homemaker-layout/tests/test_operators.py

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"""Operator tests (oracle-free): every child is a valid, canonical genome."""
import copy
from pathlib import Path
import numpy as np
import pytest
from homemaker_layout import dom, genome, operators
CORPUS = Path(__file__).parent.parent / "examples" / "programme-house"
FILES = ["2f45907abd9accac2a124d311732f749.dom", "candidate-002.dom",
"c964435454c459f86c3ed9a5a7621132.dom"]
TYPES = ["k1", "l1", "b1", "b2", "t1", "C", "O"]
pytestmark = pytest.mark.skipif(not CORPUS.is_dir(), reason="Corpus not available")
def canonical(root: dom.Node) -> None:
"""Child must encode to a genome that decode/encode holds fixed."""
g1 = genome.encode(root)
g2 = genome.encode(genome.decode(g1))
assert g2 == g1
@pytest.mark.parametrize("name", sorted(operators.MUTATIONS))
def test_mutations_yield_canonical_genomes(name):
op = operators.MUTATIONS[name]
for f in FILES:
root = genome.decode(genome.encode(dom.load(str(CORPUS / f))))
for seed in range(5):
child, desc = op(root, np.random.default_rng(seed), TYPES)
assert desc.startswith(name.split("_")[0]) or "noop" in desc
canonical(child)
# the parent must never be mutated in place
canonical(root)
def test_divide_grows_and_undivide_shrinks():
root = genome.decode(genome.encode(dom.load(str(CORPUS / FILES[0]))))
n_leaves = sum(len(lvl.leaves()) for lvl in dom.levels(root))
child, _ = operators.mutate_divide(root, np.random.default_rng(0), TYPES)
assert sum(len(lvl.leaves()) for lvl in dom.levels(child)) == n_leaves + 1
child, desc = operators.mutate_undivide(root, np.random.default_rng(0), TYPES)
if "noop" not in desc:
assert sum(len(lvl.leaves()) for lvl in dom.levels(child)) < n_leaves
def test_level_add_delete():
root = genome.decode(genome.encode(dom.load(str(CORPUS / FILES[0]))))
n = len(dom.levels(root))
up, _ = operators.mutate_level_add(root, np.random.default_rng(0), TYPES)
assert len(dom.levels(up)) == n + 1
canonical(up)
down, _ = operators.mutate_level_delete(root, np.random.default_rng(0), TYPES)
assert len(dom.levels(down)) == n - 1
def test_relink_clears_stale_below_after_base_undivide():
# regression: dom.link must clear below-links whose path vanished, or
# geometry on the mutated tree dereferences orphaned nodes
from homemaker_layout import geometry
root = genome.decode(genome.encode(dom.load(str(CORPUS / FILES[0]))))
# force an undivide on the BASE storey specifically
base = dom.levels(root)[0]
cands = [n for li, n in operators._owned_branches(root)
if li == 0 and not n.left.divided and not n.right.divided]
assert cands, "corpus design has no base leaf-pair branch"
import copy as _copy
child = _copy.deepcopy(root)
target = dom.levels(child)[0].by_id(cands[0].id)
target.division = None
target.left = target.right = None
target.type = "l1"
dom.link(child)
geometry.clear_cache()
for lvl in dom.levels(child):
for leaf in lvl.leaves():
for i in range(4):
geometry.coordinate(leaf, i) # must not raise
canonical(child)
assert base.by_id(cands[0].id) is not None # parent untouched
def test_all_mutations_survive_undivided_tree():
# an undivided plot (init.dom-style seed) must never crash an operator
bare = dom.Node(type="O", node=[[0, 0], [10, 0], [10, 8], [0, 8]],
height=2.7, wall_outer=0.25, wall_inner=0.08)
dom.link(bare)
for name, op in operators.MUTATIONS.items():
for seed in range(3):
child, desc = op(bare, np.random.default_rng(seed), TYPES)
assert desc, name
canonical(child)
def test_unfold_shared_leaves_materialises_deficit():
# homemaker-py-yaa: a share=k leaf must unfold into k distinct same-code
# leaves (paying down the count deficit) with the share stamp cleared, while
# every non-shared leaf keeps its identity. Footprint is preserved: the k
# children tile the original leaf, so total plot area is unchanged.
from homemaker_layout import geometry
root = dom.Node(node=[[0, 0], [12, 0], [12, 8], [0, 8]],
height=2.7, wall_outer=0.25, wall_inner=0.08,
rotation=0, division=[0.5, 0.5])
root.left = dom.Node(type="n", share=3, share_type="n") # 3-room shared leaf
root.right = dom.Node(type="C") # untouched
dom.link(root)
geometry.clear_cache()
area_before = geometry.area(root)
created = operators.unfold_shared_leaves(root)
assert created == 2 # 3 rooms - 1 leaf
leaves = root.leaves()
assert sum(1 for lf in leaves if lf.type == "n") == 3 # three distinct n
assert sum(1 for lf in leaves if lf.type == "C") == 1 # C untouched
assert all(lf.share == 1 for lf in leaves) # stamps cleared
geometry.clear_cache()
assert geometry.area(root) == pytest.approx(area_before) # footprint kept
canonical(root) # genome round-trips
kpu: Schedule B in-run leaf-share grain annealing (search_annealed) Ramp the leaf-share grain down within one continuous run (e.g. 4->3->2->off), carrying the whole population across each step — graduated non-convexity over the single hard sharing->off transition of the §15 finish. - operators.unfold_shared_leaves(above=cap): unfold only leaves whose share exceeds the new grain cap, leaving smaller-share leaves collapsed for the next step. above=1 (default) keeps the full-unfold §15 behaviour. - driver: max_share override threaded through _overrides_for/_fitness_for/ _evaluate so a phase can rebuild the evaluator at a lower leaf_share_max cap; search(seed_pop=) evaluates an explicit initial population so a phase hands its whole population to the next instead of restarting from a single best. - driver.search_annealed: one phase per descending grain then a de-share polish; unfold-above-cap between steps; cumulative accounting + grain-tagged history; honest canonical best (byte-for-byte verified vs homemaker-fitness). - evolve: --anneal-grain LADDER CLI (self-finishing; §15 finish not applied). 8iv settled the primitive (grid unfold beat the circulation-aware slice), so the ramp reuses the plain balanced-grid unfold at every step. Tests: unfold above-cap selectivity, seed_pop seeding, search_annealed phase stitching / honest finish / degenerate-ladder fallback. 258 pass. DESIGN §16. Head-to-head A/B on harbor-house still to run; verdict pending (issue open). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01M8566xAxTnwtJTkpXjYNZm
2026-07-16 08:38:08 +01:00
def test_unfold_shared_leaves_above_grain_cap():
# homemaker-py-kpu (Schedule B): ``above=cap`` unfolds only leaves whose
# share EXCEEDS the grain cap, leaving smaller-share leaves collapsed for the
# next lower grain. A share=4 leaf unfolds under above=3; a share=3 leaf does
# not — it stays a single shared leaf.
from homemaker_layout import geometry
root = dom.Node(node=[[0, 0], [12, 0], [12, 8], [0, 8]],
height=2.7, wall_outer=0.25, wall_inner=0.08,
rotation=0, division=[0.5, 0.5])
root.left = dom.Node(type="n", share=4, share_type="n") # exceeds cap 3
root.right = dom.Node(type="m", share=3, share_type="m") # at cap 3, kept
dom.link(root)
kpu: Schedule B in-run leaf-share grain annealing (search_annealed) Ramp the leaf-share grain down within one continuous run (e.g. 4->3->2->off), carrying the whole population across each step — graduated non-convexity over the single hard sharing->off transition of the §15 finish. - operators.unfold_shared_leaves(above=cap): unfold only leaves whose share exceeds the new grain cap, leaving smaller-share leaves collapsed for the next step. above=1 (default) keeps the full-unfold §15 behaviour. - driver: max_share override threaded through _overrides_for/_fitness_for/ _evaluate so a phase can rebuild the evaluator at a lower leaf_share_max cap; search(seed_pop=) evaluates an explicit initial population so a phase hands its whole population to the next instead of restarting from a single best. - driver.search_annealed: one phase per descending grain then a de-share polish; unfold-above-cap between steps; cumulative accounting + grain-tagged history; honest canonical best (byte-for-byte verified vs homemaker-fitness). - evolve: --anneal-grain LADDER CLI (self-finishing; §15 finish not applied). 8iv settled the primitive (grid unfold beat the circulation-aware slice), so the ramp reuses the plain balanced-grid unfold at every step. Tests: unfold above-cap selectivity, seed_pop seeding, search_annealed phase stitching / honest finish / degenerate-ladder fallback. 258 pass. DESIGN §16. Head-to-head A/B on harbor-house still to run; verdict pending (issue open). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01M8566xAxTnwtJTkpXjYNZm
2026-07-16 08:38:08 +01:00
geometry.clear_cache()
created = operators.unfold_shared_leaves(root, above=3)
assert created == 3 # only the share=4 leaf
leaves = root.leaves()
assert sum(1 for lf in leaves if lf.type == "n") == 4 # materialised
assert all(lf.share == 1 for lf in leaves if lf.type == "n")
m = [lf for lf in leaves if lf.type == "m"]
assert len(m) == 1 and m[0].share == 3 # kept collapsed
canonical(root)
HARBOR = Path(__file__).parent.parent / "examples" / "harbor-house"
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_constructive_topology_has_no_missing_spaces():
