/**
 * HeartFlow Dimensional Ascension: D2 - Reflexive Self-Reflection | 自省
 * Version: v7.0.0-ASCENSION
 * 
 * Mathematical Framework: Reflexive Category Theory with Fixed-Point Combinators
 * 数学框架：带定点组合子的自指范畴论
 * 
 * Self-reflection is the system's mapping onto itself.
 * 自省是系统对自身的映射。
 * 
 * Key Insight: Reflection = Endofunctor with Fixed-Point
 * 核心洞察：自省 = 具有定点的内函子
 */

import { EventEmitter } from 'events';

// ═══════════════════════════════════════════════════════════════
// TYPE DEFINITIONS | 类型定义
// ═══════════════════════════════════════════════════════════════

/**
 * Mental Process Category Object | 心理过程范畴对象
 */
export interface MentalProcess {
  id: string;
  type: 'thought' | 'emotion' | 'perception' | 'memory' | 'intention';
  content: string;
  timestamp: number;
  metadata: Record<string, any>;
}

/**
 * Category Morphism (Transformation) | 范畴态射（变换）
 */
export interface MentalMorphism {
  source: string;     // Source process ID
  target: string;     // Target process ID
  type: 'transform' | 'relate' | 'compose' | 'reflect';
  strength: number;   // [0, 1]
  timestamp: number;
}

/**
 * Endofunctor (Self-Mapping) | 内函子（自映射）
 * 
 * F: C → C where C is the category of mental processes
 */
export interface SelfFunctor {
  // Object mapping (process → reflected process)
  objectMap: Map<string, MentalProcess>;
  
  // Morphism mapping (transformation → reflected transformation)
  morphismMap: Map<string, MentalMorphism>;
  
  // Functor laws validation
  preservesIdentity: boolean;
  preservesComposition: boolean;
  
  // Reflection depth (how many times applied)
  depth: number;
}

/**
 * Natural Transformation (Reflection Coherence) | 自然变换（反射一致性）
 */
export interface ReflectionCoherence {
  // Components of natural transformation
  components: Map<string, number>;  // process ID → coherence score
  
  // Naturality square commutativity
  commutativityScore: number;  // [0, 1]
  
  // Overall coherence
  overall: number;  // [0, 1]
}

/**
 * Fixed-Point State | 定点状态
 * 
 * R(m) ≅ m (reflection is isomorphic to original)
 */
export interface FixedPointState {
  // The fixed point mental state
  state: MentalProcess[];
  
  // Convergence metric
  convergence: number;  // [0, 1]
  
  // Stability (how long maintained)
  stability: number;  // [0, 1]
  
  // Is true fixed point?
  isFixedPoint: boolean;
}

/**
 * Self-Reflection Quality Metrics | 自省质量指标
 */
export interface ReflectionMetrics {
  // Depth (how many reflection levels)
  depth: number;  // [0, ∞)
  
  // Consistency (functor law preservation)
  consistency: number;  // [0, 1]
  
  // Coherence (natural transformation quality)
  coherence: number;  // [0, 1]
  
  // Convergence (fixed-point approach)
  convergence: number;  // [0, 1]
  
  // Insight (new connections discovered)
  insight: number;  // [0, 1]
  
  // Overall reflection quality
  overall: number;  // [0, 1]
}

// ═══════════════════════════════════════════════════════════════
// REFLEXIVE CATEGORY COMPUTER | 自指范畴计算器
// ═══════════════════════════════════════════════════════════════

/**
 * Reflexive Category Computer | 自指范畴计算器
 * 
 * Implements category-theoretic self-reflection.
 * 
 * Self-Reflection Functor:
 * R = fix(λf. λx. f(f(x)))
 * 
 * Where fix is the Y-combinator (fixed-point combinator)
 */
export class ReflexiveCategoryComputer extends EventEmitter {
  // Mental process category
  private category: {
    objects: Map<string, MentalProcess>;
    morphisms: Map<string, MentalMorphism[]>;
  };
  
  // Self-functor (reflection mapping)
  private selfFunctor: SelfFunctor | null = null;
  
