trade_analysis_data.go 24 KB

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  1. package trade_analysis
  2. import (
  3. "eta/eta_api/models/data_manage"
  4. tradeAnalysisModel "eta/eta_api/models/data_manage/trade_analysis"
  5. "eta/eta_api/services/data"
  6. "eta/eta_api/utils"
  7. "fmt"
  8. "sort"
  9. "strings"
  10. "time"
  11. )
  12. // FormatCompanyTradeData2EdbMappings [公司-合约加总]转为指标数据
  13. func FormatCompanyTradeData2EdbMappings(companyTradeData []*tradeAnalysisModel.ContractCompanyTradeData, tradeType, dateType, dateTypeNum int, startDate, endDate string, chartEdbList []*data_manage.ChartSaveItem) (edbMappings []*data_manage.ChartEdbInfoMapping, chartName string, err error) {
  14. edbMappings = make([]*data_manage.ChartEdbInfoMapping, 0)
  15. // 期货公司名称作为标识进行匹配
  16. edbMap := make(map[string]*data_manage.ChartSaveItem)
  17. if len(chartEdbList) > 0 {
  18. for _, v := range chartEdbList {
  19. edbMap[v.UniqueFlag] = v
  20. }
  21. }
  22. for k, v := range companyTradeData {
  23. mapping := new(data_manage.ChartEdbInfoMapping)
  24. mapping.EdbName = v.CompanyName
  25. mapping.EdbNameEn = v.CompanyName
  26. mapping.EdbAliasName = v.CompanyName
  27. mapping.EdbAliasNameEn = v.CompanyName
  28. mapping.Frequency = "日度"
  29. mapping.FrequencyEn = data.GetFrequencyEn(mapping.Frequency)
  30. mapping.SourceName = utils.SourceNameTradeAnalysis
  31. mapping.Source = utils.CHART_SOURCE_TRADE_ANALYSIS_PROCESS
  32. mapping.IsAxis = 1
  33. mapping.EdbInfoType = 1
  34. mapping.StartDate = v.StartDate.Format(utils.FormatDate)
  35. mapping.EndDate = v.EndDate.Format(utils.FormatDate)
  36. mapping.ConvertUnit = tradeAnalysisModel.WarehouseDefaultUnit // 固定单位
  37. mapping.UniqueFlag = v.CompanyName // 期货公司名称作为每条曲线的唯一标识
  38. // 有配置那么取配置中的图例名称和左右轴
  39. edbConf := edbMap[mapping.UniqueFlag]
  40. if edbConf != nil {
  41. mapping.EdbName = edbConf.EdbAliasName
  42. mapping.EdbNameEn = edbConf.EdbAliasName
  43. mapping.EdbAliasName = edbConf.EdbAliasName
  44. mapping.EdbAliasNameEn = edbConf.EdbAliasName
  45. mapping.IsAxis = edbConf.IsAxis
  46. }
  47. // 根据参数取日期范围
  48. var startTime, endTime time.Time
  49. if dateType > 0 {
  50. st, ed := utils.GetDateByDateTypeV2(dateType, startDate, endDate, dateTypeNum, 0)
  51. if st != "" {
  52. startTime, _ = time.ParseInLocation(utils.FormatDate, st, time.Local)
  53. }
  54. if startTime.IsZero() {
  55. startTime = v.StartDate
  56. }
  57. if ed != "" {
  58. endTime, _ = time.ParseInLocation(utils.FormatDate, ed, time.Local)
  59. }
  60. if endTime.IsZero() {
  61. endTime = v.EndDate
  62. }
  63. }
  64. // 指标数据和最值
  65. edbData := make([]*data_manage.EdbDataList, 0)
  66. var minData, maxData float64
  67. for dk, dv := range v.DataList {
  68. if dv.Date.Before(startTime) || dv.Date.After(endTime) {
  69. continue
  70. }
  71. // 交易方向
  72. var val float64
  73. if tradeType == tradeAnalysisModel.WarehouseBuyChartType {
  74. if dv.BuyValType == tradeAnalysisModel.TradeDataTypeNull {
  75. continue
  76. }
  77. val = float64(dv.BuyVal)
  78. }
  79. if tradeType == tradeAnalysisModel.WarehouseSoldChartType {
