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Calculate ranking recall from relevant items

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This commit is contained in:
Andras Schmelczer 2026-10-27 16:51:56 +00:00
commit 946ad4486c
1 changed files with 25 additions and 12 deletions
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20
tests/utilities/test_evaluate_ranking.py
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@ -16,7 +16,7 @@ def test_default() -> None:
reverse_order=True,
)
assert results == {"d": 5 / 6, "c": 2 / 3, "b": 2 / 5}
assert results == {"d": 1.0, "c": 1.0, "b": 1 / 2}
results = evaluate_ranking(
["a", "a", "b", "b", "c", "d", "d", "d"],
@ -26,7 +26,23 @@ def test_default() -> None:
disable_interpolation=True,
)
assert results == {"a": 0.6, "b": 0.4, "c": 0.2}
assert results == {"a": 2 / 3, "b": 2 / 5, "c": 2 / 7}
@pytest.mark.parametrize("disable_interpolation", [False, True])
def test_perfect_ranking_at_full_recall(disable_interpolation: bool) -> None:
assert evaluate_ranking(
[1, 1, 0, 0],
[4, 3, 2, 1],
target_recall=1,
disable_interpolation=disable_interpolation,
plot=False,
) == {0: 1.0}
def test_tied_scores_cannot_be_separated_by_a_threshold() -> None:
for labels in ([1, 0], [0, 1]):
assert evaluate_ranking(labels, [1, 1], target_recall=1, plot=False) == {0: 0.5}
def test_mismatching_lengths() -> None: