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@@ -0,0 +1,234 @@
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+package services
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+
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+import (
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+ "errors"
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+ "eta/eta_index_lib/models"
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+ "eta/eta_index_lib/utils"
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+ "fmt"
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+ "github.com/shopspring/decimal"
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+ "github.com/yidane/formula"
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+ "strconv"
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+ "strings"
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+ "time"
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+)
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+
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+// GetCalculateByRuleByNineParams 获取预测规则9的计算参数
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+func GetCalculateByRuleByNineParams(req models.RuleConfig) (formula string, edbInfoList []*models.EdbInfo, edbInfoIdBytes []string, err error, errMsg string) {
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+ formula = req.Value
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+ formula = strings.Replace(formula, "（", "(", -1)
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+ formula = strings.Replace(formula, "）", ")", -1)
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+ formula = strings.Replace(formula, "，", ",", -1)
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+ formula = strings.Replace(formula, "。", ".", -1)
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+ formula = strings.Replace(formula, "%", "*0.01", -1)
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+
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+ //检验公式
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+ var checkFormulaStr string
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+ for _, tmpEdbInfoId := range req.EdbInfoIdArr {
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+ checkFormulaStr += tmpEdbInfoId.FromTag + ","
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+ edbInfoIdBytes = append(edbInfoIdBytes, tmpEdbInfoId.FromTag)
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+ }
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+
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+ formulaSlice, err := utils.CheckFormulaJson(formula)
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+ if err != nil {
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+ errMsg = "公式格式错误，请重新填写"
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+ err = errors.New(errMsg)
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+ return
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+ }
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+ for _, f := range formulaSlice {
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+ formulaMap := utils.CheckFormula(f)
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+ for _, v := range formulaMap {
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+ if !strings.Contains(checkFormulaStr, v) {
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+ errMsg = "公式错误，请重新填写"
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+ err = errors.New(errMsg)
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+ return
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+ }
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+ }
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+ }
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+
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+ //关联的指标信息
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+ edbInfoList = make([]*models.EdbInfo, 0)
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+
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+ for _, tmpEdbInfoId := range req.EdbInfoIdArr {
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+ fromEdbInfo, tmpErr := models.GetEdbInfoById(tmpEdbInfoId.EdbInfoId)
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+ if tmpErr != nil {
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+ if tmpErr.Error() == utils.ErrNoRow() {
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+ err = errors.New("指标 " + strconv.Itoa(tmpEdbInfoId.EdbInfoId) + " 不存在")
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+ } else {
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+ err = errors.New("获取指标失败:Err:" + tmpErr.Error())
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+ }
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+ errMsg = "数据计算失败"
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+ return
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+ }
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+ edbInfoList = append(edbInfoList, fromEdbInfo)
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+ }
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+
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+ for _, v := range formulaSlice {
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+ formulaMap := utils.CheckFormula(v)
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+ //预先计算，判断公式是否正常
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+ ok, _ := models.CheckFormula2(edbInfoList, formulaMap, v, edbInfoIdBytes)
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+ if !ok {
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+ errMsg = "生成计算指标失败，请使用正确的计算公式"
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+ err = errors.New(errMsg)
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+ return
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+ }
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+ }
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+
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+ return
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+}
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+
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+// CalculateByRuleByNine 动态环差规则计算入库
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+func CalculateByRuleByNine(formulaStr string, edbInfoList []*models.EdbInfo, edbInfoIdBytes []string, emptyType, maxEmptyType int) (dataList []*models.EdbDataList, err error) {
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+ realSaveDataMap := make(map[string]map[int]float64)
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+ saveDataMap := make(map[string]map[int]float64)
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+ dateList := make([]string, 0) //日期
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+
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+ // 最小的结束日期 , 最晚的数据开始日期
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+ var minLatestDate, maxStartDate time.Time
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+ formulaStr = strings.ToUpper(formulaStr)
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+ // 获取关联指标数据
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+ for edbInfoIndex, v := range edbInfoList {
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+ // todo eta_api和eta_index_lib两个函数的逻辑不一致
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+ sourceDataList, tmpErr := models.GetPredictEdbDataListAll(v, 1)
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+ if tmpErr != nil {
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+ err = tmpErr
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+ return
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+ }
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+ dataMap := make(map[string]float64)
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+ lenData := len(sourceDataList)
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+ for _, dv := range sourceDataList {
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+ // 实际数据
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+ if val, ok := realSaveDataMap[dv.DataTime]; ok {
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+ if _, ok1 := val[v.EdbInfoId]; !ok1 {
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+ val[v.EdbInfoId] = dv.Value
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+ }
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+ } else {
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+ temp := make(map[int]float64)
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+ temp[v.EdbInfoId] = dv.Value
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+ realSaveDataMap[dv.DataTime] = temp
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+ }
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+
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+ // saveDataMap 待计算的数据
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+ if val, ok := saveDataMap[dv.DataTime]; ok {
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+ if _, ok1 := val[v.EdbInfoId]; !ok1 {
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+ val[v.EdbInfoId] = dv.Value
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+ }
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+ } else {
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+ temp2 := make(map[int]float64)
