Merge branch 'feature/eta_1.6.3' into custom

controllers/base_from_calculate.go

@@ -2302,3 +2302,119 @@ func (this *CalculateController) BatchEditMulti() {
 	br.Data = resp
 	br.IsAddLog = true
 }
+
+// StepCalculate
+// @Title 多步骤计算
+// @Description 多步骤计算
+// @Param request body models.StepCalculateBySearchData true "type json string"
+// @Success Ret=200 返回指标id
+// @router /base/step_calculate [post]
+func (this *CalculateController) StepCalculate() {
+	br := new(models.BaseResponse).Init()
+	defer func() {
+		if br.ErrMsg == "" {
+			br.IsSendEmail = false
+		}
+		this.Data["json"] = br
+		this.ServeJSON()
+	}()
+	var req models.StepCalculateBySearchData
+	if e := json.Unmarshal(this.Ctx.Input.RequestBody, &req); e != nil {
+		br.Msg = "参数解析异常"
+		br.ErrMsg = fmt.Sprintf("参数解析失败, Err: %v", e)
+		return
+	}
+	//sort.Slice(req.Calculates, func(i, j int) bool {
+	//	return req.Calculates[i].Sort < req.Calculates[j].Sort
+	//})
+	//
+	//var errMsg string
+	//originData, e := models.EdbInfoSearchDataToData(req.DataList)
+	//if e != nil {
+	//	br.Msg = "基础数据异常"
+	//	br.ErrMsg = fmt.Sprintf("计算失败, 基础数据异常, Err: %v", e)
+	//	return
+	//}
+	//
+	//calculateData := originData
+	//dateDataMap := make(map[time.Time]float64)
+	//for _, v := range req.Calculates {
+	//	baseCalculate := models.BaseCalculate{
+	//		DataList:      calculateData,
+	//		Frequency:     v.Frequency,
+	//		Formula:       v.Formula,
+	//		Calendar:      v.Calendar,
+	//		MoveType:      v.MoveType,
+	//		MoveFrequency: v.MoveFrequency,
+	//		FromFrequency: v.FromFrequency,
+	//		Source:        v.Source,
+	//	}
+	//
+	//	// 计算方式
+	//	switch baseCalculate.Source {
+	//	case utils.EdbBaseCalculateLjzzy:
+	//		dateDataMap, e, errMsg = baseCalculate.Ljzzy()
+	//	case utils.EdbBaseCalculateLjzzj:
+	//		dateDataMap, e, errMsg = baseCalculate.Ljzzj()
+	//	case utils.EdbBaseCalculateTbz:
+	//		dateDataMap, e, errMsg = baseCalculate.Tbz()
+	//	case utils.EdbBaseCalculateTcz:
+	//		dateDataMap, e, errMsg = baseCalculate.Tcz()
+	//	case utils.EdbBaseCalculateNszydpjjs:
+	//		dateDataMap, e, errMsg = baseCalculate.Nszydpjjs()
+	//	case utils.EdbBaseCalculateHbz:
+	//		dateDataMap, e, errMsg = baseCalculate.Hbz()
+	//	case utils.EdbBaseCalculateHcz:
+	//		dateDataMap, e, errMsg = baseCalculate.Hcz()
+	//	case utils.EdbBaseCalculateUpFrequency:
+	//		dateDataMap, e, errMsg = baseCalculate.UpFrequency()
+	//	case utils.EdbBaseCalculateDownFrequency:
+	//		dateDataMap, e, errMsg = baseCalculate.DownFrequency()
+	//	case utils.EdbBaseCalculateTimeShift:
+	//		dateDataMap, e, errMsg = baseCalculate.TimeShift()
+	//	case utils.EdbBaseCalculateCjjx:
+	//		dateDataMap, e, errMsg = baseCalculate.Cjjx()
+	//	case utils.EdbBaseCalculateAnnualized:
+	//		dateDataMap, e, errMsg = baseCalculate.Annualized()
+	//	case utils.EdbBaseCalculateLjz:
+	//		dateDataMap, e, errMsg = baseCalculate.Ljz()
+	//	case utils.EdbBaseCalculateLjzNczj:
+	//		dateDataMap, e, errMsg = baseCalculate.LjzNczj()
+	//	case utils.EdbBaseCalculateExponentialSmoothing:
+	//		dateDataMap, e, errMsg = baseCalculate.ExponentialSmoothing()
+	//	case utils.EdbBaseCalculateRjz:
+	//		dateDataMap, e, errMsg = baseCalculate.Rjz()
+	//	default:
+	//		errMsg = "计算方式无效"
+	//		e = fmt.Errorf("%s:%d", errMsg, baseCalculate.Source)
+	//	}
+	//	if e != nil {
+	//		br.Msg = "计算失败"
+	//		if errMsg != "" {
+	//			br.Msg = errMsg
+	//		}
+	//		br.ErrMsg = e.Error()
+	//		return
+	//	}
+	//
+	//	calculateData = models.TransDateData2EdbData(dateDataMap)
+	//}
+	resultData, dates, errMsg, e := services.StepCalculate(req.DataList, req.Calculates)
+	if e != nil {
+		br.Msg = "计算失败"
+		if errMsg != "" {
+			br.Msg = errMsg
+		}
+		br.ErrMsg = fmt.Sprintf("分步骤计算失败, Err: %v", e)
+		return
+	}
+
+	br.Ret = 200
+	br.Success = true
+	br.Msg = "计算成功"
+	br.Data = models.BaseCalculateResp{
+		DataMap:  resultData,
+		DateList: dates,
+	}
+	br.IsAddLog = true
+}

