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Reduced-field window U: heat_transmission derived the synthesised-window raw U from u_window(all None) -> the 2.5 placeholder regardless of glazing. Now routes the (uniform) glazing_type code through u_window (RdSAP Table 24) so e.g. double pre-2002 reads 2.8, not 2.5. Only the pre-SAP10 reduced-field path is affected (21.0.1 certs carry per-window U upstream) — the RdSAP-21.0.1 corpus gauge is unchanged at 66.9% within-0.5. test_real_cert_sap_accuracy: pin uprn_10002468137 (RdSAP-17.1, all-electric storage heaters) at SAP 61, validated against Elmhurst on identical inputs (dual off-peak immersion, 110 L cylinder, 2 baths). Our engine reproduces Elmhurst's fuel cost to the penny; lodged 55 is the old SAP-2012 schema. Tooling to grow the accuracy corpus: - scripts/fetch_real_life_epc_sample.py — capture a cert by UPRN into the corpus. - scripts/compare_epc_paths.py — diff gov-API vs Elmhurst-summary EpcPropertyData and run both through the engine, localising mapper vs calculator differences. - skill validate-cert-sap-accuracy — the end-to-end loop (capture -> Elmhurst inputs -> human builds -> compare -> reconcile -> pin in the test). - skill epc-to-elmhurst-rdsap-inputs reference: corrected immersion (code 1=dual), cylinder size (code 2 = Normal/110 L), and bath-count (WWHRS sub-tab) mappings. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> |
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| .. | ||
| __init__.py | ||
| appendix_h_solar.py | ||
| dimensions.py | ||
| energy_requirements.py | ||
| fabric_energy_efficiency.py | ||
| fuel_cost.py | ||
| heat_transmission.py | ||
| internal_gains.py | ||
| mean_internal_temperature.py | ||
| mev.py | ||
| photovoltaic.py | ||
| rating.py | ||
| solar_gains.py | ||
| space_cooling.py | ||
| space_heating.py | ||
| utilisation_factor.py | ||
| ventilation.py | ||
| water_heating.py | ||