@pytest.mark.parametrize('reference_data, current_data, data_mapping, dataset, expected_result', ((pd.DataFrame({'target': [1, 2, 3, 4], 'prediction': [1, 2, 3, 4]}), None, ColumnMapping(), None, BaseWidgetInfo(type='big_graph', title='test_widget', size=1)), (pd.DataFrame({'target': [1, 2, 3, 4], 'prediction': [1, 2, 3, 4]}), pd.DataFrame({'target': [1, 2, 3, 4], 'prediction': [1, 2, 3, 4]}), ColumnMapping(), 'reference', BaseWidgetInfo(type='big_graph', title='test_widget', size=1))))
def test_reg_error_normality_widget_simple_case(widget: RegErrorNormalityWidget, reference_data: pd.DataFrame, current_data: pd.DataFrame, data_mapping: ColumnMapping, dataset: Optional[str], expected_result: BaseWidgetInfo) -> None:
    if (dataset is not None):
        widget.dataset = dataset
    analyzer = RegressionPerformanceAnalyzer()
    analyzer.options_provider = widget.options_provider
    analyzer_results = analyzer.calculate(reference_data, current_data, data_mapping)
    result = widget.calculate(reference_data, current_data, data_mapping, {RegressionPerformanceAnalyzer: analyzer_results})
    if (expected_result is not None):
        assert (result.type == expected_result.type)
        assert (result.title == expected_result.title)
        assert (result.size == expected_result.size)
        assert (result.params is not None)
    else:
        assert (result is None)
@pytest.mark.parametrize('reference_data, current_data, data_mapping, dataset, expected_result', ((pd.DataFrame({'target': [1, 2, 3, 4], 'prediction': [1, 2, 3, 4]}), None, ColumnMapping(), None, BaseWidgetInfo(type='big_graph', title='test_widget', size=1)), (pd.DataFrame({'target': [1, 2, 3, 4], 'prediction': [1, 2, 3, 4]}), pd.DataFrame({'target': [1, 2, 3, 4], 'prediction': [1, 2, 3, 4]}), ColumnMapping(), 'reference', BaseWidgetInfo(type='big_graph', title='test_widget', size=1))))
def test_reg_error_normality_widget_simple_case(widget: RegErrorNormalityWidget, reference_data: pd.DataFrame, current_data: pd.DataFrame, data_mapping: ColumnMapping, dataset: Optional[str], expected_result: BaseWidgetInfo) -> None:
    if (dataset is not None):
        widget.dataset = dataset
    analyzer = RegressionPerformanceAnalyzer()
    analyzer.options_provider = widget.options_provider
    analyzer_results = analyzer.calculate(reference_data, current_data, data_mapping)
    result = widget.calculate(reference_data, current_data, data_mapping, {RegressionPerformanceAnalyzer: analyzer_results})
    if (expected_result is not None):
        assert (result.type == expected_result.type)
        assert (result.title == expected_result.title)
        assert (result.size == expected_result.size)
        assert (result.params is not None)
    else:
        assert (result is None)