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: !
  @brief Creates KD-tree node.
  
  @param[in] data (list): Data point that is presented as list of coordinates.
  @param[in] payload (any): Payload of node (pointer to essence that is attached to this node).
  @param[in] left (node): Node of KD-Tree that represents left successor.
  @param[in] right (node): Node of KD-Tree that represents right successor.
  @param[in] disc (uint): Index of dimension of that node.
  @param[in] parent (node): Node of KD-Tree that represents parent.
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code: def __init__(
      self,
      data=None,
      payload=None,
      left=None,
      right=None,
      disc=None,
      parent=None,
  ):
      """!
      @brief Creates KD-tree node.
  
      @param[in] data (list): Data point that is presented as list of coordinates.
      @param[in] payload (any): Payload of node (pointer to essence that is attached to this node).
      @param[in] left (node): Node of KD-Tree that represents left successor.
      @param[in] right (node): Node of KD-Tree that represents right successor.
      @param[in] disc (uint): Index of dimension of that node.
      @param[in] parent (node): Node of KD-Tree that represents parent.
  
      """
  
      ## Data point that is presented as list of coordinates.
      self.data = data
  
      ## Payload of node that can be used by user for storing specific information in the node.
      self.payload = payload
  
      ## Left node successor of the node.
      self.left = left
  
      ## Right node successor of the node.
      self.right = right
  
      ## Index of dimension.
      self.disc = disc
  
      ## Parent node of the node.
      self.parent = parent
  
imports: import numpy
  import matplotlib.pyplot
  from pyclustering.utils import euclidean_distance_square, find_left_element
label_desc: Use image node_id 1 to create a new node object  with example: obj = node(data, payload, left, right, disc, parent)