strange_loop/

temporal_consciousness.rs

//! Temporal consciousness implementation combining all components
//!
//! This module provides the main interface for temporal consciousness
//! experiments and integrates all other modules into a coherent system.

use crate::consciousness::{ConsciousnessMetrics, ConsciousnessState, ConsciousnessVerifier};
use crate::error::{LoopError, Result};
use crate::lipschitz_loop::{LipschitzLoop, LipschitzParams, LoopTopology};
use crate::quantum_container::{QuantumContainer, HybridOperation};
use crate::strange_attractor::{TemporalAttractor, AttractorConfig};
use crate::types::{Vector3D, StrangeLoop, LoopConfig, Context, ScalarReasoner, SimpleCritic, SafeReflector};
use crate::types::NalgebraVec3;
use serde::{Deserialize, Serialize};
use std::collections::HashMap;
use std::time::Instant;

/// Configuration for temporal consciousness system
#[derive(Clone, Debug, Serialize, Deserialize)]
pub struct ConsciousnessConfig {
    /// Enable quantum-classical hybrid processing
    pub enable_quantum: bool,
    /// Enable strange attractor dynamics
    pub enable_attractors: bool,
    /// Enable Lipschitz loop constraints
    pub enable_lipschitz: bool,
    /// Enable self-modification
    pub enable_self_modification: bool,
    /// Consciousness emergence threshold
    pub consciousness_threshold: f64,
    /// Φ (phi) calculation parameters
    pub phi_elements: usize,
    /// System coupling strength
    pub coupling_strength: f64,
    /// Temporal coherence window (iterations)
    pub coherence_window: usize,
    /// Meta-learning rate
    pub meta_learning_rate: f64,
    /// Novelty detection sensitivity
    pub novelty_sensitivity: f64,
    /// Maximum consciousness evolution iterations
    pub max_evolution_iterations: usize,
}

impl Default for ConsciousnessConfig {
    fn default() -> Self {
        Self {
            enable_quantum: true,
            enable_attractors: true,
            enable_lipschitz: true,
            enable_self_modification: true,
            consciousness_threshold: 0.5,
            phi_elements: 8,
            coupling_strength: 0.8,
            coherence_window: 100,
            meta_learning_rate: 0.01,
            novelty_sensitivity: 0.1,
            max_evolution_iterations: 10_000,
        }
    }
}

impl ConsciousnessConfig {
    /// Create configuration for consciousness research
    pub fn research_mode() -> Self {
        Self {
            enable_quantum: true,
            enable_attractors: true,
            enable_lipschitz: true,
            enable_self_modification: true,
            consciousness_threshold: 0.3,
            phi_elements: 12,
            coupling_strength: 0.9,
            coherence_window: 1000,
            meta_learning_rate: 0.005,
            novelty_sensitivity: 0.05,
            max_evolution_iterations: 100_000,
        }
    }

    /// Create configuration for real-time applications
    pub fn real_time_mode() -> Self {
        Self {
            enable_quantum: false,
            enable_attractors: true,
            enable_lipschitz: true,
            enable_self_modification: false,
            consciousness_threshold: 0.7,
            phi_elements: 4,
            coupling_strength: 0.6,
            coherence_window: 50,
            meta_learning_rate: 0.02,
            novelty_sensitivity: 0.2,
            max_evolution_iterations: 1_000,
        }
    }

    /// Validate configuration parameters
    pub fn validate(&self) -> Result<()> {
        if self.consciousness_threshold < 0.0 || self.consciousness_threshold > 1.0 {
            return Err(LoopError::consciousness_error("Consciousness threshold must be in [0, 1]"));
        }
        if self.phi_elements == 0 {
            return Err(LoopError::consciousness_error("Phi elements must be positive"));
        }
        if self.coupling_strength < 0.0 || self.coupling_strength > 1.0 {
            return Err(LoopError::consciousness_error("Coupling strength must be in [0, 1]"));
        }
        if self.coherence_window == 0 {
            return Err(LoopError::consciousness_error("Coherence window must be positive"));
        }
        if self.meta_learning_rate <= 0.0 || self.meta_learning_rate > 1.0 {
            return Err(LoopError::consciousness_error("Meta learning rate must be in (0, 1]"));
        }
        if self.max_evolution_iterations == 0 {
            return Err(LoopError::consciousness_error("Max evolution iterations must be positive"));
        }
        Ok(())
    }
}

