A testing pipeline that allows us to run a behavioural phenotyping of our virtual worm running the same test statistics the Schafer Lab used on their worm data.
You can go to settings and in the "danger zone" delete the repo.
Thanks again for the updates! Feel free to use github to push more updates to segworm if it's being actively worked on. Next step is probably to identify areas where the Open Worm Analysis Toolbox needs to be brought into sync with your ~3 years of changes...
I've put an issue up on the OWAT repository for this: openworm/open-worm-analysis-toolbox#189
thanks!
Necessary* Skillset. I have been told to go he in the main Chat... So how can I be of help, do you have any beginner project/tasks?
For #113, I agree with your suggestion that converting from WCON to BDML will be easier than the reverse, so if you start with that it would be awesome!
You'll probably still have questions - if you do please feel free to set up a quick meeting by google hangouts with me using http://www.meetme.so/MichaelCurrie
Or just chat away on here if you prefer
Cheers! Thanks for your interest!
@MichaelCurrie I have a question about outputing the data as an ordered dictionary... From what I understand the dic cotains subdics, each representing a worm, my question is how those subdictionarys arranged, are the Indexed by timestep (Like BDML)? Or is there some other arrangement? Any way the way to convert the data to BDML is probably by two nested loops, the outer loop loops over the worms and the inner loop loops over the data and generates the XML file.
The biggest issue is the fact that BDML requires a sort of graphical representaition for each object, which means we must create one for each worm, proceduraly. Cronin, Et al. create such a thing by patching together a bunch of lines, I hope Dr. Ken Ho can help us with such a thing.
Hi @ido77778! The format is discussed in detail here https://github.com/openworm/tracker-commons/blob/master/WCON_format.md and the schema is here. The part of the schema relevant to your question is the "data" part.
However, rather than writing a tool to parse WCON files yourself, I highly recommend you use https://github.com/openworm/tracker-commons/tree/master/src/Python or one of the other languages available here: https://github.com/openworm/tracker-commons/tree/master/src.
I wrote the Python version and I can say that you would do something like
import wcon; w = wcon.WCONWorms.load_from_file('test_file.wcon')
then, you can access the worm's data as a pandas dataframe.
just play with the
w object in your python shell to see what's possible
or look at the API here: https://github.com/openworm/tracker-commons/tree/master/src/Python
Your task to complete the issue openworm/tracker-commons#113 would be to write a function that can take such a
w object and output a valid BDML object.
So by doing this, I've saved you half the effort (loading WCON).
Hope this helps! Let me know if you need anything else.
Hey @aexbrown @ichoran @ver228 @Eviatar here is OpenWorm senior contributor Balázs Szigeti's omega turns survey: http://groups.inf.ed.ac.uk/worms/index.html
Please consider participating!
- Worm literature is notoriously poor in defining behavior. We have a strong definition for pirouettes at http://www.wormbook.org/chapters/www_behavior/behavior.html#sec7_6
But it's a weird and forced definition.
Worse yet
From Wormbook "Some researchers include omega turns as reversals. And, some researchers count increased backward locomotion as a reversal or response; most do not. A precise definition of the behavior to be scored is critical for analysis."
Generally, behavior has been a fudge and we need stronger definitions.
- Andre defined upsilon turns to differentiate less sharp turns that are not omega turns but we really should just quantify omega-like turns with a histogram to see what the distribution is. If it's clearly unimodal, we need a new definition. Otherwise, we can strike a threshold using the histo.
Should've been labeled #2. Is Gitter autocorrecting me?
Sorry Stephen, should I move the convo elsewhere?
No no, this is good!
Continung.
- The list of videos is quite interesting. Sometimes the worm touches itself & sometimes it doesn't but comes close. For me, an omega turn is a ~180 degree reorienting event that uses proprioception to determine the opposing direction. Do we need touch to do this? How about just the wave of food/media motion that can be felt as the worm approaches its tail compressing the media between its 2 extremities? And, maybe my definition isn't teh popular one?
Arggghhh. That was #3.
Moreover, sometimes an omega is preceded by reversal. These are clearly conjoint behavior and they should have their own name when coupled.
Furthermore. Often the omega is a smooth turn but, in the videos, some omega-like turns are interrupted by foraging (is this a mutant?), defecation, and other non-smooth perhaps independent behavior. If we consider these non-omega turns we may lose mutant behaviors that decoupled omegas from their smooth execution. On the other hand, these may truly not be omega turns. We need to make a hard choice here.
I'll let Andre weigh in. He may have strong opinions having faced this problem multiple times.
I'll need to follow up (as best as I can given a lack of access to published literature) with the cited publications, but has there been any other comprehensive large-scale data analysis work on worm movement like in Andre's paper http://biorxiv.org/content/early/2015/04/08/017707 ? Naively it feels to me that an often repeated sequence of shapes-over-time can be used as a context-neutral method to further characterize context-sensitive movement behaviors such as the Omega (full disclosure: I have no clue what is meant by an omega turn.)
The reason I asked is because in my previous field of application performance analysis, a very similar problem plagues the research community where characterizing the (high level) "behavior" of various scientific code kernels is concerned.
