code: def correct_scores(sample_path, answer_path, ccore_flag, **kwargs):
      data_type = kwargs.get("data_type", "points")
  
      sample = read_sample(sample_path)
      if data_type == "distance_matrix":
          sample = calculate_distance_matrix(
              sample, distance_metric(type_metric.EUCLIDEAN_SQUARE)
          )
  
      clusters = answer_reader(answer_path).get_clusters()
  
      scores = (
          silhouette(
              sample, clusters, ccore=ccore_flag, data_type=data_type
          )
          .process()
          .get_score()
      )
  
      assertion.eq(len(sample), len(scores))
      for score in scores:
          assertion.le(-1.0, score)
          assertion.ge(1.0, score)
  
      return scores
  
file_path: pyclustering/pyclustering/cluster/tests/silhouette_templates.py
imports: import math
  from pyclustering.cluster.silhouette import silhouette, silhouette_ksearch
  from pyclustering.samples import answer_reader
  from pyclustering.samples.definitions import SIMPLE_SAMPLES
  from pyclustering.tests.assertion import assertion
  from pyclustering.utils import read_sample, calculate_distance_matrix, distance_metric, type_metric
label_desc: Use image node_id 1 for calling the silhouette_test_template obj's underlying member method code with example usage: obj.correct_scores(sample_path, answer_path, ccore_flag) and returns: scores