predict_edb_info.go 26 KB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343344345346347348349350351352353354355356357358359360361362363364365366367368369370371372373374375376377378379380381382383384385386387388389390391392393394395396397398399400401402403404405406407408409410411412413414415416417418419420421422423424425426427428429430431432433434435436437438439440441442443444445446447448449450451452453454455456457458459460461462463464465466467468469470471472473474475476477478479480481482483484485486487488489490491492493494495496497498499500501502503504505506507508509510511512513514515516517518519520521522523524525526527528529530531532533534535536537538539540541542543544545546547548549550551552553554555556557558559560561562563564565566567568569570571572573574575576577578579580581582583584585586587588589590591592593594595596597598599600601602603604605606607608609610611612613614615616617618619620621622623624625626627628629630631632633634635636637638639640641642643644645646647648649650651652653654655656657658659660661662663664665666667668669670671672673674675676677678679680681682683684685686687688689690691
  1. package data
  2. import (
  3. "encoding/json"
  4. "errors"
  5. "fmt"
  6. "github.com/shopspring/decimal"
  7. "hongze/hongze_ETA_mobile_api/models/data_manage"
  8. "hongze/hongze_ETA_mobile_api/utils"
  9. "strconv"
  10. "time"
  11. )
  12. // GetPredictEdbInfoDataList 获取预测指标的未来数据
  13. func GetPredictEdbInfoDataList(predictEdbConf data_manage.PredictEdbConf, latestDateStr string, lastDataValue float64, endDateStr, frequency string) (predictEdbInfoData []*data_manage.EdbData, 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. dataValue := lastDataValue
  23. if predictEdbConf.RuleType == 2 {
  24. dataValue = predictEdbConf.FixedValue
  25. }
  26. //获取后面的预测数据
  27. dayList := getPredictEdbDayList(latestDate, endDate, frequency)
  28. predictEdbInfoData = make([]*data_manage.EdbData, 0)
  29. lenDayList := len(dayList)
  30. if lenDayList > 0 {
  31. for i := lenDayList - 1; i >= 0; i-- {
  32. v := dayList[i]
  33. predictEdbInfoData = append(predictEdbInfoData, &data_manage.EdbData{
  34. EdbDataId: predictEdbConf.PredictEdbInfoId + 100000 + i,
  35. EdbInfoId: predictEdbConf.PredictEdbInfoId,
  36. DataTime: v.Format(utils.FormatDate),
  37. Value: dataValue,
  38. })
  39. }
  40. }
  41. return
  42. }
  43. // GetChartPredictEdbInfoDataList 获取图表的预测指标的未来数据
  44. func GetChartPredictEdbInfoDataList(predictEdbConf data_manage.PredictEdbConf, filtrateStartDateStr, latestDateStr string, lastDataValue float64, endDateStr, frequency string) (predictEdbInfoData []*data_manage.EdbDataList, err error) {
  45. endDate, err := time.ParseInLocation(utils.FormatDate, endDateStr, time.Local)
  46. if err != nil {
  47. return
  48. }
  49. latestDate, err := time.ParseInLocation(utils.FormatDate, latestDateStr, time.Local)
  50. if err != nil {
  51. return
  52. }
  53. // 开始预测数据的时间
  54. startDate := latestDate
  55. // 如果有筛选时间的话
  56. if filtrateStartDateStr != `` {
  57. filtrateStartDate, tmpErr := time.ParseInLocation(utils.FormatDate, filtrateStartDateStr, time.Local)
