Model/tests/orchestration/test_modelling_goal_objectives.py

"""The ModellingOrchestrator aligns the Optimiser's objective with the
Scenario's goal (ADR-0062): Reducing CO2 emissions maximises the carbon
reduction the budget buys, Energy Savings maximises the annual bill saving,
and Increasing EPC keeps its SAP target semantics. End-to-end through
``run_modelling`` (no database) with the real calculator, against the
uninsulated solid-brick 001431 dwelling where the SAP-optimal and
carbon-optimal packages diverge at a £16,000 budget.
"""

from __future__ import annotations

import dataclasses

import pytest

from datatypes.epc.domain.epc_property_data import EpcPropertyData
from domain.fuel_rates.fuel import Fuel
from domain.fuel_rates.fuel_rates import FuelRate, FuelRates
from domain.modelling.measure_type import MeasureType
from domain.modelling.plan import Plan
from domain.modelling.scenario import Scenario
from harness.console import run_modelling
from repositories.fuel_rates.fuel_rates_repository import FuelRatesRepository
from repositories.fuel_rates.fuel_rates_static_file_repository import (
    FuelRatesStaticFileRepository,
)
from tests.domain.modelling._elmhurst_recommendation import (
    parse_recommendation_summary,
)


def _solid_brick_dwelling() -> EpcPropertyData:
    return parse_recommendation_summary("solid_brick_ewi_001431_before.pdf")


def _scenario(goal: str, *, budget: float) -> Scenario:
    return Scenario(
        id=999, goal=goal, goal_value="", budget=budget, is_default=True
    )


def test_reducing_co2_scenario_buys_carbon_not_sap() -> None:
    # Arrange — at £16,000 the SAP objective buys the wall + floor + £3,200
    # gas boiler package (~2,069 kg CO2/yr, SAP 72.9). The carbon objective
    # swaps the boiler for electric storage heaters (~1,098 kg/yr) — a lower
    # SAP, but ~970 kg/yr less carbon on the low-carbon grid.
    epc = _solid_brick_dwelling()

    # Act — the same dwelling and budget under each goal.
    sap_led: Plan = run_modelling(
        epc,
        scenario=_scenario("Valuation Improvement", budget=16000.0),
        print_table=False,
    )
    carbon_led: Plan = run_modelling(
        epc,
        scenario=_scenario("Reducing CO2 emissions", budget=16000.0),
        print_table=False,
    )

    # Assert — the goal changes the outcome in the goal's favour: the carbon
    # plan cuts materially more CO2 than the SAP plan buys with the same
    # money, and the gas boiler that wins on SAP-per-£ is rejected.
    assert (
        carbon_led.post_retrofit.co2_kg_per_yr
        < sap_led.post_retrofit.co2_kg_per_yr - 500.0
    )
    selected = {measure.measure_type for measure in carbon_led.measures}
    assert MeasureType.GAS_BOILER_UPGRADE not in selected


def test_a_goal_aligned_scenario_without_a_budget_fails_loudly() -> None:
    # Arrange — 'reduce as much as possible within this budget' is undefined
    # without a budget: unconstrained it would recommend every beneficial
    # measure. A budget-less goal-aligned Scenario is a misconfiguration and
    # must fail visibly, not produce a maximal plan.
    epc = _solid_brick_dwelling()
    budgetless = Scenario(
        id=999,
        goal="Reducing CO2 emissions",
        goal_value="",
        budget=None,
        is_default=True,
    )

    # Act / Assert
    with pytest.raises(ValueError, match="budget"):
        run_modelling(epc, scenario=budgetless, print_table=False)


class _FixedFuelRates(FuelRatesRepository):
    def __init__(self, rates: FuelRates) -> None:
        self._rates = rates

    def get_current(self) -> FuelRates:
        return self._rates


def _cheap_electricity_snapshot() -> FuelRates:
    """The committed snapshot with electricity at 1p/kWh — a world where any
    electric heating out-bills gas, while SAP's internal price book (which the
    calculator rates against) is unmoved."""
    base = FuelRatesStaticFileRepository().get_current()
    rates = dict(base.rates)
    rates[Fuel.ELECTRICITY] = FuelRate(
        unit_rate_p_per_kwh=1.0,
        standing_charge_p_per_day=rates[Fuel.ELECTRICITY].standing_charge_p_per_day,
    )
    return dataclasses.replace(base, rates=rates)


def test_energy_savings_scenario_prices_packages_at_the_live_fuel_rates() -> None:
    # Arrange — SAP is itself a cost metric, but it prices energy from its
    # internal tariff book. The Energy Savings goal must price at the *live*
    # Fuel Rates snapshot: with 1p/kWh electricity, electric heating slashes
    # the bill even though SAP still scores the gas boiler package higher.
    epc = _solid_brick_dwelling()

    # Act
    plan: Plan = run_modelling(
        epc,
        scenario=_scenario("Energy Savings", budget=16000.0),
        fuel_rates=_FixedFuelRates(_cheap_electricity_snapshot()),
        print_table=False,
    )

    # Assert — the bill objective abandons the boiler for electric heating.
    selected = {measure.measure_type for measure in plan.measures}
    assert MeasureType.GAS_BOILER_UPGRADE not in selected
    assert selected & {
        MeasureType.AIR_SOURCE_HEAT_PUMP,
        MeasureType.HIGH_HEAT_RETENTION_STORAGE_HEATERS,
    }