.beads/issues.jsonl

@@ -55,7 +55,7 @@
 {"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 =\u003e 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)","status":"closed","priority":2,"issue_type":"feature","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-11T23:37:27Z","created_by":"Bruno Postle","updated_at":"2026-06-12T13:07:37Z","started_at":"2026-06-12T12:54:23Z","closed_at":"2026-06-12T13:07:37Z","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.","dependencies":[{"issue_id":"homemaker-py-nyb","depends_on_id":"homemaker-py-k2g","type":"blocks","created_at":"2026-06-12T00:39:36Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":1,"dependent_count":1,"comment_count":0}
 {"id":"homemaker-py-k2g","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 \u003c-\u003e .dom round-trip on all 35 corpus files preserves fitness; multi-storey wall stacking preserved","status":"closed","priority":2,"issue_type":"feature","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-11T23:37:26Z","created_by":"Bruno Postle","updated_at":"2026-06-12T12:52:34Z","started_at":"2026-06-12T10:55:21Z","closed_at":"2026-06-12T12:52:34Z","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.","dependency_count":0,"dependent_count":1,"comment_count":0}
 {"id":"homemaker-py-d0s","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 \u003e=3 candidates; one optimiser chosen and recorded in DESIGN.md","status":"closed","priority":2,"issue_type":"task","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-11T23:36:59Z","created_by":"Bruno Postle","updated_at":"2026-06-13T08:48:13Z","started_at":"2026-06-12T21:22:15Z","closed_at":"2026-06-13T08:48:13Z","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.*","dependencies":[{"issue_id":"homemaker-py-d0s","depends_on_id":"homemaker-py-1p0","type":"blocks","created_at":"2026-06-12T00:39:35Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":1,"dependent_count":0,"comment_count":0}
-{"id":"homemaker-py-161","title":"In-search evaluation of shape_rotate/deslim GA operators (7fm follow-up)","description":"homemaker-py-7fm's finish-time hill-climb found zero improving moves for\nmutate_shape_rotate/mutate_deslim (operators.py) on the 6-layout harbor-house\nsweep — every candidate move traded a shape fail for a new adjacency/access\nfail on the already co-evolved layout. That's a different regime from\nin-search use: a full multi-generation GA run gives selection pressure and\npopulation diversity a chance to accept a locally-worse move that a later\nstep or recombination completes.\n\nTo test: thread `fit` through driver.search (currently only reqs is passed to\noperators.mutate; shape_rotate/deslim need `fit` and currently no-op inside\nthe GA). Gate with an enable_shape_repair-style flag, mirroring how\nenable_reassociate (§12.3) let 9gp.2 do a clean A/B. Run full-budget\nharbor-house search with/without across seeds, compare final fail counts.\n\nIf negative again, the geometry-intrinsic residual on harbor-house-scale\nprogrammes may be a genuine floor for this representation, not a repairable\ninefficiency (consistent with §17/§19's framing). See DESIGN.md §19 and bd\nmemory collapse-global-94g-and-any-label-usage-optimisation for full context.","notes":"RESULT (negative, confirms 7fm): full sweep at budget=1,000,000, pop=16, child_budget=80, workers=4, harbor-house/init.dom cold-start, 4 seeds (0-3):\n\nenable_shape_repair=False (baseline): fails [14,15,12,17] mean=14.50, fitness mean=1.741e-05\nenable_shape_repair=True:             fails [17,14,16,12] mean=14.75, fitness mean=1.24e-05\n\nNo improvement from threading fit into the GA and letting shape_rotate/deslim fire in-search — mean fails is marginally WORSE with the operators enabled, and the 0.25 delta is far inside the seed-to-seed spread (12-17) in both arms. Matches the smaller pilot (budget=20000, 3 seeds: off mean=31.33, on mean=32.00) at a different scale, and matches 7fm's finish-time hill-climb finding that these operators trade one fail for another on already-co-evolved harbor-house layouts.\n\nConclusion: in-search selection pressure and population diversity do NOT rescue shape_rotate/deslim on harbor-house-scale programmes. Supports DESIGN.md §19's framing — the residual fails here look like a genuine floor for this representation on this programme, not a repairable inefficiency reachable by richer local operators. Consistent with bd memory collapse-global-94g-and-any-label-usage-optimisation (geometry-intrinsic fails need geometry/topology search, not local repair or relabeling).\n\nCode kept (not reverted): driver.search()/search_staged() gained enable_shape_repair: bool = False, threading a cached fitness.Fitness instance into operators.mutate() only when set, mirroring the enable_reassociate clean-toggle pattern. Default off reproduces prior runs byte-for-byte. Test: test_enable_shape_repair_threads_fit_into_mutate in tests/test_driver.py. Kept for reuse/reproducibility per the enable_reassociate precedent, not because the flag should default on.","status":"closed","priority":3,"issue_type":"task","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-07-19T10:05:51Z","created_by":"Bruno Postle","updated_at":"2026-07-22T15:54:47Z","started_at":"2026-07-19T19:57:48Z","closed_at":"2026-07-22T15:54:47Z","close_reason":"Closed","dependency_count":0,"dependent_count":0,"comment_count":0}
