predict_edb.go 44 KB

1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374757677787980818283848586878889909192939495969798991001011021031041051061071081091101111121131141151161171181191201211221231241251261271281291301311321331341351361371381391401411421431441451461471481491501511521531541551561571581591601611621631641651661671681691701711721731741751761771781791801811821831841851861871881891901911921931941951961971981992002012022032042052062072082092102112122132142152162172182192202212222232242252262272282292302312322332342352362372382392402412422432442452462472482492502512522532542552562572582592602612622632642652662672682692702712722732742752762772782792802812822832842852862872882892902912922932942952962972982993003013023033043053063073083093103113123133143153163173183193203213223233243253263273283293303313323333343353363373383393403413423433443453463473483493503513523533543553563573583593603613623633643653663673683693703713723733743753763773783793803813823833843853863873883893903913923933943953963973983994004014024034044054064074084094104114124134144154164174184194204214224234244254264274284294304314324334344354364374384394404414424434444454464474484494504514524534544554564574584594604614624634644654664674684694704714724734744754764774784794804814824834844854864874884894904914924934944954964974984995005015025035045055065075085095105115125135145155165175185195205215225235245255265275285295305315325335345355365375385395405415425435445455465475485495505515525535545555565575585595605615625635645655665675685695705715725735745755765775785795805815825835845855865875885895905915925935945955965975985996006016026036046056066076086096106116126136146156166176186196206216226236246256266276286296306316326336346356366376386396406416426436446456466476486496506516526536546556566576586596606616626636646656666676686696706716726736746756766776786796806816826836846856866876886896906916926936946956966976986997007017027037047057067077087097107117127137147157167177187197207217227237247257267277287297307317327337347357367377387397407417427437447457467477487497507517527537547557567577587597607617627637647657667677687697707717727737747757767777787797807817827837847857867877887897907917927937947957967977987998008018028038048058068078088098108118128138148158168178188198208218228238248258268278288298308318328338348358368378388398408418428438448458468478488498508518528538548558568578588598608618628638648658668678688698708718728738748758768778788798808818828838848858868878888898908918928938948958968978988999009019029039049059069079089099109119129139149159169179189199209219229239249259269279289299309319329339349359369379389399409419429439449459469479489499509519529539549559569579589599609619629639649659669679689699709719729739749759769779789799809819829839849859869879889899909919929939949959969979989991000100110021003100410051006100710081009101010111012101310141015101610171018101910201021102210231024102510261027102810291030103110321033103410351036103710381039104010411042104310441045104610471048104910501051105210531054105510561057105810591060106110621063106410651066106710681069107010711072107310741075107610771078107910801081108210831084108510861087108810891090109110921093109410951096109710981099110011011102110311041105110611071108110911101111111211131114111511161117111811191120112111221123112411251126112711281129113011311132113311341135113611371138113911401141114211431144114511461147114811491150115111521153115411551156115711581159116011611162116311641165116611671168116911701171117211731174117511761177117811791180118111821183118411851186118711881189119011911192119311941195119611971198119912001201120212031204120512061207120812091210121112121213121412151216121712181219122012211222122312241225122612271228122912301231123212331234123512361237123812391240124112421243124412451246124712481249125012511252125312541255125612571258125912601261126212631264126512661267126812691270127112721273127412751276127712781279128012811282128312841285128612871288128912901291129212931294129512961297129812991300130113021303130413051306130713081309131013111312131313141315131613171318131913201321132213231324132513261327132813291330133113321333133413351336133713381339134013411342134313441345134613471348134913501351135213531354135513561357135813591360136113621363136413651366136713681369137013711372
  1. package logic
  2. import (
  3. "errors"
  4. "eta/eta_index_lib/models"
  5. "eta/eta_index_lib/utils"
  6. "fmt"
  7. "strconv"
  8. "strings"
  9. "time"
  10. )
  11. // AddPredictEdbInfo 新增预测指标
  12. func AddPredictEdbInfo(sourceEdbInfoId, classifyId int, edbName, dataDateType string, endDateType int, ruleList []models.RuleConfig, minValue, maxValue float64, sysUserId int, sysUserName, lang string) (edbInfo *models.EdbInfo, err error, errMsg string) {
  13. var sourceEdbInfo *models.EdbInfo
  14. // 来源指标信息校验
  15. {
  16. sourceEdbInfo, err = models.GetEdbInfoById(sourceEdbInfoId)
  17. if err != nil && !utils.IsErrNoRow(err) {
  18. errMsg = "新增失败"
  19. err = errors.New("获取来源指标失败,Err:" + err.Error())
  20. return
  21. }
  22. if sourceEdbInfo == nil {
  23. errMsg = "找不到该来源指标"
  24. err = errors.New(errMsg)
  25. return
  26. }
  27. //必须是普通的指标
  28. if sourceEdbInfo.EdbInfoType != 0 {
  29. errMsg = "来源指标异常,不是普通的指标"
  30. err = errors.New(errMsg)
  31. return
  32. }
  33. //if !utils.InArrayByStr([]string{"日度", "周度", "月度", "年度"}, sourceEdbInfo.Frequency) {
  34. // errMsg = "预测指标只支持选择日度、周度、月度、年度的指标"
  35. // err = errors.New(errMsg)
  36. // return
  37. //}
  38. }
  39. var classifyInfo *models.EdbClassify
  40. // 来源分类信息校验
  41. {
  42. classifyInfo, err = models.GetEdbClassifyById(classifyId)
  43. if err != nil && !utils.IsErrNoRow(err) {
  44. errMsg = "新增失败"
  45. err = errors.New("获取预测指标分类失败,Err:" + err.Error())
  46. return
  47. }
  48. if classifyInfo == nil {
  49. errMsg = "找不到该预测指标分类"
  50. err = errors.New(errMsg)
  51. return
  52. }
