wzy-warehouse
129 lines
4.8 KiB
Python
129 lines
4.8 KiB
Python
"""
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地震灾害链预测接口
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"""
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import asyncio
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from typing import List, Dict, Any, Optional
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from fastapi import APIRouter, HTTPException
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from app.schemas.api_schemas import EarthquakePredictRequest, PredictResponse, PredictData
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from app.utils.api_deps import get_earthquake_model, get_prediction_semaphore
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from app.repositories.dbn_repository import dbn_repository
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from app.config.paths import get_logger
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router = APIRouter(prefix="/earthquake", tags=["地震灾害链"])
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logger = get_logger("api.earthquake")
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SOURCE_TYPE_MAP = {1: "隐患点", 2: "风险点"}
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LEVEL_MAP = {"低": "低", "中": "中", "较高": "较高", "高": "高"}
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def _build_prediction_map(results: List[Dict[str, Any]]) -> Dict[str, float]:
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"""将模型原始结果转换为存储格式: {id_type: 概率百分比}"""
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result_map = {}
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for r in results:
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probs = r.get("disaster_probabilities", {})
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if not probs:
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continue
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source_id = r["source_id"]
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source_type = r.get("source_type")
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max_hazard = max(probs, key=probs.get)
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# key 格式: {source_id}_{source_type}，value 为百分比概率
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key = f"{source_id}_{source_type}"
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result_map[key] = round(probs[max_hazard] * 100, 2)
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return result_map
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def _fetch_points(point_ids: Optional[List[int]], region_code: Optional[str]) -> List[Dict[str, Any]]:
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"""获取点位列表"""
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if point_ids:
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return dbn_repository.get_points_by_ids(point_ids)
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return dbn_repository.get_all_points(region_code)
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def _predict_sync(point_ids: Optional[List[int]], region_code: Optional[str],
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magnitude: float, depth: float,
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epicenter_lon: float, epicenter_lat: float) -> tuple:
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"""
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同步执行地震预测（在线程池中运行）
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Returns:
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(结果map,)
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"""
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points = _fetch_points(point_ids, region_code)
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if not points:
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return {}
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model = get_earthquake_model()
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raw_results = model.predict_multiple_points(
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points,
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magnitude=magnitude,
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depth=depth,
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epicenter_lon=epicenter_lon,
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epicenter_lat=epicenter_lat,
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)
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result_map = _build_prediction_map(raw_results)
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return result_map
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@router.post("/predict", response_model=PredictResponse, summary="地震灾害链预测")
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async def predict_earthquake(req: EarthquakePredictRequest):
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"""
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根据震级、震源深度和震中位置，批量预测隐患点/风险点的次生灾害概率。
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- **disaster_name**: 灾害名称
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- **point_ids**: 点位ID列表（可选，不传则查询所有点）
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- **region_code**: 行政区划代码（可选，不传则不限区域）
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- **magnitude**: 震级(Richter)
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- **depth**: 震源深度(km)，默认10km
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- **epicenter_lon**: 震中经度
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- **epicenter_lat**: 震中纬度
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- **occurred_time**: 地震发生时间
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- **operation_type**: 操作类型（如 '实时监测', '情景模拟', '应急评估'）
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"""
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semaphore = get_prediction_semaphore()
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async with semaphore:
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loop = asyncio.get_event_loop()
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try:
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result_map = await loop.run_in_executor(
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None, _predict_sync, req.point_ids, req.region_code,
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req.magnitude, req.depth, req.epicenter_lon, req.epicenter_lat
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)
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except Exception as e:
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logger.error(f"地震预测失败: {e}", exc_info=True)
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raise HTTPException(status_code=500, detail=f"预测失败: {e}")
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# 保存推理结果
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record_id = None
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if result_map:
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try:
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# 使用传入的 occurred_time，如果未传则使用当前时间
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from datetime import datetime
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occurred_time = req.occurred_time if req.occurred_time else datetime.now()
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# 存储经过默认值处理的条件
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condition = {
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"point_ids": req.point_ids,
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"region_code": req.region_code,
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"magnitude": req.magnitude,
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"depth": req.depth, # 已有默认值 10.0
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"epicenter_lon": req.epicenter_lon,
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"epicenter_lat": req.epicenter_lat,
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"occurred_time": occurred_time.isoformat() if hasattr(occurred_time, 'isoformat') else str(occurred_time)
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}
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record_id = dbn_repository.save_inference_result(
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disaster_name=req.disaster_name,
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event_type="earthquake",
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occurred_time=occurred_time,
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operation_type=req.operation_type,
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condition=condition,
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result=result_map
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)
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logger.info(f"推理结果已保存，record_id={record_id}")
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except Exception as e:
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logger.error(f"保存推理结果失败: {e}", exc_info=True)
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return PredictResponse(code=200, message="success", data=PredictData(record_id=record_id, list=result_map))
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