[yt-users] Covering Grid Dimensions: multiple refinement levels

[Michael Zingale]

I've done this in the past:

ref = int(np.product(ds.ref_factors[0:max_level]))


# allocate for our uniformly-gridded result
dims = ds.domain_dimensions*ref

this will work for a more general case when the jump between levels can
change as a function of level.

On Thu, Nov 19, 2015 at 9:10 AM, Carla Bernhardt <
carla.j.bernhardt at gmail.com> wrote:

> Dear YT Users,
>
> To better understand covering_grid (or smoothed_covering_grid), can
> someone explain what dimensions I should use when I have multiple levels of
> refinement? If I have 1 level of refinement from AMR data, the dimensions
> should be the same, I believe, but what if I have 2 or 3 levels of
> refinement? Should the fixed resolution region then have dimensions of
> dims*2^2 and dims*3^2 respectively?
>
> Here is one example from a tutorial
> <http://yt-project.org/doc/examining/low_level_inspection.html#examining-grid-data-in-a-fixed-resolution-array>
> if that helps isolate my question:
> all_data_level_2 = ds.covering_grid(level=2, left_edge=[0,0.0,0.0],
>                                       dims=ds.domain_dimensions * 2**2)
>
> Thanks in advance,
> Carla
>
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>


-- 
Michael Zingale
Associate Professor

Dept. of Physics & Astronomy • Stony Brook University • Stony Brook, NY
11794-3800
*phone*:  631-632-8225
*e-mail*: Michael.Zingale at stonybrook.edu
*web*: http://www.astro.sunysb.edu/mzingale
github: http://github.com/zingale
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