predict_edb_info.go 15 KB

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  1. package data
  2. import (
  3. "encoding/json"
  4. "errors"
  5. "github.com/shopspring/decimal"
  6. "hongze/hongze_chart_lib/models"
  7. "hongze/hongze_chart_lib/models/data_manage"
  8. "hongze/hongze_chart_lib/utils"
  9. "strconv"
  10. "time"
  11. )
  12. // GetChartPredictEdbInfoDataList 获取图表的预测指标的未来数据
  13. func GetChartPredictEdbInfoDataList(predictEdbConf data_manage.PredictEdbConf, filtrateStartDateStr, latestDateStr string, lastDataValue float64, endDateStr, frequency string) (predictEdbInfoData []*models.EdbDataList, err error) {
  14. endDate, err := time.ParseInLocation(utils.FormatDate, endDateStr, time.Local)
  15. if err != nil {
  16. return
  17. }
  18. latestDate, err := time.ParseInLocation(utils.FormatDate, latestDateStr, time.Local)
  19. if err != nil {
  20. return
  21. }
  22. // 开始预测数据的时间
  23. startDate := latestDate
  24. // 如果有筛选时间的话
  25. if filtrateStartDateStr != `` {
  26. filtrateStartDate, tmpErr := time.ParseInLocation(utils.FormatDate, filtrateStartDateStr, time.Local)
  27. if tmpErr != nil {
  28. err = tmpErr
  29. return
  30. }
  31. //如果筛选时间晚于实际数据时间,那么就以筛选时间作为获取预测数据的时间
  32. if filtrateStartDate.After(latestDate) {
  33. startDate = filtrateStartDate.AddDate(0, 0, -1)
  34. }
  35. }
  36. dataValue := lastDataValue
  37. if predictEdbConf.RuleType == 2 {
  38. dataValue = predictEdbConf.FixedValue
  39. }
  40. //获取后面的预测数据
  41. dayList := getPredictEdbDayList(startDate, endDate, frequency)
  42. predictEdbInfoData = make([]*models.EdbDataList, 0)
  43. for k, v := range dayList {
  44. predictEdbInfoData = append(predictEdbInfoData, &models.EdbDataList{
  45. EdbDataId: predictEdbConf.PredictEdbInfoId + 10000000000 + k,
  46. EdbInfoId: predictEdbConf.PredictEdbInfoId,
  47. DataTime: v.Format(utils.FormatDate),
  48. Value: dataValue,
  49. DataTimestamp: (v.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
  50. })
  51. }
  52. return
  53. }
  54. // GetPredictEdbDayList 获取预测指标日期列表
  55. func getPredictEdbDayList(startDate, endDate time.Time, frequency string) (dayList []time.Time) {
  56. //if !utils.InArrayByStr([]string{"日度", "周度", "月度"}, frequency)
  57. switch frequency {
  58. case "日度":
  59. for currDate := startDate.AddDate(0, 0, 1); currDate.Before(endDate) || currDate.Equal(endDate); currDate = currDate.AddDate(0, 0, 1) {
  60. //周六、日排除
  61. if currDate.Weekday() == time.Sunday || currDate.Weekday() == time.Saturday {
  62. continue
  63. }
  64. dayList = append(dayList, currDate)
  65. }
  66. case "周度":
  67. //nextDate := startDate.AddDate(0, 0, 7)
  68. for currDate := startDate.AddDate(0, 0, 7); currDate.Before(endDate) || currDate.Equal(endDate); currDate = currDate.AddDate(0, 0, 7) {
  69. dayList = append(dayList, currDate)
  70. }
  71. case "月度":
  72. for currDate := startDate; currDate.Before(endDate) || currDate.Equal(endDate); {
  73. currDate = time.Date(currDate.Year(), currDate.Month(), 1, 0, 0, 0, 0, time.Now().Location()).AddDate(0, 1, -1)
  74. if !currDate.After(endDate) && !currDate.Equal(startDate) {
  75. dayList = append(dayList, currDate)
  76. }
  77. currDate = currDate.AddDate(0, 0, 1)
  78. }
  79. }
  80. return
  81. }
  82. // GetPredictDataListByPredictEdbInfoId 根据预测指标id获取预测指标的数据
