| """Tests for evaluation metrics.""" |
| import sys |
| from pathlib import Path |
| sys.path.insert(0, str(Path(__file__).parent.parent)) |
|
|
| import pytest |
| import numpy as np |
| from src.telern.evaluate import dcg_at_k, ndcg_at_k, mrr_at_k, compute_metrics |
|
|
|
|
| class TestDCG: |
| def test_empty(self): |
| assert dcg_at_k(np.array([]), 3) == 0.0 |
|
|
| def test_all_zeros(self): |
| assert dcg_at_k(np.zeros(10), 5) == 0.0 |
|
|
| def test_perfect_ranking(self): |
| scores = np.array([2.0, 2.0, 2.0, 1.0, 1.0]) |
| dcg = dcg_at_k(scores, 3) |
| expected = (3 / np.log2(2)) + (3 / np.log2(3)) + (3 / np.log2(4)) |
| assert abs(dcg - expected) < 1e-6 |
|
|
| def test_k_larger_than_array(self): |
| scores = np.array([2.0, 1.0]) |
| dcg = dcg_at_k(scores, 5) |
| assert dcg > 0 |
|
|
| def test_dcg_decreases_with_rank(self): |
| scores_good = np.array([2.0, 1.0, 0.0]) |
| scores_bad = np.array([0.0, 1.0, 2.0]) |
| assert dcg_at_k(scores_good, 3) > dcg_at_k(scores_bad, 3) |
|
|
|
|
| class TestNDCG: |
| def test_perfect(self): |
| scores = np.array([2.0, 1.0, 0.0]) |
| assert abs(ndcg_at_k(scores, 3) - 1.0) < 1e-6 |
|
|
| def test_all_zeros(self): |
| assert ndcg_at_k(np.zeros(10), 5) == 0.0 |
|
|
| def test_imperfect(self): |
| scores = np.array([1.0, 2.0, 0.0]) |
| ndcg = ndcg_at_k(scores, 3) |
| assert 0.0 < ndcg < 1.0 |
|
|
| def test_empty(self): |
| assert ndcg_at_k(np.array([]), 3) == 0.0 |
|
|
|
|
| class TestMRR: |
| def test_first_position(self): |
| scores = np.array([1.0, 0.0, 0.0]) |
| assert abs(mrr_at_k(scores, 3) - 1.0) < 1e-6 |
|
|
| def test_second_position(self): |
| scores = np.array([0.0, 1.0, 0.0]) |
| assert abs(mrr_at_k(scores, 3) - 0.5) < 1e-6 |
|
|
| def test_third_position(self): |
| scores = np.array([0.0, 0.0, 1.0]) |
| assert abs(mrr_at_k(scores, 3) - 1.0 / 3) < 1e-6 |
|
|
| def test_no_relevant(self): |
| scores = np.array([0.0, 0.0, 0.0]) |
| assert mrr_at_k(scores, 3) == 0.0 |
|
|
| def test_k_limit(self): |
| scores = np.array([0.0, 0.0, 1.0, 1.0]) |
| assert mrr_at_k(scores, 2) == 0.0 |
|
|
|
|
| class TestComputeMetrics: |
| def test_all_metrics_present(self): |
| metrics = compute_metrics(np.array([1.0, 0.0, 0.0, 0.0, 0.0])) |
| for k in [3, 5, 10]: |
| assert f"ndcg@{k}" in metrics |
| assert f"mrr@{k}" in metrics |
|
|
| def test_metric_values_in_range(self): |
| metrics = compute_metrics(np.array([1.0, 0.5, 0.0, 0.0, 0.2])) |
| for v in metrics.values(): |
| assert 0.0 <= v <= 1.0 |
|
|
| def test_custom_k(self): |
| metrics = compute_metrics(np.array([1.0, 0.0]), k_values=[1, 2]) |
| assert "ndcg@1" in metrics |
| assert "mrr@1" in metrics |
| assert "mrr@2" in metrics |
|
|
