Files
QuanTAlib/lib/trends/dwma/Dwma.Tests.cs
T
Miha Kralj ac8b2dbb3f feat(tests): enhance tests with GBM for noise generation and improve tolerance for MAMA validation
feat(trends): implement IDisposable in Bessel and Conv classes to manage event subscriptions
fix(trends): add validation for period and parameters in Kama and MGDI calculations
fix(trends): clamp logarithmic calculations in JMA to avoid -Infinity
2025-12-25 20:18:14 -08:00

216 lines
6.7 KiB
C#

using System;
using Xunit;
namespace QuanTAlib;
public class DwmaTests
{
[Fact]
public void Constructor_InvalidPeriod_ThrowsArgumentException()
{
Assert.Throws<ArgumentException>(() => new Dwma(0));
Assert.Throws<ArgumentException>(() => new Dwma(-1));
}
[Fact]
public void Update_ValidInput_CalculatesCorrectly()
{
// DWMA(3) of [1, 2, 3, 4, 5]
// WMA(3) of [1, 2, 3, 4, 5]
// 1: 1
// 2: (1*1 + 2*2) / 3 = 5/3 = 1.666...
// 3: (1*1 + 2*2 + 3*3) / 6 = 14/6 = 2.333...
// 4: (1*2 + 2*3 + 3*4) / 6 = 20/6 = 3.333...
// 5: (1*3 + 2*4 + 3*5) / 6 = 26/6 = 4.333...
// WMA(3) results: [1, 1.666, 2.333, 3.333, 4.333]
// DWMA(3) = WMA(3) of [1, 1.666, 2.333, 3.333, 4.333]
// 1: 1
// 2: (1*1 + 2*1.666) / 3 = 4.333/3 = 1.444...
// 3: (1*1 + 2*1.666 + 3*2.333) / 6 = (1 + 3.333 + 7) / 6 = 11.333/6 = 1.888...
var dwma = new Dwma(3);
var v1 = dwma.Update(new TValue(DateTime.UtcNow, 1)).Value;
var v2 = dwma.Update(new TValue(DateTime.UtcNow, 2)).Value;
var v3 = dwma.Update(new TValue(DateTime.UtcNow, 3)).Value;
Assert.Equal(1.0, v1, 6);
Assert.Equal(1.444444, v2, 5);
Assert.Equal(1.888888, v3, 5);
}
[Fact]
public void Update_IsNewFalse_CorrectsValue()
{
var dwma = new Dwma(3);
dwma.Update(new TValue(DateTime.UtcNow, 1));
dwma.Update(new TValue(DateTime.UtcNow, 2));
// Update with 3, then correct to 4
var v3 = dwma.Update(new TValue(DateTime.UtcNow, 3), isNew: true).Value;
var v3_corrected = dwma.Update(new TValue(DateTime.UtcNow, 4), isNew: false).Value;
// Manual calc for sequence [1, 2, 4]
// WMA(3):
// 1: 1
// 2: 1.666
// 4: (1*1 + 2*2 + 3*4) / 6 = 17/6 = 2.8333
// DWMA(3) of [1, 1.666, 2.8333]
// 3: (1*1 + 2*1.666 + 3*2.8333) / 6 = (1 + 3.333 + 8.5) / 6 = 12.833/6 = 2.1388
Assert.Equal(1.888888, v3, 5); // From previous test
Assert.Equal(2.138888, v3_corrected, 5);
}
[Fact]
public void Reset_ClearsState()
{
var dwma = new Dwma(3);
dwma.Update(new TValue(DateTime.UtcNow, 1));
dwma.Update(new TValue(DateTime.UtcNow, 2));
dwma.Reset();
Assert.False(dwma.IsHot);
var v1 = dwma.Update(new TValue(DateTime.UtcNow, 1)).Value;
Assert.Equal(1.0, v1);
}
[Fact]
public void StaticCalculate_MatchesInstance()
{
int period = 10;
int count = 100;
var source = new TSeries();
var dwma = new Dwma(period);
for (int i = 0; i < count; i++)
{
source.Add(new TValue(DateTime.UtcNow.AddMinutes(i), i));
dwma.Update(source.Last);
}
var staticResult = Dwma.Batch(source, period);
Assert.Equal(source.Count, staticResult.Count);
Assert.Equal(dwma.Last.Value, staticResult.Last.Value, 8);
}
[Fact]
public void IterativeCorrections_RestoreToOriginalState()
{
var dwma = new Dwma(10);
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);
dwma.Update(tenthInput, isNew: true);
}
// Remember state after 10 values
double valueAfterTen = dwma.Last.Value;
// Generate 9 corrections with isNew=false (different values)
for (int i = 0; i < 9; i++)
{
var bar = gbm.Next(isNew: false);
dwma.Update(new TValue(bar.Time, bar.Close), isNew: false);
}
// Feed the remembered 10th input again with isNew=false
TValue finalValue = dwma.Update(tenthInput, isNew: false);
// Should match the original state after 10 values
Assert.Equal(valueAfterTen, finalValue.Value, 1e-9);
}
[Fact]
public void NaN_Input_UsesLastValidValue()
{
var dwma = new Dwma(5);
dwma.Update(new TValue(DateTime.UtcNow, 100));
dwma.Update(new TValue(DateTime.UtcNow, 110));
var resultAfterNaN = dwma.Update(new TValue(DateTime.UtcNow, double.NaN));
Assert.True(double.IsFinite(resultAfterNaN.Value));
Assert.NotEqual(0, resultAfterNaN.Value);
}
[Fact]
public void SpanCalc_ValidatesInput()
{
double[] source = [1, 2, 3, 4, 5];
double[] output = new double[5];
double[] wrongSizeOutput = new double[3];
Assert.Throws<ArgumentOutOfRangeException>(() => Dwma.Calculate(source.AsSpan(), output.AsSpan(), 0));
Assert.Throws<ArgumentException>(() => Dwma.Calculate(source.AsSpan(), wrongSizeOutput.AsSpan(), 3));
}
[Fact]
public void SpanCalc_HandlesNaN()
{
double[] source = [100, 110, double.NaN, 120, 130];
double[] output = new double[5];
Dwma.Calculate(source.AsSpan(), output.AsSpan(), 3);
foreach (var val in output)
{
Assert.True(double.IsFinite(val));
}
}
[Fact]
public void AllModes_ProduceSameResult()
{
// Arrange
int period = 10;
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 = Dwma.Batch(series, period);
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];
Dwma.Calculate(spanInput, spanOutput, period);
double spanResult = spanOutput[^1];
// 3. Streaming Mode
var streamingInd = new Dwma(period);
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 Dwma(pubSource, period);
for (int i = 0; i < series.Count; i++)
{
pubSource.Add(series[i]);
}
double eventingResult = eventingInd.Last.Value;
// Assert
Assert.Equal(expected, spanResult, precision: 9);
Assert.Equal(expected, streamingResult, precision: 9);
Assert.Equal(expected, eventingResult, precision: 9);
}
}