Measurement honesty so we optimise SAP-relevant accuracy, not SAP-neutral
misses (ADR-0030 Component Accuracy):
- Add construction_age_band_pm1: an exact-or-adjacent-band hit. Adjacent
RdSAP age bands carry near-identical U-values, so an off-by-one is
~SAP-neutral. Full corpus: exact 78.5% but ±1-band 91.7% (fixture
63.9% -> 83.3%) — most age misses are adjacent.
- Drop window_count from the gate's residual ceilings (cosmetic): the
predicted picture clusters at a mapper-default 4 windows vs actuals 1-21,
but total_window_area (the SAP-relevant signal) stays tight at ~3.4 m2.
Gate: + construction_age_band_pm1 floor 0.8333; window_count no longer gated.
Closes#1222
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Investigated recency-weighting (weight cohort votes by an exponential decay
in cert age). Key finding: it must be SELECTIVE. On the validation corpus it
HURTS permanent categoricals (wall 91.2->89.5, age 78.5->75.7 — discards
still-valid data) but clearly HELPS time-varying ones, where a recent
neighbour reflects the current physical state:
roof_insulation_thickness 56.7 -> 60.7% corpus (+4pp)
29.4 -> 41.2% fixture (+12pp)
So apply a recency-weighted mode only to roof_insulation_thickness (loft
top-ups happen over time); keep the plain mode for permanent categoricals.
tau = 4yr (~2.8yr half-life); falls back to plain mode when no registration
dates are lodged. Gate floor ratcheted 0.2941 -> 0.4118.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
These independent fabric categoricals were template-copied; mode them like
the construction categoricals. Verified mode beats template before applying.
Big fixture win on roof insulation thickness (doubled), floor insulation
neutral-to-positive:
roof_insulation_thickness 14.7% -> 29.4% (gate floor ratcheted up)
floor_insulation 90.6% (unchanged on the fixture)
Glazing type was tried too (+1.6pp on the 40-postcode corpus) but REGRESSED
the 36-target fixture (0.50 -> 0.44) — the gate caught it. Glazing moding is
marginal/noisy, so it's left on the template; revisit with a larger corpus.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
"One scorer, two harnesses" (ADR-0030): the committed gate, the local script,
and the future battle-test must run the *same* scoring. Extract it:
- domain/epc_prediction/validation.py — `iter_predictions` (the single
leave-one-out orchestration: latest-per-address hold-out, SAP-10.2 target
filter, all-vintage source) + `evaluate_component_accuracy` (calculator-free
ComponentAccuracy aggregation, the primary signal). Unit-tested.
- harness/epc_prediction_corpus.py — `load_corpus(dir)` IO: corpus dir ->
Comparable cohorts (maps payloads, carries address + registration_date).
validate_epc_prediction.py now just loads + calls the scorer for the component
section and iterates iter_predictions for the calculator-floored end-to-end.
Identical numbers (181 targets, SAP MAE 6.34) — behaviour-preserving.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Heating is the dominant SAP lever (ablating it to actual cut the SAP error
~7 -> ~4.5) yet was entirely unscored. Add the heating group to
compare_prediction's categorical_hits: main fuel / category / control (off
the primary MainHeatingDetail), water-heating fuel / code, has-cylinder,
cylinder insulation, secondary heating (off SapHeating).
Template-copied baseline on the 40-postcode corpus (no predictor change
yet — this just makes the signal visible):
heating_main_fuel 93.4%
heating_main_category 92.7%
water_heating_fuel/code 91.7% / 92.4%
heating_main_control 62.1% <- weak
has_hot_water_cylinder 78.5%
cylinder_insulation_type 35.8% (n=120) <- weak
secondary_heating_type 16.8% (n=125) <- weak
Fuel/category predict well from the template; controls, cylinder, and
secondary heating are poor and now drive the next predictor slices.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
ADR-0030 commits Component Accuracy to ~19 categorical components (5 today
+ 8 heating + glazing/renewables). Flat *_correct dataclass fields don't
scale — each needs manual runner wiring. Collapse them into a single
`categorical_hits: dict[str, Optional[bool]]` keyed by component name, which
also matches the runner's name-keyed aggregation (now generic: it tallies
whatever components the comparison reports). No behaviour change; the
classification rates are identical (wall n 578->575 is the 3 certs whose
actual wall is None, now correctly counted as not-applicable via _classify).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The register lists every historical lodgement, so a postcode cohort
contains the same physical address many times (LS61AA: 15 certs / 11
addresses; NG71AA: 15 / 9 — "FLAT 3" appears 3x in each). Two
consequences:
- Production: a re-lodged neighbour was counting up to 3x towards the
cohort mode. select_comparables now dedupes candidates to the latest
cert per address (one comparable per real neighbour) — Comparable
gains address + registration_date (the register metadata its docstring
already anticipated, read straight off the cached payload).
