fixed merge conflicts

This commit is contained in:
Michael Duong 2023-08-10 20:13:29 +00:00
commit abe894a94d
8 changed files with 119 additions and 259 deletions

2
.idea/Model.iml generated
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@ -7,7 +7,7 @@
<sourceFolder url="file://$MODULE_DIR$/open_uprn" isTestSource="false" />
<sourceFolder url="file://$MODULE_DIR$/recommendations" isTestSource="false" />
</content>
<orderEntry type="jdk" jdkName="Python 3.10 (model_data)" jdkType="Python SDK" />
<orderEntry type="jdk" jdkName="Python 3.10 (backend)" jdkType="Python SDK" />
<orderEntry type="sourceFolder" forTests="false" />
</component>
</module>

2
.idea/misc.xml generated
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@ -1,6 +1,6 @@
<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="ProjectRootManager" version="2" project-jdk-name="Python 3.10 (model_data)" project-jdk-type="Python SDK" />
<component name="ProjectRootManager" version="2" project-jdk-name="Python 3.10 (backend)" project-jdk-type="Python SDK" />
<component name="PythonCompatibilityInspectionAdvertiser">
<option name="version" value="3" />
</component>

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@ -0,0 +1,15 @@
from backend.app.db.connection import db_engine
from backend.app.db.models.materials import Material
from sqlalchemy.orm import sessionmaker
def get_materials():
"""
This function will retrieve all materials from the database.
:return: A list of Material objects if successful, an empty list otherwise.
"""
Session = sessionmaker(bind=db_engine)
with Session() as session:
materials = session.query(Material).all()
return materials if materials else []

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@ -0,0 +1,51 @@
import enum
from sqlalchemy import Column, Integer, String, Float, Enum, TIMESTAMP
from sqlalchemy.orm import declarative_base
from sqlalchemy.sql import func
Base = declarative_base()
class MaterialType(enum.Enum):
suspended_floor_insulation = "suspended_floor_insulation"
solid_floor_insulation = "solid_floor_insulation"
external_wall_insulation = "external_wall_insulation"
internal_wall_insulation = "internal_wall_insulation"
class DepthUnit(enum.Enum):
mm = "mm"
class CostUnit(enum.Enum):
gbp_sq_meter = "gbp_sq_meter"
class RValueUnit(enum.Enum):
square_meter_kelvin_per_watt = "square_meter_kelvin_per_watt"
class ThermalConductivityUnit(enum.Enum):
watt_per_meter_kelvin = "watt_per_meter_kelvin"
class Material(Base):
__tablename__ = 'material'
id = Column(Integer, primary_key=True, autoincrement=True)
type = Column(Enum(MaterialType, values_callable=lambda x: [e.value for e in x]), nullable=False)
description = Column(String, nullable=False)
depths = Column(String) # You may want to use a specific JSON type depending on the database
depth_unit = Column(Enum(DepthUnit, values_callable=lambda x: [e.value for e in x]), nullable=False)
cost = Column(Float)
cost_unit = Column(Enum(CostUnit, values_callable=lambda x: [e.value for e in x]), nullable=False)
r_value_per_mm = Column(Float)
r_value_unit = Column(Enum(RValueUnit, values_callable=lambda x: [e.value for e in x]), nullable=False)
thermal_conductivity = Column(Float)
thermal_conductivity_unit = Column(
Enum(ThermalConductivityUnit, values_callable=lambda x: [e.value for e in x]),
nullable=False
)
link = Column(String)
created_at = Column(TIMESTAMP, nullable=False, server_default=func.now())

18
backend/app/db/utils.py Normal file
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@ -0,0 +1,18 @@
import enum
def row2dict(row):
"""
Generic function to convert a SQLAlchemy row to a dictionary.
May not be the best practice implementing like this but works for the moment
"""
d = {}
for column in row.__table__.columns:
val = getattr(row, column.name)
if isinstance(val, enum.Enum):
val = val.value
d[column.name] = val
return d

