predict_edb_info.go 41 KB

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  1. package data
  2. import (
  3. "encoding/json"
  4. "errors"
  5. "eta/eta_api/models/data_manage"
  6. "eta/eta_api/models/data_manage/request"
  7. "eta/eta_api/models/system"
  8. "eta/eta_api/services/data/data_manage_permission"
  9. "eta/eta_api/utils"
  10. "fmt"
  11. "github.com/shopspring/decimal"
  12. "strconv"
  13. "strings"
  14. "time"
  15. )
  16. // AddPredictEdbInfo 新增预测指标
  17. func AddPredictEdbInfo(sourceEdbInfoId, classifyId int, edbName string, ruleList []request.RuleConfig, sysUserId int, sysUserName, requestBody, requestUrl string) (edbInfo *data_manage.EdbInfo, err error, errMsg string) {
  18. var sourceEdbInfo *data_manage.EdbInfo
  19. // 来源指标信息校验
  20. {
  21. sourceEdbInfo, err = data_manage.GetEdbInfoById(sourceEdbInfoId)
  22. if err != nil && !utils.IsErrNoRow(err) {
  23. errMsg = "新增失败"
  24. err = errors.New("获取来源指标失败,Err:" + err.Error())
  25. return
  26. }
  27. if sourceEdbInfo == nil {
  28. errMsg = "找不到该来源指标"
  29. err = nil
  30. return
  31. }
  32. //必须是普通的指标
  33. if sourceEdbInfo.EdbInfoType != 0 {
  34. errMsg = "来源指标异常,不是普通的指标"
  35. return
  36. }
  37. if !utils.InArrayByStr([]string{"日度", "周度", "月度"}, sourceEdbInfo.Frequency) {
  38. errMsg = "预测指标只支持选择日度、周度、月度的指标"
  39. return
  40. }
  41. }
  42. var classifyInfo *data_manage.EdbClassify
  43. // 来源分类信息校验
  44. {
  45. classifyInfo, err = data_manage.GetEdbClassifyById(classifyId)
  46. if err != nil && !utils.IsErrNoRow(err) {
  47. errMsg = "新增失败"
  48. err = errors.New("获取预测指标分类失败,Err:" + err.Error())
  49. return
  50. }
  51. if classifyInfo == nil {
  52. errMsg = "找不到该预测指标分类"
  53. err = nil
  54. return
  55. }
  56. //必须是预测指标分类
  57. if classifyInfo.ClassifyType != 1 {
  58. errMsg = "预测指标分类异常,不是预测指标分类"
  59. return
  60. }
  61. }
  62. edbName = strings.Trim(edbName, " ")
  63. edbCode := sourceEdbInfo.EdbCode + "_" + time.Now().Format(utils.FormatShortDateTimeUnSpace)
  64. // 判断该来源指标是否已经被引用了
  65. {
  66. //predictEdbConf, tmpErr := data_manage.GetPredictEdbConfBySourceEdbInfoId(sourceEdbInfoId)
  67. //if tmpErr != nil && tmpErr.Error() != utils.ErrNoRow() {
  68. // errMsg = "新增失败"
  69. // err = tmpErr
  70. // return
  71. //}
  72. // 如果该来源指标已经被引用了,那么不允许再次使用
  73. //if predictEdbConf != nil {
  74. // //获取预测指标详情
  75. // predictEdbInfo, tmpErr := data_manage.GetEdbInfoById(predictEdbConf.PredictEdbInfoId)
  76. // if tmpErr != nil {
  77. // errMsg = "新增失败"
  78. // err = tmpErr
  79. // return
  80. // }
  81. // //获取预测指标的分类
  82. // edbClassifyInfo, tmpErr := data_manage.GetEdbClassifyById(predictEdbInfo.ClassifyId)
  83. // if tmpErr != nil {
  84. // errMsg = "新增失败"
  85. // err = tmpErr
  86. // return
  87. // }
  88. // errMsg = "该指标已存在数据库,目录为:" + edbClassifyInfo.ClassifyName + ",请重新选择指标"
  89. // err = errors.New(errMsg)
  90. // return
  91. //}
  92. }
  93. //判断指标名称是否存在
  94. var condition string
  95. var pars []interface{}
  96. condition += " AND edb_info_type=? "
  97. pars = append(pars, 1)
  98. condition += " AND edb_name=? "
  99. pars = append(pars, edbName)
  100. count, err := data_manage.GetEdbInfoCountByCondition(condition, pars)
  101. if err != nil {
  102. errMsg = "判断指标名称是否存在失败"
  103. err = errors.New("判断指标名称是否存在失败,Err:" + err.Error())
  104. return
  105. }
  106. if count > 0 {
  107. errMsg = "指标名称已存在,请重新填写"
  108. return
  109. }
  110. timestamp := strconv.FormatInt(time.Now().UnixNano(), 10)
  111. edbInfo = &data_manage.EdbInfo{
  112. //EdbInfoId: 0,
  113. EdbInfoType: 1,
  114. SourceName: "预测指标",
  115. Source: utils.DATA_SOURCE_PREDICT,
  116. EdbCode: edbCode,
  117. EdbName: edbName,
  118. EdbNameSource: edbName,
  119. Frequency: sourceEdbInfo.Frequency,
  120. Unit: sourceEdbInfo.Unit,
  121. StartDate: sourceEdbInfo.StartDate,
  122. ClassifyId: classifyId,
  123. SysUserId: sysUserId,
  124. SysUserRealName: sysUserName,
  125. UniqueCode: utils.MD5(utils.DATA_PREFIX + "_" + timestamp),
  126. CreateTime: time.Now(),
  127. ModifyTime: time.Now(),
  128. MinValue: sourceEdbInfo.MinValue,
  129. MaxValue: sourceEdbInfo.MaxValue,
  130. CalculateFormula: sourceEdbInfo.CalculateFormula,
  131. EdbType: 1,
  132. //Sort: sourceEdbInfo.,
  133. LatestDate: sourceEdbInfo.LatestDate,
  134. LatestValue: sourceEdbInfo.LatestValue,
  135. MoveType: sourceEdbInfo.MoveType,
  136. MoveFrequency: sourceEdbInfo.MoveFrequency,
  137. NoUpdate: sourceEdbInfo.NoUpdate,
  138. ServerUrl: "",
  139. }
  140. // 关联关系表
  141. calculateMappingList := make([]*data_manage.EdbInfoCalculateMapping, 0)
  142. fromEdbMap := make(map[int]int)
  143. // 源指标关联关系表
  144. calculateMappingItem := &data_manage.EdbInfoCalculateMapping{
  145. //EdbInfoCalculateMappingId: 0,
  146. //EdbInfoId: 0,
  147. Source: edbInfo.Source,
  148. SourceName: edbInfo.SourceName,
  149. EdbCode: edbInfo.EdbCode,
  150. FromEdbInfoId: sourceEdbInfo.EdbInfoId,
