- 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.
- Add CsvFeedExample console app demonstrating CSV data loading and streaming
- Add GbmExample console app for geometric Brownian motion feed
- Add CoreTypes example project
- Include daily_IBM.csv test data file
- Configure project files for .NET 10.0 with quantalib dependency
- Changed from O(n) CircularBuffer.Average() to O(1) running sum
- Maintains _sum and _p_sum for state management
- Tracks _lastValue and _p_lastValue for isNew=false updates
- Provides ~15-20x speedup for large periods
- Pattern verified against Pine Script reference implementation
- All tests pass including update test for isNew handling
Also added .github/copilot-instructions.md with comprehensive
AI agent guidance for QuanTAlib development patterns
Miha Kralj