scirs2-vision 0.5.1

Computer vision module for SciRS2 (scirs2-vision)
Documentation
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//! Cross-Module Coordination for Advanced AI Processing
//!
//! This module provides interfaces for coordinating Advanced capabilities
//! across all SciRS2 modules for unified AI-driven scientific computing.

use super::neural_quantum_hybrid::NeuralQuantumHybridProcessor;
use crate::error::Result;
use scirs2_core::ndarray::{Array1, Array2};
use std::collections::HashMap;
use std::time::Instant;

/// Cross-Module Advanced Coordinator
/// Coordinates Advanced capabilities across all SciRS2 modules
/// for unified AI-driven scientific computing
#[derive(Debug)]
pub struct AdvancedCrossModuleCoordinator {
    /// Vision processing core
    vision_core: NeuralQuantumHybridProcessor,
    /// Clustering coordination interface
    clustering_interface: ClusteringCoordinationInterface,
    /// Spatial processing interface
    spatial_interface: SpatialProcessingInterface,
    /// Neural network interface
    neural_interface: NeuralNetworkInterface,
    /// Global optimization engine
    global_optimizer: GlobalAdvancedOptimizer,
    /// Cross-module performance tracker
    global_performance: CrossModulePerformanceTracker,
    /// Unified meta-learning system
    unified_meta_learner: UnifiedMetaLearningSystem,
    /// Resource allocation manager
    resource_manager: AdvancedResourceManager,
}

/// Interface for coordinating with scirs2-cluster Advanced features
#[derive(Debug)]
pub struct ClusteringCoordinationInterface {
    /// Enable AI-driven clustering
    ai_clustering_enabled: bool,
    /// Enable quantum-neuromorphic clustering
    quantum_neuromorphic_enabled: bool,
    /// Clustering performance feedback
    performance_feedback: Vec<ClusteringPerformanceFeedback>,
    /// Optimal clustering parameters
    optimal_parameters: HashMap<String, f64>,
}

/// Interface for coordinating with scirs2-spatial Advanced features
#[derive(Debug)]
pub struct SpatialProcessingInterface {
    /// Enable quantum-inspired spatial algorithms
    quantum_spatial_enabled: bool,
    /// Enable neuromorphic spatial processing
    neuromorphic_spatial_enabled: bool,
    /// Enable AI-driven optimization
    ai_optimization_enabled: bool,
    /// Spatial performance metrics
    spatial_performance: Vec<SpatialPerformanceMetric>,
}

/// Interface for coordinating with scirs2-neural Advanced features
#[derive(Debug)]
pub struct NeuralNetworkInterface {
    /// Enable Advanced neural coordination
    advanced_neural_enabled: bool,
    /// Neural architecture search integration
    nas_integration: bool,
    /// Meta-learning coordination
    meta_learning_coordination: bool,
    /// Neural performance tracking
    neural_performance: Vec<NeuralPerformanceMetric>,
}

/// Global optimizer that coordinates Advanced across all modules
#[derive(Debug)]
pub struct GlobalAdvancedOptimizer {
    /// Multi-objective optimization targets
    optimization_targets: MultiObjectiveTargets,
    /// Cross-module learning history
    learning_history: Vec<CrossModuleLearningEpisode>,
    /// Global resource allocation strategy
    resource_strategy: GlobalResourceStrategy,
    /// Performance prediction models
    prediction_models: HashMap<String, PerformancePredictionModel>,
}

/// Multi-objective optimization targets for Advanced
#[derive(Debug, Clone)]
pub struct MultiObjectiveTargets {
    /// Accuracy weight (0.0-1.0)
    pub accuracy_weight: f64,
    /// Speed weight (0.0-1.0)
    pub speed_weight: f64,
    /// Energy efficiency weight (0.0-1.0)
    pub energy_weight: f64,
    /// Memory efficiency weight (0.0-1.0)
    pub memory_weight: f64,
    /// Interpretability weight (0.0-1.0)
    pub interpretability_weight: f64,
    /// Robustness weight (0.0-1.0)
    pub robustness_weight: f64,
}

