foxhunt/ml/tests/regime_transition_features_test.rs

//! Comprehensive Unit Tests for Transition Probability Features (Wave D Phase 3, Agent D15)
//!
//! This test suite validates transition probability features (indices 216-220, 5 features):
//! 1. **Stability P(i→i)** (216): Probability of staying in current regime
//! 2. **Most Likely Next Regime** (217): Index of regime with highest transition probability
//! 3. **Shannon Entropy** (218): H = -Σ P(i→j) log₂ P(i→j), uncertainty measure
//! 4. **Expected Duration** (219): E[T] = 1 / (1 - P[i][i]), bars until transition
//! 5. **Change Probability** (220): 1 - P(i→i), probability of regime change
//!
//! ## Test Coverage (15 tests across 5 categories)
//! - ✅ Stability tests (3): P(i→i) calculation, deterministic transitions, random transitions
//! - ✅ Most likely next tests (3): argmax calculation, tie breaking, index encoding
//! - ✅ Entropy tests (3): bounds [0, log₂N], deterministic (entropy=0), uniform (max entropy)
//! - ✅ Expected duration tests (3): duration calculation, integration with TransitionMatrix, edge cases
//! - ✅ Change probability tests (3): complement of stability, bounds [0, 1], deterministic vs random
//!
//! ## TDD Methodology
//! Tests written to validate full implementation of TransitionProbabilityFeatures.

use ml::ensemble::MarketRegime;
use ml::regime::transition_probability_features::TransitionProbabilityFeatures;

// ==================== CATEGORY 1: STABILITY TESTS (3 tests) ====================

#[test]
fn test_stability_self_transition_probability() {
    // Test: Stability feature correctly tracks P(i→i) for current regime
    let regimes = vec![
        MarketRegime::Bull,
        MarketRegime::Bear,
        MarketRegime::Sideways,
    ];

    let mut features = TransitionProbabilityFeatures::new(regimes, 0.2, 1);

    // Create a strongly persistent sequence: Bull → Bull → Bull
    for _ in 0..10 {
        features.update(MarketRegime::Bull);
    }

    let result = features.compute_features();
    let stability = result[0];

    // After 10 self-transitions, stability should be very high (>0.8)
    assert!(
        stability > 0.8 && stability <= 1.0,
        "Stability for persistent regime should be >0.8, got {}",
        stability
    );
}

#[test]
fn test_stability_deterministic_transitions() {
    // Test: Deterministic self-transitions yield stability ≈ 1.0
    let regimes = vec![MarketRegime::Sideways];

    let mut features = TransitionProbabilityFeatures::new(regimes, 0.1, 1);

    // Only one regime: all transitions are self-transitions
    for _ in 0..20 {
        features.update(MarketRegime::Sideways);
    }

    let result = features.compute_features();
    let stability = result[0];

    // With only self-transitions, stability should approach 1.0
    assert!(
        stability > 0.95,
        "Deterministic self-transitions should yield stability >0.95, got {}",
        stability
    );
}

#[test]
fn test_stability_random_transitions() {
    // Test: Random transitions between regimes yield lower stability
    let regimes = vec![
        MarketRegime::Bull,
        MarketRegime::Bear,
        MarketRegime::Sideways,
    ];

    let mut features = TransitionProbabilityFeatures::new(regimes, 0.2, 1);

    // Alternate between regimes (low persistence)
    let sequence = vec![
        MarketRegime::Bull,
        MarketRegime::Bear,
        MarketRegime::Sideways,
        MarketRegime::Bull,
        MarketRegime::Bear,
        MarketRegime::Sideways,
    ];

    for regime in sequence {
        features.update(regime);
    }

    let result = features.compute_features();
    let stability = result[0];

    // With frequent transitions, stability should be lower (<0.6)
    assert!(
        stability < 0.6,
        "Random transitions should yield stability <0.6, got {}",
        stability
    );
}

// ==================== CATEGORY 2: MOST LIKELY NEXT REGIME TESTS (3 tests) ====================

#[test]
fn test_most_likely_next_argmax_calculation() {
    // Test: Most likely next regime correctly identifies highest transition probability
    let regimes = vec![
        MarketRegime::Bull,
        MarketRegime::Bear,
        MarketRegime::Sideways,
    ];

    let mut features = TransitionProbabilityFeatures::new(regimes, 0.2, 1);

    // Create pattern: Bull → Sideways (repeated)
    for _ in 0..10 {
        features.update(MarketRegime::Bull);
        features.update(MarketRegime::Sideways);
    }

    // Ensure current regime is Bull
    features.update(MarketRegime::Bull);

    let result = features.compute_features();
    let most_likely_idx = result[1] as usize;

    // Most likely next regime from Bull should be Sideways (index 2)
    assert_eq!(
        most_likely_idx, 2,
        "Most likely next regime after Bull should be Sideways (index 2), got {}",
        most_likely_idx
    );
}