# §11.2: the constructive seeder must instantiate every required space by
# construction (count + level), so check_space_counts reports zero missing.
from homemaker_layout import graph, programme
reqs = programme.load_programme_dir(str(HARBOR))
types = sorted(reqs) + ["C", "O"]
seed = dom.load(str(HARBOR / "init.dom"))
for trial in range(5):
root = operators.constructive_topology(
seed, reqs, np.random.default_rng(trial), types)
_, missing = graph.check_space_counts(root, reqs)
assert missing == [], f"trial {trial} left {missing}"
# required level partition respected: level-N rooms land on storey N
lvls = dom.levels(root)
for code, req in reqs.items():
if code[0].lower() in "cos" or req.level is None:
continue
for li, lvl in enumerate(lvls):
for leaf in lvl.leaves():
if leaf.type == code:
assert li == req.level
canonical(root)
def test_leaf_share_explicit_and_type_guarded():
# erc.3 §13.3: explicit multiplicity, honoured only while type==share_type so
# a retype silently invalidates a stale share (no operator reset needed).
from homemaker_layout.graph import leaf_share
leaf = dom.Node(type="n", share=3, share_type="n")
assert leaf_share(leaf, 4) == 3
assert leaf_share(leaf, 2) == 2 # clamped at max_share
leaf.type = "ba" # retyped → share no longer matches
assert leaf_share(leaf, 4) == 1
plain = dom.Node(type="n") # default share 1
assert leaf_share(plain, 4) == 1
def _reqs(**share_kw):
"""Build a tiny programme: sized 'b' (share per kwarg), sized 'k', unsized 'C'."""
from homemaker_layout.programme import SpaceReq
b = SpaceReq(code="b", size=12.0, has_size=True, count=5)
if "b" in share_kw:
b.share, b.has_share = share_kw["b"], True
k = SpaceReq(code="k", size=20.0, has_size=True, count=4)
if "k" in share_kw:
k.share, k.has_share = share_kw["k"], True
c = SpaceReq(code="C", size=0.0, has_size=False, count=3) # unsized circulation
return {"b": b, "k": k, "C": c}
def _mults(plan_entry):
return sorted(plan_entry)
def test_share_grain_opt_in_mode():
# homemaker-py-x3b: factor 0 = per-code opt-in. A code shares iff it carries an
# explicit share:N>=2; sized codes without the key, and unsized codes, do not.
reqs = _reqs(b=3)
assert operators._share_grain(reqs["b"], 0) == 3 # explicit opt-in
assert operators._share_grain(reqs["k"], 0) == 1 # sized but no key → unshared
assert operators._share_grain(reqs["C"], 0) == 1 # unsized → never shareable
assert operators._share_grain(_reqs(b=1)["b"], 0) == 1 # share:1 stays unshared
def test_share_grain_global_mode_with_per_code_override():
# factor>=2 = global: every sized code shares at the factor unless its entry
# overrides — share:1 opts OUT, share:N sets that code's grain to N.
reqs = _reqs(b=1, k=4)
assert operators._share_grain(reqs["b"], 3) == 1 # explicit share:1 → opt out
assert operators._share_grain(reqs["k"], 3) == 4 # explicit share:4 → grain 4
assert operators._share_grain(_reqs()["k"], 3) == 3 # no key → global factor 3
assert operators._share_grain(_reqs()["C"], 3) == 1 # unsized → never shareable
def test_share_rooms_opt_in_groups_only_flagged_code():
# factor 0: only 'b' (share:3) collapses into runs of 3; 'k' and 'C' untouched.
rooms = ["b"] * 5 + ["k"] * 4 + ["C"] * 3
reduced, plan = operators._share_rooms(rooms, _reqs(b=3), 0)
assert _mults(plan["b"]) == [2, 3] # 5 rooms → runs of 3 + 2
assert plan["k"] == [1, 1, 1, 1] # no share key → unshared
assert plan["C"] == [1, 1, 1] # unsized → unshared
assert reduced.count("b") == 2 and reduced.count("k") == 4
def test_share_rooms_global_with_opt_out():
# factor 3 global: 'k' shares at 3 (no key), 'b' opted OUT via share:1.
rooms = ["b"] * 5 + ["k"] * 4
reduced, plan = operators._share_rooms(rooms, _reqs(b=1), 3)
assert plan["b"] == [1, 1, 1, 1, 1] # share:1 → opt out, stays 5 leaves
assert _mults(plan["k"]) == [1, 3] # 4 rooms → run of 3 + 1
# multiplicities always sum back to the original room counts (no rooms lost)
assert sum(plan["b"]) == 5 and sum(plan["k"]) == 4
def test_share_rooms_default_off_parity():
# Master switch off path: callers never invoke _share_rooms, but a single
# instance or grain<2 must yield the identity plan regardless of factor.
rooms = ["b", "k", "k", "C"]
reduced, plan = operators._share_rooms(rooms, _reqs(), 0) # opt-in, no keys
assert reduced == rooms and all(m == 1 for ms in plan.values() for m in ms)
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_leaf_sharing_reduces_leaves_and_covers_rooms():
# erc.3 §13.3: leaf_sharing builds fewer leaves, and coverage-counting lets
# the larger shared leaves satisfy several same-code rooms without missing.
from homemaker_layout import graph, programme
reqs = programme.load_programme_dir(str(HARBOR))
types = sorted(reqs) + ["C", "O"]
seed = dom.load(str(HARBOR / "init.dom"))
for trial in range(3):
plain = operators.constructive_topology(
seed, reqs, np.random.default_rng(trial), types)
shared = operators.constructive_topology(
seed, reqs, np.random.default_rng(trial), types,
leaf_sharing=True, leaf_share_factor=2)
n_plain = sum(len(l.leaves()) for l in dom.levels(plain))
n_shared = sum(len(l.leaves()) for l in dom.levels(shared))
assert n_shared < n_plain, f"trial {trial}: {n_shared} !< {n_plain}"
# Default-OFF parity: the flag defaults reproduce the strict count check.
assert (graph.check_space_counts(shared, reqs)
== graph.check_space_counts(shared, reqs, leaf_sharing=False))
# Coverage suppresses missings: the shared tree scored WITH leaf_sharing
# has fewer missing fails than the same tree scored without it.
_strict, miss_off = graph.check_space_counts(shared, reqs)
_cov, miss_on = graph.check_space_counts(shared, reqs, leaf_sharing=True)
assert len(miss_on) < len(miss_off), f"trial {trial}: sharing didn't cover"
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_interior_outside_seeds_landlocked_wells_and_scales_count():
# ld2 §13.6: interior_outside seeds O on the most landlocked leaves (lower
# external-perimeter exposure) instead of the most peripheral one, and scales
# the O count with the room count. Construction must still cover every room.
from homemaker_layout import graph, geometry, programme
reqs = programme.load_programme_dir(str(HARBOR))
types = sorted(reqs) + ["C", "O"]
seed = dom.load(str(HARBOR / "init.dom"))
def _outside_exposure(root):
geometry.clear_cache()
dom.link(root)
exps, n_o = [], 0
for lvl in dom.levels(root):
for leaf in lvl.leaves():
if leaf.type and leaf.type[0].lower() == "o":
n_o += 1
exps.append(operators._ext_exposure(leaf))
return n_o, (sum(exps) / len(exps) if exps else 0.0)
for trial in range(3):
peri = operators.constructive_topology(
seed, reqs, np.random.default_rng(trial), types,
interior_outside=False)
inter = operators.constructive_topology(
seed, reqs, np.random.default_rng(trial), types,
interior_outside=True, outside_divisor=3)
# no missing rooms either way
assert graph.check_space_counts(inter, reqs)[1] == []
n_peri, _exp_peri = _outside_exposure(peri)
n_inter, exp_inter = _outside_exposure(inter)
# the lever adds more outside leaves (scaled with room count)…
assert n_inter > n_peri, f"trial {trial}: {n_inter} !> {n_peri}"
# …and places them on landlocked leaves: a well averaging < 1 external
# plot edge is interior by construction (peripheral mode does not aim
# for this — its single O is chosen by circulation distance, so it can
# land anywhere — hence we assert the absolute landlocked property).
assert exp_inter < 1.0, (
f"trial {trial}: interior O wells not landlocked (mean exp {exp_inter})")
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_adjacency_aware_seeding_cuts_adjacency_access_fails():
# s44: adjacency-aware construction clusters rooms around a connected
# circulation spine, cutting the adjacency-to-c + access fails that random
# type assignment leaves stranded. Compare like-for-like over several seeds.
import copy
from homemaker_layout import fitness, programme
reqs = programme.load_programme_dir(str(HARBOR))
conf, cost = fitness.load_config(str(HARBOR))
fit = fitness.Fitness(conf, cost)
types = sorted(reqs) + ["C", "O"]
seed = dom.load(str(HARBOR / "init.dom"))
def adj_access(aware: bool) -> float:
total = 0
for trial in range(6):
root = operators.constructive_topology(
seed, reqs, np.random.default_rng(trial), types,
adjacency_aware=aware)
_, fails = fit.score_with_fails(copy.deepcopy(root))
total += sum(1 for f in fails if "adjacent" in f or "access" in f
or "inaccessible" in f)
return total / 6
assert adj_access(True) < adj_access(False)
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_adjacency_aware_lift_cuts_adjacency_access_fails():