controllers/factor_edb_series/factor_edb_series.go

@@ -0,0 +1,416 @@
+package factor_edb_series
+
+import (
+	"encoding/json"
+	"eta/eta_index_lib/controllers"
+	"eta/eta_index_lib/logic"
+	"eta/eta_index_lib/models"
+	"eta/eta_index_lib/services"
+	"eta/eta_index_lib/utils"
+	"fmt"
+	"strconv"
+	"sync"
+	"time"
+)
+
+// FactorEdbSeriesController 因子指标系列
+type FactorEdbSeriesController struct {
+	controllers.BaseAuthController
+}
+
+// Recalculate
+// @Title 因子指标系列-重计算
+// @Description 因子指标系列-重计算
+// @Success 200 {object} models.FactorEdbRecalculateReq
+// @router /recalculate [post]
+func (this *FactorEdbSeriesController) Recalculate() {
+	br := new(models.BaseResponse).Init()
+	defer func() {
+		if br.ErrMsg == "" {
+			br.IsSendEmail = false
+		}
+		this.Data["json"] = br
+		this.ServeJSON()
+	}()
+	var req models.FactorEdbRecalculateReq
+	if e := json.Unmarshal(this.Ctx.Input.RequestBody, &req); e != nil {
+		br.Msg = "参数解析异常！"
+		br.ErrMsg = fmt.Sprintf("参数解析失败, Err: %v", e)
+		return
+	}
+	if req.EdbInfoId <= 0 {
+		br.Msg = "参数有误"
+		br.ErrMsg = fmt.Sprintf("指标ID有误, EdbInfoId: %d", req.EdbInfoId)
+		return
+	}
+
+	cacheKey := utils.CACHE_EDB_DATA_REFRESH + "_factor_edb_recalculate_" + req.EdbCode
+	if utils.Rc.IsExist(cacheKey) {
+		br.Ret = 501
+		br.Success = true
+		br.Msg = fmt.Sprintf("系统处理中, 请稍后重试, 指标编码: %s", req.EdbCode)
+		return
+	}
+	utils.Rc.SetNX(cacheKey, 1, 10*time.Minute)
+	defer func() {
+		_ = utils.Rc.Delete(cacheKey)
+	}()
+
+	// 获取指标信息
+	edbInfo, e := models.GetEdbInfoById(req.EdbInfoId)
+	if e != nil {
+		if e.Error() == utils.ErrNoRow() {
+			br.Msg = "指标不存在"
+			br.ErrMsg = fmt.Sprintf("指标不存在, EdbInfoId: %d, EdbCode: %s", req.EdbInfoId, req.EdbCode)
+			return
+		}
+		br.Msg = "操作失败"
+		br.ErrMsg = fmt.Sprintf("获取指标信息失败, Err: %v", e)
+		return
+	}
+
+	// 查询指标关联的系列
+	mappings := make([]*models.FactorEdbSeriesMapping, 0)
+	{
+		ob := new(models.FactorEdbSeriesMapping)
+		cond := fmt.Sprintf(" AND %s = ?", ob.Cols().EdbInfoId)
+		pars := make([]interface{}, 0)
+		pars = append(pars, req.EdbInfoId)
+		fields := []string{ob.Cols().FactorEdbSeriesId, ob.Cols().EdbInfoId, ob.Cols().EdbCode}
+		list, e := ob.GetItemsByCondition(cond, pars, fields, "")
+		if e != nil {
+			br.Msg = "操作失败"
+			br.ErrMsg = fmt.Sprintf("获取指标系列关联失败, Err: %v", e)
+			return
+		}
+		mappings = list
+	}
+	if len(mappings) == 0 {
+		br.Ret = 200
+		br.Success = true
+		br.Msg = "操作成功"
+		return
+	}
+
+	// 获取系列信息
+	seriesIds := make([]int, 0)
+	seriesExist := make(map[int]bool)
+	for _, v := range mappings {
+		if !seriesExist[v.FactorEdbSeriesId] {
+			seriesExist[v.FactorEdbSeriesId] = true
+			seriesIds = append(seriesIds, v.FactorEdbSeriesId)
+		}
+	}
+	if len(seriesIds) == 0 {
+		br.Ret = 200
+		br.Success = true
+		br.Msg = "操作成功"
+		return
+	}
+	seriesMap := make(map[int]*models.FactorEdbSeries, 0)
+	{
+		ob := new(models.FactorEdbSeries)
+		cond := fmt.Sprintf(" AND %s IN (%s)", ob.Cols().PrimaryId, utils.GetOrmInReplace(len(seriesIds)))
+		pars := make([]interface{}, 0)
+		pars = append(pars, seriesIds)
+		fields := []string{ob.Cols().PrimaryId, ob.Cols().EdbInfoType, ob.Cols().CalculateStep, ob.Cols().CalculateState}
+		list, e := ob.GetItemsByCondition(cond, pars, fields, "")
+		if e != nil {
+			br.Msg = "操作失败"
+			br.ErrMsg = fmt.Sprintf("获取指标系列失败, Err: %v", e)
+			return
+		}
+		for _, v := range list {
+			seriesMap[v.FactorEdbSeriesId] = v
+		}
+	}
+
+	// 获取指标原数据
+	edbData, e := models.GetEdbDataAllByEdbCode(edbInfo.EdbCode, edbInfo.Source, edbInfo.SubSource, 0)
+	if e != nil {
+		br.Msg = "操作失败"
+		br.ErrMsg = fmt.Sprintf("获取指标数据失败, EdbCode: %s, Err: %v", edbInfo.EdbCode, e)
+		return
+	}
+	if len(edbData) == 0 {
+		br.Msg = "指标无数据"
+		br.ErrMsg = fmt.Sprintf("指标无数据, EdbCode: %s", edbInfo.EdbCode)
+		return
+	}
+
+	for _, v := range mappings {
+		series := seriesMap[v.FactorEdbSeriesId]
+		if series == nil {
+			continue
+		}
+		// 系列无计算则忽略
+		if series.CalculateState != models.FactorEdbSeriesCalculateNone || series.CalculateStep == "" {
+			continue
+		}
+		var calculates []models.CalculatesReq
+		if e = json.Unmarshal([]byte(series.CalculateStep), &calculates); e != nil {
+			br.Msg = "计算步骤异常"
+			br.ErrMsg = fmt.Sprintf("计算步骤异常, SeriesId: %d, Err: %v", series.FactorEdbSeriesId, e)
+			return
+		}
+
+		// 重新计算相关数据
+		e = services.FactorEdbStepCalculate(v.FactorEdbSeriesId, v.EdbInfoId, v.EdbCode, edbData, calculates)
+		if e != nil {
+			br.Msg = "因子指标计算失败"
+			br.ErrMsg = fmt.Sprintf("因子指标计算失败, SeriesId: %d, EdbCode: %s, Err: %v", v.FactorEdbSeriesId, v.EdbCode, e)
+			return
+		}
+	}
+
+	br.Ret = 200
+	br.Success = true
+	br.Msg = "操作成功"
+}
+
+// ChartRecalculate
+// @Title 图表数据-重计算
+// @Description 图表数据-重计算
+// @Success 200 {object} models.FactorEdbRecalculateReq
+// @router /chart_recalculate [post]
+func (this *FactorEdbSeriesController) ChartRecalculate() {
+	br := new(models.BaseResponse).Init()
+	defer func() {
+		if br.ErrMsg == "" {
+			br.IsSendEmail = false
+		}
+		this.Data["json"] = br
+		this.ServeJSON()
+	}()
+	var req models.FactorEdbChartRecalculateReq
+	if e := json.Unmarshal(this.Ctx.Input.RequestBody, &req); e != nil {
+		br.Msg = "参数解析异常！"
+		br.ErrMsg = fmt.Sprintf("参数解析失败, Err: %v", e)
+		return
+	}
+	if req.ChartInfoId <= 0 {
+		br.Msg = "参数有误"
+		br.ErrMsg = fmt.Sprintf("指标ID有误, ChartInfoId: %d", req.ChartInfoId)
+		return
+	}
+
+	cacheKey := utils.CACHE_CHART_INFO_DATA + "_factor_chart_recalculate_" + strconv.Itoa(req.ChartInfoId)
+	if utils.Rc.IsExist(cacheKey) {
+		br.Ret = 501
+		br.Success = true
+		br.Msg = fmt.Sprintf("系统处理中, 请稍后重试, 图表ID: %s", req.ChartInfoId)
+		return
+	}
+	utils.Rc.SetNX(cacheKey, 1, 10*time.Minute)
+	defer func() {
+		_ = utils.Rc.Delete(cacheKey)
+	}()
+
+	// 查询图表关联的系列指标
+	mappings := make([]*models.FactorEdbSeriesChartMapping, 0)
+	{
+		ob := new(models.FactorEdbSeriesChartMapping)
+		cond := fmt.Sprintf(" AND %s = ?", ob.Cols().ChartInfoId)
+		pars := make([]interface{}, 0)
+		pars = append(pars, req.ChartInfoId)
+		fields := []string{ob.Cols().PrimaryId, ob.Cols().CalculateType, ob.Cols().CalculatePars, ob.Cols().FactorEdbSeriesId, ob.Cols().EdbInfoId}
+		list, e := ob.GetItemsByCondition(cond, pars, fields, "")
+		if e != nil {
+			br.Msg = "操作失败"
+			br.ErrMsg = fmt.Sprintf("获取指标系列关联失败, Err: %v", e)
+			return
+		}
+		mappings = list
+	}
+	if len(mappings) == 0 {
+		br.Ret = 200
+		br.Success = true
+		br.Msg = "操作成功"
+		return
+	}
+	seriesIds := make([]int, 0)
+	edbInfoIds := make([]int, 0)
+	for _, v := range mappings {
+		seriesIds = append(seriesIds, v.FactorEdbSeriesId)
+		edbInfoIds = append(edbInfoIds, v.EdbInfoId)
+	}
+
+	// 获取因子指标及系列信息
+	seriesIdItem := make(map[int]*models.FactorEdbSeries)
+	{
+		ob := new(models.FactorEdbSeries)
+		cond := fmt.Sprintf(" AND %s IN (%s)", ob.Cols().PrimaryId, utils.GetOrmInReplace(len(seriesIds)))
+		pars := make([]interface{}, 0)
+		pars = append(pars, seriesIds)
+		items, e := ob.GetItemsByCondition(cond, pars, []string{}, fmt.Sprintf("%s ASC", ob.Cols().PrimaryId))
+		if e != nil {
+			br.Msg = "获取失败"
+			br.ErrMsg = "获取因子指标系列失败, Err: " + e.Error()
+			return
+		}
+		for _, v := range items {
+			seriesIdItem[v.FactorEdbSeriesId] = v
+		}
+	}
+	edbIdItem := make(map[int]*models.EdbInfo)
+	edbItems, e := models.GetEdbInfoByIdList(edbInfoIds)
+	if e != nil {
+		br.Msg = "获取失败"
+		br.ErrMsg = "获取因子指标失败, Err: " + e.Error()
+		return
+	}
+	for _, v := range edbItems {
+		edbIdItem[v.EdbInfoId] = v
+	}
+
+	// 重新计算
+	calculateWorkers := make(chan struct{}, 10)
+	wg := sync.WaitGroup{}
+	calculateDataOb := new(models.FactorEdbSeriesCalculateData)
+	for _, v := range mappings {
+		edbItem := edbIdItem[v.EdbInfoId]
+		if edbItem == nil {
+			continue
+		}
+		seriesItem := seriesIdItem[v.FactorEdbSeriesId]
+		if seriesItem == nil {
+			continue
+		}
+
+		wg.Add(1)
+		go func(chartMapping *models.FactorEdbSeriesChartMapping, edb *models.EdbInfo, series *models.FactorEdbSeries) {
+			defer func() {
+				wg.Done()
+				<-calculateWorkers
+			}()
+			calculateWorkers <- struct{}{}
+
+			// 相关性计算
+			if chartMapping.CalculateType == models.FactorEdbSeriesChartCalculateTypeCorrelation {
+				// 解析计算参数
+				if chartMapping.CalculatePars == "" {
+					utils.FileLog.Info(fmt.Sprintf("相关性-计算参数为空, MappingId: %d", chartMapping.FactorEdbSeriesChartMappingId))
+					return
+				}
+				var calculatePars models.FactorEdbSeriesChartCalculateCorrelationReq
+				if e := json.Unmarshal([]byte(chartMapping.CalculatePars), &calculatePars); e != nil {
+					utils.FileLog.Info(fmt.Sprintf("相关性-计算参数解析失败, MappingId: %d, err: %v", chartMapping.FactorEdbSeriesChartMappingId, e))
+					return
+				}
+
+				// 获取标的指标信息及数据
+				baseEdb, e := models.GetEdbInfoById(calculatePars.BaseEdbInfoId)
+				if e != nil {
+					utils.FileLog.Info(fmt.Sprintf("相关性-获取标的指标失败, MappingId: %d, err: %v", chartMapping.FactorEdbSeriesChartMappingId, e))
+					return
+				}
+				calculateUnitDays, ok := utils.FrequencyDaysMap[calculatePars.CalculateUnit]
+				if !ok {
+					utils.FileLog.Info(fmt.Sprintf("相关性-错误的计算窗口频度, MappingId: %d", chartMapping.FactorEdbSeriesChartMappingId))
+					return
+				}
+				calculateDays := calculatePars.CalculateValue * calculateUnitDays
+
+				dataListA := make([]*models.EdbInfoSearchData, 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:
+						list, e := models.GetEdbDataList(baseEdb.Source, baseEdb.SubSource, baseEdb.EdbInfoId, startDate, endDate)
+						if e != nil {
+							utils.FileLog.Info(fmt.Sprintf("相关性-获取标的指标数据失败, EdbInfoId: %d, err: %v", baseEdb.EdbInfoId, e))
+							return
+						}
+						dataListA = models.TransEdbInfoDataList2SearchData(list)
+					case 1:
+						dataListA, _, e, _ = models.GetPredictDataListByPredictEdbInfo(baseEdb, 1, startDate)
+						if e != nil {
+							utils.FileLog.Info(fmt.Sprintf("相关性-获取标的指标数据失败, EdbInfoId: %d, err: %v", baseEdb.EdbInfoId, e))
+							return
+						}
+					default:
+						utils.FileLog.Info(fmt.Sprintf("相关性-标的指标类型异常, EdbInfoId: %d", baseEdb.EdbInfoId))
+						return
+					}
+				}
+
+				// 获取指标数据
+				dataListB := make([]*models.EdbInfoSearchData, 0)
+				if series.CalculateState == models.FactorEdbSeriesCalculated {
+					cond := fmt.Sprintf(" AND %s = ? AND %s = ?", calculateDataOb.Cols().FactorEdbSeriesId, calculateDataOb.Cols().EdbInfoId)
+					pars := make([]interface{}, 0)
+					pars = append(pars, chartMapping.FactorEdbSeriesId, chartMapping.EdbInfoId)
+					dataItems, e := calculateDataOb.GetItemsByCondition(cond, pars, []string{calculateDataOb.Cols().DataTime, calculateDataOb.Cols().Value}, fmt.Sprintf("%s ASC", calculateDataOb.Cols().DataTime))
+					if e != nil {
+						utils.FileLog.Info(fmt.Sprintf("相关性-获取因子指标数据失败, MappingId: %d, err: %v", chartMapping.FactorEdbSeriesChartMappingId, e))
+						return
+					}
+					dataListB = models.TransEdbSeriesCalculateData2EdbDataList(dataItems)
+				} else {
+					switch edb.EdbInfoType {
+					case 0:
+						list, e := models.GetEdbDataList(edb.Source, edb.SubSource, edb.EdbInfoId, "", "")
+						if e != nil {
+							utils.FileLog.Info(fmt.Sprintf("相关性-获取因子指标数据失败, EdbInfoId: %d, err: %v", edb.EdbInfoId, e))
+							return
+						}
+						dataListB = models.TransEdbInfoDataList2SearchData(list)
+					case 1:
+						dataListB, e = models.GetPredictEdbDataListAll(baseEdb, 1)
+						if e != nil {
+							utils.FileLog.Info(fmt.Sprintf("相关性-获取因子指标数据失败, EdbInfoId: %d, err: %v", edb.EdbInfoId, e))
+							return
+						}
+					default:
+						utils.FileLog.Info(fmt.Sprintf("相关性-因子指标类型异常, EdbInfoId: %d", edb.EdbInfoId))
+						return
+					}
+				}
+
+				// 计算相关性
+				xEdbIdValue, yDataList, e := logic.CalculateCorrelation(calculatePars.LeadValue, calculatePars.LeadUnit, baseEdb.Frequency, edb.Frequency, dataListA, dataListB)
+				if e != nil {
+					utils.FileLog.Info(fmt.Sprintf("相关性-计算失败, EdbInfoId: %d", edb.EdbInfoId))
+					return
+				}
+
+				// X及Y轴数据
+				yData := yDataList[0].Value
+				yLen := len(yData)
+				values := make([]models.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] = models.FactorEdbSeriesCorrelationMatrixValues{
+						XData: x, YData: y,
+					}
+				}
+
+				// 更新计算结果
+				b, e := json.Marshal(values)
+				if e != nil {
+					utils.FileLog.Info(fmt.Sprintf("相关性-计算结果JSON格式化失败, err: %v", e))
+					return
+				}
+				chartMapping.CalculateData = string(b)
+				chartMapping.ModifyTime = time.Now().Local()
+				if e = chartMapping.Update([]string{chartMapping.Cols().CalculateData, chartMapping.Cols().ModifyTime}); e != nil {
+					utils.FileLog.Info(fmt.Sprintf("相关性-更新矩阵数据失败, err: %v", e))
+					return
+				}
+			}
+		}(v, edbItem, seriesItem)
+	}
+	wg.Wait()
+
+	br.Ret = 200
+	br.Success = true
+	br.Msg = "操作成功"
+}

logic/chart_correlation.go

@@ -0,0 +1,195 @@
+package logic
+
+import (
+	"eta/eta_index_lib/models"
+	"eta/eta_index_lib/utils"
+	"fmt"
+)
+
+// CalculateCorrelation 计算相关性-获取x轴和y轴
+func CalculateCorrelation(leadValue int, leadUnit, frequencyA, frequencyB string, dataListA, dataListB []*models.EdbInfoSearchData) (xEdbIdValue []int, yDataList []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([]*EdbDataList, 0)
+	//switch baseEdbInfo.EdbInfoCategoryType {
+	//case 0:
+	//	aDataList, err = 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([]*EdbDataList, 0)
+	//switch changeEdbInfo.EdbInfoCategoryType {
+	//case 0:
+	//	bDataList, err = 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([]*models.EdbInfoSearchData, 0)
+	baseDataMap := make(map[string]float64)
+	changeDataList := make([]*models.EdbInfoSearchData, 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 := models.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 := models.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 := models.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([]YData, 0)
+	yDate := "0000-00-00"
+	yDataList = append(yDataList, YData{
+		Date:  yDate,
+		Value: yData,
+	})
+	return
+}

models/base_calculate.go

@@ -1851,3 +1851,35 @@ func GetDateDataAndDateList(dateDataMap map[time.Time]float64) (dateStrDataMap m
 
 	return
 }
+
+// StepCalculateBySearchData
+// @Description: 分步骤计算
+type StepCalculateBySearchData struct {
+	DataList   []*EdbInfoSearchData `description:"基础数据"`
+	Calculates []CalculatesReq
+}
+
+type CalculatesReq struct {
+	Formula       interface{}
+	Calendar      string `description:"公历/农历"`
+	Frequency     string `description:"需要转换的频度"`
+	MoveType      int    `description:"移动方式:1:领先(默认),2:滞后"`
+	MoveFrequency string `description:"移动频度"`
+	FromFrequency string `description:"来源的频度"`
+	Source        int    `description:"1：累计值转月；2：累计值转季；3：同比值；4：同差值；5：N数值移动平均数计算；6：环比值；7：环差值；8：升频；9：降频；10：时间移位；11：超季节性；12：年化；13：累计值；14：累计值年初至今；15：指数修匀；16：日均值"`
+	Sort          int    `description:"计算顺序"`
+}
+
+func TransDateData2EdbData(dateData map[time.Time]float64) (edbData []*EdbInfoData) {
+	edbData = make([]*EdbInfoData, 0)
+	for d, v := range dateData {
+		edbData = append(edbData, &EdbInfoData{
+			DataTime: d,
+			Value:    v,
+		})
+	}
+	sort.Slice(edbData, func(i, j int) bool {
+		return edbData[i].DataTime.Before(edbData[j].DataTime)
+	})
+	return
+}

models/db.go

@@ -80,6 +80,9 @@ func init() {
 	// 自有数据指标
 	initBusinessEdb()
 
