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First, we find the optimal reference using the wcs's find_optimal_celestial_wcs We pass the inputs_fits_list, optimized_wcs, and optimized shape to get the arrays and footprints using wcs's reproject_adaptive Then, we pass the arrays and footprints to get the cropped data using prepare_for_sum Which returns the largest interior rectangle found in the stacked images
jnation3406
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Feb 18, 2026
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A few questions and comments but in general looks good. I think we will want to add reprojection as an option to other operations as well, so its probably worth moving all the helper functions into there own utils file. We should make another story and check in with Rachel on what other operations she wants to have the option to reproject on.
| c0, c1 = cols[0], cols[-1] + 1 | ||
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| # now shrink until the *edges* are fully valid | ||
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This iterative approach seems like it'll be slow, but I can't immediately think of a more efficient way
…3.11. everything runs smoothly
… since they don't work
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FEATURE: Stacking - reprojection
Background
Users could only do simple stacking. So when the input data was intended to track objects in our Solar System, the stacked output would be blurry. Now, with reprojection, the users can stack input data with moving objects and the output shows the movement of the object with the alignment being in the background.
Implementation
We obtain the
optimized_wcsandotpimized_shapeby using wcs'sfind_optimal_celestial_wcs.We then pass these two values to
reproject_images_to_referencealong with the list ofinput_fitsand we get anarrayand afootprint.These are then used to crop the data correctly. Because some values are
NaNand therefore return jagged edges, we must remove them and find the largest internal rectangle in the footprint.This is done through
prepare_for_sumwhich takes the arrays (images) and footprints. We find thecommon_b(oundary)boxby cropping the boundary box from the footprint.crop_bbox_from_footprinttakes the footprints and returns the coordinates of rows and columns with the largest internal rectangle in the footprint per each footprint.Then, we find where the boundary boxes intersect (
intersect_bboxes) and return those coordinates.Lastly, we crop the intersected boundary box.
Note: there is a library that would take care of the logic to find the largest internal rectangle, but it would mean adding another dependency @jnation3406 let me know what you think https://github.com/OpenStitching/lir
VISUALS
Screen.Recording.2026-02-17.at.2.30.02.PM.mov