code: def acovf_fft(x, demean=True):
      """autocovariance function with call to fftconvolve, biased
  
      Parameters
      ----------
      x : array_like
          timeseries, signal
      demean : bool
          If true, then demean time series
  
      Returns
      -------
      acovf : ndarray
          autocovariance for data, same length as x
  
      might work for nd in parallel with time along axis 0
  
      """
      from scipy import signal
  
      x = np.asarray(x)
  
      if demean:
          x = x - x.mean()
  
      signal.fftconvolve(x, x[::-1])[
          len(x) - 1 : len(x) + 10
      ] / x.shape[0]
  
label_desc: Use image node_id 1 for calling a global function with example usage: acovf_fft(x, demean) without return types