import wcon; w = wcon.WCONWorms.load_from_file('test_file.wcon')
wobject in your python shell to see what's possible
wobject and output a valid BDML object.
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!
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.