Test completeness

lib/trends/kama/Kama.Tests.cs

@@ -60,6 +60,7 @@ public class KamaTests
 
         // Streaming
         var streamingResults = new TSeries();
+        Assert.True(series.Count > 0);
         foreach (var item in series)
         {
             streamingResults.Add(kamaStreaming.Update(item));
@@ -69,9 +70,9 @@ public class KamaTests
         var batchResults = kamaBatch.Update(series);
 
         Assert.Equal(streamingResults.Count, batchResults.Count);
-        for (int i = 0; i < streamingResults.Count; i++)
+        foreach (var (stream, batch) in streamingResults.Zip(batchResults))
         {
-            Assert.Equal(streamingResults[i].Value, batchResults[i].Value, 1e-9);
+            Assert.Equal(stream.Value, batch.Value, 1e-9);
         }
     }
 
@@ -168,4 +169,112 @@ public class KamaTests
         
         Assert.Equal(100, kama.Last.Value);
     }
+
+    [Fact]
+    public void Kama_Calc_IsNew_AcceptsParameter()
+    {
+        var kama = new Kama(10);
+        kama.Update(new TValue(DateTime.UtcNow, 100), isNew: true);
+        Assert.Equal(100, kama.Last.Value);
+    }
+
+    [Fact]
+    public void Kama_IterativeCorrections_RestoreToOriginalState()
+    {
+        var kama = new Kama(10);
+        var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1);
+
+        // Feed 20 new values (enough to fill buffer and stabilize)
+        TValue lastInput = default;
+        for (int i = 0; i < 20; i++)
+        {
+            var bar = gbm.Next(isNew: true);
+            lastInput = new TValue(bar.Time, bar.Close);
+            kama.Update(lastInput, isNew: true);
+        }
+
+        // Remember state
+        double valueAfter = kama.Last.Value;
+
+        // Generate 5 corrections with isNew=false (different values)
+        for (int i = 0; i < 5; i++)
+        {
+            var bar = gbm.Next(isNew: false);
+            kama.Update(new TValue(bar.Time, bar.Close), isNew: false);
+        }
+
+        // Feed the remembered last input again with isNew=false
+        TValue finalValue = kama.Update(lastInput, isNew: false);
+
+        // Should match the original state
+        Assert.Equal(valueAfter, finalValue.Value, 1e-9);
+    }
+
+    [Fact]
+    public void Kama_SpanCalc_ValidatesInput()
+    {
+        double[] source = [1, 2, 3, 4, 5];
+        double[] output = new double[5];
+        double[] wrongSizeOutput = new double[3];
+
+        Assert.Throws<ArgumentException>(() => Kama.Calculate(source.AsSpan(), output.AsSpan(), 0));
+        Assert.Throws<ArgumentException>(() => Kama.Calculate(source.AsSpan(), wrongSizeOutput.AsSpan(), 3));
+    }
+
+    [Fact]
+    public void Kama_SpanCalc_HandlesNaN()
+    {
+        double[] source = [100, 110, double.NaN, 120, 130];
+        double[] output = new double[5];
+
+        Kama.Calculate(source.AsSpan(), output.AsSpan(), 3);
+
+        foreach (var val in output)
+        {
+            Assert.True(double.IsFinite(val));
+        }
+    }
+
+    [Fact]
+    public void Kama_AllModes_ProduceSameResult()
+    {
+        // Arrange
+        int period = 10;
+        var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 123);
+        var bars = gbm.Fetch(1000, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
+        var series = bars.Close;
+        
+        // 1. Batch Mode
+        var batchSeries = Kama.Calculate(series, period);
+        double expected = batchSeries.Last.Value;
+
+        // 2. Span Mode
+        var tValues = series.Values.ToArray();
+        var spanInput = new ReadOnlySpan<double>(tValues);
+        var spanOutput = new double[tValues.Length];
+        Kama.Calculate(spanInput, spanOutput, period);
+        double spanResult = spanOutput[^1];
+
+        // 3. Streaming Mode
+        var streamingInd = new Kama(period);
+        for (int i = 0; i < series.Count; i++)
+        {
+            streamingInd.Update(series[i]);
+        }
+        double streamingResult = streamingInd.Last.Value;
+
+        // 4. Eventing Mode
+        var pubSource = new TSeries();
+        var eventingInd = new Kama(pubSource, period);
+        for (int i = 0; i < series.Count; i++)
+        {
+            pubSource.Add(series[i]);
+        }
+        double eventingResult = eventingInd.Last.Value;
+
+        // Assert
+        Assert.Equal(expected, spanResult, precision: 9);
+        Assert.Equal(expected, streamingResult, precision: 9);
+        Assert.Equal(expected, eventingResult, precision: 9);
+    }
 }

lib/trends/kama/Kama.cs

@@ -227,6 +227,12 @@ public sealed class Kama : ITValuePublisher
         return new TSeries(t, v);
     }
 
+    public static TSeries Calculate(TSeries source, int period, int fastPeriod = 2, int slowPeriod = 30)
+    {
+        var kama = new Kama(period, fastPeriod, slowPeriod);
+        return kama.Update(source);
+    }
+
     public static void Calculate(ReadOnlySpan<double> source, Span<double> output, int period, int fastPeriod = 2, int slowPeriod = 30)
     {
         if (period <= 0) throw new ArgumentException("Period must be greater than 0", nameof(period));