  58. if tmpErr != nil {
  59. err = tmpErr
  60. return
  61. }
  62. //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
  63. if filtrateStartDate.After(latestDate) {
  64. startDate = filtrateStartDate.AddDate(0, 0, -1)
  65. }
  66. }
  67. dataValue := lastDataValue
  68. if predictEdbConf.RuleType == 2 {
  69. dataValue = predictEdbConf.FixedValue
  70. }
  71. //获取后面的预测数据
  72. dayList := getPredictEdbDayList(startDate, endDate, frequency)
  73. predictEdbInfoData = make([]*data_manage.EdbDataList, 0)
  74. for k, v := range dayList {
  75. predictEdbInfoData = append(predictEdbInfoData, &data_manage.EdbDataList{
  76. EdbDataId: predictEdbConf.PredictEdbInfoId + 100000 + k,
  77. EdbInfoId: predictEdbConf.PredictEdbInfoId,
  78. DataTime: v.Format(utils.FormatDate),
  79. Value: dataValue,
  80. 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
  81. })
  82. }
  83. return
  84. }
  85. // GetChartPredictEdbInfoDataListByConfList 获取图表的预测指标的未来数据
  86. func GetChartPredictEdbInfoDataListByConfList(predictEdbConfList []data_manage.PredictEdbConfAndData, filtrateStartDateStr, latestDateStr, endDateStr, frequency string, realPredictEdbInfoData []*data_manage.EdbDataList) (predictEdbInfoData []*data_manage.EdbDataList, minValue, maxValue float64, err error, errMsg string) {
  87. endDate, err := time.ParseInLocation(utils.FormatDate, endDateStr, time.Local)
  88. if err != nil {
  89. return
  90. }
  91. latestDate, err := time.ParseInLocation(utils.FormatDate, latestDateStr, time.Local)
  92. if err != nil {
  93. return
  94. }
  95. // 开始预测数据的时间
  96. startDate := latestDate
  97. // 如果有筛选时间的话
  98. if filtrateStartDateStr != `` {
  99. filtrateStartDate, tmpErr := time.ParseInLocation(utils.FormatDate, filtrateStartDateStr, time.Local)
  100. if tmpErr != nil {
  101. err = tmpErr
  102. return
  103. }
  104. //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
  105. if filtrateStartDate.After(latestDate) {
  106. startDate = filtrateStartDate.AddDate(0, 0, -1)
  107. }
  108. }
  109. //var dateArr []string
  110. // 对应日期的值
  111. existMap := make(map[string]float64)
  112. for _, v := range realPredictEdbInfoData {
  113. //dateArr = append(dateArr, v.DataTime)
  114. existMap[v.DataTime] = v.Value
  115. }
  116. predictEdbInfoData = make([]*data_manage.EdbDataList, 0)
  117. //dataValue := lastDataValue
  118. //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
  119. for _, predictEdbConf := range predictEdbConfList {
  120. dataEndTime := endDate
  121. if predictEdbConf.EndDate.Before(dataEndTime) {
  122. dataEndTime = predictEdbConf.EndDate
  123. }
  124. var tmpMinValue, tmpMaxValue float64 // 当前预测结果中的最大/最小值
  125. dayList := getPredictEdbDayList(startDate, dataEndTime, frequency)
  126. if len(dayList) <= 0 { // 如果未来没有日期的话,那么就退出当前循环,进入下一个循环
  127. continue
  128. }
  129. switch predictEdbConf.RuleType {
  130. case 1: //1:最新
  131. var lastDataValue float64 //最新值
  132. tmpAllData := make([]*data_manage.EdbDataList, 0)
  133. tmpAllData = append(tmpAllData, realPredictEdbInfoData...)
  134. tmpAllData = append(tmpAllData, predictEdbInfoData...)