  80. if dv.SoldValType == tradeAnalysisModel.TradeDataTypeNull {
  81. continue
  82. }
  83. val = float64(dv.SoldVal)
  84. }
  85. if tradeType == tradeAnalysisModel.WarehousePureBuyChartType {
  86. if dv.PureBuyValType == tradeAnalysisModel.TradeDataTypeNull {
  87. continue
  88. }
  89. val = float64(dv.PureBuyVal)
  90. }
  91. if dk == 0 {
  92. minData = val
  93. maxData = val
  94. }
  95. if val < minData {
  96. minData = val
  97. }
  98. if val > maxData {
  99. maxData = val
  100. }
  101. edbData = append(edbData, &data_manage.EdbDataList{
  102. DataTime: dv.Date.Format(utils.FormatDate),
  103. DataTimestamp: dv.Date.UnixNano() / 1e6,
  104. Value: val,
  105. })
  106. }
  107. mapping.MinData = minData
  108. mapping.MaxData = maxData
  109. mapping.DataList = edbData
  110. edbMappings = append(edbMappings, mapping)
  111. // 图表默认名称
  112. if k == 0 {
  113. chartName += strings.ReplaceAll(v.ClassifyType, ",", "")
  114. }
  115. chartName += v.CompanyName
  116. }
  117. // 图表名称后缀
  118. chartName += tradeAnalysisModel.WarehouseTypeSuffixNames[tradeType]
  119. return
  120. }
  121. func GetOriginTradeData(exchange, classifyName string, contracts, companies []string, predictRatio float64) (companyTradeData []*tradeAnalysisModel.ContractCompanyTradeData, err error) {
  122. // 各原始数据表期货公司名称不一致
  123. companyMap := make(map[string]string)
  124. {
  125. ob := new(tradeAnalysisModel.TradeFuturesCompany)
  126. list, e := ob.GetItemsByCondition(``, make([]interface{}, 0), []string{}, "")
  127. if e != nil {
  128. err = fmt.Errorf("获取期货公司名称失败: %v", e)
  129. return
  130. }
  131. switch exchange {
  132. case "zhengzhou":
  133. for _, v := range list {
  134. companyMap[v.ZhengzhouName] = v.CompanyName
  135. }
  136. case "dalian":
  137. for _, v := range list {
  138. companyMap[v.DalianName] = v.CompanyName
  139. }
  140. case "shanghai":
  141. for _, v := range list {
  142. companyMap[v.ShanghaiName] = v.CompanyName
  143. }
  144. case "cffex":
  145. for _, v := range list {
  146. companyMap[v.CffexName] = v.CompanyName
  147. }
  148. case "ine":
  149. for _, v := range list {
  150. companyMap[v.IneName] = v.CompanyName
  151. }
  152. case "guangzhou":
  153. for _, v := range list {
  154. companyMap[v.GuangzhouName] = v.CompanyName
  155. }
  156. }
  157. }
  158. var queryCompanies []string
  159. for _, v := range companies {
  160. // TOP20用空名称去查询
  161. if v == tradeAnalysisModel.TradeFuturesCompanyTop20 {
  162. queryCompanies = append(queryCompanies, "")
  163. continue
  164. }
  165. companyName, ok := companyMap[v]
  166. if !ok {
  167. utils.FileLog.Info(fmt.Sprintf("交易所%s公司名称映射不存在: %s", exchange, v))
  168. continue
  169. }
  170. queryCompanies = append(queryCompanies, companyName)
  171. }
  172. // TODO:(广期所查询方式不一样)获取多单/空单原始数据
  173. originList, e := tradeAnalysisModel.GetTradeDataByClassifyAndCompany(exchange, classifyName, contracts, queryCompanies)
  174. if e != nil {
  175. err = fmt.Errorf("获取多空单原始数据失败, %v", e)
  176. return
  177. }
  178. keyItems := make(map[string]*tradeAnalysisModel.ContractCompanyTradeData)
  179. keyDateData := make(map[string]*tradeAnalysisModel.ContractCompanyTradeDataList)
