code: def experiment_execution_time(ccore=False):
      "Performance measurement"
      template_clustering(
          0.5, 3, SIMPLE_SAMPLES.SAMPLE_SIMPLE1, False, ccore
      )
      template_clustering(
          1, 2, SIMPLE_SAMPLES.SAMPLE_SIMPLE2, False, ccore
      )
      template_clustering(
          0.7, 3, SIMPLE_SAMPLES.SAMPLE_SIMPLE3, False, ccore
      )
      template_clustering(
          0.7, 3, SIMPLE_SAMPLES.SAMPLE_SIMPLE4, False, ccore
      )
      template_clustering(
          0.7, 3, SIMPLE_SAMPLES.SAMPLE_SIMPLE5, False, ccore
      )
      template_clustering(
          0.5, 3, SIMPLE_SAMPLES.SAMPLE_ELONGATE, False, ccore
      )
      template_clustering(
          0.5, 3, FCPS_SAMPLES.SAMPLE_LSUN, False, ccore
      )
      template_clustering(
          0.5, 2, FCPS_SAMPLES.SAMPLE_TARGET, False, ccore
      )
      template_clustering(
          0.15, 7, FCPS_SAMPLES.SAMPLE_TWO_DIAMONDS, False, ccore
      )
      template_clustering(
          0.25, 2, FCPS_SAMPLES.SAMPLE_WING_NUT, False, ccore
      )
      template_clustering(
          0.5, 3, FCPS_SAMPLES.SAMPLE_CHAINLINK, False, ccore
      )
      template_clustering(1, 3, FCPS_SAMPLES.SAMPLE_HEPTA, False, ccore)
      template_clustering(
          0.4, 3, FCPS_SAMPLES.SAMPLE_TETRA, False, ccore
      )
      template_clustering(15, 3, FCPS_SAMPLES.SAMPLE_ATOM, False, ccore)
  
imports: import random
  from pyclustering.cluster import cluster_visualizer
  from pyclustering.cluster.dbscan import dbscan
  from pyclustering.utils import read_sample
  from pyclustering.utils import timedcall
  from pyclustering.samples.definitions import SIMPLE_SAMPLES, FCPS_SAMPLES
label_desc: Use image node_id 20 for calling a global function with example usage: experiment_execution_time(ccore) without return types