+	// 初始化因子指标系列
+	initFactorEdbSeries()
+
 	// 初始化部分数据表变量(直接init会有顺序问题=_=!)
 	InitEdbSource()
 }
@@ -178,3 +181,13 @@ func initBusinessEdb() {
 		new(EdbBusinessSource),     // 自有数据（商家）指标来源
 	)
 }
+
+// initFactorEdbSeries 因子指标系列数据表
+func initFactorEdbSeries() {
+	orm.RegisterModel(
+		new(FactorEdbSeries),              // 因子指标系列
+		new(FactorEdbSeriesChartMapping),  // 因子指标系列-图表关联
+		new(FactorEdbSeriesMapping),       // 因子指标系列-指标计算数据
+		new(FactorEdbSeriesCalculateData), // 因子指标系列-指标关联
+	)
+}

models/edb_info.go

@@ -1511,3 +1511,37 @@ func GetEdbInfoByEdbCodeList(source int, edbCodeList []string) (items []*EdbInfo
 
 	return
 }
+
+func TransEdbInfoSearchData2DataList(items []*EdbInfoSearchData) (list []*EdbDataList) {
+	if len(items) == 0 {
+		return
+	}
+	list = make([]*EdbDataList, 0)
+	for _, v := range items {
+		list = append(list, &EdbDataList{
+			EdbDataId:     v.EdbDataId,
+			EdbInfoId:     v.EdbInfoId,
+			DataTime:      v.DataTime,
+			DataTimestamp: v.DataTimestamp,
+			Value:         v.Value,
+		})
+	}
+	return
+}
+
+func TransEdbInfoDataList2SearchData(items []*EdbDataList) (list []*EdbInfoSearchData) {
+	if len(items) == 0 {
+		return
+	}
+	list = make([]*EdbInfoSearchData, 0)
+	for _, v := range items {
+		list = append(list, &EdbInfoSearchData{
+			EdbDataId:     v.EdbDataId,
+			EdbInfoId:     v.EdbInfoId,
+			DataTime:      v.DataTime,
+			DataTimestamp: v.DataTimestamp,
+			Value:         v.Value,
+		})
+	}
+	return
+}

models/factor_edb_series.go

@@ -0,0 +1,363 @@
+package models
+
+import (
+	"encoding/json"
+	"eta/eta_index_lib/utils"
+	"fmt"
+	"github.com/beego/beego/v2/client/orm"
+	"strings"
+	"time"
+)
+
+const (
+	FactorEdbSeriesCalculateNone = 0
+	FactorEdbSeriesCalculating   = 1
+	FactorEdbSeriesCalculated    = 2
+)
+
+// FactorEdbSeries 因子指标系列表
+type FactorEdbSeries struct {
+	FactorEdbSeriesId int       `orm:"column(factor_edb_series_id);pk"`
+	SeriesName        string    `description:"系列名称"`
+	EdbInfoType       int       `description:"关联指标类型：0-普通指标；1-预测指标"`
+	CalculateStep     string    `description:"计算步骤-JSON"`
+	CalculateState    int       `description:"计算状态: 0-无计算; 1-计算中; 2-计算完成"`
+	CreateTime        time.Time `description:"创建时间"`
+	ModifyTime        time.Time `description:"修改时间"`
+}
+
+func (m *FactorEdbSeries) TableName() string {
+	return "factor_edb_series"
+}
+
+type FactorEdbSeriesCols struct {
+	PrimaryId      string
+	SeriesName     string
+	EdbInfoType    string
+	CalculateStep  string
+	CalculateState string
+	CreateTime     string
+	ModifyTime     string
+}
+
+func (m *FactorEdbSeries) Cols() FactorEdbSeriesCols {
+	return FactorEdbSeriesCols{
+		PrimaryId:      "factor_edb_series_id",
+		SeriesName:     "series_name",
+		EdbInfoType:    "edb_info_type",
+		CalculateStep:  "calculate_step",
+		CalculateState: "calculate_state",
+		CreateTime:     "create_time",
+		ModifyTime:     "modify_time",
+	}
+}
+
+func (m *FactorEdbSeries) Create() (err error) {
+	o := orm.NewOrm()
+	id, err := o.Insert(m)
+	if err != nil {
+		return
+	}
+	m.FactorEdbSeriesId = int(id)
+	return
+}
+
+func (m *FactorEdbSeries) CreateMulti(items []*FactorEdbSeries) (err error) {
+	if len(items) == 0 {
+		return
+	}
+	o := orm.NewOrm()
+	_, err = o.InsertMulti(len(items), items)
+	return
+}
+
+func (m *FactorEdbSeries) Update(cols []string) (err error) {
+	o := orm.NewOrm()
+	_, err = o.Update(m, cols...)
+	return
+}
+
+func (m *FactorEdbSeries) Remove() (err error) {
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`DELETE FROM %s WHERE %s = ? LIMIT 1`, m.TableName(), m.Cols().PrimaryId)
+	_, err = o.Raw(sql, m.FactorEdbSeriesId).Exec()
+	return
+}
+
+func (m *FactorEdbSeries) MultiRemove(ids []int) (err error) {
+	if len(ids) == 0 {
+		return
+	}
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`DELETE FROM %s WHERE %s IN (%s)`, m.TableName(), m.Cols().PrimaryId, utils.GetOrmInReplace(len(ids)))
+	_, err = o.Raw(sql, ids).Exec()
+	return
+}
+
+func (m *FactorEdbSeries) GetItemById(id int) (item *FactorEdbSeries, err error) {
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`SELECT * FROM %s WHERE %s = ? LIMIT 1`, m.TableName(), m.Cols().PrimaryId)
+	err = o.Raw(sql, id).QueryRow(&item)
+	return
+}
+
+func (m *FactorEdbSeries) GetItemByCondition(condition string, pars []interface{}, orderRule string) (item *FactorEdbSeries, err error) {
+	o := orm.NewOrm()
+	order := ``
+	if orderRule != "" {
+		order = ` ORDER BY ` + orderRule
+	}
+	sql := fmt.Sprintf(`SELECT * FROM %s WHERE 1=1 %s %s LIMIT 1`, m.TableName(), condition, order)
+	err = o.Raw(sql, pars).QueryRow(&item)
+	return
+}
+
+func (m *FactorEdbSeries) GetCountByCondition(condition string, pars []interface{}) (count int, err error) {
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`SELECT COUNT(1) FROM %s WHERE 1=1 %s`, m.TableName(), condition)
+	err = o.Raw(sql, pars).QueryRow(&count)
+	return
+}
+
+func (m *FactorEdbSeries) GetItemsByCondition(condition string, pars []interface{}, fieldArr []string, orderRule string) (items []*FactorEdbSeries, err error) {
+	o := orm.NewOrm()
+	fields := strings.Join(fieldArr, ",")
+	if len(fieldArr) == 0 {
+		fields = `*`
+	}
+	order := fmt.Sprintf(`ORDER BY %s DESC`, m.Cols().CreateTime)
+	if orderRule != "" {
+		order = ` ORDER BY ` + orderRule
+	}
+	sql := fmt.Sprintf(`SELECT %s FROM %s WHERE 1=1 %s %s`, fields, m.TableName(), condition, order)
+	_, err = o.Raw(sql, pars).QueryRows(&items)
+	return
+}
+
+func (m *FactorEdbSeries) GetPageItemsByCondition(condition string, pars []interface{}, fieldArr []string, orderRule string, startSize, pageSize int) (items []*FactorEdbSeries, err error) {
+	o := orm.NewOrm()
+	fields := strings.Join(fieldArr, ",")
+	if len(fieldArr) == 0 {
+		fields = `*`
+	}
+	order := fmt.Sprintf(`ORDER BY %s DESC`, m.Cols().CreateTime)
+	if orderRule != "" {
+		order = ` ORDER BY ` + orderRule
+	}
+	sql := fmt.Sprintf(`SELECT %s FROM %s WHERE 1=1 %s %s LIMIT ?,?`, fields, m.TableName(), condition, order)
+	_, err = o.Raw(sql, pars, startSize, pageSize).QueryRows(&items)
+	return
+}
+
+// FactorEdbSeriesItem 多因子系列信息
+type FactorEdbSeriesItem struct {
+	SeriesId      int                            `description:"多因子系列ID"`
+	SeriesName    string                         `description:"系列名称"`
+	EdbInfoType   int                            `description:"关联指标类型：0-普通指标；1-预测指标"`
+	CalculateStep []FactorEdbSeriesCalculatePars `description:"计算步骤-JSON"`
+	CreateTime    string                         `description:"创建时间"`
+	ModifyTime    string                         `description:"修改时间"`
+}
+
+func (m *FactorEdbSeries) Format2Item() (item *FactorEdbSeriesItem) {
+	item = new(FactorEdbSeriesItem)
+	item.SeriesId = m.FactorEdbSeriesId
+	item.SeriesName = m.SeriesName
+	item.EdbInfoType = m.EdbInfoType
+	if m.CalculateStep != "" {
+		_ = json.Unmarshal([]byte(m.CalculateStep), &item.CalculateStep)
+	}
+	item.CreateTime = utils.TimeTransferString(utils.FormatDateTime, m.CreateTime)
+	item.ModifyTime = utils.TimeTransferString(utils.FormatDateTime, m.ModifyTime)
+	return
+}
+
+// FactorEdbSeriesCalculatePars 计算参数
+type FactorEdbSeriesCalculatePars struct {
+	Formula       interface{} `description:"N值/移动天数/指数修匀alpha值/计算公式等"`
+	Calendar      string      `description:"公历/农历"`
+	Frequency     string      `description:"需要转换的频度"`
+	MoveType      int         `description:"移动方式: 1-领先(默认); 2-滞后"`
+	MoveFrequency string      `description:"移动频度"`
+	FromFrequency string      `description:"来源的频度"`
+	Source        int         `description:"计算方式来源(不是指标来源)"`
+	Sort          int         `description:"计算顺序"`
+}
+
+// CreateSeriesAndMapping 新增系列和指标关联
+func (m *FactorEdbSeries) CreateSeriesAndMapping(item *FactorEdbSeries, mappings []*FactorEdbSeriesMapping) (seriesId int, err error) {
+	if item == nil {
+		err = fmt.Errorf("series is nil")
+		return
+	}
+	o := orm.NewOrm()
+	tx, e := o.Begin()
+	if e != nil {
+		err = fmt.Errorf("orm begin err: %v", e)
+		return
+	}
+	defer func() {
+		if err != nil {
+			_ = tx.Rollback()
+			return
+		}
+		_ = tx.Commit()
+	}()
+
+	id, e := tx.Insert(item)
+	if e != nil {
+		err = fmt.Errorf("insert series err: %v", e)
+		return
+	}
+	seriesId = int(id)
+	item.FactorEdbSeriesId = seriesId
+
+	if len(mappings) > 0 {
+		for _, v := range mappings {
+			v.FactorEdbSeriesId = seriesId
+		}
+		_, e = tx.InsertMulti(200, mappings)
+		if e != nil {
+			err = fmt.Errorf("insert multi mapping err: %v", e)
+			return
+		}
+	}
+	return
+}
+
+// EditSeriesAndMapping 编辑系列和指标关联
+func (m *FactorEdbSeries) EditSeriesAndMapping(item *FactorEdbSeries, mappings []*FactorEdbSeriesMapping, updateCols []string) (err error) {
+	if item == nil {
+		err = fmt.Errorf("series is nil")
+		return
+	}
+	o := orm.NewOrm()
+	tx, e := o.Begin()
+	if e != nil {
+		err = fmt.Errorf("orm begin err: %v", e)
+		return
+	}
+	defer func() {
+		if err != nil {
+			_ = tx.Rollback()
+			return
+		}
+		_ = tx.Commit()
+	}()
+
+	_, e = tx.Update(item, updateCols...)
+	if e != nil {
+		err = fmt.Errorf("update series err: %v", e)
+		return
+	}
+
+	// 清除原指标关联
+	mappingOb := new(FactorEdbSeriesMapping)
+	cond := fmt.Sprintf("%s = ?", mappingOb.Cols().FactorEdbSeriesId)
+	pars := make([]interface{}, 0)
+	pars = append(pars, item.FactorEdbSeriesId)
+	sql := fmt.Sprintf(`DELETE FROM %s WHERE %s`, mappingOb.TableName(), cond)
+	_, e = tx.Raw(sql, pars).Exec()
+	if e != nil {
+		err = fmt.Errorf("remove mapping err: %v", e)
+		return
+	}
+
+	if len(mappings) > 0 {
+		for _, v := range mappings {
+			v.FactorEdbSeriesId = item.FactorEdbSeriesId
+		}
+		_, e = tx.InsertMulti(200, mappings)
+		if e != nil {
+			err = fmt.Errorf("insert multi mapping err: %v", e)
+			return
+		}
+	}
+	return
+}
+
+// FactorEdbSeriesStepCalculateResp 批量计算响应
+type FactorEdbSeriesStepCalculateResp struct {
+	SeriesId int                                  `description:"多因子指标系列ID"`
+	Fail     []FactorEdbSeriesStepCalculateResult `description:"计算失败的指标"`
+	Success  []FactorEdbSeriesStepCalculateResult `description:"计算成功的指标"`
+}
+
+// FactorEdbSeriesStepCalculateResult 批量计算结果
+type FactorEdbSeriesStepCalculateResult struct {
+	EdbInfoId int    `description:"指标ID"`
+	EdbCode   string `description:"指标编码"`
+	Msg       string `description:"提示信息"`
+	ErrMsg    string `description:"错误信息"`
+}
+
+// FactorEdbSeriesDetail 因子指标系列-详情
+type FactorEdbSeriesDetail struct {
+	*FactorEdbSeriesItem
+	EdbMappings []*FactorEdbSeriesMappingItem
+}
+
+// FactorEdbSeriesCorrelationMatrixResp 因子指标系列-相关性矩阵响应
+type FactorEdbSeriesCorrelationMatrixResp struct {
+	Fail    []FactorEdbSeriesCorrelationMatrixItem `description:"计算失败的指标"`
+	Success []FactorEdbSeriesCorrelationMatrixItem `description:"计算成功的指标"`
+}
+
+// FactorEdbSeriesCorrelationMatrixItem 因子指标系列-相关性矩阵信息
+type FactorEdbSeriesCorrelationMatrixItem struct {
+	SeriesId   int                                      `description:"因子指标系列ID"`
+	EdbInfoId  int                                      `description:"指标ID"`
+	EdbCode    string                                   `description:"指标编码"`
+	EdbName    string                                   `description:"指标名称"`
+	Values     []FactorEdbSeriesCorrelationMatrixValues `description:"X轴和Y轴数据"`
+	Msg        string                                   `description:"提示信息"`
+	ErrMsg     string                                   `description:"错误信息"`
+	Used       bool                                     `description:"是否选中"`
+	SourceName string                                   `description:"指标来源名称"`
+}
+
+// FactorEdbSeriesCorrelationMatrixValues 因子指标系列-相关性矩阵XY值
+type FactorEdbSeriesCorrelationMatrixValues struct {
+	XData int     `description:"X轴数据"`
+	YData float64 `description:"Y轴数据"`
+}
+
+// FactorEdbSeriesCorrelationMatrixOrder 排序规则[0 1 2 3 -1 -2 -3]
+type FactorEdbSeriesCorrelationMatrixOrder []FactorEdbSeriesCorrelationMatrixValues
+
+func (a FactorEdbSeriesCorrelationMatrixOrder) Len() int {
+	return len(a)
+}
+
+func (a FactorEdbSeriesCorrelationMatrixOrder) Swap(i, j int) {
+	a[i], a[j] = a[j], a[i]
+}
+
+func (a FactorEdbSeriesCorrelationMatrixOrder) Less(i, j int) bool {
+	// 非负数优先
+	if a[i].XData >= 0 && a[j].XData < 0 {
+		return true
+	}
+	if a[i].XData < 0 && a[j].XData >= 0 {
+		return false
+	}
+	// 非负数升序排序
+	if a[i].XData >= 0 {
+		return a[i].XData < a[j].XData
+	}
+	// 负数按绝对值的降序排序（即数值的升序）
+	return a[i].XData > a[j].XData
+}
+
+// FactorEdbRecalculateReq 因子指标重新计算
+type FactorEdbRecalculateReq struct {
+	EdbInfoId int    `description:"指标ID"`
+	EdbCode   string `description:"指标编码"`
+}
+
+// FactorEdbChartRecalculateReq 因子指标关联的图表数据重计算
+type FactorEdbChartRecalculateReq struct {
+	ChartInfoId int `description:"图表ID"`
+	//EdbInfoId   int    `description:"指标ID"`
+	//EdbCode     string `description:"指标编码"`
+}

