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feat: oversampled PSF inversion wiring — mapping formalism (phase 2b) #356
Description
Activity
Phase 2b implemented — at the ship sign-off checkpoint
Committed locally on
feature/psf-oversample-inversion(efa985d2, not pushed). Diff: 5 files, +191/−3 (an initial line-ending normalization of two CRLF files was caught and reverted, so the diff is content-only).Verification
Leg Result Tests PyAutoArray 860 passed (3 new); downstream PyAutoGalaxy 940, PyAutoLens 334 against the branch Delta-kernel identity mapping_matrix_over_sampledmean-binned ==mapping_matrixto 1e-14End-to-end s=2 operated_mapping_matrix_listmatches an independent brute-force fine-raster convolution to ≤2.3e-16Guards linear-func objects, data_linear_func_matrixpreload, and sparsepsf_weighted_dataall raise under an oversampled PSFReview Surface: python-source flag. Verdict: CLEAN Memory profile ×s² FFT cube at s=2 / 1000 src ≈ 2.1 GB fp64 (vs 0.52 GB at s=1) — fine on A100, tight on 6 GB cards; feature stays opt-in, chunking / fp32 are the mitigations (full table in the drafted PR body) Awaiting ship approval (supervised
--auto): on approval the branch is pushed and the pending-release PR opens with the drafted body.🤖 Generated with Claude Code
🚢 Shipped (human-approved; workspace-level tests deferred to phase 3 by explicit decision): PR #357 (
pending-release). Ends at PR-open per the --auto contract — merge on your word. Phase 2c (PyAutoGalaxy consumer switch) is now unblocked and starting.🤖 Generated with Claude Code
✅ Merged as PR #357 (squash). Phase 2b complete — oversampled inversion wiring (mapping formalism) is on main. Workspace-level tests follow in phase 3.
🤖 Generated with Claude Code
- added a commit that references this issue
on Jul 8, 2026
Overview
Phase 2b of oversampled PSF convolution: wire the phase-2a Convolver API (#354, PR #355) into the inversion's mapping formalism, per §4 of the approved design (
PyAutoMind/feature/autoarray/oversampling_design.md, approved in #353). Blocked until PR #355 merges — it builds directly on the 2a API.Plan
Mapper.mapping_matrix_over_sampled: one row per sub-pixel, nosub_fractionfold (the existingmapping_matrixfolds sub-pixels to image resolution before the Convolver ever sees them, which is exactly what oversampled convolution must intercept).AbstractInversionImaging.operated_mapping_matrix_list(autoarray/inversion/inversion/imaging/abstract.py:104-116— the actual PSF application site;mapping.pyitself needs no logic change) through the oversampled Convolver path whenpsf.convolve_over_sample_size > 1.psf.kernel.nativedirectly and cannot support oversampling yet:InversionImagingSparse.psf_weighted_dataand the preloaded linear-func operated matrices (abstract.py:215-230).(ny·s, nx·s, n_src)) on a realistic pixelization before anything defaults on — the main risk flagged in the design; chunking is the noted mitigation.Detailed implementation plan
Affected Repositories
Branch Survey
Deferred to start (task is blocked on PR #355; survey ages out).
Suggested branch:
feature/psf-oversample-inversionImplementation Steps
inversion/mappers/abstract.py:mapping_matrix_over_sampledproperty reusing the existing sub→pix index maps (slim_for_sub_slim), emitting shape(n_unmasked·s², n_src)in per-pixel sub-block order — the 2a Convolver input format.inversion/inversion/imaging/abstract.py::operated_mapping_matrix_list: whenself.psf.convolve_over_sample_size > 1, passlinear_obj.mapping_matrix_over_sampledtopsf.convolved_mapping_matrix_from(which already handles the fine-grid scatter/convolve/bin from 2a); otherwise unchanged.InversionImagingSparse.psf_weighted_dataand the linear-func kernel consumers raiseInversionException/DatasetExceptionwhen the psf is oversampled (deferred formalism, per the approved design).mapping_matrix_over_sampledbinned by mean ==mapping_matrix); end-to-end mapping-formalism inversion at s=2 against a brute-force reference built from the ground-truth machinery; guard tests; full suite.Key Files
autoarray/inversion/mappers/abstract.py—mapping_matrix(sub_fraction fold) at lines 255–275autoarray/inversion/inversion/imaging/abstract.py— PSF application + linear-func preloadsautoarray/inversion/inversion/imaging/sparse.py— guard targetPyAutoMind/feature/autoarray/oversampling_design.md§4 — the approved design (do not re-design)Acceptance
Original Prompt
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See
PyAutoMind/issued/oversampling_phase_2b_inversion_wiring.md(phase 2b split ofoversampling_phase_2_core_api.md; design approved in #353; predecessor #354 / PR #355).