How to use the pynwb.form.build.GroupBuilder function in pynwb

def test_mutually_exclusive_attributes(self):
        gb1 = GroupBuilder('gb1', attributes={'attr1': 'my_attribute1'})
        gb2 = GroupBuilder('gb2', attributes={'attr2': 'my_attribute2'})
        gb1.deep_update(gb2)
        self.assertIn('attr2', gb2)
        self.assertEqual(gb2['attr2'], 'my_attribute2')

def test_mutually_exclusive_datasets(self):
        gb1 = GroupBuilder('gb1', datasets={'dataset1': DatasetBuilder('dataset1', [1, 2, 3])})
        gb2 = GroupBuilder('gb2', datasets={'dataset2': DatasetBuilder('dataset2', [4, 5, 6])})
        gb1.deep_update(gb2)
        self.assertIn('dataset2', gb1)
        # self.assertIs(gb1['dataset2'], gb2['dataset2'])
        self.assertListEqual(gb1['dataset2'].data, gb2['dataset2'].data)

def test_mutually_exclusive_subgroups(self):
        gb1 = GroupBuilder('gb1', {'subgroup1': GroupBuilder('subgroup1')})
        gb2 = GroupBuilder('gb2', {'subgroup2': GroupBuilder('subgroup2')})
        gb1.deep_update(gb2)
        self.assertIn('subgroup2', gb1)
        gb1sg = gb1['subgroup2']
        gb2sg = gb2['subgroup2']
        self.assertIs(gb1sg, gb2sg)

def test_invalid_incorrect_type_validate(self):
        builder = GroupBuilder('my_bar', attributes={'data_type': 'Bar', 'attr1': 10})
        result = self.vmap.validate(builder)
        self.assertEqual(len(result), 2)
        self.assertIsInstance(result[0], DtypeError)  # noqa: F405
        self.assertEqual(result[0].name, 'Bar/attr1')
        self.assertIsInstance(result[1], MissingError)  # noqa: F405
        self.assertEqual(result[1].name, 'Bar/data')

def setUp(self):
        self.gb = GroupBuilder('gb')
        self.gb2 = GroupBuilder('gb2', source='file1')

def test_mutually_exclusive_attributes(self):
        gb1 = GroupBuilder('gb1', attributes={'attr1': 'my_attribute1'})
        gb2 = GroupBuilder('gb2', attributes={'attr2': 'my_attribute2'})
        gb1.deep_update(gb2)
        self.assertIn('attr2', gb2)
        self.assertEqual(gb2['attr2'], 'my_attribute2')

ts = TimeSeries('test_timeseries', 'example_source',
                        list(range(100, 200, 10)), 'SIunit', timestamps=list(range(10)), resolution=0.1)
        self.container.add_acquisition(ts)

        ts_builder = GroupBuilder('test_timeseries',
                                  attributes={'source': 'example_source',
                                              'neurodata_type': 'TimeSeries',
                                              'help': 'General purpose TimeSeries'},
                                  datasets={'data': DatasetBuilder('data', list(range(100, 200, 10)),
                                                                   attributes={'unit': 'SIunit',
                                                                               'conversion': 1.0,
                                                                               'resolution': 0.1}),
                                            'timestamps': DatasetBuilder('timestamps', list(range(10)),
                                                                         attributes={'unit': 'Seconds',
                                                                                     'interval': 1})})
        self.builder = GroupBuilder(
            'root', groups={'acquisition': GroupBuilder('acquisition', groups={'test_timeseries': ts_builder}),
                            'analysis': GroupBuilder('analysis'),
                            'general': GroupBuilder('general'),
                            'processing': GroupBuilder('processing'),
                            'stimulus': GroupBuilder(
                                'stimulus',
                                groups={'presentation': GroupBuilder('presentation'),
                                        'templates': GroupBuilder('templates')})},
            datasets={'file_create_date': DatasetBuilder('file_create_date', [str(self.create_date)]),
                      'identifier': DatasetBuilder('identifier', 'TEST123'),
                      'session_description': DatasetBuilder('session_description', 'a test NWB File'),
                      'nwb_version': DatasetBuilder('nwb_version', '1.0.6'),
                      'session_start_time': DatasetBuilder('session_start_time', str(self.start_time))},
            attributes={'neurodata_type': 'NWBFile'})

def test_intersecting_subgroups(self):
        subgroup2 = GroupBuilder('subgroup2')
        gb1 = GroupBuilder('gb1', {'subgroup1': GroupBuilder('subgroup1'), 'subgroup2': subgroup2})
        gb2 = GroupBuilder('gb2', {'subgroup2': GroupBuilder('subgroup2'), 'subgroup3': GroupBuilder('subgroup3')})
        gb1.deep_update(gb2)
        self.assertIn('subgroup3', gb1)
        self.assertIs(gb1['subgroup3'], gb2['subgroup3'])
        self.assertIs(gb1['subgroup2'], subgroup2)

attributes={'ancestry': 'TimeSeries',
                                                   'neurodata_type': 'TimeSeries',
                                                   'int_array_attribute': [0, 1, 2, 3],
                                                   'str_array_attribute': ['a', 'b', 'c', 'd'],
                                                   'help': 'General purpose TimeSeries'},
                                       datasets={'data': DatasetBuilder('data', list(range(100, 200, 10)),
                                                                        attributes={'unit': 'SIunit',
                                                                                    'conversion': 1.0,
                                                                                    'resolution': 0.1}),
                                                 'timestamps': DatasetBuilder(
                                                     'timestamps', list(range(10)),
                                                     attributes={'unit': 'Seconds', 'interval': 1})})
        self.ts = TimeSeries('test_timeseries', list(range(100, 200, 10)),
                             unit='SIunit', resolution=0.1, timestamps=list(range(10)))
        self.manager.prebuilt(self.ts, self.ts_builder)
        self.builder = GroupBuilder(
            'root',
            source=self.path,
            groups={'acquisition':
                    GroupBuilder('acquisition',
                                 groups={'timeseries':
                                         GroupBuilder('timeseries',
                                                      groups={'test_timeseries': self.ts_builder}),
                                         'images': GroupBuilder('images')}),
                    'analysis': GroupBuilder('analysis'),
                    'epochs': GroupBuilder('epochs'),
                    'general': GroupBuilder('general'),
                    'processing': GroupBuilder('processing',
                                               groups={'test_module':
                                                       GroupBuilder('test_module',
                                                                    links={'test_timeseries_link':
                                                                           LinkBuilder(self.ts_builder,