eta_api/services/data/correlation/chart_info.go

package correlation

import (
	"encoding/json"
	"errors"
	"eta/eta_api/models/data_manage"
	"eta/eta_api/models/system"
	"eta/eta_api/services/alarm_msg"
	"eta/eta_api/services/data"
	"eta/eta_api/utils"
	"fmt"
	"github.com/shopspring/decimal"
	"math"
	"sort"
	"strconv"
	"strings"
	"sync"
	"time"
)

// HandleDataByLinearRegression 线性方程插值法补全数据
func HandleDataByLinearRegression(originList []*data_manage.EdbDataList, handleDataMap map[string]float64) (newList []*data_manage.EdbDataList, err error) {
	if len(originList) < 2 {
		return
	}

	var startEdbInfoData *data_manage.EdbDataList
	for _, v := range originList {
		handleDataMap[v.DataTime] = v.Value

		// 第一个数据就给过滤了,给后面的试用
		if startEdbInfoData == nil {
			startEdbInfoData = v
			newList = append(newList, &data_manage.EdbDataList{
				DataTime: v.DataTime,
				Value:    v.Value,
			})
			continue
		}

		// 获取两条数据之间相差的天数
		startDataTime, _ := time.ParseInLocation(utils.FormatDate, startEdbInfoData.DataTime, time.Local)
		currDataTime, _ := time.ParseInLocation(utils.FormatDate, v.DataTime, time.Local)
		betweenHour := int(currDataTime.Sub(startDataTime).Hours())
		betweenDay := betweenHour / 24

		// 如果相差一天,那么过滤
		if betweenDay <= 1 {
			startEdbInfoData = v
			newList = append(newList, &data_manage.EdbDataList{
				DataTime: v.DataTime,
				Value:    v.Value,
			})
			continue
		}

		// 生成线性方程式
		var a, b float64
		{
			coordinateData := make([]utils.Coordinate, 0)
			tmpCoordinate1 := utils.Coordinate{
				X: 1,
				Y: startEdbInfoData.Value,
			}
			coordinateData = append(coordinateData, tmpCoordinate1)
			tmpCoordinate2 := utils.Coordinate{
				X: float64(betweenDay) + 1,
				Y: v.Value,
			}
			coordinateData = append(coordinateData, tmpCoordinate2)

			a, b = utils.GetLinearResult(coordinateData)
			if math.IsNaN(a) || math.IsNaN(b) {
				err = fmt.Errorf("线性方程公式生成失败")
				return
			}
		}

		// 生成对应的值
		{
			for i := 1; i < betweenDay; i++ {
				tmpDataTime := startDataTime.AddDate(0, 0, i)
				aDecimal := decimal.NewFromFloat(a)
				xDecimal := decimal.NewFromInt(int64(i) + 1)
				bDecimal := decimal.NewFromFloat(b)

				val, _ := aDecimal.Mul(xDecimal).Add(bDecimal).Round(4).Float64()
				handleDataMap[tmpDataTime.Format(utils.FormatDate)] = val
				newList = append(newList, &data_manage.EdbDataList{
					DataTime: tmpDataTime.Format(utils.FormatDate),
					Value:    val,
				})
			}
		}

		// 最后将自己赋值
		newList = append(newList, &data_manage.EdbDataList{
			EdbDataId: v.EdbDataId,
			DataTime:  v.DataTime,
			Value:     v.Value,
		})

		startEdbInfoData = v
	}
	return
}

// MoveDataDaysToNewDataList 平移指标数据生成新的数据序列
func MoveDataDaysToNewDataList(dataList []*data_manage.EdbDataList, moveDay int) (newDataList []data_manage.EdbDataList, dateDataMap map[string]float64) {
	dateMap := make(map[time.Time]float64)
	var minDate, maxDate time.Time
	dateDataMap = make(map[string]float64)

	for _, v := range dataList {
		currDate, _ := time.ParseInLocation(utils.FormatDate, v.DataTime, time.Local)
		if minDate.IsZero() || currDate.Before(minDate) {
			minDate = currDate
		}
		if maxDate.IsZero() || currDate.After(maxDate) {
			maxDate = currDate
		}
		dateMap[currDate] = v.Value
	}

	// 处理领先、滞后数据
	newDateMap := make(map[time.Time]float64)
	for currDate, value := range dateMap {
		newDate := currDate.AddDate(0, 0, moveDay)
		newDateMap[newDate] = value
	}
	minDate = minDate.AddDate(0, 0, moveDay)
	maxDate = maxDate.AddDate(0, 0, moveDay)

	// 获取日期相差日
	dayNum := utils.GetTimeSubDay(minDate, maxDate)

	for i := 0; i <= dayNum; i++ {
		currDate := minDate.AddDate(0, 0, i)
		tmpValue, ok := newDateMap[currDate]
		if !ok {
			//找不到数据，那么就用前面的数据吧
			if len(newDataList)-1 < 0 {
				tmpValue = 0
			} else {
				tmpValue = newDataList[len(newDataList)-1].Value
			}
		}
		tmpData := data_manage.EdbDataList{
			DataTime: currDate.Format(utils.FormatDate),
			Value:    tmpValue,
		}
		dateDataMap[tmpData.DataTime] = tmpData.Value
		newDataList = append(newDataList, tmpData)
	}
	return
}

// GetChartEdbInfoFormat 相关性图表-获取指标信息
func GetChartEdbInfoFormat(chartInfoId int, edbInfoMappingA, edbInfoMappingB *data_manage.ChartEdbInfoMapping) (edbList []*data_manage.ChartEdbInfoMapping, err error) {
	edbList = make([]*data_manage.ChartEdbInfoMapping, 0)
	if edbInfoMappingA == nil || edbInfoMappingB == nil {
		err = fmt.Errorf("指标信息有误")
		return
	}

	edbInfoMappingA.FrequencyEn = data.GetFrequencyEn(edbInfoMappingA.Frequency)
	if edbInfoMappingA.Unit == `无` {
		edbInfoMappingA.Unit = ``
	}
	if edbInfoMappingB.Unit == `无` {
		edbInfoMappingB.Unit = ``
	}
	if chartInfoId <= 0 {
		edbInfoMappingA.IsAxis = 1
		edbInfoMappingA.LeadValue = 0
		edbInfoMappingA.LeadUnit = ""
		edbInfoMappingA.ChartEdbMappingId = 0
		edbInfoMappingA.ChartInfoId = 0
		edbInfoMappingA.IsOrder = false
		edbInfoMappingA.EdbInfoType = 1
		edbInfoMappingA.ChartStyle = ""
		edbInfoMappingA.ChartColor = ""
		edbInfoMappingA.ChartWidth = 0

		edbInfoMappingB.IsAxis = 1
		edbInfoMappingB.LeadValue = 0
		edbInfoMappingB.LeadUnit = ""
		edbInfoMappingB.ChartEdbMappingId = 0
		edbInfoMappingB.ChartInfoId = 0
		edbInfoMappingB.IsOrder = false
		edbInfoMappingB.EdbInfoType = 1
		edbInfoMappingB.ChartStyle = ""
		edbInfoMappingB.ChartColor = ""
		edbInfoMappingB.ChartWidth = 0
	} else {
		edbInfoMappingA.LeadUnitEn = data.GetLeadUnitEn(edbInfoMappingA.LeadUnit)
		edbInfoMappingB.LeadUnitEn = data.GetLeadUnitEn(edbInfoMappingB.LeadUnit)
	}
	edbList = append(edbList, edbInfoMappingA, edbInfoMappingB)
	return
}

// GetChartDataByEdbInfo 相关性图表-根据指标信息获取x轴和y轴
func GetChartDataByEdbInfo(edbInfoMappingA, edbInfoMappingB *data_manage.ChartEdbInfoMapping, leadValue int, leadUnit, startDate, endDate, extraConfig string) (xEdbIdValue []int, yDataList []data_manage.YData, err error) {
	xData := make([]int, 0)
	yData := make([]float64, 0)
	if leadValue == 0 {
		xData = append(xData, 0)
	}
	if leadValue > 0 {
		leadMin := 0 - leadValue
		xLen := 2*leadValue + 1
		for i := 0; i < xLen; i++ {
			n := leadMin + i
			xData = append(xData, n)
		}
	}

	// 计算窗口，不包含第一天
	startDateTime, _ := time.ParseInLocation(utils.FormatDate, startDate, time.Local)
	startDate = startDateTime.AddDate(0, 0, 1).Format(utils.FormatDate)

	//// 2023-03-02 时间序列始终以指标B为基准, 始终是A进行平移
	//baseEdbInfo := edbInfoMappingB
	//changeEdbInfo := edbInfoMappingA
	// 2023-03-17 时间序列始终以指标A为基准, 始终是B进行平移
	baseEdbInfo := edbInfoMappingA
	changeEdbInfo := edbInfoMappingB

	// 获取时间基准指标在时间区间内的值
	aDataList := make([]*data_manage.EdbDataList, 0)
	switch baseEdbInfo.EdbInfoCategoryType {
	case 0:
		aDataList, err = data_manage.GetEdbDataList(baseEdbInfo.Source, baseEdbInfo.SubSource, baseEdbInfo.EdbInfoId, startDate, endDate)
	case 1:
		_, aDataList, _, _, err, _ = data.GetPredictDataListByPredictEdbInfoId(baseEdbInfo.EdbInfoId, startDate, endDate, false)
	default:
		err = errors.New("指标base类型异常")
		return
	}

