// Comprehensive metrics and monitoring for streaming optimization
//
// This module provides detailed performance metrics, monitoring capabilities,
// and analytics for streaming optimization systems.

use scirs2_core::numeric::Float;
use std::collections::{BTreeMap, HashMap};
use std::time::{Duration, SystemTime, UNIX_EPOCH};

#[allow(unused_imports)]
use crate::error::Result;

/// Streaming metrics collector and analyzer
#[derive(Debug)]
pub struct StreamingMetricsCollector<A: Float + Send + Sync> {
    /// Performance metrics
    performance_metrics: PerformanceMetrics<A>,

    /// Resource utilization metrics
    resource_metrics: ResourceMetrics,

    /// Quality metrics
    quality_metrics: QualityMetrics<A>,

    /// Business metrics
    business_metrics: BusinessMetrics<A>,

    /// Historical data storage
    historical_data: HistoricalMetrics<A>,

    /// Real-time dashboards
    dashboards: Vec<Dashboard>,

    /// Alert system
    alert_system: AlertSystem<A>,

    /// Metric aggregation settings
    aggregation_config: AggregationConfig,

    /// Export configuration
    export_config: ExportConfig,
}

/// Performance-related metrics
#[derive(Debug, Clone)]
pub struct PerformanceMetrics<A: Float + Send + Sync> {
    /// Throughput measurements
    pub throughput: ThroughputMetrics,

    /// Latency measurements
    pub latency: LatencyMetrics,

    /// Accuracy and convergence metrics
    pub accuracy: AccuracyMetrics<A>,

    /// Stability metrics
    pub stability: StabilityMetrics<A>,

    /// Efficiency metrics
    pub efficiency: EfficiencyMetrics<A>,
}

/// Throughput measurements
#[derive(Debug, Clone)]
pub struct ThroughputMetrics {
    /// Samples processed per second
    pub samples_per_second: f64,

    /// Updates per second
    pub updates_per_second: f64,

    /// Gradient computations per second
    pub gradients_per_second: f64,

    /// Peak throughput achieved
    pub peak_throughput: f64,

    /// Minimum throughput observed
    pub min_throughput: f64,

    /// Throughput variance
    pub throughput_variance: f64,

    /// Throughput trend (positive = increasing)
    pub throughput_trend: f64,
}

/// Latency measurements
#[derive(Debug, Clone)]
pub struct LatencyMetrics {
    /// End-to-end latency statistics
    pub end_to_end: LatencyStats,

    /// Gradient computation latency
    pub gradient_computation: LatencyStats,

    /// Update application latency
    pub update_application: LatencyStats,

    /// Communication latency (for distributed)
    pub communication: LatencyStats,

    /// Queue waiting time
    pub queue_wait_time: LatencyStats,

    /// Processing jitter
    pub jitter: f64,
}

/// Detailed latency statistics
#[derive(Debug, Clone)]
pub struct LatencyStats {
    /// Mean latency
    pub mean: Duration,

    /// Median latency
    pub median: Duration,

    /// 95th percentile
    pub p95: Duration,

    /// 99th percentile
    pub p99: Duration,

    /// 99.9th percentile
    pub p999: Duration,

    /// Maximum latency observed
    pub max: Duration,

    /// Minimum latency observed
    pub min: Duration,

    /// Standard deviation
    pub std_dev: Duration,
}

/// Accuracy and convergence metrics
#[derive(Debug, Clone)]
pub struct AccuracyMetrics<A: Float + Send + Sync> {
    /// Current loss value
    pub current_loss: A,

    /// Loss reduction rate
    pub loss_reduction_rate: A,

    /// Convergence rate
    pub convergence_rate: A,

    /// Prediction accuracy (if applicable)
    pub prediction_accuracy: Option<A>,

    /// Gradient magnitude
    pub gradient_magnitude: A,

    /// Parameter stability
    pub parameter_stability: A,

    /// Learning progress score
    pub learning_progress: A,
}

/// Model stability metrics
#[derive(Debug, Clone)]
pub struct StabilityMetrics<A: Float + Send + Sync> {
    /// Loss variance
    pub loss_variance: A,

