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https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-21 20:18:05 +00:00
Refactor documentation links in numerics, oscillators, reversals, and statistics modules to use relative paths; update Bias class to handle division by zero more robustly; remove obsolete CUMMEAN Pine script; enhance trend indicators documentation; add Visual Studio Code workspace configuration.
This commit is contained in:
Miha Kralj
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using Xunit;
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namespace QuanTAlib.Tests;
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/// <summary>
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/// Validation tests for HOMOD - Homodyne Discriminator.
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/// Since HOMOD is a proprietary Ehlers algorithm with no standard library implementations,
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/// these tests validate mathematical properties and internal consistency.
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/// </summary>
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public class HomodValidationTests
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{
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private const double Tolerance = 1e-9;
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#region Mathematical Property Validation
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[Fact]
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public void Homod_OutputWithinConfiguredBounds()
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{
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// HOMOD output should always be within [minPeriod, maxPeriod] bounds
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const double minPeriod = 6;
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const double maxPeriod = 50;
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var homod = new Homod(minPeriod, maxPeriod);
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var gbm = new GBM(seed: 42);
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var bars = gbm.Fetch(1000, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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foreach (var bar in bars)
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{
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var result = homod.Update(new TValue(bar.Time, bar.Close));
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// After warmup, values should be strictly within bounds
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if (homod.IsHot)
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{
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Assert.True(result.Value >= minPeriod && result.Value <= maxPeriod,
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$"Value {result.Value} out of bounds [{minPeriod}, {maxPeriod}]");
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}
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}
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}
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[Fact]
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public void Homod_SmoothTransitions()
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{
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// HOMOD should produce smooth transitions due to EMA smoothing
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var homod = new Homod(6, 50);
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var gbm = new GBM(seed: 42);
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var bars = gbm.Fetch(500, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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double? prevValue = null;
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int largeJumps = 0;
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foreach (var bar in bars)
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{
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var result = homod.Update(new TValue(bar.Time, bar.Close));
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if (prevValue.HasValue && homod.IsHot)
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{
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double change = Math.Abs(result.Value - prevValue.Value);
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// Large jumps (>10 periods) should be rare due to smoothing
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if (change > 10)
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{
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largeJumps++;
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}
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}
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prevValue = result.Value;
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}
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// Allow at most 5% large jumps
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Assert.True(largeJumps < 25, $"Too many large jumps: {largeJumps}");
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}
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[Theory]
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[InlineData(42)]
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[InlineData(123)]
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[InlineData(456)]
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public void Homod_DeterministicOutput(int seed)
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{
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// Same input should always produce same output
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var gbm = new GBM(seed: seed);
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var bars1 = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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gbm = new GBM(seed: seed);
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var bars2 = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var homod1 = new Homod(6, 50);
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var homod2 = new Homod(6, 50);
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for (int i = 0; i < bars1.Count; i++)
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{
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var result1 = homod1.Update(new TValue(bars1[i].Time, bars1[i].Close));
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var result2 = homod2.Update(new TValue(bars2[i].Time, bars2[i].Close));
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Assert.Equal(result1.Value, result2.Value, Tolerance);
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}
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}
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#endregion
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#region Cycle Detection Validation
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[Fact]
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public void Homod_DetectsSyntheticCycle()
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{
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// Create a synthetic sine wave with known period
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const int knownPeriod = 20;
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var homod = new Homod(6, 50);
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// Generate 500 bars of sine wave
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for (int i = 0; i < 500; i++)
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{
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double value = 100.0 + 10.0 * Math.Sin(2.0 * Math.PI * i / knownPeriod);
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homod.Update(new TValue(DateTime.UtcNow.AddSeconds(i), value));
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}
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// After convergence, detected period should be near the known period
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// Allow some tolerance due to phase estimation and smoothing
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Assert.InRange(homod.DominantCycle, knownPeriod - 5, knownPeriod + 5);
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}
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[Theory]
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[InlineData(10)]
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[InlineData(15)]
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[InlineData(25)]
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[InlineData(35)]
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public void Homod_TracksVaryingCycles(int period)
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{
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var homod = new Homod(6, 50);
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// Generate sine wave with specified period
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for (int i = 0; i < 600; i++)
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{
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double value = 100.0 + 10.0 * Math.Sin(2.0 * Math.PI * i / period);
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homod.Update(new TValue(DateTime.UtcNow.AddSeconds(i), value));
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}
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// Should detect approximately the correct period
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Assert.InRange(homod.DominantCycle, period - 6, period + 6);
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}
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#endregion
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#region Mode Consistency Validation
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[Fact]
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public void Homod_StreamingMatchesTSeries()
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{
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var gbm = new GBM(seed: 42);
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var bars = gbm.Fetch(300, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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// Streaming mode
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var streaming = new Homod(6, 50);
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var streamingResults = new double[bars.Count];
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for (int i = 0; i < bars.Count; i++)
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{
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streamingResults[i] = streaming.Update(new TValue(bars[i].Time, bars[i].Close)).Value;
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}
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// TSeries mode
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var tSeries = new TSeries();
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foreach (var bar in bars)
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{
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tSeries.Add(new TValue(bar.Time, bar.Close));
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}
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var tSeriesResult = Homod.Calculate(tSeries, 6, 50);
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// Compare all values
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for (int i = 0; i < bars.Count; i++)
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{
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Assert.Equal(streamingResults[i], tSeriesResult[i].Value, Tolerance);
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}
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}
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[Fact]
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public void Homod_BatchMatchesStreaming()
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{
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var gbm = new GBM(seed: 42);
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var bars = gbm.Fetch(300, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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// Streaming mode
