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.
113 lines
6.2 KiB
Python
113 lines
6.2 KiB
Python
"""Estimate a scenario's time-cumulative concentration coverage before output filtering."""
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from datetime import datetime, timedelta
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from math import isfinite
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from typing import Any
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from app.services.node_coverage import MAX_COVERAGE_NODES, generate_node_coverage
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def _sample_times(start: datetime, duration: int, metadata: dict) -> list[datetime]:
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explicit = metadata.get("sample_times")
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if explicit is not None:
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times = [datetime.fromisoformat(value) for value in explicit]
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else:
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offset, step, count = (metadata.get(key) for key in ("report_start", "report_step", "num_periods"))
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if (any(type(value) is not int for value in (offset, step, count))
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or offset < 0 or step <= 0 or not 0 < count <= 86401):
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raise ValueError("missing or invalid report grid")
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times = [start + timedelta(seconds=offset + index * step) for index in range(count)]
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if (not times or len(times) > 86401 or any(at.tzinfo is None for at in times)
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or any(not start <= at <= start + timedelta(seconds=duration) for at in times)
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or any(left >= right for left, right in zip(times, times[1:]))):
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raise ValueError("invalid simulation sample times")
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return times
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def estimate_contaminant_impact(network: str, start: datetime, duration: int,
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simulation: dict[str, Any], *, threshold_mg_l: float = 0,
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model_only: bool = False) -> dict[str, Any]:
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"""Use every native node and report sample; never infer propagation from requested nodes."""
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impact: dict[str, Any] = {
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"status": "unavailable", "phase": "after_contamination_before_intervention",
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"window_start": start.isoformat(), "window_end": (start + timedelta(seconds=duration)).isoformat(),
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"threshold_mg_l": threshold_mg_l, "threshold_operator": ">", "concentration_unit": "mg/L",
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"threshold_purpose": "scenario_display_not_drinking_water_standard",
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"model_temporality": "current_model", "quantity": "total_model_concentration",
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"boundary_source": "model_only_no_live_scada" if model_only else "model_with_start_time_scada",
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"boundary": "给定源浓度、模型初始水质及反应条件下，整个模拟时段内超过展示阈值的节点覆盖；"
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"首达时间为首个超过阈值的报告采样时刻。不是污染确诊、源独立贡献、现场污染边界或饮用水合格判定。",
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}
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output = {"impact": impact}
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unit = simulation.get("units", {}).get("quality")
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factor = {"mgl": 1.0, "mg/l": 1.0, "ugl": 0.001, "ug/l": 0.001}.get(
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str(unit).strip().lower().replace("μ", "u").replace("µ", "u"))
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impact["input_concentration_unit"] = unit
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if factor is None:
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impact["reason"] = "unsupported_or_missing_concentration_unit"
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return output
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try:
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times = _sample_times(start, duration, simulation.get("times", {}))
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except (TypeError, ValueError, OverflowError):
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impact["reason"] = "simulation_has_no_verified_sample_times"
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return output
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rows = simulation.get("node_results", [])
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ids = [str(row["node"]) for row in rows]
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if not ids or len(ids) != len(set(ids)):
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impact["reason"] = "missing_or_duplicate_simulation_nodes"
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return output
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affected, unavailable, incomplete = [], [], []
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for row in rows:
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node = str(row["node"])
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samples = row.get("result") or []
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if len(samples) > len(times):
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impact["reason"] = "simulation_sample_count_mismatch"
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return output
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valid = []
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for at, sample in zip(times, samples):
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value = sample.get("quality") if isinstance(sample, dict) else None
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if isinstance(value, bool) or value is None:
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continue
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try:
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concentration = float(value) * factor
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except (TypeError, ValueError, OverflowError):
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continue
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if isfinite(concentration) and concentration >= 0:
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valid.append((at, concentration))
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if not valid:
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unavailable.append(node)
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continue
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if len(valid) != len(times):
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incomplete.append(node)
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exceedances = [(at, value) for at, value in valid if value > threshold_mg_l]
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if exceedances:
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peak_at, peak = max(valid, key=lambda item: item[1])
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affected.append({"node_id": node, "first_exceedance_sample_at": exceedances[0][0].isoformat(),
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"peak_mg_l": peak, "peak_at": peak_at.isoformat(),
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"valid_sample_count": len(valid), "complete": len(valid) == len(times)})
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impact.update(status="partial" if unavailable or incomplete else "ready",
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node_count=len(ids), report_sample_count=len(times),
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reported_from=times[0].isoformat(), reported_through=times[-1].isoformat(),
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unavailable_node_ids=unavailable, incomplete_node_ids=incomplete,
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affected_node_count=len(affected), nodes=affected,
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affected_node_ids=[item["node_id"] for item in affected])
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if len(unavailable) == len(ids):
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impact.update(status="unavailable", reason="no_valid_concentration_samples")
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return output
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if len(affected) > MAX_COVERAGE_NODES:
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impact.update(coverage_status="unavailable", coverage_reason="affected_nodes_exceed_10000_coverage_limit")
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return output
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geometry = generate_node_coverage(network, [{
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"group_id": "contaminant_exposure", "title": f"模拟浓度>{threshold_mg_l:g} mg/L的累计节点范围",
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"node_ids": impact["affected_node_ids"],
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}])
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impact["coverage_status"] = geometry["coverage"]["status"]
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geometry["coverage"]["boundary"] = impact["boundary"]
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for feature in geometry["map_payload"]["features"]:
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feature["properties"].update(impact_phase=impact["phase"], concentration_unit="mg/L",
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threshold_mg_l=threshold_mg_l, model_estimate=True,
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window_start=impact["window_start"], window_end=impact["window_end"])
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if geometry["coverage"]["status"] == "partial":
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impact["status"] = "partial"
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output.update(geometry)
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return output
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