A Python library to facilitate path sampling algorithms.
OpenPathSampling (OPS) makes it easy to perform many variants of transition path sampling (TPS) and transition interface sampling (TIS), as well as other useful calculations for rare events, such as committor analysis and flux calculations. In addition, it is a powerful library to build new path sampling methods.
OPS is independent of the underlying molecular dynamics engine, and currently has support for OpenMM and Gromacs, as well as an internal engine suitable for 2D toy models.
Documentation is still in progress. Please see Getting Help for how to contact us with questions.
To see the most recent updates to the code, see the release notes page on GitHub.
OPS was described in a pair of papers published in JCTC:
David W.H. Swenson, Jan-Hendrik Prinz, Frank Noé, John D. Chodera, and Peter G. Bolhuis. “OpenPathSampling: A flexible, open framework for path sampling simulations. 1. Basics.” J. Chem. Theory Comput. 15, 813 (2019). https://doi.org/10.1021/acs.jctc.8b00626
David W.H. Swenson, Jan-Hendrik Prinz, Frank Noé, John D. Chodera, and Peter G. Bolhuis. “OpenPathSampling: A flexible, open framework for path sampling simulations. 2. Building and Customizing Path Ensembles and Sample Schemes.” J. Chem. Theory Comput. 15, 837 (2019). https://doi.org/10.1021/acs.jctc.8b00627
openpathsampling.bib (citation keys
- User Guide Topics
- OpenPathSampling terminology
- Preparing for path sampling
- Setting up sample sets
- Output during simulations
- Data objects
- Creating collective variables
- Ensembles apply to trajectories, not frames
- Common setups
- Which network should I use?
- Transitions and Networks
- TIS Analysis
- Advanced Uses of OPS Ensembles
- How I use OpenPathSampling
- Command Line Interface
- The OPS Ecosystem
- Frequently Asked Questions
- Getting Help
- Overviews for Developers
- OpenPathSampling API