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implementing filter_photo_supply_lookup in property class

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Khalim Conn-Kowlessar 2024-01-05 16:23:41 +00:00
parent ce2229f817
commit 7c532d3c87
1 changed files with 12 additions and 29 deletions
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41
backend/Property.py
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@ -8,6 +8,7 @@ import pandas as pd
from etl.epc.DataProcessor import DataProcessor
from etl.epc.settings import POTENTIAL_COLUMNS, EFFICIENCY_FEATURES, BUILT_FORM_REMAP
from etl.epc_clean.epc_attributes.all_cleaners import all_cleaner_map
from etl.solar.SolarPhotoSupply import SolarPhotoSupply
from utils.logger import setup_logger
from utils.s3 import read_dataframe_from_s3_parquet
from BaseUtility import Definitions
@ -849,37 +850,19 @@ class Property(Definitions):
"Need to set insulation floor area and pitched roof area before setting solar pv roof area"
)
# TODO: Create a class for the solar etl process and make this one of the functions, which applies a different
# method depending on the data type
def classify_floor_area(new_area, thresholds):
for i, threshold in enumerate(thresholds):
if new_area <= threshold:
return i # Returns the decile index (0 to 9)
return len(thresholds)
floor_area_decile = classify_floor_area(
self.floor_area, floor_area_decile_thresholds["floor_area_decile_thresholds"].values
photo_supply_matched = SolarPhotoSupply.filter_photo_supply_lookup(
photo_supply_lookup=photo_supply_lookup,
floor_area_decile_thresholds=floor_area_decile_thresholds,
tenure=self.data["tenure"],
built_form=self.data["built-form"],
property_type=self.data["property-type"],
construction_age_band=self.construction_age_band,
is_flat=self.roof["is_flat"],
is_pitched=self.roof["is_pitched"],
is_roof_room=self.roof["is_roof_room"],
floor_area=self.floor_area
)
# Given the photo_supply_lookup, we esimate the percentage of the roof that is suitable for solar panels
# TODO: Move this to the ETL process, since we need to know that tenure should be lower
tenure = self.data["tenure"].lower()
photo_supply_matched = photo_supply_lookup[
(photo_supply_lookup["tenure"] == tenure) &
(photo_supply_lookup["built_form"] == self.data["built-form"]) &
(photo_supply_lookup["property_type"] == self.data["property-type"]) &
(photo_supply_lookup["construction_age_band"] == self.construction_age_band) &
(photo_supply_lookup["is_flat"] == self.roof["is_flat"]) &
(photo_supply_lookup["is_pitched"] == self.roof["is_pitched"]) &
(photo_supply_lookup["is_roof_room"] == self.roof["is_roof_room"])
]
if floor_area_decile in photo_supply_matched["floor_area_decile"].values:
photo_supply_matched = photo_supply_matched[
photo_supply_matched["floor_area_decile"] == floor_area_decile
]
percentage_of_roof = photo_supply_matched["photo_supply_median"].mean()
percentage_of_roof = percentage_of_roof / 100