code: def correlate_1(h1, h2):  # 32 us @array, 56 us @list \w 100 bins
      r"""
      Correlation distance.
  
      Turns the histogram correlation into a distance measure for normalized, positive
      histograms.
  
      .. math::
  
          d_{\bar{corr}}(H, H') = 1-\frac{d_{corr}(H, H')}{2}.
  
      See `correlate` for the definition of :math:`d_{corr}(H, H')`.
  
      *Attributes:*
  
      - semimetric
  
      *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:*
  
      - :math:`d(H, H')\in[0, 1]`
      - :math:`d(H, H) = 0`
      - :math:`d(H, H') = d(H', H)`
  
      *Attributes for not-equal histograms:*
  
      - not applicable
  
      Parameters
      ----------
      h1 : sequence
          The first histogram.
      h2 : sequence
          The second histogram, same bins as ``h1``.
  
      Returns
      -------
      correlate : float
          Correlation distnace between the histograms.
  
      Notes
      -----
      Returns 0.5 if one of h1 or h2 contains only zeros.
      """
      return (1.0 - correlate(h1, h2)) / 2.0
  
imports: import math
  import scipy
label_desc: Use image node_id 27 for calling a global function with example usage: correlate_1(h1, h2) and returns: unknown