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d58ac60d29
Introduce domain/modelling/measure_type.py — a StrEnum with one member per modelled measure (the 15 the generators emit). A StrEnum so each member *is* its string value: it persists straight into the `recommendation` varchar column, is the optimiser's group-by key, and compares equal to the catalogue / EPC strings — so it replaces the per-generator string constants with no persistence or optimiser change. Repoint every generator's measure-type constant/literal to a MeasureType member (wall, solid_wall, roof, floor, glazing, lighting, ventilation, heating, solar). Field annotations stay `str` for now; tightening them to MeasureType is the next slice. This is the enum the historical engine deferred (engine.py:970 "TODO - formalise property measure types into an enum") and the vocabulary the forthcoming `considered_measures` allowlist will speak (mirroring the legacy `inclusions`). Suite green: tests/domain/modelling + orchestration + harness 253 pass + 3 xfail; pyright clean on the enum + generators. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
64 lines
2.7 KiB
Python
64 lines
2.7 KiB
Python
"""The lighting Recommendation Generator (LED upgrade).
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Detects a dwelling's non-LED fixed-lighting bulbs and emits one "Lighting"
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Recommendation whose single Option converts **every** bulb to LED (ADR-0023).
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SAP 10.2 RdSAP §12-1 rates lamp efficacy LED > low-energy-unknown > CFL >
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incandescent, so converting every non-LED type — incandescent, CFL, and the
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"low energy, type unknown" (LEL) bulbs alike — strictly improves the Appendix L
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lighting energy (worksheet line (232)).
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Unlike the fabric generators this is a **whole-dwelling** Measure: its overlay
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writes the four top-level bulb counts directly (`led = total`, the rest 0). It
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is a free Optimiser candidate — an LED upgrade improves SAP at low cost, so the
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Optimiser keeps or leaves it for least-cost-to-target (contrast ventilation's
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forced dependency). Detection + pricing only; impact is produced later by
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scoring (ADR-0016).
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"""
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from typing import Final, Optional
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from datatypes.epc.domain.epc_property_data import EpcPropertyData
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from domain.modelling.measure_type import MeasureType
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from domain.modelling.recommendation import Cost, MeasureOption, Recommendation
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from domain.modelling.simulation import EpcSimulation, LightingOverlay
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from repositories.product.product_repository import ProductRepository
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_LIGHTING_MEASURE_TYPE: Final[MeasureType] = MeasureType.LOW_ENERGY_LIGHTING
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def recommend_lighting(
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epc: EpcPropertyData, products: ProductRepository
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) -> Optional[Recommendation]:
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"""Return a lighting Recommendation upgrading every non-LED bulb to LED — its
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single Option — else None when the dwelling has no non-LED bulbs (already
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all-LED, or no bulb counts lodged)."""
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led: int = epc.led_fixed_lighting_bulbs_count or 0
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cfl: int = epc.cfl_fixed_lighting_bulbs_count or 0
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incandescent: int = epc.incandescent_fixed_lighting_bulbs_count or 0
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low_energy: int = epc.low_energy_fixed_lighting_bulbs_count or 0
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non_led: int = cfl + incandescent + low_energy
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if non_led == 0:
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return None
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product = products.get(_LIGHTING_MEASURE_TYPE)
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overlay = EpcSimulation(
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lighting=LightingOverlay(
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led_fixed_lighting_bulbs_count=led + non_led,
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cfl_fixed_lighting_bulbs_count=0,
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incandescent_fixed_lighting_bulbs_count=0,
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low_energy_fixed_lighting_bulbs_count=0,
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)
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)
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cost = Cost(
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total=non_led * product.unit_cost_per_m2,
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contingency_rate=product.contingency_rate,
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)
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option = MeasureOption(
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measure_type=_LIGHTING_MEASURE_TYPE,
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description="Replace all non-LED bulbs with LED",
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overlay=overlay,
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cost=cost,
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material_id=product.id,
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)
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return Recommendation(surface="Lighting", options=(option,))
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