	// 获取变频指标所有日期的值, 插值法完善数据
	bDataList := make([]*data_manage.EdbDataList, 0)
	switch changeEdbInfo.EdbInfoCategoryType {
	case 0:
		bDataList, err = data_manage.GetEdbDataList(changeEdbInfo.Source, changeEdbInfo.SubSource, changeEdbInfo.EdbInfoId, "", "")
	case 1:
		_, bDataList, _, _, err, _ = data.GetPredictDataListByPredictEdbInfoId(changeEdbInfo.EdbInfoId, "", "", false)
	default:
		err = errors.New("指标change类型异常")
		return
	}
	//changeDataMap := make(map[string]float64)
	//newChangeDataList, e := HandleDataByLinearRegression(bDataList, changeDataMap)
	//if e != nil {
	//	err = fmt.Errorf("获取变频指标插值法Map失败, Err: %s", e.Error())
	//	return
	//}

	// 2023-03-17 时间序列始终以指标A为基准, 始终是B进行平移
	baseDataList := make([]*data_manage.EdbDataList, 0)
	baseDataMap := make(map[string]float64)
	changeDataList := make([]*data_manage.EdbDataList, 0)
	changeDataMap := make(map[string]float64)

	// 先把低频指标升频为高频
	{
		frequencyIntMap := map[string]int{
			"日度": 1,
			"周度": 2,
			"旬度": 3,
			"月度": 4,
			"季度": 5,
			"年度": 6,
		}

		// 如果A指标是高频，那么就需要对B指标进行升频
		if frequencyIntMap[edbInfoMappingA.Frequency] < frequencyIntMap[edbInfoMappingB.Frequency] {
			tmpNewChangeDataList, e := HandleDataByLinearRegression(bDataList, changeDataMap)
			if e != nil {
				err = fmt.Errorf("获取变频指标插值法Map失败, Err: %s", e.Error())
				return
			}
			changeDataList = tmpNewChangeDataList
			baseDataList = aDataList
			for _, v := range baseDataList {
				baseDataMap[v.DataTime] = v.Value
			}

		} else if frequencyIntMap[edbInfoMappingA.Frequency] > frequencyIntMap[edbInfoMappingB.Frequency] {
			// 如果B指标是高频，那么就需要对A指标进行升频
			tmpNewChangeDataList, e := HandleDataByLinearRegression(aDataList, baseDataMap)
			if e != nil {
				err = fmt.Errorf("获取变频指标插值法Map失败, Err: %s", e.Error())
				return
			}
			baseDataList = tmpNewChangeDataList

			changeDataList = bDataList
			for _, v := range changeDataList {
				changeDataMap[v.DataTime] = v.Value
			}
		} else {
			baseDataList = aDataList
			for _, v := range baseDataList {
				baseDataMap[v.DataTime] = v.Value
			}
			changeDataList = bDataList
			for _, v := range changeDataList {
				changeDataMap[v.DataTime] = v.Value
			}
		}

	}

	// 计算不领先也不滞后时的相关系数
	baseCalculateData := make([]float64, 0)
	baseDataTimeArr := make([]string, 0)
	for i := range baseDataList {
		baseDataTimeArr = append(baseDataTimeArr, baseDataList[i].DataTime)
		baseCalculateData = append(baseCalculateData, baseDataList[i].Value)
	}

	//zeroBaseData := make([]float64, 0)
	//zeroCalculateData := make([]float64, 0)
	//for i := range baseDataTimeArr {
	//	tmpBaseVal, ok1 := baseDataMap[baseDataTimeArr[i]]
	//	tmpCalculateVal, ok2 := changeDataMap[baseDataTimeArr[i]]
	//	if ok1 && ok2 {
	//		zeroBaseData = append(zeroBaseData, tmpBaseVal)
	//		zeroCalculateData = append(zeroCalculateData, tmpCalculateVal)
	//	}
	//}
	//if len(zeroBaseData) != len(zeroCalculateData) {
	//	err = fmt.Errorf("相关系数两组序列元素数不一致, %d-%d", len(baseCalculateData), len(zeroCalculateData))
	//	return
	//}
	//zeroRatio := utils.CalculateCorrelationByIntArr(zeroBaseData, zeroCalculateData)
	//if leadValue == 0 {
	//	yData = append(yData, zeroRatio)
	//}

	// 计算领先/滞后N期
	if leadValue > 0 {
		// 平移变频指标领先/滞后的日期(单位天)
		moveUnitDays := utils.FrequencyDaysMap[leadUnit]

		for i := range xData {
			//if xData[i] == 0 {
			//	yData = append(yData, zeroRatio)
			//	continue
			//}
			xCalculateData := make([]float64, 0)
			yCalculateData := make([]float64, 0)

			// 平移指定天数
			mDays := int(moveUnitDays) * xData[i]
			_, dMap := MoveDataDaysToNewDataList(changeDataList, mDays)

			// 取出对应的基准日期的值
			for i2 := range baseDataTimeArr {
				tmpDate := baseDataTimeArr[i2]
				if yVal, ok := dMap[tmpDate]; ok {
					xCalculateData = append(xCalculateData, baseCalculateData[i2])
					yCalculateData = append(yCalculateData, yVal)
				}
			}
			if len(yCalculateData) <= 0 {
				//err = fmt.Errorf("领先滞后相关系数两组序列元素数不一致, %d-%d", len(baseCalculateData), len(yCalculateData))
				//return
				// 领先滞后后，没有可以计算的数据了
				continue
			}

			// 公式计算出领先/滞后频度对应点的相关性系数
			ratio := utils.CalculateCorrelationByIntArr(xCalculateData, yCalculateData)
			yData = append(yData, ratio)
		}
	}

	// 图例
	var extra data_manage.CorrelationChartInfoExtraConfig
	legend := new(data_manage.CorrelationChartLegend)
	if extraConfig != "" {
		if e := json.Unmarshal([]byte(extraConfig), &extra); e != nil {
			err = fmt.Errorf("图例解析异常, err: %v", e)
			return
		}
		if len(extra.LegendConfig) > 0 {
			legend = extra.LegendConfig[0]
		}
	}

	xEdbIdValue = xData
	yDataList = make([]data_manage.YData, 0)
	yDate := "0000-00-00"
	var y data_manage.YData
	y.Date = yDate
	y.Value = yData
	if legend != nil {
		y.Name = legend.LegendName
		y.Color = legend.Color
	}
	yDataList = append(yDataList, y)
	return
}

// RollingCorrelationChartDataResp 滚动相关性图表数据
type RollingCorrelationChartDataResp struct {
	MaxData             float64
	MinData             float64
	LatestDate          string `description:"真实数据的最后日期"`
	EdbInfoCategoryType int
	ChartColor          string
	ChartStyle          string
	PredictChartColor   string
	ChartType           int
	ChartWidth          int
	EdbName             string
	EdbNameEn           string
	Unit                string
	UnitEn              string
	IsAxis              int
	DataList            []data_manage.EdbDataList
}

// GetRollingCorrelationChartDataByEdbInfo 滚动相关性计算
func GetRollingCorrelationChartDataByEdbInfo(edbInfoMappingA, edbInfoMappingB *data_manage.ChartEdbInfoMapping, leadValue int, leadUnit string, calculateValue int, calculateUnit string, startDate, endDate, chartName, chartNameEn string) (dataResp RollingCorrelationChartDataResp, err error) {
	dataResp = RollingCorrelationChartDataResp{
		DataList:          make([]data_manage.EdbDataList, 0),
		MaxData:           0,
		MinData:           0,
		ChartColor:        "#00f",
		ChartStyle:        `spline`,
		PredictChartColor: `#00f`,
		ChartType:         0,
		ChartWidth:        3,
		EdbName:           chartName,
		EdbNameEn:         chartNameEn,
		IsAxis:            1,
	}
	dataList := make([]data_manage.EdbDataList, 0)

	// 计算窗口，不包含第一天
	startDateTime, _ := time.ParseInLocation(utils.FormatDate, startDate, time.Local)
	startDate = startDateTime.AddDate(0, 0, 1).Format(utils.FormatDate)

	baseEdbInfo := edbInfoMappingA
	changeEdbInfo := edbInfoMappingB

	// 获取时间基准指标在时间区间内的值
	aDataList := make([]*data_manage.EdbDataList, 0)
	switch baseEdbInfo.EdbInfoCategoryType {
	case 0:
		aDataList, err = data_manage.GetEdbDataList(baseEdbInfo.Source, baseEdbInfo.SubSource, baseEdbInfo.EdbInfoId, startDate, endDate)
	case 1:
		_, aDataList, _, _, err, _ = data.GetPredictDataListByPredictEdbInfoId(baseEdbInfo.EdbInfoId, startDate, endDate, true)
	default:
		err = errors.New("指标base类型异常")
		return
	}

	// 获取变频指标所有日期的值, 插值法完善数据
	bDataList := make([]*data_manage.EdbDataList, 0)
	switch changeEdbInfo.EdbInfoCategoryType {
	case 0:
		bDataList, err = data_manage.GetEdbDataList(changeEdbInfo.Source, changeEdbInfo.SubSource, changeEdbInfo.EdbInfoId, "", "")
	case 1:
		_, bDataList, _, _, err, _ = data.GetPredictDataListByPredictEdbInfoId(changeEdbInfo.EdbInfoId, "", "", false)
	default:
		err = errors.New("指标change类型异常")
		return
	}

	// 数据平移变频指标领先/滞后的日期(单位天)
	// 2023-03-17 时间序列始终以指标A为基准, 始终是B进行平移
	//baseDataList := make([]*data_manage.EdbDataList, 0)
	baseDataMap := make(map[string]float64)
	changeDataList := make([]*data_manage.EdbDataList, 0)
	changeDataMap := make(map[string]float64)