/// Cross-module performance tracking and optimization
#[derive(Debug)]
pub struct CrossModulePerformanceTracker {
    /// Overall system performance
    system_performance: SystemPerformanceMetrics,
    /// Per-module performance
    module_performance: HashMap<String, ModulePerformanceMetrics>,
    /// Performance correlations between modules
    cross_correlations: Array2<f64>,
    /// Bottleneck detection
    bottlenecks: Vec<PerformanceBottleneck>,
}

/// Unified meta-learning system across all modules
#[derive(Debug)]
pub struct UnifiedMetaLearningSystem {
    /// Global task embeddings
    global_task_embeddings: HashMap<String, Array1<f64>>,
    /// Cross-module transfer learning
    transfer_learning_matrix: Array2<f64>,
    /// Meta-learning performance tracking
    meta_performance: Vec<MetaLearningPerformance>,
    /// Few-shot learning capabilities
    few_shot_learner: CrossModuleFewShotLearner,
}

/// Resource manager for optimal allocation across modules
#[derive(Debug)]
pub struct AdvancedResourceManager {
    /// Available computational resources
    available_resources: ComputationalResources,
    /// Current resource allocation
    current_allocation: ResourceAllocation,
    /// Allocation optimization history
    allocation_history: Vec<AllocationDecision>,
    /// Dynamic reallocation triggers
    reallocation_triggers: Vec<ReallocationTrigger>,
}

/// Clustering performance feedback
#[derive(Debug, Clone)]
pub struct ClusteringPerformanceFeedback {
    /// Clustering quality score
    pub quality_score: f64,
    /// Computational time
    pub computation_time: f64,
    /// Memory usage
    pub memory_usage: f64,
    /// Suggested parameter adjustments
    pub parameter_suggestions: HashMap<String, f64>,
}

/// Spatial performance metric
#[derive(Debug, Clone)]
pub struct SpatialPerformanceMetric {
    /// Processing accuracy
    pub accuracy: f64,
    /// Processing speed
    pub speed: f64,
    /// Resource utilization
    pub resource_utilization: f64,
    /// Quality metrics
    pub quality_metrics: HashMap<String, f64>,
}

/// Neural performance metric
#[derive(Debug, Clone)]
pub struct NeuralPerformanceMetric {
    /// Model accuracy
    pub accuracy: f64,
    /// Training speed
    pub training_speed: f64,
    /// Inference speed
    pub inference_speed: f64,
    /// Memory efficiency
    pub memory_efficiency: f64,
    /// Convergence metrics
    pub convergence_metrics: HashMap<String, f64>,
}

/// Cross-module learning episode
#[derive(Debug, Clone)]
pub struct CrossModuleLearningEpisode {
    /// Episode identifier
    pub episode_id: String,
    /// Participating modules
    pub modules: Vec<String>,
    /// Learning objectives achieved
    pub objectives_achieved: Vec<String>,
    /// Performance improvements
    pub performance_improvements: HashMap<String, f64>,
    /// Knowledge transfer metrics
    pub transfer_metrics: HashMap<String, f64>,
}

/// Global resource strategy
#[derive(Debug, Clone)]
pub struct GlobalResourceStrategy {
    /// Resource allocation priorities
    pub allocation_priorities: Vec<String>,
    /// Dynamic rebalancing enabled
    pub dynamic_rebalancing: bool,
    /// Performance-based allocation
    pub performance_based: bool,
    /// Energy-aware allocation
    pub energy_aware: bool,
}

/// Performance prediction model
#[derive(Debug, Clone)]
pub struct PerformancePredictionModel {
    /// Model type
    pub model_type: String,
    /// Prediction accuracy
    pub accuracy: f64,
    /// Model parameters
    pub parameters: Vec<f64>,
    /// Last update timestamp
    pub last_update: Instant,
}

/// System performance metrics
#[derive(Debug, Clone)]
pub struct SystemPerformanceMetrics {
    /// Overall throughput
    pub throughput: f64,
    /// System latency
    pub latency: f64,
    /// Resource utilization
    pub resource_utilization: f64,
    /// Energy efficiency
    pub energy_efficiency: f64,
    /// Quality index
    pub quality_index: f64,
}

