package models import ( "encoding/json" "errors" "fmt" "github.com/beego/beego/v2/client/orm" "github.com/shopspring/decimal" "hongze/hongze_edb_lib/utils" "strconv" "strings" "time" ) // SavePredictCalculateKszs 预测扩散指数 func SavePredictCalculateKszs(reqEdbInfoId, classifyId int, edbName, frequency, unit, formula string, relationCalculateEdbInfoIdList []EdbInfoCalculateEdbInfoIdReq, edbCode, uniqueCode string, sysUserId int, sysUserRealName string) (edbInfo *EdbInfo, latestDateStr string, latestValue float64, err error, errMsg string) { o := orm.NewOrm() to, err := o.Begin() if err != nil { return } defer func() { if err != nil { fmt.Println("SavePredictCalculateKszs,Err:" + err.Error()) _ = to.Rollback() } else { _ = to.Commit() } }() fmt.Println("reqEdbInfoId:", reqEdbInfoId) tagMap := make(map[string]int) //指标的标签map relationEdbInfoList := make([]*EdbInfo, 0) if reqEdbInfoId <= 0 { edbInfo = &EdbInfo{ //EdbInfoId: 0, EdbInfoType: 1, SourceName: utils.DATA_SOURCE_NAME_PREDICT_CALCULATE_KSZS, Source: utils.DATA_SOURCE_PREDICT_CALCULATE_KSZS, EdbCode: edbCode, EdbName: edbName, EdbNameSource: edbName, Frequency: frequency, Unit: unit, //StartDate: "", //EndDate: "", ClassifyId: classifyId, SysUserId: sysUserId, SysUserRealName: sysUserRealName, UniqueCode: uniqueCode, CreateTime: time.Now(), ModifyTime: time.Now(), MinValue: 0, MaxValue: 0, CalculateFormula: formula, EdbType: 2, Sort: 0, MoveType: 0, MoveFrequency: "", NoUpdate: 0, ServerUrl: "", EdbNameEn: "", UnitEn: "", LatestDate: "", LatestValue: 0, ChartImage: "", } newEdbInfoId, tmpErr := to.Insert(edbInfo) if tmpErr != nil { err = tmpErr return } edbInfo.EdbInfoId = int(newEdbInfoId) //关联关系 calculateMappingItemList := make([]*EdbInfoCalculateMapping, 0) for _, v := range relationCalculateEdbInfoIdList { tmpEdbInfo, tmpErr := GetEdbInfoById(v.EdbInfoId) if tmpErr != nil { err = tmpErr return } relationEdbInfoList = append(relationEdbInfoList, tmpEdbInfo) calculateMappingItem := new(EdbInfoCalculateMapping) calculateMappingItem.CreateTime = time.Now() calculateMappingItem.ModifyTime = time.Now() calculateMappingItem.Sort = 1 calculateMappingItem.EdbCode = edbCode calculateMappingItem.EdbInfoId = edbInfo.EdbInfoId calculateMappingItem.FromEdbInfoId = tmpEdbInfo.EdbInfoId calculateMappingItem.FromEdbCode = tmpEdbInfo.EdbCode calculateMappingItem.FromEdbName = tmpEdbInfo.EdbName calculateMappingItem.FromSource = tmpEdbInfo.Source calculateMappingItem.FromSourceName = tmpEdbInfo.SourceName calculateMappingItem.FromTag = v.FromTag calculateMappingItem.Source = edbInfo.Source calculateMappingItem.SourceName = edbInfo.SourceName calculateMappingItemList = append(calculateMappingItemList, calculateMappingItem) tagMap[v.FromTag] = v.EdbInfoId } _, err = to.InsertMulti(len(calculateMappingItemList), calculateMappingItemList) if err != nil { return } } else { edbInfo, err = GetEdbInfoById(reqEdbInfoId) if err != nil { if err.Error() == utils.ErrNoRow() { errMsg = `获取指标信息失败` } return } if edbInfo.EdbInfoType != 1 { errMsg = `该指标不是预测指标` err = errors.New(errMsg) return } //修改指标信息 edbInfo.EdbName = edbName edbInfo.EdbNameSource = edbName edbInfo.Frequency = frequency edbInfo.Unit = unit edbInfo.ClassifyId = classifyId edbInfo.CalculateFormula = formula edbInfo.ModifyTime = time.Now() _, err = to.Update(edbInfo, "EdbName", "EdbNameSource", "Frequency", "Unit", "ClassifyId", "CalculateFormula", "ModifyTime") if err != nil { return } //删除,计算指标关联的,基础指标的关联关系 sql := ` DELETE FROM edb_info_calculate_mapping WHERE edb_info_id = ? ` _, err = to.Raw(sql, edbInfo.EdbInfoId).Exec() if err != nil { err = errors.New("删除计算指标关联关系失败,Err:" + err.Error()) return } //清空原有数据 tableName := GetEdbDataTableName(edbInfo.Source) sql = ` DELETE FROM ` + tableName + ` WHERE edb_info_id = ? ` _, err = to.Raw(sql, edbInfo.EdbInfoId).Exec() if err != nil { return } //关联关系 calculateMappingItemList := make([]*EdbInfoCalculateMapping, 0) for _, v := range relationCalculateEdbInfoIdList { tmpEdbInfo, tmpErr := GetEdbInfoById(v.EdbInfoId) if tmpErr != nil { err = tmpErr return } relationEdbInfoList = append(relationEdbInfoList, tmpEdbInfo) calculateMappingItem := new(EdbInfoCalculateMapping) calculateMappingItem.CreateTime = time.Now() calculateMappingItem.ModifyTime = time.Now() calculateMappingItem.Sort = 1 calculateMappingItem.EdbCode = edbInfo.EdbCode calculateMappingItem.EdbInfoId = edbInfo.EdbInfoId calculateMappingItem.FromEdbInfoId = tmpEdbInfo.EdbInfoId calculateMappingItem.FromEdbCode = tmpEdbInfo.EdbCode calculateMappingItem.FromEdbName = tmpEdbInfo.EdbName calculateMappingItem.FromSource = tmpEdbInfo.Source calculateMappingItem.FromSourceName = tmpEdbInfo.SourceName calculateMappingItem.FromTag = v.FromTag calculateMappingItem.Source = edbInfo.Source calculateMappingItem.SourceName = edbInfo.SourceName calculateMappingItemList = append(calculateMappingItemList, calculateMappingItem) tagMap[v.FromTag] = v.EdbInfoId } _, err = to.InsertMulti(len(calculateMappingItemList), calculateMappingItemList) if err != nil { return } } // 计算数据 latestDateStr, latestValue, err = refreshAllPredictCalculateKszs(to, edbInfo.EdbInfoId, edbInfo.Source, relationEdbInfoList, edbCode, formula, tagMap) return } // RefreshAllPredictCalculateKszs 刷新全部预测扩散指数数据 func RefreshAllPredictCalculateKszs(edbInfo *EdbInfo) (latestDateStr string, latestValue float64, err error) { edbInfoCalculateDetailList, err := GetEdbInfoCalculateDetailList(edbInfo.EdbInfoId) if err != nil { return } tagMap := make(map[string]int) relationEdbInfoList := make([]*EdbInfo, 0) for _, v := range edbInfoCalculateDetailList { tagMap[v.FromTag] = v.FromEdbInfoId fromEdbInfo, _ := GetEdbInfoById(v.FromEdbInfoId) relationEdbInfoList = append(relationEdbInfoList, fromEdbInfo) } o := orm.NewOrm() to, err := o.Begin() if err != nil { return } defer func() { if err != nil { fmt.Println("RefreshAllCalculateKszs,Err:" + err.Error()) _ = to.Rollback() } else { _ = to.Commit() } }() // 计算数据 latestDateStr, latestValue, err = refreshAllPredictCalculateKszs(to, edbInfo.EdbInfoId, edbInfo.Source, relationEdbInfoList, edbInfo.EdbCode, edbInfo.CalculateFormula, tagMap) return } // refreshAllPredictCalculateKszs 刷新预测年化数据 func refreshAllPredictCalculateKszs(to orm.TxOrmer, edbInfoId, source int, relationEdbInfoList []*EdbInfo, edbCode, calculateFormula string, tagMap map[string]int) (latestDateStr string, latestValue float64, err error) { edbInfoIdStr := strconv.Itoa(edbInfoId) tableName := GetEdbDataTableName(utils.DATA_SOURCE_PREDICT_CALCULATE_KSZS) // 获取扩散指标关联的指标id checkEdbInfoIdMap := make(map[int]int) { var config KszsConfig err = json.Unmarshal([]byte(calculateFormula), &config) if err != nil { return } if config.DateType == 1 { for _, tmpEdbInfoId := range tagMap { checkEdbInfoIdMap[tmpEdbInfoId] = tmpEdbInfoId } } else { for _, v := range config.CheckList { if tmpEdbInfoId, ok := tagMap[v]; ok { checkEdbInfoIdMap[tmpEdbInfoId] = tmpEdbInfoId } } } } //获取当前指标的所有数据 existDataList, err := GetAllEdbDataListByTo(to, edbInfoId, source) if err != nil { return } //计算指标的map existDataMap := make(map[string]*EdbData, 0) removeDateMap := make(map[string]string) for _, v := range existDataList { existDataMap[v.DataTime] = v removeDateMap[v.DataTime] = `` } var latestDateTime time.Time //真实数据的最后日期 var hasValLatestDateTime time.Time // 存在数据的真实日期(正常情况下,这两个值是相等的,除非出现一种情况:真实数据的最后日期当天 计算不出结果,那么 hasValLatestDateTime 不等于 latestDateTime) //获取来源指标的数据 