| Name | spib JSON |
| Version |
1.1.0
JSON |
| download |
| home_page | https://github.com/wangdedi1997/spib |
| Summary | SPIB is a deep learning-based framework that learns the reaction coordinates from high dimensional molecular simulation trajectories. |
| upload_time | 2023-12-15 04:38:07 |
| maintainer | |
| docs_url | None |
| author | Dedi Wang |
| requires_python | >=3.6 |
| license | MIT license |
| keywords |
spib
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
|
| coveralls test coverage |
No coveralls.
|
====
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.
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