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JP-3127: Fix bounding box in MRS TSO observations #7492
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Codecov ReportPatch coverage:
Additional details and impacted files@@ Coverage Diff @@
## master #7492 +/- ##
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- Coverage 77.60% 77.59% -0.01%
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Files 452 452
Lines 36095 36094 -1
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- Hits 28010 28008 -2
- Misses 8085 8086 +1
... and 1 file with indirect coverage changes Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here. ☔ View full report in Codecov by Sentry. |
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Looks good to me. Maybe a brief (1 or 2 sentence) description of what the problem was and how it's been fixed would be nice in the description section of the ticket.
Regtest run started at https://plwishmaster.stsci.edu:8081/job/RT/job/JWST-Developers-Pull-Requests/601 Whoops, forgot to pin the CRDS context for run 601, so it tried to run snowball flagging without opencv being installed. I've started another run with context pinned to 1062, so that snowball doesn't run: |
Regtest run https://plwishmaster.stsci.edu:8081/job/RT/job/JWST-Developers-Pull-Requests/606/ using context 1068 shows 6 expected differences in MRS TSO results. Looks good. |
Resolves JP-3127
This PR fixes a problem with the computation of the bounding box of a MIRI MRS TSO observation. The bounding box is defined by the shape of the data. The code assumed an MRS observation, the input to assign_wcs is always a 2D image and used the shape of the data array in a simplistic way to determine the bounding box. Since TSO observations are cubes this created very small bounding boxes. Fixed by calling the correct function,
transform_bbox_from_shape
, already available in assign_wcs/utils.pyChecklist for maintainers
CHANGES.rst
within the relevant release sectionHow to run regression tests on a PR