- Validation: leave-one-out leaked — predicting a flat from a near-
identical re-lodgement of itself. The harness now holds out a whole
address (excludes every sibling cert) and evaluates on the latest cert
per address (the best ground truth).
Removing the leak gives the honest numbers (19 distinct addresses):
wall_construction 93.1% -> 89.5%
construction_age_band 65.5% -> 52.6%
roof_construction 79.3% -> 68.4%
floor_area mean|.| 37.9 -> 52.6 m2
The earlier figures were inflated by self-leakage; these are the real
accuracy to beat.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Only main wall_construction was set to the cohort mode; the other
homogeneous categoricals (wall insulation, construction age band, roof
construction, floor construction) were left as template-copied, so one
median-size template's quirks set them. Apply the same cohort-mode
mechanism to all of them per ADR-0029 decision 4 — the template still
supplies geometry, only the categorical codes move to the mode.
Verified mode beats (or ties) template-copy per categorical before
applying. Smoke corpus (29 leave-one-out) classification rates:
construction_age_band 55.2% -> 65.5%
roof_construction 72.4% -> 79.3%
floor_construction 46.2% -> 84.6%
wall_insulation_type 93.1% (tie — already template-strong)
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The comparison only scored main wall_construction; everything else the
predictor produces (by template-copy) went unmeasured. Extend
compare_prediction to the rest of the ADR-0029 homogeneous categoricals —
wall insulation type, construction age band, roof construction, floor
construction — and aggregate per-categorical classification rates in the
runner. A categorical hit is "not applicable" (None, excluded from the
denominator) when the actual lodges no value, so absent-roof flats don't
score free wins.
Smoke corpus (29 leave-one-out, all but wall are template-copied today):
wall_construction 93.1%
wall_insulation_type 93.1%
construction_age_band 55.2% <- loud; candidate for cohort-mode
roof_construction 72.4%
floor_construction 46.2% (n=13)
These numbers drive the next slice (extend cohort-mode coverage).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Template (the comparable whose structure/geometry is copied wholesale)
was members[0] — an arbitrary draw from the API search order. With floor
area varying widely within a property_type cohort (NG71AA houses span
51-340 m2), this made the copied geometry noisy and systematically large.
Pick the member whose floor area is closest to the cohort median instead,
implementing ADR-0029 decision 4's unimplemented "closest on size"
criterion while keeping the structure coherent (it is still one real
property, so floor dims / windows / parts stay internally consistent for
the calculator).
Smoke corpus (29 leave-one-out predictions):
floor_area mean|.| 68.0 -> 37.9 m2 (bias +46.8 -> -3.9)
window_area mean|.| 11.1 -> 7.3 m2
parts mean|.| 1.00 -> 0.38
SAP |pred-calc - calc(actual)| MAE 7.19 -> 4.86
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Pure compare_prediction (TDD): wall-construction classification hit + signed
residuals on floor area, window count, total window area, building-parts count.
Plus validate_epc_prediction.py (IO plumbing): drops each cert from its postcode
cohort, predicts from the rest on guaranteed inputs only, aggregates the metrics,
and reports SAP three ways (pred-calc vs lodged / vs calc-on-actual / vs the
neighbour-mean baseline). Smoke run: wall 90.9%, floor-area mean|·| 42.6 m2 (a
real signal — template-copied floor area is noisy), SAP pred-calc edges baseline.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
predict() copies a representative template comparable's structure (coherent for
the calculator), overrides the homogeneous categorical with the cohort mode
(robust to an atypical template), then applies known Landlord Overrides on top
(a known value wins over the estimate). Proven on wall construction; roof/floor/
insulation/age extend on the same mode+override mechanism, driven next by the
validation harness metrics.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Pure-domain select_comparables: property type is an always-hard filter; built
form and known Landlord Overrides (e.g. solid brick) are conditioning filters on
the filter-then-relax ladder — applied while >= minimum_cohort survive, relaxed
otherwise (the mixed-street border case degrades gracefully). PredictionTarget
(known inputs) + Comparable (epc + register metadata) + ComparableProperties
(selected cohort). Weighting (recency x similarity) follows in the synthesis slice.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Flat per-dwelling decommission price (sample_catalogue \£250) + 0.25 contingency
(covers unknown heater count / hard-wired-vs-plugged / repaint extent). The JSON
repo joins the contingency from config, proven by the new repo test. No composite
Products machinery — a lodged secondary is one roughly-fixed job, not room-scaled.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
recommend_secondary_heating_removal offers one standalone Option that clears the
lodged secondary system. Eligibility is purely physical (offer iff
sap_heating.secondary_heating_type is set) — no effectiveness gate, since a
lodged secondary is a fixed emitter per RdSAP (portables are ignored), and the
electric-storage §A.2.2 no-op is the Optimiser's call (ADR-0028 decisions 1-2).
