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| import numpy as np | |
| from patch_view.patching import apply_patching, compute_patch_statistics | |
| def test_single_constraint_backward_compatibility(): | |
| metric = np.array([2.0, 3.0, 6.0, 2.0, 3.0, 4.0]) | |
| patches = apply_patching(metric, constraint="global", threshold=5.0) | |
| assert len(patches) == 2 | |
| assert patches[0] == [0, 1] | |
| assert patches[1] == [2, 3, 4, 5] | |
| def test_multi_constraint_combination(): | |
| metric = np.array([1.0, 2.0, 3.0, 8.0, 2.0, 3.0]) | |
| patches = apply_patching( | |
| metric, | |
| constraints={ | |
| "global": 5.0, | |
| "additive": 3.0, | |
| }, | |
| ) | |
| assert len(patches) == 2 | |
| assert patches[0] == [0, 1, 2] | |
| assert patches[1] == [3, 4, 5] | |
| def test_cumulative_constraint_behavior(): | |
| metric = np.array([2.0, 3.0, 4.0, 2.0, 3.0, 4.0]) | |
| patches = apply_patching(metric, constraints={"cumulative": 8.0}) | |
| assert len(patches) == 3 | |
| assert patches[0] == [0, 1] | |
| assert patches[1] == [2, 3, 4] | |
| assert patches[2] == [5] | |
| def test_cumulative_max_constraint_keeps_sums_small(): | |
| metric = np.array([2.0, 3.0, 4.0, 2.0, 3.0]) | |
| patches = apply_patching(metric, constraints={"cumulative_max": 8.0}) | |
| for patch in patches: | |
| patch_sum = np.sum(metric[patch]) | |
| assert patch_sum <= 11.0 # allow threshold plus one token overflow | |
| def test_compute_patch_statistics_matches_expected_values(): | |
| patches = [[0, 1], [2, 3, 4], [5]] | |
| stats = compute_patch_statistics(patches) | |
| assert stats["num_patches"] == 3 | |
| assert stats["avg_size"] == np.mean([2, 3, 1]) | |
| assert stats["min_size"] == 1 | |
| assert stats["max_size"] == 3 | |