import db from '../config/database';
import { logger } from '../utils/logger';

export interface ABTestAnalysisInput {
  tenantId: string;
  shopId: string;
  taskId: string;
  traceId: string;
  businessType: 'TOC' | 'TOB';
  testId: string;
  analysisType: 'CONVERSION' | 'REVENUE' | 'CTR' | 'BOUNCE_RATE' | 'CUSTOM';
  confidenceLevel?: number;
  minSampleSize?: number;
}

export interface ABTestAnalysisResult {
  success: boolean;
  testId: string;
  analysisType: string;
  analyzedAt: Date;
  variants: VariantAnalysis[];
  winner?: {
    variantId: string;
    variantName: string;
    improvement: number;
    confidence: number;
  };
  recommendation: string;
  isStatisticallySignificant: boolean;
}

export interface VariantAnalysis {
  variantId: string;
  variantName: string;
  visitors: number;
  conversions: number;
  conversionRate: number;
  revenue?: number;
  averageOrderValue?: number;
  confidenceInterval: {
    lower: number;
    upper: number;
  };
  standardError: number;
}

export interface StatisticalSummary {
  testId: string;
  totalVisitors: number;
  totalConversions: number;
  overallConversionRate: number;
  chiSquare?: number;
  pValue?: number;
  degreesOfFreedom?: number;
  power?: number;
}

export interface TrendAnalysisInput {
  tenantId: string;
  shopId: string;
  taskId: string;
  traceId: string;
  businessType: 'TOC' | 'TOB';
  testId: string;
  granularity: 'HOURLY' | 'DAILY' | 'WEEKLY';
  startDate: Date;
  endDate: Date;
}

export interface TrendAnalysisResult {
  success: boolean;
  testId: string;
  granularity: string;
  trends: TrendDataPoint[];
  insights: string[];
}

export interface TrendDataPoint {
  timestamp: Date;
  variantId: string;
  variantName: string;
  visitors: number;
  conversions: number;
  conversionRate: number;
  cumulativeVisitors: number;
  cumulativeConversions: number;
  cumulativeConversionRate: number;
}

export interface SegmentAnalysisInput {
  tenantId: string;
  shopId: string;
  taskId: string;
  traceId: string;
  businessType: 'TOC' | 'TOB';
  testId: string;
  segmentBy: 'DEVICE' | 'GEO' | 'REFERRER' | 'USER_TYPE' | 'TIME';
}

export interface SegmentAnalysisResult {
  success: boolean;
  testId: string;
  segmentBy: string;
  segments: SegmentData[];
  insights: string[];
}

export interface SegmentData {
  segmentName: string;
  segmentValue: string;
  variants: VariantSegmentData[];
  winner?: {
    variantId: string;
    variantName: string;
    lift: number;
  };
}

export interface VariantSegmentData {
  variantId: string;
  variantName: string;
  visitors: number;
  conversions: number;
  conversionRate: number;
  lift: number;
}

export class ABTestAnalysisService {
  static async analyzeABTest(input: ABTestAnalysisInput): Promise<ABTestAnalysisResult> {
    const { tenantId, shopId, taskId, traceId, businessType, testId, analysisType, confidenceLevel = 0.95, minSampleSize = 100 } = input;

    logger.info(`[ABTestAnalysisService] Analyzing A/B test - testId: ${testId}, type: ${analysisType}, tenantId: ${tenantId}, traceId: ${traceId}`);

    try {
      const test = await db('cf_ab_tests')
        .where({ id: testId, tenant_id: tenantId, shop_id: shopId })
        .first();

      if (!test) {
        throw new Error(`A/B test not found: ${testId}`);
      }

      const variants = await db('cf_ab_test_variants')
        .where({ test_id: testId })
        .select('*');

      if (variants.length < 2) {
        throw new Error('A/B test must have at least 2 variants');
      }

      const variantAnalysis: VariantAnalysis[] = [];
      let controlVariant: VariantAnalysis | null = null;

      for (const variant of variants) {
        const stats = await this.getVariantStats(testId, variant.id, analysisType);

