- 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.
- Revised README.md to enhance clarity on core functionalities and usage instructions.
- Updated USAGE.md to reflect the new pipeline script and its parameters.
- Modified .gitignore to include additional output files for better management.
- Removed outdated output files (all_results.csv, report.md, strong_breakout_up.csv, strong_breakout_down.csv) to streamline data handling.
- Improved structure and descriptions in documentation for better user guidance.
- 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.
- Updated all_results.csv with additional stock data and breakout strength metrics.
- Revised report.md to improve clarity and detail on stock selection criteria and results.
- Expanded strong_breakout_down.csv and strong_breakout_up.csv with new entries reflecting recent analysis.
- Introduced new chart images for selected stocks to visualize breakout patterns.
- Added plot_converging_triangles.py script for generating visualizations of stocks meeting convergence criteria.
- Enhanced report_converging_triangles.py to allow for date-specific reporting and improved output formatting.
- Optimized run_converging_triangle.py for performance and added execution time logging.
- 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.
