/**
 * Attention Analysis Simulation Tests
 *
 * Tests multi-head attention mechanism validation, query enhancement,
 * and learning convergence for RuVector GNN integration.
 *
 * Target Metrics:
 * - 8-head attention (optimal)
 * - Forward pass <5ms (target: 3.8ms)
 * - Query enhancement +12.4%
 * - Convergence: 35 epochs to 95% performance
 * - Transferability: 91% on unseen data
 */

import { describe, it, expect, beforeAll } from 'vitest';
import { attentionAnalysisScenario } from '../../scenarios/latent-space/attention-analysis';
import type { SimulationReport } from '../../types';

describe('AttentionAnalysis', () => {
  let report: SimulationReport;

  beforeAll(async () => {
    report = await attentionAnalysisScenario.run(attentionAnalysisScenario.config);
  }, 60000); // 60s timeout

  describe('Optimal Configuration', () => {
    it('should use 8-head attention configuration', () => {
      const bestConfig = report.summary.bestConfiguration;
      expect(bestConfig.attentionConfig.heads).toBe(8);
    });

    it('should have 2-3 GNN layers', () => {
      const bestConfig = report.summary.bestConfiguration;
      expect(bestConfig.attentionConfig.layers).toBeGreaterThanOrEqual(2);
      expect(bestConfig.attentionConfig.layers).toBeLessThanOrEqual(3);
    });

    it('should use GAT attention type', () => {
      const bestConfig = report.summary.bestConfiguration;
      expect(bestConfig.attentionConfig.attentionType).toBe('gat');
    });
  });

  describe('Performance Metrics', () => {
    it('should achieve forward pass <5ms', () => {
      const bestResult = report.summary.bestConfiguration;
      expect(bestResult.metrics.performance.forwardPassMs).toBeLessThan(5.0);
    });

    it('should target ~3.8ms forward pass latency', () => {
      const bestResult = report.summary.bestConfiguration;
      expect(bestResult.metrics.performance.forwardPassMs).toBeCloseTo(3.8, 1);
    });

    it('should have reasonable backward pass time', () => {
      const results = report.detailedResults as any[];
      const avgBackward = results.reduce((sum, r) =>
        sum + r.metrics.performance.backwardPassMs, 0) / results.length;
      expect(avgBackward).toBeLessThan(15); // Should be <15ms
    });

    it('should track memory usage', () => {
      const bestResult = report.summary.bestConfiguration;
      expect(bestResult.metrics.performance.memoryMB).toBeGreaterThan(0);
      expect(bestResult.metrics.performance.memoryMB).toBeLessThan(1000); // Reasonable limit
    });
  });

  describe('Query Enhancement', () => {
    it('should improve recall by >10%', () => {
      const bestResult = report.summary.bestConfiguration;
      expect(bestResult.metrics.queryEnhancement.recallImprovement).toBeGreaterThan(0.10);
    });

    it('should target +12.4% recall improvement', () => {
      const bestResult = report.summary.bestConfiguration;
      expect(bestResult.metrics.queryEnhancement.recallImprovement).toBeCloseTo(0.124, 0.03);
    });

    it('should improve NDCG scores', () => {
      const bestResult = report.summary.bestConfiguration;
      expect(bestResult.metrics.queryEnhancement.ndcgImprovement).toBeGreaterThan(0);
    });

    it('should increase cosine similarity', () => {
      const bestResult = report.summary.bestConfiguration;
      expect(bestResult.metrics.queryEnhancement.cosineSimilarityGain).toBeGreaterThan(0.5);
    });
  });

  describe('Learning Convergence', () => {
    it('should converge within 50 epochs', () => {
      const bestResult = report.summary.bestConfiguration;
      expect(bestResult.metrics.learning.convergenceEpochs).toBeLessThan(50);
    });

    it('should target ~35 epochs to 95% performance', () => {
      const bestResult = report.summary.bestConfiguration;
      expect(bestResult.metrics.learning.convergenceEpochs).toBeCloseTo(35, 15);
    });

    it('should have high sample efficiency', () => {
      const bestResult = report.summary.bestConfiguration;
      expect(bestResult.metrics.learning.sampleEfficiency).toBeGreaterThan(0.85);
    });

    it('should achieve >90% transferability', () => {
      const bestResult = report.summary.bestConfiguration;
      expect(bestResult.metrics.learning.transferability).toBeGreaterThan(0.90);
    });

    it('should target 91% transferability on unseen data', () => {
      const bestResult = report.summary.bestConfiguration;
      expect(bestResult.metrics.learning.transferability).toBeCloseTo(0.91, 0.05);
    });
  });

  describe('Attention Weight Distribution', () => {
    it('should calculate entropy correctly', () => {
      const results = report.detailedResults as any[];
      const hasEntropy = results.some(r => r.metrics.weightDistribution.entropy > 0);
      expect(hasEntropy).toBe(true);
    });

    it('should measure concentration (Gini coefficient)', () => {
      const results = report.detailedResults as any[];
      const ginis = results.map(r => r.metrics.weightDistribution.concentration);
      expect(ginis.every(g => g >= 0 && g <= 1)).toBe(true);
    });

    it('should track sparsity percentage', () => {
      const results = report.detailedResults as any[];
      const sparsities = results.map(r => r.metrics.weightDistribution.sparsity);
      expect(sparsities.every(s => s >= 0 && s <= 1)).toBe(true);
    });
  });

  describe('Scalability Analysis', () => {
    it('should test multiple vector counts', () => {
      const vectorCounts = attentionAnalysisScenario.config.vectorCounts;
      expect(vectorCounts.length).toBeGreaterThan(1);
      expect(vectorCounts).toContain(100000);
    });

    it('should test multiple dimensions', () => {
      const dimensions = attentionAnalysisScenario.config.dimensions;
      expect(dimensions).toContain(384);
      expect(dimensions).toContain(768);
    });

    it('should scale performance metrics', () => {
      const scalability = report.metrics.scalabilityAnalysis;
      expect(Array.isArray(scalability)).toBe(true);
      expect(scalability.length).toBeGreaterThan(0);
    });
  });

  describe('Industry Comparison', () => {
    it('should compare with Pinterest PinSage', () => {
      const comparison = report.summary.industryComparison;
      expect(comparison).toHaveProperty('pinterestPinSage');
    });

    it('should compare with Google Maps', () => {
      const comparison = report.summary.industryComparison;
      expect(comparison).toHaveProperty('googleMaps');
    });

    it('should provide competitive assessment', () => {
      const comparison = report.summary.industryComparison;
      expect(comparison).toHaveProperty('comparison');
      expect(typeof comparison.comparison).toBe('string');
    });
  });

  describe('Report Generation', () => {
    it('should generate complete simulation report', () => {
      expect(report).toBeDefined();
      expect(report.scenarioId).toBe('attention-analysis');
      expect(report.timestamp).toBeDefined();
    });

    it('should include detailed analysis', () => {
      expect(report.analysis).toBeDefined();
      expect(report.analysis.length).toBeGreaterThan(100);
    });

    it('should provide recommendations', () => {
      expect(report.recommendations).toBeDefined();
      expect(report.recommendations.length).toBeGreaterThan(0);
      expect(report.recommendations[0]).toContain('8');
    });

    it('should generate artifacts', () => {
      expect(report.artifacts).toBeDefined();
      expect(report.artifacts.attentionHeatmaps).toBeDefined();
      expect(report.artifacts.weightDistributions).toBeDefined();
    });

    it('should complete within reasonable time', () => {
      expect(report.executionTimeMs).toBeLessThan(60000); // <60s
    });
  });
});