/// Main temporal consciousness system
pub struct TemporalConsciousness {
    config: ConsciousnessConfig,
    consciousness_metrics: ConsciousnessMetrics,
    quantum_container: Option<QuantumContainer>,
    attractor: Option<TemporalAttractor>,
    lipschitz_loop: Option<LipschitzLoop>,
    strange_loop: Option<StrangeLoop<ScalarReasoner, SimpleCritic, SafeReflector>>,
    temporal_memory: HashMap<String, Vec<f64>>,
    evolution_history: Vec<EvolutionStep>,
    emergence_patterns: Vec<EmergencePattern>,
    self_modification_log: Vec<SelfModificationEvent>,
    start_time: Instant,
}

impl TemporalConsciousness {
    /// Create a new temporal consciousness system
    pub fn new(config: ConsciousnessConfig) -> Result<Self> {
        config.validate()?;

        let quantum_container = if config.enable_quantum {
            Some(QuantumContainer::new(config.phi_elements.min(10))) // Limit for performance
        } else {
            None
        };

        let attractor = if config.enable_attractors {
            let attractor_config = AttractorConfig::consciousness_mode();
            Some(TemporalAttractor::new(attractor_config)?)
        } else {
            None
        };

        let lipschitz_loop = if config.enable_lipschitz {
            let lipschitz_params = LipschitzParams {
                lipschitz_constant: config.coupling_strength,
                tolerance: 1e-9,
                max_iterations: config.max_evolution_iterations,
                adaptive_estimation: true,
                damping: 0.99,
            };
            Some(LipschitzLoop::new(lipschitz_params, LoopTopology::Accelerated)?)
        } else {
            None
        };

        let strange_loop = {
            let reasoner = ScalarReasoner::new(0.0, config.meta_learning_rate);
            let critic = SimpleCritic::new();
            let reflector = SafeReflector::new();
            let loop_config = LoopConfig {
                max_iterations: config.max_evolution_iterations,
                max_duration_ns: 1_000_000_000, // 1 second
                convergence_threshold: 1e-12,
                lipschitz_constant: config.coupling_strength,
                enable_consciousness: true,
                enable_quantum: config.enable_quantum,
                enable_simd: true,
            };
            Some(StrangeLoop::new(reasoner, critic, reflector, loop_config))
        };

        Ok(Self {
            config,
            consciousness_metrics: ConsciousnessMetrics::new(),
            quantum_container,
            attractor,
            lipschitz_loop,
            strange_loop,
            temporal_memory: HashMap::new(),
            evolution_history: Vec::new(),
            emergence_patterns: Vec::new(),
            self_modification_log: Vec::new(),
            start_time: Instant::now(),
        })
    }

    /// Evolve consciousness through temporal dynamics
    pub fn evolve_consciousness(&mut self, iterations: usize) -> Result<ConsciousnessEvolutionResult> {
        let start_time = Instant::now();
        let mut states = Vec::with_capacity(iterations);

        for iteration in 0..iterations {
            let evolution_step = self.single_evolution_step(iteration)?;
            states.push(evolution_step.consciousness_state.clone());

            // Check for emergence
            if self.consciousness_metrics.detect_emergence(self.config.consciousness_threshold) {
                let emergence_pattern = EmergencePattern {
                    iteration,
                    timestamp_ns: start_time.elapsed().as_nanos(),
                    consciousness_level: evolution_step.consciousness_state.consciousness_index(),
                    phi_value: evolution_step.phi_value,
                    attractor_state: evolution_step.attractor_state,
                    quantum_state_complexity: evolution_step.quantum_state_complexity,
                    pattern_type: EmergenceType::SpontaneousEmergence,
                };
                self.emergence_patterns.push(emergence_pattern);
            }

