roman-corgi/corgidrp
Oct 2025 – Oct 2025
1 Month active
Languages Used
Python
Technical Skills
Data ProcessingImage CorrectionImage RotationPytestScientific ComputingTesting
clarissardoo
PROFILE
Clarissardoo
Clarissa Rizzo developed polarization data support for the roman-corgi/corgidrp repository, focusing on enhancing Northup processing and distortion correction workflows. She implemented robust handling of 3D polarization data, ensuring correct image rotation and WCS updates across all polarization planes. Using Python and leveraging scientific computing and testing frameworks like Pytest, Clarissa validated new features with comprehensive end-to-end and unit tests. Her approach included dual-pass distortion correction for independent polarization frames and careful data shape management. The work enabled more efficient and reliable analysis of polarized datasets, maintaining compatibility with existing pipelines and demonstrating depth in both data processing and testing.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
2
Lines of code
713
Activity Months1
Your Network
33 people
Work History
October 2025
3 Commits • 2 Features
Oct 1, 2025October 2025 performance summary for roman-corgi/corgidrp: Delivered polarization data support across Northup processing and distortion correction with end-to-end test coverage and robust data shape handling. Implemented pol_data flag validation, ensured correct rotation and WCS updates across all polarization planes, and extended distortion correction to process polarization data by iterating twice for both frames. These changes enable researchers to analyze polarized data more efficiently and with higher confidence, while preserving compatibility with existing workflows.
3 Commits • 2 Features
Oct 1, 2025October 2025 performance summary for roman-corgi/corgidrp: Delivered polarization data support across Northup processing and distortion correction with end-to-end test coverage and robust data shape handling. Implemented pol_data flag validation, ensured correct rotation and WCS updates across all polarization planes, and extended distortion correction to process polarization data by iterating twice for both frames. These changes enable researchers to analyze polarized data more efficiently and with higher confidence, while preserving compatibility with existing workflows.
October 2025
Activity
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Quality Metrics
Correctness96.6%
Maintainability86.6%
Architecture86.6%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Data ProcessingImage CorrectionImage RotationPytestScientific ComputingTestingUnit TestingWCS Handling
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