[yt-dev] Confusing distribution of the number of particles per octree node

[Bili Dong - Gmail]

Oh I see. Thank you for clarifying this! Now I recall that it's actually
written in the doc. I just didn't truly understand it when I read it before.

-Bili

On Thu, Feb 4, 2016 at 11:13 AM, Matthew Turk <matthewturk at gmail.com> wrote:

> Hi Bili,
>
> I've looked into this, and I think the issue is that a given oct is
> refined based on the numebr of particles in it, but the way that the count
> is done is based on the number of cells.  If you change to
> over_refine_factor=0 (so that the number of cells is the same as the number
> of octs) then you get n_p mean of about 16, which should be okay.
>
> My check of this can be seen here, where I experimented with setting it to
> 2, instead of 1 (default) or 0.
>
> http://paste.yt-project.org/show/6218/
>
> -Matt
>
> On Thu, Feb 4, 2016 at 12:57 PM, Bili Dong - Gmail <qobilidop at gmail.com>
> wrote:
>
>> Hi all,
>>
>> I'm looking at the number of particles per octree node (n_p hereafter)
>> (a.k.a. the ('deposit', 'all_count') field) and find the results confusing.
>> To my understanding, an octree node is refined (into 8 sub-nodes) only when
>> n_p (of that node) > n_ref, so eventually n_p.mean (the average value of
>> n_p) should be greater than n_ref/8. But the number I get is much smaller.
>> When n_ref = 64, I get n_p.mean approximately 2 for all my tests.
>>
>> I'm wondering if my understanding of the octree refining process if
>> correct? And if so, how to explain the weird distribution of n_p?
>>
>> Here's the link to my tests:
>> https://nbviewer.jupyter.org/gist/qobilidop/d8f4cb85f1b465770854
>>
>> Thanks,
>> Bili
>>
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>>
>
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