code: def template_clustering(
      number_clusters,
      path,
      number_represent_points=5,
      compression=0.5,
      draw=True,
      ccore_flag=True,
  ):
      sample = read_sample(path)
  
      cure_instance = cure(
          sample,
          number_clusters,
          number_represent_points,
          compression,
          ccore_flag,
      )
      (ticks, _) = timedcall(cure_instance.process)
  
      clusters = cure_instance.get_clusters()
      representors = cure_instance.get_representors()
      means = cure_instance.get_means()
  
      print("Sample: ", path, "\t\tExecution time: ", ticks, "\n")
      # print([len(cluster) for cluster in clusters])
  
      if draw is True:
          visualizer = cluster_visualizer()
  
          visualizer.append_clusters(clusters, sample)
  
          for cluster_index in range(len(clusters)):
              visualizer.append_cluster_attribute(
                  0, cluster_index, representors[cluster_index], "*", 10
              )
              visualizer.append_cluster_attribute(
                  0, cluster_index, [means[cluster_index]], "o"
              )
  
          visualizer.show()
  
imports: from pyclustering.utils import read_sample
  from pyclustering.utils import timedcall
  from pyclustering.samples.definitions import SIMPLE_SAMPLES
  from pyclustering.samples.definitions import FCPS_SAMPLES
  from pyclustering.cluster import cluster_visualizer
  from pyclustering.cluster.cure import cure
label_desc: Use image node_id 1 for calling a global function with example usage: template_clustering(number_clusters, path, number_represent_points, compression, draw, ccore_flag) without return types