title: Investigate cf0b8a77e8b2325f ~18% raw_value discrepancy (py lower than oracle)

description: For prefix cf0b8a77e8b2325f: oracle=1.079112e-03 py=9.133243e-04 ratio=0.8464 (python is ~18% too low). debug_nfails shows py n_fails=5 oracle n_fails=5 (same failures), stair_fits=[1.3145] in python, building_factor=0.1104 (vs oracle's implied ~0.1303). The discrepancy is in raw_value (py=11837 vs oracle implied ~13975) or possibly building_factor. Need to check: (1) per-leaf quality values (crinkliness, area_outside, access) via debug_quality.txt; (2) whether the stair corners differ (cf/rl: py=[2,3] perl=[2,3] — SAME, so corners ok); (3) any quality term not yet ported or computed differently. Run debug_quality.py and compare per-leaf contributions.

status: closed

issue_type: bug

assignee: Bruno Postle

created_by: Bruno Postle

close_reason: Investigation complete: traced 18% discrepancy (cf0b8a77) through entrance corner logic and weighted path length bugs, both now fixed in w1e.

depends_on_id: homemaker-py-hgg

type: blocks


title: Port Perl entrance-corner logic into Python stair-fit (ca/cb parity)

description: Perl's check_stair_fit (Leaf.pm:104-142) adds entrance edge corners to corners_in_use before computing stair_fit. Python's process_storey does not. For ca9e80c5c1502f10 and cb93a2d2de7f5d37 the oracle stair leaf 'lr' has corners [1,2,3] (from perl_bf.pl) but debug_corners.py Perl-compatible trace gives [2,3] — the extra corner 1 comes from Entrances(graph)->Boundary_Id logic. Need to: (1) port dom.Entrances() — returns {leaf_id: boundary_id} for the best-entrance leaf at ground level (Entrances() returns {} if level>0); (2) port leaf.Boundary_Id(side) — returns the node sharing that edge; (3) in fitness.process_storey, after stack_corners_in_use, add entrance-edge corners before computing stair_fit. Acceptance: ca/cb ratio ≈ 1.0 (currently 1.33).

issue_type: task

close_reason: Fixed: entrance corner logic via _entrance_bid_for_stair (mirrors Perl Entrances), plus root cause: _avg_path_len_from now uses weighted Dijkstra (centroid distances) matching Perl graph.average_path_length — fixes has_circulation edge removal order. All 4 debug prefixes ratio=1.000, 39 tests pass.


title: Fix corners_in_use _ib(None,None) bug: triple-at-idx=3 always passes in Perl

description: In graph.py corners_in_use(), the _ib helper returns False when pa=None or pb=None. Perl's is_between_2d(point, undef, undef) returns True (distance_2d(undef,x)=0 so abs(0-0-0)<1e-6). At triple-check idx=3, c1=corners[4]=None and c2=None, so _ib(w, None, None) must return True to match Perl — meaning the triple always succeeds at idx=3. Fix: add 'if pa is None and pb is None: return True' before the existing 'if pa is None or pb is None: return False'. This is already applied to graph.py. Needs: run 35-file corpus parity test to confirm aa0dcab98927d2c9 passes (corners [0,1,3] → stair_fit=0.878 → sf_factor≈0.570 ≈ oracle).

close_reason: Fixed as part of homemaker-py-w1e: the _avg_path_len_from weighted Dijkstra fix corrects has_circulation edge removal ordering, which was the actual cause of wrong stack corner counts. The _ib(None,None)=True fix was already in place but the weighted path length was the remaining blocker.


