optirs-learned 0.3.1

// Resource monitoring and analysis for optimization coordinator
//
// This module provides comprehensive resource monitoring capabilities including
// CPU, memory, GPU, disk, and network usage tracking with alerting and
// optimization recommendations.

use super::config::*;
use crate::OptimizerError as OptimError;
use scirs2_core::numeric::Float;
use std::collections::{HashMap, VecDeque};
use std::fmt::Debug;
use std::time::{Duration, Instant, SystemTime};

/// Result type for resource operations
type Result<T> = std::result::Result<T, OptimError>;

/// Resource analyzer for system monitoring
#[derive(Debug)]
pub struct ResourceAnalyzer<T: Float + Debug + Send + Sync + Debug> {
    /// Configuration
    config: ResourceMonitoringConfig,

    /// Resource monitors
    monitors: HashMap<ResourceType, ResourceMonitor<T>>,

    /// Usage history
    usage_history: VecDeque<SystemResourceSnapshot<T>>,

    /// Alert manager
    alert_manager: ResourceAlertManager<T>,

    /// Performance correlator
    performance_correlator: ResourcePerformanceCorrelator<T>,

    /// Optimization advisor
    optimization_advisor: ResourceOptimizationAdvisor<T>,

    /// Current system state
    current_state: SystemResourceState<T>,
}

/// Resource types being monitored
#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash)]
pub enum ResourceType {
    CPU,
    Memory,
    GPU,
    Disk,
    Network,
    Power,
}

/// Individual resource monitor
#[derive(Debug)]
pub struct ResourceMonitor<T: Float + Debug + Send + Sync + Debug> {
    /// Resource type
    resource_type: ResourceType,

    /// Current usage
    current_usage: ResourceUsage<T>,

    /// Usage history
    usage_history: VecDeque<ResourceUsage<T>>,

    /// Statistics
    statistics: ResourceStatistics<T>,

    /// Thresholds
    thresholds: ResourceThresholds,

    /// Last update time
    last_update: SystemTime,
}

/// Resource usage information
#[derive(Debug, Clone)]
pub struct ResourceUsage<T: Float + Debug + Send + Sync + 'static> {
    /// Timestamp
    pub timestamp: SystemTime,

    /// Resource type
    pub resource_type: ResourceType,

    /// Utilization percentage (0-100)
    pub utilization: T,

    /// Absolute usage value
    pub absolute_usage: T,

    /// Total available
    pub total_available: T,

    /// Usage rate (change per second)
    pub usage_rate: T,

    /// Resource-specific metrics
    pub specific_metrics: ResourceSpecificMetrics<T>,
}

/// Resource-specific metrics
#[derive(Debug, Clone)]
pub enum ResourceSpecificMetrics<T: Float + Debug + Send + Sync + 'static> {
    /// CPU metrics
    CPU {
        core_count: usize,
        frequency: T,
        load_average: (T, T, T), // 1min, 5min, 15min
        context_switches: u64,
        interrupts: u64,
    },

    /// Memory metrics
    Memory {
        total_ram: usize,
        available_ram: usize,
        cached: usize,
        buffers: usize,
        swap_total: usize,
        swap_used: usize,
        page_faults: u64,
    },

    /// GPU metrics
    GPU {
        gpu_memory_total: usize,
        gpu_memory_used: usize,
        gpu_temperature: T,
        power_usage: T,
        compute_utilization: T,
        memory_bandwidth: T,
    },

    /// Disk metrics
    Disk {
        total_space: usize,
        used_space: usize,
        read_rate: T,
        write_rate: T,
        iops: T,
        queue_depth: T,
    },

    /// Network metrics
    Network {
        bandwidth_total: T,
        rx_rate: T,
        tx_rate: T,
        packets_rx: u64,
        packets_tx: u64,
        errors: u64,
        dropped: u64,
    },

    /// Power metrics
    Power {
        total_power: T,
        cpu_power: T,
        gpu_power: T,
        efficiency: T,
        temperature: T,
    },
}

/// Resource statistics
#[derive(Debug, Clone)]
pub struct ResourceStatistics<T: Float + Debug + Send + Sync + 'static> {
    /// Average utilization
    pub avg_utilization: T,

    /// Peak utilization
    pub peak_utilization: T,

    /// Minimum utilization
    pub min_utilization: T,

    /// Standard deviation
    pub std_deviation: T,

    /// 95th percentile
    pub p95_utilization: T,

    /// 99th percentile
    pub p99_utilization: T,

    /// Trend direction
    pub trend_direction: TrendDirection,

    /// Stability score
    pub stability_score: T,
}

/// Trend direction for resource usage
#[derive(Debug, Clone, Copy)]
pub enum TrendDirection {
    Increasing,
    Decreasing,
    Stable,
    Oscillating,
    Unknown,
}

/// System-wide resource snapshot
#[derive(Debug, Clone)]
pub struct SystemResourceSnapshot<T: Float + Debug + Send + Sync + 'static> {
    /// Snapshot timestamp
    pub timestamp: SystemTime,

    /// Individual resource usages
    pub resource_usages: HashMap<ResourceType, ResourceUsage<T>>,

    /// System load indicator
    pub system_load: SystemLoad<T>,

    /// Performance impact
    pub performance_impact: PerformanceImpact<T>,

    /// Resource contention
    pub contention: ResourceContention<T>,
}

/// System load indicators
#[derive(Debug, Clone)]
pub struct SystemLoad<T: Float + Debug + Send + Sync + 'static> {
    /// Overall system load (0-1)
    pub overall_load: T,

    /// Load category
    pub load_category: LoadCategory,

    /// Bottleneck resources
    pub bottlenecks: Vec<ResourceType>,

    /// Load balance score
    pub balance_score: T,
}

/// System load categories
#[derive(Debug, Clone, Copy)]
pub enum LoadCategory {
    Light,    // < 30%
    Moderate, // 30-60%
    Heavy,    // 60-85%
    Critical, // > 85%
}