+{"id":"homemaker-py-161","title":"In-search evaluation of shape_rotate/deslim GA operators (7fm follow-up)","description":"homemaker-py-7fm's finish-time hill-climb found zero improving moves for\nmutate_shape_rotate/mutate_deslim (operators.py) on the 6-layout harbor-house\nsweep — every candidate move traded a shape fail for a new adjacency/access\nfail on the already co-evolved layout. That's a different regime from\nin-search use: a full multi-generation GA run gives selection pressure and\npopulation diversity a chance to accept a locally-worse move that a later\nstep or recombination completes.\n\nTo test: thread `fit` through driver.search (currently only reqs is passed to\noperators.mutate; shape_rotate/deslim need `fit` and currently no-op inside\nthe GA). Gate with an enable_shape_repair-style flag, mirroring how\nenable_reassociate (§12.3) let 9gp.2 do a clean A/B. Run full-budget\nharbor-house search with/without across seeds, compare final fail counts.\n\nIf negative again, the geometry-intrinsic residual on harbor-house-scale\nprogrammes may be a genuine floor for this representation, not a repairable\ninefficiency (consistent with §17/§19's framing). See DESIGN.md §19 and bd\nmemory collapse-global-94g-and-any-label-usage-optimisation for full context.","status":"open","priority":3,"issue_type":"task","owner":"bruno@postle.net","created_at":"2026-07-19T10:05:51Z","created_by":"Bruno Postle","updated_at":"2026-07-19T10:05:51Z","dependency_count":0,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-qpk","title":"In-search WFC collapse: run collapse_global per-eval during search (A/B vs finish-time)","description":"94g landed and validated the FINISH-TIME global cell-\u003eroom collapse (label search\nover a fixed geometry, monotone, best layout 15-\u003e12). The original 94g thrust was\na per-eval IN-SEARCH collapse: evolution searches unlabelled floorplans and the\nfitness collapses (optimally labels) each candidate before scoring, so search\noptimises the condensed objective directly. This issue is that step.\n\nMECHANISM: call collapse_global (or a cheaper incremental variant) inside\n_evaluate_full before the checks, same as the 9o5 collapse_superposition hook\n(fitness.py:_evaluate_full gates on self._superpose). Reuse the 94g substrate:\nc/o/s partition, level hard constraint, adjacency relaxation, public-access pin,\nthreshold objective.\n\nRISK (carried from homemaker-py-xi7, why 9o5 went negative): fitness =\nmax-over-labellings flattens/roughens the landscape — many topologies collapse to\nsimilar best scores, removing the gradient evolution climbs. AMPLIFIED at full\n(global) scope. The finish-time result does NOT de-risk this: finish-time is\nstrictly cannot-worsen by construction; in-search changes the objective every\neval. MUST A/B superpose-global ON vs OFF with a relaxation-gap log, exactly like\nxi7 did for 9o5, before adopting.\n\nCOST: collapse_global builds graphs + an assignment relaxation per eval — far more\nthan 9o5's per-class collapse. Needs an incremental/cheap variant or caching to be\naffordable in the inner loop; profile first.\n\nPrereq ordering: circulation placement (homemaker-py-qi6) and shape repair change\nthe skeleton/geometry the collapse labels over, so ideally sequence those first.\nRelated: 94g (finish-time, done), xi7 (9o5 A/B + relaxation-gap log), 9o5.","notes":"A/B VALIDATION COMPLETE (2026-07-19), xi7 protocol, 4 workers, equal eval\nbudget, both arms finished with standard --collapse (94g finish-time) so\ncomparison is on the final COLLAPSED score:\n\nharbor-house (init.dom, budget=2500, seeds 1-3): ON WINS 3/3.\n  mean fails 80.3 -\u003e 72.0 (s1 85-\u003e74, s2 76-\u003e65, s3 80-\u003e77). No losses.\nprogramme-house (init.dom, budget=3000, seeds 1-5): ON wins 3/5.\n  mean fails 8.4 -\u003e 7.8 (s1 8-\u003e5, s2 8-\u003e7, s4 10-\u003e9 win; s3 8-\u003e9, s5 8-\u003e9\n  loss by 1 fail). Weaker/noisier on this much smaller building (already\n  near its geometry floor, see section13/section19).\nCOMBINED head-to-head: ON 6, OFF 2.\n\nVERDICT: POSITIVE, and the OPPOSITE of the 9o5/xi7 prior (which was\nNULL/NEGATIVE for the per-class interchange relaxation). Unlike 9o5, this is\nthe SAME global WFC-style matching section17/94g already proved\nmonotone/positive at finish time -- running it every eval lets the outer\nsearch see the condensed objective instead of discovering it only once, and\nthe gradient survives rather than flattening. Effect scales WITH building\nsize (harbor-house clean 3/3 vs programme-house mixed), opposite of the 9o5\nlandscape-flattening fear.\n\nCOST: harbor-house wall-clock 102.6s(OFF)-\u003e177.8s(ON) ~1.73x;\nprogramme-house 39.0s-\u003e43.7s ~1.12x. Matches the profiled 1.5-1.9x/eval\nfigure.\n\nDECISION: kept default OFF (programme-house sample too mixed/small to flip\ndefault; 9o5/xi7 scar warrants a second larger-budget confirmation first),\nbut --collapse-insearch is a genuine, tested, working opt-in for\nharbor-house-scale-or-larger programmes. DESIGN.md section20 has full\nwriteup + per-seed numbers. Not filing a follow-up issue -- a larger-N\nprogramme-house seed sweep would be the natural next step if this gets\nrevisited, noted in DESIGN.md as a low-priority idea, not a blocker.\n\nRaw run logs/doms: /tmp scratchpad qpk_ab/ (not committed, ephemeral).","status":"closed","priority":3,"issue_type":"feature","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-07-18T10:12:54Z","created_by":"Bruno Postle","updated_at":"2026-07-19T19:18:44Z","started_at":"2026-07-19T10:11:11Z","closed_at":"2026-07-19T19:18:44Z","close_reason":"A/B validation complete: POSITIVE (opposite of 9o5/xi7 prior). Harbor-house ON wins 3/3 (mean fails 80.3-\u003e72.0); programme-house mixed 3/5. Combined 6/2. Kept default OFF pending a larger programme-house sample, but --collapse-insearch is a working, documented opt-in. See DESIGN.md section20.","dependencies":[{"issue_id":"homemaker-py-qpk","depends_on_id":"homemaker-py-94g","type":"discovered-from","created_at":"2026-07-18T11:12:54Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":0,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-kpu","title":"Schedule B: in-run leaf-sharing annealing (ramp grain down, unfold at each step)","description":"Spun out of homemaker-py-yaa, whose investigation is complete. yaa proved Schedule A (two-phase warm-start) works ONLY when shared leaves are unfolded at the sharing-\u003eno-sharing transition: naive warm-start stalls at 8.66e-08/70 fails, but unfold-then-de-share reaches 4.19e-06/15 fails — matching the direct --no-leaf-sharing baseline. operators.unfold_shared_leaves() is built, tested, and proven.