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Vector Trading Guide

Dragon Wallets SDK Version 0.8.5

Learn how to implement high-performance, phi-resonant vector trading using the Dragon Wallets SDK, enabling up to 9 billion operations per second with sub-millisecond latency.

Introduction to Vector Trading

Vector trading represents a revolutionary approach to financial transactions by leveraging geometric pathways and mathematical constants to optimize transaction routing, throughput, and security.

What is Vector Trading?

In the DragonFire ecosystem, vector trading routes financial operations through multi-dimensional pathways optimized using mathematical constants (particularly the golden ratio φ), resulting in:

  • Ultra-low latency: <1ms transaction completion
  • Extreme throughput: Up to 9 billion operations per second
  • Enhanced security: Transactions follow phi-resonant pathways difficult to predict or intercept
  • Mathematical efficiency: Operations flow along natural patterns found in nature
  • Geometric coherence: Seamless integration with the Dragon Ports system
Vector Trading Concept Visualization
Visualization of vector trading pathways through geometric dimensions

Vector Trading vs. Traditional Transactions

Characteristic Traditional Transactions Vector Trading
Latency 10ms - 1000ms <1ms
Throughput Thousands per second Billions per second
Routing Linear, sequential processing Geometric, parallel processing
Optimization Manual optimization Phi-resonant auto-optimization
Security Static security measures Rotational, phi-based security
Dimensional Space 2D (source → destination) Multi-dimensional (3D-7D)

Key Concepts

Understanding the fundamental concepts behind vector trading is essential for effective implementation.

Vector Paths

Multi-dimensional routes through which transactions flow, optimized using mathematical constants to minimize resistance and maximize throughput.

Phi-Resonance

The use of the golden ratio (φ ≈ 1.618...) to create naturally optimized transaction pathways that follow patterns found throughout nature and mathematics.

Dimensional Mapping

Techniques for mapping transaction operations to specific geometric dimensions to align with their natural mathematical properties.

Port Integration

Integration with the Dragon Ports system for routing transactions through appropriate geometric gateways based on operation type.

Harmonic Patterns

Transaction patterns that leverage mathematical harmonics (φ, π, √2, √3, e) for specific types of operations and use cases.

Vector Space

The multi-dimensional computational environment where transactions are processed, typically using 7-dimensional vectors for optimal performance.

The Mathematics of Vector Trading

Vector trading is fundamentally rooted in mathematical principles that govern natural harmonics and geometric efficiency:

Phi-Resonant Path Efficiency
E = 1 - (1/φd)
Where:
  • E = path efficiency (0-1)
  • φ = golden ratio (1.618...)
  • d = dimensional complexity
Vector Operation Throughput
T = B × φn × (1-L)
Where:
  • T = operations per second
  • B = baseline throughput
  • n = optimization factor
  • L = latency factor (0-1)

Configuring Vector Trading

Before executing vector trades, you need to configure the vector trading environment for optimal performance.

Basic Configuration

import { DragonFireClient } from '@dragonfire/client';
import { WalletClient } from '@dragonfire/wallet-client';

// Initialize clients
const dragonfire = new DragonFireClient({
  apiKey: 'YOUR_API_KEY',
  region: 'us-west'
});
await dragonfire.connect();

const wallet = new WalletClient(dragonfire);

// Configure vector trading
await wallet.configureVectorTrading({
  // Core vector settings
  defaultPattern: 'phi',           // Default mathematical pattern (phi, pi, sqrt2, sqrt3, e)
  dimensionality: 7,               // 7-dimensional vector space
  optimizationLevel: 'maximum',    // Maximum optimization level
  
  // Performance settings
  adaptiveRouting: true,           // Dynamically adapt routes based on network conditions
  resonanceThreshold: 0.85,        // Minimum resonance threshold for path selection
  cacheIntegration: true,          // Integrate with DragonFire Cache for faster operations
  precomputeCommonPaths: true,     // Precompute commonly used transaction paths
  
