pytseg

Tiny toolbox for time series segmentation.

https://github.com/raoulheese/pytseg

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Tiny toolbox for time series segmentation.

README.rst

*****************************************
Time series segmentation toolbox (pytseg)
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Tiny toolbox for time series segmentation.

The toolbox presumes a (univariate or multivariate) time series. For example, consider the following univariate time series:

.. image:: https://raw.githubusercontent.com/RaoulHeese/pytseg/main/docs/source/_static/plot1.png
    :target: https://github.com/RaoulHeese/pytseg/blob/main/demos/demo-1.ipynb
    :alt: plot1

Such a time series can then be segmented into distinguishable segments using the toolbox:

.. image:: https://raw.githubusercontent.com/RaoulHeese/pytseg/main/docs/source/_static/plot2.png
    :target: https://github.com/RaoulHeese/pytseg/blob/main/demos/demo-1.ipynb
    :alt: plot2

All segments are marked in different colors in the plot. And, finally, these segments can be assigned labels like stationarity:

.. image:: https://raw.githubusercontent.com/RaoulHeese/pytseg/main/docs/source/_static/plot3.png
    :target: https://github.com/RaoulHeese/pytseg/blob/main/demos/demo-1.ipynb
    :alt: plot3
   
Green lines indicate stationary segments of the time series.

**Installation**

Install the package via pip or clone this repository. To use pip, type:

.. code-block:: sh

  $ pip install pytseg

**Usage**

Documentation: ``_.

Demo notebooks can be found in the `demos/` directory of this repository.

📖 **Citation**

The implemented univariate time series segmentation closely follows:

.. code-block:: tex

  @article{PhysRevE.69.021108,
           title = {Heuristic segmentation of a nonstationary time series},
           author = {Fukuda, Kensuke and Eugene Stanley, H. and Nunes Amaral, Lu\'{\i}s A.},
           journal = {Phys. Rev. E},
           volume = {69},
           issue = {2},
           pages = {021108},
           numpages = {12},
           year = {2004},
           month = {2},
           publisher = {American Physical Society},
           doi = {10.1103/PhysRevE.69.021108},
           url = {https://link.aps.org/doi/10.1103/PhysRevE.69.021108}
          }

There is no affiliation with the authors of this article.

*This project is currently not under development and is not actively maintained.*

Owner

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Heese"
  given-names: "Raoul"
  orcid: "https://orcid.org/0000-0001-7479-3339"
title: "pytseq"
version: 0.1
date-released: 2022-09-14
url: "https://github.com/RaoulHeese/pytseq"

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