Python rewrite of the Urb/Homemaker stack
Bruno Postle
e95a3477a8
The constructive seeder was never nondeterministic: _assign_adjacency_aware ends every max/min with a unique leaf-idx tiebreak and uses set unions only for membership, so iteration order never leaks. constructive_topology(seed=0) is byte-identical across processes for every example programme. The cited "sig 4480 vs 16064" was a measurement artifact — Python's builtin hash() of a str is salted per process (PYTHONHASHSEED), so an identical signature hashes to different ints run-to-run. The real run-to-run noise was parallel-only: driver._run_batch admitted futures via as_completed (completion order), and admit() is order-sensitive (accrues n_evals per result; keeps the first individual of an equal-key tie as best). A long parallel run diverged 167 vs 161 fails (maple seed 0). Fix: admit futures in submission order (block on each result in turn; all still run concurrently), reproducing the serial admission sequence. Two workers=4 runs are now byte-identical. Serial (workers=1) was already byte-for-byte reproducible. Per-seed numbers are reproducible only at a fixed worker count; serial != parallel is expected (children/iteration 1 vs n_workers changes batch granularity). - driver: iterate futs in submission order, not as_completed - test: test_search_parallel_is_reproducible (fails on pre-fix, passes on fix) - DESIGN.md §12.4: corrected the reproducibility note Closes homemaker-py-xcy Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> |
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|---|---|---|
| .beads | ||
| .claude | ||
| examples | ||
| experiments | ||
| src/homemaker_layout | ||
| tests | ||
| .gitignore | ||
| AGENTS.md | ||
| CLAUDE.md | ||
| DESIGN.md | ||
| pyproject.toml | ||
| README.md | ||
homemaker-layout
Programme-driven building-layout search over slicing trees. A clean-room Python successor to the Perl Urb project, intended to eventually be 100% Python.
Why a rewrite
Urb represents a building as a binary slicing tree where room sizes are derived top-down from division ratios. That makes room area an emergent property of every cut above it, which:
- gives the genome low locality (a cut near the root rescales every descendant),
- makes target room sizes nearly impossible to hit, so the gaussian size penalty dominates fitness, and
- defeats crossover (transplanted subtrees lose their proportions).
homemaker inverts this: leaves carry target dimensions from the programme and division ratios are solved bottom-up for a fixed topology. The evolutionary search then only explores topology + types + adjacency.
Phase plan
Solver experiment: port Urb's geometry, re-solve ratios from programme targets, score the result against the original via the Perl oracle.✓Native Python fitness (retire the Perl oracle).✓- Memetic search (current): canonical slicing genome + high-locality operators + Nelder-Mead inner loop.
Layout
src/homemaker_layout/dom.py— read/write Urb.domYAML into aNodetree.src/homemaker_layout/geometry.py— faithful port of Urb's top-down geometry.src/homemaker_layout/programme.py— parsepatterns.configspace requirements.src/homemaker_layout/solver.py— bottom-up ratio solve (scipy).src/homemaker_layout/fitness.py— native Python fitness evaluator.src/homemaker_layout/fitness_cmd.py—homemaker-fitnessCLI (drop-in forurb-fitness.pl).src/homemaker_layout/graph.py— leaf-adjacency graph for programme-driven checks.src/homemaker_layout/genome.py— topology genome: base-floor tree + per-storey deltas.src/homemaker_layout/operators.py— high-locality mutation and subtree crossover.src/homemaker_layout/innerloop.py— ratio optimisation inner loop (Nelder-Mead / CMA-ES).src/homemaker_layout/driver.py— memetic search outer loop.src/homemaker_layout/evolve.py—homemaker-evolveCLI entry point.src/homemaker_layout/oracle.py— legacy Perl shim, kept for cross-validation only.