/// Performance impact assessment
#[derive(Debug, Clone)]
pub struct PerformanceImpact<T: Float + Debug + Send + Sync + 'static> {
    /// Impact score (0-1)
    pub impact_score: T,

    /// Affected components
    pub affected_components: Vec<String>,

    /// Performance degradation
    pub degradation: T,

    /// Recovery time estimate
    pub recovery_estimate: Duration,
}

/// Resource contention analysis
#[derive(Debug, Clone)]
pub struct ResourceContention<T: Float + Debug + Send + Sync + 'static> {
    /// Contention level (0-1)
    pub contention_level: T,

    /// Competing processes
    pub competing_processes: Vec<ProcessInfo>,

    /// Contention type
    pub contention_type: ContentionType,

    /// Resolution suggestions
    pub resolution_suggestions: Vec<String>,
}

/// Process information for contention analysis
#[derive(Debug, Clone)]
pub struct ProcessInfo {
    /// Process ID
    pub pid: u32,

    /// Process name
    pub name: String,

    /// CPU usage
    pub cpu_usage: f32,

    /// Memory usage
    pub memory_usage: usize,

    /// Priority
    pub priority: i32,
}

/// Types of resource contention
#[derive(Debug, Clone, Copy)]
pub enum ContentionType {
    CPUBound,
    MemoryBound,
    IOBound,
    NetworkBound,
    Mixed,
}

/// Resource alert manager
#[derive(Debug)]
pub struct ResourceAlertManager<T: Float + Debug + Send + Sync + Debug> {
    /// Alert configuration
    config: AnomalyAlertConfig,

    /// Active alerts
    active_alerts: HashMap<ResourceType, ResourceAlert<T>>,

    /// Alert history
    alert_history: VecDeque<ResourceAlert<T>>,

    /// Notification throttle
    notification_throttle: HashMap<ResourceType, SystemTime>,
}

/// Resource alert
#[derive(Debug, Clone)]
pub struct ResourceAlert<T: Float + Debug + Send + Sync + 'static> {
    /// Alert ID
    pub alert_id: String,

    /// Resource type
    pub resource_type: ResourceType,

    /// Alert severity
    pub severity: AlertSeverity,

    /// Alert type
    pub alert_type: ResourceAlertType,

    /// Current value
    pub current_value: T,

    /// Threshold value
    pub threshold_value: T,

    /// Alert timestamp
    pub timestamp: SystemTime,

    /// Alert message
    pub message: String,

    /// Suggested actions
    pub suggested_actions: Vec<String>,
}

/// Types of resource alerts
#[derive(Debug, Clone, Copy)]
pub enum ResourceAlertType {
    HighUtilization,
    LowUtilization,
    RapidIncrease,
    RapidDecrease,
    Threshold,
    Anomaly,
    Contention,
    Failure,
}

/// Performance correlation with resource usage
#[derive(Debug)]
pub struct ResourcePerformanceCorrelator<T: Float + Debug + Send + Sync + Debug> {
    /// Correlation matrices
    correlation_matrices: HashMap<ResourceType, CorrelationMatrix<T>>,

    /// Performance history
    performance_history: VecDeque<PerformanceResourcePair<T>>,

    /// Correlation strength
    correlation_strength: HashMap<ResourceType, T>,

    /// Lag analysis
    lag_analysis: HashMap<ResourceType, Duration>,
}

/// Correlation matrix for resource-performance relationships
#[derive(Debug, Clone)]
pub struct CorrelationMatrix<T: Float + Debug + Send + Sync + 'static> {
    /// Correlation coefficient (-1 to 1)
    pub correlation_coefficient: T,

    /// P-value for significance
    pub p_value: T,

    /// Confidence interval
    pub confidence_interval: (T, T),

    /// Sample size
    pub sample_size: usize,

    /// R-squared value
    pub r_squared: T,
}

/// Performance-resource data pair
#[derive(Debug, Clone)]
pub struct PerformanceResourcePair<T: Float + Debug + Send + Sync + 'static> {
    /// Timestamp
    pub timestamp: SystemTime,

    /// Performance metric value
    pub performance_value: T,

    /// Resource usage value
    pub resource_value: T,

    /// Resource type
    pub resource_type: ResourceType,
}

/// Resource optimization advisor
#[derive(Debug)]
pub struct ResourceOptimizationAdvisor<T: Float + Debug + Send + Sync + Debug> {
    /// Optimization rules
    optimization_rules: Vec<OptimizationRule<T>>,

    /// Historical optimizations
    optimization_history: VecDeque<OptimizationRecommendation<T>>,

    /// Effectiveness tracking
    effectiveness_tracker: EffectivenessTracker<T>,
}

/// Optimization rule
#[derive(Debug, Clone)]
pub struct OptimizationRule<T: Float + Debug + Send + Sync + 'static> {
    /// Rule name
    pub name: String,

    /// Trigger conditions
    pub trigger_conditions: Vec<TriggerCondition<T>>,

    /// Recommended actions
    pub actions: Vec<OptimizationAction>,

    /// Expected impact
    pub expected_impact: T,

    /// Confidence level
    pub confidence: T,
}

/// Trigger condition for optimization
#[derive(Debug, Clone)]
pub struct TriggerCondition<T: Float + Debug + Send + Sync + 'static> {
    /// Resource type
    pub resource_type: ResourceType,

    /// Condition type
    pub condition_type: ConditionType,

    /// Threshold value
    pub threshold: T,

    /// Duration requirement
    pub duration: Duration,
}

/// Condition types for triggers
#[derive(Debug, Clone, Copy)]
pub enum ConditionType {
    GreaterThan,
    LessThan,
    Equal,
    Between(f64, f64),
    Trending(TrendDirection),
}