\n\nSchedule B is the in-run variant: instead of a manual two-phase chain, anneal leaf_share_factor down within a single driver run (e.g. 4-\u003e3-\u003e2-\u003eoff) at eval thresholds. At each grain transition: (1) rebuild the cached (dir,sharing) evaluator at the new grain, (2) UNFOLD shared leaves that drop below the new grain so the population stays materialised (reuse operators.unfold_shared_leaves), (3) re-evaluate the whole population under the new evaluator, (4) resume local search. Gradual grain ramp = graduated non-convexity: avoids a single fitness cliff, keeps gross topology fixed on the smaller effective problem early, polishes per-room size/proportion/width late.\n\nDriver hooks needed (driver.py): the evaluator is cached per (dir, sharing) at fitness.py:415 and driver caches one per worker; the ramp must rebuild it and re-score the pop at each threshold. Modest change. Compare head-to-head vs (a) direct baseline 5.14e-06 and (b) the manual unfold warm-chain 4.19e-06 from yaa — does a graduated ramp beat a single hard unfold transition?\n\nWants the circulation-aware unfold from homemaker-py-8iv once available.","notes":"A/B DONE — NEGATIVE (2026-07-17). harbor-house 3M (500k/grain x3 + 1.5M polish, workers 4, ~22h): Schedule B = 1.26e-08 / 23 fails (canonical byte-for-byte). Loses decisively to both targets: direct baseline 5.14e-06/15 and warm-chain 4.19e-06/15 (~400x worse, +8 fails). Graduated ramp FALSIFIED: each grain step spikes fails (phase-end 19-\u003e21-\u003e27, final unfold 27-\u003e36); per-phase budget re-polishes partially-materialised states that the next step materialises further, so coarse-grain gains don't carry forward; polish started from a deeper hole (36) than the warm chain's single clean transition and only reached 23. The sharing-phase topology skeleton (yaa) is best cashed in ONCE at full grain, not annealed. Machinery retained (search_annealed, --anneal-grain, unfold above=, seed_pop, max_share override) — correct/tested/honest — but §15 single-transition finish stays the default. DESIGN §16 updated. Closing.","status":"closed","priority":3,"issue_type":"feature","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-07-15T06:48:11Z","created_by":"Bruno Postle","updated_at":"2026-07-17T15:33:01Z","started_at":"2026-07-16T06:47:57Z","closed_at":"2026-07-17T15:33:01Z","close_reason":"Closed","dependencies":[{"issue_id":"homemaker-py-kpu","depends_on_id":"homemaker-py-8iv","type":"blocks","created_at":"2026-07-15T07:48:30Z","created_by":"Bruno Postle","metadata":"{}"},{"issue_id":"homemaker-py-kpu","depends_on_id":"homemaker-py-yaa","type":"blocks","created_at":"2026-07-15T07:48:28Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":2,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-8iv","title":"unfold: route circulation to interior children (access/adjacency fails)","description":"Follow-up to homemaker-py-yaa. operators.unfold_shared_leaves() materialises a share=k leaf into a BALANCED binary subtree of k equal-target children. This closes the count deficit (all critical missing-room fails) but the balanced split creates interior children with no direct edge onto a corridor, so it introduces access/adjacency polish fails. Measured on harbor-house evolved-3M.dom: after unfold, 0 critical but 59 total fails, of which ~14 access + ~12 adjacency are attributable to the unrouted interior rooms (18 size / 2 width / 2 proportion are the k*target-\u003eper-leaf sizing mismatch, a separate concern).\n\nIdea: make the unfold subdivision circulation-aware instead of purely balanced — bias each cut so every new child retains an edge onto the shared leaf's original access boundary (or onto a sibling circulation leaf), mirroring the adjacency-aware constructive seeder (§11.6). Options: (a) orient/order the k-leaf subtree so children fan off the corridor side rather than nesting inward; (b) reserve a thin circulation spine within the unfolded block; (c) let a few post-unfold local-search evals fix it (cheaper, but that is exactly what the warm-start already does). Compare final endpoint with/without circulation-aware unfold against the 3M direct baseline (5.14e-06).\n\nRelates to the in-run annealing driver change (Schedule B, option B in yaa): if annealing rebuilds+re-evaluates the population at each grain transition, the unfold used there wants the same circulation-aware subdivision.","notes":"A/B VERDICT (seed 0, budget 150k, 4 workers, warm-start no-sharing polish from\nevolved-3M.dom): GRID WINS DECISIVELY. Circulation-aware slice LOSES.\n  slice: 41 fails, fitness 3.52e-14\n  grid : 25 fails, fitness 2.36e-09  (~5 orders better, 16 fewer fails)\nGrid led at EVERY milestone and the gap widened, not a near-tie:\n  ~12k evals slice 67 / grid 49;  ~36k slice 56 / grid 39;\n  ~85k slice 46 / grid 30;  ~130k slice 41 / grid 25.\nSlice never crossed. The thin-slab geometric debt (proportion/long/width) from\nforcing all k rooms onto one corridor wall costs MORE than the access routing\nsaves: local search re-routes access via topology moves (level_retype,\nplace_missing, level_fix) faster than it can widen thin slices (which it can't,\nwithout topology change — k equal slices of a compact leaf are intrinsically\nthin). Grid's squarer children are the better warm-start; yaa already showed grid\nreaches 4.19e-06.\n\nCONCLUSION: circulation-aware slicing is the WRONG trade. Retain the grid unfold.\nThe 8iv hypothesis (route access at unfold time) is falsified for the warm-start\nregime — access is better left to local search on a squarer seed. n=1 but the\ngap is large and monotone across the whole 150k-eval trajectory.","status":"closed","priority":3,"issue_type":"feature","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-07-12T15:38:34Z","created_by":"Bruno Postle","updated_at":"2026-07-16T06:35:46Z","started_at":"2026-07-15T13:46:49Z","closed_at":"2026-07-16T06:35:46Z","close_reason":"Investigated and falsified. Circulation-aware unfold (slice shared leaves perpendicular to their access edge so every child touches the corridor) was implemented + unit-tested, but the warm-start A/B (evolved-3M seed, 150k-eval no-sharing polish) shows it LOSES decisively to the existing balanced grid: slice 41 fails/3.5e-14 vs grid 25 fails/2.4e-09, grid leading monotonically at every milestone. Forcing k rooms onto one wall makes intrinsically thin slices whose geometric debt (proportion/long/width) local search cannot pay down without topology change, whereas grid's squarer children let local search re-route access cheaply via level_retype/place_missing/level_fix. Conclusion: retain grid unfold; access is better left to local search on a squarer seed. Code reverted (operators.py, test_operators.py back to grid). Findings in issue notes; A/B traces in examples/harbor-house/ab-8iv-*.","dependencies":[{"issue_id":"homemaker-py-8iv","depends_on_id":"homemaker-py-yaa","type":"blocks","created_at":"2026-07-12T16:48:16Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":1,"dependent_count":1,"comment_count":0}
