eta_index_lib/models/predict_edb_data_calculate_kszs.go

package models

import (
	"encoding/json"
	"errors"
	"fmt"
	"github.com/beego/beego/v2/client/orm"
	"github.com/shopspring/decimal"
	"hongze/hongze_edb_lib/utils"
	"strconv"
	"strings"
	"time"
)

// SavePredictCalculateKszs 预测扩散指数
func SavePredictCalculateKszs(reqEdbInfoId, classifyId int, edbName, frequency, unit, formula string, relationCalculateEdbInfoIdList []EdbInfoCalculateEdbInfoIdReq, edbCode, uniqueCode string, sysUserId int, sysUserRealName string) (edbInfo *EdbInfo, latestDateStr string, latestValue float64, err error, errMsg string) {
	o := orm.NewOrm()
	to, err := o.Begin()
	if err != nil {
		return
	}
	defer func() {
		if err != nil {
			fmt.Println("SavePredictCalculateKszs,Err:" + err.Error())
			_ = to.Rollback()
		} else {
			_ = to.Commit()
		}
	}()
	fmt.Println("reqEdbInfoId:", reqEdbInfoId)

	tagMap := make(map[string]int) //指标的标签map
	relationEdbInfoList := make([]*EdbInfo, 0)
	if reqEdbInfoId <= 0 {
		edbInfo = &EdbInfo{
			//EdbInfoId:        0,
			EdbInfoType:   1,
			SourceName:    utils.DATA_SOURCE_NAME_PREDICT_CALCULATE_KSZS,
			Source:        utils.DATA_SOURCE_PREDICT_CALCULATE_KSZS,
			EdbCode:       edbCode,
			EdbName:       edbName,
			EdbNameSource: edbName,
			Frequency:     frequency,
			Unit:          unit,
			//StartDate:        "",
			//EndDate:          "",
			ClassifyId:       classifyId,
			SysUserId:        sysUserId,
			SysUserRealName:  sysUserRealName,
			UniqueCode:       uniqueCode,
			CreateTime:       time.Now(),
			ModifyTime:       time.Now(),
			MinValue:         0,
			MaxValue:         0,
			CalculateFormula: formula,
			EdbType:          2,
			Sort:             0,
			MoveType:         0,
			MoveFrequency:    "",
			NoUpdate:         0,
			ServerUrl:        "",
			EdbNameEn:        "",
			UnitEn:           "",
			LatestDate:       "",
			LatestValue:      0,
			ChartImage:       "",
		}
		newEdbInfoId, tmpErr := to.Insert(edbInfo)
		if tmpErr != nil {
			err = tmpErr
			return
		}
		edbInfo.EdbInfoId = int(newEdbInfoId)

		//关联关系
		calculateMappingItemList := make([]*EdbInfoCalculateMapping, 0)
		for _, v := range relationCalculateEdbInfoIdList {
			tmpEdbInfo, tmpErr := GetEdbInfoById(v.EdbInfoId)
			if tmpErr != nil {
				err = tmpErr
				return
			}
			relationEdbInfoList = append(relationEdbInfoList, tmpEdbInfo)

			calculateMappingItem := new(EdbInfoCalculateMapping)
			calculateMappingItem.CreateTime = time.Now()
			calculateMappingItem.ModifyTime = time.Now()
			calculateMappingItem.Sort = 1
			calculateMappingItem.EdbCode = edbCode
			calculateMappingItem.EdbInfoId = edbInfo.EdbInfoId
			calculateMappingItem.FromEdbInfoId = tmpEdbInfo.EdbInfoId
			calculateMappingItem.FromEdbCode = tmpEdbInfo.EdbCode
			calculateMappingItem.FromEdbName = tmpEdbInfo.EdbName
			calculateMappingItem.FromSource = tmpEdbInfo.Source
			calculateMappingItem.FromSourceName = tmpEdbInfo.SourceName
			calculateMappingItem.FromTag = v.FromTag
			calculateMappingItem.Source = edbInfo.Source
			calculateMappingItem.SourceName = edbInfo.SourceName
			calculateMappingItemList = append(calculateMappingItemList, calculateMappingItem)