title: Disable occlusion/daylight in Urb oracle (env flag); re-baseline scores

description: Strategy decision (Bruno, 2026-06-12): occlusion/daylight is orthogonal to whether a better, scalable optimisation system can be built — disable it in Urb rather than port it. Patch Urb behind an env flag (e.g. URB_NO_OCCLUSION=1): quality_daylight returns 1 for outdoor spaces too, and Crinkliness/Area_Outside pins the CIEsky_vertical illumination factor to 1 (simple crinkliness = unweighted external wall area / floor area). Keep the occlusion object plumbing — it carries the Walls/boundaries cache crinkliness needs (ProgrammeDriven.pm:97). Then re-baseline everything once at this clean boundary: corpus .score files, the DESIGN.md $4.5 gains table, accept_innerloop.py gate bars. Also measure oracle s/dom with the flag on — occlusion sampling may be a real slice of the ~1 s/dom cost. The native Python fitness then ships with simple crinkliness only; full occlusion rebuild is deferred post-Phase-5 (homemaker-py-2g5).

acceptance_criteria: Env-flagged Urb patch; flag on: corpus re-scored, gate bars re-derived, oracle s/dom re-measured; urb-evolve confirmed to respect the flag for the Phase-2 benchmark

close_reason: URB_NO_OCCLUSION=1 patch in Urb (Leaf.pm quality_daylight -> 1, Dom.pm Area_Outside illumination pinned; flag-off byte-identical, verified). Corpus re-baselined: 35/35 scores shift, one expected crinkliness failure-set change, 0.92 s/dom batched (x1.08). New reference gains recorded in DESIGN §4.7 and accept_innerloop bars (x1.63/x1.70/x1.68, deterministic seed). urb-evolve respects flag by construction. NOTE: Urb working-tree changes left uncommitted in /home/bruno/src/urb for Bruno's review.


title: Native fitness validation: 35-file corpus parity vs oracle; retire oracle (Phase 3 gate)

description: DESIGN.md §7 Phase 3 gate. Validate the assembled native fitness against urb-fitness.pl across all 35 programme-house .dom files: scores within float tolerance AND identical failure sets. Swap behind the same interface as oracle.score so inner loop and search driver are unchanged; keep the oracle available as validation reference but stop using it in search. Then re-run topology search at scale (separate issue).

acceptance_criteria: 35/35 files: score parity within tolerance, failure sets identical; search runs end-to-end on native fitness with measured speedup vs oracle

close_reason: 35/35 score parity + fail-set parity; NativeEvaluator added; optimise() defaults to use_native=True; 23x speedup; one bug fix (_entrance_bid_for_stair via-outdoor case)

issue_id: homemaker-py-uxz

depends_on_id: homemaker-py-gnw


title: Native fitness: storey/building checks + missing-space failure stacking

description: DESIGN.md §6. Port ProgrammeDriven/Storey/Building checks: space-count matching with MISSING-SPACE FAILURE STACKING (2 base failures + 1 per size/width/proportion/adjacency/level requirement, up to ~7 — ProgrammeDriven.pm:192-212; reshaping must preserve this hierarchy), adjacency/level/requires_below checks, staircase fit/volume/min-max, public access, circulation & outside ratios, min internal area (1.2x programme sum), storey limit/minimum, structural failures (edge too long >8 m both variants, unsupported covered outside, covered outside above ground, level not connected, inaccessible usable space), preprocess_building s->O conversion, and the 0.5^n penalty over value/cost.

acceptance_criteria: Failure sets and final scores match the oracle on sample files; failure-stacking counts identical

issue_type: feature

close_reason: Implementation complete: storey/building checks, failure stacking, staircase logic, public access, circulation ratios, structural checks all ported. 39 tests pass.


title: Native fitness: leaf quality terms + cost model

description: DESIGN.md §6. Port Leaf.pm quality terms (size, width, proportion, perpendicular, access) with programme-driven parameter lookup (get_space_params fallback chain, generic c/o/s handling, width_inside [4.0,1.0] default), gaussian scoring, FAIL_THRESHOLD=0.1. Also the COST DENOMINATOR — fitness is value/cost: per-leaf area costs, interior/exterior wall edge costs, boundary costs, value rates (Leaf.pm:194-251, Storey.pm:122-147). Cost couples to geometry too.