  135. lenTmpAllData := len(tmpAllData)
  136. if lenTmpAllData > 0 {
  137. lastDataValue = tmpAllData[lenTmpAllData-1].Value
  138. }
  139. predictEdbInfoData = GetChartPredictEdbInfoDataListByRule1(predictEdbConf.PredictEdbInfoId, lastDataValue, dayList, predictEdbInfoData, existMap)
  140. tmpMaxValue = lastDataValue
  141. tmpMinValue = lastDataValue
  142. case 2: //2:固定值
  143. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  144. if tmpErr != nil {
  145. err = tmpErr
  146. return
  147. }
  148. dataValue, _ := tmpValDecimal.Float64()
  149. predictEdbInfoData = GetChartPredictEdbInfoDataListByRule1(predictEdbConf.PredictEdbInfoId, dataValue, dayList, predictEdbInfoData, existMap)
  150. tmpMaxValue = dataValue
  151. tmpMinValue = dataValue
  152. case 3: //3:同比
  153. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  154. if tmpErr != nil {
  155. err = tmpErr
  156. return
  157. }
  158. tbValue, _ := tmpValDecimal.Float64()
  159. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleTb(predictEdbConf.PredictEdbInfoId, tbValue, dayList, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  160. case 4: //4:同差
  161. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  162. if tmpErr != nil {
  163. err = tmpErr
  164. return
  165. }
  166. tcValue, _ := tmpValDecimal.Float64()
  167. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleTc(predictEdbConf.PredictEdbInfoId, tcValue, dayList, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  168. case 5: //5:环比
  169. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  170. if tmpErr != nil {
  171. err = tmpErr
  172. return
  173. }
  174. hbValue, _ := tmpValDecimal.Float64()
  175. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleHb(predictEdbConf.PredictEdbInfoId, hbValue, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  176. case 6: //6:环差
  177. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  178. if tmpErr != nil {
  179. err = tmpErr
  180. return
  181. }
  182. hcValue, _ := tmpValDecimal.Float64()
  183. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleHc(predictEdbConf.PredictEdbInfoId, hcValue, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  184. case 7: //7:N期移动均值
  185. nValue, tmpErr := strconv.Atoi(predictEdbConf.Value)
  186. if tmpErr != nil {
  187. err = tmpErr
  188. return
  189. }
  190. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleNMoveMeanValue(predictEdbConf.PredictEdbInfoId, nValue, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  191. case 8: //8:N期段线性外推值
  192. nValue, tmpErr := strconv.Atoi(predictEdbConf.Value)
  193. if tmpErr != nil {
  194. err = tmpErr
  195. return
  196. }
  197. if nValue <= 1 {
  198. errMsg = `N期段线性外推值的N值必须大于1`
  199. err = errors.New(errMsg)
  200. return
  201. }
  202. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleNLinearRegression(predictEdbConf.PredictEdbInfoId, nValue, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  203. if err != nil {
  204. return
  205. }
  206. case 9: //9:动态环差”预测规则;
  207. //规则计算的环差值map
  208. hcDataMap := make(map[string]float64)
  209. if predictEdbConf.PredictEdbInfoId > 0 { //已经生成的动态数据
  210. tmpPredictEdbRuleDataList, tmpErr := data_manage.GetPredictEdbRuleDataList(predictEdbConf.PredictEdbInfoId, predictEdbConf.ConfigId, startDate.Format(utils.FormatDate), endDate.Format(utils.FormatDate))
  211. if tmpErr != nil {
  212. err = tmpErr
  213. return
  214. }
  215. for _, v := range tmpPredictEdbRuleDataList {
  216. hcDataMap[v.DataTime] = v.Value
  217. }
  218. } else { //未生成的动态数据,需要使用外部传入的数据进行计算
  219. if len(predictEdbConf.DataList) <= 0 {
  220. return
  221. }
  222. for _, v := range predictEdbConf.DataList {
