predict_edb_info.go 24 KB

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  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. }
  320. //startDate = dataEndTime.AddDate(0, 0, 1)
  321. if startDate.Before(dataEndTime) {
  322. startDate = dataEndTime
  323. }
  324. if tmpMinValue < minValue {
  325. minValue = tmpMinValue
  326. }
  327. if tmpMaxValue > maxValue {
  328. maxValue = tmpMaxValue
  329. }
  330. }
  331. return
  332. }
  333. // GetPredictEdbDayList 获取预测指标日期列表
  334. func getPredictEdbDayList(startDate, endDate time.Time, frequency string) (dayList []time.Time) {
  335. //if !utils.InArrayByStr([]string{"日度", "周度", "月度"}, frequency)
  336. switch frequency {
  337. case "日度":
  338. for currDate := startDate.AddDate(0, 0, 1); currDate.Before(endDate) || currDate.Equal(endDate); currDate = currDate.AddDate(0, 0, 1) {
  339. //周六、日排除
  340. if currDate.Weekday() == time.Sunday || currDate.Weekday() == time.Saturday {
  341. continue
  342. }
  343. dayList = append(dayList, currDate)
  344. }
  345. case "周度":
  346. //nextDate := startDate.AddDate(0, 0, 7)
  347. for currDate := startDate.AddDate(0, 0, 7); currDate.Before(endDate) || currDate.Equal(endDate); currDate = currDate.AddDate(0, 0, 7) {
  348. dayList = append(dayList, currDate)
  349. }
  350. case "月度":
  351. for currDate := startDate; currDate.Before(endDate) || currDate.Equal(endDate); {
  352. currDate = time.Date(currDate.Year(), currDate.Month(), 1, 0, 0, 0, 0, time.Now().Location()).AddDate(0, 1, -1)
  353. if !currDate.After(endDate) && !currDate.Equal(startDate) {
  354. dayList = append(dayList, currDate)
  355. }
  356. currDate = currDate.AddDate(0, 0, 1)
  357. }
  358. case "年度":
  359. for currDate := startDate; currDate.Before(endDate) || currDate.Equal(endDate); {
  360. currDate = time.Date(currDate.Year()+1, 12, 31, 0, 0, 0, 0, time.Now().Location())
  361. if !currDate.After(endDate) && !currDate.Equal(startDate) {
  362. dayList = append(dayList, currDate)
  363. }
  364. }
  365. }
  366. return
  367. }
  368. // GetPredictDataListByPredictEdbInfoId 根据预测指标id获取预测指标的数据
  369. 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) {
  370. edbInfo, err = data_manage.GetEdbInfoById(edbInfoId)
  371. if err != nil {
  372. errMsg = `获取预测指标信息失败`
  373. return
  374. }
  375. dataList, sourceEdbInfoItem, predictEdbConf, err, errMsg = GetPredictDataListByPredictEdbInfo(edbInfo, startDate, endDate, isTimeBetween)
  376. return
  377. }
  378. // GetPredictDataListByPredictEdbInfo 根据预测指标信息获取预测指标的数据
  379. 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) {
  380. // 非计算指标,直接从表里获取数据
  381. if edbInfo.EdbType != 1 {
  382. if !isTimeBetween { //如果不是区间数据,那么就结束日期为空
  383. endDate = ``
  384. }
  385. return GetPredictCalculateDataListByPredictEdbInfo(edbInfo, startDate, endDate)
  386. }
  387. // 查找该预测指标配置
  388. predictEdbConfList, err := data_manage.GetPredictEdbConfListById(edbInfo.EdbInfoId)
  389. if err != nil && err.Error() != utils.ErrNoRow() {
  390. errMsg = "获取预测指标配置信息失败"
  391. return
  392. }
  393. if len(predictEdbConfList) == 0 {
  394. errMsg = "获取预测指标配置信息失败"
  395. err = errors.New(errMsg)
  396. return
  397. }
  398. predictEdbConf = predictEdbConfList[0]
  399. // 来源指标
  400. sourceEdbInfoItem, err = data_manage.GetEdbInfoById(predictEdbConf.SourceEdbInfoId)
  401. if err != nil {
  402. if err.Error() == utils.ErrNoRow() {
  403. errMsg = "找不到来源指标信息"
  404. err = errors.New(errMsg)
  405. }
  406. return
  407. }
  408. allDataList := make([]*data_manage.EdbDataList, 0)
