Commit Graph
5 Commits
Author SHA1 Message Date
Miha Kralj 875998b288 Add eventing support to WMA indicator and implement unit tests for various indicators
- Enhanced WMA indicator with event-driven capabilities using ITValuePublisher interface.
- Created a new TODO file listing various indicators and their corresponding libraries.
- Added unit tests for DEMA, HMA, TEMA, and WMA indicators to ensure proper functionality.
- Implemented tests for handling new bars, ticks, and historical data updates across indicators.
- Verified that indicators correctly compute values and handle different source types.
2025-12-07 16:46:38 -08:00
Miha Kralj 967096d4f5 Refactor and optimize various components of QuanTAlib
- 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.
2025-12-04 13:49:05 -08:00
Miha Kralj 626a2afa9b chore: Update .gitignore to exclude SonarQube files and add Codacy and SonarScanner scripts
refactor: Remove WarmupPeriod logging from SMA and WMA examples
2025-11-30 17:17:55 -08:00
Miha Kralj 2d28b8f62a Add Span API for SMA, EMA, and WMA with zero-allocation performance improvements
- Implemented zero-allocation methods for SMA, EMA, and WMA calculations using ReadOnlySpan and Span.
- Added unit tests for Span API to validate input, match TSeries calculations, handle NaN values, and ensure zero allocation.
- Enhanced documentation to include usage examples for the new Span API.
- Introduced performance benchmarks comparing the new Span API against existing TSeries implementations and other libraries.
2025-11-29 20:48:01 -08:00
Miha Kralj 1f80cfda74 feat: Implement SIMD-optimized Multi-Period Simple Moving Average (SMA) with RingBuffer
- Added SmaVector class for calculating multiple SMAs in parallel using SIMD.
- Introduced RingBuffer class for efficient circular buffer management with running sum.
- Implemented unit tests for RingBuffer to ensure correctness and performance.
- Enhanced Add method in RingBuffer to support bar correction semantics.
- Added methods for calculating Min and Max using SIMD acceleration.
- Improved performance with pinned memory and direct span access for SIMD compatibility.
2025-11-29 18:28:42 -08:00