//! Real-time monitoring system for SciRS2 integration
//!
//! This module provides real-time metrics collection, alert management,
//! and historical data tracking for comprehensive monitoring.

// Framework infrastructure - components designed for future use
#![allow(dead_code)]
use super::{
    config::{AlertSeverity, ComparisonType},
    event_system::ScirS2Event,
};
use std::collections::HashMap;
use std::time::{Duration, Instant};

/// SciRS2 monitoring system
#[derive(Debug)]
pub struct ScirS2MonitoringSystem {
    /// Real-time metrics
    pub real_time_metrics: HashMap<String, f64>,

    /// Historical data points
    pub historical_data: Vec<MonitoringDataPoint>,

    /// Alert conditions
    pub alert_conditions: Vec<AlertCondition>,

    /// Active alerts
    pub active_alerts: Vec<ActiveAlert>,

    /// Monitoring configuration
    config: MonitoringConfig,

    /// Data retention settings
    retention: DataRetentionSettings,

    /// Metric aggregators
    aggregators: HashMap<String, MetricAggregator>,
}

/// Monitoring configuration
#[derive(Debug, Clone)]
pub struct MonitoringConfig {
    /// Enable real-time monitoring
    pub enabled: bool,

    /// Metrics collection interval
    pub collection_interval: Duration,

    /// Alert check interval
    pub alert_check_interval: Duration,

    /// Maximum historical data points
    pub max_historical_points: usize,

    /// Enable metric aggregation
    pub enable_aggregation: bool,

    /// Alert throttling duration
    pub alert_throttle_duration: Duration,
}

/// Data retention settings
#[derive(Debug, Clone)]
pub struct DataRetentionSettings {
    /// Retain raw data for this duration
    pub raw_data_retention: Duration,

    /// Retain aggregated data for this duration
    pub aggregated_data_retention: Duration,

    /// Compression threshold for historical data
    pub compression_threshold: usize,

    /// Enable automatic cleanup
    pub auto_cleanup: bool,
}

/// Monitoring data point
#[derive(Debug, Clone)]
pub struct MonitoringDataPoint {
    /// Timestamp
    pub timestamp: Instant,

    /// Metric name
    pub metric_name: String,

    /// Metric value
    pub value: f64,

    /// Additional context
    pub context: HashMap<String, String>,

    /// Data source
    pub source: String,
}

/// Alert condition
#[derive(Debug, Clone)]
pub struct AlertCondition {
    /// Unique condition ID
    pub id: String,

    /// Metric name to monitor
    pub metric_name: String,

    /// Alert threshold
    pub threshold: f64,

    /// Comparison type
    pub comparison: ComparisonType,

    /// Alert severity
    pub severity: AlertSeverity,

    /// Alert description
    pub description: String,

    /// Enabled status
    pub enabled: bool,

    /// Cooldown period
    pub cooldown: Duration,

    /// Last triggered time
    pub last_triggered: Option<Instant>,
}

/// Active alert
#[derive(Debug, Clone)]
pub struct ActiveAlert {
    /// Alert condition that triggered this
    pub condition: AlertCondition,

    /// When the alert was triggered
    pub triggered_at: Instant,

    /// Current metric value that triggered the alert
    pub current_value: f64,

    /// Whether the alert has been acknowledged
    pub acknowledged: bool,

    /// Acknowledgment timestamp
    pub acknowledged_at: Option<Instant>,

    /// Alert count (for repeated alerts)
    pub count: u32,
}

/// Metric aggregator for statistical analysis
#[derive(Debug, Clone)]
pub struct MetricAggregator {
    /// Metric name
    pub name: String,

    /// All values in current window
    pub values: Vec<f64>,

    /// Window size
    pub window_size: usize,

    /// Aggregation statistics
    pub stats: AggregationStats,

    /// Last update timestamp
    pub last_update: Instant,
}

/// Aggregation statistics
#[derive(Debug, Clone)]
pub struct AggregationStats {
    /// Minimum value
    pub min: f64,

    /// Maximum value
    pub max: f64,

    /// Average value
    pub avg: f64,

    /// Standard deviation
    pub std_dev: f64,

    /// 95th percentile
    pub p95: f64,

    /// 99th percentile
    pub p99: f64,

    /// Count of values
    pub count: usize,
}

/// Monitoring dashboard data
#[derive(Debug, Clone)]
pub struct DashboardData {
    /// Current metrics snapshot
    pub current_metrics: HashMap<String, f64>,

