Files

180 lines
6.1 KiB
C#

using Xunit;
using Xunit.Abstractions;
namespace QuanTAlib.Tests;
public sealed class MadhValidationTests : IDisposable
{
private readonly ITestOutputHelper _output;
private readonly ValidationTestData _testData;
private const int DefaultShortLength = 8;
private const int DefaultDominantCycle = 27;
public MadhValidationTests(ITestOutputHelper output)
{
_output = output;
_testData = new ValidationTestData(10000);
}
public void Dispose()
{
_testData.Dispose();
}
// ========== Self-consistency Validation ==========
[Fact]
public void Madh_BatchStreaming_Match()
{
// Streaming
var streaming = new Madh(DefaultShortLength, DefaultDominantCycle);
var streamResults = new List<double>(_testData.Data.Count);
for (int i = 0; i < _testData.Data.Count; i++)
{
TValue r = streaming.Update(_testData.Data[i], isNew: true);
streamResults.Add(r.Value);
}
// Batch
TSeries batchResults = Madh.Batch(_testData.Data, DefaultShortLength, DefaultDominantCycle);
int mismatchCount = 0;
double maxDiff = 0;
for (int i = 0; i < streamResults.Count; i++)
{
double diff = Math.Abs(streamResults[i] - batchResults[i].Value);
if (diff > 1e-10)
{
mismatchCount++;
maxDiff = Math.Max(maxDiff, diff);
}
}
_output.WriteLine($"Madh({DefaultShortLength},{DefaultDominantCycle}) Batch vs Streaming: {mismatchCount} mismatches, max diff = {maxDiff:E3}");
Assert.Equal(0, mismatchCount);
}
[Fact]
public void Madh_SpanBatch_MatchesStreaming()
{
// Streaming
var streaming = new Madh(DefaultShortLength, DefaultDominantCycle);
var streamResults = new List<double>(_testData.Data.Count);
for (int i = 0; i < _testData.Data.Count; i++)
{
TValue r = streaming.Update(_testData.Data[i], isNew: true);
streamResults.Add(r.Value);
}
// Span batch
double[] output = new double[_testData.Data.Count];
Madh.Batch(_testData.Data.Values, output, DefaultShortLength, DefaultDominantCycle);
int mismatchCount = 0;
double maxDiff = 0;
for (int i = 0; i < streamResults.Count; i++)
{
double diff = Math.Abs(streamResults[i] - output[i]);
if (diff > 1e-10)
{
mismatchCount++;
maxDiff = Math.Max(maxDiff, diff);
}
}
_output.WriteLine($"Madh({DefaultShortLength},{DefaultDominantCycle}) Span vs Streaming: {mismatchCount} mismatches, max diff = {maxDiff:E3}");
Assert.Equal(0, mismatchCount);
}
[Fact]
public void Madh_DifferentParams_ProduceDifferentResults()
{
TSeries result1 = Madh.Batch(_testData.Data, 5, 10);
TSeries result2 = Madh.Batch(_testData.Data, 10, 20);
int lastIdx = _testData.Data.Count - 1;
_output.WriteLine($"Madh(5,10) last = {result1[lastIdx].Value:F6}");
_output.WriteLine($"Madh(10,20) last = {result2[lastIdx].Value:F6}");
Assert.NotEqual(result1[lastIdx].Value, result2[lastIdx].Value);
}
[Fact]
public void Madh_ConstantInput_ConvergesToZero()
{
var indicator = new Madh(5, 10);
double constantVal = 100.0;
double lastResult = double.NaN;
for (int i = 0; i < 1000; i++)
{
TValue r = indicator.Update(new TValue(DateTime.UtcNow.AddSeconds(i), constantVal));
lastResult = r.Value;
}
_output.WriteLine($"Madh(5,10) constant input result after 1000 bars: {lastResult:E6}");
Assert.True(Math.Abs(lastResult) < 1e-6, $"Expected near-zero for constant input, got {lastResult}");
}
[Fact]
public void Madh_Calculate_ReturnsHotIndicator()
{
(TSeries results, Madh indicator) = Madh.Calculate(_testData.Data, DefaultShortLength, DefaultDominantCycle);
Assert.Equal(_testData.Data.Count, results.Count);
Assert.True(indicator.IsHot);
// Verify the indicator can continue streaming
TValue next = indicator.Update(new TValue(DateTime.UtcNow, 100.0), isNew: true);
Assert.True(double.IsFinite(next.Value));
_output.WriteLine($"Madh({DefaultShortLength},{DefaultDominantCycle}) Calculate: {results.Count} bars, last = {results[results.Count - 1].Value:F6}");
}
[Fact]
public void Madh_BarCorrection_ProducesConsistentResults()
{
// Build reference: 100 bars then bar 101
var reference = new Madh(DefaultShortLength, DefaultDominantCycle);
for (int i = 0; i < 100; i++)
{
reference.Update(_testData.Data[i], isNew: true);
}
reference.Update(new TValue(DateTime.UtcNow, 50.0), isNew: true);
double referenceVal = reference.Last.Value;
// Build test: 100 bars, wrong bar 101, then correct bar 101
var test = new Madh(DefaultShortLength, DefaultDominantCycle);
for (int i = 0; i < 100; i++)
{
test.Update(_testData.Data[i], isNew: true);
}
test.Update(new TValue(DateTime.UtcNow, 999.0), isNew: true); // wrong
test.Update(new TValue(DateTime.UtcNow, 50.0), isNew: false); // correct
double testVal = test.Last.Value;
_output.WriteLine($"Reference: {referenceVal:F10}, Corrected: {testVal:F10}");
Assert.Equal(referenceVal, testVal, 1e-10);
}
[Fact]
public void Madh_SubsetValidation_StableBehavior()
{
using var subset = _testData.CreateSubset(200);
TSeries results = Madh.Batch(subset.Data, DefaultShortLength, DefaultDominantCycle);
int nanCount = 0;
for (int i = 0; i < results.Count; i++)
{
if (!double.IsFinite(results[i].Value))
{
nanCount++;
}
}
_output.WriteLine($"Madh({DefaultShortLength},{DefaultDominantCycle}) on 200-bar subset: {nanCount} non-finite values");
Assert.Equal(0, nanCount);
}
}