Data for the paper "How does ion temperature gradient turbulence depend on magnetic geometry? Insights from data and machine learning"

Contents: 20250102-01_GX_stellarator_dataset.h5: The primary dataset, including flux tube geometries and gyrokinetic heat fluxes 20250102-01_GX_stellarator_dataset.README: Detailed description of the variables in 20250102-01_GX_stellarator_dataset.h5 gyrokinetics_machine_learning_demo.py: Example script for using the data in 20250102-01_GX_stellarator_dataset.h5 20250119-01-gyrokinetics_machine_learning_zenodo.20250213.tar: Contains many other files such scripts for generating the equilibria, running GX, extracting the heat fluxes, training and evaluating the neural networks, and producing the figures in the paper. Also contains the MHD equilibria and the trained neural network parameters.