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sam-fogarty

PROFILE

Sam-fogarty

Samuel Fogarty contributed to the DUNE/ndlar_flow and DUNE/larnd-sim repositories by engineering robust data processing and calibration workflows for detector simulation. He overhauled pedestal processing by refactoring code into modular Python classes, enabling multi-file HDF5 input and streamlined JSON output, and automated data generation using Bash scripting. Samuel introduced a lookup-table-based pixel ID mapping to improve geometry handling and consolidated configuration defaults for calibration parameters. In DUNE/larnd-sim, he enhanced simulation reliability by adding explicit out-of-bounds protection in CUDA-accelerated track pixel mapping. His work emphasized maintainability, reproducibility, and throughput, with careful attention to documentation and workflow automation throughout the development process.

Overall Statistics

Feature vs Bugs

67%Features

Repository Contributions

12Total
Bugs
2
Commits
12
Features
4
Lines of code
890
Activity Months3

Your Network

33 people

Shared Repositories

33

Work History

July 2025

3 Commits • 2 Features

Jul 1, 2025

July 2025 progress on DUNE/ndlar_flow focused on architectural refactor and automation to scale pedestal processing. Implemented a pedestal processing overhaul into separate classes for histogram generation and pedestal JSON creation, enabling multi-file HDF5 pedestal inputs, with updated configuration and documentation reflecting the new architecture. Added shell-based automation for pedestal data generation for 2x2 and FSD detectors using h5flow, including defined input directories, file lists, outputs, and a workflow YAML. These changes improve throughput, reproducibility, and scalability of the data-processing pipeline.

June 2025

8 Commits • 2 Features

Jun 1, 2025

June 2025 focused on delivering core data quality improvements and a streamlined pedestal workflow in DUNE/ndlar_flow. Key features include a Pixel Unique ID generation overhaul that introduces a per-pixel ID mapping using a LUT (later migrated to a dedicated function) and consolidation of ID defaults for pedestal, ADC counts, and gain; a new GeneratePedestals workflow that computes channel pedestals from LArPix data, outputs JSON and HDF5, and is integrated with H5Flow; and targeted calibration fixes addressing prompt hit handling and ADC-to-millivolt calculations. These efforts improve data consistency, processing throughput, and maintainability, enabling more reliable detector calibration, faster onboarding of new data, and clearer documentation.

April 2025

1 Commits

Apr 1, 2025

April 2025 monthly summary for DUNE/larnd-sim: Implemented an important robustness enhancement by adding explicit out-of-bounds protection in the track pixel mapping code. The boundary checks guard get_track_pixel_map and get_track_pixel_map2 against indexing errors when calculated indices exceed the unique_pix array, significantly reducing crash risk and data corruption in simulations.

Activity

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Quality Metrics

Correctness86.8%
Maintainability88.4%
Architecture83.2%
Performance83.4%
AI Usage20.0%

Skills & Technologies

Programming Languages

BashPythonRSTYAML

Technical Skills

CUDACalibrationCode OrganizationCode RefactoringConfiguration ManagementData EngineeringData ProcessingDetector SimulationDocumentationGeometry ProcessingHDF5JSONNumPyPerformance OptimizationPython

Repositories Contributed To

2 repos

Overview of all repositories you've contributed to across your timeline

DUNE/ndlar_flow

Jun 2025 Jul 2025
2 Months active

Languages Used

PythonRSTYAMLBash

Technical Skills

CalibrationCode OrganizationConfiguration ManagementData EngineeringData ProcessingDetector Simulation

DUNE/larnd-sim

Apr 2025 Apr 2025
1 Month active

Languages Used

Python

Technical Skills

CUDAPerformance Optimization