Model/recommendations/FloorRecommendations.py

import math
from typing import List
from BaseUtility import Definitions
from datatypes.enums import QuantityUnits
from backend.Property import Property
from recommendations.recommendation_utils import (
    r_value_per_mm_to_u_value, calculate_u_value_uplift, is_diminishing_returns, update_lowest_selected_u_value,
    get_recommended_part, get_floor_u_value
)
from recommendations.rdsap_tables import FLOOR_LEVEL_MAP


class FloorRecommendations(Definitions):
    # part L building regulations indicate that any rennovations on an existing property's walls should
    # achieve a U-value of no higher than 0.3
    BUILDING_REGULATIONS_PART_L_MAX_U_VALUE = 0.25
    # We don't recommend measures that are too low because it becomes expensive, therefore we aim to avoid
    # diminishing returns. This value should be verified with Osmosis (TODO)
    DIMINISHING_RETURNS_U_VALUE = 0.2

    REGION_LOOKUP = {
        "England and Wales": "England_Wales",
    }

    PART_L_YEAR_CUTOFF = 2002

    def __init__(
        self,
        property_instance: Property,
        materials: List,
    ):
        self.property = property_instance
        # For audit purposes, when estimating u values we'll store it
        self.estimated_u_value = None

        # Will contains a list of recommended measures
        self.recommendations = []

        self.materials = materials

        self.suspended_floor_insulation_parts = [
            part for part in self.materials if part["type"] == "suspended_floor_insulation"
        ]
        self.solid_floor_insulation_parts = [
            part for part in self.materials if part["type"] == "solid_floor_insulation"
        ]

    def recommend(self):
        u_value = self.property.floor["thermal_transmittance"]
        is_suspended = self.property.floor["is_suspended"]
        is_solid = self.property.floor["is_solid"]
        floor_level = (
            FLOOR_LEVEL_MAP[self.property.data["floor-level"]] if
            self.property.data["floor-level"] not in self.DATA_ANOMALY_MATCHES else None
        )
        property_type = self.property.data["property-type"]

        year_built = self.property.year_built

        if self.property.floor["another_property_below"] | (self.property.floor["insulation_thickness"] in [
            "average", "above average"
        ]):
            # If there's another property below, it's likely impractical to recommend a floor upgrade,
            # or if the floor is already insualted
            return

        # If the property is a flat that isn't at ground level, it's likely impractical to recommend a floor upgrade
        if (floor_level != 0) and (property_type == "Flat"):
            return

        if u_value:

            # By being built more recently than this, it means that the property was likely build with soild
            # concrete floors with insulation already
            if year_built < self.PART_L_YEAR_CUTOFF:
                raise NotImplementedError("Not investigated this use case")

            if u_value <= self.BUILDING_REGULATIONS_PART_L_MAX_U_VALUE:
                # The floor is already compliant
                return

        u_value = get_floor_u_value(
            floor_type=self.property.floor_type,
            area=float(self.property.data["total-floor-area"]),
            perimeter=self.property.perimeter,
            age_band=self.property.age_band,
            insulation_thickness=self.property.floor["insulation_thickness"],
            wall_type=self.property.wall_type
        )
        self.estimated_u_value = u_value

        if is_suspended:
            # Given the U-value, we recommend underfloor insulation
            self.recommend_floor_insulation(u_value=u_value, parts=self.suspended_floor_insulation_parts)

        if is_solid:
            # Given the U-value, we recommend solid floor insulation options which are usually solid foam
            self.recommend_floor_insulation(u_value=u_value, parts=self.solid_floor_insulation_parts)

    @staticmethod
    def _make_floor_description(part, depth):
        return f"Install {depth}{part['depth_unit']} {part['description']} insulation"

    def recommend_floor_insulation(self, u_value, parts):
        """
        This method is tasked with estimating the impact of performing suspended floor insulation
        :return:
        """

        lowest_selected_u_value = None
        for part in parts:
            for depth, cost_per_unit in zip(part["depths"], part["cost"]):

                part_u_value = r_value_per_mm_to_u_value(depth, part["r_value_per_mm"])
                _, new_u_value = calculate_u_value_uplift(u_value, part_u_value)
                new_u_value = math.ceil(new_u_value * 100.0) / 100.0

                if is_diminishing_returns(
                    self.recommendations, new_u_value, lowest_selected_u_value, self.DIMINISHING_RETURNS_U_VALUE
                ):
                    continue

                if new_u_value <= self.BUILDING_REGULATIONS_PART_L_MAX_U_VALUE:
                    lowest_selected_u_value = update_lowest_selected_u_value(lowest_selected_u_value, new_u_value)

                    estimated_cost = cost_per_unit * self.property.floor_area

                    self.recommendations.append(
                        {
                            "parts": [
                                get_recommended_part(
                                    part=part,
                                    selected_depth=depth,
                                    quantity=self.property.floor_area,
                                    quantity_unit=QuantityUnits.m2.value,
                                    selected_total_cost=estimated_cost
                                ),
                            ],
                            "type": "floor_insulation",
                            "description": self._make_floor_description(part, depth),
                            "starting_u_value": u_value,
                            "new_u_value": new_u_value,
                            "sap_points": None,
                            "cost": estimated_cost,
                        }
                    )