@pytest.mark.parametrize('durbin_watson_pvalue', [0.1, 1, 2, 2.5, 3, 3.9])
def test_check_residual_autocorrelation(self, linearity_validator_obj, durbin_watson_mock, durbin_watson_pvalue):
    'Given data\n        When residual_autocorrelation is called\n        Then must create durbin_watson_value'
    durbin_watson_mock.return_value = durbin_watson_pvalue
    linearity_validator_obj.check_residual_autocorrelation()
    assert (linearity_validator_obj.durbin_watson_value == durbin_watson_mock.return_value)
    assert durbin_watson_mock.called
    assert (durbin_watson_mock.call_args_list == [call(linearity_validator_obj.fitted_result.resid)])
Given data
When residual_autocorrelation is called
Then must create durbin_watson_value
@pytest.mark.parametrize('durbin_watson_pvalue', [0.1, 1, 2, 2.5, 3, 3.9])
def test_check_residual_autocorrelation(self, linearity_validator_obj, durbin_watson_mock, durbin_watson_pvalue):
    'Given data\n        When residual_autocorrelation is called\n        Then must create durbin_watson_value'
    durbin_watson_mock.return_value = durbin_watson_pvalue
    linearity_validator_obj.check_residual_autocorrelation()
    assert (linearity_validator_obj.durbin_watson_value == durbin_watson_mock.return_value)
    assert durbin_watson_mock.called
    assert (durbin_watson_mock.call_args_list == [call(linearity_validator_obj.fitted_result.resid)])