trustformers-mobile 0.1.1

//! Sustainable AI Framework for Mobile Devices
//!
//! Provides carbon footprint tracking, renewable energy-aware inference scheduling,
//! green AI metrics, sustainable model compression, and energy-optimal batch processing.

use std::sync::{Arc, Mutex};
use std::time::{Duration, SystemTime, UNIX_EPOCH};
use trustformers_core::errors::Result;
use trustformers_core::tensor::Tensor;

#[derive(Debug, Clone)]
pub struct SustainableAIConfig {
    pub carbon_intensity_threshold: f32, // gCO2/kWh
    pub renewable_energy_minimum: f32,   // 0.0 to 1.0
    pub energy_budget_per_hour: f32,     // Wh
    pub enable_carbon_tracking: bool,
    pub enable_renewable_scheduling: bool,
    pub green_metrics_interval: Duration,
    pub energy_optimization_level: EnergyOptimizationLevel,
}

#[derive(Debug, Clone)]
pub enum EnergyOptimizationLevel {
    Minimal,    // Basic energy tracking
    Moderate,   // Energy-aware scheduling
    Aggressive, // Maximum green optimization
    Adaptive,   // Dynamic based on conditions
}

impl Default for SustainableAIConfig {
    fn default() -> Self {
        Self {
            carbon_intensity_threshold: 400.0, // gCO2/kWh - global average
            renewable_energy_minimum: 0.3,     // 30% renewable minimum
            energy_budget_per_hour: 5.0,       // 5Wh per hour for mobile AI
            enable_carbon_tracking: true,
            enable_renewable_scheduling: true,
            green_metrics_interval: Duration::from_secs(300), // 5 minutes
            energy_optimization_level: EnergyOptimizationLevel::Moderate,
        }
    }
}

#[derive(Debug)]
pub struct CarbonFootprintTracker {
    config: SustainableAIConfig,
    metrics: Arc<Mutex<CarbonMetrics>>,
    energy_history: Arc<Mutex<Vec<EnergyMeasurement>>>,
    location_cache: Arc<Mutex<Option<GridLocation>>>,
}

#[derive(Debug, Clone, Default)]
pub struct CarbonMetrics {
    pub total_co2_grams: f32,
    pub inference_count: u64,
    pub total_energy_wh: f32,
    pub average_carbon_intensity: f32,
    pub renewable_percentage: f32,
    pub green_score: f32, // 0.0 to 1.0, higher is better
}

#[derive(Debug, Clone)]
pub struct EnergyMeasurement {
    pub timestamp: SystemTime,
    pub energy_consumed_wh: f32,
    pub carbon_intensity: f32,
    pub renewable_fraction: f32,
    pub operation_type: OperationType,
}

#[derive(Debug, Clone)]
pub enum OperationType {
    Inference,
    Training,
    ModelLoading,
    Optimization,
    DataProcessing,
}

#[derive(Debug, Clone)]
pub struct GridLocation {
    pub country_code: String,
    pub region: String,
    pub latitude: f32,
    pub longitude: f32,
    pub timezone: String,
}

impl CarbonFootprintTracker {
    pub fn new(config: SustainableAIConfig) -> Self {
        Self {
            config,
            metrics: Arc::new(Mutex::new(CarbonMetrics::default())),
            energy_history: Arc::new(Mutex::new(Vec::new())),
            location_cache: Arc::new(Mutex::new(None)),
        }
    }

    pub fn track_operation(
        &self,
        operation_type: OperationType,
        energy_consumed: f32,
        duration_ms: u64,
    ) -> Result<CarbonImpact> {
        let timestamp = SystemTime::now();
        let carbon_intensity = self.get_current_carbon_intensity()?;
        let renewable_fraction = self.get_renewable_fraction()?;

        let carbon_emission = energy_consumed * carbon_intensity / 1000.0; // Convert to grams
        let renewable_energy = energy_consumed * renewable_fraction;
        let fossil_energy = energy_consumed - renewable_energy;

        let measurement = EnergyMeasurement {
            timestamp,
            energy_consumed_wh: energy_consumed,
            carbon_intensity,
            renewable_fraction,
            operation_type: operation_type.clone(),
        };

        self.add_measurement(measurement)?;

        let impact = CarbonImpact {
            carbon_emission_grams: carbon_emission,
            energy_consumed_wh: energy_consumed,
            renewable_energy_wh: renewable_energy,
            fossil_energy_wh: fossil_energy,
            carbon_intensity,
            duration_ms,
            operation_type,
            sustainability_score: self
                .calculate_sustainability_score(carbon_intensity, renewable_fraction)?,
        };

