10 modelling_e2e properties failed with "unmapped SAP code in fuel_code: 10":
the billing layer (`sap_code_to_fuel`) had no carrier for Table-32 code 10
(dual fuel, mineral + wood) and raised rather than guess one.
SAP 10.2 treats dual fuel as its OWN fuel (its own Table-12 factors), so model
it as its own billing carrier rather than collapsing onto wood or coal:
- New `Fuel.DUAL_FUEL_MINERAL_AND_WOOD`.
- `_CODE_TO_FUEL[10]` -> that carrier.
- Fuel Rates snapshot prices it at 7.69 p/kWh — the midpoint of the COAL proxy
(7.13) and WOOD_LOGS (8.25). This mirrors SAP's own construction: Table-32
dual fuel (3.99) ~= midpoint of house coal (3.67) and wood logs (4.23).
Marked `derived` with a documented _note/_gap/_assumption (like the COAL and
HEAT_NETWORK proxies), since there is no retail blend price.
A dedicated carrier + rate (vs a one-line map to an existing carrier) keeps the
fuel identity faithful to SAP and avoids mispricing dual fuel as pure wood/coal.
Tests: code 10 -> DUAL_FUEL carrier; snapshot prices it at 7.69; grid-export
codes (36/60) still raise (the genuine no-carrier case).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Fitting sealed glazing units changes two things beyond the pane's U/g
that the cascade reads, which the overlay didn't model — leaving the
double/secondary before→after pins ~0.7 SAP short (xfail):
1. Draught-proofing (RdSAP 10 §8.1). Sealed units draught-proof the panes
they replace, re-lodging the dwelling-level `percent_draughtproofed`
(cert 001431: 84 → 100). The §2 cascade reads that dwelling-level
value, so the overlay now carries it. `_recompute_percent_draughtproofed`
anchors on the lodged before-% — `after = round((round(before%/100 × N)
+ flips) / N × 100)`, N = openable windows (vertical + roof) + doors,
flips = upgraded panes that were not draught-proofed — so it's robust
to incomplete window extraction (unchanged openings are already in the
aggregate). ~0.3 SAP.
2. Frame factor (§6 solar gains). A replacement unit re-lodges its own
FF=0.70, overriding the pane it replaced — the two "single glazing,
known data" panes lodge FF 1.00 / 0.50 (one is 6.6 m²), so leaving them
unchanged understated solar gains by ~+150 kWh space heating. `WindowOverlay`
now carries `frame_factor`, written flat onto the window. ~0.4 SAP.
Wiring: `EpcSimulation.percent_draughtproofed` + `WindowOverlay.frame_factor`
new fields; `apply_simulations` / `_fold_window` write them; the glazing
generator computes both from the upgraded set and cert 001431's after.
Un-xfails `test_{double,secondary}_glazing_overlay_reproduces_the_relodged_after`
— both now pin SAP/CO2/PE to the relodged after within tolerance. Updates
the two `test_glazing_recommendation` overlay expectations for the new
`frame_factor`. 96 modelling tests pass; zero new pyright errors.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
A Landlord Override's building_part is a positional index (0=main, 1=extension
1…, ADR-0004), but the gov-API EPC can label that slot differently (e.g. lodge
the 2nd part as 'other', not 'extension_1'). The previous fix skipped such
orphaned overrides, silently discarding the landlord's correction. Now the
override falls back onto the EPC's part at that position (via _resolve_part), so
the correction lands; only a position the EPC models no part at is skipped
(no geometry to model a wholly-absent part). Replaces the skip-only behaviour.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Corpus validation of the modelling_e2e photovoltaic_supply-as-list fix. Cert
6102-6227-8000-0083-2292 (RdSAP-20.0.0 semi, gas combi + 2× 1.14 kW PV arrays)
crashed from_rdsap_schema_20_0_0 on the measured-array list; the fix routes it
through the dict-tolerant _map_schema_21_pv. PV correctly credited: engine 61
(no PV) → 66 (+5). Built in Elmhurst (evidence: epc.json + summary + worksheet,
fabric+heating; the PV "New Technologies" Panel-details grid deferred): worksheet
