def test_tno_at_lon_lat(get_dataframe):
"""
Regression test for #108. TNO should work at lon-lat level.
"""
tno = TotalNetworkObjects(
start="2016-01-01",
stop="2016-01-07",
network_object=make_spatial_unit("versioned-cell"),
spatial_unit=make_spatial_unit("lon-lat"),
)
assert tno.get_dataframe().sum().value == 330
def test_bad_params(bad_arg, bad_val):
"""Test value errors are raised for bad params"""
with pytest.raises(ValueError):
TotalNetworkObjects(start="2016-01-01",
stop="2016-12-30",
table="calls",
**{bad_arg: bad_val})
def test_bad_total_by():
"""Test value errors are raised for bad 'total_by' param"""
with pytest.raises(ValueError):
TotalNetworkObjects(
start="2016-01-01",
stop="2016-12-30",
table="calls",
total_by="BAD_TOTAL_BY",
)
def test_bad_statistic():
"""Test that invalid stat for aggregate raises value error."""
with pytest.raises(ValueError):
AggregateNetworkObjects(
total_network_objects=TotalNetworkObjects(start="2016-01-01",
stop="2016-12-30",
table="calls"),
statistic="count",
)
def test_bad_aggregate_by():
"""Test that invalid 'aggregate_by' param raises value error."""
with pytest.raises(ValueError):
AggregateNetworkObjects(
total_network_objects=TotalNetworkObjects(start="2016-01-01",
stop="2016-12-30",
table="calls"),
aggregate_by="BAD_AGGREGATE_BY",
)
def test_bad_spatial_units(bad_arg, spatial_unit_type):
"""
Test InvalidSpatialUnitErrors are raised for bad 'network_object' or
'spatial_unit' params.
"""
su = make_spatial_unit(spatial_unit_type)
with pytest.raises(InvalidSpatialUnitError):
TotalNetworkObjects(start="2016-01-01",
stop="2016-12-30",
table="calls",
**{bad_arg: su})
def _flowmachine_query_obj(self):
"""
Return the underlying flowmachine daily_location object.
Returns
-------
Query
"""
return TotalNetworkObjects(
start=self.start_date,
stop=self.end_date,
spatial_unit=get_spatial_unit_obj(self.aggregation_unit),
total_by=self.total_by,
)
def _flowmachine_query_obj(self):
"""
Return the underlying flowmachine daily_location object.
Returns
-------
Query
"""
return TotalNetworkObjects(
start=self.start_date,
stop=self.end_date,
level=self.aggregation_unit,
period=self.period,
)
def _flowmachine_query_obj(self):
"""
Return the underlying flowmachine daily_location object.
Returns
-------
Query
"""
return TotalNetworkObjects(
start=self.start_date,
stop=self.end_date,
spatial_unit=self.aggregation_unit,
total_by=self.total_by,
table=self.event_types,
subscriber_subset=self.subscriber_subset,
)
def test_count_returns_correct_values(get_dataframe):
"""
TotalNetworkObjects returns correct values.
"""
instance = TotalNetworkObjects(start="2016-01-01",
stop="2016-12-30",
table="calls",
total_by="hour")
df = get_dataframe(instance)
#
# This will compare the very first
# value with an independently
# computed value.
#
assert df.value[34] == 31
def test_median_returns_correct_values(get_dataframe):
"""
features.network.TotalNetworkObjects median aggregate returns correct values.
"""
instance = AggregateNetworkObjects(
total_network_objects=TotalNetworkObjects(
table="calls", period="hour", network_object="versioned-site"),
by="day",
statistic="median",
)
#
# This will compare the very first
# value with an independently
# computed value.
#
assert get_dataframe(instance).head(1)["median"][0] == 25
def test_aggregate_returns_correct_values(stat, expected, get_dataframe):
"""
AggregateNetworkObjects returns correct values.
"""
instance = AggregateNetworkObjects(
total_network_objects=TotalNetworkObjects(start="2016-01-01",
stop="2016-12-30",
table="calls",
total_by="hour"),
statistic=stat,
)
df = get_dataframe(instance)
#
# This will compare the very first
# value with an independently
# computed value.
#
assert pytest.approx(df.value[0]) == expected
def test_mean_returns_correct_values(get_dataframe):
"""
features.network.TotalNetworkObjects aggregation returns correct values.
"""
instance = AggregateNetworkObjects(
total_network_objects=TotalNetworkObjects(
start="2016-01-01",
stop="2016-12-30",
total_by="hour",
network_object=make_spatial_unit("versioned-site"),
),
aggregate_by="day",
)
#
# This will compare the very first
# value with an independently
# computed value.
#
assert get_dataframe(instance).head(1)["value"][0] == pytest.approx(
28.7916666666)
def test_period_agg_default(total_by, aggregate_by_expected):
"""Correct aggregation period is deduced."""
inst = AggregateNetworkObjects(total_network_objects=TotalNetworkObjects(
start="2016-01-01", stop="2016-12-30", total_by=total_by))
assert inst.aggregate_by == aggregate_by_expected