def test_ndcg_score(self):
"""Different k."""
ground_truth = [1, 0, 2]
predictions = [[0.35, 0.05, 0.2], [0.1, 0.2, 0.3], [0.6, 0.04, 0.59]]
score = ndcg_score(ground_truth, predictions, k=1)
assert score == 0
score = ndcg_score(ground_truth, predictions, k=2)
assert score == 0.2103099178571525
score = ndcg_score(ground_truth, predictions, k=3)
assert score == 0.54364325119048584
def test_ndcg_score(self):
"""Different k."""
ground_truth = [1, 0, 2]
predictions = [
[0.35, 0.05, 0.2],
[0.1, 0.2, 0.3],
[0.6, 0.04, 0.59]
]
score = ndcg_score(ground_truth, predictions, k=1)
assert score == 0
score = ndcg_score(ground_truth, predictions, k=2)
assert score == 0.2103099178571525
score = ndcg_score(ground_truth, predictions, k=3)
assert score == 0.54364325119048584
def test_ndcg_score_perfect(self):
"""Perfect NDCG case."""
ground_truth = [1, 0, 2]
predictions = [
[0.15, 0.55, 0.2],
[0.7, 0.2, 0.1],
[0.06, 0.04, 0.9]
]
score = ndcg_score(ground_truth, predictions)
assert score == 1.0
def test_ndcg_score_perfect(self):
"""Perfect NDCG case."""
ground_truth = [1, 0, 2]
predictions = [[0.15, 0.55, 0.2], [0.7, 0.2, 0.1], [0.06, 0.04, 0.9]]
score = ndcg_score(ground_truth, predictions)
assert score == 1.0