  // Security settings
  securityLevel: 'high',           // High-security operation mode
  rwtIntegration: true,            // Integrate with RWT for secure authentication
  nonLinearRouting: true,          // Use non-linear routing for enhanced security
  
  // Advanced settings
  portMappingStrategy: 'geometric', // Map operations to appropriate geometric ports
  harmonicResonance: true,         // Enable harmonic resonance for optimal paths
  dimensionalCrossing: 'optimized'  // Optimize paths across dimensional boundaries
});

Configuration Parameters

Parameter Type Description Default
defaultPattern string Default mathematical pattern for optimization ('phi', 'pi', 'sqrt2', 'sqrt3', 'e') 'phi'
dimensionality number Dimensional complexity of vector space (3-11) 7
optimizationLevel string Level of path optimization ('minimal', 'standard', 'high', 'maximum') 'standard'
adaptiveRouting boolean Dynamically adapt routes based on network conditions true
resonanceThreshold number Minimum resonance threshold for path selection (0-1) 0.75
cacheIntegration boolean Integrate with DragonFire Cache for faster operations true
securityLevel string Security level for transactions ('standard', 'high', 'maximum') 'standard'
portMappingStrategy string Strategy for mapping operations to geometric ports ('direct', 'semantic', 'geometric') 'semantic'

Performance Tip

For maximum performance (approaching 9 billion operations per second), it's recommended to use these settings:

  • dimensionality: 7
  • defaultPattern: 'phi'
  • optimizationLevel: 'maximum'
  • cacheIntegration: true
  • precomputeCommonPaths: true
  • harmonicResonance: true

Note that maximum performance settings may require more computational resources during initialization but provide optimal throughput during operation.

Basic Vector Trading

Let's start with a simple vector trade to understand the core functionality.

Simple Vector Transaction

// Execute a simple vector transaction
const result = await wallet.createTransaction({
  recipient: 'wallet_789',     // Recipient wallet ID or address
  amount: 50.75,               // Transaction amount
  currency: 'USD',             // Currency code
  memo: 'Payment for services' // Transaction memo
}, {
  // Vector trading options
  vectorRouting: 'phi',        // Vector routing pattern
  priority: 'high',            // Transaction priority
  securityLevel: 'high',       // Security level for transaction
  maxFee: 1.5,                 // Maximum fee allowed
  timeout: 30000               // Transaction timeout (ms)
});

console.log('Transaction created:');
console.log('Transaction ID:', result.transactionId);
console.log('Status:', result.status);
console.log('Execution time:', result.executionTimeMs, 'ms');
console.log('Fee:', result.fee);
console.log('Vector path:', result.vectorPath);

Vector Trading with Batches

For high-throughput applications, batch processing is significantly more efficient:

// Create a batch of transactions for vector processing
const batchResult = await wallet.createTransactionBatch({
  // Array of transactions to process
  transactions: [
    { recipient: 'wallet_001', amount: 10.50, currency: 'USD' },
    { recipient: 'wallet_002', amount: 25.75, currency: 'USD' },
    { recipient: 'wallet_003', amount: 5.20, currency: 'USD' },
    { recipient: 'wallet_004', amount: 100.00, currency: 'USD' },
    { recipient: 'wallet_005', amount: 75.30, currency: 'USD' }
  ],
  // Batch processing options
  options: {
    vectorPattern: 'phi',          // Vector routing pattern
    parallelExecution: true,       // Execute in parallel
    atomicBatch: false,            // Non-atomic (partial success allowed)
    priority: 'high',              // High priority processing
    timeoutMs: 60000               // 60-second timeout
  }
});

console.log('Batch processing results:');
console.log('Processed transactions:', batchResult.processedCount);
console.log('Successful transactions:', batchResult.successCount);
console.log('Failed transactions:', batchResult.failedCount);
console.log('Total processing time:', batchResult.totalTimeMs, 'ms');
console.log('Operations per second:', batchResult.opsPerSecond);

