def determine_risk_indicators(db):
deter_alerts = DeterRepository()
deter_hist = DeterHistoricalRepository()
startdate = datetime.datetime.now().date()
enddate = datetime.date(2017, 1, 1)
groups_repo = DeterClassGroupRepository(db)
class_groups = groups_repo.list()
units_repo = SpatialUnitInfoRepository(db)
units = units_repo.list()
for u in units:
sutablename = u.dataname
print(f'Processing {sutablename} risk indicators...')
as_attribute_name = u.as_attribute_name
surepo = SpatialUnitDynamicMapperFactory.instance()\
.create_spatial_unit(sutablename, as_attribute_name)
su = surepo.get()
uc = DetermineRiskIndicators(su, deter_alerts, deter_hist,
class_groups, startdate, enddate)
model_indicators = uc.execute()
rirepo = RiskIndicatorsRepository(sutablename, as_attribute_name, db)
rirepo.save(model_indicators)
def test_update_on_startup(mocker):
db = DataAccessHelper.createdb('postgresql://*****:*****@localhost:5432/det_autoup_onstart')
DataAccessHelper.add_class_groups(db)
susdata = [{'tablename': 'csAmz_150km',
'shpname': 'csAmz_150km_epsg_4326',
'as_attribute_name': 'id'}]
for sudata in susdata:
DataAccessHelper.add_spatial_unit(db, sudata['tablename'], sudata['shpname'])
startdate = date(2021, 2, 28)
enddate = date(2021, 1, 1)
DataAccessHelper.determine_risk_indicators(db, startdate, enddate)
deter_repo = DeterRepository()
deter_url = 'postgresql://*****:*****@localhost:5432/DETER-B'
date_now = datetime.now()
DataAccessHelper.del_deter_data(deter_url, date_now) # clean if last test fail
rirepo = RiskIndicatorsRepository(susdata[0]['tablename'], susdata[0]['as_attribute_name'], db)
indicators_1 = rirepo.list()
assert len(indicators_1) == 357
assert indicators_1[0].date.isoformat() == '2021-02-28'
assert indicators_1[0].percentage == 0.0004478673808316384
assert indicators_1[0].area == 0.10077016068752663
assert indicators_1[0].classname == 'DS'
DataAccessHelper.add_deter_data(deter_url, 5, date_now)
uc = DeterDailyUpdate(deter_repo, 1)
mocker.patch.object(DeterDailyUpdate, '_get_enddate', return_value=date(2021, 1, 1))
uc.execute(db)
assert uc.last_update() == date_now.date().isoformat()
indicators_2 = rirepo.list()
assert len(indicators_2) == 358
yesterday_indicator = get_newest_indicator(indicators_2, date_now.date())
assert yesterday_indicator.date.isoformat() == date_now.date().isoformat()
assert round(yesterday_indicator.percentage, 5) == round(0.0028141977493854964, 5)
assert round(yesterday_indicator.area, 5) == 0.63319
assert yesterday_indicator.classname == 'DS'
uc.terminate()
DataAccessHelper.del_deter_data(deter_url, date_now)
db.drop()
def test_uc_basic():
db = setdb(
'postgresql://*****:*****@localhost:5432/det_risk_uc_basic')
set_only_one_group(db)
units_repo = SpatialUnitInfoRepository(db)
units = units_repo.list()
sutablename = units[0].dataname
as_attribute_name = units[0].as_attribute_name
surepo = SpatialUnitDynamicMapperFactory.instance()\
.create_spatial_unit(sutablename, as_attribute_name)
su = surepo.get()
deter_repo = DeterRepository()
startdate = datetime.date(2021, 1, 1)
enddate = datetime.date(2020, 12, 1)
groups_repo = DeterClassGroupRepository(db)
class_groups = groups_repo.list()
uc = DetermineRiskIndicators(su, deter_repo, None, class_groups, startdate,
enddate)
model_indicators = uc.execute()
rirepo = RiskIndicatorsRepository(sutablename, as_attribute_name, db)
rirepo.save(model_indicators)
rilast = rirepo.get_most_recent()
assert rilast.date == startdate
indicators = rirepo.list()
indicators_per_feature = {}
expected_total_per_feature = determine_risk_indicators_results.total_per_feature
for ind in indicators:
if ind.feature.id not in indicators_per_feature:
indicators_per_feature[ind.feature.id] = 0
indicators_per_feature[ind.feature.id] += ind.percentage
assert len(model_indicators) == len(indicators) == 322
assert (len(indicators_per_feature) == len(expected_total_per_feature) ==
132)
for i in range(len(expected_total_per_feature)):
# print(f'{{\'id\': {i.feature.id}, \'percentage\': {i.percentage}}},')
assert expected_total_per_feature[i]['id'] in indicators_per_feature
assert (round(expected_total_per_feature[i]['percentage'], 5) == round(
indicators_per_feature[expected_total_per_feature[i]['id']], 5))
expected_per_day = determine_risk_indicators_results.percentage_per_day
gp = Geoprocessing()
for i in range(len(indicators)):
# print(f'{{\'id\': {indicators[i].feature.id}, \'percentage\': {indicators[i].percentage},'
# + f' \'area\': {indicators[i].area}, \'date\': \'{indicators[i].date}\'}},')
assert int(indicators[i].area * 100 / indicators[i].percentage)\
== int(gp.degrees_to_km2(indicators[i].feature.geom.area))
assert expected_per_day[i]['id'] == indicators[i].feature.id
assert round(expected_per_day[i]['percentage'],
5) == round(indicators[i].percentage, 5)
assert expected_per_day[i]['date'] == str(indicators[i].date)
db.drop()