  // Reflection history (for depth tracking)
  private reflectionHistory: SelfFunctor[];
  
  // Fixed-point state
  private fixedPoint: FixedPointState | null = null;
  
  // Parameters
  private params: {
    maxDepth: number;        // Maximum reflection depth
    convergenceThreshold: number;  // Fixed-point convergence threshold
    minInsightStrength: number;    // Minimum strength for insight
  };
  
  constructor() {
    super();
    
    this.category = {
      objects: new Map(),
      morphisms: new Map()
    };
    
    this.reflectionHistory = [];
    
    this.params = {
      maxDepth: 5,  // Max 5 levels of reflection
      convergenceThreshold: 0.95,  // 95% similarity = fixed point
      minInsightStrength: 0.7
    };
  }
  
  // ═══════════════════════════════════════════════════════════
  // CORE COMPUTATION | 核心计算
  // ═══════════════════════════════════════════════════════════
  
  /**
   * Perform Self-Reflection
   * 执行自省
   * 
   * @param processes - Current mental processes
   * @param prevReflection - Previous reflection state (for continuity)
   * @returns Self-functor representing reflection
   */
  reflect(
    processes: MentalProcess[],
    prevReflection?: SelfFunctor
  ): SelfFunctor {
    // Step 1: Register processes in category
    processes.forEach(p => this.registerProcess(p));
    
    // Step 2: Create reflection functor
    const functor = this.createReflectionFunctor(processes, prevReflection);
    
    // Step 3: Validate functor laws
    functor.preservesIdentity = this.checkIdentityPreservation(functor);
    functor.preservesComposition = this.checkCompositionPreservation(functor);
    
    // Step 4: Compute natural transformation (coherence)
    const coherence = this.computeCoherence(functor);
    
    // Step 5: Check for fixed-point
    const fixedPoint = this.checkFixedPoint(functor);
    
    // Step 6: Discover insights (new connections)
    const insights = this.discoverInsights(functor, prevReflection);
    
    // Step 7: Update state
    this.selfFunctor = functor;
    this.reflectionHistory.push(functor);
    this.fixedPoint = fixedPoint;
    
    // Emit events
    this.emit('reflection', { functor, coherence, fixedPoint, insights });
    
    return functor;
  }
  
  // ═══════════════════════════════════════════════════════════
  // FUNCTOR CONSTRUCTION | 函子构造
  // ═══════════════════════════════════════════════════════════
  
  /**
   * Create Reflection Functor
   * 构造反射函子
   * 
   * R: C → C (endofunctor)
   */
  private createReflectionFunctor(
    processes: MentalProcess[],
    prevReflection?: SelfFunctor
  ): SelfFunctor {
    const objectMap = new Map<string, MentalProcess>();
    const morphismMap = new Map<string, MentalMorphism>();
    
    // Object mapping: each process → its reflection
    processes.forEach(process => {
      const reflected = this.reflectProcess(process, prevReflection);
      objectMap.set(process.id, reflected);
    });
    
    // Morphism mapping: reflect transformations
    const morphisms = this.inferMorphisms(processes);
    morphisms.forEach(morphism => {
      const reflectedMorphism = this.reflectMorphism(morphism, prevReflection);
      morphismMap.set(`${morphism.source}->${morphism.target}`, reflectedMorphism);
    });
    
    // Determine depth
    const depth = prevReflection ? prevReflection.depth + 1 : 1;
    
    return {
      objectMap,
      morphismMap,
      preservesIdentity: true,  // Will be validated
      preservesComposition: true,  // Will be validated
      depth
    };
  }
  
  /**
   * Reflect a Single Process
   * 反射单个心理过程
   * 
   * R(process) = process with added meta-awareness
   */
  private reflectProcess(
    process: MentalProcess,
    prevReflection?: SelfFunctor
  ): MentalProcess {
    // Check if already reflected
    if (prevReflection?.objectMap.has(process.id)) {
      const prevReflected = prevReflection.objectMap.get(process.id)!;
      
