"""Tests for probability aggregation utilities."""

import pytest

from sentinel.models import RiskScore
from sentinel.probability_aggregation import (
    AggregatedRisk,
    aggregate_probabilities,
    categorize_risk,
    get_display_cancer_type,
    normalize_cancer_type,
    separate_score_types,
)


class TestAggregateProbabilities:
    """Test probability aggregation functionality."""

    def test_single_model_per_cancer_type(self):
        """Test aggregation with one model per cancer type."""
        scores = [
            RiskScore(
                name="Gail",
                score="1.5%",
                cancer_type="breast",
                probability_percent=1.5,
                time_horizon_years=5.0,
                score_type="probability",
            ),
            RiskScore(
                name="PLCOm2012",
                score="2.3%",
                cancer_type="lung",
                probability_percent=2.3,
                time_horizon_years=6.0,
                score_type="probability",
            ),
        ]

        aggregated = aggregate_probabilities(scores)

        assert len(aggregated) == 2

        # Check breast cancer aggregation
        breast_agg = next(agg for agg in aggregated if agg.cancer_type == "breast")
        assert breast_agg.time_horizon_years == 5.0
        assert breast_agg.avg_probability_percent == 1.5
        assert breast_agg.risk_category == "Moderate"  # 1.5% for 5-year horizon
        assert breast_agg.model_count == 1
        assert len(breast_agg.individual_scores) == 1
        assert breast_agg.individual_scores[0].name == "Gail"

        # Check lung cancer aggregation
        lung_agg = next(agg for agg in aggregated if agg.cancer_type == "lung")
        assert lung_agg.time_horizon_years == 6.0
        assert lung_agg.avg_probability_percent == 2.3
        assert lung_agg.risk_category == "Moderate"  # 2.3% for 6-year horizon
        assert lung_agg.model_count == 1

    def test_multiple_models_same_cancer_same_horizon(self):
        """Test aggregation when multiple models assess same cancer with same time horizon."""
        scores = [
            RiskScore(
                name="Model1",
                score="2.0%",
                cancer_type="breast",
                probability_percent=2.0,
                time_horizon_years=10.0,
                score_type="probability",
            ),
            RiskScore(
                name="Model2",
                score="3.0%",
                cancer_type="breast",
                probability_percent=3.0,
                time_horizon_years=10.0,
                score_type="probability",
            ),
            RiskScore(
                name="Model3",
                score="4.0%",
                cancer_type="breast",
                probability_percent=4.0,
                time_horizon_years=10.0,
                score_type="probability",
            ),
        ]

        aggregated = aggregate_probabilities(scores)

        assert len(aggregated) == 1
        agg = aggregated[0]

        assert agg.cancer_type == "breast"
        assert agg.time_horizon_years == 10.0
        assert agg.avg_probability_percent == pytest.approx(3.0)  # (2+3+4)/3
        assert agg.risk_category == "Moderate"  # 3.0% for 10-year horizon
        assert agg.model_count == 3
        assert len(agg.individual_scores) == 3

    def test_multiple_models_same_cancer_different_horizons(self):
        """Test aggregation with same cancer type but different time horizons."""
        scores = [
            RiskScore(
                name="Model1",
                score="1.5%",
                cancer_type="breast",
                probability_percent=1.5,
                time_horizon_years=5.0,
                score_type="probability",
            ),
            RiskScore(
                name="Model2",
                score="3.0%",
                cancer_type="breast",
                probability_percent=3.0,
                time_horizon_years=10.0,
                score_type="probability",
            ),
            RiskScore(
                name="Model3",
                score="15.0%",
                cancer_type="breast",
                probability_percent=15.0,
                time_horizon_years=79.0,
                score_type="probability",
            ),
        ]

        aggregated = aggregate_probabilities(scores)

        assert len(aggregated) == 3  # Three different time horizons

        # Verify each time horizon is separate
        horizons = {agg.time_horizon_years for agg in aggregated}
        assert horizons == {5.0, 10.0, 79.0}

        # Verify each has single model
        for agg in aggregated:
            assert agg.model_count == 1

    def test_excludes_non_probability_scores(self):
        """Test that non-probability scores are excluded from aggregation."""
        scores = [
            RiskScore(
                name="Gail",
                score="1.5%",
                cancer_type="breast",
                probability_percent=1.5,
                time_horizon_years=5.0,
                score_type="probability",
            ),
            RiskScore(
                name="PCPT",
                score="No Cancer: 45%, Low Grade: 30%, High Grade: 25%",
                cancer_type="prostate",
                probability_percent=None,
                time_horizon_years=None,
                score_type="categorical",
            ),
            RiskScore(
                name="Model",
                score="N/A: Age out of range",
                cancer_type="lung",
                probability_percent=None,
                time_horizon_years=None,
                score_type="not_applicable",
            ),
        ]