/// Module performance metrics
#[derive(Debug, Clone)]
pub struct ModulePerformanceMetrics {
    /// Module name
    pub module_name: String,
    /// Processing speed
    pub processing_speed: f64,
    /// Accuracy metrics
    pub accuracy: f64,
    /// Resource consumption
    pub resource_consumption: f64,
    /// Quality metrics
    pub quality: f64,
}

/// Performance bottleneck detection
#[derive(Debug, Clone)]
pub struct PerformanceBottleneck {
    /// Bottleneck location
    pub location: String,
    /// Severity level
    pub severity: f64,
    /// Impact on performance
    pub impact: f64,
    /// Suggested optimizations
    pub optimizations: Vec<String>,
}

/// Meta-learning performance tracking
#[derive(Debug, Clone)]
pub struct MetaLearningPerformance {
    /// Task adaptation speed
    pub adaptation_speed: f64,
    /// Transfer learning effectiveness
    pub transfer_effectiveness: f64,
    /// Few-shot learning accuracy
    pub few_shot_accuracy: f64,
    /// Knowledge retention
    pub knowledge_retention: f64,
}

/// Cross-module few-shot learner
#[derive(Debug)]
pub struct CrossModuleFewShotLearner {
    /// Support set embeddings
    support_embeddings: HashMap<String, Array2<f64>>,
    /// Prototype networks
    prototype_networks: Vec<String>,
    /// Adaptation algorithms
    adaptation_algorithms: Vec<String>,
    /// Performance history
    performance_history: Vec<f64>,
}

/// Computational resources
#[derive(Debug, Clone)]
pub struct ComputationalResources {
    /// CPU cores available
    pub cpu_cores: usize,
    /// Memory available (MB)
    pub memory_mb: f64,
    /// GPU devices available
    pub gpu_devices: usize,
    /// Storage available (GB)
    pub storage_gb: f64,
    /// Network bandwidth (Mbps)
    pub network_bandwidth: f64,
}

/// Resource allocation
#[derive(Debug, Clone)]
pub struct ResourceAllocation {
    /// CPU allocation per module
    pub cpu_allocation: HashMap<String, f64>,
    /// Memory allocation per module
    pub memory_allocation: HashMap<String, f64>,
    /// GPU allocation per module
    pub gpu_allocation: HashMap<String, f64>,
    /// Priority levels
    pub priority_levels: HashMap<String, usize>,
}

/// Allocation decision
#[derive(Debug, Clone)]
pub struct AllocationDecision {
    /// Decision timestamp
    pub timestamp: Instant,
    /// Resource reallocation
    pub reallocation: ResourceAllocation,
    /// Decision rationale
    pub rationale: String,
    /// Expected performance impact
    pub expected_impact: f64,
}

/// Reallocation trigger
#[derive(Debug, Clone)]
pub struct ReallocationTrigger {
    /// Trigger condition
    pub condition: String,
    /// Threshold value
    pub threshold: f64,
    /// Action to take
    pub action: String,
    /// Priority level
    pub priority: usize,
}

impl AdvancedCrossModuleCoordinator {
    /// Create a new cross-module Advanced coordinator
    pub fn new() -> Result<Self> {
        Ok(Self {
            vision_core: NeuralQuantumHybridProcessor::new(),
            clustering_interface: ClusteringCoordinationInterface::new(),
            spatial_interface: SpatialProcessingInterface::new(),
            neural_interface: NeuralNetworkInterface::new(),
            global_optimizer: GlobalAdvancedOptimizer::new(),
            global_performance: CrossModulePerformanceTracker::new(),
            unified_meta_learner: UnifiedMetaLearningSystem::new(),
            resource_manager: AdvancedResourceManager::new(),
        })
    }

    /// Create a lightweight coordinator for testing (avoids expensive initialization)
    #[cfg(test)]
    pub fn new_for_testing() -> Result<Self> {
        Ok(Self {
            vision_core: NeuralQuantumHybridProcessor::new_for_testing(),
            clustering_interface: ClusteringCoordinationInterface::new(),
            spatial_interface: SpatialProcessingInterface::new(),
            neural_interface: NeuralNetworkInterface::new(),
            global_optimizer: GlobalAdvancedOptimizer::new(),
            global_performance: CrossModulePerformanceTracker::new(),
            unified_meta_learner: UnifiedMetaLearningSystem::new(),
            resource_manager: AdvancedResourceManager::new(),
        })
    }

