raphaelvallat/antropy
AntroPy: entropy and complexity of (EEG) time-series in Python
This tool helps researchers and practitioners analyze the complexity and regularity of time-series data, particularly from biological signals like EEG. You input raw physiological recordings or other time-series, and it outputs various entropy and fractal dimension metrics that describe patterns and randomness. It's designed for scientists, clinicians, or engineers working with time-dependent data who need to quantify its intrinsic properties for feature extraction or signal processing research.
360 stars. Used by 2 other packages. Available on PyPI.
Use this if you need to calculate a wide range of entropy and fractal dimension measures from time-series data, especially physiological signals, for quantitative analysis and feature extraction.
Not ideal if you are looking for a general-purpose signal visualization tool or need advanced machine learning models built on these features, as it focuses specifically on calculating complexity metrics.
Stars
360
Forks
58
Language
Python
License
BSD-3-Clause
Category
Last pushed
Mar 09, 2026
Commits (30d)
0
Dependencies
4
Reverse dependents
2
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