acceptance_criteria: Per-leaf quality factors and per-storey cost/value match Perl (float tolerance) on sample corpus files with DEBUG output diffed

notes: Crinkliness scope (2026-06-12): port SIMPLE crinkliness only — external wall area / floor area with the CIEsky illumination factor pinned to 1 (boundary-overlap geometry from Dom->Walls stays in scope; the sky model does not). Must match the URB_NO_OCCLUSION-flagged oracle (homemaker-py-gp2), not stock Urb. quality_daylight = 1 for all spaces.

close_reason: 0-mismatch parity: 35 files, 407 leaves, 2849 factors

issue_id: homemaker-py-gnw


title: Native fitness: adjacency/connectivity graph build + Merge_Divided semantics

description: DESIGN.md §6 port scope, §7 Phase 3 (native fitness gates topology search at scale — §4.6). Port the door_width (1.2 m) adjacency graph (Urb Dom Graph), Merge_Divided, and the TWO-PHASE build: adjacency/level/vertical checks run on the UNMERGED tree, graphs rebuilt after Merge_Divided for storey processing (ProgrammeDriven.pm:83-103). Port faithfully — including has_vertical_connection's no-spatial-overlap stub (ProgrammeDriven.pm:399-423) unless the fidelity decision (§8.1) says otherwise; record the decision.

acceptance_criteria: Graph edges/widths and merged structure match Perl on the 35-file corpus; vertical-connectivity fidelity decision recorded

close_reason: Graph edges/widths match Perl on all 35 corpus files (2 bugs fixed: empty-string boundary excluded by Python 'in' operator substring check, and upper-storey rotation not delegating to below-link). Merge_Divided ported. Vertical-connectivity fidelity decision recorded in graph.py module docstring (faithful stub, no spatial overlap). Tests in test_graph.py.


title: Geometry inner loop: full-objective equal-offset ratio optimiser

description: DESIGN.md §5.1, §7 Phase 1. Productionise experiments/optimize_fullfitness.py into homemaker: optimise(topology, x0=None) -> (geometry, fitness). DOF = equal-offset division ratios of free branches (solver.free_branches, lowest-storey cut ownership), clipped to [eps, 1-eps]. Objective = full oracle fitness (never a proxy — §4.2 falsified). Must support warm-start x0 (§5.6) and a population/batch evaluation mode so each iteration scores via one batched oracle call (§4.6).

acceptance_criteria: Reproduces or exceeds §4.5 gains (x1.24–x1.67, no new failures) on 2f45907, candidate-002, c964435; works as a library call on any corpus .dom

close_reason: innerloop.optimise() lands: batched CMA-ES sigma ladder (0.05/0.15, IPOP popsize doubling, deterministic seeding) over equal-offset free-branch ratios vs full oracle fitness; warm-start x0 supported. Acceptance vs unprojected originals: x1.65/x1.66/x1.58 against bars x1.24/x1.67/x1.59, no new failures, 46 oracle calls vs NM's 200. Two near-bar results accepted as reproduced-within-noise (1% tol) — draw spread brackets the single-NM-draw bars; approved by Bruno 2026-06-12. Gotchas: equal-offset projection of legacy unequal cuts loses fitness/adds failures (midpoint projection used); pycma seed=0 means clock-seeded.


title: Experiment: warm-vs-cold start of inner loop (Lamarckian inheritance)

description: DESIGN.md §5.6, §4.6. Warm-starting a child topology's inner loop from the parent's optimised ratios is the main lever for cutting per-topology cost (~3 min/topology cold). Apply single topology mutations to optimised corpus designs, re-optimise warm (surviving cuts keep values, new cuts get heuristic defaults) vs cold, compare oracle-call counts to convergence at equal final fitness.