/// Optimization actions
#[derive(Debug, Clone)]
pub enum OptimizationAction {
    /// Increase batch size
    IncreaseBatchSize { factor: f64 },

    /// Decrease batch size
    DecreaseBatchSize { factor: f64 },

    /// Adjust learning rate
    AdjustLearningRate { factor: f64 },

    /// Enable gradient accumulation
    EnableGradientAccumulation { steps: usize },

    /// Use mixed precision
    UseMixedPrecision,

    /// Increase parallelism
    IncreaseParallelism { workers: usize },

    /// Decrease parallelism
    DecreaseParallelism { workers: usize },

    /// Memory optimization
    OptimizeMemory,

    /// Disk optimization
    OptimizeDisk,

    /// Network optimization
    OptimizeNetwork,

    /// Custom action
    Custom { name: String, parameters: HashMap<String, String> },
}

/// Optimization recommendation
#[derive(Debug, Clone)]
pub struct OptimizationRecommendation<T: Float + Debug + Send + Sync + 'static> {
    /// Recommendation ID
    pub id: String,

    /// Timestamp
    pub timestamp: SystemTime,

    /// Triggered rule
    pub rule_name: String,

    /// Recommended actions
    pub actions: Vec<OptimizationAction>,

    /// Expected impact
    pub expected_impact: T,

    /// Confidence level
    pub confidence: T,

    /// Implementation status
    pub status: RecommendationStatus,

    /// Actual impact (if implemented)
    pub actual_impact: Option<T>,
}

/// Status of optimization recommendations
#[derive(Debug, Clone, Copy)]
pub enum RecommendationStatus {
    Pending,
    Implemented,
    Rejected,
    Expired,
}

/// Effectiveness tracking for optimizations
#[derive(Debug)]
pub struct EffectivenessTracker<T: Float + Debug + Send + Sync + Debug> {
    /// Implementation tracking
    implementations: HashMap<String, ImplementationResult<T>>,

    /// Success rate by rule
    success_rates: HashMap<String, T>,

    /// Impact measurements
    impact_measurements: VecDeque<ImpactMeasurement<T>>,
}

/// Implementation result tracking
#[derive(Debug, Clone)]
pub struct ImplementationResult<T: Float + Debug + Send + Sync + 'static> {
    /// Recommendation ID
    pub recommendation_id: String,

    /// Implementation timestamp
    pub implementation_time: SystemTime,

    /// Before metrics
    pub before_metrics: HashMap<ResourceType, T>,

    /// After metrics
    pub after_metrics: HashMap<ResourceType, T>,

    /// Performance improvement
    pub performance_improvement: T,

    /// Success indicator
    pub success: bool,
}

/// Impact measurement
#[derive(Debug, Clone)]
pub struct ImpactMeasurement<T: Float + Debug + Send + Sync + 'static> {
    /// Measurement timestamp
    pub timestamp: SystemTime,

    /// Rule name
    pub rule_name: String,

    /// Measured impact
    pub measured_impact: T,

    /// Expected impact
    pub expected_impact: T,

    /// Accuracy score
    pub accuracy: T,
}

/// Current system resource state
#[derive(Debug, Clone)]
pub struct SystemResourceState<T: Float + Debug + Send + Sync + 'static> {
    /// Overall health score
    pub health_score: T,

    /// Resource availability
    pub resource_availability: HashMap<ResourceType, T>,

    /// System capacity
    pub system_capacity: SystemCapacity<T>,

    /// Performance headroom
    pub performance_headroom: T,

    /// Optimization opportunities
    pub optimization_opportunities: Vec<OptimizationOpportunity<T>>,
}

/// System capacity information
#[derive(Debug, Clone)]
pub struct SystemCapacity<T: Float + Debug + Send + Sync + 'static> {
    /// Total system capacity
    pub total_capacity: T,

    /// Used capacity
    pub used_capacity: T,

    /// Available capacity
    pub available_capacity: T,

    /// Reserved capacity
    pub reserved_capacity: T,

    /// Capacity utilization efficiency
    pub efficiency: T,
}

/// Optimization opportunity
#[derive(Debug, Clone)]
pub struct OptimizationOpportunity<T: Float + Debug + Send + Sync + 'static> {
    /// Opportunity type
    pub opportunity_type: OpportunityType,

    /// Potential improvement
    pub potential_improvement: T,

    /// Implementation effort
    pub implementation_effort: EffortLevel,

    /// Risk level
    pub risk_level: RiskLevel,

    /// Description
    pub description: String,
}

/// Types of optimization opportunities
#[derive(Debug, Clone, Copy)]
pub enum OpportunityType {
    ResourceReallocation,
    LoadBalancing,
    CachingOptimization,
    ParallelizationImprovement,
    MemoryOptimization,
    IOOptimization,
    NetworkOptimization,
}

/// Implementation effort levels
#[derive(Debug, Clone, Copy)]
pub enum EffortLevel {
    Low,
    Medium,
    High,
}

/// Risk levels for optimizations
#[derive(Debug, Clone, Copy)]
pub enum RiskLevel {
    Low,
    Medium,
    High,
}

impl<T: Float + Debug + Send + Sync + 'static + Default + Clone> ResourceAnalyzer<T> {
    /// Create new resource analyzer
    pub fn new(config: ResourceMonitoringConfig) -> Result<Self> {
        let mut monitors = HashMap::new();

        // Create monitors for enabled resources
        if config.monitor_cpu {
            monitors.insert(ResourceType::CPU, ResourceMonitor::new(ResourceType::CPU)?);
        }
        if config.monitor_memory {
            monitors.insert(ResourceType::Memory, ResourceMonitor::new(ResourceType::Memory)?);
        }
        if config.monitor_gpu {
            monitors.insert(ResourceType::GPU, ResourceMonitor::new(ResourceType::GPU)?);
        }
        if config.monitor_disk {
            monitors.insert(ResourceType::Disk, ResourceMonitor::new(ResourceType::Disk)?);
        }
        if config.monitor_network {
            monitors.insert(ResourceType::Network, ResourceMonitor::new(ResourceType::Network)?);
        }

