class_docstr: !
  @brief The class represents clustering algorithm ROCK.
  
  Example:
  @code
      from pyclustering.cluster import cluster_visualizer
      from pyclustering.cluster.rock import rock
      from pyclustering.samples.definitions import FCPS_SAMPLES
      from pyclustering.utils import read_sample
  
      # Read sample for clustering from file.
      sample = read_sample(FCPS_SAMPLES.SAMPLE_HEPTA)
  
      # Create instance of ROCK algorithm for cluster analysis. Seven clusters should be allocated.
      rock_instance = rock(sample, 1.0, 7)
  
      # Run cluster analysis.
      rock_instance.process()
  
      # Obtain results of clustering.
      clusters = rock_instance.get_clusters()
  
      # Visualize clustering results.
      visualizer = cluster_visualizer()
      visualizer.append_clusters(clusters, sample)
      visualizer.show()
  @endcode
     
docstr: !
  @brief Creates 2D adjacency matrix (list of lists) where each element described existence of link between points (means that points are neighbors).
docstr_tok: ["!","@","brief","Creates","2D","adjacency","matrix","(","list","of","lists",")","where","each","element","described","existence","of","link","between","points","(","means","that","points","are","neighbors",")","."]
code: def __create_adjacency_matrix(self):
      """!
      @brief Creates 2D adjacency matrix (list of lists) where each element described existence of link between points (means that points are neighbors).
  
      """
  
      size_data = len(self.__pointer_data)
  
      self.__adjacency_matrix = [
          [0 for i in range(size_data)] for j in range(size_data)
      ]
      for i in range(0, size_data):
          for j in range(i + 1, size_data):
              distance = euclidean_distance(
                  self.__pointer_data[i], self.__pointer_data[j]
              )
              if distance <= self.__eps:
                  self.__adjacency_matrix[i][j] = 1
                  self.__adjacency_matrix[j][i] = 1
  
file_path: pyclustering/pyclustering/cluster/rock.py
imports: from pyclustering.cluster.encoder import type_encoding
  from pyclustering.utils import euclidean_distance
  from pyclustering.core.wrapper import ccore_library
  import pyclustering.core.rock_wrapper
label_desc: Use image node_id 7 for calling the rock obj's underlying member method code with example usage: obj.__create_adjacency_matrix() without return types