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@ -11,17 +11,19 @@ from utils.logger import setup_logger
from recommendations.FloorRecommendations import FloorRecommendations
from recommendations.WallRecommendations import WallRecommendations
from utils.uvalue_estimates import classify_decile_newvalues
from backend.app.db.utils import row2dict
from starlette.responses import Response
# database interaction functions
from backend.app.db.functions.property_functions import (
create_property, create_property_targets, update_property_data, create_property_details_epc
)
from backend.app.db.functions.materials_functions import get_materials
# TODO: This is placeholder until data is stored in DB
from backend.app.plan.uvalue_estimates_walls import uvalue_estimates_walls
from backend.app.plan.uvalue_estimates_floors import uvalue_estimates_floors
from backend.app.plan.temp_cleaned_data import cleaned
from backend.app.plan.temp_materials_db import materials
logger = setup_logger()
@ -81,10 +83,11 @@ lighting_averages = [
]
def get_materials(materials):
def filter_materials(materials):
materials_by_type = defaultdict(list)
for material in materials:
material = row2dict(material)
material_type = material["type"]
materials_by_type[material_type].append(material)
@ -134,6 +137,9 @@ async def trigger_plan(body: PlanTriggerRequest):
)
)
if not input_properties:
return Response(status_code=204)
logger.info("Getting EPC data")
for p in input_properties:
p.search_address_epc()
@ -155,11 +161,19 @@ async def trigger_plan(body: PlanTriggerRequest):
# The materials data could be cached or local so we don't need to make
# consistent requrests to the backend for
# the same data
materials_by_type = get_materials(materials)
# TODO: It might not be the best choice to store the materials data in a database table since thi
# table probably won't be very large and won't be updated that often. It might be better to
# store this data in s3 load it into memory when the app starts up. We will test this
materials = get_materials()
materials_by_type = filter_materials(materials)
logger.info("Getting components and properties recommendations")
recommendations = []
for property_id, p in enumerate(input_properties):
recommendations = {}
for p in input_properties:
property_recommendations = []
# For each property, classiy floor area decide
total_floor_area_group_decile = classify_decile_newvalues(
decile_boundaries=floors_decile_data["decile_boundaries"],
@ -187,11 +201,8 @@ async def trigger_plan(body: PlanTriggerRequest):
total_floor_area_group_decile=total_floor_area_group_decile
)
floor_recommender.recommend()
# insert property id
for rec in floor_recommender.recommendations:
rec["property_id"] = property_id
recommendations.extend(floor_recommender.recommendations)
property_recommendations.extend(floor_recommender.recommendations)
# Wall recommendations
# We would make this u-value query directly to the database
@ -219,13 +230,12 @@ async def trigger_plan(body: PlanTriggerRequest):
materials=materials_by_type["external_wall_insulation"] + materials_by_type["internal_wall_insulation"]
)
wall_recomendations.recommend()
# insert property id
for rec in wall_recomendations.recommendations:
rec["property_id"] = property_id
recommendations.extend(wall_recomendations.recommendations)
property_recommendations.extend(wall_recomendations.recommendations)
# Once we're done, we'll store:
recommendations[p.id] = property_recommendations
# Once we're done, we'll store:
# 1) the property data
# 2) the property details (epc)
# 3) the recommendations
@ -238,4 +248,10 @@ async def trigger_plan(body: PlanTriggerRequest):
property_data = p.get_full_property_data()
update_property_data(property_id=p.id, portfolio_id=body.portfolio_id, property_data=property_data)
return {"recommendations": recommendations}
# Upload recommendations
recommendations_to_upload = recommendations[p.id]
if not recommendations:
continue
# Create a plan
return Response(status_code=200)