  151. FromEdbCode: sourceEdbInfo.EdbCode,
  152. FromEdbName: sourceEdbInfo.EdbName,
  153. FromSource: sourceEdbInfo.Source,
  154. FromSourceName: sourceEdbInfo.SourceName,
  155. //FromTag: "",
  156. Sort: 1,
  157. CreateTime: time.Now(),
  158. ModifyTime: time.Now(),
  159. }
  160. fromEdbMap[sourceEdbInfoId] = sourceEdbInfoId
  161. calculateMappingList = append(calculateMappingList, calculateMappingItem)
  162. // 预测指标配置
  163. predictEdbConfList := make([]*data_manage.PredictEdbConf, 0)
  164. for _, v := range ruleList {
  165. // 预测指标配置
  166. ruleEndDate, tmpErr := time.ParseInLocation(utils.FormatDate, v.EndDate, time.Local)
  167. if tmpErr != nil {
  168. errMsg = "规则配置的截止日期异常,请重新填写"
  169. return
  170. }
  171. // 没有数据,自己瞎测试
  172. //switch v.RuleType {
  173. //case 3: //3:同比
  174. // v.Value = "0.1"
  175. //case 4: //4:同差
  176. // v.Value = "10"
  177. //case 5: //5:环比
  178. // v.Value = "0.1"
  179. //case 6: //6:环差
  180. // v.Value = "0.1"
  181. //case 7: //7:N期移动均值
  182. // v.Value = "5"
  183. //case 8: //8:N期段线性外推值
  184. // v.Value = "5"
  185. //}
  186. switch v.RuleType {
  187. case 8: //N期段线性外推值
  188. valInt, tmpErr := strconv.Atoi(v.Value)
  189. if tmpErr != nil {
  190. errMsg = "N期段线性外推值的N值异常"
  191. return
  192. }
  193. if valInt <= 1 {
  194. errMsg = "N期段线性外推值的N值必须大于1"
  195. return
  196. }
  197. case 9: //9:动态环差
  198. for _, v := range v.EdbInfoIdArr {
  199. fromEdbMap[v.EdbInfoId] = v.EdbInfoId
  200. }
  201. }
  202. tmpPredictEdbConf := &data_manage.PredictEdbConf{
  203. PredictEdbInfoId: 0,
  204. SourceEdbInfoId: sourceEdbInfoId,
  205. RuleType: v.RuleType,
  206. //FixedValue: v.Value,
  207. Value: v.Value,
  208. EndDate: ruleEndDate,
  209. ModifyTime: time.Now(),
  210. CreateTime: time.Now(),
  211. }
  212. edbInfo.EndDate = v.EndDate
  213. predictEdbConfList = append(predictEdbConfList, tmpPredictEdbConf)
  214. }
  215. err = data_manage.AddPredictEdb(edbInfo, calculateMappingItem, predictEdbConfList)
  216. if err != nil {
  217. errMsg = "保存失败"
  218. err = errors.New("保存失败,Err:" + err.Error())
  219. return
  220. }
  221. //新增操作日志
  222. {
  223. edbLog := new(data_manage.EdbInfoLog)
  224. edbLog.EdbInfoId = edbInfo.EdbInfoId
  225. edbLog.SourceName = edbInfo.SourceName
  226. edbLog.Source = edbInfo.Source
  227. edbLog.EdbCode = edbInfo.EdbCode
  228. edbLog.EdbName = edbInfo.EdbName
  229. edbLog.ClassifyId = edbInfo.ClassifyId
  230. edbLog.SysUserId = sysUserId
  231. edbLog.SysUserRealName = sysUserName
  232. edbLog.CreateTime = time.Now()
  233. edbLog.Content = requestBody
  234. edbLog.Status = "新增指标"
  235. edbLog.Method = requestUrl
  236. go data_manage.AddEdbInfoLog(edbLog)
  237. }
  238. //添加es
  239. AddOrEditEdbInfoToEs(edbInfo.EdbInfoId)
  240. return
  241. }
  242. // EditPredictEdbInfo 编辑预测指标
  243. func EditPredictEdbInfo(edbInfoId, classifyId int, edbName string, ruleList []request.RuleConfig, sysUserId int, sysUserName, requestBody, requestUrl string) (edbInfo *data_manage.EdbInfo, err error, errMsg string) {
  244. // 指标信息校验
  245. {
  246. edbInfo, err = data_manage.GetEdbInfoById(edbInfoId)
  247. if err != nil && !utils.IsErrNoRow(err) {
  248. errMsg = "修改失败"
  249. err = errors.New("获取预测指标失败,Err:" + err.Error())
  250. return
  251. }
  252. if edbInfo == nil {
  253. errMsg = "找不到该预测指标"
  254. err = nil
  255. return
  256. }
  257. //必须是普通的指标
  258. if edbInfo.EdbInfoType != 1 {
  259. errMsg = "指标异常,不是预测指标"
  260. return
  261. }
  262. }
  263. var predictEdbConf *data_manage.PredictEdbConf
  264. // 指标配置信息校验
  265. {
  266. // 查找该预测指标配置
  267. predictEdbConfList, tmpErr := data_manage.GetPredictEdbConfListById(edbInfo.EdbInfoId)
  268. if tmpErr != nil && !utils.IsErrNoRow(tmpErr) {
  269. errMsg = "修改失败"
  270. err = errors.New("获取预测指标配置信息失败,Err:" + tmpErr.Error())
  271. return
  272. }
  273. if len(predictEdbConfList) == 0 {
  274. errMsg = "找不到该预测指标配置"
  275. err = nil
  276. return
  277. }
  278. predictEdbConf = predictEdbConfList[0]
  279. }
  280. //判断指标名称是否存在
  281. var condition string
  282. var pars []interface{}
  283. condition += " AND edb_info_id<>? "
  284. pars = append(pars, edbInfoId)
  285. condition += " AND edb_info_type=? "
  286. pars = append(pars, 1)
  287. condition += " AND edb_name=? "
  288. pars = append(pars, edbName)
  289. count, err := data_manage.GetEdbInfoCountByCondition(condition, pars)
  290. if err != nil {
  291. errMsg = "判断指标名称是否存在失败"
  292. err = errors.New("判断指标名称是否存在失败,Err:" + err.Error())
  293. return
  294. }
  295. if count > 0 {
  296. errMsg = "指标名称已存在,请重新填写"
  297. return
  298. }
  299. edbInfo.EdbName = edbName
  300. edbInfo.EdbNameSource = edbName
  301. edbInfo.ClassifyId = classifyId
  302. edbInfo.ModifyTime = time.Now()
  303. updateEdbInfoCol := []string{"EdbName", "EdbNameSource", "ClassifyId", "EndDate", "ModifyTime"}
  304. // 预测指标配置