        const conversionRate = stats.visitors > 0 ? stats.conversions / stats.visitors : 0;
        const standardError = Math.sqrt((conversionRate * (1 - conversionRate)) / stats.visitors);
        const zScore = this.getZScore(confidenceLevel);

        const analysis: VariantAnalysis = {
          variantId: variant.id,
          variantName: variant.name,
          visitors: stats.visitors,
          conversions: stats.conversions,
          conversionRate,
          revenue: stats.revenue,
          averageOrderValue: stats.conversions > 0 ? (stats.revenue || 0) / stats.conversions : 0,
          confidenceInterval: {
            lower: Math.max(0, conversionRate - zScore * standardError),
            upper: Math.min(1, conversionRate + zScore * standardError),
          },
          standardError,
        };

        variantAnalysis.push(analysis);

        if (variant.is_control) {
          controlVariant = analysis;
        }
      }

      if (!controlVariant && variantAnalysis.length > 0) {
        controlVariant = variantAnalysis[0];
      }

      let winner: { variantId: string; variantName: string; improvement: number; confidence: number } | undefined;
      let isStatisticallySignificant = false;

      if (controlVariant) {
        const bestVariant = variantAnalysis.reduce((best, current) =>
          current.conversionRate > best.conversionRate ? current : best
        );

        if (bestVariant.variantId !== controlVariant.variantId) {
          const pooledSE = Math.sqrt(
            Math.pow(bestVariant.standardError, 2) + Math.pow(controlVariant.standardError, 2)
          );
          const zScore = (bestVariant.conversionRate - controlVariant.conversionRate) / pooledSE;
          const pValue = this.calculatePValue(zScore);

          isStatisticallySignificant = pValue < (1 - confidenceLevel);

          if (isStatisticallySignificant && bestVariant.visitors >= minSampleSize) {
            winner = {
              variantId: bestVariant.variantId,
              variantName: bestVariant.variantName,
              improvement: ((bestVariant.conversionRate - controlVariant.conversionRate) / controlVariant.conversionRate) * 100,
              confidence: confidenceLevel * 100,
            };
          }
        }
      }

      const recommendation = this.generateRecommendation(variantAnalysis, winner, isStatisticallySignificant, minSampleSize);

      await db('cf_ab_test_analyses').insert({
        id: `ANALYSIS-${Date.now()}-${Math.random().toString(36).substr(2, 9)}`,
        test_id: testId,
        tenant_id: tenantId,
        shop_id: shopId,
        task_id: taskId,
        trace_id: traceId,
        business_type: businessType,
        analysis_type: analysisType,
        confidence_level: confidenceLevel,
        winner_variant_id: winner?.variantId,
        improvement: winner?.improvement,
        is_significant: isStatisticallySignificant,
        recommendation,
        analyzed_at: new Date(),
      });

      logger.info(`[ABTestAnalysisService] A/B test analysis completed - testId: ${testId}, winner: ${winner?.variantName || 'none'}`);

      return {
        success: true,
        testId,
        analysisType,
        analyzedAt: new Date(),
        variants: variantAnalysis,
        winner,
        recommendation,
        isStatisticallySignificant,
      };
    } catch (error: any) {
      logger.error(`[ABTestAnalysisService] A/B test analysis failed - testId: ${testId}, error: ${error.message}`);
      throw error;
    }
  }

  static async analyzeTrends(input: TrendAnalysisInput): Promise<TrendAnalysisResult> {
    const { tenantId, shopId, taskId, traceId, businessType, testId, granularity, startDate, endDate } = input;

    logger.info(`[ABTestAnalysisService] Analyzing trends - testId: ${testId}, granularity: ${granularity}, tenantId: ${tenantId}, traceId: ${traceId}`);

    try {
      const variants = await db('cf_ab_test_variants')
        .where({ test_id: testId })
        .select('*');

      const trends: TrendDataPoint[] = [];
      const insights: string[] = [];

      const timeIntervals = this.generateTimeIntervals(startDate, endDate, granularity);

      for (const interval of timeIntervals) {
        for (const variant of variants) {
          const stats = await this.getVariantStatsForPeriod(testId, variant.id, interval.start, interval.end);

