style patterns

lib/statistics/beta/Beta.cs

@@ -272,4 +272,4 @@ public sealed class Beta : AbstractBase
             _sumRm2 = FusedMultiplyAdd(rm, rm, _sumRm2);
         }
     }
-}
+}

lib/statistics/cma/Cma.Quantower.Tests.cs

@@ -166,4 +166,4 @@ public class CmaIndicatorTests
         indicator.ProcessUpdate(new UpdateArgs(UpdateReason.NewBar));
         Assert.Equal(20.0, indicator.LinesSeries[0].GetValue(0), 1e-10); // CMA = (10+20+30)/3 = 20
     }
-}
+}

lib/statistics/cma/Cma.Tests.cs

@@ -401,7 +401,9 @@ public class CmaTests
 
         var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 42);
         for (int i = 0; i < source.Length; i++)
+        {
             source[i] = gbm.Next().Close;
+        }
 
         // Warm up
         Cma.Batch(source.AsSpan(), output.AsSpan());
@@ -520,7 +522,10 @@ public class CmaTests
     public void Calculate_ReturnsCorrectResultsAndHotIndicator()
     {
         var series = new TSeries();
-        for (int i = 1; i <= 10; i++) series.Add(DateTime.UtcNow, i * 10);
+        for (int i = 1; i <= 10; i++)
+        {
+            series.Add(DateTime.UtcNow, i * 10);
+        }
         // 10, 20, 30, 40, 50, 60, 70, 80, 90, 100
 
         var (results, indicator) = Cma.Calculate(series);

lib/statistics/cma/Cma.cs

@@ -96,7 +96,10 @@ public sealed class Cma : AbstractBase
     /// <param name="step">Time interval between values (not used for CMA)</param>
     public override void Prime(ReadOnlySpan<double> source, TimeSpan? step = null)
     {
-        if (source.Length == 0) return;
+        if (source.Length == 0)
+        {
+            return;
+        }
 
         // Reset state
         _state = default;
@@ -162,7 +165,10 @@ public sealed class Cma : AbstractBase
 
     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);
@@ -207,10 +213,15 @@ public sealed class Cma : AbstractBase
     public static void Batch(ReadOnlySpan<double> source, Span<double> output)
     {
         if (source.Length != output.Length)
+        {
             throw new ArgumentException("Source and output must have the same length", nameof(output));
+        }
 
         int len = source.Length;
-        if (len == 0) return;
+        if (len == 0)
+        {
+            return;
+        }
 
         double mean = 0;
         double lastValid = double.NaN;
@@ -230,9 +241,13 @@ public sealed class Cma : AbstractBase
         {
             double val = source[i];
             if (double.IsFinite(val))
+            {
                 lastValid = val;
+            }
             else
+            {
                 val = lastValid;
+            }
 
             // M_n = M_(n-1) + alpha * delta using FMA for single-rounding precision
             double alpha = 1.0 / (i + 1);
@@ -264,4 +279,4 @@ public sealed class Cma : AbstractBase
         _p_state = default;
         Last = default;
     }
-}
+}

lib/statistics/covariance/Covariance.Simd.Tests.cs

@@ -82,8 +82,15 @@ public class CovarianceSimdTests
         {
             double x = dataX[i];
             double y = dataY[i];
-            if (!double.IsFinite(x)) x = 0;
-            if (!double.IsFinite(y)) y = 0;
+            if (!double.IsFinite(x))
+            {
+                x = 0;
+            }
+
+            if (!double.IsFinite(y))
+            {
+                y = 0;
+            }
 
             var res = scalarCov.Update(x, y);
             Assert.Equal(res.Value, result.Values[i], precision: 9);

lib/statistics/covariance/Covariance.cs

@@ -182,7 +182,9 @@ public sealed class Covariance : AbstractBase
     public static TSeries Calculate(TSeries sourceX, TSeries sourceY, int period, bool isPopulation = false)
     {
         if (sourceX.Count != sourceY.Count)
+        {
             throw new ArgumentException("Source series must have the same length", nameof(sourceY));
+        }
 
         int len = sourceX.Count;
         var t = new List<long>(len);
@@ -203,12 +205,20 @@ public sealed class Covariance : AbstractBase
     public static void Batch(ReadOnlySpan<double> sourceX, ReadOnlySpan<double> sourceY, Span<double> output, int period, bool isPopulation = false)
     {
         if (sourceX.Length != sourceY.Length || sourceX.Length != output.Length)
+        {
             throw new ArgumentException("All spans must have the same length", nameof(output));
+        }
+
         if (period < 2)
+        {
             throw new ArgumentException("Period must be greater than or equal to 2", nameof(period));
+        }
 
         int len = sourceX.Length;
-        if (len == 0) return;
+        if (len == 0)
+        {
+            return;
+        }
 
