feat(dynamics): add PlusDI, MinusDI, PlusDM, MinusDM indicators

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
This commit is contained in:
Miha Kralj
2026-03-11 20:21:52 -07:00
parent 56b86bebfb
commit 33d20f2a18
437 changed files with 4589 additions and 2792 deletions
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# LAGUERRE: Ehlers Laguerre Filter
> *The problem with conventional filters is that they use unit delays. All-pass filters replace unit delays with frequency-dependent delays, and that changes everything.*
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Filter |
@@ -18,8 +20,6 @@
- Requires `WarmupBars` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
> "The problem with conventional filters is that they use unit delays. All-pass filters replace unit delays with frequency-dependent delays, and that changes everything." — John F. Ehlers
## Introduction
The Laguerre Filter is a four-element IIR (Infinite Impulse Response) filter designed by John F. Ehlers that uses cascaded all-pass sections controlled by a single damping factor γ (gamma). It produces remarkably smooth output from only four data elements. When γ = 0, the filter degenerates to a 4-tap FIR (triangular weighted average). As γ approaches 1, smoothing increases with correspondingly greater lag. The filter achieves smoothing quality comparable to much longer conventional moving averages while maintaining a fixed 4-element structure.