Feature parity with MuseInference.jl

[marius311]

List of things needed to get to feature parity with the Julia version of this package:

• Parallelization (a pmap placeholder is there but needs exploration how to make sure its usable with popular parallelizers, so maybe multiprocessing, joblib, ipyparallel, and jax.pmap)
  • A progress bar which works with parallel
• Broyden Hessian updates (maybe use a proper Broyden solver rather rolling our own? the motivation in MuseInference.jl to roll our own was to work with more array types, but here that's less an issue since theres fewer of them)
• getH / getJ still need implementing