StFT: Spatio-temporal-Fourier-Transformer-for-Long-term-Dynamics-Prediction

Training StFT

To train StFT on the plasma MHD dataset:

python train.py

By default, the results will be saved to the ray_results at home directory. To customize the saved direcotry, you can change the save_path variable in the train.py file.

See the LICENSE file for copyright and licensing information.

About

*** Copyright Notice ***

Spatio-temporal Fourier Transformer for Long-term Dynamics Prediction (StFT) Copyright (c) 2025, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved.

If you have questions about your rights to use or distribute this software, please contact Berkeley Lab's Intellectual Property Office at [email protected].

NOTICE. This Software was developed under funding from the U.S. Department of Energy and the U.S. Government consequently retains certain rights. As such, the U.S. Government has been granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the Software to reproduce, distribute copies to the public, prepare derivative works, and perform publicly and display publicly, and to permit others to do so.