blackSwanCS/Higgs_collaboration_B
Jun 2025 – Jun 2025
1 Month active
Languages Used
Python
Technical Skills
Data AnalysisData VisualizationMachine LearningNumerical MethodsPythonPython Scripting
Benjamin Plumejeau
PROFILE
Benjamin Plumejeau
Developed a comprehensive TES Uncertainty Analysis and Score Histogram Shifting feature for the blackSwanCS/Higgs_collaboration_B repository, focusing on systematic uncertainty quantification in scientific computing workflows. Leveraging Python and statistical modeling, the work refined the tes_fitter module to support tes_range-based fitting and per-bin delta calculations, enabling granular analysis of uncertainty across histogram bins. Polynomial fitting coefficients were generated to support robust modeling, and plotting utilities were implemented to visualize nominal versus shifted score distributions under varying TES scenarios. The final fit function was completed, and groundwork was established for future JES uncertainty analysis, demonstrating depth in data analysis and visualization.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
7Total
Bugs
0
Commits
7
Features
1
Lines of code
930
Activity Months1
Your Network
41 peopleShared Repositories
21
Work History
June 2025
7 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for blackSwanCS/Higgs_collaboration_B: Delivered a robust TES Uncertainty Analysis and Score Histogram Shifting feature. Refined the tes_fitter and integrated tes_range-based fitting, enabling per-bin delta calculations and generation of polynomial fitting coefficients. Implemented granular bin-by-bin uncertainty handling (loop over bins to compute delta S and Delta N) and shifted score distributions under varying TES scenarios. Developed plotting utilities to compare nominal vs shifted histograms, including a visualization for a chosen TES value. Finalized tes_fitter version for team stats and completed the final fit function, laying the groundwork for JES uncertainty analysis (placeholder).
7 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for blackSwanCS/Higgs_collaboration_B: Delivered a robust TES Uncertainty Analysis and Score Histogram Shifting feature. Refined the tes_fitter and integrated tes_range-based fitting, enabling per-bin delta calculations and generation of polynomial fitting coefficients. Implemented granular bin-by-bin uncertainty handling (loop over bins to compute delta S and Delta N) and shifted score distributions under varying TES scenarios. Developed plotting utilities to compare nominal vs shifted histograms, including a visualization for a chosen TES value. Finalized tes_fitter version for team stats and completed the final fit function, laying the groundwork for JES uncertainty analysis (placeholder).
June 2025
Activity
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Quality Metrics
Correctness82.8%
Maintainability80.0%
Architecture80.0%
Performance62.8%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Data AnalysisData VisualizationMachine LearningNumerical MethodsPythonPython ScriptingScientific ComputingStatistical ModelingSystematic Uncertainty Analysis
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