         // SIMD overhead amortizes well for datasets >= 256 elements
         const int SimdThreshold = 256;
@@ -242,8 +252,15 @@ public sealed class Covariance : AbstractBase
         {
             double x = sourceX[i];
             double y = sourceY[i];
-            if (!double.IsFinite(x)) x = 0;
-            if (!double.IsFinite(y)) y = 0;
+            if (!double.IsFinite(x))
+            {
+                x = 0;
+            }
+
+            if (!double.IsFinite(y))
+            {
+                y = 0;
+            }
 
             sumX += x;
             sumY += y;
@@ -270,8 +287,15 @@ public sealed class Covariance : AbstractBase
         {
             double x = sourceX[i];
             double y = sourceY[i];
-            if (!double.IsFinite(x)) x = 0;
-            if (!double.IsFinite(y)) y = 0;
+            if (!double.IsFinite(x))
+            {
+                x = 0;
+            }
+
+            if (!double.IsFinite(y))
+            {
+                y = 0;
+            }
 
             double oldX = bufferX[bufferIndex];
             double oldY = bufferY[bufferIndex];
@@ -283,7 +307,10 @@ public sealed class Covariance : AbstractBase
             bufferX[bufferIndex] = x;
             bufferY[bufferIndex] = y;
             bufferIndex++;
-            if (bufferIndex >= period) bufferIndex = 0;
+            if (bufferIndex >= period)
+            {
+                bufferIndex = 0;
+            }
 
             double n = period;
             double numerator = sumXY - (sumX * sumY) / n;
@@ -357,7 +384,10 @@ public sealed class Covariance : AbstractBase
 
         (double sumX, double sumY, double sumXY) = WarmupCovariance(period, len, isPopulation, ref srcXRef, ref srcYRef, ref outRef);
 
-        if (len <= period) return;
+        if (len <= period)
+        {
+            return;
+        }
 
         var vInvN = Vector256.Create(invN);
         var vInvDenom = Vector256.Create(invDenom);
@@ -452,13 +482,27 @@ public sealed class Covariance : AbstractBase
         {
             double x = Unsafe.Add(ref srcXRef, i);
             double y = Unsafe.Add(ref srcYRef, i);
-            if (!double.IsFinite(x)) x = 0;
-            if (!double.IsFinite(y)) y = 0;
+            if (!double.IsFinite(x))
+            {
+                x = 0;
+            }
+
+            if (!double.IsFinite(y))
+            {
+                y = 0;
+            }
 
             double oldX = Unsafe.Add(ref srcXRef, i - period);
             double oldY = Unsafe.Add(ref srcYRef, i - period);
-            if (!double.IsFinite(oldX)) oldX = 0;
-            if (!double.IsFinite(oldY)) oldY = 0;
+            if (!double.IsFinite(oldX))
+            {
+                oldX = 0;
+            }
+
+            if (!double.IsFinite(oldY))
+            {
+                oldY = 0;
+            }
 
             sumX = sumX - oldX + x;
             sumY = sumY - oldY + y;
@@ -468,4 +512,4 @@ public sealed class Covariance : AbstractBase
             Unsafe.Add(ref outRef, i) = numerator * invDenom;
         }
     }
-}
+}

lib/statistics/linreg/LinReg.cs

@@ -76,7 +76,9 @@ public sealed class LinReg : AbstractBase
     public LinReg(int period, int offset = 0)
     {
         if (period <= 0)
+        {
             throw new ArgumentException("Period must be greater than 0", nameof(period));
+        }
 
         _period = period;
         _offset = offset;
@@ -262,7 +264,10 @@ public sealed class LinReg : AbstractBase
 
     public override TSeries Update(TSeries source)
     {
-        if (source.Count == 0) return new TSeries([], []);
+        if (source.Count == 0)
+        {
+            return new TSeries([], []);
+        }
 
         int len = source.Count;
         var t = new List<long>(len);
@@ -332,12 +337,20 @@ public sealed class LinReg : AbstractBase
     public static void Calculate(ReadOnlySpan<double> source, Span<double> output, int period, int offset = 0, double initialLastValid = 0)
     {
         if (source.Length != output.Length)
+        {
             throw new ArgumentException("Source and output must have the same length", nameof(output));
+        }
+
         if (period <= 0)
+        {
             throw new ArgumentException("Period must be greater than 0", nameof(period));
+        }
 
         int len = source.Length;
-        if (len == 0) return;
+        if (len == 0)
+        {
+            return;
+        }
 
         // Stack allocate for typical periods (most < 100)
         // ArrayPool for large periods to avoid stack overflow
@@ -353,87 +366,95 @@ public sealed class LinReg : AbstractBase
         try
         {
 
-        double sum_y = 0;
-        double sum_xy = 0;
-        double lastValid = initialLastValid;
-        int bufferIndex = 0;
-        int count = 0;
+            double sum_y = 0;
+            double sum_xy = 0;
+            double lastValid = initialLastValid;
+            int bufferIndex = 0;
+            int count = 0;
 
