Phase 3: JavaScript pattern decoder implementation

Completed JavaScript port of pattern_decoder.py with full client-side
RF signal analysis capability for Sub-GHz devices.

## New Files Created (8 files, ~2,100 lines):

### Core Decoder Modules:
- static/js/decoder/protocol-database.js (410 lines)
  * 18 RF protocol signatures (Weather, Garage, TPMS, Doorbells, Security, Remotes)
  * ProtocolSignature class with timing/frequency matching
  * ProtocolDatabase with indexed queries
  * Categories: Weather Sensors (7), Garage Doors (3), TPMS (2), etc.

- static/js/decoder/pulse-analyzer.js (238 lines)
  * K-means clustering for SHORT/LONG pulse detection
  * identifyPulseWidths() using k-means
  * decodeToBits() for PWM encoding (SHORT=0, LONG=1)
  * analyzePulseTrain() for comprehensive timing analysis
  * validatePulseData() quality checks
  * estimateSNR() signal quality estimation

- static/js/decoder/fingerprint.js (312 lines)
  * PulseFingerprint class for statistical characteristics
  * extractFingerprint() - mean, std, duty cycle, pulse/gap ratio
  * calculateSimilarity() - 0-1 similarity score with weights
  * compareToProtocol() - protocol library matching
  * classifySignal() - heuristic device type classification
  * generateReport() - debugging output

- static/js/decoder/pattern-decoder.js (457 lines)
  * DeviceMatch class (standardized result format)
  * PatternDecoder main decoder class
  * Multi-strategy decoding:
    - Strategy 1: Timing pattern analysis (K-means + protocol DB)
    - Strategy 2: Statistical fingerprint matching
    - Strategy 3: Heuristic classification (fallback)
  * Match deduplication and ranking
  * Statistics tracking (success rate, avg confidence)

- static/js/decoder/index.js (226 lines)
  * ES6 module exports for all decoder components
  * parseSubFile() - Flipper Zero .sub parser
  * quickDecode() - convenience API
  * decodeFromURL() - fetch and decode remote files
  * decodeFromFile() - browser File API support
  * getVersion() - version and feature info

### Demo & Testing:
- static/decoder-demo.html (374 lines)
  * Beautiful drag-and-drop UI for .sub file upload
  * Real-time client-side decoding (no server needed!)
  * Interactive results with confidence badges
  * Signal quality visualization
  * Debug console output
  * Mobile-responsive design

- static/js/decoder/test.js (120 lines)
  * Node.js test suite for decoder
  * Tests all 4 strategies (timing, fingerprint, protocol DB, heuristics)
  * Validates parsing, analysis, and matching
  * Example output shows 7 matches @ 43.3% confidence

- package.json
  * Enable ES6 modules ("type": "module")
  * NPM script: "test:decoder"

## Test Results:
 JavaScript decoder successfully tested with Node.js
 Found 7 device matches on test .sub file (43.3% best confidence)
 All modules working: protocol DB (18 protocols), pulse analysis, fingerprinting, decoding
 Browser demo ready at /static/decoder-demo.html

## Features:
- 🔬 K-means pulse width clustering
- 📊 Statistical fingerprinting
- 📚 Protocol library matching (18 protocols)
- 🎯 Multi-strategy matching
- 📱 Client-side decoding (privacy-focused)
- 🌐 Browser and Node.js compatible
-  Single-transmission decoding (no repetitions needed)

## Next Steps:
- Integrate decoder into main upload UI
- Test with T-Embed and Flipper datasets
- Optimize for larger .sub files
- Add more protocol signatures

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
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{
"name": "giglez",
"version": "1.0.0",
"description": "IoT RF Device Mapping Platform - Wigle for Sub-GHz Signals",
"type": "module",
"scripts": {
"test:decoder": "node static/js/decoder/test.js"
},
"keywords": [
"rf",
"iot",
"sub-ghz",
"flipper-zero",
"pattern-decoder",
"signal-analysis"
],
"author": "GigLez",
"license": "MIT"
}
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>GigLez Pattern Decoder - Browser Demo</title>
<style>
* {
margin: 0;
padding: 0;
box-sizing: border-box;
}
body {
font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
min-height: 100vh;
padding: 20px;
}
.container {
max-width: 1200px;
margin: 0 auto;
background: white;
border-radius: 12px;
box-shadow: 0 10px 40px rgba(0, 0, 0, 0.2);
overflow: hidden;
}
.header {
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
color: white;
padding: 30px;
text-align: center;
}
.header h1 {
font-size: 2.5em;
margin-bottom: 10px;
}
.header p {
font-size: 1.1em;
opacity: 0.9;
}
.content {
padding: 30px;
}
.upload-section {
background: #f7f9fc;
border: 2px dashed #667eea;
border-radius: 8px;
padding: 40px;
text-align: center;
margin-bottom: 30px;
cursor: pointer;
transition: all 0.3s ease;
}
.upload-section:hover {
border-color: #764ba2;
background: #eef2f7;
}
.upload-section.dragover {
background: #e3e9f3;
border-color: #764ba2;
}
.upload-icon {
font-size: 3em;
margin-bottom: 15px;
}
.btn {
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
color: white;
border: none;
padding: 12px 30px;
font-size: 1em;
border-radius: 6px;
cursor: pointer;
transition: transform 0.2s ease;
}
.btn:hover {
transform: translateY(-2px);
}
.btn:active {
transform: translateY(0);
}
.file-input {
display: none;
}
.results-section {
display: none;
}
.results-section.visible {
display: block;
}
.file-info {
background: #f7f9fc;
border-radius: 8px;
padding: 20px;
margin-bottom: 20px;
}
.file-info h3 {
color: #667eea;
margin-bottom: 15px;
}
.info-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
gap: 15px;
}
.info-item {
background: white;
padding: 12px;
border-radius: 6px;
}
.info-item label {
font-size: 0.85em;
color: #666;
display: block;
margin-bottom: 5px;
}
.info-item value {
font-weight: 600;
color: #333;
font-size: 1.1em;
}
.matches-container {
margin-top: 20px;
}
.matches-header {
display: flex;
justify-content: space-between;
align-items: center;
margin-bottom: 15px;
}
.matches-header h3 {
color: #667eea;
}
.badge {
background: #667eea;
color: white;
padding: 5px 12px;
border-radius: 20px;
font-size: 0.9em;
}
.match-card {
background: white;
border: 2px solid #e3e9f3;
border-radius: 8px;
padding: 20px;
margin-bottom: 15px;
transition: all 0.3s ease;
}
.match-card:hover {
border-color: #667eea;
box-shadow: 0 4px 12px rgba(102, 126, 234, 0.15);
}
.match-header {
display: flex;
justify-content: space-between;
align-items: start;
margin-bottom: 15px;
}
.device-name {
font-size: 1.3em;
font-weight: 600;
color: #333;
}
.manufacturer {
color: #666;
font-size: 0.95em;
margin-top: 5px;
}
.confidence-badge {
padding: 8px 16px;
border-radius: 20px;
font-weight: 600;
font-size: 0.9em;
}
.confidence-high {
background: #10b981;
color: white;
}
.confidence-medium {
background: #f59e0b;
color: white;
}
.confidence-low {
background: #6b7280;
color: white;
}
.match-details {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(150px, 1fr));
gap: 10px;
margin-top: 15px;
padding-top: 15px;
border-top: 1px solid #e3e9f3;
}
.detail-item {
font-size: 0.9em;
}
.detail-label {
color: #666;
margin-bottom: 3px;
}
.detail-value {
color: #333;
font-weight: 600;
}
.no-matches {
text-align: center;
padding: 40px;
color: #666;
}
.no-matches-icon {
font-size: 3em;
margin-bottom: 15px;
opacity: 0.3;
}
.debug-section {
margin-top: 30px;
background: #f7f9fc;
border-radius: 8px;
padding: 20px;
}
.debug-section h3 {
color: #667eea;
margin-bottom: 15px;
}
.debug-output {
background: #1e293b;
color: #e2e8f0;
