Metadata-Version: 2.1
Name: spib
Version: 1.1.0
Summary: SPIB is a deep learning-based framework that learns the reaction coordinates from high dimensional molecular simulation trajectories.
Home-page: https://github.com/wangdedi1997/spib
Author: Dedi Wang
Author-email: dwang97@umd.edu
License: MIT license
Keywords: spib
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
License-File: LICENSE
License-File: AUTHORS.rst
Requires-Dist: torch

====
spib
====


.. image:: https://img.shields.io/pypi/v/spib.svg
        :target: https://pypi.python.org/pypi/spib

.. image:: https://img.shields.io/travis/wangdedi1997/spib.svg
        :target: https://travis-ci.com/wangdedi1997/spib

.. image:: https://readthedocs.org/projects/spib/badge/?version=latest
        :target: https://spib.readthedocs.io/en/latest/?version=latest
        :alt: Documentation Status



State Predictive Information Bottleneck (SPIB)

* Author: Dedi Wang
* Free software: MIT license
* Documentation: https://spib.readthedocs.io.


What is it?
-----------

SPIB is a deep learning-based framework for dimension reduction and Markov model construction of MD trajectories. Please read and cite this manuscript when using SPIB: https://aip.scitation.org/doi/abs/10.1063/5.0038198. Here is an implementation of SPIB in Pytorch.


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
=======

1.1.0 (2023-12-14)
------------------

* Complete rewrite of everything allowing more robust dimension reduction and Markov model construction of MD trajectories.

0.1.0 (2023-01-13)
------------------

* First release on PyPI.
