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Modified diffusion entropy analysis; a temporal complexity analysis method

Project description

Diffusion entropy analysis

pytest status mkdocs status python versions pypi version ruff uv

Diffusion Entropy Analysis is a time-series analysis method for detecting temporal scaling in a data set, such as particle motion, a seismograph, or an electroencephalograph signal. Diffusion Entropy Analysis converts a timeseries into a diffusion trajectory and uses the entropy of this trajectory to measure the temporal scaling in the data. This is accomplished by moving a window along the trajectory, then using the relationship between the natural logarithm of the length of the window and the Shannon entropy to extract the scaling of the time-series process.

For further details about the method and how it works, please see Culbreth, G., Baxley, J. and Lambert, D., 2023. Detecting temporal scaling with modified diffusion entropy analysis. arXiv preprint arXiv:2311.11453.

Installation and use

The pymdea package is available on pypi and can be installed with pip:

pip install pymdea

pymdea can also be installed with uv

uv add pymdea

A user guide is available in the documentation.

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numpy scipy polars matplotlib seaborn tqdm pytest ruff material for mkdocs mkdocstrings

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