Priced at a flat per-dwelling decommission cost, not room-scaled.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The first overlay surface that sets fields to *absent* rather than to a
target state: _fold_secondary_heating clears sap_heating.secondary_heating_type
+ secondary_fuel_type, so the calculator's Table 11 secondary-fraction split
(SAP 10.2 §9a) routes 100% of space heating to the main. On an electric-storage
main RdSAP §A.2.2 re-forces a default secondary, making removal a no-op there —
left to the Optimiser to de-select (ADR-0028 decisions 2-3).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Don't offer a like-for-like gas boiler swap to a dwelling whose existing gas
boiler is already at least as efficient as the new condensing boiler (SAP 10.2
Table 4b codes 102/104 = 84% winter) — it gains nothing, and the dwelling gets
the tune-up (cylinder + controls) instead. `_already_condensing` compares the
existing code's Table 4b winter efficiency to 84%; a non-Table-4b code (solid
fuel) has no comparable efficiency and is never treated as already-condensing.
The gate is GAS-ONLY: a non-gas boiler → gas is a fuel switch whose value (cost
/ carbon) is not captured by winter efficiency, so oil/LPG/coal → gas is never
suppressed on efficiency grounds (only gated on the mains-gas connection).
This correctly demotes the gas-with-cylinder example (cert lodges code 114
"Regular, condensing", 84% winter) to a tune-up case — confirming that 114→102
is ~0 boiler-efficiency gain in both our calc and Elmhurst (both Table 4b 84%);
Elmhurst's uplift there came from the cylinder + flue, not the boiler. The
boiler-with-cylinder overlay stays validated by the lpg pin (code 115, non-
condensing + cylinder) and by recasting the 114 fixtures' code to a pre-1998
non-condensing boiler (110) in the boiler tests — the overlay overwrites the
code to 102 regardless, so only eligibility changes, not the delta-0 result.
New tests: an already-condensing gas boiler yields no boiler upgrade (but a
tune-up); an oil condensing boiler is not gated (the fuel switch survives).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Replace the flat placeholder scalars (boiler £3000; tune-up £500/£900) with a
per-dwelling composite cost, mirroring the ASHP architecture (ADR-0025): a
`HeatingRates` table (data, `heating_rates.json`), typed `BoilerCostInputs` /
`TuneUpCostInputs`, pure `Products.boiler_bundle_cost` / `tune_up_cost`, and
modelling-layer interpreters that read the dwelling into those inputs.
The cost mirrors the Simulation Overlay component-for-component, sharing the
controls + cylinder pricing across both options:
- tune-up (standard) = standard controls + cylinder fixes
- tune-up (zone) = zone controls + cylinder fixes
- boiler upgrade = £3200 all-in + standard controls (only when the upgrade
fired a controls change) + cylinder fixes
Standard controls are priced INCREMENTALLY — only the parts missing to reach
SAP 2106 (programmer £120 / room thermostat £150 / TRV £35×radiators), read
from a Table 4e Group-1 feature map so a dwelling that already has a room
thermostat + TRVs is only charged the programmer. Zone controls are a full
smart kit (hub £205 + smart TRV £50×radiators) — the smart TRV is itself the
room sensor, so there is no separate per-room sensor line. Cylinder fixes:
jacket £50 (when under-insulated) + thermostat £150 (when absent). The boiler
is a like-for-like wet swap (no radiators/flue/pipework — eligibility already
requires an existing wet boiler), so those dead-code extras are not modelled.