        if let Ok(mut metrics) = self.metrics.lock() {
            metrics.total_co2_grams += carbon_emission;
            metrics.inference_count += 1;
            metrics.total_energy_wh += energy_consumed;
            metrics.average_carbon_intensity =
                (metrics.average_carbon_intensity + carbon_intensity) / 2.0;
            metrics.renewable_percentage =
                (metrics.renewable_percentage + renewable_fraction) / 2.0;
            metrics.green_score = self.calculate_green_score(&metrics)?;
        }

        Ok(impact)
    }

    fn get_current_carbon_intensity(&self) -> Result<f32> {
        // In production, this would query real-time grid data APIs
        // For now, we simulate based on time of day and location
        let hour = SystemTime::now()
            .duration_since(UNIX_EPOCH)
            .map_err(|_| {
                trustformers_core::TrustformersError::runtime_error(
                    "Time calculation failed".to_string(),
                )
            })?
            .as_secs()
            / 3600
            % 24;

        let base_intensity = match hour {
            6..=9 | 18..=21 => 450.0, // Peak hours - higher fossil fuel use
            10..=16 => 300.0,         // Solar peak - lower intensity
            22..=23 | 0..=5 => 350.0, // Night - wind dominance
            _ => 400.0,               // Default
        };

        // Add some variability
        let variability = (hour as f32 * 17.0).sin() * 50.0;
        Ok((base_intensity + variability).max(200.0).min(800.0))
    }

    fn get_renewable_fraction(&self) -> Result<f32> {
        // Simulate renewable energy fraction based on time and weather
        let hour = SystemTime::now()
            .duration_since(UNIX_EPOCH)
            .map_err(|_| {
                trustformers_core::TrustformersError::runtime_error(
                    "Time calculation failed".to_string(),
                )
            })?
            .as_secs()
            / 3600
            % 24;

        let solar_fraction = match hour {
            7..=17 => ((hour as f32 - 12.0).abs() / 6.0).cos().max(0.0) * 0.4,
            _ => 0.0,
        };

        let wind_fraction = 0.2 + (hour as f32 * 7.0).sin().abs() * 0.3;
        let hydro_fraction = 0.15;

        let total_renewable = (solar_fraction + wind_fraction + hydro_fraction).min(0.85);
        Ok(total_renewable)
    }

    fn calculate_sustainability_score(
        &self,
        carbon_intensity: f32,
        renewable_fraction: f32,
    ) -> Result<f32> {
        let carbon_score = (800.0 - carbon_intensity) / 600.0; // Normalize 200-800 range
        let renewable_score = renewable_fraction;
        let efficiency_score = if carbon_intensity < self.config.carbon_intensity_threshold {
            1.0
        } else {
            0.5
        };

        let score = (carbon_score * 0.4 + renewable_score * 0.4 + efficiency_score * 0.2)
            .max(0.0)
            .min(1.0);

        Ok(score)
    }

    fn calculate_green_score(&self, metrics: &CarbonMetrics) -> Result<f32> {
        if metrics.inference_count == 0 {
            return Ok(0.0);
        }

        let carbon_efficiency = (500.0 - metrics.average_carbon_intensity) / 300.0;
        let renewable_score = metrics.renewable_percentage;
        let energy_efficiency =
            1.0 / (1.0 + metrics.total_energy_wh / metrics.inference_count as f32);

        let score = (carbon_efficiency * 0.4 + renewable_score * 0.4 + energy_efficiency * 0.2)
            .max(0.0)
            .min(1.0);

        Ok(score)
    }

    fn add_measurement(&self, measurement: EnergyMeasurement) -> Result<()> {
        if let Ok(mut history) = self.energy_history.lock() {
            history.push(measurement);

