
Aneesh contributed to the roman-corgi/corgidrp repository by developing and refining features for astrometric calibration, imaging mode differentiation, and data integrity over a three-month period. Using Python and its testing frameworks, Aneesh implemented VISTYPE-based processing to distinguish coronagraphic imaging from spectroscopy, enhanced calibration workflows, and improved header management for L3/L4 imaging products. The work included robust error handling, metadata management, and comprehensive end-to-end and unit testing, resulting in more reliable data outputs and streamlined test infrastructure. Aneesh’s technical approach emphasized maintainability and traceability, with updates to documentation and data formats that clarified provenance and improved user-facing clarity.
March 2026 monthly summary for roman-corgi/corgidrp focused on delivering VISTYPE-based processing, stabilizing test infrastructure, and enhancing the on-sky dispersion calibration workflow. The work improved cross-mode consistency (coronagraphic imaging vs spectroscopy), strengthened end-to-end validation, and reduced maintenance overhead through mocks simplification.
March 2026 monthly summary for roman-corgi/corgidrp focused on delivering VISTYPE-based processing, stabilizing test infrastructure, and enhancing the on-sky dispersion calibration workflow. The work improved cross-mode consistency (coronagraphic imaging vs spectroscopy), strengthened end-to-end validation, and reduced maintenance overhead through mocks simplification.
February 2026 (2026-02) — Delivered foundational data quality, provenance, and documentation improvements for the corgidrp repository, focusing on header hygiene, astrometric calibration, data lineage, and user clarity. This work reduces downstream processing errors, improves traceability, and accelerates analysis readiness across L3/L4 imaging products.
February 2026 (2026-02) — Delivered foundational data quality, provenance, and documentation improvements for the corgidrp repository, focusing on header hygiene, astrometric calibration, data lineage, and user clarity. This work reduces downstream processing errors, improves traceability, and accelerates analysis readiness across L3/L4 imaging products.
January 2026: Delivered fixes to Satspot saturation prevention and end-to-end test cropping in roman-corgi/corgidrp. Fixed improper e2e cropping and implemented an exposure-time guard for satspot files to prevent saturation when exposure times exceed 100 seconds, improving output reliability and test stability.
January 2026: Delivered fixes to Satspot saturation prevention and end-to-end test cropping in roman-corgi/corgidrp. Fixed improper e2e cropping and implemented an exposure-time guard for satspot files to prevent saturation when exposure times exceed 100 seconds, improving output reliability and test stability.

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