mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-07-28 09:47:43 +00:00
995 lines
28 KiB
C#
995 lines
28 KiB
C#
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namespace QuanTAlib.Tests;
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public class SimdExtensionsTests
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{
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// ContainsNonFinite tests
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[Fact]
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public void ContainsNonFinite_EmptySpan_ReturnsFalse()
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{
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var span = ReadOnlySpan<double>.Empty;
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Assert.False(span.ContainsNonFinite());
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}
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[Fact]
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public void ContainsNonFinite_AllFinite_ReturnsFalse()
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{
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double[] data = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.False(span.ContainsNonFinite());
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}
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[Fact]
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public void ContainsNonFinite_ContainsNaN_ReturnsTrue()
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{
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double[] data = [1.0, 2.0, double.NaN, 4.0, 5.0, 6.0, 7.0, 8.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.True(span.ContainsNonFinite());
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}
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[Fact]
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public void ContainsNonFinite_ContainsPositiveInfinity_ReturnsTrue()
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{
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double[] data = [1.0, 2.0, 3.0, double.PositiveInfinity, 5.0, 6.0, 7.0, 8.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.True(span.ContainsNonFinite());
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}
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[Fact]
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public void ContainsNonFinite_ContainsNegativeInfinity_ReturnsTrue()
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{
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double[] data = [1.0, 2.0, 3.0, 4.0, double.NegativeInfinity, 6.0, 7.0, 8.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.True(span.ContainsNonFinite());
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}
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[Fact]
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public void ContainsNonFinite_NonFiniteInRemainder_ReturnsTrue()
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{
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double[] data = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, double.NaN];
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var span = new ReadOnlySpan<double>(data);
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Assert.True(span.ContainsNonFinite());
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}
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[Fact]
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public void ContainsNonFinite_SingleNaN_ReturnsTrue()
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{
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double[] data = [double.NaN];
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var span = new ReadOnlySpan<double>(data);
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Assert.True(span.ContainsNonFinite());
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}
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[Fact]
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public void ContainsNonFinite_TwoElements_AllFinite_ReturnsFalse()
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{
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double[] data = [1.0, 2.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.False(span.ContainsNonFinite());
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}
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[Fact]
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public void ContainsNonFinite_TwoElements_OneNaN_ReturnsTrue()
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{
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double[] data = [1.0, double.NaN];
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var span = new ReadOnlySpan<double>(data);
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Assert.True(span.ContainsNonFinite());
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}
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// SumSIMD tests
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[Fact]
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public void SumSIMD_EmptySpan_ReturnsZero()
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{
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var span = ReadOnlySpan<double>.Empty;
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Assert.Equal(0.0, span.SumSIMD());
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}
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[Fact]
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public void SumSIMD_SingleElement_ReturnsElement()
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{
