2025.8.5 1. 动态溯源模块添加延迟数据周期异常合并功能

feiyu02

2025-08-05 176d7d8283e66ccf63878c9ab823e900df94b748

 src/main/kotlin/com/flightfeather/uav/biz/sourcetrace/model/PollutedData.kt

@@ -6,6 +6,9 @@
import com.flightfeather.uav.common.utils.DateUtil
import com.flightfeather.uav.domain.entity.BaseRealTimeData
import com.flightfeather.uav.lightshare.bean.DataVo
import com.flightfeather.uav.socket.eunm.FactorType
import java.util.Date
import kotlin.math.round

/**
 * 污染数据
@@ -13,6 +16,23 @@
 * @author feiyu02
 */
class PollutedData() {

    inner class Statistic(){
        var factorId: Int? = null
        var factorName: String? = null
        var subFactorId: List<Int>? = null
        var subFactorName: List<String>? = null
        var selectedFactor: FactorFilter.SelectedFactor? = null

        // 因子量级平均变化幅度
        var avgPer: Double? = null
        // 因子量级平均变化速率
        var avgRate: Double? = null

        var avg: Double? = null
        var min: Double? = null
        var max: Double? = null
    }

    /**
     * 9. 关联因子
@@ -26,34 +46,50 @@
    constructor(
        start: BaseRealTimeData,
        end: BaseRealTimeData?,
        factor: FactorFilter.SelectedFactor,
        factorList: List<FactorFilter.SelectedFactor>,
        exceptionData: List<BaseRealTimeData>,
        historyData: List<BaseRealTimeData>,
        eType: ExceptionType,
        windLevelCondition: RTExcWindLevelConfig.WindLevelCondition,
        windLevelCondition: RTExcWindLevelConfig.WindLevelCondition?,
    ) : this() {
        exception = eType.des
        exceptionType = eType.value
        factorId = factor.main.value
        factorName = factor.main.des
        subFactorId = factor.subs.map { it.value }
        subFactorName = factor.subs.map { it.des }
        selectedFactor = factor

        startTime = DateUtil.instance.dateToString(start.dataTime, DateUtil.DateStyle.HH_MM_SS)
        endTime = DateUtil.instance.dateToString(end?.dataTime, DateUtil.DateStyle.HH_MM_SS) ?: startTime
        startData = start.getByFactorType(factor.main)
        endData = end?.getByFactorType(factor.main) ?: startData
        startTime = start.dataTime
        endTime = end?.dataTime
//        startData = start.getByFactorType(factor.main)
//        endData = end?.getByFactorType(factor.main) ?: startData
        startData = start
        endData = end

        windSpeed = exceptionData.first().windSpeed?.toDouble()
        percentage = windLevelCondition.mutationRate.first
        times = windLevelCondition.countLimit
        times = windLevelCondition?.countLimit

        dataList.add(start)
        exceptionData.forEach {
            dataList.add(it)
            dataVoList.add(it.toDataVo())
        }
        dataVoList.addAll(dataList.map { it.toDataVo() })
        historyDataList.addAll(historyData.map { it.toDataVo() })

        calPer()

        factorList.forEach { f->
            statisticMap[f.main] = Statistic().apply {
                factorId = f.main.value
                factorName = f.main.des
                subFactorId = f.subs.map { it.value }
                subFactorName = f.subs.map { it.des }
                selectedFactor = f

                avgPer = calPer(f.main)
                avgRate = calRate(f.main)

                val s = dataSummary(exceptionData, f.main)
                avg = s.first
                min = s.second
                max = s.third
            }
        }
    }

    var deviceCode: String? = null
@@ -61,40 +97,74 @@
    var exception: String? = null
    var exceptionType: Int? = null

    var factorId: Int? = null
    var factorName: String? = null
    var subFactorId: List<Int>? = null
    var subFactorName: List<String>? = null
    var selectedFactor: FactorFilter.SelectedFactor? = null
    var startTime: Date? = null
    var endTime: Date? = null

    var startTime: String? = null
    var endTime: String? = null

    var startData: Float? = null
    var endData: Float? = null
    var startData: BaseRealTimeData? = null
    var endData: BaseRealTimeData? = null

    // 风速
    var windSpeed: Double? = null

    // 因子量级变化幅度
    var percentage: Double? = null
    // 因子量级平均变化幅度
    var avgPer: Double? = null

    // 发生次数
    var times: Int? = null

    var historyDataList = mutableListOf<DataVo>()
    // 异常监测数据
    var dataList: MutableList<BaseRealTimeData> = mutableListOf()
    var dataVoList: MutableList<DataVo> = mutableListOf()

    private fun calPer() {
        if (dataList.size < 2) return
    var statisticMap = mutableMapOf<FactorType, Statistic>()

    fun toFactorNames(): String {
        val factors = statisticMap.entries.map { it.key }.sortedBy { it.value }.joinToString(";") { it.des }
        return factors
    }

    private fun calPer(factorType: FactorType): Double? {
        val list = dataList
        if (list.size < 2) return null

        var total = .0
        for (i in 0 until dataList.size - 1) {
            total += dataList[i].getByFactorType(selectedFactor!!.main)!!
        for (i in 0 until list.size - 1) {
            val p = list[i].getByFactorType(factorType) ?: .0f
            val n = list[i + 1].getByFactorType(factorType) ?: .0f
            total += (n - p) / p
        }
        avgPer = total / (dataList.size - 1)
        return total / (list.size - 1)
    }

    private fun calRate(factorType: FactorType): Double? {
        val list = dataList
        if (list.size < 2) return null

        var total = .0
        for (i in 0 until list.size - 1) {
            val p = list[i].getByFactorType(factorType) ?: .0f
            val n = list[i + 1].getByFactorType(factorType) ?: .0f
            total += (n - p) / 4
        }
        return total / (list.size - 1)
    }

    private fun dataSummary(exceptionData: List<BaseRealTimeData?>, factorType: FactorType): Triple<Double, Double,
            Double> {
        var min = -1.0
        var max = -1.0
        var total = .0
        var count = 0
        exceptionData.forEach {
            val value = it?.getByFactorType(factorType)?.toDouble() ?: return@forEach
            if (min == -1.0 || min > value) {
                min = round(value * 1000) / 1000
            }
            if (max == -1.0 || max < value) {
                max = round(value * 1000) / 1000
            }
            total += value
            count++
        }
        val avg = if (count == 0) .0 else round(total / count * 1000) / 1000
        return Triple(avg, min, max)
    }
}