This repository contains end-to-end code for a data-driven decision-making process utilizing gigabytes of data from the MicroBooNE detector. The project spans from data ideation to production, ensuring robust and efficient data handling and analysis. Process Description
- Data Decoding and Reorganization: Converts binary data from 1.6 ms chunks to 2.3 ms chunks, aligning with detector requirements for full ionization collection.
- Pattern Recognition and Filtering: Implements traditional algorithms to identify specific topologies and patterns within the data.
- Filters out data once the specified patterns are detected, optimizing for targeted analysis.
Key Features Efficient Data Handling: Processes large datasets to meet specific detector time window requirements. Robust Pattern Recognition: Utilizes proven algorithms for accurate data filtering. End-to-End Workflow: Covers the complete lifecycle from data decoding to pattern identification and filtering.
Contact For questions or collaborations, please reach out at [email protected]