  223. currentDate, tmpErr := time.ParseInLocation(utils.FormatDate, v.DataTime, time.Local)
  224. if tmpErr != nil {
  225. continue
  226. }
  227. // 只处理时间段内的数据
  228. if currentDate.Before(startDate) || currentDate.After(endDate) {
  229. continue
  230. }
  231. hcDataMap[v.DataTime] = v.Value
  232. }
  233. }
  234. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleTrendsHC(predictEdbConf.PredictEdbInfoId, dayList, realPredictEdbInfoData, predictEdbInfoData, hcDataMap, existMap)
  235. case 10: //10:根据 给定终值后插值 规则获取预测数据
  236. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  237. if tmpErr != nil {
  238. err = tmpErr
  239. return
  240. }
  241. finalValue, _ := tmpValDecimal.Float64()
  242. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleFinalValueHc(predictEdbConf.PredictEdbInfoId, finalValue, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  243. case 11: //11:根据 季节性 规则获取预测数据
  244. var seasonConf SeasonConf
  245. tmpErr := json.Unmarshal([]byte(predictEdbConf.Value), &seasonConf)
  246. if tmpErr != nil {
  247. err = errors.New("季节性配置信息异常:" + tmpErr.Error())
  248. return
  249. }
  250. calendar := "公历"
  251. if seasonConf.Calendar == "农历" {
  252. calendar = "农历"
  253. }
  254. yearList := make([]int, 0)
  255. //选择方式,1:连续N年;2:指定年份
  256. if seasonConf.YearType == 1 {
  257. if seasonConf.NValue < 1 {
  258. err = errors.New("连续N年不允许小于1")
  259. return
  260. }
  261. currYear := time.Now().Year()
  262. for i := 0; i < seasonConf.NValue; i++ {
  263. yearList = append(yearList, currYear-i-1)
  264. }
  265. } else {
  266. yearList = seasonConf.YearList
  267. }
  268. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleSeason(predictEdbConf.PredictEdbInfoId, yearList, calendar, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  269. if err != nil {
  270. return
  271. }
  272. case 12: //12:根据 移动平均同比 规则获取预测数据
  273. var moveAverageConf MoveAverageConf
  274. tmpErr := json.Unmarshal([]byte(predictEdbConf.Value), &moveAverageConf)
  275. if tmpErr != nil {
  276. err = errors.New("季节性配置信息异常:" + tmpErr.Error())
  277. return
  278. }
  279. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleMoveAverageTb(predictEdbConf.PredictEdbInfoId, moveAverageConf.NValue, moveAverageConf.Year, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  280. if err != nil {
  281. return
  282. }
  283. case 13: //13:根据 同比增速差值 规则获取预测数据
  284. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  285. if tmpErr != nil {
  286. err = tmpErr
  287. return
  288. }
  289. tbEndValue, _ := tmpValDecimal.Float64()
  290. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleTbzscz(predictEdbConf.PredictEdbInfoId, tbEndValue, dayList, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  291. case 14: //14:根据 一元线性拟合 规则获取预测数据
  292. var ruleConf RuleLineNhConf
  293. err = json.Unmarshal([]byte(predictEdbConf.Value), &ruleConf)
  294. if err != nil {
  295. err = errors.New("一元线性拟合配置信息异常:" + err.Error())
  296. return
  297. }
  298. // 规则计算的拟合残差值map
  299. newNhccDataMap := make(map[string]float64)
  300. if predictEdbConf.PredictEdbInfoId > 0 { //已经生成的动态数据
  301. tmpPredictEdbRuleDataList, tmpErr := data_manage.GetPredictEdbRuleDataList(predictEdbConf.PredictEdbInfoId, predictEdbConf.ConfigId, "", "")
  302. if tmpErr != nil {
  303. err = tmpErr
  304. return
  305. }
  306. for _, v := range tmpPredictEdbRuleDataList {
  307. newNhccDataMap[v.DataTime] = v.Value
  308. }
  309. } else { //未生成的动态数据,需要使用外部传入的数据进行计算
  310. newNhccDataMap, err = getCalculateNhccData(append(realPredictEdbInfoData, predictEdbInfoData...), ruleConf)
  311. if err != nil {
  312. return
  313. }
  314. }
  315. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleLineNh(predictEdbConf.PredictEdbInfoId, dayList, realPredictEdbInfoData, predictEdbInfoData, newNhccDataMap, existMap)