	// A指标不管三七二十一，先变个频再说
	{
		_, e := HandleDataByLinearRegression(aDataList, baseDataMap)
		if e != nil {
			err = fmt.Errorf("获取变频指标插值法Map失败, Err: %s", e.Error())
			return
		}
		//baseDataList = tmpNewChangeDataList
	}
	// B指标不管三七二十一，先变个频再说
	{
		tmpNewChangeDataList, e := HandleDataByLinearRegression(bDataList, changeDataMap)
		if e != nil {
			err = fmt.Errorf("获取变频指标插值法Map失败, Err: %s", e.Error())
			return
		}
		changeDataList = tmpNewChangeDataList

		// 平移下日期
		moveUnitDays := utils.FrequencyDaysMap[leadUnit]
		_, changeDataMap = MoveDataDaysToNewDataList(changeDataList, leadValue*moveUnitDays)
	}

	// 计算计算时，需要多少个日期内数据
	calculateDay := utils.FrequencyDaysMap[calculateUnit] * calculateValue

	// 计算 每个日期的相关性值
	{
		startDateTime, _ := time.ParseInLocation(utils.FormatDate, startDate, time.Local)
		if endDate == `` {
			endDate = baseEdbInfo.EndDate
		}
		endDateTime, _ := time.ParseInLocation(utils.FormatDate, endDate, time.Local)
		endDateTime = endDateTime.AddDate(0, 0, -(calculateDay - 1))

		// 是否开始第一条数据
		var isStart, isNotFirst bool
		for currDay := startDateTime; !currDay.After(endDateTime); currDay = currDay.AddDate(0, 0, 1) {
			yCalculateData := make([]float64, 0)
			baseCalculateData := make([]float64, 0)

			// 取出对应的基准日期的值
			for i := 0; i < calculateDay; i++ {
				iDay := currDay.AddDate(0, 0, i).Format(utils.FormatDate)

				tmpBaseValue, ok1 := baseDataMap[iDay]
				tmpChangeValue, ok2 := changeDataMap[iDay]
				if ok1 && ok2 {
					baseCalculateData = append(baseCalculateData, tmpBaseValue)
					yCalculateData = append(yCalculateData, tmpChangeValue)
				} else {
					continue
				}
			}

			// 公式计算出领先/滞后频度对应点的相关性系数
			var ratio float64
			if len(baseCalculateData) > 0 {
				ratio = utils.CalculateCorrelationByIntArr(baseCalculateData, yCalculateData)
			} else {
				// 没有数据的话，那就不返回
				continue
			}

			// 过滤前面都是0的数据
			{
				if ratio != 0 {
					isStart = true
				}

				if !isStart {
					continue
				}
			}

			dataTime := currDay.AddDate(0, 0, calculateDay-1)
			dataList = append(dataList, data_manage.EdbDataList{
				//EdbDataId:     0,
				EdbInfoId:     0,
				DataTime:      dataTime.Format(utils.FormatDate),
				DataTimestamp: dataTime.UnixNano() / 1e6,
				Value:         ratio,
			})

			if !isNotFirst {
				dataResp.MinData = ratio
				dataResp.MaxData = ratio
				isNotFirst = true
			}
			if dataResp.MinData > ratio {
				dataResp.MinData = ratio
			}
			if dataResp.MaxData < ratio {
				dataResp.MaxData = ratio
			}
		}
		dataResp.DataList = dataList
	}

	return
}

// ChartInfoRefresh 图表刷新
func ChartInfoRefresh(chartInfoId int, uniqueCode string) (isAsync bool, err error) {
	var errMsg string
	defer func() {
		if err != nil {
			tips := fmt.Sprintf("CorrelationChartInfoRefresh: %s", errMsg)
			utils.FileLog.Info(tips)
			go alarm_msg.SendAlarmMsg(tips, 3)
		}
	}()
	correlationChart := new(data_manage.ChartInfoCorrelation)
	if err = correlationChart.GetItemById(chartInfoId); err != nil {
		errMsg = "获取相关性图表失败, Err: " + err.Error()
		return
	}

	// 多因子刷新-异步
	if correlationChart.AnalysisMode == 1 {
		isAsync = true

		go func() {
			// 1.刷新图表关联的指标
			mappings, e := data_manage.GetChartEdbMappingList(chartInfoId)
			if e != nil {
				utils.FileLog.Info(fmt.Sprintf("获取图表关联指标失败, err: %v", e))
				return
			}
			if len(mappings) == 0 {
				utils.FileLog.Info("图表无关联指标")
				return
			}
			var edbIds []int
			for _, v := range mappings {
				edbIds = append(edbIds, v.EdbInfoId)
			}
			if e, _ = data.EdbInfoRefreshAllFromBaseV3(edbIds, false, true, false); e != nil {
				utils.FileLog.Info(fmt.Sprintf("批量刷新指标失败, err: %v", e))
				return
			}

			// 2.刷新指标系列计算数据
			for _, v := range mappings {
				_, e = data.PostRefreshFactorEdbRecalculate(v.EdbInfoId, v.EdbCode)
				if e != nil {
					utils.FileLog.Info(fmt.Sprintf("PostRefreshFactorEdbRecalculate err: %v", e))
					continue
				}
			}

			// 3.刷新图表矩阵
			_, e = data.PostRefreshFactorEdbChartRecalculate(chartInfoId)
			if e != nil {
				utils.FileLog.Info(fmt.Sprintf("PostRefreshFactorEdbRecalculate err: %v", e))
				return
			}

			// 4.清除图表缓存
			key := utils.HZ_CHART_LIB_DETAIL + uniqueCode
			_ = utils.Rc.Delete(key)
		}()
		return
	}

	// 批量刷新ETA指标
	err, _ = data.EdbInfoRefreshAllFromBaseV3([]int{correlationChart.EdbInfoIdFirst, correlationChart.EdbInfoIdSecond}, false, true, false)
	if err != nil {
		return
	}

	// 重新生成数据并更新
	edbInfoMappingA, err := data_manage.GetChartEdbMappingByEdbInfoId(correlationChart.EdbInfoIdFirst)
	if err != nil {
		errMsg = "获取相关性图表, A指标mapping信息失败, Err:" + err.Error()
		return
	}
	edbInfoMappingB, err := data_manage.GetChartEdbMappingByEdbInfoId(correlationChart.EdbInfoIdSecond)
	if err != nil {
		errMsg = "获取相关性图表, B指标mapping信息失败, Err:" + err.Error()
		return
	}
	periodData, correlationData, err := GetChartDataByEdbInfo(edbInfoMappingA, edbInfoMappingB, correlationChart.LeadValue, correlationChart.LeadUnit, correlationChart.StartDate.Format(utils.FormatDate), correlationChart.EndDate.Format(utils.FormatDate), "")
	if err != nil {
		errMsg = "获取相关性图表, 图表计算值失败, Err:" + err.Error()
		return
	}
	periodDataByte, err := json.Marshal(periodData)
	if err != nil {
		errMsg = "相关性图表, X轴信息有误, Err:" + err.Error()
		return
	}
	correlationDataByte, err := json.Marshal(correlationData[0].Value)
	if err != nil {
		errMsg = "相关性图表, Y轴信息有误, Err:" + err.Error()
		return
	}
	correlationChart.PeriodData = string(periodDataByte)
	correlationChart.CorrelationData = string(correlationDataByte)
	correlationChart.ModifyTime = time.Now().Local()
	correlationUpdateCols := []string{"PeriodData", "CorrelationData", "ModifyTime"}
	if err = correlationChart.Update(correlationUpdateCols); err != nil {
		errMsg = "更新相关性图表失败, Err:" + err.Error()
		return
	}
	return
}

// GetChartAndCorrelationInfo 获取图表信息和相关信息信息
func GetChartAndCorrelationInfo(chartInfoId int) (chartInfo *data_manage.ChartInfo, correlationInfo *data_manage.ChartInfoCorrelation, tips string, err error) {
	item, e := data_manage.GetChartInfoById(chartInfoId)
	if e != nil {
		if e.Error() == utils.ErrNoRow() {
			tips = "图表已被删除, 请刷新页面"
			err = fmt.Errorf("图表已被删除, 请刷新页面")
			return
		}
		err = fmt.Errorf("获取图表信息失败, Err: %s", e.Error())
		return
	}
	if item.Source != utils.CHART_SOURCE_CORRELATION {
		tips = "该图不是相关性图表"
		err = fmt.Errorf("该图不是相关性图表")
		return
	}
	chartInfo = item
	correlationInfo = new(data_manage.ChartInfoCorrelation)
	if e = correlationInfo.GetItemById(chartInfo.ChartInfoId); e != nil {
		err = fmt.Errorf("获取图表相关性信息失败, Err: %s", e.Error())
		return
	}
	return
}