-        double full_sum_x = 0.5 * period * (period - 1);
-        double full_sum_x2 = (period - 1.0) * period * (2.0 * period - 1.0) / 6.0;
-        double full_denom = period * full_sum_x2 - full_sum_x * full_sum_x;
+            double full_sum_x = 0.5 * period * (period - 1);
+            double full_sum_x2 = (period - 1.0) * period * (2.0 * period - 1.0) / 6.0;
+            double full_denom = period * full_sum_x2 - full_sum_x * full_sum_x;
 
-        for (int i = 0; i < len; i++)
-        {
-            double val = source[i];
-            if (double.IsFinite(val))
-                lastValid = val;
-            else
-                val = lastValid;
-
-            if (count < period)
+            for (int i = 0; i < len; i++)
             {
-                buffer[count] = val;
-                sum_y += val;
-                count++;
-
-                sum_xy = 0;
-                for (int j = 0; j < count; j++)
+                double val = source[i];
+                if (double.IsFinite(val))
                 {
-                    sum_xy = Math.FusedMultiplyAdd(count - 1 - j, buffer[j], sum_xy);
-                }
-
-                if (count <= 1)
-                {
-                    output[i] = val;
+                    lastValid = val;
                 }
                 else
                 {
-                    double n = count;
-                    double sx = 0.5 * n * (n - 1);
-                    double sx2 = (n - 1.0) * n * (2.0 * n - 1.0) / 6.0;
-                    double denom = n * sx2 - sx * sx;
+                    val = lastValid;
+                }
 
-                    if (Math.Abs(denom) < MinDenominator)
+                if (count < period)
+                {
+                    buffer[count] = val;
+                    sum_y += val;
+                    count++;
+
+                    sum_xy = 0;
+                    for (int j = 0; j < count; j++)
+                    {
+                        sum_xy = Math.FusedMultiplyAdd(count - 1 - j, buffer[j], sum_xy);
+                    }
+
+                    if (count <= 1)
                     {
                         output[i] = val;
                     }
                     else
                     {
-                        double m = Math.FusedMultiplyAdd(n, sum_xy, -sx * sum_y) / denom;
-                        double b = Math.FusedMultiplyAdd(-m, sx, sum_y) / n;
-                        output[i] = Math.FusedMultiplyAdd(-m, offset, b);
+                        double n = count;
+                        double sx = 0.5 * n * (n - 1);
+                        double sx2 = (n - 1.0) * n * (2.0 * n - 1.0) / 6.0;
+                        double denom = n * sx2 - sx * sx;
+
+                        if (Math.Abs(denom) < MinDenominator)
+                        {
+                            output[i] = val;
+                        }
+                        else
+                        {
+                            double m = Math.FusedMultiplyAdd(n, sum_xy, -sx * sum_y) / denom;
+                            double b = Math.FusedMultiplyAdd(-m, sx, sum_y) / n;
+                            output[i] = Math.FusedMultiplyAdd(-m, offset, b);
+                        }
+                    }
+
+                    if (count == period)
+                    {
+                        bufferIndex = 0;
                     }
                 }
+                else
+                {
+                    double oldest = buffer[bufferIndex];
+                    double prev_sum_y = sum_y;
 
-            if (count == period)
-            {
-                bufferIndex = 0;
+                    sum_xy = sum_xy + prev_sum_y - period * oldest;
+                    sum_y = sum_y - oldest + val;
+                    buffer[bufferIndex] = val;
+
+                    bufferIndex++;
+                    if (bufferIndex >= period)
+                    {
+                        bufferIndex = 0;
+                    }
+
+                    double m = Math.FusedMultiplyAdd(period, sum_xy, -full_sum_x * sum_y) / full_denom;
+                    double b = Math.FusedMultiplyAdd(-m, full_sum_x, sum_y) / period;
+                    output[i] = Math.FusedMultiplyAdd(-m, offset, b);
+                }
             }
         }
-        else
-        {
-            double oldest = buffer[bufferIndex];
-            double prev_sum_y = sum_y;
-
-            sum_xy = sum_xy + prev_sum_y - period * oldest;
-            sum_y = sum_y - oldest + val;
-            buffer[bufferIndex] = val;
-
-            bufferIndex++;
-            if (bufferIndex >= period)
-                bufferIndex = 0;
-
-            double m = Math.FusedMultiplyAdd(period, sum_xy, -full_sum_x * sum_y) / full_denom;
-            double b = Math.FusedMultiplyAdd(-m, full_sum_x, sum_y) / period;
-            output[i] = Math.FusedMultiplyAdd(-m, offset, b);
-        }
-    }
-        }
         finally
         {
             if (rentedBuffer != null)
+            {
                 ArrayPool<double>.Shared.Return(rentedBuffer);
+            }
         }
     }
 
@@ -448,4 +469,4 @@ public sealed class LinReg : AbstractBase
         Intercept = 0;
         RSquared = 0;
     }
-}
+}

lib/statistics/median/Median.Tests.cs

@@ -264,14 +264,21 @@ public class MedianTests
         // Arrange
         int period = 5;
         double[] data = new double[20];
-        for (int i = 0; i < data.Length; i++) data[i] = i;
+        for (int i = 0; i < data.Length; i++)
+        {
+            data[i] = i;
+        }
 
