Rank 19 (silver medal) solution of the Kaggle featured competition TrackML Particle Tracking Challenge

This repository only contains the code for predicting a single event. See CFlow for scaling the code to all 125 testing events.

1. Cluster hits using DBSCAN on transformed data using various parameters to generate a pool of track candidates. This step is in /mymodule/cluster2.py
2. Remove duplicate tracks from the pool of candidates. Create a track object for each candidate. Perform helix fitting and outlier removal. This step is in /mymodule/track.py
3. Merge tracks. This step is in /mymodule/merger.py
4. Above procedures are repeated several times with various parameters, focusing on clustering tracks with longer length first.

The full pipeline is in pipeline.ipynb