relationEdbDataMap := make(map[int]map[string]float64) // 获取选择指标的 需要数据的 开始日期和结束日期 var startDate, endDate time.Time for _, v := range relationEdbInfoList { tmpLatestDate, _ := time.ParseInLocation(utils.FormatDate, v.LatestDate, time.Local) if latestDateTime.IsZero() || latestDateTime.After(tmpLatestDate) { // 真实数据的最后日期 latestDateTime = tmpLatestDate } tmpDataList, tmpErr := GetPredictEdbDataListAll(v, 1) if tmpErr != nil { err = tmpErr return } if tmpDataList != nil { if _, ok2 := checkEdbInfoIdMap[v.EdbInfoId]; ok2 { lenTmpDataList := len(tmpDataList) if lenTmpDataList > 0 { tmpStartTime, _ := time.ParseInLocation(utils.FormatDate, tmpDataList[0].DataTime, time.Local) tmpEndTime, _ := time.ParseInLocation(utils.FormatDate, tmpDataList[lenTmpDataList-1].DataTime, time.Local) if startDate.IsZero() || tmpStartTime.Before(startDate) { startDate = tmpStartTime } if tmpEndTime.IsZero() || tmpEndTime.After(endDate) { endDate = tmpEndTime } } } // 用上期的数据补充当期的数据处理 handleDataMap := make(map[string]float64) err = HandleDataByPreviousData(tmpDataList, handleDataMap) if err != nil { return } relationEdbDataMap[v.EdbInfoId] = handleDataMap } } addSql := ` INSERT INTO ` + tableName + ` (edb_info_id,edb_code,data_time,value,create_time,modify_time,data_timestamp) values ` var isAdd bool for currDate := startDate.AddDate(0, 0, 1); !currDate.After(endDate); currDate = currDate.AddDate(0, 0, 1) { currDateStr := currDate.Format(utils.FormatDate) //环差指数列表 tmpValList := make([]float64, 0) for _, dataMap := range relationEdbDataMap { currVal, ok := dataMap[currDateStr] if !ok { continue } perVal, ok := dataMap[currDate.AddDate(0, 0, -1).Format(utils.FormatDate)] if !ok { continue } var tmpVal float64 if currVal > perVal { tmpVal = 1 } else if currVal == perVal { tmpVal = 0.5 } else { tmpVal = 0 } tmpValList = append(tmpValList, tmpVal) } lenTmpValList := len(tmpValList) if lenTmpValList <= 0 { continue } currValDeci := decimal.NewFromFloat(0) for _, tmpVal := range tmpValList { currValDeci = currValDeci.Add(decimal.NewFromFloat(tmpVal)) } currVal, _ := currValDeci.Div(decimal.NewFromInt(int64(lenTmpValList))).Round(4).Float64() // 如果存在数据的真实日期为空,或者 当前日期 早于或等于 实际数据的日期,那么就给 存在数据的真实日期 赋值 if hasValLatestDateTime.IsZero() || currDate.Before(latestDateTime) || currDate.Equal(latestDateTime) { latestValue = currVal hasValLatestDateTime = currDate } // 判断扩散指数指标是否存在数据 if existData, ok := existDataMap[currDateStr]; ok { // 处理扩散指数数据的值 existValStr := existData.Value existValDeci, tmpErr := decimal.NewFromString(existValStr) if tmpErr != nil { err = tmpErr return } existVal, _ := existValDeci.Round(4).Float64() // 判断扩散指数数据的值 与 当前计算出来的结果, 如果两个数据结果不相等的话,那么就修改咯 if existVal != currVal { err = ModifyEdbDataById(source, existData.EdbDataId, fmt.Sprint(currVal)) if err != nil { return } } } else { // 直接入库 timestamp := currDate.UnixNano() / 1e6 timestampStr := fmt.Sprintf("%d", timestamp) addSql += GetAddSql(edbInfoIdStr, edbCode, currDateStr, timestampStr, fmt.Sprint(currVal)) isAdd = true } delete(removeDateMap, currDateStr) } if isAdd { addSql = strings.TrimRight(addSql, ",") _, err = to.Raw(addSql).Exec() } // 移除不存在的日期数据 if len(removeDateMap) > 0 { removeDateList := make([]string, 0) //需要移除的日期 for k := range removeDateMap { removeDateList = append(removeDateList, k) } removeDateStr := strings.Join(removeDateList, `","`) removeDateStr = `"` + removeDateStr + `"` sql := fmt.Sprintf(` DELETE FROM %s WHERE edb_info_id = ? and data_time in (%s) `, tableName, removeDateStr) _, err = to.Raw(sql, edbInfoId).Exec() if err != nil { err = fmt.Errorf("删除扩散指数指标数据失败,Err:" + err.Error()) return } } // 真实数据的最后日期 latestDateStr = hasValLatestDateTime.Format(utils.FormatDate) return }