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@@ -0,0 +1,490 @@
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+package services
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+
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+import (
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+ "encoding/json"
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+ "eta/eta_index_lib/models"
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+ "eta/eta_index_lib/utils"
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+ "fmt"
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+ "os"
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+ "os/exec"
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+ "path/filepath"
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+ "strconv"
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+ "time"
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+
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+ "github.com/tealeg/xlsx"
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+)
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+
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+const (
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+ ALL_DATE = iota + 1
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+ LAST_N_YEARS
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+ RANGE_DATE
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+ RANGE_DATE_TO_NOW
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+)
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+
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+type EdbStlConfig struct {
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+ EdbInfoId int `description:"指标ID"`
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+ CalculateStlConfigId int `description:"计算的STL配置ID"`
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+ DataRangeType int `description:"数据时间类型：1-全部时间，2-最近N年，3-区间设置，4-区间设置(至今)"`
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+ StartDate string `description:"开始日期"`
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+ EndDate string `description:"结束日期"`
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+ LastNYear int `description:"最近N年"`
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+ Period int `description:"数据的周期，根据频率设置"`
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+ Seasonal int `description:"季节性成分窗口大小，一般为period+1,可以设置为大于period的正奇数"`
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+ Trend int `description:"趋势成分窗口大小，一般为period+1,可以设置为大于period的正奇数"`
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+ Fraction float64 `description:"趋势项的平滑系数，默认为0.2，区间为[0-1]"`
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+ Robust bool `description:"是否使用稳健方法: true(使用) false(不使用) "`
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+ TrendDeg int `description:"分解中趋势多项式次数，默认为1，不超过5的正整数"`
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+ SeasonalDeg int `description:"分解中季节性多项次数，默认为1，不超过5的正整数"`
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+ LowPassDeg int `description:"分解中低通滤波器次数，默认为1，不超过5的正整数"`
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+}
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+
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+type ChartEdbInfo struct {
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+ EdbInfoId int
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+ Title string
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+ Unit string
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+ Frequency string
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+ MaxData float64
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+ MinData float64
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+ ClassifyId int
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+ ClassifyPath string
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+ DataList []*EdbData
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+}
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+
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+type EdbData struct {
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+ Value float64
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+ DataTime string
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+ DataTimestamp int64
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+}
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+
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+func RefreshStlData(edbInfoId int) (msg string, err error) {
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+ calculateStl, err := models.GetEdbInfoCalculateMappingDetail(edbInfoId)
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+ if err != nil {
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+ return
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+ }
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+
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+ fromEdbInfo, err := models.GetEdbInfoById(calculateStl.FromEdbInfoId)
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+ if err != nil {
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+ return
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+ }
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+ var stlConfig EdbStlConfig
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+ if err = json.Unmarshal([]byte(calculateStl.CalculateFormula), &stlConfig); err != nil {
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+ return
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+ }
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+ var condition string
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+ var pars []interface{}
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+ switch stlConfig.DataRangeType {
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+ case ALL_DATE:
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+ case LAST_N_YEARS:
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+ condition += " AND data_time >=?"
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+ year := time.Now().Year()
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+ lastDate := time.Date(year-stlConfig.LastNYear, 1, 1, 0, 0, 0, 0, time.Local)
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+ pars = append(pars, lastDate)
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+ case RANGE_DATE:
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+ condition = " AND data_time >=? AND data_time <=?"
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+ pars = append(pars, stlConfig.StartDate, stlConfig.EndDate)
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+ case RANGE_DATE_TO_NOW:
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+ condition = " AND data_time >=?"
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+ pars = append(pars, stlConfig.StartDate)
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+ }
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+ condition += " AND edb_code =?"