  305. predictEdbConfList := make([]*data_manage.PredictEdbConf, 0)
  306. for _, v := range ruleList {
  307. // 预测指标配置
  308. ruleEndDate, tmpErr := time.ParseInLocation(utils.FormatDate, v.EndDate, time.Local)
  309. if tmpErr != nil {
  310. errMsg = "规则配置的截止日期异常,请重新填写"
  311. return
  312. }
  313. switch v.RuleType {
  314. case 8: //N期段线性外推值
  315. valInt, tmpErr := strconv.Atoi(v.Value)
  316. if tmpErr != nil {
  317. errMsg = "N期段线性外推值的N值异常"
  318. return
  319. }
  320. if valInt <= 1 {
  321. errMsg = "N期段线性外推值的N值必须大于1"
  322. return
  323. }
  324. case 9: //9:动态环差
  325. }
  326. tmpPredictEdbConf := &data_manage.PredictEdbConf{
  327. PredictEdbInfoId: edbInfoId,
  328. SourceEdbInfoId: predictEdbConf.SourceEdbInfoId,
  329. RuleType: v.RuleType,
  330. //FixedValue: v.Value,
  331. Value: v.Value,
  332. EndDate: ruleEndDate,
  333. ModifyTime: time.Now(),
  334. CreateTime: time.Now(),
  335. }
  336. predictEdbConfList = append(predictEdbConfList, tmpPredictEdbConf)
  337. edbInfo.EndDate = v.EndDate
  338. }
  339. err = data_manage.EditPredictEdb(edbInfo, predictEdbConfList, updateEdbInfoCol)
  340. if err != nil {
  341. errMsg = "保存失败"
  342. err = errors.New("保存失败,Err:" + err.Error())
  343. return
  344. }
  345. //新增操作日志
  346. {
  347. edbLog := new(data_manage.EdbInfoLog)
  348. edbLog.EdbInfoId = edbInfo.EdbInfoId
  349. edbLog.SourceName = edbInfo.SourceName
  350. edbLog.Source = edbInfo.Source
  351. edbLog.EdbCode = edbInfo.EdbCode
  352. edbLog.EdbName = edbInfo.EdbName
  353. edbLog.ClassifyId = edbInfo.ClassifyId
  354. edbLog.SysUserId = sysUserId
  355. edbLog.SysUserRealName = sysUserName
  356. edbLog.CreateTime = time.Now()
  357. edbLog.Content = requestBody
  358. edbLog.Status = "编辑指标"
  359. edbLog.Method = requestUrl
  360. go data_manage.AddEdbInfoLog(edbLog)
  361. }
  362. //添加es
  363. AddOrEditEdbInfoToEs(edbInfoId)
  364. // 刷新关联指标
  365. go EdbInfoRefreshAllFromBaseV2(edbInfo.EdbInfoId, true, false)
  366. return
  367. }
  368. // RefreshPredictEdbInfo 刷新预测指标
  369. func RefreshPredictEdbInfo(edbInfoId int, refreshAll bool) (edbInfo *data_manage.EdbInfo, isAsync bool, err error, errMsg string) {
  370. // 指标信息校验
  371. {
  372. edbInfo, err = data_manage.GetEdbInfoById(edbInfoId)
  373. if err != nil && !utils.IsErrNoRow(err) {
  374. errMsg = "刷新失败"
  375. err = errors.New("获取预测指标失败,Err:" + err.Error())
  376. return
  377. }
  378. if edbInfo == nil {
  379. errMsg = "找不到该预测指标"
  380. err = nil
  381. return
  382. }
  383. //必须是预测的指标
  384. if edbInfo.EdbInfoType != 1 {
  385. errMsg = "指标异常,不是预测指标"
  386. return
  387. }
  388. }
  389. err, isAsync = EdbInfoRefreshAllFromBaseV2(edbInfo.EdbInfoId, refreshAll, false)
  390. return
  391. }
  392. // MovePredictEdbInfo 移动预测指标
  393. func MovePredictEdbInfo(edbInfoId, classifyId, prevEdbInfoId, nextEdbInfoId int, sysUser *system.Admin, requestBody, requestUrl string) (err error, errMsg string) {
  394. //判断分类是否存在
  395. count, _ := data_manage.GetEdbClassifyCountById(classifyId)
  396. if count <= 0 {
  397. errMsg = "分类已被删除,不可移动,请刷新页面"
  398. return
  399. }
  400. edbInfo, err := data_manage.GetEdbInfoById(edbInfoId)
  401. if err != nil {
  402. if err != nil && !utils.IsErrNoRow(err) {
  403. errMsg = "移动失败"
  404. err = errors.New("获取预测指标失败,Err:" + err.Error())
  405. return
  406. }
  407. if edbInfo == nil {
  408. errMsg = "找不到该预测指标"
  409. err = nil
  410. return
  411. }
  412. return
  413. }
  414. var haveOperaAuth bool
  415. // 权限校验
  416. {
  417. haveOperaAuth, err = data_manage_permission.CheckEdbPermissionByEdbInfoId(edbInfo.EdbInfoId, edbInfo.ClassifyId, edbInfo.IsJoinPermission, sysUser.AdminId)
  418. if err != nil {
  419. errMsg = "移动失败"
  420. err = errors.New("校验指标权限失败,Err:" + err.Error())
  421. return
  422. }
  423. }
  424. // 移动权限校验
  425. button := GetEdbOpButton(sysUser, edbInfo.SysUserId, edbInfo.EdbType, edbInfo.EdbInfoType, haveOperaAuth)
  426. if !button.MoveButton {
  427. errMsg = "无权限操作"
  428. err = nil
  429. return
  430. }
  431. //如果改变了分类,那么移动该指标数据
  432. if edbInfo.ClassifyId != classifyId {
  433. err = data_manage.MoveEdbInfo(edbInfoId, classifyId)
  434. if err != nil {
  435. errMsg = "移动失败"
  436. err = errors.New("移动预测指标失败,Err:" + err.Error())
  437. return
  438. }
  439. }
  440. updateCol := make([]string, 0)
  441. //如果有传入 上一个兄弟节点分类id
  442. if prevEdbInfoId > 0 {
  443. prevEdbInfo, tmpErr := data_manage.GetEdbInfoById(prevEdbInfoId)
  444. if tmpErr != nil {
  445. errMsg = "移动失败"
  446. err = errors.New("获取上一个兄弟节点分类信息失败,Err:" + tmpErr.Error())
  447. return
  448. }
  449. //如果是移动在两个兄弟节点之间
  450. if nextEdbInfoId > 0 {
  451. //下一个兄弟节点
  452. nextEdbInfo, tmpErr := data_manage.GetEdbInfoById(nextEdbInfoId)
  453. if tmpErr != nil {
  454. errMsg = "移动失败"
  455. err = errors.New("获取下一个兄弟节点分类信息失败,Err:" + tmpErr.Error())
  456. return
  457. }
  458. //如果上一个兄弟与下一个兄弟的排序权重是一致的,那么需要将下一个兄弟(以及下个兄弟的同样排序权重)的排序权重+2,自己变成上一个兄弟的排序权重+1
