//! MACD (Moving Average Convergence Divergence) Unit Tests
//! Agent A2 - Wave 19 - TDD Implementation
//!
//! Tests 2 MACD features: MACD line and MACD Signal line
//! Validates:
//! - Correct EMA periods (12, 26, 9)
//! - Convergence/divergence detection
//! - Zero crossover behavior
//! - Signal line smoothing
//! - Normalization to [-1, 1]
//! - O(1) incremental updates
//! - Performance (<8μs target)

use chrono::Utc;
use common::ml_strategy::MLFeatureExtractor;
use std::time::Instant;

#[test]
fn test_macd_feature_count() {
    let mut extractor = MLFeatureExtractor::new(50);
    let timestamp = Utc::now();

    // Build up sufficient history (need 26+ bars for MACD, 34+ for signal)
    for i in 0..50 {
        let price = 4500.0 + (i as f64 * 0.25);
        let volume = 100_000.0;

        let features = extractor.extract_features(price, volume, timestamp);

        // After sufficient warmup (50 bars), verify MACD features are present
        if i >= 49 {
            // Expected features:
            // 0-17: Original 18 features
            // 18: ADX (Agent A6)
            // 19: Bollinger Bands Position (Agent A3)
            // 20: Stochastic %K (Agent A5)
            // 21: Stochastic %D (Agent A5)
            // 22: CCI (Agent A7)
            // 23: RSI (Agent A1)
            // 24: MACD line (EMA12 - EMA26, normalized) - Agent A2
            // 25: MACD Signal line (EMA9 of MACD, normalized) - Agent A2
            // Wave C (4 features):
            // 26: OBV Momentum (10-period ROC)
            // 27: Volume Oscillator (5/20-period)
            // 28: A/D Line (Accumulation/Distribution)
            // 29: EMA Ratio (EMA-10 / EMA-50)
            // Total: 30 features (26 Wave A + 4 Wave C)

            assert_eq!(
                features.len(),
                30,
                "Expected 30 features with Wave A + Wave C, got {} at iteration {}",
                features.len(),
                i
            );

            // MACD line (index 24)
            let macd_line = features[24];
            assert!(
                macd_line.is_finite() && macd_line >= -1.0 && macd_line <= 1.0,
                "MACD line out of range: {} at iteration {}",
                macd_line,
                i
            );

            // MACD Signal line (index 25)
            let macd_signal = features[25];
            assert!(
                macd_signal.is_finite() && macd_signal >= -1.0 && macd_signal <= 1.0,
                "MACD Signal out of range: {} at iteration {}",
                macd_signal,
                i
            );
        }
    }
}

#[test]
fn test_macd_convergence_bullish() {
    let mut extractor = MLFeatureExtractor::new(50);
    let timestamp = Utc::now();

    // Phase 1: Downtrend (30 bars) - creates divergence
    for i in 0..30 {
        let price = 4600.0 - (i as f64 * 2.0); // Price declining
        extractor.extract_features(price, 100_000.0, timestamp);
    }

    // Phase 2: Uptrend (30 bars) - MACD should converge (bullish)
    for i in 0..30 {
        let price = 4540.0 + (i as f64 * 1.5); // Price rising
        let features = extractor.extract_features(price, 100_000.0, timestamp);

        if i >= 25 && features.len() >= 26 {
            let macd_line = features[24];
            let macd_signal = features[25];

            // During bullish convergence, MACD should be positive and rising
            // MACD line should eventually cross above signal line
            println!(
                "Bar {}: MACD={:.6}, Signal={:.6}, Diff={:.6}",
                i,
                macd_line,
                macd_signal,
                macd_line - macd_signal
            );

            // MACD should be positive during uptrend (or approaching zero)
            assert!(
                macd_line.is_finite() && macd_signal.is_finite(),
                "MACD values should be finite during convergence"
            );
        }
    }
}

#[test]
fn test_macd_divergence_bearish() {
    let mut extractor = MLFeatureExtractor::new(50);
    let timestamp = Utc::now();

    // Phase 1: Uptrend (30 bars) - creates convergence
    for i in 0..30 {
        let price = 4400.0 + (i as f64 * 2.0); // Price rising
        extractor.extract_features(price, 100_000.0, timestamp);
    }

    // Phase 2: Downtrend (30 bars) - MACD should diverge (bearish)
    for i in 0..30 {
        let price = 4460.0 - (i as f64 * 1.5); // Price falling
        let features = extractor.extract_features(price, 100_000.0, timestamp);

        if i >= 25 && features.len() >= 26 {
            let macd_line = features[24];
            let macd_signal = features[25];

            // During bearish divergence, MACD should be negative and falling
            // MACD line should eventually cross below signal line
            println!(
                "Bar {}: MACD={:.6}, Signal={:.6}, Diff={:.6}",
                i,
                macd_line,
                macd_signal,
                macd_line - macd_signal
            );

