ood_learning_setting

Spatio-temporal OOD Learning Setting

In this sub-setting, we use and adapt the code repository of the STONE model.

1. Generating the SD and GBA sub-datasets from CA dataset

In the experiments of our paper, we used SD dataset with years from 2019 to 2020, which were generated from CA dataset, followed by LargeST. For example, you can download CA dataset from the provided link and please place the downloaded archive.zip file in the data/ca folder and unzip the file.

First of all, you should go through a jupyter notebook process_ca_his.ipynb in the folder data/ca to process and generate a cleaned version of the flow data. Then, please go through all the cells in the provided jupyter notebooks generate_sd_dataset.ipynb in the folder data/sd and generate_gla_dataset.ipynb in the folder data/gla respectively. Finally use the commands below to generate traffic flow data for our experiments.

python data/generate_data_for_training.py --dataset sd_gba --years 2019
python data/generate_data_for_training.py --dataset sd_gba --years 2020

2. Environmental Requirments

The experiment requires the same environment as LargeST.

3. Model Running

To train STONE on SD, for example, you may execute this command in the terminal:

bash experiments/stone/run_train.sh

or directly execute the Python file in the terminal:

python experiments/stone/main.py --device cuda:1 --dataset SD --years 2019 --model_name stone --seed 0 --bs 64 --c 10 --ood 1 --tood 1 --new_node_ratio 0.1

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To test STONE w/o ST-TTC (i.e., Normal test) on SD, First, you should make sure that line 231 in main.py file contains the following:

engine.evaluate(args.mode)

and then, you may execute this command in the terminal:

bash experiments/stone/run_test.sh

or directly execute the Python file in the terminal:

python experiments/stone/main.py --device cuda:1 --dataset SD --years 2019 --model_name stone --seed 0 --bs 1 --c 10 --ood 1 --tood 1 --new_node_ratio 0.1 --mode test

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To test STONE w/ ST-TTC on SD, First, you should make sure that line 231 in main.py file contains the following:

engine.evaluate_with_ttc(args.mode, args.group, args.sd_lr)

and then, you may execute this command in the terminal:

bash experiments/stone/run_test.sh

or directly execute the Python file in the terminal:

python experiments/stone/main.py --device cuda:1 --dataset SD --years 2019 --model_name stone --seed 0 --bs 1 --c 10 --ood 1 --tood 1 --new_node_ratio 0.1 --mode test