Files
QuanTAlib/lib/averages/sma/Sma.Tests.cs
T
Miha Kralj 1f80cfda74 feat: Implement SIMD-optimized Multi-Period Simple Moving Average (SMA) with RingBuffer
- Added SmaVector class for calculating multiple SMAs in parallel using SIMD.
- Introduced RingBuffer class for efficient circular buffer management with running sum.
- Implemented unit tests for RingBuffer to ensure correctness and performance.
- Enhanced Add method in RingBuffer to support bar correction semantics.
- Added methods for calculating Min and Max using SIMD acceleration.
- Improved performance with pinned memory and direct span access for SIMD compatibility.
2025-11-29 18:28:42 -08:00

363 lines
10 KiB
C#

using System;
using Xunit;
using QuanTAlib;
namespace QuanTAlib.Tests;
public class SmaTests
{
[Fact]
public void Sma_Constructor_ValidatesInput()
{
Assert.Throws<ArgumentException>(() => new Sma(0));
Assert.Throws<ArgumentException>(() => new Sma(-1));
var sma = new Sma(10);
Assert.NotNull(sma);
}
[Fact]
public void Sma_Calc_ReturnsValue()
{
var sma = new Sma(10);
Assert.Equal(0, sma.Value.Value);
TValue result = sma.Update(new TValue(DateTime.UtcNow, 100));
Assert.True(result.Value > 0);
Assert.Equal(result.Value, sma.Value.Value);
}
[Fact]
public void Sma_FirstValue_ReturnsItself()
{
var sma = new Sma(10);
TValue result = sma.Update(new TValue(DateTime.UtcNow, 100));
Assert.Equal(100.0, result.Value, 1e-10);
}
[Fact]
public void Sma_Calc_IsNew_AcceptsParameter()
{
var sma = new Sma(10);
sma.Update(new TValue(DateTime.UtcNow, 100), isNew: true);
double value1 = sma.Value;
sma.Update(new TValue(DateTime.UtcNow, 200), isNew: true);
double value2 = sma.Value;
// Values should change with new bars
Assert.NotEqual(value1, value2);
}
[Fact]
public void Sma_Calc_IsNew_False_UpdatesValue()
{
var sma = new Sma(10);
sma.Update(new TValue(DateTime.UtcNow, 100));
sma.Update(new TValue(DateTime.UtcNow, 110), isNew: true);
double beforeUpdate = sma.Value;
sma.Update(new TValue(DateTime.UtcNow, 120), isNew: false);
double afterUpdate = sma.Value;
// Update should change the value
Assert.NotEqual(beforeUpdate, afterUpdate);
}
[Fact]
public void Sma_Reset_ClearsState()
{
var sma = new Sma(10);
sma.Update(new TValue(DateTime.UtcNow, 100));
sma.Update(new TValue(DateTime.UtcNow, 105));
double valueBefore = sma.Value;
sma.Reset();
Assert.Equal(0, sma.Value.Value);
// After reset, should accept new values
sma.Update(new TValue(DateTime.UtcNow, 50));
Assert.NotEqual(0, sma.Value.Value);
Assert.NotEqual(valueBefore, sma.Value.Value);
}
[Fact]
public void Sma_Properties_Accessible()
{
var sma = new Sma(10);
Assert.Equal(0, sma.Value.Value);
Assert.False(sma.IsHot);
sma.Update(new TValue(DateTime.UtcNow, 100));
Assert.NotEqual(0, sma.Value.Value);
}
[Fact]
public void Sma_IsHot_BecomesTrueWhenBufferFull()
{
var sma = new Sma(5);
Assert.False(sma.IsHot);
for (int i = 1; i <= 4; i++)
{
sma.Update(new TValue(DateTime.UtcNow, i * 10));
Assert.False(sma.IsHot);
}
sma.Update(new TValue(DateTime.UtcNow, 50));
Assert.True(sma.IsHot);
}
[Fact]