// Check individual transaction results
batchResult.results.forEach((result, index) => {
  console.log(`Transaction ${index + 1}:`);
  console.log('  ID:', result.transactionId);
  console.log('  Status:', result.status);
  console.log('  Execution time:', result.executionTimeMs, 'ms');
});

Analyzing Vector Paths

After executing a vector transaction, you can analyze its path for insights:

// Analyze a transaction's vector path
const analysis = await wallet.analyzeVectorPath('tx_123456789', {
  detailLevel: 'high',           // Analysis detail level
  includeAlternatives: true,     // Include alternative paths
  optimizationSuggestions: true  // Include optimization suggestions
});

console.log('Vector path analysis:');
console.log('Path length:', analysis.pathLength);
console.log('Efficiency rating:', analysis.efficiencyRating.toFixed(2), '/10');
console.log('Mathematical pattern:', analysis.pattern);
console.log('Completion time:', analysis.completionTimeMs, 'ms');
console.log('Processing nodes:', analysis.processingNodes);

// Check optimization suggestions
if (analysis.optimizationSuggestions) {
  console.log('Suggested optimizations:');
  analysis.optimizationSuggestions.forEach(suggestion => {
    console.log(`- ${suggestion.description}`);
    console.log(`  Efficiency improvement: ${suggestion.improvementPercent}%`);
  });
}

Advanced Vector Patterns

Different vector patterns optimize for specific types of transactions and use cases.

Available Patterns

Phi (φ) Pattern

1.618...

Use case: General-purpose transactions, balanced performance

Benefits: Highest overall efficiency, natural optimization

Mathematical basis: Golden ratio (aligns with natural patterns)

vectorPattern: 'phi'

Pi (π) Pattern

3.14159...

Use case: Recurring payments, cyclical operations

Benefits: Optimized for repeated operations, circular paths

Mathematical basis: Circle constant (aligns with cycles)

vectorPattern: 'pi'

Square Root of 2 (√2) Pattern

1.414...

Use case: High-throughput batch operations

Benefits: Maximum operations per second, binary optimization

Mathematical basis: Diagonal of unit square (binary scaling)

vectorPattern: 'sqrt2'

Square Root of 3 (√3) Pattern

1.732...

Use case: Multi-signature transactions, triangulated verification

Benefits: Optimal for multi-party operations, triangular stability

Mathematical basis: Triangle height constant (triangulation)

vectorPattern: 'sqrt3'

Euler's Number (e) Pattern

2.718...

Use case: Growth-based operations, compound calculations

Benefits: Optimal for interest-bearing transactions, growth modeling

Mathematical basis: Natural exponential growth constant

vectorPattern: 'e'

Pattern Selection Strategy

Choose the appropriate pattern based on the transaction type and requirements:

// Strategy for selecting optimal vector patterns
function selectOptimalPattern(transactionType, options = {}) {
  // Default to phi pattern for general transactions
  let pattern = 'phi';
  
  switch (transactionType) {
    case 'standard':
      // General transactions - use phi pattern
      pattern = 'phi';
      break;
      
    case 'recurring':
      // Recurring payments - use pi pattern
      pattern = 'pi';
      break;
      
    case 'batch':
      // High-volume batch processing - use sqrt2 pattern
      pattern = 'sqrt2';
      break;
      
    case 'multi-signature':
      // Multi-signature transactions - use sqrt3 pattern
      pattern = 'sqrt3';
      break;
      
    case 'interest-bearing':
      // Interest or growth-based transactions - use e pattern
      pattern = 'e';
      break;
  }
  