          const cumulativeStats = await this.getVariantCumulativeStats(testId, variant.id, interval.end);

          trends.push({
            timestamp: interval.start,
            variantId: variant.id,
            variantName: variant.name,
            visitors: stats.visitors,
            conversions: stats.conversions,
            conversionRate: stats.visitors > 0 ? stats.conversions / stats.visitors : 0,
            cumulativeVisitors: cumulativeStats.visitors,
            cumulativeConversions: cumulativeStats.conversions,
            cumulativeConversionRate: cumulativeStats.visitors > 0 ? cumulativeStats.conversions / cumulativeStats.visitors : 0,
          });
        }
      }

      const trendInsights = this.analyzeTrendPatterns(trends);
      insights.push(...trendInsights);

      logger.info(`[ABTestAnalysisService] Trend analysis completed - testId: ${testId}, dataPoints: ${trends.length}`);

      return {
        success: true,
        testId,
        granularity,
        trends,
        insights,
      };
    } catch (error: any) {
      logger.error(`[ABTestAnalysisService] Trend analysis failed - testId: ${testId}, error: ${error.message}`);
      throw error;
    }
  }

  static async analyzeSegments(input: SegmentAnalysisInput): Promise<SegmentAnalysisResult> {
    const { tenantId, shopId, taskId, traceId, businessType, testId, segmentBy } = input;

    logger.info(`[ABTestAnalysisService] Analyzing segments - testId: ${testId}, segmentBy: ${segmentBy}, tenantId: ${tenantId}, traceId: ${traceId}`);

    try {
      const variants = await db('cf_ab_test_variants')
        .where({ test_id: testId })
        .select('*');

      const segments = await this.getSegmentData(testId, variants, segmentBy);
      const insights = this.generateSegmentInsights(segments);

      logger.info(`[ABTestAnalysisService] Segment analysis completed - testId: ${testId}, segments: ${segments.length}`);

      return {
        success: true,
        testId,
        segmentBy,
        segments,
        insights,
      };
    } catch (error: any) {
      logger.error(`[ABTestAnalysisService] Segment analysis failed - testId: ${testId}, error: ${error.message}`);
      throw error;
    }
  }

  static async getStatisticalSummary(testId: string, tenantId: string): Promise<StatisticalSummary> {
    const test = await db('cf_ab_tests')
      .where({ id: testId, tenant_id: tenantId })
      .first();

    if (!test) {
      throw new Error(`A/B test not found: ${testId}`);
    }

    const variants = await db('cf_ab_test_variants')
      .where({ test_id: testId })
      .select('*');

    let totalVisitors = 0;
    let totalConversions = 0;
    const variantData: { visitors: number; conversions: number }[] = [];

    for (const variant of variants) {
      const stats = await this.getVariantStats(testId, variant.id, 'CONVERSION');
      totalVisitors += stats.visitors;
      totalConversions += stats.conversions;
      variantData.push({ visitors: stats.visitors, conversions: stats.conversions });
    }

    const overallConversionRate = totalVisitors > 0 ? totalConversions / totalVisitors : 0;

    const chiSquare = this.calculateChiSquare(variantData, totalVisitors, totalConversions);
    const degreesOfFreedom = variants.length - 1;
    const pValue = this.calculateChiSquarePValue(chiSquare, degreesOfFreedom);

    return {
      testId,
      totalVisitors,
      totalConversions,
      overallConversionRate,
      chiSquare,
      pValue,
      degreesOfFreedom,
      power: this.calculateStatisticalPower(variantData, overallConversionRate),
    };
  }

  private static async getVariantStats(testId: string, variantId: string, analysisType: string): Promise<{
    visitors: number;
    conversions: number;
    revenue: number;
  }> {
    const visitors = await db('cf_ab_test_assignments')
      .where({ test_id: testId, variant_id: variantId })
      .count('* as count')
      .first();

    let conversions = 0;
    let revenue = 0;

