def test_min_value_quantities(self):
rule = Rule.objects.create(name='min_str_rule', data_type=Rule.TYPE_EUI, min=10, max=100, units='kBtu/ft**2/year')
self.assertTrue(rule.minimum_valid(15))
self.assertTrue(rule.minimum_valid('15'))
self.assertTrue(rule.maximum_valid(15))
self.assertTrue(rule.maximum_valid('15'))
self.assertFalse(rule.minimum_valid(5))
self.assertFalse(rule.minimum_valid('5'))
self.assertFalse(rule.maximum_valid(150))
self.assertFalse(rule.maximum_valid('150'))
# All of these should value since they are less than 10 (e.g. 5 kbtu/m2/year =~ 0.5 kbtu/ft2/year)
# different units on check data
self.assertFalse(rule.minimum_valid(ureg.Quantity(5, "kBtu/ft**2/year")))
self.assertFalse(rule.minimum_valid(ureg.Quantity(5, "kBtu/m**2/year"))) # ~ 0.5 kbtu/ft2/year
self.assertFalse(rule.maximum_valid(ureg.Quantity(110, "kBtu/ft**2/year")))
self.assertFalse(rule.maximum_valid(ureg.Quantity(1100, "kBtu/m**2/year"))) # ~ 102.2 kbtu/ft2/year
# these should all pass
self.assertTrue(rule.minimum_valid(ureg.Quantity(10, "kBtu/ft**2/year")))
self.assertTrue(rule.minimum_valid(ureg.Quantity(110, "kBtu/m**2/year"))) # 10.22 kbtu/ft2/year
# test the rule with different units
rule = Rule.objects.create(name='min_str_rule', data_type=Rule.TYPE_EUI, min=10, max=100, units='kBtu/m**2/year')
self.assertFalse(rule.minimum_valid(ureg.Quantity(0.05, "kBtu/ft**2/year"))) # ~ 0.538 kbtu/m2/year
self.assertFalse(rule.maximum_valid(ureg.Quantity(15, "kBtu/ft**2/year"))) # ~ 161 kbtu/m2/year
self.assertFalse(rule.minimum_valid(ureg.Quantity(5, "kBtu/m**2/year")))
self.assertFalse(rule.maximum_valid(ureg.Quantity(110, "kBtu/m**2/year")))
def test_incorrect_pint_unit_conversions(self):
rule = Rule.objects.create(name='min_str_rule', data_type=Rule.TYPE_EUI, min=10, max=100, units='ft**2')
# this should error out nicely
with self.assertRaises(UnitMismatchError):
self.assertFalse(rule.minimum_valid(ureg.Quantity(5, "kBtu/ft**2/year")))
with self.assertRaises(UnitMismatchError):
self.assertFalse(rule.maximum_valid(ureg.Quantity(5, "kBtu/ft**2/year")))
def setUp(self):
user_details = {
'username': '******',
'password': '******',
'email': '*****@*****.**',
'first_name': 'Test',
'last_name': 'User',
}
self.user = User.objects.create_user(**user_details)
self.org_a, _, _ = create_organization(self.user)
self.org_b, _, _ = create_organization(self.user)
cycle_a = FakeCycleFactory(organization=self.org_a, user=self.user).get_cycle(name="Cycle Org A")
cycle_b = FakeCycleFactory(organization=self.org_b, user=self.user).get_cycle(name="Cycle Org B")
self.analysis_a = (
FakeAnalysisFactory(organization=self.org_a, user=self.user).get_analysis(
name='Quite neat',
service=Analysis.BSYNCR,
)
)
view_factory_a = FakePropertyViewFactory(cycle=cycle_a, organization=self.org_a, user=self.user)
self.property_views_a = [
view_factory_a.get_property_view(
# override unitted fields so that hashes are correct
site_eui=ureg.Quantity(
float(view_factory_a.fake.random_int(min=50, max=600)),
"kilobtu / foot ** 2 / year"
),
gross_floor_area=ureg.Quantity(
float(view_factory_a.fake.random_number(digits=6)),
"foot ** 2"
),
)
for i in range(2)]