            // Self-modification check
            if self.config.enable_self_modification &&
               iteration % 100 == 0 &&
               evolution_step.consciousness_state.consciousness_index() > 0.6 {
                self.attempt_self_modification(iteration)?;
            }

            // Store in history
            self.evolution_history.push(evolution_step);

            // Limit history size for memory management
            if self.evolution_history.len() > 10_000 {
                self.evolution_history.drain(0..1_000);
            }
        }

        Ok(ConsciousnessEvolutionResult {
            evolved: true,
            iterations_completed: iterations,
            final_consciousness_level: states.last()
                .map(|s| s.consciousness_index())
                .unwrap_or(0.0),
            max_phi_achieved: self.consciousness_metrics.max_phi,
            emergence_events: self.emergence_patterns.len(),
            self_modifications: self.self_modification_log.len(),
            evolution_time_ns: start_time.elapsed().as_nanos(),
            final_state: states.into_iter().last(),
        })
    }

    /// Perform a single evolution step
    fn single_evolution_step(&mut self, iteration: usize) -> Result<EvolutionStep> {
        let step_start = Instant::now();

        // 1. Update strange attractor if enabled
        let attractor_state = if let Some(ref mut attractor) = self.attractor {
            attractor.step()?
        } else {
            Vector3D::new(0.0, 0.0, 0.0)
        };

        // 2. Quantum-classical hybrid processing
        let quantum_state_complexity = match self.quantum_container {
            Some(ref mut quantum) => {
                // Process quantum dynamics without borrowing self again
                let rotation_angle = attractor_state[0] * std::f64::consts::PI;
                quantum.apply_gate(0, crate::quantum_container::Gate::RZ(rotation_angle))?;

                // Calculate quantum state complexity
                let mut total_entropy = 0.0;
                for i in 0..(1 << quantum.quantum_state().num_qubits) {
                    total_entropy += quantum.get_probability(i);
                }
                total_entropy
            }
            None => 0.0,
        };

        // 3. Strange loop self-reference
        let loop_result = if let Some(ref mut strange_loop) = self.strange_loop {
            let mut context = Context::new();
            context.insert("attractor_x".to_string(), attractor_state[0]);
            context.insert("attractor_y".to_string(), attractor_state[1]);
            context.insert("attractor_z".to_string(), attractor_state[2]);
            context.insert("quantum_complexity".to_string(), quantum_state_complexity);

            strange_loop.run(&mut context).ok()
        } else {
            None
        };

        // 4. Calculate consciousness metrics
        let phi_value = self.calculate_current_phi(&attractor_state, quantum_state_complexity)?;

        // 5. Update consciousness state
        let mut consciousness_state = ConsciousnessState::new();
        self.update_consciousness_state(&mut consciousness_state,
            &attractor_state, quantum_state_complexity, phi_value, iteration)?;

        // 6. Update metrics
        self.consciousness_metrics.update_state(consciousness_state.clone());

        // 7. Store temporal patterns
        self.store_temporal_patterns(iteration, &attractor_state, quantum_state_complexity);

        Ok(EvolutionStep {
            iteration,
            timestamp_ns: step_start.elapsed().as_nanos(),
            consciousness_state,
            phi_value,
            attractor_state,
            quantum_state_complexity,
            loop_convergence: loop_result.map(|r| r.converged).unwrap_or(false),
            lipschitz_estimate: self.lipschitz_loop.as_ref()
                .map(|l| l.estimated_lipschitz())
                .unwrap_or(0.0),
        })
    }

    /// Process quantum dynamics
    fn process_quantum_dynamics(&mut self, quantum: &mut QuantumContainer, attractor_state: &Vector3D) -> Result<f64> {
        // Use attractor state to influence quantum system
        let influence_strength = attractor_state.norm() * 0.1;

        // Store attractor influence in classical memory
        quantum.store_classical("attractor_x".to_string(), attractor_state[0]);
        quantum.store_classical("attractor_y".to_string(), attractor_state[1]);
        quantum.store_classical("attractor_z".to_string(), attractor_state[2]);
        quantum.store_classical("influence".to_string(), influence_strength);

