Welcome to pyts, a Python package for time series transformation and classification !
pyts is a Python package for time series transformation and classification. It aims to provide state-of-the-art as well as recently published algorithms for time series classification. Most of these algorithms transform time series, thus pyts provides several tools to perform these transformations.
Installation
Dependencies
pyts has been tested on Python 2.7 and 3.5 with the following dependencies:
- numpy (>= 1.13.3)
- scipy (>= 0.13.3)
- scikit-learn (>=0.17.0)
- future (>=0.13.0) (for Python 2 compatibility)
To run the examples matplotlib is required (matplotlib >= 2.0.0 has been tested).
User installation
If you already have a working installation of numpy, scipy and
scikit-learn, you can easily install pyts using pip
pip install pyts
You can also get the latest version of pyts by cloning the repository
git clone https://github.com/johannfaouzi/pyts.git
cd pyts
pip install .
Documentation
For more information about the algorithms implemented in pyts as well as how to use them, you can have a look at the HTML documentation
Citation
pyts is registered on Zenodo. If you use it in a scientific publication, please cite us
@misc{johann_faouzi_2018_1244152,
author = {Johann Faouzi},
title = {{pyts: a Python package for time series transformation and classification}},
month = may,
year = 2018,
doi = {10.5281/zenodo.1244152},
url = {https://doi.org/10.5281/zenodo.1244152}
}