Python rewrite of the Urb/Homemaker stack
Find a file
Claude 84907694d0
Record what the crinkliness examination found: 39.13, 39.14, 39.15
39.13 -- the tail rescale, and its verdict. NULL, and not for want of power:
12 of 12 pairs byte-identical, both programmes, same trajectories. The failing
tail is 0.034% of corpus value, so making it orderable cannot move a search.
Kept (free, and k54 needs the region orderable) but recorded as correct and
inert, not as a fix. It also corrects gvb's premise: zero exposure is NOT
beyond the inner loop's reach -- perturbing division ratios alone moves the
zero-exposure set on 6-12 of 12 trials at +-25%, and in the direction wanted
(harbor s1 8 -> 6 buried leaves).

39.14 -- what the factor actually rewards. 1/crink is the room's depth from
its daylit wall in storey-heights, so the variable is sound and its fail
boundary (1.62h = 4.86 m) agrees with 38.3's independently-derived frontage
bound. The two-sided gaussian on it is not: the near side penalises surplus
daylight that edge_cost and outside_edge_cost already bill at 100 and 133.3
per m2, it has never once produced a fail (it needs crink > 21.5; corpus max
is 3.95), and its peak sits at a 2.5 m deep room -- an ordinary 4 m room
scores 0.395 and the corpus's realised median depth is 2.95 m. The search
built what it was paid for. A/B at pilot budget is underpowered rather than
null: the arms reach different layouts but the same fail counts.

39.15 -- the magic numbers. A sigma is not a preference, it is an acceptance
interval target +- 2.1460*sigma, so it decides failures. The blanket
hypothesis does not survive -- programme-house reaches 1 fail, structural on
two of three seeds. The specific one does, and it shows 39.1's CLEAN verdict
answered a weaker question: sweeping a spec's tolerance box asks whether SOME
shape is feasible, and all 67 pass, but at the DECLARED target area and aspect
harbor needs 7 corner rooms and maple 6, while health-centre and
programme-house need none. Within-programme, those codes fail 62% and 78% of
their instances against 26% and 31% for all others. Three declared quantities
are jointly contradictory and nothing said so; the resolution is an author
decision, not a retuned constant.

Also recorded: 82% of size fails are rooms larger than target, which is the
same shape of double-charge but explicitly NOT the same case -- size's upper
bound is the main brake on growth and must not be removed on the analogy.

405 passed, 72 skipped.

Closes homemaker-py-9gj, homemaker-py-u5q.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MJ84Feep79Hhm3E4zZJmnB
2026-09-05 15:11:11 +00:00
.beads bd: close homemaker-py-ut5 2026-09-04 17:17:03 +00:00
.claude Scaffold homemaker-py with validated geometry port 2026-06-10 20:50:20 +01:00
examples coldstart maple-court seed 2 @ 500000: 55 fails (11h/44s) 2026-09-03 10:06:06 +01:00
experiments Record what the crinkliness examination found: 39.13, 39.14, 39.15 2026-09-05 15:11:11 +00:00
src/homemaker_layout Make the crinkliness factor one-sided: stop billing the daylit wall twice 2026-09-05 07:27:02 +00:00
tests Make the crinkliness factor one-sided: stop billing the daylit wall twice 2026-09-05 07:27:02 +00:00
.gitignore Ignore the A/B harnesses' per-process shard files 2026-09-05 06:29:15 +00:00
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 Record what the crinkliness examination found: 39.13, 39.14, 39.15 2026-09-05 15:11:11 +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.