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Python rewrite of the Urb/Homemaker stack
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Bruno Postle c01a8a0887 Native fitness: leaf quality terms + cost model (homemaker-py-gnw) 
Port Urb's programme-driven fitness leaf quality factors (perpendicular,
proportion, size, width, crinkliness, daylight, access), value rates,
and cost model (per-leaf area costs, interior/exterior wall edge costs,
boundary costs) to Python.  Passes 0-mismatch parity against the Urb
oracle across all 35 corpus files (407 leaves, 2849 factors), using
URB_NO_OCCLUSION=1 simple crinkliness (illumination factor pinned to 1).

Key fixes: _dist must use math.sqrt not math.hypot (1-ULP difference
flips boundary overlap predicates); leaf-scope fail regex requires ^\d+/
prefix to exclude building-level failure messages.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-13 07:59:21 +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 Native fitness: leaf quality terms + cost model (homemaker-py-gnw) 2026-06-13 07:59:21 +01:00
src/homemaker Native fitness: leaf quality terms + cost model (homemaker-py-gnw) 2026-06-13 07:59:21 +01:00
tests Fix benchmark cell arg order and mutate_swap on undivided trees 2026-06-12 23:26:22 +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.