  459. if prevEdbInfo.Sort == nextEdbInfo.Sort || prevEdbInfo.Sort == edbInfo.Sort {
  460. //变更兄弟节点的排序
  461. updateSortStr := `sort + 2`
  462. _ = data_manage.UpdateEdbInfoSortByClassifyId(prevEdbInfo.ClassifyId, prevEdbInfo.Sort, prevEdbInfo.EdbInfoId, updateSortStr)
  463. } else {
  464. //如果下一个兄弟的排序权重正好是上个兄弟节点 的下一层,那么需要再加一层了
  465. if nextEdbInfo.Sort-prevEdbInfo.Sort == 1 {
  466. //变更兄弟节点的排序
  467. updateSortStr := `sort + 1`
  468. _ = data_manage.UpdateEdbInfoSortByClassifyId(prevEdbInfo.ClassifyId, prevEdbInfo.Sort, prevEdbInfo.EdbInfoId, updateSortStr)
  469. }
  470. }
  471. }
  472. edbInfo.Sort = prevEdbInfo.Sort + 1
  473. edbInfo.ModifyTime = time.Now()
  474. updateCol = append(updateCol, "Sort", "ModifyTime")
  475. } else {
  476. firstClassify, tmpErr := data_manage.GetFirstEdbInfoByClassifyId(classifyId)
  477. if tmpErr != nil && !utils.IsErrNoRow(tmpErr) {
  478. errMsg = "移动失败"
  479. err = errors.New("获取获取当前父级分类下的排序第一条的分类信息失败,Err:" + err.Error())
  480. return
  481. }
  482. //如果该分类下存在其他分类,且第一个其他分类的排序等于0,那么需要调整排序
  483. if firstClassify != nil && firstClassify.Sort == 0 {
  484. updateSortStr := ` sort + 1 `
  485. _ = data_manage.UpdateEdbInfoSortByClassifyId(firstClassify.ClassifyId, 0, firstClassify.EdbInfoId-1, updateSortStr)
  486. }
  487. edbInfo.Sort = 0 //那就是排在第一位
  488. edbInfo.ModifyTime = time.Now()
  489. updateCol = append(updateCol, "Sort", "ModifyTime")
  490. }
  491. //更新
  492. if len(updateCol) > 0 {
  493. err = edbInfo.Update(updateCol)
  494. if err != nil {
  495. errMsg = "移动失败"
  496. err = errors.New("修改失败,Err:" + err.Error())
  497. return
  498. }
  499. //添加es
  500. AddOrEditEdbInfoToEs(edbInfo.EdbInfoId)
  501. }
  502. //新增操作日志
  503. {
  504. edbLog := new(data_manage.EdbInfoLog)
  505. edbLog.EdbInfoId = edbInfo.EdbInfoId
  506. edbLog.SourceName = edbInfo.SourceName
  507. edbLog.Source = edbInfo.Source
  508. edbLog.EdbCode = edbInfo.EdbCode
  509. edbLog.EdbName = edbInfo.EdbName
  510. edbLog.ClassifyId = edbInfo.ClassifyId
  511. edbLog.SysUserId = sysUser.AdminId
  512. edbLog.SysUserRealName = sysUser.RealName
  513. edbLog.CreateTime = time.Now()
  514. edbLog.Content = requestBody
  515. edbLog.Status = "移动指标"
  516. edbLog.Method = requestUrl
  517. go data_manage.AddEdbInfoLog(edbLog)
  518. }
  519. return
  520. }
  521. // GetChartPredictEdbInfoDataListByConfList 获取图表的预测指标的未来数据
  522. func GetChartPredictEdbInfoDataListByConfList(predictEdbConfList []data_manage.PredictEdbConfAndData, filtrateStartDateStr, latestDateStr, endDateStr string, endDateType int, frequency, dataDateType string, realPredictEdbInfoData []*data_manage.EdbDataList) (predictEdbInfoData []*data_manage.EdbDataList, minValue, maxValue float64, err error, errMsg string) {
  523. hasEndNum := 0 //如果选择了未来期数,用来保存已经预测过的期数
  524. var endDate time.Time
  525. if endDateStr != `` {
  526. endDate, err = time.ParseInLocation(utils.FormatDate, endDateStr, time.Local)
  527. if err != nil {
  528. return
  529. }
  530. }
  531. latestDate, err := time.ParseInLocation(utils.FormatDate, latestDateStr, time.Local)
  532. if err != nil {
  533. return
  534. }
  535. // 开始预测数据的时间
  536. startDate := latestDate
  537. // 如果有筛选时间的话
  538. if filtrateStartDateStr != `` {
  539. filtrateStartDate, tmpErr := time.ParseInLocation(utils.FormatDate, filtrateStartDateStr, time.Local)
  540. if tmpErr != nil {
  541. err = tmpErr
  542. return
  543. }
  544. //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
  545. if filtrateStartDate.After(latestDate) {
  546. startDate = filtrateStartDate.AddDate(0, 0, -1)
  547. }
  548. }
  549. //var dateArr []string
  550. // 对应日期的值
  551. existMap := make(map[string]float64)
  552. for _, v := range realPredictEdbInfoData {
  553. //dateArr = append(dateArr, v.DataTime)
  554. existMap[v.DataTime] = v.Value
  555. }
  556. predictEdbInfoData = make([]*data_manage.EdbDataList, 0)
  557. //dataValue := lastDataValue
  558. //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,17:动态同比,18:动态同差
  559. for _, predictEdbConf := range predictEdbConfList {
  560. dataEndTime := endDate
  561. if !predictEdbConf.EndDate.IsZero() && predictEdbConf.EndDate.Before(dataEndTime) {
  562. dataEndTime = predictEdbConf.EndDate
  563. }
  564. var tmpMinValue, tmpMaxValue float64 // 当前预测结果中的最大/最小值
  565. endNum := predictEdbConf.EndNum - hasEndNum
  566. if endNum <= 0 && endDateType == 1 {
  567. err = fmt.Errorf("预测期数不能小于等于0")
  568. return
  569. }
  570. dayList := getPredictEdbDayList(startDate, dataEndTime, frequency, dataDateType, endDateType, endNum)
  571. 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
  572. continue
  573. }
  574. switch predictEdbConf.RuleType {
  575. case 1: //1:最新
  576. var lastDataValue float64 //最新值
  577. tmpAllData := make([]*data_manage.EdbDataList, 0)
  578. tmpAllData = append(tmpAllData, realPredictEdbInfoData...)
