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60 lines
2.5 KiB
Python
60 lines
2.5 KiB
Python
import pandas as pd
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import pytest
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from model_data.tests.test_data.test_lighting_attributes_cases import test_cases
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from model_data.epc_attributes.LightingAttributes import LightingAttributes
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# An example averages dataset to use in tests. It is a dictionary where the key is a lighting description and the
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# value is the expected proportion.
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averages = pd.DataFrame(
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[
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{"lighting-description": "good lighting efficiency", "low-energy-lighting": 0.75},
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{"lighting-description": "excellent lighting efficiency", "low-energy-lighting": 1.0},
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{"lighting-description": "below average lighting efficiency", "low-energy-lighting": 0.25}
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]
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)
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class TestLightingAttributes:
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def test_no_lighting(self):
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lighting = LightingAttributes("no low energy lighting", averages)
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result = lighting.process()
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assert result == {"low_energy_proportion": 0}
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def test_all_outlets(self):
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lighting = LightingAttributes("Low energy lighting in all fixed outlets", averages)
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result = lighting.process()
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assert result == {"low_energy_proportion": 1}
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def test_good_efficiency(self):
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lighting = LightingAttributes("Good lighting efficiency", averages)
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result = lighting.process()
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assert result == {"low_energy_proportion": 0.75}
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def test_excellent_efficiency(self):
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lighting = LightingAttributes("Excellent lighting efficiency", averages)
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result = lighting.process()
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assert result == {"low_energy_proportion": 1}
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def test_below_average_efficiency(self):
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lighting = LightingAttributes("Below average lighting efficiency", averages)
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result = lighting.process()
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assert result == {"low_energy_proportion": 0.25}
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def test_percentage(self):
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lighting = LightingAttributes("Low energy lighting in 50% of fixed outlets", averages)
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result = lighting.process()
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assert result == {"low_energy_proportion": 0.5}
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def test_unknown_description(self):
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with pytest.raises(NotImplementedError):
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LightingAttributes("This is an unknown description", averages).process()
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@pytest.mark.parametrize(
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"test_case",
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test_cases
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)
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def test_process_mainheat(self, test_case):
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expected_result = test_case.copy()
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del expected_result["original_description"]
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result = LightingAttributes(test_case['original_description'], averages).process()
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assert sorted(result.items()) == sorted(expected_result.items())
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