  316. if err != nil {
  317. return
  318. }
  319. case 15: //15:N年均值:过去N年同期均值。过去N年可以连续或者不连续,指标数据均用线性插值补全为日度数据后计算;
  320. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleNAnnualAverage(predictEdbConf.PredictEdbInfoId, predictEdbConf.Value, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  321. if err != nil {
  322. return
  323. }
  324. case 16: //16:年度值倒推
  325. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleAnnualValueInversion(predictEdbConf.PredictEdbInfoId, predictEdbConf.Value, dayList, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  326. if err != nil {
  327. return
  328. }
  329. }
  330. // 下一个规则的开始日期
  331. {
  332. lenPredictEdbInfoData := len(predictEdbInfoData)
  333. if lenPredictEdbInfoData > 0 {
  334. tmpDataEndTime, _ := time.ParseInLocation(utils.FormatDate, predictEdbInfoData[lenPredictEdbInfoData-1].DataTime, time.Local)
  335. if startDate.Before(tmpDataEndTime) {
  336. startDate = tmpDataEndTime
  337. }
  338. }
  339. }
  340. //startDate = dataEndTime.AddDate(0, 0, 1)
  341. if startDate.Before(dataEndTime) {
  342. startDate = dataEndTime
  343. }
  344. if tmpMinValue < minValue {
  345. minValue = tmpMinValue
  346. }
  347. if tmpMaxValue > maxValue {
  348. maxValue = tmpMaxValue
  349. }
  350. }
  351. return
  352. }
  353. // GetPredictEdbDayList 获取预测指标日期列表
  354. func getPredictEdbDayList(startDate, endDate time.Time, frequency string) (dayList []time.Time) {
  355. //if !utils.InArrayByStr([]string{"日度", "周度", "月度"}, frequency)
  356. switch frequency {
  357. case "日度":
  358. for currDate := startDate.AddDate(0, 0, 1); currDate.Before(endDate) || currDate.Equal(endDate); currDate = currDate.AddDate(0, 0, 1) {
  359. //周六、日排除
  360. if currDate.Weekday() == time.Sunday || currDate.Weekday() == time.Saturday {
  361. continue
  362. }
  363. dayList = append(dayList, currDate)
  364. }
  365. case "周度":
  366. //nextDate := startDate.AddDate(0, 0, 7)
  367. for currDate := startDate.AddDate(0, 0, 7); currDate.Before(endDate) || currDate.Equal(endDate); currDate = currDate.AddDate(0, 0, 7) {
  368. dayList = append(dayList, currDate)
  369. }
  370. case "旬度":
  371. for currDate := startDate.AddDate(0, 0, 1); currDate.Before(endDate) || currDate.Equal(endDate); {
  372. nextDate := currDate.AddDate(0, 0, 1)
  373. //每个月的10号、20号、最后一天,那么就写入
  374. if nextDate.Day() == 11 || nextDate.Day() == 21 || nextDate.Day() == 1 {
  375. dayList = append(dayList, currDate)
  376. }
  377. currDate = nextDate
  378. }
  379. case "月度":
  380. for currDate := startDate; currDate.Before(endDate) || currDate.Equal(endDate); {
  381. currDate = time.Date(currDate.Year(), currDate.Month(), 1, 0, 0, 0, 0, time.Now().Location()).AddDate(0, 1, -1)
  382. if !currDate.After(endDate) && !currDate.Equal(startDate) {
  383. dayList = append(dayList, currDate)
  384. }
  385. currDate = currDate.AddDate(0, 0, 1)
  386. }
  387. case "季度":
  388. for currDate := startDate; currDate.Before(endDate) || currDate.Equal(endDate); {
  389. // 每月的最后一天
  390. currDate = time.Date(currDate.Year(), currDate.Month(), 1, 0, 0, 0, 0, time.Now().Location()).AddDate(0, 1, -1)
  391. if !currDate.After(endDate) && !currDate.Equal(startDate) {
  392. // 季度日期就写入,否则不写入
  393. if currDate.Month() == 3 || currDate.Month() == 6 || currDate.Month() == 9 || currDate.Month() == 12 {
  394. dayList = append(dayList, currDate)
  395. }
  396. }
  397. currDate = currDate.AddDate(0, 0, 1)
  398. }
  399. case "半年度":
  400. for currDate := startDate; currDate.Before(endDate) || currDate.Equal(endDate); {
  401. // 每月的最后一天
  402. currDate = time.Date(currDate.Year(), currDate.Month(), 1, 0, 0, 0, 0, time.Now().Location()).AddDate(0, 1, -1)