  53. //必须是预测指标分类
  54. if classifyInfo.ClassifyType != 1 {
  55. errMsg = "预测指标分类异常,不是预测指标分类"
  56. err = errors.New(errMsg)
  57. return
  58. }
  59. }
  60. edbName = strings.Trim(edbName, " ")
  61. edbCode := sourceEdbInfo.EdbCode + "_" + time.Now().Format(utils.FormatShortDateTimeUnSpace)
  62. // 根据指标名称和指标ID校验库中是否还存在其他同名指标
  63. existEdbName, err := CheckExistByEdbNameAndEdbInfoId(utils.PREDICT_EDB_INFO_TYPE, 0, edbName, lang)
  64. if err != nil {
  65. errMsg = "判断指标名称是否存在失败"
  66. err = errors.New("判断指标名称是否存在失败,Err:" + err.Error())
  67. return
  68. }
  69. if existEdbName {
  70. errMsg = "指标名称已存在,请重新填写"
  71. err = errors.New(errMsg)
  72. return
  73. }
  74. timestamp := strconv.FormatInt(time.Now().UnixNano(), 10)
  75. if dataDateType == `` {
  76. dataDateType = `自然日`
  77. }
  78. edbInfo = &models.EdbInfo{
  79. //EdbInfoId: 0,
  80. EdbInfoType: 1,
  81. SourceName: "预测指标",
  82. Source: utils.DATA_SOURCE_PREDICT,
  83. EdbCode: edbCode,
  84. EdbName: edbName,
  85. EdbNameSource: edbName,
  86. Frequency: sourceEdbInfo.Frequency,
  87. Unit: sourceEdbInfo.Unit,
  88. StartDate: sourceEdbInfo.StartDate,
  89. ClassifyId: classifyId,
  90. SysUserId: sysUserId,
  91. SysUserRealName: sysUserName,
  92. UniqueCode: utils.MD5(utils.DATA_PREFIX + "_" + timestamp),
  93. CreateTime: time.Now(),
  94. ModifyTime: time.Now(),
  95. MinValue: minValue,
  96. MaxValue: maxValue,
  97. CalculateFormula: sourceEdbInfo.CalculateFormula,
  98. EdbType: 1,
  99. //Sort: sourceEdbInfo.,
  100. LatestDate: sourceEdbInfo.LatestDate,
  101. LatestValue: sourceEdbInfo.LatestValue,
  102. MoveType: sourceEdbInfo.MoveType,
  103. MoveFrequency: sourceEdbInfo.MoveFrequency,
  104. NoUpdate: sourceEdbInfo.NoUpdate,
  105. ServerUrl: "",
  106. EdbNameEn: edbName,
  107. UnitEn: sourceEdbInfo.UnitEn,
  108. DataDateType: dataDateType,
  109. Sort: models.GetAddEdbMaxSortByClassifyId(classifyId, utils.PREDICT_EDB_INFO_TYPE),
  110. EndDateType: endDateType,
  111. }
  112. // 关联关系表
  113. calculateMappingList := make([]*models.EdbInfoCalculateMapping, 0)
  114. fromEdbMap := make(map[int]int)
  115. // 源指标关联关系表
  116. calculateMappingItem := &models.EdbInfoCalculateMapping{
  117. //EdbInfoCalculateMappingId: 0,
  118. //EdbInfoId: 0,
  119. Source: edbInfo.Source,
  120. SourceName: edbInfo.SourceName,
  121. EdbCode: edbInfo.EdbCode,
  122. FromEdbInfoId: sourceEdbInfo.EdbInfoId,
  123. FromEdbCode: sourceEdbInfo.EdbCode,
  124. FromEdbName: sourceEdbInfo.EdbName,
  125. FromSource: sourceEdbInfo.Source,
  126. FromSourceName: sourceEdbInfo.SourceName,
  127. //FromTag: "",
  128. Sort: 1,
  129. CreateTime: time.Now(),
  130. ModifyTime: time.Now(),
  131. }
  132. fromEdbMap[sourceEdbInfoId] = sourceEdbInfoId
  133. calculateMappingList = append(calculateMappingList, calculateMappingItem)
  134. // 动态环差 计算列表
  135. calculateRuleMap := make(map[int]models.CalculateRule, 0)
  136. // 预测指标配置
  137. predictEdbConfList := make([]*models.PredictEdbConf, 0)
  138. var ruleEndDate time.Time
  139. for ruleIndex, v := range ruleList {
  140. if endDateType == 0 {
  141. // 预测指标配置
  142. ruleEndDate, err = time.ParseInLocation(utils.FormatDate, v.EndDate, time.Local)
  143. if err != nil {
  144. errMsg = "规则配置的截止日期异常,请重新填写"
  145. err = errors.New(errMsg)
  146. return
  147. }
  148. } else {
  149. if v.EndNum <= 0 {
  150. errMsg = "截止期数不正确,请输入大于等于1的整数"
  151. err = errors.New(errMsg)
  152. return
  153. }
  154. }
  155. //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,9:动态环差,10:根据 给定终值后插值 规则获取预测数据,11:根据 季节性 规则获取预测数据,12:根据 移动平均同比 规则获取预测数据
  156. // 环比、环差、动态环差、季节性、移动平均同比不支持年度
  157. if sourceEdbInfo.Frequency == "年度" && utils.InArrayByInt([]int{5, 6, 11, 12}, v.RuleType) {
  158. errMsg = "环比、环差、动态环差、季节性、移动平均同比不支持年度指标"
  159. err = errors.New(errMsg)
  160. return
  161. }
  162. if v.RuleType == 16 && endDateType == 1 {
  163. errMsg = "年度值倒推不支持截止期数"
  164. err = errors.New(errMsg)
  165. return
  166. }
  167. switch v.RuleType {
  168. case 8: //N期段线性外推值
  169. valInt, tmpErr := strconv.Atoi(v.Value)
  170. if tmpErr != nil {
  171. errMsg = "N期段线性外推值的N值异常"
  172. err = errors.New(errMsg)
  173. return
  174. }
  175. if valInt <= 1 {
  176. errMsg = "N期段线性外推值的N值必须大于1"
  177. err = errors.New(errMsg)
  178. return
  179. }
  180. case 9: //9:动态环差
  181. if v.Value == "" {
  182. errMsg = "请填写计算规则"
  183. err = errors.New(errMsg)
  184. return
  185. }
  186. formula := v.Value
  187. formula = strings.Replace(formula, "(", "(", -1)
  188. formula = strings.Replace(formula, ")", ")", -1)
  189. formula = strings.Replace(formula, ",", ",", -1)
  190. formula = strings.Replace(formula, "。", ".", -1)
  191. formula = strings.Replace(formula, "%", "*0.01", -1)
  192. v.Value = formula
  193. //检验公式
  194. var formulaStr string
  195. var edbInfoIdBytes []string
  196. for _, tmpEdbInfoId := range v.EdbInfoIdArr {
  197. formulaStr += tmpEdbInfoId.FromTag + ","
  198. edbInfoIdBytes = append(edbInfoIdBytes, tmpEdbInfoId.FromTag)
  199. }
  200. formulaSlice, tErr := utils.CheckFormulaJson(formula)
  201. if tErr != nil {
  202. errMsg = "公式格式错误,请重新填写"
  203. err = errors.New(errMsg)
  204. return
  205. }
  206. for _, fm := range formulaSlice {
  207. formulaMap, e := utils.CheckFormula(fm)
  208. if e != nil {
  209. err = fmt.Errorf("公式错误,请重新填写")
  210. return
  211. }
  212. for _, f := range formulaMap {
  213. if !strings.Contains(formulaStr, f) {
  214. errMsg = "公式错误,请重新填写"
  215. err = errors.New(errMsg)
  216. return
  217. }
  218. }
  219. }
  220. //关联的指标信息
  221. edbInfoList := make([]*models.EdbInfo, 0)
  222. // 动态环差规则 关系表
  223. trendsMappingList := make([]*models.PredictEdbConfCalculateMapping, 0)
  224. for k, tmpEdbInfoId := range v.EdbInfoIdArr {
  225. fromEdbInfo, tmpErr := models.GetEdbInfoById(tmpEdbInfoId.EdbInfoId)
  226. if tmpErr != nil {
  227. err = tmpErr
  228. if err.Error() == utils.ErrNoRow() {
