Two-pass org_ref-matched builder for property_overrides (classify via ChatGPT
into the landlord ledger, validate+apply user edits, write idempotently);
ephemeral-Postgres smoke proves the one-property chain without creds.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Caught live writing property_overrides on portfolio 796: the Python
override_component SAEnum lagged the DB enum, so reading a new-component row
back threw LookupError. Guard it with a consistency test.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The FE-owned `material.type` pgEnum cannot carry `secondary_heating_removal`,
so pricing it through the DB catalogue raises a DataError that poisons the
session — the modelling pipeline crashed on any property with a lodged
secondary heater unless the measure was excluded on the Scenario.
Realise the `ProductRepository` docstring's intent (DB catalogue today, a JSON
file for costs the ETL does not yet supply, behind the same port): add a
`CompositeProductRepository` that resolves an override source first, then the
catalogue. Checking the override first keeps that Measure Type away from the DB
entirely; every other type misses the override and falls through unchanged.
- off_catalogue_costs.json prices it at £270 flat per-dwelling — the legacy
`Costs.heater_removal` ported to the new flat model (ADR-0028):
(£25 + £200 baseline) x 1.2 VAT, for the single fixed secondary a cert lodges.
Contingency (0.25) is joined from config, not the file.
- Wire the composite into PostgresUnitOfWork.product and run_modelling_e2e, so
the first-run pipeline and the local runner both honour the overlay.
- Integration test: drop the unrealistic seeded secondary_heating_removal DB
rows (the pgEnum can't hold the type) and assert it is JSON-sourced
(material_id is None, cost £270) end-to-end through a real Unit of Work.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
An uninsulated stone wall of lodged thickness, age bands A-E, is billed by
the RdSAP 10 §5.6 Table-12 formula on its measured thickness — sandstone /
limestone U = 54.876·W^-0.561, granite / whinstone U = 45.315·W^-0.513. Two
bugs suppressed it:
1. CAP: the as-built branch capped the formula result at the Table-6
typical-thickness default (`if u0 >= 1.7: return 1.7`). But the formula
only dips below 1.7 past ~488 mm (sandstone) / ~640 mm (granite), so the
cap nullified §5.6 for essentially every real-thickness stone wall,
under-counting fabric loss and over-rating. A measured 400 mm sandstone
age-B wall is 1.90 (Elmhurst-confirmed), not 1.70.
2. NO INSULATION-STATE GATE: the branch fired for any stone wall with a
lodged thickness, including ones whose insulation is "Unknown". RdSAP
treats an unknown-insulation wall via the Table-6 typical-thickness
default, NOT as bare stone of the lodged thickness — so a 50 mm granite
wall with Unknown insulation must read 1.70 (worksheet), not the formula's
6.09. Gated on `wall_insulation_type is not None`.
Fixes the 2 long-standing stone-U unit tests (granite 120 mm → 3.8871,
sandstone 120 mm → 3.7408 — they were correct red tests, not "known fails").
Corpus within-0.5 70.3% -> 71.6% (MAE 0.833 -> 0.822); ratcheted floors to
0.71 / 0.83. Worksheet fixture 000565 (granite 50 mm Unknown → 1.70) still
passes via the insulation gate. The two stone groups (sandstone/limestone vs
granite/whinstone) keep their distinct §5.6 coefficients.
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 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>
