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@@ -2,6 +2,8 @@ package models
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import (
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"errors"
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+ "fmt"
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+ "github.com/nosixtools/solarlunar"
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"github.com/shopspring/decimal"
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"hongze/hongze_edb_lib/utils"
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"math"
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@@ -709,3 +711,328 @@ func GetChartPredictEdbInfoDataListByRuleFinalValueHc(edbInfoId int, finalValue
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}
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return
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}
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+
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+// SeasonConf 季节性规则的配置
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+type SeasonConf struct {
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+ Calendar string `description:"公历、农历"`
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+ YearType int `description:"选择方式，1：连续N年；2：指定年份"`
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+ NValue int `description:"连续N年"`
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+ YearList []int `description:"指定年份列表"`
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+}
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+
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+// GetChartPredictEdbInfoDataListByRuleSeason 根据 季节性 规则获取预测数据
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+// ETA预测规则：季节性
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+//已知选定指标A最近更新日期： 2022-12-6 200
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+//设置预测截止日期2023-01-06
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+//1、选择过去N年，N=3
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+//则过去N年为2021、2020、2019
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+//指标A日期 实际值 指标A日期
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+//2019/12/5 150 2019/12/6
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+//2020/12/5 180 2020/12/6
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+//2021/12/5 210 2021/12/6
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+//2019/12/31 200 2020/1/1
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+//2020/12/31 210 2021/1/1
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+//2021/12/31 250 2022/1/1
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+//
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+//计算12.7预测值，求过去N年环差均值=[(100-150)+(160-180)+(250-210)]/3=-10
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+//则12.7预测值=12.6值+过去N年环差均值=200-10=190
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+//以此类推...
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+//
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+//计算2023.1.2预测值，求过去N年环差均值=[(300-200)+(220-210)+(260-250)]/3=40
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+//则2023.1.2预测值=2023.1.1值+过去N年环差均值
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+func GetChartPredictEdbInfoDataListByRuleSeason(edbInfoId int, yearsList []int, calendar string, startDate, endDate time.Time, frequency string, realPredictEdbInfoData, predictEdbInfoData []*EdbInfoSearchData, existMap map[string]float64) (newPredictEdbInfoData []*EdbInfoSearchData, minValue, maxValue float64, err error) {
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+ allDataList := make([]*EdbInfoSearchData, 0)
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+ allDataList = append(allDataList, realPredictEdbInfoData...)
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+ allDataList = append(allDataList, predictEdbInfoData...)
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+ newPredictEdbInfoData = predictEdbInfoData
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+
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+ // 获取每个年份的日期数据需要平移的天数
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+ moveDayMap := make(map[int]int, 0) // 每个年份的春节公历
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+ {
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+ if calendar == "公历" {
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+ for _, year := range yearsList {
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+ moveDayMap[year] = 0 //公历就不平移了
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+ }
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+ } else {
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+ currentDay := time.Now()
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+ if currentDay.Month() >= 11 { //如果大于等于11月份，那么用的是下一年的春节
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+ currentDay = currentDay.AddDate(1, 0, 0)
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+ }
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+
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+ currentYear := currentDay.Year()
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+ currentYearCjnl := fmt.Sprintf("%d-01-01", currentYear) //当年的春节农历
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+ currentYearCjgl := solarlunar.LunarToSolar(currentYearCjnl, false) //当年的春节公历
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+ currentYearCjglTime, tmpErr := time.ParseInLocation(utils.FormatDate, currentYearCjgl, time.Local)
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+ if tmpErr != nil {
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+ err = errors.New("当前春节公历日期转换失败:" + tmpErr.Error())
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+ return
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+ }
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+
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+ // 指定的年份
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+ for _, year := range yearsList {
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+ tmpYearCjnl := fmt.Sprintf("%d-01-01", year) //指定年的春节农历
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+ tmpYearCjgl := solarlunar.LunarToSolar(tmpYearCjnl, false) //指定年的春节公历
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+ //moveDayList = append(moveDayList, 0) //公历就不平移了
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+
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+ tmpYearCjglTime, tmpErr := time.ParseInLocation(utils.FormatDate, tmpYearCjgl, time.Local)
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+ if tmpErr != nil {
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+ err = errors.New(fmt.Sprintf("%d公历日期转换失败:%s", year, tmpErr.Error()))
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+ return
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+ }
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+
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+ tmpCurrentYearCjglTime := currentYearCjglTime.AddDate(year-currentYear, 0, 0)