    /// Alert summary
    pub alert_summary: AlertSummary,

    /// Top metrics by activity
    pub top_metrics: Vec<TopMetric>,

    /// System health score
    pub health_score: f64,

    /// Trend analysis
    pub trends: HashMap<String, TrendAnalysis>,
}

/// Alert summary information
#[derive(Debug, Clone)]
pub struct AlertSummary {
    /// Total active alerts
    pub total_active: usize,

    /// Alerts by severity
    pub by_severity: HashMap<String, usize>,

    /// Recent alert activity
    pub recent_activity: Vec<RecentAlertActivity>,
}

/// Top metric information
#[derive(Debug, Clone)]
pub struct TopMetric {
    /// Metric name
    pub name: String,

    /// Current value
    pub value: f64,

    /// Change from previous period
    pub change: f64,

    /// Activity level (0.0 to 1.0)
    pub activity: f64,
}

/// Recent alert activity
#[derive(Debug, Clone)]
pub struct RecentAlertActivity {
    /// Alert condition ID
    pub condition_id: String,

    /// Activity type
    pub activity_type: AlertActivityType,

    /// Timestamp
    pub timestamp: Instant,

    /// Value at the time
    pub value: f64,
}

/// Alert activity types
#[derive(Debug, Clone)]
pub enum AlertActivityType {
    Triggered,
    Resolved,
    Acknowledged,
    Escalated,
}

/// Trend analysis result
#[derive(Debug, Clone)]
pub struct TrendAnalysis {
    /// Trend direction
    pub direction: TrendDirection,

    /// Trend strength (0.0 to 1.0)
    pub strength: f64,

    /// Confidence in the trend (0.0 to 1.0)
    pub confidence: f64,

    /// Predicted next value
    pub predicted_value: Option<f64>,
}

/// Trend directions
#[derive(Debug, Clone, PartialEq)]
pub enum TrendDirection {
    Increasing,
    Decreasing,
    Stable,
    Volatile,
}

impl ScirS2MonitoringSystem {
    /// Create new monitoring system
    pub fn new() -> Self {
        Self {
            real_time_metrics: HashMap::new(),
            historical_data: Vec::new(),
            alert_conditions: Vec::new(),
            active_alerts: Vec::new(),
            config: MonitoringConfig::default(),
            retention: DataRetentionSettings::default(),
            aggregators: HashMap::new(),
        }
    }

    /// Update a real-time metric
    pub fn update_metric(&mut self, name: String, value: f64) {
        self.update_metric_with_context(name, value, HashMap::new());
    }

    /// Update metric with additional context
    pub fn update_metric_with_context(
        &mut self,
        name: String,
        value: f64,
        context: HashMap<String, String>,
    ) {
        let now = Instant::now();

        // Update real-time metrics
        self.real_time_metrics.insert(name.clone(), value);

        // Add to historical data
        let data_point = MonitoringDataPoint {
            timestamp: now,
            metric_name: name.clone(),
            value,
            context,
            source: "scirs2_integration".to_string(),
        };
        self.historical_data.push(data_point);

        // Trim historical data if needed
        if self.historical_data.len() > self.config.max_historical_points {
            self.historical_data.remove(0);
        }

        // Update aggregator
        if self.config.enable_aggregation {
            self.update_aggregator(&name, value, now);
        }
    }

    /// Add alert condition
    pub fn add_alert_condition(&mut self, condition: AlertCondition) {
        self.alert_conditions.push(condition);
    }

    /// Remove alert condition
    pub fn remove_alert_condition(&mut self, condition_id: &str) {
        self.alert_conditions.retain(|c| c.id != condition_id);
        self.active_alerts
            .retain(|a| a.condition.id != condition_id);
    }

    /// Check all alert conditions
    pub fn check_alerts(&mut self) {
        let now = Instant::now();
        let mut alerts_to_trigger = Vec::new();
        let mut conditions_to_update = Vec::new();

        for (index, condition) in self.alert_conditions.iter().enumerate() {
            if !condition.enabled {
                continue;
            }

            // Check cooldown
            if let Some(last_triggered) = condition.last_triggered {
                if now.duration_since(last_triggered) < condition.cooldown {
                    continue;
                }
            }

            // Get current metric value
            if let Some(&current_value) = self.real_time_metrics.get(&condition.metric_name) {
                let alert_triggered = match condition.comparison {
                    ComparisonType::GreaterThan => current_value > condition.threshold,
                    ComparisonType::LessThan => current_value < condition.threshold,
                    ComparisonType::Equal => {
                        (current_value - condition.threshold).abs() < f64::EPSILON
                    }
                    ComparisonType::NotEqual => {
                        (current_value - condition.threshold).abs() > f64::EPSILON
                    }
                };

                if alert_triggered {
                    alerts_to_trigger.push((condition.clone(), current_value));
                    conditions_to_update.push(index);
                }
            }
        }

