ai_predict_model_index.go 14 KB

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  1. package services
  2. import (
  3. "encoding/json"
  4. aiPredictModel "eta/eta_api/models/ai_predict_model"
  5. "eta/eta_api/models/data_manage"
  6. "eta/eta_api/services/data"
  7. "eta/eta_api/utils"
  8. "fmt"
  9. "sort"
  10. "strconv"
  11. "time"
  12. )
  13. func ImportAiPredictModelIndexAndData(imports []*aiPredictModel.AiPredictModelImportData, adminId int, adminRealName string) (err error) {
  14. if len(imports) == 0 {
  15. return
  16. }
  17. // 查询已存在的标的
  18. indexOb := new(aiPredictModel.AiPredictModelIndex)
  19. indexNameItem := make(map[string]*aiPredictModel.AiPredictModelIndex)
  20. {
  21. list, e := indexOb.GetItemsByCondition("", make([]interface{}, 0), []string{}, "")
  22. if e != nil {
  23. err = fmt.Errorf("获取标的失败, %v", e)
  24. return
  25. }
  26. for _, v := range list {
  27. indexNameItem[v.IndexName] = v
  28. }
  29. }
  30. updateCols := []string{indexOb.Cols().ClassifyId, indexOb.Cols().ModelFramework, indexOb.Cols().PredictDate, indexOb.Cols().PredictValue, indexOb.Cols().DirectionAccuracy, indexOb.Cols().AbsoluteDeviation, indexOb.Cols().ExtraConfig, indexOb.Cols().SysUserId, indexOb.Cols().SysUserRealName, indexOb.Cols().ModifyTime}
  31. updateIndexes := make([]*aiPredictModel.AiPredictModelImportData, 0)
  32. createIndexes := make([]*aiPredictModel.AiPredictModelImportData, 0)
  33. maxSort, err := indexOb.GetSortMax()
  34. if err != nil {
  35. err = fmt.Errorf("获取标的最大排序失败, %v", err)
  36. return
  37. }
  38. for _, v := range imports {
  39. exist := indexNameItem[v.Index.IndexName]
  40. // 编辑
  41. if exist != nil {
  42. // 图例信息
  43. if exist.ExtraConfig != "" && v.Index.ExtraConfig != "" {
  44. var oldConfig, newConfig aiPredictModel.AiPredictModelIndexExtraConfig
  45. if e := json.Unmarshal([]byte(exist.ExtraConfig), &oldConfig); e != nil {
  46. err = fmt.Errorf("标的原配置解析失败, Config: %s, Err: %v", exist.ExtraConfig, e)
  47. return
  48. }
  49. if e := json.Unmarshal([]byte(v.Index.ExtraConfig), &newConfig); e != nil {
  50. err = fmt.Errorf("标的新配置解析失败, Config: %s, Err: %v", v.Index.ExtraConfig, e)
  51. return
  52. }
  53. oldConfig.DailyChart.PredictLegendName = newConfig.DailyChart.PredictLegendName
  54. b, _ := json.Marshal(oldConfig)
  55. v.Index.ExtraConfig = string(b)
  56. }
  57. v.Index.AiPredictModelIndexId = exist.AiPredictModelIndexId
  58. v.Index.IndexCode = exist.IndexCode
  59. updateIndexes = append(updateIndexes, v)
  60. continue
  61. }
  62. // 新增标的/图表
  63. indexCode, e := utils.GenerateEdbCode(1, "IPM")
  64. if e != nil {
  65. err = fmt.Errorf("生成标的编码失败, %v", e)
  66. return
  67. }
  68. v.Index.IndexCode = indexCode
  69. v.Charts = GetAiPredictCharts(v.Index.IndexName, adminId, adminRealName)
  70. maxSort = maxSort + 1
  71. v.Index.Sort = maxSort
  72. createIndexes = append(createIndexes, v)
  73. }
  74. // 新增/更新指标
  75. chartIds, e := indexOb.ImportIndexAndData(createIndexes, updateIndexes, updateCols)
  76. if e != nil {
  77. err = fmt.Errorf("导入指标失败, %v", e)
  78. return
  79. }
  80. // 更新图表ES
  81. if len(chartIds) == 0 {
