dtft.py

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


def my_dtft(sample: np.ndarray, f: np.ndarray, fs: int) -> np.ndarray:
    ns = np.arange(0, sample.size, 1)
    f_tmp = f
    exp_power = (ns * (-1j) * 2 * np.pi) / fs
    exp_power = np.outer(f_tmp, exp_power)
    e_arr = np.exp(exp_power)
    res = np.dot(e_arr, sample)
    return np.abs(res)


if __name__ == '__main__':
    fs, x = wav.read('record.wav')
    x = x.astype(np.float32)
    start_point = 100
    frequencies = np.arange(40, 501, 1)
    spec = my_dtft(x, frequencies, fs)
    max_ind = np.argmax(spec[:start_point]) + start_point
    f_tone = frequencies[max_ind]
    print(f'Основной тон {f_tone}')
    plt.plot(frequencies, spec, label="Спектр сигнала")
    plt.xlabel("Частота")
    plt.ylabel("Амплитуда")
    plt.grid(True)
    plt.show()