predict_edb_info.go 41 KB

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  1. package data
  2. import (
  3. "encoding/json"
  4. "errors"
  5. "eta_gn/eta_api/models/data_manage"
  6. "eta_gn/eta_api/models/data_manage/request"
  7. "eta_gn/eta_api/models/system"
  8. "eta_gn/eta_api/services/data/data_manage_permission"
  9. "eta_gn/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 && !utils.IsErrNoRow(tmpErr) {
  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. if v.EndDate != `` {
  213. endDateTime, tmpErr := utils.FormatDateStrToTime(v.EndDate)
  214. if tmpErr != nil {
  215. err = tmpErr
  216. return
  217. }
  218. edbInfo.EndDate = endDateTime
  219. }
  220. predictEdbConfList = append(predictEdbConfList, tmpPredictEdbConf)
  221. }
  222. err = data_manage.AddPredictEdb(edbInfo, calculateMappingItem, predictEdbConfList)
  223. if err != nil {
  224. errMsg = "保存失败"
  225. err = errors.New("保存失败,Err:" + err.Error())
  226. return
  227. }
  228. //新增操作日志
  229. {
  230. edbLog := new(data_manage.EdbInfoLog)
  231. edbLog.EdbInfoId = edbInfo.EdbInfoId
  232. edbLog.SourceName = edbInfo.SourceName
  233. edbLog.Source = edbInfo.Source
  234. edbLog.EdbCode = edbInfo.EdbCode
  235. edbLog.EdbName = edbInfo.EdbName
  236. edbLog.ClassifyId = edbInfo.ClassifyId
  237. edbLog.SysUserId = sysUserId
  238. edbLog.SysUserRealName = sysUserName
  239. edbLog.CreateTime = time.Now()
  240. edbLog.Content = requestBody
  241. edbLog.Status = "新增指标"
  242. edbLog.Method = requestUrl
  243. go data_manage.AddEdbInfoLog(edbLog)
  244. }
  245. //添加es
  246. AddOrEditEdbInfoToEs(edbInfo.EdbInfoId)
  247. return
  248. }
  249. // EditPredictEdbInfo 编辑预测指标
  250. func EditPredictEdbInfo(edbInfoId, classifyId int, edbName string, ruleList []request.RuleConfig, sysUserId int, sysUserName, requestBody, requestUrl string) (edbInfo *data_manage.EdbInfo, err error, errMsg string) {
  251. // 指标信息校验
  252. {
  253. edbInfo, err = data_manage.GetEdbInfoById(edbInfoId)
  254. if err != nil && !utils.IsErrNoRow(err) {
  255. errMsg = "修改失败"
  256. err = errors.New("获取预测指标失败,Err:" + err.Error())
  257. return
  258. }
  259. if edbInfo == nil {
  260. errMsg = "找不到该预测指标"
  261. err = nil
  262. return
  263. }
  264. //必须是普通的指标
  265. if edbInfo.EdbInfoType != 1 {
  266. errMsg = "指标异常,不是预测指标"
  267. return
  268. }
  269. }
  270. var predictEdbConf *data_manage.PredictEdbConf
  271. // 指标配置信息校验
  272. {
  273. // 查找该预测指标配置
  274. predictEdbConfList, tmpErr := data_manage.GetPredictEdbConfListById(edbInfo.EdbInfoId)
  275. if tmpErr != nil && !utils.IsErrNoRow(tmpErr) {
  276. errMsg = "修改失败"
  277. err = errors.New("获取预测指标配置信息失败,Err:" + tmpErr.Error())
  278. return
  279. }
  280. if len(predictEdbConfList) == 0 {
  281. errMsg = "找不到该预测指标配置"
  282. err = nil
  283. return
  284. }
  285. predictEdbConf = predictEdbConfList[0]
  286. }
  287. //判断指标名称是否存在
  288. var condition string
  289. var pars []interface{}
  290. condition += " AND edb_info_id<>? "
  291. pars = append(pars, edbInfoId)
  292. condition += " AND edb_info_type=? "
  293. pars = append(pars, 1)
  294. condition += " AND edb_name=? "
  295. pars = append(pars, edbName)
  296. count, err := data_manage.GetEdbInfoCountByCondition(condition, pars)
  297. if err != nil {
  298. errMsg = "判断指标名称是否存在失败"
  299. err = errors.New("判断指标名称是否存在失败,Err:" + err.Error())
  300. return
  301. }
  302. if count > 0 {
  303. errMsg = "指标名称已存在,请重新填写"
  304. return
  305. }
  306. edbInfo.EdbName = edbName
  307. edbInfo.EdbNameSource = edbName
  308. edbInfo.ClassifyId = classifyId
  309. edbInfo.ModifyTime = time.Now()
  310. updateEdbInfoCol := []string{"EdbName", "EdbNameSource", "ClassifyId", "EndDate", "ModifyTime"}
  311. // 预测指标配置
  312. predictEdbConfList := make([]*data_manage.PredictEdbConf, 0)
  313. for _, v := range ruleList {
  314. // 预测指标配置
  315. ruleEndDate, tmpErr := time.ParseInLocation(utils.FormatDate, v.EndDate, time.Local)
  316. if tmpErr != nil {
  317. errMsg = "规则配置的截止日期异常,请重新填写"
  318. return
  319. }
  320. switch v.RuleType {
  321. case 8: //N期段线性外推值
  322. valInt, tmpErr := strconv.Atoi(v.Value)
  323. if tmpErr != nil {
  324. errMsg = "N期段线性外推值的N值异常"
  325. return
  326. }
  327. if valInt <= 1 {
  328. errMsg = "N期段线性外推值的N值必须大于1"
  329. return
  330. }
  331. case 9: //9:动态环差
  332. }
  333. tmpPredictEdbConf := &data_manage.PredictEdbConf{
  334. PredictEdbInfoId: edbInfoId,