            // Keep only last 1000 measurements
            if history.len() > 1000 {
                history.remove(0);
            }
        }
        Ok(())
    }

    pub fn get_carbon_metrics(&self) -> CarbonMetrics {
        if let Ok(metrics) = self.metrics.lock() {
            metrics.clone()
        } else {
            CarbonMetrics::default()
        }
    }

    pub fn get_hourly_report(&self) -> Result<HourlyReport> {
        let now = SystemTime::now();
        let hour_ago = now - Duration::from_secs(3600);

        if let Ok(history) = self.energy_history.lock() {
            let recent_measurements: Vec<_> =
                history.iter().filter(|m| m.timestamp >= hour_ago).collect();

            if recent_measurements.is_empty() {
                return Ok(HourlyReport::default());
            }

            let total_energy: f32 = recent_measurements.iter().map(|m| m.energy_consumed_wh).sum();
            let avg_carbon_intensity: f32 =
                recent_measurements.iter().map(|m| m.carbon_intensity).sum::<f32>()
                    / recent_measurements.len() as f32;
            let avg_renewable: f32 =
                recent_measurements.iter().map(|m| m.renewable_fraction).sum::<f32>()
                    / recent_measurements.len() as f32;

            let total_carbon = total_energy * avg_carbon_intensity / 1000.0;

            Ok(HourlyReport {
                total_energy_wh: total_energy,
                total_carbon_grams: total_carbon,
                average_carbon_intensity: avg_carbon_intensity,
                renewable_percentage: avg_renewable,
                operation_count: recent_measurements.len(),
                sustainability_score: self
                    .calculate_sustainability_score(avg_carbon_intensity, avg_renewable)?,
                energy_efficiency: total_energy / recent_measurements.len() as f32,
            })
        } else {
            Ok(HourlyReport::default())
        }
    }
}

#[derive(Debug, Clone)]
pub struct CarbonImpact {
    pub carbon_emission_grams: f32,
    pub energy_consumed_wh: f32,
    pub renewable_energy_wh: f32,
    pub fossil_energy_wh: f32,
    pub carbon_intensity: f32,
    pub duration_ms: u64,
    pub operation_type: OperationType,
    pub sustainability_score: f32,
}

#[derive(Debug, Clone, Default)]
pub struct HourlyReport {
    pub total_energy_wh: f32,
    pub total_carbon_grams: f32,
    pub average_carbon_intensity: f32,
    pub renewable_percentage: f32,
    pub operation_count: usize,
    pub sustainability_score: f32,
    pub energy_efficiency: f32,
}

#[derive(Debug)]
pub struct RenewableEnergyScheduler {
    config: SustainableAIConfig,
    scheduled_tasks: Arc<Mutex<Vec<ScheduledTask>>>,
    energy_forecast: Arc<Mutex<EnergyForecast>>,
}

#[derive(Debug, Clone)]
pub struct ScheduledTask {
    pub id: String,
    pub priority: TaskPriority,
    pub estimated_energy: f32,
    pub earliest_start: SystemTime,
    pub deadline: SystemTime,
    pub task_type: TaskType,
    pub renewable_requirement: f32,
}

#[derive(Debug, Clone)]
pub enum TaskPriority {
    Low,
    Medium,
    High,
    Critical,
}

#[derive(Debug, Clone)]
pub enum TaskType {
    BatchInference,
    ModelTraining,
    ModelOptimization,
    DataPreprocessing,
    BackgroundSync,
}

#[derive(Debug, Clone)]
pub struct EnergyForecast {
    pub hourly_renewable_fraction: Vec<f32>,
    pub hourly_carbon_intensity: Vec<f32>,
    pub forecast_timestamp: SystemTime,
    pub confidence_score: f32,
}

impl RenewableEnergyScheduler {
    pub fn new(config: SustainableAIConfig) -> Self {
        Self {
            config,
            scheduled_tasks: Arc::new(Mutex::new(Vec::new())),
            energy_forecast: Arc::new(Mutex::new(EnergyForecast::default())),
        }
    }

    pub fn schedule_task(&self, task: ScheduledTask) -> Result<SchedulingDecision> {
        let current_time = SystemTime::now();
        let renewable_fraction = self.get_current_renewable_fraction()?;

        if renewable_fraction >= task.renewable_requirement {
            return Ok(SchedulingDecision::ExecuteNow {
                task_id: task.id.clone(),
                estimated_carbon: self.estimate_carbon_impact(&task)?,
                renewable_fraction,
            });
        }

        let optimal_time = self.find_optimal_execution_time(&task)?;

        if let Ok(mut tasks) = self.scheduled_tasks.lock() {
            tasks.push(task.clone());
            tasks.sort_by_key(|t| t.earliest_start);
        }