  229. errMsg = "指标 " + strconv.Itoa(tmpEdbInfoId.EdbInfoId) + " 不存在"
  230. err = errors.New(errMsg)
  231. return
  232. }
  233. errMsg = "获取指标失败:Err:" + err.Error()
  234. err = errors.New(errMsg)
  235. return
  236. }
  237. edbInfoList = append(edbInfoList, fromEdbInfo)
  238. //总的 预测指标与所有相关联指标的关系表(不仅仅该条规则)
  239. {
  240. if _, ok := fromEdbMap[tmpEdbInfoId.EdbInfoId]; !ok {
  241. fromEdbMap[tmpEdbInfoId.EdbInfoId] = tmpEdbInfoId.EdbInfoId
  242. calculateMappingItem := &models.EdbInfoCalculateMapping{
  243. EdbInfoCalculateMappingId: 0,
  244. EdbInfoId: 0,
  245. Source: edbInfo.Source,
  246. SourceName: edbInfo.SourceName,
  247. EdbCode: "",
  248. FromEdbInfoId: fromEdbInfo.EdbInfoId,
  249. FromEdbCode: fromEdbInfo.EdbCode,
  250. FromEdbName: fromEdbInfo.EdbName,
  251. FromSource: fromEdbInfo.Source,
  252. FromSourceName: fromEdbInfo.SourceName,
  253. //FromTag: tmpEdbInfoId.FromTag,
  254. Sort: k + 1,
  255. CreateTime: time.Now(),
  256. ModifyTime: time.Now(),
  257. }
  258. calculateMappingList = append(calculateMappingList, calculateMappingItem)
  259. }
  260. }
  261. // 动态环差规则 关系表
  262. tmpPredictEdbConfCalculateMapping := &models.PredictEdbConfCalculateMapping{
  263. //PredictEdbConfCalculateMappingId: 0,
  264. EdbInfoId: 0,
  265. ConfigId: 0,
  266. FromEdbInfoId: fromEdbInfo.EdbInfoId,
  267. FromEdbCode: fromEdbInfo.EdbCode,
  268. FromEdbName: fromEdbInfo.EdbName,
  269. FromSource: fromEdbInfo.Source,
  270. FromSourceName: fromEdbInfo.SourceName,
  271. FromTag: tmpEdbInfoId.FromTag,
  272. Sort: k + 1,
  273. CreateTime: time.Now(),
  274. ModifyTime: time.Now(),
  275. }
  276. trendsMappingList = append(trendsMappingList, tmpPredictEdbConfCalculateMapping)
  277. }
  278. for _, f := range formulaSlice {
  279. formulaMap, e := utils.CheckFormula(f)
  280. if e != nil {
  281. err = fmt.Errorf("公式错误,请重新填写")
  282. return
  283. }
  284. //预先计算,判断公式是否正常
  285. ok, _ := models.CheckFormula2(edbInfoList, formulaMap, f, edbInfoIdBytes)
  286. if !ok {
  287. errMsg = "生成计算指标失败,请使用正确的计算公式"
  288. err = errors.New(errMsg)
  289. return
  290. }
  291. }
  292. calculateRuleMap[ruleIndex] = models.CalculateRule{
  293. TrendsCalculateMappingList: trendsMappingList,
  294. EdbInfoList: edbInfoList,
  295. EdbInfoIdBytes: edbInfoIdBytes,
  296. Formula: formula,
  297. RuleType: v.RuleType,
  298. EndDate: v.EndDate,
  299. EdbInfoIdArr: v.EdbInfoIdArr,
  300. }
  301. case 14: //14:根据 一元线性拟合 规则获取预测数据
  302. if v.Value == "" {
  303. errMsg = "请填写一元线性拟合规则"
  304. err = errors.New(errMsg)
  305. return
  306. }
  307. //关联的指标信息
  308. edbInfoList := make([]*models.EdbInfo, 0)
  309. // 动态环差规则 关系表
  310. trendsMappingList := make([]*models.PredictEdbConfCalculateMapping, 0)
  311. for k, tmpEdbInfoId := range v.EdbInfoIdArr {
  312. fromEdbInfo, tmpErr := models.GetEdbInfoById(tmpEdbInfoId.EdbInfoId)
  313. if tmpErr != nil {
  314. err = tmpErr
  315. if err.Error() == utils.ErrNoRow() {
  316. errMsg = "指标 " + strconv.Itoa(tmpEdbInfoId.EdbInfoId) + " 不存在"
  317. err = errors.New(errMsg)
  318. return
  319. }
  320. errMsg = "获取指标失败:Err:" + err.Error()
  321. err = errors.New(errMsg)
  322. return
  323. }
  324. edbInfoList = append(edbInfoList, fromEdbInfo)
  325. //总的 预测指标与所有相关联指标的关系表(不仅仅该条规则)
  326. {
  327. if _, ok := fromEdbMap[tmpEdbInfoId.EdbInfoId]; !ok {
  328. fromEdbMap[tmpEdbInfoId.EdbInfoId] = tmpEdbInfoId.EdbInfoId
  329. tmpCalculateMappingItem := &models.EdbInfoCalculateMapping{
  330. EdbInfoCalculateMappingId: 0,
  331. EdbInfoId: 0,
  332. Source: edbInfo.Source,
  333. SourceName: edbInfo.SourceName,
  334. EdbCode: "",
  335. FromEdbInfoId: fromEdbInfo.EdbInfoId,
  336. FromEdbCode: fromEdbInfo.EdbCode,
  337. FromEdbName: fromEdbInfo.EdbName,
  338. FromSource: fromEdbInfo.Source,
  339. FromSourceName: fromEdbInfo.SourceName,
  340. //FromTag: tmpEdbInfoId.FromTag,
  341. Sort: k + 1,
  342. CreateTime: time.Now(),
  343. ModifyTime: time.Now(),
  344. }
  345. calculateMappingList = append(calculateMappingList, tmpCalculateMappingItem)
  346. }
  347. }
  348. // 动态环差规则 关系表
  349. tmpPredictEdbConfCalculateMapping := &models.PredictEdbConfCalculateMapping{
  350. //PredictEdbConfCalculateMappingId: 0,
  351. EdbInfoId: 0,
  352. ConfigId: 0,
  353. FromEdbInfoId: fromEdbInfo.EdbInfoId,
  354. FromEdbCode: fromEdbInfo.EdbCode,
  355. FromEdbName: fromEdbInfo.EdbName,
  356. FromSource: fromEdbInfo.Source,
  357. FromSourceName: fromEdbInfo.SourceName,
  358. FromTag: tmpEdbInfoId.FromTag,
  359. Sort: k + 1,
  360. CreateTime: time.Now(),
  361. ModifyTime: time.Now(),
  362. }
  363. trendsMappingList = append(trendsMappingList, tmpPredictEdbConfCalculateMapping)
  364. }
  365. calculateRuleMap[ruleIndex] = models.CalculateRule{
  366. TrendsCalculateMappingList: trendsMappingList,
  367. EdbInfoList: edbInfoList,
  368. //EdbInfoIdBytes: edbInfoIdBytes,
  369. //Formula: formula,
  370. RuleType: v.RuleType,
  371. EndDate: v.EndDate,
  372. EdbInfoIdArr: v.EdbInfoIdArr,
  373. }
  374. case 17, 18:
  375. //关联的指标信息
  376. edbInfoList := make([]*models.EdbInfo, 0)
  377. edbInfoId, parseErr := strconv.Atoi(v.Value)
  378. if parseErr != nil {
  379. errMsg = "请填写正确的指标id"
  380. err = errors.New(errMsg)
  381. return
  382. }
  383. fromEdbInfo, tmpErr := models.GetEdbInfoById(edbInfoId)
  384. if tmpErr != nil {
  385. err = tmpErr
  386. if err.Error() == utils.ErrNoRow() {
  387. errMsg = "指标 " + strconv.Itoa(edbInfoId) + " 不存在"
  388. err = errors.New(errMsg)
  389. return
  390. }
  391. errMsg = "获取指标失败:Err:" + err.Error()
  392. err = errors.New(errMsg)
  393. return
  394. }
  395. edbInfoList = append(edbInfoList, fromEdbInfo)
  396. //总的 预测指标与所有相关联指标的关系表(不仅仅该条规则)
  397. fromEdbMap[edbInfoId] = edbInfoId
  398. calculateMappingItem = &models.EdbInfoCalculateMapping{
  399. EdbInfoCalculateMappingId: 0,
  400. EdbInfoId: 0,