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double[] data = [42.5];
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var span = new ReadOnlySpan<double>(data);
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Assert.Equal(42.5, span.SumSIMD());
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}
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[Fact]
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public void SumSIMD_TwoElements_ReturnsSum()
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{
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double[] data = [1.5, 2.5];
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var span = new ReadOnlySpan<double>(data);
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Assert.Equal(4.0, span.SumSIMD());
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}
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[Fact]
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public void SumSIMD_MultipleElements_ReturnsCorrectSum()
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{
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double[] data = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.Equal(55.0, span.SumSIMD(), precision: 10);
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}
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[Fact]
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public void SumSIMD_LargeArray_ReturnsCorrectSum()
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{
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double[] data = new double[1000];
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for (int i = 0; i < data.Length; i++)
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data[i] = i + 1.0;
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var span = new ReadOnlySpan<double>(data);
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const double expected = 1000.0 * 1001.0 / 2.0;
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Assert.Equal(expected, span.SumSIMD(), precision: 8);
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}
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[Fact]
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public void SumSIMD_ContainsNaN_ReturnsNaN()
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{
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double[] data = [1.0, 2.0, double.NaN, 4.0, 5.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.True(double.IsNaN(span.SumSIMD()));
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}
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[Fact]
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public void SumSIMD_ContainsInfinity_ReturnsNaN()
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{
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double[] data = [1.0, 2.0, double.PositiveInfinity, 4.0, 5.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.True(double.IsNaN(span.SumSIMD()));
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}
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[Fact]
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public void SumSIMD_NegativeValues_ReturnsCorrectSum()
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{
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double[] data = [-1.0, -2.0, -3.0, -4.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.Equal(-10.0, span.SumSIMD());
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}
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// MinSIMD tests
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[Fact]
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public void MinSIMD_EmptySpan_ReturnsNaN()
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{
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var span = ReadOnlySpan<double>.Empty;
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Assert.True(double.IsNaN(span.MinSIMD()));
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}
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[Fact]
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public void MinSIMD_SingleElement_ReturnsElement()
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{
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double[] data = [42.5];
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var span = new ReadOnlySpan<double>(data);
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Assert.Equal(42.5, span.MinSIMD());
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}
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[Fact]
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public void MinSIMD_TwoElements_ReturnsMinimum()
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{
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double[] data = [5.0, 2.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.Equal(2.0, span.MinSIMD());
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}
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[Fact]
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public void MinSIMD_MultipleElements_ReturnsMinimum()
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{
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double[] data = [5.0, 2.0, 8.0, 1.0, 9.0, 3.0, 7.0, 4.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.Equal(1.0, span.MinSIMD());
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}
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[Fact]
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public void MinSIMD_ContainsNaN_ReturnsNaN()
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{
