1. 新增卫星遥测网格热力图计算逻辑

feiyu02

2025-03-27 bde043c8fd1a076f44c402dd56c62d401afbfb16

 src/main/kotlin/com/flightfeather/uav/biz/satellite/SatelliteGridManage.kt

@@ -2,6 +2,11 @@

import com.flightfeather.uav.common.utils.MapUtil
import com.flightfeather.uav.domain.entity.*
import com.flightfeather.uav.model.underwaygrid.GridCellAndData
import com.flightfeather.uav.model.underwaygrid.GridCellSop
import com.flightfeather.uav.model.underwaygrid.UnderwayGridModel
import com.flightfeather.uav.socket.eunm.FactorType
import org.springframework.beans.BeanUtils
import kotlin.math.PI
import kotlin.math.sqrt

@@ -237,12 +242,13 @@
        realTimeDataList.forEach {
            if (it.longitude == null || it.latitude == null) return@forEach

            searchGirdIn(it.longitude!!.toDouble() to it.latitude!!.toDouble(), gridCellList)?.let { cell ->
                if (!dataMap.containsKey(cell)) {
                    dataMap[cell] = mutableListOf()
            SatelliteGridUtil.searchGirdIn(it.longitude!!.toDouble() to it.latitude!!.toDouble(), gridCellList)
                ?.let { cell ->
                    if (!dataMap.containsKey(cell)) {
                        dataMap[cell] = mutableListOf()
                    }
                    dataMap[cell]?.add(it)
                }
                dataMap[cell]?.add(it)
            }
        }

        // 统计每个网格中的均值
@@ -250,11 +256,12 @@
        val gridDataDetailList = mutableListOf<GridDataDetail>()
        dataMap.forEach { (k, v) ->
            val avgData = v.avg()
            val dataDetail = GridDataDetail().apply {
            val dataDetail = GridDataDetail()
            BeanUtils.copyProperties(avgData, dataDetail)
            dataDetail.apply {
                dataId = gridData?.id
                groupId = k.groupId
                cellId = k.cellIndex
                pm25 = avgData.pm25
                rank
            }
            gridDataDetailList.add(dataDetail)
@@ -270,26 +277,57 @@
    }

    /**
     * 计算坐标点在哪个卫星网格内
     * @date 2025.2.14
     * @param point 坐标点
     * @param gridCellList 卫星网格
     * 计算热力图网格，即网格周边扩散影响权重计算
     * @param gridDataDetail 网格监测数据
     * @param gridCellList 区域网格数组
     * @param option 区域网格参数信息
     * @param searchLength 计算周边八方向（上下左右及四个对角）网格的长度
     * @return 周边网格及对应的监测数据结果
     */
    fun searchGirdIn(point: Pair<Double, Double>, gridCellList: List<GridCell?>): GridCell? {
        for (i in gridCellList.indices) {
            val gridCell = gridCellList[i] ?: continue
            val polygon = listOf(
                gridCell.point1Lon.toDouble() to gridCell.point1Lat.toDouble(),
                gridCell.point2Lon.toDouble() to gridCell.point2Lat.toDouble(),
                gridCell.point3Lon.toDouble() to gridCell.point3Lat.toDouble(),
                gridCell.point4Lon.toDouble() to gridCell.point4Lat.toDouble(),
            )
            if (MapUtil.isPointInPolygon(point, polygon)) {
                return gridCell
    fun heatMap(
        gridDataDetail: GridDataDetail, gridCellList: List<GridCell?>,
        option: GridGroupOption, searchLength: Int,
    ): List<GridDataDetail> {
        // 找到网格数据对应的网格信息
        val gridCell = gridCellList.find { it?.cellIndex == gridDataDetail.cellId }
            ?: throw IllegalArgumentException("网格数据和给定的区域网格不匹配")

        // 获取周边网格
        val surroundGridCellList =
            SatelliteGridUtil.searchDiffuseGrid(gridDataDetail.cellId, gridCellList, option, searchLength)

        // 使用走航网格权重模型，计算周边网格的监测数据值
        val underwayGridModel = UnderwayGridModel()
        val dataList = listOf(GridCellAndData(gridCell, gridDataDetail))
        val gridCellSopList = surroundGridCellList.map {
            GridCellSop(
                it,
                it.id.toString(),
                it.cellIndex.toString(),
                it.cellIndex.toString()
            ) }
        underwayGridModel.execute(dataList, gridCellSopList)
        val resMap = underwayGridModel.outputResult()

        // 格式化结果并返回
        val result = mutableListOf<GridDataDetail>()
        gridCellSopList.forEach {
            val resGridDataDetail = GridDataDetail().apply {
                dataId = gridDataDetail.dataId
                groupId = gridDataDetail.groupId
                cellId = it.gridCell.cellIndex
            }

            val key = "${it.sourceName};${it.index}"
            val d = resMap[key]
            d?.forEach { (t, u) ->
                val avg = u["综合(${t})"]?.average ?: .0
                resGridDataDetail.setFactorValue(FactorType.getByName(t), avg.toFloat())
            }
            result.add(resGridDataDetail)
        }

        return null
        return result
    }

}