    /// Gradient variance
    pub gradient_variance: A,

    /// Parameter drift
    pub parameter_drift: A,

    /// Oscillation detection
    pub oscillation_score: A,

    /// Divergence probability
    pub divergence_probability: A,

    /// Stability confidence
    pub stability_confidence: A,
}

/// Efficiency metrics
#[derive(Debug, Clone)]
pub struct EfficiencyMetrics<A: Float + Send + Sync> {
    /// Computational efficiency
    pub computational_efficiency: A,

    /// Memory efficiency
    pub memory_efficiency: A,

    /// Communication efficiency (for distributed)
    pub communication_efficiency: A,

    /// Energy efficiency (if measurable)
    pub energy_efficiency: Option<A>,

    /// Resource utilization score
    pub resource_utilization: A,

    /// Cost efficiency
    pub cost_efficiency: A,
}

/// Resource utilization metrics
#[derive(Debug, Clone)]
pub struct ResourceMetrics {
    /// CPU utilization
    pub cpu_utilization: f64,

    /// Memory usage
    pub memory_usage: MemoryUsage,

    /// GPU utilization (if applicable)
    pub gpu_utilization: Option<f64>,

    /// Network bandwidth usage
    pub network_bandwidth: f64,

    /// Disk I/O usage
    pub disk_io: f64,

    /// Thread utilization
    pub thread_utilization: f64,
}

/// Memory usage breakdown
#[derive(Debug, Clone)]
pub struct MemoryUsage {
    /// Total allocated memory (bytes)
    pub total_allocated: u64,

    /// Currently used memory (bytes)
    pub current_used: u64,

    /// Peak memory usage (bytes)
    pub peak_usage: u64,

    /// Memory fragmentation ratio
    pub fragmentation_ratio: f64,

    /// Garbage collection overhead
    pub gc_overhead: f64,

    /// Memory efficiency
    pub efficiency: f64,
}

/// Quality metrics for streaming optimization
#[derive(Debug, Clone)]
pub struct QualityMetrics<A: Float + Send + Sync> {
    /// Data quality score
    pub data_quality: A,

    /// Model quality metrics
    pub model_quality: ModelQuality<A>,

    /// Concept drift metrics
    pub concept_drift: ConceptDriftMetrics<A>,

    /// Anomaly detection metrics
    pub anomaly_detection: AnomalyMetrics<A>,

    /// Robustness metrics
    pub robustness: RobustnessMetrics<A>,
}

/// Model quality assessment
#[derive(Debug, Clone)]
pub struct ModelQuality<A: Float + Send + Sync> {
    /// Training quality score
    pub training_quality: A,

    /// Generalization ability
    pub generalization_score: A,

    /// Overfitting detection
    pub overfitting_score: A,

    /// Underfitting detection
    pub underfitting_score: A,

    /// Model complexity score
    pub complexity_score: A,
}

/// Concept drift monitoring metrics
#[derive(Debug, Clone)]
pub struct ConceptDriftMetrics<A: Float + Send + Sync> {
    /// Drift detection confidence
    pub drift_confidence: A,

    /// Drift magnitude
    pub drift_magnitude: A,

    /// Drift frequency
    pub drift_frequency: f64,

    /// Adaptation effectiveness
    pub adaptation_effectiveness: A,

    /// Time to detect drift
    pub detection_latency: Duration,
}

/// Anomaly detection metrics
#[derive(Debug, Clone)]
pub struct AnomalyMetrics<A: Float + Send + Sync> {
    /// Anomaly score
    pub anomaly_score: A,

    /// False positive rate
    pub false_positive_rate: A,

    /// False negative rate
    pub false_negative_rate: A,

    /// Detection accuracy
    pub detection_accuracy: A,

    /// Anomaly frequency
    pub anomaly_frequency: f64,
}

/// Model robustness metrics
#[derive(Debug, Clone)]
pub struct RobustnessMetrics<A: Float + Send + Sync> {
    /// Noise tolerance
    pub noise_tolerance: A,

    /// Adversarial robustness
    pub adversarial_robustness: A,

    /// Input perturbation sensitivity
    pub perturbation_sensitivity: A,

    /// Recovery capability
    pub recovery_capability: A,

    /// Fault tolerance
    pub fault_tolerance: A,
}

/// Business and operational metrics
#[derive(Debug, Clone)]
pub struct BusinessMetrics<A: Float + Send + Sync> {
    /// System availability
    pub availability: f64,

