SIMD Refactor: Merge simd-dev into dev (#55)

Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Co-authored-by: aider (openrouter/anthropic/claude-sonnet-4) <aider@aider.chat>
Co-authored-by: Warp <agent@warp.dev>

lib/trends_FIR/conv/Conv.Tests.cs

@@ -0,0 +1,231 @@
+
+namespace QuanTAlib;
+
+public class ConvTests
+{
+    [Fact]
+    public void Constructor_EmptyKernel_ThrowsArgumentException()
+    {
+        Assert.Throws<ArgumentException>(() => new Conv(Array.Empty<double>()));
+        Assert.Throws<ArgumentException>(() => new Conv(null!));
+    }
+
+    [Fact]
+    public void BasicCalculation_MatchesExpected()
+    {
+        // Kernel: [0.5, 1.0]
+        // Data: [1, 2, 3, 4]
+        // 1: 1*1.0 = 1.0 (partial)
+        // 2: 1*0.5 + 2*1.0 = 2.5
+        // 3: 2*0.5 + 3*1.0 = 4.0
+        // 4: 3*0.5 + 4*1.0 = 5.5
+
+        double[] kernel = [0.5, 1.0];
+        var conv = new Conv(kernel);
+
+        var result1 = conv.Update(new TValue(DateTime.UtcNow, 1));
+        Assert.Equal(1.0, result1.Value);
+
+        var result2 = conv.Update(new TValue(DateTime.UtcNow, 2));
+        Assert.Equal(2.5, result2.Value);
+
+        var result3 = conv.Update(new TValue(DateTime.UtcNow, 3));
+        Assert.Equal(4.0, result3.Value);
+
+        var result4 = conv.Update(new TValue(DateTime.UtcNow, 4));
+        Assert.Equal(5.5, result4.Value);
+    }
+
+    [Fact]
+    public void BarCorrection_UpdatesCorrectly()
+    {
+        double[] kernel = [0.5, 1.0];
+        var conv = new Conv(kernel);
+
+        // 1
+        conv.Update(new TValue(DateTime.UtcNow, 1));
+
+        // 2 (isNew=true) -> 2.5
+        var res1 = conv.Update(new TValue(DateTime.UtcNow, 2), isNew: true);
+        Assert.Equal(2.5, res1.Value);
+
+        // Update 2 to 3 (isNew=false)
+        // Buffer was [1, 2]. Now [1, 3].
+        // 1*0.5 + 3*1.0 = 3.5
+        var res2 = conv.Update(new TValue(DateTime.UtcNow, 3), isNew: false);
+        Assert.Equal(3.5, res2.Value);
+
+        // New bar 4 (isNew=true)
+        // Buffer was [1, 3]. New bar 4. Buffer becomes [3, 4].
+        // 3*0.5 + 4*1.0 = 1.5 + 4 = 5.5
+        var res3 = conv.Update(new TValue(DateTime.UtcNow, 4), isNew: true);
+        Assert.Equal(5.5, res3.Value);
+    }
+
+    [Fact]
+    public void NanHandling_UsesLastValid()
+    {
+        double[] kernel = [1.0, 1.0]; // Sum of last 2
+        var conv = new Conv(kernel);
+
+        // 1 -> 1
+        conv.Update(new TValue(DateTime.UtcNow, 1));
+
+        // NaN -> treated as 1. Buffer: [1, 1]. Result: 2.
+        var res = conv.Update(new TValue(DateTime.UtcNow, double.NaN));
+        Assert.Equal(2.0, res.Value);
+
+        // 2 -> Buffer: [1, 2]. Result: 3.
+        res = conv.Update(new TValue(DateTime.UtcNow, 2));
+        Assert.Equal(3.0, res.Value);
+    }
+
+    [Fact]
+    public void StaticCalculate_MatchesObjectApi()
+    {
+        double[] kernel = [0.5, 1.0];
+        var source = new TSeries();
+        source.Add(new TValue(DateTime.UtcNow, 1));
+        source.Add(new TValue(DateTime.UtcNow, 2));
+        source.Add(new TValue(DateTime.UtcNow, 3));
+        source.Add(new TValue(DateTime.UtcNow, 4));
+
+        var result = Conv.Batch(source, kernel);
+
+        Assert.Equal(1.0, result.Values[0]);
+        Assert.Equal(2.5, result.Values[1]);
+        Assert.Equal(4.0, result.Values[2]);
+        Assert.Equal(5.5, result.Values[3]);
+    }
+
+    [Fact]
+    public void Reset_ClearsState()
+    {
+        double[] kernel = [1.0, 1.0];
+        var conv = new Conv(kernel);
