code: def testPredictFivePointsUserMetric(self):
      centers = [[0.2, 0.1], [4.0, 1.0], [2.0, 2.0], [2.3, 3.9]]
      to_predict = [
          [0.3, 0.2],
          [4.1, 1.1],
          [3.9, 1.1],
          [2.1, 1.9],
          [2.1, 4.1],
      ]
      metric = distance_metric(
          type_metric.USER_DEFINED,
          func=distance_metric(type_metric.EUCLIDEAN),
      )
      KmediansTestTemplates.templatePredict(
          SIMPLE_SAMPLES.SAMPLE_SIMPLE3,
          centers,
          to_predict,
          [0, 1, 1, 2, 3],
          False,
          metric=metric,
      )
  
imports: import unittest
  import numpy
  import matplotlib
  from pyclustering.cluster.tests.kmedians_templates import KmediansTestTemplates
  from pyclustering.cluster.kmedians import kmedians
  from pyclustering.samples.definitions import SIMPLE_SAMPLES
  from pyclustering.utils import read_sample
  from pyclustering.utils.metric import type_metric, distance_metric
label_desc: Use image node_id 36 for calling the KmediansUnitTest obj's underlying member method code with example usage: obj.testPredictFivePointsUserMetric() without return types