shapecurve.leaf_constraints derived each leaf's feasible area from its own
type's base (target, sigma). quality_size does not: a leaf holding k
same-code rooms is centred on k*target with sigma*k, and a co-typed leaf
adds both codes' targets. The DP modelled neither, so eligible() excluded
leaf_sharing/max_share/multi_use -- and leaf_sharing defaults True in
driver.search, so the guard excluded essentially every real run. The DP was
correct and unreachable.
Why the guard could not just be dropped, measured before touching it: on 6
harbor constructed seeds, 24 of 24 shared leaves (100%) have a real area
outside the unscaled single-room bounds. Relaxing eligible without
modelling k would have made the DP call every one of those topologies
infeasible -- false negatives that prune feasible topologies and misdirect
the NM warm-start. The guard was load-bearing.
Fix: mirror quality_size by asking the SAME Fitness object -- k =
graph.leaf_share(leaf, fit._max_share) when fit._leaf_sharing, then
target*k / sigma*k, else fit._leaf_co_type for the additive case. Same
object, same flags, same branch order, deliberately not re-derived: 39.5's
cpsat._matches bug was a solver optimising a relation the scorer had moved,
and this is the same hazard class.
Verified as an exact inversion: for every shared leaf in a real seed,
quality_size evaluated at the DP's amin and amax returns FAIL_THRESHOLD to
1e-9 (k=3 n-leaf: bounds [128.50, 231.50], both 0.100000).
superpose stays excluded for a different reason than the others: it does
not rescale a target, it changes which type the leaf is scored as, and the
collapse happens after the DP has read leaf.type.
shapecurve_warmstart/shapecurve_prune remain default off, so no current run
changes -- including the cold-start baseline in progress. They are now
applicable, which unblocks homemaker-py-v4s.
Closes homemaker-py-tym.
Lint at parity (46); tests 387 passed (3 new, 1 legacy rewritten to the new
contract rather than deleted), 0 failed.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MJ84Feep79Hhm3E4zZJmnB
Generalise shapecurve.py's DP to process dom.levels(root) bottom-up per
storey instead of assuming a single free tree. A divided node's split is
free only per solver.free_branches' own criterion (below is None or
undivided there) -- geometry.coordinate always mirrors a below-linked
node's corners from the storey below regardless of whether that storey's
counterpart is divided, so every free region at any storey reduces to the
exact same single-region problem the pre-existing _check/realise already
solved. New _region_roots finds below-fixed leaves (checked directly,
gridless) and below-fixed-box/free-split fringe nodes per storey;
_solve_all_levels realises each storey before checking the one above and
snapshots+restores on any infeasibility, preserving solve()'s all-or-nothing
and is_feasible()'s never-writes contracts across the whole tree.
eligible() now allows any storey count.
Validated on the real (non-de-risked) examples/harbor-house: 200 random
2-storey topologies, DP-vs-NM agreement 99.5%, 0 false negatives, 117.7x
speedup (DESIGN.md §37.6). Full suite 397 passed.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LSwQwpEaHFBkeVSDDWd75S
Adds shapecurve.is_feasible() (a non-mutating refactor of solve()'s check
phase) and a shapecurve_prune flag composing the DP's exact feasible/
infeasible verdict with operators.predicted_shape_fails' existing heuristic
prune: DP-feasible vetoes a heuristic prune outright; DP-infeasible only
hard-prunes when the incumbent already has zero total fails (exact, since
infeasible proves the shape-fail floor is >=1); otherwise defers unchanged
to today's heuristic threshold. Conservative by design since a wrong prune
is unrecoverable.
Validated 0/400 false negatives across two structurally distinct plots
(harbor-house-l0 + a newly-added programme-house sweep, the first genuinely
non-rectangular plot this DP has been checked against). The real
driver.search A/B on harbor-house-l0 measured NULL (byte-identical off/on)
for a root-caused, pre-existing reason: predicted_shape_fails rarely
triggers organically at this scale, so neither new branch had an opening to
fire -- not a defect in this change. Full writeup: DESIGN.md §37.5.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LSwQwpEaHFBkeVSDDWd75S
Promotes the validated shape-curve DP (experiments/shapecurve_spike.py,
2g7.4, DESIGN.md §37.2) from a reference-only spike into
src/homemaker_layout/shapecurve.py, and wires it into driver._evaluate as a
warm-start for innerloop.optimise: when eligible (single storey, no
leaf_sharing/superpose/max_share/multi_use) and no caller-supplied x0, the
DP's exact shape-feasible ratio point is written onto the tree before NM
runs, off by default (shapecurve_warmstart=/--shapecurve-warmstart).
Caught and fixed a latent bug promoting the spike: realise() could leave
numpy.float64 in `division`, which yaml.safe_dump can't serialise — the
original spike never round-tripped through dom.dumps so this was never hit.
A/B on harbor-house-l0 (experiments/ab_shapecurve_warmstart.py, budget=2000,
5 seeds): mean total fails 16.6 (on) vs 19.6 (off), ~3.5x mean fitness
improvement; mean hard-fail count alone was a noise-level wash at this
sample size. Full writeup in DESIGN.md §37.4.
Deliberately deferred to new tracked beads (children of 2g7): DP-exact hard
pre-filter (wkh), multi-storey below-link support (koo), leaf_sharing/
co_type modelling (tym), true skew-quad polygon algebra (ekc) — 6xh stays
in_progress pending those.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LSwQwpEaHFBkeVSDDWd75S