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double[] data = [5.0, 2.0, double.NaN, 1.0, 9.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.True(double.IsNaN(span.MinSIMD()));
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}
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[Fact]
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public void MinSIMD_MinInRemainder_ReturnsCorrectMin()
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{
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double[] data = [5.0, 2.0, 8.0, 6.0, 9.0, 3.0, 7.0, 4.0, 0.5];
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var span = new ReadOnlySpan<double>(data);
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Assert.Equal(0.5, span.MinSIMD());
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}
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[Fact]
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public void MinSIMD_NegativeValues_ReturnsMinimum()
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{
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double[] data = [-5.0, -2.0, -8.0, -1.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.Equal(-8.0, span.MinSIMD());
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}
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// MaxSIMD tests
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[Fact]
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public void MaxSIMD_EmptySpan_ReturnsNaN()
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{
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var span = ReadOnlySpan<double>.Empty;
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Assert.True(double.IsNaN(span.MaxSIMD()));
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}
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[Fact]
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public void MaxSIMD_SingleElement_ReturnsElement()
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{
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double[] data = [42.5];
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var span = new ReadOnlySpan<double>(data);
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Assert.Equal(42.5, span.MaxSIMD());
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}
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[Fact]
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public void MaxSIMD_TwoElements_ReturnsMaximum()
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{
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double[] data = [5.0, 9.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.Equal(9.0, span.MaxSIMD());
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}
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[Fact]
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public void MaxSIMD_MultipleElements_ReturnsMaximum()
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{
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double[] data = [5.0, 2.0, 8.0, 1.0, 9.0, 3.0, 7.0, 4.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.Equal(9.0, span.MaxSIMD());
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}
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[Fact]
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public void MaxSIMD_ContainsNaN_ReturnsNaN()
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{
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double[] data = [5.0, 2.0, double.NaN, 1.0, 9.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.True(double.IsNaN(span.MaxSIMD()));
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}
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[Fact]
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public void MaxSIMD_MaxInRemainder_ReturnsCorrectMax()
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{
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double[] data = [5.0, 2.0, 8.0, 6.0, 4.0, 3.0, 7.0, 1.0, 99.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.Equal(99.0, span.MaxSIMD());
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}
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[Fact]
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public void MaxSIMD_NegativeValues_ReturnsMaximum()
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{
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double[] data = [-5.0, -2.0, -8.0, -1.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.Equal(-1.0, span.MaxSIMD());
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}
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// AverageSIMD tests
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[Fact]
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public void AverageSIMD_EmptySpan_ReturnsNaN()
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{
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var span = ReadOnlySpan<double>.Empty;
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Assert.True(double.IsNaN(span.AverageSIMD()));
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}
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[Fact]
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public void AverageSIMD_TwoElements_ReturnsAverage()
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{
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double[] data = [2.0, 4.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.Equal(3.0, span.AverageSIMD());
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}
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[Fact]
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public void AverageSIMD_MultipleElements_ReturnsCorrectAverage()
