[Yt-dev] RMS mass overdensity method

[Stephen Skory]

Hi,

> - in _get_over_density(), I am using the pf.h.sphere() method to cut out the 
> particles inside the smoothing sphere, but I'm not sure I want to do this. I'm 
> aware that as it is it won't work using the _partition_hierarchy_3d method. Can 
> you give me a suggestion of the 'right' way to do this? I'd wonder if investing 
> time in the KDtree scipy stuff Matt emailed about earlier is worth it, but we 
> already have this domain decomposition plus oversampling machinery, and we 
> definitely need the oversampling for this method. And domain decomposition makes 
> data reading so much faster.

I thought about this some more, and it's obvious what is a better way to go. If pf.h.sphere() is a 'good' way to do this, for each task it should operate on pf, and skip the _partition_heirarchy_3d .data_source, but only choose a random center in its own sub-region. This will eliminate the over-sampling required in the interior sub-regions, but the edges still need padding. Does this make sense?

Alternatively, if doing this domain decomposition and then randomly choosing centers granulates the randomness, which I frankly don't think is a problem, I could pre-build a list of random centers and each task would only use ones it owns.

Thanks!

 _______________________________________________________
sskory at physics.ucsd.edu           o__  Stephen Skory
http://physics.ucsd.edu/~sskory/ _.>/ _Graduate Student
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