  // Override based on specific transaction properties
  if (options.highPriority && options.batchSize > 1000) {
    // High priority batch processing
    pattern = 'sqrt2';
  }
  
  if (options.signatoryCount > 2) {
    // Multi-party transactions with 3+ signatories
    pattern = 'sqrt3';
  }
  
  if (options.recurringSchedule) {
    // Transactions on a recurring schedule
    pattern = 'pi';
  }
  
  return pattern;
}

// Example usage
const transactionType = 'batch';
const options = {
  highPriority: true,
  batchSize: 5000,
  signatoryCount: 1
};

const optimalPattern = selectOptimalPattern(transactionType, options);
console.log('Optimal pattern for this transaction:', optimalPattern);

// Execute transaction with selected pattern
const result = await wallet.createTransaction({
  recipient: 'wallet_123',
  amount: 100,
  currency: 'USD'
}, {
  vectorPattern: optimalPattern
});

Advanced Pattern Insights

You can combine multiple patterns for complex transactions:

// Execute a transaction with a hybrid pattern
const result = await wallet.createTransaction({
  recipient: 'wallet_789',
  amount: 50.75,
  currency: 'USD'
}, {
  // Use a hybrid pattern with weighted components
  vectorPattern: {
    primary: 'phi',     // Primary pattern (70% weight)
    secondary: 'sqrt2', // Secondary pattern (30% weight)
    weights: [0.7, 0.3] // Pattern weights
  }
});

Optimization Techniques

Maximize performance and efficiency with these advanced optimization techniques.

Path Precomputation

// Precompute common transaction paths for faster execution
await wallet.precomputeVectorPaths({
  // Common transaction scenarios to precompute
  scenarios: [
    {
      name: 'standard-payment',
      sourceType: 'personal-wallet',
      destinationType: 'external-wallet',
      volumeLevel: 'medium',
      frequency: 'occasional'
    },
    {
      name: 'recurring-subscription',
      sourceType: 'personal-wallet',
      destinationType: 'merchant-wallet',
      volumeLevel: 'low',
      frequency: 'monthly'
    },
    {
      name: 'high-volume-trading',
      sourceType: 'trading-wallet',
      destinationType: 'exchange-wallet',
      volumeLevel: 'high',
      frequency: 'continuous'
    }
  ],
  // Precomputation options
  options: {
    optimizationLevel: 'maximum',   // Maximum optimization
    cacheResults: true,             // Cache precomputed paths
    refreshInterval: 3600000,       // Refresh every hour (ms)
    computeAlternatives: true       // Compute alternative paths
  }
});

// Check precomputation status
const precomputationStatus = await wallet.getPrecomputationStatus();
console.log('Precomputed scenarios:', precomputationStatus.scenarioCount);
console.log('Path cache hit rate:', precomputationStatus.cacheHitRate);
console.log('Average path efficiency:', precomputationStatus.averageEfficiency);

// Use precomputed paths
const result = await wallet.createTransaction({
  recipient: 'wallet_123',
  amount: 100,
  currency: 'USD'
}, {
  usePrecomputedPath: true,         // Use precomputed path if available
  scenario: 'standard-payment'      // Specify the scenario
});

Dimensional Optimization

// Optimize transaction processing across dimensions
await wallet.optimizeDimensions({
  // Active dimensions (3-11)
  activeDimensions: [3, 5, 7, 11],
  
  // Dimension-specific settings
  dimensionSettings: {
    3: { // 3D dimension
      primaryUse: 'structural-operations',
      optimizationPattern: 'tetrahedron',
      resonanceThreshold: 0.7
    },
    5: { // 5D dimension
      primaryUse: 'complex-routing',
      optimizationPattern: 'pentatope',
      resonanceThreshold: 0.8
    },
    7: { // 7D dimension
      primaryUse: 'high-throughput',
      optimizationPattern: '7-simplex',
      resonanceThreshold: 0.9
    },
    11: { // 11D dimension
      primaryUse: 'security-operations',
      optimizationPattern: 'prime-resonance',
      resonanceThreshold: 0.95
    }
  },
  
