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Adds a committed integration test driving the full API path — raw gov-EPC response → from_api_response → cert_to_inputs → calculate_sap_from_inputs — across all 1000 certs in the in-repo RdSAP-21.0.1 corpus, and pins the aggregate accuracy of our continuous SAP (plus CO2 and primary energy) against each cert's lodged figures. Mirrors scripts/eval_api_sap_accuracy.py but runs in CI off the committed corpus (~2s, no /tmp sample needed). Scoped to RdSAP-21.0.1 — the SAP 10.2-era schema whose lodged rating uses the same methodology we compute (a fair target). Pre-SAP10 schemas (17.x-20.0.0) lodge SAP 2012 ratings and are out of scope (guarded for mapping only by test_mapper_corpus.py). Current: SAP within-0.5 = 65.0%, MAE = 1.174 (tight floor/ceiling — the optimised gauge). CO2 MAE = 0.27 t/yr (bias +0.17) and PE MAE = 14.6 kWh/m2/yr (bias +8.9) are reported + loosely guarded: cost is well-calibrated but CO2/PE both run ~+5-10% high (uniform across fuels — a systematic CO2/PE-factor or scope gap, not yet investigated). Thresholds ratchet as slices tighten each metric. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> |
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| .. | ||
| chatgpt | ||
| epc_client | ||
| magic_plan | ||
| postgres | ||
| solar | ||
| __init__.py | ||
| conftest.py | ||
| test_address2uprn_queue_client.py | ||
| test_csv_s3_client.py | ||
| test_s3_client.py | ||
| test_s3_uri.py | ||
| test_sqs_client.py | ||