SBNSoftware/sbndcode
Sep 2025 – Sep 2025
1 Month active
Languages Used
Python
Technical Skills
Command-line ScriptingData VisualizationROOT AnalysisScientific Computing
Francisco Javier Nicolás-Arnaldos
PROFILE
Francisco Javier Nicolás-arnaldos
During September 2025, Francisco J. Nicolás developed a PTB Trigger Event Visualization Tool for the SBNSoftware/sbndcode repository, focusing on improving data quality assessment for analysts. He implemented the tool in Python, leveraging command-line scripting and ROOT analysis to process PTB data and generate stacked histograms of Low Level and High Level Trigger events relative to a reference time. The tool features customizable CLI options and outputs visualizations as PDF files, streamlining the review process for trigger behavior. Francisco concentrated on robust feature delivery and code quality, providing a practical solution that enhances scientific computing workflows without addressing major bug fixes.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
233
Activity Months1
Your Network
58 peopleSame Organization
@ugr.es3
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55
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Dom BrailsfordMember
Work History
September 2025
1 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for SBNSoftware/sbndcode focused on feature delivery and enabling analysts to quickly assess trigger behavior in PTB data. The main deliverable was a visualization tool that enhances data interpretation and supports faster data quality checks, contributing to safer and more efficient data processing pipelines.
1 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for SBNSoftware/sbndcode focused on feature delivery and enabling analysts to quickly assess trigger behavior in PTB data. The main deliverable was a visualization tool that enhances data interpretation and supports faster data quality checks, contributing to safer and more efficient data processing pipelines.
September 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Command-line ScriptingData VisualizationROOT AnalysisScientific Computing
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