Complete thin Dx-composition wrapper indicators with full test coverage:
- PlusDi/MinusDi: Directional Indicator wrappers (DiPlus/DiMinus from Dx)
- PlusDm/MinusDm: Directional Movement wrappers (DmPlus/DmMinus from Dx)
- Individual validation tests per indicator directory (TALib, Skender, bounds)
- Combined unit tests (DiDm.Tests.cs) and validation tests (DiDm.Validation.Tests.cs)
- Quantower wrappers + tests for all 4 indicators
- PineScript v6 implementations with compensated RMA
- Normalized .md documentation for all indicators and categories
- 182 tests passing, 0 failures
- Implemented the TRAMA (Trend Regularity Adaptive Moving Average) class with adaptive EMA logic.
- Added unit tests for TRAMA functionality, including constructor validation, basic calculations, state management, and robustness checks.
- Created validation tests to ensure consistency across different modes of operation (streaming, batch, and static calculations).
- Enhanced documentation for TRAMA, including performance profiles and quality metrics.
- Updated workspace configuration by removing unnecessary folder references.
- LTMA (Linear Trend Moving Average): Introduces a predictive moving average using dual cascaded EMAs for trend estimation.
- MCNMA (McNicholl EMA): Implements a zero-lag TEMA using a cascaded EMA structure for enhanced responsiveness.
- NLMA (Non-Lag Moving Average): Utilizes a damped cosine kernel to achieve reduced lag in moving averages.
- NMA (Natural Moving Average): Adapts smoothing based on volatility profiles using a square-root kernel.
- NYQMA (Nyquist Moving Average): Applies the Nyquist-Shannon theorem to prevent aliasing in cascaded moving averages.
- RAIN (Rainbow Moving Average): Combines multiple SMA layers with weighted averages for multi-scale smoothing.
- TRAMA (Trend Regularity Adaptive Moving Average): Adapts smoothing based on the frequency of new highs and lows in price data.
- Implemented Prime method in Vel, Ao, Apo, Frama, Adl, Adosc, Aobv, Cmf, Efi, Eom, Iii, Kvo, Mfi, Nvi, Obv, Pvd, Pvi, Pvo, Pvr, Pvt, Tvi, Twap, Va, Vf, Vo, Vroc, Vwad, Vwap, and Vwma classes.
- The Prime method resets the indicator state and processes the provided historical bar data to initialize the indicator.
- Added warmup period property to Adl and Wad classes to define the minimum number of data points required for validity.
- Updated benchmark tests to use Batch methods for performance evaluation.
- Implemented ChopIndicator for Quantower with configurable period and cold value display.
- Created Chop class for calculating the Choppiness Index with detailed documentation.
- Added comprehensive unit tests for Chop functionality, covering various market conditions and edge cases.
- Developed markdown documentation for CHOP, detailing its historical context, mathematical foundation, and usage examples.
- Established a remediation plan for channel indicators documentation, identifying gaps and prioritizing updates.
- Updated Codacy instructions to streamline usage guidelines.
- Refactored Bbands class to utilize ArrayPool for memory management, preventing stack overflow on large series.
- Changed Fcb class to use long for monotonic deques to avoid truncation issues.
- Enhanced Kchannel class to ensure safe defaults for non-finite values.
- Improved Maenv class to prevent double-priming during calculations.
- Modified Mmchannel class to ensure non-negative buffer indices and removed unnecessary state tracking.
- Updated Pchannel class to correctly reference IsHot state.
- Refined Regchannel class to avoid double-processing during calculations.
- Enhanced Starchannel class to sanitize non-finite values during calculations.
- Adjusted Stbands.Quantower.cs to allow finer control over multiplier precision.
- Updated Ubands class to only update last valid values on new bars.
- Modified Uchannel.Quantower.cs to allow for finer multiplier precision.
- Enhanced Vwapbands classes to include standard deviation calculations and ensure consistent array lengths.
- Refactored Vwapsd classes to include standard deviation outputs and ensure consistent array lengths.
- Updated MonotonicDeque to use long for indices to prevent overflow.
- Improved Mdape class to handle zero actual values with a substitute value for error calculation.
- Enhanced Rae class to ensure correct state management during updates.
- Refined Wmape class to simplify the logic for finding last valid actual and predicted values.
- Updated Cmf.Quantower classes to ensure MinHistoryDepths reflects the current period.
- Updated buffer handling in TheilU and Wmape classes to ensure consistency after adding new values.
- Changed the resync interval constant in TukeyBiweight for better clarity.
- Refactored state structures to record structs in Gauss, Hann, Hp, Hpf, Kalman, Loess, Notch, and other filter classes for improved performance and readability.
- Enhanced numerical stability in Mama class calculations using Fused Multiply-Add (FMA) for precision.
- Added comprehensive tests for Atan2 validation to compare .NET's Math.Atan2 with PineScript's implementation, ensuring accuracy across various edge cases.
- Updated NDepend badges to reflect changes in classes, methods, and lines of code.
- 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.
Miha Kralj