  401. Source: edbInfo.Source,
  402. SourceName: edbInfo.SourceName,
  403. EdbCode: "",
  404. FromEdbInfoId: fromEdbInfo.EdbInfoId,
  405. FromEdbCode: fromEdbInfo.EdbCode,
  406. FromEdbName: fromEdbInfo.EdbName,
  407. FromSource: fromEdbInfo.Source,
  408. FromSourceName: fromEdbInfo.SourceName,
  409. //FromTag: tmpEdbInfoId.FromTag,
  410. Sort: 1,
  411. CreateTime: time.Now(),
  412. ModifyTime: time.Now(),
  413. }
  414. calculateMappingList = append(calculateMappingList, calculateMappingItem)
  415. calculateRuleMap[ruleIndex] = models.CalculateRule{
  416. EdbInfoList: edbInfoList,
  417. RuleType: v.RuleType,
  418. EndDate: v.EndDate,
  419. EdbInfoIdArr: v.EdbInfoIdArr,
  420. }
  421. }
  422. tmpPredictEdbConf := &models.PredictEdbConf{
  423. PredictEdbInfoId: 0,
  424. SourceEdbInfoId: sourceEdbInfoId,
  425. RuleType: v.RuleType,
  426. //FixedValue: v.Value,
  427. Value: v.Value,
  428. //EndDate: ruleEndDate,
  429. ModifyTime: time.Now(),
  430. CreateTime: time.Now(),
  431. EndNum: v.EndNum,
  432. }
  433. if endDateType == 0 {
  434. tmpPredictEdbConf.EndDate = ruleEndDate
  435. }
  436. //todo 指标最终的截止日期的更新
  437. edbInfo.EndDate = v.EndDate
  438. predictEdbConfList = append(predictEdbConfList, tmpPredictEdbConf)
  439. }
  440. err, errMsg = models.AddPredictEdb(edbInfo, calculateMappingList, predictEdbConfList, calculateRuleMap)
  441. return
  442. }
  443. // EditPredictEdbInfo 编辑预测指标
  444. func EditPredictEdbInfo(edbInfoId, classifyId int, edbName, dataDateType string, endDateType int, ruleList []models.RuleConfig, minValue, maxValue float64, lang string) (edbInfo *models.EdbInfo, err error, errMsg string) {
  445. // 指标信息校验
  446. {
  447. edbInfo, err = models.GetEdbInfoById(edbInfoId)
  448. if err != nil && !utils.IsErrNoRow(err) {
  449. errMsg = "修改失败"
  450. err = errors.New("获取预测指标失败,Err:" + err.Error())
  451. return
  452. }
  453. if edbInfo == nil {
  454. errMsg = "找不到该预测指标"
  455. err = errors.New(errMsg)
  456. return
  457. }
  458. //必须是普通的指标
  459. if edbInfo.EdbInfoType != 1 {
  460. errMsg = "指标异常,不是预测指标"
  461. err = errors.New(errMsg)
  462. return
  463. }
  464. }
  465. var predictEdbConf *models.PredictEdbConf
  466. // 指标配置信息校验
  467. {
  468. // 查找该预测指标配置
  469. predictEdbConfList, tmpErr := models.GetPredictEdbConfListById(edbInfo.EdbInfoId)
  470. if tmpErr != nil && !utils.IsErrNoRow(tmpErr) {
  471. errMsg = "修改失败"
  472. err = errors.New("获取预测指标配置信息失败,Err:" + tmpErr.Error())
  473. return
  474. }
  475. if len(predictEdbConfList) == 0 {
  476. errMsg = "找不到该预测指标配置"
  477. err = errors.New(errMsg)
  478. return
  479. }
  480. predictEdbConf = predictEdbConfList[0]
  481. }
  482. // 根据指标名称和指标ID校验库中是否还存在其他同名指标
  483. existEdbName, err := CheckExistByEdbNameAndEdbInfoId(utils.PREDICT_EDB_INFO_TYPE, edbInfoId, edbName, lang)
  484. if err != nil {
  485. errMsg = "判断指标名称是否存在失败"
  486. err = errors.New("判断指标名称是否存在失败,Err:" + err.Error())
  487. return
  488. }
  489. if existEdbName {
  490. errMsg = "指标名称已存在,请重新填写"
  491. err = errors.New(errMsg)
  492. return
  493. }
  494. if dataDateType == `` {
  495. dataDateType = `自然日`
  496. }
  497. switch lang {
  498. case utils.EnLangVersion:
  499. edbInfo.EdbNameEn = edbName
  500. default:
  501. edbInfo.EdbName = edbName
  502. }
  503. edbInfo.EdbNameSource = edbName
  504. edbInfo.ClassifyId = classifyId
  505. edbInfo.MinValue = minValue
  506. edbInfo.MaxValue = maxValue
  507. edbInfo.DataDateType = dataDateType
  508. edbInfo.ModifyTime = time.Now()
  509. edbInfo.EndDateType = endDateType
  510. updateEdbInfoCol := []string{"EdbName", "EdbNameEn", "EdbNameSource", "ClassifyId", "EndDate", "MinValue", "MaxValue", "DataDateType", "ModifyTime", "EndDateType"}
  511. var sourceEdbInfo *models.EdbInfo
  512. // 来源指标信息校验
  513. {
  514. sourceEdbInfo, err = models.GetEdbInfoById(predictEdbConf.SourceEdbInfoId)
  515. if err != nil && !utils.IsErrNoRow(err) {
  516. errMsg = "新增失败"
  517. err = errors.New("获取来源指标失败,Err:" + err.Error())
  518. return
  519. }
  520. if sourceEdbInfo == nil {
  521. errMsg = "找不到该来源指标"
  522. err = errors.New(errMsg)
  523. return
  524. }
  525. //必须是普通的指标
  526. if sourceEdbInfo.EdbInfoType != 0 {
  527. errMsg = "来源指标异常,不是普通的指标"
  528. err = errors.New(errMsg)
  529. return
  530. }
  531. //if !utils.InArrayByStr([]string{"日度", "周度", "月度", "年度"}, sourceEdbInfo.Frequency) {
  532. // errMsg = "预测指标只支持选择日度、周度、月度、年度的指标"
  533. // err = errors.New(errMsg)
  534. // return
  535. //}
  536. }
  537. // 预测指标配置
  538. // 关联关系表
  539. calculateMappingList := make([]*models.EdbInfoCalculateMapping, 0)
  540. fromEdbMap := make(map[int]int)
  541. // 源指标关联关系表
  542. calculateMappingItem := &models.EdbInfoCalculateMapping{
  543. //EdbInfoCalculateMappingId: 0,
  544. EdbInfoId: edbInfoId,
  545. Source: edbInfo.Source,
  546. SourceName: edbInfo.SourceName,
  547. EdbCode: edbInfo.EdbCode,
  548. FromEdbInfoId: sourceEdbInfo.EdbInfoId,
  549. FromEdbCode: sourceEdbInfo.EdbCode,
  550. FromEdbName: sourceEdbInfo.EdbName,
  551. FromSource: sourceEdbInfo.Source,
  552. FromSourceName: sourceEdbInfo.SourceName,
  553. //FromTag: "",
  554. Sort: 1,
  555. CreateTime: time.Now(),
  556. ModifyTime: time.Now(),
  557. }
  558. fromEdbMap[sourceEdbInfo.EdbInfoId] = sourceEdbInfo.EdbInfoId
  559. calculateMappingList = append(calculateMappingList, calculateMappingItem)
  560. // 动态环差 计算列表
  561. calculateRuleMap := make(map[int]models.CalculateRule, 0)
  562. // 预测指标配置
  563. predictEdbConfList := make([]*models.PredictEdbConf, 0)
  564. for ruleIndex, v := range ruleList {
  565. var ruleEndDate time.Time
  566. if endDateType == 0 {
  567. // 预测指标配置
  568. ruleEndDate, err = time.ParseInLocation(utils.FormatDate, v.EndDate, time.Local)
  569. if err != nil {
  570. errMsg = "规则配置的截止日期异常,请重新填写"
  571. err = errors.New(errMsg)
  572. return
  573. }
  574. } else {