public void Sma_CalculatesCorrectAverage()
{
var sma = new Sma(5);
sma.Update(new TValue(DateTime.UtcNow, 10));
sma.Update(new TValue(DateTime.UtcNow, 20));
sma.Update(new TValue(DateTime.UtcNow, 30));
sma.Update(new TValue(DateTime.UtcNow, 40));
sma.Update(new TValue(DateTime.UtcNow, 50));
// SMA(5) of 10,20,30,40,50 = 150/5 = 30
Assert.Equal(30.0, sma.Value.Value, 1e-10);
}
[Fact]
public void Sma_SlidingWindow_Works()
{
var sma = new Sma(3);
sma.Update(new TValue(DateTime.UtcNow, 10));
sma.Update(new TValue(DateTime.UtcNow, 20));
sma.Update(new TValue(DateTime.UtcNow, 30));
// SMA(3) of 10,20,30 = 60/3 = 20
Assert.Equal(20.0, sma.Value.Value, 1e-10);
sma.Update(new TValue(DateTime.UtcNow, 40));
// SMA(3) of 20,30,40 = 90/3 = 30
Assert.Equal(30.0, sma.Value.Value, 1e-10);
sma.Update(new TValue(DateTime.UtcNow, 50));
// SMA(3) of 30,40,50 = 120/3 = 40
Assert.Equal(40.0, sma.Value.Value, 1e-10);
}
[Fact]
public void Sma_IterativeCorrections_RestoreToOriginalState()
{
var sma = new Sma(5);
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);
sma.Update(tenthInput, isNew: true);
}
// Remember SMA state after 10 values
double smaAfterTen = sma.Value;
// Generate 9 corrections with isNew=false (different values)
for (int i = 0; i < 9; i++)
{
var bar = gbm.Next(isNew: false);
sma.Update(new TValue(bar.Time, bar.Close), isNew: false);
}
// Feed the remembered 10th input again with isNew=false
TValue finalSma = sma.Update(tenthInput, isNew: false);
// SMA should match the original state after 10 values
Assert.Equal(smaAfterTen, finalSma.Value, 1e-10);
}
[Fact]
public void Sma_BatchCalc_MatchesIterativeCalc()
{
var smaIterative = new Sma(10);
var smaBatch = new Sma(10);
var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1);
// Generate data
var series = new TSeries();
for (int i = 0; i < 100; i++)
{
var bar = gbm.Next(isNew: true);
series.Add(bar.Time, bar.Close);
}
Assert.True(series.Count > 0);
// Calculate iteratively
var iterativeResults = new TSeries();
foreach (var item in series)
{
iterativeResults.Add(smaIterative.Update(item));
}
// Calculate batch
var batchResults = smaBatch.Update(series);
// Compare
Assert.Equal(iterativeResults.Count, batchResults.Count);
for (int i = 0; i < iterativeResults.Count; i++)
{
Assert.Equal(iterativeResults[i].Value, batchResults[i].Value, 1e-10);
Assert.Equal(iterativeResults[i].Time, batchResults[i].Time);
}
}
[Fact]
public void Sma_Result_ImplicitConversionToDouble()
{
var sma = new Sma(10);
sma.Update(new TValue(DateTime.UtcNow, 100));
// This should compile and work because TValue has implicit conversion to double
double result = sma.Value;
Assert.Equal(100.0, result, 1e-10);
}
[Fact]
public void Sma_NaN_Input_UsesLastValidValue()
{
var sma = new Sma(5);
// Feed some valid values
sma.Update(new TValue(DateTime.UtcNow, 100));
sma.Update(new TValue(DateTime.UtcNow, 110));
// Feed NaN - should use last valid value (110)
var resultAfterNaN = sma.Update(new TValue(DateTime.UtcNow, double.NaN));
// Result should be finite (not NaN)
Assert.True(double.IsFinite(resultAfterNaN.Value));