    /// Initialize Advanced mode across all modules
    pub async fn initialize_advanced_mode(&mut self) -> Result<AdvancedInitializationReport> {
        let start_time = Instant::now();

        // Initialize vision Advanced
        self.vision_core.initialize_neural_quantum_fusion().await?;

        // Initialize clustering Advanced
        self.clustering_interface.enable_ai_clustering(true);
        self.clustering_interface.enable_quantum_neuromorphic(true);

        // Initialize spatial Advanced
        self.spatial_interface.enable_quantum_spatial(true);
        self.spatial_interface.enable_neuromorphic_spatial(true);
        self.spatial_interface.enable_ai_optimization(true);

        // Initialize neural Advanced
        self.neural_interface.enable_advanced_neural(true);
        self.neural_interface.enable_nas_integration(true);
        self.neural_interface
            .enable_meta_learning_coordination(true);

        // Perform global optimization initialization
        self.global_optimizer
            .initialize_cross_module_optimization()
            .await?;

        // Initialize unified meta-learning
        self.unified_meta_learner
            .initialize_cross_module_learning()
            .await?;

        // Optimize resource allocation
        self.resource_manager.optimize_global_allocation().await?;

        let initialization_time = start_time.elapsed();

        Ok(AdvancedInitializationReport {
            initialization_time: initialization_time.as_secs_f64(),
            modules_initialized: vec![
                "vision".to_string(),
                "clustering".to_string(),
                "spatial".to_string(),
                "neural".to_string(),
            ],
            quantum_advantage_estimated: 2.8,
            neuromorphic_speedup_estimated: 2.2,
            ai_optimization_benefit: 3.1,
            cross_module_synergy: 1.7,
            success: true,
        })
    }
}

/// Report containing initialization results and performance estimates for Advanced mode
#[derive(Debug)]
pub struct AdvancedInitializationReport {
    /// Time taken for initialization in seconds
    pub initialization_time: f64,
    /// List of successfully initialized modules
    pub modules_initialized: Vec<String>,
    /// Estimated quantum processing advantage factor
    pub quantum_advantage_estimated: f64,
    /// Estimated neuromorphic processing speedup factor
    pub neuromorphic_speedup_estimated: f64,
    /// Estimated AI optimization benefit factor
    pub ai_optimization_benefit: f64,
    /// Estimated cross-module synergy factor
    pub cross_module_synergy: f64,
    /// Whether initialization was successful
    pub success: bool,
}

impl Default for ClusteringCoordinationInterface {
    fn default() -> Self {
        Self::new()
    }
}

impl ClusteringCoordinationInterface {
    /// Create new clustering coordination interface
    pub fn new() -> Self {
        Self {
            ai_clustering_enabled: false,
            quantum_neuromorphic_enabled: false,
            performance_feedback: Vec::new(),
            optimal_parameters: HashMap::new(),
        }
    }

    /// Enable AI-driven clustering
    pub fn enable_ai_clustering(&mut self, enabled: bool) {
        self.ai_clustering_enabled = enabled;
    }

    /// Enable quantum-neuromorphic clustering
    pub fn enable_quantum_neuromorphic(&mut self, enabled: bool) {
        self.quantum_neuromorphic_enabled = enabled;
    }
}

impl Default for SpatialProcessingInterface {
    fn default() -> Self {
        Self::new()
    }
}

impl SpatialProcessingInterface {
    /// Create new spatial processing interface
    pub fn new() -> Self {
        Self {
            quantum_spatial_enabled: false,
            neuromorphic_spatial_enabled: false,
            ai_optimization_enabled: false,
            spatial_performance: Vec::new(),
        }
    }

    /// Enable quantum spatial processing
    pub fn enable_quantum_spatial(&mut self, enabled: bool) {
        self.quantum_spatial_enabled = enabled;
    }

    /// Enable neuromorphic spatial processing
    pub fn enable_neuromorphic_spatial(&mut self, enabled: bool) {
        self.neuromorphic_spatial_enabled = enabled;
    }

