code: def template_predict(self, path, amount, points, ccore):
      metric = distance_metric(type_metric.EUCLIDEAN)
  
      sample = read_sample(path)
      gmeans_instance = gmeans(sample, amount, ccore).process()
      centers = gmeans_instance.get_centers()
  
      closest_clusters = gmeans_instance.predict(points)
  
      self.assertEqual(len(points), len(closest_clusters))
  
      for i in range(len(points)):
          cluster_index = closest_clusters[i]
          distance = metric(centers[cluster_index], points[i])
          for center_index in range(len(centers)):
              if center_index != cluster_index:
                  other_distance = metric(
                      centers[center_index], points[i]
                  )
                  self.assertLessEqual(distance, other_distance)
  
imports: import unittest
  import matplotlib
  from pyclustering.cluster.tests.gmeans_templates import gmeans_test_template
  from pyclustering.cluster.gmeans import gmeans
  from pyclustering.utils import read_sample, distance_metric, type_metric
  from pyclustering.samples.definitions import SIMPLE_SAMPLES, FCPS_SAMPLES, SIMPLE_ANSWERS
label_desc: Use image node_id 40 for calling the gmeans_unit_test obj's underlying member method code with example usage: obj.template_predict(path, amount, points, ccore) without return types