Run torsion comparisons

[mattwthompson]

• [ ] Make a different main.py that runs torsions
  • [ ] This will use TorsionStore and some iteration of QCArchiveTorsionDataset
• [ ] Store some TorsionDrive dataset in datasets/
  • [ ] New version of download_and_filter_dataset.py (which is run once per dataset/iteration thereof, not in different versions of CI) OR
  • [ ] Just add a cached dataset into datasets/
  • [ ] The name of the dataset is reference in the "run config" file, which is used in workflow triggering
• [x] Actually make models for storing torsion outputs
• [x] Think about updating the existing workflow, which globs up whatever is there. Make sure it adds the torsion outputs, whatever they are
• [ ] Make sure the TorsionStore database are successfully uploaded to Zenodo
• [ ] Work with science team to establish a (rough) dataset for benchmarking torsions (100-200?)
  • [ ] As a stopgap, @ntBre can just filter out an arbitrary 100-200 torsions from the fitting dataset (some nuance with the filters that are applied)
• [ ] Build out basic metric(s) for qualitatively analyzing torsion profiles (i.e. without needing to look at dozens of plots)
  • [ ] Only want a ballpark estimate, leave room for more detailed analyzes in the future

[mattwthompson]

ref https://github.com/openforcefield/yammbs/pull/76/

[mattwthompson]

With https://github.com/openforcefield/yammbs/pull/76/commits/a7298a8038073b104e25d01fd6b0803b3474a3bd, MM profiles and some (extremely approximate) metrics and be stored after optimization

[ntBre]

That's great news! Does that mean I should work on a new version of main.py and a dataset script?

[mattwthompson]

I started something in #13 - please suggest (or simply make) whatever changes stand out as useful to you.

In my local setup (with YAMMBS at that commit), these files script generates a plot, a metrics JSON, and an "outputs" JSON which stores the MM-minimized profiles: https://gist.github.com/mattwthompson/820328f2736193e3edb06eadc0bac742