72 lines
2.7 KiB
Python
72 lines
2.7 KiB
Python
"""L1: value grounding -- multi-column LSH exposure (spec D14a).
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The D14a deviation: a value cited in the question (e.g. 'ablazione') may match
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MULTIPLE columns (a boolean flag, a free-text patologia field). The old behavior
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collapsed matches to a single best column, hiding the alternative grounding.
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aggregate_lsh_multi exposes every column where the value appears, grouped by table,
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so the value-grounding widget can let the reviewer choose which column(s) anchor
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the value.
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"""
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from tht.search import aggregate_lsh_multi
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def test_value_in_multiple_columns_returns_all():
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hits = [
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{"table": "t", "column": "c1", "value": "ablazione", "score": 0.9},
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{"table": "t", "column": "c2", "value": "ablazione", "score": 0.7},
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]
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result = aggregate_lsh_multi(hits)
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# NOT collapsed to single best -- both columns exposed
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cols = {h["column"] for h in result["t"]}
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assert cols == {"c1", "c2"}
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def test_values_grouped_by_table():
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hits = [
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{"table": "pazienti", "column": "flag_abl", "value": "ablazione", "score": 0.9},
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{"table": "ricoveri", "column": "procedura", "value": "ablazione", "score": 0.6},
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]
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result = aggregate_lsh_multi(hits)
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assert set(result.keys()) == {"pazienti", "ricoveri"}
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assert result["pazienti"][0]["column"] == "flag_abl"
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assert result["ricoveri"][0]["column"] == "procedura"
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def test_within_column_keeps_best_value():
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# two hits on the SAME column: keep the best-scored value (no duplicate rows
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# for one column), but the column still appears once.
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hits = [
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{"table": "t", "column": "c", "value": "ablazione", "score": 0.9},
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{"table": "t", "column": "c", "value": "ablaz", "score": 0.5},
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]
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result = aggregate_lsh_multi(hits)
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rows = result["t"]
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assert len(rows) == 1
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assert rows[0]["value"] == "ablazione" # best score kept
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assert rows[0]["score"] == 0.9
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def test_columns_ordered_by_score_desc_within_table():
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hits = [
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{"table": "t", "column": "low", "value": "x", "score": 0.3},
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{"table": "t", "column": "high", "value": "x", "score": 0.95},
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{"table": "t", "column": "mid", "value": "x", "score": 0.6},
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]
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result = aggregate_lsh_multi(hits)
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cols = [h["column"] for h in result["t"]]
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assert cols == ["high", "mid", "low"]
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def test_empty_hits_returns_empty():
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assert aggregate_lsh_multi([]) == {}
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def test_value_grounded_decision_type_exists():
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# D14a adds the value_grounded decision type so the gate can record the
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# reviewer's choice of which column(s) anchor a cited value.
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import typing
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from tht.decisions import DecisionType
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args = typing.get_args(DecisionType)
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assert "value_grounded" in args
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