Files
QuanTAlib/lib/cycles/fsi/tests/Fsi.Validation.Tests.cs

159 lines
4.2 KiB
C#

namespace QuanTAlib.Tests;
public class FsiValidationTests
{
private static readonly Random _rng = new(42);
private static TSeries MakeSeries(int count = 500)
{
var series = new TSeries();
double price = 100.0;
for (int i = 0; i < count; i++)
{
price += (_rng.NextDouble() - 0.5) * 2.0;
series.Add(new TValue(DateTime.UtcNow.AddMinutes(i), price));
}
return series;
}
[Fact]
public void BatchStreaming_Match()
{
var series = MakeSeries(300);
int period = 20;
double bw = 0.1;
// Streaming
var streaming = new Fsi(period, bw);
var streamResults = new double[series.Count];
for (int i = 0; i < series.Count; i++)
{
streamResults[i] = streaming.Update(series[i]).Value;
}
// Batch
var batchResult = Fsi.Batch(series, period, bw);
for (int i = 0; i < series.Count; i++)
{
Assert.Equal(streamResults[i], batchResult[i].Value, 10);
}
}
[Fact]
public void SpanStreaming_Match()
{
var series = MakeSeries(300);
int period = 20;
double bw = 0.1;
// Streaming
var streaming = new Fsi(period, bw);
var streamResults = new double[series.Count];
for (int i = 0; i < series.Count; i++)
{
streamResults[i] = streaming.Update(series[i]).Value;
}
// Span batch
var spanResults = new double[series.Count];
Fsi.Batch(series.Values, spanResults, period, bw);
for (int i = 0; i < series.Count; i++)
{
Assert.Equal(streamResults[i], spanResults[i], 10);
}
}
[Fact]
public void DifferentPeriods_ProduceDifferentOutputs()
{
var series = MakeSeries(300);
var result1 = new double[series.Count];
var result2 = new double[series.Count];
Fsi.Batch(series.Values, result1, 20, 0.1);
Fsi.Batch(series.Values, result2, 40, 0.1);
bool allEqual = true;
for (int i = 50; i < series.Count; i++)
{
if (Math.Abs(result1[i] - result2[i]) > 1e-12)
{
allEqual = false;
break;
}
}
Assert.False(allEqual, "Different periods should produce different outputs");
}
[Fact]
public void ConstantInput_ProducesZero()
{
int count = 200;
var src = new double[count];
var dst = new double[count];
Array.Fill(src, 100.0);
Fsi.Batch(src, dst, 20, 0.1);
// After warmup, constant input → all-zero bandpass → output = 0
for (int i = 20; i < count; i++)
{
Assert.Equal(0.0, dst[i], 10);
}
}
[Fact]
public void Calculate_ReturnsHotIndicator()
{
var series = MakeSeries(200);
var (results, indicator) = Fsi.Calculate(series, 20, 0.1);
Assert.Equal(series.Count, results.Count);
Assert.True(indicator.IsHot);
}
[Fact]
public void BarCorrection_Consistency()
{
var series = MakeSeries(100);
var fsi = new Fsi(20, 0.1);
foreach (var bar in series)
{
fsi.Update(bar);
}
// New bar
double v1 = fsi.Update(new TValue(DateTime.UtcNow, 105.0), isNew: true).Value;
// Corrections
_ = fsi.Update(new TValue(DateTime.UtcNow, 108.0), isNew: false);
_ = fsi.Update(new TValue(DateTime.UtcNow, 112.0), isNew: false);
double v4 = fsi.Update(new TValue(DateTime.UtcNow, 105.0), isNew: false).Value;
Assert.Equal(v1, v4, 10);
}
[Fact]
public void SubsetStability()
{
// Running on a longer series should not change earlier values
var series = MakeSeries(300);
int period = 20;
double bw = 0.1;
var result200 = new double[200];
Fsi.Batch(series.Values[..200], result200, period, bw);
var result300 = new double[300];
Fsi.Batch(series.Values, result300, period, bw);
// First 200 bars of both runs must match exactly
for (int i = 0; i < 200; i++)
{
Assert.Equal(result200[i], result300[i], 15);
}
}
}