- Introduced a new API for converging triangle detection, including the main function `detect_matrix()` for batch processing of stock data.
- Added detailed documentation for the API, covering usage examples, parameter configurations, and output structures.
- Created new markdown files for reference and usage instructions, enhancing the overall documentation quality.
New files:
- `src/triangle_detector_api.py`: Core API implementation.
- `docs/triangle_api_reference.md`: Comprehensive API reference documentation.
- `discuss/20260129-三角形强度.md`: Documentation for triangle strength detection functions.
- `docs/2026-01-29_三角形数据_server.md`: Detailed usage of the triangle detection functions.
- Upgraded charting functionality from line graphs to K线图 for improved technical analysis.
- Introduced a new daily best stocks report, outputting the top-performing stocks over the last 500 days.
- Implemented automatic logging of execution details for better traceability.
- Updated the .gitignore to include new output files related to the K线图 and logs.
Files modified:
- scripts/plot_converging_triangles.py: Enhanced to support K线图 rendering.
- scripts/run_converging_triangle.py: Added logging and daily best reporting features.
- README.md: Updated to reflect new features and usage instructions.
- New files: docs/K线图说明.md for detailed K线图 usage and features.
- Introduced an interactive HTML stock viewer for visualizing strength scores and filtering stocks based on user-defined thresholds.
- Added `--all-stocks` parameter to generate charts for all 108 stocks, including those not meeting convergence criteria.
- Implemented a new scoring system for breakout strength, incorporating fitting adherence to improve accuracy.
- Updated multiple documentation files, including usage instructions and feature overviews, to reflect recent enhancements.
- Improved error handling and file naming conventions to ensure compatibility across platforms.
- Added `--show-details` parameter to `pipeline_converging_triangle.py` for generating detailed charts that display all pivot points and fitting lines.
- Implemented an iterative outlier removal algorithm in `fit_pivot_line` to improve the accuracy of pivot point fitting by eliminating weak points.
- Updated `USAGE.md` to include new command examples for the detailed mode.
- Revised multiple documentation files to reflect recent changes and improvements in the pivot detection and visualization processes.
- Added support for a detailed chart mode in plot_converging_triangles.py, allowing users to visualize all pivot points and fitting lines.
- Improved pivot fitting logic to utilize multiple representative points, enhancing detection accuracy and reducing false positives.
- Introduced a new real-time detection mode with flexible zone parameters for better responsiveness in stock analysis.
- Updated README.md and USAGE.md to reflect new features and usage instructions.
- Added multiple documentation files detailing recent improvements, including pivot point fitting and visualization enhancements.
- Cleaned up and archived outdated scripts to streamline the project structure.
- Added pipeline_converging_triangle.py for streamlined execution of detection, reporting, and chart generation.
- Introduced triangle_config.py for centralized parameter management across scripts.
- Updated plot_converging_triangles.py to utilize parameters from the new config file.
- Revised report_converging_triangles.py to reflect dynamic detection window based on configuration.
- Enhanced existing scripts for improved error handling and output consistency.
- Added new documentation files for usage instructions and parameter configurations.
- 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.
