docs: def cid_ce(x, normalize):
      """
      This function calculator is an estimate for a time series complexity [1] (A more complex time series has more peaks,
      valleys etc.). It calculates the value of
  
      .. math::
  
          \\sqrt{ \\sum_{i=0}^{n-2lag} ( x_{i} - x_{i+1})^2 }
  
      .. rubric:: References
  
      |  [1] Batista, Gustavo EAPA, et al (2014).
      |  CID: an efficient complexity-invariant distance for time series.
      |  Data Mining and Knowledge Discovery 28.3 (2014): 634-669.
  
      :param x: the time series to calculate the feature of
      :type x: numpy.ndarray
      :param normalize: should the time series be z-transformed?
      :type normalize: bool
  
      :return: the value of this feature
      :return type: float
      """
      if not isinstance(x, (np.ndarray, pd.Series)):
          x = np.asarray(x)
      if normalize:
          s = np.std(x)
          if s!=0:
              x = (x - np.mean(x))/s
          else:
              return 0.0
  
      x = np.diff(x)
      return np.sqrt(np.dot(x, x))