         // Act
         double[] output = new double[data.Length];
         Median.Batch(data, output, period);
 
         var series = new TSeries();
-        for (int i = 0; i < data.Length; i++) series.Add(new TValue(DateTime.MinValue, data[i]));
+        for (int i = 0; i < data.Length; i++)
+        {
+            series.Add(new TValue(DateTime.MinValue, data[i]));
+        }
+
         var batchSeries = Median.Batch(series, period);
 
         // Assert

lib/statistics/median/Median.Validation.Tests.cs

@@ -86,7 +86,10 @@ public sealed class MedianValidationTests : IDisposable
     private static double CalculateMedian(List<double> sortedWindow)
     {
         int count = sortedWindow.Count;
-        if (count == 0) return 0; // Or NaN
+        if (count == 0)
+        {
+            return 0; // Or NaN
+        }
 
         int mid = count / 2;
         if (count % 2 != 0)

lib/statistics/median/Median.cs

@@ -38,7 +38,9 @@ public sealed class Median : AbstractBase, IDisposable
     public Median(int period)
     {
         if (period <= 0)
+        {
             throw new ArgumentException("Period must be greater than 0", nameof(period));
+        }
 
         _period = period;
         _buffer = new RingBuffer(period);
@@ -76,7 +78,10 @@ public sealed class Median : AbstractBase, IDisposable
     /// </summary>
     public override void Prime(ReadOnlySpan<double> source, TimeSpan? step = null)
     {
-        if (source.Length == 0) return;
+        if (source.Length == 0)
+        {
+            return;
+        }
 
         _buffer.Clear();
         int warmupLength = Math.Min(source.Length, WarmupPeriod);
@@ -151,7 +156,10 @@ public sealed class Median : AbstractBase, IDisposable
 
     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);
@@ -178,7 +186,10 @@ public sealed class Median : AbstractBase, IDisposable
         // validCount = elements in sortedBuffer BEFORE insertion
         int validCount = _buffer.Count - 1;
         int index = Array.BinarySearch(_sortedBuffer, 0, validCount, value);
-        if (index < 0) index = ~index;
+        if (index < 0)
+        {
+            index = ~index;
+        }
 
         if (index < validCount)
         {
@@ -224,12 +235,20 @@ public sealed class Median : AbstractBase, IDisposable
     public static void Batch(ReadOnlySpan<double> source, Span<double> output, int period)
     {
         if (source.Length != output.Length)
+        {
             throw new ArgumentException("Source and output must have the same length", nameof(output));
+        }
+
         if (period <= 0)
+        {
             throw new ArgumentException("Period must be greater than 0", nameof(period));
+        }
 
         int len = source.Length;
-        if (len == 0) return;
+        if (len == 0)
+        {
+            return;
+        }
 
         // Always use ArrayPool to avoid CS8353 stackalloc escape issues
         double[] rentedSorted = ArrayPool<double>.Shared.Rent(period);
@@ -266,7 +285,10 @@ public sealed class Median : AbstractBase, IDisposable
                 windowIdx = (windowIdx + 1) % period;
 
                 int newIndex = BinarySearchSpan(sortedBuffer, count, val);
-                if (newIndex < 0) newIndex = ~newIndex;
+                if (newIndex < 0)
+                {
+                    newIndex = ~newIndex;
+                }
 
                 if (newIndex < count)
                 {
@@ -300,11 +322,18 @@ public sealed class Median : AbstractBase, IDisposable
             int mid = lo + ((hi - lo) >> 1);
             int cmp = span[mid].CompareTo(value);
             if (cmp == 0)
+            {
                 return mid;
+            }
+
             if (cmp < 0)
+            {
                 lo = mid + 1;
+            }
             else
+            {
                 hi = mid - 1;
+            }
         }
         return ~lo;
     }
@@ -325,7 +354,10 @@ public sealed class Median : AbstractBase, IDisposable
     /// </summary>
     public new void Dispose()
     {
-        if (_disposed) return;
+        if (_disposed)
+        {
+            return;
+        }
 
         if (_source != null)
         {
@@ -335,4 +367,4 @@ public sealed class Median : AbstractBase, IDisposable
 
         _disposed = true;
     }
-}
+}

lib/statistics/skew/Skew.Tests.cs

@@ -284,7 +284,10 @@ public class SkewTests
     public void Reset_ClearsState()
     {
         var skew = new Skew(5);
-        for (int i = 0; i < 5; i++) skew.Update(new TValue(DateTime.UtcNow, i));
+        for (int i = 0; i < 5; i++)
+        {
+            skew.Update(new TValue(DateTime.UtcNow, i));
+        }
 
         skew.Reset();
         Assert.False(skew.IsHot);
@@ -380,7 +383,10 @@ public class SkewTests
         // Create large dataset to trigger SIMD path (>= 256)
         int count = 1000;
         var data = new double[count];
-        for (int i = 0; i < count; i++) data[i] = (double)i;
+        for (int i = 0; i < count; i++)
+        {
+            data[i] = (double)i;
+        }
 
