- Updated class count in classes.svg from 938 to 1078.
- Adjusted comments percentage in comments.svg from 33.06 to 33.02.
- Revised average cyclomatic complexity in complexity.svg from 2.19 to 2.12.
- Increased source files count in files.svg from 1099 to 1275.
- Updated lines of code in loc.svg from 114549 to 129859.
- Increased methods count in methods.svg from 12035 to 14066.
- Updated public types count in public-api.svg from 1086 to 1225.
- Revised missing indicators report with updated counts and categories, reflecting recent implementations and planned additions.
- Introduced YZV class for calculating Yang-Zhang Volatility, a comprehensive volatility measure that incorporates overnight, open-to-close, and high-low components.
- Implemented calculation methods, including batch processing for TBarSeries and spans.
- Added documentation for YZV, detailing its mathematical foundation, performance profile, and trading applications.
- Updated volume index documentation to reflect changes in file paths.
- Refactored VWMA calculation method to use a more generic source parameter instead of price.
- Implemented Vwapsd class for calculating VWAP with configurable standard deviation bands.
- Added methods for updating the indicator with new bars and calculating VWAPSD using both bar series and span arrays.
- Created comprehensive validation tests for VWAPSD, including checks for consistency between streaming and batch modes, mathematical correctness, and handling of edge cases such as NaN values and zero volume bars.
- Ensured that the implementation adheres to performance standards with tests for large datasets and fractional numDevs values.
- Implemented CMF indicator in Cmf.cs with detailed calculations and methods.
- Created unit tests for CMF validation against Skender, Ooples, and batch processing.
- Added documentation for CMF in Cmf.md, explaining its purpose, calculations, and usage.
- Updated project files to include new statistics library.
- Updated NDepend badges to reflect changes in classes, methods, and lines of code.
- Implemented Sdchannel class for calculating standard deviation channels based on linear regression.
- Added detailed documentation for SDCHANNEL, including overview, calculation methods, and interpretation.
- Updated project files to include new numerics library components in Channels and Volatility projects.
Miha Kralj