Assignment 2, COMP9417: Kaggle competition (https://www.kaggle.com/c/trackml-particle-identification). The challenge is to build an algorithm that quickly reconstructs particle tracks from 3D points left in the silicon detectors.
These instructions will get you a copy of the project up and running on your local machine for testing purposes.
- Python 3.0+ either locally or in a virtual environment.
- Datasets from kaggle: https://www.kaggle.com/c/trackml-particle-identification/data
- Packages required:
trackml
: https://github.com/LAL/trackml-library.git This is the competition-specific package.numpy
,pandas
,tqdm
,scikit_learn
for our current best-performing solutiontrain_trackml-DBSCAN.py
(see the next section for how to install).- The other version,
train_trackml-HDBSCAN.py
, which gives a lower score than the DBSCAN version, requires an extra packagehdbscan
. However this package is not able to be installed on CSE lab computers unless with sudo permission.
First, clone this repository to your local machine. You may skip this step if you already have all the files: two python scripts and a requirements.txt
.
git clone https://github.com/XifeiNi/TrackML.git
There is a requirements.txt
bundled in this repository that lists the required packages you need to install. These are all compatible with the CSE lab environment. They can be installed using the following commands:
pip3 install --user -r requirements.txt
If that fails, you may use the following commands:
pip3 install --user git+https://github.com/LAL/trackml-library.git
pip3 install --user numpy pandas scikit_learn tqdm
Additionally, if you wish to run the alternative solution train_trackml-HDBSCAN.py
, you will need to install one more package using the following command:
pip3 install --user hdbscan
However note that this package is not able to be installed on CSE lab computer unless with sudo permission, because it requires certain linux packages that are missing on the lab computers. As it is not required in our current best-performing solution, we have not included it in requirements.txt
.
Run either script as usual:
python3 train_trackml-DBSCAN.py
python3 train_trackml-HDBSCAN.py
- Cecilia Ni
- Shahedul Islam
- Kavi Shah
- Yi Xiao
This project is licensed under the MIT License - see the LICENSE.md file for details
- The kaggle community
- CERN: the European Organization for Nuclear Research