- 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.
- Introduced type definitions for various classes in the QuanTAlib library, including Ema, EmaVector, EmaState, TSeries, CsvFeed, GBM, TBarSeries, TBar, and TValue.
- Added methods and properties for each class to enhance functionality and maintainability.
- Created a lock file to manage dependencies and ensure consistent builds.
- 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