models/factor_edb_series_calculate_data.go

@@ -0,0 +1,190 @@
+package models
+
+import (
+	"eta/eta_index_lib/utils"
+	"fmt"
+	"github.com/beego/beego/v2/client/orm"
+	"strings"
+	"time"
+)
+
+// FactorEdbSeriesCalculateData 因子指标系列-指标计算数据表
+type FactorEdbSeriesCalculateData struct {
+	FactorEdbSeriesCalculateDataId int       `orm:"column(factor_edb_series_calculate_data_id);pk"`
+	FactorEdbSeriesId              int       `description:"因子指标系列ID"`
+	EdbInfoId                      int       `description:"指标ID"`
+	EdbCode                        string    `description:"指标编码"`
+	DataTime                       time.Time `description:"数据日期"`
+	Value                          float64   `description:"数据值"`
+	CreateTime                     time.Time `description:"创建时间"`
+	ModifyTime                     time.Time `description:"修改时间"`
+	DataTimestamp                  int64     `description:"数据日期时间戳"`
+}
+
+func (m *FactorEdbSeriesCalculateData) TableName() string {
+	return "factor_edb_series_calculate_data"
+}
+
+type FactorEdbSeriesCalculateDataCols struct {
+	PrimaryId         string
+	FactorEdbSeriesId string
+	EdbInfoId         string
+	EdbCode           string
+	DataTime          string
+	Value             string
+	CreateTime        string
+	ModifyTime        string
+	DataTimestamp     string
+}
+
+func (m *FactorEdbSeriesCalculateData) Cols() FactorEdbSeriesCalculateDataCols {
+	return FactorEdbSeriesCalculateDataCols{
+		PrimaryId:         "factor_edb_series_calculate_data_id",
+		FactorEdbSeriesId: "factor_edb_series_id",
+		EdbInfoId:         "edb_info_id",
+		EdbCode:           "edb_code",
+		DataTime:          "data_time",
+		Value:             "value",
+		CreateTime:        "create_time",
+		ModifyTime:        "modify_time",
+		DataTimestamp:     "data_timestamp",
+	}
+}
+
+func (m *FactorEdbSeriesCalculateData) Create() (err error) {
+	o := orm.NewOrm()
+	id, err := o.Insert(m)
+	if err != nil {
+		return
+	}
+	m.FactorEdbSeriesCalculateDataId = int(id)
+	return
+}
+
+func (m *FactorEdbSeriesCalculateData) CreateMulti(items []*FactorEdbSeriesCalculateData) (err error) {
+	if len(items) == 0 {
+		return
+	}
+	o := orm.NewOrm()
+	_, err = o.InsertMulti(500, items)
+	return
+}
+
+func (m *FactorEdbSeriesCalculateData) Update(cols []string) (err error) {
+	o := orm.NewOrm()
+	_, err = o.Update(m, cols...)
+	return
+}
+
+func (m *FactorEdbSeriesCalculateData) Remove() (err error) {
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`DELETE FROM %s WHERE %s = ? LIMIT 1`, m.TableName(), m.Cols().PrimaryId)
+	_, err = o.Raw(sql, m.FactorEdbSeriesCalculateDataId).Exec()
+	return
+}
+
+func (m *FactorEdbSeriesCalculateData) MultiRemove(ids []int) (err error) {
+	if len(ids) == 0 {
+		return
+	}
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`DELETE FROM %s WHERE %s IN (%s)`, m.TableName(), m.Cols().PrimaryId, utils.GetOrmInReplace(len(ids)))
+	_, err = o.Raw(sql, ids).Exec()
+	return
+}
+
+func (m *FactorEdbSeriesCalculateData) RemoveByCondition(condition string, pars []interface{}) (err error) {
+	if condition == "" {
+		return
+	}
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`DELETE FROM %s WHERE %s`, m.TableName(), condition)
+	_, err = o.Raw(sql, pars).Exec()
+	return
+}
+
+func (m *FactorEdbSeriesCalculateData) GetItemById(id int) (item *FactorEdbSeriesCalculateData, err error) {
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`SELECT * FROM %s WHERE %s = ? LIMIT 1`, m.TableName(), m.Cols().PrimaryId)
+	err = o.Raw(sql, id).QueryRow(&item)
+	return
+}
+
+func (m *FactorEdbSeriesCalculateData) GetItemByCondition(condition string, pars []interface{}, orderRule string) (item *FactorEdbSeriesCalculateData, err error) {
+	o := orm.NewOrm()
+	order := ``
+	if orderRule != "" {
+		order = ` ORDER BY ` + orderRule
+	}
+	sql := fmt.Sprintf(`SELECT * FROM %s WHERE 1=1 %s %s LIMIT 1`, m.TableName(), condition, order)
+	err = o.Raw(sql, pars).QueryRow(&item)
+	return
+}
+
+func (m *FactorEdbSeriesCalculateData) GetCountByCondition(condition string, pars []interface{}) (count int, err error) {
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`SELECT COUNT(1) FROM %s WHERE 1=1 %s`, m.TableName(), condition)
+	err = o.Raw(sql, pars).QueryRow(&count)
+	return
+}
+
+func (m *FactorEdbSeriesCalculateData) GetItemsByCondition(condition string, pars []interface{}, fieldArr []string, orderRule string) (items []*FactorEdbSeriesCalculateData, err error) {
+	o := orm.NewOrm()
+	fields := strings.Join(fieldArr, ",")
+	if len(fieldArr) == 0 {
+		fields = `*`
+	}
+	order := fmt.Sprintf(`ORDER BY %s DESC`, m.Cols().CreateTime)
+	if orderRule != "" {
+		order = ` ORDER BY ` + orderRule
+	}
+	sql := fmt.Sprintf(`SELECT %s FROM %s WHERE 1=1 %s %s`, fields, m.TableName(), condition, order)
+	_, err = o.Raw(sql, pars).QueryRows(&items)
+	return
+}
+
+func (m *FactorEdbSeriesCalculateData) GetPageItemsByCondition(condition string, pars []interface{}, fieldArr []string, orderRule string, startSize, pageSize int) (items []*FactorEdbSeriesCalculateData, err error) {
+	o := orm.NewOrm()
+	fields := strings.Join(fieldArr, ",")
+	if len(fieldArr) == 0 {
+		fields = `*`
+	}
+	order := fmt.Sprintf(`ORDER BY %s DESC`, m.Cols().CreateTime)
+	if orderRule != "" {
+		order = ` ORDER BY ` + orderRule
+	}
+	sql := fmt.Sprintf(`SELECT %s FROM %s WHERE 1=1 %s %s LIMIT ?,?`, fields, m.TableName(), condition, order)
+	_, err = o.Raw(sql, pars, startSize, pageSize).QueryRows(&items)
+	return
+}
+
+// FactorEdbSeriesCalculateDataItem 因子指标系列-计算数据信息
+type FactorEdbSeriesCalculateDataItem struct {
+	DataId            int     `description:"数据ID"`
+	FactorEdbSeriesId int     `description:"因子指标系列ID"`
+	EdbInfoId         int     `description:"指标ID"`
+	EdbCode           string  `description:"指标编码"`
+	DataTime          string  `description:"数据日期"`
+	Value             float64 `description:"数据值"`
+}
+
+func (m *FactorEdbSeriesCalculateData) Format2Item() (item *FactorEdbSeriesCalculateDataItem) {
+	item = new(FactorEdbSeriesCalculateDataItem)
+	item.DataId = m.FactorEdbSeriesCalculateDataId
+	item.FactorEdbSeriesId = m.FactorEdbSeriesId
+	item.EdbInfoId = m.EdbInfoId
+	item.EdbCode = m.EdbCode
+	return
+}
+
+// TransEdbSeriesCalculateData2EdbDataList 转换数据格式
+func TransEdbSeriesCalculateData2EdbDataList(items []*FactorEdbSeriesCalculateData) (list []*EdbInfoSearchData) {
+	list = make([]*EdbInfoSearchData, 0)
+	for _, v := range items {
+		list = append(list, &EdbInfoSearchData{
+			DataTime: v.DataTime.Format(utils.FormatDate),
+			Value:    v.Value,
+		})
+	}
+	return
+}

