lerobot/robot-learning-tutorial

1// Test utilities for Large Dataset Support2// Run in browser console to validate sampling behavior3 4/**5 * Test suite for large dataset sampling6 */7export const LargeDatasetTests = {8  9  /**10   * Test basic sampling functionality11   */12  testBasicSampling() {13    console.log('🧪 Testing basic sampling functionality...');14    15    // Generate a dataset that should trigger sampling16    if (window.trackioInstance) {17      const result = window.trackioInstance.generateMassiveDataset(1000, 2);18      console.log('✅ Basic sampling test completed:', result);19      return result;20    } else {21      console.error('❌ trackioInstance not found');22      return null;23    }24  },25 26  /**27   * Test massive dataset performance28   */29  testMassiveDataset() {30    console.log('🧪 Testing massive dataset (10K points)...');31    32    if (window.trackioInstance) {33      const startTime = performance.now();34      const result = window.trackioInstance.generateMassiveDataset(10000, 3);35      const endTime = performance.now();36      37      console.log(`✅ Massive dataset test completed in ${(endTime - startTime).toFixed(2)}ms`);38      console.log('📊 Result:', result);39      return { result, duration: endTime - startTime };40    } else {41      console.error('❌ trackioInstance not found');42      return null;43    }44  },45 46  /**47   * Test sampling strategies48   */49  async testSamplingStrategies() {50    console.log('🧪 Testing different sampling strategies...');51    52    const { AdaptiveSampler } = await import('./adaptive-sampler.js');53    54    // Generate test data55    const testData = Array.from({ length: 1000 }, (_, i) => ({56      step: i + 1,57      value: Math.sin(i * 0.01) + Math.random() * 0.158    }));59 60    const strategies = ['uniform', 'smart', 'lod'];61    const results = {};62 63    strategies.forEach(strategy => {64      const sampler = new AdaptiveSampler({ 65        maxPoints: 400, 66        targetPoints: 100,67        adaptiveStrategy: strategy 68      });69      70      const startTime = performance.now();71      const result = sampler.sampleSeries(testData, strategy);72      const endTime = performance.now();73      74      results[strategy] = {75        originalLength: testData.length,76        sampledLength: result.data.length,77        compressionRatio: result.compressionRatio,78        duration: endTime - startTime,79        strategy: result.strategy80      };81      82      console.log(`📊 ${strategy}: ${result.data.length} points (${(result.compressionRatio * 100).toFixed(1)}% retained) in ${(endTime - startTime).toFixed(2)}ms`);83    });84 85    console.log('✅ Strategy comparison test completed');86    return results;87  },88 89  /**90   * Performance benchmark across different dataset sizes91   */92  async benchmarkPerformance() {93    console.log('🧪 Running performance benchmark...');94    95    const { AdaptiveSampler } = await import('./adaptive-sampler.js');96    const sampler = new AdaptiveSampler();97    98    const sizes = [500, 1000, 2000, 5000, 10000];99    const results = [];100 101    for (const size of sizes) {102      console.log(`🔄 Testing ${size} points...`);103      104      // Generate test data105      const testData = Array.from({ length: size }, (_, i) => ({106        step: i + 1,107        value: Math.sin(i * 0.001) + Math.cos(i * 0.003) + Math.random() * 0.05108      }));109 110      // Measure sampling performance111      const startTime = performance.now();112      const result = sampler.sampleSeries(testData);113      const endTime = performance.now();114 115      const testResult = {116        originalSize: size,117        sampledSize: result.data.length,118        compressionRatio: result.compressionRatio,119        duration: endTime - startTime,120        pointsPerMs: result.data.length / (endTime - startTime)121      };122 123      results.push(testResult);124      console.log(`📊 ${size} → ${result.data.length} points (${(result.compressionRatio * 100).toFixed(1)}%) in ${(endTime - startTime).toFixed(2)}ms`);125    }126 127    console.log('✅ Performance benchmark completed');128    console.table(results);129    return results;130  },131 132  /**133   * Test feature preservation134   */135  async testFeaturePreservation() {136    console.log('🧪 Testing feature preservation...');137    138    const { AdaptiveSampler } = await import('./adaptive-sampler.js');139    const sampler = new AdaptiveSampler({ preserveFeatures: true });140    141    // Generate data with clear features (peaks, valleys, inflection points)142    const testData = [];143    for (let i = 0; i < 1000; i++) {144      let value = 0;145      146      // Add some peaks and valleys147      value += Math.sin(i * 0.02) * 2;           // Main oscillation148      value += Math.sin(i * 0.1) * 0.5;          // Faster oscillation149      value += Math.cos(i * 0.005) * 1.5;        // Slow trend150      151      // Add sharp peaks at specific points152      if (i === 200 || i === 600 || i === 800) {153        value += 3;154      }155      156      // Add noise157      value += (Math.random() - 0.5) * 0.1;158      159      testData.push({ step: i + 1, value });160    }161 162    const result = sampler.sampleSeries(testData);163    const features = result.features;164 165    console.log('🎯 Feature detection results:');166    console.log(`   Peaks found: ${features?.peaks?.length || 0}`);167    console.log(`   Valleys found: ${features?.valleys?.length || 0}`);168    console.log(`   Inflection points: ${features?.inflectionPoints?.length || 0}`);169    console.log(`   Compression: ${testData.length} → ${result.data.length} (${(result.compressionRatio * 100).toFixed(1)}%)`);170 171    // Check if our artificial peaks are preserved172    const preservedPeaks = [200, 600, 800].filter(peakStep => 173      result.sampledIndices.some(idx => Math.abs(idx - peakStep) <= 2)174    );175    176    console.log(`🎯 Artificial peaks preserved: ${preservedPeaks.length}/3`);177    console.log('✅ Feature preservation test completed');178    179    return { result, features, preservedPeaks };180  },181 182  /**183   * Run all tests184   */185  async runAllTests() {186    console.log('🚀 Running complete large dataset test suite...');187    188    const results = {189      basicSampling: this.testBasicSampling(),190      massiveDataset: this.testMassiveDataset(),191      samplingStrategies: await this.testSamplingStrategies(),192      performanceBenchmark: await this.benchmarkPerformance(),193      featurePreservation: await this.testFeaturePreservation()194    };195 196    console.log('🎉 All tests completed!');197    console.log('📋 Full test results:', results);198    199    return results;200  }201};202 203/**204 * Quick test function for browser console205 */206export function testLargeDatasets() {207  return LargeDatasetTests.runAllTests();208}209 210/**211 * Expose to global scope for easy testing212 */213if (typeof window !== 'undefined') {214  window.LargeDatasetTests = LargeDatasetTests;215  window.testLargeDatasets = testLargeDatasets;216}217 218// Example usage in browser console:219// testLargeDatasets()220// LargeDatasetTests.testMassiveDataset()221// LargeDatasetTests.benchmarkPerformance()222