			tagMap[v.FromTag] = v.EdbInfoId
		}
		_, err = to.InsertMulti(len(calculateMappingItemList), calculateMappingItemList)
		if err != nil {
			return
		}
	} else {
		edbInfo, err = GetEdbInfoById(reqEdbInfoId)
		if err != nil {
			if err.Error() == utils.ErrNoRow() {
				errMsg = `获取指标信息失败`
			}
			return
		}
		if edbInfo.EdbInfoType != 1 {
			errMsg = `该指标不是预测指标`
			err = errors.New(errMsg)
			return
		}
		//修改指标信息
		edbInfo.EdbName = edbName
		edbInfo.EdbNameSource = edbName
		edbInfo.Frequency = frequency
		edbInfo.Unit = unit
		edbInfo.ClassifyId = classifyId
		edbInfo.CalculateFormula = formula
		edbInfo.ModifyTime = time.Now()
		_, err = to.Update(edbInfo, "EdbName", "EdbNameSource", "Frequency", "Unit", "ClassifyId", "CalculateFormula", "ModifyTime")
		if err != nil {
			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.Raw(sql, edbInfo.EdbInfoId).Exec()
		if err != nil {
			err = errors.New("删除计算指标关联关系失败,Err:" + err.Error())
			return
		}
		//清空原有数据
		tableName := GetEdbDataTableName(edbInfo.Source)
		sql = ` DELETE FROM ` + tableName + ` WHERE edb_info_id = ? `
		_, err = to.Raw(sql, edbInfo.EdbInfoId).Exec()
		if err != nil {
			return
		}

		//关联关系
		calculateMappingItemList := make([]*EdbInfoCalculateMapping, 0)
		for _, v := range relationCalculateEdbInfoIdList {
			tmpEdbInfo, tmpErr := GetEdbInfoById(v.EdbInfoId)
			if tmpErr != nil {
				err = tmpErr
				return
			}
			relationEdbInfoList = append(relationEdbInfoList, tmpEdbInfo)

			calculateMappingItem := new(EdbInfoCalculateMapping)
			calculateMappingItem.CreateTime = time.Now()
			calculateMappingItem.ModifyTime = time.Now()
			calculateMappingItem.Sort = 1
			calculateMappingItem.EdbCode = edbInfo.EdbCode
			calculateMappingItem.EdbInfoId = edbInfo.EdbInfoId
			calculateMappingItem.FromEdbInfoId = tmpEdbInfo.EdbInfoId
			calculateMappingItem.FromEdbCode = tmpEdbInfo.EdbCode
			calculateMappingItem.FromEdbName = tmpEdbInfo.EdbName
			calculateMappingItem.FromSource = tmpEdbInfo.Source
			calculateMappingItem.FromSourceName = tmpEdbInfo.SourceName
			calculateMappingItem.FromTag = v.FromTag
			calculateMappingItem.Source = edbInfo.Source
			calculateMappingItem.SourceName = edbInfo.SourceName
			calculateMappingItemList = append(calculateMappingItemList, calculateMappingItem)

			tagMap[v.FromTag] = v.EdbInfoId
		}
		_, err = to.InsertMulti(len(calculateMappingItemList), calculateMappingItemList)
		if err != nil {
			return
		}

	}

	// 计算数据
	latestDateStr, latestValue, err = refreshAllPredictCalculateKszs(to, edbInfo.EdbInfoId, edbInfo.Source, relationEdbInfoList, edbCode, formula, tagMap)

	return
}

// RefreshAllPredictCalculateKszs 刷新全部预测扩散指数数据
func RefreshAllPredictCalculateKszs(edbInfo *EdbInfo) (latestDateStr string, latestValue float64, err error) {
	edbInfoCalculateDetailList, err := GetEdbInfoCalculateDetailList(edbInfo.EdbInfoId)
	if err != nil {
		return
	}
	tagMap := make(map[string]int)
	relationEdbInfoList := make([]*EdbInfo, 0)
	for _, v := range edbInfoCalculateDetailList {
		tagMap[v.FromTag] = v.FromEdbInfoId
		fromEdbInfo, _ := GetEdbInfoById(v.FromEdbInfoId)
		relationEdbInfoList = append(relationEdbInfoList, fromEdbInfo)
	}

	o := orm.NewOrm()
	to, err := o.Begin()
	if err != nil {
		return
	}
	defer func() {
		if err != nil {
			fmt.Println("RefreshAllCalculateKszs,Err:" + err.Error())
			_ = to.Rollback()
		} else {
			_ = to.Commit()
		}
	}()