    /// Service level objectives (SLO) compliance
    pub slo_compliance: f64,

    /// Cost metrics
    pub cost_metrics: CostMetrics<A>,

    /// User satisfaction metrics
    pub user_satisfaction: Option<A>,

    /// Business value score
    pub business_value: A,
}

/// Cost-related metrics
#[derive(Debug, Clone)]
pub struct CostMetrics<A: Float + Send + Sync> {
    /// Computational cost
    pub computational_cost: A,

    /// Infrastructure cost
    pub infrastructure_cost: A,

    /// Energy cost
    pub energy_cost: A,

    /// Opportunity cost
    pub opportunity_cost: A,

    /// Total cost of ownership
    pub total_cost: A,
}

/// Historical metrics storage
#[derive(Debug)]
pub struct HistoricalMetrics<A: Float + Send + Sync> {
    /// Time-series data storage
    time_series: BTreeMap<u64, MetricsSnapshot<A>>,

    /// Aggregated historical data
    aggregated_data: HashMap<AggregationPeriod, Vec<AggregatedMetrics<A>>>,

    /// Retention policy
    retention_policy: RetentionPolicy,

    /// Compression settings
    compression_config: CompressionConfig,
}

/// Point-in-time metrics snapshot
#[derive(Debug, Clone)]
pub struct MetricsSnapshot<A: Float + Send + Sync> {
    /// Timestamp
    pub timestamp: u64,

    /// Performance metrics at this time
    pub performance: PerformanceMetrics<A>,

    /// Resource metrics at this time
    pub resource: ResourceMetrics,

    /// Quality metrics at this time
    pub quality: QualityMetrics<A>,

    /// Business metrics at this time
    pub business: BusinessMetrics<A>,
}

/// Aggregation periods for historical data
#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash)]
pub enum AggregationPeriod {
    Minute,
    Hour,
    Day,
    Week,
    Month,
}

/// Aggregated metrics over a time period
#[derive(Debug, Clone)]
pub struct AggregatedMetrics<A: Float + Send + Sync> {
    /// Time period start
    pub period_start: u64,

    /// Time period end  
    pub period_end: u64,

    /// Mean values
    pub mean: MetricsSnapshot<A>,

    /// Maximum values
    pub max: MetricsSnapshot<A>,

    /// Minimum values
    pub min: MetricsSnapshot<A>,

    /// Standard deviation
    pub std_dev: MetricsSnapshot<A>,
}

/// Data retention policy
#[derive(Debug, Clone)]
pub struct RetentionPolicy {
    /// Raw data retention (seconds)
    pub raw_data_retention: u64,

    /// Aggregated data retention by period
    pub aggregated_retention: HashMap<AggregationPeriod, u64>,

    /// Automatic cleanup enabled
    pub auto_cleanup: bool,

    /// Maximum storage size (bytes)
    pub max_storage_size: u64,
}

/// Data compression configuration
#[derive(Debug, Clone)]
pub struct CompressionConfig {
    /// Enable compression
    pub enabled: bool,

    /// Compression algorithm
    pub algorithm: CompressionAlgorithm,

    /// Compression ratio target
    pub target_ratio: f64,

    /// Lossy compression tolerance
    pub lossy_tolerance: f64,
}

/// Compression algorithms
#[derive(Debug, Clone, Copy)]
pub enum CompressionAlgorithm {
    None,
    Gzip,
    Lz4,
    Zstd,
    Custom,
}

/// Real-time dashboard
#[derive(Debug)]
pub struct Dashboard {
    /// Dashboard name
    pub name: String,

    /// Dashboard widgets
    pub widgets: Vec<Widget>,

    /// Update frequency
    pub update_frequency: Duration,

    /// Auto-refresh enabled
    pub auto_refresh: bool,
}

/// Dashboard widget
#[derive(Debug)]
pub struct Widget {
    /// Widget type
    pub widget_type: WidgetType,