  579. tmpAllData = append(tmpAllData, predictEdbInfoData...)
  580. lenTmpAllData := len(tmpAllData)
  581. if lenTmpAllData > 0 {
  582. lastDataValue = tmpAllData[lenTmpAllData-1].Value
  583. }
  584. predictEdbInfoData = GetChartPredictEdbInfoDataListByRule1(predictEdbConf.PredictEdbInfoId, lastDataValue, dayList, predictEdbInfoData, existMap)
  585. tmpMaxValue = lastDataValue
  586. tmpMinValue = lastDataValue
  587. case 2: //2:固定值
  588. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  589. if tmpErr != nil {
  590. err = tmpErr
  591. return
  592. }
  593. dataValue, _ := tmpValDecimal.Float64()
  594. predictEdbInfoData = GetChartPredictEdbInfoDataListByRule1(predictEdbConf.PredictEdbInfoId, dataValue, dayList, predictEdbInfoData, existMap)
  595. tmpMaxValue = dataValue
  596. tmpMinValue = dataValue
  597. case 3: //3:同比
  598. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  599. if tmpErr != nil {
  600. err = tmpErr
  601. return
  602. }
  603. tbValue, _ := tmpValDecimal.Float64()
  604. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleTb(predictEdbConf.PredictEdbInfoId, tbValue, dayList, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  605. case 4: //4:同差
  606. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  607. if tmpErr != nil {
  608. err = tmpErr
  609. return
  610. }
  611. tcValue, _ := tmpValDecimal.Float64()
  612. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleTc(predictEdbConf.PredictEdbInfoId, tcValue, dayList, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  613. case 5: //5:环比
  614. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  615. if tmpErr != nil {
  616. err = tmpErr
  617. return
  618. }
  619. hbValue, _ := tmpValDecimal.Float64()
  620. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleHb(predictEdbConf.PredictEdbInfoId, hbValue, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  621. case 6: //6:环差
  622. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  623. if tmpErr != nil {
  624. err = tmpErr
  625. return
  626. }
  627. hcValue, _ := tmpValDecimal.Float64()
  628. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleHc(predictEdbConf.PredictEdbInfoId, hcValue, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  629. case 7: //7:N期移动均值
  630. nValue, tmpErr := strconv.Atoi(predictEdbConf.Value)
  631. if tmpErr != nil {
  632. err = tmpErr
  633. return
  634. }
  635. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleNMoveMeanValue(predictEdbConf.PredictEdbInfoId, nValue, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  636. case 8: //8:N期段线性外推值
  637. nValue, tmpErr := strconv.Atoi(predictEdbConf.Value)
  638. if tmpErr != nil {
  639. err = tmpErr
  640. return
  641. }
  642. if nValue <= 1 {
  643. errMsg = `N期段线性外推值的N值必须大于1`
  644. err = errors.New(errMsg)
  645. return
  646. }
  647. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleNLinearRegression(predictEdbConf.PredictEdbInfoId, nValue, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  648. if err != nil {
  649. return
  650. }
  651. case 9: //9:动态环差”预测规则;
  652. //规则计算的环差值map
  653. hcDataMap := make(map[string]float64)
  654. if predictEdbConf.PredictEdbInfoId > 0 { //已经生成的动态数据
  655. tmpPredictEdbRuleDataList, tmpErr := data_manage.GetPredictEdbRuleDataList(predictEdbConf.PredictEdbInfoId, predictEdbConf.ConfigId, startDate.Format(utils.FormatDate), endDate.Format(utils.FormatDate))
  656. if tmpErr != nil {
  657. err = tmpErr
  658. return
  659. }
  660. for _, v := range tmpPredictEdbRuleDataList {
  661. hcDataMap[v.DataTime] = v.Value
  662. }
  663. } else { //未生成的动态数据,需要使用外部传入的数据进行计算
  664. if len(predictEdbConf.DataList) <= 0 {
  665. return
  666. }
  667. for _, v := range predictEdbConf.DataList {
  668. currentDate, tmpErr := time.ParseInLocation(utils.FormatDate, v.DataTime, time.Local)
  669. if tmpErr != nil {
  670. continue
  671. }
  672. // 只处理时间段内的数据
  673. if currentDate.Before(startDate) || currentDate.After(endDate) {
  674. continue
  675. }
  676. hcDataMap[v.DataTime] = v.Value
  677. }
  678. }
  679. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleTrendsHC(predictEdbConf.PredictEdbInfoId, dayList, realPredictEdbInfoData, predictEdbInfoData, hcDataMap, existMap)
  680. case 10: //10:根据 给定终值后插值 规则获取预测数据
  681. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  682. if tmpErr != nil {
  683. err = tmpErr
  684. return
  685. }
  686. finalValue, _ := tmpValDecimal.Float64()
  687. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleFinalValueHc(predictEdbConf.PredictEdbInfoId, finalValue, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  688. case 11: //11:根据 季节性 规则获取预测数据
  689. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleSeason(predictEdbConf.PredictEdbInfoId, predictEdbConf.Value, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  690. if err != nil {
  691. return
  692. }
  693. case 12: //12:根据 移动平均同比 规则获取预测数据
  694. var moveAverageConf MoveAverageConf
  695. tmpErr := json.Unmarshal([]byte(predictEdbConf.Value), &moveAverageConf)
  696. if tmpErr != nil {
  697. err = errors.New("季节性配置信息异常:" + tmpErr.Error())
  698. return
  699. }
  700. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleMoveAverageTb(predictEdbConf.PredictEdbInfoId, moveAverageConf.NValue, moveAverageConf.Year, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  701. if err != nil {
  702. return
  703. }
  704. case 13: //13:根据 同比增速差值 规则获取预测数据
  705. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  706. if tmpErr != nil {
  707. err = tmpErr
  708. return
  709. }
  710. tbEndValue, _ := tmpValDecimal.Float64()
  711. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleTbzscz(predictEdbConf.PredictEdbInfoId, tbEndValue, dayList, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  712. case 14: //14:根据 一元线性拟合 规则获取预测数据
