def test_normalize_unnormalize_without_dataset(self, stats):
        result_normalized, _ = MainTransformer.normalize(None, {},
                                                         inplace=False)
        result_unnormalize = MainTransformer.unnormalize(None, {},
                                                         inplace=False)

        assert result_normalized is None and result_unnormalize is None
    def test_normalize_and_unnormalize(self, stats):
        copied_dataset = pandas.DataFrame({
            'TestColumn': [1.0, 2.0, 3.0],
            'TestColumn2': [5.0, 6.0, 7.0]
        })

        unnormalized_dataset = copied_dataset.copy()

        normalized, statistics = MainTransformer.normalize(copied_dataset,
                                                           inplace=False,
                                                           stats=stats)

        if stats is None:
            mean_one = np.mean(copied_dataset['TestColumn'])
            std_one = np.std(copied_dataset['TestColumn'])

            mean_two = np.mean(copied_dataset['TestColumn2'])
            std_two = np.std(copied_dataset['TestColumn2'])
        else:
            mean_one = stats['TestColumn']['mean']
            std_one = stats['TestColumn']['std']

            mean_two = stats['TestColumn2']['mean']
            std_two = stats['TestColumn2']['std']

        copied_dataset['TestColumn'] -= mean_one
        copied_dataset['TestColumn2'] -= mean_two

        copied_dataset['TestColumn'] /= std_one
        copied_dataset['TestColumn2'] /= std_two

        manual_stats = {
            'TestColumn': {
                'mean': mean_one,
                'std': std_one
            },
            'TestColumn2': {
                'mean': mean_two,
                'std': std_two
            }
        }

        assert copied_dataset.equals(normalized)
        assert statistics == manual_stats

        MainTransformer.unnormalize(normalized, statistics, inplace=True)

        print(unnormalized_dataset)
        print(normalized)
        assert unnormalized_dataset.equals(normalized)