@@ -82,25 +82,25 @@
 {"id":"homemaker-py-erc.5","title":"Experiment: compactness-aware cuts (minimize leaf perimeter/area)","description":"Attacks the #1 factor, crinkliness (346) — a per-leaf perimeter/area property DISTINCT from proportion (aspect ratio). Proportion-aware seeding (leu.2) sizes splits but does not bias toward balanced, square-ish subdivision. Add a KD-tree-style 'keep both children compact' cut rule (prefer the cut orientation/position that minimises summed child perimeter/area) in construction.\n\nCONDITIONAL on Diagnostic A: if A shows per-leaf shape-fail is FLAT across densities (floor intrinsic to slicing density), better cuts at the same leaf count will not pay → this should be closed wont-fix in favour of leaf-sharing. Only build if A shows shape-fail RISES with density. A/B vs §12.2 baseline, seeds 0/1/2, 20000 evals, staged, default-OFF. Record DESIGN.md §13.5.","notes":"DEPRIORITISED by erc.1 verdict (§13.1): per-leaf shape-fail flat vs slicing density and cuts already squarest (_size_divisions_from_targets picks squarest rotation) yet still ~1.8 fails/leaf =\u003e little compactness headroom at fixed leaf count. Floor is intrinsic to leaf COUNT, not cut quality. Revisit only if leaf-sharing (erc.3) underdelivers.","status":"closed","priority":4,"issue_type":"feature","owner":"bruno@postle.net","created_at":"2026-06-22T23:16:21Z","created_by":"Bruno Postle","updated_at":"2026-06-28T13:22:17Z","closed_at":"2026-06-28T13:22:17Z","close_reason":"wont-fix (DESIGN §13.7): Diag A (§13.1) showed the floor is intrinsic to leaf COUNT not cut quality; revisit condition was 'only if leaf-sharing underdelivers' but leaf-sharing OVER-delivered (−32…−39%, §13.3). Condition unmet.","dependencies":[{"issue_id":"homemaker-py-erc.5","depends_on_id":"homemaker-py-erc","type":"parent-child","created_at":"2026-06-23T00:16:21Z","created_by":"Bruno Postle","metadata":"{}"},{"issue_id":"homemaker-py-erc.5","depends_on_id":"homemaker-py-erc.1","type":"blocks","created_at":"2026-06-23T00:16:43Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":1,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-2g5","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-\u003eWalls.","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.\nReframed 2026-06-17: orthogonal to epic homemaker-py-c4c. This is fitness FIDELITY (restoring daylight + shaded-wall selection pressure to match Perl), not search CAPABILITY — it changes what 'good' means, not the search's ability to find good. It will NOT improve final designs in the sense currently sought. Stays P4, deferred until the topology-search-quality epic lands and optimisation is fully native.","status":"open","priority":4,"issue_type":"feature","owner":"bruno@postle.net","created_at":"2026-06-11T23:38:25Z","created_by":"Bruno Postle","updated_at":"2026-06-17T19:14:48Z","dependency_count":0,"dependent_count":0,"comment_count":0}
 {"_type":"memory","key":"adjacency-in-binary-slicing-tree-is-structural-not","value":"Adjacency in binary slicing tree is structural, not geometric: the inner-loop NM cannot fix topological adjacency failures. Two paths exist: (1) tree-sibling adjacency — a node is adjacent to its sibling in the tree; (2) cross-zone geometric adjacency — leaves from different subtrees that happen to share a boundary. Staircase/adjacency fails require a topology mutation that changes which nodes are siblings or which zones touch. This was proved empirically on programme-house: staircase fail from rot=0 layout could not be fixed by NM but was fixed by level_retype creating a two-C topology (2026-06-14/15)."}
+{"_type":"memory","key":"unfold-strategy-for-shared-leaves-homemaker-py-8iv","value":"Unfold strategy for shared leaves (homemaker-py-8iv, resolved 2026-07-16): use the BALANCED GRID (operators._grow_balanced/_size_subtree_equal), NOT circulation-aware slicing. Slicing a shared leaf perpendicular to its access edge so every child touches the corridor was implemented + A/B-tested and LOST decisively (150k-eval warm-start polish from evolved-3M: slice 41 fails/3.5e-14 vs grid 25 fails/2.4e-09, grid ahead at every milestone). Reason: k rooms all touching one wall are intrinsically thin slices; that geometric debt (proportion/long/width) is unfixable without topology change, while the grid's squarer children let local search re-route access cheaply via level_retype/place_missing/level_fix. Lesson: at the sharing-\u003eno-sharing transition, prioritise squarer children and leave access to local search; do not reintroduce slicing in Schedule B (kpu)."}
 {"_type":"memory","key":"deceptive-valleys-in-topology-search-when-every-single","value":"Deceptive valleys in topology search: when every single-step mutation from a target state passes through a high-fail intermediary (e.g. level_fix displaces a room into 5+ new fails), a compound operator that atomically applies two coordinated changes can escape. Design compound operators to land on the low-fail state directly, bypassing the deceptive gradient. Programme-house example: level_compound_fix atomically moves the level-constrained room AND re-inserts the displaced room adjacent to C in one step (operators.py, 2026-06-14)."}
-{"_type":"memory","key":"warm-x0-initialization-bug-pattern-when-a-topology","value":"warm_x0 initialization bug pattern: when a topology operator explicitly sets division ratios on a newly-created node (e.g. compound_fix sets node.division=[0.25,0.25] for t3), parent.ratios has no entry for that node (it was a leaf). warm_x0 defaults it to 0.5, corrupting the inner loop's starting point and making the operator invisible to lex comparison. Fix: only propagate child ratios for nodes where the parent node was NOT already divided; stale hidden nodes revealed by structural mutations (swap flipping b.below) must NOT contribute their pre-writeback values. See driver.py lines 259-267 (fixed 2026-06-14)."}
