STSM

Official code for the paper 'Spatial-temporal Forecasting for Regions without Observations', EDBT 2024

Requirements

-torch -pandas -numpy -tables -geographiclib -scikit-learn -tqdm

The details are in the requirement.txt

Dataset

-Dataset: including the AirQ and PEMS08's traffic data, and unobserved-valid-observed idxs for each split -data: (1) AirQ and PEMS08 contain the temporal adjacent matrix (2) each 1-hop sub-graph's region graph are in the floder "region_graph"

Down data and Dataset from this link: https://drive.google.com/drive/folders/1IfwQRto6yFWRC6lwrKVCzMSm7Ivae8Qh?usp=sharing

Document

• models\cl_gcc_cnn_all.py
• preprocess\split_dat_set.py horizontally or vertically split the dataset

Train the model

In RWOF

• chmod +x ./pems08.sh (chmod +x ./airq.sh) ./pems08.sh (./airq.sh)

• python -u run_model.py --unknown_ratio 0.5 --dataset pems08 --ada 1 --a_sg_nk 0.5 --lweight 0.5 --k 35

a_sg_nk is 𝜖𝑠𝑔 in paper; lweight is lambda in paper

Questions

If you have any quesitons, please contact me at suxs3@student.unimelb.edu.au