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+ pars = append(pars, fromEdbInfo.EdbCode)
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+
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+ edbData, err := models.GetEdbDataByCondition(fromEdbInfo.Source, fromEdbInfo.SubSource, condition, pars)
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+ if err != nil {
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+ return
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+ }
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+ var condMsg string
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+ if stlConfig.Period < 2 || stlConfig.Period > len(edbData) {
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+ condMsg += "period必须是一个大于等于2的正整数，且必须小于时间序列的长度"
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+ }
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+ if stlConfig.Seasonal < 3 || stlConfig.Seasonal%2 == 0 || stlConfig.Seasonal <= stlConfig.Period {
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+ if condMsg != "" {
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+ condMsg += "\n"
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+ }
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+ condMsg += "seasonal必须是一个大于等于3的奇整数，且必须大于period"
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+ }
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+ if stlConfig.Trend < 3 || stlConfig.Trend%2 == 0 || stlConfig.Trend <= stlConfig.Period {
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+ if condMsg != "" {
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+ condMsg += "\n"
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+ }
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+ condMsg += "trend必须是一个大于等于3的奇整数，且必须大于period"
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+ }
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+ if stlConfig.Fraction < 0 || stlConfig.Fraction > 1 {
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+ if condMsg != "" {
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+ condMsg += "\n"
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+ }
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+ condMsg += "fraction必须是一个介于[0-1]之间"
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+ }
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+ if 1 > stlConfig.TrendDeg || stlConfig.TrendDeg > 5 {
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+ if condMsg != "" {
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+ condMsg += "\n"
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+ }
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+ condMsg += "trend_deg请设置成1-5的整数"
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+ }
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+ if 1 > stlConfig.SeasonalDeg || stlConfig.SeasonalDeg > 5 {
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+ if condMsg != "" {
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+ condMsg += "\n"
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+ }
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+ condMsg += "seasonal_deg请设置成1-5的整数"
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+ }
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+ if 1 > stlConfig.LowPassDeg || stlConfig.LowPassDeg > 5 {
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+ if condMsg != "" {
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+ condMsg += "\n"
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+ }
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+ condMsg += "low_pass_deg请设置成1-5的整数"
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+ }
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+ if condMsg != "" {
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+ msg = condMsg
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+ err = fmt.Errorf("参数错误")
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+ return
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+ }
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+
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+ dir, _ := os.Executable()
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+ exPath := filepath.Dir(dir) + "/static/stl_tmp"
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+ err = CheckOsPathAndMake(exPath)
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+ if err != nil {
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+ msg = "计算失败"
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+ return
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+ }
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+ loadFilePath := exPath + "/" + strconv.Itoa(fromEdbInfo.SysUserId) + "_" + time.Now().Format(utils.FormatDateTimeUnSpace) + ".xlsx"
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+ err = SaveToExcel(edbData, loadFilePath)
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+ if err != nil {
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+ msg = "保存数据到Excel失败"
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+ return
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+ }
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+ defer os.Remove(loadFilePath)
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+ saveFilePath := exPath + "/" + strconv.Itoa(fromEdbInfo.SysUserId) + "_" + time.Now().Format(utils.FormatDateTimeUnSpace) + "_res" + ".xlsx"
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+ err = execStlPythonCode(loadFilePath, saveFilePath, stlConfig.Period, stlConfig.Seasonal, stlConfig.Trend, stlConfig.TrendDeg, stlConfig.SeasonalDeg, stlConfig.LowPassDeg, stlConfig.Fraction, stlConfig.Robust)
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+ if err != nil {
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+ msg = "执行Python代码失败"
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+ return
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+ }
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+
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+ trendChart, seasonalChart, residualChart, err := ParseStlExcel(saveFilePath)
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+ if err != nil {
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+ msg = "解析Excel失败"
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+ return
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+ }
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+ defer os.Remove(saveFilePath)
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+ edbInfo, err := models.GetEdbInfoById(edbInfoId)
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+ if err != nil {
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+ msg = "获取指标信息失败"
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+ return
