From 0c423f30abf401d321cbccc0b1595dbb0f4c6596 Mon Sep 17 00:00:00 2001
From: Chris Frankland-Wright <christopherjfrankland@googlemail.com>
Date: Tue, 24 Jun 2025 21:55:26 +0100
Subject: [PATCH] additional diagnostic

---
 ltc_probe.py | 43 ++++++++++++++++++++++++++++++++-----------
 1 file changed, 32 insertions(+), 11 deletions(-)

diff --git a/ltc_probe.py b/ltc_probe.py
index b1c6e77..9dded3c 100644
--- a/ltc_probe.py
+++ b/ltc_probe.py
@@ -2,8 +2,8 @@
 
 """
 ltc_probe.py
-Improved LTC-like signal probe — detects pulse duration patterns
-consistent with bi-phase mark code used in SMPTE LTC.
+Advanced LTC-like signal probe using pulse duration clustering
+for reliable short/long classification — works even with imbalanced timecodes.
 """
 
 import numpy as np
@@ -12,38 +12,59 @@ import sounddevice as sd
 DURATION = 1.0  # seconds
 SAMPLERATE = 48000
 CHANNELS = 1
-MIN_EDGES = 1000  # sanity threshold
+MIN_EDGES = 1000
 
 def detect_rising_edges(signal):
     above_zero = signal > 0
     edges = np.where(np.logical_and(~above_zero[:-1], above_zero[1:]))[0]
     return edges
 
+def cluster_durations(durations):
+    if len(durations) < 2:
+        return None, None
+
+    # Use 2-means clustering (basic method)
+    durations = np.array(durations)
+    mean1, mean2 = np.min(durations), np.max(durations)
+    
+    for _ in range(10):  # converge in a few iterations
+        group1 = durations[np.abs(durations - mean1) < np.abs(durations - mean2)]
+        group2 = durations[np.abs(durations - mean1) >= np.abs(durations - mean2)]
+        if len(group1) == 0 or len(group2) == 0:
+            break
+        mean1 = np.mean(group1)
+        mean2 = np.mean(group2)
+    
+    short = group1 if mean1 < mean2 else group2
+    long = group2 if mean1 < mean2 else group1
+    return short, long
+
 def analyze_pulse_durations(edges, samplerate):
     durations = np.diff(edges) / samplerate
     if len(durations) == 0:
         return None
 
-    short_pulse_threshold = np.median(durations) * 1.5
-    short = durations[durations <= short_pulse_threshold]
-    long = durations[durations > short_pulse_threshold]
+    short, long = cluster_durations(durations)
+    if short is None or long is None:
+        return None
 
+    total = len(durations)
     return {
-        "count": len(durations),
+        "count": total,
         "avg_width_ms": np.mean(durations) * 1000,
         "short_pulses": len(short),
         "long_pulses": len(long),
-        "short_pct": (len(short) / len(durations)) * 100,
-        "long_pct": (len(long) / len(durations)) * 100
+        "short_pct": (len(short) / total) * 100,
+        "long_pct": (len(long) / total) * 100
     }
 
 def verdict(pulse_data):
     if pulse_data is None or pulse_data["count"] < MIN_EDGES:
         return "❌ No signal or not enough pulses"
-    elif 20 <= pulse_data["short_pct"] <= 80:
+    elif 10 <= pulse_data["short_pct"] <= 90:
         return f"✅ LTC-like bi-phase signal detected ({pulse_data['count']} pulses)"
     else:
-        return f"⚠️ Inconsistent signal — may be non-LTC or noisy"
+        return f"⚠️ Pulse imbalance suggests non-LTC or noisy signal"
 
 def main():
     print("🔍 Capturing 1 second of audio for LTC probing...")