Hi Maan, First, thanks for the detailed report, and sorry for taking a couple of days to respond. The basic issue is illustrated by running the following code snippet for both datasets: ad = ds.all_data() mass= ad['gas', 'density'] * ad['index', 'cell_volume'] print(mass.sum().to('Msun')) For snapshot_52, this prints ~2.6*10^15 Msun, but for snapshot_53 it prints 4.1*10^15 Msun. This implies that the SPH smoothing operation used by yt isn't conserving mass very well for your arepo data. One possible cause might be that for Gadget data, yt uses the ('PartType0', 'SmoothingLength') field to evaluate the smoothing kernel during the projection. I don't actually know how arepo generates this field, since presumably not actually doing any SPH smoothing. Perhaps using this field is a bad estimate for arepo data and we should be trying to generate SPH smoothing lengths self-consistently inside yt, like we do for tipsy data? Finally, I went ahead and calculated the smoothed projection using a version of yt that partially implements the "demeshening" effort, where we are trying to eliminate the global octree mesh for particle data. This will hopefully be part of what will be called yt either yt 3.4 or yt 4.0 (we haven't discussed yet whether this change is big enough to warrant a major version bump). This is an in-development version of yt that is partially broken - I had to add some ugly hacks to produce these images - and is unfortunately not yet ready for general use. That said, it gives you an idea of what we're working toward here. Here's what the projections look like in the demeshening: snapshot_052: http://i.imgur.com/z9fhN7R.png snapshot_053: http://i.imgur.com/ZWZIW3B.png Note that the demeshening work will also make it much easier to add a slice and projection pixelizer that is aware of the voronoi mesh. In fact, if you're interested in contributing, I think that would be a great place to start hacking on yt for someone who works with arepo data. Sorry to not have a conclusive, satisfying answer for you. I hope that gives you some more context on the limitations of the current support for arepo data in yt. -Nathan On Wed, Nov 2, 2016 at 3:17 PM, Maan Hani <mhani@uvic.ca> wrote:
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