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+ }
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+ err = SyncUpdateRelationEdbInfo(edbInfo, stlConfig, trendChart, seasonalChart, residualChart)
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+ if err != nil {
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+ msg = "更新关联指标失败"
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+ return
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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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+func SyncUpdateRelationEdbInfo(edbInfo *models.EdbInfo, config EdbStlConfig, trendData, seasonalData, residualData ChartEdbInfo) (err error) {
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+ configId, err := models.GetCalculateStlConfigMappingIdByEdbInfoId(edbInfo.EdbInfoId)
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+ if err != nil {
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+ return
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+ }
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+ mappingList, err := models.GetCalculateStlConfigMappingByConfigId(configId)
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+ if err != nil {
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+ return
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+ }
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+ for _, v := range mappingList {
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+ edbInfo, er := models.GetEdbInfoById(v.EdbInfoId)
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+ if er != nil {
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+ continue
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+ }
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+ switch v.StlEdbType {
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+ case 1:
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+ // 趋势指标
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+ er = UpdateStlEdbData(edbInfo, config, edbInfo.EdbCode, trendData)
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+ case 2:
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+ // 季节性指标
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+ er = UpdateStlEdbData(edbInfo, config, edbInfo.EdbCode, seasonalData)
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+ case 3:
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+ // 残差指标
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+ er = UpdateStlEdbData(edbInfo, config, edbInfo.EdbCode, residualData)
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+ default:
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+ utils.FileLog.Info("未知的stlEdbType类型, mapping:%v", v)
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+ continue
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+ }
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+ if er != nil {
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+ utils.FileLog.Error("更新指标数据失败, edbInfoId:%v, err:%v", v.EdbInfoId, er)
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+ err = er
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+ continue
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+ }
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+ }
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+ // 同步更新计算配置
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+ newStlConf := &models.CalculateStlConfig{
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+ CalculateStlConfigId: configId,
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+ Config: edbInfo.CalculateFormula,
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+ ModifyTime: time.Now(),
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+ }
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+ err = newStlConf.Update([]string{"config", "modify_time"})
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+ return
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+}
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+
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+func UpdateStlEdbData(edbInfo *models.EdbInfo, config EdbStlConfig, edbCode string, edbData ChartEdbInfo) (err error) {
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+ var dataList []*models.EdbDataCalculateStl
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+ for _, v := range edbData.DataList {
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+ dataTime, _ := time.Parse(utils.FormatDate, v.DataTime)
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+ dataList = append(dataList, &models.EdbDataCalculateStl{
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+ EdbInfoId: edbData.EdbInfoId,
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+ EdbCode: edbCode,
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+ DataTime: dataTime,
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+ Value: v.Value,
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+ CreateTime: time.Now(),
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+ ModifyTime: time.Now(),
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+ DataTimestamp: dataTime.UnixMilli(),
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+ })
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+ }
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+ err = models.DeleteAndInsertEdbDataCalculateStl(edbCode, dataList)
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+ if err != nil {
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+ return
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+ }
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+
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+ models.ModifyEdbInfoDataStatus(int64(edbInfo.EdbInfoId), edbInfo.Source, edbInfo.SubSource, edbInfo.EdbCode)
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+
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+ maxAndMinItem, _ := models.GetEdbInfoMaxAndMinInfo(edbInfo.Source, edbInfo.SubSource, edbInfo.EdbCode)
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+ if maxAndMinItem != nil {
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+ err = models.ModifyEdbInfoMaxAndMinInfo(edbInfo.EdbInfoId, maxAndMinItem)
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+ if err != nil {
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+ return
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+ }
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+ }
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+
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+ bconfig, _ := json.Marshal(config)
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+ edbInfo.CalculateFormula = string(bconfig)
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+ edbInfo.ModifyTime = time.Now()