  180. keyDateDataExist := make(map[string]bool)
  181. for _, v := range originList {
  182. // TOP20对应数据库中的空名称
  183. companyName := v.CompanyName
  184. if companyName == "" {
  185. companyName = tradeAnalysisModel.TradeFuturesCompanyTop20
  186. }
  187. k := fmt.Sprintf("%s-%s", v.ClassifyType, companyName)
  188. if keyItems[k] == nil {
  189. keyItems[k] = new(tradeAnalysisModel.ContractCompanyTradeData)
  190. keyItems[k].CompanyName = companyName
  191. keyItems[k].ClassifyType = v.ClassifyType
  192. keyItems[k].DataList = make([]*tradeAnalysisModel.ContractCompanyTradeDataList, 0)
  193. }
  194. kd := fmt.Sprintf("%s-%s", k, v.DataTime.Format(utils.FormatDate))
  195. if keyDateData[kd] == nil {
  196. keyDateData[kd] = new(tradeAnalysisModel.ContractCompanyTradeDataList)
  197. keyDateData[kd].Date = v.DataTime
  198. }
  199. if v.ValType == 1 {
  200. keyDateData[kd].BuyVal = v.Val
  201. keyDateData[kd].BuyValType = tradeAnalysisModel.TradeDataTypeOrigin
  202. keyDateData[kd].BuyChange = v.ValChange
  203. keyDateData[kd].BuyChangeType = tradeAnalysisModel.TradeDataTypeOrigin
  204. }
  205. if v.ValType == 2 {
  206. keyDateData[kd].SoldVal = v.Val
  207. keyDateData[kd].SoldValType = tradeAnalysisModel.TradeDataTypeOrigin
  208. keyDateData[kd].SoldChange = v.ValChange
  209. keyDateData[kd].SoldChangeType = tradeAnalysisModel.TradeDataTypeOrigin
  210. }
  211. if !keyDateDataExist[kd] {
  212. keyItems[k].DataList = append(keyItems[k].DataList, keyDateData[kd])
  213. keyDateDataExist[kd] = true
  214. }
  215. }
  216. // TODO:(广期所查询方式不一样)获取[合约]每日的末位多空单
  217. contractLastBuyDateVal := make(map[string]map[time.Time]int)
  218. contractLastSoldDateVal := make(map[string]map[time.Time]int)
  219. {
  220. lastOriginList, e := tradeAnalysisModel.GetLastTradeDataByClassify(exchange, classifyName, contracts)
  221. if e != nil {
  222. err = fmt.Errorf("获取末位多空单原始数据失败, %v", e)
  223. return
  224. }
  225. for _, v := range lastOriginList {
  226. if v.ValType == 1 {
  227. if contractLastBuyDateVal[v.ClassifyType] == nil {
  228. contractLastBuyDateVal[v.ClassifyType] = make(map[time.Time]int)
  229. }
  230. contractLastBuyDateVal[v.ClassifyType][v.DataTime] = v.Val
  231. continue
  232. }
  233. if contractLastSoldDateVal[v.ClassifyType] == nil {
  234. contractLastSoldDateVal[v.ClassifyType] = make(map[time.Time]int)
  235. }
  236. contractLastSoldDateVal[v.ClassifyType][v.DataTime] = v.Val
  237. }
  238. }
  239. // 填充[合约-公司]预估数据, 并根据[公司-多合约]分组, [公司]算作一个指标, 指标值为[多个合约]的计算加总
  240. companyContracts := make(map[string][]*tradeAnalysisModel.ContractCompanyTradeData)
  241. for _, v := range keyItems {
  242. td, fd, ed, e := PredictingTradeData(v.DataList, contractLastBuyDateVal[v.ClassifyType], contractLastSoldDateVal[v.ClassifyType], predictRatio)
  243. if e != nil {
  244. err = fmt.Errorf("数据补全失败, %v", e)
  245. return
  246. }
  247. v.DataList = td
  248. v.StartDate = fd
  249. v.EndDate = ed
  250. if companyContracts[v.CompanyName] == nil {
  251. companyContracts[v.CompanyName] = make([]*tradeAnalysisModel.ContractCompanyTradeData, 0)
  252. }
