Tiny toolbox for time series segmentation
Project description
Tiny toolbox for time series segmentation.
The toolbox presumes a (univariate or multivariate) time series. For example, consider the following univariate time series:
Such a time series can then be segmented into distinguishable segments using the toolbox:
All segments are marked in different colors in the plot. And, finally, these segments can be assigned labels like stationarity:
Green lines indicate stationary segments of the time series.
Installation
Install the package via pip or clone this repository. To use pip, type:
$ pip install pytseg
Usage
Documentation: https://pytseg.readthedocs.io/en/latest/.
Demo notebooks can be found in the demos/ directory of this repository.
📖 Citation
If you find this code useful in your research, please consider citing:
@misc{pytseg2022,
author = {Raoul Heese},
title = {pytseg},
year = {2022},
publisher = {GitHub},
journal = {{GitHub} repository},
howpublished = {\url{https://github.com/RaoulHeese/pytseg}},
}
The implemented univariate time series segmentation closely follows:
@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.
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