code: def setup_input():
      input_1 = [[0, 1 / 3.0], [0, 1.0], [2 / 3.0, 1.0]]
      input_2 = [[0, 1 / 3.0], [2 / 3.0, 1 / 3.0], [2 / 3.0, 1.0]]
      input_3 = [[2 / 3.0, 0], [2 / 3.0, 2 / 3.0], [0, 2 / 3.0]]
      input_4 = [[1 / 3.0, 1.0], [1.0, 1.0], [1, 1 / 3.0]]
      input_5 = [[1 / 3.0, 1.0], [1 / 3.0, 1 / 3.0], [1, 1 / 3.0]]
      input_6 = [[1 / 3.0, 2 / 3.0], [1 / 3.0, 0], [1.0, 0]]
      input_sample = np.concatenate(
          [input_1, input_2, input_3, input_4, input_5, input_6]
      )
      return input_sample
  
imports: from numpy.testing import assert_equal, assert_allclose
  from pytest import raises, fixture, warns, mark
  import numpy
  import warnings
  from SALib.sample.morris.morris import sample, _check_group_membership, _check_if_num_levels_is_even, _compute_optimised_trajectories, _generate_p_star, _compute_b_star, _generate_trajectory, _generate_x_star
  from SALib.util import read_param_file, compute_groups_matrix, _define_problem_with_groups, _compute_delta
label_desc: Use image node_id 1 for calling a global function with example usage: setup_input() and returns: input_sample