[yt-users] Clump tracking!

Sun Oct 7 09:33:14 PDT 2012

I'll send it off list.  There are a bunch of things in it that don't
work and need some explanation, and I don't want to pollute the list.

Anyone else who wants this thing, chime in.

> When you talk about tracer particles, you mean that you put an "imaginary"

That's exactly right.   So they need to be in before you start the simulations.

d.

> 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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