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https://github.com/mihakralj/QuanTAlib.git
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Add Span API for SMA, EMA, and WMA with zero-allocation performance improvements
- Implemented zero-allocation methods for SMA, EMA, and WMA calculations using ReadOnlySpan and Span. - Added unit tests for Span API to validate input, match TSeries calculations, handle NaN values, and ensure zero allocation. - Enhanced documentation to include usage examples for the new Span API. - Introduced performance benchmarks comparing the new Span API against existing TSeries implementations and other libraries.
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@@ -359,4 +359,111 @@ public class SmaTests
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Assert.Equal(200.0, sma.Update(new TValue(DateTime.UtcNow, 200)).Value, 1e-10);
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Assert.Equal(150.0, sma.Update(new TValue(DateTime.UtcNow, 150)).Value, 1e-10);
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}
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// ============== Span API Tests ==============
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[Fact]
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public void Sma_SpanCalc_ValidatesInput()
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{
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double[] source = [1, 2, 3, 4, 5];
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double[] output = new double[5];
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double[] wrongSizeOutput = new double[3];
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// Period must be > 0
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Assert.Throws<ArgumentException>(() => Sma.Calculate(source.AsSpan(), output.AsSpan(), 0));
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Assert.Throws<ArgumentException>(() => Sma.Calculate(source.AsSpan(), output.AsSpan(), -1));
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// Output must be same length as source
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Assert.Throws<ArgumentException>(() => Sma.Calculate(source.AsSpan(), wrongSizeOutput.AsSpan(), 3));
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}
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[Fact]
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public void Sma_SpanCalc_MatchesTSeriesCalc()
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{
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var series = new TSeries();
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double[] source = new double[100];
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double[] output = new double[100];
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var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: 42);
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for (int i = 0; i < 100; i++)
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{
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var bar = gbm.Next(isNew: true);
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source[i] = bar.Close;
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series.Add(bar.Time, bar.Close);
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}
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// Calculate with TSeries API
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var tseriesResult = Sma.Calculate(series, 10);
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// Calculate with Span API
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Sma.Calculate(source.AsSpan(), output.AsSpan(), 10);
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// Compare results
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for (int i = 0; i < 100; i++)
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{
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Assert.Equal(tseriesResult[i].Value, output[i], 1e-10);
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}
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}
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[Fact]
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public void Sma_SpanCalc_CalculatesCorrectly()
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{
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double[] source = [10, 20, 30, 40, 50];
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double[] output = new double[5];
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Sma.Calculate(source.AsSpan(), output.AsSpan(), 3);
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// SMA(3) warmup: 10, (10+20)/2=15, (10+20+30)/3=20, then sliding: (20+30+40)/3=30, (30+40+50)/3=40
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Assert.Equal(10.0, output[0], 1e-10);
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Assert.Equal(15.0, output[1], 1e-10);
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Assert.Equal(20.0, output[2], 1e-10);
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Assert.Equal(30.0, output[3], 1e-10);
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Assert.Equal(40.0, output[4], 1e-10);
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}
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[Fact]
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public void Sma_SpanCalc_ZeroAllocation()
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{
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double[] source = new double[10000];
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double[] output = new double[10000];
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var rng = new Random(42);
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for (int i = 0; i < source.Length; i++)
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source[i] = rng.NextDouble() * 100;
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// Warm up
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Sma.Calculate(source.AsSpan(), output.AsSpan(), 100);
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// This test verifies the method runs without throwing
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// (allocation is measured by BenchmarkDotNet, not unit tests)
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Assert.True(double.IsFinite(output[^1]));
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}
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[Fact]
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public void Sma_SpanCalc_HandlesNaN()
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{
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double[] source = [100, 110, double.NaN, 120, 130];
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double[] output = new double[5];
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Sma.Calculate(source.AsSpan(), output.AsSpan(), 3);
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// All outputs should be finite
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foreach (var val in output)
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{
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Assert.True(double.IsFinite(val), $"Expected finite value but got {val}");
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}
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}
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[Fact]
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public void Sma_SpanCalc_Period1_ReturnsInput()
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{
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double[] source = [10, 20, 30, 40, 50];
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double[] output = new double[5];
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Sma.Calculate(source.AsSpan(), output.AsSpan(), 1);
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for (int i = 0; i < source.Length; i++)
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{
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Assert.Equal(source[i], output[i], 1e-10);
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}
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}
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}
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