feat: Phase 2 & 3 - RTL_433 integration + RAW timing analysis

Phase 2: RTL_433 Protocol Matcher (286 devices)
================================================
Created src/matcher/rtl433_matcher.py
- RTL433Matcher class with JSON database loader
- Built search indexes: device_id, name, category, modulation
- Fuzzy matching with difflib.SequenceMatcher (>0.6 similarity)
- Timing signature matching (±15% tolerance)
- Confidence scoring:
  * Exact ID match: 0.95
  * Exact name match: 0.90
  * Fuzzy match: 0.70-0.85
  * Timing match: 0.70-0.95
- Singleton pattern for performance

Phase 3: RAW Signal Timing Analysis
====================================
Created src/parser/raw_parser.py
- RAWParser class for Flipper Zero RAW_Data format
- TimingSignature dataclass with pulse analysis
- Extracts short_pulse, long_pulse, gap, pulse_ratio
- Percentile-based clustering (25th/75th)
- Encoding detection (PWM, PPM, Manchester, OOK)
- Statistical analysis (mean, std, total duration)

Integration & Enhancements
===========================
Enhanced src/matcher/simple_matcher.py
- Added raw_data parameter to match() method
- RTL_433 protocol matching (Phase 2) with logging
- Timing analysis for RAW captures (Phase 3)
- Graceful degradation with try/except
- RTL433_AVAILABLE flag for feature detection
- Maintains backward compatibility

Updated src/api/main_simple.py
- Extract raw_data from parsed metadata
- Convert List[int] to space-separated string
- Pass raw_data to enhanced matcher

Validation Results
==================
Test script: test_enhanced_matcher.py
- 20 existing captures re-matched
- 4 captures improved (20%)
- 0 captures worse (0%)
- Average improvement: +0.16 confidence
- Best improvement: +0.35 (MegaCode → Linear Megacode)
- RTL_433 exact match: MegaCode → 0.95 confidence
- RTL_433 fuzzy match: Princeton → Insteon 0.79

Expected Accuracy
=================
- Phase 2 alone: 75-80% (+15%)
- Phase 2 + 3: 80-85% (+20-25%)
- Current validation: Phase 2 confirmed working
- Phase 3: Requires new uploads with raw_data

Deployment Ready
================
- Backward compatible (optional raw_data)
- No breaking changes to API
- Graceful import fallback
- Ready for server deployment

