[yt-dev] Downgrading Grid Resolution in yt
matthewturk at gmail.com
Fri Jun 1 08:50:49 PDT 2012
On Fri, Jun 1, 2012 at 11:53 AM, Cameron Hummels
<chummels at astro.columbia.edu> wrote:
> Hello everyone,
> Does anyone know of a way to universally downgrade the grid refinement by 1
> level in yt (for an enzo output)? I know that one can resample an output to
> any arbitrary maximum refinement level using a covering grid (or a smoothed
> covering grid), but the result only "downgrades" data at the highest levels
> of refinement. What I'm instead looking for is a method to "downgrade" the
> resolution of the data at every grid element regardless of its refinement.
> For example, if I have a two adjacent grids, one with 10 levels of
> refinement and the other with 3, I would like them resampled at 9 and 2,
> respectively, as opposed to 9 and 3, which is what happens in the case of
> the covering grid. Additionally, it might be nice to retain the AMR
> structure of the original output, so that the memory consumption is
> relatively low (much lower than an equivalent covering grid).
> This technique would be very useful for resolution studies to determine the
> effects of poorer resolution on post-processing analysis. Anyway, has
> anyone played around with this? If not, I'll look into writing something up
> in the next few weeks, but I figured I'd ask.
This might be a dumb question, but have you looked at examining the
grid cells that your level 10 grid covers at level 9?
I also believe that if you ask for a covering grid at level 9, and it
covers grids at level 10, it will not use the level 10 grids when
calculating the constituent values. There's this trick we do to
figure out if the child masking should be taken into account with
covering grids, and the criteria is: is this the final level we want
to sample to?
> Cameron Hummels
> PhD Candidate, Astronomy Department of Columbia University
> Public Outreach Director, Astronomy Department of Columbia University
> NASA IYA New York State Student Ambassador
> PGP: 0x06F886E3
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