Python rewrite of the Urb/Homemaker stack
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Claude 225e673ae3
Staged harness re-scored under a different objective than it searched
run_staged_search.py reported MISMATCH on its BASELINE arm -- the
LEAFSHARE=0/MULTIUSE=0 control every A/B compares against. Two facts
combined: driver.search_staged had no collapse_insearch parameter at all,
so every inner search() call inherited search()'s True default
unconditionally; and no example patterns.config sets the key, so the final
_native_score rescore got False from a bare load_config. Search optimised
one objective, the rescore graded another.

The 7ua fix pinned the key inside a fitness.load_config monkeypatch, but
that patch was installed only `if leaf_share or multi_use` -- so it fixed
every arm except the control.

Fixed in the right place: search_staged now HAS the parameter (default
True, byte-identical to the inherited default), threaded into all three
internal search() calls. The harness chooses the arm explicitly (COLLAPSE,
default 1), passes it to the search, and passes the SAME value to
_native_score, which overrides the key rather than hoping the config
carries it. The rescore mirrors the search by construction.

Verified on programme-house, budget 150:
  baseline    MISMATCH 1.56663e-08 vs 1.51708e-08  ->  OK
  COLLAPSE=0  (knob did not exist)                 ->  OK 1.66216e-08
  LEAFSHARE=1 / MULTIUSE=1                         ->  OK

COLLAPSE=0 scoring differently confirms the knob is not a no-op, and the
default arm's search result is unchanged, so no prior staged number moves.

Audited the other three search_staged callers: run_and_capture_91f.py
already pins collapse_insearch: True; run_island_ab.py never re-scores;
probe_harbor_floor.py did NOT pin it and had the same bug -- now fixed, and
that is the harness which produced every 13.x floor number.

The recorded mitigating factor -- only the continuous score moved, the fail
count matched, and the run_*_ab.sh greps read only the count -- is true and
is exactly what made it dangerous: a harness that reports MISMATCH on its
own control, invisibly to the metric of record, trains everyone to ignore
the warning.

Closes homemaker-py-4ok.

Lint at parity (46); tests 381 passed, 0 failed.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MJ84Feep79Hhm3E4zZJmnB
2026-08-29 12:11:38 +00:00
.beads Staged harness re-scored under a different objective than it searched 2026-08-29 12:11:38 +00:00
.claude Scaffold homemaker-py with validated geometry port 2026-06-10 20:50:20 +01:00
examples Declare toilet-to-sleeping adjacency where the brief supports it 2026-08-29 10:57:44 +00:00
experiments Staged harness re-scored under a different objective than it searched 2026-08-29 12:11:38 +00:00
src/homemaker_layout Staged harness re-scored under a different objective than it searched 2026-08-29 12:11:38 +00:00
tests constructive_topology was ordered by memory address on the cpsat path 2026-08-29 11:45:19 +00:00
.gitignore bd init: initialize beads issue tracking 2026-06-11 23:27:11 +01:00
AGENTS.md §39.7: access requirements become a declared usage: attribute (homemaker-py-sel) 2026-08-26 13:39:41 +00:00
CLAUDE.md §39.7: access requirements become a declared usage: attribute (homemaker-py-sel) 2026-08-26 13:39:41 +00:00
DESIGN.md Staged harness re-scored under a different objective than it searched 2026-08-29 12:11:38 +00:00
pyproject.toml homemaker-py-2g7.5: CP-SAT exact room-code assignment (seeder + reassign op) 2026-08-04 09:19:36 +01:00
README.md §39.7: access requirements become a declared usage: attribute (homemaker-py-sel) 2026-08-26 13:39:41 +00:00

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

  1. Solver experiment: 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. Memetic search: canonical slicing genome + high-locality operators + Nelder-Mead inner loop.
  4. Penalty reshaping: lexicographic (-n_fails, fitness) outer-search comparison.
  5. Representation upgrade: canonical slicing encoding + bottom-up shape feasibility, scaled to larger programmes.
  6. Search-quality experiments (current): a long running series of opt-in levers tried against the harbor-house, health-centre, and programme-house example corpora — leaf-sharing, finish-time cell→room collapse, ruin-and-recreate LNS, 2-opt polish, multi-use/co-located leaves, adjacency-graph and bubble-diagram fitness signals, and more. Most of these are negative/null results kept as opt-in flags or reference code rather than defaults. See DESIGN.md §11 onward for the full, numbered experiment log with methodology and results for each.

Layout

  • src/homemaker_layout/dom.py — read/write Urb .dom YAML into a Node tree.
  • src/homemaker_layout/geometry.py — faithful port of Urb's top-down geometry.
  • src/homemaker_layout/programme.py — parse patterns.config space 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.pyhomemaker-fitness CLI (drop-in for urb-fitness.pl).
  • src/homemaker_layout/collapse_cmd.pyhomemaker-collapse CLI: finish-time global cell→room relabel of a .dom.
  • 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.pyhomemaker-evolve CLI entry point.
  • src/homemaker_layout/oracle.py — legacy Perl shim, kept for cross-validation only.
  • src/homemaker_layout/bubble.py — 3D bubble-diagram adjacency fitness-signal prototype (DESIGN.md §27); validated null, not wired into fitness.py — reference only.

Room codes and reserved names

Leaf types live in three namespaces that share a first character. Only the first is enforced; the other two are conventions the fitness function reads, so a room's spelling can change how it is scored.

1. Generic structural types — C, O, S (reserved). The leaves the search itself creates: C circulation, O outside, S sahn (an outside court that also serves as circulation). Always uppercase. A programme code spelled exactly C, O or S is rejected at load.

2. Programme room codes — anything else, lowercase. k1, b1, cr1, of, and single-character codes like r or t. These may start with any letter: since DESIGN.md §39.4 the generic tests match C/O/S exactly, so naming a room cr1 no longer makes it circulation. (Before that fix it did — and silently dropped it from the required-space check entirely.)

3. Access requirements — the usage: attribute. Every space declares one of living, kitchen, bedroom, toilet, utility, none. Mandatory, no fallback, and a missing or unknown value is a load error. It replaced a first-character convention (b/t/l/k) under which a room silently inherited another room's connectivity rules from its spelling — la1 "Laundry Room" was trimmed as a living room (DESIGN.md §39.7).

spaces:
  la1:
    usage: utility          # controlled, drives engine behaviour
    name: Laundry Room      # free text, building-specific

A usage value exists only where the engine treats it differently, so the vocabulary is closed: a new access class means new code, not new config. Check a programme with:

python experiments/audit_programme_config.py

which reports reserved-name collisions, the usage class each code picks up, and whether each room's size/width/proportion/crinkliness targets are mutually satisfiable at all.