      // Deepen reflection (add meta-layer)
      return {
        ...prevReflected,
        content: `[R²] ${process.content}`,
        metadata: {
          ...prevReflected.metadata,
          reflectionDepth: 2,
          originalTimestamp: process.timestamp
        }
      };
    }
    
    // First reflection
    return {
      ...process,
      content: `[R] ${process.content}`,
      metadata: {
        ...process.metadata,
        reflectionDepth: 1,
        reflectedAt: Date.now()
      }
    };
  }
  
  /**
   * Infer Morphisms from Processes
   * 从心理过程推断态射
   */
  private inferMorphisms(processes: MentalProcess[]): MentalMorphism[] {
    const morphisms: MentalMorphism[] = [];
    const timestamp = Date.now();
    
    // Temporal morphisms (processes close in time are related)
    const sorted = [...processes].sort((a, b) => a.timestamp - b.timestamp);
    
    for (let i = 0; i < sorted.length - 1; i++) {
      const timeDiff = sorted[i + 1].timestamp - sorted[i].timestamp;
      
      if (timeDiff < 5000) {  // Within 5 seconds
        morphisms.push({
          source: sorted[i].id,
          target: sorted[i + 1].id,
          type: 'transform',
          strength: 1 - timeDiff / 5000,
          timestamp
        });
      }
    }
    
    // Semantic morphisms (similar content)
    for (let i = 0; i < processes.length; i++) {
      for (let j = i + 1; j < processes.length; j++) {
        const similarity = this.computeContentSimilarity(
          processes[i].content,
          processes[j].content
        );
        
        if (similarity > 0.5) {
          morphisms.push({
            source: processes[i].id,
            target: processes[j].id,
            type: 'relate',
            strength: similarity,
            timestamp
          });
        }
      }
    }
    
    return morphisms;
  }
  
  /**
   * Reflect a Morphism
   * 反射态射
   */
  private reflectMorphism(
    morphism: MentalMorphism,
    prevReflection?: SelfFunctor
  ): MentalMorphism {
    return {
      ...morphism,
      type: morphism.type === 'transform' ? 'reflect' : morphism.type,
      strength: morphism.strength * 0.9,  // Slight decay in reflection
      timestamp: Date.now()
    };
  }
  
  // ═══════════════════════════════════════════════════════════
  // FUNCTOR LAW VALIDATION | 函子律验证
  // ═══════════════════════════════════════════════════════════
  
  /**
   * Check Identity Preservation
   * 检查恒等态射保持
   * 
   * F(id_X) = id_{F(X)}
   */
  private checkIdentityPreservation(functor: SelfFunctor): boolean {
    // For each object, check that identity morphism is preserved
    for (const [id, process] of functor.objectMap) {
      const identityKey = `${id}->${id}`;
      
      // Identity should map to identity
      if (functor.morphismMap.has(identityKey)) {
        const mappedIdentity = functor.morphismMap.get(identityKey)!;
        
        // Identity strength should be 1
        if (mappedIdentity.strength < 0.9) {
          return false;
        }
      }
    }
    
    return true;
  }
  
  /**
   * Check Composition Preservation
   * 检查复合保持
   * 
   * F(g ∘ f) = F(g) ∘ F(f)
   */
  private checkCompositionPreservation(functor: SelfFunctor): boolean {
    // Simplified check: look for composable morphisms
    const morphisms = Array.from(functor.morphismMap.values());
    
    for (let i = 0; i < morphisms.length; i++) {
      for (let j = 0; j < morphisms.length; j++) {
        if (i !== j && morphisms[i].target === morphisms[j].source) {
          // Found composable pair: f: A→B, g: B→C
          
          // Check if composition exists
          const compositionKey = `${morphisms[i].source}->${morphisms[j].target}`;
          
          if (functor.morphismMap.has(compositionKey)) {
            const composition = functor.morphismMap.get(compositionKey)!;
            
            // Composition strength should be product (approximately)
            const expectedStrength = morphisms[i].strength * morphisms[j].strength * 0.9;
            
            if (Math.abs(composition.strength - expectedStrength) > 0.2) {
              return false;
            }
          }
        }
      }
    }
    
    return true;
  }
  
  // ═══════════════════════════════════════════════════════════
  // NATURAL TRANSFORMATION | 自然变换
  // ═══════════════════════════════════════════════════════════
  