+
+        conv.Update(new TValue(DateTime.UtcNow, 1));
+        conv.Update(new TValue(DateTime.UtcNow, 2));
+        Assert.True(conv.IsHot);
+
+        conv.Reset();
+        Assert.False(conv.IsHot);
+        Assert.Equal(0, conv.Last.Value);
+
+        // Should behave as new
+        var res = conv.Update(new TValue(DateTime.UtcNow, 1));
+        Assert.Equal(1.0, res.Value);
+    }
+
+    [Fact]
+    public void LeadingNaN_RemainsNaN()
+    {
+        double[] kernel = [1.0];
+        var conv = new Conv(kernel);
+        var res = conv.Update(new TValue(DateTime.UtcNow, double.NaN));
+        Assert.True(double.IsNaN(res.Value));
+    }
+
+    [Fact]
+    public void IterativeCorrections_RestoreToOriginalState()
+    {
+        double[] kernel = [0.5, 1.0];
+        var conv = new Conv(kernel);
+        var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1);
+
+        // Feed 10 new values
+        TValue tenthInput = default;
+        for (int i = 0; i < 10; i++)
+        {
+            var bar = gbm.Next(isNew: true);
+            tenthInput = new TValue(bar.Time, bar.Close);
+            conv.Update(tenthInput, isNew: true);
+        }
+
+        // Remember state after 10 values
+        double valueAfterTen = conv.Last.Value;
+
+        // Generate 9 corrections with isNew=false (different values)
+        for (int i = 0; i < 9; i++)
+        {
+            var bar = gbm.Next(isNew: false);
+            conv.Update(new TValue(bar.Time, bar.Close), isNew: false);
+        }
+
+        // Feed the remembered 10th input again with isNew=false
+        TValue finalValue = conv.Update(tenthInput, isNew: false);
+
+        // Should match the original state after 10 values
+        Assert.Equal(valueAfterTen, finalValue.Value, 1e-9);
+    }
+
+    [Fact]
+    public void AllModes_ProduceSameResult()
+    {
+        // Arrange
+        double[] kernel = [0.1, 0.2, 0.3, 0.4];
+        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 = Conv.Batch(series, kernel);
+        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];
+        Conv.Batch(spanInput, spanOutput, kernel);
+        double spanResult = spanOutput[^1];
+
+        // 3. Streaming Mode
+        var streamingInd = new Conv(kernel);
+        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 Conv(pubSource, kernel);
+        for (int i = 0; i < series.Count; i++)
+        {
+            pubSource.Add(series[i]);
+        }
+        double eventingResult = eventingInd.Last.Value;
+
+        // Assert
+        Assert.Equal(expected, spanResult, 1e-9);
+        Assert.Equal(expected, streamingResult, 1e-9);
+        Assert.Equal(expected, eventingResult, 1e-9);
+    }
+
+    [Fact]
+    public void SpanCalc_ValidatesInput()
+    {
+        double[] source = [1, 2, 3, 4, 5];
+        double[] output = new double[5];
+        double[] wrongSizeOutput = new double[3];
+        double[] kernel = [0.5, 0.5];
+
+        Assert.Throws<ArgumentException>(() => Conv.Batch(source.AsSpan(), output.AsSpan(), Array.Empty<double>()));
+        Assert.Throws<ArgumentException>(() => Conv.Batch(source.AsSpan(), wrongSizeOutput.AsSpan(), kernel));
+    }
+
+    [Fact]
+    public void SpanCalc_HandlesNaN()
+    {
+        double[] source = [100, 110, double.NaN, 120, 130];
+        double[] output = new double[5];
+        double[] kernel = [0.5, 0.5];
+
+        Conv.Batch(source.AsSpan(), output.AsSpan(), kernel);
+
+        foreach (var val in output)
+        {
+            Assert.True(double.IsFinite(val));
+        }
+    }
+}