    /// Metrics to display
    pub metrics: Vec<String>,

    /// Display configuration
    pub config: WidgetConfig,
}

/// Types of dashboard widgets
#[derive(Debug, Clone)]
pub enum WidgetType {
    LineChart,
    BarChart,
    Gauge,
    Table,
    Heatmap,
    Histogram,
    ScatterPlot,
    TextDisplay,
}

/// Widget configuration
#[derive(Debug, Clone)]
pub struct WidgetConfig {
    /// Widget title
    pub title: String,

    /// Time range to display
    pub time_range: Duration,

    /// Refresh rate
    pub refresh_rate: Duration,

    /// Color scheme
    pub color_scheme: String,

    /// Size and position
    pub layout: WidgetLayout,
}

/// Widget layout information
#[derive(Debug, Clone)]
pub struct WidgetLayout {
    /// X position
    pub x: u32,

    /// Y position
    pub y: u32,

    /// Width
    pub width: u32,

    /// Height
    pub height: u32,
}

/// Alert system for monitoring
#[derive(Debug)]
pub struct AlertSystem<A: Float + Send + Sync> {
    /// Alert rules
    pub rules: Vec<AlertRule<A>>,

    /// Active alerts
    pub active_alerts: Vec<Alert<A>>,

    /// Alert history
    pub alert_history: Vec<Alert<A>>,

    /// Notification channels
    pub notification_channels: Vec<NotificationChannel>,
}

/// Alert rule definition
#[derive(Debug, Clone)]
pub struct AlertRule<A: Float + Send + Sync> {
    /// Rule name
    pub name: String,

    /// Metric to monitor
    pub metric_path: String,

    /// Condition
    pub condition: AlertCondition<A>,

    /// Severity level
    pub severity: AlertSeverity,

    /// Evaluation frequency
    pub evaluation_frequency: Duration,

    /// Notification settings
    pub notifications: Vec<String>,
}

/// Alert conditions
#[derive(Debug, Clone)]
pub enum AlertCondition<A: Float + Send + Sync> {
    /// Threshold crossing
    Threshold {
        operator: ComparisonOperator,
        value: A,
    },

    /// Rate of change
    RateOfChange { threshold: A, time_window: Duration },

    /// Anomaly detection
    Anomaly { sensitivity: A },

    /// Custom condition
    Custom { expression: String },
}

/// Comparison operators for alerts
#[derive(Debug, Clone, Copy)]
pub enum ComparisonOperator {
    GreaterThan,
    LessThan,
    GreaterThanOrEqual,
    LessThanOrEqual,
    Equal,
    NotEqual,
}

/// Alert severity levels
#[derive(Debug, Clone, Copy)]
pub enum AlertSeverity {
    Critical,
    Warning,
    Info,
}

/// Active or historical alert
#[derive(Debug, Clone)]
pub struct Alert<A: Float + Send + Sync> {
    /// Alert ID
    pub id: String,

    /// Rule that triggered the alert
    pub rule_name: String,

    /// Timestamp when alert was triggered
    pub triggered_at: SystemTime,

    /// Timestamp when alert was resolved (if applicable)
    pub resolved_at: Option<SystemTime>,

    /// Current metric value
    pub current_value: A,

    /// Threshold that was breached
    pub threshold: A,

    /// Alert severity
    pub severity: AlertSeverity,

    /// Alert message
    pub message: String,
}

/// Notification channels
#[derive(Debug, Clone)]
pub enum NotificationChannel {
    Email {
        addresses: Vec<String>,
    },
    Webhook {
        url: String,
        headers: HashMap<String, String>,
    },
    Slack {
        webhook_url: String,
        channel: String,
    },
    PagerDuty {
        integration_key: String,
    },
    Custom {
        config: HashMap<String, String>,
    },
}

/// Metrics aggregation configuration
#[derive(Debug, Clone)]
pub struct AggregationConfig {
    /// Default aggregation functions
    pub default_functions: Vec<AggregationFunction>,

    /// Custom aggregations by metric
    pub custom_aggregations: HashMap<String, Vec<AggregationFunction>>,

    /// Aggregation intervals
    pub intervals: Vec<Duration>,

    /// Maximum aggregation window
    pub max_window: Duration,
}

/// Aggregation functions
#[derive(Debug, Clone, Copy)]
pub enum AggregationFunction {
    Mean,
    Median,
    Min,
    Max,
    Sum,
    Count,
    StdDev,
    Percentile(u8), // e.g., Percentile(95) for P95
}