-{"_type":"memory","key":"strategy-decision-2026-06-12-bruno-occlusion-daylight","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."}
-{"_type":"memory","key":"user-preference-bruno-this-is-a-fedora-system","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."}
 {"_type":"memory","key":"experiment-harness-gotcha-the-leaf-sharing-relaxed-objective","value":"Experiment harness gotcha: the leaf-sharing RELAXED objective (§13.3) is injected ONLY by monkeypatching fitness.load_config in the parent process (run_staged_search.py / probe scripts). This is parent-process-only and does NOT propagate into ProcessPoolExecutor workers (n_workers\u003e1), which re-import fitness fresh and score under the STRICT on-disk patterns.config -\u003e r.n_fails MISMATCH (worker strict vs parent relaxed re-score). ALL §13.x floor runs were therefore SERIAL. Any future PARALLEL leaf-sharing experiment will silently mis-score until leaf_sharing lives on disk/CLI (tracked: homemaker-py-x3b). The parallel driver itself is correct; both paths score via load_config(programme_dir)."}
-{"_type":"memory","key":"island-model-psk-14-is-a-null-priming","value":"Island model (psk, §14) is a NULL: priming a population from N converged independent elites + crossover-heavy migration does not beat best-of-N at equal total budget (maple island 124 vs control 116). The child_probe instrument shows WHY: area-matched crossover across independently-converged elites almost never synthesizes (1-3 of ~64 children beat the better parent, max drop 2-5) because the slicing encoding is non-canonical (9gp), so splices are disruptive not combinatorial. Search-machinery null #3 after graded-objective and niching/restarts; residual stays geometry/shape-bound."}
-{"_type":"memory","key":"run-to-run-reproducibility-in-homemaker-layout-serial","value":"Run-to-run reproducibility in homemaker-layout: serial search (workers=1) is byte-for-byte deterministic; parallel (workers\u003e1) is now deterministic too AFTER fixing driver._run_batch to admit futures in submission order (was as_completed/completion order, bug xcy). Reproducibility holds only for a FIXED worker count — serial vs parallel differ because children-per-iteration is 1 vs n_workers (different batch granularity), which is expected, not a bug. The constructive seeder was NEVER nondeterministic: _assign_adjacency_aware has unique idx tiebreaks; comparing topologies with Python builtin hash() of the signature STRING is invalid (PYTHONHASHSEED salts str hashing per process) — use a stable hash (sha1) or genome.signature equality."}
-{"_type":"memory","key":"homemaker-py-3l6-fix-leaf-sharing-evolve-runs","value":"homemaker-py-3l6 fix: leaf-sharing evolve runs now auto-finish before write via driver.polish_finish — unfold_shared_leaves() then a warm-started leaf_sharing=False polish search (--polish-budget, default budget//2). Makes the written .dom honest under canonical homemaker-fitness (internal==canonical when leaf_sharing off). Interrupt path forces polish_budget=0 (unfold+rescore only). This is yaa's unfold-then-polish, made automatic; Schedule B annealing is still kpu."}
 {"_type":"memory","key":"homemaker-py-pythonpath-set-pythonpath-home-bruno-src","value":"homemaker-layout PYTHONPATH: package installed as 'homemaker-layout' via pip install -e . so 'import homemaker_layout' works from anywhere without PYTHONPATH. For running tests use 'python -m pytest' from project root /home/bruno/src/homemaker-layout (pyproject.toml adds src/ automatically). Never try pip show homemaker — that's the old homemaker-addon conflict."}
-{"_type":"memory","key":"never-use-corpus-filenames-candidate-001-dom-candidate","value":"Never use corpus filenames (candidate-001.dom, candidate-002.dom, generated.dom, init.dom, etc.) as --output targets when running experiments. These are test fixtures. Always write experimental outputs to scratch/ or a timestamped path. Lesson from 2026-06-14: warm-start runs overwrote candidate-001/002.dom and broke graph tests."}
+{"_type":"memory","key":"correction-to-urb-fitness-bug-memory-bruno-2026","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."}
-{"_type":"memory","key":"urb-fitness-bug-found-fixed-2026-06-12","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."}
-{"_type":"memory","key":"9o5-multi-use-leaves-is-path-a-superposition","value":"9o5 multi-use leaves is path (a) — superposition as SEARCH RELAXATION that COLLAPSES to specific usage at the end, NOT path (b) loose-fit/no-collapse. Bruno's intent: codes with SIMILAR leaf requirements form an interchangeable equivalence class; during evolution the solver doesn't commit which leaf serves which specific usage (smoother landscape, no fighting over exact leaf usage); at the end the layout is CONDENSED to specific usages by brute-forcing the in-class assignment (3 interchangeable usages over 3 leaves = 3! = 6 combinations to check, pick best). 'Derive automatically' compatibility = requirement-similarity grouping. This reverses the issue's stated 'path b preferred' note."}
-{"_type":"memory","key":"cli-tool-style-prefer-python-m-homemaker-module","value":"CLI tool style: prefer python -m homemaker.module --parameters pattern, installable via pip install -e . with pyproject.toml entry_points. Not standalone bin/ scripts."}
-{"_type":"memory","key":"collapse-global-94g-and-any-label-usage-optimisation","value":"collapse_global (94g) and any label/usage optimisation CANNOT fix geometry-intrinsic fails. The harbor-house 15-fail best layout contains long-thin cells that are useless whatever room usage is assigned — their width/proportion/crinkliness fails are shape-bound, not label slack. Two consequences: (1) do not over-claim collapse gains — only ~2-3 of that layout's fails are reclaimable relabel slack, the rest are geometry- or building-level bound; (2) the threshold objective must not be tuned to 'pass' a degenerate cell via a permissive room type — a metric-pass on a physically useless space is gaming, not a fix. Real remedies for these are geometry/topology search (cell shape) and circulation placement, filed separately, not the collapse."}