#[test]
fn test_most_likely_next_tie_breaking() {
    // Test: Tie breaking when multiple regimes have equal probability
    let regimes = vec![MarketRegime::Bull, MarketRegime::Bear];

    let mut features = TransitionProbabilityFeatures::new(regimes, 0.1, 10);

    // With no updates, both transitions have equal probability (uniform initialization)
    let result = features.compute_features();
    let most_likely_idx = result[1] as usize;

    // Should return the first matching index (0 or 1)
    assert!(
        most_likely_idx < 2,
        "Most likely index should be valid (0-1), got {}",
        most_likely_idx
    );
}

#[test]
fn test_most_likely_next_index_encoding() {
    // Test: Index encoding correctly maps regime to 0-based index
    let regimes = vec![
        MarketRegime::Bull,     // Index 0
        MarketRegime::Bear,     // Index 1
        MarketRegime::Sideways, // Index 2
    ];

    let features = TransitionProbabilityFeatures::new(regimes, 0.1, 1);
    let result = features.compute_features();
    let most_likely_idx = result[1];

    // Index should be in valid range [0, 2]
    assert!(
        most_likely_idx >= 0.0 && most_likely_idx <= 2.0,
        "Most likely index should be in [0, 2], got {}",
        most_likely_idx
    );
}

// ==================== CATEGORY 3: ENTROPY TESTS (3 tests) ====================

#[test]
fn test_entropy_bounds() {
    // Test: Shannon entropy stays within bounds [0, log₂(N)]
    let regimes = vec![
        MarketRegime::Bull,
        MarketRegime::Bear,
        MarketRegime::Sideways,
        MarketRegime::HighVolatility,
    ];

    let mut features = TransitionProbabilityFeatures::new(regimes.clone(), 0.2, 1);

    // Create diverse transition pattern
    let sequence = vec![
        MarketRegime::Bull,
        MarketRegime::Bear,
        MarketRegime::Sideways,
        MarketRegime::HighVolatility,
        MarketRegime::Bull,
    ];

    for regime in sequence {
        features.update(regime);
    }

    let result = features.compute_features();
    let entropy = result[2];

    let max_entropy = (regimes.len() as f64).log2();

    assert!(
        entropy >= 0.0 && entropy <= max_entropy,
        "Entropy should be in [0, {:.4}], got {:.4}",
        max_entropy,
        entropy
    );
}

#[test]
fn test_entropy_deterministic_zero() {
    // Test: Deterministic transitions (single outcome) yield entropy ≈ 0
    let regimes = vec![MarketRegime::Sideways];

    let mut features = TransitionProbabilityFeatures::new(regimes, 0.1, 1);

    // Only one regime: deterministic transitions
    for _ in 0..20 {
        features.update(MarketRegime::Sideways);
    }

    let result = features.compute_features();
    let entropy = result[2];

    // Deterministic case: entropy should be near zero
    assert!(
        entropy < 0.1,
        "Deterministic transitions should yield low entropy (<0.1), got {:.4}",
        entropy
    );
}

#[test]
fn test_entropy_uniform_maximum() {
    // Test: Uniform distribution over regimes yields maximum entropy
    let regimes = vec![
        MarketRegime::Bull,
        MarketRegime::Bear,
        MarketRegime::Sideways,
        MarketRegime::HighVolatility,
    ];

    // With min_obs=100, insufficient data forces uniform Laplace smoothing
    let features = TransitionProbabilityFeatures::new(regimes.clone(), 0.1, 100);

    let result = features.compute_features();
    let entropy = result[2];

    let max_entropy = (regimes.len() as f64).log2();

    // Uniform distribution should yield near-maximum entropy
    assert!(
        (entropy - max_entropy).abs() < 0.5,
        "Uniform distribution should yield entropy ≈ {:.4}, got {:.4}",
        max_entropy,
        entropy
    );
}

// ==================== CATEGORY 4: EXPECTED DURATION TESTS (3 tests) ====================

#[test]
fn test_expected_duration_calculation() {
    // Test: Expected duration correctly calculated as E[T] = 1 / (1 - P[i][i])
    let regimes = vec![MarketRegime::Sideways];

    let mut features = TransitionProbabilityFeatures::new(regimes, 0.1, 1);

    // Create high persistence: P(Sideways→Sideways) ≈ 0.9
    for _ in 0..20 {
        features.update(MarketRegime::Sideways);
    }

    let result = features.compute_features();
    let duration = result[3];

    // E[T] = 1 / (1 - 0.9) = 10 periods (approximately)
    assert!(
        duration > 5.0,
        "High persistence should yield duration >5 periods, got {:.2}",
        duration
    );
}

#[test]
fn test_expected_duration_integration_with_transition_matrix() {
    // Test: Duration feature integrates correctly with underlying TransitionMatrix
    let regimes = vec![MarketRegime::Bull, MarketRegime::Bear];

    let mut features = TransitionProbabilityFeatures::new(regimes, 0.2, 1);

