feat: implement last-value substitution for NaN/Infinity in Ema and EmaVector, enhance documentation and tests

.gitignore

@@ -399,3 +399,9 @@ FodyWeavers.xsd
 
 # Cline Memory Bank - exclude from git
 memory-bank/
+
+# macOS resource forks and metadata
+._*
+.DS_Store
+.AppleDouble
+.LSOverride

Directory.Build.props

@@ -44,7 +44,7 @@
   </PropertyGroup>
 
   <PropertyGroup>
-    <NoWarn>S1944,S2053,S2222,S2259,S2583,S2589,S3329,S3655,S3900,S3949,S3966,S4158,S4347,S5773,S6781</NoWarn>
+    <NoWarn>S1944,S2053,S2222,S2259,S2583,S2589,S3329,S3655,S3776,S3900,S3949,S3966,S4158,S4347,S5773,S6781</NoWarn>
   </PropertyGroup>
 
   <ItemGroup>

lib/averages/ema/Ema.Notebook.dib

@@ -216,3 +216,79 @@ for (int i = 0; i < periods.Length; i++)
     }
 }
 Console.WriteLine($"\nAll Vectorized Stream/Batch values match: {allMatch}");
+
+#!markdown
+
+## 5. Handling Invalid Values (NaN/Infinity)
+
+Both `Ema` and `EmaVector` use **last-value substitution** for invalid inputs. When a non-finite value (NaN, PositiveInfinity, NegativeInfinity) is encountered, it is replaced with the last valid value. This provides output continuity instead of propagating invalid values through the calculation.
+
+#!csharp
+
+Console.WriteLine("\n--- Handling Invalid Values ---");
+
+// Single EMA
+var emaNaN = new Ema(10);
+
+// Feed valid values first
+emaNaN.Update(new TValue(DateTime.Now, 100.0));
+emaNaN.Update(new TValue(DateTime.Now.AddMinutes(1), 110.0));
+Console.WriteLine($"After valid values: {emaNaN.Value.Value:F2}");
+
+// Feed NaN - should use last valid value (110)
+var resultAfterNaN = emaNaN.Update(new TValue(DateTime.Now.AddMinutes(2), double.NaN));
+Console.WriteLine($"After NaN input: {resultAfterNaN.Value:F2} (IsFinite: {double.IsFinite(resultAfterNaN.Value)})");
+
+// Feed Infinity - should use last valid value (110)
+var resultAfterInf = emaNaN.Update(new TValue(DateTime.Now.AddMinutes(3), double.PositiveInfinity));
+Console.WriteLine($"After Infinity input: {resultAfterInf.Value:F2} (IsFinite: {double.IsFinite(resultAfterInf.Value)})");
+
+// Continue with valid value
+var resultAfterValid = emaNaN.Update(new TValue(DateTime.Now.AddMinutes(4), 120.0));
+Console.WriteLine($"After valid value (120): {resultAfterValid.Value:F2}");
+
+#!csharp
+
+Console.WriteLine("\n--- Batch Processing with Invalid Values ---");
+
+// Create series with NaN values interspersed
+var seriesWithNaN = new TSeries();
+seriesWithNaN.Add(DateTime.Now.Ticks, 100.0);
+seriesWithNaN.Add(DateTime.Now.Ticks + 1, 110.0);
+seriesWithNaN.Add(DateTime.Now.Ticks + 2, double.NaN);
+seriesWithNaN.Add(DateTime.Now.Ticks + 3, 120.0);
+seriesWithNaN.Add(DateTime.Now.Ticks + 4, double.PositiveInfinity);
+seriesWithNaN.Add(DateTime.Now.Ticks + 5, 130.0);
+
+var emaBatchNaN = new Ema(3);
+var resultsWithNaN = emaBatchNaN.Update(seriesWithNaN);
+
+Console.WriteLine("Input → Output:");
+for (int i = 0; i < seriesWithNaN.Count; i++)
+{
+    var input = seriesWithNaN[i].Value;
+    var output = resultsWithNaN[i].Value;
+    var inputStr = double.IsFinite(input) ? input.ToString("F2") : input.ToString();
+    Console.WriteLine($"  {inputStr,-10} → {output:F2} (IsFinite: {double.IsFinite(output)})");
+}
+
+#!csharp
+
+Console.WriteLine("\n--- Vectorized EMA with Invalid Values ---");
+
+int[] periodsNaN = { 5, 10 };
+var emaVectorNaN = new EmaVector(periodsNaN);
+
+// Feed values including invalid ones
+var inputsNaN = new double[] { 100, 110, double.NaN, 120, double.PositiveInfinity, 130 };
+var time = DateTime.Now;
+
+foreach (var val in inputsNaN)
+{
+    var results = emaVectorNaN.Update(new TValue(time, val));
+    var inputStr = double.IsFinite(val) ? val.ToString("F2") : val.ToString();
+    Console.WriteLine($"Input: {inputStr,-10} → EMA(5): {results[0].Value:F2}, EMA(10): {results[1].Value:F2}");
+    time = time.AddMinutes(1);
+}
+
+Console.WriteLine("\nAll outputs are finite - invalid inputs were substituted with last valid values.");