padding: 15px;
border-radius: 6px;
font-family: 'Courier New', monospace;
font-size: 0.85em;
max-height: 300px;
overflow-y: auto;
white-space: pre-wrap;
}
.stats-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(150px, 1fr));
gap: 15px;
margin-bottom: 20px;
}
.stat-card {
background: white;
padding: 15px;
border-radius: 6px;
text-align: center;
}
.stat-value {
font-size: 2em;
font-weight: 700;
color: #667eea;
}
.stat-label {
color: #666;
font-size: 0.9em;
margin-top: 5px;
}
.loading {
text-align: center;
padding: 40px;
color: #667eea;
}
.spinner {
border: 4px solid #f3f4f6;
border-top: 4px solid #667eea;
border-radius: 50%;
width: 40px;
height: 40px;
animation: spin 1s linear infinite;
margin: 0 auto 15px;
}
@keyframes spin {
0% { transform: rotate(0deg); }
100% { transform: rotate(360deg); }
}
</style>
</head>
<body>
<div class="container">
<div class="header">
<h1>🔬 GigLez Pattern Decoder</h1>
<p>Client-Side RF Signal Analysis for Sub-GHz Devices</p>
</div>
<div class="content">
<!-- Upload Section -->
<div class="upload-section" id="uploadSection">
<div class="upload-icon">📡</div>
<h2>Drop .sub file or click to upload</h2>
<p style="margin: 15px 0;">Supports Flipper Zero and LilyGo T-Embed RAW captures</p>
<button class="btn" onclick="document.getElementById('fileInput').click()">
Choose File
</button>
<input type="file" id="fileInput" class="file-input" accept=".sub,.txt">
</div>
<!-- Loading -->
<div class="loading" id="loadingSection" style="display: none;">
<div class="spinner"></div>
<p>Analyzing RF signal...</p>
</div>
<!-- Results Section -->
<div class="results-section" id="resultsSection">
<!-- File Info -->
<div class="file-info">
<h3>📄 File Information</h3>
<div class="info-grid" id="fileInfoGrid"></div>
</div>
<!-- Decoder Stats -->
<div class="stats-grid" id="statsGrid"></div>
<!-- Matches -->
<div class="matches-container">
<div class="matches-header">
<h3>🎯 Device Matches</h3>
<span class="badge" id="matchCount">0 matches</span>
</div>
<div id="matchesContainer"></div>
</div>
<!-- Debug Section -->
<div class="debug-section">
<h3>🐛 Debug Output</h3>
<div class="debug-output" id="debugOutput"></div>
</div>
</div>
</div>
</div>
<script type="module">
import { decodeFromFile, parseSubFile, getVersion } from './js/decoder/index.js';
let debugLog = [];
// Override console.log for debug output
const originalLog = console.log;
console.log = function(...args) {
debugLog.push(args.join(' '));
originalLog.apply(console, args);
};
// Print version info
const version = getVersion();
console.log(`${version.name} v${version.version}`);
console.log(`Loaded ${version.protocols} protocols`);
// File upload handling
const fileInput = document.getElementById('fileInput');
const uploadSection = document.getElementById('uploadSection');
const loadingSection = document.getElementById('loadingSection');
const resultsSection = document.getElementById('resultsSection');
fileInput.addEventListener('change', handleFileSelect);
// Drag and drop
uploadSection.addEventListener('dragover', (e) => {
e.preventDefault();
uploadSection.classList.add('dragover');
});
uploadSection.addEventListener('dragleave', () => {
uploadSection.classList.remove('dragover');
});
uploadSection.addEventListener('drop', (e) => {
e.preventDefault();
uploadSection.classList.remove('dragover');
const files = e.dataTransfer.files;
if (files.length > 0) {
handleFile(files[0]);
}
});
async function handleFileSelect(e) {
const file = e.target.files[0];
if (file) {
await handleFile(file);
}
}
async function handleFile(file) {
debugLog = [];
console.log(`\n=== Analyzing ${file.name} ===\n`);
// Show loading
uploadSection.style.display = 'none';
loadingSection.style.display = 'block';
resultsSection.classList.remove('visible');
try {
// Parse file
const content = await file.text();
const metadata = parseSubFile(content);
console.log('Parsed metadata:', metadata);
// Decode with debug enabled
const matches = await decodeFromFile(file, { debug: true, minConfidence: 0.3 });
console.log(`\nFound ${matches.length} device matches\n`);
// Display results
displayResults(file.name, metadata, matches);
} catch (error) {
console.error('Error:', error);
alert('Failed to decode file: ' + error.message);
uploadSection.style.display = 'block';
loadingSection.style.display = 'none';
}
}
function displayResults(filename, metadata, matches) {
// Hide loading, show results
loadingSection.style.display = 'none';
resultsSection.classList.add('visible');
// File info
const fileInfoGrid = document.getElementById('fileInfoGrid');
fileInfoGrid.innerHTML = `
<div class="info-item">
<label>Filename</label>
<value>${filename}</value>
</div>
<div class="info-item">
<label>Protocol</label>
<value>${metadata.protocol || 'Unknown'}</value>
</div>
<div class="info-item">
<label>Frequency</label>
<value>${metadata.frequency ? (metadata.frequency / 1e6).toFixed(2) + ' MHz' : 'Unknown'}</value>
</div>
<div class="info-item">
<label>Preset</label>
<value>${metadata.preset || 'Unknown'}</value>
</div>
<div class="info-item">
<label>Pulses</label>
<value>${metadata.raw_data?.length || 0}</value>
</div>
`;
// Stats
const statsGrid = document.getElementById('statsGrid');
const avgConfidence = matches.length > 0
? (matches.reduce((sum, m) => sum + m.confidence, 0) / matches.length * 100).toFixed(1)
: 0;
statsGrid.innerHTML = `
<div class="stat-card">
<div class="stat-value">${matches.length}</div>
<div class="stat-label">Matches Found</div>
</div>
<div class="stat-card">
<div class="stat-value">${avgConfidence}%</div>
<div class="stat-label">Avg Confidence</div>
</div>
<div class="stat-card">
<div class="stat-value">${matches.length > 0 ? (matches[0].confidence * 100).toFixed(1) + '%' : 'N/A'}</div>
<div class="stat-label">Best Match</div>
</div>
`;
// Match count badge
document.getElementById('matchCount').textContent = `${matches.length} match${matches.length !== 1 ? 'es' : ''}`;
// Matches
const matchesContainer = document.getElementById('matchesContainer');
if (matches.length === 0) {
matchesContainer.innerHTML = `
<div class="no-matches">
<div class="no-matches-icon">🔍</div>
<p>No device matches found</p>
<p style="margin-top: 10px; font-size: 0.9em;">Try adjusting the minimum confidence threshold or check the debug output below.</p>
</div>
`;
} else {
matchesContainer.innerHTML = matches.map((match, index) => {
const confidence = (match.confidence * 100).toFixed(1);
const confidenceClass = confidence >= 70 ? 'confidence-high' :
confidence >= 50 ? 'confidence-medium' : 'confidence-low';
const details = Object.entries(match.matchDetails || {})
.map(([key, value]) => `
<div class="detail-item">
<div class="detail-label">${key.replace(/_/g, ' ')}</div>
<div class="detail-value">${value}</div>
</div>
`).join('');
return `
<div class="match-card">
<div class="match-header">
<div>
<div class="device-name">${index + 1}. ${match.deviceName}</div>
<div class="manufacturer">${match.manufacturer}</div>
</div>
<div class="confidence-badge ${confidenceClass}">
${confidence}%
</div>
</div>
<div style="margin-bottom: 10px;">
<span style="background: #e3e9f3; padding: 4px 10px; border-radius: 12px; font-size: 0.85em; color: #667eea;">
${match.matchMethod}
</span>
</div>
${details ? `<div class="match-details">${details}</div>` : ''}
</div>
`;
}).join('');
}
// Debug output
document.getElementById('debugOutput').textContent = debugLog.join('\n');
}
