(curl): norm(v, 'Hcurl0') does not include L^2 term
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