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