// Allow reset
document.getElementById('resultsSection').addEventListener('click', (e) => {
if (e.target.classList.contains('btn')) {
uploadSection.style.display = 'block';
resultsSection.classList.remove('visible');
}
});
</script>
</body>
</html>
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/**
* GigLez Statistical Fingerprint Extractor
* JavaScript port of Python pattern_decoder.py fingerprinting
*
* Extracts statistical characteristics from pulse data
* for device matching
*
* @module fingerprint
*/
/**
* Calculate mean of array
* @private
*/
function mean(arr) {
if (arr.length === 0) return 0;
return arr.reduce((sum, val) => sum + val, 0) / arr.length;
}
/**
* Calculate standard deviation of array
* @private
*/
function std(arr) {
if (arr.length === 0) return 0;
const m = mean(arr);
const variance = arr.reduce((sum, val) => sum + Math.pow(val - m, 2), 0) / arr.length;
return Math.sqrt(variance);
}
/**
* Calculate sum of array
* @private
*/
function sum(arr) {
return arr.reduce((a, b) => a + b, 0);
}
/**
* Pulse Fingerprint - Statistical characteristics of a signal
*/
export class PulseFingerprint {
constructor({
meanPulseWidth = 0,
stdPulseWidth = 0,
meanGapWidth = 0,
stdGapWidth = 0,
pulseGapRatio = 0,
dutyCycle = 0,
pulseCount = 0,
minPulse = 0,
maxPulse = 0,
minGap = 0,
maxGap = 0
}) {
this.meanPulseWidth = meanPulseWidth;
this.stdPulseWidth = stdPulseWidth;
this.meanGapWidth = meanGapWidth;
this.stdGapWidth = stdGapWidth;
this.pulseGapRatio = pulseGapRatio;
this.dutyCycle = dutyCycle;
this.pulseCount = pulseCount;
this.minPulse = minPulse;
this.maxPulse = maxPulse;
this.minGap = minGap;
this.maxGap = maxGap;
}
/**
* Convert to plain object
* @returns {Object}
*/
toObject() {
return {
meanPulseWidth: this.meanPulseWidth,
stdPulseWidth: this.stdPulseWidth,
meanGapWidth: this.meanGapWidth,
stdGapWidth: this.stdGapWidth,
pulseGapRatio: this.pulseGapRatio,
dutyCycle: this.dutyCycle,
pulseCount: this.pulseCount,
minPulse: this.minPulse,
maxPulse: this.maxPulse,
minGap: this.minGap,
maxGap: this.maxGap
};
}
/**
* Get human-readable summary
* @returns {string}
*/
toString() {
return `Fingerprint(pulses=${this.pulseCount}, ` +
`mean=${this.meanPulseWidth.toFixed(1)}μs, ` +
`duty=${(this.dutyCycle * 100).toFixed(1)}%)`;
}
}
/**
* Extract statistical fingerprint from pulse data
*
* Analyzes timing characteristics to create a unique
* signature for the signal
*
* @param {number[]} pulses - Raw pulse data (positive = HIGH, negative = LOW)
* @returns {PulseFingerprint}
*/
export function extractFingerprint(pulses) {
if (!pulses || pulses.length === 0) {
return new PulseFingerprint({});
}
// Separate HIGH pulses and LOW gaps
const highPulses = pulses.filter(p => p > 0);
const lowPulses = pulses.filter(p => p < 0).map(Math.abs);
// Calculate pulse statistics
const meanPulse = mean(highPulses);
const stdPulse = std(highPulses);
// Calculate gap statistics
const meanGap = mean(lowPulses);
const stdGap = std(lowPulses);
// Calculate timing ratios
const totalHigh = sum(highPulses);
const totalLow = sum(lowPulses);
const totalTime = totalHigh + totalLow;
const pulseGapRatio = meanGap > 0 ? meanPulse / meanGap : 0;
const dutyCycle = totalTime > 0 ? totalHigh / totalTime : 0;
return new PulseFingerprint({
meanPulseWidth: meanPulse,
stdPulseWidth: stdPulse,
meanGapWidth: meanGap,
stdGapWidth: stdGap,
pulseGapRatio,
dutyCycle,
pulseCount: pulses.length,
minPulse: highPulses.length > 0 ? Math.min(...highPulses) : 0,
maxPulse: highPulses.length > 0 ? Math.max(...highPulses) : 0,
minGap: lowPulses.length > 0 ? Math.min(...lowPulses) : 0,
maxGap: lowPulses.length > 0 ? Math.max(...lowPulses) : 0
});
}
/**
* Calculate similarity between two fingerprints
* Returns a score from 0 (no match) to 1 (perfect match)
*
* @param {PulseFingerprint} fp1 - First fingerprint
* @param {PulseFingerprint} fp2 - Second fingerprint
* @returns {number} Similarity score (0-1)
*/
export function calculateSimilarity(fp1, fp2) {
// Pulse width similarity (40% weight)
const pulseWidthError = Math.abs(fp1.meanPulseWidth - fp2.meanPulseWidth) /
Math.max(fp1.meanPulseWidth, fp2.meanPulseWidth);
const pulseWidthSimilarity = Math.max(0, 1 - pulseWidthError);
// Pulse count similarity (30% weight)
const countError = Math.abs(fp1.pulseCount - fp2.pulseCount) /
Math.max(fp1.pulseCount, fp2.pulseCount);
const countSimilarity = Math.max(0, 1 - countError);
// Duty cycle similarity (20% weight)
const dutyError = Math.abs(fp1.dutyCycle - fp2.dutyCycle);
const dutySimilarity = Math.max(0, 1 - dutyError);
// Pulse/gap ratio similarity (10% weight)
const ratioError = Math.abs(fp1.pulseGapRatio - fp2.pulseGapRatio) /
Math.max(fp1.pulseGapRatio, fp2.pulseGapRatio);
const ratioSimilarity = Math.max(0, 1 - ratioError);
// Weighted average
return (
pulseWidthSimilarity * 0.4 +
countSimilarity * 0.3 +
dutySimilarity * 0.2 +
ratioSimilarity * 0.1
);
}
/**
* Compare fingerprint against expected protocol characteristics
* Used for protocol library matching
*
* @param {PulseFingerprint} fingerprint - Observed fingerprint
* @param {Object} expected - Expected characteristics from protocol
* @param {number} expected.shortPulseUs - Expected short pulse width
* @param {number} expected.longPulseUs - Expected long pulse width
* @param {number} expected.typicalPulseCount - Expected pulse count
* @returns {Object} { pulseSimilarity, countSimilarity, overall }
*/
export function compareToProtocol(fingerprint, expected) {
// Expected mean pulse is average of short and long
const expectedMeanPulse = (expected.shortPulseUs + expected.longPulseUs) / 2;
// Pulse width comparison
const pulseError = Math.abs(expectedMeanPulse - fingerprint.meanPulseWidth) / expectedMeanPulse;
const pulseSimilarity = Math.max(0, 1 - pulseError);
// Pulse count comparison
const countError = Math.abs(expected.typicalPulseCount - fingerprint.pulseCount) /
expected.typicalPulseCount;
const countSimilarity = Math.max(0, 1 - countError);
// Overall score (weighted)
const overall = (pulseSimilarity * 0.6 + countSimilarity * 0.4) * 0.8; // Scale down for lower confidence
return {
pulseSimilarity,
countSimilarity,
overall,
pulseError: `${(pulseError * 100).toFixed(2)}%`,
countError: `${(countError * 100).toFixed(2)}%`
};
}
/**
* Classify signal type based on fingerprint
* Uses heuristics to guess signal type
*
* @param {PulseFingerprint} fingerprint
* @returns {Object} { type, confidence, reason }
*/
export function classifySignal(fingerprint) {
const { meanPulseWidth, dutyCycle, pulseCount, pulseGapRatio } = fingerprint;
// Very short pulses (< 100μs) - likely TPMS or high-speed protocol
if (meanPulseWidth < 100) {
return {
type: 'TPMS or High-Speed',
confidence: 0.7,
reason: `Very short pulses (${meanPulseWidth.toFixed(0)}μs)`
};
}
// Short pulses (100-300μs) - likely Acurite or similar
if (meanPulseWidth >= 100 && meanPulseWidth < 300) {
return {
type: 'Acurite-like',
confidence: 0.6,
reason: `Short pulses (${meanPulseWidth.toFixed(0)}μs)`
};
}
// Medium pulses (300-700μs) - likely garage door openers or remotes
if (meanPulseWidth >= 300 && meanPulseWidth < 700) {
return {
type: 'Remote Control',
confidence: 0.6,
reason: `Medium pulses (${meanPulseWidth.toFixed(0)}μs)`
};
}
// Long pulses (700+μs) - likely Oregon Scientific or weather sensors
if (meanPulseWidth >= 700) {
return {
type: 'Weather Sensor',
confidence: 0.7,
reason: `Long pulses (${meanPulseWidth.toFixed(0)}μs)`
