Useful tools for periodicity analysis in time series data.

Documentation: https://periodicity.readthedocs.io

Currently includes:

• 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:
  • george implementation
  • celerite2 implementation
  • celerite2.theano implementation

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.