class_docstr: !
  @brief Random center initializer is for generation specified amount of random of centers for specified data.
class_docstr_tok: ["!","@","brief","Random","center","initializer","is","for","generation","specified","amount","of","random","of","centers","for","specified","data","."]
docstr: !
  @brief Generates and returns random center.
  
  @param[in] return_index (bool): If True then returns index of point from input data instead of point itself.
docstr_tok: ["!","@","brief","Generates","and","returns","random","center",".","@","param","[","in","]","return_index","(","bool",")",":","If","True","then","returns","index","of","point","from","input","data","instead","of","point","itself","."]
code: def __create_center(self, return_index):
      """!
      @brief Generates and returns random center.
  
      @param[in] return_index (bool): If True then returns index of point from input data instead of point itself.
  
      """
      random_index_point = random.randint(0, len(self.__data))
      if random_index_point not in self.__available_indexes:
          random_index_point = self.__available_indexes.pop()
      else:
          self.__available_indexes.remove(random_index_point)
  
      if return_index:
          return random_index_point
      return self.__data[random_index_point]
  
file_path: pyclustering/pyclustering/cluster/center_initializer.py
imports: import numpy
  import random
  import warnings
  from pyclustering.utils.metric import distance_metric, type_metric
label_desc: Use image node_id 3 for calling the random_center_initializer obj's underlying member method code with example usage: obj.__create_center(return_index) and returns: self, random_index_point