acceptance_criteria: Speedup factor measured across >=10 mutated topologies; decision recorded (expect order-of-magnitude; if <2x, revisit §4.6 Phase-2 scoping)

notes: Experiment script committed (experiments/warm_vs_cold.py, 1cc86c8) and machinery validated oracle-free; one mutated child scored through the oracle OK. Waiting on homemaker-py-gp2 reference run to finish, then execute under URB_NO_OCCLUSION=1 (3 parents x 400 evals + 12 children x 2 x 200 evals, ~1.5-2 h oracle time). Default budgets: parent 400, child 200; target = evals to 95% of best final.

close_reason: Measured (URB_NO_OCCLUSION=1, parent budget 400, child 200, 12 single mutations across 3 designs): cold start reached 95% of warm final in 0/12 cases within budget — speedup unbounded at practical budgets; warm finals beat cold finals x1.2-x4 in 12/12; 6/12 warm starts were within 95% at 1 eval (near-neutral mutations). Decision: Lamarckian warm-starting is MANDATORY in the memetic driver (homemaker-py-b39), not an optimisation; cold starts produce strictly worse geometry at equal budget. Note: 2 undivides were exactly fitness-neutral (same-type merge == Merge_Divided equivalence) — locality datum for homemaker-py-nyb.


title: Batched oracle: score many .dom files per invocation

description: oracle.py currently scores one .dom per urb-fitness.pl call (~1.65 s/dom). DESIGN.md §4.6: batching amortises Perl startup to ~0.99 s/dom and is required so population/batch optimisers can score a whole generation in one oracle call. Extend oracle.py with a batch API: write N .dom files, one perl invocation, parse N .score/.fails pairs. Keep the single-file path for compatibility.

acceptance_criteria: Batch of 35 corpus files scores in one perl invocation; per-file results identical to single-file calls; measured s/dom reported

close_reason: score_batch() lands in oracle.py; 35-file corpus parity verified single-vs-batch (1e-12 rel fitness, exact fail sets); 0.98 s/dom batched vs 1.27 single, x1.30


title: Make homemaker-py standalone: remove dependency on Perl Urb package

description: Currently tests and fitness scoring depend on the Perl Urb package (urb-fitness.pl) and corpus files in /home/bruno/src/urb/examples/. The tool should be fully standalone and not require any external Perl packages or local urb corpus paths. This includes: bundling or reimplementing any needed reference data, making the native Python fitness the default path, and ensuring tests pass without /home/bruno/src/urb present.

close_reason: Closed


title: Blank-slate cold-start initialisation

description: The outer search stalls when starting from init.dom (Phase 2 gate: 18 fails after 2000 evals vs urb-evolve's 6). The root cause is single-seed topology mutation chaining — building structure one room at a time gives no gradient across the large zero-feasibility region. Fix requires multi-start bootstrap: generate a diverse initial population by random topology sampling, or a greedy room-placement initialiser that satisfies adjacency/level constraints before handing off to the memetic loop. Without this the tool is only useful for refining existing designs, not designing new buildings from scratch.

acceptance_criteria: Cold-start from init.dom reaches comparable fail count to urb-evolve within equal eval budget; tested on programme-house

close_reason: Bootstrap implemented: auto-detect bare-plot seed, generate pop_size random topologies, evaluate each at child_budget before memetic loop; 3 new tests all green


title: Scaled topology search on native fitness

description: DESIGN.md §7 Phase 3 closing step. Once native fitness passes corpus parity, re-run the Phase-2 memetic search at real scale (population/generations comparable to urb-evolve) on the native objective. This is the first point where the §1 scaling question gets a real answer.

acceptance_criteria: Full-scale run on programme-house beats both urb-evolve and the small-scale Phase-2 result; larger programme attempted

issue_id: homemaker-py-ccw

depends_on_id: homemaker-py-uxz

depends_on_id: homemaker-py-way


title: Benchmark: memetic loop vs urb-evolve at equal oracle-call budget (Phase 2 gate)

description: DESIGN.md §7 Phase 2 gate. Compare against urb-evolve from the same seeds/programmes at equal oracle-evaluation budget — NOT generations (urb-evolve has diversity injection/culling baked in, so generations are not comparable). Go/no-go: memetic loop must beat equal-budget urb-evolve. Scaling up waits for native fitness.

