import pandas as pd
import pytest
from model_data.tests.test_data.test_lighting_attributes_cases import test_cases
from model_data.epc_attributes.LightingAttributes import LightingAttributes

# An example averages dataset to use in tests. It is a dictionary where the key is a lighting description and the
# value is the expected proportion.
averages = pd.DataFrame(
    [
        {"lighting-description": "good lighting efficiency", "low-energy-lighting": 0.75},
        {"lighting-description": "excellent lighting efficiency", "low-energy-lighting": 1.0},
        {"lighting-description": "below average lighting efficiency", "low-energy-lighting": 0.25}
    ]
)


class TestLightingAttributes:
    def test_no_lighting(self):
        lighting = LightingAttributes("no low energy lighting", averages)
        result = lighting.process()
        assert result == {"low_energy_proportion": 0}

    def test_all_outlets(self):
        lighting = LightingAttributes("Low energy lighting in all fixed outlets", averages)
        result = lighting.process()
        assert result == {"low_energy_proportion": 1}

    def test_good_efficiency(self):
        lighting = LightingAttributes("Good lighting efficiency", averages)
        result = lighting.process()
        assert result == {"low_energy_proportion": 0.75}

    def test_excellent_efficiency(self):
        lighting = LightingAttributes("Excellent lighting efficiency", averages)
        result = lighting.process()
        assert result == {"low_energy_proportion": 1}

    def test_below_average_efficiency(self):
        lighting = LightingAttributes("Below average lighting efficiency", averages)
        result = lighting.process()
        assert result == {"low_energy_proportion": 0.25}

    def test_percentage(self):
        lighting = LightingAttributes("Low energy lighting in 50% of fixed outlets", averages)
        result = lighting.process()
        assert result == {"low_energy_proportion": 0.5}

    def test_unknown_description(self):
        with pytest.raises(NotImplementedError):
            LightingAttributes("This is an unknown description", averages).process()

    @pytest.mark.parametrize(
        "test_case",
        test_cases
    )
    def test_process_mainheat(self, test_case):
        expected_result = test_case.copy()
        del expected_result["original_description"]
        result = LightingAttributes(test_case['original_description'], averages).process()
        assert sorted(result.items()) == sorted(expected_result.items())