GPT SECOND Script

import numpy as np
import matplotlib.pyplot as plt
import wave

# Load WAV file
filename = "original.wav"

with wave.open(filename, 'rb') as wf:
    sample_rate = wf.getframerate()
    n_frames = wf.getnframes()
    audio = wf.readframes(n_frames)

# Convert to numpy array
data = np.frombuffer(audio, dtype=np.int16)

# If stereo, take one channel
if wf.getnchannels() == 2:
    data = data[::2]

# Parameters
window_size = 4096
hop_size = 2048

targets = [1492, 1987, 2255]
time_axis = []
band_energy = {freq: [] for freq in targets}

# Sliding FFT
for start in range(0, len(data) - window_size, hop_size):
    window = data[start:start + window_size]
    window = window * np.hanning(window_size)
    spectrum = np.fft.rfft(window)
    freqs = np.fft.rfftfreq(window_size, 1 / sample_rate)

    time_axis.append(start / sample_rate)

    for target in targets:
        idx = np.argmin(np.abs(freqs - target))
        band_energy[target].append(np.abs(spectrum[idx]))

# Plot
plt.figure(figsize=(12, 8))

for target in targets:
    plt.plot(time_axis, band_energy[target], label=f"{target} Hz")

plt.xlabel("Time (seconds)")
plt.ylabel("Amplitude")
plt.title("Band Energy Over Time")
plt.legend()
plt.show()