        Ok(SchedulingDecision::Schedule {
            task_id: task.id.clone(),
            scheduled_time: optimal_time,
            estimated_carbon: self.estimate_carbon_impact(&task)?,
            reason: "Waiting for higher renewable energy availability".to_string(),
        })
    }

    fn find_optimal_execution_time(&self, task: &ScheduledTask) -> Result<SystemTime> {
        let forecast = if let Ok(forecast) = self.energy_forecast.lock() {
            forecast.clone()
        } else {
            self.generate_forecast()?
        };

        let current_hour = SystemTime::now()
            .duration_since(UNIX_EPOCH)
            .map_err(|_| {
                trustformers_core::TrustformersError::runtime_error(
                    "Time calculation failed".to_string(),
                )
            })?
            .as_secs()
            / 3600;

        let mut best_time = task.earliest_start;
        let mut best_score = 0.0f32;

        for (hour_offset, &renewable_fraction) in
            forecast.hourly_renewable_fraction.iter().enumerate()
        {
            let execution_time =
                task.earliest_start + Duration::from_secs(hour_offset as u64 * 3600);

            if execution_time > task.deadline {
                break;
            }

            let carbon_intensity =
                forecast.hourly_carbon_intensity.get(hour_offset).unwrap_or(&400.0);
            let score = renewable_fraction * 0.7 + (800.0 - carbon_intensity) / 800.0 * 0.3;

            if renewable_fraction >= task.renewable_requirement && score > best_score {
                best_score = score;
                best_time = execution_time;
            }
        }

        Ok(best_time)
    }

    fn generate_forecast(&self) -> Result<EnergyForecast> {
        let mut hourly_renewable = Vec::with_capacity(24);
        let mut hourly_carbon = Vec::with_capacity(24);

        for hour in 0..24 {
            // Simulate renewable energy forecast
            let solar_factor = if (6..=18).contains(&hour) {
                ((hour as f32 - 12.0).abs() / 6.0).cos().max(0.0) * 0.5
            } else {
                0.0
            };

            let wind_factor = 0.25 + (hour as f32 * 3.0).sin().abs() * 0.35;
            let base_renewable = 0.15; // Hydro and other

            let renewable_fraction = (solar_factor + wind_factor + base_renewable).min(0.9);
            hourly_renewable.push(renewable_fraction);

            // Carbon intensity inversely related to renewable fraction
            let carbon_intensity = 200.0 + (1.0 - renewable_fraction) * 400.0;
            hourly_carbon.push(carbon_intensity);
        }

        Ok(EnergyForecast {
            hourly_renewable_fraction: hourly_renewable,
            hourly_carbon_intensity: hourly_carbon,
            forecast_timestamp: SystemTime::now(),
            confidence_score: 0.8,
        })
    }

    fn get_current_renewable_fraction(&self) -> Result<f32> {
        let hour = SystemTime::now()
            .duration_since(UNIX_EPOCH)
            .map_err(|_| {
                trustformers_core::TrustformersError::runtime_error(
                    "Time calculation failed".to_string(),
                )
            })?
            .as_secs()
            / 3600
            % 24;

        let solar = if (7..=17).contains(&hour) {
            ((hour as f32 - 12.0).abs() / 5.0).cos().max(0.0) * 0.4
        } else {
            0.0
        };

        let wind = 0.2 + (hour as f32 * 5.0).sin().abs() * 0.25;
        let other = 0.15;

        Ok((solar + wind + other).min(0.85))
    }

    fn estimate_carbon_impact(&self, task: &ScheduledTask) -> Result<f32> {
        let carbon_intensity =
            match SystemTime::now().duration_since(UNIX_EPOCH).map(|d| d.as_secs() / 3600 % 24) {
                Ok(hour) => 200.0 + (1.0 - self.get_current_renewable_fraction()?) * 400.0,
                Err(_) => 400.0, // Default
            };

        Ok(task.estimated_energy * carbon_intensity / 1000.0)
    }

    pub fn get_pending_tasks(&self) -> Vec<ScheduledTask> {
        if let Ok(tasks) = self.scheduled_tasks.lock() {
            tasks.clone()
        } else {
            Vec::new()
        }
    }

    pub fn update_forecast(&self, forecast: EnergyForecast) -> Result<()> {
        if let Ok(mut current_forecast) = self.energy_forecast.lock() {
            *current_forecast = forecast;
        }
        Ok(())
    }
}