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+ moveDay := utils.GetTimeSubDay(tmpYearCjglTime, tmpCurrentYearCjglTime)
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+ moveDayMap[year] = moveDay //公历平移
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+ }
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+ }
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+ }
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+
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+ index := len(allDataList)
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+ //获取后面的预测日期
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+ dayList := getPredictEdbDayList(startDate, endDate, frequency)
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+
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+ //获取后面的预测数据
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+ predictEdbInfoData = make([]*EdbInfoSearchData, 0)
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+ for k, currentDate := range dayList {
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+ tmpHistoryVal := decimal.NewFromFloat(0) //往期的差值总和
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+ tmpHistoryValNum := 0 // 往期差值计算的数量
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+
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+ tmpLenAllDataList := len(allDataList)
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+ tmpK := tmpLenAllDataList - 1 //上1期数据的下标
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+ lastDayStr := allDataList[tmpK].DataTime
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+ lastDayVal := allDataList[tmpK].Value
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+ lastDay, tmpErr := time.ParseInLocation(utils.FormatDate, lastDayStr, time.Local)
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+ if tmpErr != nil {
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+ err = errors.New("获取上期日期转换失败:" + tmpErr.Error())
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+ }
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+ for _, year := range yearsList {
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+ moveDay := moveDayMap[year] //需要移动的天数
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+ var tmpHistoryCurrentVal, tmpHistoryLastVal float64
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+ var isFindHistoryCurrent, isFindHistoryLast bool //是否找到前几年的数据
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+
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+ //前几年当日的日期
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+ tmpHistoryCurrentDate := currentDate.AddDate(year-currentDate.Year(), 0, moveDay)
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+ for i := 0; i <= 35; i++ { // 前后35天找数据，找到最近的值，先向后面找，再往前面找
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+ tmpDate := tmpHistoryCurrentDate.AddDate(0, 0, i)
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+ if val, ok := existMap[tmpDate.Format(utils.FormatDate)]; ok {
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+ tmpHistoryCurrentVal = val
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+ isFindHistoryCurrent = true
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+ break
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+ } else {
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+ tmpDate := tmpHistoryCurrentDate.AddDate(0, 0, -i)
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+ if val, ok := existMap[tmpDate.Format(utils.FormatDate)]; ok {
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+ tmpHistoryCurrentVal = val
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+ isFindHistoryCurrent = true
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+ break
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+ }
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+ }
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+ }
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+
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+ //前几年上一期的日期
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+ tmpHistoryLastDate := lastDay.AddDate(year-lastDay.Year(), 0, moveDay)
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+ for i := 0; i <= 35; i++ { // 前后35天找数据，找到最近的值，先向后面找，再往前面找
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+ tmpDate := tmpHistoryLastDate.AddDate(0, 0, i)
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+ if val, ok := existMap[tmpDate.Format(utils.FormatDate)]; ok {
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+ tmpHistoryLastVal = val
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+ isFindHistoryLast = true
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+ break
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+ } else {
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+ tmpDate := tmpHistoryLastDate.AddDate(0, 0, -i)
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+ if val, ok := existMap[tmpDate.Format(utils.FormatDate)]; ok {
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+ tmpHistoryLastVal = val
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+ isFindHistoryLast = true
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+ break
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+ }
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+ }
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+ }
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+
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+ // 如果两个日期对应的数据都找到了，那么计算两期的差值
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+ if isFindHistoryCurrent && isFindHistoryLast {
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+ af := decimal.NewFromFloat(tmpHistoryCurrentVal)
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+ bf := decimal.NewFromFloat(tmpHistoryLastVal)
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+ tmpHistoryVal = tmpHistoryVal.Add(af.Sub(bf))
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+ tmpHistoryValNum++
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+ }
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+ }
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+
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+ //计算的差值与选择的年份数量不一致，那么当前日期不计算
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+ if tmpHistoryValNum != len(yearsList) {
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+ continue
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+ }
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+ lastDayValDec := decimal.NewFromFloat(lastDayVal)
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+ val, _ := tmpHistoryVal.Div(decimal.NewFromInt(int64(tmpHistoryValNum))).Add(lastDayValDec).RoundCeil(4).Float64()
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+
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+ currentDateStr := currentDate.Format(utils.FormatDate)
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+ tmpData := &EdbInfoSearchData{
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+ EdbDataId: edbInfoId + 10000000000 + index + k,