  403. if !currDate.After(endDate) && !currDate.Equal(startDate) {
  404. // 半年度日期就写入,否则不写入
  405. if currDate.Month() == 6 || currDate.Month() == 12 {
  406. dayList = append(dayList, currDate)
  407. }
  408. }
  409. currDate = currDate.AddDate(0, 0, 1)
  410. }
  411. case "年度":
  412. for currDate := startDate; currDate.Before(endDate) || currDate.Equal(endDate); {
  413. currDate = time.Date(currDate.Year()+1, 12, 31, 0, 0, 0, 0, time.Now().Location())
  414. if !currDate.After(endDate) && !currDate.Equal(startDate) {
  415. dayList = append(dayList, currDate)
  416. }
  417. }
  418. }
  419. return
  420. }
  421. // GetPredictDataListByPredictEdbInfoId 根据预测指标id获取预测指标的数据
  422. func GetPredictDataListByPredictEdbInfoId(edbInfoId int, startDate, endDate string, isTimeBetween bool) (edbInfo *data_manage.EdbInfo, dataList []*data_manage.EdbDataList, sourceEdbInfoItem *data_manage.EdbInfo, predictEdbConf *data_manage.PredictEdbConf, err error, errMsg string) {
  423. edbInfo, err = data_manage.GetEdbInfoById(edbInfoId)
  424. if err != nil {
  425. errMsg = `获取预测指标信息失败`
  426. return
  427. }
  428. dataList, sourceEdbInfoItem, predictEdbConf, err, errMsg = GetPredictDataListByPredictEdbInfo(edbInfo, startDate, endDate, isTimeBetween)
  429. return
  430. }
  431. // GetPredictDataListByPredictEdbInfo 根据预测指标信息获取预测指标的数据
  432. func GetPredictDataListByPredictEdbInfo(edbInfo *data_manage.EdbInfo, startDate, endDate string, isTimeBetween bool) (dataList []*data_manage.EdbDataList, sourceEdbInfoItem *data_manage.EdbInfo, predictEdbConf *data_manage.PredictEdbConf, err error, errMsg string) {
  433. // 非计算指标,直接从表里获取数据
  434. if edbInfo.EdbType != 1 {
  435. if !isTimeBetween { //如果不是区间数据,那么就结束日期为空
  436. endDate = ``
  437. }
  438. return GetPredictCalculateDataListByPredictEdbInfo(edbInfo, startDate, endDate)
  439. }
  440. // 查找该预测指标配置
  441. predictEdbConfList, err := data_manage.GetPredictEdbConfListById(edbInfo.EdbInfoId)
  442. if err != nil && err.Error() != utils.ErrNoRow() {
  443. errMsg = "获取预测指标配置信息失败"
  444. return
  445. }
  446. if len(predictEdbConfList) == 0 {
  447. errMsg = "获取预测指标配置信息失败"
  448. err = errors.New(errMsg)
  449. return
  450. }
  451. predictEdbConf = predictEdbConfList[0]
  452. // 来源指标
  453. sourceEdbInfoItem, err = data_manage.GetEdbInfoById(predictEdbConf.SourceEdbInfoId)
  454. if err != nil {
  455. if err.Error() == utils.ErrNoRow() {
  456. errMsg = "找不到来源指标信息"
  457. err = errors.New(errMsg)
  458. }
  459. return
  460. }
  461. allDataList := make([]*data_manage.EdbDataList, 0)
  462. //获取指标数据(实际已生成)
  463. dataList, err = data_manage.GetEdbDataList(sourceEdbInfoItem.Source, sourceEdbInfoItem.EdbInfoId, startDate, endDate)
  464. if err != nil {
  465. return
  466. }
  467. // 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
  468. if startDate != `` {
  469. allDataList, err = data_manage.GetEdbDataList(sourceEdbInfoItem.Source, sourceEdbInfoItem.EdbInfoId, "", "")
  470. if err != nil {
  471. return
  472. }
  473. } else {
  474. allDataList = dataList
  475. }
  476. // 获取预测指标未来的数据
  477. predictDataList := make([]*data_manage.EdbDataList, 0)
  478. endDateStr := edbInfo.EndDate //预测指标的结束日期
  479. if isTimeBetween { //如果是时间区间,那么
  480. reqEndDateTime, _ := time.ParseInLocation(utils.FormatDate, endDate, time.Local)
  481. endDateTime, _ := time.ParseInLocation(utils.FormatDate, edbInfo.EndDate, time.Local)
  482. // 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
  483. if reqEndDateTime.Before(endDateTime) {
  484. endDateStr = endDate
  485. }
  486. }
  487. //predictDataList, err = GetChartPredictEdbInfoDataList(*predictEdbConf, startDate, sourceEdbInfoItem.LatestDate, sourceEdbInfoItem.LatestValue, endDateStr, edbInfo.Frequency)
