Delete ltc_probe.py

ltc_probe.py

@@ -1,91 +0,0 @@
-#!/usr/bin/env python3
-
-"""
-ltc_probe.py
-Advanced LTC-like signal probe using pulse duration clustering
-for reliable short/long classification — works even with imbalanced timecodes.
-"""
-
-import numpy as np
-import sounddevice as sd
-
-DURATION = 1.0  # seconds
-SAMPLERATE = 48000
-CHANNELS = 1
-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, long = cluster_durations(durations)
-    if short is None or long is None:
-        return None
-
-    total = len(durations)
-    return {
-        "count": total,
-        "avg_width_ms": np.mean(durations) * 1000,
-        "short_pulses": len(short),
-        "long_pulses": len(long),
-        "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 10 <= pulse_data["short_pct"] <= 90:
-        return f"✅ LTC-like bi-phase signal detected ({pulse_data['count']} pulses)"
-    else:
-        return f"⚠️ Pulse imbalance suggests non-LTC or noisy signal"
-
-def main():
-    print("🔍 Capturing 1 second of audio for LTC probing...")
-    audio = sd.rec(int(DURATION * SAMPLERATE), samplerate=SAMPLERATE, channels=CHANNELS, dtype='float32')
-    sd.wait()
-
-    signal = audio.flatten()
-    edges = detect_rising_edges(signal)
-    pulse_data = analyze_pulse_durations(edges, SAMPLERATE)
-
-    print(f"\n📊 Pulse Analysis:")
-    if pulse_data:
-        print(f"  Total pulses:      {pulse_data['count']}")
-        print(f"  Avg pulse width:   {pulse_data['avg_width_ms']:.2f} ms")
-        print(f"  Short pulses:      {pulse_data['short_pulses']} ({pulse_data['short_pct']:.1f}%)")
-        print(f"  Long pulses:       {pulse_data['long_pulses']} ({pulse_data['long_pct']:.1f}%)")
-    else:
-        print("  Not enough data to analyze.")
-
-    print("\n🧭 Verdict:")
-    print(" ", verdict(pulse_data))
-
-if __name__ == "__main__":
-    main()