package com.flightfeather.uav.lightshare.service.impl
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import com.flightfeather.uav.biz.FactorFilter
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import com.flightfeather.uav.biz.dataanalysis.ExceptionAnalysisController
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import com.flightfeather.uav.biz.dataanalysis.model.ExceptionResult
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import com.flightfeather.uav.biz.report.MissionGridFusion
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import com.flightfeather.uav.biz.report.MissionInventory
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import com.flightfeather.uav.biz.report.MissionRiskArea
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import com.flightfeather.uav.biz.report.MissionSummary
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import com.flightfeather.uav.biz.sourcetrace.model.PollutedClue
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import com.flightfeather.uav.common.exception.BizException
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import com.flightfeather.uav.common.location.LocationRoadNearby
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import com.flightfeather.uav.common.utils.GsonUtils
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import com.flightfeather.uav.domain.entity.*
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import com.flightfeather.uav.domain.mapper.MissionMapper
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import com.flightfeather.uav.domain.repository.*
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import com.flightfeather.uav.lightshare.bean.AreaVo
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import com.flightfeather.uav.lightshare.bean.GridDataDetailMixVo
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import com.flightfeather.uav.lightshare.eunm.PollutionDegree
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import com.flightfeather.uav.lightshare.eunm.SceneType
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import com.flightfeather.uav.lightshare.service.DataAnalysisService
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import com.flightfeather.uav.lightshare.service.SatelliteDataCalculateService
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import com.flightfeather.uav.socket.eunm.FactorType
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import com.flightfeather.uav.socket.sender.MsgType
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import org.springframework.stereotype.Service
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import tk.mybatis.mapper.entity.Example
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import java.util.*
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/**
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* 数据分析服务接口实现类
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* 提供走航任务数据的统计分析、污染溯源、任务清单及详情生成等核心业务功能
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* 整合多数据源完成数据聚合与分析，为前端提供标准化的统计结果
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* @date 2025/5/8
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* @author feiyu02
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*/
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@Service
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class DataAnalysisServiceImpl(
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private val missionRep: MissionRep,
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private val missionMapper: MissionMapper,
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private val realTimeDataRep: RealTimeDataRep,
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private val locationRoadNearby: LocationRoadNearby,
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private val segmentInfoRep: SegmentInfoRep,
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private val sourceTraceRep: SourceTraceRep,
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private val sceneInfoRep: SceneInfoRep,
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private val satelliteGridRep: SatelliteGridRep,
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private val satelliteDataCalculateService: SatelliteDataCalculateService
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) : DataAnalysisService {
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/**
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* 污染溯源分析
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* 对指定走航任务进行多因子污染数据分析，识别异常数据点和潜在污染源
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* @param missionCode 走航任务编码（主键）
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* @return 异常结果列表，包含异常类型、位置、浓度值等详细信息
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* @throws BizException 当走航任务不存在时抛出
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* @see ExceptionAnalysisController 异常分析控制器，处理具体的数据分析逻辑
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*/
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override fun pollutionTrace(missionCode: String): List<ExceptionResult> {
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val mission = missionRep.findOne(missionCode) ?: throw BizException("走航任务不存在")
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val exceptionAnalysisController =
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ExceptionAnalysisController(realTimeDataRep, locationRoadNearby, segmentInfoRep)
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return exceptionAnalysisController.execute(
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mission, FactorFilter.builder()
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// .withMain(FactorType.NO2)
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.withMain(FactorType.CO)
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// .withMain(FactorType.H2S)
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// .withMain(FactorType.SO2)
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// .withMain(FactorType.O3)
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.withMain(FactorType.PM25)
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.withMain(FactorType.PM10)
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.withMain(FactorType.VOC)
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.create()
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)
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}
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/**
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* 获取历史污染溯源结果
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* 查询指定任务的历史污染溯源结果并序列化为JSON字符串
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* @param missionCode 走航任务编码
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* @return 历史污染溯源结果的JSON字符串，具体格式由sourceTraceRep实现决定
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* @throws BizException 当走航任务不存在时抛出
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*/
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override fun fetchHistory(missionCode: String): String {
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val mission = missionRep.findOne(missionCode) ?: throw BizException("走航任务不存在")
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val res = sourceTraceRep.fetchList(mission.deviceCode, mission.startTime, mission.endTime)
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return GsonUtils.gson.toJson(res)
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}
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/**
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* 生成走航任务汇总统计
