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100 lines
5 KiB
Python
100 lines
5 KiB
Python
import pytest
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from recommendations.SolarPvRecommendations import SolarPvRecommendations
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from backend.Property import Property
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from etl.epc.Record import EPCRecord
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import pandas as pd
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import numpy as np
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class TestSolarPvRecommendations:
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@pytest.fixture
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def property_instance_invalid_type(self):
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# Setup the property_instance with an invalid property type
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epc_record = EPCRecord()
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epc_record.prepared_epc = {
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"property-type": "InvalidType", "county": "Broxbourne", "photo-supply": None
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}
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property_instance_invalid_type = Property(id=1, address="", postcode="", epc_record=epc_record)
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property_instance_invalid_type.roof = {"is_flat": False, "is_pitched": False, "is_roof_room": False}
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return property_instance_invalid_type
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@pytest.fixture
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def property_instance_invalid_roof(self):
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# Setup the property_instance with invalid roof type
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epc_record = EPCRecord()
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epc_record.prepared_epc = {
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"county": "Huntingdonshire", "property-type": "House", "photo-supply": None
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}
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property_instance_invalid_roof = Property(id=1, address="", postcode="", epc_record=epc_record)
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property_instance_invalid_roof.roof = {
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"is_flat": False, "is_pitched": False, "is_roof_room": False, "thermal_transmittance": None
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}
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return property_instance_invalid_roof
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@pytest.fixture
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def property_instance_has_solar_pv(self):
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# Setup the property_instance without existing solar pv
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epc_record = EPCRecord()
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epc_record.prepared_epc = {"photo-supply": "40", "county": "Huntingdonshire",
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"property-type": "House"}
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property_instance_has_solar_pv = Property(id=1, address="", postcode="", epc_record=epc_record)
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property_instance_has_solar_pv.roof = {"is_flat": True, "thermal_transmittance": None}
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return property_instance_has_solar_pv
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@pytest.fixture
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def property_instance_valid_all(self):
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# Setup a valid property_instance that passes all conditions
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epc_record = EPCRecord()
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epc_record.prepared_epc = {"property-type": "House", "photo-supply": None, "county": "Huntingdonshire"}
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property_instance_valid_all = Property(id=1, address="", postcode="", epc_record=epc_record)
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property_instance_valid_all.roof_area = 40
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property_instance_valid_all.number_of_floors = 2
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property_instance_valid_all.roof = {"is_flat": True, "thermal_transmittance": None}
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property_instance_valid_all.solar_panel_configuration = {
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"panel_performance": pd.DataFrame(
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[
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{
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"panneled_roof_area": 20,
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"n_panels": 10,
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"array_wattage": 4000,
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"initial_ac_kwh_per_year": 3800
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}
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]
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)
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}
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return property_instance_valid_all
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def test_invalid_property_type(self, property_instance_invalid_type):
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solar_pv = SolarPvRecommendations(property_instance_invalid_type)
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solar_pv.recommend(phase=0)
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assert not solar_pv.recommendation
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def test_invalid_roof_type(self, property_instance_invalid_roof):
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solar_pv = SolarPvRecommendations(property_instance_invalid_roof)
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solar_pv.recommend(phase=0)
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assert not solar_pv.recommendation
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def test_existing_solar_pv(self, property_instance_has_solar_pv):
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solar_pv = SolarPvRecommendations(property_instance_has_solar_pv)
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solar_pv.recommend(phase=0)
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assert not solar_pv.recommendation
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def test_valid_all_conditions(self, property_instance_valid_all):
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solar_pv = SolarPvRecommendations(property_instance_valid_all)
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solar_pv.recommend(phase=0)
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assert len(solar_pv.recommendation) == 2
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assert solar_pv.recommendation == [
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{'phase': 0, 'parts': [], 'type': 'solar_pv', 'measure_type': 'solar_pv',
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'description': 'Install a 4.0 kilowatt-peak (kWp) solar panel system.', 'starting_u_value': None,
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'new_u_value': None, 'sap_points': np.float64(10.0), 'already_installed': False,
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'total': 6013.139999999999, 'subtotal': 5010.95, 'vat': 0, 'labour_hours': 48, 'labour_days': 2,
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'photo_supply': np.float64(50.0), 'has_battery': False, 'initial_ac_kwh_per_year': np.int64(3800),
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'description_simulation': {'photo-supply': np.float64(50.0)}},
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{'phase': 0, 'parts': [], 'type': 'solar_pv', 'measure_type': 'solar_pv',
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'description': 'Install a 4.0 kilowatt-peak (kWp) solar panel system, with a battery.',
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'starting_u_value': None, 'new_u_value': None, 'sap_points': np.float64(10.0), 'already_installed': False,
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'total': 10537.008, 'subtotal': 8780.84, 'vat': 0, 'labour_hours': 48, 'labour_days': 2,
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'photo_supply': np.float64(50.0), 'has_battery': True, 'initial_ac_kwh_per_year': np.int64(3800),
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'description_simulation': {'photo-supply': np.float64(50.0)}}
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]
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