  82. return
  83. }
  84. go func() {
  85. for _, v := range chartIds {
  86. data.EsAddOrEditChartInfo(v)
  87. }
  88. }()
  89. return
  90. }
  91. func GetAiPredictChartDetailByData(indexItem *aiPredictModel.AiPredictModelIndex, indexData []*aiPredictModel.AiPredictModelData, source int) (resp *data_manage.ChartInfoDetailResp, err error) {
  92. resp = new(data_manage.ChartInfoDetailResp)
  93. // 标的配置
  94. var extraConfig aiPredictModel.AiPredictModelIndexExtraConfig
  95. if indexItem.ExtraConfig != "" {
  96. if e := json.Unmarshal([]byte(indexItem.ExtraConfig), &extraConfig); e != nil {
  97. err = fmt.Errorf("标的额外配置解析失败, Config: %s, Err: %v", indexItem.ExtraConfig, e)
  98. return
  99. }
  100. }
  101. // 图表信息
  102. var predictLegendName, confLeftMin, confLeftMax, unit string
  103. if source == aiPredictModel.ModelDataSourceDaily {
  104. predictLegendName = extraConfig.DailyChart.PredictLegendName
  105. if predictLegendName == "" {
  106. predictLegendName = "Predicted"
  107. }
  108. unit = extraConfig.DailyChart.Unit
  109. confLeftMin = extraConfig.DailyChart.LeftMin
  110. confLeftMax = extraConfig.DailyChart.LeftMax
  111. }
  112. if source == aiPredictModel.ModelDataSourceMonthly {
  113. predictLegendName = "预测值"
  114. unit = extraConfig.MonthlyChart.Unit
  115. confLeftMin = extraConfig.MonthlyChart.LeftMin
  116. confLeftMax = extraConfig.MonthlyChart.LeftMax
  117. }
  118. // 这里简单兼容下吧,暂时就不修数据了
  119. if confLeftMin == "" {
  120. confLeftMin = indexItem.LeftMin
  121. }
  122. if confLeftMax == "" {
  123. confLeftMax = indexItem.LeftMax
  124. }
  125. // 获取指标对应的图表
  126. chartSourceMapping := map[int]int{
  127. aiPredictModel.ModelDataSourceMonthly: utils.CHART_SOURCE_AI_PREDICT_MODEL_MONTHLY,
  128. aiPredictModel.ModelDataSourceDaily: utils.CHART_SOURCE_AI_PREDICT_MODEL_DAILY,
  129. }
  130. chartInfo, e := data_manage.GetAiPredictChartInfoByIndexId(chartSourceMapping[source], indexItem.AiPredictModelIndexId)
  131. if e != nil && !utils.IsErrNoRow(e) {
  132. err = fmt.Errorf("获取标的图表失败, %v", e)
  133. return
  134. }
  135. // 获取曲线图主题样式
  136. chartView := new(data_manage.ChartInfoView)
  137. if chartInfo != nil && chartInfo.ChartInfoId > 0 {
  138. chartView.ChartInfoId = chartInfo.ChartInfoId
  139. chartView.ChartName = chartInfo.ChartName
  140. chartView.ChartNameEn = chartInfo.ChartNameEn
  141. chartView.Source = chartInfo.Source
  142. chartView.ChartImage = chartInfo.ChartImage
  143. } else {
  144. chartView.ChartName = indexItem.IndexName
  145. chartView.ChartNameEn = indexItem.IndexName
  146. }
  147. chartView.ChartType = utils.CHART_SOURCE_DEFAULT
  148. chartTheme, e := data.GetChartThemeConfig(0, chartView.ChartType, utils.CHART_TYPE_CURVE)
  149. if e != nil {
  150. err = fmt.Errorf("获取图表主题样式失败, %v", e)
  151. return
  152. }
  153. chartView.ChartThemeStyle = chartTheme.Config
  154. chartView.ChartThemeId = chartTheme.ChartThemeId
  155. chartView.ChartName = indexItem.IndexName
  156. chartView.ChartNameEn = indexItem.IndexName
  157. chartView.DateType = 3
  158. chartView.Calendar = "公历"
  159. chartView.ChartSource = "AI预测模型"
  160. chartView.ChartSourceEn = "AI预测模型"
