code: def templateClusteringWithAnswers(
      sample_path, answer_path, radius, neighbors, ccore, **kwargs
  ):
      random_order = kwargs.get("random_order", False)
      repeat = kwargs.get("repeat", 1)
  
      for _ in range(repeat):
          sample = read_sample(sample_path)
  
          sample_index_map = [i for i in range(len(sample))]
          if random_order:
              shuffle(sample_index_map)
  
          sample_shuffled = [sample[i] for i in sample_index_map]
  
          dbscan_instance = dbscan(
              sample_shuffled, radius, neighbors, ccore
          )
          dbscan_instance.process()
  
          clusters = dbscan_instance.get_clusters()
          noise = dbscan_instance.get_noise()
  
          for cluster in clusters:
              for i in range(len(cluster)):
                  cluster[i] = sample_index_map[cluster[i]]
  
          for i in range(len(noise)):
              noise[i] = sample_index_map[noise[i]]
          noise = sorted(noise)
  
          reader = answer_reader(answer_path)
          expected_noise = sorted(reader.get_noise())
          expected_length_clusters = reader.get_cluster_lengths()
  
          assertion.eq(
              len(sample),
              sum([len(cluster) for cluster in clusters]) + len(noise),
          )
          assertion.eq(
              sum(expected_length_clusters),
              sum([len(cluster) for cluster in clusters]),
          )
          assertion.eq(
              expected_length_clusters,
              sorted([len(cluster) for cluster in clusters]),
          )
          assertion.eq(expected_noise, noise)
  
imports: import os
  import pickle
  import tempfile
  from random import random, shuffle
  from pyclustering.utils import read_sample, calculate_distance_matrix
  from pyclustering.cluster.dbscan import dbscan
  from pyclustering.tests.assertion import assertion
  from pyclustering.samples.definitions import SIMPLE_SAMPLES
  from pyclustering.samples import answer_reader
label_desc: Use image node_id 2 for calling the DbscanTestTemplates obj's underlying member method code with example usage: obj.templateClusteringWithAnswers(sample_path, answer_path, radius, neighbors, ccore) without return types