models/factor_edb_series_calculate_func.go

@@ -0,0 +1,153 @@
+package models
+
+import (
+	"eta/eta_index_lib/utils"
+	"fmt"
+	"github.com/beego/beego/v2/client/orm"
+	"strings"
+	"time"
+)
+
+// FactorEdbSeriesCalculateFunc 多因子系列-计算方式表
+type FactorEdbSeriesCalculateFunc struct {
+	FactorEdbSeriesCalculateFuncId int       `orm:"column(factor_edb_series_calculate_func_id);pk"`
+	CalculateName                  string    `description:"计算方式名称"`
+	Source                         int       `description:"计算方式来源"`
+	EdbInfoType                    int       `description:"指标计算类型：0-普通指标；1-预测指标"`
+	CreateTime                     time.Time `description:"创建时间"`
+	ModifyTime                     time.Time `description:"修改时间"`
+}
+
+func (m *FactorEdbSeriesCalculateFunc) TableName() string {
+	return "factor_edb_series_calculate_func"
+}
+
+type FactorEdbSeriesCalculateFuncCols struct {
+	PrimaryId     string
+	CalculateName string
+	Source        string
+	EdbInfoType   string
+	CreateTime    string
+	ModifyTime    string
+}
+
+func (m *FactorEdbSeriesCalculateFunc) Cols() FactorEdbSeriesCalculateFuncCols {
+	return FactorEdbSeriesCalculateFuncCols{
+		PrimaryId:     "factor_edb_series_calculate_func_id",
+		CalculateName: "calculate_name",
+		Source:        "source",
+		EdbInfoType:   "edb_info_type",
+		CreateTime:    "create_time",
+		ModifyTime:    "modify_time",
+	}
+}
+
+func (m *FactorEdbSeriesCalculateFunc) Create() (err error) {
+	o := orm.NewOrm()
+	id, err := o.Insert(m)
+	if err != nil {
+		return
+	}
+	m.FactorEdbSeriesCalculateFuncId = int(id)
+	return
+}
+
+func (m *FactorEdbSeriesCalculateFunc) CreateMulti(items []*FactorEdbSeriesCalculateFunc) (err error) {
+	if len(items) == 0 {
+		return
+	}
+	o := orm.NewOrm()
+	_, err = o.InsertMulti(len(items), items)
+	return
+}
+
+func (m *FactorEdbSeriesCalculateFunc) Update(cols []string) (err error) {
+	o := orm.NewOrm()
+	_, err = o.Update(m, cols...)
+	return
+}
+
+func (m *FactorEdbSeriesCalculateFunc) Remove() (err error) {
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`DELETE FROM %s WHERE %s = ? LIMIT 1`, m.TableName(), m.Cols().PrimaryId)
+	_, err = o.Raw(sql, m.FactorEdbSeriesCalculateFuncId).Exec()
+	return
+}
+
+func (m *FactorEdbSeriesCalculateFunc) MultiRemove(ids []int) (err error) {
+	if len(ids) == 0 {
+		return
+	}
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`DELETE FROM %s WHERE %s IN (%s)`, m.TableName(), m.Cols().PrimaryId, utils.GetOrmInReplace(len(ids)))
+	_, err = o.Raw(sql, ids).Exec()
+	return
+}
+
+func (m *FactorEdbSeriesCalculateFunc) GetItemById(id int) (item *FactorEdbSeriesCalculateFunc, err error) {
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`SELECT * FROM %s WHERE %s = ? LIMIT 1`, m.TableName(), m.Cols().PrimaryId)
+	err = o.Raw(sql, id).QueryRow(&item)
+	return
+}
+
+func (m *FactorEdbSeriesCalculateFunc) GetItemByCondition(condition string, pars []interface{}, orderRule string) (item *FactorEdbSeriesCalculateFunc, err error) {
+	o := orm.NewOrm()
+	order := ``
+	if orderRule != "" {
+		order = ` ORDER BY ` + orderRule
+	}
+	sql := fmt.Sprintf(`SELECT * FROM %s WHERE 1=1 %s %s LIMIT 1`, m.TableName(), condition, order)
+	err = o.Raw(sql, pars).QueryRow(&item)
+	return
+}
+
+func (m *FactorEdbSeriesCalculateFunc) GetCountByCondition(condition string, pars []interface{}) (count int, err error) {
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`SELECT COUNT(1) FROM %s WHERE 1=1 %s`, m.TableName(), condition)
+	err = o.Raw(sql, pars).QueryRow(&count)
+	return
+}
+
+func (m *FactorEdbSeriesCalculateFunc) GetItemsByCondition(condition string, pars []interface{}, fieldArr []string, orderRule string) (items []*FactorEdbSeriesCalculateFunc, err error) {
+	o := orm.NewOrm()
+	fields := strings.Join(fieldArr, ",")
+	if len(fieldArr) == 0 {
+		fields = `*`
+	}
+	order := fmt.Sprintf(`ORDER BY %s DESC`, m.Cols().CreateTime)
+	if orderRule != "" {
+		order = ` ORDER BY ` + orderRule
+	}
+	sql := fmt.Sprintf(`SELECT %s FROM %s WHERE 1=1 %s %s`, fields, m.TableName(), condition, order)
+	_, err = o.Raw(sql, pars).QueryRows(&items)
+	return
+}
+
+func (m *FactorEdbSeriesCalculateFunc) GetPageItemsByCondition(condition string, pars []interface{}, fieldArr []string, orderRule string, startSize, pageSize int) (items []*FactorEdbSeriesCalculateFunc, err error) {
+	o := orm.NewOrm()
+	fields := strings.Join(fieldArr, ",")
+	if len(fieldArr) == 0 {
+		fields = `*`
+	}
+	order := fmt.Sprintf(`ORDER BY %s DESC`, m.Cols().CreateTime)
+	if orderRule != "" {
+		order = ` ORDER BY ` + orderRule
+	}
+	sql := fmt.Sprintf(`SELECT %s FROM %s WHERE 1=1 %s %s LIMIT ?,?`, fields, m.TableName(), condition, order)
+	_, err = o.Raw(sql, pars, startSize, pageSize).QueryRows(&items)
+	return
+}
+
+// FactorEdbSeriesCalculateFuncItem 多因子系列-计算方式
+type FactorEdbSeriesCalculateFuncItem struct {
+	CalculateName string `description:"计算方式名称"`
+	Source        int    `description:"计算方式来源"`
+}
+
+func (m *FactorEdbSeriesCalculateFunc) Format2Item() (item *FactorEdbSeriesCalculateFuncItem) {
+	item = new(FactorEdbSeriesCalculateFuncItem)
+	item.CalculateName = m.CalculateName
+	item.Source = m.Source
+	return
+}

models/factor_edb_series_chart_mapping.go

@@ -0,0 +1,176 @@
+package models
+
+import (
+	"eta/eta_index_lib/utils"
+	"fmt"
+	"github.com/beego/beego/v2/client/orm"
+	"strings"
+	"time"
+)
+
+const (
+	FactorEdbSeriesChartCalculateTypeCorrelation = 1 // 相关性计算
+)
+
+// FactorEdbSeriesChartMapping 因子指标系列-图表关联
+type FactorEdbSeriesChartMapping struct {
+	FactorEdbSeriesChartMappingId int       `orm:"column(factor_edb_series_chart_mapping_id);pk"`
+	ChartInfoId                   int       `description:"图表ID"`
+	Source                        int       `description:"图表来源, 同chart_info表source"`
+	CalculateType                 int       `description:"计算方式: 1-相关性"`
+	CalculatePars                 string    `description:"计算参数-JSON(如计算窗口等)"`
+	CalculateData                 string    `description:"计算数据-JSON(如相关性矩阵等)"`
+	FactorEdbSeriesId             int       `description:"因子指标系列ID"`
+	EdbInfoId                     int       `description:"指标ID"`
+	EdbUsed                       int       `description:"指标是否使用: 0-否; 1-是"`
+	CreateTime                    time.Time `description:"创建时间"`
+	ModifyTime                    time.Time `description:"修改时间"`
+}
+
+func (m *FactorEdbSeriesChartMapping) TableName() string {
+	return "factor_edb_series_chart_mapping"
+}
+
+type MultipleFactorSeriesChartMappingCols struct {
+	PrimaryId         string
+	ChartInfoId       string
+	Source            string
+	CalculateType     string
+	CalculatePars     string
+	CalculateData     string
+	FactorEdbSeriesId string
+	EdbInfoId         string
+	EdbUsed           string
+	CreateTime        string
+	ModifyTime        string
+}
+
+func (m *FactorEdbSeriesChartMapping) Cols() MultipleFactorSeriesChartMappingCols {
+	return MultipleFactorSeriesChartMappingCols{
+		PrimaryId:         "factor_edb_series_chart_mapping_id",
+		ChartInfoId:       "chart_info_id",
+		Source:            "source",
+		CalculateType:     "calculate_type",
+		CalculatePars:     "calculate_pars",
+		CalculateData:     "calculate_data",
+		FactorEdbSeriesId: "factor_edb_series_id",
+		EdbInfoId:         "edb_info_id",
+		EdbUsed:           "edb_used",
+		CreateTime:        "create_time",
+		ModifyTime:        "modify_time",
+	}
+}
+
+func (m *FactorEdbSeriesChartMapping) Create() (err error) {
+	o := orm.NewOrm()
+	id, err := o.Insert(m)
+	if err != nil {
+		return
+	}
+	m.FactorEdbSeriesChartMappingId = int(id)
+	return
+}
+
+func (m *FactorEdbSeriesChartMapping) CreateMulti(items []*FactorEdbSeriesChartMapping) (err error) {
+	if len(items) == 0 {
+		return
+	}
+	o := orm.NewOrm()
+	_, err = o.InsertMulti(len(items), items)
+	return
+}
+
+func (m *FactorEdbSeriesChartMapping) Update(cols []string) (err error) {
+	o := orm.NewOrm()
+	_, err = o.Update(m, cols...)
+	return
+}
+
+func (m *FactorEdbSeriesChartMapping) Remove() (err error) {
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`DELETE FROM %s WHERE %s = ? LIMIT 1`, m.TableName(), m.Cols().PrimaryId)
+	_, err = o.Raw(sql, m.FactorEdbSeriesChartMappingId).Exec()
+	return
+}
+
+func (m *FactorEdbSeriesChartMapping) MultiRemove(ids []int) (err error) {
+	if len(ids) == 0 {
+		return
+	}
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`DELETE FROM %s WHERE %s IN (%s)`, m.TableName(), m.Cols().PrimaryId, utils.GetOrmInReplace(len(ids)))
+	_, err = o.Raw(sql, ids).Exec()
+	return
+}
+
+func (m *FactorEdbSeriesChartMapping) GetItemById(id int) (item *FactorEdbSeriesChartMapping, err error) {
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`SELECT * FROM %s WHERE %s = ? LIMIT 1`, m.TableName(), m.Cols().PrimaryId)
+	err = o.Raw(sql, id).QueryRow(&item)
+	return
+}
+
+func (m *FactorEdbSeriesChartMapping) GetItemByCondition(condition string, pars []interface{}, orderRule string) (item *FactorEdbSeriesChartMapping, err error) {
+	o := orm.NewOrm()
+	order := ``
+	if orderRule != "" {
+		order = ` ORDER BY ` + orderRule
+	}
+	sql := fmt.Sprintf(`SELECT * FROM %s WHERE 1=1 %s %s LIMIT 1`, m.TableName(), condition, order)
+	err = o.Raw(sql, pars).QueryRow(&item)
+	return
+}
+
+func (m *FactorEdbSeriesChartMapping) GetCountByCondition(condition string, pars []interface{}) (count int, err error) {
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`SELECT COUNT(1) FROM %s WHERE 1=1 %s`, m.TableName(), condition)
+	err = o.Raw(sql, pars).QueryRow(&count)
+	return
+}
+
+func (m *FactorEdbSeriesChartMapping) GetItemsByCondition(condition string, pars []interface{}, fieldArr []string, orderRule string) (items []*FactorEdbSeriesChartMapping, err error) {
+	o := orm.NewOrm()
+	fields := strings.Join(fieldArr, ",")
+	if len(fieldArr) == 0 {
+		fields = `*`
+	}
+	order := fmt.Sprintf(`ORDER BY %s DESC`, m.Cols().CreateTime)
+	if orderRule != "" {
+		order = ` ORDER BY ` + orderRule
+	}
+	sql := fmt.Sprintf(`SELECT %s FROM %s WHERE 1=1 %s %s`, fields, m.TableName(), condition, order)
+	_, err = o.Raw(sql, pars).QueryRows(&items)
+	return
+}
+
+func (m *FactorEdbSeriesChartMapping) GetPageItemsByCondition(condition string, pars []interface{}, fieldArr []string, orderRule string, startSize, pageSize int) (items []*FactorEdbSeriesChartMapping, err error) {
+	o := orm.NewOrm()
+	fields := strings.Join(fieldArr, ",")
+	if len(fieldArr) == 0 {
+		fields = `*`
+	}
+	order := fmt.Sprintf(`ORDER BY %s DESC`, m.Cols().CreateTime)
+	if orderRule != "" {
+		order = ` ORDER BY ` + orderRule
+	}
+	sql := fmt.Sprintf(`SELECT %s FROM %s WHERE 1=1 %s %s LIMIT ?,?`, fields, m.TableName(), condition, order)
+	_, err = o.Raw(sql, pars, startSize, pageSize).QueryRows(&items)
+	return
+}
+
+// GetDistinctSeriesIdByChartId 获取图表关联的系列ID
+func (m *FactorEdbSeriesChartMapping) GetDistinctSeriesIdByChartId(chartId int) (seriesIds []int, err error) {
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`SELECT DISTINCT %s FROM %s WHERE %s = ?`, m.Cols().FactorEdbSeriesId, m.TableName(), m.Cols().ChartInfoId)
+	_, err = o.Raw(sql, chartId).QueryRows(&seriesIds)
+	return
+}
+
+// FactorEdbSeriesChartCalculateCorrelationReq 图表相关性计算参数
+type FactorEdbSeriesChartCalculateCorrelationReq struct {
+	BaseEdbInfoId  int    `description:"标的指标ID"`
+	LeadValue      int    `description:"领先期数"`
+	LeadUnit       string `description:"频度"`
+	CalculateValue int    `description:"计算窗口"`
+	CalculateUnit  string `description:"计算频度"`
+}

