Major release with new features and bug-fixes
Features:
- Includes several new gradient-free optimizers from multiple frameworks -- Nevergrad, Pymoo, Platypus, and MOBOpt. Updated documentation to reflect new algorithms
- Better LAMMPS support, both for spawning LAMMPS jobs and reading LAMMPS dump/output files
- Better error handling -- Errors now generate
np.nanobjectives, instead of crashing the optimization routine - Ability to save and restart from previously evaluated variable sets
- More examples for serial/parallel forcefield parameterization using LAMMPS/GULP, and parameterization of hybrid forcefields
- Parallelization using both multiprocessing and mpi pools