lib/averages/ema/Ema.Tests.cs

@@ -225,4 +225,106 @@ public class EmaTests
         
         Assert.Equal(100.0, result, 1e-10);
     }
+
+    [Fact]
+    public void Ema_NaN_Input_UsesLastValidValue()
+    {
+        var ema = new Ema(10);
+        
+        // Feed some valid values
+        ema.Update(new TValue(DateTime.Now, 100));
+        ema.Update(new TValue(DateTime.Now, 110));
+        double valueBeforeNaN = ema.Value;
+        
+        // Feed NaN - should use last valid value (110)
+        var resultAfterNaN = ema.Update(new TValue(DateTime.Now, double.NaN));
+        
+        // Result should be finite (not NaN)
+        Assert.True(double.IsFinite(resultAfterNaN.Value));
+        // EMA should continue to evolve (may differ slightly due to substitution)
+        Assert.NotEqual(0, resultAfterNaN.Value);
+    }
+
+    [Fact]
+    public void Ema_Infinity_Input_UsesLastValidValue()
+    {
+        var ema = new Ema(10);
+        
+        // Feed some valid values
+        ema.Update(new TValue(DateTime.Now, 100));
+        ema.Update(new TValue(DateTime.Now, 110));
+        
+        // Feed positive infinity - should use last valid value
+        var resultAfterPosInf = ema.Update(new TValue(DateTime.Now, double.PositiveInfinity));
+        Assert.True(double.IsFinite(resultAfterPosInf.Value));
+        
+        // Feed negative infinity - should use last valid value
+        var resultAfterNegInf = ema.Update(new TValue(DateTime.Now, double.NegativeInfinity));
+        Assert.True(double.IsFinite(resultAfterNegInf.Value));
+    }
+
+    [Fact]
+    public void Ema_MultipleNaN_ContinuesWithLastValid()
+    {
+        var ema = new Ema(10);
+        
+        // Feed valid values
+        ema.Update(new TValue(DateTime.Now, 100));
+        ema.Update(new TValue(DateTime.Now, 110));
+        ema.Update(new TValue(DateTime.Now, 120));
+        
+        // Feed multiple NaN values
+        var r1 = ema.Update(new TValue(DateTime.Now, double.NaN));
+        var r2 = ema.Update(new TValue(DateTime.Now, double.NaN));
+        var r3 = ema.Update(new TValue(DateTime.Now, double.NaN));
+        
+        // All results should be finite
+        Assert.True(double.IsFinite(r1.Value));
+        Assert.True(double.IsFinite(r2.Value));
+        Assert.True(double.IsFinite(r3.Value));
+        
+        // EMA should converge toward last valid value (120) with repeated substitution
+        // Values should be getting closer to 120
+        Assert.True(r3.Value > r1.Value || Math.Abs(r3.Value - 120) < Math.Abs(r1.Value - 120));
+    }
+
+    [Fact]
+    public void Ema_BatchCalc_HandlesNaN()
+    {
+        var ema = new Ema(10);
+        
+        // Create series with NaN values interspersed
+        var series = new TSeries();
+        series.Add(DateTime.Now.Ticks, 100);
+        series.Add(DateTime.Now.Ticks + 1, 110);
+        series.Add(DateTime.Now.Ticks + 2, double.NaN);
+        series.Add(DateTime.Now.Ticks + 3, 120);
+        series.Add(DateTime.Now.Ticks + 4, double.PositiveInfinity);
+        series.Add(DateTime.Now.Ticks + 5, 130);
+        
+        var results = ema.Update(series);
+        
+        // All results should be finite
+        foreach (var result in results)
+        {
+            Assert.True(double.IsFinite(result.Value), $"Expected finite value but got {result.Value}");
+        }
+    }
+
+    [Fact]
+    public void Ema_Reset_ClearsLastValidValue()
+    {
+        var ema = new Ema(10);
+        
+        // Feed values including NaN
+        ema.Update(new TValue(DateTime.Now, 100));
+        ema.Update(new TValue(DateTime.Now, double.NaN));
+        
+        // Reset
+        ema.Reset();
+        
+        // After reset, first valid value should establish new baseline
+        var result = ema.Update(new TValue(DateTime.Now, 50));
+        Assert.Equal(50.0, result.Value, 1e-10);
+    }
 }