};
}
return {
type: 'Unknown',
confidence: 0.3,
reason: 'Pulse characteristics do not match known patterns'
};
}
/**
* Generate detailed fingerprint report
* For debugging and analysis
*
* @param {PulseFingerprint} fingerprint
* @returns {string} Multi-line report
*/
export function generateReport(fingerprint) {
const classification = classifySignal(fingerprint);
return `
Pulse Fingerprint Report
========================
Basic Statistics:
Total Pulses: ${fingerprint.pulseCount}
Mean Pulse Width: ${fingerprint.meanPulseWidth.toFixed(2)} μs
Std Dev: ${fingerprint.stdPulseWidth.toFixed(2)} μs
Mean Gap Width: ${fingerprint.meanGapWidth.toFixed(2)} μs
Std Dev: ${fingerprint.stdGapWidth.toFixed(2)} μs
Pulse Range:
Min Pulse: ${fingerprint.minPulse} μs
Max Pulse: ${fingerprint.maxPulse} μs
Min Gap: ${fingerprint.minGap} μs
Max Gap: ${fingerprint.maxGap} μs
Timing Characteristics:
Pulse/Gap Ratio: ${fingerprint.pulseGapRatio.toFixed(3)}
Duty Cycle: ${(fingerprint.dutyCycle * 100).toFixed(2)}%
Classification:
Likely Type: ${classification.type}
Confidence: ${(classification.confidence * 100).toFixed(0)}%
Reason: ${classification.reason}
`.trim();
}
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/**
* GigLez Pattern Decoder - Main Entry Point
* JavaScript RF Signal Decoder for Sub-GHz Devices
*
* Export all decoder modules for browser and Node.js usage
*
* @module giglez-decoder
* @version 1.0.0
*/
// ============================================================================
// Protocol Database
// ============================================================================
export {
ProtocolSignature,
ProtocolDatabase,
WEATHER_SENSORS,
GARAGE_DOOR_OPENERS,
DOORBELLS,
TIRE_PRESSURE,
SECURITY_SENSORS,
REMOTE_CONTROLS,
ALL_PROTOCOLS,
protocolDb
} from './protocol-database.js';
// ============================================================================
// Pulse Analysis
// ============================================================================
export {
kMeans,
identifyPulseWidths,
decodeToBits,
analyzePulseTrain,
validatePulseData,
estimateSNR
} from './pulse-analyzer.js';
// ============================================================================
// Statistical Fingerprinting
// ============================================================================
export {
PulseFingerprint,
extractFingerprint,
calculateSimilarity,
compareToProtocol,
classifySignal,
generateReport
} from './fingerprint.js';
// ============================================================================
// Pattern Decoder (Main)
// ============================================================================
export {
DeviceMatch,
PatternDecoder,
decode
} from './pattern-decoder.js';
// ============================================================================
// Convenience API
// ============================================================================
/**
* Quick decode function - analyze .sub file and return device matches
*
* @param {Object} metadata - Parsed .sub file metadata
* @param {number} metadata.frequency - Frequency in Hz
* @param {string} metadata.preset - Modulation preset
* @param {string} metadata.protocol - Protocol name
* @param {number[]} metadata.raw_data - Pulse timing array
* @param {Object} options - Decoder options
* @param {number} options.minConfidence - Minimum confidence threshold (default: 0.4)
* @param {number} options.maxResults - Maximum results to return (default: 10)
* @param {boolean} options.debug - Enable debug logging (default: false)
* @returns {Promise<Array>} Array of DeviceMatch objects
*
* @example
* import { quickDecode } from './decoder/index.js';
*
* const metadata = {
* frequency: 433920000,
* preset: 'FuriHalSubGhzPresetOok270Async',
* protocol: 'RAW',
* raw_data: [2980, -240, 520, -980, 520, -980, ...]
* };
*
* const matches = await quickDecode(metadata, { debug: true });
* console.log(matches[0].toString());
*/
export async function quickDecode(metadata, options = {}) {
const { PatternDecoder } = await import('./pattern-decoder.js');
const decoder = new PatternDecoder(options);
return decoder.decode(metadata);
}
/**
* Parse Flipper Zero .sub file format
*
* @param {string} content - Raw .sub file content
* @returns {Object} Parsed metadata
*
* @example
* const content = await fetch('capture.sub').then(r => r.text());
* const metadata = parseSubFile(content);
* const matches = await quickDecode(metadata);
*/
export function parseSubFile(content) {
const lines = content.split('\n');
const metadata = {
filetype: null,
version: null,
frequency: null,
preset: null,
protocol: null,
bit: null,
key: null,
te: null,
raw_data: []
};
for (const line of lines) {
const trimmed = line.trim();
if (!trimmed || trimmed.startsWith('#')) continue;
if (trimmed.includes(':')) {
const [key, value] = trimmed.split(':', 2).map(s => s.trim());
switch (key) {
case 'Filetype':
metadata.filetype = value;
break;
case 'Version':
metadata.version = parseInt(value);
break;
case 'Frequency':
metadata.frequency = parseInt(value);
break;
case 'Preset':
metadata.preset = value;
break;
case 'Protocol':
metadata.protocol = value;
break;
case 'Bit':
metadata.bit = parseInt(value);
break;
case 'Key':
metadata.key = value;
break;
case 'TE':
metadata.te = parseInt(value);
break;
case 'RAW_Data':
// Parse pulse timing array
const pulses = value.split(/\s+/)
.map(s => parseInt(s))
.filter(n => !isNaN(n));
metadata.raw_data.push(...pulses);
break;
}
}
}
return metadata;
}
/**
* Decode .sub file from URL
*
* @param {string} url - URL to .sub file
* @param {Object} options - Decoder options
* @returns {Promise<Array>} Device matches
*
* @example
* const matches = await decodeFromURL('https://example.com/capture.sub');
* console.log(`Found ${matches.length} potential devices`);
*/
export async function decodeFromURL(url, options = {}) {
const response = await fetch(url);
const content = await response.text();
const metadata = parseSubFile(content);
return quickDecode(metadata, options);
}
/**
* Decode .sub file from File object (browser)
*
* @param {File} file - File object from file input
* @param {Object} options - Decoder options
* @returns {Promise<Array>} Device matches
*
* @example
* document.getElementById('fileInput').addEventListener('change', async (e) => {
* const file = e.target.files[0];
* const matches = await decodeFromFile(file, { debug: true });
* console.log(matches);
* });
*/
export async function decodeFromFile(file, options = {}) {
const content = await file.text();
const metadata = parseSubFile(content);
return quickDecode(metadata, options);
}
/**
* Get decoder version information
* @returns {Object} Version info
*/
export async function getVersion() {
const { ALL_PROTOCOLS } = await import('./protocol-database.js');
return {
version: '1.0.0',
name: 'GigLez Pattern Decoder',
description: 'JavaScript RF Signal Decoder for Sub-GHz Devices',
protocols: ALL_PROTOCOLS.length,
features: [
'K-means pulse width clustering',
'Statistical fingerprinting',
'Protocol library matching',
'18 built-in protocols',
'Single-transmission decoding',
'Browser and Node.js compatible'
]
};
}
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/**
* GigLez Pattern-Based Decoder
* JavaScript port of Python pattern_decoder.py
*
* Main decoder class combining timing analysis, fingerprinting,
* and protocol matching for single-transmission RF captures
*
* @module pattern-decoder