  335. SourceEdbInfoId: predictEdbConf.SourceEdbInfoId,
  336. RuleType: v.RuleType,
  337. //FixedValue: v.Value,
  338. Value: v.Value,
  339. EndDate: ruleEndDate,
  340. ModifyTime: time.Now(),
  341. CreateTime: time.Now(),
  342. }
  343. predictEdbConfList = append(predictEdbConfList, tmpPredictEdbConf)
  344. if v.EndDate != `` {
  345. endDateTime, tmpErr2 := utils.FormatDateStrToTime(v.EndDate)
  346. if tmpErr2 != nil {
  347. err = tmpErr2
  348. return
  349. }
  350. edbInfo.EndDate = endDateTime
  351. }
  352. }
  353. err = data_manage.EditPredictEdb(edbInfo, predictEdbConfList, updateEdbInfoCol)
  354. if err != nil {
  355. errMsg = "保存失败"
  356. err = errors.New("保存失败,Err:" + err.Error())
  357. return
  358. }
  359. //新增操作日志
  360. {
  361. edbLog := new(data_manage.EdbInfoLog)
  362. edbLog.EdbInfoId = edbInfo.EdbInfoId
  363. edbLog.SourceName = edbInfo.SourceName
  364. edbLog.Source = edbInfo.Source
  365. edbLog.EdbCode = edbInfo.EdbCode
  366. edbLog.EdbName = edbInfo.EdbName
  367. edbLog.ClassifyId = edbInfo.ClassifyId
  368. edbLog.SysUserId = sysUserId
  369. edbLog.SysUserRealName = sysUserName
  370. edbLog.CreateTime = time.Now()
  371. edbLog.Content = requestBody
  372. edbLog.Status = "编辑指标"
  373. edbLog.Method = requestUrl
  374. go data_manage.AddEdbInfoLog(edbLog)
  375. }
  376. //添加es
  377. AddOrEditEdbInfoToEs(edbInfoId)
  378. // 刷新关联指标
  379. go EdbInfoRefreshAllFromBaseV2(edbInfo.EdbInfoId, true, false)
  380. return
  381. }
  382. // RefreshPredictEdbInfo 刷新预测指标
  383. func RefreshPredictEdbInfo(edbInfoId int, refreshAll bool) (edbInfo *data_manage.EdbInfo, isAsync bool, err error, errMsg string) {
  384. // 指标信息校验
  385. {
  386. edbInfo, err = data_manage.GetEdbInfoById(edbInfoId)
  387. if err != nil && !utils.IsErrNoRow(err) {
  388. errMsg = "刷新失败"
  389. err = errors.New("获取预测指标失败,Err:" + err.Error())
  390. return
  391. }
  392. if edbInfo == nil {
  393. errMsg = "找不到该预测指标"
  394. err = nil
  395. return
  396. }
  397. //必须是预测的指标
  398. if edbInfo.EdbInfoType != 1 {
  399. errMsg = "指标异常,不是预测指标"
  400. return
  401. }
  402. }
  403. err, isAsync = EdbInfoRefreshAllFromBaseV2(edbInfo.EdbInfoId, refreshAll, false)
  404. return
  405. }
  406. // MovePredictEdbInfo 移动预测指标
  407. func MovePredictEdbInfo(edbInfoId, classifyId, prevEdbInfoId, nextEdbInfoId int, sysUser *system.Admin, requestBody, requestUrl string) (err error, errMsg string) {
  408. //判断分类是否存在
  409. count, _ := data_manage.GetEdbClassifyCountById(classifyId)
  410. if count <= 0 {
  411. errMsg = "分类已被删除,不可移动,请刷新页面"
  412. return
  413. }
  414. edbInfo, err := data_manage.GetEdbInfoById(edbInfoId)
  415. if err != nil {
  416. if err != nil && !utils.IsErrNoRow(err) {
  417. errMsg = "移动失败"
  418. err = errors.New("获取预测指标失败,Err:" + err.Error())
  419. return
  420. }
  421. if edbInfo == nil {
  422. errMsg = "找不到该预测指标"
  423. err = nil
  424. return
  425. }
  426. return
  427. }
  428. var haveOperaAuth bool
  429. // 权限校验
  430. {
  431. haveOperaAuth, err = data_manage_permission.CheckEdbPermissionByEdbInfoId(edbInfo.EdbInfoId, edbInfo.ClassifyId, edbInfo.IsJoinPermission, sysUser.AdminId)
  432. if err != nil {
  433. errMsg = "移动失败"
  434. err = errors.New("校验指标权限失败,Err:" + err.Error())
  435. return
  436. }
  437. }
  438. // 移动权限校验
  439. button := GetEdbOpButton(sysUser, edbInfo.SysUserId, edbInfo.EdbType, edbInfo.EdbInfoType, haveOperaAuth)
  440. if !button.MoveButton {
  441. errMsg = "无权限操作"
  442. err = nil
  443. return
  444. }
  445. //如果改变了分类,那么移动该指标数据
  446. if edbInfo.ClassifyId != classifyId {
  447. err = data_manage.MoveEdbInfo(edbInfoId, classifyId)
  448. if err != nil {
  449. errMsg = "移动失败"
  450. err = errors.New("移动预测指标失败,Err:" + err.Error())
  451. return
  452. }
  453. }
  454. updateCol := make([]string, 0)
  455. //如果有传入 上一个兄弟节点分类id
  456. if prevEdbInfoId > 0 {
  457. prevEdbInfo, tmpErr := data_manage.GetEdbInfoById(prevEdbInfoId)
  458. if tmpErr != nil {
  459. errMsg = "移动失败"
  460. err = errors.New("获取上一个兄弟节点分类信息失败,Err:" + tmpErr.Error())
  461. return
  462. }
  463. //如果是移动在两个兄弟节点之间
  464. if nextEdbInfoId > 0 {
  465. //下一个兄弟节点
  466. nextEdbInfo, tmpErr := data_manage.GetEdbInfoById(nextEdbInfoId)
  467. if tmpErr != nil {
  468. errMsg = "移动失败"
  469. err = errors.New("获取下一个兄弟节点分类信息失败,Err:" + tmpErr.Error())
  470. return
  471. }
  472. //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
