package chart import ( "encoding/json" "errors" "github.com/shopspring/decimal" edbDataModel "hongze/hongze_yb/models/tables/edb_data" edbInfoModel "hongze/hongze_yb/models/tables/edb_info" predictEdbConfModel "hongze/hongze_yb/models/tables/predict_edb_conf" predictEdbRuleDataModel "hongze/hongze_yb/models/tables/predict_edb_rule_data" "hongze/hongze_yb/utils" "strconv" "time" ) // GetChartPredictEdbInfoDataList 获取图表的预测指标的未来数据 func GetChartPredictEdbInfoDataList(predictEdbConf predictEdbConfModel.PredictEdbConf, filtrateStartDateStr, latestDateStr string, lastDataValue float64, endDateStr, frequency string) (predictEdbInfoData []*edbDataModel.EdbDataList, err error) { endDate, err := time.ParseInLocation(utils.FormatDate, endDateStr, time.Local) if err != nil { return } latestDate, err := time.ParseInLocation(utils.FormatDate, latestDateStr, time.Local) if err != nil { return } // 开始预测数据的时间 startDate := latestDate // 如果有筛选时间的话 if filtrateStartDateStr != `` { filtrateStartDate, tmpErr := time.ParseInLocation(utils.FormatDate, filtrateStartDateStr, time.Local) if tmpErr != nil { err = tmpErr return } //如果筛选时间晚于实际数据时间,那么就以筛选时间作为获取预测数据的时间 if filtrateStartDate.After(latestDate) { startDate = filtrateStartDate.AddDate(0, 0, -1) } } dataValue := lastDataValue if predictEdbConf.RuleType == 2 { dataValue = predictEdbConf.FixedValue } //获取后面的预测数据 dayList := getPredictEdbDayList(startDate, endDate, frequency) predictEdbInfoData = make([]*edbDataModel.EdbDataList, 0) for k, v := range dayList { predictEdbInfoData = append(predictEdbInfoData, &edbDataModel.EdbDataList{ EdbDataId: int(predictEdbConf.PredictEdbInfoID) + 10000000000 + k, EdbInfoId: int(predictEdbConf.PredictEdbInfoID), DataTime: v.Format(utils.FormatDate), Value: dataValue, DataTimestamp: (v.UnixNano() / 1e6) + 1000, //前端需要让加1s,说是2022-09-01 00:00:00 这样的整点不合适 }) } return } // GetChartPredictEdbInfoDataListByConfList 获取图表的预测指标的未来数据 func GetChartPredictEdbInfoDataListByConfList(predictEdbConfList []*predictEdbConfModel.PredictEdbConf, filtrateStartDateStr, latestDateStr, endDateStr, frequency string, realPredictEdbInfoData []*edbDataModel.EdbDataList) (predictEdbInfoData []*edbDataModel.EdbDataList, minValue, maxValue float64, err error) { endDate, err := time.ParseInLocation(utils.FormatDate, endDateStr, time.Local) if err != nil { return } latestDate, err := time.ParseInLocation(utils.FormatDate, latestDateStr, time.Local) if err != nil { return } // 开始预测数据的时间 startDate := latestDate // 如果有筛选时间的话 if filtrateStartDateStr != `` { filtrateStartDate, tmpErr := time.ParseInLocation(utils.FormatDate, filtrateStartDateStr, time.Local) if tmpErr != nil { err = tmpErr return } //如果筛选时间晚于实际数据时间,那么就以筛选时间作为获取预测数据的时间 if filtrateStartDate.After(latestDate) { startDate = filtrateStartDate.AddDate(0, 0, -1) } } //var dateArr []string // 对应日期的值 existMap := make(map[string]float64) for _, v := range realPredictEdbInfoData { //dateArr = append(dateArr, v.DataTime) existMap[v.DataTime] = v.Value } predictEdbInfoData = make([]*edbDataModel.EdbDataList, 0) //dataValue := lastDataValue //预测规则,1:最新,2:固定值,3:同比,4:同差,5:环比,6:环差,7:N期移动均值,8:N期段线性外推值 for _, predictEdbConf := range predictEdbConfList { dataEndTime := endDate if predictEdbConf.EndDate.Before(dataEndTime) { dataEndTime = predictEdbConf.EndDate } var tmpMinValue, tmpMaxValue float64 // 当前预测结果中的最大/最小值 dayList := getPredictEdbDayList(startDate, dataEndTime, frequency) if len(dayList) <= 0 { // 如果未来没有日期的话,那么就退出当前循环,进入下一个循环 continue } switch predictEdbConf.RuleType { case 1: //1:最新 var lastDataValue float64 //最新值 tmpAllData := make([]*edbDataModel.EdbDataList, 0) tmpAllData = append(tmpAllData, realPredictEdbInfoData...) tmpAllData = append(tmpAllData, predictEdbInfoData...) lenTmpAllData := len(tmpAllData) if lenTmpAllData > 0 { lastDataValue = tmpAllData[lenTmpAllData-1].Value } predictEdbInfoData = GetChartPredictEdbInfoDataListByRule1(int(predictEdbConf.PredictEdbInfoID), lastDataValue, startDate, dataEndTime, frequency, predictEdbInfoData, existMap) tmpMaxValue = lastDataValue tmpMinValue = lastDataValue case 2: //2:固定值 tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value) if tmpErr != nil { err = tmpErr return } dataValue, _ := tmpValDecimal.Float64() predictEdbInfoData = GetChartPredictEdbInfoDataListByRule1(int(predictEdbConf.PredictEdbInfoID), dataValue, startDate, dataEndTime, frequency, predictEdbInfoData, existMap) tmpMaxValue = dataValue tmpMinValue = dataValue case 3: //3:同比 tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value) if tmpErr != nil { err = tmpErr return } tbValue, _ := tmpValDecimal.Float64() predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleTb(int(predictEdbConf.PredictEdbInfoID), tbValue, startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap) case 4: //4:同差 tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value) if tmpErr != nil { err = tmpErr return } tcValue, _ := tmpValDecimal.Float64() predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleTc(int(predictEdbConf.PredictEdbInfoID), tcValue, startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap) case 5: //5:环比 tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value) if tmpErr != nil { err = tmpErr return } hbValue, _ := tmpValDecimal.Float64() predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleHb(int(predictEdbConf.PredictEdbInfoID), hbValue, startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap) case 6: //6:环差 tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value) if tmpErr != nil { err = tmpErr return } hcValue, _ := tmpValDecimal.Float64() predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleHc(int(predictEdbConf.PredictEdbInfoID), hcValue, startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap) case 7: //7:N期移动均值 nValue, tmpErr := strconv.Atoi(predictEdbConf.Value) if tmpErr != nil { err = tmpErr return } predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleNMoveMeanValue(int(predictEdbConf.PredictEdbInfoID), nValue, startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap) case 8: //8:N期段线性外推值 nValue, tmpErr := strconv.Atoi(predictEdbConf.Value) if tmpErr != nil { err = tmpErr return } predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleNLinearRegression(int(predictEdbConf.PredictEdbInfoID), nValue, startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap) if err != nil { return } case 9: //9:动态环差”预测规则; predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleTrendsHC(int(predictEdbConf.PredictEdbInfoID), int(predictEdbConf.ConfigID), startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap) case 10: //10:根据 给定终值后插值 规则获取预测数据 tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value) if tmpErr != nil { err = tmpErr return } finalValue, _ := tmpValDecimal.Float64() predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleFinalValueHc(int(predictEdbConf.PredictEdbInfoID), finalValue, startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap) case 11: //11:根据 季节性 规则获取预测数据 var seasonConf SeasonConf tmpErr := json.Unmarshal([]byte(predictEdbConf.Value), &seasonConf) if tmpErr != nil { err = errors.New("季节性配置信息异常:" + tmpErr.Error()) return } calendar := "公历" if seasonConf.Calendar == "农历" { calendar = "农历" } yearList := make([]int, 0) //选择方式,1:连续N年;2:指定年份 if seasonConf.YearType == 1 { if seasonConf.NValue < 1 { err = errors.New("连续N年不允许小于1") return } currYear := time.Now().Year() for i := 0; i < seasonConf.NValue; i++ { yearList = append(yearList, currYear-i-1) } } else { yearList = seasonConf.YearList } predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleSeason(int(predictEdbConf.PredictEdbInfoID), yearList, calendar, startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap) if err != nil { return } case 12: //12:根据 移动平均同比 规则获取预测数据 var moveAverageConf MoveAverageConf tmpErr := json.Unmarshal([]byte(predictEdbConf.Value), &moveAverageConf) if tmpErr != nil { err = errors.New("季节性配置信息异常:" + tmpErr.Error()) return } predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleMoveAverageTb(int(predictEdbConf.PredictEdbInfoID), moveAverageConf.NValue, moveAverageConf.Year, startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap) if err != nil { return } case 13: //13:根据 同比增速差值 规则获取预测数据 tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value) if tmpErr != nil { err = tmpErr return } tbEndValue, _ := tmpValDecimal.Float64() predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleTbzscz(int(predictEdbConf.PredictEdbInfoID), tbEndValue, dayList, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap) case 14: //14:根据 一元线性拟合 规则获取预测数据 var ruleConf RuleLineNhConf err = json.Unmarshal([]byte(predictEdbConf.Value), &ruleConf) if err != nil { err = errors.New("一元线性拟合配置信息异常:" + err.Error()) return } // 规则计算的拟合残差值map newNhccDataMap := make(map[string]float64) if predictEdbConf.PredictEdbInfoID > 0 { //已经生成的动态数据 tmpPredictEdbRuleDataList, tmpErr := predictEdbRuleDataModel.GetPredictEdbRuleDataList(int(predictEdbConf.PredictEdbInfoID), int(predictEdbConf.ConfigID), "", "") if tmpErr != nil { err = tmpErr return } for _, v := range tmpPredictEdbRuleDataList { newNhccDataMap[v.DataTime.Format(utils.FormatDate)] = v.Value } } else { //未生成的动态数据,需要使用外部传入的数据进行计算 newNhccDataMap, err = getCalculateNhccData(append(realPredictEdbInfoData, predictEdbInfoData...), ruleConf) if err != nil { return } } predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleLineNh(int(predictEdbConf.PredictEdbInfoID), dayList, realPredictEdbInfoData, predictEdbInfoData, newNhccDataMap, existMap) if err != nil { return } } //startDate = dataEndTime.AddDate(0, 0, 1) if startDate.Before(dataEndTime) { startDate = dataEndTime } if tmpMinValue < minValue { minValue = tmpMinValue } if tmpMaxValue < maxValue { maxValue = tmpMaxValue } } return } // GetPredictEdbDayList 获取预测指标日期列表 func getPredictEdbDayList(startDate, endDate time.Time, frequency string) (dayList []time.Time) { //if !utils.InArrayByStr([]string{"日度", "周度", "月度"}, frequency) switch frequency { case "日度": for currDate := startDate.AddDate(0, 0, 1); currDate.Before(endDate) || currDate.Equal(endDate); currDate = currDate.AddDate(0, 0, 1) { //周六、日排除 if currDate.Weekday() == time.Sunday || currDate.Weekday() == time.Saturday { continue } dayList = append(dayList, currDate) } case "周度": //nextDate := startDate.AddDate(0, 0, 7) for currDate := startDate.AddDate(0, 0, 7); currDate.Before(endDate) || currDate.Equal(endDate); currDate = currDate.AddDate(0, 0, 7) { dayList = append(dayList, currDate) } case "月度": for currDate := startDate; currDate.Before(endDate) || currDate.Equal(endDate); { currDate = time.Date(currDate.Year(), currDate.Month(), 1, 0, 0, 0, 0, time.Now().Location()).AddDate(0, 1, -1) if !currDate.After(endDate) && !currDate.Equal(startDate) { dayList = append(dayList, currDate) } currDate = currDate.AddDate(0, 0, 1) } case "年度": for currDate := startDate; currDate.Before(endDate) || currDate.Equal(endDate); { currDate = time.Date(currDate.Year()+1, 12, 31, 0, 0, 0, 0, time.Now().Location()) if !currDate.After(endDate) && !currDate.Equal(startDate) { dayList = append(dayList, currDate) } } } return } // GetPredictDataListByPredictEdbInfoId 根据预测指标id获取预测指标的数据 func GetPredictDataListByPredictEdbInfoId(edbInfoId int, startDate, endDate string, isTimeBetween bool) (edbInfo *edbInfoModel.EdbInfo, dataList []*edbDataModel.EdbDataList, sourceEdbInfoItem *edbInfoModel.EdbInfo, predictEdbConf *predictEdbConfModel.PredictEdbConf, err error, errMsg string) { edbInfo, err = edbInfoModel.GetEdbInfoById(edbInfoId) if err != nil { errMsg = `获取预测指标信息失败` return } dataList, sourceEdbInfoItem, predictEdbConf, err, errMsg = GetPredictDataListByPredictEdbInfo(edbInfo, startDate, endDate, isTimeBetween) return } // GetPredictDataListByPredictEdbInfo 根据预测指标信息获取预测指标的数据 func GetPredictDataListByPredictEdbInfo(edbInfo *edbInfoModel.EdbInfo, startDate, endDate string, isTimeBetween bool) (dataList []*edbDataModel.EdbDataList, sourceEdbInfoItem *edbInfoModel.EdbInfo, predictEdbConf *predictEdbConfModel.PredictEdbConf, err error, errMsg string) { // 非计算指标,直接从表里获取数据 if edbInfo.EdbType != 1 { if !isTimeBetween { endDate = `` } return GetPredictCalculateDataListByPredictEdbInfo(edbInfo, startDate, endDate) } // 查找该预测指标配置 predictEdbConfList, err := predictEdbConfModel.GetPredictEdbConfListById(edbInfo.EdbInfoId) if err != nil { errMsg = "获取预测指标配置信息失败" return } if len(predictEdbConfList) == 0 { errMsg = "获取预测指标配置信息失败" err = errors.New(errMsg) return } predictEdbConf = predictEdbConfList[0] // 来源指标 sourceEdbInfoItem, err = edbInfoModel.GetEdbInfoById(int(predictEdbConf.SourceEdbInfoID)) if err != nil { if err == utils.ErrNoRow { errMsg = "找不到来源指标信息" err = errors.New(errMsg) } return } allDataList := make([]*edbDataModel.EdbDataList, 0) //获取指标数据(实际已生成) dataList, err = edbDataModel.GetEdbDataList(sourceEdbInfoItem.Source, sourceEdbInfoItem.EdbInfoId, startDate, endDate) if err != nil { return } // 如果选择了日期,那么需要筛选所有的数据,用于未来指标的生成 if startDate != `` { allDataList, err = edbDataModel.GetEdbDataList(sourceEdbInfoItem.Source, sourceEdbInfoItem.EdbInfoId, "", "") if err != nil { return } } else { allDataList = dataList } // 获取预测指标未来的数据 predictDataList := make([]*edbDataModel.EdbDataList, 0) endDateStr := edbInfo.EndDate.Format(utils.FormatDate) //预测指标的结束日期 if isTimeBetween { //如果是时间区间,那么 reqEndDateTime, _ := time.ParseInLocation(utils.FormatDate, endDate, time.Local) // 如果选择的时间区间结束日期 晚于 当天,那么预测数据截止到当天 if reqEndDateTime.Before(edbInfo.EndDate) { endDateStr = endDate } } //predictDataList, err = GetChartPredictEdbInfoDataList(*predictEdbConf, startDate, sourceEdbInfoItem.LatestDate.Format(utils.FormatDate), sourceEdbInfoItem.LatestValue, endDateStr, edbInfo.Frequency) var predictMinValue, predictMaxValue float64 predictDataList, predictMinValue, predictMaxValue, err = GetChartPredictEdbInfoDataListByConfList(predictEdbConfList, startDate, sourceEdbInfoItem.LatestDate.Format(utils.FormatDate), endDateStr, edbInfo.Frequency, allDataList) if err != nil { return } dataList = append(dataList, predictDataList...) if len(predictDataList) > 0 { // 如果最小值 大于 预测值,那么将预测值作为最小值数据返回 if edbInfo.MinValue > predictMinValue { edbInfo.MinValue = predictMinValue } // 如果最大值 小于 预测值,那么将预测值作为最大值数据返回 if edbInfo.MaxValue < predictMaxValue { edbInfo.MaxValue = predictMaxValue } } return } // GetPredictCalculateDataListByPredictEdbInfo 根据预测运算指标信息获取预测指标的数据 func GetPredictCalculateDataListByPredictEdbInfo(edbInfo *edbInfoModel.EdbInfo, startDate, endDate string) (dataList []*edbDataModel.EdbDataList, sourceEdbInfoItem *edbInfoModel.EdbInfo, predictEdbConf *predictEdbConfModel.PredictEdbConf, err error, errMsg string) { dataList, err = edbDataModel.GetEdbDataList(edbInfo.Source, edbInfo.EdbInfoId, startDate, endDate) return }