DUNE/waffles
Feb 2025 – Oct 2025
8 Months active
Languages Used
C++PythonROOTYAMLCSVShell
Technical Skills
Code OrganizationConfiguration ManagementData AnalysisData ProcessingData VisualizationFile Handling
fgalizzi
PROFILE
Fgalizzi
Federico Galati developed and maintained core data analysis pipelines for the DUNE/waffles repository, focusing on waveform processing, time resolution analysis, and self-triggering studies. He engineered robust Python and ROOT-based workflows that automated data ingestion, channel mapping, and configuration management, enabling scalable, reproducible analyses across large datasets. His work included building HDF5/CSV data loaders, optimizing file I/O, and implementing advanced plotting and signal processing routines. By refactoring code for maintainability and integrating performance optimizations, Federico improved data quality, analysis speed, and reliability. His contributions demonstrated depth in scientific computing, data engineering, and automation, supporting evolving experimental requirements.
Overall Statistics
Feature vs Bugs
90%Features
Repository Contributions
63Total
Bugs
2
Commits
63
Features
18
Lines of code
13,744
Activity Months8
Work History
October 2025
3 Commits • 1 Features
Oct 1, 2025Month: 2025-10 — This month focused on stabilizing data access, restoring critical functionality, and hardening the noise-results workflow in DUNE/waffles. Key outcomes include performance improvements through caching, restoration of waveform data reading from HDF5, and robust fixes that improve portability and reliability across environments.
3 Commits • 1 Features
Oct 1, 2025Month: 2025-10 — This month focused on stabilizing data access, restoring critical functionality, and hardening the noise-results workflow in DUNE/waffles. Key outcomes include performance improvements through caching, restoration of waveform data reading from HDF5, and robust fixes that improve portability and reliability across environments.
October 2025
September 2025
10 Commits • 4 Features
Sep 1, 2025September 2025 performance summary for DUNE/waffles focused on delivering automated data workflows, robust channel mapping between Daphne and NP04, and scalable analysis configuration. The month emphasized automation, reproducibility, and clearer APIs to accelerate noise studies and Coldbox data preparation, enabling faster study iterations and higher data quality across NP04 DAPHNE workflows.
September 2025
10 Commits • 4 Features
Sep 1, 2025September 2025 performance summary for DUNE/waffles focused on delivering automated data workflows, robust channel mapping between Daphne and NP04, and scalable analysis configuration. The month emphasized automation, reproducibility, and clearer APIs to accelerate noise studies and Coldbox data preparation, enabling faster study iterations and higher data quality across NP04 DAPHNE workflows.
August 2025
3 Commits • 1 Features
Aug 1, 2025Month: 2025-08 — Focused on advancing the self-triggering analysis pipeline for DUNE/waffles, delivering feature enhancements, robust data products, and improved visualization to enable informed threshold decisions and clearer communication of performance metrics. Commits referenced: e1ea122, bf6e487, eb3134f.
3 Commits • 1 Features
Aug 1, 2025Month: 2025-08 — Focused on advancing the self-triggering analysis pipeline for DUNE/waffles, delivering feature enhancements, robust data products, and improved visualization to enable informed threshold decisions and clearer communication of performance metrics. Commits referenced: e1ea122, bf6e487, eb3134f.
August 2025
July 2025
11 Commits • 3 Features
Jul 1, 2025July 2025 monthly summary for DUNE/waffles: Three core features delivered and several robustness improvements across the STtrigger pipeline, channel mapping, and self-triggered analysis plotting. The work provides end-to-end data processing from waveform conversion to analysis visualization, with a strong emphasis on reliability, reproducibility, and enabling scalable workflows for multi-run studies.
July 2025
11 Commits • 3 Features
Jul 1, 2025July 2025 monthly summary for DUNE/waffles: Three core features delivered and several robustness improvements across the STtrigger pipeline, channel mapping, and self-triggered analysis plotting. The work provides end-to-end data processing from waveform conversion to analysis visualization, with a strong emphasis on reliability, reproducibility, and enabling scalable workflows for multi-run studies.