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{
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double[] data = [1.0, 2.0, 3.0, 4.0, 5.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.Equal(3.0, span.AverageSIMD(), precision: 10);
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}
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[Fact]
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public void AverageSIMD_ContainsNaN_ReturnsNaN()
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{
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double[] data = [1.0, double.NaN, 3.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.True(double.IsNaN(span.AverageSIMD()));
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}
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// VarianceSIMD tests
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[Fact]
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public void VarianceSIMD_LessThanTwoElements_ReturnsZero()
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{
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double[] data = [42.5];
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var span = new ReadOnlySpan<double>(data);
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Assert.Equal(0.0, span.VarianceSIMD());
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}
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[Fact]
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public void VarianceSIMD_EmptySpan_ReturnsZero()
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{
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var span = ReadOnlySpan<double>.Empty;
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Assert.Equal(0.0, span.VarianceSIMD());
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}
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[Fact]
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public void VarianceSIMD_TwoElements_ReturnsCorrect()
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{
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double[] data = [1.0, 3.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.Equal(2.0, span.VarianceSIMD(), precision: 10);
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}
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[Fact]
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public void VarianceSIMD_ThreeElements_ReturnsCorrect()
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{
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double[] data = [1.0, 2.0, 3.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.Equal(1.0, span.VarianceSIMD(), precision: 10);
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}
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[Fact]
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public void VarianceSIMD_MultipleElements_ReturnsCorrectVariance()
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{
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double[] data = [2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0];
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var span = new ReadOnlySpan<double>(data);
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double variance = span.VarianceSIMD();
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Assert.True(Math.Abs(variance - 4.571428) < 0.0001);
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}
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[Fact]
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public void VarianceSIMD_WithProvidedMean_UsesProvidedMean()
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{
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double[] data = [2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0];
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var span = new ReadOnlySpan<double>(data);
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double mean = 5.0;
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double variance = span.VarianceSIMD(mean);
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Assert.True(variance > 0);
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}
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[Fact]
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public void VarianceSIMD_ContainsNaN_ReturnsNaN()
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{
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double[] data = [2.0, double.NaN, 4.0, 5.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.True(double.IsNaN(span.VarianceSIMD()));
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}
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[Fact]
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public void VarianceSIMD_WithNaNMean_ReturnsNaN()
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{
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double[] data = [2.0, 4.0, 4.0, 5.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.True(double.IsNaN(span.VarianceSIMD(double.NaN)));
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}
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[Fact]
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public void VarianceSIMD_WithInfinityMean_ReturnsNaN()
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{
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double[] data = [2.0, 4.0, 4.0, 5.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.True(double.IsNaN(span.VarianceSIMD(double.PositiveInfinity)));
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}
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// StdDevSIMD tests
