Artifact of the paper: DiffNO: Neural Operator Learning using Physically Structured Constrained Diffusion Model

To train a model, first ensure that the dataset is correctly placed in the datasets folder. After setting up the environment, navigate to the folder corresponding to each experiment, modify the content in Main_Green.py, uncomment eval_stage1 and train_stage2, and run the following command to train the model:

```python

python Main_Green.py

```

To test a model, modify the content in Main_Green.py, uncomment eval_stage1 and eval_stage2, and run the following command to test the model:

```python

python Main_Green.py

```

After the program has completed all test data inference, the test results will be saved to testset_err.txt, and the average l2 error of the test set will be output, which corresponds to the results in the experiment section of the paper. The image of the predicted result versus the actual result will be saved to tesetset_pic folder.