A Python package for construction and analysis of ordinal partition networks and computation of the permutation entropy from time-series data.
For details on permutation entropy, see:
Bandt, C., & Pompe, B. (2002). Permutation Entropy: A Natural Complexity Measure for Time Series. Physical Review Letters, 88(17), Article 17. https://doi.org/10.1103/PhysRevLett.88.174102
For ordinal partition networks, see:
McCullough, M., Small, M., & Iu, H. H.-C. (2015). Measuring the Complexity of Time Series Using Ordinal Partition Networks. 4.
McCullough, M., Small, M., Stemler, T., & Iu, H. H.-C. (2015). Time lagged ordinal partition networks for capturing dynamics of continuous dynamical systems. Chaos: An Interdisciplinary Journal of Nonlinear Science, 25(5), Article 5. https://doi.org/10.1063/1.4919075
- igraph
- numpy
- scipy
- scikit-learn
- cython
run ./install.sh
If you use OPyN in a publication, please cite:
Varley, T. F., & Sporns, O. (2022). Network Analysis of Time Series: Novel Approaches to Network Neuroscience. Frontiers in Neuroscience, 15. https://www.frontiersin.org/article/10.3389/fnins.2021.787068