         var series = new TSeries(new System.Collections.Generic.List<long>(new long[count]), new System.Collections.Generic.List<double>(data));
 

lib/statistics/skew/Skew.cs

@@ -104,7 +104,11 @@ public sealed class Skew : AbstractBase
             // Calculate 2nd moment (Variance)
             // m2 = Sum((x-mean)^2) / n = (SumSq - Sum^2/n) / n
             double m2Numerator = _sumSq - (_sum * _sum) / n;
-            if (m2Numerator < Epsilon) m2Numerator = 0;
+            if (m2Numerator < Epsilon)
+            {
+                m2Numerator = 0;
+            }
+
             double m2 = m2Numerator / n;
 
             // Calculate 3rd moment
@@ -143,7 +147,10 @@ public sealed class Skew : AbstractBase
 
     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);
@@ -225,12 +232,20 @@ public sealed class Skew : AbstractBase
     public static void Batch(ReadOnlySpan<double> source, Span<double> output, int period, bool isPopulation = false)
     {
         if (source.Length != output.Length)
+        {
             throw new ArgumentException("Source and output must have the same length", nameof(output));
+        }
+
         if (period < 3)
+        {
             throw new ArgumentException("Period must be greater than or equal to 3", nameof(period));
+        }
 
         int len = source.Length;
-        if (len == 0) return;
+        if (len == 0)
+        {
+            return;
+        }
 
         // Try SIMD path for large, clean datasets
         // SIMD overhead amortizes well for datasets >= 256 elements
@@ -260,7 +275,10 @@ public sealed class Skew : AbstractBase
         for (; i < warmupEnd; i++)
         {
             double val = source[i];
-            if (!double.IsFinite(val)) val = 0;
+            if (!double.IsFinite(val))
+            {
+                val = 0;
+            }
 
             sum += val;
             sumSq += val * val;
@@ -275,10 +293,16 @@ public sealed class Skew : AbstractBase
         for (; i < len; i++)
         {
             double val = source[i];
-            if (!double.IsFinite(val)) val = 0;
+            if (!double.IsFinite(val))
+            {
+                val = 0;
+            }
 
             double oldVal = source[i - period];
-            if (!double.IsFinite(oldVal)) oldVal = 0;
+            if (!double.IsFinite(oldVal))
+            {
+                oldVal = 0;
+            }
 
             sum = sum - oldVal + val;
             sumSq = sumSq - (oldVal * oldVal) + (val * val);
@@ -297,7 +321,11 @@ public sealed class Skew : AbstractBase
                 for (int k = 0; k < period; k++)
                 {
                     double v = source[startIdx + k];
-                    if (!double.IsFinite(v)) v = 0;
+                    if (!double.IsFinite(v))
+                    {
+                        v = 0;
+                    }
+
                     recalcSum += v;
                     recalcSumSq += v * v;
                     recalcSumCu += v * v * v;
@@ -315,13 +343,20 @@ public sealed class Skew : AbstractBase
         double mean = sum / n;
 
         double m2Numerator = sumSq - (sum * sum) / n;
-        if (m2Numerator < Epsilon) return 0;
+        if (m2Numerator < Epsilon)
+        {
+            return 0;
+        }
+
         double m2 = m2Numerator / n;
 
         double m3Numerator = sumCu - 3 * mean * sumSq + 2 * n * mean * mean * mean;
         double m3 = m3Numerator / n;
 
-        if (m2 <= Epsilon) return 0;
+        if (m2 <= Epsilon)
+        {
+            return 0;
+        }
 
         double g1 = m3 / (m2 * Math.Sqrt(m2));
 
@@ -367,7 +402,10 @@ public sealed class Skew : AbstractBase
 
         WarmupSkew(period, isPopulation, ref srcRef, ref outRef, out double sum, out double sumSq, out double sumCu);
 
-        if (len <= period) return;
+        if (len <= period)
+        {
+            return;
+        }
 
         var vInvN = Vector256.Create(invN);
         var vN = Vector256.Create(n);
@@ -509,4 +547,4 @@ public sealed class Skew : AbstractBase
             Unsafe.Add(ref outRef, i) = CalculateSkewFromSums(sum, sumSq, sumCu, n, isPopulation);
         }
     }
-}
+}

lib/statistics/stddev/StdDev.Validation.Tests.cs

@@ -19,9 +19,16 @@ public sealed class StdDevValidationTests : IDisposable
 
     private void Dispose(bool disposing)
     {
-        if (_disposed) return;
+        if (_disposed)
+        {
+            return;
+        }
+
         _disposed = true;
-        if (disposing) _testData?.Dispose();
+        if (disposing)
+        {
+            _testData?.Dispose();
+        }
     }
 