    if (analysisType === 'CONVERSION' || analysisType === 'CTR') {
      const convResult = await db('cf_ab_test_conversions')
        .where({ test_id: testId, variant_id: variantId })
        .count('* as count')
        .first();
      conversions = parseInt(convResult?.count || '0');
    } else if (analysisType === 'REVENUE') {
      const revResult = await db('cf_ab_test_conversions')
        .where({ test_id: testId, variant_id: variantId })
        .sum('revenue as total')
        .first();
      revenue = parseFloat(revResult?.total || '0');
      conversions = await db('cf_ab_test_conversions')
        .where({ test_id: testId, variant_id: variantId })
        .count('* as count')
        .then(r => parseInt(r[0]?.count || '0'));
    }

    return {
      visitors: parseInt(visitors?.count || '0'),
      conversions,
      revenue,
    };
  }

  private static async getVariantStatsForPeriod(
    testId: string,
    variantId: string,
    startDate: Date,
    endDate: Date
  ): Promise<{ visitors: number; conversions: number }> {
    const visitors = await db('cf_ab_test_assignments')
      .where({ test_id: testId, variant_id: variantId })
      .whereBetween('created_at', [startDate, endDate])
      .count('* as count')
      .first();

    const conversions = await db('cf_ab_test_conversions')
      .where({ test_id: testId, variant_id: variantId })
      .whereBetween('created_at', [startDate, endDate])
      .count('* as count')
      .first();

    return {
      visitors: parseInt(visitors?.count || '0'),
      conversions: parseInt(conversions?.count || '0'),
    };
  }

  private static async getVariantCumulativeStats(
    testId: string,
    variantId: string,
    endDate: Date
  ): Promise<{ visitors: number; conversions: number }> {
    const visitors = await db('cf_ab_test_assignments')
      .where({ test_id: testId, variant_id: variantId })
      .where('created_at', '<=', endDate)
      .count('* as count')
      .first();

    const conversions = await db('cf_ab_test_conversions')
      .where({ test_id: testId, variant_id: variantId })
      .where('created_at', '<=', endDate)
      .count('* as count')
      .first();

    return {
      visitors: parseInt(visitors?.count || '0'),
      conversions: parseInt(conversions?.count || '0'),
    };
  }

  private static async getSegmentData(
    testId: string,
    variants: any[],
    segmentBy: string
  ): Promise<SegmentData[]> {
    const segments: SegmentData[] = [];

    const segmentValues = await this.getSegmentValues(testId, segmentBy);

    for (const segmentValue of segmentValues) {
      const variantSegments: VariantSegmentData[] = [];

      for (const variant of variants) {
        const stats = await this.getSegmentVariantStats(testId, variant.id, segmentBy, segmentValue);
        const controlStats = await this.getSegmentVariantStats(testId, variants[0].id, segmentBy, segmentValue);

        const lift = controlStats.conversionRate > 0
          ? ((stats.conversionRate - controlStats.conversionRate) / controlStats.conversionRate) * 100
          : 0;

        variantSegments.push({
          variantId: variant.id,
          variantName: variant.name,
          visitors: stats.visitors,
          conversions: stats.conversions,
          conversionRate: stats.conversionRate,
          lift,
        });
      }

      const bestVariant = variantSegments.reduce((best, current) =>
        current.conversionRate > best.conversionRate ? current : best
      );

      segments.push({
        segmentName: this.getSegmentName(segmentBy),
        segmentValue,
        variants: variantSegments,
        winner: {
          variantId: bestVariant.variantId,
          variantName: bestVariant.variantName,
          lift: bestVariant.lift,
        },
      });
    }

    return segments;
  }

  private static async getSegmentValues(testId: string, segmentBy: string): Promise<string[]> {
    let query = db('cf_ab_test_assignments')
      .where({ test_id: testId })
      .distinct(segmentBy.toLowerCase());

    const results = await query;
    return results.map((r: any) => r[segmentBy.toLowerCase()]).filter(Boolean);
  }

  private static async getSegmentVariantStats(
    testId: string,
    variantId: string,
    segmentBy: string,
    segmentValue: string
  ): Promise<{ visitors: number; conversions: number; conversionRate: number }> {
    const visitors = await db('cf_ab_test_assignments')
      .where({ test_id: testId, variant_id: variantId })
      .where(segmentBy.toLowerCase(), segmentValue)
      .count('* as count')
      .first();