  473. if prevEdbInfo.Sort == nextEdbInfo.Sort || prevEdbInfo.Sort == edbInfo.Sort {
  474. //变更兄弟节点的排序
  475. updateSortStr := `sort + 2`
  476. _ = data_manage.UpdateEdbInfoSortByClassifyId(prevEdbInfo.ClassifyId, prevEdbInfo.Sort, prevEdbInfo.EdbInfoId, updateSortStr)
  477. } else {
  478. //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
  479. if nextEdbInfo.Sort-prevEdbInfo.Sort == 1 {
  480. //变更兄弟节点的排序
  481. updateSortStr := `sort + 1`
  482. _ = data_manage.UpdateEdbInfoSortByClassifyId(prevEdbInfo.ClassifyId, prevEdbInfo.Sort, prevEdbInfo.EdbInfoId, updateSortStr)
  483. }
  484. }
  485. }
  486. edbInfo.Sort = prevEdbInfo.Sort + 1
  487. edbInfo.ModifyTime = time.Now()
  488. updateCol = append(updateCol, "Sort", "ModifyTime")
  489. } else {
  490. firstClassify, tmpErr := data_manage.GetFirstEdbInfoByClassifyId(classifyId)
  491. if tmpErr != nil && !utils.IsErrNoRow(tmpErr) {
  492. errMsg = "移动失败"
  493. 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())
  494. return
  495. }
  496. //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
  497. if firstClassify != nil && firstClassify.Sort == 0 {
  498. updateSortStr := ` sort + 1 `
  499. _ = data_manage.UpdateEdbInfoSortByClassifyId(firstClassify.ClassifyId, 0, firstClassify.EdbInfoId-1, updateSortStr)
  500. }
  501. edbInfo.Sort = 0 //那就是排在第一位
  502. edbInfo.ModifyTime = time.Now()
  503. updateCol = append(updateCol, "Sort", "ModifyTime")
  504. }
  505. //更新
  506. if len(updateCol) > 0 {
  507. err = edbInfo.Update(updateCol)
  508. }
  509. if err != nil {
  510. errMsg = "移动失败"
  511. err = errors.New("修改失败,Err:" + err.Error())
  512. return
  513. }
  514. //新增操作日志
  515. {
  516. edbLog := new(data_manage.EdbInfoLog)
  517. edbLog.EdbInfoId = edbInfo.EdbInfoId
  518. edbLog.SourceName = edbInfo.SourceName
  519. edbLog.Source = edbInfo.Source
  520. edbLog.EdbCode = edbInfo.EdbCode
  521. edbLog.EdbName = edbInfo.EdbName
  522. edbLog.ClassifyId = edbInfo.ClassifyId
  523. edbLog.SysUserId = sysUser.AdminId
  524. edbLog.SysUserRealName = sysUser.RealName
  525. edbLog.CreateTime = time.Now()
  526. edbLog.Content = requestBody
  527. edbLog.Status = "移动指标"
  528. edbLog.Method = requestUrl
  529. go data_manage.AddEdbInfoLog(edbLog)
  530. }
  531. return
  532. }
  533. // GetChartPredictEdbInfoDataListByConfList 获取图表的预测指标的未来数据
  534. func GetChartPredictEdbInfoDataListByConfList(predictEdbConfList []data_manage.PredictEdbConfAndData, filtrateStartDateStr, latestDateStr, endDateStr, frequency, dataDateType string, realPredictEdbInfoData []*data_manage.EdbDataList) (predictEdbInfoData []*data_manage.EdbDataList, minValue, maxValue float64, err error, errMsg string) {
  535. endDate, err := time.ParseInLocation(utils.FormatDate, endDateStr, time.Local)
  536. if err != nil {
  537. return
  538. }
  539. latestDate, err := time.ParseInLocation(utils.FormatDate, latestDateStr, time.Local)
  540. if err != nil {
  541. return
  542. }
  543. // 开始预测数据的时间
  544. startDate := latestDate
  545. // 如果有筛选时间的话
  546. if filtrateStartDateStr != `` {
  547. filtrateStartDate, tmpErr := time.ParseInLocation(utils.FormatDate, filtrateStartDateStr, time.Local)
  548. if tmpErr != nil {
  549. err = tmpErr
  550. return
  551. }
  552. //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
  553. if filtrateStartDate.After(latestDate) {
  554. startDate = filtrateStartDate.AddDate(0, 0, -1)
  555. }
  556. }
  557. //var dateArr []string
  558. // 对应日期的值
  559. existMap := make(map[string]float64)
  560. for _, v := range realPredictEdbInfoData {
  561. //dateArr = append(dateArr, v.DataTime)
  562. existMap[v.DataTime] = v.Value
  563. }
  564. predictEdbInfoData = make([]*data_manage.EdbDataList, 0)
  565. //dataValue := lastDataValue
  566. //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
  567. for _, predictEdbConf := range predictEdbConfList {
  568. dataEndTime := endDate
  569. if predictEdbConf.EndDate.Before(dataEndTime) {
  570. dataEndTime = predictEdbConf.EndDate
  571. }
  572. var tmpMinValue, tmpMaxValue float64 // 当前预测结果中的最大/最小值
  573. dayList := getPredictEdbDayList(startDate, dataEndTime, frequency, dataDateType)
  574. 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
  575. continue
  576. }
  577. switch predictEdbConf.RuleType {
  578. case 1: //1:最新
  579. var lastDataValue float64 //最新值
  580. tmpAllData := make([]*data_manage.EdbDataList, 0)
  581. tmpAllData = append(tmpAllData, realPredictEdbInfoData...)