  // Cross-dimensional settings
  crossDimensional: {
    enabled: true,
    optimizationMethod: 'harmonic-mapping',
    crossingThreshold: 0.8
  }
});

// Execute a transaction with dimensional targeting
const result = await wallet.createTransaction({
  recipient: 'wallet_789',
  amount: 50.75,
  currency: 'USD'
}, {
  targetDimension: 7,               // Target the 7D dimension
  dimensionalCrossing: 'adaptive'   // Allow adaptive dimensional crossing
});

Cache Integration

Integrate with DragonFire Cache for significant performance improvements:

// Import necessary modules
import { DragonFireClient } from '@dragonfire/client';
import { WalletClient } from '@dragonfire/wallet-client';
import { CacheClient } from '@dragonfire/cache-client';

// Initialize clients
const dragonfire = new DragonFireClient({ apiKey: 'YOUR_API_KEY' });
await dragonfire.connect();

const wallet = new WalletClient(dragonfire);
const cache = new CacheClient(dragonfire);

// Configure cache integration for vector trading
await wallet.configureCacheIntegration({
  // Connect to DragonFire Cache
  cacheClient: cache,
  
  // Cache settings
  settings: {
    pathCacheTTL: 3600000,          // Path cache TTL (1 hour)
    transactionCacheTTL: 300000,    // Transaction cache TTL (5 minutes)
    precomputeCacheSize: 10000,     // Size of precompute cache
    resultCacheEnabled: true,       // Enable result caching
    statsCacheEnabled: true,        // Enable statistics caching
    
    // Cache optimization
    cacheOptimization: 'phi',       // Phi-resonant cache optimization
    cacheDimensionality: 3,         // Cache dimensionality
    compressCache: true,            // Enable cache compression
    priorityLevels: 3               // Cache priority levels
  }
});

// Execute a transaction with cache integration
const result = await wallet.createTransaction({
  recipient: 'wallet_789',
  amount: 50.75,
  currency: 'USD'
}, {
  useCache: true,                   // Use cache for transaction
  cachePriority: 'high',            // High cache priority
  invalidateCache: false            // Don't invalidate cache
});

Adaptive Optimization

Let the system automatically adapt and optimize based on transaction patterns:

// Configure adaptive optimization
await wallet.configureAdaptiveOptimization({
  // Learning settings
  learning: {
    enabled: true,
    learningRate: 0.05,             // 5% learning rate
    adaptationSpeed: 'balanced',    // Balanced adaptation speed
    patternRecognition: true,       // Enable pattern recognition
    anomalyDetection: true          // Enable anomaly detection
  },
  
  // Adaptation targets
  adaptTargets: {
    vectorPattern: true,            // Adapt vector pattern
    dimensionality: true,           // Adapt dimensionality
    routingStrategy: true,          // Adapt routing strategy
    cacheStrategy: true,            // Adapt cache strategy
    portMapping: true               // Adapt port mapping
  },
  
  // Constraints
  constraints: {
    minEfficiency: 0.7,             // Minimum efficiency threshold
    maxLatency: 5,                  // Maximum latency (ms)
    safetyMargin: 0.1,              // 10% safety margin
    fallbackPattern: 'phi'          // Default fallback pattern
  }
});

// Execute transactions with adaptive optimization
// The system will automatically optimize over time
const result = await wallet.createTransaction({
  recipient: 'wallet_123',
  amount: 100,
  currency: 'USD'
}, {
  adaptiveOptimization: true        // Enable adaptive optimization
});

Port Integration

Integrate vector trading with the Dragon Ports system for geometric routing through appropriate pathways.

