def test_error_when_not_modal_location():
"""
Test that error is raised if modal_locations is not a ModalLocation.
"""
dl = daily_location("2016-01-01", spatial_unit=make_spatial_unit("lon-lat"))
with pytest.raises(ValueError):
Displacement("2016-01-01", "2016-01-02", modal_locations=dl, statistic="avg")
def test_min_displacement_zero(get_dataframe):
"""
When time period for diplacement and home location are the same min displacement
should be zero for all subscribers
"""
df = get_dataframe(Displacement("2016-01-01", "2016-01-07", statistic="min"))
assert df.statistic.sum() == 0
def test_returns_expected_values(stat, sub_a_expected, sub_b_expected,
get_dataframe):
"""
Test that we get expected return values for the various statistics
"""
sub_a_id, sub_b_id = "j6QYNbMJgAwlVORP", "NG1km5NzBg5JD8nj"
df = get_dataframe(Displacement("2016-01-01", "2016-01-07",
statistic=stat)).set_index("subscriber")
assert df.loc[sub_a_id].statistic, pytest.approx(sub_a_expected)
assert df.loc[sub_b_id].statistic, pytest.approx(sub_b_expected)
def test_returns_expected_result_for_unit_m(get_dataframe):
"""
Test that we get expected results when unit='m'.
"""
sub_a_id, sub_b_id = "j6QYNbMJgAwlVORP", "NG1km5NzBg5JD8nj"
df = get_dataframe(
Displacement("2016-01-01", "2016-01-07", statistic="max", unit="m")
).set_index("subscriber")
assert df.loc[sub_a_id].statistic == pytest.approx(500809.349)
assert df.loc[sub_b_id].statistic == pytest.approx(387024.628)
def test_invalid_statistic_raises_error():
"""
Test that passing an invalid statistic raises an error.
"""
dl = daily_location("2016-01-01",
spatial_unit=make_spatial_unit("lon-lat"))
with pytest.raises(ValueError):
Displacement("2016-01-01",
"2016-01-07",
reference_location=dl,
statistic="BAD_STATISTIC")
def test_error_when_modal_location_not_lon_lat():
"""
Test that error is raised if home location passed to class
is not using lon-lat spatial unit
"""
ml = ModalLocation(
*[daily_location(d) for d in list_of_dates("2016-01-01", "2016-01-02")]
)
with pytest.raises(ValueError):
Displacement("2016-01-01", "2016-01-02", modal_locations=ml, statistic="avg")
def test_error_when_home_location_not_latlong():
"""
Test that error is raised if home location passed to class
is not using level lat-lon
"""
hl = HomeLocation(
*[daily_location(d) for d in list_of_dates("2016-01-01", "2016-01-02")]
)
with pytest.raises(ValueError):
Displacement("2016-01-01", "2016-01-02", home_locations=hl, statistic="avg")
def test_error_when_reference_location_is_not_a_base_location():
"""
Test that error is raised if reference_locations is not an object of type `BaseLocation`.
"""
not_an_instance_of_base_location = Mock()
with pytest.raises(ValueError):
Displacement(
"2016-01-01",
"2016-01-02",
reference_location=not_an_instance_of_base_location,
statistic="avg",
)
def test_error_when_reference_location_not_lon_lat():
"""
Test that error is raised if home location passed to class
is not using lon-lat spatial unit
"""
rl = daily_location("2016-01-01")
with pytest.raises(ValueError):
Displacement("2016-01-01",
"2016-01-02",
reference_location=rl,
statistic="avg")
def test_min_displacement_zero(get_dataframe):
"""
When time period for diplacement and home location are the same min displacement
should be zero for all subscribers
"""
rl = daily_location("2016-01-01",
spatial_unit=make_spatial_unit("lon-lat"))
df = get_dataframe(
Displacement("2016-01-01",
"2016-01-07",
reference_location=rl,
statistic="min"))
assert df.value.sum() == 0
def _unsampled_query_obj(self):
"""
Return the underlying flowmachine displacement object.
Returns
-------
Query
"""
return Displacement(
start=self.start,
stop=self.stop,
statistic=self.statistic,
reference_location=self.reference_location._flowmachine_query_obj,
subscriber_subset=self.subscriber_subset,
)
def test_subscriber_with_home_loc_but_no_calls_is_ommitted(get_dataframe):
"""
Test that a subscriber who has no activity between start and stop
but has a home location is omitted by default.
