"""Step 2 tests — the promoted blocking validator + IR (B1). Crafted IR, deterministic.

Determinism is asserted over FIXED inputs (seed 20260624), never through an LLM. The
out-of-range path returns a ``Rejection`` that carries no percentiles, so it can never be
consumed as validated. Pattern: tests/spikes/test_c_validator.py.
"""

import pytest
from pydantic import ValidationError

from portfolio_optimiser.ir import AffectedItem, SavingsProposal
from portfolio_optimiser.reference_domain import load_reference_projects
from portfolio_optimiser.validator import (
    Rejection,
    ValidatedProposal,
    _monte_carlo,
    proposal_for,
    validate_proposal,
)

_ASSUMPTIONS = {"05.2": (200.0, 230.0), "03.1": (290.0, 330.0)}


@pytest.fixture(scope="module")
def project():
    return load_reference_projects()[0]  # FV42-GSV-E1


def _valid(project) -> SavingsProposal:
    # Affected total ~1.48M NOK; 30% feasible cap ~0.44M. Claim 200k is comfortably feasible.
    return proposal_for(
        project, ["05.2", "03.1"], claimed_saving_nok=200_000, assumptions=_ASSUMPTIONS
    )


def _out_of_range(project) -> SavingsProposal:
    # Constructs fine (800k <= 1.48M total) but far exceeds the ~0.44M feasible cap.
    return proposal_for(
        project, ["05.2", "03.1"], claimed_saving_nok=800_000, assumptions=_ASSUMPTIONS
    )


def test_valid_proposal_yields_ordered_percentiles(project) -> None:
    result = validate_proposal(_valid(project))
    assert isinstance(result, ValidatedProposal)
    assert result.p10 <= result.p50 <= result.p90  # P10 <= P50 <= P90
    assert result.nominal_feasible > 0  # the CBC solve produced a feasible bound


def test_out_of_range_is_structurally_blocked(project) -> None:
    result = validate_proposal(_out_of_range(project))
    assert isinstance(result, Rejection)
    assert result.reason  # carries a human-readable reason
    # A Rejection carries no percentiles -> it can never be consumed as validated.
    with pytest.raises(AttributeError):
        _ = result.p50  # type: ignore[attr-defined]


def test_monte_carlo_is_reproducible(project) -> None:
    a = validate_proposal(_valid(project))
    b = validate_proposal(_valid(project))
    assert isinstance(a, ValidatedProposal) and isinstance(b, ValidatedProposal)
    assert (a.p10, a.p50, a.p90) == (b.p10, b.p50, b.p90)


def test_pydantic_blocks_negative_quantity() -> None:
    with pytest.raises(ValidationError):
        SavingsProposal(
            project_id="X",
            measure="bad",
            affected_items=[{"code": "A", "quantity": -1, "unit_cost": 10}],
            claimed_saving_nok=1,
        )


def test_pydantic_blocks_claim_above_affected_total(project) -> None:
    with pytest.raises(ValidationError):
        proposal_for(project, ["05.2"], claimed_saving_nok=99_000_000)


def _above_nominal_within_p90() -> SavingsProposal:
    """Review counterexample #1: affected total 300000 -> nominal feasible 0.30 x 300000 =
    90000, but the band [0.70, 1.40] is skewed UPWARD around unit_cost 1.0, so the Monte
    Carlo P90 sits above it. A claim of 100000 therefore clears the P90 stage while
    exceeding the deterministic bound the CBC solve actually established."""
    return SavingsProposal(
        project_id="BYGG-KONTOR-NORD",
        measure="LED-retrofit av 200 lysrorarmaturer",
        affected_items=[AffectedItem(code="ENERGI-TOTAL-EL", quantity=300_000, unit_cost=1.0)],
        claimed_saving_nok=100_000,
        assumptions={"ENERGI-TOTAL-EL": (0.70, 1.40)},
    )


def test_claim_above_nominal_feasible_is_blocked_though_p90_would_pass() -> None:
    """S2.7 (1): the validator enforces its OWN stage-2 boundary. The nominal block is an
    INDEPENDENT gate — neither stage dominates the other, because an upward-skewed band
    lifts P90 above nominal while a downward-skewed one pushes it below."""
    proposal = _above_nominal_within_p90()
    # Control: without the nominal block this proposal VALIDATES — the P90 stage lets it
    # through. If this assert ever fails, the test below has stopped gating the new stage.
    _, _, p90 = _monte_carlo(proposal)
    assert proposal.claimed_saving_nok <= p90

    result = validate_proposal(proposal)
    assert isinstance(result, Rejection)
    assert "nominal" in result.reason


def test_pydantic_blocks_assumption_band_that_excludes_unit_cost() -> None:
    """S2.7 (2): an assumption band is uncertainty AROUND the item's own unit_cost, so it
    must enclose it. A band of [1.8, 2.2] around unit_cost 1.0 states a different price,
    not an uncertainty — every Monte Carlo sample would then exceed the item's own cost."""
    with pytest.raises(ValidationError):
        SavingsProposal(
            project_id="X",
            measure="band around the wrong centre",
            affected_items=[AffectedItem(code="A", quantity=1000, unit_cost=1.0)],
            claimed_saving_nok=100,
            assumptions={"A": (1.8, 2.2)},
        )


def test_assumption_band_bounds_are_inclusive() -> None:
    """The enclosure is ``low <= unit_cost <= high``: a band that touches the unit_cost at
    either end is a legitimate one-sided uncertainty, not a violation."""
    for band in ((1.0, 1.4), (0.7, 1.0)):
        SavingsProposal(
            project_id="X",
            measure="one-sided uncertainty",
            affected_items=[AffectedItem(code="A", quantity=1000, unit_cost=1.0)],
            claimed_saving_nok=100,
            assumptions={"A": band},
        )