  161. chartView.Unit = unit
  162. chartView.UnitEn = unit
  163. // EdbList-固定一条为标的实际值、一条为预测值
  164. edbList := make([]*data_manage.ChartEdbInfoMapping, 0)
  165. edbActual, edbPredict := new(data_manage.ChartEdbInfoMapping), new(data_manage.ChartEdbInfoMapping)
  166. edbActual.EdbName = indexItem.IndexName
  167. edbActual.EdbNameEn = indexItem.IndexName
  168. edbActual.IsAxis = 1
  169. edbActual.Unit = unit
  170. edbActual.UnitEn = unit
  171. edbPredict.EdbName = predictLegendName
  172. edbPredict.EdbNameEn = predictLegendName
  173. edbPredict.IsAxis = 1
  174. edbPredict.Unit = unit
  175. edbPredict.UnitEn = unit
  176. actualData, predictData := make([]*data_manage.EdbDataList, 0), make([]*data_manage.EdbDataList, 0)
  177. var startDate, endDate time.Time
  178. var actualValues, predictValues []float64
  179. var actualNewest, predictNewest bool
  180. var actualLatestTimestamp int64 // 实际值最后一天的时间戳,作为日度图表的分割线
  181. for k, v := range indexData {
  182. // 如果实际值和预测值都是null那么该日期无效直接忽略
  183. if !v.Value.Valid && !v.PredictValue.Valid {
  184. continue
  185. }
  186. // 将有效值加入[]float64,最后取极值
  187. if v.Value.Valid {
  188. actualValues = append(actualValues, v.Value.Float64)
  189. }
  190. if v.PredictValue.Valid {
  191. predictValues = append(predictValues, v.PredictValue.Float64)
  192. }
  193. // 开始结束时间
  194. if k == 0 {
  195. startDate = v.DataTime
  196. endDate = v.CreateTime
  197. }
  198. if v.DataTime.Before(startDate) {
  199. startDate = v.DataTime
  200. }
  201. if v.DataTime.After(endDate) {
  202. endDate = v.DataTime
  203. }
  204. // 指标数据
  205. if v.Value.Valid {
  206. if !actualNewest {
  207. edbActual.LatestDate = v.DataTime.Format(utils.FormatDate)
  208. edbActual.LatestValue = v.Value.Float64
  209. actualLatestTimestamp = v.DataTime.UnixNano() / 1e6
  210. actualNewest = true
  211. }
  212. actualData = append(actualData, &data_manage.EdbDataList{
  213. DataTime: v.DataTime.Format(utils.FormatDate),
  214. Value: v.Value.Float64,
  215. DataTimestamp: v.DataTimestamp,
  216. })
  217. }
  218. if v.PredictValue.Valid {
  219. if !predictNewest {
  220. edbPredict.LatestDate = v.DataTime.Format(utils.FormatDate)
  221. edbPredict.LatestValue = v.Value.Float64
  222. predictNewest = true
  223. }
  224. predictData = append(predictData, &data_manage.EdbDataList{
  225. DataTime: v.DataTime.Format(utils.FormatDate),
  226. Value: v.PredictValue.Float64,
  227. DataTimestamp: v.DataTimestamp,
  228. })
  229. }
  230. }
  231. // 图表数据这里均做一个升序排序
  232. sort.Slice(actualData, func(i, j int) bool {
  233. return actualData[i].DataTimestamp < actualData[j].DataTimestamp
  234. })
  235. sort.Slice(predictData, func(i, j int) bool {
  236. return predictData[i].DataTimestamp < predictData[j].DataTimestamp
  237. })
  238. // 极值
  239. actualMin, actualMax := utils.FindMinMax(actualValues)
  240. predictMin, predictMax := utils.FindMinMax(predictValues)
  241. edbActual.MinData = actualMin
  242. edbActual.MaxData = actualMax
  243. edbPredict.MinData = predictMin
  244. edbPredict.MaxData = predictMax
  245. edbActual.DataList = actualData
  246. edbPredict.DataList = predictData
