Hi Stephanie,
I've not heard of this bug, but I've had some difficulty with
arbitrary_grids in the past. You might try using a covering_grid instead
of an arbitrary_grid object since it is designed with grid-based datasets
in mind whereas arbitrary_grids are more suited to particle-based
datasets. This will give you a uniform grid at whatever resolution you
desire (200 pc). If that doesn't work, perhaps it is a problem with your
user-defined fields? But given that it works with cut_regions, I think
it's unlikely to be your field definition.
http://yt-project.org/docs/dev/examining/low_level_inspection.html#examining...
Hope this helps!
Cameron
On Mon, Aug 7, 2017 at 10:14 PM, Stephanie Tonnesen
Hi yt-users!
I have a simulation run on Enzo that has a best resolution cell size of ~40 pc. I would like to be able to compare my run to observations that are at a resolution of ~200 pc. I want to save a bunch of data in a fits file with that resolution. It looks like the way to do this is to create an arbitrary_grid object. If someone has a better method, please tell me!
So I have my artbitrary_grid object, and I am making arrays of fields:
xp = arbgridobj['x'] ...etc....
xp = np.array(xp) ...etc...
my code keeps crashing when I try to get a user-defined field for my arbitrary_grid object. If I try to get the field for a cut_region my code runs just fine. Is user-defined fields + arbitrary_grid objects just something that yt can't do or is there some different way to make this happen than in a cut_region?
Thanks!!
Best, Stephanie
-- Dr. Stephanie Tonnesen Alvin E. Nashman Postdoctoral Fellow Carnegie Observatories, Pasadena, CA stonnes@gmail.com
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-- Cameron Hummels NSF Postdoctoral Fellow Department of Astronomy California Institute of Technology http://chummels.org