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[Fact]
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public void StdDevSIMD_TwoElements_ReturnsCorrect()
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{
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double[] data = [1.0, 3.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.True(Math.Abs(span.StdDevSIMD() - 1.414) < 0.01);
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}
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[Fact]
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public void StdDevSIMD_MultipleElements_ReturnsCorrectStdDev()
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{
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double[] data = [2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0];
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var span = new ReadOnlySpan<double>(data);
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double stdDev = span.StdDevSIMD();
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Assert.True(Math.Abs(stdDev - 2.138) < 0.01);
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}
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[Fact]
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public void StdDevSIMD_WithProvidedMean_Works()
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{
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double[] data = [2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0];
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var span = new ReadOnlySpan<double>(data);
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double stdDev = span.StdDevSIMD(5.0);
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Assert.True(stdDev > 0);
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}
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[Fact]
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public void StdDevSIMD_ContainsNaN_ReturnsNaN()
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{
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double[] data = [2.0, double.NaN, 4.0, 5.0];
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var span = new ReadOnlySpan<double>(data);
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Assert.True(double.IsNaN(span.StdDevSIMD()));
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}
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// MinMaxSIMD tests
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[Fact]
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public void MinMaxSIMD_EmptySpan_ReturnsBothNaN()
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{
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var span = ReadOnlySpan<double>.Empty;
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var (min, max) = span.MinMaxSIMD();
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Assert.True(double.IsNaN(min));
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Assert.True(double.IsNaN(max));
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}
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[Fact]
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public void MinMaxSIMD_SingleElement_ReturnsSameValue()
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{
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double[] data = [42.5];
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var span = new ReadOnlySpan<double>(data);
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var (min, max) = span.MinMaxSIMD();
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Assert.Equal(42.5, min);
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Assert.Equal(42.5, max);
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}
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[Fact]
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public void MinMaxSIMD_TwoElements_ReturnsCorrect()
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{
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double[] data = [5.0, 2.0];
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var span = new ReadOnlySpan<double>(data);
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var (min, max) = span.MinMaxSIMD();
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Assert.Equal(2.0, min);
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Assert.Equal(5.0, max);
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}
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[Fact]
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public void MinMaxSIMD_MultipleElements_ReturnsCorrectMinMax()
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{
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double[] data = [5.0, 2.0, 8.0, 1.0, 9.0, 3.0, 7.0, 4.0];
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var span = new ReadOnlySpan<double>(data);
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var (min, max) = span.MinMaxSIMD();
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Assert.Equal(1.0, min);
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Assert.Equal(9.0, max);
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}
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[Fact]
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public void MinMaxSIMD_ContainsNaN_ReturnsBothNaN()
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{
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double[] data = [5.0, 2.0, double.NaN, 1.0, 9.0];
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var span = new ReadOnlySpan<double>(data);
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var (min, max) = span.MinMaxSIMD();