-{"_type":"memory","key":"programme-house-optimisation-result-2026-06-14-15","value":"Programme-house optimisation result (2026-06-14/15): best achievable is 1 fail (l1 wrong level, score ~0.005). 0 fails is geometrically impossible: l1 (min 27m²) must occupy ll (~23m²) at level 0, which eliminates the t3-adj-C provider; dividing ll into lll(l1)+llr(C) gives llr proportion ~6:1 (fails). Python memetic optimizer achieves 1 fail in 50k evals vs Perl optimiser's 2-3 fails. Winning topology: TWO C nodes at level 0 — ll(C) for t3-adj-C via geometric contact, rl(C) for staircase via tree-sibling adjacency to rrr(O). Best .dom: scratch/from-warmstart-fixed.dom and scratch/from-compound3-fixed.dom."}
-{"_type":"memory","key":"proportion-aware-constructive-seeding-leu-2-12-2","value":"Proportion-aware constructive seeding (leu.2/§12.2): sizing seed cuts from target AREAS only regresses (thin slivers wreck aspect); you must ALSO pick each cut's rotation for child squareness. It is a convergence ACCELERATOR via a deeper local optimum around the constructed topology: wins where that topology is roughly right and budget is scarce (harbor -13%, maple -10% at 20k evals) but DELAYS small programmes where the seed must be restructured by undivide (programme-house regresses at fixed budget, yet reaches the floor given budget - speed, not asymptote). Default-on. Also: n_storeys must honour storey_minimum, not just level: keys (programme-house storey_minimum:2, all rooms level:0 - was seeded 1 storey short; cq1)."}
 {"_type":"memory","key":"experiment-seeding-pitfall-run-search-scaled-py-s","value":"Experiment seeding pitfall: run_search_scaled.py's default PH_SEED (c964…dom) is a FINISHED programme-house design — passing it warm-starts and floors at ~3 fails, NOT a blank-slate topology search. For blank-slate runs comparable to §11.5/§11.6 baselines, seed from examples/programme-house/init.dom (a bare undivided plot; driver bootstrap auto-triggers only on bare plots). Bit the 6zy sweep — first pass used c964 and falsely showed 3-fail floor across the whole grid."}
 {"_type":"memory","key":"ld2-13-6-interior-o-seed-diagnostic-all","value":"ld2/§13.6 interior-O seed diagnostic: ALL crinkliness fails in the constructed bal+share seed are UNDER-exposed (crink\u003c0.62, landlocked rooms with no facade + no uncovered-O neighbour) — zero over-exposed sliver fails. So the erc crinkliness residual is genuine under-daylighting, validating the interior light-well premise. Default outside_divisor=6 was too sparse (null: harbor 147-\u003e142, crinkliness even rose). odiv=3 is the seed-optimal joint setting: harbor seed fails 147-\u003e129 (-18), maple 219-\u003e206 (-14), landlocked fails drop, at cost of more leaves (harbor +4, maple +8). Because it ADDS leaves it carries the §13.4 wash-out risk; A/B to convergence pending."}
-{"_type":"memory","key":"unfold-strategy-for-shared-leaves-homemaker-py-8iv","value":"Unfold strategy for shared leaves (homemaker-py-8iv, resolved 2026-07-16): use the BALANCED GRID (operators._grow_balanced/_size_subtree_equal), NOT circulation-aware slicing. Slicing a shared leaf perpendicular to its access edge so every child touches the corridor was implemented + A/B-tested and LOST decisively (150k-eval warm-start polish from evolved-3M: slice 41 fails/3.5e-14 vs grid 25 fails/2.4e-09, grid ahead at every milestone). Reason: k rooms all touching one wall are intrinsically thin slices; that geometric debt (proportion/long/width) is unfixable without topology change, while the grid's squarer children let local search re-route access cheaply via level_retype/place_missing/level_fix. Lesson: at the sharing-\u003eno-sharing transition, prioritise squarer children and leave access to local search; do not reintroduce slicing in Schedule B (kpu)."}
+{"_type":"memory","key":"programme-house-optimisation-result-2026-06-14-15","value":"Programme-house optimisation result (2026-06-14/15): best achievable is 1 fail (l1 wrong level, score ~0.005). 0 fails is geometrically impossible: l1 (min 27m²) must occupy ll (~23m²) at level 0, which eliminates the t3-adj-C provider; dividing ll into lll(l1)+llr(C) gives llr proportion ~6:1 (fails). Python memetic optimizer achieves 1 fail in 50k evals vs Perl optimiser's 2-3 fails. Winning topology: TWO C nodes at level 0 — ll(C) for t3-adj-C via geometric contact, rl(C) for staircase via tree-sibling adjacency to rrr(O). Best .dom: scratch/from-warmstart-fixed.dom and scratch/from-compound3-fixed.dom."}
 {"_type":"memory","key":"urb-oracle-nondeterminism-urb-fitness-pl-output-varies","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)."}
-{"_type":"memory","key":"correction-to-urb-fitness-bug-memory-bruno-2026","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."}
+{"_type":"memory","key":"9o5-multi-use-leaves-is-path-a-superposition","value":"9o5 multi-use leaves is path (a) — superposition as SEARCH RELAXATION that COLLAPSES to specific usage at the end, NOT path (b) loose-fit/no-collapse. Bruno's intent: codes with SIMILAR leaf requirements form an interchangeable equivalence class; during evolution the solver doesn't commit which leaf serves which specific usage (smoother landscape, no fighting over exact leaf usage); at the end the layout is CONDENSED to specific usages by brute-forcing the in-class assignment (3 interchangeable usages over 3 leaves = 3! = 6 combinations to check, pick best). 'Derive automatically' compatibility = requirement-similarity grouping. This reverses the issue's stated 'path b preferred' note."}
+{"_type":"memory","key":"collapse-global-94g-and-any-label-usage-optimisation","value":"collapse_global (94g) and any label/usage optimisation CANNOT fix geometry-intrinsic fails. The harbor-house 15-fail best layout contains long-thin cells that are useless whatever room usage is assigned — their width/proportion/crinkliness fails are shape-bound, not label slack. Two consequences: (1) do not over-claim collapse gains — only ~2-3 of that layout's fails are reclaimable relabel slack, the rest are geometry- or building-level bound; (2) the threshold objective must not be tuned to 'pass' a degenerate cell via a permissive room type — a metric-pass on a physically useless space is gaming, not a fix. Real remedies for these are geometry/topology search (cell shape) and circulation placement, filed separately, not the collapse."}