# ld5: lift_base_to_storeys grows the upper-floor circulation spine off the
# inherited core and clusters rooms around it, cutting the same fail classes
# on the storeys above the base.
import copy
from homemaker_layout import fitness, programme
reqs = programme.load_programme_dir(str(HARBOR))
conf, cost = fitness.load_config(str(HARBOR))
fit = fitness.Fitness(conf, cost)
types = sorted(reqs) + ["C", "O"]
n_st = programme.n_storeys_required(reqs)
seed = dom.load(str(HARBOR / "init.dom"))
def adj_access(aware: bool) -> float:
total = 0
for trial in range(5):
rng = np.random.default_rng(trial)
buckets = programme.partition_rooms_by_storey(reqs, n_st, rng)
base = operators.constructive_topology(seed, reqs, rng, types)
base0 = dom.levels(base)[0]
base0.above = None
lifted = operators.lift_base_to_storeys(
base0, buckets[1:], rng, types, reqs=reqs, adjacency_aware=aware)
_, fails = fit.score_with_fails(copy.deepcopy(lifted))
total += sum(1 for f in fails if "adjacent" in f or "access" in f
or "inaccessible" in f)
return total / 5
assert adj_access(True) < adj_access(False)
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_construction_beam_width_default_matches_greedy():
# homemaker-py-c94: beam_width=1 (the default, both explicit and implicit)
# must reproduce the prior one-shot greedy room placement byte-for-byte.
from homemaker_layout import programme
reqs = programme.load_programme_dir(str(HARBOR))
types = sorted(reqs) + ["C", "O"]
seed = dom.load(str(HARBOR / "init.dom"))
for trial in range(3):
plain = operators.constructive_topology(
seed, reqs, np.random.default_rng(trial), types)
explicit = operators.constructive_topology(
seed, reqs, np.random.default_rng(trial), types,
construction_beam_width=1)
assert genome.encode(plain) == genome.encode(explicit)
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_construction_beam_width_yields_valid_seed():
# A beam_width>1 seed must still satisfy the same construction invariants
# as the greedy path: every required space present, canonical genome.
from homemaker_layout import graph, programme
reqs = programme.load_programme_dir(str(HARBOR))
types = sorted(reqs) + ["C", "O"]
seed = dom.load(str(HARBOR / "init.dom"))
for trial in range(5):
root = operators.constructive_topology(
seed, reqs, np.random.default_rng(trial), types,
construction_beam_width=4)
_, missing = graph.check_space_counts(root, reqs)
assert missing == [], f"trial {trial} left {missing}"
canonical(root)
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_construction_beam_width_lift_yields_valid_seed():
# Each upper storey's placed room multiset must match its requested
# bucket exactly (the invariant lift_base_to_storeys/_assign_adjacency_
# aware owns) and the whole tree must stay canonical. Unlike
# constructive_topology, a base built from the FULL reqs (as in
# test_adjacency_aware_lift_cuts_adjacency_access_fails above) need not
# sum with an independently-drawn upper bucket split to the whole-building
# total, so this checks the per-storey bucket invariant instead of
# graph.check_space_counts.
from collections import Counter
from homemaker_layout import programme
reqs = programme.load_programme_dir(str(HARBOR))
types = sorted(reqs) + ["C", "O"]
n_st = programme.n_storeys_required(reqs)
seed = dom.load(str(HARBOR / "init.dom"))
for trial in range(3):
rng = np.random.default_rng(trial)
buckets = programme.partition_rooms_by_storey(reqs, n_st, rng)
base = operators.constructive_topology(seed, reqs, rng, types)
base0 = dom.levels(base)[0]
base0.above = None
lifted = operators.lift_base_to_storeys(
base0, buckets[1:], rng, types, reqs=reqs,
construction_beam_width=4)
lvls = dom.levels(lifted)
for bucket, lvl in zip(buckets[1:], lvls[1:]):
placed = Counter(lf.type for lf in lvl.leaves() if lf.type in bucket)
assert placed == Counter(bucket), f"trial {trial}: {placed} != {bucket}"
canonical(lifted)
def test_beam_place_rooms_is_deterministic_given_inputs():
# _beam_place_rooms takes no rng — same inputs must give the same
# placement every call (only the caller's code-order shuffle is
# stochastic, already exercised via constructive_topology above).
class Req:
def __init__(self, adjacency):
self.adjacency = adjacency
reqs = {"a": Req([("c",)]), "b": Req([("a",)]), "c": Req([])}
slots = [dom.Node(type=None) for _ in range(3)]
idx = {L: i for i, L in enumerate(slots)}
deg = {L: 1 for L in slots}
dominated = set(slots)
def _nbrs(L):
return set(slots) - {L}
codes = ["a", "b"]
r1 = operators._beam_place_rooms(codes, slots, dominated, deg, idx,
_nbrs, reqs, beam_width=2)
r2 = operators._beam_place_rooms(codes, slots, dominated, deg, idx,
_nbrs, reqs, beam_width=2)
assert r1 == r2
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_construction_assign_cpsat_yields_valid_seed():
# homemaker-py-2g7.5: the CP-SAT room-labelling path must satisfy the same
# construction invariants as the greedy path — every required space
# present, canonical genome.
from homemaker_layout import graph, programme
reqs = programme.load_programme_dir(str(HARBOR))
types = sorted(reqs) + ["C", "O"]
seed = dom.load(str(HARBOR / "init.dom"))
for trial in range(5):
root = operators.constructive_topology(
seed, reqs, np.random.default_rng(trial), types,
assign_solver="cpsat")
_, missing = graph.check_space_counts(root, reqs)
assert missing == [], f"trial {trial} left {missing}"
canonical(root)
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_assign_cpsat_matches_or_beats_greedy_secondary_adjacency():
# homemaker-py-2g7.5: CP-SAT solves the same room-labelling decision the
# greedy/beam heuristic approximates exactly — its secondary-adjacency
# (not the access/adjacent-to-c fails the dominating-set step already
# solves) fail count must be strictly lower in aggregate.
import copy
from homemaker_layout import fitness, programme
reqs = programme.load_programme_dir(str(HARBOR))
conf, cost = fitness.load_config(str(HARBOR))
fit = fitness.Fitness(conf, cost)
types = sorted(reqs) + ["C", "O"]
seed = dom.load(str(HARBOR / "init.dom"))
def secondary_fails(solver: str) -> list[int]:
counts = []
for trial in range(10):
root = operators.constructive_topology(
seed, reqs, np.random.default_rng(trial), types,
assign_solver=solver)
_, fails = fit.score_with_fails(copy.deepcopy(root))
counts.append(sum(1 for f in fails if "not adjacent to" in f))
return counts
# Per-seed outcomes are noisy (both solvers depend on the same random
# room-order shuffle before falling into their own placement logic), so
# the comparison is on the aggregate over several seeds, not every seed
# individually — measured on harbor-house (10 seeds): cpsat wins on
# most, ties on a few, loses on rare ones, net ~13% fewer total fails.
§39.4 completion + §39.5 retraction + §39.6: the usage namespace is NOT clean Answering "are we clean". Generic namespace: yes. Usage namespace: no. FINISH §39.4. The first sweep missed sites, found by a full re-grep: graph.py's free-area budget, operators.py host-preference / keep-type / repair-candidate, fitness.py's ("l","c","k") public-access test, bubble.py's generic adjacency reference, and -- the important one -- cpsat.py, which was still matching adjacency by raw startswith. graph.code_matches_requirement is now the single public answer to "does this leaf count as the thing the programme asked to be next to", shared by has_adjacency, has_vertical_connection and cpsat. RETRACT §39.5. It concluded 2g7.5's CP-SAT seeder win did not survive the correction. That was wrong. The cause was the missed cpsat matcher above: the exact solver was optimising a different relation than the scorer checked, so a failing test reporting an incomplete sweep was misread as a baseline shift. Re-measured over 6 seeds, cpsat now wins on both programmes (harbor 102/92, maple 156/154). xfail removed. REAL BUG UNDERNEATH: CP-SAT was never deterministic despite num_search_workers=1 and a comment claiming it. neighbors[slot] is a set of dom.Node, which hashes by id() -- a memory address -- so raw iteration made the model-build order vary and CP-SAT returned a different equally-optimal assignment each run (measured 194/180/171/182 over four identical aggregates). sorted() on the slot indices fixes it. Also paired the wall-clock cap with max_deterministic_time (solves run ~124ms against a 2s cap, so nothing was timing out -- latent hazard, not the cause). solve_room_labels is now reproducible on every captured instance; constructive_topology on the cpsat path still is not, filed as homemaker-py-fdp (plausible contributor to b8g). §39.6 THE SECOND NAMESPACE. Usage prefixes b/t/l/k (bedroom/toilet/living/ kitchen) classify programme codes by first letter and stay prefix-based by design, but they are not inert: has_circulation deletes graph edges from them. Four corpus rooms are misclassified by spelling -- la1 "Laundry Room" and li1 "Library Corner" as living, br1 "Staff Room" as bedroom, tr1 "Treatment Room" as toilet. Measured on a health-centre seed: tr1 loses its edge to the adjacent O, br1 loses its edge to t10 "Staff WC" -- both feed the connectivity fails §38 found persisting. Filed homemaker-py-sel; an explicit usage: key is the fix, but it changes fitness for correctly-spelled programmes too so it needs its own A/B. DOCS. README gains a "Room codes and reserved names" section; CLAUDE.md and AGENTS.md gain the same summary for agents. audit_programme_config.py now reports the usage class each code picks up alongside the namespace and satisfiability checks. DESIGN §37.2's note calling the c/o/s quirk "existing product behaviour, not a bug" is annotated as superseded. Corpus audit: zero generic-namespace violations across all ten example programmes. 346 passed, same 7 pre-existing fixture failures, lint unchanged. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01MJ84Feep79Hhm3E4zZJmnB
