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recommend_heating joins the free candidate pool in _candidate_recommendations; the HHR storage bundle reaches the optimised package for an electric/off-gas dwelling. Catalogue + contingency (legacy 0.10) gain high_heat_retention_storage_heaters; report.py _triggers_for explains the heating trigger (electric/off-gas main); the harness _GENERATOR_MEASURE_TYPES forcing test covers it. ASHP + boiler bundles still to come. ADR-0024. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
33 lines
1.1 KiB
Python
33 lines
1.1 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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}
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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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