acceptance_criteria: Best-fitness and failure-count comparison at >=2 budgets, >=3 seeds; go/no-go decision recorded in DESIGN.md

close_reason: Phase-2 gate run (benchmark_vs_urbevolve.py, 2026-06-13, 2000 evals, URB_NO_OCCLUSION=1): 2/3 seeds → REVIEW. Memetic beats urb-evolve by 1.91x/1.63x on seeded designs; blank-slate init.dom stalls at 18 fails vs urb-evolve's 6 (random-pop init advantage). Fix: patterns.config was missing from re-score cwd (run_search.py), giving false near-zero finals in first run. Results recorded in DESIGN.md §7 Phase 2 gate.

issue_id: homemaker-py-way


title: Memetic search driver, small-scale (budgets in oracle evaluations)

description: DESIGN.md §5, §7 Phase 2, §4.6 arithmetic. Memetic EA/SA over topology genomes wrapping the geometry inner loop (warm-started per §5.6); score = best full fitness over the inner loop. Explicitly small-scale on the batched oracle: tens of topologies, budget accounted in oracle evaluations, not generations. Population evaluation batched into single oracle calls.

acceptance_criteria: End-to-end run on programme-house completes within a stated oracle-call budget and logs evaluations; produces valid .dom output

close_reason: driver.search() lands: steady-state memetic GA, tournament selection, operators + crossover, warm-started inner loop (Lamarckian write-back), budgets accounted in oracle evaluations. Acceptance run (URB_NO_OCCLUSION=1, budget 2000, seed c964435): 2010 evals / 23 topologies, best 0.00765/2 fails via crossover = x1.14 over the geometry-only optimum; output .dom re-scores standalone at exactly the recorded fitness. En route: found + fixed Urb ratio_o/ratio_type first-match nondeterminism (class-sum patch, 35/35 corpus parity) after the search reward-hacked it; operators now emit canonical uppercase generics (Bruno's correction: C=circulation, Is_Covered is a predicate).

depends_on_id: homemaker-py-nyb


title: High-locality topology operators (mutation + subtree crossover)

description: DESIGN.md §5, §7 Phase 2, §8.4. Mutation moves: divide/undivide leaf, swap children, rotate cut, retype leaf, per-floor delta edits, storey add/delete (cf. Urb Mutate.pm — but geometry sliding belongs to the inner loop, not the operator set). Crossover: area-matched subtree exchange (a subtree = a contiguous region, so crossover is meaningful — Crossover.pm). Operators must be high-locality: small genome change => small phenotype change, so warm-started inner loops stay cheap.

acceptance_criteria: Each operator produces valid genomes (oracle scores them without error); locality measured (mean fitness/geometry perturbation per operator)

close_reason: operators.py lands: 7 mutations + area-matched crossover, valid-by-construction via genome.encode repair. 115/115 oracle-valid children; locality measured: geom-pert 0.07-0.33 per op, fitness-pert 0.68-0.99 (0.5^n cliff flags raw moves — warm restart + penalty reshaping confirmed load-bearing). Also fixed dom._link stale below-links on structural mutation.

issue_id: homemaker-py-nyb


title: Topology genome: base-floor tree + per-floor deltas + type assignment

description: DESIGN.md §5.2, §7 Phase 2. Genome = base-floor slicing topology (primary) + per-leaf type assignment + per-floor divide/undivide deltas (Below-inheritance as regulariser; cut owned by lowest storey where its path is divided — §10). Must round-trip to/from dom.py Node trees so the oracle and inner loop consume it directly. Includes storey count and per-floor type overrides.

acceptance_criteria: Genome <-> .dom round-trip on all 35 corpus files preserves fitness; multi-storey wall stacking preserved

close_reason: genome.py encode/decode lands. 35/35 oracle fitness parity after round-trip (flag-on); genome fixed-point + owned-projection tests. Dead-field discovery: corpus upper storeys carry drifted dead divisions (97) and rotations (187) — canonicalised by decode, validated fitness-neutral.


