acf.py

import numpy as np
import statsmodels.tsa.stattools as st
import scipy.io.wavfile as wav
import matplotlib.pyplot as plt


def my_acf(sample: np.ndarray, m: int) -> np.float32:
    avg = np.mean(sample)
    x1 = sample[:len(sample) - m]
    x2 = sample[m:]
    res = np.sum((x1 - avg) * (x2 - avg))
    return res / ((len(sample - m) * np.var(sample)))


if __name__ == '__main__':
    fs, x = wav.read('record.wav')
    x = x.astype(np.float32) / max(abs(min(x)), abs(max(x)))
    my_r = my_acf(x, 5)
    r = st.acf(x, True, nlags=1500)
    print(my_r, r)
    time = np.linspace(0, len(r), len(r))
    plt.xticks(np.arange(0, len(r), step=100))
    plt.xlabel("Отсчеты")
    plt.ylabel("АКФ")
    plt.plot(r)
    plt.grid(True)
    start_point = 100
    max_ind = np.argmax(r[start_point:]) + start_point
    f_tone = fs / max_ind
    print(f'частота основного тона: {f_tone}')
    plt.show()