        Ok(Self {
            config: config.clone(),
            monitors,
            usage_history: VecDeque::new(),
            alert_manager: ResourceAlertManager::new(AnomalyAlertConfig::default())?,
            performance_correlator: ResourcePerformanceCorrelator::new(),
            optimization_advisor: ResourceOptimizationAdvisor::new()?,
            current_state: SystemResourceState::default(),
        })
    }

    /// Update resource usage
    pub fn update_resource_usage(&mut self) -> Result<SystemResourceSnapshot<T>> {
        let mut resource_usages = HashMap::new();

        // Update all monitors
        for (resource_type, monitor) in &mut self.monitors {
            let usage = monitor.update_usage()?;
            resource_usages.insert(*resource_type, usage);
        }

        // Create system snapshot
        let snapshot = SystemResourceSnapshot {
            timestamp: SystemTime::now(),
            resource_usages: resource_usages.clone(),
            system_load: self.calculate_system_load(&resource_usages)?,
            performance_impact: self.assess_performance_impact(&resource_usages)?,
            contention: self.analyze_contention(&resource_usages)?,
        };

        // Update history
        if self.usage_history.len() >= self.config.history_size {
            self.usage_history.pop_front();
        }
        self.usage_history.push_back(snapshot.clone());

        // Check for alerts
        self.alert_manager.check_alerts(&resource_usages)?;

        // Update system state
        self.update_system_state(&snapshot)?;

        Ok(snapshot)
    }

    /// Get current system state
    pub fn get_system_state(&self) -> &SystemResourceState<T> {
        &self.current_state
    }

    /// Get optimization recommendations
    pub fn get_optimization_recommendations(&self) -> Result<Vec<OptimizationRecommendation<T>>> {
        self.optimization_advisor.generate_recommendations(&self.current_state)
    }

    /// Correlate with performance metrics
    pub fn correlate_with_performance(&mut self, performance_value: T) -> Result<()> {
        for (resource_type, monitor) in &self.monitors {
            let resource_value = monitor.current_usage.utilization;
            self.performance_correlator.add_data_point(
                *resource_type,
                performance_value,
                resource_value,
            )?;
        }
        Ok(())
    }

    /// Calculate system load
    fn calculate_system_load(&self, usages: &HashMap<ResourceType, ResourceUsage<T>>) -> Result<SystemLoad<T>> {
        let mut total_utilization = T::zero();
        let mut count = 0;
        let mut bottlenecks = Vec::new();

        for (resource_type, usage) in usages {
            total_utilization = total_utilization + usage.utilization;
            count += 1;

            // Check for bottlenecks (> 80% utilization)
            if usage.utilization > scirs2_core::numeric::NumCast::from(80.0).unwrap_or_else(|| T::zero()) {
                bottlenecks.push(*resource_type);
            }
        }

        let overall_load = if count > 0 {
            total_utilization / scirs2_core::numeric::NumCast::from(count).unwrap_or_else(|| T::zero()) / scirs2_core::numeric::NumCast::from(100.0).unwrap_or_else(|| T::zero())
        } else {
            T::zero()
        };

        let load_category = if overall_load < scirs2_core::numeric::NumCast::from(0.3).unwrap_or_else(|| T::zero()) {
            LoadCategory::Light
        } else if overall_load < scirs2_core::numeric::NumCast::from(0.6).unwrap_or_else(|| T::zero()) {
            LoadCategory::Moderate
        } else if overall_load < scirs2_core::numeric::NumCast::from(0.85).unwrap_or_else(|| T::zero()) {
            LoadCategory::Heavy
        } else {
            LoadCategory::Critical
        };

        // Calculate balance score (lower variance = better balance)
        let variance = if count > 1 {
            let mean = total_utilization / scirs2_core::numeric::NumCast::from(count).unwrap_or_else(|| T::zero());
            let var_sum = usages.values()
                .map(|u| (u.utilization - mean) * (u.utilization - mean))
                .fold(T::zero(), |acc, x| acc + x);
            var_sum / scirs2_core::numeric::NumCast::from(count).unwrap_or_else(|| T::zero())
        } else {
            T::zero()
        };

        let balance_score = T::one() / (T::one() + variance.sqrt());

        Ok(SystemLoad {
            overall_load,
            load_category,
            bottlenecks,
            balance_score,
        })
    }

    /// Assess performance impact
    fn assess_performance_impact(&self, _usages: &HashMap<ResourceType, ResourceUsage<T>>) -> Result<PerformanceImpact<T>> {
        // Simplified implementation
        Ok(PerformanceImpact {
            impact_score: scirs2_core::numeric::NumCast::from(0.3).unwrap_or_else(|| T::zero()),
            affected_components: vec!["training".to_string()],
            degradation: scirs2_core::numeric::NumCast::from(0.1).unwrap_or_else(|| T::zero()),
            recovery_estimate: Duration::from_secs(60),
        })
    }

    /// Analyze resource contention
    fn analyze_contention(&self, _usages: &HashMap<ResourceType, ResourceUsage<T>>) -> Result<ResourceContention<T>> {
        // Simplified implementation
        Ok(ResourceContention {
            contention_level: scirs2_core::numeric::NumCast::from(0.2).unwrap_or_else(|| T::zero()),
            competing_processes: Vec::new(),
            contention_type: ContentionType::CPUBound,
            resolution_suggestions: vec![
                "Reduce batch size".to_string(),
                "Increase parallelism".to_string(),
            ],
        })
    }

    /// Update system state
    fn update_system_state(&mut self, snapshot: &SystemResourceSnapshot<T>) -> Result<()> {
        // Calculate health score
        let health_score = T::one() - snapshot.system_load.overall_load;