/// Export configuration for metrics
#[derive(Debug, Clone)]
pub struct ExportConfig {
    /// Export formats
    pub formats: Vec<ExportFormat>,

    /// Export destinations
    pub destinations: Vec<ExportDestination>,

    /// Export frequency
    pub frequency: Duration,

    /// Batch size for exports
    pub batch_size: usize,
}

/// Export formats
#[derive(Debug, Clone)]
pub enum ExportFormat {
    Json,
    Csv,
    Parquet,
    Prometheus,
    InfluxDB,
    Custom { format: String },
}

/// Export destinations
#[derive(Debug, Clone)]
pub enum ExportDestination {
    File {
        path: String,
    },
    Database {
        connection_string: String,
    },
    S3 {
        bucket: String,
        prefix: String,
    },
    Http {
        endpoint: String,
        headers: HashMap<String, String>,
    },
    Kafka {
        topic: String,
        brokers: Vec<String>,
    },
}

impl<A: Float + Default + Clone + std::fmt::Debug + Send + Sync + Send + Sync>
    StreamingMetricsCollector<A>
{
    /// Create a new metrics collector
    pub fn new() -> Self {
        Self {
            performance_metrics: PerformanceMetrics::default(),
            resource_metrics: ResourceMetrics::default(),
            quality_metrics: QualityMetrics::default(),
            business_metrics: BusinessMetrics::default(),
            historical_data: HistoricalMetrics::new(),
            dashboards: Vec::new(),
            alert_system: AlertSystem::new(),
            aggregation_config: AggregationConfig::default(),
            export_config: ExportConfig::default(),
        }
    }

    /// Record a new metrics sample
    pub fn record_sample(&mut self, sample: MetricsSample<A>) -> Result<()> {
        // Update current metrics
        self.update_performance_metrics(&sample)?;
        self.update_resource_metrics(&sample)?;
        self.update_quality_metrics(&sample)?;
        self.update_business_metrics(&sample)?;

        // Store historical data
        let timestamp = SystemTime::now()
            .duration_since(UNIX_EPOCH)
            .unwrap()
            .as_secs();

        let snapshot = MetricsSnapshot {
            timestamp,
            performance: self.performance_metrics.clone(),
            resource: self.resource_metrics.clone(),
            quality: self.quality_metrics.clone(),
            business: self.business_metrics.clone(),
        };

        self.historical_data.store_snapshot(snapshot)?;

        // Check alerts
        self.alert_system.evaluate_rules(&sample)?;

        Ok(())
    }

    /// Get current metrics summary
    pub fn get_current_metrics(&self) -> MetricsSummary<A> {
        MetricsSummary {
            performance: self.performance_metrics.clone(),
            resource: self.resource_metrics.clone(),
            quality: self.quality_metrics.clone(),
            business: self.business_metrics.clone(),
            timestamp: SystemTime::now(),
        }
    }

    /// Get historical metrics for a time range
    pub fn get_historical_metrics(
        &self,
        start_time: SystemTime,
        end_time: SystemTime,
    ) -> Result<Vec<MetricsSnapshot<A>>> {
        self.historical_data.get_range(start_time, end_time)
    }

    /// Get aggregated metrics
    pub fn get_aggregated_metrics(
        &self,
        period: AggregationPeriod,
        start_time: SystemTime,
        end_time: SystemTime,
    ) -> Result<Vec<AggregatedMetrics<A>>> {
        self.historical_data
            .get_aggregated(period, start_time, end_time)
    }

    /// Export metrics to configured destinations
    pub fn export_metrics(&self) -> Result<()> {
        // Implementation would export to configured destinations
        Ok(())
    }

    fn update_performance_metrics(&mut self, sample: &MetricsSample<A>) -> Result<()> {
        // Update performance metrics based on _sample
        Ok(())
    }

    fn update_resource_metrics(&mut self, sample: &MetricsSample<A>) -> Result<()> {
        // Update resource metrics based on _sample
        Ok(())
    }

    fn update_quality_metrics(&mut self, sample: &MetricsSample<A>) -> Result<()> {
        // Update quality metrics based on _sample
        Ok(())
    }

    fn update_business_metrics(&mut self, sample: &MetricsSample<A>) -> Result<()> {
        // Update business metrics based on _sample
        Ok(())
    }
}

impl<A: Float + Default + Clone + std::fmt::Debug + Send + Sync + Send + Sync> Default
    for StreamingMetricsCollector<A>
{
    fn default() -> Self {
        Self::new()
    }
}

