tsfel 0.0.3

Library for time series feature extraction

Time Series Feature Extraction Library

Intuitive time series feature extraction

This repository hosts the TSFEL - Time Series Feature Extraction Library python package. TSFEL assists researchers on exploratory feature extraction tasks on time series without requiring significant programming effort.

Users can interact with TSFEL using two methods:

Online

It does not requires installation as it relies on Google Colabs and a user interface provided by Google Sheets

Offline

Advanced users can take full potential of TSFEL by installing as a python package

pip install https://github.com/fraunhoferportugal/tsfel/archive/v0.0.2.zip

Includes a comprehensive number of features

TSFEL is optimized for time series and automatically extracts over 50 different features on the statistical, temporal and spectral domains.

Functionalities

• Intuitive, fast deployment and reproducible: interactive UI for feature selection and customization
• Computational complexity evaluation: estimate the computational effort before extracting features
• Comprehensive documentation: each feature extraction method has a detailed explanation
• Unit tested: we provide unit tests for each feature
• Easily extended: adding new features is easy and we encourage you to contribute with your custom features

Acknowledgements

We would like to acknowledge the financial support obtained from North Portugal Regional Operational Programme (NORTE 2020), Portugal 2020 and the European Regional Development Fund (ERDF) from European Union through the project Symbiotic technology for societal efficiency gains: Deus ex Machina (DEM), NORTE-01-0145-FEDER-000026.