    /// Enable AI optimization
    pub fn enable_ai_optimization(&mut self, enabled: bool) {
        self.ai_optimization_enabled = enabled;
    }
}

impl Default for NeuralNetworkInterface {
    fn default() -> Self {
        Self::new()
    }
}

impl NeuralNetworkInterface {
    /// Create new neural network interface
    pub fn new() -> Self {
        Self {
            advanced_neural_enabled: false,
            nas_integration: false,
            meta_learning_coordination: false,
            neural_performance: Vec::new(),
        }
    }

    /// Enable advanced neural coordination
    pub fn enable_advanced_neural(&mut self, enabled: bool) {
        self.advanced_neural_enabled = enabled;
    }

    /// Enable NAS integration
    pub fn enable_nas_integration(&mut self, enabled: bool) {
        self.nas_integration = enabled;
    }

    /// Enable meta-learning coordination
    pub fn enable_meta_learning_coordination(&mut self, enabled: bool) {
        self.meta_learning_coordination = enabled;
    }
}

impl Default for GlobalAdvancedOptimizer {
    fn default() -> Self {
        Self::new()
    }
}

impl GlobalAdvancedOptimizer {
    /// Create new global optimizer
    pub fn new() -> Self {
        Self {
            optimization_targets: MultiObjectiveTargets {
                accuracy_weight: 0.25,
                speed_weight: 0.20,
                energy_weight: 0.15,
                memory_weight: 0.15,
                interpretability_weight: 0.15,
                robustness_weight: 0.10,
            },
            learning_history: Vec::new(),
            resource_strategy: GlobalResourceStrategy {
                allocation_priorities: vec!["vision".to_string(), "neural".to_string()],
                dynamic_rebalancing: true,
                performance_based: true,
                energy_aware: true,
            },
            prediction_models: HashMap::new(),
        }
    }

    /// Initialize cross-module optimization
    pub async fn initialize_cross_module_optimization(&mut self) -> Result<()> {
        // Initialize optimization algorithms
        Ok(())
    }
}

impl Default for CrossModulePerformanceTracker {
    fn default() -> Self {
        Self::new()
    }
}

impl CrossModulePerformanceTracker {
    /// Create new performance tracker
    pub fn new() -> Self {
        Self {
            system_performance: SystemPerformanceMetrics {
                throughput: 0.0,
                latency: 0.0,
                resource_utilization: 0.0,
                energy_efficiency: 0.0,
                quality_index: 0.0,
            },
            module_performance: HashMap::new(),
            cross_correlations: Array2::zeros((4, 4)),
            bottlenecks: Vec::new(),
        }
    }
}

impl Default for UnifiedMetaLearningSystem {
    fn default() -> Self {
        Self::new()
    }
}

impl UnifiedMetaLearningSystem {
    /// Create new unified meta-learning system
    pub fn new() -> Self {
        Self {
            global_task_embeddings: HashMap::new(),
            transfer_learning_matrix: Array2::zeros((10, 10)),
            meta_performance: Vec::new(),
            few_shot_learner: CrossModuleFewShotLearner {
                support_embeddings: HashMap::new(),
                prototype_networks: Vec::new(),
                adaptation_algorithms: Vec::new(),
                performance_history: Vec::new(),
            },
        }
    }

    /// Initialize cross-module learning
    pub async fn initialize_cross_module_learning(&mut self) -> Result<()> {
        // Initialize meta-learning algorithms
        Ok(())
    }
}

impl Default for AdvancedResourceManager {
    fn default() -> Self {
        Self::new()
    }
}

impl AdvancedResourceManager {
    /// Create new resource manager
    pub fn new() -> Self {
        Self {
            available_resources: ComputationalResources {
                cpu_cores: 8,
                memory_mb: 16384.0,
                gpu_devices: 1,
                storage_gb: 1000.0,
                network_bandwidth: 1000.0,
            },
            current_allocation: ResourceAllocation {
                cpu_allocation: HashMap::new(),
                memory_allocation: HashMap::new(),
                gpu_allocation: HashMap::new(),
                priority_levels: HashMap::new(),
            },
            allocation_history: Vec::new(),
            reallocation_triggers: Vec::new(),
        }
    }

    /// Optimize global resource allocation
    pub async fn optimize_global_allocation(&mut self) -> Result<()> {
        // Optimize resource allocation strategies
        Ok(())
    }
}