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feat(market): Add 15m/1h timeframes for comprehensive trend analysis
## Problem Merged WebSocket architecture (nofxaios/dev) only supported 3m/4h intervals, but adaptive.txt v5.5.6.1 requires 15m/1h data for: - BTC state evaluation (line 105-107) - Multi-confirmation checklist (line 146, 159) - False breakout detection (line 176, 182) - Confidence scoring (line 197) ## Solution Add 15m and 1h timeframe support across WebSocket pipeline: ### 1. market/monitor.go (+64/-40 lines) - Add klineDataMap15m and klineDataMap1h to WSMonitor struct - Update subKlineTime: ["3m", "4h"] → ["3m", "15m", "1h", "4h"] - Extend initializeHistoricalData() to load 15m/1h historical klines - Update getKlineDataMap() switch to handle all 4 timeframes - Fix bug: line 109 used wrong variable (klines vs klines4h) ### 2. market/types.go (+26/-1 lines) - Add MidTermData15m struct (15-minute short-term trend filtering) - Add MidTermData1h struct (1-hour mid-term trend confirmation) - Update Data struct to include: - MidTermSeries15m *MidTermData15m - MidTermSeries1h *MidTermData1h ### 3. market/data.go (+171/-2 lines) - Update Get() to fetch klines15m and klines1h via WebSocket - Implement calculateMidTermSeries15m() - computes EMA20, MACD, RSI7/14 for 15m - Implement calculateMidTermSeries1h() - computes EMA20, MACD, RSI7/14 for 1h - Update Format() to output 15m/1h series data for AI prompt context ## Impact Assessment ### WebSocket Load (Binance limit: 1024 streams/connection) - 8 coins × 4 timeframes = 32 streams (3% usage) ✅ - 100 coins × 4 timeframes = 400 streams (39% usage) ✅ - 250 coins × 4 timeframes = 1000 streams (98% usage) ⚠️ ### Benefits - Enables adaptive.txt standard mode: 15m/1h/4h multi-timeframe confirmation - Restores false breakout detection: 15m RSI vs 1h RSI divergence checks - Improves confidence scoring: 15m/1h/4h MACD alignment validation - Zero REST API calls (WebSocket cache, no rate limit risk) ## Testing Notes - Monitor initial subscription logs for "已加载 X 的历史K线数据-15m/1h" - Verify AI prompts contain "Mid-term series (15-minute intervals)" section - Check decision logs reference 15m/1h indicators in reasoning Related: adaptive.txt v5.5.6.1 requirements, NoFxAiOS/dev WebSocket merge
This commit is contained in:
ZhouYongyou
@@ -15,9 +15,11 @@ type WSMonitor struct {
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symbols []string
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featuresMap sync.Map
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alertsChan chan Alert
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klineDataMap3m sync.Map // 存储每个交易对的K线历史数据
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klineDataMap4h sync.Map // 存储每个交易对的K线历史数据
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tickerDataMap sync.Map // 存储每个交易对的ticker数据
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klineDataMap3m sync.Map // 存储每个交易对的K线历史数据
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klineDataMap15m sync.Map // 存储每个交易对的15分钟K线历史数据
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klineDataMap1h sync.Map // 存储每个交易对的1小时K线历史数据
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klineDataMap4h sync.Map // 存储每个交易对的K线历史数据
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tickerDataMap sync.Map // 存储每个交易对的ticker数据
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batchSize int
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filterSymbols sync.Map // 使用sync.Map来存储需要监控的币种和其状态
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symbolStats sync.Map // 存储币种统计信息
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@@ -32,7 +34,7 @@ type SymbolStats struct {
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}
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var WSMonitorCli *WSMonitor
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var subKlineTime = []string{"3m", "4h"} // 管理订阅流的K线周期
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var subKlineTime = []string{"3m", "15m", "1h", "4h"} // 管理订阅流的K线周期
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func NewWSMonitor(batchSize int) *WSMonitor {
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WSMonitorCli = &WSMonitor{
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@@ -89,25 +91,40 @@ func (m *WSMonitor) initializeHistoricalData() error {
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defer wg.Done()
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defer func() { <-semaphore }()
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// 获取历史K线数据
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klines, err := apiClient.GetKlines(s, "3m", 100)
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// 获取3分钟历史K线数据
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klines3m, err := apiClient.GetKlines(s, "3m", 100)
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if err != nil {
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log.Printf("获取 %s 历史数据失败: %v", s, err)
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return
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log.Printf("获取 %s 3m历史数据失败: %v", s, err)
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} else if len(klines3m) > 0 {
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m.klineDataMap3m.Store(s, klines3m)
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log.Printf("已加载 %s 的历史K线数据-3m: %d 条", s, len(klines3m))
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}
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if len(klines) > 0 {
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m.klineDataMap3m.Store(s, klines)
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log.Printf("已加载 %s 的历史K线数据-3m: %d 条", s, len(klines))
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// 获取15分钟历史K线数据
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klines15m, err := apiClient.GetKlines(s, "15m", 100)
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if err != nil {
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log.Printf("获取 %s 15m历史数据失败: %v", s, err)
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} else if len(klines15m) > 0 {
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m.klineDataMap15m.Store(s, klines15m)
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log.Printf("已加载 %s 的历史K线数据-15m: %d 条", s, len(klines15m))
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}
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// 获取历史K线数据
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// 获取1小时历史K线数据
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klines1h, err := apiClient.GetKlines(s, "1h", 100)
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if err != nil {
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log.Printf("获取 %s 1h历史数据失败: %v", s, err)
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} else if len(klines1h) > 0 {
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m.klineDataMap1h.Store(s, klines1h)
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log.Printf("已加载 %s 的历史K线数据-1h: %d 条", s, len(klines1h))
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}
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// 获取4小时历史K线数据
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klines4h, err := apiClient.GetKlines(s, "4h", 100)
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if err != nil {
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log.Printf("获取 %s 历史数据失败: %v", s, err)
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return
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}
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if len(klines4h) > 0 {
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m.klineDataMap4h.Store(s, klines)
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log.Printf("已加载 %s 的历史K线数据-4h: %d 条", s, len(klines))
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log.Printf("获取 %s 4h历史数据失败: %v", s, err)
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} else if len(klines4h) > 0 {
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m.klineDataMap4h.Store(s, klines4h)
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log.Printf("已加载 %s 的历史K线数据-4h: %d 条", s, len(klines4h))
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}
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}(symbol)
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}
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@@ -180,11 +197,16 @@ func (m *WSMonitor) handleKlineData(symbol string, ch <-chan []byte, _time strin
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func (m *WSMonitor) getKlineDataMap(_time string) *sync.Map {
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var klineDataMap *sync.Map
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if _time == "3m" {
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switch _time {
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case "3m":
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klineDataMap = &m.klineDataMap3m
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} else if _time == "4h" {
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case "15m":
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klineDataMap = &m.klineDataMap15m
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case "1h":
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klineDataMap = &m.klineDataMap1h
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case "4h":
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klineDataMap = &m.klineDataMap4h
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} else {
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default:
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klineDataMap = &sync.Map{}
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}
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return klineDataMap
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