        // Trigger alerts and update conditions
        for (condition, current_value) in alerts_to_trigger {
            self.trigger_alert(condition, current_value, now);
        }

        for index in conditions_to_update {
            self.alert_conditions[index].last_triggered = Some(now);
        }

        // Check for alert resolution
        self.check_alert_resolution();
    }

    /// Process monitoring event
    pub fn process_event(&mut self, event: &ScirS2Event) {
        let _now = Instant::now();

        // Extract metrics from event
        match event {
            ScirS2Event::Allocation {
                size, allocator, ..
            } => {
                self.update_metric(format!("{}_allocations", allocator), 1.0);
                self.update_metric(format!("{}_allocated_bytes", allocator), *size as f64);
            }
            ScirS2Event::MemoryPressure {
                level,
                available_memory,
                ..
            } => {
                let pressure_value = match level {
                    crate::memory_profiler::allocation::PressureLevel::None => 0.0,
                    crate::memory_profiler::allocation::PressureLevel::Low => 0.25,
                    crate::memory_profiler::allocation::PressureLevel::Medium => 0.5,
                    crate::memory_profiler::allocation::PressureLevel::High => 0.75,
                    crate::memory_profiler::allocation::PressureLevel::Critical => 1.0,
                };
                self.update_metric("memory_pressure".to_string(), pressure_value);
                self.update_metric("available_memory".to_string(), *available_memory as f64);
            }
            ScirS2Event::PoolUtilizationChange {
                pool_id,
                new_utilization,
                ..
            } => {
                self.update_metric(format!("{}_utilization", pool_id), *new_utilization);
            }
            ScirS2Event::PerformanceDegradation {
                allocator,
                degradation_amount,
                ..
            } => {
                self.update_metric(
                    format!("{}_performance_degradation", allocator),
                    *degradation_amount,
                );
            }
            _ => {}
        }
    }

    /// Get dashboard data
    pub fn get_dashboard_data(&self) -> DashboardData {
        DashboardData {
            current_metrics: self.real_time_metrics.clone(),
            alert_summary: self.get_alert_summary(),
            top_metrics: self.get_top_metrics(),
            health_score: self.calculate_health_score(),
            trends: self.analyze_trends(),
        }
    }

    /// Get historical data for a metric
    pub fn get_metric_history(
        &self,
        metric_name: &str,
        duration: Duration,
    ) -> Vec<MonitoringDataPoint> {
        let cutoff = Instant::now() - duration;
        self.historical_data
            .iter()
            .filter(|point| point.metric_name == metric_name && point.timestamp > cutoff)
            .cloned()
            .collect()
    }

    /// Acknowledge an alert
    pub fn acknowledge_alert(&mut self, condition_id: &str) {
        let now = Instant::now();
        for alert in &mut self.active_alerts {
            if alert.condition.id == condition_id {
                alert.acknowledged = true;
                alert.acknowledged_at = Some(now);
            }
        }
    }

    /// Clear acknowledged alerts
    pub fn clear_acknowledged_alerts(&mut self) {
        self.active_alerts.retain(|alert| !alert.acknowledged);
    }

    /// Get aggregation statistics for a metric
    pub fn get_metric_stats(&self, metric_name: &str) -> Option<&AggregationStats> {
        self.aggregators.get(metric_name).map(|agg| &agg.stats)
    }

    /// Update monitoring configuration
    pub fn update_config(&mut self, config: MonitoringConfig) {
        self.config = config;
    }

    /// Cleanup old data based on retention settings
    pub fn cleanup_old_data(&mut self) {
        if !self.retention.auto_cleanup {
            return;
        }

        let now = Instant::now();
        let cutoff = now - self.retention.raw_data_retention;

        // Remove old historical data
        self.historical_data
            .retain(|point| point.timestamp > cutoff);

        // Remove resolved alerts older than retention period
        self.active_alerts.retain(|alert| {
            if alert.acknowledged {
                if let Some(ack_time) = alert.acknowledged_at {
                    now.duration_since(ack_time) < Duration::from_secs(7 * 24 * 60 * 60)
                } else {
                    true
                }
            } else {
                true
            }
        });
    }

    // Private helper methods

    fn update_aggregator(&mut self, name: &str, value: f64, timestamp: Instant) {
        let aggregator =
            self.aggregators
                .entry(name.to_string())
                .or_insert_with(|| MetricAggregator {
                    name: name.to_string(),
                    values: Vec::new(),
                    window_size: 1000,
                    stats: AggregationStats::default(),
                    last_update: timestamp,
                });

        aggregator.values.push(value);
        aggregator.last_update = timestamp;

