package com.flightfeather.uav.biz.sourcetrace.model
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import com.flightfeather.uav.biz.FactorFilter
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import com.flightfeather.uav.biz.dataanalysis.model.ExceptionTag
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import com.flightfeather.uav.biz.dataanalysis.model.ExceptionType
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import com.flightfeather.uav.biz.sourcetrace.config.RTExcWindLevelConfig
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import com.flightfeather.uav.common.utils.DateUtil
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import com.flightfeather.uav.domain.entity.BaseRealTimeData
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import com.flightfeather.uav.domain.entity.avg
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import com.flightfeather.uav.lightshare.bean.DataVo
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import com.flightfeather.uav.socket.eunm.FactorType
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import java.util.Date
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import kotlin.math.round
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/**
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* 污染数据
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* @date 2025/5/27
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* @author feiyu02
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*/
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class PollutedData() {
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companion object {
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// 默认数据采样时间间隔，单位：秒
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const val DEFAULT_PERIOD = 4
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}
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/**
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* 异常数据分组情况统计
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*/
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inner class ExcGroup{
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constructor(dataIndexList: List<Int>, factorType: FactorType){
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this.dataIndexList = dataIndexList
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this.factorType = factorType
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val first = getFirstDataValue()?.toDouble()
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val last = getLastDataValue()?.toDouble()
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if (first != null && last != null) {
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per = round((last - first) / first * 100) / 100
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rate = round((last - first) / DEFAULT_PERIOD * 100) / 100
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}
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}
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var factorType: FactorType? = null
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/**
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* 异常数据对应历史数据[historyDataList]中的索引值
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*/
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var dataIndexList: List<Int>? = null
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// 变化幅度
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var per: Double? = null
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// 变化速率
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var rate: Double? = null
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/**
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* 获取异常数据的第一个数据
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* !!!!第一个数据其实是首个异常数据的前一个数据值!!!!
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*/
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fun getFirstData(): BaseRealTimeData? {
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return dataIndexList?.firstOrNull()?.let {
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val i = if (it > 0) it - 1 else it
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historyDataList[i].toBaseRealTimeData(BaseRealTimeData::class.java)
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}
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}
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fun getFirstDataValue(): Float? {
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return getFirstData()?.getByFactorType(factorType)
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}
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/**
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* 获取异常数据的最后一个数据
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*/
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fun getLastData(): BaseRealTimeData? {
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return dataIndexList?.lastOrNull()?.let {
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historyDataList[it].toBaseRealTimeData(BaseRealTimeData::class.java)
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}
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}
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fun getLastDataValue(): Float? {
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return getLastData()?.getByFactorType(factorType)
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}
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}
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/**
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* 各监测因子异常统计信息
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*/
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inner class Statistic(){
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var factorId: Int? = null
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var factorName: String? = null
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var subFactorId: List<Int>? = null
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var subFactorName: List<String>? = null
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var selectedFactor: FactorFilter.SelectedFactor? = null
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/**
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* 异常数据对应历史数据[historyDataList]中的索引值
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*/
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var dataIndexList: List<Int>? = null
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// 因子量级平均变化幅度
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var avgPer: Double? = null
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// 因子量级平均变化速率
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var avgRate: Double? = null
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var avg: Double? = null
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var min: Double? = null
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var max: Double? = null
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var excGroup: List<ExcGroup>? = null
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/**
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* 获取异常数据
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*/
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fun getExceptionData(): List<BaseRealTimeData>? {
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return dataIndexList?.map { historyDataList[it].toBaseRealTimeData(BaseRealTimeData::class.java) }
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}
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/**
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* 获取异常数据分段情况
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* 将连续的异常数据分为一组
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*/
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fun getExceptionDataGroup(): List<List<Int>> {
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val res = mutableListOf<MutableList<Int>>()
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var curGroup = mutableListOf<Int>()
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var lastIndex = -2
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dataIndexList?.forEach {
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if (curGroup.isEmpty()) {
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curGroup.add(it)
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} else if (it - lastIndex == 1) {
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curGroup.add(it)
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} else {
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res.add(curGroup)
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curGroup = mutableListOf(it)
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}
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lastIndex = it
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}
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if (curGroup.isNotEmpty()) {
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res.add(curGroup)
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}
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return res
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}
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}
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constructor(exceptions: List<Pair<FactorFilter.SelectedFactor, ExceptionTag>>, eType: ExceptionType,) : this() {
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// 遍历所有的因子的异常，整合统一的异常结果，具体如下
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var startData: BaseRealTimeData? = null
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var endData: BaseRealTimeData? = null
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var historyData = mutableListOf<BaseRealTimeData>()
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var _times = 0
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exceptions.forEach { e ->
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// 将采样时间最早的数据作为开始数据
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if (startData == null) {
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startData = e.second.startData
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} else {
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if (e.second.startData?.dataTime!! < startData!!.dataTime) {
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startData = e.second.startData
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}
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}
