Files
QuanTAlib/lib/oscillators/fisher/Fisher.Tests.cs
T
Miha Kralj 92709ef2ed Add Stochastic Oscillator implementation and validation tests
- Implemented Stochastic Oscillator (%K and %D) in Stoch.cs with streaming and batch processing capabilities.
- Added validation tests for the Stochastic Oscillator in Stoch.Validation.Tests.cs, ensuring consistency with Skender.Stock.Indicators.
- Created documentation for the Stochastic Oscillator in Stoch.md, detailing its mathematical formula, architecture, parameters, and common pitfalls.
- Updated project file to include necessary numeric libraries for highest and lowest calculations.
2026-02-12 14:29:54 -08:00

415 lines
12 KiB
C#

using Xunit;
namespace QuanTAlib.Tests;
public sealed class FisherTests
{
private const double Tolerance = 1e-9;
// ───── A) Constructor validation ─────
[Fact]
public void Constructor_DefaultPeriod_IsValid()
{
var fisher = new Fisher();
Assert.Equal(10, fisher.Period);
Assert.Equal("Fisher(10)", fisher.Name);
}
[Fact]
public void Constructor_InvalidPeriod_Throws()
{
var ex = Assert.Throws<ArgumentException>(() => new Fisher(period: 0));
Assert.Equal("period", ex.ParamName);
}
[Fact]
public void Constructor_NegativePeriod_Throws()
{
var ex = Assert.Throws<ArgumentException>(() => new Fisher(period: -5));
Assert.Equal("period", ex.ParamName);
}
[Fact]
public void Constructor_InvalidAlpha_Zero_Throws()
{
var ex = Assert.Throws<ArgumentException>(() => new Fisher(period: 10, alpha: 0));
Assert.Equal("alpha", ex.ParamName);
}
[Fact]
public void Constructor_InvalidAlpha_OverOne_Throws()
{
var ex = Assert.Throws<ArgumentException>(() => new Fisher(period: 10, alpha: 1.5));
Assert.Equal("alpha", ex.ParamName);
}
[Fact]
public void Constructor_CustomPeriod_SetsCorrectly()
{
var fisher = new Fisher(period: 20);
Assert.Equal(20, fisher.Period);
Assert.Equal("Fisher(20)", fisher.Name);
}
// ───── B) Basic calculation ─────
[Fact]
public void Update_ReturnsTValue()
{
var fisher = new Fisher(period: 5);
var result = fisher.Update(new TValue(DateTime.UtcNow, 100.0));
Assert.IsType<TValue>(result);
}
[Fact]
public void Update_Last_IsAccessible()
{
var fisher = new Fisher(period: 5);
fisher.Update(new TValue(DateTime.UtcNow, 100.0));
Assert.True(double.IsFinite(fisher.Last.Value));
}
[Fact]
public void Update_FisherAndSignal_Accessible()
{
var fisher = new Fisher(period: 5);
for (int i = 0; i < 10; i++)
{
fisher.Update(new TValue(DateTime.UtcNow, 100.0 + i));
}
Assert.True(double.IsFinite(fisher.FisherValue));
Assert.True(double.IsFinite(fisher.Signal));
}
[Fact]
public void Update_RisingPrices_PositiveFisher()
{
var fisher = new Fisher(period: 5);
for (int i = 0; i < 20; i++)
{
fisher.Update(new TValue(DateTime.UtcNow, 100.0 + i * 2));
}
Assert.True(fisher.FisherValue > 0, "Rising prices should produce positive Fisher");
}
[Fact]
public void Update_FallingPrices_NegativeFisher()
{
var fisher = new Fisher(period: 5);
for (int i = 0; i < 20; i++)
{
fisher.Update(new TValue(DateTime.UtcNow, 200.0 - i * 2));
}
Assert.True(fisher.FisherValue < 0, "Falling prices should produce negative Fisher");
}
// ───── C) State + bar correction ─────
[Fact]
public void Update_IsNew_False_RollsBack()
{
var fisher = new Fisher(period: 5);
for (int i = 0; i < 12; i++)
{
fisher.Update(new TValue(DateTime.UtcNow, 100.0 + i), isNew: true);
}
fisher.Update(new TValue(DateTime.UtcNow, 105.0), isNew: false);