     #region Skender Validation

lib/statistics/stddev/StdDev.cs

@@ -57,7 +57,10 @@ public sealed class StdDev : AbstractBase
 
     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);
@@ -189,4 +192,4 @@ public sealed class StdDev : AbstractBase
             data[i] = (val > 0) ? Math.Sqrt(val) : 0.0;
         }
     }
-}
+}

lib/statistics/sum/Sum.Tests.cs

@@ -392,7 +392,9 @@ public class SumTests
 
         var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 42);
         for (int i = 0; i < source.Length; i++)
+        {
             source[i] = gbm.Next().Close;
+        }
 
         Sum.Batch(source.AsSpan(), output.AsSpan(), 100);
 
@@ -520,7 +522,9 @@ public class SumTests
     {
         var series = new TSeries();
         for (int i = 1; i <= 10; i++)
+        {
             series.Add(DateTime.UtcNow, i * 10);
+        }
         // 10, 20, 30, 40, 50, 60, 70, 80, 90, 100
 
         var (results, indicator) = Sum.Calculate(series, 5);

lib/statistics/sum/Sum.Validation.Tests.cs

@@ -26,9 +26,16 @@ public sealed class SumValidationTests : IDisposable
 
     private void Dispose(bool disposing)
     {
-        if (_disposed) return;
+        if (_disposed)
+        {
+            return;
+        }
+
         _disposed = true;
-        if (disposing) _testData?.Dispose();
+        if (disposing)
+        {
+            _testData?.Dispose();
+        }
     }
 
     [Fact]

lib/statistics/sum/Sum.cs

@@ -67,7 +67,9 @@ public sealed class Sum : AbstractBase
     public Sum(int period)
     {
         if (period <= 0)
+        {
             throw new ArgumentException("Period must be greater than 0", nameof(period));
+        }
 
         _period = period;
         _buffer = new RingBuffer(period);
@@ -163,7 +165,10 @@ public sealed class Sum : AbstractBase
     /// </summary>
     public override void Prime(ReadOnlySpan<double> source, TimeSpan? step = null)
     {
-        if (source.Length == 0) return;
+        if (source.Length == 0)
+        {
+            return;
+        }
 
         // Reset state
         _buffer.Clear();
@@ -284,7 +289,10 @@ public sealed class Sum : AbstractBase
 
     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);
@@ -325,12 +333,20 @@ public sealed class Sum : AbstractBase
     public static void Batch(ReadOnlySpan<double> source, Span<double> output, int period)
     {
         if (source.Length != output.Length)
+        {
             throw new ArgumentException("Source and output must have the same length", nameof(output));
+        }
+
         if (period <= 0)
+        {
             throw new ArgumentException("Period must be greater than 0", nameof(period));
+        }
 
         int len = source.Length;
-        if (len == 0) return;
+        if (len == 0)
+        {
+            return;
+        }
 
         CalculateScalarCore(source, output, period);
     }
@@ -378,72 +394,82 @@ public sealed class Sum : AbstractBase
             int tickCount = 0;
 
             // Warmup phase
-        int warmupEnd = Math.Min(period, len);
-        for (int i = 0; i < warmupEnd; i++)
-        {
-            double val = source[i];
-            if (double.IsFinite(val))
-                lastValid = val;
-            else
-                val = lastValid;
+            int warmupEnd = Math.Min(period, len);
+            for (int i = 0; i < warmupEnd; i++)
+            {
+                double val = source[i];
+                if (double.IsFinite(val))
+                {
+                    lastValid = val;
+                }
+                else
+                {
+                    val = lastValid;
+                }
 
-            // Kahan-Babuška add
-            double y = val - c;
-            double t = sum + y;
-            c = t - sum - y;
-            sum = t;
+                // Kahan-Babuška add
+                double y = val - c;
+                double t = sum + y;
+                c = t - sum - y;
+                sum = t;
 
-            double z = c - cc;
-            double tt = sum + z;
-            cc = tt - sum - z;
-            sum = tt;
+                double z = c - cc;
+                double tt = sum + z;
+                cc = tt - sum - z;
+                sum = tt;
 
-            buffer[i] = val;
-            output[i] = sum;
-        }
+                buffer[i] = val;
+                output[i] = sum;
+            }
 
-        // Main phase with sliding window
-        for (int i = period; i < len; i++)
-        {
-            double val = source[i];
-            if (double.IsFinite(val))
-                lastValid = val;
-            else
-                val = lastValid;
+            // Main phase with sliding window
+            for (int i = period; i < len; i++)
+            {
+                double val = source[i];
+                if (double.IsFinite(val))
+                {
+                    lastValid = val;
+                }
+                else
+                {
+                    val = lastValid;
+                }
 
-            double oldVal = buffer[bufferIndex];
+                double oldVal = buffer[bufferIndex];
 
-            // Kahan-Babuška subtract old value
-            double yS = -oldVal - c;
-            double tS = sum + yS;
-            c = tS - sum - yS;
-            sum = tS;
+                // Kahan-Babuška subtract old value
+                double yS = -oldVal - c;
+                double tS = sum + yS;
+                c = tS - sum - yS;
+                sum = tS;
 
