code: def log_power_spectrum(frames, fft_points=512, normalize=True):
      
      power_spec = power_spectrum(frames, fft_points)
      power_spec[power_spec <= 1e-20] = 1e-20
      log_power_spec = 10 * np.log10(power_spec)
      if normalize:
          return log_power_spec - np.max(log_power_spec)
      else:
          return log_power_spec
docs: Log power spectrum of each frame in frames.
  
      Args:
          frames (array): The frame array in which each row is a frame.
          fft_points (int): The length of FFT. If fft_length is greater than
              frame_len, the frames will be zero-padded.
          normalize (bool): If normalize=True, the log power spectrum
              will be normalized.
  
      Returns:
             array: The power spectrum - If frames is an
             num_frames x sample_per_frame matrix, output will be
             num_frames x fft_length.