jiang
2e4f6cb93b
Add isolated burst and pollution impact evidence, parallel work-order workflows, persisted notifications and graph updates. Checkpoint current code. Known follow-ups remain for large pollution result previews and graceful geometry failure.
60 lines
2.6 KiB
Python
60 lines
2.6 KiB
Python
"""Clock-phase normal envelopes frozen before replay; never inspect future readings."""
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from datetime import datetime
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from math import isfinite
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CALIBRATION_VERSION = "scada-monitor-calibration@2"
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DIAGNOSTIC_POLICY = "normal-phase-envelope@1"
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def weighted_diagnosis(document: dict) -> bool:
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return (document.get("monitoring_config") or {}).get("decision_policy") == "weighted"
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def current_calibration(document: dict, start: datetime) -> dict | None:
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calibration = document.get("monitoring_calibration") or {}
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if (calibration.get("version") == CALIBRATION_VERSION
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and calibration.get("diagnostic_policy") == DIAGNOSTIC_POLICY
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and calibration.get("knowledge_cutoff") == start.isoformat()):
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return calibration
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return None
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def pollution_signal(document: dict, event: dict) -> bool:
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"""Water-quality measurements have their own incident investigation workflow."""
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if event.get("category") == "data_quality":
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return False
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devices = {item["device_id"]: item.get("device_type") for item in document.get("devices", [])}
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ids = event.get("device_ids") or next((item.get("device_ids", [])
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for item in (document.get("config") or {}).get("rules", [])
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if item["rule_id"] == event.get("rule_id")), [])
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return bool(ids) and all(devices.get(device) in {"quality", "water_quality"} for device in ids)
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def diagnostic_signal(document: dict, event: dict) -> bool:
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"""Never revive a persisted fixed-percentage event as new diagnosis evidence."""
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if event.get("category") == "data_quality" or pollution_signal(document, event):
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return False
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if not weighted_diagnosis(document):
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return True
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rules = (document.get("config") or {}).get("rules", [])
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rule = next((item for item in rules if item["rule_id"] == event["rule_id"]), None)
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return bool(rule and (rule["kind"] == "bounds" or event.get("diagnostic_policy") == DIAGNOSTIC_POLICY))
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def normal_profile_bounds(profile: dict | None, at: datetime) -> tuple[float, float] | None:
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if not profile:
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return None
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interval = profile.get("interval_seconds", 0)
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if not profile.get("phase_origin"):
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return None
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origin = datetime.fromisoformat(profile["phase_origin"])
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lower, upper = profile.get("lower", []), profile.get("upper", [])
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offset = (at - origin).total_seconds()
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if interval <= 0 or offset < 0 or offset % interval or not lower or len(lower) != len(upper):
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return None
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slot = int(offset // interval) % len(lower)
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low, high = lower[slot], upper[slot]
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if low is None or high is None or not isfinite(low) or not isfinite(high):
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return None
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return float(low), float(high)
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