This it the official github for "DSSTGNN"
- python>=3.8
- torch>=2.0.0
- numpy>=1.23.5
- pandas>=1.5.3
- scipy>=1.10.1
- tables>=3.8.0
- pywavelets>=1.4.1
It is publicly available at: Zenodo.
The METEO-SC dataset can be download from BaiduNetdisk or GoogleDrive. And the METEO-NUS dataset is from WEATHER-5K. Also, you can generate the data by running the following code.
python generate_training_data.py
We provide default training codes in train.py. You can train the model as follows:
python train.py
For more parameter information, please refer to train.py. We provide a more detailed and complete command description for the training code:
python -u train.py
--device DEVICE
--data DATA
--input_dim INPUT_DIM
--channels CHANNELS
--num_nodes NUM_NODES
--input_len INPUT_LEN
--output_len OUTPUT_LEN
--batch_size BATCH_SIZE
--learning_rate LEARNING_RATE
--dropout DROPOUT
--weight_decay WEIGHT_DECAY
--epochs EPOCHS
--print_every PRINT_EVERY
--save SAVE
--es_patience ES_PATIENCE
For the testing, you can run the code below:
python test.py
- Code: MIT License
- Data: CC BY 4.0 License
The dataset used in this study is publicly available and can be freely used under the CC BY 4.0 license.