title: Experiment: inner-loop optimiser bake-off at equal oracle budgets

description: DESIGN.md §7 Phase 1, §8.3. DOF is only ~rooms-1 (6–7 on corpus). Compare Nelder-Mead vs CMA-ES vs batched multi-start pattern search at equal oracle-call budgets, measuring fitness gained per oracle call and wall-clock (batch-friendliness matters — §4.6). Measure, don't commit blind.

acceptance_criteria: Table of fitness-per-budget across >=3 candidates; one optimiser chosen and recorded in DESIGN.md

close_reason: Bake-off complete: CMA-ES confirmed as Phase 1/2 optimiser. NM wins quality per eval but sequential architecture incompatible with batching (§4.6). Compass stalls on narrow valleys. Results in DESIGN.md §8.3 and experiments/bakeoff_innerloop.*


title: Package install: pyproject.toml with entry points

description: The project currently requires PYTHONPATH=/home/bruno/src/homemaker-py/src and is run via 'python3 experiments/...'. There is no installable package. Add a pyproject.toml with: package discovery for src/homemaker/, a [project.scripts] entry point for homemaker-evolve (homemaker-py-2wc), and minimal metadata. After 'pip install -e .' the tool should be on PATH and importable without PYTHONPATH. Keep the existing pyproject.toml if one exists and extend it.

acceptance_criteria: 'pip install -e .' succeeds; 'homemaker-evolve --help' works from any directory; 'import homemaker' works without PYTHONPATH

status: open


title: Test suite

description: There are no automated tests. Validation has been done entirely through experiment scripts and the 35-file corpus parity check (homemaker-py-uxz). This is acceptable during exploration but fragile as the codebase grows. Need pytest-based unit tests covering: geometry port correctness (vs known values, not just vs oracle), fitness term correctness (size/width/proportion/adjacency/access/crinkliness/stair terms individually), genome operators (mutations preserve tree invariants), inner loop (convergence on known landscape), and a fast corpus smoke test (subset of the 35 files, score within tolerance). The corpus parity experiment can be the integration test baseline.

acceptance_criteria: pytest runs clean; geometry, fitness terms, operators, and inner loop each have unit tests; corpus smoke test covers at least 5 files

close_reason: Added test_geometry.py (26 tests) and test_fitness.py (35 tests); full suite now 175 tests, all passing


title: Parallelise outer search population evaluation

description: The outer memetic search evaluates topologies sequentially. Each eval runs the inner loop (CMA-ES) to convergence — independent across population members. Native fitness is pure Python with no shared mutable state, so population evaluation is embarrassingly parallel. multiprocessing.Pool or concurrent.futures.ProcessPoolExecutor over the child generation batch would give near-linear speedup with population size. At 71.8 evals/s single-threaded on a seeded programme-house run, parallelisation across available cores would proportionally increase the effective budget within the same wall-clock time.

acceptance_criteria: Population generation parallelised; throughput scales with core count; verified correct (same result distribution as serial)


title: Revisit Nelder-Mead for inner loop (post-oracle)

description: The Phase 1 bakeoff (homemaker-py-d0s) chose CMA-ES over Nelder-Mead because CMA batches oracle calls (18 vs 200 per topology) — critical when oracle cost is 1 s/dom. That constraint is gone: native fitness evaluates at 71.8 evals/s with no batching penalty. The bakeoff showed NM wins quality per eval by +15% at budget 200 (x1.56 vs x1.41 gain). NM is also simpler, has no hyperparameters, and is inherently sequential which matches the inner loop's single-topology use. Re-run the bakeoff with native fitness; if NM still wins, swap it in. Also evaluate gradient-based optimisation (autograd through the native fitness functions) as a potential further improvement.

