Introductory examples

Trivial examples based on two data sets, a 5-dimensional Lorenz’96 model and hydraulic flow into Everglades National Park through three flow control spillways. An introduction to Empirical Dynamic Modeling (EDM) can be found in the EDM docs and general information in Wikipedia.

1. ccm_example.py Compute convergent cross mapping (CCM) between two components of the Lorenz’5D

2. embed_dimension_example.py Estimate embedding dimension (E) of the Everglades flow data

3. predict_nonlinear_example.py Examine nonlinearity through the S-Map theta parameter

4. simplex_example.py Four examples using Simplex for out of sample prediction of Lorenz’96 variables.

   1. Prediction of V3 from time delay embedding of V3

   2. Prediction of V3 from time delay embedding of V1 (cross mapping)

   3. Prediction of V3 from multivariate embedding of V1,V2,V4,V5

   4. Prediction of V3 from mixed-multivariate embedding of V1,V2,V4,V5

5. smap_example.py Two examples using SMap for out of sample prediction of Lorenz’96 variables.

   1. Prediction and Jacobians of V3 from time delay embedding of V3

   2. Prediction and Jacobians of V3 from multivariate embedding of V1,V2,V4,V5

CCM Transformer

CCM Transformer

EmbedDimension Transformer

EmbedDimension Transformer

PredictNonlinear Transformer

PredictNonlinear Transformer

SMap Estimator

SMap Estimator

Simplex Estimator

Simplex Estimator