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Assert.True(double.IsNaN(min));
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Assert.True(double.IsNaN(max));
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}
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[Fact]
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public void MinMaxSIMD_MinMaxInRemainder_ReturnsCorrect()
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{
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double[] data = [5.0, 2.0, 8.0, 6.0, 4.0, 3.0, 7.0, 5.0, 0.1, 99.0];
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var span = new ReadOnlySpan<double>(data);
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var (min, max) = span.MinMaxSIMD();
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Assert.Equal(0.1, min);
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Assert.Equal(99.0, max);
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}
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[Fact]
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public void MinMaxSIMD_NegativeValues_ReturnsCorrect()
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{
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double[] data = [-5.0, -2.0, -8.0, -1.0];
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var span = new ReadOnlySpan<double>(data);
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var (min, max) = span.MinMaxSIMD();
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Assert.Equal(-8.0, min);
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Assert.Equal(-1.0, max);
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}
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// Add/Subtract tests
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[Fact]
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public void Add_SameLength_CorrectResult()
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{
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double[] left = [1.0, 2.0, 3.0, 4.0, 5.0];
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double[] right = [10.0, 20.0, 30.0, 40.0, 50.0];
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double[] result = new double[5];
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SimdExtensions.Add(left, right, result);
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Assert.Equal(11.0, result[0]);
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Assert.Equal(22.0, result[1]);
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Assert.Equal(33.0, result[2]);
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Assert.Equal(44.0, result[3]);
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Assert.Equal(55.0, result[4]);
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}
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[Fact]
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public void Add_DifferentLengths_ThrowsArgumentException()
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{
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double[] left = [1.0, 2.0];
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double[] right = [1.0];
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double[] result = new double[2];
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Assert.Throws<ArgumentException>(() => SimdExtensions.Add(left, right, result));
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}
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[Fact]
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public void Subtract_SameLength_CorrectResult()
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{
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double[] left = [10.0, 20.0, 30.0, 40.0, 50.0];
|
|
double[] right = [1.0, 2.0, 3.0, 4.0, 5.0];
|
|
double[] result = new double[5];
|
|
|
|
SimdExtensions.Subtract(left, right, result);
|
|
|
|
Assert.Equal(9.0, result[0]);
|
|
Assert.Equal(18.0, result[1]);
|
|
Assert.Equal(27.0, result[2]);
|
|
Assert.Equal(36.0, result[3]);
|
|
Assert.Equal(45.0, result[4]);
|
|
}
|
|
|
|
[Fact]
|
|
public void Subtract_DifferentLengths_ThrowsArgumentException()
|
|
{
|
|
double[] left = [1.0, 2.0];
|
|
double[] right = [1.0];
|
|
double[] result = new double[2];
|
|
|
|
Assert.Throws<ArgumentException>(() => SimdExtensions.Subtract(left, right, result));
|
|
}
|
|
|
|
// DotProduct tests
|
|
[Fact]
|
|
public void DotProduct_SameLength_CorrectResult()
|
|
{
|
|
double[] a = [1.0, 2.0, 3.0];
|
|
double[] b = [4.0, 5.0, 6.0];
|
|
// 1*4 + 2*5 + 3*6 = 4 + 10 + 18 = 32
|
|
Assert.Equal(32.0, a.DotProduct(b));
|
|
}
|
|
|
|
[Fact]
|
|
public void DotProduct_DifferentLengths_ThrowsArgumentException()
|
|
{
|
|
double[] a = [1.0, 2.0];
|
|
double[] b = [1.0];
|
|
Assert.Throws<ArgumentException>(() => a.DotProduct(b));
|
|
}
|
|
|
|
[Fact]
|
|
public void DotProduct_EmptySpans_ReturnsZero()
|
|
{
|
|
double[] a = [];
|
|
double[] b = [];
|
|
Assert.Equal(0.0, a.DotProduct(b));
|
|
}
|
|
|
|
// Integration tests
|
|
[Fact]
|
|
public void SIMD_WorksWithTSeriesValues()
|
|
{
|
|
var series = new TSeries(100);
|
|
|
|
for (int i = 0; i < 100; i++)
|
|
{
|
|
series.Add(DateTime.UtcNow.Ticks + i, i + 1.0);
|
|
}
|
|
|
|
var values = series.Values;
|
|
|
|
double sum = values.SumSIMD();
|
|
double avg = values.AverageSIMD();
|
|
double min = values.MinSIMD();
|
|
double max = values.MaxSIMD();
|
|
var (minAlt, maxAlt) = values.MinMaxSIMD();
|
|
|
|
Assert.Equal(5050.0, sum, precision: 8);
|
|
Assert.Equal(50.5, avg, precision: 8);
|
|
Assert.Equal(1.0, min);
|
|
Assert.Equal(100.0, max);
|
|
Assert.Equal(min, minAlt);
|
|
Assert.Equal(max, maxAlt);
|
|
}
|
|
|
|
[Fact]
