//! Performance Benchmarks for Wave D Regime Detection Features
//!
//! Agent D17 - Wave D feature performance validation:
//! - CUSUM Statistics (Agent D13, indices 201-210)
//! - ADX & Directional Indicators (Agent D14, indices 211-215)
//! - Regime Transition Probabilities (Agent D15, indices 216-220)
//! - Adaptive Strategy Metrics (Agent D16, indices 221-224)
//!
//! ## Performance Targets
//! - CUSUM: <50μs per bar
//! - ADX: <80μs per bar
//! - Transition: <50μs per bar
//! - Adaptive: <100μs per bar
//!
//! ## Run Benchmarks
//! ```bash
//! cargo bench -p ml --bench wave_d_features_bench
//! ```

use chrono::Utc;
use criterion::{black_box, criterion_group, criterion_main, Criterion};
use ml::ensemble::MarketRegime;
use ml::features::{
    extraction::OHLCVBar,
    regime_adaptive::RegimeAdaptiveFeatures,
    regime_adx::{OHLCVBar as ADXBar, RegimeADXFeatures},
    regime_cusum::RegimeCUSUMFeatures,
    regime_transition::RegimeTransitionFeatures,
};
use std::time::Duration;

// ============================================================================
// Test Data Generators
// ============================================================================

/// Generate realistic log returns for CUSUM testing
fn generate_log_returns(num_bars: usize, seed: u64) -> Vec<f64> {
    use std::f64::consts::PI;

    let mut rng = fastrand::Rng::with_seed(seed);
    let mut returns = Vec::with_capacity(num_bars);

    for i in 0..num_bars {
        // Simulate regime changes with drift shifts
        let regime_phase = (i / 50) % 4;
        let drift = match regime_phase {
            0 => 0.0,    // Normal regime
            1 => 0.002,  // Positive drift
            2 => 0.0,    // Return to normal
            3 => -0.002, // Negative drift
            _ => 0.0,
        };

        // Add cycle component
        let cycle = (i as f64 * 0.1 * PI).sin() * 0.0005;

        // Add noise
        let noise = (rng.f64() - 0.5) * 0.005;

        returns.push(drift + cycle + noise);
    }

    returns
}

/// Generate realistic OHLCV bars for ADX testing
fn generate_ohlcv_bars(num_bars: usize, seed: u64) -> Vec<ADXBar> {
    use std::f64::consts::PI;

    let mut rng = fastrand::Rng::with_seed(seed);
    let mut bars = Vec::with_capacity(num_bars);
    let mut close = 100.0;
    let base_time = Utc::now().timestamp();

    for i in 0..num_bars {
        // Combine trend, cycle, and noise
        let trend = (i as f64 * 0.01) % 10.0 - 5.0;
        let cycle = (i as f64 * 0.1 * PI).sin() * 2.0;
        let noise = (rng.f64() - 0.5) * 0.5;

        close += trend * 0.01 + cycle * 0.05 + noise;
        close = close.max(50.0).min(150.0);

        // Generate realistic OHLC with typical 0.1-0.5% intrabar range
        let range = close * 0.003 * (1.0 + rng.f64());
        let high = close + range * rng.f64();
        let low = close - range * rng.f64();
        let open = low + (high - low) * rng.f64();
        let volume = 10000.0 + (i as f64 * 0.5 * PI).sin().abs() * 5000.0 + rng.f64() * 2000.0;

        bars.push(ADXBar {
            timestamp: base_time + (i as i64 * 60),
            open,
            high,
            low,
            close,
            volume,
        });
    }

    bars
}

/// Generate realistic OHLCV bars (extraction format) for Adaptive testing
fn generate_extraction_bars(num_bars: usize, seed: u64) -> Vec<OHLCVBar> {
    use std::f64::consts::PI;

    let mut rng = fastrand::Rng::with_seed(seed);
    let mut bars = Vec::with_capacity(num_bars);
    let mut close = 100.0;
    let base_time = Utc::now();

    for i in 0..num_bars {
        // Combine trend, cycle, and noise
        let trend = (i as f64 * 0.01) % 10.0 - 5.0;
        let cycle = (i as f64 * 0.1 * PI).sin() * 2.0;
        let noise = (rng.f64() - 0.5) * 0.5;

        close += trend * 0.01 + cycle * 0.05 + noise;
        close = close.max(50.0).min(150.0);

        // Generate realistic OHLC with typical 0.1-0.5% intrabar range
        let range = close * 0.003 * (1.0 + rng.f64());
        let high = close + range * rng.f64();
        let low = close - range * rng.f64();
        let open = low + (high - low) * rng.f64();
        let volume = 10000.0 + (i as f64 * 0.5 * PI).sin().abs() * 5000.0 + rng.f64() * 2000.0;

        bars.push(OHLCVBar {
            timestamp: base_time + chrono::Duration::seconds(i as i64 * 60),
            open,
            high,
            low,
            close,
            volume,
        });
    }

    bars
}

/// Generate realistic regime sequence for Transition testing
fn generate_regime_sequence(num_regimes: usize, seed: u64) -> Vec<MarketRegime> {
    let mut rng = fastrand::Rng::with_seed(seed);
    let regimes = vec![
        MarketRegime::Normal,
        MarketRegime::Trending,
        MarketRegime::Sideways,
        MarketRegime::Bull,
        MarketRegime::Bear,
        MarketRegime::HighVolatility,
        MarketRegime::Crisis,
    ];