models/factor_edb_series_mapping.go

@@ -0,0 +1,167 @@
+package models
+
+import (
+	"eta/eta_index_lib/utils"
+	"fmt"
+	"github.com/beego/beego/v2/client/orm"
+	"strings"
+	"time"
+)
+
+// FactorEdbSeriesMapping 因子指标系列-指标关联表
+type FactorEdbSeriesMapping struct {
+	FactorEdbSeriesMappingId int       `orm:"column(factor_edb_series_mapping_id);pk"`
+	FactorEdbSeriesId        int       `description:"因子指标系列ID"`
+	EdbInfoId                int       `description:"指标ID"`
+	EdbCode                  string    `description:"指标编码"`
+	CreateTime               time.Time `description:"创建时间"`
+	ModifyTime               time.Time `description:"修改时间"`
+}
+
+func (m *FactorEdbSeriesMapping) TableName() string {
+	return "factor_edb_series_mapping"
+}
+
+type FactorEdbSeriesMappingCols struct {
+	PrimaryId         string
+	FactorEdbSeriesId string
+	EdbInfoId         string
+	EdbCode           string
+	CreateTime        string
+	ModifyTime        string
+}
+
+func (m *FactorEdbSeriesMapping) Cols() FactorEdbSeriesMappingCols {
+	return FactorEdbSeriesMappingCols{
+		PrimaryId:         "factor_edb_series_mapping_id",
+		FactorEdbSeriesId: "factor_edb_series_id",
+		EdbInfoId:         "edb_info_id",
+		EdbCode:           "edb_code",
+		CreateTime:        "create_time",
+		ModifyTime:        "modify_time",
+	}
+}
+
+func (m *FactorEdbSeriesMapping) Create() (err error) {
+	o := orm.NewOrm()
+	id, err := o.Insert(m)
+	if err != nil {
+		return
+	}
+	m.FactorEdbSeriesMappingId = int(id)
+	return
+}
+
+func (m *FactorEdbSeriesMapping) CreateMulti(items []*FactorEdbSeriesMapping) (err error) {
+	if len(items) == 0 {
+		return
+	}
+	o := orm.NewOrm()
+	_, err = o.InsertMulti(len(items), items)
+	return
+}
+
+func (m *FactorEdbSeriesMapping) Update(cols []string) (err error) {
+	o := orm.NewOrm()
+	_, err = o.Update(m, cols...)
+	return
+}
+
+func (m *FactorEdbSeriesMapping) Remove() (err error) {
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`DELETE FROM %s WHERE %s = ? LIMIT 1`, m.TableName(), m.Cols().PrimaryId)
+	_, err = o.Raw(sql, m.FactorEdbSeriesMappingId).Exec()
+	return
+}
+
+func (m *FactorEdbSeriesMapping) MultiRemove(ids []int) (err error) {
+	if len(ids) == 0 {
+		return
+	}
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`DELETE FROM %s WHERE %s IN (%s)`, m.TableName(), m.Cols().PrimaryId, utils.GetOrmInReplace(len(ids)))
+	_, err = o.Raw(sql, ids).Exec()
+	return
+}
+
+func (m *FactorEdbSeriesMapping) RemoveByCondition(condition string, pars []interface{}) (err error) {
+	if condition == "" {
+		return
+	}
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`DELETE FROM %s WHERE %s`, m.TableName(), condition)
+	_, err = o.Raw(sql, pars).Exec()
+	return
+}
+
+func (m *FactorEdbSeriesMapping) GetItemById(id int) (item *FactorEdbSeriesMapping, err error) {
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`SELECT * FROM %s WHERE %s = ? LIMIT 1`, m.TableName(), m.Cols().PrimaryId)
+	err = o.Raw(sql, id).QueryRow(&item)
+	return
+}
+
+func (m *FactorEdbSeriesMapping) GetItemByCondition(condition string, pars []interface{}, orderRule string) (item *FactorEdbSeriesMapping, err error) {
+	o := orm.NewOrm()
+	order := ``
+	if orderRule != "" {
+		order = ` ORDER BY ` + orderRule
+	}
+	sql := fmt.Sprintf(`SELECT * FROM %s WHERE 1=1 %s %s LIMIT 1`, m.TableName(), condition, order)
+	err = o.Raw(sql, pars).QueryRow(&item)
+	return
+}
+
+func (m *FactorEdbSeriesMapping) GetCountByCondition(condition string, pars []interface{}) (count int, err error) {
+	o := orm.NewOrm()
+	sql := fmt.Sprintf(`SELECT COUNT(1) FROM %s WHERE 1=1 %s`, m.TableName(), condition)
+	err = o.Raw(sql, pars).QueryRow(&count)
+	return
+}
+
+func (m *FactorEdbSeriesMapping) GetItemsByCondition(condition string, pars []interface{}, fieldArr []string, orderRule string) (items []*FactorEdbSeriesMapping, err error) {
+	o := orm.NewOrm()
+	fields := strings.Join(fieldArr, ",")
+	if len(fieldArr) == 0 {
+		fields = `*`
+	}
+	order := fmt.Sprintf(`ORDER BY %s DESC`, m.Cols().CreateTime)
+	if orderRule != "" {
+		order = ` ORDER BY ` + orderRule
+	}
+	sql := fmt.Sprintf(`SELECT %s FROM %s WHERE 1=1 %s %s`, fields, m.TableName(), condition, order)
+	_, err = o.Raw(sql, pars).QueryRows(&items)
+	return
+}
+
+func (m *FactorEdbSeriesMapping) GetPageItemsByCondition(condition string, pars []interface{}, fieldArr []string, orderRule string, startSize, pageSize int) (items []*FactorEdbSeriesMapping, err error) {
+	o := orm.NewOrm()
+	fields := strings.Join(fieldArr, ",")
+	if len(fieldArr) == 0 {
+		fields = `*`
+	}
+	order := fmt.Sprintf(`ORDER BY %s DESC`, m.Cols().CreateTime)
+	if orderRule != "" {
+		order = ` ORDER BY ` + orderRule
+	}
+	sql := fmt.Sprintf(`SELECT %s FROM %s WHERE 1=1 %s %s LIMIT ?,?`, fields, m.TableName(), condition, order)
+	_, err = o.Raw(sql, pars, startSize, pageSize).QueryRows(&items)
+	return
+}
+
+// FactorEdbSeriesMappingItem 因子指标系列-指标关联信息
+type FactorEdbSeriesMappingItem struct {
+	SeriesId  int    `description:"因子指标系列ID"`
+	EdbInfoId int    `description:"指标ID"`
+	EdbCode   string `description:"指标编码"`
+	EdbName   string `description:"指标名称"`
+	EdbNameEn string `description:"指标名称-英文"`
+}
+
+func (m *FactorEdbSeriesMapping) Format2Item() (item *FactorEdbSeriesMappingItem) {
+	item = new(FactorEdbSeriesMappingItem)
+	item.SeriesId = m.FactorEdbSeriesId
+	item.EdbInfoId = m.EdbInfoId
+	item.EdbCode = m.EdbCode
+	return
+}

routers/commentsRouter.go

@@ -7,6 +7,24 @@ import (
 
 func init() {
 
+    beego.GlobalControllerRouter["eta/eta_index_lib/controllers/factor_edb_series:FactorEdbSeriesController"] = append(beego.GlobalControllerRouter["eta/eta_index_lib/controllers/factor_edb_series:FactorEdbSeriesController"],
+        beego.ControllerComments{
+            Method: "ChartRecalculate",
+            Router: `/chart_recalculate`,
+            AllowHTTPMethods: []string{"post"},
+            MethodParams: param.Make(),
+            Filters: nil,
+            Params: nil})
+
+    beego.GlobalControllerRouter["eta/eta_index_lib/controllers/factor_edb_series:FactorEdbSeriesController"] = append(beego.GlobalControllerRouter["eta/eta_index_lib/controllers/factor_edb_series:FactorEdbSeriesController"],
+        beego.ControllerComments{
+            Method: "Recalculate",
+            Router: `/recalculate`,
+            AllowHTTPMethods: []string{"post"},
+            MethodParams: param.Make(),
+            Filters: nil,
+            Params: nil})
+
     beego.GlobalControllerRouter["eta/eta_index_lib/controllers/fix:CustomAnalysisController"] = append(beego.GlobalControllerRouter["eta/eta_index_lib/controllers/fix:CustomAnalysisController"],
         beego.ControllerComments{
             Method: "FixTableV1",
@@ -232,6 +250,15 @@ func init() {
             Filters: nil,
             Params: nil})
 
+    beego.GlobalControllerRouter["eta/eta_index_lib/controllers:CalculateController"] = append(beego.GlobalControllerRouter["eta/eta_index_lib/controllers:CalculateController"],
+        beego.ControllerComments{
+            Method: "StepCalculate",
+            Router: `/base/step_calculate`,
+            AllowHTTPMethods: []string{"post"},
+            MethodParams: param.Make(),
+            Filters: nil,
+            Params: nil})
+
     beego.GlobalControllerRouter["eta/eta_index_lib/controllers:CalculateController"] = append(beego.GlobalControllerRouter["eta/eta_index_lib/controllers:CalculateController"],
         beego.ControllerComments{
             Method: "BatchEdit",

routers/router.go

@@ -9,6 +9,7 @@ package routers
 
 import (
 	"eta/eta_index_lib/controllers"
+	"eta/eta_index_lib/controllers/factor_edb_series"
 	"eta/eta_index_lib/controllers/fix"
 	"eta/eta_index_lib/controllers/future_good"
 	"eta/eta_index_lib/controllers/open"
@@ -275,6 +276,11 @@ func init() {
 				&controllers.ShanghaiSmmController{},
 			),
 		),
+		beego.NSNamespace("/factor_edb_series",
+			beego.NSInclude(
+				&factor_edb_series.FactorEdbSeriesController{},
+			),
+		),
 	)
 	beego.AddNamespace(ns)
 }

services/base_from_calculate.go

@@ -5,6 +5,7 @@ import (
 	"eta/eta_index_lib/models"
 	"eta/eta_index_lib/utils"
 	"fmt"
+	"sort"
 	"strconv"
 	"strings"
 	"time"
@@ -1009,3 +1010,79 @@ func EdbCalculateAdd(req models.EdbInfoCalculateSaveReq, lang string) (edbInfo *
 
