Physics-Informed-WNO

The repository provides Python codes for the numerical examples illustrated in the paper ‘Physics informed WNO’ Please go through the paper to understand the implemented algorithm. Requirements:

1. Install python package pytorch, numpy, pandas, matplotlib etc.

2. There are four separate folders containing data sets (data generation codes) and implementation codes, where the folders are named as ‘Burger's’, ‘Nagumo’, ‘Non-homogeneous Poissons’, and ‘Allen-Cahn’.

3. Add the data (generated data) path to load the data and use the run(Main_physics) file to execute program.

4. If you find the code helpful, please cite the paper. @article{navaneeth2023physics, title={Physics informed WNO}, author={N, Navaneeth and Tripura, Tapas and Chakraborty, Souvik}, journal={arXiv preprint arXiv:2302.05925}, year={2023} }