def test_post_process_location_calc_with_zero_value_entry(self):
unit_type = IndicatorBlueprint.PERCENTAGE
calc_type = IndicatorBlueprint.SUM
display_type = IndicatorBlueprint.RATIO
blueprint = RatioTypeIndicatorBlueprintFactory(
unit=unit_type,
calculation_formula_across_locations=calc_type,
calculation_formula_across_periods=calc_type,
display_type=display_type,
)
partneractivity_reportable = RatioReportableToPartnerActivityProjectContextFactory(
content_object=self.project_context, blueprint=blueprint)
partneractivity_reportable.disaggregations.clear()
add_disaggregations_to_reportable(
partneractivity_reportable,
disaggregation_targets=["age", "gender", "height"])
LocationWithReportableLocationGoalFactory(
location=self.loc1,
reportable=partneractivity_reportable,
)
ir = ClusterIndicatorReportFactory(
reportable=partneractivity_reportable,
report_status=INDICATOR_REPORT_STATUS.due,
)
# Creating Level-3 disaggregation location data for all locations
generate_3_num_disagg_data(partneractivity_reportable,
indicator_type="ratio")
loc_data1 = ir.indicator_location_data.first()
# Mark some data entries on location data 1 to be zero
level_reported_3_key = None
tuple_disaggregation = get_cast_dictionary_keys_as_tuple(
loc_data1.disaggregation)
for key in tuple_disaggregation:
if len(key) == 3:
level_reported_3_key = key
break
validated_data = copy.deepcopy(loc_data1.disaggregation)
old_totals = validated_data['()']
loc_data1.disaggregation[str(level_reported_3_key)]['d'] = 0
loc_data1.disaggregation[str(level_reported_3_key)]['v'] = 0
loc_data1.disaggregation[str(level_reported_3_key)]['c'] = 0
loc_data1.save()
RatioIndicatorDisaggregator.post_process(loc_data1)
self.assertNotEqual(old_totals['c'],
loc_data1.disaggregation['()']['c'])
def test_post_process_reporting_period_percentage_calc(self):
unit_type = IndicatorBlueprint.PERCENTAGE
calc_type = IndicatorBlueprint.SUM
display_type = IndicatorBlueprint.RATIO
blueprint = RatioTypeIndicatorBlueprintFactory(
unit=unit_type,
calculation_formula_across_locations=calc_type,
calculation_formula_across_periods=calc_type,
display_type=display_type,
)
partneractivity_reportable = RatioReportableToPartnerActivityProjectContextFactory(
content_object=self.project_context, blueprint=blueprint)
partneractivity_reportable.disaggregations.clear()
add_disaggregations_to_reportable(
partneractivity_reportable,
disaggregation_targets=["age", "gender", "height"])
LocationWithReportableLocationGoalFactory(
location=self.loc1,
reportable=partneractivity_reportable,
)
LocationWithReportableLocationGoalFactory(
location=self.loc2,
reportable=partneractivity_reportable,
)
for _ in range(2):
ClusterIndicatorReportFactory(
reportable=partneractivity_reportable,
report_status=INDICATOR_REPORT_STATUS.due,
)
# Creating Level-3 disaggregation location data for all locations
generate_3_num_disagg_data(partneractivity_reportable,
indicator_type="ratio")
for loc_data in IndicatorLocationData.objects.filter(
indicator_report__reportable=partneractivity_reportable):
RatioIndicatorDisaggregator.post_process(loc_data)
# Indicator total only gets calculated if it's accepted or is sent back
for ir in partneractivity_reportable.indicator_reports.all():
ir.report_status = INDICATOR_REPORT_STATUS.accepted
ir.save()
latest_accepted_indicator_report = partneractivity_reportable.indicator_reports.order_by(
'-time_period_start').first()
self.assertEquals(partneractivity_reportable.total['c'] * 100,
latest_accepted_indicator_report.total['c'] * 100)
def test_post_process_reporting_period_max_calc(self):
unit_type = IndicatorBlueprint.NUMBER
calc_type = IndicatorBlueprint.MAX
blueprint = QuantityTypeIndicatorBlueprintFactory(
unit=unit_type,
calculation_formula_across_locations=calc_type,
calculation_formula_across_periods=calc_type,
)
partneractivity_reportable = QuantityReportableToPartnerActivityProjectContextFactory(
content_object=self.project_context, blueprint=blueprint)
partneractivity_reportable.disaggregations.clear()
add_disaggregations_to_reportable(
partneractivity_reportable,
disaggregation_targets=["age", "gender", "height"])
LocationWithReportableLocationGoalFactory(
location=self.loc1,
reportable=partneractivity_reportable,
)
LocationWithReportableLocationGoalFactory(
location=self.loc2,
reportable=partneractivity_reportable,
)
for _ in range(2):
ClusterIndicatorReportFactory(
reportable=partneractivity_reportable,
report_status=INDICATOR_REPORT_STATUS.due,
)
# Creating Level-3 disaggregation location data for all locations
generate_3_num_disagg_data(partneractivity_reportable,
