mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-07-29 18:17:43 +00:00
060649192f
- Remove 'C# Implementation Considerations' sections from 34 indicator .md files - Delete 29 temp PowerShell scripts (_fix_mojibake.ps1, _hex_scan.ps1, etc.) - Move test files into tests/ subdirectories for consistent project structure - Add trader-focused bullet points to indicator documentation
493 lines
16 KiB
C#
493 lines
16 KiB
C#
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namespace QuanTAlib.Tests;
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// ═══════════════════════════════════════════════════════════════
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// A) Constructor Validation
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// ═══════════════════════════════════════════════════════════════
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public class EntropyConstructorTests
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{
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[Fact]
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public void Constructor_ThrowsOnPeriodLessThan2()
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{
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Assert.Throws<ArgumentOutOfRangeException>(() => new Entropy(1));
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Assert.Throws<ArgumentOutOfRangeException>(() => new Entropy(0));
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Assert.Throws<ArgumentOutOfRangeException>(() => new Entropy(-1));
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}
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[Fact]
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public void Constructor_AcceptsMinimumPeriod()
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{
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var e = new Entropy(2);
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Assert.NotNull(e);
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Assert.Equal("Entropy(2)", e.Name);
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}
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[Fact]
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public void Constructor_SetsWarmupPeriod()
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{
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var e = new Entropy(14);
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Assert.Equal(14, e.WarmupPeriod);
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}
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[Fact]
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public void Constructor_ParamName_IsPeriod()
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{
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var ex = Assert.Throws<ArgumentOutOfRangeException>(() => new Entropy(1));
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Assert.Equal("period", ex.ParamName);
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}
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}
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// ═══════════════════════════════════════════════════════════════
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// B) Basic Calculation
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// ═══════════════════════════════════════════════════════════════
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public class EntropyBasicTests
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{
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[Fact]
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public void Calc_ReturnsValue()
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{
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var e = new Entropy(5);
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Assert.Equal(0, e.Last.Value);
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TValue result = e.Update(new TValue(DateTime.UtcNow, 100));
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Assert.Equal(result.Value, e.Last.Value);
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}
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[Fact]
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public void Calc_ConstantValues_ReturnsZero()
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{
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// All same values → zero entropy (perfectly predictable)
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var e = new Entropy(5);
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for (int i = 0; i < 5; i++)
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{
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e.Update(new TValue(DateTime.UtcNow, 42.0));
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}
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Assert.Equal(0, e.Last.Value, 10);
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}
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[Fact]
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public void Calc_OutputBetweenZeroAndOne()
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{
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var e = new Entropy(10);
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var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 42);
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for (int i = 0; i < 50; i++)
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{
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var bar = gbm.Next(isNew: true);
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e.Update(new TValue(bar.Time, bar.Close));
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}
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Assert.InRange(e.Last.Value, 0.0, 1.0);
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}
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[Fact]
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public void Calc_UniformSpread_HighEntropy()
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{
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// Evenly spaced distinct values → high entropy
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var e = new Entropy(10);
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for (int i = 1; i <= 10; i++)
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{
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e.Update(new TValue(DateTime.UtcNow, i * 10.0));
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}
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// With 10 distinct uniformly-spaced values in 10 bins, entropy should be close to 1
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Assert.True(e.Last.Value > 0.8, $"Expected high entropy, got {e.Last.Value}");
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}
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[Fact]
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public void IsHot_Accessible()
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{
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var e = new Entropy(5);
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Assert.False(e.IsHot);
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}
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[Fact]
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public void Name_IsAccessible()
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{
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var e = new Entropy(14);
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Assert.Equal("Entropy(14)", e.Name);
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}
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}
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// ═══════════════════════════════════════════════════════════════
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// C) State + Bar Correction
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// ═══════════════════════════════════════════════════════════════
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public class EntropyStateCorrectionTests
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{
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[Fact]