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* 按时间范围和行政区划统计走航任务的关键指标（任务数量、异常率、平均里程等）
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* @param startTime 统计起始时间（包含）
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* @param endTime 统计结束时间（包含）
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* @param areaVo 区域参数，包含省、市、区三级行政区划编码
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* @return 汇总统计对象，包含任务总数、异常点数量、平均里程等核心指标
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* @see MissionSummary 汇总统计处理器，封装具体的统计逻辑实现
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*/
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override fun generateMissionSummary(startTime: Date, endTime: Date, areaVo: AreaVo): MissionSummary.Summary {
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val clues = mutableListOf<PollutedClue?>()
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val missions = missionRep.findByAreaAndTime(areaVo, startTime, endTime).onEach {
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it ?: return@onEach
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val clue = sourceTraceRep.fetchList(it.deviceCode, it.startTime, it.endTime, MsgType.PolClue) as List<PollutedClue?>
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clues.addAll(clue)
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}
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val summary = MissionSummary().execute(startTime, endTime, missions, clues)
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return summary
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}
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/**
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* 生成走航任务清单（按时间和区域筛选）
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* 根据时间范围和行政区划查询走航任务，并关联污染线索数据生成任务列表
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* @param startTime 查询起始时间（包含）
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* @param endTime 查询结束时间（包含）
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* @param areaVo 区域参数，包含省、市、区编码
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* @return 走航任务信息列表，每个元素包含任务基本信息和关联的污染线索
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* @see MissionRep.findByAreaAndTime 区域时间筛选数据源
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* @see generateMissionList 重载方法，处理已关联的数据对
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*/
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override fun generateMissionList(startTime: Date, endTime: Date, areaVo: AreaVo): List<MissionInventory.MissionInfo> {
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val missionClues = missionRep.findByAreaAndTime(areaVo, startTime, endTime).filterNotNull().map {
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it to sourceTraceRep.fetchList(it.deviceCode, it.startTime, it.endTime, MsgType.PolClue) as List<PollutedClue?>
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}
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return generateMissionList(missionClues)
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}
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/**
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* 生成走航任务清单（直接处理任务数据）
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* 接收已关联的任务-污染线索数据对，生成格式化的任务列表
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* @param missionClues 任务-污染线索数据对列表，Pair.first为任务对象，Pair.second为对应污染线索
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* @return 标准化的走航任务信息列表，包含任务基本属性和污染统计信息
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* @see MissionInventory 任务清单生成器，封装具体格式化逻辑
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*/
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override fun generateMissionList(missionClues: List<Pair<Mission, List<PollutedClue?>>>): List<MissionInventory.MissionInfo> {
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return MissionInventory().generateMissionList(missionClues)
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}
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/**
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* 生成走航任务详情（按时间和区域筛选）
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* 根据时间范围和行政区划查询任务，整合实时监测数据生成详细任务报告
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* @param startTime 查询起始时间（包含）
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* @param endTime 查询结束时间（包含）
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* @param areaVo 区域参数，包含省、市、区编码
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* @return 任务详情列表，每个元素包含任务完整信息、污染线索及实时监测数据
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* @see MissionRep.findByAreaAndTime 区域时间筛选数据源
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* @see realTimeDataRep.fetchData 实时数据获取接口
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*/
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override fun generateMissionDetail(startTime: Date, endTime: Date, areaVo: AreaVo): List<MissionInventory.MissionDetail> {
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val missionCluesData = missionRep.findByAreaAndTime(areaVo, startTime, endTime).filterNotNull().map {
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Triple(
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it,
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sourceTraceRep.fetchList(it.deviceCode, it.startTime, it.endTime, MsgType.PolClue) as List<PollutedClue?>,
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realTimeDataRep.fetchData(it)
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)
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}
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val keyScenes = sceneInfoRep.findBySceneTypes(
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listOf(
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SceneType.TYPE19.value,
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SceneType.TYPE20.value,
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SceneType.TYPE21.value
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)
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)
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return generateMissionDetail(keyScenes, missionCluesData)
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}
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/**
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* 生成走航任务详情（直接处理任务数据）
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* 接收已关联的任务-污染线索-实时数据三元组，生成详细任务报告
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* @param keyScenes 关键场景列表，用于分析走航是否经过该区域
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* @param missionCluesData 任务数据三元组列表，Triple分别为任务对象、污染线索列表、实时数据列表
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* @return 标准化的任务详情列表，包含完整的任务属性、污染分析和监测数据统计
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* @see MissionInventory.generateMissionDetail 详情生成核心逻辑
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*/
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override fun generateMissionDetail(
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keyScenes: List<SceneInfo?>,
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missionCluesData: List<Triple<Mission, List<PollutedClue?>, List<BaseRealTimeData>>>,
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): List<MissionInventory.MissionDetail> {
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return missionCluesData.map {
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MissionInventory().generateMissionDetail(keyScenes, it.first, it.second, it.third)
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}
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}
