mirror of
https://github.com/NoFxAiOS/nofx.git
synced 2026-07-09 14:00:57 +08:00
Add multi-timeframe data analysis support
Introduces 15m and 1h timeframes to Data struct and related calculations for more robust multi-timeframe analysis. Updates system prompt to reflect new data sources and analysis methods, and extends Format output to include mid-term series. Enhances signal quality and trend confirmation by leveraging multiple timeframes.
This commit is contained in:
ZhouYongyou
@@ -279,20 +279,35 @@ func buildSystemPrompt(accountEquity float64, btcEthLeverage, altcoinLeverage in
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// === 开仓信号强度 ===
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sb.WriteString("# 🎯 开仓标准（严格）\n\n")
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sb.WriteString("只在**强信号**时开仓，不确定就观望。\n\n")
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sb.WriteString("**你拥有的完整数据**：\n")
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sb.WriteString("- 📊 **原始序列**：3分钟价格序列(MidPrices数组) + 4小时K线序列\n")
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sb.WriteString("- 📈 **技术序列**：EMA20序列、MACD序列、RSI7序列、RSI14序列\n")
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sb.WriteString("- 💰 **资金序列**：成交量序列、持仓量(OI)序列、资金费率\n")
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sb.WriteString("- 🎯 **筛选标记**：AI500评分 / OI_Top排名（如果有标注）\n\n")
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sb.WriteString("**你拥有的完整数据（多时间框架分析）**：\n\n")
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sb.WriteString("**📊 四个时间框架序列**（每个包含最近10个数据点）：\n")
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sb.WriteString("1. **3分钟序列**：用于获取实时价格（当前价格 = 最后一根K线的收盘价）\n")
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sb.WriteString(" - Mid prices, EMA20, MACD, RSI7, RSI14\n")
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sb.WriteString("2. **15分钟序列**：短期趋势过滤（覆盖最近2.5小时）\n")
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sb.WriteString(" - Mid prices, EMA20, MACD, RSI7, RSI14\n")
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sb.WriteString("3. **1小时序列**：中期趋势确认（覆盖最近10小时）\n")
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sb.WriteString(" - Mid prices, EMA20, MACD, RSI7, RSI14\n")
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sb.WriteString("4. **4小时序列**：长期趋势方向（覆盖最近40小时）\n")
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sb.WriteString(" - EMA20 vs EMA50, ATR, Volume, MACD, RSI14\n\n")
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sb.WriteString("**💰 资金数据**：\n")
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sb.WriteString("- 持仓量(OI)变化、资金费率、成交量对比\n\n")
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sb.WriteString("**🎯 多时间框架分析建议**：\n")
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sb.WriteString("- **趋势共振**：当15m/1h/4h三个时间框架方向一致时 → 高信心度信号\n")
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sb.WriteString("- **趋势过滤**：用1h和4h确认主趋势，避免在震荡中交易\n")
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sb.WriteString("- **入场时机**：用15m寻找入场点，确保不在短期逆势位置开仓\n")
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sb.WriteString("- **背离识别**：价格创新高但MACD未创新高（多时间框架对比）\n")
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sb.WriteString("- **假突破过滤**：15m突破但1h/4h未确认 → 可能是假突破\n\n")
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sb.WriteString("**分析方法**（完全由你自主决定）：\n")
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sb.WriteString("- 自由运用序列数据，你可以做但不限于趋势分析、形态识别、支撑阻力、技术阻力位、斐波那契、波动带计算\n")
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sb.WriteString("- 多维度交叉验证（价格+量+OI+指标+序列形态）\n")
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sb.WriteString("- 自由运用多时间框架序列，做趋势分析、形态识别、支撑阻力、背离判断\n")
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sb.WriteString("- 多维度交叉验证（多时间框架 + 量价 + OI + 资金费率）\n")
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sb.WriteString("- 用你认为最有效的方法发现高确定性机会\n")
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sb.WriteString("- 综合信心度 ≥ 75 才开仓\n\n")
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sb.WriteString("- **综合信心度 ≥ 75 才开仓**\n\n")
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sb.WriteString("**避免低质量信号**：\n")
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sb.WriteString("- 单一时间框架分析（必须多时间框架共振）\n")
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sb.WriteString("- 时间框架矛盾（15m上涨但1h/4h下跌）\n")
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sb.WriteString("- 单一维度（只看一个指标）\n")
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sb.WriteString("- 相互矛盾（涨但量萎缩）\n")
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sb.WriteString("- 横盘震荡\n")
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sb.WriteString("- 横盘震荡（多个时间框架都无明确趋势）\n")
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sb.WriteString("- 刚平仓不久（<15分钟）\n\n")
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// === 夏普比率自我进化 ===
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192
market/data.go
192
market/data.go
@@ -21,8 +21,10 @@ type Data struct {
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CurrentRSI7 float64
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OpenInterest *OIData
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FundingRate float64
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IntradaySeries *IntradayData
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LongerTermContext *LongerTermData
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IntradaySeries *IntradayData // 3分钟数据 - 实时价格
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MidTermSeries15m *MidTermData15m // 15分钟数据 - 短期趋势
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MidTermSeries1h *MidTermData1h // 1小时数据 - 中期趋势
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LongerTermContext *LongerTermData // 4小时数据 - 长期趋势
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}
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// OIData Open Interest数据
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@@ -31,7 +33,7 @@ type OIData struct {
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Average float64
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}
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// IntradayData 日内数据(3分钟间隔)
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// IntradayData 日内数据(3分钟间隔) - 主要用于获取实时价格
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type IntradayData struct {
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MidPrices []float64
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EMA20Values []float64
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@@ -40,6 +42,24 @@ type IntradayData struct {
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RSI14Values []float64
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}
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// MidTermData15m 15分钟时间框架数据 - 短期趋势过滤
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type MidTermData15m struct {
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MidPrices []float64
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EMA20Values []float64
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MACDValues []float64
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RSI7Values []float64
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RSI14Values []float64
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}
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// MidTermData1h 1小时时间框架数据 - 中期趋势确认
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type MidTermData1h struct {
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MidPrices []float64
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EMA20Values []float64
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MACDValues []float64
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RSI7Values []float64
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RSI14Values []float64
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}
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// LongerTermData 长期数据(4小时时间框架)
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type LongerTermData struct {
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EMA20 float64
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@@ -68,13 +88,25 @@ func Get(symbol string) (*Data, error) {
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// 标准化symbol
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symbol = Normalize(symbol)
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// 获取3分钟K线数据 (最近10个)
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// 获取3分钟K线数据 (最近10个) - 用于实时价格
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klines3m, err := getKlines(symbol, "3m", 40) // 多获取一些用于计算
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if err != nil {
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return nil, fmt.Errorf("获取3分钟K线失败: %v", err)
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}
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// 获取4小时K线数据 (最近10个)
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// 获取15分钟K线数据 (最近10个) - 短期趋势
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klines15m, err := getKlines(symbol, "15m", 40)
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if err != nil {
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return nil, fmt.Errorf("获取15分钟K线失败: %v", err)
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}
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// 获取1小时K线数据 (最近10个) - 中期趋势
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klines1h, err := getKlines(symbol, "1h", 60)
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if err != nil {
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return nil, fmt.Errorf("获取1小时K线失败: %v", err)
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}
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// 获取4小时K线数据 (最近10个) - 长期趋势
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klines4h, err := getKlines(symbol, "4h", 60) // 多获取用于计算指标
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if err != nil {
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return nil, fmt.Errorf("获取4小时K线失败: %v", err)
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@@ -115,10 +147,16 @@ func Get(symbol string) (*Data, error) {
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// 获取Funding Rate
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fundingRate, _ := getFundingRate(symbol)
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// 计算日内系列数据
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// 计算日内系列数据 (3分钟)
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intradayData := calculateIntradaySeries(klines3m)
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// 计算长期数据
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// 计算15分钟系列数据
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midTermData15m := calculateMidTermSeries15m(klines15m)
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// 计算1小时系列数据
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midTermData1h := calculateMidTermSeries1h(klines1h)
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// 计算长期数据 (4小时)
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longerTermData := calculateLongerTermData(klines4h)
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return &Data{
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@@ -132,6 +170,8 @@ func Get(symbol string) (*Data, error) {
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OpenInterest: oiData,
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FundingRate: fundingRate,
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IntradaySeries: intradayData,
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MidTermSeries15m: midTermData15m,
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MidTermSeries1h: midTermData1h,
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LongerTermContext: longerTermData,
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}, nil
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}
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@@ -340,6 +380,96 @@ func calculateIntradaySeries(klines []Kline) *IntradayData {
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return data
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}
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// calculateMidTermSeries15m 计算15分钟系列数据
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func calculateMidTermSeries15m(klines []Kline) *MidTermData15m {
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data := &MidTermData15m{
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MidPrices: make([]float64, 0, 10),
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EMA20Values: make([]float64, 0, 10),
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MACDValues: make([]float64, 0, 10),
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RSI7Values: make([]float64, 0, 10),
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RSI14Values: make([]float64, 0, 10),
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}
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// 获取最近10个数据点
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start := len(klines) - 10
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if start < 0 {
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start = 0
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}
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for i := start; i < len(klines); i++ {
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data.MidPrices = append(data.MidPrices, klines[i].Close)
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// 计算每个点的EMA20
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if i >= 19 {
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ema20 := calculateEMA(klines[:i+1], 20)
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data.EMA20Values = append(data.EMA20Values, ema20)
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}
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// 计算每个点的MACD
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if i >= 25 {
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macd := calculateMACD(klines[:i+1])
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data.MACDValues = append(data.MACDValues, macd)
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}
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// 计算每个点的RSI
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if i >= 7 {
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rsi7 := calculateRSI(klines[:i+1], 7)
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data.RSI7Values = append(data.RSI7Values, rsi7)
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}
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if i >= 14 {
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rsi14 := calculateRSI(klines[:i+1], 14)
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data.RSI14Values = append(data.RSI14Values, rsi14)
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}
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}
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return data
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}
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// calculateMidTermSeries1h 计算1小时系列数据
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func calculateMidTermSeries1h(klines []Kline) *MidTermData1h {
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data := &MidTermData1h{
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MidPrices: make([]float64, 0, 10),
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EMA20Values: make([]float64, 0, 10),
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MACDValues: make([]float64, 0, 10),
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RSI7Values: make([]float64, 0, 10),
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RSI14Values: make([]float64, 0, 10),
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}
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// 获取最近10个数据点
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start := len(klines) - 10
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if start < 0 {
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start = 0
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}
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for i := start; i < len(klines); i++ {
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data.MidPrices = append(data.MidPrices, klines[i].Close)
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// 计算每个点的EMA20
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if i >= 19 {
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ema20 := calculateEMA(klines[:i+1], 20)
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data.EMA20Values = append(data.EMA20Values, ema20)
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}
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// 计算每个点的MACD
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if i >= 25 {
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macd := calculateMACD(klines[:i+1])
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data.MACDValues = append(data.MACDValues, macd)
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}
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// 计算每个点的RSI
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if i >= 7 {
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rsi7 := calculateRSI(klines[:i+1], 7)
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data.RSI7Values = append(data.RSI7Values, rsi7)
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}
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if i >= 14 {
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rsi14 := calculateRSI(klines[:i+1], 14)
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data.RSI14Values = append(data.RSI14Values, rsi14)
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}
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}
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return data
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}
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// calculateLongerTermData 计算长期数据
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func calculateLongerTermData(klines []Kline) *LongerTermData {
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data := &LongerTermData{
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@@ -493,6 +623,54 @@ func Format(data *Data) string {
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}
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}
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if data.MidTermSeries15m != nil {
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sb.WriteString("Mid‑term series (15‑minute intervals, oldest → latest):\n\n")
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if len(data.MidTermSeries15m.MidPrices) > 0 {
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sb.WriteString(fmt.Sprintf("Mid prices: %s\n\n", formatFloatSlice(data.MidTermSeries15m.MidPrices)))
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}
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if len(data.MidTermSeries15m.EMA20Values) > 0 {
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sb.WriteString(fmt.Sprintf("EMA indicators (20‑period): %s\n\n", formatFloatSlice(data.MidTermSeries15m.EMA20Values)))
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}
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if len(data.MidTermSeries15m.MACDValues) > 0 {
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sb.WriteString(fmt.Sprintf("MACD indicators: %s\n\n", formatFloatSlice(data.MidTermSeries15m.MACDValues)))
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}
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if len(data.MidTermSeries15m.RSI7Values) > 0 {
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sb.WriteString(fmt.Sprintf("RSI indicators (7‑Period): %s\n\n", formatFloatSlice(data.MidTermSeries15m.RSI7Values)))
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}
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if len(data.MidTermSeries15m.RSI14Values) > 0 {
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sb.WriteString(fmt.Sprintf("RSI indicators (14‑Period): %s\n\n", formatFloatSlice(data.MidTermSeries15m.RSI14Values)))
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}
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}
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if data.MidTermSeries1h != nil {
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sb.WriteString("Mid‑term series (1‑hour intervals, oldest → latest):\n\n")
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if len(data.MidTermSeries1h.MidPrices) > 0 {
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sb.WriteString(fmt.Sprintf("Mid prices: %s\n\n", formatFloatSlice(data.MidTermSeries1h.MidPrices)))
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}
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if len(data.MidTermSeries1h.EMA20Values) > 0 {
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sb.WriteString(fmt.Sprintf("EMA indicators (20‑period): %s\n\n", formatFloatSlice(data.MidTermSeries1h.EMA20Values)))
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}
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if len(data.MidTermSeries1h.MACDValues) > 0 {
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sb.WriteString(fmt.Sprintf("MACD indicators: %s\n\n", formatFloatSlice(data.MidTermSeries1h.MACDValues)))
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}
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if len(data.MidTermSeries1h.RSI7Values) > 0 {
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sb.WriteString(fmt.Sprintf("RSI indicators (7‑Period): %s\n\n", formatFloatSlice(data.MidTermSeries1h.RSI7Values)))
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}
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if len(data.MidTermSeries1h.RSI14Values) > 0 {
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sb.WriteString(fmt.Sprintf("RSI indicators (14‑Period): %s\n\n", formatFloatSlice(data.MidTermSeries1h.RSI14Values)))
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}
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}
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if data.LongerTermContext != nil {
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sb.WriteString("Longer‑term context (4‑hour timeframe):\n\n")
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Reference in New Issue
Block a user