*/
import { protocolDb } from './protocol-database.js';
import { identifyPulseWidths, decodeToBits, analyzePulseTrain, validatePulseData, estimateSNR } from './pulse-analyzer.js';
import { extractFingerprint, calculateSimilarity, compareToProtocol, classifySignal } from './fingerprint.js';
/**
* Device Match Result
* Standardized format matching Python MatchResult
*/
export class DeviceMatch {
constructor({
deviceName,
manufacturer = 'Unknown',
confidence = 0.0,
matchMethod = 'pattern',
matchDetails = {}
}) {
this.deviceName = deviceName;
this.manufacturer = manufacturer;
this.confidence = confidence;
this.matchMethod = matchMethod;
this.matchDetails = matchDetails;
}
/**
* Convert to plain object for JSON serialization
*/
toObject() {
return {
device_name: this.deviceName,
manufacturer: this.manufacturer,
confidence: this.confidence,
match_method: this.matchMethod,
match_details: this.matchDetails
};
}
/**
* Human-readable string representation
*/
toString() {
return `${this.manufacturer} ${this.deviceName} (${(this.confidence * 100).toFixed(1)}% via ${this.matchMethod})`;
}
}
/**
* Pattern-Based RF Signal Decoder
*
* Decodes single-transmission Sub-GHz captures from Flipper Zero,
* LilyGo T-Embed CC1101, and other devices
*/
export class PatternDecoder {
constructor(options = {}) {
this.minConfidence = options.minConfidence || 0.4;
this.maxResults = options.maxResults || 10;
this.debug = options.debug || false;
// Load protocol database
this.protocolDb = protocolDb;
// Statistics
this.stats = {
totalDecodes: 0,
successfulDecodes: 0,
failedDecodes: 0,
averageConfidence: 0
};
}
/**
* Main decoding method - analyze .sub file RAW_Data
*
* @param {Object} metadata - Parsed .sub file metadata
* @param {number} metadata.frequency - Frequency in Hz
* @param {string} metadata.preset - Modulation preset
* @param {string} metadata.protocol - Protocol name (may be "RAW")
* @param {number[]} metadata.raw_data - Array of pulse timings (positive=HIGH, negative=LOW)
* @returns {DeviceMatch[]} Array of device matches sorted by confidence
*/
decode(metadata) {
this.stats.totalDecodes++;
try {
// Validate input
if (!metadata.raw_data || metadata.raw_data.length === 0) {
if (this.debug) console.log('❌ No RAW_Data found in metadata');
this.stats.failedDecodes++;
return [];
}
// Validate pulse data quality
const validation = validatePulseData(metadata.raw_data);
if (!validation.valid) {
if (this.debug) {
console.log('⚠️ Pulse data quality issues:');
validation.issues.forEach(issue => console.log(` - ${issue}`));
}
// Continue anyway, but flag low quality
}
// Estimate signal quality
const snr = estimateSNR(metadata.raw_data);
if (this.debug) {
console.log(`📊 Signal Quality: ${(snr * 100).toFixed(1)}%`);
}
const matches = [];
// Strategy 1: Timing Pattern Analysis
const timingMatches = this._decodeTimingPatterns(metadata);
matches.push(...timingMatches);
// Strategy 2: Statistical Fingerprint Matching
const fingerprintMatches = this._matchFingerprint(metadata);
matches.push(...fingerprintMatches);
// Strategy 3: Heuristic Classification (fallback)
if (matches.length === 0) {
const heuristicMatches = this._classifyByHeuristics(metadata);
matches.push(...heuristicMatches);
}
// Deduplicate and rank matches
const rankedMatches = this._rankMatches(matches);
// Filter by minimum confidence
const filteredMatches = rankedMatches.filter(m => m.confidence >= this.minConfidence);
// Limit results
const finalMatches = filteredMatches.slice(0, this.maxResults);
// Update statistics
if (finalMatches.length > 0) {
this.stats.successfulDecodes++;
const avgConf = finalMatches.reduce((sum, m) => sum + m.confidence, 0) / finalMatches.length;
this.stats.averageConfidence = (this.stats.averageConfidence * (this.stats.successfulDecodes - 1) + avgConf) / this.stats.successfulDecodes;
} else {
this.stats.failedDecodes++;
}
if (this.debug) {
console.log(`✅ Found ${finalMatches.length} matches`);
finalMatches.forEach((m, i) => {
console.log(` ${i + 1}. ${m.toString()}`);
});
}
return finalMatches;
} catch (error) {
if (this.debug) {
console.error('❌ Decode error:', error);
}
this.stats.failedDecodes++;
return [];
}
}
/**
* Strategy 1: Timing Pattern Analysis
* Uses K-means clustering to identify pulse widths and match against protocol library
*
* @private
*/
_decodeTimingPatterns(metadata) {
const matches = [];
try {
// Identify SHORT and LONG pulse widths using K-means
const { shortPulse, longPulse, shortGap, longGap } = identifyPulseWidths(metadata.raw_data);
if (this.debug) {
console.log(`🔍 Timing Analysis:`);
console.log(` Short Pulse: ${shortPulse.toFixed(1)} μs`);
console.log(` Long Pulse: ${longPulse.toFixed(1)} μs`);
console.log(` Short Gap: ${shortGap.toFixed(1)} μs`);
console.log(` Long Gap: ${longGap.toFixed(1)} μs`);
}
// Match against protocol database
const protocolMatches = this.protocolDb.findByTiming(
shortPulse,
longPulse,
metadata.frequency
);
if (this.debug && protocolMatches.length > 0) {
console.log(`📚 Protocol Database Matches: ${protocolMatches.length}`);
}
// Convert protocol matches to DeviceMatch objects
for (const proto of protocolMatches) {
// Calculate confidence based on timing accuracy
const shortError = Math.abs(shortPulse - proto.shortPulseUs) / proto.shortPulseUs;
const longError = Math.abs(longPulse - proto.longPulseUs) / proto.longPulseUs;
const avgError = (shortError + longError) / 2;
const timingConfidence = Math.max(0, 1 - avgError);
// Frequency match bonus
const freqMatch = proto.matchesFrequency(metadata.frequency);
const freqBonus = freqMatch ? 0.1 : 0;
const confidence = Math.min(1.0, timingConfidence + freqBonus);
// Decode bit pattern
const bitPattern = decodeToBits(metadata.raw_data, shortPulse, longPulse);
matches.push(new DeviceMatch({
deviceName: proto.name,
manufacturer: proto.manufacturer || proto.category,
confidence: confidence,
matchMethod: 'timing_pattern',
matchDetails: {
protocol_name: proto.name,
category: proto.category,
short_pulse_us: shortPulse,
long_pulse_us: longPulse,
expected_short: proto.shortPulseUs,
expected_long: proto.longPulseUs,
timing_error: `${(avgError * 100).toFixed(2)}%`,
frequency_match: freqMatch,
bit_pattern: bitPattern,
bit_count: bitPattern.length
}
}));
}
} catch (error) {
if (this.debug) {
console.error('⚠️ Timing pattern analysis failed:', error);
}
}
return matches;
}
/**
* Strategy 2: Statistical Fingerprint Matching
* Extracts statistical characteristics and compares against protocol library
*
* @private
*/
_matchFingerprint(metadata) {
const matches = [];
try {
// Extract statistical fingerprint
const fingerprint = extractFingerprint(metadata.raw_data);
if (this.debug) {
console.log(`🔬 Fingerprint: ${fingerprint.toString()}`);
}
// Compare against all protocols
for (const proto of this.protocolDb.getAll()) {
const comparison = compareToProtocol(fingerprint, {
shortPulseUs: proto.shortPulseUs,
longPulseUs: proto.longPulseUs,
typicalPulseCount: proto.typicalPulseCount
});
// Only include if confidence is reasonable
if (comparison.overall >= 0.3) {
matches.push(new DeviceMatch({
deviceName: proto.name,
manufacturer: proto.manufacturer || proto.category,
confidence: comparison.overall,
matchMethod: 'fingerprint',
matchDetails: {
protocol_name: proto.name,
category: proto.category,
pulse_similarity: comparison.pulseSimilarity.toFixed(3),
count_similarity: comparison.countSimilarity.toFixed(3),
pulse_error: comparison.pulseError,
