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added tests for averages cleaning

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Khalim Conn-Kowlessar 2026-03-11 21:03:20 +00:00
parent 3bf641f49d
commit 12d1223f17
1 changed files with 85 additions and 0 deletions
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85
etl/epc/tests/test_epcrecord.py
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@ -309,3 +309,88 @@ class TestEpcRecord:
base_record._apply_cleaning_rules()
assert base_record._prepared_epc["extension-count"] == 2
def test_apply_averages_cleaning_fills_missing_values(self, cleaning_data):
record = EPCRecord(run_mode="training", cleaning_data=cleaning_data)
record._prepared_epc = {
"property-type": cleaning_data["property_type"].iloc[0],
"local-authority": cleaning_data["local_authority"].iloc[0],
"total-floor-area": float(cleaning_data["total_floor_area"].iloc[0]),
"number-habitable-rooms": None,
"number-heated-rooms": None,
"floor-height": None,
}
record._apply_averages_cleaning()
assert record._prepared_epc["number-habitable-rooms"] is not None
assert record._prepared_epc["number-heated-rooms"] is not None
assert record._prepared_epc["floor-height"] is not None
def test_apply_averages_cleaning_no_missing(self, cleaning_data):
record = EPCRecord(run_mode="training", cleaning_data=cleaning_data)
record._prepared_epc = {
"property-type": cleaning_data["property_type"].iloc[0],
"local-authority": cleaning_data["local_authority"].iloc[0],
"total-floor-area": float(cleaning_data["total_floor_area"].iloc[0]),
"number-habitable-rooms": 5,
"number-heated-rooms": 5,
"floor-height": 2.5,
}
original = record._prepared_epc.copy()
record._apply_averages_cleaning()
assert record._prepared_epc == original
def test_apply_averages_cleaning_caps_heated_rooms(self, cleaning_data):
record = EPCRecord(run_mode="training", cleaning_data=cleaning_data)
record._prepared_epc = {
"property-type": cleaning_data["property_type"].iloc[0],
"local-authority": cleaning_data["local_authority"].iloc[0],
"total-floor-area": float(cleaning_data["total_floor_area"].iloc[0]),
"number-habitable-rooms": None,
"number-heated-rooms": None,
"floor-height": None,
}
record._apply_averages_cleaning()
assert (
record._prepared_epc["number-heated-rooms"]
<= record._prepared_epc["number-habitable-rooms"]
)
def test_apply_averages_cleaning_floor_area_filter(self, cleaning_data):
record = EPCRecord(run_mode="training", cleaning_data=cleaning_data)
floor_area = float(cleaning_data["total_floor_area"].median())
record._prepared_epc = {
"property-type": cleaning_data["property_type"].iloc[0],
"local-authority": cleaning_data["local_authority"].iloc[0],
"total-floor-area": floor_area,
"number-habitable-rooms": None,
"number-heated-rooms": None,
"floor-height": None,
}
record._apply_averages_cleaning()
assert record._prepared_epc["floor-height"] > 0
def test_apply_averages_cleaning_requires_cleaning_data(self):
record = EPCRecord(run_mode="training", cleaning_data=None)
record._prepared_epc = {}
with pytest.raises(ValueError):
record._apply_averages_cleaning()