indicator_type="quantity")
report_total = 0
for loc_data in IndicatorLocationData.objects.filter(
indicator_report__reportable=partneractivity_reportable):
QuantityIndicatorDisaggregator.post_process(loc_data)
# Indicator total only gets calculated if it's accepted or is sent back
for ir in partneractivity_reportable.indicator_reports.all():
ir.report_status = INDICATOR_REPORT_STATUS.accepted
ir.save()
if ir.total['c'] > report_total:
report_total = ir.total['c']
self.assertEquals(partneractivity_reportable.total['c'], report_total)
def test_post_process_location_percentage_calc(self):
unit_type = IndicatorBlueprint.PERCENTAGE
calc_type = IndicatorBlueprint.SUM
display_type = IndicatorBlueprint.PERCENTAGE
blueprint = RatioTypeIndicatorBlueprintFactory(
unit=unit_type,
calculation_formula_across_locations=calc_type,
calculation_formula_across_periods=calc_type,
display_type=display_type,
)
partneractivity_reportable = RatioReportableToPartnerActivityProjectContextFactory(
content_object=self.project_context, blueprint=blueprint)
partneractivity_reportable.disaggregations.clear()
add_disaggregations_to_reportable(
partneractivity_reportable,
disaggregation_targets=["age", "gender", "height"])
LocationWithReportableLocationGoalFactory(
location=self.loc1,
reportable=partneractivity_reportable,
)
LocationWithReportableLocationGoalFactory(
location=self.loc2,
reportable=partneractivity_reportable,
)
ir = ClusterIndicatorReportFactory(
reportable=partneractivity_reportable,
report_status=INDICATOR_REPORT_STATUS.due,
)
# Creating Level-3 disaggregation location data for all locations
generate_3_num_disagg_data(partneractivity_reportable,
indicator_type="ratio")
v_total = 0
d_total = 0
for loc_data in ir.indicator_location_data.all():
RatioIndicatorDisaggregator.post_process(loc_data)
v_total += loc_data.disaggregation['()']['v']
d_total += loc_data.disaggregation['()']['d']
ratio_value = v_total / (d_total * 1.0)
self.assertEquals(ir.total['c'], ratio_value * 100)
def test_post_process_location_avg_calc(self):
unit_type = IndicatorBlueprint.NUMBER
calc_type = IndicatorBlueprint.AVG
blueprint = QuantityTypeIndicatorBlueprintFactory(
unit=unit_type,
calculation_formula_across_locations=calc_type,
)
partneractivity_reportable = QuantityReportableToPartnerActivityProjectContextFactory(
content_object=self.project_context, blueprint=blueprint)
partneractivity_reportable.disaggregations.clear()
add_disaggregations_to_reportable(
partneractivity_reportable,
disaggregation_targets=["age", "gender", "height"])
LocationWithReportableLocationGoalFactory(
location=self.loc1,
reportable=partneractivity_reportable,
)
LocationWithReportableLocationGoalFactory(
location=self.loc2,
reportable=partneractivity_reportable,
)
ir = ClusterIndicatorReportFactory(
reportable=partneractivity_reportable,
report_status=INDICATOR_REPORT_STATUS.due,
)
# Creating Level-3 disaggregation location data for all locations
generate_3_num_disagg_data(partneractivity_reportable,
indicator_type="quantity")
avg_value = 0
for loc_data in ir.indicator_location_data.all():
QuantityIndicatorDisaggregator.post_process(loc_data)
avg_value += loc_data.disaggregation['()']['c']
avg_value /= (ir.indicator_location_data.count() * 1.0)
self.assertEquals(ir.total['c'], avg_value)
def setUp(self):
self.country = CountryFactory()
self.workspace = WorkspaceFactory(countries=[
self.country,
])
self.response_plan = ResponsePlanFactory(workspace=self.workspace)
self.cluster = ClusterFactory(type='cccm',
response_plan=self.response_plan)
self.loc_type = GatewayTypeFactory(country=self.country)
self.carto_table = CartoDBTableFactory(location_type=self.loc_type,
country=self.country)
self.loc1 = LocationFactory(gateway=self.loc_type,
carto_db_table=self.carto_table)
self.loc2 = LocationFactory(gateway=self.loc_type,
carto_db_table=self.carto_table)
self.unicef_officer = PersonFactory()
self.unicef_focal_point = PersonFactory()
self.partner_focal_point = PersonFactory()
self.objective = ClusterObjectiveFactory(cluster=self.cluster,
locations=[
self.loc1,
self.loc2,
])
self.activity = ClusterActivityFactory(
cluster_objective=self.objective, locations=[self.loc1, self.loc2])
self.partner = PartnerFactory(
country_code=self.country.country_short_code)
self.user = NonPartnerUserFactory()
self.partner_user = PartnerUserFactory(partner=self.partner)
ClusterPRPRoleFactory(user=self.user,
workspace=self.workspace,
cluster=self.cluster,
role=PRP_ROLE_TYPES.cluster_imo)
IPPRPRoleFactory(user=self.partner_user,
workspace=self.workspace,
role=PRP_ROLE_TYPES.ip_authorized_officer)
