Improve Gaia alignment robustness, diagnostics, and fallback behavior in WCS pipeline#78
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- Implemented unit tests to verify the behavior of the align_to_gaia function when the Gaia catalog is unavailable or when SExtractor returns no sources. - Enhanced the solve_wcs module with helper functions for logging and writing fallback headers to FITS files, ensuring clear documentation of fallback reasons in the header. - Improved the validation of refined WCS by adding checks for pixel scale and anisotropy, enhancing the robustness of the WCS alignment process.
- Added functionality to the align_to_gaia function to handle scenarios where the Gaia catalog is unavailable or SExtractor returns no sources. - Introduced logging and fallback header writing in the solve_wcs module for better documentation of fallback reasons. - Enhanced validation checks for refined WCS, including pixel scale and anisotropy, to improve robustness.
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Summary
solve_wcs.align_to_gaiawhere iterative matching could collapse and produce pathological WCS solutions.GAIAFAIL) plus fallback dispersion defaults so downstream selection/stacking remains stable.tests/test_wcs.py(no Gaia catalog / no SExtractor detections).Why
In real reductions with sparse Gaia matches (e.g., 6–7 stars), Gaia refinement could intermittently yield unstable/sheared WCS fits, causing severe reprojection distortion or frame loss. This PR makes the alignment stage resilient and transparent while preserving usable coarse solutions.
Validation
pytest tests/test_wcs.py -k "not integration"passes.pytest tests -m "not integration") passes.