code: def template_self_organization(
      file,
      rows,
      cols,
      time,
      structure,
      init_type=None,
      init_radius=None,
      init_rate=None,
      umatrix=False,
      pmatrix=False,
      awards=False,
  ):
      parameters = som_parameters()
  
      if init_type is not None:
          parameters.init_type = init_type
      if init_radius is not None:
          parameters.init_radius = init_radius
      if init_rate is not None:
          parameters.init_learn_rate = init_rate
  
      sample = read_sample(file)
      network = som(rows, cols, structure, parameters, True)
      network.train(sample, time)
      network.show_network(False, dataset=False)
  
      if umatrix is True:
          network.show_distance_matrix()
  
      if pmatrix is True:
          network.show_density_matrix()
  
      if awards is True:
          network.show_winner_matrix()
  
imports: from pyclustering.nnet.som import som
  from pyclustering.nnet.som import type_conn
  from pyclustering.nnet.som import type_init
  from pyclustering.nnet.som import som_parameters
  from pyclustering.samples.definitions import SIMPLE_SAMPLES
  from pyclustering.samples.definitions import FCPS_SAMPLES
  from pyclustering.utils import read_sample
  import matplotlib.pyplot
  from matplotlib import cm
  from pylab import *
label_desc: Use image node_id 1 for calling a global function with example usage: template_self_organization(file, rows, cols, time, structure, init_type, init_radius, init_rate, umatrix, pmatrix, awards) without return types