tests/test_iaa.py

import csv

from legex.analysis.iaa import (
    PRIMARY,
    cohen_kappa,
    pairwise_agreement,
    summarise_by_field,
    write_kappa_audit_csv,
)


def test_cohen_kappa_perfect_agreement() -> None:
    pairs = [("a", "a"), ("b", "b"), ("a", "a"), ("b", "b")]
    assert cohen_kappa(pairs) == 1.0


def test_cohen_kappa_chance_agreement_is_zero() -> None:
    # Both annotators split 50/50 but never coincide better than chance.
    pairs = [("a", "a"), ("a", "b"), ("b", "a"), ("b", "b")]
    k = cohen_kappa(pairs)
    assert k is not None
    assert abs(k) < 1e-9


def test_cohen_kappa_single_category_undefined() -> None:
    assert cohen_kappa([("a", "a"), ("a", "a")]) is None


def test_cohen_kappa_too_few_items() -> None:
    assert cohen_kappa([("a", "b")]) is None


def _labels_two_annotators():
    # Two annotators, one country, three cases, two fields.
    return {
        (PRIMARY, "ch", "c1"): {"f1": "x", "f2": "1"},
        (PRIMARY, "ch", "c2"): {"f1": "y", "f2": "2"},
        (PRIMARY, "ch", "c3"): {"f1": "z", "f2": ""},
        ("de", "ch", "c1"): {"f1": "x", "f2": "1"},
        ("de", "ch", "c2"): {"f1": "WRONG", "f2": "2"},
        ("de", "ch", "c3"): {"f1": "z", "f2": ""},
    }


def test_pairwise_agreement_counts() -> None:
    rows = pairwise_agreement(_labels_two_annotators())
    by_field = {r.field: r for r in rows}
    assert by_field["f1"].n == 3
    assert by_field["f1"].n_agree_exact == 2  # c1, c3 agree; c2 differs
    assert by_field["f2"].n_agree_exact == 3
    assert by_field["f2"].pct_exact == 1.0


def test_pairwise_tolerant_handles_numeric() -> None:
    labels = {
        (PRIMARY, "ch", "c1"): {"amount": "1500"},
        ("de", "ch", "c1"): {"amount": "1500.0"},
    }
    rows = pairwise_agreement(labels)
    assert rows[0].n_agree_tolerant == 1


def test_summarise_by_field_weights_by_n() -> None:
    rows = pairwise_agreement(_labels_two_annotators())
    summary = summarise_by_field(rows)
    assert summary["f2"]["pct_exact"] == 1.0
    assert 0.0 <= summary["f1"]["pct_exact"] <= 1.0


def test_write_kappa_audit_csv(tmp_path) -> None:
    labels = {
        (PRIMARY, "ch", "c1"): {"f1": "x", "amount": "1500"},
        (PRIMARY, "ch", "c2"): {"f1": "y", "amount": "10"},
        ("de", "ch", "c1"): {"f1": "x", "amount": "1500.0"},
        ("de", "ch", "c2"): {"f1": "WRONG", "amount": "10"},
    }
    path = tmp_path / "kappa_audit.csv"
    n = write_kappa_audit_csv(labels, path)
    rows = list(csv.DictReader(path.open(encoding="utf-8")))
    # 1 country, 1 pair, 2 shared cases, 2 fields -> 4 cells.
    assert n == 4 == len(rows)
    cell = {(r["case_id"], r["field"]): r for r in rows}
    # f1 on c1 agrees both ways; amount 1500 vs 1500.0 is tolerant-only.
    assert cell[("c1", "f1")]["decision_exact"] == "yes"
    assert cell[("c1", "f1")]["decision_tolerant"] == "yes"
    assert cell[("c1", "amount")]["decision_exact"] == "no"
    assert cell[("c1", "amount")]["decision_tolerant"] == "yes"
    # f1 on c2 disagrees both ways.
    assert cell[("c2", "f1")]["decision_exact"] == "no"
    assert cell[("c2", "f1")]["decision_tolerant"] == "no"