Files
QuanTAlib/lib/core/simd/SimdExtensions.Tests.cs
T
2025-11-26 20:17:01 -08:00

250 lines
7.1 KiB
C#

using System;
using Xunit;
using QuanTAlib;
namespace QuanTAlib.Tests;
public class SimdExtensionsTests
{
[Fact]
public void SumSIMD_EmptySpan_ReturnsZero()
{
var span = ReadOnlySpan<double>.Empty;
Assert.Equal(0.0, span.SumSIMD());
}
[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 SumSIMD_MultipleElements_ReturnsCorrectSum()
{
double[] data = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(55.0, span.SumSIMD(), precision: 10);
}
[Fact]
public void SumSIMD_LargeArray_ReturnsCorrectSum()
{
double[] data = new double[1000];
for (int i = 0; i < data.Length; i++)
data[i] = i + 1.0;
var span = new ReadOnlySpan<double>(data);
double expected = 1000.0 * 1001.0 / 2.0; // Sum of 1..1000
Assert.Equal(expected, span.SumSIMD(), precision: 8);
}
[Fact]
public void MinSIMD_EmptySpan_ReturnsNaN()
{
var span = ReadOnlySpan<double>.Empty;
Assert.True(double.IsNaN(span.MinSIMD()));
}
[Fact]
public void MinSIMD_SingleElement_ReturnsElement()
{
double[] data = [42.5];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(42.5, span.MinSIMD());
}
[Fact]
public void MinSIMD_MultipleElements_ReturnsMinimum()
{
double[] data = [5.0, 2.0, 8.0, 1.0, 9.0, 3.0, 7.0, 4.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(1.0, span.MinSIMD());
}
[Fact]
public void MaxSIMD_EmptySpan_ReturnsNaN()
{
var span = ReadOnlySpan<double>.Empty;
Assert.True(double.IsNaN(span.MaxSIMD()));
}
[Fact]
public void MaxSIMD_SingleElement_ReturnsElement()
{
double[] data = [42.5];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(42.5, span.MaxSIMD());
}
[Fact]
public void MaxSIMD_MultipleElements_ReturnsMaximum()
{
double[] data = [5.0, 2.0, 8.0, 1.0, 9.0, 3.0, 7.0, 4.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(9.0, span.MaxSIMD());
}
[Fact]
public void AverageSIMD_EmptySpan_ReturnsNaN()
{
var span = ReadOnlySpan<double>.Empty;
Assert.True(double.IsNaN(span.AverageSIMD()));
}
[Fact]
public void AverageSIMD_MultipleElements_ReturnsCorrectAverage()
{
double[] data = [1.0, 2.0, 3.0, 4.0, 5.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(3.0, span.AverageSIMD(), precision: 10);
}
[Fact]
public void VarianceSIMD_LessThanTwoElements_ReturnsNaN()
{
double[] data = [42.5];
var span = new ReadOnlySpan<double>(data);
Assert.True(double.IsNaN(span.VarianceSIMD()));
}
[Fact]
public void VarianceSIMD_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);
// Expected variance: 4.571428... (sample variance)
double variance = span.VarianceSIMD();
Assert.True(Math.Abs(variance - 4.571428) < 0.0001);
}
[Fact]
public void StdDevSIMD_MultipleElements_ReturnsCorrectStdDev()
{
double[] data = [2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0];
var span = new ReadOnlySpan<double>(data);
// Expected std dev: sqrt(4.571428) ≈ 2.138
double stdDev = span.StdDevSIMD();
Assert.True(Math.Abs(stdDev - 2.138) < 0.01);
}
[Fact]
public void MinMaxSIMD_EmptySpan_ReturnsBothNaN()
{
var span = ReadOnlySpan<double>.Empty;
var (min, max) = span.MinMaxSIMD();
Assert.True(double.IsNaN(min));
Assert.True(double.IsNaN(max));
}
[Fact]
public void MinMaxSIMD_SingleElement_ReturnsSameValue()
{
double[] data = [42.5];
var span = new ReadOnlySpan<double>(data);
var (min, max) = span.MinMaxSIMD();
Assert.Equal(42.5, min);
Assert.Equal(42.5, max);
}
[Fact]
public void MinMaxSIMD_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) = span.MinMaxSIMD();
Assert.Equal(1.0, min);
Assert.Equal(9.0, max);
}
[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); // Sum of 1..100
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()
{
// Generate large dataset
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;
// Warm up
_ = closeValues.SumSIMD();
// Test SIMD operations
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();
// Verify results are valid
Assert.True(sum > 0);
Assert.True(avg > 0);
Assert.True(min > 0);
Assert.True(max > min);
Assert.True(variance > 0);
Assert.True(stdDev > 0);
// Performance should be sub-millisecond for 10k elements
Assert.True(sw.ElapsedMilliseconds < 10,
$"SIMD operations took {sw.ElapsedMilliseconds}ms, expected < 10ms");
}
}