1. 添加网格化数据分钟均值计算逻辑

feiyu02

2021-11-10 db7243622e8b5f4cc23de5594b2d973562f0b2a3

 src/main/kotlin/com/flightfeather/uav/domain/entity/BaseRealTimeData.kt

@@ -1,13 +1,19 @@
package com.flightfeather.uav.domain.entity

import com.flightfeather.uav.common.utils.DateUtil
import com.flightfeather.uav.dataprocess.AvgPair
import com.flightfeather.uav.lightshare.bean.DataVo
import com.flightfeather.uav.socket.bean.AirData
import com.flightfeather.uav.socket.eunm.FactorType
import java.math.BigDecimal
import java.time.LocalDateTime
import java.time.ZoneId
import java.time.ZoneOffset
import java.util.*
import javax.persistence.Column
import javax.persistence.Id
import kotlin.math.cos
import kotlin.math.sin

/**
 * 实时监测数据基类
@@ -103,4 +109,153 @@
            add(AirData().apply { setData(FactorType.HEIGHT, height) })
        }
    }
}

fun List<RealTimeDataGrid>.avg(): RealTimeDataGrid {
    //风向采用单位矢量法求取均值
    var u = 0f//东西方位分量总和
    var v = 0f//南北方位分量总和
    var c = 0//风向数据计数

    //除风向外的其他因子采用算术平均法求取均值
    val tmpList = mutableListOf<AvgPair>()
    repeat(17) {
        tmpList.add(AvgPair(0f, 0))
    }

    forEach {
        //风向
        it.windDirection?.let {w ->
            u += sin(w)
            v += cos(w)
            c++
        }
        //其余因子
        tmpList[0].apply {
            it.latitude?.let {
                t += it.toFloat()
                this.c++
            }
        }
        tmpList[1].apply {
            it.longitude?.let {
                t += it.toFloat()
                this.c++
            }
        }
        tmpList[2].apply {
            it.altitude?.let {
                t += it
                this.c++
            }
        }
        tmpList[3].apply {
            it.no2?.let {
                t += it
                this.c++
            }
        }
        tmpList[4].apply {
            it.co?.let {
                t += it
                this.c++
            }
        }
        tmpList[5].apply {
            it.h2s?.let {
                t += it
                this.c++
            }
        }
        tmpList[6].apply {
            it.so2?.let {
                t += it
                this.c++
            }
        }
        tmpList[7].apply {
            it.o3?.let {
                t += it
                this.c++
            }
        }
        tmpList[8].apply {
            it.pm25?.let {
                t += it
                this.c++
            }
        }
        tmpList[9].apply {
            it.pm10?.let {
                t += it
                this.c++
            }
        }
        tmpList[10].apply {
            it.temperature?.let {
                t += it
                this.c++
            }
        }
        tmpList[11].apply {
            it.humidity?.let {
                t += it
                this.c++
            }
        }
        tmpList[12].apply {
            it.voc?.let {
                t += it
                this.c++
            }
        }
        tmpList[13].apply {
            it.noi?.let {
                t += it
                this.c++
            }
        }
        tmpList[14].apply {
            it.velocity?.let {
                t += it
                this.c++
            }
        }
        tmpList[15].apply {
            it.windSpeed?.let {
                t += it
                this.c++
            }
        }
        tmpList[16].apply {
            it.height?.let {
                t += it
                this.c++
            }
        }
    }

    return RealTimeDataGrid().apply {
        val time = LocalDateTime.ofInstant(get(0).dataTime?.toInstant(), ZoneId.systemDefault()).withSecond(0)
        deviceCode = get(0).deviceCode
        dataTime = Date.from(time.atZone(ZoneId.systemDefault()).toInstant())
        createTime = dataTime
        latitude = tmpList[0].avg().toBigDecimal()
        longitude = tmpList[1].avg().toBigDecimal()
        altitude = tmpList[2].avg()
        no2 = tmpList[3].avg()
        co = tmpList[4].avg()
        h2s = tmpList[5].avg()
        so2 = tmpList[6].avg()
        o3 = tmpList[7].avg()
        pm25 = tmpList[8].avg()
        pm10 = tmpList[9].avg()
        temperature = tmpList[10].avg()
        humidity = tmpList[11].avg()
        voc = tmpList[12].avg()
        noi = tmpList[13].avg()
        velocity = tmpList[14].avg()
        windSpeed = tmpList[15].avg()
        height = tmpList[16].avg()
    }
}