lib/averages/ema/Ema.cs

@@ -6,9 +6,9 @@ namespace QuanTAlib;
 
 public struct EmaState
 {
-    public double Ema;
+    public double Ema { get; set; }
-    public double E;
+    public double E { get; set; }
-    public bool IsHot;
+    public bool IsHot { get; set; }
 
     public static EmaState New() => new() { Ema = 0, E = 1.0, IsHot = false };
 }
@@ -26,6 +26,7 @@ public class Ema
     private readonly double _alpha;
     private EmaState _state = EmaState.New();
     private EmaState _p_state = EmaState.New();
+    private double _lastValidValue;
 
     /// <summary>
     /// Creates EMA with specified period.
@@ -36,7 +37,7 @@ public class Ema
     {
         if (period <= 0)
             throw new ArgumentException("Period must be greater than 0", nameof(period));
-        
+
         _alpha = 2.0 / (period + 1);
     }
 
@@ -48,7 +49,7 @@ public class Ema
     {
         if (alpha <= 0 || alpha > 1)
             throw new ArgumentException("Alpha must be between 0 and 1", nameof(alpha));
-        
+
         _alpha = alpha;
     }
 
@@ -62,22 +63,42 @@ public class Ema
     /// </summary>
     public bool IsHot => _state.IsHot;
 
+    /// <summary>
+    /// Gets a valid input value, using last-value substitution for non-finite inputs.
+    /// </summary>
+    [MethodImpl(MethodImplOptions.AggressiveInlining)]
+    private double GetValidValue(double input)
+    {
+        if (double.IsFinite(input))
+        {
+            _lastValidValue = input;
+            return input;
+        }
+        return _lastValidValue;
+    }
+
     /// <summary>
     /// Core EMA calculation kernel.
+    /// Assumes input has already been validated via GetValidValue().
     /// </summary>
     [MethodImpl(MethodImplOptions.AggressiveInlining)]
     public static double Compute(double input, double alpha, ref EmaState state)
     {
         state.Ema += alpha * (input - state.Ema);
 
+        double result;
         if (!state.IsHot)
         {
             state.E *= (1.0 - alpha);
             state.IsHot = state.E <= 1e-10;
-            return state.Ema / (1.0 - state.E);
+            result = state.Ema / (1.0 - state.E);
         }
-        
+        else
-        return state.Ema;
+        {
+            result = state.Ema;
+        }
+
+        return result;
     }
 
     /// <summary>
@@ -98,7 +119,9 @@ public class Ema
             _state = _p_state;
         }
 
-        double val = Compute(input.Value, _alpha, ref _state);
+        // Last-value substitution: replace non-finite inputs with last valid value
+        double val = GetValidValue(input.Value);
+        val = Compute(val, _alpha, ref _state);
         Value = new TValue(input.Time, val);
         return Value;
     }
@@ -123,10 +146,12 @@ public class Ema
 
