[yt-users] Nearest neighbours

[Elizabeth Tasker]

Hi Matt,

I actually use that to get my initial sweep of objects and it works 
great. This next step through it more complex than just a contour, since 
it's not obvious what my boundary line will be: it depends on the 
environment of each object which gives saddle points in the potential 
field. (This is why this program is taking me a while. *One day* it will 
be complete and work and I will win at life. Yes.)

I'm good with covering grids, honest. I was just seeing if I could be 
smarter easily.

Elizabeth



Matthew Turk wrote:
> 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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