  83. func GetPredictDataListByPredictEdbInfoId(edbInfoId int, startDate, endDate string, isTimeBetween bool) (edbInfo *data_manage.EdbInfo, dataList []*models.EdbDataList, sourceEdbInfoItem *data_manage.EdbInfo, predictEdbConf *data_manage.PredictEdbConf, err error, errMsg string) {
  84. edbInfo, err = data_manage.GetEdbInfoById(edbInfoId)
  85. if err != nil {
  86. errMsg = `获取预测指标信息失败`
  87. return
  88. }
  89. dataList, sourceEdbInfoItem, predictEdbConf, err, errMsg = GetPredictDataListByPredictEdbInfo(edbInfo, startDate, endDate, isTimeBetween)
  90. return
  91. }
  92. // GetPredictDataListByPredictEdbInfo 根据预测指标信息获取预测指标的数据
  93. func GetPredictDataListByPredictEdbInfo(edbInfo *data_manage.EdbInfo, startDate, endDate string, isTimeBetween bool) (dataList []*models.EdbDataList, sourceEdbInfoItem *data_manage.EdbInfo, predictEdbConf *data_manage.PredictEdbConf, err error, errMsg string) {
  94. // 非计算指标,直接从表里获取数据
  95. if edbInfo.EdbType != 1 {
  96. if !isTimeBetween {
  97. endDate = ``
  98. }
  99. return GetPredictCalculateDataListByPredictEdbInfo(edbInfo, startDate, endDate)
  100. }
  101. // 查找该预测指标配置
  102. predictEdbConfList, err := data_manage.GetPredictEdbConfListById(edbInfo.EdbInfoId)
  103. if err != nil && err.Error() != utils.ErrNoRow() {
  104. errMsg = "获取预测指标配置信息失败"
  105. return
  106. }
  107. if len(predictEdbConfList) == 0 {
  108. errMsg = "获取预测指标配置信息失败"
  109. err = errors.New(errMsg)
  110. return
  111. }
  112. predictEdbConf = predictEdbConfList[0]
  113. if predictEdbConf == nil {
  114. errMsg = "获取预测指标配置信息失败"
  115. err = errors.New(errMsg)
  116. return
  117. }
  118. // 来源指标
  119. sourceEdbInfoItem, err = data_manage.GetEdbInfoById(predictEdbConf.SourceEdbInfoId)
  120. if err != nil {
  121. if err.Error() == utils.ErrNoRow() {
  122. errMsg = "找不到来源指标信息"
  123. err = errors.New(errMsg)
  124. }
  125. return
  126. }
  127. // 所有数据
  128. allDataList := make([]*models.EdbDataList, 0)
  129. //获取指标数据(实际已生成)
  130. dataList, err = models.GetEdbDataList(sourceEdbInfoItem.Source, sourceEdbInfoItem.EdbInfoId, startDate, endDate)
  131. if err != nil {
  132. return
  133. }
  134. // 如果选择了日期,那么需要筛选所有的数据,用于未来指标的生成
  135. if startDate != `` {
  136. allDataList, err = models.GetEdbDataList(sourceEdbInfoItem.Source, sourceEdbInfoItem.EdbInfoId, "", "")
  137. if err != nil {
  138. return
  139. }
  140. } else {
  141. allDataList = dataList
  142. }
  143. // 获取预测指标未来的数据
  144. predictDataList := make([]*models.EdbDataList, 0)
  145. endDateStr := edbInfo.EndDate //预测指标的结束日期
  146. if isTimeBetween { //如果是时间区间,那么
  147. reqEndDateTime, _ := time.ParseInLocation(utils.FormatDate, endDate, time.Local)
  148. endDateTime, _ := time.ParseInLocation(utils.FormatDate, edbInfo.EndDate, time.Local)
  149. // 如果选择的时间区间结束日期 晚于 当天,那么预测数据截止到当天
  150. if reqEndDateTime.Before(endDateTime) {
  151. endDateStr = endDate
  152. }
  153. }
  154. //predictDataList, err = GetChartPredictEdbInfoDataList(*predictEdbConf, startDate, sourceEdbInfoItem.LatestDate, sourceEdbInfoItem.LatestValue, endDateStr, edbInfo.Frequency)
  155. var predictMinValue, predictMaxValue float64
  156. predictDataList, predictMinValue, predictMaxValue, err = GetChartPredictEdbInfoDataListByConfList(predictEdbConfList, startDate, sourceEdbInfoItem.LatestDate, endDateStr, edbInfo.Frequency, allDataList)
  157. if err != nil {
  158. return
  159. }
  160. dataList = append(dataList, predictDataList...)
