qubicsoft/qubic
Feb 2025 – Feb 2025
1 Month active
Languages Used
PythonYAML
Technical Skills
ConfigurationData HandlingDebuggingInstrument SimulationNoise ModelingSoftware Refactoring
Alexandre Huchet
PROFILE
Alexandre Huchet
During February 2025, Huchet developed a unified noise management and instrument acquisition framework for the qubicsoft/qubic repository, focusing on DB and UWB instruments. By introducing the QubicTotNoise class, Huchet consolidated noise modeling and acquisition logic, streamlining cross-instrument workflows. The work addressed a critical missing component map file, resolving shape inconsistencies in FMM UWB and CMM. Using Python and YAML, Huchet enhanced testing and debugging by adding default instrument settings and debugging hooks, which improved reliability and reduced validation time. The project demonstrated depth in configuration, data handling, and software refactoring, resulting in more maintainable and efficient instrument simulation code.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
1,161
Activity Months1
Your Network
42 people
Work History
February 2025
2 Commits • 1 Features
Feb 1, 2025February 2025: Delivered a unified noise management and instrument acquisition framework for DB/UWB by introducing the QubicTotNoise class and consolidating instrument acquisition flows. Fixed critical environment issues, including a missing AllDataSet_Components_MapMaking.pkl, which resolved shape problems in FMM UWB and CMM. Enhanced testing and debugging with default DB instrument settings and debugging hooks. Result: greater cross-instrument reliability, reduced debugging time, and accelerated feature validation.
2 Commits • 1 Features
Feb 1, 2025February 2025: Delivered a unified noise management and instrument acquisition framework for DB/UWB by introducing the QubicTotNoise class and consolidating instrument acquisition flows. Fixed critical environment issues, including a missing AllDataSet_Components_MapMaking.pkl, which resolved shape problems in FMM UWB and CMM. Enhanced testing and debugging with default DB instrument settings and debugging hooks. Result: greater cross-instrument reliability, reduced debugging time, and accelerated feature validation.
February 2025
Activity
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Quality Metrics
Correctness70.0%
Maintainability70.0%
Architecture60.0%
Performance50.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonYAML
Technical Skills
ConfigurationData HandlingDebuggingInstrument SimulationNoise ModelingSoftware Refactoring
Repositories Contributed To
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