view_factory_b = FakePropertyViewFactory(cycle=cycle_b, organization=self.org_b, user=self.user)
self.property_views_b = [
view_factory_b.get_property_view(
# override unitted fields so that hashes are correct
site_eui=ureg.Quantity(
float(view_factory_b.fake.random_int(min=50, max=600)),
"kilobtu / foot ** 2 / year"
),
gross_floor_area=ureg.Quantity(
float(view_factory_b.fake.random_number(digits=6)),
"foot ** 2"
),
)
for i in range(2)]
def test_rename_quantity_field_to_another_quantity_field_unsuccessful(
self):
# This should be unsuccessful because conversions don't exist between certain column units
expected_data = []
original_column_count = Column.objects.count()
new_col_name = 'site_eui'
for i in range(1, 5):
area = i * 100.5
self.property_state_factory.get_property_state(
data_state=DATA_STATE_MATCHING, gross_floor_area=area)
# Capture these pre-rename-attempt values
expected_data.append(ureg.Quantity(area, "foot ** 2"))
old_column = Column.objects.filter(
column_name='gross_floor_area').first()
result = old_column.rename_column(new_col_name, force=True)
self.assertEqual(result, [
False,
"The column data can't be converted to the new column due to conversion contraints (e.g., converting square feet to kBtu etc.)."
])
new_column_count = Column.objects.count()
self.assertEqual(original_column_count, new_column_count)
# check that the states' gross_floor_area values were unchanged
results = list(
PropertyState.objects.filter(
organization=self.org).order_by('id').values_list(
'gross_floor_area', flat=True))
self.assertListEqual(results, expected_data)
def test_rename_quantity_field_to_another_quantity_field_success(self):
expected_data = []
new_col_name = 'occupied_floor_area'
for i in range(1, 5):
area = i * 100.5
self.property_state_factory.get_property_state(
data_state=DATA_STATE_MATCHING, gross_floor_area=area)
# Capture the magnitude with default occupied_floor_area units
expected_data.append(ureg.Quantity(area, "foot ** 2"))
old_column = Column.objects.filter(
column_name='gross_floor_area').first()
result = old_column.rename_column(new_col_name, force=True)
self.assertTrue(result)
results = list(
PropertyState.objects.filter(
organization=self.org).order_by('id').values_list(new_col_name,
flat=True))
self.assertListEqual(results, expected_data)
# Check that gross_floor_areas were cleared
for p in PropertyState.objects.all():
self.assertIsNone(p.gross_floor_area)
def test_rename_extra_data_field_to_quantity_field_unsuccessful(self):
expected_data = []
original_column_count = Column.objects.count()
new_col_name = 'gross_floor_area'
for i in range(0, 2):
# add a valid and invalid area
area = (100 if i == 0 else "not a number")
state = self.property_state_factory.get_property_state(
data_state=DATA_STATE_MATCHING,
extra_data={self.extra_data_column.column_name: area})
# Capture default gross_floor_areas
expected_data.append(
ureg.Quantity(state.gross_floor_area, "foot ** 2"))
result = self.extra_data_column.rename_column(new_col_name, force=True)
self.assertEqual(result, [
False,
"The column data aren't formatted properly for the new column due to type constraints (e.g., Datatime, Quantities, etc.)."
