Tools and Methods associated with the Eigenvector Method for Umbrella Sampling (EMUS)

pip install emus==0.9.4



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.

The code is released under the LGPL license.
If this poses a problem for your use, please contact the developer. The package also makes use of some code from the emcee python package, which was released under the MIT license.
This license is therefore included as well.

Copyright (c) 2017 Erik Henning Thiede, Brian Van Koten, Jonathan Weare, Aaron R. Dinner.


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.