(Version 1.1 - Nov. 28th, 2024)
For reproducing the paper's results, explore plot_results.ipynb
For training the model run main.py
For training and exploring the model, run main.ipynb
For testing a model, run test_model.py
Both main.py and main.ipynb use a config.yaml as reference configuration file.
The repository is divided in the following folders:
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database: Creation of hydrodynamic simulations (D-Hydro simulations.ipynb) [requires the license and installation of "D-HYDRO Suite 1D2D"] and conversion of the NETCDF output files into PyTorch Geometric-friendly data (create_dataset.ipynb). Also contains the output of the hydrodynamic simulations (raw_datasets: for downloading the datasets go to https://doi.org/10.5281/zenodo.13326595). This is converted into Pickle files that are then stored and separated into training and testing datasets in datasets.
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models: Deep learning models developed for surrogating the hydraulic one: contains a base class with common inputs and functions and one for the SWE-GNN and mSWE-GNN models.
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results: Contains results and trained models of the mSWE-GNN Pareto front, used for the paper's results.
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training: Contains loss and training functions.
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utils: Contains Python functions for loading, creating and scaling the dataset. There are also other miscellaneous functions and visualization functions.
The required libraries are in requirements.txt.