        aggregated = aggregate_probabilities(scores)

        assert len(aggregated) == 1
        assert aggregated[0].cancer_type == "breast"

    def test_empty_list(self):
        """Test aggregation with empty score list."""
        aggregated = aggregate_probabilities([])
        assert aggregated == []

    def test_all_non_probability_scores(self):
        """Test aggregation when all scores are non-probability."""
        scores = [
            RiskScore(
                name="PCPT",
                score="Results",
                cancer_type="prostate",
                score_type="categorical",
            ),
            RiskScore(
                name="Model",
                score="N/A",
                cancer_type="lung",
                score_type="not_applicable",
            ),
        ]

        aggregated = aggregate_probabilities(scores)
        assert aggregated == []

    def test_case_insensitive_cancer_type_grouping(self):
        """Test that cancer types are grouped case-insensitively."""
        scores = [
            RiskScore(
                name="Model1",
                score="1.5%",
                cancer_type="Breast",
                probability_percent=1.5,
                time_horizon_years=5.0,
                score_type="probability",
            ),
            RiskScore(
                name="Model2",
                score="1.8%",
                cancer_type="breast",
                probability_percent=1.8,
                time_horizon_years=5.0,
                score_type="probability",
            ),
            RiskScore(
                name="Model3",
                score="1.7%",
                cancer_type="BREAST",
                probability_percent=1.7,
                time_horizon_years=5.0,
                score_type="probability",
            ),
        ]

        aggregated = aggregate_probabilities(scores)

        assert len(aggregated) == 1
        assert aggregated[0].cancer_type == "breast"  # normalized to lowercase
        assert aggregated[0].model_count == 3
        assert aggregated[0].avg_probability_percent == pytest.approx(1.6667, abs=0.001)


class TestSeparateScoreTypes:
    """Test score type separation functionality."""

    def test_separate_all_types(self):
        """Test separation of all three score types."""
        scores = [
            RiskScore(
                name="Gail",
                score="1.5%",
                score_type="probability",
            ),
            RiskScore(
                name="BOADICEA",
                score="2.0%",
                score_type="probability",
            ),
            RiskScore(
                name="PCPT",
                score="No Cancer: 45%",
                score_type="categorical",
            ),
            RiskScore(
                name="Model",
                score="N/A: Age out of range",
                score_type="not_applicable",
            ),
            RiskScore(
                name="Model2",
                score="N/A: Invalid",
                score_type="not_applicable",
            ),
        ]

        separated = separate_score_types(scores)

        assert len(separated["probability"]) == 2
        assert len(separated["categorical"]) == 1
        assert len(separated["not_applicable"]) == 2

    def test_empty_list(self):
        """Test separation with empty list."""
        separated = separate_score_types([])

        assert separated["probability"] == []
        assert separated["categorical"] == []
        assert separated["not_applicable"] == []

    def test_only_probabilities(self):
        """Test separation when all scores are probabilities."""
        scores = [
            RiskScore(name="Model1", score="1%", score_type="probability"),
            RiskScore(name="Model2", score="2%", score_type="probability"),
        ]

        separated = separate_score_types(scores)

        assert len(separated["probability"]) == 2
        assert separated["categorical"] == []
        assert separated["not_applicable"] == []


class TestFilterFunctions:
    """Test individual filter functions."""

    def test_separate_score_types_for_probability(self):
        """Test using separate_score_types to get probability scores."""
        scores = [
            RiskScore(name="Model1", score="1%", score_type="probability"),
            RiskScore(name="Model2", score="Result", score_type="categorical"),
            RiskScore(name="Model3", score="2%", score_type="probability"),
        ]

        separated = separate_score_types(scores)

        assert len(separated["probability"]) == 2
        assert all(
            score.score_type == "probability" for score in separated["probability"]
        )

    def test_separate_score_types_for_categorical(self):
        """Test using separate_score_types to get categorical scores."""
        scores = [
            RiskScore(name="Model1", score="1%", score_type="probability"),
            RiskScore(name="Model2", score="Result", score_type="categorical"),
            RiskScore(name="Model3", score="N/A", score_type="not_applicable"),
        ]

        separated = separate_score_types(scores)

        assert len(separated["categorical"]) == 1
        assert separated["categorical"][0].score_type == "categorical"

    def test_separate_score_types_for_not_applicable(self):
        """Test using separate_score_types to get not_applicable scores."""
        scores = [
            RiskScore(name="Model1", score="1%", score_type="probability"),
            RiskScore(
                name="Model2", score="N/A: Reason 1", score_type="not_applicable"
            ),
            RiskScore(
                name="Model3", score="N/A: Reason 2", score_type="not_applicable"
            ),
        ]

        separated = separate_score_types(scores)

        assert len(separated["not_applicable"]) == 2
        assert all(
            score.score_type == "not_applicable"
            for score in separated["not_applicable"]
        )

