package com.flightfeather.uav.model
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import com.flightfeather.uav.common.utils.DateUtil
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import com.flightfeather.uav.common.utils.ExcelUtil
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import com.flightfeather.uav.socket.eunm.FactorType
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import org.apache.poi.xssf.streaming.SXSSFWorkbook
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import java.io.File
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import java.io.FileOutputStream
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import java.util.*
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import kotlin.math.round
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/**
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* 污染源影响程度权重分析模型
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* 基类
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*/
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abstract class BaseModel<M : BaseMData, S: BaseSOP> {
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data class ResultCell(
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var total: Double = 0.0,
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var count: Int = 0,
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var average: Double = 0.0
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) {
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fun average(): Double {
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average = if (count == 0) .0 else round(total / count * 100) / 100
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return average
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}
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}
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abstract var dataPrep: BaseDataPrep<M, S>
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// 权重因子，在进行计算分析时使用的监测因子
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abstract var factorTypes: List<FactorType>
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// 权重值，多种权重进行乘积计算
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abstract var weights: List<BaseWeight<M, S>>
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// 计算结果
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private val rMap = mutableMapOf<String, MutableMap<String, MutableMap<String, ResultCell>>>()
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// 结果筛选方式
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abstract var sections: List<BaseSection<M, S>>
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/**
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* 污染源影响程度计算
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* @param mDataList 监测数据集合
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* @param sopList 污染源集合
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*/
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open fun execute(mDataList: List<M>, sopList: List<S>, hasNext: Boolean = false) {
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if (!hasNext) rMap.clear()
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//1. 数据预处理
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val mList = dataPrep.mDataPrep(mDataList)
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val sList = dataPrep.sopPrep(sopList)
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mList.forEach m@{ m ->
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if (!mDataCheck(m)) return@m
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sList.forEach s@{ s ->
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if (!sopCheck(s)) return@s
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weightCompute(m, s)
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}
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}
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}
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/**
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* 单点权重计算
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* 计算污染源对单次监测数据产生的影响效果
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* @param mData 监测数据
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* @param sop 污染源
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*/
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private fun weightCompute(mData: M, sop: S) {
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val effect = BaseEffect(sop.sourceId, sop.sourceName, sop.index)
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// 将原监测数据按照权重计算出结果值
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factorTypes.forEach { type ->
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var result = mData.getFactorData(type) ?: return@forEach
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weights.forEach {
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result *= it.getWeight(mData, sop)?: return
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}
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effect.value.add(Pair(type, result))
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}
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// 向结果值添加筛选标签
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sections.forEach { it.filter(mData, sop, effect) }
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// 保存结果
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formatConversion2(effect)
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}
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fun outputToExcel(
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fName: String? = null,
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_workbook: SXSSFWorkbook? = null,
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_out: FileOutputStream? = null,
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sheetName: String = "sheet1",
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done: Boolean = true
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): Pair<SXSSFWorkbook, FileOutputStream>? {
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// val rMap = formatConversion()
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val workbook = _workbook ?: SXSSFWorkbook()
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val fileName = fName ?: "污染溯源权重模型${DateUtil.instance.dateToString(Date(), "yyyy-MM-ddHHmmss")}.xls"
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// val filePath = "E:\\work\\export\\$fileName"
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// val filePath = "E:\\工作\\开发\\走航监测\\算法相关\\自动输出\\$fileName"
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val filePath = "E:\\工作\\开发\\走航监测\\算法相关\\自动输出\\网格化\\$fileName"
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val out = _out ?: FileOutputStream(File(filePath))
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// 表头组（多行表头）
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val heads = mutableListOf<Array<String>>()
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// 表头行
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val h1 = mutableListOf<String>()
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h1.add("编号")
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h1.add("污染源")
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// arrayOf("早上", "上午", "中午", "下午", "傍晚", "夜间")
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val contents = mutableListOf<Array<Any>>()
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var isFirst = true
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rMap.forEach { (source, tMap) ->
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// 新建一行
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val contentList = mutableListOf<Any>()
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// 添加污染源名称
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val l = source.split(";")
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contentList.add(l[1].toIntOrNull() ?: 0)
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contentList.add(l[0])
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tMap.forEach { (factorType, lMap) ->
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sections.forEach {
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val types = mutableListOf<String>().apply {
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addAll(it.sectionType)
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addAll(it.constType)
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}
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var max = 0.0
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var maxP = types[0]
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types.forEach type@{se ->
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val lKey = "$se($factorType)"
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if (lMap.containsKey(lKey)) {
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val resultCell = lMap[lKey] ?: return@type
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// val size = resultCell.count
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// 添加该分类作为表头
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val h = lKey
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// val h = "$lKey($size)"
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if (!h1.contains(h)) {
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h1.add(h)
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}
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// 将原始的数据换算得出结果，可以是求出均值、总和等等
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// FIXME: 2021/6/23 此处先默认为求均值
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val average = resultCell.average()
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if (average > max) {
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max = average
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maxP = se
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}
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// 当前行添加该分类下的结果值
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contentList.add(average)
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}
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}
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if (isFirst) {
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h1.add("最高时段")
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h1.add("最高时段值")
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}
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contentList.add(maxP)
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contentList.add(max)
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}
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}
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isFirst = false
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contents.add(contentList.toTypedArray())
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}
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contents.sortByDescending {
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val i = it[0]
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if (i is Int) {
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i
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} else {
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0
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}
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}
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heads.add(h1.toTypedArray())
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ExcelUtil.write(heads, contents, workbook, sheetName)
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return if (!done) {
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Pair(workbook, out)
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} else {
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workbook.write(out)
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workbook.close()
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out.flush()
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out.close()
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null
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}
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}
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fun outputResult(): MutableMap<String, MutableMap<String, MutableMap<String, ResultCell>>> {
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rMap.forEach { (_, v) ->
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v.forEach { (_, v2) ->
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v2.forEach { (_, v3) ->
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v3.average()
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}
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}
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}
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return rMap
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}
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/**
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* 将计算结果格式化为多层级的键对值结构
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* 第一层按照不同污染源的索引值进行分类
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* 第二层按照监测因子类型进行分类
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* 第三层按照自定义的标签进行分类
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*/
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private fun formatConversion2(e: BaseEffect) {
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val rKey = "${e.sourceName};${e.index}"
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if (!rMap.containsKey(rKey)) {
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rMap[rKey] = mutableMapOf()
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}
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val lMap = rMap[rKey]!!
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e.value.forEach { v ->
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if (!lMap.containsKey(v.first.des)) {
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lMap[v.first.des] = mutableMapOf()
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}
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val tMap = lMap[v.first.des]!!
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e.tag.forEach { t ->
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val factorName = v.first.des
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val lKey = t.levelName + "($factorName)"
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if (!tMap.containsKey(lKey)) {
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tMap[lKey] = ResultCell()
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}
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tMap[lKey]?.run {
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total += v.second
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if (factorName != FactorType.H2S.name || v.second > 0) {
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count++
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}
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}
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}
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}
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}
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/**
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* 监测数据合法性检查
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*/
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abstract fun mDataCheck(m: M): Boolean
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/**
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* 污染源数据合法性检查
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*/
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abstract fun sopCheck(s: S): Boolean
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}
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