code: def performance_measure_random_points(ccore):
      clustering_random_points(1000, 5, ccore)
      clustering_random_points(2000, 5, ccore)
      clustering_random_points(3000, 5, ccore)
      clustering_random_points(4000, 5, ccore)
      clustering_random_points(5000, 5, ccore)
      clustering_random_points(10000, 5, ccore)
      clustering_random_points(20000, 5, ccore)
  
imports: import random
  from pyclustering.samples.definitions import SIMPLE_SAMPLES, FCPS_SAMPLES, FAMOUS_SAMPLES
  from pyclustering.cluster import cluster_visualizer_multidim
  from pyclustering.cluster.center_initializer import kmeans_plusplus_initializer
  from pyclustering.cluster.kmeans import kmeans, kmeans_observer, kmeans_visualizer
  from pyclustering.utils import read_sample
  from pyclustering.utils import timedcall
  from pyclustering.utils.metric import distance_metric, type_metric
label_desc: Use image node_id 21 for calling a global function with example usage: performance_measure_random_points(ccore) without return types