/// Individual metrics sample
#[derive(Debug, Clone)]
pub struct MetricsSample<A: Float + Send + Sync> {
    /// Timestamp of the sample
    pub timestamp: SystemTime,

    /// Loss value
    pub loss: A,

    /// Gradient magnitude
    pub gradient_magnitude: A,

    /// Processing time
    pub processing_time: Duration,

    /// Memory usage
    pub memory_usage: u64,

    /// Additional custom metrics
    pub custom_metrics: HashMap<String, A>,
}

/// Complete metrics summary
#[derive(Debug, Clone)]
pub struct MetricsSummary<A: Float + Send + Sync> {
    /// Performance metrics
    pub performance: PerformanceMetrics<A>,

    /// Resource metrics
    pub resource: ResourceMetrics,

    /// Quality metrics
    pub quality: QualityMetrics<A>,

    /// Business metrics
    pub business: BusinessMetrics<A>,

    /// Summary timestamp
    pub timestamp: SystemTime,
}

// Implement default traits for metrics structs
impl<A: Float + Default + Send + Sync + Send + Sync> Default for PerformanceMetrics<A> {
    fn default() -> Self {
        Self {
            throughput: ThroughputMetrics::default(),
            latency: LatencyMetrics::default(),
            accuracy: AccuracyMetrics::default(),
            stability: StabilityMetrics::default(),
            efficiency: EfficiencyMetrics::default(),
        }
    }
}

impl Default for ThroughputMetrics {
    fn default() -> Self {
        Self {
            samples_per_second: 0.0,
            updates_per_second: 0.0,
            gradients_per_second: 0.0,
            peak_throughput: 0.0,
            min_throughput: f64::MAX,
            throughput_variance: 0.0,
            throughput_trend: 0.0,
        }
    }
}

impl Default for LatencyMetrics {
    fn default() -> Self {
        Self {
            end_to_end: LatencyStats::default(),
            gradient_computation: LatencyStats::default(),
            update_application: LatencyStats::default(),
            communication: LatencyStats::default(),
            queue_wait_time: LatencyStats::default(),
            jitter: 0.0,
        }
    }
}

impl Default for LatencyStats {
    fn default() -> Self {
        Self {
            mean: Duration::from_micros(0),
            median: Duration::from_micros(0),
            p95: Duration::from_micros(0),
            p99: Duration::from_micros(0),
            p999: Duration::from_micros(0),
            max: Duration::from_micros(0),
            min: Duration::from_micros(u64::MAX),
            std_dev: Duration::from_micros(0),
        }
    }
}

impl<A: Float + Default + Send + Sync + Send + Sync> Default for AccuracyMetrics<A> {
    fn default() -> Self {
        Self {
            current_loss: A::default(),
            loss_reduction_rate: A::default(),
            convergence_rate: A::default(),
            prediction_accuracy: None,
            gradient_magnitude: A::default(),
            parameter_stability: A::default(),
            learning_progress: A::default(),
        }
    }
}

impl<A: Float + Default + Send + Sync + Send + Sync> Default for StabilityMetrics<A> {
    fn default() -> Self {
        Self {
            loss_variance: A::default(),
            gradient_variance: A::default(),
            parameter_drift: A::default(),
            oscillation_score: A::default(),
            divergence_probability: A::default(),
            stability_confidence: A::default(),
        }
    }
}

impl<A: Float + Default + Send + Sync + Send + Sync> Default for EfficiencyMetrics<A> {
    fn default() -> Self {
        Self {
            computational_efficiency: A::default(),
            memory_efficiency: A::default(),
            communication_efficiency: A::default(),
            energy_efficiency: None,
            resource_utilization: A::default(),
            cost_efficiency: A::default(),
        }
    }
}