// AddChartInfo 添加图表
func AddChartInfo(req data_manage.AddChartInfoReq, source int, sysUser *system.Admin, lang string) (chartInfo *data_manage.ChartInfo, err error, errMsg string, isSendEmail bool) {
	isSendEmail = true

	req.ChartName = strings.Trim(req.ChartName, " ")
	if req.ChartName == "" {
		errMsg = "请填写图表名称！"
		err = errors.New(errMsg)
		isSendEmail = false
		return
	}
	if req.ChartClassifyId <= 0 {
		errMsg = "分类参数错误！"
		err = errors.New(errMsg)
		isSendEmail = false
		return
	}
	// 相关性图表配置
	if req.CorrelationChartInfo.LeadValue == 0 && source == utils.CHART_SOURCE_CORRELATION {
		errMsg = "请输入领先期数"
		err = errors.New(errMsg)
		isSendEmail = false
		return
	}
	if req.CorrelationChartInfo.LeadUnit == "" {
		errMsg = "请填写领先单位"
		err = errors.New(errMsg)
		isSendEmail = false
		return
	}
	//if req.CorrelationChartInfo.StartDate == "" || req.CorrelationChartInfo.EndDate == "" {
	//	errMsg = "请填写开始结束日期"
	//	err = errors.New(errMsg)
	//	isSendEmail = false
	//	return
	//}
	//startDate, e := time.Parse(utils.FormatDate, req.CorrelationChartInfo.StartDate)
	//if e != nil {
	//	errMsg = "开始日期格式有误"
	//	err = errors.New(errMsg)
	//	isSendEmail = false
	//	return
	//}
	//endDate, e := time.Parse(utils.FormatDate, req.CorrelationChartInfo.EndDate)
	//if e != nil {
	//	errMsg = "结束日期格式有误"
	//	err = errors.New(errMsg)
	//	isSendEmail = false
	//	return
	//}
	if len(req.CorrelationChartInfo.EdbInfoIdList) != 2 {
		errMsg = "请选择AB指标"
		err = errors.New(errMsg)
		isSendEmail = false
		return
	}

	chartClassify, err := data_manage.GetChartClassifyById(req.ChartClassifyId)
	if err != nil {
		if err.Error() == utils.ErrNoRow() {
			errMsg = "分类不存在"
			err = errors.New(errMsg)
			isSendEmail = false
			return
		}
		errMsg = "获取分类信息失败"
		err = errors.New("获取分类信息失败，Err:" + err.Error())
		return
	}
	if chartClassify == nil {
		errMsg = "分类不存在"
		err = errors.New(errMsg)
		isSendEmail = false
		return
	}

	var edbInfoIdArr []int
	for _, v := range req.CorrelationChartInfo.EdbInfoIdList {
		edbInfoId := v.EdbInfoId
		edbInfo, tmpErr := data_manage.GetEdbInfoById(edbInfoId)
		if tmpErr != nil {
			if tmpErr.Error() == utils.ErrNoRow() {
				errMsg = "指标不存在！"
				err = errors.New("指标不存在，edbInfoId:" + strconv.Itoa(edbInfoId))
				return
			} else {
				errMsg = "获取指标信息失败！"
				err = errors.New("获取图表的指标信息失败，Err:" + tmpErr.Error())
				return
			}
		}

		if edbInfo == nil {
			errMsg = "指标已被删除，请重新选择！"
			err = errors.New("指标不存在，ChartInfoId:" + strconv.Itoa(edbInfoId))
			return
		} else {
			if edbInfo.EdbInfoId <= 0 {
				errMsg = "指标已被删除，请重新选择！"
				err = errors.New("指标不存在，ChartInfoId:" + strconv.Itoa(edbInfoId))
				return
			}
		}

		edbInfoIdArr = append(edbInfoIdArr, edbInfoId)
		edbInfo.EdbNameSource = edbInfo.EdbName
	}

	sort.Ints(edbInfoIdArr)
	var edbInfoIdArrStr []string
	for _, v := range edbInfoIdArr {
		edbInfoIdArrStr = append(edbInfoIdArrStr, strconv.Itoa(v))
	}
	edbInfoIdStr := strings.Join(edbInfoIdArrStr, ",")
	var chartInfoId int

	// 判断图表是否存在
	{
		var condition string
		var pars []interface{}

		switch lang {
		case utils.EnLangVersion:
			condition += " AND chart_name_en = ? AND source = ? "
		default:
			condition += " AND chart_name=? AND source = ? "
		}
		pars = append(pars, req.ChartName, source)
		count, tmpErr := data_manage.GetChartInfoCountByCondition(condition, pars)
		if tmpErr != nil {
			errMsg = "判断图表名称是否存在失败"
			err = errors.New("判断图表名称是否存在失败,Err:" + tmpErr.Error())
			return
		}

		if count > 0 {
			errMsg = "图表已存在，请重新填写"
			err = errors.New(errMsg)
			isSendEmail = false
			return
		}
	}

	disableVal := data.CheckIsDisableChart(edbInfoIdArr)

	chartInfo = new(data_manage.ChartInfo)
	chartInfo.ChartName = req.ChartName
	chartInfo.ChartNameEn = req.ChartName
	chartInfo.EdbInfoIds = edbInfoIdStr
	chartInfo.ChartClassifyId = req.ChartClassifyId
	chartInfo.SysUserId = sysUser.AdminId
	chartInfo.SysUserRealName = sysUser.RealName
	chartInfo.CreateTime = time.Now()
	chartInfo.ModifyTime = time.Now()
	chartInfo.IsSetName = 0
	timestamp := strconv.FormatInt(time.Now().UnixNano(), 10)
	chartInfo.UniqueCode = utils.MD5(utils.CHART_PREFIX + "_" + timestamp)
	chartInfo.ChartType = 9 // 相关性图
	chartInfo.Calendar = "公历"
	chartInfo.DateType = 6
	chartInfo.StartDate = req.StartDate
	chartInfo.EndDate = req.EndDate
	chartInfo.SeasonStartDate = req.StartDate
	chartInfo.SeasonEndDate = req.EndDate
	chartInfo.LeftMin = req.LeftMin
	chartInfo.LeftMax = req.LeftMax
	chartInfo.RightMin = req.RightMin
	chartInfo.RightMax = req.RightMax
	chartInfo.Disabled = disableVal
	chartInfo.Source = source
	chartInfo.ChartThemeId = req.ChartThemeId
	chartInfo.SourcesFrom = req.SourcesFrom
	chartInfo.Instructions = req.Instructions
	chartInfo.MarkersLines = req.MarkersLines
	chartInfo.MarkersAreas = req.MarkersAreas
	if req.ExtraConfig != "" {
		chartInfo.ExtraConfig = req.ExtraConfig
	}

	// 指标信息
	mapList := make([]*data_manage.ChartEdbMapping, 0)
	for _, v := range req.CorrelationChartInfo.EdbInfoIdList {
		mapItem := new(data_manage.ChartEdbMapping)
		mapItem.EdbInfoId = v.EdbInfoId
		mapItem.CreateTime = time.Now()
		mapItem.ModifyTime = time.Now()
		edbTimestamp := strconv.FormatInt(time.Now().UnixNano(), 10)
		mapItem.UniqueCode = utils.MD5(utils.CHART_PREFIX + "_" + edbTimestamp + "_" + strconv.Itoa(v.EdbInfoId))
		mapItem.IsOrder = true
		mapItem.IsAxis = 1
		mapItem.EdbInfoType = 1
		mapItem.Source = utils.CHART_SOURCE_CORRELATION
		mapList = append(mapList, mapItem)
	}

	// 相关性图表扩展信息
	correlationChart := new(data_manage.ChartInfoCorrelation)
	correlationChart.LeadValue = req.CorrelationChartInfo.LeadValue
	correlationChart.LeadUnit = req.CorrelationChartInfo.LeadUnit
	correlationChart.CalculateValue = req.CorrelationChartInfo.CalculateValue
	correlationChart.CalculateUnit = req.CorrelationChartInfo.CalculateUnit
	correlationChart.BaseCalculateValue = req.CorrelationChartInfo.BaseCalculateValue
	correlationChart.BaseCalculateUnit = req.CorrelationChartInfo.BaseCalculateUnit

	// 滚动相关性会有日期等信息
	if source == utils.CHART_SOURCE_ROLLING_CORRELATION {
		correlationChart.DateType = req.CorrelationChartInfo.DateType
		if req.CorrelationChartInfo.StartDate != `` {
			startDateTime, tmpErr := time.ParseInLocation(utils.FormatDate, req.CorrelationChartInfo.StartDate, time.Local)
			if tmpErr != nil {
				err = tmpErr
				return
			}
			correlationChart.StartDate = startDateTime
		}
		if req.CorrelationChartInfo.EndDate != `` {
			endDateTime, tmpErr := time.ParseInLocation(utils.FormatDate, req.CorrelationChartInfo.EndDate, time.Local)
			if tmpErr != nil {
				err = tmpErr
				return
			}
			correlationChart.EndDate = endDateTime
		}
	}
	correlationChart.EdbInfoIdFirst = req.CorrelationChartInfo.EdbInfoIdList[0].EdbInfoId
	correlationChart.EdbInfoIdSecond = req.CorrelationChartInfo.EdbInfoIdList[1].EdbInfoId
	correlationChart.CreateTime = time.Now().Local()
	correlationChart.ModifyTime = time.Now().Local()
	//// 生成图表x轴y轴数据
	//edbInfoMappingA, e := data_manage.GetChartEdbMappingByEdbInfoId(req.CorrelationChartInfo.EdbInfoIdList[0].EdbInfoId)
	//if e != nil {
	//	errMsg = "获取失败"
	//	err = errors.New("获取相关性图表, A指标mapping信息失败, Err:" + e.Error())
	//	return
	//}
	//edbInfoMappingB, e := data_manage.GetChartEdbMappingByEdbInfoId(req.CorrelationChartInfo.EdbInfoIdList[1].EdbInfoId)
	//if e != nil {
	//	errMsg = "获取失败"
	//	err = errors.New("获取相关性图表, B指标mapping信息失败, Err:" + e.Error())
	//	return
	//}
	//periodData, correlationData, e := GetChartDataByEdbInfo(edbInfoMappingA, edbInfoMappingB, req.CorrelationChartInfo.LeadValue, req.CorrelationChartInfo.LeadUnit, req.CorrelationChartInfo.StartDate, req.CorrelationChartInfo.EndDate)
	//if e != nil {
	//	errMsg = "获取失败"
	//	err = errors.New("获取相关性图表, 图表计算值失败, Err:" + e.Error())
	//	return
	//}
	//periodDataByte, e := json.Marshal(periodData)
	//if e != nil {
	//	errMsg = "获取失败"
	//	err = errors.New("相关性图表, X轴信息有误, Err:" + e.Error())
	//	return
	//}
	//correlationDataByte, e := json.Marshal(correlationData[0].Value)
	//if e != nil {
	//	errMsg = "获取失败"
	//	err = errors.New("相关性图表, Y轴信息有误, Err:" + e.Error())
	//	return
	//}
	//correlationChart.PeriodData = string(periodDataByte)
	//correlationChart.CorrelationData = string(correlationDataByte)

