code: def selection_r(acquisition_function,
                  samples_y_aggregation,
                  x_bounds,
                  x_types,
                  regressor_gp,
                  num_starting_points=100,
                  minimize_constraints_fun=None):
      '''
      Selecte R value
      '''
      minimize_starting_points = [lib_data.rand(x_bounds, x_types) \
                                      for i in range(0, num_starting_points)]
      outputs = selection(acquisition_function, samples_y_aggregation,
                          x_bounds, x_types, regressor_gp,
                          minimize_starting_points,
                          minimize_constraints_fun=minimize_constraints_fun)
  
      return outputf selection_r(acquisition_function,
                  samples_y_aggregation,
                  x_bounds,
                  x_types,
                  regressor_gp,
                  num_starting_points=100,
                  minimize_constraints_fun=None):
      '''
      Selecte R value
      '''
      minimize_starting_points = [lib_data.rand(x_bounds, x_types) \
                                      for i in range(0, num_starting_points)]
      outputs = selection(acquisition_function, samples_y_aggregation,
                          x_bounds, x_types, regressor_gp,
                          minimize_starting_points,
                          minimize_constraints_fun=minimize_constraints_fun)
  
      return outputs
docs: Selecte R value