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@ -1,242 +0,0 @@
suspended_floor_insulation_parts = [
{
# Example product
# All product types here:
# https://www.insulationsuperstore.co.uk/browse/insulation/brand/recticel/filterby/application/floors.html
"id": 1,
"type": "suspended_floor_insulation",
"description": "Rigid Insulation Foam Boards",
"depths": [25, 30, 40, 50, 60, 70, 75, 80, 90, 100, 110, 120, 130, 140, 150],
"depth_unit": "mm",
"cost": None,
"cost_unit": None,
"r_value_per_mm": 0.04545454545454546,
"r_value_unit": "square_meter_kelvin_per_watt",
"thermal_conductivity": 0.022,
"thermal_conductivity_unit": "watt_per_meter_kelvin",
"link": "https://www.insulationsuperstore.co.uk/product/recticel-eurothane-general-purpose-pir-insulation"
"-board-2400-x-1200-x-100mm.html"
},
{
# All product types here:
# https://www.insulationsuperstore.co.uk/browse/insulation/brand/rockwool/filterby/application/floors
# /material/mineral-wool.html
"id": 2,
"type": "suspended_floor_insulation",
"description": "Mineral Wool Floor Insulation",
"depths": [25, 40, 50, 60, 75, 100],
"depth_unit": "mm",
"cost": None,
"cost_unit": None,
"r_value_per_mm": 0.02857142857142857,
"r_value_unit": "square_meter_kelvin_per_watt",
"thermal_conductivity": 0.035,
"thermal_conductivity_unit": "watt_per_meter_kelvin",
"link": "https://www.insulationsuperstore.co.uk/product/rockwool-rwa45-acoustic-insulation-slab-100mm-2-88m2"
"-pack.html"
},
]
solid_floor_insulation_parts = [
{
# All product types here:
# https://www.insulationexpress.co.uk/floor-insulation/solid-floor-insulation?brand=7015&p=1
# Example screed https://www.screwfix.com/p/mapei-ultraplan-3240-self-levelling-compound-25kg/4959f
"id": 3,
"type": "solid_floor_insulation",
"description": "Rigid Insulation Foam Boards with floor screed",
"depths": [25, 50, 70, 75, 100],
"depth_unit": "mm",
"cost": None,
"cost_unit": None,
"r_value_per_mm": 0.04545454545454546,
"r_value_unit": "square_meter_kelvin_per_watt",
"thermal_conductivity": 0.052631578947368425,
"thermal_conductivity_unit": "watt_per_meter_kelvin",
"link": "https://www.insulationexpress.co.uk/floor-insulation/solid-floor-insulation/k103-100mm"
},
]
external_wall_insulation_parts = [
{
"id": 4,
"type": "external_wall_insulation",
"description": "Mineral Wool External Wall Insulation",
"depths": [30, 50, 70, 80, 90, 100, 150, 200],
"depth_unit": "mm",
"cost": None,
"cost_unit": None,
"r_value_per_mm": 0.0278,
"r_value_unit": "square_meter_kelvin_per_watt",
"thermal_conductivity": 0.036,
"thermal_conductivity_unit": "watt_per_meter_kelvin",
"link": "https://insulationgo.co.uk/100mm-rockwool-external-wall-insulation-dual-density-slabs-a1-non"
"-combustible-slab-ewi-render-fire/"
},
{
"id": 5,
"type": "external_wall_insulation",
"description": "Expanded Polystyrene External Wall Insulation",
"depths": [25, 50, 100, 125],
"depth_unit": "mm",
"cost": None,
"cost_unit": None,
"r_value_per_mm": 0.02703,
"r_value_unit": "square_meter_kelvin_per_watt",
"thermal_conductivity": 0.037,
"thermal_conductivity_unit": "watt_per_meter_kelvin",
"link": "https://www.insulationking.co.uk/products/polystyrene-eps70?variant=44156186558759"
},
{
"id": 6,
"type": "external_wall_insulation",
"description": "Phenolic Foam External Wall Insulation",
"depths": [20, 50, 100],
"depth_unit": "mm",
"cost": None,
"cost_unit": None,
"r_value_per_mm": 0.043478260869565216,
"r_value_unit": "square_meter_kelvin_per_watt",
"thermal_conductivity": 0.023,
"thermal_conductivity_unit": "watt_per_meter_kelvin",
"link": "https://www.insulationshop.co/20mm_kooltherm_k5_external_wall_kingspan.html"
},
{
"id": 7,
"type": "external_wall_insulation",
"description": "Polyisocyanurate/Polyurethane Foam External Wall Insulation",
"depths": [],
"depth_unit": "mm",
"cost": None,
"cost_unit": None,
"r_value_per_mm": None,
"r_value_unit": "square_meter_kelvin_per_watt",
"thermal_conductivity": None,
"thermal_conductivity_unit": "watt_per_meter_kelvin",
"link": None
},
{
"id": 8,
"type": "external_wall_insulation",
"description": "Wood Fiber External Wall Insulation",
"depths": [40, 60],
"depth_unit": "mm",