Assert.NotEqual(0, resultAfterNaN.Value);
}
[Fact]
public void Sma_Infinity_Input_UsesLastValidValue()
{
var sma = new Sma(5);
// Feed some valid values
sma.Update(new TValue(DateTime.UtcNow, 100));
sma.Update(new TValue(DateTime.UtcNow, 110));
// Feed positive infinity - should use last valid value
var resultAfterPosInf = sma.Update(new TValue(DateTime.UtcNow, double.PositiveInfinity));
Assert.True(double.IsFinite(resultAfterPosInf.Value));
// Feed negative infinity - should use last valid value
var resultAfterNegInf = sma.Update(new TValue(DateTime.UtcNow, double.NegativeInfinity));
Assert.True(double.IsFinite(resultAfterNegInf.Value));
}
[Fact]
public void Sma_MultipleNaN_ContinuesWithLastValid()
{
var sma = new Sma(5);
// Feed valid values
sma.Update(new TValue(DateTime.UtcNow, 100));
sma.Update(new TValue(DateTime.UtcNow, 110));
sma.Update(new TValue(DateTime.UtcNow, 120));
// Feed multiple NaN values
var r1 = sma.Update(new TValue(DateTime.UtcNow, double.NaN));
var r2 = sma.Update(new TValue(DateTime.UtcNow, double.NaN));
var r3 = sma.Update(new TValue(DateTime.UtcNow, double.NaN));
// All results should be finite
Assert.True(double.IsFinite(r1.Value));
Assert.True(double.IsFinite(r2.Value));
Assert.True(double.IsFinite(r3.Value));
}
[Fact]
public void Sma_BatchCalc_HandlesNaN()
{
var sma = new Sma(5);
// Create series with NaN values interspersed
var series = new TSeries();
series.Add(DateTime.UtcNow.Ticks, 100);
series.Add(DateTime.UtcNow.Ticks + 1, 110);
series.Add(DateTime.UtcNow.Ticks + 2, double.NaN);
series.Add(DateTime.UtcNow.Ticks + 3, 120);
series.Add(DateTime.UtcNow.Ticks + 4, double.PositiveInfinity);
series.Add(DateTime.UtcNow.Ticks + 5, 130);
var results = sma.Update(series);
// All results should be finite
foreach (var result in results)
{
Assert.True(double.IsFinite(result.Value), $"Expected finite value but got {result.Value}");
}
}
[Fact]
public void Sma_Reset_ClearsLastValidValue()
{
var sma = new Sma(5);
// Feed values including NaN
sma.Update(new TValue(DateTime.UtcNow, 100));
sma.Update(new TValue(DateTime.UtcNow, double.NaN));
// Reset
sma.Reset();
// After reset, first valid value should establish new baseline
var result = sma.Update(new TValue(DateTime.UtcNow, 50));
Assert.Equal(50.0, result.Value, 1e-10);
}
[Fact]
public void Sma_StaticCalculate_Works()
{
var series = new TSeries();
series.Add(DateTime.UtcNow.Ticks, 10);
series.Add(DateTime.UtcNow.Ticks + 1, 20);
series.Add(DateTime.UtcNow.Ticks + 2, 30);
series.Add(DateTime.UtcNow.Ticks + 3, 40);
series.Add(DateTime.UtcNow.Ticks + 4, 50);
var results = Sma.Calculate(series, 3);
Assert.Equal(5, results.Count);
// SMA(3) for last value: (30+40+50)/3 = 40
Assert.Equal(40.0, results.Last.Value, 1e-10);
}
[Fact]
public void Sma_Period1_ReturnsInputValues()
{
var sma = new Sma(1);
Assert.Equal(100.0, sma.Update(new TValue(DateTime.UtcNow, 100)).Value, 1e-10);
Assert.Equal(200.0, sma.Update(new TValue(DateTime.UtcNow, 200)).Value, 1e-10);
Assert.Equal(150.0, sma.Update(new TValue(DateTime.UtcNow, 150)).Value, 1e-10);
}
}