code: def shepards(distances, power=2):
      """Basic inverse distance weighting function
  
      Parameters
      ----------
      distances: list/numpy.ndarray
          1D list of numbers (ex. distance results from call to KDTree.query)
  
      power: int
          Default of 2 used since the referenced paper stated an exponent of 2 "gives seemingly
          satisfactory results"
  
      Returns
      -------
      numpy.ndarray
          1D list of numbers that sum to 1, represents weights of provided distances, in order.
  
      References
      ----------
  
      Shepard, Donald (1968). "A two-dimensional interpolation function for irregularly-spaced data".
      Proceedings of the 1968 ACM National Conference. pp. 517-524. doi:10.1145/800186.810616
      """
      return to_percentage(1 / np.power(distances, power))
  
label_desc: Use image node_id 1 for calling a global function with example usage: shepards(distances, power) and returns: to_percentage