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271 lines
12 KiB
Python
271 lines
12 KiB
Python
import pytest
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import numpy as np
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from types import SimpleNamespace
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from recommendations.tests.test_data.measures_to_optimise import measures_to_optimise
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from recommendations.optimiser import optimiser_functions
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from recommendations.optimiser.GainOptimiser import GainOptimiser
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from recommendations.optimiser.CostOptimiser import CostOptimiser
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class TestPrepareInputMeasures:
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def test_returns_expected_structure_without_ventilation(self):
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recs = [
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[ # loft insulation measure
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{"recommendation_id": "loft1", "type": "loft_insulation", "total": 100, "kwh_savings": 200,
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"energy_cost_savings": 10, "has_battery": False, "measure_type": "loft_insulation",
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"partial_project_funding": 0, "partial_project_score": 0,
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"uplift_project_score": 0,
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},
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],
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]
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measures = optimiser_functions.prepare_input_measures(recs, goal="Energy Savings", needs_ventilation=False)
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assert isinstance(measures, list)
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assert measures[0][0]["id"] == "loft1"
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assert measures[0][0]["cost"] == 100
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assert measures[0][0]["gain"] == 200
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def test_bundles_ventilation_when_needed(self, monkeypatch):
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# patch measures_needing_ventilation so that "wall_insulation" needs ventilation
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monkeypatch.setattr(optimiser_functions.assumptions, "measures_needing_ventilation",
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["internal_wall_insulation"])
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recs = [
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[{"recommendation_id": "wall1", "type": "internal_wall_insulation", "total": 500, "kwh_savings": 300,
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"energy_cost_savings": 5, "has_battery": False, "measure_type": "internal_wall_insulation",
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"partial_project_funding": 0, "partial_project_score": 0, "uplift_project_score": 0,
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}],
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[{"recommendation_id": "vent1", "type": "mechanical_ventilation", "total": 50, "kwh_savings": 30,
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"energy_cost_savings": 5, "has_battery": False, "measure_type": "mechanical_ventilation",
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"partial_project_funding": 0, "partial_project_score": 0, "uplift_project_score": 0, }],
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]
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measures = optimiser_functions.prepare_input_measures(recs, goal="Energy Savings", needs_ventilation=True)
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wall_option = measures[0][0]
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assert wall_option["cost"] == 550
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assert wall_option["gain"] == 330
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assert "+mechanical_ventilation" in wall_option["type"]
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def test_filters_out_negative_cost_savings(self):
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recs = [
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[{"recommendation_id": "bad1", "type": "loft_insulation", "total": 200, "kwh_savings": 100,
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"energy_cost_savings": -5, "has_battery": False,
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"partial_project_funding": 0, "partial_project_score": 0, "uplift_project_score": 0, }],
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]
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measures = optimiser_functions.prepare_input_measures(recs, goal="Energy Savings", needs_ventilation=False)
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assert measures == [] # should skip negative cost saving recs
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class TestCalculateFixedGain:
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def test_no_required_measures_returns_zero(self):
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fixed_gain = optimiser_functions.calculate_fixed_gain(
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[], {}, SimpleNamespace(id="P1"), needs_ventilation=False
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)
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assert fixed_gain == 0
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def test_sums_max_sap_points_per_type(self, monkeypatch):
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monkeypatch.setattr(optimiser_functions.assumptions, "measures_needing_ventilation",
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["internal_wall_insulation"])
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required_measures = [
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[{"type": "internal_wall_insulation", "sap_points": 5},
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{"type": "internal_wall_insulation", "sap_points": 10}],
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[{"type": "loft_insulation", "sap_points": 3}]
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]
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recommendations = {"P1": [[{"type": "mechanical_ventilation", "sap_points": 2}]]}
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prop = SimpleNamespace(id="P1")
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gain = optimiser_functions.calculate_fixed_gain(
