code: def test_compute_elementary_effects_scaled(morris_data):
      """
      Inputs for elementary effects taken from Exercise 5 from Saltelli (2008).
      See page 140-145.
      `model_inputs` are from trajectory t_1 from table 3.10 on page 141.
      `desired` was manual calculated in an Excel spreadsheet after confirming
      the results from the original paper.
      """
      model_inputs, model_outputs = morris_data
  
      delta = 2.0 / 3
  
      actual = _compute_elementary_effects(
          model_inputs, model_outputs, 16, delta, scaling=True
      )
      desired = np.array(
          [
              [-0.181634813],
              [0.345250299],
              [0.071454753],
              [0.352948837],
              [0.137866888],
              [0.076670871],
              [-0.152252439],
              [-0.285251912],
              [-0.080726583],
              [0.240017431],
              [0.419563468],
              [0.024244438],
              [0.12731585],
              [0.101289958],
              [0.63202974],
          ],
          dtype=float,
      )
      assert_allclose(actual, desired, atol=1e-2)
  
file_path: SALib/tests/test_analyze_morris.py
imports: from pytest import raises, fixture
  import numpy
  from numpy.testing import assert_allclose, assert_equal
  from SALib.analyze.morris import analyze, _compute_mu_star_confidence, _compute_elementary_effects, _reorganize_output_matrix, _compute_grouped_metric, _compute_grouped_sigma, _check_if_array_of_floats
label_desc: Use image node_id 7 for calling a global function with example usage: test_compute_elementary_effects_scaled(morris_data) without return types