count_error: comparison.countError,
mean_pulse_width: fingerprint.meanPulseWidth.toFixed(1),
duty_cycle: `${(fingerprint.dutyCycle * 100).toFixed(1)}%`,
pulse_count: fingerprint.pulseCount
}
}));
}
}
} catch (error) {
if (this.debug) {
console.error('⚠️ Fingerprint matching failed:', error);
}
}
return matches;
}
/**
* Strategy 3: Heuristic Classification (Fallback)
* Uses signal characteristics to guess device type when no protocol match
*
* @private
*/
_classifyByHeuristics(metadata) {
const matches = [];
try {
const fingerprint = extractFingerprint(metadata.raw_data);
const classification = classifySignal(fingerprint);
if (classification.confidence >= 0.3) {
matches.push(new DeviceMatch({
deviceName: classification.type,
manufacturer: 'Unknown',
confidence: classification.confidence,
matchMethod: 'heuristic',
matchDetails: {
classification: classification.type,
reason: classification.reason,
mean_pulse_width: fingerprint.meanPulseWidth.toFixed(1),
pulse_count: fingerprint.pulseCount,
duty_cycle: `${(fingerprint.dutyCycle * 100).toFixed(1)}%`
}
}));
}
} catch (error) {
if (this.debug) {
console.error('⚠️ Heuristic classification failed:', error);
}
}
return matches;
}
/**
* Deduplicate and rank matches by confidence
*
* @private
* @param {DeviceMatch[]} matches - Array of device matches
* @returns {DeviceMatch[]} Sorted and deduplicated matches
*/
_rankMatches(matches) {
// Group by device name + manufacturer
const grouped = {};
for (const match of matches) {
const key = `${match.manufacturer}::${match.deviceName}`;
if (!grouped[key]) {
grouped[key] = match;
} else {
// Keep match with higher confidence
if (match.confidence > grouped[key].confidence) {
grouped[key] = match;
}
}
}
// Convert back to array and sort by confidence
const deduplicated = Object.values(grouped);
deduplicated.sort((a, b) => b.confidence - a.confidence);
return deduplicated;
}
/**
* Analyze pulse train for debugging
* Returns detailed timing information
*
* @param {number[]} pulses - Raw pulse data
* @returns {Object} Detailed analysis
*/
analyze(pulses) {
const analysis = analyzePulseTrain(pulses);
const fingerprint = extractFingerprint(pulses);
const validation = validatePulseData(pulses);
const snr = estimateSNR(pulses);
return {
timing: analysis,
fingerprint: fingerprint.toObject(),
validation,
snr,
quality: snr > 0.8 ? 'excellent' : snr > 0.6 ? 'good' : snr > 0.4 ? 'fair' : 'poor'
};
}
/**
* Get decoder statistics
* @returns {Object} Decoder stats
*/
getStats() {
return {
...this.stats,
successRate: this.stats.totalDecodes > 0
? (this.stats.successfulDecodes / this.stats.totalDecodes * 100).toFixed(1) + '%'
: '0%'
};
}
/**
* Reset statistics
*/
resetStats() {
this.stats = {
totalDecodes: 0,
successfulDecodes: 0,
failedDecodes: 0,
averageConfidence: 0
};
}
}
/**
* Convenience function to decode a .sub file metadata object
*
* @param {Object} metadata - Parsed .sub file
* @param {Object} options - Decoder options
* @returns {DeviceMatch[]} Device matches
*/
export function decode(metadata, options = {}) {
const decoder = new PatternDecoder(options);
return decoder.decode(metadata);
}
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/**
* GigLez RF Protocol Database
* JavaScript port of Python protocol_database.py
*
* Contains timing signatures for 18 known RF protocols
* @module protocol-database
*/
export class ProtocolSignature {
constructor({
name,
category,
manufacturer = null,
model = null,
frequency = 433920000,
frequencyTolerance = 100000,
shortPulseUs = 500,
longPulseUs = 1000,
timingTolerance = 0.2,
preamblePattern = null,
syncPattern = null,
minBits = 24,
maxBits = 64,
typicalPulseCount = 100,
minConfidence = 0.6
}) {
this.name = name;
this.category = category;
this.manufacturer = manufacturer;
this.model = model;
this.frequency = frequency;
this.frequencyTolerance = frequencyTolerance;
this.shortPulseUs = shortPulseUs;
this.longPulseUs = longPulseUs;
this.timingTolerance = timingTolerance;
this.preamblePattern = preamblePattern;
this.syncPattern = syncPattern;
this.minBits = minBits;
this.maxBits = maxBits;
this.typicalPulseCount = typicalPulseCount;
this.minConfidence = minConfidence;
}
/**
* Check if observed timing matches this protocol
* @param {number} shortUs - Observed short pulse width (microseconds)
* @param {number} longUs - Observed long pulse width (microseconds)
* @returns {boolean}
*/
matchesTiming(shortUs, longUs) {
const shortMin = this.shortPulseUs * (1 - this.timingTolerance);
const shortMax = this.shortPulseUs * (1 + this.timingTolerance);
const longMin = this.longPulseUs * (1 - this.timingTolerance);
const longMax = this.longPulseUs * (1 + this.timingTolerance);
return (shortMin <= shortUs && shortUs <= shortMax) &&
(longMin <= longUs && longUs <= longMax);
}
/**
* Check if frequency matches this protocol
* @param {number} freq - Observed frequency (Hz)
* @returns {boolean}
*/
matchesFrequency(freq) {
return Math.abs(freq - this.frequency) <= this.frequencyTolerance;
}
}
// Weather Sensor Protocols
export const WEATHER_SENSORS = [
new ProtocolSignature({
name: 'Oregon Scientific v2.1',
category: 'Weather Sensor',
manufacturer: 'Oregon Scientific',
shortPulseUs: 488,
longPulseUs: 976,
preamblePattern: '10101010101010101010101010101010', // 32-bit preamble
syncPattern: '1000',
minBits: 64,
maxBits: 128,
typicalPulseCount: 200
}),
new ProtocolSignature({
name: 'Oregon Scientific v3.0',
category: 'Weather Sensor',
manufacturer: 'Oregon Scientific',
shortPulseUs: 500,
longPulseUs: 1000,
preamblePattern: '101010101010101010101010101010101010101010101010', // 48-bit preamble
syncPattern: '1000',
minBits: 64,
maxBits: 128,
typicalPulseCount: 250
}),
new ProtocolSignature({
name: 'Acurite Tower Sensor',
category: 'Weather Sensor',
manufacturer: 'Acurite',
shortPulseUs: 220,
longPulseUs: 440,
syncPattern: '10',
minBits: 56,
maxBits: 64,
typicalPulseCount: 130
}),
new ProtocolSignature({
name: 'Acurite 5n1 Weather Station',
category: 'Weather Sensor',
manufacturer: 'Acurite',
shortPulseUs: 220,
longPulseUs: 440,
minBits: 64,
maxBits: 80,
typicalPulseCount: 160
}),
new ProtocolSignature({
name: 'LaCrosse TX141TH-Bv2',
category: 'Weather Sensor',
manufacturer: 'LaCrosse',
shortPulseUs: 500,
longPulseUs: 1000,
preamblePattern: '10101010', // 8-bit preamble
minBits: 40,
maxBits: 48,
typicalPulseCount: 100
}),
new ProtocolSignature({
name: 'Nexus Temperature/Humidity',
category: 'Weather Sensor',
manufacturer: 'Nexus',
shortPulseUs: 500,
longPulseUs: 1000,
preamblePattern: '11111111', // 8-bit preamble
minBits: 36,
maxBits: 40,
typicalPulseCount: 90
}),
new ProtocolSignature({
name: 'Ambient Weather F007TH',
category: 'Weather Sensor',
manufacturer: 'Ambient Weather',
shortPulseUs: 500,
longPulseUs: 1000,
minBits: 64,
maxBits: 72,
typicalPulseCount: 150
})
];
// Garage Door Opener Protocols
export const GARAGE_DOOR_OPENERS = [
new ProtocolSignature({
name: 'Princeton',
category: 'Garage Door Opener',
manufacturer: null,
shortPulseUs: 400,
longPulseUs: 1200,
preamblePattern: '1111', // 4-bit preamble
syncPattern: '10',
minBits: 24,
maxBits: 32,
typicalPulseCount: 60
}),
new ProtocolSignature({
name: 'Chamberlain/LiftMaster',
category: 'Garage Door Opener',
manufacturer: 'Chamberlain',
shortPulseUs: 300,
longPulseUs: 900,
minBits: 32,
maxBits: 40,
typicalPulseCount: 80,
frequency: 315000000 // 315 MHz
}),
new ProtocolSignature({
name: 'Linear MegaCode',
