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1424e2110e
`test_pashub_sap_accuracy_wythenshawe` graded against the manifest `pre_sap` (`hubspot_deal_data.pre_sap`) — surveyor hand-entered and frequently wrong, which floated a misleading 79% / MAE 0.75. Grade instead against the DB PasHub-assessment SAP (`epc_property_energy_performance.energy_rating_current`, `ep.source='lodged'`), matched by UPRN or postcode+house-number. `scripts/enrich_pashub_wythenshawe_oracle.py` resolves each fixture's oracle SAP once (DB required, not run in CI) and bakes `oracle_sap` / `oracle_match` into `manifest.json`, so the harness stays DB-free. 148/168 resolve (39 UPRN + 109 address); the 20 unmatched carry `oracle_sap` null and are excluded from the aggregate until PasHub sources their SAP. With the six from_site_notes fixes, the 148 matched score within-0.5 89.2% (132/148), MAE 0.297 (was, vs pre_sap, 79.2% / 0.754). Ratchets re-baselined 0.75→0.88 floor, 0.85→0.31 ceiling. The residual tail is the integer-oracle rounding floor (spec-correct dwellings) plus a couple of spec-literal gaps, not engine defects. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
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| .. | ||
| fixtures | ||
| __init__.py | ||
| test_elmhurst_end_to_end.py | ||
| test_elmhurst_extractor.py | ||
| test_end_to_end.py | ||
| test_extractor.py | ||
| test_heating_systems_corpus.py | ||
| test_pashub_sap_accuracy.py | ||
| test_pashub_sap_accuracy_lrha_wave3.py | ||
| test_pashub_sap_accuracy_wythenshawe.py | ||
| test_pdf.py | ||
| test_room_heater_worksheet_001431.py | ||
| test_summary_pdf_mapper_chain.py | ||