LDMX-Software/pflib
Sep 2025 – Jan 2026
4 Months active
Languages Used
C++PythonYAML
Technical Skills
C++ DevelopmentCommand Line InterfaceConfiguration ManagementData AnalysisEmbedded SystemsFile Handling
Andreas Pettersson
PROFILE
Andreas Pettersson
Anders Pettersson contributed to the LDMX-Software/pflib repository by developing and enhancing features for hardware testing, calibration, and data analysis workflows. He implemented multi-channel calibration routines, YAML-based configuration management, and advanced data visualization tools such as 2D heatmaps and statistical utilities. Using C++ and Python, Anders improved the reliability of time scan tasks and streamlined data processing pipelines by introducing robust file handling and dynamic parameter management. His work addressed both feature development and bug fixes, demonstrating depth in embedded systems, signal processing, and user interface design, while ensuring traceability and maintainability through clear commit practices and documentation.
Overall Statistics
Feature vs Bugs
78%Features
Repository Contributions
11Total
Bugs
2
Commits
11
Features
7
Lines of code
4,472
Activity Months4
Work History
January 2026
3 Commits • 2 Features
Jan 1, 2026January 2026 monthly summary for LDMX-Software/pflib: Delivered key enhancements to data visualization and statistics, plus a targeted reliability fix. Key accomplishments include: 2D heatmap visualization for inv_vref/noinv_vref with derivative plotting and improved docs; new statistical utilities for mean and standard deviation; and a temporary n_links handling fix in ECONDEventPacket to prevent incorrect link counts in multi-channel scans. These changes improve data interpretation, accelerate analysis workflows, and reduce risk in event processing. Demonstrated strengths in Python development, data visualization, statistics, documentation, and cross-team collaboration.
3 Commits • 2 Features
Jan 1, 2026January 2026 monthly summary for LDMX-Software/pflib: Delivered key enhancements to data visualization and statistics, plus a targeted reliability fix. Key accomplishments include: 2D heatmap visualization for inv_vref/noinv_vref with derivative plotting and improved docs; new statistical utilities for mean and standard deviation; and a temporary n_links handling fix in ECONDEventPacket to prevent incorrect link counts in multi-channel scans. These changes improve data interpretation, accelerate analysis workflows, and reduce risk in event processing. Demonstrated strengths in Python development, data visualization, statistics, documentation, and cross-team collaboration.
January 2026
December 2025
4 Commits • 2 Features
Dec 1, 2025December 2025 monthly summary for LDMX-Software/pflib: Delivered two major feature sets that enhance calibration usability and data processing capabilities. LED Calibration Menu Enhancements introduces a menu-based LED calibration setup with prompts for offset adjustments and a reorganized calibration options layout to improve usability. Multi-Channel Calibration, Cross-Talk Scanning, and Scan Task Configuration implements multi-channel TOT calibration across channels, multi-channel cross-talk scanning, ADC performance assessment, and dynamic handling of link counts in scan tasks to support flexible data processing.
December 2025
4 Commits • 2 Features
Dec 1, 2025December 2025 monthly summary for LDMX-Software/pflib: Delivered two major feature sets that enhance calibration usability and data processing capabilities. LED Calibration Menu Enhancements introduces a menu-based LED calibration setup with prompts for offset adjustments and a reorganized calibration options layout to improve usability. Multi-Channel Calibration, Cross-Talk Scanning, and Scan Task Configuration implements multi-channel TOT calibration across channels, multi-channel cross-talk scanning, ADC performance assessment, and dynamic handling of link counts in scan tasks to support flexible data processing.
October 2025
1 Commits
Oct 1, 2025October 2025 monthly summary: Focused on stabilizing time scan configuration in pflib. Delivered a targeted bug fix that ensures tot and toa parameters are only included when totscan is true, preventing incorrect zero values and misconfigurations. This change improves reliability of the time scan task and reduces production risk. Key fix linked to commit 8f6b4eff8da8c2d7385cf6e963c910412f72dedf (issue #223). Result: more predictable behavior for downstream components and users. Maintained code quality through focused debugging, review, and traceability to the ticket.
1 Commits
Oct 1, 2025October 2025 monthly summary: Focused on stabilizing time scan configuration in pflib. Delivered a targeted bug fix that ensures tot and toa parameters are only included when totscan is true, preventing incorrect zero values and misconfigurations. This change improves reliability of the time scan task and reduces production risk. Key fix linked to commit 8f6b4eff8da8c2d7385cf6e963c910412f72dedf (issue #223). Result: more predictable behavior for downstream components and users. Maintained code quality through focused debugging, review, and traceability to the ticket.
October 2025
September 2025
3 Commits • 3 Features
Sep 1, 20252025-09 monthly summary for LDMX-Software/pflib: Delivered key enhancements to improve channel-level control, testing workflow, and multi-file data analysis. The changes enable selecting a specific channel for pulsing, add a YAML-based configuration to support Lund environment testing, and implement cross-file CSV analysis and plotting with multi-channel support and adjustable visualization limits. These deliverables reduce manual steps, improve test coverage, and provide a more scalable data analysis workflow, positively impacting reliability and decision-making in hardware testing and data processing.
September 2025
3 Commits • 3 Features
Sep 1, 20252025-09 monthly summary for LDMX-Software/pflib: Delivered key enhancements to improve channel-level control, testing workflow, and multi-file data analysis. The changes enable selecting a specific channel for pulsing, add a YAML-based configuration to support Lund environment testing, and implement cross-file CSV analysis and plotting with multi-channel support and adjustable visualization limits. These deliverables reduce manual steps, improve test coverage, and provide a more scalable data analysis workflow, positively impacting reliability and decision-making in hardware testing and data processing.
Activity
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Quality Metrics
Correctness85.4%
Maintainability81.8%
Architecture81.8%
Performance83.6%
AI Usage25.4%
Skills & Technologies
Programming Languages
C++PythonYAML
Technical Skills
Bug FixingC++C++ DevelopmentC++ developmentC++ programmingCMakeCommand Line InterfaceConfiguration ManagementData AnalysisEmbedded SystemsFile HandlingHardware TestingPlottingPython scriptingSoftware Development
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