	// 新增图表和指标mapping
	chartInfoId, e := data_manage.CreateCorrelationChartAndEdb(chartInfo, mapList, correlationChart)
	if e != nil {
		errMsg = "操作失败"
		err = errors.New("新增相关性图表失败, Err: " + e.Error())
		return
	}

	// 添加指标引用记录
	_ = data.SaveChartEdbInfoRelation(edbInfoIdArr, chartInfo)
	//添加es数据
	go data.EsAddOrEditChartInfo(chartInfoId)

	return
}

// EditChartInfo 编辑图表
func EditChartInfo(req data_manage.EditChartInfoReq, sysUser *system.Admin, lang string) (chartItem *data_manage.ChartInfo, err error, errMsg string, isSendEmail bool) {
	isSendEmail = true

	chartItem, err = data_manage.GetChartInfoById(req.ChartInfoId)
	if err != nil {
		if err.Error() == utils.ErrNoRow() {
			errMsg = "图表已被删除，请刷新页面"
			err = errors.New(errMsg)
			isSendEmail = false
			return
		}
		errMsg = "获取图表信息失败"
		err = errors.New("获取图表信息失败,Err:" + err.Error())
		return
	}

	if chartItem.Source != utils.CHART_SOURCE_CORRELATION && chartItem.Source != utils.CHART_SOURCE_ROLLING_CORRELATION {
		errMsg = "该图不是相关性图表！"
		err = errors.New(errMsg)
		isSendEmail = false
		return
	}

	req.ChartName = strings.Trim(req.ChartName, " ")
	if req.ChartClassifyId <= 0 {
		errMsg = "分类参数错误！"
		err = errors.New(errMsg)
		isSendEmail = false
		return
	}
	// 相关性图表配置
	if req.CorrelationChartInfo.LeadValue == 0 && chartItem.Source == utils.CHART_SOURCE_CORRELATION {
		errMsg = "请输入领先期数"
		err = errors.New(errMsg)
		isSendEmail = false
		return
	}
	if req.CorrelationChartInfo.LeadUnit == "" {
		errMsg = "请填写领先单位"
		err = errors.New(errMsg)
		isSendEmail = false
		return
	}
	//if req.CorrelationChartInfo.StartDate == "" || req.CorrelationChartInfo.EndDate == "" {
	//	errMsg = "请填写开始结束日期"
	//	err = errors.New(errMsg)
	//	isSendEmail = false
	//	return
	//}
	startDate, e := time.Parse(utils.FormatDate, req.CorrelationChartInfo.StartDate)
	if e != nil {
		errMsg = "开始日期格式有误"
		err = errors.New(errMsg)
		isSendEmail = false
		return
	}
	var endDate time.Time
	if req.CorrelationChartInfo.EndDate != `` {
		endDate, e = time.Parse(utils.FormatDate, req.CorrelationChartInfo.EndDate)
		if e != nil {
			errMsg = "结束日期格式有误"
			err = errors.New(errMsg)
			isSendEmail = false
			return
		}
	}
	if len(req.CorrelationChartInfo.EdbInfoIdList) != 2 {
		errMsg = "请选择AB指标"
		err = errors.New(errMsg)
		isSendEmail = false
		return
	}

	chartClassify, err := data_manage.GetChartClassifyById(req.ChartClassifyId)
	if err != nil {
		if err.Error() == utils.ErrNoRow() {
			errMsg = "分类不存在"
			err = errors.New(errMsg)
			isSendEmail = false
			return
		}
		errMsg = "获取分类信息失败"
		err = errors.New("获取分类信息失败，Err:" + err.Error())
		return
	}
	if chartClassify == nil {
		errMsg = "分类不存在"
		err = errors.New(errMsg)
		isSendEmail = false
		return
	}

	// 图表操作权限
	ok := data.CheckOpChartPermission(sysUser, chartItem.SysUserId, true)
	if !ok {
		errMsg = "没有该图表的操作权限"
		err = errors.New(errMsg)
		isSendEmail = false
		return
	}

	var edbInfoIdArr []int
	for _, v := range req.CorrelationChartInfo.EdbInfoIdList {
		edbInfoId := v.EdbInfoId
		edbInfo, tmpErr := data_manage.GetEdbInfoById(edbInfoId)
		if tmpErr != nil {
			if tmpErr.Error() == utils.ErrNoRow() {
				errMsg = "图表不存在！"
				err = errors.New("图表指标不存在，ChartInfoId:" + strconv.Itoa(edbInfoId))
				return
			} else {
				errMsg = "获取图表信息失败！"
				err = errors.New("获取图表的指标信息失败，Err:" + tmpErr.Error())
				return
			}
		}

		if edbInfo == nil {
			errMsg = "指标不存在！"
			err = errors.New("指标不存在，ChartInfoId:" + strconv.Itoa(edbInfoId))
			return
		}
		edbInfoIdArr = append(edbInfoIdArr, edbInfoId)
	}

	sort.Ints(edbInfoIdArr)
	var edbInfoIdArrStr []string
	for _, v := range edbInfoIdArr {
		edbInfoIdArrStr = append(edbInfoIdArrStr, strconv.Itoa(v))
	}
	edbInfoIdStr := strings.Join(edbInfoIdArrStr, ",")

	//判断图表是否存在
	{
		var condition string
		var pars []interface{}
		condition += " AND chart_info_id <> ? "
		pars = append(pars, req.ChartInfoId)
		switch lang {
		case utils.EnLangVersion:
			condition += " AND chart_name_en = ? AND source = ? "
		default:
			condition += " AND chart_name=? AND source = ? "
		}
		pars = append(pars, req.ChartName, chartItem.Source)
		count, tmpErr := data_manage.GetChartInfoCountByCondition(condition, pars)
		if tmpErr != nil {
			errMsg = "判断图表名称是否存在失败"
			err = errors.New("判断图表名称是否存在失败,Err:" + tmpErr.Error())
			return
		}
		if count > 0 {
			errMsg = "图表已存在，请重新填写"
			err = errors.New(errMsg)
			isSendEmail = false
			return
		}
	}

	correlationChart := new(data_manage.ChartInfoCorrelation)
	if e := correlationChart.GetItemById(chartItem.ChartInfoId); e != nil {
		errMsg = "操作失败"
		err = errors.New("图表相关性信息不存在, Err: " + e.Error())
		return
	}

	// 图表启用与否
	disableVal := data.CheckIsDisableChart(edbInfoIdArr)

	// 重新生成图表值, 并修改相关性图表扩展信息
	//edbInfoMappingA, e := data_manage.GetChartEdbMappingByEdbInfoId(req.CorrelationChartInfo.EdbInfoIdList[0].EdbInfoId)
	//if e != nil {
	//	errMsg = "获取失败"
	//	err = errors.New("获取相关性图表, A指标mapping信息失败, Err:" + e.Error())
	//	return
	//}
	//edbInfoMappingB, e := data_manage.GetChartEdbMappingByEdbInfoId(req.CorrelationChartInfo.EdbInfoIdList[1].EdbInfoId)
	//if e != nil {
	//	errMsg = "获取失败"
	//	err = errors.New("获取相关性图表, B指标mapping信息失败, Err:" + e.Error())
	//	return
	//}
	//periodData, correlationData, e := GetChartDataByEdbInfo(edbInfoMappingA, edbInfoMappingB, req.CorrelationChartInfo.LeadValue, req.CorrelationChartInfo.LeadUnit, req.CorrelationChartInfo.StartDate, req.CorrelationChartInfo.EndDate)
	//if e != nil {
	//	errMsg = "获取失败"
	//	err = errors.New("获取相关性图表, 图表计算值失败, Err:" + e.Error())
	//	return
	//}
	//periodDataByte, e := json.Marshal(periodData)
	//if e != nil {
	//	errMsg = "获取失败"
	//	err = errors.New("相关性图表, X轴信息有误, Err:" + e.Error())
	//	return
	//}
	//correlationDataByte, e := json.Marshal(correlationData[0].Value)
	//if e != nil {
	//	errMsg = "获取失败"
	//	err = errors.New("相关性图表, Y轴信息有误, Err:" + e.Error())
	//	return
	//}
	correlationChart.LeadValue = req.CorrelationChartInfo.LeadValue
	correlationChart.LeadUnit = req.CorrelationChartInfo.LeadUnit
	correlationChart.CalculateValue = req.CorrelationChartInfo.CalculateValue
	correlationChart.CalculateUnit = req.CorrelationChartInfo.CalculateUnit
	correlationChart.StartDate = startDate
	correlationChart.EndDate = endDate
	correlationChart.EdbInfoIdFirst = req.CorrelationChartInfo.EdbInfoIdList[0].EdbInfoId
	correlationChart.EdbInfoIdSecond = req.CorrelationChartInfo.EdbInfoIdList[1].EdbInfoId

	// 滚动相关性会有日期等信息
	if chartItem.Source == utils.CHART_SOURCE_ROLLING_CORRELATION {
		correlationChart.DateType = req.CorrelationChartInfo.DateType
	}
	//correlationChart.PeriodData = string(periodDataByte)
	//correlationChart.CorrelationData = string(correlationDataByte)
	correlationChart.ModifyTime = time.Now().Local()
	//correlationUpdateCols := []string{"LeadValue", "LeadUnit", "StartDate", "EndDate", "EdbInfoIdFirst", "EdbInfoIdSecond", "PeriodData","CorrelationData", "ModifyTime"}
	correlationUpdateCols := []string{"LeadValue", "LeadUnit", "CalculateValue", "CalculateUnit", "DateType", "StartDate", "EndDate", "EdbInfoIdFirst", "EdbInfoIdSecond", "ModifyTime"}