Port-Vector Mapping

Different transaction types naturally map to specific geometric ports:

  • FINANCE Port (010): Primary port for financial transactions using triangular geometry
  • USER Port (001): Identity verification for transaction authentication
  • CREATOR Port (011): Generation of new transaction types and templates
  • KNOWLEDGE Port (101): Analytics and optimization of transaction patterns
  • DRAGONFIRE Port (110): Coordination of multi-part transaction processes

Port-Aware Vector Trading

// Import necessary modules
import { DragonFireClient } from '@dragonfire/client';
import { WalletClient } from '@dragonfire/wallet-client';
import { PortClient } from '@dragonfire/ports-client';

// Initialize clients
const dragonfire = new DragonFireClient({ apiKey: 'YOUR_API_KEY' });
await dragonfire.connect();

const wallet = new WalletClient(dragonfire);
const ports = new PortClient(dragonfire);

// Configure port integration for vector trading
await wallet.configurePortIntegration({
  // Connect to Ports client
  portClient: ports,
  
  // Port routing settings
  portRouting: {
    defaultPort: 'FINANCE',               // Default port for transactions
    portMappingStrategy: 'geometric',     // Geometric port mapping
    crossPortEnabled: true,               // Enable cross-port operations
    geometricCoherence: true,             // Maintain geometric coherence
    
    // Port-specific settings
    portSettings: {
      'FINANCE': {
        priority: 'highest',              // Highest priority for FINANCE port
        optimizationPattern: 'triangle',  // Triangular optimization
        resonanceThreshold: 0.9           // High resonance threshold
      },
      'USER': {
        priority: 'high',                 // High priority for USER port
        optimizationPattern: 'line',      // Linear optimization
        resonanceThreshold: 0.8           // Standard resonance threshold
      }
    }
  }
});

// Execute a transaction with port-specific routing
const result = await wallet.createTransaction({
  recipient: 'wallet_789',
  amount: 50.75,
  currency: 'USD'
}, {
  // Port routing options
  portRouting: {
    primaryPort: 'FINANCE',               // Primary port (FINANCE - triangle)
    supportPorts: ['USER', 'STORAGE'],    // Support ports for the transaction
    portPath: 'FINANCE → USER → FINANCE', // Explicit port path
    optimizePath: true                    // Optimize the port path
  }
});

Geometric Transaction Analysis

Analyze transactions through their geometric properties:

// Analyze transaction geometry
const geometry = await wallet.analyzeTransactionGeometry('tx_123456789', {
  dimensionalMap: true,            // Generate dimensional map
  geometricVisualization: true,    // Generate visualization
  portPathAnalysis: true,          // Analyze port path
  resonanceScore: true             // Calculate resonance score
});

console.log('Transaction geometry:');
console.log('Geometric form:', geometry.form);
console.log('Dimensional structure:', geometry.dimensionalStructure);
console.log('Port path:', geometry.portPath);
console.log('Resonance score:', geometry.resonanceScore);
console.log('Optimization rating:', geometry.optimizationRating);

// Visualize the transaction geometry
const visualization = await wallet.visualizeTransactionGeometry('tx_123456789', {
  format: '3d',                    // 3D visualization
  highlightPortCrossings: true,    // Highlight port crossings
  showOptimalPath: true,           // Show optimal path
  colorScheme: 'phi-resonant'      // Phi-resonant color scheme
});

Performance Metrics

Measure and optimize vector trading performance with comprehensive metrics.

Measuring Transaction Performance

// Measure vector trading performance
const performanceMetrics = await wallet.measureVectorPerformance({
  // Test parameters
  testDuration: 60000,             // 60-second test
  transactionCount: 10000,         // 10,000 test transactions
  transactionSize: 'mixed',        // Mixed transaction sizes
  concurrencyLevel: 'maximum',     // Maximum concurrency
  