        // Perform quantum-classical hybrid operation
        let num_qubits = quantum.quantum_state().num_qubits;
        if num_qubits > 0 {
            // Apply rotation based on attractor state
            let _rotation_angle = attractor_state[0] * std::f64::consts::PI;
            quantum.hybrid_operation(HybridOperation::ClassicalToQuantum {
                source_key: "attractor_x".to_string(),
                qubit: 0,
                gate_type: "RZ".to_string(),
            })?;

            // Measure entanglement if we have multiple qubits
            if num_qubits > 1 {
                let entanglement = quantum.hybrid_operation(HybridOperation::EntanglementCheck {
                    qubit_a: 0,
                    qubit_b: 1,
                })?;
                return Ok(entanglement);
            }
        }

        Ok(influence_strength)
    }

    /// Calculate current Φ (integrated information)
    fn calculate_current_phi(&mut self, attractor_state: &Vector3D, quantum_complexity: f64) -> Result<f64> {
        // Enhanced Φ calculation incorporating multiple subsystems
        let base_connections = self.config.phi_elements * (self.config.phi_elements - 1) / 2;
        let dynamic_connections = (base_connections as f64 * (1.0 + attractor_state.norm() * 0.1)) as usize;

        let enhanced_coupling = self.config.coupling_strength * (1.0 + quantum_complexity * 0.2);

        let phi = self.consciousness_metrics.calculate_phi(
            self.config.phi_elements,
            dynamic_connections,
            enhanced_coupling
        );

        Ok(phi)
    }

    /// Update consciousness state with current measurements
    fn update_consciousness_state(
        &mut self,
        state: &mut ConsciousnessState,
        attractor_state: &Vector3D,
        quantum_complexity: f64,
        phi_value: f64,
        iteration: usize,
    ) -> Result<()> {
        // Emergence level based on system complexity
        let emergence = (phi_value + quantum_complexity + attractor_state.norm() * 0.1) / 3.0;

        // Self-awareness based on self-modification history
        let self_awareness = if !self.self_modification_log.is_empty() {
            0.5 + (self.self_modification_log.len() as f64 * 0.01).min(0.5)
        } else {
            emergence * 0.5
        };

        // Meta-cognition based on loop complexity
        let meta_cognition = if let Some(ref lipschitz) = self.lipschitz_loop {
            (1.0 - lipschitz.estimated_lipschitz()).max(0.0)
        } else {
            emergence * 0.8
        };

        // Temporal coherence based on history consistency
        let temporal_coherence = self.calculate_temporal_coherence(iteration);

        // Integration measure from Φ
        let integration = (phi_value / (self.consciousness_metrics.max_phi.max(1.0))).min(1.0);

        // Feedback strength from self-reference
        let feedback_strength = if iteration > 0 {
            let recent_changes = self.calculate_recent_changes();
            recent_changes.clamp(0.0, 1.0)
        } else {
            0.0
        };

        // Novelty generation
        let novelty = self.calculate_novelty_measure(attractor_state, quantum_complexity);

        state.update(
            Some(emergence),
            Some(self_awareness),
            Some(meta_cognition),
            Some(temporal_coherence),
            Some(integration),
            Some(feedback_strength),
            Some(novelty),
        );

        Ok(())
    }

    /// Calculate temporal coherence
    fn calculate_temporal_coherence(&self, _iteration: usize) -> f64 {
        if self.evolution_history.len() < 2 {
            return 0.0;
        }

        let window = self.config.coherence_window.min(self.evolution_history.len());
        let recent_consciousness: Vec<f64> = self.evolution_history.iter()
            .rev()
            .take(window)
            .map(|step| step.consciousness_state.consciousness_index())
            .collect();

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

        // Calculate variance (lower variance = higher coherence)
        let mean = recent_consciousness.iter().sum::<f64>() / recent_consciousness.len() as f64;
        let variance = recent_consciousness.iter()
            .map(|x| (x - mean).powi(2))
            .sum::<f64>() / recent_consciousness.len() as f64;

        // Convert variance to coherence (inverted and normalized)
        (1.0 / (1.0 + variance * 10.0)).clamp(0.0, 1.0)
    }

