Closed ghost closed 8 years ago
1) an attempt at the sufficiently dense frame sequence problem can be found here: https://github.com/AidanRocke/behavioral_syntax/blob/master/utilities/numericalc.py
_look for the sequencefilter function
2) meanwhile, it's not certain whether the videos must be of similar length or have similar starting and ending times. I don't know whether C. Elegans locomotion patterns stabilize after a certain point...but I think that's a separate issue.
Upon further reflection, I realize that my intentions were misplaced.
The ideal approach would require very low tolerance for missing frames(ex. 5% per video) . There's really no reason why worm trackers should be so crappy.
if the data is too sparse(i.e. too many frames are missing or there are too many gaps between frames), make sure to throw out that video, and notify the user