var corrected = fisher.Last;
fisher.Update(new TValue(DateTime.UtcNow, 105.0), isNew: false);
var corrected2 = fisher.Last;
Assert.Equal(corrected.Value, corrected2.Value, Tolerance);
}
[Fact]
public void Update_IterativeCorrections_Restore()
{
var fisher = new Fisher(period: 5);
double[] data = new double[15];
for (int i = 0; i < data.Length; i++)
{
data[i] = 100 + i * 2;
}
for (int i = 0; i < data.Length; i++)
{
fisher.Update(new TValue(DateTime.UtcNow, data[i]), isNew: true);
}
var baseline = fisher.Last.Value;
fisher.Update(new TValue(DateTime.UtcNow, 999.0), isNew: false);
fisher.Update(new TValue(DateTime.UtcNow, 888.0), isNew: false);
fisher.Update(new TValue(DateTime.UtcNow, data[^1]), isNew: false);
Assert.Equal(baseline, fisher.Last.Value, Tolerance);
}
[Fact]
public void Reset_ClearsState()
{
var fisher = new Fisher(period: 5);
for (int i = 0; i < 10; i++)
{
fisher.Update(new TValue(DateTime.UtcNow, 100.0 + i));
}
fisher.Reset();
Assert.False(fisher.IsHot);
Assert.Equal(0.0, fisher.Last.Value);
}
// ───── D) Warmup/convergence ─────
[Fact]
public void IsHot_FlipsAfterPeriod()
{
int period = 10;
var fisher = new Fisher(period);
for (int i = 0; i < period - 1; i++)
{
fisher.Update(new TValue(DateTime.UtcNow, 100.0 + i));
Assert.False(fisher.IsHot);
}
fisher.Update(new TValue(DateTime.UtcNow, 110.0));
Assert.True(fisher.IsHot);
}
[Fact]
public void WarmupPeriod_MatchesPeriod()
{
var fisher = new Fisher(period: 14);
Assert.Equal(14, fisher.WarmupPeriod);
}
// ───── E) Robustness ─────
[Fact]
public void Update_NaN_UsesLastValid()
{
var fisher = new Fisher(period: 5);
for (int i = 0; i < 10; i++)
{
fisher.Update(new TValue(DateTime.UtcNow, 100.0 + i));
}
_ = fisher.Last.Value;
fisher.Update(new TValue(DateTime.UtcNow, double.NaN));
Assert.True(double.IsFinite(fisher.Last.Value));
}
[Fact]
public void Update_Infinity_UsesLastValid()
{
var fisher = new Fisher(period: 5);
for (int i = 0; i < 10; i++)
{
fisher.Update(new TValue(DateTime.UtcNow, 100.0 + i));
}
fisher.Update(new TValue(DateTime.UtcNow, double.PositiveInfinity));
Assert.True(double.IsFinite(fisher.Last.Value));
}
[Fact]
public void Update_BatchNaN_RemainsFinite()
{
var fisher = new Fisher(period: 5);
for (int i = 0; i < 3; i++)
{
fisher.Update(new TValue(DateTime.UtcNow, double.NaN));
}
Assert.True(double.IsFinite(fisher.Last.Value));
}
// ───── F) Consistency (4 modes match) ─────
[Fact]
public void AllModes_ProduceSameResults()
{
int period = 10;
var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: 42);
var bars = gbm.Fetch(500, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
TSeries source = bars.Close;
// 1. Streaming
var streaming = new Fisher(period);
var streamResults = new double[source.Count];
for (int i = 0; i < source.Count; i++)
{
streamResults[i] = streaming.Update(source[i]).Value;
}
// 2. Batch TSeries
TSeries batchSeries = Fisher.Batch(source, period);
// 3. Batch Span
var spanOutput = new double[source.Count];
Fisher.Batch(source.Values, spanOutput, period);
// 4. Event-based
var eventSource = new TSeries();
var eventIndicator = new Fisher(eventSource, period);
var eventResults = new double[source.Count];
for (int i = 0; i < source.Count; i++)
{
eventSource.Add(source[i]);
eventResults[i] = eventIndicator.Last.Value;
}
for (int i = 0; i < source.Count; i++)
{