2026-08-26 10:09:14 +00:00
# The cpsat path is not yet bit-reproducible (homemaker-py-fdp): the solver
# itself is deterministic, but something upstream of it in
# _assign_adjacency_aware still varies, so a single 10-seed aggregate can
# straddle greedy's (deterministic) value. Averaging three repeats asserts
# what is actually claimed -- better IN AGGREGATE -- instead of being flaky
# by construction. Measured after §39.4: greedy 189, cpsat 185/177/180/182.
greedy = sum(secondary_fails("greedy"))
cpsat_runs = [sum(secondary_fails("cpsat")) for _ in range(3)]
mean_cpsat = sum(cpsat_runs) / len(cpsat_runs)
assert mean_cpsat < greedy, f"cpsat {cpsat_runs} (mean {mean_cpsat}) vs greedy {greedy}"
def test_reassign_noop_without_reqs():
root = genome.decode(genome.encode(dom.load(str(CORPUS / FILES[0]))))
child, desc = operators.mutate_reassign(root, np.random.default_rng(0), TYPES)
assert desc == "reassign noop"
canonical(child)
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_reassign_fires_and_preserves_room_multiset():
# homemaker-py-2g7.5: the reassign operator must fire (find at least one
# wing to re-label) on a real seeded design, and it must preserve the
# wing's exact room-code multiset — only the leaf<->code labelling
# changes, never the topology or which codes are present.
from collections import Counter
from homemaker_layout import programme
reqs = programme.load_programme_dir(str(HARBOR))
types = sorted(reqs) + ["C", "O"]
seed = dom.load(str(HARBOR / "init.dom"))
Declare toilet-to-sleeping adjacency where the brief supports it A toilet next to a sleeping room is a positive even with no door between them (Brand): the adjacency is what makes a later knock-through possible. The engine already scores it -- check_adjacency runs against the unfiltered graph_base_pre -- but only where a programme declares it, and only programme-house did. Declared: harbor-house t -> n bathrooms serve the Neighborhoods (communal sleeping); both unpinned, 6 t / 5 n maple-court tt -> r Upper Bathrooms among Individual Rooms, both level 2, already 62% adjacent at seed time NOT declared, and checking before declaring is what caught these: maple t -> n is IMPOSSIBLE. Adjacency is evaluated per level, and maple pins t to level 0, n to level 1. Declaring it would have added six permanently unsatisfiable fails; the 0% seed-time rate was a hard impossibility, not search difficulty. maple's ground floor has six bathrooms and one sleeping room (Clinic Room x1) -- a ground-floor WC in a communal building is public, so Brand does not apply anyway. health-centre has no dedicated WC. The ruling was that a treatment room "may give access to a toilet, but this would be a dedicated toilet"; t9 is a Public WC and t10 a Staff WC. Earning the credit needs a WC added to the brief -- programme authoring, filed as homemaker-py-5nw. Both declarations are reachable (best of 8 seeds 2/3 harbor, 2/2 maple), so the search gets a gradient not a permanent penalty. evolved-3M-nols-3 84 -> 89 fails, all five the new requirement. Cost: cpsat assignment ~7.5x slower on harbor (0.28 -> 2.11s per seed); greedy, the default, unchanged at 0.06s. Ordinary runs pay nothing, but 39.5's cpsat-vs-greedy verdict was measured on a cheaper problem than the corpus now poses -- filed as homemaker-py-vjd. Two tests were over-fitted to the old seeds and are repaired to assert their intent, not relaxed to pass: reassign now sweeps six constructive seeds (seed 0's better-seeded design legitimately has nothing to improve, 5 of 6 others fire), and repair_circulation asserts that repair strictly helps plus a >=85% bar rather than a sampled 100% hardened into a guarantee (measured 25% -> 92%, stable over 6 and 12 seeds). Closes homemaker-py-3qj. Lint at parity (46); tests 379 passed, 0 failed. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01MJ84Feep79Hhm3E4zZJmnB
2026-08-29 10:57:44 +00:00
# Sweep several constructive seeds rather than pinning seed 0. The operator
# only fires when it finds a wing worth re-labelling, so a seed that happens
# to be already-optimal is a legitimate noop, not a broken operator --
# declaring harbor's `t -> n` adjacency (homemaker-py-3qj) made the
# adjacency-aware seeder good enough that seed 0 became exactly that case,
# while 5 of 6 other seeds still fire. Pinning one seed was testing the
# seeder's luck, not the operator.
fired = False
Declare toilet-to-sleeping adjacency where the brief supports it A toilet next to a sleeping room is a positive even with no door between them (Brand): the adjacency is what makes a later knock-through possible. The engine already scores it -- check_adjacency runs against the unfiltered graph_base_pre -- but only where a programme declares it, and only programme-house did. Declared: harbor-house t -> n bathrooms serve the Neighborhoods (communal sleeping); both unpinned, 6 t / 5 n maple-court tt -> r Upper Bathrooms among Individual Rooms, both level 2, already 62% adjacent at seed time NOT declared, and checking before declaring is what caught these: maple t -> n is IMPOSSIBLE. Adjacency is evaluated per level, and maple pins t to level 0, n to level 1. Declaring it would have added six permanently unsatisfiable fails; the 0% seed-time rate was a hard impossibility, not search difficulty. maple's ground floor has six bathrooms and one sleeping room (Clinic Room x1) -- a ground-floor WC in a communal building is public, so Brand does not apply anyway. health-centre has no dedicated WC. The ruling was that a treatment room "may give access to a toilet, but this would be a dedicated toilet"; t9 is a Public WC and t10 a Staff WC. Earning the credit needs a WC added to the brief -- programme authoring, filed as homemaker-py-5nw. Both declarations are reachable (best of 8 seeds 2/3 harbor, 2/2 maple), so the search gets a gradient not a permanent penalty. evolved-3M-nols-3 84 -> 89 fails, all five the new requirement. Cost: cpsat assignment ~7.5x slower on harbor (0.28 -> 2.11s per seed); greedy, the default, unchanged at 0.06s. Ordinary runs pay nothing, but 39.5's cpsat-vs-greedy verdict was measured on a cheaper problem than the corpus now poses -- filed as homemaker-py-vjd. Two tests were over-fitted to the old seeds and are repaired to assert their intent, not relaxed to pass: reassign now sweeps six constructive seeds (seed 0's better-seeded design legitimately has nothing to improve, 5 of 6 others fire), and repair_circulation asserts that repair strictly helps plus a >=85% bar rather than a sampled 100% hardened into a guarantee (measured 25% -> 92%, stable over 6 and 12 seeds). Closes homemaker-py-3qj. Lint at parity (46); tests 379 passed, 0 failed. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01MJ84Feep79Hhm3E4zZJmnB
2026-08-29 10:57:44 +00:00
for construct_seed in range(6):
root = operators.constructive_topology(
seed, reqs, np.random.default_rng(construct_seed), types)
before = Counter(lf.type for lf in root.leaves())
for trial in range(20):
child, desc = operators.mutate_reassign(
root, np.random.default_rng(trial), types, reqs=reqs)
canonical(child)
after = Counter(lf.type for lf in child.leaves())
assert after == before, (
f"construct seed {construct_seed}, trial {trial}: "
f"room multiset changed ({desc})")
if not desc.endswith("noop"):
fired = True
assert fired, "reassign never fired on any of 6 real seeded designs"
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_place_missing_repairs_deficient_tree():
# §11.2 repair: iterating mutate_place_missing drives a deficient design's
# missing-space count to zero, then noops once the required set is complete.
from homemaker_layout import graph, programme
reqs = programme.load_programme_dir(str(HARBOR))
types = sorted(reqs) + ["C", "O"]
rng = np.random.default_rng(0)
root = dom.load(str(HARBOR / "generated.dom"))
_, missing0 = graph.check_space_counts(root, reqs)
assert missing0, "fixture should start deficient"
for _ in range(len(missing0) + 5):
root, desc = operators.mutate_place_missing(root, rng, types, reqs=reqs)
canonical(root)
_, missing = graph.check_space_counts(root, reqs)
if not missing:
break
assert missing == []
_, desc = operators.mutate_place_missing(root, rng, types, reqs=reqs)
assert desc == "place_missing noop"
def test_crossover_yields_canonical_pair():
a = genome.decode(genome.encode(dom.load(str(CORPUS / FILES[0]))))
b = genome.decode(genome.encode(dom.load(str(CORPUS / FILES[1]))))
for seed in range(5):
ca, cb, desc = operators.crossover(a, b, np.random.default_rng(seed))
assert desc.startswith("crossover")
canonical(ca)
canonical(cb)
# --------------------------------------------------------------------------- #
# 9gp.2 — M3 re-association move
# --------------------------------------------------------------------------- #
def _leaf_types(root: dom.Node) -> list[str]:
return sorted(lf.type or "." for lvl in dom.levels(root) for lf in lvl.leaves())
def _same_axis_chain() -> dom.Node:
"""A 3-leaf ``(a|b)|c`` tree with two parallel (same-orientation) cuts."""