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+ err = edbInfo.Update([]string{"calculate_formula", "modify_time"})
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+ if err != nil {
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+ return
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+ }
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+ return
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+}
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+
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+func CheckOsPathAndMake(path string) (err error) {
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+ if _, er := os.Stat(path); os.IsNotExist(er) {
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+ err = os.MkdirAll(path, os.ModePerm)
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+ }
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+ return
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+}
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+
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+func SaveToExcel(data []*models.EdbInfoSearchData, filePath string) (err error) {
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+ xlsxFile := xlsx.NewFile()
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+ sheetNew, err := xlsxFile.AddSheet("Tmp")
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+ if err != nil {
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+ return
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+ }
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+ titleRow := sheetNew.AddRow()
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+ titleRow.AddCell().SetString("日期")
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+ titleRow.AddCell().SetString("值")
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+
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+ for i, d := range data {
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+ row := sheetNew.Row(i + 1)
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+ row.AddCell().SetString(d.DataTime)
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+ row.AddCell().SetFloat(d.Value)
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+ }
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+ err = xlsxFile.Save(filePath)
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+ if err != nil {
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+ return
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+ }
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+ return
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+}
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+
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+func ParseStlExcel(excelPath string) (TrendChart, SeasonalChart, ResidualChart ChartEdbInfo, err error) {
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+ file, err := xlsx.OpenFile(excelPath)
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+ if err != nil {
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+ return
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+ }
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+ for _, sheet := range file.Sheets {
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+ switch sheet.Name {
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+ case "季节":
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+ var MinData, MaxData float64
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+ for i, row := range sheet.Rows {
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+ if i == 0 {
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+ continue
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+ }
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+ var date string
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+ var dataTimestamp int64
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+ if row.Cells[0].Type() == xlsx.CellTypeNumeric {
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+ dataNum, _ := strconv.ParseFloat(row.Cells[0].Value, 64)
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+ tmpTime := xlsx.TimeFromExcelTime(dataNum, false)
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+ date = tmpTime.Format(utils.FormatDate)
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+ dataTimestamp = tmpTime.UnixMilli()
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+ } else {
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+ timeDate, _ := time.Parse(utils.FormatDateTime, date)
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+ date = timeDate.Format(utils.FormatDate)
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+ dataTimestamp = timeDate.UnixMilli()
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+ }
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+ fv, _ := row.Cells[1].Float()
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+ if MinData == 0 || fv < MinData {
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+ MinData = fv
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+ }
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+ if MaxData == 0 || fv > MaxData {
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+ MaxData = fv
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+ }
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+ SeasonalChart.DataList = append(SeasonalChart.DataList, &EdbData{DataTime: date, Value: fv, DataTimestamp: dataTimestamp})
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+ }
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+ SeasonalChart.MinData = MinData
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+ SeasonalChart.MaxData = MaxData
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+ case "趋势":
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+ var MinData, MaxData float64
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+ for i, row := range sheet.Rows {
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+ if i == 0 {
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+ continue
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+ }
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+ var date string
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+ var dataTimestamp int64
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+ if row.Cells[0].Type() == xlsx.CellTypeNumeric {
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+ dataNum, _ := strconv.ParseFloat(row.Cells[0].Value, 64)
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+ tmpTime := xlsx.TimeFromExcelTime(dataNum, false)
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+ date = tmpTime.Format(utils.FormatDate)
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+ dataTimestamp = tmpTime.UnixMilli()