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+ //EdbInfoId: edbInfoId,
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+ DataTime: currentDateStr,
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+ Value: val,
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+ //DataTimestamp: (currentDate.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
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+ }
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+ newPredictEdbInfoData = append(newPredictEdbInfoData, tmpData)
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+ allDataList = append(allDataList, tmpData)
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+ existMap[currentDateStr] = val
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+
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+ // 最大最小值
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+ if val < minValue {
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+ minValue = val
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+ }
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+ if val > maxValue {
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+ maxValue = val
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+ }
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+ }
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+ return
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+}
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+
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+// MoveAverageConf 移动平均同比规则的配置
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+type MoveAverageConf struct {
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+ Year int `description:"指定年份"`
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+ NValue int `description:"N期的数据"`
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+}
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+
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+// GetChartPredictEdbInfoDataListByRuleMoveAverageTb 根据 移动平均同比 规则获取预测数据
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+// ETA预测规则：季节性
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+//2、选择指定N年，N=3
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+//指定N年为2012、2015、2018
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+//指标A日期 实际值 指标A日期 实际值
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+//2012/12/5 150 2012/12/6 130
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+//2015/12/5 180 2015/12/6 150
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+//2018/12/5 210 2018/12/6 260
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+//2012/12/31 200 2013/1/1 200
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+//2015/12/31 210 2016/1/1 250
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+//2018/12/31 250 2019/1/1 270
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+//计算12.7预测值，求过去N年环差均值=[(130-150)+(150-180)+(290-210)]/3=10
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+//则12.7预测值=12.6值+过去N年环差均值=200+10=210
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+//以此类推...
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+//计算2023.1.2预测值，求过去N年环差均值=[(200-200)+(250-210)+(270-250)]/3=16.67
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+//则2023.1.2预测值=2023.1.1值+过去N年环差均值
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+func GetChartPredictEdbInfoDataListByRuleMoveAverageTb(edbInfoId int, nValue, year int, startDate, endDate time.Time, frequency string, realPredictEdbInfoData, predictEdbInfoData []*EdbInfoSearchData, existMap map[string]float64) (newPredictEdbInfoData []*EdbInfoSearchData, minValue, maxValue float64, err error) {
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+ allDataList := make([]*EdbInfoSearchData, 0)
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+ allDataList = append(allDataList, realPredictEdbInfoData...)
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+ allDataList = append(allDataList, predictEdbInfoData...)
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+ newPredictEdbInfoData = predictEdbInfoData
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+
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+ lenAllData := len(allDataList)
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+ if lenAllData < nValue || lenAllData <= 0 {
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+ return
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+ }
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+ if nValue <= 0 {
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+ return
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+ }
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+ // 分母
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+ decimalN := decimal.NewFromInt(int64(nValue))
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+
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+ //获取后面的预测数据
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+ dayList := getPredictEdbDayList(startDate, endDate, frequency)
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+ for k, currentDate := range dayList {
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+ tmpLenAllDataList := len(allDataList)
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+ tmpIndex := tmpLenAllDataList - 1 //上1期数据的下标
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+
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+ averageDateList := make([]string, 0) //计算平均数的日期
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+
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+ // 数据集合中的最后一个数据
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+ tmpDecimalVal := decimal.NewFromFloat(allDataList[tmpIndex].Value)
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+ averageDateList = append(averageDateList, allDataList[tmpIndex].DataTime)
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+ for tmpK := 2; tmpK <= nValue; tmpK++ {
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+ tmpIndex2 := tmpIndex - tmpK //上N期的值
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+ tmpDecimalVal2 := decimal.NewFromFloat(allDataList[tmpIndex2].Value)
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+ tmpDecimalVal = tmpDecimalVal.Add(tmpDecimalVal2)
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+ averageDateList = append(averageDateList, allDataList[tmpIndex2].DataTime)
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+ }
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+ // 最近的N期平均值
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+ tmpAverageVal := tmpDecimalVal.Div(decimalN)
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+
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+ var tmpHistoryCurrentVal float64 // 前几年当日的数据值
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+ var isFindHistoryCurrent, isFindHistoryLast bool //是否找到前几年的数据
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+ tmpHistoryDecimalVal := decimal.NewFromFloat(0) //前几年N期数据总值
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+