"""
p2 = ("2016-01-01 12:01:00", "2016-01-01 15:20:00")
subscriber = "OdM7np8LYEp1mkvP"
rl = daily_location("2016-01-01",
spatial_unit=make_spatial_unit("lon-lat"))
d = Displacement(*p2, reference_location=rl)
df = get_dataframe(d).set_index("subscriber")
assert subscriber not in df
def test_returns_expected_values(stat, unit, sub_a_expected, sub_b_expected,
get_dataframe):
"""
Test that we get expected return values for the various statistics
"""
sub_a_id, sub_b_id = "j6QYNbMJgAwlVORP", "NG1km5NzBg5JD8nj"
rl = daily_location("2016-01-01",
spatial_unit=make_spatial_unit("lon-lat"))
df = get_dataframe(
Displacement("2016-01-01",
"2016-01-07",
reference_location=rl,
statistic=stat,
unit=unit)).set_index("subscriber")
assert df.loc[sub_a_id].value == pytest.approx(sub_a_expected)
assert df.loc[sub_b_id].value == pytest.approx(sub_b_expected)
def test_pass_reference_location(get_dataframe):
"""
Test that we can pass a home location object to the class
"""
rl = daily_location("2016-01-01",
spatial_unit=make_spatial_unit("lon-lat"))
df = get_dataframe(
Displacement("2016-01-01",
"2016-01-07",
reference_location=rl,
statistic="avg"))
df = df.set_index("subscriber")
val = df.loc["j6QYNbMJgAwlVORP"].value
assert val == pytest.approx(370.301009034846)
def test_get_all_users_in_modal_location(get_dataframe):
"""
This tests that diplacement values are returned for all subscribers
in the home location object.
"""
p1 = ("2016-01-02 10:00:00", "2016-01-02 12:00:00")
p2 = ("2016-01-01 12:01:00", "2016-01-01 15:20:00")
hl = ModalLocation(*[
daily_location(d, level="lat-lon", hours=(12, 13))
for d in list_of_dates(p1[0], p1[1])
])
d = Displacement(p2[0], p2[1], modal_locations=hl)
hl_subscribers = set(get_dataframe(hl).subscriber)
d_subscribers = set(get_dataframe(d).subscriber)
assert not (hl_subscribers - d_subscribers)
def test_pass_modal_location(get_dataframe):
"""
Test that we can pass a home location object to the class
"""
hl = ModalLocation(*[
daily_location(d, level="lat-lon")
for d in list_of_dates("2016-01-01", "2016-01-06")
])
df = get_dataframe(
Displacement("2016-01-01",
"2016-01-07",
modal_locations=hl,
statistic="avg"))
df = df.set_index("subscriber")
val = df.loc["j6QYNbMJgAwlVORP"].statistic
assert val == pytest.approx(169.926194)
def test_subscriber_with_home_loc_but_no_calls_is_nan(get_dataframe):
"""
Test that a subscriber who has no activity between start and stop
but has a home location returns a nan value
"""
p2 = ("2016-01-01 12:01:00", "2016-01-01 15:20:00")
subscriber = "OdM7np8LYEp1mkvP"
rl = daily_location("2016-01-01",
spatial_unit=make_spatial_unit("lon-lat"))
d = Displacement(p2[0],
p2[1],
reference_location=rl,
return_subscribers_not_seen=True)
df = get_dataframe(d).set_index("subscriber")
assert isnan(df.loc[subscriber].value)
def test_subscriber_with_home_loc_but_no_calls_is_nan(get_dataframe):
"""
Test that a subscriber who has no activity between start and stop
but has a home location returns a nan value
"""
p1 = ("2016-01-02 10:00:00", "2016-01-02 12:00:00")
p2 = ("2016-01-01 12:01:00", "2016-01-01 15:20:00")
subscriber = "OdM7np8LYEp1mkvP"
hl = ModalLocation(*[
daily_location(d, level="lat-lon", hours=(12, 13))
for d in list_of_dates(p1[0], p1[1])
])
d = Displacement(p2[0], p2[1], modal_locations=hl)
df = get_dataframe(d).set_index("subscriber")
assert isnan(df.loc[subscriber].statistic)
def test_pass_modal_location(get_dataframe):
"""
Test that we can pass a home location object to the class
"""
ml = ModalLocation(
*[
daily_location(d, spatial_unit=make_spatial_unit("lon-lat"))
for d in list_of_dates("2016-01-01", "2016-01-06")
]
)
df = get_dataframe(
Displacement("2016-01-01", "2016-01-07", modal_locations=ml, statistic="avg")
)
df = df.set_index("subscriber")
val = df.loc["j6QYNbMJgAwlVORP"].statistic
assert val == pytest.approx(176.903620)
def test_get_all_users_in_reference_location(get_dataframe):
"""
This tests that displacement values are returned for all subscribers
in the home location object.
"""
p2 = ("2016-01-01 12:01:00", "2016-01-01 15:20:00")
rl = daily_location("2016-01-01",
spatial_unit=make_spatial_unit("lon-lat"))
d = Displacement(p2[0],
p2[1],
reference_location=rl,
return_subscribers_not_seen=True)
ml_subscribers = set(get_dataframe(rl).subscriber)
d_subscribers = set(get_dataframe(d).subscriber)
assert not (ml_subscribers - d_subscribers)
def test_invalid_statistic_raises_error():
"""
Test that passing an invalid statistic raises an error.
"""
with pytest.raises(ValueError):
Displacement("2016-01-01", "2016-01-07", statistic="BAD_STATISTIC")