  713. var ruleConf RuleLineNhConf
  714. err = json.Unmarshal([]byte(predictEdbConf.Value), &ruleConf)
  715. if err != nil {
  716. err = errors.New("一元线性拟合配置信息异常:" + err.Error())
  717. return
  718. }
  719. // 规则计算的拟合残差值map
  720. newNhccDataMap := make(map[string]float64)
  721. if predictEdbConf.PredictEdbInfoId > 0 { //已经生成的动态数据
  722. tmpPredictEdbRuleDataList, tmpErr := data_manage.GetPredictEdbRuleDataList(predictEdbConf.PredictEdbInfoId, predictEdbConf.ConfigId, "", "")
  723. if tmpErr != nil {
  724. err = tmpErr
  725. return
  726. }
  727. for _, v := range tmpPredictEdbRuleDataList {
  728. newNhccDataMap[v.DataTime] = v.Value
  729. }
  730. } else { //未生成的动态数据,需要使用外部传入的数据进行计算
  731. newNhccDataMap, err = getCalculateNhccData(append(realPredictEdbInfoData, predictEdbInfoData...), ruleConf)
  732. if err != nil {
  733. return
  734. }
  735. }
  736. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleLineNh(predictEdbConf.PredictEdbInfoId, dayList, realPredictEdbInfoData, predictEdbInfoData, newNhccDataMap, existMap)
  737. if err != nil {
  738. return
  739. }
  740. 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;
  741. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleNAnnualAverage(predictEdbConf.PredictEdbInfoId, predictEdbConf.Value, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  742. if err != nil {
  743. return
  744. }
  745. case 16: //16:年度值倒推
  746. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleAnnualValueInversion(predictEdbConf.PredictEdbInfoId, predictEdbConf.Value, dayList, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  747. if err != nil {
  748. return
  749. }
  750. case 17, 18:
  751. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleDynamicYOYComparisonOrDifference(predictEdbConf.RuleType, predictEdbConf.PredictEdbInfoId, predictEdbConf.Value, dayList, realPredictEdbInfoData, existMap)
  752. if err != nil {
  753. return
  754. }
  755. }
  756. // 下一个规则的开始日期
  757. {
  758. lenPredictEdbInfoData := len(predictEdbInfoData)
  759. if lenPredictEdbInfoData > 0 {
  760. if endDateType == 1 {
  761. hasEndNum = predictEdbConf.EndNum
  762. }
  763. tmpDataEndTime, _ := time.ParseInLocation(utils.FormatDate, predictEdbInfoData[lenPredictEdbInfoData-1].DataTime, time.Local)
  764. if startDate.Before(tmpDataEndTime) {
  765. startDate = tmpDataEndTime
  766. }
  767. }
  768. }
  769. if tmpMinValue < minValue {
  770. minValue = tmpMinValue
  771. }
  772. if tmpMaxValue > maxValue {
  773. maxValue = tmpMaxValue
  774. }
  775. }
  776. return
  777. }
  778. // GetPredictEdbDayList 获取预测指标日期列表
  779. func getPredictEdbDayList(startDate, endDate time.Time, frequency, dataDateType string, endDateType, endNum int) (dayList []time.Time) {
  780. if dataDateType == `` {
  781. dataDateType = `交易日`
  782. }
  783. if endDateType == 0 { // 截止日期
  784. switch frequency {
  785. case "日度":
  786. for currDate := startDate.AddDate(0, 0, 1); currDate.Before(endDate) || currDate.Equal(endDate); currDate = currDate.AddDate(0, 0, 1) {
  787. // 如果日期类型是交易日的时候,那么需要将周六、日排除
  788. if dataDateType == `交易日` && (currDate.Weekday() == time.Sunday || currDate.Weekday() == time.Saturday) {
  789. continue
  790. }
  791. dayList = append(dayList, currDate)
  792. }
  793. case "周度":
  794. //nextDate := startDate.AddDate(0, 0, 7)
  795. for currDate := startDate.AddDate(0, 0, 7); currDate.Before(endDate) || currDate.Equal(endDate); currDate = currDate.AddDate(0, 0, 7) {
  796. dayList = append(dayList, currDate)
  797. }
  798. case "旬度":
  799. for currDate := startDate.AddDate(0, 0, 1); currDate.Before(endDate) || currDate.Equal(endDate); {
  800. nextDate := currDate.AddDate(0, 0, 1)
  801. //每个月的10号、20号、最后一天,那么就写入
  802. if nextDate.Day() == 11 || nextDate.Day() == 21 || nextDate.Day() == 1 {
  803. dayList = append(dayList, currDate)
  804. }
  805. currDate = nextDate
  806. }
  807. case "月度":
  808. for currDate := startDate; currDate.Before(endDate) || currDate.Equal(endDate); {
  809. currDate = time.Date(currDate.Year(), currDate.Month(), 1, 0, 0, 0, 0, time.Now().Location()).AddDate(0, 1, -1)
  810. if !currDate.After(endDate) && !currDate.Equal(startDate) {
  811. dayList = append(dayList, currDate)
  812. }
  813. currDate = currDate.AddDate(0, 0, 1)
  814. }
  815. case "季度":
  816. for currDate := startDate; currDate.Before(endDate) || currDate.Equal(endDate); {
  817. // 每月的最后一天
  818. currDate = time.Date(currDate.Year(), currDate.Month(), 1, 0, 0, 0, 0, time.Now().Location()).AddDate(0, 1, -1)
  819. if !currDate.After(endDate) && !currDate.Equal(startDate) {
  820. // 季度日期就写入,否则不写入
  821. if currDate.Month() == 3 || currDate.Month() == 6 || currDate.Month() == 9 || currDate.Month() == 12 {
  822. dayList = append(dayList, currDate)
  823. }
  824. }
  825. currDate = currDate.AddDate(0, 0, 1)
  826. }
  827. case "半年度":
  828. for currDate := startDate; currDate.Before(endDate) || currDate.Equal(endDate); {
  829. // 每月的最后一天
  830. currDate = time.Date(currDate.Year(), currDate.Month(), 1, 0, 0, 0, 0, time.Now().Location()).AddDate(0, 1, -1)
  831. if !currDate.After(endDate) && !currDate.Equal(startDate) {
  832. // 半年度日期就写入,否则不写入
  833. if currDate.Month() == 6 || currDate.Month() == 12 {
  834. dayList = append(dayList, currDate)
  835. }
  836. }
  837. currDate = currDate.AddDate(0, 0, 1)
  838. }
  839. case "年度":
  840. for currDate := startDate; currDate.Before(endDate) || currDate.Equal(endDate); {
  841. currDate = time.Date(currDate.Year()+1, 12, 31, 0, 0, 0, 0, time.Now().Location())
  842. if !currDate.After(endDate) && !currDate.Equal(startDate) {
  843. dayList = append(dayList, currDate)
