code: def noelle_2(h1, h2):  # 26 us @array, 52 us @list \w 100 bins
      r"""
      Extension of `fidelity_based` proposed by [1]_.
  
      .. math::
  
          d_{\sqrt{1-F}}(H, H') = \sqrt{1 - d_{F}(H, H')}
  
      See `fidelity_based` for the definition of :math:`d_{F}(H, H')`.
  
      *Attributes:*
  
      - metric
  
      *Attributes for normalized histograms:*
  
      - :math:`d(H, H')\in[0, 1]`
      - :math:`d(H, H) = 0`
      - :math:`d(H, H') = d(H', H)`
  
      *Attributes for not-normalized histograms:*
  
      - not applicable
  
      *Attributes for not-equal histograms:*
  
      - not applicable
  
      Parameters
      ----------
      h1 : sequence
          The first histogram, normalized.
      h2 : sequence
          The second histogram, normalized, same bins as ``h1``.
  
      Returns
      -------
      fidelity_based : float
          Fidelity based distance.
  
      References
      ----------
      .. [1] M. Noelle "Distribution Distance Measures Applied to 3-D Object Recognition", 2003
      """
      return math.sqrt(1.0 - fidelity_based(h1, h2))
  
imports: import math
  import scipy
label_desc: Use image node_id 18 for calling a global function with example usage: noelle_2(h1, h2) and returns: math