  409. //获取指标数据(实际已生成)
  410. dataList, err = data_manage.GetEdbDataList(sourceEdbInfoItem.Source, sourceEdbInfoItem.EdbInfoId, startDate, endDate)
  411. if err != nil {
  412. return
  413. }
  414. // 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
  415. if startDate != `` {
  416. allDataList, err = data_manage.GetEdbDataList(sourceEdbInfoItem.Source, sourceEdbInfoItem.EdbInfoId, "", "")
  417. if err != nil {
  418. return
  419. }
  420. } else {
  421. allDataList = dataList
  422. }
  423. // 获取预测指标未来的数据
  424. predictDataList := make([]*data_manage.EdbDataList, 0)
  425. endDateStr := edbInfo.EndDate //预测指标的结束日期
  426. if isTimeBetween { //如果是时间区间,那么
  427. reqEndDateTime, _ := time.ParseInLocation(utils.FormatDate, endDate, time.Local)
  428. endDateTime, _ := time.ParseInLocation(utils.FormatDate, edbInfo.EndDate, time.Local)
  429. // 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
  430. if reqEndDateTime.Before(endDateTime) {
  431. endDateStr = endDate
  432. }
  433. }
  434. //predictDataList, err = GetChartPredictEdbInfoDataList(*predictEdbConf, startDate, sourceEdbInfoItem.LatestDate, sourceEdbInfoItem.LatestValue, endDateStr, edbInfo.Frequency)
  435. predictEdbConfDataList := make([]data_manage.PredictEdbConfAndData, 0)
  436. for _, v := range predictEdbConfList {
  437. predictEdbConfDataList = append(predictEdbConfDataList, data_manage.PredictEdbConfAndData{
  438. ConfigId: v.ConfigId,
  439. PredictEdbInfoId: v.PredictEdbInfoId,
  440. SourceEdbInfoId: v.SourceEdbInfoId,
  441. RuleType: v.RuleType,
  442. FixedValue: v.FixedValue,
  443. Value: v.Value,
  444. EndDate: v.EndDate,
  445. ModifyTime: v.ModifyTime,
  446. CreateTime: v.CreateTime,
  447. DataList: make([]*data_manage.EdbDataList, 0),
  448. })
  449. }
  450. var predictMinValue, predictMaxValue float64
  451. predictDataList, predictMinValue, predictMaxValue, err, _ = GetChartPredictEdbInfoDataListByConfList(predictEdbConfDataList, startDate, sourceEdbInfoItem.LatestDate, endDateStr, edbInfo.Frequency, allDataList)
  452. if err != nil {
  453. return
  454. }
  455. dataList = append(dataList, predictDataList...)
  456. if len(predictDataList) > 0 {
  457. // 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
  458. if edbInfo.MinValue > predictMinValue {
  459. edbInfo.MinValue = predictMinValue
  460. }
  461. // 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
  462. if edbInfo.MaxValue < predictMaxValue {
  463. edbInfo.MaxValue = predictMaxValue
  464. }
  465. }
  466. return
  467. }
  468. // GetChartDataList 通过完整的预测数据 进行 季节性图、公历、农历处理
  469. func GetChartDataList(dataList []*data_manage.EdbDataList, chartType int, calendar, latestDateStr, startDate string) (resultDataList interface{}, err error) {
  470. startDateReal := startDate
  471. calendarPreYear := 0
  472. if calendar == "农历" {
  473. newStartDateReal, err := time.Parse(utils.FormatDate, startDateReal)
  474. if err != nil {
  475. fmt.Println("time.Parse:" + err.Error())
  476. }
  477. calendarPreYear = newStartDateReal.Year() - 1
  478. newStartDateReal = newStartDateReal.AddDate(-1, 0, 0)
  479. startDateReal = newStartDateReal.Format(utils.FormatDate)
  480. }
  481. // 曲线图
  482. if chartType == 1 {
  483. resultDataList = dataList
  484. return
  485. }
  486. //实际数据的截止日期
  487. latestDate, tmpErr := time.Parse(utils.FormatDate, latestDateStr)
  488. if tmpErr != nil {
  489. err = errors.New(fmt.Sprint("获取最后实际数据的日期失败,Err:" + tmpErr.Error() + ";LatestDate:" + latestDateStr))
  490. return
