ref: v3变更,，备份缺少csv，菜单同级检查名称，ims忙时周统计

src/modules/ne_data/service/kpi_report.go

@@ -349,3 +349,153 @@ func (r KpiReport) IMSBusyHour(coreUid string, neUid string, timestamp int64) []
 	}
 	return data
 }
+
+// 定义结构体用于存储话务量值和对应的时间
+type TrafficData struct {
+	Time  int64   `json:"time"`  // 时间戳（毫秒）
+	Value float64 `json:"value"` // 话务量值
+}
+
+// IMSBusyWeek IMS忙时流量统计 周
+func (r KpiReport) IMSBusyWeek(coreUid string, neUid string, weekStart, weekEnd int64) map[string]any {
+	weekStartTime := time.UnixMilli(weekStart)
+	weekEndTime := time.UnixMilli(weekEnd)
+
+	// 1. 获取一周内每小时的呼叫数据
+	// 转换为毫秒级时间戳
+	rows := r.kpiReportRepository.SelectIMS(coreUid, neUid, weekStartTime.UnixMilli(), weekEndTime.UnixMilli())
+
+	// 创建一个map来存储按时间段合并后的数据
+	timeGroup := make(map[int64]map[string]int64)
+	// 遍历每个数据项
+	for _, row := range rows {
+		// 将毫秒时间戳转换为小时级时间戳（保留到小时的起始毫秒）
+		timeHour := row.CreatedAt / 3600000 * 3600000 // 1小时 = 3600000毫秒
+
+		// 解析 JSON 字符串为 map
+		var kpiValues []map[string]any
+		err := json.Unmarshal([]byte(row.KpiValues), &kpiValues)
+		if err != nil {
+			continue
+		}
+
+		var callAttempts, callCompletions int64
+		for _, v := range kpiValues {
+			if k, ok := v["kpiId"]; ok {
+				if k == "SCSCF.06" {
+					callAttempts = parse.Number(v["value"])
+				}
+				if k == "SCSCF.09" {
+					callCompletions = parse.Number(v["value"])
+				}
+			}
+		}
+		// 合并到对应的小时段
+		if _, exists := timeGroup[timeHour]; !exists {
+			timeGroup[timeHour] = map[string]int64{
+				"callAttempts":    0,
+				"callCompletions": 0,
+			}
+		}
+		timeGroup[timeHour]["callAttempts"] += callAttempts
+		timeGroup[timeHour]["callCompletions"] += callCompletions
+	}
+
+	// 时间组合输出
+	data := make([]map[string]any, 0, len(timeGroup))
+	for hour, sums := range timeGroup {
+		data = append(data, map[string]any{
+			"timeGroup":       fmt.Sprintf("%d", hour),
+			"callAttempts":    sums["callAttempts"],
+			"callCompletions": sums["callCompletions"],
+		})
+	}
+
+	if len(data) == 0 {
+		return map[string]any{
+			"busyHourAverageBHCA": 0,
+			"busyHourAverageBHCC": 0,
+			"topFourHoursBHCA":    []float64{},
+			"topFourHoursBHCC":    []float64{},
+			"totalHours":          0,
+		}
+	}
+
+	// 2. 分离BHCA和BHCC数据，并按降序排序
+	var bhcaData []TrafficData
+	var bhccData []TrafficData
+
+	for _, row := range data {
+		// 获取时间戳
+		timeValue := int64(0)
+		if t, ok := row["timeGroup"]; ok {
+			timeValue = parse.Number(t)
+		}
+
+		// 处理BHCA数据
+		if value, ok := row["callAttempts"]; ok {
+			bhcaVal := parse.Number(value)
+			bhcaData = append(bhcaData, TrafficData{
+				Time:  timeValue,
+				Value: float64(bhcaVal),
+			})
+		}
+
+		// 处理BHCC数据
+		if value, ok := row["callCompletions"]; ok {
+			bhccVal := parse.Number(value)
+			bhccData = append(bhccData, TrafficData{
+				Time:  timeValue,
+				Value: float64(bhccVal),
+			})
+		}
+	}
+	// 按降序排序（值大的在前）
+	sort.Slice(bhcaData, func(i, j int) bool { return bhcaData[i].Value > bhcaData[j].Value })
+	sort.Slice(bhccData, func(i, j int) bool { return bhccData[i].Value > bhccData[j].Value })
+
+	// 3. 取前四个最高值并计算平均值
+	topFourBHCA := getTopFourTrafficData(bhcaData)
+	topFourBHCC := getTopFourTrafficData(bhccData)
+
+	avgBHCA := calculateTrafficDataAverage(topFourBHCA)
+	avgBHCC := calculateTrafficDataAverage(topFourBHCC)
+
+	// 4. 返回结果
+	return map[string]any{
+		"busyHourAverageBHCA": avgBHCA,
+		"busyHourAverageBHCC": avgBHCC,
+		"topFourHoursBHCA":    topFourBHCA,
+		"topFourHoursBHCC":    topFourBHCC,
+		"totalHours":          len(data),
+	}
+}
+
+// 辅助函数：获取前四个最高值的TrafficData
+func getTopFourTrafficData(data []TrafficData) []TrafficData {
+	if len(data) == 0 {
+		return []TrafficData{}
+	}
+
+	// 最多取前四个值
+	maxCount := 4
+	if len(data) < maxCount {
+		maxCount = len(data)
+	}
+
+	return data[:maxCount]
+}
+
+// 辅助函数：计算TrafficData的平均值
+func calculateTrafficDataAverage(data []TrafficData) float64 {
+	if len(data) == 0 {
+		return 0
+	}
+
+	var sum float64 = 0
+	for _, v := range data {
+		sum += v.Value
+	}
+
+	return sum / float64(len(data))
+}