docs: remove C# Implementation Considerations sections, clean up temp scripts, reorganize test files

- Remove 'C# Implementation Considerations' sections from 34 indicator .md files
- Delete 29 temp PowerShell scripts (_fix_mojibake.ps1, _hex_scan.ps1, etc.)
- Move test files into tests/ subdirectories for consistent project structure
- Add trader-focused bullet points to indicator documentation

lib/trends_IIR/dsma/Dsma.md

@@ -158,89 +158,6 @@ DSMA is not implemented in mainstream libraries (TA-Lib, Skender, Tulip, Ooples)
 - **Bounds**: Output remains within [min, max] price range ±1% tolerance
 - **Mathematical Consistency**: Streaming updates match batch calculations (ε < 1e-10)
 
-## C# Implementation Considerations
-
-### State Management
-
-DSMA uses a comprehensive State record struct combining all filter stages:
-
-```csharp
-[StructLayout(LayoutKind.Auto)]
-private record struct State
-{
-    public double Filt;       // current filtered value
-    public double Filt1;      // filt[t-1]
-    public double Filt2;      // filt[t-2]
-    public double Zeros1;     // deviation[t-1]
-    public double SumSquared; // running sum for RMS
-    public double Result;     // current DSMA value
-    public double LastPrice;  // last valid price
-    public int Bars;
-}
-```
-
-Bar correction requires coordinated rollback of both state and RingBuffer:
-
-```csharp
-if (isNew) { _p_state = _state; _filtSquaredBuffer.Snapshot(); }
-else { _state = _p_state; _filtSquaredBuffer.Restore(); }
-```
-
-### RingBuffer for RMS
-
-The RingBuffer maintains O(1) running sum updates for RMS calculation:
-
-```csharp
-double removed = _filtSquaredBuffer.Add(filtSq);
-_state.SumSquared = Math.FusedMultiplyAdd(-1.0, removed, _state.SumSquared + filtSq);
-```
-
-The buffer's `Snapshot()`/`Restore()` methods enable atomic rollback on bar corrections.
-
-### Precomputed Constants
-
-Constructor calculates all filter coefficients once:
-
-```csharp
-double arg = SqrtTwo * Math.PI / (period * 0.5);
-double a1 = Math.Exp(-arg);
-_b1 = 2.0 * a1 * Math.Cos(arg);
-_a1Sq = a1 * a1;
-_c1Half = (1.0 - _b1 + _a1Sq) * 0.5;
-_periodRecip = 1.0 / period;
-_scaleAdjustment = scaleFactor * 5.0 / period;
-```
-
-### FMA Usage
-
-FMA optimizes the Super Smoother IIR and adaptive EMA:
-
-```csharp
-// Super Smoother: filt = c1Half*(zeros+zeros1) + b1*filt1 - a1Sq*filt2
-double filtPart2 = Math.FusedMultiplyAdd(_state.Filt1, _b1, -_a1Sq * _state.Filt2);
-
-// Adaptive EMA: result = prevResult*decay + alpha*value
-double result = Math.FusedMultiplyAdd(_state.Result, decay, alpha * value);
-```
-
-### Memory Layout
-
-| Field | Type | Size | Purpose |
-| :--- | :--- | :---: | :--- |
-| `_b1` | double | 8B | Super Smoother coefficient |
-| `_c1Half` | double | 8B | Halved c₁ coefficient |
-| `_a1Sq` | double | 8B | a₁² coefficient |
-| `_periodRecip` | double | 8B | 1/period |
-| `_scaleAdjustment` | double | 8B | Combined scale factor |
-| `_filtSquaredBuffer` | RingBuffer | ~8B+period×8B | Circular buffer for RMS |
-| `_state` | State | ~64B | Current calculation state |
-| `_p_state` | State | ~64B | Previous state for rollback |
-| **Total (fixed)** | | **~176B + period×8B** | Per indicator instance |
-
-### SIMD Limitations
-
-The 2-pole IIR recursion and adaptive alpha dependency on running RMS preclude SIMD parallelization across bars. The `Calculate(Span)` method uses a scalar loop—parallelization should target multiple independent series rather than within-series vectorization.
-
 ## Common Pitfalls
 
 1. **Warmup Period**: DSMA requires `Period` bars to fill the Super Smoother delay line and RMS buffer. The first `Period` outputs will be unstable. Use `IsHot` to detect when the indicator has sufficient history.