root = dom.Node(rotation=0, division=[0.4, 0.4])
root.left = dom.Node(rotation=0, division=[0.5, 0.5])
root.left.left = dom.Node(type="A")
root.left.right = dom.Node(type="B")
root.right = dom.Node(type="C")
dom.link(root)
return root
def test_reassociate_preserves_leaves_changes_shape():
root = _same_axis_chain()
before_types = _leaf_types(root)
before_sig = genome.signature(root)
child, desc = operators.mutate_reassociate(root, np.random.default_rng(0), TYPES)
assert "noop" not in desc
# leaf set + types are an invariant; only the tree shape changes
assert _leaf_types(child) == before_types
assert genome.signature(child) != before_sig
canonical(child)
# parent untouched in place
assert genome.signature(root) == before_sig
canonical(root)
def test_reassociate_noop_on_perpendicular_cuts():
# Outer cut rotation 0, inner cut rotation 1 (perpendicular) → not the
# associativity precondition, so there is no candidate and it noops.
root = dom.Node(rotation=0, division=[0.4, 0.4])
root.left = dom.Node(rotation=1, division=[0.5, 0.5])
root.left.left = dom.Node(type="A")
root.left.right = dom.Node(type="B")
root.right = dom.Node(type="C")
dom.link(root)
_, desc = operators.mutate_reassociate(root, np.random.default_rng(0), TYPES)
assert desc == "reassociate noop"
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_reassociate_on_corpus_is_canonical_and_total():
from homemaker_layout import programme
reqs = programme.load_programme_dir(str(HARBOR))
types = sorted(reqs) + ["C", "O"]
root = dom.load(str(HARBOR / "generated.dom"))
before = _leaf_types(root)
for seed in range(8):
child, desc = operators.mutate_reassociate(root, np.random.default_rng(seed), types)
canonical(child)
if "noop" not in desc:
# leaf multiset preserved even on a real multi-storey tree
assert _leaf_types(child) == before
# --------------------------------------------------------------------------- #
# 9gp.1 — shape-feasibility proxy
# --------------------------------------------------------------------------- #
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_predicted_shape_fails_is_nonneg_and_pure():
from homemaker_layout import fitness, programme
reqs = programme.load_programme_dir(str(HARBOR))
conf, cost = fitness.load_config(str(HARBOR))
fit = fitness.Fitness(conf, cost)
root = dom.load(str(HARBOR / "generated.dom"))
n_leaves = sum(len(lvl.leaves()) for lvl in dom.levels(root))
pred = operators.predicted_shape_fails(root, reqs, fit)
assert isinstance(pred, int) and pred >= 0
# input root is untouched (a deep copy is laid out and scored)
assert sum(len(lvl.leaves()) for lvl in dom.levels(root)) == n_leaves
# deterministic
assert operators.predicted_shape_fails(root, reqs, fit) == pred
# --------------------------------------------------------------------------- #
# 7fm — targeted shape repair (shape_rotate / deslim)
# --------------------------------------------------------------------------- #
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_shape_failing_flags_known_fail_only():
from homemaker_layout import fitness, programme
conf, cost = fitness.load_config(str(HARBOR))
fit = fitness.Fitness(conf, cost)
root = dom.load(str(HARBOR / "generated.dom"))
lvl0 = dom.levels(root)[0]
# generated.dom/0/rr (type "r") has a real proportion fail (fixture,
# verified via homemaker-fitness); an outside leaf is never a candidate
# regardless of its geometry.
assert operators._shape_failing(lvl0.by_id("rr"), fit)
assert not operators._shape_failing(lvl0.by_id("lllrl"), fit) # type O
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_mutate_shape_rotate_noop_without_fit():
root = dom.load(str(HARBOR / "generated.dom"))
child, desc = operators.mutate_shape_rotate(root, np.random.default_rng(0), TYPES)
assert "noop" in desc
canonical(child)
def _with_forced_slim_leaf(root: dom.Node, code: str = "r") -> tuple[dom.Node, str]:
"""Force a real, deterministic shape fail: divide the largest outside leaf
95/5 into (``code``, "C"). The 5% side is narrow/high-aspect on any real
plot, and both sides are fresh leaves (a valid deslim candidate too),
unlike the fixture's organic fails which may not have a mergeable sibling."""
from homemaker_layout import geometry
child = copy.deepcopy(root)
lvl0 = dom.levels(child)[0]
host = max((lf for lf in lvl0.leaves() if lf.type == "O"), key=geometry.area)
host_id = host.id
host.division = [0.05, 0.05]
host.rotation = 0
host.left = dom.Node(type=code)
host.right = dom.Node(type="C")
host.type = None
child = operators._finalise(child)
leaf_id = (host_id + "l") if host_id else "l"
return child, leaf_id
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_mutate_shape_rotate_targets_a_failing_cut():
from homemaker_layout import fitness, programme
reqs = programme.load_programme_dir(str(HARBOR))
types = sorted(reqs) + ["C", "O"]
conf, cost = fitness.load_config(str(HARBOR))
fit = fitness.Fitness(conf, cost)
root, leaf_id = _with_forced_slim_leaf(dom.load(str(HARBOR / "generated.dom")))
assert operators._shape_failing(dom.levels(root)[0].by_id(leaf_id), fit)
child, desc = operators.mutate_shape_rotate(root, np.random.default_rng(0), types, fit=fit)
assert "noop" not in desc
canonical(child)
# only the rotation of the targeted cut changes; leaf multiset preserved
assert _leaf_types(child) == _leaf_types(root)
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_mutate_deslim_merges_failing_leaf_and_is_repairable():
from homemaker_layout import fitness, graph, programme
reqs = programme.load_programme_dir(str(HARBOR))
types = sorted(reqs) + ["C", "O"]
conf, cost = fitness.load_config(str(HARBOR))
fit = fitness.Fitness(conf, cost)
root, _leaf_id = _with_forced_slim_leaf(dom.load(str(HARBOR / "generated.dom")))
n_leaves = sum(len(lvl.leaves()) for lvl in dom.levels(root))
child, desc = operators.mutate_deslim(root, np.random.default_rng(0), types, fit=fit)
assert "noop" not in desc
canonical(child)
# a merge strictly reduces the leaf count...
assert sum(len(lvl.leaves()) for lvl in dom.levels(child)) == n_leaves - 1
# ...and the displaced room is repairable by the existing place_missing op
_, missing = graph.check_space_counts(child, reqs)
assert missing
rng = np.random.default_rng(0)
for _ in range(len(missing) + 5):
child, _ = operators.mutate_place_missing(child, rng, types, reqs=reqs)
_, missing = graph.check_space_counts(child, reqs)
if not missing:
break
assert missing == []
# --------------------------------------------------------------------------- #
# 8sh — insert/relocate-circulation repair (mechanism (a) follow-on to qi6)
# --------------------------------------------------------------------------- #
def _row_of_three(mid_type: str) -> dom.Node:
"""Three same-height leaves in a row: ``C | [mid_type | C]``. The two ``C``
leaves each share a full-height edge with the middle leaf but not with
each other, so their circulation components are disconnected a 2-fail
``level 0 not connected`` fixture for a single ``mid_type`` leaf bridge."""
root = dom.Node(rotation=0, division=[1 / 3, 1 / 3],
node=[[0, 0], [12, 0], [12, 4], [0, 4]],
height=2.7, wall_outer=0.25, wall_inner=0.08)
root.left = dom.Node(type="C")
root.right = dom.Node(rotation=0, division=[0.5, 0.5])
root.right.left = dom.Node(type=mid_type)
root.right.right = dom.Node(type="C")
dom.link(root)
return root
def _diamond(top_right_type: str) -> dom.Node:
"""2x2 grid: ``C``/``O`` on the left column, ``top_right_type``/``C`` on
the right, so the two ``C`` corners have two equal-length bridge routes
one through the free ``O`` leaf, one through ``top_right_type``."""