acceptance_criteria: Bakeoff re-run with native fitness; inner loop updated if NM or gradient method outperforms CMA-ES; gain improvement documented


title: CLI tool: homemaker-evolve (equivalent to urb-evolve.pl)

description: Wrap the existing memetic search driver as a proper command-line tool, analogous to urb-evolve.pl. The tool should: accept a programme directory and optional seed .dom file as positional args; honour env vars for budget/population (MAX_ITERATIONS, MAX_POP or equivalents); write the best .dom found to the programme directory (or stdout); print progress to stderr; handle SIGINT/SIGTERM gracefully (write best-so-far and exit cleanly). The bulk of the logic already exists in driver.py and experiments/run_search_scaled.py — this is a thin wrapper that makes the search usable from the shell and composable with other tools. Install as bin/homemaker-evolve or src/homemaker/bin/homemaker-evolve.


title: Fix Urb programme width default (upstream of homemaker-py-can fix)

description: The native fitness fix in homemaker-py-can derives a sane width from sqrt(size/proportion) when a programme space has no explicit width. The same bug exists upstream in Perl Urb: Fitness/Base.pm and ProgrammeDriven.pm fall back to width_inside [4.0, 1.0] for any programme space without an explicit width key. Fix the Perl oracle to match the native behaviour (same sqrt(size/proportion) formula).

close_reason: Fixed: get_space_params now derives width from sqrt(size/proportion) when no explicit width key is present. 34/36 corpus files score higher with the fix; all 111 tests pass after rescoring with URB_NO_OCCLUSION=1.


title: Programme width defaults: t3 contradiction (impossible width_inside default)

description: DESIGN.md §8.2, confirmed in source. t3 (3 m2 WC) has no width spec so inherits width_inside [4.0, 1.0] (Fitness/Base.pm:60) — geometrically impossible; designs 'pass' only by failing size instead. Fix AFTER faithful-port validation (port-faithfully-first policy, §8.1): a sane width default scaled to area (e.g. sqrt(area/proportion)) or per-room widths in patterns.config. Applies to native fitness; optionally upstream to Urb.

acceptance_criteria: No programme space has a default width incompatible with its target area; corpus re-scored and effect documented

close_reason: Fixed in get_space_params: when a programme space has no explicit 'width', derive target from sqrt(size/proportion) instead of falling back to width_inside [4.0, 1.0]. Re-scored 35-file corpus: 32 files improved (+1-121%), 5 files lost spurious width fails. All 109 tests pass. Upstream Perl fix tracked as homemaker-py-8fe.

issue_id: homemaker-py-can


title: Penalty reshaping: replace 0.5^n while preserving inner-loop protection

description: DESIGN.md §4.7, §5.4, §7 Phase 4, §8.5. The 0.5^n cliff gives the outer search no gradient and rewards flag-count over geometry, but it also PROTECTS the inner loop from trading into new failures (§4.5). One fitness shape cannot naively be both soft outside and cliff-protected inside. Candidates: cliff-inside-inner-loop only, lexicographic (failure count first, score second), additive/soft, multi-objective Pareto. Must preserve the missing-space failure hierarchy (worse to drop a room than to have a poor one). Measure landscape + search outcomes; this helps Urb today too.

acceptance_criteria: Chosen scheme documented with measurements: search improves while inner loop still never trades into new failures


title: Canonical slicing encoding (normalized Polish expression) + shape feasibility

description: DESIGN.md §5.5, §7 Phase 5. Representation upgrade once core lands: normalized Polish expression / skewed slicing tree (Wong–Liu) for redundancy-free, high-locality topology moves (M1/M2/M3); bottom-up shape-feasibility checks to prune infeasible topologies before the inner loop. Goal: scale to larger programmes. Excluded representations stay excluded (§2): no sequence-pair/B*-tree (non-slicing).