  253. companyContracts[v.CompanyName] = append(companyContracts[v.CompanyName], v)
  254. }
  255. // 以[公司]为组, 计算合约加总
  256. mussyTradeData := make(map[string]*tradeAnalysisModel.ContractCompanyTradeData)
  257. for k, v := range companyContracts {
  258. companyData := new(tradeAnalysisModel.ContractCompanyTradeData)
  259. companyData.CompanyName = k
  260. companyData.DataList = make([]*tradeAnalysisModel.ContractCompanyTradeDataList, 0)
  261. contractArr := make([]string, 0)
  262. // 合约加总
  263. sumDateData := make(map[time.Time]*tradeAnalysisModel.ContractCompanyTradeDataList)
  264. for _, vv := range v {
  265. contractArr = append(contractArr, vv.ClassifyType)
  266. for _, dv := range vv.DataList {
  267. if sumDateData[dv.Date] == nil {
  268. sumDateData[dv.Date] = new(tradeAnalysisModel.ContractCompanyTradeDataList)
  269. sumDateData[dv.Date].Date = dv.Date
  270. }
  271. // 数据类型以第一个非零值为准, 只处理多空和净多, 变化就不管了
  272. if sumDateData[dv.Date].BuyValType == tradeAnalysisModel.TradeDataTypeNull && dv.BuyValType > tradeAnalysisModel.TradeDataTypeNull {
  273. sumDateData[dv.Date].BuyValType = dv.BuyValType
  274. }
  275. if sumDateData[dv.Date].BuyValType == tradeAnalysisModel.TradeDataTypeOrigin && dv.BuyValType == tradeAnalysisModel.TradeDataTypeCalculate {
  276. sumDateData[dv.Date].BuyValType = dv.BuyValType
  277. }
  278. if dv.BuyValType > tradeAnalysisModel.TradeDataTypeNull {
  279. sumDateData[dv.Date].BuyVal += dv.BuyVal
  280. }
  281. // 空单
  282. if sumDateData[dv.Date].SoldValType == tradeAnalysisModel.TradeDataTypeNull && dv.SoldValType > tradeAnalysisModel.TradeDataTypeNull {
  283. sumDateData[dv.Date].SoldValType = dv.SoldValType
  284. }
  285. if sumDateData[dv.Date].SoldValType == tradeAnalysisModel.TradeDataTypeOrigin && dv.SoldValType == tradeAnalysisModel.TradeDataTypeCalculate {
  286. sumDateData[dv.Date].SoldValType = dv.SoldValType
  287. }
  288. if dv.SoldValType > tradeAnalysisModel.TradeDataTypeNull {
  289. sumDateData[dv.Date].SoldVal += dv.SoldVal
  290. }
  291. // 净多单
  292. if sumDateData[dv.Date].PureBuyValType == tradeAnalysisModel.TradeDataTypeNull && dv.PureBuyValType > tradeAnalysisModel.TradeDataTypeNull {
  293. sumDateData[dv.Date].PureBuyValType = dv.PureBuyValType
  294. }
  295. if sumDateData[dv.Date].PureBuyValType == tradeAnalysisModel.TradeDataTypeOrigin && dv.PureBuyValType == tradeAnalysisModel.TradeDataTypeCalculate {
  296. sumDateData[dv.Date].PureBuyValType = dv.PureBuyValType
  297. }
  298. if dv.PureBuyValType > tradeAnalysisModel.TradeDataTypeNull {
  299. sumDateData[dv.Date].PureBuyVal += dv.PureBuyVal
  300. }
  301. }
  302. // 多个合约比对开始结束时间
  303. if companyData.StartDate.IsZero() {
  304. companyData.StartDate = vv.StartDate
  305. }
  306. if vv.StartDate.Before(companyData.StartDate) {
  307. companyData.StartDate = vv.StartDate
  308. }
  309. if companyData.EndDate.IsZero() {
  310. companyData.EndDate = vv.EndDate
  311. }
  312. if vv.EndDate.Before(companyData.EndDate) {
  313. companyData.EndDate = vv.EndDate
  314. }
  315. }
  316. for _, sv := range sumDateData {
  317. companyData.DataList = append(companyData.DataList, sv)
