This repository contains the supporting codes for the article Robust inference of causality in high-dimensional dynamical processes from the Information Imbalance of distance ranks (unpublished).
The functions employed to compute the Imbalance Gain in the paper are in the Python files utilities.py and imbalance_gain.py, and their use is illustrated in the notebook tutorial.ipynb.
The subdirectory dynamical-systems contains the scripts to generate the trajectories of the dynamical systems analyzed in the paper.
The codes require installing the packages NumPy (1.24.2), Matplotlib (3.7.0), SciPy (1.10.1), scikit-learn (1.2.1) and Joblib (1.2.0) - the versions reported are the ones employed in the analysis. The Information Imbalance is also implemented in the DADApy package.