  247. edbList = append(edbList, edbActual, edbPredict)
  248. // 上下限
  249. if confLeftMin != "" {
  250. chartView.LeftMin = confLeftMin
  251. } else {
  252. leftMin := actualMin
  253. if leftMin > predictMin {
  254. leftMin = predictMin
  255. }
  256. chartView.LeftMin = fmt.Sprint(leftMin)
  257. }
  258. if confLeftMax != "" {
  259. chartView.LeftMax = confLeftMax
  260. } else {
  261. leftMax := actualMax
  262. if leftMax < predictMax {
  263. leftMax = predictMax
  264. }
  265. chartView.LeftMax = fmt.Sprint(leftMax)
  266. }
  267. chartView.StartDate = startDate.Format(utils.FormatDate)
  268. chartView.EndDate = endDate.Format(utils.FormatDate)
  269. // 日度图表的分割线日期
  270. if source == aiPredictModel.ModelDataSourceDaily {
  271. var dataResp struct {
  272. ActualLatestTimestamp int64
  273. }
  274. dataResp.ActualLatestTimestamp = actualLatestTimestamp
  275. resp.DataResp = dataResp
  276. }
  277. resp.ChartInfo = chartView
  278. resp.EdbInfoList = edbList
  279. return
  280. }
  281. // GetAiPredictCharts 获取AI预测模型图表
  282. func GetAiPredictCharts(indexName string, adminId int, adminRealName string) (charts []*aiPredictModel.AiPredictModelImportCharts) {
  283. charts = make([]*aiPredictModel.AiPredictModelImportCharts, 0)
  284. // 日度/月度图表
  285. frequencyArr := []int{aiPredictModel.ModelDataSourceMonthly, aiPredictModel.ModelDataSourceDaily}
  286. sourceMapping := map[int]int{
  287. aiPredictModel.ModelDataSourceMonthly: utils.CHART_SOURCE_AI_PREDICT_MODEL_MONTHLY,
  288. aiPredictModel.ModelDataSourceDaily: utils.CHART_SOURCE_AI_PREDICT_MODEL_DAILY,
  289. }
  290. suffixNameMapping := map[int]string{
  291. aiPredictModel.ModelDataSourceMonthly: "预测模型/回测",
  292. aiPredictModel.ModelDataSourceDaily: "预测模型",
  293. }
  294. for _, v := range frequencyArr {
  295. chartSource := sourceMapping[v]
  296. newChart := new(aiPredictModel.AiPredictModelImportCharts)
  297. // 新增图表
  298. chartName := fmt.Sprintf("%s%s", indexName, suffixNameMapping[v])
  299. chartInfo := new(data_manage.ChartInfo)
  300. chartInfo.ChartName = chartName
  301. chartInfo.ChartNameEn = chartName
  302. chartInfo.ChartType = utils.CHART_TYPE_CURVE
  303. chartInfo.Calendar = "公历"
  304. chartInfo.SysUserId = adminId
  305. chartInfo.SysUserRealName = adminRealName
  306. chartInfo.CreateTime = time.Now()
  307. chartInfo.ModifyTime = time.Now()
  308. chartInfo.Source = chartSource
  309. time.Sleep(time.Microsecond)
  310. chartInfo.UniqueCode = utils.MD5(utils.CHART_PREFIX + "_" + strconv.FormatInt(time.Now().UnixNano(), 10))
  311. newChart.ChartInfo = chartInfo
  312. // chart_edb_mapping中edb_info_id为标的ID
  313. edbMapping := new(data_manage.ChartEdbMapping)
  314. //edbMapping.EdbInfoId = indexId
  315. //edbMapping.UniqueCode = utils.MD5(fmt.Sprint(utils.CHART_PREFIX, "_", indexId, "_", strconv.FormatInt(time.Now().UnixNano(), 10)))
  316. edbMapping.Source = chartSource
  317. edbMapping.CreateTime = time.Now().Local()
  318. edbMapping.ModifyTime = time.Now().Local()
  319. newChart.EdbMappings = append(newChart.EdbMappings, edbMapping)
  320. charts = append(charts, newChart)
  321. }
  322. return