-            double zS = c - cc;
-            double ttS = sum + zS;
-            cc = ttS - sum - zS;
-            sum = ttS;
+                double zS = c - cc;
+                double ttS = sum + zS;
+                cc = ttS - sum - zS;
+                sum = ttS;
 
-            // Kahan-Babuška add new value
-            double yA = val - c;
-            double tA = sum + yA;
-            c = tA - sum - yA;
-            sum = tA;
+                // Kahan-Babuška add new value
+                double yA = val - c;
+                double tA = sum + yA;
+                c = tA - sum - yA;
+                sum = tA;
 
-            double zA = c - cc;
-            double ttA = sum + zA;
-            cc = ttA - sum - zA;
-            sum = ttA;
+                double zA = c - cc;
+                double ttA = sum + zA;
+                cc = ttA - sum - zA;
+                sum = ttA;
 
-            buffer[bufferIndex] = val;
-            bufferIndex++;
-            if (bufferIndex >= period)
-                bufferIndex = 0;
+                buffer[bufferIndex] = val;
+                bufferIndex++;
+                if (bufferIndex >= period)
+                {
+                    bufferIndex = 0;
+                }
 
-            output[i] = sum;
+                output[i] = sum;
 
-            // Periodic resync for long sequences
-            tickCount++;
+                // Periodic resync for long sequences
+                tickCount++;
                 if (tickCount >= ResyncInterval)
                 {
                     tickCount = 0;
@@ -468,7 +494,10 @@ public sealed class Sum : AbstractBase
         }
         finally
         {
-            if (bufferArray != null) ArrayPool<double>.Shared.Return(bufferArray);
+            if (bufferArray != null)
+            {
+                ArrayPool<double>.Shared.Return(bufferArray);
+            }
         }
     }
 
@@ -482,4 +511,4 @@ public sealed class Sum : AbstractBase
         _p_state = default;
         Last = default;
     }
-}
+}

lib/statistics/variance/Variance.Quantower.cs

@@ -52,7 +52,9 @@ public sealed class VarianceIndicator : Indicator, IWatchlistIndicator
     protected override void OnUpdate(UpdateArgs args)
     {
         if (args.Reason != UpdateReason.NewBar && args.Reason != UpdateReason.HistoricalBar)
+        {
             return;
+        }
 
         var item = this.HistoricalData[this.Count - 1, SeekOriginHistory.Begin];
         double value = _priceSelector(item);

lib/statistics/variance/Variance.Tests.cs

@@ -46,20 +46,20 @@ public class VarianceTests
     {
         // Use simple known values for easier debugging
         var variance = new Variance(3);
-        
+
         // Add 3 values: 1, 2, 3
         variance.Update(new TValue(DateTime.UtcNow, 1), isNew: true);
         variance.Update(new TValue(DateTime.UtcNow, 2), isNew: true);
         var originalResult = variance.Update(new TValue(DateTime.UtcNow, 3), isNew: true);
-        
+
         double expectedVariance = originalResult.Value; // Variance of [1,2,3]
-        
+
         // Now correct the 3rd value to 10 (isNew=false)
         variance.Update(new TValue(DateTime.UtcNow, 10), isNew: false);
-        
+
         // Correct back to original value 3 (isNew=false)
         var restoredResult = variance.Update(new TValue(DateTime.UtcNow, 3), isNew: false);
-        
+
         // Should match original variance
         Assert.Equal(expectedVariance, restoredResult.Value, 1e-10);
     }
@@ -351,7 +351,10 @@ public class VarianceTests
         // Create large dataset to trigger SIMD path (>= 256)
         const int count = 1000;
         var data = new double[count];
-        for (int i = 0; i < count; i++) data[i] = (double)i;
+        for (int i = 0; i < count; i++)
+        {
+            data[i] = (double)i;
+        }
 
         var series = new TSeries(new System.Collections.Generic.List<long>(new long[count]), new System.Collections.Generic.List<double>(data));
 
@@ -714,4 +717,4 @@ public class VarianceTests
         Assert.Equal(0, output[0]); // N=1
         Assert.Equal(50, output[1]); // Var([10,20]) = 50
     }
-}
+}

lib/statistics/variance/Variance.cs

@@ -100,7 +100,10 @@ public sealed class Variance : AbstractBase
             double numerator = _sumSq - (_buffer.Sum * _buffer.Sum) / n;
 
             // Handle floating point noise
-            if (numerator < 0) numerator = 0;
+            if (numerator < 0)
+            {
+                numerator = 0;
+            }
 
             double denominator = _isPopulation ? n : (n - 1);
             variance = numerator / denominator;
@@ -113,7 +116,10 @@ public sealed class Variance : AbstractBase
 
     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);
@@ -181,12 +187,20 @@ public sealed class Variance : AbstractBase
     public static void Batch(ReadOnlySpan<double> source, Span<double> output, int period, bool isPopulation = false)
     {
         if (source.Length != output.Length)
+        {
             throw new ArgumentException("Source and output must have the same length", nameof(output));
+        }
+
         if (period < 2)
+        {
             throw new ArgumentException("Period must be greater than or equal to 2", nameof(period));
+        }
 
         int len = source.Length;
-        if (len == 0) return;
+        if (len == 0)
+        {
+            return;
+        }
 