        // Trim window if needed
        if aggregator.values.len() > aggregator.window_size {
            aggregator.values.remove(0);
        }

        // Update statistics
        aggregator.update_stats();
    }

    fn trigger_alert(&mut self, condition: AlertCondition, value: f64, timestamp: Instant) {
        // Check if alert already exists
        if let Some(existing_alert) = self
            .active_alerts
            .iter_mut()
            .find(|a| a.condition.id == condition.id)
        {
            existing_alert.count += 1;
            existing_alert.current_value = value;
            existing_alert.triggered_at = timestamp;
        } else {
            // Create new alert
            let alert = ActiveAlert {
                condition,
                triggered_at: timestamp,
                current_value: value,
                acknowledged: false,
                acknowledged_at: None,
                count: 1,
            };
            self.active_alerts.push(alert);
        }
    }

    fn check_alert_resolution(&mut self) {
        let mut resolved_alerts = Vec::new();

        for (index, alert) in self.active_alerts.iter().enumerate() {
            if let Some(&current_value) = self.real_time_metrics.get(&alert.condition.metric_name) {
                let alert_resolved = match alert.condition.comparison {
                    ComparisonType::GreaterThan => current_value <= alert.condition.threshold,
                    ComparisonType::LessThan => current_value >= alert.condition.threshold,
                    ComparisonType::Equal => {
                        (current_value - alert.condition.threshold).abs() > f64::EPSILON
                    }
                    ComparisonType::NotEqual => {
                        (current_value - alert.condition.threshold).abs() < f64::EPSILON
                    }
                };

                if alert_resolved {
                    resolved_alerts.push(index);
                }
            }
        }

        // Remove resolved alerts in reverse order to maintain indices
        for index in resolved_alerts.into_iter().rev() {
            self.active_alerts.remove(index);
        }
    }

    fn get_alert_summary(&self) -> AlertSummary {
        let mut by_severity = HashMap::new();

        for alert in &self.active_alerts {
            let severity_str = format!("{:?}", alert.condition.severity);
            *by_severity.entry(severity_str).or_insert(0) += 1;
        }

        // Get recent activity (simplified)
        let recent_activity = self
            .active_alerts
            .iter()
            .take(10)
            .map(|alert| RecentAlertActivity {
                condition_id: alert.condition.id.clone(),
                activity_type: AlertActivityType::Triggered,
                timestamp: alert.triggered_at,
                value: alert.current_value,
            })
            .collect();

        AlertSummary {
            total_active: self.active_alerts.len(),
            by_severity,
            recent_activity,
        }
    }

    fn get_top_metrics(&self) -> Vec<TopMetric> {
        let mut metrics: Vec<_> = self
            .real_time_metrics
            .iter()
            .map(|(name, &value)| {
                let change = self.calculate_metric_change(name);
                let activity = self.calculate_metric_activity(name);

                TopMetric {
                    name: name.clone(),
                    value,
                    change,
                    activity,
                }
            })
            .collect();

        // Sort by activity level
        metrics.sort_by(|a, b| {
            b.activity
                .partial_cmp(&a.activity)
                .unwrap_or(std::cmp::Ordering::Equal)
        });
        metrics.truncate(10); // Top 10 metrics

        metrics
    }

    fn calculate_health_score(&self) -> f64 {
        // Simplified health score calculation
        let mut score = 1.0;

        // Penalize active alerts
        let alert_penalty = self.active_alerts.len() as f64 * 0.1;
        score -= alert_penalty;

        // Consider metric trends
        let negative_trends = self
            .analyze_trends()
            .values()
            .filter(|trend| trend.direction == TrendDirection::Decreasing)
            .count() as f64;

        score -= negative_trends * 0.05;

        score.max(0.0)
    }

    fn analyze_trends(&self) -> HashMap<String, TrendAnalysis> {
        let mut trends = HashMap::new();

        for (metric_name, _) in &self.real_time_metrics {
            if let Some(trend) = self.analyze_metric_trend(metric_name) {
                trends.insert(metric_name.clone(), trend);
            }
        }

        trends
    }

    fn analyze_metric_trend(&self, metric_name: &str) -> Option<TrendAnalysis> {
        let recent_points: Vec<_> = self
            .historical_data
            .iter()
            .filter(|point| point.metric_name == metric_name)
            .rev()
            .take(20)
            .collect();

        if recent_points.len() < 5 {
            return None;
        }

        // Simplified trend analysis
        let values: Vec<f64> = recent_points.iter().map(|p| p.value).collect();
        let (slope, confidence) = self.calculate_linear_trend(&values);

        let direction = if slope > 0.1 {
            TrendDirection::Increasing
        } else if slope < -0.1 {
            TrendDirection::Decreasing
        } else {
            TrendDirection::Stable
        };