  582. tmpAllData = append(tmpAllData, predictEdbInfoData...)
  583. lenTmpAllData := len(tmpAllData)
  584. if lenTmpAllData > 0 {
  585. lastDataValue = tmpAllData[lenTmpAllData-1].Value
  586. }
  587. predictEdbInfoData = GetChartPredictEdbInfoDataListByRule1(predictEdbConf.PredictEdbInfoId, lastDataValue, dayList, predictEdbInfoData, existMap)
  588. tmpMaxValue = lastDataValue
  589. tmpMinValue = lastDataValue
  590. case 2: //2:固定值
  591. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  592. if tmpErr != nil {
  593. err = tmpErr
  594. return
  595. }
  596. dataValue, _ := tmpValDecimal.Float64()
  597. predictEdbInfoData = GetChartPredictEdbInfoDataListByRule1(predictEdbConf.PredictEdbInfoId, dataValue, dayList, predictEdbInfoData, existMap)
  598. tmpMaxValue = dataValue
  599. tmpMinValue = dataValue
  600. case 3: //3:同比
  601. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  602. if tmpErr != nil {
  603. err = tmpErr
  604. return
  605. }
  606. tbValue, _ := tmpValDecimal.Float64()
  607. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleTb(predictEdbConf.PredictEdbInfoId, tbValue, dayList, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  608. case 4: //4:同差
  609. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  610. if tmpErr != nil {
  611. err = tmpErr
  612. return
  613. }
  614. tcValue, _ := tmpValDecimal.Float64()
  615. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleTc(predictEdbConf.PredictEdbInfoId, tcValue, dayList, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  616. case 5: //5:环比
  617. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  618. if tmpErr != nil {
  619. err = tmpErr
  620. return
  621. }
  622. hbValue, _ := tmpValDecimal.Float64()
  623. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleHb(predictEdbConf.PredictEdbInfoId, hbValue, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  624. case 6: //6:环差
  625. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  626. if tmpErr != nil {
  627. err = tmpErr
  628. return
  629. }
  630. hcValue, _ := tmpValDecimal.Float64()
  631. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleHc(predictEdbConf.PredictEdbInfoId, hcValue, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  632. case 7: //7:N期移动均值
  633. nValue, tmpErr := strconv.Atoi(predictEdbConf.Value)
  634. if tmpErr != nil {
  635. err = tmpErr
  636. return
  637. }
  638. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleNMoveMeanValue(predictEdbConf.PredictEdbInfoId, nValue, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  639. case 8: //8:N期段线性外推值
  640. nValue, tmpErr := strconv.Atoi(predictEdbConf.Value)
  641. if tmpErr != nil {
  642. err = tmpErr
  643. return
  644. }
  645. if nValue <= 1 {
  646. errMsg = `N期段线性外推值的N值必须大于1`
  647. err = errors.New(errMsg)
  648. return
  649. }
  650. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleNLinearRegression(predictEdbConf.PredictEdbInfoId, nValue, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  651. if err != nil {
  652. return
  653. }
  654. case 9: //9:动态环差”预测规则;
  655. //规则计算的环差值map
  656. hcDataMap := make(map[string]float64)
  657. if predictEdbConf.PredictEdbInfoId > 0 { //已经生成的动态数据
  658. tmpPredictEdbRuleDataList, tmpErr := data_manage.GetPredictEdbRuleDataList(predictEdbConf.PredictEdbInfoId, predictEdbConf.ConfigId, startDate.Format(utils.FormatDate), endDate.Format(utils.FormatDate))
  659. if tmpErr != nil {
  660. err = tmpErr
  661. return
  662. }
  663. for _, v := range tmpPredictEdbRuleDataList {
  664. hcDataMap[v.DataTime] = v.Value
  665. }
  666. } else { //未生成的动态数据,需要使用外部传入的数据进行计算
  667. if len(predictEdbConf.DataList) <= 0 {
  668. return
  669. }
  670. for _, v := range predictEdbConf.DataList {
  671. currentDate, tmpErr := time.ParseInLocation(utils.FormatDate, v.DataTime, time.Local)
  672. if tmpErr != nil {
  673. continue
  674. }
  675. // 只处理时间段内的数据
  676. if currentDate.Before(startDate) || currentDate.After(endDate) {
  677. continue
  678. }
  679. hcDataMap[v.DataTime] = v.Value
  680. }
  681. }
  682. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleTrendsHC(predictEdbConf.PredictEdbInfoId, dayList, realPredictEdbInfoData, predictEdbInfoData, hcDataMap, existMap)
  683. case 10: //10:根据 给定终值后插值 规则获取预测数据
  684. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  685. if tmpErr != nil {
  686. err = tmpErr
  687. return
  688. }
  689. finalValue, _ := tmpValDecimal.Float64()