  491. }
  492. latestDateYear := latestDate.Year() //实际数据截止年份
  493. if calendar == "农历" {
  494. if len(dataList) <= 0 {
  495. resultDataList = data_manage.EdbDataResult{}
  496. } else {
  497. result, tmpErr := data_manage.AddCalculateQuarterV4(dataList)
  498. if tmpErr != nil {
  499. err = errors.New("获取农历数据失败,Err:" + tmpErr.Error())
  500. return
  501. }
  502. // 处理季节图的截止日期
  503. for k, edbDataItems := range result.List {
  504. var cuttingDataTimestamp int64
  505. // 切割的日期时间字符串
  506. cuttingDataTimeStr := latestDate.AddDate(0, 0, edbDataItems.BetweenDay).Format(utils.FormatDate)
  507. //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
  508. if edbDataItems.Year >= latestDateYear {
  509. for _, tmpData := range edbDataItems.Items {
  510. if tmpData.DataTime == cuttingDataTimeStr {
  511. cuttingDataTimestamp = tmpData.DataTimestamp
  512. break
  513. }
  514. }
  515. }
  516. edbDataItems.CuttingDataTimestamp = cuttingDataTimestamp
  517. result.List[k] = edbDataItems
  518. }
  519. if result.List[0].Year != calendarPreYear {
  520. itemList := make([]*data_manage.EdbDataList, 0)
  521. items := new(data_manage.EdbDataItems)
  522. //items.Year = calendarPreYear
  523. items.Items = itemList
  524. newResult := new(data_manage.EdbDataResult)
  525. newResult.List = append(newResult.List, items)
  526. newResult.List = append(newResult.List, result.List...)
  527. resultDataList = newResult
  528. } else {
  529. resultDataList = result
  530. }
  531. }
  532. } else {
  533. currentYear := time.Now().Year()
  534. quarterDataList := make([]*data_manage.QuarterData, 0)
  535. quarterMap := make(map[int][]*data_manage.EdbDataList)
  536. var quarterArr []int
  537. for _, v := range dataList {
  538. itemDate, tmpErr := time.Parse(utils.FormatDate, v.DataTime)
  539. if tmpErr != nil {
  540. err = errors.New("季度指标日期转换,Err:" + tmpErr.Error() + ";DataTime:" + v.DataTime)
  541. return
  542. }
  543. year := itemDate.Year()
  544. newItemDate := itemDate.AddDate(currentYear-year, 0, 0)
  545. timestamp := newItemDate.UnixNano() / 1e6
  546. v.DataTimestamp = timestamp
  547. if findVal, ok := quarterMap[year]; !ok {
  548. quarterArr = append(quarterArr, year)
  549. findVal = append(findVal, v)
  550. quarterMap[year] = findVal
  551. } else {
  552. findVal = append(findVal, v)
  553. quarterMap[year] = findVal
  554. }
  555. }
  556. for _, v := range quarterArr {
  557. itemList := quarterMap[v]
  558. quarterItem := new(data_manage.QuarterData)
  559. quarterItem.Year = v
  560. quarterItem.DataList = itemList
  561. //如果等于最后的实际日期,那么将切割时间戳记录
  562. if v == latestDateYear {
  563. var cuttingDataTimestamp int64
  564. for _, tmpData := range itemList {
  565. if tmpData.DataTime == latestDateStr {
  566. cuttingDataTimestamp = tmpData.DataTimestamp
  567. break
  568. }
  569. }
  570. quarterItem.CuttingDataTimestamp = cuttingDataTimestamp
  571. } else if v > latestDateYear {
  572. //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
  573. if len(itemList) > 0 {
  574. quarterItem.CuttingDataTimestamp = itemList[0].DataTimestamp - 100
  575. }
  576. }
  577. quarterDataList = append(quarterDataList, quarterItem)
  578. }
  579. resultDataList = quarterDataList
  580. }
  581. return
  582. }
  583. // GetPredictCalculateDataListByPredictEdbInfo 根据预测运算指标信息获取预测指标的数据
  584. 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) {
  585. dataList, err = data_manage.GetEdbDataList(edbInfo.Source, edbInfo.EdbInfoId, startDate, endDate)
  586. return
  587. }