code: def selection_r(x_bounds,
                  x_types,
                  clusteringmodel_gmm_good,
                  clusteringmodel_gmm_bad,
                  num_starting_points=100,
                  minimize_constraints_fun=None):
      '''
      Call selection
      '''
      minimize_starting_points = [lib_data.rand(x_bounds, x_types)\
                                      for i in range(0, num_starting_points)]
      outputs = selection(x_bounds, x_types,
                          clusteringmodel_gmm_good,
                          clusteringmodel_gmm_bad,
                          minimize_starting_points,
                          minimize_constraints_fun)
      return outputf selection_r(x_bounds,
                  x_types,
                  clusteringmodel_gmm_good,
                  clusteringmodel_gmm_bad,
                  num_starting_points=100,
                  minimize_constraints_fun=None):
      '''
      Call selection
      '''
      minimize_starting_points = [lib_data.rand(x_bounds, x_types)\
                                      for i in range(0, num_starting_points)]
      outputs = selection(x_bounds, x_types,
                          clusteringmodel_gmm_good,
                          clusteringmodel_gmm_bad,
                          minimize_starting_points,
                          minimize_constraints_fun)
      return outputs
docs: Call selection