// Performance Optimization System for Web Audio Visualizer
// Optimized for Hugging Face Spaces free tier deployment

interface PerformanceMetrics {
  fps: number
  frameTime: number
  memoryUsage: number
  cpuUsage: number
  gpuMemory: number
  particleCount: number
  lastUpdate: number
}

interface OptimizationSettings {
  targetFPS: number
  minFPS: number
  maxParticles: number
  minParticles: number
  adaptiveQualityStep: number
  memoryThreshold: number
  cpuThreshold: number
}

interface CacheEntry {
  data: any
  timestamp: number
  accessCount: number
  size: number
}

export class PerformanceOptimizer {
  private metrics: PerformanceMetrics
  private settings: OptimizationSettings
  private frameHistory: number[] = []
  private lastFrameTime: number = 0
  private adaptiveLevel: number = 1.0 // 1.0 = max quality, 0.1 = min quality
  
  // Caching system
  private shaderCache: Map<string, any> = new Map()
  private geometryCache: Map<string, any> = new Map()
  private materialCache: Map<string, any> = new Map()
  private calculationCache: Map<string, CacheEntry> = new Map()
  
  // Object pools for reuse
  private bufferPool: Map<string, Float32Array[]> = new Map()
  
  // Performance monitoring
  private performanceObserver: PerformanceObserver | null = null
  private memoryInfo: any = null

  constructor(settings: Partial<OptimizationSettings> = {}) {
    this.settings = {
      targetFPS: 60,
      minFPS: 30,
      maxParticles: 15000,
      minParticles: 3000,
      adaptiveQualityStep: 0.05,
      memoryThreshold: 100 * 1024 * 1024, // 100MB
      cpuThreshold: 80, // 80% CPU usage
      ...settings
    }

    this.metrics = {
      fps: 60,
      frameTime: 16.67,
      memoryUsage: 0,
      cpuUsage: 0,
      gpuMemory: 0,
      particleCount: this.settings.maxParticles,
      lastUpdate: performance.now()
    }

    this.initializePerformanceMonitoring()
  }

  private initializePerformanceMonitoring() {
    // Modern performance monitoring
    if ('PerformanceObserver' in window) {
      this.performanceObserver = new PerformanceObserver((_list) => {
        // Performance entries are processed in updatePerformance method
      })
      try {
        this.performanceObserver.observe({ entryTypes: ['measure'] })
      } catch (e) {
        console.warn('Performance monitoring not fully supported')
      }
    }

    // Memory monitoring for supported browsers
    if ('memory' in performance) {
      this.memoryInfo = (performance as any).memory
    }
  }

  // Adaptive quality management
  updatePerformance(currentTime: number): void {
    const deltaTime = currentTime - this.lastFrameTime
    this.lastFrameTime = currentTime

    if (deltaTime > 0) {
      const currentFPS = 1000 / deltaTime
      this.frameHistory.push(currentFPS)
      
      // Keep only last 60 frames for rolling average
      if (this.frameHistory.length > 60) {
        this.frameHistory.shift()
      }

      // Calculate average FPS
      const avgFPS = this.frameHistory.reduce((a, b) => a + b, 0) / this.frameHistory.length
      this.metrics.fps = Math.round(avgFPS)
      this.metrics.frameTime = deltaTime

      // Update memory usage if available
      if (this.memoryInfo) {
        this.metrics.memoryUsage = this.memoryInfo.usedJSHeapSize
        this.metrics.gpuMemory = this.memoryInfo.totalJSHeapSize
      }

      // Adaptive quality adjustment
      this.adjustQualityLevel()
    }
  }

  private adjustQualityLevel(): void {
    const { fps } = this.metrics
    const { targetFPS, minFPS, adaptiveQualityStep } = this.settings

    if (fps < minFPS) {
      // Performance is bad, reduce quality aggressively
      this.adaptiveLevel = Math.max(0.1, this.adaptiveLevel - adaptiveQualityStep * 2)
      console.warn(`🚨 Performance low (${fps} FPS), reducing quality to ${(this.adaptiveLevel * 100).toFixed(0)}%`)
    } else if (fps < targetFPS) {
      // Performance is below target, reduce quality gradually
      this.adaptiveLevel = Math.max(0.1, this.adaptiveLevel - adaptiveQualityStep)
    } else if (fps > targetFPS + 10 && this.adaptiveLevel < 1.0) {
      // Performance is good, increase quality gradually
      this.adaptiveLevel = Math.min(1.0, this.adaptiveLevel + adaptiveQualityStep * 0.5)
    }

    // Update particle count based on quality level
    const targetParticles = Math.floor(
      this.settings.minParticles + 
      (this.settings.maxParticles - this.settings.minParticles) * this.adaptiveLevel
    )
    this.metrics.particleCount = targetParticles
  }

  // Smart caching system
  getCachedCalculation(key: string, calculator: () => any, ttl: number = 1000): any {
    const cached = this.calculationCache.get(key)
    const now = performance.now()

    if (cached && (now - cached.timestamp) < ttl) {
      cached.accessCount++
      return cached.data
    }

    // Calculate new value
    const data = calculator()
    this.calculationCache.set(key, {
      data,
      timestamp: now,
      accessCount: 1,
      size: this.estimateSize(data)
    })

