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fixed sample in slides

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Khalim Conn-Kowlessar 2024-04-03 20:02:37 +01:00
parent 519dc6cfcb
commit 47ebf866ee
3 changed files with 55 additions and 20 deletions
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1
backend/app/plan/router.py
View file

@ -389,7 +389,6 @@ async def trigger_plan(body: PlanTriggerRequest):
# Commit final changes # Commit final changes
session.commit() session.commit()
except IntegrityError: except IntegrityError:
logger.error("Database integrity error occurred", exc_info=True) logger.error("Database integrity error occurred", exc_info=True)
session.rollback() session.rollback()

35
etl/customers/gla_croydon_demo/slides.py
View file

@ -28,20 +28,22 @@ SAP_TARGET_2 = 100
CUSTOMER_KEY = "gla-demo" CUSTOMER_KEY = "gla-demo"
# Sample UPRNS # Sample UPRNS
archetype_1_sample = ['100020618076', '100020619814', '100020581792', '100020671205', '100020585305', '100020606853', archetype_1_sample = ['100020604138', '200001192253', '100020581792', '100020576940', '200001187196', '100020618060',
'100020625813', '100020618042', '200001188304', '200001187196', '100020603026', '100020604138', '100020625813', '100020578756', '100020618076', '200001187197', '100020619814', '100020617489',
'100020615039', '200001188299', '100020618060', '200001192253'] '100020588913']
archetype_2_sample = ['100020616325', '100020665634', '100020665654', '100020665638', '100020587936', '100020587905', archetype_2_sample = ['100020585002', '100020615603', '100020665652', '100020626800', '100020624347', '100020624348',
'100020665645', '100020625597', '100022907528', '100020665630', '100020624348', '10001008257', '100020576459', '10001007455', '100020666716', '100020609610', '100020625451', '100020625597',
'100020666735', '100020698027', '100020624351', '100020665656', '100020666716', '100020665632', '100020624351', '100020665634', '100020624350', '100020665640', '100020665632', '100022917303',
'100020666715', '100020645639', '200001191309', '100020625451', '100020624347', '100020665658', '100020665656', '10014055968', '100020630285', '100020665638', '100020616325', '100020637405',
'100020585002', '100022917303', '100020665650', '100020667737', '100020620659', '100022904981', '100020698027', '100020657902', '100020688226', '100020653786', '100020642337', '100020665643']
'100020642337', '100020657902', '100020615603', '100020626800', '100020665647', '100020665643']
archetype_3_sample = ['100020607980', '200001193193', '100020581690', '100020665611'] archetype_3_sample = ['100020594652', '100020697787', '100020577523', '100020633162', '100020601138', '100020595611',
archetype_4_sample = ['100020631683', '100020607667', '100020660228', '100020605116', '200001187539', '100020582907', '100020597485', '100020614883', '100020605342', '100020654671', '100020575611', '100020607980',
'100020610165', '100020650607', '100020655500', '100020598277', '100020642537'] '200001185785', '100020616446', '100020692380']
archetype_4_sample = ['100020596436', '100020610165', '200001187539', '100020655500', '100020582907', '100020598277',
'100020650607', '100020605116', '100020650603']
def scenario_1(): def scenario_1():
@ -182,10 +184,11 @@ def make_sample():
asset_list = pd.DataFrame(asset_list) asset_list = pd.DataFrame(asset_list)
# From the asset list, we deduce how many properties we need # From the asset list, we deduce how many properties we need
archetype_1_sample_size = 16 # Need to figure out the sizes
archetype_2_sample_size = 36 archetype_1_sample_size = 13
archetype_3_sample_size = 4 archetype_2_sample_size = 30
archetype_4_sample_size = 11 archetype_3_sample_size = 15
archetype_4_sample_size = 9
# We take the sample and we'll keep the uprns static # We take the sample and we'll keep the uprns static
archetype_1_sample = asset_list[ archetype_1_sample = asset_list[

39
recommendations/HeatingRecommender.py
View file

@ -4,6 +4,7 @@ from recommendations.Costs import Costs
from recommendations.recommendation_utils import check_simulation_difference from recommendations.recommendation_utils import check_simulation_difference
from backend.Property import Property from backend.Property import Property
from etl.epc_clean.epc_attributes.MainheatAttributes import MainHeatAttributes from etl.epc_clean.epc_attributes.MainheatAttributes import MainHeatAttributes
from etl.epc_clean.epc_attributes.HotWaterAttributes import HotWaterAttributes
from recommendations.HeatingControlRecommender import HeatingControlRecommender from recommendations.HeatingControlRecommender import HeatingControlRecommender
@ -35,7 +36,14 @@ class HeatingRecommender:
return return
# if the property has mains heating with boiler and radiators, we recommend optimal heating controls # if the property has mains heating with boiler and radiators, we recommend optimal heating controls
if self.property.main_heating["clean_description"] in ["Boiler and radiators, mains gas"]: has_boiler = self.property.main_heating["clean_description"] in ["Boiler and radiators, mains gas"]
# We also check that the property doesn't have a heating system, but it has access to the mains gas
no_heating_has_mains = self.property.main_heating["clean_description"] in [
'No system present, electric heaters assumed'
] and self.property.data["mains-gas-flag"]
if has_boiler or no_heating_has_mains:
self.recommend_boiler_upgrades(phase=phase) self.recommend_boiler_upgrades(phase=phase)
return return
@ -254,12 +262,37 @@ class HeatingRecommender:
) )
# If heating and hot water come from the mains, we need a combi boiler, otherwise we need a regular boiler # If heating and hot water come from the mains, we need a combi boiler, otherwise we need a regular boiler
is_combi = self.property.hotwater["clean_description"] in ["From main system"] hotwater_from_mains = self.property.hotwater["clean_description"] in ["From main system"]
access_to_mains_no_system = self.property.main_heating["clean_description"] in [
'No system present, electric heaters assumed'
] and self.property.data["mains-gas-flag"]
is_combi = hotwater_from_mains or access_to_mains_no_system
if is_combi: if is_combi:
description = "Upgrade to a low carbon combi boiler" description = "Upgrade to a low carbon combi boiler"
else: else:
description = "Upgrade to a low carbon boiler" description = "Upgrade to a low carbon boiler"
simulation_config = {"mainheat_energy_eff_ending": "Good"}
if access_to_mains_no_system:
# Installation of a boiler improves the hot water system so we need to reflect this in
# the outcome of the recommendation
heating_ending_config = MainHeatAttributes("Boiler and radiators, mains gas").process()
hotwater_ending_config = HotWaterAttributes("From main system").process()
heating_simulation_config = check_simulation_difference(
new_config=heating_ending_config, old_config=self.property.main_heating
)
hotwater_simulation_config = check_simulation_difference(
new_config=hotwater_ending_config, old_config=self.property.hotwater
)
simulation_config = {
**simulation_config,
**heating_simulation_config,
**hotwater_simulation_config,
"hot_water_energy_eff_ending": "Good"
}
self.recommendations.append( self.recommendations.append(
{ {
"phase": recommendation_phase, "phase": recommendation_phase,
@ -271,7 +304,7 @@ class HeatingRecommender:
"starting_u_value": None, "starting_u_value": None,
"new_u_value": None, "new_u_value": None,
"sap_points": None, "sap_points": None,
"simulation_config": {"mainheat_energy_eff_ending": "Good"}, "simulation_config": simulation_config,
**self.costs.low_carbon_boiler(is_combi=is_combi, size=f"{boiler_size}kw") **self.costs.low_carbon_boiler(is_combi=is_combi, size=f"{boiler_size}kw")
} }
) )