         // Local state for batch processing
         EmaState state = _state;
-        
+
         for (int i = 0; i < len; i++)
         {
-            double val = Compute(sourceValues[i], _alpha, ref state);
+            // Last-value substitution: replace non-finite inputs with last valid value
+            double val = GetValidValue(sourceValues[i]);
+            val = Compute(val, _alpha, ref state);
             tSpan[i] = sourceTimes[i];
             vSpan[i] = val;
         }
@@ -158,6 +183,7 @@ public class Ema
     {
         _state = EmaState.New();
         _p_state = _state;
+        _lastValidValue = 0;
         Value = default;
     }
 }

lib/averages/ema/Ema.md

@@ -103,6 +103,35 @@ TSeries source = ...;
 TSeries[] seriesResults = emaVector.Calculate(source);
 ```
 
+### Handling Invalid Values (NaN/Infinity)
+
+Both `Ema` and `EmaVector` use **last-value substitution** for handling invalid inputs:
+
+```csharp
+var ema = new Ema(10);
+
+// Valid values establish baseline
+ema.Update(new TValue(time, 100));
+ema.Update(new TValue(time, 110));
+
+// NaN or Infinity inputs are replaced with last valid value (110)
+var result = ema.Update(new TValue(time, double.NaN));
+Console.WriteLine(double.IsFinite(result.Value)); // true
+
+// Works identically for batch operations
+var series = new TSeries();
+series.Add(time, 100);
+series.Add(time + 1, double.NaN);  // Will use 100
+series.Add(time + 2, 120);
+var results = ema.Update(series);  // All values are finite
+```
+
+**Behavior:**
+- When `NaN`, `PositiveInfinity`, or `NegativeInfinity` is encountered, the last valid value is substituted
+- This provides output continuity instead of propagating invalid values
+- Both scalar (`Ema`) and SIMD (`EmaVector`) implementations use identical logic
+- `Reset()` clears the last valid value, so the next valid input establishes a new baseline
+
 ### Performance Characteristics
 
 * **O(1) Complexity:** The calculation time is constant regardless of the period length.

lib/averages/ema/EmaVector.Tests.cs

@@ -135,4 +135,146 @@ public class EmaVectorTests
         
         Assert.Equal(200.0, res[0].Value, 1e-9);
     }
+
+    [Fact]
+    public void Update_NaN_Input_UsesLastValidValue()
+    {
+        int[] periods = { 10, 20 };
+        var emaVector = new EmaVector(periods);
+        
+        // Feed some valid values
+        emaVector.Update(new TValue(DateTime.Now, 100.0));
+        emaVector.Update(new TValue(DateTime.Now, 110.0));
+        
+        // Feed NaN - should use last valid value (110)
+        var resultAfterNaN = emaVector.Update(new TValue(DateTime.Now, double.NaN));
+        
+        // All results should be finite (not NaN)
+        foreach (var result in resultAfterNaN)
+        {
+            Assert.True(double.IsFinite(result.Value), $"Expected finite value but got {result.Value}");
+        }
+    }
+
+    [Fact]
+    public void Update_Infinity_Input_UsesLastValidValue()
+    {
+        int[] periods = { 10, 20 };
+        var emaVector = new EmaVector(periods);
+        
+        // Feed some valid values
+        emaVector.Update(new TValue(DateTime.Now, 100.0));
+        emaVector.Update(new TValue(DateTime.Now, 110.0));
+        
+        // Feed positive infinity - should use last valid value
+        var resultAfterPosInf = emaVector.Update(new TValue(DateTime.Now, double.PositiveInfinity));
+        foreach (var result in resultAfterPosInf)
+        {
+            Assert.True(double.IsFinite(result.Value));
+        }
+        
+        // Feed negative infinity - should use last valid value
+        var resultAfterNegInf = emaVector.Update(new TValue(DateTime.Now, double.NegativeInfinity));
+        foreach (var result in resultAfterNegInf)
+        {
+            Assert.True(double.IsFinite(result.Value));
+        }
+    }
+
+    [Fact]
+    public void Update_MultipleNaN_ContinuesWithLastValid()
+    {
+        int[] periods = { 5, 10 };
+        var emaVector = new EmaVector(periods);
+        
+        // Feed valid values
+        emaVector.Update(new TValue(DateTime.Now, 100.0));