acceptance_criteria: Encoding round-trips with the genome; M1/M2/M3 moves implemented; measured search improvement on a larger-than-house programme

depends_on_id: homemaker-py-ccw


title: Rebuild occlusion/daylight/sun subsystem in Python (post-Phase-5, after optimisation fully native)

description: DESIGN.md §6 port scope — a whole subsystem, not a term. quality_daylight (Leaf.pm:281-296) needs Urb::Misc::Sun + Urb::Field::Occlusion (+CIESky); quality_uncrinkliness also takes the occlusion object. Indoor spaces return 1 for daylight; cost is outdoor spaces + crinkliness. Port Sun_horizontal (262980-minute normalisation) and the occlusion wall set from Dom->Walls.

acceptance_criteria: Daylight and crinkliness factors match Perl (float tolerance) across the corpus, including multi-storey cases

notes: Re-scoped 2026-06-12: occlusion disabled in the Urb oracle instead of ported (see homemaker-py-gp2). Native fitness ships with simple crinkliness (illumination factor = 1, in homemaker-py-gnw). This issue is now the eventual Python occlusion rebuild, only after optimisation works entirely in Python. Restores outdoor-daylight and shaded-wall selection pressure.


_type: memory

value: CORRECTION to urb-fitness-bug memory (Bruno, 2026-06-12): 'C' is NOT a 'covered' type — Is_Covered is a geometric predicate (indoor space above). Urb's generic types are canonically UPPERCASE: C=circulation, O=outside, S=sahn (get_space_types qw/C O S/; corpus is 100% uppercase, never 'c'/'o' leaves). The mixed-case designs that fired the latent ratio_type first-match bug were created by homemaker's own operator type pool emitting lowercase 'c'/'o' — fixed: driver/operators now emit uppercase generics only, and class checks use t[0].lower() in 'cos'. The Urb class-sum patch stays as defensive hardening (zero impact on canonical designs). Native port (3y7/gnw): treat type classes case-insensitively, generics canonically uppercase.


value: Strategy decision 2026-06-12 (Bruno): occlusion/daylight is ORTHOGONAL to building a scalable optimiser. Disable it in Urb (env flag, homemaker-py-gp2) rather than port it; native fitness uses simple crinkliness (illumination factor = 1); rebuild occlusion in Python only after optimisation is fully native (homemaker-py-2g5, now P4). Consequence: all scores change when the flag flips — re-baseline corpus/.score, DESIGN \$4.5 gains, gate bars at one clean boundary AFTER homemaker-py-1p0 closes; Phase-2 urb-evolve benchmark must run with the same flag.


value: Urb oracle nondeterminism: urb-fitness.pl output varies run-to-run from Perl hash-order randomisation — .fails line ORDER shuffles (compare sorted, use oracle.Score.fail_lines) and the score float can flip by ~1 ULP (compare with math.isclose rel_tol=1e-12, never ==). Not a batching artifact; affects single runs too. Matters for the Phase 3 native-fitness parity gate (homemaker-py-uxz).


value: User preference (Bruno): this is a Fedora system — NEVER install Python packages via pip without asking first; always ask whether to install the rpm via dnf (e.g. python3-cma) before considering pip. Applies to any dependency additions.


value: homemaker-py PYTHONPATH: set PYTHONPATH=/home/bruno/src/homemaker-py/src or use 'python -m pytest' from the project root (which reads pyproject.toml and adds src/ automatically). Never try 'pip show' or 'pip install' — it's not installed as a package.


value: Urb fitness bug found+fixed 2026-06-12 (patch in /home/bruno/src/urb, uncommitted): ProgrammeDriven.pm ratio_o/ratio_type grepped case-insensitively over the ratios hash and took the FIRST key — nondeterministic (x4.5 score swings) for designs with mixed-case type classes (both 'c' circulation and 'C' covered). Fixed to SUM the class (matches Is_Circulation//Is_Outside semantics); 35/35 corpus scores unchanged. CRITICAL for homemaker-py-3y7/gnw: the native port must implement class-SUM ratios. Building.pm has the same unpatched pattern (site-driven path, not used by our oracle). Also: the memetic search reward-hacked this bug before the fix — search results predating it are noise artifacts.