33 lines
1.2 KiB
Python
33 lines
1.2 KiB
Python
import polars as pl
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from pipeline.transform.merge import (
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_is_dynamic_poi_metric_column,
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_less_deprived_percentile_expr,
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)
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def test_less_deprived_percentile_expr_preserves_direction_and_nulls() -> None:
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df = pl.DataFrame({"Income Score (rate)": [1.0, 2.0, 3.0, None]})
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result = df.lazy().with_columns(
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_less_deprived_percentile_expr("Income Score (rate)")
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).collect()
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assert result["Income Score (rate)"].to_list() == [100.0, 50.0, 0.0, None]
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def test_less_deprived_percentile_expr_uses_exact_scale_endpoints() -> None:
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df = pl.DataFrame({"Income Score (rate)": [1.0, 1.0, 2.0, 3.0, 3.0]})
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result = df.lazy().with_columns(
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_less_deprived_percentile_expr("Income Score (rate)")
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).collect()
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assert result["Income Score (rate)"].to_list() == [100.0, 100.0, 50.0, 0.0, 0.0]
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def test_dynamic_poi_metric_columns_are_area_level() -> None:
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assert _is_dynamic_poi_metric_column("Distance to nearest Cafe POI (km)")
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assert _is_dynamic_poi_metric_column("Number of Cafe POIs within 2km")
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assert _is_dynamic_poi_metric_column("Number of Cafe POIs within 5km")
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assert not _is_dynamic_poi_metric_column("Number of restaurants within 2km")
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