nu-radio/NuRadioMC
Nov 2024 – Nov 2024
1 Month active
Languages Used
Python
Technical Skills
Data AnalysisDebuggingFile ManagementPython DevelopmentSignal Processing
Arthur Corstanje
PROFILE
Arthur Corstanje
During November 2024, Arjen Corstanje enhanced the NuRadioMC repository by developing two targeted features focused on data quality and signal processing. He implemented persistent RFI filtering debug plots, saving per-event PDF outputs in structured directories with clear labeling to support reproducibility and post-mortem analysis. Additionally, he updated the SNR-based polarization classification to use the standard deviation of the absolute Hilbert envelope, aligning with established signal processing practices for more reliable results. Working primarily in Python, Arjen demonstrated skills in data analysis, debugging, and file management. The work reflects a disciplined, traceable approach to feature development and code maintenance.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
38
Activity Months1
Your Network
35 people
Work History
November 2024
2 Commits • 2 Features
Nov 1, 2024Month: 2024-11 – NuRadioMC: Delivered two feature-focused improvements that enhance debugging, data quality, and signal-processing accuracy. Implemented Persistent RFI filtering debug plots by saving per-event PDFs and preserving output in event-specific directories with filenames indicating whether they represent the median spectrum or RFI cleaning flags (commit a18b55bd11cab42aa28a57943c5725e2671bda76). Implemented SNR-based polarization classification using the standard deviation of the absolute Hilbert envelope, aligning with standard signal-processing practice and improving determination of the dominant polarization (commit 4d51156d75671f5637adb009db65194de15c3de0). No major bugs fixed reported for this period. Impact: improved data quality controls, reproducibility, and debugging capabilities, along with more reliable polarization classification. Technologies/skills demonstrated: Python, signal processing (Hilbert transform, envelope analysis), per-event directory management, PDF plotting for debugging, and disciplined commit history for traceability.
2 Commits • 2 Features
Nov 1, 2024Month: 2024-11 – NuRadioMC: Delivered two feature-focused improvements that enhance debugging, data quality, and signal-processing accuracy. Implemented Persistent RFI filtering debug plots by saving per-event PDFs and preserving output in event-specific directories with filenames indicating whether they represent the median spectrum or RFI cleaning flags (commit a18b55bd11cab42aa28a57943c5725e2671bda76). Implemented SNR-based polarization classification using the standard deviation of the absolute Hilbert envelope, aligning with standard signal-processing practice and improving determination of the dominant polarization (commit 4d51156d75671f5637adb009db65194de15c3de0). No major bugs fixed reported for this period. Impact: improved data quality controls, reproducibility, and debugging capabilities, along with more reliable polarization classification. Technologies/skills demonstrated: Python, signal processing (Hilbert transform, envelope analysis), per-event directory management, PDF plotting for debugging, and disciplined commit history for traceability.
November 2024
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance60.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Data AnalysisDebuggingFile ManagementPython DevelopmentSignal Processing
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