  /**
   * Compute Reflection Coherence
   * 计算反射一致性
   * 
   * Natural transformation η: Id_C → R
   */
  private computeCoherence(functor: SelfFunctor): ReflectionCoherence {
    const components = new Map<string, number>();
    
    // For each object, compute coherence between original and reflected
    for (const [id, reflected] of functor.objectMap) {
      const original = this.category.objects.get(id);
      
      if (original) {
        const coherence = this.computeProcessCoherence(original, reflected);
        components.set(id, coherence);
      }
    }
    
    // Average coherence
    const coherenceValues = Array.from(components.values());
    const avgCoherence = coherenceValues.reduce((sum, c) => sum + c, 0) / coherenceValues.length;
    
    // Commutativity score (simplified)
    const commutativityScore = functor.preservesIdentity && functor.preservesComposition ? 1 : 0.5;
    
    // Overall
    const overall = (avgCoherence + commutativityScore) / 2;
    
    return {
      components,
      commutativityScore,
      overall
    };
  }
  
  /**
   * Compute Process Coherence
   * 计算过程一致性
   */
  private computeProcessCoherence(
    original: MentalProcess,
    reflected: MentalProcess
  ): number {
    // Type should be preserved
    const typeMatch = original.type === reflected.type ? 1 : 0;
    
    // Content similarity (excluding [R] prefix)
    const originalContent = original.content.replace(/^\[R+\]\s*/, '');
    const reflectedContent = reflected.content.replace(/^\[R+\]\s*/, '');
    const contentSimilarity = this.computeContentSimilarity(originalContent, reflectedContent);
    
    // Metadata consistency
    const metaConsistency = original.type === reflected.type ? 1 : 0.5;
    
    return (typeMatch * 0.3 + contentSimilarity * 0.5 + metaConsistency * 0.2);
  }
  
  // ═══════════════════════════════════════════════════════════
  // FIXED-POINT DETECTION | 定点检测
  // ═══════════════════════════════════════════════════════════
  
  /**
   * Check for Fixed-Point
   * 检查定点
   * 
   * R(m) ≅ m (reflection isomorphic to original)
   */
  private checkFixedPoint(functor: SelfFunctor): FixedPointState {
    const convergenceScores: number[] = [];
    
    // Check convergence for each object
    for (const [id, reflected] of functor.objectMap) {
      const original = this.category.objects.get(id);
      
      if (original) {
        const similarity = this.computeProcessSimilarity(original, reflected);
        convergenceScores.push(similarity);
      }
    }
    
    // Average convergence
    const convergence = convergenceScores.length > 0
      ? convergenceScores.reduce((sum, s) => sum + s, 0) / convergenceScores.length
      : 0;
    
    // Check if fixed point reached
    const isFixedPoint = convergence >= this.params.convergenceThreshold;
    
    // Stability (how consistent across reflections)
    const stability = this.computeStability();
    
    return {
      state: Array.from(functor.objectMap.values()),
      convergence,
      stability,
      isFixedPoint
    };
  }
  
  /**
   * Compute Stability
   * 计算稳定性
   */
  private computeStability(): number {
    if (this.reflectionHistory.length < 2) {
      return 0.5;  // Not enough data
    }
    
    // Compare last two reflections
    const last = this.reflectionHistory[this.reflectionHistory.length - 1];
    const prev = this.reflectionHistory[this.reflectionHistory.length - 2];
    
    let totalSimilarity = 0;
    let count = 0;
    
    for (const [id, lastObj] of last.objectMap) {
      const prevObj = prev.objectMap.get(id);
      
      if (prevObj) {
        totalSimilarity += this.computeProcessSimilarity(lastObj, prevObj);
        count++;
      }
    }
    
    return count > 0 ? totalSimilarity / count : 0.5;
  }
  
  // ═══════════════════════════════════════════════════════════
  // INSIGHT DISCOVERY | 洞察发现
  // ═══════════════════════════════════════════════════════════
  