#[derive(Debug, Clone)]
pub enum SchedulingDecision {
    ExecuteNow {
        task_id: String,
        estimated_carbon: f32,
        renewable_fraction: f32,
    },
    Schedule {
        task_id: String,
        scheduled_time: SystemTime,
        estimated_carbon: f32,
        reason: String,
    },
    Reject {
        task_id: String,
        reason: String,
    },
}

impl Default for EnergyForecast {
    fn default() -> Self {
        Self {
            hourly_renewable_fraction: vec![0.3; 24],
            hourly_carbon_intensity: vec![400.0; 24],
            forecast_timestamp: SystemTime::now(),
            confidence_score: 0.5,
        }
    }
}

#[derive(Debug)]
pub struct SustainableModelCompression {
    config: SustainableAIConfig,
    compression_history: Arc<Mutex<Vec<CompressionEvent>>>,
}

#[derive(Debug, Clone)]
pub struct CompressionEvent {
    pub timestamp: SystemTime,
    pub original_size: usize,
    pub compressed_size: usize,
    pub energy_saved: f32,
    pub accuracy_loss: f32,
    pub compression_technique: CompressionTechnique,
}

#[derive(Debug, Clone)]
pub enum CompressionTechnique {
    GreenQuantization,
    EnergyAwarePruning,
    CarbonOptimalDistillation,
    SustainableSparsification,
}

impl SustainableModelCompression {
    pub fn new(config: SustainableAIConfig) -> Self {
        Self {
            config,
            compression_history: Arc::new(Mutex::new(Vec::new())),
        }
    }

    pub fn compress_for_sustainability(
        &self,
        model_data: &Tensor,
        target_energy_reduction: f32,
        max_accuracy_loss: f32,
    ) -> Result<SustainableCompressionResult> {
        let original_size = model_data.size() * std::mem::size_of::<f32>();
        let mut compressed_data = model_data.clone();
        let mut total_energy_saved = 0.0f32;
        let mut total_accuracy_loss = 0.0f32;

        // Apply green quantization
        if target_energy_reduction > 0.2 {
            let (quantized_data, energy_saved, accuracy_loss) =
                self.apply_green_quantization(&compressed_data)?;
            compressed_data = quantized_data;
            total_energy_saved += energy_saved;
            total_accuracy_loss += accuracy_loss;
        }

        // Apply energy-aware pruning
        if target_energy_reduction > 0.4 && total_accuracy_loss < max_accuracy_loss * 0.7 {
            let (pruned_data, energy_saved, accuracy_loss) =
                self.apply_energy_aware_pruning(&compressed_data)?;
            compressed_data = pruned_data;
            total_energy_saved += energy_saved;
            total_accuracy_loss += accuracy_loss;
        }

        // Apply sustainable sparsification if needed
        if total_energy_saved < target_energy_reduction
            && total_accuracy_loss < max_accuracy_loss * 0.8
        {
            let (sparse_data, energy_saved, accuracy_loss) =
                self.apply_sustainable_sparsification(&compressed_data)?;
            compressed_data = sparse_data;
            total_energy_saved += energy_saved;
            total_accuracy_loss += accuracy_loss;
        }

        let compressed_size = compressed_data.size() * std::mem::size_of::<f32>();
        let compression_ratio = compressed_size as f32 / original_size as f32;

        let event = CompressionEvent {
            timestamp: SystemTime::now(),
            original_size,
            compressed_size,
            energy_saved: total_energy_saved,
            accuracy_loss: total_accuracy_loss,
            compression_technique: CompressionTechnique::GreenQuantization,
        };

        self.add_compression_event(event)?;

        Ok(SustainableCompressionResult {
            compressed_model: compressed_data,
            compression_ratio,
            energy_reduction: total_energy_saved,
            accuracy_loss: total_accuracy_loss,
            carbon_impact_reduction: self.estimate_carbon_reduction(total_energy_saved)?,
            sustainability_score: self.calculate_compression_sustainability_score(
                compression_ratio,
                total_energy_saved,
                total_accuracy_loss,
            )?,
        })
    }

    fn apply_green_quantization(&self, data: &Tensor) -> Result<(Tensor, f32, f32)> {
        let size = data.size();
        let mut quantized_values = Vec::with_capacity(size);

        // Apply energy-optimal quantization (8-bit with green threshold)
        let data_vec = data.data()?;
        for &original_value in data_vec.iter() {
            let quantized_value = (original_value * 127.0).round() / 127.0;
            quantized_values.push(quantized_value);
        }

        let shape = data.shape();
        let quantized_tensor = Tensor::from_vec(quantized_values, &shape)?;
        let energy_saved = 0.25; // 25% energy reduction from 8-bit quantization
        let accuracy_loss = 0.02; // 2% typical accuracy loss

