
Worked on the roman-corgi/corgidrp repository to enhance scientific data processing workflows, focusing on polarization data support and robust error handling. Developed features enabling Northup processing and distortion correction to handle 3D polarization data, ensuring correct rotation and WCS updates across all polarization planes. Improved test coverage using Pytest and mocking, aligning validation with real-world scenarios and increasing CI reliability. Addressed image header error handling for L4/L3 datasets, reducing processing risk and improving maintainability. Updated documentation in reStructuredText to clarify error reporting and processing history. All work was implemented in Python, emphasizing data validation, testing, and technical writing.
February 2026 monthly summary for roman-corgi/corgidrp: Delivered targeted bug fixes for L4/L3 image header handling, updated documentation for error reporting and processing history, and strengthened test coverage and code hygiene. These changes enhance data processing reliability for non-coron and polar L4 datasets and improve maintainability and troubleshooting.
February 2026 monthly summary for roman-corgi/corgidrp: Delivered targeted bug fixes for L4/L3 image header handling, updated documentation for error reporting and processing history, and strengthened test coverage and code hygiene. These changes enhance data processing reliability for non-coron and polar L4 datasets and improve maintainability and troubleshooting.
November 2025 performance summary for roman-corgi/corgidrp: focused on strengthening test coverage for bad pixel correction and improving test stability in CI. Implemented Bad Pixel Correction Testing Improvements by using mock polarization data across multiple frames to reflect production scenarios, increasing validation reliability and reducing regression risk. Cleaned test output by removing noise (no print statements) and added comments for maintainability. These changes reduce cycle time for bug fixes and PR reviews while aligning validation with real-world data.
November 2025 performance summary for roman-corgi/corgidrp: focused on strengthening test coverage for bad pixel correction and improving test stability in CI. Implemented Bad Pixel Correction Testing Improvements by using mock polarization data across multiple frames to reflect production scenarios, increasing validation reliability and reducing regression risk. Cleaned test output by removing noise (no print statements) and added comments for maintainability. These changes reduce cycle time for bug fixes and PR reviews while aligning validation with real-world data.
October 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 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.

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