jdrusso / msm_we

History-augmented Markov analysis of weighted ensemble trajectories.

msm_we

• Authors: John Russo, Jeremy Copperman
• Free software: MIT license
• Documentation: https://msm-we.readthedocs.io .

Background

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.

Features

• 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

Known Issues

• 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

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.