        Ok((quantized_tensor, energy_saved, accuracy_loss))
    }

    fn apply_energy_aware_pruning(&self, data: &Tensor) -> Result<(Tensor, f32, f32)> {
        let data_vec = data.data()?;

        // Calculate magnitude-based pruning threshold
        let mut magnitudes: Vec<f32> = data_vec.iter().map(|x| x.abs()).collect();
        magnitudes.sort_by(|a, b| a.partial_cmp(b).expect("Operation failed"));

        let pruning_threshold = magnitudes[data_vec.len() * 30 / 100]; // Prune bottom 30%

        let pruned_values: Vec<f32> = data_vec
            .iter()
            .map(
                |&value| {
                    if value.abs() > pruning_threshold {
                        value
                    } else {
                        0.0
                    }
                },
            )
            .collect();

        let shape = data.shape();
        let pruned_tensor = Tensor::from_vec(pruned_values, &shape)?;
        let energy_saved = 0.30; // 30% energy reduction from pruning
        let accuracy_loss = 0.05; // 5% accuracy loss from aggressive pruning

        Ok((pruned_tensor, energy_saved, accuracy_loss))
    }

    fn apply_sustainable_sparsification(&self, data: &Tensor) -> Result<(Tensor, f32, f32)> {
        let data_vec = data.data()?;
        let mut sparse_values = Vec::with_capacity(data_vec.len());

        // Apply structured sparsification with carbon optimization
        for (i, &value) in data_vec.iter().enumerate() {
            // Keep every 4th value in structured pattern for efficient computation
            if i % 4 == 0 || value.abs() > 0.1 {
                sparse_values.push(value);
            } else {
                sparse_values.push(0.0);
            }
        }

        let shape = data.shape();
        let sparse_tensor = Tensor::from_vec(sparse_values, &shape)?;
        let energy_saved = 0.20; // 20% additional energy reduction
        let accuracy_loss = 0.03; // 3% accuracy loss from sparsification

        Ok((sparse_tensor, energy_saved, accuracy_loss))
    }

    fn estimate_carbon_reduction(&self, energy_reduction: f32) -> Result<f32> {
        let typical_carbon_intensity = 400.0; // gCO2/kWh
        let typical_inference_energy = 0.001; // 1 mWh per inference

        let energy_saved_per_inference = typical_inference_energy * energy_reduction;
        let carbon_saved_per_inference = energy_saved_per_inference * typical_carbon_intensity;

        Ok(carbon_saved_per_inference)
    }

    fn calculate_compression_sustainability_score(
        &self,
        compression_ratio: f32,
        energy_reduction: f32,
        accuracy_loss: f32,
    ) -> Result<f32> {
        let efficiency_score = energy_reduction;
        let accuracy_penalty = accuracy_loss * 2.0; // Penalize accuracy loss
        let compression_bonus = (1.0 - compression_ratio) * 0.5;

        let score = (efficiency_score + compression_bonus - accuracy_penalty).max(0.0).min(1.0);

        Ok(score)
    }

    fn add_compression_event(&self, event: CompressionEvent) -> Result<()> {
        if let Ok(mut history) = self.compression_history.lock() {
            history.push(event);

            // Keep only last 100 events
            if history.len() > 100 {
                history.remove(0);
            }
        }
        Ok(())
    }

    pub fn get_compression_history(&self) -> Vec<CompressionEvent> {
        if let Ok(history) = self.compression_history.lock() {
            history.clone()
        } else {
            Vec::new()
        }
    }
}

#[derive(Debug, Clone)]
pub struct SustainableCompressionResult {
    pub compressed_model: Tensor,
    pub compression_ratio: f32,
    pub energy_reduction: f32,
    pub accuracy_loss: f32,
    pub carbon_impact_reduction: f32,
    pub sustainability_score: f32,
}

#[derive(Debug)]
pub struct EnergyOptimalBatchProcessor {
    config: SustainableAIConfig,
    batch_queue: Arc<Mutex<Vec<BatchTask>>>,
    processing_stats: Arc<Mutex<BatchProcessingStats>>,
}

#[derive(Debug, Clone)]
pub struct BatchTask {
    pub id: String,
    pub data: Vec<Tensor>,
    pub priority: TaskPriority,
    pub estimated_energy: f32,
    pub carbon_budget: f32,
    pub deadline: SystemTime,
}

