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.
55 lines
1.6 KiB
Markdown
55 lines
1.6 KiB
Markdown
# Technical Patterns Lab
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技术形态识别研究与实验仓库，聚焦收敛三角形等形态的批量检测、突破强度计算与可视化验证。
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## 核心功能
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- **收敛三角形检测**：基于枢轴点 + 边界线拟合 + 几何约束
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- **批量滚动计算**：支持多股票 × 多交易日的历史回测
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- **突破强度评分**：0~1 连续分数，综合价格、收敛度、成交量
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## 目录结构
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```
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technical-patterns-lab/
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├── src/ # 核心算法
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│ ├── converging_triangle.py # 收敛三角形检测
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│ └── archive/ # 归档代码
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├── scripts/ # 运行脚本
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│ ├── run_converging_triangle.py # 批量检测（主脚本）
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│ └── run_sym_triangle_pkl.py # 对称三角形检测
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├── data/ # 数据文件
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│ ├── open.pkl, high.pkl, low.pkl, close.pkl, volume.pkl
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├── outputs/ # 输出结果
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│ ├── converging_triangles/ # 收敛三角形结果
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│ └── sym_triangles/ # 对称三角形结果
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└── docs/ # 文档
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```
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## 快速开始
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```powershell
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# 1. 激活环境
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.\.venv\Scripts\Activate.ps1
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# 2. 安装依赖（首次）
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pip install numpy pandas matplotlib
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# 3. 运行批量检测
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python scripts/run_converging_triangle.py
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```
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## 输出示例
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```
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检测结果: 1837 个有效三角形
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- 向上突破: 258 次
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- 向下突破: 251 次
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- 高强度突破: 375 个 (strength > 0.3)
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```
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## 相关文档
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- `docs/突破强度计算方法.md` - 突破强度的计算逻辑
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- `docs/对称三角形识别-Python实现.md` - 算法原理说明
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