Useful tools for periodicity analysis in time series data.
Project description
Periodicity
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
implementationcelerite2
implementationcelerite2.theano
implementation
Installation
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
.
Development
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.
Project details
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