# OpenPathSampling¶

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, as well as an internal engine suitable for 2D toy models.

To learn more about what OPS can do, look at our examples. If you want to jump right in, take a look at how easy it is to install!

Note

To see the most recent updates to the code, see the release notes page on GitHub.

## Citing¶

OPS was described in a pair of papers published in JCTC:

1. 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

2. 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

Both citations: openpathsampling.bib (citation keys ops1 and ops2).