category: 'Garage Door Opener',
manufacturer: 'Linear',
shortPulseUs: 250,
longPulseUs: 500,
minBits: 32,
maxBits: 32,
typicalPulseCount: 70,
frequency: 318000000 // 318 MHz
})
];
// Doorbell Protocols
export const DOORBELLS = [
new ProtocolSignature({
name: 'Honeywell Doorbell',
category: 'Doorbell',
manufacturer: 'Honeywell',
shortPulseUs: 175,
longPulseUs: 340,
minBits: 48,
maxBits: 48,
typicalPulseCount: 100
})
];
// TPMS Protocols
export const TIRE_PRESSURE = [
new ProtocolSignature({
name: 'Toyota TPMS',
category: 'TPMS',
manufacturer: 'Toyota',
shortPulseUs: 50,
longPulseUs: 100,
minBits: 64,
maxBits: 80,
typicalPulseCount: 160,
frequency: 315000000 // 315 MHz
}),
new ProtocolSignature({
name: 'Schrader TPMS',
category: 'TPMS',
manufacturer: 'Schrader',
shortPulseUs: 50,
longPulseUs: 100,
minBits: 64,
maxBits: 80,
typicalPulseCount: 160,
frequency: 433920000 // 433.92 MHz
})
];
// Security Sensor Protocols
export const SECURITY_SENSORS = [
new ProtocolSignature({
name: 'Magellan',
category: 'Security Sensor',
manufacturer: 'Paradox',
shortPulseUs: 250,
longPulseUs: 500,
minBits: 32,
maxBits: 48,
typicalPulseCount: 80,
frequency: 433920000
})
];
// Remote Control Protocols
export const REMOTE_CONTROLS = [
new ProtocolSignature({
name: 'PT2262',
category: 'Remote Control',
manufacturer: null,
shortPulseUs: 350,
longPulseUs: 1050,
preamblePattern: '1111', // 4-bit preamble
minBits: 24,
maxBits: 24,
typicalPulseCount: 50
}),
new ProtocolSignature({
name: 'PT2260',
category: 'Remote Control',
manufacturer: null,
shortPulseUs: 300,
longPulseUs: 900,
minBits: 24,
maxBits: 24,
typicalPulseCount: 50
}),
new ProtocolSignature({
name: 'EV1527',
category: 'Remote Control',
manufacturer: null,
shortPulseUs: 300,
longPulseUs: 900,
minBits: 24,
maxBits: 24,
typicalPulseCount: 50
}),
new ProtocolSignature({
name: 'HCS301',
category: 'Remote Control',
manufacturer: 'Microchip',
shortPulseUs: 400,
longPulseUs: 800,
minBits: 66,
maxBits: 66,
typicalPulseCount: 140
})
];
// Combined protocol list
export const ALL_PROTOCOLS = [
...WEATHER_SENSORS,
...GARAGE_DOOR_OPENERS,
...DOORBELLS,
...TIRE_PRESSURE,
...SECURITY_SENSORS,
...REMOTE_CONTROLS
];
/**
* Protocol Database class for querying and indexing protocols
*/
export class ProtocolDatabase {
constructor() {
this.protocols = ALL_PROTOCOLS;
this._byCategory = {};
this._byFrequency = {};
this._indexProtocols();
}
/**
* Build indexes for fast lookup
* @private
*/
_indexProtocols() {
for (const proto of this.protocols) {
// Index by category
if (!this._byCategory[proto.category]) {
this._byCategory[proto.category] = [];
}
this._byCategory[proto.category].push(proto);
// Index by frequency (rounded to MHz)
const freqMHz = Math.round(proto.frequency / 1_000_000);
if (!this._byFrequency[freqMHz]) {
this._byFrequency[freqMHz] = [];
}
this._byFrequency[freqMHz].push(proto);
}
}
/**
* Find protocols matching timing characteristics
* @param {number} shortUs - Short pulse width (microseconds)
* @param {number} longUs - Long pulse width (microseconds)
* @param {number} [frequency] - Optional frequency filter (Hz)
* @returns {ProtocolSignature[]}
*/
findByTiming(shortUs, longUs, frequency = null) {
let candidates = this.protocols;
if (frequency) {
const freqMHz = Math.round(frequency / 1_000_000);
candidates = this._byFrequency[freqMHz] || this.protocols;
}
const matches = [];
for (const proto of candidates) {
if (proto.matchesTiming(shortUs, longUs)) {
if (!frequency || proto.matchesFrequency(frequency)) {
matches.push(proto);
}
}
}
return matches;
}
/**
* Find protocols by category
* @param {string} category - Category name
* @returns {ProtocolSignature[]}
*/
findByCategory(category) {
return this._byCategory[category] || [];
}
/**
* Find protocols by frequency
* @param {number} frequency - Frequency in Hz
* @returns {ProtocolSignature[]}
*/
findByFrequency(frequency) {
const matches = [];
for (const proto of this.protocols) {
if (proto.matchesFrequency(frequency)) {
matches.push(proto);
}
}
return matches;
}
/**
* Get all protocols
* @returns {ProtocolSignature[]}
*/
getAll() {
return this.protocols;
}
/**
* Get database statistics
* @returns {Object}
*/
getStatistics() {
return {
totalProtocols: this.protocols.length,
categories: Object.keys(this._byCategory),
byCategory: Object.fromEntries(
Object.entries(this._byCategory).map(([cat, protos]) => [cat, protos.length])
),
frequencyBands: [...new Set(
this.protocols.map(p => Math.round(p.frequency / 1_000_000))
)].sort((a, b) => a - b)
};
}
}
// Export singleton instance
export const protocolDb = new ProtocolDatabase();
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/**
* GigLez Pulse Width Analysis using K-means clustering
* JavaScript port of Python pattern_decoder.py pulse analysis
*
* @module pulse-analyzer
*/
/**
* Simple K-means clustering for 1D data
* Used to identify SHORT and LONG pulse widths
*
* @param {number[]} data - Array of pulse widths
* @param {number} k - Number of clusters (default: 2 for SHORT/LONG)
* @param {number} maxIterations - Maximum iterations (default: 100)
* @returns {number[]} Array of cluster centers
*/
export function kMeans(data, k = 2, maxIterations = 100) {
if (data.length < k) {
return data.map(v => v);
}
// Initialize centroids using min and max values
const sorted = [...data].sort((a, b) => a - b);
let centroids = k === 2
? [sorted[0], sorted[sorted.length - 1]]
: Array.from({ length: k }, (_, i) =>
sorted[Math.floor((i / k) * sorted.length)]
);
for (let iter = 0; iter < maxIterations; iter++) {
// Assign points to nearest centroid
const clusters = Array.from({ length: k }, () => []);
for (const point of data) {
const distances = centroids.map(c => Math.abs(point - c));
const nearestIdx = distances.indexOf(Math.min(...distances));
clusters[nearestIdx].push(point);
}
// Update centroids (mean of each cluster)
const newCentroids = clusters.map(cluster => {
if (cluster.length === 0) return centroids[0]; // Handle empty cluster
return cluster.reduce((sum, val) => sum + val, 0) / cluster.length;
});
// Check convergence
const converged = centroids.every((c, i) =>
Math.abs(c - newCentroids[i]) < 1
);
centroids = newCentroids;
if (converged) break;
}
return centroids.sort((a, b) => a - b);
}
/**
* Identify SHORT and LONG pulse widths from pulse train
* Uses K-means clustering to automatically detect the two pulse durations
*
* @param {number[]} pulses - Raw pulse data (positive = HIGH, negative = LOW)
* @returns {Object} { shortPulse, longPulse, shortGap, longGap }
*/
export function identifyPulseWidths(pulses) {
// Separate HIGH pulses (positive) and LOW gaps (negative)
const highPulses = pulses.filter(p => p > 0).map(Math.abs);
const lowPulses = pulses.filter(p => p < 0).map(Math.abs);
// Cluster into SHORT/LONG
let shortPulse = 0, longPulse = 0;
if (highPulses.length >= 2) {
const [short, long] = kMeans(highPulses, 2);
shortPulse = short;
longPulse = long;
} else if (highPulses.length === 1) {
shortPulse = longPulse = highPulses[0];
}
let shortGap = 0, longGap = 0;
if (lowPulses.length >= 2) {
const [short, long] = kMeans(lowPulses, 2);
shortGap = short;
longGap = long;
} else if (lowPulses.length === 1) {
shortGap = longGap = lowPulses[0];
}
return { shortPulse, longPulse, shortGap, longGap };
}
/**
* Decode pulse train to binary string using PWM encoding
* SHORT pulse = 0, LONG pulse = 1
*
* @param {number[]} pulses - Raw pulse data
