class_docstr: !
  @brief Class represents clustering algorithm CLARANS (a method for clustering objects for spatial data mining).
class_docstr_tok: ["!","@","brief","Class","represents","clustering","algorithm","CLARANS","(","a","method","for","clustering","objects","for","spatial","data","mining",")","."]
docstr: !
  @brief Verify input parameters for the algorithm and throw exception in case of incorrectness.
docstr_tok: ["!","@","brief","Verify","input","parameters","for","the","algorithm","and","throw","exception","in","case","of","incorrectness","."]
code: def __verify_arguments(self):
      """!
      @brief Verify input parameters for the algorithm and throw exception in case of incorrectness.
  
      """
      if len(self.__pointer_data) == 0:
          raise ValueError(
              "Input data is empty (size: '%d')."
              % len(self.__pointer_data)
          )
  
      if self.__number_clusters <= 0:
          raise ValueError(
              "Amount of cluster (current value: '%d') for allocation should be greater than 0."
              % self.__number_clusters
          )
  
      if self.__numlocal < 0:
          raise ValueError(
              "Local minima (current value: '%d') should be greater or equal to 0."
              % self.__numlocal
          )
  
      if self.__maxneighbor < 0:
          raise ValueError(
              "Maximum number of neighbors (current value: '%d') should be greater or "
              "equal to 0." % self.__maxneighbor
          )
  
file_path: pyclustering/pyclustering/cluster/clarans.py
imports: import random
  from pyclustering.cluster.encoder import type_encoding
  from pyclustering.utils import euclidean_distance_square
label_desc: Use image node_id 2 for calling the clarans obj's underlying member method code with example usage: obj.__verify_arguments() without return types