Daniel,
first, please replace the email address for the mailing list in your
browser: it is [EMAIL PROTECTED] The old address is obsolete.
it seems to me, that the following smoothing algorithms make sense in 1D:
/ limit_level_difference_at_vertices
eliminate_unrefined_islands
patch_level_1
coarsest_level_1
eliminate_refined_inner_islands
eliminate_refined_boundary_islands
do_not_produce_unrefined_islands
Additionally, these should do the proper things in 1D as well.
smoothing_on_refinement
smoothing_on_coarsening
maximum_smoothing
I think, what you describe is the first method only. If you want to
implement any of those, I suggest to read the source code as well as the
docs.
On the other hand, the documentation is a bit bold there: if your error
estimator does not indicate refinement, yhere should be no degradation
of accuracy. That is, if it IS a reliable and efficient estimator.
Therefore, I'd suggest you try without smoothing.
Best,
Guido
/Daniel Goldberg wrote:
> Hi all
>
> I'm using a 1D model to try to test out an a posteriori estimator (I
> figure 1D will make it easier to identify whether the estimator is
> more effective than a generic one, and also I have some nice
> quasi-analytic 1D solutions). I realized that there is no mesh
> regularization implemented for the call to the 1-D version of
> prepare_coarsening_and_refinement(), which could degrade accuracy, right?
>
> I figure it should not be so difficult to implement the regularization
> step in 1D on my own, but I was wondering if I could get some
> assistance from someone who has tried it or thought about it? Would I
> do a similar reverse sweep, from highest down to (2nd) lowest level,
> to the one described in the docs, where at each level I check that if
> a cell's level after refinement would be 2 higher than that of its
> neighboring cell, then the neighboring cell is marked for refinement?
> And I noticed the fix_coarsen_flags() function is called even in 1D..
> would it just need to be called once after the aforementioned sweep?
>
> Thanks very much,
> Dan
>
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