"""Characterisation of the FE-facing portfolio aggregation
(`aggregate_portfolio_recommendations`): it sums a Scenario's **default**
Recommendations and writes the totals onto the Scenario row.

This pins the `recommendation.plan_id` linkage the m2m retirement introduced
(ADR-0017 amendment): the aggregation joins Recommendation → Plan on
`recommendation.plan_id`, so only measures carrying the right `plan_id` (and
`default = True`) are summed.
"""

from __future__ import annotations

from sqlmodel import Session

from backend.app.db.functions.portfolio_functions import (
    aggregate_portfolio_recommendations,
)
from backend.app.db.models.recommendations import (
    PlanModel,
    Recommendation,
    ScenarioModel,
)
from domain.modelling.portfolio_goal import PortfolioGoal
from tests.utilities.floats import assert_float_matches


def _rec(
    *, plan_id: int, default: bool, cost: float, kwh: float, gbp: float, co2: float
) -> Recommendation:
    return Recommendation(
        property_id=10,
        plan_id=plan_id,
        type="cavity_wall_insulation",
        measure_type="cavity_wall_insulation",
        description="Cavity wall insulation",
        estimated_cost=cost,
        kwh_savings=kwh,
        energy_cost_savings=gbp,
        co2_equivalent_savings=co2,
        total_work_hours=4.0,
        default=default,
        already_installed=False,
    )


def test_aggregation_sums_default_measures_linked_by_plan_id(
    db_session: Session,
) -> None:
    # Arrange — one Scenario + Plan, two default measures (summed) plus a
    # non-default one (excluded), all linked by recommendation.plan_id.
    db_session.add(
        ScenarioModel(
            id=7,
            portfolio_id=1,
            goal=PortfolioGoal.INCREASING_EPC,
            goal_value="C",
            is_default=True,
        )
    )
    db_session.add(
        PlanModel(id=100, portfolio_id=1, property_id=10, scenario_id=7, is_default=True)
    )
    db_session.add_all(
        [
            _rec(plan_id=100, default=True, cost=1000.0, kwh=500.0, gbp=120.0, co2=0.5),
            _rec(plan_id=100, default=True, cost=500.0, kwh=300.0, gbp=80.0, co2=0.2),
            # excluded: not default
            _rec(plan_id=100, default=False, cost=9.0, kwh=9.0, gbp=9.0, co2=9.0),
        ]
    )
    db_session.commit()

    # Act
    aggregate_portfolio_recommendations(
        db_session,
        portfolio_id=1,
        scenario_id=7,
        total_valuation_increase=2500.0,
        labour_days=3.0,
        aggregated_data={},
    )
    db_session.commit()

    # Assert — the default measures' sums land on the Scenario row
    scenario = db_session.query(ScenarioModel).filter_by(id=7).one()
    assert scenario.cost is not None
    assert_float_matches(scenario.cost, 1500.0)  # 1000 + 500
    assert scenario.energy_savings is not None
    assert_float_matches(scenario.energy_savings, 800.0)  # Σ kwh_savings
    assert scenario.energy_cost_savings is not None
    assert_float_matches(scenario.energy_cost_savings, 200.0)  # 120 + 80
    assert scenario.co2_equivalent_savings is not None
    assert_float_matches(scenario.co2_equivalent_savings, 0.7)  # 0.5 + 0.2
    assert scenario.total_work_hours is not None
    assert_float_matches(scenario.total_work_hours, 8.0)  # 4 + 4
    assert scenario.property_valuation_increase == 2500.0
    assert scenario.labour_days == 3.0