Figures are research-validated 2025/26 UK installed costs (legacy Costs.py
lineage); fully-loaded totals with one contingency on top (Model B, not the
legacy VAT/preliminaries engine). Contingency: boiler 0.26; tune-ups 0.10
(was a 0.15 placeholder). ADR-0027 records the design; CONTEXT.md's Heating
Eligibility entry updated to cover the partial boiler/tune-up family + composed
cost. Products cost pins (delta<=1e-9) + interpreter tests + generator
composite-cost assertions.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Add the system tune-up to the heating Recommendation: keep the existing wet
boiler but install better heating controls and fix the cylinder. Two competing
Options (the Optimiser picks <=1 across the whole heating rec) per the user's
two best control end-states:
- system_tune_up — standard controls (programmer + room thermostat +
TRVs, SAP 10.2 Table 4e code 2106)
- system_tune_up_zoned — time-and-temperature zone control (code 2110, type 3):
more SAP uplift for more cost
Both keep the boiler (no fuel / SAP code / flue change), set the control
ABSOLUTELY to their end-state, and apply the conditional cylinder fixes (an
80 mm jacket when under-insulated, a thermostat when absent — only when a
cylinder exists). Each control option is offered only when it genuinely improves
the existing control — standard is skipped when the control is already 2106 /
2110 / 2112, zone when already 2110 / 2112 — so neither is ever a downgrade or a
no-op.
Validated against the Elmhurst "system tune up" re-lodgements (cert 001431):
nine befores spanning controls 2101-2113 all converge to the two common afters,
proving the control overlay is absolute. The cascade pin is parametrised over
two starting controls (2101 "no control" + 2113 "room thermostat and TRVs") x
both afters, delta 0 (SAP/CO2/PE).
Wires the two MeasureTypes through contingencies (0.15), the offline catalogue
(500 / 900), the catalogue-coverage list, the report triggers, and the ARA
first-run seed.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Pin the coal-boiler-with-cylinder upgrade and add the `boiler_flue_type`
end-state field. A solid-fuel (coal) boiler (fuel 11, SAP code 153) on a
mains-gas street converts to a gas condensing boiler (fuel 11->26, code 102) —
the non-gas->gas path for a solid-fuel system, eligible because code 153 is in
the wet-boiler solid-fuel range 151-161 and mains gas is present.
New `boiler_flue_type` HeatingOverlay field, routed to main_heating_details[0]
and set to 2 (room-sealed/balanced) on both boiler shapes: every relodged after
lodges flue type 2, but coal's before lodged none. The field is SAP-inert (the
cascade score is unchanged by it), so it is written purely for end-state
fidelity — the overlay now represents the installed condensing boiler's flue.
Validated via the overlay-equality unit tests.
The coal after predates the user-locked "always add a cylinder thermostat when
absent" rule, so it stale-lodged thermostat 'N'; the pin corrects it to the
rule's end-state 'Y' in-test (the gas with-cylinder after got the same
correction by re-lodging). The cylinder is already 80 mm insulated, so the
jacket is skipped and only the thermostat is added; controls (2106) are
unchanged. Cascade-pinned delta 0 (SAP/CO2/PE).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Extend the gas-boiler-upgrade Option to combi (no-cylinder) dwellings and add
the controls upgrade shared by both boiler shapes. A dwelling has a cylinder or
it does not, so the one `gas_boiler_upgrade` Option is shaped per dwelling:
- no cylinder -> a gas condensing combi (Table 4b code 104), no cylinder fields
touched;
- a cylinder -> a regular boiler (code 102) heating it, with the conditional
cylinder jacket/thermostat (slice 1).
Controls: bring an inadequate boiler control up to full programmer + room
thermostat + TRVs (SAP 10.2 Table 4e Group 1 code 2106). "Inadequate" = the
Group-1 codes with NO room thermostat (2101, 2102, 2107, 2108, 2109, 2111) —
these lack boiler interlock (Table 4c(2) / footnote c) p.171), so adding a room
thermostat genuinely improves SAP. Room-thermostatted (2103/2104/2105/2106/2113)
or better zone controls (2110/2112) are left unchanged — never downgraded, so
no phantom uplift. The with-cylinder cert (control 2106) is therefore untouched
and its pin still holds at delta 0.