"cost": None,
"cost_unit": None,
"r_value_per_mm": 0.023255813953488375,
"r_value_unit": "square_meter_kelvin_per_watt",
"thermal_conductivity": 0.043,
"thermal_conductivity_unit": "watt_per_meter_kelvin",
"link": "https://www.mikewye.co.uk/product/steico-duo-dry/"
},
{
"id": 9,
"type": "external_wall_insulation",
"description": "Aerogel External Wall Insulation",
"depths": [10, 20, 30, 40, 50, 60, 70],
"depth_unit": "mm",
"cost": None,
"cost_unit": None,
"r_value_per_mm": 0.06666666666666667,
"r_value_unit": "square_meter_kelvin_per_watt",
"thermal_conductivity": 0.015,
"thermal_conductivity_unit": "watt_per_meter_kelvin",
"link": "https://www.thermablok.co.uk/site/wp-content/uploads/2022/09/Thermablok-Aerogel-Insulation-Blanket"
"-TDS-AIS-and-Steel-Related-Details.pdf"
},
{
"id": 10,
"type": "external_wall_insulation",
"description": "Vacuum Insulation Panels External Wall Insulation",
"depths": [45, 60],
"depth_unit": "mm",
"cost": None,
"cost_unit": None,
"r_value_per_mm": 0.16666666666666666,
"r_value_unit": "square_meter_kelvin_per_watt",
"thermal_conductivity": 0.006,
"thermal_conductivity_unit": "watt_per_meter_kelvin",
"link": None
}
]
internal_wall_insulation_parts = [
{
"id": 11,
"type": "internal_wall_insulation",
"description": "Rigid Insulation Boards Internal Wall Insulation",
"depths": [25, 40, 50, 75, 100],
"depth_unit": "mm",
"cost": None,
"cost_unit": None,
"r_value_per_mm": 0.026315789473684213,
"r_value_unit": "square_meter_kelvin_per_watt",
"thermal_conductivity": 0.038,
"thermal_conductivity_unit": "watt_per_meter_kelvin",
"link": "https://www.insulationshop.co/25mm_polystyrene_insulation_eps_70jablite.html"
},
{
"id": 12,
"type": "internal_wall_insulation",
"description": "Mineral Wool Internal Wall Insulation",
"depths": [140],
"depth_unit": "mm",
"cost": None,
"cost_unit": None,
"r_value_per_mm": 0.02857142857142857,
"r_value_unit": "square_meter_kelvin_per_watt",
"thermal_conductivity": 0.035,
"thermal_conductivity_unit": "watt_per_meter_kelvin",
"link": "https://www.rockwool.com/siteassets/rw-uk/downloads/datasheets/flexi.pdf"
},
{
"id": 13,
"type": "internal_wall_insulation",
"description": "Insulated Plasterboard Internal Wall Insulation",
"depths": [25, 80],
"depth_unit": "mm",
"cost": None,
"cost_unit": None,
"r_value_per_mm": 0.02857142857142857,
"r_value_unit": "square_meter_kelvin_per_watt",
"thermal_conductivity": 0.019,
"thermal_conductivity_unit": "watt_per_meter_kelvin",
"link": "https://www.kingspan.com/gb/en/products/insulation-boards/wall-insulation-boards/kooltherm-k118"
"-insulated-plasterboard/"
},
{
"id": 14,
"type": "internal_wall_insulation",
"description": "Reflective Internal Wall Insulation",
"depths": [],
"depth_unit": "mm",
"cost": None,
"cost_unit": None,
"r_value_per_mm": None,
"r_value_unit": "square_meter_kelvin_per_watt",
"thermal_conductivity": None,
"thermal_conductivity_unit": "watt_per_meter_kelvin",
"link": None
},
{
"id": 15,
"type": "internal_wall_insulation",
"description": "Vacuum Insulation Panels Wall Insulation",
"depths": [20, 30],
"depth_unit": "mm",
"cost": None,
"cost_unit": None,
"r_value_per_mm": 0.125,
"r_value_unit": "square_meter_kelvin_per_watt",
"thermal_conductivity": 0.008,
"thermal_conductivity_unit": "watt_per_meter_kelvin",
"link": "https://www.insulationsuperstore.co.uk/product/vacutherm-vacupor-nt-b2-vacuum-insulated-panel-1m-x"
"-600mm-x-30mm.html"
},
]
materials = (
suspended_floor_insulation_parts + solid_floor_insulation_parts + external_wall_insulation_parts + \
internal_wall_insulation_parts
)

View file

@ -299,6 +299,7 @@ def app():
# Clean using averages
avgs = iterative_filtering(cleaning_averages, property_data)
# TODO: Should probably do a mean/median?
field_value = avgs[field].iloc[0]
if pd.isnull(field_value):
@ -343,6 +344,7 @@ def app():
rdsap_change = ending_record[RDSAP_RESPONSE] - starting_record[RDSAP_RESPONSE]
heat_demand_change = ending_record[HEAT_DEMAND_RESPONSE] - starting_record[HEAT_DEMAND_RESPONSE]
# TODO: Should this be <= 0?
if rdsap_change == 0:
# Assumption: We aren't interested in records that exhibit no change
continue