 {"_type":"memory","key":"multi-storey-staircase-consistency-when-dividing-or-retyping","value":"Multi-storey staircase consistency: when dividing or retyping a circulation (C) leaf at one level, the same structural change should be propagated to the matching leaf on ALL other storeys so the stair core path is maintained. The optimizer cannot fix staircase disruptions through trial-and-error geometry alone — it requires a synchronized multi-level operator that applies the same topology change to every storey simultaneously."}
+{"_type":"memory","key":"never-use-corpus-filenames-candidate-001-dom-candidate","value":"Never use corpus filenames (candidate-001.dom, candidate-002.dom, generated.dom, init.dom, etc.) as --output targets when running experiments. These are test fixtures. Always write experimental outputs to scratch/ or a timestamped path. Lesson from 2026-06-14: warm-start runs overwrote candidate-001/002.dom and broke graph tests."}
+{"_type":"memory","key":"cli-tool-style-prefer-python-m-homemaker-module","value":"CLI tool style: prefer python -m homemaker.module --parameters pattern, installable via pip install -e . with pyproject.toml entry_points. Not standalone bin/ scripts."}
+{"_type":"memory","key":"homemaker-py-3l6-fix-leaf-sharing-evolve-runs","value":"homemaker-py-3l6 fix: leaf-sharing evolve runs now auto-finish before write via driver.polish_finish — unfold_shared_leaves() then a warm-started leaf_sharing=False polish search (--polish-budget, default budget//2). Makes the written .dom honest under canonical homemaker-fitness (internal==canonical when leaf_sharing off). Interrupt path forces polish_budget=0 (unfold+rescore only). This is yaa's unfold-then-polish, made automatic; Schedule B annealing is still kpu."}
+{"_type":"memory","key":"urb-fitness-bug-found-fixed-2026-06-12","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."}
+{"_type":"memory","key":"warm-x0-initialization-bug-pattern-when-a-topology","value":"warm_x0 initialization bug pattern: when a topology operator explicitly sets division ratios on a newly-created node (e.g. compound_fix sets node.division=[0.25,0.25] for t3), parent.ratios has no entry for that node (it was a leaf). warm_x0 defaults it to 0.5, corrupting the inner loop's starting point and making the operator invisible to lex comparison. Fix: only propagate child ratios for nodes where the parent node was NOT already divided; stale hidden nodes revealed by structural mutations (swap flipping b.below) must NOT contribute their pre-writeback values. See driver.py lines 259-267 (fixed 2026-06-14)."}
+{"_type":"memory","key":"island-model-psk-14-is-a-null-priming","value":"Island model (psk, §14) is a NULL: priming a population from N converged independent elites + crossover-heavy migration does not beat best-of-N at equal total budget (maple island 124 vs control 116). The child_probe instrument shows WHY: area-matched crossover across independently-converged elites almost never synthesizes (1-3 of ~64 children beat the better parent, max drop 2-5) because the slicing encoding is non-canonical (9gp), so splices are disruptive not combinatorial. Search-machinery null #3 after graded-objective and niching/restarts; residual stays geometry/shape-bound."}
+{"_type":"memory","key":"proportion-aware-constructive-seeding-leu-2-12-2","value":"Proportion-aware constructive seeding (leu.2/§12.2): sizing seed cuts from target AREAS only regresses (thin slivers wreck aspect); you must ALSO pick each cut's rotation for child squareness. It is a convergence ACCELERATOR via a deeper local optimum around the constructed topology: wins where that topology is roughly right and budget is scarce (harbor -13%, maple -10% at 20k evals) but DELAYS small programmes where the seed must be restructured by undivide (programme-house regresses at fixed budget, yet reaches the floor given budget - speed, not asymptote). Default-on. Also: n_storeys must honour storey_minimum, not just level: keys (programme-house storey_minimum:2, all rooms level:0 - was seeded 1 storey short; cq1)."}
+{"_type":"memory","key":"strategy-decision-2026-06-12-bruno-occlusion-daylight","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."}
+{"_type":"memory","key":"run-to-run-reproducibility-in-homemaker-layout-serial","value":"Run-to-run reproducibility in homemaker-layout: serial search (workers=1) is byte-for-byte deterministic; parallel (workers\u003e1) is now deterministic too AFTER fixing driver._run_batch to admit futures in submission order (was as_completed/completion order, bug xcy). Reproducibility holds only for a FIXED worker count — serial vs parallel differ because children-per-iteration is 1 vs n_workers (different batch granularity), which is expected, not a bug. The constructive seeder was NEVER nondeterministic: _assign_adjacency_aware has unique idx tiebreaks; comparing topologies with Python builtin hash() of the signature STRING is invalid (PYTHONHASHSEED salts str hashing per process) — use a stable hash (sha1) or genome.signature equality."}
+{"_type":"memory","key":"user-preference-bruno-this-is-a-fedora-system","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."}

src/homemaker_layout/driver.py

@@ -235,7 +235,6 @@ def search(
     seed_adjacency_aware: bool = True,
     seed_proportion_aware: bool = True,
     enable_reassociate: bool = False,
-    enable_shape_repair: bool = False,
     feasibility_filter: bool = False,
     feasibility_max_shape_fails: int | None = None,
     circ_divisor: int = 3,
@@ -295,16 +294,6 @@ def search(
     finish time, so search optimises the collapsed objective directly. Carries
     the 9o5/xi7 landscape-flattening risk at global scope — do not flip default
     on without a positive A/B (DESIGN.md §17 follow-on).
