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fix(hilbert): support offset-centre circular masks - #313
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Previously Hilbert image-mesh raised PixelizationException for offset-centre circular masks whose centres didn't land on a pixel half-integer, and would have silently sampled the wrong region of the image for those that slipped through. This commit fixes both halves of the bug. - Mask2D.is_circular rewritten to be quantization-robust: bbox square within one pixel, geometric centre pixel unmasked, and a reference circular mask reconstructed from the inferred centre+radius must match the input within rim quantization tolerance. The new predicate correctly accepts offset circles and rejects annular and square masks that previously false-passed. - Mask2D.circular_radius now derives the radius from the bbox extent rather than the central row count. Numerically identical for centred masks; correct for offset centres. - hilbert.image_and_grid_from now translates Hilbert sample points by mask_centre, so the curve actually probes the masked region of the image. For masks centred at the origin (every current test/smoke case) the shift is a no-op and likelihoods are bit-identical. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Summary
Fixes a user-reported bug where
Hilbertimage-mesh raisedPixelizationExceptionfor circular masks with offset centres (e.g. lens systems whose mask centre is not at the field-of-view origin). The bug had two compounding halves:Mask2D.is_circularreturnedFalsefor genuinely circular offset masks due to pixel-quantization asymmetry, and even if the check were bypassed the Hilbert sampler always probed the image around(0, 0)rather than the mask centre.API Changes
Mask2D.is_circularis now quantization-robust and correctly distinguishes filled discs from annular and square masks (previously annular masks were false-positives).Mask2D.circular_radiusderives the radius from the bbox extent. Numerically identical for centred masks.hilbert.image_and_grid_fromgains an optionalmask_centre=(0.0, 0.0)parameter and translates the Hilbert sample points by it. For masks centred at the origin (every current test/smoke case) this is a no-op.See full details below.
Test Plan
test_autoarray/mask/test_mask_2d.pycover offset centres (5 parametrised positions), annular masks, square unmasked regions, andcircular_radiusfor offset centres.test_autoarray/inversion/pixelization/image_mesh/test_hilbert.pyasserts that the resulting mesh points lie inside the mask's circle for an offset-centre mask.[-1.02590674, -1.70984456]), confirming Delaunay-Hilbert smoke tests will produce unchanged likelihoods.Full API Changes (for automation & release notes)
Changed Behaviour
Mask2D.is_circular— algorithm rewritten. Now returnsTruefor offset-centre circular masks (was: returnedFalsewhen centre offset caused pixel-quantization asymmetry). Now returnsFalsefor annular masks (was: returnedTruebecause central row/column counts were symmetric).Mask2D.circular_radius— computed from the bounding-box extent of the unmasked region (was: from the unmasked-pixel count in a single guessed central row). Numerically identical for centred masks; correct rather than spurious for offset centres.Changed Signature
autoarray.inversion.mesh.image_mesh.hilbert.image_and_grid_from(image, mask, mask_radius, pixel_scales, hilbert_length, mask_centre=(0.0, 0.0))— new trailing keywordmask_centre, defaults to(0.0, 0.0)so existing callers are unaffected.Migration
None required. All changes are either additive (new optional kwarg with backward-compatible default) or strictly bug-fix behaviour. Workspaces and tests using centred masks see no numerical change.
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