  // Measurement settings
  measurements: {
    throughput: true,              // Measure throughput (ops/sec)
    latency: true,                 // Measure latency (ms)
    resourceUsage: true,           // Measure resource usage
    errorRate: true,               // Measure error rate
    pathEfficiency: true,          // Measure path efficiency
    portUtilization: true          // Measure port utilization
  }
});

console.log('Vector performance metrics:');
console.log('Average throughput:', performanceMetrics.throughput.average, 'ops/sec');
console.log('Peak throughput:', performanceMetrics.throughput.peak, 'ops/sec');
console.log('Average latency:', performanceMetrics.latency.average, 'ms');
console.log('99th percentile latency:', performanceMetrics.latency.p99, 'ms');
console.log('Error rate:', performanceMetrics.errorRate * 100, '%');
console.log('Average path efficiency:', performanceMetrics.pathEfficiency.average);
console.log('Resource utilization:', performanceMetrics.resourceUsage.cpuPercent, '% CPU');

// Generate performance visualization
const visualization = await wallet.visualizePerformance(performanceMetrics, {
  format: 'interactive',          // Interactive visualization
  metrics: ['throughput', 'latency', 'efficiency'],
  timeResolution: 'second',       // Per-second resolution
  highlightAnomalities: true      // Highlight anomalies
});

Performance Optimization Recommendations

// Get performance optimization recommendations
const recommendations = await wallet.getPerformanceRecommendations({
  // Analysis scope
  basedOn: {
    recentTransactions: true,     // Analyze recent transactions
    systemConfiguration: true,    // Analyze system configuration
    resourceConstraints: true,    // Consider resource constraints
    timeRange: {                  // Time range for analysis
      start: new Date(Date.now() - 86400000), // Last 24 hours
      end: new Date()
    }
  },
  
  // Recommendation options
  options: {
    maxRecommendations: 5,        // Maximum number of recommendations
    minImpactPercent: 5,          // Minimum 5% impact
    focusAreas: [                 // Focus areas
      'throughput',
      'latency',
      'reliability'
    ],
    implementationDifficulty: 'all' // All difficulty levels
  }
});

console.log('Performance optimization recommendations:');
recommendations.forEach((rec, index) => {
  console.log(`Recommendation ${index + 1}: ${rec.title}`);
  console.log(`Description: ${rec.description}`);
  console.log(`Expected impact: ${rec.impactPercent}% improvement in ${rec.impactArea}`);
  console.log(`Implementation difficulty: ${rec.difficulty}`);
  console.log(`Implementation steps: ${rec.implementationSteps.join(', ')}`);
  console.log('---');
});

Performance Dashboard

Real-time Performance Monitoring

Vector trading performance can be monitored in real-time through the DragonFire Developer Portal dashboard:

Vector Trading Performance Dashboard

To access the dashboard, use:

// Generate dashboard access token
const dashboardToken = await wallet.generateDashboardToken({
  metrics: ['all'],                  // Monitor all metrics
  refreshInterval: 1000,             // 1-second refresh interval
  duration: 3600000                  // 1-hour validity
});

console.log('Dashboard URL:', `https://developer.dragonfire.ai/dashboard?token=${dashboardToken}`);

Complete Implementation Example

A comprehensive example of vector trading implementation with advanced features:

// Vector Trading Implementation Example
// -----------------------------------------

// Import necessary modules
import { DragonFireClient } from '@dragonfire/client';
import { WalletClient } from '@dragonfire/wallet-client';
import { PortClient } from '@dragonfire/ports-client';
import { CacheClient } from '@dragonfire/cache-client';

// Initialize the DragonFire ecosystem
async function initializeDragonFire() {
  // Connect to DragonFire
  const dragonfire = new DragonFireClient({
    apiKey: 'YOUR_API_KEY',
    region: 'us-west',
    securityLevel: 'high'
  });
  await dragonfire.connect();
  
  // Initialize clients
  const wallet = new WalletClient(dragonfire);
  const ports = new PortClient(dragonfire);
  const cache = new CacheClient(dragonfire);
  
  // Configure the vector trading environment
  await wallet.configureVectorTrading({
    defaultPattern: 'phi',
    dimensionality: 7,
    optimizationLevel: 'maximum',