Source code for final project of IFEEMCS520100 Fundamentals of Artificial Intelligence Programme course at TU Delft.
- Roman Volovoy (R.Volovoy@student.tudelft.nl)
- Xianzhi Zhang (X.Zhang-85@student.tudelft.nl)
- Yuncong Liu (Y.Liu-138@student.tudelft.nl)
- Zhengchu Wu (Z.Wu-27@student.tudelft.nl)
Pipenv is used for dependency management, install it if needed.
pip install pipenv
Install all packages with dev dependencies from Pipfile.lock
; this will take a while.
pipenv install -d
Enter python environment
pipenv shell
Run a simple example. It will run an example simulation and then launch a visualization of the result.
python example_run.py && python visualization.py --file ./results/test_run.json
This repo contains trained models of all different datasets (2 HA, 2 HH, 1 AH) clusters.
Re-clustering and re-training can be performed by running sh ./train.sh
. This process can take a very long time (approx. 2 hours on 12 core machine)
There are many small unit tests to verify that the models work by themselves. These tests can be run with the following command:
pytest -n 2 tests.py
Running the tests will output all simulation results in the test_results
folder. The output can be viewed by running
python visualization.py -f test_results/<test-name>.json