  844. }
  845. }
  846. }
  847. } else { // 截止期数
  848. switch frequency {
  849. case "日度":
  850. for i := 1; i <= endNum; i++ {
  851. currDate := startDate.AddDate(0, 0, i)
  852. // 如果日期类型是交易日的时候,那么需要将周六、日排除
  853. if dataDateType == `交易日` && (currDate.Weekday() == time.Sunday || currDate.Weekday() == time.Saturday) {
  854. continue
  855. }
  856. dayList = append(dayList, currDate)
  857. }
  858. case "周度":
  859. for i := 1; i <= endNum; i++ {
  860. currDate := startDate.AddDate(0, 0, i*7)
  861. dayList = append(dayList, currDate)
  862. }
  863. case "旬度":
  864. currDate := startDate
  865. for i := 1; len(dayList) < endNum; i++ {
  866. currDate = currDate.AddDate(0, 0, 1)
  867. nextDate := currDate.AddDate(0, 0, 1)
  868. //每个月的10号、20号、最后一天,那么就写入
  869. if nextDate.Day() == 11 || nextDate.Day() == 21 || nextDate.Day() == 1 {
  870. dayList = append(dayList, currDate)
  871. }
  872. }
  873. case "月度":
  874. currDate := startDate
  875. for i := 0; i <= endNum; i++ {
  876. currDate = time.Date(currDate.Year(), currDate.Month(), 1, 0, 0, 0, 0, time.Now().Location()).AddDate(0, 1, -1)
  877. if !currDate.Equal(startDate) {
  878. dayList = append(dayList, currDate)
  879. }
  880. currDate = currDate.AddDate(0, 0, 1)
  881. }
  882. case "季度":
  883. currDate := startDate
  884. endNum = endNum * 3
  885. for i := 0; i <= endNum; i++ {
  886. currDate = time.Date(currDate.Year(), currDate.Month(), 1, 0, 0, 0, 0, time.Now().Location()).AddDate(0, 1, -1)
  887. if currDate.After(startDate) {
  888. // 季度日期就写入,否则不写入
  889. if currDate.Month() == 3 || currDate.Month() == 6 || currDate.Month() == 9 || currDate.Month() == 12 {
  890. dayList = append(dayList, currDate)
  891. }
  892. }
  893. currDate = currDate.AddDate(0, 0, 1)
  894. }
  895. case "半年度":
  896. currDate := startDate
  897. endNum = endNum * 6
  898. for i := 0; i <= endNum; i++ {
  899. currDate = time.Date(currDate.Year(), currDate.Month(), 1, 0, 0, 0, 0, time.Now().Location()).AddDate(0, 1, -1)
  900. if currDate.After(startDate) {
  901. // 季度日期就写入,否则不写入
  902. if currDate.Month() == 6 || currDate.Month() == 12 {
  903. dayList = append(dayList, currDate)
  904. }
  905. }
  906. currDate = currDate.AddDate(0, 0, 1)
  907. }
  908. case "年度":
  909. for i := 1; i <= endNum; i++ {
  910. currDate := startDate.AddDate(i, 0, 0)
  911. currDate, _ = time.ParseInLocation(utils.FormatDate, fmt.Sprintf(`%d-12-31`, currDate.Year()), time.Local)
  912. dayList = append(dayList, currDate)
  913. }
  914. }
  915. }
  916. return
  917. }
  918. // GetPredictDataListByPredictEdbInfoId 根据预测指标id获取预测指标的数据(日期正序返回)
  919. 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) {
  920. edbInfo, err = data_manage.GetEdbInfoById(edbInfoId)
  921. if err != nil {
  922. errMsg = `获取预测指标信息失败`
  923. return
  924. }
  925. dataList, sourceEdbInfoItem, predictEdbConf, err, errMsg = GetPredictDataListByPredictEdbInfo(edbInfo, startDate, endDate, isTimeBetween)
  926. return
  927. }
  928. // GetPredictDataListByPredictEdbInfo 根据预测指标信息获取预测指标的数据
  929. 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) {
  930. if !isTimeBetween { //如果不是区间数据,那么就结束日期为空
  931. endDate = ``
  932. }
  933. return GetPredictCalculateDataListByPredictEdbInfo(edbInfo, startDate, endDate)
  934. }
  935. // GetChartDataList 通过完整的预测数据 进行 季节性图、公历、农历处理
  936. func GetChartDataList(dataList []*data_manage.EdbDataList, chartType int, calendar, latestDateStr, startDate string) (resultDataList interface{}, err error) {
  937. startDateReal := startDate
  938. calendarPreYear := 0
  939. if calendar == "农历" {
  940. newStartDateReal, err := time.Parse(utils.FormatDate, startDateReal)
  941. if err != nil {
  942. fmt.Println("time.Parse:" + err.Error())
  943. }
  944. calendarPreYear = newStartDateReal.Year() - 1
  945. newStartDateReal = newStartDateReal.AddDate(-1, 0, 0)
  946. startDateReal = newStartDateReal.Format(utils.FormatDate)
  947. }
  948. if latestDateStr == `` {
  949. return
  950. }
  951. //实际数据的截止日期
  952. latestDate, tmpErr := time.Parse(utils.FormatDate, latestDateStr)
  953. if tmpErr != nil {
  954. err = errors.New(fmt.Sprint("获取最后实际数据的日期失败,Err:" + tmpErr.Error() + ";LatestDate:" + latestDateStr))
  955. return
  956. }
  957. latestDateYear := latestDate.Year() //实际数据截止年份
  958. // 曲线图
  959. if chartType == 1 {
  960. resultDataList = dataList
  961. return
  962. }
  963. if calendar == "农历" {
  964. if len(dataList) <= 0 {
  965. resultDataList = data_manage.EdbDataResult{}
  966. } else {
  967. result, tmpErr := data_manage.AddCalculateQuarterV4(dataList)
  968. if tmpErr != nil {
  969. err = errors.New("获取农历数据失败,Err:" + tmpErr.Error())
  970. return
  971. }
  972. // 处理季节图的截止日期
  973. for k, edbDataItems := range result.List {
  974. var cuttingDataTimestamp int64
  975. // 切割的日期时间字符串
  976. cuttingDataTimeStr := latestDate.AddDate(0, 0, edbDataItems.BetweenDay).Format(utils.FormatDate)
  977. //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
  978. if edbDataItems.Year >= latestDateYear {
  979. for _, tmpData := range edbDataItems.Items {
  980. if tmpData.DataTime == cuttingDataTimeStr {
  981. cuttingDataTimestamp = tmpData.DataTimestamp
  982. break
  983. }
  984. }
  985. }
  986. edbDataItems.CuttingDataTimestamp = cuttingDataTimestamp
  987. result.List[k] = edbDataItems
  988. }
  989. if result.List[0].Year != calendarPreYear {
  990. itemList := make([]*data_manage.EdbDataList, 0)
  991. items := new(data_manage.EdbDataItems)
  992. //items.Year = calendarPreYear
  993. items.Items = itemList
  994. newResult := new(data_manage.EdbDataResult)
  995. newResult.List = append(newResult.List, items)
  996. newResult.List = append(newResult.List, result.List...)