    const conversions = await db('cf_ab_test_conversions')
      .where({ test_id: testId, variant_id: variantId })
      .where(segmentBy.toLowerCase(), segmentValue)
      .count('* as count')
      .first();

    const visitorCount = parseInt(visitors?.count || '0');
    const conversionCount = parseInt(conversions?.count || '0');

    return {
      visitors: visitorCount,
      conversions: conversionCount,
      conversionRate: visitorCount > 0 ? conversionCount / visitorCount : 0,
    };
  }

  private static getZScore(confidenceLevel: number): number {
    const zScores: Record<number, number> = {
      0.9: 1.645,
      0.95: 1.96,
      0.99: 2.576,
    };
    return zScores[confidenceLevel] || 1.96;
  }

  private static calculatePValue(zScore: number): number {
    return 2 * (1 - this.normalCDF(Math.abs(zScore)));
  }

  private static normalCDF(x: number): number {
    const t = 1 / (1 + 0.2316419 * Math.abs(x));
    const d = 0.3989423 * Math.exp((-x * x) / 2);
    const prob = d * t * (0.3193815 + t * (-0.3565638 + t * (1.781478 + t * (-1.821256 + t * 1.330274))));
    return x > 0 ? 1 - prob : prob;
  }

  private static calculateChiSquare(
    variantData: { visitors: number; conversions: number }[],
    totalVisitors: number,
    totalConversions: number
  ): number {
    const expectedRate = totalVisitors > 0 ? totalConversions / totalVisitors : 0;
    let chiSquare = 0;

    for (const variant of variantData) {
      const expectedConversions = variant.visitors * expectedRate;
      const expectedNonConversions = variant.visitors * (1 - expectedRate);

      if (expectedConversions > 0) {
        chiSquare += Math.pow(variant.conversions - expectedConversions, 2) / expectedConversions;
      }
      if (expectedNonConversions > 0) {
        chiSquare += Math.pow((variant.visitors - variant.conversions) - expectedNonConversions, 2) / expectedNonConversions;
      }
    }

    return chiSquare;
  }

  private static calculateChiSquarePValue(chiSquare: number, degreesOfFreedom: number): number {
    return Math.exp(-chiSquare / 2) / Math.sqrt(2 * Math.PI * degreesOfFreedom);
  }

  private static calculateStatisticalPower(
    variantData: { visitors: number; conversions: number }[],
    baselineRate: number
  ): number {
    if (variantData.length < 2) return 0;

    const effectSize = Math.abs(variantData[1].conversions / variantData[1].visitors - baselineRate);
    const pooledSE = Math.sqrt((2 * baselineRate * (1 - baselineRate)) / variantData[0].visitors);

    return effectSize / pooledSE;
  }

  private static generateTimeIntervals(
    startDate: Date,
    endDate: Date,
    granularity: 'HOURLY' | 'DAILY' | 'WEEKLY'
  ): { start: Date; end: Date }[] {
    const intervals: { start: Date; end: Date }[] = [];
    let current = new Date(startDate);

    while (current < endDate) {
      const intervalStart = new Date(current);
      let intervalEnd: Date;

      switch (granularity) {
        case 'HOURLY':
          intervalEnd = new Date(current.getTime() + 60 * 60 * 1000);
          break;
        case 'DAILY':
          intervalEnd = new Date(current.getTime() + 24 * 60 * 60 * 1000);
          break;
        case 'WEEKLY':
          intervalEnd = new Date(current.getTime() + 7 * 24 * 60 * 60 * 1000);
          break;
      }

      intervals.push({ start: intervalStart, end: intervalEnd });
      current = intervalEnd;
    }

    return intervals;
  }

  private static analyzeTrendPatterns(trends: TrendDataPoint[]): string[] {
    const insights: string[] = [];

    const variantGroups: Record<string, TrendDataPoint[]> = {};
    for (const trend of trends) {
      if (!variantGroups[trend.variantId]) {
        variantGroups[trend.variantId] = [];
      }
      variantGroups[trend.variantId].push(trend);
    }