  161. if len(predictDataList) > 0 {
  162. // 如果最小值 大于 预测值,那么将预测值作为最小值数据返回
  163. if edbInfo.MinValue > predictMinValue {
  164. edbInfo.MinValue = predictMinValue
  165. }
  166. // 如果最大值 小于 预测值,那么将预测值作为最大值数据返回
  167. if edbInfo.MaxValue < predictMaxValue {
  168. edbInfo.MaxValue = predictMaxValue
  169. }
  170. }
  171. return
  172. }
  173. // GetPredictCalculateDataListByPredictEdbInfo 根据预测运算指标信息获取预测指标的数据
  174. func GetPredictCalculateDataListByPredictEdbInfo(edbInfo *data_manage.EdbInfo, startDate, endDate string) (dataList []*models.EdbDataList, sourceEdbInfoItem *data_manage.EdbInfo, predictEdbConf *data_manage.PredictEdbConf, err error, errMsg string) {
  175. dataList, err = models.GetEdbDataList(edbInfo.Source, edbInfo.EdbInfoId, startDate, endDate)
  176. return
  177. }
  178. // GetChartPredictEdbInfoDataListByConfList 获取图表的预测指标的未来数据
  179. func GetChartPredictEdbInfoDataListByConfList(predictEdbConfList []*data_manage.PredictEdbConf, filtrateStartDateStr, latestDateStr, endDateStr, frequency string, realPredictEdbInfoData []*models.EdbDataList) (predictEdbInfoData []*models.EdbDataList, minValue, maxValue float64, err error) {
  180. endDate, err := time.ParseInLocation(utils.FormatDate, endDateStr, time.Local)
  181. if err != nil {
  182. return
  183. }
  184. latestDate, err := time.ParseInLocation(utils.FormatDate, latestDateStr, time.Local)
  185. if err != nil {
  186. return
  187. }
  188. // 开始预测数据的时间
  189. startDate := latestDate
  190. // 如果有筛选时间的话
  191. if filtrateStartDateStr != `` {
  192. filtrateStartDate, tmpErr := time.ParseInLocation(utils.FormatDate, filtrateStartDateStr, time.Local)
  193. if tmpErr != nil {
  194. err = tmpErr
  195. return
  196. }
  197. //如果筛选时间晚于实际数据时间,那么就以筛选时间作为获取预测数据的时间
  198. if filtrateStartDate.After(latestDate) {
  199. startDate = filtrateStartDate.AddDate(0, 0, -1)
  200. }
  201. }
  202. //var dateArr []string
  203. // 对应日期的值
  204. existMap := make(map[string]float64)
  205. for _, v := range realPredictEdbInfoData {
  206. //dateArr = append(dateArr, v.DataTime)
  207. existMap[v.DataTime] = v.Value
  208. }
  209. predictEdbInfoData = make([]*models.EdbDataList, 0)
  210. //dataValue := lastDataValue
  211. //预测规则,1:最新,2:固定值,3:同比,4:同差,5:环比,6:环差,7:N期移动均值,8:N期段线性外推值
  212. for _, predictEdbConf := range predictEdbConfList {
  213. dataEndTime := endDate
  214. if predictEdbConf.EndDate.Before(dataEndTime) {
  215. dataEndTime = predictEdbConf.EndDate
  216. }
  217. var tmpMinValue, tmpMaxValue float64 // 当前预测结果中的最大/最小值
  218. switch predictEdbConf.RuleType {
  219. case 1: //1:最新
  220. var lastDataValue float64 //最新值
  221. tmpAllData := make([]*models.EdbDataList, 0)
  222. tmpAllData = append(tmpAllData, realPredictEdbInfoData...)
  223. tmpAllData = append(tmpAllData, predictEdbInfoData...)
