Added lighting desciption tests

model_data/epc_attributes/LightingAttributes.py

@@ -32,4 +32,4 @@ class LightingAttributes:
                 "low_energy_proportion": proportion
             }
 
-        return {"low_energy_proportion": 0}
+        raise NotImplementedError("Not handled this case - investigate me")

model_data/tests/test_data/test_lighting_attributes_cases.py

@@ -25,9 +25,9 @@ test_cases = [
     {'original_description': 'Low energy lighting in 51% of fixed outlets', 'low_energy_proportion': 0.51},
     {'original_description': 'Low energy lighting in 99% of fixed outlets', 'low_energy_proportion': 0.99},
     {'original_description': 'Low energy lighting in 100% of fixed outlets', 'low_energy_proportion': 1.0},
-    {'original_description': 'Good lighting efficiency', 'low_energy_proportion': 98.16666666666667},
-    {'original_description': 'Below average lighting efficiency', 'low_energy_proportion': 0.0},
-    {'original_description': 'Excelent lighting efficiency', 'low_energy_proportion': 0},
+    {'original_description': 'Good lighting efficiency', 'low_energy_proportion': 0.75},
+    {'original_description': 'Below average lighting efficiency', 'low_energy_proportion': 0.25},
+    {'original_description': 'Excellent lighting efficiency', 'low_energy_proportion': 1.0},
     {'original_description': 'Low energy lighting in 2% of fixed outlets', 'low_energy_proportion': 0.02},
     {'original_description': 'No Low energy lighting', 'low_energy_proportion': 0}
 ]

model_data/tests/test_lighting_attributes.py

@@ -0,0 +1,60 @@
+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())