root = dom.Node(rotation=0, division=[0.5, 0.5],
node=[[0, 0], [8, 0], [8, 8], [0, 8]],
height=2.7, wall_outer=0.25, wall_inner=0.08)
root.left = dom.Node(rotation=1, division=[0.5, 0.5])
root.left.left = dom.Node(type="C")
root.left.right = dom.Node(type="O")
root.right = dom.Node(rotation=1, division=[0.5, 0.5])
root.right.left = dom.Node(type=top_right_type)
root.right.right = dom.Node(type="C")
dom.link(root)
return root
def _n_circ_components(root: dom.Node) -> int:
import networkx as nx
G = _geo_leaf_graph(root)
circ = [n for n in G.nodes() if dom.is_circulation(n)]
return len(list(nx.connected_components(G.subgraph(circ))))
def _geo_leaf_graph(lvl: dom.Node):
from homemaker_layout import geometry, graph as _graph
return geometry.leaf_graph(lvl, _graph.DOOR_WIDTH)
def test_mutate_bridge_circulation_noop_when_already_connected():
root = _row_of_three("C") # all three already circulation → one component
assert _n_circ_components(root) == 1
_, desc = operators.mutate_bridge_circulation(root, np.random.default_rng(0), TYPES)
assert desc == "bridge_circulation noop"
def test_mutate_bridge_circulation_bridges_fragmented_level():
root = _row_of_three("O")
assert _n_circ_components(root) == 2
child, desc = operators.mutate_bridge_circulation(root, np.random.default_rng(0), TYPES)
assert "noop" not in desc
assert desc.startswith("bridge_circulation")
canonical(child)
assert _n_circ_components(child) == 1
# the free 'O' leaf was converted; the two original 'C' leaves untouched
mid = dom.levels(child)[0].by_id("rl")
assert mid.type == "C"
# parent left untouched
assert dom.levels(root)[0].by_id("rl").type == "O"
def test_mutate_bridge_circulation_falls_back_to_required_room_if_only_route():
from homemaker_layout import programme
root = _row_of_three("b1")
reqs = {"b1": programme.SpaceReq(code="b1")}
assert _n_circ_components(root) == 2
child, desc = operators.mutate_bridge_circulation(
root, np.random.default_rng(0), TYPES + ["b1"], reqs=reqs)
assert "noop" not in desc
assert _n_circ_components(child) == 1
assert dom.levels(child)[0].by_id("rl").type == "C"
def test_mutate_bridge_circulation_prefers_free_leaf_over_required_room():
from homemaker_layout import programme
root = _diamond("b1")
reqs = {"b1": programme.SpaceReq(code="b1")}
assert _n_circ_components(root) == 2
child, desc = operators.mutate_bridge_circulation(
root, np.random.default_rng(0), TYPES + ["b1"], reqs=reqs)
assert "noop" not in desc
canonical(child)
assert _n_circ_components(child) == 1
# bridges via the free 'O' leaf ('lr'), not the required 'b1' ('rl')
lvl0 = dom.levels(child)[0]
assert lvl0.by_id("lr").type == "C"
assert lvl0.by_id("rl").type == "b1"
§39.4: tighten generic-type matching, reverting the harbor rename Supersedes the previous commit's approach. Renaming harbor's four colliding codes fixed one programme; tightening the matching rule fixes the rule, so a room may be called anything. cr1/of/st1/st2 are restored and the examples are byte-identical to their pre-§39 state -- which also means existing .dom artefacts (evolved-3M*) stay valid, so migrate_ju3_rename.py is deleted. The rule: Urb has exactly three GENERIC structural types (get_space_types: qw/C O S/), the leaves the search creates. Measured across the corpus: 154 C, 110 O, 1 S, not one lowercase generic -- while every programme code is lowercase, including single-character ones (r, t, m, n). Case is the discriminator, not length. Every generic test was type[0].lower() in (...), a case-insensitive PREFIX that swept up any programme code starting with those letters; they now match the generic set exactly. 30 sites across dom, fitness, graph, operators, programme, shapecurve and bubble. NOT applied to the SEMANTIC prefixes: l/k/b/t classify programme codes by first letter (graph.py builds bedroom<->toilet and kitchen<->living relations from them) and stay prefix-based. Where the namespaces were mixed in one expression they were split -- has_circulation's ("b","l","k","c") is three semantic prefixes plus dom.is_circulation; access()'s ("l","c","s") is semantic l plus the generic circulation set. New: dom.GENERIC_{CIRCULATION,OUTSIDE,TYPES} + is_generic(); fitness. _generic_class(), replacing the _t0 dispatch in quality_size/quality_width/ quality_proportion/value_rate -- the four terms that mattered most and that a first sweep missed, since they dispatch through a t0 variable rather than an inline test. graph._adjacency_target resolves a generic adjacency requirement (programmes write "adjacency: [c, o]") to the generic set while every other requirement keeps Perl's prefix semantics. Two subtleties: S is in both generic sets but takes the OUTSIDE parameter families -- a first translation tested circulation first and silently gave S the circulation params, caught by test_get_space_params_sahn_proportion. And validate_codes survives, narrowed to a code spelled exactly C/O/S, which is a genuine ambiguity; merely starting with c/o/s is now fine. Invariant asserted as a test: test_scoring_is_invariant_under_programme_code_ spelling relabels one tree and its config together and re-scores. Bit-identical across 12 comparisons (6 seeds x collapse on/off). Re-baseline (seed 1, 20k, original names): 58 fails (15 hard / 43 soft) against the real 37-instance programme, with cr1 at 79.1 m2 vs declared 80 (was 32.9 and 17.1), of/st1/st2 all present and in band, and one fail naming any of them. 57 -> 58 on a 5-instance-harder programme is within noise: "did not regress". Fallout (§39.5): 2g7.5's CP-SAT seeder win does not survive. Over 6 seeds -- harbor real 102/114 (cpsat loses), harbor old-effective 98/99 (tie, so the win was already marginal), maple-court 156/144 (cpsat wins). maple is the control: the solver did not regress, harbor's programme changed. Test xfail'd with that reason plus a maple companion; both assign_solver flags stay default off. Filed homemaker-py-w6x to re-check other narrow-margin harbor A/Bs. 345 passed, 1 xfailed, same 7 pre-existing fixture failures. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01MJ84Feep79Hhm3E4zZJmnB
2026-08-26 09:45:28 +00:00
@pytest.mark.skipif(not (HARBOR.parent / "maple-court").is_dir(),
reason="maple-court not available")
def test_assign_cpsat_beats_greedy_on_a_namespace_clean_programme():
§39.4 completion + §39.5 retraction + §39.6: the usage namespace is NOT clean Answering "are we clean". Generic namespace: yes. Usage namespace: no. FINISH §39.4. The first sweep missed sites, found by a full re-grep: graph.py's free-area budget, operators.py host-preference / keep-type / repair-candidate, fitness.py's ("l","c","k") public-access test, bubble.py's generic adjacency reference, and -- the important one -- cpsat.py, which was still matching adjacency by raw startswith. graph.code_matches_requirement is now the single public answer to "does this leaf count as the thing the programme asked to be next to", shared by has_adjacency, has_vertical_connection and cpsat. RETRACT §39.5. It concluded 2g7.5's CP-SAT seeder win did not survive the correction. That was wrong. The cause was the missed cpsat matcher above: the exact solver was optimising a different relation than the scorer checked, so a failing test reporting an incomplete sweep was misread as a baseline shift. Re-measured over 6 seeds, cpsat now wins on both programmes (harbor 102/92, maple 156/154). xfail removed. REAL BUG UNDERNEATH: CP-SAT was never deterministic despite num_search_workers=1 and a comment claiming it. neighbors[slot] is a set of dom.Node, which hashes by id() -- a memory address -- so raw iteration made the model-build order vary and CP-SAT returned a different equally-optimal assignment each run (measured 194/180/171/182 over four identical aggregates). sorted() on the slot indices fixes it. Also paired the wall-clock cap with max_deterministic_time (solves run ~124ms against a 2s cap, so nothing was timing out -- latent hazard, not the cause). solve_room_labels is now reproducible on every captured instance; constructive_topology on the cpsat path still is not, filed as homemaker-py-fdp (plausible contributor to b8g). §39.6 THE SECOND NAMESPACE. Usage prefixes b/t/l/k (bedroom/toilet/living/ kitchen) classify programme codes by first letter and stay prefix-based by design, but they are not inert: has_circulation deletes graph edges from them. Four corpus rooms are misclassified by spelling -- la1 "Laundry Room" and li1 "Library Corner" as living, br1 "Staff Room" as bedroom, tr1 "Treatment Room" as toilet. Measured on a health-centre seed: tr1 loses its edge to the adjacent O, br1 loses its edge to t10 "Staff WC" -- both feed the connectivity fails §38 found persisting. Filed homemaker-py-sel; an explicit usage: key is the fix, but it changes fitness for correctly-spelled programmes too so it needs its own A/B. DOCS. README gains a "Room codes and reserved names" section; CLAUDE.md and AGENTS.md gain the same summary for agents. audit_programme_config.py now reports the usage class each code picks up alongside the namespace and satisfiability checks. DESIGN §37.2's note calling the c/o/s quirk "existing product behaviour, not a bug" is annotated as superseded. Corpus audit: zero generic-namespace violations across all ten example programmes. 346 passed, same 7 pre-existing fixture failures, lint unchanged. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01MJ84Feep79Hhm3E4zZJmnB
2026-08-26 10:09:14 +00:00
"""§39.5 companion: the same property on a second, namespace-clean
programme.
Kept because it was this pair that caught an incomplete §39.4 sweep:
``cpsat._matches`` was still matching adjacency by raw prefix after
``graph.has_adjacency`` had been tightened, so the exact solver was
optimising a different relation than the scorer checked. Two programmes
make that class of drift visible instead of looking like noise.
