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 Returns list of not `None` children of the node.
  
  @return (list) list of not `None` children of the node; if the node does not have children
                  then `None` is returned.
docstr_tok: ["!","@","brief","Returns","list","of","not","`","None","`","children","of","the","node",".","@","return","(","list",")","list","of","not","`","None","`","children","of","the","node",";","if","the","node","does","not","have","children","then","`","None","`","is","returned","."]
code: def get_children(self):
      """!
      @brief Returns list of not `None` children of the node.
  
      @return (list) list of not `None` children of the node; if the node does not have children
                      then `None` is returned.
  
      """
  
      if self.left is not None:
          yield self.left
      if self.right is not None:
          yield self.right
  
imports: import numpy
  import matplotlib.pyplot
  from pyclustering.utils import euclidean_distance_square, find_left_element
label_desc: Use image node_id 4 for calling the node obj's underlying member method code with example usage: obj.get_children() without return types