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| """Counterfactual consequence: cosmetic violations classify as | |
| NO_MATERIAL_CONSEQUENCE; a missed crossing pedestrian is SAFETY_CRITICAL; | |
| every verdict carries measured evidence from both branches.""" | |
| from __future__ import annotations | |
| import pytest | |
| from sensorflow.rotr.attribution import attribute | |
| from sensorflow.rotr.consequence import classify | |
| def classified(bank_v1, detections_v1): | |
| out = {} | |
| for sc in bank_v1: | |
| for v in detections_v1[sc.scenario_id]: | |
| attr = attribute(sc, v) | |
| out[v.violation_id] = (sc, v, attr, classify(sc, v, attr)) | |
| return out | |
| def _by_kind_cause(classified, kind, cause): | |
| return [t for t in classified.values() | |
| if t[0].planted.kind == kind and t[0].planted.cause_layer == cause] | |
| class TestClasses: | |
| def test_missed_crossing_pedestrian_is_safety_critical(self, classified): | |
| cases = _by_kind_cause(classified, "fail_yield_pedestrian", "perception") | |
| assert cases | |
| for sc, v, attr, cf in cases: | |
| assert cf.consequence_class == "SAFETY_CRITICAL" | |
| assert cf.observed_safety.min_clearance_m is not None | |
| assert cf.observed_safety.min_clearance_m < 1.5 | |
| def test_cosmetic_wrong_lane_is_no_material_consequence(self, classified): | |
| cases = _by_kind_cause(classified, "wrong_lane_association", | |
| "localization") | |
| assert cases | |
| for sc, v, attr, cf in cases: | |
| assert cf.consequence_class == "NO_MATERIAL_CONSEQUENCE" | |
| assert cf.planner_evaluation.max_position_divergence_m < 2.0 | |
| def test_control_fault_replays_the_plan(self, classified): | |
| cases = _by_kind_cause(classified, "stop_overshoot", "control") | |
| assert cases | |
| for sc, v, attr, cf in cases: | |
| assert cf.planner_evaluation.engine == "planned-trajectory" | |
| assert cf.consequence_class != "NO_MATERIAL_CONSEQUENCE" | |
| class TestEvidence: | |
| def test_both_branches_measured(self, classified): | |
| for sc, v, attr, cf in classified.values(): | |
| pe = cf.planner_evaluation | |
| assert pe.observed_trajectory and pe.corrected_trajectory | |
| assert pe.engine | |
| for sa in (cf.observed_safety, cf.corrected_safety): | |
| assert sa.max_braking_mps2 >= 0.0 | |
| assert "surrogate" in sa.surrogate_caveat.lower() or \ | |
| "TTC" in sa.surrogate_caveat | |
| def test_counterfactual_provenance_labeled(self, classified): | |
| for sc, v, attr, cf in classified.values(): | |
| assert cf.provenance.source == "COUNTERFACTUAL" | |
| assert cf.corrected_layers | |