Skip to content

ehthiede/EMUS

master
Switch branches/tags
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Description

This is an implementation of the EMUS algorithm for recombining data from umbrella sampling calculations and other data sources coming from biased probability densities. The code is currently in open Beta, please contact the author at thiede [at symbol] uchicago [dot] edu with any bugs, errors, or questions.

For usage and documentations, see the HTML documentation, which can be accessed by opening docs/html/index.html in a browser. We are currently working on hosting the documentation online; this README will be updated with a link once that is accomplished.

If you are using this code, please also cite the EMUS paper, which can be found at Journal of Chemical Physics. In addition, the code for the asymtotic variance of MBAR in iter_avar.py is based on research in the following preprint.. The data used in the preprint can be found here..

The code is released under the MIT license.

Copyright (c) 2022 Erik Henning Thiede, Sherry Li, Brian Van Koten, Jonathan Weare, Aaron R. Dinner.


Installation

To install from the code, use the command python setup.py install or pip install -e .. You can also install from the python repository pip install emus.

About

Implementation of the EMUS algorithm for recombining multiple biased data sources in python

Resources

License

Stars

Watchers

Forks

Packages

No packages published