98 lines
2.1 KiB
Go
98 lines
2.1 KiB
Go
package service
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import (
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"level_go/internal/model"
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"math"
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"sort"
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"gorm.io/gorm"
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)
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type StockService struct {
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DB *gorm.DB
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}
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func roundTo4(val float64) float64 {
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return math.Round(val*10000) / 10000
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}
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func (s *StockService) AnalyzePerformance(startDate, endDate string) ([]model.AnalysisResponse, error) {
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var results []model.AnalysisResponse
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var limits []struct {
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TsCode string
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Name string
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Open float64
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High float64
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}
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// 1. 查找涨停股票
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query := `
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SELECT l.ts_code, l.name, d.open, d.high
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FROM stock_limit_data l
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LEFT JOIN stock_daily d ON l.ts_code = d.ts_code AND l.trade_date = d.trade_date
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WHERE l.trade_date = ? AND l.status = 1`
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if err := s.DB.Raw(query, startDate).Scan(&limits).Error; err != nil {
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return nil, err
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}
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// 2. 分析区间数据
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for _, stock := range limits {
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var dailies []model.StockDaily
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s.DB.Where("ts_code = ? AND trade_date BETWEEN ? AND ?", stock.TsCode, startDate, endDate).
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Order("trade_date ASC").Find(&dailies)
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if len(dailies) == 0 {
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continue
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}
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// A. 找最高点
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maxPrice := -1.0
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maxIdx := 0
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for i, d := range dailies {
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if d.High >= maxPrice {
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maxPrice = d.High
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maxIdx = i
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}
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}
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// B. 找最高点后的最低点
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postData := dailies[maxIdx+1:]
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var minLow, dropPct, reboundPct float64
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if len(postData) > 0 {
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minLow = postData[0].Low
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for _, p := range postData {
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if p.Low < minLow {
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minLow = p.Low
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}
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}
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lastClose := postData[len(postData)-1].Close
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dropPct = roundTo4(((maxPrice - minLow) / maxPrice) * 100)
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if minLow > 0 {
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reboundPct = roundTo4(((lastClose - minLow) / minLow) * 100)
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}
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}
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results = append(results, model.AnalysisResponse{
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Code: stock.TsCode,
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Name: stock.Name,
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DayOpen: stock.Open,
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DayHigh: stock.High,
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MaxHigh: maxPrice,
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MaxDate: dailies[maxIdx].TradeDate.Format("2006-01-02"),
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PostMinLow: minLow,
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DropPct: dropPct,
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ReboundPct: reboundPct,
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})
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}
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// 3. 按降幅排序
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sort.Slice(results, func(i, j int) bool {
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return results[i].DropPct > results[j].DropPct
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})
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return results, nil
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}
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