feat:新增一元拟合预测规则，同比增速预测规则

logic/predict_edb.go

@@ -737,8 +737,9 @@ func RefreshPredictEdbInfo(edbInfoId int) (edbInfo *models.EdbInfo, err error, e
 				return
 			}
 		case 14: //14：根据 一元线性拟合 规则获取预测数据
+
 			if v.Value == "" {
-				errMsg = "请配置规则"
+				errMsg = "一元线性拟合规则信息未配置"
 				return
 			}
 			err = models.RefreshCalculateByRuleByLineNh(*edbInfo, predictEdbConfAndDataList, *v)

models/edb_info.go

@@ -590,8 +590,9 @@ func GetChartPredictEdbInfoDataListByConfList(predictEdbConfList []*PredictEdbCo
 			hcDataMap := make(map[string]float64) //规则计算的环差值map
 
 			if predictEdbConf.PredictEdbInfoId > 0 {
-				tmpPredictEdbRuleDataList, err := GetPredictEdbRuleDataItemList(predictEdbConf.PredictEdbInfoId, predictEdbConf.ConfigId, startDate.Format(utils.FormatDate), endDate.Format(utils.FormatDate))
-				if err != nil {
+				tmpPredictEdbRuleDataList, tmpErr := GetPredictEdbRuleDataItemList(predictEdbConf.PredictEdbInfoId, predictEdbConf.ConfigId, startDate.Format(utils.FormatDate), endDate.Format(utils.FormatDate))
+				if tmpErr != nil {
+					err = tmpErr
 					return
 				}
 				for _, v := range tmpPredictEdbRuleDataList {
@@ -674,9 +675,9 @@ func GetChartPredictEdbInfoDataListByConfList(predictEdbConfList []*PredictEdbCo
 			predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleTbzscz(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
-			tmpErr := json.Unmarshal([]byte(predictEdbConf.Value), &ruleConf)
-			if tmpErr != nil {
-				err = errors.New("季节性配置信息异常:" + tmpErr.Error())
+			err = json.Unmarshal([]byte(predictEdbConf.Value), &ruleConf)
+			if err != nil {
+				err = errors.New("一元线性拟合规则配置信息异常:" + err.Error())
 				return
 			}