mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-14 08:38:04 +00:00
- 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.
415 lines
12 KiB
C#
415 lines
12 KiB
C#
using Xunit;
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namespace QuanTAlib.Tests;
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public sealed class FisherTests
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{
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private const double Tolerance = 1e-9;
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// ───── A) Constructor validation ─────
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[Fact]
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public void Constructor_DefaultPeriod_IsValid()
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{
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var fisher = new Fisher();
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Assert.Equal(10, fisher.Period);
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Assert.Equal("Fisher(10)", fisher.Name);
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}
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[Fact]
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public void Constructor_InvalidPeriod_Throws()
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{
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var ex = Assert.Throws<ArgumentException>(() => new Fisher(period: 0));
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Assert.Equal("period", ex.ParamName);
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}
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[Fact]
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public void Constructor_NegativePeriod_Throws()
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{
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var ex = Assert.Throws<ArgumentException>(() => new Fisher(period: -5));
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Assert.Equal("period", ex.ParamName);
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}
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[Fact]
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public void Constructor_InvalidAlpha_Zero_Throws()
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{
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var ex = Assert.Throws<ArgumentException>(() => new Fisher(period: 10, alpha: 0));
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Assert.Equal("alpha", ex.ParamName);
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}
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[Fact]
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public void Constructor_InvalidAlpha_OverOne_Throws()
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{
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var ex = Assert.Throws<ArgumentException>(() => new Fisher(period: 10, alpha: 1.5));
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Assert.Equal("alpha", ex.ParamName);
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}
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[Fact]
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public void Constructor_CustomPeriod_SetsCorrectly()
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{
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var fisher = new Fisher(period: 20);
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Assert.Equal(20, fisher.Period);
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Assert.Equal("Fisher(20)", fisher.Name);
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}
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// ───── B) Basic calculation ─────
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[Fact]
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public void Update_ReturnsTValue()
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{
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var fisher = new Fisher(period: 5);
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var result = fisher.Update(new TValue(DateTime.UtcNow, 100.0));
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Assert.IsType<TValue>(result);
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}
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[Fact]
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public void Update_Last_IsAccessible()
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{
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var fisher = new Fisher(period: 5);
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fisher.Update(new TValue(DateTime.UtcNow, 100.0));
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Assert.True(double.IsFinite(fisher.Last.Value));
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}
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[Fact]
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public void Update_FisherAndSignal_Accessible()
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{
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var fisher = new Fisher(period: 5);
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for (int i = 0; i < 10; i++)
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{
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fisher.Update(new TValue(DateTime.UtcNow, 100.0 + i));
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}
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Assert.True(double.IsFinite(fisher.FisherValue));
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Assert.True(double.IsFinite(fisher.Signal));
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}
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[Fact]
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public void Update_RisingPrices_PositiveFisher()
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{
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var fisher = new Fisher(period: 5);
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for (int i = 0; i < 20; i++)
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{
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fisher.Update(new TValue(DateTime.UtcNow, 100.0 + i * 2));
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}
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Assert.True(fisher.FisherValue > 0, "Rising prices should produce positive Fisher");
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}
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[Fact]
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public void Update_FallingPrices_NegativeFisher()
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{
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var fisher = new Fisher(period: 5);
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for (int i = 0; i < 20; i++)
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{
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fisher.Update(new TValue(DateTime.UtcNow, 200.0 - i * 2));
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}
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Assert.True(fisher.FisherValue < 0, "Falling prices should produce negative Fisher");
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}
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// ───── C) State + bar correction ─────
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[Fact]
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public void Update_IsNew_False_RollsBack()
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{
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var fisher = new Fisher(period: 5);
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for (int i = 0; i < 12; i++)
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{
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fisher.Update(new TValue(DateTime.UtcNow, 100.0 + i), isNew: true);
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}
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fisher.Update(new TValue(DateTime.UtcNow, 105.0), isNew: false);
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var corrected = fisher.Last;
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fisher.Update(new TValue(DateTime.UtcNow, 105.0), isNew: false);
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var corrected2 = fisher.Last;
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Assert.Equal(corrected.Value, corrected2.Value, Tolerance);
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}
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[Fact]
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public void Update_IterativeCorrections_Restore()
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{
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var fisher = new Fisher(period: 5);
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double[] data = new double[15];
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for (int i = 0; i < data.Length; i++)
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{
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data[i] = 100 + i * 2;
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}
