DUNE/ndlar_flow
Nov 2024 – Feb 2025
4 Months active
Languages Used
PythonYAMLJSON
Technical Skills
Data AnalysisData ReconstructionMachine LearningSignal ProcessingSoftware EngineeringConfiguration Management
Stephen Greenberg
PROFILE
Stephen Greenberg
Stephen Greenberg contributed to the DUNE/ndlar_flow repository by developing and refining charge reconstruction and calibration features for embedded systems in Python. Over four months, he implemented a multi-stage noise filtering pipeline, adaptive low current filters with channel-specific thresholds, and ADC droop calibration logic that accounts for chip-level voltage variations, all aimed at improving the fidelity of reconstructed signals. He enhanced configuration management using YAML and JSON, adding detailed documentation to facilitate onboarding and reduce misconfiguration risk. His work demonstrated depth in data calibration, signal processing, and maintainable software engineering, resulting in robust, traceable, and reproducible data analysis workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
4
Lines of code
525
Activity Months4
Your Network
198 people
Work History
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025 (2025-02) monthly summary for DUNE/ndlar_flow focusing on delivering better noise filtering and robust configuration handling. Highlights include channel-specific low current filtering and ADC calibration tuning, with strong emphasis on maintainability and deterministic behavior across channel configurations.
1 Commits • 1 Features
Feb 1, 2025February 2025 (2025-02) monthly summary for DUNE/ndlar_flow focusing on delivering better noise filtering and robust configuration handling. Highlights include channel-specific low current filtering and ADC calibration tuning, with strong emphasis on maintainability and deterministic behavior across channel configurations.
February 2025
January 2025
1 Commits • 1 Features
Jan 1, 20252025-01 Monthly Summary (DUNE/ndlar_flow) - Focus: Implement ADC droop calibration for hit charge in CalibHitBuilder, enabling per-chip calibration and improved charge measurement fidelity across all calibrations. - Scope: Feature delivery with tracked commit; no explicit bug fixes reported in this period for this repo.
January 2025
1 Commits • 1 Features
Jan 1, 20252025-01 Monthly Summary (DUNE/ndlar_flow) - Focus: Implement ADC droop calibration for hit charge in CalibHitBuilder, enabling per-chip calibration and improved charge measurement fidelity across all calibrations. - Scope: Feature delivery with tracked commit; no explicit bug fixes reported in this period for this repo.
December 2024
1 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for DUNE/ndlar_flow: Focused on improving configuration maintainability by documenting CalibNoiseFilter.yaml. Delivered detailed comments clarifying parameter purposes and references to external docs, facilitating faster onboarding and fewer misconfigurations. No major bugs fixed this month; maintenance emphasis on documentation and knowledge transfer.
1 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for DUNE/ndlar_flow: Focused on improving configuration maintainability by documenting CalibNoiseFilter.yaml. Delivered detailed comments clarifying parameter purposes and references to external docs, facilitating faster onboarding and fewer misconfigurations. No major bugs fixed this month; maintenance emphasis on documentation and knowledge transfer.
December 2024
November 2024
1 Commits • 1 Features
Nov 1, 2024In November 2024, the DUNE/ndlar_flow effort delivered key enhancements to the charge reconstruction pipeline. A Noise Filtering stage was implemented, integrating three filters (low current, correlated post-trigger, and hot pixel) to improve the quality of reconstructed hits. Hit-building was updated to include chip and channel IDs, enhancing traceability for downstream analyses, and the charge calculation was adjusted to use hardcoded conversion factors for consistent calibration across datasets. The changes were merged into develop from the feature-noise-filter work stream, consolidating the noise-filter improvements and aligning with prior work referenced by the commit history. Overall this month focused on robust feature delivery, code quality, and preparing the ground for higher-quality data products. No explicit bug fixes were documented in this month; the emphasis was on feature development, integration, and calibration groundwork.
November 2024
1 Commits • 1 Features
Nov 1, 2024In November 2024, the DUNE/ndlar_flow effort delivered key enhancements to the charge reconstruction pipeline. A Noise Filtering stage was implemented, integrating three filters (low current, correlated post-trigger, and hot pixel) to improve the quality of reconstructed hits. Hit-building was updated to include chip and channel IDs, enhancing traceability for downstream analyses, and the charge calculation was adjusted to use hardcoded conversion factors for consistent calibration across datasets. The changes were merged into develop from the feature-noise-filter work stream, consolidating the noise-filter improvements and aligning with prior work referenced by the commit history. Overall this month focused on robust feature delivery, code quality, and preparing the ground for higher-quality data products. No explicit bug fixes were documented in this month; the emphasis was on feature development, integration, and calibration groundwork.
Activity
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Quality Metrics
Correctness87.6%
Maintainability85.0%
Architecture75.0%
Performance72.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
JSONPythonYAML
Technical Skills
Configuration ManagementData AnalysisData CalibrationData ReconstructionDocumentationEmbedded SystemsMachine LearningPython DevelopmentSignal ProcessingSoftware Engineering
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