IPPRPRoleFactory(user=self.partner_user,
workspace=self.workspace,
cluster=None,
role=PRP_ROLE_TYPES.cluster_member)
self.project = PartnerProjectFactory(
partner=self.partner,
clusters=[self.cluster],
locations=[self.loc1, self.loc2],
)
self.p_activity = ClusterActivityPartnerActivityFactory(
partner=self.partner,
cluster_activity=self.activity,
)
self.project_context = PartnerActivityProjectContextFactory(
project=self.project,
activity=self.p_activity,
)
self.sample_disaggregation_value_map = {
"height": ["tall", "medium", "short", "extrashort"],
"age": ["1-2m", "3-4m", "5-6m", '7-10m', '11-13m', '14-16m'],
"gender": ["male", "female", "other"],
}
blueprint = QuantityTypeIndicatorBlueprintFactory(
unit=IndicatorBlueprint.NUMBER,
calculation_formula_across_locations=IndicatorBlueprint.SUM,
calculation_formula_across_periods=IndicatorBlueprint.SUM,
)
self.partneractivity_reportable = QuantityReportableToPartnerActivityProjectContextFactory(
content_object=self.project_context, blueprint=blueprint)
LocationWithReportableLocationGoalFactory(
location=self.loc1,
reportable=self.partneractivity_reportable,
)
LocationWithReportableLocationGoalFactory(
location=self.loc2,
reportable=self.partneractivity_reportable,
)
self.pd = ProgrammeDocumentFactory(workspace=self.workspace,
partner=self.partner,
sections=[
SectionFactory(),
],
unicef_officers=[
self.unicef_officer,
],
unicef_focal_point=[
self.unicef_focal_point,
],
partner_focal_point=[
self.partner_focal_point,
])
for idx in range(2):
qpr_period = QPRReportingPeriodDatesFactory(
programme_document=self.pd)
ProgressReportFactory(
start_date=qpr_period.start_date,
end_date=qpr_period.end_date,
due_date=qpr_period.due_date,
report_number=idx + 1,
report_type=qpr_period.report_type,
is_final=False,
programme_document=self.pd,
submitted_by=self.user,
submitting_user=self.user,
)
for idx in range(6):
hr_period = HRReportingPeriodDatesFactory(
programme_document=self.pd)
ProgressReportFactory(
start_date=hr_period.start_date,
end_date=hr_period.end_date,
due_date=hr_period.due_date,
report_number=idx + 1,
report_type=hr_period.report_type,
is_final=False,
programme_document=self.pd,
submitted_by=self.user,
submitting_user=self.user,
)
self.cp_output = PDResultLinkFactory(programme_document=self.pd, )
self.llo = LowerLevelOutputFactory(cp_output=self.cp_output, )
self.llo_reportable = QuantityReportableToLowerLevelOutputFactory(
content_object=self.llo,
blueprint=QuantityTypeIndicatorBlueprintFactory(
unit=IndicatorBlueprint.NUMBER,
calculation_formula_across_locations=IndicatorBlueprint.SUM,
))
self.llo_reportable.disaggregations.clear()
self.partneractivity_reportable.disaggregations.clear()
# Create the disaggregations and values in the db for all response plans
# including one for no response plan as well
for disagg_name, values in self.sample_disaggregation_value_map.items(
):
disagg = IPDisaggregationFactory(name=disagg_name)
cluster_disagg = DisaggregationFactory(
name=disagg_name, response_plan=self.response_plan)
self.llo_reportable.disaggregations.add(disagg)
self.partneractivity_reportable.disaggregations.add(cluster_disagg)
for value in values:
DisaggregationValueFactory(disaggregation=cluster_disagg,
value=value)
DisaggregationValueFactory(disaggregation=disagg, value=value)
LocationWithReportableLocationGoalFactory(
location=self.loc1,
reportable=self.llo_reportable,
)
LocationWithReportableLocationGoalFactory(
location=self.loc2,
reportable=self.llo_reportable,
)
for _ in range(2):
with patch("django.db.models.signals.ModelSignal.send", Mock()):
ClusterIndicatorReportFactory(
reportable=self.partneractivity_reportable,
report_status=INDICATOR_REPORT_STATUS.submitted,
)
# Creating Level-3 disaggregation location data for all locations
generate_3_num_disagg_data(self.partneractivity_reportable,
indicator_type="quantity")
for loc_data in IndicatorLocationData.objects.filter(
indicator_report__reportable=self.partneractivity_reportable):
QuantityIndicatorDisaggregator.post_process(loc_data)
for pr in self.pd.progress_reports.all():
ProgressReportIndicatorReportFactory(
progress_report=pr,
reportable=self.llo_reportable,
report_status=INDICATOR_REPORT_STATUS.submitted,
overall_status=OVERALL_STATUS.met,
)
# Creating Level-3 disaggregation location data for all locations
generate_3_num_disagg_data(self.llo_reportable,
indicator_type="quantity")
for loc_data in IndicatorLocationData.objects.filter(
indicator_report__reportable=self.llo_reportable):
QuantityIndicatorDisaggregator.post_process(loc_data)
super().setUp()