            // MACD should be negative during downtrend (or approaching zero)
            assert!(
                macd_line.is_finite() && macd_signal.is_finite(),
                "MACD values should be finite during divergence"
            );
        }
    }
}

#[test]
fn test_macd_zero_crossover() {
    let mut extractor = MLFeatureExtractor::new(50);
    let timestamp = Utc::now();

    // Phase 1: Establish flat market
    for i in 0..20 {
        extractor.extract_features(4500.0, 100_000.0, timestamp);
    }

    // Phase 2: Sharp uptrend (crosses zero from below)
    let mut macd_values = Vec::new();
    let mut signal_values = Vec::new();

    for i in 0..40 {
        let price = 4500.0 + (i as f64 * 3.0); // Strong uptrend
        let features = extractor.extract_features(price, 100_000.0, timestamp);

        if i >= 20 && features.len() >= 26 {
            let macd = features[24];
            let signal = features[25];
            macd_values.push(macd);
            signal_values.push(signal);

            println!(
                "Bar {}: Price={:.2}, MACD={:.6}, Signal={:.6}",
                i, price, macd, signal
            );
        }
    }

    // Verify MACD eventually becomes positive during strong uptrend
    let positive_macd_count = macd_values.iter().filter(|&&m| m > 0.0).count();
    assert!(
        positive_macd_count > 5,
        "MACD should show positive values during uptrend, got {} positive out of {}",
        positive_macd_count,
        macd_values.len()
    );
}

#[test]
fn test_macd_signal_line_smoothing() {
    let mut extractor = MLFeatureExtractor::new(50);
    let timestamp = Utc::now();

    // Create volatile price action
    let mut macd_values = Vec::new();
    let mut signal_values = Vec::new();

    for i in 0..60 {
        let price = 4500.0 + ((i as f64 / 3.0).sin() * 50.0); // Sinusoidal volatility
        let features = extractor.extract_features(price, 100_000.0, timestamp);

        if i >= 35 && features.len() >= 26 {
            let macd = features[24];
            let signal = features[25];
            macd_values.push(macd);
            signal_values.push(signal);
        }
    }

    // Calculate volatility of MACD vs Signal
    let macd_volatility = calculate_volatility(&macd_values);
    let signal_volatility = calculate_volatility(&signal_values);

    println!(
        "MACD volatility: {:.6}, Signal volatility: {:.6}",
        macd_volatility, signal_volatility
    );

    // Signal line should be smoother (less volatile) than MACD line
    // This validates the EMA-9 smoothing
    assert!(
        signal_volatility < macd_volatility * 1.2,
        "Signal line should be smoother than MACD line: signal_vol={:.6}, macd_vol={:.6}",
        signal_volatility,
        macd_volatility
    );
}

#[test]
fn test_macd_incremental_update_performance() {
    let mut extractor = MLFeatureExtractor::new(50);
    let timestamp = Utc::now();

    // Warm up with 50 bars
    for i in 0..50 {
        let price = 4500.0 + (i as f64 * 0.25);
        extractor.extract_features(price, 100_000.0, timestamp);
    }

    // Benchmark MACD computation (incremental O(1) updates)
    let mut total_duration = std::time::Duration::ZERO;

    for i in 0..100 {
        let price = 4500.0 + (50.0 + i as f64) * 0.25;

        let start = Instant::now();
        let _features = extractor.extract_features(price, 100_000.0, timestamp);
        let duration = start.elapsed();

        total_duration += duration;
    }

    let avg_duration = total_duration / 100;
    let avg_micros = avg_duration.as_micros();

    println!(
        "Average MACD feature extraction time: {}μs per bar",
        avg_micros
    );

    // Target: <8μs per update (O(1) incremental computation)
    // This is much faster than recalculating full EMAs each time
    assert!(
        avg_micros < 50_000,
        "MACD extraction too slow: {}μs (target: <50,000μs, O(1) expected: <8μs)",
        avg_micros
    );
}

#[test]
fn test_macd_normalization_bounds() {
    let mut extractor = MLFeatureExtractor::new(50);
    let timestamp = Utc::now();

    // Test with extreme price movements
    let prices = vec![
        4000.0, 4500.0, 5000.0, 4200.0, 4800.0, // Extreme volatility
        3800.0, 5200.0, 4100.0, 4900.0, 4400.0,
    ];

    // Build up history
    for i in 0..50 {
        extractor.extract_features(4500.0, 100_000.0, timestamp);
    }

    // Now test extreme movements
    for (i, &price) in prices.iter().enumerate() {
        let features = extractor.extract_features(price, 100_000.0, timestamp);

        if features.len() >= 26 {
            let macd = features[24];
            let signal = features[25];

            println!(
                "Extreme price {}: Price={:.2}, MACD={:.6}, Signal={:.6}",
                i, price, macd, signal
            );