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+ } else {
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+ timeDate, _ := time.Parse(utils.FormatDateTime, date)
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+ date = timeDate.Format(utils.FormatDate)
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+ dataTimestamp = timeDate.UnixMilli()
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+ }
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+ fv, _ := row.Cells[1].Float()
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+ if MinData == 0 || fv < MinData {
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+ MinData = fv
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+ }
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+ if MaxData == 0 || fv > MaxData {
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+ MaxData = fv
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+ }
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+ TrendChart.DataList = append(TrendChart.DataList, &EdbData{DataTime: date, Value: fv, DataTimestamp: dataTimestamp})
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+ }
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+ TrendChart.MaxData = MaxData
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+ TrendChart.MinData = MinData
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+ case "残差":
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+ var MinData, MaxData float64
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+ for i, row := range sheet.Rows {
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+ if i == 0 {
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+ continue
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+ }
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+ var date string
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+ var dataTimestamp int64
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+ if row.Cells[0].Type() == xlsx.CellTypeNumeric {
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+ dataNum, _ := strconv.ParseFloat(row.Cells[0].Value, 64)
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+ tmpTime := xlsx.TimeFromExcelTime(dataNum, false)
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+ date = tmpTime.Format(utils.FormatDate)
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+ dataTimestamp = tmpTime.UnixMilli()
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+ } else {
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+ timeDate, _ := time.Parse(utils.FormatDateTime, date)
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+ date = timeDate.Format(utils.FormatDate)
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+ dataTimestamp = timeDate.UnixMilli()
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+ }
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+ fv, _ := row.Cells[1].Float()
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+ if MinData == 0 || fv < MinData {
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|
|
+ MinData = fv
|
|
|
+ }
|
|
|
+ if MaxData == 0 || fv > MaxData {
|
|
|
+ MaxData = fv
|
|
|
+ }
|
|
|
+ ResidualChart.DataList = append(ResidualChart.DataList, &EdbData{DataTime: date, Value: fv, DataTimestamp: dataTimestamp})
|
|
|
+ }
|
|
|
+ ResidualChart.MaxData = MaxData
|
|
|
+ ResidualChart.MinData = MinData
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return
|
|
|
+}
|
|
|
+
|
|
|
+func execStlPythonCode(path, toPath string, period, seasonal, trend, trendDeg, seasonalDeg, lowPassDeg int, fraction float64, robust bool) (err error) {
|
|
|
+ pythonCode := `
|
|
|
+import pandas as pd
|
|
|
+from statsmodels.tsa.seasonal import STL
|
|
|
+from statsmodels.nonparametric.smoothers_lowess import lowess
|
|
|
+from statsmodels.tsa.stattools import adfuller
|
|
|
+from statsmodels.stats.diagnostic import acorr_ljungbox
|
|
|
+import numpy as np
|
|
|
+import json
|
|
|
+import warnings
|
|
|
+warnings.filterwarnings('ignore')
|
|
|
+
|
|
|
+file_path = r"%s"
|
|
|
+df = pd.read_excel(file_path, parse_dates=['日期'])
|
|
|
+df.set_index('日期', inplace=True)
|
|
|
+
|
|
|
+
|
|
|
+period = %d
|
|
|
+seasonal = %d
|
|
|
+trend = %d
|
|
|
+fraction = %g
|
|
|
+seasonal_deg = %d
|
|
|
+trend_deg = %d
|
|
|
+low_pass_deg = %d
|
|
|
+robust = %s
|
|
|
+
|
|
|
+stl = STL(
|
|
|
+ df['值'],
|
|
|
+ period=period,
|
|
|
+ seasonal=seasonal,
|
|
|
+ trend=trend,
|
|
|
+ low_pass=None,
|
|
|
+ seasonal_deg=seasonal_deg,
|
|
|
+ trend_deg=trend_deg,
|
|
|
+ low_pass_deg=low_pass_deg,
|
|
|
+ seasonal_jump=1,
|
|
|
+ trend_jump=1,
|
|
|
+ low_pass_jump=1,
|
|
|
+ robust=robust
|
|
|
+)
|
|
|
+result = stl.fit()
|
|
|
+
|
|
|
+smoothed = lowess(df['值'], df.index, frac=fraction)
|
|
|
+
|
|
|
+trend_lowess = smoothed[:, 1]
|
|
|
+
|
|
|
+# 季节图
|
|
|
+seasonal_component = result.seasonal
|
|
|
+# 趋势图
|
|
|
+trend_lowess_series = pd.Series(trend_lowess, index=df.index)
|
|
|
+# 残差图
|
|
|
+residual_component = df['值'] - trend_lowess - seasonal_component
|
|
|
+
|
|
|
+# 计算打印残差的均值
|
|
|
+residual_mean = np.mean(residual_component)
|
|
|
+# 计算打印残差的方差
|
|
|
+residual_var = np.std(residual_component)
|
|
|
+# 计算打印残差的ADF检验结果, 输出p-value
|
|
|
+adf_result = adfuller(residual_component)
|
|
|
+# 根据p-value判断是否平稳
|
|
|
+lb_test = acorr_ljungbox(residual_component, lags=period, return_df=True)
|
|
|
+
|
|
|
+output_file = r"%s"
|
|
|
+
|
|
|
+with pd.ExcelWriter(output_file) as writer:
|
|
|
+ # 保存季节图
|
|
|
+ pd.Series(seasonal_component, index=df.index, name='值').to_frame().reset_index().rename(columns={'index': '日期'}).to_excel(writer, sheet_name='季节', index=False)
|
|
|
+ # 保存趋势图
|
|
|
+ trend_lowess_series.to_frame(name='值').reset_index().rename(columns={'index': '日期'}).to_excel(writer, sheet_name='趋势', index=False)
|
|
|
+ # 保存残差图
|
|
|
+ pd.Series(residual_component, index=df.index, name='值').to_frame().reset_index().rename(columns={'index': '日期'}).to_excel(writer, sheet_name='残差', index=False)
|
|
|
+
|
|
|
+output = json.dumps({
|
|
|
+ 'residual_mean': residual_mean,
|
|
|
+ 'residual_var': residual_var,
|
|
|
+ 'adf_p_value': adf_result[1],
|
|
|
+ 'lb_test_p_value': lb_test['lb_pvalue'].values[0],
|
|
|
+ 'lb_test_stat': lb_test['lb_stat'].values[0]
|
|
|
+})
|
|
|
+
|
|
|
+print(output)
|
|
|
+ `
|
|
|
+ robustStr := "True"
|
|
|
+ if !robust {
|
|
|
+ robustStr = "False"
|
|
|
+ }
|
|
|
+
|
|
|
+ pythonCode = fmt.Sprintf(pythonCode, path, period, seasonal, trend, fraction, seasonalDeg, trendDeg, lowPassDeg, robustStr, toPath)
|
|
|
+ // cmd := exec.Command(`python3`, "-c", pythonCode)
|
|
|
+ cmd := exec.Command(`D:\conda\envs\py311\python`, "-c", pythonCode)
|
|
|
+ _, err = cmd.CombinedOutput()
|
|
|
+ if err != nil {
|
|
|
+ return
|
|
|
+ }
|
|
|
+ defer cmd.Process.Kill()
|
|
|
+ return
|
|
|
+}
|
zqbao