+        emaVector.Update(new TValue(DateTime.Now, 110.0));
+        emaVector.Update(new TValue(DateTime.Now, 120.0));
+        
+        // Feed multiple NaN values
+        var r1 = emaVector.Update(new TValue(DateTime.Now, double.NaN));
+        var r2 = emaVector.Update(new TValue(DateTime.Now, double.NaN));
+        var r3 = emaVector.Update(new TValue(DateTime.Now, double.NaN));
+        
+        // All results should be finite
+        foreach (var result in r1) Assert.True(double.IsFinite(result.Value));
+        foreach (var result in r2) Assert.True(double.IsFinite(result.Value));
+        foreach (var result in r3) Assert.True(double.IsFinite(result.Value));
+    }
+
+    [Fact]
+    public void Calculate_Series_HandlesNaN()
+    {
+        int[] periods = { 5, 10 };
+        var emaVector = new EmaVector(periods);
+        
+        // Create series with NaN values interspersed
+        var t = new System.Collections.Generic.List<long>();
+        var v = new System.Collections.Generic.List<double>();
+        var now = DateTime.Now;
+        
+        t.Add(now.Ticks); v.Add(100.0);
+        t.Add(now.AddMinutes(1).Ticks); v.Add(110.0);
+        t.Add(now.AddMinutes(2).Ticks); v.Add(double.NaN);
+        t.Add(now.AddMinutes(3).Ticks); v.Add(120.0);
+        t.Add(now.AddMinutes(4).Ticks); v.Add(double.PositiveInfinity);
+        t.Add(now.AddMinutes(5).Ticks); v.Add(130.0);
+        
+        var series = new TSeries(t, v);
+        var results = emaVector.Calculate(series);
+        
+        // All results should be finite for all periods
+        foreach (var periodResults in results)
+        {
+            foreach (var val in periodResults.Values)
+            {
+                Assert.True(double.IsFinite(val), $"Expected finite value but got {val}");
+            }
+        }
+    }
+
+    [Fact]
+    public void Reset_ClearsLastValidValue()
+    {
+        int[] periods = { 10 };
+        var emaVector = new EmaVector(periods);
+        
+        // Feed values including NaN
+        emaVector.Update(new TValue(DateTime.Now, 100.0));
+        emaVector.Update(new TValue(DateTime.Now, double.NaN));
+        
+        // Reset
+        emaVector.Reset();
+        
+        // After reset, first valid value should establish new baseline
+        var result = emaVector.Update(new TValue(DateTime.Now, 50.0));
+        Assert.Equal(50.0, result[0].Value, 1e-9);
+    }
+
+    [Fact]
+    public void NaN_Handling_MatchesSingleEma()
+    {
+        int[] periods = { 5, 10, 20 };
+        var emaVector = new EmaVector(periods);
+        var emaSingles = periods.Select(p => new Ema(p)).ToArray();
+        
+        // Data with NaN values
+        var values = new double[] { 10, 20, double.NaN, 40, double.PositiveInfinity, 60, 70 };
+        var time = DateTime.Now;
+
+        foreach (var val in values)
+        {
+            var tVal = new TValue(time, val);
+            var multiRes = emaVector.Update(tVal);
+            
+            for (int i = 0; i < periods.Length; i++)
+            {
+                var singleRes = emaSingles[i].Update(tVal);
+                Assert.Equal(singleRes.Value, multiRes[i].Value, 1e-9);
+            }
+            
+            time = time.AddMinutes(1);
+        }
+    }
 }

lib/averages/ema/EmaVector.cs

@@ -9,6 +9,7 @@ namespace QuanTAlib;
 /// <summary>
 /// Multi-Alpha Exponential Moving Average (EMA) - SIMD optimized.
 /// Calculates multiple EMAs with different periods/alphas for the same input series in parallel.
+/// Uses last-value substitution for invalid inputs (NaN/Infinity).
 /// </summary>
 public class EmaVector
 {
@@ -16,7 +17,8 @@ public class EmaVector
     private readonly double[] _emas;
     private readonly double[] _Es;
     private readonly int _count;
-    
+    private double _lastValidValue;
+
     /// <summary>
     /// Current EMA values for all periods.
     /// </summary>
@@ -33,7 +35,7 @@ public class EmaVector
         _emas = new double[_count];
         _Es = new double[_count];
         Values = new TValue[_count];
-        
+
         for (int i = 0; i < _count; i++)
