feat(AnalysisImaging): plumb dataset_model into adapt_images_via_instance_from#512
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…ance_from Threads the per-iteration dataset_model and xp backend into adapt_images_via_instance_from so AdaptImages can rotate its cached image-plane mesh grid alongside the data grid for multi-band fits. Adds 3 chi^2=0 simulate-and-fit tests in test_simulate_and_fit_imaging.py exercising the full lensing chain (Tracer + DatasetModel rotation): offset-only, rotated mass, and combined offset+rotation. Refs PyAutoLens#511, PyAutoArray#312, PyAutoGalaxy#416. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Summary
AnalysisImaging.fit_fromnow passes the per-iterationdataset_modelandself._xpthroughadapt_images_via_instance_from, so adaptive pixelization mesh grids stay in the same rotated/shifted frame as the data grid in multi-band fits.This is the small but load-bearing PyAutoLens-side change to complete the multi-band grid-rotation feature. Adds 3
chi^2 = 0simulate-and-fit regression tests at the full lensing chain (Tracer + DatasetModel rotation).Depends on
PyAutoArray#312 and PyAutoGalaxy#416 (the latter is what defines the new
dataset_modelkwarg onAnalysisDataset.adapt_images_via_instance_from). CI will be red on this PR until both merge.Scripts Changed
None beyond the test file.
Test plan
python -m pytest test_autolens/— 277 tests pass on this branchtest_simulate_and_fit_imaging.pycovering the strong-lens use case (Hannah's actual JWST scenario):test__perfect_fit__sim_offset_lens_and_source__fit_with_dataset_model_grid_offset__chi_squared_zerotest__perfect_fit__sim_rotated_lens_mass__fit_with_dataset_model_grid_rotation__chi_squared_zerotest__perfect_fit__sim_offset_and_rotated_lens__fit_with_dataset_model_offset_and_rotation__chi_squared_zeroEach one simulates a strong-lens system with shifted/rotated mass and source profiles, fits with identity-frame profiles + matching
DatasetModelparameters, and assertschi_squared = pytest.approx(0.0, abs=1e-4).Refs PyAutoLens#511.