    // Clean cache if it gets too large
    this.cleanCache()
    return data
  }

  // Shader caching for Three.js materials
  getCachedShader(vertexShader: string, fragmentShader: string, uniforms: any): any {
    const key = this.hashShader(vertexShader, fragmentShader)
    
    if (this.shaderCache.has(key)) {
      const cached = this.shaderCache.get(key)
      // Update uniforms on cached shader
      Object.assign(cached.uniforms, uniforms)
      return cached
    }

    // Create new shader (this would be done in the component)
    return null // Component will create and cache
  }

  cacheShader(vertexShader: string, fragmentShader: string, material: any): void {
    const key = this.hashShader(vertexShader, fragmentShader)
    this.shaderCache.set(key, material)
  }

  // Geometry and buffer pooling
  getPooledBuffer(type: string, size: number): Float32Array {
    const poolKey = `${type}_${size}`
    
    if (!this.bufferPool.has(poolKey)) {
      this.bufferPool.set(poolKey, [])
    }

    const pool = this.bufferPool.get(poolKey)!
    
    if (pool.length > 0) {
      const buffer = pool.pop()!
      buffer.fill(0) // Reset buffer
      return buffer
    }

    // Create new buffer if pool is empty
    return new Float32Array(size)
  }

  returnPooledBuffer(type: string, size: number, buffer: Float32Array): void {
    const poolKey = `${type}_${size}`
    
    if (!this.bufferPool.has(poolKey)) {
      this.bufferPool.set(poolKey, [])
    }

    const pool = this.bufferPool.get(poolKey)!
    
    // Limit pool size to prevent memory bloat
    if (pool.length < 5) {
      pool.push(buffer)
    }
  }

  // Level of Detail (LOD) calculations
  getLODSettings(distance: number, importance: number = 1.0): {
    particleSize: number
    updateFrequency: number
    detailLevel: number
  } {
    const distanceFactor = Math.max(0.1, Math.min(1.0, 5.0 / distance))
    const qualityFactor = this.adaptiveLevel * importance
    
    return {
      particleSize: distanceFactor * qualityFactor,
      updateFrequency: Math.max(1, Math.floor(10 / (distanceFactor * qualityFactor))),
      detailLevel: distanceFactor * qualityFactor
    }
  }

  // Frame skipping for heavy operations
  shouldSkipFrame(_operation: string, frequency: number): boolean {
    const frameCount = Math.floor(performance.now() / 16.67) // Approximate frame count
    const skipPattern = Math.max(1, Math.floor(frequency / this.adaptiveLevel))
    
    return frameCount % skipPattern !== 0
  }

  // Memory management
  private cleanCache(): void {
    const now = performance.now()
    const maxCacheAge = 30000 // 30 seconds
    const maxCacheSize = 50 * 1024 * 1024 // 50MB

    let totalSize = 0
    const entries = Array.from(this.calculationCache.entries())
    
    // Calculate total cache size
    entries.forEach(([_, entry]) => {
      totalSize += entry.size
    })

    // Clean old or least used entries if cache is too large
    if (totalSize > maxCacheSize) {
      entries
        .sort((a, b) => {
          const scoreA = a[1].accessCount / (now - a[1].timestamp)
          const scoreB = b[1].accessCount / (now - b[1].timestamp)
          return scoreA - scoreB // Lower score = less valuable
        })
        .slice(0, Math.floor(entries.length * 0.3)) // Remove 30% least valuable
        .forEach(([key, _]) => {
          this.calculationCache.delete(key)
        })
    }

    // Remove old entries
    entries.forEach(([key, entry]) => {
      if (now - entry.timestamp > maxCacheAge) {
        this.calculationCache.delete(key)
      }
    })
  }

  // Utility functions
  private hashShader(vertex: string, fragment: string): string {
    // Simple hash function for shader caching
    let hash = 0
    const str = vertex + fragment
    for (let i = 0; i < str.length; i++) {
      const char = str.charCodeAt(i)
      hash = ((hash << 5) - hash) + char
      hash = hash & hash // Convert to 32-bit integer
    }
    return hash.toString()
  }

  private estimateSize(obj: any): number {
    // Rough size estimation for caching
    const str = JSON.stringify(obj)
    return str.length * 2 // Approximate bytes (UTF-16)
  }

  // Public getters
  getMetrics(): PerformanceMetrics {
    return { ...this.metrics }
  }

  getAdaptiveLevel(): number {
    return this.adaptiveLevel
  }

  getOptimalParticleCount(baseCount: number): number {
    return Math.floor(baseCount * this.adaptiveLevel)
  }

  getOptimalUpdateFrequency(baseFrequency: number): number {
    return Math.max(1, Math.floor(baseFrequency / this.adaptiveLevel))
  }

  // Cleanup
  dispose(): void {
    if (this.performanceObserver) {
      this.performanceObserver.disconnect()
    }
    
    this.shaderCache.clear()
    this.geometryCache.clear()
    this.materialCache.clear()
    this.calculationCache.clear()
    this.bufferPool.clear()
  }
}

// Singleton instance for global use
export const performanceOptimizer = new PerformanceOptimizer({
  targetFPS: 60,
  minFPS: 25, // Lower threshold for Hugging Face Spaces
  maxParticles: 8000, // Reduced for CPU deployment
  minParticles: 2000,
  adaptiveQualityStep: 0.08,
  memoryThreshold: 80 * 1024 * 1024, // 80MB for free tier
  cpuThreshold: 75
})