Validated by the combi before/after re-lodgement (cert 001431, gas boiler
upgrade - no cylinder): control 2111 "TRVs and bypass" -> 2106, fan flue
False->True, SAP code 112 -> 104. Cascade-pinned delta 0 (SAP/CO2/PE). Removed
the slice-1 placeholder test asserting no boiler Option fires without a cylinder
(the combi Option now correctly fires there).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Add the first boiler-upgrade option to the single "Heating & Hot Water"
Recommendation (ADR-0024 expansion): a dwelling whose existing wet boiler heats
a hot-water cylinder is offered a new gas condensing boiler, with the cylinder
jacketed when under-insulated and given a thermostat when absent. One competing
Option (the Optimiser picks <=1), folded into one composite Plan line.
The end-state is read from the Elmhurst before/after re-lodgements (cert 001431,
gas boiler upgrade - with cylinder), which REVISE ADR-0024:
- Target is always a gas condensing boiler, not fuel-preserving: every after
lodges fuel 26. Gas->gas always; a non-gas wet boiler ->gas only with a
mains-gas connection; electric boilers are left alone (electrification is the
upgrade path). Eligibility = wet-boiler SAP code (Table 4a/4b 101-141 /
151-161 / 191-196) + not an electric boiler + mains gas present.
- End-state is a Table 4b SAP code, not a PCDB index: code 102 (regular boiler
+ cylinder). The calculator derives the condensing seasonal efficiency from
the code, so no efficiency input exists or is needed.
- A modern condensing boiler has a fanned flue: the after flips
`fan_flue_present` False->True on every cert (SAP 10.2 Table 4f flue-fan +
the Table 4b condensing-efficiency basis). Added as a new HeatingOverlay
field, routed to main_heating_details[0].
- Cylinder thermostat is always added when absent (user-locked); the jacket is
the 80 mm `cylinder_insulation_type=2` end-state, applied only when the
cylinder is below 80 mm (never downgrading a better one). Both are conditional
per-dwelling components, not a frozen overlay.
Cascade-pinned delta-0 (SAP/CO2/PE) against the relodged after via
`_assert_overlay_reproduces_after`. NB the absolute SAP on this dwelling is
subject to a separate Summary-path mapper roof-fidelity gap (we read the roof
better-insulated than Elmhurst, scoring ~75 vs the printed 56); the gap is
identical on before+after (the boiler measure never touches the roof) so it
cancels and the pin still proves the exact heating field-delta. Tracked on the
calculator branch.
Wires the new `gas_boiler_upgrade` MeasureType through contingencies (0.26),
the offline sample catalogue, the catalogue-coverage list, and the ARA
first-run integration seed (the option fires on any mains-gas boiler+cylinder
dwelling).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Add domain/modelling/considered_measures.py::restrict_to_considered_measures —
the pure allowlist that limits a run to a chosen set of MeasureType (mirroring
the legacy engine's `inclusions`). It filters at the Option level, so a
multi-option Recommendation (e.g. Heating & Hot Water competing HHRSH against
an ASHP bundle) is kept with only its allowed Options; a Recommendation left
with none is dropped. None = consider everything (unrestricted default).
Thread `considered_measures: frozenset[MeasureType] | None` through
ModellingOrchestrator.run -> _plan_for -> _scored_candidate_groups /
_candidate_recommendations (applies the filter) and _measure_dependencies
(suppresses a forced dependency whose required measure is outside the
allowlist, so a restricted run forces nothing it is not considering). The
local-run seam (harness.console.run_modelling) gains the same param.
The Optimiser still freely chooses among survivors — including none. Tests:
the pure filter (3 cases) + an orchestrator-seam test proving a
{solar_pv}-restricted run yields only solar_pv options. 257 pass + 3 xfail;
pyright clean.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Tighten the recommendation/plan vocabulary off generic str:
MeasureOption.measure_type and PlanMeasure.measure_type are now MeasureType
(also _GlazingTarget.measure_type, MeasureDependency.triggers ->
frozenset[MeasureType], and the optimiser's chosen/required-type locals).
Because MeasureType is a StrEnum the change is transparent to persistence
(the `recommendation` varchar column), the optimiser group-by key, and every
`== "solar_pv"`-style comparison — so pyright now enforces the enum at every
construction site with no runtime behaviour change.
The catalogue boundary stays str: ProductRepository.get(measure_type: str)
and Product.measure_type are unchanged (they map arbitrary DB/JSON rows), so
the fake product repos in tests need no edit. Test construction helpers coerce
their str arg via MeasureType(...); direct constructions use members.