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override fun generateClueByRiskArea(
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startTime: Date,
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endTime: Date,
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areaVo: AreaVo,
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): List<MissionRiskArea.ClueByArea> {
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val clues = mutableListOf<PollutedClue?>()
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missionRep.findByAreaAndTime(areaVo, startTime, endTime).onEach {
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it ?: return@onEach
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val clue = sourceTraceRep.fetchList(it.deviceCode, it.startTime, it.endTime, MsgType.PolClue) as List<PollutedClue?>
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clues.addAll(clue)
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}
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val keyScenes = sceneInfoRep.findBySceneTypes(
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listOf(
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SceneType.TYPE19.value,
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SceneType.TYPE20.value,
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SceneType.TYPE21.value
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)
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)
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return generateClueByRiskArea(keyScenes, clues)
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}
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override fun generateClueByRiskArea(
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keyScenes: List<SceneInfo?>,
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pollutedClues: List<PollutedClue?>,
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): List<MissionRiskArea.ClueByArea> {
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return MissionRiskArea().generateClueByRiskArea(keyScenes, pollutedClues)
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}
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override fun generateGridFusion(
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factorTypes: List<FactorType>,
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startTime: Date,
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endTime: Date,
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areaVo: AreaVo,
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): List<MissionGridFusion.GridFusionByAQI> {
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val gridLen = 100
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// 查询100米网格的具体网格数据
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val gridGroup = satelliteGridRep.fetchGridGroup(GridGroup().apply {
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type = "sub"
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length = gridLen.toDouble()
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provinceCode = areaVo.provinceCode
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cityCode = areaVo.cityCode
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districtCode = areaVo.districtCode
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}).firstOrNull() ?: throw BizException("未查询到100米网格")
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val gridCells = satelliteGridRep.fetchGridCell(gridGroup.id).filterNotNull()
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// 查询范围内的所有走航任务
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val missions = missionRep.findByAreaAndTime(areaVo, startTime, endTime)
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// 根据空气质量等级分类
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val missionGroups = missions.groupBy { PollutionDegree.getByDes(it?.pollutionDegree ?: "") }
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// 查询每个等级下的走航任务对应的网格数据（如果没有数据则剔除该任务）
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val gridDataDetailList = missionGroups.mapNotNull { (degree, missionList) ->
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// 筛选出有网格融合数据的走航任务(同时获取对应的融合数据id列表)
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val gridDataIds = mutableListOf<Int>()
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val validMissions = missionList.filter {mission ->
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val gridData = satelliteGridRep.fetchGridData(GridData().apply { missionCode = mission?.missionCode }).firstOrNull()
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val res = gridData != null
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if (res) gridDataIds.add(gridData?.id ?: 0)
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res
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}
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// 合并每个等级下的网格数据
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val gridDataDetailMixVos = satelliteDataCalculateService.mixUnderwayGridData(gridGroup.id, gridDataIds)
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// 统计每个走航任务的走航详情信息
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val missionCluesData = validMissions.filterNotNull().map {
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Triple(
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it,
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sourceTraceRep.fetchList(it.deviceCode, it.startTime, it.endTime, MsgType.PolClue) as List<PollutedClue?>,
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realTimeDataRep.fetchData(it)
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)
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}
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val keyScenes = sceneInfoRep.findBySceneTypes(
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listOf(
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SceneType.TYPE19.value,
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SceneType.TYPE20.value,
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SceneType.TYPE21.value
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)
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)
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val missionDetails = generateMissionDetail(keyScenes, missionCluesData)
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return@mapNotNull Triple(degree, missionDetails, gridDataDetailMixVos)
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}.filter { it.second.isNotEmpty() }
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return generateGridFusion(factorTypes, gridLen, gridCells, gridDataDetailList)
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}
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override fun generateGridFusion(
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factorTypes: List<FactorType>,
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gridLen: Int,
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gridCells: List<GridCell>,
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dataList: List<Triple<PollutionDegree, List<MissionInventory.MissionDetail>, List<GridDataDetailMixVo>>>,
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): List<MissionGridFusion.GridFusionByAQI> {
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return MissionGridFusion(sceneInfoRep).generateGridFusion(factorTypes, gridLen, gridCells, dataList)
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}
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}
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