|
|
public void SIMD_WorksWithTBarSeriesClose()
|
|
{
|
|
var gbm = new GBM(startPrice: 100.0);
|
|
long startTime = DateTime.UtcNow.Ticks;
|
|
var interval = TimeSpan.FromMinutes(1);
|
|
var bars = gbm.Fetch(1000, startTime, interval);
|
|
|
|
var closeValues = bars.Close.Values;
|
|
|
|
double sum = closeValues.SumSIMD();
|
|
double avg = closeValues.AverageSIMD();
|
|
double min = closeValues.MinSIMD();
|
|
double max = closeValues.MaxSIMD();
|
|
|
|
Assert.True(sum > 0);
|
|
Assert.True(avg > 0);
|
|
Assert.True(min > 0);
|
|
Assert.True(max > min);
|
|
}
|
|
|
|
[Fact]
|
|
public void SIMD_PerformanceTest_LargeDataset()
|
|
{
|
|
var gbm = new GBM(startPrice: 100.0);
|
|
long startTime = DateTime.UtcNow.Ticks;
|
|
var interval = TimeSpan.FromMinutes(1);
|
|
var bars = gbm.Fetch(10000, startTime, interval);
|
|
var closeValues = bars.Close.Values;
|
|
|
|
_ = closeValues.SumSIMD();
|
|
|
|
var sw = System.Diagnostics.Stopwatch.StartNew();
|
|
|
|
double sum = closeValues.SumSIMD();
|
|
double avg = closeValues.AverageSIMD();
|
|
double min = closeValues.MinSIMD();
|
|
double max = closeValues.MaxSIMD();
|
|
var (minAlt, maxAlt) = closeValues.MinMaxSIMD();
|
|
double variance = closeValues.VarianceSIMD();
|
|
double stdDev = closeValues.StdDevSIMD();
|
|
|
|
sw.Stop();
|
|
|
|
Assert.True(sum > 0);
|
|
Assert.True(avg > 0);
|
|
Assert.True(min > 0);
|
|
Assert.True(max > min);
|
|
Assert.Equal(min, minAlt);
|
|
Assert.Equal(max, maxAlt);
|
|
Assert.True(variance > 0);
|
|
Assert.True(stdDev > 0);
|
|
|
|
Assert.True(sw.ElapsedMilliseconds < 100,
|
|
$"SIMD operations took {sw.ElapsedMilliseconds}ms, expected < 100ms");
|
|
}
|
|
|
|
[Fact]
|
|
public void SIMD_ScalarFallback_SmallArray()
|
|
{
|
|
double[] data = [1.0, 2.0, 3.0];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
|
|
Assert.Equal(6.0, span.SumSIMD());
|
|
Assert.Equal(1.0, span.MinSIMD());
|
|
Assert.Equal(3.0, span.MaxSIMD());
|
|
Assert.Equal(2.0, span.AverageSIMD());
|
|
|
|
var (min, max) = span.MinMaxSIMD();
|
|
Assert.Equal(1.0, min);
|
|
Assert.Equal(3.0, max);
|
|
}
|
|
}
|
|
|
|
// Tests for internal scalar implementations
|
|
public class SimdScalarFallbackTests
|
|
{
|
|
[Fact]
|
|
public void ContainsNonFiniteScalar_AllFinite_ReturnsFalse()
|
|
{
|
|
double[] data = [1.0, 2.0, 3.0, 4.0];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
Assert.False(SimdExtensions.ContainsNonFiniteScalar(span));
|
|
}
|
|
|
|
[Fact]
|
|
public void ContainsNonFiniteScalar_ContainsNaN_ReturnsTrue()
|
|
{
|
|
double[] data = [1.0, double.NaN, 3.0];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
Assert.True(SimdExtensions.ContainsNonFiniteScalar(span));
|
|
}
|
|
|
|
[Fact]
|
|
public void ContainsNonFiniteScalar_ContainsInfinity_ReturnsTrue()
|
|
{
|
|
double[] data = [1.0, double.PositiveInfinity, 3.0];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
Assert.True(SimdExtensions.ContainsNonFiniteScalar(span));
|
|
}
|
|
|
|
[Fact]
|
|
public void ContainsNonFiniteScalar_Empty_ReturnsFalse()
|
|
{
|
|
var span = ReadOnlySpan<double>.Empty;
|
|
Assert.False(SimdExtensions.ContainsNonFiniteScalar(span));
|
|
}
|
|
|
|
[Fact]
|
|
public void SumScalar_MultipleElements_ReturnsCorrectSum()
|
|
{
|
|
double[] data = [1.0, 2.0, 3.0, 4.0, 5.0];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
Assert.Equal(15.0, SimdExtensions.SumScalar(span));
|
|
}
|
|
|
|
[Fact]
|
|
public void SumScalar_NegativeValues_ReturnsCorrectSum()
|
|
{
|
|
double[] data = [-1.0, -2.0, 3.0];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
Assert.Equal(0.0, SimdExtensions.SumScalar(span));
|
|
}
|
|
|
|
[Fact]
|
|
public void SumScalar_Empty_ReturnsZero()
|
|
{
|
|
var span = ReadOnlySpan<double>.Empty;
|
|
Assert.Equal(0.0, SimdExtensions.SumScalar(span));
|
|
}
|
|
|
|
[Fact]
|
|
public void MinScalar_MultipleElements_ReturnsMinimum()
|
|
{
|
|
double[] data = [5.0, 2.0, 8.0, 1.0, 9.0];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
Assert.Equal(1.0, SimdExtensions.MinScalar(span));
|
|
}
|
|
|
|
[Fact]
|
|
public void MinScalar_NegativeValues_ReturnsMinimum()
|
|
{
|
|
double[] data = [-5.0, -2.0, -8.0, -1.0];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
Assert.Equal(-8.0, SimdExtensions.MinScalar(span));
|
|
}
|
|
|
|
[Fact]
|
|
public void MinScalar_SingleElement_ReturnsElement()
|
|
{
|
|
double[] data = [42.5];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
Assert.Equal(42.5, SimdExtensions.MinScalar(span));
|
|
}
|
|
|
|
[Fact]
|
|
public void MaxScalar_MultipleElements_ReturnsMaximum()
|
|
{
|
|
double[] data = [5.0, 2.0, 8.0, 1.0, 9.0];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
Assert.Equal(9.0, SimdExtensions.MaxScalar(span));
|
|
}
|
|
|
|
[Fact]
|
|
public void MaxScalar_NegativeValues_ReturnsMaximum()
|
|
{
|
|
double[] data = [-5.0, -2.0, -8.0, -1.0];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
Assert.Equal(-1.0, SimdExtensions.MaxScalar(span));
|
|
}
|
|
|
|
[Fact]
|
|
public void MaxScalar_SingleElement_ReturnsElement()
|
|
{
|
|
double[] data = [42.5];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
Assert.Equal(42.5, SimdExtensions.MaxScalar(span));
|
|
}
|
|
|
|
[Fact]
|
|
public void VarianceScalar_MultipleElements_ReturnsCorrectVariance()
|
|
{
|
|
double[] data = [2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
double mean = 5.0;
|
|
double variance = SimdExtensions.VarianceScalar(span, mean);
|
|
Assert.True(Math.Abs(variance - 4.571428) < 0.0001);
|
|
}
|
|
|
|
[Fact]
|
|
public void VarianceScalar_TwoElements_ReturnsCorrectVariance()
|
|
{
|
|
double[] data = [1.0, 3.0];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
double mean = 2.0;
|
|
