Python rewrite of the Urb/Homemaker stack
Bruno Postle
2491a9be12
Seed O as interior light wells (most-landlocked leaves first, count scaled by room count via outside_divisor) instead of one peripheral O, attacking the erc crinkliness residual: seed diagnostic confirms every crinkliness fail is under-exposed (landlocked), none over-exposed. A/B (20k evals, seeds 0/1/2, bal+share stack, §13.6): control reproduces §13.5; interior odiv=3 gives harbor -16.4% (all seeds improve) and maple -2.8% (net-neutral). Default-optimal divisor 3 found by seed sweep (6 was null). Lever default OFF; default-ON flip tracked as erc.8. - operators: interior_outside + outside_divisor through constructive_topology, lift_base_to_storeys, _assign_adjacency_aware (fix n_circ budget for >1 O) - driver.search/search_staged threading; run_staged_search.py INTERIORO/ODIV env - test_interior_outside_seeds_landlocked_wells_and_scales_count - experiments/run_interioro_ab.sh; DESIGN.md §13.6 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.