From e923f06d572c9a0e3b1eb2c54471af02c9d95bcf Mon Sep 17 00:00:00 2001
From: feiyu02 <risaku@163.com>
Date: 星期四, 18 十二月 2025 10:05:05 +0800
Subject: [PATCH] Merge remote-tracking branch 'origin/master'

---
 src/main/kotlin/com/flightfeather/uav/biz/sourcetrace/model/PollutedData.kt |  148 ++++++++++++++++++++++++++++++-------------------
 1 files changed, 90 insertions(+), 58 deletions(-)

diff --git a/src/main/kotlin/com/flightfeather/uav/biz/sourcetrace/model/PollutedData.kt b/src/main/kotlin/com/flightfeather/uav/biz/sourcetrace/model/PollutedData.kt
index 5661859..577b38b 100644
--- a/src/main/kotlin/com/flightfeather/uav/biz/sourcetrace/model/PollutedData.kt
+++ b/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
 
 /**
  * 姹℃煋鏁版嵁
@@ -14,19 +17,27 @@
  */
 class PollutedData() {
 
-    /**
-     * 9. 鍏宠仈鍥犲瓙
-     * 	a) pm2.5銆乸m10鐗瑰埆楂橈紝涓よ�呭湪鍚勬儏鍐典笅鍚屾灞曠ず锛宲m2.5鍗爌m10鐨勬瘮閲嶅彉鍖栵紝姣旈噸瓒婇珮锛岃秺鏈夊彲鑳芥槸椁愰ギ
-     * 	b) pm10鐗瑰埆楂樸�乸m2.5杈冮珮锛屽ぇ棰楃矑鎵皹姹℃煋锛屽彧灞曠ずpm10锛宲m2.5鍗爌m10鐨勬瘮閲嶅彉鍖栵紝宸ュ湴涓轰富
-     * 	c) VOC杈冮珮锛屽悓姣旇绠梡m2.5鐨勯噺绾э紝鍙兘瀛樺湪鍚屾鍋忛珮锛堟苯淇�佸姞娌圭珯锛�, 鍚屾璁$畻O3鏄惁鏈夐珮鍊�
-     * 	d) VOC杈冮珮锛屽浜庡姞娌圭珯锛堣溅杈嗘嫢鍫垫儏鍐碉級锛孋O涓�鑸緝楂�, 鍚屾璁$畻O3鏄惁鏈夐珮鍊�
-     * 	e) 姘哀鍖栧悎鐗╋紝涓�鑸敱浜庢満鍔ㄨ溅灏炬皵锛屽悓姝ヨ绠桟O
-     */
+    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
+
+        // 鍥犲瓙閲忕骇骞冲潎鍙樺寲骞呭害
+        var avgPer: Double? = null
+        // 鍥犲瓙閲忕骇骞冲潎鍙樺寲閫熺巼
+        var avgRate: Double? = null
+
+        var avg: Double? = null
+        var min: Double? = null
+        var max: Double? = null
+    }
 
     constructor(
         start: BaseRealTimeData,
         end: BaseRealTimeData?,
-        factor: FactorFilter.SelectedFactor,
+        factorList: List<FactorFilter.SelectedFactor>,
         exceptionData: List<BaseRealTimeData>,
         historyData: List<BaseRealTimeData>,
         eType: ExceptionType,
@@ -34,21 +45,15 @@
     ) : 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
+        startTime = start.dataTime
+        endTime = end?.dataTime
 //        startData = start.getByFactorType(factor.main)
 //        endData = end?.getByFactorType(factor.main) ?: startData
-        startData = start
-        endData = end
+//        startData = start
+//        endData = end
 
         windSpeed = exceptionData.first().windSpeed?.toDouble()
-        percentage = windLevelCondition?.mutationRate?.first
         times = windLevelCondition?.countLimit
 
         dataList.add(start)
@@ -58,8 +63,24 @@
         dataVoList.addAll(dataList.map { it.toDataVo() })
         historyDataList.addAll(historyData.map { it.toDataVo() })
 
-        calPer()
-        calRate()
+
+        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(dataList, f.main)
+                avg = s.first
+                min = s.second
+                max = s.third
+            }
+        }
     }
 
     var deviceCode: String? = null
@@ -67,63 +88,74 @@
     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: BaseRealTimeData? = null
-    var endData: BaseRealTimeData? = null
+//    var startData: BaseRealTimeData? = null
+//    var endData: BaseRealTimeData? = null
 
     // 椋庨��
     var windSpeed: Double? = null
-
-    // 鍥犲瓙閲忕骇鍙樺寲骞呭害
-    var percentage: Double? = null
-    // 鍥犲瓙閲忕骇骞冲潎鍙樺寲骞呭害
-    var avgPer: Double? = null
-    // 鍥犲瓙閲忕骇骞冲潎鍙樺寲閫熺巼
-    var avgRate: Double? = null
 
     // 鍙戠敓娆℃暟
     var times: Int? = null
 
     var historyDataList = mutableListOf<DataVo>()
-    // 寮傚父鐩戞祴鏁版嵁
+    // 寮傚父鐩戞祴鏁版嵁锛屽寘鍚崟娆″紓甯镐腑鎵�鏈夊彂鐢熶簡寮傚父鐨勬暟鎹�硷紙鍙兘涓嶆槸鏃堕棿杩炵画鐨勬暟鎹級
     var dataList: MutableList<BaseRealTimeData> = mutableListOf()
     var dataVoList: MutableList<DataVo> = mutableListOf()
 
-    private fun calPer() {
-        val list = dataList
-//        list.add(startData)
-//        list.addAll(dataList)
-        if (list.size < 2) return
+    var statisticMap = mutableMapOf<FactorType, Statistic>()
 
-        var total = .0
-        for (i in 0 until list.size - 1) {
-            val p = list[i]?.getByFactorType(selectedFactor!!.main)!!
-            val n = list[i + 1]?.getByFactorType(selectedFactor!!.main)!!
-            total += (n - p) / p
-        }
-        avgPer = total / (list.size - 1)
+    fun toFactorNames(): String {
+        val factors = statisticMap.entries.map { it.key }.sortedBy { it.value }.joinToString(";") { it.des }
+        return factors
     }
 
-    private fun calRate() {
+    private fun calPer(factorType: FactorType): Double? {
         val list = dataList
-//        list.add(startData)
-//        list.addAll(dataList)
-        if (list.size < 2) return
+        if (list.size < 2) return null
 
         var total = .0
         for (i in 0 until list.size - 1) {
-            val p = list[i]?.getByFactorType(selectedFactor!!.main)!!
-            val n = list[i + 1]?.getByFactorType(selectedFactor!!.main)!!
+            val p = list[i].getByFactorType(factorType) ?: .0f
+            val n = list[i + 1].getByFactorType(factorType) ?: .0f
+            total += (n - p) / p
+        }
+        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
         }
-        avgRate = total / (list.size - 1)
+        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)
     }
 }
\ No newline at end of file

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