Assert.Equal(2.0, SimdExtensions.VarianceScalar(span, mean), precision: 10);
|
|
}
|
|
|
|
[Fact]
|
|
public void MinMaxScalar_MultipleElements_ReturnsCorrectMinMax()
|
|
{
|
|
double[] data = [5.0, 2.0, 8.0, 1.0, 9.0, 3.0, 7.0, 4.0];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
var (min, max) = SimdExtensions.MinMaxScalar(span);
|
|
Assert.Equal(1.0, min);
|
|
Assert.Equal(9.0, max);
|
|
}
|
|
|
|
[Fact]
|
|
public void MinMaxScalar_NegativeValues_ReturnsCorrectMinMax()
|
|
{
|
|
double[] data = [-5.0, -2.0, -8.0, -1.0];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
var (min, max) = SimdExtensions.MinMaxScalar(span);
|
|
Assert.Equal(-8.0, min);
|
|
Assert.Equal(-1.0, max);
|
|
}
|
|
|
|
[Fact]
|
|
public void MinMaxScalar_SingleElement_ReturnsSameValue()
|
|
{
|
|
double[] data = [42.5];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
var (min, max) = SimdExtensions.MinMaxScalar(span);
|
|
Assert.Equal(42.5, min);
|
|
Assert.Equal(42.5, max);
|
|
}
|
|
|
|
// Additional edge case tests
|
|
[Fact]
|
|
public void DotProduct_ContainsNaN_PropagatesNaN()
|
|
{
|
|
double[] a = [1.0, double.NaN, 3.0];
|
|
double[] b = [4.0, 5.0, 6.0];
|
|
double result = a.DotProduct(b);
|
|
Assert.True(double.IsNaN(result));
|
|
}
|
|
|
|
[Fact]
|
|
public void DotProduct_ContainsInfinity_PropagatesCorrectly()
|
|
{
|
|
double[] a = [1.0, double.PositiveInfinity, 3.0];
|
|
double[] b = [4.0, 5.0, 6.0];
|
|
double result = a.DotProduct(b);
|
|
Assert.True(double.IsPositiveInfinity(result));
|
|
}
|
|
|
|
[Fact]
|
|
public void Add_ContainsNaN_PropagatesNaN()
|
|
{
|
|
double[] left = [1.0, double.NaN, 3.0];
|
|
double[] right = [4.0, 5.0, 6.0];
|
|
double[] result = new double[3];
|
|
|
|
SimdExtensions.Add(left, right, result);
|
|
|
|
Assert.Equal(5.0, result[0]);
|
|
Assert.True(double.IsNaN(result[1]));
|
|
Assert.Equal(9.0, result[2]);
|
|
}
|
|
|
|
[Fact]
|
|
public void Subtract_ContainsNaN_PropagatesNaN()
|
|
{
|
|
double[] left = [10.0, double.NaN, 30.0];
|
|
double[] right = [1.0, 2.0, 3.0];
|
|
double[] result = new double[3];
|
|
|
|
SimdExtensions.Subtract(left, right, result);
|
|
|
|
Assert.Equal(9.0, result[0]);
|
|
Assert.True(double.IsNaN(result[1]));
|
|
Assert.Equal(27.0, result[2]);
|
|
}
|
|
|
|
[Fact]
|
|
public void ContainsNonFinite_NegativeInfinityAtStart_ReturnsTrue()
|
|
{
|
|
double[] data = [double.NegativeInfinity, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
Assert.True(span.ContainsNonFinite());
|
|
}
|
|
|
|
[Fact]
|
|
public void ContainsNonFinite_NegativeInfinityAtEnd_ReturnsTrue()
|
|
{
|
|
double[] data = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, double.NegativeInfinity];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
Assert.True(span.ContainsNonFinite());
|
|
}
|
|
|
|
[Fact]
|
|
public void VarianceSIMD_SingleElement_ReturnsZero()
|
|
{
|
|
double[] data = [42.5];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
Assert.Equal(0.0, span.VarianceSIMD());
|
|
}
|
|
|
|
[Fact]
|
|
public void StdDevSIMD_SingleElement_ReturnsZero()
|
|
{
|
|
double[] data = [42.5];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
Assert.Equal(0.0, span.StdDevSIMD());
|
|
}
|
|
|
|
[Fact]
|
|
public void StdDevSIMD_EmptySpan_ReturnsZero()
|
|
{
|
|
var span = ReadOnlySpan<double>.Empty;
|
|
Assert.Equal(0.0, span.StdDevSIMD());
|
|
}
|
|
|
|
[Fact]
|
|
public void SumSIMD_SingleElement_ReturnsElement()
|
|
{
|
|
double[] data = [42.5];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
Assert.Equal(42.5, span.SumSIMD());
|
|
}
|
|
|
|
[Fact]
|
|
public void AverageSIMD_SingleElement_ReturnsElement()
|
|
{
|
|
double[] data = [42.5];
|
|
var span = new ReadOnlySpan<double>(data);
|
|
Assert.Equal(42.5, span.AverageSIMD());
|
|
}
|
|
|
|
[Fact]
|
|
public void DotProduct_SingleElement_ReturnsProduct()
|
|
{
|
|
double[] a = [3.0];
|
|
double[] b = [4.0];
|
|
Assert.Equal(12.0, a.DotProduct(b));
|
|
}
|
|
|
|
[Fact]
|
|
public void DotProduct_TwoElements_ReturnsCorrect()
|
|
{
|
|
double[] a = [2.0, 3.0];
|
|
double[] b = [4.0, 5.0];
|
|
// 2*4 + 3*5 = 8 + 15 = 23
|
|
Assert.Equal(23.0, a.DotProduct(b));
|
|
}
|
|
|
|
[Fact]
|
|
public void Add_SingleElement_Works()
|
|
{
|
|
double[] left = [5.0];
|
|
double[] right = [3.0];
|
|
double[] result = new double[1];
|
|
|
|
SimdExtensions.Add(left, right, result);
|
|
|
|
Assert.Equal(8.0, result[0]);
|
|
}
|
|
|
|
[Fact]
|
|
public void Subtract_SingleElement_Works()
|
|
{
|
|
double[] left = [5.0];
|
|
double[] right = [3.0];
|
|
double[] result = new double[1];
|
|
|
|
SimdExtensions.Subtract(left, right, result);
|
|
|
|
Assert.Equal(2.0, result[0]);
|
|
}
|
|
|
|
[Fact]
|
|
public void Add_EmptyArrays_Works()
|
|
{
|
|
double[] left = [];
|
|
double[] right = [];
|
|
double[] result = [];
|
|
|
|
SimdExtensions.Add(left, right, result); // Should not throw
|
|
|
|
Assert.Empty(result);
|
|
}
|
|
|
|
[Fact]
|
|
public void Subtract_EmptyArrays_Works()
|
|
{
|
|
double[] left = [];
|
|
double[] right = [];
|
|
double[] result = [];
|
|
|
|
SimdExtensions.Subtract(left, right, result); // Should not throw
|
|
|
|
Assert.Empty(result);
|
|
}
|
|
|
|
[Fact]
|
|
public void Add_ResultTooSmall_ThrowsArgumentException()
|
|
{
|
|
double[] left = [1.0, 2.0, 3.0];
|
|
double[] right = [4.0, 5.0, 6.0];
|
|
double[] result = new double[2]; // Too small
|
|
|
|
Assert.Throws<ArgumentException>(() => SimdExtensions.Add(left, right, result));
|
|
}
|
|
|
|
[Fact]
|
|
public void Subtract_ResultTooSmall_ThrowsArgumentException()
|
|
{
|
|
double[] left = [1.0, 2.0, 3.0];
|
|
double[] right = [4.0, 5.0, 6.0];
|
|
double[] result = new double[2]; // Too small
|
|
|
|
Assert.Throws<ArgumentException>(() => SimdExtensions.Subtract(left, right, result));
|
|
}
|
|
} |