code: def test_constant_output():
      """
      No variance in model outputs, which should produce 0 sensitivity.
      """
  
      def mock_model(X):
          r, _ = X.shape
          return np.array([0.4] * r)
  
      problem = {
          "num_vars": 3,
          "names": ["x1", "x2", "x3"],
          "bounds": [[0, 1], [0, 1], [0, 1]],
      }
      N = 256
      param_values = sobol_sample(problem, N, calc_second_order=False)
      model_results = mock_model(param_values)
      Si = sobol.analyze(
          problem, model_results, calc_second_order=False
      )
  
      assert np.all(
          Si["S1"] == 0.0
      ), "Constant outputs should produce 0 first order sensitivity"
      assert np.all(
          Si["ST"] == 0.0
      ), "Constant outputs should produce 0 total order sensitivity"
      assert np.all(
          Si["S1_conf"] == 0.0
      ), "Constant outputs should produce 0 CI"
      assert np.all(
          Si["ST_conf"] == 0.0
      ), "Constant outputs should produce 0 CI"
  
imports: from pytest import raises, mark
  from numpy.testing import assert_equal, assert_allclose
  import numpy
  from scipy.stats import norm
  from SALib.analyze import sobol
  from SALib.sample.sobol import sample
  from SALib.sample import sobol_sequence
  from SALib.test_functions import Ishigami, Sobol_G
  from SALib.util import read_param_file
label_desc: Use image node_id 12 for calling a global function with example usage: test_constant_output() and returns: np