""" 暴雨灾害链预测接口 """ import asyncio from datetime import datetime from typing import List, Dict, Any, Optional from fastapi import APIRouter, HTTPException from app.schemas.api_schemas import RainfallPredictRequest, PredictResponse, PredictionItem, UpdateMonitoringTimeRequest from app.utils.api_deps import get_rainfall_model, get_prediction_semaphore from app.repositories.dbn_repository import dbn_repository from app.core.rainfall_manager import rainfall_manager from app.config.paths import get_logger from app.utils.time_converter import TimeConverter router = APIRouter(prefix="/rainfall", tags=["暴雨灾害链"]) logger = get_logger("api.rainfall") SOURCE_TYPE_MAP = {1: "隐患点", 2: "风险点"} LEVEL_MAP = {"低": "低", "中": "中", "较高": "较高", "高": "高"} def _build_prediction_items(results: List[Dict[str, Any]]) -> List[PredictionItem]: """将模型原始结果转换为接口返回格式""" items = [] for r in results: probs = r.get("disaster_probabilities", {}) levels = r.get("disaster_levels", {}) if not probs: continue max_hazard = max(probs, key=probs.get) items.append(PredictionItem( id=r["source_id"], # 使用 source_id(隐患点/风险点ID)而非 xian_risk_factors.id type=SOURCE_TYPE_MAP.get(r.get("source_type"), "未知"), probability=round(probs[max_hazard], 4), level=LEVEL_MAP.get(levels.get(max_hazard, "none"), "无"), )) return items def _fetch_points(point_ids: Optional[List[int]], region_code: Optional[str]) -> List[Dict[str, Any]]: """获取点位列表""" if point_ids: return dbn_repository.get_points_by_ids(point_ids) return dbn_repository.get_all_points(region_code) def _predict_sync(point_ids: Optional[List[int]], region_code: Optional[str], rainfall: Optional[float], duration: Optional[float], operation_type: str) -> tuple: """ 同步执行暴雨预测(在线程池中运行) Returns: (预测结果列表, 原始结果, 输入条件, 当前时间) """ points = _fetch_points(point_ids, region_code) if not points: return [], [], {}, datetime.now() model = get_rainfall_model() raw_results = model.predict_multiple_points(points, rainfall=rainfall, duration=duration) items = _build_prediction_items(raw_results) # 构建条件和结果用于保存 now = datetime.now() condition = { "point_ids": point_ids, "region_code": region_code, "rainfall": rainfall, "duration": duration } save_results = [ { "point_id": r.get("source_id"), # 使用 source_id(隐患点/风险点ID)而非 xian_risk_factors.id "source_type": r.get("source_type"), "lon": r.get("lon"), "lat": r.get("lat"), "disaster_probabilities": r.get("disaster_probabilities", {}), "disaster_levels": r.get("disaster_levels", {}) } for r in raw_results ] return items, save_results, condition, now @router.post("/update-monitoring-time", summary="更新降雨监测查询时间") async def update_monitoring_time(req: UpdateMonitoringTimeRequest): """ 更新降雨站点监测的查询时间,触发重新计算 - **query_time**: 新的查询时间,格式: YYYY-MM-DD HH:mm:ss """ try: # 将字符串时间解析为 datetime 对象 new_time = TimeConverter.parse_input_time(req.query_time) # 更新监测时间,触发重新计算 result = rainfall_manager.update_query_time(new_time) logger.info(f"更新监测时间成功: {result}") return { "code": 200, "message": "success", "data": result } except ValueError as e: logger.error(f"时间格式错误: {e}") raise HTTPException(status_code=400, detail=f"时间格式错误: {e}") except Exception as e: logger.error(f"更新监测时间失败: {e}", exc_info=True) raise HTTPException(status_code=500, detail=f"更新监测时间失败: {e}") @router.post("/predict", response_model=PredictResponse, summary="暴雨灾害链预测") async def predict_rainfall(req: RainfallPredictRequest): """ 根据降雨量和持续时间,批量预测隐患点/风险点的灾害概率和等级。 - **point_ids**: 点位ID列表(可选,不传则查询所有点) - **region_code**: 行政区划代码(可选,不传则不限区域) - **rainfall**: 累计降雨量(mm),不传则从气象表自动获取 - **duration**: 降雨持续时间(h),不传则从气象表自动获取 - **operation_type**: 操作类型(如 '实时监测', '情景模拟', '应急评估') """ semaphore = get_prediction_semaphore() async with semaphore: loop = asyncio.get_event_loop() try: items, save_results, condition, now = await loop.run_in_executor( None, _predict_sync, req.point_ids, req.region_code, req.rainfall, req.duration, req.operation_type ) except Exception as e: logger.error(f"暴雨预测失败: {e}", exc_info=True) raise HTTPException(status_code=500, detail=f"预测失败: {e}") # 保存推理结果 record_id = None if save_results: try: record_id = dbn_repository.save_inference_result( event_type="rainfall", occurred_time=now, operation_type=req.operation_type, condition=condition, result=save_results ) logger.info(f"推理结果已保存,record_id={record_id}") except Exception as e: logger.error(f"保存推理结果失败: {e}", exc_info=True) return PredictResponse(code=200, message="success", data=items, record_id=record_id)