https://github.com/soleyhyman/peccary

Package for identifying regular, complex, and stochastic behavior in timeseries
https://github.com/soleyhyman/peccary

astro astronomy astrophysics chaos chaotic-systems dynamics orbital-dynamics physics python

Last synced: 15 days ago
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Package for identifying regular, complex, and stochastic behavior in timeseries

• Host: GitHub
• URL: https://github.com/soleyhyman/peccary
• Owner: soleyhyman
• License: mit
• Created: 2024-07-11T16:53:17.000Z (7 months ago)
• Default Branch: main
• Last Pushed: 2024-12-10T01:32:50.000Z (about 2 months ago)
• Last Synced: 2024-12-10T02:26:43.768Z (about 2 months ago)
• Topics: astro, astronomy, astrophysics, chaos, chaotic-systems, dynamics, orbital-dynamics, physics, python
• Language: Python
• Homepage: https://peccary.readthedocs.io
• Size: 1.17 MB
• Stars: 3
• Watchers: 1
• Forks: 2
• Open Issues: 2
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE

Awesome Lists containing this project

README

        
|logo|

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PECCARY

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|PyPI| |conda| |Zenodo| |License|

PECCARY (Permutation Entropy and statistiCal Complexity Analysis for astRophYsics) 

is a pure-python package for distinguishing between regular, complex, and stochastic

behavior in timeseries. It is based on the work by 

`Bandt & Pompe (2002) `__ , 

`Rosso et al. (2007) `__ , 

and `Weck et al. (2015) `__.

This code is also based on work by collaborator David Schaffner, who wrote the initial 

version of some of the method, called `PESCy `__.

In addition to calculating the Permutation Entropy ($H$) and Statistical Complexity

($C$) values, this package also has plotting tools for the $HC$-plane and visualizing the 

resulting $[H,C]$ values for various timeseries.

A detailed summary of the PECCARY method can be found in Hyman, Daniel, & Schaffner (`arXiv:2407.11970 `__). 

If you make use of PECCARY, please include a citation to Hyman, Daniel, & Schaffner (`arXiv:2407.11970 `__)

in any publications.

Documentation

-------------

|Documentation Status|

The documentation for ``peccary`` is hosted on `Read the Docs `__.

Installation and Dependencies

-----------------------------

The recommended way to install the latest stable version of ``peccary`` 

is with ``pip`` via the terminal with the command:

>>> pip install peccary

You can also use the command:

>>> python -m pip install peccary

or with ``conda`` via:

>>> conda install -c conda-forge peccary

See the `installation instructions `__

in the `documentation `__ for more instructions.

.. |PyPI| image:: https://badge.fury.io/py/peccary.svg

   :target: https://pypi.org/project/peccary/

.. |conda| image:: https://anaconda.org/conda-forge/peccary/badges/version.svg

   :target: https://anaconda.org/conda-forge/peccary

.. |Documentation Status| image:: https://readthedocs.org/projects/peccary/badge/?version=latest

   :target: http://peccary.readthedocs.io/en/latest/?badge=latest

.. |logo| image:: https://peccary.readthedocs.io/en/latest/_static/peccary-logo-banner.png

   :target: https://github.com/soleyhyman/peccary

   :width: 400

.. |License| image:: http://img.shields.io/badge/license-MIT-blue.svg?style=flat

   :target: https://github.com/soleyhyman/peccary/blob/main/LICENSE

.. |Zenodo| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.13168299.svg

   :target: https://doi.org/10.5281/zenodo.13168299