docs: refresh README benchmarks and document the robustness contract#9
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…work All numbers re-measured on one machine with the scripts in examples/ against the current main (post data-structure rework, cavity repair, and PyO3 fast paths): - standalone incremental insertion: 40-291x vs the Python reference (was 17-42x before the rework; the Rust side got 2-8x faster) - LearnerND end-to-end: 3.7x vs Python LearnerND and 7x vs Learner2D at 5K points, with a note explaining why the end-to-end ratio is smaller (adaptive's own Python loss machinery dominates once the triangulation is fast) - note that numbers are machine-dependent and how they were produced Also: mention the now-supported neighbor-aware losses and the two neighbor-query methods in the API list, and add a short Robustness section describing the validate/repair/reject contract on degenerate input, pointing at src/tolerances.rs.
Semantic line breaks instead of hard-wrapped paragraphs, so future diffs touch exactly the sentences that changed.
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Summary
The README's performance tables predated PRs #5-#8, and were measured on a different machine than anything quoted since. All numbers are now re-measured in one sitting on one machine with the repo's own scripts:
examples/benchmark_vs_python.py, best of 3): 40× (2D/1K) up to 291× (3D/2K) vs the Python reference — the old table said 17-42×; the core got 2-8× faster in Core data-structure overhaul: interned simplices, facet adjacency, incremental hull #5 while the reference got slower at scale (its O(n²) hull handling).Also:
curvature_loss_function()) now work.src/tolerances.rs.examples/adaptive_learnernd.pydocstring numbers updated to match.pre-commit clean; docs-only change.