  575. if v.EndNum <= 0 {
  576. errMsg = "截止期数不正确,请输入大于等于1的整数"
  577. err = errors.New(errMsg)
  578. return
  579. }
  580. }
  581. //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,9:动态环差,10:根据 给定终值后插值 规则获取预测数据,11:根据 季节性 规则获取预测数据,12:根据 移动平均同比 规则获取预测数据
  582. // 环比、环差、动态环差、季节性、移动平均同比不支持年度
  583. if sourceEdbInfo.Frequency == "年度" && utils.InArrayByInt([]int{5, 6, 11, 12}, v.RuleType) {
  584. errMsg = "环比、环差、动态环差、季节性、移动平均同比不支持年度指标"
  585. err = errors.New(errMsg)
  586. return
  587. }
  588. if v.RuleType == 16 && endDateType == 1 {
  589. errMsg = "年度值倒推不支持截止期数"
  590. err = errors.New(errMsg)
  591. return
  592. }
  593. switch v.RuleType {
  594. case 8: //N期段线性外推值
  595. valInt, tmpErr := strconv.Atoi(v.Value)
  596. if tmpErr != nil {
  597. errMsg = "N期段线性外推值的N值异常"
  598. err = errors.New(errMsg)
  599. return
  600. }
  601. if valInt <= 1 {
  602. errMsg = "N期段线性外推值的N值必须大于1"
  603. err = errors.New(errMsg)
  604. return
  605. }
  606. case 9: //9:动态环差
  607. if v.Value == "" {
  608. errMsg = "请填写计算规则"
  609. err = errors.New(errMsg)
  610. return
  611. }
  612. formula := v.Value
  613. formula = strings.Replace(formula, "(", "(", -1)
  614. formula = strings.Replace(formula, ")", ")", -1)
  615. formula = strings.Replace(formula, ",", ",", -1)
  616. formula = strings.Replace(formula, "。", ".", -1)
  617. formula = strings.Replace(formula, "%", "*0.01", -1)
  618. v.Value = formula
  619. //检验公式
  620. var formulaStr string
  621. var edbInfoIdBytes []string
  622. for _, tmpEdbInfoId := range v.EdbInfoIdArr {
  623. formulaStr += tmpEdbInfoId.FromTag + ","
  624. edbInfoIdBytes = append(edbInfoIdBytes, tmpEdbInfoId.FromTag)
  625. }
  626. formulaSlice, tErr := utils.CheckFormulaJson(formula)
  627. if tErr != nil {
  628. errMsg = "公式格式错误,请重新填写"
  629. err = errors.New(errMsg)
  630. return
  631. }
  632. for _, fm := range formulaSlice {
  633. formulaMap, e := utils.CheckFormula(fm)
  634. if e != nil {
  635. err = fmt.Errorf("公式错误,请重新填写")
  636. return
  637. }
  638. for _, f := range formulaMap {
  639. if !strings.Contains(formulaStr, f) {
  640. errMsg = "公式错误,请重新填写"
  641. err = errors.New(errMsg)
  642. return
  643. }
  644. }
  645. }
  646. //关联的指标信息
  647. edbInfoList := make([]*models.EdbInfo, 0)
  648. // 动态环差规则 关系表
  649. trendsMappingList := make([]*models.PredictEdbConfCalculateMapping, 0)
  650. for k, tmpEdbInfoId := range v.EdbInfoIdArr {
  651. fromEdbInfo, tmpErr := models.GetEdbInfoById(tmpEdbInfoId.EdbInfoId)
  652. if tmpErr != nil {
  653. err = tmpErr
  654. if err.Error() == utils.ErrNoRow() {
  655. errMsg = "指标 " + strconv.Itoa(tmpEdbInfoId.EdbInfoId) + " 不存在"
  656. err = errors.New(errMsg)
  657. return
  658. }
  659. errMsg = "获取指标失败:Err:" + err.Error()
  660. err = errors.New(errMsg)
  661. return
  662. }
  663. edbInfoList = append(edbInfoList, fromEdbInfo)
  664. //总的 预测指标与所有相关联指标的关系表(不仅仅该条规则)
  665. {
  666. if _, ok := fromEdbMap[tmpEdbInfoId.EdbInfoId]; !ok {
  667. fromEdbMap[tmpEdbInfoId.EdbInfoId] = tmpEdbInfoId.EdbInfoId
  668. calculateMappingItem := &models.EdbInfoCalculateMapping{
  669. EdbInfoCalculateMappingId: 0,
  670. EdbInfoId: edbInfoId,
  671. Source: utils.DATA_SOURCE_CALCULATE,
  672. SourceName: "指标运算",
  673. EdbCode: "",
  674. FromEdbInfoId: fromEdbInfo.EdbInfoId,
  675. FromEdbCode: fromEdbInfo.EdbCode,
  676. FromEdbName: fromEdbInfo.EdbName,
  677. FromSource: fromEdbInfo.Source,
  678. FromSourceName: fromEdbInfo.SourceName,
  679. //FromTag: tmpEdbInfoId.FromTag,
  680. Sort: k + 1,
  681. CreateTime: time.Now(),
  682. ModifyTime: time.Now(),
  683. }
  684. calculateMappingList = append(calculateMappingList, calculateMappingItem)
  685. }
  686. }
  687. // 动态环差规则 关系表
  688. tmpPredictEdbConfCalculateMapping := &models.PredictEdbConfCalculateMapping{
  689. //PredictEdbConfCalculateMappingId: 0,
  690. EdbInfoId: edbInfoId,
  691. ConfigId: 0,
  692. FromEdbInfoId: fromEdbInfo.EdbInfoId,
  693. FromEdbCode: fromEdbInfo.EdbCode,
  694. FromEdbName: fromEdbInfo.EdbName,
  695. FromSource: fromEdbInfo.Source,
  696. FromSourceName: fromEdbInfo.SourceName,
  697. FromTag: tmpEdbInfoId.FromTag,
  698. Sort: k + 1,
  699. CreateTime: time.Now(),
  700. ModifyTime: time.Now(),
  701. }
  702. trendsMappingList = append(trendsMappingList, tmpPredictEdbConfCalculateMapping)
  703. }
  704. for _, f := range formulaSlice {
  705. formulaMap, e := utils.CheckFormula(f)
  706. if e != nil {
  707. err = fmt.Errorf("公式错误,请重新填写")
  708. return
  709. }
  710. //预先计算,判断公式是否正常
  711. ok, _ := models.CheckFormula2(edbInfoList, formulaMap, f, edbInfoIdBytes)
  712. if !ok {
  713. errMsg = "生成计算指标失败,请使用正确的计算公式"
  714. err = errors.New(errMsg)
  715. return
  716. }
  717. }
  718. calculateRuleMap[ruleIndex] = models.CalculateRule{
  719. TrendsCalculateMappingList: trendsMappingList,
  720. EdbInfoList: edbInfoList,
  721. EdbInfoIdBytes: edbInfoIdBytes,
  722. Formula: formula,
  723. RuleType: v.RuleType,
  724. EndDate: v.EndDate,
  725. EdbInfoIdArr: v.EdbInfoIdArr,
  726. }
  727. case 14: //14:根据 一元线性拟合 规则获取预测数据
  728. if v.Value == "" {
  729. errMsg = "请填写一元线性拟合规则"
  730. err = errors.New(errMsg)
  731. return
  732. }
  733. //关联的指标信息
  734. edbInfoList := make([]*models.EdbInfo, 0)
  735. // 动态环差规则 关系表
  736. trendsMappingList := make([]*models.PredictEdbConfCalculateMapping, 0)
  737. for k, tmpEdbInfoId := range v.EdbInfoIdArr {
  738. fromEdbInfo, tmpErr := models.GetEdbInfoById(tmpEdbInfoId.EdbInfoId)
  739. if tmpErr != nil {
  740. err = tmpErr
  741. if err.Error() == utils.ErrNoRow() {
  742. errMsg = "指标 " + strconv.Itoa(tmpEdbInfoId.EdbInfoId) + " 不存在"
  743. err = errors.New(errMsg)
  744. return
  745. }
  746. errMsg = "获取指标失败:Err:" + err.Error()
  747. err = errors.New(errMsg)
  748. return
  749. }
  750. edbInfoList = append(edbInfoList, fromEdbInfo)
  751. //总的 预测指标与所有相关联指标的关系表(不仅仅该条规则)
  752. {
