fix: mixed-dataset factor graphs crash combined visualization#587
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A mixed-dataset FactorGraphModel (e.g. AnalysisImaging + AnalysisWeak, the weak series' combined strong+weak example) routes every factor's analysis into the lead factor's Visualizer.visualize_combined, which previously treated all of them as its own type (AttributeError: 'FitWeak' object has no attribute 'data'). VisualizerImaging / VisualizerInterferometer now filter to their own Analysis type before building fits, returning early (before plotter construction) when none remain; every factor still visualizes its own fit individually. First mixed-type graph exercised this path. Surfaced by the combined strong+weak example (autolens_workspace#247). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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Summary
The first mixed-dataset
FactorGraphModel(AnalysisImaging + AnalysisWeak, built by the weak series' combined strong+weak example) crashed during on-the-fly visualization: PyAutoFit routes every factor's analysis into the lead factor'sVisualizer.visualize_combined, and the imaging/interferometer implementations assumed all analyses were their own type (AttributeError: 'FitWeak' object has no attribute 'data'). Both now filter to their ownAnalysistype before building fits and return early (before plotter construction) when none remain; every factor still visualizes its own fit individually. Surfaced by autolens_workspace#247.API Changes
None — internal fix to visualization behaviour under mixed factor graphs.
Test Plan
VisualizerImaging.visualize_combinedwith only non-imaging analyses returns without touching paths.test_autolens/suite: 357 passed.modeling.pyjoint Nautilus fit runs to completion (previously crashed at the first combined-visualization call).Validation checklist (--auto run)
🤖 Generated with Claude Code