  318. }
  319. sort.Slice(companyData.DataList, func(i, j int) bool {
  320. return companyData.DataList[i].Date.Before(companyData.DataList[j].Date)
  321. })
  322. companyData.ClassifyType = strings.Join(contractArr, ",")
  323. mussyTradeData[k] = companyData
  324. }
  325. // 数据根据公司排序, 不然会随机乱
  326. companyTradeData = make([]*tradeAnalysisModel.ContractCompanyTradeData, 0)
  327. for _, v := range companies {
  328. if mussyTradeData[v] != nil {
  329. companyTradeData = append(companyTradeData, mussyTradeData[v])
  330. }
  331. }
  332. return
  333. }
  334. // PredictingTradeData 根据数据库中的多空数据填充预估数据
  335. func PredictingTradeData(originData []*tradeAnalysisModel.ContractCompanyTradeDataList, lastBuyDateVal, lastSoldDateVal map[time.Time]int, predictRatio float64) (newData []*tradeAnalysisModel.ContractCompanyTradeDataList, firstDate, endDate time.Time, err error) {
  336. // 测试用的验证数据
  337. //lastBuyDateVal, lastSoldDateVal = make(map[time.Time]int), make(map[time.Time]int)
  338. //lastBuyDateVal[time.Date(2024, 7, 16, 0, 0, 0, 0, time.Local)] = 4602
  339. //lastBuyDateVal[time.Date(2024, 7, 17, 0, 0, 0, 0, time.Local)] = 5116
  340. //lastBuyDateVal[time.Date(2024, 7, 18, 0, 0, 0, 0, time.Local)] = 5130
  341. //lastBuyDateVal[time.Date(2024, 7, 19, 0, 0, 0, 0, time.Local)] = 5354
  342. //lastBuyDateVal[time.Date(2024, 7, 22, 0, 0, 0, 0, time.Local)] = 5916
  343. //lastBuyDateVal[time.Date(2024, 7, 23, 0, 0, 0, 0, time.Local)] = 6524
  344. //lastBuyDateVal[time.Date(2024, 7, 26, 0, 0, 0, 0, time.Local)] = 6575
  345. //lastBuyDateVal[time.Date(2024, 7, 29, 0, 0, 0, 0, time.Local)] = 7461
  346. //lastBuyDateVal[time.Date(2024, 7, 30, 0, 0, 0, 0, time.Local)] = 8488
  347. //
  348. //lastSoldDateVal[time.Date(2024, 7, 11, 0, 0, 0, 0, time.Local)] = 5467
  349. //lastSoldDateVal[time.Date(2024, 7, 12, 0, 0, 0, 0, time.Local)] = 5248
  350. //lastSoldDateVal[time.Date(2024, 7, 15, 0, 0, 0, 0, time.Local)] = 5102
  351. //lastSoldDateVal[time.Date(2024, 7, 16, 0, 0, 0, 0, time.Local)] = 4771
  352. //lastSoldDateVal[time.Date(2024, 7, 23, 0, 0, 0, 0, time.Local)] = 5989
  353. //lastSoldDateVal[time.Date(2024, 7, 26, 0, 0, 0, 0, time.Local)] = 6745
  354. //lastSoldDateVal[time.Date(2024, 7, 30, 0, 0, 0, 0, time.Local)] = 7272
  355. //
  356. //originData = make([]*tradeAnalysisModel.ContractCompanyTradeDataList, 0)
  357. //originData = append(originData, &tradeAnalysisModel.ContractCompanyTradeDataList{
  358. // Date: time.Date(2024, 7, 10, 0, 0, 0, 0, time.Local),
  359. // BuyVal: 14324,
  360. // BuyValType: tradeAnalysisModel.TradeDataTypeOrigin,
  361. // BuyChange: -1107,
  362. // BuyChangeType: tradeAnalysisModel.TradeDataTypeOrigin,
  363. // SoldVal: 0,
  364. // SoldValType: tradeAnalysisModel.TradeDataTypeNull,
  365. // SoldChange: 0,
  366. // SoldChangeType: tradeAnalysisModel.TradeDataTypeNull,
  367. //}, &tradeAnalysisModel.ContractCompanyTradeDataList{
  368. // Date: time.Date(2024, 7, 11, 0, 0, 0, 0, time.Local),
  369. // BuyVal: 14280,
  370. // BuyValType: tradeAnalysisModel.TradeDataTypeOrigin,
  371. // BuyChange: -44,
  372. // BuyChangeType: tradeAnalysisModel.TradeDataTypeOrigin,
