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

lib/trends_FIR/alma/Alma.md

@@ -1,5 +1,7 @@
 # ALMA: Arnaud Legoux Moving Average
 
+> *Gaussian distributions govern everything from particle diffusion to the distribution of shoe sizes. Applying them to price action isn't 'technical analysis'; it's just physics with a profit motive.*
+
 | Property         | Value                            |
 | ---------------- | -------------------------------- |
 | **Category**     | Trend (FIR MA)                        |
@@ -17,8 +19,6 @@
 - Requires `period` bars of warmup before first valid output (IsHot = true).
 - Validated against TA-Lib, Skender, and Tulip reference implementations where available.
 
-> "Gaussian distributions govern everything from particle diffusion to the distribution of shoe sizes. Applying them to price action isn't 'technical analysis'; it's just physics with a profit motive."
-
 ALMA is a Finite Impulse Response (FIR) filter that applies a Gaussian window to price data. Unlike the Simple Moving Average (which treats 10-minute-old data with the same reverence as 1-minute-old data) or the Exponential Moving Average (which holds onto history like a hoarder), ALMA allows you to shape the weight distribution precisely. It lets you define the trade-off between smoothness and lag using standard deviation ($\sigma$) and offset, rather than arbitrary periods.
 
 ## Historical Context / The Standard