  690. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleFinalValueHc(predictEdbConf.PredictEdbInfoId, finalValue, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  691. case 11: //11:根据 季节性 规则获取预测数据
  692. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleSeason(predictEdbConf.PredictEdbInfoId, predictEdbConf.Value, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  693. if err != nil {
  694. return
  695. }
  696. case 12: //12:根据 移动平均同比 规则获取预测数据
  697. var moveAverageConf MoveAverageConf
  698. tmpErr := json.Unmarshal([]byte(predictEdbConf.Value), &moveAverageConf)
  699. if tmpErr != nil {
  700. err = errors.New("季节性配置信息异常:" + tmpErr.Error())
  701. return
  702. }
  703. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleMoveAverageTb(predictEdbConf.PredictEdbInfoId, moveAverageConf.NValue, moveAverageConf.Year, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  704. if err != nil {
  705. return
  706. }
  707. case 13: //13:根据 同比增速差值 规则获取预测数据
  708. tmpValDecimal, tmpErr := decimal.NewFromString(predictEdbConf.Value)
  709. if tmpErr != nil {
  710. err = tmpErr
  711. return
  712. }
  713. tbEndValue, _ := tmpValDecimal.Float64()
  714. predictEdbInfoData, tmpMinValue, tmpMaxValue = GetChartPredictEdbInfoDataListByRuleTbzscz(predictEdbConf.PredictEdbInfoId, tbEndValue, dayList, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  715. case 14: //14:根据 一元线性拟合 规则获取预测数据
  716. var ruleConf RuleLineNhConf
  717. err = json.Unmarshal([]byte(predictEdbConf.Value), &ruleConf)
  718. if err != nil {
  719. err = errors.New("一元线性拟合配置信息异常:" + err.Error())
  720. return
  721. }
  722. // 规则计算的拟合残差值map
  723. newNhccDataMap := make(map[string]float64)
  724. if predictEdbConf.PredictEdbInfoId > 0 { //已经生成的动态数据
  725. tmpPredictEdbRuleDataList, tmpErr := data_manage.GetPredictEdbRuleDataList(predictEdbConf.PredictEdbInfoId, predictEdbConf.ConfigId, "", "")
  726. if tmpErr != nil {
  727. err = tmpErr
  728. return
  729. }
  730. for _, v := range tmpPredictEdbRuleDataList {
  731. newNhccDataMap[v.DataTime] = v.Value
  732. }
  733. } else { //未生成的动态数据,需要使用外部传入的数据进行计算
  734. newNhccDataMap, err = getCalculateNhccData(append(realPredictEdbInfoData, predictEdbInfoData...), ruleConf)
  735. if err != nil {
  736. return
  737. }
  738. }
  739. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleLineNh(predictEdbConf.PredictEdbInfoId, dayList, realPredictEdbInfoData, predictEdbInfoData, newNhccDataMap, existMap)
  740. if err != nil {
  741. return
  742. }
  743. 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;
  744. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleNAnnualAverage(predictEdbConf.PredictEdbInfoId, predictEdbConf.Value, dayList, realPredictEdbInfoData, predictEdbInfoData, existMap)
  745. if err != nil {
  746. return
  747. }
  748. case 16: //16:年度值倒推
  749. predictEdbInfoData, tmpMinValue, tmpMaxValue, err = GetChartPredictEdbInfoDataListByRuleAnnualValueInversion(predictEdbConf.PredictEdbInfoId, predictEdbConf.Value, dayList, frequency, realPredictEdbInfoData, predictEdbInfoData, existMap)
  750. if err != nil {
  751. return
  752. }
  753. }
  754. // 下一个规则的开始日期
  755. {
  756. lenPredictEdbInfoData := len(predictEdbInfoData)
  757. if lenPredictEdbInfoData > 0 {
  758. tmpDataEndTime, _ := time.ParseInLocation(utils.FormatDate, predictEdbInfoData[lenPredictEdbInfoData-1].DataTime, time.Local)
  759. if startDate.Before(tmpDataEndTime) {
  760. startDate = tmpDataEndTime
  761. }
  762. }
  763. }
  764. if tmpMinValue < minValue {
  765. minValue = tmpMinValue
  766. }
  767. if tmpMaxValue > maxValue {
  768. maxValue = tmpMaxValue
  769. }
  770. }
  771. return
  772. }
  773. // GetPredictEdbDayList 获取预测指标日期列表
  774. func getPredictEdbDayList(startDate, endDate time.Time, frequency, dataDateType string) (dayList []time.Time) {
  775. //if !utils.InArrayByStr([]string{"日度", "周度", "月度"}, frequency)
  776. if dataDateType == `` {
  777. dataDateType = `交易日`
  778. }
  779. switch frequency {
  780. case "日度":
  781. for currDate := startDate.AddDate(0, 0, 1); currDate.Before(endDate) || currDate.Equal(endDate); currDate = currDate.AddDate(0, 0, 1) {
  782. // 如果日期类型是交易日的时候,那么需要将周六、日排除
  783. if dataDateType == `交易日` && (currDate.Weekday() == time.Sunday || currDate.Weekday() == time.Saturday) {
  784. continue
  785. }
  786. dayList = append(dayList, currDate)
  787. }
  788. case "周度":
  789. //nextDate := startDate.AddDate(0, 0, 7)