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for (int i = 0; i < data.Length; i++)
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{
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fisher.Update(new TValue(DateTime.UtcNow, data[i]), isNew: true);
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}
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var baseline = fisher.Last.Value;
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fisher.Update(new TValue(DateTime.UtcNow, 999.0), isNew: false);
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fisher.Update(new TValue(DateTime.UtcNow, 888.0), isNew: false);
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fisher.Update(new TValue(DateTime.UtcNow, data[^1]), isNew: false);
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Assert.Equal(baseline, fisher.Last.Value, Tolerance);
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}
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[Fact]
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public void Reset_ClearsState()
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{
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var fisher = new Fisher(period: 5);
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for (int i = 0; i < 10; i++)
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{
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fisher.Update(new TValue(DateTime.UtcNow, 100.0 + i));
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}
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fisher.Reset();
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Assert.False(fisher.IsHot);
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Assert.Equal(0.0, fisher.Last.Value);
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}
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// ───── D) Warmup/convergence ─────
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[Fact]
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public void IsHot_FlipsAfterPeriod()
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{
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int period = 10;
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var fisher = new Fisher(period);
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for (int i = 0; i < period - 1; i++)
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{
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fisher.Update(new TValue(DateTime.UtcNow, 100.0 + i));
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Assert.False(fisher.IsHot);
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}
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fisher.Update(new TValue(DateTime.UtcNow, 110.0));
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Assert.True(fisher.IsHot);
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}
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[Fact]
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public void WarmupPeriod_MatchesPeriod()
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{
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var fisher = new Fisher(period: 14);
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Assert.Equal(14, fisher.WarmupPeriod);
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}
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// ───── E) Robustness ─────
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[Fact]
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public void Update_NaN_UsesLastValid()
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{
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var fisher = new Fisher(period: 5);
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for (int i = 0; i < 10; i++)
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{
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fisher.Update(new TValue(DateTime.UtcNow, 100.0 + i));
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}
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_ = fisher.Last.Value;
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fisher.Update(new TValue(DateTime.UtcNow, double.NaN));
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Assert.True(double.IsFinite(fisher.Last.Value));
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}
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[Fact]
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public void Update_Infinity_UsesLastValid()
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{
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var fisher = new Fisher(period: 5);
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for (int i = 0; i < 10; i++)
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{
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fisher.Update(new TValue(DateTime.UtcNow, 100.0 + i));
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}
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fisher.Update(new TValue(DateTime.UtcNow, double.PositiveInfinity));
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Assert.True(double.IsFinite(fisher.Last.Value));
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}
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[Fact]
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public void Update_BatchNaN_RemainsFinite()
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{
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var fisher = new Fisher(period: 5);
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for (int i = 0; i < 3; i++)
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{
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fisher.Update(new TValue(DateTime.UtcNow, double.NaN));
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}
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Assert.True(double.IsFinite(fisher.Last.Value));
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}
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// ───── F) Consistency (4 modes match) ─────
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[Fact]
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public void AllModes_ProduceSameResults()
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{
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int period = 10;
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var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: 42);
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var bars = gbm.Fetch(500, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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TSeries source = bars.Close;
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// 1. Streaming
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var streaming = new Fisher(period);
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var streamResults = new double[source.Count];
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for (int i = 0; i < source.Count; i++)
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{
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streamResults[i] = streaming.Update(source[i]).Value;
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}
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// 2. Batch TSeries
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TSeries batchSeries = Fisher.Batch(source, period);
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// 3. Batch Span
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var spanOutput = new double[source.Count];
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Fisher.Batch(source.Values, spanOutput, period);
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// 4. Event-based
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var eventSource = new TSeries();
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var eventIndicator = new Fisher(eventSource, period);
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var eventResults = new double[source.Count];
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for (int i = 0; i < source.Count; i++)
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{
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eventSource.Add(source[i]);
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eventResults[i] = eventIndicator.Last.Value;
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}
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for (int i = 0; i < source.Count; i++)
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{
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Assert.Equal(streamResults[i], batchSeries.Values[i], Tolerance);
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Assert.Equal(streamResults[i], spanOutput[i], Tolerance);
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Assert.Equal(streamResults[i], eventResults[i], Tolerance);
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}
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}
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// ───── G) Span API tests ─────
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[Fact]
