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(() => new Fisher(period: 0)); Assert.Equal("period", ex.ParamName); } [Fact] public void Constructor_NegativePeriod_Throws() { var ex = Assert.Throws(() => new Fisher(period: -5)); Assert.Equal("period", ex.ParamName); } [Fact] public void Constructor_InvalidAlpha_Zero_Throws() { var ex = Assert.Throws(() => new Fisher(period: 10, alpha: 0)); Assert.Equal("alpha", ex.ParamName); } [Fact] public void Constructor_InvalidAlpha_OverOne_Throws() { var ex = Assert.Throws(() => 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(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(() => 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(() => Fisher.Batch(src, output, 0)); Assert.Equal("period", ex.ParamName); } [Fact] public void Batch_Span_Empty_NoException() { var src = ReadOnlySpan.Empty; var output = Span.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); } }