impl Default for ResourceMetrics {
    fn default() -> Self {
        Self {
            cpu_utilization: 0.0,
            memory_usage: MemoryUsage::default(),
            gpu_utilization: None,
            network_bandwidth: 0.0,
            disk_io: 0.0,
            thread_utilization: 0.0,
        }
    }
}

impl Default for MemoryUsage {
    fn default() -> Self {
        Self {
            total_allocated: 0,
            current_used: 0,
            peak_usage: 0,
            fragmentation_ratio: 0.0,
            gc_overhead: 0.0,
            efficiency: 0.0,
        }
    }
}

impl<A: Float + Default + Send + Sync + Send + Sync> Default for QualityMetrics<A> {
    fn default() -> Self {
        Self {
            data_quality: A::default(),
            model_quality: ModelQuality::default(),
            concept_drift: ConceptDriftMetrics::default(),
            anomaly_detection: AnomalyMetrics::default(),
            robustness: RobustnessMetrics::default(),
        }
    }
}

impl<A: Float + Default + Send + Sync + Send + Sync> Default for ModelQuality<A> {
    fn default() -> Self {
        Self {
            training_quality: A::default(),
            generalization_score: A::default(),
            overfitting_score: A::default(),
            underfitting_score: A::default(),
            complexity_score: A::default(),
        }
    }
}

impl<A: Float + Default + Send + Sync + Send + Sync> Default for ConceptDriftMetrics<A> {
    fn default() -> Self {
        Self {
            drift_confidence: A::default(),
            drift_magnitude: A::default(),
            drift_frequency: 0.0,
            adaptation_effectiveness: A::default(),
            detection_latency: Duration::from_micros(0),
        }
    }
}

impl<A: Float + Default + Send + Sync + Send + Sync> Default for AnomalyMetrics<A> {
    fn default() -> Self {
        Self {
            anomaly_score: A::default(),
            false_positive_rate: A::default(),
            false_negative_rate: A::default(),
            detection_accuracy: A::default(),
            anomaly_frequency: 0.0,
        }
    }
}

impl<A: Float + Default + Send + Sync + Send + Sync> Default for RobustnessMetrics<A> {
    fn default() -> Self {
        Self {
            noise_tolerance: A::default(),
            adversarial_robustness: A::default(),
            perturbation_sensitivity: A::default(),
            recovery_capability: A::default(),
            fault_tolerance: A::default(),
        }
    }
}

impl<A: Float + Default + Send + Sync + Send + Sync> Default for BusinessMetrics<A> {
    fn default() -> Self {
        Self {
            availability: 0.0,
            slo_compliance: 0.0,
            cost_metrics: CostMetrics::default(),
            user_satisfaction: None,
            business_value: A::default(),
        }
    }
}

impl<A: Float + Default + Send + Sync + Send + Sync> Default for CostMetrics<A> {
    fn default() -> Self {
        Self {
            computational_cost: A::default(),
            infrastructure_cost: A::default(),
            energy_cost: A::default(),
            opportunity_cost: A::default(),
            total_cost: A::default(),
        }
    }
}

impl<A: Float + Send + Sync + Send + Sync> HistoricalMetrics<A> {
    fn new() -> Self {
        Self {
            time_series: BTreeMap::new(),
            aggregated_data: HashMap::new(),
            retention_policy: RetentionPolicy::default(),
            compression_config: CompressionConfig::default(),
        }
    }

    fn store_snapshot(&mut self, snapshot: MetricsSnapshot<A>) -> Result<()> {
        self.time_series.insert(snapshot.timestamp, snapshot);
        Ok(())
    }

    fn get_range(
        &self,
        start_time: SystemTime,
        end_time: SystemTime,
    ) -> Result<Vec<MetricsSnapshot<A>>> {
        let start_ts = start_time.duration_since(UNIX_EPOCH).unwrap().as_secs();
        let end_ts = end_time.duration_since(UNIX_EPOCH).unwrap().as_secs();

        let snapshots = self
            .time_series
            .range(start_ts..=end_ts)
            .map(|(_, snapshot)| snapshot.clone())
            .collect();