Suite green: tests/domain/modelling + orchestration + harness 253 pass + 3
xfail; pyright clean on production + tests (pre-existing moto + property-
override-rowcount baselines untouched).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Introduce domain/modelling/measure_type.py — a StrEnum with one member per
modelled measure (the 15 the generators emit). A StrEnum so each member *is*
its string value: it persists straight into the `recommendation` varchar
column, is the optimiser's group-by key, and compares equal to the catalogue /
EPC strings — so it replaces the per-generator string constants with no
persistence or optimiser change.
Repoint every generator's measure-type constant/literal to a MeasureType
member (wall, solid_wall, roof, floor, glazing, lighting, ventilation,
heating, solar). Field annotations stay `str` for now; tightening them to
MeasureType is the next slice.
This is the enum the historical engine deferred (engine.py:970
"TODO - formalise property measure types into an enum") and the vocabulary the
forthcoming `considered_measures` allowlist will speak (mirroring the legacy
`inclusions`).
Suite green: tests/domain/modelling + orchestration + harness 253 pass + 3
xfail; pyright clean on the enum + generators.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Pulls in 42 commits of calculator/mapper accuracy fixes from the per-cert
mapper-validation and floor/roof/heating fronts.
Conflict resolutions:
- mapper `_is_elmhurst_roof_window`: main dropped the branch's "wall location →
vertical" guard (it broke cert 000516's rooflight), but that re-broke cert
001431's two External-wall U>3.0 windows (which must stay vertical). The two
certs lodge a BYTE-IDENTICAL §11 row, so neither location nor U separates
them — the real discriminator is the room-in-roof context. Replaced the
unconditional U>3.0 backstop with one gated on the BP having a room-in-roof
(`_elmhurst_bp_has_room_in_roof`): 000516's Main BP has a "Room in roof type
1" (→ rooflight), 001431's does not (→ vertical). Validated against BOTH —
full Elmhurst worksheet suite 1038 pass + the 001431 window-extraction pin.
- property_postgres_repository: kept main's `ids_by_uprn` method + the branch's
`_restrictions_of` helper.
- sap_fuel.py: the branch relocated it to domain/billing/ (already carrying
main's to_table_32_code normalization), so kept the old path deleted.
Fallout from main's fabric fixes (validated by the boiler-3 real-cert pin which
still reproduces at delta 0):
- re-pinned the boiler-1 + boiler-instant-hw ASHP snapshot scores;
- main's §14.2 gas-boiler main-fuel derivation resolved the BGB/102 baseline
gap, so `test_gas_boiler_instant_hw_before_baselines` is now a passing test
(was an xfail tripwire).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Slice 6 of the Solar PV Recommendation Generator (ADR-0026). `recommend_solar`
emits one "Solar PV" Recommendation of up to five conservatively-sized configs
× {no battery, battery} = ≤10 competing Options (a free Optimiser candidate).
Each Option folds a SolarOverlay built from the chosen config: one
PhotovoltaicArray per non-north segment (peak_power = panels × panelCapacityW /
1000; orientation/pitch from geometry; generation-calibrated overshading),
is_dwelling_export_capable set True absolutely, a diverter when the dwelling
has a cylinder (None for a combi), a 5 kWh battery for the battery variant, and
the per-config composite cost from Products.solar_bundle_cost.
Eligibility = house/bungalow ∧ not listed/heritage (blocks_internal, the same
gate as ASHP — a conservation area does NOT block PV) ∧ no existing PV ∧ a
feasible SolarPotential. Flats and existing-PV top-up are deferred.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Slice 7 of the Solar PV Recommendation Generator (ADR-0026). Adds the
composite per-dwelling Solar PV cost on the Products collection (ADR-0025
pattern): pv_system(kWp band, nearest of the ECOPV06-13 EA bands 1.0→4.5 kWp,
floor/cap at the ends) + scaffolding(£900 first elevation + £450 each
additional, default 2) + enabling base (EICR £150 + DNO £50 + 2-way consumer
unit £330) + [diverter £980 if cylinder] + [battery if the with-battery
variant] → Cost(total, contingency_rate 0.15).
Rates are data in the committed solar_rates.json (Southern Housing "SOLAR PV &
BATTERY" EA column), loaded via SolarRates.from_json/.default and injectable.