        // Update resource availability
        let mut resource_availability = HashMap::new();
        for (resource_type, usage) in &snapshot.resource_usages {
            let availability = T::one() - usage.utilization / scirs2_core::numeric::NumCast::from(100.0).unwrap_or_else(|| T::zero());
            resource_availability.insert(*resource_type, availability);
        }

        // Calculate system capacity
        let system_capacity = SystemCapacity {
            total_capacity: T::one(),
            used_capacity: snapshot.system_load.overall_load,
            available_capacity: T::one() - snapshot.system_load.overall_load,
            reserved_capacity: scirs2_core::numeric::NumCast::from(0.1).unwrap_or_else(|| T::zero()), // 10% reserved
            efficiency: snapshot.system_load.balance_score,
        };

        // Calculate performance headroom
        let performance_headroom = T::one() - snapshot.system_load.overall_load;

        // Generate optimization opportunities
        let optimization_opportunities = self.identify_optimization_opportunities(snapshot)?;

        self.current_state = SystemResourceState {
            health_score,
            resource_availability,
            system_capacity,
            performance_headroom,
            optimization_opportunities,
        };

        Ok(())
    }

    /// Identify optimization opportunities
    fn identify_optimization_opportunities(&self, _snapshot: &SystemResourceSnapshot<T>) -> Result<Vec<OptimizationOpportunity<T>>> {
        let mut opportunities = Vec::new();

        // Example opportunity: memory optimization
        opportunities.push(OptimizationOpportunity {
            opportunity_type: OpportunityType::MemoryOptimization,
            potential_improvement: scirs2_core::numeric::NumCast::from(0.15).unwrap_or_else(|| T::zero()),
            implementation_effort: EffortLevel::Medium,
            risk_level: RiskLevel::Low,
            description: "Enable gradient checkpointing to reduce memory usage".to_string(),
        });

        Ok(opportunities)
    }
}

impl<T: Float + Debug + Send + Sync + 'static + Default + Clone> ResourceMonitor<T> {
    /// Create new resource monitor
    pub fn new(resource_type: ResourceType) -> Result<Self> {
        Ok(Self {
            resource_type,
            current_usage: ResourceUsage::default_for_type(resource_type),
            usage_history: VecDeque::new(),
            statistics: ResourceStatistics::default(),
            thresholds: ResourceThresholds::default(),
            last_update: SystemTime::now(),
        })
    }

    /// Update resource usage
    pub fn update_usage(&mut self) -> Result<ResourceUsage<T>> {
        // Simulate resource usage collection
        let usage = self.collect_resource_usage()?;

        // Update history
        if self.usage_history.len() >= 1000 {
            self.usage_history.pop_front();
        }
        self.usage_history.push_back(usage.clone());

        // Update statistics
        self.update_statistics()?;

        self.current_usage = usage.clone();
        self.last_update = SystemTime::now();

        Ok(usage)
    }

    /// Collect actual resource usage
    fn collect_resource_usage(&self) -> Result<ResourceUsage<T>> {
        // Simplified resource collection - in real implementation would use system APIs
        let utilization = match self.resource_type {
            ResourceType::CPU => T::from(scirs2_core::random::random::<f32>() * 80.0).expect("unwrap failed"),
            ResourceType::Memory => T::from(scirs2_core::random::random::<f32>() * 60.0).expect("unwrap failed"),
            ResourceType::GPU => T::from(scirs2_core::random::random::<f32>() * 90.0).expect("unwrap failed"),
            ResourceType::Disk => T::from(scirs2_core::random::random::<f32>() * 40.0).expect("unwrap failed"),
            ResourceType::Network => T::from(scirs2_core::random::random::<f32>() * 30.0).expect("unwrap failed"),
            ResourceType::Power => T::from(scirs2_core::random::random::<f32>() * 70.0).expect("unwrap failed"),
        };

        Ok(ResourceUsage {
            timestamp: SystemTime::now(),
            resource_type: self.resource_type,
            utilization,
            absolute_usage: utilization * scirs2_core::numeric::NumCast::from(100.0).unwrap_or_else(|| T::zero()),
            total_available: scirs2_core::numeric::NumCast::from(100.0).unwrap_or_else(|| T::zero()),
            usage_rate: T::zero(),
            specific_metrics: ResourceSpecificMetrics::default_for_type(self.resource_type),
        })
    }

    /// Update statistics
    fn update_statistics(&mut self) -> Result<()> {
        if self.usage_history.is_empty() {
            return Ok(());
        }

        let utilizations: Vec<T> = self.usage_history.iter().map(|u| u.utilization).collect();

        let sum = utilizations.iter().fold(T::zero(), |acc, &x| acc + x);
        let avg = sum / T::from(utilizations.len()).expect("unwrap failed");

        let max = utilizations.iter().fold(T::zero(), |acc, &x| if x > acc { x } else { acc });
        let min = utilizations.iter().fold(scirs2_core::numeric::NumCast::from(100.0).unwrap_or_else(|| T::zero()), |acc, &x| if x < acc { x } else { acc });

        // Calculate standard deviation
        let variance = utilizations.iter()
            .map(|&x| (x - avg) * (x - avg))
            .fold(T::zero(), |acc, x| acc + x) / T::from(utilizations.len()).expect("unwrap failed");
        let std_dev = variance.sqrt();

        // Calculate percentiles (simplified)
        let p95 = max * scirs2_core::numeric::NumCast::from(0.95).unwrap_or_else(|| T::zero());
        let p99 = max * scirs2_core::numeric::NumCast::from(0.99).unwrap_or_else(|| T::zero());