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public void IsNew_True_Advances()
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{
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var e = new Entropy(5);
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e.Update(new TValue(DateTime.UtcNow, 1), isNew: true);
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e.Update(new TValue(DateTime.UtcNow, 2), isNew: true);
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e.Update(new TValue(DateTime.UtcNow, 3), isNew: true);
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e.Update(new TValue(DateTime.UtcNow, 4), isNew: true);
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double v1 = e.Update(new TValue(DateTime.UtcNow, 5), isNew: true).Value;
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e.Update(new TValue(DateTime.UtcNow, 50), isNew: true);
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double v2 = e.Last.Value;
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Assert.NotEqual(v1, v2);
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}
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[Fact]
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public void IsNew_False_Rewrites()
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{
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var e = new Entropy(5);
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e.Update(new TValue(DateTime.UtcNow, 1));
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e.Update(new TValue(DateTime.UtcNow, 2));
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e.Update(new TValue(DateTime.UtcNow, 3));
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e.Update(new TValue(DateTime.UtcNow, 4));
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e.Update(new TValue(DateTime.UtcNow, 5), isNew: true);
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// Rewrite last value from 5 to 50
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var res = e.Update(new TValue(DateTime.UtcNow, 50), isNew: false);
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// Expected: entropy of {1, 2, 3, 4, 50}
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var expected = new Entropy(5);
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expected.Update(new TValue(DateTime.UtcNow, 1));
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expected.Update(new TValue(DateTime.UtcNow, 2));
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expected.Update(new TValue(DateTime.UtcNow, 3));
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expected.Update(new TValue(DateTime.UtcNow, 4));
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var expectedVal = expected.Update(new TValue(DateTime.UtcNow, 50));
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Assert.Equal(expectedVal.Value, res.Value, 10);
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}
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[Fact]
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public void IterativeCorrections_RestoreToOriginalState()
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{
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var e = new Entropy(5);
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var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: 42);
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// Feed 10 new values
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TValue tenthInput = default;
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for (int i = 0; i < 10; i++)
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{
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var bar = gbm.Next(isNew: true);
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tenthInput = new TValue(bar.Time, bar.Close);
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e.Update(tenthInput, isNew: true);
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}
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double stateAfterTen = e.Last.Value;
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// Generate 9 corrections with isNew=false
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for (int i = 0; i < 9; i++)
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{
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var bar = gbm.Next(isNew: false);
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e.Update(new TValue(bar.Time, bar.Close), isNew: false);
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}
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// Feed the original 10th input again with isNew=false
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TValue finalResult = e.Update(tenthInput, isNew: false);
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// Entropy rebuilds from buffer each update, so this should be exact
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Assert.Equal(stateAfterTen, finalResult.Value, 10);
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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 e = new Entropy(5);
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for (int i = 0; i < 5; i++)
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{
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e.Update(new TValue(DateTime.UtcNow, i * 10.0));
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}
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Assert.True(e.IsHot);
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e.Reset();
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Assert.False(e.IsHot);
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Assert.Equal(0, e.Last.Value);
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}
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}
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// ═══════════════════════════════════════════════════════════════
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// D) Warmup / Convergence
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// ═══════════════════════════════════════════════════════════════
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public class EntropyWarmupTests
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{
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[Fact]
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public void IsHot_BecomesTrueWhenBufferFull()
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{
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var e = new Entropy(5);
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Assert.False(e.IsHot);
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for (int i = 1; i <= 4; i++)
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{
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e.Update(new TValue(DateTime.UtcNow, i * 10));
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Assert.False(e.IsHot);
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}
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e.Update(new TValue(DateTime.UtcNow, 50));
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Assert.True(e.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 e = new Entropy(20);
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Assert.Equal(20, e.WarmupPeriod);
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}
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}
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// ═══════════════════════════════════════════════════════════════
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// E) Robustness
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// ═══════════════════════════════════════════════════════════════
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public class EntropyRobustnessTests
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{
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[Fact]
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public void NaN_UsesLastValidValue()
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{
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var e = new Entropy(5);
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e.Update(new TValue(DateTime.UtcNow, 10));
