How to use the flowmachine.features.daily_location function in flowmachine

def test_daily_location_1_df(get_dataframe, diff_reporter):
    """
    Simple daily location query returns the expected data.
    """
    dl = daily_location("2016-01-01", "2016-01-02")
    df = get_dataframe(dl)
    verify(df.to_csv(), diff_reporter)

def test_daily_location_5_sql(diff_reporter):
    """
    Daily location query with non-default parameters returns the expected data.
    """
    subset_query = CustomQuery(
        "SELECT DISTINCT msisdn AS subscriber FROM events.calls WHERE msisdn in ('GNLM7eW5J5wmlwRa', 'e6BxY8mAP38GyAQz', '1vGR8kp342yxEpwY')"
    )
    dl = daily_location(
        "2016-01-05",
        level="cell",
        hours=(23, 5),
        method="last",
        # subscriber_identifier="imei",
        # column_name="admin2pcod",
        # ignore_nulls=False,
        subscriber_subset=subset_query,
    )
    sql = pretty_sql(dl.get_query())
    verify(sql, diff_reporter)

def test_daily_location_2_df(get_dataframe, diff_reporter):
    """
    Daily location query with non-default parameters returns the expected data.
    """
    dl = daily_location(
        "2016-01-04",
        level="admin2",
        hours=(3, 9),
        method="most-common",
        # subscriber_identifier="imei",
        # column_name="admin2pcod",
        ignore_nulls=False,
        subscriber_subset=[
            "2GJxeNazvlgZbqj6",
            "7qKmzkeMbmk5nOa0",
            "8dpPLR15XwR7jQyN",
            "1NqnrAB9bRd597x2",
        ],
    )
    df = get_dataframe(dl)
    verify(df.to_csv(), diff_reporter)

def test_daily_location_1_sql(diff_reporter):
    """
    Simple daily location query returns the expected SQL string.
    """
    dl = daily_location("2016-01-01", "2016-01-02")
    sql = pretty_sql(dl.get_query())
    verify(sql, diff_reporter)

def test_daily_location_4_sql(diff_reporter):
    """
    Regression test; this verifies the SQL statement for the test below (which checks the resulting dataframe)
    """
    subset_query = CustomQuery(
        "SELECT * FROM (VALUES ('dr9xNYK006wykgXj')) as tmp (subscriber)"
    )
    dl = daily_location(
        "2016-01-05",
        table="events.calls",
        hours=(22, 6),
        subscriber_subset=subset_query,
    )
    sql = pretty_sql(dl.get_query())
    verify(sql, diff_reporter)

import concurrent.futures
from flowmachine.core.errors import UnstorableQueryError

flowmachine.connect()

print("Constructing query objects")

admin1_spatial_unit = flowmachine.core.make_spatial_unit("admin", level=1)
admin3_spatial_unit = flowmachine.core.make_spatial_unit("admin", level=3)
vsite_spatial_unit = flowmachine.core.make_spatial_unit("versioned-site")
vcell_spatial_unit = flowmachine.core.make_spatial_unit("versioned-cell")

# FlowClient example usage
example_usage_queries = [
    flowmachine.features.utilities.spatial_aggregates.SpatialAggregate(
        locations=flowmachine.features.daily_location(
            date="2016-01-01", spatial_unit=admin3_spatial_unit, method="last"
        )
    ),
    flowmachine.features.utilities.spatial_aggregates.SpatialAggregate(
        locations=flowmachine.features.ModalLocation(
            *[
                flowmachine.features.daily_location(
                    date=dl_date, spatial_unit=admin3_spatial_unit, method="last"
                )
                for dl_date in pd.date_range("2016-01-01", "2016-01-03", freq="D")
            ]
        )
    ),
    flowmachine.features.Flows(
        flowmachine.features.daily_location(
            date="2016-01-01", spatial_unit=admin1_spatial_unit, method="last"

def _flowmachine_query_obj(self):
        """
        Return the underlying flowmachine daily_location object.

        Returns
        -------
        Query
        """
        from flowmachine.features import daily_location

        return daily_location(
            date=self.date,
            level=self.aggregation_unit,
            method=self.method,
            subscriber_subset=self.subscriber_subset,
        )

def _unsampled_query_obj(self):
        """
        Return the underlying flowmachine daily_location object.

        Returns
        -------
        Query
        """
        return daily_location(
            date=self.date,
            spatial_unit=self.aggregation_unit,
            method=self.method,
            table=self.event_types,
            subscriber_subset=self.subscriber_subset,
        )

locations=flowmachine.features.daily_location(
            date="2016-01-01", spatial_unit=admin3_spatial_unit, method="last"
        )
    ),
    flowmachine.features.utilities.spatial_aggregates.SpatialAggregate(
        locations=flowmachine.features.ModalLocation(
            *[
                flowmachine.features.daily_location(
                    date=dl_date, spatial_unit=admin3_spatial_unit, method="last"
                )
                for dl_date in pd.date_range("2016-01-01", "2016-01-03", freq="D")
            ]
        )
    ),
    flowmachine.features.Flows(
        flowmachine.features.daily_location(
            date="2016-01-01", spatial_unit=admin1_spatial_unit, method="last"
        ),
        flowmachine.features.daily_location(
            date="2016-01-07", spatial_unit=admin1_spatial_unit, method="last"
        ),
    ),
    flowmachine.features.TotalLocationEvents(
        start="2016-01-01",
        stop="2016-01-08",
        spatial_unit=admin3_spatial_unit,
        interval="hour",
    ),
]

# Flows above normal
date_ranges = {

spatial_unit=admin3_spatial_unit,
        interval="hour",
    ),
]

# Flows above normal
date_ranges = {
    "benchmark": pd.date_range("2016-01-01", "2016-01-21", freq="D"),
    "comparison": pd.date_range("2016-01-21", "2016-02-10", freq="D"),
    "focal": pd.date_range("2016-02-10", "2016-02-28", freq="D"),
}
flows_above_normal_queries = [
    flowmachine.features.utilities.spatial_aggregates.SpatialAggregate(
        locations=flowmachine.features.ModalLocation(
            *[
                flowmachine.features.daily_location(
                    date=dl_date.strftime("%Y-%m-%d"),
                    spatial_unit=admin3_spatial_unit,
                    method="last",
                )
                for dl_date in dates
            ]
        )
    )
    for dates in date_ranges.values()
] + [
    flowmachine.features.Flows(
        flowmachine.features.ModalLocation(
            *[
                flowmachine.features.daily_location(
                    date=dl_date.strftime("%Y-%m-%d"),
                    spatial_unit=admin3_spatial_unit,