  753. if _, ok := fromEdbMap[tmpEdbInfoId.EdbInfoId]; !ok {
  754. fromEdbMap[tmpEdbInfoId.EdbInfoId] = tmpEdbInfoId.EdbInfoId
  755. tmpCalculateMappingItem := &models.EdbInfoCalculateMapping{
  756. EdbInfoCalculateMappingId: 0,
  757. EdbInfoId: 0,
  758. Source: utils.DATA_SOURCE_CALCULATE,
  759. SourceName: "指标运算",
  760. EdbCode: "",
  761. FromEdbInfoId: fromEdbInfo.EdbInfoId,
  762. FromEdbCode: fromEdbInfo.EdbCode,
  763. FromEdbName: fromEdbInfo.EdbName,
  764. FromSource: fromEdbInfo.Source,
  765. FromSourceName: fromEdbInfo.SourceName,
  766. //FromTag: tmpEdbInfoId.FromTag,
  767. Sort: k + 1,
  768. CreateTime: time.Now(),
  769. ModifyTime: time.Now(),
  770. }
  771. calculateMappingList = append(calculateMappingList, tmpCalculateMappingItem)
  772. }
  773. }
  774. // 动态环差规则 关系表
  775. tmpPredictEdbConfCalculateMapping := &models.PredictEdbConfCalculateMapping{
  776. //PredictEdbConfCalculateMappingId: 0,
  777. EdbInfoId: 0,
  778. ConfigId: 0,
  779. FromEdbInfoId: fromEdbInfo.EdbInfoId,
  780. FromEdbCode: fromEdbInfo.EdbCode,
  781. FromEdbName: fromEdbInfo.EdbName,
  782. FromSource: fromEdbInfo.Source,
  783. FromSourceName: fromEdbInfo.SourceName,
  784. FromTag: tmpEdbInfoId.FromTag,
  785. Sort: k + 1,
  786. CreateTime: time.Now(),
  787. ModifyTime: time.Now(),
  788. }
  789. trendsMappingList = append(trendsMappingList, tmpPredictEdbConfCalculateMapping)
  790. }
  791. // todo
  792. calculateRuleMap[ruleIndex] = models.CalculateRule{
  793. TrendsCalculateMappingList: trendsMappingList,
  794. EdbInfoList: edbInfoList,
  795. //EdbInfoIdBytes: edbInfoIdBytes,
  796. //Formula: formula,
  797. RuleType: v.RuleType,
  798. EndDate: v.EndDate,
  799. EdbInfoIdArr: v.EdbInfoIdArr,
  800. }
  801. case 17, 18:
  802. //关联的指标信息
  803. edbInfoList := make([]*models.EdbInfo, 0)
  804. edbInfoId, parseErr := strconv.Atoi(v.Value)
  805. if parseErr != nil {
  806. errMsg = "请填写正确的指标id"
  807. err = errors.New(errMsg)
  808. return
  809. }
  810. fromEdbInfo, tmpErr := models.GetEdbInfoById(edbInfoId)
  811. if tmpErr != nil {
  812. err = tmpErr
  813. if err.Error() == utils.ErrNoRow() {
  814. errMsg = "指标 " + strconv.Itoa(edbInfoId) + " 不存在"
  815. err = errors.New(errMsg)
  816. return
  817. }
  818. errMsg = "获取指标失败:Err:" + err.Error()
  819. err = errors.New(errMsg)
  820. return
  821. }
  822. edbInfoList = append(edbInfoList, fromEdbInfo)
  823. //总的 预测指标与所有相关联指标的关系表(不仅仅该条规则)
  824. fromEdbMap[edbInfoId] = edbInfoId
  825. calculateMappingItem = &models.EdbInfoCalculateMapping{
  826. EdbInfoCalculateMappingId: 0,
  827. EdbInfoId: 0,
  828. Source: edbInfo.Source,
  829. SourceName: edbInfo.SourceName,
  830. EdbCode: "",
  831. FromEdbInfoId: fromEdbInfo.EdbInfoId,
  832. FromEdbCode: fromEdbInfo.EdbCode,
  833. FromEdbName: fromEdbInfo.EdbName,
  834. FromSource: fromEdbInfo.Source,
  835. FromSourceName: fromEdbInfo.SourceName,
  836. //FromTag: tmpEdbInfoId.FromTag,
  837. Sort: 1,
  838. CreateTime: time.Now(),
  839. ModifyTime: time.Now(),
  840. }
  841. calculateMappingList = append(calculateMappingList, calculateMappingItem)
  842. calculateRuleMap[ruleIndex] = models.CalculateRule{
  843. EdbInfoList: edbInfoList,
  844. RuleType: v.RuleType,
  845. EndDate: v.EndDate,
  846. EdbInfoIdArr: v.EdbInfoIdArr,
  847. }
  848. }
  849. tmpPredictEdbConf := &models.PredictEdbConf{
  850. PredictEdbInfoId: edbInfoId,
  851. SourceEdbInfoId: sourceEdbInfo.EdbInfoId,
  852. RuleType: v.RuleType,
  853. //FixedValue: v.Value,
  854. Value: v.Value,
  855. EndDate: ruleEndDate,
  856. EndNum: v.EndNum,
  857. ModifyTime: time.Now(),
  858. CreateTime: time.Now(),
  859. }
  860. if endDateType == 0 {
  861. tmpPredictEdbConf.EndDate = ruleEndDate
  862. }
  863. // todo
  864. edbInfo.EndDate = v.EndDate
  865. predictEdbConfList = append(predictEdbConfList, tmpPredictEdbConf)
  866. }
  867. err, errMsg = models.EditPredictEdb(edbInfo, updateEdbInfoCol, calculateMappingList, predictEdbConfList, calculateRuleMap)
  868. return
  869. }
  870. // RefreshPredictEdbInfo 更新基础预测指标规则中的动态数据
  871. func RefreshPredictEdbInfo(edbInfoId int) (edbInfo *models.EdbInfo, err error, errMsg string) {
  872. // 指标信息校验
  873. {
  874. edbInfo, err = models.GetEdbInfoById(edbInfoId)
  875. if err != nil && !utils.IsErrNoRow(err) {
  876. errMsg = "刷新失败"
  877. err = errors.New("获取预测指标失败,Err:" + err.Error())
  878. return
  879. }
  880. if edbInfo == nil {
  881. errMsg = "找不到该预测指标"
  882. err = nil
  883. return
  884. }
  885. //必须是普通的指标
  886. if edbInfo.EdbInfoType != 1 {
  887. errMsg = "指标异常,不是预测指标"
  888. return
  889. }
  890. }
  891. // 配置 与 指标的 关联关系表
  892. list, err := models.GetPredictEdbConfCalculateMappingListByEdbInfoId(edbInfoId)
  893. if err != nil {
  894. return
  895. }
  896. // 没有关联指标,不需要刷新
  897. if len(list) <= 0 {
  898. return
  899. }
  900. // 配置关联的指标信息
  901. predictEdbConfCalculateMappingListMap := make(map[int][]*models.PredictEdbConfCalculateMapping)
  902. configIdList := make([]int, 0) //关联配置id
  903. edbInfoIdList := make([]int, 0) //关联指标配置id
  904. edbInfoIdMap := make(map[int]int, 0) //关联指标配置map
  905. for _, v := range list {
  906. configList, ok := predictEdbConfCalculateMappingListMap[v.ConfigId]
  907. if !ok {
  908. configList = make([]*models.PredictEdbConfCalculateMapping, 0)
  909. configIdList = append(configIdList, v.ConfigId)
  910. }
  911. if _, ok := edbInfoIdMap[v.FromEdbInfoId]; !ok {
  912. edbInfoIdList = append(edbInfoIdList, v.FromEdbInfoId)
  913. }
  914. configList = append(configList, v)
  915. predictEdbConfCalculateMappingListMap[v.ConfigId] = configList
  916. }
  917. predictEdbConfList, err := models.GetPredictEdbConfListByConfigIdList(configIdList)
  918. if err != nil {
  919. errMsg = "刷新失败"
  920. err = errors.New("获取预测指标配置信息失败,Err:" + err.Error())
  921. return
  922. }
  923. if len(predictEdbConfList) == 0 {
