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-grid-data-in-a-fixed-resolution-array

Hope this helps!

Cameron

On Mon, Aug 7, 2017 at 10:14 PM, Stephanie Tonnesen <stonnes@gmail.com> wrote:

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