§39.4: tighten generic-type matching, reverting the harbor rename Supersedes the previous commit's approach. Renaming harbor's four colliding codes fixed one programme; tightening the matching rule fixes the rule, so a room may be called anything. cr1/of/st1/st2 are restored and the examples are byte-identical to their pre-§39 state -- which also means existing .dom artefacts (evolved-3M*) stay valid, so migrate_ju3_rename.py is deleted. The rule: Urb has exactly three GENERIC structural types (get_space_types: qw/C O S/), the leaves the search creates. Measured across the corpus: 154 C, 110 O, 1 S, not one lowercase generic -- while every programme code is lowercase, including single-character ones (r, t, m, n). Case is the discriminator, not length. Every generic test was type[0].lower() in (...), a case-insensitive PREFIX that swept up any programme code starting with those letters; they now match the generic set exactly. 30 sites across dom, fitness, graph, operators, programme, shapecurve and bubble. NOT applied to the SEMANTIC prefixes: l/k/b/t classify programme codes by first letter (graph.py builds bedroom<->toilet and kitchen<->living relations from them) and stay prefix-based. Where the namespaces were mixed in one expression they were split -- has_circulation's ("b","l","k","c") is three semantic prefixes plus dom.is_circulation; access()'s ("l","c","s") is semantic l plus the generic circulation set. New: dom.GENERIC_{CIRCULATION,OUTSIDE,TYPES} + is_generic(); fitness. _generic_class(), replacing the _t0 dispatch in quality_size/quality_width/ quality_proportion/value_rate -- the four terms that mattered most and that a first sweep missed, since they dispatch through a t0 variable rather than an inline test. graph._adjacency_target resolves a generic adjacency requirement (programmes write "adjacency: [c, o]") to the generic set while every other requirement keeps Perl's prefix semantics. Two subtleties: S is in both generic sets but takes the OUTSIDE parameter families -- a first translation tested circulation first and silently gave S the circulation params, caught by test_get_space_params_sahn_proportion. And validate_codes survives, narrowed to a code spelled exactly C/O/S, which is a genuine ambiguity; merely starting with c/o/s is now fine. Invariant asserted as a test: test_scoring_is_invariant_under_programme_code_ spelling relabels one tree and its config together and re-scores. Bit-identical across 12 comparisons (6 seeds x collapse on/off). Re-baseline (seed 1, 20k, original names): 58 fails (15 hard / 43 soft) against the real 37-instance programme, with cr1 at 79.1 m2 vs declared 80 (was 32.9 and 17.1), of/st1/st2 all present and in band, and one fail naming any of them. 57 -> 58 on a 5-instance-harder programme is within noise: "did not regress". Fallout (§39.5): 2g7.5's CP-SAT seeder win does not survive. Over 6 seeds -- harbor real 102/114 (cpsat loses), harbor old-effective 98/99 (tie, so the win was already marginal), maple-court 156/144 (cpsat wins). maple is the control: the solver did not regress, harbor's programme changed. Test xfail'd with that reason plus a maple companion; both assign_solver flags stay default off. Filed homemaker-py-w6x to re-check other narrow-margin harbor A/Bs. 345 passed, 1 xfailed, same 7 pre-existing fixture failures. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01MJ84Feep79Hhm3E4zZJmnB
2026-08-26 09:45:28 +00:00
"""
import copy
from homemaker_layout import fitness, programme
maple = HARBOR.parent / "maple-court"
reqs = programme.load_programme_dir(str(maple))
conf, cost = fitness.load_config(str(maple))
fit = fitness.Fitness(conf, cost)
types = sorted(reqs) + ["C", "O"]
seed = dom.load(str(maple / "init.dom"))
def secondary_fails(solver: str) -> int:
total = 0
for trial in range(6):
root = operators.constructive_topology(
seed, reqs, np.random.default_rng(trial), types,
assign_solver=solver)
_, fails = fit.score_with_fails(copy.deepcopy(root))
total += sum(1 for f in fails if "not adjacent to" in f)
return total
assert secondary_fails("cpsat") < secondary_fails("greedy")
§39.9: level-not-connected is destroyed by the resize, not by the search Answers homemaker-py-yql. §39.8 established the search is not PAID to sever circulation; this establishes where connectivity actually goes. CONSTRUCTED, THEN LOST -- at construction time, in the resize. _assign_adjacency_aware picks circulation as a CONNECTED dominating set and succeeds every time. _size_divisions_from_targets then moves every wall to hit the programme's area targets and destroys it. Measured over 20 constructed seeds per programme, fully-connected seeds: harbor-house 1/20, health-centre 1/20, maple-court 0/20. The control -- same seeds with proportion_aware=False, i.e. no resize -- is 100% connected on all three. Mechanism confirmed on health-centre: 41 of 49 circulation-to-circulation edges destroyed by the resize, surviving shared walls squeezed to 0.54-1.11 m against door_width=1.2, so they stop counting as edges. This is the failure mode §37.7 recorded for CP-SAT assignment, never looked for in connectivity, where it costs 35-95 points. §39.7 COST CHECK: zero. Identical rates under prefix-inferred vs declared usages -- has_circulation never trims C-C edges, so last commit's usage change could not and did not make connectivity harder to achieve. REPAIR MEASURED NEGATIVE. operators.repair_circulation_settled applies §37.7's own alternating-minimisation fix (re-connect against the settled geometry by retyping the cheapest bridging leaves to C). It restores 100% connectivity on all three programmes -- and is still the wrong trade: connectivity fails fall 0.8-1.7 per seed while missing-room fails rise 5.0-8.5, because every retyped leaf displaces a required room at a 3-5 fail cascade (§38.5). Kept default off with the write-up, per house style for a null lever, plus a byte-identical default test and a test asserting it does reconnect every storey. NEXT LEVER, FILED: preserve the connection during the resize (constrain _size_divisions_from_targets so a shared C-C boundary cannot fall below door_width) rather than rebuild it afterwards at the programme's expense -- a constraint on an existing solve, not a new repair pass. solver.py's existing min_width_generic is the same idea applied to leaf width rather than to a shared boundary, so it may belong beside it. Adds experiments/diag_connectivity_yql.py (construct / cost / survive reports). 355 passed (+2 new), same 7 pre-existing fixture failures, lint unchanged. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01MJ84Feep79Hhm3E4zZJmnB
2026-08-26 14:39:07 +00:00
# --------------------------------------------------------------------------- #
# homemaker-py-yql / DESIGN.md §39.9 — settled-geometry circulation repair
# --------------------------------------------------------------------------- #
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_repair_circulation_default_off_reproduces_prior_seeds():
"""Default off must be byte-identical, like every other experimental flag."""
from homemaker_layout import programme
reqs = programme.load_programme_dir(str(HARBOR))
types = sorted(reqs) + ["C", "O"]
seed = dom.load(str(HARBOR / "init.dom"))
kw = dict(min_storeys=programme.storey_minimum(str(HARBOR)),
adjacency_aware=True, proportion_aware=True, circ_divisor=3)
def sig(**extra):
root = operators.constructive_topology(
seed, reqs, np.random.default_rng(3), types, **kw, **extra)
return tuple(lf.type for lvl in dom.levels(root) for lf in lvl.leaves())
assert sig() == sig(repair_circulation=False)
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_repair_circulation_reconnects_every_storey():
"""§39.9: the constructed circulation dominating set is connected, but
_size_divisions_from_targets then moves every wall and the shared
boundaries it relied on drop below door_width. Repairing against the
SETTLED geometry restores connectivity measured 52% -> 100% of levels on
harbor-house. (Whether that is a net WIN is a different question: it is
not, see §39.9 it displaces required rooms. Hence default off.)
"""
import networkx as nx
from homemaker_layout import geometry, graph as graph_mod, programme
reqs = programme.load_programme_dir(str(HARBOR))
types = sorted(reqs) + ["C", "O"]
seed = dom.load(str(HARBOR / "init.dom"))
def levels_connected(repair: bool) -> tuple[int, int]:
ok = tot = 0
for s in range(6):
root = operators.constructive_topology(
seed, reqs, np.random.default_rng(s), types,
min_storeys=programme.storey_minimum(str(HARBOR)),
adjacency_aware=True, proportion_aware=True, circ_divisor=3,
repair_circulation=repair)
for lvl in dom.levels(root):
geometry.clear_cache()
G = geometry.leaf_graph(lvl, graph_mod.DOOR_WIDTH)
circ = [n for n in G.nodes() if dom.is_circulation(n)]
tot += 1
if circ and nx.is_connected(G.subgraph(circ)):
ok += 1
return ok, tot
off_ok, off_tot = levels_connected(False)
on_ok, on_tot = levels_connected(True)
Declare toilet-to-sleeping adjacency where the brief supports it A toilet next to a sleeping room is a positive even with no door between them (Brand): the adjacency is what makes a later knock-through possible. The engine already scores it -- check_adjacency runs against the unfiltered graph_base_pre -- but only where a programme declares it, and only programme-house did. Declared: harbor-house t -> n bathrooms serve the Neighborhoods (communal sleeping); both unpinned, 6 t / 5 n maple-court tt -> r Upper Bathrooms among Individual Rooms, both level 2, already 62% adjacent at seed time NOT declared, and checking before declaring is what caught these: maple t -> n is IMPOSSIBLE. Adjacency is evaluated per level, and maple pins t to level 0, n to level 1. Declaring it would have added six permanently unsatisfiable fails; the 0% seed-time rate was a hard impossibility, not search difficulty. maple's ground floor has six bathrooms and one sleeping room (Clinic Room x1) -- a ground-floor WC in a communal building is public, so Brand does not apply anyway. health-centre has no dedicated WC. The ruling was that a treatment room "may give access to a toilet, but this would be a dedicated toilet"; t9 is a Public WC and t10 a Staff WC. Earning the credit needs a WC added to the brief -- programme authoring, filed as homemaker-py-5nw. Both declarations are reachable (best of 8 seeds 2/3 harbor, 2/2 maple), so the search gets a gradient not a permanent penalty. evolved-3M-nols-3 84 -> 89 fails, all five the new requirement. Cost: cpsat assignment ~7.5x slower on harbor (0.28 -> 2.11s per seed); greedy, the default, unchanged at 0.06s. Ordinary runs pay nothing, but 39.5's cpsat-vs-greedy verdict was measured on a cheaper problem than the corpus now poses -- filed as homemaker-py-vjd. Two tests were over-fitted to the old seeds and are repaired to assert their intent, not relaxed to pass: reassign now sweeps six constructive seeds (seed 0's better-seeded design legitimately has nothing to improve, 5 of 6 others fire), and repair_circulation asserts that repair strictly helps plus a >=85% bar rather than a sampled 100% hardened into a guarantee (measured 25% -> 92%, stable over 6 and 12 seeds). Closes homemaker-py-3qj. Lint at parity (46); tests 379 passed, 0 failed. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01MJ84Feep79Hhm3E4zZJmnB