  224. lenTmpAllData := len(tmpAllData)
  225. if lenTmpAllData > 0 {
  226. lastDataValue = tmpAllData[lenTmpAllData-1].Value
  227. }
  228. predictEdbInfoData = GetChartPredictEdbInfoDataListByRule1(predictEdbConf.PredictEdbInfoId, lastDataValue, startDate, dataEndTime, frequency, predictEdbInfoData, existMap)
  229. tmpMaxValue = lastDataValue
  230. tmpMinValue = lastDataValue
  231. case 2: //2:固定值
  232. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  233. if tmpErr != nil {
  234. err = tmpErr
  235. return
  236. }
  237. dataValue, _ := tmpValDecimal.Float64()
  238. predictEdbInfoData = GetChartPredictEdbInfoDataListByRule1(predictEdbConf.PredictEdbInfoId, dataValue, startDate, dataEndTime, frequency, predictEdbInfoData, existMap)
  239. tmpMaxValue = dataValue
  240. tmpMinValue = dataValue
  241. case 3: //3:同比
  242. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  243. if tmpErr != nil {
  244. err = tmpErr
  245. return
  246. }
  247. tbValue, _ := tmpValDecimal.Float64()
  248. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleTb(predictEdbConf.PredictEdbInfoId, tbValue, startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  249. case 4: //4:同差
  250. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  251. if tmpErr != nil {
  252. err = tmpErr
  253. return
  254. }
  255. tcValue, _ := tmpValDecimal.Float64()
  256. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleTc(predictEdbConf.PredictEdbInfoId, tcValue, startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  257. case 5: //5:环比
  258. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  259. if tmpErr != nil {
  260. err = tmpErr
  261. return
  262. }
  263. hbValue, _ := tmpValDecimal.Float64()
  264. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleHb(predictEdbConf.PredictEdbInfoId, hbValue, startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  265. case 6: //6:环差
  266. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  267. if tmpErr != nil {
  268. err = tmpErr
  269. return
  270. }
  271. hcValue, _ := tmpValDecimal.Float64()
  272. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleHc(predictEdbConf.PredictEdbInfoId, hcValue, startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  273. case 7: //7:N期移动均值
  274. nValue, tmpErr := strconv.Atoi(predictEdbConf.Value)
  275. if tmpErr != nil {
  276. err = tmpErr
  277. return
  278. }
  279. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleNMoveMeanValue(predictEdbConf.PredictEdbInfoId, nValue, startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  280. case 8: //8:N期段线性外推值
  281. nValue, tmpErr := strconv.Atoi(predictEdbConf.Value)
  282. if tmpErr != nil {
  283. err = tmpErr
  284. return
  285. }
  286. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleNLinearRegression(predictEdbConf.PredictEdbInfoId, nValue, startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  287. case 9: //9:动态环差”预测规则;
  288. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleTrendsHC(predictEdbConf.PredictEdbInfoId, predictEdbConf.ConfigId, startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  289. case 10: //10:根据 给定终值后插值 规则获取预测数据
  290. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  291. if tmpErr != nil {
  292. err = tmpErr
  293. return
  294. }
  295. finalValue, _ := tmpValDecimal.Float64()
  296. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleFinalValueHc(predictEdbConf.PredictEdbInfoId, finalValue, startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  297. case 11: //11:根据 季节性 规则获取预测数据
  298. var seasonConf SeasonConf
  299. tmpErr := json.Unmarshal([]byte(predictEdbConf.Value), &seasonConf)
  300. if tmpErr != nil {
  301. err = errors.New("季节性配置信息异常:" + tmpErr.Error())
  302. return
  303. }
  304. calendar := "公历"
  305. if seasonConf.Calendar == "农历" {
  306. calendar = "农历"
  307. }
  308. yearList := make([]int, 0)
  309. //选择方式,1:连续N年;2:指定年份
  310. if seasonConf.YearType == 1 {
  311. if seasonConf.NValue < 1 {
  312. err = errors.New("连续N年不允许小于1")
  313. return
  314. }
  315. currYear := time.Now().Year()
  316. for i := 0; i < seasonConf.NValue; i++ {
  317. yearList = append(yearList, currYear-i-1)
  318. }
  319. } else {
  320. yearList = seasonConf.YearList
  321. }
  322. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleSeason(predictEdbConf.PredictEdbInfoId, yearList, calendar, startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  323. if err != nil {
  324. return
  325. }
  326. case 12: //12:根据 移动平均同比 规则获取预测数据
  327. var moveAverageConf MoveAverageConf
  328. tmpErr := json.Unmarshal([]byte(predictEdbConf.Value), &moveAverageConf)
  329. if tmpErr != nil {
  330. err = errors.New("季节性配置信息异常:" + tmpErr.Error())
  331. return
  332. }
  333. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleMoveAverageTb(predictEdbConf.PredictEdbInfoId, moveAverageConf.NValue, moveAverageConf.Year, startDate, dataEndTime, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  334. if err != nil {
  335. return
  336. }
  337. }
  338. //startDate = dataEndTime.AddDate(0, 0, 1)
  339. if startDate.Before(dataEndTime) {
  340. startDate = dataEndTime
  341. }
  342. if tmpMinValue < minValue {
  343. minValue = tmpMinValue
  344. }
  345. if tmpMaxValue < maxValue {
  346. maxValue = tmpMaxValue
  347. }
  348. }
  349. return
  350. }