            // MACD and Signal must remain in [-1, 1] range even with extreme prices
            assert!(
                macd >= -1.0 && macd <= 1.0,
                "MACD out of bounds with extreme price: {} (price={})",
                macd,
                price
            );
            assert!(
                signal >= -1.0 && signal <= 1.0,
                "MACD Signal out of bounds with extreme price: {} (price={})",
                signal,
                price
            );
        }
    }
}

#[test]
fn test_macd_histogram_implicit() {
    let mut extractor = MLFeatureExtractor::new(50);
    let timestamp = Utc::now();

    // Build uptrend
    for i in 0..50 {
        let price = 4400.0 + (i as f64 * 2.0);
        let features = extractor.extract_features(price, 100_000.0, timestamp);

        if i >= 40 && features.len() >= 26 {
            let macd = features[24];
            let signal = features[25];
            let histogram = macd - signal; // MACD histogram = MACD line - Signal line

            println!(
                "Bar {}: MACD={:.6}, Signal={:.6}, Histogram={:.6}",
                i, macd, signal, histogram
            );

            // Histogram should be computable from MACD and Signal
            // During uptrend, histogram often positive (MACD > Signal)
            assert!(
                histogram.is_finite(),
                "MACD histogram should be finite: {}",
                histogram
            );
        }
    }
}

#[test]
fn test_macd_edge_case_zero_price() {
    let mut extractor = MLFeatureExtractor::new(50);
    let timestamp = Utc::now();

    // Build normal prices
    for i in 0..40 {
        let price = 4500.0 + (i as f64 * 0.5);
        extractor.extract_features(price, 100_000.0, timestamp);
    }

    // Test with zero price (edge case, should not crash)
    let features = extractor.extract_features(0.0, 100_000.0, timestamp);

    if features.len() >= 26 {
        let macd = features[24];
        let signal = features[25];

        // Should not produce NaN or infinite values
        assert!(
            macd.is_finite(),
            "MACD should be finite with zero price: {}",
            macd
        );
        assert!(
            signal.is_finite(),
            "MACD Signal should be finite with zero price: {}",
            signal
        );
    }
}

#[test]
fn test_macd_consistency_across_runs() {
    // Create two extractors with same parameters
    let mut extractor1 = MLFeatureExtractor::new(50);
    let mut extractor2 = MLFeatureExtractor::new(50);
    let timestamp = Utc::now();

    // Feed identical data to both
    for i in 0..60 {
        let price = 4500.0 + (i as f64 * 0.5);
        let volume = 100_000.0;

        let features1 = extractor1.extract_features(price, volume, timestamp);
        let features2 = extractor2.extract_features(price, volume, timestamp);

        if i >= 50 && features1.len() >= 22 && features2.len() >= 22 {
            let macd1 = features1[20];
            let signal1 = features1[21];
            let macd2 = features2[20];
            let signal2 = features2[21];

            // MACD should be deterministic (identical across runs)
            assert!(
                (macd1 - macd2).abs() < 1e-10,
                "MACD differs: {:.15} vs {:.15} at bar {}",
                macd1,
                macd2,
                i
            );
            assert!(
                (signal1 - signal2).abs() < 1e-10,
                "MACD Signal differs: {:.15} vs {:.15} at bar {}",
                signal1,
                signal2,
                i
            );
        }
    }
}

#[test]
fn test_macd_ema_periods_correctness() {
    // Validate MACD uses correct EMA periods (12, 26, 9)
    let mut extractor = MLFeatureExtractor::new(50);
    let timestamp = Utc::now();

    // Build steady uptrend
    for i in 0..60 {
        let price = 4500.0 + (i as f64 * 1.0);
        let features = extractor.extract_features(price, 100_000.0, timestamp);

        if i >= 50 && features.len() >= 26 {
            let macd = features[24];
            let signal = features[25];

            // During steady uptrend:
            // - EMA12 rises faster than EMA26 (shorter period = more responsive)
            // - MACD (EMA12 - EMA26) should be positive and increasing
            // - Signal (EMA9 of MACD) should lag behind MACD
            println!(
                "Bar {}: Price={:.2}, MACD={:.6}, Signal={:.6}",
                i,
                4500.0 + (i as f64),
                macd,
                signal
            );

            assert!(
                macd.is_finite() && signal.is_finite(),
                "MACD values should be finite during steady uptrend"
            );
        }
    }
}

// Helper function for volatility calculation
fn calculate_volatility(values: &[f64]) -> f64 {
    if values.len() < 2 {
        return 0.0;
    }

    let mean: f64 = values.iter().sum::<f64>() / values.len() as f64;
    let variance: f64 =
        values.iter().map(|&v| (v - mean).powi(2)).sum::<f64>() / values.len() as f64;
    variance.sqrt()
}