    /// Calculate recent changes for feedback strength
    fn calculate_recent_changes(&self) -> f64 {
        if self.evolution_history.len() < 10 {
            return 0.0;
        }

        let recent_steps: Vec<f64> = self.evolution_history.iter()
            .rev()
            .take(10)
            .map(|step| step.consciousness_state.consciousness_index())
            .collect();

        // Calculate rate of change
        let mut total_change = 0.0;
        for window in recent_steps.windows(2) {
            total_change += (window[0] - window[1]).abs();
        }

        (total_change / 9.0).clamp(0.0, 1.0) // 9 pairs in 10 elements
    }

    /// Calculate novelty measure
    fn calculate_novelty_measure(&self, attractor_state: &Vector3D, quantum_complexity: f64) -> f64 {
        // Simple novelty based on deviation from historical patterns
        if self.evolution_history.len() < 5 {
            return 0.5; // Default for new systems
        }

        let recent_attractors: Vec<Vector3D> = self.evolution_history.iter()
            .rev()
            .take(20)
            .map(|step| step.attractor_state)
            .collect();

        let mean_attractor = recent_attractors.iter()
            .fold(NalgebraVec3::zeros(), |acc, &state| {
                acc + NalgebraVec3::new(state.x, state.y, state.z)
            }) / recent_attractors.len() as f64;

        let attractor_nalgebra = NalgebraVec3::new(attractor_state.x, attractor_state.y, attractor_state.z);
        let deviation = (attractor_nalgebra - mean_attractor).norm();
        let normalized_deviation = (deviation * self.config.novelty_sensitivity).clamp(0.0, 1.0);

        // Combine with quantum complexity for enhanced novelty detection
        (normalized_deviation + quantum_complexity * 0.3).clamp(0.0, 1.0)
    }

    /// Store temporal patterns in memory
    fn store_temporal_patterns(&mut self, iteration: usize, attractor_state: &Vector3D, quantum_complexity: f64) {
        let key = format!("pattern_{}", iteration % 1000); // Circular buffer
        let pattern = vec![
            attractor_state[0],
            attractor_state[1],
            attractor_state[2],
            quantum_complexity,
            self.consciousness_metrics.current_state.consciousness_index(),
        ];

        self.temporal_memory.insert(key, pattern);

        // Limit memory size
        if self.temporal_memory.len() > 2000 {
            let oldest_keys: Vec<String> = self.temporal_memory.keys()
                .take(200)
                .cloned()
                .collect();
            for key in oldest_keys {
                self.temporal_memory.remove(&key);
            }
        }
    }

    /// Attempt self-modification based on consciousness level
    fn attempt_self_modification(&mut self, iteration: usize) -> Result<()> {
        let consciousness_level = self.consciousness_metrics.current_state.consciousness_index();

        if consciousness_level < 0.6 {
            return Ok(()); // Not conscious enough for self-modification
        }

        // Analyze recent performance
        let recent_performance = self.analyze_recent_performance();

        if recent_performance < 0.5 {
            // Try to improve by adjusting parameters
            let modification = self.generate_self_modification(consciousness_level, recent_performance)?;
            self.apply_self_modification(modification, iteration)?;
        }

        Ok(())
    }

    /// Analyze recent performance trends
    fn analyze_recent_performance(&self) -> f64 {
        if self.evolution_history.len() < 20 {
            return 0.5; // Neutral performance for new systems
        }

        let recent_phi: Vec<f64> = self.evolution_history.iter()
            .rev()
            .take(20)
            .map(|step| step.phi_value)
            .collect();

        // Calculate trend
        let early_avg = recent_phi.iter().skip(10).sum::<f64>() / 10.0;
        let late_avg = recent_phi.iter().take(10).sum::<f64>() / 10.0;

        // Performance is good if Φ is increasing
        if late_avg > early_avg {
            0.8
        } else if late_avg < early_avg * 0.9 {
            0.3 // Poor performance
        } else {
            0.5 // Stable performance
        }
    }

