[yt-users] Nearest neighbours

[Matthew Turk]

Hi Elizabeth,

We have an "extract_connected_sets" routine that may work for what you
are doing.  This is what the clump finder is built on.  You can supply
it a threshold, and it will conduct FOF on the cells, returning
objects (and boundary values) that satisfy it.  Unfortunately, right
now it only works with threshholding in one dimension.  So, what you
can do is define a field that returns 1/0 for whether it should be
included, and then perform the contouring with extract_connected_sets
on your initial data object.

-Matt

On Tue, Sep 13, 2011 at 5:22 PM, Elizabeth Tasker <taskere at mcmaster.ca> wrote:
> Hi Matt and Sam,
>
> I just want to do a friends-of-friends scheme where I add cells to an
> ordered list if their properties (density, Potential field etc) satisfy my
> criteria.
>
> Unfortunately, that does mean that I might walk completely off one grid,
> ghost zones and all, and onto another one, so I think what Matt suggests
> below only buys me a few extra steps.
>
> Sam, your routine probably was what I was thinking of, but my question
> wasn't supposed to cause extra work! It was more a "does this exist and
> everyone is using it apart from me?" query. I'll keep with extracted grids
> and then if I run into issues or this later morphs into a useful analysis
> routine that people want to use or parallelise, perhaps we'll revisit the
> question of using trees.
>
> Thanks again,
>
> Elizabeth
>
> Matthew Turk wrote:
>>
>> Elizabeth,
>>
>> If you request ghost zones you can do this.  In particular, requested
>> unsmoothed ghost zones will ensure no interpolation occurs.  You can
>> do this either by yourself, grid by grid with
>> grid_obj.retrieve_ghost_zones(...) or you can use ValidateSpatial in a
>> field definition.
>>
>> It might help if you shared what kind of operation you want to do once
>> you have the 26.  If you have the index of a cell, you can just
>> access:
>>
>> grid[field][index_i+1, index_j+1, index_k+1]
>>
>> and do the +/- and 0/1 modifications.
>>
>> -Matt
>>
>> On Tue, Sep 13, 2011 at 5:04 PM, Elizabeth Tasker <taskere at mcmaster.ca>
>> wrote:
>>
>>>
>>> Hi Stephen,
>>>
>>> Honestly, I was just hoping there was some magically pre-programmed way
>>> to
>>> grab the 26 most refined neighbours of a cell, regardless of which grid
>>> they
>>> were on or level that happened to be. Mapping to an extracted region is
>>> no
>>> hassle, I was just checking there wasn't a smart, quick way of doing this
>>> already.
>>>
>>> Thanks for the info!
>>>
>>> Elizabeth
>>>
>>>
>>>
>>> Stephen Skory wrote:
>>>
>>>>
>>>> Elizabeth,
>>>>
>>>>
>>>>
>>>>>
>>>>> So ... how hard are we talking? :)
>>>>>
>>>>>
>>>>
>>>> The thing is, in all honesty the kdtree we're using in yt (in
>>>> parallelHF and in a few other places) is not very convenient. It's
>>>> written in fortran, so the array orderings are backwards from the rest
>>>> of python (which is C based). It's also confusing to use, it has a
>>>> weird wrapper to access the functions that isn't very easy to
>>>> understand. The only reason we're using it is in my tests I found this
>>>> kdtree implementation to be significantly faster than the alternatives
>>>> out there.
>>>>
>>>> Perhaps if I knew a bit more about what you wanted to do I could help
>>>> you come up with a solution that avoids the kdtree. Are you interested
>>>> in only the nearest 6 touching cells to a cell? Or do you want to look
>>>> at the edges and the corners? Farther out? Do you care about
>>>> periodicity? You mentioned looking at grids of coarser resolution, do
>>>> you still think you'd like to have neighbor cells returned from a
>>>> lower resolution grid?
>>>>
>>>>
>>>>
>>>
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>>>
>>
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