55 = engine-on-Elmhurst-inputs 55 exactly → calculator faithful. The +6 engine-vs-
Elmhurst base-dwelling residual is the documented RdSAP-default gap (band-C cavity-
uninsulated suspended-floor semi). Pinned engine 66.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Corpus validation of the modelling_e2e built_form fix. Cert 8742-6624-9300-2780-4926
(SAP-Schema-16.0, ground-floor electric-storage-heater flat) omits built_form; the
mapper now derives it from dwelling_type. built_form is ML-only so the fix is
SAP-neutral: engine 66 = lodged 66 exactly. Built in Elmhurst (evidence: epc.json +
summary + worksheet): worksheet 54, engine-on-Elmhurst-inputs 53 ≈ 54 → calculator
faithful. The +12 engine-vs-Elmhurst is a build/input gap (cert size-1 small cylinder
unrepresentable in Elmhurst's Normal/110L-minimum entry → higher HW + reduced-field
16.0 defaults). Pinned engine 66.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Table 5 reads "Number of extract fans if known; if number is unknown:
[age-band default]" — the default is an UNKNOWN-fallback, NOT a floor. The
cascade applied `max(lodged, table_5_default)`, flooring a genuinely-lodged
count up to the age-band minimum: e.g. an age H-M dwelling lodging 2 extract
fans was billed at the 6-8-room default of 3, over-counting ventilation line
(8) and the heat-loss coefficient. Fixed to `lodged if lodged > 0 else
default` (a lodged 0 is the Elmhurst/RdSAP "unknown" form → default; any
positive count is taken literally).
Surfaced by Khalim's Elmhurst stress worksheet (simulated case 46): this was
its last ventilation residual — our Jan effective ACH 9.14 -> 9.0748 (exact
match to the accredited worksheet), SAP 29 -> 30 = Elmhurst, cost £1496 vs
£1493. Corpus IMPROVED: within-0.5 71.6% -> 72.5%, MAE 0.819 -> 0.815 (the
max-flooring over-counted ventilation on every cert lodging fans below its
age default). Floor ratcheted 0.71 -> 0.72. pyright not installed locally.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
When the main heating system does not heat every habitable room (heated rooms
< habitable rooms), SAP 10.2 Appendix A.2.2 assumes the unheated rooms are
served by a portable-electric secondary heater, so the Table 11 secondary
fraction (0.10 for a boiler main) must be costed at the electricity tariff —
even when the cert lodges no explicit secondary system.
`_secondary_fraction` previously returned 0 unless a secondary was lodged or
the main was a forced-secondary electric-storage code, dropping the assumed
secondary and billing 100% of space heat to the (cheaper) main fuel — an
over-rate. Added an `unheated_habitable_rooms` trigger plus
`_has_unheated_habitable_rooms(epc)`, which prefers the lodged
`any_unheated_rooms` flag and guards the gov-API `heated_rooms_count == 0`
"not provided" sentinel. The secondary fuel/efficiency cascade already
defaults to portable electric (code 693) when no secondary code is lodged.
Worksheet-validated on simulated case 46 (heated 4 < habitable 7, no lodged
secondary): the assumed 10% electric secondary (2289 kWh, ~£260) lifted our
SAP 39 -> 29.35 vs accredited Elmhurst 30 (cost £1502 vs £1493, within 0.6%).
Corpus UNCHANGED (71.6% / MAE 0.819): all 17 corpus certs with heated <
habitable already lodge an explicit secondary description, so the gov-API
path was already costing it; this only adds the assumed secondary where none
is lodged (Elmhurst / reduced-field path). pyright not installed locally.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The SAP rating is spec-floored at 1 ("if the result of the calculation is
less than 1, the rating is 1"). `sap_rating_integer` already clamps, but the
continuous `sap_score_continuous` did not — so a degenerate dwelling could
emit a physically impossible negative SAP. Apply the same max(1, …) floor to
the continuous value (the un-rounded part is for sensitivity near real
ratings, not for negative ratings).