The £2,000 / 5 kWh battery is NOT on the rate sheet — a flagged estimate
(battery_estimate=true), confirmed with the user to stand in until a DB rate.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Slice 5 of the Solar PV Recommendation Generator (ADR-0026). Adds the flat
`SolarOverlay` and `_fold_solar`, the sixth Simulation Overlay surface: like
the ventilation/lighting overlays it targets no building part and folds its
fields onto `sap_energy_source` (home of the SAP Appendix M PV inputs) —
photovoltaic_arrays (absolute target, one PhotovoltaicArray per non-north
segment, replacing the dwelling's existing arrays), pv_diverter_present,
pv_connection, is_dwelling_export_capable (set True absolutely), pv_batteries.
Omitted fields leave the baseline unchanged (combi → no diverter); the
baseline is never mutated.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Slice 4 of the Solar PV Recommendation Generator (ADR-0026).
`select_conservative_configs` turns Google's full solarPanelConfigs ladder
into up to five competing array configs for the Optimiser: drop north-facing
planes (within 30° of due north, wrap-aware), cap usable panels at ~70% of
maxArrayPanelsCount (imagery misses obstructions; MCS edge setback), collapse
rungs that trim to the same usable size keeping the higher-generation layout,
then sample five spanning min→max by expected generation. Returns () when
nothing usable remains.
Real London example → 5 rungs at 4/12/19/26/34 panels (all ≤34.3 = 70% of
49); synthetic cases pin the north-drop and the 70% cap.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Slice 3 of the Solar PV Recommendation Generator (ADR-0026). Per roof segment,
back-solve the effective overshading factor ZPV from Google's expected
generation against SAP's own unshaded annual output:
ZPV = (yearlyEnergyDcKwh × 0.955) / (0.8 × kWp × S)
reusing the calculator's Appendix U3.3 annual solar radiation S via a new
public seam `pv_annual_solar_radiation_kwh_per_m2`. Dividing Google's
generation by SAP's S cancels orientation/tilt and isolates shading; the
result snaps to the RdSAP bucket {1:1.0, 2:0.8, 3:0.5, 4:0.35} via the
ADR-0026 midpoint cutpoints (≥0.90→1, 0.65–0.90→2, 0.425–0.65→3, <0.425→4;
ZPV>1→1). The real London example's planes all back-solve to ZPV>1 → code 1.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Slice 2 of the Solar PV Recommendation Generator (ADR-0026). Adds the
strictly-typed `SolarPotential` domain projection over the raw Google Solar
`buildingInsights` JSON that Ingestion persists (SolarRepository): the
`solarPanelConfigs` ladder, each rung broken into its roof segments with
Google's continuous azimuth/tilt mapped to the SAP octant
(`azimuth_to_sap_octant`, 0°=N clockwise → 1=N..8=NW, matching the
calculator's ORIENTATION_BY_SAP10_CODE) and RdSAP §11.1 pitch code
(`pitch_to_sap_code`, snap to {0→1,30→2,45→3,60→4,90→5}).
Pinned against the real London buildingInsights example (mirrored into
fixtures from the user-provided RTF): 400 W panels, maxArrayPanelsCount 49,
46-rung ladder, per-segment SE/NW/NE/SW octants at ~32° → pitch code 2.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The API `floor_heat_loss` code is authoritative — confirmed by joining each
single-BP cert's code to its independent `floors[].description` (which the
gov register publishes alongside the code):
code 1 ↔ "To external air" (exposed, 9/9)
code 2 ↔ "To unheated space" (semi-exposed, 6/6)
code 3 ↔ "(other premises below)" (partially htd, 9/9)
code 6 ↔ "(another dwelling below)" (party, 176/176)
code 7 ↔ "Solid"/"Suspended …" (ground, all)
Code 3 was mis-mapped to "To unheated space" (semi-exposed) and, on
mid-/top-floor flats, had its floor area zeroed entirely by the
dwelling-level exposure heuristic. RdSAP 10 §3.12 (PDF p.25) classes a
flat's floor over non-domestic "other premises … heated, but at different
times" as "above a partially heated space" → the §5.14 (PDF p.47) constant
U=0.7 W/m²K — distinct from semi-exposed (Table 20) and party (no loss).
Fix: the mapper sets `is_above_partially_heated_space` on the floor=0
dimension for code 3 (string → "(other premises below)" for fidelity), and
the heat-transmission step lets that per-BP lodgement override the flat
suppression upward (mirroring the existing exposed / "another dwelling
below" overrides). The cascade already routes is_above_partial → U=0.7.