  924. errMsg = "找不到该预测指标配置"
  925. err = nil
  926. return
  927. }
  928. // 指标信息
  929. edbInfoList, err := models.GetEdbInfoByIdList(edbInfoIdList)
  930. if err != nil {
  931. err = errors.New("获取关联指标失败,Err:" + err.Error())
  932. return
  933. }
  934. // 指标信息map
  935. edbInfoListMap := make(map[int]*models.EdbInfo)
  936. for _, v := range edbInfoList {
  937. edbInfoListMap[v.EdbInfoId] = v
  938. }
  939. predictEdbConfAndDataList := make([]*models.PredictEdbConfAndData, 0)
  940. // 刷新所有的规则
  941. for _, v := range predictEdbConfList {
  942. // 每次规则计算的时候,产生的临时数据
  943. resultDataList := make([]*models.EdbInfoSearchData, 0)
  944. switch v.RuleType {
  945. case 9: //动态环差值
  946. if v.Value == "" {
  947. errMsg = "请填写计算规则"
  948. return
  949. }
  950. // todo 动态环差的空值类型处理
  951. formula := v.Value
  952. // 动态环差规则 关系表
  953. trendsMappingList := predictEdbConfCalculateMappingListMap[v.ConfigId]
  954. // 关联标签
  955. edbInfoIdArr := make([]models.EdbInfoFromTag, 0)
  956. //关联的指标信息
  957. edbInfoList := make([]*models.EdbInfo, 0)
  958. for _, trendsMapping := range trendsMappingList {
  959. tmpEdbInfo, ok := edbInfoListMap[trendsMapping.FromEdbInfoId]
  960. if ok {
  961. edbInfoList = append(edbInfoList, tmpEdbInfo)
  962. }
  963. // 关联标签
  964. edbInfoIdArr = append(edbInfoIdArr, models.EdbInfoFromTag{
  965. EdbInfoId: trendsMapping.FromEdbInfoId,
  966. FromTag: trendsMapping.FromTag,
  967. })
  968. }
  969. //检验公式
  970. var formulaStr string
  971. var edbInfoIdBytes []string
  972. for _, tmpEdbInfoId := range edbInfoIdArr {
  973. formulaStr += tmpEdbInfoId.FromTag + ","
  974. edbInfoIdBytes = append(edbInfoIdBytes, tmpEdbInfoId.FromTag)
  975. }
  976. formulaSlice, tErr := utils.CheckFormulaJson(formula)
  977. if tErr != nil {
  978. errMsg = "公式格式错误,请重新填写"
  979. err = errors.New(errMsg)
  980. return
  981. }
  982. for _, fm := range formulaSlice {
  983. formulaMap, e := utils.CheckFormula(fm)
  984. if e != nil {
  985. err = fmt.Errorf("公式错误,请重新填写")
  986. return
  987. }
  988. for _, f := range formulaMap {
  989. if !strings.Contains(formulaStr, f) {
  990. errMsg = "公式错误,请重新填写"
  991. err = errors.New(errMsg)
  992. return
  993. }
  994. }
  995. //预先计算,判断公式是否正常
  996. ok, _ := models.CheckFormula2(edbInfoList, formulaMap, fm, edbInfoIdBytes)
  997. if !ok {
  998. errMsg = "生成计算指标失败,请使用正确的计算公式"
  999. return
  1000. }
  1001. }
  1002. rule := models.CalculateRule{
  1003. EdbInfoId: v.PredictEdbInfoId,
  1004. ConfigId: v.ConfigId,
  1005. TrendsCalculateMappingList: trendsMappingList,
  1006. EdbInfoList: edbInfoList,
  1007. EdbInfoIdBytes: edbInfoIdBytes,
  1008. Formula: formula,
  1009. RuleType: v.RuleType,
  1010. EndDate: v.EndDate.Format(utils.FormatDate),
  1011. EdbInfoIdArr: edbInfoIdArr,
  1012. }
  1013. resultDataList, err = models.RefreshCalculateByRuleBy9(rule)
  1014. if err != nil {
  1015. return
  1016. }
  1017. case 14: //14:根据 一元线性拟合 规则获取预测数据
  1018. if v.Value == "" {
  1019. errMsg = "一元线性拟合规则信息未配置"
  1020. return
  1021. }
  1022. err, errMsg = models.RefreshCalculateByRuleByLineNh(*edbInfo, predictEdbConfAndDataList, *v)
  1023. if err != nil {
  1024. return
  1025. }
  1026. }
  1027. // 规则配置(含数据)
  1028. tmpPredictEdbConfAndData := &models.PredictEdbConfAndData{
  1029. ConfigId: 0,
  1030. PredictEdbInfoId: 0,
  1031. SourceEdbInfoId: v.SourceEdbInfoId,
  1032. RuleType: v.RuleType,
  1033. FixedValue: v.FixedValue,
  1034. Value: v.Value,
  1035. EndDate: v.EndDate,
  1036. ModifyTime: v.ModifyTime,
  1037. CreateTime: v.CreateTime,
  1038. DataList: resultDataList,
  1039. }
  1040. predictEdbConfAndDataList = append(predictEdbConfAndDataList, tmpPredictEdbConfAndData)
  1041. }
  1042. return
  1043. }
  1044. // checkExistByEdbName
  1045. // @Description: 根据指标名称校验该指标是否存在库中
  1046. // @author: Roc
  1047. // @datetime 2024-04-18 14:58:52
  1048. // @param edbInfoType int
  1049. // @param edbName string
  1050. // @param lang string
  1051. // @return has bool
  1052. // @return err error
  1053. func checkExistByEdbName(edbInfoType int, edbName, lang string) (has bool, err error) {
  1054. var condition string
  1055. var pars []interface{}
  1056. condition += " AND edb_info_type=? "
  1057. pars = append(pars, edbInfoType)
  1058. switch lang {
  1059. case utils.EnLangVersion:
  1060. condition += " AND edb_name_en = ? "
  1061. default:
  1062. condition += " AND edb_name=? "
  1063. }
  1064. pars = append(pars, edbName)
  1065. count, err := models.GetEdbInfoCountByCondition(condition, pars)
  1066. if err != nil {
  1067. return
  1068. }
  1069. if count > 0 {
  1070. has = true
  1071. return
  1072. }
  1073. return
  1074. }
  1075. // checkExistByEdbNameAndEdbInfoId
  1076. // @Description: 根据指标名称和指标ID校验库中是否还存在其他同名指标
  1077. // @author: Roc
  1078. // @datetime 2024-04-18 15:00:19
  1079. // @param edbInfoType int
  1080. // @param edbInfoId int
  1081. // @param edbName string
  1082. // @param lang string
  1083. // @return has bool
  1084. // @return err error
  1085. func checkExistByEdbNameAndEdbInfoId(edbInfoType, edbInfoId int, edbName, lang string) (has bool, err error) {
  1086. var condition string
  1087. var pars []interface{}
  1088. condition += " AND edb_info_type=? "
  1089. pars = append(pars, edbInfoType)
  1090. condition += " AND edb_info_id<>? "
  1091. pars = append(pars, edbInfoId)
  1092. switch lang {
  1093. case utils.EnLangVersion:
  1094. condition += " AND edb_name_en = ? "
  1095. default:
  1096. condition += " AND edb_name=? "
  1097. }
  1098. pars = append(pars, edbName)
  1099. count, err := models.GetEdbInfoCountByCondition(condition, pars)
  1100. if err != nil {
  1101. return
  1102. }
  1103. if count > 0 {
  1104. has = true
  1105. return
  1106. }
  1107. return
  1108. }
  1109. // CheckExistByEdbNameAndEdbInfoId
  1110. // @Description: 根据指标名称和指标ID校验库中是否还存在其他同名指标
  1111. // @author: Roc
