- Introduced a new `Sum` class implementing the Kahan-Babuška algorithm for high-precision rolling summation.
- Added comprehensive documentation for the `Sum` class, detailing its mathematical foundation, performance profile, and use cases.
- Refactored `VarianceIndicator` tests to improve clarity and coverage, including checks for different source types and the ability to change properties.
- Enhanced `UsfIndicator` tests to validate initialization, processing of updates, and property changes.
- Updated `UsfIndicator` implementation to simplify source handling and improve short name generation.
- Modified Qodana configuration to exclude unused auto property accessor warnings.
- Introduced Cma class for calculating the Cumulative Moving Average using Welford's algorithm with FMA for precision.
- Added methods for batch processing and streaming updates.
- Implemented a comprehensive markdown documentation for CMA, covering its mathematical foundation, performance profile, and use cases.
- Enhanced existing trend indicators (Bessel, Butter, Htit, Jma, Mama, Ssf, Vidya) with FMA for improved numerical stability and precision.
- Updated Adosc to utilize a single-pass algorithm for performance optimization.
- Fixed date initialization in benchmarks to ensure UTC consistency.
- Cleaned up code by removing unused using directives from various test and implementation files in the trends and volume directories.
- This includes files related to HMA, HTIT, JMA, KAMA, LSMA, MAMA, MGDI, PWMA, RMA, SMA, SSF, SUPER, T3, TEMA, TRIMA, USF, VIDYA, WMA, ATR, ADL, and ADOSC.
- Improved code readability and maintainability by streamlining imports.
- Updated RsiIndicatorTests to ensure proper initialization and state checks.
- Added new tests for Rsx, Vel, and Adosc indicators to validate behavior under iterative corrections and edge cases (NaN, Infinity).
- Enhanced Bessel indicator tests and implementation with consistent formatting.
- Improved Ema and Pwma implementations by ensuring proper handling of values.
- Introduced mock classes for charting to facilitate testing without dependencies.
- Ensured all indicators produce consistent results across different modes of operation.
- Cleaned up code formatting and added missing commas for better readability.
- Removed unnecessary blank lines in multiple test files to enhance readability.
- Ensured consistent spacing and formatting in the `Trima`, `Usf`, `Vidya`, `Wma`, and `Atr` test classes.
- Updated comments for clarity and consistency in the `Atr` and `Adl` classes.
- Adjusted project files for better structure and maintainability.
- Updated event handler signatures to use TValueEventArgs for consistency in Mama, Mgdi, Pwma, Rma, Sma, Ssf, Super, T3, Tema, Trima, Usf, Vidya, Wma, and Atr classes.
- Enhanced argument validation by specifying parameter names in exceptions for clarity.
- Adjusted tests to align with new event handler signatures.
- Improved code readability and maintainability by using structured records and lambda expressions.
- Enhanced Alma class by simplifying the CalculateWeightedSum method and removing unnecessary comments.
- Removed SIMD-related methods from Conv class, replacing them with optimized DotProduct calls.
- Updated Sma and Wma classes to use source.ContainsNonFinite() for non-finite value checks, improving readability and performance.
- Updated .coderabbit.yaml to exclude additional file types from reviews, improving the focus on relevant code changes.
- Modified scanner.sh to handle test failures more gracefully, ensuring that analysis stops on test failures and improving logging.
- Improved sonarscanner.sh to ensure build and test failures are properly reported, enhancing CI reliability.
- Refined SimdExtensions.cs documentation for clarity on variance calculation methods.
- Cleaned up TSeries.Tests.cs by simplifying the test structure and ensuring proper namespace usage.
- Fixed potential issues in tseries.cs by ensuring correct handling of DateTime values.
- Enhanced CsvFeed.cs to improve error handling during CSV parsing, ensuring robustness against malformed data.
- Updated GBM.cs to correctly calculate volume in the current bar, ensuring accurate simulation.
- Adjusted index.html to use globalThis for better compatibility across environments.
- Refined quantalib.csproj to exclude unnecessary files from compilation, streamlining the build process.
- Added comprehensive tests for the Mama class to ensure correct behavior during updates and state management.
- Improved error handling in various trend classes (Kama, Dema, Ema, T3, Tema, Wma) to ensure NaN values are managed correctly.
- Removed redundant Mama.Repro.Tests.cs file and consolidated tests into Mama.Tests.cs for better organization.
- Enhanced T3 and Tema classes to maintain state integrity during updates, particularly with NaN values.
- Removed WmaVector class to streamline weighted moving average calculations.
- Simplified RingBuffer implementation by removing unnecessary comments and improving clarity.
- Enhanced SIMD extensions for better performance and readability.
- Updated TBar and TBarSeries classes to improve property calculations and reduce overhead.
- Cleaned up TValue struct by removing redundant comments.
- Added comprehensive unit tests for IndicatorExtensions and TrimaIndicator to ensure functionality and correctness.
- Enhanced TBarSeriesTests with additional constructors, methods, and assertions for better coverage.
- Improved TSeriesTests to include new constructors, methods, and edge cases.
- Expanded TValueTests to cover constructors, implicit conversions, equality checks, and hash codes.
- Updated project file to target .NET 10.0 and include internal visibility for tests.
- Added Codacy configuration for code quality checks.
- Introduced TBar struct for efficient OHLCV data representation.
- Implemented TBarSeries class for high-performance collection of TBar instances using Structure of Arrays (SoA) layout.
- Added TSeries class for time-series data management with zero-copy access.
- Created TValue struct for time-value pairs with implicit conversions.
- Defined IFeed interface for consistent data feed implementations.
- Developed CsvFeed class for loading historical OHLCV data from CSV files.
- Implemented GBM class for generating synthetic financial data using Geometric Brownian Motion.
- Added Quantower project files for Averages indicator with necessary dependencies and configurations.
- Included extensive usage examples and notebooks for TBar, TBarSeries, TSeries, TValue, and feed implementations.
Miha Kralj