#[derive(Debug, Default, Clone)]
pub struct BatchProcessingStats {
    pub total_batches_processed: u64,
    pub total_energy_saved: f32,
    pub average_batch_efficiency: f32,
    pub carbon_footprint_reduced: f32,
}

impl EnergyOptimalBatchProcessor {
    pub fn new(config: SustainableAIConfig) -> Self {
        Self {
            config,
            batch_queue: Arc::new(Mutex::new(Vec::new())),
            processing_stats: Arc::new(Mutex::new(BatchProcessingStats::default())),
        }
    }

    pub fn add_batch_task(&self, task: BatchTask) -> Result<()> {
        if let Ok(mut queue) = self.batch_queue.lock() {
            queue.push(task);
            queue.sort_by(|a, b| {
                // Sort by energy efficiency and deadline
                let a_efficiency = a.estimated_energy / a.data.len() as f32;
                let b_efficiency = b.estimated_energy / b.data.len() as f32;
                a_efficiency
                    .partial_cmp(&b_efficiency)
                    .expect("Operation failed")
                    .then(a.deadline.cmp(&b.deadline))
            });
        }
        Ok(())
    }

    pub fn process_optimal_batch(&self) -> Result<BatchProcessingResult> {
        let current_renewable = self.get_current_renewable_fraction()?;
        let optimal_batch_size = self.calculate_optimal_batch_size(current_renewable)?;

        let tasks = if let Ok(mut queue) = self.batch_queue.lock() {
            if queue.is_empty() {
                return Ok(BatchProcessingResult::default());
            }

            let batch_size = optimal_batch_size.min(queue.len());
            queue.drain(0..batch_size).collect::<Vec<_>>()
        } else {
            return Ok(BatchProcessingResult::default());
        };

        let total_data_points = tasks.iter().map(|t| t.data.len()).sum::<usize>();
        let total_estimated_energy: f32 = tasks.iter().map(|t| t.estimated_energy).sum();

        // Simulate batch processing with energy optimization
        let start_time = SystemTime::now();
        let actual_energy = self.simulate_batch_processing(&tasks)?;
        let processing_duration = start_time.elapsed().unwrap_or_default();

        let energy_efficiency = if total_estimated_energy > 0.0 {
            1.0 - (actual_energy / total_estimated_energy)
        } else {
            0.0
        };

        let carbon_saved = (total_estimated_energy - actual_energy)
            * self.get_current_carbon_intensity()?
            / 1000.0;

        self.update_processing_stats(tasks.len(), actual_energy, energy_efficiency, carbon_saved)?;

        Ok(BatchProcessingResult {
            processed_tasks: tasks.len(),
            total_data_points,
            energy_consumed: actual_energy,
            energy_saved: total_estimated_energy - actual_energy,
            processing_time_ms: processing_duration.as_millis() as u64,
            carbon_footprint: actual_energy * self.get_current_carbon_intensity()? / 1000.0,
            renewable_energy_used: actual_energy * current_renewable,
            efficiency_score: energy_efficiency,
        })
    }

    fn calculate_optimal_batch_size(&self, renewable_fraction: f32) -> Result<usize> {
        // Larger batches when more renewable energy is available
        let base_batch_size = match self.config.energy_optimization_level {
            EnergyOptimizationLevel::Minimal => 4,
            EnergyOptimizationLevel::Moderate => 8,
            EnergyOptimizationLevel::Aggressive => 16,
            EnergyOptimizationLevel::Adaptive => (4.0 + renewable_fraction * 12.0) as usize,
        };

        Ok(base_batch_size)
    }

    fn simulate_batch_processing(&self, tasks: &[BatchTask]) -> Result<f32> {
        if tasks.is_empty() {
            return Ok(0.0);
        }

        let sequential_energy: f32 = tasks.iter().map(|t| t.estimated_energy).sum();
        let batch_efficiency = 0.7 + (tasks.len() as f32).log2() * 0.1; // Economies of scale

        Ok(sequential_energy * batch_efficiency)
    }

    fn get_current_renewable_fraction(&self) -> Result<f32> {
        // Reuse the renewable fraction calculation from scheduler
        let hour = SystemTime::now()
            .duration_since(UNIX_EPOCH)
            .map_err(|_| {
                trustformers_core::TrustformersError::runtime_error(
                    "Time calculation failed".to_string(),
                )
            })?
            .as_secs()
            / 3600
            % 24;

        let solar = if (7..=17).contains(&hour) {
            ((hour as f32 - 12.0).abs() / 5.0).cos().max(0.0) * 0.4
        } else {
            0.0
        };

        let wind = 0.2 + (hour as f32 * 5.0).sin().abs() * 0.25;
        let other = 0.15;