  997. resultDataList = newResult
  998. } else {
  999. resultDataList = result
  1000. }
  1001. }
  1002. } else {
  1003. currentYear := time.Now().Year()
  1004. quarterDataList := make([]*data_manage.QuarterData, 0)
  1005. quarterMap := make(map[int][]*data_manage.EdbDataList)
  1006. var quarterArr []int
  1007. for _, v := range dataList {
  1008. itemDate, tmpErr := time.Parse(utils.FormatDate, v.DataTime)
  1009. if tmpErr != nil {
  1010. err = errors.New("季度指标日期转换,Err:" + tmpErr.Error() + ";DataTime:" + v.DataTime)
  1011. return
  1012. }
  1013. year := itemDate.Year()
  1014. newItemDate := itemDate.AddDate(currentYear-year, 0, 0)
  1015. timestamp := newItemDate.UnixNano() / 1e6
  1016. v.DataTimestamp = timestamp
  1017. if findVal, ok := quarterMap[year]; !ok {
  1018. quarterArr = append(quarterArr, year)
  1019. findVal = append(findVal, v)
  1020. quarterMap[year] = findVal
  1021. } else {
  1022. findVal = append(findVal, v)
  1023. quarterMap[year] = findVal
  1024. }
  1025. }
  1026. for _, v := range quarterArr {
  1027. itemList := quarterMap[v]
  1028. quarterItem := new(data_manage.QuarterData)
  1029. quarterItem.Year = v
  1030. quarterItem.DataList = itemList
  1031. //如果等于最后的实际日期,那么将切割时间戳记录
  1032. if v == latestDateYear {
  1033. var cuttingDataTimestamp int64
  1034. for _, tmpData := range itemList {
  1035. if tmpData.DataTime == latestDateStr {
  1036. cuttingDataTimestamp = tmpData.DataTimestamp
  1037. break
  1038. }
  1039. }
  1040. quarterItem.CuttingDataTimestamp = cuttingDataTimestamp
  1041. } else if v > latestDateYear {
  1042. //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
  1043. if len(itemList) > 0 {
  1044. quarterItem.CuttingDataTimestamp = itemList[0].DataTimestamp - 100
  1045. }
  1046. }
  1047. quarterDataList = append(quarterDataList, quarterItem)
  1048. }
  1049. resultDataList = quarterDataList
  1050. }
  1051. return
  1052. }
  1053. // GetPredictCalculateDataListByPredictEdbInfo 根据预测运算指标信息获取预测指标的数据
  1054. 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) {
  1055. dataList, err = data_manage.GetEdbDataList(edbInfo.Source, edbInfo.SubSource, edbInfo.EdbInfoId, startDate, endDate)
  1056. return
  1057. }
  1058. // ModifyPredictEdbBaseInfoBySourceEdb 根据来源ETA指标修改预测指标的基础信息
  1059. func ModifyPredictEdbBaseInfoBySourceEdb(sourceEDdbInfo *data_manage.EdbInfo, frequency, unit string) {
  1060. list, err := data_manage.GetGroupPredictEdbBySourceEdbInfoId(sourceEDdbInfo.EdbInfoId)
  1061. if err != nil {
  1062. return
  1063. }
  1064. for _, v := range list {
  1065. v.Frequency = frequency
  1066. v.Unit = unit
  1067. v.Update([]string{"Frequency", "Unit"})
  1068. AddOrEditEdbInfoToEs(v.EdbInfoId)
  1069. }
  1070. }
  1071. // ModifyPredictEdbEnBaseInfoBySourceEdb 根据来源ETA指标修改预测指标的英文基础信息
  1072. func ModifyPredictEdbEnBaseInfoBySourceEdb(sourceEDdbInfo *data_manage.EdbInfo, unitEn string) {
  1073. list, err := data_manage.GetGroupPredictEdbBySourceEdbInfoId(sourceEDdbInfo.EdbInfoId)
  1074. if err != nil {
  1075. return
  1076. }
  1077. for _, v := range list {
  1078. v.UnitEn = unitEn
  1079. v.Update([]string{"UnitEn"})
  1080. AddOrEditEdbInfoToEs(v.EdbInfoId)
  1081. }
  1082. }
  1083. // ModifyPredictEdbUnitBySourceEdbInfoId
  1084. // @Description: 根据来源ETA指标修改预测指标的频度和单位基础信息
  1085. // @author: Roc
  1086. // @datetime 2024-01-05 11:07:39
  1087. // @param sourceEdbInfoId int
  1088. // @param frequency string
  1089. // @param unit string
  1090. // @return err error
  1091. func ModifyPredictEdbUnitBySourceEdbInfoId(sourceEdbInfoId int, frequency, unit string) (err error) {
  1092. list, err := data_manage.GetGroupPredictEdbBySourceEdbInfoId(sourceEdbInfoId)
  1093. if err != nil {
  1094. return
  1095. }
  1096. for _, v := range list {
  1097. v.Frequency = frequency
  1098. v.Unit = unit
  1099. v.Update([]string{"Frequency", "Unit"})
  1100. AddOrEditEdbInfoToEs(v.EdbInfoId)
  1101. }
  1102. return
  1103. }