Merge branch '11.7' into debug

# Conflicts:
#	models/edb_info.go
#	routers/commentsRouter.go

models/edb_data_calculate_nhcc.go

@@ -6,6 +6,7 @@ import (
 	"github.com/beego/beego/v2/client/orm"
 	"github.com/shopspring/decimal"
 	"hongze/hongze_edb_lib/utils"
+	"math"
 	"strings"
 	"time"
 )
@@ -487,6 +488,10 @@ func refreshAllCalculateNhcc(to orm.TxOrmer, edbInfo *EdbInfo, existItemA, exist
 		a, b = getLinearResult(coordinateData)
 	}
 
+	if math.IsNaN(a) || math.IsNaN(b) {
+		err = errors.New("线性方程公式生成失败")
+		return
+	}
 	//fmt.Println("a:", a, ";======b:", b)
 
 	//计算B’

models/edb_info.go

@@ -552,7 +552,10 @@ func GetChartPredictEdbInfoDataListByConfList(predictEdbConfList []*PredictEdbCo
 				err = tmpErr
 				return
 			}
-			predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleNLinearRegression(predictEdbConf.PredictEdbInfoId, nValue, startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
+			predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleNLinearRegression(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(predictEdbConf.PredictEdbInfoId, 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

models/predict_edb_info_rule.go

@@ -1,8 +1,10 @@
 package models
 
 import (
+	"errors"
 	"github.com/shopspring/decimal"
 	"hongze/hongze_edb_lib/utils"
+	"math"
 	"time"
 )
 
@@ -458,7 +460,7 @@ func GetChartPredictEdbInfoDataListByRuleNMoveMeanValue(edbInfoId int, nValue in
 //	例1：过去5期值(N=5)分别为：3，5，7，9，11（每两期值之间的时间间隔相等）。那么按照线性回归方程推算，未来三期的预测值是：13，15，17。
 //
 //	例2：过去6期值(N=6)分别为：3，3，5，7，9，11（每两期值之间的时间间隔相等）。那么按照线性回归方程推算，未来三期的预测值是：12.33，14.05，15.76。例1和例2的区别在于，多加了一期数据，导致回归方程发生改变，从而预测值不同。
-func GetChartPredictEdbInfoDataListByRuleNLinearRegression(edbInfoId int, nValue int, startDate, endDate time.Time, frequency string, realPredictEdbInfoData, predictEdbInfoData []*EdbInfoSearchData, existMap map[string]float64) (newPredictEdbInfoData []*EdbInfoSearchData, minValue, maxValue float64) {
+func GetChartPredictEdbInfoDataListByRuleNLinearRegression(edbInfoId int, nValue int, startDate, endDate time.Time, frequency string, realPredictEdbInfoData, predictEdbInfoData []*EdbInfoSearchData, existMap map[string]float64) (newPredictEdbInfoData []*EdbInfoSearchData, minValue, maxValue float64, err error) {
 	//var errMsg string
 	//defer func() {
 	//	if errMsg != `` {
@@ -491,6 +493,10 @@ func GetChartPredictEdbInfoDataListByRuleNLinearRegression(edbInfoId int, nValue
 		coordinateData = append(coordinateData, tmpCoordinate)
 	}
 	a, b := getLinearResult(coordinateData)
+	if math.IsNaN(a) || math.IsNaN(b) {
+		err = errors.New("线性方程公式生成失败")
+		return
+	}
 	//fmt.Println("a:", a, ";======b:", b)
 
 	aDecimal := decimal.NewFromFloat(a)