  373. //}, &tradeAnalysisModel.ContractCompanyTradeDataList{
  374. // Date: time.Date(2024, 7, 12, 0, 0, 0, 0, time.Local),
  375. // BuyVal: 14214,
  376. // BuyValType: tradeAnalysisModel.TradeDataTypeOrigin,
  377. // BuyChange: -66,
  378. // BuyChangeType: tradeAnalysisModel.TradeDataTypeOrigin,
  379. //}, &tradeAnalysisModel.ContractCompanyTradeDataList{
  380. // Date: time.Date(2024, 7, 15, 0, 0, 0, 0, time.Local),
  381. // BuyVal: 14269,
  382. // BuyValType: tradeAnalysisModel.TradeDataTypeOrigin,
  383. // BuyChange: 55,
  384. // BuyChangeType: tradeAnalysisModel.TradeDataTypeOrigin,
  385. //}, &tradeAnalysisModel.ContractCompanyTradeDataList{
  386. // Date: time.Date(2024, 7, 17, 0, 0, 0, 0, time.Local),
  387. // SoldVal: 5254,
  388. // SoldValType: tradeAnalysisModel.TradeDataTypeOrigin,
  389. // SoldChange: 708,
  390. // SoldChangeType: tradeAnalysisModel.TradeDataTypeOrigin,
  391. //}, &tradeAnalysisModel.ContractCompanyTradeDataList{
  392. // Date: time.Date(2024, 7, 18, 0, 0, 0, 0, time.Local),
  393. // SoldVal: 6595,
  394. // SoldValType: tradeAnalysisModel.TradeDataTypeOrigin,
  395. // SoldChange: 1341,
  396. // SoldChangeType: tradeAnalysisModel.TradeDataTypeOrigin,
  397. //}, &tradeAnalysisModel.ContractCompanyTradeDataList{
  398. // Date: time.Date(2024, 7, 19, 0, 0, 0, 0, time.Local),
  399. // SoldVal: 5938,
  400. // SoldValType: tradeAnalysisModel.TradeDataTypeOrigin,
  401. // SoldChange: -657,
  402. // SoldChangeType: tradeAnalysisModel.TradeDataTypeOrigin,
  403. //}, &tradeAnalysisModel.ContractCompanyTradeDataList{
  404. // Date: time.Date(2024, 7, 22, 0, 0, 0, 0, time.Local),
  405. // SoldVal: 6131,
  406. // SoldValType: tradeAnalysisModel.TradeDataTypeOrigin,
  407. // SoldChange: 193,
  408. // SoldChangeType: tradeAnalysisModel.TradeDataTypeOrigin,
  409. //}, &tradeAnalysisModel.ContractCompanyTradeDataList{
  410. // Date: time.Date(2024, 7, 29, 0, 0, 0, 0, time.Local),
  411. // SoldVal: 6679,
  412. // SoldValType: tradeAnalysisModel.TradeDataTypeOrigin,
  413. // SoldChange: 312,
  414. // SoldChangeType: tradeAnalysisModel.TradeDataTypeOrigin,
  415. //})
  416. if len(originData) == 0 {
  417. return
  418. }
  419. if predictRatio < 0 || predictRatio > 1 {
  420. err = fmt.Errorf("估计参数不在0-1之间")
  421. return
  422. }
  423. sort.Slice(originData, func(i, j int) bool {
  424. return originData[i].Date.Before(originData[j].Date)
  425. })
  426. dateVal := make(map[time.Time]*tradeAnalysisModel.ContractCompanyTradeDataList)
  427. for _, v := range originData {
  428. dateVal[v.Date] = v
  429. }
  430. // 生成开始日期-1d(可能会往前面推算一天)至结束日期间的交易日, 以交易日为时间序列遍历
  431. tradeDays := utils.GetTradingDays(originData[0].Date.AddDate(0, 0, -1), originData[len(originData)-1].Date)
  432. for k, v := range tradeDays {
  433. // T日多空均无的情况
  434. //bothLast := false
  435. if dateVal[v] == nil {
  436. // T-1和T+1[原始数据]均无值, 那么T日无数据
  437. hasPrev, hasNext := false, false
  438. if k-1 >= 0 {
  439. hasPrev = true
  440. }
  441. if k+1 <= len(tradeDays)-1 {
  442. hasNext = true
  443. }
  444. if !hasPrev && !hasNext {
  445. continue
  446. }
