Welcome to msm_we’s documentation!

msm_we

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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.

Contents:

Indices and tables