Cleanup part one

help_scripts/sound.py

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+import numpy as np
+import soundfile as sf
+from scipy.signal import lfilter, fftconvolve
+
+# Global Parameters
+sample_rate = 44100
+duration_seconds = 30
+samples = duration_seconds * sample_rate
+t = np.linspace(0, duration_seconds, samples, endpoint=False)
+
+# === 1. Aggressive White Noise + Reverb ===
+def aggressive_white_noise():
+    noise = np.random.normal(0, 0.07, samples)
+
+    # High-pass filter
+    b = [0.95, -0.95]
+    a = [1, -0.85]
+    filtered_noise = lfilter(b, a, noise)
+
+    # Reverb via impulse response (short decaying tail)
+    impulse_response = np.exp(-np.linspace(0, 1.5, int(0.3 * sample_rate)))
+    impulse_response = impulse_response * np.random.uniform(0.8, 1.2, impulse_response.shape)
+    reverb_noise = fftconvolve(filtered_noise, impulse_response, mode='full')[:samples]
+
+    return reverb_noise
+
+white_noise = aggressive_white_noise()
+
+# === 3. Metallic Sonar Ping with Echo ===
+def generate_sonar_ping(start_time, freq=5000, ping_duration=0.82):
+    ping_t = np.linspace(0, ping_duration, int(sample_rate * ping_duration), endpoint=False)
+
+    # FM modulation for metallic texture
+    mod_freq = 1000 # Modulating frequency
+    fm_wave = np.sin(2 * np.pi * freq * ping_t + 5 * np.sin(2 * np.pi * mod_freq * ping_t))
+
+    envelope = np.exp(-8 * ping_t)
+    ping = fm_wave * envelope * 0.6
+
+    mod_freq = 4000 # Modulating frequency
+    fm_wave = np.sin(2 * np.pi * freq * ping_t + 5 * np.sin(2 * np.pi * mod_freq * ping_t))
+
+    envelope = np.exp(-8 * ping_t)
+    ping = fm_wave * envelope * 0.9
+
+    mod_freq = 7000 # Modulating frequency
+    fm_wave = np.sin(2 * np.pi * freq * ping_t + 5 * np.sin(2 * np.pi * mod_freq * ping_t))
+
+    envelope = np.exp(-8 * ping_t)
+    ping = fm_wave * envelope * 0.5
+
+    # Add echo (delay)
+    echo_delay = int(0.01 * sample_rate)
+    echo = np.pad(ping * 0.1, (echo_delay, 0), 'constant')[:len(ping)]
+    ping = ping + echo
+    echo_delay = int(0.06 * sample_rate)
+    echo = np.pad(ping * 0.1, (echo_delay, 0), 'constant')[:len(ping)]
+    ping = ping + echo
+    echo_delay = int(0.06 * sample_rate)
+    echo = np.pad(ping * 0.1, (echo_delay, 0), 'constant')[:len(ping)]
+    ping = ping + echo
+    echo_delay = int(0.1 * sample_rate)
+    echo = np.pad(ping * 0.1, (echo_delay, 0), 'constant')[:len(ping)]
+    ping = ping + echo
+    echo_delay = int(0.2 * sample_rate)
+    echo = np.pad(ping * 0.1, (echo_delay, 0), 'constant')[:len(ping)]
+    ping = ping + echo
+
+
+
+
+    sonar = np.zeros(samples)
+    start_sample = int(start_time * sample_rate)
+    end_sample = start_sample + len(ping)
+    if end_sample <= samples:
+        sonar[start_sample:end_sample] = ping
+    return sonar
+
+sonar_total = np.zeros(samples)
+np.random.seed(42)
+ping_times = np.cumsum(np.random.uniform(0.5, 3.0, size=12))
+ping_times = ping_times[ping_times < duration_seconds]
+for pt in ping_times:
+    sonar_total += generate_sonar_ping(pt)
+
+# === 4. Combine & Normalize ===
+final_mix = 0.2*white_noise  + 3.0*sonar_total
+final_mix = final_mix / np.max(np.abs(final_mix))
+
+# === 5. Export ===
+file_path = 'test.wav'
+sf.write(file_path, final_mix, sample_rate)
+print(f"✅ Saved to: {file_path}")