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rUv
acddd777a7
Record ADRs 421 to 423, actual dependency integration, bounded input and evidence authority, duration evaluation, security regressions and measured receipts. Preserve negative predictive and caching results; no model promotion.
97 lines
4.3 KiB
Python
97 lines
4.3 KiB
Python
import copy
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import json
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from pathlib import Path
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import tempfile
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import unittest
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from csi_training.active_evaluation import evaluate, load
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def fixture():
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budget = dict(packets=10, airtime_ms=20, energy_mj=30, available_sensors=["wifi", "radar"])
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sessions = []
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for i in range(4):
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sessions.append(dict(room=f"room{i}", session=f"session{i}",
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budget=dict(baseline=budget.copy(), candidate=budget.copy()), intervals=[
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dict(start_ms=0, end_ms=1000, truth="empty", baseline="occupied", candidate="empty"),
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dict(start_ms=1000, end_ms=2000, truth="occupied", baseline="occupied", candidate="occupied")]))
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return dict(schemaVersion=1, evidence="SYNTHETIC", sessions=sessions)
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class ActiveEvaluationTests(unittest.TestCase):
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def test_duration_and_gate_never_authorize_promotion(self):
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result = evaluate(fixture())
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self.assertEqual(result["metrics"]["false_duration_relative_reduction"], 1)
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self.assertEqual(result["numericalGate"], "pass")
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self.assertEqual(result["fieldAcceptance"], "not_established")
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self.assertFalse(result["promotionAuthorized"])
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def test_abstention_cannot_hide_recall_loss(self):
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doc = fixture()
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for session in doc["sessions"]:
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session["intervals"][1]["candidate"] = "unknown"
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result = evaluate(doc)
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self.assertEqual(result["metrics"]["candidate_recall"], 0)
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self.assertEqual(result["numericalGate"], "fail")
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def test_zero_baseline_or_one_room_is_inconclusive(self):
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doc = fixture()
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for session in doc["sessions"]:
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session["intervals"][0]["baseline"] = "empty"
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self.assertEqual(evaluate(doc)["numericalGate"], "inconclusive")
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self.assertEqual(evaluate({**fixture(), "sessions": fixture()["sessions"][:1]})["numericalGate"], "inconclusive")
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def test_abstention_on_empty_cannot_game_false_occupied_duration(self):
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doc = fixture()
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for session in doc["sessions"]:
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session["intervals"][0]["candidate"] = "unknown"
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result = evaluate(doc)
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self.assertEqual(result["metrics"]["false_duration_relative_reduction"], 1)
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self.assertEqual(result["metrics"]["unknown_empty_delta"], 1)
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self.assertEqual(result["numericalGate"], "fail")
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def test_recall_interval_not_conditioned_on_false_events(self):
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doc = fixture()
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for session in doc["sessions"]:
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session["intervals"][0]["baseline"] = "empty"
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result = evaluate(doc)
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self.assertEqual(result["bootstrap"]["valid"], 0)
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self.assertEqual(result["bootstrap"]["recall_valid"], 1000)
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self.assertEqual(result["bootstrap"]["recall_delta_interval"], [0, 0])
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def test_room_clustering_keeps_sessions_together(self):
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doc = fixture()
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doc["sessions"][1]["room"] = "room0"
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self.assertEqual(evaluate(doc)["rooms"], 3)
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def test_invalid_budget_timestamp_schema_and_truth(self):
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mutations = [lambda d: d["sessions"][0]["budget"]["candidate"].update(packets=11),
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lambda d: d["sessions"][0]["intervals"][1].update(start_ms=500),
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lambda d: d["sessions"][0]["intervals"][1].update(end_ms=float("nan")),
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lambda d: d["sessions"][0]["intervals"][1].update(truth="unknown"),
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lambda d: d["sessions"][0]["budget"]["candidate"].update(available_sensors=["extra"]),
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lambda d: d.update(schemaVersion=True),
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lambda d: d["sessions"].append(copy.deepcopy(d["sessions"][0]))]
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for mutation in mutations:
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doc = fixture()
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mutation(doc)
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with self.assertRaises(ValueError):
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evaluate(doc)
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def test_strict_file_reader(self):
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with tempfile.TemporaryDirectory() as directory:
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path = Path(directory) / "manifest.json"
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path.write_text(json.dumps(fixture()))
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self.assertEqual(evaluate(load(path))["numericalGate"], "pass")
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path.write_text('{"schemaVersion":1,"schemaVersion":2}')
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with self.assertRaises(ValueError):
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load(path)
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link = Path(directory) / "link"
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link.symlink_to(path)
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with self.assertRaises(OSError):
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load(link)
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if __name__ == "__main__":
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unittest.main()
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