===============
SPIB-WE plug-in
===============
.. image:: https://img.shields.io/pypi/v/spib_we.svg
:target: https://pypi.python.org/pypi/spib_we
.. image:: https://img.shields.io/travis/wangdedi1997/spib_we.svg
:target: https://travis-ci.com/wangdedi1997/spib_we
.. image:: https://readthedocs.org/projects/spib-we/badge/?version=latest
:target: https://spib-we.readthedocs.io/en/latest/?version=latest
:alt: Documentation Status
This is a WESTPA 2.0 plug-in for SPIB augmented weighted ensemble.
* Free software: MIT license
* Documentation: https://spib-we.readthedocs.io.
Features
--------
* Employ SPIB to automatically construct low-dimensional CVs to augment weighted ensemble simulations;
* Implement a rectilinear grid binning scheme to automatically determine bin sizes for uniformly binning SPIB-learned CVs;
* Propose a hybrid approach that combines SPIB-learned CVs with expert-based CVs to achieve more reliable sampling.
Credits
-------
This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.
.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
=======
History
=======
0.1.0 (2023-01-16)
------------------
* First release on PyPI.
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