  790. for currDate := startDate.AddDate(0, 0, 7); currDate.Before(endDate) || currDate.Equal(endDate); currDate = currDate.AddDate(0, 0, 7) {
  791. dayList = append(dayList, currDate)
  792. }
  793. case "旬度":
  794. for currDate := startDate.AddDate(0, 0, 1); currDate.Before(endDate) || currDate.Equal(endDate); {
  795. nextDate := currDate.AddDate(0, 0, 1)
  796. //每个月的10号、20号、最后一天,那么就写入
  797. if nextDate.Day() == 11 || nextDate.Day() == 21 || nextDate.Day() == 1 {
  798. dayList = append(dayList, currDate)
  799. }
  800. currDate = nextDate
  801. }
  802. case "月度":
  803. for currDate := startDate; currDate.Before(endDate) || currDate.Equal(endDate); {
  804. currDate = time.Date(currDate.Year(), currDate.Month(), 1, 0, 0, 0, 0, time.Now().Location()).AddDate(0, 1, -1)
  805. if !currDate.After(endDate) && !currDate.Equal(startDate) {
  806. dayList = append(dayList, currDate)
  807. }
  808. currDate = currDate.AddDate(0, 0, 1)
  809. }
  810. case "季度":
  811. for currDate := startDate; currDate.Before(endDate) || currDate.Equal(endDate); {
  812. // 每月的最后一天
  813. currDate = time.Date(currDate.Year(), currDate.Month(), 1, 0, 0, 0, 0, time.Now().Location()).AddDate(0, 1, -1)
  814. if !currDate.After(endDate) && !currDate.Equal(startDate) {
  815. // 季度日期就写入,否则不写入
  816. if currDate.Month() == 3 || currDate.Month() == 6 || currDate.Month() == 9 || currDate.Month() == 12 {
  817. dayList = append(dayList, currDate)
  818. }
  819. }
  820. currDate = currDate.AddDate(0, 0, 1)
  821. }
  822. case "半年度":
  823. for currDate := startDate; currDate.Before(endDate) || currDate.Equal(endDate); {
  824. // 每月的最后一天
  825. currDate = time.Date(currDate.Year(), currDate.Month(), 1, 0, 0, 0, 0, time.Now().Location()).AddDate(0, 1, -1)
  826. if !currDate.After(endDate) && !currDate.Equal(startDate) {
  827. // 半年度日期就写入,否则不写入
  828. if currDate.Month() == 6 || currDate.Month() == 12 {
  829. dayList = append(dayList, currDate)
  830. }
  831. }
  832. currDate = currDate.AddDate(0, 0, 1)
  833. }
  834. case "年度":
  835. for currDate := startDate; currDate.Before(endDate) || currDate.Equal(endDate); {
  836. currDate = time.Date(currDate.Year()+1, 12, 31, 0, 0, 0, 0, time.Now().Location())
  837. if !currDate.After(endDate) && !currDate.Equal(startDate) {
  838. dayList = append(dayList, currDate)
  839. }
  840. }
  841. }
  842. return
  843. }
  844. // GetPredictDataListByPredictEdbInfoId 根据预测指标id获取预测指标的数据(日期正序返回)
  845. 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) {
  846. edbInfo, err = data_manage.GetEdbInfoById(edbInfoId)
  847. if err != nil {
  848. errMsg = `获取预测指标信息失败`
  849. return
  850. }
  851. dataList, sourceEdbInfoItem, predictEdbConf, err, errMsg = GetPredictDataListByPredictEdbInfo(edbInfo, startDate, endDate, isTimeBetween)
  852. return
  853. }
  854. // GetPredictDataListByPredictEdbInfo 根据预测指标信息获取预测指标的数据
  855. 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) {
  856. // 非计算指标,直接从表里获取数据
  857. if edbInfo.EdbType != 1 {
  858. if !isTimeBetween { //如果不是区间数据,那么就结束日期为空
  859. endDate = ``
  860. }
  861. return GetPredictCalculateDataListByPredictEdbInfo(edbInfo, startDate, endDate)
  862. }
  863. // 查找该预测指标配置
  864. predictEdbConfList, err := data_manage.GetPredictEdbConfListById(edbInfo.EdbInfoId)
  865. if err != nil && !utils.IsErrNoRow(err) {
  866. errMsg = "获取预测指标配置信息失败"
  867. return
  868. }
  869. if len(predictEdbConfList) == 0 {
  870. errMsg = "获取预测指标配置信息失败"
  871. err = errors.New(errMsg)
  872. return
  873. }
  874. predictEdbConf = predictEdbConfList[0]
  875. // 来源指标
  876. sourceEdbInfoItem, err = data_manage.GetEdbInfoById(predictEdbConf.SourceEdbInfoId)
  877. if err != nil {
  878. if utils.IsErrNoRow(err) {
  879. errMsg = "找不到来源指标信息"
  880. err = errors.New(errMsg)
  881. }
  882. return
  883. }
  884. allDataList := make([]*data_manage.EdbDataList, 0)
  885. //获取指标数据(实际已生成)
  886. dataList, err = data_manage.GetEdbDataList(sourceEdbInfoItem.Source, sourceEdbInfoItem.SubSource, sourceEdbInfoItem.EdbInfoId, startDate, endDate)
  887. if err != nil {
  888. return
  889. }
  890. // 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
  891. if startDate != `` {
  892. allDataList, err = data_manage.GetEdbDataList(sourceEdbInfoItem.Source, sourceEdbInfoItem.SubSource, sourceEdbInfoItem.EdbInfoId, "", "")
  893. if err != nil {
  894. return
  895. }
  896. } else {
  897. allDataList = dataList
  898. }
