Refactor code formatting and improve consistency across various test files

- Removed unnecessary blank lines in multiple test files to enhance readability.
- Ensured consistent spacing and formatting in the `Trima`, `Usf`, `Vidya`, `Wma`, and `Atr` test classes.
- Updated comments for clarity and consistency in the `Atr` and `Adl` classes.
- Adjusted project files for better structure and maintainability.

docs/api.md

@@ -33,7 +33,7 @@ Every indicator exposes the following core properties and methods:
 
 ## 2. Mode A: Batch (Stateless)
 
-**Purpose:** Backtesting, Data Analysis, Optimization  
+**Purpose:** Backtesting, Data Analysis, Optimization
 **Method:** `static Batch`
 
 Batch mode provides stateless, SIMD-accelerated processing of historical arrays. It is optimized for maximum throughput and zero heap allocation.
@@ -67,7 +67,7 @@ TSeries sma = Sma.Batch(history, 14);
 
 ## 3. Mode B: Streaming (Stateful)
 
-**Purpose:** Live Trading, Event Processing  
+**Purpose:** Live Trading, Event Processing
 **Method:** `Update`
 
 Streaming mode handles real-time data ingestion using O(1) complexity per update. It maintains internal state (circular buffers, running sums) to process ticks with minimal latency.
@@ -109,7 +109,7 @@ var sma = new Sma(source, 14);
 var ema = new Ema(sma, 5);
 
 // Updates flow automatically
-source.Add(new TValue(time, price)); 
+source.Add(new TValue(time, price));
 // sma updates, then ema updates automatically
 ```
 
@@ -117,7 +117,7 @@ source.Add(new TValue(time, price));
 
 ## 4. Mode C: Priming (The Bridge)
 
-**Purpose:** Switching from Batch to Streaming  
+**Purpose:** Switching from Batch to Streaming
 **Method:** `Prime`
 
 Priming mode hydrates a streaming instance using the minimal required tail of historical data. It calculates the intersection of *History Available* and *State Required*, allowing an indicator to become "Hot" without processing the entire history.
@@ -132,7 +132,7 @@ double[] history = ...; // e.g., 100,000 bars
 
 // Efficiently processes only the last 'period' bars needed to fill the buffer
 // O(Warmup) initialization instead of O(History)
-indicator.Prime(history); 
+indicator.Prime(history);
 
 // Indicator is now "Hot" and ready for the next live tick
 Console.WriteLine(indicator.IsHot); // true
@@ -193,7 +193,7 @@ The initial portion of the output contains "cold" values.
 
 ```mermaid
 graph LR
-    H[Historical Data] 
+    H[Historical Data]
     L[Live Data]
 
     subgraph "Mode A: Batch"

docs/integration.md

@@ -36,7 +36,7 @@ public class MySmaIndicator : Indicator
     {
         // Get price from Quantower
         double price = ClosePrice;
-        
+
         // Update QuanTAlib
         // Note: Quantower handles bar updates, so a check is performed to determine whether this is a new bar or an update
         bool isNew = args.Reason == UpdateReason.NewBar;
@@ -73,10 +73,10 @@ protected override void OnBarUpdate()
 {
     // NinjaTrader calls OnBarUpdate for every tick (if Calculate = OnEachTick)
     // or once per bar (if Calculate = OnBarClose)
-    
+
     bool isNew = IsFirstTickOfBar; // Logic depends on Calculate mode
     var result = _sma.Update(new TValue(Time[0], Close[0]), isNew);
-    
+
     Value[0] = result.Value;
 }
 ```
@@ -104,7 +104,7 @@ public class MyAlgorithm : QCAlgorithm
         {
             var bar = data.Bars["SPY"];
             var result = _mySma.Update(new TValue(bar.EndTime, (double)bar.Close));
-            
+
             if (_mySma.IsHot)
             {
                 Plot("Indicators", "SMA", result.Value);