* @param {number} shortPulse - SHORT pulse width (microseconds)
* @param {number} longPulse - LONG pulse width (microseconds)
* @returns {string} Binary string (e.g., "101010110")
*/
export function decodeToBits(pulses, shortPulse, longPulse) {
const threshold = (shortPulse + longPulse) / 2;
const bits = [];
for (const pulse of pulses) {
if (pulse > 0) { // Only decode HIGH pulses
const duration = Math.abs(pulse);
bits.push(duration < threshold ? '0' : '1');
}
}
return bits.join('');
}
/**
* Analyze pulse train and extract timing information
* Returns comprehensive timing analysis for debugging
*
* @param {number[]} pulses - Raw pulse data
* @returns {Object} Timing analysis including pulse widths, counts, patterns
*/
export function analyzePulseTrain(pulses) {
const highPulses = pulses.filter(p => p > 0).map(Math.abs);
const lowPulses = pulses.filter(p => p < 0).map(Math.abs);
const { shortPulse, longPulse, shortGap, longGap } = identifyPulseWidths(pulses);
const bitPattern = decodeToBits(pulses, shortPulse, longPulse);
return {
// Pulse width identification
shortPulse,
longPulse,
shortGap,
longGap,
// Bit pattern
bitPattern,
bitCount: bitPattern.length,
// Counts
totalPulses: pulses.length,
highPulseCount: highPulses.length,
lowPulseCount: lowPulses.length,
// High pulse statistics
highPulseStats: {
min: Math.min(...highPulses),
max: Math.max(...highPulses),
mean: highPulses.reduce((a, b) => a + b, 0) / highPulses.length,
median: highPulses.sort((a, b) => a - b)[Math.floor(highPulses.length / 2)]
},
// Low pulse (gap) statistics
lowPulseStats: {
min: Math.min(...lowPulses),
max: Math.max(...lowPulses),
mean: lowPulses.reduce((a, b) => a + b, 0) / lowPulses.length,
median: lowPulses.sort((a, b) => a - b)[Math.floor(lowPulses.length / 2)]
}
};
}
/**
* Validate pulse data quality
* Checks for common issues in RF captures
*
* @param {number[]} pulses - Raw pulse data
* @returns {Object} { valid: boolean, issues: string[] }
*/
export function validatePulseData(pulses) {
const issues = [];
if (!pulses || pulses.length === 0) {
return { valid: false, issues: ['No pulse data provided'] };
}
if (pulses.length < 20) {
issues.push(`Very short capture (${pulses.length} pulses) - may not be decodable`);
}
const allPositive = pulses.every(p => p > 0);
const allNegative = pulses.every(p => p < 0);
if (allPositive || allNegative) {
issues.push('Pulse data is all positive or all negative - should alternate');
}
const highPulses = pulses.filter(p => p > 0).map(Math.abs);
const lowPulses = pulses.filter(p => p < 0).map(Math.abs);
if (highPulses.length < 5) {
issues.push('Too few HIGH pulses for reliable analysis');
}
if (lowPulses.length < 5) {
issues.push('Too few LOW pulses (gaps) for reliable analysis');
}
// Check for outliers (pulses > 100ms are suspicious)
const outliers = pulses.filter(p => Math.abs(p) > 100000);
if (outliers.length > 0) {
issues.push(`${outliers.length} suspiciously long pulses (>100ms) detected`);
}
return {
valid: issues.length === 0,
issues
};
}
/**
* Calculate Signal-to-Noise Ratio (SNR) estimate
* Based on pulse width consistency
*
* @param {number[]} pulses - Raw pulse data
* @returns {number} SNR estimate (0-1, higher is better)
*/
export function estimateSNR(pulses) {
const { shortPulse, longPulse } = identifyPulseWidths(pulses);
const highPulses = pulses.filter(p => p > 0).map(Math.abs);
if (highPulses.length < 10) return 0;
// Count how many pulses are close to SHORT or LONG
const threshold = (shortPulse + longPulse) / 2;
const shortTolerance = shortPulse * 0.3;
const longTolerance = longPulse * 0.3;
const consistentPulses = highPulses.filter(p => {
const nearShort = Math.abs(p - shortPulse) <= shortTolerance;
const nearLong = Math.abs(p - longPulse) <= longTolerance;
return nearShort || nearLong;
});
return consistentPulses.length / highPulses.length;
}
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/**
* Simple Node.js test for GigLez Pattern Decoder
*
* Run with: node static/js/decoder/test.js
*/
import { decode, parseSubFile, getVersion } from './index.js';
// Test .sub file content (RAW format)
const testSubFile = `Filetype: Flipper SubGhz RAW File
Version: 1
Frequency: 315000000
Preset: FuriHalSubGhzPresetOok650Async
Protocol: RAW
RAW_Data: 2980 -240 520 -980 520 -980 1000 -500 480 -1020 520 -980 1000 -500
`;
async function runTest() {
console.log('='.repeat(80));
console.log('GigLez Pattern Decoder - Node.js Test');
console.log('='.repeat(80));
console.log();
// Print version
const version = await getVersion();
console.log(`${version.name} v${version.version}`);
console.log(`Protocols: ${version.protocols}`);
console.log(`Features:`);
version.features.forEach(f => console.log(` - ${f}`));
console.log();
console.log('-'.repeat(80));
console.log('Test 1: Parse .sub file');
console.log('-'.repeat(80));
const metadata = parseSubFile(testSubFile);
console.log('Parsed metadata:');
console.log(` Frequency: ${metadata.frequency / 1e6} MHz`);
console.log(` Protocol: ${metadata.protocol}`);
console.log(` Preset: ${metadata.preset}`);
console.log(` Pulses: ${metadata.raw_data.length}`);
console.log(` Raw Data: ${metadata.raw_data.join(' ')}`);
console.log();
console.log('-'.repeat(80));
console.log('Test 2: Decode signal');
console.log('-'.repeat(80));
const matches = await decode(metadata, { debug: true, minConfidence: 0.3 });
console.log();
console.log(`Found ${matches.length} device matches:`);
console.log();
if (matches.length === 0) {
console.log(' ❌ No matches found');
} else {
matches.forEach((match, i) => {
console.log(` ${i + 1}. ${match.toString()}`);
console.log(` Method: ${match.matchMethod}`);
if (match.matchDetails) {
console.log(` Details:`);
Object.entries(match.matchDetails).forEach(([key, value]) => {
console.log(` - ${key}: ${value}`);
});
}
console.log();
});
}
console.log('-'.repeat(80));
console.log('Test 3: Protocol database query');
console.log('-'.repeat(80));
// Import protocol database directly
const { protocolDb } = await import('./protocol-database.js');
console.log(`Total protocols: ${protocolDb.getAll().length}`);
console.log();
const stats = protocolDb.getStatistics();
console.log('Categories:');
Object.entries(stats.byCategory).forEach(([cat, count]) => {
console.log(` - ${cat}: ${count} protocols`);
});
console.log();
console.log('Frequency bands:');
stats.frequencyBands.forEach(freq => {
console.log(` - ${freq} MHz`);
});
console.log();
console.log('-'.repeat(80));
console.log('Test 4: Pulse analysis');
console.log('-'.repeat(80));
const { analyzePulseTrain, extractFingerprint } = await import('./pulse-analyzer.js');
const analysis = analyzePulseTrain(metadata.raw_data);
console.log('Timing Analysis:');
console.log(` Short Pulse: ${analysis.shortPulse.toFixed(1)} μs`);
console.log(` Long Pulse: ${analysis.longPulse.toFixed(1)} μs`);
console.log(` Bit Pattern: ${analysis.bitPattern}`);
console.log(` Bit Count: ${analysis.bitCount}`);
console.log();
const { extractFingerprint: fpExtract } = await import('./fingerprint.js');
const fingerprint = fpExtract(metadata.raw_data);
console.log('Statistical Fingerprint:');
console.log(` ${fingerprint.toString()}`);
console.log(` Duty Cycle: ${(fingerprint.dutyCycle * 100).toFixed(1)}%`);
console.log();
console.log('='.repeat(80));
console.log('✅ All tests completed!');
console.log('='.repeat(80));
}
runTest().catch(err => {
console.error('❌ Test failed:', err);
process.exit(1);
});