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.
85 lines
1.8 KiB
Markdown
85 lines
1.8 KiB
Markdown
# 使用说明
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## 快速启动
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```powershell
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.\.venv\Scripts\Activate.ps1
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python scripts/run_converging_triangle.py
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```
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## 1. 创建与激活虚拟环境
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```powershell
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# 创建环境（首次）
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python -m venv .venv
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# 激活环境
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.\.venv\Scripts\Activate.ps1
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```
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## 2. 安装依赖
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```powershell
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pip install numpy pandas matplotlib
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```
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## 3. 运行脚本
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### 收敛三角形批量检测（主脚本）
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```powershell
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python scripts/run_converging_triangle.py
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```
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输出：
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- `outputs/converging_triangles/all_results.csv` - 全部检测结果
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- `outputs/converging_triangles/strong_breakout_up.csv` - 高强度向上突破
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- `outputs/converging_triangles/strong_breakout_down.csv` - 高强度向下突破
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### 对称三角形检测（单点检测）
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```powershell
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python scripts/run_sym_triangle_pkl.py
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```
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输出：
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- `outputs/sym_triangles/*.png` - 各股票图表
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- `outputs/sym_triangles/summary.csv` - 汇总表
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## 4. 参数调整
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编辑 `scripts/run_converging_triangle.py` 顶部的参数区：
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```python
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PARAMS = ConvergingTriangleParams(
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window=400, # 分析窗口大小
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pivot_k=20, # 枢轴点检测窗口
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shrink_ratio=0.8, # 收敛比阈值
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# ...
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)
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RECENT_DAYS = 500 # 计算最近 N 天（None=全部历史）
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ONLY_VALID = True # 只输出有效三角形
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```
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## 5. 数据格式
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数据文件位于 `data/` 目录，格式为 pkl：
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```python
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{
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'mtx': ndarray (n_stocks, n_days), # 数据矩阵
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'dtes': ndarray (n_days,), # 日期 (20050104)
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'tkrs': ndarray (n_stocks,), # 股票代码 (SH600000)
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'tkrs_name': ndarray (n_stocks,), # 股票名称
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}
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```
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## 6. 备注
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- 关闭环境：`deactivate`
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- 权限问题（PowerShell）：
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```powershell
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Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser
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```
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