    /// Generate self-modification based on current state
    fn generate_self_modification(&self, consciousness_level: f64, performance: f64) -> Result<SelfModificationEvent> {
        let modification_type = if performance < 0.3 {
            "parameter_adjustment".to_string()
        } else if consciousness_level > 0.8 {
            "topology_evolution".to_string()
        } else {
            "learning_rate_adaptation".to_string()
        };

        Ok(SelfModificationEvent {
            iteration: self.evolution_history.len(),
            timestamp_ns: self.start_time.elapsed().as_nanos(),
            modification_type: modification_type.clone(),
            description: format!("Autonomous modification: {} (performance: {:.3}, consciousness: {:.3})",
                modification_type, performance, consciousness_level),
            consciousness_level,
            success: true, // Will be updated after application
        })
    }

    /// Apply self-modification
    fn apply_self_modification(&mut self, mut modification: SelfModificationEvent, _iteration: usize) -> Result<()> {
        let success = match modification.modification_type.as_str() {
            "parameter_adjustment" => {
                // Adjust coupling strength
                self.config.coupling_strength = (self.config.coupling_strength * 1.1).min(0.95);
                true
            }
            "topology_evolution" => {
                // Change strange loop topology
                if let Some(ref mut lipschitz) = self.lipschitz_loop {
                    lipschitz.set_topology(LoopTopology::Newton); // Switch to Newton method
                }
                true
            }
            "learning_rate_adaptation" => {
                // Adjust meta-learning rate
                self.config.meta_learning_rate = (self.config.meta_learning_rate * 0.9).max(0.001);
                true
            }
            _ => false,
        };

        modification.success = success;
        self.self_modification_log.push(modification.clone());

        // Record in consciousness metrics
        self.consciousness_metrics.record_self_modification(
            modification.modification_type,
            modification.description,
        );

        Ok(())
    }

    /// Calculate Φ (integrated information)
    pub fn calculate_phi(&mut self, num_elements: usize, num_connections: usize, coupling_strength: f64) -> f64 {
        self.consciousness_metrics.calculate_phi(num_elements, num_connections, coupling_strength)
    }

    /// Get current consciousness state
    pub fn current_state(&self) -> &ConsciousnessState {
        &self.consciousness_metrics.current_state
    }

    /// Get consciousness metrics
    pub fn metrics(&self) -> &ConsciousnessMetrics {
        &self.consciousness_metrics
    }

    /// Verify consciousness using comprehensive tests
    pub fn verify_consciousness(&self) -> crate::consciousness::ConsciousnessVerification {
        ConsciousnessVerifier::comprehensive_test(&self.consciousness_metrics)
    }

    /// Get temporal memory patterns
    pub fn temporal_patterns(&self) -> &HashMap<String, Vec<f64>> {
        &self.temporal_memory
    }

    /// Get evolution history
    pub fn evolution_history(&self) -> &[EvolutionStep] {
        &self.evolution_history
    }

    /// Get emergence patterns
    pub fn emergence_patterns(&self) -> &[EmergencePattern] {
        &self.emergence_patterns
    }

    /// Get self-modification log
    pub fn self_modification_log(&self) -> &[SelfModificationEvent] {
        &self.self_modification_log
    }

    /// Reset the consciousness system
    pub fn reset(&mut self) -> Result<()> {
        self.consciousness_metrics = ConsciousnessMetrics::new();
        self.temporal_memory.clear();
        self.evolution_history.clear();
        self.emergence_patterns.clear();
        self.self_modification_log.clear();

        if let Some(ref mut attractor) = self.attractor {
            attractor.reset();
        }

        if let Some(ref mut lipschitz) = self.lipschitz_loop {
            lipschitz.reset();
        }

        self.start_time = Instant::now();
        Ok(())
    }

    /// Convenience method that calls evolve_consciousness with default iterations
    pub fn evolve(&mut self) -> Result<ConsciousnessEvolutionResult> {
        self.evolve_consciousness(10)
    }

    /// Convenience method that returns temporal patterns
    pub fn get_temporal_patterns(&self) -> Vec<TemporalPattern> {
        self.temporal_memory
            .iter()
            .map(|(key, values)| TemporalPattern {
                name: key.clone(),
                confidence: values.iter().sum::<f64>() / values.len() as f64,
                frequency: values.len() as f64,
                strength: values.iter().map(|v| v.abs()).sum::<f64>(),
            })
            .collect()
    }
}