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var streaming = new Homod(6, 50);
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var streamingResults = new double[bars.Count];
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for (int i = 0; i < bars.Count; i++)
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{
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streamingResults[i] = streaming.Update(new TValue(bars[i].Time, bars[i].Close)).Value;
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}
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// Batch mode
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double[] source = new double[bars.Count];
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double[] batchResults = new double[bars.Count];
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for (int i = 0; i < bars.Count; i++)
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{
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source[i] = bars[i].Close;
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}
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Homod.Batch(source, batchResults, 6, 50);
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// Compare all values
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for (int i = 0; i < bars.Count; i++)
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{
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Assert.Equal(streamingResults[i], batchResults[i], Tolerance);
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}
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}
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[Fact]
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public void Homod_EventChainMatchesStreaming()
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{
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var gbm = new GBM(seed: 42);
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var bars = gbm.Fetch(300, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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// Streaming mode
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var streaming = new Homod(6, 50);
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var streamingResults = new double[bars.Count];
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for (int i = 0; i < bars.Count; i++)
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{
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streamingResults[i] = streaming.Update(new TValue(bars[i].Time, bars[i].Close)).Value;
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}
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// Event chain mode
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var source = new TSeries();
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var chained = new Homod(source, 6, 50);
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var chainedResults = new List<double>();
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chained.Pub += (object? _, in TValueEventArgs args) => chainedResults.Add(args.Value.Value);
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foreach (var bar in bars)
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{
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source.Add(new TValue(bar.Time, bar.Close));
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}
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// Compare all values
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Assert.Equal(streamingResults.Length, chainedResults.Count);
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for (int i = 0; i < bars.Count; i++)
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{
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Assert.Equal(streamingResults[i], chainedResults[i], Tolerance);
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}
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}
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#endregion
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#region Robustness Validation
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[Fact]
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public void Homod_HandlesVolatileInput()
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{
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var homod = new Homod(6, 50);
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var random = new Random(42);
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// Highly volatile random input
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for (int i = 0; i < 500; i++)
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{
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double value = 100.0 + (random.NextDouble() - 0.5) * 50;
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var result = homod.Update(new TValue(DateTime.UtcNow.AddSeconds(i), value));
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Assert.True(double.IsFinite(result.Value));
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if (homod.IsHot)
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{
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Assert.InRange(result.Value, 6, 50);
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}
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}
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}
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[Fact]
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public void Homod_HandlesConstantInput()
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{
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var homod = new Homod(6, 50);
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// Constant input - no cycle present
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for (int i = 0; i < 500; i++)
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{
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var result = homod.Update(new TValue(DateTime.UtcNow.AddSeconds(i), 100.0));
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Assert.True(double.IsFinite(result.Value));
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}
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// Should still produce valid output within bounds
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Assert.InRange(homod.DominantCycle, 6, 50);
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}
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[Fact]
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public void Homod_HandlesTrendingInput()
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{
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var homod = new Homod(6, 50);
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// Strong uptrend with no cyclical component
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for (int i = 0; i < 500; i++)
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{
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double value = 100.0 + i * 0.5;
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var result = homod.Update(new TValue(DateTime.UtcNow.AddSeconds(i), value));
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Assert.True(double.IsFinite(result.Value));
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}
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Assert.InRange(homod.DominantCycle, 6, 50);
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}
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[Fact]
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public void Homod_HandlesNegativePrices()
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{
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var homod = new Homod(6, 50);
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// Negative values (e.g., oscillator output)
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for (int i = 0; i < 500; i++)
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{
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double value = Math.Sin(2.0 * Math.PI * i / 20) * 10; // Oscillates -10 to +10
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var result = homod.Update(new TValue(DateTime.UtcNow.AddSeconds(i), value));
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Assert.True(double.IsFinite(result.Value));
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}
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Assert.InRange(homod.DominantCycle, 6, 50);
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}
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#endregion
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#region Warmup Validation
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[Fact]
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public void Homod_WarmupConvergence()
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{
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var homod = new Homod(6, 50);
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var gbm = new GBM(seed: 42);
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var bars = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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int i = 0;
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foreach (var bar in bars)
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{
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homod.Update(new TValue(bar.Time, bar.Close));
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i++;
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if (i == homod.WarmupPeriod)
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{
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Assert.True(homod.IsHot);
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break;
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}
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}
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}
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[Fact]
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public void Homod_StableAfterWarmup()
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{
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var homod = new Homod(6, 50);
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// Generate synthetic cycle
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for (int i = 0; i < 200; i++)
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{
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double value = 100.0 + 10.0 * Math.Sin(2.0 * Math.PI * i / 20);
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homod.Update(new TValue(DateTime.UtcNow.AddSeconds(i), value));
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}
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// Record values after warmup
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var postWarmupValues = new List<double>();
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for (int i = 200; i < 400; i++)
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{
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double value = 100.0 + 10.0 * Math.Sin(2.0 * Math.PI * i / 20);
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var result = homod.Update(new TValue(DateTime.UtcNow.AddSeconds(i), value));
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postWarmupValues.Add(result.Value);
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}
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// Standard deviation should be low for stable signal
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double mean = postWarmupValues.Average();
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double stdDev = Math.Sqrt(postWarmupValues.Select(v => (v - mean) * (v - mean)).Average());
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// Std dev should be relatively small for stable cycle detection
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Assert.True(stdDev < 5, $"Standard deviation {stdDev} is too high for stable signal");
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}
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#endregion
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}
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