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// 将采样时间最晚的作为结束数据
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if (endData == null) {
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endData = e.second.endData
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} else {
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if (e.second.endData?.dataTime!! > endData!!.dataTime) {
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endData = e.second.endData
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}
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}
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// 将所有历史数据去重合并
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if (historyData.isEmpty()) {
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historyData = e.second.historyData
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} else {
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e.second.historyData.forEach {
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if (historyData.find { d -> d.dataTime == it.dataTime } == null) {
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historyData.add(it)
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}
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}
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}
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_times += e.second.exceptionData.size
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}
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// 按照采样时间升序排列
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historyData.sortBy { it.dataTime }
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exception = eType.des
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exceptionType = eType.value
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startTime = startData?.dataTime
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endTime = endData?.dataTime
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windSpeed = historyData.avg().windSpeed?.toDouble()
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times = _times
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historyDataList.addAll(historyData.map { it.toDataVo() })
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// 再次整合异常数据，分别计算各因子的异常结果统计
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exceptions.forEach {e ->
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statisticMap[e.first.main] = Statistic().apply {
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factorId = e.first.main.value
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factorName = e.first.main.des
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subFactorId = e.first.subs.map { it.value }
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subFactorName = e.first.subs.map { it.des }
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selectedFactor = e.first
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dataIndexList = e.second.exceptionData.map {
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historyDataList.indexOfFirst { d ->
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d.time == DateUtil.instance.dateToString(it.dataTime, DateUtil.DateStyle.YYYY_MM_DD_HH_MM_SS)
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}
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}
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val s = dataSummary(e.second.exceptionData, e.first.main)
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avg = s.first
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min = s.second
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max = s.third
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excGroup = getExceptionDataGroup().map { ExcGroup(it, e.first.main) }
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avgPer = excGroup?.mapNotNull { it.per }?.average()
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avgRate = excGroup?.mapNotNull { it.rate }?.average()
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}
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}
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}
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var deviceCode: String? = null
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var exception: String? = null
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var exceptionType: Int? = null
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var startTime: Date? = null
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var endTime: Date? = null
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// 风速
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var windSpeed: Double? = null
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// 发生次数
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var times: Int? = null
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var historyDataList = mutableListOf<DataVo>()
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// 异常监测数据，包含单次异常中所有发生了异常的数据值（可能不是时间连续的数据）
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// var dataList: MutableList<BaseRealTimeData> = mutableListOf()
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// var dataVoList: MutableList<DataVo> = mutableListOf()
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var statisticMap = mutableMapOf<FactorType, Statistic>()
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/**
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* 获取所有异常因子名称
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*/
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fun toFactorNames(): String {
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val factors = statisticMap.entries.map { it.key }.sortedBy { it.value }.joinToString(";") { it.des }
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return factors
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}
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fun getExceptionAvgData(): BaseRealTimeData {
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val exceptionDataList = statisticMap.flatMap { it.value.getExceptionData() ?: emptyList() }
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val avgData = exceptionDataList.avg()
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return avgData
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}
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/**
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* 获取异常数据中心坐标（异常数据中经度纬度的平均值）
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*/
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fun getExceptionCenter(): Pair<Double, Double>? {
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val avgData = getExceptionAvgData()
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val wgs84Lng = avgData.longitude?.toDouble()
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val wgs84Lat = avgData.latitude?.toDouble()
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return if (wgs84Lng == null || wgs84Lat == null) null else Pair(wgs84Lng, wgs84Lat)
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}
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private fun calPer(exceptionData: List<BaseRealTimeData?>, factorType: FactorType): Double? {
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if (exceptionData.size < 2) return null
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var total = .0
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for (i in 0 until exceptionData.size - 1) {
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val p = exceptionData[i]?.getByFactorType(factorType) ?: .0f
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val n = exceptionData[i + 1]?.getByFactorType(factorType) ?: .0f
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total += (n - p) / p
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}
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return total / (exceptionData.size - 1)
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}
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private fun calRate(exceptionData: List<BaseRealTimeData?>, factorType: FactorType): Double? {
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if (exceptionData.size < 2) return null
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var total = .0
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for (i in 0 until exceptionData.size - 1) {
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val p = exceptionData[i]?.getByFactorType(factorType) ?: .0f
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val n = exceptionData[i + 1]?.getByFactorType(factorType) ?: .0f
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total += (n - p) / 4
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}
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return total / (exceptionData.size - 1)
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}
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private fun dataSummary(exceptionData: List<BaseRealTimeData?>, factorType: FactorType): Triple<Double, Double,
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Double> {
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var min = -1.0
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var max = -1.0
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var total = .0
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var count = 0
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exceptionData.forEach {
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val value = it?.getByFactorType(factorType)?.toDouble() ?: return@forEach
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if (min == -1.0 || min > value) {
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min = round(value * 1000) / 1000
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}
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if (max == -1.0 || max < value) {
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max = round(value * 1000) / 1000
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}
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total += value
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count++
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}
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val avg = if (count == 0) .0 else round(total / count * 1000) / 1000
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return Triple(avg, min, max)
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}
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}
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