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required_measures, recommendations, prop, needs_ventilation=True
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)
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# Should take max of wall (10) + loft (3) + ventilation (2)
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assert gain == 15
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class TestCalculateGain:
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def test_returns_none_for_energy_savings_goal(self):
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body = SimpleNamespace(goal="Energy Savings")
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prop = SimpleNamespace(data={"current-energy-efficiency": "50"})
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gain = optimiser_functions.calculate_gain(body, prop, fixed_gain=0)
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assert gain is None
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def test_calculates_gain_for_epc(self, monkeypatch):
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# patch cost optimiser calculation
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monkeypatch.setattr(optimiser_functions, "epc_to_sap_lower_bound", lambda goal_value: 69)
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body = SimpleNamespace(goal="Increasing EPC", goal_value="C", simulate_sap_10=False)
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prop = SimpleNamespace(data={"current-energy-efficiency": "50"})
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gain = optimiser_functions.calculate_gain(body, prop, fixed_gain=2)
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assert gain == 18.5
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class TestAddRequiredMeasures:
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def test_adds_cheapest_required_measure(self):
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property_id = "P1"
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required_measures = [
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[{"recommendation_id": "a", "total": 100, "sap_points": 5, "type": "loft_insulation"},
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{"recommendation_id": "b", "total": 80, "sap_points": 6, "type": "loft_insulation"}]
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]
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recommendations = {
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"P1": [[{"recommendation_id": "a", "total": 100, "sap_points": 5, "type": "loft_insulation"},
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{"recommendation_id": "b", "total": 80, "sap_points": 6, "type": "loft_insulation"}]]
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}
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selected = set()
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result = optimiser_functions.add_required_measures(property_id, required_measures, recommendations, selected)
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# cheapest should be b
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assert "b" in selected
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assert any(rec["id"] == "b" for rec in result)
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class TestAddBestPracticeMeasures:
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def test_adds_ventilation_and_trickle_vents(self, monkeypatch):
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monkeypatch.setattr(optimiser_functions.assumptions, "measures_needing_ventilation",
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["internal_wall_insulation"])
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property_id = "P1"
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solution = [{"type": "internal_wall_insulation", "id": "w1", "gain": 10, "cost": 100}]
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recommendations = {
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"P1": [
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[{"type": "mechanical_ventilation", "recommendation_id": "vent1"}],
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[{"type": "trickle_vents", "recommendation_id": "trickle1"}]
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]
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}
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selected = set()
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updated = optimiser_functions.add_best_practice_measures(property_id, solution, recommendations, selected)
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assert "vent1" in updated
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assert "trickle1" in updated
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class TestFlattenRecommendationsWithDefaults:
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def test_marks_selected_and_flattens(self):
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property_id = "P1"
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recommendations = {
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"P1": [
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[{"recommendation_id": "a", "foo": 1}, {"recommendation_id": "b", "foo": 2}],
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[{"recommendation_id": "c", "foo": 3}]
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]
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}
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selected = {"b", "c"}
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result = optimiser_functions.flatten_recommendations_with_defaults(property_id, recommendations, selected)
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# All recs should now have a default key
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assert all("default" in rec for rec in result)
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assert next(r for r in result if r["recommendation_id"] == "b")["default"] is True
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assert next(r for r in result if r["recommendation_id"] == "a")["default"] is False
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class TestIncreasingEpcE2e:
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"""
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Test out the classic increasing EPC optimisation flow end-to-end.
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We have a goal (Increasing EPC), no budget, and we expect the optimiser to choose
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the best set of measures and include best-practice ventilation.
