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Added basic solar recommendations

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Khalim Conn-Kowlessar 2024-01-16 11:10:56 +00:00
parent 5becd8d11b
commit 0c76e4b9d1
6 changed files with 100 additions and 2 deletions
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7
etl/eligibility/ha_15_32/app.py
View file

@ -980,6 +980,8 @@ def analyse_ha_15_results(results_df, ha15, no_house_numbers):
results_df["warmfront_identified"]
]
warmfront_identified = warmfront_identified
n_identified = (warmfront_identified["gbis_eligible"] | warmfront_identified["eco4_eligible"]).sum()
success_rate = n_identified / warmfront_identified.shape[0]
@ -1030,6 +1032,11 @@ def analyse_ha_15_results(results_df, ha15, no_house_numbers):
(results_df["eco4_eligible"] == True)
].copy()
new_possibilities_gbis = results_df[
(~results_df["warmfront_identified"]) &
(results_df["eco4_eligible"] == False) & (results_df["gbis_eligible"] == True)
].copy()
# These are future possibilityies
future_possibilities_eco = results_df[
(~results_df["warmfront_identified"]) &

2
etl/eligibility/ha_15_32/ha16_app.py
View file

@ -478,7 +478,7 @@ def get_epc_data(data, cleaned, cleaning_data, created_at, photo_supply_lookup,
def analyse_results(results_df, data, survey_list):
analysis_data = data[["row_id", "survey_key", "warmfront_identified"]].merge(
analysis_data = data[["row_id", "survey_key", "warmfront_identified", "row_colour_name"]].merge(
results_df, how="left", on="row_id"
).merge(
survey_list[["survey_key", survey_list.columns[0]]].rename(columns={survey_list.columns[0]: "funding_scheme"}),

5
etl/eligibility/ha_15_32/ha25_app.py
View file

@ -787,6 +787,11 @@ def analyse_results(results_df, data, eco4_prospects_survey_list):
results_df, how="left", on="row_id"
)
analysis_data = analysis_data.merge(
eco4_prospects_survey_list[["survey_key", "ADDRESS 1", "NO", "POSTCODE"]],
how="left", on="survey_key"
)
# NEW
analysis_data["roof_insulation_thickness"] = np.where(
pd.isnull(analysis_data["roof_insulation_thickness"]), None, analysis_data["roof_insulation_thickness"]

6
etl/eligibility/ha_15_32/ha7_app.py
View file

@ -272,6 +272,8 @@ def analyse_ha_7(results_df, data):
data[["row_id", "row_code", "Property Type", "Construction Year Band"]], how="left", on="row_id"
)
analysis_data["row_code"].value_counts()
# NEW
analysis_data["roof_insulation_thickness"] = np.where(
@ -304,6 +306,10 @@ def analyse_ha_7(results_df, data):
)
]
wf_identified = analysis_data[
(analysis_data["row_code"] == "potential ECO4")
]
# END NEW
warmfront_identification = analysis_data["row_code"].value_counts()

3
recommendations/SolarPvRecommendations.py
View file

@ -31,7 +31,8 @@ class SolarPvRecommendations:
is_valid_roof_type = (
self.property.roof["is_flat"] or self.property.roof["is_pitched"] or self.property.roof["is_roof_room"]
)
has_no_existing_solar_pv = not self.property.data["photo-supply"] in [
# If there is no existing solar PV, the photo-supply field will be None or a missing value
has_no_existing_solar_pv = self.property.data["photo-supply"] in [
None, 0, self.property.DATA_ANOMALY_MATCHES
]

79
recommendations/tests/test_solar_pv_recommendations.py
View file

@ -0,0 +1,79 @@
import pytest
from recommendations.SolarPvRecommendations import SolarPvRecommendations
from backend.Property import Property
class TestSolarPvRecommendations:
@pytest.fixture
def property_instance_invalid_type(self):
# Setup the property_instance with an invalid property type
property_instance_invalid_type = Property(id=1, address="", postcode="")
property_instance_invalid_type.data = {
"property-type": "InvalidType", "county": "Broxbourne", "photo-supply": None
}
property_instance_invalid_type.roof = {"is_flat": False, "is_pitched": False, "is_roof_room": False}
return property_instance_invalid_type
@pytest.fixture
def property_instance_invalid_roof(self):
# Setup the property_instance with invalid roof type
property_instance_invalid_roof = Property(id=1, address="", postcode="")
property_instance_invalid_roof.data = {
"county": "Huntingdonshire", "property-type": "House", "photo-supply": None
}
property_instance_invalid_roof.roof = {"is_flat": False, "is_pitched": False, "is_roof_room": False}
return property_instance_invalid_roof
@pytest.fixture
def property_instance_has_solar_pv(self):
# Setup the property_instance without existing solar pv
property_instance_has_solar_pv = Property(id=1, address="", postcode="")
property_instance_has_solar_pv.data = {"photo-supply": "40", "county": "Huntingdonshire",
"property-type": "House"}
property_instance_has_solar_pv.roof = {"is_flat": True}
return property_instance_has_solar_pv
@pytest.fixture
def property_instance_valid_all(self):
# Setup a valid property_instance that passes all conditions
property_instance_valid_all = Property(id=1, address="", postcode="")
property_instance_valid_all.solar_pv_roof_area = 20
property_instance_valid_all.solar_pv_percentage = 40
property_instance_valid_all.data = {"property-type": "House", "photo-supply": None, "county": "Huntingdonshire"}
property_instance_valid_all.roof = {"is_flat": True}
return property_instance_valid_all
def test_invalid_property_type(self, property_instance_invalid_type):
solar_pv = SolarPvRecommendations(property_instance_invalid_type)
solar_pv.recommend()
assert not solar_pv.recommendation
def test_invalid_roof_type(self, property_instance_invalid_roof):
solar_pv = SolarPvRecommendations(property_instance_invalid_roof)
solar_pv.recommend()
assert not solar_pv.recommendation
def test_existing_solar_pv(self, property_instance_has_solar_pv):
solar_pv = SolarPvRecommendations(property_instance_has_solar_pv)
solar_pv.recommend()
assert not solar_pv.recommendation
def test_valid_all_conditions(self, property_instance_valid_all):
solar_pv = SolarPvRecommendations(property_instance_valid_all)
solar_pv.recommend()
assert solar_pv.recommendation == [
{
'parts': [],
'type': 'solar_pv',
'description': 'Install a 4 kilowatt-peak (kWp) solar photovoltaic (PV) panel system on the roof',
'starting_u_value': None,
'new_u_value': None,
'sap_points': None,
'total': 8527.0752,
'subtotal': 7105.896,
'vat': 1421.1791999999996,
'labour_hours': 72,
'labour_days': 2,
'photo_supply': 4000
}
]