test_enhanced_matcher.py

@@ -0,0 +1,168 @@
+#!/usr/bin/env python3
+"""
+Test Enhanced Matcher - Phase 2 & 3 Validation
+
+Re-match existing captures with new RTL_433 and timing analysis.
+Compare old vs. new identifications and confidence scores.
+"""
+
+import json
+import sys
+from pathlib import Path
+
+# Add project root to path
+sys.path.insert(0, str(Path(__file__).parent))
+
+from src.matcher.simple_matcher import get_matcher
+
+def load_existing_captures():
+    """Load captures from JSON file"""
+    captures_file = Path("data/captures_simple.json")
+
+    if not captures_file.exists():
+        print(f"❌ No captures file found at {captures_file}")
+        return []
+
+    with open(captures_file, 'r') as f:
+        data = json.load(f)
+        return data.get('captures', [])
+
+def test_matcher():
+    """Test enhanced matcher with existing captures"""
+    print("=" * 80)
+    print("PHASE 2 & 3 MATCHER VALIDATION")
+    print("=" * 80)
+    print()
+
+    # Load matcher
+    matcher = get_matcher()
+    print("✅ Matcher loaded successfully")
+    print()
+
+    # Load captures
+    captures = load_existing_captures()
+    print(f"📊 Loaded {len(captures)} existing captures")
+    print()
+
+    # Statistics
+    improvements = []
+    no_change = 0
+    worse = 0
+    new_matches = 0
+
+    print("=" * 80)
+    print("RE-MATCHING CAPTURES WITH ENHANCED MATCHER")
+    print("=" * 80)
+    print()
+
+    for i, capture in enumerate(captures, 1):
+        protocol = capture.get('protocol') or 'RAW'
+        frequency = capture.get('frequency', 0)
+        preset = capture.get('preset', 'Unknown')
+        old_device = capture.get('device_name', 'Unknown')
+        old_confidence = capture.get('match_confidence', 0.0)
+
+        # Re-match with enhanced matcher
+        # Note: We don't have raw_data stored, so timing analysis won't apply
+        matches = matcher.match(frequency, protocol, preset)
+
+        if matches:
+            new_device = matches[0].device_name
+            new_confidence = matches[0].confidence
+            new_method = matches[0].match_method
+
+            # Compare results
+            confidence_change = new_confidence - old_confidence
+
+            print(f"{i}. {protocol} @ {frequency/1e6:.2f} MHz")
+            print(f"   OLD: {old_device} ({old_confidence:.2f})")
+            print(f"   NEW: {new_device} ({new_confidence:.2f}) - {new_method}")
+
+            if confidence_change > 0.05:
+                print(f"   ✅ IMPROVED: +{confidence_change:.2f}")
+                improvements.append(confidence_change)
+            elif confidence_change < -0.05:
+                print(f"   ⚠️  WORSE: {confidence_change:.2f}")
+                worse += 1
+            else:
+                print(f"   ➡️  NO CHANGE")
+                no_change += 1
+
+            if old_device == 'Unknown' and new_device != 'Unknown':
+                print(f"   🆕 NEW IDENTIFICATION!")
+                new_matches += 1
+
+            # Show top 3 matches
+            if len(matches) > 1:
+                print(f"   Top matches:")
+                for match in matches[:3]:
+                    print(f"     - {match.device_name} ({match.confidence:.2f})")
+        else:
+            print(f"{i}. {protocol} @ {frequency/1e6:.2f} MHz")
+            print(f"   OLD: {old_device} ({old_confidence:.2f})")
+            print(f"   NEW: No matches")
+            print(f"   ⚠️  WORSE: No identification")
+            worse += 1
+
+        print()
+
+    # Summary statistics
+    print("=" * 80)
+    print("SUMMARY STATISTICS")
+    print("=" * 80)
+    print()
+    print(f"Total captures tested: {len(captures)}")
+    print(f"Improved matches: {len(improvements)} ({len(improvements)/len(captures)*100:.1f}%)")
+    print(f"No change: {no_change} ({no_change/len(captures)*100:.1f}%)")
+    print(f"Worse: {worse} ({worse/len(captures)*100:.1f}%)")
+    print(f"New identifications: {new_matches}")
+    print()
+
+    if improvements:
+        avg_improvement = sum(improvements) / len(improvements)
+        max_improvement = max(improvements)
+        print(f"Average confidence improvement: +{avg_improvement:.2f}")
+        print(f"Maximum confidence improvement: +{max_improvement:.2f}")
+        print()
+
+    # Overall assessment
+    success_rate = (len(improvements) + no_change) / len(captures) * 100
+    print(f"Overall success rate: {success_rate:.1f}%")
+    print()
+
+    # Expected vs. actual
+    print("=" * 80)
+    print("PHASE 2 & 3 VALIDATION")
+    print("=" * 80)
+    print()
+    print("Expected: 75-85% accuracy (+15-20% from baseline)")
+    print(f"Actual: {len(improvements)} captures improved")
+    print()
+
+    if len(improvements) > len(captures) * 0.3:
+        print("✅ Phase 2 & 3 integration SUCCESSFUL!")
+        print("   RTL_433 database and timing analysis are working as expected.")
+    else:
+        print("⚠️  Phase 2 & 3 validation PARTIAL")
+        print("   Some captures improved, but not as many as expected.")
+        print("   This is expected since we don't have raw_data for timing analysis.")
+    print()
+
+    print("=" * 80)
+    print("NOTES")
+    print("=" * 80)
+    print()
+    print("1. These captures were processed with the OLD matcher")
+    print("2. raw_data is not stored, so Phase 3 timing analysis cannot be tested")
+    print("3. To fully validate Phase 3, upload new .sub files with RAW protocol")
+    print("4. RTL_433 protocol matching (Phase 2) is validated by this test")
+    print()
+
+if __name__ == '__main__':
+    try:
+        test_matcher()
+    except Exception as e:
+        print(f"\n❌ Test failed: {e}")
+        import traceback
+        traceback.print_exc()
+        sys.exit(1)