  447. // T+1有值, 优先从T+1推, 然后继续走下面计算净多单的逻辑
  448. if hasNext {
  449. nextDay := tradeDays[k+1]
  450. if dateVal[nextDay] != nil {
  451. // T+1有多/空及多空变化, 且是原始数据, 那么推出数据并在map中新加一日数据
  452. if dateVal[nextDay].BuyValType == tradeAnalysisModel.TradeDataTypeOrigin && dateVal[nextDay].BuyChangeType == tradeAnalysisModel.TradeDataTypeOrigin {
  453. if _, ok := dateVal[v]; !ok {
  454. dateVal[v] = new(tradeAnalysisModel.ContractCompanyTradeDataList)
  455. dateVal[v].Date = v
  456. }
  457. dateVal[v].BuyVal = dateVal[nextDay].BuyVal - dateVal[nextDay].BuyChange
  458. dateVal[v].BuyValType = tradeAnalysisModel.TradeDataTypeOrigin
  459. }
  460. if dateVal[nextDay].SoldValType == tradeAnalysisModel.TradeDataTypeOrigin && dateVal[nextDay].SoldChangeType == tradeAnalysisModel.TradeDataTypeOrigin {
  461. if _, ok := dateVal[v]; !ok {
  462. dateVal[v] = new(tradeAnalysisModel.ContractCompanyTradeDataList)
  463. dateVal[v].Date = v
  464. }
  465. dateVal[v].SoldVal = dateVal[nextDay].SoldVal - dateVal[nextDay].SoldChange
  466. dateVal[v].SoldValType = tradeAnalysisModel.TradeDataTypeOrigin
  467. }
  468. }
  469. }
  470. // T+1没推出来而T-1有值, 那么T多空均取末位, 计算净多单
  471. _, has := dateVal[v]
  472. if hasPrev && !has {
  473. sv, sok := lastSoldDateVal[v]
  474. bv, bok := lastBuyDateVal[v]
  475. if !sok && !bok {
  476. continue
  477. }
  478. dateVal[v] = new(tradeAnalysisModel.ContractCompanyTradeDataList)
  479. dateVal[v].Date = v
  480. if sok {
  481. dateVal[v].SoldVal = int(predictRatio*float64(sv) + 0.5)
  482. dateVal[v].SoldValType = tradeAnalysisModel.TradeDataTypeCalculate
  483. }
  484. if bok {
  485. dateVal[v].BuyVal = int(predictRatio*float64(bv) + 0.5)
  486. dateVal[v].BuyValType = tradeAnalysisModel.TradeDataTypeCalculate
  487. }
  488. if dateVal[v].BuyValType > tradeAnalysisModel.TradeDataTypeNull && dateVal[v].SoldValType > tradeAnalysisModel.TradeDataTypeNull {
  489. dateVal[v].PureBuyVal = dateVal[v].BuyVal - dateVal[v].SoldVal
  490. dateVal[v].PureBuyValType = tradeAnalysisModel.TradeDataTypeCalculate
  491. }
  492. continue
  493. }
  494. }
  495. // 多空均有的情况下计算净多单
  496. if dateVal[v].BuyValType == tradeAnalysisModel.TradeDataTypeOrigin && dateVal[v].SoldValType == tradeAnalysisModel.TradeDataTypeOrigin {
  497. dateVal[v].PureBuyVal = dateVal[v].BuyVal - dateVal[v].SoldVal
  498. dateVal[v].PureBuyValType = tradeAnalysisModel.TradeDataTypeOrigin // 原始值算出来的也作原始值
  499. }
  500. // 仅有多单, 空单取末位, 计算净多单
  501. if dateVal[v].BuyValType == tradeAnalysisModel.TradeDataTypeOrigin && dateVal[v].SoldValType == tradeAnalysisModel.TradeDataTypeNull {
  502. if sv, ok := lastSoldDateVal[v]; ok {
  503. dateVal[v].SoldVal = int(predictRatio*float64(sv) + 0.5) // 估计参数*末位值, 向上取整
  504. dateVal[v].SoldValType = tradeAnalysisModel.TradeDataTypeCalculate
  505. dateVal[v].PureBuyVal = dateVal[v].BuyVal - dateVal[v].SoldVal
  506. dateVal[v].PureBuyValType = tradeAnalysisModel.TradeDataTypeCalculate
  507. }
  508. }
  509. // 仅有空单, 多单取末位, 计算净多单
  510. if dateVal[v].SoldValType == tradeAnalysisModel.TradeDataTypeOrigin && dateVal[v].BuyValType == tradeAnalysisModel.TradeDataTypeNull {
  511. if sv, ok := lastBuyDateVal[v]; ok {
  512. dateVal[v].BuyVal = int(predictRatio*float64(sv) + 0.5)
  513. dateVal[v].BuyValType = tradeAnalysisModel.TradeDataTypeCalculate
  514. dateVal[v].PureBuyVal = dateVal[v].BuyVal - dateVal[v].SoldVal
  515. dateVal[v].PureBuyValType = tradeAnalysisModel.TradeDataTypeCalculate
  516. }
  517. }
  518. }
  519. // 二次遍历, 计算与T-1的变化值
  520. for k, v := range tradeDays {
  521. // 无T/T-1数据, 忽略
  522. if dateVal[v] == nil {
  523. continue
  524. }
  525. if k-1 < 0 {
  526. continue
  527. }
  528. beforeDay := tradeDays[k-1]
  529. if dateVal[beforeDay] == nil {
  530. continue
  531. }
  532. // 多单变化
  533. if dateVal[v].BuyChangeType == tradeAnalysisModel.TradeDataTypeNull {
  534. if dateVal[v].BuyValType > tradeAnalysisModel.TradeDataTypeNull && dateVal[beforeDay].BuyValType > tradeAnalysisModel.TradeDataTypeNull {
  535. dateVal[v].BuyChange = dateVal[v].BuyVal - dateVal[beforeDay].BuyVal
  536. // 如果当日多单或者前日多单是估计值, 那么多单变化也为估计值
  537. if dateVal[v].BuyValType == tradeAnalysisModel.TradeDataTypeCalculate || dateVal[beforeDay].BuyValType == tradeAnalysisModel.TradeDataTypeCalculate {
  538. dateVal[v].BuyChangeType = tradeAnalysisModel.TradeDataTypeCalculate
  539. }
  540. }
  541. }
  542. // 空单变化
  543. if dateVal[v].SoldChangeType == tradeAnalysisModel.TradeDataTypeNull {
  544. if dateVal[v].SoldValType > tradeAnalysisModel.TradeDataTypeNull && dateVal[beforeDay].SoldValType > tradeAnalysisModel.TradeDataTypeNull {
  545. dateVal[v].SoldChange = dateVal[v].SoldVal - dateVal[beforeDay].SoldVal
  546. // 如果当日空单或者前日空单是估计值, 那么空单变化也为估计值
  547. if dateVal[v].SoldValType == tradeAnalysisModel.TradeDataTypeCalculate || dateVal[beforeDay].SoldValType == tradeAnalysisModel.TradeDataTypeCalculate {
  548. dateVal[v].SoldChangeType = tradeAnalysisModel.TradeDataTypeCalculate
  549. }
  550. }
  551. }
  552. // 净多变化
  553. if dateVal[v].PureBuyChangeType == tradeAnalysisModel.TradeDataTypeNull {
  554. if dateVal[v].PureBuyValType > tradeAnalysisModel.TradeDataTypeNull && dateVal[beforeDay].PureBuyValType > tradeAnalysisModel.TradeDataTypeNull {
  555. dateVal[v].PureBuyChange = dateVal[v].PureBuyVal - dateVal[beforeDay].PureBuyVal
  556. dateVal[v].PureBuyChangeType = tradeAnalysisModel.TradeDataTypeOrigin
  557. // 如果当日净多单或者前日净多单是估计值, 那么净多单变化也为估计值
  558. if dateVal[v].PureBuyValType == tradeAnalysisModel.TradeDataTypeCalculate || dateVal[beforeDay].PureBuyValType == tradeAnalysisModel.TradeDataTypeCalculate {
  559. dateVal[v].PureBuyChangeType = tradeAnalysisModel.TradeDataTypeCalculate
  560. }
  561. }
  562. }
  563. }
  564. // 重新遍历map, 生成数据序列并排序
  565. newData = make([]*tradeAnalysisModel.ContractCompanyTradeDataList, 0)
  566. for _, v := range dateVal {
  567. if v.BuyValType == tradeAnalysisModel.TradeDataTypeNull && v.SoldValType == tradeAnalysisModel.TradeDataTypeNull {
  568. continue
  569. }
  570. newData = append(newData, v)
  571. }
  572. sort.Slice(newData, func(i, j int) bool {
  573. return newData[i].Date.Before(newData[j].Date)
  574. })
  575. if len(newData) > 0 {
  576. firstDate = newData[0].Date
  577. endDate = newData[len(newData)-1].Date
  578. }
  579. return
  580. }