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+ temp2[v.EdbInfoId] = dv.Value
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+ saveDataMap[dv.DataTime] = temp2
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+ }
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+
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+ // 以第一个指标的日期作为基准日期
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+ if edbInfoIndex == 0 {
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+ dateList = append(dateList, dv.DataTime)
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+ }
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+
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+ if lenData > 0 {
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+ tmpLatestDate, _ := time.ParseInLocation(utils.FormatDate, sourceDataList[lenData-1].DataTime, time.Local)
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+ if minLatestDate.IsZero() || minLatestDate.After(tmpLatestDate) {
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+ minLatestDate = tmpLatestDate
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+ }
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+
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+ tmpStartDate, _ := time.ParseInLocation(utils.FormatDate, sourceDataList[0].DataTime, time.Local)
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+ if maxStartDate.IsZero() || maxStartDate.Before(tmpStartDate) {
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+ maxStartDate = tmpStartDate
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+ }
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+ }
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+ }
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+ item := new(models.CalculateItems)
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+ item.EdbInfoId = v.EdbInfoId
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+ item.DataMap = dataMap
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+ }
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+
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+ models.HandleDateSaveDataMap(dateList, maxStartDate, minLatestDate, realSaveDataMap, saveDataMap, edbInfoList, emptyType)
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+ // 添加数据
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+ dataList = make([]*models.EdbDataList, 0)
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+
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+ // 计算规则
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+ formulaDateSlice, formulaDateMap, err := utils.HandleFormulaJson(formulaStr, maxStartDate.Format(utils.FormatDate))
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+ if err != nil {
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+ return
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+ }
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+ existDataMap := make(map[string]string)
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+ // 判断是否特殊处理max和min函数
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+ maxDealFlag := false
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+ if emptyType == 4 && maxEmptyType == 2 {
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+ maxDealFlag = true
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+ }
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+ for k, date := range dateList {
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+ sv := saveDataMap[date]
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+ // 当空值处理类型选择了不计算时，只要有一个指标在某个日期没有值(即空值)，则计算指标在该日期没有值
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+ if emptyType == 1 {
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+ if len(sv) != len(edbInfoList) {
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+ continue
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+ }
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+ }
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+ //fmt.Println(sk, sv)
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+ // 根据时间范围，选择对应的公式
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+ formulaMap := make(map[string]string)
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+ formulaStr = ""
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+ for _, fv := range formulaDateSlice {
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+ if date >= fv {
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+ if f, ok := formulaDateMap[fv]; ok {
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+ formulaStr = f
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+ formulaMap = utils.CheckFormula(formulaStr)
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+ }
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+ break
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+ }
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+ }
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+ if formulaStr == "" {
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+ continue
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+ }
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+ svMax := make(map[int]float64)
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+ if maxDealFlag {
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+ // 特殊处理max和min函数，如果原本的值为空，则选择空值参与运算
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+ if svMaxData, ok := realSaveDataMap[date]; ok {
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+ svMax = svMaxData
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+ }
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+ }
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+
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+ //fmt.Println(date, sv)
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+
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+ formulaFormStr := models.ReplaceFormula(edbInfoList, sv, svMax, formulaMap, formulaStr, edbInfoIdBytes, maxDealFlag)
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+ if formulaFormStr == `` {
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+ //计算公式异常，那么就移除该指标
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+ continue
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+ }
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+
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+ //fmt.Println(fmt.Sprintf("formulaFormStr:%s", formulaFormStr))
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+ fmt.Println(fmt.Sprintf("%s:formulaFormStr:%s", date, formulaFormStr))
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+ expression := formula.NewExpression(formulaFormStr)
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+ calResult, tmpErr := expression.Evaluate()
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+ if tmpErr != nil {
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+ // 分母为0的报错
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+ if strings.Contains(tmpErr.Error(), "divide by zero") {
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+ continue
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+ }
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+ err = errors.New("计算失败：Err:" + tmpErr.Error() + ";formulaStr:" + formulaFormStr)
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+ return
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+ }
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+ calVal, tmpErr := calResult.Float64()
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+ if tmpErr != nil {
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+ err = errors.New("计算失败：获取计算值失败 Err:" + tmpErr.Error() + ";formulaStr:" + formulaFormStr)
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+ fmt.Println(err)
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+ return
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+ }
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+
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+ saveValue, _ := decimal.NewFromFloat(calVal).RoundCeil(4).Float64() //utils.SubFloatToString(calVal, 4)
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+ dataTime, _ := time.Parse(utils.FormatDate, date)
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+ timestamp := dataTime.UnixNano() / 1e6
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+
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+ if _, existOk := existDataMap[date]; !existOk {
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+ tmpPredictEdbRuleData := &models.EdbDataList{
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+ EdbDataId: k,
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+ EdbInfoId: 0,
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+ DataTime: date,
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+ DataTimestamp: timestamp,
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+ Value: saveValue,
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+ }
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+ dataList = append(dataList, tmpPredictEdbRuleData)
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+ }
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+ existDataMap[date] = date
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+ }
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+ return
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+}
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