 	return
 }
+
+// StepCalculate 多公式计算
+func StepCalculate(dataList []*models.EdbInfoSearchData, calculates []models.CalculatesReq) (resultData map[string]float64, dates []string, errMsg string, err error) {
+	sort.Slice(calculates, func(i, j int) bool {
+		return calculates[i].Sort < calculates[j].Sort
+	})
+	originData, e := models.EdbInfoSearchDataToData(dataList)
+	if e != nil {
+		err = fmt.Errorf("基础数据转换异常, err: %v", e)
+		return
+	}
+
+	calculateData := originData
+	dateDataMap := make(map[time.Time]float64)
+	for _, v := range calculates {
+		baseCalculate := models.BaseCalculate{
+			DataList:      calculateData,
+			Frequency:     v.Frequency,
+			Formula:       v.Formula,
+			Calendar:      v.Calendar,
+			MoveType:      v.MoveType,
+			MoveFrequency: v.MoveFrequency,
+			FromFrequency: v.FromFrequency,
+			Source:        v.Source,
+		}
+
+		// 计算方式
+		switch baseCalculate.Source {
+		case utils.EdbBaseCalculateLjzzy:
+			dateDataMap, e, errMsg = baseCalculate.Ljzzy()
+		case utils.EdbBaseCalculateLjzzj:
+			dateDataMap, e, errMsg = baseCalculate.Ljzzj()
+		case utils.EdbBaseCalculateTbz:
+			dateDataMap, e, errMsg = baseCalculate.Tbz()
+		case utils.EdbBaseCalculateTcz:
+			dateDataMap, e, errMsg = baseCalculate.Tcz()
+		case utils.EdbBaseCalculateNszydpjjs:
+			dateDataMap, e, errMsg = baseCalculate.Nszydpjjs()
+		case utils.EdbBaseCalculateHbz:
+			dateDataMap, e, errMsg = baseCalculate.Hbz()
+		case utils.EdbBaseCalculateHcz:
+			dateDataMap, e, errMsg = baseCalculate.Hcz()
+		case utils.EdbBaseCalculateUpFrequency:
+			dateDataMap, e, errMsg = baseCalculate.UpFrequency()
+		case utils.EdbBaseCalculateDownFrequency:
+			dateDataMap, e, errMsg = baseCalculate.DownFrequency()
+		case utils.EdbBaseCalculateTimeShift:
+			dateDataMap, e, errMsg = baseCalculate.TimeShift()
+		case utils.EdbBaseCalculateCjjx:
+			dateDataMap, e, errMsg = baseCalculate.Cjjx()
+		case utils.EdbBaseCalculateAnnualized:
+			dateDataMap, e, errMsg = baseCalculate.Annualized()
+		case utils.EdbBaseCalculateLjz:
+			dateDataMap, e, errMsg = baseCalculate.Ljz()
+		case utils.EdbBaseCalculateLjzNczj:
+			dateDataMap, e, errMsg = baseCalculate.LjzNczj()
+		case utils.EdbBaseCalculateExponentialSmoothing:
+			dateDataMap, e, errMsg = baseCalculate.ExponentialSmoothing()
+		case utils.EdbBaseCalculateRjz:
+			dateDataMap, e, errMsg = baseCalculate.Rjz()
+		default:
+			errMsg = "计算方式无效"
+			e = fmt.Errorf("%s:%d", errMsg, baseCalculate.Source)
+		}
+		if e != nil {
+			err = fmt.Errorf("计算失败, err: %v", e)
+			return
+		}
+
+		calculateData = models.TransDateData2EdbData(dateDataMap)
+	}
+	resultData, dates = models.GetDateDataAndDateList(dateDataMap)
+	//resp.DataMap = resultData
+	//resp.DateList = dates
+	return
+}

services/factor_edb_series.go

@@ -0,0 +1,75 @@
+package services
+
+import (
+	"eta/eta_index_lib/models"
+	"eta/eta_index_lib/services/alarm_msg"
+	"eta/eta_index_lib/utils"
+	"fmt"
+	"time"
+)
+
+// FactorEdbStepCalculate 因子指标-多公式计算
+func FactorEdbStepCalculate(seriesId, edbInfoId int, edbCode string, edbData []*models.EdbInfoSearchData, calculates []models.CalculatesReq) (err error) {
+	if len(edbData) == 0 || len(calculates) == 0 {
+		return
+	}
+	defer func() {
+		if err != nil {
+			tips := fmt.Sprintf("FactorEdbStepCalculate计算失败, EdbCode: %s, ErrMsg: %v", edbCode, err)
+			utils.FileLog.Info(tips)
+			go alarm_msg.SendAlarmMsg(tips, 2)
+		}
+	}()
+
+	// 重新计算-先清除原数据
+	calculateDataOb := new(models.FactorEdbSeriesCalculateData)
+	{
+		cond := fmt.Sprintf("%s = ?", calculateDataOb.Cols().FactorEdbSeriesId)
+		pars := make([]interface{}, 0)
+		pars = append(pars, seriesId)
+		if e := calculateDataOb.RemoveByCondition(cond, pars); e != nil {
+			err = fmt.Errorf("清除原数据失败, err: %v", e)
+			return
+		}
+	}
+
+	// 多公式嵌套计算
+	dataMap, dateList, _, e := StepCalculate(edbData, calculates)
+	if e != nil {
+		err = fmt.Errorf("嵌套计算失败, err: %v", e)
+		return
+	}
+
+	// 计算成功的保存结果
+	dataArr := make([]*models.FactorEdbSeriesCalculateData, 0)
+	for _, d := range dateList {
+		val, ok := dataMap[d]
+		if !ok {
+			continue
+		}
+		dataTime, e := time.ParseInLocation(utils.FormatDate, d, time.Local)
+		if e != nil {
+			err = fmt.Errorf("解析计算结果日期失败, err: %v", e)
+			return
+		}
+		dataArr = append(dataArr, &models.FactorEdbSeriesCalculateData{
+			FactorEdbSeriesId: seriesId,
+			EdbInfoId:         edbInfoId,
+			EdbCode:           edbCode,
+			DataTime:          dataTime,
+			Value:             val,
+			CreateTime:        time.Now().Local(),
+			ModifyTime:        time.Now().Local(),
+			DataTimestamp:     dataTime.UnixNano() / 1e6,
+		})
+	}
+	if len(dataArr) == 0 {
+		//err = fmt.Errorf("计算结果无数据")
+		return
+	}
+	if e = calculateDataOb.CreateMulti(dataArr); e != nil {
+		err = fmt.Errorf("保存计算结果失败, err: %v", e)
+		return
+	}
+	return
+}

utils/calculate.go

@@ -50,6 +50,54 @@ func GetLinearResult(s []Coordinate) (gradient, intercept float64) {
 	return
 }
 
+// CalculateCorrelationByIntArr 相关性计算
+// 计算步骤
+// 1.分别计算两个序列的平均值Mx和My
+// 2.分别计算两个序列的标准偏差SDx和SDy	=> √{1/(n-1)*SUM[(Xi-Mx)²]}
+// 3.计算相关系数	=> SUM[(Xi-Mx)*(Yi-My)]/[(N-1)(SDx*SDy)]
+func CalculateCorrelationByIntArr(xArr, yArr []float64) (ratio float64) {
+	// 序列元素数要一致
+	xLen := float64(len(xArr))
+	yLen := float64(len(yArr))
+	if xLen == 0 || xLen != yLen {
+		return
+	}
+
+	// 计算Mx和My
+	var Xa, Ya float64
+	for i := range xArr {
+		Xa += xArr[i]
+	}
+	Mx := Xa / xLen
+	for i := range yArr {
+		Ya += yArr[i]
+	}
+	My := Ya / yLen
+
+	// 计算标准偏差SDx和SDy
+	var Xb, Yb, SDx, SDy float64
+	for i := range xArr {
+		Xb += (xArr[i] - Mx) * (xArr[i] - Mx)
+	}
+	SDx = math.Sqrt(1 / (xLen - 1) * Xb)
+	for i := range yArr {
+		Yb += (yArr[i] - My) * (yArr[i] - My)
+	}
+	SDy = math.Sqrt(1 / (yLen - 1) * Yb)
+
+	// 计算相关系数
+	var Nume, Deno float64
+	for i := 0; i < int(xLen); i++ {
+		Nume += (xArr[i] - Mx) * (yArr[i] - My)
+	}
+	Deno = (xLen - 1) * (SDx * SDy)
+	ratio = Nume / Deno
+	if math.IsNaN(ratio) {
+		ratio = 0
+	}
+	return
+}
+
 // ComputeCorrelation 通过一组数据获取相关系数R
 // 计算步骤
 // 1.分别计算两个序列的平均值Mx和My