  488. predictEdbConfDataList := make([]data_manage.PredictEdbConfAndData, 0)
  489. for _, v := range predictEdbConfList {
  490. predictEdbConfDataList = append(predictEdbConfDataList, data_manage.PredictEdbConfAndData{
  491. ConfigId: v.ConfigId,
  492. PredictEdbInfoId: v.PredictEdbInfoId,
  493. SourceEdbInfoId: v.SourceEdbInfoId,
  494. RuleType: v.RuleType,
  495. FixedValue: v.FixedValue,
  496. Value: v.Value,
  497. EndDate: v.EndDate,
  498. ModifyTime: v.ModifyTime,
  499. CreateTime: v.CreateTime,
  500. DataList: make([]*data_manage.EdbDataList, 0),
  501. })
  502. }
  503. var predictMinValue, predictMaxValue float64
  504. predictDataList, predictMinValue, predictMaxValue, err, _ = GetChartPredictEdbInfoDataListByConfList(predictEdbConfDataList, startDate, sourceEdbInfoItem.LatestDate, endDateStr, edbInfo.Frequency, allDataList)
  505. if err != nil {
  506. return
  507. }
  508. dataList = append(dataList, predictDataList...)
  509. if len(predictDataList) > 0 {
  510. // 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
  511. if edbInfo.MinValue > predictMinValue {
  512. edbInfo.MinValue = predictMinValue
  513. }
  514. // 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
  515. if edbInfo.MaxValue < predictMaxValue {
  516. edbInfo.MaxValue = predictMaxValue
  517. }
  518. }
  519. return
  520. }
  521. // GetChartDataList 通过完整的预测数据 进行 季节性图、公历、农历处理
  522. func GetChartDataList(dataList []*data_manage.EdbDataList, chartType int, calendar, latestDateStr, startDate string) (resultDataList interface{}, err error) {
  523. startDateReal := startDate
  524. calendarPreYear := 0
  525. if calendar == "农历" {
  526. newStartDateReal, err := time.Parse(utils.FormatDate, startDateReal)
  527. if err != nil {
  528. fmt.Println("time.Parse:" + err.Error())
  529. }
  530. calendarPreYear = newStartDateReal.Year() - 1
  531. newStartDateReal = newStartDateReal.AddDate(-1, 0, 0)
  532. startDateReal = newStartDateReal.Format(utils.FormatDate)
  533. }
  534. // 曲线图
  535. if chartType == 1 {
  536. resultDataList = dataList
  537. return
  538. }
  539. //实际数据的截止日期
  540. latestDate, tmpErr := time.Parse(utils.FormatDate, latestDateStr)
  541. if tmpErr != nil {
  542. err = errors.New(fmt.Sprint("获取最后实际数据的日期失败,Err:" + tmpErr.Error() + ";LatestDate:" + latestDateStr))
  543. return
  544. }
  545. latestDateYear := latestDate.Year() //实际数据截止年份
  546. if calendar == "农历" {
  547. if len(dataList) <= 0 {
  548. resultDataList = data_manage.EdbDataResult{}
  549. } else {
  550. result, tmpErr := data_manage.AddCalculateQuarterV4(dataList)
  551. if tmpErr != nil {
  552. err = errors.New("获取农历数据失败,Err:" + tmpErr.Error())
  553. return
  554. }
  555. // 处理季节图的截止日期
  556. for k, edbDataItems := range result.List {
  557. var cuttingDataTimestamp int64
  558. // 切割的日期时间字符串
  559. cuttingDataTimeStr := latestDate.AddDate(0, 0, edbDataItems.BetweenDay).Format(utils.FormatDate)
  560. //如果等于最后的实际日期,那么遍历找到该日期对应的时间戳,并将其赋值为 切割时间戳
  561. if edbDataItems.Year >= latestDateYear {
  562. for _, tmpData := range edbDataItems.Items {
  563. if tmpData.DataTime == cuttingDataTimeStr {
  564. cuttingDataTimestamp = tmpData.DataTimestamp
  565. break
  566. }
  567. }
  568. }
  569. edbDataItems.CuttingDataTimestamp = cuttingDataTimestamp
  570. result.List[k] = edbDataItems
  571. }
  572. if result.List[0].Year != calendarPreYear {
  573. itemList := make([]*data_manage.EdbDataList, 0)
  574. items := new(data_manage.EdbDataItems)
  575. //items.Year = calendarPreYear
  576. items.Items = itemList
  577. newResult := new(data_manage.EdbDataResult)
  578. newResult.List = append(newResult.List, items)
  579. newResult.List = append(newResult.List, result.List...)