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public void Batch_Span_MismatchedLengths_Throws()
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{
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var src = new double[10];
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var output = new double[5];
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var ex = Assert.Throws<ArgumentException>(() => Fisher.Batch(src, output, 5));
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Assert.Equal("output", ex.ParamName);
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}
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[Fact]
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public void Batch_Span_InvalidPeriod_Throws()
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{
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var src = new double[10];
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var output = new double[10];
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var ex = Assert.Throws<ArgumentException>(() => Fisher.Batch(src, output, 0));
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Assert.Equal("period", ex.ParamName);
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}
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[Fact]
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public void Batch_Span_Empty_NoException()
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{
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var src = ReadOnlySpan<double>.Empty;
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var output = Span<double>.Empty;
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Fisher.Batch(src, output, 5);
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Assert.True(true);
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}
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[Fact]
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public void Batch_Span_MatchesTSeries()
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{
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var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: 42);
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var bars = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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TSeries source = bars.Close;
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TSeries batchSeries = Fisher.Batch(source, 10);
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var spanOutput = new double[source.Count];
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Fisher.Batch(source.Values, spanOutput, 10);
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for (int i = 0; i < source.Count; i++)
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{
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Assert.Equal(batchSeries.Values[i], spanOutput[i], 12);
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}
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}
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[Fact]
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public void Batch_Span_NaN_Handled()
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{
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double[] src = [100, 101, double.NaN, 103, 104, 105, 106, 107, 108, 109];
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var output = new double[src.Length];
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Fisher.Batch(src, output, 5);
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for (int i = 0; i < output.Length; i++)
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{
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Assert.True(double.IsFinite(output[i]));
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}
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}
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// ───── H) Chainability ─────
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[Fact]
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public void Event_PubFires()
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{
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var source = new TSeries();
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var fisher = new Fisher(source, period: 5);
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int count = 0;
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fisher.Pub += (object? _, in TValueEventArgs _) => count++;
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source.Add(new TValue(DateTime.UtcNow, 100.0));
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Assert.Equal(1, count);
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}
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[Fact]
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public void Event_ChainingWorks()
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{
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var source = new TSeries();
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var fisher = new Fisher(source, period: 5);
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for (int i = 0; i < 20; i++)
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{
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source.Add(new TValue(DateTime.UtcNow, 100.0 + i));
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}
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Assert.True(fisher.IsHot);
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Assert.True(double.IsFinite(fisher.Last.Value));
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}
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// ───── Domain-specific tests ─────
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[Fact]
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public void FisherTransform_MathematicalProperties()
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{
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// Fisher Transform is arctanh: should be odd function
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// For normalized input 0, Fisher should be 0
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var fisher = new Fisher(period: 5);
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// Feed constant price → normalized = 0 → Fisher ≈ 0
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for (int i = 0; i < 20; i++)
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{
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fisher.Update(new TValue(DateTime.UtcNow, 100.0));
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}
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Assert.True(Math.Abs(fisher.FisherValue) < 0.1,
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$"Constant price should produce Fisher near 0, got {fisher.FisherValue}");
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}
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[Fact]
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public void FisherTransform_OutputIsUnbounded()
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{
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// Fisher can exceed ±2 with strong trends
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var fisher = new Fisher(period: 5);
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// Create a very strong uptrend
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for (int i = 0; i < 30; i++)
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{
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fisher.Update(new TValue(DateTime.UtcNow, 100.0 + i * 10));
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}
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// Fisher should be significantly positive
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Assert.True(fisher.FisherValue > 1.0,
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$"Strong uptrend should produce Fisher > 1, got {fisher.FisherValue}");
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}
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[Fact]
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public void Signal_LagseFisher()
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{
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// Signal is EMA of Fisher, so under strong trend it should lag
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var fisher = new Fisher(period: 5);
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for (int i = 0; i < 30; i++)
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{
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fisher.Update(new TValue(DateTime.UtcNow, 100.0 + i * 5));
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}
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// Both should be positive in uptrend
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Assert.True(fisher.FisherValue > 0);
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Assert.True(fisher.Signal > 0);
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}
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}
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