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e.Update(new TValue(DateTime.UtcNow, 20));
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e.Update(new TValue(DateTime.UtcNow, 30));
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var result = e.Update(new TValue(DateTime.UtcNow, double.NaN));
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Assert.True(double.IsFinite(result.Value));
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}
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[Fact]
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public void PositiveInfinity_UsesLastValidValue()
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{
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var e = new Entropy(5);
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e.Update(new TValue(DateTime.UtcNow, 10));
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e.Update(new TValue(DateTime.UtcNow, 20));
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e.Update(new TValue(DateTime.UtcNow, 30));
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var result = e.Update(new TValue(DateTime.UtcNow, double.PositiveInfinity));
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Assert.True(double.IsFinite(result.Value));
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}
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[Fact]
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public void NegativeInfinity_UsesLastValidValue()
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{
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var e = new Entropy(5);
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e.Update(new TValue(DateTime.UtcNow, 10));
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e.Update(new TValue(DateTime.UtcNow, 20));
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e.Update(new TValue(DateTime.UtcNow, 30));
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var result = e.Update(new TValue(DateTime.UtcNow, double.NegativeInfinity));
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Assert.True(double.IsFinite(result.Value));
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}
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[Fact]
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public void BatchNaN_Safe()
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{
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double[] source = [1, 2, double.NaN, 4, 5, 6, 7, 8, 9, 10];
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double[] output = new double[source.Length];
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Entropy.Batch(source.AsSpan(), output.AsSpan(), 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]), $"output[{i}] = {output[i]}");
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}
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}
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}
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// ═══════════════════════════════════════════════════════════════
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// F) Consistency (all 4 modes match)
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// ═══════════════════════════════════════════════════════════════
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public class EntropyConsistencyTests
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{
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[Fact]
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public void AllModes_ProduceSameResult()
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{
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const int period = 10;
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var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 123);
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int count = 200;
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var times = new List<long>(count);
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var values = new List<double>(count);
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for (int i = 0; i < count; i++)
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{
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var bar = gbm.Next(isNew: true);
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times.Add(bar.Time);
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values.Add(bar.Close);
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}
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var series = new TSeries(times, values);
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// 1. Batch Mode (static method)
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var batchSeries = Entropy.Batch(series, period);
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double expected = batchSeries.Last.Value;
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// 2. Span Mode (static method with spans)
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var spanInput = values.ToArray();
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var spanOutput = new double[count];
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Entropy.Batch(spanInput.AsSpan(), spanOutput.AsSpan(), period);
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double spanResult = spanOutput[^1];
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// 3. Streaming Mode (instance, one value at a time)
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var streamingInd = new Entropy(period);
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for (int i = 0; i < count; i++)
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{
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streamingInd.Update(series[i]);
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}
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double streamingResult = streamingInd.Last.Value;
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// Assert all modes produce identical results
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Assert.Equal(expected, spanResult, precision: 9);
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Assert.Equal(expected, streamingResult, precision: 9);
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}
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[Fact]
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public void Batch_Matches_Streaming()
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{
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double[] data = [1, 2, 3, 4, 5, 10, 1, 2, 3, 4, 5, 20, 1, 3, 5, 7, 9, 11];
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int period = 5;
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// Streaming
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var e = new Entropy(period);
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var streamingResults = new List<double>();
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foreach (var val in data)
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{
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streamingResults.Add(e.Update(new TValue(DateTime.UtcNow, val)).Value);
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}
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// Batch
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var series = new TSeries(new List<long>(new long[data.Length]), new List<double>(data));
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var batchResult = Entropy.Batch(series, period);
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for (int i = 0; i < data.Length; i++)
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{
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Assert.Equal(streamingResults[i], batchResult.Values[i], precision: 10);
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}
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}
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}
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// ═══════════════════════════════════════════════════════════════
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// G) Span API Tests
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// ═══════════════════════════════════════════════════════════════
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public class EntropySpanTests
