Optimize UCIE colormap performance with half-space penalty#42
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Replace slow Delaunay/cdist-based optimization with fast ConvexHull half-space inequalities. This achieves ~5-20x speedup on large embeddings. Key changes: - Replace Delaunay.find_simplex with ConvexHull half-space test - Replace cdist distance matrix with facet violation penalty - Add support point subsampling for optimization - Cache LAB/RGB gamut hulls for reuse - Add verbose parameter to control logging - Remove per-iteration print statements Performance on 100k points: 3D LAB ~6s, 2D ~0.1s Also integrates optimize_embedding into core.py with --optimize flag for both 3D (LAB/RGB) and 2D colormaps. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add --optimize/--no-optimize flags to CLI options table - Update 3D Embeddings section to explain default optimization - Add performance benchmarks for rotation optimization Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Exclude slow benchmark tests from CI run - Replace deprecated UCIE colormap with LAB (optimization enabled by default) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Code reviewNo issues found. Checked for bugs and CLAUDE.md compliance. |
Code reviewNo issues found. Checked for bugs and CLAUDE.md compliance. |
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Replace slow Delaunay/cdist-based optimization with fast ConvexHull half-space inequalities. This achieves ~5-20x speedup on large embeddings.
Key changes:
Performance on 100k points: 3D LAB ~6s, 2D ~0.1s
Also integrates optimize_embedding into core.py with --optimize flag for both 3D (LAB/RGB) and 2D colormaps.