def test_analysis_of_morris_results():
    model_input = np.array([[0, 1. / 3], [0, 1], [2. / 3, 1],
                             [0, 1. / 3], [2. / 3, 1. / 3], [2. / 3, 1],
                             [2. / 3, 0], [2. / 3, 2. / 3], [0, 2. / 3],
                             [1. / 3, 1], [1, 1], [1, 1. / 3],
                             [1. / 3, 1], [1. / 3, 1. / 3], [1, 1. / 3],
                             [1. / 3, 2. / 3], [1. / 3, 0], [1, 0]],
                            dtype=np.float)

    model_output = np.array([0.97, 0.71, 2.39, 0.97, 2.30, 2.39, 
                             1.87, 2.40, 0.87, 2.15, 1.71, 1.54, 
                             2.15, 2.17, 1.54, 2.20, 1.87, 1.0],
                       dtype=np.float)

    problem = {
     'num_vars': 2,
     'names': ['Test 1', 'Test 2'],
     'groups': None,
     'bounds': [[0.0, 1.0], [0.0, 1.0]]
    }

    Si = analyze(problem, model_input, model_output,
                 num_resamples=1000,
                 conf_level=0.95,
                 print_to_console=False)

    desired_mu = np.array([0.66, 0.21])
    assert_allclose(Si['mu'], desired_mu, rtol=1e-1, 
                    err_msg="The values for mu are incorrect")
    desired_mu_star = np.array([1.62, 0.35])
    assert_allclose(Si['mu_star'], desired_mu_star, rtol=1e-2, 
                    err_msg="The values for mu star are incorrect")
    desired_sigma = np.array([1.79, 0.41])
    assert_allclose(Si['sigma'], desired_sigma, rtol=1e-2, 
                    err_msg="The values for sigma are incorrect")
    desired_names = ['Test 1', 'Test 2']
    assert_equal(Si['names'], desired_names, 
                 err_msg="The values for names are incorrect")
Removes all occurences of given `values` from `list`.
dataset/ETHPy150Open SALib/SALib/SALib/tests/test_analyze_morris.py/test_analysis_of_morris_results--crossover with--dataset/ETHPy150Open shellderp/sublime-robot-plugin/lib/robot/libraries/Collections.py/_List.remove_values_from_list