  580. resultDataList = newResult
  581. } else {
  582. resultDataList = result
  583. }
  584. }
  585. } else {
  586. currentYear := time.Now().Year()
  587. quarterDataList := make([]*data_manage.QuarterData, 0)
  588. quarterMap := make(map[int][]*data_manage.EdbDataList)
  589. var quarterArr []int
  590. for _, v := range dataList {
  591. itemDate, tmpErr := time.Parse(utils.FormatDate, v.DataTime)
  592. if tmpErr != nil {
  593. err = errors.New("季度指标日期转换,Err:" + tmpErr.Error() + ";DataTime:" + v.DataTime)
  594. return
  595. }
  596. year := itemDate.Year()
  597. newItemDate := itemDate.AddDate(currentYear-year, 0, 0)
  598. timestamp := newItemDate.UnixNano() / 1e6
  599. v.DataTimestamp = timestamp
  600. if findVal, ok := quarterMap[year]; !ok {
  601. quarterArr = append(quarterArr, year)
  602. findVal = append(findVal, v)
  603. quarterMap[year] = findVal
  604. } else {
  605. findVal = append(findVal, v)
  606. quarterMap[year] = findVal
  607. }
  608. }
  609. for _, v := range quarterArr {
  610. itemList := quarterMap[v]
  611. quarterItem := new(data_manage.QuarterData)
  612. quarterItem.Year = v
  613. quarterItem.DataList = itemList
  614. //如果等于最后的实际日期,那么将切割时间戳记录
  615. if v == latestDateYear {
  616. var cuttingDataTimestamp int64
  617. for _, tmpData := range itemList {
  618. if tmpData.DataTime == latestDateStr {
  619. cuttingDataTimestamp = tmpData.DataTimestamp
  620. break
  621. }
  622. }
  623. quarterItem.CuttingDataTimestamp = cuttingDataTimestamp
  624. } else if v > latestDateYear {
  625. //如果大于最后的实际日期,那么第一个点就是切割的时间戳
  626. if len(itemList) > 0 {
  627. quarterItem.CuttingDataTimestamp = itemList[0].DataTimestamp - 100
  628. }
  629. }
  630. quarterDataList = append(quarterDataList, quarterItem)
  631. }
  632. resultDataList = quarterDataList
  633. }
  634. return
  635. }
  636. // GetPredictCalculateDataListByPredictEdbInfo 根据预测运算指标信息获取预测指标的数据
  637. func GetPredictCalculateDataListByPredictEdbInfo(edbInfo *data_manage.EdbInfo, startDate, endDate string) (dataList []*data_manage.EdbDataList, sourceEdbInfoItem *data_manage.EdbInfo, predictEdbConf *data_manage.PredictEdbConf, err error, errMsg string) {
  638. dataList, err = data_manage.GetEdbDataList(edbInfo.Source, edbInfo.EdbInfoId, startDate, endDate)
  639. return
  640. }