Khalim Conn-Kowlessar 31ced27162 feat(modelling): surface the full candidate measure menu with per-measure cost ... The run only showed the measures the Optimiser selected, so a candidate it passed over (e.g. an ASHP it found too costly for the target band) and that measure's cost were invisible. Add `harness.console.candidate_recommendations` — every Generator Option with its per-Option cost, before optimisation — and have run_modelling_e2e print the full menu per property (flagging the selected Options), write a "cost per measure" section into the markdown, and emit a per-Option modelling_e2e_candidates.csv. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>		2026-06-16 15:03:26 +00:00
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__init__.py	feat(modelling): sense-check table for a Plan in the DB-less harness	2026-06-04 08:06:53 +00:00
test_cohort.py	feat(modelling): turnkey offline cohort script (tables + CSV)	2026-06-04 09:30:53 +00:00
test_console.py	feat(modelling): surface the full candidate measure menu with per-measure cost	2026-06-16 15:03:26 +00:00
test_epc_bulk.py	feat(modelling): read the gov EPC bulk export via HTTP range requests	2026-06-04 12:16:18 +00:00
test_epc_prediction_corpus.py	feat(epc-prediction): thread coordinates onto Comparable + target (#1227)	2026-06-15 14:46:01 +00:00
test_plan_table.py	refactor(modelling): type measure_type fields as MeasureType	2026-06-08 20:13:31 +00:00
test_report.py	test(harness): re-pin golden-cert plans to the gain-maximising packages	2026-06-15 13:57:27 +00:00