Assert.Equal(streamResults[i], batchSeries.Values[i], Tolerance);
Assert.Equal(streamResults[i], spanOutput[i], Tolerance);
Assert.Equal(streamResults[i], eventResults[i], Tolerance);
}
}
// ───── G) Span API tests ─────
[Fact]
public void Batch_Span_MismatchedLengths_Throws()
{
var src = new double[10];
var output = new double[5];
var ex = Assert.Throws<ArgumentException>(() => Fisher.Batch(src, output, 5));
Assert.Equal("output", ex.ParamName);
}
[Fact]
public void Batch_Span_InvalidPeriod_Throws()
{
var src = new double[10];
var output = new double[10];
var ex = Assert.Throws<ArgumentException>(() => Fisher.Batch(src, output, 0));
Assert.Equal("period", ex.ParamName);
}
[Fact]
public void Batch_Span_Empty_NoException()
{
var src = ReadOnlySpan<double>.Empty;
var output = Span<double>.Empty;
Fisher.Batch(src, output, 5);
Assert.True(true);
}
[Fact]
public void Batch_Span_MatchesTSeries()
{
var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: 42);
var bars = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
TSeries source = bars.Close;
TSeries batchSeries = Fisher.Batch(source, 10);
var spanOutput = new double[source.Count];
Fisher.Batch(source.Values, spanOutput, 10);
for (int i = 0; i < source.Count; i++)
{
Assert.Equal(batchSeries.Values[i], spanOutput[i], 12);
}
}
[Fact]
public void Batch_Span_NaN_Handled()
{
double[] src = [100, 101, double.NaN, 103, 104, 105, 106, 107, 108, 109];
var output = new double[src.Length];
Fisher.Batch(src, output, 5);
for (int i = 0; i < output.Length; i++)
{
Assert.True(double.IsFinite(output[i]));
}
}
// ───── H) Chainability ─────
[Fact]
public void Event_PubFires()
{
var source = new TSeries();
var fisher = new Fisher(source, period: 5);
int count = 0;
fisher.Pub += (object? _, in TValueEventArgs _) => count++;
source.Add(new TValue(DateTime.UtcNow, 100.0));
Assert.Equal(1, count);
}
[Fact]
public void Event_ChainingWorks()
{
var source = new TSeries();
var fisher = new Fisher(source, period: 5);
for (int i = 0; i < 20; i++)
{
source.Add(new TValue(DateTime.UtcNow, 100.0 + i));
}
Assert.True(fisher.IsHot);
Assert.True(double.IsFinite(fisher.Last.Value));
}
// ───── Domain-specific tests ─────
[Fact]
public void FisherTransform_MathematicalProperties()
{
// Fisher Transform is arctanh: should be odd function
// For normalized input 0, Fisher should be 0
var fisher = new Fisher(period: 5);
// Feed constant price → normalized = 0 → Fisher ≈ 0
for (int i = 0; i < 20; i++)
{
fisher.Update(new TValue(DateTime.UtcNow, 100.0));
}
Assert.True(Math.Abs(fisher.FisherValue) < 0.1,
$"Constant price should produce Fisher near 0, got {fisher.FisherValue}");
}
[Fact]
public void FisherTransform_OutputIsUnbounded()
{
// Fisher can exceed ±2 with strong trends
var fisher = new Fisher(period: 5);
// Create a very strong uptrend
for (int i = 0; i < 30; i++)
{
fisher.Update(new TValue(DateTime.UtcNow, 100.0 + i * 10));
}
// Fisher should be significantly positive
Assert.True(fisher.FisherValue > 1.0,
$"Strong uptrend should produce Fisher > 1, got {fisher.FisherValue}");
}
[Fact]
public void Signal_LagseFisher()
{
// Signal is EMA of Fisher, so under strong trend it should lag
var fisher = new Fisher(period: 5);
for (int i = 0; i < 30; i++)
{
fisher.Update(new TValue(DateTime.UtcNow, 100.0 + i * 5));
}
// Both should be positive in uptrend
Assert.True(fisher.FisherValue > 0);
Assert.True(fisher.Signal > 0);
}
}