	// 修改图表与指标mapping
	req.ChartType = 9
	err = data_manage.EditCorrelationChartInfoAndMapping(&req, edbInfoIdStr, "公历", 6, disableVal, ``,
		correlationChart, correlationUpdateCols)
	if err != nil {
		errMsg = "保存失败"
		err = errors.New("保存失败,Err:" + err.Error())
		return
	}

	resp := new(data_manage.AddChartInfoResp)
	resp.ChartInfoId = chartItem.ChartInfoId
	resp.UniqueCode = chartItem.UniqueCode
	resp.ChartType = req.ChartType

	// 添加指标引用记录
	_ = data.SaveChartEdbInfoRelation(edbInfoIdArr, chartItem)
	//添加es数据
	go data.EsAddOrEditChartInfo(chartItem.ChartInfoId)
	//修改my eta es数据
	go data.EsAddOrEditMyChartInfoByChartInfoId(chartItem.ChartInfoId)

	return
}

// CopyChartInfo 复制图表
func CopyChartInfo(configId, classifyId int, chartName string, correlationChartInfoReq data_manage.CorrelationChartInfoReq, oldChartInfo *data_manage.ChartInfo, sysUser *system.Admin, lang string) (chartInfo *data_manage.ChartInfo, err error, errMsg string, isSendEmail bool) {
	configSource := 2
	isSendEmail = true
	// 获取相关性图的配置
	multipleGraphConfigChartMapping, err := data_manage.GetMultipleGraphConfigChartMappingByIdAndSource(configId, configSource)
	if err != nil {
		return
	}
	multipleGraphConfig, err := data_manage.GetMultipleGraphConfigById(configId)
	if err != nil {
		return
	}
	multipleGraphConfig.MultipleGraphConfigId = 0
	err = data_manage.AddMultipleGraphConfig(multipleGraphConfig)
	if err != nil {
		return
	}

	// 添加图
	addChartReq := data_manage.AddChartInfoReq{
		ChartClassifyId:      classifyId,
		ChartName:            chartName,
		ChartType:            utils.CHART_TYPE_CURVE,
		Calendar:             "公历",
		CorrelationChartInfo: correlationChartInfoReq,
		ChartThemeId:         oldChartInfo.ChartThemeId,
		SourcesFrom:          oldChartInfo.SourcesFrom,
		Instructions:         oldChartInfo.Instructions,
		MarkersLines:         oldChartInfo.MarkersLines,
		MarkersAreas:         oldChartInfo.MarkersAreas,
	}
	chartSource := utils.CHART_SOURCE_CORRELATION // 默认是相关性图
	chartInfo, err, errMsg, isSendEmail = AddChartInfo(addChartReq, chartSource, sysUser, lang)
	if err != nil {
		return
	}

	// 添加关系
	multipleGraphConfigChartMapping = &data_manage.MultipleGraphConfigChartMapping{
		//Id:                    0,
		MultipleGraphConfigId: multipleGraphConfig.MultipleGraphConfigId,
		ChartInfoId:           chartInfo.ChartInfoId,
		Source:                configSource,
		ModifyTime:            time.Now(),
		CreateTime:            time.Now(),
	}
	err = data_manage.AddMultipleGraphConfigChartMapping(multipleGraphConfigChartMapping)
	if err != nil {
		return
	}

	//添加es数据
	go data.EsAddOrEditChartInfo(chartInfo.ChartInfoId)

	return
}

// CalculateCorrelation 计算相关性-获取x轴和y轴
func CalculateCorrelation(leadValue int, leadUnit, frequencyA, frequencyB string, dataListA, dataListB []*data_manage.EdbDataList) (xEdbIdValue []int, yDataList []data_manage.YData, err error) {
	xData := make([]int, 0)
	yData := make([]float64, 0)
	if leadValue == 0 {
		xData = append(xData, 0)
	}
	if leadValue > 0 {
		leadMin := 0 - leadValue
		xLen := 2*leadValue + 1
		for i := 0; i < xLen; i++ {
			n := leadMin + i
			xData = append(xData, n)
		}
	}

	// 计算窗口，不包含第一天
	//startDateTime, _ := time.ParseInLocation(utils.FormatDate, startDate, time.Local)
	//startDate = startDateTime.AddDate(0, 0, 1).Format(utils.FormatDate)

	//// 2023-03-02 时间序列始终以指标B为基准, 始终是A进行平移
	//baseEdbInfo := edbInfoMappingB
	//changeEdbInfo := edbInfoMappingA
	// 2023-03-17 时间序列始终以指标A为基准, 始终是B进行平移
	//baseEdbInfo := edbInfoMappingA
	//changeEdbInfo := edbInfoMappingB

	// 获取时间基准指标在时间区间内的值
	//aDataList := make([]*data_manage.EdbDataList, 0)
	//switch baseEdbInfo.EdbInfoCategoryType {
	//case 0:
	//	aDataList, err = data_manage.GetEdbDataList(baseEdbInfo.Source, baseEdbInfo.SubSource, baseEdbInfo.EdbInfoId, startDate, endDate)
	//case 1:
	//	_, aDataList, _, _, err, _ = data.GetPredictDataListByPredictEdbInfoId(baseEdbInfo.EdbInfoId, startDate, endDate, false)
	//default:
	//	err = errors.New("指标base类型异常")
	//	return
	//}
	//
	//// 获取变频指标所有日期的值, 插值法完善数据
	//bDataList := make([]*data_manage.EdbDataList, 0)
	//switch changeEdbInfo.EdbInfoCategoryType {
	//case 0:
	//	bDataList, err = data_manage.GetEdbDataList(changeEdbInfo.Source, changeEdbInfo.SubSource, changeEdbInfo.EdbInfoId, "", "")
	//case 1:
	//	_, bDataList, _, _, err, _ = data.GetPredictDataListByPredictEdbInfoId(changeEdbInfo.EdbInfoId, "", "", false)
	//default:
	//	err = errors.New("指标change类型异常")
	//	return
	//}
	//changeDataMap := make(map[string]float64)
	//newChangeDataList, e := HandleDataByLinearRegression(bDataList, changeDataMap)
	//if e != nil {
	//	err = fmt.Errorf("获取变频指标插值法Map失败, Err: %s", e.Error())
	//	return
	//}

	// 2023-03-17 时间序列始终以指标A为基准, 始终是B进行平移
	baseDataList := make([]*data_manage.EdbDataList, 0)
	baseDataMap := make(map[string]float64)
	changeDataList := make([]*data_manage.EdbDataList, 0)
	changeDataMap := make(map[string]float64)

	// 先把低频指标升频为高频
	{
		frequencyIntMap := map[string]int{
			"日度": 1,
			"周度": 2,
			"旬度": 3,
			"月度": 4,
			"季度": 5,
			"年度": 6,
		}

		// 如果A指标是高频，那么就需要对B指标进行升频
		if frequencyIntMap[frequencyA] < frequencyIntMap[frequencyB] {
			tmpNewChangeDataList, e := HandleDataByLinearRegression(dataListB, changeDataMap)
			if e != nil {
				err = fmt.Errorf("获取变频指标插值法Map失败, Err: %s", e.Error())
				return
			}
			changeDataList = tmpNewChangeDataList
			baseDataList = dataListA
			for _, v := range baseDataList {
				baseDataMap[v.DataTime] = v.Value
			}

		} else if frequencyIntMap[frequencyA] > frequencyIntMap[frequencyB] {
			// 如果B指标是高频，那么就需要对A指标进行升频
			tmpNewChangeDataList, e := HandleDataByLinearRegression(dataListA, baseDataMap)
			if e != nil {
				err = fmt.Errorf("获取变频指标插值法Map失败, Err: %s", e.Error())
				return
			}
			baseDataList = tmpNewChangeDataList

			changeDataList = dataListB
			for _, v := range changeDataList {
				changeDataMap[v.DataTime] = v.Value
			}
		} else {
			baseDataList = dataListA
			for _, v := range baseDataList {
				baseDataMap[v.DataTime] = v.Value
			}
			changeDataList = dataListB
			for _, v := range changeDataList {
				changeDataMap[v.DataTime] = v.Value
			}
		}

	}

	// 计算不领先也不滞后时的相关系数
	baseCalculateData := make([]float64, 0)
	baseDataTimeArr := make([]string, 0)
	for i := range baseDataList {
		baseDataTimeArr = append(baseDataTimeArr, baseDataList[i].DataTime)
		baseCalculateData = append(baseCalculateData, baseDataList[i].Value)
	}

	//zeroBaseData := make([]float64, 0)
	//zeroCalculateData := make([]float64, 0)
	//for i := range baseDataTimeArr {
	//	tmpBaseVal, ok1 := baseDataMap[baseDataTimeArr[i]]
	//	tmpCalculateVal, ok2 := changeDataMap[baseDataTimeArr[i]]
	//	if ok1 && ok2 {
	//		zeroBaseData = append(zeroBaseData, tmpBaseVal)
	//		zeroCalculateData = append(zeroCalculateData, tmpCalculateVal)
	//	}
	//}
	//if len(zeroBaseData) != len(zeroCalculateData) {
	//	err = fmt.Errorf("相关系数两组序列元素数不一致, %d-%d", len(baseCalculateData), len(zeroCalculateData))
	//	return
	//}
	//zeroRatio := utils.CalculateCorrelationByIntArr(zeroBaseData, zeroCalculateData)
	//if leadValue == 0 {
	//	yData = append(yData, zeroRatio)
	//}

