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recommend_heating now receives planning_restrictions in the orchestrator (the ASHP planning gate); the ASHP bundle joins the free candidate pool for every house/bungalow. Catalogue + contingency (legacy 0.25) gain air_source_heat_pump; report.py _triggers_for explains the ASHP trigger; the harness forcing test covers it. Integration tests seed an air_source_heat_pump MaterialRow (ASHP fires on every house, the broadest trigger yet). NB the optimiser correctly does NOT select ASHP for an EPC-band goal — gas->electric does not improve the SAP cost-rating; ASHP is a CO2/PE measure, selectable once non-EPC goals land. ASHP bundle COMPLETE (S5-S7). ADR-0024. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
34 lines
1.2 KiB
Python
34 lines
1.2 KiB
Python
"""Per-Measure-Type contingency rates.
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The one cost component carried separately from a Product's fully-loaded total
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(CONTEXT.md). Mirrors the legacy `recommendations/Costs.py::Costs.CONTINGENCIES`;
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extended as each measure type lands.
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"""
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_CONTINGENCY_RATES: dict[str, float] = {
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"cavity_wall_insulation": 0.10,
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"loft_insulation": 0.10,
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"sloping_ceiling_insulation": 0.10,
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"flat_roof_insulation": 0.10,
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"suspended_floor_insulation": 0.20,
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"solid_floor_insulation": 0.26,
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"mechanical_ventilation": 0.26,
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"external_wall_insulation": 0.26,
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"internal_wall_insulation": 0.26,
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"double_glazing": 0.15,
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"secondary_glazing": 0.15,
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"low_energy_lighting": 0.26,
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"high_heat_retention_storage_heaters": 0.10,
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"air_source_heat_pump": 0.25,
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}
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def contingency_rate(measure_type: str) -> float:
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"""Return the contingency rate for a Measure Type, raising if unknown
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(strict — do not silently default, per the repo's strict-raise convention)."""
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try:
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return _CONTINGENCY_RATES[measure_type]
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except KeyError as exc:
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raise ValueError(
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f"no contingency rate configured for measure type {measure_type!r}"
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) from exc
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