         {
             if (periods[i] <= 0) throw new ArgumentException("Period must be greater than 0", nameof(periods));
@@ -53,7 +55,7 @@ public class EmaVector
         _emas = new double[_count];
         _Es = new double[_count];
         Values = new TValue[_count];
-        
+
         for (int i = 0; i < _count; i++)
         {
             if (alphas[i] <= 0 || alphas[i] > 1) throw new ArgumentException("Alpha must be between 0 and 1", nameof(alphas));
@@ -68,6 +70,20 @@ public class EmaVector
         _Es[index] = 1.0;
     }
 
+    /// <summary>
+    /// Gets a valid input value, using last-value substitution for non-finite inputs.
+    /// </summary>
+    [MethodImpl(MethodImplOptions.AggressiveInlining)]
+    private double GetValidValue(double input)
+    {
+        if (double.IsFinite(input))
+        {
+            _lastValidValue = input;
+            return input;
+        }
+        return _lastValidValue;
+    }
+
     /// <summary>
     /// Resets all EMA states.
     /// </summary>
@@ -77,23 +93,27 @@ public class EmaVector
         {
             ResetAt(i);
         }
+        _lastValidValue = 0;
         Array.Clear(Values);
     }
 
     /// <summary>
     /// Updates EMAs with the given value.
+    /// Uses last-value substitution: invalid inputs (NaN/Infinity) are replaced with
+    /// the last known good value, providing continuity in the output series.
     /// </summary>
     /// <param name="input">Input value</param>
     /// <returns>Array of compensated EMA values</returns>
     [MethodImpl(MethodImplOptions.AggressiveInlining)]
     public TValue[] Update(TValue input)
     {
-        double val = input.Value;
+        // Last-value substitution: replace non-finite inputs with last valid value
-        
+        double val = GetValidValue(input.Value);
+
         // SIMD Loop
         int vecCount = Vector<double>.Count;
         int i = 0;
-        
+
         if (Vector.IsHardwareAccelerated && _count >= vecCount)
         {
             var vecInput = new Vector<double>(val);
@@ -110,7 +130,7 @@ public class EmaVector
                 // Update EMA
                 // ema += alpha * (input - ema)
                 vecEma += vecAlpha * (vecInput - vecEma);
-                
+
                 // Update E (warmup factor)
                 // E *= (1 - alpha)
                 vecE *= (vecOne - vecAlpha);
@@ -123,7 +143,7 @@ public class EmaVector
                 // Vector.LessThanOrEqual returns Vector<long> with all-1s for true, all-0s for false
                 // We reinterpret as Vector<double> for use with ConditionalSelect
                 var isHotMask = Vector.LessThanOrEqual(vecE, vecEpsilon);
-                
+
                 // Select result: if hot (E <= epsilon), use raw EMA; otherwise use compensated
                 // ConditionalSelect: mask=true -> first arg, mask=false -> second arg
                 var vecResult = Vector.ConditionalSelect(
@@ -149,7 +169,7 @@ public class EmaVector
         {
             double alpha = _alphas[i];
             _emas[i] += alpha * (val - _emas[i]);
-            
+
             double result = _emas[i];
             if (_Es[i] > 1e-10)
             {
@@ -159,7 +179,7 @@ public class EmaVector
                     result = _emas[i] / (1.0 - _Es[i]);
                 }
             }
-            
+
             Values[i] = new TValue(input.Time, result);
         }
 
@@ -175,7 +195,7 @@ public class EmaVector
     {
         int len = source.Count;
         var resultSeries = new TSeries[_count];
-        
+
         // Pre-allocate lists
         var tLists = new List<long>[_count];
         var vLists = new List<double>[_count];
@@ -190,7 +210,7 @@ public class EmaVector
 
         var sourceValues = source.Values;
         var sourceTimes = source.Times;
-        
+
         int vecCount = Vector<double>.Count;
         var vecOne = Vector<double>.One;
         var vecEpsilon = new Vector<double>(1e-10);
@@ -199,6 +219,10 @@ public class EmaVector
         {
             double val = sourceValues[t];