Removes a -12.3 accuracy outlier on the committed corpus (cert 422000111926,
lodged at the floor of 1, was computing -11.3): within-0.5 70.2% -> 70.3%,
MAE 0.845 -> 0.833. Ratcheted the corpus MAE ceiling to 0.84. Unit-pinned in
test_calculator.
pyright not installed in this codespace (strict gate not run locally).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The gov-API lodges secondary fuel as an enum whose value can COLLIDE with a
different same-valued RdSAP 10 Table 32 / SAP 10.2 Table 12 fuel code:
- enum 9 = "dual fuel (mineral and wood)" vs Table code 9 = LPG SC11F
- enum 5 = "anthracite" vs Table code 5 = LPG (bulk)
The main-fuel boundary already canonicalises these (`_GOV_API_COLLISION_
FUELS`), but the SECONDARY-heating cost + CO2/PE paths never did — they took
the bare same-value lookup, so a dual-fuel room heater was priced as LPG
(3.48 vs dual-fuel 3.99 p/kWh) and emitted as LPG (CO2 0.241 vs 0.087),
and an anthracite secondary as bulk LPG (12.19 vs 3.64 p/kWh). The price
under-count over-rates SAP; the CO2 over-count inflates emissions.
Fix: add enum 9 to `_GOV_API_COLLISION_FUELS` (5 and 33 were already there)
and canonicalise the secondary fuel code on both the cost
(`_secondary_fuel_cost_gbp_per_kwh`) and factor (`_secondary_fuel_code`)
paths, mirroring the main-fuel boundary. canonical_fuel_code only touches
{5,9,33}, so genuinely Table-coded secondaries (House coal 11, wood logs 20,
community fuels 30-32) are left unchanged — confirmed by a full-map audit.
Corpus: within-0.5 69.7% -> 70.2% (MAE 0.854 -> 0.845; dual-fuel-secondary
cohort 42.9% -> 49.0%, signed +0.55 -> +0.41) and CO2 MAE 0.12 -> 0.08 t/yr
(bias +0.04 -> 0.00). Ratcheted the corpus floors (within 0.70, MAE 0.85,
CO2 0.09, PE 4.0). A prior session deferred enum 9 ("direction not
understood") while the EPC PE/CO2 lens was confounded by the climate-cascade
bug (fc7c4d2d); on the corrected lens the over-rate direction is clear.
pyright not installed in this codespace (strict gate not run locally).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The SAP/EI rating is computed on UK-average weather (Appendix U Tables
U1-U3 region 0) so ratings are nationally comparable, but Appendix U
paragraph 1 (PDF p.124) requires that "other calculations (such as for
energy use and costs on EPCs) are done using local weather. Weather data
for each postcode district are taken from the PCDB". `Sap10Calculator.
calculate` ran ONE cascade (UK-average) and fed it to SAP, CO2 AND primary
energy, so every cert's EPC-displayed CO2/PE were computed on the wrong
climate. Because most of England is warmer than the UK-average, this
systematically OVER-counted heating demand on the emissions/PE outputs.
The two cascades (`cert_to_inputs` rating, `cert_to_demand_inputs`
postcode) already existed; this wires the demand cascade into the
production entry point and grafts its CO2/PE onto the rating result (SAP
unchanged). The corpus gauge's longstanding +5% CO2/PE over-estimate was
mostly this climate bug, NOT (as previously diagnosed) per-cert mapper
fidelity:
CO2 MAE 0.26 -> 0.12 t/yr (bias +0.18 -> +0.04)
PE MAE 13.6 -> 3.8 kWh/m2 (bias +9.0 -> +0.24)
SAP within-0.5 = 69.7% (rating cascade, unchanged)
Worksheet-validated to 1e-4 on simulated case 45 (heat-pump ground-floor
flat, postcode W6): the P960 prints the current dwelling twice — Block 1
on UK-average weather (SAP 60.5318, CO2 692.13) and Block 2 on postcode
weather (CO2 626.78, PE 6581.59). Both reproduce exactly. Added a tracked
case-45 Summary fixture + two-cascade cascade pin as a permanent guard,
and ratcheted the corpus CO2/PE ceilings to 0.13 / 4.2. The e2e Elmhurst
suite (Block-1 line refs) now pins the rating cascade directly; the two
Vaillant overlay snapshots refreshed to demand-cascade CO2/PE.
pyright not installed in this codespace (strict gate not run locally);
change is type-trivial (dataclasses.replace over SapResult).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
