def test_is_above_threshold(self):
group = DefinitionGroup(
name="G2",
model=None,
cycle="",
selected_fields=["consumption"],
selected_formulations=[],
sample_formulation_model_overridden={},
sample_formulation_model_overrides={},
aggregation=sum_comparison,
has_factors=None,
factors=None,
has_thresholds=True,
thresholds={
u"abc3tc-paed": 10, u"efv200-paed": 10, u"tdf3tcefv-adult": "200"
},
)
result = GroupResult(
group=group,
values=None,
factored_records=[],
aggregate=500.0,
tracer=Tracer.F1(),
)
self.assertEqual(result.is_above_threshold(), True)
def test_groups_have_insufficient_data_if_the_aggregate_is_below_the_threshold(
self):
group1 = DefinitionGroup(
name="G1",
model=None,
cycle=current_cycle,
selected_fields=["consumption"],
selected_formulations=[],
sample_formulation_model_overridden={},
sample_formulation_model_overrides={},
aggregation=sum_comparison,
has_factors=None,
factors=None,
has_thresholds=True,
thresholds={
u"abc3tc-paed": 10,
u"efv200-paed": 10,
u"tdf3tcefv-adult": 200
},
)
group2 = DefinitionGroup(
name="G2",
model=None,
cycle=previous_cycle,
selected_fields=["consumption"],
selected_formulations=[],
sample_formulation_model_overridden={},
sample_formulation_model_overrides={},
aggregation=sum_comparison,
has_factors=None,
factors=None,
has_thresholds=True,
thresholds={
u"abc3tc-paed": 10,
u"efv200-paed": 10,
u"tdf3tcefv-adult": 200
},
)
result1 = GroupResult(
group=group1,
values=None,
factored_records=[r1],
aggregate=50.0,
tracer=tracer,
)
result2 = GroupResult(
group=group2,
values=None,
factored_records=[r2],
aggregate=40.0,
tracer=tracer,
)
self.assertFalse(Comparison().groups_have_adequate_data(
[result1, result2]))
def _group_values_from_db(self, group, cycle, sample_location, tracer):
model = group.model.as_model()
if group.has_overrides:
model_id = group.sample_formulation_model_overrides.get(
tracer.key, {}).get("id", None)
if model_id:
model = group.model.as_model(model_id)
if model:
formulations = self.get_formulations(group, tracer)
db_records = model.objects.filter(
name=sample_location["name"],
cycle=parse_cycle(cycle, group),
district=sample_location["district"],
formulation__in=formulations,
).values_list("formulation", *group.selected_fields)
records = [
DataRecord(formulation=r[0],
fields=group.selected_fields,
values=r[1:]) for r in db_records
]
factored_values = get_factored_records(group.factors, records)
return GroupResult(
group=group,
values=records,
factored_records=factored_values,
tracer=tracer,
aggregate=self.aggregate_values(group, factored_values),
)
def _group_values_from_location_data(self, group, facility_data,
other_facility_data, tracer):
data_source = other_facility_data if group.cycle and group.cycle.id == "Previous" else facility_data
records = self.get_records_from_data_source(data_source, group)
if records:
formulations = self.get_formulations(group, tracer)
data_records = self.get_values_from_records(
records, formulations, group.selected_fields)
factored_records = get_factored_records(group.factors,
data_records)
return GroupResult(
group=group,
values=data_records,
factored_records=factored_records,
tracer=tracer,
aggregate=self.aggregate_values(group, factored_records),
)
return GroupResult(group=group,
values=[],
factored_records=[],
tracer=tracer,
aggregate=None)