A Jupyter notebook GUI front-end for the pyEDM package. An introduction to EDM with documentation is avilable online. The pyEDM package documentation is in the API docs. The EDM packages are developed and maintained by the Sugihara Lab.
Functionality includes:
- Simplex projection (Sugihara and May 1990)
- Sequential Locally Weighted Global Linear Maps (S-map) (Sugihara 1994)
- Multivariate embeddings (Dixon et. al. 1999)
- Convergent cross mapping (Sugihara et. al. 2012)
- Multiview embedding (Ye and Sugihara 2016)
pyEDM is hosted on the Python Package Index respository (PyPI) at pyEDM.
It can be installed from the command line using the Python pip module: python -m pip install pyEDM.
Download the jpyEDM source.
Start Jupyter notebook.
Open "jpyEDM/notebooks/pyEDM Version 0.ipynb".
A brief video presentation.
Sugihara G. and May R. 1990. Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series. Nature, 344:734–741.
Sugihara G. 1994. Nonlinear forecasting for the classification of natural time series. Philosophical Transactions: Physical Sciences and Engineering, 348 (1688) : 477–495.
Dixon, P. A., M. Milicich, and G. Sugihara, 1999. Episodic fluctuations in larval supply. Science 283:1528–1530.
Sugihara G., May R., Ye H., Hsieh C., Deyle E., Fogarty M., Munch S., 2012. Detecting Causality in Complex Ecosystems. Science 338:496-500.
Ye H., and G. Sugihara, 2016. Information leverage in interconnected ecosystems: Overcoming the curse of dimensionality. Science 353:922–925.