    def test_separate_score_types_for_all_types(self):
        """Test using separate_score_types to get all score types at once."""
        scores = [
            RiskScore(name="Model1", score="1%", score_type="probability"),
            RiskScore(name="Model2", score="2%", score_type="probability"),
            RiskScore(name="Model3", score="Result", score_type="categorical"),
            RiskScore(name="Model4", score="N/A: Age", score_type="not_applicable"),
        ]

        separated = separate_score_types(scores)

        assert len(separated["probability"]) == 2
        assert len(separated["categorical"]) == 1
        assert len(separated["not_applicable"]) == 1


class TestAggregatedRiskDataclass:
    """Test the AggregatedRisk dataclass."""

    def test_dataclass_creation(self):
        """Test creating an AggregatedRisk object."""
        score = RiskScore(
            name="Gail",
            score="1.5%",
            cancer_type="breast",
            probability_percent=1.5,
            time_horizon_years=5.0,
            score_type="probability",
        )

        agg = AggregatedRisk(
            cancer_type="breast",
            time_horizon_years=5.0,
            avg_probability_percent=1.5,
            risk_category="Low",
            model_count=1,
            individual_scores=[score],
        )

        assert agg.cancer_type == "breast"
        assert agg.time_horizon_years == 5.0
        assert agg.avg_probability_percent == 1.5
        assert agg.risk_category == "Low"
        assert agg.model_count == 1
        assert len(agg.individual_scores) == 1


class TestNormalizeCancerType:
    """Test cancer type normalization."""

    def test_normalize_with_cancer_suffix(self):
        """Test removing 'cancer' suffix."""
        assert normalize_cancer_type("Breast Cancer") == "breast"
        assert normalize_cancer_type("Lung cancer") == "lung"
        assert normalize_cancer_type("PROSTATE CANCER") == "prostate"

    def test_normalize_without_cancer_suffix(self):
        """Test normalization without 'cancer' suffix."""
        assert normalize_cancer_type("Breast") == "breast"
        assert normalize_cancer_type("LUNG") == "lung"
        assert normalize_cancer_type("Prostate") == "prostate"

    def test_normalize_with_whitespace(self):
        """Test trimming whitespace."""
        assert normalize_cancer_type("  Breast Cancer  ") == "breast"
        assert normalize_cancer_type("Lung   cancer") == "lung"

    def test_normalize_empty_string(self):
        """Test empty string."""
        assert normalize_cancer_type("") == ""

    def test_display_cancer_type(self):
        """Test display-friendly cancer type names."""
        assert get_display_cancer_type("breast") == "Breast"
        assert get_display_cancer_type("lung") == "Lung"
        assert get_display_cancer_type("prostate") == "Prostate"


class TestCategorizeRisk:
    """Test risk categorization."""

    def test_categorize_short_horizon_very_low(self):
        """Test very low risk for short time horizon."""
        assert categorize_risk(0.3, 5.0) == "Very Low"

    def test_categorize_short_horizon_low(self):
        """Test low risk for short time horizon."""
        assert categorize_risk(1.0, 5.0) == "Low"

    def test_categorize_short_horizon_moderate(self):
        """Test moderate risk for short time horizon."""
        assert categorize_risk(2.0, 5.0) == "Moderate"

    def test_categorize_short_horizon_moderately_high(self):
        """Test moderately high risk for short time horizon."""
        assert categorize_risk(4.0, 5.0) == "Moderately High"

    def test_categorize_short_horizon_high(self):
        """Test high risk for short time horizon."""
        assert categorize_risk(6.0, 5.0) == "High"

    def test_categorize_long_horizon_very_low(self):
        """Test very low risk for long time horizon."""
        assert categorize_risk(0.5, 10.0) == "Very Low"

    def test_categorize_long_horizon_low(self):
        """Test low risk for long time horizon."""
        assert categorize_risk(2.0, 10.0) == "Low"

    def test_categorize_long_horizon_moderate(self):
        """Test moderate risk for long time horizon."""
        assert categorize_risk(5.0, 10.0) == "Moderate"

    def test_categorize_long_horizon_moderately_high(self):
        """Test moderately high risk for long time horizon."""
        assert categorize_risk(10.0, 10.0) == "Moderately High"

    def test_categorize_long_horizon_high(self):
        """Test high risk for long time horizon."""
        assert categorize_risk(20.0, 10.0) == "High"

    def test_categorize_lifetime_risk(self):
        """Test categorization for lifetime risk."""
        assert categorize_risk(0.5, 79.0) == "Very Low"
        assert categorize_risk(2.0, 79.0) == "Low"
        assert categorize_risk(5.0, 79.0) == "Moderate"
        assert categorize_risk(12.0, 79.0) == "Moderately High"
        assert categorize_risk(20.0, 79.0) == "High"