class_docstr: !
  @brief Represents a node in a KD-Tree.
  @details The KD-Tree node contains point's coordinates, discriminator, payload and pointers to parent and children.
  
  @see kdtree_balanced
  @see kdtree
class_docstr_tok: ["!","@","brief","Represents","a","node","in","a","KD-Tree",".","@","details","The","KD-Tree","node","contains","point","'s","coordinates",",","discriminator",",","payload","and","pointers","to","parent","and","children",".","@","see","kdtree_balanced","@","see","kdtree"]
docstr: !
  @return (string) Default representation of the node.
docstr_tok: ["!","@","return","(","string",")","Default","representation","of","the","node","."]
code: def __repr__(self):
      """!
      @return (string) Default representation of the node.
  
      """
      left = None
      right = None
  
      if self.left is not None:
          left = self.left.data
  
      if self.right is not None:
          right = self.right.data
  
      return "(%s: [L:'%s', R:'%s'])" % (self.data, left, right)
  
imports: import numpy
  import matplotlib.pyplot
  from pyclustering.utils import euclidean_distance_square, find_left_element
label_desc: Use image node_id 2 for calling the node obj's underlying member method code with example usage: obj.__repr__() and returns: unknown