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https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-22 20:48:04 +00:00
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.
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using Xunit;
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namespace QuanTAlib.Tests;
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public sealed class CfoTests
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{
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private const int DefaultPeriod = 14;
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private const double Tolerance = 1e-10;
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// ───── A) Constructor validation ─────
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[Fact]
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public void Constructor_PeriodZero_ThrowsArgumentException()
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{
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var ex = Assert.Throws<ArgumentException>(() => new Cfo(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_ThrowsArgumentException()
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{
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var ex = Assert.Throws<ArgumentException>(() => new Cfo(period: -1));
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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_ValidPeriod_SetsProperties()
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{
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var cfo = new Cfo(period: 10);
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Assert.Equal(10, cfo.Period);
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Assert.Equal("Cfo(10)", cfo.Name);
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Assert.Equal(10, cfo.WarmupPeriod);
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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 cfo = new Cfo(DefaultPeriod);
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var result = cfo.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 cfo = new Cfo(DefaultPeriod);
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cfo.Update(new TValue(DateTime.UtcNow, 100.0));
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Assert.NotEqual(default, cfo.Last);
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Assert.False(cfo.IsHot);
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Assert.Equal($"Cfo({DefaultPeriod})", cfo.Name);
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}
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[Fact]
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public void Update_ConstantInput_ZeroCfo()
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{
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var cfo = new Cfo(period: 5);
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for (int i = 0; i < 10; i++)
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{
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cfo.Update(new TValue(DateTime.UtcNow, 50.0));
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}
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// Constant input => TSF == source => CFO == 0
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Assert.Equal(0.0, cfo.Last.Value, Tolerance);
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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_True_AdvancesState()
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{
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var cfo = new Cfo(DefaultPeriod);
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cfo.Update(new TValue(DateTime.UtcNow, 100.0), isNew: true);
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cfo.Update(new TValue(DateTime.UtcNow, 110.0), isNew: true);
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var last = cfo.Last;
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// Should have two distinct updates
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Assert.NotEqual(default, last);
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}
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[Fact]
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public void Update_IsNew_False_RollsBack()
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{
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var cfo = new Cfo(period: 5);
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for (int i = 0; i < 6; i++)
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{
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cfo.Update(new TValue(DateTime.UtcNow, 100.0 + i), isNew: true);
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}
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// Bar correction: rewrite last bar
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cfo.Update(new TValue(DateTime.UtcNow, 105.0), isNew: false);
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var corrected = cfo.Last;
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// Repeat same correction — should produce identical result
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cfo.Update(new TValue(DateTime.UtcNow, 105.0), isNew: false);
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var corrected2 = cfo.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 cfo = new Cfo(period: 5);
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double[] data = [100, 102, 104, 106, 108, 110];
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for (int i = 0; i < data.Length; i++)
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{
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cfo.Update(new TValue(DateTime.UtcNow, data[i]), isNew: true);
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}
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var baseline = cfo.Last.Value;
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// Correct last bar 3 times, then restore original
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cfo.Update(new TValue(DateTime.UtcNow, 999.0), isNew: false);
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cfo.Update(new TValue(DateTime.UtcNow, 888.0), isNew: false);
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cfo.Update(new TValue(DateTime.UtcNow, data[^1]), isNew: false);
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Assert.Equal(baseline, cfo.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 cfo = new Cfo(DefaultPeriod);
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for (int i = 0; i < 20; i++)
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{
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cfo.Update(new TValue(DateTime.UtcNow, 100.0 + i));
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}
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Assert.True(cfo.IsHot);
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cfo.Reset();
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Assert.False(cfo.IsHot);
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Assert.Equal(default, cfo.Last);
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}
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// ───── D) Warmup / convergence ─────
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[Fact]
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public void IsHot_FlipsWhenBufferFull()
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{
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var cfo = new Cfo(period: 5);
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for (int i = 0; i < 4; i++)
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{
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cfo.Update(new TValue(DateTime.UtcNow, 100.0 + i));
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Assert.False(cfo.IsHot);
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}
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cfo.Update(new TValue(DateTime.UtcNow, 104.0));
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Assert.True(cfo.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 cfo = new Cfo(period: 20);
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Assert.Equal(20, cfo.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 cfo = new Cfo(period: 5);
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for (int i = 0; i < 6; i++)
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{
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cfo.Update(new TValue(DateTime.UtcNow, 100.0 + i));
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}
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cfo.Update(new TValue(DateTime.UtcNow, double.NaN));
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Assert.True(double.IsFinite(cfo.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 cfo = new Cfo(period: 5);
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for (int i = 0; i < 6; i++)
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{
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cfo.Update(new TValue(DateTime.UtcNow, 100.0 + i));
