def test_close_time_only(self):
dycast_parameters = test_helper_functions.get_dycast_parameters()
risk_service = risk_service_module.RiskService(dycast_parameters)
comparative_test_service = comparative_test_service_module.ComparativeTestService(
dycast_parameters)
session = database_service.get_sqlalchemy_session()
riskdate = datetime.date(int(2016), int(3), int(25))
gridpoints = geography_service.generate_grid(dycast_parameters)
clusters_per_point_query = risk_service.get_clusters_per_point_query(
session, gridpoints, riskdate)
clusters_per_point = risk_service.get_clusters_per_point_from_query(
clusters_per_point_query)
risk_service.enrich_clusters_per_point_with_close_space_and_time(
clusters_per_point)
# Compare to old query
daily_cases_query = comparative_test_service.get_daily_cases_query(
session, riskdate)
for point in gridpoints:
cases_in_cluster_query = comparative_test_service.get_cases_in_cluster_query(
daily_cases_query, point)
count_old = comparative_test_service.get_close_time_only(
cases_in_cluster_query)
for cluster in clusters_per_point:
if cluster.point.equals(
geography_service.get_shape_from_sqlalch_element(
point)):
self.assertEqual(cluster.close_in_time, count_old)
def test_get_clusters_per_point_query(self):
dycast_parameters = test_helper_functions.get_dycast_parameters(
large_dataset=False)
risk_service = risk_service_module.RiskService(dycast_parameters)
comparative_test_service = comparative_test_service_module.ComparativeTestService(
dycast_parameters)
session = database_service.get_sqlalchemy_session()
riskdate = datetime.date(int(2016), int(3), int(25))
gridpoints = geography_service.generate_grid(dycast_parameters)
clusters_per_point_query = risk_service.get_clusters_per_point_query(
session, gridpoints, riskdate)
clusters_per_point = risk_service.get_clusters_per_point_from_query(
clusters_per_point_query)
daily_cases_query = comparative_test_service.get_daily_cases_query(
session, riskdate)
for cluster in clusters_per_point:
point_wkt_element = geography_service.get_wktelement_from_wkt(
cluster.point.wkt)
cases_in_cluster_query = comparative_test_service.get_cases_in_cluster_query(
daily_cases_query, point_wkt_element)
vector_count_new = cluster.get_case_count()
vector_count_old = database_service.get_count_for_query(
cases_in_cluster_query)
self.assertEqual(vector_count_new, vector_count_old)
def test_insert_risk(self):
dycast_parameters = test_helper_functions.get_dycast_parameters()
risk_service = risk_service_module.RiskService(dycast_parameters)
session = database_service.get_sqlalchemy_session()
gridpoints = geography_service.generate_grid(dycast_parameters)
point = geography_service.get_shape_from_sqlalch_element(gridpoints[0])
risk = Risk(risk_date=datetime.date(int(2016), int(3), int(25)),
number_of_cases=5,
lat=point.x,
long=point.y,
close_pairs=3,
close_space=2,
close_time=1,
cumulative_probability=0.032)
session.query(Risk.risk_date).filter(Risk.risk_date == risk.risk_date,
Risk.lat == risk.lat,
Risk.long == risk.long) \
.delete()
risk_service.insert_risk(session, risk)
session.commit()
session.query(Risk.risk_date).filter(Risk.risk_date == risk.risk_date,
Risk.lat == risk.lat,
Risk.long == risk.long) \
.one()
def test_generate_grid(self):
dycast_paramaters = dycast_parameters.DycastParameters()
dycast_paramaters.srid_of_extent = "29193"
dycast_paramaters.extent_min_x = 197457.283284349
dycast_paramaters.extent_min_y = 7639474.3256114
dycast_paramaters.extent_max_x = 198056.722079
dycast_paramaters.extent_max_y = 7639344.265401
gridpoints = geography_service.generate_grid(dycast_paramaters)
self.assertIsNotNone(gridpoints)
self.assertGreaterEqual(len(gridpoints), 1)
def test_close_time_only_old(self):
dycast_parameters = test_helper_functions.get_dycast_parameters()
comparative_test_service = comparative_test_service_module.ComparativeTestService(
dycast_parameters)
session = database_service.get_sqlalchemy_session()
riskdate = datetime.date(int(2016), int(3), int(25))
gridpoints = geography_service.generate_grid(dycast_parameters)
point = gridpoints[0]
daily_cases_query = comparative_test_service.get_daily_cases_query(
session, riskdate)
cases_in_cluster_query = comparative_test_service.get_cases_in_cluster_query(
daily_cases_query, point)
