Basic implementation of PatternCoordinator and adjusting gcal_od to the new interface
Basic implementation of PatternCoordinatorImages, modify gcal_od to work with it and provide shouval with example JSON dataset specification
Global definition of x and y, rename available_dims to inherent_dims, avoidance of explicit definition of PatternCoordinatorImage.synthesizedisparity, removed constructor of PatternCoordinator
Change to metafeature approach: Move functions into own classes, so ImaGen and topographica parts are independent
Moved x&y to become synthesize functions as well, added documentation, fixed call of PatternCoordinator so it only gets called once
Allow arbitrary synthetic pattern generator, unified __call__ function in PatternCoordinator
Bugfix in disparity, reordered metafeature_mapping to get disparity to work, created animation for better visualization
Export cells to python files for use in other notebooks

Added minor documentation
Min_separation as parameter
Changed gcal.ty to use PatternCoordinator, support Nature dataset
Deleted num_aff as it is not used in GCAL
Renamed e to label and added documentation
Added input parameters to tiny.ty
Added analysis code back to model
Remove PatternCoordinatorSynthetic and make PatternCoordinator self-contained instead
Match filename_template with {} rather than ##
Use composer with Composite as default rather than SeparatedComposite
Changed file to use conventions given in Topographica's developer manual
Use param_keywords() from param
Use ClassSelector with is_instance=False from param
Many small hacks and tweaks
Add compatibility with PatternCoordinator from ImaGen
Rename SynthesizeFn to ValueCoordinator
Change seed to match Gaussian in gcal.ty
Split ImaGen and Topographica part
Added import statement in models for new patterncoordinator module in ImaGen
Let notebook reproduce metafeatures.py and patterncoordinator.py exactly, use new export magic, cleanup
Incorporated changes in names in patterncoordinator.py from ImaGen