	// 计算领先/滞后N期
	if leadValue > 0 {
		// 平移变频指标领先/滞后的日期(单位天)
		moveUnitDays := utils.FrequencyDaysMap[leadUnit]

		for i := range xData {
			//if xData[i] == 0 {
			//	yData = append(yData, zeroRatio)
			//	continue
			//}
			xCalculateData := make([]float64, 0)
			yCalculateData := make([]float64, 0)

			// 平移指定天数
			mDays := int(moveUnitDays) * xData[i]
			_, dMap := MoveDataDaysToNewDataList(changeDataList, mDays)

			// 取出对应的基准日期的值
			for i2 := range baseDataTimeArr {
				tmpDate := baseDataTimeArr[i2]
				if yVal, ok := dMap[tmpDate]; ok {
					xCalculateData = append(xCalculateData, baseCalculateData[i2])
					yCalculateData = append(yCalculateData, yVal)
				}
			}
			if len(yCalculateData) <= 0 {
				//err = fmt.Errorf("领先滞后相关系数两组序列元素数不一致, %d-%d", len(baseCalculateData), len(yCalculateData))
				//return
				// 领先滞后后，没有可以计算的数据了
				continue
			}

			// 公式计算出领先/滞后频度对应点的相关性系数
			ratio := utils.CalculateCorrelationByIntArr(xCalculateData, yCalculateData)
			yData = append(yData, ratio)
		}
	}

	xEdbIdValue = xData
	yDataList = make([]data_manage.YData, 0)
	yDate := "0000-00-00"
	yDataList = append(yDataList, data_manage.YData{
		Date:  yDate,
		Value: yData,
	})
	return
}

// GetFactorChartDataByChartId 获取多因子相关性图表数据
func GetFactorChartDataByChartId(chartInfoId int, extraConfig string) (xEdbIdValue []int, yDataList []data_manage.YData, err error) {
	if chartInfoId <= 0 {
		return
	}
	// 指标对应的图例
	extra := new(data_manage.CorrelationChartInfoExtraConfig)
	if extraConfig != "" {
		if e := json.Unmarshal([]byte(extraConfig), extra); e != nil {
			err = fmt.Errorf("解析图表额外配置失败, err: %v", e)
			return
		}
	}
	legends := make(map[string]*data_manage.CorrelationChartLegend)
	if extra != nil {
		for _, v := range extra.LegendConfig {
			s := fmt.Sprintf("%d-%d", v.SeriesId, v.EdbInfoId)
			legends[s] = v
		}
	}

	// 获取图表引用到的系列指标
	chartMappingOb := new(data_manage.FactorEdbSeriesChartMapping)
	cond := fmt.Sprintf(" AND %s = ? AND %s = 1", chartMappingOb.Cols().ChartInfoId, chartMappingOb.Cols().EdbUsed)
	pars := make([]interface{}, 0)
	pars = append(pars, chartInfoId)
	chartMappings, e := chartMappingOb.GetItemsByCondition(cond, pars, []string{}, "")
	if e != nil {
		err = fmt.Errorf("获取图表引用系列指标失败")
		return
	}

	// 取出计算结果
	yDataList = make([]data_manage.YData, 0)
	yDate := "0000-00-00"
	for k, m := range chartMappings {
		var values []data_manage.FactorEdbSeriesCorrelationMatrixValues
		if m.CalculateData != "" {
			e = json.Unmarshal([]byte(m.CalculateData), &values)
			if e != nil {
				err = fmt.Errorf("系列指标计算数据有误, err: %v", e)
				return
			}
		}
		var y []float64
		for _, v := range values {
			if k == 0 {
				xEdbIdValue = append(xEdbIdValue, v.XData)
			}
			y = append(y, v.YData)
		}
		var yData data_manage.YData
		yData.Date = yDate
		yData.Value = y
		yData.SeriesEdb.SeriesId = m.FactorEdbSeriesId
		yData.SeriesEdb.EdbInfoId = m.EdbInfoId

		// 图例
		s := fmt.Sprintf("%d-%d", m.FactorEdbSeriesId, m.EdbInfoId)
		legend := legends[s]
		if legend != nil {
			yData.Name = legend.LegendName
			yData.Color = legend.Color
		}
		yDataList = append(yDataList, yData)
	}
	return
}

// RemoveCorrelationRelate 删除相关性图表关联信息
func RemoveCorrelationRelate(chartInfoId int) (err error) {
	if chartInfoId <= 0 {
		return
	}
	// 相关性图表
	chartCorrelate := new(data_manage.ChartInfoCorrelation)
	if e := chartCorrelate.GetItemById(chartInfoId); e != nil && e.Error() != utils.ErrNoRow() {
		err = fmt.Errorf("获取相关性图表信息失败, %v", e)
		return
	}
	if chartCorrelate == nil {
		return
	}

	// 删除相关性图
	if e := chartCorrelate.Delete(); e != nil {
		err = fmt.Errorf("删除相关性图表失败, %v", e)
		return
	}

	// 多因子
	if chartCorrelate.AnalysisMode != 1 {
		return
	}
	seriesIds := make([]int, 0)

	// 删除图表关联
	chartMappingOb := new(data_manage.FactorEdbSeriesChartMapping)
	{
		cond := fmt.Sprintf(" AND %s = ?", chartMappingOb.Cols().ChartInfoId)
		pars := make([]interface{}, 0)
		pars = append(pars, chartCorrelate.CorrelationChartInfoId)
		items, e := chartMappingOb.GetItemsByCondition(cond, pars, []string{}, "")
		if e != nil {
			err = fmt.Errorf("获取图表关联指标系列失败, %v", e)
			return
		}
		for _, v := range items {
			if !utils.InArrayByInt(seriesIds, v.FactorEdbSeriesId) {
				seriesIds = append(seriesIds, v.FactorEdbSeriesId)
			}
		}
		removeCond := fmt.Sprintf(" %s = ?", chartMappingOb.Cols().ChartInfoId)
		if e = chartMappingOb.RemoveByCondition(removeCond, pars); e != nil {
			err = fmt.Errorf("删除图表关联指标系列失败, %v", e)
			return
		}
	}

	// 删除系列
	if len(seriesIds) == 0 {
		return
	}
	seriesOb := new(data_manage.FactorEdbSeries)
	if e := seriesOb.MultiRemove(seriesIds); e != nil {
		err = fmt.Errorf("删除系列失败, %v", e)
		return
	}

	edbMappingOb := new(data_manage.FactorEdbSeriesMapping)
	{
		cond := fmt.Sprintf(" %s IN (%s)", edbMappingOb.Cols().FactorEdbSeriesId, utils.GetOrmInReplace(len(seriesIds)))
		pars := make([]interface{}, 0)
		pars = append(pars, seriesIds)
		if e := edbMappingOb.RemoveByCondition(cond, pars); e != nil {
			err = fmt.Errorf("删除系列指标失败, %v", e)
			return
		}
	}
	calculateOb := new(data_manage.FactorEdbSeriesCalculateData)
	{
		cond := fmt.Sprintf(" %s IN (%s)", calculateOb.Cols().FactorEdbSeriesId, utils.GetOrmInReplace(len(seriesIds)))
		pars := make([]interface{}, 0)
		pars = append(pars, seriesIds)
		if e := calculateOb.RemoveByCondition(cond, pars); e != nil {
			err = fmt.Errorf("删除系列指标计算失败, %v", e)
			return
		}
	}
	return
}

// CalculateCorrelationMatrix 计算相关性矩阵
func CalculateCorrelationMatrix(req data_manage.CalculateCorrelationMatrixPars) (resp data_manage.FactorEdbSeriesCorrelationMatrixResp, chartMappings []*data_manage.FactorEdbSeriesChartMapping, err error) {
	if req.BaseEdbInfoId <= 0 {
		err = fmt.Errorf("请选择标的指标")
		return
	}
	if len(req.SeriesIds) == 0 {
		err = fmt.Errorf("请选择因子指标系列")
		return
	}
	if req.Correlation.LeadValue <= 0 {
		err = fmt.Errorf("分析周期不允许设置为负数或0")
		return
	}
	if req.Correlation.LeadUnit == "" {
		err = fmt.Errorf("请选择分析周期频度")
		return
	}
	leadUnitDays, ok := utils.FrequencyDaysMap[req.Correlation.LeadUnit]
	if !ok {
		err = fmt.Errorf("错误的分析周期频度: %s", req.Correlation.LeadUnit)
		return
	}

	if req.Correlation.CalculateUnit == "" {
		err = fmt.Errorf("请选择计算窗口频度")
		return
	}
	calculateUnitDays, ok := utils.FrequencyDaysMap[req.Correlation.CalculateUnit]
	if !ok {
		err = fmt.Errorf("计算窗口频度有误: %s", req.Correlation.CalculateUnit)
		return
	}
	leadDays := 2 * req.Correlation.LeadValue * leadUnitDays
	calculateDays := req.Correlation.CalculateValue * calculateUnitDays
	if calculateDays < leadDays {
		err = fmt.Errorf("计算窗口必须≥2*分析周期")
		return
	}

	// 获取标的指标信息及数据
	baseEdb, e := data_manage.GetEdbInfoById(req.BaseEdbInfoId)
	if e != nil {
		err = fmt.Errorf("获取标的指标失败, %v", e)
		return
	}
	dataListA := make([]*data_manage.EdbDataList, 0)
	{
		// 标的指标数据日期区间
		startDate := time.Now().AddDate(0, 0, -calculateDays).Format(utils.FormatDate)
		endDate := time.Now().Format(utils.FormatDate)
		startDateTime, _ := time.ParseInLocation(utils.FormatDate, startDate, time.Local)
		startDate = startDateTime.AddDate(0, 0, 1).Format(utils.FormatDate) // 不包含第一天
		switch baseEdb.EdbInfoType {
		case 0:
			dataListA, e = data_manage.GetEdbDataList(baseEdb.Source, baseEdb.SubSource, baseEdb.EdbInfoId, startDate, endDate)
		case 1:
			_, dataListA, _, _, e, _ = data.GetPredictDataListByPredictEdbInfoId(baseEdb.EdbInfoId, startDate, endDate, false)
		default:
			err = fmt.Errorf("标的指标类型异常: %d", baseEdb.EdbInfoType)
			return
		}
		if e != nil {
			err = fmt.Errorf("获取标的指标数据失败, %v", e)
			return
		}
	}