])
new_column_count = Column.objects.count()
self.assertEqual(original_column_count, new_column_count)
# check that the states' gross_floor_area values were unchanged
results = list(
PropertyState.objects.filter(
organization=self.org).order_by('id').values_list(
'gross_floor_area', flat=True))
self.assertListEqual(results, expected_data)
def create_travel_distances(new=False):
# run to create travel details for the divisions
if new:
TravelDetails.objects.all().delete()
for division_a in CountryDivision.objects.all():
for division_b in CountryDivision.objects.all().annotate(
_distance=Distance(Centroid('geom'), Centroid(
division_a.geom))):
d = ureg.Quantity(division_b._distance.mi * ureg.mi)
td = TravelDetails(distance=d, destination=division_a)
td.save()
division_b.distances.add(td)
division_b.save()
print(td)
def test_rename_extra_data_field_to_quantity_field_success(self):
expected_data = []
new_col_name = 'gross_floor_area'
for i in range(1, 5):
area = i * 100.5
self.property_state_factory.get_property_state(
data_state=DATA_STATE_MATCHING,
extra_data={self.extra_data_column.column_name: area})
expected_data.append(ureg.Quantity(area, "foot ** 2"))
result = self.extra_data_column.rename_column(new_col_name, force=True)
self.assertTrue(result)
results = list(
PropertyState.objects.filter(
organization=self.org).order_by('id').values_list(
'gross_floor_area', flat=True))
self.assertListEqual(results, expected_data)
def setUp(self):
user_details = {
'username': '******',
'password': '******',
'email': '*****@*****.**',
'first_name': 'Test',
'last_name': 'User',
}
self.user = User.objects.create_user(**user_details)
self.org, _, _ = create_organization(self.user)
property_state = (
FakePropertyStateFactory(organization=self.org).get_property_state(
# fields required for analysis
latitude=39.76550841416409,
longitude=-104.97855661401148))
self.analysis_property_view = (
FakeAnalysisPropertyViewFactory(
organization=self.org,
user=self.user).get_analysis_property_view(
property_state=property_state,
# analysis args
name='Quite neat',
service=Analysis.BSYNCR,
))
self.meter = Meter.objects.create(
property=self.analysis_property_view.property,
source=Meter.PORTFOLIO_MANAGER,
source_id="Source ID",
type=Meter.ELECTRICITY_GRID,
)
tz_obj = timezone(TIME_ZONE)
self.meter_reading = MeterReading.objects.create(
meter=self.meter,
start_time=make_aware(datetime(2018, 1, 1, 0, 0, 0),
timezone=tz_obj),
end_time=make_aware(datetime(2018, 1, 2, 0, 0, 0),
timezone=tz_obj),
reading=12345,
source_unit='kWh',
conversion_factor=1.00)
#
# Setup more properties with linked meters with 12 valid meter readings.
# These properties, unmodified, should successfully run thorugh the bsyncr pipeline
#
property_view_factory = FakePropertyViewFactory(organization=self.org)
self.good_property_views = []
self.num_good_property_views = 3
for i in range(self.num_good_property_views):
pv = property_view_factory.get_property_view(
# fields required for analysis
latitude=39.76550841416409,
longitude=-104.97855661401148,
# override unitted fields so that hashes are correct
site_eui=ureg.Quantity(
float(
property_view_factory.fake.random_int(min=50,
max=600)),
"kilobtu / foot ** 2 / year"),
gross_floor_area=ureg.Quantity(
float(property_view_factory.fake.random_number(digits=6)),
"foot ** 2"),
)
self.good_property_views.append(pv)
self.analysis_b = (FakeAnalysisFactory(organization=self.org,
user=self.user).get_analysis(
name='Good Analysis',
service=Analysis.BSYNCR))
self.good_meters = []
for i in range(self.num_good_property_views):
self.good_meters.append(
Meter.objects.create(
property=self.good_property_views[i].property,
source=Meter.PORTFOLIO_MANAGER,
source_id="Source ID",
type=Meter.ELECTRICITY_GRID,
))
tz_obj = timezone(TIME_ZONE)
for j in range(1, 13):
MeterReading.objects.create(
meter=self.good_meters[i],
start_time=make_aware(datetime(2019, j, 1, 0, 0, 0),
timezone=tz_obj),
end_time=make_aware(datetime(2019, j, 28, 0, 0, 0),
timezone=tz_obj),
reading=12345,
source_unit='kWh',
conversion_factor=1.00)