Python rewrite of the Urb/Homemaker stack
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Claude 148988df14
constructive_topology was ordered by memory address on the cpsat path
assign_solver="cpsat" gave a different leaf-type signature on every run
from an identical seed, in the same process. One line:

  assignable = scope if scope is not None else set(leaves)
  noncirc = [L for L in assignable if L not in circ]      # id() order

assignable is a set of dom.Node, and Node hashes by id() -- a memory
address -- so iterating it ordered noncirc, and hence room_slots, by where
the objects happened to land in memory. That shifts between calls within
one process as allocation patterns change, with no seed involved.

Only cpsat showed it. The greedy path re-sorts every slot list with -idx[L]
as a unique tiebreak and is immune to the incoming order; CP-SAT consumes
room_slots order as its model's variable order, and the labelling problem
has many equally-optimal solutions. Greedy was not more correct, it was
masking a defect that had been there all along.

Fix: iterate the tree-ordered list, use the set only for membership.

Verified on programme-house, harbor-house and maple-court: 1 distinct
signature over 5 runs on both solvers, and 1 across 4 processes started
with different PYTHONHASHSEED, so context_types' string sets are not a
second source. test_constructive_topology_is_bit_reproducible guards both.

Method: rather than guess which set was at fault, instrument
solve_room_labels with an id-free fingerprint of inputs and outputs and
isolate the FIRST call, since later calls legitimately depend on earlier
ones through leaf types. Five runs gave five distinct first-call inputs,
placing the fault upstream of the solver in one step.

Every A/B on the cpsat path was comparing arms that differed partly by
memory layout -- 39.5's cpsat-vs-greedy verdict included, already down for
re-measurement under homemaker-py-vjd. Same id()-keying hazard as the
documented geometry._cache issue and a plausible contributor to
homemaker-py-b8g, which stays open: n_workers>1 has its own BLAS mechanism
and is not addressed here.

Closes homemaker-py-fdp.

Lint at parity (46); tests 381 passed (2 new), 0 failed.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MJ84Feep79Hhm3E4zZJmnB
2026-08-29 11:45:19 +00:00
.beads constructive_topology was ordered by memory address on the cpsat path 2026-08-29 11:45:19 +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 Checkpoint long searches; the cold-start runs were lost to a reclaimed box 2026-08-29 05:43:58 +00:00
src/homemaker_layout constructive_topology was ordered by memory address on the cpsat path 2026-08-29 11:45:19 +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 constructive_topology was ordered by memory address on the cpsat path 2026-08-29 11:45:19 +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.