| from crosswire.study import RunConfig, run | |
| def test_classical_learner_cannot_spend_past_cap_to_finish_model(): | |
| result = run(RunConfig(family='latch', policy='aalpy', budget=4)) | |
| assert result['metrics']['target_steps'] <= 4 | |
| assert result['metrics']['target_calls'] <= 4 | |
| assert result['baseline']['library'] == 'aalpy' | |
| assert result['baseline']['version'] == '1.6.2' | |
| if not result['baseline']['model_complete']: | |
| assert result['decision']['admitted'] is False | |
| def test_classical_baseline_is_reproducible_without_global_rng_changes(): | |
| import random | |
| random.seed(813) | |
| before = random.getstate() | |
| a = run(RunConfig(family='latch', policy='aalpy', budget=32)) | |
| b = run(RunConfig(family='latch', policy='aalpy', budget=32)) | |
| assert a['scientific_hash'] == b['scientific_hash'] | |
| assert random.getstate() == before | |
| def test_completed_classical_model_reports_comparison_transition_work(): | |
| result = run(RunConfig(family='latch', policy='aalpy', budget=256)) | |
| detail = result['baseline'] | |
| assert result['metrics']['target_calls'] <= 256 | |
| if detail['model_complete'] and detail['model_product_pairs']: | |
| assert detail['comparison_source_steps'] > 0 | |
| assert detail['comparison_hypothesis_steps'] > 0 | |