    (0..num_regimes)
        .map(|_| regimes[rng.usize(0..regimes.len())])
        .collect()
}

// ============================================================================
// CUSUM Features Benchmarks (Agent D13, indices 201-210)
// ============================================================================

/// Benchmark CUSUM features cold start (single update)
fn bench_cusum_features_cold(c: &mut Criterion) {
    let mut group = c.benchmark_group("cusum_features");
    group.measurement_time(Duration::from_secs(5));

    let returns = generate_log_returns(1000, 42);

    group.bench_function("single_update_cold", |b| {
        b.iter(|| {
            let mut features = RegimeCUSUMFeatures::new(0.0, 1.0, 0.5, 4.0);
            let result = features.update(black_box(returns[0]));
            black_box(result);
        });
    });

    group.finish();
}

/// Benchmark CUSUM features warm state (incremental updates)
fn bench_cusum_features_warm(c: &mut Criterion) {
    let mut group = c.benchmark_group("cusum_features_warm");
    group.measurement_time(Duration::from_secs(5));

    let returns = generate_log_returns(1000, 43);

    // Warm up with 100 bars
    let mut features = RegimeCUSUMFeatures::new(0.0, 1.0, 0.5, 4.0);
    for &ret in returns.iter().take(100) {
        features.update(ret);
    }

    group.bench_function("single_update_warm", |b| {
        let mut feat = RegimeCUSUMFeatures::new(0.0, 1.0, 0.5, 4.0);
        // Pre-warm
        for &ret in returns.iter().take(100) {
            feat.update(ret);
        }

        let mut idx = 100;
        b.iter(|| {
            let result = feat.update(black_box(returns[idx % returns.len()]));
            black_box(result);
            idx += 1;
        });
    });

    group.finish();
}

/// Benchmark CUSUM features full sequence (all 10 features)
fn bench_cusum_features_sequence(c: &mut Criterion) {
    let mut group = c.benchmark_group("cusum_features_sequence");
    group.measurement_time(Duration::from_secs(10));

    let returns = generate_log_returns(500, 44);

    group.bench_function("500_bars_full_pipeline", |b| {
        b.iter(|| {
            let mut features = RegimeCUSUMFeatures::new(0.0, 1.0, 0.5, 4.0);
            for &ret in returns.iter() {
                let result = features.update(black_box(ret));
                black_box(result);
            }
        });
    });

    group.finish();
}

// ============================================================================
// ADX Features Benchmarks (Agent D14, indices 211-215)
// ============================================================================

/// Benchmark ADX features cold start
fn bench_adx_features_cold(c: &mut Criterion) {
    let mut group = c.benchmark_group("adx_features");
    group.measurement_time(Duration::from_secs(5));

    let bars = generate_ohlcv_bars(1000, 45);

    group.bench_function("single_update_cold", |b| {
        b.iter(|| {
            let mut features = RegimeADXFeatures::new(14);
            let result = features.update(black_box(&bars[0]));
            black_box(result);
        });
    });

    group.finish();
}

/// Benchmark ADX features warm state
fn bench_adx_features_warm(c: &mut Criterion) {
    let mut group = c.benchmark_group("adx_features_warm");
    group.measurement_time(Duration::from_secs(5));

    let bars = generate_ohlcv_bars(1000, 46);

    // Warm up with 28 bars (2 * period for full ADX initialization)
    let mut features = RegimeADXFeatures::new(14);
    for bar in bars.iter().take(28) {
        features.update(bar);
    }

    group.bench_function("single_update_warm", |b| {
        let mut feat = RegimeADXFeatures::new(14);
        // Pre-warm
        for bar in bars.iter().take(28) {
            feat.update(bar);
        }

        let mut idx = 28;
        b.iter(|| {
            let result = feat.update(black_box(&bars[idx % bars.len()]));
            black_box(result);
            idx += 1;
        });
    });

    group.finish();
}

/// Benchmark ADX features full sequence
fn bench_adx_features_sequence(c: &mut Criterion) {
    let mut group = c.benchmark_group("adx_features_sequence");
    group.measurement_time(Duration::from_secs(10));

    let bars = generate_ohlcv_bars(500, 47);

    group.bench_function("500_bars_full_pipeline", |b| {
        b.iter(|| {
            let mut features = RegimeADXFeatures::new(14);
            for bar in bars.iter() {
                let result = features.update(black_box(bar));
                black_box(result);
            }
        });
    });

    group.finish();
}

// ============================================================================
// Transition Features Benchmarks (Agent D15, indices 216-220)
// ============================================================================

