[yt-users] Clump tracking!

Sun Oct 7 08:28:06 PDT 2012

It would be awesome if you could send me your code! I am sure it would 
be of quite some help to take at least a look at it. And yes, I really 
hope that I won't run into a lot of problems with my systems. Even 
though I got some thousand snapshots, I have access to nice server, 
where i can grab at least 64 cores where I can track the clumps from 
different clusters simutanously, so this is hopefully no problem.

When you talk about tracer particles, you mean that you put an 
"imaginary" particle in e.g. every cell and let it follow the velocity 
field to determine where the cells that make up a clump end up?

Best regards,
Patrick

Am 06.10.2012 19:11, schrieb David Collins:
> Yeah, clump tracking is one of the logs in my project log jam right
> now.  As Eve said, I also had problems with mass stability because of
> the definition of "clump."   Elizabeth Tasker has had success with
> tracking clumps in her disk galaxy simulations--she does a single
> density threshold for the clump definition and center of mass
> trajectory to track clumps, and those results seem pretty solid.  So
> it may work for some systems.  Her flow is relatively laminar,
> especially at the beginning, which I believe makes the problem much
> easier. I imagine you will have a similar
> problem with significant fluctuations in galaxy clusters, though the
> turbulence is of a lower mach number than I was dealing with, so it
> might not be so bad.
>
> I initially did something basically as you described-- pickle the
> clumps to disk, simple n^2 loop, comparing time-advanced center of
> mass from clumps in t=1 to extents in t=2.  I would recommend against
> eliminating based on mass since you don't have a surface that's
> actually legrangian.   For my purposes, n^2 was fast enough since I
> only had a few hundred timsteps and a few hundred clumps in each
> snapshot.  Ran in an hour or two.  I can send you my code, but I'm
> quite sure the effort to get my overly complicated 3 year old thing
> running again is higher than doing it fresh.
>
> It is true that I've been looking at using tracer particles.  I can't
> tell if it works yet.  It's either super cool or totally useless.
>
> d.
>
> On Sat, Oct 6, 2012 at 2:30 AM, Eve Lee <evelee at berkeley.edu> wrote:
>> Hi Patrick,
>>
>> I did something very similar when I tried to track clumps (molecular clump
>> in star formation simulation in my case) using the centre of mass of the
>> clump (we ended up using the position of the densest pixel instead of the
>> centre of mass since CoM tracking gave a huge fluctuation in mass) and using
>> the velocity vector of that centre to infer the direction of the progenitor
>> of that clump.
>>
>> What I noticed was that the mass is still quite unstable due to the
>> intrinsic definition of the clump. I found that starting lv 3, the mass
>> fluctuation is so great I couldn't trust my tracking any more. I'm not sure
>> if you'll encounter the same problem.
>>
>> David Collins has been working on this extensively using tracer particles so
>> he should be able to help you more.
>>
>> Best Regards,
>>
>> Eve
>>
>>
>> On 10/5/2012 4:15 PM, Patrick Rieser wrote:
>>> As I am running a little bit out of time to finish this, I thought about
>>> doint this the simple and "brute force" way.
>>> So this is the current plan: I am going to iterate through all snapshots
>>> we have, and write out all clump objects with pickle. Starting at snapshot 0
>>> i am going to estimate the position of the center of mass of the clump in
>>> the new snapshot using it's bulk velocity and see if I can find the clump in
>>> the surrounding area (looping through all clumps in the following snapshot).
>>> If I find one or more, I will compare the mass and identify it as the same
>>> or not (if the mass doesn't match maybe i check if a second one vanished).
>>> This might not be a very elegant way, but I hope it works for our system
>>> (galaxy cluster). I am quite new to this stuff, so if I got any horrible
>>> mistakes here, please correct me.
>>>
>>>> For instance, we include a Cython
>>>> kD-tree that we use to provide a nearest-neighbor search when doing
>>>> merger trees.
>>>
>>> Thanks, I will take a look into that!
>>>
>>>
>>>> and you didn't
>>>> want to go full-on "lagrangian coherent structures"
>>>
>>> I took a look at it and it seems really interesting. It's really a pity I
>>> don't have enough time at the moment.
>>>
>>> best wishes,
>>> Patrick
>>>
>>>
>>>
>>> On 2012-10-05 18:07, Matthew Turk wrote:
>>>> Hi Patrick,
>>>>
>>>> Thanks for writing, and welcome to yt-users.  :)
>>>>
>>>> On Thu, Oct 4, 2012 at 9:42 AM, Patrick Rieser
>>>> <patrick.rieser at uibk.ac.at> wrote:
>>>>> Heya everyone!
>>>>>
>>>>> I am trying to track clumps across multiple snapshots (from flash). Now
>>>>> my
>>>>> questions is, has anybody done something like this and would be willing
>>>>> to
>>>>> share his/her code?
>>>> David Collins wrote some code that did this, a couple years ago.  I
>>>> don't know the current status.
>>>>
>>>> If you wanted to write a new set of code to do this (and you didn't
>>>> want to go full-on "lagrangian coherent structures") there are some
>>>> things in yt that could help out.  For instance, we include a Cython
>>>> kD-tree that we use to provide a nearest-neighbor search when doing
>>>> merger trees.  This is used in a very simple way in the code in
>>>> yt/analysis_modules/halo_merger_tree/enzofof_merger_tree.py , where
>>>> halos are loaded into a variable called halo_kdtree.  This then gets
>>>> searched with a ball query.  You could in principle load the clumps
>>>> into the same kdtree structure, perform the search, and then apply
>>>> selection criteria for clump tracking based on that.  (Of course this
>>>> is just the first step in identifying clump motion -- but it would be
>>>> a way to reduce from N^2 searching.)
>>>>
>>>> Let us know if you run into any tricks or have any successes -- this
>>>> is a pretty cool idea, and I'd love to see where it leads you!
>>>>
>>>> -Matt
>>>>
>>>>> Best Wishes,
>>>>> Patrick
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