         // Try SIMD path for large, clean datasets
         const int SimdThreshold = 256;
@@ -237,7 +251,10 @@ public sealed class Variance : AbstractBase
         for (; i < warmupEnd; i++)
         {
             double val = source[i];
-            if (!double.IsFinite(val)) val = 0; // Fallback
+            if (!double.IsFinite(val))
+            {
+                val = 0; // Fallback
+            }
 
             sum += val;
             sumSq = Math.FusedMultiplyAdd(val, val, sumSq);
@@ -247,7 +264,11 @@ public sealed class Variance : AbstractBase
             if (n > 1)
             {
                 double numerator = sumSq - (sum * sum) / n;
-                if (numerator < 0) numerator = 0;
+                if (numerator < 0)
+                {
+                    numerator = 0;
+                }
+
                 double denominator = isPopulation ? n : (n - 1);
                 output[i] = numerator / denominator;
             }
@@ -262,7 +283,10 @@ public sealed class Variance : AbstractBase
         for (; i < len; i++)
         {
             double val = source[i];
-            if (!double.IsFinite(val)) val = 0; // Fallback
+            if (!double.IsFinite(val))
+            {
+                val = 0; // Fallback
+            }
 
             double oldVal = buffer[bufferIndex];
 
@@ -272,11 +296,18 @@ public sealed class Variance : AbstractBase
 
             buffer[bufferIndex] = val;
             bufferIndex++;
-            if (bufferIndex >= period) bufferIndex = 0;
+            if (bufferIndex >= period)
+            {
+                bufferIndex = 0;
+            }
 
             double n = period;
             double numerator = sumSq - (sum * sum) / n;
-            if (numerator < 0) numerator = 0;
+            if (numerator < 0)
+            {
+                numerator = 0;
+            }
+
             double denominator = isPopulation ? n : (n - 1);
             output[i] = numerator / denominator;
 
@@ -305,7 +336,11 @@ public sealed class Variance : AbstractBase
             if (n > 1)
             {
                 double num = sumSq - (sum * sum) / n;
-                if (num < 0) num = 0;
+                if (num < 0)
+                {
+                    num = 0;
+                }
+
                 double den = isPopulation ? n : (n - 1);
                 Unsafe.Add(ref outRef, i) = num / den;
             }
@@ -330,7 +365,10 @@ public sealed class Variance : AbstractBase
 
         WarmupVariance(period, isPopulation, ref srcRef, ref outRef, out double sum, out double sumSq);
 
-        if (len <= period) return;
+        if (len <= period)
+        {
+            return;
+        }
 
         var vInvN = Vector512.Create(invN);
         var vInvDenom = Vector512.Create(invDenom);
@@ -420,7 +458,11 @@ public sealed class Variance : AbstractBase
             sumSq = Math.FusedMultiplyAdd(val, val, sumSq);
 
             double numerator = sumSq - sum * sum * invN;
-            if (numerator < 0) numerator = 0;
+            if (numerator < 0)
+            {
+                numerator = 0;
+            }
+
             Unsafe.Add(ref outRef, i) = numerator * invDenom;
         }
     }
@@ -439,7 +481,10 @@ public sealed class Variance : AbstractBase
 
         WarmupVariance(period, isPopulation, ref srcRef, ref outRef, out double sum, out double sumSq);
 
-        if (len <= period) return;
+        if (len <= period)
+        {
+            return;
+        }
 
         var vInvN = Vector128.Create(invN);
         var vInvDenom = Vector128.Create(invDenom);
@@ -517,7 +562,11 @@ public sealed class Variance : AbstractBase
             sumSq = Math.FusedMultiplyAdd(val, val, sumSq);
 
             double numerator = sumSq - sum * sum * invN;
-            if (numerator < 0) numerator = 0;
+            if (numerator < 0)
+            {
+                numerator = 0;
+            }
+
             Unsafe.Add(ref outRef, i) = numerator * invDenom;
         }
     }
@@ -536,7 +585,10 @@ public sealed class Variance : AbstractBase
 
         WarmupVariance(period, isPopulation, ref srcRef, ref outRef, out double sum, out double sumSq);
 
-        if (len <= period) return;
+        if (len <= period)
+        {
+            return;
+        }
 
         var vInvN = Vector256.Create(invN);
         var vInvDenom = Vector256.Create(invDenom);
@@ -634,8 +686,12 @@ public sealed class Variance : AbstractBase
             sumSq = Math.FusedMultiplyAdd(val, val, sumSq);
 
             double numerator = sumSq - sum * sum * invN;
-            if (numerator < 0) numerator = 0;
+            if (numerator < 0)
+            {
+                numerator = 0;
+            }
+
             Unsafe.Add(ref outRef, i) = numerator * invDenom;
         }
     }
-}
+}