	// 计算数据
	latestDateStr, latestValue, err = refreshAllPredictCalculateKszs(to, edbInfo.EdbInfoId, edbInfo.Source, relationEdbInfoList, edbInfo.EdbCode, edbInfo.CalculateFormula, tagMap)
	return
}

// refreshAllPredictCalculateKszs 刷新预测年化数据
func refreshAllPredictCalculateKszs(to orm.TxOrmer, edbInfoId, source int, relationEdbInfoList []*EdbInfo, edbCode, calculateFormula string, tagMap map[string]int) (latestDateStr string, latestValue float64, err error) {
	edbInfoIdStr := strconv.Itoa(edbInfoId)
	tableName := GetEdbDataTableName(utils.DATA_SOURCE_PREDICT_CALCULATE_KSZS)

	// 获取扩散指标关联的指标id
	checkEdbInfoIdMap := make(map[int]int)
	{
		var config KszsConfig
		err = json.Unmarshal([]byte(calculateFormula), &config)
		if err != nil {
			return
		}
		if config.DateType == 1 {
			for _, tmpEdbInfoId := range tagMap {
				checkEdbInfoIdMap[tmpEdbInfoId] = tmpEdbInfoId
			}
		} else {
			for _, v := range config.CheckList {
				if tmpEdbInfoId, ok := tagMap[v]; ok {
					checkEdbInfoIdMap[tmpEdbInfoId] = tmpEdbInfoId
				}
			}
		}
	}

	//获取当前指标的所有数据
	existDataList, err := GetAllEdbDataListByTo(to, edbInfoId, source)
	if err != nil {
		return
	}
	//计算指标的map
	existDataMap := make(map[string]*EdbData, 0)
	removeDateMap := make(map[string]string)
	for _, v := range existDataList {
		existDataMap[v.DataTime] = v
		removeDateMap[v.DataTime] = ``
	}

	var latestDateTime time.Time       //真实数据的最后日期
	var hasValLatestDateTime time.Time // 存在数据的真实日期(正常情况下,这两个值是相等的,除非出现一种情况:真实数据的最后日期当天 计算不出结果,那么 hasValLatestDateTime 不等于 latestDateTime)
	//获取来源指标的数据
	relationEdbDataMap := make(map[int]map[string]float64)
	// 获取选择指标的 需要数据的 开始日期和结束日期
	var startDate, endDate time.Time
	for _, v := range relationEdbInfoList {
		tmpLatestDate, _ := time.ParseInLocation(utils.FormatDate, v.LatestDate, time.Local)
		if latestDateTime.IsZero() || latestDateTime.After(tmpLatestDate) {
			// 真实数据的最后日期
			latestDateTime = tmpLatestDate
		}

		tmpDataList, tmpErr := GetPredictEdbDataListAll(v, 1)
		if tmpErr != nil {
			err = tmpErr
			return
		}
		if tmpDataList != nil {
			if _, ok2 := checkEdbInfoIdMap[v.EdbInfoId]; ok2 {
				lenTmpDataList := len(tmpDataList)
				if lenTmpDataList > 0 {
					tmpStartTime, _ := time.ParseInLocation(utils.FormatDate, tmpDataList[0].DataTime, time.Local)
					tmpEndTime, _ := time.ParseInLocation(utils.FormatDate, tmpDataList[lenTmpDataList-1].DataTime, time.Local)

					if startDate.IsZero() || tmpStartTime.Before(startDate) {
						startDate = tmpStartTime
					}

