class_docstr: !
  @brief Represents data cluster in CURE term. 
  @details CURE cluster is described by points of cluster, representation points of the cluster and by the cluster center.
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docstr: !
  @brief Constructor of CURE cluster.
  
  @param[in] point (list): Point represented by list of coordinates.
  @param[in] index (uint): Index point in dataset.
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code: def __init__(self, point, index):
      """!
      @brief Constructor of CURE cluster.
  
      @param[in] point (list): Point represented by list of coordinates.
      @param[in] index (uint): Index point in dataset.
  
      """
  
      ## List of points that make up cluster.
      self.points = []
  
      ## Point indexes in dataset.
      self.indexes = -1
  
      ## Mean of points that make up cluster.
      self.mean = None
  
      ## List of points that represents clusters.
      self.rep = []
  
      if point is not None:
          self.points = [point]
          self.indexes = [index]
          self.mean = point
          self.rep = [point]
  
      ## Pointer to the closest cluster.
      self.closest = None
  
      ## Distance to the closest cluster.
      self.distance = float("inf")
  
imports: import numpy
  from pyclustering.cluster.encoder import type_encoding
  from pyclustering.utils import euclidean_distance_square
  from pyclustering.container.kdtree import kdtree
  from pyclustering.core.wrapper import ccore_library
  import pyclustering.core.cure_wrapper
label_desc: Use image node_id 1 to create a new cure_cluster object  with example: obj = cure_cluster(point, index)