code: def cluster_wing_nut():
      "Almost good!"
      start_centers = [[-1.5, 1.5], [1.5, 1.5]]
      template_clustering(start_centers, FCPS_SAMPLES.SAMPLE_WING_NUT)
  
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 13 for calling a global function with example usage: cluster_wing_nut() without return types