  323. }
  324. // FixAiPredictCharts 修复AI预测模型图表
  325. func FixAiPredictCharts() {
  326. var err error
  327. defer func() {
  328. if err != nil {
  329. fmt.Println(err)
  330. }
  331. fmt.Println("修复完成")
  332. }()
  333. fmt.Println("开始修复")
  334. indexOb := new(aiPredictModel.AiPredictModelIndex)
  335. indexes, e := indexOb.GetItemsByCondition("", make([]interface{}, 0), []string{}, "")
  336. if e != nil {
  337. err = fmt.Errorf("获取所有标的失败, %v", e)
  338. return
  339. }
  340. // 日度/月度图表
  341. frequencyArr := []int{aiPredictModel.ModelDataSourceMonthly, aiPredictModel.ModelDataSourceDaily}
  342. sourceMapping := map[int]int{
  343. aiPredictModel.ModelDataSourceMonthly: utils.CHART_SOURCE_AI_PREDICT_MODEL_MONTHLY,
  344. aiPredictModel.ModelDataSourceDaily: utils.CHART_SOURCE_AI_PREDICT_MODEL_DAILY,
  345. }
  346. suffixNameMapping := map[int]string{
  347. aiPredictModel.ModelDataSourceMonthly: "预测模型/回测",
  348. aiPredictModel.ModelDataSourceDaily: "预测模型",
  349. }
  350. chartOb := new(data_manage.ChartInfo)
  351. for _, v := range indexes {
  352. for _, fre := range frequencyArr {
  353. chartSource := sourceMapping[fre]
  354. item, e := data_manage.GetAiPredictChartInfoByIndexId(chartSource, v.AiPredictModelIndexId)
  355. if e != nil && !utils.IsErrNoRow(e) {
  356. err = fmt.Errorf("获取AI预测模型图表失败, %v", e)
  357. return
  358. }
  359. // 由于标的名称是固定的所以chart_info没有什么可更新的, 已加入过就忽略
  360. if item != nil && item.ChartInfoId > 0 {
  361. fmt.Printf("标的%d-%d图表已存在, continue\n", v.AiPredictModelIndexId, chartSource)
  362. continue
  363. }
  364. // 新增图表
  365. chartName := fmt.Sprintf("%s%s", v.IndexName, suffixNameMapping[fre])
  366. chartInfo := new(data_manage.ChartInfo)
  367. chartInfo.ChartName = chartName
  368. chartInfo.ChartNameEn = chartName
  369. chartInfo.ChartType = utils.CHART_TYPE_CURVE
  370. chartInfo.Calendar = "公历"
  371. chartInfo.SysUserId = v.SysUserId
  372. chartInfo.SysUserRealName = v.SysUserRealName
  373. chartInfo.CreateTime = time.Now()
  374. chartInfo.ModifyTime = time.Now()
  375. chartInfo.Source = chartSource
  376. time.Sleep(time.Microsecond)
  377. chartInfo.UniqueCode = utils.MD5(utils.CHART_PREFIX + "_" + strconv.FormatInt(time.Now().UnixNano(), 10))
  378. // chart_edb_mapping中edb_info_id为标的ID
  379. mappings := make([]*data_manage.ChartEdbMapping, 0)
  380. edbMapping := new(data_manage.ChartEdbMapping)
  381. edbMapping.EdbInfoId = v.AiPredictModelIndexId
  382. edbMapping.UniqueCode = utils.MD5(fmt.Sprint(utils.CHART_PREFIX, "_", v.AiPredictModelIndexId, "_", strconv.FormatInt(time.Now().UnixNano(), 10)))
  383. edbMapping.Source = chartSource
  384. edbMapping.CreateTime = time.Now().Local()
  385. edbMapping.ModifyTime = time.Now().Local()
  386. mappings = append(mappings, edbMapping)
  387. // 新增图表
  388. if e = chartOb.AddChartInfoAndEdbMappings(chartInfo, mappings); e != nil {
  389. err = fmt.Errorf("新增图表及mapping失败, %v", e)
  390. return
  391. }
  392. // 写入ES
  393. if chartInfo.ChartInfoId <= 0 {
  394. err = fmt.Errorf("图表ID有误")
  395. return
  396. }
  397. go data.EsAddOrEditChartInfo(chartInfo.ChartInfoId)
  398. }
  399. }
  400. return
  401. }