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Python rewrite of the Urb/Homemaker stack
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Bruno Postle e2b3e20070 Phase-2 gate benchmark: memetic loop vs urb-evolve at equal eval budgets 
experiments/benchmark_vs_urbevolve.py (homemaker-py-way): 3 seed designs
(init from scratch, c964435 weak, 2f45907 strong) x 2000-eval runs, the
1000-eval tier read from each run's best-so-far log; urb-evolve gets two
population sizes (default 128 = ~16 generations at this budget, and 16 =
~130) and credit for its better one. Counts via the MAX_EVALS counter
patch in urb-evolve.pl (committed in the urb repo); both systems under
URB_NO_OCCLUSION=1; all finals re-scored through urb-fitness.pl as the
common deterministic yardstick.

run_search.py generalised to (budget, rng-seed, seed.dom, out.dom);
innerloop.optimise now handles 0-DOF topologies (an undivided plot like
init.dom scores once instead of crashing CMA).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-06-12 22:22:16 +01:00
.beads Phase-2 gate benchmark: memetic loop vs urb-evolve at equal eval budgets 2026-06-12 22:22:16 +01:00
.claude Scaffold homemaker-py with validated geometry port 2026-06-10 20:50:20 +01:00
experiments Phase-2 gate benchmark: memetic loop vs urb-evolve at equal eval budgets 2026-06-12 22:22:16 +01:00
src/homemaker Phase-2 gate benchmark: memetic loop vs urb-evolve at equal eval budgets 2026-06-12 22:22:16 +01:00
tests Native fitness: adjacency graph + merge_divided (homemaker-py-3y7) 2026-06-12 21:57:45 +01:00
.gitignore bd init: initialize beads issue tracking 2026-06-11 23:27:11 +01:00
AGENTS.md bd init: initialize beads issue tracking 2026-06-11 23:27:11 +01:00
CLAUDE.md Scaffold homemaker-py with validated geometry port 2026-06-10 20:50:20 +01:00
DESIGN.md Re-baseline under URB_NO_OCCLUSION: new reference gains, DESIGN §4.7 2026-06-12 10:31:38 +01:00
pyproject.toml Geometry inner loop: batched full-objective ratio optimiser (CMA-ES) 2026-06-12 09:42:24 +01:00
README.md Scaffold homemaker-py with validated geometry port 2026-06-10 20:50:20 +01:00

README.md

homemaker-py

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

  1. Solver experiment (current): port Urb's geometry, re-solve ratios from programme targets, score the result against the original via the Perl oracle.
  2. Native Python fitness (retire the Perl oracle).
  3. Canonical slicing encoding (normalized Polish expression) + memetic search.

Layout

  • src/homemaker/dom.py — read/write Urb .dom YAML into a Node tree.
  • src/homemaker/geometry.py — faithful port of Urb's top-down geometry.
  • src/homemaker/programme.py — parse patterns.config space requirements.
  • src/homemaker/solver.py — bottom-up ratio solve (scipy).
  • src/homemaker/oracle.py — Phase-1 scaffold: score a .dom via Urb's urb-fitness.pl.

The Perl oracle is the only throwaway component; everything else is permanent.