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"""
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@pytest.fixture
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def setup_case(self):
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# Dummy property object
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p = SimpleNamespace(
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id="P1",
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has_ventilation=False,
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data={"current-energy-efficiency": "52"},
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)
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# Dummy request body
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body = SimpleNamespace(
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goal="Increasing EPC",
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goal_value="C",
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optimise=True,
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budget=None,
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simulate_sap_10=False,
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required_measures=[]
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)
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recommendations = {"P1": measures_to_optimise}
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return p, body, recommendations
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def test_end_to_end_increasing_epc(self, setup_case):
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p, body, recommendations = setup_case
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# ---------------------
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# RUN THE OPTIMISATION LOOP
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# ---------------------
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property_measure_types = {rec["type"] for recs in recommendations[p.id] for rec in recs}
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property_required_measures = [m for m in recommendations[p.id] if m[0]["type"] in body.required_measures]
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measures_to_optimise = [m for m in recommendations[p.id] if m[0]["type"] not in body.required_measures]
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# ventilation flag
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needs_ventilation = any(
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x in property_measure_types for x in optimiser_functions.assumptions.measures_needing_ventilation
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) and not p.has_ventilation
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assert needs_ventilation
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# Input the various things we need - set all to 0
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for group in measures_to_optimise:
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for r in group:
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(
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r["partial_project_score"],
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r["partial_project_funding"],
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r["innovation_uplift"],
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r["uplift_project_score"],
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) = (
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0, 0, 0, 0
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)
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input_measures = optimiser_functions.prepare_input_measures(measures_to_optimise, body.goal, needs_ventilation)
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assert input_measures, "Expected measures to optimise"
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assert len(input_measures) == 7
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fixed_gain = optimiser_functions.calculate_fixed_gain(
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property_required_measures, recommendations, p, needs_ventilation
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)
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assert fixed_gain == 0, "No required measures should mean fixed gain is 0"
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gain = optimiser_functions.calculate_gain(body=body, p=p, fixed_gain=fixed_gain)
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assert gain == 18.5, "Expected gain to be calculated correctly based on fixed gain and SAP target"
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optimiser = (
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GainOptimiser(
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input_measures, max_cost=body.budget, max_gain=gain,
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allow_slack=body.goal == "Increasing EPC"
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) if body.budget else CostOptimiser(input_measures, min_gain=gain)
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)
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optimiser.setup()
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optimiser.solve()
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solution = optimiser.solution
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assert solution, "Optimiser should return a non-empty solution"
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assert all("id" in m for m in solution)
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assert any("solar_pv" in m["type"] for m in solution), "Expected solar PV to be included"
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# Collect selected measure IDs
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selected = {r["id"] for r in solution}
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assert selected == {'8_phase=7', '5_phase=4', '7_phase=6'}
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# Add required measures (none here)
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solution = optimiser_functions.add_required_measures(
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property_id=p.id, property_required_measures=property_required_measures,
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recommendations=recommendations, selected=selected,
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)
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assert solution == [
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{'id': '5_phase=4', 'cost': 58.8, 'gain': 2, 'type': 'low_energy_lighting'},
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{'id': '7_phase=6', 'cost': 30.0, 'gain': np.float64(3.6), 'type': 'secondary_heating'},
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{'id': '8_phase=7', 'cost': 6013.139999999999, 'gain': np.float64(13.0), 'type': 'solar_pv'}
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]
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total_optimised_gain = sum(m["gain"] for m in solution)
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assert total_optimised_gain == 18.6, "Total gain of optimised measures should meet or exceed target gain"
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selected = optimiser_functions.add_best_practice_measures(p.id, solution, recommendations, selected)
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# Flatten recommendations for output
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flattened = optimiser_functions.flatten_recommendations_with_defaults(p.id, recommendations, selected)
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# ---------------------
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# FINAL ASSERTIONS
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# ---------------------
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assert isinstance(flattened, list)
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assert all("default" in rec for rec in flattened)
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assert any(rec["default"] for rec in flattened), "Some measures should be marked as default"
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# We don't add ventilation as major insulation work isn't done
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ventilation_added = any(rec["recommendation_id"] == "3_phase=2" and rec["default"] for rec in flattened)
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assert not ventilation_added, "Ventilation should not be added without major insulation work"
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