Python rewrite of the Urb/Homemaker stack
Find a file
Bruno Postle 304d514573 Add unit tests for geometry and fitness modules
26 tests for geometry (area, angles, aspect, boundary ids, centroid,
offset, etc.) and 35 tests for fitness (gaussian, config lookup,
quality terms, value rates, costs, stair helpers). Suite: 175 passed.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-14 00:06:02 +01:00
.beads Add unit tests for geometry and fitness modules 2026-06-14 00:06:02 +01:00
.claude Scaffold homemaker-py with validated geometry port 2026-06-10 20:50:20 +01:00
examples/programme-house Close homemaker-py-hqw: make project standalone (no Perl/Urb dependency) 2026-06-13 23:39:20 +01:00
experiments Phase 3 gate (homemaker-py-ccw): scaled search on native fitness 2026-06-13 22:10:38 +01:00
src/homemaker Cold-start bootstrap: diverse initial population for blank-slate search 2026-06-13 23:29:12 +01:00
tests Add unit tests for geometry and fitness modules 2026-06-14 00:06:02 +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 Fix stair-fit parity: entrance corners + weighted has_circulation (homemaker-py-w1e/q70) 2026-06-13 20:55:25 +01:00
DESIGN.md Phase 3 gate (homemaker-py-ccw): scaled search on native fitness 2026-06-13 22:10:38 +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

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.