        Ok((solar + wind + other).min(0.85))
    }

    fn get_current_carbon_intensity(&self) -> Result<f32> {
        let hour = SystemTime::now()
            .duration_since(UNIX_EPOCH)
            .map_err(|_| {
                trustformers_core::TrustformersError::runtime_error(
                    "Time calculation failed".to_string(),
                )
            })?
            .as_secs()
            / 3600
            % 24;

        let base_intensity = match hour {
            6..=9 | 18..=21 => 450.0,
            10..=16 => 300.0,
            22..=23 | 0..=5 => 350.0,
            _ => 400.0,
        };

        Ok(base_intensity)
    }

    fn update_processing_stats(
        &self,
        batch_count: usize,
        energy_consumed: f32,
        efficiency: f32,
        carbon_saved: f32,
    ) -> Result<()> {
        if let Ok(mut stats) = self.processing_stats.lock() {
            stats.total_batches_processed += batch_count as u64;
            stats.total_energy_saved += efficiency;
            stats.average_batch_efficiency = (stats.average_batch_efficiency + efficiency) / 2.0;
            stats.carbon_footprint_reduced += carbon_saved;
        }
        Ok(())
    }

    pub fn get_processing_stats(&self) -> BatchProcessingStats {
        if let Ok(stats) = self.processing_stats.lock() {
            (*stats).clone()
        } else {
            BatchProcessingStats::default()
        }
    }
}

#[derive(Debug, Clone, Default)]
pub struct BatchProcessingResult {
    pub processed_tasks: usize,
    pub total_data_points: usize,
    pub energy_consumed: f32,
    pub energy_saved: f32,
    pub processing_time_ms: u64,
    pub carbon_footprint: f32,
    pub renewable_energy_used: f32,
    pub efficiency_score: f32,
}

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

    #[test]
    fn test_carbon_footprint_tracker() {
        let config = SustainableAIConfig::default();
        let tracker = CarbonFootprintTracker::new(config);

        let result = tracker.track_operation(
            OperationType::Inference,
            0.001, // 1 mWh
            100,   // 100ms
        );

        assert!(result.is_ok());
        let impact = result.expect("Operation failed");
        assert!(impact.carbon_emission_grams >= 0.0);
        assert!(impact.sustainability_score >= 0.0 && impact.sustainability_score <= 1.0);
    }

    #[test]
    fn test_renewable_energy_scheduler() {
        let config = SustainableAIConfig::default();
        let scheduler = RenewableEnergyScheduler::new(config);

        let task = ScheduledTask {
            id: "test_task".to_string(),
            priority: TaskPriority::Medium,
            estimated_energy: 0.005,
            earliest_start: SystemTime::now(),
            deadline: SystemTime::now() + Duration::from_secs(3600),
            task_type: TaskType::BatchInference,
            renewable_requirement: 0.4,
        };

        let result = scheduler.schedule_task(task);
        assert!(result.is_ok());
    }

    #[test]
    fn test_sustainable_model_compression() {
        let config = SustainableAIConfig::default();
        let compressor = SustainableModelCompression::new(config);

        let model_data = Tensor::from_vec(vec![1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0], &[2, 4])
            .expect("Failed to create tensor");

        let result = compressor.compress_for_sustainability(&model_data, 0.3, 0.1);
        assert!(result.is_ok());

        let compression_result = result.expect("Operation failed");
        assert!(compression_result.energy_reduction >= 0.0);
        assert!(compression_result.sustainability_score >= 0.0);
    }

    #[test]
    fn test_energy_optimal_batch_processor() {
        let config = SustainableAIConfig::default();
        let processor = EnergyOptimalBatchProcessor::new(config);

        let data = vec![
            Tensor::from_vec(vec![1.0, 2.0], &[2]).expect("Failed to create tensor"),
            Tensor::from_vec(vec![3.0, 4.0], &[2]).expect("Failed to create tensor"),
        ];

        let task = BatchTask {
            id: "test_batch".to_string(),
            data,
            priority: TaskPriority::Medium,
            estimated_energy: 0.002,
            carbon_budget: 0.001,
            deadline: SystemTime::now() + Duration::from_secs(1800),
        };

        assert!(processor.add_batch_task(task).is_ok());

        let result = processor.process_optimal_batch();
        assert!(result.is_ok());
    }
}