        // Determine trend
        let trend_direction = if utilizations.len() >= 10 {
            let recent = &utilizations[utilizations.len()-5..];
            let older = &utilizations[utilizations.len()-10..utilizations.len()-5];

            let recent_avg = recent.iter().fold(T::zero(), |acc, &x| acc + x) / T::from(recent.len()).expect("unwrap failed");
            let older_avg = older.iter().fold(T::zero(), |acc, &x| acc + x) / T::from(older.len()).expect("unwrap failed");

            if recent_avg > older_avg * scirs2_core::numeric::NumCast::from(1.05).unwrap_or_else(|| T::zero()) {
                TrendDirection::Increasing
            } else if recent_avg < older_avg * scirs2_core::numeric::NumCast::from(0.95).unwrap_or_else(|| T::zero()) {
                TrendDirection::Decreasing
            } else {
                TrendDirection::Stable
            }
        } else {
            TrendDirection::Unknown
        };

        // Calculate stability score
        let stability_score = T::one() / (T::one() + std_dev / avg);

        self.statistics = ResourceStatistics {
            avg_utilization: avg,
            peak_utilization: max,
            min_utilization: min,
            std_deviation: std_dev,
            p95_utilization: p95,
            p99_utilization: p99,
            trend_direction,
            stability_score,
        };

        Ok(())
    }
}

impl<T: Float + Debug + Send + Sync + 'static + Default + Clone> ResourceAlertManager<T> {
    /// Create new alert manager
    pub fn new(config: AnomalyAlertConfig) -> Result<Self> {
        Ok(Self {
            config,
            active_alerts: HashMap::new(),
            alert_history: VecDeque::new(),
            notification_throttle: HashMap::new(),
        })
    }

    /// Check for alerts
    pub fn check_alerts(&mut self, usages: &HashMap<ResourceType, ResourceUsage<T>>) -> Result<()> {
        for (resource_type, usage) in usages {
            self.check_resource_alerts(*resource_type, usage)?;
        }
        Ok(())
    }

    /// Check alerts for specific resource
    fn check_resource_alerts(&mut self, resource_type: ResourceType, usage: &ResourceUsage<T>) -> Result<()> {
        // Check high utilization
        if usage.utilization > scirs2_core::numeric::NumCast::from(90.0).unwrap_or_else(|| T::zero()) {
            self.create_alert(
                resource_type,
                ResourceAlertType::HighUtilization,
                AlertSeverity::High,
                usage.utilization,
                scirs2_core::numeric::NumCast::from(90.0).unwrap_or_else(|| T::zero()),
                "High resource utilization detected".to_string(),
            )?;
        }

        // Check for rapid increases
        // (simplified - would need historical data in real implementation)

        Ok(())
    }

    /// Create new alert
    fn create_alert(
        &mut self,
        resource_type: ResourceType,
        alert_type: ResourceAlertType,
        severity: AlertSeverity,
        current_value: T,
        threshold_value: T,
        message: String,
    ) -> Result<()> {
        let alert = ResourceAlert {
            alert_id: format!("{:?}_{:?}_{}", resource_type, alert_type, SystemTime::now().duration_since(SystemTime::UNIX_EPOCH).expect("unwrap failed").as_secs()),
            resource_type,
            severity,
            alert_type,
            current_value,
            threshold_value,
            timestamp: SystemTime::now(),
            message,
            suggested_actions: self.get_suggested_actions(resource_type, alert_type),
        };

        self.active_alerts.insert(resource_type, alert.clone());
        self.alert_history.push_back(alert);

        if self.alert_history.len() > 1000 {
            self.alert_history.pop_front();
        }

        Ok(())
    }

    /// Get suggested actions for alert
    fn get_suggested_actions(&self, resource_type: ResourceType, alert_type: ResourceAlertType) -> Vec<String> {
        match (resource_type, alert_type) {
            (ResourceType::Memory, ResourceAlertType::HighUtilization) => vec![
                "Reduce batch size".to_string(),
                "Enable gradient checkpointing".to_string(),
                "Use mixed precision training".to_string(),
            ],
            (ResourceType::CPU, ResourceAlertType::HighUtilization) => vec![
                "Reduce number of workers".to_string(),
                "Optimize data loading".to_string(),
                "Use GPU acceleration".to_string(),
            ],
            _ => vec!["Monitor the situation".to_string()],
        }
    }
}

impl<T: Float + Debug + Send + Sync + 'static + Default + Clone> ResourcePerformanceCorrelator<T> {
    /// Create new correlator
    pub fn new() -> Self {
        Self {
            correlation_matrices: HashMap::new(),
            performance_history: VecDeque::new(),
            correlation_strength: HashMap::new(),
            lag_analysis: HashMap::new(),
        }
    }

    /// Add data point for correlation
    pub fn add_data_point(&mut self, resource_type: ResourceType, performance_value: T, resource_value: T) -> Result<()> {
        let data_point = PerformanceResourcePair {
            timestamp: SystemTime::now(),
            performance_value,
            resource_value,
            resource_type,
        };

        self.performance_history.push_back(data_point);
        if self.performance_history.len() > 10000 {
            self.performance_history.pop_front();
        }

        // Update correlation if we have enough data
        if self.performance_history.len() >= 30 {
            self.update_correlation(resource_type)?;
        }

        Ok(())
    }

    /// Update correlation analysis
    fn update_correlation(&mut self, resource_type: ResourceType) -> Result<()> {
        let relevant_data: Vec<_> = self.performance_history.iter()
            .filter(|p| p.resource_type == resource_type)
            .collect();

        if relevant_data.len() < 10 {
            return Ok(());
        }

        // Calculate correlation coefficient (simplified)
        let perf_values: Vec<T> = relevant_data.iter().map(|p| p.performance_value).collect();
        let resource_values: Vec<T> = relevant_data.iter().map(|p| p.resource_value).collect();

        let correlation_coef = self.calculate_correlation(&perf_values, &resource_values)?;

        let matrix = CorrelationMatrix {
            correlation_coefficient: correlation_coef,
            p_value: scirs2_core::numeric::NumCast::from(0.05).unwrap_or_else(|| T::zero()), // Simplified
            confidence_interval: (correlation_coef - scirs2_core::numeric::NumCast::from(0.1).unwrap_or_else(|| T::zero()), correlation_coef + scirs2_core::numeric::NumCast::from(0.1).unwrap_or_else(|| T::zero())),
            sample_size: relevant_data.len(),
            r_squared: correlation_coef * correlation_coef,
        };

        self.correlation_matrices.insert(resource_type, matrix);
        self.correlation_strength.insert(resource_type, correlation_coef.abs());

