Useful tools for periodicity analysis in time series data.
- Auto-Correlation Function (and other general timeseries utilities!)
- Spectral methods:
- Lomb-Scargle periodogram
- Bayesian Lomb-Scargle with linear Trend (soon™)
- Time-frequency methods:
- Wavelet Transform
- Hilbert-Huang Transform
- Composite Spectrum
- Phase-folding methods:
- String Length
- Phase Dispersion Minimization
- Analysis of Variance (soon™)
- Decomposition methods:
- Empirical Mode Decomposition
- Local Mean Decomposition
- Variational Mode Decomposition (soon™)
- Gaussian Processes:
The latest version is available to download via PyPI:
pip install periodicity.
Alternatively, you can build the current development version from source by cloning this repo (
git clone https://github.com/dioph/periodicity.git) and running
pip install ./periodicity.
If you're interested in contributing to periodicity, install pipenv and you can setup everything you need with
pipenv install --dev.
To automatically test the project (and also check formatting, coverage, etc.), simply run
tox within the project's directory.