package models import ( "errors" "eta_gn/eta_index_lib/global" "eta_gn/eta_index_lib/utils" "fmt" "github.com/shopspring/decimal" "gorm.io/gorm" "reflect" "strconv" "strings" "time" ) // ExponentialSmoothing 指数修匀 type ExponentialSmoothing struct{} // Add 添加 func (obj ExponentialSmoothing) Add(params AddCalculateBatchParams) (edbInfo *EdbInfo, err error, errMsg string) { req := params.Req fromEdbInfo := params.FromEdbInfo edbCode := params.EdbCode to := global.DEFAULT_DmSQL.Begin() defer func() { if err != nil { to.Rollback() } else { to.Commit() } }() edbInfo = new(EdbInfo) edbInfo.Source = obj.GetSource() edbInfo.SourceName = obj.GetSourceName() edbInfo.EdbCode = edbCode edbInfo.EdbName = req.EdbName edbInfo.EdbNameSource = req.EdbName edbInfo.Frequency = req.Frequency edbInfo.Unit = req.Unit edbInfo.ClassifyId = req.ClassifyId edbInfo.SysUserId = params.SysUserId edbInfo.SysUserRealName = params.SysUserRealName edbInfo.CreateTime = time.Now() edbInfo.ModifyTime = time.Now() edbInfo.UniqueCode = params.UniqueCode edbInfo.CalculateFormula = req.Formula edbInfo.EdbNameEn = req.EdbName edbInfo.UnitEn = req.Unit edbInfo.EdbType = obj.GetEdbType() edbInfo.Sort = GetAddEdbMaxSortByClassifyId(req.ClassifyId, utils.EDB_INFO_TYPE) tmpErr := to.Create(edbInfo).Error if tmpErr != nil { err = tmpErr return } //关联关系 { calculateMappingItem := new(EdbInfoCalculateMapping) calculateMappingItem.CreateTime = time.Now() calculateMappingItem.ModifyTime = time.Now() calculateMappingItem.Sort = 1 calculateMappingItem.EdbCode = edbCode calculateMappingItem.EdbInfoId = edbInfo.EdbInfoId calculateMappingItem.FromEdbInfoId = fromEdbInfo.EdbInfoId calculateMappingItem.FromEdbCode = fromEdbInfo.EdbCode calculateMappingItem.FromEdbName = fromEdbInfo.EdbName calculateMappingItem.FromSource = fromEdbInfo.Source calculateMappingItem.FromSourceName = fromEdbInfo.SourceName calculateMappingItem.FromTag = "" calculateMappingItem.Source = edbInfo.Source calculateMappingItem.SourceName = edbInfo.SourceName calculateMappingItem.FromSubSource = fromEdbInfo.SubSource err = to.Create(calculateMappingItem).Error if err != nil { return } } //计算数据 err = obj.refresh(to, edbInfo, fromEdbInfo, edbInfo.EdbCode) return } // Edit 编辑 func (obj ExponentialSmoothing) Edit(params EditCalculateBatchParams) (err error, errMsg string) { req := params.Req edbInfo := params.EdbInfo fromEdbInfo := params.FromEdbInfo to := global.DEFAULT_DmSQL.Begin() defer func() { if err != nil { to.Rollback() } else { to.Commit() } }() tableName := GetEdbDataTableName(edbInfo.Source, edbInfo.SubSource) oldEdbInfo := *edbInfo //修改指标信息 edbInfo.EdbName = req.EdbName edbInfo.EdbNameSource = req.EdbName edbInfo.Frequency = req.Frequency edbInfo.Unit = req.Unit edbInfo.ClassifyId = req.ClassifyId edbInfo.CalculateFormula = req.Formula edbInfo.EdbNameEn = req.EdbNameEn edbInfo.UnitEn = req.UnitEn edbInfo.ModifyTime = time.Now() err = to.Model(edbInfo).Select([]string{"EdbName", "EdbNameSource", "Frequency", "Unit", "ClassifyId", "CalculateFormula", "ModifyTime", "EdbNameEn", "UnitEn"}).Updates(edbInfo).Error if err != nil { return } var existCondition string var existPars []interface{} existCondition += " AND edb_info_id=? AND from_edb_info_id=? " existPars = append(existPars, edbInfo.EdbInfoId, req.FromEdbInfoId) //判断计算指标是否被更换 count, err := GetEdbInfoCalculateCountByCondition(existCondition, existPars) if err != nil { err = errors.New("判断指标是否改变失败,Err:" + err.Error()) return } if count > 0 { // 指标未被替换,无需处理逻辑 // 如果相关配置更改了,那么重新计算 if oldEdbInfo.CalculateFormula != edbInfo.CalculateFormula { err = obj.refresh(to, edbInfo, fromEdbInfo, edbInfo.EdbCode) } 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.Exec(sql, edbInfo.EdbInfoId).Error if err != nil { return } //清空原有数据 sql = ` DELETE FROM ` + tableName + ` WHERE edb_info_id = ? ` err = to.Exec(sql, edbInfo.EdbInfoId).Error if err != nil { return } //关联关系 { calculateMappingItem := &EdbInfoCalculateMapping{ EdbInfoCalculateMappingId: 0, EdbInfoId: edbInfo.EdbInfoId, Source: obj.GetSource(), SourceName: obj.GetSourceName(), EdbCode: edbInfo.EdbCode, FromEdbInfoId: fromEdbInfo.EdbInfoId, FromEdbCode: fromEdbInfo.EdbCode, FromEdbName: fromEdbInfo.EdbName, FromSource: fromEdbInfo.Source, FromSourceName: fromEdbInfo.SourceName, FromTag: "", Sort: 1, CreateTime: time.Now(), ModifyTime: time.Now(), FromSubSource: fromEdbInfo.SubSource, } err = to.Create(calculateMappingItem).Error if err != nil { return } } //计算数据 err = obj.refresh(to, edbInfo, fromEdbInfo, edbInfo.EdbCode) return } // Refresh 刷新 func (obj ExponentialSmoothing) Refresh(params RefreshParams) (err error, errMsg string) { calculateMapping, err := GetEdbInfoCalculateMappingDetail(params.EdbInfo.EdbInfoId) if err != nil { errMsg = "GetEdbInfoCalculateLjzzyDetail Err:" + err.Error() return } fromEdbInfo, err := GetEdbInfoById(calculateMapping.FromEdbInfoId) if err != nil { errMsg = "GetEdbInfoById Err:" + err.Error() return } to := global.DEFAULT_DmSQL.Begin() defer func() { if err != nil { to.Rollback() } else { to.Commit() } }() // 计算数据 err = obj.refresh(to, params.EdbInfo, fromEdbInfo, params.EdbInfo.EdbCode) return } // GetSource 获取来源编码id func (obj ExponentialSmoothing) GetSource() int { return utils.DATA_SOURCE_CALCULATE_ZSXY } // GetSourceName 获取来源名称 func (obj ExponentialSmoothing) GetSourceName() string { return utils.DATA_SOURCE_NAME_CALCULATE_ZSXY } // GetEdbType 获取指标类型 func (obj ExponentialSmoothing) GetEdbType() int { return utils.CALCULATE_EDB_TYPE } func (obj ExponentialSmoothing) refresh(to *gorm.DB, edbInfo, fromEdbInfo *EdbInfo, edbCode string) (err error) { edbInfoId := edbInfo.EdbInfoId dataTableName := GetEdbDataTableName(edbInfo.Source, edbInfo.SubSource) edbInfoIdStr := strconv.Itoa(edbInfoId) // 获取标准差图表的指标数据 fromDataList, err := CalculateExponentialSmoothingData(fromEdbInfo, edbInfo.CalculateFormula) if err != nil { return err } //获取指标所有数据 existDataList, err := GetAllEdbDataListByTo(to, edbInfoId, edbInfo.Source, edbInfo.SubSource) if err != nil { return err } existDataMap := make(map[string]string) removeDataTimeMap := make(map[string]int) //需要移除的日期数据 for _, v := range existDataList { existDataMap[v.DataTime] = v.Value removeDataTimeMap[v.DataTime] = 1 } needAddDateMap := make(map[time.Time]int) addSql := ` INSERT INTO ` + dataTableName + `(edb_info_id,edb_code,data_time,value,create_time,modify_time,data_timestamp) values ` var isAdd bool for _, tmpData := range fromDataList { currDateStr := tmpData.DataTime currTime, tmpErr := time.ParseInLocation(utils.FormatDate, currDateStr, time.Local) if tmpErr != nil { err = tmpErr return } // 当前的实际值 saveValue := decimal.NewFromFloat(tmpData.Value).Round(4).String() existVal, ok := existDataMap[currDateStr] // 如果库中已经存在该数据的话,那么就进行值的变更操作 if ok { //校验待删除日期数据里面是否存在该元素,如果存在的话,那么移除该日期 delete(removeDataTimeMap, currDateStr) if existVal != saveValue { sql := ` UPDATE %s SET value=?,modify_time=NOW() WHERE edb_info_id=? AND data_time=? ` sql = fmt.Sprintf(sql, dataTableName) err = to.Exec(sql, saveValue, edbInfoId, currDateStr).Error if err != nil { return } } continue } // 库中不存在该日期的数据 timestamp := currTime.UnixNano() / 1e6 timeStr := fmt.Sprintf("%d", timestamp) if _, existOk := needAddDateMap[currTime]; !existOk { addSql += GetAddSql(edbInfoIdStr, edbCode, currDateStr, timeStr, saveValue) isAdd = true } needAddDateMap[currTime] = 1 } //删除已经不存在的指标数据(由于该指标当日的数据删除了) { removeDateList := make([]string, 0) for dateTime := range removeDataTimeMap { removeDateList = append(removeDateList, dateTime) } removeNum := len(removeDateList) if removeNum > 0 { sql := fmt.Sprintf(` DELETE FROM %s WHERE edb_info_id = ? and data_time in (`+utils.GetOrmInReplace(removeNum)+`) `, dataTableName) err = to.Exec(sql, edbInfo.EdbInfoId, removeDateList).Error if err != nil { fmt.Println(reflect.TypeOf(obj).Name(), " add data ;delete Err", err.Error()) err = fmt.Errorf("删除不存在的指标数据失败,Err:" + err.Error()) return } } } if isAdd { addSql = strings.TrimRight(addSql, ",") err = to.Exec(addSql).Error if err != nil { fmt.Println(reflect.TypeOf(obj).Name(), " add data Err", err.Error()) return } } return } // CalculateExponentialSmoothingData 计算指数修匀 func CalculateExponentialSmoothingData(fromEdbInfo *EdbInfo, strAlpha string) (newDataList []EdbInfoSearchData, err error) { alpha, _ := strconv.ParseFloat(strAlpha, 64) if alpha <= 0 || alpha >= 1 { err = fmt.Errorf("alpha值有误: %v", alpha) return } // 获取时间基准指标在时间区间内的值 dataList := make([]*EdbInfoSearchData, 0) switch fromEdbInfo.EdbInfoType { case 0: //获取来源指标的数据 dataList, err = GetEdbDataListAll(fromEdbInfo.Source, fromEdbInfo.SubSource, FindEdbDataListAllCond{ EdbInfoId: fromEdbInfo.EdbInfoId, }, 1) case 1: dataList, err = GetPredictEdbDataListAllByStartDate(fromEdbInfo, 1, "") default: err = errors.New(fmt.Sprint("获取失败,指标base类型异常", fromEdbInfo.EdbInfoType)) return } var preVal float64 alphaDecimal := decimal.NewFromFloat(alpha) subAlpha := decimal.NewFromFloat(1).Sub(alphaDecimal) for k, d := range dataList { // 首期的值以原始值作为指数修匀的计算值 if k == 0 { newDataList = append(newDataList, EdbInfoSearchData{ EdbDataId: k, DataTime: dataList[k].DataTime, Value: d.Value, }) preVal = d.Value continue } // 上一期的值参与计算 preDecimal := decimal.NewFromFloat(preVal) valDecimal := decimal.NewFromFloat(d.Value) partA := alphaDecimal.Mul(valDecimal) partB := subAlpha.Mul(preDecimal) res, _ := (partA.Add(partB)).Float64() preVal = res newDataList = append(newDataList, EdbInfoSearchData{ EdbDataId: k, DataTime: dataList[k].DataTime, Value: res, }) } return }