Model/tests/domain/modelling/test_scoring.py
Khalim Conn-Kowlessar 9ef97be958 refactor(modelling): type measure_type fields as MeasureType
Tighten the recommendation/plan vocabulary off generic str:
MeasureOption.measure_type and PlanMeasure.measure_type are now MeasureType
(also _GlazingTarget.measure_type, MeasureDependency.triggers ->
frozenset[MeasureType], and the optimiser's chosen/required-type locals).
Because MeasureType is a StrEnum the change is transparent to persistence
(the `recommendation` varchar column), the optimiser group-by key, and every
`== "solar_pv"`-style comparison — so pyright now enforces the enum at every
construction site with no runtime behaviour change.

The catalogue boundary stays str: ProductRepository.get(measure_type: str)
and Product.measure_type are unchanged (they map arbitrary DB/JSON rows), so
the fake product repos in tests need no edit. Test construction helpers coerce
their str arg via MeasureType(...); direct constructions use members.

Suite green: tests/domain/modelling + orchestration + harness 253 pass + 3
xfail; pyright clean on production + tests (pre-existing moto + property-
override-rowcount baselines untouched).

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-08 20:13:31 +00:00

185 lines
5.8 KiB
Python

"""Behaviour of per-measure scoring: the telescoping marginal cascade that
serves both the per-Option optimiser signal (role 1) and the final-package
display attribution (role 3) — ADR-0016. Exercises the real calculator on a
hand-built EPD; no PDF/parser involved.
"""
from typing import Sequence
from datatypes.epc.domain.epc_property_data import (
BuildingPartIdentifier,
EpcPropertyData,
)
from domain.modelling.measure_type import MeasureType
from domain.modelling.scoring.package_scorer import PackageScorer, Score
from domain.modelling.recommendation import MeasureOption
from domain.modelling.scoring.scoring import (
MeasureImpact,
cascade_scores,
independent_option_impacts,
marginal_impacts,
marginals_from_scores,
)
from domain.modelling.simulation import BuildingPartOverlay, EpcSimulation
from domain.sap10_calculator.calculator import Sap10Calculator
from tests.domain.sap10_calculator.worksheet._elmhurst_worksheet_000490 import (
build_epc,
)
_MAIN_CAVITY = EpcSimulation(
building_parts={
BuildingPartIdentifier.MAIN: BuildingPartOverlay(wall_insulation_type=2)
}
)
_EXT1_CAVITY = EpcSimulation(
building_parts={
BuildingPartIdentifier.EXTENSION_1: BuildingPartOverlay(wall_insulation_type=2)
}
)
class _CountingScorer(PackageScorer):
"""A PackageScorer stand-in that counts score() calls; the score is a
deterministic function of the overlays so distinct overlays differ."""
def __init__(self) -> None:
self.calls = 0
def score(
self, baseline: EpcPropertyData, simulations: Sequence[EpcSimulation]
) -> Score:
self.calls += 1
total = 0.0
for sim in simulations:
for overlay in sim.building_parts.values():
total += overlay.wall_insulation_type or 0
return Score(
sap_continuous=total, co2_kg_per_yr=0.0, primary_energy_kwh_per_yr=0.0
)
def _option(overlay: EpcSimulation) -> MeasureOption:
return MeasureOption(
measure_type=MeasureType.CAVITY_WALL_INSULATION, description="opt", overlay=overlay
)
def test_independent_option_impacts_score_each_distinct_overlay_once() -> None:
# Arrange
baseline: EpcPropertyData = build_epc()
scorer = _CountingScorer()
overlay_a = EpcSimulation(
building_parts={
BuildingPartIdentifier.MAIN: BuildingPartOverlay(wall_insulation_type=2)
}
)
overlay_a_dup = EpcSimulation(
building_parts={
BuildingPartIdentifier.MAIN: BuildingPartOverlay(wall_insulation_type=2)
}
)
overlay_b = EpcSimulation(
building_parts={
BuildingPartIdentifier.MAIN: BuildingPartOverlay(wall_insulation_type=3)
}
)
options = [_option(overlay_a), _option(overlay_a_dup), _option(overlay_b)]
# Act
impacts: list[MeasureImpact] = independent_option_impacts(
scorer, baseline, options
)
# Assert
# baseline scored once + one score per DISTINCT overlay (a, b) = 3, not 4
assert scorer.calls == 3
assert impacts[0].sap_points == impacts[1].sap_points == 2.0
assert impacts[2].sap_points == 3.0
def test_single_overlay_marginal_is_its_improvement_over_baseline() -> None:
# Arrange
baseline: EpcPropertyData = build_epc()
scorer = PackageScorer(Sap10Calculator())
base: Score = scorer.score(baseline, [])
filled: Score = scorer.score(baseline, [_MAIN_CAVITY])
# Act
impacts: list[MeasureImpact] = marginal_impacts(scorer, baseline, [_MAIN_CAVITY])
# Assert
assert len(impacts) == 1
assert impacts[0].sap_points > 0 # cavity fill improves SAP
assert (
abs(impacts[0].sap_points - (filled.sap_continuous - base.sap_continuous))
<= 1e-9
)
def test_cascade_scores_returns_the_baseline_plus_one_score_per_prefix() -> None:
# Arrange
baseline: EpcPropertyData = build_epc()
scorer = _CountingScorer()
overlays = [_MAIN_CAVITY, _EXT1_CAVITY]
# Act
scores: list[Score] = cascade_scores(scorer, baseline, overlays)
# Assert
# baseline (empty prefix) + one score per cumulative prefix
assert len(scores) == 3
assert scorer.calls == 3
assert scores[0].sap_continuous == 0.0 # empty prefix
assert scores[1].sap_continuous == 2.0 # MAIN cavity (type 2)
assert scores[2].sap_continuous == 4.0 # + EXTENSION_1 cavity (type 2)
def test_marginals_from_scores_are_the_consecutive_prefix_deltas() -> None:
# Arrange
baseline: EpcPropertyData = build_epc()
scorer = PackageScorer(Sap10Calculator())
overlays = [_MAIN_CAVITY, _EXT1_CAVITY]
scores: list[Score] = cascade_scores(scorer, baseline, overlays)
# Act
impacts: list[MeasureImpact] = marginals_from_scores(scores)
# Assert — each marginal is the delta over the previous prefix score
assert len(impacts) == 2
assert (
abs(impacts[0].sap_points - (scores[1].sap_continuous - scores[0].sap_continuous))
<= 1e-9
)
assert (
abs(impacts[1].sap_points - (scores[2].sap_continuous - scores[1].sap_continuous))
<= 1e-9
)
def test_marginals_telescope_to_the_whole_package_total() -> None:
# Arrange
baseline: EpcPropertyData = build_epc()
scorer = PackageScorer(Sap10Calculator())
overlays = [_MAIN_CAVITY, _EXT1_CAVITY]
base: Score = scorer.score(baseline, [])
full: Score = scorer.score(baseline, overlays)
# Act
impacts: list[MeasureImpact] = marginal_impacts(scorer, baseline, overlays)
# Assert
assert len(impacts) == 2
assert (
abs(
sum(i.sap_points for i in impacts)
- (full.sap_continuous - base.sap_continuous)
)
<= 1e-9
)
assert (
abs(
sum(i.energy_savings_kwh_per_yr for i in impacts)
- (base.primary_energy_kwh_per_yr - full.primary_energy_kwh_per_yr)
)
<= 1e-6
)