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| | | package com.flightfeather.uav.biz.sourcetrace.model |
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| | | |
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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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| | | /** |
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| | | * 污染数据 |
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| | | * @author feiyu02 |
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| | | */ |
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| | | class PollutedData() { |
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| | | |
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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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| | | /** |
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| | | * 9. 关联因子 |
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| | | * a) pm2.5、pm10特别高，两者在各情况下同步展示，pm2.5占pm10的比重变化，比重越高，越有可能是餐饮 |
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| | | * b) pm10特别高、pm2.5较高，大颗粒扬尘污染，只展示pm10，pm2.5占pm10的比重变化，工地为主 |
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| | | * c) VOC较高，同比计算pm2.5的量级，可能存在同步偏高（汽修、加油站）, 同步计算O3是否有高值 |
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| | | * d) VOC较高，处于加油站（车辆拥堵情况），CO一般较高, 同步计算O3是否有高值 |
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| | | * e) 氮氧化合物，一般由于机动车尾气，同步计算CO |
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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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| | | constructor( |
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| | | start: BaseRealTimeData, |
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| | | end: BaseRealTimeData?, |
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| | | factor: FactorFilter.SelectedFactor, |
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| | | exceptionData: List<BaseRealTimeData>, |
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| | | eType: ExceptionType, |
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| | | windLevelCondition: RTExcWindLevelConfig.WindLevelCondition, |
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| | | ) : this() { |
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| | | exception = eType.des |
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| | | exceptionType = eType.value |
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| | | factorId = factor.main.value |
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| | | factorName = factor.main.des |
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| | | subFactorId = factor.subs.map { it.value } |
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| | | subFactorName = factor.subs.map { it.des } |
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| | | selectedFactor = factor |
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| | | |
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| | | startTime = DateUtil.instance.dateToString(start.dataTime, DateUtil.DateStyle.HH_MM_SS) |
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| | | endTime = DateUtil.instance.dateToString(end?.dataTime, DateUtil.DateStyle.HH_MM_SS) ?: startTime |
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| | | startData = start.getByFactorType(factor.main) |
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| | | endData = end?.getByFactorType(factor.main) ?: startData |
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| | | |
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| | | windSpeed = exceptionData.first().windSpeed?.toDouble() |
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| | | percentage = windLevelCondition.mutationRate.first |
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| | | times = windLevelCondition.countLimit |
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| | | |
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| | | exceptionData.forEach { |
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| | | dataList.add(it) |
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| | | dataVoList.add(it.toDataVo()) |
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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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| | | calPer() |
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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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| | | |
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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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| | | /** |
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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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| | | |
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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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| | | |
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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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| | | |
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| | | var excGroup: List<ExcGroup>? = null |
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| | | |
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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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| | | /** |
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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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| | | |
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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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| | | |
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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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| | | |
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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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| | | |
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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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| | | |
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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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| | | |
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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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| | | |
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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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| | | |
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| | | var deviceCode: String? = null |
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| | | |
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| | | var exception: String? = null |
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| | | var exceptionType: Int? = null |
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| | | |
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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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| | | var startTime: String? = null |
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| | | var endTime: String? = null |
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| | | |
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| | | var startData: Float? = null |
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| | | var endData: Float? = null |
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| | | |
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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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| | | |
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| | | // 因子量级变化幅度 |
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| | | var percentage: Double? = 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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| | | |
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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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| | | // 异常监测数据 |
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| | | var dataList: MutableList<BaseRealTimeData> = mutableListOf() |
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| | | var dataVoList: MutableList<DataVo> = mutableListOf() |
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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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| | | |
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| | | private fun calPer() { |
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| | | if (dataList.size < 2) return |
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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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| | | |
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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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| | | |
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| | | var total = .0 |
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| | | for (i in 0 until dataList.size - 1) { |
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| | | total += dataList[i].getByFactorType(selectedFactor!!.main)!! |
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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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| | | avgPer = total / (dataList.size - 1) |
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| | | return total / (exceptionData.size - 1) |
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| | | } |
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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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| | | |
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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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| | | |
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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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