        Some(TrendAnalysis {
            direction,
            strength: slope.abs(),
            confidence,
            predicted_value: None, // Would implement prediction model
        })
    }

    fn calculate_linear_trend(&self, values: &[f64]) -> (f64, f64) {
        // Simplified linear regression
        let n = values.len() as f64;
        let x_sum: f64 = (0..values.len()).map(|i| i as f64).sum();
        let y_sum: f64 = values.iter().sum();
        let xy_sum: f64 = values.iter().enumerate().map(|(i, &y)| i as f64 * y).sum();
        let x2_sum: f64 = (0..values.len()).map(|i| (i as f64).powi(2)).sum();

        let slope = (n * xy_sum - x_sum * y_sum) / (n * x2_sum - x_sum.powi(2));
        let confidence = 0.8; // Simplified confidence calculation

        (slope, confidence)
    }

    fn calculate_metric_change(&self, metric_name: &str) -> f64 {
        // Calculate change from previous period (simplified)
        let recent_points: Vec<_> = self
            .historical_data
            .iter()
            .filter(|point| point.metric_name == metric_name)
            .rev()
            .take(2)
            .collect();

        if recent_points.len() == 2 {
            recent_points[0].value - recent_points[1].value
        } else {
            0.0
        }
    }

    fn calculate_metric_activity(&self, metric_name: &str) -> f64 {
        // Calculate activity level based on variance (simplified)
        let recent_points: Vec<_> = self
            .historical_data
            .iter()
            .filter(|point| point.metric_name == metric_name)
            .rev()
            .take(10)
            .map(|p| p.value)
            .collect();

        if recent_points.len() < 2 {
            return 0.0;
        }

        let mean = recent_points.iter().sum::<f64>() / recent_points.len() as f64;
        let variance = recent_points
            .iter()
            .map(|&x| (x - mean).powi(2))
            .sum::<f64>()
            / recent_points.len() as f64;

        variance.sqrt().min(1.0)
    }
}

impl Default for MonitoringConfig {
    fn default() -> Self {
        Self {
            enabled: true,
            collection_interval: Duration::from_secs(5),
            alert_check_interval: Duration::from_secs(10),
            max_historical_points: 10000,
            enable_aggregation: true,
            alert_throttle_duration: Duration::from_secs(60),
        }
    }
}

impl Default for DataRetentionSettings {
    fn default() -> Self {
        Self {
            raw_data_retention: Duration::from_secs(86400), // 1 day
            aggregated_data_retention: Duration::from_secs(86400 * 30), // 30 days
            compression_threshold: 1000,
            auto_cleanup: true,
        }
    }
}

impl Default for AggregationStats {
    fn default() -> Self {
        Self {
            min: f64::INFINITY,
            max: f64::NEG_INFINITY,
            avg: 0.0,
            std_dev: 0.0,
            p95: 0.0,
            p99: 0.0,
            count: 0,
        }
    }
}

impl MetricAggregator {
    fn update_stats(&mut self) {
        if self.values.is_empty() {
            return;
        }

        let mut sorted_values = self.values.clone();
        sorted_values.sort_by(|a, b| a.partial_cmp(b).unwrap_or(std::cmp::Ordering::Equal));

        self.stats.count = self.values.len();
        self.stats.min = sorted_values[0];
        self.stats.max = sorted_values[sorted_values.len() - 1];
        self.stats.avg = self.values.iter().sum::<f64>() / self.values.len() as f64;

        // Calculate standard deviation
        let variance = self
            .values
            .iter()
            .map(|&x| (x - self.stats.avg).powi(2))
            .sum::<f64>()
            / self.values.len() as f64;
        self.stats.std_dev = variance.sqrt();

        // Calculate percentiles
        if self.stats.count >= 20 {
            let p95_index = (self.stats.count as f64 * 0.95) as usize;
            let p99_index = (self.stats.count as f64 * 0.99) as usize;
            self.stats.p95 = sorted_values[p95_index.min(sorted_values.len() - 1)];
            self.stats.p99 = sorted_values[p99_index.min(sorted_values.len() - 1)];
        }
    }
}

// Helper trait for Duration extensions
trait DurationExt {
    fn from_days(days: u64) -> Duration;
}

impl DurationExt for Duration {
    fn from_days(days: u64) -> Duration {
        Duration::from_secs(days * 24 * 3600)
    }
}