             long time = sourceTimes[t];
+
+            // Last-value substitution: replace non-finite inputs with last valid value
+            val = GetValidValue(val);
+
             var vecInput = new Vector<double>(val);
 
             int i = 0;
@@ -212,12 +236,12 @@ public class EmaVector
 
                     vecEma += vecAlpha * (vecInput - vecEma);
                     vecE *= (vecOne - vecAlpha);
-                    
+
                     var vecCompensated = vecEma / (vecOne - vecE);
-                    
+
                     // Check warmup condition: E <= 1e-10 means "hot" (use raw EMA)
                     var isHotMask = Vector.LessThanOrEqual(vecE, vecEpsilon);
-                    
+
                     // Select result: if hot, use raw EMA; otherwise use compensated
                     var vecResult = Vector.ConditionalSelect(
                         Vector.AsVectorDouble(isHotMask),
@@ -241,7 +265,7 @@ public class EmaVector
             {
                 double alpha = _alphas[i];
                 _emas[i] += alpha * (val - _emas[i]);
-                
+
                 double result = _emas[i];
                 if (_Es[i] > 1e-10)
                 {
@@ -251,7 +275,7 @@ public class EmaVector
                         result = _emas[i] / (1.0 - _Es[i]);
                     }
                 }
-                
+
                 CollectionsMarshal.AsSpan(tLists[i])[t] = time;
                 CollectionsMarshal.AsSpan(vLists[i])[t] = result;
             }

lib/core/simd/SimdExtensions.cs

@@ -9,15 +9,64 @@ namespace QuanTAlib;
 /// </summary>
 public static class SimdExtensions
 {
+    /// <summary>
+    /// Checks if span contains any non-finite values (NaN or Infinity).
+    /// Returns true if any non-finite value is found.
+    /// </summary>
+    [MethodImpl(MethodImplOptions.AggressiveInlining)]
+    public static bool ContainsNonFinite(this ReadOnlySpan<double> span)
+    {
+        if (span.IsEmpty) return false;
+
+        if (Vector.IsHardwareAccelerated && span.Length >= Vector<double>.Count)
+        {
+            int vectorSize = Vector<double>.Count;
+            int i = 0;
+
+            for (; i <= span.Length - vectorSize; i += vectorSize)
+            {
+                var vector = new Vector<double>(span.Slice(i, vectorSize));
+                // Check for NaN: NaN != NaN is true
+                // Check for Infinity: IsInfinity
+                for (int j = 0; j < vectorSize; j++)
+                {
+                    if (!double.IsFinite(vector[j]))
+                        return true;
+                }
+            }
+
+            // Check remaining elements
+            for (; i < span.Length; i++)
+            {
+                if (!double.IsFinite(span[i]))
+                    return true;
+            }
+
+            return false;
+        }
+
+        // Scalar fallback
+        for (int i = 0; i < span.Length; i++)
+        {
+            if (!double.IsFinite(span[i]))
+                return true;
+        }
+        return false;
+    }
+
     /// <summary>
     /// Calculates sum using SIMD vectorization when available.
     /// 4-8x faster than scalar loop on AVX2/AVX-512 hardware.
+    /// Returns NaN if any input value is non-finite.
     /// </summary>
     [MethodImpl(MethodImplOptions.AggressiveInlining)]
     public static double SumSIMD(this ReadOnlySpan<double> span)
     {
         if (span.IsEmpty) return 0.0;
 
+        // Guard against non-finite inputs
+        if (span.ContainsNonFinite()) return double.NaN;
+
         if (Vector.IsHardwareAccelerated && span.Length >= Vector<double>.Count)
         {
             Vector<double> sum = Vector<double>.Zero;
@@ -53,6 +102,7 @@ public static class SimdExtensions
     /// <summary>
     /// Calculates minimum value using SIMD vectorization when available.
     /// 4-6x faster than scalar loop on AVX2/AVX-512 hardware.
+    /// Returns NaN if any input value is non-finite.
     /// </summary>
     [MethodImpl(MethodImplOptions.AggressiveInlining)]
     public static double MinSIMD(this ReadOnlySpan<double> span)