	// 获取因子系列
	seriesIdItem := make(map[int]*data_manage.FactorEdbSeries)
	{
		ob := new(data_manage.FactorEdbSeries)
		cond := fmt.Sprintf(" AND %s IN (%s)", ob.Cols().PrimaryId, utils.GetOrmInReplace(len(req.SeriesIds)))
		pars := make([]interface{}, 0)
		pars = append(pars, req.SeriesIds)
		items, e := ob.GetItemsByCondition(cond, pars, []string{}, fmt.Sprintf("%s ASC", ob.Cols().PrimaryId))
		if e != nil {
			err = fmt.Errorf("获取因子指标系列失败, %v", e)
			return
		}
		for _, v := range items {
			seriesIdItem[v.FactorEdbSeriesId] = v
		}
	}

	// 获取因子指标
	edbMappings := make([]*data_manage.FactorEdbSeriesMapping, 0)
	edbInfoIds := make([]int, 0)
	{
		ob := new(data_manage.FactorEdbSeriesMapping)
		cond := fmt.Sprintf(" AND %s IN (%s)", ob.Cols().FactorEdbSeriesId, utils.GetOrmInReplace(len(req.SeriesIds)))
		pars := make([]interface{}, 0)
		pars = append(pars, req.SeriesIds)
		order := fmt.Sprintf("%s ASC, %s ASC", ob.Cols().FactorEdbSeriesId, ob.Cols().EdbInfoId)
		items, e := ob.GetItemsByCondition(cond, pars, []string{}, order)
		if e != nil {
			err = fmt.Errorf("获取系列指标失败, %v", e)
			return
		}
		for _, v := range items {
			edbInfoIds = append(edbInfoIds, v.EdbInfoId)
		}
		edbMappings = items
	}
	edbIdItem := make(map[int]*data_manage.EdbInfo)
	edbItems, e := data_manage.GetEdbInfoByIdList(edbInfoIds)
	if e != nil {
		err = fmt.Errorf("获取因子指标信息失败, %v", e)
		return
	}
	for _, v := range edbItems {
		edbIdItem[v.EdbInfoId] = v
	}

	calculateDataOb := new(data_manage.FactorEdbSeriesCalculateData)

	calculateWorkers := make(chan struct{}, 10)
	wg := sync.WaitGroup{}
	edbExists := make(map[string]bool)
	chartKeyMap := make(map[string]*data_manage.FactorEdbSeriesChartMapping)
	for _, v := range edbMappings {
		existsKey := fmt.Sprintf("%d-%d", v.FactorEdbSeriesId, v.EdbInfoId)
		if edbExists[existsKey] {
			continue
		}
		edbExists[existsKey] = true

		edbItem := edbIdItem[v.EdbInfoId]
		if edbItem == nil {
			continue
		}
		seriesItem := seriesIdItem[v.FactorEdbSeriesId]
		if seriesItem == nil {
			continue
		}

		wg.Add(1)
		go func(mapping *data_manage.FactorEdbSeriesMapping, edb *data_manage.EdbInfo, series *data_manage.FactorEdbSeries) {
			defer func() {
				wg.Done()
				<-calculateWorkers
			}()
			calculateWorkers <- struct{}{}

			var item data_manage.FactorEdbSeriesCorrelationMatrixItem
			item.SeriesId = series.FactorEdbSeriesId
			item.EdbInfoId = edb.EdbInfoId
			item.EdbCode = edb.EdbCode
			item.EdbName = edb.EdbName

			// 指标来源
			edbList := make([]*data_manage.ChartEdbInfoMapping, 0)
			edbList = append(edbList, &data_manage.ChartEdbInfoMapping{
				EdbInfoId:           edb.EdbInfoId,
				EdbInfoCategoryType: edb.EdbInfoType,
				EdbType:             edb.EdbType,
				Source:              edb.Source,
				SourceName:          edb.SourceName,
			})
			sourceNameList, sourceNameEnList := data.GetEdbSourceByEdbInfoIdList(edbList)
			item.SourceName = strings.Join(sourceNameList, ",")
			item.SourceNameEn = strings.Join(sourceNameEnList, ",")

			// 获取指标数据
			dataListB := make([]*data_manage.EdbDataList, 0)
			if series.CalculateState == data_manage.FactorEdbSeriesCalculated {
				cond := fmt.Sprintf(" AND %s = ? AND %s = ?", calculateDataOb.Cols().FactorEdbSeriesId, calculateDataOb.Cols().EdbInfoId)
				pars := make([]interface{}, 0)
				pars = append(pars, mapping.FactorEdbSeriesId, mapping.EdbInfoId)
				dataItems, e := calculateDataOb.GetItemsByCondition(cond, pars, []string{calculateDataOb.Cols().DataTime, calculateDataOb.Cols().Value}, fmt.Sprintf("%s ASC", calculateDataOb.Cols().DataTime))
				if e != nil {
					item.Msg = fmt.Sprintf("计算失败")
					item.ErrMsg = fmt.Sprintf("获取计算数据失败, err: %v", e)
					resp.Fail = append(resp.Fail, item)
					return
				}
				dataListB = data_manage.TransEdbSeriesCalculateData2EdbDataList(dataItems)
			} else {
				switch edb.EdbInfoType {
				case 0:
					dataListB, e = data_manage.GetEdbDataList(edb.Source, edb.SubSource, edb.EdbInfoId, "", "")
				case 1:
					_, dataListB, _, _, e, _ = data.GetPredictDataListByPredictEdbInfoId(edb.EdbInfoId, "", "", false)
				default:
					item.Msg = fmt.Sprintf("计算失败")
					item.ErrMsg = fmt.Sprintf("指标类型异常, edbType: %d", edb.EdbInfoType)
					resp.Fail = append(resp.Fail, item)
					return
				}
			}

			// 计算相关性
			xEdbIdValue, yDataList, e := CalculateCorrelation(req.Correlation.LeadValue, req.Correlation.LeadUnit, baseEdb.Frequency, edb.Frequency, dataListA, dataListB)
			if e != nil {
				item.Msg = fmt.Sprintf("计算失败")
				item.ErrMsg = fmt.Sprintf("相关性计算失败, err: %v", e)
				resp.Fail = append(resp.Fail, item)
				return
			}

			// X及Y轴数据
			yData := yDataList[0].Value
			yLen := len(yData)
			values := make([]data_manage.FactorEdbSeriesCorrelationMatrixValues, len(xEdbIdValue))
			for k, x := range xEdbIdValue {
				var y float64
				if k >= 0 && k < yLen {
					y = yData[k]
				}
				y = utils.SubFloatToFloat(y, 2)
				values[k] = data_manage.FactorEdbSeriesCorrelationMatrixValues{
					XData: x, YData: y,
				}
			}

			// 图表关联
			newMapping := new(data_manage.FactorEdbSeriesChartMapping)
			newMapping.CalculateType = data_manage.FactorEdbSeriesChartCalculateTypeCorrelation

			// 计算参数
			var calculatePars data_manage.FactorEdbSeriesChartCalculateCorrelationReq
			calculatePars.BaseEdbInfoId = req.BaseEdbInfoId
			calculatePars.LeadValue = req.Correlation.LeadValue
			calculatePars.LeadUnit = req.Correlation.LeadUnit
			calculatePars.CalculateValue = req.Correlation.CalculateValue
			calculatePars.CalculateUnit = req.Correlation.CalculateUnit
			bc, e := json.Marshal(calculatePars)
			if e != nil {
				item.Msg = fmt.Sprintf("计算失败")
				item.ErrMsg = fmt.Sprintf("计算参数JSON格式化失败, err: %v", e)
				resp.Fail = append(resp.Fail, item)
				return
			}
			newMapping.CalculatePars = string(bc)

			// 计算结果, 注此处保存的是排序前的顺序
			bv, e := json.Marshal(values)
			if e != nil {
				item.Msg = fmt.Sprintf("计算失败")
				item.ErrMsg = fmt.Sprintf("计算结果JSON格式化失败, err: %v", e)
				resp.Fail = append(resp.Fail, item)
				return
			}
			newMapping.CalculateData = string(bv)
			newMapping.FactorEdbSeriesId = mapping.FactorEdbSeriesId
			newMapping.EdbInfoId = mapping.EdbInfoId
			newMapping.CreateTime = time.Now().Local()
			newMapping.ModifyTime = time.Now().Local()
			chartKeyMap[existsKey] = newMapping

			// 按照固定规则排期数[0 1 2 3 -1 -2 -3], 仅矩阵展示为此顺序
			sort.Sort(data_manage.FactorEdbSeriesCorrelationMatrixOrder(values))
			item.Msg = "计算成功"
			item.Values = values
			resp.Success = append(resp.Success, item)
		}(v, edbItem, seriesItem)
	}
	wg.Wait()

	// 新增图表关联, 此处按照顺序添加
	chartMappings = make([]*data_manage.FactorEdbSeriesChartMapping, 0)
	for _, v := range edbMappings {
		k := fmt.Sprintf("%d-%d", v.FactorEdbSeriesId, v.EdbInfoId)
		item := chartKeyMap[k]
		if item == nil {
			continue
		}
		chartMappings = append(chartMappings, item)
	}
	return
}