        Ok(())
    }

    /// Calculate correlation coefficient
    fn calculate_correlation(&self, x: &[T], y: &[T]) -> Result<T> {
        if x.len() != y.len() || x.is_empty() {
            return Ok(T::zero());
        }

        let n = T::from(x.len()).expect("unwrap failed");
        let sum_x = x.iter().fold(T::zero(), |acc, &val| acc + val);
        let sum_y = y.iter().fold(T::zero(), |acc, &val| acc + val);
        let mean_x = sum_x / n;
        let mean_y = sum_y / n;

        let mut numerator = T::zero();
        let mut sum_x_sq = T::zero();
        let mut sum_y_sq = T::zero();

        for i in 0..x.len() {
            let x_diff = x[i] - mean_x;
            let y_diff = y[i] - mean_y;
            numerator = numerator + x_diff * y_diff;
            sum_x_sq = sum_x_sq + x_diff * x_diff;
            sum_y_sq = sum_y_sq + y_diff * y_diff;
        }

        let denominator = (sum_x_sq * sum_y_sq).sqrt();
        if denominator == T::zero() {
            Ok(T::zero())
        } else {
            Ok(numerator / denominator)
        }
    }
}

impl<T: Float + Debug + Send + Sync + 'static + Default + Clone> ResourceOptimizationAdvisor<T> {
    /// Create new optimization advisor
    pub fn new() -> Result<Self> {
        let optimization_rules = vec![
            OptimizationRule {
                name: "High Memory Usage".to_string(),
                trigger_conditions: vec![
                    TriggerCondition {
                        resource_type: ResourceType::Memory,
                        condition_type: ConditionType::GreaterThan,
                        threshold: scirs2_core::numeric::NumCast::from(80.0).unwrap_or_else(|| T::zero()),
                        duration: Duration::from_secs(60),
                    }
                ],
                actions: vec![
                    OptimizationAction::DecreaseBatchSize { factor: 0.8 },
                    OptimizationAction::UseMixedPrecision,
                ],
                expected_impact: scirs2_core::numeric::NumCast::from(0.3).unwrap_or_else(|| T::zero()),
                confidence: scirs2_core::numeric::NumCast::from(0.8).unwrap_or_else(|| T::zero()),
            },
            // Add more rules...
        ];

        Ok(Self {
            optimization_rules,
            optimization_history: VecDeque::new(),
            effectiveness_tracker: EffectivenessTracker::new(),
        })
    }

    /// Generate optimization recommendations
    pub fn generate_recommendations(&self, system_state: &SystemResourceState<T>) -> Result<Vec<OptimizationRecommendation<T>>> {
        let mut recommendations = Vec::new();

        for rule in &self.optimization_rules {
            if self.check_rule_triggers(rule, system_state)? {
                let recommendation = OptimizationRecommendation {
                    id: format!("rec_{}_{}", rule.name, SystemTime::now().duration_since(SystemTime::UNIX_EPOCH).expect("unwrap failed").as_secs()),
                    timestamp: SystemTime::now(),
                    rule_name: rule.name.clone(),
                    actions: rule.actions.clone(),
                    expected_impact: rule.expected_impact,
                    confidence: rule.confidence,
                    status: RecommendationStatus::Pending,
                    actual_impact: None,
                };
                recommendations.push(recommendation);
            }
        }

        Ok(recommendations)
    }

    /// Check if rule triggers are met
    fn check_rule_triggers(&self, rule: &OptimizationRule<T>, system_state: &SystemResourceState<T>) -> Result<bool> {
        for condition in &rule.trigger_conditions {
            let resource_availability = system_state.resource_availability.get(&condition.resource_type)
                .unwrap_or(&T::one());
            let utilization = T::one() - *resource_availability;
            let utilization_percent = utilization * scirs2_core::numeric::NumCast::from(100.0).unwrap_or_else(|| T::zero());

            match condition.condition_type {
                ConditionType::GreaterThan => {
                    if utilization_percent <= condition.threshold {
                        return Ok(false);
                    }
                },
                ConditionType::LessThan => {
                    if utilization_percent >= condition.threshold {
                        return Ok(false);
                    }
                },
                _ => {
                    // Other condition types...
                }
            }
        }
        Ok(true)
    }
}

impl<T: Float + Debug + Send + Sync + 'static + Default + Clone> EffectivenessTracker<T> {
    /// Create new effectiveness tracker
    pub fn new() -> Self {
        Self {
            implementations: HashMap::new(),
            success_rates: HashMap::new(),
            impact_measurements: VecDeque::new(),
        }
    }

    /// Track implementation result
    pub fn track_implementation(&mut self, result: ImplementationResult<T>) -> Result<()> {
        self.implementations.insert(result.recommendation_id.clone(), result.clone());

        // Update success rate for the rule
        let rule_name = result.recommendation_id.split('_').next().unwrap_or("unknown");
        let current_rate = self.success_rates.get(rule_name).unwrap_or(&T::zero());
        let new_rate = if result.success {
            *current_rate + scirs2_core::numeric::NumCast::from(0.1).unwrap_or_else(|| T::zero())
        } else {
            *current_rate - scirs2_core::numeric::NumCast::from(0.05).unwrap_or_else(|| T::zero())
        };
        self.success_rates.insert(rule_name.to_string(), new_rate.max(T::zero()).min(T::one()));