  899. // 获取预测指标未来的数据
  900. predictDataList := make([]*data_manage.EdbDataList, 0)
  901. endDateStr := utils.TimeToFormatDate(edbInfo.EndDate) //预测指标的结束日期
  902. if isTimeBetween && endDate != `` { //如果是时间区间,同时截止日期不为空的情况,那么
  903. reqEndDateTime, _ := time.ParseInLocation(utils.FormatDate, endDate, time.Local)
  904. endDateTime := edbInfo.EndDate
  905. // 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
  906. if reqEndDateTime.Before(endDateTime) {
  907. endDateStr = endDate
  908. }
  909. }
  910. //predictDataList, err = GetChartPredictEdbInfoDataList(*predictEdbConf, startDate, sourceEdbInfoItem.LatestDate, sourceEdbInfoItem.LatestValue, endDateStr, edbInfo.Frequency)
  911. predictEdbConfDataList := make([]data_manage.PredictEdbConfAndData, 0)
  912. for _, v := range predictEdbConfList {
  913. predictEdbConfDataList = append(predictEdbConfDataList, data_manage.PredictEdbConfAndData{
  914. ConfigId: v.ConfigId,
  915. PredictEdbInfoId: v.PredictEdbInfoId,
  916. SourceEdbInfoId: v.SourceEdbInfoId,
  917. RuleType: v.RuleType,
  918. FixedValue: v.FixedValue,
  919. Value: v.Value,
  920. EndDate: v.EndDate,
  921. ModifyTime: v.ModifyTime,
  922. CreateTime: v.CreateTime,
  923. DataList: make([]*data_manage.EdbDataList, 0),
  924. })
  925. }
  926. //var predictMinValue, predictMaxValue float64
  927. predictDataList, _, _, err, _ = GetChartPredictEdbInfoDataListByConfList(predictEdbConfDataList, startDate, sourceEdbInfoItem.LatestDate, endDateStr, edbInfo.Frequency, edbInfo.DataDateType, allDataList)
  928. if err != nil {
  929. return
  930. }
  931. dataList = append(dataList, predictDataList...)
  932. //if len(predictDataList) > 0 {
  933. // // 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
  934. // if edbInfo.MinValue > predictMinValue {
  935. // edbInfo.MinValue = predictMinValue
  936. // }
  937. //
  938. // // 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
  939. // if edbInfo.MaxValue < predictMaxValue {
  940. // edbInfo.MaxValue = predictMaxValue
  941. // }
  942. //}
  943. return
  944. }
  945. // GetChartDataList 通过完整的预测数据 进行 季节性图、公历、农历处理
  946. func GetChartDataList(dataList []*data_manage.EdbDataList, chartType int, calendar, latestDateStr, startDate string) (resultDataList interface{}, err error) {
  947. startDateReal := startDate
  948. calendarPreYear := 0
  949. if calendar == "农历" {
  950. newStartDateReal, err := time.Parse(utils.FormatDate, startDateReal)
  951. if err != nil {
  952. fmt.Println("time.Parse:" + err.Error())
  953. }
  954. calendarPreYear = newStartDateReal.Year() - 1
  955. newStartDateReal = newStartDateReal.AddDate(-1, 0, 0)
  956. startDateReal = newStartDateReal.Format(utils.FormatDate)
  957. }
  958. //实际数据的截止日期
  959. latestDate, tmpErr := time.Parse(utils.FormatDate, latestDateStr)
  960. if tmpErr != nil {
  961. err = errors.New(fmt.Sprint("获取最后实际数据的日期失败,Err:" + tmpErr.Error() + ";LatestDate:" + latestDateStr))
  962. return
  963. }
  964. latestDateYear := latestDate.Year() //实际数据截止年份
  965. // 曲线图
  966. if chartType == 1 {
  967. resultDataList = dataList
  968. return
  969. }
  970. if calendar == "农历" {
  971. if len(dataList) <= 0 {
  972. resultDataList = data_manage.EdbDataResult{}
  973. } else {
  974. result, tmpErr := data_manage.AddCalculateQuarterV4(dataList)
  975. if tmpErr != nil {
  976. err = errors.New("获取农历数据失败,Err:" + tmpErr.Error())
  977. return
  978. }
  979. // 处理季节图的截止日期
  980. for k, edbDataItems := range result.List {
  981. var cuttingDataTimestamp int64
  982. // 切割的日期时间字符串
  983. cuttingDataTimeStr := latestDate.AddDate(0, 0, edbDataItems.BetweenDay).Format(utils.FormatDate)
  984. //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
  985. if edbDataItems.Year >= latestDateYear {
  986. for _, tmpData := range edbDataItems.Items {
  987. if tmpData.DataTime == cuttingDataTimeStr {
  988. cuttingDataTimestamp = tmpData.DataTimestamp
  989. break
  990. }
  991. }
  992. }
  993. edbDataItems.CuttingDataTimestamp = cuttingDataTimestamp
  994. result.List[k] = edbDataItems
  995. }
  996. if result.List[0].Year != calendarPreYear {
  997. itemList := make([]*data_manage.EdbDataList, 0)
  998. items := new(data_manage.EdbDataItems)
  999. //items.Year = calendarPreYear
  1000. items.Items = itemList
  1001. newResult := new(data_manage.EdbDataResult)
  1002. newResult.List = append(newResult.List, items)
  1003. newResult.List = append(newResult.List, result.List...)
