- Authors: John Russo, Jeremy Copperman
- Free software: MIT license
- Documentation: https://msm-we.readthedocs.io .
This is a package for doing history-augmented MSM (haMSM) analysis on weighted ensemble trajectories.
Weighted ensemble data produced from simulations with recycling boundary conditions are naturally in a directional ensemble. This means that a history label can be assigned to every trajectory, and an haMSM can be constructed.
- Compute a history-augmented Markov state model from WESTPA weighted ensemble data
- Estimate steady-state distributions
- Estimate flux profiles
- Estimate committors
- WESTPA plugins to automate haMSM construction
- WESTPA plugin to automate bin+allocation optimization
- Due to H5py version dependencies, this is currently not compatible with Python 3.10.
- Sometimes, on Python3.7 (and maybe below) the subprocess calls will fail. This may manifest as a silent failure, followed by hanging (which is very fun to debug!) To fix this, upgrade to Python 3.8+.
- If running with $OMP_NUM_THREADS > 1, Ray parallelism may occasionally silently hang during clustering / fluxmatrix calculations
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.
