"""Unit tests for the activation qualification predicate (EV-based gate)."""

from __future__ import annotations

from types import SimpleNamespace

from app.services.qualification import (
    best_target_probability,
    expected_value_r,
    primary_target_probability,
    setup_qualifies,
)

# Default gate: expected value is the core test; conviction/conflict/target-prob
# are optional tighteners, off here.
DEFAULT_GATE = {
    "min_expected_value": 0.15,
    "min_rr": 1.2,
    "min_confidence": 55.0,
    "min_target_probability": 0.0,
    "require_high_conviction": False,
    "exclude_conflicts": False,
}

# Strict gate: every optional tightener turned on (the old shipped defaults).
STRICT_GATE = {
    "min_expected_value": 0.0,
    "min_rr": 2.0,
    "min_confidence": 70.0,
    "min_target_probability": 60.0,
    "require_high_conviction": True,
    "exclude_conflicts": True,
}


def _setup(**kwargs):
    base = dict(
        rr_ratio=3.0,
        confidence_score=80.0,
        recommended_action="LONG_HIGH",
        risk_level="Low",
        targets=[{"probability": 50.0, "is_primary": True}],
    )
    base.update(kwargs)
    return SimpleNamespace(**base)


class TestExpectedValue:
    def test_uses_primary_target_not_best(self):
        s = _setup(
            rr_ratio=1.5,
            targets=[
                {"probability": 80.0},
                {"probability": 30.0, "is_primary": True},
            ],
        )
        # EV from the primary (30%): 0.3*1.5 - 0.7 = -0.25
        assert expected_value_r(s) == -0.25
        assert primary_target_probability(s) == 30.0

    def test_falls_back_to_best_when_no_primary_flag(self):
        s = _setup(rr_ratio=2.0, targets=[{"probability": 40.0}, {"probability": 60.0}])
        assert primary_target_probability(s) == 60.0
        # 0.6*2.0 - 0.4 = 0.8
        assert abs(expected_value_r(s) - 0.8) < 1e-9

    def test_none_when_no_targets(self):
        assert expected_value_r(_setup(targets=[])) is None
        assert primary_target_probability(_setup(targets=[])) is None


class TestSetupQualifies:
    def test_positive_ev_setup_passes(self):
        # primary 50% @ rr 3.0 → EV = 1.0
        assert setup_qualifies(_setup(), DEFAULT_GATE) is True

    def test_negative_ev_fails(self):
        # primary 30% @ rr 1.3 → EV = -0.31, below the 0.15 floor
        s = _setup(rr_ratio=1.3, targets=[{"probability": 30.0, "is_primary": True}])
        assert setup_qualifies(s, DEFAULT_GATE) is False

    def test_thin_positive_ev_below_floor_fails(self):
        # Positive but thin: 0.45*1.3 - 0.55 = 0.035, under the 0.15 floor.
        s = _setup(rr_ratio=1.3, targets=[{"probability": 45.0, "is_primary": True}])
        assert setup_qualifies(s, DEFAULT_GATE) is False

    def test_low_rr_floor_fails(self):
        assert setup_qualifies(_setup(rr_ratio=1.0), DEFAULT_GATE) is False

    def test_low_confidence_fails(self):
        assert setup_qualifies(_setup(confidence_score=40.0), DEFAULT_GATE) is False

    def test_no_targets_defers_to_rr_and_confidence(self):
        # No probability → EV uncomputable → not blocked on EV; passes on floors.
        assert setup_qualifies(_setup(targets=[]), DEFAULT_GATE) is True
        # ...but still subject to the rr/confidence floors.
        assert setup_qualifies(_setup(targets=[], rr_ratio=1.0), DEFAULT_GATE) is False

    def test_conviction_and_conflict_ignored_by_default(self):
        # Moderate action + medium risk still pass when tighteners are off.
        s = _setup(recommended_action="LONG_MODERATE", risk_level="Medium")
        assert setup_qualifies(s, DEFAULT_GATE) is True

    def test_over_progressed_setup_fails_on_live_rr(self):
        s = _setup(direction="long", target=120.0, stop_loss=95.0, current_price=117.0)
        assert setup_qualifies(s, DEFAULT_GATE) is False

    def test_fresh_setup_passes_live_rr(self):
        s = _setup(direction="long", target=120.0, stop_loss=95.0, current_price=101.0)
        assert setup_qualifies(s, DEFAULT_GATE) is True

    def test_past_stop_fails_live_rr(self):
        s = _setup(direction="long", target=120.0, stop_loss=95.0, current_price=94.0)
        assert setup_qualifies(s, DEFAULT_GATE) is False

    def test_missing_min_ev_key_skips_ev(self):
        # Legacy callers without min_expected_value: EV defaults to -inf (no floor).
        legacy = {k: v for k, v in DEFAULT_GATE.items() if k != "min_expected_value"}
        s = _setup(rr_ratio=1.3, targets=[{"probability": 30.0, "is_primary": True}])
        assert setup_qualifies(s, legacy) is True


class TestStrictTighteners:
    def test_clean_high_conviction_passes(self):
        assert setup_qualifies(_setup(targets=[{"probability": 65.0, "is_primary": True}]), STRICT_GATE) is True

    def test_moderate_action_fails(self):
        s = _setup(recommended_action="LONG_MODERATE", targets=[{"probability": 65.0, "is_primary": True}])
        assert setup_qualifies(s, STRICT_GATE) is False

    def test_non_low_risk_fails(self):
        s = _setup(risk_level="Medium", targets=[{"probability": 65.0, "is_primary": True}])
        assert setup_qualifies(s, STRICT_GATE) is False

    def test_low_target_probability_fails(self):
        assert setup_qualifies(_setup(targets=[{"probability": 40.0, "is_primary": True}]), STRICT_GATE) is False


class TestBestTargetProbability:
    def test_returns_max(self):
        s = _setup(targets=[{"probability": 40.0}, {"probability": 72.0}, {"probability": 55.0}])
        assert best_target_probability(s) == 72.0

    def test_empty_is_zero(self):
        assert best_target_probability(_setup(targets=[])) == 0.0