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}
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cfo.Update(new TValue(DateTime.UtcNow, double.PositiveInfinity));
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Assert.True(double.IsFinite(cfo.Last.Value));
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cfo.Update(new TValue(DateTime.UtcNow, double.NegativeInfinity));
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Assert.True(double.IsFinite(cfo.Last.Value));
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}
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[Fact]
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public void Update_BatchNaN_Safe()
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{
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var cfo = new Cfo(period: 5);
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for (int i = 0; i < 3; i++)
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{
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cfo.Update(new TValue(DateTime.UtcNow, double.NaN));
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}
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// No exception thrown; result should be finite (falls back to 0.0)
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Assert.True(double.IsFinite(cfo.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 Cfo(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 = Cfo.Batch(source, period);
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// 3. Batch Span
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var spanOutput = new double[source.Count];
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Cfo.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 Cfo(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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// Compare all modes
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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_MismatchedLength_ThrowsArgumentException()
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{
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var source = new double[10];
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var output = new double[5];
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var ex = Assert.Throws<ArgumentException>(() => Cfo.Batch(source.AsSpan(), output.AsSpan(), DefaultPeriod));
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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_ZeroPeriod_ThrowsArgumentException()
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{
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var source = new double[10];
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var output = new double[10];
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var ex = Assert.Throws<ArgumentException>(() => Cfo.Batch(source.AsSpan(), output.AsSpan(), 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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double[] source = [];
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double[] output = [];
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var ex = Record.Exception(() => Cfo.Batch(source.AsSpan(), output.AsSpan(), DefaultPeriod));
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Assert.Null(ex);
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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: 7);
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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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int period = 10;
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TSeries batchTs = Cfo.Batch(source, period);
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var spanOutput = new double[source.Count];
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Cfo.Batch(source.Values, spanOutput, period);
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for (int i = 0; i < source.Count; i++)
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{
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Assert.Equal(batchTs.Values[i], spanOutput[i], Tolerance);
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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 = [1, 2, double.NaN, 4, 5, 6, 7, 8, 9, 10];
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var output = new double[src.Length];
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var ex = Record.Exception(() => Cfo.Batch(src.AsSpan(), output.AsSpan(), 5));
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Assert.Null(ex);
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}
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// ───── H) Chainability ─────
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[Fact]
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public void PubEvent_FiresOnUpdate()
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{
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var cfo = new Cfo(DefaultPeriod);
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int firedCount = 0;
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cfo.Pub += (object? _, in TValueEventArgs _) => firedCount++;
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cfo.Update(new TValue(DateTime.UtcNow, 100.0));
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Assert.Equal(1, firedCount);
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}
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[Fact]
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public void EventChaining_Works()
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{
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var source = new TSeries();
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var cfo = new Cfo(source, period: 5);
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var downstream = new TSeries();
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cfo.Pub += (object? _, in TValueEventArgs e) => downstream.Add(e.Value);
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for (int i = 0; i < 10; 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.Equal(10, downstream.Count);
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}
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// ───── Calculate ─────
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[Fact]
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public void Calculate_ReturnsResultsAndHotIndicator()
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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(50, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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TSeries source = bars.Close;
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var (results, indicator) = Cfo.Calculate(source, period: 5);
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Assert.Equal(source.Count, results.Count);
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Assert.True(indicator.IsHot);
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}
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// ───── Update(TSeries) ─────
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[Fact]
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public void UpdateTSeries_MatchesStreaming()
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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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int period = 10;
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var streaming = new Cfo(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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var batch = new Cfo(period);
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TSeries batchResults = batch.Update(source);
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for (int i = 0; i < source.Count; i++)
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{
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Assert.Equal(streamResults[i], batchResults.Values[i], Tolerance);
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}
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}
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// ───── Division by zero ─────
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[Fact]
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public void Update_ZeroSource_ReturnsNaN()
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{
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var cfo = new Cfo(period: 3);
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for (int i = 0; i < 3; i++)
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{
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cfo.Update(new TValue(DateTime.UtcNow, 0.0));
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}
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Assert.True(double.IsNaN(cfo.Last.Value));
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}
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}
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