					if tmpEndTime.IsZero() || tmpEndTime.After(endDate) {
						endDate = tmpEndTime
					}
				}
			}
			// 用上期的数据补充当期的数据处理
			handleDataMap := make(map[string]float64)
			err = HandleDataByPreviousData(tmpDataList, handleDataMap)
			if err != nil {
				return
			}
			relationEdbDataMap[v.EdbInfoId] = handleDataMap
		}
	}

	addSql := ` INSERT INTO ` + tableName + ` (edb_info_id,edb_code,data_time,value,create_time,modify_time,data_timestamp) values `
	var isAdd bool

	for currDate := startDate.AddDate(0, 0, 1); !currDate.After(endDate); currDate = currDate.AddDate(0, 0, 1) {
		currDateStr := currDate.Format(utils.FormatDate)

		//环差指数列表
		tmpValList := make([]float64, 0)
		for _, dataMap := range relationEdbDataMap {
			currVal, ok := dataMap[currDateStr]
			if !ok {
				continue
			}

			perVal, ok := dataMap[currDate.AddDate(0, 0, -1).Format(utils.FormatDate)]
			if !ok {
				continue
			}

			var tmpVal float64
			if currVal > perVal {
				tmpVal = 1
			} else if currVal == perVal {
				tmpVal = 0.5
			} else {
				tmpVal = 0
			}
			tmpValList = append(tmpValList, tmpVal)
		}

		lenTmpValList := len(tmpValList)
		if lenTmpValList <= 0 {
			continue
		}

		currValDeci := decimal.NewFromFloat(0)
		for _, tmpVal := range tmpValList {
			currValDeci = currValDeci.Add(decimal.NewFromFloat(tmpVal))
		}
		currVal, _ := currValDeci.Div(decimal.NewFromInt(int64(lenTmpValList))).Round(4).Float64()

		// 如果存在数据的真实日期为空,或者 当前日期 早于或等于 实际数据的日期,那么就给 存在数据的真实日期 赋值
		if hasValLatestDateTime.IsZero() || currDate.Before(latestDateTime) || currDate.Equal(latestDateTime) {
			latestValue = currVal
			hasValLatestDateTime = currDate
		}

		// 判断扩散指数指标是否存在数据
		if existData, ok := existDataMap[currDateStr]; ok {
			// 处理扩散指数数据的值
			existValStr := existData.Value
			existValDeci, tmpErr := decimal.NewFromString(existValStr)
			if tmpErr != nil {
				err = tmpErr
				return
			}
			existVal, _ := existValDeci.Round(4).Float64()
			// 判断扩散指数数据的值 与 当前计算出来的结果, 如果两个数据结果不相等的话,那么就修改咯
			if existVal != currVal {
				err = ModifyEdbDataById(source, existData.EdbDataId, fmt.Sprint(currVal))
				if err != nil {
					return
				}
			}
		} else {
			// 直接入库
			timestamp := currDate.UnixNano() / 1e6
			timestampStr := fmt.Sprintf("%d", timestamp)
			addSql += GetAddSql(edbInfoIdStr, edbCode, currDateStr, timestampStr, fmt.Sprint(currVal))
			isAdd = true
		}

		delete(removeDateMap, currDateStr)
	}

	if isAdd {
		addSql = strings.TrimRight(addSql, ",")
		_, err = to.Raw(addSql).Exec()
	}

	// 移除不存在的日期数据
	if len(removeDateMap) > 0 {
		removeDateList := make([]string, 0) //需要移除的日期
		for k := range removeDateMap {
			removeDateList = append(removeDateList, k)
		}
		removeDateStr := strings.Join(removeDateList, `","`)
		removeDateStr = `"` + removeDateStr + `"`
		sql := fmt.Sprintf(` DELETE FROM %s WHERE edb_info_id = ? and data_time in (%s) `, tableName, removeDateStr)
		_, err = to.Raw(sql, edbInfoId).Exec()
		if err != nil {
			err = fmt.Errorf("删除扩散指数指标数据失败,Err:" + err.Error())
			return
		}
	}

	// 真实数据的最后日期
	latestDateStr = hasValLatestDateTime.Format(utils.FormatDate)

	return
}