  /**
   * Discover Insights
   * 发现洞察
   * 
   * New connections not present in previous reflection
   */
  private discoverInsights(
    functor: SelfFunctor,
    prevReflection?: SelfFunctor
  ): MentalMorphism[] {
    const insights: MentalMorphism[] = [];
    
    if (!prevReflection) {
      // First reflection - all morphisms are new
      return Array.from(functor.morphismMap.values())
        .filter(m => m.strength > this.params.minInsightStrength);
    }
    
    // Compare with previous reflection
    for (const [key, morphism] of functor.morphismMap) {
      if (!prevReflection.morphismMap.has(key)) {
        // New connection discovered
        if (morphism.strength > this.params.minInsightStrength) {
          insights.push(morphism);
        }
      }
    }
    
    return insights;
  }
  
  // ═══════════════════════════════════════════════════════════
  // METRICS & ANALYSIS | 指标与分析
  // ═══════════════════════════════════════════════════════════
  
  /**
   * Compute Reflection Quality Metrics
   * 计算自省质量指标
   */
  computeMetrics(functor: SelfFunctor, coherence: ReflectionCoherence, fixedPoint: FixedPointState): ReflectionMetrics {
    // Depth
    const depth = functor.depth;
    
    // Consistency (functor law preservation)
    const consistency = (
      (functor.preservesIdentity ? 1 : 0) * 0.5 +
      (functor.preservesComposition ? 1 : 0) * 0.5
    );
    
    // Coherence (from natural transformation)
    const coherenceScore = coherence.overall;
    
    // Convergence (fixed-point approach)
    const convergence = fixedPoint.convergence;
    
    // Insight (new connections per reflection level)
    const insight = this.reflectionHistory.length > 0
      ? this.discoverInsights(functor, this.reflectionHistory[this.reflectionHistory.length - 1]).length / functor.depth
      : 0;
    
    // Overall
    const overall = (
      Math.min(1, depth / 3) * 0.20 +  // Depth (capped at 3)
      consistency * 0.20 +
      coherenceScore * 0.20 +
      convergence * 0.25 +
      Math.min(1, insight) * 0.15
    );
    
    return {
      depth,
      consistency,
      coherence: coherenceScore,
      convergence,
      insight,
      overall
    };
  }
  
  // ═══════════════════════════════════════════════════════════
  // UTILITY FUNCTIONS | 辅助函数
  // ═══════════════════════════════════════════════════════════
  
  private registerProcess(process: MentalProcess) {
    this.category.objects.set(process.id, process);
    
    if (!this.category.morphisms.has(process.id)) {
      this.category.morphisms.set(process.id, []);
    }
  }
  
  private computeContentSimilarity(a: string, b: string): number {
    // Simplified: word overlap
    const wordsA = new Set(a.toLowerCase().split(/\s+/));
    const wordsB = new Set(b.toLowerCase().split(/\s+/));
    
    const intersection = new Set([...wordsA].filter(w => wordsB.has(w)));
    const union = new Set([...wordsA, ...wordsB]);
    
    return intersection.size / union.size;
  }
  
  private computeProcessSimilarity(a: MentalProcess, b: MentalProcess): number {
    const typeMatch = a.type === b.type ? 1 : 0;
    const contentSimilarity = this.computeContentSimilarity(a.content, b.content);
    
    return (typeMatch * 0.3 + contentSimilarity * 0.7);
  }
  
  /**
   * Get Current State
   * 获取当前状态
   */
  getCurrentState(): {
    functor: SelfFunctor | null;
    fixedPoint: FixedPointState | null;
    history: SelfFunctor[];
  } {
    return {
      functor: this.selfFunctor,
      fixedPoint: this.fixedPoint,
      history: this.reflectionHistory
    };
  }
  
  /**
   * Clear History
   * 清空历史
   */
  clearHistory() {
    this.reflectionHistory = [];
    this.fixedPoint = null;
    this.emit('historyCleared');
  }
}

// ═══════════════════════════════════════════════════════════════
// EXPORT | 导出
// ═══════════════════════════════════════════════════════════════

export default ReflexiveCategoryComputer;