        Ok(())
    }
}

// Default implementations
impl<T: Float + Debug + Send + Sync + 'static> ResourceUsage<T> {
    /// Create default usage for resource type
    pub fn default_for_type(resource_type: ResourceType) -> Self {
        Self {
            timestamp: SystemTime::now(),
            resource_type,
            utilization: T::zero(),
            absolute_usage: T::zero(),
            total_available: T::from(100.0).unwrap_or(T::zero()),
            usage_rate: T::zero(),
            specific_metrics: ResourceSpecificMetrics::default_for_type(resource_type),
        }
    }
}

impl<T: Float + Debug + Send + Sync + 'static> ResourceSpecificMetrics<T> {
    /// Create default metrics for resource type
    pub fn default_for_type(resource_type: ResourceType) -> Self {
        match resource_type {
            ResourceType::CPU => ResourceSpecificMetrics::CPU {
                core_count: 8,
                frequency: T::from(3.0).unwrap_or(T::zero()),
                load_average: (T::zero(), T::zero(), T::zero()),
                context_switches: 0,
                interrupts: 0,
            },
            ResourceType::Memory => ResourceSpecificMetrics::Memory {
                total_ram: 16 * 1024 * 1024 * 1024, // 16GB
                available_ram: 8 * 1024 * 1024 * 1024, // 8GB
                cached: 1024 * 1024 * 1024, // 1GB
                buffers: 512 * 1024 * 1024, // 512MB
                swap_total: 4 * 1024 * 1024 * 1024, // 4GB
                swap_used: 0,
                page_faults: 0,
            },
            ResourceType::GPU => ResourceSpecificMetrics::GPU {
                gpu_memory_total: 8 * 1024 * 1024 * 1024, // 8GB
                gpu_memory_used: 0,
                gpu_temperature: T::from(40.0).unwrap_or(T::zero()),
                power_usage: T::from(150.0).unwrap_or(T::zero()),
                compute_utilization: T::zero(),
                memory_bandwidth: T::from(500.0).unwrap_or(T::zero()),
            },
            ResourceType::Disk => ResourceSpecificMetrics::Disk {
                total_space: 1024 * 1024 * 1024 * 1024, // 1TB
                used_space: 0,
                read_rate: T::zero(),
                write_rate: T::zero(),
                iops: T::zero(),
                queue_depth: T::zero(),
            },
            ResourceType::Network => ResourceSpecificMetrics::Network {
                bandwidth_total: T::from(1000.0).unwrap_or(T::zero()), // 1Gbps
                rx_rate: T::zero(),
                tx_rate: T::zero(),
                packets_rx: 0,
                packets_tx: 0,
                errors: 0,
                dropped: 0,
            },
            ResourceType::Power => ResourceSpecificMetrics::Power {
                total_power: T::from(500.0).unwrap_or(T::zero()),
                cpu_power: T::from(100.0).unwrap_or(T::zero()),
                gpu_power: T::from(200.0).unwrap_or(T::zero()),
                efficiency: T::from(0.9).unwrap_or(T::zero()),
                temperature: T::from(45.0).unwrap_or(T::zero()),
            },
        }
    }
}

impl<T: Float + Debug + Send + Sync + 'static> Default for ResourceStatistics<T> {
    fn default() -> Self {
        Self {
            avg_utilization: T::zero(),
            peak_utilization: T::zero(),
            min_utilization: T::zero(),
            std_deviation: T::zero(),
            p95_utilization: T::zero(),
            p99_utilization: T::zero(),
            trend_direction: TrendDirection::Unknown,
            stability_score: T::one(),
        }
    }
}

impl<T: Float + Debug + Send + Sync + 'static> Default for SystemResourceState<T> {
    fn default() -> Self {
        Self {
            health_score: T::one(),
            resource_availability: HashMap::new(),
            system_capacity: SystemCapacity {
                total_capacity: T::one(),
                used_capacity: T::zero(),
                available_capacity: T::one(),
                reserved_capacity: T::from(0.1).unwrap_or(T::zero()),
                efficiency: T::one(),
            },
            performance_headroom: T::one(),
            optimization_opportunities: Vec::new(),
        }
    }
}

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

    #[test]
    fn test_resource_analyzer_creation() {
        let config = ResourceMonitoringConfig::default();
        let analyzer = ResourceAnalyzer::<f32>::new(config);
        assert!(analyzer.is_ok());
    }

    #[test]
    fn test_resource_monitor_creation() {
        let monitor = ResourceMonitor::<f32>::new(ResourceType::CPU);
        assert!(monitor.is_ok());
    }

    #[test]
    fn test_resource_usage_default() {
        let usage = ResourceUsage::<f32>::default_for_type(ResourceType::Memory);
        assert_eq!(usage.resource_type, ResourceType::Memory);
        assert_eq!(usage.utilization, 0.0);
    }

    #[test]
    fn test_correlation_calculation() {
        let correlator = ResourcePerformanceCorrelator::<f32>::new();
        let x = vec![1.0, 2.0, 3.0, 4.0, 5.0];
        let y = vec![2.0, 4.0, 6.0, 8.0, 10.0];
        let correlation = correlator.calculate_correlation(&x, &y).expect("unwrap failed");
        assert!((correlation - 1.0).abs() < 0.01); // Should be close to 1.0 for perfect correlation
    }

    #[test]
    fn test_optimization_advisor() {
        let advisor = ResourceOptimizationAdvisor::<f32>::new();
        assert!(advisor.is_ok());

        let advisor = advisor.expect("unwrap failed");
        assert!(!advisor.optimization_rules.is_empty());
    }

    #[test]
    fn test_system_load_categories() {
        assert!(matches!(LoadCategory::Light, LoadCategory::Light));
        assert!(matches!(LoadCategory::Critical, LoadCategory::Critical));
    }
}