docs: document viewport culling investigation and findings#596
docs: document viewport culling investigation and findings#596softmarshmallow merged 2 commits intomainfrom
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Linear O(n) viewport culling was benchmarked against real-world SVG fixtures (up to 300K nodes). It regresses 8-13% on dense scenes where most nodes are visible. Updated optimization.md item 12 to note spatial index requirement. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Caution Review failedThe pull request is closed. ℹ️ Recent review info⚙️ Run configurationConfiguration used: Organization UI Review profile: CHILL Plan: Pro Run ID: 📒 Files selected for processing (2)
WalkthroughTwo documentation files are added/updated to report investigation results for viewport culling optimization. A new investigation document details findings from benchmarking camera value caching and linear viewport culling, concluding that linear culling without spatial indexing regresses performance. An existing optimization guide is updated with a warning emphasizing that spatial indexing (R-tree) is required for viewport culling. Changes
Estimated code review effort🎯 1 (Trivial) | ⏱️ ~3 minutes ✨ Finishing Touches🧪 Generate unit tests (beta)
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Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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| Per items 6, 12, and 36 in `optimization.md`: | ||
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| - **Spatial index** (R-tree/quadtree, item 36) would make culling O(log n) instead of O(n) |
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Correct the cross-references to optimization.md items
The recommendation block points readers to the wrong follow-up work: in optimization.md, item 12 is Tight Bounds for save_layer Operations and item 36 is Scene Planner & Scheduler, while the spatial-index entry is item 38. Because this section is explicitly telling implementers what to pursue next, these misnumbered references will send follow-up work to unrelated optimizations instead of the intended spatial-index and SkPicture-caching sections.
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Linear O(n) viewport culling was benchmarked against real-world SVG fixtures (up to 300K nodes). It regresses 8-13% on dense scenes where most nodes are visible. Updated optimization.md item 12 to note spatial index requirement.
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