utils/constants.go

@@ -113,80 +113,80 @@ const (
 
 // 指标来源的中文展示
 const (
-	DATA_SOURCE_NAME_THS                                  = `同花顺`                //同花顺
-	DATA_SOURCE_NAME_WIND                                 = `wind`                  //wind
-	DATA_SOURCE_NAME_PB                                   = `彭博`                  //彭博
+	DATA_SOURCE_NAME_THS                                  = `同花顺`               //同花顺
+	DATA_SOURCE_NAME_WIND                                 = `wind`              //wind
+	DATA_SOURCE_NAME_PB                                   = `彭博`                //彭博
 	DATA_SOURCE_NAME_CALCULATE                            = `指标运算`              //指标运算
-	DATA_SOURCE_NAME_CALCULATE_LJZZY                      = `累计值转月值`          //累计值转月
-	DATA_SOURCE_NAME_CALCULATE_TBZ                        = `同比值`                //同比值
-	DATA_SOURCE_NAME_CALCULATE_TCZ                        = `同差值`                //同差值
-	DATA_SOURCE_NAME_CALCULATE_NSZYDPJJS                  = `N数值移动平均计算`     //N数值移动平均计算
+	DATA_SOURCE_NAME_CALCULATE_LJZZY                      = `累计值转月值`            //累计值转月
+	DATA_SOURCE_NAME_CALCULATE_TBZ                        = `同比值`               //同比值
+	DATA_SOURCE_NAME_CALCULATE_TCZ                        = `同差值`               //同差值
+	DATA_SOURCE_NAME_CALCULATE_NSZYDPJJS                  = `N数值移动平均计算`         //N数值移动平均计算
 	DATA_SOURCE_NAME_MANUAL                               = `手工数据`              //手工指标
-	DATA_SOURCE_NAME_LZ                                   = `隆众`                  //隆众
-	DATA_SOURCE_NAME_YS                                   = `SMM`                   //有色
-	DATA_SOURCE_NAME_CALCULATE_HBZ                        = `环比值`                //环比值->12
-	DATA_SOURCE_NAME_CALCULATE_HCZ                        = `环差值`                //环差值->13
-	DATA_SOURCE_NAME_CALCULATE_BP                         = `升频`                  //变频,2023-2-10 13:56:01调整为"升频"->14
-	DATA_SOURCE_NAME_GL                                   = `钢联`                  //钢联->15
-	DATA_SOURCE_NAME_ZZ                                   = `郑商所`                //郑商所->16
-	DATA_SOURCE_NAME_DL                                   = `大商所`                //大商所->17
-	DATA_SOURCE_NAME_SH                                   = `上期所`                //上期所->18
-	DATA_SOURCE_NAME_CFFEX                                = `中金所`                //中金所->19
+	DATA_SOURCE_NAME_LZ                                   = `隆众`                //隆众
+	DATA_SOURCE_NAME_YS                                   = `SMM`               //有色
+	DATA_SOURCE_NAME_CALCULATE_HBZ                        = `环比值`               //环比值->12
+	DATA_SOURCE_NAME_CALCULATE_HCZ                        = `环差值`               //环差值->13
+	DATA_SOURCE_NAME_CALCULATE_BP                         = `升频`                //变频,2023-2-10 13:56:01调整为"升频"->14
+	DATA_SOURCE_NAME_GL                                   = `钢联`                //钢联->15
+	DATA_SOURCE_NAME_ZZ                                   = `郑商所`               //郑商所->16
+	DATA_SOURCE_NAME_DL                                   = `大商所`               //大商所->17
+	DATA_SOURCE_NAME_SH                                   = `上期所`               //上期所->18
+	DATA_SOURCE_NAME_CFFEX                                = `中金所`               //中金所->19
 	DATA_SOURCE_NAME_SHFE                                 = `上期能源`              //上期能源->20
-	DATA_SOURCE_NAME_GIE                                  = `欧洲天然气`            //欧洲天然气->21
+	DATA_SOURCE_NAME_GIE                                  = `欧洲天然气`             //欧洲天然气->21
 	DATA_SOURCE_NAME_CALCULATE_TIME_SHIFT                 = `时间移位`              //时间移位->22
 	DATA_SOURCE_NAME_CALCULATE_ZJPJ                       = `直接拼接`              //直接拼接->23
-	DATA_SOURCE_NAME_CALCULATE_LJZTBPJ                    = `累计值同比拼接`        //累计值同比拼接->24
-	DATA_SOURCE_NAME_LT                                   = `路透`                  //路透->25
-	DATA_SOURCE_NAME_COAL                                 = `中国煤炭市场网`        //中国煤炭市场网->26
+	DATA_SOURCE_NAME_CALCULATE_LJZTBPJ                    = `累计值同比拼接`           //累计值同比拼接->24
+	DATA_SOURCE_NAME_LT                                   = `路透`                //路透->25
+	DATA_SOURCE_NAME_COAL                                 = `中国煤炭市场网`           //中国煤炭市场网->26
 	DATA_SOURCE_NAME_PYTHON                               = `代码运算`              //python代码->27
 	DATA_SOURCE_NAME_PB_FINANCE                           = `彭博财务`              //彭博财务数据->28
-	DATA_SOURCE_NAME_GOOGLE_TRAVEL                        = `our world in data`     //谷歌出行数据->29
+	DATA_SOURCE_NAME_GOOGLE_TRAVEL                        = `our world in data` //谷歌出行数据->29
 	DATA_SOURCE_NAME_PREDICT                              = `预测指标`              //普通预测指标->30
-	DATA_SOURCE_NAME_PREDICT_CALCULATE                    = `预测指标运算`          //预测指标运算->31
+	DATA_SOURCE_NAME_PREDICT_CALCULATE                    = `预测指标运算`            //预测指标运算->31
 	DATA_SOURCE_NAME_PREDICT_CALCULATE_TBZ                = `预测同比`              //预测指标 - 同比值->32
 	DATA_SOURCE_NAME_PREDICT_CALCULATE_TCZ                = `预测同差`              //预测指标 - 同差值->33
 	DATA_SOURCE_NAME_MYSTEEL_CHEMICAL                     = `钢联化工`              //钢联化工->34
 	DATA_SOURCE_NAME_CALCULATE_CJJX                       = `超季节性`              //超季节性->35
-	DATA_SOURCE_NAME_EIA_STEO                             = `EIA STERO报告`         //eia stero报告->36
+	DATA_SOURCE_NAME_EIA_STEO                             = `EIA STERO报告`       //eia stero报告->36
 	DATA_SOURCE_NAME_CALCULATE_NHCC                       = `拟合残差`              //计算指标（拟合残差）->37
-	DATA_SOURCE_NAME_COM_TRADE                            = `UN`                    //联合国商品贸易数据->38
-	DATA_SOURCE_NAME_PREDICT_CALCULATE_NSZYDPJJS          = `预测N数值移动平均计算` //预测指标 - N数值移动平均计算 -> 39
+	DATA_SOURCE_NAME_COM_TRADE                            = `UN`                //联合国商品贸易数据->38
+	DATA_SOURCE_NAME_PREDICT_CALCULATE_NSZYDPJJS          = `预测N数值移动平均计算`       //预测指标 - N数值移动平均计算 -> 39
 	DATA_SOURCE_NAME_CALCULATE_ADJUST                     = `数据调整`              //数据调整->40
-	DATA_SOURCE_NAME_SCI                                  = `SCI`                   //卓创数据（红桃三）->41
-	DATA_SOURCE_NAME_PREDICT_CALCULATE_LJZZY              = `预测累计值转月值`      //预测指标 - 累计值转月->42
-	DATA_SOURCE_NAME_PREDICT_CALCULATE_HBZ                = `预测环比值`            //预测指标 - 环比值->43
-	DATA_SOURCE_NAME_PREDICT_CALCULATE_HCZ                = `预测环差值`            //预测指标 - 环差值->44
+	DATA_SOURCE_NAME_SCI                                  = `SCI`               //卓创数据（红桃三）->41
+	DATA_SOURCE_NAME_PREDICT_CALCULATE_LJZZY              = `预测累计值转月值`          //预测指标 - 累计值转月->42
+	DATA_SOURCE_NAME_PREDICT_CALCULATE_HBZ                = `预测环比值`             //预测指标 - 环比值->43
+	DATA_SOURCE_NAME_PREDICT_CALCULATE_HCZ                = `预测环差值`             //预测指标 - 环差值->44
 	DATA_SOURCE_NAME_PREDICT_CALCULATE_BP                 = `预测升频`              //预测指标 - 升频->45
-	DATA_SOURCE_NAME_PREDICT_CALCULATE_TIME_SHIFT         = `预测时间移位`          //预测指标 - 时间移位->46
-	DATA_SOURCE_NAME_PREDICT_CALCULATE_ZJPJ               = `预测直接拼接`          //预测指标 - 直接拼接->47
-	DATA_SOURCE_NAME_PREDICT_CALCULATE_LJZTBPJ            = `预测累计值同比拼接`    //预测指标 - 累计值同比拼接->48
-	DATA_SOURCE_NAME_PREDICT_CALCULATE_CJJX               = `预测超季节性`          //预测指标 - 超季节性->49
-	DATA_SOURCE_NAME_PREDICT_CALCULATE_NHCC               = `预测拟合残差`          //预测指标 - 计算指标（拟合残差）->50
-	DATA_SOURCE_NAME_CALCULATE_JP                         = `降频`                  //降频->51
-	DATA_SOURCE_NAME_CALCULATE_NH                         = `年化`                  //年化->52
+	DATA_SOURCE_NAME_PREDICT_CALCULATE_TIME_SHIFT         = `预测时间移位`            //预测指标 - 时间移位->46
+	DATA_SOURCE_NAME_PREDICT_CALCULATE_ZJPJ               = `预测直接拼接`            //预测指标 - 直接拼接->47
+	DATA_SOURCE_NAME_PREDICT_CALCULATE_LJZTBPJ            = `预测累计值同比拼接`         //预测指标 - 累计值同比拼接->48
+	DATA_SOURCE_NAME_PREDICT_CALCULATE_CJJX               = `预测超季节性`            //预测指标 - 超季节性->49
+	DATA_SOURCE_NAME_PREDICT_CALCULATE_NHCC               = `预测拟合残差`            //预测指标 - 计算指标（拟合残差）->50
+	DATA_SOURCE_NAME_CALCULATE_JP                         = `降频`                //降频->51
+	DATA_SOURCE_NAME_CALCULATE_NH                         = `年化`                //年化->52
 	DATA_SOURCE_NAME_CALCULATE_KSZS                       = `扩散指数`              //扩散指数->53
 	DATA_SOURCE_NAME_PREDICT_CALCULATE_JP                 = `预测降频`              //预测指标 - 计算指标(降频)->54
 	DATA_SOURCE_NAME_PREDICT_CALCULATE_NH                 = `预测年化`              //预测指标 - 计算指标(年化)->55
-	DATA_SOURCE_NAME_PREDICT_CALCULATE_KSZS               = `预测扩散指数`          //预测指标 - 计算指标(扩散指数)->56
+	DATA_SOURCE_NAME_PREDICT_CALCULATE_KSZS               = `预测扩散指数`            //预测指标 - 计算指标(扩散指数)->56
 	DATA_SOURCE_NAME_BAIINFO                              = `百川盈孚`              //百川盈孚 ->57
 	DATA_SOURCE_NAME_STOCK_PLANT                          = `存量装置`              //存量装置 ->58
-	DATA_SOURCE_NAME_CALCULATE_CORRELATION                = `相关性计算`            //相关性计算->59
-	DATA_SOURCE_NAME_NATIONAL_STATISTICS                  = `国家统计局`            //国家统计局->60
-	DATA_SOURCE_NAME_CALCULATE_LJZZJ                      = `累计值转季值`          //累计值转季 -> 61
-	DATA_SOURCE_NAME_CALCULATE_LJZ                        = `累计值`                //累计值 -> 62
-	DATA_SOURCE_NAME_CALCULATE_LJZNCZJ                    = `年初至今累计值`        //累计值(年初至今） -> 63
-	DATA_SOURCE_NAME_PREDICT_CALCULATE_LJZZJ              = `预测累计值转季值`      //预测指标 - 累计值转季->64
-	DATA_SOURCE_NAME_PREDICT_CALCULATE_LJZ                = `预测累计值`            //预测指标 - 累计值 -> 65
-	DATA_SOURCE_NAME_PREDICT_CALCULATE_LJZNCZJ            = `预测年初至今累计值`    //预测指标 - 累计值(年初至今） -> 66
-	DATA_SOURCE_NAME_CALCULATE_STANDARD_DEVIATION         = `标准差`                //标准差->67
-	DATA_SOURCE_NAME_CALCULATE_PERCENTILE                 = `百分位`                //百分位->68
-	DATA_SOURCE_NAME_PREDICT_CALCULATE_STANDARD_DEVIATION = `预测标准差`            //预测标准差->69
-	DATA_SOURCE_NAME_PREDICT_CALCULATE_PERCENTILE         = `预测百分位`            //预测百分位->70
+	DATA_SOURCE_NAME_CALCULATE_CORRELATION                = `相关性计算`             //相关性计算->59
+	DATA_SOURCE_NAME_NATIONAL_STATISTICS                  = `国家统计局`             //国家统计局->60
+	DATA_SOURCE_NAME_CALCULATE_LJZZJ                      = `累计值转季值`            //累计值转季 -> 61
+	DATA_SOURCE_NAME_CALCULATE_LJZ                        = `累计值`               //累计值 -> 62
+	DATA_SOURCE_NAME_CALCULATE_LJZNCZJ                    = `年初至今累计值`           //累计值(年初至今） -> 63
+	DATA_SOURCE_NAME_PREDICT_CALCULATE_LJZZJ              = `预测累计值转季值`          //预测指标 - 累计值转季->64
+	DATA_SOURCE_NAME_PREDICT_CALCULATE_LJZ                = `预测累计值`             //预测指标 - 累计值 -> 65
+	DATA_SOURCE_NAME_PREDICT_CALCULATE_LJZNCZJ            = `预测年初至今累计值`         //预测指标 - 累计值(年初至今） -> 66
+	DATA_SOURCE_NAME_CALCULATE_STANDARD_DEVIATION         = `标准差`               //标准差->67
+	DATA_SOURCE_NAME_CALCULATE_PERCENTILE                 = `百分位`               //百分位->68
+	DATA_SOURCE_NAME_PREDICT_CALCULATE_STANDARD_DEVIATION = `预测标准差`             //预测标准差->69
+	DATA_SOURCE_NAME_PREDICT_CALCULATE_PERCENTILE         = `预测百分位`             //预测百分位->70
 	DATA_SOURCE_NAME_FUBAO                                = `富宝数据`              //富宝数据->71
 	DATA_SOURCE_NAME_CALCULATE_ZSXY                       = `指数修匀`              //指数修匀->72
-	DATA_SOURCE_NAME_PREDICT_CALCULATE_ZSXY               = `预测指数修匀`          //预测指数修匀->73
-	DATA_SOURCE_NAME_CALCULATE_ZDYFX                      = `自定义分析`            //自定义分析->74
+	DATA_SOURCE_NAME_PREDICT_CALCULATE_ZSXY               = `预测指数修匀`            //预测指数修匀->73
+	DATA_SOURCE_NAME_CALCULATE_ZDYFX                      = `自定义分析`             //自定义分析->74
 	DATA_SOURCE_NAME_YONYI                                = `涌益咨询`              // 涌益咨询
 	DATA_SOURCE_NAME_FENWEI                               = `汾渭数据`              // 汾渭煤炭
 	DATA_SOURCE_NAME_MTJH                                 = `煤炭江湖`              // 煤炭江湖->80
@@ -293,3 +293,23 @@ const (
 	PercentCalculateTypeRange = 0 // 百分位算法类型-数据区间
 	PercentCalculateTypeNum   = 1 // 百分位算法类型-数据个数
 )
+
+// 指标计算方式
+const (
+	EdbBaseCalculateLjzzy                = 1  // 累计值转月->1
+	EdbBaseCalculateLjzzj                = 2  // 累计值转季->2
+	EdbBaseCalculateTbz                  = 3  // 同比值->3
+	EdbBaseCalculateTcz                  = 4  // 同差值->4
+	EdbBaseCalculateNszydpjjs            = 5  // N数值移动平均数计算->5
+	EdbBaseCalculateHbz                  = 6  // 环比值->6
+	EdbBaseCalculateHcz                  = 7  // 环差值->7
+	EdbBaseCalculateUpFrequency          = 8  // 升频->8
+	EdbBaseCalculateDownFrequency        = 9  // 降频->9
+	EdbBaseCalculateTimeShift            = 10 // 时间移位->10
+	EdbBaseCalculateCjjx                 = 11 // 超季节性->11
+	EdbBaseCalculateAnnualized           = 12 // 年化->12
+	EdbBaseCalculateLjz                  = 13 // 累计值->13
+	EdbBaseCalculateLjzNczj              = 14 // 累计值年初至今->14
+	EdbBaseCalculateExponentialSmoothing = 15 // 指数修匀->15
+	EdbBaseCalculateRjz                  = 16 // 日均值->16
+)