2026-08-29 10:57:44 +00:00
# The claim is that repairing against the SETTLED geometry restores
# connectivity the wall-settling destroyed -- not that it never fails. It is
# a heuristic over already-placed walls; nothing makes it complete. The
# original `on_ok == on_tot` hardened a sampled 100% into a guarantee, and
# it broke the moment the seeds changed (homemaker-py-3qj's `t -> n`
# adjacency reseeds harbor): measured 25% -> 92%, stable across 6 and 12
# seeds. The bar below is a real regression detector, comfortably clear of
# 92% but well above the 25% baseline.
§39.9: level-not-connected is destroyed by the resize, not by the search Answers homemaker-py-yql. §39.8 established the search is not PAID to sever circulation; this establishes where connectivity actually goes. CONSTRUCTED, THEN LOST -- at construction time, in the resize. _assign_adjacency_aware picks circulation as a CONNECTED dominating set and succeeds every time. _size_divisions_from_targets then moves every wall to hit the programme's area targets and destroys it. Measured over 20 constructed seeds per programme, fully-connected seeds: harbor-house 1/20, health-centre 1/20, maple-court 0/20. The control -- same seeds with proportion_aware=False, i.e. no resize -- is 100% connected on all three. Mechanism confirmed on health-centre: 41 of 49 circulation-to-circulation edges destroyed by the resize, surviving shared walls squeezed to 0.54-1.11 m against door_width=1.2, so they stop counting as edges. This is the failure mode §37.7 recorded for CP-SAT assignment, never looked for in connectivity, where it costs 35-95 points. §39.7 COST CHECK: zero. Identical rates under prefix-inferred vs declared usages -- has_circulation never trims C-C edges, so last commit's usage change could not and did not make connectivity harder to achieve. REPAIR MEASURED NEGATIVE. operators.repair_circulation_settled applies §37.7's own alternating-minimisation fix (re-connect against the settled geometry by retyping the cheapest bridging leaves to C). It restores 100% connectivity on all three programmes -- and is still the wrong trade: connectivity fails fall 0.8-1.7 per seed while missing-room fails rise 5.0-8.5, because every retyped leaf displaces a required room at a 3-5 fail cascade (§38.5). Kept default off with the write-up, per house style for a null lever, plus a byte-identical default test and a test asserting it does reconnect every storey. NEXT LEVER, FILED: preserve the connection during the resize (constrain _size_divisions_from_targets so a shared C-C boundary cannot fall below door_width) rather than rebuild it afterwards at the programme's expense -- a constraint on an existing solve, not a new repair pass. solver.py's existing min_width_generic is the same idea applied to leaf width rather than to a shared boundary, so it may belong beside it. Adds experiments/diag_connectivity_yql.py (construct / cost / survive reports). 355 passed (+2 new), same 7 pre-existing fixture failures, lint unchanged. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01MJ84Feep79Hhm3E4zZJmnB
2026-08-26 14:39:07 +00:00
assert on_ok > off_ok, f"repair did not help: {off_ok}/{off_tot} -> {on_ok}/{on_tot}"
Declare toilet-to-sleeping adjacency where the brief supports it A toilet next to a sleeping room is a positive even with no door between them (Brand): the adjacency is what makes a later knock-through possible. The engine already scores it -- check_adjacency runs against the unfiltered graph_base_pre -- but only where a programme declares it, and only programme-house did. Declared: harbor-house t -> n bathrooms serve the Neighborhoods (communal sleeping); both unpinned, 6 t / 5 n maple-court tt -> r Upper Bathrooms among Individual Rooms, both level 2, already 62% adjacent at seed time NOT declared, and checking before declaring is what caught these: maple t -> n is IMPOSSIBLE. Adjacency is evaluated per level, and maple pins t to level 0, n to level 1. Declaring it would have added six permanently unsatisfiable fails; the 0% seed-time rate was a hard impossibility, not search difficulty. maple's ground floor has six bathrooms and one sleeping room (Clinic Room x1) -- a ground-floor WC in a communal building is public, so Brand does not apply anyway. health-centre has no dedicated WC. The ruling was that a treatment room "may give access to a toilet, but this would be a dedicated toilet"; t9 is a Public WC and t10 a Staff WC. Earning the credit needs a WC added to the brief -- programme authoring, filed as homemaker-py-5nw. Both declarations are reachable (best of 8 seeds 2/3 harbor, 2/2 maple), so the search gets a gradient not a permanent penalty. evolved-3M-nols-3 84 -> 89 fails, all five the new requirement. Cost: cpsat assignment ~7.5x slower on harbor (0.28 -> 2.11s per seed); greedy, the default, unchanged at 0.06s. Ordinary runs pay nothing, but 39.5's cpsat-vs-greedy verdict was measured on a cheaper problem than the corpus now poses -- filed as homemaker-py-vjd. Two tests were over-fitted to the old seeds and are repaired to assert their intent, not relaxed to pass: reassign now sweeps six constructive seeds (seed 0's better-seeded design legitimately has nothing to improve, 5 of 6 others fire), and repair_circulation asserts that repair strictly helps plus a >=85% bar rather than a sampled 100% hardened into a guarantee (measured 25% -> 92%, stable over 6 and 12 seeds). Closes homemaker-py-3qj. Lint at parity (46); tests 379 passed, 0 failed. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01MJ84Feep79Hhm3E4zZJmnB
2026-08-29 10:57:44 +00:00
assert on_ok / on_tot >= 0.85, (
f"repair reconnected only {on_ok}/{on_tot} storeys "
f"({100 * on_ok / on_tot:.0f}%), against ~92% expected")
§39.10: preserving constructed connectivity is NULL — and it reframes §39.9 §39.9 named the upstream fix: keep circulation connected DURING the resize rather than rebuilding it after. Built and measured. It does not help, and the reason matters more than the lever. Both halves of the re-cut do damage, in different proportions per programme. Freezing rotations and letting only ratios move (% levels connected, 12 seeds): harbor 100 -> 71 -> 50, health-centre 100 -> 8 -> 8, maple 100 -> 92 -> 67. So health-centre is destroyed entirely by the ratio and maple mostly by the rotation; a fix must be able to give back either. operators._size_divisions_preserving_circulation snapshots every cut, resizes, then reverts the cuts on the tree path between each circulation pair the resize broke -- programme fully intact, no retyping, only geometry given back. It works on connectivity (harbor 50->92%, maple 67->97%, health-centre 8->17%) and costs area accuracy: constructed-seed fails harbor 96.6->141.5, maple 141.8->175.8, size fails roughly double. (A greedy single-cut revert barely moved -- it stalls where no ONE revert helps though two would. Targeting the broken pairs is what made connectivity work.) The obvious defence -- raw constructed seeds understate it, the resize is only a warm start, the inner loop should recover -- was TESTED AND FAILS. Full search, harbor-house, 12000 evals, seed 1: OFF 43 fails, 9 hard, 3 connectivity ON 65 fails, 26 hard, 4 connectivity Worse on every axis, including connectivity itself. REFRAMING: §39.9's fact stands (the resize destroys 41 of 49 circulation edges) but is NOT ACTIONABLE, because construction-time connectivity does not determine final connectivity. The search discards and rebuilds the seeder's circulation either way, and constraining the seed only spends area quality the search cannot recover. Together with §39.8 (not an incentive problem) that retires the framing this thread inherited from §38: connectivity is neither a construction problem nor an incentive one. Both flags (repair_circulation, preserve_circulation) stay default off with the numbers recorded, plus byte-identical-default tests. Do not revisit either without a new formulation -- the standing this document gives bubble.py. 356 passed (+1 new), same 7 pre-existing fixture failures, lint unchanged. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01MJ84Feep79Hhm3E4zZJmnB
2026-08-26 15:11:46 +00:00
@pytest.mark.skipif(not HARBOR.is_dir(), reason="harbor-house not available")
def test_preserve_circulation_default_off_reproduces_prior_seeds():
"""§39.10 measured NULL, so the default must stay byte-identical."""
from homemaker_layout import geometry, programme
reqs = programme.load_programme_dir(str(HARBOR))
types = sorted(reqs) + ["C", "O"]
seed = dom.load(str(HARBOR / "init.dom"))
kw = dict(min_storeys=programme.storey_minimum(str(HARBOR)),
adjacency_aware=True, proportion_aware=True, circ_divisor=3)
def sig(**extra):
geometry.clear_cache()
root = operators.constructive_topology(
seed, reqs, np.random.default_rng(5), types, **kw, **extra)
geometry.clear_cache()
return tuple((lf.type, round(geometry.area(lf), 6))
for lvl in dom.levels(root) for lf in lvl.leaves())
assert sig() == sig(preserve_circulation=False)
# ...and it does change something when enabled, or the A/B measured nothing
assert sig() != sig(preserve_circulation=True)