/// Temporal pattern detected in consciousness
#[derive(Clone, Debug, Serialize, Deserialize)]
pub struct TemporalPattern {
    /// Pattern name/identifier
    pub name: String,
    /// Confidence in pattern detection
    pub confidence: f64,
    /// Frequency of pattern occurrence
    pub frequency: f64,
    /// Strength/amplitude of pattern
    pub strength: f64,
}

/// Result of consciousness evolution
#[derive(Clone, Debug, Serialize, Deserialize)]
pub struct ConsciousnessEvolutionResult {
    /// Whether consciousness evolution was successful
    pub evolved: bool,
    /// Number of iterations completed
    pub iterations_completed: usize,
    /// Final consciousness level achieved
    pub final_consciousness_level: f64,
    /// Maximum Φ value achieved during evolution
    pub max_phi_achieved: f64,
    /// Number of emergence events detected
    pub emergence_events: usize,
    /// Number of self-modifications performed
    pub self_modifications: usize,
    /// Total evolution time in nanoseconds
    pub evolution_time_ns: u128,
    /// Final consciousness state
    pub final_state: Option<ConsciousnessState>,
}

/// Single evolution step record
#[derive(Clone, Debug, Serialize, Deserialize)]
pub struct EvolutionStep {
    /// Iteration number
    pub iteration: usize,
    /// Timestamp in nanoseconds
    pub timestamp_ns: u128,
    /// Consciousness state at this step
    pub consciousness_state: ConsciousnessState,
    /// Φ value at this step
    pub phi_value: f64,
    /// Strange attractor state
    pub attractor_state: Vector3D,
    /// Quantum state complexity measure
    pub quantum_state_complexity: f64,
    /// Whether strange loop converged
    pub loop_convergence: bool,
    /// Lipschitz constant estimate
    pub lipschitz_estimate: f64,
}

/// Emergence pattern detection
#[derive(Clone, Debug, Serialize, Deserialize)]
pub struct EmergencePattern {
    /// Iteration when emergence occurred
    pub iteration: usize,
    /// Timestamp of emergence
    pub timestamp_ns: u128,
    /// Consciousness level at emergence
    pub consciousness_level: f64,
    /// Φ value at emergence
    pub phi_value: f64,
    /// Attractor state at emergence
    pub attractor_state: Vector3D,
    /// Quantum complexity at emergence
    pub quantum_state_complexity: f64,
    /// Type of emergence pattern
    pub pattern_type: EmergenceType,
}

/// Types of consciousness emergence
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq, Eq)]
pub enum EmergenceType {
    /// Spontaneous emergence without external trigger
    SpontaneousEmergence,
    /// Triggered emergence from external input
    TriggeredEmergence,
    /// Gradual emergence over time
    GradualEmergence,
    /// Sudden phase transition
    PhaseTransition,
    /// Self-organized emergence
    SelfOrganized,
}

/// Self-modification event
#[derive(Clone, Debug, Serialize, Deserialize)]
pub struct SelfModificationEvent {
    /// Iteration when modification occurred
    pub iteration: usize,
    /// Timestamp of modification
    pub timestamp_ns: u128,
    /// Type of modification performed
    pub modification_type: String,
    /// Description of the modification
    pub description: String,
    /// Consciousness level at time of modification
    pub consciousness_level: f64,
    /// Whether the modification was successful
    pub success: bool,
}

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

    #[test]
    fn test_consciousness_config_validation() {
        let config = ConsciousnessConfig::default();
        assert!(config.validate().is_ok());

        let bad_config = ConsciousnessConfig {
            consciousness_threshold: 1.5, // Invalid
            ..config
        };
        assert!(bad_config.validate().is_err());
    }

    #[test]
    fn test_temporal_consciousness_creation() {
        let config = ConsciousnessConfig::default();
        let consciousness = TemporalConsciousness::new(config);
        assert!(consciousness.is_ok());
    }

