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Author SHA1 Message Date
de60200bbc Phase 6 §11.2: programme-aware construction + missing-room repair (c4c.2)
Make the required programme room set a constructive invariant instead of
something the topology search must stumble onto by random divide+retype.

- operators.constructive_topology: bootstrap seeder that sizes each storey to
  its required rooms (partitioned by level; level-free rooms distributed),
  +1 core C and +1 O per storey, then assigns types. Stochastic for population
  diversity. Wired into driver bootstrap when the programme has required spaces.
- operators.mutate_place_missing: repair op that inserts a missing required
  space by dividing a host leaf into [room | remainder]. Lex-safe host ranking
  (generic O first, never displace a required room); honours required level.
  Weight 2.0 in the mutation mix; noops cheaply once the set is complete.

A/B on harbor-house (20k evals, seed 0, identical config):
  old random-bootstrap 133 fails (103 missing, 77%)
  new constructive     105 fails ( 12 missing, 11%)  -21% total, missing-stack
  collapsed; seed head-start 163->139.
§4.10 regression PASS: warmstart-2f4 still reaches a 1-fail population at 50k.

Verdict (DESIGN.md §11.2): construction is necessary and reframes the
bottleneck to quality-fail packing of a complete dense design (crinkliness/
size/access/edge) -> unblocks §11.3 staging, motivates §11.4 graded objective.
Follow-up filed (homemaker-py-s44): adjacency-aware seeding.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-17 22:51:58 +01:00
65085d5c3d Fix warm_x0 to honour operator-specified ratios on new splits
When a compound operator (e.g. level_compound_fix) creates a new
internal node and explicitly sets its division ratio, that ratio was
silently overridden: warm_x0 received parent.ratios which had no entry
for the new node, so Nelder-Mead started at the default 0.5 instead
of the operator's intended 0.25 (for rrl/rrr).  Result: NM evaluated
the compound topology at the wrong geometry and scored 3 fails instead
of 1 — so lex always rejected the compound child, making
level_compound_fix invisible to the outer search.

Fix: for nodes that are genuinely newly divided (not divided in the
parent tree at the same path), inherit the child's operator-set ratio
rather than defaulting to 0.5.  Structural mutations (e.g. swap) can
reveal hidden level-N nodes that retain stale pre-writeback ratios —
those are correctly excluded by checking parent_node.divided.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-15 07:27:03 +01:00
191f603440 Add core_divide, core_undivide, level_fix operators; wire reqs to mutate()
core_divide: divides a C leaf simultaneously on ALL storeys that share that
path, maintaining staircase consistency as an atomic invariant rather than
requiring multi-step recovery.

core_undivide: reverses core_divide consistently across all floors, merging
a C sub-core back into a single C leaf everywhere.

level_fix: atomically moves a level-constrained room to its required floor
by retyping the largest leaf there and vacating the wrong-floor leaf to C.
Requires `reqs` (SpaceReq dict); disabled (zero probability) without it.

mutate() gains `reqs=None` parameter; driver.search() passes its already-
loaded reqs so level_fix fires during the main memetic loop.

Together these let the optimiser escape the deceptive valley around the
2-fail warmstart: level_fix moves l1 to level 0 (reducing fails 2→1),
then core_divide can split the C core to accommodate the displaced t3.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-14 16:10:20 +01:00
3c8f7aba07 Lexicographic outer-search comparison, preserve inner-loop cliff (homemaker-py-yg5)
Outer search now ranks individuals by (-n_fails, fitness) instead of raw
fitness scalar.  This prevents high-score 3-fail designs from displacing
2-fail designs in tournament selection and population replacement — the
root cause of the §4.8 pathology where flag count dominates geometry.

Inner loop is unchanged: it still optimises against the raw 0.5^n fitness
scalar, so the cliff that prevents trading into new failures remains intact
(0/9 regressions in experiments/penalty_reshape.py).

Also removes stale _CHILD_INNER_KW = {"sigmas": (0.05,)}: this was left
over from the CMA-ES era; the NM inner loop default (homemaker-py-d6d)
does not accept a sigmas parameter.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-14 09:20:03 +01:00
646ee30ab6 Rename package: homemaker → homemaker-layout
- src/homemaker/ → src/homemaker_layout/; all imports updated
- pyproject.toml: name = homemaker-layout, entry point updated
- .beads/config.yaml: dolt sync.remote updated to homemaker-layout.git
- Delete temporary debug/perl scripts from project root
- README.md, DESIGN.md: package path references updated
- GitHub repo renamed; git remote updated

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-14 08:18:06 +01:00
Renamed from src/homemaker/driver.py (Browse further)