        Ok(snapshots)
    }

    fn get_aggregated(
        &self,
        period: AggregationPeriod,
        start_time: SystemTime,
        end_time: SystemTime,
    ) -> Result<Vec<AggregatedMetrics<A>>> {
        // Implementation would aggregate data for the specified _period
        Ok(Vec::new())
    }
}

impl<A: Float + Send + Sync + Send + Sync> AlertSystem<A> {
    fn new() -> Self {
        Self {
            rules: Vec::new(),
            active_alerts: Vec::new(),
            alert_history: Vec::new(),
            notification_channels: Vec::new(),
        }
    }

    fn evaluate_rules(&mut self, sample: &MetricsSample<A>) -> Result<()> {
        // Implementation would evaluate all alert rules
        Ok(())
    }
}

impl Default for RetentionPolicy {
    fn default() -> Self {
        let mut aggregated_retention = HashMap::new();
        aggregated_retention.insert(AggregationPeriod::Minute, 3600 * 24); // 1 day
        aggregated_retention.insert(AggregationPeriod::Hour, 3600 * 24 * 7); // 1 week
        aggregated_retention.insert(AggregationPeriod::Day, 3600 * 24 * 30); // 1 month
        aggregated_retention.insert(AggregationPeriod::Week, 3600 * 24 * 365); // 1 year
        aggregated_retention.insert(AggregationPeriod::Month, 3600 * 24 * 365 * 5); // 5 years

        Self {
            raw_data_retention: 3600 * 24, // 1 day
            aggregated_retention,
            auto_cleanup: true,
            max_storage_size: 1024 * 1024 * 1024 * 10, // 10GB
        }
    }
}

impl Default for CompressionConfig {
    fn default() -> Self {
        Self {
            enabled: true,
            algorithm: CompressionAlgorithm::Zstd,
            target_ratio: 0.3,
            lossy_tolerance: 0.01,
        }
    }
}

impl Default for AggregationConfig {
    fn default() -> Self {
        Self {
            default_functions: vec![
                AggregationFunction::Mean,
                AggregationFunction::Min,
                AggregationFunction::Max,
                AggregationFunction::Percentile(95),
            ],
            custom_aggregations: HashMap::new(),
            intervals: vec![
                Duration::from_secs(60),    // 1 minute
                Duration::from_secs(3600),  // 1 hour
                Duration::from_secs(86400), // 1 day
            ],
            max_window: Duration::from_secs(86400 * 30), // 30 days
        }
    }
}

impl Default for ExportConfig {
    fn default() -> Self {
        Self {
            formats: vec![ExportFormat::Json],
            destinations: vec![ExportDestination::File {
                path: "/tmp/streaming_metrics".to_string(),
            }],
            frequency: Duration::from_secs(300), // 5 minutes
            batch_size: 1000,
        }
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn test_metrics_collector_creation() {
        let collector = StreamingMetricsCollector::<f64>::new();
        assert_eq!(
            collector.performance_metrics.throughput.samples_per_second,
            0.0
        );
        assert!(collector.dashboards.is_empty());
    }

    #[test]
    fn test_metrics_sample() {
        let sample = MetricsSample {
            timestamp: SystemTime::now(),
            loss: 0.5f64,
            gradient_magnitude: 0.1f64,
            processing_time: Duration::from_millis(10),
            memory_usage: 1024,
            custom_metrics: HashMap::new(),
        };

        assert_eq!(sample.loss, 0.5f64);
        assert_eq!(sample.gradient_magnitude, 0.1f64);
    }

    #[test]
    fn test_latency_stats_default() {
        let stats = LatencyStats::default();
        assert_eq!(stats.mean, Duration::from_micros(0));
        assert_eq!(stats.min, Duration::from_micros(u64::MAX));
    }

    #[test]
    fn test_aggregation_period() {
        let periods = [
            AggregationPeriod::Minute,
            AggregationPeriod::Hour,
            AggregationPeriod::Day,
            AggregationPeriod::Week,
            AggregationPeriod::Month,
        ];

        assert_eq!(periods.len(), 5);
    }

    #[test]
    fn test_alert_severity() {
        let severities = [
            AlertSeverity::Critical,
            AlertSeverity::Warning,
            AlertSeverity::Info,
        ];

        assert_eq!(severities.len(), 3);
    }
}