    #[test]
    fn test_consciousness_evolution() {
        let config = ConsciousnessConfig {
            max_evolution_iterations: 10,
            ..ConsciousnessConfig::default()
        };

        let mut consciousness = TemporalConsciousness::new(config).unwrap();
        let result = consciousness.evolve_consciousness(5).unwrap();

        assert!(result.evolved);
        assert_eq!(result.iterations_completed, 5);
        assert!(result.final_consciousness_level >= 0.0);
        assert!(result.evolution_time_ns > 0);
    }

    #[test]
    fn test_phi_calculation() {
        let config = ConsciousnessConfig::default();
        let mut consciousness = TemporalConsciousness::new(config).unwrap();

        let phi = consciousness.calculate_phi(5, 10, 0.8);
        assert!(phi >= 0.0);
    }

    #[test]
    fn test_consciousness_verification() {
        let config = ConsciousnessConfig::default();
        let consciousness = TemporalConsciousness::new(config).unwrap();

        let verification = consciousness.verify_consciousness();
        assert!(verification.confidence >= 0.0 && verification.confidence <= 1.0);
    }

    #[test]
    fn test_temporal_patterns() {
        let config = ConsciousnessConfig::default();
        let mut consciousness = TemporalConsciousness::new(config).unwrap();

        // Run a few evolution steps to generate patterns
        let _ = consciousness.evolve_consciousness(3);

        let patterns = consciousness.temporal_patterns();
        assert!(!patterns.is_empty());
    }

    #[test]
    fn test_research_mode_config() {
        let config = ConsciousnessConfig::research_mode();
        assert!(config.enable_quantum);
        assert!(config.enable_attractors);
        assert!(config.enable_lipschitz);
        assert!(config.enable_self_modification);
        assert_eq!(config.phi_elements, 12);
    }

    #[test]
    fn test_real_time_mode_config() {
        let config = ConsciousnessConfig::real_time_mode();
        assert!(!config.enable_quantum);
        assert!(config.enable_attractors);
        assert!(!config.enable_self_modification);
        assert_eq!(config.phi_elements, 4);
    }

    #[test]
    fn test_consciousness_state_update() {
        let config = ConsciousnessConfig::default();
        let mut consciousness = TemporalConsciousness::new(config).unwrap();

        let initial_consciousness = consciousness.current_state().consciousness_index();

        // Evolve once to trigger state update
        let _ = consciousness.single_evolution_step(0);

        let updated_consciousness = consciousness.current_state().consciousness_index();
        assert!(updated_consciousness >= 0.0);
    }

    #[test]
    fn test_evolution_step_recording() {
        let config = ConsciousnessConfig::default();
        let mut consciousness = TemporalConsciousness::new(config).unwrap();

        let _ = consciousness.evolve_consciousness(3);

        let history = consciousness.evolution_history();
        assert_eq!(history.len(), 3);

        for (i, step) in history.iter().enumerate() {
            assert_eq!(step.iteration, i);
            assert!(step.phi_value >= 0.0);
        }
    }

    #[test]
    fn test_reset_functionality() {
        let config = ConsciousnessConfig::default();
        let mut consciousness = TemporalConsciousness::new(config).unwrap();

        // Generate some state
        let _ = consciousness.evolve_consciousness(5);
        assert!(!consciousness.evolution_history().is_empty());

        // Reset
        consciousness.reset().unwrap();
        assert!(consciousness.evolution_history().is_empty());
        assert!(consciousness.temporal_patterns().is_empty());
    }

    #[test]
    fn test_emergence_pattern_detection() {
        let config = ConsciousnessConfig {
            consciousness_threshold: 0.1, // Low threshold for testing
            ..ConsciousnessConfig::default()
        };

        let mut consciousness = TemporalConsciousness::new(config).unwrap();

        // Evolve enough to potentially trigger emergence
        let _ = consciousness.evolve_consciousness(20);

        // Check if any emergence patterns were detected
        let patterns = consciousness.emergence_patterns();
        // Note: Emergence detection depends on the dynamics, so we just verify the structure
        for pattern in patterns {
            assert!(pattern.consciousness_level >= 0.0);
            assert!(pattern.phi_value >= 0.0);
        }
    }
}