/// Benchmark Transition features cold start
fn bench_transition_features_cold(c: &mut Criterion) {
    let mut group = c.benchmark_group("transition_features");
    group.measurement_time(Duration::from_secs(5));

    let regimes = generate_regime_sequence(1000, 48);

    group.bench_function("single_update_cold", |b| {
        b.iter(|| {
            let mut features = RegimeTransitionFeatures::new(4, 0.1);
            let result = features.update(black_box(regimes[0]));
            black_box(result);
        });
    });

    group.finish();
}

/// Benchmark Transition features warm state
fn bench_transition_features_warm(c: &mut Criterion) {
    let mut group = c.benchmark_group("transition_features_warm");
    group.measurement_time(Duration::from_secs(5));

    let regimes = generate_regime_sequence(1000, 49);

    // Warm up with 50 regime observations
    let mut features = RegimeTransitionFeatures::new(4, 0.1);
    for &regime in regimes.iter().take(50) {
        features.update(regime);
    }

    group.bench_function("single_update_warm", |b| {
        let mut feat = RegimeTransitionFeatures::new(4, 0.1);
        // Pre-warm
        for &regime in regimes.iter().take(50) {
            feat.update(regime);
        }

        let mut idx = 50;
        b.iter(|| {
            let result = feat.update(black_box(regimes[idx % regimes.len()]));
            black_box(result);
            idx += 1;
        });
    });

    group.finish();
}

/// Benchmark Transition features full sequence
fn bench_transition_features_sequence(c: &mut Criterion) {
    let mut group = c.benchmark_group("transition_features_sequence");
    group.measurement_time(Duration::from_secs(10));

    let regimes = generate_regime_sequence(500, 50);

    group.bench_function("500_regimes_full_pipeline", |b| {
        b.iter(|| {
            let mut features = RegimeTransitionFeatures::new(4, 0.1);
            for &regime in regimes.iter() {
                let result = features.update(black_box(regime));
                black_box(result);
            }
        });
    });

    group.finish();
}

// ============================================================================
// Adaptive Features Benchmarks (Agent D16, indices 221-224)
// ============================================================================

/// Benchmark Adaptive features cold start
fn bench_adaptive_features_cold(c: &mut Criterion) {
    let mut group = c.benchmark_group("adaptive_features");
    group.measurement_time(Duration::from_secs(5));

    let bars = generate_extraction_bars(100, 51);

    group.bench_function("single_update_cold", |b| {
        b.iter(|| {
            let mut features = RegimeAdaptiveFeatures::new(20, 100_000.0, 14);
            let result = features.update(
                black_box(MarketRegime::Normal),
                black_box(0.01),
                black_box(50_000.0),
                black_box(&bars),
            );
            black_box(result);
        });
    });

    group.finish();
}

/// Benchmark Adaptive features warm state
fn bench_adaptive_features_warm(c: &mut Criterion) {
    let mut group = c.benchmark_group("adaptive_features_warm");
    group.measurement_time(Duration::from_secs(5));

    let bars = generate_extraction_bars(100, 52);
    let regimes = generate_regime_sequence(100, 53);

    // Warm up with 20 updates
    let mut features = RegimeAdaptiveFeatures::new(20, 100_000.0, 14);
    for i in 0..20 {
        features.update(regimes[i], 0.01, 50_000.0, &bars);
    }

    group.bench_function("single_update_warm", |b| {
        let mut feat = RegimeAdaptiveFeatures::new(20, 100_000.0, 14);
        // Pre-warm
        for i in 0..20 {
            feat.update(regimes[i], 0.01, 50_000.0, &bars);
        }

        let mut idx = 20;
        b.iter(|| {
            let result = feat.update(
                black_box(regimes[idx % regimes.len()]),
                black_box(0.01),
                black_box(50_000.0),
                black_box(&bars),
            );
            black_box(result);
            idx += 1;
        });
    });

    group.finish();
}

/// Benchmark Adaptive features full sequence
fn bench_adaptive_features_sequence(c: &mut Criterion) {
    let mut group = c.benchmark_group("adaptive_features_sequence");
    group.measurement_time(Duration::from_secs(10));

    let bars = generate_extraction_bars(100, 54);
    let regimes = generate_regime_sequence(500, 55);

    group.bench_function("500_updates_full_pipeline", |b| {
        b.iter(|| {
            let mut features = RegimeAdaptiveFeatures::new(20, 100_000.0, 14);
            for &regime in regimes.iter() {
                let result = features.update(
                    black_box(regime),
                    black_box(0.01),
                    black_box(50_000.0),
                    black_box(&bars),
                );
                black_box(result);
            }
        });
    });

    group.finish();
}

// ============================================================================
// Criterion Configuration
// ============================================================================

criterion_group!(
    benches,
    // CUSUM Features (Agent D13)
    bench_cusum_features_cold,
    bench_cusum_features_warm,
    bench_cusum_features_sequence,
    // ADX Features (Agent D14)
    bench_adx_features_cold,
    bench_adx_features_warm,
    bench_adx_features_sequence,
    // Transition Features (Agent D15)
    bench_transition_features_cold,
    bench_transition_features_warm,
    bench_transition_features_sequence,
    // Adaptive Features (Agent D16)
    bench_adaptive_features_cold,
    bench_adaptive_features_warm,
    bench_adaptive_features_sequence,
);

criterion_main!(benches);