    // Create persistent Bull regime
    for _ in 0..15 {
        features.update(MarketRegime::Bull);
    }

    let result = features.compute_features();
    let duration = result[3];

    // Direct validation: duration from TransitionMatrix should match feature
    let matrix_duration = features
        .transition_matrix()
        .get_expected_duration(MarketRegime::Bull);

    assert!(
        (duration - matrix_duration).abs() < 1e-6,
        "Feature duration should match TransitionMatrix, got feature={:.4}, matrix={:.4}",
        duration,
        matrix_duration
    );
}

#[test]
fn test_expected_duration_edge_cases() {
    // Test: Edge cases - zero persistence, low observations
    let regimes = vec![MarketRegime::Bull, MarketRegime::Bear];

    let mut features = TransitionProbabilityFeatures::new(regimes, 0.5, 1);

    // Alternate between regimes (zero persistence in each regime)
    for _ in 0..10 {
        features.update(MarketRegime::Bull);
        features.update(MarketRegime::Bear);
    }

    // Ensure current regime is Bull
    features.update(MarketRegime::Bull);

    let result = features.compute_features();
    let duration = result[3];

    // Low persistence: duration should be near 1.0 (immediate exit)
    assert!(
        duration >= 1.0 && duration < 3.0,
        "Low persistence should yield duration near 1.0, got {:.2}",
        duration
    );
}

// ==================== CATEGORY 5: CHANGE PROBABILITY TESTS (3 tests) ====================

#[test]
fn test_change_probability_complement_of_stability() {
    // Test: Change probability = 1 - stability (exact complement)
    let regimes = vec![
        MarketRegime::Bull,
        MarketRegime::Bear,
        MarketRegime::Sideways,
    ];

    let mut features = TransitionProbabilityFeatures::new(regimes, 0.2, 1);

    // Create mixed transition pattern
    for _ in 0..5 {
        features.update(MarketRegime::Bull);
        features.update(MarketRegime::Bear);
    }

    let result = features.compute_features();
    let stability = result[0];
    let change_prob = result[4];

    // Change probability should be exact complement of stability
    assert!(
        (stability + change_prob - 1.0).abs() < 1e-10,
        "stability + change_prob should equal 1.0, got {:.10} + {:.10} = {:.10}",
        stability,
        change_prob,
        stability + change_prob
    );
}

#[test]
fn test_change_probability_bounds() {
    // Test: Change probability stays within [0, 1]
    let regimes = vec![
        MarketRegime::Bull,
        MarketRegime::Bear,
        MarketRegime::Sideways,
        MarketRegime::HighVolatility,
    ];

    let mut features = TransitionProbabilityFeatures::new(regimes, 0.2, 1);

    // Create diverse transitions
    let sequence = vec![
        MarketRegime::Bull,
        MarketRegime::Bear,
        MarketRegime::Sideways,
        MarketRegime::HighVolatility,
    ];

    for regime in sequence {
        features.update(regime);
    }

    let result = features.compute_features();
    let change_prob = result[4];

    assert!(
        change_prob >= 0.0 && change_prob <= 1.0,
        "Change probability should be in [0, 1], got {:.4}",
        change_prob
    );
}

#[test]
fn test_change_probability_deterministic_vs_random() {
    // Test: Compare change probability for deterministic vs random transitions

    // Deterministic case: single regime (low change probability)
    let regimes_det = vec![MarketRegime::Sideways];
    let mut features_det = TransitionProbabilityFeatures::new(regimes_det, 0.1, 1);

    for _ in 0..20 {
        features_det.update(MarketRegime::Sideways);
    }

    let result_det = features_det.compute_features();
    let change_prob_det = result_det[4];

    // Random case: alternating regimes (high change probability)
    let regimes_rand = vec![MarketRegime::Bull, MarketRegime::Bear];
    let mut features_rand = TransitionProbabilityFeatures::new(regimes_rand, 0.2, 1);

    for _ in 0..10 {
        features_rand.update(MarketRegime::Bull);
        features_rand.update(MarketRegime::Bear);
    }

    let result_rand = features_rand.compute_features();
    let change_prob_rand = result_rand[4];

    // Random transitions should have higher change probability than deterministic
    assert!(
        change_prob_rand > change_prob_det,
        "Random transitions should have higher change probability than deterministic, got random={:.4}, det={:.4}",
        change_prob_rand,
        change_prob_det
    );

    // Deterministic case should have low change probability (<0.1)
    assert!(
        change_prob_det < 0.1,
        "Deterministic case should have change probability <0.1, got {:.4}",
        change_prob_det
    );

    // Random case should have high change probability (>0.5)
    assert!(
        change_prob_rand > 0.5,
        "Random case should have change probability >0.5, got {:.4}",
        change_prob_rand
    );
}