  1112. // @datetime 2024-04-18 15:01:44
  1113. // @param edbInfoType int
  1114. // @param edbInfoId int
  1115. // @param edbName string
  1116. // @param lang string
  1117. // @return has bool
  1118. // @return err error
  1119. func CheckExistByEdbNameAndEdbInfoId(edbInfoType, edbInfoId int, edbName, lang string) (has bool, err error) {
  1120. // 指标没有入库的情况
  1121. if edbInfoId == 0 {
  1122. return checkExistByEdbName(edbInfoType, edbName, lang)
  1123. }
  1124. //指标已经入库的情况
  1125. return checkExistByEdbNameAndEdbInfoId(edbInfoType, edbInfoId, edbName, lang)
  1126. }
  1127. // AddStaticPredictEdbInfo 新增静态指标数据
  1128. func AddStaticPredictEdbInfo(sourceEdbInfoId, classifyId int, edbName, frequency, unit string, sysUserId int, sysUserName, lang string) (edbInfo *models.EdbInfo, err error, errMsg string) {
  1129. var sourceEdbInfo *models.EdbInfo
  1130. // 来源指标信息校验
  1131. {
  1132. sourceEdbInfo, err = models.GetEdbInfoById(sourceEdbInfoId)
  1133. if err != nil && !utils.IsErrNoRow(err) {
  1134. errMsg = "新增失败"
  1135. err = errors.New("获取来源指标失败,Err:" + err.Error())
  1136. return
  1137. }
  1138. if sourceEdbInfo == nil {
  1139. errMsg = "找不到该来源指标"
  1140. err = errors.New(errMsg)
  1141. return
  1142. }
  1143. }
  1144. var classifyInfo *models.EdbClassify
  1145. // 来源分类信息校验
  1146. {
  1147. classifyInfo, err = models.GetEdbClassifyById(classifyId)
  1148. if err != nil && !utils.IsErrNoRow(err) {
  1149. errMsg = "新增失败"
  1150. err = errors.New("获取预测指标分类失败,Err:" + err.Error())
  1151. return
  1152. }
  1153. if classifyInfo == nil {
  1154. errMsg = "找不到该预测指标分类"
  1155. err = errors.New(errMsg)
  1156. return
  1157. }
  1158. //必须是预测指标分类
  1159. if classifyInfo.ClassifyType != 1 {
  1160. errMsg = "预测指标分类异常,不是预测指标分类"
  1161. err = errors.New(errMsg)
  1162. return
  1163. }
  1164. }
  1165. edbName = strings.Trim(edbName, " ")
  1166. edbCode := sourceEdbInfo.EdbCode + "_" + time.Now().Format(utils.FormatShortDateTimeUnSpace)
  1167. // 根据指标名称和指标ID校验库中是否还存在其他同名指标
  1168. existEdbName, err := CheckExistByEdbNameAndEdbInfoId(utils.PREDICT_EDB_INFO_TYPE, 0, edbName, lang)
  1169. if err != nil {
  1170. errMsg = "判断指标名称是否存在失败"
  1171. err = errors.New("判断指标名称是否存在失败,Err:" + err.Error())
  1172. return
  1173. }
  1174. if existEdbName {
  1175. errMsg = "指标名称已存在,请重新填写"
  1176. err = errors.New(errMsg)
  1177. return
  1178. }
  1179. timestamp := strconv.FormatInt(time.Now().UnixNano(), 10)
  1180. edbInfo = &models.EdbInfo{
  1181. //EdbInfoId: 0,
  1182. EdbInfoType: sourceEdbInfo.EdbInfoType,
  1183. SourceName: sourceEdbInfo.SourceName,
  1184. Source: sourceEdbInfo.Source,
  1185. EdbCode: edbCode,
  1186. EdbName: edbName,
  1187. EdbNameSource: edbName,
  1188. Frequency: frequency,
  1189. Unit: unit,
  1190. StartDate: sourceEdbInfo.StartDate,
  1191. EndDate: sourceEdbInfo.EndDate,
  1192. ClassifyId: classifyId,
  1193. SysUserId: sysUserId,
  1194. SysUserRealName: sysUserName,
  1195. UniqueCode: utils.MD5(utils.DATA_PREFIX + "_" + timestamp),
  1196. CreateTime: time.Now(),
  1197. ModifyTime: time.Now(),
  1198. MinValue: sourceEdbInfo.MinValue,
  1199. MaxValue: sourceEdbInfo.MaxValue,
  1200. EndValue: sourceEdbInfo.EndValue,
  1201. CalculateFormula: sourceEdbInfo.CalculateFormula,
  1202. EdbType: sourceEdbInfo.EdbType,
  1203. //Sort: sourceEdbInfo.,
  1204. LatestDate: sourceEdbInfo.LatestDate,
  1205. LatestValue: sourceEdbInfo.LatestValue,
  1206. MoveType: sourceEdbInfo.MoveType,
  1207. MoveFrequency: sourceEdbInfo.MoveFrequency,
  1208. NoUpdate: sourceEdbInfo.NoUpdate,
  1209. IsUpdate: sourceEdbInfo.IsUpdate,
  1210. ServerUrl: "",
  1211. EdbNameEn: edbName,
  1212. UnitEn: sourceEdbInfo.UnitEn,
  1213. DataDateType: sourceEdbInfo.DataDateType,
  1214. Sort: models.GetAddEdbMaxSortByClassifyId(classifyId, utils.PREDICT_EDB_INFO_TYPE),
  1215. IsStaticData: 1,
  1216. }
  1217. // 关联关系表
  1218. calculateMappingList := make([]*models.EdbInfoCalculateMapping, 0)
  1219. fromEdbMap := make(map[int]int)
  1220. // 源指标关联关系表
  1221. calculateMappingItem := &models.EdbInfoCalculateMapping{
  1222. //EdbInfoCalculateMappingId: 0,
  1223. //EdbInfoId: 0,
  1224. Source: edbInfo.Source,
  1225. SourceName: edbInfo.SourceName,
  1226. EdbCode: edbInfo.EdbCode,
  1227. FromEdbInfoId: sourceEdbInfo.EdbInfoId,
  1228. FromEdbCode: sourceEdbInfo.EdbCode,
  1229. FromEdbName: sourceEdbInfo.EdbName,
  1230. FromSource: sourceEdbInfo.Source,
  1231. FromSourceName: sourceEdbInfo.SourceName,
  1232. //FromTag: "",
  1233. Sort: 1,
  1234. CreateTime: time.Now(),
  1235. ModifyTime: time.Now(),
  1236. }
  1237. fromEdbMap[sourceEdbInfoId] = sourceEdbInfoId
  1238. calculateMappingList = append(calculateMappingList, calculateMappingItem)
  1239. newPredictEdbConfList := make([]*models.PredictEdbConf, 0)
  1240. //查询原先的预测指标配置项
  1241. if sourceEdbInfo.EdbType == 1 {
  1242. // 查找该预测指标配置
  1243. predictEdbConfList, tmpErr := models.GetPredictEdbConfListById(sourceEdbInfo.EdbInfoId)
  1244. if tmpErr != nil && !utils.IsErrNoRow(tmpErr) {
  1245. errMsg = "获取预测指标配置信息失败"
  1246. err = errors.New("获取预测指标配置信息失败,Err:" + tmpErr.Error())
  1247. return
  1248. }
  1249. if len(predictEdbConfList) > 0 {
  1250. // 遍历
  1251. for _, v := range predictEdbConfList {
  1252. tmpPredictEdbConf := &models.PredictEdbConf{
  1253. PredictEdbInfoId: 0,
  1254. SourceEdbInfoId: sourceEdbInfoId,
  1255. RuleType: v.RuleType,
  1256. FixedValue: v.FixedValue,
  1257. Value: v.Value,
  1258. EmptyType: v.EmptyType,
  1259. MaxEmptyType: v.MaxEmptyType,
  1260. EndDate: v.EndDate,
  1261. ModifyTime: time.Now(),
  1262. CreateTime: time.Now(),
  1263. }
  1264. newPredictEdbConfList = append(newPredictEdbConfList, tmpPredictEdbConf)
  1265. }
  1266. }
  1267. }
  1268. err, errMsg = models.AddPredictStaticEdb(edbInfo, sourceEdbInfo, calculateMappingList, newPredictEdbConfList)
  1269. return
  1270. }