-
-    ``enable_shape_repair`` (homemaker-py-161, EXPERIMENTAL, default off) threads
-    a ``fitness.Fitness`` instance into ``operators.mutate`` so the ``shape_rotate``
-    and ``deslim`` repair operators (homemaker-py-7fm) can fire during the GA
-    instead of no-opping. 7fm's finish-time hill-climb found these operators never
-    improve an already-co-evolved layout (every candidate move traded one fail for
-    another); this flag tests whether in-search selection pressure lets a
-    locally-worse move survive to be completed by a later step or crossover — a
-    different regime. Mirrors ``enable_reassociate``'s clean-toggle A/B pattern
-    (§12.3, 9gp.2): default off reproduces prior runs byte-for-byte.
     """
     from .oracle import DEFAULT_URB_ROOT
 
@@ -317,13 +306,6 @@ def search(
     mutation_weights = dict(_MUTATION_WEIGHTS)
     if not enable_reassociate:
         mutation_weights["reassociate"] = 0.0
-    # homemaker-py-161: shape_rotate/deslim are gated by operators.mutate itself
-    # (fit_ops go to zero probability when fit=None) — only build the Fitness
-    # instance, and thus only let them fire, when explicitly enabled.
-    shape_repair_fit = (
-        _fitness_for(str(programme_dir), leaf_sharing, superpose, max_share,
-                     conn_grade, collapse_insearch)
-        if enable_shape_repair else None)
     # Optional ranking bonus (DESIGN.md §11.3 Stage 1): bias selection toward
     # individuals with high substrate-readiness via a multiplicative factor
     # (1 + W·bonus) on fitness. The reported fitness/history stay the TRUE
@@ -580,8 +562,7 @@ def search(
                     parent = _tournament(pop, rng, _key, k=tournament_k)
                     child_root, desc = operators.mutate(parent.root, rng, types,
                                                         weights=mutation_weights,
-                                                        reqs=reqs, base_p=base_p,
+                                                        reqs=reqs, base_p=base_p)
-                                                        fit=shape_repair_fit)
                     # Carry operator-specified ratios for nodes that are genuinely
                     # newly divided (existed as leaves in the parent, are now
                     # divided in the child).  Structural mutations (e.g. swap) can
@@ -914,7 +895,6 @@ def search_staged(
     seed_adjacency_aware: bool = True,
     seed_proportion_aware: bool = True,
     enable_reassociate: bool = False,
-    enable_shape_repair: bool = False,
     feasibility_filter: bool = False,
     feasibility_max_shape_fails: int | None = None,
     circ_divisor: int = 3,
@@ -970,7 +950,6 @@ def search_staged(
                       seed_adjacency_aware=seed_adjacency_aware,
                       seed_proportion_aware=seed_proportion_aware,
                       enable_reassociate=enable_reassociate,
-                      enable_shape_repair=enable_shape_repair,
                       feasibility_filter=feasibility_filter,
                       feasibility_max_shape_fails=feasibility_max_shape_fails,
                       circ_divisor=circ_divisor,
@@ -1007,7 +986,6 @@ def search_staged(
             seed_adjacency_aware=seed_adjacency_aware,
             seed_proportion_aware=seed_proportion_aware,
             enable_reassociate=enable_reassociate,
-            enable_shape_repair=enable_shape_repair,
             feasibility_filter=feasibility_filter,
             feasibility_max_shape_fails=feasibility_max_shape_fails,
             circ_divisor=circ_divisor,
@@ -1053,7 +1031,6 @@ def search_staged(
         niche_by_signature=niche_by_signature,
         restart_patience=restart_patience, restart_elite=restart_elite,
         enable_reassociate=enable_reassociate,
-        enable_shape_repair=enable_shape_repair,
         feasibility_filter=feasibility_filter,
         feasibility_max_shape_fails=feasibility_max_shape_fails,
         circ_divisor=circ_divisor,

tests/test_driver.py

@@ -200,36 +200,6 @@ def test_feasibility_filter_off_matches_baseline(fake_inner):
     assert off.n_evals == base.n_evals
 
 
-def test_enable_shape_repair_threads_fit_into_mutate(fake_inner, monkeypatch):
-    """homemaker-py-161: shape_rotate/deslim need a live ``fitness.Fitness`` to
-    identify failing leaves; ``search`` must only build and pass one when
-    ``enable_shape_repair=True`` — off by default, so ``operators.mutate`` sees
-    ``fit=None`` and (per its own gating) never selects those two operators."""
-    from homemaker_layout import fitness, operators
-
-    seen_fit = []
-    real_mutate = operators.mutate
-
-    def spy_mutate(root, rng, types, **kw):
-        seen_fit.append(kw.get("fit"))
-        return real_mutate(root, rng, types, **kw)
-
-    monkeypatch.setattr(operators, "mutate", spy_mutate)
-    init_root = dom.load(str(INIT_FILE))
-
-    off = driver.search(init_root, CORPUS, budget=400, pop_size=4,
-                        child_budget=60, seed_budget=100, seed=5)
-    assert seen_fit and all(f is None for f in seen_fit)
-
-    seen_fit.clear()
-    on = driver.search(init_root, CORPUS, budget=400, pop_size=4,
-                       child_budget=60, seed_budget=100, seed=5,
-                       enable_shape_repair=True)
-    assert seen_fit and all(isinstance(f, fitness.Fitness) for f in seen_fit)
-    # Gating only, not behaviour: same trajectory as the off-by-default run.
-    assert on.best.sig == off.best.sig
-
-
 def test_feasibility_filter_prunes_cheaply(fake_inner, monkeypatch):
     """§12.3 (homemaker-py-9gp.1): a pruned topology costs one feasibility eval
     instead of the full child_budget, so the filter explores far more topologies