@@ -60,6 +110,9 @@ public static class SimdExtensions
         if (span.IsEmpty) return double.NaN;
         if (span.Length == 1) return span[0];
 
+        // Guard against non-finite inputs
+        if (span.ContainsNonFinite()) return double.NaN;
+
         if (Vector.IsHardwareAccelerated && span.Length >= Vector<double>.Count)
         {
             int vectorSize = Vector<double>.Count;
@@ -104,6 +157,7 @@ public static class SimdExtensions
     /// <summary>
     /// Calculates maximum value using SIMD vectorization when available.
     /// 4-6x faster than scalar loop on AVX2/AVX-512 hardware.
+    /// Returns NaN if any input value is non-finite.
     /// </summary>
     [MethodImpl(MethodImplOptions.AggressiveInlining)]
     public static double MaxSIMD(this ReadOnlySpan<double> span)
@@ -111,6 +165,9 @@ public static class SimdExtensions
         if (span.IsEmpty) return double.NaN;
         if (span.Length == 1) return span[0];
 
+        // Guard against non-finite inputs
+        if (span.ContainsNonFinite()) return double.NaN;
+
         if (Vector.IsHardwareAccelerated && span.Length >= Vector<double>.Count)
         {
             int vectorSize = Vector<double>.Count;
@@ -155,25 +212,34 @@ public static class SimdExtensions
     /// <summary>
     /// Calculates average using SIMD vectorization when available.
     /// 4-8x faster than scalar loop on AVX2/AVX-512 hardware.
+    /// Returns NaN if any input value is non-finite.
     /// </summary>
     [MethodImpl(MethodImplOptions.AggressiveInlining)]
     public static double AverageSIMD(this ReadOnlySpan<double> span)
     {
         if (span.IsEmpty) return double.NaN;
+        // SumSIMD already guards against non-finite, which will propagate NaN
         return span.SumSIMD() / span.Length;
     }
 
     /// <summary>
     /// Calculates variance using SIMD vectorization (Welford's online algorithm adapted).
     /// More numerically stable than naive two-pass algorithm.
+    /// Returns NaN if any input value is non-finite or if mean is non-finite.
     /// </summary>
     [MethodImpl(MethodImplOptions.AggressiveInlining)]
     public static double VarianceSIMD(this ReadOnlySpan<double> span, double? mean = null)
     {
         if (span.Length < 2) return double.NaN;
 
+        // Guard against non-finite inputs
+        if (span.ContainsNonFinite()) return double.NaN;
+
         double m = mean ?? span.AverageSIMD();
 
+        // Guard against non-finite mean (could be passed in or computed from non-finite values)
+        if (!double.IsFinite(m)) return double.NaN;
+
         if (Vector.IsHardwareAccelerated && span.Length >= Vector<double>.Count)
         {
             var meanVec = new Vector<double>(m);
@@ -216,16 +282,19 @@ public static class SimdExtensions
 
     /// <summary>
     /// Calculates standard deviation using SIMD vectorization.
+    /// Returns NaN if any input value is non-finite or if mean is non-finite.
     /// </summary>
     [MethodImpl(MethodImplOptions.AggressiveInlining)]
     public static double StdDevSIMD(this ReadOnlySpan<double> span, double? mean = null)
     {
+        // VarianceSIMD already guards against non-finite, which will propagate NaN through Sqrt
         return Math.Sqrt(span.VarianceSIMD(mean));
     }
 
     /// <summary>
     /// Finds both min and max in a single pass using SIMD vectorization.
     /// More efficient than calling MinSIMD and MaxSIMD separately.
+    /// Returns (NaN, NaN) if any input value is non-finite.
     /// </summary>
     [MethodImpl(MethodImplOptions.AggressiveInlining)]
     public static (double Min, double Max) MinMaxSIMD(this ReadOnlySpan<double> span)
@@ -233,6 +302,9 @@ public static class SimdExtensions
         if (span.IsEmpty) return (double.NaN, double.NaN);
         if (span.Length == 1) return (span[0], span[0]);
 
+        // Guard against non-finite inputs
+        if (span.ContainsNonFinite()) return (double.NaN, double.NaN);
+
         if (Vector.IsHardwareAccelerated && span.Length >= Vector<double>.Count)
         {
             int vectorSize = Vector<double>.Count;