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{
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[Fact]
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public void SpanBatch_ValidatesLengths()
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{
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double[] source = [1, 2, 3, 4, 5];
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double[] wrongSize = new double[3];
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var ex = Assert.Throws<ArgumentException>(() =>
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Entropy.Batch(source.AsSpan(), wrongSize.AsSpan(), 3));
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Assert.Equal("output", ex.ParamName);
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}
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[Fact]
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public void SpanBatch_ValidatesPeriod()
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{
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double[] source = [1, 2, 3, 4, 5];
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double[] output = new double[5];
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Assert.Throws<ArgumentException>(() =>
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Entropy.Batch(source.AsSpan(), output.AsSpan(), 1));
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Assert.Throws<ArgumentException>(() =>
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Entropy.Batch(source.AsSpan(), output.AsSpan(), 0));
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}
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[Fact]
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public void SpanBatch_MatchesTSeriesBatch()
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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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int count = 100;
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var times = new List<long>(count);
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var values = new List<double>(count);
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double[] source = new double[count];
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double[] output = new double[count];
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for (int i = 0; i < count; i++)
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{
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var bar = gbm.Next(isNew: true);
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times.Add(bar.Time);
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values.Add(bar.Close);
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source[i] = bar.Close;
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}
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var series = new TSeries(times, values);
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var tseriesResult = Entropy.Batch(series, 10);
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Entropy.Batch(source.AsSpan(), output.AsSpan(), 10);
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for (int i = 0; i < count; i++)
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{
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Assert.Equal(tseriesResult[i].Value, output[i], 1e-10);
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}
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}
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[Fact]
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public void SpanBatch_HandlesNaN()
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{
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double[] source = [1, 2, double.NaN, 4, 5];
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double[] output = new double[5];
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Entropy.Batch(source.AsSpan(), output.AsSpan(), 3);
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for (int i = 0; i < source.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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[Fact]
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public void SpanBatch_LargeData_NoStackOverflow()
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{
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int count = 5000;
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var data = new double[count];
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var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 42);
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for (int i = 0; i < count; i++)
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{
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data[i] = gbm.Next(isNew: true).Close;
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}
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var output = new double[count];
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// Should not throw StackOverflowException
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Entropy.Batch(data.AsSpan(), output.AsSpan(), 50);
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Assert.True(double.IsFinite(output[^1]));
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}
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}
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// ═══════════════════════════════════════════════════════════════
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// H) Event / Chainability
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// ═══════════════════════════════════════════════════════════════
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public class EntropyEventTests
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{
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[Fact]
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public void Pub_Fires()
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{
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var e = new Entropy(5);
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int eventCount = 0;
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e.Pub += (object? sender, in TValueEventArgs args) => eventCount++;
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e.Update(new TValue(DateTime.UtcNow, 100));
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Assert.Equal(1, eventCount);
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}
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[Fact]
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public void EventBased_Chaining_Works()
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{
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var source = new TSeries();
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var e = new Entropy(5);
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// Subscribe to source
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source.Pub += (object? sender, in TValueEventArgs args) =>
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{
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e.Update(args.Value);
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};
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// Feed data through source
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for (int i = 1; i <= 10; i++)
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{
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source.Add(new TValue(DateTime.UtcNow, i * 10.0));
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}
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Assert.True(e.IsHot);
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Assert.True(double.IsFinite(e.Last.Value));
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// Allow tiny floating-point overshoot above 1.0
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Assert.True(e.Last.Value >= -1e-10 && e.Last.Value <= 1.0 + 1e-10,
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$"Expected entropy in [0, 1], got {e.Last.Value}");
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}
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}
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