Re-pins golden cert 7536-3827: its Ext2 (bp3) lodges code 3, but the cert's
lossy `floors[]` summary dropped that description, so a prior agent guessed
"code 3 = ground" (U=1.12) and concluded the residual was an irreducible
"register-rounding" artifact. It was this bug: Ext2 floor U 1.12 → 0.70,
PE -6.1952 → -5.6414, CO2 -0.1639 → -0.1492 (both toward 0), SAP unchanged.
Eval: 909 computed, 45.1% → 45.3% within 0.5, mean|err| 1.702 → 1.659,
<1.0 59.5% → 60.2%. 13 code-3 certs improve (0380 +3.71 → -0.63, 0350
+7.82 → +0.83, 2610 +7.47 → -1.29); the few that overshoot were already
failing and carry independent fabric bugs (9763's walls = 8 W/K for 60 m²).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
A mid-/top-floor flat whose lowest floor is lodged as an exposed floor
(API floor_heat_loss=1) had its floor area zeroed by the dwelling-level
exposure heuristic, which keys only on the flat label and defaults
has_exposed_floor=False (assuming the floor sits over another *heated*
dwelling). RdSAP 10 §3.12 (PDF p.25) is explicit:
"Otherwise the floor area of the flat ... is:
- an exposed floor if there is an open space below"
i.e. a flat cantilevered over a passageway IS a heat-loss floor on
Table 20. The per-BP `is_exposed_floor` lodgement is authoritative and
now overrides the dwelling-level suppression upward, mirroring the
existing "another dwelling below" party override (which suppresses
downward). The code-1↔"E To external air" enum is confirmed by the
paired API+Summary worksheet certs (0350, 3800).
Eval: 45.1% → 45.3% within 0.5 (909 computed); cert 3836 +6.79 → +0.77,
5717 +1.31 → -0.07 and 0997 +0.76 → +0.05 cross into <0.5. Two
already-failing under-rated certs (7636, 2241) shift further — both are
dominated by independent cost-side over-counts the exposed floor merely
unmasks (7636 walls = 8.98 W/K for 33.87 m² is the real defect).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
main_heating_category=9 (warm-air systems, NOT heat pump) had no entry
in _SECONDARY_HEATING_FRACTION_BY_CATEGORY, so a warm-air main with a
lodged secondary raised UnmappedSapCode in
_secondary_heating_fraction_for_category — the last calc_raise in the
API sample (cert 0380-2197-2590-2996-2715: warm air mains gas code 506 +
electric room-heater secondary).
SAP 10.2 Table 11 (p.188): a gas/oil warm-air unit falls under "All gas,
liquid and solid fuel systems" (0.10), and electric warm air under
"Other electric systems" (also 0.10) — so 0.10 regardless of fuel. The
warm-air efficiency (Table 4a code→eff: 506→0.70) and Table 4f fan
energy were already wired; this was the only missing dispatch entry.
0380 now computes: SAP 78.1 vs lodged 77 (+1.1; the residual is per-cert
fabric/PV, not the warm-air dispatch — a faithful 0380 worksheet isn't
available, sim case 28 diverges at SAP 57 / code 502 / condensing unit).
Eval: zero raises remain, computed 908→909; mean|err| 1.703→1.702.
Regression green (2448 pass incl. golden 6035 + cohort); pyright
net-zero (44=44).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The gov EPC API field wall_insulation_thermal_conductivity is OUTPUT
metadata in the openly-published EPC, not an input to the RdSAP10 tool
(Elmhurst) that produced it — its wall entry is Type + Insulation +
thickness only, with no conductivity field. So the RdSAP10 reduced-data
method always uses the SAP 10.2 §5.8 (p.41) default λ=0.04 W/m·K,
whatever code the register lodged.
`_resolve_wall_insulation_lambda_w_per_mk` previously mapped only code 1
(→0.04) and RAISED on others, blocking cert 2090-6909-8060-5201-6401
(code 3 on an internally-insulated 360mm solid-brick wall) with
calc_raise:ValueError. Now it returns the §5.8 default for any code.
Validated: 2090 computes to SAP 73.97 vs lodged 74 (err -0.03); λ of
0.04 / 0.03 / 0.025 all round to 74, and Elmhurst exposes no conductivity
input, so 0.04 is the spec-faithful RdSAP10 value. Eval computed
905→906; mean|err| 1.708→1.706. Regression green (only the 2 pre-existing
stone-wall U failures); pyright net-zero (69=69).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
