SegmentLinking/cmssw
Dec 2024 – Jan 2025
2 Months active
Languages Used
Python
Technical Skills
Data AnalysisPhysics AnalysisData Analysis Configuration
Nicola Amapane
PROFILE
Nicola Amapane
Worked on enhancing muon data analysis within the SegmentLinking/cmssw repository by introducing a bestTrackType integer to the muon data structure, enabling more granular identification and improved downstream analytics. Leveraged Python and C++ to extend CMSSW data models and implemented disciplined version control practices throughout the process. Additionally, contributed a targeted configuration update to nanoDQM, adding a BestTrackType plot for real-time monitoring of muon track types, which supports diagnostics and quality assurance workflows. The work focused on data analysis, configuration, and physics analysis, delivering stable, low-risk features that improve observability and enable more precise event selection in muon studies.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
2
Activity Months2
Your Network
418 peopleSame Organization
@cern.ch336
Shared Repositories
82
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Work History
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 achievements focused on observability and quality monitoring in the CMSSW NDA project segment. Implemented a targeted DQM configuration improvement by adding a BestTrackType plot to nanoDQM within SegmentLinking/cmssw to monitor muon track types. The change is a minor config update with low risk and immediate value for diagnostics and QA workflows.
1 Commits • 1 Features
Jan 1, 2025January 2025 achievements focused on observability and quality monitoring in the CMSSW NDA project segment. Implemented a targeted DQM configuration improvement by adding a BestTrackType plot to nanoDQM within SegmentLinking/cmssw to monitor muon track types. The change is a minor config update with low risk and immediate value for diagnostics and QA workflows.
January 2025
December 2024
1 Commits • 1 Features
Dec 1, 2024In December 2024, delivered the Muon Identification Track Type Metadata feature to SegmentLinking/cmssw, adding a bestTrackType integer to the muon data structure to store the track type used for muon identification. This enables richer muon metadata, improving identification workflows and downstream analyses. No major bugs fixed this month. Overall, the work enhances data quality and enables more granular muon analysis, supporting more precise event selection and faster insights. Technologies demonstrated include CMSSW data structure extension, C++ metadata modeling, and disciplined version control.
December 2024
1 Commits • 1 Features
Dec 1, 2024In December 2024, delivered the Muon Identification Track Type Metadata feature to SegmentLinking/cmssw, adding a bestTrackType integer to the muon data structure to store the track type used for muon identification. This enables richer muon metadata, improving identification workflows and downstream analyses. No major bugs fixed this month. Overall, the work enhances data quality and enables more granular muon analysis, supporting more precise event selection and faster insights. Technologies demonstrated include CMSSW data structure extension, C++ metadata modeling, and disciplined version control.
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance100.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Data AnalysisData Analysis ConfigurationPhysics Analysis
Repositories Contributed To
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