def METHOD_NAME(db, app, generic_report):
    """
    Create 2 Sensors, 1 Asset and 1 AssetType
    """
    dummy_asset_type = GenericAssetType(name="DummyGenericAssetType")
    db.session.add(dummy_asset_type)
    dummy_asset = GenericAsset(
        name="DummyGenericAsset", generic_asset_type=dummy_asset_type
    )
    db.session.add(dummy_asset)
    sensor1 = Sensor("sensor 1", generic_asset=dummy_asset, event_resolution="1h")
    db.session.add(sensor1)
    sensor2 = Sensor("sensor 2", generic_asset=dummy_asset, event_resolution="1h")
    db.session.add(sensor2)
    sensor3 = Sensor(
        "sensor 3",
        generic_asset=dummy_asset,
        event_resolution="1h",
        timezone="Europe/Amsterdam",
    )
    db.session.add(sensor3)
    report_sensor = Sensor(
        "report sensor", generic_asset=generic_report, event_resolution="1h"
    )
    db.session.add(report_sensor)
    daily_report_sensor = Sensor(
        "daily report sensor",
        generic_asset=generic_report,
        event_resolution="1D",
        timezone="Europe/Amsterdam",
    )
    db.session.add(daily_report_sensor)
    """
        Create 2 DataSources
    """
    source1 = DataSource("source1")
    source2 = DataSource("source2")
    """
        Create TimedBeliefs
    """
    beliefs = []
    for sensor in [sensor1, sensor2]:
        for si, source in enumerate([source1, source2]):
            for t in range(10):
                print(si)
                beliefs.append(
                    TimedBelief(
                        event_start=datetime(2023, 4, 10, tzinfo=utc)
                        + timedelta(hours=t + si),
                        belief_horizon=timedelta(hours=24),
                        event_value=t,
                        sensor=sensor,
                        source=source,
                    )
                )
    # add simple data for testing the AggregatorReporter:
    # 24 hourly events with value 1 for sensor1 and value -1 for sensor2
    for sensor, source, value in zip([sensor1, sensor2], [source1, source2], [1, -1]):
        for t in range(24):
            beliefs.append(
                TimedBelief(
                    event_start=datetime(2023, 5, 10, tzinfo=utc) + timedelta(hours=t),
                    belief_horizon=timedelta(hours=24),
                    event_value=value,
                    sensor=sensor,
                    source=source,
                )
            )
    # add simple data for testing DST transition
    for t in range(24 * 4):  # create data for 4 days
        # UTC+1 -> UTC+2
        beliefs.append(
            TimedBelief(
                event_start=datetime(2023, 3, 24, tzinfo=utc) + timedelta(hours=t),
                belief_horizon=timedelta(hours=24),
                event_value=t,
                sensor=sensor3,
                source=source1,
            )
        )
        # UTC+2 -> UTC+1
        beliefs.append(
            TimedBelief(
                event_start=datetime(2023, 10, 27, tzinfo=utc) + timedelta(hours=t),
                belief_horizon=timedelta(hours=24),
                event_value=t,
                sensor=sensor3,
                source=source1,
            )
        )
    # Add data source transition, from DataSource 1 to DataSource 2
    # At 12:00, there is one event from both of the sources
    for t in range(12):  # create data for 4 days
        # 00:00 -> 12:00
        beliefs.append(
            TimedBelief(
                event_start=datetime(2023, 4, 24, tzinfo=utc) + timedelta(hours=t),
                belief_horizon=timedelta(hours=24),
                event_value=1,
                sensor=sensor3,
                source=source1,
            )
        )
        # 12:00 -> 24:00
        beliefs.append(
            TimedBelief(
                event_start=datetime(2023, 4, 24, tzinfo=utc) + timedelta(hours=t + 12),
                belief_horizon=timedelta(hours=24),
                event_value=-1,
                sensor=sensor3,
                source=source2,
            )
        )
    # add a belief belonging to Source 2 in the second half of the day ()
    beliefs.append(
        TimedBelief(
            event_start=datetime(2023, 4, 24, tzinfo=utc) + timedelta(hours=12),
            belief_horizon=timedelta(hours=24),
            event_value=1,
            sensor=sensor3,
            source=source1,
        )
    )
    db.session.add_all(beliefs)
    db.session.commit()
    yield sensor1, sensor2, sensor3, report_sensor, daily_report_sensor