    for (const [variantId, variantTrends] of Object.entries(variantGroups)) {
      if (variantTrends.length < 2) continue;

      const firstHalf = variantTrends.slice(0, Math.floor(variantTrends.length / 2));
      const secondHalf = variantTrends.slice(Math.floor(variantTrends.length / 2));

      const firstHalfRate = firstHalf.reduce((sum, t) => sum + t.conversionRate, 0) / firstHalf.length;
      const secondHalfRate = secondHalf.reduce((sum, t) => sum + t.conversionRate, 0) / secondHalf.length;

      if (secondHalfRate > firstHalfRate * 1.1) {
        insights.push(`Variant ${variantTrends[0].variantName} shows improving trend (+${(((secondHalfRate - firstHalfRate) / firstHalfRate) * 100).toFixed(1)}%)`);
      } else if (secondHalfRate < firstHalfRate * 0.9) {
        insights.push(`Variant ${variantTrends[0].variantName} shows declining trend (${(((secondHalfRate - firstHalfRate) / firstHalfRate) * 100).toFixed(1)}%)`);
      }
    }

    return insights;
  }

  private static generateSegmentInsights(segments: SegmentData[]): string[] {
    const insights: string[] = [];

    for (const segment of segments) {
      const bestVariant = segment.variants.reduce((best, current) =>
        current.conversionRate > best.conversionRate ? current : best
      );

      if (bestVariant.lift > 10) {
        insights.push(`${segment.segmentValue}: ${bestVariant.variantName} performs significantly better (+${bestVariant.lift.toFixed(1)}%)`);
      }
    }

    return insights;
  }

  private static getSegmentName(segmentBy: string): string {
    const names: Record<string, string> = {
      DEVICE: 'Device Type',
      GEO: 'Geography',
      REFERRER: 'Referrer',
      USER_TYPE: 'User Type',
      TIME: 'Time of Day',
    };
    return names[segmentBy] || segmentBy;
  }

  private static generateRecommendation(
    variants: VariantAnalysis[],
    winner: { variantId: string; variantName: string; improvement: number; confidence: number } | undefined,
    isSignificant: boolean,
    minSampleSize: number
  ): string {
    if (winner && isSignificant) {
      return `Winner identified: ${winner.variantName} with ${winner.improvement.toFixed(2)}% improvement at ${winner.confidence}% confidence. Recommend implementing this variant.`;
    }

    const underpoweredVariants = variants.filter(v => v.visitors < minSampleSize);
    if (underpoweredVariants.length > 0) {
      return `Insufficient sample size for ${underpoweredVariants.length} variant(s). Continue running the test to reach minimum sample size of ${minSampleSize} per variant.`;
    }

    if (!isSignificant) {
      return 'No statistically significant winner found. Consider running the test longer or testing more dramatic changes.';
    }

    return 'Test is inconclusive. Consider reviewing your hypothesis and testing different variations.';
  }

  static async initializeTables(): Promise<void> {
    if (!(await db.schema.hasTable('cf_ab_test_analyses'))) {
      await db.schema.createTable('cf_ab_test_analyses', (table) => {
        table.string('id').primary();
        table.string('test_id').notNullable();
        table.string('tenant_id').notNullable();
        table.string('shop_id').notNullable();
        table.string('task_id').notNullable();
        table.string('trace_id').notNullable();
        table.enum('business_type', ['TOC', 'TOB']).notNullable();
        table.enum('analysis_type', ['CONVERSION', 'REVENUE', 'CTR', 'BOUNCE_RATE', 'CUSTOM']).notNullable();
        table.decimal('confidence_level', 3, 2).defaultTo(0.95);
        table.string('winner_variant_id');
        table.decimal('improvement', 10, 4);
        table.boolean('is_significant').defaultTo(false);
        table.text('recommendation');
        table.timestamp('analyzed_at').defaultTo(db.fn.now());

        table.foreign('test_id').references('cf_ab_tests.id');
        table.index(['test_id']);
        table.index(['tenant_id', 'shop_id']);
        table.index(['analyzed_at']);
      });
      logger.info('[ABTestAnalysisService] Created cf_ab_test_analyses table');
    }
  }
}