code: def test_compute_grouped_sigma():
      """
      Tests that a value for sigma is returned when the group contains 1 param
  
      Morris groups do not allow a value for sigma to be computed because it
      requires the use of mu (as opposed to mu_star).
  
      However, if the group consists of just one parameter, then the sampling
      will be identical to the situation in which no groups are used,
      but only for that parameter.
  
      An NA should be returned for all other groups (as opposed to 0, which could
      confuse plotting.morris)
      """
      group_matrix = np.array([[1, 0], [0, 1], [0, 1]], dtype=int)
  
      ee = np.array(
          [
              [2.52, 2.01, 2.30, -0.66, -0.93, -1.30],
              [-2.00, 0.13, -0.80, 0.25, -0.02, 0.51],
              [2.00, -0.13, 0.80, -0.25, 0.02, -0.51],
          ]
      )
      sigma = np.std(ee, axis=1, ddof=1)
  
      actual = _compute_grouped_sigma(sigma, group_matrix)
      desired = np.array([1.79352911, np.NAN], dtype=float)
      assert_allclose(actual, desired, rtol=1e-1)
  
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 13 for calling a global function with example usage: test_compute_grouped_sigma() without return types