  1004. resultDataList = newResult
  1005. } else {
  1006. resultDataList = result
  1007. }
  1008. }
  1009. } else {
  1010. currentYear := time.Now().Year()
  1011. quarterDataList := make([]*data_manage.QuarterData, 0)
  1012. quarterMap := make(map[int][]*data_manage.EdbDataList)
  1013. var quarterArr []int
  1014. for _, v := range dataList {
  1015. itemDate, tmpErr := time.Parse(utils.FormatDate, v.DataTime)
  1016. if tmpErr != nil {
  1017. err = errors.New("季度指标日期转换,Err:" + tmpErr.Error() + ";DataTime:" + v.DataTime)
  1018. return
  1019. }
  1020. year := itemDate.Year()
  1021. newItemDate := itemDate.AddDate(currentYear-year, 0, 0)
  1022. timestamp := newItemDate.UnixNano() / 1e6
  1023. v.DataTimestamp = timestamp
  1024. if findVal, ok := quarterMap[year]; !ok {
  1025. quarterArr = append(quarterArr, year)
  1026. findVal = append(findVal, v)
  1027. quarterMap[year] = findVal
  1028. } else {
  1029. findVal = append(findVal, v)
  1030. quarterMap[year] = findVal
  1031. }
  1032. }
  1033. for _, v := range quarterArr {
  1034. itemList := quarterMap[v]
  1035. quarterItem := new(data_manage.QuarterData)
  1036. quarterItem.Year = v
  1037. quarterItem.DataList = itemList
  1038. //如果等于最后的实际日期,那么将切割时间戳记录
  1039. if v == latestDateYear {
  1040. var cuttingDataTimestamp int64
  1041. for _, tmpData := range itemList {
  1042. if tmpData.DataTime == latestDateStr {
  1043. cuttingDataTimestamp = tmpData.DataTimestamp
  1044. break
  1045. }
  1046. }
  1047. quarterItem.CuttingDataTimestamp = cuttingDataTimestamp
  1048. } else if v > latestDateYear {
  1049. //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
  1050. if len(itemList) > 0 {
  1051. quarterItem.CuttingDataTimestamp = itemList[0].DataTimestamp - 100
  1052. }
  1053. }
  1054. quarterDataList = append(quarterDataList, quarterItem)
  1055. }
  1056. resultDataList = quarterDataList
  1057. }
  1058. return
  1059. }
  1060. // GetPredictCalculateDataListByPredictEdbInfo 根据预测运算指标信息获取预测指标的数据
  1061. 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) {
  1062. dataList, err = data_manage.GetEdbDataList(edbInfo.Source, edbInfo.SubSource, edbInfo.EdbInfoId, startDate, endDate)
  1063. return
  1064. }
  1065. // ModifyPredictEdbBaseInfoBySourceEdb 根据来源ETA指标修改预测指标的基础信息
  1066. func ModifyPredictEdbBaseInfoBySourceEdb(sourceEDdbInfo *data_manage.EdbInfo, frequency, unit string) {
  1067. list, err := data_manage.GetGroupPredictEdbBySourceEdbInfoId(sourceEDdbInfo.EdbInfoId)
  1068. if err != nil {
  1069. return
  1070. }
  1071. for _, v := range list {
  1072. v.Frequency = frequency
  1073. v.Unit = unit
  1074. v.Update([]string{"Frequency", "Unit"})
  1075. AddOrEditEdbInfoToEs(v.EdbInfoId)
  1076. }
  1077. }
  1078. // ModifyPredictEdbEnBaseInfoBySourceEdb 根据来源ETA指标修改预测指标的英文基础信息
  1079. func ModifyPredictEdbEnBaseInfoBySourceEdb(sourceEDdbInfo *data_manage.EdbInfo, unitEn string) {
  1080. list, err := data_manage.GetGroupPredictEdbBySourceEdbInfoId(sourceEDdbInfo.EdbInfoId)
  1081. if err != nil {
  1082. return
  1083. }
  1084. for _, v := range list {
  1085. v.UnitEn = unitEn
  1086. v.Update([]string{"UnitEn"})
  1087. AddOrEditEdbInfoToEs(v.EdbInfoId)
  1088. }
  1089. }
  1090. // ModifyPredictEdbUnitBySourceEdbInfoId
  1091. // @Description: 根据来源ETA指标修改预测指标的频度和单位基础信息
  1092. // @author: Roc
  1093. // @datetime 2024-01-05 11:07:39
  1094. // @param sourceEdbInfoId int
  1095. // @param frequency string
  1096. // @param unit string
  1097. // @return err error
  1098. func ModifyPredictEdbUnitBySourceEdbInfoId(sourceEdbInfoId int, frequency, unit string) (err error) {
  1099. list, err := data_manage.GetGroupPredictEdbBySourceEdbInfoId(sourceEdbInfoId)
  1100. if err != nil {
  1101. return
  1102. }
  1103. for _, v := range list {
  1104. v.Frequency = frequency
  1105. v.Unit = unit
  1106. v.Update([]string{"Frequency", "Unit"})
  1107. AddOrEditEdbInfoToEs(v.EdbInfoId)
  1108. }
  1109. return
  1110. }