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+ {
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+ // 前几年N期汇总期数
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+ tmpHistoryValNum := 0
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+ {
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+ //前几年当日的日期
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+ tmpHistoryCurrentDate := currentDate.AddDate(year-currentDate.Year(), 0, 0)
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+ for i := 0; i <= 35; i++ { // 前后35天找数据，找到最近的值，先向后面找，再往前面找
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+ tmpDate := tmpHistoryCurrentDate.AddDate(0, 0, i)
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+ if val, ok := existMap[tmpDate.Format(utils.FormatDate)]; ok {
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+ tmpHistoryCurrentVal = val
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+ isFindHistoryCurrent = true
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+ break
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+ } else {
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+ tmpDate := tmpHistoryCurrentDate.AddDate(0, 0, -i)
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+ if val, ok := existMap[tmpDate.Format(utils.FormatDate)]; ok {
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+ tmpHistoryCurrentVal = val
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+ isFindHistoryCurrent = true
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+ break
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+ }
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+ }
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+ }
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+ }
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+
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+ for _, averageDate := range averageDateList {
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+ lastDay, tmpErr := time.ParseInLocation(utils.FormatDate, averageDate, time.Local)
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+ if tmpErr != nil {
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+ err = tmpErr
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+ return
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+ }
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+ //前几年上一期的日期
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+ tmpHistoryLastDate := lastDay.AddDate(year-lastDay.Year(), 0, 0)
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+ for i := 0; i <= 35; i++ { // 前后35天找数据，找到最近的值，先向后面找，再往前面找
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+ tmpDate := tmpHistoryLastDate.AddDate(0, 0, i)
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+ if val, ok := existMap[tmpDate.Format(utils.FormatDate)]; ok {
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+ tmpDecimalVal2 := decimal.NewFromFloat(val)
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+ tmpHistoryDecimalVal = tmpHistoryDecimalVal.Add(tmpDecimalVal2)
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+ tmpHistoryValNum++
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+ break
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+ } else {
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+ tmpDate := tmpHistoryLastDate.AddDate(0, 0, -i)
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+ if val, ok := existMap[tmpDate.Format(utils.FormatDate)]; ok {
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+ tmpDecimalVal2 := decimal.NewFromFloat(val)
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+ tmpHistoryDecimalVal = tmpHistoryDecimalVal.Add(tmpDecimalVal2)
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+ tmpHistoryValNum++
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+ break
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+ }
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+ }
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+ }
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+ }
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+
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+ // 汇总期数与配置的N期数量一致
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+ if tmpHistoryValNum == nValue {
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+ isFindHistoryLast = true
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+ }
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+ }
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+
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+ // 如果没有找到前几年的汇总数据，或者没有找到前几年当日的数据，那么退出当前循环，进入下一循环
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+ if !isFindHistoryLast || !isFindHistoryCurrent {
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+ continue
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+ }
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+
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+ // 计算最近N期同比值
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+ tbVal := tmpAverageVal.Div(tmpHistoryDecimalVal)
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+
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+ // 预测值结果 = 同比年份同期值（tmpHistoryCurrentVal的值）* 同比值（tbVal的值）
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+ val, _ := decimal.NewFromFloat(tmpHistoryCurrentVal).Mul(tbVal).RoundCeil(4).Float64()
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+
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+ currentDateStr := currentDate.Format(utils.FormatDate)
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+ tmpData := &EdbInfoSearchData{
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+ EdbDataId: edbInfoId + 10000000000 + lenAllData + k,
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+ //EdbInfoId: edbInfoId,
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+ DataTime: currentDateStr,
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+ Value: val,
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+ //DataTimestamp: (currentDate.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
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+ }
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+ newPredictEdbInfoData = append(newPredictEdbInfoData, tmpData)
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+ allDataList = append(allDataList, tmpData)
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+ existMap[currentDateStr] = val
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+
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+ // 最大最小值
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+ if val < minValue {
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+ minValue = val
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+ }
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+ if val > maxValue {
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+ maxValue = val
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+ }
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+ }
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+ return
|
|
|
+}
|
