simple_lowpass.py

import matplotlib.pyplot as plt
import numpy as np


def normalize_freq_coeff(coeff):
  freqs = np.fft.fftfreq(coeff.shape[-1], d=1 / coeff.shape[-1])
  scale = (1 / (np.abs(freqs) + 1))
  return coeff * scale


def eq(signal):
  X = []
  for i, val in enumerate(signal):
    if i > 0:
      X.append(val + signal[i - 1])
    else:
      X.append(val)
  return np.array(X)


coeffs = np.random.normal(size=[100]) + np.random.normal(size=[100]) * 1j
norm = normalize_freq_coeff(coeffs)
signal = np.fft.ifft(norm).real
signal = np.tile(signal, 6)
eq_signal = eq(signal)
plt.plot(signal)
plt.plot(eq_signal)
plt.gca().set_ylim([-0.1, 0.1])
plt.show()