style patterns

lib/trends_IIR/dsma/Dsma.Quantower.Tests.cs

@@ -199,7 +199,7 @@ public class DsmaIndicatorTests
 
         // Process first bar
         indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
-        
+
         // Process second bar as new
         indicator.ProcessUpdate(new UpdateArgs(UpdateReason.NewBar));
         double afterNewBar = indicator.LinesSeries[0].GetValue(0);

lib/trends_IIR/dsma/Dsma.Tests.cs

@@ -232,7 +232,7 @@ public class DsmaTests
 
         // Get the last bar again after loop
         lastBar = gbm.Next(isNew: false);
-        
+
         // Inject NaN
         var nanResult = dsma.Update(new TValue(lastBar.Time, double.NaN));
 
@@ -257,7 +257,7 @@ public class DsmaTests
 
         // Get the last bar again after loop
         lastBar = gbm.Next(isNew: false);
-        
+
         // Inject Infinity
         var infResult = dsma.Update(new TValue(lastBar.Time, double.PositiveInfinity));
         var negInfResult = dsma.Update(new TValue(lastBar.Time, double.NegativeInfinity));

lib/trends_IIR/dsma/Dsma.Validation.Tests.cs

@@ -58,7 +58,7 @@ public class DsmaValidationTests
         }
 
         // In higher volatility, absolute deviation should generally be larger
-        Assert.True(highVolDeviation > lowVolDeviation * 2, 
+        Assert.True(highVolDeviation > lowVolDeviation * 2,
             $"High volatility deviation {highVolDeviation:F2} should be significantly larger than low volatility {lowVolDeviation:F2}");
     }
 
@@ -96,7 +96,7 @@ public class DsmaValidationTests
         double avgHighLag = highScaleLag / count;
 
         // Lower scale factor should have higher average lag (smoother, less responsive)
-        Assert.True(avgLowLag > avgHighLag, 
+        Assert.True(avgLowLag > avgHighLag,
             $"Low scale lag {avgLowLag:F4} should be greater than high scale lag {avgHighLag:F4}");
     }
 
@@ -133,7 +133,7 @@ public class DsmaValidationTests
         double dsmaVariance = dsmaChanges.Average();
 
         // DSMA should have lower variance than raw price
-        Assert.True(dsmaVariance < priceVariance, 
+        Assert.True(dsmaVariance < priceVariance,
             $"DSMA variance {dsmaVariance:F4} should be less than price variance {priceVariance:F4}");
     }
 
@@ -199,7 +199,7 @@ public class DsmaValidationTests
 
         var gbm = new GBM(startPrice: 100.0, mu: 0.01, sigma: 0.2, seed: 654);
         var series = new TSeries();
-        
+
         for (int i = 0; i < 100; i++)
         {
             var bar = gbm.Next(isNew: true);
@@ -254,7 +254,7 @@ public class DsmaValidationTests
         double avgLongLag = longLag / count;
 
         // Longer period should have higher average lag (more smoothing)
-        Assert.True(avgLongLag > avgShortLag, 
+        Assert.True(avgLongLag > avgShortLag,
             $"Long period lag {avgLongLag:F4} should be greater than short period lag {avgShortLag:F4}");
     }
 
@@ -319,8 +319,15 @@ public class DsmaValidationTests
 
         for (int i = 1; i < prices.Count; i++)
         {
-            if (prices[i] > prices[i - 1]) priceUpCount++;
-            if (dsmaValues[i] > dsmaValues[i - 1]) dsmaUpCount++;
+            if (prices[i] > prices[i - 1])
+            {
+                priceUpCount++;
+            }
+
+            if (dsmaValues[i] > dsmaValues[i - 1])
+            {
+                dsmaUpCount++;
+            }
         }
 
         // DSMA should have similar directional trend but smoother

lib/trends_IIR/dsma/Dsma.cs

@@ -89,9 +89,14 @@ public sealed class Dsma : AbstractBase
     public Dsma(int period, double scaleFactor = 0.5)
     {
         if (period < 2)
+        {
             throw new ArgumentOutOfRangeException(nameof(period), "Period must be >= 2.");
+        }
+
         if (scaleFactor < 0.01 || scaleFactor > 0.9)
+        {
             throw new ArgumentOutOfRangeException(nameof(scaleFactor), "Scale factor must be between 0.01 and 0.9.");
+        }
 
         WarmupPeriod = period;
         _periodRecip = 1.0 / period;
@@ -146,12 +151,16 @@ public sealed class Dsma : AbstractBase
         HandleStateSnapshot(isNew);
         value = HandleInvalidInput(value);
         if (double.IsNaN(value))
+        {
             return double.NaN;
+        }
 
         _state.Bars++;
 
         if (_state.Bars == 1)
+        {
             return InitializeFirstBar(value);
+        }
 
         return CalculateDsma(value);
     }
@@ -256,7 +265,10 @@ public sealed class Dsma : AbstractBase
     /// <returns>Time series containing DSMA values</returns>
     public override TSeries Update(TSeries source)
     {
-        if (source.Count == 0) return [];
+        if (source.Count == 0)
+        {
+            return [];
+        }
 
         int len = source.Count;
         var t = new List<long>(len);
@@ -325,7 +337,9 @@ public sealed class Dsma : AbstractBase
                                  double scaleFactor = 0.5)
     {
         if (output.Length < source.Length)
+        {
             throw new ArgumentException("Output span is shorter than source span.", nameof(output));
+        }
 
         var dsma = new Dsma(period, scaleFactor);
         for (int i = 0; i < source.Length; i++)