count = comparative_test_service.get_close_time_only(
cases_in_cluster_query)
self.assertGreater(count, 0)
def generate_risk(self):
session = database_service.get_sqlalchemy_session()
logging_service.display_current_parameter_set(self.dycast_parameters)
case_threshold = self.dycast_parameters.case_threshold
gridpoints = geography_service.generate_grid(self.dycast_parameters)
day = self.dycast_parameters.startdate
delta = datetime.timedelta(days=1)
while day <= self.dycast_parameters.enddate:
start_time = time.time()
logging.info("Starting daily_risk for %s", day)
points_above_threshold = 0
clusters_per_point_query = self.get_clusters_per_point_query(session, gridpoints, day)
clusters_per_point = self.get_clusters_per_point_from_query(clusters_per_point_query)
for cluster in clusters_per_point:
vector_count = cluster.get_case_count()
if vector_count >= case_threshold:
points_above_threshold += 1
self.get_close_space_and_time_for_cluster(cluster)
self.get_cumulative_probability_for_cluster(session, cluster)
point = geography_service.get_point_from_lat_long(cluster.point.y, cluster.point.x, self.system_srid)
risk = Risk(risk_date=day,
number_of_cases=vector_count,
lat=cluster.point.y,
long=cluster.point.x,
location=point,
close_pairs=cluster.close_space_and_time,
close_space=cluster.close_in_space,
close_time=cluster.close_in_time,
cumulative_probability=cluster.cumulative_probability)
self.insert_risk(session, risk)
session.commit()
logging.info(
"Finished daily_risk for %s: done %s points", day, len(gridpoints))
logging.info("Total points above threshold of %s: %s",
case_threshold, points_above_threshold)
logging.info("Time elapsed: %.0f seconds",
time.time() - start_time)
day += delta
try:
session.commit()
except SQLAlchemyError as e:
session.rollback()
logging.exception("There was a problem committing the risk data session")
logging.exception(e)
raise
finally:
session.close()
def generate_risk(self):
session = database_service.get_sqlalchemy_session()
logging_service.display_current_parameter_set(self.dycast_parameters)
case_threshold = self.dycast_parameters.case_threshold
gridpoints = geography_service.generate_grid(self.dycast_parameters)
day = self.dycast_parameters.startdate
delta = datetime.timedelta(days=1)
while day <= self.dycast_parameters.enddate:
daily_cases_query = self.get_daily_cases_query(session, day)
daily_case_count = database_service.get_count_for_query(
daily_cases_query)
if daily_case_count >= case_threshold:
start_time = time.time()
logging.info("Starting daily_risk for %s", day)
points_above_threshold = 0
clusters_per_point = self.get_clusters_per_point_query(
session, gridpoints, day)
for cluster in clusters_per_point:
vector_count = len(cluster.case_array)
if vector_count >= case_threshold:
points_above_threshold += 1
point = geography_service.get_shape_from_sqlalch_element(
cluster.point)
risk = Risk(risk_date=day,
number_of_cases=vector_count,
lat=point.x,
long=point.y,
location=point)
for point in gridpoints:
cases_in_cluster_query = self.get_cases_in_cluster_query(
daily_cases_query, point)
vector_count = database_service.get_count_for_query(
cases_in_cluster_query)
if vector_count >= case_threshold:
points_above_threshold += 1
risk = Risk(risk_date=day,
number_of_cases=vector_count,
lat=point.x,
long=point.y)
risk.close_pairs = self.get_close_space_and_time(
cases_in_cluster_query)
risk.close_space = self.get_close_space_only_old(
cases_in_cluster_query) - risk.close_pairs
risk.close_time = self.get_close_time_only(
cases_in_cluster_query) - risk.close_pairs
risk.cumulative_probability = self.get_cumulative_probability(
session, risk.number_of_cases, risk.close_pairs,
risk.close_space, risk.close_time)
self.insert_risk(session, risk)
logging.info("Finished daily_risk for %s: done %s points", day,
len(gridpoints))
logging.info("Total points above threshold of %s: %s",
case_threshold, points_above_threshold)
logging.info("Time elapsed: %.0f seconds",
time.time() - start_time)
else:
logging.info(
"Amount of cases for %s lower than threshold %s: %s, skipping.",
day, case_threshold, daily_case_count)
day += delta
try:
session.commit()
except SQLAlchemyError as e:
session.rollback()
logging.exception(
"There was a problem committing the risk data session")
logging.exception(e)
raise
finally:
session.close()