June 2025
10 Commits • 2 Features
Jun 1, 2025June 2025 — DUNE/waffles: Time Resolution Analysis enhancements and streamlined plotting workflow. Delivered end-to-end improvements to the time resolution analysis core and data pipeline, enabling more reliable, scalable, and reproducible results across datasets. Key impact includes API simplifications, flexible data loading (HDF5/CSV), external run/config management, channel mappings, and robust alignment/validation, as well as plotting against standard analysis folders with auto-processing of root files. These changes reduce setup time, improve data integrity, and simplify result visualization for stakeholders.
10 Commits • 2 Features
Jun 1, 2025June 2025 — DUNE/waffles: Time Resolution Analysis enhancements and streamlined plotting workflow. Delivered end-to-end improvements to the time resolution analysis core and data pipeline, enabling more reliable, scalable, and reproducible results across datasets. Key impact includes API simplifications, flexible data loading (HDF5/CSV), external run/config management, channel mappings, and robust alignment/validation, as well as plotting against standard analysis folders with auto-processing of root files. These changes reduce setup time, improve data integrity, and simplify result visualization for stakeholders.
June 2025
April 2025
10 Commits • 2 Features
Apr 1, 2025Monthly work summary for 2025-04 focused on delivering analytics enhancements in the DUNE/waffles repository and stabilizing data processing pipelines. The work center was on noise analysis/FFT integration and time-resolution analysis with improved plotting, configuration, and data handling to accelerate insights from waveform data.
April 2025
10 Commits • 2 Features
Apr 1, 2025Monthly work summary for 2025-04 focused on delivering analytics enhancements in the DUNE/waffles repository and stabilizing data processing pipelines. The work center was on noise analysis/FFT integration and time-resolution analysis with improved plotting, configuration, and data handling to accelerate insights from waveform data.
March 2025
5 Commits • 3 Features
Mar 1, 2025March 2025 performance summary for DUNE/waffles focused on delivering core analysis enhancements, robust data handling, and extended noise study capabilities. The team completed ROOT-based time alignment for time resolution analysis, expanded channel mapping to support two maps with separated data structures, and enhanced noise studies through advanced WaveformSet integration and configurable channel ignoring. These efforts improve data quality, analysis throughput, and readiness for future data formats, while maintaining strong traceability back to commits.
5 Commits • 3 Features
Mar 1, 2025March 2025 performance summary for DUNE/waffles focused on delivering core analysis enhancements, robust data handling, and extended noise study capabilities. The team completed ROOT-based time alignment for time resolution analysis, expanded channel mapping to support two maps with separated data structures, and enhanced noise studies through advanced WaveformSet integration and configurable channel ignoring. These efforts improve data quality, analysis throughput, and readiness for future data formats, while maintaining strong traceability back to commits.
March 2025
February 2025
11 Commits • 2 Features
Feb 1, 2025February 2025 monthly summary for DUNE/waffles focusing on waveform analysis enhancements. Delivered two major features: Time Resolution Analysis Framework and Noise Analysis Refactor with plotting enhancements. These efforts increased data quality, reduced analysis time, and enabled scalable, multi-channel processing with config-ready workflows. This set the foundation for more reliable time resolution studies and richer visualization tooling across waveform datasets.
February 2025
11 Commits • 2 Features
Feb 1, 2025February 2025 monthly summary for DUNE/waffles focusing on waveform analysis enhancements. Delivered two major features: Time Resolution Analysis Framework and Noise Analysis Refactor with plotting enhancements. These efforts increased data quality, reduced analysis time, and enabled scalable, multi-channel processing with config-ready workflows. This set the foundation for more reliable time resolution studies and richer visualization tooling across waveform datasets.
Activity
Loading activity data...
Quality Metrics
Correctness84.8%
Maintainability85.0%
Architecture83.0%
Performance73.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++CSVPythonROOTShellYAML
Technical Skills
AutomationClass DesignCode OptimizationCode OrganizationConfiguration ManagementData AnalysisData Analysis ConfigurationData ConfigurationData EncapsulationData EngineeringData ManagementData ProcessingData VisualizationDebuggingDetector Calibration
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline