褚宏光
543572667b
- Created README.md and USAGE.md for project overview and usage instructions. - Added core algorithm in src/converging_triangle.py for batch processing of stock data. - Introduced data files (open.pkl, high.pkl, low.pkl, close.pkl, volume.pkl) for OHLCV data. - Developed output documentation for results and breakout strength calculations. - Implemented scripts for running the detection and generating reports. - Added SVG visualizations and markdown documentation for algorithm details and usage examples.
76 lines
2.1 KiB
Markdown
76 lines
2.1 KiB
Markdown
# 对称三角形识别 - 代码讲解一页PPT
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## 1. 算法总体流程（5步）
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输入数据 → 枢轴点检测 → 边界线拟合 → 几何约束验证 → 突破判定 → 输出结果
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---
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## 2. 核心模块与函数
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**(1) 枢轴点检测**
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函数：`pivots_fractal(high, low, k)`
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作用：从高低价序列中提取明显峰谷
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关键参数：`pivot_k`（越大越严格）
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**(2) 边界线拟合**
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函数：`fit_boundary_line(x, y, mode, n_segments)`
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作用：按时间分段取极值点，拟合贴边趋势线
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关键参数：`boundary_n_segments`（越小越贴边）
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**(3) 形态验证**
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函数：`detect_sym_triangle(...)`
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包含：斜率约束、收敛判断、触碰次数、突破确认
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---
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## 3. 几何约束（对称三角形判定）
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- 上沿下降：`a_u <= upper_slope_max`
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- 下沿上升：`a_l > 0`
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- 收敛比例：`width_end / width_start <= shrink_ratio`
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- 触碰次数：上下沿均 ≥ 2 次
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---
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## 4. 突破与确认逻辑
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- 向上突破：`close[end] > upper_end * (1 + break_tol)`
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- 向下突破：`close[end] < lower_end * (1 - break_tol)`
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- 成交量确认（可选）：`volume[end] > MA(volume) * vol_k`
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- 假突破过滤：突破后 `m` 根内回到线内
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---
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## 5. 关键参数（调参入口）
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| 参数 | 含义 | 建议范围 |
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|------|------|---------|
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| `WINDOW` | 最近窗口长度 | 200~500 |
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| `PIVOT_K` | 枢轴检测窗口 | 5~30 |
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| `BOUNDARY_N_SEGMENTS` | 分段数 | 2~5 |
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| `UPPER_SLOPE_MAX` | 上沿斜率上限 | -0.01~0.10 |
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| `SHRINK_RATIO` | 收敛比例 | 0.3~0.9 |
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| `TOUCH_TOL` | 触碰容差 | 0.03~0.15 |
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---
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## 6. 结果输出结构
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`SymTriangleResult` 包含：
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- 识别区间：`start, end`
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- 趋势线：`upper_coef, lower_coef`
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- 收敛程度：`width_ratio`
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- 触碰次数：`touches_upper, touches_lower`
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- 突破信息：`breakout, volume_confirmed, false_breakout`
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---
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## 7. 文件组织
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```
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code/
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├── sym_triangle.py # 核心算法（检测+拟合+判定）
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├── run_sym_triangle_json.py # 测试脚本（参数配置+可视化）
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└── data.json # 输入数据（labels/values）
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```
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